diff --git a/pipelines/COORDINATE_CONVENTIONS.md b/pipelines/COORDINATE_CONVENTIONS.md new file mode 100644 index 0000000..9fe809b --- /dev/null +++ b/pipelines/COORDINATE_CONVENTIONS.md @@ -0,0 +1,222 @@ +# Detector coordinates in the XPCS pipelines + +Survey of the working tree, 2026-10-11. **For an oriented analysis image, +plot `(x, y)` but index `image[y, x]`.** Beam-center metadata, helper arguments, +and saved masks do not all use the same ordering. + +## Screens, files, and analysis images + +**Albula `(x, y)` is the source of IOC `beam_center_x/y` and the corresponding +HDF5 fields**, as confirmed by beamline practice. In the acquisition code, +[`update_beam_position_dict`](https://github.com/NSLS2/chx-profile-collection/blob/670a10be52a0db75f090087f6c466eabe48aaf16/startup/30-user.py#L623) +copies these PVs into `RE.md['beam_position_dict']` without swapping or +reversing them. Its comment “from CSS” refers to reading the PV values entered +through the screen. Thus the beam-center entry fields use Albula coordinates; +the CSS/Phoebus **image cursor** may still use a different orientation. + +The Python side is explicit. Let `R` be an untransformed detector frame with +`R.shape == (H, W)`, and `A` the image used for analysis. Raw zero-based pixel +coordinates `(x_raw, y_raw)` mean `R[y_raw, x_raw]`. + +| Detector selection | Loader flags | Analysis array `A` | Shape | Same pixel at analysis `(x, y)` | +| --- | --- | --- | --- | --- | +| Eiger 4M / `image`, Eiger 1M | `reverse=True, rot90=False` | `R[::-1, :]` | `(H, W)` | `(x_raw, H - 1 - y_raw)` | +| Eiger 500K | `reverse=True, rot90=True` | `np.rot90(R[::-1, :])` | `(W, H)` | `(H - 1 - y_raw, W - 1 - x_raw)` | + +These choices appear in [XPCS_auto.ipynb](XPCS_auto.ipynb), “Find beam center,” +and the three [old pipelines](old_pipelines). They are hardcoded by detector +name; no detector mounting angle is consulted. The bundled 500K example has +raw shape `(514, 1030)` and analysis shape `(1030, 514)`. + +In [chx_generic_functions.py](../pyCHX/chx_generic_functions.py), `load_data` +reverses rows before rotating, and preserves image metadata without transforming +its coordinates or mask arrays. `load_dask_data` performs the corresponding +operations on stack axes 1 and 2. Its unusual `flip(axis=(1, 1))` applies one +row reversal in the inspected Dask implementation. `rot90_clockwise` actually +calls `np.rot90`: use that expression to identify the transformation, since +its apparent direction depends on the plot origin. Direct HDF5 compression +uses the same reversal-then-rotation in +[chx_compress.py](../pyCHX/chx_compress.py), `_iter_binned_images`. + +The notebooks generally set `image.origin='lower'`, and `show_img` defaults to +`origin='lower'`: column/x increases rightward, row/y upward. Ordinary Matplotlib +defaults to `origin='upper'` unless changed. **Changing the plot origin does +not change array indices.** `cmap_albula` changes colors only. + +### What this establishes about Albula + +Because the input beam-center values come from Albula, the master's metadata +conversion directly gives its **Albula-to-analysis beam-center mapping**: + +| Detector | Albula `(ax, ay)` → analysis `(x, y)` as currently coded | +| --- | --- | +| 4M / 1M | `(ax, H - ay)` | +| 500K | `(H - ay, W - ax)` | + +This supports Albula x along raw columns and Albula y along raw rows. Relative +to the usual analysis plot, 4M/1M preserve x and reverse y; 500K swap axes and +reverse both. The acquisition helper +[`get_beam_center_update`](https://github.com/NSLS2/chx-profile-collection/blob/670a10be52a0db75f090087f6c466eabe48aaf16/startup/30-user.py#L74) +provides stronger evidence: it writes the raw maximum's zero-based column to +`BeamX` and row to `BeamY` for 4M. For 500K it finds the maximum after `np.rot90` +and undoes that coordinate change with `1030 - 1 - row`, again writing raw +`(column, row)`. The first table therefore gives the expected exact pixel +mapping for Albula readings using this same zero-based convention. The +one-pixel discrepancy with the beam-center conversion is discussed below. + +The adjacent +[`calculate_direct_beam_position`](https://github.com/NSLS2/chx-profile-collection/blob/670a10be52a0db75f090087f6c466eabe48aaf16/startup/30-user.py#L644) +also explains the detector mounting difference. For motor displacements +`dx, dy` in mm and `p=0.075` mm/pixel, it predicts (before integer rounding): + +| Detector | Change in Albula/IOC `(x, y)` | Change after analysis transformation | +| --- | --- | --- | +| 4M | `(+dx/p, +dy/p)` | `(+dx/p, -dy/p)` | +| 500K | `(+dy/p, -dx/p)` | `(+dx/p, -dy/p)` | + +Both analysis images therefore respond to detector motion along the same +axes. The 500K rotation compensates for its different mounting orientation. +This establishes relative axes and signs without needing an Albula screenshot. + +## Why beam-center numbers differ + +Acquisition has two distinct beam positions: `beam_position_dict` stores the +Albula calibration **reference** and detector motor positions at calibration; +`series(auto_beam_position=True)` updates the current 4M/500K PVs from that +reference and the current motors. It rounds to integer pixels. The nested +reference values can therefore legitimately differ from the exposure's +configuration/HDF5 values after detector motion. + +The master notebook's metadata then passes through several stages: + +| Stage | Meaning of the values | +| --- | --- | +| `get_meta_data` / `md_blue` | Configuration metadata merged with run-start metadata; start keys override matching configuration keys. `md_blue` is a snapshot of this merge. | +| `md.update(img_md)` | Matching keys are replaced again. Dask obtains beam centers from detector configuration; the fallback uses the image handler's metadata, normally from HDF5. These sources need not agree. | +| “Apply image metadata” | The notebook converts `beam_center_x/y` to analysis `(column, row)` using the Albula mapping above. | +| `inc_x0`, `inc_y0`, `center` | Master `inc_x0/inc_y0` are analysis `(x, y)`. With both arguments supplied, `check_lost_metadata` returns `center=[int(inc_x0), int(inc_y0)]`. | +| `setup_pargs['center']` | Starts as `(x, y)`; is temporarily reversed for template ROI placement on selected detectors; “Setup center args” later sets it to `(y, x)` for SAXS calculations. | +| “Save metadata” | Master SAXS writes `beam_center_x=center[1]`, `beam_center_y=center[0]`: these saved fields are **row, column**. Master WAXS and surface modes save `inc_x0/inc_y0`: **column, row**. | + +**Likely one-pixel offset:** the master and old SAXS/GISAXS notebooks use +`size - coordinate` for beam centers, whereas exact zero-based pixel mappings +use `size - 1 - coordinate`. With the PV convention explicitly implemented by +`get_beam_center_update`, the converted center is one pixel too large in +analysis y for 4M/1M, and in both analysis axes for 500K. Manual Albula cursor +numbering is not documented in these sources, so confirm that it matches the +automatic helper before changing historical calibration. A uniform one-based +convention alone would not explain the 4M formula: x would also need `-1`. +Use the exact pixel mappings for zero-based hot-pixel indices. + +`check_lost_metadata` adds another trap: without explicit center arguments it +returns `[int(md['beam_center_y']), int(md['beam_center_x'])]`. With both supplied +it returns their original `(x, y)` order. Its internal center changes affect a +copy; it does not rewrite the caller's beam-center fields. Integer conversion +also discards subpixel precision. Master surface q maps use the floating-point +`inc_x0/inc_y0` directly. Manual `surface_beam_center_x/y` fallbacks already mean +analysis coordinates and skip the loader-coordinate conversion. + +Compressed headers copy the supplied beam-center fields without a coordinate +conversion. Also, the legacy `Multifile` reader reconstructs images with shape +`(md['ncols'], md['nrows'])`; these historical names are reversed relative to +NumPy terminology. Prefer the actual image shape when identifying axes. + +## Helper argument order + +These are the implementations in +[chx_generic_functions.py](../pyCHX/chx_generic_functions.py) and +[XPCS_SAXS.py](../pyCHX/XPCS_SAXS.py), regardless of older comments or docstrings. +Reversing a two-element center changes argument order; it does not rotate or +flip an image. + +| Operation | Required coordinates | +| --- | --- | +| NumPy indexing; JSON mask nested lists | `[row, column]`, i.e. `[y, x]` / `[y][x]` | +| `plt.plot`; `show_img(center=...)` | `(x, y)`; `show_img` calls `plot1D(y, x)` internally | +| `create_cross_mask`; `create_multi_rotated_rectangle_mask` | `(x, y)`; beam-mask `x_off/y_off` follow these analysis axes | +| `show_ROI_on_image(center=...)` | `(y, x)` for setting the plot limits | +| `create_hot_pixel_mask(center=...)` | `(y, x)`, despite its `(x, y)` docstring | +| `circular_average`; `get_ring_mask`; `get_angular_mask`; `get_qval_qwid_dict` | `(y, x)`, including centers passed through `pargs` | +| `shift_mask`; `get_roi_mask_qval_qwid_by_shift` | Centers in `(y, x)`; the latter takes its effective new center from `setup_pargs`, ignoring its `new_cen` argument | +| New [geometry helpers](../pyCHX/_xpcs_pipeline_geometry.py), including `surface_q_maps` and SAXS ROI validation | `(x, y)` in the oriented image | + +For angular SAXS ROIs, zero degrees is toward increasing columns/right; +positive 90 degrees is toward increasing rows/up with `origin='lower'`. +Surface maps likewise use increasing analysis rows for the reflected-beam +displacement and vertical scattering coordinate. + +## Masks and adding a hot pixel + +The master loads `detector_mask_.json` arrays **as already oriented**; +it applies no further reversal or rotation. Here `True/1` means keep and +`False/0` means exclude. HDF5 `detectorSpecific/pixel_mask` is different: +zero means good and nonzero values encode defects. The cached +`pixel_mask_compression_*.json` belongs to that detector metadata path; +it is not the editable analysis detector-mask JSON. + +[Detector_Masks_Add_Pixels.ipynb](masking_and_rois/Detector_Masks_Add_Pixels.ipynb) +writes `[pixel[0]][pixel[1]]`. Thus `pixels_to_add` must contain **`(row, column)`**, +even though its temporary variables are called `x` and `y`. For example, a pixel +at analysis plot `(x=1119, y=1010)` is: + +```python +x, y = 1119, 1010 # analysis-image column, row +mask_data['masks']['pixel_mask'][y][x] = False +# Equivalently, in Detector_Masks_Add_Pixels.ipynb: +pixels_to_add = [(y, x)] + +# Verify against an image loaded with the pipeline's detector flags: +plt.imshow(avg_img, origin='lower', interpolation='nearest') +plt.plot(x, y, 'r+') +``` + +Use the cursor on that oriented image, or convert a verified raw pixel with +the first table. A flat index is `row * image.shape[1] + column`, in the +orientation of that particular array. The add-pixels notebook's `pcolormesh` +uses integer cell edges; its pixel centers are offset by half a pixel from +`imshow`'s integer centers. + +New manual mask/ROI inputs must declare `orientation='analysis'` (in the file +or notebook option) and match the oriented image shape. This is a declaration +and validation step, not an automatic conversion. The general SAXS ROI JSON +templates follow a separate path: shift/crop around their `original center` +in `(row, column)` order. + +## Legacy differences and remaining ambiguities + +Cell numbers below count all notebook cells from one, including Markdown cells. + +- [Old SAXS](old_pipelines/XPCS_SAXS_auto.ipynb) follows the master's early + center conversion. [Old GISAXS](old_pipelines/XPCS_GISAXS_auto.ipynb) swaps + `inc_x0/inc_y0`, then reverses the returned `center` again. + [Old WAXS](old_pipelines/XPCS_WAXS_auto.ipynb) retains a different center + conversion after loading and uses `load_mask(..., reverse=..., rot90=...)` + for its `.npy` mask. Those files cannot be assumed to have the same saved + orientation as the newer detector-mask JSONs. +- [Detector_Masks](masking_and_rois/Detector_Masks.ipynb), cell 7, reverses the + 4M metadata pixel mask, only rotates the 500K metadata mask, and leaves the + 1M metadata mask unchanged, while images use the full transformations above. + Chip masks have their own handling. This is an apparent asymmetry; historical + external mask files and their provenance are needed to establish correctness. +- [Auto_Mask_SAXS](masking_and_rois/Auto_Mask_SAXS.ipynb), cells 29–31, has an + inconsistent `hot_beam` path: `np.nonzero` row indices become `x_hots`, and + reconstruction adds `beam_center_x` to **both** index components. Its plotting + uses a different ordering. This looks like a defect, not a reliable conversion. +- [Auto_ROI_Mask_Generator](masking_and_rois/Auto_ROI_Mask_Generator.ipynb) + reverses the center for 4M/500K template placement. The master currently + checks lowercase `eiger500k` there although loading accepts both spellings; + 1M has no corresponding swap. Some plotting/masking calls also pass `(x, y)` + to helpers expecting `(y, x)`, including master `show_ROI_on_image` and + `create_hot_pixel_mask`. Symmetric centers can hide these mismatches. +- [WAXS_Geometry_Calibration](masking_and_rois/WAXS_Geometry_Calibration.ipynb) + uses a Pilatus image with `np.flipud`, then `(x, y)` beam centers; + [detector_coverage](masking_and_rois/detector_coverage.ipynb) uses simulated + geometry. Both pass `poni1=y*pixel1`, `poni2=x*pixel2` to pyFAI. Neither + establishes the CSS/Albula mapping or a general Pilatus rule for the master. + +The Albula/IOC axis mapping and relative detector orientation are supported by +the acquisition and analysis code together. What remains to check is the +Albula cursor's exact pixel origin, the one-pixel center discrepancy, and the +CSS/Phoebus image-cursor mapping. Matching asymmetric pixel landmarks across +those displays and the raw array would settle these points; distinguish the +stored calibration reference from the current exposure's beam-center values. diff --git a/pipelines/XPCS_auto.ipynb b/pipelines/XPCS_auto.ipynb new file mode 100644 index 0000000..79623c3 --- /dev/null +++ b/pipelines/XPCS_auto.ipynb @@ -0,0 +1,4466 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 6.9e-05, + "end_time": "2023-06-20T08:53:08.428761", + "exception": false, + "start_time": "2023-06-20T08:53:08.428692", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Unified XPCS analysis: SAXS, GISAXS, WAXS, and GIWAXS\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 1.299622, + "end_time": "2023-06-20T08:53:09.794917", + "exception": false, + "start_time": "2023-06-20T08:53:08.495295", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Imports and environment setup\n", + "\n", + "import time\n", + "\n", + "_xpcs_notebook_start = time.time()\n", + "_xpcs_cell_start = _xpcs_notebook_start\n", + "\n", + "import glob\n", + "import itertools\n", + "import json\n", + "import shutil\n", + "import sys\n", + "import warnings\n", + "from time import localtime, strftime\n", + "\n", + "from pyCHX.chx_packages import *\n", + "from pyCHX._xpcs_pipeline_geometry import (\n", + " build_surface_rois, build_waxs_rois, combine_detector_masks, intersect_roi_with_mask,\n", + " load_manual_mask, load_manual_roi,\n", + " plot_roi_index_rates, plot_surface_roi, plot_xpcs_correlation, resolve_geometry,\n", + " surface_profile_args_from_roi,\n", + " surface_q_maps, validate_roi,\n", + ")\n", + "#from pyCHX.chx_xpcs_xsvs_jupyter_V1 import *\n", + "#from pyCHX.chx_generic_functions import get_roi_mask_qval_qwid_by_shift\n", + "#from pyCHX.chx_generic_functions import RemoveHot,create_multi_rotated_rectangle_mask\n", + "\n", + "#sys.path.insert(0, \"/nsls2/data/chx/shared/CHX_Software/packages/database_processing/\") # Need a better way to include these directories\n", + "#sys.path.insert(0, \"/nsls2/data/chx/shared/CHX_Software/packages/AutoRun_functions/\")\n", + "from database_processing import *\n", + "from AutoRun_functions import *\n", + "\n", + "%matplotlib notebook\n", + "plt.rcParams.update({'figure.max_open_warning': 0})\n", + "plt.rcParams.update({'image.origin': 'lower'})\n", + "plt.rcParams.update({'image.interpolation': 'none'})\n", + "\n", + "%run /nsls2/data/chx/shared/CHX_Software/packages/environment_management/chx_analysis_setup_test_pyCHX.ipynb\n", + "_base_path_ = _base_path_pass_\n", + "print(colored(\"--> overwrote '_base_path_' as %s\\n\\n\"%_base_path_,'cyan'))\n", + "hostname= !hostname\n", + "if not 'saturn4' in hostname[0]:\n", + " enable_olog_attachments = False\n", + " print(colored(\"WARNING: currently running on resource %s => attachments to Olog are NOT possible!\"%(hostname[0]),'red'))\n", + " print(colored('To enable Olog attachments, this notebook needs to run on saturn4.nsls2.bnl.gov\\nFile -> Hub Control Panel -> Stop my Server -> start server and spawn to \"CHX staff @Saturn4\"','yellow'))\n", + "else:\n", + " enable_olog_attachments = True\n", + " print(colored('hostname: %s -> Olog attachments should be possible'%hostname[0],'green'))\n", + "\n", + "kernel = sys.executable\n", + "print(colored(f'sys.executable : {kernel}','green'))\n", + "\n", + "\n", + "_record_xpcs_cell_timing(\"01 - Imports and environment setup\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:53:09.798341", + "exception": false, + "start_time": "2023-06-20T08:53:09.798316", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Run controls\n", + "\n", + "Choose `saxs`, `gi_saxs`, `waxs`, or `gi_waxs` with `scat_geometry` below.\n", + "If the run start metadata contains `scat_geometry`, it takes precedence. Papermill\n", + "can still inject a value for older runs.\n", + "\n", + "For a saved mask or ROI, set `manual_mask_file` or `manual_roi_file`. A saved `.npz`\n", + "mask contains `mask` and `orientation=\"analysis\"`; a saved `.npz` ROI contains\n", + "`roi_mask`, `q_values` (one row per ROI label), and `orientation=\"analysis\"`.\n", + "Include `geometry` in either file to prevent reuse with another mode. Legacy\n", + "`.npy` masks and `(roi_mask, qval_dict)` `.pkl` ROIs require an explicit\n", + "`manual_mask_orientation` or `manual_roi_orientation` set to `\"analysis\"`.\n", + "The image and saved inputs must use the detector orientation after loading.\n", + "\n", + "Beam-mask polygon files are selected by mode as `XPCS_beam_mask_.json` in\n", + "the user masks folder. SAXS also accepts the existing `XPCS_beam_mask.json`.\n", + "Set `beam_mask_config_file` for another polygon file or `manual_mask_file` for\n", + "a complete saved beam mask. Surface modes require a calibrated incident angle,\n", + "beam center, pixel size, sample-detector distance, and wavelength; set the\n", + "corresponding `surface_*` controls when metadata lacks them.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Run controls\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "scat_geometry = 'saxs' # saxs, gi_saxs, waxs, or gi_waxs; run metadata takes precedence\n", + "\n", + "\n", + "roi_auto = True #False if True, will automatically create a roi based on the roi_type ( iso/aniso etc), currently only works for SAXS\n", + "fit_peak = False #True\n", + "\n", + "analysis_type_auto = True #if True, will take \"analysis type\" option from data acquisition func series\n", + "qphi_analysis = False #if True, will do q-phi (anisotropic analysis for transmission saxs)\n", + "\n", + "isotropic_Q_mask = 'wide' #'wide' # 'normal' # 'wide' ## select wich Q-mask to use for rings: 'normal' or 'wide'\n", + "phi_Q_mask = 'phi_4x_20deg' #'phi_4x_20deg' #'phi_12x_30deg'\n", + "\n", + " \n", + "auto_bst_mask = True # True: if custom 'XPCS_beam_mask.json' does NOT exist in .../cycle/user/masks, create a default polygon mask for beamstop\n", + "force_compress = False #force to compress data \n", + "use_local_disk = True\n", + "bin_frame = False #generally make bin_frame as False\n", + "bin_frame_number = 4 # ignored if bin_frame == False\n", + "para_compress = True #parallel compress\n", + "# run_fit_form = False #run fit form factor -> to be removed\n", + "mask_outliers = False #!!\n", + "run_waterfall = False #True #False #True #run waterfall analysis\n", + "run_profile_plot = False #run prolfile plot for gi-saxs\n", + "run_t_ROI_Inten = True #run ROI intensity as a function of time\n", + "run_get_mass_center = False # Analysis for mass center of reflective beam center\n", + "run_invariant_analysis = False\n", + "run_one_time = True #run one-time\n", + "cal_g2_error = False #True #calculate g2 signal to noise\n", + "run_fit_g2 = False #run fit one-time, the default function is \"stretched exponential\"\n", + "fit_g2_func = 'stretched'\n", + "run_two_time = True #run two-time\n", + "run_four_time = False #True #True #False #run four-time\n", + "run_xsvs= False # True #False #run visibility analysis\n", + "att_pdf_report = True #attach the pdf report to CHX olog\n", + "qth_interest = 7 #the intested single qth \n", + "\n", + "use_sqnorm = True #if True, use sq to normalize intensity -> what happens if both are true or false?\n", + "use_SG = True #if True, use the Sawitzky-Golay filter of the avg_img for normalization\n", + "use_SG_bin_frames = False #if True, use the Sawitzky-Golay filter of the (binned) frame for normalization \n", + "\n", + "use_imgsum_norm= True #if True use imgsum to normalize intensity for one-time calculatoin -> else it's doing what?\n", + "pdf_version='_%s'%strftime(\"%Y-%m-%d_%H-%M-%S\", localtime()) #for pdf report name\n", + "run_dose = False #run dose_depend analysis\n", + "\n", + "\n", + "# Optional saved inputs use the oriented analysis-image convention. .npz inputs\n", + "# carry orientation='analysis'; legacy .npy/.pkl inputs need the explicit\n", + "# orientation setting below. ROI .npz files contain roi_mask and q_values.\n", + "manual_roi_file = None\n", + "manual_mask_file = None\n", + "beam_mask_config_file = None # optional mode-specific polygon JSON\n", + "manual_roi_orientation = None\n", + "manual_mask_orientation = None\n", + "\n", + "# For surface modes, set an incident angle here if metadata has no inc_ang,\n", + "# incident_angle, or incident_angle_deg. Angles are degrees.\n", + "surface_incident_angle_deg = None\n", + "surface_beam_center_x = None # oriented image column, only used if metadata lacks a center\n", + "surface_beam_center_y = None # oriented image row\n", + "surface_pixel_size_mm = None\n", + "surface_detector_distance_mm = None\n", + "surface_wavelength_angstrom = None\n", + "surface_inplane_angle_deg = 0.0\n", + "gisaxs_q_parallel_edges = None\n", + "gisaxs_q_z_edges = None\n", + "giwaxs_q_parallel_edges = None\n", + "giwaxs_q_z_edges = None\n", + "\n", + "rawdata_link = False # linking raw data in a user sub-folder [sub-folder needs to be created first]\n", + "\n", + "# Geometry is resolved after Papermill parameters and run metadata are loaded.\n", + "\n", + "_record_xpcs_cell_timing(\"02 - Run controls\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.8e-05, + "end_time": "2023-06-20T08:53:10.127948", + "exception": false, + "start_time": "2023-06-20T08:53:10.127930", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### For 'manual' runs: specify uid" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.065196, + "end_time": "2023-06-20T08:53:10.259283", + "exception": false, + "start_time": "2023-06-20T08:53:10.194087", + "status": "completed" + }, + "tags": [ + "parameters" + ] + }, + "outputs": [], + "source": [ + "# Manual run setup\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "uid = 201401 #changed 29 May 2026 to an existing Eiger series - AF\n", + "\n", + "#####################################################################################################################\n", + "md=get_meta_data(uid)\n", + "username = md['user'] #this will be dynamically asigned as a parameter\n", + "cycle = md['cycle']\n", + "try:\n", + " users = md['user_group']\n", + "except:\n", + " users = []\n", + " \n", + "q_mask_name = '' # do NOT specify, will be created based on Q-Phi mask used and become part of hdf5 filename\n", + "track_progress = False # IF run by papermill with progress tracking, will automatically switch to 'True'\n", + "\n", + "_record_xpcs_cell_timing(\"03 - Manual run setup\", _xpcs_cell_start)\n", + "\n", + "# Start the next input-cell timer before Papermill injects parameters.\n", + "_xpcs_parameters_start = time.time()\n", + "_xpcs_parameters_recorded = False\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.7e-05, + "end_time": "2023-06-20T08:53:10.259418", + "exception": false, + "start_time": "2023-06-20T08:53:10.259401", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Papermill inserts into the cell below:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.060502, + "end_time": "2023-06-20T08:53:10.383808", + "exception": false, + "start_time": "2023-06-20T08:53:10.323306", + "status": "completed" + }, + "tags": [ + "injected-parameters" + ] + }, + "outputs": [], + "source": [ + "# Parameters\n", + "\n", + "# Papermill replaces this cell when parameters are injected. Input cell 05\n", + "# records its elapsed time in that case.\n", + "_xpcs_cell_start = _xpcs_parameters_start\n", + "_record_xpcs_cell_timing(\"04 - Papermill parameters\", _xpcs_cell_start)\n", + "_xpcs_parameters_recorded = True\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "### creating directory for saving output data " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Refresh data-session metadata\n", + "\n", + "if not _xpcs_parameters_recorded:\n", + " _record_xpcs_cell_timing(\"04 - Papermill parameters\", _xpcs_parameters_start)\n", + " _xpcs_parameters_recorded = True\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "# Data security modification: username for file creation is now the data_session. Should we fix this in the papermill level?\n", + "md=get_meta_data(uid)\n", + "scat_geometry = resolve_geometry(md, scat_geometry)\n", + "md['scat_geometry'] = scat_geometry\n", + "if scat_geometry != 'saxs':\n", + " qphi_analysis = False\n", + " roi_auto = False\n", + " use_sqnorm = False\n", + " run_xsvs = False\n", + " run_invariant_analysis = False\n", + "if scat_geometry != 'gi_saxs':\n", + " run_profile_plot = False\n", + "scat_geometry_ = {'gi_waxs': 'gi_saxs', 'waxs': 'gi_waxs'}.get(scat_geometry, scat_geometry)\n", + "print('scattering geometry:', scat_geometry)\n", + "username = md['data_session']\n", + "\n", + "_record_xpcs_cell_timing(\"05 - Refresh data-session metadata\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Create results directory\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "default_dir = _base_path_\n", + "data_dir0 = create_user_folder(cycle, username, default_dir if alternate_directory is None else alternate_directory)\n", + "md=get_meta_data(uid)\n", + "uid=md['uid']\n", + "print('The current uid for analysis is: %s...'%uid[:8])\n", + "data_dir = os.path.join(data_dir0, '%s/'%uid)\n", + "os.makedirs(data_dir, exist_ok=True)\n", + "print('Results from this analysis will be stashed in the directory %s' % data_dir)\n", + "uidstr = 'uid=%s'%uid\n", + "\n", + "_record_xpcs_cell_timing(\"06 - Create results directory\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "### set up progress tracking" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Set up progress tracking\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if 'process_id' in locals(): #if process_id has been inserted by papermill\n", + " settings_dict_={'run_one_time':run_one_time,'run_two_time':run_two_time,'xsvs':run_xsvs}\n", + " prog_dict_file = get_progress_dict_filename(uid,md['cycle'],md['user'],default_dir)\n", + " track_progress = create_new_prog_dict_run_XPCS_SAXS(prog_dict_file=prog_dict_file,process_id=process_id,settings_dict=settings_dict_, verbose=True)\n", + "if track_progress:\n", + " print('going to track progress in %s '%prog_dict_file)\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='Load data and compress', progress='start',start_time=time.time(), stop_time=None, verbose=True)\n", + "else: print('Not tracking progress...notebook is likely being run outside of papermill')\n", + "\n", + "_record_xpcs_cell_timing(\"07 - Set up progress tracking\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.610795, + "end_time": "2023-06-20T08:53:11.060747", + "exception": false, + "start_time": "2023-06-20T08:53:10.449952", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Resolve source data files\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "sud = get_sid_filenames_v3(db[uid])\n", + "data_fullpath = sud[2]\n", + "\n", + "print ('scan_id, full-uid, data path are: %s--%s--%s'%(sud[0], sud[1], data_fullpath ))\n", + "\n", + "_record_xpcs_cell_timing(\"08 - Resolve source data files\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.8e-05, + "end_time": "2023-06-20T08:53:11.060904", + "exception": false, + "start_time": "2023-06-20T08:53:11.060886", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Don't Change the lines below here" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.6e-05, + "end_time": "2023-06-20T08:53:11.131323", + "exception": false, + "start_time": "2023-06-20T08:53:11.131297", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "* get metadata" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 1.388821, + "end_time": "2023-06-20T08:53:12.578892", + "exception": false, + "start_time": "2023-06-20T08:53:11.190071", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Load metadata and detector list\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "taus=None;g2=None;tausb=None;g2b=None;g12b=None;taus4=None;g4=None;times_xsv=None;contrast_factorL=None; lag_steps = None \n", + "\n", + "md = get_meta_data( uid )\n", + "scat_geometry = resolve_geometry(md, scat_geometry)\n", + "md['scat_geometry'] = scat_geometry\n", + "md_blue = md.copy()\n", + "detectors = sorted(get_detectors(db[uid]))\n", + "print('The detectors are:%s'%detectors)\n", + "if len(detectors) >1:\n", + " md['detector'] = detectors[1]\n", + " print( md['detector'])\n", + "\n", + "_record_xpcs_cell_timing(\"09 - Load metadata and detector list\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.070582, + "end_time": "2023-06-20T08:53:12.652922", + "exception": false, + "start_time": "2023-06-20T08:53:12.582340", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Find beam center\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if 'eiger4m' in md['detector'] or md['detector'] == 'image': \n", + " reverse= True\n", + " rot90= False\n", + "elif ('eiger500k' in md['detector']) or ('eiger500K' in md['detector']): \n", + " reverse= True\n", + " rot90=True\n", + "elif 'eiger1m' in md['detector']: \n", + " reverse= True\n", + " rot90=False\n", + "print('Image reverse: %s\\nImage rotate 90: %s'%(reverse, rot90)) \n", + "try:\n", + " cx , cy = md_blue['beam_center_x'], md_blue['beam_center_y']\n", + " print('(cx,cy) = (%s,%s)'%(cx,cy))\n", + "except:\n", + " print('Will find cx,cy later.')\n", + "\n", + "_record_xpcs_cell_timing(\"10 - Find beam center\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.8e-05, + "end_time": "2023-06-20T08:53:12.658217", + "exception": false, + "start_time": "2023-06-20T08:53:12.658189", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Load ROI defined by \"XPCS_Setup\" Pipeline" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 5.1e-05, + "end_time": "2023-06-20T08:53:12.726548", + "exception": false, + "start_time": "2023-06-20T08:53:12.726497", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "#### Define data analysis type" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.061195, + "end_time": "2023-06-20T08:53:12.843922", + "exception": false, + "start_time": "2023-06-20T08:53:12.782727", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Select analysis type and ROI mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "if scat_geometry == 'saxs':\n", + " mask_list = check_roi_masknames(_mask_path_+'ROI_masks/')\n", + " iso_masks = [item for item in mask_list if 'phi' not in item]\n", + " phi_masks = [item for item in mask_list if 'phi' in item]\n", + " if analysis_type_auto and 'analysis' in md:\n", + " requested = md['analysis']\n", + " if requested in phi_masks:\n", + " qphi_analysis, phi_Q_mask = True, requested\n", + " elif requested in iso_masks:\n", + " qphi_analysis, isotropic_Q_mask = False, requested\n", + " else:\n", + " qphi_analysis = requested not in ('iso', '', None)\n", + " scat_geometry_ = 'ang_saxs' if qphi_analysis else 'saxs'\n", + "else:\n", + " qphi_analysis = False\n", + " scat_geometry_ = {'gi_waxs': 'gi_saxs', 'waxs': 'gi_waxs'}.get(scat_geometry, scat_geometry)\n", + " gisaxs_inc_type = md.get('analysis')\n", + "print('analysis geometry:', scat_geometry_, 'qphi:', qphi_analysis)\n", + "_record_xpcs_cell_timing(\"11 - Select analysis type and ROI mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:12.847398", + "exception": false, + "start_time": "2023-06-20T08:53:12.847376", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Load Data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Load detector images\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "try: # preferred: load images as dask_array\n", + " imgs,img_md=load_dask_data(uid,md['detector'], _mask_path_+'pixel_masks/',reverse=reverse,rot90=rot90)\n", + " print(colored('SUCCESSFULLY LOADED DATA AS dask-array!','green'))\n", + "except:\n", + " print(colored('COULD NOT LOAD DATA AS dask-array, reverting to slow data loading....','red'))\n", + " imgs = load_data(uid,md['detector'],reverse=reverse,rot90=rot90)\n", + " img_md=imgs.md\n", + " print(colored('COULD NOT LOAD DATA AS dask-arry, falling back to slow data loading....','red'))\n", + "imgs\n", + "\n", + "_record_xpcs_cell_timing(\"12 - Load detector images\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Apply image metadata\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "md.update( img_md )\n", + "missing_center = 'beam_center_x' not in md or 'beam_center_y' not in md\n", + "if missing_center and scat_geometry in ('gi_saxs', 'gi_waxs'):\n", + " if surface_beam_center_x is None or surface_beam_center_y is None:\n", + " raise ValueError('Missing surface beam center in metadata; set surface_beam_center_x and surface_beam_center_y')\n", + " md['beam_center_x'] = surface_beam_center_x\n", + " md['beam_center_y'] = surface_beam_center_y\n", + "md['number of images'] = int(md['number of images'])\n", + "pixel_mask=np.ones( np.shape(imgs[0]))\n", + "if not missing_center and reverse and not rot90:\n", + " md['beam_center_y']=np.shape(imgs[0])[0]- md['beam_center_y']\n", + "if not missing_center and reverse and rot90:\n", + " xc=md['beam_center_y'];yc=md['beam_center_x']\n", + " yc=np.shape(imgs[0])[0]-yc\n", + " xc=np.shape(imgs[0])[1]-xc\n", + " md['beam_center_y']=yc;md['beam_center_x']=xc\n", + "if rot90 and not reverse:\n", + " raise Exception('ERROR: somebody still needs to figure out the transformation for reverse=%s and rot90=%s!'%(reverse,rot90))\n", + "print('Beam Center: xc: %s yc: %s'%(md['beam_center_x'],md['beam_center_y']))\n", + "\n", + "_record_xpcs_cell_timing(\"13 - Apply image metadata\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "### create aggregate image of OAV images" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Aggregate OAV images\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "save_oavs = False\n", + "found_oavs = False\n", + "for d in detectors:\n", + " if 'OAV_image' in d:\n", + " found_oavs=True \n", + " \n", + "if found_oavs:\n", + " try:\n", + " save_oavs_tifs_v2( uid, data_dir )\n", + " save_oavs = True\n", + " print('successfully created aggregate image from individual OAV images')\n", + " except:\n", + " print('Failed to create aggregate image from individual OAV images -> OAV images will not be attached to Olog.')\n", + "\n", + "_record_xpcs_cell_timing(\"14 - Aggregate OAV images\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1e-05, + "end_time": "2023-06-20T08:53:14.325272", + "exception": false, + "start_time": "2023-06-20T08:53:14.325262", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### load detector mask" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Load detector mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "detector_mask_path = _mask_path_+'pixel_masks/'\n", + "detector_mask_filename = 'detector_mask_%s.json'%md['detector'].split('_')[0]\n", + "with open(detector_mask_path+detector_mask_filename) as stream:\n", + " det_mask_dict=json.load(stream)\n", + "det_mask=combine_detector_masks(det_mask_dict, imgs[0].shape, md['detector'])\n", + "\n", + "_record_xpcs_cell_timing(\"15 - Load detector mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:53:15.500297", + "exception": false, + "start_time": "2023-06-20T08:53:15.500273", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### load beam mask dictionary and re-create polygon mask for current detector and direct beam position" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.087476, + "end_time": "2023-06-20T08:53:15.656345", + "exception": false, + "start_time": "2023-06-20T08:53:15.568869", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Load beam-mask configuration for the selected scattering geometry.\n", + "_xpcs_cell_start = time.time()\n", + "mask_path = default_dir+'%s/%s/masks/'%(cycle, username)\n", + "if beam_mask_config_file is not None:\n", + " beam_candidates = [str(beam_mask_config_file)]\n", + "else:\n", + " beam_candidates = [os.path.join(mask_path, 'XPCS_beam_mask_%s.json'%scat_geometry)]\n", + " if scat_geometry == 'saxs':\n", + " beam_candidates.append(os.path.join(mask_path, 'XPCS_beam_mask.json'))\n", + "beam_mask_source = next((path for path in beam_candidates if os.path.isfile(path)), None)\n", + "if beam_mask_source is not None:\n", + " with open(beam_mask_source) as stream:\n", + " polygon_dict = json.load(stream)\n", + " if not isinstance(polygon_dict, dict) or not isinstance(polygon_dict.get('masks'), dict):\n", + " raise ValueError('Beam-mask configuration must contain a masks dictionary: %s'%beam_mask_source)\n", + " print('loading %s beam mask from %s'%(scat_geometry, beam_mask_source))\n", + "elif beam_mask_config_file is not None:\n", + " raise FileNotFoundError('Beam-mask configuration not found: %s'%beam_mask_config_file)\n", + "elif auto_bst_mask or manual_mask_file is not None:\n", + " beam_mask_source = 'generated:%s:beam_mask'%scat_geometry\n", + " if scat_geometry == 'saxs':\n", + " polygon_dict={'masks':{'partial_mask':{'x_off': [0, -80], 'y_off': [0, 0],\n", + " 'wy_left': [20, 0], 'wy_right': [10, 36], 'wx_up': [20, 0],\n", + " 'wx_down': [20, 0], 'center_radius': [0, 0]}}}\n", + " elif scat_geometry == 'gi_saxs':\n", + " polygon_dict={'masks':{'partial_mask':{'x_off': [0, 0], 'y_off': [0, 0],\n", + " 'wy_left': [0, 0], 'wy_right': [0, 0], 'wx_up': [36, 0],\n", + " 'wx_down': [36, 0], 'center_radius': [0, 0]}}}\n", + " else:\n", + " polygon_dict={'masks': {}}\n", + " if manual_mask_file is None:\n", + " warnings.warn('No %s beam-mask configuration found; the generated beam mask is empty. Set beam_mask_config_file or manual_mask_file to exclude the beam shadow.'%scat_geometry, RuntimeWarning)\n", + "else:\n", + " raise FileNotFoundError('No %s beam mask; set beam_mask_config_file or manual_mask_file'%scat_geometry)\n", + "_record_xpcs_cell_timing(\"16 - Load beam-mask configuration for the selected scattering geometry.\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.071073, + "end_time": "2023-06-20T08:53:15.731017", + "exception": false, + "start_time": "2023-06-20T08:53:15.659944", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Define polygon mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "print('polygon masks: (could edit dictionary entries to modify mask here)')\n", + "polygon_dict['masks']\n", + "\n", + "_record_xpcs_cell_timing(\"17 - Define polygon mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Define polygon mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry == 'saxs' and beam_mask_source.startswith('generated:') and 'partial_mask' in polygon_dict['masks']:\n", + " polygon_dict['masks']['partial_mask']['wy_right']= [8, 26]\n", + " polygon_dict['masks']['partial_mask']['wx_up']= [8, 0]\n", + " polygon_dict['masks']['partial_mask']['wx_down']= [8, 0]\n", + " polygon_dict['masks']['partial_mask']['wy_left']= [8, 0]\n", + " polygon_dict['masks']['partial_mask']['x_off'] = [0, -63]\n", + "\n", + "_record_xpcs_cell_timing(\"18 - Define polygon mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.8e-05, + "end_time": "2023-06-20T08:53:15.731673", + "exception": false, + "start_time": "2023-06-20T08:53:15.731655", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "#### re-create multi-polygon mask:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.129297, + "end_time": "2023-06-20T08:53:15.924466", + "exception": false, + "start_time": "2023-06-20T08:53:15.795169", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Build polygon mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "polygon_mask=np.ones_like( det_mask , dtype = bool)\n", + "if 'rmask' in list(polygon_dict['masks'].keys()):\n", + " rmask_dict={}\n", + " for aa,a in enumerate(polygon_dict['masks']['rmask']['angles']):\n", + " rmask_dict[a] = create_multi_rotated_rectangle_mask( pixel_mask, \n", + " center= [ md['beam_center_x'], md['beam_center_y'] ], length=polygon_dict['masks']['rmask']['length'][aa], width=polygon_dict['masks']['rmask']['width'][aa], angles=[a] )\n", + "\n", + " for aa,a in enumerate(list(rmask_dict.keys())):\n", + " if aa == 0:\n", + " rmask = rmask_dict[a]\n", + " else:\n", + " rmask*=rmask_dict[a]\n", + " polygon_mask*=rmask\n", + "if 'partial_mask' in list(polygon_dict['masks'].keys()):\n", + " partialmask_dict={}\n", + " for ii,i in enumerate(range(len(polygon_dict['masks']['partial_mask']['x_off']))[:]): # [:] use all elements in list; [:2] use the first two elements in list, etc. to create masks\n", + " partialmask_dict[ii] = create_cross_mask( pixel_mask,center= [ md['beam_center_x']+polygon_dict['masks']['partial_mask']['x_off'][i], md['beam_center_y']+polygon_dict['masks']['partial_mask']['y_off'][i] ], \n", + " wy_left= polygon_dict['masks']['partial_mask']['wy_left'][i], wy_right= polygon_dict['masks']['partial_mask']['wy_right'][i], \n", + " wx_up= polygon_dict['masks']['partial_mask']['wx_up'][i], wx_down= polygon_dict['masks']['partial_mask']['wx_down'][i],center_radius= polygon_dict['masks']['partial_mask']['center_radius'][i])\n", + " \n", + " for i in list(partialmask_dict.keys()):\n", + " if i == 0:\n", + " partial_mask = partialmask_dict[i]\n", + " else:\n", + " partial_mask*=partialmask_dict[i]\n", + " polygon_mask*=partial_mask\n", + "if 'window_mask' in list(polygon_dict['masks'].keys()):\n", + " try: # center_circle has been renamed to center_disk at some point -> with try this works on old and new environements\n", + " window_shadow = ~create_cross_mask( pixel_mask, center=[md['beam_center_x'],md['beam_center_y']],\n", + " wy_left= 0, wy_right= 0, \n", + " wx_up= 0, wx_down= 0,center_disk=True, center_radius= polygon_dict['masks']['window_mask']['center_radius'])\n", + " except:\n", + " window_shadow = ~create_cross_mask( pixel_mask, center=[md['beam_center_x'],md['beam_center_y']],\n", + " wy_left= 0, wy_right= 0, \n", + " wx_up= 0, wx_down= 0,center_circle=True, center_radius= polygon_dict['masks']['window_mask']['center_radius'])\n", + " print('using \"create_cross_mask\" for older python environments')\n", + " polygon_mask*=window_shadow\n", + "\n", + "_record_xpcs_cell_timing(\"19 - Build polygon mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.915534, + "end_time": "2023-06-20T08:53:17.094650", + "exception": false, + "start_time": "2023-06-20T08:53:16.179116", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot detector and beam masks\n", + "_xpcs_cell_start = time.time()\n", + "if manual_mask_file is not None:\n", + " polygon_mask = load_manual_mask(manual_mask_file, det_mask.shape, manual_mask_orientation, geometry=scat_geometry)\n", + " mask_input_source = str(manual_mask_file)\n", + "else:\n", + " mask_input_source = beam_mask_source\n", + "mask = polygon_mask * det_mask\n", + "mask_copy = mask.copy()\n", + "fig, ax = plt.subplots(1, 3, figsize=(15, 5))\n", + "fig.suptitle('detector mask: %s\\nbeam mask: %s'%(detector_mask_path+detector_mask_filename, mask_input_source))\n", + "for axis, image, title in zip(ax, (det_mask, polygon_mask, mask),\n", + " ('detector mask', 'beam mask', 'combined mask')):\n", + " axis.imshow(image)\n", + " axis.set_title(title)\n", + "_record_xpcs_cell_timing(\"20 - Plot detector and beam masks\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.07127, + "end_time": "2023-06-20T08:53:17.274749", + "exception": false, + "start_time": "2023-06-20T08:53:17.203479", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Display metadata\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "print_dict( md, ['suid', 'number of images', 'uid', 'scan_id', 'start_time', 'stop_time', 'sample', 'Measurement',\n", + " 'acquire period', 'exposure time', \n", + " 'det_distance', 'beam_center_x', 'beam_center_y', ] )\n", + "\n", + "_record_xpcs_cell_timing(\"21 - Display metadata\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.6e-05, + "end_time": "2023-06-20T08:53:17.276413", + "exception": false, + "start_time": "2023-06-20T08:53:17.276397", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Overwrite Some Metadata if Wrong Input" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:17.336854", + "exception": false, + "start_time": "2023-06-20T08:53:17.336832", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Define incident beam center (also define reflection beam center for gisaxs)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.060425, + "end_time": "2023-06-20T08:53:17.715880", + "exception": false, + "start_time": "2023-06-20T08:53:17.655455", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Incident beam center in the oriented analysis image (column, row).\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "inc_x0 = float(md['beam_center_x'])\n", + "inc_y0 = float(md['beam_center_y'])\n", + "print('incident beam center:', inc_x0, inc_y0)\n", + "\n", + "_record_xpcs_cell_timing(\"22 - Incident beam center in the oriented analysis image (column, row).\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.06776, + "end_time": "2023-06-20T08:53:17.787324", + "exception": false, + "start_time": "2023-06-20T08:53:17.719564", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Validate experiment metadata\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry in ('gi_saxs', 'gi_waxs'):\n", + " if 'x_pixel_size' not in md:\n", + " if surface_pixel_size_mm is None:\n", + " raise ValueError('Missing surface pixel size in metadata; set surface_pixel_size_mm')\n", + " md['x_pixel_size'] = float(surface_pixel_size_mm) / 1000\n", + " if 'det_distance' not in md and 'detector_distance' not in md:\n", + " if surface_detector_distance_mm is None:\n", + " raise ValueError('Missing surface detector distance in metadata; set surface_detector_distance_mm')\n", + " md['det_distance'] = float(surface_detector_distance_mm) / 1000\n", + " if 'wavelength' not in md and 'incident_wavelength' not in md:\n", + " if surface_wavelength_angstrom is None:\n", + " raise ValueError('Missing surface wavelength in metadata; set surface_wavelength_angstrom')\n", + " md['wavelength'] = float(surface_wavelength_angstrom)\n", + "dpix, lambda_, Ldet, exposuretime, timeperframe, center = check_lost_metadata(\n", + " md, md['number of images'], inc_x0 = inc_x0, inc_y0= inc_y0, pixelsize = 7.5*10*(-5) )\n", + "if scat_geometry in ('gi_saxs', 'gi_waxs'):\n", + " surface_maps = surface_q_maps(\n", + " mask.shape, (inc_x0, inc_y0), dpix, Ldet, lambda_, md,\n", + " incident_angle_deg=surface_incident_angle_deg,\n", + " inplane_angle_deg=surface_inplane_angle_deg,\n", + " )\n", + " qr_map, qz_map = surface_maps['q_parallel'], surface_maps['q_z']\n", + " refl_x0, refl_y0 = surface_maps['reflected_center']\n", + " md['incident_angle_deg'] = surface_maps['incident_angle_deg']\n", + " md['inplane_angle_deg'] = surface_maps['inplane_angle_deg']\n", + "\n", + "setup_pargs=dict(uid=uidstr, dpix= dpix, Ldet=Ldet, lambda_= lambda_, exposuretime=exposuretime,\n", + " timeperframe=timeperframe, center=center, path= data_dir)\n", + "print_dict( setup_pargs )\n", + "\n", + "_record_xpcs_cell_timing(\"23 - Validate experiment metadata\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.595578, + "end_time": "2023-06-20T08:53:18.574809", + "exception": false, + "start_time": "2023-06-20T08:53:17.979231", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Apply detector mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "show_img(np.array(mask,dtype=int),image_name = uidstr + '_mask', save=False, path=data_dir, aspect=1, center=center)\n", + "mask_load=mask.copy()\n", + "\n", + "imgsa = apply_mask( imgs, np.array(mask,dtype=int) )\n", + "\n", + "_record_xpcs_cell_timing(\"24 - Apply detector mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.7e-05, + "end_time": "2023-06-20T08:53:18.574944", + "exception": false, + "start_time": "2023-06-20T08:53:18.574927", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Check several frames average intensity" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 4.5e-05, + "end_time": "2023-06-20T08:53:18.651470", + "exception": false, + "start_time": "2023-06-20T08:53:18.651425", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "#### Load ROI mask depending on data analysis type" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 4.591728, + "end_time": "2023-06-20T08:53:23.364728", + "exception": false, + "start_time": "2023-06-20T08:53:18.773000", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Load and align ROI mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "roi_date = 'N.A'\n", + "roi_input_source = None\n", + "if scat_geometry == 'saxs':\n", + " q_mask_name = phi_Q_mask if qphi_analysis else isotropic_Q_mask\n", + " if manual_roi_file is not None or not roi_auto:\n", + " if manual_roi_file is None:\n", + " raise ValueError('Set manual_roi_file when roi_auto is False')\n", + " fp = str(manual_roi_file)\n", + " roi_mask, qval_dict = load_manual_roi(\n", + " fp, mask.shape, scat_geometry, orientation=manual_roi_orientation,\n", + " mask=mask, center=(inc_x0, inc_y0), dpix=dpix,\n", + " distance=Ldet, wavelength=lambda_)\n", + " roi_input_source = fp\n", + " else:\n", + " fp = _mask_path_+'ROI_masks/general_roi_mask_%s.json'%q_mask_name\n", + " with open(fp) as stream:\n", + " mask_dict = json.loads(json.load(stream))\n", + " roi_mask0 = np.array(mask_dict['roi_mask'])\n", + " old_cen = mask_dict['original center']\n", + " if 'eiger500k' in md['detector'] or 'eiger4m' in md['detector']:\n", + " setup_pargs['center'] = center[::-1]\n", + " roi_mask, qval_dict, qwid_dict = get_roi_mask_qval_qwid_by_shift(\n", + " new_cen=[0, 0], new_mask=mask, old_cen=old_cen,\n", + " old_roi_mask=roi_mask0, limit_qnum=180,\n", + " setup_pargs=setup_pargs, geometry=scat_geometry_)\n", + " setup_pargs['center'] = center\n", + " roi_input_source = fp\n", + " roi_mask2 = roi_mask.copy()\n", + "elif scat_geometry in ('gi_saxs', 'gi_waxs'):\n", + " q_mask_name = scat_geometry\n", + " parallel_edges = gisaxs_q_parallel_edges if scat_geometry == 'gi_saxs' else giwaxs_q_parallel_edges\n", + " z_edges = gisaxs_q_z_edges if scat_geometry == 'gi_saxs' else giwaxs_q_z_edges\n", + " if manual_roi_file is not None:\n", + " fp = str(manual_roi_file)\n", + " roi_mask, qval_dict = load_manual_roi(\n", + " fp, mask.shape, scat_geometry, orientation=manual_roi_orientation,\n", + " mask=mask, q_maps=surface_maps)\n", + " surface_rois = surface_profile_args_from_roi(roi_mask, qval_dict, surface_maps)\n", + " roi_input_source = fp\n", + " else:\n", + " surface_rois = build_surface_rois(qr_map, qz_map, mask,\n", + " parallel_edges=parallel_edges, z_edges=z_edges,\n", + " parallel_count=8 if scat_geometry == 'gi_saxs' else 12,\n", + " z_count=3 if scat_geometry == 'gi_saxs' else 4)\n", + " roi_mask, qval_dict = surface_rois['roi_mask'], surface_rois['qval_dict']\n", + " fp = 'generated:%s:%s'%(scat_geometry, md['uid'])\n", + " roi_input_source = fp\n", + " Qr, Qz = surface_rois['Qr'], surface_rois['Qz']\n", + " Qrs, Qzs = Qr, Qz\n", + " roi_masks, qval_dicts = roi_mask.copy(), qval_dict.copy()\n", + " ticks = None\n", + " validate_roi(roi_mask, qval_dict, mask.shape, scat_geometry,\n", + " mask=mask, q_maps=surface_maps)\n", + " roi_mask2 = roi_mask.copy()\n", + "else:\n", + " # WAXS intensity bands use the compressed average image, available in cell 52.\n", + " q_mask_name = 'waxs'\n", + " roi_mask = None\n", + " roi_mask2 = None\n", + " fp = 'generated:waxs:%s'%md['uid']\n", + "_record_xpcs_cell_timing(\"25 - Load and align ROI mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.291226, + "end_time": "2023-06-20T08:53:23.656043", + "exception": false, + "start_time": "2023-06-20T08:53:23.364817", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Display ROI mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "#roi_mask = shift_mask(roi_mask, 10,30) #if shift mask to get new mask\n", + "if roi_mask is not None:\n", + " show_img(roi_mask, aspect=1.0, image_name = fp, center=center,vmin=0)\n", + "\n", + "_record_xpcs_cell_timing(\"26 - Display ROI mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 1.24473, + "end_time": "2023-06-20T08:53:24.902640", + "exception": false, + "start_time": "2023-06-20T08:53:23.657910", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Correlate sample average image\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "img_choice_N = 5\n", + "img_samp_index = random.sample( range(md['number of images']), img_choice_N) \n", + "avg_img = get_avg_img( imgsa, img_samp_index, plot_ = False, uid =uidstr)\n", + "if avg_img.max() == 0:\n", + " print('There are no photons recorded for this uid: %s'%uid)\n", + " print('The data analysis should be terminated! Please try another uid.')\n", + "\n", + "_record_xpcs_cell_timing(\"27 - Correlate sample average image\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.470349, + "end_time": "2023-06-20T08:53:25.374747", + "exception": false, + "start_time": "2023-06-20T08:53:24.904398", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Display sample image\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "show_img( imgsa[ 5], vmin = .01, vmax = 10, logs=False, aspect=1, #save_format='tif',\n", + " image_name= uidstr + '_img_avg', save=True, path=data_dir, cmap=cmap_albula,center=center)\n", + "\n", + "_record_xpcs_cell_timing(\"28 - Display sample image\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.3e-05, + "end_time": "2023-06-20T08:53:25.377076", + "exception": false, + "start_time": "2023-06-20T08:53:25.377053", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Compress Data\n", + "* Generate a compressed data with filename\n", + "* Replace old mask with a new mask with removed hot pixels\n", + "* Do average image\n", + "* Do each image sum\n", + "* Find badframe_list for where image sum above bad_pixel_threshold\n", + "* Check shutter open frame to get good time series\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.195835, + "end_time": "2023-06-20T08:53:25.642595", + "exception": false, + "start_time": "2023-06-20T08:53:25.446760", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate photon occupancy\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "compress=True\n", + "photon_occ = len( np.where(avg_img)[0] ) / ( np.shape(imgsa[0])[0]*np.shape(imgsa[0])[1]*md['number of images'])\n", + "#compress = photon_occ < .4 #if the photon ocupation < 0.5, do compress\n", + "print (\"The non-zeros photon occupation is %s.\"%( photon_occ))\n", + "print(\"Will \" + 'Always ' + ['NOT', 'DO'][compress] + \" apply compress process.\")\n", + "\n", + "_record_xpcs_cell_timing(\"29 - Calculate photon occupancy\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.059335, + "end_time": "2023-06-20T08:53:25.703430", + "exception": false, + "start_time": "2023-06-20T08:53:25.644095", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Define good start\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if \"eiger4m\" in md['detector'] or md['detector'] == 'image': \n", + " good_start = 0 #make the good_start at least 0\n", + "elif (\"eiger500k\" in md['detector']) or (\"eiger500K\" in md['detector']): \n", + " good_start = 0#100 #5 #make the good_start at least 0\n", + "elif \"eiger1m\" in md['detector'] or md['detector'] == 'image': \n", + " good_start = 0 \n", + " \n", + "if bin_frame:\n", + " bin_frame_number=bin_frame_number\n", + " acquisition_period = md['acquire period']\n", + " timeperframe = acquisition_period * bin_frame_number\n", + "else:\n", + " bin_frame_number =1\n", + "print('first frame to be used: %s\\nframe binning: %s'%(good_start,bin_frame_number))\n", + "\n", + "_record_xpcs_cell_timing(\"30 - Define good start\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.4e-05, + "end_time": "2023-06-20T08:53:25.835315", + "exception": false, + "start_time": "2023-06-20T08:53:25.835301", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### change compression behavior if necessary" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.067655, + "end_time": "2023-06-20T08:53:25.963892", + "exception": false, + "start_time": "2023-06-20T08:53:25.896237", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Set compression behavior\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "#force_compress = False\n", + "#use_local_disk = True\n", + "print('force compression: %s use local disk: %s'%(force_compress,use_local_disk))\n", + "\n", + "_record_xpcs_cell_timing(\"31 - Set compression behavior\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 19.133555, + "end_time": "2023-06-20T08:53:45.099043", + "exception": false, + "start_time": "2023-06-20T08:53:25.965488", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Compress detector data\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "imgs_=np.ones(md['number of images']) #just need to fake an array of appropriate length for the compression routine\n", + "\n", + "\n", + "# if not use_local_disk:\n", + "# cmp_path = '/nsls2/data/chx/legacy/Compressed_Data'\n", + "# else:\n", + "# cmp_path = '/tmp_data/compressed'\n", + "# print(here)\n", + " \n", + " \n", + "cmp_path = data_dir0[:-8] + 'Compressed_Data' \n", + "if bin_frame_number==1: \n", + " cmp_file = '/uid_%s.cmp'%md['uid']\n", + "else:\n", + " cmp_file = '/uid_%s_bined--%s.cmp'%(md['uid'],bin_frame_number)\n", + "\n", + "#force_compress = True\n", + "filename = cmp_path + cmp_file \n", + "mask2, avg_img, imgsum, bad_frame_list = compress_eigerdata(imgs_, det_mask, md, filename, ########## NEW: mask -> det_mask\n", + " force_compress= force_compress, para_compress= para_compress, bad_pixel_threshold = 1e14,\n", + " reverse=reverse, rot90=rot90, nobytes=4,\n", + " bins=bin_frame_number, num_sub= 100, num_max_para_process= 500, with_pickle=True,\n", + " direct_load_data =use_local_disk, data_path = data_fullpath, new_path = '/tmp/' ) \n", + " \n", + "if scat_geometry == 'waxs':\n", + " if manual_roi_file is not None:\n", + " fp = str(manual_roi_file)\n", + " roi_mask, qval_dict = load_manual_roi(\n", + " fp, mask.shape, scat_geometry, orientation=manual_roi_orientation, mask=mask)\n", + " roi_input_source = fp\n", + " else:\n", + " roi_mask, qval_dict = build_waxs_rois(avg_img, mask)\n", + " roi_input_source = fp\n", + " roi_mask2 = roi_mask.copy()\n", + " validate_roi(roi_mask, qval_dict, mask.shape, scat_geometry, mask=mask)\n", + " show_img(roi_mask, aspect=1.0, image_name=uidstr+'_waxs_ROI', center=center, vmin=0)\n", + "\n", + "min_inten = 10 \n", + "good_start = max(good_start, np.where( np.array(imgsum) > min_inten )[0][0] ) \n", + "print ('The good_start frame number is: %s '%good_start)\n", + "\n", + "FD = Multifile(filename, good_start, len(imgs_)//bin_frame_number )\n", + "\n", + "\n", + "uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + "print( uid_ )\n", + "plot1D( y = imgsum[ np.array( [i for i in np.arange(good_start, len(imgsum)) if i not in bad_frame_list])],\n", + " title =uidstr + '_imgsum', xlabel='Frame', ylabel='Total_Intensity', legend='imgsum' )\n", + "Nimg = int( md['number of images']/bin_frame_number )\n", + "\n", + "# mask2 = mask * pixel_mask * Chip_Mask\n", + "mask_copy = mask.copy()\n", + "mask_copy2 = mask.copy()\n", + "\n", + "#avg_img *= mask\n", + "\n", + "show_img( avg_img, vmin=1e-1, vmax= 1e2, logs=True, aspect=1, #save_format='tif',\n", + " image_name= uidstr + '_img_avg', save=True, \n", + " path=data_dir, center=center, cmap = cmap_albula )\n", + "\n", + "_record_xpcs_cell_timing(\"32 - Compress detector data\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "tags": [] + }, + "source": [ + "### Linking Raw data in 'rawdata' folder [folder needs to be created first]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Link raw data\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if(rawdata_link):\n", + " #data_fullpath - h5 file\n", + " #filename - cmp file\n", + " rawdata_folder = data_dir0[:-8]+'rawdata'\n", + " h5_linkname = rawdata_folder+'/'+cmp_file[:-4]+'.h5'\n", + " \n", + " #print('The raw data directory is: %s'%rawdata_folder)\n", + " #print('The hdf5 file is: %s'%data_fullpath)\n", + " #print('The cmp file is: %s'%filename[:])\n", + " #print('The h5 link name is: %s'%h5_linkname)\n", + " !ln -s {data_fullpath} {h5_linkname}\n", + " !ln -s {filename} {rawdata_folder+'/'}\n", + "\n", + "_record_xpcs_cell_timing(\"33 - Link raw data\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Update load/compression progress\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if track_progress:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='Load data and compress', progress='stop',start_time=None, stop_time=time.time(), verbose=True)\n", + " if settings_dict_['run_one_time']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='run_one_time', progress='start',start_time=time.time(), stop_time=None, verbose=True)\n", + "\n", + "_record_xpcs_cell_timing(\"34 - Update load/compression progress\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:45.101921", + "exception": false, + "start_time": "2023-06-20T08:53:45.101899", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Get bad frame list by a polynominal fit" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.071967, + "end_time": "2023-06-20T08:53:45.251004", + "exception": false, + "start_time": "2023-06-20T08:53:45.179037", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Set compressed-data range\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "good_end= None # 2000 \n", + "if good_end is not None:\n", + " FD = Multifile(filename, good_start, min( len(imgs_)//bin_frame_number, good_end) )\n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( uid_ )\n", + "\n", + "_record_xpcs_cell_timing(\"35 - Set compressed-data range\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.067784, + "end_time": "2023-06-20T08:53:45.324256", + "exception": false, + "start_time": "2023-06-20T08:53:45.256472", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Optional refine start frame\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "re_define_good_start =False\n", + "if re_define_good_start:\n", + " good_start = 180\n", + " #good_end = 19700\n", + " good_end = len(imgs_)\n", + " FD = Multifile(filename, good_start, good_end) \n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( FD.beg, FD.end)\n", + "\n", + "_record_xpcs_cell_timing(\"36 - Optional refine start frame\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.44143, + "end_time": "2023-06-20T08:53:45.767239", + "exception": false, + "start_time": "2023-06-20T08:53:45.325809", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Identify bad frames\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "bad_frame_list = get_bad_frame_list( imgsum, fit='both', plot=True,polyfit_order = 30, \n", + " scale= 3.5, good_start = good_start, good_end=good_end, uid= uidstr, path=data_dir)\n", + "\n", + "print( 'The bad frame list length is: %s'%len(bad_frame_list) )\n", + "\n", + "_record_xpcs_cell_timing(\"37 - Identify bad frames\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:45.769771", + "exception": false, + "start_time": "2023-06-20T08:53:45.769749", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Create new mask by masking the bad pixels and get new avg_img" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.069057, + "end_time": "2023-06-20T08:53:45.916919", + "exception": false, + "start_time": "2023-06-20T08:53:45.847862", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Save frame intensities\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "imgsum_y = imgsum[ np.array( [i for i in np.arange( len(imgsum)) if i not in bad_frame_list])]\n", + "imgsum_x = np.arange( len( imgsum_y))\n", + "save_lists( [imgsum_x, imgsum_y], label=['Frame', 'Total_Intensity'],\n", + " filename=uidstr + '_img_sum_t', path= data_dir )\n", + "print('number of bad pixels masked: %s'%len(imgsum_y))\n", + "\n", + "_record_xpcs_cell_timing(\"38 - Save frame intensities\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:53:45.920912", + "exception": false, + "start_time": "2023-06-20T08:53:45.920888", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Plot time~ total intensity of each frame" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.225016, + "end_time": "2023-06-20T08:53:46.212031", + "exception": false, + "start_time": "2023-06-20T08:53:45.987015", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot frame intensities\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "plot1D( y = imgsum_y, title = uidstr + '_img_sum_t', xlabel='Frame', c='b',\n", + " ylabel='Total_Intensity', legend='imgsum', save=True, path=data_dir)\n", + "\n", + "_record_xpcs_cell_timing(\"39 - Plot frame intensities\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.1e-05, + "end_time": "2023-06-20T08:53:46.214725", + "exception": false, + "start_time": "2023-06-20T08:53:46.214704", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Get Dynamic Mask (currently designed for 500K)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.8e-05, + "end_time": "2023-06-20T08:53:46.289744", + "exception": false, + "start_time": "2023-06-20T08:53:46.289726", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# NEED ALL Detectors! There are 3 bit-depth levels!\n", + "### check Dectris documentation: 16/8/4 bit(?)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.067637, + "end_time": "2023-06-20T08:53:46.423218", + "exception": false, + "start_time": "2023-06-20T08:53:46.355581", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Build dynamic detector mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if \"eiger4m\" in md['detector'] or md['detector'] == 'image': \n", + " pass\n", + "elif (\"eiger500k\" in md['detector']) or (\"eiger500K\" in md['detector']): \n", + " if md['eiger500K_single_cam_acquire_period'] <= 0.00015: #will check this logic\n", + " if imgs[0].dtype == 'uint8':\n", + " print('Create dynamic mask for 500K due to 9K data acquistion!!!')\n", + " #bdp = find_bad_pixels_FD( bad_frame_list, FD, img_shape = avg_img.shape, threshold= 15 ) \n", + " bdp = find_bad_pixels_FD( np.arange(Nimg), FD, img_shape = avg_img.shape, threshold= 15 ) \n", + " mask = mask_copy2.copy()\n", + " mask *=bdp \n", + " mask_copy = mask.copy()\n", + " show_img( np.array(mask,dtype=int), image_name='New Mask_uid=%s'%uid, aspect=1 )\n", + "\n", + "dynamic_mask_applied = not np.array_equal(mask, mask_copy2)\n", + "if dynamic_mask_applied and scat_geometry != 'saxs':\n", + " roi_mask, qval_dict = intersect_roi_with_mask(roi_mask, qval_dict, mask, geometry=scat_geometry)\n", + " roi_mask2 = roi_mask.copy()\n", + " print('Dynamic mask updated %s ROIs'%len(qval_dict))\n", + "\n", + "_record_xpcs_cell_timing(\"40 - Build dynamic detector mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.9e-05, + "end_time": "2023-06-20T08:53:46.423875", + "exception": false, + "start_time": "2023-06-20T08:53:46.423856", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## SAXS Scattering Geometry" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.065967, + "end_time": "2023-06-20T08:53:46.625511", + "exception": false, + "start_time": "2023-06-20T08:53:46.559544", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Setup center args\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "setup_pargs['center'] = center[::-1]\n", + "\n", + "_record_xpcs_cell_timing(\"41 - Setup center args\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 1.376382, + "end_time": "2023-06-20T08:53:48.007758", + "exception": false, + "start_time": "2023-06-20T08:53:46.631376", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate SAXS circular average\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='saxs':\n", + " outlier_threshold = 5.5 # change here, if necessary\n", + " maximum_outlier_fraction = .1\n", + " \n", + " roi_mask = roi_mask2.copy()\n", + " ## Get circular average| * Do plot and save q~iq\n", + " mask = mask_copy.copy()\n", + " hmask = create_hot_pixel_mask( avg_img, threshold = 2e8, center=center, center_radius= 100)\n", + " mask =np.array( mask * hmask, dtype=bool)\n", + " \n", + " if mask_outliers:\n", + " hhmask = outlier_mask(avg_img,mask,roi_mask,outlier_threshold = outlier_threshold, maximum_outlier_fraction = maximum_outlier_fraction,verbose=False,plot=False)\n", + " mask =np.array( mask * hhmask, dtype=bool)\n", + " \n", + " qp_saxs, iq_saxs, q_saxs = get_circular_average( avg_img * det_mask , mask * hmask, save=True,\n", + " #qp_saxs, iq_saxs, q_saxs = get_circular_average( avg_img * det_mask*mask , mask, save=True,\n", + " pargs=setup_pargs )\n", + " plot_circular_average( qp_saxs, iq_saxs, q_saxs, pargs=setup_pargs, show_pixel=True,\n", + " xlim=[qp_saxs.min(), qp_saxs.max()*1.0], ylim = [iq_saxs.min(), iq_saxs.max()*2] )\n", + " \n", + " print('Removed %s hot pixels.'%len(np.nonzero(hmask-1)[0]))\n", + " roi_mask, qval_dict = intersect_roi_with_mask(roi_mask, qval_dict, mask, geometry='saxs')\n", + "\n", + "_record_xpcs_cell_timing(\"42 - Calculate SAXS circular average\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 2.431654, + "end_time": "2023-06-20T08:53:50.439550", + "exception": false, + "start_time": "2023-06-20T08:53:48.007896", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Validate and plot SAXS ROIs\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='saxs': \n", + " qr = np.array( [qval_dict[k][0] for k in sorted( qval_dict.keys())] )\n", + " if qphi_analysis == False:\n", + " try:\n", + " qr_cal, qr_wid = get_QrQw_From_RoiMask( roi_mask, setup_pargs ) \n", + " print(len(qr)) \n", + " if (qr_cal - qr).sum() >=1e-3:\n", + " print( 'The loaded ROI mask might not be applicable to this UID: %s.'%uid)\n", + " print('Please check the loaded roi mask file.')\n", + " except:\n", + " print('Something is wrong with the roi-mask. Please check the loaded roi mask file.') \n", + " \n", + " \n", + " show_ROI_on_image( avg_img*roi_mask, roi_mask, center, label_on = False, rwidth = 600, alpha=.9, \n", + " save=True, path=data_dir, uid=uidstr, vmin= 1e-1,\n", + " vmax= 1e3, #np.max(avg_img),\n", + " aspect=1,\n", + " show_roi_edge=True, \n", + " show_ang_cor = True) \n", + " plot_qIq_with_ROI( q_saxs, iq_saxs, np.unique(qr), logs=True, uid=uidstr, \n", + " xlim=[q_saxs.min(), q_saxs.max()*1.02],#[0.0001,0.08],\n", + " ylim = [iq_saxs.min(), iq_saxs.max()*1.02], save=True, path=data_dir)\n", + "\n", + "_record_xpcs_cell_timing(\"43 - Validate and plot SAXS ROIs\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:50.443489", + "exception": false, + "start_time": "2023-06-20T08:53:50.443467", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Time Depedent I(q) Analysis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate time-dependent I(q)\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='saxs':\n", + " slice_num=3\n", + " slice_width=2\n", + " Nimg = FD.end - FD.beg \n", + " time_edge = create_time_slice( Nimg, slice_num=slice_num, slice_width=slice_width, edges = None )\n", + " time_edge = np.array( time_edge ) + good_start \n", + " if slice_num*slice_width >10: # doing circular average from sparsified data\n", + " qpt, iqst, qt = get_t_iqc( FD, time_edge, mask*det_mask, pargs=setup_pargs, nx=1500, show_progress= False )\n", + " else: # if we only need a few images, circular average from dask.array is faster\n", + " qpt, iqst, qt = get_t_iqc_imstack( imgs, time_edge, mask*det_mask, pargs=setup_pargs, nx=1500, show_progress= False )\n", + " plot_t_iqc( qt, iqst, time_edge, pargs=setup_pargs, xlim=[qt.min(), qt.max()],\n", + " ylim = [iqst.min(), iqst.max()], save=True )\n", + "\n", + "_record_xpcs_cell_timing(\"44 - Calculate time-dependent I(q)\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.1e-05, + "end_time": "2023-06-20T08:53:52.730777", + "exception": false, + "start_time": "2023-06-20T08:53:52.730756", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## For fit one peak" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.071287, + "end_time": "2023-06-20T08:53:52.881893", + "exception": false, + "start_time": "2023-06-20T08:53:52.810606", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Fit SAXS peak\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='saxs':\n", + " if fit_peak: \n", + " q1 = 0.162\n", + " x = q_saxs\n", + " y= iq_saxs\n", + " aind = [ find_index( q_saxs, q1 ) ]\n", + " w = 50\n", + " xrange = [ aind[0] -w, aind[0] + w] \n", + " cen, cen_std, wid, wid_std, xf, out = fit_one_peak_curve( x, y, xrange ) \n", + " fp = data_dir + uidstr + '_qIq_fit.png' \n", + " ax = plot_xy_with_fit( x, y, xf, out, cen, cen_std,wid, wid_std,\n", + " xlim=[0.01,0.3],xlabel= 'q ('r'$\\AA^{-1}$)',\n", + " ylabel='I(q)', filename=fp)\n", + "\n", + "_record_xpcs_cell_timing(\"45 - Fit SAXS peak\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.073766, + "end_time": "2023-06-20T08:53:52.961597", + "exception": false, + "start_time": "2023-06-20T08:53:52.887831", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate scattering invariant\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_invariant_analysis:\n", + " if scat_geometry =='saxs':\n", + " invariant = get_iq_invariant( qt, iqst )\n", + " time_stamp = time_edge[:,0] * timeperframe\n", + "\n", + " if scat_geometry =='saxs':\n", + " plot_q2_iq( qt, iqst, time_stamp,pargs=setup_pargs,ylim=[ -0.001, 0.01] , \n", + " xlim=[0.007,0.2],legend_size= 6 )\n", + "\n", + " if scat_geometry =='saxs':\n", + " plot_time_iq_invariant( time_stamp, invariant, pargs=setup_pargs, )\n", + "\n", + " if False:\n", + " iq_int = np.zeros( len(iqst) )\n", + " fig, ax = plt.subplots()\n", + " q = qt\n", + " for i in range(iqst.shape[0]):\n", + " yi = iqst[i] * q**2\n", + " iq_int[i] = yi.sum()\n", + " time_labeli = 'time_%s s'%( round( time_edge[i][0] * timeperframe, 3) )\n", + " plot1D( x = q, y = yi, legend= time_labeli, xlabel='Q (A-1)', ylabel='I(q)*Q^2', title='I(q)*Q^2 ~ time',\n", + " m=markers[i], c = colors[i], ax=ax, ylim=[ -0.001, 0.01] , xlim=[0.007,0.2],\n", + " legend_size=4)\n", + "\n", + " #print( iq_int )\n", + "\n", + "_record_xpcs_cell_timing(\"46 - Calculate scattering invariant\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.7e-05, + "end_time": "2023-06-20T08:53:52.964961", + "exception": false, + "start_time": "2023-06-20T08:53:52.964934", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# GiSAXS Scattering Geometry" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.052256, + "end_time": "2023-06-20T08:53:53.088428", + "exception": false, + "start_time": "2023-06-20T08:53:53.036172", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot calibrated surface q map\n", + "_xpcs_cell_start = time.time()\n", + "if scat_geometry in ('gi_saxs', 'gi_waxs'):\n", + " plot_surface_roi(avg_img, roi_mask, surface_maps, data_dir, uidstr)\n", + "_record_xpcs_cell_timing(\"47 - Plot calibrated surface q map\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.9e-05, + "end_time": "2023-06-20T08:53:53.116316", + "exception": false, + "start_time": "2023-06-20T08:53:53.116287", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Static Analysis for gisaxs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.081684, + "end_time": "2023-06-20T08:53:53.277810", + "exception": false, + "start_time": "2023-06-20T08:53:53.196126", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Static GISAXS ROIs are generated from this run's calibrated map.\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "if scat_geometry == 'gi_saxs':\n", + " print('GISAXS static ROI count:', len(qval_dicts))\n", + "\n", + "_record_xpcs_cell_timing(\"48 - Static GISAXS ROIs are generated from this run's calibrated map.\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.068521, + "end_time": "2023-06-20T08:53:53.349071", + "exception": false, + "start_time": "2023-06-20T08:53:53.280550", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate time-dependent GISAXS profiles\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='gi_saxs': \n", + " Nimg = FD.end - FD.beg \n", + " time_edge = create_time_slice( N= Nimg, slice_num= 3, slice_width= 2, edges = None )\n", + " time_edge = np.array( time_edge ) + good_start\n", + " print( time_edge ) \n", + " qrt_pds = get_t_qrc( FD, time_edge, Qrs, Qzs, qr_map, qz_map, mask=mask, path=data_dir, uid = uidstr ) \n", + " plot_qrt_pds( qrt_pds, time_edge, qz_index = 0, uid = uidstr, path = data_dir )\n", + "\n", + "_record_xpcs_cell_timing(\"49 - Calculate time-dependent GISAXS profiles\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.1e-05, + "end_time": "2023-06-20T08:53:53.353582", + "exception": false, + "start_time": "2023-06-20T08:53:53.353561", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Make a Profile Plot" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.068581, + "end_time": "2023-06-20T08:53:53.493133", + "exception": false, + "start_time": "2023-06-20T08:53:53.424552", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate GISAXS waterfall from a ROI generated for this run.\n", + "_xpcs_cell_start = time.time()\n", + "if scat_geometry == 'gi_saxs' and run_profile_plot:\n", + " waterfall_roi = np.asarray(roi_mask == 1, dtype=np.int32)\n", + " wat = cal_waterfallc(FD, waterfall_roi, qindex=1,\n", + " save=True, path=data_dir, uid=uidstr)\n", + "_record_xpcs_cell_timing(\"50 - Calculate GISAXS waterfall from a ROI generated for this run.\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.070595, + "end_time": "2023-06-20T08:53:53.568310", + "exception": false, + "start_time": "2023-06-20T08:53:53.497715", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot GISAXS waterfall\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='gi_saxs':\n", + " if run_profile_plot:\n", + " plot_waterfallc( wat, qindex=1, aspect=None, vmin=1, vmax= np.max( wat), uid=uidstr, save =True, \n", + " path=data_dir, beg= FD.beg)\n", + "\n", + "_record_xpcs_cell_timing(\"51 - Plot GISAXS waterfall\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.9e-05, + "end_time": "2023-06-20T08:53:53.570297", + "exception": false, + "start_time": "2023-06-20T08:53:53.570278", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Dynamic Analysis for gi_saxs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.068646, + "end_time": "2023-06-20T08:53:53.712641", + "exception": false, + "start_time": "2023-06-20T08:53:53.643995", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate GISAXS 1D profile\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='gi_saxs': \n", + " # ROI overlay saved by the private surface plotting adapter. \n", + " ## Get 1D Curve (Q||-intensity¶)\n", + " qr_1d_pds = cal_1d_qr( avg_img, Qr, Qz, qr_map, qz_map, inc_x0= None, mask=mask, setup_pargs=setup_pargs )\n", + " plot_qr_1d_with_ROI( qr_1d_pds, qr_center=np.unique( np.array(list( qval_dict.values() ) )[:,0] ),\n", + " loglog=True, save=True, uid=uidstr, path = data_dir)\n", + "\n", + "_record_xpcs_cell_timing(\"52 - Calculate GISAXS 1D profile\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.7e-05, + "end_time": "2023-06-20T08:53:53.720709", + "exception": false, + "start_time": "2023-06-20T08:53:53.720682", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# GiWAXS Scattering Geometry" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.068797, + "end_time": "2023-06-20T08:53:53.860284", + "exception": false, + "start_time": "2023-06-20T08:53:53.791487", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot WAXS and GIWAXS ROIs\n", + "_xpcs_cell_start = time.time()\n", + "if scat_geometry == 'gi_waxs':\n", + " plot_surface_roi(avg_img, roi_mask, surface_maps, data_dir, uidstr)\n", + "elif scat_geometry == 'waxs':\n", + " show_ROI_on_image(avg_img, roi_mask, label_on=True, alpha=.5,\n", + " save=True, path=data_dir, uid=uidstr, vmin=0.1, vmax=500)\n", + "_record_xpcs_cell_timing(\"53 - Plot WAXS and GIWAXS ROIs\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.7e-05, + "end_time": "2023-06-20T08:53:53.867728", + "exception": false, + "start_time": "2023-06-20T08:53:53.867701", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "* Extract the labeled array" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.184571, + "end_time": "2023-06-20T08:53:54.121427", + "exception": false, + "start_time": "2023-06-20T08:53:53.936856", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Extract ROI pixel labels\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "qind, pixelist = roi.extract_label_indices(roi_mask)\n", + "noqs = len(np.unique(qind))\n", + "print('calculating correlation functions for %s Qs'%noqs)\n", + "\n", + "_record_xpcs_cell_timing(\"54 - Extract ROI pixel labels\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1e-05, + "end_time": "2023-06-20T08:53:54.121592", + "exception": false, + "start_time": "2023-06-20T08:53:54.121582", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "* Number of pixels in each q box" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.258516, + "end_time": "2023-06-20T08:53:54.467645", + "exception": false, + "start_time": "2023-06-20T08:53:54.209129", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot ROI pixel counts\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "nopr = np.bincount(qind, minlength=(noqs+1))[1:]\n", + "roi_x = range(len(nopr))\n", + "plt.semilogy(roi_x,nopr,'ro',fillstyle='none');plt.xlabel('ROI #');plt.ylabel('number of pixels in ROI')\n", + "\n", + "_record_xpcs_cell_timing(\"55 - Plot ROI pixel counts\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.3e-05, + "end_time": "2023-06-20T08:53:54.467774", + "exception": false, + "start_time": "2023-06-20T08:53:54.467761", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Check one ROI intensity" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.514916, + "end_time": "2023-06-20T08:53:55.063776", + "exception": false, + "start_time": "2023-06-20T08:53:54.548860", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Check ROI intensity\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "roi_inten = check_ROI_intensity( avg_img, roi_mask, ring_number=min(5, len(qval_dict)), uid =uidstr ) #roi starting from 1\n", + "\n", + "_record_xpcs_cell_timing(\"56 - Check ROI intensity\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.3e-05, + "end_time": "2023-06-20T08:53:55.066661", + "exception": false, + "start_time": "2023-06-20T08:53:55.066638", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Do a waterfall analysis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.06989, + "end_time": "2023-06-20T08:53:55.215259", + "exception": false, + "start_time": "2023-06-20T08:53:55.145369", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate waterfall analysis\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "qth_interest = min(2, len(qval_dict)) # ROI index starts from 1\n", + "if scat_geometry =='saxs' or scat_geometry =='gi_waxs' or scat_geometry == 'gi_saxs' or scat_geometry == 'waxs':\n", + " if run_waterfall: \n", + " wat = cal_waterfallc( FD, roi_mask, qindex= qth_interest, save =True, path=data_dir, uid=uidstr)\n", + " plot_waterfallc( wat, qth_interest, aspect= None, vmin=1e-1, vmax= wat.max(), uid=uidstr, save =True, \n", + " path=data_dir, beg= FD.beg, cmap = cmap_vge )\n", + "\n", + "_record_xpcs_cell_timing(\"57 - Calculate waterfall analysis\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 4.682422, + "end_time": "2023-06-20T08:53:59.904224", + "exception": false, + "start_time": "2023-06-20T08:53:55.221802", + "status": "completed" + }, + "scrolled": true, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate ROI intensities over time\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "ring_avg = None \n", + "if run_t_ROI_Inten:\n", + " times_roi, mean_int_sets = cal_each_ring_mean_intensityc(FD, roi_mask, timeperframe = None, multi_cor= False )\n", + " mean_int_setsF = np.zeros( [FD.end, mean_int_sets.shape[1] ] )\n", + " mean_int_setsF[FD.beg:FD.end] =mean_int_sets\n", + " plot_each_ring_mean_intensityc( times_roi, mean_int_sets, uid = uidstr, save=True, path=data_dir )\n", + " roi_avg = np.average( mean_int_sets, axis=0)\n", + "\n", + "_record_xpcs_cell_timing(\"58 - Calculate ROI intensities over time\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:53:59.909109", + "exception": false, + "start_time": "2023-06-20T08:53:59.909084", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Analysis for mass center of reflective beam center" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.076743, + "end_time": "2023-06-20T08:54:00.072146", + "exception": false, + "start_time": "2023-06-20T08:53:59.995403", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate ROI mass center\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_get_mass_center:\n", + " cx, cy = get_mass_center_one_roi(FD, roi_mask, roi_ind=min(25, len(qval_dict)))\n", + " fig,ax=plt.subplots(2)\n", + " plot1D( cx, m='o', c='b',ax=ax[0], legend='mass center-refl_X', \n", + " ylim=[940, 960], ylabel='posX (pixel)')\n", + " plot1D( cy, m='s', c='r',ax=ax[1], legend='mass center-refl_Y', \n", + " ylim=[1540, 1544], xlabel='frames',ylabel='posY (pixel)')\n", + "\n", + "_record_xpcs_cell_timing(\"59 - Calculate ROI mass center\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:54:00.077918", + "exception": false, + "start_time": "2023-06-20T08:54:00.077893", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## One time Correlation\n", + "\n", + "Note : Enter the number of buffers for Muliti tau one time correlation\n", + "number of buffers has to be even. More details in https://github.com/scikit-beam/scikit-beam/blob/master/skbeam/core/correlation.py" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.8e-05, + "end_time": "2023-06-20T08:54:00.154143", + "exception": false, + "start_time": "2023-06-20T08:54:00.154115", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### if define another good_series" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.076908, + "end_time": "2023-06-20T08:54:00.306452", + "exception": false, + "start_time": "2023-06-20T08:54:00.229544", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Select one-time correlation range\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "good_start_g2 = FD.beg\n", + "good_end_g2 = FD.end\n", + "define_good_series = False\n", + "hdf5_name_extension=''\n", + "if 'rstop' in locals() or 'rstart' in locals():\n", + " define_good_series = True\n", + "if define_good_series:\n", + " if 'rstart' in locals():\n", + " good_start_g2 = rstart\n", + " if 'rstop' in locals():\n", + " good_end_g2 = rstop\n", + " hdf5_name_extension = '_%s_%s'%(good_start_g2,good_end_g2)\n", + " FD = Multifile(filename, beg = good_start_g2, end = good_end_g2) #end=1000)\n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( uid_ )\n", + "\n", + "_record_xpcs_cell_timing(\"60 - Select one-time correlation range\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.295086, + "end_time": "2023-06-20T08:54:00.604436", + "exception": false, + "start_time": "2023-06-20T08:54:00.309350", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Build correlation normalization\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if use_sqnorm:#for transmision SAXS\n", + " norm = get_pixelist_interp_iq( qp_saxs, iq_saxs, roi_mask, setup_pargs['center'])\n", + " print('Using circular average in the normalization of G2 for SAXS scattering.')\n", + "elif use_SG:#for Gi-SAXS or WAXS\n", + " avg_imgf = sgolay2d( avg_img, window_size= 11, order= 5) * mask\n", + " norm=np.ravel(avg_imgf)[pixelist] \n", + " print('Using smoothed image by SavitzkyGolay filter in the normalization of G2.') \n", + "elif use_SG_bin_frames:#for Gi-SAXS or WAXS\n", + " avg_imgf = sgolay2d( avg_img, window_size= 11, order= 5) * mask\n", + " norm_avg=np.ravel(avg_imgf)[pixelist] \n", + " #print('Using smoothed image by SavitzkyGolay filter in the normalization of G2.')\n", + " bins_number = 1 \n", + " norm = get_SG_norm( FD, pixelist, bins=bins_number, mask=mask, window_size= 11, order=5 ) \n", + " print('Using smoothed bined: %s frames by SavitzkyGolay filter in the normalization of G2.'%bins_number) \n", + "else: \n", + " norm= None\n", + " print('Using simple (average) normalization of G2.') \n", + "\n", + "if use_imgsum_norm:\n", + " imgsum_ = imgsum\n", + " print('Using frame total intensity for intensity normalization in g2 calculation.') \n", + "else:\n", + " imgsum_ = None\n", + "\n", + "_record_xpcs_cell_timing(\"61 - Build correlation normalization\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 76.981197, + "end_time": "2023-06-20T08:55:17.588517", + "exception": false, + "start_time": "2023-06-20T08:54:00.607320", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate one-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_one_time: \n", + " if cal_g2_error: \n", + " g2,lag_steps,g2_err = cal_g2p(FD,roi_mask,bad_frame_list,good_start, num_buf = 8,\n", + " num_lev= None,imgsum= imgsum_, norm=norm, cal_error= True )\n", + " else: \n", + " g2,lag_steps = cal_g2p(FD,roi_mask,bad_frame_list,good_start, num_buf = 8,\n", + " num_lev= None,imgsum= imgsum_, norm=norm, cal_error= False )\n", + "\n", + "_record_xpcs_cell_timing(\"62 - Calculate one-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.051688, + "end_time": "2023-06-20T08:55:17.642066", + "exception": false, + "start_time": "2023-06-20T08:55:17.590378", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Save one-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_one_time:\n", + " \n", + " taus = lag_steps * timeperframe \n", + " try:\n", + " g2_pds = save_g2_general( g2, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0],\n", + " qz = np.array( list( qval_dict.values() ) )[:g2.shape[1],1],\n", + " uid=uid_+'_g2.csv', path= data_dir, return_res=True )\n", + " except:\n", + " g2_pds = save_g2_general( g2, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0], \n", + " uid=uid_+'_'+q_mask_name+'_g2.csv', path= data_dir, return_res=True ) \n", + " if cal_g2_error: \n", + " try:\n", + " g2_err_pds = save_g2_general( g2_err, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0],\n", + " qz = np.array( list( qval_dict.values() ) )[:g2.shape[1],1],\n", + " uid=uid_+'_g2_err.csv', path= data_dir, return_res=True )\n", + " except:\n", + " g2_err_pds = save_g2_general( g2_err, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0], \n", + " uid=uid_+'_'+q_mask_name+'_g2_err.csv', path= data_dir, return_res=True )\n", + "\n", + "_record_xpcs_cell_timing(\"63 - Save one-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.3e-05, + "end_time": "2023-06-20T08:55:17.707341", + "exception": false, + "start_time": "2023-06-20T08:55:17.707318", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Fit g2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.163419, + "end_time": "2023-06-20T08:55:17.958540", + "exception": false, + "start_time": "2023-06-20T08:55:17.795121", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Fit one-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_one_time:\n", + " try:\n", + " g2_fit_result, taus_fit, g2_fit = get_g2_fit_general( g2, taus, \n", + " function = fit_g2_func, vlim=[0.95, 1.05], fit_range= None, \n", + " fit_variables={'baseline':False, 'beta': True, 'alpha':True,'relaxation_rate':True,}, \n", + " guess_values={'baseline':1.0,'beta': 0.2,'alpha':1.0,'relaxation_rate':1e-3},\n", + " guess_limits = dict( baseline =[.9, 2], alpha=[0, 2],\n", + " beta = [0.01, 0.4], relaxation_rate= [1e-7, 1e7]) ,) \n", + " g2_fit_paras = save_g2_fit_para_tocsv(g2_fit_result, filename= uid_ +'_'+q_mask_name +'_g2_fit_paras.csv', path=data_dir ) \n", + " g2_fit_failed = False\n", + " except:\n", + " g2_fit_failed = True\n", + " from pandas import DataFrame # need to make up a fit result, otherwise writing the pdf report becomes difficult\n", + " g2_fit_paras=DataFrame(np.zeros([np.shape(g2)[1],4]),columns=['beta','relaxation_rate','alpha','baseline'])\n", + "\n", + "_record_xpcs_cell_timing(\"64 - Fit one-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 10.75033, + "end_time": "2023-06-20T08:55:28.711559", + "exception": false, + "start_time": "2023-06-20T08:55:17.961229", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot one-time correlation fit\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_one_time:\n", + " if cal_g2_error:\n", + " g2_fit_err = np.zeros_like(g2_fit)\n", + " if not g2_fit_failed:\n", + " \n", + " plot_xpcs_correlation( g2_dict={1:g2, 2:g2_fit}, taus_dict={1:taus, 2:taus_fit},\n", + " vlim=[0.95, 1.05], g2_err_dict= {1:g2_err, 2: g2_fit_err},\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= g2_fit_result, geometry=scat_geometry_, mode=scat_geometry,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '_fit',\n", + " qpi_analysis=True)\n", + " else:\n", + " plot_xpcs_correlation(g2_dict={1:g2, }, taus_dict={1:taus,},\n", + " vlim=[0.95, 1.05], g2_err_dict= {1:g2_err},\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])),\n", + " fit_res= None, geometry=scat_geometry_, mode=scat_geometry,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '',\n", + " qpi_analysis=True)\n", + " \n", + " else: \n", + " if not g2_fit_failed:\n", + " plot_xpcs_correlation( g2_dict={1:g2, 2:g2_fit}, taus_dict={1:taus, 2:taus_fit}, vlim=[0.95, 1.05],\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= g2_fit_result, geometry=scat_geometry_, mode=scat_geometry,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '_fit',\n", + " qpi_analysis=True)\n", + " else: \n", + " plot_xpcs_correlation( g2_dict={1:g2}, taus_dict={1:taus}, vlim=[0.95, 1.05],\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= None, geometry=scat_geometry_, mode=scat_geometry,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '',\n", + " qpi_analysis=True)\n", + "\n", + "_record_xpcs_cell_timing(\"65 - Plot one-time correlation fit\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.234143, + "end_time": "2023-06-20T08:55:28.948579", + "exception": false, + "start_time": "2023-06-20T08:55:28.714436", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Analyze one-time relaxation rates\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_one_time and scat_geometry != 'waxs':\n", + " try:\n", + " if True:\n", + " fs, fe = 0, 6\n", + " #fs,fe=0, 6\n", + " qval_dict_ = {k:qval_dict[k] for k in list(qval_dict.keys())[fs:fe] }\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict_, g2_fit_paras['relaxation_rate'][fs:fe], \n", + " geometry= scat_geometry_ )\n", + " plot_q_rate_fit_general( qval_dict_, g2_fit_paras['relaxation_rate'][fs:fe], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ , path= data_dir )\n", + " elif False:\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict, g2_fit_paras['relaxation_rate'],\n", + " fit_range=[0, 26], geometry= scat_geometry_ ) \n", + " plot_q_rate_fit_general( qval_dict, g2_fit_paras['relaxation_rate'], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ ,\n", + " show_fit=False, path= data_dir, plot_all_range=False) \n", + " else:\n", + " ##plot log_q, log_rate\n", + " plot_q_rate_general( qval_dict, g2_fit_paras['relaxation_rate'], \n", + " geometry= scat_geometry_,uid=uid_ , path= data_dir )\n", + "\n", + " plot_q_g2fitpara_general( qval_dict, g2_fit_paras, \n", + " geometry= scat_geometry_,uid=uid_ , path= data_dir )\n", + " except:\n", + " pass\n", + "\n", + "if run_one_time and scat_geometry == 'waxs':\n", + " plot_roi_index_rates(g2_fit_paras['relaxation_rate'], data_dir, uid_)\n", + "\n", + "_record_xpcs_cell_timing(\"66 - Analyze one-time relaxation rates\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Update one-time progress\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if track_progress:\n", + " if settings_dict_['run_one_time']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='run_one_time', progress='stop',start_time=None, stop_time=time.time(), verbose=True)\n", + " if settings_dict_['run_two_time']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='run_two_time', progress='start',start_time=time.time(), stop_time=None, verbose=True)\n", + "\n", + "_record_xpcs_cell_timing(\"67 - Update one-time progress\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2e-05, + "end_time": "2023-06-20T08:55:28.951373", + "exception": false, + "start_time": "2023-06-20T08:55:28.951353", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# For two-time" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.09029, + "end_time": "2023-06-20T08:55:29.141606", + "exception": false, + "start_time": "2023-06-20T08:55:29.051316", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Select two-time correlation range\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "define_good_series = True #making sure that the 2TCF takes ALL data into account -> this should be the default!\n", + "if define_good_series:\n", + " good_start = 0\n", + " good_end =md['number of images']\n", + " FD = Multifile(filename, beg = good_start, end = good_end)\n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( uid_ )\n", + "\n", + "_record_xpcs_cell_timing(\"68 - Select two-time correlation range\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 4.251569, + "end_time": "2023-06-20T08:55:33.393743", + "exception": false, + "start_time": "2023-06-20T08:55:29.142174", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Load two-time pixel data\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "data_pixel = None\n", + "if run_two_time: \n", + " data_pixel = Get_Pixel_Arrayc( FD, pixelist, norm= norm, ).get_data()\n", + " \n", + " ### With another normalizaiton by using roi_intensity for each frame\n", + " #data_pixel = Get_Pixel_Arrayc( FD, pixelist, norm= norm, mean_int_sets = mean_int_setsF,qind=qind ).get_data()\n", + "\n", + "_record_xpcs_cell_timing(\"69 - Load two-time pixel data\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 11.132962, + "end_time": "2023-06-20T08:55:44.530064", + "exception": false, + "start_time": "2023-06-20T08:55:33.397102", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate two-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "g12b=None\n", + "if run_two_time: \n", + " g12b = auto_two_Arrayc( data_pixel, roi_mask, index = None )\n", + " if run_dose:\n", + " np.save( data_dir + 'uid=%s_g12b'%uid, g12b)\n", + "\n", + "_record_xpcs_cell_timing(\"70 - Calculate two-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.500428, + "end_time": "2023-06-20T08:55:45.031827", + "exception": false, + "start_time": "2023-06-20T08:55:44.531399", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot two-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_two_time:\n", + " \n", + " show_C12( g12b , q_ind=min(6, g12b.shape[2]), qlabel=dict(itertools.islice(qval_dict.items(),g12b.shape[2])),\n", + " #N1= FD.beg,logs=False, N2=min( FD.end,10000), \n", + " vmin= 1.00, vmax=1.25, timeperframe=timeperframe,save=True, \n", + " path= data_dir, uid = uid_ ,cmap=plt.cm.jet)#cmap=cmap_albula)\n", + "\n", + "_record_xpcs_cell_timing(\"71 - Plot two-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.119291, + "end_time": "2023-06-20T08:55:45.152574", + "exception": false, + "start_time": "2023-06-20T08:55:45.033283", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Derive one-time correlation from two-time data\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "multi_tau_steps = True\n", + "if run_two_time:\n", + " if lag_steps is None:\n", + " num_bufs=8\n", + " noframes = FD.end - FD.beg\n", + " num_levels = int(np.log( noframes/(num_bufs-1))/np.log(2) +1) +1\n", + " tot_channels, lag_steps, dict_lag = multi_tau_lags(num_levels, num_bufs)\n", + " max_taus= lag_steps.max()\n", + " \n", + " #max_taus= lag_steps.max() \n", + " max_taus = Nimg \n", + " #tausb = np.arange( g2b.shape[0])[:max_taus] *timeperframe\n", + " if multi_tau_steps:\n", + " lag_steps_ = lag_steps[ lag_steps <= g12b.shape[0] ]\n", + " g2b = get_one_time_from_two_time(g12b)[lag_steps_]\n", + " tausb = lag_steps_ *timeperframe\n", + " else:\n", + " tausb = (np.arange( g12b.shape[0]) *timeperframe)[:-200]\n", + " g2b = (get_one_time_from_two_time(g12b))[:-200]\n", + " \n", + " g2b_pds = save_g2_general( g2b, taus=tausb, qr= np.array( list( qval_dict.values() ) )[:g2b.shape[1],0],\n", + " qz=(np.array(list(qval_dict.values()))[:g2b.shape[1],1] if scat_geometry in ('gi_saxs', 'gi_waxs') else None),\n", + " uid=uid_+'_'+q_mask_name+'_g2b.csv', path= data_dir, return_res=True )\n", + "\n", + "_record_xpcs_cell_timing(\"72 - Derive one-time correlation from two-time data\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.336093, + "end_time": "2023-06-20T08:55:45.495206", + "exception": false, + "start_time": "2023-06-20T08:55:45.159113", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Fit derived correlations\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_two_time: \n", + " try: \n", + " g2b_fit_result, tausb_fit, g2b_fit = get_g2_fit_general( g2b, tausb, \n", + " function = fit_g2_func, vlim=[0.95, 1.05], fit_range= None, \n", + " fit_variables={'baseline':False, 'beta': True, 'alpha':True,'relaxation_rate':True}, \n", + " guess_values={'baseline':1.0,'beta': 0.15,'alpha':1.0,'relaxation_rate':1e-3,},\n", + " guess_limits = dict( baseline =[1, 1.8], alpha=[0, 2],\n", + " beta = [0, 1], relaxation_rate= [1e-8, 5000]) ) \n", + " g2b_fit_paras = save_g2_fit_para_tocsv(g2b_fit_result, filename= uid_ +'_'+q_mask_name+'_g2b_fit_paras.csv', path=data_dir )\n", + " g2b_fit_failed = False\n", + " except:\n", + " g2b_fit_failed = True\n", + " from pandas import DataFrame\n", + " g2b_fit_paras = DataFrame(np.zeros([g2b.shape[1], 4]),\n", + " columns=['beta', 'relaxation_rate', 'alpha', 'baseline'])\n", + "\n", + "_record_xpcs_cell_timing(\"73 - Fit derived correlations\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 11.971538, + "end_time": "2023-06-20T08:55:57.468178", + "exception": false, + "start_time": "2023-06-20T08:55:45.496640", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot derived correlation fit\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_two_time:\n", + " if not g2b_fit_failed:\n", + " plot_xpcs_correlation( g2_dict={1:g2b, 2:g2b_fit}, taus_dict={1:tausb, 2:tausb_fit}, vlim=[0.95, 1.05],\n", + " qval_dict=dict(itertools.islice(qval_dict.items(),g2b.shape[1])), fit_res= g2b_fit_result, geometry=scat_geometry_, mode=scat_geometry,filename=uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '_b_fit')\n", + " else:\n", + " plot_xpcs_correlation( g2_dict={1:g2b,}, taus_dict={1:tausb, }, vlim=[0.95, 1.05],\n", + " qval_dict=dict(itertools.islice(qval_dict.items(),g2b.shape[1])), fit_res= None,\n", + " geometry=scat_geometry_, mode=scat_geometry,filename=uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '')\n", + "\n", + "_record_xpcs_cell_timing(\"74 - Plot derived correlation fit\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.054888, + "end_time": "2023-06-20T08:55:57.524735", + "exception": false, + "start_time": "2023-06-20T08:55:57.469847", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Fit derived relaxation rates\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_two_time and not g2b_fit_failed and scat_geometry != 'waxs' and len(qval_dict) >= 2:\n", + " D0b, qrate_fit_resb = get_q_rate_fit_general( dict(itertools.islice(qval_dict.items(),g2b.shape[1])), g2b_fit_paras['relaxation_rate'],\n", + " fit_range=[0, 10], geometry= scat_geometry_ )\n", + "\n", + "_record_xpcs_cell_timing(\"75 - Fit derived relaxation rates\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.245365, + "end_time": "2023-06-20T08:55:57.835965", + "exception": false, + "start_time": "2023-06-20T08:55:57.590600", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Analyze derived relaxation rates\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_two_time and scat_geometry != 'waxs':\n", + " try:\n", + " if True:\n", + " fs, fe = 0, 8\n", + " #fs,fe=0, 6\n", + " qval_dict_ = {k:qval_dict[k] for k in list(qval_dict.keys())[fs:fe] }\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict_, g2b_fit_paras['relaxation_rate'][fs:fe], \n", + " geometry= scat_geometry_ )\n", + " plot_q_rate_fit_general( qval_dict_, g2b_fit_paras['relaxation_rate'][fs:fe], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' , path= data_dir )\n", + " elif False:\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict, g2b_fit_paras['relaxation_rate'],\n", + " fit_range=[0, 26], geometry= scat_geometry_ ) \n", + " plot_q_rate_fit_general( qval_dict, g2_fit_paras['relaxation_rate'], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' ,\n", + " show_fit=False, path= data_dir, plot_all_range=False) \n", + " else:\n", + " ##plot log_q, log_rate\n", + " plot_q_rate_general( qval_dict, g2b_fit_paras['relaxation_rate'], \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' , path= data_dir )\n", + "\n", + " plot_q_g2fitpara_general( qval_dict, g2b_fit_paras, \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' , path= data_dir )\n", + " except:\n", + " pass\n", + "\n", + "if run_two_time and scat_geometry == 'waxs':\n", + " plot_roi_index_rates(g2b_fit_paras['relaxation_rate'], data_dir, uid_+'_two_time')\n", + "\n", + "_record_xpcs_cell_timing(\"76 - Analyze derived relaxation rates\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 10.49927, + "end_time": "2023-06-20T08:56:08.336783", + "exception": false, + "start_time": "2023-06-20T08:55:57.837513", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Compare one- and two-time correlations\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_two_time and run_one_time:\n", + " plot_xpcs_correlation( g2_dict={1:g2, 2:g2b}, taus_dict={1:taus, 2:tausb},vlim=[0.99, 1.007],\n", + " qval_dict=dict(itertools.islice(qval_dict.items(),g2.shape[1])), g2_labels=['from_one_time', 'from_two_time'],\n", + " geometry=scat_geometry_, mode=scat_geometry,filename=uid_+'_g2_two_g2', path= data_dir, ylabel='g2', )\n", + "\n", + "_record_xpcs_cell_timing(\"77 - Compare one- and two-time correlations\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.1e-05, + "end_time": "2023-06-20T08:56:08.338611", + "exception": false, + "start_time": "2023-06-20T08:56:08.338590", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Run Dose dependent analysis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.100158, + "end_time": "2023-06-20T08:56:08.560280", + "exception": false, + "start_time": "2023-06-20T08:56:08.460122", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Run dose-dependent two-time analysis\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_dose:\n", + " get_two_time_mulit_uids( [uid], roi_mask, norm= norm, bin_frame_number=1, \n", + " path= data_dir0, force_generate=False, compress_path = cmp_path + '/' )\n", + "\n", + "_record_xpcs_cell_timing(\"78 - Run dose-dependent two-time analysis\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.085135, + "end_time": "2023-06-20T08:56:08.667038", + "exception": false, + "start_time": "2023-06-20T08:56:08.581903", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Print transmission\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "try:\n", + " print( 'transmission: %s exposure time: %s [s]'%(md['transmission'],exposuretime) )\n", + "except:\n", + " md['transmission'] =1\n", + " print( 'transmission: %s exposure time: %s [s]'%(md['transmission'],exposuretime) )\n", + "\n", + "_record_xpcs_cell_timing(\"79 - Print transmission\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.056217, + "end_time": "2023-06-20T08:56:08.766145", + "exception": false, + "start_time": "2023-06-20T08:56:08.709928", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Print dose\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_dose:\n", + " N = len(imgs)\n", + " print(N)\n", + " #exposure_dose = md['transmission'] * exposuretime* np.int_([ N/16, N/8, N/4 ,N/2, 3*N/4, N*0.99 ])\n", + " exposure_dose = md['transmission'] * exposuretime* np.int_([ N/8, N/4 ,N/2, 3*N/4, N*0.99 ])\n", + " \n", + " print( exposure_dose )\n", + "\n", + "_record_xpcs_cell_timing(\"80 - Print dose\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.056837, + "end_time": "2023-06-20T08:56:08.876104", + "exception": false, + "start_time": "2023-06-20T08:56:08.819267", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate dose-dependent correlations\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_dose:\n", + " taus_uids, g2_uids = get_series_one_time_mulit_uids( [ uid ], qval_dict, good_start=good_start, \n", + " path= data_dir0, exposure_dose = exposure_dose, num_bufs =8, save_g2= False,\n", + " dead_time = 0, trans = [ md['transmission'] ] )\n", + "\n", + "_record_xpcs_cell_timing(\"81 - Calculate dose-dependent correlations\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.084866, + "end_time": "2023-06-20T08:56:09.015565", + "exception": false, + "start_time": "2023-06-20T08:56:08.930699", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot dose-dependent correlations\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_dose: \n", + " plot_dose_g2( taus_uids, g2_uids, ylim=[1.0, 1.2], vshift= 0.00,\n", + " qval_dict = qval_dict, fit_res= None, geometry= scat_geometry_,\n", + " filename= '%s_dose_analysis'%uid_, \n", + " path= data_dir, function= None, ylabel='g2_Dose', g2_labels= None, append_name= '' )\n", + "\n", + "_record_xpcs_cell_timing(\"82 - Plot dose-dependent correlations\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.044648, + "end_time": "2023-06-20T08:56:09.085824", + "exception": false, + "start_time": "2023-06-20T08:56:09.041176", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot selected dose-dependent correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_dose:\n", + " qth_interest = min(5, len(qval_dict))\n", + " plot_dose_g2( taus_uids, g2_uids, qth_interest= qth_interest, ylim=[0.98, 1.4], vshift= 0.00,\n", + " qval_dict = qval_dict, fit_res= None, geometry= scat_geometry_,\n", + " filename= '%s_dose_analysis'%uidstr, \n", + " path= data_dir, function= None, ylabel='g2_Dose', g2_labels= None, append_name= '' )\n", + "\n", + "_record_xpcs_cell_timing(\"83 - Plot selected dose-dependent correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Update two-time progress\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if track_progress:\n", + " if settings_dict_['run_two_time']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='run_two_time', progress='stop',start_time=None, stop_time=time.time(), verbose=True)\n", + " if settings_dict_['xsvs']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='xsvs', progress='start',start_time=time.time(), stop_time=None, verbose=True)\n", + "\n", + "_record_xpcs_cell_timing(\"84 - Update two-time progress\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:09.152401", + "exception": false, + "start_time": "2023-06-20T08:56:09.152376", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Four Time Correlation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.09842, + "end_time": "2023-06-20T08:56:09.356039", + "exception": false, + "start_time": "2023-06-20T08:56:09.257619", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate four-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_four_time:\n", + " g4 = get_four_time_from_two_time(g12b, g2=g2b)[:int(max_taus)]\n", + "\n", + "_record_xpcs_cell_timing(\"85 - Calculate four-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.06727, + "end_time": "2023-06-20T08:56:09.438027", + "exception": false, + "start_time": "2023-06-20T08:56:09.370757", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Save four-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_four_time:\n", + " taus4 = np.arange( g4.shape[0])*timeperframe \n", + " g4_pds = save_g2_general( g4, taus=taus4, qr=np.array( list( qval_dict.values() ) )[:,0],\n", + " qz=None, uid=uid_ +'_g4.csv', path= data_dir, return_res=True )\n", + "\n", + "_record_xpcs_cell_timing(\"86 - Save four-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.074563, + "end_time": "2023-06-20T08:56:09.560723", + "exception": false, + "start_time": "2023-06-20T08:56:09.486160", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot four-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_four_time:\n", + " plot_xpcs_correlation( g2_dict={1:g4}, taus_dict={1:taus4},vlim=[0.95, 1.05], qval_dict=qval_dict, fit_res= None, \n", + " geometry=scat_geometry_, mode=scat_geometry,filename=uid_+'_g4',path= data_dir, ylabel='g4')\n", + "\n", + "_record_xpcs_cell_timing(\"87 - Plot four-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:09.597732", + "exception": false, + "start_time": "2023-06-20T08:56:09.597708", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Speckle Visiblity" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.091965, + "end_time": "2023-06-20T08:56:09.794479", + "exception": false, + "start_time": "2023-06-20T08:56:09.702514", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Prepare XSVS analysis\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_xsvs: \n", + " max_cts = get_max_countc(FD, roi_mask ) \n", + " #max_cts = 15 #for eiger 500 K\n", + " qind, pixelist = roi.extract_label_indices( roi_mask )\n", + " noqs = len( np.unique(qind) )\n", + " nopr = np.bincount(qind, minlength=(noqs+1))[1:]\n", + " #time_steps = np.array( utils.geometric_series(2, len(imgs) ) )\n", + " time_steps = [0,1] #only run the first two levels\n", + " num_times = len(time_steps) \n", + " times_xsvs = exposuretime + (2**( np.arange( len(time_steps) ) ) -1 ) * timeperframe \n", + " print( 'The max counts are: %s'%max_cts )\n", + "\n", + "_record_xpcs_cell_timing(\"88 - Prepare XSVS analysis\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:09.814905", + "exception": false, + "start_time": "2023-06-20T08:56:09.814881", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Do histogram " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.072564, + "end_time": "2023-06-20T08:56:09.992027", + "exception": false, + "start_time": "2023-06-20T08:56:09.919463", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate XSVS histograms\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_xsvs:\n", + " if roi_avg is None:\n", + " times_roi, mean_int_sets = cal_each_ring_mean_intensityc(FD, roi_mask, timeperframe = None, ) \n", + " roi_avg = np.average( mean_int_sets, axis=0)\n", + " \n", + " spec_bins, spec_his, spec_std, spec_sum = xsvsp( FD, np.int_(roi_mask), norm=None,\n", + " max_cts=int(max_cts+2), bad_images=bad_frame_list, only_two_levels=True ) \n", + " spec_kmean = np.array( [roi_avg * 2**j for j in range( spec_his.shape[0] )] )\n", + " spec_pds = save_bin_his_std( spec_bins, spec_his, spec_std, filename=uid_+'_spec_res.csv', path=data_dir )\n", + "\n", + "_record_xpcs_cell_timing(\"89 - Calculate XSVS histograms\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:10.031751", + "exception": false, + "start_time": "2023-06-20T08:56:10.031727", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Do historam fit by negtive binominal function with maximum likehood method" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.080963, + "end_time": "2023-06-20T08:56:10.222574", + "exception": false, + "start_time": "2023-06-20T08:56:10.141611", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Fit XSVS histograms\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_xsvs: \n", + " ML_val, KL_val,K_ = get_xsvs_fit( spec_his, spec_sum, spec_kmean, \n", + " spec_std, max_bins=2, fit_range=[1,60], varyK= False )\n", + " #print( 'The observed average photon counts are: %s'%np.round(K_mean,4))\n", + " #print( 'The fitted average photon counts are: %s'%np.round(K_,4)) \n", + " print( 'The difference sum of average photon counts between fit and data are: %s'%np.round( \n", + " abs(np.sum( spec_kmean[0,:] - K_ )),4))\n", + " print( '#'*30)\n", + " qth= 0 \n", + " print( 'The fitted M for Qth= %s are: %s'%(qth, ML_val[qth]) )\n", + " print( K_[qth])\n", + " print( '#'*30)\n", + "\n", + "_record_xpcs_cell_timing(\"90 - Fit XSVS histograms\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:10.255723", + "exception": false, + "start_time": "2023-06-20T08:56:10.255699", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Plot fit results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.045892, + "end_time": "2023-06-20T08:56:10.408180", + "exception": false, + "start_time": "2023-06-20T08:56:10.362288", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot XSVS fits\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_xsvs: \n", + " qr = [qval_dict[k][0] for k in list(qval_dict.keys()) ]\n", + " plot_xsvs_fit( spec_his, ML_val, KL_val, K_mean = spec_kmean, spec_std=spec_std,\n", + " xlim = [0,10], vlim =[.9, 1.1],\n", + " uid=uid_, qth= qth_interest, logy= True, times= times_xsvs, q_ring_center=qr, path=data_dir)\n", + " \n", + " plot_xsvs_fit( spec_his, ML_val, KL_val, K_mean = spec_kmean, spec_std = spec_std,\n", + " xlim = [0,15], vlim =[.9, 1.1],\n", + " uid=uid_, qth= None, logy= True, times= times_xsvs, q_ring_center=qr, path=data_dir )\n", + "\n", + "_record_xpcs_cell_timing(\"91 - Plot XSVS fits\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.6e-05, + "end_time": "2023-06-20T08:56:10.476055", + "exception": false, + "start_time": "2023-06-20T08:56:10.476029", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Get contrast" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.099953, + "end_time": "2023-06-20T08:56:10.680532", + "exception": false, + "start_time": "2023-06-20T08:56:10.580579", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate XSVS contrast\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_xsvs:\n", + " contrast_factorL = get_contrast( ML_val)\n", + " spec_km_pds = save_KM( spec_kmean, KL_val, ML_val, qs=qr, level_time=times_xsvs, uid=uid_, path = data_dir )\n", + " #spec_km_pds\n", + "\n", + "_record_xpcs_cell_timing(\"92 - Calculate XSVS contrast\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:10.698770", + "exception": false, + "start_time": "2023-06-20T08:56:10.698745", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Plot contrast with g2 results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.096136, + "end_time": "2023-06-20T08:56:10.905433", + "exception": false, + "start_time": "2023-06-20T08:56:10.809297", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Compare XSVS contrast and correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_xsvs: \n", + " plot_g2_contrast( contrast_factorL, g2b, times_xsvs, tausb, qr, \n", + " vlim=[0.8,1.2], qth = qth_interest, uid=uid_,path = data_dir, legend_size=14)\n", + "\n", + " plot_g2_contrast( contrast_factorL, g2b, times_xsvs, tausb, qr, \n", + " vlim=[0.8,1.2], qth = None, uid=uid_,path = data_dir, legend_size=4)\n", + "\n", + "_record_xpcs_cell_timing(\"93 - Compare XSVS contrast and correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Update XSVS progress\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if track_progress:\n", + " if settings_dict_['xsvs']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='xsvs', progress='stop',start_time=None, stop_time=time.time(), verbose=True)\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='save data and report', progress='start',start_time=time.time(), stop_time=None, verbose=True)\n", + "\n", + "_record_xpcs_cell_timing(\"94 - Update XSVS progress\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:10.922696", + "exception": false, + "start_time": "2023-06-20T08:56:10.922672", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Export Results to a HDF5 File" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 2.206983, + "end_time": "2023-06-20T08:56:13.236872", + "exception": false, + "start_time": "2023-06-20T08:56:11.029889", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Assemble and save result metadata\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "md['hostname'] = hostname[0]\n", + "md['kernel'] = kernel\n", + "md['detector_mask_file']=detector_mask_path+detector_mask_filename\n", + "md['det_mask_dict'] = det_mask_dict\n", + "md['polygon_mask']= polygon_dict\n", + "md['roi_mask_file']= fp\n", + "md['roi_source'] = roi_input_source\n", + "md['mask_source'] = mask_input_source\n", + "md['beam_mask_source'] = beam_mask_source\n", + "md['mask_file'] = mask_input_source\n", + "md['dynamic_mask_applied'] = dynamic_mask_applied\n", + "md['scat_geometry'] = scat_geometry\n", + "if scat_geometry in ('gi_saxs', 'gi_waxs'):\n", + " md['surface_geometry'] = {\n", + " 'incident_angle_deg': surface_maps['incident_angle_deg'],\n", + " 'inplane_angle_deg': surface_maps['inplane_angle_deg'],\n", + " 'incident_center': surface_maps['incident_center'],\n", + " 'reflected_center': surface_maps['reflected_center'],\n", + " 'q_parallel_edges': surface_rois['parallel_edges'],\n", + " 'q_z_edges': surface_rois['z_edges'],\n", + " }\n", + " md['surface_reflected_center_x'] = refl_x0\n", + " md['surface_reflected_center_y'] = refl_y0\n", + "md['mask'] = mask\n", + "#md['NOTEBOOK_FULL_PATH'] = data_dir + get_current_pipeline_fullpath(NFP).split('/')[-1]\n", + "md['good_start'] = good_start\n", + "md['bad_frame_list'] = bad_frame_list\n", + "md['avg_img'] = avg_img\n", + "md['roi_mask'] = roi_mask\n", + "md['mask_outliers'] = mask_outliers\n", + "if mask_outliers:\n", + " md['outlier_threshold'] = outlier_threshold\n", + " md['maximum_outlier_fraction'] = maximum_outlier_fraction\n", + "md['setup_pargs'] = setup_pargs\n", + "if scat_geometry == 'gi_saxs': \n", + " md['Qr'] = Qr\n", + " md['Qz'] = Qz\n", + " md['qval_dict'] = qval_dict\n", + " md['beam_center_x'] = inc_x0\n", + " md['beam_center_y']= inc_y0\n", + " md['beam_refl_center_x'] = refl_x0\n", + " md['beam_refl_center_y'] = refl_y0\n", + "\n", + "\n", + "elif scat_geometry == 'gi_waxs':\n", + " md['qval_dict'] = qval_dict\n", + " md['beam_center_x'] = inc_x0\n", + " md['beam_center_y'] = inc_y0\n", + " md['beam_refl_center_x'] = refl_x0\n", + " md['beam_refl_center_y'] = refl_y0\n", + "elif scat_geometry == 'waxs':\n", + " md['qval_dict'] = qval_dict\n", + " md['beam_center_x'] = inc_x0\n", + " md['beam_center_y'] = inc_y0\n", + "else:\n", + " md['qr']= qr\n", + " #md['qr_edge'] = qr_edge\n", + " md['qval_dict'] = qval_dict\n", + " md['beam_center_x'] = center[1]\n", + " md['beam_center_y']= center[0] \n", + "\n", + "md['beg'] = FD.beg\n", + "md['end'] = FD.end\n", + "md['qth_interest'] = qth_interest\n", + "md['metadata_file'] = data_dir + 'uid=%s_md.pkl'%uid\n", + "\n", + "md['beg_OneTime'] = good_start_g2\n", + "md['end_OneTime'] = good_end_g2\n", + "\n", + "psave_obj( md, data_dir + 'uid=%s_md.pkl'%uid ) #save the setup parameters\n", + "save_dict_csv( md, data_dir + 'uid=%s_md.csv'%uid, 'w')\n", + "\n", + "Exdt = {} \n", + "if scat_geometry == 'gi_saxs': \n", + " for k,v in zip( ['md', 'roi_mask','qval_dict','avg_img','mask','pixel_mask', 'imgsum', 'bad_frame_list', 'qr_1d_pds'], \n", + " [md, roi_mask, qval_dict, avg_img,mask,pixel_mask, imgsum, bad_frame_list, qr_1d_pds] ):\n", + " Exdt[ k ] = v\n", + "elif scat_geometry == 'saxs': \n", + " for k,v in zip( ['md', 'q_saxs', 'iq_saxs','iqst','qt','roi_mask','qval_dict','avg_img','mask','pixel_mask', 'imgsum', 'bad_frame_list'], \n", + " [md, q_saxs, iq_saxs, iqst, qt,roi_mask, qval_dict, avg_img,mask,pixel_mask, imgsum, bad_frame_list] ):\n", + " Exdt[ k ] = v\n", + "elif scat_geometry in ('gi_waxs', 'waxs'): \n", + " for k,v in zip( ['md', 'roi_mask','qval_dict','avg_img','mask','pixel_mask', 'imgsum', 'bad_frame_list'], \n", + " [md, roi_mask, qval_dict, avg_img,mask,pixel_mask, imgsum, bad_frame_list] ):\n", + " Exdt[ k ] = v\n", + " \n", + "if scat_geometry in ('gi_saxs', 'gi_waxs'):\n", + " Exdt['q_parallel_edges'] = surface_rois['parallel_edges']\n", + " Exdt['q_z_edges'] = surface_rois['z_edges']\n", + "if run_waterfall:Exdt['wat'] = wat\n", + "if run_t_ROI_Inten:Exdt['times_roi'] = times_roi;Exdt['mean_int_sets']=mean_int_sets\n", + "if run_one_time:\n", + " if run_invariant_analysis:\n", + " for k,v in zip( ['taus','g2','g2_fit_paras', 'time_stamp','invariant'], [taus,g2,g2_fit_paras,time_stamp,invariant] ):Exdt[ k ] = v\n", + " else:\n", + " for k,v in zip( ['taus','g2','g2_fit_paras' ], [taus,g2,g2_fit_paras ] ):Exdt[ k ] = v\n", + " \n", + "if run_two_time:\n", + " for k,v in zip( ['tausb','g2b','g2b_fit_paras', 'g12b'], [tausb,g2b,g2b_fit_paras,g12b] ):Exdt[ k ] = v\n", + " #for k,v in zip( ['tausb','g2b','g2b_fit_paras', ], [tausb,g2b,g2b_fit_paras] ):Exdt[ k ] = v \n", + "if run_dose:\n", + " for k,v in zip( [ 'taus_uids', 'g2_uids' ], [taus_uids, g2_uids] ):Exdt[ k ] = v\n", + "if run_four_time:\n", + " for k,v in zip( ['taus4','g4'], [taus4,g4] ):Exdt[ k ] = v\n", + "if run_xsvs:\n", + " for k,v in zip( ['spec_kmean','spec_pds','times_xsvs','spec_km_pds','contrast_factorL'], \n", + " [ spec_kmean,spec_pds,times_xsvs,spec_km_pds,contrast_factorL] ):Exdt[ k ] = v\n", + "\n", + "_record_xpcs_cell_timing(\"95 - Assemble and save result metadata\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.24575, + "end_time": "2023-06-20T08:56:13.485609", + "exception": false, + "start_time": "2023-06-20T08:56:13.239859", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Export HDF5 results\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "#export_xpcs_results_to_h5( 'uid=%s_%s_Res%s.h5'%(md['uid'],q_mask_name,hdf5_name_extension), data_dir, export_dict = Exdt )\n", + "export_xpcs_results_to_h5( 'uid=%s_%s%s_Res.h5'%(md['uid'],q_mask_name,hdf5_name_extension), data_dir, export_dict = Exdt )\n", + "\n", + "_record_xpcs_cell_timing(\"96 - Export HDF5 results\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.072672, + "end_time": "2023-06-20T08:56:13.561092", + "exception": false, + "start_time": "2023-06-20T08:56:13.488420", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Append result path to user list\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "try:\n", + " from pyCHX.chx_generic_functions import append_txtfile\n", + " outp = default_dir+'%s/%s/'%(md['cycle'],username)\n", + " append_txtfile( filename = outp + username + '.lst', \n", + " data = np.array( [ outp + 'Results/' + md['uid'] + '/uid=%s__Res.h5'%md['uid']]))\n", + "except:\n", + " print('ERROR: unable to append output textfile for this uid.')\n", + "\n", + "_record_xpcs_cell_timing(\"97 - Append result path to user list\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:13.616508", + "exception": false, + "start_time": "2023-06-20T08:56:13.616483", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Create a PDF Report" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.069555, + "end_time": "2023-06-20T08:56:13.800176", + "exception": false, + "start_time": "2023-06-20T08:56:13.730621", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Determine PDF report name\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "pdf_out_dir = data_dir0\n", + "\n", + "pdf_filename = \"XPCS_Analysis_Report2_for_uid=%s%s%s.pdf\"%(uid,pdf_version,q_mask_name)\n", + "if run_xsvs:\n", + " pdf_filename = \"XPCS_XSVS_Analysis_Report_for_uid=%s%s%s.pdf\"%(uid,pdf_version,q_mask_name)\n", + "\n", + "_record_xpcs_cell_timing(\"98 - Determine PDF report name\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.555317, + "end_time": "2023-06-20T08:56:14.398855", + "exception": false, + "start_time": "2023-06-20T08:56:13.843538", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Create PDF report\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "# cheating here a little: the function argument 'False' hardcodes the absence of the form factor fit\n", + "make_pdf_report( data_dir, uid, pdf_out_dir, pdf_filename, username, \n", + " False,run_one_time, run_two_time, run_four_time, run_xsvs, run_dose,\n", + " report_type= ('gi_waxs' if scat_geometry == 'waxs' else scat_geometry), report_invariant= run_invariant_analysis,\n", + " md = md )\n", + "\n", + "_record_xpcs_cell_timing(\"99 - Create PDF report\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Finish report progress tracking\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if track_progress:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='save data and report', progress='stop',start_time=None, stop_time=time.time(), verbose=True)\n", + "\n", + "_record_xpcs_cell_timing(\"100 - Finish report progress tracking\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:56:14.401737", + "exception": false, + "start_time": "2023-06-20T08:56:14.401715", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Attach the PDF report to Olog " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 9.582586, + "end_time": "2023-06-20T08:56:24.099192", + "exception": false, + "start_time": "2023-06-20T08:56:14.516606", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Attach PDF report to Olog\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if att_pdf_report and enable_olog_attachments:\n", + " lops=0\n", + " while lops<5:\n", + " try:\n", + " update_olog_uid_with_file( uid[:6], text='Add XPCS Analysis PDF Report', \n", + " filename=pdf_out_dir + pdf_filename, append_name='_R1' )\n", + " lops=5\n", + " except:\n", + " print(\"Failed to attach PDF report to Olog...try again in 10s\")\n", + " time.sleep(10)\n", + " lops+=1\n", + " if lops == 5:\n", + " print(\"Failed final attempt to attach PDF to Olog!\")\n", + "if not enable_olog_attachments:\n", + " print('Olog attachments are NOT possible as this notebook (or the papermill that is calling it) is NOT running on saturn4.\\nConnection to Olog is blocked by firewall, so we are not going to waste time trying.')\n", + "\n", + "_record_xpcs_cell_timing(\"101 - Attach PDF report to Olog\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:24.102253", + "exception": false, + "start_time": "2023-06-20T08:56:24.102228", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Save the OAV images" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.048241, + "end_time": "2023-06-20T08:56:24.267903", + "exception": false, + "start_time": "2023-06-20T08:56:24.219662", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Attach OAV images to Olog\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if save_oavs:\n", + " try:\n", + " #os.environ['HTTPS_PROXY'] = 'https://proxy:8888'\n", + " #os.environ['no_proxy'] = 'cs.nsls2.local,localhost,127.0.0.1'\n", + " update_olog_uid_with_file( uid[:6], text='Add OVA images', \n", + " filename= data_dir + 'uid=%s_OVA_images.png'%uid, append_name='_img' )\n", + " except:\n", + " print('failed to update Olog with OAV images')\n", + "\n", + "_record_xpcs_cell_timing(\"102 - Attach OAV images to Olog\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:28.531315", + "exception": false, + "start_time": "2023-06-20T08:56:28.531290", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# The End!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Prepare timing report\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "_xpcs_timing_report_heading = \"XPCS NOTEBOOK CELL TIMING REPORT\"\n", + "_record_xpcs_cell_timing(\"103 - Prepare timing report\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Complete and print timing report\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "_record_xpcs_cell_timing(\"104 - Complete and print timing report\", _xpcs_cell_start)\n", + "_xpcs_notebook_elapsed = time.time() - _xpcs_notebook_start\n", + "_xpcs_timed_total = sum(xpcs_cell_timings.values())\n", + "\n", + "print(\"\\n\" + \"=\" * 80)\n", + "print(_xpcs_timing_report_heading)\n", + "print(\"=\" * 80)\n", + "for _xpcs_label, _xpcs_elapsed in xpcs_cell_timings.items():\n", + " print(f\"{_xpcs_label:<65} {_xpcs_elapsed:>10.2f} s\")\n", + "print(\"-\" * 80)\n", + "print(f\"{'Timed cells total':<65} {_xpcs_timed_total:>10.2f} s\")\n", + "print(f\"{'Notebook wall time':<65} {_xpcs_notebook_elapsed:>10.2f} s\")\n", + "print(\"=\" * 80)\n" + ] + } + ], + "metadata": { + "celltoolbar": "Tags", + "kernelspec": { + "display_name": "Python 3 (current)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.14" + }, + "papermill": { + "duration": 202.500649, + "end_time": "2023-06-20T08:56:29.773278", + "environment_variables": {}, + "exception": false, + "output_path": "/nsls2/data/chx/legacy/analysis/2023_2/petrash/ResPipelines/XPCS_SAXS_2023_auto_test_v0_09f3d800-0018-4ee8-8fb3-4bb082ec26db.ipynb", + "parameters": { + "cycle": "2023_2", + "run_dose": false, + "run_two_time": true, + "uid": "09f3d800-0018-4ee8-8fb3-4bb082ec26db", + "username": "petrash" + }, + "start_time": "2023-06-20T08:53:07.272629", + "version": "0.15.0" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/pipelines/beam_center_position_issue.md b/pipelines/beam_center_position_issue.md new file mode 100644 index 0000000..b1646b2 --- /dev/null +++ b/pipelines/beam_center_position_issue.md @@ -0,0 +1,12 @@ +# Beam-center position issue + +The [acquisition center finder](https://github.com/NSLS2/chx-profile-collection/blob/670a10be52a0db75f090087f6c466eabe48aaf16/startup/30-user.py#L74) writes zero-based raw pixel coordinates to BeamX/BeamY. `load_data` flips detector rows and, for Eiger 500K, then applies `np.rot90`. For raw `(x, y)` and raw shape `(H, W)`, the matching analysis pixel is: + +| Detector | Correct analysis `(x, y)` | Current pipeline | Offset | +| --- | --- | --- | --- | +| Eiger 4M/1M | `(x, H-1-y)` | `(x, H-y)` | `+1` row | +| Eiger 500K | `(H-1-y, W-1-x)` | `(H-y, W-x)` | `+1` on both axes | + +The same conversion appears in the SAXS mask and ROI notebooks. It can shift beam masks, ROIs, and calibrated q maps. Separately, the unified pipeline writes SAXS result metadata with `beam_center_x` and `beam_center_y` swapped. + +**Check before changing historical results:** compare a direct-beam pixel in a raw frame, its BeamX/BeamY values, and its location in the oriented analysis image for each detector. The automatic finder is zero-based; manually entered centers may have a different convention. See [coordinate conventions](pipelines/COORDINATE_CONVENTIONS.md) for the full trace. diff --git a/pipelines/masking_and_rois/Auto_Mask_SAXS.ipynb b/pipelines/masking_and_rois/Auto_Mask_SAXS.ipynb new file mode 100644 index 0000000..cede379 --- /dev/null +++ b/pipelines/masking_and_rois/Auto_Mask_SAXS.ipynb @@ -0,0 +1,862 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Masking Pipeline" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## CHX Olog Logbook\n", + "CHX Olog (https://logbook.nsls2.bnl.gov/11-ID/) [requires VPN from offsite]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[32mrunning on: jupyter_hub environment: standard\n", + "\u001b[0m\n", + "\u001b[36msetting '_base_path_' as /nsls2/data/chx/legacy/analysis/\u001b[0m\n", + "\u001b[36msetting '_base_path_pass_' as /nsls2/data/chx/proposals/\u001b[0m\n", + "\u001b[36msetting '_mask_path_' as /nsls2/data/chx/shared/CHX_Setup/Detector_masks/\n", + "\u001b[0m\n", + "\u001b[32mRe-imported pyCHX from /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/\u001b[0m\n", + "\u001b[32mRe-imported chx_compress from /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/chx_compress.py\u001b[0m\n", + "\u001b[32mRe-imported chx_olog functions from /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/chx_olog.py\u001b[0m\n", + "\u001b[35m\n", + "environment dependent settings and patches:\u001b[0m\n", + "using \"%matplotlib inline\" for plotting\n", + "\u001b[36m--> overwrote '_base_path_' as /nsls2/data/chx/proposals/\u001b[0m\n" + ] + } + ], + "source": [ + "from pyCHX.chx_packages import *\n", + "%matplotlib notebook\n", + "plt.rcParams.update({'figure.max_open_warning': 0})\n", + "plt.rcParams.update({ 'image.origin': 'lower' })\n", + "plt.rcParams.update({ 'image.interpolation': 'none' })\n", + "import pickle as cpk\n", + "from pyCHX.chx_xpcs_xsvs_jupyter_V1 import *\n", + "from pyCHX.chx_generic_functions import RemoveHot,create_multi_rotated_rectangle_mask\n", + "import json\n", + "\n", + "%run /nsls2/data/chx/shared/CHX_Software/packages/environment_management/chx_analysis_setup_test_pyCHX.ipynb\n", + "_base_path_ = _base_path_pass_\n", + "print(colored(\"--> overwrote '_base_path_' as %s\"%_base_path_,'cyan'))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Path for Saving Results" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Select the image series to create a mask" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "uid = '9d074654' #(scan num: 141284) (Measurement: single image for mask )" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "md = get_meta_data( uid )\n", + "cycle= md['cycle'] \n", + "username = md['user']\n", + "\n", + "## Can overwrite user and cycle below, if the metadata is not correct:\n", + "# cycle = ''\n", + "# user = ''" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The mask will be saved in : /nsls2/data/chx/legacy/analysis//2023_3/CHX staff/masks/\n", + "looking for detector mask in /nsls2/data/chx/shared/CHX_Setup/Detector_masks/pixel_masks/\n" + ] + } + ], + "source": [ + "path = '%s/%s/%s/masks/'%(_base_path_,cycle,username)\n", + "print (\"The mask will be saved in : %s\"%path)\n", + "det_mask_path = _mask_path_+'pixel_masks/' #'%s/masks/'%(_base_path_)\n", + "print('looking for detector mask in %s'%det_mask_path)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Detector is: eiger4m_single_image\n" + ] + }, + { + "ename": "KeyError", + "evalue": "'data path'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[5], line 3\u001b[0m\n\u001b[1;32m 1\u001b[0m detector \u001b[38;5;241m=\u001b[39m get_detector( db[uid ] )\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28mprint\u001b[39m (\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mDetector is: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m%\u001b[39mdetector )\n\u001b[0;32m----> 3\u001b[0m sud \u001b[38;5;241m=\u001b[39m \u001b[43mget_sid_filenames\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdb\u001b[49m\u001b[43m[\u001b[49m\u001b[43muid\u001b[49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 4\u001b[0m \u001b[38;5;28mprint\u001b[39m (\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mscan_id, full-uid, data path are: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m--\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m--\u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m%\u001b[39m(sud[\u001b[38;5;241m0\u001b[39m], sud[\u001b[38;5;241m1\u001b[39m], sud[\u001b[38;5;241m2\u001b[39m][\u001b[38;5;241m0\u001b[39m] ))\n\u001b[1;32m 6\u001b[0m \u001b[38;5;66;03m## image rotations from analysis pipeline:\u001b[39;00m\n", + "File \u001b[0;32m/nsls2/data/chx/shared/CHX_Software/packages/pyCHX/chx_generic_functions.py:3461\u001b[0m, in \u001b[0;36mget_sid_filenames\u001b[0;34m(hdr, verbose)\u001b[0m\n\u001b[1;32m 3455\u001b[0m stop_doc \u001b[38;5;241m=\u001b[39m hdr\u001b[38;5;241m.\u001b[39mstop\n\u001b[1;32m 3456\u001b[0m success \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m 3458\u001b[0m ret \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m 3459\u001b[0m start_doc[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mscan_id\u001b[39m\u001b[38;5;124m\"\u001b[39m],\n\u001b[1;32m 3460\u001b[0m start_doc[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124muid\u001b[39m\u001b[38;5;124m\"\u001b[39m],\n\u001b[0;32m-> 3461\u001b[0m glob\u001b[38;5;241m.\u001b[39mglob(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[43mstart_doc\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mdata path\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m*_\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mstart_doc[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124msequence id\u001b[39m\u001b[38;5;124m'\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m_master.h5\u001b[39m\u001b[38;5;124m\"\u001b[39m),\n\u001b[1;32m 3462\u001b[0m ) \u001b[38;5;66;03m# looking for (eiger) datafile at the path specified in metadata\u001b[39;00m\n\u001b[1;32m 3463\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(ret[\u001b[38;5;241m2\u001b[39m]) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m 3464\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m verbose:\n", + "\u001b[0;31mKeyError\u001b[0m: 'data path'" + ] + } + ], + "source": [ + "detector = get_detector( db[uid ] )\n", + "print ('Detector is: %s'%detector )\n", + "sud = get_sid_filenames(db[uid])\n", + "print ('scan_id, full-uid, data path are: %s--%s--%s'%(sud[0], sud[1], sud[2][0] ))\n", + "\n", + "## image rotations from analysis pipeline:\n", + "if md['detector'] =='eiger4m_single_image' or md['detector'] == 'image': \n", + " reverse= True\n", + " rot90= False\n", + "elif md['detector'] =='eiger500K_single_image': \n", + " reverse= True\n", + " rot90=True\n", + "elif md['detector'] =='eiger1m_single_image': \n", + " reverse= True\n", + " rot90=False\n", + "print('detector: %s -> Image reverse: %s, Image rotate 90: %s'%(md['detector'].split('_')[0],reverse, rot90))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "imgs = load_data( uid, detector, reverse= reverse, rot90=rot90 )\n", + "md.update( imgs.md );Nimg = len(imgs);\n", + "md['number of images'] = Nimg\n", + "pixel_mask=np.ones( np.shape(imgs[0]))\n", + "print( 'The data are: %s' %imgs )\n", + "print(md['beam_center_x'],md['beam_center_y'])\n", + "if reverse and not rot90:\n", + " md['beam_center_y']=np.shape(imgs[0])[0]- md['beam_center_y']\n", + " print(md['beam_center_y'])\n", + "if reverse and rot90:\n", + " xc=md['beam_center_y'];yc=md['beam_center_x']\n", + " yc=np.shape(imgs[0])[0]-yc\n", + " xc=np.shape(imgs[0])[1]-xc\n", + " print(xc,yc)\n", + " md['beam_center_y']=yc;md['beam_center_x']=xc\n", + "if rot90 and not reverse:\n", + " raise Exception('ERROR: somebody still needs to figure out the transformation for reverse=%s and rot90=%s!'%(reverse,rot90))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Get the detector mask created by Detector_masks....ipynb" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "detector_ = md['detector'].split('_')[0];det_mask_file = det_mask_path+'detector_mask_%s.json'%detector_\n", + "try: \n", + " json_open=open(det_mask_file)\n", + " det_mask_dict=json.load(json_open)\n", + " det_mask_dict.keys()\n", + " print('loading detector mask: '+det_mask_file)\n", + "except:\n", + " raise Exception('ERROR: detector mask file %s not found!'%det_mask_file)\n", + "fig,ax = plt.subplots(1,4,figsize=(20,5))\n", + "plt.suptitle('detector: %s detector mask file: %s'%(detector_,det_mask_file))\n", + "\n", + "for kk,k in enumerate(list(det_mask_dict['masks'].keys())):\n", + " plt.subplot(1,4,kk+1)\n", + " plt.title(k)\n", + " plt.imshow( det_mask_dict['masks'][k])\n", + " pixel_mask*=det_mask_dict['masks'][k]\n", + "plt.subplot(1,4,4)\n", + "plt.title('combined')\n", + "plt.imshow(pixel_mask)\n", + "masked=np.nonzero(np.array(pixel_mask)+~np.array(det_mask_dict['masks']['chip_mask'])<1)\n", + "#cmap = plt.cm.get_cmap('viridis')\n", + "cmap=plt.colormaps['viridis']\n", + "plt.plot(masked[1],masked[0],'+',color=cmap(0))\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### show image and the combined detector mask" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "img_choice_N = 1 #can change this number to select more frames for average\n", + "img_samp_index = random.sample( range(len(imgs)), img_choice_N) \n", + "avg_img = get_avg_img( imgs, img_samp_index, plot_ = False, uid = uid)\n", + "show_img( avg_img*pixel_mask , vmin=.01, vmax=1e3, logs=True,\n", + " image_name ='uid=%s'%uid, aspect=1, cmap= cmap_albula )\n", + "plt.plot(md['beam_center_x'],md['beam_center_y'],'bo')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Create polygon masks -> these are masked regions like the beamstop that should be 'attached' to the direct beam position\n", + "## polygon mask is NOT depending on the detector (Eiger4M or Eiger500k)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "polygon_dict = {'uid':md['uid'],'masks':{}} # start dictionary to collect all information to create polygon mask" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Create a rotated region" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "if False:\n", + " length=[2000,2000];width=[10,20];angles=[10,60] \n", + " \n", + " if len(length) ==1 and len(angles)>1: # multiple angles, all masks with same length\n", + " length=list(np.ones(len(angles))*length)\n", + " if len(width) ==1 and len(angles)>1: # multiple angles, all masks with same width\n", + " width=list(np.ones(len(angles))*width)\n", + " print('agnles: %s\\nlengths: %s\\nwidths: %s'%(angles,length, width))\n", + " polygon_dict['masks']['rmask']={'length':length,'width':width,'angles':angles}\n", + "\n", + " rmask_dict={}\n", + " for aa,a in enumerate(angles):\n", + " rmask_dict[a] = create_multi_rotated_rectangle_mask( imgs[0], \n", + " center= [ md['beam_center_x'], md['beam_center_y'] ], length=length[aa], width=width[aa], angles=[a] )\n", + "\n", + " for aa,a in enumerate(list(rmask_dict.keys())):\n", + " if aa == 0:\n", + " rmask = rmask_dict[a]\n", + " else:\n", + " rmask*=rmask_dict[a]\n", + " show_img(avg_img*pixel_mask*rmask,vmin=0.1e-0,vmax=1e4, logs=True, \n", + " image_name= 'uid= %s with pixel mask'%uid , aspect=1, cmap= cmap_albula )" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### To create multi-rectangle masks, for each sub-mask\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "#### create the right part mask\n", + "\n", + "if '4m' in md['detector']:\n", + " partial_mask = create_cross_mask( avg_img, center=[md['beam_center_x']- 100, md['beam_center_y']+50 ], #center=[509,185],\n", + " wy_left= 0, wy_right= 60, \n", + " wx_up= 0, wx_down= 0,center_radius= 0 )\n", + " ##for GiSAXS\n", + " #partial_mask = create_cross_mask( avg_img, center=[md['beam_center_x']- 200, \n", + " # md['beam_center_y'] ], #center=[509,185],\n", + " # wy_left= 0, wy_right= 79, \n", + " # wx_up= 0, wx_down= 0,center_radius= 0 ) \n", + " \n", + "elif '500K' in md['detector']:\n", + " partial_mask = create_cross_mask( avg_img, center=[md['beam_center_x']+60 , md['beam_center_y']+50 ], #center=[509,185],\n", + " wy_left= 0, wy_right= 0, \n", + " wx_up= 0, wx_down= 35,center_radius= 0 )\n", + "else:\n", + " print('Please check the detectors.')\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "if True:\n", + " x_off = [0,-80]\n", + " y_off = [0,0]\n", + " wy_left = [20,0]\n", + " wy_right = [10,30]\n", + " wx_up = [10,0]\n", + " wx_down = [10,0]\n", + " center_radius = [0,0]\n", + "\n", + " polygon_dict['masks']['partial_mask']={'x_off':x_off,'y_off':y_off,'wy_left':wy_left,'wy_right':wy_right,'wx_up':wx_up,'wx_down':wx_down,'center_radius':center_radius}\n", + " partialmask_dict={}\n", + " for ii,i in enumerate(range(len(x_off))[:]): # [:] use all elements in list; [:2] use the first two elements in list, etc. to create masks\n", + " partialmask_dict[ii] = create_cross_mask( avg_img,center= [ md['beam_center_x']+x_off[i], md['beam_center_y']+y_off[i] ], \n", + " wy_left= wy_left[i], wy_right= wy_right[i], \n", + " wx_up= wx_up[i], wx_down= wx_down[i],center_radius= center_radius[i])\n", + " \n", + " for ii,i in enumerate(list(partialmask_dict.keys())):\n", + " if ii == 0:\n", + " partial_mask = partialmask_dict[i]\n", + " else:\n", + " partial_mask*=partialmask_dict[i]\n", + " show_img( partial_mask, show_colorbar=False )\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### create a circular mask for windows" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "if False:\n", + " center_radius=980\n", + " window_shadow = ~create_cross_mask( avg_img, center=[md['beam_center_x'],md['beam_center_y']],\n", + " wy_left= 0, wy_right= 0, \n", + " wx_up= 0, wx_down= 0,center_disk=True, center_radius= center_radius)\n", + " polygon_dict['masks']['window_mask']={'center_radius':center_radius}\n", + "else:\n", + " try:\n", + " polygon_dict['masks'].pop('window_mask')\n", + " except: pass" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Test: re-create multi-polygon mask:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "polygon_mask=np.ones_like( pixel_mask , dtype = bool)\n", + "if 'rmask' in list(polygon_dict['masks'].keys()):\n", + " rmask_dict={}\n", + " for aa,a in enumerate(polygon_dict['masks']['rmask']['angles']):\n", + " rmask_dict[a] = create_multi_rotated_rectangle_mask( pixel_mask, \n", + " center= [ md['beam_center_x'], md['beam_center_y'] ], length=polygon_dict['masks']['rmask']['length'][aa], width=polygon_dict['masks']['rmask']['width'][aa], angles=[a] )\n", + "\n", + " for aa,a in enumerate(list(rmask_dict.keys())):\n", + " if aa == 0:\n", + " rmask = rmask_dict[a]\n", + " else:\n", + " rmask*=rmask_dict[a]\n", + " polygon_mask*=rmask\n", + "if 'partial_mask' in list(polygon_dict['masks'].keys()):\n", + " partialmask_dict={}\n", + " for ii,i in enumerate(range(len(polygon_dict['masks']['partial_mask']['x_off']))[:]): # [:] use all elements in list; [:2] use the first two elements in list, etc. to create masks\n", + " partialmask_dict[ii] = create_cross_mask( pixel_mask,center= [ md['beam_center_x']+polygon_dict['masks']['partial_mask']['x_off'][i], md['beam_center_y']+polygon_dict['masks']['partial_mask']['y_off'][i] ], \n", + " wy_left= polygon_dict['masks']['partial_mask']['wy_left'][i], wy_right= polygon_dict['masks']['partial_mask']['wy_right'][i], \n", + " wx_up= polygon_dict['masks']['partial_mask']['wx_up'][i], wx_down= polygon_dict['masks']['partial_mask']['wx_down'][i],center_radius= polygon_dict['masks']['partial_mask']['center_radius'][i])\n", + " \n", + " for i in list(partialmask_dict.keys()):\n", + " if i == 0:\n", + " partial_mask = partialmask_dict[i]\n", + " else:\n", + " partial_mask*=partialmask_dict[i]\n", + " polygon_mask*=partial_mask\n", + "if 'window_mask' in list(polygon_dict['masks'].keys()):\n", + " window_shadow = ~create_cross_mask( pixel_mask, center=[md['beam_center_x'],md['beam_center_y']],\n", + " wy_left= 0, wy_right= 0, \n", + " wx_up= 0, wx_down= 0,center_disk=True, center_radius= polygon_dict['masks']['window_mask']['center_radius'])\n", + " polygon_mask*=window_shadow" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "(600.0, 1300.0)" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "show_img(avg_img*pixel_mask*polygon_mask,vmin=1e-0,vmax=1e3, logs=True, \n", + " image_name= 'uid= %s with pixel mask'%uid , aspect=1, cmap= cmap_albula )\n", + "plt.xlim(800,1500);plt.ylim(600,1300)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Check for additional hot pixels e.g. around the direct beam position (best done with an 'empty' image (no sample)!!)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "values above 100 : [112. 190. 215. 130.]\n", + "number of elements above 100: 0\n" + ] + }, + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "second_check=False\n", + "if True:\n", + " thresh=100\n", + " x=avg_img*pixel_mask*polygon_mask\n", + " print('values above %s : %s'%(thresh,x[x>thresh]))\n", + " print('number of elements above %s: %s'%(thresh,len(x[x>5000])))\n", + " p=plt.hist(x[x>thresh])\n", + " plt.yscale('log')\n", + " second_check=True" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "if second_check:\n", + " thresh=6000\n", + " hots=np.nonzero(x > thresh)\n", + " polygon_dict['masks']['hot_beam']={'x_hots':(hots[0]-md['beam_center_x']).tolist(),'y_hots':(hots[1]-md['beam_center_y']).tolist()}" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "if 'hot_beam'in list(polygon_dict['masks'].keys()):\n", + " for i in range(len( polygon_dict['masks']['hot_beam']['x_hots'])):\n", + " if polygon_dict['masks']['hot_beam']['x_hots'][i]+md['beam_center_x'] > 0 and polygon_dict['masks']['hot_beam']['y_hots'][i]+md['beam_center_y'] > 0:\n", + " polygon_mask[int(polygon_dict['masks']['hot_beam']['x_hots'][i]+md['beam_center_x']),int(polygon_dict['masks']['hot_beam']['y_hots'][i]+md['beam_center_x'])]=0" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "show_img(avg_img*pixel_mask*polygon_mask,vmin=1e-0,vmax=1e1, logs=True, \n", + " image_name= 'uid= %s with pixel mask'%uid , aspect=1, cmap= cmap_albula )\n", + "for ii,i in enumerate(polygon_dict['masks']['hot_beam']['x_hots']):\n", + " plt.plot(i+md['beam_center_x'],polygon_dict['masks']['hot_beam']['y_hots'][ii]+md['beam_center_y'],'b+')\n", + "plt.plot(md['beam_center_x'],md['beam_center_y'],'bo')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Check SAXS analysis with detector and pixel mask -> stop the rotation galore!!" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## try without rotations" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Beam_center_x has been changed to 1137.0. (no change in raw metadata): \n", + "Beam_center_y has been changed to 937.0. (no change in raw metadata): \n", + "uid--> uid=9d074654\n", + "dpix--> 0.075\n", + "Ldet--> 16033.390730000001\n", + "lambda_--> 1.2846772192850509\n", + "exposuretime--> 0.1\n", + "timeperframe--> 1.0\n", + "center--> [1137, 937]\n", + "path--> /nsls2/data/chx/legacy/analysis//2023_3/CHX staff/masks/\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask = np.array ( pixel_mask*polygon_mask , dtype = bool )\n", + "center= [ md['beam_center_x'], md['beam_center_y']]\n", + "\n", + "#uidstr = 'uid=%s'%uid\n", + "# if md['detector'] =='eiger4m_single_image' or md['detector'] == 'image' or md['detector']=='eiger1m_single_image': \n", + "# inc_x0 = imgs[0].shape[0] -md['beam_center_y'] \n", + "# inc_y0 = md['beam_center_x'] \n", + "# img_avg=avg_img[::-1]\n", + "\n", + "dpix, lambda_, Ldet, exposuretime, timeperframe, center = check_lost_metadata(\n", + " md, Nimg, inc_x0 = center[1], inc_y0= center[0], pixelsize = 7.5*10*(-5) )\n", + "setup_pargs=dict(uid='uid=%s'%uid, dpix= dpix, Ldet=Ldet, lambda_= lambda_, exposuretime=exposuretime,\n", + " timeperframe=timeperframe, center=center[::-1], path= path)\n", + "print_dict( setup_pargs )\n", + "show_img( avg_img*mask, vmin=.5, vmax= 1e4, logs=True, aspect=1, #save_format='tif',\n", + " image_name= 'uid=%s'%uid + '_img_avg', save=False, \n", + " path=path, center=center[::-1], cmap = cmap_albula ) " + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/nsls2/users/lwiegart/.local/lib/python3.11/site-packages/pyCHX/XPCS_SAXS.py:537: UserWarning: Attempt to set non-positive ylim on a log-scaled axis will be ignored.\n", + " ax1.set_ylim(ylim)\n" + ] + }, + { + "data": { + "text/plain": [ + "{'uid': 'uid=9d074654',\n", + " 'dpix': 0.075,\n", + " 'Ldet': 16033.390730000001,\n", + " 'lambda_': 1.2846772192850509,\n", + " 'exposuretime': 0.1,\n", + " 'timeperframe': 1.0,\n", + " 'center': [937, 1137],\n", + " 'path': '/nsls2/data/chx/legacy/analysis//2023_3/CHX staff/masks/'}" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "setup_pargs['center']=center\n", + "qp_saxs, iq_saxs, q_saxs = get_circular_average( avg_img*mask , mask , save=False,\n", + " pargs=setup_pargs )\n", + "plot_circular_average( qp_saxs, iq_saxs, q_saxs, pargs=setup_pargs, show_pixel=True,\n", + " xlim=[qp_saxs.min(), qp_saxs.max()*1.0], ylim = [iq_saxs.min(), iq_saxs.max()*2],save=False)\n", + "setup_pargs" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Load an ROI mask" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "26\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/nsls2/users/lwiegart/.local/lib/python3.11/site-packages/pyCHX/XPCS_SAXS.py:1556: UserWarning: Attempt to set non-positive ylim on a log-scaled axis will be ignored.\n", + " axes.set_ylim(ylim)\n" + ] + }, + { + "data": { + "image/png": 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J8nOpVVZWYs6cOVAqlfD09IS7uzs8PT1x5swZnD592uQYjdm4cSMKCwsxfvx4zbHx48dDEAStWflx48bhwIEDWjPMK1euRFxcnKbqxs6dO1FZWYmnn35a6+egUCjwwAMP6J3p0zfWnJwcTJw4Ec2aNYO7uzs8PDw0KT3q77eoqAiHDx/G8OHD4enpqXlugwYNkJiYqNXftm3bIJPJMHr0aK1xhYWFoX379iZnIPv27Yvz588jIyMDpaWl+O2335CQkIDevXtrZjp3794NLy8vrXQZSwwdOlTr69jYWJSWliInJ8eqfocMGQK5XK7VLwDNXYmzZ8/izz//xJNPPgkAWtdp8ODByMrK0nt3wRzC/271i7nrEhsbqzdlwhB91w248/0dOnQIZWVleOSRR7TadevWTW+aXG3BwcFITEzEF198ofn7d/36dWzZsgVPP/003N3vrOH/+eef0a9fPwQEBEAul2vuCuXl5Vn9cwTM+1l17doVP/74I6ZNm4ZffvkFJSUlVp+fxGHgS04rLy8PYWFhOscNHevQoYPJf0qlUut5X3/9NXr06IFHHnkEgYGB6N27N0aOHIkOHTqgSZMmZo8lMDAQMplM7+2q/Px8AEBQUJDe73f58uVo1KgRhg0bpnX81q1bSEpKwv/93/8hIiICN27cwI0bNzSpGjdu3NBUawgODgYAtG7dWivHWCaTYeDAgfjnn39M/oFXByHq0lkXL17E22+/jRkzZsDT01Nz/srKSlRXV+PGjRuaP9rqdAP1P3Vu6KxZs7SOt2zZEsCd6hEZGRlGxyRGeHi41tfqwN2WFSCmTp2Kt956C8OHD8fWrVvx+++/Iy0tDe3bt9f7RlZ7jMYsX74cCoUCCQkJmmseGxuLqKgorFq1SvPh4cknn4SXl5fmNqpKpUJaWprWLV51ykBcXJzWz8HDwwMbNmzQydFVl7uqqbq6GgMGDMCmTZvw2muv4aeffkJqaqomH1X9/V6/fh2CIOit+lH72NWrVzVta4/r0KFDJkuIqdMXdu/ejd9++w0VFRXo06cP+vXrh59++knzWI8ePeDt7W20L1PUv1tq6hQpawMWU/2qf3avvPKKzjWaNGkSABi9TmJ+xzIzMwEAzZo1Mzlec17DgOnvT/23UszrxZDx48fj8uXLmg8769atQ1lZmVbOcWpqKgYMGAAAWLZsGfbv34+0tDRMnz5dazzWMOdn9Z///Aevv/46Nm/ejN69eyMoKAjDhw/XSdkg6bGcGdmUQqHQLDKqSUxNzODgYGRnZ+sc13ds1qxZmjxEYyIjIzV/5AGgcePG2L59O3JycpCdnY3IyEh4e3tj0aJFGDVqlNlj8fb2xl133aWzuAkATp48CW9vb7Ro0ULnsWPHjuHYsWN4+eWXdUqo5ebm4urVq/joo4/w0Ucf6Tw3MDAQw4YNw+bNm9GyZUv4+Pjo/d7Vszr6Fs0Za3f+/HmUlJRg8uTJmpJitc8/efJkLFy4EO+8845W3rOfnx+A2zPy6kWDwJ03vy5duiAoKAhbtmzB3Llzrcrzrf1c9YKlf/75x+gburHXaEhIiNFzrlmzBk8//TTmzJmj89yGDRuaHKMhf//9N3777TcAhkvL7dy5E4MHD9b8/L/88ku8++67WLlyJRQKBR5//HFNW/X38c0332h9IDJE3zjT09Nx4sQJrFq1CmPGjNEcr71AT/3hT19+bu3fl5CQEMhkMuzbt08n1x7Qzb+vrWnTprj77ruxe/duREVFoUuXLmjYsCH69u2LSZMm4ffff8ehQ4dE/W1wVuqf3RtvvKG1UKsmdYlEfQYMGIClS5di8+bNmDZtmt42mzdvhru7O+6//36T47E2F782dWBs6PUiZtZ34MCBiIiIwMqVKzFw4ECsXLkS9957r9ZEx/r16+Hh4YFt27ZplW3bvHmzyf7V7Wv/naj9PmbOz8rX1xczZ87EzJkzcfXqVc3sb2JiIv7880+TYyLLMfAlm4qKikJOTg6uXr2q+fReXl6OnTt3mnxu79698f777+PEiRNaKQZr167VaVs7sDLE0Btp48aNNQuN/vOf/6CoqEgrgDNnLCNGjMDChQtx6dIlTcB18+ZNbNq0CUOHDtW69aamXrA0YcIEncfCwsKwZ88enePz5s3Dr7/+ih9//FHzB9fd3R3Dhg3DN998g8zMTM2bhiAI2LFjB1q2bGkymFu9ejU8PDw0q+A7dOig9/xTpkxBQUEBVq5cqZlVjYqK0vtGFRERgYiICJ3jHh4eeP311/H6669j9uzZePvtt3Xa5OTk4MyZM+jRo4fRcdc2YMAAyOVyLF68GPHx8QbbRUVFaS1kBG4Hnn/99ZfJayWTyXReUz/88AMuX76Mu+66y6zx1qR+PSxbtkynn5KSEgwbNgwrVqzQVCQZN24cNm7ciO3bt2PNmjUYMWKEVuA9cOBAuLu749y5c2alW9SkDnhqf7+fffaZ1te+vr7o0qULNm/ejA8//FCT7nDr1i1s27ZNq606reby5cs6t7rF6tevHzZu3IhmzZphyJAhAIC7774bzZs3x9tvv42KigqDC9vUpJq9NdS3Nf3ec889aNWqFU6cOKHzAUuM4cOHQ6lUYt68eRg5cqROmsKGDRuwa9cuPPnkk3rvatnavffeCy8vL2zYsEErWDx06BAuXLggKvCVy+V46qmnsHDhQuzbtw+HDx/WeV3KZDK4u7trpZWUlJRg9erVJvtXj+GPP/7AwIEDNce///57rXaW/qxCQ0MxduxYnDhxAgsXLkRxcbHBCQyyHgNfsqlHH30Ub7/9Nh577DG8+uqrKC0txX/+8x9ROZ5TpkzBihUrMGTIELz77rsIDQ3FV199pffTsKHAypRly5YBAFq2bIkbN27gxx9/xPLlyzFnzhx06tTJorG88sorWL16NYYMGYJZs2bBy8sL8+bNQ2lpqd4dx0pLS7F27Vp0794dbdq00XlcoVDoLemzatUqyOVyncdmz56NH3/8EQkJCXjnnXfg7++Pzz//HCdOnNBa/f/BBx9ApVKhb9++aNq0KXJycrB8+XLs2rUL77zzjiboa9iwod7zN2zYEJWVlVYX/H/11Vdx+vRpzJgxA6mpqXjiiSc0G1js3bsXS5cuxcyZM80OfKOiovDmm29i9uzZKCkp0ZSiUqlUyM3N1cwCPvXUUxg9ejQmTZqEhx56CBcuXMD777+vmTE25sEHH8SqVavQunVrxMbG4siRI/jggw+sSq+orKzEl19+iTZt2ujN9waAxMREfP/997h27RoaNWqEAQMGoGnTppg0aRKys7N1qoJERUVh1qxZmD59Os6fP4+EhAQEBgbi6tWrSE1N1cw+GdO6dWu0bNkS06ZNgyAICAoKwtatWzW3l2uaNWsWhgwZgoEDB2Ly5MmoqqrCBx98gAYNGmhSfgCgR48e+Ne//oVx48bh8OHDuP/+++Hr64usrCz89ttvaNeuHZ5//nmj4+rbty8WLVqE3NxcrRz0vn37YuXKlQgMDNQqZaaPn58fIiMjsWXLFvTt2xdBQUEICQkRFXSZ0q5dO2zatAmLFy9G586d4ebmZvYmJJ999hkGDRqEgQMHYuzYsWjSpAny8/Nx+vRpHD16VKukW21yuRzffvst+vfvj/j4eLz88suIj49HWVkZtm7diqVLlyI2NhaLFy+29lu1SFBQEKZOnYq5c+ciMDAQI0aMwD///IOZM2ciPDzc5B0qtfHjx2P+/Pl44okn4O3tjUcffVTr8SFDhmDBggV44okn8K9//Qt5eXn48MMPTd5VAG5PPvTr108zxsjISPz000/YtGmTTluxP6t7770XDz74IGJjYxEYGIjTp09j9erViI+PZ9Bra45bV0euYvv27UKHDh0Eb29voUWLFsKnn34qqqqDIAiCSqUS+vfvLygUCiEoKEiYMGGCsGXLFkk2sBAEQfjss8+ENm3aCD4+PkKDBg2Enj17Cps3b9bb1pyxnD17Vhg+fLjg7+8v+Pj4CH379hWOHDmit9+vvvpK1Cr62gxtYCEIgnDy5ElhyJAhgp+fn6BQKIRu3boJW7du1Wrz/fffC/fdd5/QqFEjwd3dXfDz8xN69uyptZrcGKk2sFDbsmWLMGTIEM14AgMDhd69ewtLlizRqg4AA1Ud0tLS9Pb75ZdfCnFxcYJCoRAaNGggdOzYUWsVdnV1tfD+++8LLVq0EBQKhdClSxfh559/FlXV4fr168KECROExo0bCz4+PsJ9990n7Nu3z+Cq8K+//trkddi8ebMAQFi4cKHBNjt27NCphvDmm28KAIRmzZoZXOW/efNmoXfv3oK/v7/g5eUlREZGCqNGjRJ2796taWPsdaX+HfDz8xMCAwOFhx9+WLh48aLeigjfffed0K5dO8HT01No3ry5MG/ePOHFF18UAgMDdfpdsWKFcO+99wq+vr6Ct7e30LJlS+Hpp58WDh8+bOxSCYJw+2fg5uYm+Pr6CuXl5Zrj6t+rkSNH6jxH3wYFu3fvFjp27Ch4eXkJADR/iwxtYKF+3WVkZBgdX35+vjBq1CihYcOGgkwm0/zdM7aBhb7reeLECeGRRx4RGjduLHh4eAhhYWFCnz59RFdEuXbtmvD6668LrVu31nyPAITnnntO9CYUkZGRwpAhQww+pq+qQ+3XvL7fo+rqauHdd98VmjZtKnh6egqxsbHCtm3bhPbt2wsjRowQNTZBEITu3bsLAAxWclmxYoVwzz33CF5eXkKLFi2EuXPnCsuXL9f5Oep7fWRlZQmjRo0SgoKChICAAGH06NHC4cOH9VZ6EfOzmjZtmtClSxchMDBQM56XXnpJyM3NFf39kmVkgmCicjMREZGVKioqNItGd+3a5ejhuLzLly8jPj4efn5++PXXX02m9dhbRkYGWrdujRkzZuDNN9909HCoHmHgS0REkpswYQL69++P8PBwZGdnY8mSJfj111+xa9cukzm3ZB+nT5/Gfffdh8jISOzZswcBAQEOGceJEyewbt06dO/eHf7+/vjrr7/w/vvvo7CwEOnp6aKrOxCJwRxfIiKS3M2bN/HKK6/g2rVr8PDwQKdOnbB9+3YGvU6kTZs2TrFTmK+vLw4fPozly5fjxo0bCAgIQK9evfDee+8x6CXJccaXiIiIiFwCN7AgIiIiIpfAwJeIiIiIXAIDXyIiIiJyCVzcZkR1dTWuXLkCPz8/ybdpJCIiIiLrCYKAmzdvIiIiwuSmJwx89UhOTkZycjLKy8tx7tw5Rw+HiIiIiEy4dOmSyZ0zWdXBiIKCAjRs2BBNnl8FN687WwiuGBOHri2CRPVRXF6Jru/9BABInd4XPp7SfdZg3+ybfbNv9s2+2Tf7dra+7a2wsBDNmjXTlMMzpu5+l3agTm9w8/LRCnzL3bzg7+8vqg/38krNc/39/SV9YbFv9s2+2Tf7Zt/sm307W9+OIiYtlYvbLDD7BxWqqjlRTkRERFSXMPC1QFZBKVIz8h09DCIiIiIyAwNfC+XcLHX0EIiIiIjIDAx8LdTYT+HoIRARERGRGRj46pGcnAylUom4uDi9j4cHKNA1WlxVByIiIiJyDgx89UhKSoJKpUJaWprex4e2D4fcjRtaEBEREdUlDHwt8P2JLFZ1ICIiIqpjGPhagFUdiIiIiOoeBr4WYlUHIiIiorqFga+FWNWBiIiIqG6p+/vT2ZkMQBirOhARERHVOZzxNYO6jsOMRCWrOhARERHVMQx89TBUxzcsQIHFozshISbcQSMjIiIiIksx8NVDXx3fHi2D8eHD7dFfGebAkRERERGRpZjjK9L+c3nYfy4P4QEKzEhUctaXiIiIqI7hjK+ZsgtK8fyao9iRnuXooRARERGRGRj4mkm9X9vMrSru3kZERERUhzDwtYAA7t5GREREVNcw8LUCd28jIiIiqjsY+FqBu7cRERER1R2s6mAB7t5GREREVPdwxlcPQxtYqAng7m1EREREdQ0DXz30bWBBRERERHUbA18LyMByZkRERER1DQNfC7CcGREREVHdw8DXCixnRkRERFR3MPC1AsuZEREREdUdDHwt1NDHg+XMiIiIiOoQBr4WYiEzIiIiorqFga+FrhdXcHEbERERUR3CwNcKXNxGREREVHcw8LUCF7cRERER1R0MfC0UHqDg4jYiIiKiOoSBrx7JyclQKpWIi4sz2GZo+3DI3bjEjYiIiKiuYOCrR1JSElQqFdLS0gy2Wbo3AzvSs+w4KiIiIiKyBgNfK8zcqkJVteDoYRARERGRCAx8LSQAyCooZUkzIiIiojqCga+VWNKMiIiIqG5g4GslljQjIiIiqhsY+FqBJc2IiIiI6g4GvlZgSTMiIiKiuoOBrxVWH7rIqg5EREREdQQDXysUl1fhvz+dcfQwiIiIiEgEBr5W+vy385z1JSIiIqoDGPha6VZZFWv5EhEREdUBDHwlwFq+RERERM6Pga8EQny9HD0EIiIiIjKBga8UWNGMiIiIyOkx8JVA7q0yRw+BiIiIiExg4CsBbltMRERE5PwY+IpgLJOhoY8Hty0mIiIiqgMY+OqRnJwMpVKJuLg4AICxKr03iiuQosq2z8CIiIiIyGIMfPVISkqCSqVCWloaAMDb0/hlmrbpJDexICIiInJyDHxFKCmvNvr4jeIKHDqXZ6fREBEREZElGPhK5OD5XEcPgYiIiIiMYOArGRbzJSIiInJmDHwlEt8y2NFDICIiIiIjGPiKIDMxmSuTAXFRLGlGRERE5MwY+IogmCjYIAjAkQvX7TMYIiIiIrIIA1+J5NwsdfQQiIiIiMgIBr4SycwtdvQQiIiIiMgIBr4iNPbzNNlmfdpFbmJBRERE5MQY+IrwcOdmJttkFZQiNSPfDqMhIiIiIksw8BWhaaC3qHbZBSU2HgkRERERWYqBrwjXi8tFtcsvEteOiIiIiOyPga8IAd6mc3wBoKGPuHZEREREZH8MfEUoKBE3k3tD5MwwEREREdkfA18RAn29RLULaiCuHRERERHZHwNfEUL9FKLaXcxjLV8iIiIiZ8XAV4TOUYEI8zc9m8tavkRERETOi4GvCHI3GR7v2txkO9byJSIiInJeDHxFah7kI6rdrlNZNh4JEREREVmCga9IYmv0fnv0MtMdiIiIiJwQA1+RxFZsKCytZLoDERERkRNi4CtSmL+4yg4AkHOz1IYjISIiIiJLuETgO2LECAQGBmLUqFEW99E1OghBvh6i2jYWWf6MiIiIiOzHJQLfF198EV9++aVVfcjdZJiV2NZkOzcZ0Dky0KpzEREREZH0XCLw7d27N/z8/KzuJ1jETG61ABy5cN3qcxERERGRtJw+8N27dy8SExMREREBmUyGzZs367RZtGgRoqOjoVAo0LlzZ+zbt88mY8kuKBHVjiXNiIiIiJyP0we+RUVFaN++PT799FO9j2/YsAFTpkzB9OnTcezYMfTs2RODBg3CxYsXzT5XWVkZCgsLtf7VxJJmRERERHWX0we+gwYNwrvvvouRI0fqfXzBggWYMGECnnnmGbRp0wYLFy5Es2bNsHjxYrPPNXfuXAQEBGj+NWvWTOtxljQjIiIiqrucPvA1pry8HEeOHMGAAQO0jg8YMAAHDhwwu7833ngDBQUFmn+XLl3SepwlzYiIiIjqLndHD8Aaubm5qKqqQmhoqNbx0NBQZGdna74eOHAgjh49iqKiIjRt2hTfffcd4uLidPrz8vKCl5fhWV11SbP8ogqTY2NJMyIiIiLnUqcDXzWZTKb1tSAIWsd27twpyXnUJc1eWH/c+HjAkmZEREREzqZOpzqEhIRALpdrze4CQE5Ojs4ssFTElDQTACz+5ZxNzk9ERERElqnTga+npyc6d+6MlJQUreMpKSno3r27xf0mJydDqVTqTYcQm7u78kAGKzsQERERORGnT3W4desWzp49q/k6IyMDx48fR1BQEJo3b46pU6fiqaeeQpcuXRAfH4+lS5fi4sWLmDhxosXnTEpKQlJSEgoLCxEQEKD1WIivuMoON4orkJqRj/bNAkw3JiIiIiKbc/rA9/Dhw+jdu7fm66lTpwIAxowZg1WrVuHRRx9FXl4eZs2ahaysLMTExGD79u2IjIy0zYBkppuo3Z4dZuBLRERE5AycPvDt1asXBMF4ysCkSZMwadIku4wn91aZ6Las7EBERETkPOp0jq8jiA1mG3i5o2t0kI1HQ0RERERiMfDVw9jitq7RQQjzN53n6yE3IyeCiIiIiGyOga8eSUlJUKlUSEtL03lM7ibD412bm+zj+v8WtxERERGRc2Dga4HmQT6i2mUXlNh4JEREREQkFgNfC+QXlUvajoiIiIhsj4GvBYIaiKvl+88NzvgSEREROQsGvhYI8xdX2eH741e4exsRERGRk2Dgq4exqg7A7coOQb4eJvvJKyrH4czrUg+PiIiIiCzAwFcPY1UdgNuVHYa1jxDV10+ns6UcGhERERFZiIGvhZoGiqvssOX4FRuPhIiIiIjEYOBrIbEL3G6WVdl4JEREREQkBgNfC4ld4EZEREREzoGBr4W6Rgch0Mfd0cMgIiIiIpEY+OphqqoDcHuB25j4KPsNioiIiIiswsBXD1NVHdSiGzWw04iIiIiIyFoMfK3Q2I95vkRERER1BQNfK3SNDkJ4gAIyA4/LAIT6i6v+QERERES2xcDXCnI3GWYkKo22eXNwazuNhoiIiIiMYeBrpYSYcPzr/mi41Zr2lQF4pmcU+ivDHDIuIiIiItLGelxW2pGehaV7MyDUOi4AWLYvE1XVtR8hIiIiIkfgjK8VqqoFzNyq0gl6a1qx/4LdxkNEREREhjHw1UNMHV8ASM3IR1ZBqZ1GRURERETWYOCrh9g6vjk3GfQSERER1RUMfK3AOr5EREREdQcDXyt0jQ5CkK+Ho4dBRERERCIw8LWC3E2Gd4fFOHoYRERERCQCA18rDY6NQH9lY0cPg4iIiIhMYOBrpapqAWmZ1x09DCIiIiIygYGvlQ6dz8ON4gpHD4OIiIiITGDga6WD5/IcPQQiIiIiEoGBr9W4JTERERFRXcDAVw+xO7cBQHyLEDuMiIiIiIisxcBXD7E7twFAt5bBCPB2F9VvVTVnh4mIiIgchYGvleRuMozvES2q7WFWfyAiIiJyGAa+Emge5COq3dXCEhuPhIiIiIgMYeArgfyiclHtrhex7BkRERGRozDwlUBQAy9R7S4XcMaXiIiIyFEY+EogzF8hqt13Ry9zgRsRERGRgzDwlUDX6CAE+piu7FBUXoVD3PCCiIiIyCEY+EpA7iZDfItgUW0Pns+18WiIiIiISB8GvhKJCmkgqh0zHYiIiIgcg4GvRAJ9PCVtR0RERETSYuArkRA/cZUdrrCyAxEREZFDMPDVIzk5GUqlEnFxcaKfI7ayw7rfL7KyAxEREZEDMPDVIykpCSqVCmlpaaKf0zU6CA29TVd2KK2sxoGzXOBGREREZG8MfCUid5Ph7lA/UW1nbj1l49EQERERUW0MfCXU0MdDVLuz14pQXllt49EQERERUU0MfCUUFyWuli8ArD6YabuBEBEREZEOBr4SGtM9SnTbC/nFthsIEREREelg4CshT3c3xLcIFNU2MsjHxqMhIiIiopoY+Ersi/HdIBPR7kpBqc3HQkRERER3MPCVmKe7G8bfF2my3cr9GVzgRkRERGRHDHxtICLAdBpDtcAFbkRERET2xMDXBjLyiiRtR0RERETWY+BrA2JyfM1pR0RERETWY+BrAx2biavsIJcx9CUiIiKyFwa+NhDe0FtUu2+OXkZVtWDj0RARERERwMDXJrpGByHI1/T2xbfKKvHpz2ftMCIiIiIiYuBrA3I3GRJjw0W1Xbk/g7O+RERERHbAwNdGxMayN0oqkJqRb9vBEBEREREDX32Sk5OhVCoRFxdnRS/iF67l3OQubkRERES2xsBXj6SkJKhUKqSlpVncR1Sw6U0s1EJ8vSw+DxERERGJw8DXRp6KjxLdNi2TqQ5EREREtsbA10Y83d3Qt3UjUW2X7jvPBW5ERERENsbA14ae6dlSVLvi8iocOpdn49EQERERuTYGvjbUNToIPh7iLvHB87k2Hg0RERGRa2Pga0NyNxl6tAoR2ZrbFxMRERHZEgNfG3ukczNR7dwY9xIRERHZFANfG3MTGdH+5+ez2JGeZePREBEREbkuBr42lldUJrrtzK0qVncgIiIishEGvjbWqIFCdNusglJuX0xERERkIwx8baxLVKBZ7bl9MREREZFtMPC1MbmZq9Ya+4mfISYiIiIi8Rj4OhFvDzd0jQ5y9DCIiIiI6iUGvk6kpKIaKapsRw+DiIiIqF5i4OtkWNmBiIiIyDYY+NpRh2YBJtuwsgMRERGRbTDwtaO/sm+KavfatydsPBIiIiIi18PA145KKqpFtbuUX4Itxy/beDREREREroWBr5N6Y9NJ5voSERERSYiBr5MqLq9iri8RERGRhBj4OjHu4kZEREQkHQa+duTjad7lTlFdtdFIiIiIiFwPA187em94jFntt/2Rhe1/ZNloNERERESuhYGvHQ2MCcdz90eb9ZzXvv2Di9yIiIiIJFDvA99t27bhnnvuQatWrfD55587ejh4Y7ASi57oBA83maj2t8oq8enPZ208KiIiIqL6r14HvpWVlZg6dSp+/vlnHD16FPPnz0d+vuMrJfRThqLSjFnclQcyOOtLREREZKV6Hfimpqaibdu2aNKkCfz8/DB48GDs3LnT0cPC6oOZMCeMvVFcwdJmRERERFZy6sB37969SExMREREBGQyGTZv3qzTZtGiRYiOjoZCoUDnzp2xb98+zWNXrlxBkyZNNF83bdoUly87fke0C/nFZj8nu6DEBiMhIiIich1OHfgWFRWhffv2+PTTT/U+vmHDBkyZMgXTp0/HsWPH0LNnTwwaNAgXL14EAAiC7ryqTGY4t7asrAyFhYVa/2whMsjH7OfkF5XbYCRERERErsOpA99Bgwbh3XffxciRI/U+vmDBAkyYMAHPPPMM2rRpg4ULF6JZs2ZYvHgxAKBJkyZaM7z//PMPwsPDDZ5v7ty5CAgI0Pxr1qyZtN/Q/zwVHwVxS9vuCGrgZZOxEBEREbkKpw58jSkvL8eRI0cwYMAAreMDBgzAgQMHAABdu3ZFeno6Ll++jJs3b2L79u0YOHCgwT7feOMNFBQUaP5dunTJJmP3dHfDg7FhZj3nQm6RTcZCRERE5CrqbOCbm5uLqqoqhIaGah0PDQ1FdnY2AMDd3R0fffQRevfujY4dO+LVV19FcHCwwT69vLzg7++v9c9W+inNC3y/PHSBlR2IiIiIrODu6AFYq3bOriAIWseGDh2KoUOH2ntYJjX2U5jVPr+oHKkZ+YhvaThwJyIiIiLD6uyMb0hICORyuWZ2Vy0nJ0dnFthcycnJUCqViIuLs6ofY7pGByE8wLzgd9cpbl9MREREZKk6G/h6enqic+fOSElJ0TqekpKC7t27W9V3UlISVCoV0tLSrOrHGLmbDDMSlWY9Z33aJaY7EBEREVnIqQPfW7du4fjx4zh+/DgAICMjA8ePH9eUK5s6dSo+//xzrFixAqdPn8ZLL72EixcvYuLEiQ4ctXgJMeFYMroTvD3E/RhKKqpx6FyejUdFREREVD85dY7v4cOH0bt3b83XU6dOBQCMGTMGq1atwqOPPoq8vDzMmjULWVlZiImJwfbt2xEZGemoIZstISYcfgoPPPn576LaHziXix6tQmw8KiIiIqL6x6kD3169eundhKKmSZMmYdKkSXYakW10axEMhYcMpRWm0xjSMrl1MREREZElnDrVwVXI3WTodXdjUW1VWYXM8yUiIiKyAANfPexR1aG2p7pFiWp3q6wKqRmc9SUiIiIyFwNfPexR1aG2bi2D4eMpF9U252apjUdDREREVP8w8HUScjcZnu0ZLaptiK+XjUdDREREVP8w8HUiXaPF7cq2LvWijUdCREREVP8w8HUiOTfLRLXbdjIL2//gLm5ERERE5mDgq4cjFrcBQP4tcYEvAEzdeJzVHYiIiIjMwMBXD0csbgOAIF9P0W1LK6ux5JdzNhwNERERUf3CwNeJhAV4m9V+1YEMG42EiIiIqP5h4OtEukYHwcdD/I+kqLzahqMhIiIiql8Y+DoRuZsMz97fwtHDICIiIqqXGPg6mRf73g1vM2Z9iYiIiEgcRlhORu4mw8ePdnD0MIiIiIjqHQa+ejiqnJlaQkw4RnVq4pBzExEREdVXDHz1cFQ5s5p63BXisHMTERER1UcMfJ2UuaXNiIiIiMg4Br5Oqmt0EAIU7qLbcxc3IiIiIuMY+DopuZsM/do0Ft3+s1/P23A0RERERHUfA18nFtZQfLrD8t/Oc9aXiIiIyAgGvk5MBpnotiUV1Th0Ls+GoyEiIiKq2xj4OrH4lsFmtf9w1582GgkRERFR3cfAVw9H1/FV69YiGL5ectHtj18qQHlltQ1HRERERFR3MfDVwxnq+AK3F7h98FCs6PYCgC8OZNhuQERERER1GANfJzc4NgJD2oWKbv/x7jPYkZ5lwxERERER1U0MfOuAAW3DRbctLq/C82uOMvglIiIiqoWBbx3Q2E9h9nNmblWxvBkRERFRDQx864Cu0UEI8vUQ3V4AkFVQitSMfNsNioiIiKiOYeBbB8jdZBjRoYnZz8suKLHBaIiIiIjqJga+dUQ/ZZjZz3nju5PY/scVG4yGiIiIqO5h4FtHdI0OQpi/l1nPKa2oxqS1x/B/a48w35eIiIhcHgNfPZxlA4ua5G4yPBbXzKLnbv0jG53fTWGlByIiInJpDHz1cJYNLGqzZlO2G8UVLHNGRERELs3dkidlZmZi3759yMzMRHFxMRo1aoSOHTsiPj4eCoX5pbdILOvSFQTcLnPWXxkGuZtMmiERERER1RFmBb5r167Ff/7zH6SmpqJx48Zo0qQJvL29kZ+fj3PnzkGhUODJJ5/E66+/jsjISFuN2WXFtwjBp3vOWdWHusxZfMtgiUZFREREJI2qagGpGfnIuVmKxn4KdI0OknSyTnTg26lTJ7i5uWHs2LHYuHEjmjdvrvV4WVkZDh48iPXr16NLly5YtGgRHn74YckGSkC3lsEI8HZHQUmlVf3k3CyVaERERERE0tiRnoWZW1XIKrgTp4QHKDAjUYmEGPG72BojOsd39uzZOHz4MF544QWdoBcAvLy80KtXLyxZsgSnT59GVFSUJAOkO+RuMsx/KNbqfizZCY6IiIjIVnakZ+H5NUe1gl4AyC4olXSNkujAd8iQIaI7DQkJcaqKCPVJQkw4XurXyqLnynD7k1PX6CBpB0VERERkoapqATO3qvSuZFIfm7lVJUlpVosWtxUWFopu6+/vb8kpyIioEF+LnicAmJGo5MI2IiIichqpGfk6M701CZBujZJFgW/Dhg0hkxkPngRBgEwmQ1VVlUUDI8OsSVX4M6uQVR2IiIjIaYhdeyTFGiWLAt+VK1di2rRpGDt2LOLj4wEABw8exBdffIG5c+cyv9fGukYHITxAYfTTkSELfzqLVQcvYN7IdpIlihMRERFZSuyEnhRrlCwKfL/88kssWLAAjz/+uObY0KFD0a5dOyxduhS//PKL1QMjw+RuMsxIVGLimqMWPf9GcQUmrjmKJaM7MfglIiIih1JP6GUXlOrN85UBCJNojZJFO7cdPHgQXbp00TnepUsXpKamWj0oMi0hJhyfPNbeqj6kShQnIiIispR6Qk8fdWKmVGuULAp8mzVrhiVLlugc/+yzz9CsWTOrB+VoycnJUCqVTl+Zor8yzKrnqxPFiYiIiBwpISYci0d3gpe7dmgaFqDAYgnvUFuU6vDxxx/joYcews6dO9GtWzcAwKFDh3Du3Dl8++23kgzMkZKSkpCUlITCwkIEBAQ4ejiiNG7ggZxbFWY/j5tZEBERkTNIiAnH/a3+QcrpHADAume7Sb5zm0UzvoMHD8aZM2cwbNgw5OfnIy8vD8OGDcPff/+NwYMHSzY4Em/6g/pvEZjCzSyIiIjIWdSsGhbfMljyKlQWzfgCQNOmTfHee+9JORayQn9lGCb0KMDy/Zmin8PNLIiIiMiViJ7xvXjxolkdX7582ezBkHX6mZnz26NliI1GQkREROR8RAe+cXFxePbZZ41WbSgoKMCyZcsQExODTZs2STJAEq9rdBDC/L1Et//m6D+4b/7Pku1/TUREROTMRKc6nD59GnPmzEFCQgI8PDzQpUsXREREQKFQ4Pr161CpVDh16hS6dOmCDz74AIMGDbLluEkPuZsM7wxta1Z936yCUjy/5qikKyaJiIiInJHoGd+goCB8+OGHuHLlChYvXoy7774bubm5OHPmDADgySefxJEjR7B//34GvQ6UEBOORU90NOs5AljTl4iIiOo/sxe3KRQKjBw5EiNHjrTFeEgCg2MjMCYjH18cvCD6OeqavvEtg204MiIiIiLHMSvwFRvsMr/X8YrKKs1+Tooqm4EvERER1VtmBb51ZTMHV7cjPQvfHDW/qsaW41cwfYg0WwISERERORuzAt+VK1faahwkkapqATO3qix6bl5ROQ6dy0OPVixzRkRERPWPRTu3kfNKzchHVoHl2xA/u/owy5sRERFRvcTAt57JuWl50AsAxeVVeH7NUaSosiUaEREREZFzYOBbzzT2U1jdhwBgzvY/rR8MERERkRNh4FvPdI0OQniAAtYuT7taWCbJeIiIiIicBQPfekbuJsOMRKWjh0FERETkdBj41kMJMeFYPLoTwgOsT3sgIiIiqi/M3rnNFSQnJyM5ORlVVVWOHorFEmLC0V8ZhtSMfCzbdw4//3nN0UMiIiIicijO+OqRlJQElUqFtLQ0Rw/FKnI3GeJbBmPF2K6Y0reVo4dDRERE5FAMfF3E//VthQBvD0cPg4iIiMhhGPi6CLmbDON7RFn03KpqQdrBEBERETkAA18X0qpxA4uedzjzusQjISIiIrI/Br4uoqpawOwfTlv03J//vCrxaIiIiIjsj4Gvi0jNyEdWgWXbGa8+dBE70rMkHhERERGRfTHwdRE5Ny0LetWmfXsS+8/mMt+XiIiI6iwGvi6isZ91m1ncKKnAk5//jvvm/8zZXyIiIqqTGPi6iK7RQQgPUEBmZT/ZBaV4fs1RBr9ERERU5zDwdRFyNxlmJCqt7ked6DBzq4ppD0RERFSnMPB1IQkx4Vg8uhPCA6xLexAAZBWUIjUjX5qBEREREdkBA18XkxATjt9e74PhHSKs7svaBXNERERE9sTA1wXJ3WR4uHMzq/sJ8fWSYDRERERE9sHA10V1axmMAG93q/p4+esTXORGREREdQYDXxcld5NhfI9oq/rILizFRFZ4ICIiojqCga8LiwrxlaSfaZtOssIDEREROT0Gvi7M2k0t1G4UV+DTn89K0hcRERGRrTDwdWFdo4MQ5i/NArWVBzI460tEREROjYGvC5O7yfDO0LaS9HWjuIJ1fYmIiMipMfB1cQkx4VgyuhN8POVW98W6vkREROTMGPgSEmLCsezpLlb3w7q+RERE5MwY+BIAoFuLYIQHKCCzoo+kdSxtRkRERM6LgS8BuJ3vOyNRCQAWB783iitY15eIiIiclksEviNGjEBgYCBGjRrl6KE4tYSYcCwe3QlhAdaVOZu5VcUKD0REROR0XCLwffHFF/Hll186ehh1QkJMOH57vQ9eH3iPxX1kFZSywgMRERE5HZcIfHv37g0/Pz9HD6POkLvJEOznaVUfrPBAREREzsbhge/evXuRmJiIiIgIyGQybN68WafNokWLEB0dDYVCgc6dO2Pfvn32H6iLadTAunSH//50BvvP5qKqWkBVtYCD5/Kw5fhlHDyXxzQIIiIicgh3Rw+gqKgI7du3x7hx4/DQQw/pPL5hwwZMmTIFixYtQo8ePfDZZ59h0KBBUKlUaN68OQCgc+fOKCsr03nurl27EBERIXosZWVlWv0UFhZa8B3VD12iAq16/tlrRXjy89/h4ymHp7sbbhRXaB4LlWi3OCIiIiJzODzwHTRoEAYNGmTw8QULFmDChAl45plnAAALFy7Ezp07sXjxYsydOxcAcOTIEUnGMnfuXMycOVOSvui24vIqFJdXaR27Wqj7IYWIiIjI1hye6mBMeXk5jhw5ggEDBmgdHzBgAA4cOCD5+d544w0UFBRo/l26dEnyc9QVhzOv2+U8THsgIiIie3H4jK8xubm5qKqqQmhoqNbx0NBQZGdni+5n4MCBOHr0KIqKitC0aVN89913iIuL02nn5eUFLy/ehgeAa7fsszjtcOZ19G7d2C7nIiIiItfm1IGvmkymvaWCIAg6x4zZuXOn1EOq96xd3CaWvQJsIiIiIqdOdQgJCYFcLteZ3c3JydGZBSZpWbu4TSx7BdhERERETh34enp6onPnzkhJSdE6npKSgu7du9vsvMnJyVAqlXrTIVyF3M3SjYvNY68Am4iIiMjhge+tW7dw/PhxHD9+HACQkZGB48eP4+LFiwCAqVOn4vPPP8eKFStw+vRpvPTSS7h48SImTpxoszElJSVBpVIhLS3NZueoS2xZfuznP6/arG8iIiKimhye43v48GH07t1b8/XUqVMBAGPGjMGqVavw6KOPIi8vD7NmzUJWVhZiYmKwfft2REZGOmrILmf31AeQfrkQv525huRfzkna9+T1J+DlLkdCTLik/RIRERHV5vDAt1evXhAE4yWtJk2ahEmTJtlpRFSb3E2G+JbB6BodhE3HLiO7oBRSFiGbuVWF/sowu6VXEBERkWtyeKoD1R1yNxlmJCol7zeroBSpGfmS90tERERUEwNfPbi4zbCEmHAsHt0J4QHSVmPYf/Yathy/jIPn8ripBREREdmEw1MdnFFSUhKSkpJQWFiIgIAARw/H6STEhKO/MgypGfnYeSoLqw5csLrPT/fcyR0OD1BgRqKSeb9EREQkKc74kkXUeb/vDI3Boic6Sdp3VkEpnl9zFDvSsyTtl4iIiFwbA1+y2uDYcCx6oiOkXJom4PaiN6Y9EBERkVQY+JIkBsdGYGz3KEn75KI3IiIikhIDX5LMgLZhkveZXVAieZ9ERETkmhj46sGqDpbpGh0kebWH/KJySfsjIiIi18XAVw9uWWwZW9T5bejjKWl/RERE5LoY+JKkEmLCMapTE8n6e2/7aVZ3ICIiIkkw8CXJzRkZC6l2H84vKsfENUcxe+spbm5BREREVmHgS5LzdHfDsz2jJe1z+f5MPL7sEDrPTsEnu/9mAExERERmY+BLNvHGYCWe7Rkleb83Sirw8e4z6PxuClMgiIiIyCwMfPVgVQdpTB/SFv99vKNN+r5RXMHd3YiIiMgsDHz1YFUH6SS2j8CS0Z0Q4O0ued/c3Y2IiIjMwcCXbC4hJhyLnuxsk765uxsRERGJxcCX7KJbi2AE+XrYpO8UVbZN+iUiIqL6hYEv2YXcTYZ3h8XYpO8tx68w3YGIiIhMYuBLdjM4NgLP3S9tmTMAyCsqZ7oDERERmcTAl+yqY/NAm/S7bN85m/RLRERE9QcDX7KbqmoBM7eqbNL3z39ew/Y/WNqMiIiIDGPgqwfr+NpGakY+sgpKbdb/W1vSmetLREREBjHw1YN1fG0j56btgl7gdq7vm9/+YdNzEBERUd3FwJfsprGfwubn2HryTmkzljkjIiJynKpqAQfP5WHL8cs4eC7PKe7KSr+dFpEBXaODEB6gsGm6Q02T15+Al7scCTHhdjkfERER3bYjPQszt6q03vPDAxSYkajUel+uqhaQmpGPnJulaOyngCDYNjhm4Et2I3eTYUaiEhPXHLXbOd/87iT6tA6Fp/udmxu1f8m6RgdB7iaz25iIiIjqsx3pWXh+zVHUDmGzC0rx/JqjWDy6ExJiwvUGx17utk1GYOBLdpUQE45PHmuPyetP2OV8+UUV6Db3J8wZEWPwl0zfJ1AiIiIyn7qCk755WwGADMDMrSpUVwNJa3WD47LKapuOjzm+ZHf9lWF2PV9+UTkmrjmKSWsOY+KaozqpFupPoDvSWQ6NiIjIGqYqOAkAsgpK8e8t6XqD45pskRPMwJcc6pPH2iPM38su59qeflXvcfWv1cytKqdIvCciIqqrxFZwyi8qN9nGFruyMvAlh+qvDMP+aX3xUr+7HToO9SdQbn1MRERkOSkrONmiDCoDX3I4uZsMk/u1wpLRnRAeYPuSZ8bYutYwERFRfaau4GRoybgMQJCvh6i+bFEGlYGvHty5zTESYsLx2+t9sO7ZbhjfI8ohY8jMLXbIeYmIiOoDdQUnADrBr/rrd4fFGA2O1bpGB0k9PAa++nDnNseRu8nQNToIP6Y7ZvOJhbv/5iI3IiIiEQxtUJEQE47FozshrNZd3LAABRaP7oTBsREGg+OabFFqlOXMyOmYWhFqazO3qtBfGcbavkRERAaYKg+aEBOO/sowtHxzOwAgqXdLTO1/j+a9VR0c66vja8uSZpzxJafjyDxb9SK3Q+fyHDYGIiIiZ6beoMJUedCaE0iRwb46E0rqFEe1qGAf3N8qxIYjZ+BLTsgWyezmSlrLur5ERES1mdqgAtBfHrSySn+50JrBsK+XO2Qy295tZeBLTsfUilB7uFFSwU0tiIiIahG7QUXt8qCV1bbdkU0sBr7kdGquCHU0bmpBRER0h9h0xNrtKgzM+NobA19ySuqkd0fW9eWmFkRERNrEpiPWbldZ5RwzvqzqQE5LvSI0NSMfKapsbD5+RdQWh1L77cw15Nwshb9CXMFtIiIiZ1FVLSA1Ix85N0vR2E+BrtFBVlUtUqcjZheU6s3zleF22bLaNXjP5xZhy/HLkozBGgx8yanJ3WSIbxmM+JbBmD5EqQmCVx+8gAo7pSAk/3LOLuchIiKSkrGSY/ff3ciiPtXpiM+vOarzmDqUnZGo1AlsN6Rdwoa0S1pjSIgJt2gM1mCqA9UZ6iD47cS2ODUrAUE+ng4by/s7Tjvs3ERERKYYKjmWVVCKiWuOYt52y9/H1OmIwb7a78PqDSrUAa2hBeK1y57ZEwNfqpM83d0wZ2QMZDC+64utrDpwEe/9oHLAmYmIiIwzVnJM7ctDFzX/n6Iyf7fUhJhwLHqyk+brdc92w2+v99EEvVXVAt75Xv/7pLGyZ7bGwFeP5ORkKJVKxMXFOXooZIShLRHtZdm+DGz/486nVUNbNxIREdmTuTugTl5/wqLZ15rpDN1aaOftfvrzGWQXml/2zNaY46tHUlISkpKSUFhYiICAAEcPh4yovQBuxf5Mu57/rS3pGBgThhRVtsE8KvX4pFpYQEREZIwlO6DO3KpCf2WYWe9PNad3qgVA/r+n7kjPwse7z4jqw967tTLwpTqv5gI4QMCK/Rfsdu68onJ8+vNZLNz9t84tpez/5VE19PHAjeIKzXFHJvUTEVH9Z8kOqOrZ19vvpbeZUxFCEAQAMk2ahVi5N8vMHqs1GPhSvVFVLeCHk+bnKVlr5f4Mo1s31gx6gTtJ/TUXABAREUnFVMkxQ2rOvhqrCKF+76oZAquz+8xNs5j9g30XizPHl+qN1Ix8XC207ydH4Pb2xuZwZFI/ERHVf5bugKqeKTZUEcJYNYZq4fb7mTWpC4Vmvp9agoEv1Rv2zhMCgABvy26acFc4IiKyJfUC8JAG4kp/hv9v0wljFSHETNxk5hZZNmDcfl8UBNtOCDHVgeoNS3KarFVcXmXV8x0RrBMRkWtIiAlHVLAvEj7ZZ7KtetOJg+fyjKYqqCduVu3PwM3SSs3xakEwa1GbPpXVAq4X23bWl4Ev1Rtdo4MQ6u9l13SHiirrPplaE6xLvQ0lERHVPx7ud27uf/RwLObv+As5tRaUffJYe03ertgJmdq5uTtOZuP9nX9aOVqgrNK6CSVTGPhSvSF3k+HNwa0xef0Jk219veQoKrPtL5cpMhlwvajcoueKWXRARETkJrszIfLAPY3Rs1UjdJ3zk1ab/sowzf9bOiEz9WvT771ieLnLJenHEAa+VK/c/uXV/eUL8/fC412bIyrEF439FKisqsZTK1LtP8AaBAFIWnsUi906ae2Z/snuv+EhlyO+ZTC6tQjWmcVVLzrQVz6N1SKIiFyHmDt/NXNmq6oFk3cGLa0IIQV3NxkCfTxsew6b9k7kQCvHxqGwtELvH4OqagE+nnKrc3SlMHOrCq8NvEfz9Wd7MwAAn+45Cy93N/Rp3Riju0WiW4tgTXtDiw5ksKwIORER1S1i7/zVXINWWS1ozQDrI3eT4a0hSkxae1TyMZsSHqCAzMT4rMXAl+qte1sEwcdT/0tc7ibDc/e3sCoJXwrqRQIvbdR/i6issho/pmfjx/RsNPTxwLjuUaIWHdQuQk5ERNKrqhbw+/l8ra+t7a/mDG5ME3+9jxvaqVT/nb87Y6qsqoaHiUmRHelZmP2D+A0opOSnsH1YysCXXNYLfVph5YFMnQ0mnNWN4gqn3QKSiMjV6Jtx7bfgV8wc2taidDN9/YX6e2n+P0WVjXk//mVy8qP2nT+h1oyvsdjcUCqdvdjjLizr+JLLkrvJMG9kO9THhABHlHYjInIVhjZ4uFpYZnCDB0v7U5u8/oSoHdFq14mvGcRWVQuajSZqM1a/V83W75eVVlZKEoOBL7k0dYHvhjZOprenhj4e6BodBED623BERK5OTIBozs6cYvqzhPrOn9aMb5XhwFfMVsO2fgdxl9t+KoqBL7m8/sowKGxcPsWebhRXIEWVjR3pWbhv/s8YtypN81i/Bb9iR3oWqqoFHDyXhy3HL+PguTwGxEREIpkKEM3dmVNMwGmJM1dv4eC5PFRWV2uOVVUL0Bf3/n4+H9mFjk+R8/G0/Xsxc3zJ5aVmOMcvvJRe++YECkt1c6WuFpZh4pqjaOjjoZXbzBrARETiiF1DIXU7c3265yw+3XNWa8viyupqvYHvuFVpCPKtP3c+jeGMrx7JyclQKpWIi4tz9FDIDurjQjB9QW9NtRf0qVcCm5uXRkTkasSuoZC6naVyb93ZKOnEpRv4z09/622XX+T4hd5c3OYgSUlJUKlUSEtLM92Y6jwuBLuTt2VOXhoRkStSb/BgKBtVhtt30dRrLcT0F+rnZbqhBN7ZqsI3Ry+bbOeoRd9c3EZkB+o/Yq5OnZe2an+G6Nzfmo//fj6fQTMR1XtyNxlmJCoNPi4AeCyumc5xQ2srUlTZuFVeaavhWiTQ19N0Ixuwx+I25viSy1P/EZu4xv671Dij2T+c1vy/vtzf8spqrD6Yib1ncnHkwp3FG+NWpTFXmIjqFDFb/uqjrgg0deMJvbfnP959BuvTLmn+HhraZW1o+3As3ZvhsLq5hrw1pI3BjZVsiYvbiOwkISYci57oiBfWHTNa3NvV1N4FaO52FZbtyzB4jfTvGkRE5HzEbvlrSEJMOH75+xrWp17S+3hWQSkmrjmKB2PD8cMfWTrBbVZBqWaLemcTFuDtkPPaertigKkORBqDYyPw6eOdHD0Mp1Iz9/e9H1T4bK/hoLd2e6Y9EJG9mFui0dCGEeYu9BUM1MStaZueoNdZmZufXBdxxpeohsGx4Vji1klnFsDLXYayyrryp0ta6tzfz38TNzOhbn/oXB56tAqx6diIiMyduTW2YYS+LX+NOXW50LrBOxH1dzojUWn0+w708cD1YsdXgLAUA1+iWhJiwtFfGaaV91VZVY2nVqQ6emgOJWJiQ8uzqw9jwSPtmfJARFoszavVRz1zW/vPk7G0q8OZ10VvQBHfMtjoudOv1J/AN0xkmkddDnoBBr5EesndZFp/8KqqBQR4u6OgxLlW3jqz4vIqTFxzFEscmO8r5RssUV207Y8raBbo6zSvfWOzs/ff3UirranfX3Nmbmu6dsv6jSXU564vVo6Nw/13N3KK14itMfAlEkHuJsM7iW0dssq1rhN7y9ASxt4YzXmDJapPUlTZmv9/7ZuTAJxjd0ZTs7MLH2uvOZaiysa8H/8ymr5gztbB7ZsFaI7n3Sw3+JyaatZ4r/23prKq2ibbDDvKvS1u5/QePJen+R7tpbGfF3JultntfAx8iUTYkZ6FeTv+dPQw6qTatwylmoU1FthWVwOT1uqWp9P3BmtvnIUmW9qRnoXJ63U/oDu64oqY2dk52+/8jRXzPZi3JfCdwHf+zr+Mtpfh9m1/9QIvfX9rpPyNfbZnNJbtc2x1B30fNCzl4yk3awe2/+vTCm9tSbf6vGIx8CUywdAsBYn34/9WSF8vKsfsH3SD1beGtEGgrxeyC0qQX1SOoAZeaOh9Z9/42rdrjc0cTVxzFIYq4uh7g7UHdbCbosrG5uNXkF90Z8bJGWbi6hNX/mBh7Pa7uYu2pCZmdvZqofFZv9rfgzlbAtecBTem9gIvQ39rpHw/+PrIPxL2Zhl9HzQsFRcVhF//via6/QN2vgPHwJfICGOzFCTelwcv4MuDF/Q+llVQiklrjxl9fs3btW8NaYPZP5w2OHMEGF+IJ+YNVkr6ZotqcvRMXH0i5vZ4fWbOrX99i7as/dBg7PliZ2dNqfk9qHfdzC4oNfg3OtDHHb/8fRWr9meK6r/mAi97/f2/UccXi9XWPMjH0UMwioEvkRGm3kjUukYFIjXzuh1G5NrEBMnm+v18PgpLK2wyO5iiysaU9SeMvnHacyauvs+GOuMtfnsy79a/Nms3czD1fKlzRnNulkLuJsNbQ5R605rUrhdX4rNfxaURKNzd8NaQNqJziOsKX085isxIPajvGPgSGSH2jeSvqzcR6ueFq2Yk6POPkXMYtypN8/9Szw7O2f6nqNkiseWTrGFtYGNvUgXpjr7Fb0/m3PqvyZKSYOY+v78yzOTsbIDCHQWl4irnNPZTYEd6Fmb/IF1lhdLKaiStPYZkAIG+XpoUrbqO7zPaGPgSGSH2jaSgpBLj+7XAx7v/Ntm2gZcc7z8Ui4Ex4Th0Lg/PfnkYxRX8w+QM1FuMvtSvFV7o08pgkFQzKAvx9QJkQE5hKfKLyuGruPNn1dyUCqluB9cmJjBxpkoXUgfp9vhg4QzUt/4NzVLWXrQFiFt09s73p+Cn8EDurTL4Kzy02phTUmxGohLPrzkKGfTnyIoJetXfw/WiciStlX7thQBw6/p6joEvkRFdo4PQ0NsDN0pM52BFhfhgyehOmLbppE7OlhuAAW1D8VR8FLq1CNYEVD1aheC5B1rg491nbDF8stDHu89g1YFMvDc8BoNjI7QeM5Wza40QXy+tckJSpCKIDUx2vXS/VeeRirWzj8bk3Cy1eCbZlikxUpG7yTAjUYmJa3Rv/RvalUtMXnB2YRme/Px3vY+bk1ecEBOOxaN1d8Y0hwAgoW0oXvv2D5vl3jLord8Y+BIZIXeTYVyPKFGBaWM/BeJbBqO/Mgz//ekMPv/tPG6V3Z7JrQZw4p8CDC+t0HnDfKFPK6zYn8HNMZzM9eIKTFp7DInpWfjokY44cuE6dp3KwsoD+hfpWauhjwde/voEsgvvBARh/l54vGtzRIX4orGfAjFN/M3uV2xgcrhGjro6yFPPZufeKjO4gYCpDQZSM/Jx6XqRqLFKuZWsPpm5xbhv/s8WzSTXTInx8ZBjcLswzBkZC093N7PHYUsJMeH45LH2OvnOhnblqvl6M9eHO/9E+2aBotqq72YkxISjT+tQ3P3vHy0+r61+B8k1MPAlMuGFPq2w8kCmwZW3tW8fpqiy8clPZ0TPWMndZJg1rK2k5WRIOlv/yMa2kz+avWWzuW6/vrRfY9mFZVofukL9vTT/L3ZHLrHpE4fO52r+v2aQV1OQrwdGdGiCfsowg6Xp1MGVoZnxFFU2hnVoqrd/sUH6qv0ZCPHzEv1hQAYgwMcDC3f/bdZMsqESWMUVVfjm6GV8e+wy/tUzGm8MVpocgz3d3qnszt+Tdc920/s62ZGehdnbTll8nhX7L2BKX09RbbMLSrH/bC5+On0Vm49fsficZBsB3u4oLKmUZBa92tZ/LK3EwJfIBLmbDPNGthN1+9DSGavab1TkXJzl73jNnGGxO3KJzVP/bK/ple/5RRVYvj8Tyw2UhlIHkf+6PxpL92bo/T2YvP4EvNzlescrNkif/cNpzf/X/DAAQCd/tObX5vxeVlULeO8H4/WeBeHOdRMb/JozCy7VAr/9Z69h/9lcxLcM1qRaSVWf/MuDmQjzV+BqoeFFawAw90duAOTMCkoq4eUuQ1nl7Z+iumykJRj4EtUDYm8fWltHEwAS24Vh60lxxdb9vOS4WcaFca7MVO5r58hABPl6am2aYSvqt7tl+/QHvWrTNp3Um65gScmrmh8GPnmsvU4d3wBvD7QO98Oh8/lGx117Jvn383mit1FdujcD993VCN3vCjEamJqaBa8Z6GbmFmNd6kWtVARLF/h9uufc//57FgHe7hjbPQpfHLggyexefnEFXuoXjYUiFvaSk6vxghjbI9riwDczV1xqk6Mw8CUSqeas7Puj2um9zWxNHU21iEBvUX10jQpEZl4xA18Xp36vmvbtSfgpPLQWT6oDLXsEvTWZWhx0o7gCn/58FpP7tQIAlFdWY/XBTJzLvQVvDzeUVFRbdN4+rUPxYGwTtHxz+51zlVQYDXprsvSNXgDw1IpUhPp5omerRvDxckdkkA+eio+Cp7sbqqoFfPrzWYNVXyavPwHVlUJ8fyLL6AdnddWRRU90RKCvl96Z4PLKarz57R8G+ygoqcQnP5216Ps0pLyyCs84wba7ZCXZnfsj1izePCjy981RGPgSWeDB2Aj4eOr++lhaR7OmrlHBom47c8MMqulGSQWe/Px3zawgAKfeanvlgQy80OcuvL/jNJbty5BkJf3hzOsoq3TcB8GrN8vxzdHLmq/f234afds0xsl/CpBtorSdmN95tdqbuKhzr6/eLMMPf2TZ/Wee/Ms5WB4mkTNo6O2OorI7C6yX7T3vwNHYFgNfIgmZ2kJTXx1NnT5aBKGhj4fRbSxlMufJOyXnop4VbODl7rRBL3B71nfy+mPY9od0mwRcLSyRfDbTGtUCkKLKsfl51LnXjuTMrzUyrayyGjVvtLy33bK7H3WBc9VhIarj1HU0AejMgBiqo6mvj3kj2xk9D4NeMuVWmfOXx/tBwqAXAI5fulEvtpglsjdL04vqonof+F66dAm9evWCUqlEbGwsvv76a0cPieo5dZH2sADtdIawAIXo4vsJMeFYMroTwmqtWA/z98KEHlFSDpfIYaT+/LY+7R+JeySi+qbepzq4u7tj4cKF6NChA3JyctCpUycMHjwYvr6+jh4a1WMJMeHorwyzqhSRoT5SM/JF3dYcFBOGH9PFVYcgIiJyBfU+8A0PD0d4+O0ZtsaNGyMoKAj5+fkMfMnm5G4ygyXLrOlDbB7xp090QooqG29vSUfOTfuu6iciInJGDk912Lt3LxITExEREQGZTIbNmzfrtFm0aBGio6OhUCjQuXNn7Nu3z6JzHT58GNXV1WjWrJmVoyZyHHPyiBNiwvHTy73sOTwiIiKn5fDAt6ioCO3bt8enn36q9/ENGzZgypQpmD59Oo4dO4aePXti0KBBuHjxoqZN586dERMTo/PvypU72yLm5eXh6aefxtKlSw2OpaysDIWFhVr/iJyROXnENdMrau9yRURE5EocnuowaNAgDBo0yODjCxYswIQJE/DMM88AABYuXIidO3di8eLFmDt3LgDgyJEjRs9RVlaGESNG4I033kD37t0Ntps7dy5mzpxpwXdBZH+W5BHvnvoA0i8Xatr//OdVLP9Nt4bqkHahGNKuCZLW3t6m2ZxFSC1DfHAut9iC74iIiMi2HB74GlNeXo4jR45g2rRpWscHDBiAAwcOiOpDEASMHTsWffr0wVNPPWW07RtvvIGpU6dqvi4sLGRaBDk1c/OIa7ePbxmMVwe2xuqDmbiQX6y12xQALHbrpHeLVWMiGjLwJSIi5+TUgW9ubi6qqqoQGhqqdTw0NBTZ2eJWq+/fvx8bNmxAbGysJn949erVaNdOt06ql5cXvLx4K5hci6e7Gyb0bKH3sZqzytkFJZj9w2lcLyo3OAMcHqBAcANP2w2WiIjICk4d+KrJZNq3bgVB0DlmyH333YfqatcpzEwktZqzxN6ecjy/5iju7OiubUaiEjtPXbXr+IiIiMRy+OI2Y0JCQiCXy3Vmd3NycnRmgaWUnJwMpVKJuLg4m52DqC4ytKgOAD55rL3O5hzcbIOIiJyJUwe+np6e6Ny5M1JSUrSOp6SkGF2kZq2kpCSoVCqkpaXZ7BxEdVVCTDh+e70P1j3bDe+PupMy1F8ZptO2n55jREREjuLwVIdbt27h7Nmzmq8zMjJw/PhxBAUFoXnz5pg6dSqeeuopdOnSBfHx8Vi6dCkuXryIiRMnOnDURK5Nnf7QvjwAr31zUusxQbiTBGFqsw0iIiJ7cnjge/jwYfTu3VvztbqqwpgxY7Bq1So8+uijyMvLw6xZs5CVlYWYmBhs374dkZGRjhoyERlRM8BVb7ZhLC8YAGQyQGBkTERENubwwLdXr15aM0T6TJo0CZMmTbLTiIhISuq84Npl0YJ8PTCiQxP0U4ahc2Qgjly4jpybpcjMLca61IvILhRfQo2IiEgMhwe+RFT/idlso2Z94Rf63IWlv57D/J1/OWK4RERUTzn14jZHYVUHIstV19gG7uC5PFT972t1XvCwDk0Q3zLY6A5zcjcZRscznYmIiKTFwFcPVnUgssyO9CyknL5Tx/fxZYdw3/yfsSM9y+y+jAXG9iQDMLnvXY4eBhERSYCBLxFJIkWVjefXHEVphfaGMdkFpXh+zVGLgl+1UH/H7aiY/ERHvNT/Hs3XAQpmiBER1VUMfIlIEnO2/6m3aoP62MytKk3ag7l2T30Abw1pY/HYgNszt+Zq6OOBgTHhWuPudU8jq8ZBRLYX6O3h6CGQk2LgS0SSuFpYZvAxAUBWQSlSM/It6lvuJsPYHtEIs3Dmt6GPB0L9dXebM+VGcQU+/fks7pv/s+bYlhOWz1ybSx2sN/ThmziROfopQ/Hc/dGOHgY5IQa+enBxG5Ft5Ny0vESZ3E2Gd4a2tei5N4or8NHD7bHu2W745LEOWDlW/O/2x7v/1irDZgu+XnKM6xGFIF9PreNhAQosGd0J80a2s2jGmkzrEtnQ0UMgGyipqEKHZoGOHoZNBfnyA7ElmKymR1JSEpKSklBYWIiAgABHD4eo3mjsZ/6sa00JMeFYMroTpm06iRvFFWY9N7eoDMM6NAEAFJdXWjUOqX30cHskxITj30OUBku+LR7dCTO+P2V0Zt3ZuMkAC7NbbEb9AUI9rNPZN+0+Bk+5DA19PJFzs+78LOuabX9kYc+fOY4ehs2MiY/Exfxi7PnrmqOHUudwxpeIJBHq72VwVlIGIDzgdiBnrYSYcBz5d398NeFevNC7JYZ3iBD1PGuDbjEsmZV9qd/dSIgJB2C85FtCTDh2T31A8/XKsXH45LEO8HPQYruuUaZn06oF4K0hbfD+qHZ2GJE4YQEKLHqyk+brorIqu4/h6e5RmD6ktd3P62qKyu3/s7WX4vIqBr0W4owvEUnizcGtMWX9CZ2tidWh24xEpWQlyuRuMvRoFYIerUJQVS3g94x8ZBeU6l1cJ8PtYMdY0K1vzJZMVIYFKDBt0D2YvP4EgNsfBnIKywz2FerniRf6iC+VVvP63dsiCD6e7ngwNkIzS3zm6i18uuesyX7mj4zBtO/SrdomunW4P1Izr5tsF+Lnhf7KULz2zUnLT6ZHQx8P0bP+/gp3zBwWgzB/aT58iaHOy9Y3xtimDdGvTWMAJyQ/rzPOspP0fvjjiqOHUGcx8CUiSfRXhmHxaLnO1sRhAQrMSFRqZjWlJneTYUaiEs+vOWpR0P3JY+0x78e/dMb8WFwzfLz7jMnzvzWkDUL8vDSpCWWVVVAHNIY+DKiVVQlIUWVbdW3Us8TA7Q1DxAS+zYMb4F89o/HZ3gyLzxsZ5COqnTkz7bWDNn3BY/j/Xk/9lWE4dC4Pk746goJS46kr80bGYnDsnWt88Fye6DFZItDHA+8Nj8HAmHDNh5KGPh4Ys+J2bfjqWpHpyrFxuFFcjvyicgQ18ELjBl6ADMi9VYYU1VVs+8P0gkr1a4xBr2sorlU2ksRj4EtEkhGzNbGtzrt4dCeLgu7+yjA8GNtEZ8wAsD7tksmZ5LE9og1+f+oPA4ZykguKK/D8mqNYPLqTJB8MukYHITxAIWr2Wx0sL9uXoRMs+Xi4oaSi2mgfT8VH4fPfMkSd6/aHAe3H9H1A+fTxjgj09dL5ORh6PfVoFYJZw9tqZtj1ee7+aK2gFwCyC227WPFGcQWS1h7D4tEyzc+1Zkm82mX91LP3+gzr0ASDY7Lw7y3pyC8q1xyv/SEhLECBwTFhWL4/U/Q4Lb2zIZWX+rVC8yAfvP39Kdw08eGFSCoMfIlIUjVnIO3JmqDb0JitmUlW668MwzvfqwDoBr7C//qauVWF/sowqz8gmDv7/cZgJV4e0BqrD2bi7LVbWJd6CQAw96F2JtNWPN3dLLo+hmbYjX1AMfZ66q8Mg76UgSBfD7w7LAaDY7VzwHekZ2H2tlMG+zNk5dg4FJZWoLGfAteLyjFr2ylkG1hoaOrn+vfVmxjQNlT0uQfHhmNgjPZru3NkII5cuK71Wk/NyDcr8AUcG/xO7nc3ACD9coHZ43Zmjv5AQcYx8NUjOTkZycnJqKqqv4nxRPWR1EG3NTPJaqkZ+UZnGGvWOJZi7OaO2dPdDRN6tkBxeaUm8BWbtmLJ9TE0wy7FXYGawam+PnekZ+H5NUdFBSUNvT3w0SPtMeGLwwB0Z2UDfDzw5Oe/G3x+zZ9rQUk5Zm5VaR77bO95bD5+2azvTd9ru/bX6hl/Q+X3ZACCGngi79btmeOFj3XAvB//1P7Z+XuhsLQSxXZcGNZPKW6m+qluzbH60EXbD8hKYQEKvDWkDSatPWazc3h7yFFSwRjFEgx89WA5MyJSszZ9Q2ztYmtqHNcmRcqJ2D4sOZet7goYSxmoqhYwc6vKZNCrHvW8h9oZHWPuLXGlyFJU2Vi5P1PnvLYoS6ee8Z+45qjOY+rva2z3KHy0628At3ORf321t9bMcefIQHSds9uuga+pgB24ndv91oNtsft0js3ralvj9YH3YELPFvB0dwNsGPj2uCsYu0/X33JttsTAl4jIBGsCNbGLu6QutyZFcCm2D0elt5gjNSNfVMAU5OuJ90bEICEm3Gi9Z7E/r83Hr5gMti3dylufhJhwfPJYe52857AABYa2D8eqGjOrT69I0ywWVNe4Pnguz+wa2bUF+XrielG56Nv9xgJ2tbeGtNGk1xhr52jzd/6FLw9dwIxEpdV9De8QgVB/BT7be17nsT6tG+PwhetW/6xcEev4EhHZkHo2yx41jskwsTPq/x7SRlQKi5ifa5Cvh9aCNEMOiygLZ47bec+3vT+qHdY92w1vDVFi6d4M5NUaT3ZBKZ5fcxQ70m9XjrD0zkPN65AvMuhVnxO4E7AbMvuH09iRnoWEmHCM6xFl0RjtRX1NrRHg7YGPHumAyf1a6X1c7ibDvJHOUx+7LmHgS0RkQ+rZLEB3gwtb1Dgm/cTO0IYFeItqJ+bnOuJ/s6imXLtlu1v3D8ZGoGt0EGb/oD/NQ31s5lYVqqoFi+88WDJnPbFGwA1oB+y11QzQOzRrqDnujEGwFPP3L/a9y+jfBBluVwx5d3iMzmPhAbbfrKcuY+BLRGRj6kVgYbXekMICFJKVMiPjbDHzburn2s9IIFdTowa2DVRMpXnUXIhn6jrVZurzmszE49M2ndSkehhL+agZoFdX3Wk3QBmGRU900tR8rinQxwPP3R9tfAA2Ym3w2+uexib6v32GB+5upDn2VLdIrHu2G357vY+VZzctpIGnzc9hK8zxJSKyA0fVOKbbrN3oxBBjP9eqasFoXWW1LiK2f7aGOQssTV2nml+/PvAezN/5l9E+Te0OeKO4Ap/+fBaT+7UymfKhDtDf+j5dc+zxZYcQHqDAnOExCPD2xMHzuQBu55x3axGMFFU2AMs3anEUNxOfGNTXtWazuBr1uW3N18sdubdMp/E4I874EhHZiXoR2LAOTRDfMphBr53Zaubd0M/VWDpE7efbkrkLLI1dp5p5uMF+0sz6rTyQgapqQXTKx60y7YoT2QWlSFp7DDfLKvDKwNZ4ZeA96HFXCABolZGrS0y9ItSfJ2Q1Il+5qel1K9WXv1ec8dWDdXyJiOone8+8G6p1HOrvZZOSZvqYs6OfmqHrVHNLbqlSNG4UVyA1I9/i/gxtGCK2koclwvy9AMhwtdD4bL45vP+3Y6IYmhnfGsfkNp7KbNpQgQv5JbY9iR0w8NWDdXyJiOove5df0xdExjTxR7t3dtnl/JameZi6Tl2iAk2mcojdxSznZin6tDae12qMvo1gpKyNXZMMwDtD2wKA1dUbanKvcf2PXryOZkE+Btuqc3xrTvLKbDzja+v+7YWpDkRERDbm6DQXW6R5mKpsIQPwYKy4BX6N/RSSXJOawa41tbENjSTQx0NzvdTXNNTfy+Lz+CnuzD/WTOGYuvEE7pv/8/9ylA1zs2OqQ33BGV8iIiIXYIs0D1PbVvdXhmHf2RSDGy3UTLO4nUZxW+1UkNs1kU1v1lAz2DWV4mHItITW+OJgptb309DbA+N6ROGFPq20rldCTDh63BVi0ex9Ay85jvy7P+7+948AdGfGswtKdTYiUdOf6sDAVwwGvkRERC7CFmkepgLqeSPb4fk1R3UCO2NpFrunPoD0y4VaWyk/8MEes/KUa6Z4mCPAxx2/vd5H9AcESwPODx82vGEHYDxFRPNYjVO7MfAVhYEvERERWcVYQG1qVlhfmoW+/izJU1afe8b3p0QvJrxRXGHxB4RQfy/kFJYZDVrV20QDQLe5u80+BwDNlK8MTHUwFwNfIiIisikp0iwsCaDVzzMnHeF6cTmqqgWLZnLfHNwaU9afMLio76V+rfBCn1ZIUWXrnQUX6045szvH3LhqSxQGvkRERGRzUqRZWBpAmxPELt2bga0nsowG04b0V4Zh8Wi5TnAOAG3C/TC5392oqhYwc6v+LaTF0pvjyxlfURj4EhERUZ0hRQBtqsxadkEpnl9z1KKKF7WD88nrjwMAGv1v4Z0U9YUFdapDjWBXihxfL7kMk3rfhY93n7G6L2fFiXE9kpOToVQqERcX5+ihEBERkYQ+eay9Tlm32tRB8cytKlRVmz83W7N8nZo6LpWivrAm1aHGMXX/2/+4YnG/K8Z2xeR+d1v8/LqAga8eSUlJUKlUSEtLc/RQiIiISEL9lWH47fU+eGtIG6Ptam6KIQV1kCq2vnCwr6fWFtFaY1OnOmhN8sqwIz0Lk9Yes2h84QEKdLPjxi6OwlQHIiIicilyNxlC/MRtPCHVDnDqzSbE1BcO8vXAwTf6orK6Guotomu6s7jtTuRbLQiYtumkxePTVxWjPuKMLxEREbkcsTOv1uwAV5M6RhWz492cEe3g6W44RLuT43vn2KYj/xjcKMSUTx5rb9HufXURA18iIiJyOTU3u9BHhtu3/021M6ZmfvD14grN11JtIV0zcN5qRW5vf6W4raXrA6Y6EBERkcsxdlvf2KYYYu1Iz8LMrSrN10cuXMd983/WlEmzprbxnRzfO21vlVUZaE01MfAlIiIiqsHUphim7EjP0rtBRe0yaZaWZhOg3rmNzMXAl4iIiFyap1yGL8bfa/GucjUZ26BCwO1gdeZWFforw6xeTMY9K8zHwJeIiIhcmkxm/aYYaqY2qKhZJs3Sc97Zue1O5BvSwBN5t8oNVopo6ONh8eK3+oSL24iIiIgkIrb8mTVl0tTBbbVwJ8wd0u52WoahSeB5I9tZfL76hIEvERERuTQpUwbsUSZNEG7nEff96BfNsS8OXkCAjwcCfDy02oYHKLDEgq2X6yumOhARERFJxNQGFTLcXjxnTZm0v7IL8f6OP3X6LyiugADgpX6tEBXia3W+cn3EGV89kpOToVQqERcX5+ihEBERkQ3UrLFbVS1ofW0NUxtUANbvkrb7dI7RxXPr0y7hwdgIxLcMZtBbCwNfPZKSkqBSqZCWlubooRAREZHEdqRn4b75P2u+rqgScN/8n7EjPUuS/qXaoMKQW2WVBh+ruXiOdDHVgYiIiFxGiiobU9afMFlj11rWbFAhBWsWz9VnDHyJiIjIZczZrpsbC0hfYxeAxRtUSMGaxXP1GVMdiIiIyGVcLSwz+Fh9SBOQ4XYlB2sWz9VnDHyJiIiIanCWNAFzF9xJtXiuPmOqAxEREVENzpImcDjzulntwwIUmJGoZM1eIxj4EhERkcsI9fdCTmGZzWrsSmnPn1dFtXs6PhKDYsJZs1cEpjoQERGRy3hzcGsAtquxK5WqagFb/7giqu2gmHDW7BWJgS8RERG5jP7KMJvW2JVKakY+rhcbrterFuzr6TQz1HUBUx2IiIjIpTi6xq4YYhfYDesQ4VTjdnYMfImIiMjlOLLGrhhiF9j1V4bZeCT1C1MdiIiIiJxM1+gghPp7GW3Der3mY+BLRERE5GTkbjLNQrzaZP/75ywL8eoSBr5ERERETshQGoOzLcSrS5jjS0REROTkVo6NQ2FphVMuxKtLGPgSERERObl7WwTBx5Nhm7WY6kBERERELoGBrx7JyclQKpWIi4tz9FCIiIiISCIMfPVISkqCSqVCWlqao4dCRERERBJh4EtERERELoGBLxERERG5BAa+REREROQSGPgSERERkUtg4EtERERELoGBLxERERG5BAa+REREROQSGPgSERERkUtg4EtERERELoGBLxERERG5BAa+REREROQS3B09AGcmCAIAoLCw0OI+issrUV1WrOmn0lO6S86+2Tf7Zt/sm32zb/Ytlrqv2mr3ra9dZamA6rISnf+31s2bhZrzlZfIUe5VpfU9i6Fup47bjJEJYlq5qH/++QfNmjVz9DCIiIiIyIRLly6hadOmRtsw8DWiuroaV65cgZ+fH2QymaOH4xQKCwvRrFkzXLp0Cf7+/o4eTp3Ea2g9XkPr8Rpaj9fQeryG1uM1vD3Te/PmTURERMDNzXgWL1MdjHBzczP5ycFV+fv7u+wvmFR4Da3Ha2g9XkPr8Rpaj9fQeq5+DQMCAkS14+I2IiIiInIJDHyJiIiIyCUw8CWzeHl5YcaMGfDy8nL0UOosXkPr8Rpaj9fQeryG1uM1tB6voXm4uI2IiIiIXAJnfImIiIjIJTDwJSIiIiKXwMCXiIiIiFwCA18iIiIicgkMfF3MokWLEB0dDYVCgc6dO2Pfvn1G2//666/o3LkzFAoFWrRogSVLlui0+fbbb6FUKuHl5QWlUonvvvtO6/F33nkHMplM619YWJik35c9SX0NT506hYceeghRUVGQyWRYuHChJOd1Zo64hnwdGr+Gy5YtQ8+ePREYGIjAwED069cPqampVp/XmTniGvJ1aPwabtq0CV26dEHDhg3h6+uLDh06YPXq1Vaf15k54hrWt9ehWQRyGevXrxc8PDyEZcuWCSqVSpg8ebLg6+srXLhwQW/78+fPCz4+PsLkyZMFlUolLFu2TPDw8BC++eYbTZsDBw4IcrlcmDNnjnD69Glhzpw5gru7u3Do0CFNmxkzZght27YVsrKyNP9ycnJs/v3agi2uYWpqqvDKK68I69atE8LCwoSPP/7Y6vM6M0ddQ74OjV/DJ554QkhOThaOHTsmnD59Whg3bpwQEBAg/PPPPxaf15k56hrydWj8Gu7Zs0fYtGmToFKphLNnzwoLFy4U5HK5sGPHDovP68wcdQ3r0+vQXAx8XUjXrl2FiRMnah1r3bq1MG3aNL3tX3vtNaF169Zax5577jmhW7dumq8feeQRISEhQavNwIEDhccee0zz9YwZM4T27dtbOXrnYItrWFNkZKTeoM3c8zozR11Dvg7FX0NBEITKykrBz89P+OKLLyw+rzNz1DXk69C8aygIgtCxY0fh3//+t8XndWaOuob16XVoLqY6uIjy8nIcOXIEAwYM0Do+YMAAHDhwQO9zDh48qNN+4MCBOHz4MCoqKoy2qd3nmTNnEBERgejoaDz22GM4f/68td+S3dnqGtrivM7KUddQja/DO0xdw+LiYlRUVCAoKMji8zorR11DNb4O7zB2DQVBwE8//YS//voL999/v8XndVaOuoZq9eF1aAkGvi4iNzcXVVVVCA0N1ToeGhqK7Oxsvc/Jzs7W276yshK5ublG29Ts895778WXX36JnTt3YtmyZcjOzkb37t2Rl5cnxbdmN7a6hrY4r7Ny1DUE+Do09xpOmzYNTZo0Qb9+/Sw+r7Ny1DUE+DoUcw0LCgrQoEEDeHp6YsiQIfjvf/+L/v37W3xeZ+WoawjUn9ehJdwdPQCyL5lMpvW1IAg6x0y1r33cVJ+DBg3S/H+7du0QHx+Pli1b4osvvsDUqVPN/yYczBbX0BbndWaOuIZ8HYq/hu+//z7WrVuHX375BQqFwqrzOjNHXEO+Dk1fQz8/Pxw/fhy3bt3CTz/9hKlTp6JFixbo1auXxed1Zo64hvXtdWgOBr4uIiQkBHK5XOdTZE5Ojs6nR7WwsDC97d3d3REcHGy0jaE+AcDX1xft2rXDmTNnLPlWHMZW19AW53VWjrqG+vB1qP8afvjhh5gzZw52796N2NhYq87rrBx1DfXh61D3Grq5ueGuu+4CAHTo0AGnT5/G3Llz0atXL74OJbiG+tTV16ElmOrgIjw9PdG5c2ekpKRoHU9JSUH37t31Pic+Pl6n/a5du9ClSxd4eHgYbWOoTwAoKyvD6dOnER4ebsm34jC2uoa2OK+zctQ11IevQ91r+MEHH2D27NnYsWMHunTpYvV5nZWjrqE+fB2a/l0WBAFlZWUWn9dZOeoa6lNXX4cWsedKOnIsddmU5cuXCyqVSpgyZYrg6+srZGZmCoIgCNOmTROeeuopTXt12ZSXXnpJUKlUwvLly3XKpuzfv1+Qy+XCvHnzhNOnTwvz5s3TKWf28ssvC7/88otw/vx54dChQ8KDDz4o+Pn5ac5bl9jiGpaVlQnHjh0Tjh07JoSHhwuvvPKKcOzYMeHMmTOiz1uXOOoa8nVo/BrOnz9f8PT0FL755hutEkc3b94Ufd66xFHXkK9D49dwzpw5wq5du4Rz584Jp0+fFj766CPB3d1dWLZsmejz1iWOuob16XVoLga+LiY5OVmIjIwUPD09hU6dOgm//vqr5rExY8YIDzzwgFb7X375RejYsaPg6ekpREVFCYsXL9bp8+uvvxbuuecewcPDQ2jdurXw7bffaj3+6KOPCuHh4YKHh4cQEREhjBw5Ujh16pRNvj97kPoaZmRkCAB0/tXux9h56xpHXEO+Do1fw8jISL3XcMaMGaLPW9c44hrydWj8Gk6fPl246667BIVCIQQGBgrx8fHC+vXrzTpvXeOIa1jfXofmkAnC/7KiiYiIiIjqMeb4EhEREZFLYOBLRERERC6BgS8RERERuQQGvkRERETkEhj4EhEREZFLYOBLRERERC6BgS8RERERuQQGvkRERETkEhj4EhEREZFLYOBLRORCtm3bhhYtWiAuLg5///232c8fMWIEAgMDMWrUKBuMjojItrhlMRGRC7n77ruxaNEinDp1CgcPHsT69evNev6ePXtw69YtfPHFF/jmm29sNEoiItvgjC8RUT2Tl5eHxo0bIzMzU+exkJAQ3HXXXWjRogUCAgLM7rt3797w8/PT+9ioUaOwYMECs/skIrIXBr5ERE7o0qVLmDBhAiIiIuDp6YnIyEhMnjwZeXl5Jp87d+5cJCYmIioqSuexcePGoWXLlnj22WcxZ84cScf89ttv47333kNhYaGk/RIRSYWBLxGRkzl//jy6dOmCv//+G+vWrcPZs2exZMkS/PTTT4iPj0d+fr7B55aUlGD58uV45plndB6rrKzEJ598gtdeew03b95EYGCgTpvOnTsjJiZG59+VK1dMjjs2NhZRUVH46quvzPuGiYjsxN3RAyAiIm1JSUnw9PTErl274O3tDQBo3rw5OnbsiJYtW2L69OlYvHix3uf++OOPcHd3R3x8vM5jS5YsQYsWLZCUlIR58+bhzJkzuOeee7TaHDlyxKqxDx06FOvWrcPzzz9vVT9ERLbAGV8iIieSn5+PnTt3YtKkSZqgVy0sLAxPPvkkNmzYAEPrkvfu3YsuXbroHL9+/Tpmz56N+fPno2nTpggICMDx48clH3/Xrl2RmpqKsrIyyfsmIrIWA18iIidy5swZCIKANm3a6H28TZs2uH79Oq5du6b38czMTEREROgcf/vttzFixAhNv0qlEidOnDB7fAMHDsTDDz+M7du3o2nTpkhLS9N6vEmTJigrK0N2drbZfRMR2RpTHYiI6hD1TK+np6fex0tKSqBQKLSOqVQqrFmzBqdPn9Yci4mJsWjGd+fOnUYfV89SFxcXm903EZGtMfAlInIid911F2QyGVQqFYYPH67z+J9//olGjRqhYcOGep8fEhKC69evax176aWXcOPGDTRt2lRzrLq6GuHh4VIOHQA0C+8aNWoked9ERNZiqgMRkRMJDg5G//79sWjRIpSUlGg9lp2dja+++gpjx441+PyOHTtCpVJpvt62bRuOHDmCY8eO4fjx45p/y5cvx5UrVwymTFgqPT0dTZs2RUhIiKT9EhFJgTu3ERE5mTNnzqB79+5o06YN3n33XURHR+PUqVN49dVX4e7ujn379qFBgwZ6n3vy5El06tQJOTk5aNCgAWJiYjB+/Hi8/vrrWu0uXryIyMhIpKSkoF+/fpKNfezYsZDL5Vi+fLlkfRIRSYUzvkRETqZVq1ZIS0tDixYt8MgjjyAyMhKDBg3C3Xffjf379xsMegGgXbt26NKlCzZu3Ij//ve/uHHjBl544QWdds2aNYOPj4+klR1KS0vx3Xff4dlnn5WsTyIiKXHGl4ioDpgxYwYWLFiAXbt26a3RW9P27dvxyiuvID09HW5u9pvfSE5OxpYtW7Br1y67nZOIyBxc3EZEVAfMnDkTUVFR+P3333HvvfcaDWgHDx6MM2fO4PLly2jWrJndxujh4YH//ve/djsfEZG5OONLRERERC6BOb5ERERE5BIY+BIRERGRS2DgS0REREQugYEvEREREbkEBr5ERERE5BIY+BIRERGRS2DgS0REREQugYEvEREREbkEBr5ERERE5BIY+BIRERGRS2DgS0REREQu4f8BELn7WoRhAfAAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "roi_mask_path = _mask_path_ + 'ROI_masks/'\n", + "roi_mask_norm = roi_mask_path + 'general_roi_mask_norm.json'\n", + "f = open(roi_mask_norm) ### load json file\n", + "tmp = json.load(f);f.close()\n", + "mask_dict=json.loads(tmp);del tmp\n", + "roi_mask0 = np.array(mask_dict['roi_mask']) \n", + "old_cen=mask_dict['original center'] \n", + "\n", + "\n", + "setup_pargs['center']=center[::-1]\n", + "roi_mask, qval_dict, qwid_dict = get_roi_mask_qval_qwid_by_shift( \n", + " new_cen=center, new_mask= mask, old_cen=old_cen,\n", + " old_roi_mask=roi_mask0, limit_qnum= None,\n", + " setup_pargs=setup_pargs, geometry = 'saxs',\n", + " ) \n", + "\n", + "\n", + "qr = np.array( [qval_dict[k][0] for k in sorted( qval_dict.keys())] )\n", + "try:\n", + " qr_cal, qr_wid = get_QrQw_From_RoiMask( roi_mask, setup_pargs ) \n", + " print(len(qr)) \n", + " if (qr_cal - qr).sum() >=1e-3:\n", + " print( 'The loaded ROI mask might not be applicable to this UID: %s.'%uid)\n", + " print('Please check the loaded roi mask file.')\n", + "except:\n", + " print('Something is wrong with the roi-mask. Please check the loaded roi mask file.') \n", + " \n", + "plot_qIq_with_ROI( q_saxs, iq_saxs, np.unique(qr), logs=True, uid='uid=%s'%uid, \n", + " xlim=[q_saxs.min(), q_saxs.max()*1.02],#[0.0001,0.08],\n", + " ylim = [iq_saxs.min(), iq_saxs.max()*1.02], save=False, path=path)\n", + " \n", + "roi_mask = roi_mask * mask" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Save the polymask dictionary " + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "if False:\n", + "#if True:\n", + " mask_filename = 'XPCS_beam_mask.json'\n", + " gowrite=False\n", + " if os.path.isfile(path+mask_filename): # file exists, check if overwriting is ok\n", + " check = input(prompt='file %s exists. Overwrite existing file: y/n?'%(path+mask_filename))\n", + " if check == 'y':\n", + " gowrite = True\n", + " else: print('DATA NOT WRITTEN TO FILE!')\n", + " else: gowrite =True\n", + " if gowrite:\n", + " with open(path+mask_filename, \"w\") as outfile:\n", + " json.dump(polygon_dict, outfile)\n", + " print('metadata has been written to %s'%path+mask_filename)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (current)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.12" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/pipelines/masking_and_rois/Auto_ROI_Mask_Generator.ipynb b/pipelines/masking_and_rois/Auto_ROI_Mask_Generator.ipynb new file mode 100644 index 0000000..20226dc --- /dev/null +++ b/pipelines/masking_and_rois/Auto_ROI_Mask_Generator.ipynb @@ -0,0 +1,580 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/nsls2/software/common/jupyter/kernel_envs/current/.pixi/envs/default/lib/python3.12/site-packages/databroker/v1.py:75: UserWarning: In databroker 2.x, there are separate notions of 'server' and 'client', and register_handler(...) has no effect on the client. Likely this is being done for you on the server side, so you should not worry about this message unless you encounter trouble loading large array data.\n", + " warnings.warn(\n", + "/nsls2/software/common/jupyter/kernel_envs/current/.pixi/envs/default/lib/python3.12/site-packages/pyCHX/chx_generic_functions.py:827: SyntaxWarning: invalid escape sequence '\\m'\n", + " text_string = \"%s $\\mu$m\" % scalebar_size\n", + "/nsls2/software/common/jupyter/kernel_envs/current/.pixi/envs/default/lib/python3.12/site-packages/pyCHX/chx_correlationc.py:893: SyntaxWarning: invalid escape sequence '\\i'\n", + " g_2(q, \\\\tau) = \\\\beta_1[g_1(q, \\\\tau)]^{2} + g_\\infty\n", + "/nsls2/software/common/jupyter/kernel_envs/current/.pixi/envs/default/lib/python3.12/site-packages/pyCHX/chx_specklecp.py:1557: SyntaxWarning: invalid escape sequence '\\G'\n", + " P(K) =(\\frac{M}{})^M \\frac{K^(M-1)}{\\Gamma(M)}\\exp(-M\\frac{K}{})\n", + "/nsls2/software/common/jupyter/kernel_envs/current/.pixi/envs/default/lib/python3.12/site-packages/pyCHX/chx_specklecp.py:1634: SyntaxWarning: invalid escape sequence '\\e'\n", + " P(K) = \\frac{^K}{K!}\\exp(-)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[32mrunning on: jupyter_hub environment: standard\n", + "\u001b[0m\n", + "\u001b[36msetting '_base_path_' as /nsls2/data/chx/legacy/analysis/\u001b[0m\n", + "\u001b[36msetting '_base_path_pass_' as /nsls2/data/chx/proposals/\u001b[0m\n", + "\u001b[36msetting '_mask_path_' as /nsls2/data/chx/shared/CHX_Setup/Detector_masks/\n", + "\u001b[0m\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/patches/roi_nr_2019_3_0_1.py\" to fix ROI numbering for PHI-sliced data sets. Should get fixed in pyCHX...\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/patches/chx_outlier_detection.py\": this should become part of pyCHX.\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/patches/fix_get_sid_filenames.py\": this should be fixed and re-deployed in pyCHX.\n", + "\u001b[35m\n", + "environment dependent settings and patches:\u001b[0m\n", + "using \"%matplotlib inline\" for plotting\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/patches/polygonmask_fix.py\".\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/backups/chx_compress_05012024.py\": temporary fix for depreciated np.float.\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/backups/chx_correlationc_05012024.py\": temporary fix for depreciated np.float.\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/backups/Create_Report_05012024.py\": temporary fix for depreciated np.float.\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/backups/xpcs_timepixel_05012024.py\": temporary fix for depreciated np.float.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/nsls2/data2/chx/shared/CHX_Software/packages/pyCHX/backups/chx_correlationc_05012024.py:744: SyntaxWarning: invalid escape sequence '\\i'\n", + " g_2(q, \\\\tau) = \\\\beta_1[g_1(q, \\\\tau)]^{2} + g_\\infty\n", + "/nsls2/data2/chx/shared/CHX_Software/packages/pyCHX/backups/chx_generic_functions_05012024.py:727: SyntaxWarning: invalid escape sequence '\\m'\n", + " text_string='%s $\\mu$m'%scalebar_size\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/backups/chx_generic_functions_05012024.py\": temporary fix for depreciated np.float. np.int, collection.Iterable\n" + ] + } + ], + "source": [ + "from pyCHX.chx_packages import *\n", + "plt.rcParams.update({'figure.max_open_warning': 0})\n", + "plt.rcParams.update({ 'image.origin': 'lower' })\n", + "plt.rcParams.update({ 'image.interpolation': 'none' })\n", + "import itertools\n", + "from copy import deepcopy\n", + "import json\n", + "from termcolor import colored\n", + "%run /nsls2/data/chx/shared/CHX_Software/packages/environment_management/chx_analysis_setup.ipynb" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "mask_selection = 'phi_4x10deg_reduced_q' # select a mask to create, NOTE: if this is a new mask, need to enter parameters in mask_param_dict first!\n", + "\n", + "\n", + "mask_param_dict={'phi_12x30_rot45_fineQ':\n", + " {'flow_geometry':False,'inner_radius':24,'outer_radius':4000,'num_rings':150,'gap_ring_number':1,'width':'auto','edges':None,\n", + " 'ang_centers':np.array([15,45, 75, 105, 135, 165, 195, 225, 255, 285, 315, 345 ])-180,'ang_width':30-.01,\n", + " 'inner_angle':None,'outer_angle':None,'num_angles':None,'comment':'12x30deg phi-segments, rotated 45deg, i.e. there is e.g. a segment centered around 45deg, smaller Q-rings than \"12x30_rot45\"'},\n", + " \n", + " 'phi_4x20deg':\n", + " {'flow_geometry':False,'inner_radius':10,'outer_radius':4000,'num_rings':65,'gap_ring_number':1,'width':'auto','edges':None,\n", + " 'ang_centers':np.array([0,90,180,270])-180,'ang_width':20-.01,\n", + " 'inner_angle':-10,'outer_angle':350,'num_angles':None,'comment':'12x30deg phi-segments, rotated 45deg, i.e. there is e.g. a segment centered around 45deg, smaller Q-rings than \"12x30_rot45\"'},\n", + "\n", + " 'phi_4x10deg_reduced_q':\n", + " {'flow_geometry':False,'inner_radius':10,'outer_radius':2000,'num_rings':32,'gap_ring_number':1,'width':'auto','edges':None,\n", + " 'ang_centers':np.array([0,90,180,270])-180,'ang_width':10-.01,\n", + " 'inner_angle':-5,'outer_angle':355,'num_angles':None,'comment':'4x10deg phi-segments'},\n", + " \n", + " 'phi_12x30_rot45':\n", + " {'flow_geometry':False,'inner_radius':10,'outer_radius':4000,'num_rings':65,'gap_ring_number':1,'width':'auto','edges':None,\n", + " 'ang_centers':np.array([15,45, 75, 105, 135, 165, 195, 225, 255, 285, 315, 345 ])-180,'ang_width':30-.01,\n", + " 'inner_angle':None,'outer_angle':None,'num_angles':None,'comment':'12x30deg phi-segments, rotated 45deg, i.e. there is e.g. a segment centered around 45deg'},\n", + " \n", + " 'phi_16x22_5deg':\n", + " {'flow_geometry':False,'inner_radius':10,'outer_radius':4000,'num_rings':65,'gap_ring_number':1,'width':'auto','edges':None,\n", + " 'ang_centers':np.array([ 0, 22.5, 45., 67.5, 90., 112.5, 135., 157.5, 180., 202.5, 225., 247.5, 270., 292.5, 315., 337.5])-180,'ang_width':22.5-.01,\n", + " 'inner_angle':None,'outer_angle':None,'num_angles':None,'comment':'16x22.5deg phi-segments'},\n", + " \n", + " 'phi_12x15deg_flow': # THIS IS JUST AN EXAMPLE, this mask might have never been created\n", + " {'flow_geometry':True,'inner_radius':10,'outer_radius':4000,'num_rings':65,'gap_ring_number':1,'width':'auto','edges':None,\n", + " 'ang_centers':np.array([ 0., 15 ,30, 45., 60, 75, 90., 105, 120., 135, 150., 165, 180])-180,'ang_width':15-.01,\n", + " 'inner_angle':0,'outer_angle':180,'num_angles':12,'comment':'12x15deg phi-segments, combining centro-symmetric phi-segements'},\n", + " \n", + " 'super_wide': # THIS IS JUST AN EXAMPLE for a non Phi-sliced mask, this mask has never been created\n", + " {'flow_geometry':False,'inner_radius':10,'outer_radius':4000,'num_rings':25,'gap_ring_number':1,'width':'auto','edges':None,\n", + " 'ang_centers':None,'ang_width':None,\n", + " 'inner_angle':None,'outer_angle':None,'num_angles':None,'comment':'non-phi-sliced mask with super-wide rings'},\n", + " }\n", + "\n", + "###################################################################################################################################################\n", + "if mask_param_dict[mask_selection]['width']=='auto':\n", + " width = ( mask_param_dict[mask_selection]['outer_radius'] - mask_param_dict[mask_selection]['inner_radius'])/(mask_param_dict[mask_selection]['num_rings'] + mask_param_dict[mask_selection]['gap_ring_number'])\n", + "else:\n", + " width = mask_param_dict[mask_selection]['width']\n", + "\n", + "if mask_param_dict[mask_selection]['flow_geometry']:\n", + " ang_edges=None\n", + " ang_width = mask_param_dict[mask_selection]['ang_width']\n", + "else:\n", + " try:\n", + " ang_edges = get_non_uniform_edges( mask_param_dict[mask_selection]['ang_centers'], mask_param_dict[mask_selection]['ang_width'], number_rings=1 ) \n", + " ang_width = None\n", + " except:\n", + " ang_edges=None\n", + " ang_width=None\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Create the oversized ROI-mask" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "pixel_num_thres=100 # minimum number of pixels for an ROI (ROIs with smaller number of pixels will be discarded)\n", + "sx = 8000 # size of oversized ROI-mask\n", + "cen='auto' # center in oversized ROI-maks [x,y] -> recommended: 'auto', which picks the geometrical center\n", + "#######################################################################################################################\n", + "\n", + "shape = np.array( [sx,sx] )\n", + "if cen == 'auto':\n", + " cen = shape//2\n", + "else: \n", + " assert len(cen)==2, \"ERROR: cen must be either 'auto' or a list of the form [x,y]\"\n", + " cen=np.array(cen)\n", + "m = np.ones( shape )\n", + "\n", + "## update mask_param_dict with this information:\n", + "mask_param_dict[mask_selection]['ROI mask size']=sx\n", + "mask_param_dict[mask_selection]['original center']=cen\n", + "mask_param_dict[mask_selection]['pixel_num_thres']=pixel_num_thres\n", + "\n", + "# 'fake' setup parameters to create Q-mask\n", + "setup_pargs0 ={'uid': 'xxx',\n", + " 'dpix': 0.07500000356230885,\n", + " 'Ldet': 10113.499641418457,\n", + " 'lambda_': 1.2846771, \n", + " 'center': cen,\n", + " 'path': ''}\n", + " \n", + "center = setup_pargs0['center']\n", + "\n", + "#create Q-mask\n", + "roi_mask0, qr, qr_edge = get_ring_mask( m, inner_radius= mask_param_dict[mask_selection]['inner_radius'], \n", + " outer_radius = mask_param_dict[mask_selection]['outer_radius'] , width = width, num_rings = mask_param_dict[mask_selection]['num_rings'], edges=mask_param_dict[mask_selection]['edges'],\n", + " unit='pixel', pargs=setup_pargs0 )\n", + "\n", + "try:\n", + " if mask_param_dict[mask_selection]['ang_centers']==None and mask_param_dict[mask_selection]['ang_width']==None and mask_param_dict[mask_selection]['inner_angle']==None and mask_param_dict[mask_selection]['outer_angle']==None and mask_param_dict[mask_selection]['num_angles']==None:\n", + " geometry='saxs'\n", + " roi_mask0, good_ind = combine_two_roi_mask( roi_mask0, np.ones(np.shape(roi_mask0),dtype=int),pixel_num_thres=pixel_num_thres) \n", + "except:\n", + " geometry='ang_saxs'\n", + " \n", + "if geometry=='ang_saxs': #create Phi-mask\n", + " if np.min(ang_edges)<-180. or np.max(ang_edges)>180.:\n", + " fix_180_angle=True\n", + " else: fix_180_angle=False\n", + "\n", + " roi_mask_ang, ang_center, ang_edge = get_angular_mask( m, inner_angle= mask_param_dict[mask_selection]['inner_angle'], \n", + " outer_angle = mask_param_dict[mask_selection]['outer_angle'], width = ang_width, edges = ang_edges,\n", + " num_angles = mask_param_dict[mask_selection]['num_angles'], center = center, flow_geometry= mask_param_dict[mask_selection]['flow_geometry'],fix_180_angle=fix_180_angle ) \n", + " # combine Q- and Phi-mask\n", + " roi_mask0, good_ind = combine_two_roi_mask( roi_mask0, roi_mask_ang,pixel_num_thres=pixel_num_thres) " + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.imshow(roi_mask0,cmap='jet')\n", + "plt.axis('equal');plt.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Image reverse: True\n", + "Image rotate 90: False\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/nsls2/data2/chx/shared/CHX_Software/packages/pyCHX/backups/chx_generic_functions_05012024.py:727: SyntaxWarning: invalid escape sequence '\\m'\n", + " text_string='%s $\\mu$m'%scalebar_size\n" + ] + }, + { + "ename": "AttributeError", + "evalue": "'numpy.ndarray' object has no attribute 'md'", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mAttributeError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[5]\u001b[39m\u001b[32m, line 22\u001b[39m\n\u001b[32m 20\u001b[39m rot90=\u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[32m 21\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33m'\u001b[39m\u001b[33mImage reverse: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[33mImage rotate 90: \u001b[39m\u001b[38;5;132;01m%s\u001b[39;00m\u001b[33m'\u001b[39m%(reverse, rot90)) \n\u001b[32m---> \u001b[39m\u001b[32m22\u001b[39m imgs = \u001b[43mload_data\u001b[49m\u001b[43m(\u001b[49m\u001b[43m \u001b[49m\u001b[43muid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmd\u001b[49m\u001b[43m[\u001b[49m\u001b[33;43m'\u001b[39;49m\u001b[33;43mdetector\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mreverse\u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43mreverse\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrot90\u001b[49m\u001b[43m=\u001b[49m\u001b[43mrot90\u001b[49m\u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m 23\u001b[39m md.update( imgs.md );Nimg = \u001b[38;5;28mlen\u001b[39m(imgs);md[\u001b[33m'\u001b[39m\u001b[33mnumber of images\u001b[39m\u001b[33m'\u001b[39m] = Nimg\n\u001b[32m 24\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m reverse \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m rot90:\n", + "\u001b[36mFile \u001b[39m\u001b[32m/nsls2/data2/chx/shared/CHX_Software/packages/pyCHX/backups/chx_generic_functions_05012024.py:3310\u001b[39m, in \u001b[36mload_data\u001b[39m\u001b[34m(uid, detector, fill, reverse, rot90)\u001b[39m\n\u001b[32m 3307\u001b[39m imgs = \u001b[38;5;28mlist\u001b[39m(hdr.data(detector))\n\u001b[32m 3309\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(imgs[\u001b[32m0\u001b[39m])>=\u001b[32m1\u001b[39m:\n\u001b[32m-> \u001b[39m\u001b[32m3310\u001b[39m md = \u001b[43mimgs\u001b[49m\u001b[43m[\u001b[49m\u001b[32;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m.\u001b[49m\u001b[43mmd\u001b[49m\n\u001b[32m 3311\u001b[39m imgs = pims.pipeline(\u001b[38;5;28;01mlambda\u001b[39;00m img: img)(imgs[\u001b[32m0\u001b[39m])\n\u001b[32m 3312\u001b[39m imgs.md = md\n", + "\u001b[31mAttributeError\u001b[39m: 'numpy.ndarray' object has no attribute 'md'" + ] + } + ], + "source": [ + "# load some real data\n", + "uid = '2db38df2-5fb7-49c8-a03e-490c5747da8c' #.01s x200fr membrane on 4M\n", + "md = get_meta_data( uid )\n", + "limit_qnum = 60 # maximum number of ROIs to create (starts from smalles Q and Phi)\n", + "\n", + "#####################################################################################################\n", + "detectors = sorted(get_detectors(db[uid]))\n", + "if len(detectors) >1:\n", + " md['detector'] = detectors[1]\n", + " print( md['detector'])\n", + " \n", + "if md['detector'] =='eiger4m_single_image' or md['detector'] == 'image': \n", + " reverse= True\n", + " rot90= False\n", + "elif md['detector'] =='eiger500K_single_image': \n", + " reverse= True\n", + " rot90=True\n", + "elif md['detector'] =='eiger1m_single_image': \n", + " reverse= True\n", + " rot90=False\n", + "print('Image reverse: %s\\nImage rotate 90: %s'%(reverse, rot90)) \n", + "imgs = load_data( uid, md['detector'], reverse= reverse, rot90=rot90 )\n", + "md.update( imgs.md );Nimg = len(imgs);md['number of images'] = Nimg\n", + "if reverse and not rot90:\n", + " md['beam_center_y']=np.shape(imgs[0])[0]- md['beam_center_y']\n", + "if reverse and rot90:\n", + " xc=md['beam_center_y'];yc=md['beam_center_x']\n", + " yc=np.shape(imgs[0])[0]-yc\n", + " xc=np.shape(imgs[0])[1]-xc\n", + " md['beam_center_y']=yc;md['beam_center_x']=xc\n", + "inc_y0 = md['beam_center_y']\n", + "inc_x0 = md['beam_center_x']\n", + "dpix, lambda_, Ldet, exposuretime, timeperframe, center = check_lost_metadata(\n", + " md, Nimg, inc_x0 = inc_x0, inc_y0= inc_y0, pixelsize = 7.5*10*(-5) )\n", + "scat_geometry='saxs'\n", + "setup_pargs=dict(uid=uid, dpix= dpix, Ldet=Ldet, lambda_= lambda_, exposuretime=exposuretime,\n", + " timeperframe=timeperframe, center=center, path= None)\n", + "print_dict( setup_pargs )\n", + "img_samp_index = random.sample( range(len(imgs)), 20) \n", + "avg_img = get_avg_img( imgs, img_samp_index, plot_ = False, uid =uid)\n", + "mask=np.ones(np.shape(avg_img))\n", + "if md['detector'] =='eiger500K_single_image':\n", + " setup_pargs['center']=center[::-1]\n", + "if md['detector'] =='eiger4m_single_image':\n", + " setup_pargs['center']=center[::-1]\n", + "roi_mask, qval_dict, qwid_dict = get_roi_mask_qval_qwid_by_shift(new_cen=[0,0], new_mask= np.ones(np.shape(avg_img),dtype=int), old_cen=mask_param_dict[mask_selection]['original center'],old_roi_mask=roi_mask0, limit_qnum= limit_qnum, setup_pargs= setup_pargs, geometry = geometry) " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "Q_nr=0\n", + "phi_=0 # ignored if geometry == 'saxs'\n", + "\n", + "if geometry == 'ang_saxs':\n", + " [roi_nr,Q,phi,Q_list,phi_list]=get_roi_nr(qval_dict,q=Q_nr,phi=phi_,q_nr=True, phi_nr=False, q_thresh=1E-4, p_thresh=1, silent=True)\n", + " phi_str=np.round(phi,1)\n", + "else:\n", + " roi_nr=Q_nr\n", + " Q=qval_dict[Q_nr]\n", + " phi_str='N.A.'\n", + "print('roi #: %s'%roi_nr)\n", + "ind = roi_mask!=roi_nr\n", + "nroi_mask=deepcopy(roi_mask)\n", + "nroi_mask[ind]=1\n", + "nroi_mask[np.invert(ind)]=1000" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "show_img( avg_img*nroi_mask, vmin = .001, vmax = 1000, logs=True, aspect=1, #save_format='tif',\n", + " image_name='roi #: %s Q: %s $\\Phi$: %s'%(roi_nr,np.round(Q,4),phi_str) , save=False, path=None, cmap=cmap_albula,center=center)\n", + "extend=200\n", + "plt.xlim(center[0]-extend/2,center[0]+extend/2,);plt.ylim(center[1]-extend/2,center[1]+extend/2,)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "Q_nr=[0,1,2,]\n", + "extend=600 # show region of extend x extend pixels around center\n", + "\n", + "##################################################################################\n", + "nrows=int(np.ceil(len(Q_nr)/3))\n", + "fig,ax=plt.subplots(nrows,3,figsize=(22,nrows*4.5))\n", + "\n", + "\n", + "for i,q_nr in enumerate(Q_nr):\n", + " sum_mask=np.zeros(np.shape(avg_img))*np.nan\n", + " plt.subplot(nrows,3,1+i)\n", + " if geometry == 'ang_saxs':\n", + " for phi_ in mask_param_dict[mask_selection]['ang_centers']:\n", + " try:\n", + " [roi_nr,Q,phi,Q_list,phi_list]=get_roi_nr(qval_dict,q=q_nr,phi=phi_,q_nr=True, phi_nr=False, q_thresh=1E-4, p_thresh=3, silent=True)\n", + " #print('roi #: %s Q: %s Phi: %s'%(roi_nr,Q,phi))\n", + " ind = roi_mask==roi_nr+1\n", + " sum_mask[ind]=phi_\n", + " except:\n", + " pass\n", + " elif geometry == 'saxs':\n", + " ind = roi_mask==q_nr+1\n", + " sum_mask[ind]=q_nr+1\n", + " avg_img_=deepcopy(avg_img)\n", + " ind=avg_img>np.max(avg_img[:,5])*.9\n", + " avg_img_[ind]=np.nan\n", + " plt.imshow(avg_img_,norm='log',vmin=.1,vmax=1000,cmap = cmap_albula,alpha=.5)\n", + " # cm='viridis'\n", + " # cm='Spectral'\n", + " cm='jet'\n", + " plt.imshow(sum_mask,cmap=cm,alpha=.7)\n", + " if geometry =='ang_saxs':\n", + " plt.colorbar(ticks=mask_param_dict[mask_selection]['ang_centers'],label='$\\Phi$-centers [deg.]')\n", + "\n", + " plt.xlim(center[0]-extend/2,center[0]+extend/2,);plt.ylim(center[1]-extend/2,center[1]+extend/2,)\n", + " plt.title('Q #: %s mask: %s'%(q_nr,mask_selection))\n", + " pc=i+1\n", + "for i in range(pc+1,nrows*3+1):\n", + " plt.subplot(nrows,3,i);plt.axis('off')\n", + "plt.tight_layout()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[32mSAVED current ROI mask as /nsls2/data/chx/shared/CHX_Setup/Detector_masks/ROI_masks/general_roi_mask_phi_4x10deg_reduced_q.json\u001b[0m\n" + ] + } + ], + "source": [ + "if True:\n", + " # create .json filename\n", + " roi_mask_path=_mask_path_+'ROI_masks/'\n", + " roi_maskname='general_roi_mask_'+mask_selection+'.json'\n", + " json_file=roi_mask_path+roi_maskname\n", + " if not os.path.isfile(json_file): #roi_maskfle doesn't exist already -> good to save!\n", + " save_dict={};save_dict['roi maskname']=mask_selection\n", + " for k in list(mask_param_dict[mask_selection]):\n", + " if type(mask_param_dict[mask_selection][k]) == type(np.array([])):\n", + " save_dict[k]=mask_param_dict[mask_selection][k].tolist()\n", + " else:\n", + " save_dict[k]=mask_param_dict[mask_selection][k]\n", + " save_dict['roi_mask']=roi_mask0.tolist()\n", + " with open(json_file, \"w\") as outfile:\n", + " json.dump(json.dumps(save_dict), outfile)\n", + " print(colored('SAVED current ROI mask as %s'%json_file,'green'))\n", + " else:\n", + " print(colored('ERROR: file %s already exist, cannot overwrite it as it might be used by many users...'%json_file,'red'))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "_STOP:_the_END" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "### How to load ROI-mask\n", + "# f = open(json_file) ### load json file\n", + "# tmp = json.load(f);f.close()\n", + "# mask_dict=json.loads(tmp);del tmp\n", + "# mask_dict['roi_mask']=np.array(mask_dict['roi_mask'])" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### saving current mask in legacy format (.npy) and in legacy location" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "if False:\n", + " # create .npy filename\n", + " legacy_maskfile_path = '/nsls2/data/chx/shared/masks/'\n", + " npy_file = legacy_maskfile_path+'general_roi_mask_'+mask_selection+'.npy'\n", + " if not os.path.isfile(npy_file): #roi_maskfle doesn't exist already -> good to save!\n", + " np.save(npy_file, roi_mask0)\n", + " print('Saved mask %s as legacy mask %s'%(mask_selection,npy_file))\n", + " else:\n", + " print(colored('ERROR: file %s already exist, cannot overwrite it as it might be used by many...'%npy_file,'red'))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### saving legacy masks as json files [not all metadata is known...]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "legacy_mask_param_dict={'norm':\n", + " {'roi_maskname':'norm','flow_geometry':False,'inner_radius':10,'outer_radius':4000,'num_rings':'unknown','gap_ring_number':'unknown','width':'unknown','edges':'unknown',\n", + " 'ang_centers':'unknown','ang_width':'unknown',\n", + " 'inner_angle':'unknown','outer_angle':'unknown','num_angles':'unknown','ROI mask size':8000,'original center':[4000,4000],'pixel_num_thres':'unknown','comment':'isotropic Q-mask without Phi-slicing, normal width rings, created from legacy .npy file'},\n", + " 'wide':\n", + " {'roi_maskname':'wide','flow_geometry':False,'inner_radius':10,'outer_radius':4000,'num_rings':'unknown','gap_ring_number':'unknown','width':'unknown','edges':'unknown',\n", + " 'ang_centers':'unknown','ang_width':'unknown',\n", + " 'inner_angle':'unknown','outer_angle':'unknown','num_angles':'unknown','ROI mask size':8000,'original center':[4000,4000],'pixel_num_thres':'unknown','comment':'isotropic Q-mask without Phi-slicing, wide rings, created from legacy .npy file'},\n", + " 'phi_12x_15deg_flow':\n", + " {'roi_maskname':'phi_12x15deg_flow','flow_geometry':True,'inner_radius':10,'outer_radius':4000,'num_rings':'unknown','gap_ring_number':'unknown','width':'unknown','edges':'unknown',\n", + " 'ang_centers':'unknown','ang_width':'unknown',\n", + " 'inner_angle':'unknown','outer_angle':'unknown','num_angles':'unknown','ROI mask size':8000,'original center':[4000,4000],'pixel_num_thres':'unknown','comment':'12x15deg mask for flow, created from legacy .npy file'},\n", + " 'phi_12x_30deg_flow':\n", + " {'roi_maskname':'phi_12x_30deg_flow','flow_geometry':True,'inner_radius':10,'outer_radius':4000,'num_rings':'unknown','gap_ring_number':'unknown','width':'unknown','edges':'unknown',\n", + " 'ang_centers':'unknown','ang_width':'unknown',\n", + " 'inner_angle':'unknown','outer_angle':'unknown','num_angles':'unknown','ROI mask size':8000,'original center':[4000,4000],'pixel_num_thres':'unknown','comment':'12x30deg mask for flow, created from legacy .npy file'},\n", + " 'phi_12x_30deg':\n", + " {'roi_maskname':'phi_12x_30deg','flow_geometry':False,'inner_radius':10,'outer_radius':4000,'num_rings':'unknown','gap_ring_number':'unknown','width':'unknown','edges':'unknown',\n", + " 'ang_centers':'unknown','ang_width':'unknown',\n", + " 'inner_angle':'unknown','outer_angle':'unknown','num_angles':'unknown','ROI mask size':8000,'original center':[4000,4000],'pixel_num_thres':'unknown','comment':'12x30deg mask, created from legacy .npy file'},\n", + " 'phi_4x_20deg':\n", + " {'roi_maskname':'phi_4x_20deg','flow_geometry':False,'inner_radius':10,'outer_radius':4000,'num_rings':'unknown','gap_ring_number':'unknown','width':'unknown','edges':'unknown',\n", + " 'ang_centers':'unknown','ang_width':'unknown',\n", + " 'inner_angle':'unknown','outer_angle':'unknown','num_angles':'unknown','ROI mask size':8000,'original center':[4000,4000],'pixel_num_thres':'unknown','comment':'4x20deg mask, created from legacy .npy file'},\n", + " \n", + " }\n", + "\n", + "legacy_mask_path = _base_path_+'masks/' \n", + "\n", + "if False:\n", + " for m in list(legacy_mask_param_dict.keys()):\n", + " roi_maskname='general_roi_mask_'+m+'.json'\n", + " json_file=roi_mask_path+roi_maskname\n", + " save_dict=legacy_mask_param_dict[m]\n", + " lm = np.load(legacy_mask_path+'general_roi_mask_%s.npy'%m)\n", + " save_dict['roi_mask']=lm.tolist()\n", + " del lm\n", + " if not os.path.isfile(json_file): #roi_maskfle doesn't exist already -> good to save!\n", + " with open(json_file, \"w\") as outfile:\n", + " json.dump(json.dumps(save_dict), outfile)\n", + " print(colored('SAVED current ROI mask as %s'%json_file,'green'))\n", + " else:\n", + " print(colored('ERROR: file %s already exist, cannot overwrite it as it might be used by many...'%json_file,'red'))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (current)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/pipelines/masking_and_rois/Detector_Masks.ipynb b/pipelines/masking_and_rois/Detector_Masks.ipynb new file mode 100644 index 0000000..3ca1732 --- /dev/null +++ b/pipelines/masking_and_rois/Detector_Masks.ipynb @@ -0,0 +1,344 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Detector Mask Pipeline\n", + "This notebook creates detector specific masks for:\n", + "- module gaps\n", + "- chip gaps\n", + "- bad pixels" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## CHX Olog NoteBook\n", + "CHX Olog (https://logbook.nsls2.bnl.gov/11-ID/) [need VPN from offsite location]\n" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "OBJECT CACHE: Will use up to 121_499_065_958 bytes (15% of total physical RAM)\n", + "/nsls2/conda/envs/2024-1.0-py311-tiled-rc1/lib/python3.11/site-packages/databroker/v1.py:72: UserWarning: In databroker 2.x, there are separate notions of 'server' and 'client', and register_handler(...) has no effect on the client. Likely this is being done for you on the server side, so you should not worry about this message unless you encounter trouble loading large array data.\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[32mrunning on: jupyter_hub environment: standard\n", + "\u001b[0m\n", + "\u001b[36msetting '_base_path_' as /nsls2/data/chx/legacy/analysis/\u001b[0m\n", + "\u001b[36msetting '_mask_path_' as /nsls2/data/chx/shared/CHX_Setup/Detector_masks/\n", + "\u001b[0m\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/patches/roi_nr_2019_3_0_1.py\" to fix ROI numbering for PHI-sliced data sets. Should get fixed in pyCHX...\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/patches/chx_outlier_detection.py\": this should become part of pyCHX.\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/patches/fix_get_sid_filenames.py\": this should be fixed and re-deployed in pyCHX.\n", + "\u001b[35m\n", + "environment dependent settings and patches:\u001b[0m\n", + "using \"%matplotlib inline\" for plotting\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/patches/polygonmask_fix.py\".\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/chx_compress.py\": temporary fix for depreciated np.float.\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/chx_correlationc.py\": temporary fix for depreciated np.float.\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/Create_Report.py\": temporary fix for depreciated np.float.\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/xpcs_timepixel.py\": temporary fix for depreciated np.float.\n", + "ran \"%run -i /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/chx_generic_functions.py\": temporary fix for depreciated np.float. np.int, collection.Iterable\n" + ] + } + ], + "source": [ + "from pyCHX.chx_packages import *\n", + "%matplotlib notebook\n", + "plt.rcParams.update({'figure.max_open_warning': 0})\n", + "plt.rcParams.update({ 'image.origin': 'lower' })\n", + "plt.rcParams.update({ 'image.interpolation': 'none' })\n", + "from termcolor import colored\n", + "from time import strftime\n", + "from pyCHX.chx_xpcs_xsvs_jupyter_V1 import *\n", + "from pyCHX.chx_generic_functions import RemoveHot,create_multi_rotated_rectangle_mask\n", + "import json\n", + "\n", + "%run /nsls2/data/chx/shared/CHX_Software/packages/environment_management/chx_analysis_setup.ipynb" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### DARK image series to find bad pixels on the detector (typically 5 images, 1s)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "uid = '66cca048' # (scan num: 134037) (Measurement: dark images 4M for mask )\n", + "#uid = '17646add' # (scan num: 134038) (Measurement: dark images 500k for mask )" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Detector is: eiger500K_single_image\n", + "scan_id, full-uid, data path are: 134038--17646add-3c7e-4212-8d58-08d6ec50d227--/nsls2/data/chx/legacy/data/2023/05/31/d04b833a-8fbe-455d-97e8_434_data_000001.h5\n", + "detector: eiger500K -> Image reverse: True, Image rotate 90: True\n" + ] + } + ], + "source": [ + "md = get_meta_data( uid )\n", + "detector = get_detector( db[uid ] )\n", + "print ('Detector is: %s'%detector )\n", + "sud = get_sid_filenames(db[uid])\n", + "\n", + "print ('scan_id, full-uid, data path are: %s--%s--%s'%(sud[0], sud[1], sud[2][0] ))\n", + "\n", + "## image rotations from analysis pipeline:\n", + "if md['detector'] =='eiger4m_single_image' or md['detector'] == 'image': \n", + " reverse= True\n", + " rot90= False\n", + "elif md['detector'] =='eiger500K_single_image': \n", + " reverse= True\n", + " rot90=True\n", + "elif md['detector'] =='eiger1m_single_image': \n", + " reverse= True\n", + " rot90=False\n", + "print('detector: %s -> Image reverse: %s, Image rotate 90: %s'%(md['detector'].split('_')[0],reverse, rot90))" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The data are: (Pipeline,) processed through proc_func. Original repr:\n", + " (Pipeline,) processed through proc_func. Original repr:\n", + " (Images,) processed through proc_func. Original repr:\n", + " \n", + " Length: 5 frames\n", + " Frame Shape: 514 x 1030\n", + " Pixel Datatype: uint32\n" + ] + } + ], + "source": [ + "imgs = load_data( uid, detector, reverse= reverse,rot90=rot90 )\n", + "#imgs = load_data( uid, detector, reverse= True )\n", + "md.update( imgs.md );Nimg = len(imgs);\n", + "#if 'number of images' not in list(md.keys()):\n", + "md['number of images'] = Nimg\n", + "\n", + "pixel_mask = 1- np.int_( np.array( imgs.md['pixel_mask'], dtype= bool) )\n", + "print( 'The data are: %s' %imgs )\n", + "\n", + "if detector =='eiger1m_single_image':\n", + " chip_mask_name ='%sEiger1M_Chip_Mask.npy'%(_mask_path_+'chip_masks/')\n", + " chip_mask=np.load( chip_mask_name )\n", + " bad_pixel_list_name = 'None'\n", + "elif detector =='eiger4m_single_image' or md['detector'] == 'image':\n", + " chip_mask_name = '%sEiger4M_Chip_Mask.npy'%(_mask_path_+'chip_masks/')\n", + " chip_mask= np.array(np.load(chip_mask_name), dtype=bool)\n", + " bad_pixel_list_name='%s2019_2/BadPix_4M.npy'%_base_path_\n", + " BadPix = np.load(bad_pixel_list_name ) \n", + " pixel_mask.ravel()[BadPix] = 0\n", + " pixel_mask = reverse_updown( pixel_mask )\n", + "elif detector =='eiger500K_single_image':\n", + " chip_mask_name = '%sEiger500K_Chip_Mask.npy'%(_mask_path_+'chip_masks/')\n", + " chip_mask= np.load( chip_mask_name )\n", + " chip_mask = np.rot90(chip_mask)\n", + " pixel_mask = np.rot90( pixel_mask )\n", + " bad_pixel_list_name = 'None'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Check for bad pixels in dark images -> pixels that have counts >1 in at least 2 frames are considered 'bad' (this should avoid catching cosmic rays as 'bad' pixels)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "s=np.shape(imgs);fr=s[0];dims=(s[1],s[2])\n", + "darks_mask = np.zeros(s)\n", + "darks_mask_ = np.zeros(s)\n", + "for f in range(fr):\n", + " darks_mask_[f][(imgs[f]*pixel_mask*chip_mask)>0]=1\n", + " darks_mask[f][(imgs[f]*chip_mask)>0]=1\n", + "dark_mask = np.ones(dims)\n", + "dark_mask_ = np.ones(dims)\n", + "dark_mask[np.sum(darks_mask,axis=0)>2]=0\n", + "dark_mask_[np.sum(darks_mask_,axis=0)>2]=0" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig,ax = plt.subplots(1,5,figsize = (25,5))\n", + "plt.suptitle('counts >0 in dark images',y=.9)\n", + "for i in range(np.max([5,darks_mask.shape[0]])):\n", + " plt.subplot(1,5,i+1)\n", + " plt.imshow(chip_mask)\n", + " masked=np.nonzero(darks_mask[i]>0)\n", + " plt.plot(masked[1],masked[0],'r+')" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[]" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig,ax = plt.subplots(2,3,figsize = (30,22))\n", + "plt.suptitle('Detector Masks for %s'%detector.split('_')[0], fontsize=20,y=.92)\n", + "\n", + "plt.subplot(2,3,1);plt.title('chip mask \\n%s'%chip_mask_name)\n", + "plt.imshow(chip_mask)\n", + "\n", + "plt.subplot(2,3,2);plt.title('pixel mask with bad pixels from:\\n%s'%bad_pixel_list_name)\n", + "plt.imshow(chip_mask)\n", + "masked=np.nonzero(pixel_mask+~chip_mask<1)\n", + "plt.plot(masked[1],masked[0],'r+')\n", + "\n", + "plt.subplot(2,3,3);plt.title('bad pixels masked by function \"mask_badpixels\"')\n", + "bad_pix_mask = np.ones(pixel_mask.shape)\n", + "bad_pix_mask = mask_badpixels( pixel_mask, md['detector'])\n", + "plt.imshow(bad_pix_mask*chip_mask)\n", + "masked=np.nonzero(bad_pix_mask+~chip_mask<1)\n", + "plt.plot(masked[1],masked[0],'r+')\n", + "\n", + "plt.subplot(2,3,4);plt.title('hot pixels in >2 dark images')\n", + "plt.imshow(dark_mask*chip_mask)\n", + "hot_dark=np.nonzero(dark_mask+~chip_mask<1)\n", + "plt.plot(hot_dark[1],hot_dark[0],'r+')\n", + "\n", + "plt.subplot(2,3,5);plt.title('hot pixels in >2 dark images NOT in pixel mask')\n", + "plt.imshow(chip_mask)\n", + "hot_dark=np.nonzero(dark_mask_+~chip_mask<1)\n", + "plt.plot(hot_dark[1],hot_dark[0],'r+')\n", + "\n", + "plt.subplot(2,3,6);plt.title('combined mask')\n", + "plt.imshow(chip_mask*pixel_mask*bad_pix_mask*dark_mask)\n", + "hot_dark=np.nonzero(pixel_mask*bad_pix_mask*dark_mask_+~chip_mask<1)\n", + "cmap=plt.colormaps['viridis']\n", + "plt.plot(hot_dark[1],hot_dark[0],'+',color=cmap(0))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[31mfile /nsls2/data/chx/shared/CHX_Setup/Detector_masks/pixel_masks/detector_mask_eiger500K.json exists and should not be overwritten.\u001b[0m\n", + "Rename existing file, e.g. as detector_mask_eiger500K, and try saving again._04172024.json\n", + "\u001b[31mDATA NOT WRITTEN TO FILE!\u001b[0m\n" + ] + } + ], + "source": [ + "if True:\n", + " det_mask_dict = {'uid':md['uid'],'detector':md['detector'].split('_')[0],'masks':{'dark_mask':np.array(dark_mask,dtype=bool).tolist(),'pixel_mask':np.array(pixel_mask*bad_pix_mask,dtype=bool).tolist(),'chip_mask':np.array(chip_mask,dtype=bool).tolist()}}\n", + " mask_filename = 'detector_mask_%s.json'%det_mask_dict['detector']\n", + " path = _mask_path_+'pixel_masks/'\n", + " if os.path.isfile(path+mask_filename): # file exists, check if overwriting is ok\n", + " print(colored('file %s exists and should not be overwritten.'%(path+mask_filename),'red'))\n", + " print('Rename existing file, e.g. as %s, and try saving again.'%(mask_filename.split('.')[0]+'_%s.json'%strftime('%m%d%Y',time.localtime())))\n", + " print(colored('DATA NOT WRITTEN TO FILE!','red'))\n", + " else: \n", + " with open(path+mask_filename, \"w\") as outfile:\n", + " json.dump(det_mask_dict, outfile)\n", + " print(colored('metadata has been written to %s'%path+mask_filename,'green'))\n", + " \n", + " \n", + " " + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (current)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.14" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/pipelines/masking_and_rois/Detector_Masks_Add_Pixels.ipynb b/pipelines/masking_and_rois/Detector_Masks_Add_Pixels.ipynb new file mode 100644 index 0000000..5b6895b --- /dev/null +++ b/pipelines/masking_and_rois/Detector_Masks_Add_Pixels.ipynb @@ -0,0 +1,188 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "f6808051-2a78-471c-8171-42df2b06585d", + "metadata": {}, + "outputs": [], + "source": [ + "import json\n", + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "fpath = \"/nsls2/data2/chx/shared/CHX_Setup/Detector_masks/pixel_masks/detector_mask_eiger4m.json\"\n", + "\n", + "with open(fpath, \"r\") as f:\n", + " mask_data = json.load(f)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "2c2284c6-2aff-47db-a44a-db7bb06ea3a7", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "mask_arr = np.array(mask_data['masks']['pixel_mask'])\n", + "\n", + "plt.figure()\n", + "plt.pcolormesh(mask_arr)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "29ab968f-c54c-4f2e-a2a9-c5f56ce81a0d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[(1010, 1119), (1010, 1118), (1010, 1120), (1010, 1117)]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pixels_to_add = [[938,1141], [1326,1408], [937,1141], [939,1141]]\n", + "\n", + "x0, y0 = 1117, 1153\n", + "x1, y1 = 1120, 1156\n", + "\n", + "pixels_to_add = [[x, y] for x in range(x0, x1 + 1)\n", + " for y in range(y0, y1 + 1)]\n", + "\n", + "\"\"\"\n", + "pixels_to_add = [(1117, 1011),\n", + " (1118, 1011),\n", + " (1119, 1011),\n", + " (1120, 1011),\n", + " (1117, 1012),\n", + " (1118, 1012),\n", + " (1119, 1012),\n", + " (1120, 1012),\n", + " (1117, 1013),\n", + " (1118, 1013),\n", + " (1119, 1013),\n", + " (1120, 1013)]\n", + "\n", + "\n", + "[(1117, 1011),\n", + " (1118, 1011),\n", + " (1119, 1011),\n", + " (1120, 1011),\n", + " (1117, 1012),\n", + " (1118, 1012),\n", + " (1119, 1012),\n", + " (1120, 1012),\n", + " (1117, 1013),\n", + " (1118, 1013),\n", + " (1119, 1013),\n", + " (1120, 1013)]\n", + " \"\"\"\n", + "\n", + "x = [1013, 1013, 1012, 1011, 1012, 1013, 1013, 1011, 1012, 1011, 1011, 1012]\n", + "y = [1118, 1117, 1119, 1118, 1120, 1119, 1120, 1119, 1118, 1120, 1117, 1117]\n", + "\n", + "\n", + "x = [1010, 1010, 1010, 1010]\n", + "y = [1119, 1118, 1120, 1117]\n", + "\"\"\"\n", + "(1010, 1119) : 5264.0\n", + "(1010, 1118) : 5264.0\n", + "(1010, 1120) : 3147.8\n", + "(1010, 1117) : 752.0\n", + "\"\"\"\n", + "\n", + "pixels_to_add = list(zip(x,y))\n", + "\n", + "pixels_to_add" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "61e400cf-222b-433f-a71d-b9f7d2d7fa7a", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Masked out 4 pixels!\n" + ] + } + ], + "source": [ + "num_pix_modified = 0\n", + "\n", + "for pixel in pixels_to_add:\n", + " curr_val = mask_data['masks']['pixel_mask'][pixel[0]][pixel[1]]\n", + " if curr_val == True:\n", + " mask_data['masks']['pixel_mask'][pixel[0]][pixel[1]] = False\n", + " num_pix_modified += 1\n", + " \n", + "print(f\"Masked out {num_pix_modified} pixels!\")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "f499893e-0afe-423f-a50e-f38d90d29fa3", + "metadata": {}, + "outputs": [], + "source": [ + "save = True\n", + "\n", + "if save:\n", + " with open(fpath, \"w\") as f:\n", + " json.dump(mask_data, f)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "60c1883b-b9a2-4867-8c38-a1eb4782e700", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (current)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.13" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/pipelines/masking_and_rois/WAXS_Geometry_Calibration.ipynb b/pipelines/masking_and_rois/WAXS_Geometry_Calibration.ipynb new file mode 100644 index 0000000..01ba9d4 --- /dev/null +++ b/pipelines/masking_and_rois/WAXS_Geometry_Calibration.ipynb @@ -0,0 +1,1293 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "03986e9e-3929-4e70-8fdb-dc13214a1fdc", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Tiled version 0.1.0a120\n", + "/nsls2/conda/envs/2024-2.0-py311-tiled/lib/python3.11/site-packages/databroker/v1.py:72: UserWarning: In databroker 2.x, there are separate notions of 'server' and 'client', and register_handler(...) has no effect on the client. Likely this is being done for you on the server side, so you should not worry about this message unless you encounter trouble loading large array data.\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "running on: jupyter_hub environment: standard\n", + "setting '_base_path_' as /nsls2/data/chx/legacy/analysis/\n", + "setting '_mask_path_' as /nsls2/data/chx/shared/CHX_Setup/Detector_masks/\n", + "ran \"%run -i /nsls2/data/chx/legacy/analysis/2022_3/lwiegart/development/roi_nr_2019_3_0_1.py\" to fix ROI numbering for PHI-sliced data sets. Should get fixed in pyCHX...\n", + "ran \"%run -i /nsls2/data/chx/legacy/analysis/2023_2/lwiegart/pyCHX_June2023/chx_outlier_detection.py\": this should become part of pyCHX.\n", + "ran \"%run -i /nsls2/data/chx/legacy/analysis/2023_2/lwiegart/pyCHX_June2023/fix_get_sid_filenames.py\": this should be fixed and re-deployed in pyCHX.\n", + "\n", + "environment dependent settings and patches:\n", + "using \"%matplotlib inline\" for plotting\n", + "ran \"%run -i /nsls2/data/chx/legacy/analysis/2022_3/lwiegart/development/polygonmask_fix.py\".\n", + "ran \"%run -i /nsls2/data/chx/legacy/analysis/2023_2/lwiegart/pyCHX_June2023/chx_compress.py\": temporary fix for depreciated np.float.\n", + "ran \"%run -i /nsls2/data/chx/legacy/analysis/2023_2/lwiegart/pyCHX_June2023/chx_correlationc.py\": temporary fix for depreciated np.float.\n", + "ran \"%run -i /nsls2/data/chx/legacy/analysis/2023_2/lwiegart/pyCHX_June2023/Create_Report.py\": temporary fix for depreciated np.float.\n", + "ran \"%run -i /nsls2/data/chx/legacy/analysis/2023_2/lwiegart/pyCHX_June2023/xpcs_timepixel.py\": temporary fix for depreciated np.float.\n", + "ran \"%run -i /nsls2/data/chx/legacy/analysis/2023_2/lwiegart/pyCHX_June2023/chx_generic_functions.py\": temporary fix for depreciated np.float. np.int, collection.Iterable\n", + "successfully imported CHX channel archiver and related functions\n" + ] + } + ], + "source": [ + "# header for current kernel\n", + "from pyCHX.chx_packages import *\n", + "plt.rcParams.update({'figure.max_open_warning': 0})\n", + "plt.rcParams.update({ 'image.origin': 'lower' })\n", + "plt.rcParams.update({ 'image.interpolation': 'none' })\n", + "import matplotlib.patches as mpatches\n", + "from copy import deepcopy\n", + "from scipy.signal import argrelmax\n", + "\n", + "%run /nsls2/data/chx/legacy/analysis/2022_3/lwiegart/development/standard_functions.py\n", + "%run /nsls2/data/chx/legacy/analysis/2022_3/lwiegart/development/chx_analysis_setup.ipynb\n", + "%run -i /nsls2/data/chx/legacy/analysis/2022_3/lwiegart/development/archiver_setup.py" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "de66f054-3a69-445a-a455-915ec17a0dd2", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Defaulting to user installation because normal site-packages is not writeable\n", + "Requirement already satisfied: scikit-guess in /nsls2/users/lwiegart/.local/lib/python3.11/site-packages (0.0.1a0)\n", + "Requirement already satisfied: numpy>=1.7 in /nsls2/conda/envs/2024-2.0-py311-tiled/lib/python3.11/site-packages (from scikit-guess) (1.26.4)\n", + "Requirement already satisfied: scipy in /nsls2/conda/envs/2024-2.0-py311-tiled/lib/python3.11/site-packages (from scikit-guess) (1.13.0)\n", + "\u001b[33mDEPRECATION: py4xs 2023.1.23.0 has a non-standard dependency specifier scipy>-=1.6. pip 24.1 will enforce this behaviour change. A possible replacement is to upgrade to a newer version of py4xs or contact the author to suggest that they release a version with a conforming dependency specifiers. Discussion can be found at https://github.com/pypa/pip/issues/12063\u001b[0m\u001b[33m\n", + "\u001b[0mNote: you may need to restart the kernel to use updated packages.\n" + ] + } + ], + "source": [ + "pip install scikit-guess" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "60c5a976-af6b-4473-982a-ee84d14f728f", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import skg # this wouldn't work running jupyter hub on CHX srv2 environment" + ] + }, + { + "cell_type": "markdown", + "id": "cc66016c-1412-41f8-9622-0e8ea14d95d3", + "metadata": {}, + "source": [ + "### Specify dataset to load" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "id": "f358b1ca-21d9-49c8-9ade-8ff060742982", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "uid list: 75a5f055 -> scan list: 159929\n", + "IF output will be saved, it will be saved as: /nsls2/data/chx/legacy/analysis/2024_3/cai/Results/Pilatus_800k_calibration_uid_75a5f055.pkl\n" + ] + } + ], + "source": [ + "user = 'cai'\n", + "cycle = '2024_3'\n", + "\n", + "# silver behenate colibration (list should contain only one scan_id or uid)\n", + "scan_list = [157601] # WAXS detector position optimized for Rufina's samples\n", + "scan_list = [157615] # WAXS detector position optimized PP 3D printing\n", + "scan_list = [159929] # WAXS detector ~130mm\n", + "\n", + "result_dir = '%s%s/%s/%s/'%(_base_path_,cycle,user,'Results')\n", + "\n", + "###############################################################################################################\n", + "(scan_list,uid)=get_uid_list(scan_list,user=user,cycle=cycle,uid_length=8,verbose=True)\n", + "assert len(uid)==1,'list should only contain one scan_id or uid'\n", + "filepath=result_dir+'Pilatus_800k_calibration_uid_%s.pkl'%uid[0]\n", + "print('IF output will be saved, it will be saved as: %s'%filepath)" + ] + }, + { + "cell_type": "markdown", + "id": "ab218eaa-279e-4593-9b2a-d7f7142e601b", + "metadata": {}, + "source": [ + "### Calibration setup" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "id": "655d2f33-d8a3-4b74-b4af-b274c05a3e09", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "couldn't find image shape...skip!\n", + "getting archived data for PVs ['XF:11IDA-OP{Mono:DCM-Ax:Energy}Mtr.RBV']\n", + "uid: 75a5f055\n", + "time: start of uid - 10s to end of uid +0s\n", + "2024-10-31 13:51:19 - 2024-10-31 13:51:30\n", + "sample detector distance: 0.13[m] X-ray wavelength: 8.853817039205885e-11[m]\n" + ] + } + ], + "source": [ + "center=(701,374) # guess for beam center [detector pixles]\n", + "#box_width=198 # width of box (around guessed beam center) to contain at least the first diffraction ring of the calibrant\n", + "box_width=124\n", + "\n", + "calibrant_name = 'AgBh' # name of calibrant (needs to match pyFai library, only tested for 'AgBh')\n", + "\n", + "### below should be metadata information\n", + "md=get_meta_data(uid[0])\n", + "sample_det_distance = md['pilatus800k sample-detector distance']/1000 # this is NOT a detector PV...name could change depending on user\n", + "# currently don't have detector metadata for energy...\n", + "pv_E = 'XF:11IDA-OP{Mono:DCM-Ax:Energy}Mtr.RBV'\n", + "res_dict=get_archived_pvs_from_uid(pv_list=[pv_E],uid=uid[0],pre=10,post=0,verbose=True)\n", + "E=np.average(res_dict[pv_E]['data'])\n", + "wavelength=1E-9*(1239.8/E)\n", + "\n", + "print('sample detector distance: %s[m] X-ray wavelength: %s[m]'%(np.round(sample_det_distance,3),wavelength))" + ] + }, + { + "cell_type": "markdown", + "id": "689dc9e2-9bb5-427c-a12c-95f53486f13d", + "metadata": {}, + "source": [ + "### plot data with approximate beam center" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "id": "1872171c-8478-4f0c-bf5c-90e61af80e40", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "WARNING:databroker.mongo_normalized:'pilatus800_image' actually has dtype '" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "h=db[uid[0]]\n", + "f=h.start['detectors'][0]+'_image'\n", + "print(f)\n", + "im=list(h.data(f))\n", + "\n", + "img = np.flipud(im[0][0])\n", + "plt.imshow(img,norm='log',vmin=100,vmax=3000)\n", + "plt.title('scan_id: %s, uid: %s\\ncalibrant: %s'%(scan_list[0],uid[0],calibrant_name))\n", + "plt.xlabel('x-pos. [pixel]');plt.ylabel('y-pos. [pixel]')\n", + "extend=450\n", + "plt.plot(center[0],center[1],'ro',label='guess for center:\\n(%s,%s)'%(center[0],center[1]))\n", + "#c = mpatches.Circle(center,200,color='r',fill=False)\n", + "\n", + "c= mpatches.Rectangle((center[0]-box_width/2,center[1]-box_width/2),box_width,box_width,color='r',fill=False,label='box to find \\nlowest order \\ndiffraction ring')\n", + "\n", + "ax=plt.gca()\n", + "ax.add_patch(c)\n", + "\n", + "plt.xlim(center[0]-extend/2,center[0]+extend/2);plt.ylim(center[1]-extend/2,center[1]+extend/2)\n", + "plt.legend(loc='lower right')\n", + "\n", + "ax.set_aspect('equal')" + ] + }, + { + "cell_type": "markdown", + "id": "30ec3f55-dc65-4c97-84c6-5b71c3dc824b", + "metadata": {}, + "source": [ + "### finding the beam center: 1$^{st}$ iteration" + ] + }, + { + "cell_type": "code", + "execution_count": 114, + "id": "a4129a2e-567c-41b1-a1f8-c075a0620b74", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fitbox = img[int(center[1]-box_width/2):int(center[1]+box_width/2),int(center[0]-box_width/2):int(center[0]+box_width/2)]\n", + "# do some thresholding\n", + "ind2=fitbox< 5*np.nanmean(fitbox) # this is hardcoded, but maybe ok as long as silver behenate is used for calibration (intensity ratio of rings should be setup independent)\n", + "\n", + "fitbox_=deepcopy(fitbox)\n", + "fitbox_[ind2]=0\n", + "#get local maxima\n", + "\n", + "ind=argrelmax(fitbox_,axis=1,order=50)\n", + "fig,ax = plt.subplots(1,3,figsize=(16,4))\n", + "plt.suptitle('first iteration of finding the correct beam center from guess (%s,%s)'%(center[0],center[1]))\n", + "plt.subplot(1,3,1)\n", + "plt.imshow(fitbox_);plt.title('data points on first diffraction ring of calibrant')\n", + "plt.xlabel('x-pos. [pixel] (in sub-image)');plt.ylabel('y-pos. [pixel] (in sub-image)')\n", + "#plt.plot(center[0],center[1],'ro')\n", + "for i in range(len(ind[0])):\n", + " plt.plot(ind[1][i],ind[0][i],'r.',markersize=3,alpha=.5)\n", + "\n", + "# create dataset and fit to sphere:\n", + "data=[]\n", + "for i in range(len(ind[0])):\n", + " data.append((ind[1][i],ind[0][i]))\n", + "\n", + "r, c = skg.nsphere_fit(data,scaling=True)\n", + "\n", + "cfit1 = mpatches.Circle(c,r,color='r',fill=False)\n", + "\n", + "\n", + "plt.subplot(1,3,2)\n", + "plt.imshow(fitbox_);plt.title('beam center after first iteration')\n", + "ax=plt.gca()\n", + "cp=deepcopy(cfit1)\n", + "ax.add_patch(cp)\n", + "ax.set_aspect('equal');xl=ax.get_xlim();yl=ax.get_ylim()\n", + "ax.plot(c[0],c[1],'r+',markersize=10)\n", + "ax.set_xlim(xl); ax.set_ylim(yl)\n", + "plt.xlabel('x-pos. [pixel] (in sub-image)');plt.ylabel('y-pos. [pixel] (in sub-image)')\n", + "\n", + "radius = []\n", + "for d in data:\n", + " radius.append(((d[0]-c[0])**2+(d[1]-c[1])**2)**.5)\n", + "plt.subplot(1,3,3);plt.title('distribution of radii from data points with new center')\n", + "plt.plot(radius,'.');plt.xlabel('data point no');plt.ylabel('radius [pixel]');plt.grid(True)" + ] + }, + { + "cell_type": "markdown", + "id": "4d36c57c-3b7b-4a65-866e-4e9b19de3594", + "metadata": {}, + "source": [ + "### finding the beam center: 2$^{nd}$ iteration" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "id": "ee066c40-6673-4c8e-9ad3-6de0f49b67bf", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 70.39976829, 141.89059059])" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 79, + "id": "5563cb60-3864-4e8b-a501-3e62848aaa64", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "c=np.array([70,60])" + ] + }, + { + "cell_type": "code", + "execution_count": 115, + "id": "d399a21e-da05-4f03-8256-4f2b2c6d4550", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "beam_center x=707, y=369\n", + "beam_center x=707, y=369\n" + ] + }, + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'y-pos [pixel]')" + ] + }, + "execution_count": 115, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig,ax = plt.subplots(1,3,figsize=(16,4))\n", + "plt.suptitle('second iteration of finding the correct beam center from new guess (%s,%s)'%(np.round(c[0]),np.round(c[1])),y=1.05)\n", + "\n", + "out_ind=np.invert(is_outlier(np.array(radius),2.))\n", + "data_=np.array(data)[out_ind]\n", + "\n", + "# fit again remaining data to circle:\n", + "r_, c_ = skg.nsphere_fit(data_,scaling=True)\n", + "cfit2 = mpatches.Circle(c_,r_,color='r',fill=False)\n", + "\n", + "\n", + "plt.subplot(1,3,1)\n", + "plt.imshow(fitbox_);plt.title('data points on first diffraction ring of calibrant')\n", + "ax=plt.gca()\n", + "cp=deepcopy(cfit2)\n", + "ax.add_patch(cp)\n", + "ax.set_aspect('equal');xl=ax.get_xlim();yl=ax.get_ylim()\n", + "ax.plot(c_[0],c_[1],'r+',markersize=10)\n", + "ax.set_xlim(xl); ax.set_ylim(yl)\n", + "plt.xlabel('x-pos. [pixel] (in sub-image)');plt.ylabel('y-pos. [pixel] (in sub-image)')\n", + "\n", + "plt.subplot(1,3,2)\n", + "radius_ = []\n", + "for d in data_:\n", + " radius_.append(((d[0]-c_[0])**2+(d[1]-c_[1])**2)**.5)\n", + "plt.plot(radius_,'.');plt.xlabel('data point no');plt.ylabel('radius [pixel]');plt.grid(True)\n", + "# need to calculat coordiantes back for whole image\n", + "beam_center=(int(np.round(center[0]+c_[0]-np.shape(fitbox)[0]/2,0)),int(np.round(center[1]+c_[1]-np.shape(fitbox)[1]/2,0)))\n", + "print('beam_center x=%s, y=%s'%(beam_center[0],beam_center[1]))\n", + "plt.title('distribution of radii -> new center: (%s,%s)\\ncenter of whole image: (%s,%s)'%(np.round(c_[0]),np.round(c_[1]),beam_center[0],beam_center[1]))\n", + "\n", + "plt.subplot(1,3,3)\n", + "# need to calculate coordiantes back for whole image\n", + "beam_center=(int(np.round(center[0]+c_[0]-np.shape(fitbox)[0]/2,0)),int(np.round(center[1]+c_[1]-np.shape(fitbox)[1]/2,0)))\n", + "print('beam_center x=%s, y=%s'%(beam_center[0],beam_center[1]))\n", + "\n", + "### plot whole image with fitted center and radius of 0-order peak\n", + "\n", + "plt.imshow(img,norm='log',vmin=100,vmax=3000);plt.title('refined beam center')\n", + "\n", + "plt.plot('ro',label='(%s,%s)'%(beam_center[0],beam_center[1]))\n", + "plt.legend(title='updated center:',loc='lower right',fontsize=12)\n", + "circ = mpatches.Circle(beam_center,r,color='r',fill=False)\n", + "circ1=deepcopy(circ)\n", + "ax=plt.gca()\n", + "ax.add_patch(circ1)\n", + "ax.set_aspect('equal')\n", + "plt.xlabel('x-pos [pixel]');plt.ylabel('y-pos [pixel]')\n" + ] + }, + { + "cell_type": "markdown", + "id": "cee2580b-e793-40f7-8484-5871e751a570", + "metadata": {}, + "source": [ + "### Further Geometry Refinement with pyFAI" + ] + }, + { + "cell_type": "code", + "execution_count": 116, + "id": "d9a3f245-70b6-406b-a4e1-ea09d282e474", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "import pyFAI\n", + "from pyFAI import calibrant\n", + "from pyFAI import geometryRefinement" + ] + }, + { + "cell_type": "markdown", + "id": "c0f9b2c1-261b-43e1-8fac-557b09d5904a", + "metadata": {}, + "source": [ + "### create masks" + ] + }, + { + "cell_type": "code", + "execution_count": 117, + "id": "45c908b4-2bc4-419a-bb4b-0fb75cb0729f", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "corner_masking = True # mask stripe of pixels with widht dx,dy around detector cutout\n", + "dx=20\n", + "dy=20\n", + "\n", + "platform_masking = False\n", + "px=500\n", + "py=250\n", + "\n", + "fix,ax = plt.subplots(1,4,figsize=(24,5))\n", + "plt.subplot(1,4,1)\n", + "plt.imshow(img,norm='log',vmin=200,vmax=2000)\n", + "plt.title('data: %s'%uid);plt.xlabel('x [pixel]');plt.ylabel('y [pixel]')\n", + "\n", + "mask = np.zeros(np.shape(img))\n", + "m = img<0\n", + "mask[m]=1\n", + "plt.subplot(1,4,2)\n", + "plt.imshow(mask)\n", + "plt.title('detector mask');plt.xlabel('x [pixel]');plt.ylabel('y [pixel]')\n", + "\n", + "plt.subplot(1,4,3)\n", + "corner_mask=np.zeros(shape(mask))\n", + "if corner_masking:\n", + " corner_mask[0:423+dx,487-dx:487]=1\n", + " corner_mask[423:423+dy,487-dx:]=1\n", + " plt.imshow(corner_mask);plt.title('corner mask: dx=%s pix, dy=%s pix'%(dx,dy));plt.xlabel('x [pixel]');plt.ylabel('y [pixel]')\n", + "\n", + "plt.subplot(1,4,4)\n", + "platform_mask=np.zeros(shape(mask))\n", + "if platform_masking:\n", + " platform_mask[0:py+dx,0:px]=1\n", + " plt.imshow(platform_mask);plt.title('platform mask: px=%s pix, py=%s pix'%(px,py));plt.xlabel('x [pixel]');plt.ylabel('y [pixel]')\n", + "mask_=mask+corner_mask+platform_mask" + ] + }, + { + "cell_type": "markdown", + "id": "23c36b2d-a560-454f-9803-e4e6fa561dab", + "metadata": {}, + "source": [ + "### setting up detector and geometry for calibration of detector geometry" + ] + }, + { + "cell_type": "code", + "execution_count": 118, + "id": "5d90edb9-6ca1-4659-8e07-eab073c03449", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "detector = pyFAI.detector_factory(\"Pilatus1M\")\n", + "aintegrator=pyFAI.azimuthalIntegrator.AzimuthalIntegrator(dist=sample_det_distance, poni1=beam_center[1]*detector.pixel1, poni2=beam_center[0]*detector.pixel2, rot1=0, rot2=0, rot3=0, pixel1=None, pixel2=None, splineFile=None, detector=detector, wavelength=wavelength)\n", + "calibrant = pyFAI.calibrant.get_calibrant(calibrant_name,wavelength=wavelength)\n", + "pyFAI.calibrant.Calibrant.save_dSpacing(calibrant,filename=calibrant_name) # this is required to use 'calibrant' in geometry refinement..." + ] + }, + { + "cell_type": "markdown", + "id": "3d6be17d-44c2-42cc-8776-e694f2c251bf", + "metadata": {}, + "source": [ + "### measured and theoretical peak position without geometry refinement" + ] + }, + { + "cell_type": "code", + "execution_count": 119, + "id": "4864099f-3ee2-4012-a44a-cf328ec77f24", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'integrated intensity [arb.u.]')" + ] + }, + "execution_count": 119, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "azi_2th = aintegrator.integrate1d(img,npt=1200,mask=mask_,unit='2th_deg')\n", + "plt.semilogy(azi_2th[0],azi_2th[1])\n", + "# find local maxima:\n", + "from scipy.signal import argrelextrema\n", + "max_2th = 12 #max range to look for extrema\n", + "ind = azi_2th[0]<=max_2th\n", + "amax = argrelextrema(azi_2th[1][ind], np.greater,order=20)\n", + "\n", + "for a in amax[0]:\n", + " plt.semilogy(azi_2th[0][a],azi_2th[1][a],'r.')\n", + "\n", + " \n", + "delta=1.5\n", + "rings_2th = azi_2th[0][amax]\n", + "peak_list=calibrant.get_peaks(unit='2th_deg')\n", + "index=[];peak_2th=[]\n", + "for a in rings_2th:\n", + " m=np.argmin(np.abs(peak_list-a))\n", + " if np.abs(peak_list[m]-a) <= delta:\n", + " index.append(m);peak_2th.append(peak_list[m])\n", + "ax=plt.gca()\n", + "yl=ax.get_ylim()\n", + "index=sorted(list(set(index)))\n", + "for ii,i in enumerate(index):\n", + " plt.semilogy([peak_2th[ii],peak_2th[ii]],[yl[0]*1.1,yl[1]*.9],'g--')\n", + " \n", + "plt.xlabel(r'2$\\theta$ [deg.]');plt.ylabel('integrated intensity [arb.u.]')" + ] + }, + { + "cell_type": "markdown", + "id": "a2a8de8f-f429-4706-8342-56c20f29ee1a", + "metadata": {}, + "source": [ + "### 1$^{st}$ refinement: optimize sample-detector distance only using some low order rings" + ] + }, + { + "cell_type": "code", + "execution_count": 120, + "id": "9f89e156-1967-434b-a3f9-6c57cf5ea77c", + "metadata": {}, + "outputs": [], + "source": [ + "search_ind_order = 5 # initial search for peak positions up to index of order search_ind_order (starts at 0!)\n", + "d_pix= 20 # maximum difference between measured and theoretical peak position\n", + "histogram_thresh = .1 # threshold for histogram: only bins with a count > histogram_thresh * total number of datapoints will be considered 'valid' radii\n" + ] + }, + { + "cell_type": "code", + "execution_count": 127, + "id": "8da643da-ae24-4510-b92d-1563b10ac4b6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 127, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "cali_map=calibrant.fake_calibration_image(aintegrator,W=1E-5)\n", + "radial_strip = cali_map[beam_center[1],beam_center[0]:]\n", + "h=radial_strip<1E-3 # there are some (numerical?) fluctuations that get picked up as relative maxima...\n", + "radial_strip[h]=0\n", + "ring_rad_pix = argrelmax(radial_strip,order=20)[0]\n", + "box_width=d_pix+ring_rad_pix[search_ind_order]\n", + "fitbox = img[int(beam_center[1]-box_width):int(beam_center[1]+box_width),int(beam_center[0]-box_width):int(beam_center[0]+box_width)]\n", + "\n", + "fig,ax = plt.subplots(1,3,figsize=(16,4))\n", + "plt.suptitle('selecting data for 1$^{st}$ gemeotry refinement: sample-detector distance only using some low order rings',y=1.05)\n", + "\n", + "plt.subplot(1,3,1);plt.title('sub-image for ring search')\n", + "plt.imshow(fitbox,norm='log');plt.xlabel('x [pixel] in sub-image');plt.ylabel('y [pixel] in sub-image')\n", + "\n", + "plt.subplot(1,3,2);plt.title('data points on rings N<=%s'%search_ind_order)\n", + "ind2=fitbox< 2.5*np.nanmean(fitbox) # this is hardcoded, but maybe ok as long as silver behenate is used for calibration (intensity ratio of rings should be setup independent)\n", + "\n", + "fitbox_=deepcopy(fitbox)\n", + "fitbox_[ind2]=0\n", + "#get local maxima\n", + "\n", + "ind=argrelmax(fitbox_,axis=1,order=50)\n", + "plt.imshow(fitbox_)\n", + "radius=[]\n", + "plt.plot(box_width,box_width,'r+')\n", + "for i in range(len(ind[0])):\n", + " plt.plot(ind[1][i],ind[0][i],'r.',markersize=2,alpha=.5)\n", + " radius.append(((ind[1][i]-box_width)**2+(ind[0][i]-box_width)**2)**.5)\n", + "plt.xlabel('x [pixel] in sub-image');plt.ylabel('y [pixel] in sub-image')\n", + "\n", + "radius_hist = np.histogram(radius)\n", + "plt.subplot(1,3,3)\n", + "plt.hist(radius,radius_hist[1]);plt.xlabel('radius [pixel]');plt.ylabel('n (number of data points)');plt.grid(True)\n", + "plt.plot([radius_hist[1][0],radius_hist[1][-1]],len(radius)*np.array([histogram_thresh,histogram_thresh]),'r--',label='n > %sx number of datapoints'%histogram_thresh)\n", + "plt.legend(loc='upper right')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 134, + "id": "a736bbf5-d3e2-4327-8526-b1fbcd18e18f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 134, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# downselect histogram: ignore bins with less than 10% of total number of found maxima to create 'valid radii' list\n", + "radii_list=[];sum_i=0\n", + "for ii,i in enumerate(radius_hist[0]):\n", + " if i>=.1*len(radius):\n", + " radii_list.append(radius_hist[1][ii:ii+2])\n", + " sum_i+=i\n", + "ave_radii_list = np.average(radii_list,axis=1)\n", + "rad_index=[]\n", + "for r in ave_radii_list:\n", + " rad_index.append([r,np.argmin(np.abs(ring_rad_pix-r))])\n", + "rad_index=[]\n", + "for r in ave_radii_list:\n", + " rad_index.append([r,np.argmin(np.abs(ring_rad_pix-r))])\n", + " \n", + "# create data for geometry refinement module\n", + "data=np.ndarray(shape=(sum_i,3))\n", + "pixel_position_x=[];pixel_position_y=[];pixel_index=[]\n", + "for i in range(len(ind[0])):\n", + " # plt.plot(ind[1][i],ind[0][i],'r.')\n", + " r=((ind[1][i]-box_width)**2+(ind[0][i]-box_width)**2)**.5\n", + " for ll,l in enumerate(radii_list):\n", + " if r >= l[0] and r <= l[1]:\n", + " pixel_position_x.append(ind[1][i]+beam_center[0]-box_width)\n", + " pixel_position_y.append(ind[0][i]+beam_center[1]-box_width)\n", + " pixel_index.append(int(rad_index[ll][1]))\n", + " #ring_info.append([ind[1][i]+beam_center[0]-box_width,ind[0][i]+beam_center[1]-box_width,rad_index[ll][1]])\n", + "data[:,0]=pixel_position_y\n", + "data[:,1]=pixel_position_x\n", + "data[:,2]=pixel_index\n", + "\n", + "## add legend with index, label with calibrant\n", + "fig,ax=plt.subplots(figsize=(6,6))\n", + "plt.imshow(img,norm='log',vmin=200,vmax=3000,cmap='gray');plt.title('data points on low index rings for sample detector refinement\\nscan_id: %s uid: %s'%(scan_list[0],uid[0]))\n", + "plt.xlabel('x [pixel]');plt.ylabel('y [pixel]')\n", + "color_list=[]\n", + "for i in range(np.shape(data)[0]):\n", + " if data[i][2] not in color_list:\n", + " color_list.append(data[i][2])\n", + " lab='N = %s'%int(data[i][2])\n", + " else:\n", + " lab=''\n", + " plt.plot(data[i][1],data[i][0],'.',color='C%s'%int(data[i][2]),markersize=.75,alpha=.5,label=lab)\n", + "plt.legend(title='ring index',loc='lower right',scatterpoints=3,markerscale=10,reverse=True)" + ] + }, + { + "cell_type": "markdown", + "id": "60203de7-3a61-48b8-a916-f133eca670ca", + "metadata": {}, + "source": [ + "### refine sample-detector distance only" + ] + }, + { + "cell_type": "code", + "execution_count": 136, + "id": "37bfa47e-0d12-4bcd-9a51-f55636521da0", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "initial geometry parameters:\n", + "Detector Pilatus 1M\t PixelSize= 1.720e-04, 1.720e-04 m\t BottomRight (3)\n", + "Wavelength= 8.853817e-11 m\n", + "SampleDetDist= 1.400000e-01 m\tPONI= 6.346800e-02, 1.216040e-01 m\trot1=0.000000 rot2=0.000000 rot3=0.000000 rad\n", + "DirectBeamDist= 140.000 mm\tCenter: x=707.000, y=369.000 pix\tTilt= 0.000° tiltPlanRotation= 0.000° 𝛌= 0.885Å\n", + "\n", + "residuals for initial refinement: 6.84597815905763e-06\n", + "updated geometry parameters:\n", + "Detector Pilatus 1M\t PixelSize= 1.720e-04, 1.720e-04 m\t BottomRight (3)\n", + "Wavelength= 8.853817e-11 m\n", + "SampleDetDist= 3.832882e-01 m\tPONI= 6.346800e-02, 1.216040e-01 m\trot1=0.000000 rot2=0.000000 rot3=0.000000 rad\n", + "DirectBeamDist= 383.288 mm\tCenter: x=707.000, y=369.000 pix\tTilt= 0.000° tiltPlanRotation= 0.000° 𝛌= 0.885Å\n" + ] + } + ], + "source": [ + "geo_refine=pyFAI.geometryRefinement.GeometryRefinement(data=data, dist=sample_det_distance, poni1=beam_center[1]*detector.pixel1, poni2=beam_center[0]*detector.pixel2, rot1=0, rot2=0, rot3=0, detector=detector, wavelength=wavelength, calibrant=calibrant)\n", + "print('initial geometry parameters:')\n", + "print(geo_refine)\n", + "residuals = geo_refine.refine3(fix=['poni1','poni2','rot1','rot2','rot3','wavelength','center'])\n", + "print('\\nresiduals for initial refinement: %s\\nupdated geometry parameters:'%residuals)\n", + "print(geo_refine)\n", + "\n", + "sample_det_distance = geo_refine.get_dist()\n", + "# update aintegrator with new sample-detector distance !!!\n", + "aintegrator=pyFAI.azimuthalIntegrator.AzimuthalIntegrator(dist=sample_det_distance, poni1=beam_center[1]*detector.pixel1, poni2=beam_center[0]*detector.pixel2, rot1=0, rot2=0, rot3=0, pixel1=None, pixel2=None, splineFile=None, detector=detector, wavelength=wavelength)" + ] + }, + { + "cell_type": "code", + "execution_count": 137, + "id": "6648a2c7-ab30-40b5-a0f6-8f13c930c074", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "azi_2th = aintegrator.integrate1d(img,npt=1200,mask=mask_,unit='2th_deg')\n", + "plt.semilogy(azi_2th[0],azi_2th[1])\n", + "plt.title('measured and theoretical peak positions after sample-detector distance refinement\\ncalibrant: %s sd= %smm\\nscan_id: %s uid: %s'%(calibrant_name,np.round(sample_det_distance*1000,3),scan_list[0],uid[0]))\n", + "# find local maxima:\n", + "from scipy.signal import argrelextrema\n", + "max_2th = 12 #max range to look for extrema\n", + "ind = azi_2th[0]<=max_2th\n", + "amax = argrelextrema(azi_2th[1][ind], np.greater,order=20)\n", + "\n", + "for a in amax[0]:\n", + " plt.semilogy(azi_2th[0][a],azi_2th[1][a],'r.')\n", + "\n", + " \n", + "delta=1.5\n", + "rings_2th = azi_2th[0][amax]\n", + "peak_list=calibrant.get_peaks(unit='2th_deg')\n", + "index=[];peak_2th=[]\n", + "for a in rings_2th:\n", + " m=np.argmin(np.abs(peak_list-a))\n", + " if np.abs(peak_list[m]-a) <= delta:\n", + " index.append(m);peak_2th.append(peak_list[m])\n", + "ax=plt.gca()\n", + "yl=ax.get_ylim()\n", + "index=sorted(list(set(index)))\n", + "for ii,i in enumerate(index):\n", + " plt.semilogy([peak_2th[ii],peak_2th[ii]],[yl[0]*1.1,yl[1]*.9],'g--')\n", + "plt.xlabel(r'2$\\theta$ [deg.]');plt.ylabel('intensity [arb.u.]');plt.grid(True,which='both')\n" + ] + }, + { + "cell_type": "markdown", + "id": "9bee862a-403a-435b-b7d5-990c592bf484", + "metadata": {}, + "source": [ + "## Full Geometry Refinement" + ] + }, + { + "cell_type": "markdown", + "id": "b4483ffa-8dd3-4140-99c5-e387294fbe81", + "metadata": {}, + "source": [ + "### setup" + ] + }, + { + "cell_type": "code", + "execution_count": 138, + "id": "52999f83-a34f-484f-ad00-1e079c6dcac8", + "metadata": {}, + "outputs": [], + "source": [ + "ddr=5 # maximum allowed difference between theoretical and measured peak positions [pixel]\n", + "dr=10 # radii within this value will be assumed to be the same radius" + ] + }, + { + "cell_type": "code", + "execution_count": 139, + "id": "442e19b9-a0ad-40a7-a24a-8cb96aa96ba3", + "metadata": {}, + "outputs": [], + "source": [ + "### get all possible radii from fake calibration image: take cuts along the 4 principle directions\n", + "cali_map=calibrant.fake_calibration_image(aintegrator,W=1E-6)\n", + "ring_rad_pix_ = []\n", + "for i in range(4):\n", + " if i == 0:\n", + " radial_strip = cali_map[beam_center[1],beam_center[0]:]\n", + " elif i == 1:\n", + " radial_strip = cali_map[beam_center[1]:,beam_center[0]]\n", + " elif i == 2:\n", + " radial_strip = cali_map[:beam_center[1],beam_center[0]]\n", + " radial_strip = np.flip(radial_strip)\n", + " elif i == 3:\n", + " radial_strip = cali_map[beam_center[1],:beam_center[0]]\n", + " radial_strip = np.flip(radial_strip)\n", + " h=radial_strip<1E-3;radial_strip[h]=0\n", + " ring_rad_pix_+=(argrelmax(radial_strip, order=20)[0].tolist())\n", + "ring_rad_pix_=sorted(list(set(ring_rad_pix_)))\n", + "# # ensure we're not double counting some close values...not sure if the same threshold would work for any calibrant, but probably ok for AgBh\n", + "dx=[]\n", + "for i in range(len(ring_rad_pix_)):\n", + " if i == 0:\n", + " dx.append(ring_rad_pix_[i]-0)\n", + " else:\n", + " dx.append(ring_rad_pix_[i]-ring_rad_pix_[i-1])\n", + "dx=np.array(dx)\n", + "h=dx>dr\n", + "ring_rad_pix=np.array(ring_rad_pix_)[h]\n", + "\n", + "# # ensure we're not double counting some close values...not sure if the same threshold would work for any calibrant, but probably ok for AgBh\n", + "dx=[]\n", + "for i in range(len(ring_rad_pix_)):\n", + " if i == 0:\n", + " dx.append(ring_rad_pix_[i]-0)\n", + " else:\n", + " dx.append(ring_rad_pix_[i]-ring_rad_pix_[i-1])\n", + "dx=np.array(dx)\n", + "h=dx>dr;dx=dx[h]\n", + "ring_rad_pix=np.array(ring_rad_pix_)[h]" + ] + }, + { + "cell_type": "code", + "execution_count": 140, + "id": "e93e5f7b-d9f8-4b84-ae2d-5480dc858c82", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_15678/190477075.py:10: RuntimeWarning: Mean of empty slice\n", + " g=tmp<2*np.nanmean(tmp)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "geometry parameters before final refinement:\n", + "Detector Pilatus 1M\t PixelSize= 1.720e-04, 1.720e-04 m\t BottomRight (3)\n", + "Wavelength= 8.853817e-11 m\n", + "SampleDetDist= 3.832882e-01 m\tPONI= 6.346800e-02, 1.216040e-01 m\trot1=0.000000 rot2=0.000000 rot3=0.000000 rad\n", + "DirectBeamDist= 383.288 mm\tCenter: x=707.000, y=369.000 pix\tTilt= 0.000° tiltPlanRotation= 0.000° 𝛌= 0.885Å\n", + "\n", + "residuals for final refinement: 6.539923412382132e-06\n", + "updated geometry parameters:\n", + "Detector Pilatus 1M\t PixelSize= 1.720e-04, 1.720e-04 m\t BottomRight (3)\n", + "Wavelength= 8.853817e-11 m\n", + "SampleDetDist= 3.909312e-01 m\tPONI= 6.270496e-02, 1.216434e-01 m\trot1=0.000000 rot2=0.000000 rot3=0.000000 rad\n", + "DirectBeamDist= 390.931 mm\tCenter: x=707.229, y=364.564 pix\tTilt= 0.000° tiltPlanRotation= 0.000° 𝛌= 0.885Å\n" + ] + }, + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'y [pixel]')" + ] + }, + "execution_count": 140, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "x_pos=[];y_pos=[];index_=[]\n", + "for i in range(len(ring_rad_pix)):\n", + " ma=np.zeros(np.shape(img))*np.nan;mi=np.ones(np.shape(img))\n", + " if i == 0:\n", + " ma[beam_center[1]-ring_rad_pix[i]-ddr:beam_center[1]+ring_rad_pix[i]+ddr,beam_center[0]-ring_rad_pix[i]-ddr:beam_center[0]+ring_rad_pix[i]+ddr]=1\n", + " else:\n", + " mi[beam_center[1]-ring_rad_pix[i-2]-ddr:beam_center[1]+ring_rad_pix[i-2]+ddr,beam_center[0]-ring_rad_pix[i-2]-ddr:beam_center[0]+ring_rad_pix[i-2]+ddr]=np.nan\n", + " ma[beam_center[1]-ring_rad_pix[i]-ddr:beam_center[1]+ring_rad_pix[i]+ddr,beam_center[0]-ring_rad_pix[i]-ddr:beam_center[0]+ring_rad_pix[i]+ddr]=1\n", + " tmp=ma*mi*img\n", + " g=tmp<2*np.nanmean(tmp)\n", + " tmp[g]=0\n", + "\n", + " ind = argrelmax(tmp, order=dr)\n", + " r=((ind[1]-beam_center[0])**2+(ind[0]-beam_center[1])**2)**.5\n", + " id1=r<=ring_rad_pix[i]+ddr;id2=r>=ring_rad_pix[i]-ddr\n", + "\n", + " x_pos+=list(ind[0][id1*id2])\n", + " y_pos+=list(ind[1][id1*id2])\n", + " index_+=list(i*np.ones(len(ind[1][id1*id2])))\n", + "\n", + " \n", + "# create data for geometry refinement module\n", + "data2=np.ndarray(shape=(len(x_pos),3))\n", + "data2[:,0]=x_pos\n", + "data2[:,1]=y_pos\n", + "data2[:,2]=index_\n", + "\n", + "fig,ax = plt.subplots(1,3,figsize=(16,5))\n", + "plt.suptitle('Full geometry refinement scan_id: %s uid: %s'%(scan_list[0],uid[0]),y=1.05)\n", + "\n", + "plt.subplot(1,3,1);plt.title('data for refinement')\n", + "plt.imshow(img,norm='log',vmin=200,vmax=3000,cmap='gray')\n", + "color_list = []\n", + "for i in range(np.shape(data2)[0]):\n", + " if data2[i][2] not in color_list:\n", + " color_list.append(data2[i][2])\n", + " lab='%s'%int(data2[i][2])\n", + " else:\n", + " lab=''\n", + " plt.plot(data2[i][1],data2[i][0],'.',color='C%s'%int(data2[i][2]),markersize=.75,alpha=.5,label=lab)\n", + "plt.legend(title='ring index N',loc='lower right',scatterpoints=3,markerscale=10,reverse=False,ncols=2)\n", + "plt.xlabel('x [pixel]');plt.ylabel('y [pixel]')\n", + "\n", + "geo_refine=pyFAI.geometryRefinement.GeometryRefinement(data=data, dist=sample_det_distance, poni1=beam_center[1]*detector.pixel1, poni2=beam_center[0]*detector.pixel2, rot1=0, rot2=0, rot3=0, detector=detector, wavelength=wavelength, calibrant=calibrant)\n", + "print('geometry parameters before final refinement:')\n", + "print(geo_refine)\n", + "residuals2=geo_refine.refine3(fix=['rot1','rot2','rot3','wavelength'])#['poni1','poni2','rot1','rot2','rot3','wavelength'])\n", + "print('\\nresiduals for final refinement: %s\\nupdated geometry parameters:'%residuals2)\n", + "print(geo_refine)\n", + "geo_config=geo_refine.get_config()\n", + "# update aintegrator with new sample-detector distance !!!\n", + "aintegrator=pyFAI.azimuthalIntegrator.AzimuthalIntegrator(dist=geo_config['dist'], poni1=geo_config['poni1'], poni2=geo_config['poni2'], rot1=geo_config['rot1'], rot2=geo_config['rot2'], rot3=geo_config['rot3'], pixel1=None, pixel2=None, splineFile=None, detector=detector, wavelength=wavelength)\n", + "\n", + "plt.subplot(1,3,2)\n", + "azi_2th = aintegrator.integrate1d(img,npt=1200,mask=mask_,unit='2th_deg')\n", + "plt.semilogy(azi_2th[0],azi_2th[1])\n", + "plt.title('measured and theoretical peak positions \\nafter final refinement\\ncalibrant: %s sd= %smm'%(calibrant_name,np.round(geo_config['dist']*1000,3)))\n", + "# find local maxima:\n", + "from scipy.signal import argrelextrema\n", + "max_2th = 12 #max range to look for extrema\n", + "ind = azi_2th[0]<=max_2th\n", + "amax = argrelextrema(azi_2th[1][ind], np.greater,order=20)\n", + "\n", + "for a in amax[0]:\n", + " plt.semilogy(azi_2th[0][a],azi_2th[1][a],'r.')\n", + "\n", + " \n", + "delta=1.5\n", + "rings_2th = azi_2th[0][amax]\n", + "peak_list=calibrant.get_peaks(unit='2th_deg')\n", + "index=[];peak_2th=[]\n", + "for a in rings_2th:\n", + " m=np.argmin(np.abs(peak_list-a))\n", + " if np.abs(peak_list[m]-a) <= delta:\n", + " index.append(m);peak_2th.append(peak_list[m])\n", + "ax=plt.gca()\n", + "yl=ax.get_ylim()\n", + "index=sorted(list(set(index)))\n", + "for ii,i in enumerate(index):\n", + " plt.semilogy([peak_2th[ii],peak_2th[ii]],[yl[0]*1.1,yl[1]*.9],'g--')\n", + "plt.xlabel('Q [nm$^{-1}$]');plt.ylabel('intensity [arb.u.]');plt.grid(True,which='both')\n", + "\n", + "plt.subplot(1,3,3);plt.title('calibrant: %s'%calibrant_name)\n", + "cali_map = calibrant.fake_calibration_image(aintegrator,W=1E-6)\n", + "u=cali_map<.5;cali_map[u]=np.nan\n", + "u=cali_map>.5;cali_map[u]=1\n", + "plt.imshow(img,norm='log',vmin=200,vmax=3000,cmap='gray')\n", + "plt.imshow(cali_map,cmap='hsv')\n", + "plt.xlabel('x [pixel]');plt.ylabel('y [pixel]')" + ] + }, + { + "cell_type": "markdown", + "id": "8ac65290-3698-45ee-a321-0a076a60ffa0", + "metadata": {}, + "source": [ + "### Save Geometry Calibration (requires flag!)" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "bf048c39-43a9-4656-a30d-205a5ad7fc09", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "IF True, calibration data would be saved as /nsls2/data/chx/legacy/analysis/2024_3/lwiegart/Results/Pilatus_800k_calibration_uid_f6ce48a5.pkl\n" + ] + } + ], + "source": [ + "print('IF True, calibration data would be saved as %s'%filepath)\n", + "if False:\n", + " u=get_meta_data(uid[0],verbose=False)['uid']\n", + " # there seems to be no good method to get the refined beam center back...?\n", + " x_beam_pos = float(str(geo_refine).split('Center:')[-1].split('=')[1].split(',')[0])\n", + " y_beam_pos = float(str(geo_refine).split('Center:')[-1].split('=')[2].split(',')[0].split(' ')[0])\n", + " config_dict = {'scan_id':scan_list[0],'uid':u,'calibrant':calibrant_name,'detector':geo_config['detector'],'direct_beam_x':x_beam_pos,'direct_beam_y':y_beam_pos,\n", + " 'energy':geo_refine.get_energy(),'geo_config':geo_config} \n", + " save_pickle(filepath,config_dict,verbose=True)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "c6934a33-1949-4f90-ae59-e2db04c210cc", + "metadata": {}, + "outputs": [ + { + "ename": "NameError", + "evalue": "name '_stop' is not defined", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[22], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43m_stop\u001b[49m\n", + "\u001b[0;31mNameError\u001b[0m: name '_stop' is not defined" + ] + } + ], + "source": [ + "_stop" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "id": "4e8fade3-530f-4f26-a682-b9dfe31a23ab", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Loading data from file: /nsls2/data/chx/legacy/analysis/2024_2/lwiegart/Results/Pilatus_800k_calibration_uid_e03f0866.pkl\n", + "dict_keys(['scan_id', 'uid', 'calibrant', 'detector', 'direct_beam_x', 'direct_beam_y', 'energy', 'geo_config'])\n" + ] + }, + { + "data": { + "text/plain": [ + "Detector Pilatus 1M\t PixelSize= 1.720e-04, 1.720e-04 m\t BottomRight (3)\n", + "Wavelength= 1.284634e-10 m\n", + "SampleDetDist= 3.185822e-01 m\tPONI= 5.584996e-02, 1.072362e-01 m\trot1=0.000000 rot2=0.000000 rot3=0.000000 rad\n", + "DirectBeamDist= 318.582 mm\tCenter: x=623.466, y=324.709 pix\tTilt= 0.000° tiltPlanRotation= 0.000° 𝛌= 1.285Å" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# how to load the calibration data and configure AzimuthalIntegrator\n", + "config_dict=load_pickle(filepath,verbose=True)\n", + "print(config_dict.keys())\n", + "aintegrator=pyFAI.azimuthalIntegrator.AzimuthalIntegrator(dist=config_dict['geo_config']['dist'], poni1=config_dict['geo_config']['poni1'], poni2=config_dict['geo_config']['poni2'],\n", + " rot1=config_dict['geo_config']['rot1'], rot2=config_dict['geo_config']['rot2'], rot3=config_dict['geo_config']['rot3'], \n", + " pixel1=None, pixel2=None, splineFile=None, detector=config_dict['geo_config']['detector'], wavelength=config_dict['geo_config']['wavelength'])\n", + "aintegrator" + ] + }, + { + "cell_type": "markdown", + "id": "a262ed3d-03d7-4c8b-b65f-a93911b65213", + "metadata": {}, + "source": [ + "### try some radial integration" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "id": "d1e598d1-e8e8-4a7c-a522-a93433781b79", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "azi = aintegrator.integrate1d(img,npt=1200,mask=mask_)\n", + "plt.semilogy(azi[0],azi[1])\n", + "plt.xlabel('Q [nm$^{-1}$]');plt.ylabel('intensity [arb.u.]')\n", + "plt.grid(True,which='both')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "04aaf63d-d2e9-49d0-a248-8a0d8004b3cf", + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 61, + "id": "19216594-b7b9-4028-8bd6-99ccafe2c3c6", + "metadata": { + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, '$\\\\Phi$ [$^o$]')" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "phi_map=aintegrator.integrate2d(img, npt_rad=600, npt_azim=360,mask=mask_,unit=\"q_nm^-1\")\n", + "\n", + "fig,ax = plt.subplots(figsize=(6,5))\n", + "plt.imshow(phi_map[0],norm='log',extent=[phi_map[1][0], phi_map[1][-1], phi_map[2][0],phi_map[2][-1]])\n", + "ax=plt.gca()\n", + "ax.set_aspect('auto')\n", + "plt.xlabel('Q [nm$^{-1}$]');plt.ylabel('$\\Phi$ [$^o$]')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ba2e85b1-b2a5-4303-936c-979df39472ef", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (current)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.14" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/pipelines/masking_and_rois/detector_coverage.ipynb b/pipelines/masking_and_rois/detector_coverage.ipynb new file mode 100644 index 0000000..45a554b --- /dev/null +++ b/pipelines/masking_and_rois/detector_coverage.ipynb @@ -0,0 +1,446 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "64ad7785-69d2-4993-970f-110b6d18d5e6", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/nsls2/conda/envs/2024-2.0-py311-tiled/lib/python3.11/site-packages/databroker/v1.py:72: UserWarning: In databroker 2.x, there are separate notions of 'server' and 'client', and register_handler(...) has no effect on the client. Likely this is being done for you on the server side, so you should not worry about this message unless you encounter trouble loading large array data.\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[32mrunning on: jupyter_hub environment: standard\n", + "\u001b[0m\n", + "\u001b[36msetting '_base_path_' as /nsls2/data/chx/legacy/analysis/\u001b[0m\n", + "\u001b[36msetting '_base_path_pass_' as /nsls2/data/chx/proposals/\u001b[0m\n", + "\u001b[36msetting '_mask_path_' as /nsls2/data/chx/shared/CHX_Setup/Detector_masks/\n", + "\u001b[0m\n", + "\u001b[32mRe-imported pyCHX from /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/\u001b[0m\n", + "\u001b[32mRe-imported chx_compress from /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/chx_compress.py\u001b[0m\n", + "\u001b[32mRe-imported chx_olog functions from /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/chx_olog.py\u001b[0m\n", + "\u001b[35m\n", + "environment dependent settings and patches:\u001b[0m\n", + "using \"%matplotlib inline\" for plotting\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/nsls2/conda/envs/2024-2.0-py311-tiled/lib/python3.11/site-packages/databroker/v1.py:72: UserWarning: In databroker 2.x, there are separate notions of 'server' and 'client', and register_handler(...) has no effect on the client. Likely this is being done for you on the server side, so you should not worry about this message unless you encounter trouble loading large array data.\n", + " warnings.warn(\n" + ] + } + ], + "source": [ + "# header for current kernel\n", + "from pyCHX.chx_packages import *\n", + "plt.rcParams.update({'figure.max_open_warning': 0})\n", + "plt.rcParams.update({ 'image.origin': 'lower' })\n", + "plt.rcParams.update({ 'image.interpolation': 'none' })\n", + "\n", + "import sys\n", + "sys.path.insert(0, \"/nsls2/data/chx/shared/CHX_Software/packages/standard_functions/\")\n", + "sys.path.insert(0, \"/nsls2/data/chx/shared/CHX_Software/packages/pass_dict/\")\n", + "from pass_database import *\n", + "from standard_functions import *\n", + "from scipy.optimize import fsolve, differential_evolution,dual_annealing,shgo,direct, Bounds,curve_fit\n", + "from skimage.draw import disk\n", + "from chxtools import xfuncs as xf\n", + "\n", + "%run /nsls2/data/chx/shared/CHX_Software/packages/environment_management/chx_analysis_setup_test_pyCHX.ipynb" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "996c21e1-72e1-4867-87b9-f01c660c4e8c", + "metadata": {}, + "outputs": [], + "source": [ + "import pyFAI\n", + "from pyFAI import calibrant\n", + "from pyFAI import geometryRefinement\n", + "from pyFAI.method_registry import Method,IntegrationMethod" + ] + }, + { + "cell_type": "markdown", + "id": "e8ffbcac-d975-4caa-86b1-ce551b7a953c", + "metadata": {}, + "source": [ + "### Detector Configuration" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "a2549739-cf9d-4f2f-b799-f3d6705dde9c", + "metadata": {}, + "outputs": [], + "source": [ + "use_WAXS_detector = False # IF True: do calculations for both SAXS and WAXS detector, IF False: only do calculations for SAXS detector\n", + "\n", + "### WAXS detector setup (IGNORED IF use_WAXS_detector = False\n", + "waxs_sample_det_distance = .75 #[m]\n", + "#waxs_beam_center=[1050,350] # direct beam position [pixel] 1.8M\n", + "waxs_beam_center=[1150,250]\n", + "#beam_center=[600,350] # direct beam position [pixel] 800k\n", + "waxs_det = 'Pilatus1.8M' #'Pilatus800k'\n", + "waxs_calibrant_name = 'PBBA'#'AgBh'\n", + "\n", + "### SAXS detector setup\n", + "saxs_sample_det_distance = 10 #[m]\n", + "saxs_beam_center=[1000,1000]\n", + "\n", + "saxs_det = 'eiger2_4m' #'Pilatus800k''Pilatus4_2M'\n", + "saxs_calibrant_name = 'nano_lattice_hex'#'PBBA'#'C14H30O'#'AgBh'\n", + "saxs_bst_width_mm = 4 #[mm]\n", + "\n", + "### SAXS entrance window\n", + "saxs_window_position = .15 # position of entrance window downstream of WAXS detector [m] 1) IF use_WAXS_detector = True: position is relative to waxs_sample_det_distance; 2) IF use_WAXS_detector = False: position is relative to nominal sample position\n", + "RW = 5 # radius of entrance window [mm]\n", + "saxs_window_offsset=[0,0] # offset of saxs entrance window from direct beam position [mm]\n", + "\n", + "##### global ##########\n", + "E=9.65 # X-ray energy [keV]\n", + "qunit = 'q_nm^-1'\n", + "#####################################\n", + "wavelength = xf.get_Lambda(E)\n", + "det_dict = {'Pilatus800k':'Pilatus1M','Pilatus1.8M':'Pilatus4_2M'}\n", + "\n", + "#### same conversions\n", + "\n", + "if use_WAXS_detector:\n", + " offset_from_waxs_det = saxs_window_position\n", + "else:\n", + " offset_from_waxs_det = saxs_window_position\n", + " waxs_sample_det_distance=0" + ] + }, + { + "cell_type": "markdown", + "id": "67544783-3bde-4043-a4be-cab00b2fde75", + "metadata": {}, + "source": [ + "### Create a custom calibrant for SAXS" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "abbacd45-522e-4fca-973e-ec04a74a32bd", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Primitive hexagonal cell a=500.0000 b=500.0000 c=1500.0000 alpha=90.000 beta=90.000 gamma=120.000\n" + ] + } + ], + "source": [ + "### create 'calibrant' for SAXS (standard calibrants might not show any rings at typical SAXS Q-ranges...)\n", + "if True:\n", + " from pyFAI.calibrant import Cell\n", + " nano_lattice_hex = Cell.hexagonal(500,1500)\n", + " print(nano_lattice_hex)\n", + " nano_lattice_hex.save(\"nano_lattice_hex\",doi=\"made-up\", dmin=20,dest_dir=\"/nsls2/data/chx/shared/CHX_Setup/custom_calibrants/\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "43c7afa5-e543-470b-9fd8-86da51a109db", + "metadata": {}, + "outputs": [], + "source": [ + "saxs_detector = pyFAI.detector_factory(saxs_det)\n", + "saxs_bst_width = int(np.round(saxs_bst_width_mm/(saxs_detector.pixel1*1E3)))\n", + "saxs_aintegrator=pyFAI.azimuthalIntegrator.AzimuthalIntegrator(dist=saxs_sample_det_distance, poni1=saxs_beam_center[1]*saxs_detector.pixel1, poni2=saxs_beam_center[0]*saxs_detector.pixel2, rot1=0, rot2=0, rot3=0, pixel1=None, pixel2=None, splineFile=None, detector=saxs_detector, wavelength=wavelength)\n", + "try:\n", + " pyFAI.calibrant.ALL_CALIBRANTS(saxs_calibrant_name)\n", + " saxs_calibrant = pyFAI.calibrant.get_calibrant(saxs_calibrant_name,wavelength=wavelength)\n", + " pyFAI.calibrant.Calibrant.save_dSpacing(saxs_calibrant,filename=saxs_calibrant_name) # this is required to use 'calibrant' in geometry refinement...\n", + "except:\n", + " #from pyFAI.calibrant import Calibrant\n", + " saxs_calibrant = pyFAI.calibrant.Calibrant(\"/nsls2/data/chx/shared/CHX_Setup/custom_calibrants/%s.D\"%saxs_calibrant_name, wavelength=wavelength)" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "97dcb472-398e-4185-8ee2-99d793884a69", + "metadata": {}, + "outputs": [], + "source": [ + "if use_WAXS_detector:\n", + " waxs_detector = pyFAI.detector_factory(det_dict[waxs_det])\n", + " aintegrator=pyFAI.azimuthalIntegrator.AzimuthalIntegrator(dist=waxs_sample_det_distance, poni1=waxs_beam_center[1]*waxs_detector.pixel1, poni2=waxs_beam_center[0]*waxs_detector.pixel2, rot1=0, rot2=0, rot3=0, pixel1=None, pixel2=None, splineFile=None, detector=waxs_detector, wavelength=wavelength)\n", + " waxs_calibrant = pyFAI.calibrant.get_calibrant(waxs_calibrant_name,wavelength=wavelength)\n", + " pyFAI.calibrant.Calibrant.save_dSpacing(waxs_calibrant,filename=waxs_calibrant_name) # this is required to use 'calibrant' in geometry refinement..." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "a6ca2acd-c8b9-458e-9cf7-f08b619df69a", + "metadata": {}, + "outputs": [], + "source": [ + "saxs_map = saxs_calibrant.fake_calibration_image(saxs_aintegrator,W=1E-9)+.1\n", + "\n", + "## create beamstop mask for SAXS\n", + "saxs_mask = np.zeros(np.shape(saxs_map))\n", + "hw=int(np.round(saxs_bst_width/2))\n", + "saxs_mask[saxs_beam_center[1]-hw:saxs_beam_center[1]+hw,saxs_beam_center[0]-hw:]=1\n", + "\n", + "if use_WAXS_detector:\n", + " cali_map = waxs_calibrant.fake_calibration_image(aintegrator,W=1E-6)+.1\n", + "\n", + " ## create the corner masks for missing modules\n", + " if waxs_det == 'Pilatus800k':\n", + " corner_mask = np.zeros(np.shape(cali_map))\n", + " corner_mask[0:420,480:]=1\n", + " ## Pilatus1.8M\n", + " if waxs_det == 'Pilatus1.8M':\n", + " corner_mask = np.zeros(np.shape(cali_map))\n", + " corner_mask[0:420,960:]=1\n", + " corner_mask_=np.invert(np.array(corner_mask,dtype=bool))" + ] + }, + { + "cell_type": "markdown", + "id": "f156f450-a38e-4ad5-b359-48c43290f70a", + "metadata": {}, + "source": [ + "### WAXS detector Q-range" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "3503f91b-a176-41e0-80a2-f51173b91457", + "metadata": {}, + "outputs": [], + "source": [ + "if use_WAXS_detector:\n", + " fig,ax = plt.subplots(1,3,figsize=(16,5))\n", + " plt.suptitle('E: %skeV sdd: %sm beam-center: %s detector: %s sample: %s (WAXS)'%(E,waxs_sample_det_distance,waxs_beam_center,waxs_det,waxs_calibrant_name))\n", + " \n", + " plt.subplot(1,3,1)\n", + " plt.imshow(cali_map*corner_mask_)\n", + " plt.plot(waxs_beam_center[0],waxs_beam_center[1],'r+',markersize=10)\n", + " plt.xlabel('x [pixel]');plt.ylabel('y [pixel')\n", + " \n", + " plt.subplot(1,3,2)\n", + " azi= aintegrator.integrate1d(cali_map,npt=1200,mask=corner_mask,unit=qunit)\n", + " plt.loglog(azi[0],azi[1]*np.exp(-(azi[0])**2*.01)+azi[0]**(-2))\n", + " plt.grid(True,which='both');plt.xlabel(qunit);plt.ylabel('I(q) [arb.u.]')\n", + " plt.xlim(left=.5)\n", + " \n", + " plt.subplot(1,3,3)\n", + " mmethod=[]\n", + " for m in IntegrationMethod.select_method(dim=2):\n", + " mmethod.append(m)\n", + " phi_map=aintegrator.integrate2d(cali_map, npt_rad=1200, npt_azim=360,unit=\"q_nm^-1\",mask=corner_mask, method=mmethod[3],polarization_factor=1) \n", + " plt.imshow(phi_map[0],norm='log',extent=[phi_map[1][0], phi_map[1][-1], phi_map[2][0],phi_map[2][-1]],cmap=cmap_albula)\n", + " ax=plt.gca()\n", + " ax.set_aspect('auto')\n", + " plt.xlabel('Q [nm$^{-1}$]');plt.ylabel('$\\Phi$ [$^o$]')\n", + " plt.grid(True,'both',linestyle='--',color='red')\n", + " \n", + " plt.tight_layout()" + ] + }, + { + "cell_type": "markdown", + "id": "ca8b0bbf-acbf-4b06-b835-e560f19a3fa4", + "metadata": {}, + "source": [ + "### calculate shadow of waxs detector and SAXS entrance window on downstream saxs detector" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "b987c52e-4c76-4e2c-bc3d-c4f3cc05f0c9", + "metadata": {}, + "outputs": [], + "source": [ + "if use_WAXS_detector:\n", + " ## WAXS detector shadow\n", + " dpix_x = np.sum(corner_mask[waxs_beam_center[1],:waxs_beam_center[0]])\n", + " dpix_y = np.sum(corner_mask[waxs_beam_center[1]:,waxs_beam_center[0]])\n", + " waxs_shadow_angle_x = np.arctan(dpix_x*waxs_detector.pixel1/waxs_sample_det_distance)\n", + " waxs_shadow_angle_y = np.arctan(dpix_y*waxs_detector.pixel2/waxs_sample_det_distance)\n", + " saxs_shadow_x = saxs_sample_det_distance * np.tan(waxs_shadow_angle_x)\n", + " saxs_shadow_y = saxs_sample_det_distance * np.tan(waxs_shadow_angle_y)\n", + " saxs_shadow_pix_x = int(np.ceil(saxs_shadow_x/saxs_detector.pixel1))\n", + " saxs_shadow_pix_y = int(np.ceil(saxs_shadow_y/saxs_detector.pixel2))\n", + " waxs_detector_shadow_mask = np.ones(np.shape(saxs_mask))\n", + " waxs_detector_shadow_mask[saxs_beam_center[1]+saxs_shadow_pix_y:,:]=0\n", + " if saxs_beam_center[0]-saxs_shadow_pix_x >0:\n", + " waxs_detector_shadow_mask[:,0:saxs_beam_center[0]-saxs_shadow_pix_x]=0\n", + "\n", + "## SAXS entrance window shadow\n", + "alpha = np.arctan((RW/1000)/(offset_from_waxs_det+waxs_sample_det_distance))\n", + "Rpix_shadow = int(np.ceil(saxs_sample_det_distance*np.tan(alpha) / saxs_detector.pixel1))\n", + "saxs_window_offset_pix = [int(np.round(saxs_window_offsset[0]*1E-3/saxs_detector.pixel1)),int(np.round(saxs_window_offsset[1]*1E-3/saxs_detector.pixel2))]\n", + "rr, cc = disk((saxs_beam_center[1]-saxs_window_offset_pix[1], saxs_beam_center[0]+ saxs_window_offset_pix[0]), Rpix_shadow)\n", + "saxs_window_shadow_mask = np.zeros(np.shape(saxs_mask))\n", + "ind1=rr>=0;ind2=cc>=0\n", + "ind3=rr" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "### plotting\n", + "fig,ax = plt.subplots(1,2,figsize=(10,4))\n", + "plt.suptitle('Shadows on SAXS detector %s at %sm'%(saxs_det,saxs_sample_det_distance))\n", + "if use_WAXS_detector:\n", + " plt.subplot(1,2,1)\n", + " plt.imshow(waxs_detector_shadow_mask,vmin=0,vmax=1)\n", + " plt.title('from WAXS detector at %sm'%(waxs_sample_det_distance),fontsize=10)\n", + " plt.plot(saxs_beam_center[0],saxs_beam_center[1],'r+')\n", + " plt.xlabel('x [pixel]');plt.ylabel('y [pixel]')\n", + "\n", + "plt.subplot(1,2,2)\n", + "plt.imshow(saxs_window_shadow_mask,vmin=0,vmax=1)\n", + "plt.plot(saxs_beam_center[0],saxs_beam_center[1],'r+')\n", + "plt.xlabel('x [pixel]');plt.ylabel('y [pixel]')\n", + "plt.title('from window with R=%smm at %sm'%(RW,waxs_sample_det_distance+offset_from_waxs_det),fontsize=10)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "63becf85-087b-497c-b1ef-36065666c3a2", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig,ax = plt.subplots(1,3,figsize=(16,5))\n", + "plt.suptitle('E: %skeV sdd: %sm beam-center: %s detector: %s sample: %s (SAXS)'%(E,saxs_sample_det_distance,saxs_beam_center,saxs_det,saxs_calibrant_name))\n", + "\n", + "plt.subplot(1,3,1)\n", + "if use_WAXS_detector:\n", + " plt.imshow(saxs_map*np.array(saxs_window_shadow_mask,dtype=bool)*np.invert(np.array(saxs_mask,dtype=bool))*np.array(waxs_detector_shadow_mask,dtype=bool),norm='log') \n", + "else:\n", + " plt.imshow(saxs_map*np.invert(np.array(saxs_mask,dtype=bool)),norm='log')\n", + "plt.plot(saxs_beam_center[0],saxs_beam_center[1],'r+',markersize=10)\n", + "plt.xlabel('x [pixel]');plt.ylabel('y [pixel')\n", + "\n", + "plt.subplot(1,3,2)\n", + "if use_WAXS_detector:\n", + " saxs_azi= saxs_aintegrator.integrate1d(saxs_map,mask=np.invert(np.array(saxs_window_shadow_mask,dtype=bool)*np.invert(np.array(saxs_mask,dtype=bool))*np.array(waxs_detector_shadow_mask,dtype=bool)),npt=1200,unit=qunit)\n", + "else:\n", + " saxs_azi= saxs_aintegrator.integrate1d(saxs_map,mask=np.invert(np.array(saxs_window_shadow_mask,dtype=bool)*np.invert(np.array(saxs_mask,dtype=bool))),npt=1200,unit=qunit)\n", + "plt.loglog(saxs_azi[0],saxs_azi[1]*np.exp(-(saxs_azi[0])**2*.01)+1E-4*saxs_azi[0]**(-4))\n", + "plt.grid(True,which='both');plt.xlabel(qunit);plt.ylabel('I(q) [arb.u.]')\n", + "\n", + "plt.subplot(1,3,3)\n", + "mmethod=[]\n", + "for m in IntegrationMethod.select_method(dim=2):\n", + " mmethod.append(m)\n", + "if use_WAXS_detector:\n", + " saxs_phi_map=saxs_aintegrator.integrate2d(saxs_map, mask=np.invert(np.array(saxs_window_shadow_mask,dtype=bool)*np.invert(np.array(saxs_mask,dtype=bool))*np.array(waxs_detector_shadow_mask,dtype=bool)), npt_rad=1200, npt_azim=360,unit=\"q_nm^-1\",method=mmethod[3],polarization_factor=1) \n", + "else:\n", + " saxs_phi_map=saxs_aintegrator.integrate2d(saxs_map, mask=np.invert(np.array(saxs_window_shadow_mask,dtype=bool)*np.invert(np.array(saxs_mask,dtype=bool))), npt_rad=1200, npt_azim=360,unit=\"q_nm^-1\",method=mmethod[3],polarization_factor=1) \n", + "plt.imshow(saxs_phi_map[0],norm='log',extent=[saxs_phi_map[1][0], saxs_phi_map[1][-1], saxs_phi_map[2][0],saxs_phi_map[2][-1]],cmap=cmap_albula)\n", + "ax=plt.gca()\n", + "ax.set_aspect('auto')\n", + "plt.xlabel('Q [nm$^{-1}$]');plt.ylabel('$\\Phi$ [$^o$]')\n", + "plt.grid(True,'both',linestyle='--',color='red')\n", + "\n", + "plt.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "36dc1a01-85db-407a-8b4f-e170533a78a9", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e3d220a1-6072-4b41-809a-0dfe8e752d28", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (fallback)", + "language": "python", + "name": "python3_fallback" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.6" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/pipelines/old_pipelines/XPCS_GISAXS_auto.ipynb b/pipelines/old_pipelines/XPCS_GISAXS_auto.ipynb new file mode 100644 index 0000000..9c8f4c9 --- /dev/null +++ b/pipelines/old_pipelines/XPCS_GISAXS_auto.ipynb @@ -0,0 +1,5871 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 6.9e-05, + "end_time": "2023-06-20T08:53:08.428761", + "exception": false, + "start_time": "2023-06-20T08:53:08.428692", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# XPCS&XSVS Pipeline for Single-(Gi)-SAXS Run\n", + "\n", + "## Overview\n", + "\n", + "* Setup: load packages/setup path\n", + "* Load Metadata & Image Data\n", + "* Apply Mask\n", + "* Clean Data: shutter open/bad frames\n", + "* Get Q-Map\n", + "* Get 1D curve\n", + "* Define Q-ROI (qr, qz)\n", + "* Check beam damage\n", + "* One-time Correlation\n", + "* Fitting\n", + "* Two-time Correlation\n", + "The important scientific code is imported from the [chxanalys](https://github.com/yugangzhang/chxanalys/tree/master/chxanalys) and [scikit-beam](https://github.com/scikit-beam/scikit-beam) project. Refer to chxanalys and scikit-beam for additional documentation and citation information.\n", + "\n", + "\n", + "## CHX Olog Logbook\n", + "CHX Olog (https://logbook.nsls2.bnl.gov/11-ID/) [requires VPN offsite]\n", + "\n", + "## Setup\n", + "\n", + "Import packages for I/O, visualization, and analysis." + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": { + "papermill": { + "duration": 1.299622, + "end_time": "2023-06-20T08:53:09.794917", + "exception": false, + "start_time": "2023-06-20T08:53:08.495295", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[32mrunning on: jupyter_hub environment: standard\n", + "\u001b[0m\n", + "\u001b[36msetting '_base_path_' as /nsls2/data/chx/legacy/analysis/\u001b[0m\n", + "\u001b[36msetting '_base_path_pass_' as /nsls2/data/chx/proposals/\u001b[0m\n", + "\u001b[36msetting '_mask_path_' as /nsls2/data/chx/shared/CHX_Setup/Detector_masks/\n", + "\u001b[0m\n", + "\u001b[32mRe-imported pyCHX from /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/\u001b[0m\n" + ] + }, + { + "data": { + "application/javascript": [ + "/* Put everything inside the global mpl namespace */\n", + "/* global mpl */\n", + "window.mpl = {};\n", + "\n", + "mpl.get_websocket_type = function () {\n", + " if (typeof WebSocket !== 'undefined') {\n", + " return WebSocket;\n", + " } else if (typeof MozWebSocket !== 'undefined') {\n", + " return MozWebSocket;\n", + " } else {\n", + " alert(\n", + " 'Your browser does not have WebSocket support. ' +\n", + " 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n", + " 'Firefox 4 and 5 are also supported but you ' +\n", + " 'have to enable WebSockets in about:config.'\n", + " );\n", + " }\n", + "};\n", + "\n", + "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n", + " this.id = figure_id;\n", + "\n", + " this.ws = websocket;\n", + "\n", + " this.supports_binary = this.ws.binaryType !== undefined;\n", + "\n", + " if (!this.supports_binary) {\n", + " var warnings = document.getElementById('mpl-warnings');\n", + " if (warnings) {\n", + " warnings.style.display = 'block';\n", + " warnings.textContent =\n", + " 'This browser does not support binary websocket messages. ' +\n", + " 'Performance may be slow.';\n", + " }\n", + " }\n", + "\n", + " this.imageObj = new Image();\n", + "\n", + " this.context = undefined;\n", + " this.message = undefined;\n", + " this.canvas = undefined;\n", + " this.rubberband_canvas = undefined;\n", + " this.rubberband_context = undefined;\n", + " this.format_dropdown = undefined;\n", + "\n", + " this.image_mode = 'full';\n", + "\n", + " this.root = document.createElement('div');\n", + " this.root.setAttribute('style', 'display: inline-block');\n", + " this._root_extra_style(this.root);\n", + "\n", + " parent_element.appendChild(this.root);\n", + "\n", + " this._init_header(this);\n", + " this._init_canvas(this);\n", + " this._init_toolbar(this);\n", + "\n", + " var fig = this;\n", + "\n", + " this.waiting = false;\n", + "\n", + " this.ws.onopen = function () {\n", + " fig.send_message('supports_binary', { value: fig.supports_binary });\n", + " fig.send_message('send_image_mode', {});\n", + " if (fig.ratio !== 1) {\n", + " fig.send_message('set_device_pixel_ratio', {\n", + " device_pixel_ratio: fig.ratio,\n", + " });\n", + " }\n", + " fig.send_message('refresh', {});\n", + " };\n", + "\n", + " this.imageObj.onload = function () {\n", + " if (fig.image_mode === 'full') {\n", + " // Full images could contain transparency (where diff images\n", + " // almost always do), so we need to clear the canvas so that\n", + " // there is no ghosting.\n", + " fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n", + " }\n", + " fig.context.drawImage(fig.imageObj, 0, 0);\n", + " };\n", + "\n", + " this.imageObj.onunload = function () {\n", + " fig.ws.close();\n", + " };\n", + "\n", + " this.ws.onmessage = this._make_on_message_function(this);\n", + "\n", + " this.ondownload = ondownload;\n", + "};\n", + "\n", + "mpl.figure.prototype._init_header = function () {\n", + " var titlebar = document.createElement('div');\n", + " titlebar.classList =\n", + " 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n", + " var titletext = document.createElement('div');\n", + " titletext.classList = 'ui-dialog-title';\n", + " titletext.setAttribute(\n", + " 'style',\n", + " 'width: 100%; text-align: center; padding: 3px;'\n", + " );\n", + " titlebar.appendChild(titletext);\n", + " this.root.appendChild(titlebar);\n", + " this.header = titletext;\n", + "};\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n", + "\n", + "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n", + "\n", + "mpl.figure.prototype._init_canvas = function () {\n", + " var fig = this;\n", + "\n", + " var canvas_div = (this.canvas_div = document.createElement('div'));\n", + " canvas_div.setAttribute('tabindex', '0');\n", + " canvas_div.setAttribute(\n", + " 'style',\n", + " 'border: 1px solid #ddd;' +\n", + " 'box-sizing: content-box;' +\n", + " 'clear: both;' +\n", + " 'min-height: 1px;' +\n", + " 'min-width: 1px;' +\n", + " 'outline: 0;' +\n", + " 'overflow: hidden;' +\n", + " 'position: relative;' +\n", + " 'resize: both;' +\n", + " 'z-index: 2;'\n", + " );\n", + "\n", + " function on_keyboard_event_closure(name) {\n", + " return function (event) {\n", + " return fig.key_event(event, name);\n", + " };\n", + " }\n", + "\n", + " canvas_div.addEventListener(\n", + " 'keydown',\n", + " on_keyboard_event_closure('key_press')\n", + " );\n", + " canvas_div.addEventListener(\n", + " 'keyup',\n", + " on_keyboard_event_closure('key_release')\n", + " );\n", + "\n", + " this._canvas_extra_style(canvas_div);\n", + " this.root.appendChild(canvas_div);\n", + "\n", + " var canvas = (this.canvas = document.createElement('canvas'));\n", + " canvas.classList.add('mpl-canvas');\n", + " canvas.setAttribute(\n", + " 'style',\n", + " 'box-sizing: content-box;' +\n", + " 'pointer-events: none;' +\n", + " 'position: relative;' +\n", + " 'z-index: 0;'\n", + " );\n", + "\n", + " this.context = canvas.getContext('2d');\n", + "\n", + " var backingStore =\n", + " this.context.backingStorePixelRatio ||\n", + " this.context.webkitBackingStorePixelRatio ||\n", + " this.context.mozBackingStorePixelRatio ||\n", + " this.context.msBackingStorePixelRatio ||\n", + " this.context.oBackingStorePixelRatio ||\n", + " this.context.backingStorePixelRatio ||\n", + " 1;\n", + "\n", + " this.ratio = (window.devicePixelRatio || 1) / backingStore;\n", + "\n", + " var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n", + " 'canvas'\n", + " ));\n", + " rubberband_canvas.setAttribute(\n", + " 'style',\n", + " 'box-sizing: content-box;' +\n", + " 'left: 0;' +\n", + " 'pointer-events: none;' +\n", + " 'position: absolute;' +\n", + " 'top: 0;' +\n", + " 'z-index: 1;'\n", + " );\n", + "\n", + " // Apply a ponyfill if ResizeObserver is not implemented by browser.\n", + " if (this.ResizeObserver === undefined) {\n", + " if (window.ResizeObserver !== undefined) {\n", + " this.ResizeObserver = window.ResizeObserver;\n", + " } else {\n", + " var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n", + " this.ResizeObserver = obs.ResizeObserver;\n", + " }\n", + " }\n", + "\n", + " this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n", + " var nentries = entries.length;\n", + " for (var i = 0; i < nentries; i++) {\n", + " var entry = entries[i];\n", + " var width, height;\n", + " if (entry.contentBoxSize) {\n", + " if (entry.contentBoxSize instanceof Array) {\n", + " // Chrome 84 implements new version of spec.\n", + " width = entry.contentBoxSize[0].inlineSize;\n", + " height = entry.contentBoxSize[0].blockSize;\n", + " } else {\n", + " // Firefox implements old version of spec.\n", + " width = entry.contentBoxSize.inlineSize;\n", + " height = entry.contentBoxSize.blockSize;\n", + " }\n", + " } else {\n", + " // Chrome <84 implements even older version of spec.\n", + " width = entry.contentRect.width;\n", + " height = entry.contentRect.height;\n", + " }\n", + "\n", + " // Keep the size of the canvas and rubber band canvas in sync with\n", + " // the canvas container.\n", + " if (entry.devicePixelContentBoxSize) {\n", + " // Chrome 84 implements new version of spec.\n", + " canvas.setAttribute(\n", + " 'width',\n", + " entry.devicePixelContentBoxSize[0].inlineSize\n", + " );\n", + " canvas.setAttribute(\n", + " 'height',\n", + " entry.devicePixelContentBoxSize[0].blockSize\n", + " );\n", + " } else {\n", + " canvas.setAttribute('width', width * fig.ratio);\n", + " canvas.setAttribute('height', height * fig.ratio);\n", + " }\n", + " /* This rescales the canvas back to display pixels, so that it\n", + " * appears correct on HiDPI screens. */\n", + " canvas.style.width = width + 'px';\n", + " canvas.style.height = height + 'px';\n", + "\n", + " rubberband_canvas.setAttribute('width', width);\n", + " rubberband_canvas.setAttribute('height', height);\n", + "\n", + " // And update the size in Python. We ignore the initial 0/0 size\n", + " // that occurs as the element is placed into the DOM, which should\n", + " // otherwise not happen due to the minimum size styling.\n", + " if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n", + " fig.request_resize(width, height);\n", + " }\n", + " }\n", + " });\n", + " this.resizeObserverInstance.observe(canvas_div);\n", + "\n", + " function on_mouse_event_closure(name) {\n", + " /* User Agent sniffing is bad, but WebKit is busted:\n", + " * https://bugs.webkit.org/show_bug.cgi?id=144526\n", + " * https://bugs.webkit.org/show_bug.cgi?id=181818\n", + " * The worst that happens here is that they get an extra browser\n", + " * selection when dragging, if this check fails to catch them.\n", + " */\n", + " var UA = navigator.userAgent;\n", + " var isWebKit = /AppleWebKit/.test(UA) && !/Chrome/.test(UA);\n", + " if(isWebKit) {\n", + " return function (event) {\n", + " /* This prevents the web browser from automatically changing to\n", + " * the text insertion cursor when the button is pressed. We\n", + " * want to control all of the cursor setting manually through\n", + " * the 'cursor' event from matplotlib */\n", + " event.preventDefault()\n", + " return fig.mouse_event(event, name);\n", + " };\n", + " } else {\n", + " return function (event) {\n", + " return fig.mouse_event(event, name);\n", + " };\n", + " }\n", + " }\n", + "\n", + " canvas_div.addEventListener(\n", + " 'mousedown',\n", + " on_mouse_event_closure('button_press')\n", + " );\n", + " canvas_div.addEventListener(\n", + " 'mouseup',\n", + " on_mouse_event_closure('button_release')\n", + " );\n", + " canvas_div.addEventListener(\n", + " 'dblclick',\n", + " on_mouse_event_closure('dblclick')\n", + " );\n", + " // Throttle sequential mouse events to 1 every 20ms.\n", + " canvas_div.addEventListener(\n", + " 'mousemove',\n", + " on_mouse_event_closure('motion_notify')\n", + " );\n", + "\n", + " canvas_div.addEventListener(\n", + " 'mouseenter',\n", + " on_mouse_event_closure('figure_enter')\n", + " );\n", + " canvas_div.addEventListener(\n", + " 'mouseleave',\n", + " on_mouse_event_closure('figure_leave')\n", + " );\n", + "\n", + " canvas_div.addEventListener('wheel', function (event) {\n", + " if (event.deltaY < 0) {\n", + " event.step = 1;\n", + " } else {\n", + " event.step = -1;\n", + " }\n", + " on_mouse_event_closure('scroll')(event);\n", + " });\n", + "\n", + " canvas_div.appendChild(canvas);\n", + " canvas_div.appendChild(rubberband_canvas);\n", + "\n", + " this.rubberband_context = rubberband_canvas.getContext('2d');\n", + " this.rubberband_context.strokeStyle = '#000000';\n", + "\n", + " this._resize_canvas = function (width, height, forward) {\n", + " if (forward) {\n", + " canvas_div.style.width = width + 'px';\n", + " canvas_div.style.height = height + 'px';\n", + " }\n", + " };\n", + "\n", + " // Disable right mouse context menu.\n", + " canvas_div.addEventListener('contextmenu', function (_e) {\n", + " event.preventDefault();\n", + " return false;\n", + " });\n", + "\n", + " function set_focus() {\n", + " canvas.focus();\n", + " canvas_div.focus();\n", + " }\n", + "\n", + " window.setTimeout(set_focus, 100);\n", + "};\n", + "\n", + "mpl.figure.prototype._init_toolbar = function () {\n", + " var fig = this;\n", + "\n", + " var toolbar = document.createElement('div');\n", + " toolbar.classList = 'mpl-toolbar';\n", + " this.root.appendChild(toolbar);\n", + "\n", + " function on_click_closure(name) {\n", + " return function (_event) {\n", + " return fig.toolbar_button_onclick(name);\n", + " };\n", + " }\n", + "\n", + " function on_mouseover_closure(tooltip) {\n", + " return function (event) {\n", + " if (!event.currentTarget.disabled) {\n", + " return fig.toolbar_button_onmouseover(tooltip);\n", + " }\n", + " };\n", + " }\n", + "\n", + " fig.buttons = {};\n", + " var buttonGroup = document.createElement('div');\n", + " buttonGroup.classList = 'mpl-button-group';\n", + " for (var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " /* Instead of a spacer, we start a new button group. */\n", + " if (buttonGroup.hasChildNodes()) {\n", + " toolbar.appendChild(buttonGroup);\n", + " }\n", + " buttonGroup = document.createElement('div');\n", + " buttonGroup.classList = 'mpl-button-group';\n", + " continue;\n", + " }\n", + "\n", + " var button = (fig.buttons[name] = document.createElement('button'));\n", + " button.classList = 'mpl-widget';\n", + " button.setAttribute('role', 'button');\n", + " button.setAttribute('aria-disabled', 'false');\n", + " button.addEventListener('click', on_click_closure(method_name));\n", + " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", + "\n", + " var icon_img = document.createElement('img');\n", + " icon_img.src = '_images/' + image + '.png';\n", + " icon_img.srcset = '_images/' + image + '_large.png 2x';\n", + " icon_img.alt = tooltip;\n", + " button.appendChild(icon_img);\n", + "\n", + " buttonGroup.appendChild(button);\n", + " }\n", + "\n", + " if (buttonGroup.hasChildNodes()) {\n", + " toolbar.appendChild(buttonGroup);\n", + " }\n", + "\n", + " var fmt_picker = document.createElement('select');\n", + " fmt_picker.classList = 'mpl-widget';\n", + " toolbar.appendChild(fmt_picker);\n", + " this.format_dropdown = fmt_picker;\n", + "\n", + " for (var ind in mpl.extensions) {\n", + " var fmt = mpl.extensions[ind];\n", + " var option = document.createElement('option');\n", + " option.selected = fmt === mpl.default_extension;\n", + " option.innerHTML = fmt;\n", + " fmt_picker.appendChild(option);\n", + " }\n", + "\n", + " var status_bar = document.createElement('span');\n", + " status_bar.classList = 'mpl-message';\n", + " toolbar.appendChild(status_bar);\n", + " this.message = status_bar;\n", + "};\n", + "\n", + "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n", + " // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n", + " // which will in turn request a refresh of the image.\n", + " this.send_message('resize', { width: x_pixels, height: y_pixels });\n", + "};\n", + "\n", + "mpl.figure.prototype.send_message = function (type, properties) {\n", + " properties['type'] = type;\n", + " properties['figure_id'] = this.id;\n", + " this.ws.send(JSON.stringify(properties));\n", + "};\n", + "\n", + "mpl.figure.prototype.send_draw_message = function () {\n", + " if (!this.waiting) {\n", + " this.waiting = true;\n", + " this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", + " var format_dropdown = fig.format_dropdown;\n", + " var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n", + " fig.ondownload(fig, format);\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_resize = function (fig, msg) {\n", + " var size = msg['size'];\n", + " if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n", + " fig._resize_canvas(size[0], size[1], msg['forward']);\n", + " fig.send_message('refresh', {});\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n", + " var x0 = msg['x0'] / fig.ratio;\n", + " var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n", + " var x1 = msg['x1'] / fig.ratio;\n", + " var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n", + " x0 = Math.floor(x0) + 0.5;\n", + " y0 = Math.floor(y0) + 0.5;\n", + " x1 = Math.floor(x1) + 0.5;\n", + " y1 = Math.floor(y1) + 0.5;\n", + " var min_x = Math.min(x0, x1);\n", + " var min_y = Math.min(y0, y1);\n", + " var width = Math.abs(x1 - x0);\n", + " var height = Math.abs(y1 - y0);\n", + "\n", + " fig.rubberband_context.clearRect(\n", + " 0,\n", + " 0,\n", + " fig.canvas.width / fig.ratio,\n", + " fig.canvas.height / fig.ratio\n", + " );\n", + "\n", + " fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n", + " // Updates the figure title.\n", + " fig.header.textContent = msg['label'];\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n", + " fig.canvas_div.style.cursor = msg['cursor'];\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_message = function (fig, msg) {\n", + " fig.message.textContent = msg['message'];\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n", + " // Request the server to send over a new figure.\n", + " fig.send_draw_message();\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n", + " fig.image_mode = msg['mode'];\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n", + " for (var key in msg) {\n", + " if (!(key in fig.buttons)) {\n", + " continue;\n", + " }\n", + " fig.buttons[key].disabled = !msg[key];\n", + " fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n", + " if (msg['mode'] === 'PAN') {\n", + " fig.buttons['Pan'].classList.add('active');\n", + " fig.buttons['Zoom'].classList.remove('active');\n", + " } else if (msg['mode'] === 'ZOOM') {\n", + " fig.buttons['Pan'].classList.remove('active');\n", + " fig.buttons['Zoom'].classList.add('active');\n", + " } else {\n", + " fig.buttons['Pan'].classList.remove('active');\n", + " fig.buttons['Zoom'].classList.remove('active');\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.updated_canvas_event = function () {\n", + " // Called whenever the canvas gets updated.\n", + " this.send_message('ack', {});\n", + "};\n", + "\n", + "// A function to construct a web socket function for onmessage handling.\n", + "// Called in the figure constructor.\n", + "mpl.figure.prototype._make_on_message_function = function (fig) {\n", + " return function socket_on_message(evt) {\n", + " if (evt.data instanceof Blob) {\n", + " var img = evt.data;\n", + " if (img.type !== 'image/png') {\n", + " /* FIXME: We get \"Resource interpreted as Image but\n", + " * transferred with MIME type text/plain:\" errors on\n", + " * Chrome. But how to set the MIME type? It doesn't seem\n", + " * to be part of the websocket stream */\n", + " img.type = 'image/png';\n", + " }\n", + "\n", + " /* Free the memory for the previous frames */\n", + " if (fig.imageObj.src) {\n", + " (window.URL || window.webkitURL).revokeObjectURL(\n", + " fig.imageObj.src\n", + " );\n", + " }\n", + "\n", + " fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n", + " img\n", + " );\n", + " fig.updated_canvas_event();\n", + " fig.waiting = false;\n", + " return;\n", + " } else if (\n", + " typeof evt.data === 'string' &&\n", + " evt.data.slice(0, 21) === 'data:image/png;base64'\n", + " ) {\n", + " fig.imageObj.src = evt.data;\n", + " fig.updated_canvas_event();\n", + " fig.waiting = false;\n", + " return;\n", + " }\n", + "\n", + " var msg = JSON.parse(evt.data);\n", + " var msg_type = msg['type'];\n", + "\n", + " // Call the \"handle_{type}\" callback, which takes\n", + " // the figure and JSON message as its only arguments.\n", + " try {\n", + " var callback = fig['handle_' + msg_type];\n", + " } catch (e) {\n", + " console.log(\n", + " \"No handler for the '\" + msg_type + \"' message type: \",\n", + " msg\n", + " );\n", + " return;\n", + " }\n", + "\n", + " if (callback) {\n", + " try {\n", + " // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n", + " callback(fig, msg);\n", + " } catch (e) {\n", + " console.log(\n", + " \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n", + " e,\n", + " e.stack,\n", + " msg\n", + " );\n", + " }\n", + " }\n", + " };\n", + "};\n", + "\n", + "function getModifiers(event) {\n", + " var mods = [];\n", + " if (event.ctrlKey) {\n", + " mods.push('ctrl');\n", + " }\n", + " if (event.altKey) {\n", + " mods.push('alt');\n", + " }\n", + " if (event.shiftKey) {\n", + " mods.push('shift');\n", + " }\n", + " if (event.metaKey) {\n", + " mods.push('meta');\n", + " }\n", + " return mods;\n", + "}\n", + "\n", + "/*\n", + " * return a copy of an object with only non-object keys\n", + " * we need this to avoid circular references\n", + " * https://stackoverflow.com/a/24161582/3208463\n", + " */\n", + "function simpleKeys(original) {\n", + " return Object.keys(original).reduce(function (obj, key) {\n", + " if (typeof original[key] !== 'object') {\n", + " obj[key] = original[key];\n", + " }\n", + " return obj;\n", + " }, {});\n", + "}\n", + "\n", + "mpl.figure.prototype.mouse_event = function (event, name) {\n", + " if (name === 'button_press') {\n", + " this.canvas.focus();\n", + " this.canvas_div.focus();\n", + " }\n", + "\n", + " // from https://stackoverflow.com/q/1114465\n", + " var boundingRect = this.canvas.getBoundingClientRect();\n", + " var x = (event.clientX - boundingRect.left) * this.ratio;\n", + " var y = (event.clientY - boundingRect.top) * this.ratio;\n", + "\n", + " this.send_message(name, {\n", + " x: x,\n", + " y: y,\n", + " button: event.button,\n", + " step: event.step,\n", + " modifiers: getModifiers(event),\n", + " guiEvent: simpleKeys(event),\n", + " });\n", + "\n", + " return false;\n", + "};\n", + "\n", + "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n", + " // Handle any extra behaviour associated with a key event\n", + "};\n", + "\n", + "mpl.figure.prototype.key_event = function (event, name) {\n", + " // Prevent repeat events\n", + " if (name === 'key_press') {\n", + " if (event.key === this._key) {\n", + " return;\n", + " } else {\n", + " this._key = event.key;\n", + " }\n", + " }\n", + " if (name === 'key_release') {\n", + " this._key = null;\n", + " }\n", + "\n", + " var value = '';\n", + " if (event.ctrlKey && event.key !== 'Control') {\n", + " value += 'ctrl+';\n", + " }\n", + " else if (event.altKey && event.key !== 'Alt') {\n", + " value += 'alt+';\n", + " }\n", + " else if (event.shiftKey && event.key !== 'Shift') {\n", + " value += 'shift+';\n", + " }\n", + "\n", + " value += 'k' + event.key;\n", + "\n", + " this._key_event_extra(event, name);\n", + "\n", + " this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n", + " return false;\n", + "};\n", + "\n", + "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n", + " if (name === 'download') {\n", + " this.handle_save(this, null);\n", + " } else {\n", + " this.send_message('toolbar_button', { name: name });\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n", + " this.message.textContent = tooltip;\n", + "};\n", + "\n", + "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n", + "// prettier-ignore\n", + "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n", + "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n", + "\n", + "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n", + "\n", + "mpl.default_extension = \"png\";/* global mpl */\n", + "\n", + "var comm_websocket_adapter = function (comm) {\n", + " // Create a \"websocket\"-like object which calls the given IPython comm\n", + " // object with the appropriate methods. Currently this is a non binary\n", + " // socket, so there is still some room for performance tuning.\n", + " var ws = {};\n", + "\n", + " ws.binaryType = comm.kernel.ws.binaryType;\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " function updateReadyState(_event) {\n", + " if (comm.kernel.ws) {\n", + " ws.readyState = comm.kernel.ws.readyState;\n", + " } else {\n", + " ws.readyState = 3; // Closed state.\n", + " }\n", + " }\n", + " comm.kernel.ws.addEventListener('open', updateReadyState);\n", + " comm.kernel.ws.addEventListener('close', updateReadyState);\n", + " comm.kernel.ws.addEventListener('error', updateReadyState);\n", + "\n", + " ws.close = function () {\n", + " comm.close();\n", + " };\n", + " ws.send = function (m) {\n", + " //console.log('sending', m);\n", + " comm.send(m);\n", + " };\n", + " // Register the callback with on_msg.\n", + " comm.on_msg(function (msg) {\n", + " //console.log('receiving', msg['content']['data'], msg);\n", + " var data = msg['content']['data'];\n", + " if (data['blob'] !== undefined) {\n", + " data = {\n", + " data: new Blob(msg['buffers'], { type: data['blob'] }),\n", + " };\n", + " }\n", + " // Pass the mpl event to the overridden (by mpl) onmessage function.\n", + " ws.onmessage(data);\n", + " });\n", + " return ws;\n", + "};\n", + "\n", + "mpl.mpl_figure_comm = function (comm, msg) {\n", + " // This is the function which gets called when the mpl process\n", + " // starts-up an IPython Comm through the \"matplotlib\" channel.\n", + "\n", + " var id = msg.content.data.id;\n", + " // Get hold of the div created by the display call when the Comm\n", + " // socket was opened in Python.\n", + " var element = document.getElementById(id);\n", + " var ws_proxy = comm_websocket_adapter(comm);\n", + "\n", + " function ondownload(figure, _format) {\n", + " window.open(figure.canvas.toDataURL());\n", + " }\n", + "\n", + " var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n", + "\n", + " // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n", + " // web socket which is closed, not our websocket->open comm proxy.\n", + " ws_proxy.onopen();\n", + "\n", + " fig.parent_element = element;\n", + " fig.cell_info = mpl.find_output_cell(\"
\");\n", + " if (!fig.cell_info) {\n", + " console.error('Failed to find cell for figure', id, fig);\n", + " return;\n", + " }\n", + " fig.cell_info[0].output_area.element.on(\n", + " 'cleared',\n", + " { fig: fig },\n", + " fig._remove_fig_handler\n", + " );\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_close = function (fig, msg) {\n", + " var width = fig.canvas.width / fig.ratio;\n", + " fig.cell_info[0].output_area.element.off(\n", + " 'cleared',\n", + " fig._remove_fig_handler\n", + " );\n", + " fig.resizeObserverInstance.unobserve(fig.canvas_div);\n", + "\n", + " // Update the output cell to use the data from the current canvas.\n", + " fig.push_to_output();\n", + " var dataURL = fig.canvas.toDataURL();\n", + " // Re-enable the keyboard manager in IPython - without this line, in FF,\n", + " // the notebook keyboard shortcuts fail.\n", + " IPython.keyboard_manager.enable();\n", + " fig.parent_element.innerHTML =\n", + " '';\n", + " fig.close_ws(fig, msg);\n", + "};\n", + "\n", + "mpl.figure.prototype.close_ws = function (fig, msg) {\n", + " fig.send_message('closing', msg);\n", + " // fig.ws.close()\n", + "};\n", + "\n", + "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n", + " // Turn the data on the canvas into data in the output cell.\n", + " var width = this.canvas.width / this.ratio;\n", + " var dataURL = this.canvas.toDataURL();\n", + " this.cell_info[1]['text/html'] =\n", + " '';\n", + "};\n", + "\n", + "mpl.figure.prototype.updated_canvas_event = function () {\n", + " // Tell IPython that the notebook contents must change.\n", + " IPython.notebook.set_dirty(true);\n", + " this.send_message('ack', {});\n", + " var fig = this;\n", + " // Wait a second, then push the new image to the DOM so\n", + " // that it is saved nicely (might be nice to debounce this).\n", + " setTimeout(function () {\n", + " fig.push_to_output();\n", + " }, 1000);\n", + "};\n", + "\n", + "mpl.figure.prototype._init_toolbar = function () {\n", + " var fig = this;\n", + "\n", + " var toolbar = document.createElement('div');\n", + " toolbar.classList = 'btn-toolbar';\n", + " this.root.appendChild(toolbar);\n", + "\n", + " function on_click_closure(name) {\n", + " return function (_event) {\n", + " return fig.toolbar_button_onclick(name);\n", + " };\n", + " }\n", + "\n", + " function on_mouseover_closure(tooltip) {\n", + " return function (event) {\n", + " if (!event.currentTarget.disabled) {\n", + " return fig.toolbar_button_onmouseover(tooltip);\n", + " }\n", + " };\n", + " }\n", + "\n", + " fig.buttons = {};\n", + " var buttonGroup = document.createElement('div');\n", + " buttonGroup.classList = 'btn-group';\n", + " var button;\n", + " for (var toolbar_ind in mpl.toolbar_items) {\n", + " var name = mpl.toolbar_items[toolbar_ind][0];\n", + " var tooltip = mpl.toolbar_items[toolbar_ind][1];\n", + " var image = mpl.toolbar_items[toolbar_ind][2];\n", + " var method_name = mpl.toolbar_items[toolbar_ind][3];\n", + "\n", + " if (!name) {\n", + " /* Instead of a spacer, we start a new button group. */\n", + " if (buttonGroup.hasChildNodes()) {\n", + " toolbar.appendChild(buttonGroup);\n", + " }\n", + " buttonGroup = document.createElement('div');\n", + " buttonGroup.classList = 'btn-group';\n", + " continue;\n", + " }\n", + "\n", + " button = fig.buttons[name] = document.createElement('button');\n", + " button.classList = 'btn btn-default';\n", + " button.href = '#';\n", + " button.title = name;\n", + " button.innerHTML = '';\n", + " button.addEventListener('click', on_click_closure(method_name));\n", + " button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n", + " buttonGroup.appendChild(button);\n", + " }\n", + "\n", + " if (buttonGroup.hasChildNodes()) {\n", + " toolbar.appendChild(buttonGroup);\n", + " }\n", + "\n", + " // Add the status bar.\n", + " var status_bar = document.createElement('span');\n", + " status_bar.classList = 'mpl-message pull-right';\n", + " toolbar.appendChild(status_bar);\n", + " this.message = status_bar;\n", + "\n", + " // Add the close button to the window.\n", + " var buttongrp = document.createElement('div');\n", + " buttongrp.classList = 'btn-group inline pull-right';\n", + " button = document.createElement('button');\n", + " button.classList = 'btn btn-mini btn-primary';\n", + " button.href = '#';\n", + " button.title = 'Stop Interaction';\n", + " button.innerHTML = '';\n", + " button.addEventListener('click', function (_evt) {\n", + " fig.handle_close(fig, {});\n", + " });\n", + " button.addEventListener(\n", + " 'mouseover',\n", + " on_mouseover_closure('Stop Interaction')\n", + " );\n", + " buttongrp.appendChild(button);\n", + " var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n", + " titlebar.insertBefore(buttongrp, titlebar.firstChild);\n", + "};\n", + "\n", + "mpl.figure.prototype._remove_fig_handler = function (event) {\n", + " var fig = event.data.fig;\n", + " if (event.target !== this) {\n", + " // Ignore bubbled events from children.\n", + " return;\n", + " }\n", + " fig.close_ws(fig, {});\n", + "};\n", + "\n", + "mpl.figure.prototype._root_extra_style = function (el) {\n", + " el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n", + "};\n", + "\n", + "mpl.figure.prototype._canvas_extra_style = function (el) {\n", + " // this is important to make the div 'focusable\n", + " el.setAttribute('tabindex', 0);\n", + " // reach out to IPython and tell the keyboard manager to turn it's self\n", + " // off when our div gets focus\n", + "\n", + " // location in version 3\n", + " if (IPython.notebook.keyboard_manager) {\n", + " IPython.notebook.keyboard_manager.register_events(el);\n", + " } else {\n", + " // location in version 2\n", + " IPython.keyboard_manager.register_events(el);\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype._key_event_extra = function (event, _name) {\n", + " // Check for shift+enter\n", + " if (event.shiftKey && event.which === 13) {\n", + " this.canvas_div.blur();\n", + " // select the cell after this one\n", + " var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n", + " IPython.notebook.select(index + 1);\n", + " }\n", + "};\n", + "\n", + "mpl.figure.prototype.handle_save = function (fig, _msg) {\n", + " fig.ondownload(fig, null);\n", + "};\n", + "\n", + "mpl.find_output_cell = function (html_output) {\n", + " // Return the cell and output element which can be found *uniquely* in the notebook.\n", + " // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n", + " // IPython event is triggered only after the cells have been serialised, which for\n", + " // our purposes (turning an active figure into a static one), is too late.\n", + " var cells = IPython.notebook.get_cells();\n", + " var ncells = cells.length;\n", + " for (var i = 0; i < ncells; i++) {\n", + " var cell = cells[i];\n", + " if (cell.cell_type === 'code') {\n", + " for (var j = 0; j < cell.output_area.outputs.length; j++) {\n", + " var data = cell.output_area.outputs[j];\n", + " if (data.data) {\n", + " // IPython >= 3 moved mimebundle to data attribute of output\n", + " data = data.data;\n", + " }\n", + " if (data['text/html'] === html_output) {\n", + " return [cell, data, j];\n", + " }\n", + " }\n", + " }\n", + " }\n", + "};\n", + "\n", + "// Register the function which deals with the matplotlib target/channel.\n", + "// The kernel may be null if the page has been refreshed.\n", + "if (IPython.notebook.kernel !== null) {\n", + " IPython.notebook.kernel.comm_manager.register_target(\n", + " 'matplotlib',\n", + " mpl.mpl_figure_comm\n", + " );\n", + "}\n" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[32mRe-imported chx_compress from /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/chx_compress.py\u001b[0m\n", + "\u001b[32mRe-imported chx_olog functions from /nsls2/data/chx/shared/CHX_Software/packages/pyCHX/chx_olog.py\u001b[0m\n", + "\u001b[35m\n", + "environment dependent settings and patches:\u001b[0m\n", + "using \"%matplotlib inline\" for plotting\n", + "\u001b[36m--> overwrote '_base_path_' as /nsls2/data/chx/proposals/\u001b[0m\n" + ] + } + ], + "source": [ + "from pyCHX.chx_packages import *\n", + "%matplotlib notebook\n", + "plt.rcParams.update({'figure.max_open_warning': 0})\n", + "plt.rcParams.update({ 'image.origin': 'lower' })\n", + "plt.rcParams.update({ 'image.interpolation': 'none' })\n", + "from pyCHX.chx_xpcs_xsvs_jupyter_V1 import *\n", + "import itertools\n", + "\n", + "import shutil,glob\n", + "from pyCHX.chx_generic_functions import get_roi_mask_qval_qwid_by_shift \n", + "from pyCHX.chx_generic_functions import RemoveHot,create_multi_rotated_rectangle_mask\n", + "\n", + "import sys\n", + "import json\n", + "from time import localtime, strftime\n", + "sys.path.insert(0, \"/nsls2/data/chx/shared/CHX_Software/packages/database_processing/\") # Need a better way to include these directories\n", + "sys.path.insert(0, \"/nsls2/data/chx/shared/CHX_Software/packages/AutoRun_functions/\")\n", + "from database_processing import *\n", + "from AutoRun_functions import *\n", + "\n", + "%run /nsls2/data/chx/shared/CHX_Software/packages/environment_management/chx_analysis_setup_test_pyCHX.ipynb\n", + "_base_path_ = _base_path_pass_\n", + "print(colored(\"--> overwrote '_base_path_' as %s\"%_base_path_,'cyan'))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:53:09.798341", + "exception": false, + "start_time": "2023-06-20T08:53:09.798316", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Control Runs Here" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "scattering geometry: gi_saxs/gi_saxs Phi-analysis: False\n" + ] + } + ], + "source": [ + "scat_geometry = 'gi_saxs' #suport 'saxs', 'gi_saxs', 'ang_saxs' (for anisotropics saxs or flow-xpcs)\n", + "\n", + "\n", + "roi_auto = True #False if True, will automatically create a roi based on the roi_type ( iso/aniso etc), currently only works for SAXS\n", + "fit_peak = False #True\n", + "\n", + "analysis_type_auto = True #if True, will take \"analysis type\" option from data acquisition func series\n", + "qphi_analysis = False #if True, will do q-phi (anisotropic analysis for transmission saxs)\n", + "\n", + "isotropic_Q_mask = 'wide' #'wide' # 'normal' # 'wide' ## select wich Q-mask to use for rings: 'normal' or 'wide'\n", + "phi_Q_mask = 'phi_4x_20deg' #'phi_4x_20deg' #'phi_12x_30deg'\n", + "phi_Q_mask = 'phi_12x30_rot45_fineQ' #'phi_4x_20deg' #'phi_12x_30deg'\n", + " \n", + "auto_bst_mask = True # True: if custom 'XPCS_beam_mask.json' does NOT exist in .../cycle/user/masks, create a default polygon mask for beamstop\n", + "force_compress = False #force to compress data \n", + "use_local_disk = True\n", + "bin_frame = False #generally make bin_frame as False\n", + "bin_frame_number = 4 # ignored if bin_frame == False\n", + "para_compress = True #parallel compress\n", + "# run_fit_form = False #run fit form factor -> to be removed\n", + "mask_outliers = False #!!\n", + "run_waterfall = False #True #False #True #run waterfall analysis\n", + "run_profile_plot = False #run prolfile plot for gi-saxs\n", + "run_t_ROI_Inten = True #run ROI intensity as a function of time\n", + "run_get_mass_center = False # Analysis for mass center of reflective beam center\n", + "run_invariant_analysis = False\n", + "run_one_time = True #run one-time\n", + "cal_g2_error = False #True #calculate g2 signal to noise\n", + "run_fit_g2 = False #run fit one-time, the default function is \"stretched exponential\"\n", + "fit_g2_func = 'stretched'\n", + "run_two_time = True #run two-time\n", + "run_four_time = False #True #True #False #run four-time\n", + "run_xsvs= False # True #False #run visibility analysis\n", + "att_pdf_report = True #attach the pdf report to CHX olog\n", + "qth_interest = 7 #the intested single qth \n", + "\n", + "use_sqnorm = True #if True, use sq to normalize intensity -> what happens if both are true or false?\n", + "use_SG = True #if True, use the Sawitzky-Golay filter of the avg_img for normalization\n", + "use_SG_bin_frames = False #if True, use the Sawitzky-Golay filter of the (binned) frame for normalization \n", + "\n", + "use_imgsum_norm= True #if True use imgsum to normalize intensity for one-time calculatoin -> else it's doing what?\n", + "pdf_version='_%s'%strftime(\"%Y-%m-%d_%H-%M-%S\", localtime()) #for pdf report name\n", + "run_dose = False #run dose_depend analysis\n", + "\n", + "\n", + "if scat_geometry == 'gi_saxs':run_xsvs= False;use_sqnorm=False\n", + "if scat_geometry == 'gi_waxs':use_sqnorm = False\n", + "if scat_geometry != 'saxs':qphi_analysis = False;scat_geometry_ = scat_geometry;roi_auto = False \n", + "else:scat_geometry_ = ['','ang_'][qphi_analysis]+ scat_geometry \n", + "if scat_geometry != 'gi_saxs':run_profile_plot = False\n", + "\n", + "rawdata_link = False # linking raw data in a user sub-folder [sub-folder needs to be created first]\n", + "\n", + "print('scattering geometry: %s/%s Phi-analysis: %s'%(scat_geometry, scat_geometry_, qphi_analysis))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.8e-05, + "end_time": "2023-06-20T08:53:10.127948", + "exception": false, + "start_time": "2023-06-20T08:53:10.127930", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### For 'manual' runs: specify uid" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": { + "papermill": { + "duration": 0.065196, + "end_time": "2023-06-20T08:53:10.259283", + "exception": false, + "start_time": "2023-06-20T08:53:10.194087", + "status": "completed" + }, + "tags": [ + "parameters" + ] + }, + "outputs": [], + "source": [ + "uid = 168515 #(scan num: 142423) (Measurement: 0.02s x 500 fr. Trans:1.0 sample: Membrane )\n", + "#uid = 159757\n", + "#uid = '3e02174a' # (scan num: 151209) (Measurement: 0.1s x 200 fr. Trans:1.0 sample: none )\n", + "\n", + "uid = '12382b68' #(scan num: 168714) (Measurement: )\n", + "uid = '0ae234d7' #(scan num: 186237) (Measurement: XPCS series , expt=0.4, imnum=1000 frames, T=R.T., power=N.A. no growth here, sample=Si - sample 0 )\n", + "\n", + "#####################################################################################################################\n", + "md=get_meta_data(uid)\n", + "username = md['user'] #this will be dynamically asigned as a parameter\n", + "cycle = md['cycle']\n", + "try:\n", + " users = md['user_group']\n", + "except:\n", + " users = []\n", + " \n", + "q_mask_name = '' # do NOT specify, will be created based on Q-Phi mask used and become part of hdf5 filename\n", + "track_progress = False # IF run by papermill with progress tracking, will automatically switch to 'True'" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.7e-05, + "end_time": "2023-06-20T08:53:10.259418", + "exception": false, + "start_time": "2023-06-20T08:53:10.259401", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Papermill inserts into the cell below:" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "papermill": { + "duration": 0.060502, + "end_time": "2023-06-20T08:53:10.383808", + "exception": false, + "start_time": "2023-06-20T08:53:10.323306", + "status": "completed" + }, + "tags": [ + "injected-parameters" + ] + }, + "outputs": [], + "source": [ + "# Parameters\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### creating directory for saving output data " + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [], + "source": [ + "# Data security modification: username for file creation is now the data_session. Should we fix this in the papermill level?\n", + "md=get_meta_data(uid)\n", + "username = md['data_session']" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Results from this analysis will be stashed in the directory /nsls2/data/chx/proposals/2025-3/pass-317286/Results/\n", + "The current uid for analysis is: 0ae234d7...\n", + "Results from this analysis will be stashed in the directory /nsls2/data/chx/proposals/2025-3/pass-317286/Results/0ae234d7-fb12-4f03-8cdb-d64561aa93f0/\n" + ] + } + ], + "source": [ + "default_dir = _base_path_\n", + "data_dir0 = create_user_folder(cycle, username, default_dir if alternate_directory is None else alternate_directory)\n", + "md=get_meta_data(uid)\n", + "uid=md['uid']\n", + "print('The current uid for analysis is: %s...'%uid[:8])\n", + "data_dir = os.path.join(data_dir0, '%s/'%uid)\n", + "os.makedirs(data_dir, exist_ok=True)\n", + "print('Results from this analysis will be stashed in the directory %s' % data_dir)\n", + "uidstr = 'uid=%s'%uid" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### set up progress tracking" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": { + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Not tracking progress...notebook is likely being run outside of papermill\n" + ] + } + ], + "source": [ + "if 'process_id' in locals(): #if process_id has been inserted by papermill\n", + " settings_dict_={'run_one_time':run_one_time,'run_two_time':run_two_time,'xsvs':run_xsvs}\n", + " prog_dict_file = get_progress_dict_filename(uid,md['cycle'],md['user'],default_dir)\n", + " track_progress = create_new_prog_dict_run_XPCS_SAXS(prog_dict_file=prog_dict_file,process_id=process_id,settings_dict=settings_dict_, verbose=True)\n", + "if track_progress:\n", + " print('going to track progress in %s '%prog_dict_file)\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='Load data and compress', progress='start',start_time=time.time(), stop_time=None, verbose=True)\n", + "else: print('Not tracking progress...notebook is likely being run outside of papermill')" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": { + "papermill": { + "duration": 0.610795, + "end_time": "2023-06-20T08:53:11.060747", + "exception": false, + "start_time": "2023-06-20T08:53:10.449952", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "scan_id, full-uid, data path are: 186237--0ae234d7-fb12-4f03-8cdb-d64561aa93f0--/nsls2/data/chx/proposals/2025-3/pass-317286/assets/eiger4m-1/2025/12/11/d44366cd-f55d-4057-86ac_2303_master.h5\n" + ] + } + ], + "source": [ + "sud = get_sid_filenames_v3(db[uid])\n", + "data_fullpath = sud[2]\n", + "\n", + "print ('scan_id, full-uid, data path are: %s--%s--%s'%(sud[0], sud[1], data_fullpath ))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.8e-05, + "end_time": "2023-06-20T08:53:11.060904", + "exception": false, + "start_time": "2023-06-20T08:53:11.060886", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Don't Change the lines below here" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.6e-05, + "end_time": "2023-06-20T08:53:11.131323", + "exception": false, + "start_time": "2023-06-20T08:53:11.131297", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "* get metadata" + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "metadata": { + "papermill": { + "duration": 1.388821, + "end_time": "2023-06-20T08:53:12.578892", + "exception": false, + "start_time": "2023-06-20T08:53:11.190071", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The detectors are:['eiger4m_single_image']\n" + ] + } + ], + "source": [ + "taus=None;g2=None;tausb=None;g2b=None;g12b=None;taus4=None;g4=None;times_xsv=None;contrast_factorL=None; lag_steps = None \n", + "\n", + "md = get_meta_data( uid )\n", + "md_blue = md.copy()\n", + "detectors = sorted(get_detectors(db[uid]))\n", + "print('The detectors are:%s'%detectors)\n", + "if len(detectors) >1:\n", + " md['detector'] = detectors[1]\n", + " print( md['detector'])" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": { + "papermill": { + "duration": 0.070582, + "end_time": "2023-06-20T08:53:12.652922", + "exception": false, + "start_time": "2023-06-20T08:53:12.582340", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Image reverse: True\n", + "Image rotate 90: False\n", + "Will find cx,cy later.\n" + ] + } + ], + "source": [ + "if 'eiger4m' in md['detector'] or md['detector'] == 'image': \n", + " reverse= True\n", + " rot90= False\n", + "elif ('eiger500k' in md['detector']) or ('eiger500K' in md['detector']): \n", + " reverse= True\n", + " rot90=True\n", + "elif 'eiger1m' in md['detector']: \n", + " reverse= True\n", + " rot90=False\n", + "print('Image reverse: %s\\nImage rotate 90: %s'%(reverse, rot90)) \n", + "try:\n", + " cx , cy = md_blue['beam_center_x'], md_blue['beam_center_y']\n", + " print('(cx,cy) = (%s,%s)'%(cx,cy))\n", + "except:\n", + " print('Will find cx,cy later.')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.8e-05, + "end_time": "2023-06-20T08:53:12.658217", + "exception": false, + "start_time": "2023-06-20T08:53:12.658189", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Load ROI defined by \"XPCS_Setup\" Pipeline" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 5.1e-05, + "end_time": "2023-06-20T08:53:12.726548", + "exception": false, + "start_time": "2023-06-20T08:53:12.726497", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "#### Define data analysis type" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": { + "papermill": { + "duration": 0.061195, + "end_time": "2023-06-20T08:53:12.843922", + "exception": false, + "start_time": "2023-06-20T08:53:12.782727", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Will NOT DO qphis analysis.\n", + "gi_saxs\n" + ] + } + ], + "source": [ + "mask_list = check_roi_masknames(_mask_path_+'ROI_masks/')\n", + "iso_masks=[];phi_masks=[]\n", + "for m in mask_list:\n", + " if 'phi' in m: phi_masks.append(m)\n", + " else: iso_masks.append(m)\n", + "\n", + "if analysis_type_auto:#if True, will take \"analysis type\" metadata\n", + " if scat_geometry != 'gi_saxs':\n", + " if md['analysis'] in phi_masks: # specific phi_mask has been requested by data acquisition\n", + " qphi_analysis=True\n", + " phi_Q_mask = md['analysis']\n", + " print('will be using specifically requested Q-Phi-mask: %s'%phi_Q_mask)\n", + " elif md['analysis'] in iso_masks: # specific iso_mask has been requested by data acquisition\n", + " qphi_analysis=False\n", + " isotropic_Q_mask = md['analysis']\n", + " print('will be using specifically requested Q-mask: %s'%isotropic_Q_mask)\n", + " else: # no exact match with existing mask name -> fall back to preselected mask for phi/iso\n", + " qphi_analysis_ = md['analysis'] #if True, will do q-phi (anisotropic analysis for transmission saxs)\n", + " print(md['analysis'])\n", + " if qphi_analysis_ == 'iso':\n", + " qphi_analysis = False\n", + " elif qphi_analysis_ == '':\n", + " qphi_analysis = False\n", + " else:\n", + " qphi_analysis = True \n", + " else:\n", + " try:\n", + " gisaxs_inc_type = md['analysis'] \n", + " except:\n", + " gisaxs_inc_type = None\n", + " print('There is no analysis in metadata.')\n", + " \n", + "print('Will %s qphis analysis.'%['NOT DO','DO'][qphi_analysis]) \n", + "\n", + "if scat_geometry != 'saxs':qphi_analysis = False;scat_geometry_ = scat_geometry \n", + "else:scat_geometry_ = ['','ang_'][qphi_analysis]+ scat_geometry \n", + "if scat_geometry != 'gi_saxs':run_profile_plot = False \n", + " \n", + "print(scat_geometry_) \n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:12.847398", + "exception": false, + "start_time": "2023-06-20T08:53:12.847376", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Load Data" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[32mSUCCESSFULLY LOADED DATA AS dask-array!\u001b[0m\n" + ] + }, + { + "data": { + "text/html": [ + "\n", + " \n", + " \n", + " \n", + " \n", + "
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" + ], + "text/plain": [ + "dask.array" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "try: # preferred: load images as dask_array\n", + " imgs,img_md=load_dask_data(uid,md['detector'], _mask_path_+'pixel_masks/',reverse=reverse,rot90=rot90)\n", + " print(colored('SUCCESSFULLY LOADED DATA AS dask-array!','green'))\n", + "except:\n", + " print(colored('COULD NOT LOAD DATA AS dask-array, reverting to slow data loading....','red'))\n", + " imgs = load_data(uid,md['detector'],reverse=reverse,rot90=rot90)\n", + " img_md=imgs.md\n", + " print(colored('COULD NOT LOAD DATA AS dask-arry, falling back to slow data loading....','red'))\n", + "imgs" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Beam Center: xc: 1044.0 yc: 32.0\n" + ] + } + ], + "source": [ + "md.update( img_md )\n", + "md['number of images'] = int(md['number of images'])\n", + "pixel_mask=np.ones( np.shape(imgs[0]))\n", + "if reverse and not rot90:\n", + " md['beam_center_y']=np.shape(imgs[0])[0]- md['beam_center_y']\n", + "if reverse and rot90:\n", + " xc=md['beam_center_y'];yc=md['beam_center_x']\n", + " yc=np.shape(imgs[0])[0]-yc\n", + " xc=np.shape(imgs[0])[1]-xc\n", + " md['beam_center_y']=yc;md['beam_center_x']=xc\n", + "if rot90 and not reverse:\n", + " raise Exception('ERROR: somebody still needs to figure out the transformation for reverse=%s and rot90=%s!'%(reverse,rot90))\n", + "print('Beam Center: xc: %s yc: %s'%(md['beam_center_x'],md['beam_center_y']))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### create aggregate image of OAV images" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [], + "source": [ + "save_oavs = False\n", + "found_oavs = False\n", + "for d in detectors:\n", + " if 'oav' in d:\n", + " found_oavs=True \n", + " \n", + "if found_oavs:\n", + " try:\n", + " save_oavs_tifs_v2( uid, data_dir )\n", + " save_oavs = True\n", + " print('successfully created aggregate image from individual OAV images')\n", + " except:\n", + " print('Failed to create aggregate image from individual OAV images -> OAV images will not be attached to Olog.') " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1e-05, + "end_time": "2023-06-20T08:53:14.325272", + "exception": false, + "start_time": "2023-06-20T08:53:14.325262", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### load detector mask" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [], + "source": [ + "detector_mask_path = _mask_path_+'pixel_masks/'\n", + "detector_mask_filename = 'detector_mask_%s.json'%md['detector'].split('_')[0]\n", + "json_open=open(detector_mask_path+detector_mask_filename)\n", + "det_mask_dict=json.load(json_open)\n", + "for kk,k in enumerate(list(det_mask_dict['masks'].keys())):\n", + " if kk == 0:\n", + " det_mask=np.array(det_mask_dict['masks'][k],dtype=bool)\n", + " else:\n", + " det_mask*=np.array(det_mask_dict['masks'][k],dtype=bool)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:53:15.500297", + "exception": false, + "start_time": "2023-06-20T08:53:15.500273", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### load beam mask dictionary and re-create polygon mask for current detector and direct beam position" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": { + "papermill": { + "duration": 0.087476, + "end_time": "2023-06-20T08:53:15.656345", + "exception": false, + "start_time": "2023-06-20T08:53:15.568869", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "beam_mask_filename = 'XPCS_beam_mask.json'\n", + "mask_path =default_dir+'%s/%s/masks/'%(cycle,username)\n", + "try:\n", + " json_open=open(mask_path+beam_mask_filename)\n", + " polygon_dict=json.load(json_open)\n", + " print('loading user specified mask from %s'%(mask_path+beam_mask_filename))\n", + "except:\n", + " if auto_bst_mask:\n", + " if scat_geometry == 'saxs':\n", + " print('automatically creating a mask for beamstop and streaks')\n", + " polygon_dict={'masks':{'partial_mask':{'x_off': [0, -80],'y_off': [0, 0], 'wy_left': [20, 0],'wy_right': [10, 36],'wx_up': [20, 0],'wx_down': [20, 0],'center_radius': [0, 0]}}}\n", + " elif scat_geometry == 'gi_saxs':\n", + " polygon_dict={'masks':{'partial_mask':{'x_off': [0, 0],'y_off': [0, 0], 'wy_left': [0, 0],'wy_right': [0, 0],'wx_up': [36, 0],'wx_down': [36, 0],'center_radius': [0, 0]}}}\n", + " else:\n", + " raise Exception('failed to load user specified mask from %s'%(mask_path+beam_mask_filename))" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": { + "papermill": { + "duration": 0.071073, + "end_time": "2023-06-20T08:53:15.731017", + "exception": false, + "start_time": "2023-06-20T08:53:15.659944", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "polygon masks: (could edit dictionary entries to modify mask here)\n" + ] + }, + { + "data": { + "text/plain": [ + "{'partial_mask': {'x_off': [0, 0],\n", + " 'y_off': [0, 0],\n", + " 'wy_left': [0, 0],\n", + " 'wy_right': [0, 0],\n", + " 'wx_up': [36, 0],\n", + " 'wx_down': [36, 0],\n", + " 'center_radius': [0, 0]}}" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "print('polygon masks: (could edit dictionary entries to modify mask here)')\n", + "polygon_dict['masks']" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [], + "source": [ + "#polygon_dict['masks']['partial_mask']['wy_right']= [8, 26]\n", + "#polygon_dict['masks']['partial_mask']['wx_up']= [8, 0]\n", + "#polygon_dict['masks']['partial_mask']['wx_down']= [8, 0]\n", + "#polygon_dict['masks']['partial_mask']['wy_left']= [8, 0]\n", + "#polygon_dict['masks']['partial_mask']['x_off'] = [0, -63]\n", + "\n", + "polygon_dict['masks']['partial_mask']['wy_right']= [8, 46]\n", + "polygon_dict['masks']['partial_mask']['wx_up']= [0, 0]\n", + "polygon_dict['masks']['partial_mask']['wx_down']= [8, 0]\n", + "polygon_dict['masks']['partial_mask']['wy_left']= [8, 0]\n", + "polygon_dict['masks']['partial_mask']['x_off'] = [0, -200]" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.8e-05, + "end_time": "2023-06-20T08:53:15.731673", + "exception": false, + "start_time": "2023-06-20T08:53:15.731655", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "#### re-create multi-polygon mask:" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": { + "papermill": { + "duration": 0.129297, + "end_time": "2023-06-20T08:53:15.924466", + "exception": false, + "start_time": "2023-06-20T08:53:15.795169", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "polygon_mask=np.ones_like( det_mask , dtype = bool)\n", + "if 'rmask' in list(polygon_dict['masks'].keys()):\n", + " rmask_dict={}\n", + " for aa,a in enumerate(polygon_dict['masks']['rmask']['angles']):\n", + " rmask_dict[a] = create_multi_rotated_rectangle_mask( pixel_mask, \n", + " center= [ md['beam_center_x'], md['beam_center_y'] ], length=polygon_dict['masks']['rmask']['length'][aa], width=polygon_dict['masks']['rmask']['width'][aa], angles=[a] )\n", + "\n", + " for aa,a in enumerate(list(rmask_dict.keys())):\n", + " if aa == 0:\n", + " rmask = rmask_dict[a]\n", + " else:\n", + " rmask*=rmask_dict[a]\n", + " polygon_mask*=rmask\n", + "if 'partial_mask' in list(polygon_dict['masks'].keys()):\n", + " partialmask_dict={}\n", + " for ii,i in enumerate(range(len(polygon_dict['masks']['partial_mask']['x_off']))[:]): # [:] use all elements in list; [:2] use the first two elements in list, etc. to create masks\n", + " partialmask_dict[ii] = create_cross_mask( pixel_mask,center= [ md['beam_center_x']+polygon_dict['masks']['partial_mask']['x_off'][i], md['beam_center_y']+polygon_dict['masks']['partial_mask']['y_off'][i] ], \n", + " wy_left= polygon_dict['masks']['partial_mask']['wy_left'][i], wy_right= polygon_dict['masks']['partial_mask']['wy_right'][i], \n", + " wx_up= polygon_dict['masks']['partial_mask']['wx_up'][i], wx_down= polygon_dict['masks']['partial_mask']['wx_down'][i],center_radius= polygon_dict['masks']['partial_mask']['center_radius'][i])\n", + " \n", + " for i in list(partialmask_dict.keys()):\n", + " if i == 0:\n", + " partial_mask = partialmask_dict[i]\n", + " else:\n", + " partial_mask*=partialmask_dict[i]\n", + " polygon_mask*=partial_mask\n", + "if 'window_mask' in list(polygon_dict['masks'].keys()):\n", + " try: # center_circle has been renamed to center_disk at some point -> with try this works on old and new environements\n", + " window_shadow = ~create_cross_mask( pixel_mask, center=[md['beam_center_x'],md['beam_center_y']],\n", + " wy_left= 0, wy_right= 0, \n", + " wx_up= 0, wx_down= 0,center_disk=True, center_radius= polygon_dict['masks']['window_mask']['center_radius'])\n", + " except:\n", + " window_shadow = ~create_cross_mask( pixel_mask, center=[md['beam_center_x'],md['beam_center_y']],\n", + " wy_left= 0, wy_right= 0, \n", + " wx_up= 0, wx_down= 0,center_circle=True, center_radius= polygon_dict['masks']['window_mask']['center_radius'])\n", + " print('using \"create_cross_mask\" for older python environments')\n", + " polygon_mask*=window_shadow" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": { + "papermill": { + "duration": 0.915534, + "end_time": "2023-06-20T08:53:17.094650", + "exception": false, + "start_time": "2023-06-20T08:53:16.179116", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig,ax = plt.subplots(1,3,figsize=(15,5))\n", + "plt.suptitle('detector mask: %s\\nbeam mask: %s'%(mask_path+detector_mask_filename,mask_path+beam_mask_filename))\n", + "\n", + "plt.subplot(1,3,1)\n", + "plt.title('detector mask')\n", + "plt.imshow( det_mask)\n", + "plt.subplot(1,3,2)\n", + "plt.title('beam mask')\n", + "plt.imshow(polygon_mask)\n", + "plt.subplot(1,3,3)\n", + "plt.title('combined mask')\n", + "mask=polygon_mask*det_mask \n", + "plt.imshow(mask)\n", + "mask_copy=mask.copy()" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": { + "papermill": { + "duration": 0.07127, + "end_time": "2023-06-20T08:53:17.274749", + "exception": false, + "start_time": "2023-06-20T08:53:17.203479", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "suid--> 0ae234d7-fb12-4f03-8cdb-d64561aa93f0\n", + "number of images--> 1000\n", + "uid--> 0ae234d7-fb12-4f03-8cdb-d64561aa93f0\n", + "scan_id--> 186237\n", + "start_time--> 2025-12-11 15:29:25\n", + "stop_time--> 2025-12-11 15:36:11\n", + "sample--> Si - sample 0\n", + "Measurement--> XPCS series , expt=0.4, imnum=1000 frames, T=R.T., power=N.A. no growth here, sample=Si - sample 0\n", + "acquire period--> 0.4\n", + "exposure time--> 0.4\n", + "beam_center_x--> 1044.0\n", + "beam_center_y--> 32.0\n" + ] + } + ], + "source": [ + "print_dict( md, ['suid', 'number of images', 'uid', 'scan_id', 'start_time', 'stop_time', 'sample', 'Measurement',\n", + " 'acquire period', 'exposure time', \n", + " 'det_distance', 'beam_center_x', 'beam_center_y', ] )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.6e-05, + "end_time": "2023-06-20T08:53:17.276413", + "exception": false, + "start_time": "2023-06-20T08:53:17.276397", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Overwrite Some Metadata if Wrong Input" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:17.336854", + "exception": false, + "start_time": "2023-06-20T08:53:17.336832", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Define incident beam center (also define reflection beam center for gisaxs)" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": { + "papermill": { + "duration": 0.060425, + "end_time": "2023-06-20T08:53:17.715880", + "exception": false, + "start_time": "2023-06-20T08:53:17.655455", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "inc_x0, inc_y0, refl_x0,refl_y0 are: 32.0 1044.0 1044.0 667.9130061245271.\n" + ] + } + ], + "source": [ + "\n", + "if scat_geometry =='gi_saxs':\n", + "\n", + " d=md['detector'].split('_image')[0]\n", + " sample_detector_distance = md[d+'_det_distance']*1000\n", + " #inc_ang = abs(md['inc_ang'])\n", + " inc_ang = 0.46\n", + " \n", + " inc_y0 = md['beam_center_x'] \n", + " inc_x0 = md['beam_center_y'] \n", + "\n", + " #we need to figure out the mask orientation\n", + " #inc_x0 = imgs[0].shape[0]-md['beam_center_y'] \n", + " #inc_y0 = md['beam_center_x'] \n", + " \n", + " #1147 ,1550\n", + " refl_x0 = md['beam_center_x'] \n", + " #refl_y0 = 1600.645 # calculated for an incidence angle of 0.32 deg \n", + " refl_y0 = np.tan(2* np.radians(inc_ang))*sample_detector_distance/0.075 + md['beam_center_y']\n", + " \n", + " print( \"inc_x0, inc_y0, refl_x0,refl_y0 are: %s %s %s %s.\"%(inc_x0, inc_y0, refl_x0, refl_y0) )\n", + "else:\n", + " inc_y0 = md['beam_center_y']\n", + " inc_x0 = md['beam_center_x']\n", + "\n", + "#if scat_geometry =='gi_saxs':\n", + "# inc_x0 = md['beam_center_x'] \n", + "# inc_y0 = imgs[0].shape[0] - md['beam_center_x'] \n", + "# #1147 ,1550\n", + "# refl_x0 = md['beam_center_x'] \n", + "# refl_y0 = 1600.645 # calculated for an incidence angle of 0.32 deg \n", + "# \n", + "# print( \"inc_x0, inc_y0, ref_x0,ref_y0 are: %s %s %s %s.\"%(inc_x0, inc_y0, refl_x0, refl_y0) )\n", + "#else:\n", + "# inc_y0 = md['beam_center_y']\n", + "# inc_x0 = md['beam_center_x']\n", + "# \n", + "# if md['detector'] =='eiger4m_single_image' or md['detector'] == 'image' or md['detector']=='eiger1m_single_image': \n", + "# inc_x0 = imgs[0].shape[0] - md['beam_center_y'] \n", + "# inc_y0= md['beam_center_x']\n", + "# elif md['detector'] =='eiger500K_single_image': \n", + "# #inc_y0 = imgs[0].shape[1] - md['beam_center_y'] ### Changed this...not clear why\n", + "# #inc_x0 = imgs[0].shape[0] - md['beam_center_x']\n", + "# inc_x0 = imgs[0].shape[1]-md['beam_center_y']\n", + "# inc_y0 = md['beam_center_x']\n", + " \n", + " \n", + "# print(inc_x0, inc_y0)\n", + "\n", + " ###for this particular uid, manually give x0/y0\n", + " #inc_x0 = 1041\n", + " #inc_y0 = 1085" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": { + "papermill": { + "duration": 0.06776, + "end_time": "2023-06-20T08:53:17.787324", + "exception": false, + "start_time": "2023-06-20T08:53:17.719564", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Beam_center_x has been changed to 1044.0. (no change in raw metadata): \n", + "Beam_center_y has been changed to 32.0. (no change in raw metadata): \n", + "uid--> uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0\n", + "dpix--> 0.075\n", + "Ldet--> 2970.0\n", + "lambda_--> 1.284411047686732\n", + "exposuretime--> 0.399997\n", + "timeperframe--> 0.4\n", + "center--> [1044, 32]\n", + "path--> /nsls2/data/chx/proposals/2025-3/pass-317286/Results/0ae234d7-fb12-4f03-8cdb-d64561aa93f0/\n" + ] + } + ], + "source": [ + "dpix, lambda_, Ldet, exposuretime, timeperframe, center = check_lost_metadata(\n", + " md, md['number of images'], inc_x0 = inc_x0, inc_y0= inc_y0, pixelsize = 7.5*10*(-5) )\n", + "if scat_geometry =='gi_saxs':center=center[::-1]\n", + "\n", + "setup_pargs=dict(uid=uidstr, dpix= dpix, Ldet=Ldet, lambda_= lambda_, exposuretime=exposuretime,\n", + " timeperframe=timeperframe, center=center, path= data_dir)\n", + "print_dict( setup_pargs )\n" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": { + "papermill": { + "duration": 0.595578, + "end_time": "2023-06-20T08:53:18.574809", + "exception": false, + "start_time": "2023-06-20T08:53:17.979231", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "show_img(np.array(mask,dtype=int),image_name = uidstr + '_mask', save=False, path=data_dir, aspect=1, center=center)\n", + "mask_load=mask.copy()\n", + "\n", + "imgsa = apply_mask( imgs, np.array(mask,dtype=int) )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.7e-05, + "end_time": "2023-06-20T08:53:18.574944", + "exception": false, + "start_time": "2023-06-20T08:53:18.574927", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Check several frames average intensity" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 4.5e-05, + "end_time": "2023-06-20T08:53:18.651470", + "exception": false, + "start_time": "2023-06-20T08:53:18.651425", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "#### Load ROI mask depending on data analysis type" + ] + }, + { + "cell_type": "code", + "execution_count": 251, + "metadata": { + "papermill": { + "duration": 4.591728, + "end_time": "2023-06-20T08:53:23.364728", + "exception": false, + "start_time": "2023-06-20T08:53:18.773000", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The static mask is: /nsls2/data/chx/proposals/2025-3/pass-317286/masks/uid=0ae234d7_roi_masks.pkl.\n", + "The dynamic mask is: /nsls2/data/chx/proposals/2025-3/pass-317286/masks/uid=0ae234d7_roi_mask.pkl.\n", + "The qmap is: /nsls2/data/chx/proposals/2025-3/pass-317286/masks/uid=0ae234d7_qmap.pkl.\n" + ] + } + ], + "source": [ + "roi_date = 'June20_2024'\n", + "\n", + "if scat_geometry =='saxs':\n", + " ## For auto load roi mask\n", + " if roi_auto: \n", + " general_path = _mask_path_+'ROI_masks/'\n", + " if qphi_analysis == False:\n", + " fp = general_path + 'general_roi_mask_%s.json'%isotropic_Q_mask\n", + " q_mask_name = isotropic_Q_mask\n", + " elif qphi_analysis:\n", + " fp = general_path + 'general_roi_mask_%s.json'%phi_Q_mask\n", + " q_mask_name = phi_Q_mask \n", + " \n", + " f = open(fp) ### load json file\n", + " tmp = json.load(f);f.close()\n", + " mask_dict=json.loads(tmp);del tmp\n", + " roi_mask0 = np.array(mask_dict['roi_mask']) \n", + " old_cen=mask_dict['original center'] \n", + " ## NOTE: new_\"cen below\" is actually ignored: function is hardcoded to use setup_pargs['center'] as center ####\n", + " # as the roi masks were not created using the physically correct orientations of the detectors, we'll need to fudge something here...\n", + " if \"eiger500k\" in md['detector']:\n", + " setup_pargs['center']=center[::-1]\n", + " if \"eiger4m\" in md['detector']:\n", + " setup_pargs['center']=center[::-1]\n", + " roi_mask, qval_dict, qwid_dict = get_roi_mask_qval_qwid_by_shift( \n", + " new_cen=[0,0], new_mask= mask, old_cen=old_cen,\n", + " old_roi_mask=roi_mask0, limit_qnum= 180,\n", + " setup_pargs= setup_pargs, geometry = scat_geometry_,\n", + " ) \n", + " ## undo fudging:\n", + " setup_pargs['center']=center\n", + " \n", + " else: \n", + " if qphi_analysis == False:\n", + " if isotropic_Q_mask == 'normal':\n", + " #print('Here')\n", + " q_mask_name='rings'\n", + " if \"eiger4m\" in md['detector'] or md['detector'] == 'image': #for 4M \n", + " fp = roi_path + 'roi_mask_%s_4M_norm.pkl'%roi_date \n", + "\n", + " elif (\"eiger500k\" in md['detector']) or (\"eiger500K\" in md['detector']): #for 500K \n", + " fp = roi_path + 'roi_mask_%s_500K_norm.pkl'%roi_date \n", + "\n", + "\n", + " elif isotropic_Q_mask == 'wide':\n", + " q_mask_name='wide_rings'\n", + " if \"eiger4m\" in md['detector'] or md['detector'] == 'image': #for 4M \n", + " fp = roi_path + 'roi_mask_%s_4M_wide.pkl'%roi_date \n", + " elif (\"eiger500k\" in md['detector']) or (\"eiger500K\" in md['detector']): #for 500K \n", + " fp = roi_path + 'roi_mask_%s_500K_wide.pkl'%roi_date \n", + "\n", + "\n", + " elif qphi_analysis:\n", + " if phi_Q_mask =='phi_4x_20deg':\n", + " q_mask_name='phi_4x_20deg'\n", + " if md['detector'] =='eiger4m_single_image' or md['detector'] == 'image': #for 4M \n", + " fp = roi_path + 'roi_mask_%s_4M_phi_4x_20deg.pkl'%roi_date \n", + " fp = roi_path + 'roi_mask_%s_4M_phi_24x_15deg.pkl'%roi_date \n", + " \n", + " elif (md['detector'] =='eiger500k_single_image') or (md['detector'] == \"eiger500K_single_image\"): #for 500K \n", + " fp = roi_path + 'roi_mask_%s_500K_phi_4x_20deg.pkl'%roi_date \n", + "\n", + " \n", + " roi_mask,qval_dict = cpk.load( open(fp, 'rb' ) ) #for load the saved roi data\n", + " print(fp)\n", + "\n", + "## Gi_SAXS \n", + "elif scat_geometry =='gi_saxs': \n", + " # static mask \n", + " #fp = default_dir + md['cycle'] +'/masks/uid=%s_roi_masks.pkl'%ss\n", + "\n", + " user_mask_path = default_dir + md['cycle']+'/'+username+'/masks/'\n", + " ss = '0ae234d7'\n", + " #ss = 'd8d7cdce'\n", + " # static mask \n", + " fp = user_mask_path+'uid=%s_roi_masks.pkl'%ss\n", + " roi_masks,qval_dicts = cpk.load( open(fp, 'rb' ) ) #for load the saved roi data \n", + " print('The static mask is: %s.'%fp) \n", + "\n", + " fp = default_dir + md['cycle'] + '/' + username +'/masks/uid=%s_roi_mask.pkl'%(ss)\n", + " roi_mask,qval_dict = cpk.load( open(fp, 'rb' ) ) #for load the saved roi data\n", + " print('The dynamic mask is: %s.'%fp)\n", + " # q-map\n", + " fp = default_dir + md['cycle'] + '/' +username +'/masks/uid=%s_qmap.pkl'%(ss)\n", + " #print(fp)\n", + " qr_map, qz_map, ticks, Qrs, Qzs, Qr, Qz, inc_x0,refl_x0, refl_y0 = cpk.load( open(fp, 'rb' ) )\n", + " print('The qmap is: %s.'%fp)\n", + " \n", + "## WAXS \n", + "elif scat_geometry =='gi_waxs': \n", + " \n", + " fp = default_dir + md['cycle'] +'/masks/uid=278c0df1_roi_mask.pkl'\n", + " \n", + " roi_mask,qval_dict = cpk.load( open(fp, 'rb' ) ) #for load the saved roi data\n", + "\n", + "roi_mask2 = roi_mask.copy()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 252, + "metadata": { + "papermill": { + "duration": 0.291226, + "end_time": "2023-06-20T08:53:23.656043", + "exception": false, + "start_time": "2023-06-20T08:53:23.364817", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#roi_mask = shift_mask(roi_mask, 10,30) #if shift mask to get new mask\n", + "show_img(roi_masks, aspect=1.0, image_name = \"\", center=center,vmin=0)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 253, + "metadata": { + "papermill": { + "duration": 1.24473, + "end_time": "2023-06-20T08:53:24.902640", + "exception": false, + "start_time": "2023-06-20T08:53:23.657910", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "img_choice_N = 5\n", + "img_samp_index = random.sample( range(md['number of images']), img_choice_N) \n", + "avg_img = get_avg_img( imgsa, img_samp_index, plot_ = False, uid =uidstr)\n", + "if avg_img.max() == 0:\n", + " print('There are no photons recorded for this uid: %s'%uid)\n", + " print('The data analysis should be terminated! Please try another uid.')" + ] + }, + { + "cell_type": "code", + "execution_count": 254, + "metadata": { + "papermill": { + "duration": 0.470349, + "end_time": "2023-06-20T08:53:25.374747", + "exception": false, + "start_time": "2023-06-20T08:53:24.904398", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "show_img( imgsa[ 5], vmin = .01, vmax = 5, logs=False, aspect=1, #save_format='tif',\n", + " image_name= uidstr + '_img_avg', save=True, path=data_dir, cmap=cmap_albula,center=center)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.3e-05, + "end_time": "2023-06-20T08:53:25.377076", + "exception": false, + "start_time": "2023-06-20T08:53:25.377053", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Compress Data\n", + "* Generate a compressed data with filename\n", + "* Replace old mask with a new mask with removed hot pixels\n", + "* Do average image\n", + "* Do each image sum\n", + "* Find badframe_list for where image sum above bad_pixel_threshold\n", + "* Check shutter open frame to get good time series\n" + ] + }, + { + "cell_type": "code", + "execution_count": 255, + "metadata": { + "papermill": { + "duration": 0.195835, + "end_time": "2023-06-20T08:53:25.642595", + "exception": false, + "start_time": "2023-06-20T08:53:25.446760", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The non-zeros photon occupation is 0.0003361364695286567.\n", + "Will Always DO apply compress process.\n" + ] + } + ], + "source": [ + "compress=True\n", + "photon_occ = len( np.where(avg_img)[0] ) / ( np.shape(imgsa[0])[0]*np.shape(imgsa[0])[1]*md['number of images'])\n", + "#compress = photon_occ < .4 #if the photon ocupation < 0.5, do compress\n", + "print (\"The non-zeros photon occupation is %s.\"%( photon_occ))\n", + "print(\"Will \" + 'Always ' + ['NOT', 'DO'][compress] + \" apply compress process.\")" + ] + }, + { + "cell_type": "code", + "execution_count": 256, + "metadata": { + "papermill": { + "duration": 0.059335, + "end_time": "2023-06-20T08:53:25.703430", + "exception": false, + "start_time": "2023-06-20T08:53:25.644095", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "first frame to be used: 0\n", + "frame binning: 1\n" + ] + } + ], + "source": [ + "if \"eiger4m\" in md['detector'] or md['detector'] == 'image': \n", + " good_start = 0 #make the good_start at least 0\n", + "elif (\"eiger500k\" in md['detector']) or (\"eiger500K\" in md['detector']): \n", + " good_start = 0#100 #5 #make the good_start at least 0\n", + "elif \"eiger1m\" in md['detector'] or md['detector'] == 'image': \n", + " good_start = 0 \n", + " \n", + "if bin_frame:\n", + " bin_frame_number=bin_frame_number\n", + " acquisition_period = md['acquire period']\n", + " timeperframe = acquisition_period * bin_frame_number\n", + "else:\n", + " bin_frame_number =1\n", + "print('first frame to be used: %s\\nframe binning: %s'%(good_start,bin_frame_number))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.4e-05, + "end_time": "2023-06-20T08:53:25.835315", + "exception": false, + "start_time": "2023-06-20T08:53:25.835301", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### change compression behavior if necessary" + ] + }, + { + "cell_type": "code", + "execution_count": 257, + "metadata": { + "papermill": { + "duration": 0.067655, + "end_time": "2023-06-20T08:53:25.963892", + "exception": false, + "start_time": "2023-06-20T08:53:25.896237", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "force compression: False use local disk: True\n" + ] + } + ], + "source": [ + "#force_compress = False\n", + "#use_local_disk = True\n", + "print('force compression: %s use local disk: %s'%(force_compress,use_local_disk))" + ] + }, + { + "cell_type": "code", + "execution_count": 258, + "metadata": { + "papermill": { + "duration": 19.133555, + "end_time": "2023-06-20T08:53:45.099043", + "exception": false, + "start_time": "2023-06-20T08:53:25.965488", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Using already created compressed file with filename as :/nsls2/data/chx/proposals/2025-3/pass-317286/Compressed_Data/uid_0ae234d7-fb12-4f03-8cdb-d64561aa93f0.cmp.\n", + "The good_start frame number is: 0 \n", + "uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_fra_0_1000\n", + "Total time: 0.027 sec\n" + ] + }, + { + "data": { + "image/png": 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "imgs_=np.ones(md['number of images']) #just need to fake an array of appropriate length for the compression routine\n", + "\n", + "import time\n", + "t0= time.time()\n", + "\n", + "# if not use_local_disk:\n", + "# cmp_path = '/nsls2/data/chx/legacy/Compressed_Data'\n", + "# else:\n", + "# cmp_path = '/tmp_data/compressed'\n", + "# print(here)\n", + " \n", + " \n", + "cmp_path = data_dir0[:-8] + 'Compressed_Data' \n", + "if bin_frame_number==1: \n", + " cmp_file = '/uid_%s.cmp'%md['uid']\n", + "else:\n", + " cmp_file = '/uid_%s_bined--%s.cmp'%(md['uid'],bin_frame_number)\n", + "\n", + "#force_compress = True\n", + "filename = cmp_path + cmp_file \n", + "mask2, avg_img, imgsum, bad_frame_list = compress_eigerdata(imgs_, det_mask, md, filename, ########## NEW: mask -> det_mask\n", + " force_compress= force_compress, para_compress= para_compress, bad_pixel_threshold = 1e14,\n", + " reverse=reverse, rot90=rot90, nobytes=4,\n", + " bins=bin_frame_number, num_sub= 100, num_max_para_process= 500, with_pickle=True,\n", + " direct_load_data =use_local_disk, data_path = data_fullpath, new_path = '/tmp/' ) \n", + " \n", + "min_inten = 10 \n", + "good_start = max(good_start, np.where( np.array(imgsum) > min_inten )[0][0] ) \n", + "print ('The good_start frame number is: %s '%good_start)\n", + "\n", + "FD = Multifile(filename, good_start, len(imgs_)//bin_frame_number )\n", + "\n", + "\n", + "uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + "print( uid_ )\n", + "plot1D( y = imgsum[ np.array( [i for i in np.arange(good_start, len(imgsum)) if i not in bad_frame_list])],\n", + " title =uidstr + '_imgsum', xlabel='Frame', ylabel='Total_Intensity', legend='imgsum' )\n", + "Nimg = int( md['number of images']/bin_frame_number )\n", + "run_time(t0)\n", + "\n", + "# mask2 = mask * pixel_mask * Chip_Mask\n", + "mask_copy = mask.copy()\n", + "mask_copy2 = mask.copy()\n", + "\n", + "#avg_img *= mask\n", + "\n", + "show_img( avg_img, vmin=1e-1, vmax= 1e2, logs=True, aspect=1, #save_format='tif',\n", + " image_name= uidstr + '_img_avg', save=True, \n", + " path=data_dir, center=center, cmap = cmap_albula )" + ] + }, + { + "cell_type": "code", + "execution_count": 259, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "if track_progress:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='Load data and compress', progress='stop',start_time=None, stop_time=time.time(), verbose=True)\n", + " if settings_dict_['run_one_time']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='run_one_time', progress='start',start_time=time.time(), stop_time=None, verbose=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:45.101921", + "exception": false, + "start_time": "2023-06-20T08:53:45.101899", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Get bad frame list by a polynominal fit" + ] + }, + { + "cell_type": "code", + "execution_count": 260, + "metadata": { + "papermill": { + "duration": 0.071967, + "end_time": "2023-06-20T08:53:45.251004", + "exception": false, + "start_time": "2023-06-20T08:53:45.179037", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "good_end= None # 2000 \n", + "if good_end is not None:\n", + " FD = Multifile(filename, good_start, min( len(imgs_)//bin_frame_number, good_end) )\n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( uid_ )\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 261, + "metadata": { + "papermill": { + "duration": 0.067784, + "end_time": "2023-06-20T08:53:45.324256", + "exception": false, + "start_time": "2023-06-20T08:53:45.256472", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "re_define_good_start =False\n", + "if re_define_good_start:\n", + " good_start = 180\n", + " #good_end = 19700\n", + " good_end = len(imgs_)\n", + " FD = Multifile(filename, good_start, good_end) \n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( FD.beg, FD.end)" + ] + }, + { + "cell_type": "code", + "execution_count": 262, + "metadata": { + "papermill": { + "duration": 0.44143, + "end_time": "2023-06-20T08:53:45.767239", + "exception": false, + "start_time": "2023-06-20T08:53:45.325809", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/nsls2/data/chx/shared/CHX_Software/packages/pyCHX/chx_generic_functions.py:2794: RankWarning: Polyfit may be poorly conditioned\n", + " pol = np.polyfit(x, y, order)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The bad frame list length is: 29\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "bad_frame_list = get_bad_frame_list( imgsum, fit='both', plot=True,polyfit_order = 30, \n", + " scale= 3.5, good_start = good_start, good_end=good_end, uid= uidstr, path=data_dir)\n", + "\n", + "print( 'The bad frame list length is: %s'%len(bad_frame_list) )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:45.769771", + "exception": false, + "start_time": "2023-06-20T08:53:45.769749", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Create new mask by masking the bad pixels and get new avg_img" + ] + }, + { + "cell_type": "code", + "execution_count": 263, + "metadata": { + "papermill": { + "duration": 0.069057, + "end_time": "2023-06-20T08:53:45.916919", + "exception": false, + "start_time": "2023-06-20T08:53:45.847862", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "number of bad pixels masked: 971\n" + ] + } + ], + "source": [ + "imgsum_y = imgsum[ np.array( [i for i in np.arange( len(imgsum)) if i not in bad_frame_list])]\n", + "imgsum_x = np.arange( len( imgsum_y))\n", + "save_lists( [imgsum_x, imgsum_y], label=['Frame', 'Total_Intensity'],\n", + " filename=uidstr + '_img_sum_t', path= data_dir )\n", + "print('number of bad pixels masked: %s'%len(imgsum_y))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:53:45.920912", + "exception": false, + "start_time": "2023-06-20T08:53:45.920888", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Plot time~ total intensity of each frame" + ] + }, + { + "cell_type": "code", + "execution_count": 264, + "metadata": { + "papermill": { + "duration": 0.225016, + "end_time": "2023-06-20T08:53:46.212031", + "exception": false, + "start_time": "2023-06-20T08:53:45.987015", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot1D( y = imgsum_y, title = uidstr + '_img_sum_t', xlabel='Frame', c='b',\n", + " ylabel='Total_Intensity', legend='imgsum', save=True, path=data_dir)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.1e-05, + "end_time": "2023-06-20T08:53:46.214725", + "exception": false, + "start_time": "2023-06-20T08:53:46.214704", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Get Dynamic Mask (currently designed for 500K)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.8e-05, + "end_time": "2023-06-20T08:53:46.289744", + "exception": false, + "start_time": "2023-06-20T08:53:46.289726", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# NEED ALL Detectors! There are 3 bit-depth levels!\n", + "### check Dectris documentation: 16/8/4 bit(?)" + ] + }, + { + "cell_type": "code", + "execution_count": 265, + "metadata": { + "papermill": { + "duration": 0.067637, + "end_time": "2023-06-20T08:53:46.423218", + "exception": false, + "start_time": "2023-06-20T08:53:46.355581", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if \"eiger4m\" in md['detector'] or md['detector'] == 'image': \n", + " pass\n", + "elif (\"eiger500k\" in md['detector']) or (\"eiger500K\" in md['detector']): \n", + " if md['eiger500K_single_cam_acquire_period'] <= 0.00015: #will check this logic\n", + " if imgs[0].dtype == 'uint8':\n", + " print('Create dynamic mask for 500K due to 9K data acquistion!!!')\n", + " #bdp = find_bad_pixels_FD( bad_frame_list, FD, img_shape = avg_img.shape, threshold= 15 ) \n", + " bdp = find_bad_pixels_FD( np.arange(Nimg), FD, img_shape = avg_img.shape, threshold= 15 ) \n", + " mask = mask_copy2.copy()\n", + " mask *=bdp \n", + " mask_copy = mask.copy()\n", + " show_img( np.array(mask,dtype=int), image_name='New Mask_uid=%s'%uid, aspect=1 )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.9e-05, + "end_time": "2023-06-20T08:53:46.423875", + "exception": false, + "start_time": "2023-06-20T08:53:46.423856", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## SAXS Scattering Geometry" + ] + }, + { + "cell_type": "code", + "execution_count": 266, + "metadata": { + "papermill": { + "duration": 0.065967, + "end_time": "2023-06-20T08:53:46.625511", + "exception": false, + "start_time": "2023-06-20T08:53:46.559544", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "setup_pargs['center'] = center[::-1]" + ] + }, + { + "cell_type": "code", + "execution_count": 267, + "metadata": { + "papermill": { + "duration": 1.376382, + "end_time": "2023-06-20T08:53:48.007758", + "exception": false, + "start_time": "2023-06-20T08:53:46.631376", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='saxs':\n", + " outlier_threshold = 5.5 # change here, if necessary\n", + " maximum_outlier_fraction = .1\n", + " \n", + " roi_mask = roi_mask2.copy()\n", + " ## Get circular average| * Do plot and save q~iq\n", + " mask = mask_copy.copy()\n", + " hmask = create_hot_pixel_mask( avg_img, threshold = 2e8, center=center, center_radius= 100)\n", + " mask =np.array( mask * hmask, dtype=bool)\n", + " \n", + " if mask_outliers:\n", + " hhmask = outlier_mask(avg_img,mask,roi_mask,outlier_threshold = outlier_threshold, maximum_outlier_fraction = maximum_outlier_fraction,verbose=False,plot=False)\n", + " mask =np.array( mask * hhmask, dtype=bool)\n", + " \n", + " qp_saxs, iq_saxs, q_saxs = get_circular_average( avg_img * det_mask , mask * hmask, save=True,\n", + " #qp_saxs, iq_saxs, q_saxs = get_circular_average( avg_img * det_mask*mask , mask, save=True,\n", + " pargs=setup_pargs )\n", + " plot_circular_average( qp_saxs, iq_saxs, q_saxs, pargs=setup_pargs, show_pixel=True,\n", + " xlim=[qp_saxs.min(), qp_saxs.max()*1.0], ylim = [iq_saxs.min(), iq_saxs.max()*2] )\n", + " \n", + " print('Removed %s hot pixels.'%len(np.nonzero(hmask-1)[0]))\n", + " roi_mask = roi_mask * mask" + ] + }, + { + "cell_type": "code", + "execution_count": 268, + "metadata": { + "papermill": { + "duration": 2.431654, + "end_time": "2023-06-20T08:53:50.439550", + "exception": false, + "start_time": "2023-06-20T08:53:48.007896", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='saxs': \n", + " qr = np.array( [qval_dict[k][0] for k in sorted( qval_dict.keys())] )\n", + " if qphi_analysis == False:\n", + " try:\n", + " qr_cal, qr_wid = get_QrQw_From_RoiMask( roi_mask, setup_pargs ) \n", + " print(len(qr)) \n", + " if (qr_cal - qr).sum() >=1e-3:\n", + " print( 'The loaded ROI mask might not be applicable to this UID: %s.'%uid)\n", + " print('Please check the loaded roi mask file.')\n", + " except:\n", + " print('Something is wrong with the roi-mask. Please check the loaded roi mask file.') \n", + " \n", + " \n", + " show_ROI_on_image( avg_img*roi_mask, roi_mask, center, label_on = False, rwidth = 600, alpha=.9, \n", + " save=True, path=data_dir, uid=uidstr, vmin= 1e-1,\n", + " vmax= 1e3, #np.max(avg_img),\n", + " aspect=1,\n", + " show_roi_edge=True, \n", + " show_ang_cor = True) \n", + " plot_qIq_with_ROI( q_saxs, iq_saxs, np.unique(qr), logs=True, uid=uidstr, \n", + " xlim=[q_saxs.min(), q_saxs.max()*1.02],#[0.0001,0.08],\n", + " ylim = [iq_saxs.min(), iq_saxs.max()*1.02], save=True, path=data_dir)\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:50.443489", + "exception": false, + "start_time": "2023-06-20T08:53:50.443467", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Time Depedent I(q) Analysis" + ] + }, + { + "cell_type": "code", + "execution_count": 269, + "metadata": {}, + "outputs": [], + "source": [ + "if scat_geometry =='saxs':\n", + " slice_num=3\n", + " slice_width=2\n", + " Nimg = FD.end - FD.beg \n", + " time_edge = create_time_slice( Nimg, slice_num=slice_num, slice_width=slice_width, edges = None )\n", + " time_edge = np.array( time_edge ) + good_start \n", + " if slice_num*slice_width >10: # doing circular average from sparsified data\n", + " qpt, iqst, qt = get_t_iqc( FD, time_edge, mask*det_mask, pargs=setup_pargs, nx=1500, show_progress= False )\n", + " else: # if we only need a few images, circular average from dask.array is faster\n", + " qpt, iqst, qt = get_t_iqc_imstack( imgs, time_edge, mask*det_mask, pargs=setup_pargs, nx=1500, show_progress= False )\n", + " plot_t_iqc( qt, iqst, time_edge, pargs=setup_pargs, xlim=[qt.min(), qt.max()],\n", + " ylim = [iqst.min(), iqst.max()], save=True )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.1e-05, + "end_time": "2023-06-20T08:53:52.730777", + "exception": false, + "start_time": "2023-06-20T08:53:52.730756", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## For fit one peak" + ] + }, + { + "cell_type": "code", + "execution_count": 270, + "metadata": { + "papermill": { + "duration": 0.071287, + "end_time": "2023-06-20T08:53:52.881893", + "exception": false, + "start_time": "2023-06-20T08:53:52.810606", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='saxs':\n", + " if fit_peak: \n", + " q1 = 0.162\n", + " x = q_saxs\n", + " y= iq_saxs\n", + " aind = [ find_index( q_saxs, q1 ) ]\n", + " w = 50\n", + " xrange = [ aind[0] -w, aind[0] + w] \n", + " cen, cen_std, wid, wid_std, xf, out = fit_one_peak_curve( x, y, xrange ) \n", + " fp = data_dir + uidstr + '_qIq_fit.png' \n", + " ax = plot_xy_with_fit( x, y, xf, out, cen, cen_std,wid, wid_std,\n", + " xlim=[0.01,0.3],xlabel= 'q ('r'$\\AA^{-1}$)',\n", + " ylabel='I(q)', filename=fp) " + ] + }, + { + "cell_type": "code", + "execution_count": 271, + "metadata": { + "papermill": { + "duration": 0.073766, + "end_time": "2023-06-20T08:53:52.961597", + "exception": false, + "start_time": "2023-06-20T08:53:52.887831", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_invariant_analysis:\n", + " if scat_geometry =='saxs':\n", + " invariant = get_iq_invariant( qt, iqst )\n", + " time_stamp = time_edge[:,0] * timeperframe\n", + "\n", + " if scat_geometry =='saxs':\n", + " plot_q2_iq( qt, iqst, time_stamp,pargs=setup_pargs,ylim=[ -0.001, 0.01] , \n", + " xlim=[0.007,0.2],legend_size= 6 )\n", + "\n", + " if scat_geometry =='saxs':\n", + " plot_time_iq_invariant( time_stamp, invariant, pargs=setup_pargs, )\n", + "\n", + " if False:\n", + " iq_int = np.zeros( len(iqst) )\n", + " fig, ax = plt.subplots()\n", + " q = qt\n", + " for i in range(iqst.shape[0]):\n", + " yi = iqst[i] * q**2\n", + " iq_int[i] = yi.sum()\n", + " time_labeli = 'time_%s s'%( round( time_edge[i][0] * timeperframe, 3) )\n", + " plot1D( x = q, y = yi, legend= time_labeli, xlabel='Q (A-1)', ylabel='I(q)*Q^2', title='I(q)*Q^2 ~ time',\n", + " m=markers[i], c = colors[i], ax=ax, ylim=[ -0.001, 0.01] , xlim=[0.007,0.2],\n", + " legend_size=4)\n", + "\n", + " #print( iq_int )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.7e-05, + "end_time": "2023-06-20T08:53:52.964961", + "exception": false, + "start_time": "2023-06-20T08:53:52.964934", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# GiSAXS Scattering Geometry" + ] + }, + { + "cell_type": "code", + "execution_count": 272, + "metadata": { + "papermill": { + "duration": 0.052256, + "end_time": "2023-06-20T08:53:53.088428", + "exception": false, + "start_time": "2023-06-20T08:53:53.036172", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "if scat_geometry =='gi_saxs': \n", + " plot_qzr_map( qr_map, qz_map, inc_x0, ticks = ticks, data= avg_img, uid= uidstr, path = data_dir )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.9e-05, + "end_time": "2023-06-20T08:53:53.116316", + "exception": false, + "start_time": "2023-06-20T08:53:53.116287", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Static Analysis for gisaxs" + ] + }, + { + "cell_type": "code", + "execution_count": 273, + "metadata": { + "papermill": { + "duration": 0.081684, + "end_time": "2023-06-20T08:53:53.277810", + "exception": false, + "start_time": "2023-06-20T08:53:53.196126", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "if scat_geometry =='gi_saxs': \n", + " #roi_masks, qval_dicts = get_gisaxs_roi( Qrs, Qzs, qr_map, qz_map, mask= mask )\n", + " #show_qzr_roi( avg_img, roi_masks, inc_x0, ticks[:4], alpha=0.5, save=True, path=data_dir, uid=uidstr )\n", + " fig, ax = plt.subplots(figsize=(8, 8))\n", + " plt.imshow(avg_img,vmin=0,vmax=2,alpha=1)\n", + " plt.imshow(roi_masks,alpha=.5)\n", + " fp=data_dir + \"%s_ROI_on_Image\" % (uid) + \".png\"\n", + " fig.savefig(fp, dpi=fig.dpi)" + ] + }, + { + "cell_type": "code", + "execution_count": 274, + "metadata": { + "papermill": { + "duration": 0.068521, + "end_time": "2023-06-20T08:53:53.349071", + "exception": false, + "start_time": "2023-06-20T08:53:53.280550", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[[ 0 2]\n", + " [ 498 500]\n", + " [ 998 1000]]\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Averaging 2 images: 100%|██████████| 2/2 [00:00<00:00, 176.01it/s]\n", + "Averaging 2 images: 100%|██████████| 2/2 [00:00<00:00, 121.33it/s]\n", + "Averaging 2 images: 100%|██████████| 2/2 [00:00<00:00, 95.15it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The qr~time is saved in /nsls2/data/chx/proposals/2025-3/pass-317286/Results/0ae234d7-fb12-4f03-8cdb-d64561aa93f0/ with filename as uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_qrt_pds.csv\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "if scat_geometry =='gi_saxs': \n", + " Nimg = FD.end - FD.beg \n", + " time_edge = create_time_slice( N= Nimg, slice_num= 3, slice_width= 2, edges = None )\n", + " time_edge = np.array( time_edge ) + good_start\n", + " print( time_edge ) \n", + " qrt_pds = get_t_qrc( FD, time_edge, Qrs, Qzs, qr_map, qz_map, mask=mask, path=data_dir, uid = uidstr ) \n", + " plot_qrt_pds( qrt_pds, time_edge, qz_index = 0, uid = uidstr, path = data_dir )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.1e-05, + "end_time": "2023-06-20T08:53:53.353582", + "exception": false, + "start_time": "2023-06-20T08:53:53.353561", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Make a Profile Plot" + ] + }, + { + "cell_type": "code", + "execution_count": 275, + "metadata": { + "papermill": { + "duration": 0.068581, + "end_time": "2023-06-20T08:53:53.493133", + "exception": false, + "start_time": "2023-06-20T08:53:53.424552", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='gi_saxs':\n", + " if run_profile_plot:\n", + " xcorners= [ 1100, 1250, 1250, 1100 ]\n", + " ycorners= [ 850, 850, 950, 950 ] \n", + " waterfall_roi_size = [ xcorners[1] - xcorners[0], ycorners[2] - ycorners[1] ]\n", + " waterfall_roi = create_rectangle_mask( avg_img, xcorners, ycorners )\n", + " #show_img( waterfall_roi * avg_img, aspect=1,vmin=.001, vmax=1, logs=True, )\n", + " wat = cal_waterfallc( FD, waterfall_roi, qindex= 1, bin_waterfall=True,\n", + " waterfall_roi_size = waterfall_roi_size,save =True, path=data_dir, uid=uidstr)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 276, + "metadata": { + "papermill": { + "duration": 0.070595, + "end_time": "2023-06-20T08:53:53.568310", + "exception": false, + "start_time": "2023-06-20T08:53:53.497715", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='gi_saxs':\n", + " if run_profile_plot:\n", + " plot_waterfallc( wat, qindex=1, aspect=None, vmin=1, vmax= np.max( wat), uid=uidstr, save =True, \n", + " path=data_dir, beg= FD.beg)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.9e-05, + "end_time": "2023-06-20T08:53:53.570297", + "exception": false, + "start_time": "2023-06-20T08:53:53.570278", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Dynamic Analysis for gi_saxs" + ] + }, + { + "cell_type": "code", + "execution_count": 277, + "metadata": { + "papermill": { + "duration": 0.068646, + "end_time": "2023-06-20T08:53:53.712641", + "exception": false, + "start_time": "2023-06-20T08:53:53.643995", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The qr_1d is saved in /nsls2/data/chx/proposals/2025-3/pass-317286/Results/0ae234d7-fb12-4f03-8cdb-d64561aa93f0/ with filename as uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_qr_1d.csv\n" + ] + }, + { + "data": { + "image/png": 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gsYL9iZ1N4zEBclOAVzxrvlc4eAq4SiAcTenG5DEbiZO4eYjXLzYTsY/l7yXwTbrqEuta8VP0tsvnRT026cYP0/7pAI1p4qo8mdM8iGCg+Mza7O8SqGwBYXHBFeh9Cs49CeTEhV2ykRdPKAFgcY0IFos+JDo87YTiRCxOLZg7WSQ6AwmlxhMjrYloqo6+J+P7JiDrGT97KZwK4Jsub8b+lkrnXau39gLgS+YRHcwRcWdb+OT4IMgSqHd5cXjnYCh8GkuwV4Cu+PcUSF8Ah6W5OgK92LTOJqnx20wCXzV1HOAMHMM8TExm7P8wJGEp7ERQHDoot6YWpae1mKej0lEq3ZK4WdBhsmgtynExy2Ytj/hIBl9NH5Snb2rcokZtBPypfkCtWuyW+EwNuwswmmG7Qa86fGPQq5b5/TXKerp9UbCmtZjOYjaOauXQA2z2xezY7lX02xWuUngT2SpPde5RwOqmsFP1qfg41mceX3nqU0W19rz17Zuc3VYoC+ub4F7csHzVsLkGm2tgn285u61wM8/rb1+jPvegxQPhy1/4GPq4QncKtzfw/YfXONha89ee/y1+4Td+jGu752xvb7g6X/ErX/sMXsEXHnwYgK+023yvr/nl09vTl/0H2v7H1Q2uG8u/eeubvLK+zlG/4NXVVb5y/1n+0q2vcW3/jH/7g7/JJ6/c5S++7zf4m69+mv7ukqYeeGezg36nQW80/8Jz34CPrOl3PCdv73D0eAvlxKd09khjF46tO+A1LN4B5cG0Xqy0Duq1Z+9ly+aqpt2T8e6XGlcrfCU+i1HmDts1y3fED9Zreed2bthcnTE7HGiOe4atGruo6LcbVG/p92fy3oL5Xq87vBbGOjbfVLAWBhzrUKuwaQlADyd+YJyvUc7LhqqpZAkv54ASwBiBmdIoU+G7TmSPVmLmVoglQClQwY3EOVG4JriSRDNy7F+UG9GUPdgsJ9KGmLFVgwzgKOQpwfqhCrB5qUXL6InMz7J56rMY5WhpIZJjgww32VKUTKw+ANT42aVMVQQnJF1V6kil4yaZ0TmxnyNhWl42buqjDE66vABtRf/H56s83vhLLHY+6dsEAny+5kUB78N1pibkCcAsTeRhw+Cj9Wc0YHkTntjNQoeI76IrB4o8wGXfik3FBFwn/BB1mi/wQNmPH7K990HjZH3FhaMigPKMwYOSiZMDYBSleTtS7WmiBSCVji+xn3Xp3AQ207v3qQ/pmiUgjUxgmtCMwGJi4SZm7uTTAqjKBGdlnRhCVZniGuUzQ9y9Sf+y+SXuSMtdXVq0UYhFMOgLM3OxwMeguDCVq4kA8n4EKEeLMxyvKpN3zQWgLHeLyYwzZQxLYBj6kgT59Jhoro6MYX54+WGLvqU5lAWAL783WsxYiswilvepg4msZBi1ErOYc8IkRuBJeNZ5A3h8LWBSzWdBARabA+9Fac6bpCzQOgcdIPdS/YDuLL6qxLexrnDbEnSB0ZhW+mU2A76u6PcauqtbuFlFe9AkH0dlPb7S6M7R7Wqq1cDW2x39lsFrqNaW5rRnc6DRVlisqnXYSqEHT7WB1dPCarkalM1BN4uHDrc7MMwVOOjaCjtTuJnDbBTDcQNaTKm6VXgD1bkCrxjmCt0qqjMFG8Mnb97l6PU9/tZrf4RPf+p7HK3nnJ3NuXu6y7Bn2b96xt58A8BnZmcsVM+WafnDbM/Wj5irir93+gyvH17hj+6+zGd3XudT1+/wC698locnW/xWu8X9boe/891/Bl05PvqR11mfzHl8usWwLQr7v7v7cTYPFqBg/9YJ8wea0+cd2gpQV4PIEFdJUJIH1tc1dqaw79+Ah+MPGoaFZ+vuwPyBTKX1VfFv1Z1jmMkcrM4Hzp5pcJVmWFT4SlOtLcp5XCVsV33a4YPv87AlGy3dOdG1TZUDUeqwgVp36FUrm5/K4OeNHBean2Wfx3gMywWJdTpfCyNnhxy0ZnOgiqoqVFWLiTqKiihvYuAJgLXC4iuVzcIRGEWrR9oAks8r5d0EuF1Q3tEaEpT/KMgPsqxNfooZKKoQ4JjkbyEbLwtOHMl3yDI69h8m+mgMNkY6bgR0fNahJfM6ed7S9K0KGRYDcXz0JSfr3WQljLIsjSP5s3hOuhHFdabgKz1McXC4TqkzyvcUwd7o8wIgJtJm2keXmefyuHCuCsFeY2Ae50vUY4U7V7xmOUeULsB28d5GG49wnUv2Ipe19z5oTKBnDOwSwAuLLLk1TCj99KIvG9A4qUuANZ0z8R+Md3vxb63ysT6bumP/0vflHA0gUKUdFCO2MO02g8CJQqTcxZZ+J8Do93gP+alG9x4tnHd7LlsAtmmbCLzU92JSl0CyNMOkFoVeGeFWLJwEXKtq7J95WYtCvVxUU4EwXWQjfyKIwCsxj4qxr2HwM/Qu+C5WVT4mmbbDPQPzl6+VGQuVrhuESjcI83G+FkCotUR+Go2vjSjUeL3IKs4aUXbBx8vPm3xMATT9rBL/L484zwdmUjmPbwzNUUd9LtGt8/vrNBzDUs5zM0298nR7NXZmmB321CuH14p+p0b3HlsL47g5MMmcrQdPda4wrfTHzjw4CYQ5f1pTPagZtj2+9lTviL/b7IH033Qwfwj2as8/+5FvM8wV/nZL+8YWz/yRt7E3etqrjtu3HvP1t2+Dh49df5svf+8F8Ao/aOzjGbpynK7mnLVNeq5nK8WzzePL59AfULs/7PL3z26xX634+PW73B92eXlzk9966zm09vzIzTt84c6LvPXoAD23DOuKlw5vUq0UW8uWH//A91AWqjsN1UpAdTtU9Nue5tCAg2GhMGvF+W2PaRX9rucjn3idYc+ie497OKPd12y9Dc0xoJVETw/QnHrmj0XmNOfidtDu1yweWuxMgwbbaDFVd55q1TMsqiTf6qMN9fGG5p0z8b1dtWKydg63aGT+9QPdzW3ccsbIcuM9qhuEIQ/rAaXwdSVspFKysXEelvNknvabVo7dWuZgERcsTZUBH11tRF76tgtR0mQlXzD+yb/Z2vFP54sNXQEwouVDF1aZEgREGRdlhZ6AhNjKjTNkWV+yixFYFi1bflwmQwqzdLS2RUB3AViaieyIfQnm7xQVXioxTwbBcezifYOFr9S/KhA5400/I5/99MyJrZs2ld+RLz4b/SyU92X6Is63kSUuAmc1BnTxyiUojM8d+zEB3ekZwubGlxuG0nStVAaH5XUhA8T4XN4VY6m5VM+F6/+w+azf+6CxoJ8T23bZ4MR5WfgqqHJCxMMKJi+DQpWFTAkUy01FeEHJJzC+72hSnOzYEoj1hQNxAVLzLouCUYsLicJ/JF/XT8BO6dPoCx+caBoOnblgii4BXfaPKVLw6OwwXZqoR2ZyGZTEBI520OHckmUcLb6SocsDnH5eiIL2XnyRLtvhj3ZlBfgsBVRspmAP4oKOwS0giiEGw0QzTCm4UVmReJLiShGUamzuViY8R1VlQVq8B0CYDyXpNwimZdYtqutRzgnws04CWdoeFaKto+O+Pttk/9HA5vgq+FpphVl14jcWruOaoGwrjZ1X6M4y7DQoK/2yMwGsavBU5wPNyYBpLd1+TbetsTONrRWLBwPVxtEvVDBdK0wr19ADfPanv40eoD6LPnJQrWHY9tQnisU7imHp6XfF927Y8gw7jr0feYx5VPOZ2RkA/9azX+Ozn/ou99c7VO8Ii/X2a1epjivswvPm6gC/ZZnVA3/pw7+Orz2fuHGXxbzjJ66+wquDvLtfWx+wcg1r3/OH1X50/oA/sX2Hf/T6B/hjyzt8ZnbGz+zcYX9/hUfRuSpYsxTqqOLKlTOe2j7lyvuOWL+5zdGwhZ172iuOfs9hWuj6ivpcnlF5YXft0mPWGt1Dfar45mvPYc51SovkNZzfkvdkZ4rFY8vmivguoqDfNmLGPvdoC8p5dC/zQfeObleyDXT7DfVZj51X4stYG+z2jPapHfF9rYWZ9LMa3Vv6PTE910ctetWCArs9y0x93Ag1jQDAwaLaTjIMnK+hH4R93HTBfF3l9X6+FsaxqogAo/Ttw5gsI/shB7eArN1hyIEwscW0V1GWlGbnKGviBrJg/C5YPmDkf10GqySfxhEYLXVCBqQxvVkMFow+5XJdSjWXTNDJbckWOqLYXFLop3R8Um6Eexcyf6RXMrGRQVEZcUxxrBqPXQCcOf0YI1wa9T6BiRyTL7E/HkaR1ZeByAKAZepT+lS6hkW/yQm2yPq+BHqxLxPwFoNhVACgqvg9PVMxBvG+RR99OXe8Gz9f/PtSppSxef93aO950Diiu1X++wIr6EuQGD6+4IMwAX3xGhFYFoxlpOov7Ox09M1IV7xgIogMZJ7oPq8pSH3M/pVjUDu+d2lqJ02QkW9mGJsERKoqAzrGgDdeP5rGk4nchzyKPh+f+prAr0kCKC6I8aIPJogpGCxBZ/xZgr1kvijYzSLiLr3jUnhHf6Py2HCvUSR69F0EAVKj3R/jfGtKSfqOKCSGMj2HS6ZnVdciTIdsEiM46ad3FJzto5+n7/s079R8Lu/OaHwngQ5KGwGhdR0Uhcl+kt7hZ3UwYwfF0Q+47XkyQbvlTIJiBitszeBQbY/dnkkggXP4pkKveomibsWcjZLAl+q8AFOBkXQzQ79t6Hcq5g9bZsfi61ifWXTvsDMJXKnPPVtvW+xM5mG18nzt779Iv61ogn9jZBznD2HzlGV1yzN/BLrNgEevNI++exW051vdDLv0/O07n+RrX/wQp4+Wsi4d3Hr+IcOOAPe/eP0l8GCd4v/2zX8GPLy5OmBRDXzr/DbPVvK+r1enrF3DQtX80uMXOHQdf9Dtv3z8MTSK2U7L9/otfvHhh3noep7ZOkIdV3zn0Q2euXaEMo4XXnibw/s7/Cv7r/LwZBtXe166dxPdK1Tt2LqyEtM9UH3wXMRXDd01S3Oo8MZTbcTfFA92y6GsZ+cNT33q8cZjZ4rmqMcrhZ3B8v5At60xG4m81oPHrC3tvkE5T3vQUK0HdOepjzfUZ1YySu3K5sMrGBaa2f2zkM/RYOcVhIjnaiWuEYDMScCswvxfd+I32dSSgkcpfG0SUFPGCEOo9AgsqboS15G6FreYtNYHMqhQARRms7O4mqgMtoyWtRVlTDAZZ9Nk2IzHjWCp9K0bg82gh0rmURVyq9RTo4DFKFPLrBbRJ7KUlfE24brTdDml65UMcml1yoRHAtaRiJmoSxUDmJLvdwZjo7zAse/l88f7hT4nMzTxO51iDxjdOwLC8G60BJ9kn8liIzCyuVM8W/kgcawLoBlPmW4C0tj6fI50lgQG4/elufuyc32hg6YBLGVLAVmRWIr3VhmoxnPj9ZN/rB4ffylDe7G950GjtLwAvbUTUDZG3NkHbrwDU8VETkEbqpjYCfwF1O5zqgE5L/uQjHdSmWWLoGdknjV6tANIxzqfd5mT7y7sUn0Ge6O+FaAws5t+LLBG48PovLwmdBKKZYqGDO4KQD5hylIKoPSMYWAmgjAFJpVCsnjGKJwuFUIReEZ2sQrRiBEUhmO8FUZhFAgUNwLJjHyJCakQHKquC/8mnc8PbAUgQK/v44CSd+s6m2usE6f8oQRjYafovJwWk/fOZ8RUH75tsw9STIYeQCKbNgFAvEdtevR5SKcT/caiSdt53LyhOg6mvsqgBoufB6VdaVylcZFlCP5m83sCQHylcUaxekrRnPR0u01gnAR8tAcN9dkQwIrCzoRx7OcKV4MzChwoK/6NO28JELUzxfbrooSGpUrp0erjMM8cqEHx91/9JMsb53z66pugQPcqJaa+fy4peXzt+Vu/9TmqxxU/e/Or/JEXXmXv2jl/4fpLnGxm/HN73+blfs4vn97mQ/XAvlkB8K9d+T7nvvoDB45/9uCbAPwfb3+Dl9dP8flr3+XV7irXq2NcBepRzTtn27x44z4vv/40N5465m98/zO4QePmHn1uxPR/VLF+e4tuz8PbM+xLS8zG0+9ZVCfrZv4QuhdbNtegWitm940kU18oun3F/IGi3/YMWxX1Wc/+9yW1jjeAEncCV8dUOuBqTX020O/UonUqExhJT3PU4xqDa4ykb7q6JUAOMJtBfBm7XuZbCI5R/ZAZ9JAdQFmHWm9GMsH7Qj61nciIupLlbQfxSSxaXHOqqgFJ3ZMC2iD97tsugRMV2cl0kMosYwF8EnAbhmBZQGRDjNYuXVogA8WRhUhd/jPKoORWNJGDhUzzbhxImIiG0t+9bDa7N41y6V7SYlT2yG1qxCbG7npGGKVkPON5ZdR3AdCVMWP20iPgyJP9OAtza7ZSqfIGoz+zuTj+UQCp8j7kyPN04oRsGs0FIuibEimlvgsAbgQyy8uFY6Z+oqMx9WlzMnkBk+tccm7EO6NnePf2ngeNOSoqtOAHmCZi3JEw2TkUn8t3mW1LaXaK6ydQWKbfIYNMin6MF9z4RY0dln12ai52gMlEXgIon48f+UIEwBbBcPJruWR+JL/H0c6xMA1HAZz6SaqsMApeiYLlMt+cOCYXdkwkgee9L3xhinGZOI3H1A++YCPTc6cFVHw8ZNNsunYU1sGUPkomHoVBdMAu/Yni38GMOwKZSmXgGJmLyoyDaaqQfkFr8aEaLHgnIDEm+w3ji7WJnUxsbADbqq6hH0TZRQAeGcxhyCBRKfHlansZt8DYuMVM8jOuuzQ2UQjH0Rt2GrzR2KWYoVUrzv+6swzbBhcSfgN0V5co63GVpORpDmFYVCjn2RzIPe3cMH+4wc4N/VLyMgI0p5Z+W6qLnN9SdAdeAmIqxdkthenkvdgazEr86HQnTKWrYXYI3c1BwM+gOH+0ZKE6tj5+Qn2q4INrrl8/4antU/4P7/8NMJ5r7zui33X88qNPstA9Snl+/juf5Z+78RJvD3t8tO74mZ07AHyolvf3906f4RmjOdDZ5/EPou0U93t6dsR/fO/jVMryhbsvorYGMddval5+dJ2f+8SX2K5aPnjjAXj4+O076Csd7nZLc+Ixa4lCB+h3Yf6xU3SrWb6taG8PkgLp5Rluy6EsYl5eQ3sV6lPP7NihB4VtNI8/3tDuS/qcxf0BPDQnnn6hsHNNtbKShskKUKhWAh6HmcLVAhy9Ajsz6N5RHa5Qm16SVw9OmMaqwpx36OAugffCtGstczxmA1gu0hgp6yQQpmQbIa/DuC6iBSAwiKpuErPvNy1+1sD2Uu4X8zdGVirI1FEif+fEhD3NllBVOUdrTNQ9Tb+l9ThFWJAzPsqbkniAi7LOFXkc0+bej46Lrj+xoktqydKUza4qJAP3zhe6IweDlm5W8nMsh7P+9Rd0iBxSgBVFwX6G8Y3nl9hoar4uzMzRn55oqi0IoxJ0pnFJX0yuNwKOFH+Tnz11KN5/Ah5HJM7lIJtsrsz3KXVPyU6OgOUU8ZLnXnktP7l+vGbJkKbPfzg4+J4HjdPEpNl1In7OhV1CAmVpsZE3KFqNkpSOwE9C7KTdWzLjFmCyjJxWIQdX8i+MO0GlMuBMoC8DwDHbVvwr+jQ2e2fAdVlQyMgvJj6LYiScYqRyDlwhBaVkttEloRTPiz+nJvLRtUumsvRpLBjBMskrPkSCT5nB4vrTv6PZ/cJ31o6BdiwdCGOnZ+dyoEpkEcsE6ZD9E9P1Qn+jCco5MSFrYRYzGFWgTUqrE//2IZm47zpGJgtnJfozjlvTEJ2eVVMHEAmqtyJIlShRwvz1Cmg7SYYcFJayEkUdzXj0Fj+rqY42qN6inQfr6K5tif+jVjSPOzEthmFoHp6zvj5Dd45+p6JeeTZXDedPGfQAw7bBdI7z23N066hXYgZt9zWbKxXzI48zCrNRzB/INWfHjuV9WF+H5z92l2oDdtcybPvARCq5xhX4wPWHqEFTnSmqM80XvvtxHj7axtbQPp7zpw++yesPrvJL3/hJVK/43x58C9VYjk8WfPGd97PbbHjx1j3O3JzfPsspdo5dxxdW13h1UPzpnbcurJ8/yPZyX1Epy1966rf56smz/LX3/xbGOLb31zx37TFVZfmFN3+E3hl+ZPEGH7l1j+9/5Vl+8sYrNJVl9Yxj8cIpzc01rvGoXtH/1g6+8rT7imbe05w7CYqpLXoAbxTtnmL7DcnBqBz0uw7lPdtveVwFzcmAXQgI1NazeDhgOhfKTBp0J24Jqh0wa8vyfodynmFZhVRNwQc3sO16I0FdKrLxzkFT4WuDmwcArch+xEbjK1ljvmDrRfY5/DJkAwhKXFV18BsOFgBnA1gUUKIiGD1fy79obg4yg5hMHwo9nfVNyicZmcSRS0z0j+xHVgimYC+AylJ+X9xwj+VpqfNKuVvmb4xBLResTpHZDPK+DMgsA06U0ZPE32EQJjgs9zX3OW3yfbYeFV+GvsSMI4VpvDgms3Uq6LcI6kqgpcZjGX8tfOWnJnWIutUnHRg/J7F9yM/LmLlU6UxnssHH80n9TTqlBK6pr8Vxk7ErbpSfq7xuwgUJsORnTc88JVRifwrA/zu09zxoHIM1l03SfjJ5IIHFEXVeThxPYvPS9dNiC2AxUtcluCvnli/P82kBy70KwBd3btaNhMF4h0n6HBgDyeLzeHwMqlFVNTblFmPgi0WWdn3RaXqU+V+PxjV/Pu5LNj+PxzoC2ZgPLJ1TCraRo3FgCorr5qASP666MAWlsZV/T559fC+yb2Pc/cex9+Q5oZQoqzKRr7N58SbmMVzX6Jy4OzCLKYeYD+8o5fiUcoCp3nZlBFRGEGsqWMwDMxiY3qoWID0IiFRK7plSN0BIAu6EnZlJ5HQCiiBKetPhZ6E8mXUSoLDV4LTCzWtMa9HtwPp6g6+lAozuZWyHg6UMqYfmcYerFdtvbJgde+aPO5RFkkUfWbrdCjWAMzFyOgx9DYuHjvljizOKzRWNDUzid+8+hf8jK/CSCkbHeKSZMI9vfeMpmFuGLc/PfvaLko7nXGMXMq/+sy//FKpTXHvuCGaWv3Pns/hes7e7xraGN+5e46hf8g/vfpB2kHH7jc0+e7rhp5cPeX/lea3MvvQH2Cyeb3QLZqrnjc1V/uN7H+fz17/FLz1+Ae9hval5+2wHrTx7izVvPLjC//ONz/LdBzfoDjxffvQ+1pua5XbL6TvbbA4XmFYxbAlYxMNnPvY9eH3B2TNKalQ7he5F1syOPd2ebDiGuWbvu2BrRbuv0Z2n3a/wGrodzeq6YX29QrcSMb+5otlcn+ONot+bo7yn367RZxt0l9eli+4PoToRzuObCruoxWdRRf/bXhJ3z+u8/r1PQS6kEm5hvWjJ2Qgktw7vPdQ1fugFLKpxAJ5vuwQgZIMaZF4J7KKMiKAJwv1UlgshpyN1MHOXG8X4e2Q/S5kdZchEVk0DFkpWcQQcJ8xi1B8xEKY8LoG3Uu8VIHWUxzcGBcX+FOREIuSSrsz6FwrwpwqZKh+M9SRFIA5ZHyZrWJLzPt0rsW++PFancYhjr0bH+cwIF8+Tvo8ArnwnFO8kgbbc+YQzSp2SnrMkZUqzedkmQJDpPYrPlGyIxqysz4elSxYAVU36Hs3e083Iu7T3PGiMOxb5NTvUpvx+I6BfIH0lH45Nub687GSXFT52l1RbURTOwMX5k+ivcU4tMshLPpTZn3KUOihcz1s7AmFAjnqjAJUBaJUZ+pNAKUBrZEjLaOgLLF7R77QzLsa6BLRTZ+yxOwAJ2JbMY7hBnvTxHSbwFv7FKgXxX2WyAihZyOJelMnH3wXUZr/EIBiHgZSwt7hOzunIWLFEMxSIMosRdBHI+bFQjQpE6k4HBVc8r3c2yBst+RSthd1JgXmtBRy6Yg4iCjeyAyoEvPja4Bcz3LzBzWr8ohGlHCJBVddD12PWvZQP3PTCAFWa5TuSEsU1Gh0CEqqTlubUij/bvEJbj11Kip1oph4WhtXNCleLX6KrFcMSum3F+gYsHjvQkgtQgYAXA97A4m3F6h0BptrC+W35Xnee5qk11crDxqAt/Df/8CfAg9u31Fc3sDUw7Djq3Y777+yhTyt+5OoddvfWrLuaP/fCP0IvB/78lZf53FOv8W/c/Bb/aLNH7w1vDHn+PP9PXoL6H6vdGeCTzZrfOHuBrarjE/t3+Ga7zb3jXd63f4h62DCcNhjt+fy17/L+Gw9RWuaXmzk26wbfGjb3F1QHLWhPf22gORKAiIKv/eYHmb1whtegrKK+U2NrCWpRXhhFheTStDMlZuwzT7V22EZM3qaH2YmAfl8pmuOWxUPL7KgT8/OqxzbCOJ99cFfmmhefRN1Jcm/VDfQHC9zM4I2mOt2E3KIKPWTfLrUJUcvW4qM/sNGw2sCszmAvMuyDlc3WyEVGoRZzsIOAjxgAqVSqUZ9L7gVZboK7SbQ0xI1fGZihCx2TNqCFci6tDyXjFuXDiIkiybHol5k+LqxJSf6/CwCIG/NUHzp8ls3EWQZnJi4EaAZd5oM/5hSsjkkKN8n6EcGdyzIvgbf0GnKfyvRl8V/BiMZNdt7Aw0i/kgF0mdwbos4sLl4CwHjdkYl6rPeTwI7ArwSOlxApuQ+x7/E+BZD0kSSZAMTL2MxoEk/3zO8p9SsdUwDJ9H7K9+vJZu8noDG0okZlSZGXzrXpw3hc4TdYfkcR0VwAtlFSU4rdVfn+S3AQ18pkYk1zFabzismWK6BceMz8fOlwuWdOn+DSZJnmaUwBOMWiLSOs470jkMzBMxMfmxjRlvqVq7iU1HgZ2CJz2GegdsluevSoxhRCLIDcaQRiDBJJ/kcTUAvZt3GyEx2lyYnAr3RSj2A2js1gx9cuTQIFi5yuGRUOiLBomnyveN2SrTSFwEljSSqNpjZdTikUWA4Jhglm9vlMrrEO/lm1nINS6FUrYLIbUKcr8RnrBzwIu1MZ/KKBweFC4mK7qMXXrBPzoTMKt2zSM+tOalH3Sw0OdOdojroU7FKtLVt3ekwvkdK686gBuqsO3Su6bcXps4pqpcDB4oH4yG2uCshEQXViMGuF2e1QYbr1g2F1C5QTINnveuojw0/dfpmbW2f8yM07eOPpNjVXr5/wqQ+9xm/ee46r83O6Tc3fe/Apdpcbfv7lz/Lllz7If/zOx3i73ed4WPCd9hb/6YOPvOuc/P1unR840D0//73P8uLyHhtb8Xa7D4DvNP/s9vewS4daiNka4PXDKzKdB42qHdXDin/phd+SCi4nDTdvHqHODKbzuIXDrKWiy+n5jMU74CovUenWs7kOw1zhKnAVzB5DfWbl3ArcTLN9p5Xk7gq8VnQ74uu6uTbHtBZnNHYuIFAPDt0OLO91EqkfGSWjqU57UGBWEqGvukF8FyuDPtuIWGwqVDdIxaJNi69rVCubGN+2ofSfnONLs6rWqL4PQSpa8jQ6JwExOlhhqkp8hVXYtKFG/omJ1YryPFpdoiUhMTphHUewWDJasUUmcbopLjMrlPI0uscU7kzp3MLfvMxQARlYlpaaXGq2AFOBtJBgk8IyR6mTSLpyanXLlraJO1HUnZcCk0JfRrxT+ltGIqG0yoRrZpBHBo8wBmFJ92Z9M1LQI2A2/X100fyzPCf5LMaxKvpdHj9ljuPcSF2eEBejIZqAugvHlCD3knMuDa4JP1PWjou3vay990FjAHLZL0OPx9YX/4qBLKN744ViJPM0Fc4ohUO4/thkXAC9dIsMlkY+lJBp/eL3eI/oZ5JAXQSAepoTsehP+KlGQmTCcIZnTX4s8ZlUFiyJcZwUox+xsRH4hXuWTsiXsn4+X3f0fdos+RE4LHfmYiYJQSGmELzxOLgAYIExcIzHTs0NZR+DAB7lmYzsZjy/zN4fq7rIIIzY17R4C7cFv2nHfdAGNZPyZFIbN5xrBzCVOPcPNj27j3niYrBU20muxMBGqCJdiFq3AuwXM6mK0YWqF4OF+UySKHtQXqq/oBSqs3I973GLBtMOElAzrxkWhua4FxAJrG/OWV9vWN5dC6CoJVjC1xrTelyj6XaNRNWuXQaBa8/sgWb+2FOtPMu3QYfYnHZP0S9VAjKmVdilY9j2zL/d0BzBc5+9y+ylBt1BtVLM72vxu7s68Ovf/ChvPLjC1155H82yR7Wawzf3WOqO56885mf3Xqc6MqweLGmHCnOmqW5sOD+b88b3bvLygxu8tdqj1pZ/cP40AAM/nP/P71VrVMWbww7/8vNf5vGwxdkw43Cz5OPNKX/txS/z948+im4V6rDib33lc/z8Sz+Kt4obe2fs7qwxhxX2Zs8v3/kkZj7w/tsPeLRaMjuC1W1HdapRVtFdtVQPavQA23cl4GVzVfpgP7yhWoG/3WI2PiRwd1Lv2yjOn27wtQDL+swyOxxwjaI+G7Bzw/ELkpLLzg3tXk233+Dq6LNIyvXp68CGeS/zqlSyRqM3nfguaoU5bwPrLj6GbtHA/q5sqKz4SKre4ruOYW8ZQJew7gQXGDWfyc+Q31F8GzuUFkvQKJVVBHTOZb/nWA7Uk0FAjJxOmz/y5jPIt3KjnZ6PLLNTi3LNuQu1qrNZuAAgkRksjk2yyxUZOoq8r9kKlPsBZIAcIquTb2Psa0wf5zNYLSO3S/JlzPCR5N/Ihav8upS3qS/5xFFS7zROpM+mpEwuVFGA+sjUJcbOj3TYqKPekyxFI581zwhwBYCqEpiE5P+arGYXLVvT26Vr+6KPU/A4apd8F8crmqCn+i3ppIle/h3aex80pl1FBCBBQJXmiTAHRqH0BbgZ7XjUBEgWPpKJMfP5mORDEsFROTkCuCz9OlJpvkjtq3xc7EM8p0zfU/o+5vmcJ1xpik75DNO8GU+W3F+djo9jEiPzSmAoAO7ynUxK5xAX4oRRjIA0XTMCwuConcziYSyj0BvtPov7lcfl3WmxQEqT+JRdLMcisYaTXWNxLDBmEoeJs5v3YwCZhEDxnmIicGvFHzLmqQw5HqMpSMxgYa4VY4JCygnqmAMzBBNF8zkeHxVoJaZoQMzO8xmqriV6tTIo56Q8Wz+g1h2q7WS8QzoUve5DHWDFsB8qaGjQ6y4l/Z4/6jCtFwYIqFYS/NDuS6qVzYEWdtHKP7xER2sLVStpdaqNS+ZoPXh0D9pBe43EPurlICDJQftCz8uv3aLfVpJappXzlu94PnzzPt54bl49oTlSaC05Bt3c88WXPszrr9yQUao95qClfXvBxz/8BgA/98JX+PCLb7G1bLk+P6e1Fb3TfLndofpDEJ1vdlexaF6c3WNhej5/4+v8p+98isFbjtoF27clobndciz2NqA89+/us3prG1dDfbfGndcsFx1vfP8GdjAJtA/bjn7HoVqNHiR599ltxWZfg/Y0Rwp3dyEpcl5qsDMpF4iTsTadozmVeV61XnwRQ31x12jqk46D78gGxWws9cpSncsc7fZmeCPVgVCgVx12d5E2M25m6A/maR35WY05XSdztJ83MMhGSCrJbDKICvJZaU11spZqSX0veUtD+jXf9ZJ+J2QhACSCeugBSW+l6qrItBCAUAhWSxtZa0lCNQK8WAUmgszIctrCwjCtaz+VOfGzke4YHzNNvxYJACafyalBNsfUY4oM8PLBckxMIdfn0qdJdyQigKwXgy5Km/6JThplxIjXLq6h0vsqZH+hw/OmPd9vzOzm/mfQNgVZU4BcBsmq7M/+biAqgd/iWunSGZj6cj6k/pXgTJHM2/53uN6FBOQlwi7GpNQtTO4VGcURw+jz50yCa3+H9t4HjZAmsLTszyFsXBz4cOh0YRbvMi2WtENSRMYrmqdjjqgSmF7ISZW6UmTQT4t3CiTj3zlqeWy6zcBXTRZ+GVWcfFh8ziU5Su4dhyGyjwkw2pzx/8LObWxWyc9ULLr4/CW4Kyc55Cg8n03dI3ZxKuymwi2eG3fRKd2NGd+zPCcK1HKhxHNLtrB4LmUkWvsCoIScyDt+rtW4bFhiEZNUy+xiFZIQ65wnLabNSTngoo9hVQmTGFnGUPVCAGfwI6qqHKCjQ/lB58TZP4yLj5sSLYEvqgDa3krib9+IjyNKSbLuRS3l25RCO49tNM2DNWiNWcm1vVbMHqxR1tPtalwtSrY5GfBGMX/kMJ2j3zKcP1Vhes/80NIvxR9umEmaFl+QwcrC6ilwtac5dSgPs+/XuNozzEHfa1i8A89+/B7NodS0Xj3rOHtG8fZql2vPHXH/eBvzwgr/ygKM50fe9wZuV6K+f/67n8VVYLTHbju+8caz1Ebm+uNuSWUst5pDVm3Dz+zc4ePNY359s88fdPtT23f5+vlz/N9f+gl+du91fqu9xtnxgr/92ufo7yxZ9zUf+dBbYGDzeIHvDL7yeC0pdoZbHbNHivWb2zSH4M8rqdxyZMApZo8184ekUo67r0jaJbWQcfIaqg0oh/ihzjVoAf220eEdekzrQ3UZLb6Qg6ffbWgPGgmYUhJc0x5U2JmRdDyD5O+0cwlu0YME0AhA3FA/XmVZ1va4rblsfLROgS8MA5yuiInoUSpE+Ye15+RcVVeoozMBgsMga0yNAYoPANGHTZ1fb4LcMJLDMW6kY7qeps5rO+qA6APtvazJ2JeUWaGQcZWZnE9yS0kb2QvBFxTyfZJxIhwX9cWF3Lnhe1VeM4KueM9CJ2S3oXcxZUZ3Iy/PlV225LNpOrZ0D0U6pvx+5FOfspX4ou8U8rnQ0xFgqjKDhwsANuq+chNPul82YUc5rsfPmXz6Vb5v2ad4vWn95/yyMjBNY12yjxFcxGuTrzsd9JJxjJsWKK7l8vdTkiR1p3jOC7ji3dsfkkv3H2YrzYyFD4gPeajKtDJhwl5wapXLJMarTMZdJh3NC+/iS0+m3wAupcJP4V8XghdGOzifTdklO5juP5o84fjUJ9ICTexnOdHUJMq5ZATLx07A1eU6l4VAUlqS8sa+JIFTMnXhp/cSlej7gVEQUBDOKV/hdEGUi2zECGeQPM3pKEBOZ6ZxcHmcS1AZox7jtUYmcyX96TpGCzCC0MgsxFceTcaxjUoOxkXtQRmh0mI/4/hZi4+mmMqISXoIKUGiQ3td4bseNWuEDYj3WcxyJGkcgqqGtsPXNSAKVNgZUdDKB7OdmYtZ0EipwOp4g7Yu52oM16wfnYvyti75jek2+JkpKSOnvGdzxVCtPWYjgG+YC8CoV576dOD0uYbFI8fqmmZ27FM5wWrlqVaSC1I5hWkV7UEM2lDoDro9z+xQAmVe/95NGbaZYrbo6LoZ7avbdA7mvWfzHJgGqmPDV3kWPDTXNszrgfO3tqlM8INdWNo3tuApeOdoh3/ume/wqWbFZ579Gl/vlnyqWbFQf7CJvQ9dhwcebLaYH6z5Lw8/wGpo2D8458psxavuKtt1z7fevA3aU++3bDUdu82GN+5cwy4dRkF7xVOfKbyB7WvnnOkl9bHGrBXdgWNxTzHMFMO2pz3QOAOz1ytQHtaK0+c9ulNiOrYKV8m1Ntdh9xUJhqnWDjvXNMctrgnR0B50N0gQi/f4SkzbZiN+fr7SuMYIeNxI0nc/r2HTy9y0Do/Fa41bNuh1H4AhMqeXc/HFnYv/rQrpcRRBDgU5i1fZBxGCG0iIpo4AMqxn3wa3kbjeCPIvBsMpLQhaxU2ezr6Izgslo8hBeiFNFTbIi3KjGX0Qo9yLn8V7WhdkeQBnRkPPhQ1xzGeris3/yJ88XqMAi9nFiSSH87GRcHCJlEh6qPw+WY4EzIzK4ybiJOiYBJRCnwPhkvXU+JnyeBdgLQK8pF/L38N3hL9LV6AS7MXvE9idgDXvyC+xaKLg5NwLbGShk5TK7PTIHF2Aufj3BZYvPlMJ8l3ALCOEPNLB6ZzSLU5F9y8BpCpasEameQ3uhyuR+k8B0+gvjHF6SQWIih+XUc8jv5B4psnCI92hYKTKfFJlEu4IVpP/YTFJBIAV9UAj+NKZNh/l3grXjub0BFiDsCkZuWQWn/iNjKLd4o4zgdIgEKb+MyoHFakEbBkdk3aQ0cw8YU2TACGAvGRGZQxiI1gr6mBHJrG81uj3KZCcLmjnxnkVS4Aer+WKhRiZyPhOncvmpSgQE8gmB6zUdb620pkNiWM7ze0of4x9dFIeMLlGGb2JiRUoVL5mMD8rhTApm1bYC++FwUSFSi9O/L/SmPgM/ELVF7TCNyZETQsQ9ZWRMoLW4ebCELnFjGFZweDExyyM27BtcI3GtA4VzMvVyrK+JgyocrB1r6NaOfrtivljx/qqZvlQnrFfarptTb+l8JWi29bU555+R4CiGqTutO4RIHkF+qVi/hDswtNveezbC8xK+tRetVQbcL3m+Y++jb0yYBpL88jQbWr+9RvfZve5E9Zvb4H2qOOKYdvx3509zYev3+ftbh+Ab/cN//M7H+L/cfR+XttcB+CB/YOpRf1af8Dfe/wJdpqW9emcT22/yf/+2jc4bxveON5HrQyLqsNs96DBPphxdLrkjTvX8EYAnnm7oT4TRrfbh7PVDNVJpZz5I1jcC2zvtqdaienfGzlWOWjOPHvfh73vWxb3wC4U66cADzuvSUL39orGV0rYxZ0mbChkXoip2jBs1ygPPjDYvtK42qB7cWWIVgDVDvh5LdeI0cJNhe6tgCKPJP6e1bIBqitYrXOpQesEzERF2YeymoNF6ZA2JgBKQrSvHyTrgF9vAMSvsaqz0o+KVpEBgcsEBCDyIYJPpYtIaEg+zoMdJ/aOzdq88Syul0rylSATCvlTyLrpRr6M8I6HRCAL+f6TzT+FVW7USvazxFjJn1Hlz5MsZuS3nvIQhziBMjcjUBAS42tMmcYYXCNZRjJwyv6LBXiMYxNYuJGlLD9F7veIDSzGOF5jQlpk0Bn+eZLszSxluEdiAieAtLyGgpH5OuqFxIZOwGfs15Q9pnyH0QWuYE1jn54k95Y28lMcrRpffKRGn0VANjJfx9Oi/0U4bgTogOgLeMEsHSd/mHwZSIWdWfRdI4O9tDuLwSnFPRIzqrLvR5lPq2Q/44RKmf7LBU0BOgNFHSunjByeiwkfBVi8RjILq/ECSJ9P2Uqt0xiU904Ac8oSFv6JF6KhC0FXDBDv2gqQeikbGX9GQVs6vKfjfRbaMf1GPC4CSx2ukZzmXUgWHI4dMQrix5jS6yiVI7L7Ph2nmjrnbYz9HAZwEqiC9/jZTPoRIrTlXXopjWZDom+thJVpKpS1qE2H21nIuwxAU7WDRFl3A8o6+t2ZmJo9wgYF2VatBqjy+7XLhtn9tchFDXpwzA57hqVh5401ph3ol5LseXNgJHLaQXPsaffkOvWZldQ5CvqlScwmQLfvcbVncX2F6QU44pD61A3sPH0maV86AlgCVXvOnvNUp4bXXnoaPOxtrelvDjTznr/x25/js7uvYxeO+nFFda7wjef18wPO7YzvHgpA/Nb5bf7M019laTrur7f5dt9w3eQSc79f7ch1/Maj97NTt/ypvW+jGsv/+7VP8X/93k/wgf2HOKfZe+qUt+8fMG8ExKpBMZ93qF7RbPf4WqrmmI2n3/Y0xyIG9IH4Gbb7ku7IzhRbd2VMuz24+sHHzB8hDLSCk/fD6bPC8DXHnvkDcI1ic1VTbRzLt20wPYusObs9o92rApMoUdPKelY3aqk/3oSk3y6Aykrktd2ZS67GrqgjDdBJip1hb4Ff1CiX56KvDWqxAO/E33E5L5RmdL8I8q6uxBc4taIKCWGtNTO8syl4RlWVsJF1RUwInlxMogXDmAAoXF6/peUj9qMMYElsVJjnk012smTEv8t2ySb/QhBnYvliIOPEfQcyKxja6BqlvlAqBb+UATWjYM6kTiMgU8DYFSvpMOcSwEvlAX14llE6mxIgQVSs8Z2NfPqLz8eYrATJRaDnBZDrxgA1vN+sx9QYdJUALvUt9rt4BxdIDpePHemhNGSjcc/38vnc8rrl9UdAdgKK4/yMrbR6/RDtPQ8ac84p+TulxomAL0WDMQJRKSVBOVkLgHhZ4tG4myJ+F+479TMsyxCVoHZ0XAnoinv7VOaNon6oS6WeUl/La5TJuQuW70LS8LCmY37CEeiM/Yo7wGJSjnIw5gfI7yAK1MSI5t1mGoNifC44bytVjMMEMMZ3FRfWJX49o/4qNd7hx7/dZBGVu+so9IFRSaj4XhIYL/oVAWRxnh+Cf2g0HRTJypPiib5ZxoiyihViotDw0eyUBZ2qG0lLEhOGxwTjdQ2LmZigA/spqUQ0vqpS3WbVW9SqFd/G3uZIyaCg3aymPhNw4Y1Ct5IKxTUGu6hor8zSmJjO4hY11XmPN4phqxLfts4zbNX0uw2+Aq8Vdgan79MMM4W2nvpMAOTqRoUJ5QFXT4FycPasor0WwLOD/rUthrkwVQqYnTq6fTi9s83yPgKMbq4Zlh51Lr599dMrbOP54I0HHJ0t8VZh7y2YP4AvPPgwT10/BuDzP/GrNI8MgzU8Xi9xhw2/8NanOBsanqsUJ/2ctqv4rdP38d3+98/D59R1/KPNHgOKf/PWN3nt0VV+6d5nuLZ7zvUrpzx7/THfe3ydneWGo/s71Fs95+dzsArXeDbHc0k/dH+GXmnszPPcZ+/i5o52H9RJBQ9msuaDTNG9x+ngWjAo7j3YF19FD6fPO7bfVDQnnvrcUq0ds2MrbgZnns2BEZaz0bhKzqlXnvrcUYX5Y2vxc50dWglyGhz9Tp3LWGolQVVBFrmZwdeVREAv6lQRxpys0edtBmEQNk11iJruQ23qsDmKSe6jL/NgJQVVFAPJmhBcPvqw2VM61ZmOm2nf9dn1xMYAESYKWuUNZZmia+QO47NsmVpZSrbI+2zipgCD06YYbdKTj3upS6I1RJHcWSL7lxm/qJcymMP7C1a41N/wsyQqMjgNYKRgFkdERNCVY9A6BqqjDCRJr5S6OerCDACzn/zlQ5XGNvYvXT6Ol78A3jPIjO+5BIFMQO7oRvHlTM4pNgIl8Etk02Q+lddK/Q/feSYAUmcwO9XNo/tEksZdftwl7T0PGscUNSOn4LJdSNRdAEeVaNzJhEjgP7yYtOPxCXyVjOPYVOvHl7vA6E3OjwIhlm8qUuaUoLjc5V1mQriUmUtsZQGIi1rSl+1AR6Ay/j4RBlOGcQTgJwxf9MUZgbvimEsTi4dzRr6Msd/lLjEGt8TxjybvJJCzCRy4aDYqrx/PL0xQPtaQjeemPgZgF+tM+8Dilu8tLnYg1a9N71LnsfI++F6pArhGIBkEtTECHj2p6owaHOp8k0BrSlE0WKlZPavFDyz2x2hhFzvxJUMRagNLehPdWcnNWGnMWYdpLbZRqYygbYz4LW7XmLVlc6BpD0wKbNCdY3F/wGws23cGSetyNCTAopynOfcMC0W7p5k/Bt3B/AHMHhrUAKaTtC7dVStRvK34Yuo2+D3uKbbuePp7C/Qg33386buYb0pd4u+9eROFB6uwC4edK/ydOafdDNd4/s43/iif+OQr7M42PLN9xAff/zbuwYzD+zv84sMXsV5je8N5//vLMu7ohqVuuablPs9dfczTW6fMTc/j0yVvvXWN3eWGk4dbVHst9qhha9lSb3d87IW3hOntFHY7BLR4+M7dpzAbje7DuFUeOwNnPLPHCtN6fCXAfH7o2XlV0vBsrsH265p2P5Rs3DesbkrqpH6hqDZOXAiWGmU9syNHtyWTwjWyiVJe5pJExAe/Qw/1aY/dmcvcsV6YRxtzN6pQo1lYx36nlvnpPH4uFY38YPEx6KwL9dZR+GVIH+V8rg9tnfj/2kGY/xTwIp+rus71pQHskKOQrRXXkFIueIIciq4gWvo7DOONZwi2iWvMR+BqdK5mFddglINRdpliI1wEpaTjS6BWkAEjppEgl2P+2pCHckwI6CS3IzmhtMq5KhUhMNIkPZojpceAc7RxvwRQ4otUaqrQV4pU9CLhORfNyQWgKjAj5Cwi4c+ilWMw1ftRp2fAVqYhGuubEsyR+j0GduV1L/t7cr8RmLzsuHhYAaZju9QHkuJ60/PHcyE/ww8HFMv2ngeN42ipMEET01ewhRNGL+6y4neRdRybQckvYQrQ4sfxXiov4rQrin2BtKgSg6kumn1TkAikSePLxVAAxsRGqpzu5t3AnPQzP9eIOYxgq2Tb4m44/l4CzCoDNIq+5x1jAQBV4VdSXHPUlymzWfRpxDKU35U/I9CLArcEdVPhUADPdEwISKEAy0AuXwij66dzwriQ6tOGe1gXnO0pGIhockgvQA6Pz1cIau9szk+pVE4b4gQQ+sUsMJ8qgFCf31FdwdYC1UmeO78QU7bqxRQd0/G4rVnyYcQYuv0ZGJWeS4GkUwlMxfLNszSGbiZl5uqTDrsw1Kee2aHFNZphodGtpd0Pka1G0W1JPxXgNZjOs9lXYkptfahdLdc2G8/WO57q3NOceOb3DNXKS9DGnsY1Hv/MBm3h9AXP9jNn9AcDvvZ8643btPuK3afPwCuu7pxj1orqVDMsPPr2msFq7LZl5+kzvvry+7k+O+ND83vcX+/wz37sW9x46pj1UNHZij/3/Jf4Sze/xRWz5jc2+5z73x/fxk80G14ObOaj9RbLqmNja/6t53+L5mBDZw3/6w9+E+7OwcP5usEezvj2y8+geoV+Zk01GzAbJeb6PoyT9rhG/vW7Drsl4HFzRbO65dEDrD/WsbmiMCvN4h0CMJck37ZW9DuebkcCmlyl0L3D9J6qlYpA9dpRn4ofYb83kxKAjcY24p5gZyH3Z0jXZNoBHdntYI7Wa4nsd7WAp+bBuaTzmTeoVSvLRankZkEdwZtCHZ4JsDRGSmbGFD1R/ga20K83YnruJKl4ZvZFtiZ/4jr4NipywFwEDnEtD1ZM36U5OsqQKOf6IWdp8IxdZqK8ja4qweoxktm+KOmqFITUOdPMF6XFaMpO+r6/oA/GwY0kMkTV1YhZ9EOsCBMJgPhVEciYnid/n+5d+pCXQCzorOj7Hz9MvvvR9SpWSSvNxaWe1Dk1XBrjKGNH+mHasag0C4YuHeLTuJR9zc9RPHDyV5yCPX/xviPM5vN5vvgXSwVOwUViEyeAOAb4lthnquvSzVWel+/GYE/aex40SlNpXHNwCmmSJNNsGPgc6VWYRePXaWLKRFbGFDs6xhM37Zz0GPiXu6L4WQH0wgdF9y/ZDZSBLBT3nTKmE+o7+kKWgLesznLB/B5A0CgC+t365D3EsoXlLrMQSjkPos5VXKYALi5GVUzo0e6+APrpHH/xZ3ntiblnZO4uv4v3KJ9pxDiO30Fe2GTTT6T8p2MU7uWnADSYwcZjobK/VFQwIa2OJP2uyAS4CBZVVah1K2anyBpXlQQGRJ9Ja1OiYrWRJODeaFQrvld2ZyE5GgcrTI91NMetBBREUI+Yof2ikWoynlDaTXLw6c5iF8KOzY4H+h2DbsWXzc0r7FzR7hp055gdh7FwYOeK9VXD8r5DBXLDVQrz9JphSzE7cXTbYd05sHMkWEZBe9PiGrCPZnQ7Hr3RnL61zXzZU51pdKvQA1ydn6OWA/cf7uJqmD1/RrVSDA/mtGcN+tyw6mrMRrFtNvy9136E07e2eXVznU9tv8n56Zx1X/Ff3fs0/9PqOtd0zY/Pj9hSvz+s43078JWz9/FfHT/Pn77+db559xaD06z8QLtqUMAX7n+YvQ8c4xYOdSr1vH0Yo/a8Qd2boVvwtYel5ec++mXqM4VdeHaurNi6o1jeVcyOPc2ZR28EtPPOLPibIlHrwY1AebALWL4NZgOrG6FazExTn1rW1+pQGhB8ranOBOCYzmIbTbV26E6YRK81ZjNgzlqG7UbyKBqNWQem23m8MehWwKSvK4ncXrX4kP4JCMEvStj1PtR2nzWSs9F7aDvYtMJYWvEv9k0jG7jIUs6aYCoOgC3kYEwl+2yIkE6buwJURCAJELMYxPOiiVqpzComFrHI0RjlxzDIxi8eB2OZVMjpKHNLlnEMmAof+6JoRMzFW6Y4K/P/5ucT60iylkW9VzCByec+3qMgUkbZPqLOKQFWCaIiAH+XVuZ1zM+Yvxe5WqQLKuVv1O/l54WuTubZ2B9f6LCy+UlfLzsmsZCjE/P5vyM48/m9x/4oEhBM1xjFRBTnFSAi+ZDGPk0TiieU/oP6NG7vedA4KpjuC6ARdh8pOXU0xZU7qrjbKah1+VONFlkyX4fFkcEmaaHkBOGxL3nylUAvpR8o+wmpnyP6HC4uyqJNq6TkfFvxXtn3JY2X9+PjCgYtPWtxzDS6HJ8Dd6a725H5JO7So6kXEmga9TuZSgoQGBbVSHBOGcYSQGrNqOZrBLLxb+eyo/nkWTLDqHLlh3j9krWMeREhATuUCmxGME8n3xE9jtiWl5MFRFRcBYj1oRpMAv79kKIVUxTiEIIgYm5HgM0mJfpWdZUTCwdgqdohRLhqVNuhN32q8UuIpMaD3vQQd6VVmIu1wTYGuz3Dh2fRm4FuTxhLr6TG9fxRB1pRn4m5vFp5ZieWxz+isTPNsNQMSwF/syOHqwXgVWuPM1B9a87sSEyf3a6UE2wPJOq3OfU0Jwq10cwfgN+2+B2L3x5YPAK+v0D3UJ9KxPX3376B6wyzR4ZqLQxnd+B48YN30DPH1WeO+fO3voxder5/fp0P3rzPpz7yGm++cZ3//q2P8mPPvEp3MsNoR+8rjl3HXWu5ZyeJ3X+P2g1T8ecOvs/bp7v8j0cfQW80nTX8J6/8OKrTbO4ucU7x6HgLvda4mcPtWnQf5FnlGK4O+Ar0WkOr+Rvf/wz1uWPrLYX+4oL1DVg/JXOt21YsHkD74Y7FQ0lltH7KMewIu9ScOIa5ojoHPUBzZmlOZOMglV80i/sdzUkvZuhW5pBpLVhJoeS1gEmzGdDtgFdgt2dURxupZT6vJFVPCCbzsxiJHAbFhnnZB7Z9exGqHNXik+u91J6PrB9IZoGqGkUdq67PPoyDFf/HTZtN0FFu9rGkn8pWB1XIjygSKildmKKlo9tKShkDKadkNHeXG8+YGqfcPKbvxlVjLssVe6HoQvgsykHx68wgNQVQJnOworRO5fMzWEz3SiBSjQNwSl3roh996GqZH9jnn/IYcbwjsAv9KINjCqtc6EQ4mQLwZV2ajom/T0Fp0M2la1Ua0xGwUuPvUdl6VFqR0vFF38aDlq+VnrUAdhTPVerOKaBLc684bvoMkEHi9Dw16ZOOjOUP197zoLF8HyPglt5PMSEnQKcs1ZfOKyYvBADpp468YyCWWlooPgGXUW5EKIBZ7mfpu1imQBj5iEAGq/FaMQAmCZ94jYu+htOa1il9QgSJfmJqjru0sCNOJvXYJ6WyqSP0PT1f9CEqTb1KXQRS6bNwiZgoV6mU/HryIPlnZBTLVDXT4+ICCn5IIx/RyARUgQ3QJvsxRuYPxgxAFPYjNkEXu0IglCbLgDOau0xgOHxRo9ZnB/gINOP8GIaUQ1RMWV5MbN7LdbQSE1Qlkau+KSNFPXZvKyX4Fr/GWkzbrQQQMGKL87hJAIuR4Jl2SIzSsJDnsVsN9UpYofqsz/M4KMtur6Y+F/Pl8o5G955+odCdCHdXK5whpHtR9DsB/FhPe6CoTxXVWuGu9mLC7j26F3881yiu7Z+hTwzVw5p2T9He7vEa+h2P27HUJ/K+zMbjjGd1d4t/+yNf5pWvPMPTe8c8OtniP7/7o6geTtsZ339wnbubfZbXV/jOoPAwt3z24A0+OLsHwC1juD4tTfl73LxXPDrbYnZ1zfnJHHVm8I2jemqDO26YLzv8zsD8HYMfNHbL4ZcWpWHrFfEFbY4U1Ylmdrei2xMz8TDXNIeK5pGm25UXff6cwx024hPZw9Zbmu1XNe1Vmavzx46q9Zw9A3au2brX4Sp5x84o2v2abrem3xbzs24FUHf7DdVZx/pqhTnv8ZWm32nAaLodw7A/R3UDZjNIVHQsX9n22e0lbiQrI6mjCnCm1r0w6nH+xoT3w5CDPiodzMEqMWhJrqBQ81ne+E7cVFLmAj1Z31E+ueL4MvtCZOljRgTPGJSUjGIJGIpNo/xZbJynbjlwATBGpm9kVfF+FDUd0w7F31N6npGVhxFhML6pGgO09HnQdcF8GpnN9BxQRDhHHRqtd/l5L0smnvVl1pMpk0mph31xjIp/TwdtAkCj1bF8/vh9ClyBZDLWxbpXk46WLF/5Mz9IuG/s2CVAcwRe49/lOJem9Dh3fsD90rh4LszDH6K990FjOVHSRCg/Uhe+jzkNLzgUw2i3Eqn4HKyiEqgsGc4yGrvc1eQ0AQUIC+buFB3ryWaH6c6q6NsF83Q4bgQQk3DL5uh4TirfFKPOFERGMQLcvNiz6SMKnJhnMu9wfeF3V4LeCWCcsqe/w86pTDw7CioavZ/xTko11dj3sWAYvbUjUKem+dFsNgenyg5lqb8yYKYU5GW1iFRrOkdR+hh5qZXUkq7qvNgj411PFJSXijRqNpPnNiHPXDRj45PZWtCXh/lMlF1kFocBtWnxswYdgmPUYFHrFnV0VswRj9sStnDYbrDzCrus8U2Fqw3VqUS62q0GZSV4RffyzHpwKejBNQZfaexMBOvqRsXssGNz1dBta5b3+xAYAcNC3snmqiSL9gqchvkjR3MqwTa6BQKQmb0maV82BxplYftjx+x8+IjDV/cxG0VzKjWsvZNk4IsHoM6MRFMPSmpi71r8wcD/5Ys/xubWwI3ZKZxUXN86Z+v2Oe7OAj9oHtzZx4Tk66+urjGf9/zavRd4vbvGt7obnPkec9Ee9U/c/uH6CgBfabepK8vP3PoG69M5unHMDsE0lvbxHFd71icz9rbXbG6FoKLlgK4cnFScPedprzl8BcO1gX5bgHZ7zWHnoAf5HS+pihZ3pTKMqyXBuuk8roHZY43XivNbmmGhqM8U1bllWFQs3xk4f7qhPreJVZ4d9aAU3X5Dt1djOhnDnTc3gW3zVKse22gW9zdUJy12e4ZtDM5o3KySqjDzWvwXA4PoYyCFVmKu7npJIbWQqixKIW4XPq5xEyKiA4te+LeVOthHcOlszrUaWc3gM0xVyWY41nuPZpvoux4tEpDBoHO5djVk5R42qyMTeAScRuc8q2G9J9A2dZ+JbizTFskJNSETQknAMgr6QiGLAnglEmNyHRQ5YCbI3ZHVKl0/AhpG515w0YpjOGLZps9E4QcfAWZRTrc0yeKTPEuAsiRkKJ4x1tAuCaIUDV2COlVgO03ZQZUmU0l2FM891W3vxvyVDKFnnBIn6c6pvCmA4mWm9SlAHDGuk+f6Ae29Dxohj9GICiYDw3IsRyCHYhFR7FYuuUZoyflUFZNotOMrF2E8abxgktk7mB6noGiUUmHi4zdN/1MmzE6m+MlELf1Qps7U4cKpX+V1LrQANKMpJiUMDylpSoA76tck7+MIiJUMZ9mfso+hX7ITV2PzTlAS6X7lfatq7IQ+DW6JQl+XfQr3i5VhSjYg+kbFvyMgdYH1GI1bVDYTxmDaX0hpPSS10pDKGUaBObperCvunKTMCc/q6+C75VyqnKEGAcW+rmQs+hB5agx63ck9nM/5Gb3HnLUyX42Yls26l0oecdqF9yYBD5JeJX63vD8wLCu8EtOyVwrbSGqW5tSDg/lDR3PmqM9tOq/dM9Qrh7YCBLsdT7+t6PetMFzA6uu7nH1rn2ot6XZWHxgk4ne7xddefB+3LYsra7yRXIX1fEApz/YHj2keVnz9O8/jK3jn9Sts+ophx2FmA1dvHXPyYJtqpThaL7BO8zO3v8HgNT85P2L798mf8Y8uHgPwmdkZO7OWV7sbqNrx7MEhrlHc3jvGV5KmSFnFyd0dFm8ZqjN5X7Y3Uqsb+b7f8tw4OBXTtYf5fXED6LcUs0eaahMAYq1oD0hyc2iUvJtHEq1uWmFqFw8drgoAfK6pVx4709QnYqYe5gZXyfuvzq24Imw3AvaMxi5kvajBp4pC5qzFrHvM2UYi/6NpclZjFzVqtZFKMXHZbTrJLWod+mwjn9chwroy+L0t8TH0RYlQJ0x+zLeoKgn0UFqlIDK/aYvjs0zD2pHswoXAtpg4PwE4lUFn/BndYCIQVPkaqZqTUonpT2bxgiH0pUk7Hg/5symrNSEVfHHfkR5Q+Vg5rSA+LrCNXCAjksWuZPkiIZDAnB9/X7ZCH46sXmr6fSBgYhqg0jxcHJOBUBlIE/svvo8XdVhW8mrqrnQZcaTSH2nMRPEx8r0vTsrjOQLGJZi8RLdqk4FkIlkKIJn6Hm8Vr1HMhUv0+chvcgokf4f23geNaeyKWpdA2kFEIFACvfKdTXZP6ZpQTKyM0qfJtWOuqjJ/VgqQUUVi7qKSzCgJauHHUZoHEgvq3Nj5OIHVMZgdVXcpQRsCdLOZPU+JbDIoQFm8bmlKTrvWXKtVTe4xBakXdkJxXIgCK5xb+u7E509+LkWd6njPfhDBHseuBMFRCRSCe+T0fRkQLnxyyl2/sB4FMzm9TkwQqwNjEP2Vug7wkvQ3MIlSGrA4PwlClaK9M7DOaYP8YGXuxH4E9lLOCWNpdPDDDOO1lLQzet0FlkOlajAoLabs+M5DwuX6UJJyu8YEICxA0qwl4EV3EvwC4BX4ylCdtFSrAWU9/ZaR82uF2Vjqc1Fcw8JgWmG9UGB60A7ObxpOn6twlQTCSO5Gw7AQkLm8L3kE9Uqje2gPoNtTzI4l2KY5VujDCrPXcX4+Q7eKvY8cwtrwl5/+JmqQ1DyzWkDj6lt79Dte0gYtBtSVjv54hjnXPL1/wk7VcuvWI5RVdOuaWTXw26vbbFzz+5qnMbYvrK7x56+8zHce3wDlef3eVRYfOuGNd64w22mpdzt85TGdot8Oc/ioBisVXpST94KGs65JQLO9EgJY6sA6ziSVkek8zQmSKkdBv6vQMeuKE8BoOpkb6+uVVJFZhI1suXlQhEh6SXYfU+0MS8m7aFYDXitMMF/7WRWSiMsa0psOV+kQEONCiUtxjUAV8zaASkCYyC5Esjsv5TBLZsZmkOGDCdt3XSB4XHaViSCjrgVIRiBTZnOI/QrprQiyeGR1UApK15DoLxxlQjymZBhBAnYK956UKiuuzdIdorBIjEzqpcwtwGMEiyM3q4lpO+rBmFZnpLsodEuhb0ofxXSv6McY5deUcfT5uEwCUOK3SZN7jFL6FF/l5y50U7qnGlnORiB5xFCSxzE9ZNSD5PfvJw/iYczyFUAxYQ0/IV1KcBdJgEvwxkg3+cyWl4N0GQj2LpvcE6gtSZWStLhE/13S3vugMWLDcpKECTRC/AloZfAFZCB0Cagf+VsUQHJqKo6LKS/oMbDLlVMi0Aw7I58DaMrAktJsnhZcApXyDGmxljvJNCY+L7zYYmCJn0zuCOAi41dM+ugzGceJ2PdwjSRoosBL5xf+jj6Dv9JEP/J3DO9nZBYvFtKF5ODhZ06kHVo8vwjeuehUXQxUAKgJIEbzRskelOfGBQoZyEW2M4FBef8YLbnS0jvwic2Qc0UpiSk6sIS+EHjhX6zg44dBctXFvoXE4aqTXIy0ffaXHKyk0wFJQwJiph7ERzEmRsY7zMkqKWl9HhIwuwAEOyuRrG1ON2M6ixosbl5jZ4Z+p8K0YUyGADY7T3Mc6gvXMmddpbANrK9K/enZsQCbah3ATC2Rusp51tcFvGzd9cJQKmhOPKubmm4P/sSPfYXFQzBvzEB5Zo+hdwY9wN/8+ueo9jr+9I/+Iz6084Br2+dsbjjMWoGGre9VLGY9P/fxL3HtA4/ZDDWvPLjKwvS42qOMY14NvHF4wFnf8OF6SClxfr/aC7P7ACyanhev30d3muOH2+iZo64s9uEMM7PoW2vqWyvsUkB581hLGqOtnmotKXeGV7bwSgJf6lNFc+ZZPILt1xXV2rN5xuKVVINxBrpdxfyxVJPRnWOYkRhJXymaE0e7J++0WktuxmFL8nJWZ1IJaNiqJP9iK+UmdRfKTgb/WF9lsGS359hFJcFVdSXBMqsW6grTBTnSD1LdqK7y2oouRUYnt4xUD14xDmgL4CylPotVXGK5zmFAaZMAYS5OEF5IBH3RnSSCtuRSosapx6Z5YGEkg/BFwEjISTkKpqvMBZAzAqWQq0ZNg2iI+qDwE4wWnEhURMtGdIOKY+ozSIzyu9RtUzKl1FfR935qQeOCPsqVwXJ1GFHa+fq+0McTeV2+kwiMfABLigCQivOi3k1jcNF9a6TQy5uUYDBtRAq9EbJm5GvGvpDnQgLr4fhLGb4SkGbAm/tU6JIL3ZwCzghQy03EeENBZMV/OMz4TwFoDCh/lBsqTsIIJktAGH9PID7v0HLz42PKj4vgk6njb3L0jQtqshCTf2TaGXDxuAjOCpA7Ct4pq9uUILcEicUOMHXd2tHOs0w1NPLZTLtFTzJBE8apAJnJXzOCnHjuaJGq4tdCoJR0fe5QBrUuB+lEE9LY16Z4tnJH+i6+jcC4TFfpI1TsyJLvofdFXWdd0Pw6malzxKXPiiSyDhH0t20WNPHa0QfSeZQR8KiUwnedAOEoO8Kzpwo6WoWUIkYiraMADWBVhaAe1QXTdDBdq66XSOy6EtamH/B1jduey7XqSpJ/ex8UuQEF80et3EIrqCu6fWF67EzeRywZZzqH2VjsvMJXCtM7KT2oFcNckn3HiNphqVg8cOhBzM/NiQTMVGvPsD/gGqmDbOce00G/I8EbXoEzwpg1x/D3v/IZbBOqkTyosTPF4fEWs0egLPh3ZvzX3/kc3/jW+7n3cA/Tisl19hi6j7es25q/9fof4Uqz4pM7b/L0lWNee/lpGa+zigcPd7GdoTGiqGs1cOoEUD90v/f5Gm9qz6+tDzi/s8VLbz3NlaePUZ2C44q5sbgdi9YeXl3Q313iDbgK+l3Jc2lPG9yNDt0rugOHcorFPcWw8AwzWN2Es/d5zt9nUedGotc7AdH1uUSwDwvF5qDCGyXBUI3i5P3Qb0uy7/VVCWbRFnTvWV8T/1e8xxsFzmPOW8nnGACTq7SUEpwZXFLqSKR1XM4xmCIAGbc1S/kWVdujAuPnGoNfhGTefSidGfwdky/xLLsR+Ep8gv3QS2R1uWkOG8QU+BLN096N5WYEepXJvotRKUSgAHmDWVf52PgvyBAVI64hWyWmzNwIeGTL0Vi3IfInAr8g60uf+KTLoryOm9/oEhWCgFJhC5XvHUmNcS7FQg+UMj0GCSkyKCx1Tzo9W9HKfo8tg+GHK4N1CmYyd0Seuapy34k6uNQncmwEujlAlQKfFYBQkd8rfnSp0ZgmPVu6cRXgMQJagqxP7F9xXHw38eFKH8cEuosxLMkvGaT40PkZSnKinCsjszU/VHvvg8YphT1C43knNKXWy8lWVnwZASWVJ0uZ/3EU/VxS4AWIzAuyMBP4DBzTtVJgSgCJ1mb2E0Y7qDIYB+9TZHPy1wnBLMlvcbr7jc9csH4jc/vE3DyKphtNXDUqcZiZgAg2J+CwBIwwTuNTCMrRZ+VuOvZ3elwRRDICgkWFGImOjibcsk+Mq7w4JyAv3n8yZngfAl/UuKY0BJaQHFADAWBGhegygHROfFiC/2JiqAt5Io7sLgNdrRPAFLY35GasJCJbtSGqtBwPJ0yibypRmkGpqcAwqrZP46P6gfZghjnvxMfMOUmn4z1m1UuVjkgIOwTw9sImuUpAhq90krWukvHWvaffNriZxlWweCDpdtp9jVl7+h0jgS4O9r4tCki3iuZIEoirQWpPLx5Cd+DRnWL9lGfY8pgebKi1XJ97qiMBu3gJpHnm9kN87WkeGcxaUZ95uj0puceDGf6o5tuv3eadfp+3H+1jZx59taO+umG23YKHq7UED3W+YkeLCfLUlVHqvzetVobDYQtvQHk4vLPHzWcfU1/byHwYNB8+uE//TM/+80cyzpXnhWfv8aM/9W3MRqEeNOhOUR9rdAebq7DzzCmulsAjvVHgFdVK/lYW6hOfygHiQQ8CCPXg6XY0O69DJV1g/shJ8MuhgOf5YyvvtVGo3mOXBj+rqVYDXmt0L3lAvZF0PGbd47TCbAapRx1cJzzIRmUYsLUWv0WCD2SRPsacriVptrX4oRfXjfUmMIIICGxD7scQAIaPG0GSz12Z1st7j1ouijXjxfQdwWICdoS1XoDFaOqOlpcIQGN5wsmGOK3J0kIRf0a5G4HliM3iIrs4DEWAi8uyOhyb9FBkJ1XR78T46TwGKifLHlmjYvfdtMSgHpEO0zbSXSP9WsjVCcYrxySWoQWf9XYCSHncSoY1jFTR93BsAHlT3ZmOLxFpCSTHH5ISoxdMzbSsL3FDkczDBZBLl9Pjfqr4Wehv9Emdzp8yZc60fGBJ+ESWstSh40f5ge29DxojGxUW9Jhhy+BstKsJL6VkAEufwNInsdxtxVZeaxTx7C8Baj6adPN942TP5uHCx88z2QUWgC7eKi5Cl9k+YHTMKGiGcb9GFVtM7sMIJEY2NZkyxmWhYl8TE1aacuOx091p3AlPnZCnppmJ0BoB5uIeI+fwUlCnSGh3Mb0M5M/jOdOdfDCFybHhl6nZRKmc3FepEA1ZZZ/IEZNJcSwpnVBmwV0ClLEaQ+yjD4mAZex1BpmbGG1aZfAX6/DawJ5UoaavCX6M3SDXnDfCyhQM7ezRBresk9LytWHYqvG1CWxh8Eszin6vwTUas+rF323LcP6USfOi268YlibkYnQMc8380Aoj2UB1LkyjbYTpAgL7JX8vHkiuQBQMS2G7lIVhV3IP+toJO7YljFh6rY3CdIoPffJN5mbALh3NB85Qz645e5/HbjnM9RZlobraorYGHrZb6JW8q49cuYdScLBYc3DlnG8+vsXfeOXTHOh1npoovrTZ5feqvTooHtiea/UZf/bjXxKG0cGD165wsFhz2jZcuXrK946lpGBnK/avnNMcal55fI3f/J8/yvyRZ3bocZWnu2IF2O8NdN/YwdWw/Rb4CupDg3IwO5JoaQU0p3kDV68s1cYzzBSbpyxm7VCDmKVdrTj5gKHbrak2NgRJWSlLaKTPyjpcJQFUvhYTtlkPqMHR787QYS3pwWHnFcNS6kjrjQRluTqzc35WB79Jld0jlATYqJC02zeNMOdDAHnFmvNdJ2ZslVNTJVcUrfF9P86e4L2UHZwG2hHWZ9wsluvamAwQYlnB8typNSOxleS0XaXM7fsQcV34242Uvhr/8wVoivIkAq/pRrsAItMsFSWrVZqr42eR3BizgSZfy+drRqYyWa+i2bz0kYxyL94ngbz4HCq/76RrozuUIm8CIjAudHDs8wUKs3ymDPISA5n0x2UgMuq02Nc4XqW/YNkiiCv0X7x2MlkXz8/kHY9AYKn3ChCaAmXU+LyYJ3h03/j7u3R30t7zoDE68sZWArrsf6HHA1YAkKlPYHnshQTcU0AYPys3LuH6PqV+iPdLJ8hHAciMTdsxCfk4m3++Gdk8XkaAF76HJRMao5rjfUtfxdSv8JwXFmr5vNMd5fR5YWxGj/ea+OVccLKOrfDhjIsl+xkVfSkBXhzb6NtUXncKIi99huL9xD5E5rGsXV0+cxS+06jmvs/XVCoDTCCm2BGFEiMwy91LaKbKPpqekIB4/A6VQsDhTMzJXmsxPQ/B/GyENYz+VF5rMT1rLf6M1mL3tyT/Yh8UU2+TQJXSb1VKnGw2Ofl3vyOgV3cWs7bUpx2uMVQrCYBZ3rfgwNWaxTsbmtNeAi2A+eMumS2VhXrtWD5wqAHWN2CYQ79UzB9ZmjPH+tOdlBu8CnbhqE89y3tQnWr0AGalMR0MVwfsTN7DsGMlBY+Cbz94itvNY6pjw+3lMe7uAhTMlh3D4YzrH3qEuzfn+SuPefTGPqZT+NrzvS89R/dozr1HexydLuh7w/ZWy997/EkAXu4rPlA5Ptw85PeifaXd5kun7+e/P/4or66usnIz3MzzyRdfZ/e5E2ZmoH8851M7b7GoB1bf3+H00ZKztuHDn3wT1xr6heL8llTb8Rq299bYhUch9b1nR57NFcXiXk6m3u6Lub7bVvRbkjezPveYjaXd16Bh/o7h7HZFu6epznvqlWPv+xbTSsBKv1TJf7U+78Vk3lTCWoZpbecVGAF6VRt8cfscUFWddTmxt/c0h5sQ/W9TAnof2HSUkjkb5Eqspx7TU8UABZXqQrucCFxrCYjp+1AyT5PYHedQs9novUR/bDWLribhgVJpQJd9HYdhHOAS71dXeTOpsmxN/pHpZirVn74YkUuWhaVMjK3UL8XPMt9u2sBHQFgyiIX+kecu/PVN3gQmy1bxjD5EmU9dtOI7KVm45DN/CYBM1y/Bq8o+/CN9HNjibP4ugNOlgKgAVelvn4F+JIWSPinAazJRh2uoyXdxfBn3OwLM1L+S3Yx/x2Mv2xCMlGr5M/T7IgQhMY+J5Sz0uyqDcH841PieB40XmMAC4I18CIudVnqREyaxpPbz7gmSz0ZkjcK/lIg7XFuVk1CRonczi5evOUrUrRgLhAD8SkA6jcLOpZ2mwCICZTWKnLoAPou/R4xr2KFGAZPuUxwXz8/5tHKwTriQ/IzO4pER9cV5F96jG52vtM7nwzhnIuRni6xh2b8ouEtwWe66y+uV/kf4zBhaOzKPjQVo+D2m8wlVWEaBMJAFUUh8PWIQwriqppGFreQmEWyPdvZdJ99rLRUtAnOiBqk3rYyBVagMo7Wk1VEqV4oJaXewFr0Kijr2yejk2F8ftRLp2tsMfK2TlDlHAozPbosZ2y5qdO9wtaY5GtC9lzQsW4b1zTnrqw2mdTijWF1vGBaaYVklnzjdedorcPUbLXam6A48q5sGZxTDoxnrG1Cdi2/e+XOOdk/S+Jx9yGKXntP3O9SZwe1Z1jfAnIv/o+lAP6pZu4bFQ8/Lr9xCPS02Vv3yHN0p7r1xhWHbsbI1L37oDn/207+Bqi39tmL7xrmsqfOK+bynGwz7jTCNR3bJA9uzpxsOXcdR8HP8x2mnruPUzvlXD17hpJ3z9oN9/rvvCTj92tvPcHhvl4XpMWvFr37z45ze3cY+3UmN6YcNL337WUlkrqE+U+je47ct54+WDDsO9bimu+Jo94XB7fZUApH1mQQYNWcSjLS+iTC5y4rmxEtN8HOPtjA7cWyuznCVYnNgGLYMmys1y/sSMe0V2MaECGuDbXSaN3ojLKNPc8njZxX6bE19HOpKD9ESAHZR47bmIiv6AbszE5/F6NccA2OMgdNzydsIwhBG067zkpKnacT9Y7TDDdkXCPJFh5rOXZuPMVXK10iMlC6Zn77waY063pMDdoCU6Duyj5BlTMobq/K1oxXhMrOi1onVk3sWYGMq30u2L+q9eFrMoFFEdJcp3UZ5dQuyIrshZaIisYzBTzTJ/qAfR58V/1J5W4rXkh5LjT6PenNKMKSyvooRAE5m7Kh7k5JOIzS2QiZGj/F4X9qKnVA6rAB4o74XOkgVQLRgd9M7J+pqncZudK9snsw/I2OZAGqwUl1m7w/HxHzKlyPOi+09DxpLU2fKoRiZvgvzYDrJykkzuaYa757SOwmAL1duCYAqpY6J19fjhVfS7nHXVy6gyCxOdm4jcOn9pQKhnPDT3SRwYSwiII1+KaN0DQE4q2KCx2PHzs561M/xMGfAkQBjGJtRWqGS8S0DV6IAK31GSsFdCNTk0xS/jz9L1rEEk+WuPALrMvoxMqTeCzMYzcoRZE0FTNxBxr6USYOVzianmB5I61ylYT4TM5oKO0QCeG4afNfLjr1pACVAsPDb9MuZAM/gBK9qYSaxDmqTnk2txYytYsmzRkzWKj5zjMaOaUx6K4raB4WuVS49CGzfaaE2qXZwt2vQnZQPnD/YUJ8M6M6jHRJUYRRVJ35y/VIzLKDfMmyuGEyraA8aATBHYTPlwXSSWLrfk8jq2UNDtfb0u56fee7rmLWiOpUygYs3xOSqEODTXvG4xvONX/+g5G6s4K8883WaI439UAAHGhZ7Gx6+eoXvvvQM32mfwlQOtOdPX/s6T1055n/30X9Ee3/Bj1y5g/Wa3ls+Nz/huhGgcqAb9vU/vn/jjm746eVDvttX9INBOQVO0ex06GN5pv/N9h2G6z26A9MqbGtQvQSx+NozLDztjYFhS/JU6jPJml4dy5qYPZK5ogfP/JGnWntWT0HVehE5CryG2aH4OR69qLAzMBtHtXbMjoRVrNZO/CJ7+d20XqKnz3tQUjVGDxIQhYL6qEV5aK9KYJWrpR+qt+IuMQvjplWI9K+h0tmndiFVW8y6TzkafdejrMxbH9h7te5FPmqdg0u8TyUvVdOEfKdG3DzqSirCoARQOhuUrsgJP/Qi2wJz6ft+nHcRgjyITALyz+iQ3JsxMIjnxZ9xgxt8qBMLB2P3nnKzW+SWLTf34YPE9l1wP4o/VQZvI7BVyHNf9DfJ96gjAuEyAlyFz2UCd0kmjvXBiC0MYC4FjJayObUi00bQzTn4k8ICRQJFI3enpJLjCT79nqKaEw57NxClxr/G+1xCdmQgV+CPQp7ji8pr8fPyvv4iMB6Bw8v8InPHLuq20jwdjysB8g/R3vOg8VLAFHc6pgRAxcQvQUuxOxlly78A3C8DR4R7TSq6xK/DYsnRxkUuydCfzDzmhZ4i/eJ1onCIfhzJ0big+32+56i8YOhnWe/5olnCpOtcmnuxECJx3C4Ntikm8DTpeIoEnrKJU9BZAsJ4naIfsQJEAoaR7StBX7nDfZddpI/+TPGcOIYBwKOUMAUhP1vaqUXgGOvXpucJfoSxwoQNCqnMX2Z0NtsrDetNNs27oKTiM2upZqE68feiSHvjnUetNnLNdZuu6eNYnJzRHyyT2cwtZ2KqDgm+VSsMmVq3Eqwwb6CpJZ2J0fiZ+JqJP6inO5gntshVGlcb1tfn2LlhdjTQ74qDXL/XSEBEpZg97vAKtPXUpwObK5rmxFKfS4UZ08kas7VifV1867ySRNTDwqMGmD/UDEt5d5IDUvE//MNPY9ZiXu13naSWeWot0dlbkmbGG3Af2dDtetCev/GtH+VHPvV9+sMZ7krP4vqKxojvn/LQ+wo7GBa3z/kvXv4J7j3a47/61o9RX9vwvfPrVMrx+vB7HwDzS49f4Ngu+cTVu+jFwOxI0R/O8BW4mec/+s0fQ51U2IXnmY+8Q31ssHNPf9VSnYuf5/xtyaOontnQHMr8dbVn97kTdj58JPW7TzybawpXyRiur2iq1gW/UnmvpvVsv6Fo9wXsn92WICVfKbo9zeqmor2iOPyIMJbdbi2JvUPibjsPwS8e7LLGNob5oxY7M1RnnZQMXNTgPG5eM+wGf8PKpLROflaFsoAxiEaqHcWKKj4m2G57lBYfXrSRTY5SyTKhul78hgOz5a34BUfw6QMjqapaZFMEk0qn9FaJOYwZE6K8SSnbokwis4ox/U8MvlMqB75EEBQBYblZLmXUVGaVG+Fw7kg3xEoyJm+eR+5KxTVKP3r5+BIU4S8Dglk3quASU46BinKtAKe5atoYIJWb/pGlrdTFPv6dkOZEjkfUl/s2thgW76bo46WgqQSYivzTFwAgAepyTMnfMwHzCex5mVMxsMpFRnAKlsd/q+gry2T83q2luRjZ4vhsExBzGcFzSXvPg8ZoHs5RVhFkjcHkuC51mcKl2KWF80dh+lDQ7O+20MaLsAR5pT9BpvFJgDZFgF22uIr+lyDz3XJFRvNDqqldANHkFxOFR/F9vN8ofyJ5nC5LvzAyZ5RmlXRqBnqjZ3oX4Zh2kEk4ByGVmL4ApKLQK83VsQ8TYZuqK0yBbRRyWufrxD5Gf6VSWMcAl+gIrzXYQZgM/Ni/0vvMekS/1mFIck58sApzeBoLN1JOwviSlI5SiEIN5/nBCsMS/64rYS4rDdtbVKetHFNVkn4n7pZ7GxR3I2NUi6Kmk1rByefKg59XKOdpTrqUwse0A8o6Fu+sJZnzIAm3h4X4v5mVRNgOixhRDu1+jZ15hq1gfl6ENWAl1Yuykp5nfujRHcwfCtjEg5t7vAE7kwAaryUFjB489bGmOtXYN5Z4DXYpwNO00N+b47ctqhNfv6999QWqlcK1hvU7S04ebDMsPZ/95Hd5qj7C95rBaf7tj3yZp64e47ct3aZmsIa9esUDuwPA438Ck/S0/djuqxwOWzzutwR0P9uhrADG2XYraYKur/ljH/1tXnv9hpRI9IBVtDcGCeaxnvpEsayF+d2+fo5vPMdv7XL0+j6uBjtTNMcC1Jsz+Xf0ooxLvRJzdUwaPjsClFTumR86qSZzaGkOYXnfsXw7RGP3nm6vxhuJsm8OO4ZljW6FCdS9le+srCGvFaqVQC29lg0FIOCwTIRtraTLqQz6ZJVN20OIVA4bNz9r0tr180Z8FjdtVphxnUV3mFi+VclmTJLuD4n5j6X3VEyZA+M0OXF9AyNlXjJHKQm/GVsm0joNf/d9kblBF+fpFCSXWimbomycskvlcWQQF8kK+bDoSzw+6oEo5/20zCwF5sigN5UjDHppFHlNoZNS6p4Mlka6OavgCfkQ/y7BWKm/KY5VRR+jLgn6uGA4UznE0r+vxFCq+BnBa2CTcxWgeNz4/YwSl48eDLIfY/meiodIjGRxSgruifpSjd+5mpwQxyHOy+k56bwfAoDyTwFojC3naSrZvGxmLRdF8rtIgMOndxS/T5HDcdczuo+0KRsYGbnkwxh2UAmglbvT+HlcWCHVzvQevjgu3Cjt+kpWMLGHigvXSP2bjkf0ubQZcKWUCtGfJ56vywo4pGdJkXTlbjj2KQb7FCaakQm+iMweLboC5FLu7qwrgNk4oW4yt8cdfuk7OV08UZBGIBjuSWAghGGzWSjHvhidmUfie4hCS+VrOZfBaOn4Ht9hZCRRomAApU0y+yijQy1acvWLIAR830v0aFOj4vvXBjZS8lA5Lyk5ugG2FmKGjg7kvSRM9gvxFfNxvjUSWaoHR3d1KcxNUF52XjEsKmGBgH67YVhUuFmV0u3UZ50kd+7BzTTraw1oBDQ4CU45+E5HfWYTYFzfEDNpvZJo6c37B+qzAW9gfUvAX33uqc4kgTVKzKOukUonegDloD6V+269DbrV6XXYXYs5rNAHnaTweXYjQTOVxy0dugcWlt949YN84ZWPoltF+2DB3/za5zjvG37uA1+BteH0fMZvvfk+fnJ+hMNz5Z/AJD1t/+2dT1Fri/cK2xlsb/AVfPrZ12lXDe0Ny/p0xq9+7RMhEboCBzv7K6qjCt6cS7nFbY/zimEJq7e3UIPCLh2zI5Ffw1JkUb9U8PEVroKtNyWptw7BSF5JRRdloV9IGqT1dY3ZeLodKSPZ7mhxFzh22EYxe9ziakXzWIKiYo5H0zvsosJrMTnHRN8Avta4RY2dh+pElcYupO65pIGSyGs1WGG8ByeR/iEHaVyjdmcmOR2bSlLv1LX4NiolINKIT6J3VsRYXPMhf2Nco77L1ZpUZQQ8htrxvu+zTEtm4hKQ+HFp0shQlr7NUQbEn9FKMgzBZ5osy1xhyiw31/HnuzBFvrzHSNYFuV266oRqWvF6iVGMALCQq9EsrJTKpWILv+xExkQ8NGHixgGXKh0TddkFH8NizHIpvTJFnRoDxji+E8ZPHrzQj17+S2ORQKGcMkrrU+jQ2MdsyZsQTHJyBsbpM0X2ZyzaiEjxqU+jB5q+Z1WA/Ph3QXhduPYFf8h87qWE1yXtvQ8a46RObGDe7WRzcJwU5KCYyc4m76yKSZPesRr9Gy0OP6Hx40Iq+1GwacknsdghJl/C0eQjMYzlufJHvE9+vaNos/T8Bbicsm0wYgxT4EsCcYG1vIwxhMwERjNyBGzlq0nCoWDiinNG1wu7OR/MrKpkCosdso/pdEoBGZ5PRUf5KJxjiwyhUtkZffT3JCgG8jFFVDmeHA2NzyUDY5/itaKzexQeWqOaWTJvqaYejYOqqyT4I6vr+yEMjU9R1X7RJOXCEKvwkEzZ0VSmhjDHo3ndaKkxvTUToBnArvJeACLhuXpLvRpwWxJNqjY9vpboWTVkv1Q9OIbtin6pJdk3wgzaRqEGT33uGGaaaiVmGW2h3W9wtaI+dzQnjtljuVy/rdAOFt+rOPy4kTKCdwS0rG6CWUNz7PEalEcqyVgxa7dXHW4mP/d//CG7T52CksCQ5qFE8nonwRqLeuDK7RNuHJxQHRtc45ndraQ837lGd4p/9eNfRHnY9BV/8xtSWeaff+YlPv+hX+eVQaN/WKegH6J9pd3mA1ce8fX7t2m0sLjbO2vUAN/85vvBQ3Wi0Z2m37f4/QGzBrfwrN/axl4RX8YqZANyX9/CHgy4mac+VphzTbunqFces5bxMx2s1k0IepGShMMMtt+Ud+uMYv54oF47vFFs3Q3JzVeOqvUsHg3MDx26F9ay22vQg2fYrpNP49lzNU4r+i0jSdnnYsYetioBg14i7HWffQ/NRqL/3aKBSkuFmHLTGn0BoxxtaqqjFerwTIK9yiTdKqfo8Sm3YnSlkU2YipHN1gqbqHU4RuXAMNR441fHKk6S3s27WI6wkCmhZnxZqjDfeCJfIlCJ8q3MdDEFh6WrTvx+CgBiX6bpzKJMJ+iBwC4mc3MErirn+h2RBfHYKQkRjyvPKwiLUVqddEyhQ5IvJQlgJt/F7L9FJHVSUKgvwE/S4+XfFNXIIClQVWzyi48FE6QL5+8KdjBad4CCBYznhBuX4HUE+i55TwlEF4G05bmqvN4lgHjaEuiPIKdYO95n4PlDtvc8aCyp9dGkKhftJeMe/T5ylHIEdhmYJbbQ5R1ZLtDu0uJIfSgo+vK+OeiENElL5+RphHU+vyjbVII2lRdzLouYwey0+ksxWBcYSLwfOxLrIoI8LMqRY/W7vYcYQTwB70zOGecVK44t2Nb4+ciBuDxfFQK9bENMEeNzku1yEUbAFBVSvHZKyE3BFvr8s0iynSZRioqcpsvI76NkKXzXJqAazWLxnn61FpNVlH1agbMjsO2thZNzeaTos2QdvqlDkIwJ0dIeXxvxBxskuXdkQ5JZMFTSGHbmkqan7UelAtXgcMsZbl6jesmpF5+3OutRVgIp5oeDlBB0HmcUzZkoIt05TOdp98S/UXmPrUE56PY0diEKZf6wpz4TsFltPIu7MgB6kDrV4qcoJuxqJX3b7Cv8lT4l+8ZBtdvx7PyQ07s7uNrjX1gze/8Zw7bDn9aoZzacnM55+HCH03bG/JlzzHZPe8Xx2duv89yH3sFe7fkvv/kTfObFV7CPZ/yFj/9DZk3Py+ub/L8e/Ah3+wO+1Y1Ts/zjtge255nqiMN2wc/c/gbff3Bd6mwDbuno9y3NVs+w7YLvYpgYH1wH1tWjTyUP5guffhPlJHWOOarAKtBgl57954/ol0pY3bVMzfnrFd2uJDvfXHesbzvObxk2T1mqtWN9raLf0tha6k33OwpXy2ag2zWoXt51uy+J3evjDjvX2MbQ71ZsvylVXOaHPea8Q68kKEY5JBCmHTCrgebhSgKsQlochWxGRuu9qqRyESrUnO5kA5SSViPMeTOpSx3lwqweK+1QvtNbl1nJ4EeMC1GmzmfwWcfSomFdVJWsU+8libcip9/qB1ln0bKQfKR9lknWFtHXhXzQWs6PbVoedSLnEjMYN//G5OTb4TqRHBkFuhTXShYnazOOKnzmR8EzFGxluLa4QZl0/DgwkxHhkPWjTxarUXqhCBxTwGYY/9JUHkftsnRl5Z/xmabfRaAWAJqwi258nCd2JOOBghTKqZqKOXqJmh2D2Pi7mnwfwGKZHucysHkBPFLcXzHqSzwvWTXHgPFSTHBJe8+DxsucU8tAjfj5OAjGj86/cA0POTqaTNNHQBMPHL3jSZQa+RpTJ93kz1guLCMmYVWZiSm6ACGeEegbLahkKih2f8WizcfoZIKWj/zoGG/tmAkdDXYUKmMBMtrpTP+VppHLFkZxzbR7LXaxI+FS7tjL92ti8uvwTqIJqHQJiEl7Y3RzWmgFqIznTpubPBO53zibg3Hw+fcA7jMDEKIuQxBMTqMRAHBVyeehj1LJwkn1ly740YXnUVGhGS0AcLUWcOi9JPS2AvpQSK1pDzgnDKLWAu4riYBO4zpksOyNRnmP7m1I0NxL1Q5AWRdS58j33W7FsN3gjZg3UUiyZ6Be+1DPWBgvZT2zQ6lvPCwUbmZoTiUgpd9WdPsqRWmvbsDOG5766RXdvsc2Uie52nj0gwazVmJSvj3Qr2t+++RpMT8r8G8taF/ZxlcevddhvjdDac+Va6cY41i/vaSpLdW55iuvvp83T/bRhxXVWvGb3/0AarfnP7/3WV7cuc+j9RY/efB9fnx+n9e7a/zq+urF+fG7bNdNzT27y8ZWfHt9C+8V7A2cPl7ykafvoTcaf3eObhz2aQH6xjick0AWr5Ba2k7x0veeSTLLzj07r3u6Xc/soebs2/tsfeAEX3tJWRTMz/NDSdi9vKPYfk2zeOCY3zOcP20kUMmK64D4S3qqc4udaxYPJfemN5LaaHYsTLRpJS3T/MFG0jBVWlwh5hX9lQWuDgAluDjYRSXzM65Za6EbUJsOBkt3fUtMzNaiVy1+Xolv42IhwVoR8DS1bHhWa5nTg0U1tZi1jdRlT6LPhQhsLX7bkkRf5eT4spvPVophkCpOQ07o7WPd6LThC5Waou9ylMdR9pQuNpGNjOtYa9lMxsA5EDYzbr7LFmRImerGOzeqLqPqsf9ljAJPQZXF5l9O8YV+i4Esk3um3/M1s0k4XCcUohh1t8wuEnWWv+Q6BWOYIqqLa43yQBaAM8UxpGfK4DMmAM+fT55jdN84Hj7PAVV+XgDDpBN9BpUloCvZzwsgL+rX+K/QJSVRlMY86hc10pGjY5KfqM86ZqRjVe5fmR/yh2i/K9D41//6X+dzn/scOzs73Lhxg5/92Z/lO9/5zugY7z3/3r/373Hr1i0WiwV//I//cX77t397dEzbtvzVv/pXuXbtGltbW/yZP/NneOutt0bHHB4e8vnPf569vT329vb4/Oc/z9HR0e+mu9LiRCD+nOwAPCOmL2WVj5OurElcXLP017gQVFNOsOLcuKMrmUuhy3M+K5iArhI0BbPmKBmqigvcFeaDcN6EmSyj1UaRayU4K4DqxVB/soBRY1NFKu3ki11oFG7RId0XScdHjGsBFi8xTV8wu0zZwSIyMLKSRYflRxSIcbcff58uxNIJPQC4FPiiKHwclfwb5Yf0hdlZCQANACxFT2ol7GPZH0VgM31KRJwc3p0ourSZcFbYksqANoEJ0DCrC+Gu8F0XoqHFZ0ttwt9h7piTFb7vhYUJ5nm96lLffVPjq1huzeNnDW5Zi7LXEh0rpQE9w+4sAcF+b0Z9KiC2221oTgaq9UC3E3IFGoWbie9bvyXn6AFWNzTDXNPua0mxc+w5eZ9mWGr6hcIZhRrALhQeKR24vqZpHy5o9jcoB97A5hoSXe3g6Q8+wDtF89BwcrqgPtbgoL8mSb/NucY5zb/+x34dfVzx4e13ODteoHvFpg2lET24Rw0Yuf7NZx/z8etv86du/DZfffAM56sZK9/wS48+ys36mPvdzoU187tt/+3ps7y2ucbZ4ZKTfs7OzpqtRYveKF47uYJrPPZaj35Uo5TImeGkwVoty/2gxzUSwOIVLO47uiuO+kTRHmjMRsZ985Rl/Z1ddKuoVp5uT9HvyPj2Wxrl4ex5YcTsDHwlwHxYilwxrWw41jcEGG32a4aFwnSO+tTiKk27V6Nbhw5Ju12tafeNbDKcpzrtparMcYvqLG5eh9rTAqRcIyZdt2zER7Ey1I83WTYYgz5vRSb1QwrkiuvUbQUmMsq0TtJD+WEQEDYBEd77lORbTiiCNKqCWYysUjzfVGO5Fdaa7ztS6i4V1n60aCTG1GQTewCLkZFM/YhsY+lLDVneFZ/5iXzz5f18AbaiLonyOZr4w3FlfsVxfl4uAtBkbSorWWUSYtqyf332SYzp3CIAnJIe8myFXvMRbJH0YOpTlIOlyZkCXF5qis7ESg7Oyc+Yjy0A4QXypABoF1jEEuCNAXZOz1eAxQgiL6TJIfzti9/J82BqOp0A+QyAC3Cc3scPbr8r0PiFL3yBv/JX/gpf/OIX+Qf/4B8wDAN/8k/+Sc7Pz9Mx/8F/8B/wH/6H/yG/8Au/wJe+9CWeeuop/sSf+BOcnp6mY37u536Ov/t3/y6/9Eu/xK/+6q9ydnbGv/gv/ovYgjb+83/+z/PVr36VX/mVX+FXfuVX+OpXv8rnP//53013cyve2QUQWWLBMhSfDMam38edUAqciTuh6aQtAGU0VZdpfyL4SvdKLKAeL9rY4jHhumWlmzK9ThmtNUp3UA5J4QBd7tgulPAL902/TinssDCn4Drl74pAhQzCI3gemVEKtnO62EbR2HEc3o2hLABlFpaMn7/wWUymipH5xOdzhoEkCJwvACqMJo/RWeiXi7cWhnD0jNN7Kp2SeOMyE+m7TsqhdVJLtzRJ+U6UkQo53ZR16Vl8beR6o8z/Ygb2wUfJ1xX+YEfyNMaxCAm+UzCPViFIQeOWkqwb59CDoznsUOsOO69Qg0P1cq/6uBVgqRTNUYvuLbYxkuzZe6rzATV4Zoc9zkhQRLVxuNqLT+OZx1Wwesbj9gY2Bxq7EMBSbcTsvbrtA5CRFDrq+wsAdt5/THWu2LojQ//g69dZbkvuxZ3vaHZeOAYF5ljyHqpBcXP3hL/9yo8xO4SvfunDfOr2W+LfZ4TFM63C7w/s3DrFzj3Lqueb33+OXz9+gX/h1jfxveZ+t8vnr32XhRaw/N+cPMv/5/wm/zjt0HWc9Q1/ZvcNyRX59h7OK7xXmBstm7MGKofrDF55hnUNxknNaK/Yv33Cp27cwV/tMZ0Ex/Rbmt2r59i5JE1vTiQ5d7Po8RU0J+BqxbDtGLYdribUmYbt1zRtqP9drUE5WNwf8EbS6NiZwitJu1NtHLNDy2bf0G+Lf6K2sL5eiXl6p0H3jq27G4ZFYMWcx9Uau9XQ7zWSTqe3uEbjZ5Usw1A6U6071OlKymHGSjGVzjXfQzooWUNhrWmFX8zSes5FDRS+7RKYSv6NdpA11w85tYknsX+qaVC6tDbIOvd2CLJBjU3HMVJ6RBQEWRBZzH5SNabcEMfUVimobSzLy8CU8r4quqzoifxXUQ6brH+iz3dpbYu/TuT9NK3aKMMG5QafccxAcf5Yp07M7D7qpvF5pVXvQsBG4ecf5a4vwXXU+QkHBCCgyJuCkmlNgC31Mvcnfly6IiVmMF5PFXhOp/mWviMeBwlIln1LEfcJGYfvS9BZtpiMfvwuxqBW5fNHumsCHH+IpvyldsYfrj148IAbN27whS98gT/2x/4Y3ntu3brFz/3cz/Hv/rv/LiCs4s2bN/n3//1/n7/8l/8yx8fHXL9+nV/8xV/kz/25PwfA3bt3efbZZ/nlX/5l/tSf+lN8+9vf5mMf+xhf/OIX+fEf/3EAvvjFL/KTP/mTvPTSS7z44os/sG8nJyfs7e3xv6r/FYwvmKgJnE4+FOXYTsGkyqloIthJUdAmD3ZifVSxOOLCnNLI5N3FeFck949R0+V9fMjzlfoRU/ZEVi/dNy+w0f382PzsnROQEM0aMb1KGKtpME3yyaxMYXIdP09Kt5DGV4/PDcJs9HkEltMxKoXslImcmqDfrZXHlcC0vG58P9PjCoF6QeCXwjoWqo/mKTkwm5VKARgBZVByQAabSRj6/MNLYIzv+lBPt5bI5qhUtA4+S5bEcEcBElgEX4lfIs5CHWr2BnPy6D1qDasNfn8Lfd7mChtKAhZ0l/2bxNwZ0v3E+fbWO6jrV7HLmn6nolo7qtMu1aM2G4fZDKxuzKg2Esk9LDT9tjBd0QztDMxOQsLvhZiuz2+FiN8HBt17NtekIszyoWOzp7FLz7D0LN4R8+hPfO63+Z9e/wjKKmYPNKb3nN/21CcaO/P4bYs+NQIQDzr0mzP+yKdf5je/9SG88ZiNws49zY01m02D0p5b+8fcebSPOje4UJ6wPtYcvHAIwG694aBe8VOLR3yl3ebF5pAtVY+m4y/+n59Ov3/+//T26LtT1/Gd/irndsbLpzeotOPonR2qleKf//RX+ZXvf4pmp8P2GndWp2jx+lQxLD3V1VYipm8M6GMp86asAHHzkXOG72zTXnOYtWZ25KlWnuUfPeSdN6/QHCv6Hc/ivrgG+EpSGKGg/XDH4luhNKWR94MSE/VmXzM/lGTf7a7B9LkWtasUpg31pZ1n2KpR1uMaYXzrs45+p8FsLMOyoj7pJCq6kYj8+ngjGyDrZYO06eiub1E/Wgf2zkvgVsx/qDU++OPGternDWrVQvBVZN7IBqvrJcjDZStNTmkT8j6GNDtTOaDqOkdOR2CS5GhQHqMNcVhbcVl3nYC2GOwSA+PipnQo/BcnoKv8XBKS1+lZx/cs+hzbVL5ON9wjkBY2+lOXoEIvXDgmbtYjARF1ly504YR5nALAUreOCJ5StylG108sZfRl1bpw24KR5WuiI0fKPt3P52sk7JbZvqxzp76RE/1SCsvIjoLI4RIsJ5+3y95P7GO47ohx9O9yzGS+FO8mM5SqeCb5e/Ad/5P7uxwfH7O7u8u7td8V0zhtx8fHAFy5cgWAV199lXv37vEn/+SfTMfMZjN++qd/ml/7tV8D4Dd/8zfp+350zK1bt/jEJz6Rjvn1X/919vb2EmAE+Imf+An29vbSMdPWti0nJyejf0CxA4C0u1Dk8kejl1RcMJ1DdsCdAEb5LifljvU4RxHFccc1WcCZns+AMudHzJHJ0QxeJstOQTYpl6Ob7FTCsxT9KEFv3h2SrolHInKLmtejXWQB2iRy14+BTmQR3bhiQDo/PncCNwWQLM3P8RnKn+VCiMeWZuBJP1KbAst3YzXLnXopSC8TqHF8I0sQoyE9ubRYmWcsldYqdrFlTtASaFqbFFlKKhwBddzcrDcjc1cEivGnb+qgeIKZbrCoUH86+iuqrkdtQm7F6AfZi2lQaY0K0arCYEoFGN0G83pvcbU8s/KSh9FrJYASQCt07zAbSbtiFxKlrHphEn0lz7q+rqk2lubUMn8kgTGugtmRY37kqVaO1Q2Nq8XXbvkOVGdhQ+Zg+Q7UZ57T5xRuJom75/e1RANvPP/flz7G7KFBtwr3wob1DdC9onpmRXN9A2tDda6kcspZTbfn+dI7z2OeWmPnnu6Kpbq+YX06p7lXoR5XvPXggKqxbN0856fe913MbGD5/CmHqyWPzrYwyvG1R7f5+Zc/yxfeePECYPxBbUc3POp3OKhWnB4tOHq4DcuBgxcO+ZVXPoVZKfqTBuc0O9fPcTWgJfLZG+CNOf22R58YvBG/xubE0+2B/8YWehBQXZ2Lmbnd17zz1hXc0mFnMDuUcoLdvkRU27mSCPOHDe2BRLG3e2Ke1hbq04E61PPeXDHowbO+prEzAUirm5Lce9iucU3wO1SKblui9X1txAzuPPWZlB20ywbXGAGMs7DGAohy23Pqw02oaKTxyyZF/0uaHIn296G8p1vOoM/JuGNUtDdGZGrM7aiULPPACCklv8uSF0BYkgO4wMQ7W2wAjaxdlcEVlcmpswoT4gXLT18kCy+DL2J/L9nMXiyPO5FT5WY3yttyoxs3naUM9Nl6pUqQ6wvmLgwJPqeXKQMrk3uWzzquzLwR9VqU+ynQs9QRUZ8Vn02BZCZlyM8WdOmINAn9KK1hY3N5vGB8LpeeI95Xvs/m4LEFMipbMtbID8JoExHvo8t8x2OsMPrsgl6M+rgwnZeAccKOXtgUUB47nW9+cv67t39s0Oi959/5d/4dfuqnfopPfOITANy7dw+AmzfHppmbN2+m7+7du0fTNBwcHPyOx9y4cePCPW/cuJGOmba//tf/evJ/3Nvb49lnn71wTEltx0lURiRnp+B4AkS6XM7JC0XMvmo01r5YuDn/4pj2L9PipHvFz4vJmNLRFIAvlhuMn6efntECzklL87PKd270dwk0p1nyS3Y0LuqUbqcQPNPE3dPch2UUeapWMHG4Tu0CvR6uEx26QwJePwWC5eKanlu2Yrd8YVcYrzM1e5f1rSPQt2N/l9I/UTVNcZ/gL5RyebmkmIh+PyY4y3sHVZUc8L2V1EIxxVByQUnCzQugBKlS4cQPUlkX8iv6EZOpgv+Wn9WkdCDWBT+wAT+rxc+xrrA7swyEvU+1qn0TGOkQxao7i2p7zFmbwKA3IQ8jSL3pmaHfqRmWmvqoxTYa7WB26LCNRHAr7zEbSbXT7UhkruRwhObUM8wlBcuw5ZgdOla3JBjD1Yrq7P/H3p8/65acd53oJ3NN77DHs898Tg2nSlVSlao0W7IsaBw3jHE3DqCh2w2+9m0IrmmuBywHEUTwD/DbDdnAhdsBPXCxoU2AAdN0u41tDBfbkkqzSlJJNZ6qOvPZZ4/vsIbMvD88mblyvXtXSe6OjriUtSLO2Xu/7xpyrZX55De/z/N8H0U+c+hasbxoOL4iVUyypaK52FEegMKRLUSsurk7prk3QrcIwKoVqlH82FO/y+Z0QXt/BJlDF5b6qGJ0V0s5vQyqexkox6XJIb/3wrvRd0oO9qa0i5z3nbvBK/tncU6RzTXrGwv+3u338p1uvzG7wP92fJk/unaDB92UbGS4dHGPh3f2uP/mFk9fucn3P/M19KRj9HrGQ9M9RmcWaB+f+ANPfBVTOfKF4tzDe2xdPqSbOJp1sTGL88IgFjMnz7uWOEXdKLkv8C5oYRtNpZjeasgax3gXRrsWp2G075jcMcICr+UUx5b6jKY8sBRzy/S2oaukTdObluVO0O8UxlDXHdWBIfN1pye3ljFD2vo+JIy26hdfflNLYfeclqou+ngpsbdaQVX2zJ0HP1KW0LuZ8QuozpfIzHOxScb2ZsIv1JyV0BCXVHtKw0Ocl/FR47FvZ2Jfw7j21ZUITKDpEpuSxD+uekvCOcLxyWI/1rpPw4Hc8BmF+xjYvnSB6U4SGL2tdoM5JtzTgACAYQiTo49hhH7eSN9bsPv+2AgS9RB+BOIljc0OcY+rsZSpMskJRRJF4vFycT4cAOJBE5N5fEU/cbVoRbjHHvi7/hqhAS40YgXEMWx/BJJpjGT/MBLN48DkrrY5PdZfO5mLY0x+nDhY+dknT524/tts/7tB40//9E/zla98hX/8j//xie/einJ+u211n9P2f7vz/PW//tc5ODiI/9544w05JqGze6FS4kvvXbz4ATUUy06zpGM7rO1lTUJz/DmFJh+uVtIM59jxvPbeqmh1AJwpg+lPFgf8gOlMB1EC9AaZ0qGUlOr3l3sbgrcTCTDJamtVTmcgs5OCsBC3ubpvsrIMK9xVOaMTQtrJfYOAI6WTzOIYO8jJVVkKIKNo9sqKPTV+NjHWUYuNhDV0MgFEV7N/1mH1nmlxI6eaj0ETEjUsSRhWnN4lJdnPsuobZrj3lWlUkUvWtC9PKELDLc4a+Ww6FsBqe21FF+4l08K+AKrt+vYoZNL1cZF2XOFGBdmRTyzwsUKqEWBpq1y0G50TN2KIDc10TITRi4bxvZr8uCVfSrk31TnypWV5XibZfG7IWkc3FsHnZqo9CBHj3o0V2cJQHvg+r+D4qugzzi9olBH2MXtyhjLQXGspDxTlg4zRfWgeaml2DOPXMrJ3z8m+NaI905HV4DTYkY26jrYQBvIfvvhxjNVktULPNT977YvoRnHu2Xs025ZqH5otS1fnvHG0heqk9vUfeuRbjNdqKt1ijaKd59gcOqN5cuMO3+n2A9M7zEzJP959EofiiZ17WKd4ffcMtnIoHL/18tMUhWF5wfHNFx5iuSzFLb9u+e0vvo/zjz7AZo5LowP2bm+QNYrJQ8c4BZMLM3QLR88Ymk2wmWRJ27NSR9yWYhfrM6LRmNWO+YWCo4cVzbpidkkSmWzma0k34oZuJxrdgLKOxY6vab3fYUtFvjA4Dbq2ZLXF5cI057NWxN8LmbzNxGc5W4dupFKMK70slPWLlkS4Pwh6u0wLkMrzCKhc1/X1qf0xzkg5QVcVwkz6BVNYaEWXcPAoWSOxiD6mUWVaygh2PTMfs6cj+PFj3XReONwOE/R05s+bgIlBtZhsaJ+6ri9EEP6FcoipLV5d/Cb2NCa5JMC2z+yOKK9nIMNclpAKqaZwiOvr5z7Vh3f5Ngxsf0JmpNtp83yYY2ShPLThKehM2zkom7sCHCMwHjCSKWBLW5TM436/SOio8OGQrAgVZMI80N+36n8oFb2P/ao/nM4lADUFdUk7bdou1bdZrbzD8KxI9lUr36cMY/+Q+me9utB4m+1/F2j8mZ/5GX71V3+Vf/tv/y1Xr16Nn1+8eBHgBBt49+7dyD5evHiRpmnY29t7233u3DlpcO/du3eCxQxbVVVsbGwM/gHhffdb6I/WRg2qk7F7oUpJAFkJ8AwAKY77JEkjsm0po+liG/qSSQgrFfZJgM9gkCXXkF/Uyr0MrxdLDqbtDGBzBXCfyGiLNsd39PQ8p22nMH4h8eRUYL/ShjQhyJ1i8GIbUwMTnkP6ecKGxr+VEmMZ2telrpUETKaVX1KgGrO+de8KDucLoDe4a5J4pBgDlbZF634CQPXXCmASegCp+ko3slgxw/tqW1zb4LrWswJeSLhtJKHFs5kif6OEUTFW4rzqBqdVH08VyqH5MaA6g142UssXhx332ap2Y4ytCrJ5G8u2uUqkicy4oN2s6KbCKFkvMG7LDJtrTCkAL18Yqt2aZk3cl+1YgGKzkVMeW+rtnNGDlrwWYWgzEmPrtKKcWbKFZFvncxjfgW6kqG9MJTbyXgkOmm3L8iyUbxTkBxnNhsI4RX0GJtcFUBZHCl1a3vP4Dey6AeXQl5ac3Tnk/3r+K+LqzeFvf+aj6EZRKEu1XvPHPvE5ys2abD9nuSxZe1iEwm81WywPRnzpwUOYLouvtO0yvnj74VOHzuq2ZxsWruVCeUiZGb586yq79ZQ/d+YlmGecO3fI11+/ItI4eyMRxS4cxZ0cMsforsQg3rq3he4UX3z9EZgYTOloXlzDVo53rd/nXR9+A60tZiSJMDaD4kbvQl9cgHJPqujYSljJ6U2wOZQH0KwJ47vcVphKoxtDObMC4BvD6IHB5gozytCNw+bKZ7VLRnW2lAQp1XTouqMb53STAltov7gQ1lnPW5xSmCqTfxOJtXZaMqRdkUEQkzcWtaylf5eFLKa83FSodqTyJO7PS8+4SQWjSuKEg4vb+lCRzMfqZpl878AtlzF+ONoYa/uygkE2R4v6ASmDFJhOh0z4IWYxLQloe3sI/pj0s0AorMrtBJsYYw9VTy6EGE2/Ob+IFW+POlEiVSW2NIKixEb3sYkM5sthKBIxdjBeU/fsYq8L2X8fQ66C9y/Nbg4kymn2O8zdWfCs0YMsF/6lc/vK3LoKyALIDUAznCNx80SQnGK9xFWdgmzS5xjYzPRnBJP0CZC+UT0DmL7st5iLV9nElJjRagVkrgJN/+DC/X4H2+8LNDrn+Omf/ml+5Vd+hd/6rd/i2rVrg++vXbvGxYsX+Tf/5t/Ez5qm4d/9u3/H933f9wHw4Q9/mKIoBvvcunWL559/Pu7z8Y9/nIODAz772c/GfT7zmc9wcHAQ9/nOG+1/hlUTvVTOIG4jiRPsVwJhJaQG7GPYBp1d9wzhYJ/E7bsaJ5Kex/9yAhimTFwqyJrqXA2ulbJ+AaAlzGdctYXVGP29xi2Ao7dgdgcM6CrwW/kZ2z8Aw4lcTxjUq+B0lVGMF19Z1XqAGPddZRUBymL4TFZ/1zoa28gcrMR9Rmmc1eNBjg0sabxX18c7BldT3Ne7DYI2pKMHl34MO7+P8u7xGG+a5ai86I2Xk0nR+YxR5/DVWVz/PKy4vlVnUVXVazaG95xlwuZYEep2VYGe11jPdKjGeGFwAIWpJHbTjHJcpshnLcWxvz/r3Yxa9AJRkpji/L0rB1ltqfY7SYooQDnI55bldsHiLJSHkiQjeoAW3ViqfSvxedvS59upYnxPytzlC1DOsXZdCcgp4OPPfINq39G9MQErQHD2kCTXnN045huvXybbz9GNoswMe7MJ//TB02SXFuL6vtjQbRquv3Ie98aY3zl4gq6TSjFr0yVHi4psofjDay/hcke9KCiqDtVoLlza49LGIZvrc76TbVuXjFXB9cUO28WM0aTh6niPf/TgCZ545BY71Yzpzhy11KgOyj0NGiaPH5GXHdlSMsnP7hyLSLaDyaSWsoJO9v/GFx7llU9fRd2STOJ2TbHcgW5NEoiqfeky9aMd3VQAY72lsRlsXO8wldQE151U3ZlfgNmlEqeRjOkzJbbUPgO+ZbktMY5Zi7xnrWjXcmypmV9Zo5sWZI0ln7fkx60wh0VGu1ZCkaGXLXktDJhuxO7pZYMdV+LODvFpVY6bjISVbIUJVHWLmi2Ji/vgSVrUMRtZShL6PqmICSWurhPbgLCUIKEgClzX+qSZQAr4hfKoSsa+/xc9Dj7eLoS/BPsS3KRh8RbsVmf6RWkYo57RV2U+tJXBsxGubRO7G36G37N+P9d00UsysL/+7zgPevt9ghFMvTyJhyy4hr2p6OfS0JYEp0Q3sW+j8qxnWrY3vWY4aTqPDrOvk0EV53uVAGDivZ5wa6+eINjw8Ez83xHwxnkIsdMp6xpBsZIFxEAkvAecAVv0bHXfnkg2reC88ADDvQ3ZxoSp9kAxVqiJ10raki5SdKox/fbb7ws0/tRP/RS/+Iu/yD/6R/+I9fV1bt++ze3bt1ksFr4Nik9+8pP8jb/xN/jn//yf8/zzz/Pn//yfZzKZ8KM/+qMAbG5u8hf/4l/kr/7Vv8pv/uZv8sUvfpEf+7Ef49lnn+UHfuAHAHjqqaf4oR/6IX7iJ36CT3/603z605/mJ37iJ/jhH/7h7yhz+sSmhn+kbuXV+IwUSA0yl1dATcyu8quTweopUPfp544BuAz7pXI3A3AVQO0Ky3jCVawYuqpTkNl1CdU/BKDhHuJxg5sbArwTTKAffDFjLQK/4bHRneEkkLqvENCDlRSApfphq+0YuFrS5xKeW7j31ZU4DKsppCvVsNq2tq9WE6+rogs3XpMkYy6u7JN2hHMF8BfcPsbEoPY4mXh2chAUn+feWOv4rF3b9e/cGxpxS0u/jBnVwUUWn4UGX58X8GypTE6qNb2bLsuEqfETbr43R9XyvPLDhSQdKOg2R+L2LjKyWiRPXC6Tp140PbYe5+jOSuZsa6kOWol97PzK1xC1GkOGrc0EWBZzcQNrL9+TL60HiBkKMCNFtSuvpN3p6EZI9nMt5fLml8CUkhTzH155N91Yce6JXXQnJfGKA5GIuX9zi3Jfky/ATC2z+xOy2yV1l9PUOWqzRWcWvZC61srCn915gSyzPPaIeFGs0bgMPjt/FL3U7GzOyDLLzsVD7uxv0FnN/sHkZF98m+3qaI/1rOax9V2+vneRe4drfOvmRb75+iX+2M7XRLi7dNgrNW6t48L4kCI32BKqPcXu0QRbCEic7074yAe+RTdB6kNfbunWFO2WZXxL4kDzucgO2QJ0I9qXtvG1vK1jfFfCCNqJRncwvm9xOR4oCjg1hRI3s/MxpnMLWqr/2FxRHHVRBL4bK7qRppgZsqXxkj25r0utadcy8loSrVyRSUyicehl68W+nSRWhepEeYZaSrUi5ROy/MuRRUsj9dbpOhkjSsmCCQQ4GusXYpkP3/CspLdPEl/ch4gENiZloUJN+CgGHj0QWSKVo3pWMQFRMWNaKRmbqZ0NWygfGNzng3rNK/uGc7qkYMSKzR8cS1icJgv/1D6ech2Xfh+OixV4+nCjdJ5yIT7aA6uQS9CzcPjnGpBdf/kwh8akyWS+g2QuYajtOASELj53IVAC2eOPUz1DmM7jqU2NbQvsnEp+Z6VgSEyaSd/BypwWsUa60GBlH3f6T1RsewquB4xiEOwOYDQemgDVtG+sEjtvs/2+QOPf/bt/l4ODA77/+7+fS5cuxX+//Mu/HPf5a3/tr/HJT36Sn/zJn+QjH/kIN27c4Nd//ddZX+9Fbz/1qU/xp/7Un+JHfuRH+MQnPsFkMuFf/at/RZZU2/ilX/olnn32WX7wB3+QH/zBH+R973sf//Af/sPfT3MBBug5SisEoJdo28nO9MYgqusP9QwjIIuAggjoYmf1HaKPM0zOTb/PKqMYAFMYWCkYim1PQFzKYqaJKnG1qFSiI5msSsKqKGHjooYknDAcJ9zvaadesUeRAQxxeM71MZVpTEh6jYTVHFxrBcAP2MOQ8JMyhDAcCOHv0K9C4kg8L0SB2xSIGr/SjxUaekOmtO7P52U/4pdhsggu7dTARDDreuYvz4ZsaVjBp6v40FH8OaMLJ08AuFLiFtNZXzc3xDAuvWC3n3BcVXrtRRUTYVAKVxbYUYnZGIMX9XaZFre3Q0oDBukeB04p8nmHKfyxhTyrbNGJu9E4meQLLW7xXGPGOU574WgjrN/4fic6gMbJpO/AFprlmYxmqlmczVieETe3kzwU5pcdxYOcbqJoNiT+rhuBrj0b1vhqMGctu9/YkTjGM62IdT+05JGH79JsOi48e5d81EHmaKeO79l+DZ051sc13WHJR554GX2modm2/O2vfYxz02Neffkix8cjWGqm52d0TvP4o7c5bkra2yMOXt3EdYqFKTi3fczvZ/tPJvc5NhWZsuxM5vzgla+BdqhW8c9e/h5sJa5o02lYyvt9ZvsWppIkIGY5k6vHdJcbzl484PduPoZuYHHVUt4q6M63FIfynuaPSFwniMs+Sh1NRWvSFopmQ557eSh1rNHios5qF0FhOxXwrI0jq62XUMolcWmSYcaZSDCtFVR7hvGdha8tbSj3apR1ZMuOZqOgelCLGQ3gLNPoRYOZlqIxWuTkR5J0JWL1wr45DwhCZSNA6tMHQDeqvNajkvAL52RSDeDDGInb1RrXtf2EGwCn/xcSX1SWR5bQta3EMYZ5JEzYQaA7rVufyRiNwNErFAhbmA3rUwcbG9o4KFW6sjnXu9cDaxfA8eoWvg+awyGWUiVJEUnZwZPAhZ70CLYzAqDkGuFXTy5E0Wxvq1PiZjXmcJCMeuo9EOdxaVqvgTz4PZ73ZLt6IKeGc3UyR/exkuG4FKEx/M75hkUgGebilfjDOO+vzBspIBiAdn/ewCoOFgD+HiLg69/RCQAYgWWcyFa/OBmy9hbb/yGdxv9/3oJO4/dnf5pCl8kKotdgilnR4buVFU4Aa7KiVCf3cwzPAQl178+j+/NEYEjaKf15Un1D/7c/cc92pmCHvk0D/cjTjAr4WqBJicAARluv/xcGW4iFiSu7vu2+4clJU0C7cm6dtj/5PLhswwAIbQ/7hBW9X8Gm1x2IyaZteKtYx3SfdEuFuAPgjEXs3aBd8fcTdsO3P0jihH9x4eNOspfpOQLDGPTeVsoXRhY3uLdTMVhrUEUZg+pd0xBcJMPYVWmf01pYwtBX88zL7XhjlGlhYKzDTEtJhEFcxGZa+VJtJarucONCmt8aTCWsojIWW+aoN27DxXPYUsSd84W0OWsM3ThHN5Z2TWoi15taxLo1aE8EL3cU47vCSDUbisldS72lGT2wtGOFGfuqMkpR7ziqB4pmw0nySgcuk/i7bsNQPMgk8eXxBfbmmHbLUOxldOsWPenI3ywpHp8xvzfBTQzOKjAKPTLYOuPxS3f5+PRlDIp//rvfx/KSQSnH+tqS2bLELHPG60seWt/nxdcv4XKLsop3Xb3DS29cYOPsjFHe8aNnXhx0vbfTafwXB4/wJzZfo3Ydv7r/Hi5VB3z5G48BYLY61LFI6eSbDd1BiXLwJ596jl998wOgwCxyUI5iX9zoulWoy0u63Yp8qWjXBSiW+5pu6lCtiH8XM4d5ZoF9dYLTYMZSt1t34JSECzQbsl8xt9hMsTgv5QVdJlqMTknMqe4kPCBfOIojWUB0k0wYR99X6u2KrHWo1qIbQ7tZ4jIo92SBozpLu1GShxjIzqCXrSximk5YQYXUks40+nAu42BU+pjHHLVY4sYjWYTXrXzXtD7Gzy9O80zikMeV7GP7qlthknamQ+lMwj/8uFVhzEEC4oaTuYjyN/3CMh3/wS6E71JtRm9zybR4SLw9dNYrINjeRomMVtZnPKcAL7XDq+E94Rqp3U23YB9X2ahwTCRDVFTrSOchAosYSBR/bKoznM6HJ+bFBKBG70rQe1yZgyUmtXvLYwefu37uT9uWKoCsajwOMMMJkkQIkXS+j8ektl4ukjx3VrZU91INPk8a0V9A0WdGD/ZZ/ckQrKYMaWxH3/DOtfy2/ZX/c3Ua/6PYkpVRD+D6lRIkK5sU4Hsqe5B1nLyPuHqCgQt4uOIiXid1VccO6AfQwGXBCoD07V49b6hF7RsbA4r7v/tyg870WblpsHO6DTQcB4NLDVZxqyvPFFyeiBFJmclwXALsois6PS5UNUkEwFMglf4dB2FgUU8BtIPzp6EIEbSqPvsxdT2n50C+ju6mUBEisARprFK8BzWsQxsXAXg3tI/DLMuemQzv2BiJpXKiLacUQ6ZShzjHVtjC0J5MQ1UIg1H4WtZeZsRVkizijBVXXukzwQPjMJdYruxwGZ+JKwUUkotL0FWSkBBLwpVS5s0pJTqOgC0zzCijODZktZQc7CY5ppR4xnZNk9WG0b4hX1qKmaWYGZo1hW4RN/XMYStHO5HSgS6DYill8cS9DWjpT/lcoRspHWi84Ha5K8A0ax3t7ggs6Ll3NY8N1khCx/HhCFs4XCtjULeK4mbBRx9+hZfvnON/+tIn+OXnP073SI1SDrTj8vQA22nQjqbNefmVS+gWVKthZLi7WENPOw72phw3Jb+fbW5Kfmt2kV+6+37W8yVfunsVU8l9nd06xq1JXO34+QJXWPKZ4p+/9BEm3yxwBwVkjndduku76SvEaHA3R2S1whaObKEp90TcvNxXFMeyT72lWC4kPrE5Z9CNIlvKM60OJO4UBbNHhV1cntFgQVnoKiQUYWmkAkzn0A2+HnVGsyli7N2aJLW4IiNfWkyhyBatsM8K8mNZSLZrBartJPN+0frKM7ksanyfVG0nrulaZHeiFI0xmHVff7oo4jh0TrL9JU46YfitlXEY3N3OSUKbDeUEm35shUVisKvBoxBCUkLlGG8/oqRMYH2CHYiMY2LDTgnHift6G6SCtyDYUX++1Tj73vPQzwXx54DBcv184P+OnrSQOLgKGMOTSG1tsM2JlzC06wQYjUDK9fOyfz6pbe/jDf0c4xwDT1lwyzp88qFc/634r4GyCP0pWAWZIXRIJddI5vDhwcPn08vqyX89a5nsu4okY3PUybYrhguNCDjtcBEwcOe75OfK+w/7ntglbdd3tr3jQWNa+m/INg4fVoxrCO8zAYX9aqkHmIHSjh06fTcJuExXUvHYgYDqMMgYGLoGVoBQcPXGLLZw7jQwO7Q/dLQAetPnsmqgYGDYele+HxTBxRzaJSfpr5EamWAIg6EKRnPlmn37VHJPK4YqfO6SmJGUEQzG1CaZ6eEcq+cL7GI6oGIGtZOJJgJNTrqaQ3vbNjmnB5pZ4naC4aQQ2qg0QTQ4uryUkuQW71aObOt04t+nj6fJc1QQhY0r/MyXL9PgrK8WI2DTBfbQu7ZVcLevjRkYMiuxYCERRlkba0pLQL6NfRkQCRR/P8WRxIy5op8Es3mDNrIg6iaSKJMthT10CqY3G7qJd50bh8sV7TQjX0qJu6yWMoXTGwIglXPYTFFvCOhrNhSjPcvkhhrYxqyW+DyXOVQHuhWNQjsxZA0iW+PALTKKOznLhw3FQSbu39KSzTQ/++xzOA3PvfoYqvbxWBsdOnOozHF+85iXv34FFhlKO5QX1j7z0AFuZHCNxjmFuleSj1us/f0Z4x898yLrWc3s7lS6zf1SwO9S4Zwif5Dzyfc+x+KMJp+JWzYbdyzOweT8HL3U3J5vUBxJ2b/yUACcPS8xp8WxJA657Q4zgmIhz6Q715LfzymOxT6O71uaTUd+fslyW+xHtWeZvKFZ7mhKf57FOakTPj+vsZUmWzqqvQbtFyPLMxnlkZWEl5nENR4+XKKXHbZQ1GdHKOvI530SWXEsjKLNFKptUUYqyuDwJSuNxDs2XayPHuq7q86SHS3Qs2WsMa2aVhZSXSd9vSr8AsrbjNxnO0f7KQL7Snm20BjcuOrDUpzrB4Ojj1UMTFLYWs/shzCjYJuC9mOwBytemfizS9zd4ecpi/a46cQTo9TJ2O5wnhBn+DauyAiaB56TcNmV+L20ben8kOyTxkqmc1I6l4bn6XzozhBkpfcPPVByvWC317Lt9/c/PHAPc3+qURyeV5+QQ8wuHwLe5L5SoJUSM6fI8sFJz1+f/JKGL7ECBF1yr+Hew+9+fggs44lyhAkwHbCMQJB0S68Rru/euj+sbu940JhqOa0GvAYGb5gJTA9g6AdJ6gKW9zGsGx3jLIDAIK6C0Lilq5d0tRNB2Mn7iFI4CTt6ciXXG5jVutQpW5jGpPTPKYmlWxnsvTyR6lfRp7F6aRsG78AOQF287opbWQCU7p+XG7pP4v2m+mWBLUy/j+zhsH3xHkPGYWhvNOhdwvb5/ULFlhQM+kzKPgbJD2CVuLG7fiKM2dnW9gygH6wuTGZNK+/Xy3WoxRLlGclwnyLKHWJFE9H0EGgeWNplLVVfmo4Yu+IrZrhc4/JcwN+olFhKf48qMMt122dL+2xTNyoIq1/lGRmsQ7cW3XTRLtmRSPMsz+Tks1ZAXyngwuWKdj0nW1qUhXoro6tEt7Ha68gacFoxv5BTzAzFTESou7Fied6gOzBnOtqpYnkWRntGalUX4JS4VfO5ornc8aHv/RbtGUN5P6fesXzg4dclprG0tOc7XKNpNyzKKFyr+Svvf45f3nsce6UGK2OwWzP8wJVv4G6OKN8o2FuMeeaZV1EOPvn4F3BW4XLHrCnRs4yt7TmzW1N++APPwd2KxbzkrkmSsL6DzThFcWbJCzcv4s412MqhW9h7Y4Nz79rlb772AbqpI5uLnI1Z5PzMh57jh84+j9poqa9PufzkXZyGax99EzMGaxVZI5VclhcNxZsF7abh6FGHKZH71dBuKHQhLudqH7JvjZjcs2RLx9Fj8h5UB/nColvH2psdWW2Y3O0rALVrBcWRwRaKtTdrskVHtmhRFmyumd4R5rval890Z9Fen3FxvvIajTnaONxkhF74vmgt2az2Cxsf/xqYxFHP6Los83I6pSSBKVnooIM0joXjeZSrUul4T+eBQCqMK3F5ezAJPlnGuV7TVeEnc1kADjKfbXJex4A9jGzSqv0Mi/Vgp1JPyur+US3Ci/2nMjqJa3qwIE9LDyYLepXEUkbSwZgTIDEmPTrXFxiwfX5ArMiywu6p3Aunh2pnifpHjNVWPtEvke3BJZVqMj2orhXCruI1AsBy/bED7DkINeoTUWMuQvgsISiUl0uL81B455GASFfV9J+lRAhhURJAa7JQWJ1PU/Yv3EtMpCFZMKSgMCFrwncuYa/8/BRd4Kcwyf+nZE//R7v5Z+fCiiChxSPLFel54gscSNr4F5+CujT5ZMDcxYHQv5AgiJqCzcGxyT7hu+Aij+2mv+6q5lXUlpQdhi7tZNCnQqkquc/TV0QM2gPEldgqG8jqYEu+C6vfEyA37OvduC5dYYfr6gSwBQAWYoLCgLT9wIvvMHXPeGM4SGJZrRuabik4TaV8QkZkGMChr4R+4lwf0J6sDgXkkSwWQrUV+skhGMtE2kY+a6TrBQMdVqjhnv2qU2U+eSUsRKpSLhDikwCXZ+gjcT87H1vqkvfqvEyO6ix2WqGM6OaRSeWWxY4k0bhMC7torcjrWAde3NsWGlvlTG7XnhlyKOMoDhvMSHtBbZ+8AGSNo13LaDdykYux4oa2uYhKK+PIF47JDY1yok2oW5jedCy3pXa0udDSbtkYG5nfy/m9F5+kvJeRLR160vH1Bxdp1x0sMvSRvNPRXY0rHCjHL+4+yd1Xdnh256aXAFI8e/VN/u1X34c939A9UpO9WPHy0TlsIS92PGqgsvw3l57HVo79vSlmavnXt96H3WnJCstvHrznrfvZyva/Hl/hSw+usl7VTNZrnti5x/qZOe35jr/ywefYnU8oXi95/2PX6a42dJdadKv4veUW/+z1D/GHLr5E/vCcu188h+4cNxeb6BayPQEJWS2u+2LhYhUYpx00fjLsYPqNjOOHBKgqA7OLkgyTH2uqPUu+dLRTmTTFtZ2jO8fsYoEZK2EQt3PvVs44vlLhtMKUEttoSikVqDpLcdBI9SLrUEB56JOv6g46K30kz2g3R74PCohyhYh5h5rnwnbnXp8Ur5agULMlLs+9CL23eVGg2sg4DBnUWiS+VFmKyzOEbtSt1zbN+zHvawcHoKECM+Y9CUEeRwaEG4bF+PEU7VcK5kJ8dFqLfjUeEYaTvUmOT8mA9NiwuAz2sW2HsecBWA5KBfbzTapFHGP4wmatD3/ScR4SIm1FWzFpc/TghQRDT8L0Gc0QyBuVeIYGbJ7rSaA4t3mVk5j8mYLs+PL660WigjDPJc+XcNneqxfDzExvv3ug5W8kNtGtXD/8UwRiQBqZkkkBW6y0F6/Jm4LFgCtVAlhPMKL0c1W8rj9vAP5h/9Xn+zbbHwzQGB9gWCWEznqKDqFKVwPSKfrM3R7IBKC1mrkl34eOnA6aIRAbHBNWTHoIrNJVURrneEJYNRkkqYRLGmcSvutXPvT7+SznEG8TJYO0Hpxz4P4NW2Koeqo/WWEmronBfUEC4FbjNCBmMweDk7KS4by6nwzC4IzMW1qBJWUXrR0a8dO20H7v9o4ukZSVCPEv4bPwvgMgDFmQ1pcBNAlzFyaW1A0enoc3ki64iTMRH44B36GkYnwe3kCosBr2FYDqxk9iToyFwjOwqi+lhvwdXNOuzL38iEbPanHl5RntRomtMqp9mUydN/aukLrSaEU3lnZ1kwynkHrDhaZZz7CFYnm+AgfFUUuzrnC5otoz3iUtxla3jm6sqTcV8/Oi87c8IwBTd7Dc0uQLEaVup4pm09GuKRHzPtZU9yUJw12qsYWj3RSx7+rlAnV9hG5At2AmFrTDXluS72eUk5YPb7yGO9vwpdcewWn4oQ98nteOd1h/+JC/8siXMF0mCTrfWuPn3vM5/tn+NYzR/N+vfYa/+//9KPmxRjeKizsH0l0Oc9x+wUPjvbfva8C/mUlyzH+6doMra4fc393g4fU9vnn9Mlen+6h5xi/uPslHz75Gs+X4+lcfxc4KiqLjmcde5wu7D4NTaCzv27rB4qLjwx/7Jnu7a2RLx9pDR7TnW7KlyPXMHjPU5w2jexrdKkZ3lLimH13QTjX5kZbnmEExc2gD47tS0aUbSexp/UhHs55RHkq/zhqpV10edRQzC344jB4YzCgnX3SYAqr7S7Jlx/xi5ftNJn2nM+QHywjWlLGyONGKrDZSQ3pUxsWOqn1ijHOS+eyrIEUGyAmrr6xXCAiSOF0nDH7uGf+wYO/aPqZPKZw1UlEpLMq7TmKIQ6x3EGP2oOk0OwfKj9fEVjhhfKLdCok3vm3xs/AzLKQH503Gf7CRoa0heTDd/zTbGUFn73VR3s4OmLzgbVrJplZZap9JAE8AZPT7R3LCDsoI9h62sG/yO0QiJC3F63wlHzxTeTI5hcE8lSqehGNS17RbfV8pWZG4zYesaQ/UYpjYIOZS9hnOl6o/TiW/D9gETs6D/vs0byJeYdCeZB4MYQ+h38VdVuftIZg/zcN52vbOB43puwkfJaxXdD+HVUfahxzDDh46qi9gP4zZYBBHGK7Rr6r6DroqWdPL96j4GasDP7QnDYZ2xEEd78ezfQOXO/0q4lQh7TAIfbbuCaOTbqlbt3+gQ7CYrp5X3dnBCK26TULb0nPE8lZqYHziPaXum/B5AJvhWsFVHVZqvjRYfz9D0EmeJ3FKyaAKq/BwLqX6z8Lg8y7g+F0oOxafc9oJiW1VVdlLLFkfnK+V6NRFFrpDZbkANu+KUloJkHT+vYeSaCFA3zOCzsm1e4Fu/2x8Niqd6Eiq2ifWdJLAYn3SQX7UipvQT+h6IfFartDU2zlmXKA7ubdiZmLco3KO0Z7Er2F9nOFGwfhex3LLy+60luWOxCtmSyk75wqHmcj58qVk7M4vQnnsY/AmvsrLxRm6gXrH4pSj3gGbO7SWiUEvFRcu71G/q6U+a9CdwkzFJZ3NNO7WiG6rY1o1/PqN98KDgunOHFdYLuZLZrenHNxc53+89x7G4wZzvmV5yfDz3/gIf2LzJf7S5a/ypeVFmi1Ht2547JHb7M6mdF7rUW21vKcaVsc6bSuUgIUX25zre9uc3TnkhTcvgXZ868E5Hnr4HvuvbPG7L7xHxL0fPUa30N0dsbQFptWoWca///p7WdgStOOzX34Pula064rDO2u4NpOKLy+WsMxQncKUkuVcPX0MFtzrY9p1JzGghYBDWyiaTUl+yeeW6sCXYNzPaaeK+cWcelNTHhrqbRWZa4lNFPCgHNRbBZM7NctzI9qNkvJQQGExayXZype7VOniMoRUeBAJ4IqMbnsiuo2ZplsfyVyfadlHqb6fty1R0UDrvppRJzHJqizAGlRZeBAp2owy7wqzOWB4QtOsiORHRjEApxDHGCbsGDfmx3qe9/YoaC4GJjLYvvDdYDFKYr+S/cJ5tfbasEObD8T5KixMVUIKDIBbOC4FWSk5UeSD2EP52ZMLfSxgwvylYNT1lV/CZ6lId6x7nZw/uqtXAWYEcWEudfFZDz1+/Vwa53ZFvL8T95MAqyjDBkmSi4ugMwXJp7Gz8WKnAsEU4Pn70DrcGEP2MJzrJLBLya1hTKLrf66+39g3k/k4gNi3mvNXtnc8aIyrnhUUPQBWCTgMzGLaKQcu5Sxh3VY6ab8CsgMwNJTjSbOQ1QBUxjavaigqNVjRRACYDqpgMBPgG+JMorzQqjFY6SQDqn4VXCbGYeWgEyvYYKiGMgf9IIzMWohXPG2VnjCmgyQXD6xie4IrKYI8eiYvuLKBQT3pAB7TLTXSA1dAsn/oS1rBQB+rB8j+gB4U+uejynIIapV3h2kt1V6CbIRnFJ1DSgaGMn+Z17xsjTxbY4Sd9vFJMVvRPzM7LmPZNaWUrzHt2xdKC3rR8xCj6KoCigw3rnCjkuxoQbcxFibHCPOp5g3gvISOoXrQks0arHdPZwuREMqWhnwhoNrmivKow2kpKVhv5Yx3Dc1mjhlnjPakFN3ifI4yiIB3p8QtuoD6ozWTO9BOFFkjJfA2Xrboz0+wJehGMd6V8oLFscLdHMUxcOfOFmaZoQpHeeAY39Tkh1Jj2owcepZx+OY6W2tz7GZHfX0NlTsa5ygPFbpT7N9ZZ34w4sLmIarWFBsNf//WB9AovvLgMm5qyCcdL98/h31QUuxlsF9gjwuemz/Kt9vO54d8rl7n0wePU1Yd+/MxqlMU6w3mqOTmC+dxGsYXZ5ipY35nil03mKnl5Rcv8eMPf5bHHr2NcvDV1x9ifEtjL9eUR4r3P/UKlx/apVqrKQ4Vi0sOlzmcksou9RmYXV+n2VTkc0nsMRXYDEkkyqE4dJIpPdHMLom0zuQ2FHPH2pteekbB+hsd3TTDVIrDa1WsPd6sZ+S1Y3a5kqx6/7mppD/a0oc85FpApw+psIUvIQjUl9YlfKLQ6MaiFw2qkXhJO66iq9qM/XhofbxjYODwIBQF41Esg+kqqSndu1id7O6TYFBIYkzQP43AClxTC7gsClQISwkgITA+QV2hbXvR/+CezKRefQzJWU26S4S3o00Ln6WlCMN3A6ZL7I/Ks977onqJnGCXVXpuiGAy2q2w6E9sdaoBmVYbS+cViV/s279KmPRzlr/sIOkyIUASQkT2671vPbjMTs+e9iB2wCi6MNcmBE04V/guzFve3veaj6sggviuhnI5rv89zAPx4gkeSbHdIDQgudd4zkCehGPSuQcGMZLxwvS/p1hFJReJx7iVY956e8eDxrglq4y0kgswBG7JaoiEZVyNX4zu3ggIEzX8UPnE2FODfQNIHcR2uJXqMNADo9A2/HHZagchWTgk503A7+C8yWCOjycd/BArHPSxnisZcwHkpcxeTGIJLGsy2NNa0CEuMgWmK+0ZSOV4w5w+l1VQF2MBHUNQHIKWw6o+rMgDOIwaaj1AFSOafDZYvSYPPBpcJQkuWWK4Q+B9yqxmvjSiD+yXij2Ja96vYPtyX9r3gczva2JCktL+XJnXc4wuLiMJKvNaAGbuNeZqqSvtQpalZxOxXguvlbJ+qumEtbEOVxZkyw47KXF5RjZrcKNCtBsb2zOnSmEqPxkU4p5WDtqJgEIHmCqjnUpsmy3BVMJc5bNOsqsriYdbnJPn4DLJ0G3WFeY1ySQf7xrqTXmfyzMZ82danIZ8JsLU7bpvgwZyx3gXPvLoq+hGU97KOfOR+5iRiIQ3OyItg4K/8sHnaDpfb/jKEnD8gxc/jm4d5aGj2ldktWJ3MeWT732OcdHSGc3f/sxH6e6NoNY4q8j2cszIioyPAlcZXj04w7fbni5rZqZivVhydjyjyA3l9pJmXnDh0h7dhmXt4UOWdUGxr7GV4wOX3mBza45uFb+2/zSvvnqRn/nQczx59ZboJd6ssNeWvLnc5saDTepjKR9Y7mqKI3Gl2xyqB31WdbemKA8V1YG8V1tKHWoz8hOdlVjPYu5YnlEUM8vyTEG1Z1ns5DRrPsa0UExvG9ppLu95YdG1JDKhlbicl9LfUIp8YWg2CmGxW4PNhXHUjSGfd2gj2deq6aQM5cEcp7X8q3L0oqbbmoB1UsXIOVn4VAUg/RjnItOo6jbK7Ki6kWSwINODkyFsrCTThDhK7yIOtaaD3mNwl7quJWgmqrLox35g/fOszwoONkp7ncioEUsCBpIt2Lo8693ZYUvDeKJpUtHGxQRGfx49HvX7QO/WTtiydPGZzkEh9jMuxIOtwtt3r6OY2vpAFqRepH7+7OfR0+43xkkmSZ1xngpu5nRecvL5UEZoNZnyFHmbsMiP1/ZAN8aq988rgtswz0apJdXjxKCkEYDhKgER/vnvVWCfB+89tDNFlunf9OFNEQT6OSPsp/pGpBJ6g20w764+l9O3PxigMc5tKtLgKWN3oixRChYScNlnHbvhC/AgMP7zq7kQ6DvQSKQHqQMmUuvBAErdyIMkF/p7OQG0klWZWumEKgVS4T7T45KsZRXiWtLVaHh+KcgLW2AC4yLnlI4ZB4oH5cFQJgM87OcScNnHDa6AyxVDo4q8P8/gJ30cYWhD+nvYN2UfA2MQ25AAygD6lCJmUgdAGhYmMVHH1/2MbfUhADGeSTI4I0BM3dfWigs6SPGEfcPzNl2/YPH3bqcj3LgSABuyDTthXJTXZVTWwaiS2LAix5U+YSYsDLRkT9tcwJlaNmiv4WimJTbXmHGGbgxmWvoqLo7R3UX/LqwwouVhg669FuNxy+RuQ7a05EthDY+vCnvbrmVURxbdOCZ3xSU9veHQrcQ7FjPH4jwst4SVzJZyH+VLJaMHUiIPJJ6x3nZ0Wx06txxfs3zulcd44tGbvPeDr3Dz+llG145xmSObaWzh+On3fZaf/9r30Fyf8snHvkhzXPIXH/0MF84dMn/I8thH36TZcDzy6F3KzPCpb32Y2evrbI0XtFsGt9VBZZiMGroNQz7uuPToLm7dUFSGHzz/db7dtm8bvnV0nt3lFOM0nclo9kdkleHOnS0++dTn6EzGu87c5/yT96nuab788qMsXlln+tghe4sxzz5xnU+9+GFe/8JllAN1dUFzXPLg5W0ubh1SrdXU5w3u0SVbj+0L01qo6IbWLZiLDcsLhs4D68ldS7OlqA4suoHja9aHEcg7OXjGSnxq1rMn7USRL5yEHyRxWMudgnzh0MsOZR31mUoYRs+oVfuNgEXjfElATbdeYEaSRKaXLeQZ+ngp4vR+HOlZLQsan+CFZ9XDglZZJ9Vjiizqk7qu6+uv+8nVeXkpVVVxnKq6lUVVJ+NYZZkkxfjQkHC9PkkwyOToeH20t3NJst5A7SC1Q+kCPPwNvQ5l8KqkWwAf6bZq95NruLoZqkGEdqZtCJ+nbSMBTAkoJTCGznnN2OE8EzKw088G7nH/XE6VhIvzUrD99MAseo36fQUc9cA1etiUGpIiDgKQis/L2+6ghHICSPmu4gKoDKAuALYAEEmeW/g7ZQvTG0mBdQSXqt8lztFDMDn4Gd9RwAMkwLHf+rKDjh4bqnDTJ7HE22x/MEBjfL6+U8WVUgBf6eAido6UpUuZPmDoQg7Hh8ulFL98EFcuAZQGl+0gw2z1ZwBYoZ1+ixqRSfzJUNJHxf1OfAfRMAxiMuPJk3an9zxY/Z3U6XpL1/UqKxjOkcbOhGul10g7sFLiPl0FfqvM5Oo1T2MKB8+Jvg2Z7ksH2uT8flIbGL7AMCoNzvaSOyGuJNNSWkz1k4ZKXE9pFrToMqrkc9ezvG3rxWttlOZRPgYSVCwlGKRH9KJG1Q2uaRPg7a/tmRI79vIkuV8kGC/+nWc+mUAMie4sal7LZOvjrmwmgszFceuTFRztupfc8C6rdiog145yumkhOo2NsJpOa7QRMDh6YJjespJRW4BuLGYk8ju6c6LRaAXMFHMBK9o4fw3F8rwja8HmoJVj8WjnJVxALzKcUVw9u0dxqPjmrYt84c1HUAbmdSH1mS8ssBPD333jAyIgDtwzLXqp+O+f/wR3b22htONsfsjOlQP+5OZ1jo9GfOyhV+g2DNvVgmsX7+PmGfluwbnRDNVoukXBjVtnGI8b2mXOu4q3ydL329xl/MSFr3N0POJidUA7z3GF5S8+/Bzb54741Dc/zGa1YKJrFqZAWXjmsdfpLgpYbtucL9++SnYkmc6b1/apjyoArj55h73lhHZ3RDVuaGYlsy9v0p1taa9KSch6W0Ciul+CU9Q7ltEDiUu1hWO5rclaybjOGke9qan2DXpfMt7bqRK9xYXz79uSNdBVWuSVgPGdmqyxdGuFlBA87CSGNVNR4Dub+37lGbrisJHPnOuT25SXyXFePkohjKL2WdUhFtqJbJXT4vZWjR8/TSMxjK0I3juHeB/GI2HK6iYuVJ1zqNGIuKgKAMDL8agsFzveyVhXedF7PKyRf7HmtEcVqa5jEr4S7VFqvwKgSytLhYV0Ok+kgDQm0SSL8oTlE3uRgJXUDqfgMtV5TMFesviXNqvejmqdzIkqASf08efQhys5IsuWzlGD4hspaH0LUNPHPPZazGJDk7nbg7s0eWSYMR1OFv65PuSHFKSGhUZ49onbfpAMk849K9eQm/PPwyXnTNzYAyCXAs8eHAdPVHxG6fOK/SoF/gmwjDQn/btaWY+81faOB42rafrQA74BgxYkcSI7qON38Vi30nEdkZlLA3zTTh+lBHzyDBBXZoOEnATAnQCSfjs1WSdl5+JgdCfczYP9TwOTgb5Or+s7bnTbpx0ybKGjBkO2wnxGgxNAWLpSHRg+b2xW3dBpEPfqKjhdqaVGNTCCqUGG3hUTtij2vfJ7OghX7zfEEIVzpy6MdAUX2Fq/b1yN4/ukNxDBzRWMgzNeXNi3dcBKa79PKGFmDK5pe1d40jeC65o8g6LArgkLqRqDnQQRc5EqIfNlBZVC1TU4X3qtyHDjEjutwFjyeRsZm1DDtzyUGEZbyjvKFobldoYpNbqRKiHKOJY7BfVWjs2ljbbwdaI7RzeVLNrprY5mM2P/XRpT4ePoFPWmZnQPTKVi5RjVKmaXYPr+A4rXS4o7BTZHBL6nBhYZN97cod1w5IcZ2ULTrVmyNyv+wtO/Q9tlqGUGtyrynRpzoeWXP/8JAKqzCzbPHaMPMz77u09zb3edX9x9EtUqnvvWu8gWmlvzde4t1nAZdDstbxxt4ioLyoFRLHbH5KOO35hd4Ntt/+S17+Fbbc65rSMmuuHDD12n2M/4e1/7PraKJcWk4+atMzz/lcfYO5rQPVrzzS8/wh+9/HUO7q4zfSFna31OvlCYiWP39ibve+gNVKu4+9x52taHy7wxZrRe064r1FEOhzm2Eve0zaBbN6y/qhjdlXfUrKtYWaZZFwZRtzDaN3STjNEDMJWAxWLuMKVifLeTd986xncWuFxc0bbMOLqao4wTKSbnRLQ76dtmWtJsyKKm25Bse5cLW9htjkUvsSokXjf3mftZJgljtYBLl2mofQIMSsIyOr/ILgth1r33QHWhTKmSEoONSNGE2uxKa9E89XXdnbUoz1QCvWxPUBPwtscZKe8H9OVBoQcFClnMZXqoXBE8GMHupHHozvXKCat2Nmye7RvERcYFrjoRtxi9M+HwRMYrZDnH97Nqr1cJAW+r0/lyoJ+YMp7xGAb3mQK8qDAS5w3iXDSYg1U/B8t1CeveaJPjXB//JTftzz0Ah6pvb1BB6bGBP3nAEjGWsr/vYdKOW3kWAaypYb8IC4kI6BTDhg5jOwe4JgBLr6DRk5HJfNu7AYfz1Co++A62dzxohAToJcAnlbxJg2SBgVRNYByHsYbETrQqenoaSB0G2DKMqwjt8R06DIq0nWn7V10PKXNJHGg9gjmhq+VOqtfH7LfQrhTsJXIPA3AcntFgRZTcd/q8QvydWxkssQHJ8SHjOLCsoS5rGuydZwOAF0VpVw3TqpFbzWYO36fZi44kWUX1YC1+7xLAaPukGJBkFxNWd3iW0Mn3oWKEB34DsN0KYyShE1kP/rX2hztvyCQTWoLv875NOmlPsuCJ71Ap9NFcjLox6FmDWja9iHdncJMRdB12fQI+aUY5RDPPERlHVXe066LXqOe1TMh5r7uojWV8X0SfF+cKyYxFGMBupMg9UNCdI68dzZqmOHQsd3RkCqe3JMnCFrJfeeToxorxfUNWQ95IkoqycPS1Ldp1h71agxKNR32Ykc8V0xsS7/iHnv0a2VKRzTWmhP/hm99HmRtGu6CvLLiyfoA6yH0VFUWeWQ7urjG+PGPxaAeKmJzy+GO3MSPHT1z4Ou/buoEyUNwtuLb5AKUcqtVkDaCgW+Y8f/0hvt32kcvXud1uoRT8h9eeZCOb89Mf/Sxox4N6wiObD6jua/K5E3C8X/J/+Z4vsmem5BsN9abiuC5pNxzqTEO20fDV1x5m68IR8yuO6aihPFCYsWOUd/KMGmEXzcixuOAwI0exlzG/CIuLjnZdcf6991BGwLtuYLkDxcxKNrw3MbpVmJFCN/K+zEjL9/RJKd1YdBvXbnYiyZSJMkA3LVDGkdUGm4k8kzIC/LJFFxcitIb8uBERb2NRjZHKRcE93HaA8/XUfYJZ4wGpj2uUWESFq/KeYWs9Ix9iBT1Tp5KkGPCi+i5ZHHYCFgWsZNB2MftabHEWbYkKHoxgB7SWyT3L+gXjat37uOB1ve0J7Ql2d9XeKuULB6zYttTWpjHlgcFMmbwAFFNSwZ87dSkDMXFjNVFldS4IoVxxXknntmjz+zjtMIf1cYThXC6CuNVQrfjclMytQXA8hlytzN8nPG8B8HtbG7FBnCdVBJ9D1y6D8w49cilgY1gWN74X1Z8qzG/hXsM5kjanCihRYDy9ifRc8eMEgKp014CoXXgAfKfbHwjQCMMXAMOXLTtAXAH4jpmKc/dyAj0Q7GMcPeMVajyH9xcHOHHQBTo4rFAiKA3sZFpiUBrad7xVgOqN2wBU+sETB2ESBBzOkybtJA+kPyZ9LGlyx2ntCt8F98Pq59F9c4qRW233yhaz/sALa5t+Re7PLSyeOWXgJdtpq9s87+MlU+O5CjRT11HQXlQqOd4Pukzj2qY36uE9BGCYhUnFTzSRPfUTX5H7+CnvIvZAM7hIVOaD6I0RMBomlarsXfepyDiedVEK5fUdVdsJs6gQSZ1p5dsn9X3RPqasbqOciSTICLMYMltNpTGjPMqeALg8WZhl8m9yW8oM2jKTqi9HlsXZkm6kwCKi3zNxX1b7FjPSEupV0ocDIXFyoz3L7IIkWrQTRVY7ql1o1yQOcu0LuQAhLWBo9MCxuAjtpuHfv/A0zRnDx97zotjOVjGflTTr4FC8ebjF6MKc9lxHN4HjBxOYdFydHlCWHdmRpio6nn78TV7ePctkY8n/cnSFLzz3JN9z7RUefe9N/vj6m2QHmUjhTJ2Ayb2Mq5d3T/bHlc06xV475dHxfT7w8Ot88eAR/l833kdxqDl6c41ZV7L1zAMWjxje9cyb6A7eU7S8Oj/L95y7zs67d7F3xR1tOplMlIXj1zYY3VE8u3mDbgzFoaL98hqLhw22cFS7AqyLA8kmL2aOtcvHvOvyHXDw4HNnGe1buqmjOrBsvGawpWJ2SVEdtNhC4k+dJzi6iYDH8rCTii6ZTLZZbVEOmvWMaq8hP6ipz1RktRGdxpEkDozu11JFqG4xlV+kBOCEB6HW4sqsl9ixFjqDnY4GiWjd2XWfnJZ5hrFI7E3i3dmYCgjUPtzDS+FEz1NZ9soHcZEpsl2xFGhVCuPvF5xBQBvlF44B9Pk4+L7yE73XILVdASgGoBqOX/WEhC0uHE8hLFKviNa99wEGi/MB+XDa3BAvpXoSwO8ftRNT2+efb8gfCO0cuL19G0Ko1VAqjphdnTKJqd7wqnRevIZXjIg2GKJd7D0+SY5B4qEZhCyd+qxXsIRfxPes6Sq7St/fwjzlvGSarzQzCDmI13ODH+kWZZRC+1RSzSW5XngeA0DobA/I02upU+bNt9je8aAxAL0Yowjx90HmlgtAzAwBZaCoA6Wv+w6WyvHExJd4Xd2vxJLBFbdAmSdMkhxIHET+IqSuhSB2SmzLykoyrtjoj4cT53PO9cYjGeSnCniHfQL7pxKG9bQBlhq3AFpToxLOna5a48oeDw5Vz6SFe0tBaWIkBvcbQNpp7VFqGB+UtiOcMxwTMh0DMxAWhsFABIOU6q6FeqA6G4Jda/sYR9P1GY1+YSIuL+PdzJn/XkfA7azpQxwKH7+VyOW4og/MD7GFaKniAghQBKlNvZRJKmZW+4k28wkFMbu87dA+cQDrXYpAu1lKfeHGohdtrAiTLXvxct0aL9Sd001yVGdp1zJUKzqL7bpCG4ctFKYSV2Y+k+SA+UUY3+3QnSTBOC2ubGVBG2Ei55flu2ZToY24T2cXM/KFk6oxR4puDNnC6zHmoJea333jcdzZhmJniVLwkadeQuHIXq34Sxe/xh9/+CuMrszQkw7XamZdSX1U4TI43h/ztduXuLx1wGJ/xMt7Z2k2Ha/Nd3j5lUv83ZvP0k0cZmrRtaI4VpjzLfcXU77d9up8h0ne8MLRRb7y0iPM6hJrFJPHDykvLliagj935iX+5CNf5IX7F7j42C6fWW5RZR2f+9KTHLcVWa1wEwPLDHevJJ9L316ed/zOa0+gHCzPC3jb2phTzGQBe/SY9YsIWFxyLF5Z5/WvXaI+b2jXFFbD+J4wvu00o50odKuYXSj6bHUFurZUe5Z2KtqdOGjXMvKlweYKmyuqfZFdWl4YS2WYUYYtRZ4pW3bYIhPtz3MTbCFj1lR9GU2JedSoxvRzqvc6BPe0sHGafH/ey904hI2cLYQ9V+Bnf9Rs6c/Z9ZOpVqhRJdqEbecFwTOYjgUkDmpQJyXuQkWXU+MEXVxwuraVRWS4XhrDlti1flGblCVM7VvYnPOA0Z20sdEboXu1iBCKY+2QeAjzl07mjKRNqfzOEODQ2/iwzwCIqWQxGz7q7Xo/fwZwFbxZ/ZwXCZoAklJvYKKGsjrPBZYxSg/5/VPmLibMwACkhbjBQdUXF55L6EOsxH8S53RhJlOQHICsxwZRTm04D8c5OkleSb2HJ5BkwBCrcVLhuYfY+3Bt7wmLbvGked/J9o4HjSnQW3VNAydWPirL+pVHYOzSFQnh875jBM2pPhusv3b8GZmnfhAE+ZwIRFeo/oGrOInBXHWrDwW/5fco2+I/S5nFKEEQGLswwHQaG5JcGyJgU37FG+JAWR2ocCIhJuy3mkXXM5++rXl2+nkS0DwQ4w73FIBZ+tmgAW74U6noEo5/B0MYYk+6bmisw/MKzGTqqrCmF/MOz7sqxeDkec9GOiufeZe7CoH7AaDKwf27M/21YlB2CBxPmNpYDcPHdwnbJ+DW1TXdxkgMT+EZDq1Fh/FwDki2qZQMlPfsfMnEIKhspqWvymEw3vWojMVVeYxv7LyeXjBUNhcZHpcpiUtzoI2LmbfLM1J3WrdO5HZKjW6tuFFHwjLNL0r8YnnkJXlyYSGLacPRU5Zq32Eqx/y8DK1urBi/95D6fIdTivLaMbqTuDw7tqhO8diZXdarBn2Y8Zk3HqOpC5otx9/53Y/yP7/6furXp5xbP0bljjf3tsjnimyn5ufe8zmma0tuvbbDw5fv80OXvoYrHPfubmJzqBcFk5uKYj8jWyjqs4bsTsGPXPgC327bO5zy5nyT96zfZu3CjHbpq+uYjPremI1yyd+58SyFMthWM85afvf1x5m1Jd3YcXw8wlYOZxXZtOXDT71Mc8bQbnfkR5rx5hJTOS6cO+D4EcfhzXUfCuAopy3FkaNbt4PSjiq36BZcrjh+VFzS7VTiUMsDCRkY37VktSwCFudyuomi3VCM7ta4TFEedhxfKrGVlkWFA1toqr2G0W6Lbh26EUayXStxmZI+cCTJVqbKyJadZ70rkcexFrNesbw08WDQ9OElgJmU0tcDawi++hGoIkfNl7jJWIChFxQf2ICQCBfGs+sBlsT9yhjF14HH66cSwoCCJ6Lw4z7LkvKAiTRW2yZ2h6HdCrYoXZivgLRoL1Lvh0lsWLoIDv/atgedwY6HOD3vrnbWRk9GsPUpSDst4TLaq1UguSoNp4TNPSnY7ee1JEE1/L2q3BGIHTltovWoetsTkl3DfkMyyBE9f/5VDiq4qWQ+9YC+F/ROBm1suhp8llavgfDcXHKwB5o+5jYC3VXyJ7Y1EBfJO08fUnA7q+TzlAxJQ6PShp/4/Tvf3vGgcbAloCmi94Q1CsXU+1R6+lVDwlBFqjy4DpWKQtt9EG7CZibHRQ3DpAOk14sxg3lOcFunwDZeb3DepDOFwNxk5RpjStIBmLoCTgOICShJnx0QhWKjazUBmicki0iMxyrDt3rutPRfMIDpAAiALfytks+dI5TJA3rjvHrtpP19wPnKPgGcpQM2yf47Na4oPC/lwZoHcq6u+3YN3BQq6p65ZZ2cR/ftyr32o87iYkOCzX2fSZlm5XXrmgZX5pIRXeQwnVDsHgswrDthDoPRzTTKGO9O1tiJJCG4UipXuEyjmpZs3tJNcpqdMeWRHGvGuUikWEe3VqK6MEFbunGOsqL9ly2929wKs5g1lnwuVUfy2nH4Xks5syzOZthcUx5b2rXezdxsCPg0IyXxjLVj+vmCyasZyoqY9/SmiyUCj1/cZHRTrt+8uobuwJQOPdPocceLd87x42e/icsgH3WoowxbOto1x2MX7tNuGTqbUYw6XJPxMx96ju6g4udf+RD162tk52refPUc//pbH0R1CkrL+Uv7oCXusl3347fVuMs1/+L++/l22+bagv0HUz578xpPbdxCdQq7X7J8c4orHdYp7I0xv3b/GYq9jDePN9Gl5ej6htTJfpBjc1hbX5K/VrGwBXqpqe7muBzcyxOypWKUtahCqu7w2EKe6/2K2SOW6r4mG3fkc0c3UUy/lVOfcTTrCr2UeFPrIyzKQ8PinMQuthNFcSTi36qD/NhxdG1EPu8kROFOy/FVha0ylCP2tXq7QM9qyvtzlHWScV37ODmlUHVHPmvFJe01RKWeugjIj18/9OPfRikapxX5/kzqWQN2bSzn8+UIXSbC9cwWvds42IggzaJVXLw6h4BCrfsklOCNcQEs+bHaNN4WhexpvwjuOhiV/hxBv0/1C91w7vB37hnItBrW6iI6uDlDIwMYTbxm0XamHpwArpPYRrFDJt6/yAkl9tyHFg30HgNIhaHtXA2HSrY4ByTzW9h693g4lYpVsdKcgjBvxdAsP99GPccQJuYBV2ATUzY19UqFuMDes6gSHKWGP1N8Fa4bYkAVERfGsDYV/g4Hhjne9e8nnmt1HukZwNje8O8EeqVnt8N1nOv38++lfycRoAzvMcyl38H2BwM0roKY8BAVPWOTdqTVw72kSgRazvWdKDl3DAp2PUg7Ubg9+anCYIwfJ+cNICVZRcXYj6TDudXOFxjJEFuTDiyG1zmRYDNYoSTnTTtTArxPgM50n9RorRx7ItN6deCkTOVpq2voywGmRitqJaq+DcEVo/oBdML42RWwmjCGkQlI44pSkB01Gl3/vqwlJshE97UduthjsLkfwM7FWCdnfeB+YCZ1Pzn1GNEzA+EeMo3qOnFfLxtxPecZarHs7zF53qqTzGY3Kr0bWzTvcE5El0GA3liYm3x/IZU8OslU1bV3rdQtttDkMwHJZlwIkBxnUhEmvDoHTimpDrLoRCpFKUZvZKhOYubqTU03lrHoMoVuhGnsxkokWWqpLuO0klfSOdqpo9mQMoShLN7ykiFfgrLQXOwoDxVuvUPtlnzw8hv8/CsfYnwXzKxgtCuNUxstr10/jzKKC6NDzJ2Kaq3mF778PYy2F5Q3c/Irc9FddOImt4WjGrfc3VvnTz/0Bc68+wG6UeQPzVHTDveg5GB/wrfbqrxDdRrXKZ578V3ohYxZd64Bq7hx/SzdmuV4XuEu1dT3x1Rly5/70O+Qn1vK85oaZg/GrD29z9KWUnt76jBnWpyCdsNy/dZZXCtM6PK4RHUi7p3NNc0ZS/FGyfyyJBPNL8Pa6xIeML4jSUxZLd273s4wIwkRUH7uyRoolgI4J7c7TJVJ3GyhWb9uUcbRTTOadY0ZZZRHBrMxkn+jDFtKOEUEeCNh53Rj6DZH2ErjymGCSH2m8iL0uVQyCnGLvl+qppPM6s5AWUjjj+Y9a++cxDM2wbUt48D3WCJLk6ph5EVvK5Chq/JcsqSVQgS+PbsU7MqyEWAbbJGPVe4ZPh8SUpZDdYawKEwYP/HI5LFNAzsaPDmpW3nF6xNtUOL1USG8xoPEyHwpibV2XZ/EEQsJhOt6F3c41yC0Km3f6py1wq6d6mGDSJyknkJgwGIO8gDSOZ3kdQ7mSQYgsydwHCkeizkK4ZorrGL8OcBf4eTDa/aJVaH9oQBImP89WAwMY3i9K+8v5kyowYfyb/BFRJnJs1sBm2nD0370bTblTmSEvDO2w8NDNjc3+X7+JLkqvv0B392+u313++723e2723e3725/ALfOtfw2/5KDgwM2Njbecr8/GEzjd7fvbt/dvrt9d/vu9t3tu9t3t/9DW/7td/mPfNMZKsuTmIg+BkFleiVeMPkeInUf3bkxqywpTxTcwT5GLaWzQ8nCE65eFc6zQo+H75O4k3iO2Ejvasx9OTsf5Nu72RNXSpYlMkAquiUGFW7aVpIe3ibesK+O07vAB20NP9O4l5Vje+HW5BmsPhfn+tgef/yp+4eYwtUEnHD8Sr1VSTQhPq9B5ZdwzjwX11CMgUzilQIXHwLlje1Fe61FFYU8x+BSMol7KUgqBFdA+j14FxTxGYaMTZH/6GWfVFn4xCX/ftP6r2XRZ6c7J/FduYa6lfPlmWRNFzlO61hRA2PFPe0D352P5VTeXWenI5E86QxmfUQ2b1meGzHarWN9aTMSwe7ioMbd20Wd28FWYlaWOwXKQL60LM9klMeWfG4xle97GehGkmLyhdRrnj3k2HwZ6nVNfc5S7GspcTeC8shhCkX3aE31rRJbiFvUlKAbWFyUuMZyH7Y/uMu9b54FB0++7w2ef/MyoPjPH/8c//pzH0U/vGA5K8kKg+kyxlOJK/3Ll57nb73+frp5Qbmn+aMf+QIv1xf4T9du8N/deZpnNm/yvuoe+1bzzz73cZSFh997i5dun2dra85aWbP75R3qbbCl6CH+7Puei0PiH/4/L8Xff/yv3gLgK82E37rxbvL7BVys6doMZxX5fsaVJ+7yxuvncLnYoGqrprk/gvWOn732RX5p9wnu3ttEFZZ3X7jDN9+4RHEg7vpuInGl5T4sz0FWg6lA11AeShu6iaLdtJR7mq0n9jj8+rYPD5Djs0aqwuhGUe07EVC30Gwq0XtsJe60T3DSTO4ZTCmJM+Whw2US29psiiRRMTN0Y00+l6zpblqQLXzcohah+GwpLltXZDF2VtcdrhLXrFo20UUsCV6gF3Wsmx5DR0BE7TuDnVbow7nYzKoQAfu6gfEI1Xk5qsVSQjyCuzYN64iJbH7eMF5nERfd1oOqVen497ZJKsgEWS03tKMhtCW0P45n25c2TdyVrm2jmkJ0O6c2KobuIH/n+TAZJ5zH2FPDsmL8YIhTTGx/X7giEb0O95O6h4MbPJ2f0rhKLQoRUV0kTENhXvPz70C7OP09xDdm/fEndJX93D0I/wpubIbu8OH8Jf/1GKCPkzy1hnXqAY74wsQP+4QbH0IRknpWcIE84+TdrbSnn3eJWAYcJ+dKlXy/2kAYPAwAZ2AlmuG07Z3PNKo+FiIErYbElShfowB61fdeHV736fypRqM/Zzpw+nOlHbrPLA6dzqVAC3phatkpfudSQxK+S88RgEcCxmKyTgCxSXBxMD6DgZMMQv/LIO4inGcQI7L6/eqAS+P9/DOMul7p8WnyTvqMQsYynJSWSNugws/VdoXntmK4HH2MkPLGPLQ3BfY+aSOU5hsAy3BcqD0bBG6DYTSGtARhjGOJ8ZfJdT2IF6FuESDGuUSD0ZcODMYgBrr72BdFn3mfPIMgxUPdSh8PenZhkZHGOflkFxf7o4P5UkSUk0xsgGzW4DJFteclezorWnrGSgnAiUyaZlxgRhlHD5dUB4ZiYSkOaspji+pAv3aLdqzIZx3lQSuSO52jODbYAjZfhK6UesfFRoMy0Gw7ujXfRzLQNyuR7Wmh3lTkc4fLBaT94fd+jfkVx52Xz9JNBTR97dWrnDt7RH6k+c3dp2k3rQAv5aR0noXlgzHdmxM+9dKHMG3Gn3nXc7Trji8eP8Ibx1v8vTtPc3x3yhcfXGWsCnbNlPaMoVtztC5jbWPJ+fERf2brZZpHWhEKP9BsXDzm222/ffNJRqMWmztQjrObx7z34k26Ncv1ezvY0rF+Zo4rHObNscjG7Akw33tpm/Hmkj/+8FfYyY9RraI529Ge6XClRZ+tadcUyiBxoQsFWuJElYVupyM/FpD54NVtmg2HGUm7qj1QHZQHAiCXOwIEg45mN5KSf6NdGxOWJvcM3Uij/PqmGyvyhcVWmmJmyRpLs56RLaX/uEz7WFlLNy1AK3RjRIuxlD6oG+M1GV3M1nfj0sc2irbo8myF8wklblRKfGMuiS+q7aAzvm61gE6XaV9NScv3Wke1AFlIJ4kbXr1AElQ6qRKjkAS1LIMs9wkQ/qYVQ7WFMNGrkFCSxHQPMqVVb5u17s8V7BL07Uq3AAJjvGKy6JbRKj/aNpYolThoX+J0NcsZxMapAHaS75PPojJJ2NLYyxDDnQK4NJEnxCIGQOrb0Vc988/LpkDNLxISkWugF/Eu8h7cQn+uBIgOwv5WwaXqk0vDY4tC4em8zFvnKZyIcUwev7Nu0LY0FnQgGxfefTxfMmf7dg7n8GRfwnzu0WIKGOO+yTEDlJs2+q23dzxoPJF95BjoEQYGLAam+kHcA8dhJ0qrqQwV3onH94ymOjnwIII3pdSg4koaWBySZMJKr5fzSfQmTwQcy8+wMhzoUPp9opp8ADPhuv77waprdfUVgGiikRWOiWAl7ucG+5w4Z5op7augxAGvdQ/kgqEK9xFWqYE1TM7tQnZ1muAS2t51yTW9UYolCv0+mVSNIPcrfJ18vgKcXdf1+yUgMJXQiXVoQ8WYvM9cDosFZy2uqSVL068+o0HJciKz0YWMyTCRKLn1NAnHWmmiHa7unfLgsMyhbiKwtRNhYFAIcCxyqAqp8JJ7yZ3OYKaVyOvUPks1U6AV2XGNbkWqRzd90otuLRuvCXOXLTrqsyOyhaXe0hx+4iHyRhilINOzPAvdJEMbyBdG7Lp16FdGNDuW81f2GN+RZBhbShJKuyaAUBmYXVaYUqFyy+/ef5z8yE8uuST1ZEvF/stbmDMdsxtTsrnGrXWc2z7GTCybW3OuXrkvQMdoylHLv3j+o7jKcue1Mzy7dYP69TWKM0uae2MAntu/xtbmHDftsE7x1OZtXrx3nl+6/27ymyUug5/62Gf5C+e/wb88eIS326xTWKvIzy/h5ogHRxO+tX+OM2ePyAqDyi07oxk4+OmPfha30WGmlp9/5YOoq0uaO2N+/XMf4tMvPElWK37uXV/g7NYxKnNYI0xtPleYqcUWMla6NUe7pviBh75OtoBsKYLo628KM4gT3cb6rGV5FrIzNdNbhnwuwuXjXYvLweSKxXlNvhRGud7QNBsqsobFTJjl4qChOGrRtaU8MuhWFrSmyjBVRrtZxexqM85Fi1EpzKTwlV785N+0IjJvnYjTe2A2vjXrzc+yiYs9tWyk74dqKb60p54thSDINM50uLaTBZb2bGDT9vqx/nqqKATwZZlPVvNyO11HrAUcx7zzGdd+P63imnOQ6RqKBCg1VGgIxECwoyuJFH2N6QSoDbwxK+DN2wM10OZ1/TGpfYM+GTDY/ADy4rE9IRCOc8Yk1W/6f7GSWJjLwtyoe+A0IFVS0OdtsAq2NhA/AcR5lY2gLBHm9kjmuBWmUPW6ynIs8V4icxr2CfNxOH9k99TguPCcBvbZEbO2Zb8evMb79XYcVj2crGyrwC65VvxeERK5ZE4YsskrF08+P3Gxb7u940EjrAA/+WSwokhB5EBuwPXsY8oyxuNMP/hD+n3fifw5ksy7ftVk+84HfYZ1HLz+FIFJ9Ku+PsV/WL7w5P2e4mpIWbmwBemVKDO0UhEgGoPe5XKavE46uCM7mdYuhZNZ1Onq8zR2MXG/xuephtdYZT1VAJvWDPdRqwMmAZTBeMYVv+uBX8xiTJiBwGQGg5Nqonl9Q3lnWZ9B7fDAr5PqElqJiyoY36KkZxt6Yx6zqUNFHWMTCYlkQeDZUdcZkSXJ857BVj5T2lhx261P4j253LMshZfYAWEYFw1BKLzbqITpWQQtSCWC3kphxyXNVokth/2t3hY5nmzesjhfojvH4lyO0+JG7krRb2zWNNo4igOpQa1bqLdyupFifkFKyuVHmoOvbmMzhTaSsYyFcl9x9Khk9569uk+75sj2ctSrY8xUgGw20zRbYLY7Lj15j/JWzvTKDHumpbhTcP/OBuVmzezNNd64s0OzY/jhx77ET175KtWFBXqu+eFnP8/HR/tcffIOXZfx+GO3+IXXPshfOP8NjhYVzHM+sf4Se+0Elpr7D9axhYDZX/jq9/CpFz/Mn9y8vjocB5trMkZFR5Ub2k0BUx/aeYP/+uw3MYucTz7+Ba6/dh5dWv7O73yU7F5BPunI7xc8vL5Hfm7Jxz70DS4+ssuFJ+7z/771DLu3N9ncmJPfKEFDtnSUuxnvefwGulGgHe5SzW+8+Czu2pJmUyatxRlNeehodizlA025rykOFdlrI0ypxax5/FXtObJW2Ixqz7I4k2ELxWhXdB1He1JpxeaKbq2g3iqZXyykzKAfSlkr41w3luPLIpWkjJPqReEB5RmqtVILvSzEFBhxVytrRWKqNeK6NlY0GgGX5wIW80y+A1kkedbQhYk9z6EqUY3PHA5yMKq3VbIwbgei0sGeSHiK13XNM5SWcatC5RjvcnY+1KOXrEnsU1jIpovrYLdCNnawT8HjgDcXaThPUGsIZMSqnUzPG+agVcAIvVs+uKgTRjKt4JIupCOIDOBP93NAZA8dK3MFiRs8CYOCePwAWKpE2zDY43B+D+ZOSNGFtgVmMX0m6dSQiH0PdCRTFpH+/LFNgy2Zr0hAayJAPgCHK0BzeB43/D62wQ3f6WDzzyNIN8kN+fkzCb1KbzzMrd8hfnzHg8ZUNymsLIHTO4QLAyKAOHnJg1T/AE7CC/eTexr/seoOjy7hZIAEg3QC0KbHhp+rotihvf6ztARUClJJBtcJILlKw6dANAVcoY15wsSmADuA2FPYxFg5IQCilDFMr7cakwNDN0wAeqFtwTidtgVB7Mgi0g8KpXx9aDM8R2An05V+KruTlilE+dhHL4kTXNmpO6vzLiyte7kOD/RcYElj2SbPKBc5ajyWz2O4gWcl81yupTWqLLxxDuBUyg+G96TqUJbM9xkt4toBFKv5UhhHFdyAhTB+1oJnEMlz0avrLPmh6EzacYFZr6SOdWMwZYauO4qDhmzWimsRRLz5QUe9nXP80IjyyGJKTb50TO50VIcWU6ko6+O0aC/qTqq5mFLEpat9RzEX+RccNFuOekOEuk0F+dwxuq+pDh17L2+jjQA1U0Kx0ZBfnWNLh103/KGrL/Lm62fRj82ZLUtsk9FsW/L1lu7uCNUqnrh8B4BPHzzOp771Yeo7Y3auHvC5o0f5W5//KOfKI95/7k3eONrCWfhCvcZfeeRLTM/O+Sdf+15ee/ESW+eOQQlrly0UWMgPMuy3scZ/6vHPc3xjDYD1rTnsFnzt8BL/w92nyCctv/DV70E5eNfOPeodK/GNdyp++qOfRSvHU9t3+Eh1xI9sv8Kdo3XGRYsrHMfXNwB4+Klb1NvwUx//LC+8cgVzriU/0nTLHN2CvTXCFY7ZZYkJXZ6F/EhczE7jAb1jfslL77xnxvyiuKpnl8TN7TIY7Vl056g3NdXuktmljOWOpjxs0Y2lmyjGuxI3FbQ8ba7Jj2qyxrDxeiNAsu4iM6gbg62kUowZSynMUNUoAES1bHF5hhkLQFSd6A6qVkClajpUIwDWBVvgF3RKCbhkWfdjONivshSRfgLGUxGUqcIDUv+Z8iULVVmKm1pnAjKD7mEII0kZsxBfmJIIKesXmMzwfbC3KXtIclyeQxr+Ej5P2MDBFr7TejjHpOTAKaLeSuv+vtI5Iy58+7lhKFOTxAKmzCVhXuxBHhA9bcJImpOAPXin0hAviIAvXscOCY44R6sAZkmYvh7ApSxiqsHcV2UbNieQJ/09+3NHXc0+pG3wDsLiof8Q6OX7wnn6hUK6b4I2Axh0dkBoRUDomcjIeqbzdWQ+v/32jgeNsq0WVScCwt6Nm7zwwTvtAV8EkK6PvwigLa24kqL8ng5PKO+4yulXRLEWtXUnAV5sdxpv2bOCKTsY6fxVNnJ1tXkKAB3ErqxcN1ZXCAM3YbIiDZ9eMwWKq20IbT1NJDsMlJhMkjB5oWO/lRFMXdjO9cAv2aLLySbAMgSIh3OG1bxDjL3pAVja/vgcoGceQ/t8ElIKbl0As3nmY2UcKcPpmlZ00toO2lYeb+YD//PCa3pJ2cAY76hVBJDOIb/7EAfXdr6KhTxHp+U9SjUXEU3GOa+xqFCLBltK1Qy9bGOykOqEpcwWHS7X2DJDW4ercqkeo5WwmID15eGUgfE9SW4ojjrymcUWWnQWc+imInRsM2E4u0p5d6a4nV1GZB+bDTw7JskwgLCOGTRrinZDSveVx06SPVqNe2mCrRz6KKNUBjY62hsT3IHEjyoL+g2p18zlmlce7PC+y29inFzHlo7jpuRHtl/hqfdc57OvX+Oru1cwTpM9KPj3Lz7Fb84usLg98QkvsHcwJTvW2ALa8x2ucNizLfrbWOPfOXgCu2nYqJYc35/ichhlHbPr63BP2qgs1Dbn8oU9smV/vhffvMhX713mv/2t7wGgnRUsv7qBahXlkaN4bIZxmvxszb86fAiXO6qqJZ87zm4fYyuHLRyukHvoJsB6hz3fUO84iRfNBGzlx3Ld+e0p2UJhS3ySi6NZ18zPS1/PGocZF2S1ryleZr7Si2cVW4tyTkpRtn5sNTJWu0kek2Ei62gc3SSXqjJa9zXTPbuvjEFZS76/RDUtripotkdxvDqlZJ/OimZiWFg6cFUpwFKrPgEtMFjOh9042y/2A5PWtr4SUwjN8ZN10xDj0JSScZplcVwONA6hX4ymYDFUeQkehgSMxW3FoyU36n92iXB5tGl2uF8KQGFAUpymwjew68EOn8ZgpkA1YRoHXqLwUSiOoZMKVwlwVkpB4rGKsePI64mJgt4tHZ5HSuwEkfAAcFfd1IO4zAAUE45CmtyLigdwP3hG4RlaF/+l9xjv2bPLg7yCxK18AjSvejfjz4ABNH1jw/y8Ojeq/kDfZ4aezv7fCVD+FtsfCNCokgHUlyZyJ17+ALQFoKhXakon5wnHp2WRlBKQEUBldCeH1U+M50io/nSFVuT9Si8FhINB54YATU4Uzxf3C/cedkmNU9JBhnGbCUBLzjOotJKudl0SSJ2C4tQIpCBvBThKpl8qSsuQBQz3aG2f8bwSXB7PmwaEnxg8fh9n+/3yXEprpcYoPgd64xfcVYOFR1x2Slu0jxVVelgWMLTHsxMBgMesumQgD1bzIw9o/H24ppFH1hlU0/YTWMj6DIZRq54BGfnJtZCJWLUSqO+qIk7SKCXgUSEu3aOFJBLkGe1GKezfKI+gEJCM11Em7koPQlWYUxQUxy2jvQZbaI6u5rhcsdwR1gnnKA9FpFt1PvO580CjlMe+3JZsXJcpss7hEpnV5ZbqPTUZmMpRrYvq9OIcXH7fHcwyl2QO7RhfnPObrz6N2svZePRAYv7e/XlwCpuB7hSPbj2gKju+8uZD8ppzi9Nwbf0B/+2tZ3j+zhWuXbyPfVDyU1e+ghk7Hnv4Di8ensNp+CPXXuDK03dQ2lEeQnexRR9muMJx7czuyb61sj04nqAzy839TWHt1juuTXdxF2qUAb3ZcOHaLq/fPMvNu1s0Fzu6TcPf/sxH+a/f/busj2tMpfj7d57m0vk9qmeO+OQzzzG/5Dg+GPPGixewt0dc/+Yl1NiwOKpo1xTzr2wwvq1Qmy3ZkSTDKAtKOUyd85HHXkE3wuq2a4r1dx9Qn7WM78v7ypaO6gEsLkis6WjPUZ8B3ToOnvD1zrWEGrTrBabUzC5mZLUsJsw4o50W1OfGMSvaaUWzXUrd88wvLltDV2npv9qz1IHd76wsoor+enSG8v5cPg+L2SyTcIyy6Bn8qoxjKI7fOAC1ZFYDZDlKZz7+uO2/N13vNYoLQMSlm+e9V6uufQhOiKFzvV0MyTTBrkZmMSya1dDurFZ1wduxUCQgAVLxnKtzSGqfi6JPRkkBnB5eJ7Je4VzpgjicL9hzELAcYguTBM1Bcma6+E7Pk/zu2i4hSvo5tVclSeZdVs4bT9VXegvVZvrr+EN8UmEEkY4kl6D3IvZtTQawWgGaoT+4tJRhApZVAIjO94UwByTEzArZEo+PGDC9X3/PBGH1gG+StvSuyf5YFeYv/9HbhLyl2x8I0Cidxgwp8JTtSgZUmvE8jJ3oX2rqauzZx+RaSScNW8o4rjJ9Axd4Qqu/xc3EnynTeUK+xw0Zy3RgnagVnWfDldNpINW9xXcwAHjOuh6QDoygGx4fjZI3FHnWxwqGDrwK+qLxoV8prbZ7dQvyE/FBMASUPgmnvy/P3jn/XUjwScdddGv7bGkHgY2Ihi+4JJz1CwGbZECuGgUBsq5tiZmaYdXa9FI+cmq/APG1s511wnhon+gSWNJRJdI6IGXYHCJNkufi3suFyQlZ4t3GCFfKJNutV9Q7oRScRndWQKa16GWHqXKKo4Zs3vmKMBntpO9rNtd0k5x82TF+4BkdDeWBr2/tIGsdxdyStQI4bKmo9g1OQXnoqLc1ra8OY0tHvoB20+ByATGLc77yilN090bYyzXZQvHq7g7VrsaMHHqu+f6db1Ld15QHMPvmJu2G5VPf/Aib548wIyd1l61mUjSgHfOmQD/IOX/ugK/fuIxSDuYZb37zAtlC8RuzC2yeP+LuYo1H1vf42fc9xxf3H+b66+dRs4y//EeeQ2cWtdOAcjh3Sp9c2aajhvPrR9hG4xTog5zLxR5aO6qHZ3SLghv3ttFLRT7pqG7k/NwTn8debPgndz7E/oMp7boj05b3rt3EOcUvvPpBLl/YY3JTwfmabAFmJO1RRvHHP/A5cJA/PcM0Ga4Q9lZfWXBte5dyT/OFbz4mC4naoS7UHLyyierEHZ0vpWyiNhJfOr4rQFt1isU5zfSmE5axkio92cJgSpjekj5lS3m/xXFLedQJs9gaysNGFiCdQbU2xvqN9lthtTsbF0KxPGewAVrJ537cq5gpLANYOW9DRqUfK/5ced5nFQeb5FxcuPXSKUS3rFJScu9EbLm13stgBDiFxWGwM9CHtKRAMdjMaIt00p7E7qVqDtF+eBvkk3Di4jSAvNVFcfhMKSl/uMpmBoCYEiqr9tiTG2mIkXMuJiimFVCCe1l+T0rapXNxuE4aIkQyn/n7HCRYhvPFOTgwdOmcHUBvP4enbnE5bXIfjj6cLV57qIhywi2dBcaPAb5QIckyOafwDKvkUZgbw7N2w2ussr+rc2mcnxNgGX6PQPxku+Mc6kOZvtM6L+940JhmQkWWMJQlCqxV2mnCcXoI5ILbehUIpvvLT5+JrejZxACmSDrMsJH9ucJqNfkutGHQzmBQwjXT1Wik821ymp71DFlhsfOlZaBCUkoEd/5nauDS6wSAFO5jVVMyXT2utG+g4ZXecyy3lQyOFNjFTGJOsn+JqyGweoPNBtdU/24H8TxpWUBrpbRXXMn5Ewdj7MGnKgrUaNTHZZqun3wIiw0lsU7hWYb2WgtKR7eCCoxJVQwDuauqB6ZeEsd5V5obV142h8jcqk4AmKsKYWGcX9EaS7c5jtqLFLm49o5qAchlTj5vqe7NJTEgz3CZklJu4xJXyIQf6lJT5CggX8g9VXsizaNry/JMSbYQ13Z1IGykMsJSzS5qKRtYKbqJwhQKU2lMIfIwupFa1YePSXxdMXMoI98tzkNxLADITCx/9tnfed9+SAABAABJREFUY1K1dGsO1ymabS/v0yp+49Mfwj2ypNkWd/fG1pynr9xk9toGaqul2VC8evscD46n5AcZVW5495Nvsns05c88/hzzPcmW7nY6HnnvLb566yq5sizqggvFAZ9dbjJvCv7zpz6LrSz/dP+aMHXHBXSazn17E7toCv6LMy8y3VhSbi9xGfzaZz5Ce1jyExe/JvGWVmHWLOujGvWuOQvX8uy5m2yP5qhOsXHpiIOjMf/uzpPsH0ywTcatG2eYX3bYg5L6nMVNO1hqJmcW/Nqd9zK/6sgzQ7GX4SaGahd4dcxLty4AUj6w2VTYQrK7203L+La8w8WORl9Z0E4l3MDlshCY3LVUe47FWY2pFOWBuKW7tYx2KuO3m+bynq24o9WylcVBlQtTvd8I6HMOW+bYcUk3krhGOymFTTRWfiph1lXtwU9nJSkmqAUUWdRxFLsiiWFhBledidnPrpWFkeva3naEsR7GvjU4a+TcWSbhG56FUnnRe4oyf800FCXYq2DLQly0oo+nDgyZE/1XQo3swCCthhAF+xVsY+LZ6BfYiQ1MAeEqO5duK/v0SXfeBnlpsIF+I35+XAXS6fyWXieRjUt1F1PCYKCP6HowF9nLLCE8fHsGgNXPLZFljBnzpr+mUvRMYsIOxHkpOVdCLq3eY9/eFbALPQiNoI4eg9D/3c8N4YMEGIZ3Ga41KEFI35c8AxtZRE9q9BdPv1fDufY72N7xoJHAzJzoyMPvB9T3CnsY9kszo0+4mtOOlwS79vEa/lCtBh0upb1Dp1yNS1iVBzqRxJNsJ2JIEqCXBva6kPwRD/RfxZV61oOocJ7UzXyawVl1Ka/u510KMZkmrpIcJ9jIdJ903xh7qE5eC3pDNFjF9/cN9AHmaZt9HOJgUyRB5yuAOTEszlrcsu4TcIIwuFIimwOymvPsQciKjvIXyDsW15mXXKpb0JlfpXc96FMqinErz/5JIo8wK66u5Wchq1xJAugI9XpRimzWYKclet6KwHFVxEnQAd1EBIPtuEAvG6/H6NDzmmazQDcWtWwwG2PMSJ5lFiR3MtHNc7mimMlnZiR1iAGKeYduLfkCdCtgI585EffOFPUZRbumWD7WkS8EKNqdlqyx5Ica3cHm+SN0B+bGGNUp/vWDZzi6N8UVlo3NBcWhRrcKl4tg+IW1I/JjRftYg9aWh6v78sozixk7VG75Lx/6HOWVOYf7E64fn8E5xW/uPSUTgAHXaZ4Zv4HOLT9+9lsUheFD1TGf232Yn3noy2zrlnI349ZL53jfmZtUuxo9Mtw83ODbbabTHNqO5vUp61VNubOk3rEwsrzY5qxnCwA2N+fs311nOS95uV3nS288LDGWteLg3hqj13PMg5IPXbkO2lHtKbKR1Pkerddc2DriY4+9xOy4wtweU93XHL6+gZlI7Ge9rTCP1Oil8myvotx3tBMFuwWju5pmG7qRJPuUz48kNrSWmFSbyaRYHRqyJbgMiYVdShJKvpDYR13LmC2PTGTAbaHRrcGWAg6dZ3R006GMJV8aCYVwThJelJIYRQV2lMeFkWpaXCFyUarpoGnRi0bAY55h10a4opDxqUXQ3gW9xzyL4EyVBW5c+s/C93m0O6rpZKzlPl5RedFuLWPfmaEE2arkWh9T6HpwGsBjiLcMxQYUvT1eDcsJW5TIQVi/ruvtt1Lihoah3UvjFKMhSs6d2vs0BCkFnslcdWosvt831WqMiSgpAZNca3W+dqfMX3H+jrGGCamSgMFV9mygUhKeV/oM4v3Rv5MVYNuTRy4mwQ62FXJJ3hkR9J5g/EjaEsIdVrAHkUVMQat/Doo+vODtFgKhLeF8CZP6+9ne8aAxajGldHXyUk7rnDGuUeE7Re8CjqsF6F3ZbugiPg3wxfMHtjN0cl/NZQAE05ednDNK8MQVabIKSffxW5S9ybMTHUhlJ41GcC845ySgO918XJ87DciFz9Pzpc8betdz2NK4xf4B9cemgzTc70CE258r08PM5fD8Bytv30ZjYgzP4Pn686s0FjFMFmGFn1ZxCfFLOtGDDO0LUj1Z3scxBWBnBSiKCLAaXFOF/cO7Cc82TFZd5+N4fHsAZyXrmtlcwF+RCyOplEyarndv27WRgE2g3RqRHcwBJ1qNdRsnMNUZ8uMmVtZwYdLSIrEzurckWwjDqBuDLRSmzDClz65XIqejOsmMtYWcJ2v8BJ9JfCMWzEjAiTICLmwGykJ1YJm+kDO7DMWhorhRcPiItMNUMHt1g8U5cVPrRtF9cZ2PPv4SOJi/uUa2dHCp5sPvfpniiWNmXcnZp+9zZeOA/YMJv3H7KdoNi92tmNwGFhmXs4zF3oife/fnOD4cgYKj+QiXOXQrrNj15ix2mfGbsws0Tc5XmzH1sbgw/7uvf4If+9h/oFuzfP7NR2jXHKOq5fHt+3y7zVk/ERjYe3OT5VGFbhU6s/zPL3+AL9+9SjbuOF5UPHr1Ls4qruaH0k21xeaO4kBjS4XuFM/vXQYH/+UnfoeLG4eSEX1UsewKPvvNJ9CLDKcdkycP6aaObKEY3wMu1Jjjgmoftj66S7vppYtax2jPx5/WMlHp1segelf1aM/QTkRGaXE2I18KYHeZ8kkslsndlvLA4DJFeWTIWks30jRbJfm8BWPRnfWSO4ZmS7L1VWswhQbj0MdLn7iFZwyRZJo8w0xL7Po4jl2ngGUj8bx1K8k3R0tZsIX4sc4nv2gtWdRh6wxqUYuMVZdUaHJO4hvD2PXgK8YB+rHf2xIl4DTYEefd3oEVCtqw0po+dCXYPCOeiGinILqGpfP4xXzIyvY2LcqPBTvSNL1tjYDVz11m1W7S30tc5K+QEeF3k9h9X/EmLKTT+UElNj0mqqTgM9xHnN/8JcI5YRBbGEPHAhOZKpicAqpjMksy16bJMClx1I/L8Iz9vTqGyTgp6UECal1yvSxoQCfn8r+EuMYT2cx4UKhCOBsRHAYwOwCgoV2Ovp+lxIqc0J8/fS4pcD5FYeUttnc8aISAysMqw3fgECgKfQdN6ePANLq+SkxkAgfnG3aYQcCs6+MI+4yuJNt6QHfraDBc6i4NHdsPwhPSNinIWmX4wvU7w4nVULKFwOJBwHHUKvMPycfgDABr+n3aniQ+Z6D7mBoFxcm4xShUK+dVqVYiDDOqw2ZdD0ZXywsGo+Jjn4RFdUPQGNpN0BZTvUHVvlpL0vYQtBxdCWkgcVydBuDpYwyzLBErBxXApguGUPVgUClQQQTX9sY7jXXSSbwMygf0K1Rde7FjJ8yDN6aqbtDHC5EcKTJ0Y32lDJ+NnWfoo0Xfdmshl0laYh+RsoHWibSO73+2FPCXtTbq7YlLsQeKWWPBQjvRtFNFN84wpaI8tn3yiwWXK8xIMb5nOX5IYXOY3BJw0pyxjB7A5K4lq6Fblwm38SRevaX47GuPM96o0Y0Alex6xXM3H6XtMvYOptyfT5m1JeW4gzsVZI4ff/Z3WO4I4/mpb30YNTG8aYStfOzMfcpCsmJ/5iOf5dz5A+7UG2QLxdIWnF2f8Wy5IJ8pjl2LXm/51QfPUkxbJm9oXAb/zaXnubtcf8txFzfl+AcvfxwzduhaoRuFHVnYK9CNQmWO6ajBznIeG9/jyYt3+JX77+fxS3e5cWOH7EyDmTjaqaPbNJydzMApvjB/mPvfOEtWK3St2H8wFWZvYlBGsbc/Zby+pJs4TAHdrGByQ9FswJ0Xz3L+7IG8nw5sDtWBwxawuOjIWiQb2iIu6kzeqfLi78sdr884Dm5mEZjPGoPLJRu7XcvRrSNfWJZnK+pzY6xfANpxIX3Hy0Vly04Y9AAIK18es25lwWIs2bztmXVnJXxiVPaxjSDJMH4x5LSI2DtjZVHWtH21p7g4c32MYLAVgZV0SCyk1rLItt4+OBtd3cq70uWmpB1SiUbYyejGDmFN3quhvASYqiqxvUWIwSQBAKH/qCSkJ+lXg3KluredMUZSQVGczLgNQDCZDwbsKP3cF4s9pH9DnyswYOgSUsMTJjERNGEZoz0NzzsAQ93b0NM8auGafax/75IObRrE9ifza/p3BGTh8QblE8/upUxkLAMIvZ5x+l5c0NUdQq0U3A68mmEOibfv6BOo4tH9ewkHBUwTvl65B0LCTbJb30wBrW+HEdLtHQ8aozC36//u6d6+U/V6hmpwbNxSoJb8TN3FEXSdGAAqspVpFZaY+g49U5d06nCd1eywqCMJYrC8cRgIo6aDKh2sAQymq5r03GGQpqzhacymG/a8gesAeiOTriYHDJ87eR4vSBury6yCynSVnDyfwe9pzI/2zJ+jl8QZAM8eUKK0AC2bnMOYnnFVQHRRq1hZIl4rgEPrY5OCXIZKVnBaSUyUF/Z2HohH8dquEwCokEkvy0SGx68m47MI7IcPMHeJ2z8uLiZjifuqClxVemkRubes9rWmq0Jcd3mG2Z7ixlINBqWw/rmYcUG+vyCft+Km7hyLyxO5ndZ4ORZFN5J+3Y0ysqURl7QSAIeSOEbdInWq56LlpwyUx17bb12jOocpBTTltcOWkLVQHGrml72b1MHormJ8B5SRmMZ226A6RdPkuBzqsxZbwLWzu9SLEmcUXZsx/8om7V5Ft2ZZW1/wjfoCtnS47Y6fe/LzXNo84F/97vdyeDTm5XvnODOe80evPc/feuP9fHTjVZ5dexPdKh4f3eHBbMKBbciWir//te/DHhfsX9+knRWYsaI6t+BXDh5lo1zy7bat9QXvvnib4vyS7lzLn3jqc2Sl4cxDBwKojeLowYT/5PEX+O1bT/Ktmxc5ur3GXjMWkHy3gs0Wtdnyhx/6Fn908xvkM8U3Xr5Ku+4kKahVVLuasw/v4zpNt24o9jMeXt+jmCnypcSAtuuihTm+b7l/cwszEgBoSiXJTIdSYSdbWvbfDeVMxlW9odGtZFnnc8f69Y7qyNKNFc1U4ld1Y+jGOfmsE3d0I2y4Mo7RboNuHNmiRdUd7ZrUNHee9VKdHbBpqjVR7Fu0RPUgNEU1Ha6qMBtjAZpeXoosw2Xefe1F7xmVYYD3GqpeIkfluTCQYcGGk/FrTJ9MY01MdBEhfm+jigIIQv5DGxXYJYmflMs7E6pMIZI+VekXjqo/3lqJmR6AvEQwPGUko91K7GRqg1MXtbV9PDvJMek8kpAZg7km8T4NZNtSUJayj/RzY9R79OdJ5W2iF28FVKaFDcKcGlzarktiFVdUQdL7i7GOZmWOGYC+8NGK2Hf4TiVkkqMH3wGAubCPOnHuNPGmB3Eh5jIbJsOo5H0mcYqDhJ50fjix+TnrRIiVfHci8ebbbO940Bg7WZDASQNP46qiXykMJHSCWzrpuLE0UZYNWMR4vQEjSDJYSIBrDy5jAkTiGhmAzZWOFljSE0k4LkmwCcAu/Ey3NPlk9Xor9xLvJ9UwDPuf1kFXjUjXrax2kn1SMLrynVrNaHZvcV9hnyI/KUURDGhqCNOA8fB+ApAM7yjPhqsxJYkuUR4jgM34rL0bKMZD4ScRHc8p7q1cXNDax0CFZ+ABbIiPdQpc0wobCTGxyhlhWZRC3NsjLzqceSkShwTih+uGyhdhlb1YRlY2uqOdaD5iJCsa6yJozGY1el6jl17Sx0qcossUo/uSdGDKjMxP/OF5dSPvntKKfN6iOku7pulGivG9RpguLYksunXMz0kVEYlXg2Zd2mtz/1OLNuPojmZx0YkuYCMC1Ga74/yFA773oZfZuHiEqYX5pLRkS0frNO+9eBOc4l0791hcgB9695dQRnG8N+FsfoTLHcXNgv/l6Ao3drf4Ix/7MllhcA5u3DnDM+WSH7/yHA7Y7db5wQ9+gUp1KO34H1//GN3Y8clnnuP8pX10C6oyqA6W+yOsU9z85vm3Ffd+qc24MD7ilf2z1AcVLHL+t7vvpSo7Hry5iV03mCYDq/jM7jUubR6yfeaY/+TdX+fgjQ3syPGXP/R7Asxzy43lGf4/L3wfZuywE0l+saXDnmlpti13b24hacSKbmp55etX6MYOU0FxZili6wsJGSgO5R3kS9CebTSV6GouzmaM7kgfLeYixN6NNZM7Ft3Ku7S58qLtUBw5bKHJaosZ57gMjq/mPjlK6lDns1Z0QCcFWSN9SrcWl2m69RLrYxVlLEtcLcaiglJBYFicw01FpzE7rqXPjUoPCJNFb7C93r2NPsky4Zl6qdvcRVDpRhXMlzJ2U7uehuMEIBZjFv1023Vxwld53sc9p3YIImgaAAIPUCIwXFWqCEygtSdjuVfBUVjIB3AX9CFTYiSSG/6zbBhTr1JbnB6XgL74GUTt2phDkGjpDgCc6+P3Bx66ABa9dF5I6uzDxtJ5d2Xcpc/Bg7uBtzFhJ08wf47eQxbedXyUfiIJ+wWiQKXfk55w8C5Wk2pCQk6sxR3yIBxDAJkeFvo+K+84fBk+HpAw6Um+c+D4jgeNaTr+gCZfKfweAZwjAsfwd1yVBOo9ATKpxE78LpwzkYOIyvZdN1xByUkSV6oeXivEEiZgNoKqcGz4ftVIhN9XV49KDSuuJMesSu+oPB+2kzB4knOkoO60LcTXrDKLA72sHkANDE0waEU+mBSA3igHsd6kXipKJfqKqmc9tRoyhGHygB5EKj0ce13bMxXW9IAxjYEK8Y868wCul9kJ8TYxocUzGNFwhc+1hjphIf37CELeKmjE+QQX5/AJAGGiUp7x1L68WoFaNqiuw5U+2aXMZeJrDWbNxz/WDViLrXL0sqPdqkSGqcgh18Lo5Jp8YchqI5OssWS1ZGir1sQYsXzp458UIvXjV7G2VJJN3VhG9zvqM0okWzrQnWRKm0oxvW1wWo5pNiFvHPOLEstY7muqA8fsio9XqzV37m3w3O1HqbucYi9DAcXdnPqRjvtfOstLB2ep1mrmpuTa1bv8ry+/n50Lh+jK8Bt3n0K1mvqM5T9bv0E57vjC0SPYWY5qNMrBL7z2Qe6ZCQ/lC+426/zaVz/I9eYsj2zs4YzCbhoObMOPnnmRbuKoqk5i52rFjdfP8mMf+Q9vK+79rsLwwo1LtPOC/FjjSssHz7zJH955ke0rB+jDjCcv3eFPv/uzZNpy62CDd6/f5itHV7l87T5qbPjt+VXWJ0v+8tUv86CeoCcCplWjYZ7zyac/R363QLeKfKaY3ND89JOf4dqVe5RHjvLskmzpsDfGtBvSl+otGQPd2FFf6gSEr3vx9VZhCygWDu1DDJbbmuNrNh43P5+jjKM8slIj3IEtNPW2fJ7PjVTwqaTWdDfNYviDxMgqAZH+0ZmRd1v7xVK3Xgl4K31pwaaLCzU3qjBVoomqkASZcYVa1qimEaawbsSroVWv1RgXjE6AZACLwSYUkiGtmk5UE/Ks12MMIS0q2H5v07NMFp5hMR3c0MYm9ekZTvqhHYoeyEWPhe5tTxAPD+M/lDENiS8xESaXalip9ybY8NQGr8QixuQK327Xdv0cF+eBbHDevgLbafMRvd0Nbt5UczEFhomdXpWkG0jnhZ+KKOYdtgHA9WA1yu+l980QCEqkkOr/CO0Jc3OKKZzsky44VomYCH6T8zGYsxlcI4D1SF6tspyhPG3qMpcz+Hb7d0Yi87dqh1z8b9CGb7e940FjlLqJKzYIGVwhNiEKdXuNwBRo9vEQIb5DXoZLO0x4eQkDl4pyR6pdhdgIHUFguppzCViI8Rs2WVGppHOsgrtVsLW6D/SD87TYhVVACITM4RhUnV4jABR/fXl+ZnAucg9QQiB1MD4wiF1Mq8v090RvlBS+MkO4D29Ei6SUVXiWabKMWTHIIbkltHHFKPQglUQTMh2AoPKiN8zheYRYltBXinxYDSbPkrggzyo7h6pKn7ii+0sYI58XhU+SCoYw8wsOhyqLGAPlfPmyIOrtnBNWxWdyu6BTqby8iHW4cQVakR8s4mQa76kzFHtLTJXjygzVWXQjz141RhJbOiOxYcaSLcRV1q55ZtQ4srojn3W4ScX8QkF5aMBCXltmF4TJzRbCaJWHMuayWkS/26lmtAvd+xdkS0W9oSmOFMWxo5sKQCkOJGN4fFuhrMIazXJvRDFzuCtLmh2D2ssxY8VPXvkqDsXtF89RZh2qMhy9sInOpYTc+tkZ1XrNL+4+STMruH9rE9UqfuTdn+Hhy/fRuwVj3fD3vvx93HjxPOcffcDclOw3Y7K9HNcq/sHrH+VTL32Y6uyCus5ZXLZktcJODL+2/xSNO1mZKN2KA83PvftzXH7yLpfP7vO7bzzOr7/xXmZtiT7b8MToNr966wM016f8uavP8Zkbj3F+dMzN187CYU6lWn5g+xt8erHDrCmwxwX3D6fotZZss+Hnv/ER2jVHeW6BHTmWO/B3vvK93P7CeeaXHc29EcePQHe2lYSanMg4ZkuJqTRjxWhX7F11INI63UiGRtYIqEf5BUCucKFQUiUVcrLGYiqNbhzOk/Vrb7SoLvQZi8vFZV3MWrKlxZYZtvLC9Z0wl8oI85jPfTJM00mIhNa4AI6almze9GNSaezaOInl06B0dAXGrTNiszKfFNN1uFElY7HIeldk9ByJLXVtcBf7uaYUt7TYGuftV9t7QhJ3LjgpMJAyhYm7dqgy4X83Ro4JdlS/xTTuwUewvy5UikntY7BTqe1N7XGqmxhK+aXemlVSAnr7mQJSz2Suhl6ltnaQiJLMo4PkGU6C0aA4MWBk/dydnq/XbNRDIIrM3zERNiFowndxvywB0Z5MkmSXnmBadfcOSSvpJwOZn/hMXA96E2wR32X4wDkC49gn71p/7hXPpkq+i0DYJf9UnP6+mwjjt4EYZ3yQPrnE2PjCT+g0roCYNP5QzptQxyurtRhrsLLKOfH3oIPrIQCVRsjPwEq5XlLgNOp/sIVYy2CElBpkL8e4QTgJOJPB0xuYPuYSiPGH/QmTlVQwZCZxByX7Ediz0Ia0IkwYROF6XgstGr/0ZwrsrIUqzFwekOqVa6eByuk+IXstDKigjaa90QzuBOPjEUEmkqC7mBiQwJb2XcfFGEQcuLqWlW7TCNNR1/Ls8kJsgRcadkUu5/BJNLLIyfoszkrK4enZUp5nIXV5qYRddIWIJQsbU8SMS9V28b24qvA6jBrVdr5MYMb8ygRtLKqRScWGzOgyQxuHHZeglLA5QDcthGEEbKlZnB/hcs3ibCFC3GdzRnuGbqwpDx2LcznVkcQyth9cktWOZkuAhzKSWNG9MSFfOK/PCOjeXdpe6OjWLPUZ+GPv+gr5/RxXOBaPGLom5/zOIWbdMH3skL95/QO0dUa7abh+tM2z52+y/p59zFFBd3OM1paNUU0Q4a7OLPmvnvk9/sk3P8aD5QSz3fG1xVXyc0v0pSV/9szL3Jxvsv/KFma74+fe/XmundmlupvRNDlZZqnuZuga8v2czmWUKmGkT9nabcPffO0DvL57hjuH61SThrw0jPKOi+uHHNoxW5MF2sAvXf8on3z8C7zytSvYHLYuH/Ll3Sv8yhsf4hPjB7i7FflmgzsscAcFWkl/19OWP3/pS1QPwFbiMp5fcpR7WmSPjjXOKmwl76I+Y6m3oTp0qL2c9mrD8cNO3MbIMMsX4qbOFxbdwviGRjdQHnYUR45mTQvIn1lsrsgXkgRjcz/hZVK/Whn53uYaW2khn2qD7izdWPYtD8TNHCVo2g6zLosdZZzoNxZaxlpVyEKtleQZ1XWoZSsJMCH8JNO91mkAixFgWZHocYgLPLBsievZtS2DJDjv3lNZBnVLkNCKbFq0N7oHU2XZu6YTOyKJiEVvU4InIpwn2KZwXOvjIgPD7+2OC3HVA7CadLzwnRpef6AZCf1iPAV04bsV+x4ZvBBjGoBlWMyn8fEkc08AVaugMp7XkyuuDxkL1w/VXFIR9sH9rBAu8TqO4Zzl32UqvXfCdWxMn5/gAWO47x589UBsQMYEzEh/H30WuO876XM9sSVg3SUYo1+vrFx35Vwh5j0hQfp9TwH/b7G940FjYKr6FQdJB/X7uJB5Ff50/cokHchRVd5rTZ3CWvXK7/2+kUkcsJ4rAyQFoOGc4fhUPPsEI3cKuE2OH6wKk79jZ03bn/7TSebz6j/og9JPuY/IZp4GPouCsOqM146MXH7ysxDkHY1Pn0jU33QAdb4ecxgYNjF2KgBD+okHetd2iFcMMYqKYUain2TC4JLSYLYfvPRtiC4nn3gifcCXEQxGOmaGa5HgsKY3tmsTcSmHcd/5Ulo6xAApiafyfc2Nqz6OMc9xozLWxQ1ZpMa78cRFXcj9dAY7KiSrOhcXNJmmmInsCVZYHT1vUECzkdONs8j2KM/kqNaSL+Ses9qS1RLfls/le906TKWFcdTQrklcXDfWdFZLNvW+AMbjayLzki8cppAYT2Wk+kg+Fz1HfZhR7mvYavmN20/hcqgmDTubM9Qs48npHYoHOYsXNvjTV79AcacgW2imRctD5S7717dwuZNYP6v5vs2XOG5KfujaV6kXBf/TCx/HlZZMW0ajhj+2dpPvPfsqXZvxSqfZqhaYyuE6zd+58SxaOZptC3sF1sr7rc9azMSy7HL27Ip81cqWHWum4wZ9kKHulTR7I/4fD32Jg9mYu7M1/sOL7+H+rU2aix3Znrgd23XLn37PZzl6eRP9ZsXapObnX/0gP/aB3+GPXfwaxc4SHPzU1a+gJxKDOVI5i3OgWkW1B9lc8cMf+4wkKBUOpcH64ZUtFGbTsDyjGO2C2i0hc6B7YH98FZoNx2InExe0gflVJ/0pkySn8tDilPQBlCTQuBxZlBiJhVyeKage1NK/lcJMC7qxL31pElvmx7rqZHw7JfZBGMpO5HmsLNLCuHaVZPvH6kh5JvGIATQE9s3HHco4yEWiRykZM8FDoRJvi/PzQGiaP7/z41jAyMrE33bRaxBtG/ThM962SUKH12ANpVOVv0aoMhNinoOcWliwhp/GRqFx2TFZ2AavUQRwibcGTjKXKQBM30VcVPf7naoTGLwxAZQnMYon7HqYMwKrGU6VeJBSJZJ4nnit8Bz6+46Jhml4GfJ6YuW2xC0e5qcTruEAMlM8kbRJ/uwTSwZxjzaoZBBBXtR4dPRJjS6Jq/Tz1aDkIMj7is9ZJR/3v/cX7g/r4yFTwB+e3YoL/G22dz5o9NtqBvKgWsvqYKDvYAMNK/8zdNrVkoRAT1/7waCSztxrL+l+AIXNDjv2CUHTFYA2OEcycCLlrZN2hEGV0vopcAsdPl2lBZbPnyMAoQg0U5ZvhaVMgXK6wutXxf3zGZTPcivPIwWOyrcvGNPIGPo25PkQ/MV3mlwrTA6x9F/oDP4FWRvdDD1QDM/ZDftAVcmATuMatYbJWCYy65LMQOdXwbafMJyTGCMTqlAkQr6zhWR4Krm/XgPUXxc/WWR+YmpFAJk8g9kCtWhie1RrcONKtBWNFe05BTTCwui6kyzoQuRLVN1SHDUxHtHl4R1YqgcN+cJwfHWEshZdG58FayJ7lC2Eic2W1gs7W6a3lpgCdGtQFsoDh6mEZaq+XtFOFbYULcStF0TsO+j/mZFk9JpSJk5TKgE0FeI2bQSw1Mclx1/fxJaWzWyOurKkXXP80+sfobw2w6533L+/zpeOH0Z1wqw9ce0mdZfxq6+/nz9z4Yt87uBRfuRRSWqZTBsujo+Ylg0//8oH+fcvPsXFzUNeqc/xvesv43LHdHNBnlleun+OTz71ObKlws1ykakxiiceus16WbOtS95uc9sds2Up2oyXluQLxW8eX+ZnH/0iTZ3zocdeRXfw8cuv8MPvf45/efAIamz41S98DDPxrGFT8MELb7CtS379cx+i2R8xvjDnK80EO8+xVvPzz38P1x66iyst80uO7HzNv/zSxzAjR7UHKEe+kOdbHkJ5K6fdMN5NDaNbGfPzkiWtOpjegMltsCVUh1LxpzjQLM9k4oL2k54tFO1E06xJIkw+t3STXPQ8jbCXTkuIg7ixFc2mxowy8oXBjHJsmZEd1xJuAVBkFA9mwjT6RLBs0UplJBBG3eszRnvivO5oWGD5EBs3KoXNL6XGuvKg05UF+BhI1XoQ2fpx5MeeUkQwqYoCVOq1cr2NV0pqwDsnHgogVoSJ9somRsn19ioYqQAsyzKCtcgmhjj3YDNDWEoAOVGyJwA4kthu2z+jVDPQuZOFEAb2nuHfCROLMb0cTTjXCtM40MU1Jrqiw/MKEjYn2UA/J7lezibqKGeJy9clNj2NYQxzeEq2JMxfnDPDk4/7rSqZhDaYuF8Ae6n3MgWPcX4J85l3D4eqYT1YXFlwSEdLrh1iFXuGM9auDguW+Czp5zh/nt473S80VpNg32p7x4PG1TqT8fO0EzFchZwAevSA6oQWohoykpHFZAhIg9D2wK18CmMYq8uc2mnoAUQ4x0oZpXAPA/YwBZ4pWF11yadga4UtDCu9tN5q1BEMWxpzEgZ72CdtU7qFGqyr54I4GGS/4UowGtBQ6SSuNpNVebymP4cjcUerwYVUJok2QV+NMPDC+cOeeeZBYegPLooDqzyXRBb/jJ01Pk5WMixVEPKN80JYduJdXl3/DIO2po/VUaW4o12Z48ZlkhXu+ozSIADuJzI3Kr2buosTgisLyUINNa2tg9YIYGylcodqpB1Oe+ZGKTlHK0kwk7sdGIcrNNo48RZOveTOpKBdU+jWYgt/b1Z0/ZZnSqlPbBBQuHA06wIe622JdZtdyqSe8ZFlcU4yc9X5Gt0pnzADTkO3ZulmBcW9HDNyjO5mdBPQlcWgaRY5Zs1S3s5Z3Jpw9cw+ADdv7mAvNKw9dMS3rl/mxy99nvJ2wS+9+jH252PuduvsvrLNYl7y8t5Zzo5mVDcLdAf/1fbLPH/9Ia5mmmy9xTnFX7r4Ndwi45/sPYaZOJ54+BYuk1jAV/Z2OG4qXmgL3m47t3EMwPiRYz5+9hWcgm8+OM8X6jXUcc4XX76GmVq+fniJX/36R2hcxpXtfT747Ev83977O+hrc37moS/zlReu8Yu7T2I9Rp0/GPO+co5TMB41qLWOSd6AkqQidX1EeegYbdSSFd1qqdLjtYiz2pEfZXQjRbvmaLYd6vKSdk0SYeotkeJRFkyhqPY7xvctowcGW4psU7OuWW5LjWqn5N2ZSuIPXS7JLssdsQ/V/doDSRjfa/Ge9Ri/uLwwkUoxXgVAmPMMV3ovUWBktMZOqn78Z8IuuiJHz2tJ7JpUotXoXM/elZ5197qMka1HxUWz8gvJvpCDT3wJMchZJgxS1w0T5UIWdagUExbJYRFrkwWvtTHuWWxdYsecW5HcSeyYs0PFihgm5L1cwb4H5jBsYUEcQGrqVoYEXCbESsq0pUA1uM4TsqB3ByekQkrUpGTIgBTprxM8btFDFuIjAw4MnjGt+32Ujy/MdGQMBwUjVJ8kEoW+VzOuQ/vDNZL2pIktca6PYWZCTKSg8sR8FC9A715P5vJVLNI/y/C6nSxYXDiJ/OyvpwfX6PvM8D3G2M/vgsawuSHSTzpnKvYdJQAGFPgw9mCw0oHhIEqYwNT1m4pbq6I4AQZDrEY6oCIYi1R9v4KLCvmB2vYrtCgMG8BUGJxwctCvxJUM7gF6V+wKkHPOxYE7eAYrmdgn3N4r4DR+vsrwhhjHWMmAHuClxwQj2iXGM1wj1pX170kRk0KCO3gQ25glbt8sWVWnST0xptL07yucy5roMnZd108K0gC/wiXGk7ikZqvrOilX1nUSwzQq+9Jkfv6TVavEXbmmkUoV89oH7CdMsXO4qhJDNfJi38smCiKrtNRg7hc7ga1UoNoOl2u6zRFmWmFHeRI2IAk37fYIlIg2q7ZDLVqOL5fYXGM8LsoPlthM6gtLrWFwuTBMunPkc9FfDG7Q8X1LvoTyQFHMLPnM0WwIM5UtxQU5+npJu2lZ7ogrGwXlA41uFMWjMxywvGDgQo2bZ/zaK+9jej0jO5bM6NGlOXdeOIeuFa6wZLdL/sK5F3C549/PHqO91JJXHY9v3+ffvvY0tnT8Zw9/hbLoeFBPqC+3/OX3/x4HtqHaqgF4ducmFydHfOpbH0ZPOm7c28aWjhfvn8OORJOyKAzL19ZY2LdnGu/e3KIsOpZtzu88/zTVgcPtlXyoOuYjT7xMcWYJRnGwO8VWjk+sv8h/sfUq1xc7/Mq9D7A4rPib1z/A1sMHzJpSyi5uNIy2l/z2XO57Pi9x84xvvHhVuvfI0VzyAOOVMT/5ic/y5KU7ALznvddZXHTw9IKsEY3NfK4oD0TvspuIrmO+kHfZebazm2S0E0U3kTjDrHWMHhgmd+XddxPF8oxkTyvnJFkq06y93lKfKbEjn1k969C1gKyQNa1a61lAi5mW/eKqNSII3hkBoiNxR7tM4UYldjqSkAw/lu2oRC+FUVdhIVr7ZLCmQ3UW1ba+elQ+TFbIJc4xLuTyrJeM8TYlaAGqohDprBCbGIW7xS4MwpCCPQ3AEgSkRtmuFQYxjPlwPIgHJ8t7QBg8GiHuOlWWCOdJ54FB3GMyL6Q2Nm1vugUbnSY9hk0FKZ/epaq0lmfps5hPkC/h0ERdY5BYGuxdGh6GnyeTc8Q4w84k8jW6J0RS4B2vk1Znk/9ibKPqpfhUWfbAWNED5OAVCwynv4+ooGF7prL3ViYKLIFccAnIjdf3bYpcQ19VJs6N0hj+f+z9WbRlyVXfC/8iVrO705+TfVeVVVmVVaUqValU6gBZGJAQCDCdLeDqfsZYwMVGljz84gf7wcNj+OE+mM7GDGwwF2RzjbEtECCwML26KlXfV1ZmZd+cPP05u1lNxPcwI2LF2pnqvm/44ep6jXHynNx7NbG6Gf/5n3P+Z3MC/nhTWCUC2z5PszUXf5nl6x80qkgstMUCeu+heUin5WbiB9hf1NtRuDGI8nkJ03kX4aVsDhaOH3IuIireRlVrLQPjgZz3dGIW0R/PG67pXsp+vRg8RtconHfcEcC/2NPnbm3Tp3qqxVSLEbwdwPb/TzRkGbGmWGDX/Etgohc89oZ9nqMft09s9wycB3b+GvkxeSMYQik+XOz/r9pgbNpIB10xBwjTrGEFwjk69tG9nFIEE4WenIROYDP9HuNcSDfxBM890WKo3MQUBIu1mzB9i8E0EVDpmXE3DumAIcUv2fpQ1vPFTElCPd+HLCUpDJOFDFU296TuOtknXx1uLOVCj3K5RzoW/b3uulwXM8jls1SRFDDcn2DyJIQhx8sa5S7h8IiEqdM9S+9GzXg5IR0LoCxnhMHStWW8oAi0kxLdxrpvMV3D3m5XciB3EuoiId3TJHuK8QqYrlz/qpYOLXa24huOn4GjIri9sLzL+e1F5mdGVKOUQ/km2bbmxx78DAt6TJbU3NyZAQV/NjzGr5x9B92s5A92j/Ds6hH25dt878kvYncy0m7FoYMb/I1jT5GvaayCTlrx/W/9DGP75ZlGEstomJNow4GTNxnfXYKBP9o9xONXT/De/S+S7WioFWjLa5MD/KeNk5zqX2d0foZkT3N0YZO5bIKxCr2ecmJ+gxOzG7ynv8qbT71BmtfsO7CFTSBbT9ArE9LVlLqjGO+v+dk3HuHci4ep+pZXnz5BuqsprvaYLJvQArI8VpBfyMBI0dJkEaqBpbsq96zuNCLgyiBi7R1pb2iVCINXPdH6NIminBFmT3IZwSrR+VTGUndTbCptCetOirKWfLOAVMTpTUeqnOtuiq4d8+SKt+p+TrIzbuyMz3EEqbYuShemdnai1xEHqyhDOobyzmZsH6rKmQELNhLlj53bWjQfQ8FiVbbBWGg9KoRFnAIkKTa1gD+l5P02prFNId4f2dI4OuMLZhIdFbN4kzQ1D/lzDw5/ZMO/FOMUM5/QFDq6+cI6W9Iq0vG2Ni7CdM5zI4Fjwnw1XURqb9fNLAJ4gYHzIXe3/5ila9oA2yaHMYCsePsIMPpjTM+h1gE1N8/EY7sl/c3Nmb66O9ZulF1FFdVurvC5jQ0+0GHsYbwRBmyRTgEJ0qzgjhPY1EBiue+CUxCB8K+wfN2DxltAnvXgrE3JxjqLoUQ+fiB8Im7sxbjf1gMbkDy2qXUaAHSbULlqvE7vQX3JRN8YDMXUvv8dsZ2t9aJ1WmOKGMHYq2sBUD+WWGohBm9+/8ErVi2WNOzLHzP+DS6kmjSyC1lUDBOPPT5/b/hC4Qz41nkhJB4Yw8gIxTk38TFcviCOMZR8wSQY+6alom4ApfPubF0HgyOhYQGo1jhx1jQDnUguohGZHT9ulWhXjR0BZItMEv7yjcaSW+UApipreXYnZShmsX1hAFVlJF9RIV1g8iycrypr9KiQnEYtLd1sLvIkWIvemwiO3R7RXS9EZDlrTwDpqHJFBzW6tqSjmny7puo3hrWYzwTslaKPN3OxxKSaZFJjEkU6sqQTAZC9axLmTCeG3aMJdQcJQR8oSE8M6d21Q9lXmNyiCk05YzEp7B21YODhoxdFm7FS5FuWv37sZaoZg64VJgE9Vpw6fB1zuYdVcHhxi8++cg/ltjB/e+MOxSRjb5Lz4JFLjG2GSS3/7rl3ATAscv7BHU+hdlNeOH+EwYywjK9cOEQnr7Aofu/aQ2RLY+rdjKubc/y3Vx6j7kvrw62dPiOb8c7uJl9uWVjZJV9NGe12uLy2iDUKm8KLF44wO5jwu2cfod5X8va7XyPvlYxNTmkSntk6Sr2/5CNveZwLN5c4e2MFc7GHqhRnL+3n/TOX+Z3t4zz/wp3Y611u3JynewPe9fCLPLh0hfm7tqi7lqxfYvdSlAW1VPCOt75Id116Uufrmo37tIDDMxnVjCUdCxu8cKYm21FMVnBV0JJOUMzJfQ6ZF07gW9eW3k1DvjkhHRvSUUXdTygHUpWfjCvpgKOVMJG7Jb3VEtNpJjqvEapqA1VNujkEC3VPcvZUVYe8WpOJ1qaqaslJ9DY+EbmoVp6XYxJDhXVUlKfyDNXpCJOfJKLV6PKVg9xKCDEr7HhCyG3rdJpQtLMdwfwZcSR9D2vlGUkf5fBsoC9U8TRTZF9Dxa0HAlo1kZQWWPVM3xQwCGxdNDDl/nY5h3HVeMv5d/sNOfTeZlYRg+jBpF8iYgStHZvb2HaVRg67YwpjXWS/j5Av6cbaNO+IdB4jYiZI2ahoH575c+LZLa3lQC45sOkAZyw5FApeIqa0JaPnWclWnmgzrlZevS+wNFF/bBtjCHeeLTWYmJCJ7p0NG7Tm3Kbq+/Y6l9OV4l9q+boHjUArPB0emuhGT4tyNsUnhN+t3EgPpNy+m9aEiNHweWDuRb1tHuQUKI0NV9jGAS7fESQsERDzXlpbr2lqn60HIwJMfomB1jToi9lL/9105bO17eq62FC1bkT0oPowShC5Vi0PKKyj9a0CtHEeZAxW42P6IpbYcPqfuGrRei+48cJb3q5/yU0EDD04hMawaSWXzFrHELhKZm/svYfur1OWYau6YQ/9BJJIx5hQQRkz1KHqOwrlaA27e7IPp50YAGbhAGkiAt1yTriGIArK2gFKF153rI8eFQ5YSpWzrpyD5FgFm2qSUcnukZxkVKJrG9bBQmdDCnF0hYg2A6N9OVVX7mExq6ULTA2jAxarFL2bIq1jMkV6JWd8o8fWZp/xfktnE9KhtLdLJnB4/wYmhxefu4OFk5toR9z+ySsPYFPZz+y+PerZmq2iy70PXCQ9POJwdwvmK6yGj6+dotrJOL68TrXeYVTnvLJzENOxvPveF/nNi2+l2Mn5ufMPS47iUDO+2idVlkOHNjBW8dzmYRJtMJd6qFpxz8oNjh9dxSTQv6JI1lM+deNNPFv0+XLL3tk5qoGlPztBJQY7Slg6tM1dR6+TJzW9uTH3rNzgnd1NqirhtY193NyZYWerhx0m/OvLD3JkeZPODSlAmT25harkWr9x9gCzd26hKmnHaO8b8Zkbd/HM6lG+ffF50j3F+w68CMpSzhuqIuGzqycZr0B61x7KQr6l6axJODrbBmWgd8NIHquF3g2EydVgUlkPK/dZu57kxaywi/nWhN1jXSbzifSMdg5GZ12kbWyKPMeldI5BKXQh76jNhLXGgT5VSnhbFRXJ2D/DWsTqAT2uGskcLU4SvhDB2xgjMlTW5/hWTqg+LkyDRmKs9qDIiq13E3RLjcPn9CVpYNQCYxkmb9fFxpimrajXXgzAwx3fA75EOjP5HGog5Pfdlh0M4DMOjROt+yWYpVrAbyBCXCg2zAkmmrs8SAv2281ZurHLnk2Mw89B7zIGpPEcBK4PeLRvv54ffZzn7gGin9OjCubYft9yygriCGS4R9besp4POzfn7fIQw/VociJjib5pPcjWPt19aJqNuOvjw95+zBE49YU2fls3sGY7GUADMKMIWIuh9Me73XX5MsvXPWicLhxpSb3ENzMCVB5Iiv6Tbt2kuCn5LVXX3uj4itcYaHrvIwr1xtT1NDPWYv6MaY9bNULacWeblqcTrTvtpYWxTn8WnUcAqdM5LsY0RRjT+/b/jwW2/TbxvuLr5g1HzCxqJ0/jvegQLlcNiPTjthBkbPwL6ScG/2JMM58BkEZerdbCVHa7kreZRWDWJ55b6wplLK1ws6XplODOX/V6jvl0Ywo9aV2F36QQg1aUTd6jy3OM32CVZYENtLnro+3FwivRkJQqRB2KVryGo+RPIhOn1sIu9jshzIxC9O20RtWul2+WYjoZujIkw1IqnselaDQaK6Fm9zuZCFDNtkuqgTAz+XZFNUhJJjXZjsShy4EmGxpGBwlyPtmeISktnZuaYk6RFEbCzjkkI0v/BnRWE6iVC2mCSS11FzafWmKwPMRq2Dg/j0mhnFVgYG5uRDkr1y/ZTli9Mc9W2aW42eXSaIF/cMdTkFgenXuDlQPbGCtG+LvmLrKxMUBVihk9Ictrkoli0C2wGr7pwef5yCOP86GVV3j33Kt808prjPY6fOu+l6TIo1+zW3W4ujOH6RvKgaJeKpnrjL9iTqN1j/NjS2+Ahf7SiFGVcjDfYlhmjIc5d3Wu8zMvvpW5wYhv2H8GdlI+cOczSFGt5cHBRZH52VeyvjkgWSz4mRce48gdN1nfnKFcrkiPDinKlGpLxvMfnn8Xk0XL4zt3oieKdFeTbqXUNzvUPUt9ZkA5Y6l6lpkHt6g7knJgFVLdnAlInCwo8h1hgetcubxGYRttoih7rlimAyZPpH91YSnm5N6bTJwRZWzoP21TLaFq123IdlL0pKLuNOFd0+9QLfTkfRsV0k7QPdu+c4yNIgY4cXu/jvVOaVU36SSe6fJ5xC4dxXZz2T+Ibex2gqxNyGtULrIAAgA9KDR1KGQL6TEWAYFOGih0vPJgzXob453cJjdNbIazzzHQVDSRFQ8sPbsYHHyaULqPFMXgzdswn58YAy7vMFvbRF/CfMKtc0Vsz73N8rY7pAvVDTkQR8r8ceN5JIr2ic0jONwhTOtBqWeAaYCjz3H0kTM/B8dqKHG0L5B30RzbkqrDzblaNayzjqKEDmhGG4d7H47jbXEAy808pVzEilDkEn3eIrGa+x9yKeMiGA8M/Tlp3RyH5lz/l+SOWzzYanpKujyDSEIlPFR1U1EdAEDMPEY3pjlA86A2rGUkyROBtFsqtt1D06qa8g+Pz4lxuSkNHe9figZExtVdTaca23ij0cNwi4BqfMwsCw97aF/o8wIjLzKcd/SSh2o1D/J8MYdSwibG2+loX8Gw0QKS1rN1/vgQ5TpOHd+DR7dtq8tBrNOop/72BSi+CjtJsMVErrdv2VfXAexRRe3+LOKBJ42xCxMFSsLKVS1sYmwUcaLyPj8wTR3bKuwgrv+rhOn9BOfWHU2aa+cNjKuKVL77i6uGBqCTSZcYz7jiDFZZNekAY2FUyqUBye5YADNgUi1MY6Kp+zlq4ooEjEUVNVUvpXdDWJxyJkNP5J3QrhsMFsYrKbWroFYG+lclZ62cEVbTauXCmVDnOrBRKEjG0gGGxAoItKBLCUNXA0VtFRwaS3h7CA8/+DrKwu61AX/j3sfR2lDP1VgNly6vYGdqdsoOj4/nSPY0f/jyw6xdmmc536OzPOLfXHkT8wtD9h3d5PdfeoS61nQPDPmxAy/ysdNPcKlY5mffeITf2T7OoSThT59+iLv33+APrz9A/9Q233H8WS7fWKLYy+kOCgmT76QM0oK+nvDllqW7Nvi208/yF6/ex1sOXiTThsnlAZ+9fpKfOPQ83X7BH7z4CIPlIZMy5emt47zt1Gv81ebdqF5NeaXPjXKeQ/s2SNIaKo261EHPlDw2c5beYMK+xV2qKuGHjj7O0aM3sZsZyUSRTBSrlxcwHSv9wA+MOXzHTTo3NVZDZwP2H91g79l5qq5isqAYHRI2d3jE0t2Qe2NSRKA7h2QCnc1anh8leY7pSDQ2q15KMSssc1JAvistBYeHeo4pt9gsoe4k5Nsim2MyLc+FVqRDeXaLpS420WQbI6xSVIt9BwKlwEtVNXUvw3ZSbEcKYqSQphJVAa0l97CXY3sdrG+75/OKI3tkvSC+tzsg+/Fgq5uLM6gUtphI6Dp1LfdSYWMF6FmXt+hynL0zGiZ59SXyFcWm+sYCrYiKaw3oHcfGlkY20q/ngYwv+LtdFMfvPx5D+Fw3ttV/50P5rWrsqagVRN3Cptbxx40jW34uiYsRHSETkxkh2qdUkz42dQ4tVRQfQvfHjxjFJt0sKkDxWCFOXQtMYtxCEDdXm2bbCJA27J5nA/1xVcAK8dKawx3IDYypxxFxSD9mecO1nopkumuv4vVlNF81WPTL1z1obARE/QceYE1fZJqJfArYhe0cgGzlPMRhWUu7+MXdnCDiGe9PqciToP3gxNs6QxjrAbakbgJAbTzAVl5g9HL544Qim2kG0oMin+/jGb/Wy+jWj8cAwUiFcIL36v26EWsaDFoccvfGM9Zd9B5SCzg2YZ1Wz1U/bv9ZXUehqAgoq+ZlC6A8nEBkcIJnnQSQGIxgPO5YriJJguGWIhblOrxUwZMP4DpUxDfjsFnSMB4xO5toYUz8tfWToxcvrxz7iUysylWhS2GAhN2EpbRNgnzWFMJUMznpzsRVmcrElewVqMpQzmTUXcltrPMkdOVIh9K+TY1KdGVE6BvpDgOgjSWZgMkhHco7YhIBj3PnK6q+HEcZS7YrTGO2a5l/0wbgCmGWC7ItaSOoK0jGkjtnFYzXe5SjTIpq7h7x+OU7BBMn8LvPvI3NzQHdqylpT1rV2UJzpL/FVt3jm+57EVWDTeGFtUPyKBrNcmfIXpHzprsuUK/nfNPyawCMbMnqeIA1ivNbi/zilQcp5wy11bxr3+t8cOV5fv/Sg2TbmnxdU17vMr+yB0CiDPfnQ77cYi386eo9HDiyzlK6S1En0mGlK2HW8Tjj2+57lqODLb77wDOkuuZzl05SG813H32a7tFdvnjlOGuvLPOufWdZWdnh3Y8+Rz1O2DVdxuOMrVGXo3Ob7EsyrpxfIVkqqPqWfXeuYWcqsm3N6HhNudnh0tVlsCK5Uw4UO08tUszDZFH0M3WnFq1GC7snHNgsBQD21gzlrOgu+i5BPr9RV5J+YLWwi8paioFi70jKeAVxTGpLnYuUUzkr+ox17oCHQphGrcg3JvKodjKUlefIDHLpUuR7Q1sZhxoXqEklNkk1qgLBeQJnU6zkAfvCMixKu97Sadp0g4oLMKrKyWy59dM0yGyFYpnw3orNExudo7LctTY1tCIXfjwuktDKpY5Fsv3DY12420djsrR5z1XEfHmHunL9th0YDbbdOazB5kEzTxgTVWDTzKlemUKpJjIUg9pp4iUmKGKwE9JtVAOMpsidVqFoHJaPwbHyEbymmCQQGz5i5T+bfg89S+dvQSAZopWivz1YbYBitB3RXB8OQEMsRUCyHR5vgGZLE9Jt48Pekiup3b1v9jddrBqznXEF+K0V1bdcji+5fN2Dxla7vqnf0z0tYxauSWJtKHH/470MzyberkclUzcvzoEMzFy8jW0XvLS0rOKH3e8jMF7tFyOujJuWMCAeg6vyBpq8Qj9umUWbkI61LaN1i5SPUqG9XetaxWO8ZSxfAoD5h7eOwrT+vBLn2aLk91Q3gjAmz+yFNoWGW7xfYxpmNYSq3WQQjDjNdm7iCMdKkqbnrDfW0ABvf+vdJNHYhMbjtabGuvwrpV142U8CvU6Q7bBlKXlakcGziRaGA7B5Dj4E5YGkv3QezHv9SGuDfmM90xX2ZmssoWnXEcbmruI6T8iGFfnGGJMlJHsTEfGuDTZR6FHJ3vG+zGu1c6ISRdWT65Tt1dIzOBcZlrqjGC8rqr5UF9ddAQ+6EqAwPlWy+fIiyghoTM91yLctnU1L3RWZFpMJQFH9ipP7b2I6lslGl3QrIRkp6FfoEnRmKI8VfODws6ClUhrgta39/NXqXaha7vVsb8xomPMN+86Q6YpxkbJeDjh4fJ0//dzDfHLnGJerLpMy5aMnn8TUGoWFxHLu+gr35JuU1qB2U+p9JUfvvy6hdKv4sYc+w16Vf8Xe0zduzlMUKdc25nlq+zij9R7lvoq9vQ4/89JbYZhyvljhG/vn+K0X3sEgK5ibHbO91eMTrz3K3rDDqQOr1D3LZ569n5ubMzyxdQISy/35hCyrqdY7nLu2j595/jGwUI5T0pFi89klko2U/l3bqMSiKyQ3sYMrXJL/60KJ8PfYkl/MMKlicEmhKkX6wB7pWIDbaFmT7YpY+2hZciyLOYWqQJeGZGzI94z0mtaKzrYh27EsviT6ieVcKoVTw5J8q6TONcpAMqrQo4J0t5Dxz+XU3SZVQhc1yc4YXYjWqJnpkuxOBDjmToO1m7u8XZcGYm3IjfSFZcpVP5Nn7r0CXH6w0kmTxxgzdB23XtIU0Pj3Hmua9BPPUtUGW5ZNDmO8BEfYgbdQWatCVMFHLLwtCLnS3vZ72+ZsYUsA3DNyfl/ebsZqFD7Mr5SM/3YMpN+H/9xvd0sEKJoPoLGnPmc03h+EsHg8b4fq6uj4SqmWrW0xhq4YtcUEEoGmuGGHA2CB8IEG0NlGPNz/P8zjUzJzHtTdAt7UVIGJjf5wuK3FSMYA1Y2tYTV9pDI6V/w20ZwfKtAcs+rGFddR3KIeM4Uhv9zydQ8aAwPoHpb4wrXaBoUHKPrO38Cphzd8b6cU4iMWK86jDEnAwVOIbnrr4Zq6Hf5FB0KVmn8Bp3NQIiDqQ9lqGlS6/QAhpwNochQj0NwyFHEOYXTut+zbA7KWtzllQEJ4wLa7DcT7A8cAROAz5ClG12yaLYUmLB6uofsd5464go/Wcf198SEb3xM2TjGIr7kHltq1AaxqCae7VoG2LJtJwr+gaRpykGxZNgYodZNRGBMyiVknu+M/BFlHKddXWkSHlc+fVZLPaLp50Ge0brKxnawphjEWNSzCbm03EyamtsKEVKYxaBNXbGCk53SyOxG5E/dc5LtGhLxdf+p0XDNZ0NSZpphNSCeWfKskHdZ0tuX6FbM6yPJM5hS5+zy7KJOvyaDuSN5b1XX5jLMS7jx45xqqhvmZEWev7UOXCnoV1UxNOW84vryBVWBKDZsZzw2PYRPLzqVZXj1/mG5aYW52qPuGdKS4f+Yqh5c2eX10gMf6b/C/H32cG3szDKuM4liJxvDZrbv5ycPPA/Cug69TW03eK+leS3hmvJ/PDk9g+zV3L69y9to+DhxdpzSa37r5IB9cep2e+vKSOyo1DPoTks2Uce3yVgtNfjVjfnmPjz7wONtllw2TYQc13zhzhu3NPof3bYJRfPTOpxjVGSyUmNSSdSp+dN/LvOvoWf5qtMSgU7B0eJvOTc3svj0665DsSZvH8QGLqhQ7F2dRmykYSIaKctaAhsmRkmK2eS5Hh40AwUXL3l01nTUwzwykzePIoGrortcUA+3aSSq6G5bJvGaykFD1tLQS1JL7OFpJyIaGup+hakO2U5FtF1QzwtSno0o6FCkoVgaASEBlWxPRedSKZHfSvBshX1FSK9SooB5IBbNNdaPclGeNbQF558tSnOksbVI8PPtlrGMFXdFCAB7C2ntbYoumJ3Xo8pE0ESW0gn63cZol/tjYxSgXUl6GiFmMGcDbzfBxVMQXC/r1ytIxjEkotgx5i27/ISKio/Pz+3Xn10R0pmxvbPv9OEJ0RPYR5i8/n/hrEloh3npOobVufJ8gsHPTqVmeEPGfKR+RieaZmKjxuY9xipjv2nKLvnM0vGksISvJzy21DK3FEVUezKnmXGLgphzTHZhCC16Vg5gldONqpdAxHRG1zTzo8ZB/T4JiB/yv6mm3+Jvhf8fUb0PteuawXV18W6oXWg9xk2RrG9ARQKG/schNyRs5nlZ+xW3AV+vYjhkLkgb+xY5BZDTOFhMZP0y3oezD355t9ADKb6OcUZvKqQx/x/v3gMz/VrTzC/2xIkYVaMIM06xwAJrOuPrFe1M+MdtXP+e5q1yOXlTPvMWh8vhH6yZ30nlzLaYxjNk24zN1Iw1hhDUIbKUPT3sZDe/B26gaWqlQWR3YxDSVcHHk8Vu/Tqcj52ukL3O4Jv7au0R+VdfSGnB31DbqWonkyXAix9AKVdfoYSF/TySUp1z4zoNMVRsBiM6Y6FI08KzLdyxnc+n3WxlGy3I9yplUdPkSRb5TU2eKYjaj7kr7ud6qoX+1xGpFvmNICpjMa8q+orsuxt4kit4qjPdBNrJM7pvQvZRQzlo2n1imnLWMXppDTxR3nbwK4wQ91mAUq8MZTNdy6uANZg7v8vqNfdAxsFRic8MDc1d4++nXOHZojXKh5o3xCqt7M3z/wjn2JRn/1+XHmOlM2L42y9LMHhtFn5s3Z3m1TPmj3UM8sX6CPKnJs4rknj2euHGCF64dRqeGtw/OoWpYe22ZsrqNRuqXWkYJ8/mY+0+fZ3R5gJ4t6axp6mMTfnT/S/z8hTfztxZfJ1MGWyv+642H6c+N5bNdxUtlzqXri5hRipmrme+NebHo8PlXTnFnvsreJGdnkrNw3wZHB5vSsrFWFHeU7Nu/RblYi6YlgIb77rmETSWXVO2k1H1DsWDorRmROKohGSvUToLJpaWjSWDzbjnnybzkQ/oCJl1bOluGdCyOwO4R0YfsrtfMXCrwFZ4mTwUApsIuGvfcFfM5e4e6JGNJ4Ugm8o6ryoQcRozF9jvo3ZEU1EwqxzAqKeaaFOL4dLJQfGZ9dMSDJ1Rja+s69Fa3ZYUdj0No2JZVCGWqPBOh8FzUEMK7HyZ2acGqHIBSiYTOA7BD7IqdTNopLl7ZwRfGqMgmKtp2188Ffvb3f0egVHU6TUg47vjiiQnl5M5iR94DpZgE8KDPh8m9ffS2NTjUjSNuS8nhDIUw3pb6+c/bHX/MaQDpj+/yQ8EDwiZUHaR2prfDzddT82SY901TKBvnL8bTjQeIrfQ1jyXgtvg95D66edgLhIfcRAdYbz0f2wa5flHNccOzSiMu7mX/gtyfwySBefRMqNtHkyZH+/dXsXzdg8Ymz5BQkHC7sveWdpRqQs44ijpm7qb1F0MibswAQug/GYpifLHFFKvWKlTx24cXLAoPxGxhuNkNuGqF4mNwpppQdSu5OL5McagkZjPj3xByXmxsGOJQjfeETDTm2AONPehQSTgFYMMYaPYZQrPROnF+JDhPWrfBbJxL48cKTr7CNC9Tmjahbx+SCBOJakCmtaCdCK3LdxKAGAFun7cCTa4RPi/VhmdJZZkrnlEob2BduDpMFF4SSLmwmDGhSEcVZSO/4a6DVe4Z8v2olawnkiWpJP1rFfrt+lCU6YushnX5sMpJ6+hSmEcpjNFhQsZaElf8sne0Q+pqPdK9ygEEJ36bQlIYkpEAXlVD3U/I9mp0YV2fZkgKy/Ydwk7lO4ZiTtFZlxzGcpRJ5e5IUQ0UZqGimLfYmYpXrx4gnS2lSGZTMdzrYBI4v7UoldEWvufEU5xcWuN7Tj7F2eEKs3rEhZuL6Myw+sIK7z/4PKWt+fWb93Dnwjob1+dI9xRrWzOsbs5y1+Eb/MGlB5lPR/wfh5/jO/c9S1GmHB1scmh+m7RToVZz/sfWvQyWRpjDE7K0ppfKfdoyBV9u0RUkyvItg+vUMwa7nVHMWxb6Y/7lmbfwzQdfAeAP1x9AjzT9rOTvHnqOX7j0ECaFTz/zMHqs0f2K5fldvnf5ef7o9QexcxV/vHEfP3bkSbS2DMsMrSz1iQmH7lrFWiXi5UDvumJwaI90qHjl+WMsLAypO9KTOhlLKLrqiCSOOTmWTj1rsHh6ncmiFLWYgYvSWOkb3tkW5tEC2mmI7hxXlEs16chQd3WT31hZitkE0+8InupqTC7PW75d0lsrQ94staGekcKOupeKYwNQGcygK+0uK+mLjqXRXgQBbM4BrnsZ1cIgir64+WE6T91FDzyTT78rz3ZRYCeF5BvHzrazASpJxZG0UiSn8gxbFk1Ro+vupXwYuqojp9WZCt/5qaqFLfSFcR7ceG1abxvhVgfcmEZkPG5p5wsUPcOodBPyje1xDOjc9Q/fud8txi2ukPbki98mzsmcPlZMHkSRtab9Lo2j78mXNMVHEhuyphlLAGD+J4BHZ4eV7+DWiFsHABrJ2sQV2L6o1v9uKqYd+PNV1B7AuVQw/xMDx1DN7dYTIOgLbtpzYjvcbrm1KLcplonD5Coqpoyfk8BG+o9vYUVvv3z9g0ZFhOpta0InPDBRnl7UfDzsIhb29uAxBjuxZ+Qe+lbpvv88ZjujbWJB0FbCsM8njHLZwgvnuxF44BWzjf54EIBOzHDesq6d6h4TPMoI5IVzNo0kDTQsYAwOA2PpgKJPoJ72AuN8R//jF5+fo7V4yHGY2NqmmjFclynAXFURa2cbVjJxxR51Jft1OwnJ7Vo8aUm0Th3Qc9ciWHLVXC+lQ4V0YBfTVIbiG9I7712AuRJm0wl4qzRtKvwrV22ZuF7VZRUKaqzLi7JpIqE113LKJolMZIoG8Llx1HN9VG2o53ryuTGo0QQ9nEBlmonDWNSoxHRSqkEmoebaXX8nCZKMShHudka/7mqqnqQCdDcMunDXsTSu9shS9ROMq6CV8DvSx7jn8t0yRWfLMlkS2ZbOOmBEoicZIyzl0RJVaKqepZwzdDYNeivlxB036FzOyNcS7lxY4zsffoKqZ0l2NHq2pOva8mXdik+cf4Sz68v8/rU3sTYccH8+4aFDl2E7pZyx/NXm3VyuEzb2+lzZm0OX8M1veYajyxv85MkvYK3iJ+54nC+snuBnzz3C47snydKaV1cPcGl1kW8/+AIn7rnG1c15xpcH1DsZvazk2qUlfvaNR9gyXzo8faOuUMsFN4Yz/Oy5RzhxYA09X6Aniptrsxxd2WTHdAH42/texnQspdH84qU3o5Vl9vg2qob7777ETG/C+pV5fuWZd3H/scskqWFY5jw1WcFaxaH+Nm/sLnJifp2rr+8jWc2wRtG7rBkeNezcHGASMLll98IsSys70llnqaKcURTzimquRr3Rxe4rMKli7fUllAWrYeEFSIfSLlCXklqQTNzklihG+yTfceFF+X8yEWekHCjqnqRomFShEOfDZFJ8ZVxVtaqMFML4yVwpklFF3UtQkxK9O0KPCkCE5ZM9CWtjLOQZaiQ5jiqXiulkd0K6NRTmvJO7tBJvq7y9cs91tyNi+JPSvZcp9HvC8E8mrmVg0iYDXIhYOYbPjifiaHqGsxZJH1tM3LyhmlzGAIDcGDxLGBzdZr6xxjUN8CoQWjdzRwR+W5EmgKJo/u/BY1xw57YNc4wxkn7j2UZ3fDGDEZSIHPtb8uqdbSCebyJW8pZ5AA98xIn3FesBeBvT1BVMz3ExmeOJIPddY7/9nO7XBd+FhdprMSbNODyZoSJwF+2jYS9tAJXhPCJmVE67AYGNcLj73MMG71h4PBGnNXj8oLXMJ4r2/cW2wHCLrYzG0VJ5+SqWr3vQeDuB7ekWQ9OFMLdUOvu/g8djb/ne7Tg81H7f0Q7Cg9gCV7dbpo7byp2YAoi3U8sHbnnxw4vuv59O5PUgEWT8cWFLCOXexmP0oeFpT9svJj7fqePEgDoen47ulzFOooJmnfgaTP/2Y47ZUm8IjSX0hvaXLEnxDe0bZtEnD0tIORgUH372YSXfrjFNnfHw98ON3YvTGtFhU646PDSaD6FtZ3RSkQehNtDJGtCGx+uN92ldEQy5Z0wR5tGdh80SCT8b1+3FPxtJInqNPWnhpooyAGU9Ksm2xpRzaZNnFDHexYzLbcwk1KyMTM66cK3mgLqX0tmupB+wgnzXSDStqKWgobJYDXVHUQwU+XaFMor+qhGRbo10AxlLVxWFJd9Swmrt36GY1dR9w4U39qOMpVipOfvKYX7nlUdJR4ql41ukaY0BvufgM1Q7GXm3xG5lVGXCN+9/hV94/G2kqoa5CtO1vH/pBb64eydz/TE/fvAFPvLw47w4PMzN0YCuShnVKb/42tupywRrFOeu7GO41+GjJ59kcWGPZ/aOce7cAdhJqXuG+X27dJMKZipsrXhpfIQvtdyoZ6i3csoyIbmR8YG5M9i1nPTwiNNHrvKDC2eZ0RN+a/MkAB87/QR/Z/9L/P2jz9LNKso6Yf6uLYZVzof2PY/pGcxszYs3DlKv5/zEoed5Z3eTyThjt+pQ15pTvWuoA2PqrsXWkkrQ6RccObJGMoF6YDAdy/rNWXQFWVZRzlh0AZ3rCeW8Ra3mcv81Tm7H63FaMLjqaRtydYtZzczlmsG1irLnIiXuce6tVsIkj8XGqLJuCqtShcm1FGBVwlbXLqe2GmSYVJOO6qC8YKOCNRX1oa9z0SC1HtyUlUvV0Jh+BzUpBBR60+oLQfzc0MnCb+scKlXWWM8EKoXNM8ciATN9mfDTtFHnyPMm4hTYQGdXQDRiTd220T43MQ7n+gpnbxhM7ULAtvluem7ydtADC0Vjl73mIdF3/hp4JtQDzsDC0tjY6aiOP4aNol8RkAtzRTz/eVsdp4elDcMbijgDeNLteSYG0v6jOErnl5Dr2Rw3MJpRiPt27YLlMM298VrO00xrU/QaVSrbpttLS9Yvvh/QzEt++7hgtVW6DYFkamEJx56GedJv5uaFmHmN5s5p1vHLLV/3oBErciaBEqa58YLu3c33E3xEH9+OlQv7aeWrRexaa902oGlJH0C7Ybsfrr+xUyr/YSze2/Kg9zbAFQjVga1wuInGOdXhpqmac8fxfY39mP02Ud5IGEcVGTr/gk9fO6/lFTO03sgF7a3mxb8lP8WHa020D+MAq9YudKMlrzFmhrMMyaeJCnCCAawbuRprm3QAE41Hu24GXr/Ng9qqdmCzxlalVEN7iQzvqbp1VeLDLY2xC7JH3vhZi80ykQFJRNQYrRvw7qSUlDFS6FJWUthS1cL+OSfA9Dsi/u27OrjxqKoWKRGFTI5ONNn0OwGIe/HiZOSAauXGlUo3jcE112ljIoUO6ahCV5bJQirtCxGwUHVdfmNfciknc5pykMo2Q5n4+6tSGFN3E/rXhZ0cr8BkXnLhxkuK/lVF5/VMOsccFBADkAx1MK46M2R7AiyLecvq+izv3vcaVZ3wXy8/gurXzHUn2EHNvftusFrN8vcf+wJ35qucWr5BMlL8p6tvIVWGrd0eP/PCY/ynjZOc7l9lkBWcKRNuXFgiH5R89OSTKG35+/d9gZWFXT4/XuBv73uZG3uSR3n65GVUqTg9e40ra/Oo7ZS79q3yvpkrfKnlTfmY3vKIutTYzPJvrzzCN93/IpONLu+fuQzAp9+4n3GV8rNvPALAr9y4j1+88iAnZ26ilGXzwhzXRzP89sY9dG4koCyME7KVMf9+9TQ/9/RjAKyP+jy6dIE/fPlh9IUuVoEqpZVj9mKXK5vzWC9OsKvQE4UuFEdmtl23HnfNS/mpO6K3mC9In2erYLKo0aW0hqy60lGoHCi6NyuqnqbONemkYViSsTgT3fWSZGJQlaFY6DBeyUn3atJdCfEnhbxvupBnVBc1yajCdKToqp7pUs/1sV3HzHcyAXrWYBNNsjcJElPyuZPbqg3J9kie/9GkCSd75ypN5H0bTlDjieRGekdKK/DqB4mWNp5VBXUVutI0wt8uNUjpdgqSm0dUt+OYSN1gA2dvVZqFIp1gg7ydTJ0j65cQ3o6AqV/qWAbNtm2pL8YJepQQojfeTkcsVSt1yduysD+a8wtzT2MPw/nHzr27RvF1CWSFP068bjw/euYtXAPZbyuiF83nrfSweN6yzbZxn2pvy5twtBAQLcmbcOhm3zHT2JrPpoBjXCQbh7pvxR7eyEbHq6Ne2mHFqS50ViKJgTH1187KeMM+vsrl6x40BvDnf8e0uCLcMP9g+YcFPIDzFG4DBJQPY0Q3qyULoJq+k62CG2g96C10H3lQ01pR0/mWcfXy9Itxi2el2oAzFFA44HvLEr2oNs45iZk8nzgdh7FV9EAH74bmGN7gef3EqLtAOH9v5Hw4OZwbTd6endq3P90kAVM3ycUe0Ps8R79O8FxVM/b4+VDR4IPuGE0+omMPZHt3LGPFWPtzMZHh9pIJo3GTN6ScdmeWEtoNJho1mcj6jvlrCniExbCJFoakqATUu+fWJkmovFbjUtZzoBZXQGOVol4cgOscoyYuL7Iy4RxtlmK6GTZxnnHuJk4PKi3YRFMs5mRji6ot6bAi32mkj2ziOnxoEXVWpezbpIrRQZjMSyHFaDlhvJhQDhSTeU06Mvz1+58Ll14ZROC7r5gsWrqrinxTU3egswZ1z8pxtlMJadaQTBQPHr7ElWIRrSzZBSdJZBULc0NevnaAs7v7OFcpnh6eQCnoHdrjAweeZS4b8ciBi6hBxan+dT598X7WdgZ88swjzB7ZYbknuot2lPBHO8fYHHV5dXc/nx8vcMfcOkvLO7x0/SB2pub5rcOoUvOt9z3LtdHsre/Y1DLa7JJ2BNAXk5Q/feM+Pnj6s/zcU48xsiUfuPMZhmWOrRU1lr+z/yUmmx3Wihl51fZP2N/b5ebeDHc8dJkkM3QXx1gU3aTkr9//HHozoVjr8lh3G11COWNRg4p3njxDua9isqAwpWayUks6wKGS3k0Z36WXDzB7aBdlweQSru5sSaFMd81gLvfobhqSCrJdKXYp+5psz4reppE2k0khXWP8O6wLcRqGB0Rmp841dS8h2ypIXLqDyRKSiWH7zi6mI8+5Ll0xl7XoUnpW6+EE7QToTarl+XbOtzCX7jnPm8IulWeNwxapM9g0bXRMlYzfd4qxLu/QqxiIsDfBZojgf+oc9OYe+9C1rRsQGRiounbh7bSx9ZGWrvUSOD7SE9ltW1au9/WU/YkjRX6s3r6Grje6sXHWGddAbEwRIdPEQ8z0xWCyNQfdfo6Jw8e3LB5gurmqBX4cE9nkA6rIdsfESwOIW4oj0ZwZ5uMWPmiuU9xNRlbzkw8NIRCDtWjabYpqp87RjTdoNfqPkyTkQDYYI2I+3bah4JYY4EbHjsgwLK0xhesS7hFRWNoGAPnVLF/3oFFN3zSP6m3Tyk+FCjV5+OMH5radYfwkG4Wxb1euHifDtmVgIpDnlpgiB26l3m8X0o7ZvNgoxECTqfWrKYbrdkuU9+F1r1pL/HBN94EGWnqL0zkqSjkv1/9EnmQMtvxL4XM4YnaxqpsxKTde/+CPfSg29rh16O8azs+6dUrfkss2kkpx4Ysfb8wGezkgb9hpjLe17vvEacPVdWQ8rGMeXV7WaITqdKSwZVw05zSJutE48KgmhYDFxLGGiZbiGbdfVRtpB+hDPFkquotauTwk0OMqXCfTzQnC4qn070VLKDDbLhwrKeesy1raB5Y1dS911bOGyULOZCFzoWdnsFLQlcUkis62RZfGtZMDDGRDg00gmUjLuHKgyPYsk4WE/3H1NDaBaiCh0OEBAR7JRIxksWjobAqQXFzapZiT/UpXGTn+c1eP8NrWPrSydO/dod8tWN/tUxlNt1+ye2GWsc2YS0ec6lzjvrnrHExqnnnjOFtVD4Xlwc4Oaafip+98km88+QqPzb/BYj7i584/zPEjN7m/d5lBp2B73OWlnYO8cvUgG9fmsKUmyWt4doAqFX+1fje7m31+Z/v47d8zRDi8Mz/hp489Q//wHv1+QTYo+C+fexf5wRF/NTzK7196kNPz1zi6vMHPP/82Pr13AKvhQGebdy+9ClbxN+bPc+fCGq9cPkS9m1Fd6LOvv8vVtQWe3jlOPWNgpuJnn3sMta8g31LcubzG56/fQdqRftxKi11L5grsXkoxp6gGlnJg2bk2gy7AarC7KWVfuskMD0uF9N6BhNoxkcpA1Zf8xHQoldPjlRyTiki7quX5mCym7B1M6GxJkUwxp8VsaEUyrNGVkZ7m1pLtWAdahYU3Wgmg3J1IF5mOP7jPj2xskSor0ST1EQX3f9PL5d1IPUAU26DKCsoa28lRozFqOG7ksBABcOV6rQs4bWxgKDT0xQf+HXOtAtvRq8bRF/Nmm4hGsM822DB8brVPj/F7cdGJYDchEu22TdMDb2dLV/hSm7bdjat2tWoKZKCZg7RqNCDjuSgmWgLzGM0TAQxH81tMdNymwtmzea2oTF235uSwRORFCM1Os4kecPo531+/KWA5LQzekrOJSJtWrmCWBkwhm02Bbred9eMPx25IKr+zIP2j2l3kfHW1EEERueHy4+UL2qSN/zzCKE1rwhg7TGGlL7N83YPGFusXwsHuhtipCxfd9Okek0Dr/7EoOEQPSXyjI4+mVTwTjc1t3M6lmAaU8csVv6y3Yxenqf/p9QNwvs044v8b0wAcn6OnVDBO4UX2TJ3WYtji81Q0zGYWFQNMGyJ/DrcLa/twsn+pgzSQ20dt5O+4j7RShNCKMzToyNjGRsEbNxWNwxvZ4M061jUWWXfgLBgo3wnCjSGcgnY5TkpJzpJy3Vli1rGTN5NO5bTifCcXRatDBfELb63kMdYCpJUxoTe27WSocSng0LV1FPkckcsRoWxfUVrLBGos6W6J6UhOZ7I7pu5JEY/2k2RtSSbCiunakg0NVT+l6su+8q0y5DjqwmJyTb5TkU4s/eswXkjIt0V+xSYCMCbzIgbdeT1Dl4p0qKi7UC+VVF1FNWMoZyRcunfMUizX0ifa3cLd4xabWbJDQ0kVvdZFK8vW6gzDG33eeuA84/MznJhdp+5ZDiS7PNC5wqdX70Nh+eT23ahS0dEVvW7Jk+NFqq0OT03meGtnh8+u38WN8Sw/cPSLfN/8G3zy2kN88+LLdLOKTlLRn53w0Tc9ju7U9HLRNVQGhtf7qKzmof4FvtTSUSnlapefeemtWKvY2+5yfG6TYtHwIwee5K7ODUyteOrsnXz7/Kt8z+knKG2KqhTf2FvjarlAOUn5g90jzCZj5haHDJaGrJxa428uniVfS3h49gJ3HriJKUQAvZuXTFYM3z13AbOT0ckquuuWZCNFjzTfuP8M6a6i6ltsZugtj0iHisn+mnoguae+tWP/iiXftmR7VvpIp5CODcnYsncI0okw55XLWbQpoEXwOyktg6s1qhJbke/Kc1P10tDCslgQu5Ht1S6lAup+LpXR7l2vuynlTMboYA8LZNuFvBO1Eba830GPyyYNwzjnrZbQtdWuEMYXpKWO9Xc2yRrjUkAkyqAqyRmWohlhfqzrLR1wT2z3PfCra8dU2oYgCGFLZzN8zqP/zoeep22lN9/BVDY2MxQp+qiJ1o299E64z8UMeR6RzY2d9rgSOrbbsTRPtF2YE1sMJs22ccpTGLC6fYqTja7hdBFPPFa/TTxfT88j8RjCtaFh1/zcFs3rLebRrx8BvBaT6BnMaA6PC2KaznHQjjpamBpmHK1sPSvhOWkTUVJoRVPMGTOJCvx8YX1EzG0cyA+3ym2Z39ssX/+gEQfwklsTPQMwnPII4u9j7yfu2diil6OHKlDEzmsLHk38osQ5b1PbtTyeKDR+2wfejz1+Uf25JEnwcm9ZbscwhiKUyKvCjSUGUbH8UHwOHiQq2usGz9J50D60671bb0S8KHfM8MX3w3cQsI7RtDThFRDGMBEZm5awrfe2TcMKkmUN2I2vW2xQA3g3U96xkWIalyMiYr62WdfrkflesM6zlGRy582PJ067zTG/rhpTJhRQndxVWNqGAfH32y/+uieJJPf7UPZMT3ITXZs0PSkDw6xHTjDcdYfRRSXdX4yVqtS6xuaJTIq9TMS8S0PdlYmynM1DBavVinQk4FHVFl3Jc1b1U0wmsiW6NNQdjVWK4YrG+LTSXIxZNpT+0nVfQt1ShWtJxnLLBq+lpCNpXVfN1SQj14FkOyHbShhchnxTofKadEfzk4efJ++UVAPD+I0ZOotjTNfw+NUTmMzy+sYKKMtvrz7MU6PjGKtIleE75s6g5ktKm/CjB5/jjdEydx27xjObx/i9naNMqoRH597gD9fexL9fPc0HDj7L1WqBstaM65R3Lb/OZ8cLWKN4y8IF6o6le3CIGRhO7VvljimiPl40Elq/79gV7phdJ8lrvnvuAu+560WeGB/lztTysbufJFuc8O8vP8paPcNrZw6javgvW3dwfrhMsqt5e/8chU3Y3upxdLDFIC34zGiRYrnm06+/ibXxgGxQYHLLpEzpzo/5k+F+0Jbi3AzFjKLui0P9xOYJqhnrWEHFcLfD0j3rdK8mqEqR7Sr6N8BklmJeU8xDnSvybUt3vaLqaqqeYuayOAY2gc62oZyVZ0GeHUudiXi3TeQB16U800lRU3c1xVxKMjKYTJMOS+peRjIsSSYV6bCU7YxF14Z8a0Jn07XPHBWYrlQbq9q1EvQRFisOVbIzRg0nwYb51puAC0enTRelrsj7WC+N48GCd/y0dp1nxK4Eof2ikO+TtJ3f7p1eTy64vHPr8o69nWx1HVGK0EI1tovW2dzI8bZVHWky1o1dn7b7Xt0BxKn29i+LC2Pih1UT2hDWdWQ3HUDLssamxp2x4jnKH3e6GDKQDxFpErF9AWjFqVBTbOIt9hE3Z0fH9pXszWWN5jIT6TbG+w9gWS7XNDMZto/366N9fhrVUUhcEWERF9GzjVB5nEfpz6UhuWilvQFhfCGE7sDodCMR5VOqPMAM9zhSl/kqlv9XgMaA1FVUJaSjYheP5qco5aDLFLWr8/kIt4S9dZR/4V9k/x208z9crsIt1dlT4LWt8k7zoPqq3dgDaT3c7v9VM+7W9re5PmEMHnD5/d0uXD4dMp72Jj1A9MeLBV1D+Cb2oFUbYMZ5p34daELa4TPnqVmaQhutonB6fI/8C6ybPt6hMMc0Rt0Yd30doPWUvweCQAht+3HN9JvxeMNTuoR433va57JUFd5QCEOZBMZBKqwlj9Azvb5Lg7JAzzGVvjDHOIHi3HURMZLYb5ME08skNwua1mm9pt+r9YyGlRNKxjLGqptI395KWgUardC1peoL+4NCCmBqSzGTUswl6Epy2ACnt6clnF0LGKy7Gl2DstDdrClmRY+x7ogMT/cmkv/WF+BiUgTcLCqKObkv+UaCTSFbGmNyi0ktVReSwpLeyCgXan7h4puZ7OXkMwWqhsODbbJ+yfHlDdRyQZoaVL/mGxZf52C+xWJvxGfPnKKrUiyKs5vLpGjeMnOe75i7wDsXXwfg7x99lvvzCTtXZ9i+Mstntk/xhWt3UhvN5uaAJ7ZOsF7OYGvFF9buAAt7mz3ymwnrk/5XbCNY5/DyuSNYC48dfIP/vneI+WTEeiEdUH53+xidtEIBb+3s0DkwQll4qH+RrXPznLr7CrVVPP/GcbCK1147zHw64vHrdzAzOybZ0+ys9akmKSaDaq3DaNjh0nARVUt6QN21PHDiMtmuYm+3i00sZrZGjxXH960zSAthFw1UPYJGpy4s6Z60gqz6iqqXYDLpQ50UljpXVLlitCwFMmVfoQtD70ZBvmtEZzFTlDMJ23eI6Dco8u2SbKcimTigpBR6UlH3nXxN6npSp9rl5TZ2QphCSbdQkwI1kTxf08kkNFtWAgwT7ULNdSiOQSHi3WUVpGZUJe+z11KlNg6URnbAWkkr8WbJv3M+HJllxH2UVRx5iSt6oy4q1gFd5ZUM0lTSXuJ0obii2oNRpRpQEIgPn5JkG3umdSOz4yMp3u57ogAaVtHvz8+Zvoe1Ma2CxlD1HDOj0OwjjuLEwNIVCoVtonkpsHrxvuJ9tFKymu9bqiee2ZsGpfESs7h+e3/PIjHu1lggnGsrB9E5Bc1n4GsMWuLanhyKySnH/HlA2focosgl4XcgJ1oHk98BdLr9tJRdXPj6f+U0+iU8ZLRvsgduHqUb0wKQnpJWtzyMjfdyS4XSFG3cYgRpf9Z6wCIge8vDeDtQFjGgXrA89nyARseqdQ2mXpQpQNuSOAjsYTQuaACgZwn9fkMieQTs/D5CTo37rNVL27a7C6Rpm4X0XnKWBiFqKYxRASTFoNlOisYw4dbzLIN7iWwxaV9LS0PVB2AeAWCdNCAySYPBt87gekZC5Vk7md2Httw5KW8gbDtvRuWZtPzz45yUMslkjq10BlnV4sCoJHGXy12zohTwqNy9sVKF6tljPS6oexl6dxxC/aoS8W5VGVdtLcYymdTUMx3p9OLYP38tsq0CPa6oOzJhp8Pa5Sgqsl33HiXKVdpKzhoKmdwRgKcMIt49q6lzxex563LlhH1StUx2yUTR2bQMrglwURWkQzCXevLI9C3Foug+du/YZWV5l3Ikk2mxl2OOTXjv3BkSbVkf91kcjJhsddA3M57aOc4fXzjNe+ZfwWaWj6+d4uH9F6mLhF+88iB/dON+fn31Pr64fYJ92Q6/vXknT0xm+cibH+fg8TUmVYqtFWWR8rFTX2RY5Lx2Yz9YRX2+T74jt6XcV7E16vHEeB9fbjlydI1kqHh57QBndg+wXvT5w9UHuLi2yM899Rg7VZcfPfAC1UZHHkmreMu9Z7k7q1GHx7yzf47/sX0alOXQvg2shoujRZSyFFVCcmiEqhT7FnawieUfvPlxVhZ2WN/poyrYO2rpH97j4t4C9dEJ+fWU3jXFyZWbqFpx4foyr1/Zj8nAdCydDct4MQmFMqoWiaR0aBkvSh5q1ZVCqDrz91Oe9XRsGS+L9iJAMSN9yNORId+0JCNDOUio84RiPqX2oWqtMHmCyRRbd4u4drYtFcp1J2Wy3EGPSsfMa1RVUc11aHK9VNNxSWvqQaeRnFIEZwvlOqN0OzIBu/agKnVRBS0C+LqsJR+51yVEI1xet8pzfIMAX9AQ7L2SMLQtSkjSpro6iG47m+hso3LMkrBBXt+xahEJcdMAdOLSXByL6EGdb0/oHXRvV+PQb4j46HB8+eXXTxpQ6e1kXBgTpM0i8iKeO2LbPwUMA3sbN3wIYWI3Lk8wQLug01+/aO4O18aDt2lACQ2zNyWDFwiENHF5iD7MfCuTGWx5hCMCSeXGEATBo/nSY49W9XQMzP1h6iansXk+CMUuoUvNdNHN1BKILvc8hVC2q5iZ1pT8csvXPWiM+0kGSlc36u7tJFNaN7u1jwDU5DtbRQmt0QPu2csA5qANWFtUMreCwmmQ5hf/eQQSW0Uz0ct8y0sSM5a3Yxu1B3xuf7cp6rklD9KHEqZBVuz9xaF/RQM2fYeFuL0fNJI3rZfEX+Op8XiAqiLDGINg40MgqjGMHmh6cDjt8Zq6fZ29/IQHfr64BiL5IR/OcO2yImdCJWLMxWjUDaOYpq47RBXCIqooZbIKRtA0ITN/3Xw7MhdCsX59pVBBYsmFhkcFvo+u7WQkexNslgbZEaxtKqdL6etczQtYTIYlNhNtPL03weQJyahyITgBmPnGmHI2lYm3tmSbo3Bf0ollMqfJhkZy0DrCSKGg7GmKGU3VVaFgJimthEdzBVby4pIxKCPFEelI0d0wVH3Idyymb+isaZKx5N19+8rzPDx3gWwrYXFxj7RXUk4SeiqjKFKGlwes7/ZJRork0IiN1xcBxZbpsm9lm+1Jl7/Wv8mBxW3GOznFJOVQb5u1rRnODldQynJmbz8A75o7w6hMOby0SbdbsGdLFrojUJbvuetJin015YwCbVG7CYPuhGPZ+q3vU7Q8OvMG5mBBkhrmsjHfv/ga1cU+WbfC5PCOudf5+XNvweTybJyav8Fru/v47HiBNy9dZkHn7O/skMyWjKqcb7nvOcZVhqk0f+/osyz2RnzHfU9xY3UelRl+dfU0N9dmseBSA2BcZBRVQievUDVMluH1K/uxqUWViu6q5vixVfJNLZqMxwomi6BrsKn0kbYJVDPCLupSficTS1JIKgIKumuFSCotpySjSloLluKwZGNhpbO9Sp6poSEZNSxtOZOiakvvhmPTXKcjZSz5RiFMeqKx3ZRqYUC6I20ybTel7kslvSorVFGiR6WEk51YtSorGI0lUpBnkh+cJa5Qxgn8u3xoVVah17pXIQjsnXtPg76uLxApHStnm/BniygIbF48JbsuUFYcQeln70Lika0L1bLe9kFjE+N5yOduK/edB6w+XUcpYWF9nrbrKNUUTka55X7x9qooGgkzaHIh/ZhiUBfnSfp9lFNsvGce/RLrA8e/ocW2xlFBrG20cv0+HTPXihb6KSYGbxDW9aztLe0D/VCj8LJPYYvn36Y9YDP3x6HjlmKKf2b8IcJvn+Mon/kxtSrJrY0UT9wJuPVbuZTuXH0xjT/+/zSm8c///M/5ru/6Lg4fPoxSiv/23/5b6/tQkTz183/+n/9nWOc973nPLd9/8IMfbO1nY2ODD33oQ8zPzzM/P8+HPvQhNjc3v9bhxgMDaIUI4u/Em3AgcppS979tG41P3zD/sIS8CFcscosqPTRsVQRkgYZl88eNvSkPxJxGWMjPmHqRb/Gq4uqz252bP66/TnFv0nj9GCT7EEbsWca5Kr5C2G9TR+cU/+2Fcb2GWJI0wtLyTAdwJvuKvNbgHbrQQJ6FFwRotxXEjdnS9I0WixyBRzmX8AJ76RvvUbtz9MVUYFFaWD+VO7FtL87rGb00jYBqE6awk8J1e3HORlUJS5qIbputRbBXhm7bOZhZ2iQ/T0rRdITQseIWj72sAmCUhH0g0dS9jLqXhfO0ieSTAQIed8fUc92mC0ct0j3VIMFmiSuKMTLBuurVyYJM+qNDwkBWHblf6QTpEtJXob1c2VfsHbfSqzgFk4FNhI3UlaXuwOhERXmoZDKnSUeyTraZoEtLenxIOlb89oVH6aiScr5m/OIsB+d2mJ0d87vbx/ixE1/g7lNXWJoZUi9UJNpiD01QyvLy8DBb4y7jnQ4/+8YjHOlu8o0nXuOjJ5/ifTNX+OhdT3Jje5ZhlfMt8y/z6b0D/NaZx/jAgWf5m4tnqeqEgcr4keXXsEXCZ7fuIltPqDuWw/s2eeTUObavzPL08Dhfbvmz9Xs5PL9FudHhjQv7+fnXHqOaNZRFwoN3XOB3X3yUNx+4zMfufYIbdcVKusNKZ48v3jzOUrLLL155kGdfO8FPH3uGxxbO8Rc3T/HXl19ifm7Iv778IGvDPn94/X50qbCVZnfUYXZhhC00h/dv8FP3fY709ZzTC9cZDjucesv5MNkkY2GObQLnr62EtIL0ck6+CSYRaSSTKkaHDJ01gp4jVjQ3dSU5r1aByTSDa7ULiSeUrsp690hCvjYW3c/5jGIhjVJRwOQJnY2CuqOlyGpcYvvCJCpjqQYZalQKez6uSMaSK2mzFDUqSXfGmG6GGXQkbSOVKmmpfvZMoAp2w2pRFPCOmddYFIF/RbI5DD2svU1SWRpafFJLe79QMR1rJOLYTM8SeRuTJCLqTwT4nJ1SWR7C1t4OeVvSSinydrGqnaSQn0dU4+TH4M3bqogVvAU7eOAaR4S8bfRzUJzf6EFgTGTErKLFpRM5W+pZxHieSZJbVTvctSACWK1rYaZYOfdZWDf+8cfx43FEi8qzZh/RNW1pN8fb+vsTrRMKbqFdHOnJGf8TNm/G5PMgfai5aXHo9+O2CTqRhOPEHW88w+5rOUKDCkdwNGHvBgu0usJ9meVrBo17e3u8+c1v5hd+4Rdu+/3Vq1dbP7/yK7+CUorv//7vb6334Q9/uLXeL/3SL7W+/+Ef/mGefvppPvWpT/GpT32Kp59+mg996ENf63BbIDAopXsGKfYqFE2uQQzE/A0I4U6fuxA9JDHdHgHLuJel/BGBztgjioFXBCzDC+4X/1CUVZOQDO1Q9O0WnyMT95eOl5h2j4/lx+B/fJsqaMLN8XoxwJ3Oi/F5L/5ck4SQGwiOybONoQH53ufdOK8vVFL7vEoI4PDWajCa5PGgqTh1PNwzEvIIdWAMY6NtjZs0UtHUIkmd91aH8FEwuO5ahPZb2m1jjBjycF3Bao2Z6aJ82LtucmgDW+1bd3lDXVYC/lwVKICZ6bkOGMhE57d1Wo2qKKVCWikx0kVJMq5IRiV1P0cVNdl2EYoGdGWw3RxdGem4URtsnlINUtKRoRqkUrjgdCXrnhj4/o2KcpCSbyTUqSLfEYAwmVcUMxK61IWA7nzHoicy/nzH0t2wZDs6gI2lR9bIrmekeU13o6bqyud1bhkvQ1lr6txijeJPbp5mZn7EZBEuX1pmXKaUNuH3Nk/zxvYSG28s8C1HX2a00YXVnLRTsVH0KLdzkm6FtfDu/k0e627zS1ffxM+98TAAJ5fX6CUlf75zD2d3Vti3ssPv3XiIf3X5Ie5dugHAr9+8l3So2Bj2qXuWdKi4emWJJ8/fga4UN8czt3/v3LK11+XijSVsZtl3ZJPB7BjVq5npT0iUQc2XPNy9hMHyJ9v3slHPcKyzxjfse5178zHLvT3ece9rfGLrBCfSbfp5wSdefivfsHCGIzPbVEVKtdXBppZ0R/P+Q8+zs9kn20y4srrA+arL6IjrvnM15YXVw5i+YfYNJV1jcstkf0W+qSnmkP7hXUlB+IF3f4ZiVlHOWfL1hGJBoV2rba/rWHcUJlGkY8Non7DT2VDejcldJcnYMLhuJF/RQnejIHE6oFUvZbKgSUYlqqjIt0thyN17XM11KGf8OyWFWKquXf6tCkDHau16piPviWO2Qr6vl/FSSJV23Pq0rp1j6PIePQBzecfB3rh8Qd+CtKlUdbahKgWYeKcYBbP9dmhwUjZ2PjjndRPGdv3uG6bRRtEnmjHfDvx5j9oxX43iBI3t9VI78Xzi57dYtidIptXNMVuHapMZLbDlFTlUVCAYwKhub+vnFWhLurVIg4jM8L/jVK+4sNGPRzWRupZcXjyXxkwoEZZwn8XFK37/Ie/QX46IWQZHWKjGUbhdc46QfxgDRdsAScKuTXQgWiScJ1w8gRVwSnytrJskHTC9LQ64zfI1g8b3v//9/PN//s/5vu/7vtt+f/DgwdbPJz7xCb75m7+ZkydPttbr9/ut9ebn58N3L730Ep/61Kf4t//23/LOd76Td77znfzyL/8yn/zkJ3nllVe+1iEDbeCGB4/xS+Z+T0vjWM88xWr8Uy9DS6C79Z1qez/Rtv5mhjzKmM72cghTHlEoVPGLA2BhHz7PI+wo8ixjwzQd3o7HH4PXqL8n0PyOr0fsEcf78dcxCrmr6XZVgW5XDcDxFX0elLY0GVUDoGrH5Pq2YeHaRAbD78cbR8d+2qpywEwMpzXeibANqPNV0FUdMZOR9xh3saHZ1m8fQhKd3D1TuvH0PHisDUwK9O5IvFOvNdfJookFJwuiXHGNacL6waO0LvFfY3s5ajQRNkXhmEeEnSzd/SwlF7MaZJiu6Cz6exGKBlz4rRykThgZyS/TUGfSTzrbdeG/qPJOGUMxq8i3pBACrZjMabrrAhSTwlDMJNKNJpUimGLOUvaUgMKBhLStghuvrKBqKdzYvlNTL1YkE9CVYv7ADn/j0NPsO7FB1q14ePESe3sdbObe2xsdjnQ2WcqH/NSR5/jpR7/ATt1FDyq+66HHme9OeP/S8+zbv8VMb8JbDlwMeoo/ceh5Ti6vUWP5wOxFbgxnMCiGN0XvcbLRRWGZS0ZcqCwfWnkFs1Tx4PJl8uUxydERbz15Fro13aO7zHdGfLnFVhpVKfavbLE56nJksIUpNI8unOc9/VU+cuJp/sOVt6JRvGXmPM+tHub53aPcl2+RoPjW+Zd5Yu04Whmu1z22LsxhuzWZqvme+fPYQoO2UqF9z1We2TuOqhTlQk3Sqfnk6w+zuLDH02fuxJ4Yw05KtpaEavdsS5PsJZSzRtoG5lDN15Rzlo+ffxvVrKF7E0xu0SUklXuWDPTWDKnLey0GmmSChLF7CZN5jVoVhj7dqylnU9emMnGSUBpdW/rXpHLa9DJMlgj4SxOoDMmkJt+ckI4q6kGOLq04YUUtxVtd6QpTD+Q4JnXviPdtBx0Rx1+YcQVotrElWrtoSoLtdESlwNuk2sCg55hF2camWorVBj18IwkJNcq7L9EIJY5WUQoQ3NmTEHMMTPxxvT31tjCwi7phKUNRn3Nq4xSneK7y+Yi05wAfQSB1hSy+eFLR2JdoTmsxfd4O+yVmLFvHnmIGPWs5vfj5oq6bULf/LL4mNrpHU2AwgLA4Whd1R4vzMWOR8VhKJ4Art49WJ7mI+fNM3y3RSzf1+DaSsrEDcFWkM+lXj+dsD3CB6b7RzZimrpknIKxtxnI7RhUc6IzO3xcGRcP/SsvXDBq/luX69ev83u/9Hj/2Yz92y3cf//jHWVlZ4YEHHuAf/aN/xM7OTvjus5/9LPPz87z97W8Pn73jHe9gfn6ez3zmM7c91mQyYXt7u/UDBDQfaN5pKjhc1+iqxYAx+rzVmzr2EOKbFL/80XYtaR/nMahpgBcv07l90PbWpl4WeaBsO0Q8Pb543zHVHr/ofvF5mT4c7r1Qa5vCEhO9iH6/0KznH8pA1bvt8rwNbsP5u4c5TZr2fnIjmnH63s/BGPk2fYqQ5O0vm8/D8Tc5bg+oFE2lHiHnMYjrVs67D32lm2fFe+Yqy5oqSOMMocs7sj0XOhuOHXtZAiokqNs4h8e3eDJGwKo/7bwBy6oSoGmzVFhGBWQik2E7TqjbdbAgTTCDDlSmfe+jPCfTSal6GpNrkeWpDWpcUM92UVVNsldQd6XwwGQam8n9SiYCANJRTd2RbiwS1pZ7VMxlpC5/LSlEtLl2DGG+bdg7KM9m3RGhZ6ugf10KJEaHDemOJh1LAU65r0TXwtx19o1QuwnlQMLX27s9/vP5R7m2ukCxk/Pa3n56vZKV/dt8+71P89NveZzPX7+D1UnD8qXK8JETT/PHa/ezW+QcTFIyXdNNK87s7mO77PKHu4f59Zv38IHZi/zq9QcA+D8OP8flS8ukI8VCPuL77/0C7z/wPJ9/+RR/ePNNbJiCU8s3ePLSCX7gwJNUV3sczdawk4T7565xqLPJl1tmZsf8wL1f4Mb6HMUk5dXrBzh54CaPdPb4zGgRgL939FmemMzye68+AsDR3gZdlfLkZIZfO/NOEm14x+AsT+6e4OSpa3zgxLN84uW3Cvt46Cb3HbvChb0FHuxf5HsXzqIrWFne5SMnnqazrtm8OUO+MsZe7rLviIzXZGBSKBYMqlQkI006VNjUsrKwS7atsHspNjci5L0rLQmLQWO3ihnNaJ90ddGVFC5p1+0lHVnmz0r0oxokpHvy/JpMciJtIs+9tAwsA6izmTg8aIUaFwLWAJtqku2RaJummnTXbaOFqbRZQjIqoRLW3L9XWOOqqRPMoNvYBs/WpBoVCkm0i2pEOXquEEVVbj+7w8YG1VXjbIYuTW47H72IQJY1dWP2W1EmZwe0wpZFk4PvgZV3bAMQwoEl42y52+m08HZtxBH3c5qObGI4vm1YRkUbZEJzXfy85EHedOTIfxa1VmzlxfslJlJuBwKhzZq5bVrFJjGLFwBss/otgMrZ9DDv+XleeVHuiC2MQLNKIjLAhXynm4L4/QsmaECoStMWgFRZKvNHGLO/8bKtl3IKaVtEOCNgmkhGkOi7GGjahn285dp/Fcv/VND4a7/2a8zOzt7CSv7Ij/wI//E//kf+9E//lH/yT/4Jv/3bv91a59q1a+zfv/+W/e3fv59r167d9lj/4l/8i5D/OD8/z7FjxwAayQP3wrUeiAhh3y4JNNZlbJC5u4FTF7zljUwzh1o3EiuqkVFprdfKKZzyoFpeTPshmRqw5JiEUEbEPCZRuNQvHlz6FzsGGK0kag9S3bohaVvdCm59WBqcx2iakLR1YY2quvUF9h4mCKDyoNADwemWg9741HXjzaepE8q2tN4Sn/SdRJIVzqCGF165/EN37VS3K8yAP09/X11nBpXnjrGUe+kTkK3LJVKTQsZCZNhjoGxljNMste11A5MhUiDSZ9rL6yiXiI+xAkj9ra9qzGxPJkxjSXZGYhzc5IhSIRRHotFl3XTn6GSiy9jvkOxORM6kl6FLQ2ejACtgsOpqkmElwNEP2wrwm8xF8j5KkRSW3SMp5UAzc0mKK4o5Tb5t0TVkO6LhV58eM16SIorBRS3dXeah7lryK5n0OT4+opikmIFxxRYGu5fCWHQDuzc0N6/PMbkuHV2W9Ihfv3kvf+f44+wWOZ8dL/Bc0aOymt/evJOFzog8kWftby6eJdcVO3td5rMRV0dzPDB7hX9z5U383QMvAjC2FcePrfL3H/sCC9mQp4fHuTO1vOP0q+zudvm/zr+dV64d5FvveJGPnxdH97+v3c833PEa6+WAJ28ev/VdjZY3L1zity88ih5qvvv4M2RrCd8zf56fOfsWLk8Wea1M+Y21e3hLZ5vu4oh6lPLM63fwL197lM+unqQ3M+HtS+dIleXaG8t8YPYiv3fxQejVvLGxxJVX9/O+mSt8+MCL/Nczb+Xnz72FpaNbvGP+dX7mhccwKdx99DrftPIaCrh5YUF6hi85OaQdTTVbk29ZzFHpuLR+dY50KD2/dWopjxdUA6g7lnQiTsDeYVDGkowt5UBTzio6W4ZiRlMONMWsppxJqDsaVdnQdSXbLrAKJ7cjTokqpDim7kvldbrlnv00dd2QFOluIQ5YaZzkkxFW0jl0aizVz6QaNS7E8XPyUhjXGals5MJsJvtWxjbyVYmIhatOLt+5QrPwWo8nwjYaEyqkgwICFjueNJN6LC8TXmTd5EwrD1AcIEgSRxbqtmSKJwBa9pGmEBBvl3L5r597fM63s58t+++BIDRFgHXdMGfGCnB00ZigLhEDRq/GEdtQmJrzVAM4fbQpBnvTiyddpkkOHxH0c6qOQrnexraKLuO8dgfYPGNnnEpFNM+pRDdqK7c7vpsLW0RQGPMUZnDr+5SD8Llz+q27Lp4VDKLhjoxpxMdjBRcflm7m6UYiSIVxNJXiNPvwhVRfJXj8nwoaf+VXfoUf+ZEfodvttj7/8Ic/zLd+67fypje9iQ9+8IP85//8n/n0pz/Nk08+Gda5Xfn3LfqI0fKP//E/ZmtrK/xcvHhR9hPdxFbhypc5zjTo85/ZSCpGeUATL6qdjzBNFXvvNPTAjosb3PYhVBHnF9zu5bndEhXf4LyaYCBqg+r12mOuGwMZjhPo9BjIOQ8sb7omBMAYXy9/LtPq/d4AWcK+WufnwYz/3Ht9EIUxVLi+LVY3CIlLt4UAyD3LOXVvxPP3INkZXwUqyxp7mXjmwgnshiKc5r7Icer2hOBynOykaMaBGKRWZbRjU+UUXKgqlXNXPoHcH993eMlT1KRwEiAW5dfxwsVWcsD0qAhMr3SKcdevqOQYbru6k5LtSPKZDz8rrz+XaJSVCb/uJOiiRleWzlaJAtJhhcm94ZfjZnvyLFU96d4xmddku1I0oYyls1VT51IZDTDej1ROa0vqxLytgnIg2o3C8Agz9ebFS5jdjGRH09k/Il/XJAXkmxplYHy4BqNIxorVqwt8/LV3kOqaT26cpp+VPPnUPXz6wn18/vJJLtxcpJ8WGNu8Bz+wcA6dGF5f3cf2sMtbOrvhu0/uHONXrjzC5qTHH+wekZD0jrB/Q5OzsrDDnctrfPDkF+iqkl6v4MH7zvHw/CU+8/o9vH75AN9y4CW+1HLTlLytu4XaSFELJb978c1weMK/uvwQjxy8wKUbi7w8OsT/tvwqV2rLqflVHj3+Br19Q7DQz0uqOuGJjTv49PZp3nr6DF8YzzPoF1ijYCul6ll+e/NOLlQWVSnUdopWlj+6fj9Hj4huzgdmL/LS8DDm0AQ7X1HOWEzXMFkEk1jQAiKrcUp3FUxmybcrdGVJr2XoGzk2scwf2GG8oKi7inxb2ghqkSalOCgsSjoWtri7VoeWg+meMHkS/k4EKBqxFyZLML1cGPCxCfmK5UwWnEp5VuXhMk6gPhTcJVp6SRuRmaLllMp7ZxMVUjlsJ5P1/CRcSecXVRvJdXQdmABx6oaTBqhkKaooQoGIytIonBs54TBl161LZWrWkyiGB5diW4JgdCzVE0eyWqFhCBEo3YAUjGlrLwJBVsdHTjyIMO3qbDspIlm0KZCqENbSn5u3gRFhArTnPD8/ubSdJhdwirzwx4lZXr/e9BzuALmNI1IBUEX7jeeRqg6AyqufBGffzzOxg++P7e2wzx2MGNFQ5DO1fEnM4T4Pea/GC3JHQNPhkJhsmO5cFwBubRqnQ7W/ayqqDaFP9leJM/6ngca/+Iu/4JVXXuHv/t2/+xXXfctb3kKWZbz22muA5EVev379lvVWV1c5cODAbffR6XSYm5tr/UCE4mMvbJq5i1hEIAIv7Qs5fQND0cIUmA0yPkn7YY1FPUNpfCwSPTW2YAjixu1TYwp5jNGDHF6qutke3AsfG6zbhcf9Szp1nliLnUzaOSexZI0Hkb6izl9H7+16A2VpF7YYZ4A9Le8NkAd93gN0HV1s5dgCD7pjRjb2Hh24klweJMxcRT2dfQeaqhIDE3U5EPHsEsZjRy4mAjb9vqeZVWtEv9EV96gsC0UstqpCa79wvgEQ1403PC5gXEg4zd0zkf0QI6yMbQpcIDC4ylgBeu5+W1esZHOpzFaeTUD6QAtzo9GVoZrJ0C7PcbKUY1Mt7dY8e7iQU3edc2TlmFYrqkHKeEnApMm06Or15Dw6WxKqzHeNCHrXAhAw0mouG7oq2hS6GzXmtT5YmCxC3VXM3LkNiyXJSOR00rHlC2/cRe+GPA7llT51pwmb7j+yQZLVLB/cppyx3HPiCqpW3NVf5Whvk5ubM5T7Kz5295OosSbvVrx78AajK31eK1M+uXOMT2yd4J6lVVYWdlmaGQJw38I1funqm9gpO3zw0BcZl3IfPnPjLgZ5wciWPH3+BB9aeZVLO/P8l2uP8MTOHTywcJWnrx3jsy/dC9qiexWXiyW+1LKiM/7V5YfQ+wo+cuJp2E754SOP886Vs+xLd9ATzfkt2X5eVXzL4DovbR3kxw++wMfu+SKDbEK1naOUZbfo8Phrd3N2uMIds+vMzY2wCegSlLJ8ev1+vuPep/jImx9nZ9KhLBIuby5QDSw/99RjXDuzQl0m3L//GjaTwhY7W/EdDz4ZJvOZc5rxsqI3P2bvSIauIN+2dDYt2Y5ic3Mg+asGuus1dUdRd0Sncf45zWhFoyuR+bGZ6DhajeQxup7U1SBlMq+pc03dlRSMapBKZ6LakI4kpzEdVY5IkfcxGYlt0GUddEpVWWE6qbTMVAo1KqQvu1cDyBJsr4MqKupBRxww14nJpm6dfk9sRJoI+zguJP0EZD2XeuIL/6wFSil6sVoHe+dz3JoJ2jZyK76IJkhiyTtj405WPn1FJ6iuHD/kOyJDCPnXPsojRisUToYq7NKpLIRiGO3AYN2QByGPvyFLQsGNJ03CPAGhWUBrforC5jGjGP/tl1vY0gj8+n1Z63Lj3bwW2/xorrdF0UT3AnFSt9eNwaRywMkXSNXG2XMHGF0efNwJrVWt7G9BPG86mxm+82Frjw8ikN+KdLaAv7pl7g/dZaawQLvK2qNCh+Y9qLfxOn6Vtoj5V1q+TIOr//+Wf/fv/h2PPvoob37zm7/iui+88AJlWXLo0CEA3vnOd7K1tcUXvvAF3va2twHw+c9/nq2tLd71rnf9/zSeVrl8RCOHvMU4N2+adraRBpO/ye4BuoWOjr0Qd6zwuWoo5JCEGwuLBmYqIxTQ3C7/0CcvT3tN8b5jMOeMmYKmA0BcUBOdZyvcHCvgh3C1fyl0ex/+79qIKxIbBg+Qa3urh5u5biZeNiLoe00xjUnUxUVrlE4ary4qMPGAUzmAZX0oXNCfM1TWFYOk4CM4EXOqEt3kNmobKpBb91YBhihP0GBr2+hddUT7TLnQtYh8uxxEU6Nw3iRumyyF0VhCbX6Cq2pQIs1hnYG040KEhwvffcK1Sktk32pSYH0VdprI9gqopY+1qmrIZJJKR64AyBiy3ZpyLidf3aOa7ZCMKrI9CQ2aPCEZSz6WF/b2hTFJYRjtT+muyf2qOpp8WyqolREQaTXYVFrLpSMoZxS9a5bNexXpLnTXLOUsVF3LzoW5kMqT7ShMarnj8CrXr+xHGYVdKcjymgODHa7vzXK8t84d/ZsYq9lbytgo+nz0gcf5mXOP0O2WLM7vsb4xw58M92MzS7mTc6EakB8acbVcYDHd4/nNw2RJTVEnjPY6/GHnMO+bucJbe1cZqAzI+akjz/FLV9/EfG/M9qTDb68/wI/e+xleK/vsG+xx6foSG1iuX11EDSpM10KtODi/zYn8Jl9uSZRheXbI4+M57GzFb1x4G0cXN+noih954DOsaHHCfmfjAXppiVaWx8dzXCvmmc0mDJaHIZT+a/pebpxf4uE3XeAb91/g32y/g2Sh5MLNJbq9gueHR3kJy6RIsbXm5Moqr1f7qFPQHYMtNS+9dpTOUFHMWeZmxvyPtdPMzY8YbcwwmYfOlmXY65F0hUk2qSWZSBvBfD1h996KdC2lnEuczI4IgitEr7GY0+JY7FjSiSEp3SRqAQ3JXk2nlNZ8qpDcRl1aTKZQJVS9FF0aEaTXCqs0VS8lqwx1LyPdHFLP9tDjEtPvhE4yVtGShlFFidqrG0cN5D10747eG2NTqfbWpcEmznalCWokYXqbZ0H+CsTZUlna5Bfj7I6T3bKmAR4qlX7V1qtMeCUJTy548FhXEgkxRuxFnjfzSjxv+VxpPy9o3USeXKvGNiMpwMh626cQG+1zHONImJ+n6ghUmrrZv8R1pQNWzAS66Esr1z6OBvnjxMwfkT3OMtcidiqH0jOo0wyr+77VhcXvDxrg17puRKwcUTpV5Ogr5eySwwKJFGv5Mbfm5xjcOWLAGtNkZMWRNk8mxaHzuglTN40hIhANTZGtxzE0KQq2bjOUPs9RhT7m7jPr5h4/b351mPFrZxp3d3d5+umnefrppwE4d+4cTz/9NBcuXAjrbG9v81u/9Vu3ZRlff/11/tk/+2c88cQTvPHGG/z+7/8+P/iDP8gjjzzCN3zDNwBw33338e3f/u18+MMf5nOf+xyf+9zn+PCHP8wHPvAB7r333q9pvCq++NA8WPHNVhF1H6/j/26xbnXIk4y7ybRYQmdYpgtmbOTphJZyngWcDkdPU8Uxte+9OQ8I/fdTDxbQvNQxiIy9w+ljpBGb5RnC4FFBaPcXGCwasOlzUvy5xMbDfxd3dQmyDdG2FvF+p8VbgxYZLl+oaPbri0p8GDmVPs6B4fOXUuFetATV7Qajiev5jGpofc9kKq2wRSnVzg4IqyhMJOEnl3uitexDIbIdkwKfUxImCp2EThI2BrppIpOPFZZDuaImNZqIXmPpGG03uYS2Z96pcAyFdcBUhWeSkLguBTY2dHupc9duzYKeVCQjMexJ6VjISYUuDMmwpBok1JlGFwZdWfrXS9dFxkoYOpOHKd+p2D6ZBWFnkypMrin7mnLOSoGDEvHo3nWF3VeQFBarIRtKF5hkTCgG0jVcevUA1YysW09S9vV3uXxmP+NhzhdfuYvPXz7JE9dPUNUJaxcW+PmLb0ZvpIzHGevrM9x78BqzyYiP3fsEf+uez3NfVnCwv8OT14/xxZfvoqwSfmjfs5RVwsfu/iIvXjrMz51/mJeKJbZMwa+ungbg4cVL3Lw5y/cefIoPLr/Mb1x9K6+OD/KDC2dRpeI9+17F5kZCzaUi21OcHlzj7mzKQZtaHlm6xNqoz1+dvYd987sszgz5vvk3eO3mPj69eZpfuPQQfzLcz7jKOL+6zIcPvkCqau7srvLazX3s3eyHfd03cw2TwemsZLVOmZ0byXOaWEbbXc5fW+Hcxf3UpSbrlZzfWkQVSmaCHelwU3ctnGgqvidX+uysyzGSQlII8g0FRpEOQdXQ2bSYDMoZy+zL8h7rAno3DcooinnNZK5xQtOhpeopKcZKFcVCilUIOEw1JleUA6eJWAh7rQt51nVl5f0A6Szj1qE2rjBLS1/1LAni27qWntM2E7kpVVaBOSSVqm2vUSqgRBwrZYwUiiHvkfL2L00EMLpQd2j55yurEWczvJeWRrZLaWEKY3trxRZKmozFh6M9QAryKrXYPj9fBTbMvduBKfQRKL9vSwCbIUdRJ2JHi6LlcLfy2UMUx6UnKUWrSQIQs3i2jCNBEZBzINU793GqV6iSjuctN4dOO/T+PgQw6vMqYwbNOdMh2harO6SpbBPPzZ7t9XOdB2PTepBO0cIDOD+ft1hCFVViK4WfQwM7GoHQ27GpvntMIH+imozpaGUAwrZpKezzYYPcn/UV2O15P5Bg/tnQt4a5v9TyNYPGJ554gkceeYRHHnkEgH/4D/8hjzzyCP/0n/7TsM5v/uZvYq3lh37oh27ZPs9z/viP/5j3ve993HvvvXzkIx/hve99L5/+9KdJoqrfj3/84zz44IO8973v5b3vfS8PPfQQv/7rv/61Dpegou5uTuuCuxcusI23o2f9zXIPg41fApCXaYop9F5QoKrdwxeAKwThTv8CtKqgYu8ppr/9Cx0/dFMUddhHiyZ3zJgHf4FNjM5X0bBmfr1Yq8zlAIZ9xtcq1g2zTBWtRNfRP7j+RY49XCJw5zsP4F6muMfpdPi8qpxn7AzEdDupMK5m26BXaYwL/0TX151vo7VpmvwSJd60tUj4t9+TicQbNtzE5F9Y16KsCVU3ldxqUtDkONGE0x3It4nzPtOkkQGq65BrZb2xRIWcJYwc33RSmQx93pGxLgVArqseFQ17aC22kwqzUtaoqqbqSeivnM9DYUAylu4cuqhQlRWZHqDqJ1Q91aRGpZreqiWd2NA3us6U6Ct2DUkpIDMdKkYHDabSbN+p6N2QfEishDKLRelBPVlQJEdGMl+OU95x4gwXry+jD4zBgF4uSDZS8ryCqx16h/eoiwSWSwa9go/d80XGJuOtnR0u1YZnR8cwWN64tJ/l2SF33X0VgI5K+eljz7BrS5SFj5x4mpPZGhOr+a7l5wB4a3eDA/u3OJwkfGa4n25acX00y6/dvJfu0oindo6TrSeYHEzHoioYmZyvtHxh9QTjtR7zK3usbs2QamdHxgnrIwFr93WusLPWRw/leTmSbvGmfMzK3B7/2/2iKDG2FW/rbjF/QJQoMmUYvzFDPyvp9yYMFkboQvG/3/9XPHjoMu/Yd45qnKInit7MBGYr/vPmnXRmJ9hLPfJtxXw+xmSQ7misY+U7G4ZqxsL+ievSg+ShAr3riCbjSByEqivi4Nlu83776vo6VyRjAYH5di09yktLOeNaVO7WVD1N2RdQZ7WidgUuk8Wccs7n31lJs8ikqIZUwKKaSMgZrZzThRTAgLw/SIENVd0I4/uWfd4p9k6tA3JSrGOFncwaYBRsuRVywFokNG0JjI6EJ5HiOZzNiIsikwRbiaC/ynNxVn342NSRrQSfTxgUKYxpEQiNlJtqS6R5zUdLSPkJaUau2CVEkYwrcHGA1hZFW3B7OtzrmVWfWhQ7/mEOE5us4txHD/riQk1rJRJ0i5xNZNc9gHds5e1aBco42+Hd8P9o3g7t//x5eHLG7y7K62zNy1MkVNNpxR3SR54iAsUX2sThcQ/gmnxDtz//ExNUEELRMTgMKRAOhIa+14omJcKFyAPI9M91zJZ+heVrDk+/5z3vaSPr2yw//uM/zo//+I/f9rtjx47xZ3/2Z1/xOEtLS/zGb/zG1zq8WxaVJCgaoBQ8M8caBtoZ2qFZT0NHD4encgNr5B/cmGaP2B+RJTBNbmG8f2jpRgXg6h9IbPuFcZ5NyIFrPaRTHlE4+ciT8eESHwKup9aNhKJv2T51UgBeFzGm0uMHLc57cS2KWh6iv+axN1u5LHlvoD14jEG4ZxO1RnVy1wM2MopeW82H7R3IVFkHTO0qfZ1Bc/uzRQGDHowmoBOpgqzqhg32EjaWxnP0YXFrUWXtlP9dVWLpWOO9kTwneeryYEyQ01FeSHgyQeW5sIFGPH41KbAzfXGSayMTWJLIZLY3EjakkraAaiI9dm03b8CyC3+ocdmwjcMCO+hiutJ+TXnh4DSlnEvprI5BKeqOtAm0qYDVZOwmP2e/qtmcZFhCqim7TpzWWIq5lHRs6N2oqfryHBQzmqSwZHuGOpfcyeGBFFVDvpEANUlpMQUknZrsYk62Zyn7iu6RPcZ2QLZnGVxQVAMoO5bJOIN9Fb1ewTu7mzw7N6a80BepvsSSKJhsdTh2zyrHuuu87cAW/33vENfHs/zy9fs50Nvl8+MFlpMdZpMRr5cZql8xl405kq+zb98OP/vyY3zs9BNsGx0qw5d0ToUhdb71/71+Dz+8JHnX7+7fJFU1fT3hya0TGKu4sT6HmjUs79/hgdnL/Hl2iuvFHHQ3+XLLN+4/w1+pu9i+OoOar/ihpTP8t60T6F7FTxx5lp9/4W381cwp6BiW9kuRzrbpsJxUaAwrOqOwFf9x9UGGRcYPHnoSSDmUJDz04Fm+eOEO0l3Nwh1b/PiDj3O26nJ1tMAd8zdR2mI6lvF6j3SouFgu0Z+ZMJw3HNi/xYWbS6h+TbKRMj5gSMaa0T6NnoC+1CGZSM7q8CAoC501KOalACYdS45iZ8MGx0DVTqtzLpWWkJmi6kGaiixPMZuQji1VL6HuKDqbFSaTgidVW5diYRitKOZfL9FFTTmfk21OMN2MzobLC+6K8kEyqYJEmO2moYCMsqKa75EU0jHG+nlgNILZAZQTfO6evHMFyqhgn9SkDDappVsIAiYnpRxLK5TLh1SVm0eyBDseBxIhpMP0uxJZMHWUi+xskVUOwIFKUmztIi21s58KAXueafJjs86mpqmAVf9Z0KSMwtx+/HHOm18cWG51mvLn7EPVWrfnOxB7HaqrG1mxwLB6G5joRr3CAycPUuNwsZ/PfBpBVQVGLoxpmjHz88J06pVc/FaYN+Qs+sXNycEpdhXzfpsw/zq2WSU6tAGMo5Gt5wP3nR+7xxqOmGpJ+gC+V3TAI37ec/N5kzoXg9jo/lmwPvUhJpPCYCKt6a9i+ZqZxv/HLXFuggdN8cNnp5JQ/f+VagFGcKyTf7lu95J5D8Lngniw4W/y1HGavJSpmxazo5FCfXhgov3E7GXzoWqv573J8B23soX+85iN9Nt6QOzX0Spok4WwRqJFf9Ffj9DjNDIuzgjjQVx8PYKh0sGI4PL0YsMs7F10L73BCMYgEYCVZthi4qqYvacHGCelkGgYT8J1FeHsSpyMTt4qXvFC8CpJpKuDclppLrHde8jW6U/aqpb8xEyqr0M4yYUolAu/i5PnjHxVoUYT9N5Y8qWMdGQRZsTJ5RivJ+dCZxMJBfn2gLaTYXp5I1LsjKUyDuTmKbabO/07uSc2E1ZRlRV6VGK6GXVHchfT3ZpiLqfOFXU3pZhNUVZCiNUgw2ppG7h3pIkQKAPD/RJyrHMRAe+t1mS7Thg6cX2K7xmTXcxJJpZyIMUSkwsCGOtcoSwUs1JcwVijhgnFjZ48Kmf6VLNy3XRqmD2+zaGDG8ymY17YPsxnxwuc3V5m7co8uxt9Nooer+4e4O6s5o78Jqeyip+443HypOLhzpDPXL6LR4+/AcDhJKE310gZfX60Ev7+4aXX2LXCUn967wDv6m3Q1SWTKuWdK2c5uf8mdx29zs31Gf78zH0MBhO2y7ZyxO2Wv3z+AX7q6DM8cuoc7z70Ko+P50i14dTKKgkKmxu2iy4fvetJvmHhDL987QE+efEh/mj3KB9cep1fXT1NrlKODjbpdwr+cvduPr0nBYPv7t8kmymoe5b5fITB8lebp5jPR/zei2/h3UdfZWZ5iKrh3W9+ntOHrjHa7KIs3NiYZWVhh/65BHvXiNlzrr/0glQ9p0OX05jAzEUBj1ZLWoLVMFrWTJakel5X8mzUOZT9hHzbuCIpd/9zMLli76jYvmQirLTJpL2lZzK1sYz3dZk/W2I6CXU3JdsRm2AVofKayuUqVrWElB3DjpPXIXH91F1epB4Xkts36Es1dJqIzI4viul2nB5kAzqs15PF2c3SSYDlGXTyhqGrjXR6iaM4yoELb799PnIdOaqe+Yp1ZT0LFUXllAdW3r6GPG7TRCMAX6QXPvP79ItnGSE6nm6HoqfJDw/6oBEG94WSPlfP2ekA7vx28dyCaucsJqnMJ/F8HRjRZu5UPgzu5+TbVCuLPJC/Rm2W0sb3L1xQ1f7xgNQzvT5iNRUh9GCvqVCOOrRA06o4pDk5wBizmDEMcEyicqkGLRBqRUbJa1N6NtILgnuQGUgQdy6BnYyikZ4M+58Wnv5/5DLFHvq/Y4TfAlA22i6+uN7zi1+UqWPExSvBU4zB0+3GRQRC41BytLQ62vhl2iua3q/WjTzC7dax0efeEDj5mFCdHAHi5pxUY2CUiopX3OKqzVovnjVRcrj7LLQCVM21CkA6bYCe13c0pjEKgfWMQvWeqTR1U3UYGwp/rEDlS5FI6A6Dp/ltk+PiBMFVkro8SuVCxh33Ekb3Y1I0DgKeoXT6j04axHohcqXkUnhA68XDfThpWnBXKdCJyPkkOlRvAkHcuBpkQVcuHAskf7GXiSbdRHTp8o0GGGEs9WwXXFW17xWcTGRSTUcGXRlhIN35ThYT0kJChumeyK8A6Moyc9mFrgdSSFPMaSYLWvQVEymEUcpS9Qi5j0kBuoLx8Qpdwu69sr/xwZp0R5OMFPXA8PSkT3G0hK7B5JZup2S5s8dcNublM0f5a0uvcHWyQHW+z/tOP00yVgzSgkxX/OqN+/idG2/m93aO8sxkhffPXOZspfnO489SoylshcFyeqFRbhiZjNLWVMhz2VUJN03JY72L/Jurb2KtmmWy0eUvrp3ie+bPc35rCZVasvkJw1GH0nxlE1t3LZ/ePcwXL53g5b1DFDbl3KuHeP/MZUDEv9+3/LysazW7O11mBxNevnyQT+4cQwH/+vKDfNvgKkf7W1y8sI9RnfP4eI6zlebvH32WfGHM2ZsrfPzmvQzLjLcOzqHmS64V8+zudsPfb2wvoUeK+49dZt/CDqVJGC+BMRI6Tkdy/8t5Q9UVsFf1BeSrUjFZthSzUHek0EUXIuyuKtHuNLm0E8x2K5LCUPYVc+cr8l1DMjJ0V5XTRVQkoygc65hvo5U8a9aSjCqqmcSlbIBNFeOFRFQCtHZSUhbT72A6AihU7aqjy0q+9+kb/l70Mmyv4/J+awGGTic1KBgoxEnreSfZ5RI7pQc9KYVtBHnPM9dnud9tgRCVpgSNREsTDfMqCZ2ssdF+XoCp/Htnv4zYmrC+TqKITkyWeHseRZ6CkLlqHac9B9nAXqlOp7HXvm+0VxKBhqRw86To3UZzWNTIoAU+45aMXph8ag4OyhwxIePJDkdgtIp9cNfHF2O6e+J/Wg0zIqKlNd/6/cQh4qkI3y3d1eLj+P+myS3bWHe9fRh7mhgK1fAeZLv9+pQHjxVCC0E/F/swtWOhY41pOYcmHB20J79KtvHrHzQ6MBaj6NDZJQ4/R5+HyiN/83zyaczexQ9KvMQXPv7eA9a4W8s0AwqBRQoaU24cQXx0WrA0fujjMHUSPWzuJ+gIRhqCYds4tA6Nd+WvT5zIGxhG24zdG714n9H1awCulRfBSUeEdU10bb02omdsfdusOAzkWc8kui5aQ5KKrEQojoGQz1iWTejfsYWSIO700CAYVVsbMY6WRsrAPws+cdx/hjMIkSGSXtJO5idN3MRgRVbH5TqSpq4q0jWQdx1gbJ4J6+HOS0S95d6pPAvJ9cHwuUkwHbrk+LKSSct1bVDDMTZVAgx9F41cWBplBfiZVNhEz47osbA3+doeJnXHqC11T6NqS74j91yXls5WY/zTvRqrFeVA079WMl6UcG9305CMZHLsrlnsmT7ZnjBSk3sKxvsNurBk1zLKWYvelGuR90vSsTBVSV5zZ7bJTH+CLTVqrmS02ufMtf28cv4w9UzNJy89xNq4T7FgOJ2V9A4O+YGFc1y9ucCP7n+JPKl5z8w5PvfaKXZMwVO7Jzicjnhp4wC5StEoXto8yH9cvxuAbx1cJ1MJKZrfXL+LFM2KznhhcoCfPPQ8h7JN6Fe848A5/mD3COUw45GDFyg3O9hhwub6DGerL29mu4sjTnevkPVLfmjpDE+tHeWOU1f5+NopuaZJzeEk4ddu3suprOIbj73Gjx14kRMH13hb/xzfvvQ8y/0hv37zHq6N5rCDmrPrK7y8e5CTqeFMmbhHxXK4t0VZJTwzOs5PnniCc9vL9PoF9TjlpdePMt7pYBN4cfUgN9bm2NnrgoJynDJa0dS5f08UurJkR4SlrLqKasbwffd+gaR0jGRPchtNprCJFEt1Ng3jxYRyTqrrs6GV//c1dVeL5E5fS9i6n0hYuhKAiBVgONyfSk6tVqS7tbDoLte3s12H4hdnLMJvk2qqhT6kWopYCpeu4VJJlLXS47qsUFUVnK6mSC+yZ8aid8aOwXI5k55pLErY2rkVpFgbJLSCVI51URVF1HJUwJ8qa3FsXfRD6UTsm4/yQNRXGRciTlC9bmPLPavm57zSgbGQ5+fsn6Vt8+MWssY6OxtdVuNY0qijjep2m31EoWLrq6xj1st6BBrNPbWJrq+zr67wNGxT121AF8+d7rNGPYSG0fPzZZg3VcuG+u/ibi2t++aBWQBj8SHtrQDSXf8W7pjSlxQ9xrQZ7/TiHQJ3jFbE02MaSxhzTGDYqgqAtL2NA6musjsQZDEw/wrL1z9ohMYbgYYu1lGrH2gDrhjwxA9ldFFvSRyNPIG45VBrDH4f8QMSPCTPUMkxbk1KVVFol2Z8/rixhxhvG4FJ3zaxJffjx+5/ewMUjzV4hTS5K96weFAHjfaXP6avAHS5OFIF3XjW1oehbWPAmqq9aDzhxfOh3dp5xn6d6HrFSebGtvJDvKGwzhiFa+VCQVJV2FxuW1WN5qI3ku46yYtqG401ty+VJgIyXbGNchNMy9D4Y1buPFzyuHKFPKqqG2Doi2ccmLOJVG2GcWhXFFObRlfOdaiQ7iwa28lJ90omC4kASp/TqhXlXA6JIh2761EZbCa5jcVcTrXQlxCe78ahleQqTgzJqCadWHThqkoB09HUHQknVv0EmwqDqCciu1L1FLq2UlmdKNKJRV3vkG0KUChnpUgmmSj6N6Dc6GBSRdW1mL2Ux0fHeMvCeZKhIruQs3x4C50bbGZQhaYep4yuDOjOTfjN9btAWc5WmvmFIat1SVkn/Icbb+aH7v8sf7J7N6f61xmojO89+DSlrVmtS75538u8b+FFni2kCOVXbtzHz194M1fX53m5lGu7lEpu4c1qljyXApRro1nSXsmTF+8IzNt3nXyKk+mXD/uMhjlXq0XuXVzl5TKjrhLObSwzrjK+MJ5nd9zhpinZ3O3zs288wsTKGL5v/g0+fubtHExS/tbi62zs9dkad3jgwFUWZobslTmf2DrBuWI/RZEy05/w8sYB3nfwBfp6wr8++zbuX7xGcbVHf26MAo7sX4f5CltpHjv2Bvvnd8h2FGm3guNjikVL3ivRFZSziskkk9zFXIG2/JeX3xaqqW2ChKxTyHYV5Yy0ELQaaSXo3pt0In3Kk7Eh37V01kvnfCDvDlD3UrbvzKh6CeWMk4IKrfGMFMiUBlVZqtkupuNy3jqpdIJB2vzJQyrdX2wmecIUpWgx1jXWCYmjtbQFLKRNoX+3lLVRtIAI6DhnGjfHpFljc+pa7MhoLEA1ERDvIx+izpBLUU5oqyd20dZVsCFBODu20dOVxx4YuvMMTQVapIebY0JYeBqs2QBkw7nVLkRtafRuFU14Pk2bc/LzlJ8HpjUFPTDzwucxowjNfGBlH9OpW2H+ilOoYhbORNv78/L79nNHzFT6xRfTxDmUKpqPY9ZT6zZpFF3fVhFlNK5WPuH09tF+fPGL0lGBTEw20QBFFaW2BWmdUHTVXLdY1qeJrKrw/6+2CAb+3wAa3c0PekQxs+cvqgNGtxSUxBc9fnCnbmBYXMhU+Zy/2JPxN8YDqyR60KfH4lm1+EWKJWfih0+ptgfomcBY+8rnjfhQddQUHZgaK83+YrBcNy+iikPe1jbUf+QlB+PkAVIsYh4bCQuBhYvD7dOspfttfX5M3mlC1j4Uo7WEcOuq8STD5yIZoTq58951ONHQAtAVrdhKwsUqSVyxi0F1O5KjqKWFIHXV2OBgaCSPyncLknaI2lVT2ibZ24fZnUal6nQEZNZG+kg7cXFVNADY+jBQ6pLqJ4WAR2eQbSdD745DBxmTJ65C1OVkKUX/ylhyGlPR7Ex2JsJO+sfdWEw/Dy3adNmA+XIuJ92r0bUl2ysljG0sxYzknFU9140jlYlF11B1RLtPV2A6imxoULWsk5QWXVuKGUXVs5QLhmxPBlIcKtEFlD2pvNWVpe5bDh7c4OUXT/BQZ5e3nj5D9/Q2ma6xowSdGe49fhU9UZgcumnF1ZsLPLJwkQvFMvt7u3xq4028bekcRZUysQnfPXeBy8UiAIeShArDviTjie07WdI5FydLXKsr3rFwlp8+/gwfu/tJjqYi/n06KzlXKZ5YO853H3yGpyYD/ubKcxye2ybpVMwd2OVNd19gaDt8YuvEbc2FX3RieXn3AC/eOMinXn2Y+cEIaxUPzV/ibd0t3rbvPH+6fQ9zgxHdTslbu034XGWWX772AJ8fL5AkhuNzm3zb4CqL+YifPPQ85zcXGVY5p1euszfOObmwxl9unOKlzYPce+A6uaqoBpbxjR71wLA+6jPXH/OxU1/k+Y1DbI27jA/WZGdzimFGZ0NhL3epOxJ6Vhspo4NWBLz3NOlI3qlyRjq62AR6NwzpyNLZkk5G+a51faFlHd+/XFeWzqaANFVb0rE4Rap0Mk+rhqQwzJ0rpSe1b/lnISkNJtckoU+1wuYpdS+l2N8HhA1MhiU2T5zUlG20G7WSDkwTkbeyrpjN5pnkZO5NRBkhl0puX5TWKnb0dshvW1bS7ckXrTnn2k4mkeSMFUe8EsFyya12RRZVJTnTRSH52ZNCohd1FGpNoghHrIHro03Gtpst6MbWhhaoYW6JgGkMqrwqRbzEZIez53ZSNHOrjxy1VC88yHfsmZckCzmbDcHRSnmKmcd4CaD0NgDPX4eY6PEESx3PP7aZjyN2NGYZW9sHEoJ2bmJc4+DuiwetLcUVv47Ph4yu623Dw54d9IBUN4DwltaREPBBUHqxjRxPCIN7hYBEh7B4OMZXsXz9g8bI07gtmo4p6NsxhPF64SGLbnB8oWMPMKZ7/Rj8OtAwaf57/5B55qq+zUsSn1ML+Hpmj2jfdfsh9i93rHkYvrdR+72kHSrW0XEcuLNV3dq29bL7j73hAme0GqMQjItf3LGVdi+eZ+ACm+kMog9xGIPPNfT3tsnzaTzp1rV2INYXpShn4EOXBl/U4llIa8WoOibQFlHIy3tsfnwmevELV5yinZ5iXUOv03iKcW6Kv46uXzXGhE4UKk2lW4VjHkNnnFKKVtDahdFqTCeViU4rzEwXVUhVqR5OZPLSShgSz5goJZekk2JSAX1Y20zCbkkKKSJIxjXpqMZkHhBI+7ayn5KOJP/Mf1fnSqR2LNRd3wqO0G+4Gigm84rxgpYQPDB/1jCzMGT3Tlk5v5oxOVJhMjADKbpQBq6uLaAPj/ij3aM8fuZuTg5u8rcWX2ewNGR+ZsTLVw9ieoZkrmBrr4sqNS/vHuI9/VUUlvtmr/D8zlEWeyP+cvsUnx0v8P6Zy5wpE/7vjbv40707+J3t4/y1+Vd4sejwnbOXuFbN8aer98itwzKjZAL+xNYJnhse46eOPMcnrj7MejXDQGVcuLkIGxlbN2Z4e/8Sf3z2ft47d4YvteyYgtP7rvP/WXmFRw5cRBfwt/e9jF7L+MuLEp4+kG7ybXOv8O1LL1BUCV0lE/sf7x3gGw6fYTYf8+zmEf7e0WcBuFrXfPfcBV4qc/rdgu+ZP8/7Zq5wdGGTSZ0yLDO+ceUMRZ1SWAkTm44l3dZMbvbYHUuuXnGjR5IYss0EXQgorHqgS9HYRMHisW16VyU0nY6cA3C4JBmL5JCu5JmwGqkmVvJ3Pciou5qyL3JMyqk57B4RZ7DuJphMkQ7L0N/cpF7IXibbuisAjkwYcFXbkJaiSwlbp3slybCWtpdZIu+nY9lD/i+g9sYo49oEOntsu5kT25eCmGquG9py2knRAEdwoLMBBcoiNiVu/Rcca9d8wFixt0kqNsvaxgY5uxWKZWKH2oZ/nO2xoQLba8U2dlmFQgo8SAnRNBqbpFSTRgNNvnii5fgtHUNPZIgzHbrK+PNM0yYq46u4/fE8sAVJU/L55Fo7J9qfVwRKoU3ATIdz4/nHOedhHvHrOvvemnP9uBzP0rAANKHkCDgqDzjduYdju8UXL4VhOYDWimjGIG+KIfbjuQU8KqSLkW1C376dYHs9d6/dOYZ2iOHY0f5ibOI//yrZxq9/0BjfFPe71R+ypW01dSOhqSqKb3KrsTjtbfzDGGtOOYAX9uO9tHhccUcVv0wXmMQeS6y/5cPEcWValMcSflxeHGnS3nfdyAYEAOSETFG6YUW9XqI/RuqMXXSeKm2q81SnKdZogcqYBfXgMH6ZdGTkHBgOHVpA5CN8/9jYOzROiy11AFxr7HjSXH+XBI9S2LIUOr8oCLkfnqVtveTeczVNv1nrjL2i6Q/r2hGKB29CwY7yHW8UMmZnfG1RhGtpfdJ8PO5OLuExraXbS1XjRXOVf/6c3JAelwIw8wyTaAGJrupajwqpqnY6dL77g/TRNdJZozKo0lD13SSZpy4cZ0MPaus6SuhCQKJFmEjfSzrgdAP5jqXOwWooZuWLyaLoNqYjy+xdWwA8+rZXpM1dYTAvDEi3EuhXWA3JRkp6fEivX1AOFP2rimSo0cry8tWDpHsKi+I31+9ifHGGblKitOXAyjZ1qen3CtSgYmfS4bc2T/Kds5d4KN/gQyuv8J0LL7A96bJd9blYWf7H2mn+1uLrvH/mMjfHA46livtzqazfqvv81BHRaXx8vBiEvr9p9jUO5NsAzPfGXB3P8zMvvpWP3f0kP/jQ50gKeHGyQjpU7JjbMAhumdU5NycDAJ66cQyWxDmpuxZVaH519TSbdZ95nfOXO6f46WPPcMOlYHzL4DqPdbd5+9xZlrrCgB7trPOF3ZPs2ZL7soLFzohdW/ILF9/M1Z05zt1Y4fTCdf7i5ikWsz3uzG+g+xUPHL1MPV+jFwvUtQ7/8rVH6R4csrvVo5w3mAwOnljjpx/9Qgg73/PgRdZ3+9gEsi1N3YHeDUjSmskyJKUwycpKsUzVVYyWEyaLUllfzGrSsQ1C38VcKuLeHU06rChmNdVAqvmTSUUylgkuHZbYXo6uJFxc56Ixmm47NjBpHJJyNicZlSTjCsoa28kEvNbSclOYzKjJQjdverm7vF7fk1pUBkTSSjmGUY0mUpSmfAFP0rZn3lbvjhDnvHQRDMcyOhth6xo7GjcVud5O+nxsz1IWpctv9+AudXlq3vbUkqKTpJIqUxROfscBiqCpG4EmawX8eZ7D231foAOOnaNtG5Vq2h6GRzyaH8Jim7C7286fS0hZqutIFs62nWu/TTzP+vkrytkPRTk22ibW+I3HPw3i/N9OAaRJd6pbgK4p5omO7+Zh5Y8fYYHA7EXHipt8hJ9EB+1Gn/oWcIpFyAJPDE0TNNHzNh0y98+T8vhmCvf4MHhI9foqlq9/0Aht72KKcYyFOG+3tBJVY7ZQqUZ+J15s9MAHz8w0x532mPz+Yk/S0+Ue+PklzhdxIdTg0cX79fuIP/cPYCxsGr+A/lxCnqMftzdYtgGPPtwd55L46uOoU4udTMBXK3tx2nD9aI+nJSERsZ0RU9y07HPXwANOd58COPPamUxt619sf30jw2A9KPNFNxA8cMkTEabPOo9UJYmEnsrSsQMyVpu6fCUvhVBWMJ40XWXie+SNvIquq5EWZtVM3hjaRLfuo7Q2kxxI2xEWQLk8LZNJkr8ZdCFLZJKsjWhCZim6cOFol5elKkl5MJ2UZNIUEdSdJFyHYj6XFm4G0JAMHauZabKRpepqyVEDRvvcPbTCSHU2JbTYXZPbYVKYPDMHCj7/wr2kI5gspJhc9PzyqxnVwNLdsPzkoec5Nb9K3bNM5hUmc5NsYnjwobNkqman6FLNGAyaj971JGvnFjm1b5UfP/gCnU6JUpa3zpzjX555lE0DfzlaDkYvUTUvTw4z3Gucm05S8W+uvAmAC5Xlnb1r4bvVcpYf3fcyf7R7iN+6/hYmDjGfnrnKvYNr6EHFJ7ZOsKJB1YrSJtQLFft9C8wvsazemOdn33iE5dk96knCH+we4Y6jN0hmC1Y6e7wylPaqb595HYD9ScpTkwE/d/5hAK6Ui1xcXwAgVxX39S/z1Pig3EeruFDOcO/SDRJtwMDLGweYbHZIVc3rkwPURcJLNw+idhPuW7oGhyZkmwlVrVGZIdlT1D3ViI4D4xV44cIRTKkpFqSaunfTMl6Wopm6KyFp6RYkILiYVeQ7hmQkRTIosArSoUEXIseT7xrXJUaeKV0a6QSDOCm6kknUJBplEaY8ddXbkcaqci0FdeFyfZ2ygskc2PPhOmNFhNu/W0q1C2CMwfY7YeL27J1/h2xdNxJX1so7qRwgcvYAHDB0nTlsVTZzkFNVUJ7RM67vvVeCcOCw1UfZAyBogR/fLQotNkgcbb+NdU69K2jRUeGjUs5WT4MOH871RZnRdUm9fYgIEG+b43BxnCcOLgwfMZF+f/HfgbyhKZKJlTwUzVggAoK0e2aHexixl35999NIGoWTbq6rP27rOHLfiUmMuDbA7zv6WwVJoKkK6ZjIKp1djgCjtB+0Lk++DQZlM9X6fwhFxyBeRX2qcSAxApCiDRl1nfkqlq9/0DjtUfibNUXFtljA2+3DPwjQAJHbIfPIe2tT4CoCMLr1wgKNFxQ8rAZYtJYqovs9hZ5EL7b3fOLjxvkk/iWJDU+kqt96ab1nU9chbC3yCc4AeeAHgXkjdX1X4zCyp/WdjqFct+gBdWMJkgbem/LXx4eMYpAcjEZ0jf1x/ITgw93WBAkfW9WhWMb6cfoxVJUbdwP8JY9RS6W1UtDNm1ZUHjS78Lk1NYyLNhh0RlUlWhLsjRXw2OsJy6GUkwEx4Tz0uCDbGLqeuO76WyRfsqxkwgPquZ6E10rJWdTDgqQw6OEkAr5yv02qqfOkuWa1CWE+VUk3DjWpQrhNl4ZyNkOVNdl2gaqsm+B9niUut0vax3lGUReSu5hvG+qe6DgqI+0EB1dr0qFtomtKdPqUge5azWg/1D2Lna0o7p/wL888ykvPn8D2a9KRA2J1wnuOvMId+SrPbRxmeKNPZ10zm475s+EKJ05dY6Po86s37mOuM+EnDz3Pnanl++94gmv1HN/YW+OJ8VGG2x2GdYfldIcfvuML4VG8sTFLcV30II+nCv+GP1f0+MDsRQDeO3OVRxYv0tUl/2H9FCk1N8o5FgdDeknBL7z6Nt70wDm+cPlO/vrRV/iFSw/daifixcKgN+Gh2Uu858TLLKV7/I3583zvkacY1jnDKuOz4wU2zYB/fflBAB7p7HH30ir/9vr9LCZ7fPTkU7xaprwyPMQ9WcUTV04AsFV0yVTNtw2uUtYJSbem2M3526c/w9PrR3lL7yLJrrznd5+8yiubBxh0J5SzhslejtYW07XUmeXy9jw/c/YRynlDMlbkcxO6VxPSPQW5oepKwYtKLMooxosak0NSQXcVbCI5sLoUbcbuek05oxkvJXS2KpLCicOPLSYXFrLqJ5SzKTZx1dWpkiIXJXZLF3XoFGOzVJwdY6lmM2EnRyUmE6UAAF05Jt2pFQhAdJ2c0qQR/7ZW2HotzL3I6yhh/ctKchStTOh6NMFmqev1rsQGOLusCpf2U9WOgJiamI2XXqHJkfPhYAcQVZ6FCmIVojsRExbYIxftKEsHUG1jH0FyKX242J1jw6J5EmFqnohlcbwD6yNZuomMNICxdtEXgp0IwM1Hp0KOYzQOkLlFR8SFA1EtGTgPgHHzRQzqqkoaKsSADBqAG8/f7toFsORDy/73NKsZ5hTVgM9p8He7JcYTddR5buoY00xgc39o+mVDowWZps15RoBQ1klaFePxfuNwtS+4kaIce3vsc5vl6x80Rmxe62H6Up5EREUDbe8hYgS/pBBm/GB6b8nv2z/kMfPp/47DycaFLmLAGFcBV3V7e/+SxUDG0/WBqaINVn3epB+rD194Y+GP6RkpVzxjJ0UIcVgPKP01imn4KLzbnGPdepjlfPzvyIv1ulqRlyt9T3FGNWm8ZaVlXT923cgYhMRn78F1nRRFkookTqStFgynfx5cQUtgHUAMoqf1i6Y62nodtzwnNJJ33qHI74gToErHZlZ1yEcMye/+usVsr291VhkJoYGAuiicBoRcMemTK9+p4UQYj0RLjmNl0F6XLktdX95KmJZuRjKqhbXUDdOSDitMngoLWdQk4wqTJdhMM1lIRctxXJNMIPn/svdf0Zol6Xkm9kTENr87Ln1mede22qHRaHQDhBEMFwdAEwKpAYdEi+BwRhoBwxnMSFfS0oUutHQhcQ0pkZoRtSiKAs2QICmCBDA0gAiCQDfaAG3QtqrLZ1VmpT3uN9tEhC6+L2Lvk22qmmwMycKJtXJl5jm/2f/+94544/3e9/2UYK4PxBVte2GZJvviaJ29KvpQXxlch4AJNU1szkipMi48thX6qb9TQy+/ryYdoYRq3/D9F7/MR249xlPNJTZ3BdzZR1Z00XG92WG3WHH7aI61gbfMr3E3yIFdKSLvrFb5nO3srdgtVlSmZxUH1mM6awklfKkreb6HIpUF9UK96Tt+6egBvmNywJGf4Ezg3fWKd0xf4sPnnuLF5R71bUdhAg+cu8P/75m38Z3nn+MbjVgFvn33efpoudVv89Jmj5u+4/n2PD+59wx71ZoPTPb5l9ef4NxsmZ/XR8eD87v8y1uiuXyl22O3XHHd9/yxh36H/+7ak7R9wS89+y4AvvP8c1gbOX/+kF+++3asifyDm+8mFvDwmTtsuQ3mhQk+WCgiWztr/vQDH8d46UyxPd2w+LJjsrOh2+tpjmq6bXHCm6XLJE15vcQtBTDaDoyPhAqKtTCNBgiFLmI+Uq5E/tDNDNWhXPvr845inNNoEHA40Y2Yzsf9XNjE1H0FyB2QQilgwcRIcdQM946WpLstkdKEWY3ZtFJGX1SyuTMGMbY50QvLDll0jxFh5H0glmJGM6NOKbmakWQqyVCnyQqAlij1w03qAUxE3VCnjNeqFP2kbtBFux2HKTQ9LxnwEomgUp2sN0zrSZrnxlWfGAct3BjMFYU8f1RRM2PW/ASYLPJcO8y7Ub+4YW3LjunRe+dYvKY5sXnOjxlH9aRjS7q9dGxjADYGc+Ny9b0EjDFD9BEM61YidsbmmAR8731tZepOHN/4dcafAyRZw3uthpmTj7sHfA6soM5BY9wwApJ5Q5FYxSh6xxM9sPV340DyoWyt5MQp06hjdKJPtOCBEes1utD0seOLIt+sI5BnjBGDxxggpdcc09PjL64sB8PG+AZIN3NyNSe2Kz0u3Xxp1zY+vrHLOulO0gWZbtjUvmmcPWVH76+vf/Iig2HygrjZDOcz7UB9L+cgtRnUiTbfbDlDLA4GnJQxlm5KYwd3X9cxhNNacnkEBj2i9yMxsh/eR+NxZGfWZ3rfGDIQzO4338tj2hZjXW7zlxxxpip1R4a0GUz6Hu3kkr7zoRODEZZR2wZGHwZROvr+RRLh60ISfO46Y4y6o4Nem6qNMa0acYIag9KCM5/I5w0S/xETuNfvRyJ3jDCHhVxbodRFPZus5NrxixrTSDeYaBNA9fLaRhZcgi7AQHCiRyvWkq8XnaFYDaUa10aaXUs3s7hGHNTttsNPLOtzTkqKTnoRt3uBYg3FGtHJrRxuE5m+4CiODbYxXHjTLcLVKX4S8RP4rduPw/NTvvjFh2DiCdPAvOy4sVxw7c4On75xP/ft7tP0BZ85eICPLh/hv7v2JH/71lv4dCORNVdXu7x9+xrvnV7ji6srPFwg8TzAf3blczz5yIs8UbY8XMDfv/sEf+vOE7yzWvFb6zN8vrmSGcdb7YIbRwv5t99iE3s2XUF3peOTzzxKYQLUnpc3Z/hG4/ELN7nanuXb6mM+9/IVvm/7Kf7mlz7Ilw4v8mxv+dDO8/zS0QM8vHuHh6e3+Uon38WHtl/khxfXODtd8pH1Hi+sznCnm3Ot3+Hvv/he/uNLn+by4pA/+tin2MSeT955iMWkYeI6bu5v8RMXP83m2QXRwltnL2NNpJ9HHpzf5W2XrnF0MOW3lo/wP3/7b+GnkR/a+wJHj0farsBsHD/06OewZ1tsKwxjuUp9pEULW6yEnT58PLJ+uMf0om1cPeyZ3hoBRguhNExv92zOiAHGrYc5tVh5LUdHyqOeUEieY9BQ726rwC6lvFqsew2il2s4lA67kY1UNqr0co+Uy55YOWzTSzZqWVAcbLCrRtIJ5tM8n5ooXZVSn+o8TyaW0o3m/QhMannPdI+XoqUU012R41FyckNd5nUphy2nUqu1A7gxBsworsXagb1MjJy1oi0P2ro0AdFswNH1YRQSfm8gNqnsPAI0JmX86jybS80xytx9Lxli7TAHlqWcj+SYvpc4yOuFHY4vvZazJ183lV8j5CYOGRjdQ9qkx46ZtDERdK8rPB3riNE8YZIZHfcYrJ0go9I40YVNN0llIUCtFMb4q1oy6/qeI3NG62cuR4+IrhMdYvJ50bgelVGkx6Sg8HFO9VfH8Lz2eOODxsQwjkWqY7PJvcwXDBfsaAeTwz7HI93QaWcCCjBHOw8YlRr88MXfuysJYciQ0tc5sQNJF9e9eo10QafdQtYi6nuESDa35Eyv0ePGx5neO5VAxiXse2+KpBtMN2DWVuoLudHkk3QpysqZcuikkEcMCsLT5zG6Sx7t2hL4TCn5I7YtRqSEDDCd5pslp/dXpXwEY0cf1GjmWALh5F1aAty5V3lyQusGQiZDBY8aypsFz4ZBX4S+bggnd5cKTvMmJLs0U/ZiIUyhso2xLITl8BpDou9ll5sMpqOzYqpJTu9Su2XEiDvUx40u4W5RYVfi9u52J4RSjAerSzW29QLwrMGGFE0ipeZiHbIjNlRWNGiK+/uJdHgxoBEqPa6JHN8v8TnVoZShozMUSyuGGf2a2eopNtA+3hIdhHng2otnwcLs8pLJg8esjmva3ciVx28ynzcUk579F3ZoWjmAovT8T7a/zAOLfTZ9wXfMn2dedtxdzvjc8f2868JVPnzuKWrT8j8cvIl3zV8EYLvc8JdfljLyD85f5bdWIs78yb1nCNqM+rumd/j83ct8upH8xt1yzZ+6/xNc9YFHyzt8fH2J7zr/DOZuge3h6uEuVd3zR3de4OsNT+Taapunr1/gnx5f4fzZI55qLhCLwHt3X+BXrr2DZ7qSvWLJj22/xEeffhOPl56/8My38WvaKvDuZsYHp3cBeHz6Kh+78wgXdw/5J0ePsnANv3P8MP/k8DE2q4qfPv8l3j5/mbM7Sy64gg+972P83Ns/wa+8+E4+fet+Qhl5ev88F8t9Hrl4i7dNX+b//ZUPYFvD37v6XrnX9kvKI8OvPvMkbzlznVAhEoVti9H8xhT47WtDcWypr5ZUxwFfG8zSEQ00Ow63CawuQz+VMvX0Vo/bBGwPvZajXRfoZ45i6XPIfNHInGabQL0vPYr7uWzig5YQu+2SaI3ogwE/0V7urcbatMrGpc22rhNxKh1MsobRWTGR1dKqMzH9sVK9cNtj0oYsTQGpT3ypbUaDJ7eti0H36bKumLYVNrNpM5MX21YAUSpp6/yUUhVyZUYX/iy1SYxYYjtTskYCpKkPtB+BxERKpBKoQZhDnfdS1Sc9TLThxQAcQd9Pn5wCy0Hm1wQeT+CjOJIfeXIXsVzBG+bJnOiR5uKqGgBwWi/G5E9aC0Gek7WoI7gzDvcep4HoOjwO6D6x5qT1L4HFdIxjwimfRP1/WZ5cY9PmItxTrh6t+XG8zut3mSulIYzMNQr49Bxn9jGBSE4Gj48BcDZcMTqm1zHe+KARToY2M0Ln4y8Khgvg3rib0Zecx1gzmMqo+hondCtjkOrDoBtULc24fJ6/1ESbp2Mag8b8IUY/T68Zhosua/SSBiOxiwkwGnOCnRoAroId3UXLZ3UnjjMzbOOyKjEzfVmzaPS5OXAbmTDTucyfS2aj7OL6WuCXiKlreUrTyu49mZR8L3/S5LJphhK3fiYpAY8Ae0TPvxuYSAXVGRBOp3qtRJmk03lJzGLeraomyTllKZ2+1mhDErSklBjT9HVamycFkyYSDfQ2nR/yHDdtFtWnc2K6oEHf0gbQpIDvQkKLozXiGgUoHKEawLZtOlwbsnM7OqNlRIvrYHVpIjE9pcWXVjIbRyA/lFA0elnX0vc3jWIjJepuamj2CsnMK4RV6raEbfQVdHs95ZPH9JOInxiiN2z2DM4KaCgnHbOLK3wVOdqfMS9b6psOu+hY9SXLZc0fuvA0fhbYma8xLuJfnfC5zRXOFEu+7/yX+fjyYY4a0eb91Nmn+L7ZTX51eZF/8eJbee/ieZ7aiMnkdrPgxy5+Jn+G75ndyv/+qbNP5X//7H2f5d31iqs+MLWt5Dl2Z/j46iHeO73G54/vw51vCFsec7Vmq275RsNhWB5OWGyvedf0RX7q7FN86egSbuIpjec/f+AzHIQptZWNwPn79gH4wH3P8gPzV9kPLZXz3AodHzrzezy7vsD3nfsyD07v8OjkBj+8uMa1g22ev3WW/+rx3wHgrWXL3eWU32unfGFzH7/bLPiTD3+c777wNHsXjvjZ++UzHvc1//iVd/EDD38R0xn8poAAZrfDTyPUgS99/iHdFMHmXKDdNXRXJPy7PoxsLgbRuR4HVpck3Hv72SCxTICJJ/tWoxui6khY9uB046J9qlNvaV/a7OoPzhJLS7vlJEWglP+7lWdzTgxehEix6jFtT5yUxEmJnxSE0hLmFah0xE8koiqWLrfjxIchUN8YMcYApu1Ux4i4W70AMgF15OcmQ0MuXRcijTEpJNxKT/tMUDinmbKaRWtkbpdYHfkMucSoDGc22qR0iFY2w7Hr8qY1r03JeJcZSjtUW9JcbFB20w7sV2IpYTAbjsFGhKzHv0cjl5odDOtW+kXaSI/W5LH5JQFJY3KWZQ4svxf0jCtvmRQZrY/jUnMCzeVQLcqVsRCGNS5rMOMJaVlyOqfPNO7Yks9PwgRqMgK9JlKJfowf7ilRnyi7K4DOTSYgn4OUs3gvPhjKzie74aXg7wwqx+TK18ufvmf8gQCN2UxgRif/3p0BnLiwhm4l8eQXmv6d2UiGCzy3vbvnYoDBnDLKURpcXWF4XBYU6800ptv70YVajMoM4+fd+5kSu6VaurzTSJNaflwyriSgpr+Po9dLAu10PGP3eESAVHp/78WIMnYwp8nr3vOtN2TOiky76HQOU6k9sXXpLXsNzTZajum080Oa8NLOy/faKpBBSFwWspuGobUWAhyjTsAmjJrLK5Ma6xJmE3JnGhiEymbkvEwMaSqLpc8AxK4dWEsV1Gedqk5c0ufWSS5cirUYj5HL3USwm55YaCnOarlb43di4bIuMeWAhqlEi3TbFaFyVHc32D5QHguYLFfCxNhWjstPnegjIxgvoM5tBmdruZLjK5eiYYxOOn20W4bjN/fUdyzNtpH8Pm/wFzqK2uODxQRDe66nfqUAC/HqlHYvYK5OWN6ZirkiwK3n9+iudLz7/FUuTo6gtfz6y2+m3G4pbCAuCzjX8nj9Ko9VN/mXt97EI5ObPLZzm//8AQGEm9jzg/NXWWxt+M39J2iDTJTv33mGBwvDgWogP7rZBeBXlxd5qY8chJZPbLbz6f+lV9/JrU5K0x+//ggH/ZS/9vJ7mbiOdlnxIw9+lu957+9xYXLEX7vxVr7hsLBpSl7qzvD39x/h8HjKf/HQp3my2vBsb/n2+ogbrbz3w9Nb/L39R3j/ZB+AXVtROs85W7JnK466moeLNYd+ypOVSErCUUn0hqe7gv/my9/OPz58gK3Zhk8ePMQ7py/xO/sPcsEVrELNnz73ZX7l6D7+0tV3cutgTtiXkHM/jZT7cm0HbwjbPWXV08+kH3U/jyz2VsSzLfZWyeZST7swYCPdIkpG50zimpo9S7+QjUKzI7IJtwn0c9ls9HNHN3e4JlA0YoaxTaDdKWVzYuV5QTcz0SnY8mBWLaaTDjEYqO9KXqPp5W+cxXRe3Nk+4JYtdt2pm1rkGXbZgHOEicavJBbPWdE+rsToIuDQCKDUew3k/kimtViXg95QsxQJCkITGNGN9jicOyat+rjkO6qKjVvHGcOgi1amz6RKzRhYjVmwPLeOGMAgWbmx60TeM67OZS1hzJt/SFrz0RqU1sL0PmNJj353eSRA5IrRhnREaOT3PbmGSEJHHNbHdIwpaD0BxQROxyRRArnjzzNiKk8QKbmntxIbfmAkT/SsTuvMCdBn+SoPRXq8Brjn72W0/mf5WtRMxnE4+uh7H+s8M+OZXiOxlSrROjEyA5mAaTrl5uTa/A3GHwzQOA7dTMAOhostG0BGiHzM3I0X7JwxyMCIZaYxDjd3ZvpsZqOAARyM20/da8YZg8gEmr5qZ6W/SxqQdJyJCk+vk3Kw8muNvvL0vln/oa87OlfCmKHvIYAuhhGISVrCdGFrtxVT13Jzp+NLN/F4VzUa8t/RDWZtvuATcJPduD5OXyPR+7EqcrxDDEP7rBjBFKVO6DF/X7Gu8jkTHWNyhYPpe5kwczsuvXknNazWeecbI7mllrirkSDiaS2vl5zTfcgbhriYYSYTLVv5YSOgk1WYSeZbLCR3sdubkNldjQcxyRmZNgNRoj7SOQmluED7qZOsudHvTdsT6yKDW9dKVmO3U8v5sha3ls1FqAvWZ0tc67FdxE8s/cRq8DIYLwu668gLZrtlWV10hAJcE/CTyOTFggjSeWTPUh5FyrKneL5mdWOGa+D+c/vU+4FwPnWJMJgeds8fEx/aYKaefhap645njs/zwfmLmKmnqnva44qbN7fZOrfkuy9+hanx/P1X38O87Dj0M76yfy5fZxNT8KvLi7xz92U+fO4p3jK9BsBv3X2Cv/jce9ixFX/n7mPc7rYAeO7oHJeLyI6teN/kEJC2gjuTDe+YXeX/ce1JPnjpGX54+0tYE7m1mlMcW76wuo9P7j/MF1+6wp+58EW+0djeWmNd5H2TQ2ZFS1HJdff/vP52XmjP8VvrM/wHWy/zu82CD07v8uO7z3AryHX3VFfwlsW1/Frv3XmBT24u8tLxLgD/fHmZn3vyE/zUY7/Nl9aX+fHHhG3cP5jzZ85/icvOsbw947995R28c3KDXzx4iHfOXqJb6SYrwMXqgOgi73jHs1y5sM/kxYL65RJ/o6Y8MqwuWoqdluODKeaOVBuqSU+oI3Zjc1RTeSAAxU8MZ//JVarDyPL+SLeQea08hOUVK72mG9HURmNwjQBD1wRiIaap6ihg+8DySiXMde0o14E4LdmcLfSalWs7aXcH16vBLRtMO7TrDJNK2XZl+q0BJ3NG6v0uPdtLDcp3Wadt1k0GnGA0kUAZoV4jeQo3zBtejG1R2bDoLMymapRRMGZtNr2M1wmTSqUj0iP2flj0YwRXZH26mejnThvksR4cA103SHAMMneXhYLHUSUphFxGzlm8+nOTPhvkzfcJg8l4fQE1Lko/bdCooHEqRi5TJ/A3KjfDoMm+VwYGeVM8HIcd9PRjNi2RPf7ka2SGcQzyUmVohBUyoLsXH9yLIdKx2ZEONT0/kQFueNyJOMCEG0LI5epUiv5qEmtY2xMpllsQjs/P6N8nso+/ifEHAzTCCAjZk6XRxHSlx4wFuOMLJ41x+TeBlzE9n543ZhXzTofhGPJNzwDkxju0dLMk5i0dcyotJx3G6KLMjxkDs6SHCVFZLEYA0Qzvl24iKyaN3I955CaWzzfataXPmXdD6QJV/UUC02nHC/I4zTY0OklB2infs9vUc5Z/N6Ln04467apM+jxJ05HOTxIrN+1Qag4B03S6kx7dkGqAQU1BsVbtpZFyhlGWwLRqtEltAEc3cmya7HQeyvppdxikz60CwuSyjLpBidbIa2v5xIRIeaBxHlOJozDeK4NRqc5Koj5imhxjFGF/La5SDFn/mMCoLy123WKCaB2jQRbXCLbtidZQLDts07M5B9FaokF6TvuI7SL1XU8/cxgP67Mmh3yHwrD9xL583Npy/v59jCoDirWhXEbaXWiOK/opuMYQSpi5lqOHDMZGzANrmHgMUNiAMRGOCspDy/pwwoXpEV9ozvHA3l2aZQU2Ui2EIXxPveRqv8PqqObWrS0uFAd86NJn+PhmJ9/C75u+RADuhpbnmvN00fOHz36Orbkwc0/MXuVHt16ijT0/ev6zFPdMk//xhS/y5vl1nt5c5C0713nf5JAmWtr9Ce86c5V+Huij5fD6AjfveK3xzp2rAPz66jwvHO1xfr7kr776NqZlRxsK3lxL28AnKzmvd3zg+e5Mfv6310f53++o1ry4PsP/4tLnAXj+eA+A867kx7Zf4uXuDF955SLGBl7qI7909ACLsyt+8LwA22eviZbTVoHYOeJOz8ubMzx46Ta/d/s+rr94hvWlSD8FE1OnFwi3K+zaStk6QoiG+i6UR4ZYRtrtiGuhPgzUdyOrd9+PawJbz+tmY2FzVqevxa1tdC6NTjJB3SZQLHtsq5rGCMU6SueYozZnjpZLuZdCoXOBlfkhMYP9bNCYpTDuUDnwknUqOjgvco35RJh7K7riWBeEuhzm71TSTEAT8j0fUwmxHbrMkOeNqCXlMPTEhpxgMThyrRpmvET9dJ0a+BQgjGPSdGM+VEdG60l67fQcJQJSBSYGT44lC4EYvJo1yJ8p9TVOve3leVr98SNA5ofKjXzOcmDuzDBPpZJ1HJdv05qQ2U8/rNF5XWPEWN6zBmeCSH+etfnD2pDL0zCAynStKaA9AcpgROSYofIUOdEoZPjuGdbGr1PhzGtGInXGZeQxY6h/ZzZxfEyMNgGj350wtNpRR5h0xtK6bshdi/LjX8d444PGsfPqXhYv/XwMDtPFb+45kfeyjeMvMf0sXShwkvZPj0lsUEL4KYdvFNdwArSmoaWRseYiPz5pRQwjxpNR6yll06oy7y5jer18o40MPQmkKihL/UtPlPQz66iHut5o6To5GqICQzecb+8HljdpH+1ww3wViPa9lnD1s40jefINwnA8edfJcAxGIyvCkIOWd1cxSlyGFR1iVMYv9YQ1zuWw4LSrjF0vDGo6T6ozwmqZpteAVt0px1L0Udm1rBORaTrRQ2kcTlokjBcwK+3O2iwtMF2PWQmbEScSCWI2rSyG6y73wx1rU6MzUlp20oM6qCEmFlYCkp3F1wXNhRmhLvBTR79ViiasMDRnazAwv4aU9fS7Lo47cVBPpaVcNzfYHmw6/THS/M4O1VFkeZ/hxvUd2l1DdRQpj4RV2n4+4NaW6ijS7Xm6Xc/TVy+JIeZGzazq+MEHvkC7E3nv9vPyulsdXG6Y76x59qkrfMfkgKvPn8dWAbuyhFcn/NmLX+ALbc31bpf59ob/6eOfZGJ6jmPNd0wOeE4jfHZsxQcm+/zi7Xdyc7Pghb7iinMc7IvB5dvqYwBWMfDLtyQX8ZeP7ucj670c4bNlN0QMrzZSNv7Vg7cyObNmaloWeysO2gkX7r/Ln3vwM7zW+K2XHye+POHzdy+zPqr5yb1n+J4zT/FTZ5/ixmbBR44f41eO7qMyBZ9stvjlO0/ynvqQf3p8hTeVskH5BwcP59c7Vx3z2VY+y5M7r/DLR/fzUi83y3dPb3Ph/AFFGbjW7/LC4R7rtuSJsudv33gXtjP8wjPvIzSWrd0VZ7ZWvHi4y4uvnuWtZ64Ttzz1bYs/I9e67cBXkVBF2OkhGFwLe7M10cLktmgapzcgFNAuZINRtFGMMzFSHwQ1SYm2sZuLQ7+fOlwjDHe57AiF9Dgv1hrCXViqI09fWzYXJhrULfpHANsH+rn2iu4GUOcaT5hWdLu1VCisweomLckxEmNlW9EQhrkwdqbphIHMm3UzAIy+V72asJAmxqw5jnWlRhfR6cWuJ0xrZbaUpdw0mSXL5pexZjFVYIoilzFztm2RsvkYekr3vVZ7FChiVF85qjzlTEU5/qTFNimDMQ0FP9FrNyk7AK0Tx1nXDG0R5akxzf26SR9KyrpGps38CMzlrjdp3oTR+9nBiJnmYjccb2ZorR107YojT2gkkYelNTM3lUiO7HSOxut6AoHqbD9Rlh5X8sbr9PjYc1zdPQxlHHWB0efnjcGIfcx+gIxZOAlUgXs72+Xe02mMQWwiWWIc+o6/xnjjg8YxoxbjyVI1DCd3DFzGfSfTTTbO60vOr/Tl3QuoEsM1BpWJeUzaxnTxpx1R3i2NGLm864qDViO9/lg/qezYUHpWoFgoiNNSKsgFlXtwptOgpc8B9Om5ysyiWvMTAIoMxzliBLMrUHe+MZ37DD718xnJe8xiYkPOJMyfJRlPYHBbJ1dzKl2PQHLMfan1uFOuoboVxxqUHD6bPn/UD9X3efcv4L7PesVYFDJZdxIAblSrmDLJYtcPnx1kgVHzTb5+jLqeRzvp6HtM2w1dA9JusSrzBiOm49C4CrPpiFUpvXBjoJ9q5JAPxMoRaicl6n64Rq1mzUkMicFPS9yqpVhLKa2b6cnoA+2Ww1fg64LyqBeTwbaj2MjnsJ0s8iaI6aVYStRKGraTMO/yyDB9VTq5RCtxK8ZDN9PFzUB122E6OR+xCvhZYNlUfGL/EcojQ0Hg3GxJUXqubB+wPJjSb3t+t1lw8cE7YrpfGh54/FX+4mfex+XiiO+dvcSmKbnoOtax5F/ceDMAjxSRLsr18tl2xrToeGR+C6cNsp+4fIPxGN2NnCuPudbssmflWnyi7Hmwvs37tp7jmvf8yTNP859d/hzvrlfs1WsODmbceGkvd5f5RuPi3iE/8x0f48m9V9jeWefXB/jwuaf40PaLnC+FTaxNz/fuPYXD8L3zF3Nbw5/YeZ5/dPggAN8/v8rvHd0HwK12i51izbV+N7/fj+x9njefucGn7j7Aom748cufpiewWtd88IkvU806FrtrLk6PeGR+i35VMtlq+PbpS8IEe/jjD32SUEVCrdfBsSV0Fmyk3YncfnmHzRk4etgQHLlDULcFro1sdi3rS8JaR2co1yH3n5YYHiOdZKZWphxrsX2gm8u1E4qU2QiT/U6SBozJsVHRmTwXhHJYVL0aaexaA+sTi5jm5F4Aqek0rqr3YoqJAHFg7VO1opH0gZgbIEh4OF2fX4eikKDw6YQMZmLEbmQDElPE1tilm2LSYOhTzQAg7mURQeY6kwBbBi2i944qnxJpUcBUdW5mkLVvzpJc0xnUZAJltL6FcFJvl42CQg4YZTHzzeP7kwAJZA7PZKE5qfEDWW8SIZLfI7Gp+qCx5GkMtrQVIDC4utPbWzvEBI19BnJyT4DP/N73sHsnWveO1/57geDXwhlqhBnrV8flaXmZERi/Ryt57+tmc8zoOZlZHFU5zb2fYYx10u9PNY06DF99wcLJLyRdSOnn6WICBV8jBJ6o8jHdPb6IRw3Z80isXmKc0ki7lgSATmQYupMgckypp1zE5DzLAJUB7KExDOp+M/r6+dBS9mD6zOmmTFmIeYelbOC4N2hiPO3opk2vl7oSnDg3CRiHodwwDni9FzwbBbZOgdq9ImX9t7FWAKB+PlNXQ7BuVY2S8e0wqUOe0IxGMQznSXrCnmjHlUpIregpTakB2OrSzgzspBYtkDLCMUiYrwBCdShPK/CBMKtzlI4pVERfFFkXmAHvpJRjnFT6vrJzjrMKnKU4WIOx4g5NX2vnabdLjI/EStykIUWIqJPedgG37lhfmtHPHf28oFxKdxc/LXCdmBv8xBFqAXTFRsBmBAkJR8CCrw1FE7N7enLbEwpDNzdszgdcA7Y1dAuD17m82TWYThhKX8v1Gh2YxmIbQ3dQc3BrzuTxI/6HV57k9ufO4a9Pub++i20Mj128yW9ef5yf3HuGK3sH/MT7P8KP77zAhQfu0kXLfgBjIy/3Ex4tAm1T8LwSDqWR7+KBYp+f3HuG753dYt8LK7fsh8WmjT1nbMWfuPAZfnN9lqeOL/BdW0/zpW4ozb2jWnMUpvgTgiv447vP8Z0PPEOYRKyNfEp7S3+9cfNowWebOd87u8W7dl/6qt/f8H3WU97p5zxayPmfmII/c/5LcslET6l07yZ6/tTZp/nrt97Mq+stPjC9xXdMDvLr7dqKH5pfY3VcY4EHCsN/+9J7OLNYURjPpcUR/+nFL3Dc18zthscu32Badvz8J7+bovS0D3b8g8+8H9cYXANb9x3TbcsxlQcSu2MCuLMNpoezlw5YXoZQwvya6FoxMHvZ0E9Ew7g546gOWqoDMdAYHyk2kfKwJzqIViJz6gP5Iv3EEiz0M0s/lSDw6AyhkhaEyYkdCzBdyMkBNkRMJxu94rgVra812OVG7jVrCPNKQr036jwunADXaSVtOdvBEJFAZ4rPikWRNYwm6dphxDS5YdObdMabZgAJac4FmQNTv/u+y8HYqSoCutiDgFlllFK5UZoN2MF013YalWPJ64zqo6OXTi7GjI6VND2bvDzkDa/Gjpl6aMEpYDLekzihf49LzqoxzHr5MZuXKjg5ZijeQ8wocVKWJ1m+xPSmqlZaT9LcnobRD1UmXeZARER1v5+QlI3fP73PvT2mEz5IIHpMDNmTa5ZcvGE4jmQ21dcxY0Jk/L5wssw8roTqnzjeZOjvxsxlLnePSuYnXut1jjc+aIRhR+DuucjGCH5EsWdQmC7S8euMjTQJ8OnOzqRycxqp3BwZ9B6p7+a9r5MejyELbNPPylJuTn0/45yWFcY7Ee4R+ipYLEthS32vE0I42fcTTopvq3LYzSUnb62gpZRSi7Gp64qAzawFNEaAnr6vSTdPpssTmNTPGcMIkMuEaqpSjiFFK6TjKpIgOonEddJJZRlrpAQU9TPEKGUanQjTY0xZqih92LkbnfRj6Qa9T3J+63vHaS2vX+l5n04E8KVSfnJPpnM502BgvSaiZr3hZFFD9VVoOHeciM4qbE0E5NZi3ol1JR1ciuTmNJovJzE7FFYYRe1HHZ0lOLBtj68cflYKKzPVKJG6EH2Xs5RLT7FSLWMfcV2g2XHSmWO/xXaB4ulX8BOH6SK+MrQ75QBKLaJpPGfpJ3IN91NLuyURPCZANxM9WfXYMdjI5oqn2wnUB5HVZbCNgEejuHd6eUWsAzvnlhzemmNvVPQz4HzDR557gssP3OagnfJ9l5/i/3XjrbxyZ5dr/Q4A/9GZr/A764f4p3ffjjGRjx89CsDOYkMXixyK/VIfM2MI4Ezks+2MedES9Dv/W7eEIfzHd9+CM54Pn3uKdSx5S9nxjw8fyM99Z7Xifmf5F6sLAPyV628H4B31TUxv+M4zz3Gt3eUbjQ8/8HHeXUu3mh27/qrfX3BFdmB/r0YBJRB80wsbUxrHH1m8DMCWfrZNV/JTFz6LuwfUpvGjD3+GSSHP351uOFMv+dxf2mbtBRi/erDFR24+xrO3zrJsKhaPHPKuMy9zaeeQ//BdHyUUkW4rsn84lbaCtx2+jrjWYM62dJsSLNza3yJWAdvB6rw48KORMjRAs2PpZpGDJyaE2hIq0TWGQkBgNNDPHb40dFsF/cRqGRq6qZHNTMohLIRNz4atwuBnRc4gbReFAEidmzfna7lvJhX9zhSslMAlh1H+7mclthuqGP2WOoZ1XjMhZpd0mrdjXWZwktsLlioVmdfD41MEDoicJUX7EOX9EyhMgMqLJjLMJvKwQuU1aRPt7FBy1nUsAT9TVYO0SAPHgSEbMrUYTMtRrgQpOLRigolVCiI3DNpCZH5Vps4U5UBqgJSz00PTupmW1wzEyKX9HAEz1v8r4JXXjuqiZlhLx59dj0c+iJIUqUFDGskglJpOJIBbjtbnMbl0rwQtYQbteHOyIjYa2WgbT753jENVa1zazlFIbog5UiY6R/GMXxcYd3rJx5aum/G/9e8TbZPH7OvrGCZ+VST5G2McHh6ys7PD9/FHKUz52k84HafjdJyO03E6Tsfp+AM4+tjx6/wiBwcHbG9vf93H/cFgGk/H6Tgdp+N0nI7TcTpOx7/ROAWNp+N0nI7TcTpOx+k4HafjNccpaDwdp+N0nI7TcTpOx+k4Ha85TkHj6Tgdp+N0nI7TcTpOx+l4zXEKGk/H6Tgdp+N0nI7TcTpOx2uOU9B4Ok7H6Tgdp+N0nI7TcTpec5yCxtNxOk7H6Tgdp+N0nI7T8ZrjFDSejtNxOk7H6Tgdp+N0nI7XHKeg8XScjtNxOk7H6Tgdp+N0vOY4BY2n43ScjtNxOk7H6Tgdp+M1R/HaD/n3e5hJjSE1Jx+anRODNDPX3sXRa3N5Z5EmmVF7Y0bpy5iasIP0jUx9hsOoP7X20TRFQey7ew7EjvpDF/peTv6fek1qb1GqStpFWif9NY052Vc6eHkvPS7jrLSN9D25wWdqfB6DfLYYMFVN7DqM9vY0hSMcHmEXCz1ek3tNEyIET+z90Ns6ajP0EKVX6Oh3se+lv6g12ojeSk/Uthv6X8ZI9F7+XxZDQ3lriF6OJ/Ye6grTtqPzzvC5UqP33uP35rjjhtg08rvZVM5Hrw3n0zEWjqjnwuh3mvtEH69gZ4FZt3JetRd26mVrOj/0mQ2BmPpvh6j9lbX3p7Pys7KQ09j20HtiVRAnJWbdQekwbU/UHudRG9ibtpNjTv1zncNv1bhlCyESK3ne+sqc6c2GzZmKYhMojlpM2+G3poTK4tZy/UYjvZ/zsAbTB5ZXKur9gGuDHLuXY+9njmbXUh5HsFAeebqF9pANERugnxj5M4vU+9DsQnUAtpffhRp2fuMlbn3oCrOrllAYmis95Y0CP4lwpsPcqrAd7D5xl7vP7tGf7aGx/Mxbfpu//NR38gOPfIFfe/ZtYCO2sfzQmz/L26qGX9h/lNY7bu5v8XOP/S6fbma5V/NLfeSBwvDFrqKPjndUX927eTyOQpt7M38rxt+5+xg/ufcMH9vs8v7J/onfPd0VPFH2J37283/+cv73h//X1wA4CC0738Jj+mbHs73l0WLol/sXPv8+/uRbPkoTHQ8U2lOcwFHo+fjqYdrgeObWOX7u0U/xiwcP8eLTF+m3AufOHuFsYKvY8Nyzl8DAD771s/yzr7yD4tjyyFtf4alrF6nuOPw0Ut+G1QOBnS8Zllcs/bbHLS3VvhxHKA3tToRZz/SFAgJgoVhJ3/N+avATQ3kUsX2kXAV8ZekWBqPX7OzVnm7umNxpaXdK3CbQzxwmROq7LbGw9BNHtIZi7THjHsFpzvOBUBVEA27VEibSF972AdN5Ql3gjjdE7dscqwK7bKTHtLPSt9qHPG+aridaQ5jV2KYfegv3nlg4mS82HbEqZH7pZe0xuTe0IdQlXL+J3d4eekU7C5tW5l1r5N9FkXsUh0mF8UFeR+dF+p44n8r85yxhVmGaHrNpc2/lWJfy+HUjc3RdyWvo3BzLAtO0pF7Usa4w6420ctb2xjKndzLHpXXPB7B2WBNgtJ74YQ3sO5hMoGmltzayxhjnZL5tWnkfH3T9lR7fcu56bSktfb5j08h3WtdDr+W0LjlHDF7WkKLM/ZmNMfLv4DFVRWw76QtdOJmf+17W4L4f9aW2iis8Jq2JdtQ32vcDJkCus7zWpcekdT/1v06vnzBDBFOWcn5c6lGtr2ETtrADXnCKV8bn2qf5yWBMAavXni/e8KARGE4SKFDpR1+MNjHveqgqARbWycVVltB18qWnOVUbjWMVkMAA+gzgvUwe+f3QLy8dh5H3TyDQGrm4ei/H4gZwhQkDADX6Yl4BUVloo/QAtpSm667QC9zLa6SLLMoNKq8jN7bBDlg3RkBuNkBuikkFqwZT13IujJUG99YQ+w4TpMF67DpMWco5Cx48cgN1vRwjCGhru3xCYgiY3stFrDeeTCIK1MZN4YFYlpiuG24cZDJzh2uZbItSnt/1+XuIMeb7kRAxCPiLTYuxViYWJwCfdaOTlb6nD/zUf31Dvueo328Cyn4AoabvFeSX0HSEnSl21cn3ZK0cj7WyEJQWe7QhTirMakNcTDFeNy5G3jPf1IXDL2rsusOESLdTU95ZcWADsXKsz5ZM7sh3aZcNFI5uu6JY9vLZnZVF8GBNmFbYdYvfnrDZK5jc1ccYg133xEoWzFDKHxPBbQLRydlbXnKUxxHXRnxp6GeyIEcHxsMdU+M2kc05+MJvwPf+JzeZ3IKiiTTblmIVaXcM0YGvItObyP/tdaKDMIl8Zfsyf+joOhcvwP+m/gif+PLjbF854qcvvMhH1md4z9FdPrj3DDPTctEFvtu4r7rFv3v07zt+/jUmgfFoX+P3r3/8H/gMAG/j+Kt+98+ffQ9/9NFPnfzhn//q19ixFb+2vMgPzF/lbT/71a/zrzMSEP3CX17kn73tZ495vjc8XMT8s49vdvjRycGJ5/4V/kX+9+fbCY+VR0xMya8vL/Bkf8id9Yz7+utc3Vrwf9z7CH/1Nz8IFv7Q+z7Lrz7zJGbieaR+nrYt+fBDz9Be3aP8SkV4U8vF41exjcW2BtdAux2pDg22jawvRcpDS6gi9R25xtb3B6YvWqqlzLuriw7bw+JqSz8r2JyxXDpaY7uIbbyAwJmlnVlsH5ne6fG1pVh5CJFQOYwPAuY2PTijP4vYVubNUMu8ZTdyf5hVS6wKmTcVmAAyP3hdGNJ87j0mwrYpiXVJmJW4/TVhXmOXDbEuBTz1ukFN976CAHQOpuuJUwFwMg9Fef0YBERWBT//v634U//1tQGZFU5+F8ZrhB5bVfA3/y8Xh+NOG9QIZtMKMFxtBJStG5kjykI2zX0QgKKkhYBeK8DJe9i0Cv56jCnk9z4ICIsRUxaEqoBNAz5CVcrzQNe/IgOcqBtcYiBiZf11FtpO10Qja6SCSxMCcVITlysBUGVB3DRQV9C3AvYAjJM1yToBUQnwhoCxJh+rgDQrx60AN/YC/LCl/LtwgMnfm3FWvktdD0ypgFNRcwyyvgoRNSKeTDiJTcbfmTFynOm71TVd1nmXyawYvB6Lz5uPTJDFKJ+r12vIMIBIq2uZtbImlmOC5huPPxjl6RgGxJ7+pBMfFUzFiDFyIcT0ZQX5gmICNWmudVZueudO7CwSU4eCsPzlZ6YuDOjfWeROVMCoPzeJXTN2YDetXqRBgUUCnxHAENtWj93LzkbZMgFzCoqdE+BXFMSulxtEJz+juzOsyzsZAXWF3ASFXMix7wfwZ/X8WP0c+lnyhensAI67HlOVA0sZo/w+nasYBZAmkKk3Rmw7YlEoiA55go5eGNDYe+KkVtZ3dL6RCS5aS6wrmRBDICb2tdAJRG9SOf+R6HvCtJJja4TpjJNKXrNww3v4IJNVUcjvOrkpTReGXX/pdNGoZOHxEepSAHEtrFIs9NoJkTifQKcTqTFEq78PgWIlrHQsZFKd3mxlgYO8yJSHLcYH/LQglBbb9PL+tR5HaZldb9jsCWMTKotflPQzBxZcF1heNrhNYLPr6KeWZsviNhGrWLxcBWF4JjC5K2xlKMFEsG1iSWF1JbK6YKkPAuW7j+h2AtFGXGtYnwfXwLmH7jK9AdjI6qjmzZev89K1s3zslUewZ1sOVlMArjfbfMfu87yp7LjoAr/X7ALw6UaA4T86ePA1b//02K81vtyVr/n8f91xdnvJX3rxXa/rsT8wfxWATzVb35L3/nrM5RgwArzvHnZ0E09WSN5ebfgnh48D8J7pVR6d3SQC7zj3Ctfv7nAzWOo3HdFc6nm8PMZMPdXLJZujCY+duckv3n0L06pjfSnS35hQzjpsa7CtbDrc2vC/+q6Ps74Y2Tm7xPZgvKHdVbY8yAbEV4Zm1+EaqO8GQmmJFqrDgPGR6AyxlPnHNRHrI66H6Ay2l9932yWhsvQLBWvWCEjxsqCG0tLPSwEtACHQ7shG2TYd0RnCRObEaBU0xCiAEkMs3TCnOYvpPO6okbkhyOPSPR+2Z/L4MetTCDsUaplXzKaTeasu83oh89HoC0pzbTHaSCVmKs3NhZO5RTepUnVB/r0zzyDSGINRUBQrmfdiXWKaFjOu+MRUXRNWNoFJFnqfhdHa4qwA9EbX2KokTEo5X1UxHK++vum9EgGFrklWQZf8DKvVsASudC7GyjkwichZrvX9CyE0+l7WwhgzORD7Xl9TzlPaC4zX8Fi4zGIm0iVWskbEXtanGMIASK3NbGUcM3+JwY7I+xeFrHkJRBoEeEY5ZyfWVjcQPLKOmwEgpvU0bVqcI1c0geh7ZXftiJwJ0Ml9bqyVc+lfH2CEPwigMd3coMg6ATsFkXrhkSloLSOkGyuBRxhubKXhTV3Ja6bXTl9cVKClE5PQ8XqxOicXhYLCDNj0AooJKOqNn3cseRJAAWgcwGFVaklYr/owTHryOLmYzfj53hO7Efvnw1COtnZElycAHDOgNVZAc8adCl7lnGqpH0Osay0nROg6KSWMgXbXy3kzcnOmSTgDZCImBIz3A/2vjGeeqPS8x8Qy9qmkLrtQopRjYt8Pu1v9DCZEAZJ1lZlGk0GtltprN9yUbaeTt57/BKCDgEXTdlIi0t25CbJY2OONLBbpJvde/46EeS1gOUQoHbEqiYXFeHkuIWIaKWdFZ3TxsYTKSWnLGGJhZaHRCdOESL8lQBGDMClacnOdLKDESChlQd3sOLp5wfxaFBAJrM8aXCeL7uZMAoQG20OxQdlJ2H7oABPAXdwAMH0Vrly6QzRSPjw4nuJmHaGAcL7FdXLP1a6n2TU8cuEWO7sr5q7hsfteBQN/+NLn2ZuvWMeOs9WSt1Xy2qVxeF0x310v5RKKjuvpe71nrBQApccCLO8BRW8u75GRfAvHT517ivOLb445nNnNif9/sa1f93Pvhm+eQTUnEAhMzACi/8nRfQAcd3IMx7EgRAvR8P3zG1QTOXeLqsEsHRb48IMfozkfKKYdt5s5N4622Dy/wM073MbQe8eb3/IS7aWebhGJpVyXJhoObs+JTjYVpgdfG8p9R7Mn81G7rfeTj7Tbjnbb4jaBdmHxpcH0kX5i8ZWh3ZINkOkjwRn6mcN2kXZhMF6qGd22bqqc0T8Wo+Xo6AxhVmF7WejDvJZ7sg+EiYC/MKtkHmgETJg+CNNVFjKf6VoT61LATe+xx5sBACBVgXsXbLtqMktF70XqElEA18salMGGyTKpWBZQKIhM8h8rLB2gpeZKNq5KPoRCzm0stHybnmd0rqkLBddjokPAJetmWCMMGbTnz+2FBTOdz6wWgF13UqFK58F7KEs5Z4lNTWtEDAJqIIPqOK4olYVIoMpCKzsKKtP6YBKbaDMZlNck5wSEKyGS1z1lBKOCfTKw1OMZgUSTCB4UgKX1IbN9KGFSDiAxBgWFI/YxAcwEkhXs5vd1cv5NMSo764VkqmooWxtDBvbp8yTSqSzl/wp6M7BNrHHx+grPb3zQmHY9aW5M5dp+ABAZ7I2/jDGdCyQNY9LtmUonczc6hTZRyVGZPP3SdIcl5WT9okuZnKMCFJPeN12EWRCC7laivHd+LzvsYvIx60UXEUYxpuNQoJxKy0UhF1qaeORAMhM5fH6l1hPQDl4Aai3HbtIFrseRjk/wlxGdi7GZTTWqUzFlITv1UnboCRwmcJ5uYKOl3RMTZDrPCJuIMfLaqjWECBPREmXG1BjRsIwAeALjxouOCOQ7SgsAlQA5KWHptaEbgbQIEHXnby3UlSwsIUJZyPsmcOgsdt3J5G0NsSqhsPLeWgY2bZ9/Hp3Frbq8aYmVkwnfWWJh6ObCXIbKKfiT3WWY19g2ZK1iqB2hkMXMV1ZkLY0sfNEZiuM+67dcE7BdpFeCyjUQHEQL01sBE+DwbZ5uK9Jc6WnnUl68c2eLaMDfkPvBTwzXXzyL3/asHvbEYPDLktmFFVXZYy5sCCW8dGePxUOH/NGdF/jhs5/nO6bXefl4B1d4nih77pvt8+vHD/NQdZugk+Nfv/kW3jc55JcOHwDghu/5Y7vPccmN7ovRmJmvZhHnX+Nn38pxEFpuZp0Q/OSZZ17zOZs4PP7TRyeZ07dWzet+771vsS7yscmreAI/de4pAO5zlvdP93nv2RcBCN7yleYir9w4w+UHbvN3br2dM3oMH7zwLK2X72X+yCGP793i/FtuQYQbzQIaAZ8Af+GZbyO6SH3bUh5F2ssdbhPpdofqTrcwTG4BEfpagKHxkW7u6CeGYh1odguaHf1dhGLV089VcmMEhE7uegF+hcW2gWbbYmKUPXJpcMuOaA3dQu4d2wYoHf28EGBpTZYQgdxzFE4rDyIviqW+Z2LSrNFNm8lMkG16wlRKuVTlyUXfWPzOVJ4/qQQMjUuHY7I4lctjFF2ivl+sS9mATip5z0rnXGeJBgGBwePWqp1ct8RpLRvsssT0UoK2y2ZYX3TNjLWUgU3hTrCa9niT1xpTFgKgdE2MZSFrYDofTnSHCeREwzBnZsBnMK44ocOLum5FJ+SEiTGTIWmtM6rhFH25AsjkVUgehQTwepHr5PVBz29mOr0XNtpZzGQix1qprt1aLYWX+bNG1UOiEqW0zqN610xGWdXvY4bK4WwmxzepRGamoPvEn+QPSCRHXh9jBoKEIOc6kWMj7WbCDaaU+1SYWJVrdcM89I3GGx806kWd0LixbqCkT4hvR3/SjZgF0Xa4qct7ShHWZgYxI1NrM4N2AqwCqKZPSt+iS4zKhGXQlsqoeffhBJBlllMp80RBbxqSNtOMhbu+H0wocOKiiH033IgKbAcwplqJ4E88P5ev004VAYexrofnlsVoZxbztZ4u7lhXajIxg/ZTd9SortIUumssdMLQm8UUbrgxEgXvrGpPFGCmm0JZujShhrok1lUu44imcVQeTsc32iEmljqWbmRCGv0uRtlFWwNNh2kVJNph4TBNRzKzgMnGH9MKS+inTowrpcuLUigtsXT0i5KkUTSrBhMivrTYbgz2wa06TCefOVRWys1twHYBtxadl+3luNq5JdQOtwkCOgE/VRbTR5HZeGh3xABTLuVn+e0smJWj24r4CbiVodkjmxeqw4BtDbNFQ/WqgOyLF/aJ0bBVN/S9o9sKbM03+Gh5xXvuc5ZljGz2J+zN1vzG6hwPVbd45+wlHi4C+0GYkk0ni/Cyr7jaRy64kzvjp7qSv3n7Cf5tjh1b8Wx77pt6zsQMn+P1gMz/scZDxQY3WiJS6fz9030OQ0vfFHzmxn3Md9b8xN5XODs55sU+8sTl6/zWq4/xH174NPfv7PPk9iucLY+5vZoznXTcfHWH6c4Gv+P5jrc8jS0CP/zo5wglNHuG4kZJtw22Mfg6CpDciaKBLQ2hEDbdtrC8P1KsZZ5pt0VvS5TrVvRxw73iSwEnbuMzYynEqWyoXRPodmtCXYhGsgu4w42CLGHSbOOxRyIPSex9qNR40Qfd2Mk581Mt+0UEfKSNX12KprgNIofpe9Ew6kY1yVBMmnsmVWYOo24QMzupG/gTpolUZk5gIVU/zLCGGQVPpusFuOqImf2CLKfKjJvOrwk8VuXAWKnuO6r0hhC1rCzvb1IVKbGiqVLTez1fRkwrVUmY1VpK1fUjkSNaijZlkdeD2HbkqiEChmPXD4ajQs+X6vsSmxa9rLum7WT9dSrPcjazkwkDmLYXGVRQgGoGggQjc3lM37MuV8YVckjBq59Aq13peIgZdJuET3SZNTEB4HThKsGVKpYJJHrVJgJZHqfHlNf0RI7BcP79cJ3IZ40DOfQ6xhsfNOoJTi7g2Laqy4vDSbRWNIFK04qGIAidm0uacXgODA60dHOl56cdRuFOgq6QdBpJHyi7KmPdwGoiF2sWHE9qNb7oMfS9vP4IrJpcBlHmzRq54BLr6H2eYIw1GQAL26iMobODVsKNjncykWPq1Vnmh/JnBsXWikklDjdaAm/Ri3M71pVcmFoSNuoqxho1lSRgGofyiE5ORjWPaVKS3eCw00+C8vTaBHFIR+cyQIyFw64bndBH75fWE8Pwmft+AJ8gjsLKEasil5LNWhx4J0oppbIGfT9MhAloJqa2sPIagF9URGcp7zbgDH5RiTaw6fETmxe3MK2k3Lwnu1CnQHBwTOq5iFEmJwOm0esyRLqtQthGHwm1w0TwlcHXlm5uaXYcBFjvWSnhif+K8sjQTQ3NrpSw2y3Dm87dwG0Mbm0ojw39PBJK8LNIuyvHc3y/wc8iIUI/i9gicLCZ4mzgAzvP8PjZm5TbLffNDvizF7/A3/3y+/nlw/vpo8FMPbdubvM9s1s8XgqYBDJ79T3nngYEWLU4PtWIyaNVpu5NZcefOvv0658b/g3GM93XZjc3seP9030ADv81ysX/Lo3KFES9STyBmd3wz47F/b1tK0wRCJ2jcp4vNAu+bfYiFri+3ubPPvgJfvHOk9zZzPjoq4/yUHmbJ3Zv0L04o1h0rA8mfOC+Z/jtp5/A3qx4an2R+SOH9HvC/NjOYFvD/PKS7q0Ne5cOCZWhWEdcFylW8rdrDK6H1XlHeRRBpweigLlQytwYCkO3MER1g9uNZ7NbUB8oMx8iWNjsWfxUN8ReqxKlo1h5QiG6Sb9d029VeVNqukC3N6HbrfD1sOm0rR/mj7IQPWSax9L63ksFw+9ORYJSCvgsDkXSYlpxZ0drhEmMusHVeyNqZSIZYVJ5XG5AL+dgayogKs3ZCVAgcyM6J2dTH5BlVWqyCBPZ7MdEXDgngFcd0FknWNhhfZ1P88Y8dlpJAUzXScWqcFkiZVox05iUplGXmZjxewsBowp0orNZGmQMJFOqyeZQWS+iD6IjTYCukDVMdIoqL1NdugnyWHE9i4QslgVxWusx97L+FW6oRkEunZsEwtJQ1jEllyQHc3RWmT3xFpi60ot1qIqJXtaTHNiZXZQzKX85Oe7YdXldzr6I5GWIUb7PVGFLZfAw+Dhip8RS8IMM4DXGGx80Ko2bkXWMAgZzqcAMmkB1I5+o7Y9Looryjcav5MeX1fC4pA1MGsZkPvH3lF51l5FNN8m5q4xf9F5uvqKQ1x/tAozqApNA12RjTFRMmWakkQalLISJTC4pa2VHx+g1xp91BHiMMQKK0o3UdjLnJLFuuoEqLVsooDZ1pRdkGEoTCiJxJjN84kiEWELdmNkAAQAASURBVNdy40bVBqlmNN24AjSV5k8lC2uFHdSyb5xNc7k5Kljzs0onWiPxNl5eP4NUY7IOKdZVPp4T30fpRGsEkFhmQ3YW5t0ySDl6k6J1yAyCX0wE2CpIDXWKw0BMJbU4mVPpLQ+vwv/CYo/E6d1tqbyhlo1CqEVntT7vZPGqLH4iJbZYSAkOA5NbLe2WXGu2j5SbSLGJlKuIr5RJDJH6IGK7yOymMJjrC5Gv3DnP5K4wPN08Ut01mEWPqTx+R67vYmmILtLcmRJmgbAp6G5MOF7WvNSeZavY8J/e97u8st6RayYYZq7lpl8wm7Zsnfn6mQ9uRHk+WgTeU4tesDKvb7L7Vo7Hyq+toxxrArf/LcbofCvGl7uSLsrndFjeXHa8dyal6evec//ePh965FP86fNf4onqgF+59ST3F4ajuzNmpmTdlRzvz4gHJb99/BhrX9Ff7LAuQBn5wtFlYh0p1vDi3TPs1mvs0jF75Ai3AS42LNc1P3TxC4QoWsRmx9BuWboty+aMpTyS0rTtxaWf2ENhzAO+MoRC9LehFPDYL0r6uUZjRfBT2UyZNjDZl2usm8r81J2R1AGrGzHTB3xtsV3AzzQSxxpsp4kDSQZUql4QCLXcu/1czGx+VuYyMdYQpmW+303bZ9Bkmk7u3TCaC6w5wQzmilgU5i/Nbykqx/YBP7EDyHSWWFrZVIM8TgGcmBaH8nAsdK7FEGoBi7EqCFOV5+j8GUdgw3hlAlPFDplbTTLy6RwetWSf18FUogdMK6xsAlF+4oZ0ibSOpvdIc39dDsRB+jtGmbN9P1SiJnWuFKU536Qq2Uaje+YTYlFg1ps8/9P1g14xMXQjIwyJQUwExHhNjAwkRHKad8nRrBKwBPTT69sRNEtrqDG52mecltfTOUvyLH1uTGkjqaSd1umx1jGVzhnW0tcz3vigMaFr74XmT2XVdJMYo7sBvWldKq9KCdiMjStlqQJYewIUSrlAWcBMnRf5wol+MKmYUmJ9kt/DlKU8ti5zrmK6KLN7rExgyZ7I3Rq7lU0uK4Thc0R1JQd1B2eNjYIG1cCYQuMG0m5Td22x64dJMF1UIQ47Eis3cywK3aWpjjEBraR9VLehUdOK6XpxBibwl44pRs0rtKLtqwuZTIJkL4obWbWkRdq9l6KH9PIdy4Sok4Zzkk2WGAF97eis7Bad07KxAKUwE3CewXSaaFD3Y2IpnZMMtkoc336ryqWkOK0lx03dajHpN5HFw3SeMJFFKNQ2g8FojegnjWFyp8t6xXTsWDQiRxaqUMpEHo2RRchAt11SHwSaLSvu5x3L5FaL6QPNdoGvLZtzlZTanMkGguSObnaHPMZQQLsLq/OW1bmCDz78FXzn8KXoIjnT0c8jk7ojrgvcgZa6J5HdM8ew6NnbXYKNXHr4NqwKPvXyg5wrjqlMweHxhC+2NQ89cIPvn9/gyWqD95bHt25+zdv4xT7yprLjk5vtb+7+Px3/2uOyW34VILfKdFxyjj+2+1zOd+xjxEeZVx6/8iqfbuY8sX2TC+cP2LtywPsWz/Lm6TWiN7SrikfP32SvXnH27CHtViSsHM9fP0c0cHA0pX+4wZgI+wX//NW3cbCc4t60pFwJu+2aSFBJ9PEVJ1FQPXRzQ6WSim7m2JxD7q0O3AZcqyXlUqOjrKGvDX5i6bZL3NpjAsxudvRbJd3U4HrJZC2OOvy0pNiIFtk2Hl/pXNp4iuMet+7xyujb1gtzqAaa8tiLfCSVS/sg82mImNbTL8q8wey2ygyMQjVUPfpFKfNWTpoIAmrKgjArhf1TwBRqmZ+Lg5ZuR3TeYVLIXDopBnmOGmfyhjaEXErHCtAT6YpoQU2KmvERnMVPVQOpjuY4qRSURuK0VKCayrLkOTQBGOOFbY3JAZ6YT10bygPNjOy9gLlWXcyaxwjI51YQa0qpChkFZ6YQfZ/p+rx5jj5IFmWEnJ9oDHE6yXKF6IPM6zlWSaplMa25RZGBbQZk6keI1sr7qjbfuCJLzlIlK0XcJe0kKi0zXS+eAAV6JgFRJSGMAuyYKn4xZq9C9mjcI7lLRJN8304IHZfSRIqh6vY6xhsfNI7Zsyw6VYxohAbO1HIyoKSgaR/IGYbODgxeAjqp/JmCW5N7tSgV9BWC+HXhj70XZlLL4aYYDBVghrgcr+VFdSTnGyjp+RK4MwwMpXW6o9EyskGAZNqZTRXYtO3wGdKONaK7Q06UZmV3qIC1lAveJI2L3ljoYaZd6HDsKCBX4OlcnkjSF2B6L0AylZ8Tm5vA6aYdtIYp6DZEeR0jBhG76YaJ0znZ3afPkfRBzogLsPf4xUQAZ6VOcA3X9ZNCXiuowSTIhCHnPpWBh/Nm0oRSOUJpNUYCTO9pd0sN4tWNQi/nrFj2+FkprEWI2EYMJqbzhJJR2UqE/Ol5/VYpCwuIc9MayiMvjEfjs3DfhIhr5A9A0SBO61omuuDEVVouI74UVjHpwzZnZKNSriO+lgXVtoZ4qaHbjnzk6mM8ev6WOFO3DVXVE3d73rzzKmbaE5M8dBGoXc9bz13nPzjze+AN/7O9ZymWhrdeusZv3n6cL7QTqrpnGWpeOdrJt+pPXPoU3zu7iSfyyj2O6Ae1rPi2+vY3uttPx7dwfC2m9GuZbX5jdY7DWHBheswydvzo9ku8u14ydw03Dxd03vFcex5nAn/8od/h3N4Ru+WKq4e7vG/7ed775me4cvkOprPYDoyNcL3G362JDvrbNdZGlsc1/dQI292Da4WhF6e+sOUS2SPX//qsJSy8MOrHcj31U0u7MCwvGayX6z9aNJsUfC1RPqGUTVc/lQzJMCnw81ISC3zEbjx2I1ISICceYAzFSoBj2sC6jQKCzuPWvaY2GC1XGnwt64hrZR4LkwLby3saH7D6/DCrhTWtC3EqQ2bUYi2VE9lcC6BsdnUj33s5TitRXEQ0zFtMGX5aDvOqsmIiIxrWpn42gLrcPAE4EXdWylzdnKmkkUHvCVZZSiuldl8XQzzQKOPSbCRcPIPhKNr/tIGXPEYt5Vo3SANCHEgCyNWrlF+bWMRU1o8GYWPT+lVINS42bY5VM5qFLNp6KYPHSSVYYLMZjn0U25dMjxngafWKrleHshpbZlM5t8kEmnSXSXqVzk0pGEIYzORxEJAYtWmFScZbayRWKMkO0veUqmUmSdaESGE60RJ1n8mizKK+jvGGB405+iYESY5XowSQ6/xx1J0lJv1gNj6oLT2nxXspHVgz6CjS47W7jABPP3xJyaklR5R3byeEywnMJQdyUWRzDMkZlfR7Wq6V3U1QFxaDjjKbcvSqKUv6uaT6m6oiTCvCYpI1JlJC1dKyAs5YFrlUjDESSJ06rOhnCrNUTlawEyHOp8IwJqZdmT28lzDsdNxJMpA0JpGsJY0uAdQo7rjOD6UTKyXm5BqOhaXfm+MXkvBvW6+Ay0Nhsav2BMtoEqOatJEh4udi5Em6HrdsZYIKkTCREk+odKdsDXFWSxlJv79+KsA0TEv6nQnlUY/fndJvy/n1c9HnhEJAHkAsLW6lrGyEYhXw8zJPHtFArJx8b1HObagdtvX4qRxLO9cJ2cBmV8p3vjJUx0G0hhX4SqJGTJTFsViJAcDXhvoo0s0NmzMWd2kt+XhzAYzrCxAqCHcrTGewK8sry+0ck/KevavEjeNTLz3EYt5ge7nWfvaxj3PzaIsv3brI3732XnbOSNyNvX/NH956he85+xTLUHF5ccjHbz3Mz9z/WUBMLMnY4jBc0fvv6e4k0zUz5TcVQ3M6fv/GMnZ8tpnxPbNbXLCRF+7u8TvroePNGXfMD9/3Bc5MVnzixUd5uPDc8gv+8N7nKUwg3K74tRtvoQ0F37v9FK4RPSzHBf58h20Mce6xnSHulywWG7qdwPqcYX1GrncM2EsbbCcsY30Y6GYSnVOuIvUrBdFBLAzFRhjD1X2ByeUVvkTY9lpAj5S/hX0nouxklM1ZMr4Yw+pSiZ8V+EUl5W9NKUiRWMI0Rtyyk7gsQzbHSNk1YnykOT8hlnZIO9CNaQaLjTCVae4xbU953MsmOL2eNTlXUs6HUQBomdzRIP+qoNrvCPWITTSitcQHmYcgM1kJYNmVdrkpHOWxzLnuuCEnifQy/7mjRtcnqbbYLmbwWewvsV0Y2ENr8CqlidOaMFPdfCrPOptBL3VJtyizfjGWTtYCkHVpOXR/MhvpSGO8z6XemHILk/lDPQuS7Wu1BN0OQeRGz2fXQ6OVsLLMki5TFtlQG9XYlMkhzRlO5lTT9wKik1GoKDTajVzVzPFAqetY1qm6XCEVl7hK5xI5M5FSdCp7m1QiT2HdqYtcGlFlALOJ/LvTBhkKjiX3eEjSeK3xhgeNyX2cXLUJYBE1BmeUdZgd0iBso9rWjbXCyqXy8KYlO60iAogSC5iMLQn8JQo4/UlGmRA1FFSErDHtPmwqafvBQY1cSFFdambTDPlKxg4aywTGrBl2EdrVxq3FUZZ0HyHrVcgB2jJZqP5uWorWRsNWsRa/NRm0IQrqwAx5ZV2vTmPV0GjZIe2ScU6c1hlkKovbeRVZK5BU1jDvwHLZXx2FcwW8Vp9bDGyyicI84D1eheemD0RjxBnpZBJM3QxMjLiVuCGzecZ7Fa8LW4APwhD0cuP6iculkWigWMtO0h012E2PXffKAsrPbRuIhSFMLGGaJjQjgLTpobCywCR2IUTRPzlLt7D4iaU46jR30eBL0WmV6yiA1UB1KG7PYiXaqvU5OW3tXBazpFcs2ijluEr0Yf0i0s8i3e0J01uRUIHtRBdWHkeeeOQVymWkPLuh65zk6gWY2Ybi0GJaw9H+DH9OJvaPb84TOksMhknZ8+jiFgA7kw0v9pG3VC3vmxzy4zsvsDdd8Rurc9wNLW/6OnmJv3P00Ff97JuJoTkd/2bDE078/5ObbT6hEoG5KXmntnMsjQCbz90dQOPjpeetVcOP77zApfN3+UpX8VJzhvOu5IPTO9gzLQ9u3+Vsccyr/TbRRNy05yff9tvMpw1+GsWBD4Qtz/H+TECQlY1Lt5AStbWRYmXoL3VsdizttlEZBdherncA68F1MkGsVnVm2kNBnkNMBF+To7BcRwaCaePWboNbdnRzp2zlUHWRqoHRwHFlA3vRJGMlLUHajTqi1U1dHwizkm6hpe5WNrRZohJjZtZC5XDH7ajNqVQ0TNMLOFa5i9EWh5LSAPZwnZ+fqjrJeJPnXO81v9EMwDCEbMSRg0vVNmXP9LtO+szojJTxZ2p0KaQcbjKYCmIQSpyGGgaN17idTudZrQTaXta8aA121WQtulFjaUz6e2MzKZGihSR5Iq25CuozYaDsZeGIWzOp6LWp8haHErAmaKSWtjnGp5TPdcLsqN6A6FQbv9oQ5hON29OSdWJXzWjNViNrGomQiEnKlYBq32s3tTA4060dMI21Qz5lei3FL9kslfDEuLNMjGqs4XWNNzxoTGVoU5Q5g9BU2pEjuYxA6Ol0Qvu0Q1OzQQgDvZvKxym3Kg4h2zjNOEwAMjnNohoucg6UUuu1aOhyzIyi/eiDuqrQHYNeWLMJGJszsqIB6kp2TumiANnVpSBUY6CQXqgnS8AmU/qxkngCiVWQ13fHjYSwjoXOJjFzYvyR3Z2AlWxICVH6tKbzqnoW23npl6oh11HLuXFaZ/OM6cLQVtCQBd1ZUjApxXiSXMpBgKrtovRpVqbQdGKe6WfK/urEWx62mTXM0RfqRDQ+SLi2k/OdzTkgQFkF69EJwAuTQrSEemzNjugjY2EJ85LiuB8mWiAUlnZuMV2QcrOHdkd7xPZBchsjhEo7KHSSEZnKbX5W5HJW0kbZLlKsgkSIRKQEZWQRXLwM1VHA19JdplzJ7n95WQCnCTLRm1lPqAOTW9BuGbpdj+2h2jd0M8NTL17BBNiqW7hTcvnyXbDwm7cex08i2xePoQxwKNfIlw8vQjBMJh0+GG63c37+1ps4Wy15uTtz4t48U634ntkt5sbyq8eXuB1OAscX+8if0Aiav3Ltydd1v5+Orz9eHeVHvt7h7lkivn1yyPsmh1/zsT9x36f4mft+j7/47Hu+6nd/4swzvKnseMfs5Ry6vjVteHxyg4/efpQXmrNwtiMclfzm4eNcmB5jFh08sCEUEbN2FEeW6raCAQt+WzoUbY5qQgHnt4+xvTKEHQQH64d7ynWk2bLCLM4NbmPY+4w8xvZQH0bJZOyjuKl7KWMDFJtAufSszxX4iWzgqgNoz8j8HCwUa8/6jNz764sTbBvo5wWb8zV+q5L5T80dttMUg85TrqTbk5/Kpr08DrnNoW166epUyJzhZ8JuupU0EBBgSdZ1i5kGYTlTH3t1O5vWE7YmQMzRXLKZFfDmdV7LLGVy8CIAzC43J+N7EvDpvQDTxO5BZlmzzKhwEqWjmj/bB+xqo4aiYigb5zg5O1R1Ckdx0Eh1rdJ1qFTZkWr4jYJKrJG1ZFReHtZDAYd+ouXmkbTK9LJpR3ONTZDs3TApB3NO0jhqz22TGmCYxAoymB41gUOMMj6v9ZRKSBhZVOIIXwCD3jCVu43JSSvyGeLgU2g6wQypgqf6x+SjkOxFo0YXIV1M2wnZpSkoKZsxbwLGeY6vMd7woDHr71K/SVcMBo3kYEIznFJZd5QLBWRgaSot8SYtYwKTVoCZSU7Y3svPu55kVKFP7it1inVStkhi3UQ9S3B4OUTSEAXcKBA1fS87kSRgTRfhKBA1MXVGc7gSgEsXvOl6cfemnzf98HmNkfdQTR+jTi22lSiZkFyCCWQrSxjrAtN0EnORzTrCBppGXX0p/kBF4EAOXs26wbEqt+sJk0qYT2cGsOscm7NqOuqljJOjJIwRwfpa3s9XTkrb+n7J1YgP9AspQ0fV48TUUSEI62c7+ezJ2WxadVH6SHHUYNoe47U380Ru8n6qxpY+EEqHn4kYvjoKUmLulclbemEeDfSzgnbbYbtAtyU/C7UjOCk5r89LtpqvJOC7WIpWK5TCHhQbOa9+YnFtpFx6NnuOUImZJVpDqKA4t5E+vgZMgNA4ptctJgjDYlorLOSZiGuAqafbMhw1FXsPHHLc1tizDc1BjYlwbnLMuy5ezd0dnI2U85b14YTKee6r97l9uODB+jYfmN7NX+vfuPUmvn3+An/nzmN8pjnDDy6u81tHj524dZOOEeDsdMkfhDHuFf2tHhfvybX8Vo/79fv6L0f9tl/sY87O7Akch4qvtDsAfNv2C7y1avDB8sLTl5lNWiY34ertM3xo50Xm05bz82NsZ8CLySo6iHsds4tLaEXfOHvF4KeRGzd28ka42ZFj2Zo1tAtD0YrG13ZI2VvLd/1MTDXFymO8MPdFK4yjicIy2sYTKvm32wR5jS7imiAa4InDJvdzQMux8vx2IW7llImKAqoc6q+l5aAaxTBJrBC5QpJ02aGyw4ZaWbFuT3SffjKUbpPxMDorG1knwDM5kmMxOh5rsJ3H+CC6bGvw00JMOWrAjNNqMMAko6IdysgJOBFkA0uIWC8sWWKvwkzbuaqRNOn/7aodqlNKuNjODyVldXun+SXq40zbDSZFXcejk2NN5XmZp32uNLpuxAwGye712zPMuhuY280oJsvLWplIg2ycTX+c1c9o9LwWQ0QOiNmk7Yf12wc1FyVJgTKMYzNock4nXaQ2kojeizs+Odtbbf6g2IOEcbQimc+ffgGpFXI222o+tHHFEK30dZok3Dve8KAxO4NRPJEu2BiHWr61mZY3VSkGlThqE0eUfsEpFDO9dlUOGYdBQVAhsTbGqDEkoiJp/QILB6sNMUbREaZjGrGE0Vq52JwbjqXps4OXKLtBvCdOlN20hn5Pe3/aFHRtclvClE8FCBvXdlJWBumIUBbS/7jtM2uYb4zeS/xNkGMuVh39mTlxNhGWcKNttBRkysQRiJMyu6rjpMogPMxrfU8nZpc0aaQog7KQz1844kRMIG7V4Ta9gDwAZ6kPZVI1PhJK6bDiF3WeCK1qRTZnNGdxUmqpJCqTOAip0/lvt8tcVrIr+VyhFl2UlJGKoRxUOPy8lDZ6TSTUMuGlln9ynLprN9Khotm2AvycuKXbLdFGSeAwtNsyEXczK9pFxPFpu6hlMitMYYy0C0s3s/QzSzdV9iFCs2VVYyWO0fJIchaJ0GxKdXPK5VjfsnQLAaZuA9Mbic2UYzZLBwGadcUP7X0BayLhVg0TT9zpaUPBsa8JEzl/y6aisIFq0fKDZ77I+6f7/MwjH2cZan7h7qP53rl/us8yFFyoj3iwvAPAh3Ze/Lr38R/bfe513e+n4/dn/H/3H/6mHn/Ty9z5qeXD/PiZLwBQYHFEPnt0PwAPlgcAnJkt6aeBo+MJ6wtQVD2v+p6das31oy1CFbEesEiXmP2S9tkF1b6YWjrV4UYXWV8UYNmd77EBmq8sBoBYS4kaBiaxOhT2a3mpZHmx0HzUQLswuE7ut3avojzW+WHLUR2HIbaqDVKO1vAM1wmINCHqpk7X9l5Com3jsY3XIHBE95yNgFAcSsZh6nOd+2lvxJ0dpsVQGdH3J0ChmsPyoNEKjLCAfprMHV42/VrhyYAjIq7smbQdNW2P7bXffYrysVYjhQQo+lkp+shNT6wc3a5q5UIc2FFN5ojWSFagspdxomXrusStuyGGDDQVwg6sZyJb1p1syFGCw1qROWksW5yUYkxseiEElISQg0crSlbA4aTKxEpO1WjlOKiTRC0h1DgimPxQWnZWjD6J2zCQTaKKL8y6lbWpUT2mM6P+3eTyfKriRWdzY4moVcfkBUjVTJNymn2QaqlTdjHlUUbkPRN5lVr0+sCQ5hKlWqkVWHnzk7jmtcYbHjQCuaxsstCXwZiSWvglyjlvjVRLZwbgld1MiR3Mj2Ogl9MuL8WlgIZZl+Q2R2qMsetGLe/qUk7RBMmNVRWkYG/TdYOzuXBQFapZ8VmnEQph+PLFZqUZuYkIk6rC5ViVEgmRRMUgGhtDLgMY7zEhiJZH9RqxsHKtR/ncoXRYLVFLJxNHqEbaiATO9DvwW7WAMC0xJJAZreaSdVpeBtkFTku6uey0Ql3Ia1txpYVCwz8qiWCQeAuJhqDzmHVHcLKj9lOTgXu3XeE2/RCLY4zqFnVjYdGyzlAuCIWhOOzo50Xu1pLK/BIdKCysa5L+hjzJdjOr+iZhCsq1LGqicxRWMGk8i5Wnn0jWnFE207WRYh2oDgPBWVwT6GvDZrfAdVA0cgyuh2bPSTD3OmbGUUpu0v4PYHKtELdoE3Fr+ZlbG/xEjC+bM9BPJYcx9d21PRDgF17+Ng6OpoQqUpYeDgsaX/DI5CbnzwkA6HvH3nTFB88/w5ebS/y1G2/lOAa+fXJI44scxP198xvs2Y5L5QFb9vWVRU7Hv72xXWy+4e9T3+tfPhRAeK0XNvFOM8utG49Cy2eO7+dgPeFz7YQdW/G7my1WXYWd9RANP/u236Y/Lvnbz7yfVV/hN7qo7vWYeQ82EndFkhIeaLAeurM95aHBFIFiZSiWEdaOZlvML34ipjAQ6UbSOto+ikxk4Sg2ou21faTZsTR7wiQSJbMxWlifdQoK7cAkbjuKUdh+ud+IntlHAXprJFqrEBDYL8qszbatbP59bSmWvW76UiebgJ9KNJdphu4zdiUVqpTW4Fa9ZN7qupbME4MLmJxLm9onmk2P7bzM7UHi27NUSVmxkLSNMUp5OgFIJw5s6SgjEWLlYZszGHOupBopjcqJbDusl3FSjvp1+8zuRSsRZImJjYXVlqxSqpcH6XGUTlhPH+g1Psh0nTC+bZ8JkVjYrFE3muwxrDd9rlLZVk0kCegZTbDIxz2sY5lM0qSV1DM7y5FytU8ZR+3mlRJDcvxeckxH7TpTasKI01bA6hkA9T+krjXptVNnnhQ6XiZnum74FZgalWJJjnI5JPHY4boRPHlangbI3UwyE5jAncbrGJeiakxu8SaaRgPGZseU6UPu4hLVJBMTk5eYzPlEbpTIKF1dSqkmNVVPhpOUK6guXZwlTiq5ifpALFXvZix+pi0QlSGMzmaGzjQtyRVWrNS+XzgoC9ozs6zbk04kylQWllCXmNVgKGh3SwGgUVrexYkEYheHmyHIVQXJtB1R3YJJGGw3Hd2ikFJHKxqXUGgeYgLLQW4yt+k1U7HIu8CksyQioNIKm+ZaiZBInU/cSgJvbeulDNT57NYO0wrb9nR7U/qdiYT71o7pTelRmgJlo1MXtRPnc6hcfu/p9TXjDLJYSGRGEnjnfGk9Ptv0dNqXtpuL07G+K6aVaKE66MUQAxgPbu1xm4CfSj/bxDCClKiqY1moyiP5ebEJmRUhRtotSyigXAVW503+uS/B9LC8aCVn0ZGdoocPO4qlUR2lgMzNoz3tLsQCum1ZPP35LjOGzDzNjly+oYDqjsN7iztwnL1wRN87irMNhsh5d0ypFM6lnQNq6/mXT7+NL9+9yOHNBf/w5rvYxJ4YDWaktj6MBaXp+cd33/Ktut1Px+/T+IHF9W/4+xTFc7k6oIueM07kBH/mwhfxRF71PVu24i3z67z9zHVCtKxjx8R2HK8nTOoeghhqXGP4uTf9Douy4cELt/nONz8F+wXOedyhI3aW5ixwTbSM9aQjlFKKjgbJZiwDtoflAwHbpraC0E8NrpF/b/Ys1VJYRV9BsRG9cHUkGt80XyRndXUs5eli5SWhQLXBppO0glgYDefXSsHE4SsGI1wpgKrdUT23BaeRWaHSEnKKFtOqS7NXin56WrC+oFFuGVDIMF3QYwz0OxPRpVeFrA8K9NDyqp/YDLxsN5hTpPqi8/O6G7mktUSaysmtyKOyltDIumlUCwlgmo5+lpIghjVXpEuOkM0rYDddznekEHmOiaJVNE2fGUa76cTIOK+J80nOWzRhCFWPZYlZtZgQcMsml3iNrjmxcJhNM5AaMUpWcTKgJiZOTTeJacxrqjGDCztVHVNZu+1GRlddJ6PoI9HPQ4rm63qtQDpoulx1HLd+HEfgiIIuasKKXhujjmwsZuTUjULbWKZ0kPRhvSe2reRpqrwLjdSTuL0Rw/oa4w0PGoH8hQ92+JRjqDrBpENI7FFV5ro/ivAlPNOdeLwJ0h0mtu0ASiM52wmN6kkXWFRnVW5TqDdO2rGQhbOAOsRwFrfuBlNLjENHk7TD0Ys5ZQ6aVoTHttP8K90NxWTiUTYvO7WNtIwjionlxM2e7P+Fw2Z6XhgttxTgGmvpcFCsRtl6nRfnW+oQE6OWRfvRBS0Ts6/l3Ce3c3RGAGdEPjvyt1sqyLXpWDUAvJRyULdwMqGFmHMOi3WPa0RbSDonnVext8VtgjiXU16mTREIDBrIyuJnhfRsXnWEQnQ/QSNxQiGsoO11Ims9btMPPW4bicmQLEVxXqZJu1s4MdE4qxlx2vFi4WgXls2uo5tL6arZcbTbhm5bJjjbg2sCrhUXabWUFordQmJ3ylWkvqXdLgJg4YEHb8pnOywoj5B8yK1epLd3Ckxv8JNIVXdsXz4GK4tULIBGHJ+71YoYoV2VvPrqLl9pL3DzWLR4Z8oVz985g9tpmVYdzHp+8OwXmJiCd2xf5aPri3x8s8N/f+cx7nOWx0vP+7e/uvTsv5m02dPx78xYuA3/4O6bsr4RJEIp6SnfXS+pbccT1QFTU/KJg4epqg5rAju74qZ/7PFXaGPPqq948eZZbnULaSd4WOO3PGd3j4kTmYv6aaRZS5TJ0a050UF9UaJYuq2I6SzGQzdLOjQ5plAY+qmARz+J9DNDP4l0W060byjYs4aoWY7d1LDZFX2yawKbPUu59HRbJdVRxFeGbrcS81qQ5xebmMO5ozW4jce1kjvbT+W1irXPMTzJiBcLS7nfiDlOsyNNIJd5/UQ+SKidrgeyltlWdNOmEZ2eW/c5oixWBc2WVcmNw67abBI0XTgx51Fp+LeztLuVrjVSxvZbk6zfzqxXJ3Odn5WDcdIaNRcqzCgLXNNjg7J1XqLFQMu3nRpmkmSISD912eVrO4lMyuV8Bam2U216rhzpsSvYG0LHS+Kklvm9V9IilZN9gNVGGFJl5oAhAzhJ2tI6bFJLRT2eVN3LeYujSL2yGFoPJg8EUVNXtLKo61O0qpNUiZkJQRJYikL7QyfDqb62hnmnGB17uJL1P1XYtWKW5HHZnJPL0zE7tV/veMODRpMs8zGBRGX6prVcGKlfZXYuq34Pk0+8Sf0ZNfMplo7YSOxBrCoRk4Ja8y2xqnIpWQwsXi4GNZiIu1l2MNKZRKINsvA4dYBp1aySKHB1w8W6FBGyT7s9csRAKgcbH2S3GFEtRZSScx/0Ju/zzRxnFZM7PptfUlxE0uXFuhLafjM4gqNFGK7aZS1MYhJTid00nfwbpJSgr5XK0qbt6GeFGGd8yCUJ0weavUKY0FG3HmKkX4gmL9YF5XEn729lEiyWott06x63bOkXVRaHF3eOhQXVzLBQmFwyyaVoY1hdmtAtKtE26rH0M3FVu2VLPy91907OPCuXgeWlCl8a3LLLQnM/cbS7GtvkJRPRdD7v7GVXDd2W6BvLlScaKQd7jSIs15FiI10vXAf1fmR2Q0rc1aFqruaWcg2EyPS2TMTrPQGL9WGkvit5c+Uq8tJL51letExuk41Hobf0k1Seg+gizXHN8vktCVv20O166KUf8AP1HVgVVLOO9z3yLJ+89hDdSpimg37Key++yDvOvsKibKiqnh7H37nzGE0oeay+gY+WeTEIzh8uTk5Y173Hvd78h9Px+z7++fHl136QjjeVHWerr21aSq7pD0zv8lvLBwCYuI7NwYQzkxVv2brO00cXeOrqZW4FQxccZ3ePeeYrV1i9Msd2gIG7yxl4k/WJxaHD9HLf1OfXtNdm2MZKj/QjkV4ANOciwUme4/o8FCvpilQdikEm7HgtVxfYDvqZY3nRCsOo5pdqGWm3C0JlKVZaYXLSSSk6KWNXRyIz6eZONnRaPpaNbUk04jKODq1ImEwIiT7SZyZvzChWh9JNKhaWdkvmVdtoXqDm95lWQsdjrXFeajj0U4mnmezrPJ8c1qAASBiqMNVsWW1akFjWbNyJZKBnlDkzvRdwWFgx/jhLsRJWUcwsQgj4usAsN/TTgWiI00oqP22fGVe8sI1EpNJkIDqHO9rglo0+3iswthTHLcVxKy50BZN+XinQIzd2CE5ZUdXtC6mjIM0H0TSqHjQN07S5tWJ0DhZTJfBM/mNGkTdyLlMayFCKBgbtfjKl9Cp7m07kWFfatrDvh3VvzNTW1dBZLXfQSUkfZgCS1uT4PklE0XaJKfRbHdSxbYVACVpxda8PDv7+2un+HRixLInd0PUlVgWsNsrGyQ0wLpkZY7KANMfxpHL1phFHlLraTNI9RiknmxglFBSIGHXb9jkLMqZMSKM6hLqU8mqKnNEbxySQaIzEAejuK4HC2PWSv6S7JaHRJag0M5qFxTadMncuA8GUEWZXjSbsI7qU441Q5I2IbU2Qns02xfOkANnUJUB3bqG0VIdtdvmxkggAv5jgjpvsGhvaVOl3kJ1+kfpOi5+WEgpr5L1cF/OuD8Qd6IyykKXswOh6nBGa39eO8ki0NURo9yZSftGbNlYltJ2IsksBlnIA5B12mJSiR/SRv/1/uoDTfrMhGVe6SD+zVPtdBtXRgOsCt97j2Pt8zBojPylw655Qir4pFFb0T8tAsek5vlIzuyGgd3nZsnhFO7tMhSVst6U7RrnS/rnOyHeBMMOuDfjK5snVthLYHSopmbVbhmIl7mrXivGl2AQ2e45+BsVaLt1uK+I2hlBHwl7P5PmC1ZVIcWRxG2j35Lmx0l2+gX/YPoDphH185+MVLyy3WbUlW9zib/3v3goW/qsnfof//itv5sOPfoz/890P8gO7X+Rftpf4oAbT79Hym1zkqg/cr99xG3sqU3AQWnb+Pe/b/G8yfr8c1P+6r3sfR3yB9Nyvfo3fa6e8oxqClp/rSn6zvHjiMX9v/xH++O5zBCIf2+zxleMLTM5FPrp/nsN2wr+6e4GL5w8J0bAoGv7Luz/Cua1jKud5+epZqgNh/PzFlrLytLcnFMeGfh6xrSFUIruw5xq6ZYndWIqNUUYFZq96Dh432I2YvDaXPDtfNjQ7FqxIMPwkUosnC9eplrGAel9IB+sjtg0cPVgyuSOVoH5qqO96lpcLYgHTm4FiHVQnKRtwPxWtXHXQ0W0VlEdiFulmlmItG8dkJEmbcutFa7i8UjF/RRjBUEqIOEgpvORlfv7/doVuUVC/uiLMa5nXq0I6XGkmYlT3r59q1uRENrJJfpOzEyFnN7qNVEeSVCcUFqeANFSOXhMhrAaD+1pkWdNbbW4zmDTzdtWCOrBjjDkuiK4nVrUco2raXROIU12HnJV52jlZ37T0TOcxTUvYnmmSiKwxVqOJ3HFDtGKgjLEnzKa4psdteql0RQRgpfU95wGTasEDY6ikS9Qc0myetDH7BwxImXm7FB8CqL5eKn1Bm0HESQk+Yo7X5PaMbaelfV2qUhVuDOBCVG9DlNi945V4NPpevBVePBIxyuOMK1QXGwH9nIldTCyo18YkkSyby/6D1xhveKaRTZMbqEdF4qlVX+4cYjUGRzUCpvOjyBvkC+v7IY8RQetov80YYha65uBQpetzqGfvdWelDGNZnGTRghhaEnBMP/d1kdtM0fXaWUUZxhBzIHZ6v2i0JJCYSedyN5IEwkwrWsrEAma63Woafu4LapTF00BqTeT3i1reC6gOGmFLC6e9k+WSchtJxLedvFe/XWuajtyQYV4RJ5WwbSEObbHUJW7bUWtBhh252wSa3UK6waRSQi5xqGvcSRnIT9WNpkHacSaliTQZSsBuApUO2/YUawFaIIC23U6xO+ArOyrjpx6khtX5ku2nDYXmN/ZTcWE2u2XWDaXvM5TSkstPtKTdBRavSA9b4yPlJqobXBa8fiLvUzSBZsdSLD3rcwIiTYi0c9ndh0qYF9vB+rywA6Ey9FNhQZozhmbXSvnuQMpyto+5c4afRuxtAc3VXWGti03kTQ++QqgjZur502/6COW+5Y+97WP47cD2pWM+f+cSP3X+C1xZHALwX7z5kxSTns+1E4yBjx4/yp86+zSXXMHD1S3+0eGDPN0V2V17/2hyTH2O/yADxn8fx9yeDFt/c/nV4esPTW4DYDF8YLJP7WTT9v7Fsxzsz8BFzlXHHDU1z79ynsW0wZrIKy+excwluLpbRB4/e5O2LXQzB25j8PNA3OoJdcTfrakXrVQCdJ31tcyL1V1LuTR0WxG7sfhKmEG3EcAZqqT1k3uoaCL1fsidlja7jn7usK3IOqI1VEdS1p3eCpTHUkLt5o5SpTqhsphe4rU258qc00iM1PuyqQ9FMt4p819afClJDMUm5o2wPE76ZFd35BwLecEJRzUIS5p+388ERBRrr3PLkKKRTIkA7mgtJebS4qeSYNFPi7wxTT3uTZQNqAFZa6oCP9OWrkbmVV8XQ3UpVbScIe7MVdOu62RE9HZJG5h0fxHV7I/Cy2uNy0uMmsqmes25NH3AaiRQcdjIuhvBHW0Ghk+NoKJL9FnaJBenHf5OqSgpfq10ohfVVA+Mwawlci35FEyTvBBGyKDUlrBTdnfdZZmUXBwDcDWjalr6bInxjKX6LkIUsiWRUG0n2sfEkGprwhjE+5CCv8UEpUSYs5kEi9o6GC8tBU+NMGmoZiH2vQRipkynFABqh4uJGIfol1RaBgGLybKuOoCYekJ2vQRxa7eWxPwlY0tOe1ftQUyvbW1uM2TS7iKBpIhejHITGC99mBMgy05jO3Iir6UlXayKnHwfO4lEOFHo05sUH/LNEmpHvyXRB3FWk/p0u7UYOrq57LL8vNSStNXyqkYLpAu/97lsLsGnysapM9uk81LJLjVoGHa3KLNWME7lPYpll284P5VerCCgy/pIu+1OTJLFulcHnbCDbtlgegmudeteRekK2pNuxmi3FifH4CcF5dLnslC3kFJ0KKxOukMLL18Z2Xm3gW7LSHuvUt7DbXwGfn46aJfKI8lWbLdsXhxiIYuG9QIW3drT7DlsK+3+xJlpxIWtiQvzawHbS7nbtZFQk1ugdTMpIfezSLGMVEeidzQ9GQxHA805nzPrAPCGUIq2K1rARDZnhTF3a8OF7SP+1ivfTnfW08YCV3r2D2Z0q5ICy4/vvADAQeioCs+T1Ya3X7rGy8c7gLQDvOIcH9p+kSfKnr/x9Af4hf1Hv7X3+un4fRlhpC996p62jgCHqf6r4+WvkSF+o9s+8f8+OnoCn1k/iK0Crgi8Z/oihQ24peWJrRu8e+tF0QceFrRnPa6Bp25elI5DZcTvSc9z2xgeO3sLtxCtcHxxSrESM1iogL2OWGge4zpSHcLkpshCQiUA0HaR4tjSLwz9XJ7rWqnuSH92cpqACXK/yRwom1JfG/qpyY+XyoRoDDHkzk3FWmRQ4tbVew2kTWHvhRFrZJ6IpZMoL71vfW1xK0+xGoGsIPrK5KZOWjjrlUCwJjN7pvMnUzOMwWs5OLuukc3s6pLE2BQr1V+n9IwQsRvRgAer4Mhp96sxoZE246WQFqgcx09H148VcIyxeSOfMyizFlJIBtMK4Iq6NsWpNLQwmxbXhdyMwbR+WMsTCCpknUldbmLOqLRDRnGpZtnUNa1JOZAj+VKIuWMYyVegeEG6yykgVHYydZwxSetYCDEh6Rsj6JX8DEUhgDZGco9pgwBINbeaTtlFxS4SnWNziHqujo6c2bmV4aQiancZSBgDUv/p16trfMOXp8W8IsAvTGtsch2neAPnMALQZXgN6Wxa1RYasIWyYRJFE32Aicu2f9M0xPlUgF1EaOcUHG6G/ELT9dhkvokQ+4GFivNJLnmLE2soS9tNp4yilrgTA4oyeur4jrsLAU2dGlCqUnIXY4TKKYup+skRQ+dW0pc0FkMotV8IC1get/jpZLjIVZtjlMXvd2e4RiZCP6tw627oEapgzHYhM279rKA4apUF1Q4Hc5nwQi07Q0uBaXr67ZriYENfG6wf2Fe3CTBRbWlhpZSihppy3dJv1bggkRcCuhV4a6xOArS+lvwxt+6wncRM2E2Hc4b7/hOPn8niYFvP5oylPoBu7imXQOzpFgXVYc/5hafal4m43RP3pwkRX3mKTdCctiAi+ybQzaCfGYqVoTqUG7fdLSRzcQ7nbgX6qWF2o9cSsgDLo7amXBWZRdmKkaMHHbvXI8tLhsVK4kRANJH1oZhzooHVBTEE9FuR4siwaKF9pGX2XEU/hWkH3X09cemo7xj6GZx95C63n36Y7T8Eb3nbit+9do6pgQcfily5HTlcFhwczflvzPfzbQ+8AH9+zd/4/h8kRsPdByf8kF1ysH8Bdrd5YnRPHoWWc3fgu/de5e8dvYs/vvscH9/s8B2Tg6+6f39zfZbvnt7+pu75ZffvMFP551/7Icv/6Ny37O3mf/vWt/R1D/wERh1hPtXMeU+9BAZQ+ADwS0f386NbV/PPfoRDYDt/n5tXz/D8mbPE9Tbuy2cp7lvx9/lefLD4puCpxeO85/ynedfmNrvFil979m3EjYEtj2ksxdJSHkv+6Ozsih954ir/n6uX8a3D7TvKpdwDxQranYrpByPrC4ZqH7ot2UTVB/GERm9zVowy1b7kLTa7kl06uStB+Qk4bnXCPCbpiAkCPDdnDJPbka0msqgbQLJTfUokiJHyCGIR8XVBsQkcXzHMr/W5z7Tpg5jOomzqQ9EPObT0AyDx8Mr/Hq78jJrZItgWwNHPNbA7gDuQvtB+UXH9/2olvBxNueh6yqM2b+R9JWkZcVoxvdETq1Ji1TohO4qjlm67kogdJwkW3ZkpxaqnOGpoz82pbxzjgKCVrFBa1dZHsNVQLq9UF3p3LWXo4wY/r2UtsbI22Y3IiUzTgfdYZfxc2vAfb4bKWVloBFyncigpxcdeTC8YyRwmtQHsJAcZLZmLnCsS216AY3InhygmwdaL01rJoljpd5UYXtUixlmNWbXETYOZTuR9u15YQHVHR2eh70QrWrrM5Ma2k7W5rsR/oLF+cVZKFnJiDYMQIwBMhOSJuFH2cCBGAZXGGukEk1oFq/EldbQhBOHBqgrjRkbWbzDe+ExjcgjpyGVoJxfV4OYlX1CpBZDp/WCdL6yIaxN6j4kqtvKFpPylUZ5TVM1DdJqHNamHdn3JRZXL0/q30vMpvoDE0BmbL7CoMQfixtYdZ2I4VZicdRIhQlXiGgWM3hOmVRbtyntL26qkbUlny9cCjIulaEiKpZQfirWXXaaR8guqyRn3PSWJm13aDXvNLVRxdC/xD5KfKOfCNkHaDRa6G1QXt+tkcYjW0Ndy3LLDtwJwtV+z7OqNtjUU8JtzqLyE+IZCvpOgobkpt8u0Mil127VOuBG38toNwlHv95iU7aYuRtfJmSqP+hGADVoWk3iOoGzr5kyZHZK+NlRH6ra2A3MppXHdaAQGfVMX84LVzaUjz/KSxbWBUIprsz4QnaJrNdtxA31t6GtxY/spuiAadVhDDFaYjErKRJd3Dii2W9oHhMHxwRIut4Qq8t3TW7z5wqvEzvJLd55k0xXsLVa4SY/pLJ95+hEA3nruOnHtuO2nABQm8JH1HgDr1D7OVvzJc1+mNIH3L54F+JqAEfimAePp+P0d4xaCP3/rTbyzPj7x+083M17xnj+y9VL+2Sebrfzv+8o7HIWWqui52p3hTLmkn0ZCNGw2JduTDcZFVuuK0ljeNXmFa+0O9S2L6Q0/99jv8uNv+iR+Ikw7gCkDv718KE+lftfTT9VMFiXgXgKyIXVCKpeII9lHqqM+y0HSY3KcTtDqRgfFOgqTrxvg4qjFNXIfl0cBtxkYxpQWEUrpFe/WgWIT8DOXO0b5yuIacjeYaOSeD5rpavqgG26Zm+TjSRqDWQ9ZgVYfl/pamwj9bGgCgBNNZbtdalpES3B2iLqxQ1qFHIdUVdLak0K3he0z+FmJbX0+7lQdc60kjYSpbNr8VKQ90v5PMm7tqlWToDjCw7ymPTvB+ICfyBxqmi5X0mIqn1bSmME1PX6q7WjTmtn30A/NHEwI8pgYJYQ7VdUMOTqo35kOEqVpOcTJOfmc47a/UX8myShezTMC6mI9RAuZyOAJSIyhup9zALcyh4RA2J5m8iVrGHWNliYeydSqTKAXw1HWKAK5ZzeKbTTTUTwHFWE+yUxyxh6KU2JiLUG73rhvcOcP4w0PGqNRbUJUR9bYMVapW7muco0/6xUyqPT5b7eRE5zL3KAXm+hR0s0iXyqatyhi16jJ7lHt+7EqhdV0Ti7kELDrBmIqA0h0Tnagqa4lGiMGF+cGCj9KudxuRr17vdLRqYStpprcE9oa7JGK1yMjZlTLLiqM9qXNLltfOdEzqqg4lXdTWdxpBxXCEHFT3W2HUkrbU661U0zpTrgKTS7Dd3ID+ohrRVvqNp7qWMpA5VpAdXnYasiuTJpJIxNrAZCm6bS1VqDbkUgOjET39FMVWEf5GS61QOyxPuIrJ62rQgQnxhzbeJq9QjqylGl3KTlqwtBCtyhot2SSCpV0dAkFqkMy+RhCAT61HdVzHQpxf7q1AGLbw+aM7PKlLKadLubklmWbMyU4aHZkQQMBhlGF/dEOJenq7vDeoYB6H+oXCjHZVBHbwfXDbfplhSu0dG0iYb8izsVI9uVXL7HYXnPr9hZXFofsX93hnRdeZvv8sYBdoAuOnbNLPru6nzb2vHf+PJ/bvwLAl9sdfnN9FpAYlnO25Nff+/XNGfuh/bq/Ox2//2N1z/lPwexpfPjcU1/lcg9Ytm3AYfL39231ADQfKSL/7PBNHDc1n772ABeLAx584AaXFoc8fv4mO9UGQ2RSd3ymOcffvfFunjs8S3s28OibX+GG7/mnN59kem6F7aFfBKqq5+kv3M/ebE30BrO2+BrKY2kTaHthBid3Au22AEPXpQB9aHaKfP8J+JFreXpT4qzahUTrFGspkfvaUq4CYVpgvUiIml3H/FpPsdIAba/lbGOojr10i2rFwZuiyaKFet+rYUHmiVhI9SMUMm/7iROT4LLFtV6NNcWJzi5Gf+42CohqieMKlRk6iGkJ3TVeOrrktoVSbPRTYc781kRkQtbQzzS71wcx9c1qSajQSLSo2nHTSWcyq+aV9Xnp+NVuq3QqRcClAG1ncGuPbbQK1EnFrzxWE6muo6mbikT3iPPatL3EsKW1PDW8gGENUIAZnc3RQ6brBwMlAu5N22GPN1JhWndS5vWpdA+pS1yOndM1zWjOol9MVK6krft0HZfvUp6TKpRCinTkbmSlmGLoRqRVymDUx8RaMx7bTnSKbsSeItXTFLFnvBA7se+FXQTMptV86VGwuibBGG0znD5s7L0wmK9jvOFBY9YZYER/57Rc3Pdipx+5psxaI2pSppLSt5J2Xwr9XFfypam+0a7V0RWD6ClS1xlnMavNcNFpyCfGEnZmuZUfIAaVstDSs4WqJKizOToztDLqfXYNy25IdwbOqk5SowY0c1JaKrkBrAaJ3elnhXQRyPlZTjrWjATSGENx1Ej5diO0uFu2WYODxvPYMPRtTjmLIOclWf6zGcRZiv0N3VYplL+KslPrPRPlXPQzJ3rCVvSMobAUx72UQZbdENDdjxxfXnaaEoch+Vyml9ywdiEO5n4mv6tvrLR0Ymi3Cs23jLkPdXIxri5VEtED4KRdWbEKJ7SUSfck5ylQHXma3QKT+ksfdnRTS30gILPdcrgWlvehE7Oj2ypwjQC++fWAawKTWx3lKtLPC9WQikA/aNfIciXMhFsZXAvrc4ZyKeUyPxFmpFvIwuVr2FxKPXPR45UWZwDF0tDugL1ZYjqkTSBw49Y2toUHztzlMLTM5tInGBd59sY5Hn3sGq9sdjg4mrFzThinPzR/jmVT8hM7L/BXX3kP553nykJYxHfXK66Ud0/cnh/+zNfvKb17aoj5tzpm95z/ZFT6euOqD3xbfcxLvbQzTd+fHQHL//vL7+CJ2Q3evHuDsztL7vo5H1g8y49uP8OPbl3l4cktLmwfsdqf8pm79/HWnVfxQTZlP7J1lU+sHsY/O+PJ3Vd467uf58y5I9pNie3h7tUd6nlLnHuwEdJtGgSgHT1oKdaICS1oFA4CHl0r94PthWUs1oFupmXSTpi7ZrcQY4pVJjJJXgKsHpLSY6gkxsfXRvakPmYZTD8txB2sLT6Llcc1nlClTbmwg8KKSlSN7QL9TPNotcQanZEoL5B5PGXLWgmlrvd7qjubHEHWbdf42lAehxwD41Xek8rFxbLPBh3jY349kRFpSkOQTEfbemKRqj0CLnPuX99nVDG93YkO3iCAKWo51sdMTEhHmSZvqNvtciB01KgTVTsJwvr5SUG3VWpeoer4Z1IFTL21U5UsOo33iRF3OHQ1Kg428rvCif7dB9UhCgFjOj80pkjxdJ3uKpJJtLRi/iydmFG0cmdUZxid6B+NGljll+PqnrY1VOLHVNWQQuLTOhMHP0QIsFSiRzM0U2vfaNU9Hck9qqOXz2AmdTb1mPT+hROAWZb5M0Xz+uDgGx40muQKGoV3A2Al4yhdaBJlIwAw9WmOxcgZncvFJucd5XqIloONtu7LQlxjhDmD7GAynTBpUfOwTHJe3eO+Tq+fOpME7Z0MZLBnVq3s7ro+78ZyuXrEhJo+ZUJBdE5KD5EMRmOpF7fS7Kk9lOlVE6g3SUyBrslAMymzSSTrBUGer2DST4p8PkJVZK1kCoeNFg0tJ9/wrgl5gklMWxJvpyyv6GTXLJmLVgw8zuYA2FhYbJqYAspgok476LYcxVqYBD+vCKUlVPJHdpPyu34hZZVQSDRHedDgJ+JG97XsmNstCVgvjtsc3mvboE7JQlsFIneblsontyQ2x0QBduUq4EujjIDNzKt8zkC5DCILGLVDqw+F+TDqmpZ4EGHGrRcwK45zcGubS2+2RY03UB0LmCwUhIZKO2dsRcojS6igCQV//dPfxcNbt/lf3vc5CIbFYsPNzYKmLzGN5eBoBsAL/TY/cOlL3AktzgYmpuClQylPP9tbfuf4Ie7cw2D9xkq0dp9tZ6/vpj4d/86Nf3p8mU8ei0ThY/uPnihJf3SzC0jsTrs/4Z3Viu+Yvsxbt17hfZNDLjrLJzfn+WSzxTurFWeqFecuHLBcTvjO6U26zrG1u+KfLy/xtunLNBc8+/2MT7/yAPOixe1L5mGxhLJIUV4GP5VcU9sr614HinXEtmIaCyUsrzj6OgVmC2gs1tJP2ldgvfy/2ET6qbxO2ijiI+2WzLnVTUcEilWgPvRD6VzlLCmL0bZBtIab1CVE7sNsmNSRWMloDbaNdFuJWRyBYcjVpzAZSp92LfmFKaLNT9Rs1weCRvGUx8o+Wc2XNAMITk0lbOtVK+6UpYvDYxQMh8oOaxeAc5THEouDD6rVlM1GKK0QFkpiGNB2tyYbUovlSBJWlzIfqw5fGD+RDJg+Drp/oNmWEriQMWJYlG4vTkkAyUlOsXOpwYd8R1oFLIssJZO2fkVmLcWEkrSRLpejxdfgc8yQ6b1KyxJm0M+G0fDv1ObRDqVqkx6jX6hmN0cr0rdYV8IMpiBwJZTQ8rjpe+kWEyVvEW1NbHQdTNVFaToylKclUcarmcYM7PVrjDc8aIzjf1u9kHQ3kRqeJ52DqTRR2Sg7aIBpLRdxEsZCTpI33hPb7uQbKk2dMhnTF2Q32jVGmUyJ9amG9Hwt8ZoQpVdllBZEbi3CXne8EQleVap2QYfGBZm2x9eDaJkYKfaXsoFTZxmoRiXR+yn2QFvx5R3OWuMcnFNQmHSAjmLVSQ/pQjoKuE2fs7pS3hheysW9di1IDj3TDZ1SbOsplh22DRrYPRxLse6zFMCmAFTVl/bTQsoakdyc3leWdiGMpG1DDpaN+tmnN1spT9RGWi1WBW4jOk5xGUI/l8UDhEWwm47qoJeuDCHijhoWV/tcznGNp1jJjVfflWugX1SSJ9lKJI+vTS4PJ+1kAnKbc5F+YrN2qptZJnd7EdZHaM5Wql/Uy6qSne3kjrxWN5fXKZeyKGLAl4Z2y4kof29wZvYLmL8iWkfbCdPSzSzNfTq5duTevOVcWiXunD0mAuURHHx+DxPhpeM9/vJL76SY9oRoOHh1QeV63v/Y0+xsyQ74X918gn916wmeac+xXW/oCbzzzMt8fLPDo0XgSn3AP9t/64lbZioKfh4q9jkd/36NA90A/OHFteyg/+nzX+L3Du7Pj/nAZJ/fa6fsliv+xFs+CsDnm3M8VNwB4JObXc4VR1gim9jzw4trnK2XnNs9osDCqmDdlHz5zkV+8an3QjB85fZ5CHD9qfNwQQ2IDtrnhOV87NFXRDIyE11ffRiob1llDeV6DxXUDy6JBeKW3gggjM7QTwxOp/bkfK4OU1UKAXI7JanDzOLlPpvrgjPUBxJJIwBFDWlW5pnUfaWfl4SJw228bkwltivpDPupAD/XBtFfxihZi1bAKZAbBaQsxkFipcDKGg32l5aqKTnCepXwVFb6W0c1e2jzgW6rzGRJqEVqE5OcqOmwjac8aqVndq8u4SDvV6rRMdSFnINeZEa2EzBu1FwSrclZwei5chq5ZvpAtzuR/t/JG5A+lw+U+xs1rYqD2gSU8YyEaSXHEJGWt8Zo57BiiMhhLMlSMqlPHgVh6QZHuskmlNSUAiLF7WNtqahgshbJmWm1d7U21ZC1vRy0iGkt0M/MCHQnACt4Q94+TMrMRgICCrXfNGi5Wk0v0pgE1UCm8n8/dKkry3wMkkXtpOOMcydCzb/ReMODxqGNn3xBsZKcJ6OUL0AMElkguX1WKs/tqLWccxpqjUbfmAyOjNM8xBH4S7uYOK2FfUwspeY/mbbHrCWwNRlaBPmng5adzvA+npQgHwsV6lbaFQYUTBa441Zves2SSqadMPoDsvvqw4gql9KtWUvMjfTQVKZv3RJKQ6gk8FWaz/sh01EPwLTCoIZ0c9uUlegyw4bR8kItO7VQykSUNHuJrUyi5LxjbFVXqu/lZ5o7qbtg63US1AnU10U2ASVDUZhPZIduZLJI2h6i7BiLVWByp6PYePpJcoob2S23osMMhTCQKUYjhbunyTS5vyMMC4/qjKTHrHaOsFDfEY3R6oIwi0UTc2BuAo6ujdJdYioLkfGRYhVpt0VAb/tAN1MDjSOzzGk37mfapitCs6MgMsri2E/BWBH2hwpcK3l2fefw08C56TH9ji4mqh073J9h9AOu70xxG8PNgwW32i3um+0DsDXZ8Mj2bd43OWRRNhRYvmt6h5VSpN81vcPd9cAo3vA9X9KOI6f5jP/+ja/3nR0cSwzP77ViiFrYDc8dneOSds+6XOxz3smi/LmDK9z2Czah5NeOHwbgdjPnAzvP8Av7j2BmPZe3D+kPKmxrMJXHbwqKY0ssIv2moDyWa7jbiURveO6LV6gOAL3nfCX3hgTgi3MaYHN1LsxfFymPtfJh0RxG+VM0cr8Xm5CNMdISNWaQKfeY06pIxDViWksGjCS/abct/dyJpq+ParSzNHsFxToIkKytbI7197lkrIaX4rDNcWl2uRkqVSnfTyVVthFQVKxko+6aVELXNdFKPBgxSk/pIIZPMT/2BK1o2SZgmzCYHLWFLt2g0xcjkc7fzg5dbUbxddEoKFeQ1u6UA2jqvWgo19L2Vqp/o+4syWugr5ti8uxaNi3VUSeVJ6ef2xj8Vi2gKcXOKGgzK5GhxRF7SPAa4m1OZkYmaVdiD7uebKD0fXYsx64fcim1epljeSKZxYvqh0gG1bTuZwyANBWJ2uwDwB1LWT16zUH2IWc1mqCmG5DqqRqJcBZTFln/mIcfgKyxlhh8luAlEum1xjcNGn/jN36DH/uxH+PKlSsYY/iH//Afnvj9T//0T0u3ktGf7/zO7zzxmKZp+HN/7s9x7tw55vM5H/rQh7h69eqJx9y9e5cPf/jD7OzssLOzw4c//GH29/e/2cOV8rQxxEZLYlH7RybnWIyCtNMOJ5WYg7idhhFzQLdE5kRhKkflZOlTWogeMcTB1ZRc2chFk4PDE+VukBui1VaGpZauVbuYs582rTZSl+Pu5yX4oC2fHBDVACMahjiph/etnIBJNemk15d/qFsuhhOlZ6O/6+ZOgVuEohCDiTqkI+ikIOYRt+nFcFOKMNr2kWKpTjwFhbaXXbhV4GrV8JIyHe26lclS9Su+ljysbi6aoGIpTGU3k/JEsb+RGAjV37hlK0YXa8AJO+mnksFou0CYVtJdoRTAZlufMymjAddL+Hje2Rm0TWGn4veoobeozki+H9cETBeIpQDh2aupx7SUyYu1LDrRqemliUxuC+BzjXSSKFdSjnebkDVI7VYyx0gUD8ii1s0c1ZG6tMuTOsXZDbku02KYrs+g8VKugdA4NmcjRp2htjPYg4Jy3nGnmTOZt/haAGYx7XHTnv7WBOcCP/P2j9Hvedx+wa3NgueOxOBy3/SAH5pfB+B8emNOBkC3o6y/C67gj5z5HJuRyeJjWs58o41x/M0bZfyL1YWv+fOfe/RTALlTzCNF5N27L/ErR/fxivcURq7PTzZbNH3BY+Utvnx0iZlr+cRmm3VX8tuHj7JdbHCF5//P3p8F63Jd54Hgt/bemfkPZz53xsV0CYAASBCESFGiJFODKRZZpExZVbarbSvcVSo6qjqiwg7bL35oPznCT2qXg+6K7rLU7mpJLrmqPMiUKEqURFKiOIsACZAAARAAcXHHc8/0n3/KzD30w1prZ56Li4G2aLnRzIgb95zzT/nnsPfa3/qGq0drvLAZRZgDh2JigERwM0J5wyA5YHE2otwnuIll2xqIEKYF5mdkYVQAaezRrBCajQS3ANw8IRSM+CtCX07E8NsRx2iO1Ks1ZJNtE/h1Uf6BgGaVjfajY+eC5EyOwmMOthj2S1HHefaeXQzkfRU1JZ3vE48V2cgb6Aq0UviEwh1n/h5kTLVo16vsO6shETkmVv0HhbaVrLaoedwxwu02/rjzBGJCu1YK6ugFoeTYWLRenCkIZsFIZhLhYCysoJop05q4LSz7JYUcgBwHC0hnbtmAlnUHzkg3UFu9yj3PhtUA7KzpUMSUuvnOGnDCCld/XNjqsWEuKRUuW+jBqpC0y5AmH5gPKB6LRMQaCUiBKbxMjhhM2Q+SBDyBpMVABLJaA2TE0RqklkU8qdbnAQieu5DOZr/G1Ig9YAyACl804pE44S5FnruT51zqlEGqnhn4sb7sK2/fddE4m83w8MMP45/+03/6is95//vfjytXruR/H//4x489/rf/9t/Gv/k3/wa//uu/js9+9rOYTqf40Ic+hBC6qviv/tW/isceewyf+MQn8IlPfAKPPfYYfv7nf/673d18cVFZ5DYz5ZOPjKwdQx6LgvmMKs4IsWs3xy72KRFxTdYzyyQvmZMqKgHQNxolH+TC0X4xOtiaCBpmnlc8wk+AchFCtyowTZRWQ+eETz6gXeUbOieeCPk4DcWDQlcUWhQljoNKErHH3w1AwyupwV6T2xKIUbiEko2q7+EM+y9C2sZELHw5avJqLLfIJSKrf1wUJYuWUdtYSYqPAafFRDa+1jYNBbGwGBgpUq1YTwQgcVEaxQoiDLhVrN/Ljx2iI7bUaWTlnUQ0MrCw8wDIwBqHZb6XWHXIBPcw4PPTSgZsu+oyl9Iue3bIBMAgD5DtCiewVIcRtuZnaT5tAiszy4M2Txxx4BgJqQP8wKKcMNdyuJOk9Qb4sYGbM/cK4IGpHRvYpWGUpeI4QMgpSJa96oojg+H2ArEAmjVi/7iVgBQJs7pEvSjhV9iSx88dYjCoTi5QuICCLFwR4FcifmzzGayUXBQ+c3gSn1ts4ldu3Idte4TPLzewE1rc8Cu4LPf337zzS8du0ROmwKAnsvihwcEtbuTvb/8pbvdXV172t+c9Hfv9t464Vf2Dgwm+dfUMzlmLs9LNOGUnSAC+UZ/Df33qSVxbruJzV96ExjukRHjhaBvxRoV0vYKdE8pRCwockZlcQr0d4ZZcYBWHfB8ox7dZAxviE0Cex5JinmD3ecE3uM6WLn1T7uGNlJXPpk1wyyhtVVZg1+uOW9tS3A12G17QBUYX3TIJJ5vvN9Mwx814tt8Z3vBibcPjOS+UDcqDhikz0roOJXci2AaNC4UofOw4KjIaBkAU1ywqYe62BE04w0ECBJCPKCcN/EgW8y0jedoxS6XlMY+Y950Ki2g0PpbHSFtLy9QZ+ZnnVuU7NifGYlXWCjoamFutrdAEmHmTeZPloXgPWhInEIJfr3KHzCwbHq+qgnmEohegpu1CJATkCAOXvYFjyVSljPTpcVJRqg/ZUSVvhlXQtKjze7IWwIsWQZLaVHwzkHnBdnOdKrmJxFElpc4wvRXwSgtKBbMSsr1f/nvhuCZRNNEQI4zGQBXeOaTkJqNvCoENvnvm4WS7WoQMI5nkLPtNC+8y+cCA2evYvuui8QMf+AD+4T/8h/i5n/u5V3xOVVU4c+ZM/re1tZUfOzw8xC//8i/jF3/xF/He974XjzzyCH71V38Vjz/+OH7v934PAPDkk0/iE5/4BH7pl34J7373u/Hud78b/+yf/TP85m/+Jr71rW99dzssBFfepOWpLvVAxyEA+MLUat+IeWjddBGAan+jiSpBLQTEU9CwWpla3xlc92T4x+BfLSIbf2wFxFxJVeyK1F85mMqrkM9wkwUrvpY+Q9KpcMz3AAR6ZwIy+vwN+d5JLyaB5XOEk2ckLw0KLpqiFFYa3yT7CmvFMqC7Obg9H3OLOQycOOBT91oZ0LQd0q4VXKBVTtBCysfLTVtGOQkwKkqS/bRzn9sm8MzZQeBUGxaQCPE5JBRHvkN0A7dssr9Zyb6QsSD4AaOlTCDnxBYKMSOb9Tq3oN0iZp+3PIATTyZByOFh0N2sYeTQji3KQ0hRyOd/cEP4WI4XDO2Q0K46xMqgXrMIJWF0TVNqGJ21NftW2oYnunZIsDXQrrDVSBhIa/tAEU3A1BwpqKIX03CbelkXaE8FzqBeEP7WPX+CN29f49M00XsE+PCbvgqaWTTXhlgrl/hfrr8Z59YOUV23WDE1ho4XDA9vXsIXL92N9XKJb8xvwxcvX8CnJm/GB1Yu45y1+OPFFrx894+++HA+Pl+tj1vvXA+3iBX5/vZnuv3O0dmX/e1sb0LSbUtQ5adahr1L4/GcNziKDd5+G/s3/s70LP6Pg7txEMdoW4evXb0Nj9bMR4yB0E5KTOsK8xm3v+M2p7q0rUWyCe0KARstkAix4PugPGRkPVnAD3jxZJeQhSaABDTrhGImfozgIhJgjqOtuzxppajYZeTM+HnKIphyKt2YgkTQl9COLHubFp2oZLAfEEpRKBNY5EHSEXBGxgceC5MUYuTZOse2TJmJIhikhj1jKchYrQdbUMRErKBuTwwZJIkJ1ARemCYAPggn3bOfriijKfCc0K4UHB0ofMdYMI+RUhJKTugs4MDFsAoy7XQJaiO/t1q6STHl9qagNuSoPyBJJ8lzaEXpcgfKTRtGYzXGF+giYkuHuDLoii9LPZAFPBfKXJSLYkkoY6RS4nG1g5jQtdrVAi8BKfH+acxutrQrHMyi7lJghHMYK+EbBkb89Jxgseja0PwNACDTuDTKmNvE1NnoqNvJoGR1c4h82JztikFR0ZPWK4CgnPJJITD6qIVpYLSTi2bXdUvzvav7eHyx90rb94TT+OlPfxqnTp3Cfffdh4985CO4fv16fuxP/uRP0LYt3ve+9+W/nTt3Dm9961vxuc99DgDw+c9/Huvr6/ihH/qh/Jwf/uEfxvr6en7OzVtd15hMJsf+6aa+Sjl/UeB35jfKassL7GuYwMoZzMwL6MLDKV9wmZhKxNW95Fhqwck5lBAoW7mRzPdLKs9PEAIzxxFC2989WX7SjGqx5cnfR6OBCg4uzx5V6vFYt/x9hVQMEKfXaMSfKtKATiijHEhVu5W8+sumr2UhfBUpCkt2x4+j8pjRq1mI0Edu6ETgFrOiknwoM5Ko7WYkNgHXsHvNXE3UqdLMrMltlVxsJ4gHJSGMOWIxOoMwLLL6OJFYECVV/Vlp6XSq8WTZUoczVjnwPQxUfcfpLdUBHyNuZRPcki2JQsloQrJcAMZC9t0SmjEnMRifUMwi+5xppJ/jPOjlJg/ghRDcOd5QOUCQIpTEB5LbbuwNyZnTruZ2WnnEKtJ2JAKbMSMvg10uFP2ArXi09RVrC7vPEzEI+CdPvxMGCfW05Ag3iST8xuI2abUDl3c2cbCzikuTdfjVhN/ceQhrjmfhh6sbeNvZSzAU4UwEaoO/vPkcZmLsPQsVvtVuYz82eP/Zb+TLYdV0dhgAcD28sn/j97c/m+3ibDP/PE3HBYBdJADzHF/0CUvhSpxwR/j9Gw9g1ZQ47Q4BsHDm2nQVz8xP4SfPfQvrKws8cXQeV3Y2cWrzCDQMWKka3LZ9AHuyRvSEUCXYvQIU+N4ZDZq8+GlXgXYEzM7IuFokXjy1/JhSQqLECdbbyMIwgDmO2mJenkjwI4hJtsVym1BOAtvoGKAQug2AzCVkH0eml9RbXGxER0gFIQwt/NjAr7hsvm3amHnYseiKnyTdERKeto5ZsWIQIjkjAQ/8+VkAI90WRABS3DEvHjz0rw0ASEfJKMXF5u9RTFsWtMgcZtpOYMNIm3gJLz3QcjcriANIbv/WLRtli9UbU7F4zlDbNZI5D0CeV5PtjcfCuUuWjoEUGtEKHySStut8saehULqaFmFUdFxIEeeQqrTlfGWaGPj4wIvXoZp6K0Ah54SaNvsld3x7Nf1OAoqYDPLwZ3dIHkTBnVFJRSDldVQWHd9QNnIMUpGz3KImykVlVqxL8kv+PHGKISeJcIqmSpGcmoatA6OovbVOFG3G69n+1IvGD3zgA/i1X/s1/MEf/AF+8Rd/EV/+8pfxUz/1U6hrXn1evXoVZVlic3Pz2OtOnz6Nq1ev5uecOvVyrsypU6fyc27e/tE/+keZ/7i+vo7bb7+dHxC3eL45ElfdXi4gEZjwiZSCTyt9KeLYn6mVVUPMEX9xVGUVk964bCTaFX3J2Q6h7CGSNOcwdY6NCsBSeIpqIpp5knKx6qqrFJO+mMRIXJE7w4aoSmZWfgSxb5eRXGoYYiWWrNCOKberorMeEiW1kRznZIijoOQGhQhO+MZMmRiuKnROCIgZoUtEMhhwgWpmqs4m5jvK35kbKPyPxHY11HiYEOHXhqLS5oJNv4fyc0LJ3KGcppO6VWosTLeqTsiKaTb9Jrhpi3a1gKlZlWeE0Gxatr0JA5cHOv1buc8elkZ4jMUiIhRs6muXzD00UlwP99j019bS2k/aQuMb1zYJg31ehUcnKAcxlwopYXq7Rbvi4IfEPnCrBrFKSA6ZXO5FVJMMT4phwIrQ6pB/psATYRgyH7I552GXQDFq4dcjzpw8BEVgcN1gGgbY3JqiXY1IVQIMcNgMEasEv8rHcLCxRDwqEMuE6XSIN1W8MPxfdx7Cnx9fw7nyAA8OL+GOczt4trX45Rd/EABgKWJALQoi3Ft0aOJZtzh2P7+1XOKJ5nim8c3bzYXL97fv7fbfnvkmAODJtkTVmzqOYoOn2+rYc+9whIv1Ng5jg/PuAG/duAQAeL4+CQDYjw3ec+oZTBq24NkezHHjxiooAKcGRzD7PNZd3t8ALg4wHDX5vkkFt6YtRRRTjrwEgGZTBWoAqsiIuk/AyQbFESfEFDOmwJgWwmPkxVaoCO0KdwpGVyib4zerMpZb4QPrJuMi+chtZEHokmV+MIXI96kI/dpRN9bZZUS96cQEnDnJ7YjTUMLQZFNrs2hhF5JVDEK7Xonjgsl8P3VkgFUQAkiDAs06K32LaYQ95HsrDMSKRSxz1GonlZYNrpvAiKYUjG4qYlDDPpE8TxJQOhSThtvQfV5i4fIxUZBEkTw7q3k+EXEJydwatUitBWlrAtKw4rHeGG63h4hQmZylDUC6b113i7UAfIJMLVGAInRRtxMoUOQsI5CiIeA6jYtUTXihupH5g4u6pIWeFtApii1drzCsijzXk2Q8s8BFwarQ8Q1DVxAjCQiT9RTiGV0ULFRR9LblkJDcVjZGisqCP98YbjNby1Y6ajre6zDmbmdkoCwlgMqSUczXmT39p140/pW/8lfwwQ9+EG9961vxMz/zM/jt3/5tPP300/it3/qtV31dSqkzngSO/fxKz+lvf//v/30cHh7mfxcvchuEA8qF/Z8LRIFn28CGmNpajinD3yQSeRICKbxHalomlAKyOgnsoSRQePaTEq4et6d7fokqwTckymdZ+QyrjiORvx9zQpJkRqqSSk06zULc31V9DQDLGkESURIRNEcbAFsOyGNaNOpKMUPwil6CuSfaBlHUjNXnNhvNsj8kD2Jm2WZEV1sm+XNGbDNBjUcsxaSWOtK1abwUojxoABA+JoDScZtl0Yojf6f4A1H2keR2TxerGEuTUxh0ZU6Jow7tPMCKClr9wthfkT87qhekEYsew9wnjlpMaDaYU2QXLUztJfJQrgkDmKUXbzjhLBnK3J7keL/8iFvf0XBsmK35DZLleEJW/THHcXRNkGBpsfkRG3JT6PwVAUjbPIkdEWACRHWtik9GCssDwDrOuI17Fezc4OreGtqVhGYj4eLBBprgQEVCuU8gT9h7aQPlqAWqgGqlwXJZINmEYmJgXMQXJm8CAMybAv/q4C5EEJ6tT+PB0WV88vqDGFYtfnd6Fn9+fA13FUdYoeOeYDf/DnDh+GrbrV7z/e17vz1QNPjMnFN+HqtHeMGvw6v3TG+bhwLrpsRJW+DdwlN9YHgZAPCvd96Oi/UW2mDxpeU63jl+HmdP7ePe26/i2nIVYZiwVc1BM4t2I7LBt+OC0M4JYZhwcDjmroll5b+tDWLJ4pbqkmXfUUfwS8ueiy0w3GlRb/M9QOBikQIj8prbTjGhmLOXolskjK4xsuN6ljwkiuZY2dxujgWHEKhNVlIrYMfm/EhAs+Z4zBNxXKxMd//qIr1iVXGsXI6ErdeZPlNMhWYkSJrGuGpkYDH1sv8RzUbJ41NVdOOP5fE6llb44ryzseKiKvMhlc8P5gvCRwlMkPlNrVwEgMlCl6UXcEJ8I9UPsAd8pILnAJ4PVO3Mz2VDbeSinH+A+N7GjtdYtx1wox26JH6MbQAaGZe1BRxZuInSCRJqoHMxrMzbhmkCudAC+PGi554SIqN3ridu7QlKueVN2TgcahtC6GkJYm4d82eY/HpVaaccb0zQtj4ILNApHFLNed4kaTPJt4xMSrFOGgmY6xVCalv+jlHAMa2JYjom6H2t7XvSnu5vZ8+exZ133olnnnkGAHDmzBk0TYP9/f1jz7t+/TpOnz6dn3Pt2rWXvdfOzk5+zs1bVVVYW1s79g8AexX1fZAUhdPAboBvlIzy9apyfVyeT4rMKVqWYq9VnOTCT5lzl5ystELsLm6QQOFMss0FVk/dlUPQMx+C/2ZEuRVWKn6OSu2lNUDWStoAk3LD+ohvHH3PZZuv4USdiEVNW9Og5CJYVoLk+XtSSBK0zj5fZl6zn1Um+4Lv7ZIVZ4tTAyQrmZ91i+KoZfJyLm6kDdHjdcKx6hmF7doDXgQzIXCrOd/sUsgGWel5bhG7mZeVbmC/xilb9tglezeqws4uu8hEFRUlpz5nNhePtuH3J0UnpTUPgNMTAMRhgXbF5mNgGi5iOS86oV7n1ADK/EmOXmxXIGa3BmHAKm5uzzNXUlFUW0fMz/DEUB2yOXF5pKtj3q92hQvN4oiPbSiY4xgdUG/yhOgHgKuBwZ5ws14sGdyeAaYGBlcs7JIQBxFpr0TdONhSmo5rLaOM3gALi3s3dpC8gZsZBIkPvHZ1AwDw8PYlnB8c4I+efzO+ce0s9sMYP3ziOTTe4n0rLJr4/Px23IgdSnjlJgK2cuFutfXboN/fvrfbi/6Vj/Wzh4wYvr2a46FygRfr7WOPH8YGP7n2NH59jxcTT7cO32wq3OE8roSAd20+j+cOTuC+9ev44+/cg6frM9gq57hvcBU7u2swQ4/nD7aRDGCWhPaozEhaLIGNzSncoUWzmtBs8T06vJ5QHHIRWG/z/d2sAe7IZtXx4kSB6BLHmUrdEAac2w4wMumWie+XGXuWclQqP04hwQ8sTC3vv6IiOumk9Mbs4Y0Au+D5Z3S1zfQXP7LwQxW5iJgPQBg6lBOOP83jdOkQC4vqMKA8aNiF4XCZLVzcrJWUFuE6SjYztbIIz8VnRDFtWe3sRTip3ZiQmBteidBGY1JlkQ8RPMbCZtPuOCqzE0caVtLO5YJJO3RmIXoA8HGGj93v0vZOritcAHQULzmW2fsXfIyzIbYR8U/d5vQYbfuy2JTHSGrEuka1BdniTs6TAApJeIlUe55XiTo7oMYL79R2NDCd+1oRHom5dhI/RJKwDBJghYs1yaGGtKWlHkgqoOlR08g5tt3pFadaCCZDwKDiY92LAsztbc+IJsWUg0jUHLz/Gcl7/j322vKvY/ueF427u7u4ePEizp5lEvU73vEOFEWBT37yk/k5V65cwRNPPIEf+ZEfAQC8+93vxuHhIb70pU5l+cUvfhGHh4f5Oa93I4Fwc2+f2AMpjtmORr2KGCWLHS9A1UxNI9xBjhGknngEErvTCSGoK2yEmMzP7bz8KGqmJHK2ZLopYYZEra2rM5ot+QYrGHXktoagpmoCKt/RTdssFmlXXVZ/a5h7Kkx2xdd8acTYrYKk/ZxKx/wN6m5WblGAV4r6fUv2F8st+EEJt+xB4M5mr0Q4sdVxlhFF2c9Uuq7YblldTjHBCB8lDUqYEFkNLcdHIweTHAtbs2rdhK7oN5LJClH/KYm88z1jTmOyYhVEYCsJQCYTje5ig1+qGdk1beoGwZb91ppVI+3qAD8uGAENCcWM87R1IKYESVHgj/FD6pIc2sjClSV7NfoRcyO5tdbtt20SqgNOqKAAFNMkSAOyLQcLYyDHklFHyJiSLNCucbs6CnrTroJ9GYkNvWMkYEdECEsLd0QwuwWSS5i0AxQjnlDLMwu+bCv+Qj823MWhH8KNWhibkBLhkWqGUytH+Z786fFV/MbOwwBYaXuzmGLPvzKf8eas4+9v37vtDvfKx/rHTz6Nr9SrWAhF4IOrbJn25SUv1tdNiVPW4cKIbYZu+FU8vTgDB4Oz1uKhcoF3nPwOrizXQS7h+ekJvG/lSqYsxEjwjYWbEuySgEAYnFqgXWc07uBgjGQkP7pm5wFG9sUZYKNGOQHaNW5Th7MNYETwshRLnEGHwLtFgl2qkE0WXYLGMVeZUB4FQeHA0X8kjgUGCJWFm7a8mCTOs1arG0AWmdJ5cIuIwS5b4iTDdBRVV2txqtzGVIgYz0fEigvIDEQAmQvIRU5kqzA5bew2oZZgXBxp+tVyqxQv2ABTs9jQjzvvXwDc8dQWrFCXwkrVzW3qENKK4KQJWXBplz5boJEEM2hBqBQvRF7YawcGkq0MKT6ZN+9ATctdnXndoXJATkQBCbfQy/wtIBA1YrtGyEbYFKJE/6ZczOU86BRzxy2LYjMf0ojnMth6J8qcpwCUPD8XZQr6aNEbU+eoo0kvXmIJjckRxrmQLBwLZEIQu0BBIJv2pkLcZ79oba138Y/yndUP8qYFNznH+6HXXDz++Ctt33XROJ1O8dhjj+Gxxx4DADz//PN47LHH8OKLL2I6neLv/b2/h89//vN44YUX8OlPfxo/8zM/gxMnTuAv/sW/CABYX1/HL/zCL+Dv/t2/i9///d/Ho48+ir/+1/86HnroIbz3ve8FADzwwAN4//vfj4985CP4whe+gC984Qv4yEc+gg996EN485vf/N3tsHIFepMNiVl3qko50bJSITW75EIjiTwdgKwYOvgXxog3kraOudBUrkZWbScg+TabkAICcevKR3kaesKCileUbyHwvtryWMOeWcOyS6NJ4H0qikzYpRBQ7dYIgjRqjqaZLnMbGopsuo4EG0dSNDnLyKTwMNnRnrJqTotQGIKdNXnwSpZQHLWdUCgm2FndtdBTOhaHmEonPBGfV4qJgFByYUmBM1uT3Nyp5CLULjSIXqgB8npTSxG4aLmtIjeuepRxlJa44hs2B1+erDIP0jYccagDNQUu/oxPCGscVWgXAX5kkQYcMeWmnovDkPIgpd6NoaI8uMaCTX0pAisXG7h5QDllZIOitNQdowehMqzYtITyiGPM2hWL6XnmScWSY9KSAdpVYuVn4CJ0fo7fs5gC1LIAwI+Y05UMUE0S3JxgPLfskgHK03PYgpV6JgB2p4BdcNFZTAz8Kr//veeu4dJ3TmJ1UMN4YG2whLUR/+VdXwEA7IQWK3aJ9559EufWD/HSchMAcPlgAwBwIAkiZ0eHeLa1uOrXcfUmpfSZ4hD/bnLHd3eff3/7j7q9uajxzuoIw5soAt844ra1quE/d/kCAOCB6hr+wvoLmKYWN2KLrzcjvHtwgKFtgaXFqODe8L+b3AE7NSjKgOQ5tbq8ewaKwCObF3H7qT341QhEQjkBYpVQTviei0LtcjOgWRTCFzQoJwnlCyWiYUTRLiHIfUJ1ENieZ5UpJPUa30u2Tqg3HJuCExeJHPEpXonEhZ2tIwvmSkK7VkgiVYJt2SIM4AWnaWNXRCb2PVRFtG2TLPQSwtBxYlbLtJ1QcsoMDKFZ43FaOY8AslDPLFuZJ0jMtrntG0Yuj4m8ELbiwtB1XJJjbr2bc6pYs2a7gidqhCsx31AEKnme0XFbisFcgMnPStXKi3YtqpoWALHyWhGulGRMDZ2Zd90yhUweR0xZqJlBGRGDUNvmfVbBkNLOeDXs8n6i7bWHYxIhjTzHMASdgRLpvOmxOpbmkji6j0SsCWM7A3BrgBRz6zd/jaLIx0FTW3JxS9qST9KVjoxKpsRFXUqZlobI4zXzHIMUyezvSEYKaec6rYF4MgLc5k5Ju6KRW+zVcV7yK23fddH4la98BY888ggeeeQRAMDf+Tt/B4888gj+wT/4B7DW4vHHH8eHP/xh3Hffffgbf+Nv4L777sPnP/95rK6u5vf4x//4H+Nnf/Zn8Zf/8l/Gj/7oj2I0GuFjH/sYbA9x+LVf+zU89NBDeN/73of3ve99eNvb3oZf+ZVf+W539xgUy+omOWizpRSCvVa0kQLSct+fEvgiCDHL1pV8CiIWsAgnIl9ozmXRjJJxMRxItKBI/hVG1/c5mnd+h2SQ7WlURi9tClo2HOE0F4NRRSjlQk7iJK/qbFo2jBKKgg1AdtsHkFutKv5RBJPUcFTRP1WeaYuiaVkNreifIbHDiZ0lThJeXsPwPcRMltXCzOnM3lp6nHqkXT/u2fQQcmIBE561AEUelJKoz9j9nwU/fiyWEZ4Ns1OhmdHCX/UsTOGkh05QA4AFLjHxABmYIxoqFcOE45QHH5iTmJWPkGxUVl1mhaOlPHjHkhcudhlgF0EiB41EAlLOxSafhHfFE1kxY3SjnES4GaumbS3XCPFnm5rRkmQBt+SC0a8yyrncopx0QZEfL6ZAe3mEOHUod21GJJvNJKgKcOLkIYo5cNQOEMYBkxfX0K4A94+vIswKnJfr6xP7b8GjX7sXJ8wM12crWTltDF9rhdyPh+0Qa6bGgR/hqfq4lcsFF/HD4+de8ZY+6GVXv5YYZnZTzvV/rO3SzUkMr7I92f7/XhKOkUX4SzelSPyfTz4FAPiBaoobsc0m35umhAFhhQqcMAU+u8Nt68N2gGqfcP1oFf/42XdgGRyMJ5xZmcBNNUYzIRUJn//WfbhneA1URJT7bH11z/mrrHQOHJfXromR9tIIUp+g4pjqiNXNtuYiURdfJiT4FaCYBbaxKkiEbLxQinL/+ooklxpZ4OLHtuMsg4sy0wS4ecgLTh2n7JJjS/3I5kUsDOVIwL6jgiKUFEXlvWjZz9VRLlgBMOdaTbcBmDp0HaQgQr26zUVUMdU2ubRsE9gTV4o9u/RwSx3bUi5SU2HZi3feZl5hJ6rgAhhCYTqGBhKLQYzOI9ZmH8LcYQO3/VPF4qAknsrqWkFK/0pMv+lrD5DS8Rats7ngBMBjr9LPtHgkSTPLRSxAy4Y1E8uG7Wus2BYtpRAzxO+v2c4yV1FRHBPn6PyVnPj29griPgBFPuT4vlQ3/HwfOPVFvKCJFLQSepwWqxL+kbmXMXI7O8b8nKQKaeFqQkTADJCFvE+plfCQKHS517G5137K8e0nfuInusr/Ftvv/M7vvOZ7DAYDfPSjH8VHP/rRV3zO1tYWfvVXf/W73b2Xb4kTX1KKuepnbkBXZTOR1HNxt1jKcJg4r9F0qilAULnlUrgJCQB1HIKykKJF0L0lm2InZ/mCjAlpNABaLzei8kWK3CJmwq7tsjzbgDQoJTMzAsmIgbjP+5UsgaLJvEs/LOCOGAk0i4ZRPrH10XxrtR0AkG9A42N2vOfVFyOlZtnwfhQWdl53K+W+jYEosCGrJlrU0n6XArluEQe8Ejci6slDS0y5XcH2QpbbPm1AHBac9mKZbB0qlxXZ1IpKThN61A5IhDlVI8d52E3KShzPwfVtgBNCuw7+pqcOT4MCsWTxDQtYCtiF58JQkE/ykdNilD9qwNxEy1nYAE8IBsxBDBUbgPuxg5t7sdUA6nUewMaXhMA/IAx3efVvmwhDCW4O7VQwtzEmzsEdEsopKzZH1/n+TMR/i4VBMTUyAXFxqWgLEnvbRWnbJcttbUn9Q7MdUBxa3JisYHWecO1wFbZgb0u3JDx2cDuqXYPfPDoPYB/7sxGKBvjfrrwDW6M5AOCb9TZSJPzytQfx86e+jssh4P+09Sz++fW3Yq1c4rbRAWapxZgKLJNHnSJO2VsXUnuxwVYvuu61xDAFfc8ZOP/B23k7BfCfTuE4jw1GvWMcUoAli2vB48JNh1sXC/1tllo806zjeruO961cyecWAD632MSPDPfhdwb4+Npt+BsnvoX/cfudwKTEudt2sb8cIVlgYD1z8gKwvDzGYML83D85uAspENqNCHuNR+owDhi9xPdeccgWVoM9bj8nyws+0zIaaBtOTQoV/zOekUM3BRKY4mHrCOeMiF6kUAFbW5GP8EOL0TUPP2QlcrNmMNjj4IFQGqSBQYzcLSiOPGzDPMbisAUMdw9sw4ba1EbYRQs/LmBl8RpLtpcxpc0CvjgsciRpKlwea3I72xnQvMnegm7GiyUzq7NxNgDQsoWVdnIcFtloW2lEFBPK3QWy8BFgWlZkela2ZgkpF09xUOToPhIhDYxBQgC1LdKwyqJK8sxKToWFWbIfInnOa+bjkoAQYBRkAbjtbAiIYjnUst0NmppbuFbsbJzlgi8BZl53LerC5VY2G3i3gOF8abiKEbxlzdY2yxpUlTndhZJn7jwAVYLHYQnMI7Ay5C5Z3WSxbE6TGxYwR0skMlz4pZSFvNqWZvNuKdhaL5QvEaoYWZYZK4UdkGA65DTJyl66ohB8JXkOL0mqBldk0TmQFfApRfafLgukxVKMvlO/Gfuq23/6I+p/6CYcAiWRkhW1kbagY7da4tVAt0oBSFJUuOpXsi+plB6AJrjQQJzsQ9eehra6VUTjPWheZ88ranv8hMgXVVKirvInFBmNotjS1YxyPgZlj5PBj9lZk39GCIijQlZVNl906lmZDxMhW93kwi8yWqbfS5VzaviNyKtnxJQd+Kn1vGrT1Z+akovCjnzgYhrIHEFFRSkmpCHvq523oBiljcNoEothtFg02f4nDcscXA+AV71a+Ippq50smM/iE4fZC0LKYfAdopm/jwpdHPutARDvRMppD8x9MYgDl5WDyVBuRbVj5THxytwuPLd4DKOWdhEQS8uFLAHVgRqGR55s2oSgfCdHaMeGSfpDRlEUCQkVT3acZMGcyKR3dgKKWcomx8WMV+/tGpAcsDwJzM4DsUwwDU+e4ZSIlgYB1aiFnQNvOrHDYqjWAPsFys0apgYme2PEAnj24hkAwA+dfgFhAPjW4s3jq7gRW/zJ3h34oTMvYLI/wqVQ4LmG7bTaYHHv6DpO2KNcVExTynnGTXr5ylcLxouvItLobyV91+viP5XNfheCndX/xDK3RzftjyW+F07bVz6Wz7QOO4Hv01964V24szgAifx2TAWebS3+5f4F7PsxfuXGmxHGEUQJV0LAxokpKAFnqglOjo4QXcLTl84gVInV0HPiBKYiYbqosLU5BUnqzHN7J1DtdAIBzZU2LVgBPecislljx4b5KZMNvTXlkiIwvBGzXU6oOEEqOrbmoZCE+8ttT6Z5ENqxuB3USQIB2E6HEhvt+4HOA4wWhiELUuwiiqBGOxBGFpMWCJwO5Qc8TttGokcJsuBmLp1dqkettLuFNtRxHbvxl5Zs3RMql23dohG7HfFIpEWdiwaNuVUbOe2uqRWbtnO5eLPcvo7SuqVun7SSiSXbCbFDSJJ5InT+x+pHLOdQu0ZaTEHGWVCHwALERVfU3G1kalfuUMXYzcHabu9R1ciYDOzoRqIzyKIQIqThAIr2AdwWJ2uE3kVQbQOMdBJ7jiYktnv6eYpKch0iIhRrBQW0HSLpFJSS+sE5RiYFvcz8Q2sBpddlMqtcdwKO9vUc7BjD5yg1rXA9xf/xdXIa/2xG1P+Ym5GLp3DdRdVXSCMx0dSavOJSqXvSLEcrJFgIsTeoRF8GKzk/qSyAZdNlaMYEKru2MPsoeb6QiKHuROiZVEdQWSKlLqowv1ZhbyHfkiqxQwAiZaKx8l2SNdnCwSy9rABlpSKk6Ly6ScKpGzvmMRriG0KUW9nvCp262yy5ZZHk/rTLLtkmFQ7t+oC5eSOHYq+BqtBgDfz6iAc9bYMrpG4IobSwgdsPfn0ItzcDkLK3WNQkGdkPGOHaSN41W0OYbvCQ9jyh4IF3KT5ZhRS5wss0S48wLoR32OLKPzUwSwK1S/gNdtK2swZhbAAU7B05KFAc1vArJcKA1cQmCuF8wKv7YpLQrLHlhZsS/LhAu2JgWsDW6jPJhWYsuR235yvmUAoy0o4tjE9YnGiw+iLnuTbrBrbmlpofmpydW04D5kMudOtNgr8a0azyYzwp8v/RAIsBiwCWZxhNXIIzd5fbAPkGfpXbgM3WAju/vY7xCy2WJwBstoiRQJjBuiO0RwVnAQOY/PMWp9vncHWyip0t4Mn6PH5u4w9xEAe4berw6d/iVvSPnZxg/twSOD/B0B3g303vwV9YexF7rcOJgqWsTzcDvLWc4NnW4p7ieLv39le55ceve3D43m1v+g947fcqo/p79b4XfcK9srD67ekW/tbKZ/ClT67jpwdPsyXP8iRGtoH1h4BtMZ8ajGmO/TLg1/fejAsnr+HwOwlfrbZgyoDiyhE27t/Hzksb8IOINBP08MQCF9Z28fQ3b8fwjqvwz41hDTABF36h5IVTM0ss/AIwOwvUN8A2O/uE9o4G8euM5B2eAoY3IItFToKp9r20jwnVIQvpYmkQSp+N9qMjHEYgFh6NdBKaZUAi5rKZNmL/TInBXoDxFu2KhV2yMMIuEsKI0Uw/1LkkZcP/4jChXeciudrrRbUmDkgwLXdS7JQ5oJf+mc0OD7HgorTZsKh2W0DrI1dx/jOlDlhQazNLSCQoXQLPWcqjH5ZIIcEskwQ5UDc/QFrkOtYq17+/OS6sTB2AJBx9H4CSui5fj5KUqU1ii0earVxVvEgPHigqVkQfM/52OWklb20rn1V2C/fUQ1UHZQYZcpGraStGgAkBBnK90KNdASpy6uzfYABEnU/abs5uPVCVjKaGIL6KyEig1gOpcIxEOpOR2dSolQ54v5tGikQpupUPXpbs3yhejYgRVBTSotYiXlraQRBRFfsCDJZpm/01tjc+0gju70N8FFOMnQeSWAZQUXQwv/LSnAMZhrvJs6FmUnPrpBC8oI9ifZN5bnKjk6HOyifXqKnbD4KQeUkKUEUzexcxxN8xsrBGzVb586QgCuyBaOZ1dsZnNReQjbwlepARTALq3s2vOdu1xBYVErROyDY9av7NAfYxWwlQ3ebVbXbblxxovrmlPT8ss42QUa8v5zrrAmcRRyWb1mZuZez4orFTvcVh2WV4qoJPb+q8Wrb5/1CxVQRzSWWll/205PeU4CZ15hWZVtSNYnobCxHpGCHCp4RYsuGuXXiYlgf+UJhsmUGtZLYKQsBcRvVLFD9Fsd0xTWBEoo7580NJWb3J1yYjDn7ERWIoIXY/zMGKhai8E7//YJcREitiGNOy0Id8AowoRusEJEK1L/wtiWOjyNxIWyfYMqDcccwDqxIubO0iBYPRqEYK3B4KFe/jpB3gw+tPI0aDw3aAJjhsW9Y87y1HOLq0ipETHuLc4W3lHF+e34l3CYfxvoItWZrks0/jzQXjG81250vL9T/rXfj33qapxbWwln//wAqbePtk8LvTs7i/nOBn17+DVbfAZjHH1fkabl/Zx3xRYtqUqK47PDJ+AbTWgoqA2PLCaedwBeQB8oTqzAKxSqh3h/jmi7ehmCXExNfmYJ/HUVszuhhGnJxkhA9MQRD4hhdg6ajoeMstj/X1mjgkjGTC9wnGS6vZkiB+jAzGglBOWORh2iTv01vMyv/lUezGuyaKF6tn+5vIzgwx7weL45o17loYz/uOyFxGgOcW4zkiL1pCFI/dMLDHigz1gORx3mQT62gIZs4L/dyValogJFjtMGW/Qf5HPjJKOBDBaO2z3yH5Hn/dkKSShc4XUVrOObAiBJ6vpDOGkpE2ionnVlnEpz4fsSi6drg1nYm1iBYVmFEupZp989xshfOfcqFHPmQBai4YoyamIaOpKqbRQlYzmZO2e1OSZDj+/ilGoG1ZTxBFL7BYdmgevzo/xhNB6LifiZXVDLqknHWtoFS/XsipMwp65fdAB8J43zm4CMczxdBxHOV7d9xPFQu/vu0NjzSm1gNUcqHXhFy1M+G0O/gk/AyK6PkppcwR6LuskxaPKorR4qZfHAZRUskqMRUFvw4Q5AtICv0rSpgJtcq17JGKFV2M7FafL2ofutWZildEtMKxRzYbwXY5pVzo5hglQ6CFcD5an1VnNK+5MBuUQL+YnC8zvyMZyvY7kJYHEjj5pLA5VYYWTS5So2NEjpRsHVlRTQk5fjCpElpiFFPJaKebtnlwiMNSWsWioo4RYTwQI/GQCeKm5UI/loazXaXdkYjQrrBlEAt5RO04KjD50ElGHZctRxAOHezBAmkgvBgxs4UB7LxFs1nBzfn8hBErILldZjpRDYB6w7F4ZcGq73atZC/GwC1oE1Le91hZ+KFBeeSxOOFARwbtwx7tyHHubQmU0wQ/YP6WrYFYCOpSASuXPELFbbLlSWD1xShtbi58hzstFtvSFv5Rfo2bM6exOmAOmV0C4XQD7JewDdBuBewtb8PwJxe4Y+06nnj8bviVCFMbbP7BS7jy03fiXxanQT84xOq4xZ12io8evhfnhge4dOk8kID1sw7/1+tvwYUfvoG99fP4+vUH8KR5AD+3/Q2MqUAF4AAR7qY17ReXG/ghMYm+1fYbh3fgw+svwjSvk5zzH2lbphYDKrDxqYu3fPxCeQMAnwePiOlP3vmn9tn9zzz4yVfDZ2+9fWm5hncNJvn3WdEcU0zPUovVCOzZ44XvxdkZzH2J/yXdg7+08Ty+fXQb/tz4eRwsB/jSzgXcv30Nz01OI35nhOG7L2HnW3eiWmnQTCqYmhDLBLskrJw/wm2r1/Dlb98Okm7gXplALaG8h9hVYFW4hwGozwTQ0mB0lbPWbQ0sBbWfEJAcsJhzEQgizByweKBB9UyFdgzMr0VWShO3lN3co13hQo47IYRqv+FgBBG3xMKysfeMeXmwBBpwm7s4bJCcxexsgdXnZvCr7K9nmohmzaE6aEC1RxwUCEOLuU95kWhmdWe71rRde1eoN5v/92uYfPAkzJL54hTZrzeOK45ybdouK9kHbP7bnc57UApEBShysWYI7WqJYm8OGMN87qabP6CBCDJOU+uRXNVx9RuPJOktmUMvEXgMFIj6uPVZtc2aA/A80bBjRxwUoNpngSQtGsRxJRZyUpjmggwg7/N30BQYCtJxU+sdiIVPtqwRdFTAhhTY95H1C11BzPx3HCvWSIQ93IUnpLKUVrrj3Gdu4cn3joBSp6z4LxYi3JQaIfkAjEouUAPzJFNVgjSGKASQN9m+jpzlzwgi6EGbvyOkuMx8xtzhdEjZ9UTETIk7n6mvJn+N7Y2PNKZeAaY8C2uYU6DHSIi7ykcA0B1A8V9K3jPyKKgjokQNJuFNBOUxcNGkSF9WI+eNOtGLxgy2XlalsSv8JAmGV1HCb8g8BUU5ZT9i7Nqz+e9dIRlHpRipWuZVtu0xo1K9OZASk3v1b/lOxjG+DEcidoqyNCikPe7YPV94jbRsELXNkIUushILbG3Dx1hEKQLpk8RAcWWduvaCIcB7yX1mdDCU7HHFBHALP3SMJqqacMGGuCADN23Z+1EXaU0QXmDKg0C0BNvycSXxjYQlmJoNY6kN3Hrgby72FpZthmQAsXOf1damjWKMzuroZAG7DFlprsbp5FloEyqDVFn4sYNpIoppkCJc/BuFa2mbhGLOkyHAbWeKgB8zb7E6TFkpnixgaiCUqsKGiAQIi9tlFW3AkzKY3xgtEEchj3u2AR5+6NtAy+83n1Z47OIdsDXBtAa0ysdk5/Im3jS4BgJwo12BpYjdvRW0ycIdWaxtzHG65CJkr+b8Nx8MfnLzKXx6ene+S7RgfEyecy34Vy0YAeDD6y++6uN/VtvgNcQ6fV3hJL4+BeN/yBa/C6T2MIyO/f7V5fFwhU8c3ouTlr+fqsCb5PHE1XOYhRKTmqMgLwyu40oY4bmjbaRJgfetXEFKzEG0IBQTC2siyBPimkcqI+KWx1q5xOV6I3sympqRbSsLA/aRBTdrlOVTJISSF1BuwQslt2B0vZhy61p9UgFgZdCgmEWUR51vajEL2Z82StygadnRQOk9dunhx9zpWZwQlMsaIILV1Y10UBwxl7iwaFdtRvpJhtdUOfix4xZ2dqkQlFAjcK2IOhKEZyjFQ+7umCxAIbUV006M8OozD95Z9hpMyHOA2r5Q47lolXnP1hGh4m5NRg5J08269m32DlZLHbVPE+/ANJD2qZpvi++jtkgZ7eMuWy7qtOsnY3HmM4qrRfJeqFPiVdgTtsKwgpkyiAI+2CRCyNbn9+nasqkrbBO6oqtped8FEcxoY0JOaKGmkQ4mv6eKX47d3DJXq21O5hrKRj4wHzKB3VsaVYhDahAGsKBRgho7KPM8FYUAT9S9d4oSO2iyZQ8DNQKMaXxgjD1U9NW3N3zRyMIWcGGXEpJvORJQ2rTZ+DKrnlNnCE5G0dtO5l43ckHIhWEtX4hEoqq2SCMRxSSGylPb8kkUg+688tEiTFqtGfnsWRFohrMWednfqfWiyI6ImyvZrJQD1NHxM0UVDSNRTk49rnzmP+YIRMniTGpbALCgxQcelMQpnx/oog2pFXsJvRGlhZCcY+4NgY+HtaJO9N2qTbyzzJw5Oiz44X2hheR6qWhJWj9GWirs0ZhYnWd1hQW2SfBBLJNM54OVkVoZdIknD00WQOHYKqNhpbhZCNe1CXlQZnNbyLES4Qwxr9IsGWngtg5xPuvBgo+ptPWrg8BRYrWHXylhlwGhMEilhV1woe+HFqEkhKHldpQUySZwqgynSaRsx1EeBfgxYEJCecgt5mLKA69pWS062uHByw8Mc79k7EDg7F5WfOs1Bx4Z5PikPS4GvnFwFqbhWMG1tTnszKBdTRjsANbxtTzYnuPZ5WnsTkf44OpLeHJxDj974avYb0aASZjOB9hpV3F26xCbFXMX33/yCayRzwbR/e3t1RwR6ZgIY36Tzc6n5ydfZQR4/dvh98Ce53p47YFYiy4Ax5Th36vN5NXya29P75/EYWzweDPAbmzwo8O9Y49vlfNsu/NAwcevJAdqDHy0mC1YSHh/0eIPdu7HB088gWKLaQc/feqbiEXC70zPwo8T7lvfYcX03GFtdYHV0RKXJ+u4tL8BGnm8+8Gn0G4GDK5ZuDnQrHMakgpFKALFrsXGFitcykO55kfIcYGAtpMJi21ucU9fWoWt2TaLErhjQNyebtcKVHsNKHS+jUk8B0mcFsLAYbgXsThVcWdh6WHryDYzBoiVQTHnBZibR472M8TdhsazL6wBzLJly5zaM0dcCx4AKkA0Sx6Tsno6SlJVSOxKkdgWjQIjgmHgupQVGYfyJq1mFW8mQ0hVwZ+tbVwfROSTel0v5LYmrAUt6wwopFKym6UY5AV273MVVZOWdbbDEZ5gMoZ5fI3P1nX5tdpVk2In2+NZ9VcWLqYWpm0rMb7yelV3a5FU2I5bCakVvO/CKFKErq/ULicXWYn9GZOCNFIDcCvfdO1eAiOwZQFy7OcIgOsOsclJfeGNHtqUuBuqPo9EfLy8Z1Ft0n2QxBgCxxz3qWJJi+SYRTZQfiSQQa+kC5PXOSy84YtGZINt8YiKfCC5Yu/1+KWNzEdflMyl6zIileSr5FZdNUhrWBHKVDjmihDzBEiKKDUipdBd3Nw2UHgnitI3dUUs0BWkmRzctaMzrWHR5tVGctKOaNvuZmsEwesLgKgz+sxXkXI0+y13RQpVkq9tbyXu6kpN2h5JkMZsRk7oDF31O8mxskfLrh0gq0gOlucbNyuwwStvM5c2h4iTMj/Se87KdhbFlAcpPYZx0BXJAATt63iQ1EZWfhMhVI4zrkM4xh1FSuzVJpmw2gbhvO1eq0PQT5B+jvBKYoJdtMwDEs9I3cKA9yUUzJdabBu4mfBJ25iRAop8bEJlcyIFJz4gc7Tskttuet514kkWnBQUWCjjh4BpGGk0S4PqkNXVzQbfA+WhrPDnvOByC+ZDLg4HiFXCYBf4b04/xUrtBZP2QzByqTlsF1OEmo/7pek6vjK9C9d215AI2FqdYWQbGEqobIurIeCK38SvXnkHZq/guXhzkTOiAvu9Au+Um9z8kn+vbf1PqWB7qddZOGVfHWX8T327c30fT9SncYebYPsWx+cdg5eO2e5cCx5HscEP3PkCYiJsrc7yY/dvXMMZazltCMBn9u7jYokSQAnf2D2LWCUUE8LR3hjv3PgO/NKBDh3SvMALixMYXzR8b4SEYkpotjy3oRumU4QhsFrWHA245JSVQmI3FXk0PsLWUdB4VkiHymb3AS5C2fy+HXMnIVQW0UJy3U3mI5LvlNOD3YaFKoU4LigwZnmcgZU8Z7m3tStEwpnsCx+5M2QQRiVzwntAQqyKHD3IC7vIc4COoY4yMmfr0CFesq7WIkP/z+koYo2WOYjqsNF62LlyAIX6Q5Q7JKCetVsQvz/9zJQkdELUwT6yQlnCMUjjZjV+r1c8ZX9EIumQhdyl0zmR6lbUzGxfkyKPsZlfL1qAjDYKWpi5fL12v+Yy5xaxWvPJpmkvpGpuCHCSnVe4AMdowM/T+ddantsBHFd262vECzIESajrFehyzHO9kOsV+U8FMTrf9l/HkCX/qDVFv8mQpNjttbFfz/bGLxoDG19CTyggfEa1upFKXlvAMfCFpORZMd3MyJgUg4ixowBYIysIWUUI/E2W1U5UFvyZWiT2ihEA4viODLNnyFmfo9C8tqUBvjANX4zUtpmETEHTVWyGtZWwrBYLbClT5BzM7kIi4UvG3EpmNFKKXrFY6Fr3prsQc8ucjyG1bVdoS5GWrIXmaqv6W82ujx0P4TDmVreE2CdDuS1NbWBTWvSQzpTyipgSWLknqu4kZGoTEqv65LiaEBkhdJzbfXMEJDWMSupnarZ1rFznFyacoGwePiy47S0LD0U6/ZgtK6IjxFHZiVYkYxqG21gwPAExwZwHDI1mTCSClprf34vdjpsxmmIbRmL90PLxIUIxBVv7FIR2ZFBMmb+okYPRshDANBJBuOTJc3id1dRuLijOxIBazrIGAH+yRRglNKda/LXbvwwAeGD7Kr7y5L0wtcGzrYWPhlM/QAjjgNJ6WES00eLe6hp+4/rbcNbto3Qh2+68UvHY3zZ7Bcxt7ug1n/8fczvfCyn4ksTqvdb2RDP4Xu3O69qebm9Nb//Q6kvYdtNbFtQfffFhfKs5AQD4t4d3AgBeaE/gS4vb8Z7RDbxn82ks2gJfXG7g92an8fSErZbCQYXfm53G9PoKqq0FnnzmdgyvEdq5A8qA+pSHGbX445038X1vGQVfLxao10WoEljIRZaRdNMCsWDbqCvPnkSoACSgHZEUgrwwImmlJkeo9lv4EaE6YAP9xSkW4VBUL1XPRW3DCS3lNMIuApYblmkfBmhX5bhFFo2ogMSPbU6FKmYBGh7AHQIWtOSxyifYGWco+7HL4yi1bNQdBizgM7M6R8m6WUfzyWbXAD82bZj3nRJo0XS2OYA4asRO9CK8dH1uVtlKZ400VEG4f5kmpPSkthWkqlMcHysYde4EpHATQYfuu86r1oJCYN6ipLIknVONcB5j4P1XOpkUUSloF1GzlJWLaF/WJuYOHSQVTp6v+2AI2aJHaVFB27vaxuLPzq3yXASI0EWs4zLCqXNb5NQVbXNDaVIi2uEbQ1rWUjwioROvKJikFDr9XhCEtI9UStJdB0DhWL0jUGbv+2jt8vqgxjd+0agXMdAVXDF2nAXTwfx6gZIxTA7NMX1SdLUteyWJbxJ7JAm8ryuNZc0nvY/KRSms9MTqaiMjlnKBFi4ru5OsPLiAxLH9YOVVh34qxxJA5i3mKMJ8gYq6TlJw1LD22HEhdHFKxuRVCNv8cDEMa5BGVfbyYiVanT/HLGp+nWX7H20zMFexyYWmJhgovwVJzME1z9NSF/VUOCZj533i4xULk1fMub0CCL9UPCxb3wl41HJJOTQ64Grb2suEUrlchMdhBbUtYuUhn0s2Edc2FZuyc6Qg+34V+0tGCsbarolwRw3srGGl56KFXYqCXnwYTRNRHrGKmlFFSaIY8rEKJcEuA4pFzFGLseLX+zGrP5sVAz/guLNQ8r96A2hWLSffJEZjeJIlFEeSKrMEBnt8jikBplFkGYilPN8BlAh+2+Nf7N6DlXGN6CKMTfi1i+/k6w+s4k5Fwm9feSsMJdxZ7eK2E/tAIvzE2tN47Pp5bJQL/M61t+Ds+AiPzu7ET20/lW/ZP5zdectb+evN6JZ//9NCCL8X27fnJ7N/4attqhT/s9oGxPv4mfmJlz326NEdt3zN9soMjx2cBwActRV+6dqD+OK1O7HXjjCJDc7YGnes7OOkm+DKYh0A8P+88hbAAN/cOYvxqRmWB0O4OWF+LmK4WmM8qoFIGFQeMRGKkUcsI4oJ8I2r50ARaFfYLYACYCaOjerBFlZ2CQyvc/FYbxqUR8z7dTVzIpNh/8XlJo9D0Ylt1YAw3ImZe8wm0xGD3YhUGvihRXHYIJbslcpuCV2GvBYSUVrH5RHbmVETcuRpFKcGFtBxJGsq7LEx0M35b2rSDfD9TWqRU1puYwuvWnmLidhzNneJwIv0Yx2y1iN307KnnySf6GPSyVHEj/pFn6CSVGtULc+f1O8iSYdIC5uk7WVt46pVTWRhZSrZeButZzTRi5+wggCiyqbCybwicx5Rx4ckdFxKbRH3uZEZ8o1AipmXmC1qHPMSkyqWrcwrMfV4f6F3LNGLAeZjmKSDCaA7/kLnImdzQa1oXlZS97t/oK5AVZRQP0O/g2odjtV3ijD20GrlLiY9NqZ3DFKeQ7mYpFwkv57tDV80JkkNIUN84FSsEgKIhG8YOWJHf87FUFVmlLFr5Qq0n9uvlHkOKaUO1dRNLziSCyJ7wqR8QQFJcqtZcp+0CDHUtceDEFVJViaKSsr3ANCZfBuR2euFDXABpaHoYpWTLXekNcD+ha5bZRU99bYkBrDyjld8NK+hqQDUer5ZjWZyx25FauVvhQPNax4MZ4vces2WDj52g4EkFahlkZkuuxWj7IetA/9d0L8wdN2KGyQ8Tol56qE/mUtaumy3QDHCzpvcQs7XCQFqbK6WRHxeeZDWVnVuH8UkvmQJZt7CzuQ4a9t6VMC0EWGlZD5lSFhuuWz9k+MKZdHRrBeo9lkt75Yq3OFdW24ZuDkr1YspUB1GkCAwpuXjV8w4bpAS0A45t9rNIHnU0oIb8aTq5hyRVm8ic8VCxehuqKRNXQOjUYO95zdx7+p1UDAcEbjPhVsbLUxNMEuCXzjU+0PMY4XDegCYhN/YeRiDqsXTV06jsAEfXPsOPrz+Ir44uYBHa4Ywp555cLuxK7b+8TPvwB+8xLnzV0PAF5cbAI5H8P3ytQeycOZWxc+fxfZXtp5FRem1n9jbnhfj6mda+xrP/NPb7hCfxR8fvdzLceEL7IQW83Sc8/nn1p7BXDiLP7n5FCxFhNbi8ksncDWMYEAYmBaf3HkAs6aEf26M5Y0R7JJQVS3uWtnlQu6OJSgSYiJMjwawS4NlXaCZFwjBgIqIMCDYAwc3T2jXAvyIEUZbE2wDFNOYnQNAwGCPLXgAXvREyxGA7diIgT7QrhY58jOWgB90YzPz+pRD7FDuM+G3OGQfXrdkY/5i0qBdK3I72PjY8YVFWMIuCpbzpLXlq3zwKONc5XJ4AoCOL75smc5C4AW1Xkq6zldkSzoaeewFGLkb8f2hCWNU986hIGLZiFrHV2eYmqVdpYRet0faykFpUug6TDpvNk1u4Sp3T0ER/iDKQAc1PD9z9C2LGqltuUsj/Hzd1xRkX7XI1eIvi1IFVJlL3JVhwAGackaU4/Z4N3iuIS1mC+EHauSwtJFJkU4AORJXLY2yoIbnYTKc/cwIsu9iABNAJZ8LEkNtpcF1bWUpFHs0hWOm3ZCiU8ET5VVmC0HbvVem4lFHwwu9wlfn8pg6e77vt6dlC8x560663LT9Nqv+HeBVQyHxPuppqJW/EQ4EgNyWTXLBZkRTUDRjuCVNxJwOo27uPZgY4FWOcieMASyvegDI6oUyP5Cc7SKIBOZOhTuWtZlbyz6If6Rc+HLjJEEfU49PSb3CMKN7QQa/KPy+phXFr6xC1Qi11uBjuZH1JtTDJJxIEhEQUuoEKtoq8UIXkBZw5lFSZ2aerOHiP3Z51qom1KQbd9TwdxBHfZLIQ5C0tTNfM+QbRlXXygOMA9etjK1B1NhF318ZgvczrwhTJp6DwJFaQGcNVLqO1wnAzhvmPMo4YQIyCtKODYqjBn4oUYp6WiuT99EP2L/RLZIUkR1iydFovI9s3AskB4QS3OZrE1ydUE4j6k0gGeGCSVZ1O2afxnaNFaLJdPnVoQRgAB8J5IGvvnA3zLhBmIgVBoD9ZgS3BGKV4OYG5IFH985jtazx4JkraFqHD536OkwR0XiL3RDwydkZ7M7G+OrBHfhKvYq/tPE8nmxLbJuOD3jh1A5ObXAb+oy1WUm9QjyZ/+70LB5Yu4q3VTN8s6kwzqqe7832wmuInH9/xq3Yw9iqNegrbl++qYX9yB+9CAC49yZ/yv/Qbfe7EPro9/tmU+G/OPF1nLQFRtQV6J+an8LtjvK4Oo8l/quTj8MdWdx++3V84tJb8f+5+jCenpzC/GiAmAh+lAQpDLAm4eJsE0jA+nAB8twJGVx3DHjtsl9eWlpsrC4QKkEKLWG8toRpJTvaAUiMKnKcHP8eSkKz2glgooN4CzKyCPDCyXggOaFwOOJWcgJf+6XNbchMDyLmEmdUDoCvZNEutJAwYAEbEpAGBUcECqc5i1RGZbaeCUO2lwnjkkV5LUfVkY+da4UP4k2LrnsFdL68yqm3hhfnikTKWKsXYVLfQ0HnskgwpY6HnlXNYDRwIIXnqOoJJG3HE9QFej9lTIAEfrKAIi3Tp5LMhbnjpuNn7sSZznNQ98G34l4i85d24frgyzFwBx3/MfTPFwn/EZ1/Yf7+1FHvhYaWpP2tSGQuEiWWmPdFEEqdN+SQAOjew3vRVXABqu3nbkvovJrlWJT9NnOSNn0StJS6Y53BMHknFesqoNWjAOTj26e6JSlM07EdesXtjV80khRfAvVy9JBA1KE38vcGAWpaOdEdl1FD00lWXkmg7gw/Oy4MU4gdL5BuanMDfIKzUqyzLsimnXKBpKaBXlWZkNxbdfFF7WGmc+F1+Az5q4DleFEsyTYavRR6UUTgVYda/yRpnyRFZ4HjEYYhguYLyXSmDp3UVnbsbva8+gW6i1JWbyQ3PsnAw0bhxwceALnVfAx618GrKroVrg9ZOZd6kHxG8Zo2k8w7MjjQbg34PS3zDanpVtF22YopOM9G1Pi8cjOSbW3mNfMDxQg9DguE1Ur2T1r7ymlqRS2YkH3d3DwiVNyu8kMu2DW60M0j2rWCeZCOmOQeGemwTYJb8GTharb1cUs2CU4EhIIAA7SrQDFPcL14QT8wiBXHFibLCyCKXDCWRxHVHiEM+bXJSHu6AvxKRLg2RLuWYFpCSgRqkc29j+oKzUaCnRuEdY/q1BzboxnGrsF/tnIFg7LFV2Z348/f9iTu37qGU9bhyRun4acFNgdzPDNjS5dzdorrvftzYFsUJrwMQbxdjtPED/Ajw30cxRYPljXeUu7hlbabEbN/n+0ovjoHcbcZYzc2+Pj+gxjTq7fP7ysZ3XvOf2+H41sJWfrboscl/aODewEAdxVHuf3/scl57IQWn5mfwNliH5PY4O7tXQDA5XYTz7TriA545/gF0H6BunWY3xjDNAb/l9sex/btB6yOjoTGW5weHgEE3De+juKIsD2aodlIoPUGpmUrp2rXYP9glCkSyQCL3RHcPIHA6HeQU0GeLXz8kODHwHA3oTrwvJAKwHLbZUN9VkcTqkOPZsWKxU6CnbeIzmBxqmTDaRlz4sBlhwYjnMR2xBOtCUxfobqFWwTYObejTcOccD8UnnTTgQtBC9IeP45CysleYWDZgDqljCaSl86KCikAhFGZefDsJhF6lCjmZjJNKOS5gZpWFprSSi5s9h/OyGKIgLOIlZiHmy4IgQtCFX5KIdLzPlSRaCoc4qDk5wfhHgaZN13fv1HOH0HmPvZqpLKQ+SF187Ogc6Q2bH2hinPd74qiKeIIIPmW3VMIvcg+m70qdU5UCpq8q3yW7YpY3zLK2BdL6qbFrrTg+/Q4UkQ2cVeS1dFCa6Ped7HSGe0rsHUu1gIYkMQ2MIdRuZIaR6hb23bFYo8jmhFILV613nkd2xu/aFSFklwYSYqBHK+jlXwPNYLAzKRZzUKy7aOTuR7zIUPjqX8BSNs2/y/8RSj6CGRuB4B8oVF2tueLJBN55TlZvBK5FZ5hflGPkSq3jelMShWa1+9ecCGbLy517dcVYUydGrxkyP54W0MuNnGwR6+oJWk3p6rM6GY/2jDfZHpOjBED29QNTrryK4ssPCHlhYaukMz8jN4/XZVTwyt3AFwEGgOMBmyZA3R+kT52q3FiXmHmSTppn0vbom8rRH37IylU4WwW9rDBeE913ga24xEukGm4Dc4xZZRbY7Zh8YymP1BK0k4TsUwCipmHH1hptRFCZWGXPJi4eYSbJykS+fl2ycIZtwhIBLRD9l8r9wySA5ID5rfxfsZSuI6zBETAnlrC+ISte/ZyQgcAmJFHrCLosIDxhNHmQm4HA1ppAUpIgTCfDHDp6jY0h7jxFs/d2MYf7tyL946v4YlmgPef+wZMTXjpYBP7iyGebEusmxIvtNsAgM8utvEDwxexOx/n9unNwpELwx0AzG980Sf8i+tve8UhYfQaRdzr2R56DQ7iX9h4Gn90dA/etfb8a77XRb+Gx+oRLrj4ms/9Xm6P19v558pywf7tdg1HscE8NXhu7wQGlLBm+VyvmRIHDfu6Xq9X8bZyDuOBFdPCzQkbowWSS3mS+2vbzyCWwO1nb6CZVDhsh7ALwiIWoAhcur6J4oiQpiVbQC0IzUaCmzj2EE2MrrupLKCM/o2RxLgSUBzxz6YBooXEefLzjGc00fjI13IUdEn2zwQAxsCEiFAB7Yg9X93Cy70rtl8t37dumQDwog9iV0O+Gxc0097VMj6J9UwcOJiQuCiNKbsfcPcIiBU/npGrfhFAPaAByGOl2tHkOD2lFhHlQlE7K/o6FulxVGIWYSrA4j1o0cDM2y79RYsrFXFkWE7+VSULQXrtV23RA4KuKY1H5mJGDKWYksKJCtfZ66TE0bDKV3S2A9h8OKb4TTH2vAoB5VeqJ7MCRgA6GyJAuIyUPyPz3jMPExngyPup83/qzeEx5ehdjQzWIjm3xeX5JIbrZG3XopaWOBe/cvyc47Z2jFw7BKW6ddQz/mzp2PUQ0ryPeji0dgj++H7r93id2xu/aNR2pd5cWllrYaeIU964YNIVCVISNZK0l4PA9lEu+hikeOvB5v2TJYWe+jaRElmRsmCFC8qYX0tS6BJRbj2rryRL9/WEU2dfkBXgetEDWW4ftA0sgo/IKzX0ClC+sAViD3xRq+1MUrFPz/YhZUW3yWIggFHIZLh4VQWf5nnH0uZ2M6/+pFCe19lsNreBHItX7KzOq0YSfmpyjgdw4VD2V0uQ4o1b8FKca6HX+hwLlj8nREb8BgXQtLDTZU+RGLrvYbpBi1MNpL2uA6FlewzlV5q2Z2ArE4CijQBg2oA45LaVaRNsw0W1W6jPGr8mVAZuEblt5iWfWux5AEhqDv+NoliMzFh1yRFqrH5uR4TohMQfgOl53o/BXkS5T6h2ud1Hnidb3cK1AWyTcGO6gmLGE3l0YmxbBZSHhPIwYVlLosmshDEJfi1gOG5w/jQjfi8cbOFa8KgXBVIk1NMSv3LjPjw6uQMn7Rxp3aO4WOLEaIZ7Cy7I3jU4BAA8WF3Brz77w3mfnmgGeGu5xJeW63iiGeDzy41jJtSzVOGnt7/5uocIAMcsfL6bzaNbnb/Ys1J6tD6J6/PV19Vi/k59AiPzp+8R+VrbV+uVY7+/azDBIrXYjQ0uH6zjK/UqNswcn5vfCQeDlWGNeTJ4pJqhSXy+f277cQDAj609AwAwJ2tsmRLLkwEf2noCFCgbcQNAHAQksNfnzkub8KMEnyy3j4MBIlAeEOKpGm6ekExCMU2wLaGYpjy2tmsJ7UpCsUhoV4BiBgwvWhZ1NcBgP6KcBOH2cpva+IRQsL1OdeCZkkGUUXy2yWExnJszqkltBLWRQwQixwH2OYp+rElWXBCYNnIQgBf/1cLCHQnvsHCsbBYRH9U8Zrqp2M00Ppt523nLRWjju+AG4XgnpcwA7AUpCBgaSR2JUdwcHIp9LvBZxSzxeSRjkdiCqbevzkvkGQlMKuAIjFKaZefSwU4YNhfcUJQviUBQOZRL4ROKmTUnjoHnmMLl4inPmVroCijGQIAkuUEW+fqgzqkqGOp6y9L9kiJaW+4xAlYKx4zD9MUunXm3cha7lBXiOVSpYvI+ZE1+z+Tbji+vxZ+8bxIqWNKkuEzxQp6nqRf9m4RGpw4sx7iN2uVUoYs6smTRrBT+fWGOkQxseRjWZs/mlwFhr7G94YtG0uIE4JOtF1bbcmGWoWE5aQmdwkkk+UzIjbnIzAefgGMwtu1dDPzhfMHE7vNzgQd0q5LscyarOSlG4WxHXu2/Rlcx+p4pdauHlJgfaCVmSGwH1I0/hSA3qekucJXfC/KXlW7edzmYALcJBDXVdj2A3IrXx4y2VRTdLVxXZCbk48ciH3TWCUKWVq+wpEVaXimLXUNuc/NgSfMlF3LSJlcepZv2Auml6HOHPYQophxPyJzATsWoUH8alDANR4XlfVFkWc1hSZIWDPKqWnNMs2WFtLQAdFZBIsJJljgNAoBtIsLAcGyZWHTYacPHreBIQIoJbhFh64RYMQfTDwgmRLhF4HQGH5l/OOJCMVS8f+xLl+BmQLvCvEU3B/wQmJ+hzK9sVlgk4+bgOK69EuVRQnXA4gOaFCCTJBsbsNcE1a2EL1ZbLGYVjpoBqCW0iwL/63d+EMW+gy0CqIi4fbSPGwcr+J2DBxiZdMDJagoHgyZ5XJVJYZ4cTGvw3517AgDwhzv34rMLRsWeX57EuwcHOFvsZ9Pvy81GFna83m3zdSiwX0sFfYcjXJGW+rPTU/ibZ7/xuj77ynwN9xWvQZJ8lW35OiyKdJtJa/73Z6fw+Z27s9hG+Y6fPLqAnTDG1uoc76yOMDIel+frKMlhrVris0f3AABKavG5xSZW5bj99o23AgB8a7EfG3z4wqP42vI2mNUGbgZ8pV7FPLUYDhvcmI+Rxh7kueX8+MXbWcA1FaNu1V9Y4gQYx4uZYh7Qjim3qU0t1738HgsgCMXPNpywZHxgS50ScLPQ+SEag2adYJecG6958PVWmX0TmbohizzPY2T2YRRzbaWVxGEHBiQriFji11PtWfjilUsZ4Y5qsRbr+ffJGG0WilAhi1RgCHCGuY7LJlN+2P9RkL1SAASn6TECSCi3TTdB1EwduLgKQm+SxX0OvlAgQAtD7eRYy3OBk27TMUGFdF8U+VSOvfDuSI28CycCSQnNsDYrmpmaxe+RbDe/yk7k75C9krVriG5+yrxAQ11mtBRrKaaOd69tWSnskr6PzrskxuE65wtamKRQS1H4hXL+FDzic6ZIr+1eC+Sao7Pzg7wn8zb7ABMHg4BBFJl/jr2/dk8zHU3n7tDNrbppYU/g76eaBgWmMl3t1bc3fNGYgvbqe1B6UXSrGVUrmS60O6nHUr91rGoqXZlIKzolyMnW1ZGktWThhAhSVEGtiuaEvPrLxVdCRhPJGFmdocc9iN0+KTwduwtYuY1JX9Mdha6VqxC8Os0D/F2lFZLUPkcGopRXPkKU1vdRxV1+vx5s3zMsVwUYWcMrVeWXGGLYXbkV1FkxQBFP2W9VUOeVZWSbH2o8ty40z1RXvnKTZiK2cmHU30tRZ+WatJ1nWgpi+SBWGIycmhxRRWI8DgKn2CgHtbCSBhM6vk+fV6oIbhtysauemXbu4eae018cIyJ2Wkvr2WRBDcDmxKHiVXw58eyv2DKqoqdSUYRmbFgIEHlypiCKaUE2ixnzlGIJDG/wPpkmscBAlKiUmCM2vMGoZdTOk0mItUMsgNk55Ag3TB2CN0hDDzc1mOyOAQOcOXGIFDlTuCwCzNThqYPTMDbh7OAQZr9AOs8FfUDC707vwif23oJ/fv1+No/u1YB3ru3jvvIa5rHEpOU29b1Fk03A//z4+rExoI8Avp7Ul1cqDvvJLR8/OsfnAxbP+W7nzgrJ/sc3vvWanwMAL4WI6S6jpKoI/26314op7G/Kr/xzo8u4a30PdxcNdkKLNbL4Jy+8HVvFDPcXLVYKFhL9xo23Yej4mP2ljefxnlVGFA/DGFfqdQDAXmwwXQzwP199C+7c2sO/vPoDuOAiXpht476t6wgVcBSG+MTkHiwPhjg7nuDc5iHskhAGEeWBkQILoAtz+CEj2ctTPPE1q4IWDqz4iCYkm+BqyPUPSUQBYsnXLiKyLZVbBNhakHwx/AZ44QRSb9OI4ogN8GNhOBZUtmS4WIyF4ejTxBSOzJW2TBFRWhAl7hZw8Wi4uFKxYkxASNnfFQQkTXcRhwrScVoX+jJOdAXkrdqjKS+cdVELgD+fkDsg5Hkxm0oHeI9Q2q5lHHieJDUT1/3Vx3S+EQEP1FZH59UefYrKnkBHHTX0ac5ku7Ich9gzxCedZwDxxjX5/ftgCeUiVYAYBVNkzsq0o3ycQm5fp7rBMfFq5g/2hDKAgDFAFv0oKtenDOhclrmQMm/15+BcMPbbxzLHaVGvBSvJ8VVqgs79xtw0r4Of3z9erivc9XhDcbPgc/EOQEzBtTNJ3zf31i2jf6FTLqlsHqDu98xv7IrIjApmLoKs3IQvkJQvSYZXMbJiyDzEwCuXpDwT8EVDuqpS5DGEzMNIQVqikQfO49wFWUEVHAeYqrJb2eQbhJ9DdcOFobwXFYXkZ/MAlsqyF43EF5h6ROXVrzU9o1JkXkfqFdNJj62ugrJHmBRgKR1rf2QeihaaOihlxRwP0vnmsJIwM6x4jBUuYSoKLh4FOc1iG4ARQvkOauythuKpMEhKHAZAtc+r2VQ4Nk0vuP2c2zMy6AKCfCovqCqAUhEGwM094rCUY+g6RFHERalgw+1YWbbvaYO0nkzmm6oyM4wr4VwB7RqLgKI1mJ8W5KMO4q8W0Y45JYZbbZxWESqLYpFg64RmhXLr39ZsJ1LMEzgjVw6/B2IhE41lhNG0Ce0Yuc2tA5BamVAj0WwrPke0vf1NzyNGgisYvXUzg2pzgbtGN1AcOoRhxCNbL8HNCfXeEKvjJb566U6EtYALGzfw7OQE/ukLj+DafBVHL65h4Dweb4Y4e44FF19ermHVLnHZr+Fr185j6R3mqYUFYUC3Nqh+tOf7eD0Mb/mc/tYvDn9vdvqWzznyHafS4eaBHMeQzsmrFKqr5EGe8G8P78QPDQ5wOYTvmdH3rCcAKsnhB0bfAcDftyCLv3XXY/ix4R6uBY+ZWBm9bf0Sxq7BZZlUvzC7gN84vANPT0/hzuEuPja5HdfCCorLBZZXR3AmoGktDmOD/cMRntk/ifZkiydunEVlAkwLvHS0gUs3NtFsRlAkmJqRQNsC9d4QsUww1yrYhYFbEFLJ1207ouyLaGqCm/E1GSpIgSaZ6oJSQlrPi23HBWmIOXpTxTA8nnBiix8zRca03KItZt0CjaTtbHxEs2p5YbfwKKdcVLhp0y0GpXB005Zz75VrCO4y6CIwi0gUqdNLRgEHazo6jw8wy4YX3r32auYaAh0dSMZZRSu1lZ156lZiWtsAO11yoeqK3GlKwwphWPC8JUVQFjQmse1xVhbH3fidF9YxSbHIXbTkbOfFGyTeNYovr8wRADpKFsDvr+1aICOg/TkriaBS/RCzz2JfhZ0LM4BPuAzXuYtlQVaSaVTQKV3FbPkjwA4VRe89ubYg8Xnm7pnWEynvcy4I+Qvm+y9T3fQXFYAWBVQo1EUWSms6o7mU642kbfcEnvdiB4Ycq1v0PbLpeMqn7hj/8XVsb/iiMRdd1nYXlF5AQMdn6JNRDfHFIO3lLOcXPke/tct/8y9D4NhCBgDk9eIVmT2iCgci9qvKNwrJKk8vIF0FJeFaSMu3i65j2F/3r0+yzdY+6FZFZEw3UPV4lvxeqUMNe7yMrtgVJFPaCYiS2gKIwKf3Go2GsjbvN1IUBKwX6QRk1C+7/8sqsRO/SKFuKd//+jr1DMur1dYjVl3Bm79/rzBlUQwPZtzmsR2fxXfqQ7OoO8QysEdjJku3vG/ZSkcQxKiKSIIoGcX4XFrzFDkflmLKk4iuCLmlzkWkaWVRYhh15MmS+VLFlItTaoMkWxhJn0E2EFd7kWLSiFpVTrGRIo8opzIky23rdkQYXdGJlk9Fs04oD4HFKZJWHb+XXQDFlGBafhNz4OClFvvazm1AJPjGgQLBr0QsZhXePTiAmwHFkcWlep3RoJUW87qEnRuklvDi0SYWdQFjEqaLCn414MLoBobU4P7xVfzG4R3YaVdxebmOt1dzjIY1fuH0kziIfK5fCak7V+3nn79bG5s3V1du+fefXGMk8UWfjhWIbTr+/l9ermLtVVrf66ZEssALL53CXmxwzlo8vTiTowi/uFx/2Wv+ffmXvze559jvZ62Dg33Z837j+sN4y+oVNMkjJIPDdohL7QYAoDQe1xcreOvqJZx3B7gyW4NDFAsowoVqBzgs8auX3wkEwrm1QxiTMKxaXPzqWSQCbl87AAVCsgl23MI2vGAJBeDmhOLIAJZ/Ji8F4iLBLVK2kKr2gWaNx4vogMVJXmCFASRm08BXhGaVkXTjIcUK3yOctc6IvF0GuefYTsfUbORvmpCLzVhZFq4QUB1IgSDjGOn9L5GlGb3RCdtZxFGVixm7aHOKVXIWRuy7wrDsUDIg88NjYXhxCuTiIndRBI3M84LhYih5L04U/LSkVCzdv7ZD5EjFKDoPRolnJeIumnKxlc+tHSFCnu+SlVa1jMk5nk8LWGkVIwgVKEYeR2+VygIwECDxeqRtY0UTkzh96JQhGcosdhFARhPZdC7vVUUk7Ws1/846BKVTyXVCfXN0eR71PYiV566KcEHrqCzlO0lqnBaPusOp51yiCKAWg/05WalSRlv+vTkoKo2qN+8qyqkt8Qx+9RBj/XvuWEaJMuyK99fa3vBFY14ZZMSwx3/IcLeeGOQTq0qnbJmTT5BkV1rLcLfeNHrA9XnGskilt+pQ13gtZBX5S2ImSsIpgRSJIOLVDbR+TJ0TfUqsVMsXYm+FIXwJUlhbLWNEXKIB8Xnf+6gq+O1wjG/TQdqkZuMqTElif1AKGbjVHOzuFJBe0HkgQSZrZ7QSsvKWizqOKn1x935kumJcUUb9/lYGKG0Be+FIKodGV8E9v8UUI6/ObS/dWCOpJAc8t1V0oFaejBKiZaDOCnFDiGVXyKqxLULE8uSAUVIg52pTYHGL7pedLEVhnTi+zANWagTjIys2Y0IcFDnejFFG3scwLhAK4hgzw0hLEPQF4MKv3mBEZbDPx93Nxd+xZa5kdRhRzBOajYjkgPW7DuAWCbaJ7OW4wgilaXgCt0vK+5iigZ1xEegWQKKE4sDiX+zdIxN8wtg2ooYl/NDJ50GbDWCB+voIJ1Zn8AuHFAmj1SWeODyLZSrw5OwM3rf2bfz4yguY1AP8T5cewlq1xEQKrd+fncbYcHv78ZuQOg+LJ5oKr2f7Sr2af36qLXC7u/UQqZnSN3MnPza5cOz3Rw9ux0X/ciSyv5kG+Ntv+TKebU7ik7Oz+Ln1F/Cxqw8DAIY9gcyv7rINzvPt1jEBzuvZnmoLHLbHj4uaqev2P116CACwbBx+oJri2XaMa80azg4O8dnv3IdrweOdoxfxk9vfwovLbZy0Bo23uLfwaDZ4f373pQcRRgEPbV2G8QYvHWwgJcLZ0QSxYC/G89UeEAnuyCJMC0a2l4RiBrSrrP6HtKG1teYHBD9iNJHHD2STbopAdcALotN37MJ4oFkxaFcAW0NiBtl+xrRceBRHXDTVa6ysTZbyvZSRpBDzz7qR+KKGkuDHDtFyBj0SmEsswhRT+64FK1ZmKJyEBLSi3u29ceoWm2xbJibZPsLWPtNkdHzMrWr5PM19VmcHvrB6BR0R8wgL2y2AVcwn1B0V2SDwPlLhsnCTYur4i3m+7NTMbB8k76nOHEqv0mhe3pve96U8tgJCD0sAjM22NjrfZZFm1iEgc/blzPA/5QsKhYg55lpImUyFUuBCT29q2y4eWLwsk+RPkytywZtFJT5kJxbuTkIEsaHb98AtanIs+MlKaeoVd4oAQkAd1Rt4z8CPfj8VvqgoJ1+QpuukAt1ipW9d17sWYMTEXJFMLSyB4wXrq2xv/KIR6LV3eycsISeh6EkF0PkskUjulQOnPX/hMeZVpOHWNKn5dFnkx5OQhjPnEB2alx+LUbh9gMr5SVq7StLNq5ZszNrtD5N8FZkE/68m4Mb2WsHo2cH4zpML6HyqVJkNeZ+MpsYOHdQWgvJeZCDr0Dy5mzMPrXeRZ4SNn5uGZcffhNzgwoEhL4OkFLDZ5sE5yZiOnSk3gQfCYwN8ysdJ2yoZ7peBNq+8Y2JLHG3vy6CSChlElR9UaI4032xG86llQjC1Fy+2bmWXiBDGJUd8yYBu2tjxSXyAqfs2HSbnU1PL7bBYICOLFDpjd4AnKrtkFBIpwTQRtu3OIReDQDkNiAWxeKaUAlvGIZJJuF3hGMJQsc/j7Wd3kQywf2kDYUCIlv9uazb8jgVgaiAMutkveoMwjBjcsNkTst302JuN0Y4TaLNBmywSAbE1eHp2GiuDGsZF3HbnDk5VR9jamuLu7V3MJwP8wukn8fj0PC7f2IAF4TvtCn765DdxenyEB8dXsBsrfG6xia9fuS1H8d3pJseUwQUFXCiOEI/N0rfe3lkdAQD+cL6N+4vXFpjs3YT6na/28VtHtwEALvqI8+MD/Mnsrld9jyhA5LsGh1gGXkz8zdu+DgCoY9dy/7F15hPeX+7dEiG8eesfg/uLFiPX7essNXikmh37HusDVtqeXuNjMI0V5r7AtXoNAPCbNx7CgIBVUyOBcNkDP3rq2wCA8tDydTpzePDMFbxndANuSnCXK4yGNWa+RLORYJaE5xcnAEp8Hc1ZkNKO+dy4GTsDVPuJi0TigrLZABYnA8izj6iRLhvAlju25kSkuS8RKkYfAfYvrfbEBD+CxwPD6VNW+Y0RCAPHiuYESaLilrVbeLSrFWdAV1Y4wBa25vQlVQ+zdU1EGBR5Is4dISDbd2WetKJrBvle1px5agO3bp3LNjzqE6sLWWp716aOk71UKnIuC/EAMOVGiyih72hYQGp95/EIcNEn4pBb8eioKDKli8RTMfWQuuxRCDneqQMOSL9TbiHrfKhdvO47kZpvJ/lO1nVt71wcCZCTee8942ulkqnSWltVKUonkYS6JQEbA5mHrTnOa9S5tU8TU/5mpmp1aKImvzA/0mRghKlcAjyAOr6kdhXFR5m0wNXPJJmXlMLVn+sJHahD3fHM10Ue8qTY11a2Fruqqi6KrFB/re2NXzRquPcx6Ks7wGRd59aeeY196b20gJXPIPCyFktJ0kyy6kuRRlVVSfqIch+yJyKA3BK2EkeUT7bNF0KOCFQllaJ5PYIvyfNTEKi/p/TKnEojXospidVPTwijsHwlyTUKt6cej0Tb87oi67ePtRgTjkm+CRIyYpuN0gEo8kuLlr+7tjosG35zPF9XMKaq4HaFs4grg66IK504DHSFlPpJ6v/JijmsMYijKiN8esNxAoMW0eiKdy3+ZBDMkYf9dnjdckt8WALSYmJfS77uKHB+agKT+N2cuY2UUk7JATHxPVnDhPiUJNeaCfCmCXALvtlz6xpgJMOy55zxkblS1iAMLOxSC8KULXT8wMAtAvzQoDxkblezYnIsYTFNeRIsJ4zC+GhgGmB4jbOxQ0WoDnjCDiVP1GEAVHv8OwC4qSwAImACsL45x8baHLhacVTcQYlnrp1CKhKqcYPdlzZgTYLdKfDSpZM4aEeog8N7Vp9FecD3zM7RGOWewx/Nb8NXj+7Ad5oT8MngTneIu13CNydn4Sb83Bd9wpop8QPVNEcMvrM6wohKGNDLUMhXKiTvr67e8u83b1s3tZ7/ZPcOrNolfuXGfXhieR6XZht4fufVIw3H2/P88+0VczetDM1ni4P82F1y6b5en8nJTfzNv7jxHADgOU/49esPHysqt0wJZyI+u9jC0HJB8q7BBNde2sa1vTXAJkwORvjU9G48VZ8BAHzq4P5cePpxgj27wNbZQ3xrl3mgseQxoA0W16erGG3OEYYJL+1vwq008GO200FCJ6RK3DaOBdCuR85WbwXNXhrAgAs9AkbXQ/ZgzPzfYLOAa7jL1A72U+TnhMqyaMWwcpoiECseI0wr2fOW+KqwbPSfnLgjWMMOCASYlq267IKPVVgZiBI75HZuuyGOAiF2YjZtSdeK2gEqtOAUGYkUXLbZ6DsHCig3MFOXwOOWKHBVMJMt0ELs0NK246Ozapu7DX2RXUZGpWuRCzixGAPQgQK5RU3dXKRdGaTc2UpO5rDc1jWZK0htm/czewyK3R0ZsQNyXKAeQypVwW1tpy4GF2ipdJkOlazNhScEYMjdPtUGyPyaUsohE0mLWPl7Glb8vRV1FZ1ERgWlCMzWdqBOsGOUBkYdpkEQjYXL7e/c9atroZb1C7/Y1R4E4XpSB3TxjnbFZQ8QyrnThucvdmaRolXqyGNdytexvfGLxswJMKCilIMuJ8oVnR9Tfi7lgg1AxxEM4VhMUm79Ahl5yibiPbQK4JVZ6sPHkHtS+Bdo204co8IW9X2M4ZhTe7/u6lZTskK0jleQ2sK15phBKUj4IDdL63WV2lsZoyh4xdkrAEmtHYCOvFy4Dp0F8WeIdU4+TpBjkz25qIP2W58LVY6LYnSNWyyyctP2jloY6XFFbynQj/kzhBzJJIUnEk8ImZ5gpehXg24jObGDkvdXbqSMFsTEKkjhGWVit+ZXy4CdV/Z6fgBRCxLsrGEPxkaQBHncLFpucek5FiQEMlEVE7bYcJNl51Mm33OxzZ6Vpg2gxHncIAj3y7Ay1KMzJyaeUENJOVLNeLEYsTxhA2wAfmVvQ3zv+G9+RPBDjhsMA6CYAn7LIzpwqgwAN5PvbAAKCUfzASazIZLjohQWqG44uDkhvTSErQl7kxHCgFGoG/Mx5gdDPN2cQrsW8Vg9Qlg4hGHCbjPGjZ11PDM5ib+y+Rz+952HAQAfPvE1ROk+T3tJLZ/f51bx022HGqya46bcPWLCse1UTwzz3Wxv334Jbxlcwe7OKj6wchmzeYVXqEvz5mM3DL+9mh977HxPpXmztU6TXt2m5ydGO/g/Du7Ov1sYHMYGf7h/H96z9TSOwvEC+r/YfAYD0+LFw00AwFFskFwEUYKbWpzYnuC5vW20ycKZgK1qlgUyaeRRHw5wYjBFaA2ebEuEQUIYJtSzEqdXJ5hNBqj2wAr7g4qTjRaMOIaKEdd2g0VVYcCTGgX+e6gSTGDRTDsiLDeFiysIpW14oTTfH2aFNQU2uVc+sV2I1ZcFkiOYli14TN0hacZH4fQl8WJlI/4wcAgDEiPsDumHoJdGOcyLBggydvgk97CIJWTBqJccec9ejTq+tl6EewpydAI+fgMu7LKyGfzZutgmtV4BGKXsexQiZTAgqQevWqnpWK1egupGAeRCg2QxywfJZH5jflxpU/0WqvfZDzfTY5yVlreMw5qXLKIXshYYDLr9l1Y4EYkoqCdOFZQtBZ9jBbNzhQIfx7icPWRQ29f5MArAY5gqRI6RR5KOW2q6/OrcWs/tXDr+3jF0+6a50Drn5ZtRohRzt5K6WkVRRACQFrlS5WCkxa3HOQGdeNd0qnWkTG07hjwCXFv0jkGmu71ONcyt5YZvpE0gZOYX9gqGKNwDCIrX4+oBnGbxsseAjhdZCCwVu3Zl8gFUVsih5bppJU/muL+TrljIgkhV13olc0nEamfHFgFSqFLRtUDQ8oqFMhTPHAyOTJJisuhgfW1pc6ee+XU5hgpdYQYDRj91RZdD0dlQPDVNNtLOiSiQ1omPOeM0+SicR1Y7p9Lxe/rAaB7QFeKtZ95Nq/nVCYh8TrhdpMeUsu0D6Z0fA5CIb6iqAM04tL7fIlLDbVhpO7deVvSGC8LG55t442O7YuzNA35YqZjAXrd50O7HFoIIcVzBzGqElUFnx1M4xOKgS3soLey8ydyiNJDc2dUqTzyq5m7XCpQ7c4RxJcR0sRCZtwhDjhYcjw0Gex6hZIQklHwsywmb6LarFsGx/2Ix4xZ1qPgcF/PI1iGGE2KWGxYmcOG4WnGBONgNaNYMKAL1JmF0PcKXhHaVMNyNmJ4jjK517cD1T7+E2+6aYPHkGopFwvQ8UGzUSJFgn+eIQbegrpBKgF9JeNubvoOKWjz1zTOYzAb4FgpsTy/hkbc8gQvxaXzs8sOovtbg1AtL/Lc/+Dn8vy4/guLgAFtveQmfndyBjSsXsfXSSzjnDTZcxGfmJ/B3Rp8EvgH8yeWH8K5zjwMA3i4f+/Gj2/Cfr1561aHjq/UKSvK57X2rLSDBymD70YsP40Nnvw5CwuY3L2Hj6kVsvbCNmAgbL1285eub5HFhbfdlf9/41EX81tF5vGlw7WVt8iZ5vOgrJBDuLTwu+pTjFPtbmwIeHHWm5xufuognlxsodq/jB297Ac/5F7FxUwrNe3EZjz81wpN3HWGnWcP205dhzy7gbwzwPzz8ZXz04sO4//Qz+MLe3Vivlvj9wzN415nncf7gOTQvjrF6/1VsXQ346mAVJ/YuwZ1cIr04xOJMi7NXakbz7lkiXB2yQt8ntGOCHyeYGjBe0ogAREfwQ24/64LGLRLqNYNYAePLASsbBm4J9jklYLxlUR1GIIKtbywxXaOnTm5HFq6OcHPP6mifukWVZeFJeVjDjwrYmrOJ21XuIFTXuIWfJKPeLH0HDjSekS5n2FZHbHfcwRzNiTELbuYSDyvjIzVcJGaON4A4mHA06bBkl4W6zWNLHFcwy5YXhQA2//fLnL7VtMzDNsSFqzUcIafxtNLhoqJg0WHrM+qY70WdF2B67hEyfgbh12mhZC13fwRUyRxHBRoUiFHhZyP7UreCOoI5/QAji84hBZmbF0uk0YDTp4T3l2CAZZMFI2xdo52tDoXLXUKSz3SOASNCxwnVTb+3orFS9KrOIfsvZv5l7I4niXm3NUDoVZ8xCGCBDpFVKoL3nTezPq9fxCqlSusNQXHTzVxDXaj1ldUZ3NHrXPZdkFByDomJl9Li1u8Ehg5jRKLjY8ErbW98pLHfQgWQpfo9/kdG96h38oXcmpFHXUUptKuIVs9yIF9QfY5h5hjIhVaKpF65dUZuihBzcZrUVBXoXaSQ9q/N+5rENqhPYGULBoHDjeFoJ1V75YJZEU2+SJK2nrMCGlz8FUW2Ici8QydWNqJi6yN8qSwE4k/5b3xsbP4bJXDhFVXp192E2dPRexnwKO8PQEiDilfUonImtRKQwhqQFaOgrHnFJvxBagSBbX0PVe3ta15dx2O2F1lN2B6/eZPun1dzcC74oqOunaCTleGUHLuQaEUllBPvg501jGAIp4mzYYE4KjPqiQS4OSfURJnkFEUEAW7BrbNY8HFOBjANJ8AUU5+NvYspC2yM54zrZIFQGtgWmdtYHgW0a5JnvUicrtFISzsC1X5CKAl2KTYouphtgIPJCKEClhsENyOUzmNUqWJV4t8IaE4EbiWuthiYBueLPRAlYO7gbhQwLXAQKxgknFyZ4nA2QCwTBuTwwyeex/bpCS76BEKCrTye8wZ/fHAvPj0/iYuLrXye/uuzj+Lm7ZUKxk/PT+afn5qdvWXB2M/E1oIRAB7evoSPX3sInzl4M5LaFx0VyDDLLbaSHF6cbQAAPn+T+vvybB2L+PJW9K/tPIQ1U+NeMQT/6itwJucp4IsHF4797duzU/Bi6K2xhX+82EKTPG5ELk7Pn9mDAfAX1l6EXw94/+lv5Gzx0ytHuMMdYD5jvqMxEV946U34L089ilgmzH0BagziISONzaRCux5RXCtgGkabm/0BTMNIdCgIxVGCmxEG5+YsrjIQ02xGISlwuzqRoPCRr9NY8L0eHNMvAGB4nXlizSpf68my+XZybEeVjBSRiRdgpo3Zb9GI/U6yYLqI44nXtAFuFlBMRFQhqJuadwPyfNLxDNzaDjEvoHMKjDp5JOlKxMgLVoDpKSrWKxyPV0HHSdsZOIfeDZdTzSiPVRDuMb+pop3SJXEaN+uzyIVVytQpa/mFWdynlJ083ln2k4SzQq9SxDFkvju3QXsQuySHkTGdX64mrlgu7EDEFCnxJuQ5wiDnVWdgBGIt06M+6VSckOeCpHZESoHKLWMCkarGTT5+KkzNVjopyflQwae01hVZzBxAEhpZ6oq8Yy4tvQITyNoIvZZUdJOPl+vOafaDlPEfPeCkT3PTojfpQkGLTz4QHTqrrWv9X983F82vvb3xi0Ygw+g5b7rPRwCgyqd8ohVxVH8mmdg76x7hDwqUzEkyPR6B3gBKYu0ppDKKqIKcTKSVSSZ7N/Va5jGJeahA0z0OSY4qAjp+iLwutQ1f8LJqVGRVL6au1U3HP596lg76d83e1oK4N8BQ45kT0njJhE5QM1guzlNX/Mp75lb+kk2EkxRWeuzzRd7yJEAp5QKTWzRieqtorYpyCtfdLMpDtL2bVFePzvIA1UMgujYBuoQZaftGJ9xIVWG3HtQ0GWmmHg/SLQSxFHujZrUH6PesDngCSDmJASll7lSyBqZlgQtFmaRCZITRGtiG/c4oSDZ15JvfSCFJgc2IKSRWiiaeZNuxhV20CAOCH9gsBFBOWHQ8aSMmlAfgEcIAYWBQThKWJyNC0T3PeE6TUe/G5AA0BtUho9XRJSyujDGZDuHHCbFMaNcCQpnw1rOX8VPvehQ/fds38c1DNss+OBxj5cQM7VqEO7PEl44u4Jn6DK5PVrG9OkNY4fvjRruKn916HGddwrd3TsIVAZ/ceRD7syHW7RzvWWdLnP9t/8It/RtvjtDT7UbDf9+PDd6/cetEl2m6NafwPaMbOL9yiL2DFZgRX4Nrp6e3fG5/Wyz4/fbbMT41P5Xb6T9/+mt4pJrh4yKs0X2ug8Up6/ArN96Mg9jgw+vfye+lxuTXg0edzLHWNwD82PrT+Pk7vpjtiT45O4sEgiOLZeLr9SdWv4WdllXkp7YmWMYCdsjf597RNfzO4QOASTg4HCMclbBHBv9m5+0Iw4id57eRqojkEtzMIJkEGvGCgxI7ARjh0CZLaLYjTACSS2haxzSDBPYPNYxElkdJ2sCArVnRXx5yylF5JC3oBLRjA9vyQqia8P3ilhxf6gfMB1ZOMAjZz1Qtq4KYbHP0IN9PtGwR5T5mVDLk4i1pyzREpr6Ip2KypsuElhagbZh7nLTLoi1gYueFROAxRikubci86CQWZhn5sybnTydtkwp6iChhBFGsYwopEjVeVQV4wv/Tg8HpK5b5ezH2KDc9vh7AaKYUUpo0kwvafkEC5LE6F21ZwCd0IJlHSOcSooxeZkAEyGihghyZ529sV7gpsNNv3cucwfY7InKS1LdjAIE8l8rqWFoZz5lB/B+7/VHO5LHCTLmDWswZ4WNqQa8dSQVfjCS2afGsdUefyyJClY5jqgCI6RV+JgNKGahS3mXeKLe2j6XTqPBI53M9Jq+xvfHb09qrj0FOFKuROeZI26Om540IKCzcIXKAXjAZYZNFQmepopB5D40KQVY9PQQzRim8ZB80C1NXn7KCSYslv8Zxq5vI5ZsGZDMadsxZPre9DQjcGtaVKRd26Hy9VAkOCArJ6CKC5xuh0IzrxBebESKvrMCSk5a3fC6CWucwx5ICHydSr0s9vj3+Iw+4ve/QbweE7gbN/MJafbs43i8nH2gxGgK3aupGjm1346SmBQYVcwm1ra+cj6yqDoDnAXnyQ+eZ3yjK7UTI8YZ5oPIBqMQUVwtvfa8kohlic+7msOlI7DEeUzbGUcltK2JEIZYGduHRrldAkmxaAuwioV2vJE+6RSwtmnWH8oARRvIRfrXgCWivRipt9n8EgHa9RLNCaHY82hUL2yT4AcFKDFsyQLSE5QkgPeux3HRoGrbhWWxbmBaYn0uIu6LY9glIjByGEhg8/hLaN5/H8rwHzjgsTyaMLxOmdwWYuUU5AdpVINqE0TXCY7edQr19DVcWa9hzG/j1zQsI6wbFyhKhdXjwxIv43AsP4eJKg/ZkgdHmEZb7q/h/b63ijuE+iqHDS8Fj4/wqrk3WUJUtmtbhq8UW3rv5JFprsXP1HrRnXu5r+BCA/9vF9+B/uP3rx/5eTk+iXWmxAuBzi038yHA/P/ZMa3FvEVAEj9beeuh8+vmHkDYsMGrx4rmr+PB9u/ilb/8wEL56y+cDwJn1CV70Cd+6egZbm1P85InraO8/j280Q7ytXKCab6MdEb51cBce2ngBd95eoR2fx5Wn34zxfTN8vS3xQNFgmVq0EWhtgW8stvBjwz2MP9d99/b+87gNwK/t3oOtao4vFYe4PDuLJljsDo7wnaMt/PfnnsC3lut4S7GH1p7H3uULKE4tcOKOVbQb5/HpGw+hsAEmEWZHA77uGoPVM/tIiyGmsxKIBDdqUR9UwFoLYyNoXMH4hOkGx/4tzwGL0wmxjHAbBvUmYe3CISbPrzMKWAErlyOr+acRyxMGg72EtIzwKxap4TzochrQrDKyFgtCvN6gXStQTFq0qw7FkUcsLZabFuU0ws08m3hH5vWCgHKvAQwhDC0QAbvwaHyAXx/ATRuEUQE7b9FsVqiuThEHpUQJ8sIucxJ7fOvkeOGcnIVpPMK4hD2qc2CA0lLQMo+afEBYG3BkaFYWm2MUoFRamOkyzxUr/+7rOPqR27rnAbLYtZwxLfQiOAs0LVYfu9F1S3o8N7Lg8arfdZFFOUHQVI+uaKlT97P32bYMdQOQtKtF+MLHxOSoOgBd4Q0ZVw0B4PfSxC1KYuXmLFA3wvlHR7VSdFAUxzr2JiOAh9qzkenF+3YACJVFFwcc2X8xWQt48TIOwsd0zI1nMY3r5idp+3bALLezkxxb6reoZWMxq7aowWlmJAKeRsZwjSpOPl9Xer6SWBiR0L7yNaJt/RTR5WD7bj4KPV1EbmFLoYjUXSevD2j8/wOkUfOI84HsTjS3WuXmUeVTv0WdfZtkdaaVeIrZ7DqvNAAhugr61mtrJy2UsvJZkEl9j7z66OB3ONdxF/lRAHwxssIsHIuLykbUJKskvYnabv8gj0FWOUrMzdGGgoKmmJhDCeLnFk4K65i/R/9Nk8QhqiUQ38R8g7NbvxSkWlwR5cJbSdjHimpNjQH43Gl7oPVZ4KF2Nan12c4CCV1LHFKoKp+kKkFRkLrSsshn0XkrdmkGLHSBZqeK4pzqtluV6feoyhz3lHor1zCu+JzKZ9ulrhi7f2Egma+O0xl0MKIQuJ1mwKIWfV9RE9o6wC55smHD79TxIBOYfE8Ev1aBmoBQ8qrUrxaZu2XqwHnUJSEMTB6cErFFiWn4+7hlgq94v4Y3PJIBRpfZHqXeIISCk2bCgNEjACAPVJccjAcGO4RiGlDuWAx3uGB0M4ASYX6hxdqwxhPXz+LGjTW28AmE89sHmM4r3L56CADY2p6iXRQoKo+7Rsz9u3p1C8/OTuJ/vvog/mR+J9638RTWRkvUTYG/fvuXsbu/gsfmt/PpSITrrxALWN0i7/kDK5fzz1/ZuQMAstH2d5oTaJLHb1x/+JbvxxcT4T+7+wmcWZ3gt3ffilVTotx7ZSuLP15s4b7RVTy1PIez2wc4PzzA857w+eUGnpqxSvk9o1081RY4EuX3XsM8xR84/yIAYNUwz25ARU6zKYm/21/dYpuej034eMxTg61qjg+sXMbAtBjYFpvlAhEGzvL3/NLOnVmA89+d+wZKifv5Sr2K9horsn9q+ymQTbBHFslFXNtfQz0rcefpXZjGwC8d4iCgfKlAaC3qTW45IzGFYXZHQKwiyHGL2p/w2N1bQXHEHEZKQDsyMC2LXIojcBvZqPk8iyv8wHDbOwHFPMo9JMWBCNZ4UcM51bG0aFYMo+Qt3wOpMF3bOwFx4LK5NwAx+TYIBb9nqiyoZQcCpbWYltOmALCoLcSOthET7EwWnNpwkiSqrMzVFm9KEvHHXEqI7RctapiF8BbrJvMfM2jRs1ohEfOklWFX5KjAwnbjqhYkSRA6SmAe4DGUlKk0ZB3gDKOipXL5pBPXMO+yL3DhYs52tmnaQeond5HJhuvJ+05oqR0mMjz+SoGaO2LqKkLorN4EOKHQ+R9zyIRw7bPYQ1A4sbIj19nSqRCIxLIo26Yp8KSCWuV2JhyrBZJvcyMxi1PlmKReNyz/3GuLy4v488TUvENmIRQ0tgfqEEog+zdKN5KkSOyERSarvhmMCblb2v+Ox5TYr7G98YtGoFd4yQHKtZ8Wealr8ULa0So0oS56sMtmlOJOBTCa7pFS5kK8zGLmGGQsF76qrvPnCVSvLXH9O3+kvD51JzgmXp0pqk0SY6RQfr8lrPYF8p792pisFf8sLdZ4lddFQImVj+6T8EHISCSfomeKskqbNxdzx7iJ8l2M6RBEMR3PxYvGEmYVISSWMGQ1oaJ+1OcH9m4gvcmV+6jtHBNTTn+gyIptSkmSZOQ8yT6TtMaVM9iprg3CStVxc/r+a4WFqVtZBTPv0C54Xzl9hQ+C8WJ7EXpFn5DSORmGhTKmDgijglvGpldwWis+jjJp6QTXRlhRgyZpqSfL/ou2jagOAlLV45hGVkfbOsK2gKkjBvtijE5gXlfiydLVPOlxO5xb4ZqmR9qlyXwx5Hg3P+bJWG+1ZCNSbXE4H4CmDm5umLPWGuwvh6BpgeeunsRRGPBzPKFd8mRjlgamJRASFtfGGNkGW6bE0aVV0GGBLVOCgsFY3MbPjSc4ZYtjfor/6uAuAMCa8BU/KcWZblpkjit+zb+6+A4AwLOTE7gWDPMuX2FbHS/xYFlj1dWYTLnA0ojFW22HfogX6xO4UF3HVjnHu4YXQUiY+CH+8ubz+Xn3FjVODY8AACuOKR0/PrqBJvljCusD+Z77foz/x+W34Irck8/vbwMA/mh2J4IYaP7x3ptw1AwwaQe4Ml/FsuaCMwZ+/KmWfz8n7/+lG3cibbb48a2n8Zm9N+P0xgTFDChGLVAbkDd4YMQJOm5qQYENt7fXZjA1UxpsLddCJJQ3LOwBR/xtrc1QibenbZFN5G3D3qOu5tayryjH0AF8/YYB8xdDwd0LFXclpY05NgW3TYIfsaMAiO/B6iCgXXUsLgEAaDY1uEAdiDtCSmzd0zv10VKOGMyxpEkdFXg8S5LaBJkj2EqMuvGlpwgzdU8YqOMjwBxpWazHyuX5pNvUrSLlOUm50SDqtaHRvb8UPMkaYCDWAzIeZ4W2UpOEzgMxAoeqrWX+zJGFhuMIU1l0Po9IXSiCzqm5TYfuuGmXTkQbHRpJXcFjDLfQfe+4KR1LYvzgvVjQUS4Gk4ArCo5kb+MeiHGssBZT7hSCgIriQpLn6phpUQCywwm5Ilv68O7JNepcl8qm82+vIMx51cZme57uPHXzP/poYQYvhOYl7fOk6T5CpTp+mfQWF31+I9BR817H9sYvGpXsqsWUxgPqgT8mcacORcuPyVHXkxJDLt76z80nXlZA6uMIYvELFT3uoX6OEx8pr9nTXPgw3G+lxWpyIQnI7sQEGlR5BZZU6KJP0JWRoJnZ4yrzKWUf1LOwTxQm4jZuAtv3lKK26l9RMYk3WOxUztaBql7LWFe9KmjRG1QLS8nF1hZOp2AT+kDTZLSTCserWV2x6iRpunPE3mNlHjzZCkhWrD2rA6o7z7MsRvIxD9B5K3qrs/xi6sjoCTyw9a0W9LirYq3HL9Xj4dfK7N2Zc2VloM6EdTk9FBlBsXWAWcpqXnzgYDh5xi64gKbGIw7dcUsQOd/ZKkPUoc2qhakjc7k8YOoAu2QxT6wMyqOQeZK+4uNMCTmnujii7AUZSmCw2xmKU0ywLVAsOo6krYGo478FyLMaO04LxEFEGEixHAnLukAaedilwbOHJ0C7JYqJAQJh200Ri4RoE/ZnIxRzYOor/PFiE1Heg685YBkLNMnjhYMtvOCBj++/JYtcJs0Aj9ZjvGP1OwCAJy6dy6f4IDa4GtYAAL9w+kkAwO2b+/jD+TbuXt3D7c7gvznzOF5p+8CJJwAAz+yfzJdOc7bNvMSbtwuD67ixHOOzB/fijuoGDBH+zfPvQJuOo5MWBh/siXd++doD/F1Sd22/FAI2TIllarHlpmi8w2m5nt5+8iUAwJuqa7gy4+93dDTEm1Z2cHZ4iI+cfhLhqMRn5icQvcG/PbwDT8xuw5eWawiIICQ0kwHosMCj0zswLmqMHUdW+tYilQluSpiGCm4OxJLPvx8DI9fALflaiY4XG8XEwARGHdsV4ODiOkbXA4oFtzTjMCCM+LpqVh0LujzQjgn1OkRYwo4AzYpBvWayNVQ7NogFe5DGgYOdh1y4s7iGBTlqPZMMkErHKP7CZwPvRJQLxlSwaAalY5Sx9bAS96kpLtkqK6Vs5eUHNqdGZXRPEJ80KLPBfhgWuZXIzhIiuAixKyYVqTSm45y3Ld+r8nzlRHfIUsym4bqoVfSN3xNdUQd041bPw5BCZEGecublX2rajn+oPE/vM5cbQDY/zyJP1/H6+sgrF2c6nseunarKX4k9pNZnW5lUCAiS2/k9oYxjpC3HLvY6jnnrdQ51XiKZC7mWZEpWBkNkfOfYXEEljQEZy13BwnVIn1K1UspzN4m/JP8ic11RSGpMkVvTPC9JB0vnFKG4JRW69ucc0TVkAa3qITJVKkoxTV1SnL53Hj+oB4q9+vbGLxqtlYIMxw+iMR1CpwevjywmgeSz4IMkP1phZUXz+L25wu8eO3YConojpo5/YQUadvIZmfdImetGwmUBUtfiBtDPlebUF9trQzOiSVWZfZpIbx6B0rPtzjGn/8SFatFZFABSGKk0TVVZJBwP161gyRgRrQjfMfuL8U1APTW0EouzNQNBeJWxQ0rJdO+r+6ebKItz+1/IwYwcysJAi2xZTaVKB5quUOtWgynzS/ptZl2ZUZTPkrYRPLeQ8+CgCwxrkArTGerKdcSrdv7sUHLRa5atWHzwMY0Fm4/n42AM4oARkOhMF8llKLdkYiV8RYn/ipYHZRbNJI4nDJybaxu2LTJNkoKPW3PVJGQktZjzNRYKMTi2hHLKtiWsIAe38AAUM24DtluMdjYrcm6JbVKSIbTrfH1FB1FzJyQHUODkD9MShpctF5EBXLROC5ipQ3EEtN6KYhawQ48x1ShGLSgR7t3eQb0VcWm6jkd3z6Ncq/GmN13G707PYPPsBMtQ4N8d3oN7NncAABvlApclx3lUNFgxS7zYMPr2Y3c8ky+tDVPiMWnlHgpq93Pr38FDgyt4YHAZy9S+YhrLP3nh7fj9/fsBcOu7rIRUHwkPDV+65WvuL1psVXMUJuATF9+KnVCg3LV4docLXI0g/NJyDR+bnAcAfPvgBFpBA6/71fxejy94vz8+uQc/ODhCnBX4lKCoj+9zYTyNAyyaAleFq33oh3A9q42nJ6dA3uDSdB1NdPj64W2wMFj4AmbcAhsN7hru4szgCMvg0K5HOBdhpxZhAHxp9y74EUCes8n9MGFnMeYFRAWEIdgXtGYxTHWYYJfA8EaCH/B1Z+uEYs/CNJwOE4UGEQvxFp0CYUBwNUBt5NQjnS99FBN9yVlPACxhsB/YPcBHFJOaF96Rr2G7FAFawfccBVmUFcTimJhATch+jSRG2WbWiCODtGNFrZu9Xwv5mzWZH20aGSOrAmHIC3LOrCa0ayycSIoIRSny+m3rBFbQ9oqPvCgEJII0dovbvkDFEC+aBZnSDoyCFJA4WyQGBahumeeXEqLtjcN9XhwoRxEiJWDIvqSph36zWFTQSfWjFaAjj91G5l1pJWdxjD4XkHlTKV1a/CJTsTgaVxA95T0qSqht7Ji6eSchp4Cp0jrb2OSoP3O82FRkUq35yqJD90KPipYpWCkfsyQWbcd8jXv0tPxcLZ7lbxlQuhkJNL1zqzVB6O2nvqfS0KLyJdBRCbTtfqzb+urbG79oVLGIria0YEop50Lmi1+4hqSm2ABy7I+uYFLHsUNeOUgxCC4e9Xx1aKZEEkbme2gBl7yITvpolhKpVRm8rHnfbg5PV3PVJFY3ynGRYjYjhOpQr4VrDwHtjpEMFrraUsPzIG1gLYBuvkC1+CISwnBi0U7oPQ61RNDCvcvkTiH0VnHgfavKzF/JeaOKihrmyLABtxxf/d5SqFGrlAM5F9omB4S3lI4r3kSZSDHKyp8fzy2douh+j73z2bTHWu954E3y/opAqOJb0Au3jHmAVR5lKixbghQSn1hyJGGUfFrmchn49QGTnhOkbZa4XeVDZyouLTGeTNhguFlzKA89woCVom7BP3OxSmhXOE2mHVmEyki7jwtzioAfGYQB84/cPKKYcuUYHcG4iFCxTQnA3LFEXBgMV5eIwvOiBNgF5bzgdi1mxXUxA4wHyn0D0xBMAyzPeqS9CnHAedc/cOoifnf3QcTdCrGMWIQCH7zwNTy4cRVhv8KJ0QwXBjv4xtVzGLkGH1x/HifKGf7z1ctYMw0WoUDtHRapxd3DG/jcwT348+PrAIAfHBzhS8u1nMU8rfn6WjdlTpAZEuEORxhQgcsh4MZN8YH/+vBO0H6B86MD/I/ffgTLy2Pcs3EDH5ucx+3b+1jRL3uLbb1Y4K9tPwPMHTZNg2KWsLXGSStfnt2NFzzw9Ow07hrcwH5skG5UWK24RX2lXc+xhXdVNwAANxb8PX707m/h8av8WFs7fGp+Em+v5vi5276KX3/xnRiOa+w3IzxYdTzO2f4I7ojQNhbb5QwnBzN8an4SuzfWM+fxXYMJfmK0g93FGG61waBsUUyB4Q5gnhtg/ewEYSVwA2fs0V4ascJecqATcRQgJbZ/atZZbNWuUOYelkdAecjPDRVfV9FxoVgsmBZBPiGWtlPuy9qbW9rStpZcaNskVPstL4acxAE6YtFZw4WWmbeghlF3O2/5/zqw92LB97Fd9sR38i+OSy6AdL1Z8gKWIz5FzexjT9BS8BzdcifE1AHsNEAdV00RK60UIi/qTRuO+yUqMpXQzSX9tqMuaKMu4pOkqEihLBSebJGjptsyZyoKaeue44Y4TuT2r3abRPiCEAVt7BW7BADimyv0oSQ8Sh0v86ZAjhZxhQOGA2ir+RhPX2leCqxoZ41EEa58US12ZX8zNawXL6iZ0V08rxRqWlzFXvGo1kWhV/RpJ0yQPKWkpaxr0Djc3rxJnV1P7ggqh9RYmdf14HTAUvdZ8no9Z/r3mzum+XXyWbGz0VOg61ih/yrbG79oFJSkuxA73h4Xjh0PT8PEc6zgMV6gTPQ92L5vO6PvQ06k9HphtO0xjh20ENJVlVwnXUySrAT0gk/oboLWQ30Ic5EAdH5TMUrKTHfDHbswkATa7lTa+pm56OxbQfjuwsuwv64MBcVMxnRcTTJd7maM4uslBXNXSefjTYXEFjY+e4xppB6k1a8tCI3vI+HFaNpBJoTLSo+kMM7em6Dj5O+mSynQmy6pVYU1gkhS14LXlABpdWdBjx5XUUJCOFRGMrCT5YlJ2z+cl51gZyrcYSsQknPrZi2jlyl1JGbxjTPS8qIEfp+YYJZsb2Rqn600bB0YvRS007QBykHkSSrBNGwgXm8IiicFHkRUU068EPzlkMlpa1YNouWJzs1jLmaJGCHSGDgT2VbFl4TFrEIoWNjQDuVU1Iw42Tm3qNlLkvevnPJz3W1z3H/6GosgFqyM/drebZjeGAObDezc4Op0Fd9pTuA9o13EUcCl61vY9SugJaNin5ufwkQIlzfCCDuzMWZ1ia/XJ/CuwQR7+2N8pe5QuncNJvjGlNG4ZtmlwZy0bJnzr/cfyH8zSDhhSuzHBn+82OTLIFrEMuF6vQqaOlAAbiv3cLqc4KW9zVelC33tKiOIpuVCNVTds0sTMCCPRVtg087wL68+AnOixsB6LFKLqR/gPePnAQAPFFzIPrzBbey3VwcoBnxixqMab6kuYy82+HZ9GkjEIhfj8Zmj+7gYLSNSEWEXgLEJp4oJfmD8As4Uh7DjBjEahJrvt+c9oV4W8AcVprMBihm3o20DFCaAGoNiSrh7a5e9P9d5Qqv2AD804lkINKsWFJky4eZ8DWa0X4ZdToxh+6h2CBTTgGLGNjbLTYdyykUnAPihY+9Rndm0wGk7ughnTPOc4Id9REzuLRG+RMdIft6f3KHoIW0pAZIHn+R35e+yUK2LW9XsekYWE4xwnWEIZuG5wLR8XHRszu+r1mVJHsvK396iXQEQEahAwgm0JawWOZ03oVj3yFzE7WHboZRFAY0DpEVzHIlS8Yi1fBgkBjeR+B+2noWTgnxmfntGCuWY9iJxM4VLkUM9vpo33eu2qfgwSS2k5y+LP3TsVpoR0D0mP6coxXKOIpQt+y3LIGh7rXopUskJ/1Avg1wL9N6ov796nHuC0zwHEXUi04Tj7wHw3Gvd8eOfAPWSzkIma3vdzm6xkLUISTw55YAlBbCIkKlmr2Oj1FUrb6htMplgfX0dP4EPw9G/XyTY97fvb9/fvr99f/v+9v3t+9sbffOpxafxGzg8PMTa2torPu8N79NoVldgUHSxftncUiTzukJIiePx5gtuWVZlVl2p/5Haw6SmYQKrxvSJ6XXqK4WlTUllCU2g0dij1DSg4YD/l/xrjeojyV9GjDmzmqzhVaryYZKouDTTtJHs6hA6mx5ZwSIK7F0VHOGUJMNSWhxxcgSzuZEtBNKoAqaL7ntJCzgt6y4uShVt+v7eA6tjYDpnkrKSda3NopPUemA0AC2WSMNBZ6WgiKuswpXjkf3MyoJbJGJSDiJuT7fcNjJLaROqbYGSfJWUriusYSXinZQNcuOw5Pa7c13Ek6QLHP3YHUwNKFw+9owoCjIqqQ15pdZrCWQ7BSP8VG2fWKUTWJijRVYhsi8ZmG8pSmymJ3ToaRwUcBOPWHFMmV20TL0YiIWQkvJDQr1ZoJhH2KMa7caAzcbBKIxtImdflxZ+yHYlfsR+d+3IopgH1OsO1QF7ORazwC3rgjjf1yeYmDjzWham9VZCdYNw4pc/j+v//bsxuh5Qr1vEEvAjYHQtYX6SYDzz0UwA2hE4Gm4p3o0OiIMAs+SW1X/11s/h17/+I2JUzijc4M1HOJwNUF4u0JxrUZYe96xzS/Zbe6fw4PZVPPX4nYBN+OE3fwu7nmMAn9o/jfaoAqqAv33hUQDAZ+YnsOWm+MLeBXzkzDfxx4tNPDU5g184/SQ+v9zAtp3iPrHkebp1+N1HH8H6hQP8/Iln8M2mwoNljd+ZnsWLsw185PSTeKwe4Y++8Ra86d7/L3v/FivbllyHgSPmXCtz730e91WPe6t4ixRJkXqRUtFsSZTcNoFuU2bDchtuyxBk0H/8bAFWG7D9IX/4x1+N/rBhwHADjbZMCI2GDEFtC7RFtWVbLVJyiSqJjxKrRBZZVay673POPfuRmWvNGf0RMWLGyn3qBbQ/fNUJ3HvO2Ttz5VrzEXPEiBERv4t/8lufxj/7+76AH5g/wO+uj/A3f+VH8cfL38KfuHyCv/R/fiNs08/8nyzT+P/yj38c5aJhenvG8kAhD1dc/threHZzARHg//Dm38f/80t/FP/W7/v7WNHwf/36j+Lueo9/9jNfwi++/f3489/7D+Oa/7d3fh8+ffUUX3jvdfzga+/i+T98CgB44/Ip/vl/ZsZ//t4P4Y3LD/GrX/s0fvCNt/Gbv/s6ytWC/+0b/xh/YHfEf3f7cXz+a28CBfi3fvCX8f948v149+YB1uOET7/2FN/48sfxz332V/CFmzfw7m98DNOBbLUx1sc/eMTy4R4Pv2r38/z3dJRDxYNPXuP42w9RvSXg7tpqMF6+3/D0D3dc/vaM3YdWsP70qOL0koenCzDddcw3DXcfmy3T3xNe6p39bDo21FvbG20vmA5Ww1GLdUKKbk8KHF+ZPRFG0XeC+fk6WgiSuXcepT8wGY0sxowx49UqGyyDQXObvz7aYfLSOp08RfM+89SVuUYxIkXO0LWXryIKYBGRZUSm3L7pbh7Jdb3j4X/1q7j+6T+wYdN08hqNzkbqg0uzC8+u8fjvfsOqXVzf2tkSjRfMborfC9bm8hwxO81wq4+jVreBIuhXe7PBqeg56yhq7yY3AqwRwjzbPe0mq99Yq2ndGW3zepVDLwlLhhSxkmmu69Zm5yolYhZRk3E2eVBN1wW4vLRC5D5n1HlqtXI+2tV6TLcOPRyNVeVZ7Mye9ubl+XSjI9Sjn+PHI2S/jxaKPJ/VEyXtbLZ1yPvWJC+IbjKASbCWxRN3ENI6akKVcrkoCO4srViWvJws8sQk0yxTkP0uxoudhkAWE0CpDXiGb/v66IenqR0sQ3AbGsbo4ewJFQQCMNo2dI0puGQAbRqlAgQBFpiWDzYQ941MIJhlhMpMq6RTFM+YFi8KHXWfusZ1lSHyqBvl9Dafw5/ZOp7shp7T71X2O/ss9ZWAhQgYvo/SN25oPRNP5inqO7Ecw8ias8/Kzo2jwPpl1xJZyjJb7TMUN2qh1WnjvikKZhINdS183hx6cWGw5q4F+x0im07MeOjkY39cXPjuAuyoFyZDHxRaxzrK6YQB864s3qlB956NN9cIi0S3Ia8DCcCu7dnScrSesNRZ8T/qhrSYxopF0/tEsbZEjTqdPNYMAMXCfN37Duc2ab0KdD9hulk8jGMH4+lRRbucsF5VzM8W0y4WoFdvuyaCsirWq2r1JbsBxf3TBfWuoe+sHWOfBaeH1idYp27leACviWctCecbeFs4wcUHQL2DaTrhz90tc3Z91KBFUY4UsQP/0+33YX7uoclLWNcPUez3K6YD8PDqiOX9S6xa8Ob+Azy6POJXvvKmfafJ/fDp3RNcrxf42IMb4GJFnUcC2a89eR0/sjvg5onVPPytm4/jsE743PER/sH73xNJMv/N9Rv4oXnF8tqKT148x397/TreWR/jv71+HV+5eRk//vJXAAAv1TtAgf/do69Di+IX3/s9+M9/98fxqek5IMDv37+NF70+d3yEchTI0wltr6HP+8Tlc8j1hB/62Dv4nlpx9dIBN3rChIqugn/+e7+I/9XFc+x3K552K+wNAHfLhJenWzy6OuBL730cT64vsfaCT++eAACe3V3g195+A49evsX7xweYrgVtLfiFb/w+vNsWvH14BHRBvbG5eDgdMf2mlUb62tuvAh34W2//EN56/jg6AlGaUE+K9t4FIIrlyvbf/j3THN68ZYCxruYAmJ7QPje/PVsJp9X20XTXISsszCsWzl4vTd873VpCihagXRRzjg4tHEQt4uFiz5CW1M5vKpgOiul2BbvNyOKJYKpAFSuI70BwuarocxmtTrtapQUvkN0vd2H/ZFlNHnJczLFL54KFw2H9oZkks5+iYkKcAW4D2NYwwoq9j6RDfpa67t3sNtC0g7qfxvWq2yEBMM9m87wYtnrynMl8EDYwajBSwhV6cO8qxsxsAJGUlxJRIgGxuZSqluhKBpa4K8UTUHQbPmW92xz85N9nL8FWyyhrt6yjUw1rDQMjVCxlaBZ1nBnj33amWCKPD2/1Zhocb2KGnJzCLPfJ+o9LSXKBUiyjXflZ2wdWBojay5S0Kg4Mq8kLNnI5PzejOx3gZfMoDfAC6h5ql9M6SgnxXnJIm+0We99oJcXP7w1A+RavjzxoDPYv9AUare2iACcH1xG9pKzgWGSAHaCTJctALEV9FPTOiBDuJU5Ww+m0WEKGpgUC3g43WfPOLxhaCl7OF77tAzMQZP8otrVEnxXsOx3t/HjfFPGmjRu6EmaCU8vIqvT5GgSpkZUm4fWKZ0vHpt3NbhQc8LAvNFtTDSEnlBpISBQbz4tX1nUkMDGBh9pFAi8aIH9WYwe81IKXGtgwwHwmZzlZ2obPhdbN+FKonLLA4dltdgiNjaeJaWRx4UhkuZjD8Av7XgfQ7KMUBvWWbvDKqUX2ZdSCU0W7YFY9jPlbemRqSuuodw3FmZO+r3Fgdu+AEclWO/sdf16a3ZN06h9NM9P2Bl7Xh5NpIeeK6U7Rruzw3r1fUR009j3QZ2Nwdh+umJ/bUDfvh73uC+5eA/puMIjlrgLVDvnpFmhXHS9Pt6PH8K5juRJcH/YQUZweA7/30buYboEfvHgHhz5jLg3TdbH6kBfAr374KXz57uP42vOXAAD/ypuf3+ypP/P6P8BBF+ye2FhcTAuWU8X/+OUfwksXB/zQ/i0AwKNqtRw/9tINfurhW/jCe6/jSx9+HL/+7us4HGd82KwW45cOn0S7UnxltQzx080MvLvHO+0Kfad4pby49eCX7z4OnYC+U8gqaI8a9GbCV5+/jO//3rfiff/r1/4JnvSK9/oJL18ecNQJb7UV/8LHfx2/vbyMf3R8DV9dO9Z3LvGPr1/Hjzz+XeBugqrg+x++i986fMLm/IM9Xn18gzcfPMXTtx8ZcFOBPt3h55/8QTQtkNUyj//v7/4wHtUDpAPTASiLQGdgvZ2B961cjArQq/1XTh3zhwhzuFx4wWyf57ra/us7m9d6MFbx4on1ce6TddRoFyzq7fZE7O+XH5iTYz3XFe3CklisT3TxVoEa4JEtOKmnk7Wj7cxu9UlQjixB4/ag2d4CYD93x4ZJY+GwuXMbhaX9xcSSsCMwmxIabTc6clzA1p081MthjWxmaWoM3Vmd27C3i5flAdA9+oHJE/qOazj3tHWy9FH3lvpxYJQZo369d7Pvfk5EBnJ18EVAJwPoCkuaOdA0YkBGYuhspIEBzgpmLQuLY7PANO02GVnWCPb2vt2vw/sFYIW5owSagt3KqBMfekKvvcszOp0zBph6aoU4ADFctxgYwkkVLcVYU6+KgakaliDRMs+D5St10/SD9wPqU4GRrOkJRTLPm/uPyCDPGLF1FFnmfBEbqA4Ci+eVg+HoVpbBPsvwfIdKxY88aATS4IjYIvWMp0H5+obwpAnruLIiekc75tCWMr/aGoAyMJCHn3G5D61rgC3PgJYNwOnDs9JuTB03FRNNumdzs1SAenasV7RXJk0UF8FmISw9ZAq06e0w04rgtVn2tCWE6GAH2akEcIMJjM44o6agevYxC3xH4sfagi1guD4YPBrVKGrtmWa8PoW8Hk62kIYbp8Mx7o+epHrtrgHyveh6YpJjI3uHH9Y64xxY2GiBrKuxgVON6+rea2GR0nehtCxuhCdnVaNVoMY17BSDsw8aYW6l90yw7gZeLzyE4ddrF5MlyfSOcmoox26MZLHs0Hp9Qrlb/YAsKAfLyOyTl86ZmBij0Ve3eJgaVbB/atcE4H2uFeXYUJaGvreDuF1OaDvxJBhLeti/b6zm5Qd9lAGaFW1v7Ep3xqRXYDrZ869XBkD2z4yFbHvg4gObunbZsX+mKFcr/qff/n5ArLafNM+6/voep7evUO+Af/jepzHdAu+sj9FQ0FUwP7e6gD/+e/8Jbn/nEa7XHUQUbz9/hO+bgI89uMF/c/0Gvt4a/up7P4ovLY+C7fqpx78B3E2ox4KmBZ+ZBIs2/PadMY5L6uH8z7zyFdTa8WMf/yqeLsZU/trXPwUI8PPv/UF836feQb2pqHeAQIEu+JXT5Qut02VdALG6hevLDf/WD/4ydFLUovjDV1/Fy9MtnvQT/sDuiN85fQwA8KMPv4r3l4d40q/wmWnFP3r+PbjrO/y/3v5RlAZ88uI5fv35pzA/PkJV8Ht27+Ll6dbmtwHvP32IT87PUFZBnxTzfsX+KfD+8yu8srsFPGr5wZMH+K2bj6G7jKDeCi7f7bh8q+DqXSZmudzgIZz9A8rRQsPH1xTlBOyfKi6eOpMIQFZAq3UckqYhc9DJOhQdH3tJp0Ux33bsn9N5qf7+juVBRWPFgaWh7+tYv90cqfWBJYGsV1OAoPm2eXIGRnMBT2SR1jE9PwWYWi6ZeAe7Bty2KKxqgfeChxfnj0401WqoRnerrpHFW07WUIB7KK4pLEhu+7VfTP53dxCdpdTJ7UbYLrOtZBsjhM4uZpTQ0HbXgn6xSwkwEiwWPJM6bKki7iEkXCmpB8yUZvKkExa8ru4mA8i5DA7Lx+ToTDjro2wMmzgEM5qiQ8ySDhCYo2wEW7TRa0NU+8g1cFPxcF2bty1kMiyiK5hsrgeL9LUWtlxY25hZ10WCgMll9wKP+fkfIE0MgLKGo0wmdcOyupSNESsvNr6frS5kKREKj/JBp5NFyboVJw/wTiAc7OkgOAILJBD77V4ffdAoA6AIaXzvQ20IfGQQx+IQgez2iamzwtHU98X7MRaGriMTLl7BaA2GSpvpI1gYWgg0uw6mja+zSWSnFBZ3RqkO1nR4lq5RMa9ziaKm24Kqbgjc8Ij31JRaR7Fuz8hTVr6vNTYKYCAyWDFqPLqOAqXUtWzCDYOdZIZ2ZG6pl2YgkOXG5UeTFyg0GPTEYYeXlXkYgFOyYdlkDcoArwxTM7xDjZIbxFGsvHhv1GHYApS7cQ1v28NdojZObV/te/JmdfaQTAGZUUCjzposJpeQNa3L1QBaZH263lEnZyOTh1rWPmq+FUFpiummGSA89QgHlaMVEC5HD6OrWlhOxFhGAephtVIm3oyheuu26cYYg7az9XXxLlkR04yVptg9b6injrIaSJQV6AVWIsV9KN117B8esTwQtGNFvbOQ3vJIIYu4tg3o++5T31A68Kn5Cf72b/4QTm3C7ZsNsho7KCtwu+ywLBOuvLPLZV3wpx5+A7d9hqrgl578HmPKoHinXQIdKK8e8cHzK9zpgs8fX8azwwX+zt0rxtwBePXhLX5sf43yu3v8ycsnuGuuB9p1qChev3qOY59QT3a/APDJ73kf0zdpC/Oltz6B3VMb49/zcdNn1oPg+voCn5kE/+T64/ivPvhD+K+ffxr/4L038V+//yP4jds38JUPX8YXbt/AhIrvvfoA122P6r11v/DuJ/Hk3Uf4kx//TeCu4sN+iZu2x9f9sHvw8ID/z3s/gN0z35XFNHjlwxnvHB5BTtZBBQCePHsAFHghbWOK2x64+5igVwNpywNgfdnCvKLA/ombmkl9zSjaBO+Z3l0+YWuoTyab6JVAskdmdGlq2kRf6lpgtQ2dleo7WNkahnQdj7Rdjb/L2k3HuzarxdqtRI448xi2yN9rYVizNbvrjl4Esqi19FQMlssPW6uJak6t1UVt3r0pTB7K0cPnjGZFcW13yHcT5PaAURXD7Q+dWzKMrP8KBADQuQTrSGDHPtVIgGPDrvmttYtp2ECSA87c8ZqMdETWNokAvlwfSEJGGNGr43xQlnSjzVcgioh7+Da+04Gl5rNDFfU02uYGGCsG1uKQKAZUNX7vv8ud0VI5ok0bR8BrKdv5It7zG2SWFWd/9wXmWekDcNrfeaYC7L4m4/Mkb0pJhArD6842kTQB7OxlRBFjqketY4wznrIAYDC4PA+F4+X/JgPeRx3p7+T10QeNZAu5aFwDp0lEO4qHEqGXCEGE9sF7EMdnoLDkl+6sIsGpRNhBSK+rL8gAiMZ6hQbQvhyhW+wUWG/vX/Y76MUu+gznvsQAQXGHXu6MRicgOisHoG3dlOxhsfMAYc01iGUsKoqktTuTuPZRL8ufSXYsPeOb8LR4DUQ19sxDy6zPpd7U3iglB55efHuUxcH4XPSyTmzf5KVjAhy7x0vGlAyyF+LO3WfEmVXWLzMxtwPl0OAgjH2AToaD7k7oDy+ccRylMeS4miH2/tCad1lJc5cB+uqHrgvxtcBaol2Y/jA65ghQ75ZRDw2IVoE6WTFk3U1olxZ6rseG20/OVnLkZB51u6xj7YgMNnKxBBwmu/TLKTpWWD0888LbZcV83TDdOUOjiGecDqbLOz2q6JMlz1BGUFdFe9BQTwbytQLzc2Oqyu2E9b1L9MnC3bRf9SjYP3MGa1GgC9oeOD29wOkB8Ne+9GMop4IPn19id7Wg74DfObyG3bXihx6/gweXR5zWiq+sih+4fAe/etrjF5/9ANZWUACsL6/41dMV/tHNm9CLbv2oVXApMz5YH2KuDV+8/gQ+98H34t224MZb67Uraz94aDP+6+efxqMrC2PftRnfePIS2h6Yjh1//Qs/hre//ip+6en3v9A8SVH0N4+oB8WDycBte9BQDgV/++5V3Cw7/Auv/Dp+4sGXsRwmPLm+xKFNOJ0mXC/W/u2fv3oPa6+4vdlbX2YAH/vkM/z6zaewe/mAj9VrfPXmFVxKQ98pbm/3WI6mm5YuWJ7t0fY2R8/v9tCJzq4AHdb15QpYrPwj2gXQXlpRj8DhZcF6BTx6dGd9yPeW2LR7rti/V1C6huOhVaBerFsL0PaC+dCxXlVMd92wRBXsro0VBwjO4LUPbV1BYR2IGPVTY1AJPAEC1OZJYs6eOThs+zJ6TNfh5FmCh2n8RL215rFF29E4nL2TjHRNJbZs3+hULRx/8LDtNEEOR4tUuK3rnghiUpEBUAgKl5dnYz/vTmZnqVMMkDGeM2yt10NlrUQrUF6GU88N1ax+pmnFzb5rseRC3c0bkKgXuyFRCjJkEAXq9WuN3UQiBzRsp6xsC7iO0kW28Id9ZTTOgVCcZ5QgEdiEDZQBsqbqAM0iVuKJkbqzcm6YZ0SNZq9FyR7QQQ6ksnoBSEkEePQxayA3LJ3XmFS24OUziJddi8LaRlRpY+FyjDJ3qhHFjOYTHJkUltbJEpCUc9p7NK+we6dDUaO0UPw+5tWfM5Nl6Zz/Tl4ffdCYPRPA2LVSA/mP9n0KmT3TSzC6rmR9inbzFKPJea5kTwbMNxQbi3cXn7bkuQBgHcOYVIpm4V6JC12jg4wXbnVTOtgyXwS2EYyaZiIF7990ksOztYUiY3GW6jUV4aGI7sBpeD1aadQYkm4BosVD+iNhR4cOc1kjAy5CuXEbMjxYwbaeooel7f5kbIzT4jUbS3jQ4gZr9HV10fY8OaOJYShcu7Kpv0b5QGxajPAO1xBbceU1wblheN7ZS2GijB8SxTu/yGoaqo12hiC0OGCeK7pnRLPOYz3awaH71IGH+9v1ldIsHF7vbMzqrbPI7A7jYTwwVObayOVhtTqQYn12y6mhXVhoue0EzSNVFh5X1LsedR2nu+Z9s0fosXp7wrpY2FFWDW2YdKDcVfQZHiK3n5GtLEcDJOz6YfeP0Dr2KqhHQT0C042gfcpqNs7XADrwvY+fAGq1DVUEv/LBG3j96jlUBf/48AZ+7fpT+PvPvg83yw7ru5cWclbBZ6ZnWLVgvljwyavn2F8s+PXTHl/84OM4LhOevvcIh+sd3m0PcTnZuL786Wf4ta98D7oKJul4fnsB2TXMpUGXYu0OJ9MGlpPg7vTisl/7ywU/+trvWj1OdLzTVsz7Bp2Ar9y9io9f3uBx6WgqKIeKUhVdBY8fHHA1jQLjCgBN0C47drsVH99f4/F8wPLeBb6yvIalF/y/P/wh1MeO2O+qAUUodNfRrhTzh8DVfoE0wXQN05kutifLCsuGf2DJSfPFCmkGEssCrM0SslRsvixEbPPfJwtfS1ccXipY9zbHy4XYelo6poOtm7JqFPJeL8rQylagHhraDsCUtYuwEPRlwf6JS4Yo92imezS75gdmSCbsz3JYbP1zP7qdi+SS2ewVdcHKcG+2TaqRbAMA5bgaaGOYt1Yryg9EIly7dF2E+P8IZlZjyy2BhbUIx8GujErwlXSRYLtZ1VR/z51SiDGtpViERIB6YxnabK0qp8XANWsGCuy5yFgCYf/ltJqciLZM1RIR4ea7joRJG/8k74GOqIyHnYMkoa2vZZxJO2uwEMmbBPChM7czk/UKydDGGck90pvrA8c9h40nQHUgH6F4soZie0X8OTbSNPWzX+AJnP7e02kQSt0Z1z7GNoAwk3moN5wzYeQ6WZ4rlFlR77gfOQGjy43PdwqRs7JiFCdXdl+jMwT+79u+PvqgkRvKO4pwYKyzC4HhACviYdbwBBx0SvXC1dFBBgYiq7XcE7JTeeMCrkn0bOjiesme2Eow/d67tugArOqdWfRiFwsq9zOOsARDq/R2+AxkS4M5dY+YusYMilxDJ35vwozf1jbJK2QzxbO/ySCKAymWhRAygnwlppOdbDo9aDfSsWSDVseo6p82v5AxZPa2b345rKPYaxSRZWjFwlpyOI3i5Qor6+PGysr8+HNHViETXhLwBEKzNEJco5sLgGhLaIbOD4Fl9YQUC+kEO0p9koPEdjlFEoqVppDUQszDRk3HHGYA6qyj6SNNTzXdqbcXtNAPgeV0s3ghZCsN1C5rAG9LOACmo5Xk6XPF8rAYAAbQrgzUtsvZCCnP4J6eL9bGjUtrooE3kKCTtW1b9/bz6aA4vFqtHM8NHCQDdQHQTf84HTvqYgCl3sGYyg6Ut3cR8p6fVTysR2gBvvC1T6OsiuV6h998/2P4I699DYtWvPXWq7iYFhxuLcu+tYL//ff9A3zu7k1c1gXL7YwfvfoqptKxkwWtFXzswQ107pBJ8Q+ev4m7ZcLfvnsV77/3CPOHgg8/eIgv/sb3QESha8FXn7wCiELnjnVvALdPiNDx+evR/oh/7uo9KIBfffdT+Pr6GN/38geYHpzw9nuP8dJ8hyvZ4eVSoA9W7OcVn7l6gqvphJ98/EX83Ps/CAD48rsfw+4DS2I5Xu/xpx5+A196+xOoB8EXbz6Jw+0OV9MJf/qNf4T/4+/5ZVtnF0DfKabdinormG8V1+8+gOf++BqxHs/1DuiTmj7xiaKI4vQygGJs8fr1K5vPOwONWgS7GxanN9DJ0jzSgYsPVsy3Bqzr0extWe3fjQlbAiv1dOyoxx4g/PjyjHJquHrXCtGX42qg8/aEejS7Snaz7WQ4kwQi3QCoLD32lXSreqCzOdA6FZNsHFb0XQI/ZPRmy7JWcdCTgIqsfrCz00my1exIY3vY5SlONMhi5VLqoUXUI8CL28UoP8b5eX4awHBdI7oi7FfNSFodQAfdnNhyOI1e98211Ew8rMVsWJyRMiRFCbgJw5oJoIqYvY0KGLT9bs8C9HZPQJx4HpVwwiOKNFfguJgt23m1E1bcoHaTdlldW8qoGMu4xcuf3e2yuPyI1UqCfXMJ26gkkqKRLkOykkPjspG1HJnwGlKrSDLNYfMApHWLPzw6R9BnzHG387V3RMQrruPSAw/Ny3zGFjsryei4ZU5PJiUTP8/V75H38W1eH33Q2Jwd9AHW7hnQQevK8By4IFhdPfe/5ESv6zikS3Xg6TOSwBkAb0dID6oMjUr0mi6QvceFANtwDCmH3i8ZnGkA0pFEYY3KhaLd8IRkbED44illZFHr0LnkmlG6rJEwQ32jztPItKN3x42l2FL9oXNUe34+uxua8PxcfLxhBpzRo65Q97vBEud2TUCARWUYfXWP2MsRxPgwDMRn5DOsawAbYxhHCZ2ojO8GSbJ3x//IDAImTia4dZY5ROjFayp66FpLQfOe0KdXvS6ZG3Nptr6ssYC7AAEAAElEQVQKGYtTM4awafS4xW5Cv5iN2eNhUST65vadAT87+Ey3WhZje8h2cn2eXt5huu3BgK4Xfm+u95Jmh/h0Zwd2n1j6B3GAaxUcXy6RzICpoKyWwCDNusXAw2WlAbtnrnO87lgvDFwcP9Zx+Y7//rmxUvXYUbrV81uuCnoBZgeMh48ZMFkfKJZH3TOsgV9/8kkDnNcW/rx6q0C74HNvfy++cfsYUODr778MubPuLZ94eI1f+vAH8I27l9BV8ODxAd83AbfvXeHt9SXgboq+zH/yU/8E777zMqba8bm3PoPLd5yBu3M2sSj271Xo7YSPv/Yc07UxedOdgaTXLm9eaJ7eff8RDrpid63A8wn/3e/8fjw5XuJ7Hj/F/LTiC+9/EgDw1579AOoTsw0/vH8Lf/qVf4yPlR3e/9orfh9WF1MnRTmJtTUUxfpQcVgn4FTw/vEB3lkfo6KgHgXtsmG6KViPkzF2Fdi/emeM4kMATbA87mgXpnl88PEbtNnsyvEwox7hrKIBx9OVJcBMBws990kw3ZrGb3nUse4L5jvFfAcL/7qudnlYrc/zha2d1ar2oB46Dq+6Le221ua7UTmh3noXJTNwJsvYF2c3xeUZHe2ymq44IgUIFk1dM6iz95QWhB0CO5u4eZe14/jKPKIc1HfP1t4vdM1uP3Q/j7OCmuTTCllWZ0BThYpaLEGO96fqbTw1ABDcMQ1WCe70sk4rgE30hoxaIes3ri3OBqJ4dxzKkFwzHTaMTNU8QY7ryCAXDCaxeHa1S4AgxYC26/Yj65rnEVlIAlqCnHWNkj6hJVcv5eYEAjyixnE36ZLXwsygp6cOJ4XAzIkPz2YOEMwXk37gSaPVO4vVOlrwAhvpmJD5JThdVrC6SoS0C3GAxOcjUudjyc/E95BpLN6xzJN2eP5aK94+MvPdodDWvORQAsFQl5JpZKOP5CjmLEyDhfw2r488aJR56Ab8LwOj1dGHOrKM1H4fA1gKmMqPxBQaOJMBElO4FHAgEgVdJ2Mb+T1kL6O5eQnmDtSHOJsX+o4kWJbIyBsM4HAl4F6Tt8SjzrLWJLaF3X8GqICFKMQysiI7jpo/1SESB0ARchY+6372DGf3EB0cC40g9RlLGwawa5TUwcrNx/C2jz8NJItep2eWw8k8sWUZbCTDIIlBhYfbNekTQzfJllPdvfrEFIehE4lDhgBPWG+RXiBlBmRCD0eQRcDagNOCclotBPdgh+m2DZA7WdsydLWwkc+jFkG9OQ2v3sNg62UFdpOJsA+nENuLL3EI0B5M0MsdytJRTgrdz5ZI4KB3umloF3bIjBZrEu3M6rFZ+PA0sqNpCLXYe8vS0XZwhgemL/WkhNPDEhq706NqIEGB40umIysMYx6KsYnHHuHIcuqmERuPg+XStGzTNTzkLShLcfCqeLg/YboDSvN7OylefnQLPUyYS0e9E6CJhdOvFrxz8xBP7y7w5OYSX37vNfRoHix4bbqG7jrevX2A3cWCN+anAIC70wxdC9ZLRNu8sgLLYTKGbt/w7O4C060BncNrQDkBX3/20gusE1CvC/7H2zfR9sDuqQHyJ9dXeP/wAO1S0Z7v8PcOj/Hx3XO0C8XdYcZfeeuzeCDsvw785Q9+AOUEzG/copwE063gf/PoS5Cq0Kp4/uwS87OCJzeX+PXnVly8LIA0K23z4NEBWi1kezlbAeXpxnqBzw9PkG7AuDV/7irAbUU5WeF2yg8IGI0Ft5qKUEt42T01llpWgii4RtW0h2VRnB4YyzjdDea6LHBm3gBWPbrsgYyRv4TkzKpRqkrWjvn5GmYRsHVeDwbwuhfablcz+uUcCTAqw8YCsPqLiyXBFU9Ki37ToSXU7R4RMTtISQlttWv51ssSURHaSqtmwEL9suknD8HQ1dd0bC+rMYJkoFJSUAC/aXsGEhDzfnV2jWX0rtaRBOg2M+o9ShnRKw+7krmMEkJsXUhNuUd19GJGhFsZJfGxtjOgjntKtSaj1aCqt+VNSTokV/hixCxC7BLvh8JIoeNiia08b/PYKAy4VWYuuzQrEmCxcRhCM+r9rUc2swYAVY/wiGCU83PmO0B+5CXUcd84by+IwCFoDergHxAnuLjGnWQiSxq6RTpNFhFVlslj9DEw0rd+Td/+Lf8Lf9H7IA27rsBkICqoW2pPGIb0uorhHQls4XhGsLhXFBlsDrYgnh0tHgr1TjHCPtatGXt2OFkIGBjXo3dI7wwI2jk8Fk0/4zMRXLneUGuB3B4BEZSbI9DbEDi7PjEEsxFyJij230OB2wP06gLitSCtCf0EuTsaw1oLxJeP6WxWoPZRs8u9aAHMEB6XTbaz6TQ7MBVjf4+LgVzVMJp9cqZy8hC2iG94lhHQ4bUC5nntJ8jtcWTuFY6bgVuhJ9Z1eNrLYpuvNQtPzRMe/+2vmjH17ggRsjq1wZI6kMacElX81R7sMD29DdY0Cvt6kfNexHtDi3dwmNAuJkxPbuweLnZW5kOA+ekxWE3AjOXyaMb8fDE24uQZh35A8dp9rtC5oN6taPuKsnR0P+SkK9q+Yp4F+2cLTg8nvPJrHaeHFRfvHT2c3XF8dYf51pjG3WXBfG39rS3pwVjQqw8mXLxjhury73/FyvPsC9aPF1w8sYSCaWc6tPUzgvm5gaPLk2K+U8grBVdfOeH48oypAPVSsH+vYd4J1r2geEJNnwEVwWWxUjz7BTh+smH3XsVOgJd+6H2sv/Ya1ivF9KEB7pubjrl9iBsF5tNzlMsOXDToWlBuC+rHj5B39nj4+h2Wr17hrR/7Kva/8il86U5x8VvfALpgasB7P3qD6Xe+hsvHByxfv0KfFdNrR7R396h3gumLsHD+hx2YG+Spz90rK+TJhPYoHTrp1XfAr731BuZLQTkB04cF7ZWO/Re/ivW4w/p8h7//jx7gn/0DX8D8m8a4vPH6E/yl33yEf+Vj/xDTl97Ax5av44N3PwF9TzHdTLh4R/B3yw5vrl/AW8urkC6Y7hT44tdw83SPf/CDz3HxD7+G8hjQCnx//Tr+8ddfx/y1gttlwe7d5wYqO3B8u+HR1yzB6hP1Xfzub38MOAou31U8+F0LvZfV5mN5KLj4QFGaFfee7hTz8xXLZ3Z4cGcyCRTTsC4PJ+yfnLA+mHB6VLB73tHftmSr3QmYb2w9tU9NePA7J5weT5ivvQTUsRt7f1ZXT6tgvZgw3yxo+2oZz61jfbwP5txK61gJKQCRoS3dQLOoWlcXkQAU7cHOgOhpxfTxS+zfucXy8iXmJ7dAtWQ1S3xp5oi77Vkf7624/lRQbo7Q2aIE9fkdpq88wuU7B6xXM6bnR0TY2GunyuE0JCm+9+W4mL3ZWbkfBfD4F3/XMoDVbGrfT2ZXVnO+zdEd4fmwU7VGmJaRJNpdnch0qXezSYlE7FhDG94BJhjFWdC91iTBT5wJMJstYjZ9GWF2cYmV/dr15ejmGPvPwn3kmZ5D5XXYNfp+Bkxh758q0Br65R7luIRdzy+dBmgFE1ZgAFZlSqSBPwcjfc7iafeyPZ7kOhJirftYuT4EuyiUsTGZtlitR23qZ+Ygi3RZrDqLEwwGTl0StnhBb3ECTDAkBfy8k0hMnJF5Mo2tdgCOGUSBlsD3t3h95JnGqLWYtQ29j0SXTMm6p0V9ooVqJSVFuMcXqfH2igUdzJhsM66SF8NwOYDBmils8SSvaXit2Gx46X0r7q3V6ja1FtpIhtmZHCMEy2fPG3UWqbHhxnWvCXkNlbH5g23sySDxvaTlo7WVDmCryZC4HpTgmlnNwqxvsoXi2YbHJcrysPuDeEsqnYqBxdY9PFvj+yx5B+GhWRgq0f0+l7ozMGfhqhzK9jmYioWNqVOKkL79nkVtu4eYevW5zOEZuKi9dZSlGdgDXAvpoIIeO5yxce+4zy5tYGFw9ZIZ1DF63TgVQfFxKGuPOm4s/yON3V5WK3TsTEE9maG3Mjji4TxncBgOPLpny4xNZ4N21xqJMKgjhF0WeF1I2KHkRlw6UE4av7cOIcUTZOx7dBK02dlI3z/HV+3vvTpAu1OUm4LTqw2lAW9/+AjtStEvTW9XVoXO6uFTsbqJq6A8myBVMd0KllNFPQim0jHdKSbp0Kr43Q9fQp+BPnkmOwR1v+Jwu0N72bR066lCVmNdCbLe/OT7kJvJ9JcngTbrfFJuX2xq61EwvzuhXdjY754AuhQsreJHX/06HnxNIE3wjdPL0Enx8U88w7vXD3HzlUf429c/CFmBSTpKVci7O3dwBYc24+1nj9B3inKwsVyf7AEBnrUr9Grgfb4WPK53KAcLLfdrW79s1Td/WGOdv3v3APVuJCIZ06ohMyEDuFzae9YLWwv7ZxYuJnNuheftsqdH9pflqoDZ0PWkqAfbZ/ONopBBh4Ws69EYsE23llQipu2qsZNus9QjePX6kMCNRwtWZ7TF17PvZZ2430zXSB3edGdsuRXCt+8uSx/6PAy7vl6aTVs9S1vWlkLitu8KGx5Udz4DCCEwElbvFLMzGYzVXx1hY03JhcXfC+9URccXSdcJIErbUBZkH04EBTASN5jw4nZwVL1Q03aSXdzNdg7NUzjEYS+B0VLVAWlmQHn2iWc5R1esuQw9H8Oz1eoTh26aZxOTTIqxg2Yk7bxVgcnOaD+ZNJPYNdbTlEgC1ZQ4Aiu5Rq07zw5VIGon+jmaWDt1TNH3qQQP5xfqw0184bbciQsUB4I596CUUaOxt8h7iFB5nVyK5mWAgrzy+fJQtgFQB6aKTdLSt3t95EFjTCD1hFM1ndo0h2A3gJkzcUEBM3RMb4aLhYg/0uktNBCMo28+7T10bVwQBu5sIdOAsE2ecLJZQ9F1H9HRwNvNBfXuAGwk9WhU2s/1+QKwuB5TKfDlGFGLQt2gjPfaZnFG7HQayUMguHXtSGg40thT0DvP4CYb/Zd3scEjRCEYhgNujHmvtYT+CF72Bwy5A3bNBMLlxMxe+5ksXpA1KHt77kgmWlqEg6zO2WztwFwknWUHoF4QiHUiRwsTUVwdxrtZN4PxfveiPUtdjoMxqQ4iKeDuc7GEmNZRDys615VYq7/63DzX9nAfh5bpL+0e2961LQqUU3Pdms9TN0aIrdvYbq3t7HPTgaVEbA21i4Ldh5at22eB9I5ytLD1fDPCNW1X0XbWkvDig47j44LTg4JyJBC28i2lWahZi+D0cgKdYiFfANFthLo5PDKgCwBagPnWHIK6b1ivFOXtHdaHHbKI9bKeBPDuJrvnBsr4n9xWaAF2uxXtUrH0gtNLwH/75A9guhWsN9barl8YqP3C9etoxwq5qfhjn/4t9BnY7xf03Tjg61Hx1bdfw3Qt0L2HZp9VyIPVQuMveK2PbF2qGICejop6VzDXhs+/+z3GqD5TvHX7GLsHC/7wo69impqBZml4/fvex8N6AN6foUUhqyWuvH+4Qnl7Z7agAu0SKEfB/gPB0+VydP9pwFfvXsHVJ26hRbB/X7C+vOL0yMDb/Ny0pgBwd7P38LCNyXTbcXzZMu1Pj+x7xf3W40sS+3k6dGsxuDeNY69W45FAsx6NrazuQFSXQ0gHpltrp6kyWta1C2PzOiUdgNnF44p6txrQ8Ax/7CZzhuYSBzIE3trPrtGu6CANBm3jwCd71namPYy+9tzXDuRaCkfTyS3ekUV3rpssxcBnLSi3S4SDw444MBvOq0bhcNt/ZfjzIpH9HE54Z5UNIDqIUHO5rJGZHQBV7X4HcLBxjlCqO6Ho3aRF3cqtydLMbnokarRJhIf6ewCa0bYVw95nmREBGOfAQ7eyetKowhgyJqeuq9m7+LONTiqtQZbFM7b9vI5Qbx/PHgQGgZT9nMXDVQ1oxvunyfGAl+xzuVWUbCsykl98bClHq7eLSdtiYhxPNGvSgVIiISeIgEhstQLn4iDSjn4706V6kq63RCZIjXOJkrLC7nXWmGS0U/Z7SOzkt3v9UxCeBsg0ksYVwMPIwMiwdaC0n+33kUxiFC67h2zBkRteF5eGhxKeBJyCd++taySdEMxKR4QjxbUSuq6W4VQLpJWxuOPasrkXFvPU4OV940/TRsco05w8Dmw2bQDr0PNJALrxvOLMq2+kEwZzR3ZxPQ0jSIEzWd5OL9A+E7oVzhM9QAfnpNX7XFDIbu1myF0GzcV6IV/tICLDc/fnlubZjYcjcLEbwJj3lLQl6honKNB+8NN2QBWxLEsPXaGZxpP6p361s84vNNq1oh9O6C9fQZ4f0F66NDbj+QGsoakKLI/3mJ/cGYg8rWgvX1otxbuT1dlUAFcTcGjQ6zsD2VUgNydjES4m4OZkBudighxWY2om0w8VwLObK+TdW+BixvH1PfbPGnBVgN0B826y5zqswOMdygd3mF+5wrQcrGB4EUwClKuG3VTQHwHrQwshyvUC2VvrQ50F9aZBv/IW8PqrmB0AahXUh4LdjaKKhRbny4r5WrG+IZCTYvdhx3xR0T7ToY8L5g86loeCBlc7zDbv03WHvNwAnQz0rQZy56uC5UHD5bOC0yeBctVR31/QqwIPBVMBcAXoQ1d/POyot6blKxOwTBVlN+MkE2bM+LBV4LUddivQrhRlVkyl4I2X38PT0x775xN+c/1e1PkSr71yi/feucTymkLuBLsPFGUHlEtBqQo8EPRHHbJcYH2QUpLTqxwtNFoW8fC7Ah1Yp4fA6QplD+gVcKsTuhZ8fvlhHI+PMD0ouJ5egVbBs6lglkusV8DFE6unuFRB3e+xlBv0WVFWwSwXKDPwXvsYpvkiQN7brnO8uLRC2qUo8KmGemvHQ3sAyARMDaiP9wjCZ22ojyfsloblcYXOatK6GeivAfPXgdK8VukD79M7dUx3K6bHO0BXlJcn7J+sVv7pgYW0y9whFwvwcGfE2GNAHxVMp1v0/YR2NaF8cIfpam+O9ysO+lzuIg93loldYP3SX9kZiLx4gPbaA9SnB0wPdigXFgKWBxPQAYFrLpcOVLFQ7PWddfjycG99dIH+GiI8TtBamtu8ywly6ugC4OULrJ80DXJnDVRnLEspbluaFeg+mdOsu8m00rWak+7hbr1w6c6pQfYTWleUt95F//5P20JqzeyCd8+CwFsK2tmlpUC+8d6oqcjoWbfPhkNNkCWAtmWExhVb8mVpHhWxaBOrbWByCZHbQgPDEmdQnF+ZYHAZETWUADzKVwIs6jqyp5U9tamtdNCn62Js324K0G6Aj+edJ/3tjRGN0nQkf3iu+jkkZEQFdm6hAMcTRKs9QmgnEc+qO0b2kq5wv4vM+MyKgyFuwJ5/HWeSJAJntCu2exMv+6QQPwJTtM9lWHo8WQSv95FfIXBpmj9n7xbmdq9XdjNw+0IztbVZ3/4t/wt/KUwPUMQoZGoFmKQR5VRsM7C2nzjdi1JSLSoDK6SsrW1gHZ5JiGVtEUfYmqV+iPV2MzBNXk6mhBjVFqsvZLKI0YbOF5vCQy5OSbP+I2tHejYaS8dsyrF4qYIApIEFJfpDRyg99ZPWPYv1jeWi0XVBRx2p02ggP0LSGAk5pNnbYAAjvOSaTKgZTjCE42yXrO4N9Z5aBhLUdtfkeH00QdRNVM9ylnmOe9b9zlgAguLWoZcsGq5mCCvZTzN4I6sb6JczcvIIhd5kZXWeouhvvV3CKEaIR4Dp+hQhCa3FwOjBEmDMWfAElHWws31fAozX65PXdevoszjL2axG3Gk1O3dqqLeu5Vwart4+YTo0YwarlRSpnnXZHZzVwyjrVBYrbGyaHtMwnh57/cZdNaaninV38aVRjlY3syzWA3u+sXAlxH43X1tm9e65RmmW/ROrzScKLFcCWS37tu2NXbp837rR7L4+Y7oRoAH1ABxeLpAVduA3YLoVTNcFxZnKOsoY2rLbm2aw76ybyHQARDxUqoLTqx39YJnE68Nu31UUh9c7Xt89Q3k+oV0CTQu0KL7+3itYHinqnaB9zBIuLt4TlCPw0mvXVkbo4QK90JFdfvaqt+Lhe2PV5mvbP7dPL7F7bs/VZ0CvJ8zvV7z/3iPIYuHfl+Y7XHitRq1Af2S1E3cfAuv1DusVrOD5Vcf6sDnDBpzuZiwPAPFSOOiCemtzXO8sZD69Y8kRyxVQFwsTT3dA9ZI5s0sS6tFKPO0/NJbz9pMWqp+vBdNds8L0qpjuLNFJq2mVd8/NibDe1B0owP5Zi7I7ltFsoEb93FeXeixX7uQR6LD2qQDtcrbEldY9bNxxeuAHaimoh4b1wQ5gb/ZiyVz2XjsHRL3NJov0O1DSqVo0QDxJxSsRaGXSiljm9myt/vrszNVU0C6swD4i29YKjxtTpQMgnFavl1ijjJdFL+w/K/fSEnEAs3uh7WQ5GImoBzxRIsK4PF9yVzKClFohx5PZNyYLzhXllBKK1mY6Smr8GOVh9jgAOThwpBSM98v350oYbWTEMyNYqodomYRYRkh+01uaAKwWyDRDKYNJ2sQgXHiOMtwdoLKMsLnCzgovS6M7y4CntIAJR2TtjHU9ge0U40WGkt3glhTW9rPQAJ+fL11HCL4r9LSkZFy/3yC44M1C1hEhXFLLXLKVZE6L6R+JZ8xg+POvK3RdrC/1d/j6yING5URw0QIBjJS9MosMADUVA3TuwUT2Eid5mmxB70YWqsyTAbI5ZT4VGQBKXbtAFo/gxJNrolwLF6KUSPYI8BMajL7NnuOz5EwswBYas56d9lZmrDFzmR4WNTW9R3FSZVmdHKpHuvfIgG4WcnfBrQ+sC8KTHgMOstnn041UZwY7EB6dnEbpBd3N0MlD+B6iEuoQHfBJ6wG4kDvduORA2ijjAx3lHCJMXARtdqPtNb76ro4NdlbWQFIoVai/cemBuA6I4fY+M6tQjC3wDHGGdMguUP8o3Ypux7XJqEIDcFoG/RqGrJx0aF3diHayAQK0hxcRNmJJnXZh4vdeDByXRd0DH0Cd+siy2D7R6uVlGiBd7VAsI8wMIATwWk1zVppivrXwjHRrQ8j+120n1mpwVUy3inqnqIvVbtQK9MnAQt9ZDc960tDaMcva1joCtJejhabnG7GC0g5y+gT0vfVBrgcrgr08BHoXAzlvTZCdIRTpAGYP6xVg937BP/zwTSufswJPn1+iHgy8WrY4MH9jcjBtwOzTD54CAiw3M7BarcIXvbprGaUBpQPrg4rpjigJmA7dgLHa/aNbdvTpZcVvPXsNX3nyCj6zfx/THTDNHevVIFbQYR1uAEjzuVusMDfXr2UbiztBdu/lZNnTVh/V53oS1IMlsZQVKRHMxna+bpivbWzDOXbpg7UJHJ1gdBJzbrqvnblaEfim/h4/OAXQaiCxHtVlEhVtL7Ge+y61N+0dZe2x5wik5rsR3jXbw/3La6QOL17EPk5GhSUWRrTE96XbL7ba7DsLJ5fWLSlGNcpisXSW2VoHEq1DGNJ03XdPoW31gz/0beu66frCjjDUiZqmWQOARLvWqXr92dUc2eS4w88kLWXIhlyfGAQJk27KkE+ZNrykMjA+JinsKy4TMjKjDpsYuQUaxIc68LGyOTzDfL5y2DTW9SBZNIe0SfR4iHnU3/VIIKVartMcQFsCPAMwAJUTd1iihsB6A4ILUEcYn3Uro/GGsMxZSjZVxDgpAWA34y5TNdterPRfTjIKoJwifxHRdDAJ7ZDdbpvIG4Pn12IJogQihazwd/D6yINGcYZt0+EDsIW923nZGV/4BFNRlmboE0j3Ajp6aTqA0mWN4tFRY7Aao4dpslpPBJiRco8wGDpZmI/0P5ukC6v6FxnZT7R3LjjWtY0NP0+IQqKAARiGCRzwaq3Qqwu7SB4PbtZqm0KYBcdQAI1AMKJeQod6RoF5xTm1HybeJviLMHok4JQBup3NDW/SQ9x9V61jiLOuEUKgEasjRKFTNeDOTdi9SPfSInNb9/P4/gzUOQb+8wjHADZ2x8X0hxDLtm7sU5sytxkmKCXE7dHSC9lYIAydATE/pNzo1lOLumpyOEUCFdk8FTE5w9IiASgyAZ3V7Lux3oszDnJqUdZnvSiAM5NkQNuuYro5eaWAbteA3avVrlPsn5iWEQDmW2tJxixqACYPcABXj82SDAo2GjGO8XzTN63fImoyC3bPjImUZgxlaVYUvFcDhEyE2T9TyLFgOih21wYqp1sDd9OtsY27Z8DxVYUsBqjqEUBVrJeAfDhjvjHgo6cCTB3TDVCnjnICdu9WLI+ApzeX/p2A3FUDPHfF6k4uiD7TrMv4xQ8+ienWvme6FtTbtNfSS52lna8tnEqdocU3gfXSmYOHDfv3rbf3emUJPvjKBfBshw/aQ+w+7Hh0ebBC3EerXVlW4Pq9BxaC7GL1DxuwPLei6H1ClKphwfT9046LJ4rdjc1xPQK9CqaD7X9xLayBPA95qTlH853ral2Dyr8DCGZfJ2MaoXBwZXajOGhk6z6dqidJdUwH6z7EtV9O6kycXavtmLggnvVvTm330Or8fLWC2TAgW1j42hMtppvVrrv06A7DhAmWw9HZ92Nr3kEJ7iQ6s353DNanzxXSLAubSTL11AAdGna9mNEYZaG97zp0crQ/rZsdFzH2bqKjPpwmOtGBLtS7jc1bUsKSDOfhfIq9NyJVdG7JMELtXOr8s1v1DADscENHOWxzOBMkGhDO8KYqSNw3LPzs9xr3xqQQSrJ8vuLf/GxmLGux5yFr5rZWUjF0MDEIyf4TeDoLKynLPBx3nnMQoNRNH+gI22cZl8I60CRWU9N5HkSM6ujasq4jDC0YMrCe7oEgG0Nzqr3H5ySyuQfTCD+3NvWoue6ANL7f2esjDxrhuoEoiqqIYplaC9hfWQWDwgeGMFedHasWAon+lz6JUQspRNQYm54ecLoVXU1fomvbdAaQ42mwehYbQLSQAkb4QhCLqBxO5pn4ghZVrzFVQXEzgGC0oCYgDobxdIrvt+xq3zi1DsDMBU69JsGsJ8BEWJsZy4ABcZEoczCYWqPdY7O0Hu28bHM788vklc6wc4vfbwTUDJ+HVwUzaq1FiDt0Nz6O4vOjrt0RF4p3CuX98Cmn5tnICM+UYZhcr7LcnYbHFoDQgROzn2ngogwFkibIHl6W7tnI6oyBhsFSF1iXEz0GjK4GS0M5jeez3xc7rPidYewsPMfi4SzKm9chFJEVXQ8NuaSGeOIMgWGvEq3fJC/z4k4EM0oFJg1Qz87uira375mOXqdvtezltkNkF9aTelINDalgOtgQWY9rAxq7pwJ0Y820GKu3u7bvnq+tQPj+6ehMQlDbLzqmWwNt0x0gi913uwDaqcZ76wHYzStktXu6eM/GZ7pBANu2Q/TgriegP9lhOij271TUE6ATcKf3Q0DllDqmFAu5T7cKaVaCp13YvenJ1ls9KupRgGJgfP4Q+PUnrwMAnr79CNMNLNS/GpitR4DsabtSB82cTwetj1cvJA2wJE6fBlPLbGedgLavUXS6XUzBBvZJQibALkTGwBlrzzqOWiyrOvosX3r4dmd7qiyKcmygPIVjyuLescR9LU53lgjRdi4BcgcnXnNFvTmiHD35o2CwK61jen5yRjzZmqxLd4e4XVldRhw9cWVnUYPSTIZBJ3rTVxowO0YnkeyniLOswy4PpohSFnMM+4P9COXSsfYsagC2PzkmSRMXe17dvhBoVe/iBYn9GclxgMuWBihTl1hF+FoxpEfdbROlUmGL4SHzFEEikKyuf4Rr48ly0m4UJjt2P6/amAeCT5EBftWjNWGDzfNicgmA6FI2SLcB7kao2a9FnSBZy5QUg5CNYYTZ2eOa9pc6SWcZlVEij1aF1G1tBvpIMvgaIDkEOMgXGddwZpoZ1MQJAKJ7nXJMGBVUk8kRaEbklL/3ZCHdsJLf+vVPAWjEQOoMhRJAdN16IcBocRSiWNtI2nuqK5WMAuD9KC20ybAN9SIGLox2ZmZTbPiaFhsQGgVlGPSUNh61C9xoHhZVT/qwBeaeBgFcc/0fveXWDORRzOy0evQ2LVs2diQD6QjH7FKXA198zMozHUgfv9PhOVPjKdGZQIDVRPE6VUv+KOItpVJZoW7gOK7XjVm1UAbGPCpMAM05YfjF55IeM8fdGNA+PFeCw3kyMf3RsrMD/K+rh7b8UBGGMyRC+7xv3VkCEgsGx3xAx/xR4+laHtPRGltcDusY1zgwrFQJDed5tltuT9auJnsvDAyvFzXe0y4q0E0zyPnVuXhHDmNq287mqF1U9H21Q3/tASapGy2LPW+9G0C+76yItziAswxo+5xOBfVgTM/psWD3YYtSJ7IaoJxv1IqLi4VSL556FnwxUChdHTB2NLYiPDKcLQF+1gvTRq6X9v1agOWhMZXHVxRyqEC1fxOw1TtxQAqUqaPtPay9A+Zq/aBZdNqYVGM7GfZtO2D3vFsHngdjfuZrxe654lLu958uK1BODpydPUUB6stHtAtgvTAtZrlYsV7BNKWXinJbsT5UtAtgP604vlxQjgaK+iTos/2unATTTUE5iYFrABfvORg9mNbycn8yMHcJb+EnWC+GjYSOUjPGnCNqfhpINwCvk0kPrAC2gejmfcZHZyFg97wFG16azU89NGNVVb3Hs69ZAeZr2k3THtYFYHkudjEp3le5NB2Zvl0tMaRWs007S3jpXrNU3RGW1exbZGmzqLX3oQ59YOueZOFOp4csy9G1ZZM5a+2iDr00gaCXvGGyI5Z1RFYo80nSGuvSVKy2XzB/tIk99lvYZi8/ZvUHZ6/KYPdA4EdnedPC1DWE1HYz9K5TtVaA6t/L0DIjQQuJA8UmOZO32VNnL+9nTbJBpzpC3QSlvrZyObkIeVPWlTV+gIWJvRyQLIs9W2teisbHqEgwmMxn0NwKGBpEjCpGboA/q9Lpd/AYGdpiEqEN0KpWo5FFs0UwGogQtKcQvnarEc1KGoBGh7molVm9VrHL1mzuu9eI9j1ay6hq0riGJABmyOR6j5rQfC6pBrRFMM6ab/P6yINGVQB1MsDGzGVB0hxYKn4YB1LX7h0JDYcjfbYGDI/R92N8WdrM7Okru3kwUb5Axb2nqLMFA5/qizZqIaobGKRN2Z1Cn71mIcsTdA0AE62HeD8OanJrQL6i9Az1La7rs3GQcd+qYAHs7K1zw3Mg1I2qpmQakJqPGlhAhNJ1hKWN6fIyRR6GiT7TqmbIuAkZCue4L2Qq/cDxUHR0XphsXOVwGiV7vEVVdDTx3rOmrVyibI3ud+hXew/BGNAx48tEqR7XZI9nsqKydvT95AV7R7cE02S68WUPa87lqY0koVIsUYZj6fc5mHF1jWFaE61HmZKy+DiLhYxRJcKS2ehZG8OGemwoPAjUS/y4ZrQeV2cdCGJ9HU/pMFG13tSTgYr1yr67T2LA63LG7ql9r7FO9mxlVetQIwbWplsH/sV1Y7MBlO5AZL6xCMF0pzi84t+vcC0ZtZYIJlHdzu6fGAuHVcb7+VoLegX6yYF+AXRStO7dbdRsQ3ftYj0ppoN9R2zRKpDqbRir/a5X4KT3hY1tZ3aiHpslvBS7flsr6gFoFwpZgX6yBJ12AcgqmK/tT63Ah7eXkG4JMFqMWZWrZlpIIMraaIUlthw71odWSqfNwOE4ozTg9PEW2er1OBKV2s72c1ns+Zuzh8uVoC5JiyimW1weGMgpxxaSCjpGZK4JCuvJw93OyC0Pp2AuLbyt4cirt6ispx6sG0tY9dn2YHe5h4X2EOtelsVKVnXvxjIZwJbWUVpHu9pZPUiCJI9yYG1o3snEbJt/r2vCsnaShwE7KEVLTweTlNBEKBbw9n/8vP3VntvB3DzqxwKI591EsGg7NxpoAN3sCbuHaQpBC8Gimv44Put7e1Pb1+8Dna0Sa5AMIc/x79zUfMyVM6YaZ47JfGDRNQIiIBKe8qFq53QfZ0Y+j8S6tkTo20O9wcRlwiVC0C0YUaFtpSTAgbNuwtuumZ+q6UrZbYWsq58V0YFsN98DZjGxkGBpI5nWZWC6sMSdjrNcNcYqkmGkAKVGsXWGySn9suf1s7gNuz+myPcDI2fU1SsGuPw2r488aBQejNnr437LWgGGLJmlBK/rFNoDBLpXXkAk6OAAW30c7MKJ4GYkLe/UNRa2p1pNl0AGKTxL+N7xDTjV8Gbsdxog1Ji74fmMivM6MsgirO7/6YhtqAt8hd4PtRdINctEIgEmxi3ZLgDGqM7TCFcWGYZ1Awy9GOydZ+olozU8OP/3yQA/Q+FhQLkp+Exk+boJuOW0uEHwQ+zu5N1TymihCBibeWr2s2aFhM3r91AsQ8HMWvSwsLQGOTobHFlpGt6x6adaGB7AwnsmR1jGvROAH5fQiaEI+n4UKtddDeAmS4sQmM7uaa+um/K11y4HE8sxs1B2Q5uLATIvRVVvTpivV8vo9hJHbVfHmHqtRltrNl5RW/BoAJ7PJ56VKqvpJrUKds8GS8Uw93xnnTja3lgmUWfIHJhBLCzaPGO8Hr1d4aEZGycGQC3c2rE88qLfvm/6jqFcYHlgHWVQFG22NnXTLXD5DWuLt+5toOZrALsG6cDFWw4Suz3n3dHqNh5fsfvrk7Gb62WJMGqfMBjj1bRyxRN7poPid9t9prHvDPQeXzWdIbWAejQWrp4MGO7fsXI4/aJbXUPXIPZZgecTloeWfUxZAK6rgcJLtUznRT28nvYPYElNT2dMt8Drr32I9Qqe9WvsqagnJhW+X2NdLY8Fp4di8ohi83r5ngNPEawPprifslgppZ3X9OxzwelRRTl1q1Wotpbq0Z13Yo/DGrUVyThPzxfbn7XYflpa1GUsUbB7tXv1SgTmsNpzcY7k6OzccfW6ixJOGDzDWfdeML3459rY+5vSXUAQDeW0xn4Le7x2L30jwwF2tlKpNaslHK0IZ98dwX7QaKk4eNL5hQ3u3e7X9Ww6u/xkpi7dgPdoQQs7ayib8fI8obfe7TbhVNQarWyDPeVZyIgS72o1nWg8q3oCIhNtXIfHvveDmfXvdqLBCpNPgxkFoqYsRII9BNs+TmbvtQ3iI65b7ExnktHYhDrmQ7uHjW0uZWZkzcPWHA8+V2vbpJo4F3vSW2rI2iIZyMPfup8iTB9JRs4WapBV2ITAdV0965n23ssFujTAgKxHNiuLjvt9BZpVJ6/IqOgWeH6L10ceNKoDxfA64GFSJrz4AQUvEpr1iEKPBgiApasj/9aicKcqvLQBvVSflGCJWiyIWKxuuKnnkDoF2IBrHzZZxaT2eT8RhvaF0hwE8HbnGpsgKuxzEYdnPICO9D6yxv07Awik0jNRPJQbOANYekmnoZscoQT3tGux4rXegUUIEgE37EmL0qibrMmjS+AsvhfRUSazq+qlhTYJPxzHpI/CVBF9sMVCnAbG/OeaNHu8R85zLQakah2lgDi8x1OsGzKJpt3yzjNkNqpdU0ux+ogeyipHP5yo4+R6UvVkAo1MSctgt5CaJbfYNak/lK4GJLva+XRs6BfmhLRLz5quxR0EgAxErLfjCfW2eWaqP5OD17I0Z0wAOS3bDiGq6DsynhYOZQ9frWQFFevVZGFkAY6vMOmgmwbSDwaySG0vOD2yVoyHV4qDBWPA6hEGWtQOegLHsijKXYlM6gAC1cO4TN64rd7NxTOIKyBXDboU1ANMs6dAWZmM03F8xUDpfOOASwGoARDrTW0L4ldu38T5qzxYgGJhaAO9ds+Y1LK7q7GLZPmm64L5ua+vFdHxZn1orR7L0dZYPRgbiWZSBMCSgZaHiH7gy5UXib+ze3zn+UNMt/Z+ajXF9YzSya7aZ9quoM/G9tIR0MnmZ/ec5XXsGlrFO7QAocETD+13NTlI984vXUdymDtGnUXql9V/x3Cfh8KnYiVhagVL6aCYLMM6G8lgIdeO+bZZuRwSCkWwPqjexMDBVNgXbz/Ybe/TnkSkyrXxcW74urWyU4lN9ChEn0vo5+Xk+xuabMLoCR3ZvHMZkZqm204mYqF8AjJZm+19T3ijtg4i0Itclnk48SG7yY6owJ13f6+PVdtP4UyGPXSpTZALxTqTWGmh4TCPELbZMfEIhYHwwZKqiAMdPyM5LgThOYLGhJSpxlkaek5IEDnRLQ0Yukiet4IRQhYZ3eJ47sHO/Sj0TQAckZjxTLrmqGCHZU1n0OdOCZlwzhHPCX7fyRNva8p0BsafnNPM7Ca8oDxTyWhTL6kY57/naWzKD30Hr488aBQvzRADo75AqFdwdB7g0vUhcE1AAJLCRen1jsKrcb1i79tm5Ll14TT0I6TQob4pBfBVa+8la5YWQy70yYSM0EgkQJfrRIXhITDxRcMMa4ksLGyuI707Y4lRI5J7gK2ZsnCX393aZtFZzcQ2ipzu5vBamYlcPCMPEPPsRYZ2ht43vSLY/eiVe9IRgtEIt4QR5EZpLbQzoQ9kKIJZwwTUcc991IJl79d4XonesGZcp9SRpltJHY4nwao6gPexmW/XMIJRU/O4hsGKLjYeoohermR4W0e73EWnGLJGxia0YHYPr5oxZocK054ZQO/8DNeb/76nzEydnAU8NixX9hwRelIPSbLbxlTQ/UDSaUK5XYz5PDbUQ7e6kM2ysSM85oxVJJ4pPKnGAFtd/J4qTGtWDJipuK5vjwAeWgXTjYWb+mwaQNZF3D1vmI6K9cIAZbQqPFgYF2Lvn24tCWe+tsSUPts97J4B2gSXX6thLaeDYvchMN/ady8v9QBYzFyenvlabM5iK/CYKdbp1U6mMbXOJxLJKTgVlCNw8T4wP4eXGzKGtDRFnwxMoiDqUpbTAIVlse/efWiaSgCQy4Z69LE+WnvDPgnmG1+2twNUGKAeIFErTI+6WIb68kBQFvEs7Y75tmO9AOrdGiFrk0cgSkhNd0A9rJZBPVvI1pyZyXSzJ9c6psQMAFgvircMnGxeqTebC8ph8QLz1eqnVrF6porohNQuZqBW1INVG8ia7F4NkO2eu5wnn4gMP7vEhBUbohBz0sqbvtGzrVNUKcKMBIACIwS8ugJBqkUZtg5w2KEi0Is9qAHUOmxyZyvRWiyLuYgl560WodFkf+EsLJbRAUQ3Z5zvRUYyMsBJ4V5ZVsjdKcLCpml38CsA62maXZrGuZqIBbJe4hEvJiCGVpAkweyJRTzncqTMWdaodSyw8cnl8Fx+NsgfDSBrQDmHZHOposmBqNv+OoWGdVsirmwIB5lm01QqDNCvq3d6kXFvft5rvg8pA1i6/EH9/MyaSMraZFmN/CLwY6IP8QQTXQADwWUrIzDw2NNeGOfnt3t95EFjrJbshVBLlhdzW11I64yhDhYy2ghyUbKgNj+baXLBJpOYAFMZSiUN5Yt/hBnoZXjtKV7AtS2ZbaMeQRSj1Eopo14ZNyfp6EhOgYUpYEYiygaw92WzxBqld+mvkWVu7yW44vdykVN7RM1IgE6+HABBNUrgbLIUPVMuSkVMXmhdgaD2vYg1gGEo8ivZOi3FGAVqXsgOJCMOYHju9D49wcVK4bg36T2urUajjpZb9LQ92x2qlnjkmW/GBsYEe5ILghWw8G/ZalgIpsL7Sx66r0M5LR4mNiNjgG9UBeiJVNDJ7k9ODbrzwuaVGlgzjPXmYGHG2XpWL1d+OHVYFjG1nn7v9Y6Movj3uYHaVfSLabAup9Uzw4sxLs40GpiyMjpkqiBItT7hGbP2+OL/lrVjfWB7c7624uGsgWdt6jxDG3CdnV2ToIv6QnGWqhwN2EhXnF7xftgnfr/tgfq8mhaTdlcMlJVVse4FslBXJxFeridEXb22s5aFX719Feev6cPq/Zv933e2WObngtPLXMfGslr42/7e9oDuOuQk0BlAcb2qjxWAYNOnOwO1erAHWC8NKPI5p9uONlsv6vUBArj2yQAyYCH8qLMoDpyfpbUN+1wkdznAqifFclk2Oj9mvUeoeOmRkS2xFtzWRXkbhe7psLmGVjH2mOtYra+7z9vBS+m4RCeSx0Qs2jHVUT8RMEeyMHGD54NLUM5Do0xMpN3a7VznLAMwHi2BTydW6rBnKuz+EgyVjHFL8iaeL+Wwjt70BFc50uLJL5AS7QoDAMLWRmYwhx2h86pDrhMRnWRYuc+79f2OiiOuOw/WjCytwKM069CfEygSyEyTETGlJEd91G7cvDjOPkZBtpDxTLInJoUCiOhfhIkpQwsCSQeY8sckMxvl7tTOY6mWGMTP5kRNlsExWYF/NyuA1Dra9nJuKXFy8BeAMmc2OxGj6zq4GGX2cxofhsgDyJYx1sBoRahWWUVbgyrL/2Csve/i9dEHjclj5b+jLY+MAZPdzsGhN/nuY2MZ8+asUC3RRcY0D8zEkgGgKJbt6TvCmxi6RCXDR0Pg2gfZJT2aGxZZLMuYXQSUhcRpQMhIAoOVpDehCK8tfpdBE1dlT4aVraAAD9F6Ek02AvaUcY/qnm4IrlWjz2m/mA14Ff/uDZvqrCKBNoEyvUzXDIbhc02iXuw8nDW6BYywDUaGHsPifFY6Dc6sATBtCceQz+aepawNcjgBImgPd5txoyEOnRSNBwEyHQURy/heWwBHFa+Jtq7GbpPZWDp051o5CtbdmFq3GDcsnmEny2oHy+Xe14oVWmb5B0uyKB5ylzjATIvmjObELA9ADifPrFWgePaqG2jWnRuHCsPjaRyoK+tWT4/Cep2LZ8vbodNnsUzauQQ42F131EN3gGg9lsuxRVa0dcgY4EzUsnZ3zxXr5agTOB0cFC4d06F7wo2B0HaBYDbna+DyXQfRq7GR0iwUS9CqPoW7a+sks14Z67le2Jqar+2Q3T23vSarYrqx9W06RcXysODp7QXOX2VxgDYL5ltjtdos2D03lrGs1kFHJ9NcSgPmu25M6E2BrIKL9wA5OPipwOE1id7QFo4XtEvB5duezT4Z06rFwvZ2yCMAqtYR6jcHC+4cmKZ0vSgDLBKHiGWxG2gbTqpWS5YBgN3TEyqdJoEBSTpmMOe0nBrqiZ1jHBx6yJqMM9+rkwGO6OPuLT7L0W2YJ7ko7UFi+3oKifN+zMb53mI1CdfcMdQ6dMgynEwHjnE9dXsipu01ptIiBdZf3saDdkCYwCfDhtPWqdtcqzJQrXd0AlXSLMIkpzWSbiJaA4AFyLF6z+kMyGhXvS+17ucAoaM5g68rJpgcTqMkD0EH10ERK20USZ8yKkek0HToOsnyOViLCE4mPhQGhPuY59Dt5Rq5u3nInLpGy0ELD/cY301yTK3RslWclbRzswdgBBBkDnWIAEKfbffbPMFmgFB2dAkMUCkR2I37ivI6SASIjnvl2eogfYwhwO5uAUZz6B9AZFo7GA2gHGytRT+UToOP23fy+uiDRmC0A6S3yHAq6ytSD8DQcULpsXHIxlH3kLzDSKABAgBai8EUGid76UBhpLvL0GIwTO2h32AjXVdHQW5o7MhUcdHwP990OlevNt98U7bw7KLLyRgle+ZaAxibaLqHeJoslxmmpEPkRtrN9uw76l5KbP5yXFFuj2OMaBBg4xPGsnux87Vt+30HW5ruOQPFUkLHae31kgi9WZFwdpHQvffgZigYGMV8nernd4tqsF86eegsCZTt5x5qUjOuBHlRw3JpwQLnjgEMqUdx9snYYhOjwzpEuDFmr9Uo/cH5V5gzMFnXFAtlzcYQOTCEsy1kguthHWCcwm7Y/fVdge52fqAj5oSvPhPgj1aCPNRjJTVPGgI8TAljmI5trGMHd2UlEO6Yrg2QFC8IbuMFnxcrTo0i3kvZQ6cnY5bKSTEdJDKlrcyOJQNAgfWB/a4eABa+Rh8MH4Eqs6CtVJC3z7s1oGXlaEx/GKVlioPMCdbergDdy9aUk5UF0skcuP4sORxcwl57s81An4HpuRVzV7HyPQzL16OF3rWaZnO+tmcpJwSg7jvTXZaj3bexj2qgrds9z7fA8njoS/vOGERLHLLwNxSWhLMM0Gvrxe55dS3kdGf3xHUjK7xVpwE+ZrGTyUWz2o6AAWtLWPH/GNqFAU3rGMOsekRnIPusJa5YKSdOYAETEn1Xxj2X02psnLfdzGCxnBxwEIjQFjhAGwkPfYA6giIvHcPoQADL6q3+KiUNEntYveKDVYQgqJIRBoVHNWbb+4wqtX0dz9kRe5YJQMpQt9ssezgP757WYaMZqk2hSSGrmuq3omucl6HdJoD0hhibgt05tNlSNMimwm2uhg00MqEMxz7PWURv3EbyHFaMuoIpYzxKkJGsyVHAIik068/uZIseXdcRkT2rIyzFzzfqE4sYwOQZxfM6A1ueaWQ2Q3ufmGOGv4kX+KyRqGprQ6bqoJDPYWsoqrAQjyCNXXZmeG/efEOiCQfiHmOtJAb3/x+e5kstK3n8W1/4Z3g3gsEk7odGjVoCdWCxbfxeYsCjUDK9sO61l9i6h1q3CN96Ego9BU6mt7pTslVdR5vCWqDHoxmt1u0+zxlVN3DCTUODSLDX0mKmUJilarzsAIXcLGQLB8LhUbVuBoTAerXs6wAW9CgTUxo9sbnRaADcKITRp0EiYGSIvPcIyap7+gGA6MWKmKesinZlY0PQFNmA8xxaqI0BVbWwEuCbDsZqdjuQrGRNAtFcQ8zy5gFAz1AEUduxbA2dThP6xTzY7nhm9p728aex3k3R7UCv9mAIlWHivjONF9dxtCtcm7ULVDVW79Qi2auTrXQng9cJRggIYNUnQb05xhyJenYzECWLKC8IWQcwdIt+aPS9lQWa7ii0R4y/ARwHOjJYqnpnejwAVo9QDQT1qRjQXDpkAcrJwNz+w2alZS7s+eZrG5P51hI0qKeb7sY9klG0Z0Vijw2EWS1IxfpKi9B3YXUO9ZZ/iw4dp9g9WikaoO/ue/JtL5hv7HrzNR0nG8cow1QMhLWLcX/TnYXbmdAzP4fLHOBg0YBYPVkIvXhZHMsId6a2GajsFUBnwXRjKOtJA/ATmO9uLGHJSiSNbi0E5jxNAswfjeXl/IoaKLAe1ymhTgnibB/1ycLSfWcOWD1Y1v9y6ay4lxupHvIOsDkncOD6X2YPk81CseSw9WIyrWMKVWqtpi/mYUzQ5fpFA30y6vUyGxoYTmqK2kS0qLMmZIm9qVOB3J2ipquFKRGMpbTkNAP2rJFgONaRHE/BYkFtb8V3ObALAJcBCiMhvD8nCHKSi7iEKCJMiZCAS6ZY09IWc/cM7/R9wXwlciPZ6WHv/Twl2ZKjGZTkUOOXZEajRq5XRakl9Pq6tnE++dxLqZDiEjOk80JYCYX3W+L8sYxrr3lIQon5DBwPzrF92M5dvlS9jJ0x1xH5W1cDrrw3jhES0GXiVe8jVN27yejcnvIzGzArLAeoCdD63uCzEV/wfnKXm2/x+q5B4//wP/wP+NN/+k/jU5/6FEQEf/Wv/tX43bIs+Hf+nX8HP/IjP4IHDx7gU5/6FP7Nf/PfxNe//vXNNX7yJ3/S4vnpvz/7Z//s5j1PnjzBz/zMz+Cll17CSy+9hJ/5mZ/B06dPv9vbDcAotSJSyvPmzqFalqmBxMHub0Jo0AAbdC5aAJHqrhosnjoAyLSwCLyHaB2FtekR+eKQXD/RQaV5dnb4l+PqC3ZMXe4EoP08jJwA7Vzda9NRMgKwzxDgZG2EJ6dEGYoQbrtH7CURRjkEM/r1dhkhY0nGQXUkD3Gje1mAGKMU0g99S3ioPcIxAD1qHYDvtI4Mu2V1YJFCDQT8Xgg9wgYMpfv3RDigAIDadWv11mTeEaaYttOE3zJKTqgnPmTw6/1HtcrWEJIJzQXlPTwS9SWBAc6d5ZDWsV66rjUxqqHvOpyi1R89++hgsxiQNDCVSnc4m8duHHZY+9j79wYrQ82WZ5WWUwumcXS98f7dzuxENiwBt2vZZB16tnJYrXjz9XG01FvhDpaV2DHmTbzwtiXq1KM9owE7T9zwfdF2PieLYvdhdx0lwuGoR43wcD0aAAOMaStNRwcZEQOYVTFfrF7YHNYJxsFXPWkkYXBdWp9kYL1S7B6ecP5ip5PpzpJo+sWMsliJnnq7oC6K9dKeaX5u3zXfNOvRfccDDg4Cu4eU4f2UAeoGmUGuZTgBZDmjWkQ34MvwMrWB4ZS4aeqzsZPT9cntnq2retfQdtX3HKyGaUFcT2eLXtS7NYAT12D3Jgj9csZ0a0lq042BpnIwsFQX2yvR3clLcZEl7KwYAbL0Og5C6iNJAFXxbO82zgLaKHDOy3BqqcGOvYtBKvCz/j0R9QBtmOnwVOxZ1GUeQRokXVskTfJMUkou+ri/8zAiQ+pMmCM714ZtADWVBBK0df7srK07ZEdcn337nazG0ZpXW7DvN+YQiG5kaxvsLiNdEzUQbvMIBD26FPfCJJnmQEwxkk/PHNBByvB8Jbnh7zuarEicKVS19wuZ3O4ONiUOGxYRcR6KUgco47wGBggP3bn9jyRUNP7wMkMsrxe4P5g+7y7HfwOgBlKZBCRsTuLDGDjGz9jWhnMkAHELyJYy6cpxiFUbaKOM0Hf4+q5B483NDf7wH/7D+I//4//43u9ub2/xy7/8y/iLf/Ev4pd/+ZfxX/6X/yW++MUv4l/+l//le+/92Z/9WXzjG9+I//7T//Q/3fz+z/25P4fPf/7z+Pmf/3n8/M//PD7/+c/jZ37mZ77b27XFQ32A/yfMolUYYk8MULTyyxMXdDK90uSRvYDFpFAYzhbmZI2wSa2NorXLOhiwfLmupoFslo0VhT75YsFy3p+zhwOYIDKrNqEVaGxGG6NR+3EjgA5hsp8qQNJpkgXUEfIg49oTAONDT8O7iY0nGNX3PZSv58aZ98usx2BKWzBB2ZAIhdmUAHQLOUSJjhPrh5mmJNqGxfeNTRuFvJ0tLUu30G5rFmrn2vJsT7K4cjhty//wWWncGE4qBSgYiTBco+LhuaXFuGZgqcWyT7HfDSPhbI1lQZaRDDEVP1g1MTEGhvi9BI5xoDnDWU/NWMHF2JpC5tBBe4x/OlT4bLKsVn5mKqNMCvfLJnxWN6FJAjStBgKKJ0XUm8WSZmrB/FzjAGQNQCjDqVYknHtuvXQtnIPJvhPsn3YrA6QGouoplZXZIxJO5hs7vPrOE2kOHfNTSxRr+4K6ECwaCGn7gup9sstqes6y2nv3T4HT9f3wtHSg3i6RcAJ48WpnCBhGBgzcTUdL+phuW2Rqz7d+DyKewQ2Uoz0jFFgeSozjdKcoJ2cD2bIPsMSYRaNETmgVPbReDx3TjZXS2T23sbA10kcmtGvSyt0StsHC4m5/vEoAHRiWr+n7KTKhy8E7YTEZbe3WX33t1n86qhLY8+h+Z9nAp9UjIxIavbDVydHsDlQjaYX7s3mEhG1WxVjGPlsIWgkQQ8/eRzkZsmbecQa9R2ew0VddIgvbMpjX8Qyp9mFUk3BAps7KWRJZH+VxMrhJh4aV6eoj3J7YQXFHOhxFj3bpNMU6iMxg2hqx80wcRFmXLAVYv1AkOa5uN/cz2H0tWsPy84DpCOm0ZxaTBoBsGO8Z8O9r42xxsiU3qRgtftMzlJQ/oF6LMDn4HJ8IVcehaL+PftohMdPQkIb9Z9s+n8NgLD13IsrpnWGB0PGXMu45lQaK0Ho6Q0aZvB7h+JDWsb4kgJAXqFqxcvX31Zo0o3mcElj9Nq/p279l+/rpn/5p/PRP//QLf/fSSy/hb/yNv7H52X/0H/1H+KN/9I/iK1/5Cj7zmc/Ez6+urvD666+/8Dpf+MIX8PM///P4pV/6JfyxP/bHAAD/2X/2n+EnfuIn8Bu/8Rv44R/+4e/4fsda5oD44Jx809Y6Bq8IpDvA9L0bSD2BrHhxwfDATwd4vDcvlFLsr11HCLw10w+Gx6FjE5GJ6sacaPb6/N41lWYwdb8D4tMaJQOk0+tE0PnmQToDQMqdSRn0+GJDpE1GkXAk0vgAO8CLjEBglKdYvPyDGAUu3UGcMoQymFIUCY3QxohG2YQ0Lg6i2XdU0e1gitJDw7gIBehLOniWFf3BHvUg4zrdgLIuK2S/84xpC3fI8eQCcQM5EuMIbDStKu5VLlC2ubo9Wocalt8pYiwcdX6CkSBEkT9FysUuWTxpQLoGgxZa0LsT8PDCWWeNumd9LijMauSoTJOV32kd7XJGvTlZOZPTAuzt4BO1xC2t8EMNo7yQZ47XpaP7eInq0FTmUDwMNE3Xw6iavnjsD3asEVULi2sfXVqcHdbZW8TNBdNRcbgUoBsIYDIFNXRlUaxX1coFPbJEF+ksHeOhWth9tn3B/LxF6Zn10rfRAZClo1/avp9urbvJdAscu5UCmk6KqvCi486YLt2TMwyc1JOizQbs7sq5AbFSOzZmiLXUZ/i9ejIU2VMOaRn3Xk4wENk8WcQLc7PGpiU+GThtE1C7ZXYXB9iogummo+/pQBjIK2vxBCoJ4FO6yRGmOwNp/WIOEML6ilb/c6ZVsL7V7pyZbdlvdGt9Kih3i7XcpJynFHPEnFWxovbpgGeXlVODHL3Dx362dn4evi1eNcHqFrqUxoGfnFa03Q71TkckYPG17+wLs4nLYqHJtiuYPnQ7tpvu660d0ESkotGBnQOUhnNfU6Yyl/mGSdMhAUlafK6P4WRilGOZatibEY5l9YkR8YFQ0tMALdAHFXLXhlaaPYxrgRw9EY9RDih0aSMa5uBV4aVjjkfr2OUAzMKtfCYYUVJrtJyVtRmLxuQQwCJPzqhJKUY2RJjegHmsH3X5QTih/jmGrF8QWdSYJ56/5txbyNrOGlV1bOZjNmjBNIZ+LjdKz2QAS1+3ljm9BADe3I9N7sAPigECA/j52eLscyTwxpscBwR5lTDIdnltWg1KLaMSRrzymf6tX9810/jdvp49ewYRwcsvv7z5+c/93M/hYx/7GP7gH/yD+Lf/7X8bz58/j9/94i/+Il566aUAjADwx//4H8dLL72Ev/N3/s4Lv+d4POLDDz/c/Bcv7cGk3Zs4ovR5hh6OUdgztIT2L18ULV2yJwPRLVuKiD6+R1OYsg9PaHEAV6hX8IPUM65isUT4dEwmE0QkhcTJ2MAz3LLHsOlR7MCEBboJFiNhh0PjVDmz+iSNldRpZNrFRTHAMsSL8NYoXRMh7iJmBAAv3K3bRAy+vL+0ECC7kVSWkyDYFw8dudYza4CoUZHj4qEKT3qoJYAbS3xo9jzJCvJ5CTprde1RcwmAPauWYnUJAzwOwBZ6nXkKBlW8fhoYOmAIn/8uNIYEpIocJoEIcDx5ooiDE8gAykl2gEoWbxqH6N0J/aJ67UDPGm4tSjEBgBy8C0VrKBGSF2cVOqKAMtnP6qFoGGgs3saQtSSDAe7Gvq2XTIYYDPh6Nbn+FIAUTHd9MF7qGrqja68aS+gYg1q8U4gCAa7KqaPtKuZrQCfPFIcnq/j7+lww3zSgwNvTGWjaPXfmzlm2+RrO+trCkA+sewuTKeoCY7m479x+y9Kw7gXTUTHdNJTb++Z2OniP4ZNrH50V7ceD6VqXDvHezuVo/+5VrKC62r2yoDjr/LGGpYG4bhnaYuHs4kkxVnxbosXmdLNaqBy2huuxG8vW3BGoYkDItYw8JCVvXYImsvJ3K8rdYt9RrBpCFFReWYzcEl60YNiHqcTagCr6he2ferduviukKF0dINfhfLn9taQ6qwcrh1Ow6PN18/k1R1jZ1UP8OY5WdB0FVkIqld+S0xpJI9G9RTzCEiSB25IO7+Rl4epNoWvVEf6kTElkFOvmHlbXja4ppBvAQIadSJEKW+T+p4erGTFhXUDAnc3DaTh0wEgEjHNEwq5EgWuSKQIM0sUBa0omjaQb1RH181awOpUAoPH8sPJ1ZhKTkzlXA510KnpiD2u17HDqAjnGHFtqzAkYM5tIB9ftTJy/ZP+KbxASPaojU5oEChAOvEbI338ezKAPJSN0Op4332usG+4TEcDLAGqUGiLriXG/Ivcab8QzaFpzArvHOogEXiPyHb7N639W0Hg4HPDv/rv/Lv7cn/tzePz4cfz83/g3/g385b/8l/G3/tbfwl/8i38Rf+Wv/BX8q//qvxq/f+utt/CJT3zi3vU+8YlP4K233nrhd/2H/+F/GPrHl156CW+++ab9goeuG657NaBAQ2F1AaOmE71DwIzSstpcMhGku3ZkXUMfGFlPDIEDBgCYResTGiwfw76c6Gq1E4M+hkYDc6Eh4nVoIP3hmAyibXjboSnkwncgKtO8Xdj+jNJ69J0WblhmonnYM7Od7JgTWhiCv0oPqo97jnhh0oWwSw01l7zfed4YxsiGZtiVGprYxHkDJqAeLzfWBIDxfkAOyxaQiYe39rv4bHitDK/vd56hZ5rOYAS52V3EbmEc99JjDfh4nZbQHFFzGEJ3kQgB29z04a3yrjrC2LEOXL09gnUah1YRlm16WseBfrcgOnPA58GzBctxlERR13FuWpuphfFk1WA9s3eLIpHpyWzXeuiQ42KdPYBIiOi7GpqocupRQHnsDVjikV+b4NASPBBnJIuc15OtuXLyQuKqnrmLqP+3XhqAajuWBjL2TBrCVszXawAwFCsQzsz2sgJ9N1g/6UZaqIhngnvGtjMRffY56Aq8tDXKv3q6QLRd9OeL9nnHHo6WdWjxdVLEmGc/0IuXOqqHhrJ2z2Z2UFzhGcbW4ztKGfF+fGz67GHgYkCTTiJlJyxtE1IAn5t2MaEcV+/7PDJfZe12L+5IFDpKPp46jfGh1s4SmYZEJgpo56xfZ8OKF5ZW1z3rxZy0fIMtA6jZlbhO905P9dCiTJSs5jRtNM1JehRleTbZpW7L1zZ02jy0yziQ7a0DqDAxI8qHRV/tmuy0g11KjRQWnt6EVNM5liQi4dxUj+LkhEe+CFyoUaftTkkygJfmyraVZ0bIhzDmJkURorOO882qGIAKiPqV0l1fuCaHbDfHWYuezorE1Elrdl+dMisrbM3klmDkeAZFpCWdDxGBWiM6FjpIz20I8OlgkkzdiLSNewtALLLtew2M6zA5i8mOM/Ma2vbMivBxemauqXA6ymC4E/YEdGhZSdx0HRVjuus9qY0UDKIpr9lv8fquw9Pf6WtZFvzZP/tn0XvHf/Kf/Ceb3/3sz/5s/P0P/aE/hN/7e38vfvzHfxy//Mu/jB/7sR8DYB7U+UtVX/hzAPj3/r1/D3/hL/yF+PeHH36IN9980waouTC1e3287O1FCFai4KVQRwAYEOPC44sUOu/HvR1tK2RyAxYzyZmRMVkJLIaeMDxNpIXiwuEidsin2ksD0PYBxHwBbIqDM4zB0IAvRp13gDJLuADd79ENhfJ+45nPxMYVCMDakkGrBQoFjot5eEl7k/VvMlXofuf9WP2Abx1a+gjl+Byx3yoKwwIukF6NbVEab85ZoufDY1A9C1lgGMsAyEQCQP0nX9uAN2kdejzZRm9tCNZhYFccOFHPp+FN11G+g+uNNTuPJ/RHlwBgjItLCPTSwuLl+cFutNbRaUGsaPDUDsD7t0AG7BwXtYQVrA2lFii1kWRu5wntwQ71+QH68iXw3nU8gz7YA7dHu+ZkhWnlchfsofYO2U22VNcG7Cbo2tGWnRmTd9638iito8sR+uQA2U9oxwXoJ3Sx9dZax3o5Yb5Z0A8r+rq3JC+F1Xq721mhcO9y0ycrKK6HnYWALyv0w5ON02FFb3sjde4syUlvV+B2RX+0Q3e9Vjl2TO+uwPMVigltMf2hSoHcNmsldyPA9Qk6zVg7UD60tdeXDm3FAOYTwdqNdZuer7h7Y4fpuHi41/aoiqC3jt03GtAcIN9snZnft7vF/1QskxmqBmj8XNMq0Ls7NJlRngBr8TC/h9LLXcO6mzEdO9plwXSwFnvTe6sl6Jw6+rFgbkOzuuoR9XnH+mgC2Ge8K3qt0NOKNjMEf4Suzig1Lx8DAQ4L9Hiw3uU3C+R6gh5X9OMO6kkx7XJCvT4ZMzRXWwe7anPXFdru0JpakejDDH1+sE5KXaGHxaIJc7Xv2k8ohwXt0QVwexoOF2BjeVrN1j15CjACcXc0RvNyB7k+DM2b922WBxfAcTXbdDEBT26gV3uTuuxms8V3Rytv4nVVAYHsJ+D2OBh3rwYR4Wzaqf0MrB3VD2m53Jv9uDkEq6U7Zm27A3VmN+pUIHdHA45ikqH+6BLl2W3YJFkbOoDyO2/ZvwFzpOfZy6o1L7ezRLSGAJSsYXSlAcBKF7qsEE92Y21GrOsAWj2BcrJV6gaVRACvKZMlALntlWkarNhuGhGZdd0QK5GMAli1iFywmlpxnncEZzxLewfgjJzUiOBFrUaF788SQFcU9r7VGT0CK49eqTOYxtL1+G71cRGCfX+F3Gtlo5A4jPw8wgDnPHMX9TC5Ow9NB/niwDsONUZNN+QIASyA3W5ocxnJ67qpjgJgnH3+9xH6/tav/1mYxmVZ8K//6/86vvzlL+Nv/I2/sWEZX/T6sR/7MczzjC996UsAgNdffx1vv/32vfe9++67+OQnP/nCa+z3ezx+/HjzH4BtNXZgHJ5AAiYl/Q6RJWUCWn8vE0VUkavIh1aCTcadQmZhzwCFpI9zfSV6Jk6fE1TG+hJxyl8NZIjfZAhYEzhkvS+yCEnXhu6A0TdEaEASJrSElCHC5UageHqEUQFqF5X6y7PxlGbZ2DrPpl9Zl1QLLAmIAVB35IM7wufwA8I1NbI2CzX7ppdlsXsjWxmZ4M5Ctu7zlLxzMoXr8LoiZD/VENQHuKOhEherp3BJeOVkWFqP9oubdcGWYJ7sEzUvAWutSFAanqyOEiEBGHPhdpuX6ZAMh7Mc1s3CDcPkYfg8vrHOnblqHdPRWVUmDi1ZZD+eRQ6n4YA4U8R6bpZE4M+bWBpL1OgRRhSymOrlkirXuCXfbJKammdWu/aTayV0X2pjYUkwxhhqmg+2sds972i7YuHdNrqFTLcOpLu177NEFvH+1t17B48e5cWzvK2fNaJNn3QLa0f4v3ULMXuINXc50f3WKE/J/Mqq43tPHdWZN3Gt4npZUO96lLvhnmu7UWi7HFZL4hH7vrJ62FxhWsVVnV1FXGd5WDHd2j3XIzs5pQ5FDEcTJHS1eqX7YQPDjDRjO5XJIwVgpxx1CU10IoqoREW0zjxrRUpwETab5nptBmQ13UBcU1zf5+x/G8lnsYY8iaAeUwiWjubaUgcR9SYCqaIFD1qGsxnq5edPbv8l7R8HJZSvRLSjliT98TmNJMtcrcOTiFhhQ8c+IbsoamDAiuunyEd2wPki0wgxKUpoFjGIBR+LIeuCsVqeBRyv1iKxadQQpHPchzPLJhZTHVnIQUxImj+MxBV+MUvckc3kHGQwpJb4YSFkbOZQpmnoSLufC3EG+jWpRXTnn0kjAUaDbc0Mn4Pe7kknrP3s5wYZS5mn8XuuUaTvSevDGFIM21odaAczSLCJOLvGdfq4Nwe2cf5xDsmG5wow/HuurfktXv8/B40EjF/60pfwC7/wC3jttde+7Wd+7dd+Dcuy4I033gAA/MRP/ASePXuGv/f3/l685+/+3b+LZ8+e4U/8iT/x3d8UBycvdvEFcI8WNtAW+gX3FCSq0Xf/WQfaGmBx0N9AJG9kXSQnpxawiTl687Y+GKEZhbFYAj98WyyIAGkw8KrUXoiM8K1IADpmmOrOY2QZkALOZNpzKz0wLjD2mXZjHeFJIDVB98PbPxu/J1A+HDdzoJU6mGxU2pgfGHgS98RlbamPaFrkXUdjeDceTCRiYdVgAroZq2hr2HUcQqyF1vvIhqOhFRlhXq8Pdm8NgXPExIdh6Mkyst4mAAOPUfTaBPzl9hhGV5j13ah79HG72g0GJuagx3iw20SEvGr1eo3jHsOrn21tlZO3A2MNOoJvgkxee8mGRFO4MB1+0AiDWsJDWvehL/NbORqwMJYAUWBdYsxNqN/2E8rSolZovVuAavUji2sZ0XQAfiCAsER9y+T9Vwtl9kmwPqge9oYndwBlUVw8adh/2KNnMpDWvQDtoqAssPZ6dx6CnY2hbfsameORSQx4+Rjbk/X5fXNrIV8rWcTyQ1oFbbZ1XFbTMdaj3UNxINmrJQZZdrVtwu7Z2vNNj2456Ir9h/Z500Q2THcaGcrTYTh9KkCb/Vnc0al3iycbmcRAS+rGw2Sr6mOkMN2jO23F20eGjZARRgdg+kJ3EIv3VtcikeA2soyRKiKMA1LWFdjNHt70+WLiBOvcXuzMPhQZ+92bEMQ980/ahamm+oEKuVsQ/YVpA4JxkihUrWVofzcv2pWw6X0c0O5AcW8FoHbJy3CMJQ58nadR3JrnUuuQeU6hebgtGjY7Ij2tB8DR5npORqt6SxUzsAVnpcZ8RZUNSoZ4BriOlPrJTTb2OuzoKMbt9pNnD0PYU4X6+QjXpALi55OOM6HYOWIl9fw+NHVAyZKulFxEcDnmKO1NH5cAgIxGTtX1hZ6HwPMnIlzYkCjqRIlSn1qK5T24hC3O1sUTvbimarHvKf4nX5topJ+l7PJGltGecADK+GzbSsM4t6pB0nynr+8aNF5fX+Pzn/88Pv/5zwMAvvzlL+Pzn/88vvKVr2BdV/xr/9q/hs997nP4uZ/7ObTW8NZbb+Gtt97C6WSh0N/8zd/Ef/Af/Af43Oc+h9/+7d/GX//rfx1/5s/8GXz2s5/Fn/yTfxIA8Pt//+/Hv/gv/ov42Z/9WfzSL/0SfumXfgk/+7M/i3/pX/qXvqvM6XgNbjd5dK47ZCFYasi8jaAuK8LrExiFnjdTniBfLBstg3ujkbGU9HeZjURoELhQdXhoHg4EDARKrYiSQKk1ktLDWS2TTLo9WxSlXT1Rh9jMBb4BEDNQTB1pVBG9PMkCmTOcaliSkaWBog5HtsVQWV/Q3uN1uTzMSR0eXLekySvP3zMYzTLKC1TvE1pkaCL5ft9cg3Y3I2IsVmIopzp0lfNk88MNHIlE9lkyz9HWysGOxDpZxj2o3cdgUnO4YKwTUYwaal29A9BYvnK3mJbrsMS9yGkxBpYHAENIDIOznFBcxEHdaRkHkpd9Ct2TGstp9+JMZS3WUcPXFdm9KGniz8Ei3MIWZpkdddaQh7ecmpcvapE4oNU62rBFYj2ugzn0PRHZ8lUgq4ZmDpMfXJRRcez9+9jr2ArPey9mB+V9KsHISbN70qlYtvQksI4vtmbLSTEdFTprJIdIV0y3fYABZ4HahTkMzXWbZVXIa/frNJaTzbU007X2nR2EdTHmupeROV2PPdqIUv8oDhyLh/FtEsbPWfC7nuwe+1xHCR8HS2yfGUXYCaQ8/DgSxmyPtNlALfVzWmyOsZtGkpdIAO6y6pBfJ2kQ92EA87UNqQvgMiBBaV65oHtymGvCIBLrPUqjeOtR2g05LGP/0cGmnm1Zo8/90HSZc5HDngbY3HkvJbRiASyZwEPQmW1WLrtGhzCiVz1CycgREY88RU2+zLZnZxcYBEViHjcaY44Tw/ouwSJAlWqZ4+phWFWEPY3NFKwVIvK1YYv9XqLINHWKfJFRFIlnGmNHllbHPauO9nb8XiZrMOoTZIr62T1qIwKScgo4J372TAayLALZx3zls1iK946G4QBPoLGyPD4ujEJxfHKyLdeEj5/wXCVIy4Azh/s4vzyb4rzz72JCDwEt54fvjUvpcNb5HxDPniNo9/X/3/71XX/ic5/7HD772c/is5/9LADgL/yFv4DPfvaz+Pf//X8fX/va1/DX/tpfw9e+9jX8kT/yR/DGG2/Ef8x63u12+Jt/82/iT/2pP4Uf/uEfxp//838eP/VTP4Vf+IVfQE1ahp/7uZ/Dj/zIj+Cnfuqn8FM/9VP40R/9Ufylv/SXvusHDD0B3RAmkMRgJQMV36+xNsIDgBfOJlvlYuGghTFAoHKh6hCdMnPaKrn3Ea7A+cRpCHrtPkr8PcoQ8L4DDA8gKfM0Sp4Ixkaid8VPJwZM1yWewdhQ1wsmY4OVtSR7+l77vUzVn3OwVFIkeVAaXo8qItMbmjSh1CdVN9iusYkNnYXI1I35v4fOKGn3xO+P+6b1EVKK+7e1oc420gMOxi/YT4r8SzgDEmEaHfNXSiQZBXugANsEjmSlNsB17wMfOoCOZUkNTzpU6VAwu1RjLSfjE2EtGwtjKb39lncRslIkxcPaiVXx0A8BZeigFPbdDDUTnKoBRSYVDNBm2ck2fqnjRKy/ZGD9mWW1TG1bf330uOW4lVHjsqzWMceYYkW9W6yguT9zWTpKVyuE7aF8ObXQD5rcAgHQLamjRaFyUUvOqbfJIXEAOd2IlZ3p8Gxxq3coqzGjzesWAkC9OcUYyFt7vPBVBPW4Qo5LdHKJ2qVAhDrXy+oliTwMznORTLoDy3poaLuCetei5FWfho3ZPzMWWg4n1C9/A/XL34CKYDo2VJIO3HticyXHxdjJ1UL8BtLte+ebFusnDrZ04DN0D8DCrDrmE/AqBszW5f70Pcv2g7E3IhSXbFBXlOMyEtJSOE+cyQtHLJxKDLsucPuxxmcY2hYC2QBlfezRLAFyZtb+G/KmcJZyQoJSP8akSMR+jO4wG026eGmZ+Nr4vU6T14ckCyUD6AII4sP/E54N4Uhzf5tzFmYratsmMNTbaJnKe+NZmBnFYG49oZIyq8TARhOHCAPbg8XZF+Frl9soIoK1aeXojv3o+mbrh2fwAN4lnhNw3WSSpRmItDW9kW3xHMnf10czDK4JyWxfZv2CQXXnnhpYgsNgQrFhr2P/pLGMloKZ/eUZxLOc4W4gmM44n1jXOfBNWi+85nfw+q4TYX7yJ39yMFQveH2r3wHAm2++if/+v//vv+33vPrqq/gv/ov/4ru9vfsvgS1YsnOkaKsnKDQDRyFarZboINPkQK8MFgesH0VWkojEvUwCiMSuBdPWrX6UcjHQ05EC2e2gJ0uyUPeuNwCRukbA6Xin9kMoa4teiguZpwpdFgvzZi/RjYIibQAAMu88XR+hAYL4JqeXRS+yVnsvw8MEdO61EhxpNy2JrYdUCkCZ8FKGESjFSh0pRj9tB2/a+9DwKJmq1QG8aSbx4GLMK0P5bbV5nSbgcIBIGSGhpJeJLip+WLFzTRSzpQFjpvM02XdOppcMEXdiPbA2K+Hk4CvY4yKQY9+U2ZHFihKzvuIYJ0SyjXXy8cMItsfEvcnzIupyWoFpgqIOY0DDoEjZlJaxG4dAK3GQl7XFOEDdweCB7QkOFv5nb/KK6dbQhnTLZEQXa/eXqwkE+ysbbaesY1+yZuNGr9R77DFmKW9YCGCEyxz0ltbRq3ckaQqsxuSVxf405tAO+f2zFoytdEEppiGTi9nOi+sT2pUVUrcOOLaGowRQT5m8taCe2pgTlpg615Xxvr1OIRSWvNE6pBHMWujasuslMpfV+5/Xk2I6rFi9JE2A6qlgOlrrSI5lgPoiKDejvqm8/nELnZ9aAM8+C+p1s6zkQ7M5d5sQDlRXA/a1WHLTzEzNbiVcLnYox4Z24cxf68DOJS8+T1nDykMrZwyHfQomCmOOq25ASIS1WTSf1259JLjx8PZaq+ZEDgCqDLU6MLQIwAiBZpbSOiORPSLoqyF3MakQwsFS2CHOn4XNWdeorBCOFIEN9yD3XqzvZMOOp4joCLNltQNem9HssNka07o5YEygOZxLEbMKvUWZMggcYBlwijqVp9X9chn3FvNB8JQiZavVvUWTYG2NTXS7X729H0GyWCQsMovTmRr2lONBJlYE6gkkVpcwS8cw7q2rnTe0pxtW1PfrQhLJxkHmyUgQYnHa6c01dAvEMmtOgJrXWwA8n1PPrI+azZyzWBM4A5Y+fxyXntYM32sbaXsNrnF+LsDli23U+eu75yb/l/jq3bQBLI8AmNd0WrYLPiUKBFjgZPLwAkYGlZ55GHDA4GymSDJ+2q2UDMEPGRS+pEBPp+HFtD4Yy0TNg8k5PNCDeVRjDJf0TM2eO9oQAfbZttqz85MEfpOzBFGMFK4l8rHR0eqILZmA8XUQjKbuxQEVaX56WkGpJ89GYOWOyFL4HGz0MICFUgIc+v1NNVrVxdxp2ijuKXLONpojetcMtQLGsPHQodFrY66UnW0Av5d0IMWfNk/BQvDQK16rrqXWUFGn0kP2ZEmAAWAToIy+rn7AmvFdIhEq1mnSPMZhToNWPPzlTMoQrOt2fGoZmtJwfhwsxJyfGSRnAUzb6GE313pFW0QvAcT2cAESAD9Ikyax9VSzjp0pXPwfXXLgIe8RopWlo3i4udye7HO1oDRYYXQ6I4poBTnmC1tni0Zc7fnrirE/HKRl6YWFmr2o+2lFPRqLtHu+Ob3w391+wgAwn53dQgimE6iqx3F4CIuYe5mi6uCX9RqZtBN1JG9PkRwUZWb4/PwePzSsJSOg+8meK69rsTmxzjol6qNGj3oyxmxz6vtrZJXbHmC9QYbGsfKgLIP1Yzh4w4iZUxdabsDLr/ihl0ubASOkPMJGMceyLEMjRpu1ePasM37mlPUIB2tb4/yImnaxvzEiJGprVh04WdQG5sR7iDCiPiQEaJ/IRLpNiMWhiGRGcyj9PggYBYjkDMqwuI/IwEaYFGk/97GHmPhSLCtcCS4yYC3JBgO2f9vqTj9tO0kUSbYz2aEU2hWGTKGDuMmRQT9HhY42I2JZ98+oG1m1PiRgcdYCfo0SDv8G8MY49+2ZSlaYSSxkNVNDENr2YCrzOCijadvnHgkrHK9xDsS1eT3OQc4qz2A0O9CbZ8LQr55/jn9Ppe2+U6bxnw7QmA82TgC9l3u/G8xZTDITNvKkE4Qx04ufL9z4AA/6CLHlAuNupIUFUdsISTCVn59VZ2tUU+jbN03o75J9MQPjolvAsuNoPHsH6rTtxc36TX1sHKjrSpqBaxGEuD+0gMxApr4ij0Ou/1VKqj+JQbMzzMDvYm9Nf0YJ4M1NWDfyAnUtThSmFsSGi5pbXghdXFMpkTntIJDazWCNh2GKGm8C915r1K5jKE5YygL2nsF0bMGQOqsg8VwYBobjcDgiwlHZS6RhoRHyLErlekzh/zgAm/fk9Xpv+eBUdhKiU+OGT4Nh1cjAjLF1vSlaRzku28M9r73YU75/WMNOYSwF/x1hduoq7ZBWwNnS4skazcoXRVmq9F2pYDq0jzqXzUPM7InNDHRPIqknX5OscejtIdWjDzmRp5xsD5TjiumuYbpbo1uLJSwtFnJ14EQWbhRmV8hiCSXlrAvoh8tlFNdG837oBMkE02QIE+Ara9+Ec9u+WKec2+ahXpsT8QLao32lgctIUgitnu9L1sH0RJ6SdKX5YGZ2trrtEC/HBGdFI4GjiDkGXaM2ny1A36zrOsK5zAwOoIcB1oNV6sOpA9Jh1wdITcw79d/sc2/v1fG82UFq3RPN+kgE47nMs4D2k3bQ71Gzvm5dweLJoemmFvx4gp5OUZs0xvN02rJpEQ3AcEp94JTnCuU+zZNjGBXjAHtdXY6DMWsukyoe8WKEJ4OFNEf2yGXYqcxuafdok1rEx21oAPiewJqX/8rlfQiKLcJFoJYcfe1gwmgkfaqOcUsgLs7mlKNg7XfdQQhQ6tGr3ARC0zM7WbApSRNznNZkd2eYRBMB/TSBDKvNrc8R2VSyhgSCTGYhOM/EVU6g5LxssEc6q+PZdWCDtD7j2eL++7hmfr4MKL/F66MPGhVjgaXwQhzG55lL/FUkm2B4AuxjGun2GJNZ66Czc1cZIgQuSF6/FqB6+JZG7B4F39JCkthcEuEKv26dYrOMtogyFkpi9PzG3NDQA3EDQm8pgCqsev+mLV8brGdsdAe7BF8EkjQ0BH4iQxRcXDdHQOSbTEod5YvUNhw3nc51ZFOS1aEh4hxPU4TS0ZlZK4PZFZgxIqDHAKYhpgeGIfJDU4+nYRDJQi12QFDMr2sLfaSF1fkQANlZOiSadVIMwxUPx7tRE81zxgXtUoqupkckG5ULDysGkCUAd8AQzkoyNLJa2R0R2XTiAJBYqHSoq5eRWcb6CXNDvdRmLQzjx4STuDnKAqIX+ABDDPkGq+OHRIQFO9lZX1vHZayzxQ7JcnCdWrc6iACMWWTGuoP26CyU6n0G6yfFC2Lbs9RbA5H2XSmEyL9nAywS31FPCWwAeO/w4J5+MU5rB9bSPWy4DOaEmf7lMA6/wvI/tynz2J/b6gJyHcKKj/u/lQl6Pib10KNPuXS1MeHhr/DncHBKkMa1RhCW116suRIhd2lty9QBDsbcUfFrhsYvAw4HI5LXmGDIQOKw5ppL8zHV6MUenTSYGFKHXCJ6E0dZLonrxHgxFNza6C3M9Z/uQ6qHwiMTtyQQamMmuzl0xZIcz2C0nBjQ5vbfe8HHS7IdSWcN71VT2RieN34Whmykj/PANNdeQFswklJUPfu3j6kTGSQHEDUWGZGCwGwiZVU8Q/O9KhxoZxlWijoR+PH+U2WPUXRbN3WFtac1w/O81nHm0SngR7KdCvbYHfxSxjgBiJJ7Ccjp8Qh4pDAuSlkcy/RwSSZCSpyZ9pse59h5UmcmuQJw+sPRDmUSKD/LRt5wBhgZxQz78+1f/xSAxjR4pRgKZ0KHT06AHRpsRVpcSEbAr5kMcBywXoInU8ihfXQjFt5ScyaTWdO7adwbZEx6ClXyy5Xh5o3n1ZOWxRZtfFcONftzbjQwfJ7eUys5B89tTR6jbMYijG7E1gbwwzQNg8L3+GK30gqIsIX2PkLlZYQOpNboIWpA0gXiJRVDj/ny+WBYCUiekzEBMk9jDMgk5/URITFbJ1GA14djk02YmWSGvRSREGTgEhFK07kmcGyft0K3lqUvx+M4DHnwkqlsDVhWC6eFcNpAYmhxnMWEyDDW0zRKdbQ++rfe8yh1AEeyKGuzGpucY3cwlN4vPfjjMg75nHzDeWF4WnUk26T9GOBRYSAi/ZthJwrmo0PGPhVrJsvM+S/sn5wSdc50OqKwbF6FMZ+1RIcRqNpedJYvGLTMkPH6rCqwrl5D1DOjnZVpc2JOfN2OLjz2un7nQaw9AnGAgLGN7iGZ+UiREQLs6Y56UkXfG9vBEjnTjZfJYZFvSbpRrmeCs9YjwcjqjjZjD9eWmFNY0Xh2hqENYvg5QPO4R/ESOLKYHi7mgmFZf5/2PmQWqiOykZ19B3PKPUnnuXcfr3GAiiBFbTrISguHMbOPYTc0FeJnRKWPeVnaSNBixQvBNoxOEKZAOMgOPKQUc5CAFDqUeP4AaCncq9nOUgLQ05oEAnhIsI7DyRn6QXNOrGi4DFucGS0ft5GRW+xeqrOmPu4MiQdrF3WKlxFR07R/GKbmmKo/o9vbbRQv2TaydQSatPEBkhQj893Hg/PlpIIua0TNAkACw0GMuZaozchraeteW3Ks6U2ZOIbB+Qx5LAmwc7tBrmfOS6yb9Duujd7Hn8QvfOWonqqf1WeAkJ85+44NmeXfN87zb//6pwc0Rro66XjdDq7mVZc+l0EPEIzLxkMhQ6nYbJgQ2yrMw6S3UGvUE4xDQXmBAWLiHngNhke40OmZ8NYZskihsbhu0teFRqOcLWT/irg+WQRN98Pwq39G+cwcJwIYameAAWzp9Xqx7jhw8jNloKYwb22qY88lkAdPblGGt+IQaJ5U1EZCy9pGofeU/RilhwjIxLOpj6N0zhBKOwg9LRFyinkBRtstNyCyrnabXbebkkaXoRV6i1B73uyMCPVysjlQ2e6R466KEdJIYyh3x+G10kvv3XS68PENptP3COfpuDhI72P+yISor40iEWaMtZpZMxo++AHudeeU2rZuujFdmIiWDlSkECqfNTGqKnDNJeKeGHrlgSInL6vih329W9GnBLzOw/rsh+1rn0lYyrXnDBsAcyxUR7UCqIHuUrY9mV3rPCVmEADqwe/D10Z8h8sAosIBIw6ARxN8PkuJBAA6soUVBLi3V9MqF8oBlmaMK0O4qQC89fdupllN9UTzvpTFQ8rHdWjbeM85qpKfP5jD6ixp2Y6bwhLWCLayLkxGf+ywf0z4OS2JJZHBinM+GQnpfbBD59ems1Rc75xuPGrwZnuf1oF23TI06zp0eUj4fjWdYDR8WNdRJi079cC2DJx4GNeBlQg84pEdrD6u09PPOB/5DOBqXD2R0M+Q0blk2I5I7KDGUTFYxGhSgeHk5jMonimdFTw34551OEF8hlSWJsLVlG/lMymVhQvHlkRA7+M71dfIODwAjM5vtjb7/f/ynKvbJt6Pr+9ghCPzGwM4pmhBjEkGZBlYkoAIAkgThtDtZ8KuIeEOPWMeMdbNhlV1Aqd4dxtegx8paa6+zeujDxr54r7JzBTZRiD0UcEgcjIDEOp24rnqwqj7j2kwedBzYWsKBzPkyu/gPeSQSz5A41BK38tr0WsLzZtdPzLegOEhxkHvdQ65JjMNno29SCqsmsfSB5MLOdoT+meypsLfG4vYx1anapQ+vTuCNe+/DSB0QfQsCV6EwIcFz3mfMF1eZMALtkkV6uDNDWoAOR16Js5RbKxciqi30a1msSSfTfKOz0fYKDLKNKABrp0FiTOKxsKBEsHUaRleIdlxN0aym8e9nXUoUmcpNR3kwegSiCzLSLwBbD48JD9KRzl45DxwLhy0arHkLc2HdayrYTh1b/cq8xylWqS7UzVZHUP2YZWDtbeLJJowcOnQcFYswtTuMDBsOfpk+/3fWpF5Wa3LSln6ABWx91qwsVEa6PouAAy7blgpIks0Ea/bRuDJWp2Iz6wBii2hYoMkUU62P4QMWA7bUyurtvaM1ezOskmSHxiA02oAvu8sxK7OzlGWIF73ESsTiGxNRpidmlV2jGD4L5gXGfaDERKOnwzZggpGOZlg7HxpOqsW+4SHaRHXHtteCsafS7q7Hu10GkX9ewpHEgim/5jAEPUBmfna/VkpBcls5TGJTrkGOC4EdgwXiwOmcLzTGBGQ875pr7j/S0qEcQbP6gDLNpxJ8EmmCw7c4ozw58lSpNXC5fekNFHhw54tav5mhtTPEcu4TmBIPARNOyYF1tiiJwLCwa4gSoptiACSFfm7APtsZtJVx72F45zOvNbGvXA95WREzhvZwHlG1HQsboM3jkECX/CziOdohOW7M3l+TZclBS44/+52dt5z3LPj4eM6sEZ6zm/25z0Mkq7D+4gwtv88OZysEhPyKBIQwQa3+9d+weujDxprsV6MGy+ibCcbOsAFgWR4UDQWOn6v2II2eiGaMnHn+b53EMAyaTc0Z43xpnV4a7wf7QghbbxkMC/ZKwHGgs36IoxFF+JiwJNqXrBQeU22aaIx4GbNGztdOzYbGV3eQGoEH8W1ufEYuhEM/eHq4NpD0hu2MdgMTV6m1xlLVfvpVYbRzddw5gUQ1w+WMWe1jFplQDC6I9sPcaCje3LA0uJepKRQMVmFqW7CgkyqiUzJYGl87IKd1gEwudnX1eQPpQyjCIA6megw5OEJkfS9ftDI6WQ/SxoYtlFjgXiuQV3z+MPf4+WnMkPMcEwCklFAXH1Oc6iK6yBYqrTuOEZlhKntejzA/Dkppvd9KgyXcjwIFBIQGevIAQjHNRKMNBKfLOTtxcVp4AHva5x0lZy3fKAoIoQXWeB8NsXo7FGHsY+i/AHu/P3HxQHgOphMd7hk6ZC7JdoxjvlPwNvBRWb7RvjdxkJWT+5ZVgfZ6wuAu41VgGuOl4919K/nAca9op4gtLYUGuQasBq27FDCOposNh+MXmJwgkAjWHd2LBy/0AX678kGx3jYmDAreVPpwS4wwBf3etIMAjAwmu9NezRyENe5k2GMl4OtaCKR7zW/1+0bIyQGQjkfuh2PIA6yo9XHvfPfHuk6r0wRjB+/mGFjaPx82P91NFfgvcT+932z80ohjGgVGfrzADi+32vZ6kKDiRx7PmwEz9r8ytGpXEMyn/Nct5SAnUk9xnO3cbbH+Z/sPW06NbkJiN/XqPvnWk/lezDOGN6nnP08wGdDtoWbV2aRScwEgSWD9OB7fa5Mm4mBaYr1ztaY72//+uiDxtZNoMqwzovQetY2cBKomfMXmZDxAxmLiJuTBUPp0WgyqrGxdLto8sIM9I+xKPmenJIPjO/gotsctjQAugHD9mtfUL0nRixvADewzVggTF59P2/YjWffx8bhBVMR8aExKgNAAcF4SWWtTJj2MGnINoaN3i7DCzSSORxBlkxc9M3xzoAGGD/zDcQC7BvnQMf3xukkGJqdxDxo3/ZNhshGq7LZ93HIlQDfMnl5C/HQN8iUmFetK0OB2Iiao8xFYXY6Q5PVEwN6ZEOzbJL2PjR2vLdSBtOT1mVoWePf6iFyH5dmZZdEMABZ7xb6nuoIy3M9hceLwYbD63aevNtCH91mNgkwzZhSaWd7N9imMg4WMmoROZAANigyioIDDmIZiu2Qu1OSTvhhfZZkxLCsnCwpi4yZLp7tzSSS2Cd9k2CzWQvAAFcKZ9W4H9mn2Z+5lpHY5YAKzfSU0YGjGQtK0AWFFUzPZ0g8bxv3mOv3kfHq3RMfdHw/NXXBDqXnSoA6rk82o1uykVKTPBsjHXX40tBIa6HtM7lAuT923MPJkVEHVsF6qTNmflhGRw/uZ9r8kteHh85Vw07Cmd9Rk88aEdiwEfQzARER8tZlMedu9mRChjxjzDTYR81jF92+EGt2w6pm++IgzsgHLyPE69PGlWFr7Dt7YrcwxiLOM+rv/T7I6uZuYYxAcf5iHmz96mkZYV0OdyZmyOzx69sa58MmcqE6ol2cj2z/+ScQdsLqKvs8t/Sd/B3Zxnx2+32wnu72LFCEjEdkyJyAVNYpvQL0J1t6HrELoC+b98Wf+T9gq0Pkd/Df7uxEhE5HlCjuo505LvleiU++GUA9e330QSMwdFyZacgDdO6ZhTZhWNoIg8bBmoxW+nzUI8xgBnCj6IaJYdoEbKIOVTaEYdAxQGTO3Mr3n+e7NQvR5oKiIsnBPgNlWXMGDKZ1WcPQRkggFjjv3//jTbPwd/Z0zjUr9M4FDhZwRvdrMuQE2pY8EvW3BAkMJhBHMBYbkkMkAXyC2SNrfE94nQ4VHizJwI3v9DFUn/soT8PDMrObCbQ5q8IDzOqFngFbdhMiC+2hLnVwN9psOdBybWQAv+zUAIkdTeCW/15bjA3EGdIUYtG8JpkhnrxVTQ5WzCNBFGUSzGrn/TDRptToSU6wEGCvuZ7I24RJKZEBnWtLbhJfHOhuSkioQo7HSCZi+8Ho9sFJEvGsVB9vRbCG6uttY3hriQ5PYaRVUe5OXpvQAXYC3vk1Og35v4N1SnYn62uXNfoJSzfNaSSLdI0MYhZL19aBu4MltnQFvBVfhN74/ubF8PNhnmrmhWa4JclEHETc/xjrkXuEYHE1jfFgTt0GaAIv2Z6prf+ouZnHXNM9ArH2o9NWYnBUdSRB+N4ILaEz9Ho6berYwqcrmhgINm1Izw/ekIIs6yh7k/dXnD09Qt2jBuN2PRgYW2LsgsWPzYbYW6PxgzvyPq/KqAuJhrC9PHcc9J85QoMU4Bz6/bm9CDvnzmKcZ4KxF/MZRHtM25HZs/wevnKYm+xmrsCR9zOBPq993jt5c/b4feWzmGuU+5Nn2SZBKZ3fXFf+Z+zPOBswnI64vu8dn3vZJNiksyW0qWMPRLg4jVGUb8pnEv/uwDW3MYyONTGXCPZRZBRPz99xLynnm7w++qCRYZ98aOrZ5G6MUvp3BlU9/ccNmTQ9sXi48KdpJL6cTzTBTCleqmdClE7hQuIiZBmCiUWWEyAKsJpAKJ8rRNzZi3eAwUQVLvLQQaT3psSZsXHb2HD0yjMT5yFolpYZHgy/niEGB6FZPE/Qwbp/abHbLzDK1ASDBP5vzBsz2Alo/YDYbJAUut8AohRiic8GuNQYP/6dpW82oRMeSLxBpY6yOSPQY6yjrFEeo5qK9nKN5PFgglUyXDLN4YHHoUZvmIAu1Z6jURogzrObQ2e7NR7bcgw0mgkc5IMgQC+GIXOHbaOzPS0IXW/P2jL/eM7AXEcWvxBI8su5ztoomB5F52NP9iEJUU/24IvgyeUQBKxWDkoGmMoOWNsy4nYolLgnLRLtFjPDcM6STrc6QvdAwhBpnXHOBVtZRBzSOtgRD7NvWjaKRLjbOt64DfFDSKKEFWKcx814FYN5Qr+Yx3cDViN1tnaarClq2ffNuyQ5wyfGkunpZBiD40KAJckhBZJtK1u76wyPsEuS93hXgpe47ewcY+xJIA5w9bkGw/UlR3n8PWuqJMF1ksBZrIXu9UGhg9UjEeAdx3QloMxgBknD6P8WWJSgen9k2vXWhv3iGG3+PsDLSEzpzt6VcVaRfYYOG02nhXap1EFqxPXT+G5svq/DzAI6W2i2hhEgOw83CV1xpqQzi/fnjt/W0S3YstpcL/57luHJrCO/g/fDChrh9LQB2moZZEc+8zifwYjrPbCVQeI5Wyf5GrRLBJTpO0bDju3cxns7JUZpXvhv12FGFx3+F3ZeN+O+kT/wOiIbZ/VbvT76oLENg3lvUlOCyb3ilqob5B4LiIuQh0EyzpvFqK5FOQeOAQJgGzVfKwv78zWB7YbjpuLzrGnxEzwmBiMWewa8PHCAkY1JcM3vCTCZPM88Hn6ghSGltxjeW99eJ4MypI1XvBgrk1zovfKVGGLW24r38IDxSw1BtnujEEQ5Io4dwWZsVL8VMqYbL2yshy2z7OOb55eePMd/87x8rxvTDES4edNYsnMPx5kssJVxkjF/Zx4mQz3s4aoM98ScwdtZ0gM2cCrNW2eGHtW9auqf4lDOBm4wARtbmQxROC8AdF0i5C1pvQkBH++R4d6k4Y35IOjk8288aQw5BuCAaIT+mLEurW/DSqnbU1xcYbKD4pq6YKx8jAnSSjG2tHlNPl8/m4LSPNjPDpR6Sj9jUgFDmzo+J3UaYeocFs5sFZ3OtXnYXDei/+jXy2snJ02XBcEc+bWZnMGWoeVAhnGsBVnaSITwCbD2ntOwBfM0rkt0FMzG0KYOBk9TCNHnnbaYDDv3CRmp/MrPl/dTawNQgcWu7Vq6LrZnUg3CsFGcn+ykx/fbM4XzE2VPZMxn2Bq/3wTG4j653ln2ZzltvyOc2rFmI7Ob9pzPHnsXCKbRfwfAnSvuyQQm+CWULFA3rJpKx3C8NcYxzjR/pviTADyfl+dgC7gPQvmr2D8Z+OHsDOStp7Mr257z84sMIt8f4VxsSZL8HTx3eY2pbp3oDPQEwzZugHXCCOlzwXzT6QzWcoxhvAe+F+oWsoWOMct/HEAaZ3F2D/yc44N7APg7eH30QWOe4DSwoz1cv7/Y/SU5C5iLPoAXJ1jug0f+mb0v4AxUnt1nvodzynrDOuDMG4Itft5rZu94X8HapOvRuwZc4yYv+C4/iLKxy99NIOkLdGxUbqLEzuSxIqjiPXUP7/WRbKM8aNs49KGJJVUMo0BAFV4khoH175RsQM7G/F6LQ/uhh/iRtGl8XiStTj6cMjAgGDgDQ9zY7BseADtdO4xGGYeVP4eNU/K4Y23pmAOCmfR7zSGcpBkKxkGRMiQlAEL0JOd8iIDF7WNeyObzuXsaAwdULNMhPp7GlrLYch/3PVuhevGQdW7bJcV1hOnA5ueoZd28ihhzI+n5FeMw4p88KIGhcQx8YHUKo5iyO3WRLUwNGeA1VNfoYx2f4bOcvXSS2J9RN1XZmtQcImPW7AClgZe1+XJxh4Jzw+tmwApsDwwya9Sqcc3kMSr1bH2xR3uaczKWBDGnUwAKays3pDrq+y+YeQIK3iJZjn62dqBjjPmMZMPAeUwH+nk9PCTgoqMINCjjiBCva9EJwHKkYMO6Eahi2F5+D//LY00GOx/IXUc4lXMdLJs/B6VFnNaI3JR0L2luOSeCrYaPNgTpM7QzASyxsUuRvR1zD2yIhPzdmVnNZ2cAm2Q3eQ3azhifPs6jPFZxxp6dtcBY8+dgMbTIfetMvwgQ8V428+jXTnN4D3RlcMnrROiYj6xxj5rHJT0DHfkhm7L7VTqs+WziR3nmMHJ29lxkI6MTj2wXS2h+z2wR9+d3+vrog8YwimLaKE0iZ9Xo5JJFpPHq/R6yj/ekBXz/Owdg22hgQofBz6bvOQcB54vtniaDmyMt6ry58n3x+TPgy8/GzK70uw17lccjFqtuxOFk/QJ40DjmM+AcbOd7pXA9Qp8ETWUAumDp0oaJx3Rml0A4NH/2HRvvOjJlMwPqhwH/nR2BPAc8+DbAHsnDp5FMBy898nA6YKE2GspgJTmXae5o6OOwdiYD6XME9+ofEBkJDJquze/O2dYErj7u0W3Iwdj2GXj9ktqW5ftHjHmwV8m42dlNUO8/91qQZIgpno+vpa6zn2fd53Wau0H4demdHw5Dq+PrLNoqsrA/w3XaE+uejKtIynw+W3cCMMudhjdYyBPXv6TxG69eAGbkbpKQqjHv6qH4qAIQ61DGAcJ94xnJUS6JhynrfOZ9QYBIgJDAQSQFRQ26F0UoxnAOB1DS/iHa4bNjXCtsjztknghHrS8Ss73RwHLMWas0gJ3bDgLhqLLgY75JokmAQjFAHR+G43Ai8+o/a8l5ChDDuUrnBh2ocOiTjeOaEhkOSk96YN5iaMfT/uQ1OLbnQCe+n/MxnGVQG7idtLGHyEDzPQRy2bZngMI5BoxsCKlPjrikecvgjvsunM0hV4k5pHPNsch2+Fyzl23q5vnSK585YaOS4yMyxl5k1FD2z2060dBB0uHARcSG5AQ/c3aPuRVi9NLO+2FzXmNoGH3MAwyePe+mU43fW/4zLsi5E/5l/BHP1M/G7pu8PvqgMY+DLxLJmzl7JZxEekbASAg4n1hurLwo02E1DsoE4LK2gNfge883GX+fxLhDh5I8u7zoNgZWA8htFn0+nFrejOnzPABd/I586NAg5XOBY7m22DwbkJrHjsbiBRsAQNoouv2PY5fYsHzIDu/fPcgpsRHqu6X3rZHMCTs8ROJG4IZUtkaL5YkiO1W3hi3+zKBbRlF0/p7MCxCHZRjkBC43If5gaDTJEdL99z68bb/GyLpM6znPIV+raUGVmYcBHpIYn5/LmZP88nyI9b4R2ksAf/vOyJQk01JkAMo4GPuoJUq9kvDaqQQUjaSHUi07fBmHNNd/KSMsz4OTQJGHXNK2WfhPUxu4MddKltj3CeUABKDAea/avmEk+YrwNA8VJke5Di6zt7RZZBFHpyXu1Zr2Ou6/qLnUVBie+yc7d7zf6PRhY8yakwNgnjmm59EIJn1QJuEdc2I9MdoSexzp3+kaqrH8uLZMGwyAkgA6Lb3bGubn8572AtXxnJH1O9Z6vsZYvOl7Y434vVP3vLHJZThhvH7uIJLHjPtMyv1kDsXYs7zGxt4k25d//iK7mYmFdJ5sbHK+J9oXrhHadH6On6GNz0keOVTN9bIp+3R2vvHVdQDWjUZcxxjEnKTzdjNmCcgB98PI59cpQ6azIRDyeZ/2Z5zp6boB5nJoHMCGZfS1OPbwcMTINEpacwSCmzAzHal16FuVdiUDPh3/adf4/PhlGoPk+5gpOfdEXvz66INGegeJPdsUDvX/YvLCK+ybRcDXyEyT0K2E2B+4v9FexBDydRZCvLcJgE16/ybj7ZvRyfyOF22YNB55w26AWjYm59lU59eV9HM+czzT2WeyweR45eeOQznNSRiPNCf1Bc9FwBQ/x9ZQ8r15bntaA4It+C9uiLNeiz+nUSWreW4wIiFChjHnuJ6HjiCJdUiHDgFjZAg7QMieOsclOyoZqPvfI7THzxBgB+ASy5LnGEaCwDB+MahnQHNTADh+aDUvh44SqbYcxrwCgBRLqMj1C5now/BnHDB+r4pgSsUBvDKbU+yaoVNOekqsq39PMtx8fl9T0R2E35fXTsg02Du4pMzywXxCYfpQrhUfO6llsw0BWHiajoHvgRCw57mEjEOrtVGzNBwPP0TOZS3MUCZQhI9dckY0NFuIdaZ5zfJ3qvGZ2EPZnho9MvYV6/gRgFBPSTDMqEv+LvU535Qq8yHYAHwE6LPM7jrmiPeZAWDYJ15Tt7IPspYZMIajmOwUMIC/IP08nRMhPcpAy7/73HblcYhGDomxy2z9JnSPmPOwETUxsOcLLZMknI9zdi7ruzWzy9/kbNqQD23Y+Z6ia9mhzbf9gvMX54CFZwS/4+x+NxrnszM6Otfkz3Mt5TXb6bSWMZ/5zH/BeWzXGPtM3Z6FHjWxidt7yk40tYpnemuhfesxjudhaPGI0uiHPWx0AMTELBM46r01MZ5vCyy//eujDxp9EZA25oKOCfEB3dSGio9qbIaB/nMnEY0FAMAPsBYLMn8/AFsIsYhxf+MmL+1eqZPzST//bF7oGfSSOeHizMypv6xW4gsAYjY24xcpDP1NxhtIDB8SQEw/OzdkNJzJEIe2bGPkZLPgNwA0b7B8GOX7ygaLBvucwSUQmM5qcxIs5uvkcc+Z3UQx0zTuIYrbYoj9afTL2TgQBMVzpOcNhrtsnyf/F8+dvfkzEJTW98ZJyh4/wQHXDVk8kVH+KK8dQbR324T/yJ6pywhyaSYyW8z0BCJcDuhgYfKB5AyfLSE+C9eaPzfnIgOw3rxYtIzPkeWIfdNDD6mR8c6DuxvIXkaZJOFeTmNvNTaZfOEh6LODBIAlAfWOcxYy5ov7hkkjXi9Pu0aveF0b9HAcwOiM9diEpoEB7jQx0Qrcc2D4cJrHkwAPvj+41s7WUrSao5HQGP/xbH6Ysi4eF9BGnqFjTvMBr+l6npkd8x9sOrb7Oh40jQnnm+s9sdfIDleQBWkP075yjeW9d4+ZQ7KJMr6Dn822h/Oc5/EcHMXj+DV53zlhkvP3rZi5TFwkR0FoB/i+c8KD51NeJ2T4zm3x2dmzuVYGstmmv4gc+GbPkL/Lz2Dex73IVR4/noNcM5qzjoFgC3UAL57J5yVroplD/Mj/znUSP/O/M0kqbJP/Hi8AeWkO83duZHaSvjO0r3a9TdjZ72lEQMmqAveA5Td5ffRBY0qAOBd8yvlm2mzKsQA2gIOfS5OYgWhQynkRpwM5vv9cP3C+KfN783XO7xMY4d5v9jw6aGpmaW00E2l87jGU5wuJRXfTtTfGIH6WPC9+R/baz//k5o1DH16ktWzHJjM75wYxA+Zzr5HvyT/PIZjz58yZlC8a8/PvCcCYDhkeqCJbpiDrUOJAOAsb5ftJBb0jhPqiAyI/Y4xrOuSLJElCMtLxfS8a0zS3xHEpfG3h45I0nhiJJWcH0QZYbET0Zwc27xc6rh+hxDUVrLf7Y/vD0GMqEIsoPyPH+e7oj3YGGM4TKYKVwBgHYLAwaciHLpSHhTqzZgCZYdrNEmo67jeH9cQBAwtGZy1h7BNnhDdgpW11ZgTkvSMy8QO4qIVsc91XrlHOEdd4dw2gCEIDG/eiCbC17R4MO4RxP5xPZ46j9NY5u8r1MkZrrGW+6FjkseP3cU3yYOa9EuTRqYl5lPv3zXvOE72uw2nbzEcf351fSX+bi6bHouH7z5m28/Mhfwf/zetvnv3sHHmRPTkHivl6muafjB335Zk93ZxPLyJJ8n1p6paWf3e2lwZw7GMNvsjG8f7zdwaAPNuj6Z4IJO/dC+wszx1TeJZnDWOwgToiJoxaGPsn98LCI4yMFwK4qB3qdmsTCt+c6eOzJLkizJ1xTT4vkD8/frQpw3Nvr33r10cfNPrAbj2OBPzygZg+YxMxFhYnhwuEjCIXETAWZFyGh4b9ckwycB9Uxb3pvX/fu//8XhlJHt80Wyx7M2cA196uY+GdG838XekwIZuqavXI9Nygx1fnMU4AOhui/KJx50Ee/WvT2CYW7N4zZ489P7/qRti/Ccu9yDB9M0M11e14ZFCYAVE8l94fvwzEeI3lrO8tQa1fIu4hG/wc9s+G9JwB4DXbmWHP72UijcgIsfG5wiBjMKN28S0L4z8apYXSdwHYZKZu7k/GIa5q7yOT0bv9PsKaBDnJwXEQwJ7dY758jKKjhH9lZK7LmVMiiIxgAg63FQEMeW2yqLxv/l1Gwe94RX287ZqSVcc9UB/HuYwyJXDAdzb/vFcCfYKOWBc9vc/HMNYf57JBT8cUes9/Ahv2M/aenmmh03P1dP28tjOTH2DOv4t/Dxa+jz9jDfUze+Hft3H6cPZsPa3DF4AVjpWm5/lmAIaAT9Xr+bVxP4xG0Lbne0pkQeylTTWFM93zN7O738wJzvPi9vGe9j4nXJw/V37mF0mlyByeEwkbIDP+jOgd7+dFTi0wwrs+X3Em8TrnQHYzJPxOxHPdz1ZG3E8+53l/VgPXz7x8ruh2bLSN52E4eHN9OiAvGtc8bup7W+xLBnDktbaaxrx/NlFL3uMLAN5G371ZV+fvJW54wX3fv+wLXx950MiFm0WoMTrnm5Ag7GwRbkK6ktD/+GC8f5NkA0T4R88BwObjZ2n+m000QusbMfwLNu7GKzkzjJHllRnGM+PBTXW+ETfXS5soDHRPiQ8ZgJ6/fBOrH17xHS8CxDk84fcmtdp8ppD0eWmZ8JCnuh0j1Y3YPBJ2MuB4wf3GocJ7Oy3jehmQnYNWAJvwxGad4Z7BBLD5+yYEnw6Ge2HjPGbnBoafPRen5/ef1wfLwPxFgJz/ZnJK/v3m5Yf7lJKecomNDI4oQwgdHH+PATJzWJKAujOZIoOHF4xHzJOtgRjnlopZqzpg1Lh1AufRMq1vD/AAHPlAPns+thbVdODxrTU5rueG4d6Y+/9ifvn7fB/+OWrh8hxubB6Ss1CS5KKP8cxMVl6LL/pzGV1McieZeBVnSoNhTJ9PDu3GAclldSJ5zT+Ta/6d7z3ujc3vXnDPeU9mlvucueM9prJQm32foiGbLhwEwrRxTLRMmu24Xu/buZUXfP+3AFLZJm/sbpKV0F5ncHEPIGZbTwCS10HdOsyZgctn7OZz+RyRbXvVPN5RLkbP9IBn58Ow94iwKsc1CBwOnabviYHF5tn4fRspGD8rPOcw9IecAz37ks3+TrjBJgZD1pD3OR0BzkW2I/w9tntpa5zGNeLaL7j+5pXWbn7xPr6D10ceNIY3EYsbyIwhgO1cbbKlCRB1bIpYHLL5jjyxA2gB0VbNfhGLneAtp+dzE7LNz4bibltvbLMY7q2LdBjRoCTDI2cbPLcXAhALih7RxgPMYudaAyxuAGcyDN9UJ5GumcsGxMYka+TPQKN3D7DLGbvLz51pNHPy0zmwt7+Pe7rHTKT53WbEJYOW7z8b+HONawCWdg/0bloAnjMkHPNg3/zFw+DMgG9e56wXPwcM0MFOPC9cX7p9Jt7/C3+viEzprGkE0oH1IrDtgMPLzNg1E2B6kROiGGzc+RhnyUaa+xhbfj6PCZ/lnEXMzCiA0RkpXScDt3yDkYzS763dPnMcOE6SHKI01pnFT+yG8kARpAQMvIDdUTu0qOHNtoufyWAuO7gbluNsTZCh+iYO4mass6yC836uXeSf5yCGdUBfZEvOwWMGZJzX82QWjlH+DK+Vs5inuv1Mfi+vkStB+H1snAx/3yYsen49vvdsPd0DWC9g7QBsgWh+lhcB4BeNXbbvm+uefT8zznV7HgLYRN6C4UsvObOpDNmqr9t8RufyNOOabuO87/e4cPwPmQUkptrYxXiUdCbG+GGc7Qr+I2kPEe+xeRhn89APjjNz7EUgXfwF4JDfc8Y633sJ7j3cBiHj/rnFfb8xGLyPF7DH32ydnL0++qBRt4uCPxtgbLApY9HdBwmkpiXCeNgssg1VzZ8Dm0UzNrf/yjfYNnQA/nLzvaFD0O1iH10HsAWuAfz6YCbT953XZNqGFoqvN/E/Hdim8PWmrtwLx30YvXGfW4FvgNdk6Pnv/L5NiYF0WOWwfehGZDx7BnUZkN0L1RBInt1LvGjAEti/lyXnh9s9UEuW5dx7zkb+fBzzoZnmJ/48PxAI+s/CSBnAhl71PJs63wPfQwlCWjcbVgL+PCmz/969twSs8vpJ36l5nPO6CP1iAskERTnxqfctoMhjGQWU/fmDSZJx73y17VhvxpbgJh+gOcnrnOmmPo+fS+BoU2AdQJ/E5Bfnh/4Z2B7Mlv+MjFxO0klGP5yLfE+5bWcfNm8DtLPEwn8XIdc8n+dr9tyRCbCT1lUOvQPbeobfYs8ZkHtB8lnWCvLb0n0oWbb4pd7/+wvW3qZ7Uv7e9Ip9lZnG9AoAdAbKNlGWPF75rOGzA6OWX37GF9kLGfedndp7tXazfeUzvGhfn5MIOuy3rQnfvz0lgOT3n41D3FuqqACetTFE/Iu/heceP8f3yvbcGQQAxufT37cRxvOfpX0fPEK2pS8G6enwHz/ZnIcJ0IXtP/svAc171938x9eL/o2tE0gwmO8jabHTzWITTXjBPvhWr48+aDTUuPnnhiR08WpsKGAs6nyVTXmJsdDIRIpnAHIjbb5v4yUggE3OsApgS++I4YwcdvILZsC3yd5+AVCIDdKG/i/6wSZDswk3+3UHWB0GPEAnGdnW0+fPDYeme9wygvzeMAyJ/s9ZYRwXjoNMkx9k41nyKycixWfp1cb4YBjus3vY3F8GqXJf/7I1iHbd0JemwyuMfxvjGOGiPgBkZMznw9HndcxxDN6Yj77Vpw5HCJt72Wis8kGZDqYI/3Nsz0PU+bOZgT0Pd/D7HOTlNRSHaNZkjpt58c+A+z2KE6DYsOHngGZzT+p9kP05MpA7AxmbQzyN9waIEqic/S5ALT//Is2v+v/OwMWL2KvN7/n3SOzQzX/3Evzyi4D0zIk5Z7UzcBjh/KTHO2Pq7u3tc/Yslyk5/12+/jmgSVGIzefT3gnHkGDpfAxeBBjP79WfawPUslP/gvHdOqfb62bQk9cSHW8pZbtezu45avnxMz4/vO7mnnmG5ec5X1NpXUYoNz8DxlzHs2/2eR4nO6+s7inPsLz/MP7O9+dEMOVBF3ecZ8P+f1aRIf8u6/82gFIR45DP40HyJMc7Lixb8No7gCFFi/vdrO+zNaQvsn/pzOc+37JKuP/K4IS2Nb/3DMSquowjj+vZWOZz5Jv93Odjo6v8Fq9/CkAjsKFoN5gmgS95kcdEQzH+eT4nDFXnMPQmJA0dXoWMG9iEn2N95e8jqEsLVrABB8AwLhsAxmuIbDdN0jjcCxsHULH70LPnHjrH5KlRi6a2ya0WncYYj+yyvhnbTYkUXle2hjYDslwWZICyFzyHg/1hbLMHtn1c9L5tE4n03P5smblT97DHz3TzuwBYkaiBwUy+CIy2M4ZZCP6TpjYZb83sjd9/uu2NVmnj/MiZrOKMkdocuBj7YLOm0gEaY352GH9THdIZa5FZsA0o98/Fms2MiP9OCCJ4ncwOY7sW7jlPPHjpZGV2LD+L6sa5imfI95nv5+zfm7Hh718UvgWsnmXehpyPfGirjjqS5+AxP+8LwNELwYN/zz3Alq5/Dn43z3kOSP05z8fi/Jr8bMxFmpvNZ8oZW7+Zx+3zSS0jwzXduwGy7d7aRCXO125yXs4P/1FgOYGysJUy7pHOPtdw2z533EdyjsPenV9PmIQ5nnVEiLZdR/hc9+wrgCAj8svHjc9xXgmE9l3P1gWvew9wxvk1HOsNWOPXc/8lTBS/dPsUrNzmjM3/eJEzpJs/72Un85PioMjPiHtALp+/598tgihj8/9l729irW2Wun68eu0HTpTAExDOOZzk+BKDRgNxwICXCSLIS3iJDoSESCAgmmgwJ0I0zByBmigTJg4IRCDBEUxEImjQEED5EUnEaNQEFSJHjDk8ePyR87JX/werq/pT36pee98H+P31fnbn3vda67q6q6uqq6u+3Vd3XymOACekSvHHDWkpL4kNkcl5CeblFnlcM41dnk6WLu6v+tqBf5PeBqDRhxFA/atj8FHjVOfUzJil5Kh+ap5lKOwUpaFsg6LVuCNNYWeHl85vvOIReYySwEcYy3IACpxSMHH+ECjmvhbgL71xhR3T+bjR8vUp7qw40h5wTA7AtohwQl6PWeiw5AVvNxkvUa/rbFJX3im1GdamiL0QemxdjBHy7COF/LulQEnZbnqoj8XiUY46NQfdAaAs7COAJ4LArmd/usxBlvpdgSwfKCs8xICgmTEheDHwQ5AlbV3WJqVRbdZLOuTWLAYiXq48XorZWK87g++0NgpHYQS/H92zudEHy0h8yzE5u2aWZXc5FIAkHq5pRo7p8lExSAEDIftHcB5lV6/LSHCiPDqQYfsIYNNZ+wRIBDRzJoz6iZ9r04QumdBjxFRfpvYCXmIWKc3I7c0Me4C0fV0Mdu4FYNFHWg6jM6hzPwUhTa7vS8CsgND9xCJ8DwBr0vnYdWYiA19lbSH7cLg+kU8AdDwtcsDn4NH9qlmmaYwr2X9nXSvb7rsbcKyALMIg/Qb83uwq2UEgJlwmZV5tth7P+iA99ek0wAtnbMbgMeG47yYf1MrM5nb6FhNaA9ejDpSZE3T8lvgDLpVJPlf4lEGhDX8U3/jBJr0NQCMQRryHc+bORQVKUEvOsjQ+67B9L72jFQ0XrLjD2YYR0+xKE53SDTB1CFYdxrwNcO8Wx+6+PL2Z+EjXopprzZr4VMA7U3nzkX842pFkTY84BkHgTffjYY/y0oveXUVYu+NOa494r4npPbsrjn4B4FjHWQIXUaqrG+DkisDFA5O99GVU5+/keNC2GQYF2NmXdA2doaLtFLN+nVcu6t6BAXK6rp1kDGwQLF1e7xdNXWmwbXabQWtmW4cDmaTmCpBjmYQD4ATSLW0mS584uYCzp1GWurctb7dJLACItCFn+G0Fn/m4gXW1I5R9sHymWgcCASS1zjIAg6+K2Siv3zetyUwUBwwOsKjHNHPldcw9y5eApwBZC3vByQwOCqVMGYg87rfzpMfNu2FKG21QlB/1jssln+5gltsR7Ro+YTYDXfR3M9hXAyy3frOtdwOcvI4u27Hf9xnP8AccmM25n/IkFe12Lk9m4PtCjsY/hS8buWzMlq56k72t/Dq42rZi8XmT5Wr0GWmW1fMvn73ngKQexrYA3A6IVK65Y5Kt9rlc1kDHQGtGn97Abe56DfdM5A0BJ/imnYx9MkSU1b7jMT4/tUn+JIHSreuUfNPLgD/gda/jeZjx7QAaAfiSYa1rCRRKtPP8YUgX3HdjgSHl3rDp8b6Dpm7aGva3e4d3VueDo4nLNl7WXTqJOjeN6gR8fol8bTCy186IDjCqywlypeCjcu6OuZ2XBhcUDweUD2zfgQr5IUta53ils537vmHtY8igtuJOeW42fYE42rt9CTzVHDs0t13y0W6dZbjpI80gx/DfSjNO6m4gkFBf7qsc3FFvoBlAywEDj+9gfcNiTRGvme0gNB4eLGZAuzYzruc16Jus51kCB+9B4boBgwZk8psekUdwklMXzPKjXB/QXPJRWB7At/4k2CA9vjHqe6ATGLyiTaQ89BHrhR20AsjFBoaPfrTMNHLwlN6INfKBxiFvCs4WwZblaLOhj1hnnPVIvScwI+2UwVvTn9a9AFkCoE6nOezZp70m2/VpSydpLfEUXgRwp4E1dBwDh/WdoHY0+uTARm2w+IPpNLeMHAgmwCz6jFlPB32DA+k9INEnOTd9jgDC5DnWV3rMDJ5kY0kCdjcHs0E4HeQSMg1KEB8m6NFvCWDNccZwf25750kJBP7u551X6Gi3ewaOIW8CsuJ7k50IENTvY5xPEPA6DHmTDO4bBHxSVtXZnfQ2AI1m0bjacETdBWbDIM2WcqF0N14GBq8r0R5rPYePwtRIYMh+sLCCQMUNmInKDQ3DSTx7HWJcCbDKbJZ3ana49Chw5Pw3xnbZpEc+nptgkR3YAdiwpGsGQcqPDpLWME4DsLXo4Hsx+QYiHmzTTK5/5TmEqw052t+zntBVyCt6MTy6dyfoINWP5NGmYbb4PaGr20c+QNYDwi6URv8TQYcBgGB/8eeBRmeafGYurw9DkJ+oJznuXXc46Gl71tLlecAaMjHTdh0rrveL37Mu0tovXTc298yuzojpY+xY2oITArjWbLdJExRWujwiXxDOoMn5TMtZohhkc8A48wxZzKS6zc46s2VmaYY5Zl7YL9h+fLTq9gt5FcQQQDmdoKVHT636YlmBk2hm91znzJtmeJ0c+nmS+eJPMPY5fWUAEUHVcN8k4RH4tLK2mzrgjuOtA6xx5JMSz98EdD4u9j6Y+h7B5uQgc+dPPKBtvQ1Mr2UOREc7XzyZCtMn8M3xYwPcEbrB7dQ/8yDsdnNcfAMHY5mh79anNJGc95gggBMm4GL+0I0DuJU33kmOPQddnJtXi0P5kzpn/x006Y/q5+LBeSKuKWB1pvY9rbk+pbcBaGSQBdgrs2LaaIzYdPzSga+K3rv6Fwtd5yPNix9ILUaxgumewRnh7KKOK8Gh7bPkovIhRpzBReLfF9desebiVnmjmyCw6asRJjA5wCvBpu3fUZdOu+8Ava8hILZHO3jRaz6GxJ0t808LHvVxKp3sDt5wgGnkSlmoAy/ibahOAPejnG2bAACMgHlFfdNBvTj87KdvX+MtJTfecpDNR4Iw+KTZPM5KEBiYgx0CDwu+2WZpOYBZXl/l18NUZla5A4nY8ZrvZ8CcBx8JrLqekAh8Anw5gMbsWt61umcIee00in/j/31Mduh86mP2rU/wMKibbUsRoKNtDLzK4c8C7CdsOh4nEzQJLVe010mw8pzHyT44yOvJ5RgtB8LUs9MnTijrETfISI9VH/koMveRMkASGdIJE7TNyGAbiKQmlY2FoN22fYnxspzK60o87hM8HMw7zVJutSdnV1MGt63otOu/FDLyjGlkdQDc+NntF7c9ZV+K5VRe541Y+M/ofyHbFUtcsg8ys3yOqIboOW90yxPEWY/S8smAqeVs54tJidXfdWbQacUsJPnQ2Df335A8YyCWoVzoxTFJB+9G/jzilnN6G4BGs/ROVE1DlGh2UzYXr/OPhqyI3eS7/xbnLB4Fv+cuJ6AiZmaCnm2ac25D9HRZo68UJFi38EB5uTiXIzU+Ui/yZKcIr7Dvu0MMXifyKFvSXnAc4XSCFlTH+wpw12xvekdx5zSTbsB/CqAj55VZmS0zdEHzSwG9CT5wrHEx+HUHu/TmIDwBLKeNChG49oYes9igEzMGef1i6FEDKgLIrmbx5g49AfKa34FKgNuxr6f1luagx/UwM98cQJGXOWPzz16vZrvpkoltemU2c06bH33cnwTOtvW4VZ03nHTrxd74fz9yO6dxM3D7TCck5M8KSCEnAL2uFY3NRhNtIzyGjsewAohYp34f+61V8/GxgK15xYYilzOKZvCkj7LrzGCeLeQa5zSL+sDzVL1tAUZxGHXM5mKNW7ThCs7+KDaC/YD+gxnwUY5dsxioOQCkntKAd259JBdzwXKMxm/5jKvONqe2mhZ2Fm2+9K2zo2nWT/3aItYvFxiFVvCcaFn2pQGY2Tnnrjf1S+/zzOP1uM9av68AcjpQr44304nv8kQmyiK22JJNr5FetJ9MNpEfLqUbwrfzGQNX51Fm9jX2xT3OvJrI2LVlTa8/aHSF62j/nvG4YTtQYQMq3U7RxbAtN06uKPPTjOi0QffmFs8ij75JQDaCBB0FZA8PmMmK3o18xTvuTuvAJwzR/2PH9ry4TzCSHqNnHe0RMTvJFKArxQrPCOjrjSV+fuTWxwRf0A1lSJ2eenUVzFyOtGLRt/+J3oJB23qdTtOdifAUO/AgQ9AdWzdp5mBCHD4WkoAYgjk/4JJBTe21TJVYnyKQrEB/yeU22FiBlCC0AM9dP9dGRfCCU43gO3bAzHQ27bTWy8rtzNOixXWa/K5p/NaHQwc+GJwR5DJPnH3VzSo+q8Z1pHFvUgebjgKv2GThoNJB3GjW1ToPzUaQ27EmI/GrQIFvtyoAB3WVFwisAUACD2KvDsi46cIBoc5OJnm59CH15YH2AG/R12zTHFuXOut98zv9rH/7nd3Pu20MCrYcnMHM63vxmDuZX/VZPnDrQGxxTwBq/nhfZ1FTGXXnTlY3u7gu4z6ecAXRHAt3HlTcxeoyoKdPhyI0TnqeBOD2WvoSE8mnXuv4UaCmsbnxRznO41rICLxCAK34g3V1mOBOev1Bo9lNGbrLj0l/Y1H5Du6WG8CnkJMBYISgSJ4N69euj2t9gwbZuY3Sad5u2AZPYrBpGz2u6wxM4oEdcmdJoxQF1SznvJQdagAt8Zs0fcTOzqCmqK/YG4cy7ky8KrRzyNY4hJnPN0tyJV46x2C5s1FXBG787WVKp9Y1rOLIBmRwpxfOtbFjte8oI1EomgLBMkSZmyW1H/+efsrMCoFvDB4aVYYt3vKmR+kd2F362GsXF3CXoJVnaRYgWhtvzGwDvWnp0OG9xs2SfvaM0xJljCLvnomynd/1r+rzUh/9iPnsis6UpbWXuBabNJZ+fLZLZzMTUEqVWoAqfYTYzYZyBpC0416Ye968c9PzLK7N60v8xOBI+CgD5c3roB/zrrvaRmM2Z/4SMEqDMvK17Xdvirlu+wi9jCJLAmGpTukDlJv8JMWIrtwNNLOYZhv8ck2wHpVjHACl0zdkM5QZbFj0GvllrTraoTKY+0ye+bTiZ6bPDg6/Ni0rRI4v4/3Qq8ShKC4+0nXBvOr3NH8Bb2NP0Fxlg2CKd0rfcjwodSwMkOq4kyawC+kSOHfgMPnZ++n1B42utMslK5KzZCeEfRq1hBPw8pf7De8dSxbXp5m9BMZmrsPp3G7uTup5E18Wb1YovJTIlTwWjBubK6gns31Ph5MncJHo6717EWWvZeLxG3RyuX678c91bKe6BhZPp5nYJrI776pvb3fl3dtRQZjfV9bC+Wj0cREReJOO3ZYB2AlKDfWXOlFPOFHWrUHpZlt7JmvL4Wuf8tlwJXIsWhnUFF42Arld0h3s/i2CG/rn2HnyxoGxZxwPzetMpDfpeHB2NrEuikcsjeQfZgRYf7vC3lST5Tez9Aaa/Ah686pr2XS9IGdsdINLAMcG8G2C+DMrtPxaApladtRyDqzTLC1tDWYfs74EWeEKt12xDdPxUiFczqM7+Mu6QC+mhz57/cPSY/sOVC/it6ZPs2d7ttEfGxc3I3pI16CD2hbiS1d+1xtBeClv+/6W2/ZTl2TLI/xX6j+BL8a+IIOjvBnRNl8FsFU5Eu3lf0Z5ChbCJNl2WSpX8nTtGGvoKSQ+PQ4quJrCj428JCxwQfNYWPsTNzXyM/zZ3C+PIG3iBt5z3jhjnyYzLE+QXbGE5E56/UGjWW7wNBszodyVyghk5sYjMAgjmrkxdMbHG7drvASmosfd54nXu8WuCTyI0ZsYvddLoOp86LqJ4a+rwjUG+A74kE+dnSXYKTNut3L5cWQTpTo+0uOkHXSon5ilakdedG6o/wh80anDrrD+Mh6jwPGqc0k6a5wAq2OdHMUGwKR+O37BA4MkdTr9c4P19BgyzWTM2vQY7OyAudstzTS0aaTgHWqh/iQA8WDskM0kgEEHsfPSAQOEiMf2nPmj+S1AkdYdIm8e5BweUfPpwLQAWGnZhPN5GNjGLNq0AJQ+k5p2o25mYF7SbmY4lHqW7pjyKT+n9je5blwSYtuupvWADiA0me/Y5Yu5B92Zryuf5ffYu/dXuXL4OPkaJDKzPj08PFzClkrdykOKDZLH7SMtp8lyU3/pfMW0cRBfccrAtpfLbr8Sg2bSTWI+2gH9e/WptD52iKHwnoDd+DHcRpoYVQYyJNA0+jTERvGNjN2K7BXIpbi6rl2weXMIAExpbLlHQ5sTRXq2Y4kRlvOMIa+Lpd4s64uYxL8/I70NQCM8ijaKWVZoFBn9d6ejhpvy3itr22B9xOCfarC+GcfLpNmqbg3buhezmeJhn+pM6iS8TABuCciUp8hKIOUyr3qH8uSd57DTqxyZQK9s+VrMOg3IQye3dBAyiANUUJhoLN6dz8sGhXpAdiaKFG3AdjtFP+UBjmV4UPB6PcjAAXNUfHTw+Ex1rZ+x8zDbix8Zwh20xbR8ds1sB8zSlXC92M8s/GwW5uYP5bwe3zBTjuBZMpY1jxo7LhLk0Wx5NuwA5jzAO+B5uONmhUZaw3iRXe0H4Mg6dKfsFHvmY28z1+GSbek7rdczC9Aaj8Sdhs/kdW008VjfbLc1lB3Ai4ODueh7eZ1R87boQJzt9k9u4QIw6GUZAnzGF7KkJQHhmzf7aVDgdQZv+6+8LlT1ZMifgAjurVt7plRk5yADuimz0HPbbwb5aJs59xvAkl+6/ZX2MNC0XcbfQGU2e/CeCHg1o9hIjiNj81X8he08WTtCk0yM/EfwxFgwEVOdx7KmEfVrDDGzPk7OGnO6GUGfdEmPvb2sLsdq+PH7inuSjIfyTdKX775+6fpoBZCUGZwnfp+uPZXnWWX20Qhtue68s6fqfmrdg6bn1vGxpKfozWdMif92eDrRv1dvacf7PPbnmD2T9seYfodbSYgv4HIQK9zWY6MXPuLo7v8Opqf4O5Z7BbqaV7HxiVaicXjsMz/ykbbMXf3e4emUOjpdHc+R5cm8zf3yxhRf83igcY/uc+6rvL/dep5T/nezP57s3MzMro99+xSdP4NWU+456Tn1/1+TTjG8xQT3Ysgr+r5TDI76gROegwO6fE/G4ue12dtgpvElvaSX9JJe0kt6SS/pJf120wtofEkv6SW9pJf0kl7SS3pJT6YX0PiSXtJLekkv6SW9pJf0kp5ML6DxJb2kl/SSXtJLekkv6SU9mV5A40t6SS/pJb2kl/SSXtJLejK9gMaX9JJe0kt6SS/pJb2kl/RkegGNL+klvaSX9JJe0kt6SS/pyfQCGl/SS3pJL+klvaSX9JJe0pPpBTS+pJf0kl7SS3pJL+klvaQn0wtofEkv6SW9pJf0kl7SS3pJT6YX0PiSXtJLekkv6SW9pJf0kp5Mr/+7py8Xqy84N3kJ+swvGtfv1ytePH54AXhHk/lt4MXn8jtoMY9/v+x3Qo7bC+Bz/c0L0Jnvel06sMP7M+fWUcdfkuEgayvfuvbkW1njbfVbhnIfspnhXeIz53F9BT3oI+5JHdT/tcnj5Z0NzzNM9ElZUbfXYSOLSpuLNlP5G5r6WcriflK/6IrXxlhft02PMWxeJ9QvNJMMrptHs4eHTH7lH5dFj6IpazZtXC7rvbVic2qCnVpwb9eHm0PkcpldLkmbF+iA+mn6U9C3Gw82hs3H6/6O902PN96oPIZwo+qeutBraDubosdW101dXT1Rv519ZdCdkseqnu38PbUZ7WrCh7GuxCRpNXZ9VwmNcVFG2E+y/VSWxr7L3tphStaufVmBZT9a7GyVfXw0uzycaUufTvUU22rkKe3d+ZSRVZC/SBugTsauq8shdaUE/ro4o9dSfKav9LZs6vF2nZ3OzCK2JP5x/6p2Ku1GmefVIvbqu6YZr1OM6JwU7LT0SZHD60q2TVoPZs94/fTrP9OoL/Dmi7w7I2MjsbGofG2M8nLwkWnRuIKfa6530llOSwAo6nda43Yv1Um+cF0N0OWmTF5+LPBI/lLnEWNMBgt5guS1GrR2kCgnwdnrm9ctzyBvpCf6Yl2uDwXcrGeK7oIXl/F6Kzrt0O50TrZ5GEN0uohcqSvU0QJGDR6i7yF1ko/4LXaiAeJ6XV/d9mwH77nul8GJZbu1fDu39wQ4mjlPBJSbvm75GDyF/9R/18dlFHoB9saILnNT0RTVsm96kRvh+XiN62PZ+1gyBxCg+FCrAyDnowOYicekvLG/dgGU1wbKoI6kx+KfWBdoKh9xG/zY2J9hL9E5oIv1Jckodhffb9fn42OmE93qsts2iSH9Nfqq2rtnvUrZqodxEVltyDXIlgB5B8TGrY2Lv3K+XVztR0NkdV9N0CFGF/lBm+Kltsz2ns1r98Woh3Upn619gVfahhnijvtla4AWbYW21dmwCoJ6gt7M17Seea120/YZ0PHYpbHmer39dbymWIX4y3jc4Q9PGrMV/ClO0fwtVhHenpFef9DYpW4U0QII5L8HNP06Z3wUPGlZs1t+nclMiXTYAdGx3eCdnsqkcqpRprxu1GI8Cka7kYqO4HSGhjIH8IXOAjiJHKFTcQaFP4DCBBQjk21HFWgD+ZUukAVl186V2vwq1wHo1HEmvho5yW+pawjPzidnHGe+l+QSWS+NG4gs1O1cgEocE+VQ4Jr0R0fp95A3+f51LwYPDf9eJWenhtlwebzaFjwbVH8Bewu44vdNrIlP8R/O57AFEuaiO9JnmrX0eqGakLug0CYVgNL8Dh0zgFN4tE3rf5wF8DNcHrHpyExhlu0kM1bbxPXoM50f0npgX5eLVbBo+fc08QdOk/Z0XYOK3AbTB1UO/gh6yEqyUfCQfAG/AniEzwOxYGNmtZ7iS9LNzH0rie0xYA0Gy4ABMSLxxT7dkE6/1Xa1bRbP1w7Ia1naKPXf+RjIErq3nf8Ul7sYX/RiWy+aOCt7b0ZQMcYJIJrlCR+fJWQ+5e9enO9mJJWe+KdTev1BYwFqo1cOA6d/v1x6ZZsdgB4BSWOEmtxo1SBoxAzKdHqdgZhZAY5aP+krUNEAVPhlQLrTMfz7aUaTAGt2hupGrrOXIkcC+E2n09lLBTats5Xf7lhDxmaGt4xkh9zrnOHY+kxAVPMjQNFxkk4Wul5TOafPLIrzSHnI5y6fHjGngEO7mEZ/XoK315nuESz419u9PdMDugyqSd3T5pwbCAbtxVsxpZnA3K3sCN7iN7ub318MDNr4GAFa55zLLF2O7G5nDK7mljfkXoId+5nIdhrs7R+2FYZyU+hxlr3Y71jm0wV14SX4mSChSOPQb9lebO/0KfU4MOPsfgIX07I8nQ+w3QYZ6d6+xjIeL+f8rwwhI/i8YCBXANLA8inPC1/Szf5MpctyN9lu/YU2ovplOdZF/qGDArZpp9qmJnpIF3c9jJOpfXAv8SPl2fY6g+wDtyHtzBk+9VvJXhYPFwH7GnN1NrYbfBdZLZfTPPzN+E8fzUfaJ8B5L3UznB0Ph/T6g0YmB4xPrTvoGkKNrWt4/90hehpyl0dp6Hd1IK0hzt0xKEvKB4O7Pi7aKMOO1c7qNSPDp8CkJ+rgNEJKdS2ZdRSpfyewyzq6fKcBBOu+/difsb5K9UPHi+DUOX4Fp60DNXzH76hCg6DQojNX55eChGW+XUfh+JUm9OF5NI7H5wTrKot/9boOAchk7WACIA3//o3tmqqewobbEVXAwG2yBtLyTOTlssDh7qdz3h5fj+hT/tfYeVrTtCphe5UiACnMkJy/6Ih6Vl3R3KJvkn7KIJ+SL+qU4Kv16sCn2L3259P1JCxoqc/s6G1/GIOSdqbefb5Ux0FtkJ25bLASxiJ6yGpIInWAjECn9N/d9tMHImaWwC3tsZ0MUd0+0e7Jnjt6Ha3R30/gyHlRHzx6vrtlVVHthF2vPJzw8RgY/rpZ3tABOqfdzejdS11c7bBGp0ut9x5N5i8TUFI38z4jvf6gkY15bzTgyYMNnflTs2qsh4kjOS17mv0zy86l5QHG40AsBbp55o2bb3Sk2Y2eqLsiN69hRi6BOchweTh0erlGXtwhBj+iA9ZfRmWiMw8oHZg+JXfS6XG7QV6ndXCU7SMx1j1S9uQcU7CTIJXsR9dM2f4doE5opRH2Rb43toygtOuVIJl4o5NCOzKA3VW9BkWtg5fGtpfh8o6cL6n6VnDPKDrbm6cAfOOWPwFAL2tmPps4Ul+63ff1k1HPKVjEYyj0zWPKfW3wERb7TJBQvXGjmKEfgL8YOLCN1P/Qh018rLYaq67UXzsbFRqsS9s3NSZpqK109GAEI5ef7SNS2uplmWwHENTGyT9/qw0P+BHLPitYw9KjxJv6NtJs+hnvBYmuzwqtpAt8DurR+Tm1i/i45PsoJ66FP4Mc9AHR1+7M7LVAqelb7D8xYaIDOfDmEw2MVxo306QGniJ2sZm0TzQ7v3EvtRMClnnoyjwTOL7+oLEDQn6dqUP6NJAEvCTvCcEzn04pn8rQoY1xmBWFU3cgpjLrbwVoJ+Nhh1Bj7uQjnZi5FICSnAF460ZL2ll0raKPBNt1opAtgGwwXNtvroBQHNu6F8GkaS86TB3RtSNVBj3S6ByAB/3OWdOZiWNMTpz8sewCAqktkH8Y2k+Cnjv3Nphs2xxjPaIlINHAmfrT4i9UTMd7KzvwmG8EMJwZ+BEsRTC2/Cn9lWBwgp8pfdwfU+/1iajLfyPNme+3aaAN/XcZ7IgtxUBk1nqTf4tKRBfeb/2Ct63fl0BdApC0YQEPQ/LKdyafEUv9Q2T2snGJNgdw0IGRoCG2HnKJfUcVtNVdboNL90tdH4O+S3818bvw9wrAgxd9RKpfNP4wL+mvexPfE5iGHC3g1vb0IrqcIceVvZQDdTqQCr+17NlnAEtM9d8qJ+TT2ELbUN0SSEd25E9P60BP8cMJ2HX6IS+nuKqxOW2YtF2/1tmBRI3hHa9a/1NgdKXXHzSaWYA//25Wlevf1elwvSHpscy9kYF+p1Eo2OjAXQdmw5FChmMAstv1y+VsdMzv6zjVyHnN9UL9OYDdirE0axX6qY4FTDSGrKM6jDKLbmRXstLkxpfkmFyf2IhDwK4OLhav275PPujgYsChu6Nnw2ez9pD8ESiWRfkqt5cDD0HXmkAzU5EcTFyue+5iy8Fdw5svkTXxOLNqws7B1nWX30DJN62IXt32htlev2mgOYPO3tVtQqNemte5weSwBSIvQX8sPzMuI8Do6WiepBcHx96W0aRNGxivK/igLWxdjIeHzePlgr6T26FucBE/cRr80M8oSEqP+6T9Lw/o27LO1rONzGPk8bbVtp9NPcXWB5YADNBhTKC/En0kECX9hu0Y/WzmDAF02KfBm601uScgmdJsbjMGGOhrP/E6xRcR7FKe9AcdJRAGWxw4ZqsbIKdJEMv+ZYqO3d9GH8asvMcFv6ZgiynFxRCw5lE1UacamzWOjktd9sQ6u2VaigVYV5c6rMAyp3KdnK9Sxt4OoJEg57ThxBM3vvh9XwPpIMKvdWvhFHSS1lOjCrM90iod2BpDGrmjlATZuEPPaZWOI3JQ/sSPbA4KHsdtpjE6MBxlATaQK9ESnlTHqYw4jdP902wHZxGVvkFXHOXGzIgH3pUlrUGTgK6OMNnDQBxq2rFztFE/HZvMpBCcs+4u4Gs8Ddm7ug3XGExJp+G3OGZ1tiNdPoLfyHsKomgrp+PtNPx+YlaKSp8LXiyrLsjP27E869qcN4AW4HJdC1KPjc/wgO7B0PA9+RKIrUHaVCUjibhnRWcC3Jp0d3emrQF+5N/x/R6omJLP/Z9ZGgS2QXvxHCAIdtqB2dR3mvbmoC8GRLQPKZv6Sek0W6ZoNwc7Bh7N9my9wR9fd/5FM59VCnpdf5LB5eCGmkTX2V/ly0bDxpaSn183WR8nMZh/4LsM1jJBynLo1zrR4sercWby+rjzxJmPl+zHtwJEN008jCeM0NFF6qS8jN2+7r3DGIoRugmRpDfk14kMpXkPb1B28v4UyG7S6w8aO9BFA/B7itb9fnscydgA0iwbsI4oSJ9Jd187zdRJL/l+CqbsvC4fDalZd2ENH06LdRCUcPdfqsuElgQPrafbqUzj1g5iM+u4q6frlK6zstaL7ai6vqMT3j+NxDrdp+/gMX0yqDR2FvoYUocEDgWJbO8QwWd9m0d1TqPM+qiMtsuFHCLvrlA+9/XBwVnIk0VK1zuy6T55maAj15VOMl85e5H8OrCR+vO6R1vq9Rk7S+W4XhIEDoLBNjxQM6VZGPAQeRk4BAAN2xs/iv40gI8os21w7NtqEwXQ01+VxpV8jX+Zmkcvbv63TOxXXXnwFewBlClQ8M9pVvWqNk6+5VqKBeu+txd8e8z2ehuHytTXot8Ob9dbv9qz8p3vwAHqPksekxBjy5lA6RQzUt8DHSogIc+tL9eGAr3wTfK0z49YIkgq+wfQpi1922UVlNrcy76SnxpZvqSfUa950iVfjFkJxF23LPxUkFl82ei/F7A9Ky8dNnkivf6g0ezcwGpo7UyP1UYqNK+1gTkq4GMYL6sAsdQLg08gTa4pr08BqNPopwSAg7ztjsGGH81DgE0nxk6kM08tDwdDV/46MBTXqU+mcZDDHbg7SwQwDSA6E1vaYzS8c12QON1w4uDRcI1B7Pq4aejImcc7JbDAIOWXBUSkwOqOGrwQVDElO95/db0feIjrErjS5YOdOE+hEwS7BNJN6moATep+EnzC1Jhpk5pzb5zxR9W8pnQawvs3ZTLbbRJ8o37POwDMm3xltjGZlPiBges4rzNme1L/Z5vBtlpwLDzUUYq1KcB3plOXGShfrGKguMsI3tW+CPg5mzS8nsY3pMGi684QJ1jnCN3ONJM1jt0gibl44oxyz9vY14uPmgddrR+pfUela5Lfqz/5rhRzZr5H+qFrLKtQMKQDbt0YSLlmM5GjM3Rz7qdmKY7g8XfELCyX0pjqn9x3oE8pKQ95CZWNvLSOeTuQqnGHk1mnOu7F7ia9/qCxUzJHEDRA/nk+Ve6p0ZjfEb0+Ai2zYiPXr3zfMvV8uJEqLwr+VDb+Jh+U75RYbzdaSbOyjZzuACiX8tzpgZ2Tm206XbJ+7fBFlyPzpDuwb1+En+6R+aKR5EuF9qcDu6Jn4Z1BSO2GZeLezOe1EWAHnwPVIMB1KUDVzPoyg5OeEO0qeWzzQLmcbT9LjqC0DNqkeAIx1vNPWgXMyoxUiXneR/wa6nNaWuXA+sXLZnbOGX/MW3llkIZ+E2Bn/zDRibV9ZnbLLxzoMKh6O536vfqT6I9iC3pcTVpLqjLjR5r55qfbPn+Dp/LkwmoeM+jcbYF+cikzvT6UjIqfuDcwJG2/FiTCiDJ/Q9uXfdT7iq7bbJL2h2T31B38gs84Xbm5TTtEa2y7TYTtWm59jiFlzQrIUkCa3ujktNh2QpdJY/u+sT8VQI2RZxdPTxhZxgztI30jxRGJ/+kpJfJ1sa+Lcx041XrNcj1Kvzsdpo0xNb09QKMCHP6mcXQN3jVYcZyjX3+XysoUe7dtX/lVYyzOY/QNr/lTRxhZDq0/bfxpZNXU6YsdJeUl0G3qjqSB1gNIw4ev/XFAezcpTywjdFU/Nup1Tck2upnkITN9zgOdH52MXxaHmkAcg6K0d9D2/FJvuUaaKFece9O++vYdBrIArA7cre76TQB0RtEtu+pJU3ONPISP7zbGiOyBJzwwYpawYcEfScch3qtcvE3mqYX5o7nnIMQDegAM51v7yFwDEtWr1GWGYDJzYIpmpg0ov5es1wQsxFeWQYPrm7xvsLkHEgQIZnvTlwlNBk/xvxf263t2Y+gjyq/wwvstYCT/9IPshyOXS/JMS4DerPFpjewEg2EzQlfFch+VDgan2GJjTOrfOcAkT8pbim06uB5Z9gd9PCy2lQCkVV51aZfzQrtXn949RSMPWpfG7aQP9KuunNJQ7NGBQJ2h1PWNp82+ZvcB5L22btLrDxq7swhjhCUNx8b2pCBA73lKo5tmqro7NLsDYmWEI3nDUEFTO+W9EUM3E3Y0mpnBDzurgievt1vbGfk5q7BkUz2d2oF02JFjfctly+ZObRx0UkAQPgvwGlWfyfFYpl9AswMR/lYe9DfAizX0wha4g9q2o9TNS6zXvys/ChTTLAuzUicjF9cUfK7/sNA7r6tD3cN2/4n63L5t6yToM9h7WxvaEXzQJsg0cUXk2yoYDw8W76xe98dl2HjYACod17MOA+ch4emtMVJVVaDa/YTsnn3UfLEMRtoo8tv2fRQ82kXrTxU2+qbN8PpJHrHTuHe7f3v3NNPI7Uf+hgy+Em/+obzxGlno7nXy0Ci4ZlrKEiB2vCcQO7KqUpuZpNFckzrVN2kbsu+nTTkgfPd94fiMIpBX/3TQH2WbvsBd/dMswKjGHfLhZS4y+D9uELWDbijLyD49DRDWdcYg7dtTeD3FewWTXUzV2OLXGf+UnxM4bXWw6D51fjXSK4PGf/Ev/oV91Vd9lb3nPe+xMYb96I/+qPAy7W/+zb9p73nPe+z3/J7fY3/yT/5J+7f/9t+mPB/60IfsW7/1W+1TP/VT7RM+4RPsq7/6q+1Xf/VXU54PfOAD9vVf//X25ptv2ptvvmlf//Vfb7/xG7/xquzekirdd1LfGL593tsi76DvBBi1jnnNG11OyJ/3Tjwz0BG8lryN8WpS8OR0uB6TfBN8Mb8aeSdX5JPA1T1WSvJ0HbDr3FZ17vpJQLfZkeb1qE6ovwBeTSdWANYdPxSfosPihE0Cue0y/j2NVjmzyiAwt247O+CbIQo/XQBoeAl9LGeuuiG9uE0nP5FdgrKqp9iE5XyJfmfzHdDQIKBsafvZDdwm52sBIufjtVYfsXLEn8tbdidP6LIAB02HADcbHSZmNt+JfgLBLCx+h7/V/uMRtDZKE2wLf2pz1sjN+hr+CqCDfAXckj77B/3mxL2GlwL4Fq24PHac6GRhO9HmUtOKvlP/nFZsVWWflMHydV07zYPe20kDaX+VI/EyJA9lUHrappZ9l/q/56Rp2V+nN5/JDB0nBIrcs1/PGCKMGvfUf4+RH3UXXkUvSu9euY4GJ1nIn9InONTJtGe+d9rsYwCN//t//2/7E3/iT9j3fM/3tPf/zt/5O/b3/t7fs+/5nu+xn//5n7d3v/vd9qf/9J+2//W//lfked/73mc/8iM/Yj/8wz9sP/3TP20f/OAH7Su/8ivtESPNr/u6r7Nf/MVftB//8R+3H//xH7df/MVftK//+q9/VXZvSRukm8UiWtfkYKQ7aJv01LjmtDpT1/B0u2lhxGVksj6vV8sHjx6233fX7i2+5UitOyqgM6pi5GJKqbx0KMrMURNHyTp6Yp38K3SX49DHE0N0W0aukjqAHkc4sCx0k3YFS9uF05b6ORhIsnigoC1M+SQ5l3ngD865ncFmEKOj5n3yIre93hK0IV8XbMaQgLPBQewe1Twlhrj+buciJl0xnjqPA/fGEP67637bj8/Z8gX4S919JPX5GZB8DF82wlC3DuKiLTQrgIMCHqc1zeJ8SoKcqFYDtYEmvh9BgfhHH2T695RmvRavt4POk93BZqGDNCtdqlGb1WvuD7x93N6kfNhxY6+JvvMAnmLGTmTWdb4dQGtBUle3yJUGaeSPvEtH4EamxI8/HeKTC/Gnxa+4vKyXPscO11RO2/GHb9lK8jBpTGl8YmQd+bPYisaelXjEXinX/PY6dBKjK6exjX1I8zE2dvhCy5zOlPaJIH1RSTdZ8ow05vHk2WcUHsN+5Ed+xP7Mn/kzi+9p73nPe+x973uf/Y2/8TfM7Dar+K53vcv+9t/+2/aX/tJfsrfeess+7dM+zX7gB37AvvZrv9bMzP7bf/tv9t73vtd+7Md+zL70S7/U/t2/+3f2x//4H7ef+7mfs8/5nM8xM7Of+7mfs8/7vM+zf//v/7390T/6R5/k7Td/8zftzTfftD85/oy9MT4uN4ACohMy199d2V4x+x4bTe/7tXs7nE5nMQZIaByJypbKyL0yI+rOA78J5FQWyqRJ65tzPUK7VvmUhoLyp4y6k1VluF2wojPV44lm8BMZNk1/RO66anfHq26Fn9AvZgC6gPpkm4OPzkaoe9JMdn8vAHV2P8yujzbeeAM7WQfISPkCrjOpm0hrnSADcsQc6Olol/wt/Pil9WU8POyZQzMbl0szM2hp7aL+HmMkkEg51hebH/nIvv3GG/s8vuHlFWiAdx1olIpq1hrEoYeT/kvb4ZqeFDENbeFKOfSRdjAg9puS2Frrl5kVPKbNWq4v0UP0U62q6QMEnTJASDorn3b/OwczLbiCnNr1ro/5jFi9r342yXKnfyYxOp7UNnq2s+4108GPkNe0/Mp6/27W+7sSP+jrQHsTeToOab3+m+c3atJlU6c4prG/y6+Dhi42ah/pYr7nkwHfR+dH7Kfmj9pbb71ln/RJn9Tzab/Daxp/+Zd/2d7//vfbl3zJl8S1d7zjHfYFX/AF9jM/8zNmZvYLv/AL9pGPfCTlec973mOf+ZmfGXl+9md/1t58880AjGZmn/u5n2tvvvlm5NH0oQ99yH7zN38z/UXyhjXLCjw1ItF62c4/831PBJPcjXdvhOA0uqN/wigOu+e6ANmBYdal4LeMeG0fkhplxQC7nV90Ch2vXt8FQZ7yPZXugYFwft1MJ5xPCQCUq5mFZb28Fs49eefKY1KD1B0BTBxnOB6vq5uZvF1L7zpm4GDeBBjHvjYafflMVeKLAcNtpwO9u+72DSsMPIP60PYHKJq2ACP4j6Bt4H/R4iYvBUJeZ+AWARs20nq6/Y7hrQY/ZzGOzpnTxsPltgkm9W9Lu6gd+HZj8xl6gbzQfzl7UGdhguYMGlTjYmDfZ+Lh0cl0sIyBgN0Js+9MXKO9TGEk+aF16cJ2cya6oEt512cBWiKebjZrD6sfIovqCP0u7JDybRljCUPwCd2m45OuVTexe5l1Uk7Ul2yo+R58id7py5PM123rrN/1qvaVJhFsP/ny39HN8WPgryT4V/qnqA8+jkCXkzf0l4wnClRjWc81045Nalje1MX/iJvytLE78DvEG5bAKf3uoLyWy/LkFdonv58mUxSfsH05E6nH+HRx+5B+R0Hj+9//fjMze9e73pWuv+td74p773//++3jP/7j7ZM/+ZPv5nnnO99Z6L/zne+MPJq+67u+K9Y/vvnmm/be975331SQwOtd6kATjbRr6DICPmw44WcBsJee14cHSw4lOTGz5BC1DhpHt7ZDedMRlYLrlO9QXjsYr3WdoBvFKcilw6Ajd6fRNqXk8c6SOp3sKjt1fnUWrLA7WkkdebE/kZV68GvlTMWdZ6aNXMJrqqOxpxRsJYgl7z/ydR4FM03yH5zOFSAk2Qto+oXp7ch6CWwaeYMFDZyjEeF2rwK422++Vzp2WUfc3u+89sfV8/G6ZxrRFj7b6DOPAVJPjnnwKKAtd9p8UwZxMwOusLNrUnMaCFC3rd69HuVTAZ18T/3Bv7Of6/W5QXr4iU4383g510W+6Fd4jXbIsgQX+E57SwCkynrb+ERw4vdmnhDoBmslBqE/cZBWBnOQuW2zrg7vtxuw5Nd9AgR2YCTVaZCH7Z2zpbKJJGRMs4PiQxUo0XY1XnBAQZnCbzGm+JKiB5MCfaxT4B2DdcvLkhJQ72Im/FpqX81nWXavh5/3AN8pjntSu2SZJ9LvKGj0pGt32oNtJWmeLv89Ot/xHd9hb731Vvz9yq/8ihPKn/zendR+qyh/L4153eUzg5mW1q0jWwIfHTGRDwVKWmd5HRRoXDCi4uimA0Z+j6PwE6BynvQ3aemZinRe3PUVOsNIqDsK6Z5j5MgstVlHh6lpX9LhSDTpSpxZ58CYwokwb8Pj7cLWRQpQ6x5H8XEP949t2wCPtu57gZafUq77ngCBAJRIkGdCDorc1oNLie5o1TZ8NpLsT4u2SYeOj1HEJNjkBhd/Ldtc750O9rmLeuTyKv6uG4xHszKgAnik/n7Jn0k3Cww4LddPWUOmAVoTgcuwMquT7FrLq03KTLEG2A4MRlI9dkhF6k6PMJlv7r8oegjESS41sPW9DDD9805gL3Rs+6r0Ri4FJc6r0hQdRLtDzsLPsDIopL/W/hAgTSua8nPKd9FhapeRy5ro0kjD7OjL6TfLBA5j87BSd8ED4lc7vdGnM/7oLCPp+zKPVg7UT7rpbM3GFjQGdf3Y6V4Fw3R2c0i/o6Dx3e9+t5lZmQ389V//9Zh9fPe7320f/vCH7QMf+MDdPP/9v//3Qv9//I//UWYxPb3jHe+wT/qkT0p/ZtYrzpWumwMSuNHOKfn8njau3z+NfAjGOpDS8RwG0PErj4sD9F0qPR6QrcAm6l/GrmBIQfRJLia+qpH8nh4Hd2CEoyntKB3ILx1JgH2MjEGb11iv6tZ51IGEgvDT99Mono5U2yCumaWAnZmt5PRRdwQXcW7Bl98T2V4FICZaqMvzMSDFNdsyn8hHrFkBYIBXz+tr02zN2lFlERsmNs2s6i9+HI6wOy0eO8YuaNfftACEN5HX9zF2HQCx9wfMM9cdZnYCGWwbCKfBeki5bm2rv0YuyrBfkEVsYBmLyWGWgd/cPGnfiAoKY5k2aRDchrxOxywzzk/nj/5IAn88VrXctxTUFJ/mctoTSXnUgKzgZkpekOAaVx9YJJ+Zy4004DPojX5Ir7ueKTvqHiwv52mmvqvx7uBbUzmJL4lJ3m/WiJdJEvVFoK0TLpyIIYhiOfWRum7RgaH6dM0TkyjNIEtlKk+0QMMHEZwIupc0Vt6Ll+qD76TfUdD4h/7QH7J3v/vd9hM/8RNx7cMf/rD983/+z+3zP//zzczssz/7s+3jPu7jUp5f+7Vfs1/6pV+KPJ/3eZ9nb731lv2rf/WvIs+//Jf/0t56663I80pJG8eV79f0kWUYg/WPdLv1kWyYewCDPHjZ5yR3Bh1ISQ6BTtjEaLFekTLqY2QFtMqnAjk6WR0FpRlDAYxe5hRUy6hP+Oj02v3eNywH2LH12nUYXSwd9ckjbQ3Gp7rT7uZSGfJ4EawBdX4oQwQ1QTs2mxP/6eQtA4nkQLp253UGGMvlg4btMhFwNFC40zaxZ7fBrJaoL+Ra6zqT+LdyaTNK8LWq4xqyeXsMHfmbLjUuF9trEgFkaDb+vVToYs8VP7O7HdR3wkAebDVIku7kRctMgQ7XLnq+9OYj/29KdezXsNtU7cHWA7iki8Kv2/Al+wsFUSm4Q87yWE/tVmSlDcUpCGYZ1Aq/wZfUWWTXfkZ5mRf9IU0AkD+RRQe5LRDbnWDbsvvoE92OP6QCVq+Rb6//beQNUmzvU/1ql3diIc85Jo0p7cCJEe5+9rIxYWL56dS9CaRu4oQ8MOYpBniqPPm4XHKMLnjC8oSX0jvFQQXBRW+Q4xnpjWflQvrgBz9o/+k//af4/cu//Mv2i7/4i/Ypn/Ip9vt//++3973vffad3/md9hmf8Rn2GZ/xGfad3/md9nt/7++1r/u6rzMzszfffNO++Zu/2b7t277Nft/v+332KZ/yKfbt3/7t9lmf9Vn2xV/8xWZm9sf+2B+zL/uyL7Nv+ZZvsb//9/++mZn9xb/4F+0rv/Irn7Vz+pioxOs1B9Z76bkGdKKljcl69eXknv8uX+ShaXzyfOThwVIg5y7tMoJT+ZaT42yWO4FT5zPL9NP1phNGZ1n0vb06WVM91MkQHUm97si4E9esjiiDvj9K0ccO5ENoOR8mMrYgQ4MLAYH/hgMwA08KNIbV9hy1LUg/HIraDa8DDHidKWgz/7yVocMPUITvETA6e8YlBqRhe+dxkBl9OarQdev5m9hP2ef1tlnAN6mMi69hW6Qul7TrWmPjTeXYcX1Kk1+G8O+/1R66JP0Rl4LOuKwuj53fabe4F9A2wXfawwkgZcFgo+t6+NVL5q+AspHzs63vgZ/WPg95QyZD36AezArQM+YF38XHQU8paKNd57Ai/xXlx6qTfUb4DtsMG7gg78zlQk7qB212b/d5MT+5kPpVYwelrMeg0VwHTbOt19jBr3FrXXP/qbNqPL2D/pKxV08z4XfmZQzX61pGZeD9pz5Vt9RDFwNdN6cNOoozEsC1J9Mrg8b/5//5f+wLv/AL4/df+2t/zczMvuEbvsG+//u/3/76X//r9lu/9Vv2l//yX7YPfOAD9jmf8zn2T/7JP7FP/MRPjDLf/d3fbW+88YZ9zdd8jf3Wb/2WfdEXfZF9//d/vz087EWpP/RDP2R/9a/+1dhl/dVf/dXHsyHvphZYWD2PUGcE2Sih3OYRz6meLkh0RqB5T4Zwz5BuDOQjGE5xhTMUyfgPsrBMjMiks7Djl47iHQozt50he73JIUiQIi9decrRAergZ1b6vOaAmvVpHsgZzjrWqdB5NGsGuw7PYFMCLfRj+h0BLR2xYQd7oY1f08xdldfkGvoCdUm6IbttmgyqJX6poyIftHsErGmZ5wjIlvOoCQyz47E2Kf+8/VMwaHbb2PKwAZavY9xvfzHLb49xVR06JOuMwD0tQES06bAqEPV1GOgkoOEfNzobYBBs+G0CCNol2jK1+RD2Gj5DhJVfdx1rsVN/0Ha7B2wLb2PnK0fzQF6SIpBISfs3bDbFi/X7stpxih5pL9N99zBctDSQU5C+Bmbz2vCXknSMNNuqeWkPQ8qy7on7VvOojgsvJrpa7VJAJFKcFjHF56m9SB2adPCfYv7ypxpvIgZa5k+xgMY4naRi3Hcgm3i7Iz9xCROxivKs909A+Bnpt3VO4//JqZzTeC+dGp/3klFa3yCavAyBEr+fEP9TwJHBhHTu1duVdaB5j7eig2bh8klntx+5Q5w6guaNzimBsnQmytPQ6gKpjjCV3s58aIvu0eE8660L9gV4nQCBOL12ACPBoENLyZkfnHUpu+zj4QFgS/QTAWiYPcq5cW0C7c4uwg4VbLt+75CmqEk3es/O6k5V5jrLmYyl3+08/tpAB5eRn0f7vPGGxQaYYQAT0nZxj4zjU+O1gp85MZOI/HpG61Qifg+8peqlD4X9P6Vov6X5O+Bxug/9KHAoegKdGCjhWtKvWV+P6qjJVwCUWRqYJT+isrFuXE80pU3u9rc7+mKe0u5P0XB9cxmNNaADetU67p0DbLZ9f6ejE5jS2BT0m3unyZcSyxEf/br6YeWJ4FMfjyegCJs4xV3lSWn47+7pnsp5L16vvQcfHY/2U9cf+f/2nMb/o1OHzJlOIEkN6R7696TvtSYtHdFonf69w/I6a0f+Uj7hNdUFHjqn2AEf1tPtmEy8y2jKd1CfOmiSAbq+iKw2al0KPGJ0LoHEVJ+z6i5+r7/i2CAf+Y/r0DltjXpOTsbXVXUBVeo0W2tYTt1V2qYDTM7HIK+XfK+UnWaXBjCmNrnmYgloYKbO6/abY9U/RpZrmqUZmhSsnO1TP9b+Cl7udH2KG5tW5u1ibJIZZtxdrTupI5+zsY7t4TE9uqbxNjtNedQfeEBVIQRoeNPiXdi8HnUxkE9rjuwhD2o7oJl4Mos1dunsxwboBK31O95QoZunGrv1e+ns0vUZMz/NrN9mevM13RaX/U7yO5ryY+sspYl8tGPYLgc60+D7SUcNFHqjL4lPs+J/Ck+a/GxX6VfenlHnTGWyP4hOcqeupq2Tb3DfN3L21F8Py8bKwBx2pKCwxOlwHogjGuvUt4OWxkU9eYXXk/zyXTexdJMSGn+9bm6kIWD0MsrTCYP4/dMbb55Ibx/Q2DWwKjOU2oAubRSW17wdGNTDmDsAwPo74KapA7ek1Y1+Opo0SAW0XSe8y5vwoaMt5VFlp/NQo9dyZXH0CipcqzMkwGrSkVzIpQHILDnW4pTUCTUohRuOro+2H3+oc/Y6Z9ZBcrDqzOnYNFhKe3rwOsnCQD0sr5Py+seiW0a5AJFlhkH4UFlKW7lcENPwaj5cK22sJulyD8nk5RUYeXNe2QYov+jlx922j90Z696cR5A7HgQsc3BR7Ai8qm7Wtb1BAfo5zRZ1A4uiNM/CAK95yB/7oTVp7DaOgVMX4M1iwNGeawi7TrPVrKPhsRO1zL7MXWagULJzLdPUxT4ZvzV2oP0cDKt9kq9Un9IVXkKuvXmuPikgz9qWpCP1TugoAHXDG/0EaYYsTexItG3r5PT0wUyWSfkttjvq4cxh8YsS37UsE3cxh6xo73uTVEebnxkndFgixQP53eXrJjO6++U1s+f09gKNDo5ccZ2i/B2YagR+T2l2oxBPCtoS8GoMdN+sNKPzNh3BnW8CvtYbVAd0vQMoMHTZFCz7fX1JexoR629JoV8JHGXmAbITdD1FtwV2TSKovQLEJUDnMnejSAZk6lvbduT7yb7YPgDvGgCLuWjAaOidUgpm/tk4GB5cPobwZ7A32GJiFvrsZEgxYzZ8uYgORAAAUpxSm0PWi8tDvm+ZBssNM33k7MeLDNpn1Gfl++0x8D5PVj+T6FgXmQJq+AuXU2yCiqFOWmBicg11GIqlDFIu+oRnPvUr4e1oh7TTgT+vjxs0OvqpccUWr6k7bF5Goz+lKcAp2tpyewyXgaD/KjQEDKnv9jz04Sm/26Vu5PE2v6Nb3qaeQ4Yh+d0f+W/ElqJL8iqxJPyu3B5CM2g07atP0wwxuwBnpqZfxltgUKaL+fQ7vH+Km6fUTYLce1sMy6i9a+zuNoGSBuM3l52cJlz8O3HDsV/n9PqDRhqDKtrvd+DvOUaiwO40Cujukzetr3vFT/w1C2b1kTEXOKcRhhsWjEvrvgeWO0PtZFQ+i07ZBgJ4SN953oT6ulSGLnUAnroYGDmmGUyhr05eQZTzHKCPC+1Rlo60c6asuzj5Ibo7pBPY70Cq8jgtO1MHDWUHKe0qCloOxlIuAaRNJ47QCTpMnUMT0OTBXYqnlwJEcLxl4prDRHdd81nNeD1isk+L3w42fWZxTsyIRvlTagDZGFCl61mjsegi+MMfbZyfAcJNjtogsGnopz+zvATBSYi9xgDMKxQQpDNZ8Rh1ZPsMWzG0tQS71Ge9CvqjucuX+u8F9lGzK2jq2iUuie6LOa9r5e1S6z/KXmYF2cZ+WTd7ze2XplxPcs1e50lm+mzPhDzMG0dcSRunAQPranyeTki0cddtRe1X+mznRyImXPZnydNMqnR86icfHyu+oCwec3hKiB4LqLQVw2g8VH4UHHPiZ869lOyJ9PqDxqSUa25Av959998ncElHq+cbMS+vOU3S17wEL15OO4z+1ro9+M9rNqZ4Q8u9WU5Jqi9P3Q4yHeF0Het2E/UrAIKMBeAIz+pAOhA8m7qSk4WnS2BSkgLYAtQFdHDUTQDpMvnnaY0kgfU06ILgAPk6QN2911dBRJz55jzeAybC2+jyiTOLPBJ4GWj8cpm5zqxn+eQLgWECDXODP6ow6hhlg4uD1/IYfIB/2HleBwkRZFe1ppiF5ONrBuF8cYONYisIwBGg3c6YB58Ezwo61LbS7yYwKi/pMeiy8XTWYxPwQ25cM8v9g7JM3CuAhJ8uq/SF6H+dcYl/GMMS8MWZhX3D8ofLQuMbkFF1Dz3RTxR/icoSKxN02O/Yx8FX2O69zYozlyG/6pdUEeVVqGP/Dj0ueumMX/Db1VlmotFOUf2l+X7ws84PaSQbb/yhDvh5/d6EiscsBYL6XTeq8fO0VE5BobZlYIGG9jMfUb/+oJFAi38nMHSiQQSvxy9wargDnQ4yTyAyjXSu+doJ3J1AhtJPo54H6OTSvHezoduBXcpm0KeOsFpAa9nA9dEbf3cjM/5Wvoqetb25OaZx+grgdORms8qqOikj/gm6nWP2oArnTf4CfNJxMuisT3/LBQFqfGqAFAc7qEfRnYGvEA1yhn4gswcKPu7PSsnfW8drW//ediwbIGPb3N4djMB4CoCpm24Z4iDvrtgYCQPoI+d4d/Wip4+6pwwu0ywmmibVnd7GooAhasaHBmjkCZ2xzahPr3Pinn9n4ARQCRIaWCkIQMWwbdNpkMl8+l3smEBliIxmuf2TcMMKXed9WNZ1ANOxPxXIqk4M+bNC8RX1q01PlX9Y8mWqP6YhP0L1s+Ylf/QXbh/0E56XYurTrmRr9DGsutG9HkHjg4sy+BcZ0tOY9buboOCkCftP8u/ikwlIIyZJjEmiI74wFmp8Ymx0UNkBupau1U/SOtVxKpdkPfmUc3r9QaPZVuypkTi71ClQd0PrugcFd2y8rnG6Rr39yLzE9yGGbFUW5ZMjEgUk0VkaWU9GxmsE3wbdKmDuZnaTXKQljiB4F1134Jz8pB1h0uk7wJceozuIAuCKkb/y0ATloAEH6nzopp2jLV4y/Q6sU0/+u4wSUW8q63SdB28fzkwIT+FwTe4vGsmW5v7aDsicB7RPB2gi+X3msc2LNgOrWTfSZpTBVwJCTsYnsjnsNvM4QCfMagZ9M9u7pb38FF1pCvrKD/PA/kqAj4os6f3GzNYP5Qx5eU+ASRk4KHNiJ1GfNEYBIZQBfZX0aKOlTqcLv4h2jrzB4mzKdwYz0R/wGTqdu2jSEXVF/metIgFO+PTEk/oTtqn65U5m8JP0svpOAtPUp+3YUHhu/A/1U0Y76j+YR3lcfieORoMPjPzN0onW9oR+ihWXfK2087Ds58XeTxNBGvdPJ4to7DfLB4h7Pt0J7fkdc3SgMskhSWOkLjNTwPjMN8K8PUCjpw79X6/92i9PquC28Xht9PX4ZwcwW2CQLtjuUNoBkSfAl2VDbGmKjPcAdNdpTrzy9+Uh0+P9Ak5npR0zoXfqZ8cvoJqOiA7E6ova0wzltNiFHTMa+jje84B/AmleU/1wFGvD0rlnafZByzsf4gyoo9R2co90FRwQJUU+CQIJZIBGamOlhd+DRKgr2pAHS65Psm2jKb4OBEvIJz/NbD9qnvl7whKdqsxuh3ybWbuZZWLTy8OD7TeseNve8gT4TIVt36f4vBlBft3038f29Uu7/iTMMNiaX3B6M7fJsPt9ne3LjQ3hL1mOtrWydsFOAUnYjPZzFrrl3Y/51QeIDtqBi/ojLeNfmV/7Cn3/+i/JSH/U8JQGnJ2PM/iOmfOV2T+DX5lbZwl0QuZyyHmWMZ8AsGQNn2r5U8FTyObXxP+kdpo7PwcHqhPnO1iif4feY1BrVY/7B/y9plHzxws01j0FWx0I7JJOZuikCOMygaqncs4q8nb1alnHMy7Ty+PplQikutS9wzHKNU6tBYJXGTU3+f17Vxfvax41mo5u+j3PxlNGJ50zQl06UklpVF0Ej8NSZ+1kUD1EnQRnnVMQ3dAxndpLgZdZnZGMIAuZmIcORd81yro6/QTfo7ErBGp1DF0b6zqgbuYkgMEUPXZBlPeZr0kqXwCG0RTVAO2XaKeUi4GQfZbBbuzvQet2fQM6BrIp/KDuFAPHrl/YIA/7HdQ3Hvx8RgeO8zGfy5jYGflonqRCpmhj9o8ObGm7DWTb+TnDutup04P04U6fZR1z48PG+q/Yiuiffupkb2kA4Hq/NvWPdUvo0Qf59bTL2fJ3B0/TMp1WloZG9LvOJ5BGE9Btle1m1qZ/X/2igOEmVg2rfT+1tfqQzn/udpvlkbF/n5u/qIq+FHxTphCMfZ/xBpsJ9Z7KnCZtnhEXySN/E6iVCQCVHXaoj5q7Hdj+qWCtm6RhWfKk2IDXNZ3irE4QKV/PSK8/aHQn3KH4Me4fssnrJ4DQjQS6vCcARtppdHFypOTpUvl7ClyaoZPh3nOMOPEvBp3qk9/FySHdC0RXrjGyp+Ur9xpH16XuHdpmtzcueCChY3o4zIAmZwmed6ZaruO9zGpavp52WKqzHNCb7WsRMFUXM+cxy6CFNBJYQd2pDSjfwZFrwEqL/2/3/azD4vw0yIyxRDsElsLT7fveTc37IxXbrN5msdIh3uO2ucY32MT6xLkfhfs5jHvDi8403mTZj7R9TaYGWNHjXAAleBZwgM+pbZNURL4Q4H3Ha9TjvJIN2pQG9mn5IGmtU9qJM0E6eEizUmqD2j8oqATZBIyUPmmzvvWZXs2q/QrXrlfsQO18jth9GVidytjWUSsDPlufdy8ejCJG61PmatMudkUVpK0yNbIFeJEJlxjIs7/M6C8brIJm2EXu5+leAVmI2YUvxEDGANJ1+zqddkId6WuLee/eBATLK3g84RIFhrynQPRjSK8/aCxBx7byuh1EBQBZzav0T+idSe9rYytNTs8rGAp6YiCdwXRHDc1OFulUOqrpHI/qyjuX00v6OMkw5NNkF12jm+57+d10KPLl/LYLkpcTSPdmLte9gWCIzENlE8fe8ZkCgvNLHfoGJqWnnp/l/JJ2d8o9919rG9YEdNLvwEFXh3wfzb2xZuVC10JaXp3Gt7ZkNUxha4DtiXz7C9cs7s8FDsfaDT2Rd+zPoLTuxzmMdwdfi+awpn1E1wRARe/a1pBh2emIdz2D2Uc57DiCNfs4iTV9Ls7D27MV6VD0xNQUexXflAKqlIuBAi4TmJbz6YaUV+V4mlKXIf/cg7CJsslu0T7tcqAuJmg/a4I8U9v2Xo4A49THxW+xzogXLDPz98G3Qq066Q4iL/0YaSWDtNVxMh+lLCq4N3kTQBmPmEvMoa/GY+Oub/pZzeQxXhqx9VF3cIMn/VSsofskTvGOWMWTxmkFiB0w1Nik6WR3TXr9QaNZVghnc54DQDrQGXngILjWUYFha+jNH+8xr5ZL9MbZELyMbkhpR1c6G3vJZbpFvmZ5lHURh6TgiX8FhKPubkZG00mflKcAVwN/tvk/HXtzD4RSX64D7mBOepK6Y2E2ynkwKKKyjMvlTpgOYW66BJ7xyIt8iCOljAn9QIfpNYJsY1nfQ/CZggDrHos1tw9hS/lJbTcS6RsGETkUAFAsgMX96HbxOEyO/fHPdSzP6kdj9fVyEPhDtltuuJlqn34fn7nxPT90p82XEvPO5nHTPnOSChxvvHGTqwR5y/2mXe+FfK5DNkw503N9JnuY+V6Q9r6goMO2XibrnAjiBCQI8l3y8tE+UPJpMBk8HHxK6MLpGJ6okB7bOApa1c0d/0cbmcoLfFXqBJ0uRl2bl8AxbVTLi98qti72He3P3118hYzqizVWmWGQ38Rbp8fBd5xjfIo3M78GlzTd1yuf/M1yjGn6rukuJt+L6Uxd3bymAFZlPN2/k15/0EhlJEcqDeSf3WJQbYTWyVtu6A4o6eNk0iav3SghlUPn7xb5qoF3u71ZXwuW5n2a7AzFuR50WwCv5XtPlc2Fet6TQxHnpbRj4NDoudDudNTwr04otTOc1mmmIWTTII5gOPE7/VVVmFlzXiP0UtZgXZF1BQ2dme5mxIL9ho/QKWQZusbPde+idTY1ImsO2iifyvisg7C2gutEffs4nZHzKdBrzicN0Dp5VqSlo3TKo2nc5zutM2iRwUziH3yqysMGxYYIAAZ0cOpD0Q4TbS56v0LH0Zc0wGNZBI+FKnYL2VvQob+Vd/XN6GedDZplO7oI0AwAij5MHSpLTl/PqSQADpsPw9i/h/Pd9WX3SWrTsjb7VHawkOqia2PcThUysWNBj+R1aL6unx5i8sR3rTf5VY0diLlanvahRx45jx4XCli1up5d85ziQhfXkkh37nPiRXGDl+vWUd4dKD3j2iG9/qCRDdcdSG2WDawr+9xGUAMpIKR5LKyvGVIAwjzBqzveBuAoWPV7amydoZeRr/Bz0ksq29yn850zn3rfrTc9AT0Fyw7EXX/DAxT4uTeas5nr7pxZASdWZTe78XF6BVX8bpwQbaIEPPBYrtNRMy9nQ5SXLrBQ186LO+yR2yrV69/XZ3HAGpz9PwUKWCeYeKY83r6sfv3QoES1p/YwSbcKve4AeNMsH8kzRL17hpHrIsflYr5RJq2X9HxdAIpYfVl5R74XoOci150Z6ta/0ManXEelE3mH3AsAxPbqQMPIMmmWbhetmRUAWtwqZB6LTjvTKXKb9UF6Uv7eBrPtaB/paEgfoK/wJy5T8pT+L3rV7Mzn9abD+FGoHF8kOmf7Bnid+ZrqJuqkvvCp7ZpomNUNKuJLE93Ox8raasamFKe0PQ0xlT5KYhIH8nFdbI2xec7q4/XNKiEX6uh2V+t3jVeko3T5nXGti9P3Jms0PRM4vv6gkQ3RKZWfnl8TFf7cMxo5IrnXoLwf/MgMg9fJR8HsEEdQ1MgRn43MMWsoRl3ogk5n4Oma5wGPXJN2MvoO5HLtSrk2M71WHxrkmg6rv/WcSDNLjzaY6HhO7cN8SW/aYRsnHbTWI+cSlIbYJwODOiDdnWg5mPPMyhRM/bIErlcYqd7oO99rZ6aCFpcn1o5ajYe2ABpBZ4mnU8RHkJpmZaZt2AaQqCcdwG1mnFH0HdSRW/ogd1wzDe9rc0KuHBQHH2ue+kgH4hMQ8Dyq22AQeRBkdIBAoFmCv+0gH+uxCYbXX+zqB83WZ606pqGvpYYVeVmPZR86Re7g1fCdxsU+4cWajT30a+pLoi+OWi7sFW0Us3LQcwJU8C0JYMGGUpI6U37NN+S39Osp1wyy0mYTLfhmBeglbjY+LmwF5dJ6TNt5u1M6NOk5uczntsrfp4kLjXcao5mvwwz+2+vjnoOncIqC3qQDtsmi43jhIn3hBCLvYQey/6xc/zcnBQR+7fTqP5bpQF+3SaObSdDvCkA0n49I2AkUHBbjEdlcLh2FtE6tc/ramaEvfl4fG15G1gMDGnUYf80O3Sh/qfc0WLpe0k7jUfMm+RRg8tGQtGEKyN21xkknuh4Y4JCm837qdk1gPD0abumwjtHzG7p3Pc9cnm9V8frp/OOybGYoOqJYS65yj0Fj5stD83RJXg/o8jnJ/KWU1WpT2aB5YybWK6JM3jF9ux87rBl31yxkq5vwMfRHm6nZbcJgtjnztXY2BzIzH2iWc/gUKIxFa1h9zWmAp0u9lgApPifKJ95OoGn9bjd9CZ/UAR81Uj+sN/V5LysAplsXqIdGJ3kmmgH3UuxBu9NminxN/0+Dn9noTD8nyKCt3B8k+RTAqA2xE9BORh5Mhk4MtJauFFCH7ge+m3xCH+FTMKBoJzfIC+5HXETMZUzrAOYRcDbX/fvpdJbkj2cudzovUevpACCBajcJwjyKHV5A40oKmDzxgM6T8u8BQ4JONZQOPGpg0EbiY8Di6AlGwJvyEJ3xoAd+nqbMdQTF+pxn1hFHATSyUUYNmFomtRPXQMGRtEFXZgxObaGdJnUQ1BHX4YB1t/O1AbwMPjFLMvf3NDuojk2DlQZQ5pVgnmSwXW8JJAgGRY+oL9mgO2WAeLZHmo1p+pjTKeyenPxMt7N+UM9E/mFWD3W2rUpmXXLHkTgLBI3LZe2A3gU2zdvnfHzc9x4uZebR5fDH11HHBTJ2TpkzDhKAk/zUcUakVNbOH+2F62k9YU77FYwnOtKvCuL2/tyBF5Wb14bI3cnkghBcaD0rf7fBruUXNIMPvYfvx4FeJy/6tPaNOL7LrM5+TfiaJogTWNEn+cyVDhi0I6iezSyW1XQ6H5d9dNKQdkp2tOXdB+dfETMW7wmoGug4WfoUsVf1EwHIoKcUe8VuAxheDjS1vFxLuEA2tRA/dDHSY/sE392kVRd7g/fGFk5l0sBE7vHoHr3XxdcmvT1AI5VEJV9xDp9fYx5eO9HlHw3H89BQnJ6CFzWyroOYmemsU3nnNWRTYzqNTPyev72FMnQHunY8ug47oBm8UWcNOCZfCvQ6MOi711Lei7QFHuvryJmjU9czeffRdzdCTCNh10UXVA2fTZv49bQOk4+faBcSZMPOGBgafZad07inQFMdsEmeVsYp8jIx0DDY+w5ky4HwrtNC8DGvbqzqtW9bVn/E2blYmkuE9Xm97k05If5MIo3LJUDnfLzGPW5wSZtgVmCc8xZI9RH2rV683rDYDPXdBIwGqCTwnMwvmAW/W4/j4WLDzx6dZvuMTK8bxELXoBEFyRN5BohKxTyQa9vPfD/RYKOUL5YGKQG4OxCq/VN45uCxHegxIW/w7EandWqQFvCSnn6Qb6clPjWVF/2UkRN5Hzlbyrv9QAwm4pSJ5VPS2Z5qq2O3g561qCD5tMHK+7r7sOQ71/UY4F6yv78xvukn/9D0qTJJY4gVzXeXQ4+zO+2K7vBHN5lRBmZkawgPzafGWb+uj6f1sfUzwaKn1x80diDNUzTWnVmyboasq+Pe6GCIcWlSo6IRxsj5TnmCSuVRDZ7gKYFbGflcLvs1fmPkEbyCY69bHxWr/iK/ODN3SN3oR+UhfwxSKgMdBJ1Lchx39NnqGkGIQT7pAo4uASbL9kDn7b91FNiNhuloY83Yup4codqc1McA5DIQTAdN/+z0obyZ8CuBCEHtNiORr7UAHbNK6YiergmXTH4Q9823j31vrDqKOCOBQp2AGg+XBPhIfz5eb4+fr9cCNDdW22+NSbVeCCSlncK2va9Z/NYZ0xCf4MaBwKQO90xQXpNqW69m9QgjYxkCHSrS7cckof7Sv4clX0Fb0AGk0yrH3mz+cj7eE9pxvfuNPu7XuSnnNIhiPd3ymsSny9H4XZUl+Xbe076rZSbod32y0w9pj5yXA9CyblrLNn7B75U207yjXi+gS/0j/IaCsPZMYtDlodsuzylWK6ibzXXS1k2uvKcTNCGb5e8dXtHfHb7hZzm/tOFP4/md9PqDRrN+h3LXQGY1cHVgsLtOmhxlmFkFMwfaeuBnd7h0x8cJ4DqNrm7+9lFakR3G1s1qlpGNLi4X/jJzFs7JD1Pt+EvAtulcx/MYzXIwEr0ED3K9jAw9ACxnxUNedQaU9Sqf6fdydPF4pZvRdWfNxykAovHZVO/1lyUIMotZgr7S4B9kSGscBSyktUodiAhmICPqDGfs5TeB2bSl7lS+ibllTJtapu2ZNjr8YQn08bDueP3f9PrBS9C98ZXOXYxYBmAo9pBnPCeAHNo1AOM8lFNd0Mak7dAeaU1qCkz4MvPFpMuh9QBEcX0cB6llEMP8tumtMrHJKdkTy4+dP3imv9D1jw3YKIJ3fhZ214J86DnN7BPQaDvgsW/iCbp0PftnA+S3LxD9RVXCXwJdXSLvqMdjRPRRbw/OOFrzHdeS+Z/8jur64EuDjM6cN58FnGHmLe0BEDikmEHvua71r8S7puxpYqSLldqeGqMon8bkDkz7b+qgk/GQ3h6g0RX6nMetHWrvlMkpX46WCdSeidwTTTXyVLc4YDf4pw7D7gx/eIc3i/V2TrMFZzMbWpk5GFVPXQdO9K7r8NSR66ajU56UD3WCqTNd5X7XPk0HjnurTHGcd2TsDnylWtKgwGdyL3j9mP6euT2KXUjg4exF6EKDq3zPAu38JYCMrIN5hWpdLtIx1M+gwTpCMU05v6wBe5eJMw5Dz3OxBrkR928HWS92sIufj5k36NzfOatXNt+s+3wkHdc87ylBX5tn6N/7SYBU6WNYAxeztwApaXawwwvTNmDmReCMZINmTUCEPU3nUfpM8ZegwYHG3Pra53hO+VxypzML1cY7QEO22Y8bwDOcxjjL1sUF91e8n/pE1+9Wny2Po9EHws9PyyDbfYJcS31GfWfXn5Qf6m3IMhmV49SXed8s+YKS96DLDsSHHOyE6OSerwOM3p8IMhkvWIfzVfrczHkYk5kncMFh/8BTu5pL/Lf+ngJV3jv123uA+In09gCNZn3D+zU9i64L0hqwitHAUei0LxtQDwftGpc8p0aXRzMXjPySswTNNPIWuTjS1/tdp1CdcC0JedMd3GrElJ9vkUngF0FT145wVjQ5N9Fb0q06EOigALFxA3QRzMSpH98g4HVzHZYB9I5cFxe9x0aIxZMDyiMwNjglQ54ucNr+rUA5AIaXdd07/55XHfSt7fZbVVzXOpuJz2gqr0f5R4oF+Lw4FqsSCFm/rcfT+u7qqH//no97IX0Cn6qCaRlUjXqPQNHvBfgcZoP9y4uPAfk63UMX3ubkEXKntYpz04tH1q63iNmsm7TldwjAGdqBzy7Q8p70wW6QluoBzTQYks8Y9NLuPA/smRW0g0Paq+vEZVHfAiDggxEdVAXAGpCrCAo+na6uu2y+u851neA8laEvMOiL/k/kI5gKPg26E1/kqXubDGWknUcWyVOSXO/iZgLXyWizHHqeb/GnnW3M3r5PEwcaJ81kMgD1OxZg3k7WrlzhUX2g5Wvdn/bXTv5Dev1BY4eoCRbN6roGs+crsXHgLehSXnRUkDo38qSDfbuG19nTQ2fo5OuM5nTeVAtw8cnOWRbbc3E3O8hB391ILjMlbSn5FDCqkzC76a2bVSVAcv3ycTSDYRytw/YehzbDrAfLxWNC5oFuO9twHqdJ+9OpuG2cnCicNR8nanAYdtiRf5M3joQJB6gzOOx/LD4tBRKNp8wHUkkGAn+wPa/Yxallr1crj7QDeK1zEYELdB3iLfuocc6bxGcmV55Y/5j4bsqa59P+MaTvug1l3ghQI880vKLS9qeDna5fpc/uurQbZYp39jr73UCcdFNDQ7ZLvpxYUWDQgKOgDTs5pRSI6XdgBLTVAp4G7nfAqqsbPqbkGfkv+rVJHShxGfI+9illUdcAf27HCbzR75BX8s7rq04OsLu8bn+8lwajjQ/XGboyiLAtR7qv6dAeGiMUmGlsT31Q+DkBT6XHmMNXD5ttu9f6NR6e+NZ0L6ZSpg6D3EmvP2hUZSvCj9ma2TfCCbF7Oh32zT+C1BOA7VIcbMyIKAalQJW8kD+VU8sqmHPAqkafApjwHiBLgk8AG8yynuQIFlQ/B/kKWJK2G6Ph2/q27PgwszKy98fHc89U5YPRJQhFOQ9CeLR2ecj5d6UW+mUQCznc4WNtFDcjFYDu9BEI3Zmn4zo0gFnWO6/z8/i4b6Zqd/BYgZDBzIPUpMyZ/TRjNywBrX0+4qxlbAXXgU0t05beXEweGbKvdRtO8ltjXAUDKhmRNz5Fjz676fSn9pstAAKshe1w7WaqmzSSTUqATrNATd0DecJ+D8HRLL/HPWjRD0nA0joVEIYJzGYmyywNdihPObZmEeoGL9pPwi9InsmCottoH7nfnr156EvDRK9z0y4JdQ1fAjGb9vIBkPoS29+XDYZf8rITeVu7VLloZ9q2oheWSSDctu7HaF5/Kv0gseFt3cRDffKjExJDrrsNnI6v077cnrJhm06ZwFj39Hioblayre/Q/zzf6bXBT6Vn5nv9QaOCKgUKc+7Dqk+jDP/dNUAHep4CJG4warhqzO3U+Kj0+FtHEmaoa2YQybzqlOnkO90Vhymyk+8U6L28LAQ/yRgdbdY2Ct7Y+ajTS22vWyGLYKGA2L8nHYoe/MiJp+ylBDPIE4+w0DYdyHM5CqijLa6g1p4lRwfu31lPo3Pej2DZlCmzBU3dAZQN+WbOE7c6HeRg5+v+xhql700m5G2kIOwg77S7+Sb+babvtkN7XVvf087pgWthypddj39/3Os9/cidIluYjupOmOSgwQH6ZF5fTzmlGWbKk8ADq5lmrWKkjvxb7QZtXeqG7yz9hXJ5vViL7LI/rMFVOxBalHwjEcuWV2B63Wo3dsdfqb16vzXoVPzPjaEtTwduCbQSMJuSz7afCFsQPSbwxz5g+3uq00CL/B5iVvAhfs37wRB+S4JMoTPGFNi4Z43zDE/+hXxehA54Tzo7xJgykWTZH+n9MksosVFpdP2fZbu4rXk08exH1lNi7ag8PLeOJr3+oNHM6llNej8HprsNHB1ybEPtGqqUMeQ7GOaJr4t0iKdGBHrfeYz1lM3jeMoRj2FnfoR/y3iuNx3eeseIb5kqz6cOe5InnNapTbsOK456jFrXaYS3UQK+i/MJGthkdBoZaxBMgXSCDoOF1skd2AwGEhBUhqDjdQVBfPJPeR+5HZrZhABgo3njSBSRIBQfI2VPwW7Y3iThss4ZgHJjY//ONYu21D6SzGmHczT/RGwb6VqavZw4TgcgdjxciupSiubEMUGuw9BNByZs6688wsNNgsRiCupHFKgo42oPA9nQfqmfSb0JtI7ddkU29de0/66u2728kcjpGOoBQwqYTgPYKKM+aPVLPy92GxbKrzJlEwnvM7ATtIn9a7BXn8fjtwbbxvsH5OTgg+0ZNod8E/Rs1Nk370cnIJ7azywNkr0NvS040+llfW23Xz/FBPV9Hrti4ED7El8fgNNAw7YdOg22rQ4ukj7Efoo9uWzNMqYufxsjrN870JXl9Y4X5ntGehuAxgFDtdqYke3QMP7bjcTX7QS4sn2P3++NOrrjZTq+0ihy7jrv8frUSIJghSBFAaTNbNjcyUjDS99low7vccTGDs1OeTL2jl7Rxah1aKSkQwmeIGN3yLsC3dj0o7obu3w4Sl1TOO+0HQMi7C1uw8GndpNNQsW23CHPDETUSaTNB1p3EzSDFIOMy+Ek107l6WsftU7kH7ZBZrTTtTRhDowCIiJwmJTLAOa2q5m0b19iM8sCjulA72uWn7OXfNzt1+MxemqKTKMcBk5+qZtc86rIs15CxyXf9PxSf/BF0GWH73NfS6BP8rXnAZKvDPA2PeShf/IyoQfVBemDdtg4QNBQngf0ZvsaUxoAN6cwUCf0QdMOR6XJZzrU2rLqkpiz3kvt7XzRL0ThnGdYIwfytjxM6Ni/4/ceVa2q1G87C/Sx6gNHznOUAanMiur9UR/T6nf6TN5Lkye4ruVi4Hyp5e+BsC6W8Z4eb6cTL/6dezE0XnT8kJ7W2y3/OKS3AWhcSrs8ZMV2oE0Duv/2RqRiFVCU11dJHdpQJ4Pp6HZ1dh2sMyw1KgWwtx9nnvw3ZxpPRtjJq3WWndD+XfJpB+10mx4/i7wKdOa0BOpYjk5RgaMGrLTTfFg+O1GcjNKZrEt1ABlUXjrq4hgkWBQwZVuuEJl8mN3X/RBdkF+zNMOBLFtmv8jgogHu9j2/mg/OUu1a40jwM/b1acibnXQ673HGf4uHffxMOrsRs4YdkOTjar5nut00Qw3hgO99OPeypbac9G2f7UqpCVbRDk1w0SCWyqttYEc0Z+1Kv/Hr4mNUFqWv5+4lAaQvmUnf0X6NOrRmLEPYBiNyeQYOaMvRNv4VZSZ5Gb3oLZjXkwc6IKBgBP6EPA3hyfmYzCMdVw/qjoEklxJpe058oL+XpUHuv0T2dK10bNgl7XNIftDUehXMMnWgrouVSifKHyaP5syPs5WG1seUbA39kuCxi+EKLJW+0mSZVzwi8G0AGm03LBXcnZKuStdzHTWQnxpURxHtKMXqb3ZKAlb+poM5OmirxqQOgiA43juLvy65HrtRUtdRtSw/TyMe0jh1iNCpLrw/0A357zkNOMEYPTYBL8m2glx6jRUCYdIl218dntW2jE9puxTck+C5jM4+DORLR2+oM1n3YykDC9NhHepPv2e+XOzT6x879hHQ6WBiKyGrkLFkIE/UwfZYWS/KS61iqN7N1u7qPv+N1G6HmIWctzrKawTnfsXglmHxmWbeCQjcznBvjJxPB0QMygWIm5XZ6q2YbSZh1z5IoE1IHwzal8OxImKjrI9y3rOfIq/KTvvCNd9E9PiI6xP5yZ/rCvKflul0/bfbHNa1aWxYuWRZkhwjlyn0snwxaMpM5u8J3NKuPGbQT0jxbkQTG/zotzROOJ9om/YlBE1cvDsAAU9P+ct7MfiplCZx4As01pzAmk6WqN0oHV67Nxt4D+jyd3fNy542/kh6/UFjh8ZPAEvL3FMw/xTQOA2WUwMoNPVxxeFTeR4NqEzOIBVCZzXZFNNsujGrJ+Zrh7gnezf66Y7hMMv1O69Ko8g+arl74FXv8ZxLddZprSDLq2OirPKITnWpsqc6m08OIoIn29fL7kzIRBpRlwZplI12lYAX2WnrAgB4afp/boN+T+qdhnYkybF/01ataSOWlazmQAxAkW0RYO04K2dlJ7XTmH5sj8R2f1zNz1ssHutMSGF91Z/AZAyIXDhloOE5gUSr4MNppT646KT+Rtsem54q16/hVIR8iLjSMvAjNp0Fkbr4dYAXpztz2WH1jURJtonzP5uNE+WTcUL9S+NbU9+Z+c8nLeK4rUUr/IyhrGUdFjvQulVvql/aqvMzd9bkM06yGZquoe+6ao/egVzqXzigIx3P2/l/Te3gv6GttHTtbDNIjO8dD6dd0+0AYvT5iA3aeNmUI12tn3SuMsGjMVr5fOYj6tcfNJrdbxBPHfhTQ0nABHlOow0dIZwMx8zKzOEJsBaZTo/FG6NSYKgGrbLMmXdoJQe7ki7mTQDYMj110mM0o0zIpYEnORrZzFPaVAIXR86pHRFA/MgDbb+iV95jsFh10pmkNpf21UPR495lvymn1G872CRZbR0DpEFXnRoCSLE38qkBiv3B9WbNPa/D6/GAOPZnAixD4usV1Y8gD4GWiqTPiYi7jRerTUCYqhs2qcRsP3qHNuXQhwABAABJREFUM4exdrGyl3iZ1ykbXXKGOBvSC4SdTbSLB1QhrpVFuWYDFvUw5AaFTzFYZgrpB8K+L/u8TrZPAhisUP1IJwc/YSCtDhdfk/yhnjTww5fi452vBiC0fPtv+p7GxyV/ZfAPOmu9eC/HlkmfLgDVr0m/I10doMZxagdxh+ptIi/aQvv93cGp02qOIlK/RT9LWy6gR/3rwT6SXNCt+lCN6WZ1jSF9u5c5gTsvk3i2rDeNY4pTuvp4/RSvSMOsxlql9zLTiEQUfRpN3FuTqOCKYK0Dl9rw2rAdaGW5MNzmUZiOFrody8p/5EW9ZU3kOPOX6Mj0vD7mp7M5gu5mnabT4GO5AEGrLp732AUQBYMFeDaBh87K5ecMrNrA7Qf07rIwYICWjdxZk/MGL51sMXNJBGO5XShz7DQ82ADY33UPXNOkgX1IGXF8QWjaBigaxAA6rLmedppKQIKtxPmJ0WdM4n2uN47qGRmk6ZtaRlo8n7URs4dmWO+49cc1mWm2cdzKlqN1/F43cDrNyFG+BBApvNghBIlXDU6TQCPtEbHUB1ryO4J4ZdGMr0/s2lp4LQOnKZ+8NaEWAqXGn3FQWOq1XTZslrY5pMwBmPCRbIg0kN1pEgSJryjfn7pG8HHN1x0IcuQT9rQ+vV8UgM26DHqDPxqgPT0PaajP4Cd8edEj42hni01sagfds37XdtVB9BSd6qbMLsanOD36PM5nF5c78HgvsS6NXwoyFcs8tUubGOUZ6fUHjWPUzRc6w+J5/DdTCgyzGpMqW0GQNnQHWjsQcMtQ75d0aGjS7vicAvZYlx/SewJ9rJsdjI85QuaGd+1k3Qgs2k3BmdC4/eh14Dwq/11H4/fjO8rZ2XUQIjpsR7N+TxbTp0DyhAzOV7QT9Su8tbahQZfBQx3ZzN/jnl9HUFBHPEwe77rcDJgj8gatAAVD8kKc1X7zOvvBXsIFfKWgJeAWZzdGAHTaFIv9FfTmKn+9zYzqwd55c8u6LCP5KBuBPqvQAoioT2Awdr1xHZgEVwIFqioFYdRDvLLsYss3a12V8X1dQZPzSuBUgugC9gX8NsHN24wXAiyCl+7tSJqGysT+Afq011QO/Fylj3cAqosnAXKFh9QPtH1RR6gZek9rFTmLqfKynZr2HdDtZhr5/Wgt2Jz6D34vkwcep9c179tsz24SJXQ35M+k7WYjv+j03sSJ/lEnXRwhPZ7LbFY3n9AW+HSvA4mkzfq6+lW2E41XSK8/aGTSnchm4oBGXgfQgUk6LTUOpi6/OonOILo3uHSpGx10oKfrAB1AIw8EIE6PnZp5CXjizDLWIYualdfohDK714FzBcABPq+Vppml2Yekp2YBs9aTyjl/ojd1TvyjnHGtawcJbizXzpCoczp1etxTx6Yzn+p4y6yNXyd5Oj0FMhOidEEG4CSxi8DXJqeLoBT9RbKGSm8zfAHMpgWYTa/eCxVMqG1YeR3h3GViNm2Y1XWJZgEIXWxlcfWzdOh4CaQUZuCaEsMjboLQuf4jOFYCas/JLm+/460jZs1mkEP76oCJ11iEA8wlx1Rf7TpSwBiv4bxX5yk4HoBGm+DP1JewnOs3+REFZZQbfqWc0yhyJVnoB/g5rbO1VGcSCzqI7+RT6xK+BvJ7nwjavH+PF+8jvjRl8VHeCGO47z+EVjdg7mLznPtJlrdVeSIk+clr3Lvssq1uDzx0GEKBJP1yF5tI6949li+DFOR5Znr9QWPsAh372B1NGuwVlReQ0jimrjG68p7UIDqaJnUqvU4OMzkn7JBKkJv1fuJ7WAKEc1bgwLO4EnCDfN37nl1WJjrcTm9pnag8og+SfHRs+/s88WAZcKfF8tJxh9BU/ggW1KGlpRLSlmndZeMcVU/tmkgJVnPR7QJa0q0DDw8ekorNoc07/ghihkGf0u4ao0yy5KmvfW9K2YJd9oXyNhjWjbIxGzgtHjfH22IcRIbuNmtc3xh1SRAtj6HNzMZtVm1oX0uL2J05yNwF4pDFyygAkYxlkKC25cWlf6Wgzb6g9cHHbYFtt+cqn8AK+Eo0NQ30rQOIaAdV2m9Vj+w7YRT7XtIVyzflvL+dBn2JzsrD3ccK3NiuQQbXqcfJtrnDKzftDMmT1Me2RPtQxkm+qb/ORkgX8WTqIAC8lkE27jvvA/SK3Vn2V91RM4wLau/Us55bzNlB+vfu1cHUCa/RP5Cevn1M+VRccsIHMfkz+vWLzwSOrz9o5BmLfLdjaxBWz0kyEyAhjXICZy0IlPykwZ28MRJqZkbLKPNO/Z2sTrs92X/menQEE7MBY78zuRtRn47lMbvfAdzRsWzMJCgdrt/TthAZEp/iFKgf5y/40qMfLlmXASZllBl6umxdkLewMTo6acd0rWtztEWXZ2fG98YpdCC35eMU9PSy2rcEm6mVjP0xV75huz00cA2zQZ6H5TP3kjrEKdst796UMnYT+PufscuZm1diTeKwDP6SiLfXCKbH0KPSSsllDvm6fj6sDg4W70fQM5p7ypT029avsB1G3RSQZrZm/9kd8WRat9TD651/SLI0IEL7aNzT724DeHzdDY4SefSJ0cilg8QEDCGHqaxetpHH4LN9Ri7xJm1XBq2dneB6J3MaHNDHNrZR+rT4gQTiGht18Jo2hXV1S3n3FakfWdZBbNLq+hHodkvUCO7uTdR40qVwBKYaW+M1icKv80y9MXbze8fLaXJDY57SOGEJSa8/aFRgpgidyLsDTvwkPf9eXjoOI2gb6F5DCYAoAR2GfzJi0o0/6Qzp1Uwsc+m33aeRLBzJaYt+ByQp193ON3N5PyJjQjfko911PvM1XU/StU131EUZtd7pjGZm5ZGt5evhvL0+ddju1OjgnIdu1jSUh8/Tfd5D26ivb+uY0p4jfyZblODgTp3lu8AT1Q7bsxcTrA+Yz9xFp1l+vKtiV1ub15lmEXdzjyTavDpQ9De8gNUlz3jYb43Zaxxn/M6zj0855Ylmkra6XCDPbOyeQvunC+O2a/hkctnYr2Dv0dcRtIrtqK+kvUl/KPfhF+asWQu7ullKQIWCk1bvkG3OTLPz+zr4oZ6UvttvOvie+u+WzajQqrtx0MvYcnj+FKOu6D/a7xCPuoGrTlyQ37DRueVNfBtsRfmcJWvys0WnYh+0bbZdibESz7VtdVLDaTFenEBWafN1/XrtaXeTUffAqNJOA+VRy2pM8rZr7XPWOpsB9im9/qDRrDa8NoCi/qcaUQEDjUxn0kpjNkbVfTfLziWV1xER6ugMwpR+k0dBUScv69ORTzeSJP++3lGN+CjvgQddM8k2LLKzg4mjLuBv4qNxED7LWF6Hp4HKwM+1b0MNomNY3hFOfdMxAtFY1453gkeq1++B3vW6ZY+80t6cnaC9FJ3jkZcHlAgskp8BL6l0lo0jASjIiqozWOyd+3594I1WrG+c09Iax1VHevtLNMvI9NZ9ntEYYJb5nzPIs+78yJnlSX7sRJs0RpCJtqCOWsAibRU2KrZ5E74GxCNdO9/vgALlTSC4oRd2QeOg7Yqduj44mKMMyWa5kWY0dMDEwPc0IOz4EHlLXV2VXT9vfBLzet+JW8wDwMx+XmIBdJEGxvrd9XDJs6Na77RMv4CWsT/S4J48WNaXy+v22gG4VAXihz8ZUmB2veYZRI09HZ5wxrXvq19yuXTySXk4gdTu+3NAqdN7xbfBmL1dQGMHUhTsjJF36zKvpm7UQQNTB08+1FiYL67B6JUXrhGMkb/uLG5GNUkXdPyiH86WEST6J52Fdpj4nJuvE3guwc92uRSQpEOozpwvHX0xELgutV1asK6Axvb1cIIz80y5tWz3OERTAaASNEKnzY7MxEeKCtVhXa+5LGdb2qMz9JPy+uBIZBmnHxKwh1k67mZKHgdfYPXWvvgdVSzZV3CJR89Ui636nGelteqPGcUw45tt+OPloY+fnI0L1jyC1tT+X9LE7bHlViFpX+ng9WmlEVJA13Y81Q+wUNrKbY2z4yYBrfErPhiRtN/GgzInvqbBnyn/TR9JtzkQM+lnc/9NXhuWQNRmGrwibiSQuOgU/Ycg62cDAIJXszop4KzeW67U+CTSTwMH+grRa6fHTEx875KntW3Lbxsr8s9Kx/nlu+GnyqZxw7AWGbHR88Q7mrG8qBXNnxI2GGDiu+IJxpEU46+1Pr+ns4COHZRm4WPmP5Wby0eUTgcuyfMzgePrDxrVmInqE1AzdF4p14Grjn4ybusbqcvndNS56bE3pYyVznPkZ8AZnkZgCgjDsLA250lQPXYH1aTXTzo+zfiWxxBOV9ceKlgRneiZnQo4o27tyNd9vevEXQBMTljvuyMd+ZoeQu718BiSOBuucbr63fUWyxI6u3RbOdBI4HikGJvyOtDTespI2dYsHet02eZ20hLnFdTt2YoRwX8DtbnLmuWdnWRv2FrreJFjgiboO42bDfgMowNDrnn0fsljd/qDvTO/c6I9U3booQN1yYZO/UDuTbM0QEw3JLvrO6oAAJma0QDa57K5zMftFX6JQJblBA41aLPPXcUHlHxme6BDINPxQV/t/UxmGulP0xpXtWnkT+0ofCZeaYNde45NJ9lFU19K6oe0Yf3yxL2uPHlhmSfiY0v7oKvwxd63GyAVRS57Wcg4yD50sG85xiV+pezlwerETBOnOkyhqQN3UQ/iW4c51P6JZby87oPoYlzHzzMBo9nbATRqOimShnoP+PG7Nqw7kq5xSr4mOMd9ndLHvQTqhCeOyLvRhj4evgc2eT11rkOnaAEmHGvwfO0NNAVMtEPiEV/i3sFJdIHQ28ZnlJmnG/mZbaCVrqvz6R7vmLXAOTNpdZAy95+2zxWBizvVlSbLcFZhCgD2753zTLw4Pds86IBDiykAnfFfpVmCm+gaIDAeL5fm1SCx/mNebzrflCJ06g5rP5MRoNDvjBGAkYAwZiNFHwWwshaCMAcEST61BzI508fudwOx+ZY/Zvhc50FOAhgBjpql81Nmw3c9VVYntK5HwGx8YCmH+6nMoQ+mAQP9h/su5mVdTlvKtb4S/KkvTPVJn6uVgtjI+eQNOznNzAPri8vgSzdmlfNSO+B0aJsEXN136IYfxAr1zdSD+qf0XfjrXnRx5M3qOnYOPGKQ2cQYz5PWNcoTP+o14snI9XWTPR3oI83Ol94DgeRBwSqv6WHlKu8JUB7S6w8ataGYOmDlwZkG1TUmlcwRB3dosw41aN7nm09uhGodQV9HtZRzVkPs5NuV12sqaxijmkpTjwJMjppbxzrOxtydyv/or9YDCuge4Ufd5PEiecWZt5uDxKGedNc+gj4FwacC5bqj8pvoNpwgZliUD7UpHZTErCavaRBCAGlH0Ou+ipVElcBQ2t8PBRaU4iAqgaWxv5LfgevTAhSmTzMAJ3/cvGYYl678WhZb1lcKSEwbc8ZIu6tHLGewkmI3dvga6goip5MVoqKcL+rwgGiFTuKzMIMbrnebeaCyGRd/MJv25ncxDooIkLUfW/t12suM4tkvEByoYAKG4poP1Jyfg39vZ194fdhdv+hgp5xV29FFWRvNkShSpt2gAl1z4M3B0DTLR2t5lXz87j4NdtbpkXWEXiRehC3t+nisld7L31kvY4rqhTbWgCmm48siZCNsfG9m4xlfvB26k078u4I9BaXkU2OoxuYOaN6L9WP0tkK+5km3fXr7gEZVcqcknmPEMp60Ydhg/qdTxApktIGdbrcOUfl0+szTyRsgaeXp1mFNOM/SsUaVq4zUJFib7Q7WjWQou442nV8eM9AtIfBjfpwPvita6yttOHu+ul2T1CPz3r7s/PztjtPrmtc6gIhy7mR18fOu+7bxgksBMCOpNqmP2zSAdLbuYIapgDO3kSnXGdD3183PkjPxsUCR35egtdfx+Ye0lag70543VgJ0rFnBKWXN9saXdbROuxMbde6DwNfj6AXmuze+eEq7prtDf5GPnxkks/0sA6oUyKlXFRi2Ou3gMxKasNyYtoNpKnLZ70bnLFMarJEeE2xmQHZzHa9y4Z9G4081KCug518nsq8Ld34agJZ8P2i5rgcHOigXM2PqJ9Amg29Oob7m5i3Vq77HhLcJud2QUW30yXXBJykIfsmjy7gJbDvoTGiqzLbbLoG6G529LAX3UruKXjsAlfQD3strXU1oi0+fWg73wpfP/iUfBTjfScyj8UnzsR4t1wHNU31a/l59r5Bef9DIx4uKwP27p66hFMBpeSaCNF7jiIW8BA/YtRW/5+6oxUBGz0Pi+9rLwM9WBweT0BFYR0OBzWkERYdHUKfrPMoISkZzAYYvtXNEp8YI2p1H0iUdmvIrC6hN9JkctvX8afAKOZpgFSBAnS1T42zo3OI3ZONgA0BkAy9k3zdvX9OMhzqYUdksWZw3eVzUOUdnr8Sy24U4jzHaehgBZgDFU3ALcjN/YtF9mjkMs8hnLJ7WKmZgZ+ZnNu630WSmJnUw5zaVBuTnR75LHw8cRN0YDjBC3aVBkwZqZ1ZsRoM2vw87LNsYGIywLst5XBfTrD3wnDtYne82KIfC9u+2b0v+sBnX80R+oZ+AOHmfdwcEiUbymdPserV4B3jiTXlgnjv1tDw0/irFpyH+J7dx2liyR1RWwBX5D3v25T+cYZ0QQe3rutu6DFoklujAuD1yzeWh7cx63rJOYpRJjXXNXwqiMaDzZ2Z1Q0sHzLyebm2j9gkdNGl7Kl3m1Rg/hP8n7bem1x803jvMUw3GP9VwUtCNiz3d9CaHxEhtRI7KU+M5Dxg16X2lr4CpG5UoGO3K6/EZ90Yinf7acjBU7fTd6LEz5G50lhy6bX0mXrgOcFgPpvGIYQDo6SxKN4uQ7OTUncR5dCCzAMtG7wxw5e0qY/MegAoOmLZWAGET4E98JJ5n89WDw8B18JaCtNis3QDa7fK0mAlagX4DjFvw9vWGCi5v6vEyuJb6iJXrBH1lFhAyKoj0e3w9oW9qmder7Q0yvYOeGhQ6W3cduT4NsvEYIb/NgY2XSbQo1Mz5/bME8uU7+DaM6Cuot/imlTeV403WvWxl4rcPBlJ+ggPar3wPXbDPglb0Ie1v7qc588c62D7QWRr4gW6aqGC/U/l53Xm0s68IeSRedH1aB4DtK15vZffGEhlsJhsWeWJQcM3XPaV1mk1MKO2gNgu9dBMeBcRJ+Qv8owJHjZm87jHjgskd7Z/ULdc6kvenACr58N96mL7e7+RWjHEvhmtMekZ6G4DGO6DmhLZLoJzZiMxyJ2bjaKMqmGNKwNByA9OoTo+RTyOdbuSVdo81dK7S0XWWswOhqptT6hyedhjNq3pUcNbx1MmWRsziqBL9ZtYgHT/ENYaNw0udT526OCal7/mc9Bi4hyCU9DClTgSIFDsZ1JhmvncvGLQOfl2PWCyjawJtxgQT/cx8P73jOPI3cgyzeKSdQMAtr84W7oO6XdxdLs5XvObNLpvFudQxbo+1Rz6Lcay3WIyHm43E8TtebvhxPLq2aN27XJr3OXsDHnTF+zrTnto1VYY86Wa1oahvrCouO0/qZ/RPpOX0x+YnANgwKbDyEVSAlxhI0A5t01KdhG/n5jaRLdW9vqcjqZh1rna9ID/6JWl2gfyYGh7iuvorXaoCHcdX4SVou17420QvA3qmbAQdQz6V3/WddFOcvOQYFzy4jajOZvO0RsorSEr95ZrpT+HHy3RAsZOzwxLdPf4FX8JrV7Zbe3h6gQbpd68EPMZX4aEr+0R6/UFj2VDQ3DfLxqIBvgMHns/s/H7JVK9cZ6M/tfGGwE350fwEOK0TAT9q1ASxJ6DqKTpzI6uOMJNupIMqT508SrMDeF0qen4Up2BbhiHy2Fz5L03basDwwH3tjwu6C6gbZ6OAwQNma08sY3LNgw0cemXAdkBxWSy3ldefDhgnyYPjTgEhixR0Cuj2ukZmtwzs1mVdVzaVN7NyWPa0DSBX/nmd6e0uu5yTBX8LMI4HDCqmJVDIR9enDSjjcgOS018sEM2Ug3TaJOT6Tps5NuF4N/ZoaHlcTkDd9W87X3zsYDsffbPeatPkK2FjqV+jHgLAFryxXAPECCrS+m/dJWs7T3pqQONjH8P1S2PfANvTX1BQQK/0y2Sq+JH8h/JAvhREie2nTX2Hvp3sFWsIj4eUW7ZB0isbZ+hfNC6CZnl8v/xRWU99iAW09+QP0Z4n39oeJ2X5Whv/5rZhblB9ajOJ/jEfaSYexTYUiyiteBJmtY4udcvkND1riUVOb7xS7v8b0/VqNg5KNZMgc/judO6VfeptMvOwaYO09J4ad8df2ymeqEvTiffn1vexlrlH615bvMr957TjvdRuZnkivar+n5LlXv7/09Kr6ve3mZ6jiedqa6KtuzIanj1/B4HufY9rH/3o/v54trPjMrLfjh3cqe/MyDPr+1ho/3bSPR/41LWPqb7/j+R7jr7v9bfkVx7766XMK8h2L154+t30B8/l9V6+p2LTPd98ijEfS75nx2qR5VVi36vyd0ivP2gsM0u2Ub+i/zH6WUMqleW6/DojeKLrIFHfh23Wv1KIeXQWK/G1RnH+6qPuHnlsd4wzn2zSoR42Ezs/69ORTie364ZtpcYbM1bIR7p6TXmkTCWtEWXXDiUrZ80amqd6dASb6hlVv13y9iS9RFc3IBi+ex2X/cm8UR6pyxc05VLw+NgcXXR7rFc3PJDO3L/zdGRTF9vVapmOLyHNnc3j4eH2OW6Pp7muMTYrNLOP/nj6Nlt4q3Bc6rmNMUNldtPDRz6yb33cx0XdeyZL5Av9mMywQG+6TjfN9nbloZjQl7ZBo7hiM6PJY1baq2uUZHOob2I2Jd3TNJp6msR6ymkFoo8kU2dE0L3nT3zrTBjLNbTSbDra0mlEXpHP6YfvPs30dr6goRn2of1dPw+pixPF/3byCN3n5Ot8dOGfCXRKWejbr3d9pYtJXdJ4rveeeuLUYZKuvPJ1Lx52Nq6J8foZGP/1fzztacJo2u3zlhuAAdmTBu1Tg+kZTPxkPj2ex+/dOxn+SeOd1XijzMzXuhHHWB2JZbp6vfycO088ejCAh6YDJP2P22+eq6VT83Nuh9R1qHD0CshMvuMaF+WfnFv5bfu764mPvgadrOiJj3fTjrlVhx5Gq/pWAL6K3thpQGDR0XrEVM7Xc33jmpnouQEUJVh7Oae7g9/ejNIFs/V7mFwzq6Yj/S0wy0hZzCw2wjgI5GHee93iSEfveF4/yPv2+Hmd5zj2od16ePXtrEfWs9dHOihMr0y8m5adJbXCtiHHBitYDxl9ZBEpVaKvpEsaXIeU8Xa/7no2g8gv9lDqdT5lzS6BVFJA5/dWnnSGJPXLPimbEY597OBbOv+VfGcDqPRe0ieACn3n7YL1J2bM/DtswirPT/Xb+I57ZWOk8NsBxinto6nELrSxl7/7ilW/r/I1fjCWItyjY037wtdp7KEc3fVU/7qnEw/Mfzoqrx204LcCROZ/aqKk+7sHSJ/ln95OoPG04POkLG0czdeCksPvu4BL+Oj4SaNKOMITT/cMgHkK381axM6QT4aXOieCDIFq2kVrFk41gb0hv4MhCydyFbo295pF1W0Hmkv7DenYi9cEnueWM2RhoPMOK6PXKE99aODu2oKOu/ucm9eoY2x5tgKsHQhQ9qCjdYDGadaD+ROA9qx+zfO5nXMTmAnfc6lh5KqjWm/n5t5lz+7xvMa9M9uMaxT5dhduXvGjePSsxl2R5c0zafCBOld9ZZMNyz0Q3EApY+vipjOD+ucagOA3s/u9hq+0ecV11L2dKGivtimbWdz2vc+MZnc17icQoo3H9h85TwIenkWACO3H+yT1l2RjncxDO2W/7voYyqV+oPdkUNdNIOwLmR3v42mTDst0v/mp18T3mlla83i334Me1zd7X07xY2S2klDQgU6GtHGruRf+d/Hvf37vBGrdb+irZE99M9UzrQxCWN+9QX9HmzS6w8gdiGpeBbldvSpXJ+dz4nqTXn/QeA/tKygiIGMiaDOzBNq08e41pH/XbfR+vbvWjTQcAOg9PZ2+NZCRaSUexdBPdFrgpaNVrTcqspg1bDsWHVHDn8uedOizmwBaRV559EdHELRVLg2OttucwFhT0KQMml/0HTRH3xZp1sJ/oy01yPqC95CJi/wlOHOX4XFWQYPiycnTOc3DNehSAP0geJpm6dV+sKXuVXXpmB2C1mHGzSh71nC2YDF2PrfmOWJ39J69nPW4nUXrJvbtEX15vaDLmN4mgRv48HryqwDNjHyO3K4hA++7PhX0pPJsX+EnDVQae5lW2zUBKgKWpb90jXS9rFyjAlRfiYZlPjqA2r2tJQbAp7Kkq36s6Z9FVwpkDHl5Hb4qYhN5Wp9lkEieG/8zyNsp/6mNDz5CB49tGdFViiVLRp4ioBtmxthr+k6gSPlJT6ggdxdju6Tx+amlRAoyFVDqEzXNoz5Cn1pq3R3Y68DnSU/M88z1p68/aHRllXdRWm64uHbY8JLWKhxodo9Y2aiFzkraAfT4my5vB7o6EEwZyDsBcjfi6AxUeaBj5s5hJtK7x2ccx3DN5djZWlqynqc4tINDIIjUmVuCPoKwMnr1wCPOtZO1u6d6cn4l+Ocq6ZTVblGORyftTJnPEKGxpZilYbCa+3oCzV0QIYBPlVkE5tSWt8/5+FhieIljjOHDQv/zOgPIJVDXpNtj6Vv9+5zGSwDIRGcBWb4NJgHTpQseEr4B75Lr5JA9v4PgkNcDHGQPOnPnGZrH263p715ha2tdP/Hr6mcuud5o1yZ4jQF5NH/Tz468aHBsgFwxHPZNv8b7TrMJsKUPKvgCTQUkNFTfGa9lDPV4u7VxqDFg8sbyLHdv4Ok8uG4IsNr8qgdve+ikAG3te2PTL/FpWDtL2A1WLw9bfp3d1PMiWUfoWGL2KQYmMEZ+KBJ1h37WHeujtLt4dorp/qlnQPOzi42+7EsxiINzreuZx++8/qDRkwbyLik692un/LrG8UTPgYmCpVPZNEo6TU9f6tR1N+LoRlXx1z1GPSTn87qDbVn8TdBllg/L9hEYdaKdIN4kAEfMjtGBYH+dWTg/5UMdlMo77ujhFHgVxVilwWDUnXdoIl+q13kifQ1a0ENyPHZICvAaukPo09Em3vzeqLIGaHECqivyblaOw/GsDkru4YgGkMSM39ILD+lOj4eHpcfYN9bkDS+rjL/5Yz6ug7o95sv7Zm+gcv287DWQcV36+T7/8bTxY0I+Xs92OBLAsazyAGf7pp83OGJNNYMKAY72w4lPSzTTH8Fie6C32gGXmhBYDGQT35L0Y5uvlFcfk3s+6qvRXQAJ8BcXtB+Jv+h8+cOD8Gfw7Ye2TYNo0U0Cl35dfGwBZompKrfXyet8bC0DpB5AyRILtQ9ODiQ5ZhPn5qYTvMAGGRuD5sw0U5s3ftaPUNJrGku72KOxrou/Dg6VBmO++n8FrE6j2yzK+N7xFwOWgwyaumtNev1B4wkMdSCSDZBGDjM/nk6zUZY/T+W7xbja+B0tHYHRuZ6M1/OnqW15pN4ZuI5cmN+TPzJQw/Y6mD/yuu7ALwEHwVh6dL06DAG3Bo54hCHOvBvd6VmM5KmbJVHn2nW61H5PdEryNiVYa74ymMhAIa4lnjirwWLKFwJm8K2BgHoi6J22Zxm8PRoxh9k+DBn0COyL6Ld7sY4xieuBp1HDLpruz3hdmxkP4U7F1uziGWw7vbllYkwb5HVClTN2Q8/r1fQVg7ts02/DnhthdXCxZCv5MpOpPt8VPtOgLhSCsn5dQQP54u/Gpya+Gnt3IBHrg7nm2dtFbVHBgV+33bfKDFIYZeUpJfymX+tAaUmdrVsN2HGPNFnUyzfr3Mooauks+Vj0u8T3rGVLv0d+gje3A/Uf3Sxkqlfy6ObB46jQ/T31Rd9B/Yl9nmJkIi+TLp6v23DI+26v+qpA5j/hgC519WlePU2lk0kHCSdQ2JU78XZIrz9o1Ib3z64jE5Rog6uyT1O5LH8a7SlPp3o4E3caJaihpQ0z4EFHqUqTgE9HXrcMmzevoywmlplD1qfrI3UK/3iczth0mcpoje0D58L8yUlqoGM7MEi4U7qgnNO+0+GKI7aGHy0r11KA6+z1WvPr7kLqJNocwaM4d7bP7X68z9jzXaXe4B3yTttH0QzRNVUeM9cUS9p6drqRqrsYDjH90XIcrSN9bXR9dWDtoueZvj4RrxJMRbYsevSOtl8A2X2h7qyPCtZfZ1cT5ckPgfmwBY7Vb9HOUZ23SZpl6wL8ITgF6Lszyx7FFbygj7IfEgCl/kPj8XvzcPxJB2bu/XYDGjmP/w7fJMAhZHuVgCzyFkApG02Cjyn60P5DWo3/5SA99VXp00EL9R4B6SmPoZ65/Qx5TbZzsLXOt6V6EcuunIggrdFcB22W1cG5X7tcKhbgBEeHHYJH1KV9n08xukO/tR7G2S4m6QDmJPMz0usPGpmo9A7YRJ5LPheP+dqRsjQI61BQyLrUmLuRw+Wyj6/RUURX171Rg/KawCmMlHToUDgacyPv5HKAxbWZHQhPers80SbSWUo+yi5BRt8O4CNzykW6/iaYzYBlZ6vBzYQWbUw/nd7+6IE06/RP3CMAPD0CTKBmWgUM4C3Va3hP68XyeYXu3FQOdYqowtf6aQw5JtdlpqOJ6w63yDnQ+eNvn3VMG1bkDS6p+rHe1rL0vF9DiMfUyyZjY83A8UJzrX2844gdwO6+SCB1AhCiCG0+szRAi5nQuXWxKgc9pQm748xja/sKLMSWEmnpn1vYddtBwrAENtmnyswWaYz8vYBkDYwqg+hYN5OVBH+iIC7p7F66A8wiSxPko4jIUwZ/E+AZuisnZfjjcPDe8RNgLzGBMuz45Ifl5XcXf9WfahulY9vg6xgPPJXzitm+XmcT123UgQdjPK+dkvfFC/T7FFClXpQvPTWki+eUocMMvNdhjifS2ws0MnVAK65dGyO0ms/vc6TwHMTf/XUgKdZD6Nq/O43LewmoXTINjmpOU/Ing8sVZp6d3zH2ouX24FvhTQEYASAdXqtTCTAKwruz5dpHP5RbnTHuMYh1o77Qh46UJQUdrM0p+YVvswpq3cHNaQnMmbRfcurLKSuw9B8lKPjHSJcSn4Vf5JsmgG4VEZCXac1UXvPx/c83NcpmmDhUfMsYZyqOGz9pXeFqw9vj8Q24/PEyZxb9SJ4AljeG4h7XN5rZeSNM6GKsuDt3jCwBtisnNARw7fMneV6miU2gP4b9AAj4te5IrqhfeFUA3IJe7dMd2Jqyi3buogn44p5/T4M08gd+oq8rQFo+AnLv1zk2/iitBdW+IL+LP9V27nSk617J7xPxgAPMVF76XvAqumhni9UBoO1av0NepV3KUT2yvIDgPWLH7V5Zz1sGFqve9nxH3FfQVWIA9WjNevyR6THFa0LnIU5IWfWTXX7S0nOntVwHihUIv0J6/UEjg7rZTUF8rErFnt4vyfJ+vatHF50WgxqNYd7h+SSHAs1u1BKGJWt4TiMT5tf6+ZaPortmhrIAvkaGNDr00dhD1lkqh45d9JqQyeZFR6MJVM7cvpoYcNpONev1APqooyee+Yj6JOit6ktQ8PbgpiSXfXpZOnAJDpvw/vTgruqI+jWYeNu73SB/Ef1287bjeFc5kp2YBQgJQOBy2f5cfKa1hE4Fs4ip9vKWl/09Dux+zLOOsYsaYHHC/rzsuKz3VU/uuj4AtHYmYH0PkNnYveswAO7Y7RIkFRCs79rcCmDCZ3GQi8Df6DmVL+BTgEJKvA8+ktxu9xrkGyCQqlBg4mBE+AoQckj+FCLJcKOZgT99/My6Y3n1T+GTG70WEKyfLgd8bOu/vF4BMWWQLD5sSvskEIlPjYUKDoMHGQSHvdPvQ6YEkHENTz22r3MSXD7hnwd+UnwaOZbdA2oa57yMf2osPT1OZn4FmKTTDTDLgBu/y9KveZ+/U4x9Jnh8/UHjvXdCO7Dwe93j6O672TYGNpDPVnRGaLYNLxnjrPT0j/fJTwd0PS87sjvSzlC1XBllSuDSaXY1Ss7sKAjV4Ek61A8NXtuv69xJB67/ri3nbnOT9iNITPXMXk8MZB0oSLvG6dAUFAwEbLmvNNPvKTMwktKBvWJLJxDs99KOTXXAXVAeVvx0iDLzX3zlo9uRy7bfYSPDNgDVvNF8OzgEmHNW+dq/BRZ9dvH2/WI6K+q83t4U84C6d+X+uNkfx8cO6icGJu0j7OvVAkiHkLf23IB04oO242+oGUtl19wuLOfnR6Y+OkS3aD8FI0egI/Wxv4RPmWLy7ANa3x2bLffc1rwPEJA0vkHLdjKVI63Yt7Vfo1+e/Fbike2ockFPrCPyum7QP5JPhLydLyqDc/AcdWlndL/l/v0ieujairHiussWnSThbPsuWSowpRz9XRerO/l04oW/mVcBmN73/sM4lGKBYAKN46ynO8O5o3e61uGSE/+Kb/7/deTOH/yDf9DitVv4+yt/5a+Ymdk3fuM3lnuf+7mfm2h86EMfsm/91m+1T/3UT7VP+IRPsK/+6q+2X/3VX/3YGDoh9M5YdNHr6dPLsew9NH8y0hNP5Mvvd+ApjZyEr8LvNcto9sQh4EgEDrr5hd/DYGVEznwql9JRp3Y6skB1gZmYtt5Olx1PbdAwod3UUQCQzMhq4G3r80CCIKBOOGZCmnZyGiGP2EJ5DE7aqK8cBI5AwYB/AqwhCu9XmWP3cMTcJniOke8FyLGtV2U1iu97PNx7Yx7MJK4/B30BEgNgXuIz3lXdzE6mx9jOgxlALFUyNu0FhjePl/29DCbURipNvvFmf07QC+IAocJ36B1E5i7XVJ7zJ/PydtRgxSK0Ke/TZhmw3QEkXk8A32YjBflXn90N2uKWP0E4zVI2QMfruOebot57fakBQh2tiAfcENe0bYBgvy7+LvmOeaPlR5vF4Bu7tZk38SN+ipMXHbCuHVj817DsTykSZDrFsBSzm6eKGk86Wh1+8L/u7S2nxNitA/oOtLNe5unqVABMOt33e9ea9DsOGn/+53/efu3Xfi3+fuInfsLMzP7cn/tzkefLvuzLUp4f+7EfSzTe97732Y/8yI/YD//wD9tP//RP2wc/+EH7yq/8Snt8fPzYmNLDm/37PePivdP6RObnwd4s34G9k+H5fa1X+fEyHXjqDqpOuhi9wSkvJ92kjuvlxn0+lcfNTKWTC0O/D3Y3JScG2g6UdZbgnpPWKSyVOQEgOMG0kL+zF7bXQXZ1qCZ53YkTyAVtp4E1SOEAlZ/lOAMceF0auCc+yesTTlFBu5dNMcSdW2UtZsqmlxvB2nx8NJty3mDw5qI5vwYgdyPg6w3jMG9sRuHbXnxtZFr3mAZYuDfGpjf3Lm0Hx+1sYgBTecx/bA/VfUdTys8boxW0sq+ijWnjaT2oAo1QgJiC3Ev90XY/naiTILgblAzfeKU+wu1KTldQHxNlu7xiO1GefFAs9/OUuWmH7tDonEHKs6+pftWnckOS+DXV35w1f3mrCeyLPon2cXmwsJk5t3xFFpO4c/Kz9KUX+a2+Gro4xZjjABV10I8ThPqm1xSbD5M0WlczQLwbP5Wef9ffrVxW32/dHf1zb3Kl41fleCK98eycz0yf9mmfln7/rb/1t+wP/+E/bF/wBV8Q197xjnfYu9/97rb8W2+9Zd/7vd9rP/ADP2Bf/MVfbGZmP/iDP2jvfe977Sd/8iftS7/0S1+dKT3rkIdlMnW7rDy/KlhnJdVQCMwUdPrvOMdu7utOX41IO0w3krhV3OfpQFtnwCp/lHHn2+VpjFtHNS2YVF65AUmOHHDwcJK9yKUO7iB/u0Pe6jWWLeu/+Al+lN9EV+1lLf6eTkv0Qeepo/FSP8rT/lQXZlu3w25vJUnrwBg8aech5EF2J9EElwDMmcQYY1OZU2LASHpJYG9Y0vMGa+sSz0dcOpyP1/2WFwK6IevWHJg2bRmPvDXNW51x9iP7yr0BnOon3V99b45aVs3B8Dvs1YyHkj/pN7w/p3WFlu7fZlw7OzQLplB/qUPP/qR9pbrdL9HWFBDoPe0TyH9BH0uDK+S/zsqfyz+t6U8qv6ZGN/HzxLvzOPJv9eepDvSraAO2occs3VQD2WiziV/6pDXzyPhV4gV5ZBtLnEntOdNHosljbpwPr0t9OsHUaOpkm7UAD7Eu5BiZBy13wgMEmt1O7G55XEerA3gsd4q/rwAG62CoT7+raxo//OEP2w/+4A/aN33TNyUH+1M/9VP2zne+0/7IH/kj9i3f8i3267/+63HvF37hF+wjH/mIfcmXfElce8973mOf+ZmfaT/zMz9zrOtDH/qQ/eZv/mb6M7O+kcyeVmZniGYWu5C1g3QjBU+cCeEoh/Rt9PmYkvGMTUcNzD/1rCfyehoJ6UxlbPGfuf4OjEaAg65SXeuz23Dk5TRomlmaoQg+Kful0mU73Vv4TgcV8ndODykFlK5jSyfv2pzyhSO6s9C+ALRR2ALhTbfY6iFgeVAclvkc+qnB3unTnp2WzpiC76j6dp1H1aT8qf5b2QyAhD/hIcAlrvtaRgeIDix1h/M+RkeuSzt6Hd0h3rHG8Y4z3o++B66Ngz1NyO1O3t/Z7bZiphX2ALcJbP47PfZyetuO9JWJkZFAYE4pj3oTr7R9gIT43fThtIli4j77ykpc3zdFR2X21MRfZdtJ/TIGzFyTLKkFd84/QRDpKA/CW/IlpM8+RFB2+J30Dz+TZBHfc+/Q9Hai4OCkeO/kn2mz3VuTNK7Q/gjuToOkBEpFd6p3tk13VB7X+nc7q596baB/6ktEPB/loX46AHvCNgpOSYP3n0i/q6DxR3/0R+03fuM37Bu/8Rvj2pd/+ZfbD/3QD9k/+2f/zP7u3/279vM///P2p/7Un7IPfehDZmb2/ve/3z7+4z/ePvmTPznRete73mXvf//7j3V913d9l7355pvx9973vvd2Q5WZGlM6gIMGNn4BeId1E50B6neti2CMQbQbZajhdAdeaz1lgfuBJ88fThD3005dswQElUfuHKZzjo6xaOj5jgpmivOEA2qNHJ2BdSXHdMd5UAccVXs5AThbR9qpmxFfCgy26QY9BlduLIEDp52wPB4f5revUC5eY10jZ4v7Zq2tRNX+pXGsJDhnzOZtWZBlIq+ZFZBgDX80EzeLi591aEtFc8Wwm6zp/dOh2s2bnqXIw7x9t3TMRtJevS4vd6mPp6nH0AU19ZiD5UT73oAubB5KSEf/PCiwRQBNzUhfwzzL53FH72DZpt9AB6X9QwZXtuXy2iejD8nTgO4cwa2CPoAWA4N8ZfCFe7ki0IjKcI1ton151vJFXpZ3X4kZwE7/BXArv7PRBeuzHDu0/PE1ibQ9lhW/bpZ9tpno3GmLDEF61DytXUGmdjPTvbhm2ZeSbgsczUqsd1oEXQSIumvav987bscTQeUpFeyAunh+o+47GKL77u12r5B+V0Hj937v99qXf/mX23ve85649rVf+7X2FV/xFfaZn/mZ9lVf9VX2j//xP7b/8B/+g/2jf/SP7tI6Pg5a6Tu+4zvsrbfeir9f+ZVfud241wh8bB1KlGuhVHz3RjozW3+3HXaly8XscS00dpCmgfvkFNTQNXWvICr5IRvlGwMOzfNca96uM3Q66kZDp52MrIPOj/yHToVucpBdYFB+RqWlRwkd80+At6bTczF4oXkoo9e6zi8zSnEA9y5U6zfL4MDLe7sep+02q62DnzljnAv4COc1NB9oDMuPyZXoxN+wAGQBGD0uDzO+YSUO5Ha+vaxZtCnXIka55WvKOkDYXswKjr1msZup9DWS8/GwLtqrbf3JxMdWYJy9OE2A55Lx4bJ1UtLJd0GPLXCS3wnUME8Yyrap1K+8mNv4EBroFzFDpnV7f+z6NQWnz5SlQOxjaf3a3DQ4m5n85cx5W+DJPksApkAK5cfiZaIOtZk2no0s39C2WLJF/xUdlR3+6JdT9QVfGH1t7vrVHyeQJjKlN0sNK3pOvHY+0OU6zPR2gIhxqQPSnU0oFiDwoh5OmEDXITrdbq8E75O3U36/7mVZzwkbtH7ogB86cZ6d8xXTf/kv/8V+8id/0v7CX/gLd/N9+qd/uv2BP/AH7D/+x/9oZmbvfve77cMf/rB94AMfSPl+/dd/3d71rncd6bzjHe+wT/qkT0p/ZpaV0TV+MuCVNFiYWQFPOjphOu2iOgFYjmy6GcRuxpDG2hm98kIDJ7C6Eeh5VYCmIzY6y267fruFX425MWzVf3G2tsvQKfs17Tix4aPpSFEvnbpZfbSeKpagJ/IpiPXgow6hnc1gNQIyjx17WJ4tUB55SxCYyz2G6JnOHI42gYWZsmy2ESRS1sz/7bxBggkODKmPueLiAP19n0AwATfGzLXjOfILGIzZxTVryQO704B1yKaWuWcqYwMNZhwTL5K69ZZQxqHsXNXelJpnMGEj0zZQWHyWuoYQn9JucV3Wh5U3F5GMAh2AokILdRX9wKhclvih/UVoKVjs+FUwFGuK5boO2Fr+qXfv6yb6Pw0KOh84c5aWd6mfmds3RGm/Up+p+Q78RB6CrVFtNKq74L6ANNc740AZpFGvXve+fjv+auy8bcwSmn4e8Mmf0h+2sch2nfxMT7rwqXiBdNPEiGXdkBcF9gpEOzDZ0VM5T+XvpN810Ph93/d99s53vtO+4iu+4m6+//k//6f9yq/8in36p3+6mZl99md/tn3cx31c7Lo2M/u1X/s1+6Vf+iX7/M///N8eUz7K8Abo1hmY1Wsl2B+SGqxeIx/++zRKaB+di6Ep3bg+5LdZ7uR3+CWPyote76b5nxqx8G0mJ72qoeuh6Taqfq3pQAqwu0GDlyVYVwek+kzte4V+4NDYFifdptQ4Zj5yPtmozi7wzRS8z1mABBpgL/dmu/zxYSrzhKOJtnISoDFsrfUjaNgbSPZMXvy3H0Obl1fQJI+WzRIw0/WNMUMYedfM4MPFuEEmAcbrNUChbwbxQ76DR5YJPVg/iKIKwxy7YDybAm7LrAcBNAEb+R7lBFhM1itBk0tUyHQyA7Sb+ohTcFIAqQObdq2fyuiXm+VDabPKlGvkYUpfzuzvfGr7Y7et99kYVB/qS/1z5Gvsp91xQ52vpH3o5rMr13+uvMVPq+6dbfdB6tvlu9fRngm5fsc6zgbwaBxT2bQ/rXu6ca2ND15vzNQ1cavVqdV8HehzXOG8dZ9m5zOjO5wRvGussn4j76lflTjZ1K8x7Yn0uwIar9erfd/3fZ99wzd8g73xxt6g/cEPftC+/du/3X72Z3/W/vN//s/2Uz/1U/ZVX/VV9qmf+qn2Z//snzUzszfffNO++Zu/2b7t277N/uk//af2r//1v7Y//+f/vH3WZ31W7KZ+pdQF2u4Edc1/Qv+at3uDCuvqrqsBFl7dWTRJQaYGIp7jl0CmTLd3KRyd8tPI33Yy6C4BQqXJINYEEgXGejQQZw61HPnRTkP+2wAuwSDyk97FUmBJu42hg6gb4JHtYGz/mevxAOFBPXV4LqC3XSbs6pKvdzM5CZygPWh/KdjjCwclaSbxEFBwrM8+WsbJuX2ifI5Zuf4mxvo7paO6iUfLjKNjZGAHsBgzi7g2Ozsfvjv7uj8fdgDcj43nyj5WfTegad2RYUl3rHPmPLTNAohnpkO7H/6ft9tYH5d9L32CXrCkAVAaKX4eGs7PoAxaotuuzQ15ywsCpG7SCuCM+tvZvFPyfProVDtQE3gjtqBfd4P16N/Kl/Yt+BAdqJXQ0rXNKnt5EBmG+D/tVOhPnLUM3cqSl8KD0oQsg7RQpvOpKQ98cQtIwR/1yL5w2gCisigG0NjR4Ydy7NfIZbpYr3jitAmGZU4ArwOtJ1vX+KqDwifS7/iRO2ZmP/mTP2n/9b/+V/umb/qmdP3h4cH+zb/5N/YP/sE/sN/4jd+wT//0T7cv/MIvtH/4D/+hfeInfmLk++7v/m5744037Gu+5mvst37rt+yLvuiL7Pu///vt4eGJs/q6tAKWmWXjuQuc7ijcEwFF11B8LHICN1pn/L5uBxRAxXre2Vn88XY51FZ56zq81J3oiyxHsNt05o4Xz0v9nWgmYGP36Xcbl1KVjU5Kfd3IlTS4c07v3+mk6gSHmdlh44yeOUln2L3pJmQe0n4Hx0oZxqJfWKdNQ3YeWXJqF87SxKHIkH9OiyNUBmgFuVmaPZGettYzrlm/Bhinw7mjaa/mADLNIl7GBp/jxh/zdBtb9lmM17jH2cW8SaZf5D6p/yE679Yip75uN7mnRVv6weO39ZOW+3sCdVnXqb1S/qi8KXPK6/V2tqHlngJwoN/NjrCPTF5/gl4BN00ATaDvjh+nPibyUAfuPzs9BC3ZCJQAK9rIUyKBPF2f6eqbXk7vq/9UPuBD5txr8AfpOB9z0ztOVtBW4IOTDho/mMS/ZDotuPI2kniZBu2J6JZB+2OHH05H7nhdQ2L2KRYTf5yAocb/e9+1nlMMTIOt+2nM9tTZ//vTb/7mb9qbb75pf3L8GXvD3sjK6UYqTMzTqUdpdIbl+e7R5wiFZU+8hSFe0GkvvaHxuz+SVzpP3fPfHaDTulRmJoK7Fojd6SgE4aXjC+1bRivAN10/gdh7vMKx6BqpewC8C0iJXzi05Og6WYUHnTlJM4waDNh2FB98XTcgvB1J89g4V9IVRz/sNpOWANIhiNEZK4u8XkDK2NUtvXdvegnAFzGrHq7t19InXi9oY+zzHLX9zAJgOiBMIPTU7y8Xmx/+8ObhjTdudb/xxo3GRx8t2UIH1MBDbOCR/kNZsj3cfqeNP6wnqpH2LTZzADK1MbMszKN2HeWk/a9c/vFU3ewjCna8zktDZ9a8JWn+e/pZ+dlvWt/T5UE/03X0yl/4bu3vKssT3+nXCqhu4o8Z+i7aqx2wPlefyttT+nlGm7HfMs5dVa+Wv7eyaowaZt1EShcXGaeVP435z32hB+t4CqM8Kz4P+6h91H7q+iP21ltv7T0hTfpdW9P4f3SiotOIwLIReerAo46eTsBKG1qvz5kNugOdarzX9Zirm3Xs3n+payBYr+qE/PEQ8m4UpXwqrZS3Me6iU30M7W0jzlb5KLsfu4S8Xm+nK9I7pbQmc2RZUzAGzSijXW6VCR/IoEadX+W+5wftPd1i8Qgp6cTrEd6mGW18xuHGbncamJqAvBmyvYnItj6ivtvX2OVcfNjIVTiPvDBt74w22zImsUZ8TuiXs4Epz3U9Wh4WQEzXQ/rnXne5ZvYIGM1krSb4Pj3+mdPsgiA6XY/Q05J/aF/EPS/rO+nT4+ulgPHwEI/nU9NFFig/9fHyxRKBgfxpCQbLLNruU56aRUsgDwDD/UkLkpb9pWA6RGf0R+hrd1PDZ6FjVv0ieYZc3WBPARFBTth4xwf4S/dVLuFBy6cd5o1uCGxinaQ1sngRKa99gnpjWylPq79lsAZb01gcPKDNffOL2fn9zp5fY14L1u48kWLsdFrdm1uYmsFfyx9js4JB9QsdbuliFXl+Rnp7gEY9xiaBDnEwPKRTRwpMXcM7bTaWNozXqQZKvu7VQWPWmc3L5fzondd1/cNJjigzsu7agHUnHcuirlvGnT/lpS7VKZslEJdGgnSyuOf5H2AXT/EV7SkLvhkQ1Mkk3fl37gJcn+XtE+JMKVOZzeE1XI9NJ77W5opPDSbUa4ckNEA3ASeBw30/g54NVE6v7rvxbLbXJLr8ZHlmM8Bsi7+NxYHdTHyBY7S5z8rN651HzOKA+TuVueZH23dtn3bzmANhHKkjjnw+rmChYk38GLf/0lmPS//pGCTPTN0GIIsaUV+vy40zxL9mznddNJGUt6Ov38euKwZ4BDgrnw42J3XjcrN/YwPZEUR2fYNggZvpvD2bvtUO9LS+mXWUfN1s8sv9YZDJ5RUeygBhyZQGaWgst8X2VIzUqFnfugZ9rmuspwwOorDFwNYLc/Afb7zyteZdu4lNa3zn5h3/5PmLxAtXkeUeYGX+7gxHYo1uEuaEQxhnOsDa8dTlUWB6Dw8gvT1Ao82sTDNxOs9Izzlz0OnqOVDM19VJ47gH7LqG9+sqVxrNWZa/G5WQfgLV4LcDwjbrjF1Hu8h44NHM0u6608gs0QZ/DqaLc2T7iy10etDOWnTqAazhTR18OUONDnZ99/WoiR+tlwvQG+fqoDScLJylO2gHkz5bTeeegKnSRx0K5iNP/R6HSg9eJ/0N8hKQm1rGNpAce5f0PnjbVTRT/r0BBodiS/IZRp+ZS0fzhAwWvMXjXfQXHrjNslBEsZVYDxl9fekmXtGntgUbUnW7rsaqu8MUcX0muRPgC7vh92G5LcTuwlS03zd9Iw2IrhZglCC22J3auS0fYdWHJFoELvQx4KHzhSUmdH7Ky8ycx78nUKb9RK/ZIQ/l6vp9V17iRwK1aoPrHicHUp3CTwI+dzbSkEdvo6RjaSPaBK+1h477pcVD4VXiBuno4L7Yydi+Xt/O1l03y08JNY5pDNN4M6XeUz7KXE4SsZxX41qHPzpQ2sXsQ3r9QWOHpn2mT0GBWd2d3KFwVTbr6gAb6XWGomVjZII83UG2XWCKz8YIdBTSgkDLsqmM5N3T5aGWT6PNxhh5SHg5gue6HYKPIDlaK3oQ51F2W4u8vK4OuGujtLOPbeu6EdvwvPtiz7cGp6RXoev3W1oiezqnTQK9AwF9g0zy2xKgghXITpAw+SgUQCJIjA0O0myOiDDnzjLN9uv11rrBa5V9pvaymKHze7yvx+Hoo2UHggFi49WGi5bvgp7yogGCXst1K7hkSuAzNhiNdU/7b7arPYM78+3QSVEU8t2CT8z2hvIsN4viADYObw6nL4H/OOuzCCYdpoqkb0zcG0J20SPoVP+TnshIPvoBz+MDqyy85V29s9YzGtnKkwUzaax9j4NdLzuaBimg1vngsoiLJX+hwGniegGSB3/t98pjTLUJvWcH3+b9opkkSKeSwGeUmDV2u7DNhvwllmatL8RnzF39kjGIAIvx+gRIu+8aW7V+xRrKk+dTmUiD106g9KSTJ9LrDxpbsCDr+xho3Uj8XtcY98Ah87HOewtcW1A1s9O4NyPqnSzJKeBX69PR4knWoC/yckqfdSm/3ZlcVQDbDpFoY9HRHculuOxcM2mnJDODnWxqsS4PHK/OToTDhwNKjk6DqPOmgc6sBc50lsXZM4B73bbbpg0s5KvTt4M/l8OD46E+LzZko0nwqqJDNxEzXKfx3+Z47XYOYOWq8HMSCxC45Q3gOM3STOSilY7lQUq7oc0sXkWYHp9bKRMi4f5xtlLT46PND3/Y5oc+dJv9vT7mg9Q1nq8LG/AO3GPdc+cfZub8x7W8/ixAP/uY4gC3CR28JL/jzGi/6frFwD0RNi2roE1OZOv6GABU+6YW8NQO+KbM0klfKKgafDGPAtHT4d5jbBl1U0vUOyyBzyG/gw8BWgESVBeNHxY/kGUEv10qZUfNyxgSvM+tc/q/dnAcHXrnI69XjZWMZ/ATp/h7Al0R32bOq/25mwE8gVbmUxCqyfP4Y2kFzbzOP6V3on0PXB/S6w8au5EAP836DRHl3KNmvYSDQdZDGuSBjd/l0frv3Uugxe81m2kIVj2l3+L404hZeCn3JW8ClNT5HRplNGnZeBXAqW6U333j0BZNvgQ8UEZBc5fu7cQ+1jvxp/w0ndwdVvg/2YSzkVR23jFT3czYuKNOYPxGJ9bBBfsSCDXQLh3q49k8YbGASxr5LrI2sjpYhvFr2gZui85+bOxk8eo/0lplS5JraQ3jWu+azm3sjvxycLjeAc0Dw7td26m+j3zkcGPa/OhHUUfDc+iGrzw01Ik+NE14yXLn3eZuT6uSCEK7PjBq1Y4JIGgMqUYL2ywDQfoDBxOwPw5eptaN8u3B2o1fbtceko8hPDIfjDYAeVNPqx/2dd1AYpCN/ZTg5bQmkj7B/zo/tWgfwSPyJNC52qRdG62/hWbY2KltROcafyhnF2M1Pg1pu+TvFq2T/CkOHSaROoAYcna8N/x26xpPdfA6cQQ33XR8KP3u/onPJr3+oNGVdRWD6Ro8AI8+FjCLGS+CynujCH7yTQopcMr9boTQjWi0oe+BqW5U1dElL2pM1NO9ztDp9m4So9bHHicn0MlMh3V8JSR5VzmVd/B/PNdTHFlqX9kA8lSKNY0EcZChm8nwwB6zSuDbZSIoDtu+7N+JPgOjyTWXzzY9/5yGR7lTyEw8SjX0M8guAG/L4iLPRXqmXdO+xtE/4/6aLYyjZ4aZzi7qzGjcX+sJ5zqIm0fy0PkmeQXIpjrChJ/TH2riO64LtoKe8syrmQNIyjige84sxmNqmmryRQi+aUDo9XujoSEDRKktoaG7wW+Z6UJ59SsJqJEXVZL6LPSR7hgcnosL+0t6SDOAHUggY17PiU/I6e3APh/9tQvXqdHyX7K5IZ9SPzfOEZiHn4BM10dpBwK/k99R39Il14FvbIH9KUiOSRyPDQfdDJXbYHfX/f7rWA7VxUfxgQ7E1Xa7Y/N0f4P/ZozS9ZOlT6x7p3yKazR/hwM0tj8TMJq9HUCj2VZsNyvoSXdQdWArjT406Fouz+vR2DKjydcZdnV2chzfZCK8dyMqdkJN3TupLw/VILvRVJenM8aus3E0dwK4LoPKx4Cmm2Gos1NSeZMsCF7TRB7RbQQN1g0HeJoNMdFNsgMGNxR1WVsADx6K7jBwYZkSWCRI78zCiK3NNI1zs/zoeJZZe+q4pht4G5kdUcmtqgXUsPbQHyXHbB82t+g7oo1AK5rraumd0JW5eGxOWeKYHgeZ69WCfEPMqzhml5m7zAsOWXZyWhrgr13c7+zeQW0/ssfgJsXG7tGu52FeBxb87V8VwDnjQjqOQMHfkE8Ch+RvWJcbiPcR6otgg6mxcd+g4zbH9aNaXm069SkarBhv6ARGLrZY+wg7g9IxK/Y1hUb5jnoI6lJbWM7PuJV2Zzf53O8UP6OdWuQg0CtgkzqTNm91QLma2OlgmfGjiyFO5/p4+64bCU9lNF76BARPOlEAGOoYtY7g2TadpDORXXliPfr9mQPbtwdoZHLwqA12fcznN52AElP73ku73wAlcAo98nQENPitdSog05E0QYeJQZM/s90xjrQb4HJ6/K5gSjtweyA36JKX2xeRBTSUz86R0MmT37mcy71yadbTR6pN/sRvXNg6SM7amu90mKiXAyDqwpA96vZyukHGdeM8oUz8YTRfnPfcj8AV/AZQdICA1/qFnxf78+KX/Hg3ZG9Vy4ALMY52VAjcLvvrAAd2Za91kw4AAxxiFlPpGMterwHSyoaYV0kjCzd4APusunGAHmD5QQ4A7+iny7cGqo/VvS1v92/0tQ3dPv33PXkPQdnrclA7d5273xhsc+WjrZtB1sVHt76x4XFwTTvXlhbepQ+r3y4gkX7f6cq6xMQPfbvWrUn9Bvs99FBOcXCSqLOjeaqHfjeBctYJP1Lq0XZnVVzTLSmplfqctY7kZ+7sC/C892I3AXMHuHTgkPwoaDh9nrWo/ZMvSTjFKv2u5Zi/A6YaB09tIen1B41do3rQpQL1EWQCT/IoU4GT5jerDcu83SNmB7JsbDUqles5DT0PhhmAR3gnzfJ+Uqt1qqF3qTPgK97Dq7qK3+jwrhsFPqd64jBXkY35ioOAww9g84T85OUIRLn+R+1HdJx2M5J3uU5naGZpFsbrSDN8HjQ8iIL3ACYun/MOObtF+sn2KTMClwOcsvQAKoEczJd3Hufqd71bln5jC9rSwQX7gNNb3/fOaT7iZv/PfPm5h2lmbu6ZxgBxp0HFc1PEvb056AZwdp3Oh77xJXib0JHLzOZKFYlMXiYGBV5wljbMAwwFPq4H3tMgLboq4G7KT97vfBn1Tr7FDsZhQ1dK5F37QTfYnLnctNpXCYjLp/sqrZ+/l99IgJVJOg+B1ZB7dRSBfCbAY+x7BKftJrwJ0fQ+/ZgAmygLnadYYpW3VC/qax9h265PY1QXc7vv/K04g3xonNX6lacp5Z4CtWb1EbkCT00aE5+RXn/QqAHcDUenh9No8VLX13kZs9x4J2DXgUk1At21TYDUGUwnl99TI+fown8r0GB5raccg0A+Qa8zumS48kjJ61I6cV83x4gMuj4u6YJO0Ms1bZI6qQCfFPD8q8+aNW1RdiX6TIV27tmXUUCZ1vLYlmdQNjvT7gDphJwABZEvAiscszE7g+/igQGZ9Bm4Qt2rnNOS5g2+D3FzXEbMsAVP0xZgwxrC9JaYVa+zu0Dgfjfzjc9433T0IUupvH7wIa8rCkDcAQ8HcrKp5pXTKUYAUCegaBaPxtMZk+PGQ951jvZI7mFuuQbyrnuJueR3QMiBuhn6HBsR91RI2mW37jCpcuw+qruM24HsIeBPs9T/5zyX0bKpjIAFLe/6pL80aZNOf+x7ChxT0O941TYiv1IubQ5iv/dsWPcYl5s4Q2BJudMRZmjb9Chb2wgD3gDSd+xJZz8pp8bWqEN8mPphBZN+j/2/e0WhglE9tcRxhAK3Nl5ZpqXfWV/3+0RTY+ud9PqDxjIK0QZsDMRmnR4m6Lk3ErlnMAqy+Hky6q6c1nNvRFKApGwSUV2Y5Y4cnaABeU5DgXN6RD2fWEtKZ2m73pyp1pXaD2uOrtcso3bSVOcqQ4esDqsDmP5dQWlsZhFHfG8R/Gn0GyALQcT5jaCy7hfbGbIZyPb9QGJe1n+o/t1+eL9x0qoD8uDp0df/2AZ/cZv1WS63aKVd0qx+5W/BWLCXj8sZY8T7pGNt4rS93m/cePRd2OVRtIMuB6pN3enoHQwM6zrBp1M60sf58utzb97htbsDzhJsLZsG+sLwvkDgGPbAwvpbfayBDu1I217BkNff7dRlngNoCnm6tPR4IV2Xhfrbr5fc16RI6h9mpn0kJW8f6OJCQNSBAen7CiBCJJdb1xpOXG/6qwpU/BVlku8aB9m+Ezx7Xv9dgC/47/QWmwQ5gO/8ku34pOCsTU0cZXxJcRFxj/n5hPDUxxk39Yg6L3cCh9p/TzG0y5twTZNH4/gz0usPGrXRFZB5HuabsyJ/Ps5mQ3BWsAOT6rg7o+Ps2glgdY2vdShdPW6n001LGzzEKxibGdXutVLFIEfV+8kpdICco0bvXPcGAtpp2UmV/8jjTpvOtZGHDtt33jFQFV1rcLT8PYH4Jvi60y1Bfu4iwT95oGOYKMrApPyobg48p2sLRJzkdv4vD4j/c6tlWJZtgbi9Y/j2X3pln7y1ZWOGzUOctTjrodtmth8pC5gMQIiBWlqPOEamR1BJHWgAGPeP3jmmaRYzg8M2sI12X/xgdkPXTo70NOWmsOmvLBxbgQO87rYC+CD7Qy+kG/VamPaQvPAF81ReA6nkCRuy7EcDf3SgZ/8OGR2cNWf87UPQx+Yz9ZOuz9zxuyewE7e5jOQenSYlYC68dAPU59jlKU+KadBRlNMZVPCj7ZLiGa6n/LSFQ7smANjwzf4R9g1+ErgTTNDFXAWYXfxi3R0w1KVxWs8p1p+euokPa/EN+XnuRlyv9lm5/m9OPMldFflcdO2KvbfJ42RQpHEaJegjFTVY0tQ62eAJmFn/mLult8qedHGSTTcTBQ8edQ4dtwNAKnP8liUB2gG6UWA3s6id6Z6crEc3nJjt9adcNG/k657soEMA2ubxQEVnPKTcKWjZ+XrhDfQZcCQG7PpZbkq+UfOFvx9JrIKn1yxkXldmC2iOJfKMPOkQ7jEgwi3Qcy0f3/aSdkePUX6HjgAoJ2YL0/rEDhA2QfZjOXLHH8uX43RSXaDdBfd1rfA4mB+P6XG4+e5TrlsPNmZ833e2M+YHk1M+ea8y1suqA7tiQzDEGGyaZWY6YGgWQI2fozHSBGhIF7IfB4vQV5oN7NoWfTDlOdnROOShPhu9DuE3gTnvuGxr6E0/Azz6oESX4ViOd+7XdHKjsCmOqB3YQl4dxJ3sSScdOOhgvDiV03q6PurluYGGMSVNPICOxjenRQzRxeuOZ+VT73c83EmvP2j0M6VODdGlMnOwZtu68xY7UOYG5Y+mOsDGRdPxJ7Ob9xrar6kh3QOHRz3AsMuIpAmISkPrmNd8JEEa2SXmKt3gC8Ao6eTS6+WefoIv5uFv6k4cQpq5pJ7kWuK7CwZwlrzvthAOuqF7+s0BEeuxQ9tEFq7xIc/63WlLIE+x8J7+DW26gMucS2wHa7Q3w5rBTTOOrRG1xlE7Y8TsIUHnvk/RL4vdzfcsNr/v6ywid0TbxKsF/d7ix4Zs/vkYQOOc0+bjWospQNrMzOSxaTo7MhNaso8Vy8duGwdB0ewSvKdZD74M4KAJ0EtP+fGv3xe/E4CF94fktVwunYmq99f3dCB141eH9O0AiS6b01S5wVfITpm0LzTypAE2eFA6cayV+CoA/s2vyJDk8Ly8p+ALICrA3bAMcKcVEBltAd+pycuUiYErNi02PJZrHjsb/o/+XeX1LLBdl5s2wvhMGqcJiIivl54+ASTLkDenqSez6MTNPX/SDHwLjcul8v7M9PqDRlWaAhc9MNO/p7LXPbuk7wfVRqexdaNCBWq8loDY4VFCZ3zJiEbNl+QbOQ95n+KM49qoHaLQtcpbB2B5kLkJ7bZTE8guJxPt2DhzB9+k4XrRevRszj0llukycAQvU3QaTKDehm6S0R1t9xhwoKgEiAQML9CNyE7+EhjgQAbtoPwmpwyAcs92S3CTP+gq7/C9XY9DteXdy1zXyDegBBsXvBXFdxUjb7d7+fTIuLzjeu5ZSx7JY6Q76/uox+nJxCumxCdB7UdxAsG4rdUkwPRXDcbbaa7Ko1U/wTRWpvQuZvCUgo586fpz2CFAEG00svt92jtsu/Qh5HGeddnH9Qrfldsp9e1tOJ0y4A/X5c4PFUBJPgX8kMck+0qXh80Tky7Dkd370X9V5gR4eU99qd8nDZWFxZdOFIjrwODejOEaUPaxU/xL8AcbiTMX6dNIwtsV/jLqBS31mxqHOuBIe3f/enpZBeMzyzuP3bm2iX+Rh3RYj/ZBltXTY17BR73+oNFsK4SPmPVeCX5WFX5doyI1hjRyEofGHdI6clHHy7LpXMLG+LVjEcycUowemzxhkA1wSyCU90dvyCoLO8ZT6zfimtfJmUbQcV5jVHfJvJRO0HUe7VwnZ+VBSJxDgGjRSamfTkiABN/Qwrx8hMaZyDKTAcfr+u3aN+xFnJQ70Ah+E0GA9jpBduTPtFMR9+Cfd5yic9009hEu6/fc9cUaRW+KOeN+7IgmzfU9PWaFHvj2F8/HGUQHX152JvvfPGU76Pqi/5zl2nNT4mXVFbyPfZB5bDYaI3Sgb8C57fR2npey0kCQ/dLEx9A2LLVdnMEZAwtpRycYgGCXzbrT+vyyBlEHM+Iv1vcA6wP3CFaDR8N18Qnpq/dHz+fyOnDQJwhTyhv6l8tAup7Ed0zyK+kqoHjiM/lBglrw6wAttRnbZma51F8wOb9pQmXme51fTevT11KfAmSoXxof6wnHcLt0EQBYgKr40CHypvgy9ubKzp84zaQDq/395B+CPmhQ/tO+BL+mb5zR8pr/JMPpWpNef9DI0cC9UbWn6HTNFPLloTceBYHdiIT3WaYbjcwp4Eroh2HKo9vE/6j3nGddw0CeWAdlIf39w4qjI80yCjvwemqXzogVdNuss7/3yrBcqksf2ZohOmZnS0dYZvbkd2ZEZDt00gTg6fxP/IPO9SrXWIfqgNlkpoIgd539t50tHHUAYdr4qgvAb5O+tXmezVuBa4x4dJrX8AGcRNcby5w2SIh1ebbLx2NkDabUgdkGkIfdj1wTaWZxjE6bpI6yUeZjSWy66z4OJ9Y7+pmQS//lqKDRr+fMNsrfOAcysNICS97Ga11hS3eQHkEUQVMXuLycPi2gn1FAkmnd7GAtIdEnJ6mc+JFCc+UJHzi23Kkv02ak37muLg+3Mi5fmk3yMtI/uWY8JcYn6gp8TkMcY59d17olVuSXcnk/ToCLfpL5pd/qAJ2ftId0D4CNn+2ucBhoAa+UH/yE77sgv+uriUdcu17iiJQjNuhoaR7WwcTf3XE8zn8aIMxcn/q6e3H2FfzT6w8aNXUdRQGOmeVHeIYgLmXTYw8Tw5V6TyBOP1kv6XTb8jsj9jLdKMXL69tvlI46rM44bz9ynpP8HJFT1q6sljPbOmZHcQd5YQDHvW5tiTo1//QZvwQc73RS5btzGGngsRzqWPozkStXhO+LHzpkOmLym2xDZRhSrwZhCSxkZc69GSUFOQCAgQIKDlLAYdEpeSzATgARsFzOYPQyvhv6oW6kiY0kBFVxE7uhJ4DYY7bdtMv6IoEmZ7zRX2+DKa9P7Oz7ibRp3Pgw1YGntbaye6f2Ld5uvW7wp/yvMqutOdsbwCFAnZmNvSmoe4S+ifJz7vKlf7l8E0tvXHjPI48kVYBkZ03wPPIF+l5nAA8HW9b4cdq52PcwK6DV+Ts+xrXsY45HclnOn2QR3sp31DfcpuGP6NvpO8tAV41I5CyzqE07eB5/Pd+9FPU37U7AnHwgHUgz8E7tefDrxXddrMT8E+8ea83qyR/Mo3blNHmcD3m6XrfOtG4tw3rUF90Dk4f0+oPGDqQl0GF9g7CsAiE9mLqb5VLaJ8D4FMrvZj5OAMvvHbfQS13diOT03Rrjo8HFo4VL5oGdnKBDOw8dZNeJE0AyuX7ddNObU5pAlt4xepVrst6ygGmd/fCgIrPSAU5m5WUF2+3Q+KdBz/VnOY9fp22lpm4cawSwvWEkBcSUDgBg4gsPUy4AZArJOw6J3UdiXwCmaWZjP042MytrGscwvjd6OtAN0HSNR7oxC5No4XH1evVeAn6uCzm/tT8jcth44w3TNY6vmvZjXzMHfn5geRx4jjq1rMt8y5sDUlyjEsMm1vfJMwoH8vgXzOBOZ1JBFcoWdyIgIOEP9PMAZMEYeFA7l0ft0X1U/9ov1c7Vh7Avq8+eYuJDnuZ0frSzB22PCT1N3FcdnOvI71HvfciMs22bWDblS3raonWivA+aWwAneW3I29A6/1cYErq8xDaln3afKUA+QOC0HI9GphO/XV/Wx8sOiBFXkEeN0SdMcozLoKd4hddJ68T3yzmNK3WAjSAwjeoaYHQyIs4mdWDQP+8d6PvUQtkT0DRbZ989YUik2Y1slG43oonZk8daNtGe+9OdJsGRgq/WoTJQLADI+joZEi9oF9LVN9SoQ3OnwTZnG5OnqmDILrokzx1I7eQvIE71NGveBYwCsHYBKci4jH79ELzK6HoRCTqX2yNan5kZzMegZFmmaK9GvDnzdeVzgZOyNm+YTerA1YP3L6dNKcFePbibu6Z1TWD3ijkHog4uI4/ssn5ycNikOHx8yZkBwI3fdNA4QDZnV/emlRH3CECDlu9mB1jZZxSmitFPeH3rfgdr258lmHFdHkCF9gGll3yCCQ3yor7j8Of+wAedkd8a2b2upi3b3doNqCnkCG7Au1lTtGsPLbvrvPUT3idRyJEev96RPcVF8kI5c5/aber84/FxWoOtfUT5Bm22Z4qj0P2Q8vGYV5aYOQgMWyGAtb20gDpQYEh7ubdvgnXwXhdTu0HnvXiomKWLZ6Sndby8EUaSOnwHdIrkO+V6GQUpp11Or8IDja8DZP5dR3dc4Kz1ngLVNe+2bHkL4CH3lLcEnNXJzOwMCNp8pHerzOKxcAeAU8c+OF6tPzmxldLCaF207oFi1vbReqiPfUM+D4mOdig/DQ2Caq1PR7F0riErgvKwLaPTTqDd7YqB+bKvOThI7TJjp3OZIQoyncMfuNcAg4hhA6zQdiyDt2nmG0P8lX7lnEFx8HzMO2nbY8/epTWQDw+3Oh5uR4PcjsLB4zQAtNE9gnquf1Bt6fFAznvKhDMkFQRDRxsIzowZunZqwWDTN1JXA2gIU+qAyilIwf6m5meQXLy5nXeANg146JvAcFQnM2xj5Md+BcQ0NAOcqB752JdFB643fi+V5z0HYE3Y1kGeV/bkeZBBwLZv0rwdj9FRJQ/LQd/Ftw5cH+C/ay/lk/enPNXyr1yPyXayRs/id/k6Q+qdeXRTLfPfm7GLvnPIozHPcYpuINU6FZd0oLYrr5jmGen1B41d5z+NEvxYHVWw3+e9CDbXqvQT8OsAVguWTmsfFhAjMNLyHVh0Q9a6OyPqeOLBpBxJ6cHpTiOBW9UBH5F2M28NPwzsCpgS+LEsY5JTOg+dCetQ+XXGIt0/tL/yTv5uF20HAAYsv93NsM49i5gc96z684DNhd5t8HNeDHQGrq8/b87iVA7BMsoTbCBQe9n029Vxk9tnEn0DR7z5xLPi8axvDImjZaavhxR7lmAxP/povolEU+yodidsFjbC1/lRJ7FuknweBxvPT9wt7TN/nU4c6PrM6o1/obU2t+hbd8zy22Ri1lEI5A0vltuTfWWavB5PbW6AdAdmmvoJFLTvehm25+nNTuz/MZCDrablPeSd/dT7F3xu4n3l0YOsp/D1+IijYqgf+SxH+4gPiqU9qMt5nELvGKeoc8S3khqfldqE9DowCV6G+wEASQWmReaONn0N6WP9YTtxYfue/jGG+UCCPlX9i/9+6lWC/K3XFXvozmrlV/GNxv6uzOn6C2hciYDjHto2s3aU0IEVKrld6CxlWUYTN9J0nVuBwwmYhPE0m3LUWBX8mdkRqHYGGzTweL8AXoAiPSB7jJ1PZxlZZwcAO9DtzkrXmrYgmnWjDZPM5IVATZ0Wac9+5prOMMqRdlZNkkkdW4w2RV8a3KZlecruTtIQvWwC+POABvpaNwDABjlCP8loG1ywmmgv6oV2bgEMbzoyizMabZU3249fWV7SeLi0fb4cyj34OByHdqvjNssgUQdqHyNoTDIMC9CaZhZd56seHlNEoLc3xpwGaq6DJU9qR18nuvLRXxE8GNtP+ww+BypMM5n+yb4Om02gQuzWbUoHZDSyri8HCOj4lZQGxQvMtQMq8fndAdxxJBvaioDY5Y0yc9Nxmsnnm8htoi/b8p98VIkV3cD4GXbt7TtnQwN+o4t7BbAmh5DlK+CcckveFAub9mUsZf0xYbT6NGf+OkzRxXvGh8KnlNV41+XzaxoTSftUZ3eO8svj6ZUKqGk6OO+pMXSAi98JnFhfZxgd8LlcrB0RdyOH7kymoCmO01MYcBMgk5Gx3DN0pqCG60XoBFwPurko6Mh1rjPVIHF0dovnDvzrsQruYNxx6TmL4SwOASPaX4NRJpPbXxxt0FKgroGxCZZ+vTvmQwN3Cw6ZZ30mmdh2WHs0pKwDO42zZvtImKCz2YmNFSu4BeDze2Rt2ObNgQDrmfuwagczfCe1gyg+3m0PyvZ1fw78eHD3yrffVINzAO3GXznouquruf/cNGWAp+/C3jrY6yrTGZRlgGiiVzPf0JRmIAmQ/eJgIVxfAD7ZxRR7SrNYJLMMpO13Iy+56HzRcTbTSWifba7Huma9znLsSwQV3v5JKPlOOfjn9c3YdZ8ea6cZSNezxiPVMxN573gTX92R6ABQ55fUH8cRUJggSD7x1D/W96QvZQqMTuifPLiP5yxt2L2s/U4TE5cqM7GAbogtmKABb/x9uew9CR0mOAHxE1BsfFr6rXJ0Rzm9woD27QEa74FAH+kR6HWIXtPJIPz7qWH5qQ5wiLEr7zpCSnU2MwepDAy2czzkh6BKeUtlrlW2bn3iOusvAWqOaskPZwsTmBZQHED6EY4T6dLkL51u7vsJdAJIUpZ0xAGdeuOUtP2Lc9+Bog2U8QnZol7SGmBF+IrUBb0GxKTyA8ELjn6se+LzcwBY8k+9h5mqdY0Hc8cmFM6MYQdwhwl4eHRsfFmAj2v9CApTOb7p5dQfeZ2PpRbN09mO5ZifV3DMWTZLs5Z8dH587zTXQ858f8+GUtb9qH8zkLjBBdhIXIJNcPBZZvfYJyxf08e0bo6zqTcx2AEnBQ/wqSGS9pFZeScgSf0NQClsS+iRVvjUucmrjyn9jbytz7J+T/wOAWkCcQISShkTOVmHid64DvQAXlwejxPBmvod7RuoPzb1zaZcA7hUbx5DdLMN40erkzv9NcXJJ+IorxU6zdMK/u7KnWgV/uV7h2lUB68wqH39QWMHuhREPjktK8Ywxv13Nz7VGJxNY2BieX91odefjOm6+dZyBMD+Ts8569qIzmh4jZ39qaDX8ZZ03MwyMk90hqbzBG+6hgSB5h6A30zmTqf1hwPHOqwOOCcAKHqM383C7OJUSXtKXVKv0tJrDIoprwY6p00SY5dvF8Gv1J35OZofyX9LUHG9efCYUi5UOhEr9prGfKD3fjzLcwX5GNmB4C4rG0W8v8zb9ykyTvYZzCqkmT49+9Es+ZO0MebegeBN0lcWej3lmJ+RNwANl8u/j0xvlx8ys2h7A1JU0fSDbtZn4no3iCvlGvAwJd+Q+ymPZ1j2VGbwDoH6btDV/nTokwF4T0nBjFnaWJbqo34X3UKffsQsy9fIM9Z1gtQEfiUOso7yilHN2/kotyGCM9COAT42mJT6k4AW/trzuX2F/+ZjedKjLx/Ic6iPPr34cfV3jNcX6BO0tUyJqU0+grgTprjH/6uW6QbGrzCgff1Bo6cOFOnGFrNsZFHuugOMpxb0rMTHyN0Iot1QcwIztnc9O/jThubvNJMoxqFAVUGcdrB7HSCMHDODupuc9dIJHEdToovSIZfjbY+VaTpkAq94VOKzaJ1T4Oac0KHwnXjyeucuqw67Gzio7qkDiN465z0FgzqHHQNNqQP1FLAq971Nwl79GrOILAQc4H+4HUz/Xh1VfrzsujYbDw8BJvMbYHYeM0uPkQNMdZvbgld/vd61zBim2Uf0Ux7f0x2ofWzbZ56DtouujT2PGeyUHd5zbwAqfWzxkADx3HpOb9Hh7LxZc70BOEzephOFs0D3f2sRdKE+zdzH4zL6IftOAhldvzLIN3a+ID93Ofqo7k0obb/isUZ+uwFZ5af2yzu+z0yWAsEeSnm9tmRpB7f06Rcpd5BBAStjQfAktLVejWXhv4vxWbvUSP23z9Y+BySx35dHuvDxGsM1Tvjvbo3zPX+hv50PvdfRGqN+6jWmzj8e0tsHNHo6Kd6/c4avGdHH9Q6Y6IjiOX8dcCE/BJlm9w1egbGOXmhkLbCTDqa64UaMAACY9eyOGwlZr/JbnH0yeK9HnQ2uFZ3N5ggP8JE26Ag/idYzHQqdH691o0rnR98Qo4vYW4en9xC0nY4nPs5JeTcLFuASAfMIPMmLlhGaaYaAhdfvkc9WTIAPWec1P+6NMmEv225ub4DhQdW3fBOz7UP6QuwwXm2Vfnt6ACgz6/t68Heb4WtnHLXsMxeaH9PE0T7O89wHbKdZzXRupAPEPRtZji26XGw+PqY2SjO7D5dlwlj3R/OKz5F/+49pTXu7bXge+hbwwSOzFPAUwObXpH4tFz5J+oPXPazmT/yTnwaEtZvP3J7pjxt/meT08kXRkl/8uX8O/G5ROWJVml1lmQkdQW+ts9B6BnyhtqFZrC1MfUvpoi6us6afK++ntu3Lda0s35hm1rerxjHdHNcBNv7279r/ef90OH+HKVjvCRh62Y6O8nkPYD6RXn/QeFKEbpnn38UXReOa0iOg03oI9LpdSp541thzG9EXShcnY9sw5NiPlj8drYVxAUypXvxavPKpBtFMy2noY/TL/uzkNulsOhMwpPP59e6Q16ArzjAdw0AHCLlJizLx02kcAQOcnTrbCFDa3p0ToJMka9iAlPLTsc59iZ/BJ9ZSTZ8NUZ1J/eUSeU4MtmybqDfF3QLk18fDbfH4baPN3mzD43ls3M5TnI/X9hVcQ9oqHd4dwcT1sA7H5lFcI28OSZtmDv38uFP5Xlo04/gg9EE+sk+AVwPK5WJlveXKm2d616sTx4i64rH/vNGNVyz64/wJnSdh138c9Izbtf3+cuHXy4xtg9RlOuT8dsE24Sl/zsSQ+wJY+BYQ8tr1b9dba8daj4FeQyN4UODjt7pKGh+QXolH32LxedsI5kVOQKzzd6gzvUEKbZMGmuqvOp+ldjJzWY2TnDQgz0Pa0eUYYgsa29OgFnG+6Hvmx+jHwSD6VXdeowLGIrv1j+tPvHGiRcGjy6kDG+KTjg5/hy6fTq8/aGTSxrmnQJ9BU3DJhu1GGQQKfu1uQt0c1RRnPGEE4EflI1jV8vyu7+EkkDyNXFiPAh0aXhk1adAUHZcjh0x0LkC2c3QOTo+694DkdSo/h2ARfAjITI9CYA8pjXy/vD6QeQz22GysKYHQi6/AoABfSCc5VxBPC9TRRpPnQXqVoyWocSrXE7LbsunbvT1LJuWIMyjDvOkm3jF92buuC6gKtYiNon/pgd5e36CjBkBLb5NJvInz1u+anvQFSJCnfZ80aartFb9gazNRHyRj9nDunebcYFTt2L+bbJwRoOR5nWZ5Owl8pcpQQArs/7RRrQNhCTRQli5Q3uoqj+nLrB/9Ba7Th5b8ek2uJ5DTPDFJM2wGf0SwldtsvyFIn0Cwb0n7ah+Px8GW7/mTkngyR9m9bzk7jX/V2eDoO+7fO2iiAEdtibId4sQRyIM3nQHk7m/Kc+p7bEvSLS+5EF0Tjyhtjbc6UOx46fxRF7uL/dxPrz9oPAHELl93zl8ZgVltCG00fZF4R+M0CvF7XfA5bWY5ydSNYE4jIO3YJ9BK/tQQOzDqnycDNrN2gbp2CnWuHb3r46ZV5Dx0ZKUb39mh1KlKcCxBgbeumJkN4aQsriWb00BjzW8JBkUvyr9npxNUOZ2WVzEzm1RBhwO6NPxA7A169i5pbxsXYR9eXeK1rfvrHMb0Gj+1ocPBuOVNK+hHZV0gP4MA9Lzaq2yOQTuedlffTXPudZbTkgzpndSpiMh6xbuzg7cZOvY2n9cZbXMjZDBpAWJRx9x5Igt9pusI5YaR8O27X0unCEh/I5jQwUjKHwra9Ok/xihZu767Z4aHFX6L4mG79CldIJ78Qrraz9mOGkNm83moL0g2wCiK6uYV+PAW7I18fRzqHpfD41//3eiAL35Iervu62Gnh3ZwWuRVff1xkK8kG10zfpyWuek1+pETruhi7snvPEVL6zM78/ocbCTp9QeNZr0yTkrvRgU+yuhA4lP1+HXmVeBC0KVnMXaGcqqnA5Xd9xMfuoGnA8csS93d07GfSaWjnI5ep2N39p0++HnBiLAb0Sm4v11cNHTk2z2WEOeTnNEEDQbFC145xeCHIB1FSJcBSpx6LpRpPXV+4xhWZx4a+VIcGDkLs10GZhGdd/KzC/q7juPx6nXvajazAEP7ceuq4wGPgLs0sRHEzOZjPcZn87Y/A8yBLncbh62EjCMvR+lsf+BNNY94bafZK2+E2TRRX9i+xSYcB6nUQe6/Qm7ITO8w4470qJMp4vvYf6U5pgCjDAhy+7EfQq9lROKymzOa6y2b4pZcDPDO67Tel92bfSr3BXiE3NK3Sj2UaeRr7PulT97x95rawO/LAggewMvxAG3bvkTVETaCNe6REe3H9nXZ/MmI56dv8jXeqYxtf54GD+IrO+CqG4LiNbpN/MYgKmT0WKKpA1oaiyJ2Nf6iA3n6lIP3lEfiBMUiCg5ZpgOTGoOfkV5/0HgP2SuAIFDUk9TLkS936J+A6An0eJ4Tnx2d7n6AtIscki360ERwdwLEHajrgiCn8OP7YfaR/Kic2vlYTo1enSWXFnS74dMsGxxRGkhcctk0Am7aIe4xb9NOhQ4ckAJYDbItiB0oF0Key03qgPm0TCNXCnw3uvVg65G/MkA0QI5vdpnX24YLHq+zMiGv3UBP8xaYqAn3dK1heqf0yeauqucmLRp6TA9plsfdz3TKqbwZ1D9XnagDIDWANdaHua5M9HybxUSegU1BHXhkWw5bm5DILDJPFtz3y1FBoXOCLFmaEV3Tv6Be2nLQBIgEwA4fTtplto/8m9znNds+pvhwB2heDwBPC/6G9DX2TQUZnf2gn4TP2rLd1uXCt3BQF6AmOhrqg37SY27y7f4VPsF1Hbw1g1g2oPr1SOS3i424nnwo+OZJGab0wY8OINLki/B4Aomaos1lmZvawQkPKF9d/Juzvvb4qE+rcnT98Rnp9QeNZlUZbHCCku4xkjZqN6JI92V93pw3MKZ5NY/ySfBGEKEjhk4eX7ivjwcUoJHvBFrG2eh0tHLX+KQzuFM9geyunRSQ8Leed+lOw3V2edg8qJzpcUfTDv5IpHRoCVIuZ2cDqs9CB3yVwAfWQ85L3y4rc3uMDQFitPEOxmY4BiQFKjLQ0A258GnI3hXRfCyw2EqbWwIsWAIABSTqICLkRt6Vhwdu9+BVbU745zmotvnbxwDJhiQCx1d5TJ2Wymx68/G613Oug9Hn4+0xtK/5TPy2fsr2Tut5k53H+6Qd605n2Yr5h/PlqRkU5fdb27aVrl8kkGUbcK9663pIAhORef/I34+7qhXMeP7ODsTXTm9772dN1dMA5MWPtLP+J54EwKRrpGXxO9YnJ79FGt6OnV9beQfaxssNy20ZdRrknJZlc7976F9BRtYUep1T9NTFEfKtei3gSvql13GRGMV42MU/s+IXUr7uVBHW534l6UDyedIldKeNOlruHpjs6ryTXn/QqICvQ/r62QEa/04jIX0FSlpWAZc2noLDbtSlPBDw8rcbFoFjJ3OXFMBoOo22/M/f0NIdqqpORoFiO8NGJztz/bJBYf2o3088n0B72TmvjrtxfHqGZHLq1iQGQQ82HnjEuSuoT4F2f9/r+kA7QDJ49OsD5WLGg3V0AZk2vdlM6xPJAvMd7qez6yhaBCbXAUhghs+P70mPP7vR/Pobl4vZQ35cmtYdqgO/znz+aeyorptS0iYZ58Prf4XH02mWMgKxkxR5/cPfpT0s2TzXiBYdDa9r0xgX32B0qW1pmyZ+bj64RCN42XUlUDGjUBZ+EiRCwFKZaRfI90/2V4Bn973rtE2fn1g3Ws5pBXBKwA51pMEOhBmF8XW9AR8uK48VK087tHOhbOIfPm92bbDqKW+yYj3iM0vs8Txo+xR3JMaq7JwhLD5r5vvkrwCmDg9w5tX2fcUOvJ54s52XZXRQyzIEpOKrCv3TdY3pnS+8B7I74HpIrz9oVGX7rN9pFN4BsgIM7dxYVHyMPu5s9PDvOorSUUIH9DrD0Xo8+JTDSRveo17RQRppdUDNLDpgzKpeeyM86XMuR1dAK5HC3I5RO5Y6iDQTsfiOugOtZDtIM4SqG3VwksdH+W0nb+Ryu0jgrqmbMhdASecLuq0zV1miAlwCPQZ8z+AO2ovg1X58y0giTT+vQNTjqR+Zw1cFzn08js8Cjo97A/lolxa/69mKZsXm5zRbG2ni4Oyuj42RZw7RD9L6y1N5L+f6uTdY65LLk+K1PJYPcTFo8DWdelg5DiLfs4l+kyyT59s9n03bx+b4x42H/YgcRJ2/Fk/A7qJu9Sl3rns52l307ZGLlc0VjY9JPsRty7O5EpQXb1P4D/aXY30qiMGnuCzgg/na7+pT0T86H6HAOQ3W56478vp1gMsyG4h+p6dlFBk8P/lIzuaWeCRd4Z/8sR7hhXkUpPFa+JPF+7XxCxoLnVaqC/QZ63QmUst4OfEzZW/FwU/VeCz0mYd4IMW/5/mn1x80enKF8O0qJYh3DkjvWW2MkwFpw3Rvc+F3GgrvaYMzncAlDbYEtvG04XUyOQDS/AnwNjSKvpo1l8mxzL4TmFl5ZFwAn/AQAaxZ32jzMLqis+1owhl1ToN5FDz6vbAFredU3nLeaMeOvwO/JXZMoS/FQzbNoG9CYZvL7yTeaPKa7XMhvd6bfPtonAVgmrYK4LScfPCVeLcM2mC7PqvG9otzGc1uYOxxzZ7HhiaL/GmNJK+nw7XN+uNunkhT3muNOvabbhaPXd/FsUNef8weNlhkXgk+LAFjPysxH47uBHaZ7WcsdmonEBIutvGDOggLW/JgLr522cm2a9oXfLkfKaR18HdqRwn2Mbrx/Pw7kC1gjX5C/FMBAic7cbtlO+lOZ9AvNPlbeEv8L1rtsTek623DoijXgj3bbZXus91Ev8c3vViOc+m+JtiDgstSZtaj69z/nHAA42vEenksre3sZbpYfQKhTwFNyqI0SQs+7qyzPr3+oDF1fstO32fD2HDeqS8XSwBJwZjS7YxDP+8BRoKm09qnEzBxOgr8VC6nm4Az6Nzly6oToUzM23VidRCdwRaH2tzvHmG7E+G18vjEkEc6UOu4NC17Sc7ZBIBg519Z0O+8j8ornP0Iu1OHK3kjeIA/5dfzewD2oB73xeEThAa5We+Z7NJNdujy7irybJbWuXZRx+zhLhPrD92s/O0rc89C3s4fvJUNgAa7TGsO5z6kmvnax9roz8OXeShoBR82s01/TMfsnFKY5e7jYwFYB8njctlyExxCBwE25dG8z7bGxpgFsnQHOndd880xN7rog+qHQimGLgF7mpLHA3uANPSXKQUm/kr/1T7SVoZP3A5b1MHobPpGA1y6mbPU7zt/3wCaFliBr7JGHPmjLNoqfQE9HjOUyh18egfO9VrycXAIPoBOAw/mmfLH+sW+hpa1rcOQgz5e+ZeUbFfq4Us/FOipvI4vugkOl4e4gLFTB6EO8to+Jfo4gT/lkTRfcTD79gCNXaPozEOH4Jk0L9cNdgakdPQxl343M18j0zsgawxDZLkLkIVHHVldr/tonK5u6qELCt1vBcytbA0/Rfccuc7aXp3OCfq7PLmAOGd3OtecR/lLAw3DOrtpZXQcNOjIzFS/00eo7lgT+NOARwdrOS9/RwDueBFHn+IFna+J7TbimVWWQC+AQgIO2ZHmQ73zGrzurSvllYFde2g7sS80Troc7cOF7A8I0l52vakm7A6ziulg8Ls2qHrcMvi7sZPcj9c0u8oykQh0AZ5vb7nx/mn7ejfwHLbBIq7dmDDoHDdSG3pGSzawjyNy4OB5oDe/TpqlTzZ9IoCXBGmTrMdBotsM7t3zT0lYAWqJPvsh6p5OU+pMYFme8AzQSeBI6lOAHd+vuYzGIQXekUdiSSI+wItc98Gr/2YMTANkLQ/GmXcI72kTEMpEO1Pf8hc04Ce6iYjwydBTV74AzSZ+KzDUex3+UF78OvNomdZ3N2V5/Yn0+oPGzlF7w+ru2+5wb5bpaJzAk9Lozk8qfAk/ncMYOSgVGZOhHjp4Z5SXBuQkoDc2H91OMeVBRzb3dNqNkopToZ7oKJ+RppxVluRjB6KunuJtWnr8sG9u50Jnnvh15zN2GXWWPqolL+k39SLBYbVbPPYNB2goD3414PhtfTNMOGnyoAES9EN3iw3uiPbfLDX5mjr/PZfodL7rYz2i5eyhPi5OB22zDfFKwuBV+91m7Pao1yxeMdj23+s1zwi0geiZ6ZrPmhzSv8bDJV79VwKC2GqAZAGDDj72JqatBz/Kh2AyHbi+yuVH+w7cLa9xDNCJ9j0FNKd0hQ4DbM285KfYY7CBa95XR+Lzlp222/TN6J7D0gxTGfChjq4/kNcEIL1N4CdcHyGL913ORurayVBarvc4mHReO3vUMosv6i7pknRIt7kfIGvWfnLyZSGz8BBZwxilTtt60sF2G2Olz5rJTJz0sySvlKe/6XyFDvJId4x6XnJUJ/l4rXuyoX7nKVrPfDry+oNGT90ooIwiZi3jn11A6Ub4Onp4CkSe0P5pJGT6G6lcm/n4APJ0Ws/QBbYASY1xKb+U9Va40qfDKGCsCfCkOWd2Prtw5QdtsY+ekPzubDoHxrY8nZ2Y6EmAUkdLuul8M/ATo3I44sQX65c6CdYG1hyGjAZau87YvVyCXQVq2wkzQGYbvr0jetEfZvux5yjs++PlAH6hc4sy6RHwAjrOy+0Imi0rj+jpXg04xu3d1AGOFm9R/0XazOu+zuYg6ZX04G8/dNvXQjqNV3lkvcAX2yxtypk80qYJXJ7mnol0UM6ZQ51VTXy3PtF2V3MAuJle7bDAfgwA5p7ZpO2F/mljbv9XecRP23AwoE8SYKSp/8D20+ya7e+8xzcl6WfqxyxG/yw+onQR77M6MJxZzlSJ1Xx6PYFTTWIr5Xb2CcH0wPcTWE51DLkOvlxPZvupVrGhLnkbgo8YvGx7qRueOn0a6Ph3y7bZxbnrY51UUhA5S0NveuxH+tRR6z21kZZlvSc5Op+g37tYfCe9/qDRDZMLW09Ajd/v7fzVmbaufDfy0Lxdfv+eAIsYqO7QjrJiwHGvcSYKgFmvjlCe2gVdaKiz5+Nlk3Or5HEfD80tndPzXTPvCqY72Y48o2zSFcrHjFszW5nokB/ylaIL8ktwSZ8DeTzo4VoJiuq8tQrKKXw7uEoOv9OT0xtFRSnn4w2Y3Jprz3Sl1wI6K8u20kwiYo6epZhm3YYZD6ie0pfSTmp+b3ZGprfQhLpmydcmXaKyZkAHQGTrd+6k+fiYQTbPgXQ6Dw9p8FkOz3YdOMgcPKZn95M4sojrIm3re3etITgBOpurLRjIOTBmuTCzfFZmAihjzaRGmYF6nSHtjyPoRpk0wiCztn/Tf6TDwbmGmX1igN6qL/qn9Fv3V88KyPRbA3UvmiFP5ze8DNYmmnxl/4vfeHrU9X2XKz3+ha2XASTvM+ZRR+Cb6zmLPCLXgHxpkLB+x2sID7HW6esAnvFT+zsB5Cl2kwd9jW3nPy4S80iPQFLLPQf4kS8Fj12ZKTp8Rnr9QaMCoHtB4KRADToeeDqA1dF2AKebZrSsG76mtM5NDDrxcK33gheR7fGxGlcHXB1opxHOEPoj18uO444p8mvna3QeJ/lLQGA+dvSjsY/8SYdcRsh+HwFCR4LdBpXimEQXLiO/K+DreGHA6mZU+JnEl98ezFPAERud+zFwDk7L0Xc2jYXz5fGmWdBLR/Ek1eUzDQkebrOBsllj9juJ+Ro93otNM92jHtZ7mOG0YWZvvIHNY07nUupqwfMDZylefcH5WI/PKXNZW4g+OT/60Q28u6ARvCIIrrLjAYDUzBz4aX0bhPc8Z9B6yxS2cejycWGaxfuvhyU76UGK9NPO/4a9ke8hbc2+Mev31G/E1+iObl7jAE2XmaQ3ZMmAPM5MvTblCOjUZ7vesNnOrxd/u2QhePHlSSUWrDq7XfwKwAiYdblT8WXoaEFONy/CEPRYoFNKgLABes9JXTwvkyG270/RG+OM6tOxw6mu7mg8l4X5u1jdxfMTzulw0DN19fqDRrOs0O43r58AlN/XIJNG06N2LgIPpd2tbZjXagAOxFj2dI4UDWILsMvcMmZ+uHEmAaX1V+rQXaTXql/9jI5BYIuZgiQLnGNyXravBY+aLzEm/LHMyPlC3hDCElBPjoGPF2RWVXXh9YbD104sQQAzLVmP7nTBnwOxdI1fbzf3OjK/PkSdiciteDw2FP0GnUt897WKiYeIu7e6xgXgcrUdZw1jlms6P+tzmuX+QR4vUYeDRDOLR8z7gOrGQZJeAmLed5adp5m9y4GOye9Zr5m90uHe3PjCncblHErM1E4dlDa8tW+NWTT3qwQt1lT6O6lJLx3bw27j1+auOAPJufN49Vj7mNa4EgyVxHtgIAGSsetb7RlvTCoupfMJKpxnSwYIXgFU7oEalkuDt4Hf9IPKjzOO+kKuiXsiS4BQ+hKJJSGLCU0LHcZ3nqGoYFb1FDIPK0CY7XHyzfFJXXWfpSNaAo5dTI968V3jHeNG3LsT01OsE3ygA9xusJNEgH7vYZjACXdkdFq6QZZyPCO9PUCj2f01fF0jduDRr3drG/x3tzVeD+j0MnTyCiz9uoJHfczOmRAFqAoiL3RWea1Xb2xz5+U91ZFZdqAEUwocU110fgfDTR1THsXHIxUGfQHXXRuV2T3b19L9JUc3u7QVcuY3gdQuv8ordXMWJEBt41wKGXfEEmhSrAGtCSKL9g7gol+VY9Ys42HbWQGkK4gPrWf6ujezPENoAXrTWYEOdNYsatpBPG0DSG9/PV8xwJbYHQPpo4CwOFbG60G/OvkXXn+FNY3psO590YbyOvJmlLTuMdaWbj1H2/BxN3juDg73++k91tqm5P0C3ft915mxnrFA7KHfW3dL+x7BCvtpbQPaVAZY7HcL9Bja+pSOayqdH+WR5UbO230vfqbpbDqQpP+in723hppHhf3/2PvbWO2arCwUvcac877Xep7n/ervtxuapj22e0ca9zZIIGwjuEGURPzAbETjjiT8OFEhIdAxIfyRRCExQTzBjxMNARRR/2i2hkQEEU846JHTMdvm4PG0CmzQfm26+/1+nmfd95xznB9VY9Q1xqy51nqb7h153lXJWvd9z1kfo0ZVjXHVqKpR+R0fwAl1sHw5TQY3iZ5N+STTwjPEcdgDg5nWQIdQ2SBdNKT4/OeViuXn565LOnLY6aW4xo+eUYN1U7Yw9nBJDyhmWrPc4+880RTZxu/R2AlPPmjMjO4FAzkZ2DGjOR8WtHl/Y2/vUu/kdAZ13Nm442QwxxZGTjMk0JbTbjoJd+5rzO48QHqzkjCrIp4xwDPB0UvXC72ZIdcj1EW3wjvMBjvWoY1FAkgastEc9jjZMxNGGbwlwRVku3ZALgs/S5fqvLfxOZtLAi96dNX3VZHxjSC95eVApiv8mkDR6teTt3Uvmozt9qV2ErojbLWCS0EDfy7vhwZWIDBA2N2/Z1bCOiaDuxsLBhbzuGZwae94L+I4FAtmPm1t/HE+Y7ud4w3M4htLNHyWriKNRqCAwrp/Ekq+Go0Wxh/jEIFzWooO9NtzoiXeEkP7HwOOob5ofW4jy6R2U5ZNtT1yXxKksaacgCJRojA2SGn776wPOmOR5Uftl7GNCYzkPWycrS81U94ifXm7AUKJd5vJNhdEzx0ccjnG25yH8QcxHUBgLclF/8qrN8lAwDwNwIbe91zk8DMfS2OnfE6vrQ65L/R0XQ+A5iXz7nilMZNXoDhN1nFZ1/uNadS2LC8s8FjNciwDPRvPPcDJmCXrb64Dl3NDePJB4x7w4O95lpiXfgMQQfTRuMnT4iaz+B4d3GC5E1on69KLZArXmF+eZQWgKVF4bfZCcr06M82NcLBnqaMK82KNz3uzpF49WgGJeawksEMzCT1r4zBgquBhhdYb/EGY6Lb+XZDbUSTD2GjKgMPpTXkH/ncUU1XCTZ6yRYEFKsVlJQKQz7zyzMEA6xfP3+gAsVYS2Vrl+tryqhn1bkYJzqkdlLR6siNpvxdZ+P3abv3Ym7DlSd00Rjp6gtQEuVkd1dJngU5C28Al0JazP41g+wmvA77onXJmWbKsMX1vAhLAEDy/sJ2g0uNB213WwYjkfdH63A1j2PoKENs0ieMt2KHy/Af3aZJFmwmcxucbUKStHhlI5u09QDII1H8ZRGYwHnheaGjXM5JcYhmQ82N+CNdZ0zv7ynKyxg3XmKbJZjgYx+Wgye8wUSUZ6vxFSmvvuQ3SGMwGgcCHRIukMuxTqd4OpDkO15/5Q20cJj2VFgewO23Lv7POtjLCQR4qew/M8W/GIteV0fue6ezlccvw5IPGzMDesqm974EaTssz1gxsLM1qgnzdLys3fC7XAWMVJD26NgO4DnIGtE4H5Rs2KPc6Tu6I2mad+f5mzrsuHXb5bLzo8npIfN2btSIBAFMGJLwsPw7+XmjwDe0vA2gvs+a54U0WVGmw57hKdRG0+N6nEMoQdvnCWVldMgAUiptBrbd7o1fGobWTlVPrHk7rSqPFnwsQHGwL4qlnZ4lUMrbX2wW/fop24hZoQKSmcQva2G496QnpcOuLhZH6itE8Uv9lvodZvzQL4zg0MGjPlqX05zH1s7xEDRSr5Abk3zJYflZ2T1nk/dQMGK28XWVhSSXUxa8nBAKQ4+sQNzfEWN8YpPYviWXXfhL3tSK0QWvbSF/okBsAaK9ZxlNUTs4yhkMAXJS/j1UjyXiLbXCApR5v21ezMkfr/7BrGqWVk+UMt5vJMHugKXq2GgZvEwSoJNLc2JPBHaj/0SeIXucjKF1uO3q3sWp1xuImD6svx+H3WQckubtpe+urxPMxWTaNlwYqQ3qJusxo2gNiGVf4+Eg6jw8o9dJ285B9OcHpe4apgG1uDtOtY/5GDesKSO6IFPaYlTtv6BjLNl4uk+Pt5ZU723W0fZoWi1ul3dug37Nu+Lt8FSGKQt0rj3nWy/+N1q+X3/8ZaW/M+5p6LDeXm2/++EyH6/L38z1Inzwhz2lyndb2e+NruJPGy+R0e/Qt18SZ5/j7vJPJTWEvHef/mc67E/R0+jQLoZB5svcuxdNbfL/N79u+Azr96Dd4uK002xsj/cg9XXNLvj1h/P116cPPRpm97WW939fhid6725Z/XZmZvj1abql7nnxL4124C3fhLtyFu3AX7sJd+HWHO9B4F+7CXbgLd+Eu3IW7cBduDHeg8S7chbtwF+7CXbgLd+Eu3BjuQONduAt34S7chbtwF+7CXbgx3IHGu3AX7sJduAt34S7chbtwY7gDjXfhLtyFu3AX7sJduAt34cZwBxrvwl24C3fhLtyFu3AX7sKN4Q403oW7cBfuwl24C3fhLtyFG8MdaLwLd+Eu3IW7cBfuwl24CzeGO9B4F+7CXbgLd+Eu3IW7cBduDJ/xawT/3J/7c/iu7/qu8Oxd73oXXnjhBQDlDtPv+q7vwt/4G38DL774Ir7kS74Ef/Wv/lV8wRd8gce/urrChz70Ifzdv/t38ejRI3zlV34l/tpf+2v43M/93DdO0DC0ux35nkW/j5jv5cx3Z9ozurO4d0HUdfdN9uICLa91rReh272ea8qrcwco31Nqd5HmeOEuTk6DWP91ofI7tA5DTNvLe1PsTrkhpLtVe++4SqGeNY21yaYNleiqaZiuzSXAN/GePzPNvbrpli+d6sX61FeD+J2/6nckp7h+/+xOGRteIfKy0re5V5h/W/JlgUxTeGb3T+u6xjQ1rpdCdxf773Fs95/yval2hRXnG+601nivMtDur6W0/sl918qye65ZDuR3fH/zPNd7mfMdrgCWFXI4QGe6G3DVdre7DJDDVK4DlMHvv9WHDzsNRjTbz4uLKrsAnOf2fSSRvcxNvtEVYDKO5Vo+Vcg0Qpe1XCM3jlEG2J3wy+L10vNc2rB3ry6PZR7b/H1HFtr1lXw/uC5L6Q+byNu7c/1O7Jp//o16b7nfm03l+XehsbVqGGulWI1pUl2kU6/cbjn/Qksri/MU6s88BgMdy9pEmtFr9C1L6YOpfpu0G/4a7cSTVJa957rrqpvnPb52368rJUyyrDCg3Wue6VsVm5BF8U2imvPqqp6sxCivXdlvRKJzxV+nrpYu9Kust7kYbeOrd01g1ufr2u7QfiP3U4bxe3P0z4ql8Qu+4AvwsY99zP8+8pGP+Lu/+Bf/Iv7SX/pL+Ct/5a/g537u5/D888/j9/ye34NXX33V43zrt34r/uE//If4e3/v7+FnfuZn8Nprr+H3//7fj+XTuT/TBmoGDKrt3k6Ps9Y/ir8uTSCvS3u3rjFvvsdx73foBCspQmvg1BFU4eDInvH9zpaHpbXnBga9ngkw+qd9T3XxQbOjBMJlxFy+NqWcFc6mTa6777r+rSvl2xl8QgBxU6dUhgstaXn6H9V3L+R6xpfpnaTfnTba1Kf86aquAFtbIca1tEp57tGqKwm1NgZM0LtAVoUuSyhXKoAyRdTmT5Rm1a5QZ+Cr61oUJwGR8qz82fgqeUXwaHFjvdD69UrjiOMwMARKvGWN7xmIzst2vA1DAYLMz7UCLaAq7pWanTSWrtB5aYCOy+6F3jur3zCUvJe1AEV7vqzAvEDGIciwwrcydnShMSAocmGey/tlbbKh5uegnnlrv/fo9fZbY7+lICIBMAIIAE/XFbqsnof1m1YvKtrKW1bqX6uDE590KML3RrrWfNR/tz5d81cDdaBh2+jyNNS/Ob9GK5XlfaSWs6zxnYLGCSKIcxEl8Q72ZfVxxeOwAPKh1Z3qb2AWVO9CC43zoHcQ8m7iTNs7+2QAZR8MGMX+Udwq37y9jU4Hm9poQgXjQacyTUQ7d0Nr15ZNHNccCMimjFMEF4jYhip7WZ/tAcs9uWDya1lKXNYbPX3uMrAzib4u+OTvdnDwswIap2nC888/73/veMc7AJTB9Jf/8l/Gd37nd+Lrvu7r8MEPfhA//MM/jIcPH+JHf/RHAQAvv/wyfuAHfgDf+73fi6/6qq/Cb//tvx0/8iM/go985CP4yZ/8yTdOjIE0Zxw1EM9Ue+kCyEtKiPPMVhF7ViodP4E+iGPF2CuXaeYysxIESqexGQfPaDhOnr1YpzFAy3n2lLaFBEaAa3hm8Z1faTDlunbBaqpvrgMHbvONBTHlGyaSWUAo+lZm41WaLXZnnlkwMXglWhnAS8p397v9btaNCPwRn4EEqCU1CxvFc8sNg0gvqimYVmZRHMHCqBYJQZlafg4sq/CXwRSdurUxgs8kELnPGPiY5/bOQrVoucKlNI1PWkCiTxLXYoG0iggJZQNaHm8gQFnjLksEWxl4XRfMomnjdlmCUhCzGopUC2el0+hwOUF8MIDLMiTzk/k2DO0vv2eQXt9ze5ZJyJr6mSKPW1bkBfzCf9sExfpGA6XGI4rrk4yWrlmX1pqe+rFQelA+/JMta0SXgclmuZKYR9XrIb39ed13gIrzRKntjFcGDFmm0jMGYSKN/1525Y3TlQCl/04yiWkMatT6aJLvNqHN4gsay8pg0nW1ZaUhqUVsz1nGaHgU3jHvrcI2tsIkXxrtG53Rqefm9U36KFrG4ZP6pCMZTLKu7OkILmtXP6P/jvFLr0/uhM8KaPzoRz+K97znPXj/+9+Pb/iGb8B/+k//CQDwi7/4i3jhhRfw1V/91R734uICX/7lX46f/dmfBQB8+MMfxvl8DnHe85734IMf/KDH6YWrqyu88sor4Q9AYxYLrwxMeqClB9z2wKXFz+CIheseiGRQ20vPtGfLSY9upnGtM5QSKdZhb3bDnfo60BykXFW0PethAIIpLwtC0mivk4fyqR4y7NdlS0z78/7Qa1MaFhtQKPGdgWzmy96MkuuS43t/sO0UDPayguH8WPCZFaLTF3qkuLw0RY6gjEoVmxLIoM/awy0lQLUCAM2KqU5isxxUQoSW04QsUbXPZcsNA8oIrGs9xrHFARxIMXDx9MwHA2BWv5HpSIDJ8jIgxeCJFJ4v+fZAWebh3nMDJBnQK0o7+3Mli6ES0EWxoFo8BppGs9UpAGyyXC4LNv2ZxnBYciU6bUk2LP1ym67RusfgtrsM3As2nH14SinTLWnUf5108f4arHA9EcJgy+iTVje2uAdAlT83ZRReySABNEdmxLgZGAn1BxkEBpAbb3SbF381HjGtDBx40mcygunk+hp4lPqdJ/dC7y0DL1Na3iZ77DOIXMtfWtyeTKU+1GjmPkaVDX269510TSyofc06JOvxrEtBvzeAjeqhWbcnGWPfQ5qUd6+cHG6tN2P4jIPGL/mSL8Hf+lt/Cz/+4z+Ov/k3/yZeeOEFfNmXfRk++clP+r7Gd73rXSEN73l84YUXcDwe8Za3vGU3Ti98z/d8D5599ln/e+9731teZMCTmW3BZ+0dK2CeVVv8Xj6c1x7IzB0mg6ich71jBZQ7Re40nv+6zReIyjDPNKyjDuN+3bKU5aWnoEgyqJNtW/SEVW4DA5YuOLRTvzTQQ/5BytV9nFSPUB17tsbywmwstY+33zWCxug13ju4YctP3oKRBRzS7/Td24H7FfPEvgoJ2Z02JRIKeTWOIAC5SJq6AiuKqTMGrFoE5nxZnpZTZYz70TbjlXlhAMuW0w1AWcjL2DwxGMe432+l9vZ2l2bBW9a6VaUu4R4mB4liljmmkZVu4EGnbe25L82SPOK+CFRalsIzU7bQai21ODS2mZ6lM8HzMpJMGaRvbYT1CYrr/SLGzf3EQY4iWBgLkKp9aNguadcMWz+2fOp3m6wI15VkhNIY3li+B4l5b5qm0jsQ8BxMnll87jctWfsT59vGSon23vMMw7fF3SyBK1q/LxHgYxzburQl8SSbvWxNaWQjakJ6rj/Xg9+zDPZoWW7Wz6CPuCzil/NEm56x/rvRA+W32CRrF+FnhqVGZH3kfEqTrqxX80RNaFK2N/45bLaPpTgbXqd8s7W/F7rjbCfqrWPeMnzN13wN/sgf+SP4wi/8QnzVV30VfuzHfgwA8MM//MMeJ88k84b5Xrgpznd8x3fg5Zdf9r9f+ZVfKS+YYXnfEyv8bM3rzcgjQe2vJ/zzew49QdsrszeD4Gf5YAAPGi4rz344fqYjgELd0pPr16tXqOPaBomZ43vxe3xCbgMSKCwkePAy+NmAZxYA9N0O02RBk+sT6OvwE1znpHxDnoogZJn/vKyY2yDXyfjh76XlyeA8mxfV9gUhvvPxQHm5TBaw1bFVv3zhfVL+3POKitbGsgECU/oGOAFUIESKsTM+tkqyVtsAzjyXutphCx7n1g9t3xcDeLOujbQlwfr7eI3IVC37GBUVrK0FjC4kW95woH5hbWn7oLUunxufxzEdaqt9m+tl76YpysFhKHUzXnA9uS1IBoWlZ+NRbVduL9775/2EDt+A2t3Itn7iS86WP/crbfGCNc/6kueXlr2NNTUfP7DiY0VbPKOnVbKWt3bKAY176vsMKvO4CROLUIxVLtDa+JDoEyrH6tyTUSZXvN42fuLvBq64LJbf1GYuW61thkQjE2t6o/C67XdkuZO3oKTtQ0yXpfG01Al4ZgGSMZHJ8bfQc4/L+pDPIIBkpiDwuTUKZW9yPhl/7PtGT3B2sjXMMI926UBMNxBg5Xw2emI/fFaWpzk8ePAAX/iFX4iPfvSjeP755wFgYzH8+Mc/7tbH559/HqfTCS+++OJunF64uLjAM888E/4AtBnydcDOLAg9QAVslFV5Nmwbzr5zo3O5khosx+2B2ZBeWn16HcyerUvMv1cndGjc4xHzMZeZwVQX/CVeZlpy+rz0nvMywNTjW7Yo5jZyoYKtsGNabYk4hPTb2zI9H4ZQ5V2wwI83fO9FJKXg8TXWyePbJEs2LGnCmqOTkPfPauWjpThfChs67QiE/V7Q7clUE/YGCOz9ZkJYBbwwL1O/Ex4f9rnw/sLeuK3PLJ4p13luS70Wf9VyWjksSQ9Nh/SsdfVUazkAow0cGQjYC3sTAz/4RhZHA1Jm9VStYBFx7BvNQLU8avtu+57DJIWUNPOKl7VVKzgdGjjn4OCwyTo7UFVeVxrqgZtyElj9HVvwxNsYNMkQH7JON2MDY3N91rNwWt9pYFZbPo0Z28CPyVLtZeRhWCdnm4NiLJ6sXZQ/U1AN40fsJL1lV/tX2A7CVrqNzJVY7051415U6g/uHYBkUdjO44W2NKHuLKNZ4FDdXce1/F2W8YTYsyDZtRlHlnfb77opezPppnrZBIE71648Dw3b+NYzLOQ8smeCHrbgiXNuU/7MfZ7f7eldo/kW4bMOGq+urvDv/t2/w7vf/W68//3vx/PPP4+f+Imf8Pen0wn/4l/8C3zZl30ZAOCLvuiLcDgcQpyPfexj+Pmf/3mP84YDz1A5sGDN73uAKzRYAi29huI/m2H0hEKm56Z68ODnNEbDQG4seiDW8uKN/NftDezR1QWHVB5k20Gv67CcJy+xmkDai2/vAuhL/NkD2JynD9os0Lgc/9cpFy2NgzgSng4umR7PKH2CBFWlZTOgmVa0eFT/oAw3bZuEkRHECtiUEdU/7F8UifmgxhX6Tqzx5UaJ8ZUE5mYZGminQIH9LRo8zvIePYtvwQDvaPvvVmz61yDtBDGXbeCS255POPvErVoBx2ErG3qhZx2Yxmr9QxnTdhiGT1PX8eLWVAWaix9NKyhoy/gZXLssqe1rebOcsHw6/OWTr8E1DvPDJiZJFjWrdyVjbJZKPulshzps4tI6ovWb8iwsjaPluwFrRgsP922X3pdbTtvtlG1ItxmOxgtquywXKuAJh4HQDgpFa1tO1wlBzEXw3CYEEvuvgy7OxD6lyY3QPtKiBFp6slSpf5mcXEmWUJ2yEWQzk+C8aXLkxSZ5zAYEpe9C+W2MGZJ+0/c9vNELNhb38tpbYs6ANBtd9srnLTSMbW4RPuN+Gj/0oQ/ha7/2a/F5n/d5+PjHP44//+f/PF555RX8yT/5JyEi+NZv/VZ893d/Nz7wgQ/gAx/4AL77u78b9+/fxx//438cAPDss8/im77pm/Dt3/7teNvb3oa3vvWt+NCHPuTL3Z926IFAVjgmDLP5NiuUPWDF+VmeyY8YgK0C6eUdZhpk/cim8d6sh2esvFSl2vLqzV4yCOa4PQWcgTinARBmpxm0aaoP+bHztJsOLNvnJtT4eaCJrU3i2TdaUf1UDm75iPyq8W1Ad4Fy5mXlAU8UGAQ73b2grVxXZqkfiAAqLb7l50B9jfVVipfLdr1E6bkuXD0ng047U0at60o75CD0DCmNtrwgW5+Pwb8jn7A1X3VrXfrtCVNur2whN2sV0KxvBh4G8YMjMh3aEjmP52Up/hfPJ6q/bPs7y4JBmsWQQx4PlluwlFLfMSvPOLb8bBkcBTj6wZR5qUvXaCDF8mUrrPuhrH1XqvVyHOJBHOtLYfw2vgiNDXZ/E07f27I1y4NhoPaN/LD0tqxtCwOax1F9ZnHCKWkex8ZfB6OVL5BoTReBupVoZ6xKeed5Sev7PE6DldHHM8sipDonMGJgWCm9SqzTph9t0Fl77vkkOYCYZ/NnqB0eEA0bcokHtbyNj8oeaSynGOBt9GivWiz/uK7Uz7wcJpqfr5GHPW8ZjA+Cjklxu/rVyqW24k8G572VT5MFve1dWd/lOtvvHjDNk+5bhM84aPzVX/1V/LE/9sfwiU98Au94xzvwpV/6pfhX/+pf4X3vex8A4M/+2T+LR48e4U//6T/tzr3/6T/9p3j66ac9j+/7vu/DNE34+q//enfu/UM/9EMYe45g32joCb0M8ixw58hxc3CFhP1G5zx7n5yXf2eBqv0OmcEb0PY9hXqvreP1wGaoa8dcngFb7mgM0rrWGxtwbEmkQRxAHpAkYxp8Vlft18VotHy6dac81zXW07+npeZAFwsBYAPw7d3KZdNeIc+L+Mh71xzIMY9TPXPfYd66QuqQ7TxMygmI1icjgfi8dbhblSdQAF1vSY6D0xNpt+Vo4XbQ5vbHgGc7ZU084D7Q8zbgpFJ9RSq4GiCHsexHLISU08npNHcDodlyqP2JhXL7SwFx5At8T5aoajSGmFUwRgrF+2lqezeO8CU5TsOA1N5Lk318+MjrbbzoTZpUw1hnoOj+AzW6YHLQR/F8DyR3eUHzZYh0YpkDxd9YCWuZrU8qsUT8OTuv9wMqDngQxhA7wg6+ETeTwvLbl+CViDXQ5cM7jXMrLgDcXuUaX70cQYqrLV7KYsNTaodSNkh2tjrlbE1W+WSR2jG6+NHWD8F0cmb1t/MFbRxlvUplN1nMeRFfXcZ1QNZe/+b0u8u+PSMHIp2sf5gXGfBtQHJHv+7hD8urB25znN7vPVCegmh3FP7GD6+88gqeffZZfMXwhzFh2ukQiEqnByYtTi/NbUIPjG4UvezMYnRLXw9o7nWEvfpwvDUppC4Q6eS3V9ceHwFsAFtX+O/w/bryduljIZwFckdoMA3BTUpUAHEmas9lO6CDxTFZGjlk/nPdAjihvhDNFElwp0DK+voQNED77qyjspitHOzWkSz/vT4VXK7kRNqARQUevdOybIUMdeJVAVXgeCi3p1gc5oeBJTup6yBurqBxKkBgnlvasVrq7aYXo/HiAvroUTlMMs/A8dhcTilaOcyk2qf0xBbKnTCO9VYWlD6wLMDhAJzP7SQz71EcxnLzi9XdJ4s0vm25PVgrJLYbtOzhPJ+rzKnlMxjOMsnSdpZoNzexGPiv7dI72Ni7GQWA94vgouYagJjz2+2zKW38kfq7pXeMksDKXl4WxS1u/YKjJVZaGRsgVIPf5rVHH30i5enxc542sU184LzRHvV4sbnZJaTNeoieaXiYEudAaTTRHNosy+CdPAIY7umRvY6Q4t+kZ3uTSjdOJMNFT4/yxM/eZT2+ly7ryYRLZiz46fUf4OWXX25nQjrhFpttfoOHHvDg70MS7pYmC0gOeT9AzpPL2QM8vQbdE8xMl6aOaqF3eKRnFdgL19WDy+3RsQFS3QK2bcD1y5+bIP369WZe4bc0Jck8Emx5W8n0ZTp/oK18f0dKu1c3K0SqcNlsiq4CKQz0nI6iFhNHjVtPoXreuuM4mnmjiDR34nJdM196CoeVOtHLfvIkjS+lPs63xVh94y0gCVz0xtPQ8gp05TFu7+kGHM+zVSKkkakqZAO4Ex02Gdlil4AJh7wcfIsQD1Z0lI3tl8xWGJcZQ9uaYqszq/Vd0N7nSvvx2PZ5BkBBKyepTTwtycLsyLsdZBECffTco1pfaAefgqslAO7YXak/aOIVULs83VSktU6s/523kVYiPn2l9BwMWLO1rys/G13hFLTnKb4MvwGHLEsC4TT2vO0qf/xKzESAZ5Vkr2drfSzJCb5VKpMBBN4D5GQ9DwhPm/rSRoZTnYO8rnlyPs4jiud0dt5n4oM8rp+BNyavaKKlNX0PfIe6XKPfNiBOo/7M453LsXFn37McsvR7WMHy2Xg/uN3e3CcfNALXN5gvrXQY7IomM7fTWex7D4jkeFlhcbpe+WxZ8TRDTMdANqfnPIMVjcIefT0Bk8HyZmY17HTanY69B4wDX9ZtO2baA62WD5UXljXtS66/CYQ1vu9qG8rDhH04UJQFEtMaKpDiByKJhNXroV0+sWbjPs1l57JYwCYeCFLbJFpqPwiAMYNdA37kwiVYnuxZ/d5AQrpS0YKNAbNuaaFRhqEsNVucwLfUF03Q2tWBansytbNFBfGZAMFhtCrE/DSGvkx82DlpfmOwpXDzH7hpY3h/08UstSzXiA9modSaxpYbVf1qQpnqSXH3W4l4+CbXj3nJ/aDGy4tYvjexPu/uca2HXfqTV7RDMgD4OjmrdwOk2g7MiLRhy0CK5IAvAVfg4xFDem158ESNh0g+xJH0ivXpbKmLTshp3FKZbaLYG8fw9g7X+Zmc8y4klLdlwXKq/oWJL1nnr+vCzsPOGHBaUjn+qNPenpcm2jXGsfTWnoHOJI+8Abkfs36PY9t1XdZDpud6PHD9mMtKcTZ1TzI9W/hz3TMGsPcbQIr4/TYY5Zrw5IPGPcDIbjTsucXzmXgVlD3LIqcpL/fLZqWV3/OsyzoAf98tJylB7lQ9UOXgsuOw28uQCCo5T7aW9JRjFpS9E9zZfyF7unf+D1s+9+L26g1sZ2U5hAGdytgMoCRMXUhwu66koDWltbqSgGGh7Xl12mwzjbc8SIGZcF8J4LJSZEtnKJMjmoA14WwKubeX04CeCbJSn3D/tOQDBal9apo9cGl84Js9hMeoCdKlAT4A2y0W/Iz7bQ72blmiM/Bpanf/LnXZ197zEjbTFiZwVUnyyeDbnKIG3KVNkwNk9RbqTxU0yTQhHLgyoJPkh9TnIkjyr5QR9p5Z/zHwmAPz0vw72lWN3Icsrra9i+xmKfv53Lpeor4ioK0KSgeu0inrOjY2N85A+2UYjd6n6c/BSnkfrumUoZNfBzCJEZ/jVJpc9MkWBKCVGS14NN7IGTpn6xWgMtqycdIXQW4A27EPGqMUwb7nyYRPOjNLWK7WtF4vqlvmaW37WAa9B2qf1lZ+LivUKctVy0fQ9h12ZKAbJkze5/bKgfWe5ZEwh0dV6odKZVEZAfB1tnuxHLJ0Gc9wXT6N8OSDxgzYNjOHDrN5OSbHD9Y++mR3Ojc1hgGnPbNypj3QRWl64DLnx3GBmH5TJj3L1tVgbUmgyWlkWlZsOn0AbLW8wENFmPUFYEhl9wZRb1AxjxkQ27seMPXyuH9kehN/AxjQxE/KCzFpVzJ3edxLU+lQdAATSer82+uRyyUQIZ3rzSrgaBaRVn68ezqCdvchp/WQS7UmqRbrWHifhR0Ql657As8+xyG2vVA8PknNfPIxVH8vS/k+DG3PJQC/j5osm+x6R0/nVqafaq7pB76isKeJO8Foqv1HhqHucWz7EWUcIME7ApVtVweavAD8kETZb4Z4oj/wTdCuH6WxoNquFwT6qy+9Z7UtbQla6HcBYVExO3BVtCXtIKvst2zxx4Z/Vieqm9JD3XuHIDO9POrHYQiEQ19W51R4Bk8uGsTTsTurygy4FVLR6hzGN31NALy1bS2Qy4dduWgyD5Q3B21pw4SXALT3b24Q4qfSb89HW3k2yfLA+XEeRF8GT6pNfufGF+JX17iT6yrxN0AyXTrgFC1Ovl96T89aXAvZiNXTZ3u63b5nPctjNeOYPRx0i/Dkg0Zg23gcTLjuWQGY8Vlg9pRYBptA7Bweh0AV70/IM809sMbfucN1j9R36tbdf0hlm6WQywr06/YZ9p5zERJp63Voi7eZdV9Xhx1hMpArnQx2Q1xuE7YaknJlQLkB6GnwspDh90Tb9koro5/7VQKk4X2PN1mT0m8HIj1FxvvoqDyQElJO0/LRVdvys4MxtP2KAHjZOeiVJHgNdBqwzMvaxT3SEAGKary1xA+KoD0bbZkX/XHGp/2F0hlpdphE+PdQAeYQy3SAafRco7B6gYGBAT8/gT36u42rGqBYR/PBlHGgOePSyqhWRjFfkA52BPE6y50xTJNFpcM/fMOOLdeGCUHet8gnmAUOyrb3Mm9ZuPHJaPXQvE+RahPcyVAVBREI8Vhz7KV0bSNaPh3aPOMgImL/b3STZd2+u7W5phPKo1emd3lbrqf+bKCNcdDa2q+IfsEmbwZcaTm+7T+2eIFRNI4YONlP2fKDb5vxPCQ9o/oEmW/fGYCaTkoMCoHo4MpZ/j5B4Xr1dI0zlXiadFgeN2xw4XhBZ5IuYV3Z28POepXpy2DTaNicRL+dfHpzgEZW5FlZMPN6wLIHmHrPgtJJZfX8C+YZQQ+ccnl7YIxBZ87b75fWbZnr0ulI1BHzrTIBhEoDlV5uZ3lwj1fMh+tmVnud2OnhQcKDnvPq0ODAMAkbH7S8DFKXfklBAtp4Hga6NAGaAWWmGSCrXUeLsCAN1tcOXwJP+X0SHprSJHmeaWnKu6eAmwD3vWhclikhY5kp8qTk/aCE9E/LUsRYD78asL63wyE2CeRbTIB6Aprul877gw9T+b2U9lazJuRyA6vqe7uSbxjqfsA4Ht1RcvewEtWvVT4sgzr4Nv4NUlzscNq6D7Hc41z3JxJAK8C63lTDB8M8b8BPoYbxofC7uK0sB7BpmY3vUq68CZZFVKCxLLAbX8qzBojYXY8fDrFuqfDnhZS0BJ1COMHbEQ8bUKiIlnKW6Z6/UHp7ztstsqyWNKyE0rJ8MHlgh8NMD0gb89YneXLfKhvFB1s/WTwMxEwg9CO/0o/rbH1OsW1vljMBeBHAU9rSEgROR59dB8a4E6S6ErFo8p7/QHnY1/zOnjF9im0f6XQ0Tr+nq5V40q1fyicbIzh/m7DypPE6A1Yus4d3Qt2vD08+aMzonTeX8vu9dBb29jX28rnOKskzhbz/jjtFD+D26MonG0OHTNaYTAcrzVyvvFdrQ0sGY53y9wD3dSA4PFu3dN8I7DXWO5ftedBfBsyen2JrkSU6siAQK58Hqn03IEHxw33YlreBnLpEyOAm0G30oaXxOF4RuED3+1sTvZ4004G2aR9A2JtIcjzvU4tWh0aTWxDZmpSCA4Xqm693O0yboNVyrLyeEgAaeGTemMA1oCfSrIQGiua5ubURNJc1BgJsv+PpBL06wRx/exxtlje1sd67qYTrZXwYx6b0zRpIhyAk3BttAMq6lALjRBbFgXgmrUvaczslXidHbs11Xo2Nh8wjllHrCsnyIn8H6vYEanduX0UFvCWNrnX7Au3TDHv7gACMHNgo5V3T8bDa4BYbBwROmlWUae180jjYbK/wuOp1Czff+CcfCCMahly2buvkj0mmZt1vdfcmyXpFfBzH8dNAU7hZymUIgzkrIzMbaHtle33fnkeamsUzB4lJW8G1HiY7yWIZ7q1mmZ+foT+p6xlweGJgOsCe88Haja7KugMdax9XVxpNGWia7LJ3PZxwk67tGXVuET7jzr3/mwumaJmJuSFI+HWZmJnemyn4oJV+fvbbLXWd/VW9snv7Hq8DukzDBkRqTO+dJ1uJeHm2UzaXYfH3Tjf3OiwP7jBoaLDlDs/l7gVPN3TqJDFftyKi/S6Z1HiVB5sl65zOGdPvJ5s+RXl4uTyIa162X42d9G4ArCmhLJS5fbj+LdnWanZb4SGRZLs3OFlsTJGa9UjX4pxbNtaKpPS0Ophe2klbGQSYU/+SAcAaxxTz37ds0POlOe/eAHtuI8uTb0uxuOtaXO+YBa9a9/gWDJmmYrm0k8frWpvidjzWNKH0ZcvjobwfC/jSQSBzBaNDFeWnc+1WI3Se69KzQOsezCIOSWEtS3nHlvZ68EeGls75Zm1lWwTyNgEHfW2ybA7bo0ue+k/gYNEPuWjrS+3wR+ljfjp6kDC58MMgwr4Q2/7DcPe5mDN6JVpo/DMQYnBRx1CzrEeQtL3D2u7WXiut1M+05RcdYtdnvv9UXU5ueOhs134dxNoE9BvtuckENU7YwEVKryj2JeINyypPQ0xzecOyKcnLwKuWh+0b9XrxVq4spzgPpXoHXltclokduoS+s9U9ZgIitMkPT8PyOumsDPY4D9bXDOr2VkFZt2SdnDFD1n25TKNnuWYlhMKTDxpNMTMT9xqNAUwGgJZXr5F7gNHK6YG9niPPXCYQO8VeGUxXprU3y7gJiHFe+dkeH/by4rpy/QNNLJxooObbYQzI7Xnf5/xNYDCg2PAjD5xcFx5AQTIlflO0XP+wvJUAstcl8cHK8HKJX4IoLNrDlsYVARDbiWngclIcApd+dRsUIkOxXsmAsCxoRfu4MTIq4BvbEmN2meFXxHG/slqxVW5JwCR/5n5CijZMTOxvGrG5CYdlg+3PM0fX9mwqjsvFXOGMA/R0gj64B5xnyOmM9an7OD1zxKN3DHjqP894/JYRh0cKOSvm+wMuP/IQN4WHH3grxrNiOCmGWbFOgsNrZ+ggeOX9Fzg/s+JLftN/wFPDFf71P/sCvPr5wOe/59fwyf/nO3B4bYEKcH5qxPHVBcPjM/QwFnCpCrk6Qe9flqqfZ2AegGks1lJrwLoPWBXVuliBqXLf2/KcHXhb+7YGLf2Mr4psGKfJA98DO6R4GVBQn9jcd05ghW968eVuy6eCzVCWSnhntNgWDQXdlb5WeeV1xGYsxS0oWc6nV0LbNMR4YXIPUJJJPjZZNHm1pbJcGiuczza+2zhvYz7JVQdh9NwytD5gyVaWLfR8czONv+iU2cZ0uGuay8oT4tAGJkNNPlNZQc512gQti8avbBzo6EnnE1eDZDz38ayPe/qS897o0iQnbazlFcte3ryczXHsuUj9viUnhycfNK4rINoYBERwwL97pmAOWVEBCKCoN6vIIcxMdL+DMI02IHsgcI+uHhi8Tci8yel7nb53/2YGOjkvbw9NtO7Uz/gWgCOlYYBtZdigyoeJukA5EJhkWU94ZDpzW6Y8GJyYcumF0NYg3tYyqlKIty7kNmPlYK+lke15JmXA2JOvAjTlV9sg7FeHKXi7azi63LFx0FuO9jhC9xSj8MYO14jzLvUtvjbPPnn8+phO43CkA162pBy2AJiFMk3sBgEuL4BHV4VR4wAsK2QY21V3Csh5xniaIOsAmVcM84jx0YJh0e1moJ3xvB6A5ThgGhXjWYEVOD99wMu/WfCtv/Vf43U944EUq+M/+y0r/uT7/xXeMhzxf/8fn8b8/72Hx+8ALt72CI8+dh/3PjHhfL/0hemx4uLFCY/efsB0pTi8OkOWFfNTBxw/NkPrzTaiWq5UNB4NQwHPtldTpN0aQ6DcAePOxFNYhklnOZdlBhD6kVkZ+YTw5mYZKXs97YR43vPoVksBgUJt4MsiQhwYMnhsB2isTgkUuNWtfG93WAvxpFWw3b2OphKC9TMH8XfRlZWE1yEvB35AvC/a2onzT3LR46cy+Oq/nIfFr3IqiEpv+xqxV3YvL4/Ccs30TiiA0hMo9P7VAX9Wdu63rl+ybqWyBP24ni0ZLZyszveNDMh578S1sXgdwHRaNAJHIAJGEQSXY9eEJ39PI51yBNBfTrHv+UCJhR7g8nSdZdkeKO0Bur3Zir3PoCd37FxOptOVKIHlvbJDnjS48jvOq6f0QqceYj69kOu9C7Q9Ur9cVkiBN2nDsOXnwjRLWoULG6M9lC+Nhi2h2/w8DRDAGgNcn3mr72Fj6wPMdGhCGFVpOA+aMulaDDa0t31iIaj/8wftNCkqqBPXjY1FyWEzKzUDham/BMfdnTHA+9tC4EMmnI7GdbAE8WlYoMmBw6G8M9c6BkQt8OlrAeR4hKwKaDnV7fsqKa4IIPMCrXMhWbVcF79oVieb+nJYDwJRhSyKdRTIqliOA771t/6/AcABIwA8eHCFtwxHAMBTFyesRwGemnE6T1gPCpUCFsdTyW84Lzi+vmI4l/utZV6xThXEhKX+pJDHemrb+MntY38EKg0gbm7qcdBHMrm2meT+DQTg530mLN3X5V9tFsBgKbxOD9r4klIOn/q2T98e4X0OEdwoPYOGPNukCyHPVmeTVYjxdtP0KtPGZxv/Ja4fGvJhb3RX4aKUbk9smTwJ7zXmYXRm+cOTWkE6uNGph8ve+hdk2XVEdp4722o+DM7zNZrc7kHHUTzZYZTrnHWryzjvAMaT3uV4xoOers/yMOtzznuvrJw+T7hvEZ580GgCvgeY9hqTQcmONaDbQSxkUJYBjaXJoM+e9wBuDtfRzaCzRxeb6i194IXGTxakedmYT2gzPfbMBkEG0Ex3ps8G7h6/mBaeTQd6nJhtGyrXj9uFB182p+XniHWyuJs2Jd4wAAw84PfUBk6ytRkanaEONb91wWbjtyviKjSzVWKjqIQUX1veY4sLy/XCkrhXjTf8t31qiLyxMoAILOpvBwB8YAXo77ux97Wdg1VT0SaNhykpjtre5t7E+F/pEnc7VT8Y6Cig8wI7ZS22DLkqhvMKWUPSaqCJoGEvrBMgM6CjYFgUj98yYvkfHnXjPndZnr+6njCvZXlpnFaMU6FBB2A8FdA4nhU4LwU8niqBq2I4F9q1Li9q3cvpwM7He+2TIq0dDJTUvJztHS8QNkHg/Y7W1psDVZ6MLZLlH8e1vYVikwSggb8wDuD5bDwBqPW5Ql/eRqHZAqP+r9GVRGZ4aSDJ32lL54AsyoNwsCx8yQXY+M/FktN9FxlZnrfymgzVWFRQCcRT7w8rRaSELsuscCAYEVwe9QozeZe27+SQgTrzRzlNkpmuO0D1Jf2RAWGQ1x35kyYau89Yz2bd7rSlLXLA9Ydw9/Sjve/JnF66Hl7YCU8+aAS2y9KmZBg45YvfLd7e7CEz2N6ZsLwt4OO09s7K7YG+TPutQK0JcBoEvcCzm1wmPw8goWPF63VU75wJQHMdglAjGmzfynWDpqGUPg8yIM0Tg6AoduoAwC2Ffko28Ybv62W6OG/OnwVC1/SXnm1mvPSebxKxd6awAilJiZmCZWXI6WAgLtHWk0dDti4xKYVX7tTbi69KfxwLgJimpuBpAmVX5XW3meQtHCycuT9Zu5hfx3CTCrWLCHSuS7Dj2G6HgUTdMI6ADBVQlvSyNN44LjgvFVjeHHQEhqV8QgFZFf/ds/91E2/GiouhHFr56df+L3jv/RexHoBxXDGfRiz3V8z3BOPDYkE10CpzpW8texxl0ca7sexxbNcRVh7Ve42DI+YMbEg2uVscsjgGsGbvhU4KawM2NtHY3hDTymqWxPrd9v6tDZi6ldDig+6lbhzvD7W8951p8IkP5QECpVn28HjJk83N+MxXMDIIs7RtK8bWPVWlgUWEy1eN5WZwE2gzGU35WByWHRvUzPWXmJbjcvk9ecbXF+6Cy/qIyxNQfInxfbLYgT5Z1yd50OqeQF1PEHKaXt48Gcs8zzQxTsnvgl5LeTGdrGM5btiaczv59OYAjRZ6qH9vBpEBY7eBc94dMABEFzwGKHuNzR0zg7U9wNTtOGQ1CfRpLCPMvLKQw7bj2bseYN4MEInPncYb9o3mYOUFZ8O4nhcBfO4IcBccDJI6QK8lpEGt7XRzbne2YFk6y59PZNs7AzFufbGZu1c0/oX+mngYhCfVNyg2osnBIwPE5nLEb4zgvmQf4UBNKq9TtlsbufhOGrF9NodDzGsY/CRwt6/WOGGyZbQvSwGJbg1cm/VxiXx0/4Y+juDlyVL9Hw7FF2M5kDGXZV3uRwJgRVmenssSNQDodLs+L3P7XC4Ej55XfMX9X9vEmzDg5dM9nHXBr7z6XAGQlQXjtOLeU1elKyqqNRGQSp+av8fjVOgbpByMWZYIvAyUhG0elbd093PgPfHfgT6MPZUZdCDFlpe5X5jTd7cAAj658MMlDGJ6rGVgmZQ/+4ksD1LZ2j45XRSpQmOH6sj08XixDAxAc55eh1wXBkkUCLCHQ2mpDtZ/Q/lpwubFlITEEH5HgKMLGKX9bfYammzmgoTGFhNuY0nb9yDTpL0PbEpl+XfW64qtPCRZGOJkPULlZCAZQD2IT/SX89nQjVYm69894Jn1+EbuJhozTgC27vruQONO6AGlvYbbm2lavPx9XbYNszdjcd9tQ2w8Bph7DZ9DVqQ9q9t1HSTPRHr574E8A6i8XyUD1FyW/c6nKzf1SPRZvL3PHr+CcNlT2p08WAiWzPZ5EAShxN+955Lqzc/y/daZPqfTAG/qX0Bn3+519GJTr7CHjEmgtuObXBgQuhVR0JYdq2VH6IS6OtCggrnv9yZaXp8dwb7ppzXuONQ9edpORluawxTydWfH1qcVkHEsRZn1bRDAbjCZS3xZ1UGqnOthErtBZl7LoZnlGqFMdC/3y17E5QJ4/DbgN717Cxgt3JtO+KX5AlevH/G5h09ivlQoBA8urzAMWvZXotA+2AnqRTE9PJfv84Lx8dz2f7LVtVp9lUGXKf9hKCA8ex1ITsftRh92yN2urmvueCwOW838nVhT1qVsu8Em4Q3hG3vKk3hTkRhI0gaKDfA5yGp9uYvXAjbpyQSO0H425/flH1tJM2CLEyxpz7qzNL3mneXJp7hrVL+iME8+c32yPKSfAWBy1KHxtScLvUFTPXjvKND2d28srCSTnR7Zxg2GAYq77Nx2xLq5J4c8SUceWZ329NFNgJF/u7uwDv7o0chxWL8ynT39yFjHdcrN4c0FGlmxMDPZVMxKaQ+8AfEdg8we8Modxspii4jlmRs0g6wMLJkWDlmghWVQ7L/L4LF38KUHUDNve8A0lwH0wQB2OnWu3yb/TvuEutJgckGSBrsPuLok1zWPyc4zy8/4lPLYDPIdAei/6d2mXxJdnq/1E7uTOGvVrFxSG9A7B4XeBxHbJhSvrcnYVU5VrFtljlauILRvsJrQGFHVdmilPEj1asAkjC8RuJNuxbYN/HR1Gi/Z3RWKT0Sdyz3TuizlVfWdGOUFirVQgPFxXSa1q+f2AtElMzCsgE6Cd3z+p/AHn/3l3WSLDnh1vYScB0yyQg+K89WE16+OOIzVajgKdEBZll5XXyZfLqfGg1Whh6nsZxTQAQptvHBLL7WPDKH9skI1n5NuTbTneVJt35UOcKD2n9pvHVR6nNYX4zJ2a4fmmqfQHUCSy0K0Z/7V6Kv/1Pp2BXa96ws31iomRzr9L3cIGgOErQBsrau5DlYsOxDPgWm0CZuPHWllembAdtxWoryqa6o7pTX6upPtTH/nt4uvJBN2Q47Hspv+fIsFNxDJbQdQEoGbky5tO5tUK7zJSnZJZXnt6bisWzO/gss20nd50syf9t5Cb/m5J0MBdPdrdsKbAzTmWUNHUEWglMBHBid76XvBZkvZlxIrGXtmy0BMcw6syPKAZMBWHsT69Dpg73eof1pOvo439qy3cTeD4byUyHFWcsK8t/ckD4QMiPaAZtd0kHjYRThUzmZwseAjANKdbeayqHzmNQFD6Q38rFU2QcKHCzFLF+QlCdGk6HrXkTUFQ0t8LofoQAHfGz1UB997fcb5AcSDNZUHxiueuKS9jeEuZli9tvk7yxwYdmipV/GV21IU6tduWvlln60qikXRaBoHYF7LnsRBMJ7rMqygWSqdKX0FOMwCmRVXb1vxDW/9j904Fh6ej3i8HjCcgHcOK+T+Ap0Fx2nBo9MB84MCCEXhy+R2Alqt+yzVyhiuP0StnxZL61hlk6DJNJ/0duRR/e4WxnEM/ZgBfvDVaWkrsGQrJANP70uwJqH4tV/GayztL7U3UPpq7dPhOsCUprmdQivbeBV+SByWAgJXCajkPmnfNzI5l9NArburqjQ2QMvg1YAel6dORjjkZnTyZFQ8UayYUF1ZNjEwoWw2oNToAMj6Kul9r+7EEH7nIlg777Ps3CRKY7JTeJ60+37fqqvYPZqF3p5pS5f1VNbDm8kr+jqT9UMvv4xv9vTyLcKbAzT2ULz9vgl9c9rg0yiZfTPq57S22b4H2vjgjCmj6xovgz0A4aRx6ARrVLKWpnfoh/mR87mOP/lZ5ulNg6IHIsIhJXufB4XR19lfuReYJ+UBCYCOQg951/fWB3b3HqLRG+jmeCnPUK8qOINSTUJyAxavEYBB8FM6E86S0ikrTuKFRUmvevupXNGagqc2MSsSL1d6GdopnwHJkoRsBpdL2ve6LJR+aO5ibLzZOF7XdjDGLGyrFqfXWumX5hi60NEsccK+IFmhQIB5LYdgFMVXY2QeekErn6enzt33HO5NJygEsgiOMkFEIbM0aHKoeyoFxbWOAxK0gzkVJLi/88cnao9qJTS/jZbeQLRZy7OfVJZpQGf7SgvBrY7SIZYdUN18GxIgoXzs00GkD4d+fgB8qdqAC1sSPQ8qM3gESE2+sY4BaEu2QHxhcTWCm57cdNmc0wvaUrstu5sMMlIkJ2llOT+prFJxuDXSZRnJtMBO73GpXlYfzptoC8ljf+yC0ADgiDbTCUov/ZAmJet2ARq7XE+WnTzz8BPOJJs83o4u9LpvBGiUR5Zuz+hgce2Z54vGhzyp5rj8m59x+TeENwdo7DE5M59RfBbm9pv3H3IjWhxhsIP+Mm0OBia5gXsmcRYamzxpkNvnXkey+BkUOShmk/mw7fQdob/ha+7wGShmenIHznk6SCM6GAQFkMZxOgM08IYHCvM1f9b3AJqfxcqnfAiC3/ksH025suDlgzcMZGF9synujUDy2fg1Az3L2SD4tcUxgV3zalfigfYhtrLtdoxQRqeLmwWJ7w9uINhoq9fB1bZxp+IM4tI+O4zm2Fy9nBAMKI4j0bc2SxcDGXP2zQc78un6Oo7dcjoVq1m5pm+kiQSg0wiZlwYQzao3DLs24RyWewXoffN7//dr4/1vL78PH/vEc5h1gA4l9weXJ+ioOC0j5nnE8ZkryLKWFncLY+mXMiv0MMY2pHEnwwAZp8gLsTpZ/xvandsmfi6OUZ6i5jvlvMSth+asfrPFIANAIBzqYHDX24sbrJHst9HJl9rvhgAsuE9p6P80Rhi8dTGTyRQEzLEBbD7O7bnE4Z7BGdMjtQ7MC+cdp2PZuLa2DoYCtPQhPvqB+4TQFwkPr8/D8uG2Zz7YAweH23QRtFEdvR49vZV0kn1uvAOwfljTO+YB6U2eMIX+TsvYOXA7ZB0fwCyiAYppCe6xsM2jhwv4+x1opNBz0cEM7u05YKZynNwoex2Ry2Ug2jsEkcFWDhnU5k7T6xBWlj3PS8ar7bfLeZDFoHfVoQ2kbOHb66xcz9vUNQ8oL3+I7ceWx/Kl1dfzov1MmY69INL/jETC27o3m2PhEiYsCfh5PUhbBcHd+e75I7Y5A9IgzE0BcV/lvImkrDjEFGZqK3seWF8Vei1PRCDj6OAu3EU8DqGd42GFqOz4WjofR/NSyqlLxzLli62kWRBdGJuil7IMayDBZAHLAANASxsj5rPQ6RnqGNC17gmsy9D1XmpZa10NgA9ye5c704pHb79ZNP/BZ38ZMgtOeoCOwKfWchWgLILTownLVVtRGM7auoh104NNgNAOB9HYDBY9kVKHcSKFmLaYmPgxq+Q0RQtGTeeAX9s+xXZoiu6f5j6SZQhA/RPe5+x58MnI3T4BqdY/G7hrd6Gj/VHeMMuZUp4cp0UMNMfT1qDl+tjvfe9kyEJiXJJ/vCQdvBowfVafEqm1awYPli6gYG1lh0mnWCO0n73qB1BHsiTJuiYjWC+RtXDPXBhkYI0cbrwyOi0u1YMBmY19zqurMoxPJF+4rowvrgNre2n3frORIBukcj2GpC8HmhxnvvWMVNeENwdo3IA7bPcKbGYOso3T2WsVAFAuJ4M4VVL4nU2wPcCUn/MspAdsArBiwUudLXfGHojL1humSZsy3dDE5fc6da/c8H7Y5gkAm/0fGXzZs0475OUHFroBoURh3N5vtE1mSiwrTCoGiiM7ScwKGRVlyMsSZR55eqqn1YOBHee5kfA1b1Ys3bRJGTNZdNVavuItX/ema0fYOnnx/mJd1niaMAhcFOBYD1r4O75i0E4EMyC15eRVgWVu1rSIVgtIOh7b43mBqkLHATqOkOMhWpxEgLHUa7gqwHM5NkveLmhMsuniqRP+zJf8637cFIaz4N2HFyEK/Or8HBYth16G10cMVwMuDzPkNGNYyj3WGAYMpwU61OXoahkFUA/rqLd987UofpK6WBqHxkuzzo5DX2ZkhTSODZRZcNBBt7IkmczWRgN6vf20DRilfpKDtjGQncFfe5PMBlBZeb2I1KekXU3oImaNfG4LEKw3Mi2pbBpTbZ8n64tMk3kxQOSR87uOVT9Q05F7Yaxo+1QUWURL5TEey7iabl0inwJAZRlcxxkbCViG++PefvOcRtp37od+piDrwY6e5d/eTklP5zRhZYvK7OVteXRBvUa8EQ7MdLaBqLZzAr1V1z1dvxPeHKAR2IKsHqjJ+w75NDQPrAyyOJ9eo3Q7RO2MeWbB5fVA5B4o4ziZJr+vedjP17+zgr3hEArTkQW9vctguls3a5e8NPDpBBa4OX+jz4QQCxRKH+poAoGAneXZFWBWtqT8szDvlNubqiv/VriVgAWgP2MlRWmA1q7Gh8ynTdFluctPqSbF7NYNkr+lGHLkrNHH3uZKuV5f5XciEQAuS4uX+OeAJrtY4f27axpz6wqME3SZ2zYD1l92UtfyGOtSLMSv3AuHDqDuQHuYK31Di7sJO5PFP/D8/76NuxNkFjw1PAYAfHJ+CodhhRwXjFcFPN6fTtDDWA7ijFJORy8rdGpjW+updD2MG0Co81K7c+0D7gaFAM/A74yvVeaYHGXPD9Y3qA+wOyaoQpd1szePrwa0g1UlMTb90PcoLtfsj3QMw+0IALld20fxXVrry6DV/nxo8TjUNo4dUMHLCCejN2CrvvIymXg0wIJEl9OyEm1cXquTg3aaWPVvwZFWfk88C+JhzpCWIimVHzw9WCZUCB/SC/K2fmYjglD/dLkNbHnKHSaPQ+3E4/qkvPYOfrLhg3Wh54v4PcuIPcDI6Xp7EW8CmQEb7JR9TXjyQWOYcWqfYXvfGQBeZ3njBmHBmTsKxwdoM3lq3Ny5uoBLth2Aac/Axzp/Br+bwJ2z07E4XeAj09xZuubPDa20LJEHWi9dbsceCA51TPEzeOvNEFtmaLxeYx4BJOt+/bMgDH/a+LcrxDgtKaAwy0918zhGN82YWQFUcLXBzlKUqfmzc4VUlRq7O4k0GTmk0IEGJIUchlfe873UZlHy+udlY6DsQxSJexaB4jNxqO/cAkl+F71foQCd46EtY3te4ks5as6uK/3W3np5KJa6q1NJV5en9TAV59mrFkfgigrWCk0bS+OOoP7c8XZi+d9cPcByf8XnTwBW4JdffysupuLrRxZgOAMff/XpUrai+Ylci69GN7YsC3QcII/P5e7s81zqOS8AbAJAh4AA2ARUteTXFFitlztTR+vSyc2ZUJvDAKH3keh8O57El5Yv4EuyZdsD4Cenoe7T0ScvtB+yiTdJ/TXfyFIDTYJ4nAV6tE2mDAhvHGvTmGiVAuGaJCsUyaMARaE8NYxlkkVSf+cJP/JvG+Ms+4kUl6NMM8kse8e0RQbWx9J5R3GudUUGkruJ9hx3E0+pHvaIVs1UEXTRhkbT82TcCKQTP3sYg3+73tnhg2GJm/Lp6XHWf3uHYbJO702qdsKTDxqBCAyYOaycXKEM20bY6wwZ4ORystWR0wPbpZucZw+cOS21w/V8THLevU5l8XqmcaY5l7/n65FnYyLRZU4G25vOLv3OzHXdm6V1+ZqESQb0PWXQA/bOy/qX0wX3Lh3hFfZT8u/03eNwHWqZDEjzJ5fbA8P2WwB3BSFIPENT3gDCch/pDcAOr8T829JsZEH21WiHYfhkrLVJTzmHu397wnKhpRbvrzU+vwtdQgrAG4cCmqYJPn6A6m7G6Oe9wGMFvCig1Hh1Ojs9tu9TlrVYGlXbUq+V74dHrglvQHADwMP1AnKvgtoJeP3qiKemKwzDiuVSoSOwPJ6iq59xLMDW6EoO3LUuRftBpOp2B8MIXebi/Hyl/usn1ms+qzZrr7d1ydzbnycLFoYh9hux+OptyxZBXoo2a+L28Mr2ysrmt9HGBqLF0j6970iLCwJnBDqDd4C6PzOPnXBIJYQsm7HznsZmb+LI6UIRJa64hZgiB31Cr3sTYV+mlTbWSoWR+RNAZzNzojFW4vssx12fKNFNMs+zZ32b6571XtbfVNe8Euc8SPovHK5J45kxAD+zz6zTvQw0PXkdEMx55jz24uxtBWLcspfPTnjyQaOBo9xgHEKnXbfPGYn3OkUGPblBQuMMsTPl/Bkk5cG0Aazr9nmOn+nY4wGw7bhcp3xYKPOAP7mTZqAWwB3anpY94HhdmRYn8GonHtPG5UsHOOdBx8Gdvo5EWzrs4uV06pRBP5DSe4KYPgPFkI73TVJ8EQTl4iC+Sl2W3UBT0IK29CzwSGInjd0S0+l3iErU32t1yOxgrO6XS2kDYLTPYWjWRaCdeGYXO0sCj2a1mpfmh/B89j5uviRdGRpwsP2Ry1IU1roA81y7YPFZuFyMMBCuw1CrV8qTtd4qU515F3c3Evi8G64bm53w0dfeiXUuPFnvrzi/fIHL4QxFWZpWAYZTcb+jxhfVck+2ga5xgF5UB+XDUPY4VnAt4wg5TLUr0yl4PzgkzY2R8a/elhPGWt1WwM65rT80N0bJXRJS3yCZ0KzWzrgqQtoJYj4NHQ7LDOTyKY8NKjcuV1P7acsn4CDLZseXY74msbvEHb5YQWlMR1Ne++7ti5hvfR+XpMX5FdNzfYT+QDJGicTKd+Mlp/X2YbmcQVzSHdinOxwa2sS1unM7kgx2H5k1341u1CRDWfaybma4RLSzzusBtI2OYr1G+7V7YQPsO/JxDxRmDJHp4Xz2ttB0wpMPGrOlyZ7thT0k3wNcxvxsncsg0NKL7AMEzp87wo4C7s5KrNwM5HJd9gDwXtoAtjohg9ZbdXDmUx98dOsQ6sI8SsKVgdseIHTgkwYdD/LgM9LyXmMZoZ6pDmFjdu4X2uet84QVDfHK6RtavGgeITp4f1ZNk9qlWRGbYgnWEoofTkkLLSFaUnZ3Ysva9Fx5KRNVmVp5VP/gvPm6rSFsKRxHbPmvDeRMdSnZFKwAmOfmbqfyUKaxfLUrBocBMo0Ns56TFRkCmcq+QRgomZeyHG31ngb3g/jrDS/XU9IvvXbP9di9B1eYHgpOWmhe76/AoBgfSrF+WrudZzSXKyjXGz46lR/LArk6N0uh8Q+ALdeJXccYQAqNX1pi9sAKsQJ+B9lm6TaglZWXlL7mFkKlAzBApUdggK31s9hnDOTZZCEs5eZJz0pWzY380Ua/gmjJcsU+6x8DOgY2AeQYLSSTtLwLYzgDMP8pPOz9S953a+Vu9jZ26tlkM2hosZwh+cH5OE1ZJknKi+T4ZqLcMtrssQQoTZahmf8I/IgAr1dflqmZFi479XX+zDLdJ6hEg8Xt6bg93b+X/02hRw9/fwP5PfmgsWeh6gEE/r3HRFZSPfTf++7Agg+YpI4S3Nxo++vtacggxfLMznMzrdctO+c69oDyHiDMs6jMv1yPvfbozZTy9+wH0/nWUXIcp/c8CJqu1GyBwacq3NqYwSgDQS8jn3ROn5Z3y4iEIcfvTTaAJnA79auKJJ/ajJaEkm6zfCXZ2lIUpTLYc/a0vONeRzo5bQdkhthP2nV1aM+NPAvjQG5yJB52cUvVGk/yAu1ABlBud7H9juZKZ1np8JvU5esJejgUSzK3w1IdXI8D5OGpgTBFs65ZWxDYEOqv63Fnr+/e753wulZL68MJzz/3MgDg8556EbICr5wvS/ONCqhgeqzFqTcKj9VcB3H/s713ZiG0eJVHDsSo/WEWHM7D2iRXw/rfMLhF0a2MabKaD0y5hcmz1zbxUITtCTKku65rk7DTb8sjBI13YFt/LMvKQ3tm+XqdQNZ5o7HJgXCTE+g92FcpvXesQkBIQPHb78Bkz9c+uA2SX9QM3ixRxkhMg9EWlqh5nGf5yQCMhU798wlpR296/bzx+voIKb2CJicS/2r67d5SiXXeWD4rvXu4IYDdTsj7CXM9WH9rKmcPTHbp2AnZ20svHevvW8qfJx80AjczI+89zMCKBWwXzOx1anq3LjEdg0TpdD7Lx06jcTwWtvzHZfN+L8unR3MOe7MZ7uR7de0Ngj2QyXT0gFUA3EZLD3ABTSBhy4fe8nO2LGb6/B3XPy9B71i/IG3p2hWr1TEJA69nArY5Py83CZcAFFmRcD6a0vFfzV+qIiVF05LrVieQAuUTsCV6U0BCQEK5PyRfYb4cSJMLX0IUqcudtS6qZcmZ6TOyzKLYOXCiMx2IMQBaaXIH5Eo+JEXKsvRa9jHqurQl9fpezG3NMDiw1aHsmdTRTizXNMu6vUbwuonSNUEA/OqyYjgDV+uE/7Is+NyLFzE+VggU62mALgIMClkAHQXDqYLqyk8VKfTMxf0OxqH4mAQKMK6Hg3SevVRbrvb+4MAaoe30PLdnxvNO3djVDR808jZLMkdSv+F+G26VsWsse/cw98Se0P7JOjSCZZIwTNv/SEuyRo8iyJEIDNOYdHDUorh/RqWHSmnsIwMdLtfTqfMoygn7zXIk6x2jQfy3mF9So33Tnhn09epdZdRAB0myHNX0Q4kmXyWx35ZtBX/ButyRcWzps7ryCf0uL0g/ef+USNNNRgcOrGc2OpnOJwBtfGVQyfTlcdMrC9g/4R3qervw5IPGjOrzrEF123jAthH2kP91IIqfZ5DYW3JTmpHzPswMKrJroD3/aHl2k+nqnawKAynxIXwfgqIIIdOTQffmd9qEXF5is/9zb9CEcloeYtaSDW0a23MPQLJg3TsRbumFBAnPtHtui7jsdSWhNESeWB7bDDrPkiJQpoNp5r8tP/2OZ01ClgGlKUhX0nTYQMu/bN0Jh0vWNfZhF5JD6/8ZxDt4Qey7Fm8cmwVq4Dzod1h2orEIlKVrKUpaTqfQnDIMxV8jUE5ND0MBWtU6ay5rINW9jikxA2jVvc1y0Wu3Nx7eNih+5fxW6Ihy84sOeP/0EuZLwbOHRxgvltJ+QzlBbQ1TrhEs1ldZ1nJrjQjw+AQ5z2Xp2m7jmZe21FwBmC5LA+zjWCbCtteU2jTsSx23spVPy7f8y1j3vjS0qyaV+hlQwJXdSmR/fpsMp5EG/PzGGe6nhgm8r7W/zXWC9hEO66CNBbPcbURATz7Z/lCKqOhYE23cRbnWKkCEhUkfCNxQnE06rpsG+jwb6+O+FzrnybLO6qgt36qDGuBn2WHtTyeVu0Mkl2U/SeYpSJ9xHbWygwAf5xmAaE1rqy4MULnMnvPxniHCyU+6JmMJ1/VJz7NfR026pIdb9nQ9P7Nx6nXJ/fPm8OSDxgx6WEFdx6SbGiIrtbAUUcMeeLL4rLR65feAq+XbAzzXdYA9oGpxcycOnbXDg80MURFmSgySCwGxDpu8eU8bDf4wy0tAods2pJzYxx/XLQNBvrt7DzT36svfcz39twm21GZctlsuq/Djum4siCzggpaI9PX6VQ9I+js0yyHnESYeRo6gq4cAP2hQkuelMQqdpcl48jmlGwY67CKR51YvO9nrSomIU6UmqjTatXZA23t4PhcfgaHbKzDPpW51idr7uvkjrONLTguBVGCYV6wVNGpP2u6N8WvCUSb8yqO3QgdgXkYcZcHTwxF6UDxajri8PAMCjI8FywWgo3g39OV0oLrgKYd7DODCrF2mjKtSL19p6Xgprn2c/8tKoKHWI1v6lBQ4sLvHPFsYu0FKvM0+xrCPtoLMcdhMbNjHaCsP1HfUy3DecX927FHyaVbN9L47XrXu0ZRO+2Pr6i3oMMsuyyUuXyMtVukwqU7jozuRNGtv3sNrTATVgcBklvEK2jdNsptBnFD8TI9F8YN4oDKqLEh9z/feWrZuRTaAagNcOzSj5e11YN5R+d3xmuqf4+dJE+eZn1nZDq4pzx6+uA4w7tGUf98QnnzQaCGjewZ6vZPB1qnTBv2QvifwWcmKXN8Qe43Wm41wh2ILIVsUWQjnvHlmkuuS6c182HT8jmUWaEvwDMI8nfbTBFpIEPrJ8DSr67WBCR/nEXfrlHcoLwlO5uNNyrw3GeG7Rff6BtDi5bIzTXmmm4GpxyfhFywIQnnwu6q8fcYJ33Po+aeiN8YOV7ZoyhUAg05f8uY+xBb0LCS5r+YxkHjqEwIeE6rFYriZEJa9bmK+GHUty66CAmym6opHyyEYOZTr71xPLEsFIFKAVbV66uWxWOicbQI5z2VpeirWPDGgu6x90JjDLWf798Yz9LBiXcWF+HIBPDVd4b1PvQSsgotPkKXR9LrUgzHrClmKayC9PEKnEXqYCu2HqQDqw1T2gh4vKsgut7n44ROysKIuywcZsqSJwe5ECw3gVUDPN/w0v4vEZ3smpe/yFoPmXB4IFnFtB2C6fhgB2F3U1tl9z600GktmqdnCXdQa3zM42oA1ytDGnO/zrbJM0UCuFeFyI3cqHuMkd6t8tHuqY9GZJkrDelIorvE315Xz2/BYwsc2jaaoJHS0eiXw+GiybUjyXpVcKzEPdBNvU18WfGFrUaIn19XycItsza8HADmd9anevv8eMN37zs/2MEfW74xXbpqkUXhzgMYeIw0QZqXECiwzdk1IX7XlYd/5PeeTy+Z4Bjh66XKjcnn8vNchbwpZSe/FMXrz6a/M12xmd9P/DoDaAPnO3lKmcwOkmWfEEzAv0ullz880Qf2+O2OU7e8ev0zoBXDTydOAFL/jwwUbiyx9MrDM9bTneTklVycsCXGVSNEmReAHXdSSt9/h4IFRYSefFa7ITdHzJKwJ9h6bdsYMUE4om3UsC2VIuznGrI5iTqgXUsQlfxmnsuQ6L/WubKR+Jm2ptPK8gMFlw2ape/lkLfsHbQ+jKLDcP/ZB43X1vCZ86nQfFw9OGAbF/aGCoosFbzu8itfnI2Qt5Y5zaYflaFYa9ZPiw3lpy9BanovWAzHzDJxn4hnK0jzt8wy0r7Rnkuphin57Krqldyug1FPz9DvyClWXr5v+YYd0wlWD9o6WskNeAIGzMiaCk29NfdT6PZNl0YfYZwLI8zGPmNjxTBrDNoStPNh+S/UolHnkEQPKbPXUPK5Mjlwjr8yCaH+brVyJDpdtlLfTlOi3uod2znLNZCqvvNgrbb/5O4Pm7KTb5ebOtqUg+PJyN33vTWyBNGG9YWxnvMGfve/2l93z8JjLYyyXw89Zj91S7gBvFtC418A3IXgGNrxMkC19+XtvpsBLq11QWZ9ly2amdyNINZaT893rhBzMUrBHuz1j34SB9lzXIKXo8xraAAQLZe9EdKYnCJwEQje8IjpMcHh+awL8Nd26JKFT8zBn2SywrOyeLy8OvW0RvBfHlNiGt0aXlUU84/pnocoKxoV1ETzbpTcCrw4wkdzhEKlDc54cLUUS4zJHqE4y5DaCW5jcn6NQXj7ZMKviRAlDIWmLRQEstnzZLNalnjqfm2LXemimlm9gwMAMqiVOh8EdfGuqh9ZltPU4lnuqB0AU7RTzdeGWE77XHl/g6tERh3FxNl/cO+OT56fx4uP7mF4bMJxbXqLtFPVyMQLTUFg21SsELw+V9sGvQgRQxrwPF2muiTIQALbbBwA6YFRlx57C899ooI/7KVCsxeyH0VnGsqX0IV6e3PQzxhcMYOqJ6+6Vg1xdxgSOQSJQaPdXG3hRwjTSyrRK2++NDLf3IfvIMAZsLhcklaMpvb0jugKIzJWlxzYWexNUzr/KiBglMTDoLpLlm0l5mvwLEeQyO9OT5TGnT2VtJp9cmQy6eittkuqSQi4jP+vpcX5n+3UzJvDiZZsfl8P6ZFef3i68OUBjD9DwvpGw8T7ts9kFIWjvM3LvxttZ5mZ6XClKv4GZjp47Hiubwe1G+XYGRw+k8DvPs1O3DO4yQN8DvvyXeWQe+i1+z3TPM10G3b3yehMF1VZG5g/fmcu0WHk+U9VqYaG9NoGmHVoyn1mA8cEY44lnYXnSd+dbRxBvgvGpKl4C9+EUtCsHWwJsd1CH2zWCwjFSmrWGr4lzK5CD1VpeujIvXC0HNEfeQBsjdijG+kbeomG3uzgQpPTjCL/v1k5ak6LzU9u8PDq2Qxl+2EO1HQoZig/GsrxbyjfgpVVp6igbXv16wr3jGViK4+57UsDzcSr0TOOC4VT4o4NgnWp1D0Ux6yjFP2OlX9a1sKDyozwXuiWnHIKRuewZdQCogBioHDtLmBYO03aM0SQ1uKZRWl6uNLmrHJ64JzlgVvJi+W7jygAjWyHZAugnlmt9zOrugIf7j6uIPE6AtpRpchKU0MpLn0IvuG+I/VE5eVyHvsQ8MZlr5TDwQScYr3KmVherZB0n+apXr1CVm1wnkIsmlnHBEhh53/iRlpy791kngJjBXQbUeyH0Ka53q0cs2w6smo9Q0weUjnm0B8pYH7DO7unNnCfTzfvDvR7YOWyb0ubvtwhvDtBojN5zrcPM5SvwIDE+N8Z1CL0HzLiB3eJB6bMFqgcOLX2Ow8Aud9Ich/PJHacHYHM9LK7n1+nEHHpAdO+9x+kAQw5m6ctxPa+eNaNTvj1ncL3h5U5b8yDvAThXHkanpP5H+bHw7YHycIqOl7JrmoEUpYPKPUEgzXoW2iZmm+PYkjPfDR2cLNOYMgXei1scfvOBm77wcmBiADHcb0y8MHBvS6brguYOhcdv5Y0vNQ+Qw8Gtj7qu0NOpWN6mdiJY1xVaT04DaId1VEs8AOFWFOcpCmC7KNf2rQe53Z7GWwZVwXAlmMYFj7Tw6OHjI+4NJ/xPz/0HDLNiPQDrBAwz2r7LcSig0e7mHkfoOELmFZimcq/2YQQOU3HBI4L1/gXkeIAep3KKfBwgwwi5ODYeL7lfgnxrkgybpjgRMF5SX+T+ka2IHoROTOe8vNnb1YWt/9FStST/h9fpziBq2GF2fe77EOmZTbjM0pnzNxDm8WM5wcgXTgZnGc8Z0NcEBMMd4iHY+NcI3hyYEdDjMdWTsy6TubKmYy0PtO/Bisppd3RrANiC0HDCeRBNgV+UN5dHE2h/3gNtuV4A6Q+evAMsz8KzoOs6cVm/9sAgx+H3eTU0tJXEyTVPuq7T353w5INGBgHM/B7S3oC0G0Dhxm9YYnqvwXuN2escezOB3jJyD/ylmXh41kvD5faWoblO+Zn9zoCrl3furHlm2APBPMgNGGyWNqiO3X2MtCQZ6rNjAe79zsLEBxwJVCujJWoCZTMoOb6ExzHakL4r/Rm/LKF930h/mHJs9z+3JKW6faHBV7IFcGmKuNNf2Srp+9OMbbX8sM8t9xk+ZGHPKP9yh/TaxsM4BUfPrb8luoEG9kQgx0MBMtym57m6lKkA9/JQyrkonzKXfX46VN+GCneMrZdHP2TiukxRTyp/5sL7nvokhhl47vAY/+n8TClnUDx/eAmXcsYwA+OVYh3hjrynRyuwrBgf1ZtfjFeocZYFMq+Q81K+L9XyeJ7r3sei+PV4AKDQ0wm6VDc9ZvFV/l75yZPsZd5vU2oDGYZ2p7S2G1oMAPI7m6AE65zGW0TMymh5sNP5FslIsXFiDxD2KLblc2zSBqZyf7f4PjYrvcHK2pLmTNuhM4uQgFIGpYE+rXRocj1V3znY6QCiMPBJTmn9JxKjBRAn/ba2tEh12ZhbvYKIchcIPDQrn5N8nZzNIeln1kHhueWbZBKvVvUMFz3skfP1yT7lkYEj60Rg6+HDdePaPi1v/s3PgK2nlFuEJx802lKThQwwJDVWbsz87Lq9djnf3vNs7ex1klz2nmK1wIdjenF7+e3NKhgY7QFroH8Suwe6VBPo6eTZCqeB0QFsXHY2veeDRAwWw0BNg4/3p3gZHd6IxLj5Gdc3b77OwYEm1Rudds2zYu3FI4HjcZkF3EctehZiGuOhKpgKukxRt9Oqrc7C4CBUsbWX5SV5KbrbjpW2eW789BOsJoBR+E4zZzkeynejh/tk9ku2lmU0uyParZrrCj2d45LaNDU9aMvPXNex+mwMpybrq8dLWRJeFctxgE64OeyNyxR+1/3/jHUCPu/yE5h1wGt6xjSueG29xDvGGesErKNgWIDhXPYzlj2NRdHqsZyODspnGKDHkW7UUeg8Q071gM9cV0jmuVnogHoAhvjLig1o1llzm5Rch2hOV9td6oEntmL7pw/foer5tg+2+QbtbKcob6oYkAY2g6jkH/XDDlU5vdwaJjMRQGjbz0f91n4byLG/MFaV0oHqj/A8BAaVNlYsLwM7O3JdbIJW48ST6i1eW352QUL14fiNH1EukH5yWczJmdb8jGWtMUy2+We5ao/U3hNvGGgHvvB7kpNBViX84LLJZE2SawFHSKRhGKKeyqCPg02UGYzehEPs/R72eIPhyQeNeZBkJcUm3R6j82xp44BTY145PdOxZx7u/eaye0CLASDnm2nKYKtH96Y+qf69PPk7p92UXWe2PWW4l9aBF4Ubrbp574zRnyy7Xre9eFlodcqw5WDOg4V2L7BA4n6UZ9e9gRz2S9mzTh2Q6GcFRUX4JN3db7S8XfHyBnZWlkBbYu7tmbFiqqXID8bUtOEUq+rW2mh1S+NK8rLmspRnAOQwQU9nPxgjh6k5nR4av+VwKMDw8VWp0zIXGgxwugDXAnSqGxk5VcviOEBWLdbFehBGx6Gw9HQuCvhqLu5rfMkawCBYjwIhjyG/3nCUCToACsFHH74LH18ucDpNeOf0Cj6xTJgew5t9mFdMj8uBGVlWDHPdyzmvBQjaSe9lKfTXfqFTO3hSrLN1qdcmAdMIv37S93xKk6nsXonaV82SW0OYhGTZp2ZlHLzf7cnKsKTNExZt+TaLZOvPebi7FwGhlxXM+LgIw1ZieeD8qQwqu2tcC7KpAa/NyoBgCxQMbFk5HtfGcadgS7KanOY6ZPkKbEEb14/1hn1yPtZOpg9oSw33j1B/G0MdsMYyb6ML0g8DjBvgjjbZ25Pb+eyDd55kyfPPtL+Qdal/pgNjWf7x997KYk+HZ/1v9GZQ2wtvEDg++aAR2DKXn2XEzr4Og2VCYvrcqDlNbxaQhd0egLSQLYjewXoDRfudKAPiDDBzMOGTO3Du4JmvuWM6n9d+/FzfTE+m+7pZ0U1WR57h8Ww2DD5GSGnwWdpgaeQ/tDz5e5feTvxu6ORnz5Vo3fSzLPCrorIDNaw0zeFuVUJa9/BtFIYpQFNGCgeElh/vXbR84tJf7PPdvWg0CQrXyqk55raxVfqwzvV0+7LSXkO0etrVZ6lOcnFR0sng1//JIMA4tkMZY9uv6K50ruZiaRTx/X62hIuhAEpztwMBsCrm+6XcdQQ0n5fqhTciwAV4z/QSXnx8H4sOECjeMiz42PwcFMB6AGRBsXIKMFythX4DNrbEHw4DVRoMIG9WabQ4OrcuvlSlaz4ZPZ+k2GgLgAxDtCSrOsjfuFpy/5oaAKNveVjb6f3oUof37ML3Mm6GnIlTWn7eHPDyNB36BCnfNp4KNjIrufEPrX963jx26XMPeGjKiz8D3YomDjr9yuSYWRDFKkT5cL4bkcURk96QzruteTTmQe0VQvZIYYBzo8KsHC4r6yON/OgaH5QmQRkiGb864I11v8uzzhmEUNeMK3Z0V6+8PMEKZzN2JuMcAtjVLS92wpsDNDLDew0HiebgDOryjPk6AMP3sfbAKof8nmcVDAY24G+NdOZ67Tnf3is75+O/OzRnkJLBaS9P/50GBFsN7NTwXuftAW4D9Az0XXilZYLNKehUp9CmHYGSNzkbeM+WvH4B27i5rBC3ly7R68gPUYlwWkFbPt6cPqwJqb3daoSqZPPpUcu2giy+rzdYcqpS5IMwyvytSj7QzH4X+YSujYt5Lid12RJYAY8yABGBns9wN0o08y/3R0sBguauR1EPvCgt09WwVkA6z2WZdp7bfsh1LaDrvBSeTPWu6UHq/kbi2arFKngbmXxLwQ0Aw4MzZgw4zSN+4eHnYJkHPJADPn5+BqLA6RnBOgLLRekDOkoBxufmexGHqd6ljdJHzMooUnxX1rGlQ7ku0W/SCafJef8W2jI010fX1sY2ec31NWA4khV76e0FjsH3Na4NUGZ/i5u9i0H0tvgbX45WJ2BrfZdCc7vtpD6k8dhuIuEOkQGUydM01kO0BIIywJJaZgCUBEx94tlBmVm/cVqfJXKfNqaC5Cta2wbCE7ND5XrfQTrA+GnL4s70RGOuG9HD+We3aj1dY7LVJpo9Hcp6tqd/Qxzp87XndxKI+iobpOysQfacwtbQDBTz3sa9sAHH10S9dczfyKE7GBD94+X4+Y/f9awkFtjxbQZUeSZiIYMr/gwdIQnavFeLB3ruPPz9NjMOU7h7dHl+iXauY96XwYdB8uzGhEQX3GDLS3vWmwlaWQFwk4AJ9d8Z9L06myAJwoiE1d5MsAc4NzPxRL8LySyE7WVPCaVnpEg3+QRLBSm4jVLphNAHALY02jMDq0GBZzcrBmiZBXms2Yx5XduNEOPYwJspKe5LA/GVJg9+jy5dA+h5ipQ8q3sYGSuAqpMdGeuVg3MFngo/0a3UlrIqdGyOvQ0wrAfBQNdnfybCMCpeWu5jOY94uBxgqPS18xHrCKxH9T2N5YaaSu+h8K74kBzKDTBAtTxWfgqgxwl6rKep7cpFdkdkE9gsj+yTJ3RAc7ougnA/uMkK2vMqLNs6HiM2J/8FPpEJeWh9nvfVBuzRTlTb3sW2rYLirQxeGETVDEPfza3VZG+7d7rzPtSz1t/KlE58a64NIKiylMdVFyDR2OEyQzkJfHEdWY4QiAvOzTd5ZD2UZJfrPAJnsdCYT7JYhi0Mnr/RSmmcH0yP0LtrgJaDY/4NAnSkJ3q6y3Xrnl7Vrf60tuKDZT2dk/GHYRaOm9Nes9UohycfNPJgyQMnN1QPaOW9dDnfnGcGiPzdhG4POGZw6vkRUFzTpihu7AzGctk9fuR68ad38tTxN/mmzipVUV8HmnMIeabZoPMhtdteW/TyD3lk3l/DqwBo0T/8s6G1I2R8v5BJ+DxZyZ/SUTosLPl7oqUHQPNzz6InEKuwF2lWEn/V+MGOwTc5VD7xwRe/DSa1myv6NfHd4pn/P1OedhBl4bzKe5lGyDSWfYjT1ECfL09XsPL4qlgjK01yda5dowl+vXcR6RGUfB5dlbKHMh5lWYBpqGOz5LcexmJtHOs+Rutet5G21/XfFNZV8EtX74CeBjyeD5CxjJ1PvP5UYcn9BesEB7DjeW1+Iw9j4LmcZsjpDJmXssx+rp9zPUVdx6bWG2S0niAXW3Y2UaFIbpFqGWtqz7yyAzTrpJe35UXbQlF/1zuv+aS+3wpT3/kVfylPtj42q3h8Vr9ZCvoqYMAsthUiT/p4wljHXNszmOtX6fQVBG3fRQIZW74oiQWqh3rB8AlizrdVOI4pyyDXc48IyivIjp6f283kO7IhyquVnnF6LlcpOuuz+ufplfIRl0HwCeZ144/SZZ2/wQBJp9r3PT0NNL2QcQiPFy6rhyE2JMv2XdbLPHG7RXjyQeN1TLZnfIAlg8c98JP3Ptp3LvMmBM8bVTNN/llBBs8WMmDNYK47s+mk65XLfwbieuC6l79/7ywpGWC+jr8tsmW0rd8mpPbt8ZED88F+h3bjgduhFem5v+tYUYG20TocfLkJGGQ0ZsKKv5NyYsXQ1SxEt2fVEdROvimtqpDtbl/iJ59QhcYTl7rwdWziinzThpX3W8sAqO24baX5OAVaf7Il1KW+G5rFyK+3q1fgufIYhnRLSc17pomZGnBQt7CJgdaV6ndeWr+pdbG9jsOi1U8j2j3QvdCbmNwQpmnBi1f3ML0+4NG5Hc0+P6qHZLRZN6UefpFlrbik9AUh2afDUKyP4wCdksVkqYdm6ph0J9l+Al5ilxpSfaytViVLbVKE1AfYuTu7aMp7YZuj7bjEzL4Urf/6dgqpcRxcoH06lmjjy8vM4qT7PMkVXsLkMSvYPvevSZ+kKGGyniNkoCvo/JYmA0Lds8ywuK0vbK4h9E/Ky8CvUPoQrpGBPZltfS3XR7n9iO9BBrLsVGwbkVYb2OtFNloEmjtALch7+r2ZPJmeoD6/0X8pfU/HW2CXOU4qlcn6rbdCyjrrlrLnzQEa2ZybAUYPqW9mDdg2Iqfh5RhOxw3KYKSb5zUWzXxiu0cbz1z2Du5kHvQO8XiZqTOz0u+B0V3a9frvOY0BZY6nCj7dFwTxBtQOsb17+ffa1wc7L8mvO32hMxHIoNLozY6MS+Tt7+xHK5Sp9If2yWV6vCYg3eJXQdHmSi8FNodV0HziORhb6VBBLTf4xUtCy/PM/TVZ7cPJae5vY9oXbO/mGcHVDlD2Jw5STkwvc7GAVX7KOLYDMvXAhl0vJ9MIPYyQaSrLs/XUry71cM25prs4Fsvj6Qy9uKhxB6z3jwUcC4pLGq33US8L1sNQfDOuWpaGx7JMuh6wHwzwvAHQeP94xidfeQrjI2CeR+BRPT1+rnnMUuhbtd4MUwHhINWyWE5K62EsLnhE6r3aFSDW/qXjUOpWCGx+DnnVxKy6vuc0LaHx9+6kK8oDP5BEB1z4czOBSbKpnLZuYyD4ZbSodgDKxYrEoabYgssOpgEQTk23OtlLeu55Kz3PiEha3A34sx8doCDtXVver892J932nie1/EkyDUyzxvRhckfJ+Ee3DimfDSBmXcEgSGIc51Neyk4gMi8Ls+zcyHqiw+5gvwns8piw+vR0CLSjpzp6O5fRA5d5/OR8LV7v3Aa/u7aPtPDkg0ZmqgHIDGAG2oS/UdjYMrj3B8Q9hnnGEZaWU+Pz/sEeqM2NbGkynflkdFbKHHePV6y8M7iz9LsDoRMnx+O0vaX1PNB8Q7DGAe/1uWamlfNlPlhaC2Zt4lkg9xfmUa/OnF9YkuoJs5SXWbLsGW+SVo6XgKE/5rZqtJqVrFlq6ntteURlZ+3enosJz/qMFXRznZOr1eEXEPqsagVwtc+qWaCAAvRE2uley4cnRU6zVYf2R1bLVzn4QtYg4que52INFECWpVpHUfwCDqODSAlXForfFlOsblauNt4B7ugbUq7sk3mF6A2WRuPLG9hb9MFn/jOGccV6AJbzALv2ZTgBYy1rOilEAZ0Egy2rS+XRYSq0Wh8YxMFeWb5OSmxd4pB2Z9HEW7M8GvB310Vcr45Muen3MBTe00TGc1O6erB+h01qSJZkCyQ7+bZ8snHKD4RlfRomNfZsbcOTh2yrSPzuP3Xzyp93vnZXCpgmqI99T0JXPzb6CMCEQ4r8XBovs9wJwJK/ZkDXqUMXfBlxxMCsv92iTXKwV55yXmgy+Sb9t5dvNqAwbTmPYECgZ9cBwayns97pYRF+nvPcK4d/c/49i+VOePJBowVjWp79DsMWsFno+V1k5lt6Bhhc3m75Ox2CaeNDF8FiKf26AFtwkwV6Vrr51FX2CdWrRxeEEi3X8dDpT0tWwfqQhMm6JIWT6eJBbr8TrUDjeR4sJbNWtmrbn8ZlMTDgPHaVoYEtje96913neonVr9K0iZeemaBma6zX3/ie6gs0KwsrORfIRm7JQ6pFT6ne3SVnr0Zrb19WJN75kjQreKBZH7k/2knn3kRm1XK6ealucSZeckY7lW/gdFmaG5QKPPTq5D4boVqtjagHM6ScIhaUW1TqOBejz3wcSjv8Mr1+LhY8ADKXut3q5DS1zW3CB48vYnk8YblUTBcLdAReXE9YHqxY6s2HKsA6FivjehgrvQNwPGC5GItPycMAmVfoNBSwaEDI+mAFHKqVr8PYDgqd5wawmfeDtGsEuVoBZOn2JKi96lne6/aDctK9TBL4WkBz07S5hlDT9gnVaD1MQ1SkWersEE2wyPPk1sGfAQPKL+WJDA69bGlpGK/wZDfwkPLIlrQgFtvYD/sztUNgKCC9FqIv1CEDpL4siERZ+lBRbBlTf2/OFLAe7sS3PN1bhqZ8dnSF5cl6ILvL6RlQelZz/twzuhhNrI9z+p6+DsCP0htO2AssN4M1FC3vW4YnHzQG5UpgsQe4MrjpgSj+zUoPiHsOe8qUO0Cv3Cw8e502570HTmPB2zjcAU2xAggWsRzPAN+Gf0RT7ny9GUz3Sj0rOwHQvIR+m87dy7vLM6LfaM/8C65BLH56vwHSQ4sbrIba3nVdLlQhZPvxnI4sVINm4EpSn5FEc647grXG0weBjhjXlEdV9r50F+RYVeZaXe5UnvoBht4Ex5Q0LSeWttYGPPg0M5HbrJMl79YElY/TVN3zcP80vkXl5KdaRcqhkGny3xjHss/vXA+GGB+XpVoW13pgpNI+DuW3NfOA2/lpfAPhUiZAFIfXBA8uTpjunTGrAGtpp/FxOYgjq2J6OBeL51W1sBqtBnrnJZxeNr7q4VC67sWh3D99OLiPSr00ZIo2Lsw9ilI+1kbmcocnkvadxvnG5yIQlbC0T7vXWZM8vREkcvNLBXXC8ddaHfVn29XUNL4ygKJh28YPAyenkL5mnbTG911gJlWkkNykV40++8cVyUg0VDCJF9u7Sozjdtyk15iO6xji5DoRTSvJs5yHpvIkfzZZHm7V6QU2xORnmTa2yu65cTMaM+hlXc+4wULe58s0bAwzCbNkOd/ToxnnWNw3EJ580JjBW/YPlkFY7/te3FxOBp08+PMMhDtEb4bA728qc6++GYzm91wWUoezvDd7NNZO2s7vDVDULT+ZRhceWQCn+F2fYiRY9sC6bUFohG5pCnXtgBunhUFfp866VYSA/c7CuZXTLH+mjBDT+8yeLdVJITAvTbjb0q1XixQas5xd4FjWQvFrmQb+TJGyWx2th0Wkgkr/M1BmfO716ywA7b2BvpncWdkKgdFYAYlIjc9+HifafgLUAzN1SXo+l/T37jUFczxATycA1YE4XwdX+SpXZ8hhKvdQA6V/Kfx09zra2AXW41RYeJvJ/BuT3xiPC8bHiufvvYKn7l3h2UEgK6BjBY3aXAD5snldkh7mSJBKdVZu90yLlL2M5xny6FQ+z2fI6VRA54l8CA0DdF0c/HvbKOrytDYXPL19vgxugK1So8niZltETRfcO3HW1bLMy89+JaZNhNDyitdkxhuNAtj0PlE+2+GwNFEOuCwDE44AkvkctxQm/h1x72sdoxEYm8W+RgiyDn0wFCahlJevVuT9gpTWtvdkoWLyh+NmOdz9bo8SPU5q1nNGftZ3JYGytS7THrasZVmedTjJYSAaRTLg39SB6LP8cjv0zhns4Y6OK6rAE3ueV/vSBCuUdYvw5INGDqr9TaJ7wI3TAdGqZOl6wC4DHnP4vddo14FRyyP/3gNnwNYal4Hq5vtAeyiIR+Ul0azbAcD12Xtmv/dmNIEH13TsHsAPwDgLEtcQnfJo2ZJnsV0QnHhRMonPna4qJHtCea+Na1tsHQGzoKI8vO1ISBsYDPVgAU4Ko6tESprgX60qVT9MYFZFegYUZRwsQ3z4oCpyXVa62m+I7ZYFl1kWu2Ot/h7H5qDbeOU++KQefKnKdpzKnq5qPRJfdq6nqavlQHkvHi+JS13WXsq2BbU48wKdprLcC3j5vFw9zKUO0yMFcvN3xsMbOQjjNR+BB+MVfstTHy/XC06K+bKAR6zAchTooS7JT2NloWI9FqA7LIV3KoBeHNzdkPlxxDg2i+EwuHNvqWNOzLflMKI5bZcmb022WBvUuntcEZjPy/IqyphgoWa+Seljds0g8zPfDx2AptL72qd8v66Xh4abal/Nd0BHX4TwrRw5fSs4/0xAqBQW43mftwM56vSmiHB5IdiXQSYrrHy/ohQka7Q9y0RLygtwa29lAlygBMCnCOUHnlA8yfHT+2pVDfopTIo5Xc4r6QKrb57c783cerpn01698dvRKb3zD1xG3qaTgWlPn/b0Y8YnGVy+AbBo4c0DGjMDe6AG2DI5P8vAkRuWQ1jaTg2dAV8PiPUaM4OnPRDGaTfAKpUDlIHO9Aalvm550hPiJqQybQy4OX7P3UYASFyflDYA32G/fgFIEj9coFq70Cw0A9hNHoaw+LfRbnmuoUgWsF2B5OWZUiCBqJZG4jtmE4MpJo0fUHs7aGLSFMXy5rNSkBJNoFARnoUbNWy/YKgb0onq1E4ZRALVF2LdP0cHIMqS9Vj3VKICFkCmejT5UD7VLApmXSsPvcnd4iUo/h3Pc9nXWK8klLovT46HYqWrjq/lfIZnIgJZ1+IEe1kK4LLr9wYU/42AW/qu3tHxs/pphsdarHyf89zL0FHwXx4/h0+enyosnRTzg0KDaPk0y6cCWI7FOboOKE6/5xV6HH0ZWc51KXtZIesKmZcClCtYLns3tYBMWnbVdWlbCmycDgN8crYubTKg0aK3O+nmCYny1YC077C+t2Vtn8TUPpwPvHjf9rK5aJNF2AzVANQCcItyq1jVe6CL6upX0cH7pcsT/56CWMHa8t4AB45LD1jeCT+3rTRoMs+r1KHB47W4ygYHBooepcMIyd9JPgeLZa4UyddGELqrL7sNkAjRHH9HB/GydNZDrC+VeVvzy/ra9eSwPcC6Nxbsd/7M+jRPwnPavd+3DG8e0LhZMugANgaT+TvH6QHPXkNzg/Y6RHdQ7pR5E0jsmar5L+/X65WdwWGPF7mOHm9HAeZ9nqrtdCyXkdshAFEbEEOHbsUGVPr3rJSszN6BJd0eOOJDK6E9dg6/5ANVvh+JBeFO8EMs9LdxD8FfCWQyfd7X6L0poirwdVk6Qts+G518stpOnfreL3uWZ65OWklbTkknMUMHs4IVifMyq5T1a3P54tf/rQXkcRsbQKSbXEK+yWeenZTWaSwHaYahgD9Fu3FmWQsIXNZ2oljRDtEMUpx411tVtC5FD6cVy0W1SK7FT+Nv+5xfxU1B3/7cjXEA4BNrqdvzFy9jvg88ng84r7Ykr9DDWkDjUgHs0Gg2Xo2nFes0YDmOWA8j1qnclmO3wOg4Vp+NYwR7c+GBrHSgyfhvJ7ABGvs0iaJVF/ermS0tvT4FNKBI/V1IZuV9jJamPUQ7CV37cbsRqKXj22j4hpiEDRGBEVehXa/p9bYybIyZdcxWPNhKGAlq8jXwCZ3v0n5nkVzln5+idssbMycDaa4YVSYcuOPPBLpcDPXkGNUrgNUsmKS93xxYzekyvSR3w97QnhxO+odDntDn/sqgM+CKW+hyvhJ4bz9jfpfLzRPuDGb5e0+3Z3B5Q3jzgMbrQCAAnxVz2Ns8yt979yXnTtTbDGtlBisbOgo4dYRclg2W3Mk4bUjTKSd3qN6MpBd/R7DHmRcBQONXrstm4Jki6tDTBftZmHSCgcDMBw55gIXBy8A0AWF+3n6kwZgl+R6tJHB3ae0ISlOi40gCf6cMkY5SQFSA9p3q19sv1nu2e9rdFPTc9sL5dYKb8WP9qyruQQgwsrKofyPlMU4xL21uhyB13yOknbie7aBMSS/j4BMbnefqZ7G4zcHhEJW7CJbL6utxWTE8OgGqWC9GyJkOmwjwlQ/+65YvKfyvf/zf3hgHAF5dLwEAn3P4FFQUn3P/Jbz38lMAgGFQyCrQEfXUtGAdgPPTB8wPDtBDcd69HIo19fxUAYzzvaFYRUdpoNl4uq7B2gjAl+GhqEvYFUywC7FB2n5G69PVdZHwXlNuo7QHy/2E0kSkPC/jWTv3U2/25wJ++l+GmobrpzVfpT5Nci/euOI5cu6tL27AGhJ9Creu8aneDEiz/OvdWMJj1itih5HoAIrXgydp19SlV0gY61mWZXqtPllPkEwLE2XTVUY3lWOrF8FXLwkqoTxcNphetK9GE9EZ5Aza83DQRel3R/fkVbmME3o6xctGzG+jV+k56+Cclt+xzsmnrTnkE9TX6c6c9NYxf6OGHiDiPz72ziebmam5sQIwW/vLazbD5lmCpe3R5WmuAUpAPMjjwCVZxPY6IccFYn2zW54MQgMIHGJd92Y/AbwSv3Kdwu80kBmcKVsl6H1vMLkgYiEl9EkCZnfgUFrn8droE8ozCC2rh33tAUUSxMwfe+fZrK3MrJHy5AS04duL6pSZX2VdYO8UMFDgS4DeFn3FXEhuy4Fu/ekcflHuU0ADlVyHhdq7jieZyC2MKfPzGVCF2jKz9RdTzstSDuhMU+3C4pYxv1KQebquxcp4mMqhl6mcGtZxKL4b/WYTxXBaGzCqeeiA4sqmZnd+a1qa5vAGBLaFC5nxifWMp4Yz1gvgt937FRzljBWKcVyho2I4AbIqxpNiPGvZXynAcFogS/HfOMwrDq8tmF4/Y3q0lnczyQWrZ91nqoLqCBwO4t1aZ2GaqowA3Ops4HKpt+fUawhZdrKrHC9fhCzcBewFZ98MIIGW3p7bKXF7pxzH+I+2faLSHPZA2vDmNKret+JSN8k5oQzzRD4H66fhAQOdREwe1iGvLPdXGvpUz1CW1cPcCyn9WbHEiN0+y3ohVG5LsNU5xDP9wvlR1ZHaLvBHSI+tlUx7T3l3A+mZDUOt/xIotLg9K3nQ40NsD9ZnezqQ+1DP4wTrHt5SdV1+ud/t0XqL8OSDRjux1wM/PZBlISu0Xtg0skZQlxVmBqBcHh/Q2aPV4uU9hT1a/PkQ31t+AcjSDJZptLI2eVPclsl+3bh+vTgMTnPIPPHlsCSI9wBjdgiefWQGYcFZDAhl5AnBhh87AzfwSROfjCcs6AiAOm/y8i7/MKEr7dNBp8Y0vf6alWIKxcdiu2vabpfZU4SmvGWatic82bejbJcaPfgJ3PrbDgDU9lR3uI0CaMRc/0g9OT3V/ZDlT7XEKwCi/g20h28Ym3ud7M/NJ5flU+al3XYClFtfHp08rd/tPEjZSzgJsCre/pbX+gxO/LtNeGk94fF6wP/j1Q/g7cMBEMU7xhHvmV7BK+sZz1xe4cEzjzE9Ln1DBRgfLWFZWcdC12qnqqXsu1SR4lpopi0My1p8YY61o3gfoLDUu6iH2gZ24l2wf4BwGDZW6XwSP6SxCQMAvyuaQSXQ+ozItl8bfdg+55PHwR8p55lAHZ9mbkOWwEnNi8e8HdiJLoW0vcvj1jNPcoFwkssfoUF4bfoAAJCwSURBVLiVx+1ObCrLALzGjOzu7XY3tnAhkZRAu+aH2JWHQQ4hfmKP5yZfUxFBDqW/CjzD5QXKPOI8+GeWtayvhvg+yG7t9/NgSIC3y66hgt/l31kHZf6yLOX3Wedm7OP6/pqJLYUnHzQyo3MD9WZ/vTg9ILB3ApTLYiDYex9QPglSe8ZClZ/1Tlj2HHwyuMqnsdgFjV2RlDtUbx8oL82ypcxnYTubek3AWpzM495MyAa01WlIS2bMNx/QLFgT4N0bQJv25Ty0fc++LHtAN4NXVyyyH8fBJG2c9nedeK6cSPgG+d7prz0edwPVF3DrjwS+YdMGG796nOO6+n66vlWm+XMMtIY2qiA+nRoNS5OWxscdSrp66rmAS1sCXSDD2CxpgINTPz18uqonpasVa6rj0Q45VGAk1WqmhxE4TMA0QBatewQF63HAcZyxCdfw7Lrw81fvxuVwxicePQAADA9mjBAcZcWvLfdxGGaoCoYzoMYHoJzmPq/QoVhAh2XFeFownEs9hvPqh2C8D/GJ9HEoB2iO5SpGc2YOoIBuVtJA5VU5bNROw2t7ly2UlhfLnXyIxYA+Tzoq0HSXOgDdJwzfx8iWTDFAZXULQ54ASsBqEXA2cLtBP/473KykLW7o7zXDVs8O0AqTyA3HWn9ngKUagTePKwOZIghWOa5zqGz9ztgsA58gK6XF58my6wMgLJ9zwf4oy8nMm1RWCEplGwm8MtIZewbyMq0ux9V51erXWTkzPdPbh8hx7Dfr+D0w2Euf82JAamMo75PMIev7W4QnHzQCkekZqAHbJV9O15s98O/r9g1wo1lcLjd/z/Tx+zAjuGG5mzsQg81QTofuDKxyHVkoAG3AhHqwcEsALYO5zOsNH5PQ2AgZSuvCkvZF9QZrprfHA/b7aFaVUHdtz3Jb3ui+gZ6FPUrEm27gePxXn4VH6R0DySCQm4D2GysSEGVHy2xxLKSuLT+PE/uZHyyw/WdK+9OofTY+HLObCb7OD6hW8JZP8KW3lnun/e7p2helnuQVXz6texYnAzZlP6hcncvJ6WmCGPCpdzJjGKCXF+309ThA63V8cl7KwZHDiPVYeLtOguVywB99y3/sNGmnX94ifPz0NJ6SE67OZXn4weUJAPDccMRLy3284+I1XJ0mjCcFBpQ9jYehWgpRTlQDxbI4lf2N5TnSPm6Ues9L+Xt8BpYFw6uPS3yzRq4L/NYfVXLPI2VCuqrf5mJWS4hE/5kdeRBOR9u7Zd3uccx7aA3QKPVZQTicEq4etDTAjiWy0wiCBIBs7Bjd1L+t7CQiQwFBtJa4bZn4GkJYxBgIjA+IZvF+H8d5oTdcPchyhGWGJzVekmwM+9UpvqHusGcV6Mv7pCM27zKfc5D2d60s7chm73+MD1I+oZ+m9jCZZvVk7LAH2jJ+6I2FHoDk5zy57i2X3zbcUh69OUBjmOEkZc+NnMFlL3ADAf3l6AzcmA7+3PueO0MGP3uAhwVwjt+bSfTqsPe+Z5nLFjcGrtx5c7m9mWE4hZlApYPcAeG0WQ8wlwfx1Hbgxw6Q5Dp5fjvgnJegcggyvgPw9gB7SExlhNe5T5KAzCErBi6iI8B4qc+zNqWcPotCS6COaGOQaC5PImmJXj9EgahYGEACzS+j1cGBIlkqPR+zYlV+z3NxCWN9QFe/y1jmxU9ry/Hg5euyBmsazu0gj9ZlWBW4FU2rWx4VYK1LvRBgvsRnNNwbz7jSEfPjwo8PPP1xf/fzr74H94YTRLTeK43qeqewQip9Og3FmfdcTlBDUE9Z13un7e84lb2cBvDGEXpRDwO5a53Cc7V9igDcqmOW4Jo2yKhVt32654an9he32uW7oLX1KXe1Uw9PhP2LdUj0Tln7fdT2W6gMSZ+g/s/D1IbDWia3gSb6hKAdWDPgBV46L/3al4kdYEkQJYFP+Xmm2cez0icQiN9gISrTQLCP9QzKkoy1cl0GkswxUO3MS/3A6htkVagIAKGT7yxPOqCKDRYBLO7oAM8qyW37DPq5s2eR+bQjI6/FBznsAcheyLo/55H1ZtahtwhvHtAoudPWsGddY4tGBmuWzt7z7x5oy+CNO1CvY+XOtdfZMjjdS9frDHt0hg46xHx5JsUDsVdPLifTzsKrNxvqlQmg7QHcGYhenuWbBnRJ1OJy27KvsT3aA5iTGNfpoX2JvWV4r5/RwgKIaaS6Sf3n71mI1jKDkuDlYhLgzjci3T+1fmgqJwZWpv6915fo++aAQ+6vxvvNQTT6TeAE41hP99oYpb5iYBMoB1zMT6AraS3+FNeyTGttoSQb9DD5pKO42ym3wgiBIpnXeuBDgPMMnSYs94rFcbkYMc6KdQKWg2C+vEHQv8HwyvkSH5ufgwyFlncfXvJ3L734AL/48O1YziNkVogqxivFehDoJFgvRqzHEToI1osBy+WE9ThgvZjKUvphxErWRwAFMB5qXQeBXkzQcJIdge/eHgbiszWFT0dn2ctjOijnCPTYjRM7l3brobY7qfmKwM2ERVue4XG2DKYhsXXgzeOtyIa8N5Pz9NPbJEPCUjZka2kUi0+0GZ/snY+hlD1PqMPEl+RDBnI+0DkPYgrv57N4AZj2dKpQlRjA8F5ilos1TwG5C0LTBQxqlemnsGZwy++38oo6S+yn/My/r/3nN+monjzMcXL5NwG7XCbjHDbKZJ37BgAj8GYBjTdZEve+A/3OAmytc3uMv242kYFpFqLXzSp6YMues3k8d7YecO3RVjKrz7musjW779HW40lPKdhzT5s2G4c8OgN5A/yb4A55ZL6ytczABVIcBpJ2iMLBIQce2CuC0N2bKQZBbsqV2syFouXFWow+fa+OetztKVQuj5SOkCLNiobf2XNpS8HmvmRX4KS+70vdPSHJwdplSRO26qmgXO02Uj200GauOYwnDljQTlyLVOfdYzkFXQgrt70Iyinsah2Tw8HBh05TWYo+z4UxduCn7mmUZcF4ruBdUCyQCqxH4PB5D/franV7A0EVuDeccLw8AwA+cIj7JadhBUShdU/lMAOyGq0rxtfP5QDPuYIaav/1MGA9DJjvT5jvH7Acx7Lcfih7GZfjiPmyWCGXe4cgC9jCHDwdZPkzEthQbRZjHp8bcFeBIqUNExwty5U8QfH7z1V9OGZwKGO77tL7ERDGiwPUDQBLgE7RP5Rj73P+Xtf6QAlcArTv0eRI5EfkT83Dt7yQ/HFwJv20TqM0usKkNAPAmpc9snGnIBnaAWehWKbFeB+Y39LX/uMO+00HtYq3eMi0Gk2dsvN3BtO3BWeWRw9D8EQ392nzV2rxWS/yb94u0jkY1tUtVlZeqga2h4L39PE14c0BGoEolPZ+A32B1fNp1HPEyfnY973O1CuzFz+DyD1wmhvffjuAHNvvHpDcywtIAKm+4wMxvVkRv+O6MC1cdmiLzrIHl78Bi0OKn8Da3qd/v6bszPt80CeHHuj178Qzrgf4tym4jcZpysXShDhWD1IOnEZTPAOSQFtO42W/TdYSrDtm0dlYaKjv+LL0ODaFPncOhKDkH2fGzHe0U9AoSlVtryGwPbC1LOXuaOaXx1Hg8QkOHsWcTBfQYRYgPc/FmlkPYsj53PZHHqd6UrouS5vVrSr74awYTgqdyn7C/+u7f75f58a069+ncG+c8fz4Cp69fNzJS/DK6QK6lj2M7tx7VferuF5OFRwK1lHoxhiUNGbxWgqgWyc7CV63CdS8NACfytt6ulmmqbThOPjJcwjixMhpTjzIsoxlyrz4xCMfhGnAAuBl5rZkTTLKiqrtqyQHhMc8qB+7aEkyS+DjqTiHV/jkSjrxvW7pewBtNk5D4xKwaYEd7oc4DKI2gK2nQ+wzLZVzOi+D41s9qC4bdOwREx1UV5GUtn43nmvn2UY/ZPlPPAiVtDzzfth07sA+q4wM+oKNBFknZDm/AYUpzU0TaSe5xuPtOFlfWxn5PAbTxeOqp4OvCZ9x0Pg93/M9+OIv/mI8/fTTeOc734k/9If+EP79v//3Ic43fuM3gpcORARf+qVfGuJcXV3hW77lW/D2t78dDx48wB/4A38Av/qrN9+o0A09sHXd7zy4VeP7DDiBfX9KnL+964GXHK8Xdw+E9g7YAE0484DmmUYP6GYhvTsL6Qh576Scb4fP6PAvWxB5QHJdenxhIZH3PPaA+d5AyaetQ3UzmpL0aWXyfh37OnR40BN2qT5Z0OUN/73+FegNUr1E4/1ESmkF8LttAznaFFrNlw8UyB6/WKmTMpdD2zPoZWssE0DbC8d1XuYCXG3y432tgohpgl8zaFYv1QKYziWtjFO9llCqn8FGX1lyXCHzXA5QWBfxvOAuX8pydbNUQtWXdYfTUlTVACxHfMbDr776LF7VC3zuvRe3L0VxdTpgeDRgOZYKDAvcBZDUAz2yaAGFKOwbzivGRwuGufhvNMAoizpItHpr9XFZHIEPbTuA7cEbh+DCxq+EDHSCxiC2fbnXn01J0thlcMgTGBmG9qz2MTuUxYe7gqFqKEBP617LZoGEDyEHgor4LssTrWNH7YfFKxUO/gM15QEep8RHH7MMgog/QT8Rz0IFYMRvZbzLMHK7E4CXRpp7SxNWfs8y6d+z3iNg5zTn+q2Nbk7m5bOe8YFL9LAe65VfP7v71LXtw8yu2Fgv9yY6FucmcLaXR/ClTOlYj1v8DAid7lROD8S+gSDavdLh0w+/7/f9PnzDN3wDvviLvxjzPOM7v/M78ZGPfAS/8Au/gAcPiouIb/zGb8R//a//FT/4gz/o6Y7HI9761rf67z/1p/4U/vE//sf4oR/6IbztbW/Dt3/7t+NTn/oUPvzhD2PkvQ074ZVXXsGzzz6Lr8AfxCSHz2QV78JduAt34S7chbtwF56YMOsZP43/DS+//DKeeeaZ3XjT7ptPM/yTf/JPwu8f/MEfxDvf+U58+MMfxu/6Xb/Ln19cXOD555/v5vHyyy/jB37gB/C3//bfxld91VcBAH7kR34E733ve/GTP/mT+L2/9/d+psm+C3fhLtyFu3AX7sJduAvXhM84aMzh5ZdfBoBgRQSAn/7pn8Y73/lOPPfcc/jyL/9y/IW/8Bfwzne+EwDw4Q9/GOfzGV/91V/t8d/znvfggx/8IH72Z3+2Cxqvrq5wdXXlv1955ZXyhf3s8aZSC3vPgWYe7i5lpuXG6wy2ls/QHAXvLoNyuI626973zNaZHgvZp5Qv4ZIZvlfvvTrv8Yjf8RLEupDpXiJ/ekvo120j6JXvv6XVB6BlZGzj+3J7ba9My16aHg2btvCE9FuJ5/Se9zKGZSIOneUapbx5mUpznqgru3ajCmUvqHv8zDE2fGnPyQN8OU+G4vPQ9i92wzRFf4uqZSmZXWcMQ4lzOLSxF07mru3kNO3r8ZtCrk7l91h8L+rjq/L78qLsc6zX/cnFRW1jafuVbNlVFXKoonGem4NqW+o+ThBFOWU9l/4ry4Ll6XuY742+J/Cl/17wBZ/zn/HVT33MWfC3v/fdfd7U8L9++8eufQ8A/7df+u34ms/5CB6uR/yPF+2Qzf/r8XP4Vx/9AJ5+12t4+MtP4/CKYpxRDr2cFMvFgPG0QmbFehgwzK1vD+fSB3WQujy90qpkWV6VVcu91SIYHp2hxxHD61elj6jWsUx7RxVb+Wm+Pe0GH9/3OsRT8EDcYrCRHWi+IS2kMRiWoem5b7EAQr/25WxfdS3+PnuLcZu4vcArw/m5jcXN2M6Jchy0974/vW05KePR2hWUZ5Ix3TxT/CwQuu9zBXNaFjQ79fCkST5afhsXZZ36+BJ1Ly7o+V7dEiYwerphT0/V51kv9/SD65jOoVJeZs5pbgrX6ete+fxMBiCf7+yEz+pBGFXFt33bt+F3/s7fiQ9+8IP+/Gu+5mvwd/7O38FP/dRP4Xu/93vxcz/3c/if/+f/2UHfCy+8gOPxiLe85S0hv3e961144YUXumV9z/d8D5599ln/e+9732tENFCSwSLQnm8cxKaG2+w5GDrPUsNkULPZdHtDJzChugfOQsekU1ocnw++7JXpQn2ItGZ/iR5/50RYr24ZoIZBpIm2POBTXt4mvJGeFJL9zu2s2gbzhheyTWMnbzebygMTYl1YMW76WWeQGugB96fshqPyKAvSrrDvhAoIETaRI8pIRXQvwkWlckyxuqLukLDZx8i85kMwWWDas2WhCQzSb2lAwngXTrRr2YdnPveWFX5vMu+pNEA5n4tzb0XZh2cA0LuSNPIU0GPxTyiKeqgExZchUMGWVoC2+n7B33H/l/fb59MM07TgtxxmPDfGU9nvmF6BPpgxDmvxzzgWH5HmL3I5oO1jRHm+HKWcrK6AcT023q/j4A7LZdV6I05NPxU3PSWjenBinODg0fqPSPPPyPcxD9L2no7ktcAOz4DS9ybBQj5ASVZv7p7uyLu2T7eOD++vdR/jWE8De9+1cWTxKd8khjzUvLs3JYVx4VR1wA47rc9Ai2Q2Jdneq01ySYbmxkcT0b2bTfw3g0MSHhIKiu9cVjWd165dzHHSZ8jP6pjrb7Rx+Yj8CBNqqoPpHk10GA1ZR2z+OodYGEiavMqYYq8MyyP15f3y01jYo9viZJCYJ2JvMHxWLY3f/M3fjH/7b/8tfuZnfiY8/6N/9I/69w9+8IP4Hb/jd+B973sffuzHfgxf93Vft5tf8OCfwnd8x3fg277t2/z3K6+8EoGjMal3g8uecLLQA07rsp0l9GYP+V2eMWelGdxWdBo2dxTPZ6eDdmbo/jvHsY2+e9Y+T5tmU+Gd8XJAAGo5zh59Hl86gri2kVknAYrDwowB3065/r7TTsh9wPhsysxcq2R6hfKVls5PJXcEn8fjfrkjpPm5AO7XxWfTuR7tNgzmr4i5Jen1CSHStVkualnMhpJE/TmAeq0fGrjcgGXiq6BZnHp9P6dxXpIirbzW81wsiodD8c+4Vofddo3gMECGsVhDl/punPxEuE5TkS2rolyjUkHmRFcNKorj68qr+f4BhxcfllPUUwFM4+OlAMhF8b/85n+Ntw6f+ZMw94/F1c4r63189HxylzsvL/cACE7zBAyoFkNgHYFxBca58HE4r9BJMV4tUAN6qjg/fajAd8BwWotfx8up3HJjALx2J5xnDBU4+/3K2q7ug6D1+2WGTIfyWkracD2htav1i4VkGclXsyyqFv+T5bHUaFqGZO/EqGeltf+TlZBOVNtzx0LUTy2+7k5s98vjMVUyz6s6lU9JJABoB1LQPpAngWHVAiG+iEBpxcg8JWwI9pUlSy/pdyCglec61QuMWbuMJWflufwKZuMpdZa5pO9C+/bkqdHBeTD9GiehOWR52PutqaFYZ/SwRNZ3G9/OdSz4jUq9g5P0nevFwLV3UDIfkt2Tq1yHG8JnzdL4Ld/yLfhH/+gf4Z//83+Oz/3cz7027rvf/W68733vw0c/+lEAwPPPP4/T6YQXX3wxxPv4xz+Od73rXd08Li4u8Mwzz4S/buih897tIRwyage2gDGfBg2ATuOpvw1AQsyTy8jl5rps4qQOa+XtKW5+b7OoLTLY1qdXhoO6av3p0Zvr08vDOnAG8Jlnm98m+Dqz5lynm2gj4NXioOTvFlmK574ZLSIJPecNYhwG+wxQWYOYMA6A0QQ2EOjjugbNU+LZLRbtrlwS8KYcPJm6UvDr3DYn8Rrvwm0XEk+yxvqhtauBA7Mu5XEpQreOWN+qvLY7iHk5fFmqb0eQyx5UgKLQuZ6gPh7gE9BVi7udpYA9a0s9HLwZ9FiAE6Zi8bDl5/G8QsexAJhlARZ1C+Tjt0343PEG8cp97g2Ed9x7DQDwa+en8cunt2Gua0pnnXA4zoAo5gcrVIDlKFgPKFcIrorzgwHnBwX4zven4nZnGnB6+oB1BKQ2yXoY6olpqe54BMtxKH4a743Qy2N1CN4UngxDsyrab6CMAb+vey1xwiQLxQptIN940uOPgT37WScdZYnZTsG3KwIdVFaXSmwxlKG4WzJH3eYVgPsu+3hs4DjTkvs6vbc6hnEGGsMkRx1PUWSXGQq3eG50u8Q09qnaLLFOtw1waX91Yim+lasjy1z2cbkmI2yMwvNqtCR5zfmSfI13ZBOPmKE9nemyMulIz4OtlCzPO/orB5EYLwO+nnseSfH39LZhglJ5uL5gXZ11US5n78rATEdvCfw6YHpD+IyDRlXFN3/zN+Mf/IN/gJ/6qZ/C+9///hvTfPKTn8Sv/Mqv4N3vLvt9vuiLvgiHwwE/8RM/4XE+9rGP4ed//ufxZV/2ZZ8OUfuNmTtLr9HsO79jkMh7riz0Osx1DdabPVjozSAynQz6rAx+t5ldCQKIyrMZ7NDCeednGZzmztulvWOtzW0TwASBiAyQ2T0Pl+Htf82Gjb1ZIVtLeZYeBCCSgOEBanSketvNMVkw9omLZdmzoCg4ThXg/lneaXCWTcWyLA31aYrH/bZxlGG7/Ob7I53MNPZC/oDfR6wgIUe8qnsQw7WC40RjTqFm9Y8F1BskSj8PNMlQ9iz6UqhCp7FctQdAj8cCEEXK/kW7d7ou4+sw+G9Z13LN3nEqaYZyz/P56VsI4V6fu0VY1lZXxYBfOD0FAHjL+DrGccXrr11ieCxeH1mBYV4xnhXjY8WwVACylltr7N3hYV1WV2CYtbWJFBAJoLjZkVLHdax93v1vmqwpY0Xn2dvRb0Dhus5zvZO6yqd1iTxZ17ZtAEBvW4RbirmPSuuHzQejZavb5wZ4BJ6H920DQYK2jcPHTBtEmzurQ9tmPWDPGZjRz5wPjbHNPdsbubAZyKTDLD7JBYHLS2WdluW+Vv5rzcjahwBtqzNaPgy6NpNwLoMZy3VmWWr55fqarELMw9NTuVplDZexNw5Vt/H2JjJ7OnsPX2RDVV4BzQD1OvB5U8jpWc/eBJw74TMOGv/Mn/kz+JEf+RH86I/+KJ5++mm88MILeOGFF/Do0SMAwGuvvYYPfehD+Jf/8l/il37pl/DTP/3T+Nqv/Vq8/e1vxx/+w38YAPDss8/im77pm/Dt3/7t+Gf/7J/h3/ybf4M/8Sf+BL7wC7/QT1N/WqEHFnsonq2C2Rl2j9G9GVDuaD0QY99z2pwmACPdlp9nEbnx8+01JRICyOrRfRve9YRAL+51CvLa6/YyMON8mHc7oCQIzbx0lejfKzPsF13304TN1pkWE9apDVxbUb1BvNvbF7OhnfJxAarbPO2r0ieTAk7f/NyZoi1kNaG8uZe65u+HZtLYcMVkn/X+5wZirR7cl8qnCKWrVuWA0ad6vaCg3lNdXpZ7fqugnqbigPnqRHt7KghcFujlETiMkNNcrs/jg2LLWq7TO4zQcSjX8R2n6rNxBeYVw3mBToLzc3b39TXhDczuORzHshz9ydMDCFb84qN3AAB+9fxWHIYVMiiWByvWqVhF14NUZ9yCYV4xXBXFOV6tOLy+FtD4eMb02hnj4wXj1QLRCi6BslQ9iqcZziX9sNRl4lUh05T6gLQDSmM9ULZqOeDEk1J3/o1yqMj4bdcWLmvdYyj+FyzeDKhq+Wz1br/LWDALoye37xrzaAdlYhu5pXIkACsUPwMmooMIhb8wUGrxNiBzDxjwuNad50Kv2/WKAWB18+bn7bPd9Vz/8SUNmYYgzzxR21NJz7ZCqEOX5h8MDq2tUh6bMoQmlywPeY98J7AelpTOPvMy8DB04kuTQ/ab5Vw42LRDA+fFnxZn77el72EXC3sHGFP4jO9p/Ot//a8DAL7iK74iPP/BH/xBfOM3fiPGccRHPvIR/K2/9bfw0ksv4d3vfjd+9+/+3fj7f//v4+mnn/b43/d934dpmvD1X//1ePToEb7yK78SP/RDP3QrH42bwJa9jSVpB6CwZSPPDjKAzPn0rvuxsjMAtbJ6z69D/pw2W/nyDG5vqVgGQBcg72Hsxe3V12fhiV7bz+gDIHXYcHK5Q3NvoPVCVfjlO8/KqO5ZwAQwX+PkAxvI6VP79fY1BTqTQHc6WfikpXSz/Np+SU7jeTFNtc7DAPdCHQBtrbcLb1JGgUxuT8tfNlXn4u3mFF3r6dIl9vetjmx7kV3hMx/WutktW8cFdTmTlzk7e9aElbhU62TdxzhOJR8auzJW5952yGaegVWgl/VEtVlkT2fg4ghUSySA8mwc62EYlOVZ1aamzgWUfc3nfwQ3ht7E7Bbhuel1j/784WX8/+Z7hbR1wtsvX8d5GfD49XtYD4AsAlmA+d6AYVaoStl3OQqk3s6yVqvqsM6+H9NJtAM+50KvqGI8C+S0YD2OoQ4yDMA0Qk/nipnGMkmod3e7bPQT1Gu9dUch09jw0mxW3TT29ybI1L8wNqAvNR4fyLLlZj8sxWNW2+lj3zspEiyMvrfR+rwAed+gZVfG0LZNY970XGxbh9GYLORhTGcZ6T8oLsezCWAPGGhKR4Nd1yaHHHxTOZLjJtDHInjVZClNOjNM/mUbD0hAJ9e1E5/zc/lIRIWl+J3gddrb9iTx2d44zhiiWw729bV9ZvDHz7ks/uzRtsEvN/Chhs84aLzJV/i9e/fw4z/+4zfmc3l5ie///u/H93//938miIoN1QN7ewy3Dp2BJ7vPycLM/rLJmd2GsNDbu+6n1xFDnjvlhLpct7TN9Rk67oXqQMmAMdO0AaupfCFLkmrMM+fjM3Qa7EJ0cPwMxDYAPvGA3TMwrTuWiyBYAs8t805f15S3CxXLLuWXQexGmJAgCcKyKgDXefm9lZ/y2UA6aXStazu8EKrWFCo/a9ZEBAXIBw6gutkLGVyl+K0ta1P4PCMfAcjQ7h0+r2gHgOoGeldiWg5ZDAMwjNCpnP7FstZuJcCyQg8jZG5ufvRYnP8vlxOmlx4W66EI5HjAenkAzjXu2vqKDgPGx0t1TVP4sk4DhnMBSP/94YzPVnjf4ZMARjw7PcIHj4/x+voSAODxUurx4HjGld4DFFiPwPEVhY4A6uH15bLsS1wPQzmTMZY7qoGpLDkrIAqMj87QccByb8L4sHxfD2Nx1QP4YZQ2UVbo1VInEgvkIOUAzKOl9THu727Jpa0TDBbZKmNlDW0p1fqXruVeal3Xsl3A3OesGoa8skVKmksepT4a77OmNPW3DAYQ63c1IGRyCzQm6yNHw+WFYZfoGgdxr3HnN9MRClHBRhwxeGUA6fRwfhoOBDVQ2AOZgijLiV+ux6i+rmus7cWzAWSbR5it5mdAMEi0CmLLAH7GdUn0bcoFyeysCxLPhN5l/djDQb165jGU9x9K4lEPi+wBxp5+3ujIrA9uDp/x5en/ZkMWWGmm6qHHzN1G6Zi1Lb8MZKzB2cLSAzvcSTKg5b2TDPp4w/neLCTTzs97n5a/yNZsbTPWkJf95rwI8DDPNmXmAUdAd11aPXt1ykIL1M5Mi4G1zAMX+Cn0gHX5so3j7T20+vUEc6a9uzxU+cH+1BzYGk9ZCSUB0wthBk+Kkz8VCCCUSHHQS3Uxa8m2TvVn7jPUb2UYthOoPFaICBnrvdN2+nKQMmnjeOtarJ9LAy1lL2NZUtbjsZVnfeRwKPsTz/U0NQC9KMuneph8vMq8FJApKIdijmNZwq6HaLReHygA1uNY9/rdMnwaQntK4+E/vF6Wpz91uodHy4T/4ZlfwfDsyd+rAMtBMF8KzveKZXGx2xxH8SsCzcJYQKFiuZgKwLwQLPcPxeWOKtZ6leByHAufav8yl0W61L2My0rLdoBPDsy6Y14QrDtPU5SVLDPTHjG7f9p8hBof+e5pA3WS+q+56uFT1LbX0XmWQUH93eJoAHV5mdvHrWLbxmE40j3PJm+F0nMaHsN5EhvorVH9VDPXgzM0WSOBnliRzhh3sUNyqhtkGye7yMp523eXWR0ZnE9UZzqz0SDwy14otgwjfuS8Al23DDlu2CZW68/ueXo4IwNIfs54Yc+TCcvUDDRzHXtAtxPePKAR2HbUnvsdi5c7Mb8DYufPnakHOK1hMzDqggZUa8nQvu/NKLhO69Lic/lZMWfQt9dpA1mSOmrmnbbBALRN0pk3+X5nBmbMj15nD3dpI6bztDTIelbWnGZIAqg3SA3kM9DhOCzkwhIG1TPQyP0jt63lYd9r/NAuCcTZM8/b+CDpOdp7BfEq/vUOvZhi7QVJ/d395/GEY0l903jGfdye2x5HO+2tAMyNTj3BaifBy+nqchBDKI2IQM4zpFoRbYlbj8WtTFTugJxnjK+fSnnH0ffwLZdT8XNYlyOlHtpZbGl2XcvBkHHA+akJ63HEcvEGFMstBTWHpRJtbB/rkefXH1/g4688jY+fn4Z+qoDk4QzIChweKqbHisPrK8bTisPDstQ8PS6HX3So1kYpwNcOu0CB6fGK4bRifO0KsiiG8wI5L5hevYJcnVr/qnsXy4GJ0v56Otc2yZPFOkExOTfT5NDblfizM8l3a9+yUPJ2QCtYEu3TAKbSsjYNkdCfDfRZnoJ2yti+CxrIzGDPx7DGOghgAGVzcCyJxFZZHsP01WUER9a2ehQiWz6aaOUBwTwngBPAWErHdAT5lONRX2C6jM+cJAu5fCGDUJpN/YAod+0f64CsP2xC45mn/LkoKmtjhNiJazTtGXWCvumUvYdLcjp+v6fTM1B8A4D4zQUagT6Dewy7zl9cDtyYewg+g67dWcPaT79X1kB7PO13jm/CIwCxtO+S415XrtWj16H5M/BOtoPFQFjmMZ+O3nToHkjEto0YBFv5vRBo6rRfD2iFWd0Ng9qX5tM+viC07FnqjzFjKiuBSX7GIfMrCPrEl66S0iQA4xLe5tBBagtT0spgkScwxguf0KDte7M0PDbI7Y+Yk+3RAGKlN+ztrfsQ67KnPD6Vdji0Zyoo1suxjI9yEnoAFnWQKauWNIM0H40GqpcVcp4xnGYMy1r2OErxi/hphVsCyEdagPBQXe3cqwdjLg4z1mXAJCumh4Ljq6XPDjOwVuwstd7LUcotMAB0KkpblrXsexRgWFZMr58xPTxD5hJveXDEehgw3z9A7x1wfu6yWBorQJQKhIqvzqHtZ1Qtceoe2FJotYItc5NFS0fh2iGmBB7zBIYPuFj/LC54GGDmFRMCe5ZHAow8gYqOwyvv5rnJBR9eWa/w4Z061j0vKszfx7p6mUTrxjKYRQaD81xpS7DpblkukGDoToKrDBLLy8Ci8WKvP/eea2KB1bUDADeWR2npNnXJP4lme8HyN8jepLOykcaesTxjvdX75Dg9/WUycU/nW5wwAaHv2UDEeQRe7ejvW4QnHzTuNc5ewwJbpvdc3uzl13NbYB2hR1PuADnfHm3ceXsWP46X68T079WpB3z5902zl/zMDmyEQUmgJ/CgY4HNwC7T2RtQrCBynj36dWeS4G4lKB+nP9GVl6YduJGgcuHb42EGrPynnee9ePWZCXFsP4N7EFZElXZVoteqKtV6yD4b7fk142qjqPfGjrndIYtEswq1tta6JAygueOp8XVZ62ndSuPpXJaOx6EAPqnlr0tZhgYgp1NZnqXJ0nB1LsvOF8VXY7HCjX47yjoNWI8DlvtH6OFQbkyZ1+oTUXD1dnxWwzNDuTnrt13+avl88H8AAJ69eITxuGCSFfOl4vR08dG4XBSQOF9K8bE4lefrQbAcxG+MgQIyr5BVfalaB8H48IThvGB6+RGm1884vHqCPDphev0MmZfSJn6QxfKqVhubCNhwZ4DBe/Z44lD3pPpe6I41mp14C8kPcyrffIuW8nRdYXttbQlbyI9m2QLR3PGw0/Aw1LX2wVqPAoJJlll+NHbCMrk9hJA8SemDLA65dkROZ+LddS0mLS/P1xuF8uyAxEA3/7a2NgaRXhLLMMsujXmH+hOjHYQnWcry0+Uo1WtTZi03T7IdmCnRzyGBw2JWjrzOOqgH7nrf7bel2Ttwy3EZSDqPJf7uhR52sO+3PC2dw5MPGoEtuNjMKG6RrtcweZO2NQQ3sr3rHcHPeefyMh38u+tGJ8XPJ1V7n5kfufOHWVS2mGF7qOc6etqDbZzeTMjKdEHB9O5YRDPA79aZ8g31pd8bQC6RT6EMFv7YpuE4vKcrAKgkMHvB06HF3wBZROFvz7U91+B8XVyxhSUif0eKy06+Go1VYeTlaT9MkIWmKew8aQr9Sb1POZ1G+zSVU7bLQg67l5LcnHwPQ8ljmoCxutLRsi8Rq0KuzuXdVPYk6r3L8jlIPegxYL04lHTV56KsCr0w35CC8fUTDq+dC8CZShk6CKZHWvcI9pvvxnAbmQTgqRrvHWMBvu+fCi8/5/IlLKcRB1mwHgGdAB2B8wPBcllB4hE43y8ErpNgvifQqbyzvZnD0oC5VKurTgPWe8diiRW4g3Nvx2Wpel3bhGJda9+iPdfmi3FZYn3dFVN9ty71U6OM2ZMvnT7XTkJLjVb3QKaJi2+nAOqQrSBvHMK46RkD/ZYTF1FbPeFOw32PYc1gI8Prc54kM3AKMiLm7Q+l8lmtfgSWFNvvLCsCELE6c/4dOc/ta3XxvdFcPrVbYI9svwc5JNt3GcUzWHX5yKHGte1bRqfVhcvPgNB1RpW1e0YVVWytutjKQdUIAHu6noHjdaCvp3uz/8eeHLZ89oxhN4TP6jWC/02E3KGZWdnFB3/PYMP+2JLYA11ZeFkH6L3jZ0wj0D9hnYUKd5wesO2BTQt5+X2vc3I6vj7QrE4bFwIJ3HHIvqzs9R4N5eF27+nmBB3l0wWwRJPluUkjMc+c1jbtO4ClvDLwQXztAsVf53a0vTr1eTht3uiUcaxKghSBbCKCNBjFQ1RGiSX54IC7EDHrpAjUlhwhwEB7FxEVR3aro+ta9hGaBcj6Tx5LZpUaKriotzn4wZZKu4iUU9CssKZ2BzTGEVIdR5cr5wC/CnCugHNesN6/wPDwyi2KUMVwKgde5nuHYkmrls31csAgR8hpgV5MkKu5uLG5qk60xwHrJNARGN9yte0Hn8Ew9iZdAB6vB+g84D8+fAem1wUYgPEKkAWQpfhrHM+ADsB8We6cnu+1Z+somB8MkGXEOh78dhhRFOvjiuL0e1XI5VTeDwNkSJMJ1P5bwXtb1l2B4VDWy5c6Xqxdp6n1iWFoN8ewTLOT0TtuS/xEtZQlchlq37HnQAWC5AJKqM/zHewKz8P2RNqhm3a9Jn0KWdxzXh4kjkHXMWiFugxAjJuy2aaxn/W3D38GW5SB5c9AMsRj3ZbTUzlAA85ZVjP48aK53pa3yd4Bsa6a2jnL+7yqx3KV5WJ97lu5cr5UHhsPOF42tHB9Mj2BRx2+DSM21xD30uR+nr/zJ4PF3ulqozW7Awxl3g40PvmWRm6EDPLy3gGgA2zygER8zo1j4CAj/QxCe7ONDODsdKgp0fJiW59s7ezRxvRxJ9vjUR4gnNYGXnYN4J8a02Vab7KQ2kw1Pw+hM+AzzXzAxGeaJtAyAFU4WPNB1QHKuU4bScp5V0HYTAIkoLPQ0u3nSsu1dqjAl8p3eLdLFoPaBCaBsBeMlSmk72bH+aB0NVtW4OYDkfIC4PsHAZT3Y+oPqxbAYOXY8p+uxSeioJxgXhaYX0AMdQm6WhblPBd+HQ9luVrgQMJuKdHjVADjOEAeFpAn81JAogimh+eiOxSYnzpCVkCu5pLXvGK5d8D0+lL9NQqWg1nvgPPDw7Z9bgodHu6FsY6PxzqH5y/P94BR8dqp0KtD+RO/yQZYJrS9l9USuRyA+UKwHgVYgWEph2bGcwHc61jiLxcCFeDhuyY8eseEl/67Cev9i3rqeaifqBa1+jvc8oLW7epd3XGSjPY7nSo1C7X3P1aSGpeUg1zSdvglO6LfXBcIOHj0MbGmNOFmIXtO5RsIFDR6AuYxGWcZOAVReTPgSyJrM76trhk8bgAp0RGAVSfTTEu2Sua69YJZHIMusTy1iSL2BRmsiFROeEd9JJSXCerV0fRyAmysGxuhHTqw1U+s6/kvp7PfvBWK42d9ynq3B0B7aS3ddZ9OR86z17G24cm3NAJbABQ6gGyZuZfWfmfkbwDUOkRG9xtg2RduANpMe12up9NCr6PluvRAIJ9EY/o53zxjBLA5QJPj9WaXLQG52dAtfa3wlKzS6qB83eax4cu6raPzIAnQzGezhOWB7/TmQzY7dd4IDhJiPqPNdFOfctpp0uA0AKFuabZYLCBULCsoqVZC1cpWddLc6pL6ak/h8r6vUA1T1IMUR83Mh+y02SxKpkh9/ynKPrN5AY4HOrmuEL42cF2Ln8W1nAbW81xug5kXiNTl7cMB0AW4vCj7HO9dQK7O9Z5oacBVtexlPArWacL42hXcNjEOxX8jyuniUh6wTkO1wpWTyI/fMmI83uI2mByu68spDJXbcxonn3z0AMO04vVXL3EYAJmB8UrrvdPlBPVyFIxXiuNrpc3HsxZLpJYl+nVCaTdbSVVgOtU2PxVFf/FyOTBz8SIgj0/Q06k4UWf3VTw+pI57vovbJ691HNgya5avtkQc8kSbNPirKP/Momh9zcFfvWEm3nW85b0fkFEgWBErT9p7jeOpVhkKuI/HPd0cxILJJ1ihcGDXkY/F8kmZ7OoGSeVrkweBIAKBrh8Qn3E7KEL9I7AkuWbpBmpHk81e18F5FngQ9JS0dFy/vcny5mpRaxRivusQ2wLF5UhLw2WZjnc+JHl2G2zR0/u990DTK72tcL3418mRHoZg+nsnvzvhzWFp7DHafu+BLgNSPSb3EHvOF9ieWOZ3e42+C4ISnb1NuT2fZr1ZRnkQy9/bcwl0ZnQS6eDZULYkBrpTOb2B1qt3cGNzzaBgYcegawP6iYY9a7ODOhMe2LY90xbyoLKR0keC2zumr/ubFEBP8G3MEYkcJqUq0WBVtCJQFWLwd9cOpYiUU8sbRUr9OjhI5vrk8SCga+SsXdDcrdT62b3Gtj/RDrHoXBx5Fz+KM/FF/Xo/AGX1axohy1IA5lysXwY2dZB6aGaE1isCdSr3Tq+HsSo9wXJvwnJRnVtXFzXrod6oouWwiU7A57/1U/122LTLNf3+mnCqFsanJFo0j9OMaVowXcyYHxSH3stRmj4nnXC+J1guUPToUKyJoorxVP6GReuSdsljOTQgYH4dS5xiEdd19TuiIVIsvHWC6HsD7T31YZlqHfKEel1DXMlKE9guw6WJDQexqwoFvlzd9i6OhBdW399rJ7LjCWz2yZicgisicNkb7r1mp4mb/86TeJokbm6KcZlM4Cf0r40Q2L4zEAiQzLUolD7UKwMRafmwnNKapwMyq4+BuU49u4foOnSHOlFaTTwKPGU5vgKbxiIeeNmk6013OM1E/0bfyPY5x+1hiKy3c9q9PLNe5T/Wz16nROctwpNvaew1hDV4b4mWwU4PCFq4jV9Djrt3KKWXxjtmx+K4GdQ7NOZZUM6710n36pNBQLBKUjq+Jcdnj9Sx8w0uPbrtHe/VjEwCC89tuyW+2EDJNGcwr4pgdbTfPVp3wW4VmMGtTH3u/OXZctYynXpuXveEi2yTufCVIJs5w+DAWCxr87E4hGx9f9eqKJv40PiwkVum+CneWJeJF5rYrChWwMWWJuty9lCWpHVd2gnXYSjX/U0TxHz/qQG+uQDExQ49SNlLh7lkuyp0GMoBFVXoYSrX6wFtL2SlzayIxuPlYiz7HAGMj2YslyOWwwAdBIfXzxU4ljSP3zZgecuM337/l2Ob7IXrxtw14ShNbJ909t8vvvygNPciuHhF6tI0gGqcny/KQRgdBPMDxXAlmO+VOIfX62EgAdba73UsVxAOi5al+FUh84rJFRZ8y0B5pLBbc3SegbHQ5eB+HOkAjIGkyicDljZeecxuZE7j38biLaW/8z7GPIHlCY+EcVri8v7ePK+LYA2+d5EdiLMDcAiPv4AK4Xv6XJ5Zrnt9Z08mSMuCQS5htkYw0ZR5o1SGH3r0hJGMleVYKKAOJhM40qLc2M2JN0bTBuRyvrpNw5Nof8W6vhPfygr9peYfJibXLCvzONZMS6ecHCfLAd7PaM8NR9CkPuSdf18HKPn9G5RDTz5o7AVuhAwcgH6j5plwD5X3gJpSx+P0vU6xadSOoLyuw/XAV4/GzIdeXnv59AZBAEQ7g7g3S+zdeW1x9zYJC2K8bp2pLC9/QJg5Zv57Po6etvy6EYAnRbjLf6YtVHAbP9d9IxStXCUrL4h31tdNEaR2UECd7qr4uQwjm/Y2utLNAi3TyzxYV791BUCk1etRPrUegpGh+kdc1opTpQJMKZbDeqAF01jA47wWoGL7Gpfqd/EwQccBw6NTvVu50nqaiw9GKTecmKuZdWp1na6WqiQLj4fzivPTE7AC62HA8Hgu/BgKSDscZ7x9nAHccl/jGwSMOZygOFpWi2A4rhBRrNMInRQ6AOOVYJgBWRXjlWA8aa1zafb1ADx6JzA+Euik1eootCdScHzlgPGx4vBwhcyK8bRgPYyYrs4O8mQYmrVREQ+P6QJdUK162pyt8x5ic9FjfOE/OyhT37Gzbrcc+rPO+CNwCcDj8v7F2CxasVPHqhdmWvWpH4qxJXobUJSMJ3COMNHia33gOofq4ZPYMu7DiW+mbrEDZBrzNeAd9qKn6uQZpLVJlo0KtD2BzLsemKPnNhEoDE75Ag7utFc+6RXWA1lmbsaTyT37SUaNAIQllaeePNDb00mb+lDogVJOu3dQqFeetSHnm/PmOD0auIxMy0Yf9cOTvzzda0hjWO9Ye0bxGejlZ9eBybxM3DutzXQqdfAMisIek06duF75BBvT4PVNeTPg6nXuHh/2aOdy92jMM73sAofpCW200+HDoDShlQQXt9He4Afxx8ul8gOIrCBsM4vdKTuUafnzxsMsaO2TAF9oW0rn2wS4Ugwwo+Wwo/cgQWiQo2NtzrxZdksPpObT/PZ7HKKbFW+zoQA9ukpNhqG41lnXeifxCj2fXUnqfPY9eDovZf/iqtB7x0Lr5bHonQoE5/sFwK0Xh+I6R7WUNw4FWNZ7d9eLumfxMJQTw04nIOcFy+UEOa+4enrAMBeA6W56jgWBfeC5X8M9uSVg3IzjnXF9Tfil89PthwIP7l1hGFesk2K5KIARisKfsSxJXz0nOD2rOD+lWO4pdCjgcn56xVIR6PRQcPEi8OC/AE//cqnreCq8WC8GnJ494PT0CB0GYBxLO63a3JoI2ulnEZcNOpdDSsUqPNKBr8oPc7kDFCuw8Yj7TpI/kvgYJjQ7ypx9NYYDYHawqwITc73Tlrftk/7AnxTPHtHSuLVTSFN/8HWIQZYx4LRHARhoy9Qm70wYy9gA0lP+kYnlXZZtPCnvGQIiSm55mWxi90uS4gvRBKI51JH1E+krp6un720LksXdgT290897K3o9/d37zXgiY42ejs7+GPnT0mQgmjGHSPzLY4Df9ei4ITz5lsZ1BUS3p317aF6GEreH/IFtmtxYYYDptnF7oC6XgbVfxnVOr/Nsp0ffpi5J6DhP1j4ozN8zL7MbnCxcmDZf/mTe13/2uREmO2Czt+5hAu+6OHt8McHSs/JyvQMv4EomlpW0RI8eF5xZ+2iMZ/TwSfqNkBT6SQrWlQOVtVGsQ3MT4t2pvMuc09TvzNqzCUNnMlKXkc3q4BYTtTqa5WiAHCbouezfk+PBlaW464ziUgVjWS6WR6dCfD2YgnmBHqdy3d2yYn76EgAwngU412vrxhFyNeP8lkuMVytkWXF4fa3L2YL5csIwrhjOBcgs9yYsl2gg7MGE870Bx9cLUHvr4bUtH/bCRkjfTmhz+ODxsX9/77s+hd9079fw/3n1PfjkcwPGacVZjxhOxcH34dUi3uQMyFrcA83PLJBphZ7LpOL+c49xHBcogGUdsKjgtZcv8dRzD/HwPz/A5ScVp2fKgZn1oLh88QB5ZS7tsFZLryvJajmc5+Izcxih57N3W/fDua5tHysr9IUtlR0l3Z3I0WRHmrun5jan008VUNQDYMsC61etX+rGHU+ebLnzcIpkbnrYLZUGOUYZilk0edzXOpoPVdCrDThi2bmtH5cT5DHLhJCdNVIsIgD80CYsj4x223bCOozkl9JzXwliuc08yMvlSPkkecm/3RBjS+qpUr3b0YIxoAa21OYDmXm7G4fe1jTuuxng2fMeiMv6p+erkeNt2lu3+YYy+1Xg8OSDxuuEjnWgMKvTyPxsOcnInvMDImDpCTV+lvdF5pNSvX19mgaB5bUHZp0+Wp4Ng7ADgvh37uBefi5PW50coBMtHJf9VAW+WJ6dZetQf8qL88n8ztax7jujz4QJtX+eUCC3HYGnHs/LSwRBCk7TmUV3T4YTGMwDPD/fDPqaNix11eeKVM/22dzwpNzEntNVgvW5Mj+ZL6EfG3gcqt+9pZ6gHuAKZV1R9iNOcBBggHNdy8lZO9hyUU5Wy3kuz0fy13jvojwf660nAIbzAp2K5Ugenco1eMuCw6unkq7e+DK98hjrvWNzYi0CWRTzgxHTIxQrowjWUTA9VpzvD9AR+MDhk4AvGN8icH+85Ux/Lxxkxb3hhE++8gDjYcXy2gHTI8FwhWIZXbXciz2i7HVcgcOLI5aLAUPtzueX7mO5Kt+nR4pJgWcWxfn+fVxeKQ4PF6zTiPmeYJil7VutoMlxCFD6t/vXRANsPmmwsVsThCsnE2+4X9nEg98ZMDTrZn3HFkT7ZF+PdvDFboOxcprPx9LXS7dtY6VNsOo42Chc8XQ2zjZL186YNNbbi3jqOACkWFZbGrc8ekDA+BnLFZswboLGdJy1dt6xJZDrlGVVDiyDg5UUDeh13aUB0ccjy1DeP9+rE+fP+mStbuU6/AgrhQmAXgfy+F0Gdj0jEH83nLK2Q2bhfW/rWy//rJ9uAqfXhDcfaDTAtFapac+AZBmh9LnBe+CE0/Y2bXN+QN/aaOGmDtGdGWGbPrzjTpg6HteNv7M/vVjANv1N/i1D3mh8zKByA1Bv4OPmNBgLTJ7VZpCLLU25vDyTZsAcZo8M/jaE0nP6zALH8zJgZUl79SdFkIW3F7cvCHyTv/2ugK/sVfSHG6sMHx4IV6NlwZPHjH2qliXLgcaIJTOrzjgAMoY8dFlRj61UUCLAPNfnR0BWqIi7+ZGlAFE9TOX+6bVYvMarss9xvXeAPCwgcbmYMM4r5DQX/49j2Z+43jtCR8F4WiCnYvEaAMgyYrxSLBcjxqvip3E4r+V6vqcXvLge8extN/3k7TF7y2Y74RdOF/itx+ZI/P94+Tm8/96vQU8j9OUJ4ypl7+UFij/ti+LQu1gaAZ2A4awYHwuGupdzPQDLPWB+sGJ8KFgeKIbHAgyojswLKD++olgn+M05UKlDSItFcVnQ9qgZsFwgh0NbovY2H90a6cEnNCiOwHlPbO+Oaqk9hOVQ7cNiv4EGJKkvF9YPZdJBbbAZIxsljyb7Ay303mVlfcFj2ientBrAy8CK9Lym31gF0QCvRVWOtwcQBFiWssWA5ZjT2AG3m5UUoi3XlflkdG/EUqaRLYGmq5jnyYgDSeNGW5rNjDdZGXu6YEjl84pT1v8h7w4o28MDWafbs5yey+zJWKB/yLbnLm4PkAbdvK1WLzz5oBHYNsiaZhc98AfsN1S2nmSQxnnbYMz7JfbAVQ6ZhlwuA5kcnzvnBjTxIO8Mhh4w3vve66S9PDb1T4OyF7dLP9WXFe7m/ugOUOyVk9utvYALH5EdX4xsda1ltul44lcHQPbKC+86wnuzZpSy9jKLMmogUQG1214af4LvxaHc4RyKcdlMy3umpE0x95wusyC2PsJ7djbjC751Qaax+Fwcx2olrGNTBmCtp6ixtJPX9VPHqVzrdxgbH6bqV/HqDD1MGB4XFz7r/QsM8wq9nIo/SQAqgvG8YrkYy04VUYxY6n5HxeG1M+Z7RwznFethqGUWMDa8POKxHgCccauwmTjeLpmF33x4HSzCn7o84dF6xPGlAfN9BaQcfJkv6m0wdU/iciFYL4D5vkLOgE6K6WHpv8MJmF5XHF4VTFfA8DFgfDhXXgDja1dYHxRL6nIxAue5WX/NeqfJF6JZZYahLE/bUrbWW47mc5W99XT1WL0w2Glr6z98kKLuR7U+ZH3X2pxPT7dT1XHstm0WAITS2zuXOfDx1TwIWLpqwRSyLIYgCEOYxoXIEICoLWdvJ36CiK3SmAnVUjr9XxuNLYwsp9SsahaF5RiAjcwxeZ3ApdPWA5T8rke0AR2iGcyn+jsbdFjGh0CMklymvUp5Zh3vBpOkc3Lbsk6/DrDt6r+abs+Ly3VGk+sMNnm87JWfJ/a3DE8+aLSBbA3aOzXbc5/TA4shzwQWd1xClHe2N6cDdvZoKhm3JZzeSW+Plzoad0QGrWH2gm2dM+Dj8kJ92fRPAHZvJrcBj1X4sMWtN2Pich2c8d5Jic8AbEBo3mvCNHRnoyyUUp3yZMN47+COQB/XOQDGJEw3oHOjBYiHRLspIOe10ZIFldKKj/UPab85KCjNmmR7VMSurM3NDfdne2/9loHiOBQDPy8x2p42okfnxV23yLH6ZVzWsiw9DOW2FwB6OtOBnHpP9DhCL6ey/HxxwPD4XKyIh3IIRqcRIlpoEGAdBwxSTl+PV3M5WDNcFHKvZqyXxQI5zCXNWJ1dL8d6heBUThqvB+D0RkBjCvlAx02BXe94HigHXPSgkFlwekYxnIHlnmJ+qja9KuQsGK4EFy+VJethLvGGs2I4F2ftw2nFfL9Yhq+eGn03xnosVyYuR8HhtepYfartY8vDg9TnI/Ss5eDL8QhdTw0I8iRkGtEOc9H46U0wRKK1USTwLlsIN8BSaWsFnb7uThodK5XnvCzd0lve5KYHSCevlUCiPanf69iPIBYJkJmsRUtDZAb50LNYWxyXMaW+jUaTh5WAzSTY8qG8bW+6x7supHwARADa8pXB9pZmurg+kp71QGSWpUnu9vRS1gneJ0jfOb2JqAAAEwDe5FdDb2tVb1vaXmCQm/VtT7f1dPIbBI1vbD3kN3LgE0z2GXwwUYfIgMmeZeSfQRV/cuMMQ/1eG5YbuNeQrmR1O8PKwDH/AVtrKYNKrg/XA4KNFahFSPxJALRlGlje5aGl97qnWdJuIAESQBiVa3n43iF0rIOdcqVasCzfzDtJbYCiLBpASksanC/PfK1NmReulewdv2chRgqE0/uzjVSl+oIUBrGOFRz1KXfmDfjJz6BspQp1acvUe+2na7kvuFwxJ81Po5MpzWo0VKfQRoOgCcSVrEVSnHEDKLe/1LL51LQpVlm1gsX6fBiKX8dlqVcOVqC4qhtK9DhhPC24em7CcjFhvj9BBTg9NWEdS1lXz47QUXB6asByECyXgvtvf4jfdnzY5cNuIF70nFK/kXA5nfGbjp/A+OwJ73rHy9CpAsFTBYifAg6vCabXKli+UJyeFSyXKPXSAhr1UEHwJDg9Lbh6bizXIz4QnJ6bsFwM5cpBQbkRplobxa55XJbqkB3Q06m0j10bCLQxuSxtifo8Nxlm42pd4I7fWb5l/pEsyo67A2C0fsI8r+CTLX7BP+Pe+BKJB1sMWNqEHCB/iTXffAjH4gYxpm28Utogl3iZVzk9y0immUFXBFJt5QCdkGVMfk6yzZklvQQdYtEBXuW9+4nlsnoAzPMjGZon9K0xtnI9TLo7fWsDTFNdvM+YXOJJT6+tE3aw5z0ssCmukz4YOCjP63RpBok38aATnnxLozG3x+AuQKLQe99jcm50zn8PROa8+bekAZA7zN5vtgBm+no0hk+NfAp8sBllAkmbDk7A2JYSs+WvB9JzMKCQLbAZMLIQ5ayGJIzypug1l81t2tnDYjQFllzXJkYfWUTXpS0FbdBbqDzV0/I13jMt1kfQ4u8Mej+k4vlT0V5MFdgug7XqGj51KiHPli4FVV+CFPevV+PlU5BWL5EC3OqGb62HImSaSpyxLG3KUK4E9GXohRyALzWvelWcrOVaQYgUh96m1M2v4+lcrgK8d6z+GxU6lYMwWt3uPH7bhOOr5dq8q2cF02PBfFFuflkFkFXx+K0CPSguhxWv6XlzU8v/WeGPvfU/ADjgf3nPh/Hvrt6DV565gD4tuDyc8frjC+i44DiueO31i8LyVydMD208wi2oci7Wx3EFpseALOX34bXSn6+eEyzvPuFwWDC/eA/TK48KX21MVMBfrMWjW7N0mWsctv7XMWl3jNvexXqK2fxjZnDoIclPthhKlh/StlKoO5SH/1a1AzL1uZDlMEzuUYdfPXFdO3O4upMnuTTm7G5rp30zIeRxTIDEiFXEPDfbe4ByOAQtjufPIIjyhCIsHzNdFjWEjHQZpNnXJDsZ0HoeFLcLNHP8JBf5WdBvVleSv7KXL9fZwGpHH/Tq43plbelDfdE+NzTuyM29cKNRBTfjhR44DThENmzphScfNK4rMGi/IS0YSMkAITOW4/fATy++Cbs9J55cXq8sTntTuXn21MszgxtNvvNyWv/U+D2AGXoeBkXuxCy8OhYnDhsLqw1mEgZhRok+bwCKn0As0+X16+wPzeNVBFthTXn02oaBbBA4Gl1qZCHsfCUluxGy1n/z7Fxq9UmpdRUu18vYkKzwQU+tLXcFgnNkq2+2YMgAaL25xatZypPDVO4vnqq/v1pnGYZihZy1AcJxaBbxtZ7WnSaIFKvV/Mw9TK8+LiDgWE9fPz4BmKl+iuG0YL1/UV3vlKxFgfmyAPvlUA6HDAvK6eJZcXx9xaO31/dHweWnVpyeHgoGeiy4mOZfF2B8o8vTOXxiPeNSgP94ehc+cXoKX/LWX8RLywPMOuLRxQEvn+7hvA5lW+jjEXrUcnf2ApyfVgxzOWU+PVYsl+L7GIcVbT/kBCyXimfuP8aLLz3AU/NcD7GMtW0Ucphqfcpkw7YaFH+ca+ziHriD0VgUWpUBNnsZPbDlH4BZDhkgtluN6HajWl4ZG2WsbMZJa6HwYeXYpCrexMIyvY29fIe1y8Qg3+1Zp3jHaix3mSD6yXkGIDX08w90pTJ9Ngn4CornYYVK+z60sbYFcVxHLyDWI/xmYgMTar7cd+rXYNXNepnK5yDXMKWnr7uGEwBZxvaAYwZwezjB8usac1I5Fqe7jWonrw2I7Fefw5MPGjMjM9LPzLWGy3mw5as7i0LMYw9I7s0wchzex2jPs/WtV8dsxbRn3dmPZ4A+iKOBvgdS90BplxcEJHZnRBn4UL3sOQvKvMxsz4LATPT26OrOAG8QInuBN4ozzSZEGZh6e5EwDeXTK54JS32R+2OybMTJfxHgMtJhFw4av/C+L9/QRlGKFTIr+sRHW442Hlu5toexHqLAOFa9tAIY/CCF2DKndV0p9MupHqiQAXqcII/K5Gd87XEp4zCVgy/jWJanB/E7k2VRrJcFUC4Pjhgfz5DTjPmZso9xOQ6YHq+Y7w2Y75U0x1dW4GCHcoDDw2J9Wy7LgZLhBDwYT1ue3jbIHlC5fRih+NX5Af6ne5/Cyxcv4JEOeHZ8hP909Q68fLrES48uscwD5JWp7Et6dsbprQAuVgzjikeHA4arYkUFyrWD41z4BS1+HUXLKerH5wnD4+LLUo/HAhIeXRUAdSoAXUz+cP90C720AzEmn1aSvcPQ/DTaFYPLAmCIwNFCkk982tn7u/z/23vXWMuq61zwm2vtxzn1OgWU62WgTOhwcRvMDUViw40fl5Zp0yHYcuSAjQhWbNRExjGNIxnLsrCjSLYSiRvpOjiOGlvOTST40didFhZpUIBgATHNw8Y4xjguU37Ug0e965yz915r9I/5WGOONebep4pTrqpd85OqztprzceYY83Ht8acc0wEUghjouV5TV1nG8P4mdPi/XArZGhLEedp+p8wja3xoOC7sBmwG0Lr03CBPflK9UvG5cvXLEfBRP8X9TmpPojH42MOF8G0RQrkVyMiib6Oz2hF/TSPx/+6Z9LDBKHdH0oZonFNrqv34xfvV5lO+X0urySFsm+W91LjeCi3CCN5iOQg49ZCpvqW1vgxGdNPGvkXUvgtn6NRnMb0geaFRY0u8XxcGoCtaPJMaf+cW7/k88h9hWLp0iptiwhBqSCMwMj7KVLIdaB+hZk4fqjMrHNQO1m+ONq0yx1tJhIDknRFpJJS1tB4OFlGX4TQWWqNLvT87fSlVZHYvciqoujAPwiyeTm4tZXJEIpI7bjuuZ8WM+5YviC+EKexChBTM9OrJ518x7SE16cnBZ4senLgN0uEzhaWMNQ1UHZYdfIyOxJZVcDiEOh2rIyF7bCLxaG1Nnry2UFDKgxAjmSajiWP1UzHbgapCKgJo9kOymEBMyIMV3fQ3zvAcFXXnrdc2fTmz+hi5rURuvMFBivtsXyjGaDqE6hbo+oCZ8+8ousjBfEhl9TnEvH/zW/Bzw6ehieKGnv2rYQxhE7PW1IJ1dBZGWdqlIcLEAH9VwoUQwMqS5gRgIIwmrFrGjsLhPm1BuV8icFaQjkAZl4BDAGr+gMM15aouyVKIrv7vHSuduo6nOhjysJWI2+N9BaoqmrWORbGHgcZ2iSY7053w/upc1PX5JYgeN1pfaFh9Tbs5vZtmvWN/PzoMOXMCSPfMY2mLWncqukqmn5QD8v7s6aYAPfv6Nu5JFgUk2ofRjvzuUkYgVQ2P+DJfdN18n6RhxcF5WUMZWb9ZovogvWlTTKRrHKzY+H7PJY2eBzeD4o+LxZM/x3KJsc/3j/zcYn/9XVOjJHa+CLJnBynOXzfyYkh//jicmuGKC6HtsF2HC9YIqafNMqXlZqGHkf0JKmQ9+ULlnm3XrIgfPxZkIsUuVil1crAf0dpiTz415XMW6tkMg+tokdfhk7OoAM+tVrHOpB682XXZIniuXTUndEJ2UJanHxxvbFOME4E7Q7Il4cQkVx/CkKUlujIZCfrn/n1VOGLW3svLD4/q9WI5IjpgwC/7irs8ozWKPKOG6zjtX/DmkYC+FFnlhSUUOsD0LhP4evUOq7L8QN4TZGsrerb61oCUdcwvW4zm1UYu3O6tJZGuDOPqxU9dPYdBvU7qGa7KNzu59HaHjoLNcr5IYrakRxjd0eTK9NwTQflwNarcrG24QY1MADIlBitKO3u4goYrLZH8tUzNUxl8Btn7sZv9Q/hiCDajVm18sjiC6wtD2GuN4t+UWFfOYtOt0KnrHH4YN8uwASAoUFv7SIG1MOqFYs4dEaJYtGg7tt31l0zwJqZBfynVbuwupyHAWG+7uGc7h4MyeD+PRfgzStfwY7FOVTDAuWwbtYfFgao0PhTNK6eFfYDMaz5Gw3ZsZJoLIy1JwpgFkfnw5EPnoDrCt0yCc3yMkn1NcGUdmA18Ke5uGfUWNCb9YcI9V93rQOEdhSalW+zTYhmutzXd2bBbPXhvP2z9Xk8bAgi+gDfv/j8fbsW8tgujM86+LGnaf/t8sm+XvRvXKYmE8TT4myMi3SpEDGZvwouh0IcWx8WfP0/CwPEY1AIz8ahcTN+JNLh/8aNn0B7Y642Fmvy8PsyDUBM1Yu4UV4tpaqYftIIxC9TszyNI5WSGPK4QJvNyzxSfpKkfBz8yyRyRZNIi1fmSWUO94XVVPqKShFGjYSmyhd9WbKwEXlNNO4WiRbhx7n3GaejKC2fvk+LEclkGoxwhmkK2bmFCE24UEb/k9rptfQpdEdCvmh+De3rqENsyuNdbPAdptHGFp6/H5x5P0zMqTfXDdA4avbpjUZ2jZt3szIaAd2ufR6OiUOou0SFJaKjkR24vcWprq0rnJClsekauw7PdDugLmCIUK1ZgWJhGE5/KQYVeoMKwzVdlIcIg1XWmlj1OyhGNapegWJI6MzXGK4uYUbWIjbsd2AqQjGwG2EGqwxm9tYYzRQYrbI7k02nxsq1C/hfVv8HgKNYz8jq+SuXzxx5fIYNnX34D3oDhlTAFISyqLF2Zh5lUWOuv4BDwx6IDNb0FrDLrMJMOcL8yhGqooNyZoRqUGK0p489dR9PYM66RjJA56DBkwv2fOpiBDy9YQ066xZQlBT8W/rpf38ijz0ikgDjNrgUbqgxdWMpritEO0752l7uZ8657wlhjIEhMRvhr5mXjNbRgY702bBItnNucbRJNe9InWZuYjaXxH7z22OWhQQ/jSF9RoD4GsEQVs4Y+Iisz4mIogk6aNzsiLx5UVrdmmn05slj0A3LR4sbPoh9GRL9uMyPKyhca+MNKX95H23E+Kn1tcp4Ev12smoWPFkP5RjGx2g5nvn05EzluLFWq7ucL0g/jRp3GXc9BqcGadSIiMbiNZIExHFTZEyG5ZWJE0yZNv/tw2rOPmUcLR+en5aH/Fry8hclkoRUk0/dLGJ0wq11CDIf7SuHrzMJZWMbbyD0rxHGQFq5DEpDjNKi9jsjHsYTN6XxR3miLY/a4ckRiKfvp2uMKIKXz3XiLEy0HkpLl+UpB8bG7Q6s+5uCDZgGgSgGC6PmoqlqphmD/ztvWQmuVOp4eg0mrEME1XZvlieaRHZXdcdOKZOTwSwugjpdmJpQLAxQr5qBGVQww7o5pWRUwcCAevaEmXKhRt3vWAK4podiVKPuWMJIBnatYwfBojhcaVAMDYqe1W1n0TrGPuv8Xdj22ulAQfhfN/8QZ5YHsdIcwdGB/D0yfPJNzxx5Ggxndwy2z+7Feb1dWL+2gwUaYcZ09B3da93fdfHtf9p/NvYNZvHKa6uw/oz92Lcwg0G/j+HQoJ6psWL1Ii4/4yc4r3sQ97z6FtQzK1Es2P7KjJwLnaIE1c7ZN8hal0cjW1Uq61g9kCJfDwC2mYXVpY5zl8QH5rAu1k1V+6USKV+5DqZsPvwDMazrNrkMUYXvRdPEi6x3vE2HS3Gf9yHUxONnUQcHCRS33ci66XQRbW7z098RyWBtPVjG3J2g44b8kV8+4HUd1OYvTFu2SE5qfkvdEEsDXG6hp2gMMk2afK2674OjsRtjwJ7L8d7fkwRSM1gY0ScDOgEMalP4gxzbZVhOHrWNs1q8FEEVG8NasiS5S/u2xPSTRq+cSTuK+LVk+xob114Wj8+Jm1YZg3yOCKVIaWpji0yb+6EcR5D974iYKpUrkpGRL97IeNpSJ3zNIg+jfflw3XCyaYxwU6NVdqXRxwm7Z8yaqDYaUa5oZzh7RFIOA2jZBnnkO2fvgBNMGSZaPsDjioYtOuamf25IZHSf+DPmeiTK2jvXZWUjgGAJXEifkcNWfStLGPc3Og2m462OJkxbBmLBFV2TffcubTMagfo9SxgPzwMwoH4X5vAiqFOiLgxKIrvjt1fCDJ1M3RLDuR56exZRztvjBqnsoC6t1azqFSgXKtQ92x6KkZ16ntlLGK4y6L9GGPXtGsbhSgNTGcx1D+O/bNqD357Z7wp8FISRv5TUx9pR4HdnX8VBl+6Mc/59sDZ4mQz6ZoTNzhL4cjXEG0pLJD25HNAIL8+vwqH5HtbMzePM2T24cPVh/HzN6RjWJfYOZvGu014AwaBnOrh+3Qv4Wv8SlKU9BxwwjiA6wuh8n1pfjd4y6KeqS0uEwkYZ2PieAPm6EYUxTb/FdGaUe9F9/0Hk0pCnxQBo7rHnzXnUnuTUEU8KrqwCSULTfgjRBpyG6PAIXk7TfF+T0wMjXsQ5XjQNi5hMSgReWCDuQ/wzT8zgDAeif/HjhMwjIo/uL//gBCEirdHmRhunIa68/zTtvwYNWdNmZaQBx8T6aRFdvm5S7ivgJIwrUXoI8ZDETI7TLQOGCKfF4/d4uVJET+MU2n3JfTQDSyotgeknjUTNOplxL9GIMLxSckwinkmLFwvHvwSMJ1gU55V6oalpck0WH7dmlV4rlyarDMe/AiWJVPWhWB1lp58i1T791OLjKL8xeuP6iPoBJW/7A5AWvsiVjQ/Gp1Qoji9/a3oIaTD5i0JJyrAkeSeNJi7vYLkvR9dRSv+KsfGRQjLRUYNF6R5TyDusXTRoBvuycFPG9r1SWJhP8ceB/ABz8fy16XSsWxaXvnGWD9PtAqDmpJGqtieHOMLoO3ia6drN3Wy9JQxAvS5QGnQOjjBaYa2SdbeAqawF6fAbbPfXWTQoBvaovdEKA1MBh9cVqGYIhzcDZmSb52hljc6KId694mUsC46goz4SSKvixtIegQiU4Z4njEBDLnumg49u+GErvbbD8kZmKgAYoJ7poTi82PQ1RRH6ONPtWvIzGLh3PQL5oyJHaBx8u53yYSkD67uic86B9mAt+hB+dKCcbvbgJDHECUnadIKPSRL+SiMe0lgC+SaasPHGhmr+8GZLYJZC9iwQNEbiWrMF/g9ncyw+gelFyEEiTjvj2LOD7Hai/h+iTxZ9akjb92c8H54+j8fkMOK3nBXTZuakpVfrPwu3dKIle6uwiHZJ874s5K2MU1weeZ/XYzk9nfqI5KSWj+mp8UwdV8ekF9W1NBRb6ZRBI0ryxWgEUhIRf09+4ch7KaSITV0DfgpBysjzGZeOly9VYZZSeVI60oifDdhOX6Yrpy9lPjJ8ZLqnmJxF+biRisOwxuv/jiPXvGyeLMnpkZAnHyFkr+/zZPf9EYkhvOy40eTnv9KjZ/436wBbOrbpWkuiG3Qip+b+GRtIvFWB+ODWuCDxgwxVVbS2ip8GE53j69ynEFFwxt16r5xEuOem0410Y9d5kd3dzN+N2zFret3w/szCwLrYGTpXPGWJuixQzRQYrupZx9yFAZUFUBqMZjr2jGjYs5KHKwqMZgsMV1jXMoaAzmFLFqq+lbt2YtDKEfrr5rH6jQctOQLhE2d9D8uGSR9/JwGGK4x9H0TBLyY6JajTaU7i8XUJniBZMklDd+a0gY1XlvZdh74Czq2SCb4fw1S2MbExQOsXWd/jrY58CtpaEu3Utj2BiI8DTZhgaSSKwkVHC6JpU40bKv+PYm7G+wPWROEfcd7DPuxa/T2PFJElVoigA59PYJMiM0H4DNpjj8+bp1Gzvs73oxFYHxqyozhs9O54GTT5/LjA5GnJ6com+Z/Pl/f3cvwiNg57wszLIfWh6V0bi7WZQMk1/IeSBslRirI9xmt8JCkv4jCpfBWcGpZG/8K1CiYVxlm3/y3DtZxas7iSJAUZIEzWJpG2QvAk0eJl0CqyJHrymaysMs8U0ZREVq7PSH1VcRO/TF/Gj2RKlVEbYJU0tRNpWvm7ziVavuDv83i+AxGdhKwvQXYhm5a3TD8iqSy8nDJiowxf5N90bC5KOCfXP286wCYZZyWJ1uf44jcOiY1LtyGYlij6AdR4SyPvAHk985ZJZ7WJvnKrEczMDGiR+zmk4G7H68QMrXNwMxjZs6cXra/Gwxvc2dQFUC4W6B2qgz/FwRord7kI9A6MMJrtYHHOoFo/RD0sMPvLAoPVBuUiUPWtC51iaICC8IGzn0bX1BhSgYeK87F5dj+WFbxPOoJO+0SCqeDcJVHUhqwfTbZEJSzMr9zHgX2nxHdOE5qdxaEdMt14f40+fOtkJwfST4NpngPNKS7N2dPRB5FhG8VceB5GcwDu21vbxQ5rv7yNMnl5uw3hfNwgtCdCcR9gOVIRyh2fOANltkQQTvUj2P3VgkYfomzKOMgmZA99GLsf0nVjAyumyIz1/y0WyOShVh8XWzR9sqxsScMHKwsljDn8ulW/RHracx5OjrVaGtyyWNcAlCVBQNPvyo+o1tiKdtylmBlxKpDGUAkU8uWft8iGiRXdIkx1Ox0eV1uA6klW6CDYOi9J5DRSwQdffp/vruZ5tXSAuNJoXzwa0dXCA40T1MgVhIjL1xGOaxhEiIm4YmH0eaSOJWxuNH8lOYSQi39Q+KkKno7Ui7ZQu5blF2nI3lDdLWgaOYLMssPzabFOnjvDLYztJOUA1Bow+LvwyQkHxFK6Qvi4AxBN9xHYTk7eTpTE/H3v3NsPBswqTVUV8qRRBeMdf6+agTm0YOteWcCMKpCp0T1Mdv0kAaYCyoUaVBrUpUFvP4ACKOcru7uXrGWx96LdEFPUfhMMUC64jS9DwuA04P/e8Z9R7+mBujbMgZUzeM/KHe0yvR5oi95PIoxWGtQzHXT2zVsLrzuekeralm2mBywswvi1yX4drdsAY/05km1/w6FdE1kYwPnQDAjNWhCy1Eew6MfCmdSCJIb1uJwshvruyZ2to8GyGPomLwPAjxOMmrxBJJc/JSciToGg1g3xifJGE75VTRw5cn1BswOakSa5vCYSnv/mZMnLp5C9Fgn0+UH0uazPCmmhScuTRVU+nnRQZIganyQjyqCC9ZveygiI8VsZy33+knhxo8m4Dz+tTsp8uRFG1mWehrarWuafGuNTYY4C0z89Lad9PWTHkuq0xz0b9/JkGvwLIFXxloLgv0zGG1MZZAXUiGHqtyQyKfIsibTxjZN1OFpDCPL6eHyHtCiLtFaqYcT9UF4mB5eLd3CafIFIGaFX38nyRd4+HiO5oWOTHSkrdzz6sDwESfQ/ZXzpPJyNG8af6duyXMSXYVB1DpOj9WPUpOsHU28BJLInbrQcU/v4Wr3mbdK9G1q0xwhyq4LpdGF6PcDlEU6XAWCGI9QzXZhRhXJQo3ugQm/fEL19izDDCsWgQmd+hO7BITqHRigqu0mmGBD6+2p0FigcjWecelfsGqJ7kDBaadA5aGB29LFiF9DZX8BUBkVR49nFFe3yHC20j9hlxgKN8N2FOfyiqvHj4fLbCMgAdde5PfKWv24nTDObkXOr49u2IwvGfYDQcNTUXb88gQD0eu5owrK9Jj1U5fhjAwCIt+uyWcMZbXIR7mW8m6CoDhu2TjE8Z0RPdifsSMLoOaGxepKXzzQyOaLVcncTQRJGwR6DjCzTJHniwvnIrJ8JdZFEfo2sTdoGUT7RB6/sKwGtC4oV6v6phE6OI1ofLjNRrvmUdGQAQPOcp62N/cbEnlB8GF4Xo3GoiO9rco/72NaIZKvcIg3+WzNGSRJ8BP3P9Fsa/fSWRiY0RfGOSH5JSMVLy5d8Aa3KifiF8TBJwqI8l18NnBTxijDOAWkqz0n6SaUj40T+JZ18rXRNvIPNCH3KHpq/EylH+J1YB9kUNN1QeOcZrkW8yN0QWN4urPen1upsfGcrOrwmoSZfknF8/iwfiGsDaOe48kFUnnQRDb5+QHMDJYCwsaXlm44oWBY1VyVjEeoAmvdTk/XzR3bwo9EQgJ3uNm5K0lofnf/HugKogBnY9W3FYg1DhLpXoli0spqaUPVKFLU9Z5rKAqaqUQ4AU9uzo4sRYdgz6MzXqLsFqLQbYbr7raURtUG5aGU0NVDtnMUjr70F//nCJ5de3iXrY/lJ4/+19xyUpsaewSz2zq7AgDqYNduxr57Fa6NV+MXCaajqAiMyeP8Z38dphb4L/LV6gBLArCnQMx3sqCpsckSqHFjLbqjTrM+ybnDsJqpgPXZrEon3sXJpSOGXlcDWDe9ihzv+Ho3YiTGufpSlnfo2xj5nevX5GZZPYyn3SyGY+xriZ0o39dt7HGhc8ch3x/tDAHC7n91aSNVxuCeRnMy2ug/eABFfE0B8E1zb1Nncl2NVFMzE7ZJ/MEdH5aGNFqkRuiGWEYH187LPU8qszUBF1ktS+jdqwowlW0bIomx48bLwsY2P654zSDLGDRIyb5m25hGFh+NjuubaTsog4wd9Au13hfj5BEw/afQdUUpRgN6Q5MvQ/CtxIsQJjUbGJFn092Rl0+SSJDMqm6iE2nMuv+byRiOS6rWo1PJrRebLG0+rfGwAiEgnn6YWZVRJnWwUSgNtfZmLKeIo30Rjb8nmy8OJGtA+nYWHk2D5+HDRAMo39yh1l9+OpqFNSyxbBH9Dkk0vqn1PVNWw50oX8Iv//bsL5/l6skjNukO+ppGq2p3mUjUdXVVba5KXtWAyU40w3V4UrKoYkFsHR90OTD0Eyo7bXFGDOiXKRbspphxWqGa7qDsGnfkRipH12Vj3SpiKsHBaF91DNcrFIQar+yiGQGfenjFtACysLtHfW6OaMei/BiyuBQ5tKkAFwdQAlYS6SxjQCD2zTF2n1m6XCX+wdhv+34Ob0J8doVtUeOnAaeiaN2L7obUgMji0fwZlv8LqFQt4cP/52LMwi1FVYM3MIj50xgs4UA/xvYXN+NXCWnzo9J+EdD1hvGfPuZh9eYRiYQi4D0Dj1xqCnB9Fsvd5H1MUzuVOFfdLdd04/gY1PhuD+x0Ikomgu+hkIr4py4FPOXP3Os1z/9evVTQtkkSBCLV1HbvwYeshYWKSaJq/Mp3gXzVMDQPqurw4Z+jES8bhfaSBtLZGRkpw3XIFeRLJ+pDQz1CkT6eURNdFgPy4532WCRdxWklfwlbO5mQb1q/WIq/W2KWkKcdbOX6FuuNl9mHYsqfUmtpx46vU4cQxFG05pcwaUn1OirwLTD9p1F6IJCIayePXGvHSMImIyResVSoZX8ohw6ZIZCq89nUzzimurICaTCl5eH5cHknuIp1IK69o8BFpW8J6St7Jh/Vjgjhz313SuheVQ3lPk46EDLoltOqHJKXhuR80vCyiA+Vf7P53a/e4jjBYaIMWUbyODAiDfbQr1A/UqfdeFDDGveOwyYFiC5JfvxUcLhfO4gj43bW23TnC4dYwWkuu26lLsDt33eYJKgzMqEY5AqpeiXJYo+p0UNTWCjn7ygDVbAejlX73NoKFsVgkdOet2x3UVoyisjupy4HBcHUN6hJMSXjk8FnLv7bxGOGKVY2c/3XFbnux6lcAgB1vqPBvB38DG/r7cOnMXhHTYG3Rw7tWvAKs0M/Uvua0/8DX+pcA80VzlCCoeafk61QN0++BBkN3tGRhyWFVuXiuPpZNHQg+RAvTfGTIJTB+c1U1pg909yJ/jN5aWJrwLN4I08Tjx/xxYhhNgwNN+zBNuIanMUYWEcJGZQAaf42+HODtLbwW0R3IvgAsDo8U329OhGGEjecbyCDvYxGHJ1eeSCg5fir9ke//+dIeWZ4oL0bQgmVQhud/2bUZJxuUssXvNYmWEYWNR5GRQ+Qnr1tkVJJplo42TmtjjzTmaIRT4yZLJI3Tv6ZRY/P+Nwd/2XK9IFc6JzQ8rswvRRi1PFOkTisLlyMVxqczjgzy63EbacaVgcuaeiZ1ExqGCMsJbrQDTOhTbZSicfh70QBi0u+Vf2b7PFsOz33HkGhVfGDgeUZ5FQjru6KpJFbvoqMBud5Z+hGpRBNfc0YedZRQdlQzEcgOXMZPsRvnoy7yNyeLLd69cRZHNzUZtSmvA/K6gSUUHb9JwrksKQs7Le3rAqiZoqwJNBzandRUwwwr1L0O6m6Jqu/cs9SEzvzIEsj5oY1jACqtu53RigJUwJ05DRQVoRzUqLr2d90DFtcYa4k8DJgh0H+tAGoDzJfomyH21Xyn9+uA7JeWAT8bATurEWoQavb+fzIssace4KHD61GB8Eq1Cv9l1U8Uwrh0LMwVGK10fjIBhHZWE6hbAn035c38cgIAzS+E/smEU1+KYHEk/pEO2Lgd5ZzzShDJBFo+Gov4N/cDadyu7+A5ILi1Mo0rKp8mub+mIYfNWdIsX9eewjUnh6aRIVjteBvnRfbhub59uIj/8P6Cx3dxtNkG3mf466LgEZv8wjjTShxMQVDBxwA/rR7KzeK32gQjghqRbRWI3+NjphjT6iru7+X4qvRxTTmYDPx+yrgi66n0NyrXc0pSyf9yjOM1/rkcO+XvJfZB008agfaL00ieZj1MMXYkXl6wpigVjMf3acoNAVpYWVHky0/lwwmmRko1MjeucWi6kfKkKm4cES2Lgdo5KOlw+aTT6pZs8tkSB2UeV36pGymT1Kv7F2QTHY8keam0fIfnCVNEjqMRA01v798DC2bAL5iopp1diNNYVsbtmI6sLTypmh3p5ut4IOtwRwfCnQhT2urgfC6awjl8rmo7OLvd0yhKoCyspcpZnahT2qnnGesjsFgcoXN4aP0p1gRzcB7m8ALMYIji8CI6h+3f3r4hOodqFM4wVnWtY+/RbIG6C9QlMJo1oAIYriQUIwJ1gKprd1dTr8azL5+JHw/Wtcp+VEi159eBN3WsQ+8CBgV70f9Tt8JpRQ//dcVulDC4sDcfnHz/ZFji/9z1P+OePecm033w0Ab1vqkI1ClBncL+c4TMDJ0VEUBcj2GvPYEcVY0Vuiwbv4517dYulo0lk7WncI6zMvBFz4yxPiAN89dIbF2uYevhAmFoRPXTzLZumxAn+CZ1xZPxADQk06BFXINOQrP2BJK1T+3DWDY7T0iV/GOdR8LG8Xkf0ggv6ifreyLypfXfPLz8C1E+mYYybkWdFJeZPedHzIbbjCiGD3amF7ccJhJK4wn8njS8TDLg8DCt/I2etu8/NSOVj5cy5vB8xhk5JDGetIvdYfqnpwGdUAGxcv1Ax0mfJIHjvoQkifKQxIgIzdF4dTqulg6/1r6svbxyEwonc6FyKBWdNxSpI60ccm1gqiJHDUXoNtVBhmtHMmVZC5E314FJENNWA+Rpi3yiqWrW8UR6dzqQZ5IapnsuAyDyY51g+Lr3efDiKYTSh0V8UkV0Ni6L3qxBBKKNLSST9xYXWAKpfExpa8L4ANyOQI7slU3Zw/otcv78Cldsa+mh0Yi1TWNPnuk0lkS7k9oSltGKDorCoBjVKBYrYPerqKULIF+2V22n13F1osPqu98GMivjybIYgx/RSvzIrIqfeZ14Sytvd3Xt2n0Vh2ft83/8tzMb8tAEauqMbMtSrqKAmenD9HqoV81g/9k99H/jID6mnPICwFodD5yHnQdXoywI58/ttNPRAvfsORe79q3G//bG51rPipGVx7o/MvYs5649ItC45QLodEDVyNVBWFc7/Z499affAy0sIrL0eCtgWKJQBxc9ngD6eh8tfXBO6U2B4AUAdQ0+/Qw3jdxMIZvQLiLro1Cv908atQfTEFAZKdpY49o2DxaRVC3DqL814rlstIj6gyg9kmH8YyPi8PCiD+QELZDcQqTD8+WdC5T7YGMYt2QyAjn2g7pVmEaW1jMvo7aZxoWV4zyHXJbGHXDLtsjHZflXxon84lIcLuW+jOtEm0WMyqv0EzwPjRdMOk7YJ0+auWAKsH//fszNzeHd5v3ooJMmYxpSxHJcZRmXBmAra121ydy4XVM8LS2fqHI48pJKU9sMo5VPljsiXMytA48nd21FDYZNQ0id8Dw18sXLrA2SqaOdtPDRVAZivalfyryhyg5QhJNf4FpDbcVx16HMiPMM75FHcT8CsXAPQkceF7GxXpjWvcYvI4vI4vPF++E0DMNOvGC69lPKNBy6o//Qrg++jviBHmhcohQGMOJEDrj65sMWxm6EGVaoV/ZRzA8AIntUIIC630ExqkGdAvjl7ub9aoPBuA5VhpMWAB/PPxvXeWsfgeO6W63+Tmf3nHGygxMc6VBaazP+PjBhvGB/xxJP0W/x/pCnGQIAbeOD7OcFtL5c04N8rpFQTR/ciCGNGzJduWua5yf7jZYe0Y4j5SfCCCM8TN/Cvn37sGbNmnZZHU4NSyOQJhPjOnXt2bgXIuNFXwoJ0uTD8UbH70nZU4OI/0rQ3ATx337gDvHGVFZ5LcuQ+oqSg3+UF9+gwslqHf9NIeQpyhnkUDoOIkAmGcqh6VOWI0EIo69eRuDGdUYGaDmm5Z2ecTcKrmcZX+Tr43JiCXL5sPgGlvgBzdpGnyZEknUjWyCFjsCFM3qdDuX6sKAr39l1Os25wpzMBZ+PbkqavDXOklYaDmH6PbduzQALA1C/Z49pL+20EpUFDBFMTRiu7qJ7YIhok4JmcZSdLF8mMqk/8AQ4FYbn1aqbE8DTmTTgZGQcT/CxRc5GyLGM30+FkWPdctT3STK8nvuTnms6mRQu1f55uKXoVfubwrg8Ezg1SKMkeZIkaW5oNPKYGnjkbzmYSPYvvzAmhVcJq1zvJjCuEaS+PjQdjCXGgkhKx9w8DY2kaWUcp7+QL5p0goxsQJdT0LIIark40WMWzFaZE2jt5FbyDWJ7YsfTFMQZogxSdp+Ot1QaxOVyhFH6fqPU+yVH1Jxe5U5p+49HpUYqI6btpH55nef5uyUGFHZFm+A6hYjsecN+By0BmOnZdYyFsSe5lAZ1366lG83Y4wBBzdSz+hGj1TftngzPyyU/krilRZLOVFra7xQyYcxYCvLHxamL5Xj3YVwZj+nfCKNZBZe6HiAMloK184EjIkQJaAMRN9HzU17kYKsRJuOJiciD/9PKF1k+afwANo4whXDsS1Ob5h1ngdQIo/bce9OXacnrsDalZPG5TII4gL03TmY1aydRHL+Vd/TA/fGbYZT6Id+fz59bT4PMPiw1hDzIawC5PjUkZRyPpiYZniTTSdj9Kdzt+Olrfz6w31mtbYYxcpoFaBw4+w0DxpXN74xm78t0ukFvVNfOyXfFXPIAZnEIKgoUB+ft2dKFQdUvcXid9cO4YtcI3ZdejuuLJJBa3ZfwbVK+M9k3NIqKrzXiqOV5JJ38UiyVGac2MmE8dbEc736JaUw/aUxZB6T1AGgPMP6enF7SrAoatDg8TU2WcelIYqiRUZ6fds3LyX+3NjwkSBoneWG9WencFlA7rqYDqXMpeySjSCO6LhpSGXTIdvz5a/ugkSvaxcfc3HhyGJE2F8aTQElwNULcWj/J7xOixebqekqwZ0yn/hi2iEzqcQJhE/y+uW7qXMuNCBAW6QfSGa6Z3zpGFFtnTwOxw+WiaNyjeD0at5u1KECDgQ1TlNYpeF3Zv273LA0GLo5Ni3odkAG6B4cwtd2QUc2Ijy7pYkn9+BLQCJ8MJy2UvIzaBxCX5WiRCcFkZGKdkXHMcWqQRv7XDVIqGeTWP07sUpYKOXjwQabm5CVBFn2eHNoAJYmvZg1NWTu91WScNZSnH/JXyHTkcJuVBzK+Mjir1h3T1icPK8lyy2pD7by8fOrHAo/ni1nraXgdRMSV2ksZtIEqOpmAEFkuOYnlpJbLFclooj9JFugJr7ZQUfuA4O/GID61IvBpe6a0d/AdTvUghFNiolNjIh04gunPi/b1vHb69upgzs+N29RCi4OYZFbOFYu3UDofgMY57S5GhMMbSsyvK+xZ1T5/7rZinC68HsZ9xGkffVyPoWwsvFw7nHFskXWckXHMMf2kEWgTLHmwuCSJHpJU8nuaSxtOenw8boEZR9pkXG2A0qwf48IHCyJ/LqdAebosfx5PLsLVNvVwoiz1zcNItAbfxLvQ4mmEmZNYWb5J+q8ZgZREFWAnU1Asb/QXTP5a5EmN/iO3Frz8CmGRm1yMj2/YvcQaSB7HyGe+nIg2vngZgi+7llW4KSelFmj7+tDi4WTd7QxH8YlEQHDsbM8qdvmWwqFzUYDc2sbh6h72vLnA/375k6A3LmK0bqQ7cPd/k9bsJu3Wc+2al1e2W+1DKZOZjIzpwSlu0Z5+0sgJXoocap27NhBwaAOBTNMU+mCjWaokYUxVTM3iIfPl5M0YMXVMet4A4jVzsPHkwMnz9H+5VVXqS7PghDwV0pdyoWMjxeWUOg3hTTpMUo9FTGLk+tJQFrmD3OuaWxelvgqhf0ZOox3QLn5UFhc+rJGkOK3oL5gcgqyG8vJ34POD4KBu7SJrN3wDjeqL0YN/TJVF2wLJ3y2vN/4EGRCoqmw8A3esnLGbYoyx09V1bY8MrAizuwz++/aLUL3Ww7q5g9bljmYJlHWe39M+clLtNjXNzD8SNQKtpZmRkXHy4RT/CDw1SCMnhdI6pVkM/G/+l6enPZeDhidr/FkqPdUCJxbic9KTspxx0jaOdHK9aOnLNAOBEvlrVhwpU2oQ5s9k2Ty4ldaTTFnW8A4VIifz0dJtAum60T4kNHLPiXeLOCh6jvStvEf/0SH1lyyXIIQ2UvMviu/bAY/qp5jJBaMwtUyVO/+ZvXe+ZjIihv4IOGOao+O8nMEvYxG9A1MYO+VcV/ZM4G7XnRhTxHKO3KkgZYFiWNnTWgrAFARTASs6A9CKfkP8NZ16WfwylUjf7F2m3PDw988hP+R43FRfciojE+iMjJMS008aU9ZDQLcmpaadg/VNmdrm0KwcXA45iKRIFtXN4KqFl3H9QKlNhxdlY/GSAyCHtFBG8ghS0pqypvbgqA2gXF7tN9e/XBM2KQ9ebp6vf89SN+NIeSo/Hj6Kx0i117ckGeP8mXECGXajQ9QvQTRTHxuNs0UXlOUb4gjCakwzJRxedUN6/BnUzXS0JZa+HI1bH7b20efHncoDzcketbWg0mgE0+0y62Kz65p6zCsYq4NUFji8voPy/EO4+czvY9NvvIqXdp6BYv9hRW8C/L1w4iiJola3Ukh9cKU+xk51ZAKdAeS2cRJi+kmjHMA0ouIHNk+8tMFCEkHNujbOmpYilylLFo8r5eekl8fl1hM+WHmLZzRNjbYuUjrSzsjW9CDll9PWmtVM5sUHc0ncpKxReuJjIEX0vRzaSSGSVAb9Kev6WvIQwtS1pmepNy2tqKyCpGt6kBtfouee8DEiaHh4nj77Gy7dGdIhHpq4pDj05j+VclHt/C0aA3SkWyRrubRnUPt1klZWM6zskYKAnaYe1ZZXdwrMbyLc6I7I++Dan+L/+E9P4ZX3rNQthlIu/m6lBdKDr7XU4mp9gPYhkglSRoaO3DZOOkw/aeSVUk4b+sHCW+hSVjiN9GjWLZkuf6YRNKA9SI0jrFKmVHlk+cdZPnkYaR3jefGyyMFQs5hJ0qWcYTx2QOXHzmlIkcLUuwPSu1ml7FoZUnJqpEGSe64vTb5U2vK+J30RsfSXYi2jZsHU8omIvrFczTkMJ0eGjSflLg1uYQTc73DLWSRdmf0UtykKO71c1+7caBfBnzHtrY/esjkcgkZD67Ox02yGIUc4y4MLWL3N4Ou73xwVp3hNWCZlm+b1nH8wajrhv2W75Drm4WReWnoZGRkZJymmnzQCcaevEbyU5UsO9OPIoZanD8PDatYtjcBo92Q6mlUwJduRDFo8TW655MRPEjVp9ZTWG0miNPkkMZcWTh5OvrOlWIJ9Otqh8zIPXp7UkgVNbl4eSdy4y6KULjjR5umHdOXOdUFQeBk1WSLyKEmystbTiNNeQpLUxHfksXkIBDc97JxqqgmtHdlEoUymU0YfGKa0BJBGld0QQ4DxO6xrQjEiHBp0I7mKgfJho300BLkR655fy7YlLdb+vg+rWaR5G8jIyMg4yTH9PRkflFOWFnmtDRgaKZCWB39f7tbW0tfy53H4oCMJmb8v43Fyw9PSyKQmuyaH3Iyi+bjkGxt4+nwKWHsPk6x4/pkk/VJOH59bNDlpkAM2tyzzd6JNTXL5NMuhRhilrC1XRIr/QPmujEFY15gkkKQTFe7wnKhJJ6Ttl2JUaV36qeogIiu7XDsb7Wr3wTxBbEiiKQuXfdFspAHchpnakUN3fzSyDr0doSS//nEwtCqZ6eHQW4e4+czvR0X4+Nu/K3ShWPu0D4VUe9DqrKzj2gyB1OlS2lxGRgra2JGRcRww/aTRQw7KmuUqRTA1AqdZv/xzP/BpU7IyrkaI5HPNF55mYeTPtTV7Mr4kk9q1DC8tjDw/GVaz9vCy8jDj5PHQ3JnIwThpYRPhJQGU4SWhleXw1ynCMM71Ck+PX7c2yiiWPymftlmqZX0UMvJ0g4yKDpgTblPyjwV/jTapNLDWxRb59KfUoG259I68q6q9frB2953MpmOdfNczHayaXYQK+e5S7UaGlWRStktZR8cti5DpZGS8Hmh1OSPjOODUII2ys08NBCkLoEZsNLLHiYW8z6FNj6bW/HEZuCzafR5PcznC/03aICAHQU+INcsal18jV/K3vD+OyMtycrLJ5ZVTnjydlIXJW4q08mjkkuuInxeuvRONIKb0ycNxaDqQBFO+F+3MZAmNpMOtOwx5xuWmirnP8RbKKJ+QjNtJbQCh1rA7mhC76ZHvJ9QlRO6ePOnEqEIxqDD/4hrM07BdPq4rrgPtA0DTv6y7GvmXdSc1mKfayyRkopmRkXECYvpJo2bp4s94mJTlUIbn0AZojSDIOPIeH4A4sZMkNEViNItbauDR0uKDG4/LdaP5N5R6k2XWBmwug/ZuNLLIZeG/tXxT74lb57h+ZTm0vDTiyf+mSLj2QeJ/yzVy4wi0/9vyXYn2O5BkiKcnZWJxGwfeWj12RJIT5nA6jd8s4+66ndV+Ojr2d+7i8DzLwvpw9Gl4f478bHHArms0gBmOYEY1BmtrzJp4TeN/+9ElensD2rvqfZ2WutFIv/xI8HG1ZxLaR8MkHA3RzMjIyDjG6EwOcpLDD0opi4BmdZNWsElWM/6Mp+Pv83SkZUoSNp6uRiL8/ZQFipOLcZY6SUCkzFJubsWaFDdlDUxBI04aEZ5ElGX+Mm3/V7NKSjlTlipO6COSXiYscIIMamVJ5Zkijqk0ZF2Wz1Jp+bKE/Pg6ycL99jL5/Mkla2L/jYaRT1d24/76MN7KSLVz6xNOg3HyFQaoYHdWl0U4FQa1W/doDLD/IN7w6Dz+x7NvxWhFF535EarZDtbv2otaI+i8nPwdyjD8WtN1qn7xZyk9Tyu0+p2RkTGVmH7SyAf4VKfOnQ9r5E2cYDE2Ly0Pnp5GCDVI6wiPo1lCNAKhkRCNDEpZxxFFjTDxOKkB1xNmPlDL6W6NZGp6kPLydX0a6ZLXmp4kND+RsnyRzkT90EgZz5OXLQXtPaeIyFhfkgae5MVhDIIT+ZAmC8vL1dyIZGt2Qpt2EHeSDBFZzsk2wPBjCaNzqL1rHpFWyzG4MaDBEGbfIXT3W5109xvU8wvpD4GoGEsg8VKnqd3RWhvS8p9WYjWt5crIyGhh+qenAX3g0MhUKq4kRBLjBg3+XMs7RVq0/LiVxEOSSp+fZu2Sz8eVWZNdI4rjrKJyQOV69INwiuxKyM1APFxd6772tF3sGnnU3oM2DezjS4Lq76dIM38udcGfa3JpVlhJnvmHjxZOO1aRCIAikzxpJpTJy8LrLppnIW32M1V33LW3UgadavW0475ri8I5B4d1ueOnvuvKEkmeXZI8j5Fr3MeV/M3T0NxJadfj+o+MjIyMkwTTTxq1aaTUfTmAjDvGLkXq5CDDw2qDopSHX6cIlCwHT1PzByeJjia7dNfD9aCRTE9Uxlm/eDoa4VmK1U/Kqw3q8i/QlFcjk+OIespapKWTKoeUSeo7RbD5X5meJLFRXZRr9ZgMnIyl3i1M/P6j+uv17v/zZ1S7aWci+HWNjbwuSlmCakI0hc2LV5bW+kjOIXjlp8HRvLvBoJGjKG38srRpdTqNo3AigJ+RLfUHtM+a5rqQH2KTPhI1ffG05YdRtsZlHC/kj5WMZcT0k8ZxX/oposbvaeSAD8b+t9w8koK0qmjP+TUfcDTXO1pYvjDfyzOp45DT75I8SNLEp5rHrRGUJG+S9UcegyjJoBZn3AeA9ymovUtJRP11XccWXP7OvIxcttT0s38m85Bh+F+tHF7/XJ5Ij8pvXgckGZakszUFzeXh1kUf3FokNaffAGDKAqYsGhIYkrSks0XsCTCFjRPc7wB2x7aXxR/NGDYx0XjdaiRd+rtM1SvpMmvSx+G4MFyeTBwzjgdyvctYRkw/aQTSX/opEsn/RoNrgsholrhU/nIAGWch5OF5WuPW96Xk18JrhNrLJomnXIvIB3C+/k8SRS7bUjovzWKjPZM60sCtfHLQnqSP1LpNWS7p1FzeT/n1TL2/FOHh4VM+OKMyKsQmqaNCic/losaCR5YworWG0f4OPhqJEC2ldBZFmPiEGZL5Vc2OZNPtxPUxbJqpGzm4VdDnoZVb0ym/z98N/9iSkOtwtbaT0vfJavH5dcl9suono42lGCqOZd4ZxwwnPGm88847cc4552BmZgZbt27Fo48+evSJtSw0yv1xViv+e+JArFieZPqcZHCLnpY+T2PcDlktTSmTHNw48eHWQy4nj6+VQU79pax48lrKqxFyrXz+t7RMpuKOI6ApUiuJmnzG8+TpcEuytEhr9SIlswyXks/LEllIE++Mu9MxBoHZ+euijNP3G1dqRa4mIDw7pFRYssTTGANTumlmf6/gOmH5jqrmuq5htLJ4CyXfmc1IZJL4y3rK60Nqw4t/lvp44fUh5bf0ZMRSPvZOpnwyjj0mfawe67wzjhlOaNJ4zz334JZbbsFnP/tZPPPMM3jHO96BK6+8Etu3bz+yhOTaO23QSMUBGlKkDd4yXf9cG1hS+WpxU19qKesHT38cSU2VlZdZDpja4KjJzf8uJb63HGlkUhIqSQQ0C2hK5/yeRlolJAmU71MSVO2ZRsp9WuM+KqQMGmnWpk15eE5a5PnS3vRXlA25DHXOPecEUurBsC6DyKVvmnxclsTS5EcKwvgd1y6MsburQ5LDUVwewLrdMQVoOIR3/2O6HSd3zcRQ3pl0qyOXkYzb8MSv5btNEUbtYyQjIyNjSnBCk8Y77rgDH/3oR/Gxj30Mb37zm/HXf/3XOOuss/CVr3zlyBOTViPZ8UuLkSQD2gkrHNrieZnGOLKgXWs7hv1fzSWMzHMS5ACbIrsccuCUhNXHlYOoBx+0udVm3JSgh+aMW32HRfv5OAue3MWtvWuNvEV5mqYc8iMj9Z7HvaelElqeJq+74b3UAHh4Lzu15SMhk+FySKLkf1MT1sltWF6mKJrfBkDXOuMO9yk+iSY6KYa9z7Bb2mVEldwx7/Wv1L1U3dYIvtRjKC7FcXg6EhpxzNaPDA5Zd/IHRsZJghPWT+NgMMBTTz2F2267Lbp/xRVX4LHHHmuFX1xcxOJicxbtvn37AAAjVAANmwHQGHeyBLcYAaBKtxaE0bAG4B0dyzBAtCvU+gVpWyWCSYRseE9GVT95pskTdROep8MG6qYcfnDzohR2E4G0RPl4wXqUSDO69jK5cK1pPEEiqG7CU23z8WvWQl5MHyCA2H1D8TuReQQ9Gfv+TNEQn1anzNKUkP01rytSF6Es/JmySYXXp7p2077UrntE7F3J8ilC+ncvrZuAc4JdxO8QBqARL5hCmnwejX9E4+okwX+4QMjN9EaA9cc4gim6sHXfZ1c1TrwBgBaBDgGjQbM+sdOxU9Hhw8GLY9uGKQjU7QODoU27AEzHtWMiUBcwhgAzAlUjkGEbaPgmHyKg5gTat0PXRjy51nTL9RdVP/Eueb3z75q3dxKWz/CetPyWgNcT50gI7dHkcySyLEf4cR+rR5KfFuZo46Ugg/E+QH7wLDeWKudyh3u9aUwKcyTPl6Otvd70jiVS8oyRcwR7JCtNKMcJSxpfeeUVVFWFDRs2RPc3bNiAnTt3tsJ/8YtfxBe+8IXW/e/Q/xM3UEr8lc/HPRsX5kjC++taeTZJnnFyp2RIlTmV/1LyTqWppcPzmSSvdm+SfurE/aPFUvW9lGeabEt9h0eCanKQY5KOL1/iKOiQnvZ8pNzjWExcHw20uqe1EYwJl4o7Kc6k9I7m/b+eOEcS91iNh0ea7pH2t0eT36R+5vWkvZQ0jjX3WGr6yx3u9aYxKcyRPF+OtvZ60zuWOJLxVeDAgQOYm5tLPj9hSaMHP9MWsCxY3gOAz3zmM7j11lvD771792LLli3Yvn37WAWciti/fz/OOuss/PznP8eaNWuOtzgnFLJuxiPrJ42smzSybtLIukkj6yaN5dYNEeHAgQPYvHnz2HAnLGlct24dyrJsWRV3797dsj4CQL/fR7/fb92fm5vLlS2BNWvWZN0kkHUzHlk/aWTdpJF1k0bWTRpZN2ksp26WYmA7YTfC9Ho9bN26FQ888EB0/4EHHsBll112nKTKyMjIyMjIyDg1ccJaGgHg1ltvxfXXX49LLrkEl156Kf7u7/4O27dvx0033XS8RcvIyMjIyMjIOKVwQpPGa665Bq+++ir+/M//HDt27MAFF1yAb3/729iyZcvEuP1+H7fffrs6ZX2qI+smjayb8cj6SSPrJo2smzSybtLIuknjeOnG0KT91RkZGRkZGRkZGac8Ttg1jRkZGRkZGRkZGScOMmnMyMjIyMjIyMiYiEwaMzIyMjIyMjIyJiKTxoyMjIyMjIyMjInIpDEjIyMjIyMjI2MippY03nnnnTjnnHMwMzODrVu34tFHHz3eIh1TfPGLX8Rv//ZvY/Xq1Vi/fj3e//7344UXXojCfOQjH4ExJvr39re/PQqzuLiIT3ziE1i3bh1WrlyJq6++Gr/4xS9+nUVZdnz+859vlXvjxo3hORHh85//PDZv3ozZ2Vm8+93vxvPPPx+lMY16AYA3velNLd0YY/Dxj38cwKlVZ/71X/8Vv//7v4/NmzfDGINvfetb0fPlqid79uzB9ddfj7m5OczNzeH666/H3r17j3HpXj/G6Wc4HOLTn/40LrzwQqxcuRKbN2/GH/3RH+FXv/pVlMa73/3uVn269tprozAno34m1Z3lakfTqBut/zHG4K/+6q9CmGmsN0sZs0/EPmcqSeM999yDW265BZ/97GfxzDPP4B3veAeuvPJKbN++/XiLdszwyCOP4OMf/zieeOIJPPDAAxiNRrjiiitw6NChKNx73/te7NixI/z79re/HT2/5ZZb8M1vfhN33303vvOd7+DgwYO46qqrUFXVr7M4y463vOUtUbmfe+658Owv//Ivcccdd+DLX/4ynnzySWzcuBHvec97cODAgRBmWvXy5JNPRnrxJzB98IMfDGFOlTpz6NAhXHTRRfjyl7+sPl+uevLhD38Yzz77LO6//37cf//9ePbZZ3H99dcf8/K9XozTz+HDh/H000/jc5/7HJ5++mnce++9+PGPf4yrr766FfbGG2+M6tNXv/rV6PnJqJ9JdQdYnnY0jbrhOtmxYwe+9rWvwRiDP/iDP4jCTVu9WcqYfUL2OTSF+J3f+R266aabonvnn38+3XbbbcdJol8/du/eTQDokUceCfduuOEGet/73peMs3fvXup2u3T33XeHe7/85S+pKAq6//77j6W4xxS33347XXTRReqzuq5p48aN9KUvfSncW1hYoLm5Ofrbv/1bIppevWj45Cc/Seeeey7VdU1Ep26dAUDf/OY3w+/lqic//OEPCQA98cQTIczjjz9OAOhHP/rRMS7V8kHqR8N3v/tdAkAvvfRSuPeud72LPvnJTybjTIN+NN0sRzuaVt1IvO9976PLL788uncq1Bs5Zp+ofc7UWRoHgwGeeuopXHHFFdH9K664Ao899thxkurXj3379gEATj/99Oj+ww8/jPXr1+O8887DjTfeiN27d4dnTz31FIbDYaS7zZs344ILLjjpdffiiy9i8+bNOOecc3Dttdfipz/9KQBg27Zt2LlzZ1Tmfr+Pd73rXaHM06wXjsFggH/4h3/AH//xH8MYE+6fqnWGY7nqyeOPP465uTm87W1vC2He/va3Y25ubqr0Bdg+yBiDtWvXRvf/8R//EevWrcNb3vIW/Nmf/VlkNZlm/bzedjTNuvHYtWsX7rvvPnz0ox9tPZv2eiPH7BO1zzmhjxE8GrzyyiuoqgobNmyI7m/YsAE7d+48TlL9ekFEuPXWW/G7v/u7uOCCC8L9K6+8Eh/84AexZcsWbNu2DZ/73Odw+eWX46mnnkK/38fOnTvR6/Vw2mmnRemd7Lp729vehr//+7/Heeedh127duEv/uIvcNlll+H5558P5dLqy0svvQQAU6sXiW9961vYu3cvPvKRj4R7p2qdkViuerJz506sX7++lf769eunSl8LCwu47bbb8OEPfxhr1qwJ96+77jqcc8452LhxI37wgx/gM5/5DL73ve+FZRHTqp/laEfTqhuOb3zjG1i9ejU+8IEPRPenvd5oY/aJ2udMHWn04JYSwL4UeW9acfPNN+P73/8+vvOd70T3r7nmmnB9wQUX4JJLLsGWLVtw3333tRopx8muuyuvvDJcX3jhhbj00ktx7rnn4hvf+EZYjH409eVk14vEXXfdhSuvvBKbN28O907VOpPCctQTLfw06Ws4HOLaa69FXde48847o2c33nhjuL7gggvwm7/5m7jkkkvw9NNP4+KLLwYwnfpZrnY0jbrh+NrXvobrrrsOMzMz0f1przepMRs48fqcqZueXrduHcqybDHo3bt3txj7NOITn/gE/umf/gkPPfQQzjzzzLFhN23ahC1btuDFF18EAGzcuBGDwQB79uyJwk2b7lauXIkLL7wQL774YthFPa6+nAp6eemll/Dggw/iYx/72Nhwp2qdWa56snHjRuzatauV/ssvvzwV+hoOh/jDP/xDbNu2DQ888EBkZdRw8cUXo9vtRvVpmvXjcTTtaNp18+ijj+KFF16Y2AcB01VvUmP2idrnTB1p7PV62Lp1azBbezzwwAO47LLLjpNUxx5EhJtvvhn33nsv/uVf/gXnnHPOxDivvvoqfv7zn2PTpk0AgK1bt6Lb7Ua627FjB37wgx9Mle4WFxfx7//+79i0aVOY8uBlHgwGeOSRR0KZTwW9fP3rX8f69evxe7/3e2PDnap1ZrnqyaWXXop9+/bhu9/9bgjzb//2b9i3b99Jry9PGF988UU8+OCDOOOMMybGef755zEcDkN9mmb9cBxNO5p23dx1113YunUrLrrooolhp6HeTBqzT9g+54i3zpwEuPvuu6nb7dJdd91FP/zhD+mWW26hlStX0s9+9rPjLdoxw5/8yZ/Q3NwcPfzww7Rjx47w7/Dhw0REdODAAfrUpz5Fjz32GG3bto0eeughuvTSS+mNb3wj7d+/P6Rz00030ZlnnkkPPvggPf3003T55ZfTRRddRKPR6HgV7XXjU5/6FD388MP005/+lJ544gm66qqraPXq1aE+fOlLX6K5uTm699576bnnnqMPfehDtGnTpqnXi0dVVXT22WfTpz/96ej+qVZnDhw4QM888ww988wzBIDuuOMOeuaZZ8Lu3+WqJ+9973vprW99Kz3++OP0+OOP04UXXkhXXXXVr728R4px+hkOh3T11VfTmWeeSc8++2zUBy0uLhIR0U9+8hP6whe+QE8++SRt27aN7rvvPjr//PPpt37rt056/YzTzXK2o2nTjce+fftoxYoV9JWvfKUVf1rrzaQxm+jE7HOmkjQSEf3N3/wNbdmyhXq9Hl188cWR65lpBAD139e//nUiIjp8+DBdccUV9IY3vIG63S6dffbZdMMNN9D27dujdObn5+nmm2+m008/nWZnZ+mqq65qhTnZcM0119CmTZuo2+3S5s2b6QMf+AA9//zz4Xld13T77bfTxo0bqd/v0zvf+U567rnnojSmUS8e//zP/0wA6IUXXojun2p15qGHHlLb0A033EBEy1dPXn31Vbruuuto9erVtHr1arruuutoz549v6ZSHj3G6Wfbtm3JPuihhx4iIqLt27fTO9/5Tjr99NOp1+vRueeeS3/6p39Kr776apTPyaifcbpZznY0bbrx+OpXv0qzs7O0d+/eVvxprTeTxmyiE7PPMU74jIyMjIyMjIyMjCSmbk1jRkZGRkZGRkbG8iOTxoyMjIyMjIyMjInIpDEjIyMjIyMjI2MiMmnMyMjIyMjIyMiYiEwaMzIyMjIyMjIyJiKTxoyMjIyMjIyMjInIpDEjIyMjIyMjI2MiMmnMyMjIyMjIyMiYiEwaMzIyMjIyMjIyJiKTxoyMjIyMjIyMjInIpDEjIyMjIyMjI2Mi/n/03N1MhksZIwAAAABJRU5ErkJggg==", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "if scat_geometry =='gi_saxs': \n", + " fig, ax = plt.subplots(figsize=(8, 8))\n", + " plt.imshow(avg_img,vmin=0,vmax=2,alpha=1)\n", + " plt.imshow(roi_mask,alpha=.5)\n", + " fp=data_dir + \"%s_ROI_on_Image\" % (uid) + \".png\"\n", + " fig.savefig(fp, dpi=fig.dpi)\n", + " #show_qzr_roi( avg_img, roi_mask, inc_x0, ticks[:4], alpha=0.5, save=True, path=data_dir, uid=uidstr ) \n", + " ## Get 1D Curve (Q||-intensity¶)\n", + " qr_1d_pds = cal_1d_qr( avg_img, Qr, Qz, qr_map, qz_map, inc_x0= None, mask=mask, setup_pargs=setup_pargs )\n", + " plot_qr_1d_with_ROI( qr_1d_pds, qr_center=np.unique( np.array(list( qval_dict.values() ) )[:,0] ),\n", + " loglog=True, save=True, uid=uidstr, path = data_dir)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.7e-05, + "end_time": "2023-06-20T08:53:53.720709", + "exception": false, + "start_time": "2023-06-20T08:53:53.720682", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# GiWAXS Scattering Geometry" + ] + }, + { + "cell_type": "code", + "execution_count": 278, + "metadata": { + "papermill": { + "duration": 0.068797, + "end_time": "2023-06-20T08:53:53.860284", + "exception": false, + "start_time": "2023-06-20T08:53:53.791487", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='gi_waxs':\n", + " show_ROI_on_image( avg_img, roi_mask, label_on = True, alpha=.5,\n", + " save=True, path=data_dir, uid=uidstr, vmin=0.1, vmax=500)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.7e-05, + "end_time": "2023-06-20T08:53:53.867728", + "exception": false, + "start_time": "2023-06-20T08:53:53.867701", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "* Extract the labeled array" + ] + }, + { + "cell_type": "code", + "execution_count": 279, + "metadata": { + "papermill": { + "duration": 0.184571, + "end_time": "2023-06-20T08:53:54.121427", + "exception": false, + "start_time": "2023-06-20T08:53:53.936856", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "calculating correlation functions for 20 Qs\n" + ] + } + ], + "source": [ + "qind, pixelist = roi.extract_label_indices(roi_mask)\n", + "noqs = len(np.unique(qind))\n", + "print('calculating correlation functions for %s Qs'%noqs)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1e-05, + "end_time": "2023-06-20T08:53:54.121592", + "exception": false, + "start_time": "2023-06-20T08:53:54.121582", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "* Number of pixels in each q box" + ] + }, + { + "cell_type": "code", + "execution_count": 280, + "metadata": { + "papermill": { + "duration": 0.258516, + "end_time": "2023-06-20T08:53:54.467645", + "exception": false, + "start_time": "2023-06-20T08:53:54.209129", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Text(0, 0.5, 'number of pixels in ROI')" + ] + }, + "execution_count": 280, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "nopr = np.bincount(qind, minlength=(noqs+1))[1:]\n", + "roi_x = range(len(nopr))\n", + "plt.semilogy(roi_x,nopr,'ro',fillstyle='none');plt.xlabel('ROI #');plt.ylabel('number of pixels in ROI')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.3e-05, + "end_time": "2023-06-20T08:53:54.467774", + "exception": false, + "start_time": "2023-06-20T08:53:54.467761", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Check one ROI intensity" + ] + }, + { + "cell_type": "code", + "execution_count": 281, + "metadata": { + "papermill": { + "duration": 0.514916, + "end_time": "2023-06-20T08:53:55.063776", + "exception": false, + "start_time": "2023-06-20T08:53:54.548860", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "roi_inten = check_ROI_intensity( avg_img, roi_mask, ring_number= 5, uid =uidstr ) #roi starting from 1" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.3e-05, + "end_time": "2023-06-20T08:53:55.066661", + "exception": false, + "start_time": "2023-06-20T08:53:55.066638", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Do a waterfall analysis" + ] + }, + { + "cell_type": "code", + "execution_count": 282, + "metadata": { + "papermill": { + "duration": 0.06989, + "end_time": "2023-06-20T08:53:55.215259", + "exception": false, + "start_time": "2023-06-20T08:53:55.145369", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "qth_interest = 1 #the second ring. #qth_interest starting from 1\n", + "if scat_geometry =='saxs' or scat_geometry =='gi_waxs' or scat_geometry == 'gi_saxs':\n", + " if run_waterfall: \n", + " wat = cal_waterfallc( FD, roi_mask, qindex= qth_interest, save =True, path=data_dir, uid=uidstr)\n", + " plot_waterfallc( wat, qth_interest, aspect= None, vmin=1e-1, vmax= wat.max(), uid=uidstr, save =True, \n", + " path=data_dir, beg= FD.beg, cmap = cmap_vge )\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 283, + "metadata": { + "papermill": { + "duration": 4.682422, + "end_time": "2023-06-20T08:53:59.904224", + "exception": false, + "start_time": "2023-06-20T08:53:55.221802", + "status": "completed" + }, + "scrolled": true, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Get ROI intensity of each frame: 100%|██████████| 1000/1000 [00:06<00:00, 149.13it/s]\n" + ] + }, + { + "data": { + "image/png": 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+nGbJ2Xnl2LFjfE/rihUr2P79+/krCOHh4WzatGk29W3ZsoUBYNu3b3f4vrTEfN4y97ZaXhG788472Y033siKi4ttemDPnDnDevXqxXr37s3eeecdtmPHDrZ06VLm5eXFZs2aZbWPWbNmMa1Wy3744Qf2ww8/sKVLlzIfHx/24osvWpXr3bs3k8lkTKlUsg0bNrDt27ezadOmMQBsz549Lb6W5m0098j16dOHPfLII2z79u3svffeY8HBwWz06NF8uezsbNanTx+mVqv580t2djZjzHRFQqVSMalUyl599VW2Y8cO9vrrr7OgoCA2ZswYq6sUAFh0dDSLiYlhn376Kdu6dSuLi4tjHh4erLCwkC83fvx41r17d7Zu3Tq2e/du9uWXX7KFCxeyTz75xOq4WJ579+/fz3x8fNjNN9/Mt9H8+ZgyZQqLioqy+VuaNm0ai4yMZAaDweF7du7cOdazZ0/WvXt3tnbtWrZt2zb28MMPMwD8VRBn52BHXP1+fvvtt9nKlSvZ119/zfbs2cPWr1/PhgwZwvr378/q6ur4crm5uczf359FR0eztWvXsszMTPbRRx+x6dOns/Ly8lYdb0cc9cA+9dRTDAA7fPgwv2zFihUMAPvuu+8c1rd161YGgK1cuZJf1pYeWApgLTQPYP/v//6PcRzHfwGZxcfH2wSw5vpaeli2Ze/evQwA+/jjj23aZ/4QnD592u7rqq+vZwaDgc2ePZup1Wp++f79+xkA9sorr1iVP3nyJPPx8XGallBeXs4UCgXr1asXq6iosFlvrtv8uPnmm/k/EEt33HEHu+666/gTmL0ANj8/nwFgjz/+uNXyjRs3MgBOA9jvvvvO5sPfEkeXUGJjYxkA9tVXX1ktv//++5lIJGL//vuv3fpaG8DeddddzMPDgx06dMil8hUVFSw6Opo999xz/LLWXIK+//77mZeXl926r7nmGjZu3Dib5ePHj+ePbWBgINu8ebNLbTVbu3Yt8/Ly4usICQlhP/zwg1WZJUuWMAA2yy29/fbbDo+JvQDW3g+u5cuXMwBWwbM9rfkcmt+fbt26sWeeeYbt3LmTrV27loWGhrJ+/fqxqqoqvmxrjl9ycjJLS0tje/bsYV9++SW76667GACb9Jj+/fszb29vFhAQwFasWMF27drFXnrpJebj48Ouv/56h2kNrUkhcHReac78Y2fDhg1MLBazsrIyxhhjpaWlTCQSsdmzZ1uVP3bsGP+5aH5Oc+W8Yv5h/dlnn1ktl0gk7IEHHrBpnzmQ3rRpU4uv2RHL89aiRYtYeHg4MxgMrLS0lHl5ebEPPvjAbgD7wAMPMH9/f5tzx6pVqxgAh+k75vd0yZIlLDQ01Op49u7dm3l7e1vVWVNTw0JCQuy+/uYcBbDJyclW5V566SUGgJ05c4Zf5iiFYOXKlUwkEtmcUz///HMGgG3dutVq/z169LA6rkVFRUwkElmdx/39/dljjz3m9LXY+053lEJg/txkZGTwy3Q6HfPw8LD5kdCcuROgedrZ3LlzGcdx7I8//uCXuRp8tfX72Wg0MoPBwP7991+bc+OYMWNYt27d2Llz5xzutzXH2x5zfFNUVMQMBgM7f/48+/TTT5mfn59NZ8iDDz7IALCCggKH9ZnPu5bpUJRC0MF27dqFAQMGYMiQIVbLExMTbcrOmTMHBw8ebPHxzTff2Gzr7HKk5brPPvsM119/Pfz9/eHh4QGJRAKtVov8/Hy+zJYtW8BxHGbOnIn6+nr+ER4ejiFDhji8mUOv1+P222/Hv//+i88++8zund2DBg3CwYMHsWfPHrz++uvIyclBfHy81aXaL774At988w3effddp69r165dAIC77rrLavn06dNbvGyt1Wrh4eFhkwbAGLN6zc0v1zkSEBCAyZMnWy1LTEyE0WjEjz/+6FIdzixYsAAbN27E6tWrMWzYMH650Wi0aqtlysKzzz4LiUSChQsXtnm/rn6uzNasWYNffvkFX331FcaPH48777wTH3/8sUvtff/99/Hoo4/i4Ycfxo4dO7B161aMGzcOt956K7Zv386X++6773DNNdfgpptucti2Xbt2OTwmjjT/HJnLmj9njtrems+h+bLhnXfeif/9738YPXo0HnjgAWi1Whw7dgybNm3iy7bm+L311lvQaDS48cYbceutt+Kjjz7Cww8/jI8++sjq5jCj0Qi9Xo/nn38ezz33HOLi4vD0009j5cqV2Lt3b5vvvHflvAIAOTk5mDx5MkJDQyEWiyGRSHDPPfegoaEBf/75JwAgJCQEd911FzZs2IB33nkHZWVl+O2333DXXXdBLBYDsE1vcOW84owrn3NHx9/ZZ9qSRqPB2bNn8d1332Hjxo3w9PTEtGnT7JbdsmULRo8ejcjISKu6J06cCADYs2cPX3bnzp246aabEBQUxL+nCxcuRGlpKc6dO2dVr0qlQlRUFP/c29sb11xzDf79918X3iX7mv+NDR48GABcqnPLli0YOHAgVCqV1escP3683VF6Ro8ebXXjbI8ePRAWFma1r5iYGHzwwQdYtmwZDhw44PBGWVfFxcVhyJAheOutt/hla9euBcdxmDNnjtNtd+7cCaVSiZiYGKvls2bNAmMMO3fubHV7WvP9fO7cOTz44IPo1asX/3fZu3dvAOD/Nqurq7Fnzx5Mnz7dpRu+23O8ASA8PBwSiQTBwcGYPn06hg0bhvXr17u0rSXWmCLjaiqWIxTAOlFaWorw8HCb5Y6WqVSqFh9KpZLfJjQ0lN9Pc2VlZeA4Dt26dQMAbN68GdOnT0fPnj3x0UcfYf/+/Th48CCSkpKg1+v57c6ePQvGGHr06AGJRGL1OHDggN38mdraWkyZMgU///wzvv76a4wcOdLu++Hn54fhw4fjxhtvxLx585CRkYGsrCy88847AIDKyko89NBDeOSRRxAZGYkLFy7gwoULqKurA2DKfTTnRplfc/P30sPDg39f7CkpKcHXX3+NSZMm2Wy7fv16m9fsCnt3QprrtndsWuPFF1/EsmXLsHz5cjz88MNW65YsWWLV1r59+wIAfvnlF6SmpuKll16CXq/n30fzl+2FCxdscpuaCw0NhV6vtxsElJWVISQkxGb51VdfjREjRmDy5Mn49NNPMXbsWDz00EN84JaUlGTV3rFjxwIAzp8/j4ceegj33XcfVq1ahbFjx2LixIn4+OOPMWLECKvhoIqLi1u8G7q0tNTpMWnO3mem+fFz1PbWfA7Nz8ePH2+13PyFnZ2dDaBjjp85Z/vAgQMt7t8cGJn33xqunldOnDiB//znP9DpdHj99dfx008/4eDBg3xgUFNTw5d9++23ceeddyI5ORmhoaFQq9WQy+WYNGkSvLy8bN7Xls4rzoSGhjo8fwLgP+eOjr+jv8HmevfujbFjxyItLQ1paWmYMWMGfH197ZY9e/YsvvnmG5tz0YABAwCAPwf/8ssvGDduHADg3Xffxd69e3Hw4EG88MILNu+p+bU25+XlZVOuNZrX6eXlZXff9pw9exa//fabzesMCAgAY8zmu8aV9qenp+Pee+/Fe++9x+dN33PPPU7z31syb948ZGZm4o8//oDBYMC7776LqVOnOjyfmJWWltodTSAyMpJf31qufj8bjUaMGzcOmzdvxjPPPIPMzEz88ssv/PnA/J6dP38eDQ0NLo8w0Z7jDZhyvw8ePIjt27fjjjvuwI8//ohHHnnEqoz5R9Y///zjsB5zjnCvXr1c2q8jV/wwWt7e3na/LFoavxQwHWx7fzj2li1ZsgQvvvhii3X27t2bP3h9+/aFj48Pfv/9d5tyv//+Oz+0DGC6Keqqq65Cenq61a+W5q9NKpWC4zj89NNP/IfTUvNltbW1uO2227Br1y589dVX/IndFcOHD4dIJOJ7X0pKSnD27Fm88soreOWVV2zKBwcH49Zbb8WXX37J/yEVFRWhZ8+efJn6+nqnJ4YPP/wQdXV1dm/euuWWW3Dw4EGX229mmYBuZj7GzoLplrz44otYvHgxFi9ejOeff95m/Zw5c6zGvTMfm7y8PDDGMGXKFJttTp48ieDgYKxevdrpWIODBg0CYPocWf4gKSoqQklJiUtj38bExGDbtm0oLi5Gjx49sHjxYqsg3Nyb8scff6CmpgYjRoywqWP48OHYs2cPKisr4e/vj+7du+PUqVNO9xsaGmr3JipHX2Lmz4zlsWp+/By1vTWfw8GDBzsdc9jcs9gRx8/cQ2HZWzl48GCrgNZZWVe5el758ssvUVVVhc2bN/O9QAD4sVgt+fn54cMPP8Qbb7yBkydPIjIyElKpFHK5HNddd12LV1ian1ecGTRokMPzJwD+c+7o+Dv6G7QnKSkJM2fOhNFoxNtvv+2wnFQqxeDBg7F8+XK7680B0CeffAKJRIItW7ZY3ejozvFMW0MqlcLHx8fhjWRSqbRNdb722mt47bXXcOLECXz99dd49tlnce7cOWzbtq1N7UxMTMT//d//4a233sK1116LoqIiPPTQQy1uFxoaandMdPNNT219fa58Px85cgS//vorPvjgA9x77738+mPHjlmVDwkJgVgsbvGc2lGGDBnCv+74+HiMHz8e69atw+zZs/nzf3x8PJ5//nl8+eWXDoe4NH/G4+Pj29WeKz6AjY6Oxrlz53D27Fm+V6eurs7qsqYjo0ePxksvvYRff/3VKo3A8lKhWfMToSOWH1oPDw/ccsst2Lx5M1566SX+pHrixAns2rULjz/+OF+W4zh+AH6zoqIim7uFExISkJKSAp1Oh+nTpztti7nndefOndi8ebNNz05L9uzZA6PRiH79+gEw9WKZL8laSklJwZ49e/Ddd9/xH37zXcQbN260uqz+6aefOr30r9VqERkZyfc6WQoNDW1TwFlRUYGvv/7a6vLKpk2bIBKJcOONN7a6PgBYunQpFi9ejPnz52PRokV2y0RGRvJfZpYmTJhg932cMWMGrrrqKqxcuZJ/zx2ZMGECvL298cEHH1gFsOa7j1saL5Exhj179qBbt278exodHW13RA/zazhw4IDVyZYxhgMHDiA4OBh+fn4ATL2FCxcuxM6dOx2Ohzt69Gh8+umndo+JIxs3brS6099c1vw5c9T21nwOp0yZghdeeAHfffedVXD63XffgTGGa6+9FkDHHL8NGzYAAF8nANxxxx1Yt24dvvvuO6jVan65ecIJy7KucvW8Yl5vef5ijZNXOBIcHMyP+fr111/jjz/+wP/+978W29T8vOLMlClTkJycjKysLP5zXl9fj48++ggjR47kP5vOPrv2/gYd7WvKlCkICgpy+l4nJCRg69at6Nu3r9WYt81xHAcPDw8+tQIw9YR9+OGHLrXncnHUy5uQkIAVK1YgNDQUV111VYfvNyoqCg8//DAyMzOxd+/eNrURMHVizZkzB2+++Sb27dsHlUqF66+/vsX9jx07FitXrkR2djaGDh3KL9+wYQM4jsPo0aNb94Lg+vezvb83ADZXJXx8fBAbG4vPPvsMy5cvb1NQ3VYcx+Gtt96CUqnE/Pnz+Zhq+PDhGDduHLRaLe6++26b9/rnn39GWloaJkyYYHXObYsrPoC98847sXDhQsyYMQNPP/009Ho93njjDYe5TpYee+wxpKWlYdKkSVi2bBl69OiBjRs3Wg33Y9aaE6GlF198ESNGjEBCQgKeffZZfiIDqVSKJ598ki+XkJCAzZs3Izk5GVOnTsXJkyexdOlSRERE4K+//uLLXX/99ZgzZw40Gg0OHTqEG2+8EX5+fjhz5gx+/vlnDBo0CHPnzgUATJ06Fd999x1eeOEFhIaGWvXuBAYG8ukOW7ZswbvvvovJkyejd+/eMBgMOHToEF577TX069eP7w319vbmAwJLH3zwAcRisdU6hUKBmTNn4rXXXoNEIsFNN92EI0eOYNWqVQ4HfM/KysLRo0fx/PPPW5302ys0NBRz587FiRMncM0112Dr1q149913MXfuXKucs7y8POTl5QEwfclXV1fj888/BwAolUr+/XrllVewcOFCTJgwAZMmTbLpNWsp0AgPD7d7ecvb2xuhoaF23+PmQkJCMH/+fCxYsAAhISH8RAaLFy/GfffdZ5XKcuutt2LIkCFQqVQIDQ3F6dOn8cEHH2DPnj146623Wuwxi4qKwu23345169bBy8sLN998M2pra7F+/Xrs3bsXS5cu5U/Ijz32GNLT03Hrrbfi2WefRUxMDGpqarBnzx4kJCRg9OjRuOeee7B69Wrcc889WL58Oa6++mps3brV4Y9OT09PvPLKK6isrMSIESOwb98+LFu2DBMnTrQ7jIul1nwO5XI5HnroIaSmpiIgIAATJ07En3/+ifnz50OtVvNfSK05fps2bcLmzZsxadIk9O7dGxcuXMBnn32GTz75BLNmzbL64Txu3DjccsstWLJkCYxGI6699locOnQIL774IhISEqxea3FxMZ9rae6N/O6779C9e3d0796dH+Df1fNKfHw8PD098d///hfPPPMM9Ho93n77bZw/f97mdX7xxRc4ffo0FAoF9Ho9du/ejddffx0PPvggbr31Vr6cq+cVZ5KSkvDWW29h2rRpSElJQVhYGFJTU/HHH39YDb3UEby9vfm/d2eWLFmCH374Addddx3mzZuH/v37Q6/X4/jx49i6dSvWrl0LmUyGSZMm4dVXX0ViYiLmzJmD0tJSrFq1ymkvsDsMGjQIn3zyCdLT09GnTx94e3tj0KBBeOyxx/DFF1/gxhtvxOOPP47BgwfDaDTixIkT+P777/Hkk086TEez5+LFixg9ejQSExMhl8sREBCAgwcPYtu2bS1OhDJo0CDs3r0b33zzDSIiIhAQEID+/fvz65OTk/HSSy/h8OHDeO+991xqz+OPP44NGzZg0qRJWLJkCXr37o1vv/0WqampmDt3Lq655hqXX5uZq9/Pcrkcffv2xbPPPgvGGEJCQvDNN9/ghx9+sKnz1VdfxQ033ICRI0fi2WefRb9+/XD27Fl8/fXXeOedd1o9YU9rXH311ZgzZw5SU1Px888/8+egDRs24KabbsK4ceMwb948/sruzp078frrr0Mul3fM7G6tuuVLoLZu3cpUKhXz8fFhffr0YW+++aZLoxAwxlheXh6Lj49n3t7eLCQkhM2ePZt99dVXHTaRAWOMHTp0iI0dO5b5+vqywMBAdtttt/HDPFlKSUlh0dHRzMvLiykUCvbuu+/afR2MMZaWlsZGjhzJ/Pz8mI+PD+vbty+75557rO6Ch5PREizvOs3Pz2dTp07l74T19vZmcrmcPf3006y0tLTF1+doGK3a2lr25JNPsrCwMObt7c2uvfZatn//focTGdx///2M4zirYVdc5WwUggEDBrDdu3ez4cOHMy8vLxYREcGef/55myFWnI00YXmHr3lkA0ePtmrLQPivv/46u+aaa/ihphYtWmQ1BAtjjP3vf/9jI0aMYMHBwUwsFrPQ0FA2fvx4l4fQYsx0R/TLL7/MBg8ezAICAlhISAi79tpr2UcffWRzd/z58+fZo48+yqKiophEImFhYWFs0qRJVnetnjp1it1xxx3M39+fBQQEsDvuuIO/s9zeRAa//fYbi4uLYz4+PiwkJITNnTvX7hBi9rTmc1hfX89SUlJYv379mEQiYREREWzu3Lns/PnzLe7H3nHav38/Gzt2LAsPD2cSiYT5+vqyESNGsNTUVKvJCMyqq6vZ//3f/7FevXoxDw8PFhUVxZ577jmbYXvMd1+39LfNmOvnlW+++YYNGTKEeXt7s549e7Knn36aHxHE8lyYkZHBVCoVf+4ZPnw402q1Np+D1pxXHI1CwJjpbvZ77rmHhYSE8MfP2SgXrnJlkgx7oxCYl8+bN49dddVVTCKRsJCQEDZs2DD2wgsvWH0u09LSWP/+/ZmXlxfr06cPW7lyJdNqtTajRjj6G4+NjXVpkoHmbXR0PrQ3Sc/x48fZuHHjWEBAgM1IOpWVlWz+/Pmsf//+zNPTkwUFBbFBgwaxxx9/3GpIKDgYltDyb0yv17MHH3yQDR48mAUGBjIfHx/Wv39/tmjRIqsRPuyNQpCbm8uuv/565uvra/czzhhjcXFxLCQkhFVXV7f4fpn9+++/LDExkYWGhjKJRML69+/PXn75ZZu/zdbeQe/K97M59ggICGDBwcFs2rRp7MSJE3Y/b3l5eWzatGksNDSUP9fPmjWLPy+05njb42gYLcZMw2b6+/vbDMdVWVnJVqxYwVQqFfP19WW+vr5s8ODBbNmyZXbPzW0ZhYBjrNmIyYQQQgghV4hz586hd+/eeOSRR/hpTYnwXfEpBIQQQgjpek6dOoW///4bL7/8MkQiER599FF3N4l0IBpGixBCCCFXnPfeew9xcXE4evQoNm7caDXSCBE+SiEghBBCCCGCQj2whBBCCCFEUCiAJYQQQgghgkIBLCGEEEIIEZQrfhQCo9GI06dPIyAgwGq2GUIIIYQQ0jkwxlBRUYHIyEiXpsa+4gPY06dPo1evXu5uBiGEEEIIacHJkychk8laLHfFB7DmadROnjzpcIpSQgghhBDiPuXl5ejVq5fL099e8QGsOW0gMDCQAlhCCCGEkE7M1XRPuomLEEIIIYQIyhXfA+tMQ0MDjEaju5vhViKRCGKx2N3NIIQQQghxWZcMYBljuHDhAmpqatzdlE7Bx8cH3bp1o1EaCCGEECIIXTKAra+vR01NDfz9/eHt7d1lAzfGGPR6PSorK+Hv7w+JROLuJhFCCCGEtKhLBrBmPj4+XT5o4zgOlZWV7m4GIYQQQojLunQA66qGBuCnn4AzZ4CICOA//wEobZQQQgghxD1oFIIWbN4MREcDo0cDiYmm/0dHm5a3h0QigUqlgkKhQGJiIgwGA78uMzMTarUacrkcKpUKmZmZ/Lq4uDgUFBTY1Ldy5UpERUUhPDy8fQ0jhBBCCOnkKIB1YvNmYOpU4NQp6+U6nWl5e4LY0NBQ5Obm4siRIygqKkJ6enpj3TpoNBps3LgRBQUF2LRpEzQaDXQ6ndP64uPjceDAgbY3iBBCCCFEILp8AMsYUFVl+ygvB+bNM623tw0APPqoqZy97e1tZ49YLEZMTAwfoKampmL27NlQKpUAAKVSiaSkJKSmpjqtZ/jw4YiMjHT5dRNCCCGECFWXD2CrqwF/f9tHUJCpp9URxkw9s0FB9revrnZt/3q9Hnv37sX48eMBAHl5eVCr1VZl1Go18vPz2/oSCSGEEEKuKF0+gHWX0tJSqFQqSKVSBAcHQ6VSubtJhBBCCCGC0OUDWF9foLLS9rF1q2vbb91qf3tfX+fbmXNgjx8/jsLCQmRkZAAAFAoFsrOzrcrm5ORAoVC05eURQgghhFxxunwAy3GAn5/tY9w4QCYzrXe0Xa9epnL2tnd1bgSpVIqUlBSsWrUKAJCcnAytVou8vDwAQH5+PrRaLebOndsRL5cQQgghRPC6fADriFgMvP666d/Ng1Hz89de65jxYBMSElBVVYWsrCzIZDKkpaUhMTERcrkcM2bMgFarhUwmc1rHsmXLIJPJUFxcDJlM1uJNX4QQQgghQsUx5ur98sJUXl6OoKAgXLx4EYGBgQAAg8GA4uJidO/evcWZuDZvNo02YDmUVq9epuD19tsvYcMvk9a8F4QQQgghl4K9eM0ZmomrBbffDtx6K83ERQghhBDSWVAA6wKxGIiLc3crCCGEEEIIQDmwhBBCCCFEYCiAJYQQQgghgkIBrKuWLgVEItP/CSGEEEKI21AOrCuWLgUWLjT92/z/BQvc1x5CCCGEkC6MemBbYhm8mi1c2O6eWIlEApVKBYVCgcTERBgMBn5dZmYm1Go15HI5VCoVMjMz+XVxcXEoKCiwqstoNOKWW26BXC7HwIEDaQxYQgghhFzRKIB1xl7watbOINY8leyRI0dQVFSE9PR0AIBOp4NGo8HGjRtRUFCATZs2QaPRQKfTOa1v3rx5KCgowC+//IK33noLx48fb3PbCBEKZmTYtWgXjn521N1NIYQQchlRAMsYUFVl+1iwwHHwarZwoamcve1dnB9CLBYjJiaGD1BTU1Mxe/ZsKJVKAIBSqURSUpLTXlWRSIT4+HgAgK+vL/r27YvTp0+7tH9CBI0Dio8WY8sDW1CUW+Tu1hBCCLlMKICtrgb8/W0fy5a5tv2yZfa3r652aXO9Xo+9e/di/PjxAIC8vDyo1WqrMmq1Gvn5+S7Vd+rUKfz6668YMmSIa+0nRMA4jsOY5WOgP6/HO+p3cCb7DP+oOFPh7uYRQgi5ROgmLjcpLS2FSqXCsWPHMGbMGKhUqnbXWVdXh//+97945ZVX4Ofn1/5GEiIAtRdr+X+vG7aO/3fsoljELY5zQ4sIIYRcatQD6+sLVFZaP+bPb10d8+fb1uHr63QTcw7s8ePHUVhYiIyMDACAQqFAdna2VdmcnBwoFIoWm3HffffhpptuwtSpU1vXfkIErKashv/3/Qfvx5zDczDn8BwMe2CYG1tFnKHcZUJIe1EPLMcBzXsrly4FPD1bzoEFgCVL2jWkllQqRUpKClJSUjBlyhQkJydj1KhRmD59OpRKJfLz86HVarF//36n9SxbtgwGgwELXWkzIVcIxhj2vrSXf95jcA+IPcVubBFxSWPu8qHUQ4iOjYZfGF0xIoS0DvXAOrJggSk4daadwatZQkICqqqqkJWVBZlMhrS0NCQmJkIul2PGjBnQarWQyWQOt6+oqMDChQuRm5sLtVoNlUqFHTt2tLtdhHR6DAjuE8w/NdYb3dgY4iqO43DzmzdDf0GPN+VvUu4yIaTVqAfWGXNwaq9Xs53Ba1FR0x3THMchNzeXfx4fH2/13NLu3bttlgUEBMBopC9u0vVwIg5D7xuKHG0OAApghaSusg7GeiP05/WUu0wIaTUKYFtiL4jtoJ5XQkj7MYsh6xoMDW5sCWkNQ3XT5C13/3A3fEJ8AAD+Ef7uahIhREAogHWFOVhdtAh48UUKXgnpRJixKYClHlhhYIwh8/mmGQaDegch9OpQN7aIECI0lAPrqgULAKORgldCOhnLoJUCWIFgQGj/poDVcig0QghxBQWwhBBBMxoogBUaTsRh1BOj+Oe15RTAEkJahwJYQoigUQ+sMFmmfugv6t3YEkKIEFEOrBMnARQ7WR8GwPHgVoSQy8Hyxi0KYAWkKX6lFAJCSKtRD6wDtQBGABjm5DGisVxbSCQSqFQqKBQKJCYmwmBouiM3MzMTarUacrkcKpUKmZlNNzvExcWhoKDApr6kpCQMGTIEgwYNwty5c2lYLdJlUA+sMBkbmo4VpRAQQlqLAlgHPAFEwfEbJALQq7FcW5inkj1y5AiKioqQnp4OANDpdNBoNNi4cSMKCgqwadMmaDQa6HQ6p/W9/vrr+PXXX/H777+jtLQU3377bRtbRoiwUA6s8JXryt3dBEKIwHT5AJYBqLLzqAbwAgBHX4fGxvXVDrZnDrZrTiwWIyYmhg9QU1NTMXv2bCiVSgCAUqlEUlISUlNTndYTEBAAAKivr4der7caG5OQK5lVCoGBAlgh+v2j32k2LkJIq3T5ALYagL+Dx20tbHubk22rXdy/Xq/H3r17MX78eABAXl4e1Gq1VRm1Wo38/PwW67rrrrvQo0cP+Pn5ISEhwcUWECJslEIgTJY3cVWcrsC6Yev4x+F3DruxZYQQIaCbuNyktLQUKpUKx44dw5gxY6BSqdpd58aNG1FXV4dZs2YhMzMT8fHx7W8oIZ0cpRAIlMVFIr8efrhr6138c5qNixDSki7fA+sLoNLJowLAUADixvLixucVLWzn28J+zTmwx48fR2FhITIyMgAACoUC2dnZVmVzcnKgUChcej2enp6444478OWXX7pUnhCho1EIhMnyRtPouGhEDI3gHwERAW5sGSFECLp8AMsB8HPy8AewAoD5K7Kh8bl/C9txLu5fKpUiJSUFq1atAgAkJydDq9UiLy8PAJCfnw+tVou5c+c6rIMxhsLCQgCmL4Vvv/0WcrncxRYQImyUQiBQFodKJO7yX0WEkFais4YLxsE0ZBYa/z+ug+tPSEhAVVUVsrKyIJPJkJaWhsTERMjlcsyYMQNarRYymeMRZxljuOeeezBo0CAMHjwYXl5eePDBBzu4lYR0TpRCIHyWveiEEOIKyoF1AQdTr+u8xv+72rvqTFFRUVP9HIfc3Fz+eXx8vNVzS7t377ZZJhKJsHfv3g5oFSHCQykEwmQ5UgqNHkEIaS0KYF10E4A8dzeCEGLDMmilnjwBsbiJq6GOjhshpHUohYAQImiUQiBMlj2w9MODENJaFMASQgSNbuISJstxYKkHlhDSWhTAEkIEjXJgBcoihYByYAkhrUUBLCFE0CiFQJisUgioB5YQ0koUwLpox987oHxLiR1/7+iQ+iQSCVQqFRQKBRITE2EwGPh1mZmZUKvVkMvlUKlUyMzM5NfFxcWhoKDAYb1Tp07Ftdde2yFtJEQIKIVAoCxv4qIcWEJIK1EA6wLGGJ7PfB75Jfl4PvN5q56DtjLPxHXkyBEUFRUhPT0dAKDT6aDRaLBx40YUFBRg06ZN0Gg00Ol0Ldb5ww8/QCwWt1iOkCsJpRAIEw2jRQhpjy4fwDLGUFVX5fTx9R9f4+DpgwCAg6cP4us/vm5xG1eDXLFYjJiYGD5ATU1NxezZs6FUKgEASqUSSUlJSE1NdVqPwWDAihUrMH/+/Ha8G4QIBzMy7Fq0C6V/lvLLKBASDrqJixDSHl1+HNhqQzX8V/q3apvb0m9rsUzlc5Xw8/RrsZxer8fevXuxZs0aAEBeXh40Go1VGbVajfXr1zut59VXX8W9996LgACaQ5x0ERxQfLQYJ/ee5BdRD6yAUAoBIaQdunwPrLuUlpZCpVJBKpUiODgYKpWqzXXpdDp8//33uPfeezuugYR0chzHYVLqJKtlF/69gDPZZ1BxpsJNrSKuopu4CCHt0eV7YH0lvqh8rtLuOsYYYtfH4teiX9HAmk6wYk6MIeFDsOfePeA4+xPL+kp8ne7XnANbUlKC2NhYZGRkYMqUKVAoFMjOzsbkyZP5sjk5OVAoFA7rys3NRV5eHq666irU19ejuLgYkydPxtdff+20DYQInV+YH/y6+6H8VDkA4Jc3fsEvb/yC2EWxiFsc597GEedoGC1CSDt0+QCW4ziHl/q3H9uO7DPZNssbWAOyz2Rj78m9GN9vfLv2L5VKkZKSgpSUFEyZMgXJyckYNWoUpk+fDqVSifz8fGi1Wuzfv99hHZMmTcKZM2cAAMePH8eMGTMoeCVdQtW5KlSdq+KfD3tgGIbNGQb/iNalBZHLzyoHllIICCGtRCkEDjDGsGDXAogcvEUiiLBg14IOGZEgISEBVVVVyMrKgkwmQ1paGhITEyGXyzFjxgxotVrIZLJ274eQKwljDN8mf2v1N+gX5oeIoREIiKBc8M6OUggIIe3R5XtgHalrqMOJiydghP1LW0YYcbL8JOoa6uDl4dXq+ouKivh/cxyH3Nxc/nl8fLzVc0u7d+92Wm90dDQOHDjQ6vYQIjgMCBsYhrJjZTj761kAgP6i3s2NIi6jFAJCSDu4NYD98ccf8fLLL+Pw4cM4c+YMMjIycNttt9kt+8ADD2DdunVYvXo1HnvssUveNi8PLxy8/yCKq4sdlgnzC2tT8EoIaT9OxCFucRxO/HyCX5b/RT5U96r45/4R/tQb20lZjQNbbwRjzOE9BYQQ0pxbA9iqqioMGTIEGo0Gd9xxh8NyX375JbKyshAZGXkZWwf0CuqFXkG9Lus+CSGtY9l7V6GrwLph6/jndDNXJ9Ys+8poMELsSROxEEJc49YAduLEiZg4caLTMjqdDg8//DC2b9+OSZMmOS1LCOl6LMd+DYgMwH+/+S//nG7m6rwsb+ICTHmwFMASQlzVqXNgjUYj7r77bjz99NMYMGCAS9vU1taitraWf15eXn6pmkcI6QTq6+r5f19zyzWIGBrhxtYQVxkbrPNeaSQCQkhrdOpRCP73v//Bw8MD8+bNc3mblStXIigoiH/06kUpAIRcySxTCCS+Eje2hLQH3chFCGmNThvAHj58GK+//jo++OCDViX2P/fcc7h48SL/OHnyZMsbtQFjDA11dZekbkKI61hD06XojhjWjrjH6cOncSb7DM2kRghxSacNYH/66SecO3cOUVFR8PDwgIeHB/799188+eSTiI6Odridl5cXAgMDrR4diTGG0z//jO0zZuCrm25CVeMEAq0lkUigUqmgUCiQmJgIg8HAr8vMzIRarYZcLodKpUJmZia/Li4uDgUFBTb1xcXFQaFQQKVStWtaWkKExurSM8WvgtE8B3bTzZuwbtg6rBu2DoffOeymVhFChKLT5sDefffduOmmm6yWjR8/HnfffTc0Gs1lbw9jDGf27sVva9ag7MgRgOMAxlB7/jz8Ilqfc2eeSrahoQHx8fFIT0/HzJkzodPpoNFosG3bNiiVSuTl5WHChAnYv38/evbs6bTOjIwMyOXytr5EQgTJ8iYuIiDNfmzc+eWdCOoVBIBuviOEtMytAWxlZSWOHTvGP//nn3+Qm5uLkJAQREVFITQ01Kq8RCJBeHg4+vfv32FtYIyhoabG6fqzBw7g97VrcT4vD5xIZF4BAGjQ61FfXW2zndjHx6XUB7FYjJiYGOh0OgBAamoqZs+eDaVSCQBQKpVISkpCamoqli9f3tqXR8gVzzJ3klIIhMNotP7hIZVLIe0vdVNrCCFC49YA9tChQxg9ejT//IknngAA3Hvvvfjggw8uSxsaamrw6YgRLpdnzU66P9x9t91y0w8ehIevb4v16fV67N27F2vWrAEA5OXl2fQwq9VqrF+/vsW67rzzTojFYtx3331ITk5usTwhVwJKIRCoZh3nzVMKCCHEGbcGsHFxca3qMTl+/Pila8xlVlpaCpVKhWPHjmHMmDHtzlvdtGkTIiMjUVZWhokTJ2LAgAGIjY3tmMYS0olRCoFANbtAZXkzHiGEtKTT5sBeLmIfH0w/eNDuurNZWfgtNZVPHWje+woA8R9+iGA7eadiHx+n+zXnwJaUlCA2NhYZGRmYMmUKFAoFsrOzMXnyZL5sTk4OFAqF0/rMs5SFhIRg+vTpOHjwIAWwpEugFAJhat7j2nxcWEIIcabTjkJwuXAcBw9fX7uPnqNHY8KnnyLunXcQ3JiTyufANhJ7e9vd1tWhv6RSKVJSUrBq1SoAQHJyMrRaLfLy8gAA+fn50Gq1mDt3rsM66uvrUVJSAsA0kcO2bdtcnviBEKGjFAKBanasqAeWENIaXb4HtiUcxyHyhhsQcf31dkch6AgJCQlYsGABsrKyMHLkSKSlpSExMRF6vR5eXl7QarWQyWQOt6+trcX48eNRX1+PhoYGTJs2rcUpegm5UlAKgTA17y2nHFhCSGtQAOsie4FsdVERvENC2lRfUVGRVd25ubn88/j4eKvnlnbv3m2zzM/PD4cP07iJpGuiFAKBanaoKIWAENIaFMC2kmUgazQYIPb0dHeTCOmymJFZ99xR/CoYzXtcKYWAENIaXT4Htq04jqPglRA3o/QB4WreW049sISQ1qAAlhAiWFY3cIFSCASl+U1clANLCGkFCmAJIYJFPbDCZXMTF6UQEEJagQJYQohgWd7ABYByYAWExoElhLQHBbBO1NbW0iVJQjoxSiEQMEohIIS0AwWwDpw8eRK9e/fGyJEjsX379g7/YpRIJFCpVFAoFEhMTITBYODXZWZmQq1WQy6XQ6VSITMzk18XFxeHgoICm/pqamowc+ZMyOVyKBQKHDlypEPbS0hnRCkEwkUpBISQ9qAA1oHi4mKcPXsWhw8fxoQJEzo8kDVPJXvkyBEUFRUhPT0dAKDT6aDRaLBx40YUFBRg06ZN0Gg00Ol0TutbsmQJhg4dioKCAuTk5KB3794d0k5COjNKIRAwGgeWENIOXT6AZYyhqqrK5lFTUwMAMBpNJ9Xs7GxMmDABw4cPx1dffYXKykq725kfrga6YrEYMTExfICampqK2bNnQ9k4da1SqURSUhJSU1Od1pOeno5HHnkEAODt7Y2AgIA2vR+ECAmlEAgX9cASQtqjywew1dXV8Pf3t3nccMMNVuUaGkxflNnZ2bjtttsQEBBgdzvzo7q62qX96/V67N27F+PHjwcA5OXlQa1WW5VRq9XIz893WMf58+fh6emJRx55BGq1Gg8++CBqa2tb8zYQIkiUQiBcNhMZUA4sIaQVunwA6y6lpaVQqVSQSqUIDg6GSqVqc1319fX4448/cOuttyI7OxsNDQ14++23O66xhHRCzMiQ9UZWs4XuaQtpA0ohIIS0Q5cPYH19fVFZWWnz+Pnnn+2WF4vFAIChQ4fim2++sbttZWUlfH19ne7XnAN7/PhxFBYWIiMjAwCgUCiQnZ1tVTYnJwcKhcJhXVKpFIGBgZg4cSI4jsPtt9+O33//vTVvAyHCwwHnj523WkQpBMJBKQSEkPbo8gEsx3Hw8/Ozefj4+FiVswxct23bhkOHDiEhIcHutn5+fuA4zqX9S6VSpKSkYNWqVQCA5ORkaLVa5OXlAQDy8/Oh1Woxd+5cp69h7Nix+OWXXwAAu3fvhlwub/V7QYiQcByHa5+41mpZdUk1zmSfQcWZCje1iriMemAJIe3Q5QPYlohEprfIHLhmZWVh/PjxLgeorkhISEBVVRWysrIgk8mQlpaGxMREyOVyzJgxA1qtFjKZzGkdL730EubNm4fBgwfj77//xkMPPdRh7SOks/IK9LJ6/ufXf2LdsHU4/M5hN7WIuIpyYAkh7eHh7gZ0VmFhYQgPD0evXr2wdOlSjBs3rkOD1qKiIv7fHMchNzeXfx4fH2/13NLu3bvtLu/Xrx8OHDjQYe0jRAiqS6xvlrzmlmsQtzgO/hH+bmoRcRWlEBBC2oMCWAdkMhmOHz8OT0/PDg1cCSEdgzGGA6utf7T5hvoiYmiEm1pEWoVSCAgh7UABrBNeXl4tFyKEuAcDgqKCrBfRTVyCQT2whJD2oBxYQoggcSIOgxIHWS+kGEg4mh0ryoElhLQGBbCEEMGiy87C1TxgpWNJCGkNCmAJIYLV/LIzpRAIB6UQEELagwLY1vjV3Q0ghFiy6bWjGEg46CYuQkg7UADriioAswCoAGgAVDsr7BqJRAKVSgWFQoHExEQYDAZ+XWZmJtRqNeRyOVQqFTIzM/l1cXFxKCgosKqroaEBKpWKf3Tr1g2vvfZa+xtJSCdnrKegR6hsemApB5YQ0goUwLYkD8BQAB82Pt/Q+DyvfdWap5I9cuQIioqKkJ6eDgDQ6XTQaDTYuHEjCgoKsGnTJmg0Guh0Ood1icVi5Obm8o+QkBBMnjy5fQ0kRAAohUC4bCYyoBQCQkgrUADLYOphtfdYB1OwWgjA3NFjBHCscfm7TrZ18VwsFosRExPDB6ipqamYPXs2lEolAECpVCIpKQmpqaku1Xfw4EGEhISgT58+rjWAEAGjFAIBoxQCQkg7UABbDcDfweMBALUAGppt09C4fI6TbV1MM9Dr9di7dy/Gjx8PAMjLy4NarbYqo1arkZ+f71J9n376KaZPn+7azgkROOq1Ey5KISCEtAcFsG5SWloKlUoFqVSK4OBgqFSqDqn3iy++oACWdBnNe+0ohUBAmo8DSz9GCCGtQAGsL4BKB48vW9j2Kyfb+jrf1JwDe/z4cRQWFiIjIwMAoFAokJ2dbVU2JycHCoWixZfyyy+/QCqVIjo6usWyhFwJbG7iohhIMJr/2KAUAkJIa1AAywHwc/CYDGAEAHGzbcSNy29xsi3n2u6lUilSUlKwatUqAEBycjK0Wi3y8kx3ieXn50Or1WLu3Lkt1kXpA6SroV474aKbuAgh7UEBrDMcgKWwnwO7DC4HqS1JSEhAVVUVsrKyIJPJkJaWhsTERMjlcsyYMQNarRYymazFer744gtMmzatYxpFiABQCoGA0VSyhJB28HB3Azq9cQCyYX2y5WAaE7YdioqKmqrjOOTm5vLP4+PjrZ5b2r17t8M6//nnn/Y1ihCBsem1oxhIMCiFgBDSHhTAtoQDoG6xFCHEDSjoETC6iYsQ0g6UQkAIESyayEC4mqcM0I8RQkhrUABLCBEsGoVAuGgcWEJIe1AASwgRLOq1EzBKISCEtAMFsIQQwaIUAuGim7gIIe1BN3E5cbGuATX1jr8QfTw4BHk2HySWEHK5mIMeTsSZLkHXG4DaCsArwM0tIy2iHlhCSDtQAOvAxboGrMs7D2fnVDEHzFEGtymIlUgkGDBgAGpra6FWq7F+/XpIJBIAQGZmJp566inU1NTA29sbr7zyCsaOHQsAiIuLw9q1ayGXy63q27lzJ5544gkwxiCTyfDJJ58gIIC+xMmVjVWWAQBEYqDBCKCmDDixHwjpC4T2dW/jiFM2ExlQDiwhpBUohcCBmnrmNHgFgAYGpz20zpinkj1y5AiKioqQnp4OANDpdNBoNNi4cSMKCgqwadMmaDQa6HQ6p/U98cQTSE9Px6+//oprrrkGH3zwQZvaRYhglBbCWHUeACDyMM0qwl+VLisESgvd1DDiCpubuKgHlhDSCl0+gGWMoa7B9mFw8WRqsLNtXQNzORdPLBYjJiaGD1BTU1Mxe/ZsKJVKAIBSqURSUhJSU1Od1sNxHCoqKsAYQ0VFBSIiIlzaPyGCVFsBlBXC2PgDUiRunBbP8u+urNBUjnROzU6RlANLCGmNLp9CYDACr/5W2ubtNx67aHf5E4ND4UpmgV6vx969e7FmzRoAQF5eHjQajVUZc4qBM6mpqZg4cSI8PDwwZMgQTJ061bUXQIgQNQaq5svO5h5YR+VI50M9sISQ9ujyPbDuUlpaCpVKBalUiuDgYKhUqnbVt3r1auzevRunT5+GTCbDu+++2zENJaQTMzaY/m/ugaV4VTgoB5YQ0h5dvgdWIjL1ljZ3trreYe+qpbv6BaGHr+3bKGnhp4E5B7akpASxsbHIyMjAlClToFAokJ2djcmTJ/Nlc3JyoFAoHNZVXFyMP//8EwMGDAAA3HHHHfj0009x//33t9h+QoTMHPRwNBiI8FAKASGkHbp8DyzHcfAU2z4kYgeXJJuR2NnWU8yB41zbXiqVIiUlBatWrQIAJCcnQ6vVIi8vDwCQn58PrVaLuXPnOqwjODgYRUVFfB5tZmYm+vfv79L+CRGkxr8vY0OzHFgH5UjnY04h4ESNveeUQkAIaYUuH8B2BgkJCaiqqkJWVhZkMhnS0tKQmJgIuVyOGTNmQKvVQiaTOdzew8MDb7zxBsaNG4fBgwfj77//xsMPP3wZXwEhl5lXABDS1yaAtUohCOlL48F2Zs3HgaUUAkJIK3T5FAJHfDw4iDm0OA6sj6ObR1pQVFTE/5vjOOTm5vLP4+PjrZ5b2r17t93l06dPx/Tp09vUFkIEKbQvmEcAgGLbm7hoHNhOjw9YGw9dXXWd+xpDCBEcCmAdCPIUY44ymGbiIqQTYx7+ACxSCLyCgKhR1PMqAOYUAomPBHWVdTh98DTOZJ/h1/tH+CMggo4jIcQ+CmCdCPIUI8jT3a0ghDhivvGHn8iA86DgVSga+wbEjZ0A+vN6rBu2jl8duygWcYvj3NAwQogQUABLCBEs840/IsrmFxx+HFhz53k3L9ybeS+/3j/C3w2tIoQIBQWwhBDB4ntg7c3ERTq3xkNVV2XKfe0xsAcihtIMgoQQ11C/BSFEsIz1zVIIKIAVDGaoBQB4NKYQcByNA0sIcR0FsIQQwWItjQNLOqfSQrCLpnGrfYMaf3xUXwRKC93ZKkKIgFAA2wJ9eTH++nE9/tzzAf/468f10JcXt6teiUQClUoFhUKBxMREGAwGfl1mZibUajXkcjlUKhUyMzP5dXFxcSgoKLCpb/v27VCpVBgwYAAWLVrUrrYRIhTNb+KiFAIBKC0Eygr5FALOcgzfskIKYgkhLqEA1gnGGE4f3Ql9RSlqK5se+opSnD66s12XK81TyR45cgRFRUVIT08HAOh0Omg0GmzcuBEFBQXYtGkTNBoNP8uWPUajEQ888AC2bNmCI0eOID8/Hzk5OW1uGyFC0bwHllIIOrnaClOQiqbfGuZjZ56UAmWFpnKEEOJElw9gGWMw1hvsPi6e/gNVZadgM2UMGKrKTuHi6T8cbuvqF6lYLEZMTAwfoKampmL27NlQKpUAAKVSiaSkJKSmpjqso6SkBN26dYNMJgPHcRg9ejS+/PLLNrwbhAiLuQeWMw/HTPFr52ZxXjT/U+xhZypZ+iFCCGlBlx+FgDXU4+j2N9q07cncbx2uGzB+HjgPSYt16PV67N27F2vWrAEA5OXlQaPRWJVRq9VYv369wzq6d++O8vJyFBQUoG/fvtiyZQsiIuhuXnLls8mBpbhHOBqDVHMKgZHu4SKEtEKX74F1l9LSUqhUKkilUgQHB0OlUrW5Lo7jsH79eiQlJSEuLg59+/aFh0eX/21CrmDMyLBr0S5UFlUCsOjFo547wWhKIWh8bqRjRwhxXZePcjixBwaMn2ez3NhQj79+3oB6faXDbSXeAeh3w90QiW3fRs7OMkvmHNiSkhLExsYiIyMDU6ZMgUKhQHZ2NiZPnsyXzcnJgUKhcFrff/7zH+zbtw8A8Nprr6G+vt5peUIEjQOKjxaj7FiZ6SmNQiAMnMVxMgew5h8flgEsR8eTEOJcl++B5TgOIg+JzcPDyweRA8Y43TZiwGh4ePnY3Z5z8QQslUqRkpKCVatWAQCSk5Oh1WqRl5cHAMjPz4dWq8XcuXOd1lNcbBoVoaysDO+//z5mzpzp0v4JESKO4zApdRL/vLaywfT/8lpUnKEbgDotrwAgpC8AezdxNZYJ6UvTARNCWtTlA1hnAnv0g1+IDPxchzwOfqG9ENijX4fsJyEhAVVVVcjKyoJMJkNaWhoSExMhl8sxY8YMaLVayGQyp3WsWLECCoUCN9xwAxYvXozw8PAOaRshnZVfmB88AzwBAH/vvQgA0B0swuF3DruzWaQloX2BkL58j6tVD2xIX9N6QghpQZdPIXCG4zhEDhiDk7lbrXLrOI5DpHK0y72s9hQVFVnVl5ubyz+Pj4+3em5p9+7ddpevXr0aq1evbnN7CBGaqnNVqC03zeZ0dVw3/LX7AiKH98CwB4a5uWWkRaF9Ad9cAGebhkATeVPwSghxmVt7YH/88UfccsstiIyMBMdxVkM/GQwG/N///R8GDRoEPz8/REZG4p577sHp06cvaxu9A7vj6hvvxTWxs/jH1TfeC+/A7pe1HYSQJowxfJvcNAqIn9Q04oeXvwQBEXT5WQiYyNR/IqJRCAghbeDWALaqqgpDhgzBm2++abOuuroa2dnZWLBgAbKzs7F582b8+eefVjc3EUK6KAaEDQyDf7g/AMuJDNzZKNIqrFkKQX0DTWBACHGZW1MIJk6ciIkTJ9pdFxQUhB9++MFq2Zo1axATE4MTJ04gKirqcjSRENIJcSIOcYvjcOTjIwAsxoElgsH0pmCV//FhqAVO7Kc8WEKISwSVA3vx4kVwHIdu3bo5LFNbW4va2lr+eXl5+WVoGSHEHcwzcZl78agLViBKC8Eahyg0Hzuj0WIqWYCCWEKIU4IZhUCv1+PZZ59FYmIiAgMDHZZbuXIlgoKC+EevXr06ZP8NqIUOP6ABtS0XJoRcFvxMXCKayEAwaitMQWrziQwaLMqUFVI6ASHEKUEEsAaDATNmzIDRaERqaqrTss899xwuXrzIP06ePNmufTMw6LAT32MysvA0vset0GEnWDvnrJRIJFCpVFAoFEhMTITBYODXZWZmQq1WQy6XQ6VSITMzk18XFxeHgoICm/pWrlyJqKgom+GzSkpKMHr0aFx99dW4/fbbodfr29VuQjoT2x5YNzaGuKbxR4b5HNo0DiyzW44QQuzp9AGswWDA9OnT8c8//+CHH35w2vsKAF5eXggMDLR6tNVF/ImfcB+y8ARqYJoooAZnkYUn8BPuw0X81ea6zTNxHTlyBEVFRUhPTwcA6HQ6aDQabNy4EQUFBdi0aRM0Gg10Op3T+uLj43HgwAGb5StXrsSdd96Jv/76C3379sV7773X5jYT0tkY6xsDWDEFsILTfCYuClgJIa3QqQNYc/D6119/YceOHQgNDe3wfTAw1KPG7uMgnkcJchpLGvktAKAEOTiI5xxu62oPrVgsRkxMDB+gpqamYvbs2VAqlQAApVKJpKSkFnuehw8fjsjISJvlW7ZswV133QUAuOeee/DNN9+41C5ChIBPIWjM5qcgSDhY4ymVv4mrwUlhQghpxq03cVVWVuLYsWP883/++Qe5ubkICQlBZGQkpk6diuzsbGzZsgUNDQ384P8hISHw9PTskDY0QI+vMaoNWxpRjmMOt52M/fCAT4u16PV67N27F2vWrAEA5OXlQaPRWJVRq9VYv359G9poeo8DAkzjYspkshZ7cgkREj6FgEYhEA7Ourfc5iau5uUIIcQOt/bAHjp0CGq1Gmq1GgDwxBNPQK1WY+HChTh16hS+/vprnDp1CiqVChEREfxj37597mx2hygtLYVKpYJUKkVwcDBUKtUl2U/z2cLaM3sYIZ0N3wMrplEIBMMrwDSVLLM+dswyBzakr6kcIYQ44NYe2Li4OKeX/C7H5UAxvDEZ++2u24W7UIG/HW4bgD4YjY0O63XGnANbUlKC2NhYZGRkYMqUKVAoFMjOzraasCEnJwcKhcKFV2PLz88PlZWV8Pf3h06nQ0RERJvqIaQzMvfAcjSRgWAwI8PuN07gwlnTcz6ANWdp0TiwhBAXdOoc2MuBAwcP+Nh9cBDD0VvEQQQOYifbutbTKZVKkZKSglWrVgEAkpOTodVqkZeXBwDIz8+HVqvF3Llz2/T6Jk2ahI0bTUH2hg0bcMstt7SpHkI6I5seWLqLq/PjgOKjxdDlnAdgmUIAIGoUBa+EEJd0+QDWmRFYASnUjc/MX5CmtywUaozAig7ZT0JCAqqqqpCVlQWZTIa0tDQkJiZCLpdjxowZ0Gq1kMlkTutYtmwZZDIZiouLIZPJ+Ju+nnvuOXz88ce4+uqr8eeff+K+++7rkDYT0hmYRyEQS2gUAqHgOA6TUifxx6qqrA6A6cdIRZkbG0YIERSOXeG37ZaXlyMoKAgXL17kh9QyGAwoLi5G9+7dIZFInG7PwHAGu/ArXkINiuCDcAzBM4jAaJd7WTuz1rwXhHQ2SzyWgDUwTFx4Fb5b8g9kMWGYndW2qxXk8lrd61WUn7KerODGhTdi9Iuj3dQiQog72YvXnBHUVLLuwIFDJMagB65HEX5COG6EGB0zAgIhpH2ahtES/o/JrqTqXBWqzlUDAIZOD0P2p+dM/75vqDubRQgREApgXSSGF3riJnc3gxDSiFkMu2SejpTu4ur8GGP4Nvlb/nlghBf/b78wP3c0iRAiQJQDSwgRJPMIBIDFnewUv3Z+DAgbGIaIoWEArMfwZc2nkyWEEAcogCWECJL5Bi6AJjIQEk7EIW5xHIJ6+gOw6D2H9Y8SQghxhgJYQoggWfbW8Tmw1AUrOJzIoge2+WxchBDiAAWwhBBBspdCQMNoCQdrNpUsQCkEhBDXUQDrokM4hDEYg0M41CH1SSQSqFQqKBQKJCYmwmAw8OsyMzOhVqshl8uhUqmQmZnJr4uLi0NBQYFNfStXrkRUVBTCw8Otlr///vu4+uqrwXEc9Hp9h7SdkM7AqgfWnANLEazgiCy+hSiFgBDiKgpgXbQBG7ALu/AhPuyQ+sxTyR45cgRFRUVIT08HAOh0Omg0GmzcuBEFBQXYtGkTNBoNdDqd0/ri4+Nx4MABm+UjRozA999/j969e3dIuwnpLKx6YD2oB1ZwzF2wHMfPE0MpBIQQV3X5YbQYGKpRbXfdCZxAKUrBgcMn+AQA8DE+xnRMBwNDKEIRhSi72/rC16WJDsRiMWJiYvgANTU1FbNnz4ZSqQQAKJVKJCUlITU1FcuXL3dYz/Dhw+0uHzhwYIttIESILHtgOX4mWerBEwqr+FXEgTUwSiEghLisywew1aiGP/xdLl+MYtyAG1osV4lK+KHlMQ31ej327t2LNWvWAADy8vKg0WisyqjVaqxfv97lNhLSFRiL/wbQLIeyvg4oLQRC+7qrWcRl5gjWNBJBQwOlEBBCXEcpBG5SWloKlUoFqVSK4OBgqFQqdzeJEOEoLYSx9F8AACcCfwkaDEBZoSmIJZ2bRWereSQC6oElhLiqywewvvBFpZP/fsbPdrf7GT873c4Xvk73a86BPX78OAoLC5GRkQEAUCgUyM7Otiqbk5MDhULRMS+YEKGrrQDKCpumkRVzTSkEZmWFpnKk0+M4i5vwKAeWEOKiLh/AcuDg5+Q/H/gAAESNb5X5/z7wcbqdK/mvACCVSpGSkoJVq1YBAJKTk6HVapGXlwcAyM/Ph1arxdy5czv6pRMiTI3Jk8bGYMdqHFHL+OfCycvZKtJKzOJgcY3fRJRCQAhxVZcPYFsShjCEIxzDMAxrsRbDMAzhCEcYwjpsHwkJCaiqqkJWVhZkMhnS0tKQmJgIuVyOGTNmQKvVQiaTOa1j2bJlkMlkKC4uhkwmQ2pqKgDggw8+gEwmw6lTp9CvXz8899xzHdZuQtyJNZj+LxKj6S4uywi2/BSlEggBx1EKASGk1br8TVwtkUGG4zgOT3iCA4c5mIM61MELXu2qt6ioiP83x3HIzc3ln8fHx1s9t7R79267y+fPn4/58+fbLJ81axZmzZrVjpYS0jmZe2CdTiNbVgj4hwFeAZepVcRlFrGq+RhSDywhxFUUwLrAMljlwLU7eCWEtENjb6uxvjGFwCIH1u5MsjS9bKdkTiHgYHETF+XAEkJcRCkEhBBh8QoAQvrywY6o+SgERFi4phxYSiEghLiKAlhCiPCE9oXR25SHzjlLISCdl2UKgYhSCAghrUMBLCFEkJhvdwCNw2iZl9kraDPGFukcGlMIOIATNy6hHlhCiIsogHVR3dE6XHj1Aury6tzdFEIIAKPYNMSdaSIDB0mwIX3pBq5OitmbyIByYAkhLqIA1gXGKiOqv60Gq2Ko/rYaxiq6zEWIuxnrTX+HIg8Hp7GQvjSlrAD8kVmG+hrTmGiUQkAIcRUFsC1gzBS0sjpTzwCrZajeWt3ueiUSCVQqFRQKBRITE2EwGPh1mZmZUKvVkMvlUKlUyMzM5NfFxcWhoKDApr6VK1ciKioK4eHhVsvnzJmD/v37Y+DAgXjhhRfa3W5COgt+Ji6RxSgEnAfQ61ogahQFr51dYxdsxTkDqspM5z9KISCEuIoC2BYY8gww/GFoSq5jgKHAgLqj7UslME8le+TIERQVFSE9PR0AoNPpoNFosHHjRhQUFGDTpk3QaDTQ6XRO64uPj8eBAwdslk+bNg0FBQXIzc3FgQMH8OOPP7ar3YR0FubeOk6MplEIwAHegZQ2IADmFILBt0r5ZcX5xTiTfQZnss+g4gxNBUwIcazLB7CMMbA6+4+G8w2o+rbK7nZV31ah4XyDw22Zi2NPisVixMTE8AFqamoqZs+eDaVSCQBQKpVISkriZ9ZyZPjw4YiMjLRZHh8fD47j4OHhgQEDBuDUqVMutYuQzq6pB9bNDSFt03iK9ArwgKef6S6ubx/8FuuGrcO6Yetw+J3DbmwcIaSzo4kMDMCF/11o/Xa1QPmb5Q5Xd/u/boBny9Xo9Xrs3bsXa9asAQDk5eVBo9FYlVGr1Vi/fn3r22ihoqIC3377LZ566ql21UNIZ9HUA9vCRAakc2o8WLWV9airNuXATnhjAqKujwIA+Ef4u61phJDOj/ou3KS0tBQqlQpSqRTBwcFQqVSXbF+MMcyePRsPPfQQoqKiLtl+CLmcmN6Uiy4ScRYTGVAEKzS/fVXCH75u0d0QMTQCEUMjEBBBaSCEEMeoB1bS2FvaDGMMVRlVqD9Wb39wSQ7wuNoD/lMc9BJInO/WnANbUlKC2NhYZGRkYMqUKVAoFMjOzsbkyZP5sjk5OVAoFK6/pmYWLlwIPz8/PPHEE22ug5BOpbQQxjP5AACRh8U4r8YGNzWItJb5tBrYwxN1VQ0o/UcPY1UlUFtBOcyEkBZ1+R5YjuPAedo+RF4i+N3iB87T/iDonBcHvwQ/u9tynhw4FwdPl0qlSElJwapVqwAAycnJ0Gq1yMvLAwDk5+dDq9Vi7ty5bXp9H330EX788Ue88847bdqekE6ntBCs5Bh+31ICwDQOrPnvjRmNwKmD7mwdcZkphJXHhyAgzJRv1VD0B3BiP1Ba6M6GEUIEoMsHsM6I/ETwneRrd53vzb4Q+XXM25eQkICqqipkZWVBJpMhLS0NiYmJkMvlmDFjBrRaLWQymdM6li1bBplMhuLiYshkMv6mr8ceewynTp1CTEwMVCoVNmzY0CFtJsQtaiuAskKAA8rPmEYCsRn8vuY8cC7fDY0jrWJoGslFJDZPJdt4LMsKKYglhDhFKQQtkCglkByVwPBn41BaHCDpL4HnABfu0HKiqKiI/zfHccjNzeWfx8fHWz23tHv3brvL58+fj/nz59ssLykpaU8zCelcmHn6UQ5Dpkih+60S5/6qQek/NQCA+lojKs7VIQAngSAZXYrurGorwOr1AEzH0pwGYqy3+DFSVgj4h9ExJITYRT2wLeA4Dr6TfPlUAs6Lg+/N9ntlCSGXj8THNPRSbUUDvpn/NwDg4uk6HP7krKkA3dDVeVnNIwuIJXYC2OblCCHEAgWwLjCnEnB+pmC2o1IHCCFtV32+HgDgEyTGLSv6AAACwz0xbEYPdzaLuOLiKaubY80pBA3NA1hCCHGAUghc5DnAs91pA4SQdjLfrMUYfvu6GAAgUwdAepUPAMDDS8TfEEQ6qdoKoLxpQhWOg/0UAkIIcYK6EgkhwuEVAATKAAb4hZrGqvPyFzeNQmB1adq1kUDIZdZ4jCwPlcMAlo4hIcQBCmAJIcLSQwnOLwR9RgUBAMQSkcVEBo3/D+lLN/90duZjxQFiDzspBIF0Ex4hxDFKIXBFbUWzmw44OrES4k6yEWgQnQDQdAMQL6QvENrXDY0ibcX3wDZYnGeDnA8dSAjp2qgHtiWlhaaBtU8eaHp0wEDbEokEKpUKCoUCiYmJMBgM/LrMzEyo1WrI5XKoVCpkZmby6+Li4lBQUGBT38qVKxEVFYXw8HCr5QsWLMDgwYMxePBgTJs2DdXV1e1qNyGdRYNnCABTAMt5m3pjGSem4LWz49M9mp7yAayBUkAIIa6hANaZ0kLTWIT2tHOgbfNUskeOHEFRURHS09MBADqdDhqNBhs3bkRBQQE2bdoEjUYDnU7ntL74+HgcOHDAZvkzzzyD3377Db/99huio6Oh1Wrb3GZCOpOGOtO0sWKJCPBovHGL7gHq/LwCTL3kZhbjwPIpBJQCQghpAQWwjAHGettHzQXHwatZWaGpnL3tXRy/UCwWIyYmhg9QU1NTMXv2bCiVSgCAUqlEUlISP7OWI8OHD0dkZKTN8oCAgMaXyVBdXW19kwshAtYUwHJNObBEGEL7AiIJ/9RqJi5KASGEuIByYFkDULiz7duf+sX+8r5jAK7lt1ev12Pv3r1Ys2YNACAvLw8ajcaqjFqtxvr169vcxKeffhofffQR+vfvj1WrVrW5HkI6kwaDKYAVSThwnOm3OP0+ExCxqdec40T8TVxGn3AKXgkhLqEeWDcpLS2FSqWCVCpFcHAwVCrVJdvXyy+/DJ1Oh6FDh+KTTz65ZPsh5HKySiEQURes0PBXgzgRROaZuBj1qRBCXEMBLCc29ZY2f8hGuLa9bIT97Tmx083MObDHjx9HYWEhMjIyAAAKhQLZ2dlWZXNycqBQKNr08sxEIhHuuusufP755+2qh5DOwmiZQmDOIaAuWOEwHyoR1zQTV2OvOiGEtIQCWNMtsPYfrnC0rYt30EqlUqSkpPCX9pOTk6HVapGXlwcAyM/Ph1arxdy5c9v08v766y/+39988w3kcnmb6iGks7HMgeVElEIgVFYpBAajm1tDCBEKCmAdaX6nrD0ddKdsQkICqqqqkJWVBZlMhrS0NCQmJkIul2PGjBnQarWQyZyPibhs2TLIZDIUFxdDJpPxN309++yzGDhwIAYPHoyCggIsXLiw3e0lpDNoqLVIIaAhlwSHWYyj1TQTFwWwhBDXUMKRM+abCeyNRtDOO2WLior4f3Mch9zcXP55fHy81XNLu3fvtrt8/vz5mD9/vs3yL774os1tJKQza6irB2AehYB+iwuWSGQxDiwFsIQQ11AA25LQvoB/GM3ERUgn09AY7IglHDh+cHzKIRAM/lBxTSkE9ZQDSwhxDQWwrqBglZBOx3ocWEohECpOZDGRAd3ERQhxEV13I4QIUlMKgUUOLHXACkZTb7lFDmwdpRAQQlxDASwhRJD4HlhPUVP8SgGscPDDaImaZuKiFAJCiIsogCWECFJTCoGYppIVME4kahzLtymvmRBCWkIBLCFEkMx3rIs9RaCJDITH8oY7kYfpq4h6YAkhrqIA1k0kEglUKhUUCgUSExNhMBj4dZmZmVCr1ZDL5VCpVMjMzOTXxcXFoaCgwKa+lStXIioqCuHh4Xb399RTTzlcR4gQWacQmEchcGeLSFuw+nrkbSsFABhrDUBthZtbRAgRAgpgW8AYsxmax96y1jJPJXvkyBEUFRUhPT0dAKDT6aDRaLBx40YUFBRg06ZN0Gg00Ol0TuuLj4/HgQMH7K7Ly8uzGneWECFjRoZdi3ah5rweQGMKAREe8ynUUIGKs3UAgLrycuDEfqDUztjbhBBiocsHsIwx1BuNDh/5FyrwS/F5VBnqUW80ospQj1+KzyP/QoXT7VwNcMViMWJiYvgANTU1FbNnz4ZSqQQAKJVKJCUl8TNrOTJ8+HBERkbaXffMM89gxYoVrXhXCOnEOKD4aDFqymoAACKJqCkHlnpghcNouuokEokQM7MHAKDsuB5njlbizE+/4szOX1BxhnpjCSH2dflxYBsYw7cnz7ZYrqimuNnzWvxVXuWw/KRePeDhwtiUer0ee/fuxZo1awCYeks1Go1VGbVajfXr17dYlz3p6ekYPnw4oqKi2rQ9IZ0Nx3GYlDoJ+ZvzAQBlx2uA4osAAGMD3QQkCLUVYA1NaVN+Uk8AgKHGiHVTfm9c+jtiXziPuGXj3dBAQkhn1+UDWHcpLS2FSqXCsWPHMGbMGKhUqg7fR1VVFd544w3s2LGjw+smxJ38wvwg8hDBaDDi80eO8ssNeroJSBAYa+ot5wDW+LtDJOFw36cD+WL+QwZd/rY5wYwMuxbvQkl+CQZMH4AB0wa4u0mEdFldPoAVcxwm9erRYrmLdQb8fLYMN/QIQZCnxKV6nTHnwJaUlCA2NhYZGRmYMmUKFAoFsrOzMXnyZL5sTk4OFApFyy+mmb///hvHjh3jty0uLsbQoUORnZ3d6roI6UyqzlXxoxDMeG8I6sUh+FyzCxIvyocVHoZ92tMAAE4ERAzwb1oV4e9gm0vcIiPD7hd3I2xgmFWQyhhD3md5KDtWhn92/oPeN/aGfw/3tJGQrq7LB7Acx7l0qV/Mifj/e4g6LnVYKpUiJSUFKSkpmDJlCpKTkzFq1ChMnz4dSqUS+fn50Gq12L9/f6vrHjRoEM6ebUqPCA8Pp+CVCB5jDN8mf8s/D1cGoo7rZnpCU8oKBn+bAAPC5b4o/OkCGmoZfs04i+zPihE50B/j3762dXVaBJ7KO5RWQaijoNRyW3PvqnKaEueOnMO+l/eh9mIt1Elq7Fy0E/mf56O+ph6snkFfpsdb8rdw85s3AwB8pD7oMbgHAiJo6nFCLocuH8B2BgkJCViwYAGysrIwcuRIpKWlITExEXq9Hl5eXtBqtZDJZE7rWLZsGdauXYvi4mLIZDI8//zzSE5OvkyvgJDLiAFhA8OQ/4UpB1bsAaCu1r1tIq1j8UODE3MY83gv7H3X1Av71fy/IfES4cShCiBoNzyDAloMOovzmu5RKD9Zjn0v74P+gt4qCFVpVDj66VH8nPIz9Of1uHjqIs4dPYeSvBJ4BXohsFcgyk+W40z2GRR8WQDlnUrU19Tjm/u/wf7X9kN/QY/K05VWNwrqL+ixeeZm/nnsoljELY7r+PeLEGKDY+0dD6qTKy8vR1BQEC5evIjAwEAAgMFgQHFxMbp37w6JpOV0AADQ1zfgeGU1ov194e1x5VymbMt7QYi7seJjWBK2EQDwdNZwVJUakHrzr/Dp5oFnzr/g5tYRV7ynfh263AuYsbY/ro7thqXKLLujSIi8RDDWGuEZ6InAXoFgDQzeQd4Y+ehIHHz7ICpPV+L88fNAAwAOEHuJ0dCYCx0+PBxFh0xDCPqG+QIioLqoGgDgGeSJuot1/H44Dw4isQgN9Q2mulpp0F2DEP9yPPXAEtJG9uI1Z6gH1kXeHmLIu9GJiRC3Ky1Ew7lj/FORB2cxkQEzjSEa2tddrSOuEjV2BDBg95pTEIkBY71tMWOtKde5rrwOJUdL+OWb79oM7yBv6C/omwoz8MErAD54BYDqc9VW9VoGrwDA6pkpeG2D8KHhFLwScpm5dRzYH3/8EbfccgsiIyPBcRy+/PJLq/WMMSxevBiRkZHw8fFBXFwcjh49ar8yQsiVr7YCKCuE0dDUVSf2aJb3WlZIszkJAH/tzzsIJf8Y7AavziuAdfDqJn3H98V1T12HyjOVNG4tIZeRWwPYqqoqDBkyBG+++abd9S+99BJeffVVvPnmmzh48CDCw8MRHx+Pigo6SRDSJTVGPcaGpgBWJOZsJzK4sjOjrgyNx4jz8MSklUPc3Jg2aPz2LNxeiM2Jm7Fu2Docfuewe9t0hTLPvnf0s6N2n7dUnlyZ3JpCMHHiREycONHuOsYYXnvtNbzwwgu4/fbbAQDr169Hjx49sGnTJjzwwAOXs6mEkE6kod4igPXg+HuCKG4VHk4E+IZ6wcObQ72+cx9A3+6+iBwWiasTrsa2edvAwNBzZE9MSp0EAPBvHParpREP3MHcpu7K7ijOK7YaqcFyWUvtbf7anL3Wjhg311zH39//jUOphxAdGw2fUB/kfZaHA6sPIDo2Gr5SX+s2NM7WZy7vF+bX6v2Szq/T5sD+888/KCoqwrhx4/hlXl5eiI2Nxb59+xwGsLW1taitbbojuby8/JK3lRByeZlTCDgRwIlo6CwhsvyxUVlch/o604KgqCBUlVTh6olXm2Zba21MKwICewaiXFcOmCdm48DX4xPqg5rzNVbrwtXh8I/wR+G2QjAjAzhA4ifBVWOuwt8//I366noopyox7bNpYIzhs2mfQeInQV1FHYpyi3Bo7SGE9A1Bn/g+AAD/cH+nAZS9wK6loNdYb8T6sesROSwS418db1Nf80BUMUWB90e/j4v/XMSA6QMw7pVxKD5ajINvHYRslAyHUg8h6oYoHP30KMqOlUEql2LvS3vx24bfMGjmIKsglx9ebKoS546eQ+H2Qn6kh6H3DbV6rb5SX6uRIcpPlqMopwh/ffsXai/WYuh9Q+2+D8qpShTnFaO7srtpdIhm+zv761k01DXg1V6vQnmHEr5SX5Tkl+CVnq/gmluuwfm/zuOXN35B6DWhyPsiD3U1daguqcaq8FUYMH0AwoeE4/w/5xE5PBLD5gyzee/sDb1mT0f+OLF33DrLDx4h6LQBbFGRKfm+Rw/rSQZ69OiBf//91+F2K1euxIsvvnhJ29YRJBIJBgwYgNraWn6qWPMoAJmZmXjqqadQU1MDb29vvPLKKxg7diwAIC4uDmvXroVcLreqb+XKlXj77bdRV1fHv3cAMGvWLPz0008ICDDdXLB161ZERkZepldJSAdr7Go1pxCIzPmvzVMIaDxYwWAAts7/HR6eHCasvBYVFzwhVUpxNP0oxF5iXDX2KpQdK0NdRR0CZAGovViLqrNVqL1YCzDAr4cfug/ojhM/n4BspAyDEgeh/HQ5crQ5qCquQr/x/SDyFKE0vxR9x/eFV6AXzh09B8A0DviA6QOgnKrEp1M/hUgiQpgyDBdPXETy0WT4hPhgw00bEDE0oilobBzG7aqxV2Fr8lY01DYg+93G8bWfBULloQgbGIY+8X1Q8FUB3rj6Ddz4/I24auxVOLzuMCKGRqD8dLkpKMs9i78z/8b+V/bDPCDQvpf34eKJixj1+CirQJAxhrO/ncWJH08gIDIA+nI9HwArpypRfLQYWWuy4NPNB+W6ckxcMxHnC8+j6kwVDrx2AMF9gjHxjYl4teer+Ou7v8CBw5v930Rg70CweobiI8UAB/y55U/8ufVPeAZ4oq68DgMTB+L0odMo+6MMBV8WoMegHjj7+1mweoYtc7bgwKsHoLhDgYKvCvCm4k0oblfg5L6TKMkz3XDHeXBgDQxGgxHf3P8NDqw5gOriangGeII1MFSXVKPuYh0KvixA2MAw/Lj8RwTKAlFxsgJ/fvsngmRBOH/8PFjjj1ZjnRFHPj7S9PmpZ/gj4w/++TvqdyBVSPn9gwFH04/iaLopneDX9b+i/+T+OPj2QUjlUhx8+yCqzlShqrgKeV/k4eTPJ6G/qMepA6cgu1Zm00vdfUD3Fnt3LQPTc0fP8ceQ4zg+UDfvu0JXgQvHL8AzwBOGSgMOv3sY5SfL4R3kjVFPjqKA1olOM4wWx3HIyMjAbbfdBgDYt28frr/+epw+fRoRERF8ufvvvx8nT57Etm3b7NZjrwe2V69e7R5Gq6nCz4DaI4B0kan7p43Cw8NRVFSEhoYGxMfHIykpCTNnzoROp8OoUaOwbds2KJVK5OXlYcKECdi/fz969uzpMIA9dOgQIiMjMXToUJsAdsaMGZgwYYLddtAwWkRwSgtRlnsUa27KgaefCM/ljETZvzVYE58LTz8xnvv3vzQKgQCsG7IGZ34rw38/ugGnc0rQPcqIAXePAoKjwYwMe5bsQfcB3R1els5Ny0VteS0e+fMRHFp7yKqss+3tMZeXKqQoyS9xabuK0xV4teerAIDhjwzHoTcPudxb7NfDDzWlNTAyo/WQXR4AGm9mC+wdiJrSGhgqDQBn+o7kJBw/KoMkQAJDhQGAaRKFa265Br++/6vVfmSjZDi1/xT/PDAqEOUnWn9V0jvYG/rz7r9hriOZh1Hz8PZAvd7iDkKL3nqIgJB+IdCf16Ouqg5e3bxQVVSFwTMHo+CrAhiqDQi9OhRDZg5B2d9lqDhdAQ8fU79gxakKlP5VCu9gb1wovGCqWsxB4i+BX3c/nP/7PLwCvEw/xByQ+Emg+UmDCHWEwzJXkitmGK3w8HAApp5YywD23LlzNr2ylry8vODl5eX6jhgDWHXL5QCg/hxQ9CDgeyPAapyfrDhfl3qBxGIxYmJioNPpAACpqamYPXs2lEolAECpVCIpKQmpqalYvny5w3qGDx/u2msgROhC+8LodxFAjukGLkscKHgVCHPfiUgsQtxTA4CK0003dok4hxMCcCIOoxePhkgkQvcB3eEf7m9T1tn2jupsTXljg+lyvtmht1wPXgGg6myV/RUWcVT5vxaBJjO9X6y2aSfm4BUAakpqbIJXAFbBK4A2Ba8ArrjgFWgaRs0qeAWsj6MRKPuzjH9aX20q+9uG3/hlJXklyHw+03YHjaPE6cua3jvWwFB3sY7ft7PgFQAMVQa8O+JdDLprEPzD/RGuCkd0XDQN19bIraMQOHPVVVchPDwcP/zwA7+srq4Oe/bswXXXXddxO2LVwJ/+rj3+7gMYy4DKL1su62JQrNfrsXfvXowfb7o8lZeXB7VabVVGrVYjPz+/zS/x8ccfx5AhQ7Bo0SJ0kg53QtrF6G+amU7kwQE+IUC3KNMK+ngLD4emq1nM6LQov0ljwNlpLq+61mzSlTSgTRNiNMcaGH7b8Bv2vbQPmxM300gXFtwawFZWViI3Nxe5ubkATDdu5ebm4sSJE+A4Do899hhWrFiBjIwMHDlyBLNmzYKvry8SExPd2ewOUVpaCpVKBalUiuDgYKhUqkuyn5UrVyIvLw/79+9Hbm4uNmzYcEn2Q8jl1GAwfTOIPDhA7AlO4gOARiEQFMtjxTVPYu7cRGIRNHs04JqPQUwcuhTvldhLDLH3lTMzpiNShRTXPXMdbt90O4Y9MKzlDboItwawhw4dglqt5nscn3jiCajVaixcuBAA8Mwzz+Cxxx5DcnIyhg8fDp1Oh++//56/IalDcL7ANZX2H32OAVE/Nz5+AryvBcShQJ+/HW9jfnC+TncbGhqK3NxcHD9+HIWFhcjIyAAAKBQKZGdnW5XNycmBQqFo08uLiIgAx3Hw9fXFPffcg4MHD7apHkI6E2O9qctL7GExBiwRJI7jmgJYF3tgOwO/MD9I+0sv+35bPeqGCAgfFu68Tg8OIk8ROA8OHr5OMgsbdy32FtskIHr6ezrdh1eAl/OIQwRwnnZeG2d6SAJs79Hwj/BvmnnNYlPOkwNEgMhTBP+e/lbbiH3sB7yhilCn7XenQXcNwsA7B7rl89aZuTWAjYuLM+X1NHt88MEHAEwntsWLF+PMmTPQ6/XYs2cPBg4c2LGN4DhA5Gf/4dkX8L2+8XEDIPvKtE3xM463MT9cvAtaKpUiJSUFq1atAgAkJydDq9UiLy8PAJCfnw+tVou5c+e26eWZb+gyGo345ptvMGBAJ7nkRkg7GA2mQMc0CoGdiQxIp2eVzsSnEAjnAFadqzIN1dWMyKvxtXCmQMq3R7PODPNHVszBq5sXnyvp6e8JsbcYIon9r2XvYG9I/CQYOmdo0+e92deMVzfT/R/eod7gPDj4hPrgydNPwq9H053yofJQSJVS+Eh9wIk5eId4Y+SjIxGhjoB3kDd6x/U21SsGgq8ORnDfYIi9xeg3qR8CIgMg8ZdgxEMjTDcWiQDvbt7w8POwep0ePh4IkAUgekw0rhp7FcauGIvB9w5uagcH9FD3QKg8FJEjIyG/Qw75FDnCh4QDYiAoOghibzHC1eHw8PbAuFXj4OHpgV7X98J9WfchfGg4Bv53IPrf1p+vo/+Upn9HqiPhG+KLx/99HENnD0X/203rImIi4OFlG6APunsQukV3a3qP+oe2eIeQ3WC7BZyIg/wOud11Im8RfKQ+/Pve89qe8Aww/SjYNX8X1g1bR5NlNNNpb+LqlDzCgB5vA7VHTT0F7RiFwFJCQgIWLFiArKwsjBw5EmlpaUhMTIRer4eXlxe0Wi1kMpnTOpYtW4a1a9eiuLgYMpkMzz//PJKTk5GYmIiSkhIYjUbExsbi/vvv75A2E+JOfAqB2BQNcI0/GCnHW4C4xogOEEwPLGMMW+ZuQV1lHd90TsxBnaSGf7g/zh09xw+ZdO7oORz99CjqKuoQ2CsQgbKmu6vLT5bj3O/nMOG1CSjXlePYtmMoyikyfTMzIHxIOIL7BEM5VYmS/BKr4cX63NQHlWcrcebwGfj38IdyuhJnc88iXB0Or0AvFOcVY8D0AfCV+uJ84XlABAy7fxgS1ibwwzyZyyjvUPKjMBTnFcPT19NqefcB3e3++7onrzO1SyHFuaPnkPdZHlg9g/6CHg8cfsBqiClmZPAO9Ob3aW90ieZ1luSX4Ppnr0fep3ngOA53br4TfmF+eOCwxTjwq2G3HvMNfqNfHM2vM4+lW19bj4CeASjNL0W/Cf0Q/3I8UgemQuQpws1rbka5rhx/ffcXzhw+A68AL9RV16HHwB44l3cOQVFBgBG48O8FQGT64VFXbropy0fqg5qSGtPORKbPhEgsQp+b+sDD2wMDpg+AVC5FwRcFAGAKzl8ZB+8gb4QqQvHn13/yI2BUnavCqzLTKBejl43G1ROvBtA0WQbpRMNoXSr2hmWgoaOa0HtBhOjvzL/x4U0fIuwaH8z9cRIunJPg9cEfw8NbhBdqFri7ecQFawe8jrN5FzDz0zj0HSMDygqBQBnQQ+nuprXIHAA2H0+2NTeVNR/qy7JOR/VZbmMZUDrbb2uHFGuPS7Gvy9F+e8fCclg1y+HVzOPCFucV8z9Q8j/PtxljGLD9XBiNRrwW9RoqdBUYPnc4okdH231N5sky/vzmTzTUNWCydjLUSWqbcleaK2YYLUIIcYRPITAPo0UpBILDLIbMakq5EkYPLCfirHr22lqH5dBdrtTZfBtXhv5q7RBh7XEp9nU52m/vWDjbZ/PjNGbJGNd2ZDSNKztg+gCb2dSsNE6WUX6yHLpfdKivrXdctgujAJYQIjjmm7hEHo3Bj/kKtBvbRNrIahgtOoLkyiXyEGHW7lktljMH0GV/lZkC2OZj1RIAnXgcWEIIccScAyuWiGCZA0uEyHIUAgpgCTETe5nu8KMA1j4KYAkhgtOUQgDQKATCZopdWzeRASFdgYe36SJ5Q20HzIhwBaIAlhAiOE0pBKLG4JV6YIXGehgtYeXAEnI5mANY6oG1jwJYQojgNM3EBZhSCEzLr/BBVa4s5kPFcUC9aRgiNBgAfTlQW+G2ZhHSWVAA6xwFsC6qqDiD3bsXo6LiTIfUJ5FIoFKpoFAokJiYCIPBwK/LzMyEWq2GXC6HSqVCZmYmvy4uLg4FBQU29a1cuRJRUVEID7eeccVoNOKxxx5D//79IZfL8f3333dI+wlxJ3MKgdhD1HgTF93FJVh1lUDZMdO/9ReBkweAE/uB0kL3tosQN+NzYGkUArsogHVRZeUZ7NnzIiorOyaANU8le+TIERQVFSE9PR0AoNPpoNFosHHjRhQUFGDTpk3QaDTQ6XRO64uPj8eBAwdslr/77rswGo34448/cPToUQwfPrxD2k+IO1mNQkDpA4Jk7izn6hz0tpYVUhBLujQ+B1ZPObD2dPlhtBhjMBiqWyxnMNTw/6+rq2qxvETi69Kd0WKxGDExMXyAmpqaitmzZ0OpNA3mrVQqkZSUhNTUVCxfvtxhPY4C03fffRfffvstv6+QkJAW20RIZ9eUQmD6G6Ob2AWIj2CdlCkrBPzDAK+Ay9IkQjoTSiFwrssHsAZDNVaudH1qtvffv8Glcs89VwlPT78Wy+n1euzduxdr1qwBAOTl5UGj0ViVUavVWL9+vctttHTmzBm88cYb+O6773DNNdcgNTWVglgiaMzI8OeWPwEAYn4cWIpgBcfVY9VZjmltBVBbBRhqADBT4C3xATz9KcAml4SHV2MASykEdlEKgZuUlpZCpVJBKpUiODgYKpXqkuzn4sWLkMlkyM7OxsCBA7FkyZJLsh9CLhsOqDxdCQBoqGewGkaLCM4lG8O3tgIoLwLKz5geFWesbw6rrTDdMKYvN5WrONP0vPlNZGd+NeXlnv0NKPvLlLNbegwo+p3ydcklQz2wznX5HliJxBfPPVfpcH1+/mZs3/4YAA7R0bE4fnwPAIbx41+DQnG703qdMefAlpSUIDY2FhkZGZgyZQoUCgWys7MxefJkvmxOTg4UCkUrX5lJZGQkpkyZAgC444478PDDD7epHkI6C47jcHXC1Th35Bz+/aUcZ34rQ3W5KQiiYUSFo9UdqxVF1htxHBAQ3rSurgao1wMNdUBtOVBfY78evzDAwwu4eNL5/ryDTT2r5ada/mCVNQawoX1dey2EuIACWOe6fADLcZzTS/1lZccQHT0akyalws8vDFVV5/Dtt8k4f77QpRSBlkilUqSkpCAlJQVTpkxBcnIyRo0ahenTp0OpVCI/Px9arRb79+9vU/0JCQn48ccfMX36dOzevRtyubzdbSbE3SQ+EgBAVakB68ZsdXNryCVVrgN0hwGjwXZdyZ+moLah1vX6qs65Vk5/3vRwFeXrkg7EjAwFGaYRh2giA/sohaAFcXGLMH365/DzCwMA+PmFYfr0zxEbu7DD9pGQkICqqipkZWVBJpMhLS0NiYmJkMvlmDFjBrRaLWQymdM6li1bBplMhuLiYshkMqSmpgIAnnvuOaxbtw6DBw9GRkYGFi7suHYT4i76cj0AwL+7BHN2TsLMrxLc3CJyyVw8aT94BRp7XFsRvF5qpX+7uwXkSsEB5bpyAEBtRSf6jHciXb4HtiUcZz/Gd7TcVUVFRRZ1ccjNzeWfx8fHWz23tHv3brvL58+fj/nz59ss7969O3bs2NGephLSqTDG8Ne3fwEA+sV2Q4RKiqoL7m0TaT1+EALvQPc2pCNVnTXlz1IvLGknjuNw7RPX4uTekyg7VoYz2U1DePpH+CMggj5jFMASQoSFAb5SX5SiFJ6+YjS/g4sxduluDCIdz1AFoP3pWJ1GbRUFsKRD+PcwjZBUX1OPdcPW8ctjF8UibnGcm1rVeVAASwgRFE7EIer6KJz8+SQ4EQWqglRbARgbu2DZlZbf10mG/SKCV3vRlDog9hJj9r7Z/HL/CNeH/rySUQBLCBEc1hj8iEQAOA5WHa6NI2uRTqq00HTDU2PgSr3lhNhijGHfqn0AAL8wP0QMjXBzizofuomLECI4xgbTsEamHliLiQxgOvGTTsocvOIKPk4Uj5OOwIDgvsEAQFeaHKAAlhAiOOYeWE4EU8BA5/fOr7aiabxUoOlK+5V27Dzp8i5pP07EYfiDpinizec7Yo0CWEKI4DQFsKbo1SaFgHQ+Dnpcr6gMgpC+dAMX6TDmnlcKYO2jANZNJBIJVCoVFAoFEhMTYTA0jXOYmZkJtVoNuVwOlUqFzMxMfl1cXBwKCgps6lu5ciWioqIQHh5utXz8+PFQqVRQqVQICwvDY489dsleEyGXC2uw6IFtNpXsFXtp+gojyMMk8gB8QuyvC5TRTFykQ5nzwymAtY8C2BYwI8OuRbtw9LOjHVqveSrZI0eOoKioCOnp6QAAnU4HjUaDjRs3oqCgAJs2bYJGo4FOp3NaX3x8PA4cOGCzfPv27cjNzUVubi4GDBhgNUUtIULVdBOXOf/1SurG62I6+tCJLtG9yYEyoO8YQDYcCOplu778lCnHl5AOQj2wznX5UQgYYzBUO5jlpXH92V/P4uBbBxE5PBJ+Ya6NVyjxlbh0d61YLEZMTAwfoKampmL27NlQKpUAAKVSiaSkJKSmpmL58uUO6xk+fLjT/Zw9exZ//PEHYmNjXWo/IZ2ZVQ4smt3JTuf6zuly5AoEyoAeSlO+rWUXL8cBdVVAXQ0ABtTXAhwDfIIBiV9T28zb1FWb1kv8mrY3pwaUFppmB7PHnONLPbGkA/A3b9E5za4uH8Aaqg1Y6b/SpbJv9HnD5Xqfq3wOnn6eLZbT6/XYu3cv1qxZAwDIy8uDRqOxKqNWq7F+/XqX923P559/jttuuw1isbhd9RDSGViNQsBxpmCjEaUQdFJeAaYc0TLrXkqrsDZQZrpEzzGAcQCYqUDzILOuGjDUmMp5+JjKePo3BZn28lBbk5vqaHaw5jei2VNWCPiHUS4saTfqgXWuywew7lJaWgqVSoVjx45hzJgxUKlUl3R/n332GRYvXnxJ90HI5dL8Ji4iEOaeybJC2xzYkL6u91y6a/pZV38c0Y8o0gEogHWuywewEl8Jnqt8zmmZqnNVeHf4uwjtH4r4l+P55f7h/vAPtz9kisRX4rROcw5sSUkJYmNjkZGRgSlTpkChUCA7O9sqVzUnJwcKhaIVr8paUVER/vrrL9x4441troOQTsXUAcvfxMVxFun8dK7v3EL7mnookWt6HhgJRA2kHktCmjNfdKAA1q4uH8ByHOf0Uj9jDD88/QM4EYcZX85wOQfWVVKpFCkpKUhJScGUKVOQnJyMUaNGYfr06VAqlcjPz4dWq8X+/fvbvI/PP/8cU6ZMgUhE9+yRK4M5hUAkbhyBwDJ+pd6vzs8iWOUkXhS8EmIH9cA6RxFNSxgQNjAMN6fe3OHBq1lCQgKqqqqQlZUFmUyGtLQ0JCYmQi6XY8aMGdBqtZDJZE7rWLZsGWQyGYqLiyGTyZCamsqv++yzzzB9+vRL0nZC3IFPIeAASiEQJkH+znD1RrQranBbO2orAH1506O2wt0tstbZ2+ciPoAV5B/Lpdfle2Bbwok4xC2O6/B6i4qKmvbBccjNzeWfx8fHWz23tHv3brvL58+fj/nz59tdt2fPnrY2k5BOySoHlqOJDARNSLGegxvRrAhhMoPaCqC2CvwfCwfAoG98arHMr7vptViO6nDxlGnIsOZak8Ns2Q7zTXnNb9hr7XtYUWSqq/IsUHWuY9rnZtQD6xwFsIQQwbGeyKDZOuqtEAb+OAkpgoXVjWg2LneQZG+4MMvAzzJQNehNozZUFgO1F12rv/SYKaA0VLVctvkQYuZ9GxqHLmuoBTy8AHCAoRbQl5qGNnPELwwI6WM/mLUMfA01poC6vqbl9tXXmoZZ62gtHYc2ookMnKMAlhAiOKy+DkBjD0VdDVDf4OYWkbYS5NV2841opw4BRgPQYxDg5d/6oMUy8LEce9beOLSAdZBU8idQU2Zbp2cg4B1kClJry1v/2ppzJXg1KysEas6bAsXWbGdP1bmmnlTPQMAnyNQ53J7XVX4KqC4FvAMAsVdTQO3hDdTrTf9vbS9waaH9HzPmMYmdMfcaA00/MDx8YRqrWA+uqh5AYwBbW9H5e/YvMwpgCSHCUloIVlkKoLEHtqQAXI1FAEudFYIg+I5yrwBALDEFsIYqUwBSWdwYAPmYnnt4N5Wv1wO+oU29hlVnOybAbK6u3PRwF3tBdXt15GuqrwEqW+itNfMJATz9AO9ujdvqTf/38G483qcd9yKXnwKqS4Agmenz0DwoPnGgxePPldUCAJjRCJzYL8g0iEuJAlhCiHA09nYYGyymkm2GUggERpBdsI2Mph4ylP3tWvnSvy5dW0jHqykzPRzNvNaSer0pDcOShx/QUAMwY4ub8zMMmk9pNNOblVaPQhAdHY0lS5bgxIkTl6I9hBBin8UsSOYYlc+BtYyBaisva7NI+7gy5XandC4faKhzdyuI0NRXuRS8Ak3nN6sc2LJCwY6q0NFaHcA++eST+Oqrr9CnTx/Ex8fjk08+QW1t7aVoGyGENLHoWW26icsU/FgFQUbXvhyIewm6p/xsXtt75QhxFT+RQbPlQv7b6UCtDmAfeeQRHD58GIcPH4ZSqcS8efMQERGBhx9+GNnZ2ZeijZ1CfXU9ynLLUF9d3yH1SSQSqFQqKBQKJCYmwmAw8OsyMzOhVqshl8uhUqmQmZnJr4uLi0NBQYFNfStXrkRUVBTCw8Otlv/2228YOXIkVCoVYmNjceqUneFPCBEYZjUTV7N1dG4XFqF1wJYW2h9GipAOxlmkSAn6B98l0uaJDIYMGYLXX38dOp0OixYtwnvvvYcRI0ZgyJAhSEtLu+Le7IaaBlz49QIaajrmbmfzVLJHjhxBUVER0tPTAQA6nQ4ajQYbN25EQUEBNm3aBI1GA51O57S++Ph4HDhwwGb5woULsWTJEuTm5uL222/H6tWrO6T9hLiT+fzCn+CFFgQRYd5sZ5HGQsilZnlhycWsgy6lzQGswWDAp59+ismTJ+PJJ5/E8OHD8d5772H69Ol44YUXcNddd3VkOy8ZxhiMBmPLj3rTp8dY70JZg9HlAF4sFiMmJoYPUFNTUzF79mwolabhN5RKJZKSkqxm1rJn+PDhiIyMtFnOcRwqKkz5MuXl5YiIiHD5vSGkU7E4mxsbf0eKxI2r3NAc0jEElQN7hXXMkM7NsgfW6gefkP5mLqFWj0KQnZ2N999/Hx9//DHEYjHuvvturF69GnK5nC8zbtw43HjjjR3a0EuF1TMc33Tc5fJntp1xqVx0YjQ4ScsfMr1ej71792LNmjUAgLy8PGg0GqsyarUa69evd7mNlv73v/9h3LhxeOyxxxAaGoqsrKw21UOI21nMgsT3wNo5kTNP/8vdMtIGFAsS4pxlipTpRi4KXC21ugd2xIgR+Ouvv/D222/j1KlTWLVqlVXwCph6DWfMmNFhjbwSlZaWQqVSQSqVIjg4GCqV6pLs580338R7772HU6dOYerUqVi6dOkl2Q8hl0VoXyCkr20OLJ3XhYcfSoIOHiH2WKUQWP7go19/ANrQA/v333+jd+/eTsv4+fnh/fffb3OjLifOg0N0YrTddfU19XzOa11ZHUp/KUVoTCg8QzwBAGIfMTx87L+FnIfzk7I5B7akpASxsbHIyMjAlClToFAokJ2djcmTJ/Nlc3JyoFAo2vDqgM8//xxvvPEGAGDq1KlITk5uUz2EdBqhfcE8AgCUgxNzQPhgcIZ6AI1XF+jcLiiCil8F1VgHPHwBvxDTEGCV52zXtzR1rHmGqX/3Op8K1lUSP8DT3zSxA7FieYWJppO11eoAdvTo0Th48CBCQ0Otll+4cAFDhw7F33+7OKBzJ8FxnMNL/Z4STyDQ9G+Rh6mrxzvMG16hXh22f6lUipSUFKSkpGDKlClITk7GqFGjMH36dCiVSuTn50Or1WL//v1tqj8wMBC5ubn8aAb9+/fvsLYT4i6s8eIRx6FxZhsayk9o+E4kIcWEXgGmAE6IoxD4hZmuYFhOR2o5lS3QNFOUeXldNQBmf3rV3tebpkKtqzEN2F9TZj/wDWmcdre2Cqi5AMBoqs/DG5D4AgGNI+c4mpK1OQ8/wC8YAGeaDrahFhB7N07D6tP4eeJMdQNN0/IyzjQDWoMe0HfQNLuXmFUKAcWvNlodwB4/fhwNDbZ34tfW1rZ4pzyxLyEhAQsWLEBWVhZGjhyJtLQ0JCYmQq/Xw8vLC1qtFjKZzGkdy5Ytw9q1a1FcXAyZTIbnn38eycnJePvttzFr1iwwxtC9e3ds2LDhMr0qQi4dc28Ef5OD1YmezvSCIrRezW693BvAmgM4D29TwFausz99a6DMNI0pYB14WrK3zHK5d6DztgRYD9voMCA21xnYrLyl0MZA1zJwrm+cjtdeAO0qR6/B1YDZGc8AIKCHKViuq+rwESqshtGyHIVAaH8zl4jLAezXX3/N/3v79u0ICgrinzc0NCAzMxPR0dEd2rjOROwjRrch3SD2EXdIfUVFRfy/OY5Dbm4u/zw+Pt7quaXdu3fbXT5//nzMnz/fZvno0aMd1kWIUBkbTGdzkZgDwIGz6qpwT5tIKwn1OFncTHhJ+fUwBV8e3qbnHEyX2psHcIERzgPHy6m9+3Q1cO4IlgGzmaHaFIxePGX/R4p3MNBN5jiYNtfnaHsPH6C+xna5Xw/TtoAplcKc2mGVA9vYzpC+7jm2nZDLAextt90GwBRs3XvvvVbrJBIJoqOj8corr3Ro4zoTD18PhKhC3N0MQggsemA5UG+EwAlqGC0z81z09oJYy55PoCkoMuM4U4DibNvWBqAU0LRN8/fNHDh7K0097a39UcAH4E62b+nHRmAE3ztsMw5sSN+mzx5xPYA1Nk7PeNVVV+HgwYOQSqWXrFGEEOIMH8A29sDa7akgnZrgj5O9Hjx7QY693kSvANe2Je7TUb3Jbam38bPFncnjF7HI4UBoWPvadIVpdQ7sP//8cynaQQghLmMN5hxYmOJXq64K97SJtJIQb+Jqrj1BDgWrxBmvAHASz6bnNL61DZcC2DfeeANz5syBt7c3PySTI/PmzeuQhhFCiCNNKQSNPbCCjoK6NkGmEBByGXCipntuaBgtWy4FsKtXr8Zdd90Fb29vrF692mE5juMogCWEXHLmk7np/G4dAAn+0nQX0XSYKIAlxC6uMT2KUQBrj0sBrGXaAKUQEELczTwKASfimm7iajzRUwqBwFD8SogDHDgRwBoogLWn1VPJNtfQ0IDc3FycP3++I9rTqSw+U4SlRfZnB1ladBaLzxTZXecKiUQClUoFhUKBxMREGAwGfl1mZibUajXkcjk/AYFZXFwcCgoKbOpbuXIloqKiEB5uPc7eoUOHEBMTg4EDB2LOnDn8zXiECJnVKAREoOgLmRCnOI4fC5YCWFutDmAfe+wxaLVaAKbg9cYbb8TQoUPRq1cvh2OUCpWY47DwzFmbIHZp0VksPHMW4nZ8e5qnkj1y5AiKioqQnp4OANDpdNBoNNi4cSMKCgqwadMmaDSaFieJiI+Px4EDB2yWP/DAA3jnnXdw5MgRBAUF4auvvmpzmwnpLP6fvfOOk6Qu8/+7qjpOT/eknbQ5wyZYcpYliQIGPMB8HuAJ4p2KesGMiqI/BfH0gMMTARUQPTEhoLKkJS67LGzOeXLq7uncXfX7o7qrw3RPnp2e3ef9eu1OV3V9v/VUVXf1p57v832evCwE6WG2zNdRQgimBpnLJA8hglACRZH72iCMWMD+9re/5cQTTwTgT3/6E/v27WPbtm189rOf5ctf/vK4GzjRGIZBKKUX/fe5+nq+0tjA11rb+WpLG6GUzldb2vhaaztfaWzgc/X1JdsO98OmaRqnn366JVDvuusurr/+epYuXQrA0qVLue6667jrrrsG7efUU09l+vTpA9a3tLRw0kknAXDhhRfy+9//fgRnRxDKE8MKIQBrEldGCMl9fmohClYQiqOoWQErHtgBjDiNVldXlzVM/Ze//IWrr76axYsXc/311w+ZoaAcCesGlW9tGnK7W9s7uLW9o+RyIf0nLMejDX1jjkajvPjii/z4xz8GYMuWLVx77bV525x00kk88MADQ/ZVjDlz5vDss89y/vnn8/vf/17K/QpHBblZCAwdnv3mS1IrfKohk7gEYQgyIQSGCNgijNgD29jYyJYtW0ilUjz55JNcfPHFAITDYTRtfMqsHgt0d3ezcuVKpk2bRk1NDStXrpyQ/fzsZz/jm9/8JmeeeSY1NTXYbCN+ZhGEskNP5WQhUKFzazekw7tlqG1qIQ5YQSiBopCpki0CdiAjVjPXXnst11xzDc3NzSiKwiWXXALAq6++yvHHHz/uBk40FapC/wnLB93mu2lvq0NRiBsGX2ls4D8bB6+IUaEOflfOxMB2dXVx/vnn89hjj3HllVeyZMkS1q9fz7vf/W5r2zfeeIMlS5YM/6ByWLZsGatXrwbg97//Pf39/aPqRxDKiVwPrKKoXP6ji9j62E4A2t9qJ9QeAqCyuRJvsySML0fkOUMQhkKx8iSLgB3IiAXsLbfcwvLlyzl48CBXX301TqcTMGM5//M//3PcDZxoFEUZdKj/W23t3NrewTebG/lqU6M1gcuhKny1qXHM+582bRrf/e53+e53v8uVV17JTTfdxFlnncU111zD0qVL2bp1Kz/72c94+eWXR9V/Z2cn9fX1RKNRfvjDH3LnnXeO2WZBmGyyk7gARcHTUGGl0Xrosoes7c7/+vmsumXVpNgoDBPxwApCcRTV8sBKbP9ARjWefNVVVw1Y97GPfWzMxpQbGbGaEa+A9fdrre15y2Phiiuu4Ktf/SqvvvoqZ5xxBvfddx8f+tCHiEajOJ1OfvaznzFz5sxB+7j11lu555576OzsZObMmXzpS1/ipptu4sEHH+Tee+8F4Oabb7YmdAnCVMbIzQMLhDoi1g3+Q49/iMoms+xiZbOUXyxbxAUrCIOjZCenigd2IKMSsE8//TRPP/00HR0dA/KK3nfffeNiWDmQMow88Zohs5waww24rS2bQ1ZRFDZs2GAtX3LJJXnLuZRKVfaVr3yFr3zlKwPWf/7zn+fzn//8qO0UhHIkbxKXYfD4Z/5uvdewvIGq2VWTZZowTLJptMQFKwjFkRCCwRixgP3GN77BN7/5TU499VQrDvZo5ZbmppLvjYfnVRCE0WGVkrWpYEDDsmls/9NO9OQkGyaMnKP4N0QQxoRM4hqUEQvYe+65h/vvv5+PfvSjE2GPIAjCkGSyECiqmWZm1VfP5sXvv4KeNCQLwVQhc5lEvwpCcRRVKnENwojTaMXjcc4+++yJsGUAyWSSr3zlK8ybNw+32838+fP55je/KeVQBeEYxwohsLJ95Kgguc9PKcQBKwilyPHAyoP5AEYsYD/+8Y/z0EMPDb3hOPC9732Pe+65h5/85Cds3bqV//f//h/f//73raT/giAcm+SVks0gSmhKIT/IgjAEipItMCge2AGMOIQgGo1y77338ve//50TTjgBu92e9/4dd9wxbsa9/PLLvOc97+Hyyy8HYO7cuTz88MO8/vrr47YPQRCmHkYqO4krg9QMn6IoI/ajCMKxgaJICMEgjFjAvvXWW1bVqE2b8kuwjveErnPPPZd77rmHHTt2sHjxYt58803WrFkzaC7TWCxGLBazlgOBwLjaJAjC5FPUA2u9eYSNEUaHXCdBGAJVJnENwogF7DPPPDMRdhTlP/7jP/D7/Rx//PFomkYqleLb3/42H/zgB0u2ue222/jGN75xxGwcLXa7nWXLlhGLxTjppJN44IEHLG/2008/zRe+8AUikQgul4vbb7+diy66CIBVq1Zxzz335FU903Wd97znPezcuRObzcZNN93ETTfdBEBXVxdXX301hw4dYsWKFTz00EO4XK4jf8CCMI5YWQi0HO+dRBBMKaw5XHLdBKE44oEdlFGP3ezatYunnnqKSCQCTMyw3a9//Wt++ctf8tBDD7F+/XoeeOABfvCDH/DAAw+UbPPFL34Rv99v/Tt48OC42zUeZErJbtq0iba2Nn79618DcPjwYa699lp+9atfsW3bNh566CGuvfZaDh8+PGh/n/70p9m2bRuvvfYa//3f/82+ffsAU9C///3vZ+fOnSxYsID//d//nehDE4QJxTCMopO4JIRgiiIKVhCKo8jk1MEYsYDt7u7moosuYvHixVx22WW0trYC5uSu8U6Y/2//9m/853/+Jx/4wAdYsWIFH/3oR7n55pu57bbbSrZxOp34fL68f4NhGAZ6Mjzu/4b7I6ppGqeffrolUO+66y6uv/56li5dCsDSpUu57rrruOuuu0r2oaoql1xyCQAVFRUsWLCAlpYWAP785z/z4Q9/GIB//Md/5E9/+tOw7BKEsiXnq6VoRW5hcqOfGsiDhiAMTiKaDSGI9EMsOLn2lBkjDiG4+eabsdvtHDhwgCVLlljr3//+93PzzTdz++23j5tx4XAYVc3/gdI0bVzTaBmpCLsfXTZu/WVYcM1mFFvFkNtFo1FefPFFK7PCli1buPbaa/O2yYQYDIdDhw7x5ptvcuKJJwLQ39+P1+sFYObMmUN6cgWh3MkdSrPm/yjWf8IU42guhiMIo6Z7N/TszoYQtG2CAwegdgHULZhk48qDEQvYv/71rzz11FPMnDkzb/2iRYvYv3//uBkG8K53vYtvf/vbzJ49m2XLlvHGG29wxx13cN11143rfiaD7u5uVq5cya5du7jwwgutiXFjIR6P88EPfpDbb78dj8cDDPxxkB8LYSpj6AbPfD0bh6/kPOBKCMHUQi6TIJQgLV4h976Wfi+9XkTsKARsKBSiomKgZ7Grqwun0zkuRmX48Y9/zFe/+lVuuukmOjo6mD59OjfccANf+9rXxm0fiuZmwTWbi76XjHSSinaWbKu56rG560v2OxiZGNiuri7OP/98HnvsMa688kqWLFnC+vXrefe7321t+8Ybb+R5u0vx8Y9/nIsvvpirrrrKWufxeOjv76eyspLDhw/T3Nw8ZD+CULYo0Lkl+51UJQvB1EeyaAlCllgwK1Kh+CSunt1Q2QBO75G2rqwYsYB929vexoMPPsi3vvUtwPTo6brO97//fS644IJxNc7r9XLnnXcOmjZrrCiKUnKo3+GdA945E7ZvgGnTpvHd736X7373u1x55ZXcdNNNnHXWWVxzzTUsXbqUrVu38rOf/YyXX3550H5uvfVWEonEAHF/+eWX86tf/YobbriBBx98kHe9610TeTiCMKEoisKld1zK9t9vB6B9WwhbrBWSUfG8TjXkcgnCQAruYwM8sCW2OxYZsYD9/ve/z6pVq3j99deJx+P8+7//O5s3b6anp4cXX3xxImw86rniiiv46le/yquvvsoZZ5zBfffdx4c+9CGi0ShOp5Of/exnA0I2cgkGg3zta1/juOOO46STTgLgBz/4ARdffDFf/OIXufrqq/nBD37AsmXLpkSKMUEYjIq67APnfVe9DpiFTTRH2lMhN/YpQeYySViTIJQmmwd2cu0oR0YsYJcuXcpbb73F3XffjaZphEIh3ve+9/GpT31KhqdHQFtbm/VaURQ2bNhgLV9yySV5y7k8++yzA9Z5vd6SE9vq6+uLthGEqUqwNTsT9+O/Pw111kmQjPLARb8kFTfEszfVEP0qCCXJPODJg/lARixgDxw4wKxZs4p68g4cOMDs2bPHxTBBEIRCDMPgr1/4q7U8fWU1ypxmM91MsXhYoXyxfpDlugmCReHE61IeWBm5GHn4/Lx58+jsHDixqbu7m3nz5o2LUYIgCEUxoG5xHWDe2BUlNwuBeCqmIvI7LAg5OL1mqqw0RSdx1S445idwwSgErGEYRWOW+vv7p1yJUvmhk3MgTC0UVeGsm88CSmQgAAkhmCLIrUcQSlC3ICtiM7e5zPdF8sBaDDuE4HOf+xxgejm++tWv5qXSSqVSvPrqq+OSy/RIoGkaiqIQDAbxer3H7CQCwzAIBoMoioKmaZNtjiAMCz1pjqUpmpJ13x2bX+GpjSVg5eIJwgDqFoDdg6K8BYBRdxzMFs9rLsMWsG+88QZgip6NGzficDis9xwOByeeeCJf+MIXxt/CCUBVVWpra+np6aGrq2uyzZlUFEWhtrZ2QMUzQShX9JQpYE0PbFb8SCGDqcmx6kAQhCFxVmRDCGxuEa8FDFvAPvOMWf3m2muv5Uc/+hE+n2/CjDoSOJ1OGhsbSaVSk23KpKJpmohXYUqR8cCqGjkBlCKCpixy6QShBErOJC55MC9kxFkIfv7zn0+EHZOCqqoi3gRhimGkzBv5gBjYwlgxYWogHlhBKIk1OVUE7ABGVUr2u9/9Lk8//TQdHR0D8o/u2bNn3IwTBEEoJC8GNi+EQLIQTBXkGgnC8JDQqNKMWMB+/OMf57nnnuOjH/0ozc3NEr8kCMIRJRtCoIj37ihALqEglEJCCAZjxAL2iSee4PHHH+ecc86ZCHsEQRAGxZrEZcv3wEoIwRQi7xqJghWEoigl8sAKwCjywNbU1FBbWzsRtgiCIAyJ5YFVydE+SnaorURZZaF8yBsOFf0qCCXIva+JgC1kxAL2W9/6Fl/72tcIh8MTYY8gCMKgWJO4cj2wIoKmLBKGJgiDIJO4SjLiEILbb7+d3bt309jYyNy5c7Hb7Xnvr1+/ftyMEwRBKMSaxKVKCMGURa6RIAyDbAysfGcGMmIB+973vncCzBAEQRgeeTGwRbx3Mlt3iiEOWEEoiUziKs2IBezXv/71ibBDEARhWOTFwFrqR8nRQXKjL3ckBlYQhoEieWAHY8QCVhAEYTLJK2SQSkA0AEYqJ2HiJBonjBhFkWIyglAcmcQ1GMMWsDU1NcMKtu/p6RmTQYIgCIOh9xwG0oUMIt1wsDvvfYkgmALINRKEYWGl0ZIb2wCGLWDvvPPOCTRDEARhGHTvRu9rBQaWklVkEteUQUIIBGE4SCGDwRi2gP3Yxz42kXYIgiAMTiwIPbvJpHlVtYL3M0IoFjqSVgljRLJoCcJADN3g2W+8QLAjbi0L+UgMrCAIU4O0107PjYEtQtv2F6g9oQaXr/6ImSaMjKi/03p98K2/oTtSKIrCrJWXyXUTBAAFOrd20b7NzLkvAnYgEj0vCMKUIr+QQZaMJy8RDdGyebXEjJUphmHQuuVZazkZDRDr7yYa7JbrJghpFEXh8h9fai337e+jdX0rretbCbYGJ9Gy8kEErCAIU4qMBzYzucEik24Gg1DPIQLtu460acIwCLTvIpSeiJePXDdByMXT4MFTZxaLeul7L3HvKfdy7yn3su5/1k2yZeWBhBAIgjA1SAtUvYQHNoM51KbQuvkZvPXzUDW5zZULeipJ6+ZnyJ25ZeRdRrlugpAh1BEi1JMA4IxPn86JH1sJQGVz5SRaVT6IB1YQhKmB0wu1C9BT5qJacPeyQggSCcAgEQ0S7NhzRE0UBifYsYdENDhImIBcN0EAM9Tm8X/9q7XsafDQfHIzzSc34232TqJl5cOIH3FTqRT3338/Tz/9NB0dHeiZKcFpVq9ePW7GCYIg5FG3AMO1HdhT0gNromB3VeJtmH+kLBOGgbdhPnaXl2Q0G8NXEMks100QAAxoWFZPrL2NPS/6SSX0odscY4xYwH7mM5/h/vvv5/LLL2f58uXDKm4gCIIwXujOOsCMge3p66Hbn1/IwMwDa9C87AIZhi4zVM1G87IL2PPiH7Ir835C5LoJApj3t1VffxtP7NtlCth4crJNKjtGfJd45JFHePTRR7nssssmwh5BEIRB0ZOmJ0K1KWB3E43FUJScfKKKgqduFr7GhZNnpFASX+NCKqpnADvMFWbIMqDgqZsp100QctDs6dh/8cAOYMQxsA6Hg4UL5QYjCMLkoKfSAlZV8DbMx1FRZb6RFrAOl4/pSy+Q0aEyRVEUmpecn7MCHBXVuLx1ct0EIQ/FCpVKxVOTbEv5MWIB+/nPf54f/ehHkqtPEIRJIeOBVWxgd1Uyc+U7896fvvxiSYZf5ji9dXnLs095F4ve9jG5boKQiwKa3ZRpqYQI2EJGHEKwZs0annnmGZ544gmWLVuG3W7Pe/93v/vduBknCIJQiJFbiUtRQNfBQDx3UxXFwEhJfJ8gFENziAe2FCMWsNXV1Vx55ZUTYYsgCMKQWDGwmgIoGEYKAyM7GUgGh8qfgmuki4AVhCIoaOkQAl0E7ABGLGB//vOfT4QdgiAIw8KKgU17YHU9X/xIeFP5U3iNCq+hIAgm2RACmcRViBQyEARhSmHFwKYFrJGubCARBFMUBYyUeJcEYSC5k7jkIa+QUSXb++1vf8ujjz7KgQMHiMfjee+tX79+XAwTBEEoRjYGFkz1U+CZEA9s+VMYQiAeWEEYiCJptAZjxB7Y//qv/+Laa6+loaGBN954g9NPP526ujr27NnDO9/5zqE7EARBGANWDKyaCSHIv7GLfp1aKICRSky2GYJQlmQErEziGsiIBexdd93Fvffey09+8hMcDgf//u//zt/+9jc+/elP4/f7J8JGQRAEi7xCBqg5IQQSQzBVGBgDKz/OgjAQJStgxQM7gBEL2AMHDnD22WcD4Ha7CQbNmtYf/ehHefjhh8fXOkEQhDSGbvDM15+ha3sXYJZaRMkJIbCyEMiNvuzJ1a8KdO58hR3P3c/O5x8gGuicNLMEodywJnGJB3YAIxawTU1NdHebtcfnzJnDK6+8AsDevXtl9q8gCBOHAp2bOznw/AEg7YFVlAHeO7kNlT+5vxUGBsl4mFh/N9FgNy2bV8tviSAAKNlJXLoUMhjAiAXshRdeyJ/+9CcArr/+em6++WYuueQS3v/+90t+WEEQJgxFUbj8rsstcRPqjNO6oYuOt3qI9OiShWAKEWjfU+Idg1DPIQLtu46oPYJQrkgMbGlGnIXg3nvvtSZN3HjjjdTW1rJmzRre9a53ceONN467gYIgCBk8DR48DR4CBwOsfaidtQ/9FoDjP2g3a8uCuGDLHD2VpH3bGmt54IOHQuvmZ/DWz0PVRpUoRxCOGiSEoDQjvjuoqoqqZh2311xzDddcc824GiUIglCMUEeI/rZ+AM7/15kc9/6z6e48QDj4Ft2vi3CdCgQ79pCI9g+yhUEiGiTYsYeq5sVHzC5BKEcsD2xSYvsLGVUhgxdeeIGPfOQjnHXWWRw+fBiAX/ziF6xZs2aIloIgCKPDMAwev+lxawJQ0/Eemk9qYNqSSty1quXJk/jJ8sbbMB+7qzK7oogH1u7y4m2YfyTNEoSyRDywpRmxgP2///s/Lr30UtxuN2+88QaxWAyAYDDId77znXE3UBAEAQADGpY34Gn0AODyaeksBJkbu2JtJ5QvqmajYfE5g2xh0LzsAgkfEARATQvYcFeEzb/ZPMnWlBcjFrC33nor99xzDz/96U+x2+3W+rPPPluqcAmCMGEoqsKqW1Zh6KZCdXltgJpTyMDI+yOUL976edbr/Py9Cp66WfgaFx55owShDMmdxPWXm/5CqCM0yRaVDyMWsNu3b+dtb3vbgPU+n4++vr7xsEkQhGOATF7XXK9C4bpi20T7ogA4vaYHNlPIIBNDICEE5U+eaDVA1Rw4K+tweeuYvvQCKUohCJj3v7UPtZoLKkT8EW6fcTt3rbiLNbet4U+f+BPr7l034j5Hc98tR0Y8RtPc3MyuXbuYO3du3vo1a9Ywf77ELAlHB4Zu8Mwtz9C1tYtl1yxj2dXLhtXm2W88S8PyhmFtPx6UsnM0thwp+zM2d27pJHAwwJrvreHpLz2Nu9aNb5aP4KEga/97LYdfPcz006fTubmT1+96nTnnzeHVH79KMpIEwOWzseulh4lEwnn9x8OBCbNdGB8K88BW1M5g3unvm0SLBKEMUaBnv/nAnopkY2A7N3Xy9JeeBmD9T9ez9u61JCIJYoEYiqLgm+nDN8sHmN+1ri1dOLwOYoEY8WAcu9uO/5Cfv3/x7yQjSXwzfSiKwut3vc7sc2bzmw/8hlBriEhvhLnnz8XT4Dnyxz4MRixgb7jhBj7zmc9w3333oSgKLS0tvPzyy3zhC1/ga1/72kTYeMwyHEFh6Aarv76abf+3jYXvWMild1x6hK08coxUVBY7f7nrlly5hPsvvB89rnPGZ85g7d1r0eM6Z958Jh2bO9j91G7a3mhj+5+28/SXnqairoIzbz6Tzi2dVp+5Ni29eqkltob60utJ3dr3WZ8/i6X/sNSyK/d1Zh/PfuNZ6pfW07mlM+9vxs72De3se2Yfc8+fS8W0Cp655Rl2P7WbF//fi7z5wJvY3LahBW66UEBGLK69e+24i9nM5/WNn71BqC2E6lTRYzq9u3rppZeW11tQHSp6VOflH70MOsw6ZxbhrjC3T78db7PX6iseTmGkUoCB0+FEUSIA9LduxYguQXH5xs1uYYLIhC1LKVlBGICiKFzy73O59z1vDrpd+4b2vOX+ln5a1rXAEF+rvt191vYAqHDHnDuwu+wk+hOgwF3L7+Ka316Do9IBQGVzZd59eDJRjFGMt335y1/mhz/8IdFoeijP6eQLX/gC3/rWt8bdwLESCASoqqrC7/fj8038D1qh2CgUJIXipFj7jCBa8g9LeP6bz+M/6OfUG05lxhkzBvT1zC3PsOvJXbS+bg4zfHLjJ2lY1jCknXpS54GLHmD6KdPzRG+ud0xRFJZds2xQmwtFZTHxlft+rmg86/NnlTwHxYRnRpS1b2jH5rFRf1w9M86cgdPntMRcrh3P3PIMe/66h84tnaz4yAordsh/wE/r+lYaVzTSu7eXuD8OgM1tM717Ctgr7SSj5msjnv8VcVY7iQVjVM+tJhlJYnPZ6Nvbh6IpzF01l72r9wKw+IrFVNRXsPfpvbhqXNTMr8EwDLq3djP/7fPZ/OhmQq0hVLvKO3/8Tl7+4cv0bO+hoqGCVDxFrD9G7bxaFl62kN1P7aZ7VzeeOg+h7hAVtRWEO8NUzakieDiInq6Trbk0GpY3EO2N0t/eTyKUsGJCNbfGsn9YxqxzZhFoCbDnr3vo2t7Fig+vINgapHtrN7PPm82G+zcAULuglv7Wfq7+zdXUL6sfl5uWYRg8etWjbP/jdozk2Ib6T76mgfrzY1RWVDJnURMP/fNW2raG+fDPlrDwvGoSnmbs01eM2WZh/Olv6+f25ttBgQ88WUsipeOoqALMH+1ZKy/D5aufZCsFYfJJbfs7ty55cbLNsDj/6+ez6pZVE9L3SPXaqAQsQDgcZsuWLei6ztKlS6msrBy60SRwpAWsntK5e8Xd+A/6mXP+HPY+vZf5F80n1Bmi/c12Zp87m2ggStsbbay8diVd27pIxVJUza5iyfuW8Npdr9GxsYN4II7NZaPp5CYOvXgI1aaiOTSu+d01/PnGP+M/6KdmXg0KCqHOEDF/zLKhckYl7mo3M86Ywen/ejpNJzQNEIS6rvPDWT+kv6WfqnlVVEyrINGfYP7b55tiaadZLlhB4aTrTyLUGWL7H7ZTMa0CRVNQVZUlVy2hZV2Laa8/DhrUzDNFWuBAgAtvvZCz/+1sfv0Pv2b7Y9tBgcYTG+nb10esL4bD6+Dkfz6ZGafPyPdqpkXOrid28c7/eicr/2klP7/g53Ru6iQWjKHaTK9dBsWmYOgG7lo3ke4I9go7p9xwCgfWHMh/ClUYMMFHsSsYiUmImVTg8v+5nMc/8bi1yuaxkQwli27u8DmIB+LjtnvNpZGKDt/rdfInTubUG04FRv8EnnkIaXujjV1P7hqzgM3l/H+Zyfane0wB+7/Hs/BtNeY+axeg1C0Yt/0I40NGwCoqvP+JWuKJ3M+2gqd2BvPOvEZiYYVjntBrT/LDt71KKjb0thNN08lNfOjPH5owD+wRE7BThSMlYDNDo1t/u5VkNIl/n9+cIpfRWTagmDbRyAosFRxeh+URHA9Up0rTiU0YhkHrulY89R6q5lRRNbsKT5OH13/y+oA27mluIl2RvHU1i2vo3dE70PwhhFD1gmq8zV4OrjmYXVlMSDoUjLiBu95NzbwaKuor2PW4WU6yemE1ofYQiWBiBAee3sdR/emeHEb7BK6ndO5afhc9O3swUuN3YZqWVvChe5fw0Ce20bYllCdgAZh9FjjLY8hLMAm2Brlj+h0lBKzJ7FPeTVXTokmwThDKA8MwePQd/82O1d3oBfrhSDtfFr5zIRd+50KaVzZP2D5GqteGHQN73XXXDWu7++67b7hdHl2k4we7t3dnRVNu4YzijrX8GBWdcRWvAHpMp+W1Fms51B4i1B6iZW1LyTaF4hUoKl6BIb14fbv7rDgbiyLfucwwfaQzQqQzf/99u/oGNhgKKVoyIZz8iZM55YZTRtVWURWq51bTva274A1G/KCxaFUVVdOdeBsdLDq/Fm+DI6eQQf62eio5uootwoShJ9M3xJIOViknKwgYUL/IzaENNvq7kubvmgKNKxvp22uOZI4rg9yLpy2ZNqHidTQM+85w//33M2fOHE466SRJU1MERVG47MeXsf332yfblOEhl7A0hd7yXC/5McyKD69g1S2rRj18pCgKM86cwe4nd+e/kfNZVO0qp950Kq/96LW8TWyVNpL95kU58+YlvP3GqtLDywWf7VDPIbwVNcW3FSaF/q79QGEO2FyknKwgKKrCBZ+dh4JBR4sbRbNbc0keuOgBAocC9O3vo/GERhLhbBaCyqZK2t5sMwVp+resdnEtekonGUlaWQh8s3wkQgmS0aTZVjXD8UhBZVMlH3r8Q5Ytlc3lFyY6bAF744038sgjj7Bnzx6uu+46PvKRj1BbWzuRtk05fDN8uOsGDr8L5Y3qMme9A0xbPo3AwQBxfxxFU3D4HLhr3fTt7sNZZU7esgTSYA8BxZ5kR+FpHFWbUn2UCmMZgmlLp3HpHZfSeELjmGOf+lv7i65XHSonXXcScy+Yy6ZHNoEGvpk+goeDVqx4354+lr1rBpd+srp45yW0kKd25phsFsYfT91s67VR9AOuYHdVSjlZ4ZhHUVUu+MzsAaFQ//TMP/HcN5+jfll93mRowzD4zdW/wb/fz4n/dCL+/f4BGWhy22UmTXds7sAwDFpebSEWiHHjmzeWbfqsDMMWsHfddRc//OEP+d3vfsd9993HF7/4RS6//HKuv/563v72t0uwPRDqCJEI58RpFoqP3JjYYaA6VOwV9iGHCeZcOIeW11rMfaf7VzRlzHGGdUvr6N7SPfSGGXKO13qSK0HV3CqCbUFLOI6InPhW1aGix3P6UEBz5sTlFlwDR1U6xlg1y5Ke96Xz6NjcwdbfbmXhOxZyyf+7hAcueoBkLEnVrCqWXrWUrq1dTFsyjc4tnXRs7gAgEU2w+/HdqHaVpVctxeaxsf3324n2RVlw6QJ6dvXgP+A3c/cp0HRSE54mD7v/YnofF122iP1r9qM5NYyUQbQviqIpeGd40eM6vlk+vDO8dG42c6Umw0nmXTIPp89JMppk11O7sNltHP/e47FX2unZ1UPXli5C3SE80zyEOkOomoqj0sHKa1fSu7eXvU/vNY8996uaPjfuaeYEON9sH4EDAVSbysrrVrL+f9ZTUVfBwkvHXhnJMIys91WFjz71UVzVLtb9dB3TT5nOKZ84BUM3cxYuf/9yurZ25d+cu3dDz+6S/WcOq3CASIagyw/rmpR8QJNysoIwGJnKhANIl9xe9v7iqSYL2ymqwgXfuMBsmiNuy128wgjzwDqdTj74wQ/ywQ9+kP3793P//fdz0003kUgk2LJlS9lmIjgSGIbBn278E8mw6eKqX1FP19Yuc6a1YqZoqmyuNONBFUA1PUyBgwEclekZ5un1TSc2UTO/hgWXLuBv//43c6JUPIW9wszNptgV3DVuwl1hTv74yUS6I2gOjfpl9QQOBvDO9BI8FDS9XZkfh4Jh8IzAVewKRtKgdlEtyViScEeYZCTJJT+4hAMvHqB7W7eZEy6coPHkRsuDpiiKmT5qfx9NJzZRPa/aSpiciqfo29OX3ZdNQdEUqmZXWblUNz2yCf9jfgDsXvuACVqKTQE1J4WVAnWL6/DO8BLpjdC9rZtL77iUjQ9vJBkzEzFnrsO+1ftIRVPUr6ine0c37ho3kZ4Il/34MgKHA3Ru6RyQR/bCb15ovb72uWuHvNa/ufo3VEyr4KbNN+Fp8Jhf/BnZp9pMmrJUPMVZnzuLpVct5dGrHsXmtvGOH72D3U/txuaw8cm3Psnau9cWtQnMdGcPXvwgzSc3c+kdl2b3XZ3dN2RvPLlCO5MGLdeewnPVvbWbBZcuwFXlstpmbNEcGuv/Z72VomusGLphVdFafPli5l9setemnzrd2qbkTTkWHFS8ltxn7QIUmcBVfgz6bK3gqZsp5WQFAch5NB/e1qXuoRPcdjIY9eOtoigoioJhGDm1yI9h0k893dtMQeD0OelYbHrrFEVh6VVL84RFMc9eruDICBVVVTn9X06n+eRmXr/ndVLxFGd+9kzLO7X0H5by3Defy3vayqQrWv+/6wm1hWg6qQlFU8wsBA0efLN99B/uJ+qPcuqNpzLj9BmWyMmIpbNuPot4MM6yq5ex7n/WWQLKOtyCYYjc9c9+41naN7XTtaULZ5WTqllVA4YwOjZ10L3NzIfa9kYbiWiCmN+sEuKb5cM302fla21e2cw5/3GONdzx3Defo/6L5n5PvfHUvMuQOYamk5osUTbAkzdO13rZ+5dZArLwi6/a1DwhbOgGjSsaWf6B5Sz9h6UEDwdZ9v5lVDZVWk+/xVBtKv/07D8Nuu9i+y/Wz1DCvJCdf9kJmDW4xwNFUahZUEPb+jZmnD5jZI2HE3dfMAiU8DRjlxRaZU3huJ2zsg5FUaScrCBkGJl+PaYYURqtWCxmhRCsWbOGK664gmuvvZZ3vOMdqGp5zvM90nlgx4tSAnE07TMiNzfmZSx9Hwmmgo1HO3v+vodfXPILGlY08Mm3Pjkuff7huj+w4ecbuOi2izj3P88dfsNoAA6+Mugm/3vVRg6/1c+ld8zhjE++TypxlTH+g37unH0nml3hqj9Vk0iaIzDL33kzSpn+lgjCpLD3OUjGYNaZcJTf0yYsjdZNN93EI488wuzZs7n22mt55JFHqKurG5OxQmnG6sovbF8Y81LuwwRTwcajHdVuConx8sCC6SEH0yM8UVQ2LBLxWu5k3CYFTtadzz+AoqpSiUsQLMQFW4phC9h77rmH2bNnM2/ePJ577jmee+65otv97ne/GzfjBEGYPDSHBjBuMbCQI2DtIxSwwxlOTm9idx27sfhTjcLLGgv1AAotm1dLJS5BEAZl2AL2H//xH+VmIgjHEJrdFLBl4YF1eqF2wRATuUwPheSpLn8GnzdhEOo5RKB9l1TiEoTMk7nc1wYwokIGgiAcO2Q8sKlEGQhYgMyErCIith9ndkFu9GVPsGOP+UJRSuSBRSpxCQIMUq1OkGh5QRCKkhnmn5AQgtHGwNYtgOknA6a/def+nexpOUgYp9zopwh6Kkn7theH3C5TiUsQjm0kBrYUZS9gDx8+zEc+8hHq6uqoqKhg5cqVrFu3brLNEoSjHssDWw4hBLk4KtIvVKKxKPGUDum0fiAO2HIn2LGHVMIszjJYVJpmd0slLkEQSlLWYzO9vb2cc845XHDBBTzxxBM0NDSwe/duqqurJ9s0QTjqsWJgyyWEIENaoeq6WTQkGQ3RtXf9gPeF8sTbMB+b0wOEBy2VPH35RRI+IAgWcl8rpKzvDt/73veYNWsWP//5z611c+fOnTyDBOEYolzTaBmGYeoeQ08vp0jFwzlzHeRGX86omo2GRWcBfyy5jbOyjqrmxUfOKEEoWzI3tsm1ohwp6xCCP/7xj5x66qlcffXVNDQ0cNJJJ/HTn/500DaxWIxAIJD3TxCEkZMJIcAAPTU+cbCZeNqxCNj+rv3mixI39Eiga9R9C0eGymlzgOIhBIpmZ9bKyyTrjSCAxPYPQlkL2D179nD33XezaNEinnrqKW688UY+/elP8+CDD5Zsc9ttt1FVVWX9mzVr1hG0WBCOHjIhBDB+E7nG6oHVU0m6dr8GUHL2erBtF3oqOToDhSOOanOg2swsEjZnBQvP/iDuqoZJtkoQyg1xwRZS1gJW13VOPvlkvvOd73DSSSdxww038M///M/cfffdJdt88YtfxO/3W/8OHjx4BC0WhKMHywPL+IURjFXABjv2kIyHi76XcdilEjGZvT5lUPA2LKB6+vEA1M4+USpwCUIe4oItRVkL2ObmZpYuXZq3bsmSJRw4cKBkG6fTic/ny/snCMLIya2WNV4TucYqYL0N87E7PUCRWNf0fV61OWX2ermTc+kUBWuylnjOBaEE4oAdQFkL2HPOOYft27fnrduxYwdz5syZJIsE4dhB1VQU1VSF4+2BzQ1PGJlNNqbNP2XQbbyNC2T2epmTefgwveYKSvp6GboIWEHIQ5E8sKUoawF7880388orr/Cd73yHXbt28dBDD3HvvffyqU99arJNE4RjgvEuZjAeWQg8NTOBgR7YzH3eVVk36r6FI0Tm2imAoqCqGQ9sYvJsEgRhSlHWAva0007jscce4+GHH2b58uV861vf4s477+TDH/7wZJsmCMcE413MYDwErKJkxI+S7suRzisq6WamDHkhBAqqZgckhEAQSiM3tkLKfpztiiuu4IorrphsMwThmGS8ixmMTyED849mdwHga1xIRXUTsDr9vtzopwqKAslEjN7W1wEItu9hx3P3oygKs1ZeJhO6BEEmcZWkrD2wgiBMDoZu8MzXn8HQ01WvyiiEoNAToahqXilZofzJDf8I9xwmGesHQE/FifV3Ew1207J5tRSlEIQM8l0YgAhYQRAGokDn5k5iAbNmfTmFEGRu5FYYpaKS66UQ0TMVyMbAJmOhou+Heg4RaN91RK0ShLJDHsxLIgJWEIQBKIrC5Xddbi23b2yndX0rretbCbYGR93vhHhgFdX0vspk3amDkfuy1AVTaN38jMTFCoJQlLKPgRUEYXLwNHiwV9iJ98f543XZuvXnf/18Vt2yalR9jqsHNiN8VLOvrKNCFGy5k02jNZh3ySARDRLs2ENV8+JxtyEa6OTghr/keewl9lYoP+TJvBQiYAVBKEqoI0QiYqY1uuJ/rmD6qdMBqGyuHHWfmclgY/PApikZQjD2roVyQMHuqhx1UYrBBKrTO42WzauJBrvJFwYKLZtXM+/Ma4gFu0TgCuWD3NcGIAJWEIQBGIbB4zc9bi3XLKih+eTmMfc7ER5YRdFkou5UY1hzAg3q5p9CPNQ7pJCMBjrZv+6PJKLB9MTD0jvY+cKDqKodXS+Wc9aMvd30lzsGbZ81RLVsmQgvsSBkEQVbiAhYQRAGYkDD8gZaXm/Bv9+PkRqfm+fEZCFQAImBnVpkK3Fpdjd60Ylc0LblWdpK9LDzhQdBUdMPNCO76MXF6ygwdAwDDqz/EwvO/SgVVQ3j068gZJBJXCWRSVyCIAxAURVW3bKKiroKAPTU2NNoGYZhCeFMha9R9pTuz1xSFC0vllKyEJQ/uZdoTOVjDZ1yeWLZ99r/yWdPEI4gImAFQSiJopnCcDw8sLl9jEcIgeXFk0lcUxcF9OTRUT42FQ/Te2jLZJshHLXIfa0QEbCCIJRE1cxbxHh4YDPhAzA+IQSWtysziUuRUrJThqPUU9my6W+S9ksYZ+S+VgoRsIIglGQ8PbDjJmCN/BeKoubFiR2l2uiowZxw9WfAnIxVOg/s1MPQUwTadk62GcJRydHzPRkvRMAKglCS8fLAGrrBc996LtvvuHhgzSVFVVGQuQ5TAcMwaNm8mnjEb66QayYIgyM3tpKIgBUEoSTj5oFVoGtLl7WYEcajwsgPIbA8sEr++0L5EWjfRajn0FHrTNLsbnxNiybbDOGo5Cj90owBEbCCIJTE8sAmx+aBVRSFi267yFpu29A2htK0A0vJ5hUy0OVGX47oqSStm58h91odbc6l+oVnoGqSnVIYT46yL8k4It80QRBKkvHAjsckLle1y3p97yn3Wq9HXpo244FN26RqR50QOhoJduwhEU0/rBylzxiB9l1Mm3fyECVyBWEUHKXfmbEgAlYQhJJkPLDjMYmrv60/3Sl8Yu0nrPUjLk2bNiUbQmAWMlCkkEFZ422Yj93lJRHtByUTwJy7hYLN4UZzVpBKxElGA6PfmaLicPtQVM2qlAVY1bqsz4gCdpeXpuPPo2Pny6SSCZKxfjDSld5GWCQh3HOIQPsuqiSMQBgvJD1gSUTACoJQkvHywBqGweqvrAbA7rKPsSxtYQiBVvCu3OjLEVWz0bzsAg6s+2OJ32KD6SsutsRfNNBZtIRsw6KzaNv2QlEhOueUd1vlZYtx3AXXl3xvOKVg9VSSHc/eZ4rwogeh0Lr5Gbz18ySUQBg7sSBk0rIlIuay0zu5NpUR8g0TBKEk4+aBNaB2US27n9o9xipcDJzEpSrmaxm1LXt8jQvx1M7Ev/cQkL5khvnKUzcTX+NCa1uXr55Fb/tY0X6GIzYngrwwiKIYJKJBgh17Js3GXEo9BMxaeRkuX/2gDwkdO1+21uupJMlYP3aXF8MwTC815kNDrpd7sIcHYYR074ae3dnl3r3mv9oFULdg8uwqI0TACoJQkvHywCqqwmk3ncban6wdWwYCIBHrxw4k4xEAWjY/Y+5DshCUPYqiMH3ZhXRv+T3QD4qC5qzA5nAzfekFZR87mhcGUcIDa3dV4m2Yf6RNG0DE38Hulx/GKFJYYeeLvzK/J0bx7/WB9X8quj4e7iu5vPOFBwu2VjDPkVlkREGxPOWqZrNEcjIetQSx2Uy1BHHmIaBQaBcT1IY+SFlhRUXBzDlsd3pQbY7sW5Msvos9RNR6PEyrqireICNqRcSKgBUEoTTjGQOb6SMjikfVh2EQbN9DrcdtTeJKRDKxkmlbRb+WNS5fPTNPeAdwHwANC8+gbu5Jk2vUMMkLgyiK+eHb/eKvBoiisYRERAOd7F37GMli3t90vK9lgWGk+xrkoVNPDfeQx0BOyWcjHdhjZEVvKZGMoWMYg7yfQ6GgLm2KbllTzIM+UHxnMB9IcgWvkT53pc9zWrAryqAe6migkwNvPE487MfQsw8ZToeTadOnD348PbuhsuGYDycQASsIQknGMwtBJhXXWIoYBNp3kYgGwOMuvZEI2CmD6XAtb69rIZkwiFDPYYp92BLRIIlo0BRFijrkRLCiQi0t9EoLq9xt9eELOWGEGEOEjBRvg2FgGEN5qIsz7FEIeVKXPLCCIJRmPD2wGRE82hCCTB5RJS14jMIbeKZkuD52sS1MLEaO16rcwwYKURRl+B5jY5BhbUEQxoR4YAVBKMkAD2wsSNq1AKQnTtk9pittiOGssYYQWBNoKisG3S4e6htV/8IRJGeofKphGAZde9cjwlQQJhcRsIIglCSvlGzhrNhCHD5wVZk5Pm0usLvBUWkJ27F6YDMTaEp5YDOePHtFickPQtkxxZyvgBnGEu49PNlmCEcpA0aWSjEVvzzjjAhYQRBKYpWSDXZBT2TwjeMB818hNg9UNWNE4sDoPbCZCTTx/a8V30DJ/JEbe7mTV+53Cv0Q66kkLZtWT7YZwlFMLB6jvaudxmmNJbfRa+ahHuMTuEBiYAVBGATLA9vfM/pOkiHo3oXeuhEYvQcWwFfdiKvCnHGtqRpOhzNjqbXNsD0YwqRg6Abr/neDuaAo5kSnKUKwY09+yidBmAA6ejpo72ov+l57VzvBhNzjQDywgiAMguWB1cdhElc6U4yqDMxLOSy6d6P07MbrMkVrbXUttdW1dPn9dAX8KIiwmBIo0LunFwA9ZUwpf7m3YT42Z6WIWGHC6ejpwN/vp76mnpqqGnr9vXT2dqKrDhaXQZ7hcmDqPPoKgnDEUTDFpjEOaSMzw8aKETcng42EQeJvp1VVMW/RyVknrDgnyhpFUTjnC2cAEO5J0LGpj9b1rbSubyXYOtKURUcWVbMxffmFk22GcIwQi8dIpBIApPQUsXiM5mUXSJniNHIWBEEoiaqmsxCMhwc2nYVA1ZSR5TCMBQefPAY4o13ZNFoSQlD2uKrNPL6puMEjlz0NPA3A+V8/n1W3rJo8w4aBr3EhFTUzpvZErnTxA1WzMWvlZQADiiykknGSsVDBpEndrKSVTuyfSdAPsO/1P5CI+IfacfpvYQo8Fc3uIhWPDHxvDNhclSSjoXHt80hjlcxWFDy1+eWWj3VEwAqCUJK8LARjJJP6U1EB/yFwLR1mw+HteyoNRR/rRHrCAGgOhat/fxG+RnNItLK5cjLNGhaKojBj+UXsX/dH4pHA4BWvinagYnN6AEjFw+mRCT3vfUVRUG3O0oIuJ264WMUnGChIhyqZuuhtHxvZcRRw/IUfL1ltbDxKtQ5Wyaxj58tD7nM4thXbJlN5S1E1q4QtMOg511PJoauhDZOMLZrNyfTjzptyeZMnEhGwgiCUJBOvOh61AfI8sIFDUD1rYkohige2rDEMg5duNzNJVE6z03BCLTUzmifZqpHh8tVz3AXXT7YZgzJWQToaXL76CdvvYH1XNS8eU/uRbDMYpdoWCuOMEM6IYCguulu2PIvRtx+A6ubFMMaHgKMNEbCCIJREUcevEpdVyEC1xvrH3GceSmaoc3y7FcYZA6rnVcFzoNok6Zlw9DNaYaxpdlKZG9o4eHOPNmQSlyCMJ7EgRAPZfyOdrFRmqA4z1k0fl1KyaQ+sbYSSZbhDZqKEpgSKqnDSP51gvRYEoTiqzZ4TziBP5oWIB1bIkikTmmEY5UEnhfGwcyKOtdRM+doFUNkwNc5tAVYM7HiEEKT7UEf62Oz0mudwkIlc8YoGMLaYC+KCLXuMwu+CIAh5RAOddO19A6/LDkB/5z5ad24Yl3jiowURsBPNZInC4e43FoRYyIxJjBRJVl+7AOoWjK7viaCUSHTVmDZoDtMTZ3ObdnmbstsMdaxOHzirIBEyk5bqKUjHJ6HaQLOB5oRUPL3ODomwuT4RhViRKlRg2lvMZocPauZk7cyc11A3JKNmSdZkwvzr9JnHlIxCRZ3ZPh4237N7Br6O9kEyBnoim4DV7jL7sbsBBewVWVsS4fzl9DW18sAO5YG1uU1lGg+V3MQKIchU4hqJcMl8BoucR6N2AUnVbU1uEP06BchM6FNAXOeCkI9hGLRsXk0y1o/hrDbX6UmiwW5aNq9m3pnXyGQuRMBODEMJJYcXNDvmkEBOWhG7Jyu+KupMIZKIQCpqbprIEQeazWzr9Jp/Dcwynqodor3FhUSuJzAehr79EBsi7UnPbug7CBXV5n6iAUgWKSnqSAsjxTBFpLuGPJGUEVWGYR6rnjDPgbsGDMXs0+YyhaBimH0ZSlaUAQQOg/9gcTujvea/Qrp2gG8WhNpLC8wMscDQ24wn8QC0m9WpaNvIoENE/R3Z1907R7e/WCC/n6Fw1aBg5iA0Bkuj5ZsJjemMAhkR3rFlwLm0QghUxbzuTu/IHobq0p/fw+sgFedg60Gi8RiLFr0delvNz4pp7fCPUZgULA+sIg5YQSgk0L6LUM8hICeNFgpgEOo5RKB9F1VNiybRwvJABOx407G1tMjKEC8RFxnJEWDDFSn9xcvNFaWUJ3Ao9PjQwiceMP9l8B8aXt/D3W60JKPQM0rBd0QpQ9EV7UUNm5+vkoUM3DVZ8QpZUVrkQcBKo6VhftZb3yz++fU0QGWjee3sruwDTEbcpm/okViEeCqVfc/a0QiOUZgcrNyWIB5YQciip5K0bn4G0oI1Nw+siULr5mfwVtWj5pZhniJhaeOJCNjx5MArR9aDJwgTjDJUIYNIrylYc2+cJcbw89JoQemHr1CH+a8YNo/pvQfsNjuqZs8xNjfhulDOZD2wCiJgBSFLsGOPmUM2Tea7oqoqLqcLj9uD1+NFPfTawMa+mYOnJxxsxCvzXjwMGObX0u4pa2EsAna8EPEqHIWowylkMEzBOEDAjoZkNjRm3sx55ovu3Si2yqwMEv1a/oh+FYSieBvmY3d5SUT7AYOqyioA3C43i+YMETYQOGT+s3nAVQmpRHY+h56EVGxgG1sFYBQPDcyQGyZWRkgarfGgfWC8nyAcDWRGqMajkMGASVzjRc9ubKERhNIIk444yQWhOKpmo3nZBYBBQ20DNVU1I+8kGTJHuCI9pjZJhIqLV4BkeHDxCqYoPvDKyO2YYETAjpVY0Ly4gnAUMiwPbCElZuWMOo3WMLCH2ixPnoQQTAFyYmCllIEg5ONrXEh1/WwapzVOtilZYoGyE7EiYMeK/FgKRzEZb+mgabQKBavTaw45FTBhHljLDBFCU4W8GFi5bIKQh6IoNM45cbLNGEgsYE5ULxNEwAqCUJJMGtyShQx8M4sH+FcNFLCZiWDqRFdfkmfK8keyEAjCoDjc5TlxCv/BsqkwKQJWEISSqEN5YIsI1VJkUnEp2litKoHooCmD9UAkAlYQph5lMvIsAnasyLClcBSTSaM1aCGDYTIuWQgGQZEY2KlDto6B6FdBKMZIis4co0garbEyjDrtUw7VbuXaPKbxzTQ9jPH0LM1EDNDNH9xoiapdwzl3rhpTbRWr0paLrcKsuDZYhgvVYVY0K5UixdNglqk1gEgfJPqzpWXj/YPEBqS7T3tL9WQJUVjqAa7Ien0CY2CTrpqscBUBW/bkVeISBSsI+cSCZvVIYVBEwI4Hg9RpHzbuWnB4INyTXzK2kMHEj+aAVHz0NuQmQe4uUbXLVQOeOkjGASPtSUmXhnV6ob+zdHna4Qiy4aC5wO0Dp88sVWuvyCZfTkZNoanoZinazLlU7aXL3AIkwvnLucmbXb7idpRKCp2bEDoRMfdrc5vC11E5MHE0mNvmls0tTDDd32UeWybBtM0Fnvr8+NOhyrL6mgYeQ7AN4hGz71TcFOo51ydbyKD4KRgJhhUDO/a+8rC5SNUsQFFeSu9onPsXxp/cGFgZxRKEfMr9IbxMvrMiYMeLTJ32WAjrFzQZNf/aXObfjICBwYVGKfFYuyArlocST5D1HEb9xSsbeRqgdn5xGzLHM9w69ZaN89OlRHPOQynhlis6DcxStAbpmvaK6Vm0uc3zN1RVkFIic7iMpn2pczGU8C3WfrBtnd7hVUIZTbUUb4GojQbgYDZVypBptErdaIus160Y2EFufp4G8/NaKmdhAZFEAveit0OoN6cS17CaCpNIfiUuQRCmDLULyqYylwjY8WS4QmMohiMehxJPkC+KhvLODdXXSBjqPAxX4AmTiqEbbH6iCxiklOxI+svEwBbLQqDaYcEF2eVi3ul41gMdCvbSuXcduqua+dk95P0RyhjRr4IwPjh8QArig4zcjhe5TrQyQARsuTLeTzhl8sQklDm5ikKBQJsZkpKMjT2GICOCi2YhmHFK/vIQ3ul4eAvBUJBKd63ZZ14+UVGw5Y71LK1I/l5BGMBwvxNNJ2RH0UqFmmXC7DIkwtnQPzBHvGwOc7Qzs2+HZ/BR1DJBBKwgCFmcXvA0QqgdRVE47UNNHHpjF937orRu7rc2q6x34G1wjHASl/l3PLIQGOmcXEpmllnORCAJIZgCyEUShNIMZ3J47YL8ELDhjgAXOgR8zaVtKHNEwAqCkE9lgzUD1jPNDkAirHPvlRutTc7/l5mc/5+ngKMShWxMo2EYGIaB6qgE70wImmWWDXJCCIoJ2JF64axJQJl2yoD3hPIlPwRWPLCCMIC6BaSSCbTAgYHvldlQ/mQhAlYQhJLEw6an0+ZUufaRZYApNzz1DrZpjQQ6elheXcmBcIy+WJxAIklSN6h22FGNWiq1BP2Ki7DioNtoNdsXxsCWquZVgmigk/YdZsaB/u6D7HjufjAMGYqeSmTSt0kWAkEoiVE9mx1v/R1FUVh4zkfSoVLDmL9yjCACVhCEohiGwWsPtgHgqbPhP2E+fsXFyuRh9mp1tMUhYMRpaxuY0q0rbubC7VDrrXXxlJk/Sy2MgU3HsQ7XppbNq0nGzAkLejJOrL8bM5jSZm0jlDdZD6yIV0EoiaIQi6czsri8oEjtqVzkbAiCkI9V0gpq55gp4AwdgjhpV3w8ZV/CXrWWwHB0YrovFZ2kbr4emEZr+IIz0L6LUM+hIu+IaJ1S5E7ikhACQShK7gOePJgPRASsIAj5eJvAXYOiKpz+UXOSQCphMEP3Y85uVUgo9hF1qWGQ0NMe2MIQgmHqFz2VpHXzM0M2MIaoLiZMPpkfYwmBFYTBkNj+wRABKwjCQGaeBu4aNLt5i4gn4LBWjU+PjLwvRcFjxGmM9wGg2goUS6b62BAEO/aQiAYp5W3NOCsSkSOQD1EYGzmlZEXBCkJxlNyQARGwAxABKwhCcWaehta8BAAjadClVhJQK4ZoNBBDNwjc8RLBQ2ZlugFhXMOMg/Q2zMfu8jKU4LE5hieIhckjNw+sIAglyHXASpjUAETACoJQEq3WDCHQEzrNW38/rDaOUGf+CgW6d4Y4vNHMI5uXRmsEZQlVzUbzsgsoGe9aJKOWUKZYadAY9gOMIBxz5HlgJTSqEBGwgiCURHOYKQP0hI6iJ4cUG/ZIL5W9ewBw9x1ASURQFIVTvnGipTsD7XFaN/fTerCaYLxhRPb4GhfiqZ1Z5J08V4VQ5mQ9sIpM4hKEEsgkrsERASsIQkkyAhYgaTit1+5ANhOAp3cPld078XVtpXn/M1T2H6a6YyPT2l7HGe0FIKgFcPjMm/FLP23h3is3cu9FT7Duf9aNyB5FUZi+7EJUm2mLzenBWVmHs7I2mzxBbvTlT54HdnJNEYTyRSZxDYbkgRUEoSSKlr1pJnBYr6u6d2CPBwGo7tqKLRnNa1fbsZGehhUknWbZwnBXnGifOQQ29xMzOft9y6isn0Nlc+WIbXL56vHUzSTYvpvGxWdTO/sEUokom//73hH3JUwOhp4jYEXBCkJRxAM7OCJgBUEoSbhvv/U6oZteTzURwRHrwx0yixyUkh+OaB8pmwvDMNhyZweGogAGNbPsLLj4VFRt9LcfI2UWSlC0gem8MuJIKF+sayTaVRAGR1HS3le5rxUiIQSCIJTE17zAEhm9VccD4Iz2oRgGHbPOpbdhRcm2lYGDVHVuAQMcxzfgmmFmMJg5c9aYxCuYOWGBnH4kBnYqoiiKVOMShEHIpNKS/NYDmVIC9rbbbkNRFD772c9OtimCcEyg2exoDvM2kUin0Io7fRxcdDkRTwOOaN+g7W3JCIqq0HzzqTjscQC8jcUmYY0MPe2BVTMeWEXJmV8mCrbckeFQQRgu2cqIQj5TRsCuXbuWe++9lxNOOGGyTRGEYwrNYXo5KzrN7AIphwd7LMisnY9TGTiYt62zshandxp2dxWKqqGm4tZ7RtK83djdI6viVYxCD2zuTHbRRlOAvDyw4oEVhFJkRyjEA1vIlIiB7e/v58Mf/jA//elPufXWWyfbHEE4pshkIlDIZiFo6tmGzUhir6hGUdPvKwqzVl6Gy1dvbffW+r9ar1XFDcTQnNnMBqNloAeWrA4SBVv2GIkYYIb3KckwxILDzgcsCMcUaQEroxYDmRIC9lOf+hSXX345F1988ZACNhaLEYvFrOVAIDDR5gnCUU1GwNo9TWT8qXNPu5Jq5+Ce1Gigk0SwA+pASSWI95uFDFKJ4KhtiQY6ObjhLySjZrnYA+v/jKrZmHHCpTleWLnRlzXdu8Fveu5VVcXVswN6MIta1C2YXNsEoeyw8gNOrhllSNmHEDzyyCOsX7+e2267bVjb33bbbVRVVVn/Zs2aNcEWCsLRTUbA9vdkK2ztX/9Hdj7/ANFAZ9E2hmHQsnk1SjxkrUvFzGH/noOvj8qbkOkzGuwmI1Lj4T6iwW5atzybs92IuxaOFN27oWe3dY3y5m/17DbfFwTBQhEPbEnKWsAePHiQz3zmM/zyl7/E5XINq80Xv/hF/H6/9e/gwYNDNxIEoSQZAZtImDFYFf4D6IE2osFuWjavLnpjDbTvor/nEEp6qN/Q7OjmS6KRdgLtu0ZsR6B9F6GeQwz0sBqEew+Dkl4vN/ryJBY0RSoUxMDm0LPb3E4QBBNFRpZKUdYhBOvWraOjo4NTTjnFWpdKpXj++ef5yU9+QiwWQ9Py4+mcTidOp7OwK0EQRomipgDQU+bzrq93j1W4INRziED7LqqaFlnb66kkrZufobdhBXFnlbU+rWUJNh1P6+Zn8NbPG3Y6rUyfpuIpcSOXkbbyJufCGFYlriITuOQCCoKFeGBLU9YC9qKLLmLjxo1566699lqOP/54/uM//mOAeBUEYXzRU0lSKTMMIJXOIqDqiRwHmjJAjAY79pCIBnE4+gjULgLDwDDAMCMIcBlBEtEgwY49VDUvHpYdmT6Hhdzoy59SHlhBEApID5RLHtgBlLWA9Xq9LF++PG+dx+Ohrq5uwHpBEMYXQzf467/9gWjMBiRJpdKeAKBj1rnYY35qOzYOEKPehvnYXV4qA4dwhzrYf9x7MeJZUemNtmKv9eJtmD9sWzJ9JqL9lB5Kk3yJU4WiMbCCIAxAviOlKesYWEEQJhEF/PuTxFrMcAE9ZY54tM9+W04RAwW7K1+MqpqN5mUXAAZaKoYtEUaPpaz3NbtB87ILRlSNK7fPkubKjb68UYZZLU0upCBkkUpcJSlrD2wxnn322ck2QRCOCRRF4Yq7r2DHH7djYBDd4ye8qQtHtJcZsQ14qsyg1mJi1Ne4EE/tTEI9h1D0BEY8G+5T2TgLX+PCEduT7fMw+QpIwVM3E2gHJFasbHF6zVRZPbuzEQSFWrV2geSDFYQ8JAa2FOKBFQShJJ4GDxX1HgDabn+dHVf8jk1XPcP+P/djCsfiYlRRFKYvuxB7RRVaKomR9sBqDoUZyy4sPnlnCDJ9OjzV1jpnZR0ubx3Tl14ghQymAnULTJFaLIZA8sAKwgCse6Xc1wYw5TywgiAcOUIdISLdEQDqP3ECNe9eSFPr69TWpnB57UxfekFJMery1TPn5HdxcP8+9LgDAJvbkVepa6S4fPXMOeU97Hz+fjS7i8Xn/1P2TRl5nhrULcCo3APsRTd04tOW4ajwiedVEIohArYkImAFQSiKYRg8ftPj1jiNrcpJxfJpLDjhLGbPOn5Yfag2B1o8QufP9pt9OMd+y8nEgimqaVimOleGsL+Dnc8/MKCsrVBGqDklgJ2VIl4FoQRWGi2ZnToACSEQBKE4BjQsb2DeqnkA6JEkajKKawSTrxTVjqLHie3xm8s2BcMwxhbPlRGwippXnctyVKSSgxZZECYfK4Jgcs0QhClA5sYmk7gKEQErCEJRFFVh1S2raFzZCIAeTmCPB3Hbhydgo4FO1u54g4hvJtOuXwFAuCvE3/66iZef303r+laCrSOvumToesbAQatzZYosCGVInoIVGSsIpVCsLATyMF6IhBAIgjAoqs3MNqBHkqipBIc3/h3NZh90iD7jGVWTKskZc1Dt/WYfcYOX3/E7a7vzv34+q25ZNSJ7DCOdkktRi1bnytznDd3g8Ft/H1HFL+HIYOQKWNGvglAamZxaErmrC4JQEl3XCQf2ma/DSVQ9QTziBxRaNq9m3pnXFJ3ElfGMVgK6aqOrrRoAzWPj3O96mLH4LCqnzaayuXLENmU8sIaeJBntt9YXmqGoCqlEeEQVv4QjRMaJrpjV3ARBKI7lgZUY2AFICIEgCCV5q+UgfVWmlzUVToCu0zHrXHoblpccotdTyRzPKGiJMF2/3AJA9SKNunk6Ke1NGk+sx9s88sk7mUlcms2F3VWkveWB1dE014gqfglHhrzhUNGvgjAIkoWgFCJgBUEoip5Kkjj0FqnqGnM5kiRcNSuvClfr5mfQU8m8dsGOPSSiQTJKUk3GsdW5AbD7VMCwys+OhoyATUUitD2xPru+4IWiqlTVLZXwgTJGkRhYQRgcSaNVEhGwgiAUJdixB1f3Dhr63gTSIQTJGLN2Pk5l4CAZIdrXsY3D/I0InbzF7dgafERmdxB3ROk8/nXQIlSe0QyAzW0GPRaWnx0RaQEbOtxCyxMv0L+7FUPX8yuV6jr9u1pwVTSM4QwIE4VRrJBBen0qHp8EiwShPLHSaImAHYC4JgRBKIq3YT42RyWtL3QBZhaCSv9+tFQMgJSawr90C/ub/kKcbqvdLu0XsAJYDijQN7sD/bHPAGBz6oBatPzscMnEwHpmzqR2+XJa/vAKsz5wPihNpp2JJNG2Plr++CrHXXL96A5emFgsAWsAZmq11hdf5K0f/5hwayuX/vrXeJqbJ9VEQSgLrIc8EbCFiIAVBKEoqmajefkFRLp/DUCqP46iJ0nYYrSeuppYTdfgYziZ+67ajx4yMxlQ48dTt7Jo+dnhkgkhcFZVc+kjj7DtF7/gje99D++pNwAQ7fCz687fj7p/YeIxrElcCu2vvcam/76Hnk2bzB9rwyDW2ysCVhDITnI0JA/sACSEQBCEklQ1LWLlJ2YAkGgL0965ha3TnqJvf4JEu3N4nagxUiFzWDgyv3XQ8rPDIeOBVRQVRVGoXbLEXLY8FMrAlARCWZH7Y/ziF75A75YtmTcmySJBKFPSWQjkuzEQEbCCIJREURQWrlplLiR1tl4RYNepF7LrlAvp+Z95w+wE9HAUALVSI+brG5NNRk4lLoBUNGrtB6By5kxqly3DNW0artraMe1LGH/aXn6Zw88+B6R/mw0jW5xCEIQ8snO4RMAWIiEEgiAMSqyyz3o97++70Wr2A2Brjg7Z1kgpdHzjOKJ7zVKyaoXGmuAnuVB/CHfVKCdYZQSsWiBg09gqKrj0Z4+gJxJoDsfo9iFMGK9/5zvEemcDpa+/nkgcOYMEoZzJeGAlBnYA4oEVBKEkEX8Hv//sz61l+4wA7pP9uE/2Y2+ODdleCXyI2BunE90WAEB1V5IM/gsbDu4ZtUcht5QsQDI6UEgriiLitUw59UtfwlFdDWRCXgd+Dp795CcJtbYeYcsEoRyRLASlEAErCEJRDMPg8KbVOI/vx1brAiDVnTIdAcYwY0wd+5nxzQst50Fq7wWE32gk8Mp2Wt/aOEq7BvfASqxYedN01lk0n3OOuZBfBdgi7vcT6+09onYJQjkRDXSy8/kHCPccAqB9+xp2Pv8A0UDnJFtWPkgIgSAIRQm07+KQrQYjdiaqNww9UZKdbtSuL2PY92FU/2roTjxr0E7YiOq4BD2SouUb66y3gh/t4n0/H3mhAUNPAaAoGpD1wErJ8ClE+iKZ8X1ywQQhF8MwaNm8mmiwm8z3IxkLkYyFBy3hfawhHlhBEAaQKQfriPmJbreTaOkHILXznyC6AsO+f9h9Jbsj6BFTdM6538uS59ZywZ1uZl+ij6oaV3YSl3kDL5zEJZQ/0a5s3mDRr4KQT6B9F6GeQwz8chglS3gfi4iAFQRhAJlysN7gQWbd8bolDiPbDhJq+zyR7RtJtA6dRsvQ4fCNK61l3ykNzGclNQtt+KZXjaoaVzaEwPTAZgRs5lZv6FLNqdzp2brVfCEeWEHII+M8KP1EXryE97GICFhBEAbgbZiP3eUFFJr8y3DM9ALQfV8bu04/PZtGK0d7VLOUS/kbp3EbK/kqtZGTIaVgnxc2N1AV3GojjmA1YIy+GleJSVyZPLChw4f5w8UXyySgMqbm+OMB04teKj+7ZCIQjkUyzoPSD3ZmCe/RjF4dbYiAFQRhAKpmo3nZBYBBqtVHojUEQOWlARauW83CV59l/j9WconyFxbxj1zBGi7kITzUM4t3UscKFBegGRgh01OqVTuJTuvi8Bl/Q53pHHU1rsI8sMlIhPQKAFKxGNHubqI9PeKJLVOcNTU5S+l4WDX/50gyEQjHIrnOg+Io2F3eUY1eHW2IgBUEoSi+xoVU1Mxg851doKZvprqC+2Q/3hOTLJ/3QSppZgWfw0FlXtu1fJluZQMoEN3qA0Dz2lGwE6nr4PCyp0dtV24MbMuaNez7858z7+Rt99K//Zt4YssUI6doGgZUzpmDZ9asvG0kE4FwLJLrPCjOGEavjjJEwAqCUBRFUZi+9EI8S91M+9gyAJLpDC5JRz+vKp/nBT6On51FWhuAjqJA7dXTzTbdUcJvQuT16fQ++0E2bG8bkT2ZtDK9BzcB0L7lZQ5tfQLNW5jv1RTbwQMHiHZ3iwgqR/TcLAQQbm2lf/9+KQEsCJjOA0/tTAZ6YRU8dbNGPXp1tCECVhCEkrirG5h2m0L1O8yysakuMxwAxRQgXbzBWr40aB+6bs441/sT7Hz7ZnadfjrbLtnKwQc3DduO3LQyqYQZ86q5Hbiaqpn+njNNkwrv9ZJPq2zJ98Aa6JlQD7lmgmA6D5ZdiMtbh2Y3c3Brdhcubx3Tl14gKbTSiA9aEISSRAOdJGOGVcgg2enEMHLFos5Qs8gTbYeB47FNczP//ndi2HejOR/m1Oorh21HNq1MPoqqUrmgGd+y2dY6kUBTgMzMrRKVuDJEurqOkEGCUF64fPUsetvHaNv+Ip27XqFq+vHMWH7RZJtVVogHVhCEoui6zuHNqzGSTroeMtMeGTENPWAfunG6WpdhgP83MwGovmweFcun4XrbL/Gc1E6g65VhpYIZKq2Moes0v/tMa1mRhLBlT0azDnWl4oHAhNsiCOWMmk4XmCngImQRASsIQlHeajnIXs9cDKOK2F6/tT6156oh2y7puhF3Tz0YoFSYN177dHOil9PfSNOGc4edCmaotDKKquKoqcxONBPKHiNXwYrLXBAGYBgGhmFY+a4NPWWtE0wkhOAIEg10cnDDXzAMAz2VJBkzqxvZXV4UVUNRFGatvAyXr37S7MowWbYMxVhsLWyrp5JpYUT6R7REQsrsnkBRTA+fYl43VbMxa+VlAEXtalh0Fh07XyaVTJj7Kkx6qag43D7mnPLuovaP5nijgU72r/sjiWgQQzeyx5XeV8bmwc6XnkqSOPQWkfrlKMnpzPxWAv9Te0GH/lc7cBtVANib4jB9oHBsrl2Ff/UuXvv9NhTN3L+txrzd1G47F2d/K3ZX5bBSwWTSyiSi/RRTO4auk/CHQa8asi+hPIj39pkv0jGwgiDks93fTyCRZKZqjnjFDVjb1YfPbuP4au8kW1ceiICdIAqFh2EYxCN+KDIMEA/3Wa93vvBg+lWhayK9rKjYnB6SJX7MS5Jup6oahmGQiASGbJ+1pZg9I0DJOvptTg+peNjsKi0CAXQ9RTIWKhB4pmB0uH15gn9oWycKAwzDPAtG9roNtu8D6/80RJc68XDfiO0f1fGm9zXc9i5gVt9+Dhz3LuzT3GheOyl/gsOf9AEXAjD7y11ceuunB7RVNRvTl19I7NutRDea6+xe83ZjfpIMauefMqxUMJm0MgfW/bHo+4qqkjyctMajrU+poog4KlP8e/cCtiFDCJw+35EwZ1hk7uW5E2iKrRuPdqXa5K7PvGd56tLrirXV9fzyy5ntcvtUVTVvfeF+RkIpGwzDyNtPxq7CfRceX67NhesKjy2X3DZqTp7hYn2O9LqOF4X7ypyXSpvG3mCINrUB24J3ojsr0aIxZlS4JtymqYII2HEiGuhk79rHSGY8emNmYA1k848+un2Mtl1Je0a27wx5Nhj54r3oPg1jiG2EicIA1FQMdINETwQ9HAcU6r+yjdp39lJ34CROO/ebVFFTtL2vaSFL/l+UtrMqAIiHOglvmkZvW4qeuafSH0rg9XdwYP2f0t7pdMP0g03T8efRsfPlnKE0G4aeHzNr6DqRg920PPkqzgXvTjdXsHk8VM6cSbS7G1dt7QSdIWG0+ObOBQ6ZDx25DxqZ1+kfc+e0aaRSqTxxpus6uq6jqiqqqmIYBqlUKm8dZIWAoihommaty5ARTZltCkVdoYDaEQjhjydYXlWJy6aRMAze7Pbj0VSOr/YOEJCZtrv6IwQTSZZVVeLUVGIpnU19QXwOO8dVVVr7z7VrW18QfzzBimovTk0lrhu81eMnltJJAm5N5YS0F+7N3gCRlE6z28kibwU7g2FCKZ3l1V4cqkIspfNKVx8ADS4HoUSSxb5KdgZDRFM6gWQKDah1OTjO62Fzr59wUkdVFWZ43JaNueck9/gy63LP9Y5AiEA8wVKfxzpXL3X0Etd1qmw2Tqz1sac/zP5QFAOY5XKw0OdhQ4+fqG7Q7HZyXJUZcrQzGCYQT7C82suBcJS+eIL+RBIFmOZycigcRU1/dNyaRiSZQgU0VaHB5aQzFkfXdc5uqMVl04jrBht7A7gVWFLjY1d/BH8szgm1PhyqeX029gXx2jTLhsKHhcx1ynz2FEXJ+9xl2uS2yxXpuWz39xOIJ1hR48Vtt7Opx8++/gguTaXB6eBQJEbCXYNipJhT4WaGxz3YV+uYQjGO8oCKQCBAVVUVfr8f3wQ9zRuGwe6XHiHS1zIh/QvCZNDTsIK4q5qQdyb7bvo7gdV7MGIKM/6titMuiDP3pCupalpUtK2fHbzJ9+hiHRsd74VE/g9f06dPYMVVCSoDB0c05So3+xIGxHuD7Lv/78Q6/FSfcR1rfxZg/tkK77zrPdSdcAJ6IoHmKMwTK0w2f/v0b3npx5s56cO1JE5MwPQZxO76MfYr3o26YCHqrNmgKDTW1dLlcGEHKu0aKQP8yewollNViOvGsB6vVfKDhJyAS4WQDjYFKjQVHehPmiLRltbSR3rqjEMxh4vLAbsCiRHaogAaMPT0zPLARmlbcz8zKum5qelljaE/G0r6nw64FAWPTSOeShHWDVTMz3TSgGD6Mz1Yn7aozpw2mKZoJINJ6s80Q8C61nbhWaDQtWU7emUr2OKQdKAGZuJtmEf18Q2EDobwzPIQ3BNET2S/BapdpWJ6Bb0be/Et9uHf6sdZ48R3nM9qEzoYwrfYh61i4v2dI9Vr4oEdBwLtuwYVr3k/ujnr0qPoeetzvyyDtZ8sCm0pdhyljm2yjyP35pOxLSdC1HyKz9mWnG1yyawr7KuwHWSTTBVeTyNnm8HaFzuGYnbl9lf4fuHrDHrBusI+HdE+ArWLwQDnomrs23zE9wahLYa7onHQZNpr+TIBYzfxgy5LvM5/+O3YvJUYShDn3HsIJz9FwlVNbcfGkv0U0tuwgrizipq2DdiSEdS6WtSbPo99+w7ImQ+m2u2mN0jEa1mSkZwK4DpxJclFx6Gdfa6pGNOeLEVRSNfNIA70JAb+tMf04aurwgj3GBBLr0waEE3mb5GcJBFZLuIVRi5ewbyHTBXxCoPbqpd4DcN7sMn9nYgaBtFEdm8poLfgMz1Yn87+BBX7dMLp5QOPb0PXwtiTjYTbQ2jMIRnSQI2j6A7UxExCgQR9+17Hnmym+62DaMbA2Nnu7buxp+pp6dqOPVVLvCtOz95d2JONVpvD+3+HrVJn3mlXltW8GBGwY0RPJTm80SyLWShMMuKor2EFCWcVtS1rUVMxkpqTnumnYdicqMkYNS1r0VIxUpqTjnkXYwAN+5/DUDW0ZJTe6aehxfzUdmwsKn4y+8k8+WaWM8Ipsy7z5VBz2uZiFLyfK3Ay++lrWEHMWcW0lrXYUjG6G1fSXz0Xd98+prVvwNCcdE0/jZTNiZaMUZc+tswx22N+ajo2Fn2qNdK2Fu5bSy9njjEjNFM564qJytxrogKBhhWEfLMxFAVbLEB12wZ6m1YSr6gHRaWiZye17RtIaE56p5+GI21r5pgd8X50RyXejo30NqwgZXOjOzxU9O2jrn2DdYyOnGNsn3cRCVct9nAXjpifmLOKhKsKRVGxxYIkHR5c6fZoTrqnn4aac61zj0XJOf+1LWsJ1y0m5qoxr7dmR0slMABHtJeq7h10p23xpY8hkb5uaipGQnPSPu9iADzBw8QdlVS1v4W/8QS09HHaY36qW9fTM+ssmm8+lcBfdwAQDO6lx9eBrifRtFIptQwMdA7feJK5aDOoPLMBVanAoBKFLxNOOqj177c+l7miP3PtVLJekBSgRvsIT1tC2DcL9CSqoaMZOkalD39bCyBpl6YEaeFpKODatYP+hYtBVVFUdYiGgnDsYYvqNOwLY85MMNEML1rSFKQaHgAciZkD2tqTzdb2xbCn6tN/a3PaNOa16Zh1HlpqP/bNq1lw5jVlU0hBQgjGiL91BwfW/wkDc8i13zcbezyIPRYk7JtByu7JyfpecNENPW+C0+AY6e21getz+03FQLXlbacmwug2Z3adkTLb6CnT25FKgqplbUlGUdAxbBWWnWo8iO6sSntIcvoZYM9gx2agJKMYigaa6RlTklEMmzN7DKmkmQ5JSctUQ8fZu5dY1SyzjaGjJkI4Q51EauZl2w3YX6FPEkjGwOYsbu94kgyD6siepxEPkpfY3khlzwsM6/OjJPox7JWD9zuYLUYK0rNgO+5/kZZbNqNWx5n/9Bq88XkscXySpualeJvzb45/5yr8+i4O37CS3v+dh21GhGWvvgclOTe9RQh3XycR3yzQE6atqTgqkLJXmLYqKugptGgvKVe1+bkG8zqmq9OYsZMGhMP0/mwj++/YyPyzFS7/6VXULl06wuMVjhRPfepRXrlrKwuvnUvth+dh81YSbmyebLMEoaywxQycIZ1p++P4/ENvP1G0z9aIViZwRg6zZM50auYUDx0bKxJCcITxNsxHc3jorJ5Pf/V8UnY3KaePaOHDTrEnlmLiL3cyQ9769PYD+smImXQ7myt/5rWioDs82YkRhpHtJyN+7Lb8/To86Zn2mXUqurvIRBjFVtpe1KLHYNhyAtAVBcPmyt/OZs8ej2L6W2O1C3LaqOgOLxGHN3+/A85lkfNtH2T2Zn55qUGOawgMAzLCP8+cIv0U7tPccJD95xyjopR+eMjp3xSv6X5H/NSc8xkBnHOmA5vR+xzsOsXMQvAGT3L+1yOsumVV0R70fvMWY2uMojt2o1kC1kOk2pPeTXryg+bMH0JTFNBspDz1+Z/p3OuoKKY3z+0mYc88nJSHd0AoTcZvYjcSJGbMJO48Ag+WgjDFmHYgQf3hyS9g0HgghTkWNovOrt1UzZw3rAwyE42M14wRVbMxY8VFOKJ96JodSygU/hsupbYfqp/c94vtt/C9wV4X9jnc/RauL7Vt4X5L9VuszWjP61CUOvbR9DNcO0d6Xkd63ON9rmympxRHioXrVrNw3WpOXLeTU244pdjOAZXYTlNAq9UJqPkZum3v0HaO9NhV82GpJtwxpsMTjiBpAVuhR6j77cMMyI8sDIsax+SLiHKlyj7yczOaNhOFLWZgG00Q8gSS0nqJ27cPqwDNkUAE7Djga1xIvZpixu6n5EYsHJWkjG4O3fKkuaCD//fNxHd7qDw5OiB8AOA0vkNN4ni8b28HILbJR+RNnfDBuwhv6iLRER7QZiw07XkOT6TXXFBVSZ1V5uQ61NuefAK9v3SO58FIHTpI6tBBABJvrMuu272LxCuv5G+7fx+J9esH7S+5bevANq++bL5uzU7UTbzwHKn9+7LLr7xsLTsiYeqd+ZMH610OvLbsiIlHUwdsA2Z6LDCzKwA0u53McLuotJnr65x2q/0cj5vjq7xU2TUqtOxPee42Ta7inu0Zbldev81uJ3M8bmbm5BjN7ROgOi2WXaqC16bR5HLital5201L79tdpCpeZrvK9HlocjmpsmvMcLvy9lvvcuDJ6bPwXFXa8keemt1Oq33u8c7xuK1tXen+mlxO65hzcWXOd4Urr/9aZzbG31lwTJk2ucfstWlFr+twhHGdM38+QW1LkpqO8tATEXcrUc8bxLzr0SrswypAcyQon8eNKYyiKMxccTGJtY/RtP852uZdONkmCcK4otf8FMVmB1yQ1Aj+pZHO7y8i+GCI5n/czLKrl+VtX8Uizrc9wP5dtwCQ6nCx69TM9+J3NH7mZJpvPnVMNtkivSTdNQC44tnQFPe0eiqamsbUtzDB5JSSjfX2UuEyBUjizTewn3gSiReeg1gMdfYc9AP7IRYzt3c6s+v8fhK/+w0AtsuuIPnSGoyzzyX5lz9j9Pag1NRiHL4axeWCaNTctroa1fUZ9JbD+X3Omw+pFPHf/QblAx9Gm7+AxNN/I3HfT1Fqa7GfcRbxn9yJdvJpKJDd7/uuzl++7AqWnHwisy++hF2BfpK6gU1VWOgzRyJ2BUyhnrscTer0JxNUOxxMr3CxI9DPYl8lPfEEcysrcNk0oskU+/rDNLudtEZi1nqAhgoX0WTK6nuWx21tA+BJ25EhY09uv7n7cabF3iyPm4OhiHUMDS4nOwL9rKjxUZUj0ortu9nttNpm9pn7XuEx5O53sHNVzK7M+x67jWa3E0/I7LPZ46bW5WBjbyDvfGb6yrUtc2xNbidNbidv9vjx2e3M81awNxgmkEhwfJWXjmjM2m+p48mcj6RukNQNwqkk8ys97OkPUaHZUBQ4FI7itWl4bDZCyQSqorLYV2n1r0R1jKoInTM7cQfqqAxMrq8x7j2MTTcfFKcve3dZhA8AMolrvOmLJXiuravk+45QJ3FP+aShEEZHld2GPzGyZDFuTaVC0+iOJ8rCnpGQqvsuif6X2dZ8GaCAIwlx84dCdWic++/nctx7juPNX77Jrid3kehPsOyaZbSs38uB59pxLOhn9qOvoUXdVBy8gvj8d2JvKBIrPAK83dsJ1h0HwPytb3Hod5t57adBlr23mase+8RYD1mYQP7yiYdY+9OdnPKxWvq3/AL3b/4AQOTb30CbO88SoZOBUlNrCuIcIZy7PBRnfPvbLHjveyfeUGFKUvjQUIzu9V34N5bOqJJQwZ52zsYcOs748AVusAq8BRPCok5wxSDmAGc8/z3/NBXdvgZHop2K2pnMn8AsBDKJq4zx2jTmzZzPW71BXKpCVDfwaCrVDgcpw6AtGsOjqXjtdkLJJMFkikqbRn8yhVtTiaSywwkNLgeRZBLdAFVRcGkanTHzk5fpG7CGYgZso6lEUwOHJ6odNvriwxdCGfvAHALpjiWsv7nUOex0xxM4VWVA7sYKTSWc0q2/ufYXo1gfmWM1z12i6HnJ3VeGGW7T8xNImFWmMtvXuxxEc86vx2Yjkkri1mzE9BRNbhd+f7+13+p0vlF/Ik5/cuB59dg0TptWDcCbPX6cqkYklcSmqHmCtsHloD+RtM6DXVWtp/SUQZ7tucfT7HZaArbe5aAzGh/wmcnYWmGzWccYTiQJpXSa3E6cqkpSN+iLxwml21U5E/hjdlADaPVxrHxl8eytQ4/rPH/r8zx/6/MoDgUjncjylR++guLUAZWGb2zFfbIfDD/JU57G3nYaMDt7TaN+Yq6qAedNi/pRdB0UhaS72lpvi/qx93ZAWsDa0lXbgIGJe4XyI2eOop7zY2js2E7ixRcmyai0Db09JH71YMnloVh/2200nXEGnmbJqiAMxGXTOL66eEqrDGptD5Hq5wGw95+FLWmOMAVqwFBTRNx+qrsrUIwOEq5WDO1EEo4Uiq5QGTQdA/6aFEmXnYpAB+7QNCLuFAlXlP7aPrQUxFz1aKk4tqSf3mk1zNhbQXBaK7o/QdJRDbqGPW4jVNWFJ+TH7vIyY9mFZZNCC0TAjjsuTWWBtyJvyAbIG+qIpUvlFQ47VBUM5eQOGdU67GzzB6nQbLhsqjUElCF3GKfB5WSbP4jPbuf4am/eMM22vuCA4RDAGuooXD8YmWGUg6GItd+XO3tZ5PNSGY7QF49TabPjsqnWEE3uMEluH7lDMYXDTxkGszF3WCyX3OGcXHtzh58Kz+NQT8cA/lictki06DnOHT4KJOKoispJdVXWsNvbmuvz+nmzx593XWOpFBt7AyWH6oqduya3k0RawGXW5X5mbKqS9xnMHGPu68JjyPTVEomSdFzAlq7NoBhm8s4SGAVZ2I2Y+QDV9+vpxPe78V3WjnvlXlLTv4jW/UEqWpeiu6tZXFvL/qSGboDPbs/aO6MBl02zRjY8mopNVVnZOI/X7vkfjH89G0XT0BRFkg9MIbLlNkGpMD+HRiyG0Tn1J+Il+vuJ9fbiaW42y9lOQDW48eo3049is5EMh7F7POiJBKrdTjIWQ08ksDmdRfdjGAapuOkcUBQF1W63lnPXFbOzsK3mcFi2ZNpk+svtp7C/3PNQ7HXu9oXnbKKuTeG5Hcn+MttUzZpP++5nSUT7UdI+CH+tgu58EUeiHW8UUpkkLkDK1mLmR9edRN3HE3fXoDu2EK5pxJ48gKY3Y7j3oqkxqvxguMABoIGhQY3fSdw9j4roXnR3DKfLy9y8ogXnTcg5GisSQiCMG8MVf8LUo8V4ll9f/RD9f29E94/+udd1ci9z//wy9uYYzlAdF6UeGVZll8LP1ra+IPteeBWffTa98yuZ07qLDY+3sfv7W1n67iau/sMNo7ZRmHj+fN0vWffz3Zx2XS3R6Kto3/k+Rm8v4Q9fPdmmjQuXPvoosd5eNvzoR4RbW7n4F7/AVVeHoijYnM4BgqxQrKXicQzDwEgmcVRW5gm+jrVrefO//otQSwuX/PKXeZ7ezHaZ/WSEW0aM5i53vPoqG+++m/4DB0DX0eNxPHPmEOnsxOZ0Eu81J0XavF4ufeQRS5AnYzHaX32VDXfcQfjwYTAMVJcLZ3U1kbY2K12j5nZTOWMG4c5OLrr/fnyzZ6PrOi0vvGC1VRQFzePhxJtvZtejjxI+eJCK5maChw/jqqoi3N6OvaICd3Mz4dZWPM3NRLu7efsjj9C3fTub7rqL/tZWTvrc59jxyCP0Hz7MiZ/9LLsffZTggQN4mpsJd3Zy4mc/y57f/Ib+lhYu/PnPiRw+zMa77rKWPU1NRQV3MdE51Dpd12l94QW23HsvobY2LvnlLwkdOsSb//Vf1mehmHe+/bXXeOtHPyLc3s4lv/wlhiPGgfV/oqLrChTsHFxswxP+O86oeV3sLi+qLZ1PXVGYtfKysqqSNRpGqtdEwAqCMCR79cd48pu/pmZGI9s/MbYZ/g1f30rjLdvwsZCL+e2o+jgcirBp8yEWbdXYeYqTmCtJ5883ceg7r7Pk8nqu+fNNY7JRmFj+fO0vWXe/KWDrLqyj7dwL0FtbiFz/j5Nt2rjgamwk2t5e9D3N7cYzYwah1lYqmpoItbaaYq2tDcXlwunzEe3osEJiVnz60+z+v/8j3NpqdqAXhChl8nsX7sfj4YTPfY4td99NrKv0vIwpiaoOPA/lSuH1yQzB5+VmL9jG6cReUcGsa86locqM59+3zI7P/zcc4W7cviYWvu0jZTWcPx6MVK9JGi1BEEpiYHCY1WxS76Dh69s49Fg2Xtc3y2fWVih5FzFQXCmcS/3MfXKNlTu29oYiuWBHyAyPG9v991vLqbY2mrp3mnudKj9sxzCW30QxaHn1NXNdOpWWd8GC8clbnMkb7HLhqKnJW6+4XNirqwc0cTU0ZLfRNGw+H6d87WtUHXccqseDe5jZLYqJV7unhtmrrmXGGR8k4U/SvPLdRNt60MNhU5waBkYkYrZNnx93/VxSHU0YcTt2dxWz3/YxZq+6Drunxupz5tkfwF0/l5nnfDBvffPKd7Ppjp8cfeIVpo54hYEPF0ZuvL5hXcO8a3rq+yAOnU/vsJrZu7eQbGkl2taHQ68/6sTraJAYWEEQiuJnB2/yPbow82saOiT2usGRYvGP+6g+vIyDT/TQurZ1QFtPk4dUZQ+JPpj/zBpsDflTWxVySuKOgGQ4STKcpOPlrcw743oA3EGdxJrXqXBX4q6KF3NGCWWEYRgk+kMA+J01OC9/t/lGOAxV1dT88Mc0hfrp/vY36W9p4aL77sM725zwp+s6rWvWsOWnPyXU2srKz36WnQ8/TLijg4sffBBnOv9vJq4y8zo3plNzOPLWZYbmVVXF7vEMiOPUHA4WX3ONNdTf8sILvPXjH9O7ZQtgCo4ZZ3+AyqZFRPvacFU3Ee1rw107A0XVMPQUkZ7DVNTPoWKaeRw1C0/HXTuDmkVnEek+ZLXJbWvoKbp3vIhv9gpmr7oeh6cKT8M8AKrnn4KeiNH+1lPMPOdD1C29AHdNM7XHnUu4cz/uupl4GuZRs+gsQu170JMx9ESM3j2vM/vcjxDpbbHWta59DIAZZ38AT8M89vz1LpJhP40r30H7BjP3c+PKd9C942UaV76TyqZFhLsOkIwE6N3zOnPe9k+odgd6Ms7+5+6n7rhz8E4/HkNPsf+5+6matYz2DU+SCPXmna/MNodf/T+aT76cgy89QtWsZXTveJn6ZRdgc1dRMW024a4DAHga5lnnM9SxFz0Zs66TanMWfT+zHiDYso3DLz2CraKK+ZfcRKS3hWQkQOfm1dQvuwDV7kK1Oa19Fr4HoCdidG5eTd3isyw7c9v1t+209jHvok9Yx5Q5j82nDpEfZgAAgu5JREFUvRdQrHPefNp7cfoaqDv+XCoaF+L0TkNRbVTUz6Zy+lKctTOsY4ze/yTd7bsBmPbZ8oxJPdJICIEgCEX5O1cTYDe2cBXTdrydzoV/peUHjbiWBai6ug2vvgDbN26ifVM7XVu6cFY5qZpVxbJrlrH0H5by1Dd/R/+yZ1CvXgOAq3suM9dez6HTfkZlXR0n8p9UMbKa2gf+9BbJnsqS77dta6N122b+4bF/HtOxCxND28svs+HOO+nYv5i9r9pYfuNMtE+vQqmoQO/uQrHZsfu8rKyvZXqFq+Skl1KTd44Uuq6z+d572XbfL5l5zgdpXPnOCdlPsGUH3umLR/1+IVF/B66qhrx14a4DRHvbqF10urncfZhIzyHqFp3B7qf+m6aV78TTOJ/9zz3AnPM/ltc20tuGuybrlfYf3EzVrGUDlsPdhzCS8QFCPvcYIn0duKsb6Nv7BtXzThr2MY2EcNcBFM2OuyYbgxrpOYw7RyjmUsyWvn0bqJ67kkhva14/Gbq3rUG1OahZeLp1/D27XsNV1URFvXncPbtew1XdlHceRoS7k/nXnDG6tmWMxMAWIAJWEEbH37mKALtwd8/nuD//gO1XfIFIXbaE4HBiWA0MdvMwb/H/qN5zHnNfuBnbeZ3Mmn86yig8sE9e/WGi3UEWv+c/cVWbP5zts210b1xNTZuL5uNOZ9NTa3j3Q0dHLOXRxp/f9S4Ce/aQ9L6Ptm1eVn3+BA4rm1A/+mEAUls2cfacmTQtXTLJlpam7eWXWXvrrQT37aOicQEnfOzOyTZpwogGunD5pgEjF8vC+LL7yR8TSntgT/jsTcx/9zsm2aLxR2JgBUEYN2zhGuo3XwGAFh08d2ExFBSmcxG2cA1Ve88CwLF/DqlwalT2rPzcv+CqdxMLZNMtxSogkugjHjVjKI/uR/Kpzalf+hK1y5cDCu5qN9NmL8auZsuIxu/+CY4yT+T7+ne+Q7TTT+3x5zH9jKsm25wJJSNeARGvk0z1glOpmrsSQ0+hqBNXtGYqITGwE0SsO0bX2i6mnTYNza3Rt7kPPWEGnqt2lYrpFfRs6MFZ48R3nI/QwRCeWR5CB0O46l30buylZkUN4ZZwXrvqZdXYKszLlgwn8/ot3CYZThLYEcC32Je3nNlPZn0huf2qdhXvfK+1PUDPhh7ivXHqz6zHWee02mT2BRTdb+a9vs19JCNJksFkXh+5/WRs9MzyENwTRE/o6EmdhD+Bq85FzcqaorYPl8JzU2pdMZtyjwMYcE2K9TGULbnnO7e/4dieaV9oC+R/DnPPc6k+M58932If09reh7/mTWr3rgJg9ks3cfiUB4lXtZJw98IwCmnFumPE/Rp1/oupOXQmAOEDYVr7W0nFUua1PKEG/3Y/8d44tStriXZG8z5HuZ8Fm20R591+H+0v7IN0qKK3S8dRsYyGFWasm6fGR6zbjI/T3NqYPifC+NJ01llceuaZ/N/77sHflv4RdpifS1vMYNaKdxPaa0MPdeXddwqvYTKcpGdDD7HuGI4qB5pbwzvfS3BPEADvfG/Rz1Qqkir6fcj9DhXut/D7efLnvkb7iweomjUxw9yCUIy6RWdRt+gsauadMtmmlA0SQjDOZG6skdYIqf4UriaXOfEkkP/EpLk1UhHTC1V9UjV9b/SheTRSoRSOaQ7iXXFUt4oeyZ9tqVVqaA6NqmVV9G7sJdk38EnMPcuN3WvHWeek84VOXNNdpKIpbC4bkZaItZ/68+qJtEWIdkZRUHDUODAwiHXHSAWyHjKbz0YykMRebcdWYfYBoFaoaA4NR40DPakTORjB5rNhq7QRbYmiVWqoNhW71074YBibzwY6JPuzNmf6sHltJIIJSJrv2yptJPuTaJUaqf6B3rpM3xmbE/4Ejqrsa5vHRjKUHPDXVefCM8dD1+tdJPvMY6o7tY7+/f1E26MkA0lsPhv2KrvVLhFMkOzL2mTz2XBUOQgfDFvnW3Np6EndOnf2ajvVK6rp29yHkUwnbVeV7HHqoNrUotfRPcttbVPYRlEVtAqNaEvUsjNjX+ZaOeucKDZzeD4ZShJtiZqfw2gSBbO/VCRF1ZKqPPuSgaT12cAGDPKQ33bio4RXruNiflN6I+Dwk4eJtccG3SZzXgHrM++a7iLZn8yzydnoHLKvQqpPrKZ25djSfgnjRzKcJBVJ8eyX/gQJL4vOX0RHch/+M47D7U8xc1f2Q5f7fct8zjPfG+9CL92vdef1nfv5yNyzIPuZsvls2Nw2ou3RAfcdI2lY95nMPSdz39Rc5vctQ6l7kiBMFMlYmN7drxHu3EffnnWc8Nl/PirLFUsMbAFHWsDGumMc/vPhEbVx1DmId8eH3nCEbTJCuBTOeiexzpEJgqOBwvMyUedhWNdoFNd+vBjNvnvnrKG/cTP2BpVlddcNOgmrN7yDXW1/JNFrULPzQpyxmpLbjoWoC1xZfcGeV9/ivG+Zk2rEA1te9Gzooe/NvjH3M5nfG0E40uz56110bHjCWrZ7vVz22GNHXbliiYGdRGLdMfzb/CNuN5ob8XDaDCZegWNSvMLA8zJR52FY12gSf4RHs++a/ecy67UbmPfmp3F1Dz6Dds+OZ6h74X00bfqHCROvkC9eAQLtARy1Dhy1DhGvZYZvsY8ZV8xg/Qsb8tb3eyAxguJ9R4N4DbbsGHojzJn+GfwHN0+UOUIZY/e6UXOybCSCQWLpSmnHMiJgx4FkOElwT5C2Z9ro39U/2eYIwoQTORiha+3gCdJDszax77wf0rHoL0fIKpPOHSH+vnoHLz+/m9b1rQRbg0d0/0JpbBU2DHuAcFdH3vrKENiPllF5NY7/8JuEu/ejuMFebTfDumrtVMyrwD3HhaPOzpz3nY7mNX+CtUrVDEWqNFW86lHNkCug8fz5ANiqbCz4wPnp9xXrfdcMF/Yam/m31tyXrdp8T/OqOJvyY9+1Sg33dHdx091DSwKtwrTRMc2RbmPakrGn0P6S/VRq1jaap/jTS2ZfzkY7tmobmlfFVm3D2Zx/TK7pLmxVZn+Zc+hsdFr7sVfbcTVmJwuqbiXvGPL6GcLuQqz9VOQfg+oavrwKtrxF9841qB6wec1+XDOcJGI99LfupGfbeoykTNwqRNwT40BgR2BchsUEYSrQX7+F+Pz9zKt/+6DbeQ4up+bNS46QVSZ6SifmT/DSxY9Y687/+vmsumXVEbVDKI5hGBzevBp7IjzZpkwIjmkOmi6YjeY+bli5aStn+Qad8JqZxKgqDmtd9YnVRSfL5jLUxNnMxOJkJGnNH9DcmjW52O61k4qlrLkMzhon4YNhvIu81qTjzITPzIS4wsmkufuN98at+PvMXISalTXWMbjqXdZ+M/H7hROICyfWlpr4Wmqycqw7RsdLHSgo1J5sTuzL3a/m1vLszp0cXUjuhOLcSdjBPUESwQSRgxF8S3z0vdGHe5YbxaZY51mxKVb7zHmfddXlqHYDzeEgGU7S8vQWNj/4HTrXvTzo5+dYR2Jgx4FkOEmkLUKiP0G8N05439F5cxaEDPvOuxNblcLZ7ttNr5phoPc+gpbaBs6lENvCvvCTVPdG6d35HYywmdezr/l1qltPnVDbNj65iZWfOxmHZnoyKpsr8TaPPAWYMP7423ay4eBe9vygg7MuOBWH+8gVH5hIqk+qxjPDc1TFXBdm0hlpdpVjleFm+xmMTL7kwXjHb35D7dKlYzG17BipXpNP4jhgq7DhnW/+QMa6YyJghaOeuS98FoC+JX3EOtYQa/0us05dC+5K9Lib3kOfx61fg33a7yHWaLULNW5F1R342k+YELui/VEC3e3MPnWG1AovM/RUktbNz+BS65m3dP5RI14rZlfgW3j0CTtnnZMZ78hWqJJsHsPDVmGzztVgqQsH49QvfYkNd95Jz6ZN42naUYfEwE4gxeJ6MvEyMHi8UW7b3DalGM42o6EwRiiD5h7BjAvMWcO5uKa7rFilkbQZaXzSeFFoy4Ttp8T5HgpnfenrXyq+bMC+08dYLHar47jH0dXsxJmEsxe8Gwjve5pY9wmolbfSsuNxDr/1Kzp3f4v+zn8g1H0l7dsfwEhlf/hmbPhoVrxWZAd/XE1Dfx6GhQG618v29pFPphQmlmDHHhLRIFWdDmbPbRp02+F+FgrjDnMp9Zka7Pswku9f5v4tXklhvGk66ywufeQRTvva16x1iipyrRD51o0zmlujclGllUC7f3//gGTbuQm2+/f307+zH/csN8lQckAsUqbQQXBP0IolQsfKy+qoyW7f1t6Ga7orL2ehe7qbSEvEyg+ayZNq99itPKaZm3xu7sNcO7rXd5PoSQzYX/f6btCx8pLmtjUwiPfGrfyKlQsrCRpB0MFVb8Y/pSIpOl7qAB0rH2NhnlL/Vv+A+KSeDT1W7trMvrUKjVQ4lZc/NJM/Mu6PkwqksjlOMSdWZPaZm0M1N/9rpp292k7VUtMWza2RDCWt85d7vq18u7m5Y3MEd2FOVxh4HTO5e7VKDUVViuaBzeS+jXfHrfY1J9bQv7+fSHuEVCA/Z2rtybVWvt/M9cjNsQnpnLRLq6xhQv9WP93el0jQT+3eVTRsvzzvc26P1UCsxkoVq8fnW+8lI8MY1poWZfqZ8wlsDxDvjVN3ah0Ana90YvfaB+TzdVQ5OPTMaoyEgrt+Du7qxqLdurwuznv36ah7ojC4RhKOMN6G+dhdXpL6Pno3umhcOK/ktnafHdWh5uVxLvzeZOIxM4VOAIykQWhvCEetI+8zlfneZvJAZ+5dufcdV735Xs+GHjSHlnffzMRlghn/mAwmrQIJjpqjw5MslBeKotB4xhkAaC4XVQsXmh5ZRZFyg2kkBnaSGW3lplJVpHIrVw0nCB6yAffDmRBQqnLXaNuOlVJVskpVIMtU6smtVlaqitVwjqtYn8M97pFUAxtp+6HsGk581t+5mnC4i6YNV2NU7qKqqxnHwX8Y1KbBCC/4Dbamx9njqyNZ2Ud1xXxO5D8HzSWbS9vLL7Phzjupmn4+jSsHrwPumeeh7tQ68YyVGf62nRxY90e23etk6UUX4K4qPhseShehOBL3m4m+bwnCcAi1tPCHSy5BdTh4//r1tL74Im/9+MeE29p4x69/TUXT0fWULoUMCih3ASsI5YifHazjFvrYwsz1VzFt44fG3Kfq3I2y6Ke8uaSTZEUvoOJjwZDVvHJpeelF3nr2bhpWvIvqntMG3VaqcJUfhmGw95VHeeWWQyw6+23Uza3Le79lvo2aGR4WVlUeVROiBGE0RDo7eWzVKgA+uGkTiqKYE2aHkeFiKiKFDARBGDNr+TJ9bAPAW/8wjoqNY+5Tjy0gtem7TNuRSb+lA8N/fvazg1e9NxP+0iYOrrqbjoWvc2hRIm+bWDjGy795nhlXzLC88UL5oCgK05ddCEr2pydQkx2eX7qojmXz63DWOUW8Csc8uSJVT5j3OkVRjkrxOhpEwAqCUASDTMDh3mbYe+7dJOpfGnVvNsc+nM2/YO+5t9O1+K+j6mMtX8ZYbt7EU94+Ws75DqGF387bRlEUou09IoDKGJevHpvDg6KawjVVHae7yYzD99jlmglCBrWIgBWyiIAVBGFIEjV7UJfdSv2Cz46qfd1xn2HavG8RnfNsOnxgNBig5HtsE5UH6Vj4Kn116eTnNhUjdVRHRR0d6AaqZv78GHaFjnl21CWVI85uIghHM7kCNhWf+uWTx5uyFrC33XYbp512Gl6vl4aGBt773veyffv2yTZLEI4p5vV2c+G+nSyKbMftewV39RMj7iOpqKiGwXkHdmdn0BoKMLZcrcmKXlpO/S2d88wbvc1uw+6emJRywvhhgOWBVVRIOhW0pV7xmgtCDqqmobg11LcrJOLZMvUpYhzmb6SITaJ1k09Z3y2ee+45PvWpT3HaaaeRTCb58pe/zNvf/na2bNmCx+OZbPNGTYoYbTxPE29DY3J/bEdrSzkdw3iRIkYLTwPQyLl08qp1fIXHm9lWJ4GKfcD2uX1m2gEl+y9my3DO72DbjeUa6WSf9vfW1NHq9bG8o5UGOnHN/R8S2+aSjC6he9saUokYnoZ5KKqGoacIdexFT8ZQbU4qF8yicc5aKrRWK9zVMAwzjkt3s0S7YQRWlfasxl1ZIez0lJ7ZLpQJumEJWLuRos5px2fP974O5/MbJ8A2fsrx/DMOfEW/p7nfvzaep54zrO9e4bp6zqCdNeiYw7W53+1aVrKTBzmefwZgC/dQzfHM4tKj6h54tN3XpyoGBi08g+PPKkqTyvPJa2niYqIcws8OonRgw0cdJ3ISX6Wb10kSpo8d1LCcWVwKwCGepIfNeFlAkN2D/g2xj8VcRw8b8j7vDspzPkFZC9gnn3wyb/nnP/85DQ0NrFu3jre97W2TZNXQxAmwif/GIEUViwiymyqOQ0Wjl00c4HFSRFBxUcdJNHM+QfbkfYA6eIkeNlPDcqazilaeoYfNVHEcdtw0ci7trCFJmAC7WcBH2MMjzOcD7OJX+FiAgkEPWzHQ0XCwjE+h4aSN52nkPFp5jje5jTh9aLiZxRVUcxx+dlDFcWjY0EnQxw7rQ17JfNp4lh7eJEUEDTczeCcqNnwlvhiZvjKo2JnORaSIWT8+Gk5aeNr6Aha2ASxbCt/TSdDDVkDJO9+59ldxHApG3utMGx8LaeM5unkDnWjePm14qeVEeniLJAHAiZfZhDg4YFsAO1XM5J1Uczx9bOIAfyFFGLChAIaVOdVEw0sty3HTiIItbcuzdPMmOhFU3MzknYCCgkINS9CwkSLOYZ62roMNLzXpfkBDweAQT6Tfq2AZN+NnJwa6dY68LMDPDkj3m3tO4gQtG6M2O1GbHU03Y2K7Gw4zS7mOlvUfY9/TL5EI9XLqLbcw713vovXFF9n13Ucxwvtx1yTp/7jGUnahAnFF44XZC6yE3Ck1wpt8nyShAZ8NyIr96VxEP/sJ0VL8C6f1kPKsBs5OL8swdLljGNkQAhcGJzRNI06A9dyOThIFg4M8MeA7ADoKGl4WcIDHCLATMNjFL/CyiDCHSRFGxWV9b3UigD39/cvGESo4UFCLfo8HYxe/yFvewK2czDeYzgW0shoY+gG1GMXEY6FAz90uV3QP9+G51AO3gcEh/mr9HrhoZDqXUMtSZnDRoA/HMPDBYKiH8ow9hecq01duHyliHOJJ+thmiatifbSzBjDvF6XOQ67zodi2w71Oue1LHf9gD1NDORt62MQ6vkaQPVBvbhPTutjPI3ntkgRo5wWe5O156/fyKOv5GqQ/9SNhNw/nLe/iVyziH1nGp1HLbNB+SqXR2rVrF4sWLWLjxo0sX7686DaxWIxYLOtWDwQCzJo164ik0dLReYvb2cOvJnQ/Y0HBlhZRI/9gjy8akMpZVrGylAtlyTt2baEimSCuqgR1Fy2/rmDjb+rBUFh1zz1MP+88wBQnwfXX4fPcn9e+vaKSF2cvGMae1PTnNOMFtqHhSD8I5GML12CP1KDGFrLobzcCsH31W1x4xzsBJBVTmfLwO+9m+dvPxVPrIbEkSvT0J9nNg5Nt1rij4aWOE2jiPOsBEkBBo4pF+NmBgkYNS9jMncTxo+KimhUk8VsCHaCShdSygkM8UVR02/BSx0pW8O+8yXfpZj06ERRcGKSAgZOAFFxUsYgILcToLnkU9ZxGM6voYwdhDtPLRlKEUTCLjpDzm5J5ePAwkyoW08f2vDalHubBjoqCThwVFzWcgIFOLxsGbKvgApJF+jDPRD2n0sT5aceE6QzQ0g/5PayzRpgUXEzjJMuBkPtwn/uQb143FQWFQ2kHVObcqNjzrodKJV5mEqaFBAHrfGSOP9fp42U+7TxPL5tIEEDDi4fmvOteLtio5BRuYQYXT9g+jto8sIZh8J73vIfe3l5eeOGFktvdcsstfOMb3xiwfqIF7CH+ylq+VOILJQhTE1cygSuZAMNg1f60J1XVeIrjCF6Z3e4dv/kNtUtzKnAlWzESLbzgv4GVoU34EjESqspf5x9PzGYfN/uaNryfpjffX/J9yQVbnjx86d2suOw8Kqor2H7x/xKZ8ZfJNkkQhCFQsHMlayes/6M2D+y//Mu/8NZbb/Hwww8Put0Xv/hF/H6/9e/gwYMTbpufHbzGf4h4FY46MhO4LkyLV4AOTyUxZQivpq2ZdW6Df63fR5cjPaRvwInth8fVvq7Ff2X7FV9g+6W3o6c9Ftuf2ciMS6qZ8fZqyQVbphiGgZoOJdE1mV0tCFMBgyR+dk62GRZTYmztX//1X/njH//I888/z8yZMwfd1ul04nQe2eDztXyZcnP3C8J4kJnA5U4kOOvwPnSgPtyPI5WgN5HErWnsWhbha3Mv45DeBkCNUkNACeDESa/Wyz7NwXygxesjbHeaWQiUsWUfyJCs6CVZ0cv8zpOtb2B/RwBn6HVzwbEAKoYTtiAcSQzDQNHSnwFNHvwFYWpgsJYvjah64kRS1gLWMAz+9V//lccee4xnn32WefPmTbZJJRDxKhydZCZwqYY50Spis2PoKWLurXziCSAKNAEV2TZtmEI2nI5ZfVOLcyHQblPoc9pY0tXO1mmN4yZij+++iLl953DITM5EXmqunt3m3zoRsWWFgeWBNRQRsIIwdSgfvVPWAvZTn/oUDz30EH/4wx/wer20tZk/jFVVVbjdkipHEI4UjqQpMgI2lc/XJlgcA2VaOpXrEHSk7zK7E71c4u8lWlE1buLVF2tiac+lRHNuqvFwQW7Ent1Q2QBO77jsUxg7hpHNA2uoImAFQRg5ZR0De/fdd+P3+1m1ahXNzc3Wv1//+teTbZogHFN0p0xvarcR57gYfHMY4rUpCSdFwZ1OLnFpyExm9PfGhnGzSzXM+Fo1PRcaIB4qElM5NeaqHjvkhhCIB1YQpgyGXj7ZgsraAztFEiQw1mpCglDOdBBnd6qDdwEL4wZL48PzvN7QC7fkZOap1eHXXoNrbTv5P04cN/vMwAHDtMkwlzN3Dvlmlim5IQSq1HgXhKmAkTQI7N1LqLIVT3PzZJtT3h7YqcJpfIdpnGIuTBXNLQhD4EomqI6GuTe6laXpUXkd+FTj8Nr/Tw2cPBeubTKXIwpcGIYvJ2eMq53btQbesOVM7lQU1tpms10bP0+vML5ICIEgjB0jYWDoWdFhxAyMRL4IMXQDI26u04MGyedSGP3p5f785YzTcMDfVHr79Qbxf4sT6+2dwKMaPmXtgZ0qVLGIRS9fT8/f95C8vgd1uoIeNNDX6xiHwXaliuJO36yDBql1OvpqA+U4xRS8KtjeraJUKhg5JRZzXxdbLlyfKdGZ+av3GugbTXe/doaK4iztj8r0ofcbKA5QHGkbIgYooLjMY0r9MT18YICxw0BZpICWtV/vN9DX6Win5B+PkcoZMszdb9rWosdT0MaIGPD/2zvv+DiKs/F/Z3ev6E5dVrPk3hvFNhhiCKa3UEJJQugpxrTAS36BBGJqgOR9k7xJCGBKXkIoIRAgIQFCsw0Gg21sDC7g3q1mWfWka7vz+2NvT3enU7ElWxLMV5/76Hb2mWeemdm7e3b2mRm9zbYkuztq75Q8MiQhgm1rYh7H/jqJ+S8LJBjn22lOv0X/acX3f5BrZds+DAZoJwq0wzS0/BR7E9rO+tjCekPiullH5AusvRLzNatt3pEVa9PYdeG0r9wg0U4UbW0aaxenra03YuVMFMl6UvumVSIce5ol5j8tRDlxvdZeiayw0IbZx8Or9jCxqZoVCX2z0QU13fzWqDTsV3PsNjkKeIKCOZXNLC0flLbP9xVLmGRZQbYYBWSJEEgIY1Ar/JSZ9W2CvRRzq+gdkrqjgxACg2wmcT2NbCKbUdTHFpTXYpsA1LMeHYPRXMZGnsIizE5eIxpbLL6cM+M7BCbKbuJpMhlOI5vIZRwSi90soI5VRGjARQ5DOJNcxgPQwOds5zUiNOClmFJOQCBwk8MXPILagEVxIEj32xg/Z0pkNYRPj4IH9Gs05BqJ9ab9W6CdKhBTBJhgPmBBFLTjBNZC+/cv6rbSH38s0b+nYT5lYdymoU3SEKUgqyByfxRrfv8aoRswGxnsL/u6MO7+8o8TT6SlshLcyRcKYKedaDsl1jsy3YYobfkWS7Svx2QXxd7rQDTl2MFJ/1rCxfcnC+2INDacKhCTbIdIjBHIz2NOWKKOhbEPQKK9Ik2dOrLfkUmsz9cS6uXYboAYIzCftNCv0JDr0tiyOKX+7yTYpqexu6P27k599rffUtvgxDT2dqes7pDapt3Nn1hed+yJHbtXhtmhNfJkVRW/uQeOnwhNAkaN6r4TC5BrQl1s6cCLHoCj/DolU8aDEPaNQCjh2vaAGJ9wbRq2Yy7KQD9UQ+S1vykaX3sio/aewaaPhuG1NN56cD5XPDMCT+wOo8XMxjf+qH1oaMWB5unjH+RrV9i7pX124Y+xfFtiZ+w7xEFM41B+Sg5j9kmvvSXnotiWnO5ey9vRuShB1vJHtvGvuPNbzhkIYEfM6XWcaTvQxXZ2tdh2uNt4iUbW4zy6K2ImXkqxd7TSKeAQijiKL3g8vg2049A3s5WRXMwqfskeVsa2um7bDauAw/EzhF280c4xF4j4FtwitgW349BrabbpdmScmwgDN6O5jA08Gberma2M4hI28CQmkaQbjXR58pgQL8spx7nJcHQAGLiZwDVU8R4ruY8oAQyyKeAQSjkBHVen9trtrbGD15PayEUOZZyGxEJiIdBiWxg7W71nMIQzkUALO9mbsL23hkaUADoZDOVschhLAxtiO499znb+Gd/tCwwGcQT1fEo0ts1xAYen2brctkvgJXvvKAJ/3Et49m60kvbfeeZSi+h9JvJAL8nawW9Vu41reokv7U5c+8vBcGArP/yQhVdfjRVRsVyKLxcf1Nfz0O7dvPcyHDseGjV4ww/fGkzbbsSJ/+uwB6SyaRtZ1iC8DlzAzS9pzMzMYOu/SijcvY/rNce+TGW1xHW3jjZai49SjNtzIuL1q/FaGgv++Dbff3Y4AJ89+xrlF84+IF+2iv3nmRMe5OjLbQe29YzPWFd4JwAZlHAoN1PK8YgBFMGczsHtrjMdppF1PM44ZuMms0flFzKDGpbslx0Dgd64QUnXRt0pIzEdZKd2mITYzXxAMJgTYlthJ+tNtSfVLiklL339WCKH1WP8TLef7O6WRO83+3wkVDmwB4mD4cD++6yzaNy8+YDoVij6kg/q63nI2M3av8CEYrijwPZJ786PTeQKx15bgCJgJrALSFnJavcGKDWhToO3/fCtMnhm0v59AbpfMhCjaReSMu7pF8gwdRb88W0Gl7yIZVo0bNt9wL5sFfvPMyc8zNGXnwqA+7RWlhZfDGh8g3dxo5Y7UygAKhYv5oOf/IRwS/3+PbU7QPQXB1ZN4uoFpt96K/mTJ/e1GQpFr+PXddgGgwbbxy9mw12FMedVA7xANtz6wq3s9uxm4RMLbYf2YihptZfROjzYFgcrgGvz4awbCvbfKK298xpXDiAEh94yFz0rH++gQXjz8/e/LMWBIaH7ar2xXdOweIcL2cX8hEXRFIqvJpUffsinv/894fp6CIP1Vv9wXvsTahJXL1By9NGcetRRVHzwAZ898AB7V6/ua5MUil7Br+uIiyF/rn18dCtc2Ah3DYpF7UWg9Gel3PvrewEwR5n2HfSzDVw1Ee48P1nfF26omQnL1zTxndHdXM6gmyS6PIOPOYbSmTOxIhF098B+bPrlJDY5Uko2+f8cT22liiXctN8xsArFl4WP77tPPdntAjUC20sIIRh8zDGc+txzzHrkkW6NyBYffXSXMq6cnH23xe0GXe9acH/0JMyKFG43wkhzD+RyobnswHrh8eAp6MFoW3fQNLTMTEZddBFoWlK68HrxJIzAeQoL22XXfT6yR4/GlZfH6f/4B8fNm0fehAm48/I47eWXOf+jj7hw+XLO+/DD+OuYP/yBzCFDELqOJy+Ps996i3M/+ICJV12F5rFjOzOK7e1SNZ+PnJj+qXPnkjlkCGgaRnY2R959N3kTJuDKzWXq3LlJ9mUOG4aRmUn2qFEYfj8ZJSV2/WI6s0eNwpWXx5F3303u+PEYmZnkjB6NOy+PI+66C395ud1fmobQdVw5OZz28stx++PnhUDLyLD1x/pXuN3URqP8evt2cl9tm3t3fw1J68COu3gUfzntL3Gby8vL+f3vfw/AI+/Yy2hNHQ6v++3zk0MwpcDg8pKSnvV5OoTtwrYNxArlvPZXYp0kAUTiLH67D/fwCcu49WBbpVD0GxKf7Aqt/7hq7pycfvNUS8XAHiCklPER2UBFBSc/9RS+khKklJjhMJqm4c7MxDRNds6fz9pHH6WlspKTn346LiejUVx+P9FQCCsSQXO54iNKUsqktMRzQgiEYbBr4UI++fWvCezciSsri1OefZaM4uIkHWbYninp/Ng7ehP1RAIBNJcLGY1i+HyEm5sRQmB4PPHziXkT0w2PB83lYvf77/PZ739PS3U1J/3lLzRu3szqhx6ipaqKk59+Om6X5nJR9eGHfPbQQwQqKjjhT3+ieds21j76KIGqKk7405/wl5amtVV3u7EsK26fk665XERDoXh7muFwvO5OPRLbz+m/rkbvEnUkylmWRbSlJV6WY0Nqu6drcyllkq2pfZzYX51dD6n9m9jHqfYn6ks8Xr1qPldedjrDSuHlP9rLYNXpMGkE1AhAh/dr/sPMwlOT2uWZZ57hkksugTLgU6AA/nc33NgILcCC9zU+uKecyZlpJqxoGkZmJsPPPptNf/0r0rRXEjjhz38muHcvK3/zG6IPVKWNgR371+fxhQ3efWgBVy75fof9puh7nj35EY665GRMabHq0itBb2onk81oTuLvfWCdQtE/SPQj9q5ejdC0pJ2wTn7mGXLHj2/3O5D4O+Z8p0spqV66lDWPPkqgooIT/+//8JeWsmflSj793e9oqa7mlNhvcervhvPb4PxeHqiBATWJK4W+cmAduuMI7Yvc/pSfzsnqC9J9uDqq877IKg4MFauuotT1aFLa37Lg0o8EBaMMrEnZLHetpJzyJJm4AwswEVgDP9sD9+2Bd5ZA7V7YtV2j+K1x9lBubBTYlZXFqX/9a/wGxbkZcW72wL4O6iJrWWX8hlptRdvqB8CY557HHzJ498EFnLJ0BIMH2Ez2rxJ/PfkxZlxyIlFpsfqyy0BraSejHFiFwibVkUUIkHK/JlOl+y3tL7+vahJXP6O7juOBcjAP9B3TvtqSaEdndd4XWcWBYXfLWUw9H35uRwRQL+2dtHLXSSoPjzBk1nC+ePuLdvny8/NhKDAViD1pqopFmkQz4KRjBcdNdcfjEI793e/41scfc97ChWQPGxbvZ03T8GZnx51XsK+DfPckvq79iaP4LbrIaCtYtG0gu4SbWMQPaOBAL5So2FcaWI+p28tUxPb36UtzFIp+T7sQxUmT9nuCarrf0oH6+6ocWIVC0Y4dO3ZwyhmX88laiMY2SlpjgN+CB0+yj5cvXs6PfvSjdnmLi4thG7AcShbA4a2QFdu17GuHgpkjOe2ioP0lXFBAweTJ+3yTJRCUcnzSousyYRUCUHGU/ZVl3Ba/2ZBIEGY7GYEGavRcoUgi0ZE956238B2IuQQDCLUKgUKhaEdNTQ179+6FoVAWm494uAWfemBNCYipMGHSRG6d3YGDeDHwZ7iqHu6sbUvOkvC6T/C/xlOc+rfv7vdjqwbW8ym/IkJC7GTKJC57ZO9LHSE1QLGSJ1umGYEt4HAO5acHzySFYgAxUEdMexvlwCoUinYY1HD4RGA5TK4CWu2dXc8phxrdTl/LWi7hEi7m4qS8RUVFFLxRQO2MWh5ZCq9kwaAovLnTdifPavDhLToJ4dr/L+Fl3EYjG5PSpBNC0MH+4Yq+p4H1BNgVG2EFDYHRkk3UXxeXyaCEY3lcxS8rFIpOUSEECoWiHYWul1jxIqzYCse32mkrvVBjEB/i1C2dp3m6Xd7y8nL+9Kc/AVBpwCcee/etcCxrNBRgy3vDefvtN3tgoaTd6GrMLiEEX+6pqQOXpdZt7L5jOOHYwLkhNFzBvCQZF5nKeVUogFAoxJd8nn2PUA6sQqFohzOBa+r5UNNop00OQWG0TWbIhUPajb46NDc3QzVQAVTb8ak77KWB0QS0tga54YYbetdoLRZCoImEp9LKEepXCElwTTat1R3/KKufa4XCnocwdOhQpk6dyosvvkhLS0vcmQ2FQjQ0NNDa2hr/HwwGu3zf0X8pZVynZQ2cSZUqhOAAEQqFcMfWIU1HY2MjLpcLIQQej4dwOIzb7Y7/F0Kk1ZGalnic7pyUMq7feZ96HkhKT5fXsS01LV39Oqp7Y2MjmZmZaLH4t85s7259nQ9eVlZWO72p9nZU/3T5U+96HR3BYDDJHkdfZ2Wm6u+qnRJ1BYPBDm1z9EYikaSyu1NGot2p7bJ27VpOPPUSGhrAMKAgtgiAIWHBdpgyFKQBN998c7u+T0KHkiug9GLgW1AXq74p4ap/jeHWR37eef6UeqTamYoTQmA7sAJd93AE93W7DMWBx2jNYsz99TTMblsix/hkElpGJvqgEHJINZrPRQMb1C5ciq80q1atorq6murqai644ALAXuHlF7/4Bbfeeiv19fW9VlZxcTHNzc0EAgHcbjdz587l1ltvbfeb1d/o39YNEJw7l/r6elpbW1mzZk38zumVV16hvr4+6fXee++Rm5uLz+fD7/czYsQISkpKmDx5MiUlJUyfPp1HHnmk3d1Xqt7Vq1fHjx955BGGDRvGtGnTePHFF1m1ahXl5eVkZmYyfPhwioqKyMrKYsyYMfz9739n1apVlJWVkZmZSWZmJqNHj+bvf/97vBznXKJthYWFSWmJtjn1d2yaPn06L774InV1dfE65+Xl4ff7ue2221i3bl2S7enybNiwIakNVq1aFa/jI488QllZGX6/n9zcXLxeb5LeVHud96NHj+af//wnq1evpqysDJ/PR25uLhkZGfz85z9Pahefz5fURwUFBfF+y8jIiOubN28eQ4cO5ZBDDom38/DhwyksLGxnXyAQoKGhocN2Wr16NcOGDWPKlCnx8jqyLTc3F4/HQ0FBAYcccki8jo7NGRkZcXudNL/fH7f78ccfp6ysjKysrHj/v/vuu0yaNImGhgYASgbZ823CxJZsNWFs8xhKZAlnzTir8w/GNrjqaVhxpB2KMD0US86BDx7ZwCXHXBIfIZBS0tjYiGVZNDY2xj9LwWCQDRs2xO0cP348//nPfzBluH15Mb9W0zSkKfBRppygfkb2+qOYuPiXHH3F1+Jpo3ZdySEb72TSR/czaP0pNMjP+Ygf96GVCkXfU1NT0y5t7969XHPNNb3qvAJUVVURCAQACIfDzJ07F6/Xyy9+8Yt+PSKrNjLoITt27ODQQw+lrq6ua2GFYoBQUgilU2DKFHhyDgSBJh0mlcHclX9g2tHTKBNlDGNY2vzPPPMMl7x2CSWPQ2nMsbyyHq6vh6CAawtg6Etw1xwQQqO0tJTdu3fjcrkIp+wCk+4rat7mKQwariXN1xrxytPk1Pn46ImPcL36G/ToSM7LeaH3GkXRYxa0fI/ArhaarzmHIy+ZAcCmsicIZGyLj8BGfXVgujlPX9rH1ioUfcOOHTuYPHkyjY2NfW0KLpeL22+//aCMyO6rv6ZCCHpITU2Ncl6BC06FyWPgrgf5Sk6gORD178s2vepbcOd1bcdeYKMOe7zwo6+1rf0qO4hYzM/Ph2eh8nOoXGGnDffbDqwu4aEKeKXFrpeUFrt27QJIcl6BDicwtDSHEImbGEBSDGyo0csDl93HOf8BXe9+vRUHlsMzfsoTN/2JrJrmeFr08DVYBZuTFtMKR+Clf8J55x18GxWKvqampqZD5/WCU+GmyyEchRVr4JRjYO0m+1x5MWRn2sflxfbn6KFnYeJoWLMRLjwVykuSZcqLoTGQ/tjWGSE7cy73//h2jJJ7ueWWnx2kVuga5cAeIC44Fb51mn2xhCPtLzRou9gam9NfUI3N9ntof+ykdZRn886OL26nvBffhDv/COefYn8gykuS9aaS+uFwynn6Ffj9rbCjEmYdaX9gLoh9UFLtTa1TR7Y5cp21g5P/802Q6bM/nIlt4uhJbf/PN9n1/p+fwGnH2u2wekPbh7ujNu+ovYeWQvEgqG+0653Ydp9vStad2n5gt+FDz8KNl0F2ln1+eBkcNg4+XmPLdPTlk9pW6b7IEm1AJJed2l7O+/wc+KwShpVADvbEmvFhKDShWgMikHfTYBaeD8cea+tatAgqKqCoCLZta+v4kiiURuP+JRoQtmBPPWyf39aOqf2f7jpwbDxU241vp0aTx8vng0pi29G2ObDVWwaz9O0xLFoEs2a1v5YVfUNmdAwL3zuNC6ZuTT4hAdr6EODGG+Gcc9QNiEIB9ucgPweeuBf8Pmhpga9PB0vC2OH25FhNix0Ps+cvtLTAM7+GqloozAXdsOUSZaBNhxH7rEkJ40bY/w09dn6j5Ns33ca0aUdw0kkn9VErJKNCCHrIihUrmDZtWlJaYT58/qr9Y2voUNcIednOaFNsASDLvniktH97LQmWmXxBaQmPR1OPnbSO8gSD4PXGZCzQtbZyNHsbZfY22E7EiDJwu9rr1XTAsTd2IUtpn9djTxIiEXC5wLRsvYFWyPDa5/SUpw3p6mRZyR88xzbn0XBn7eC0ZXWtHavppDn2OXqc9rdiV3pdg502eqidVt8I2X77nNOWHdrbSR+l1gmgcg8MyrXbSIi2vk98ErO3wXbA3a62kVanr6JRaG6J2Sfa90FqW0kLhNb2JWWZtvOXk2nnd667dHWyYtdnql7H7jD2mq7fKgOmGvDJ64D9RaZpdr3bWAFMgzK4YxHcGUpup501UJbQZ6nXZuJxYlvHr2fdrs/uzByWlg8HYPjrT5JbncWyZ5ax644X+fExz/Pss3DRRSj6CQsXwiOvNHHG2n8x86KjCGGy4bwfYwUvRbq2InOfASDc6uYi31IWLFA3IIqvHh999BFHH300JYVw3HQYPQxaL59Drt8iKjUMYTHX9Shgf1/eE53Nn6Ln0kgmh4l1zPf8EIh9d0s4Kfwom60yLtP/xZ2uee2+3x3ujMxBx+LnxqNJ9tQ1wpBnZtMS1pjw3rusXbv2gNRbhRD0ASWFMGUMTJ0I55wIU8aCz9t2YeTF+iEpfCR2p+PI6ML+gU48dpAy+ZyDBmhG20WqJVyQGRnp9TomCAEFufYrFYHt0AiR7Mg4+URCmrMOveOsZvrS50usk3NOw3aSU21LbKfEPInlOLYAlBa2L0eINO0fO06stybsu9pEnY59ehr7E9s49XyqDMDgopT2g3jfO3XKz0n/ZaJhO7WJ9oHdPon9mNQ2WoJuafdjUv6UmwpNgO5qsz1uZ8qXmsTilUyNuvppoC2Ds8+CaVPgnM8hy7Qf/0ogoNn7zQoDxCIINXLPJnhocAW50qI1XIYhYFhWBQvFD5LK0hPaINWR1mhr87hTi+DTkrKEysRGYIXAitgV3bABRT+iogJkYzS+72/IsJB1vwZhIX3vAnaf12wvicsrFF8lduzYwZlnngmA76nH+U/ROAAEkvpoDrk0UE8Od0Svxg7iEthbglhINBbKI9GCn8QXELTP20f3mFdxr/lDLDRkPNWWso8kEp27o7PJpAWAXJqoFlm0XJmDu6aG6ZdedjCaoVsoB7YXSI0X3F862kCoO+mdbT7UXbnuyncnrTv27E+eruiuvfuqY1909cTW3tIjRM8fvd4ZmcO75jS2ysFspRwagiC9UHkknAkYVe0zZVkJTnI2ZGVjAXtDxdQQ85Ql1JPFiNZXudywRwQ6qlO6a8V5Xxl2MbKuljV5RWiGhhT2ELDQBEMbi3nhgT/z+6fO5LbbCtVj6H7CUWM3cdH0Tfz1WhMAKTTyTUFO5lNs8C1CINj03gQevO5uwA5HScU07ZHchQvt41mz7DCWxYth1y6oqoLa2PbF+fm2jtpaKCyEkhI7/6JF9vmvfQ0++wz+9S/bcc7Pt6+vYBCmT4cTT7RlHnkENm2CUaPgmmvabtwVit4mvo03ICyLBpJHIuuxRyRkymhE8rGWdnaCRMNMkOvo8XsUV7ycenJwvrrDhYWMKS3uINfBRzmwvcAjz8OoIXDpOT3T051gjlRnJfGRc0/K7c3dNy1r353xVHvi72m7SzzQO4Sma/+O2rszma7K6MudTrtb/p2ROTwZPct2XOOZvW3vO/rm6GCSqklbjIozglBPDu+a00g4tU82lhphdi5vJDqrDLdhJk3iso78CN/XvuD73iYWvXcds47vw0ZX2NRuYkR2LEhbtj12mWLuJrf+WPSWFlb9+g0efvznbA/ay59985tQXg4eD4RCsGeP7Ywmhqv84hcHxty33oL772+f/l//BXl5kJMDgwfbNv7oR8qpVfQu/v+aAx9/TOkkqBgxo6/NAeDu0mLmlvQfB1atA9sLVNbAzb+xdy065fsw506IRNtiXk0rIf41FsOXeOy8ErE6OO4oT3fLSZVJtLOjV6qeSKT9+YqaZJvCkfbtZHVRjmNbIl3VUUq7rEQbU+1Ll6c1mHwcjdKOdPZ21CfpykjXdk7bdCaXar9jX2qdu+q3VP3Oj35nck7ZGlay89pLCK0hfmcPcLy+LG3/d9amjowQMGhIJobL6RgZK0NAVBDMr2bQt16kec/GXq+HYh8JNcHexJmhtgMrE+4rJoVPJWtTCSQ82Gxqgs8/h5Ur7f81Namx1n1DXR1s3WqP+v7kJ7aD/f/+X19bpfgyccREi03fuJarx3zMOLGlr83h7qw1zC0u7FrwIKJGYHtIUVER+fn5VNbspTJh3eFIFB6aC82t9gScLbvtmeVCsx3eQXn2hKdsP9Q3wZ46GFEOTQHbuWpsjs3AdlYGSDkGO39SngA0NtnllBRCoAV274HhpXYsZH2TXXZLEA6fYD9i1jT7kVpDs60jUa8Rmyjj2NvcYk8GqqyFnRVt5UjsiUhvvA+Xn0t8YtXOyhR7gxp19VY8LdBqTyAzXPbEqqo9Mdsm2hOr0rZDrI5DB0Nxge3EGLpgwzZJps9Oq9xjvw6fYNcr2w9bYvYK7Dq73bBpOwwvt2MtGwPgz2hrS00TNAagvlHGZ+wHgjAy1t4trdAS0tlbZ1JeErMzYMfbOnUCsCfB2UGd9U12+1XtaWsbTYOi/La6Oe1bWQOHjSc+cauhGTIz7OspJxNq6zWkXkJR9m7qm2ybA0EYMdju68ZmQU0dDC+TuGKf8upaQV6OjNcxsa+bWyAny2632gYdc6TOLG0ZC60jevgJSUZabc7rqZsfpKkM7siYw49a5rX1/wT7Wq3aE1vlYbAd55y6BGHUhBotC00zAYHU2kIIsDTQ7EW+hvgXYJkj0HT1dddnpHt0Ae1mQWoDONbjN7+BV16Bq66yQxXKyuzQBl1vC1uoqIDS0rZ0h8SwCMuyQxk60+GEVlRW2k69Ex6RmlZYCKtWwebNdhfk5tr/9+yxbwgAJkyAxkZYvRoCAcjMtNd/njYNiottXTU1sH27bUNtrT3HQkr7M5mVBYcdZtfLCdF4911bfvBgqK+3wzoyM2HyZDtkY9s28Png8MPtm4G1a20bDjkELr3UnvSaWjen/qntM2MGPPywXebOnfbk5WHDbJvq6uy0wYNt/WC35YwZMGRI8goqu3bZ5eXlwbJl9s18VZVdz9Q6AlRX2/2QGJLihLMsWpQc4jJrVuchXU7/z58Pn3xip31x66OU/hBuv+BaRogd+35B9iI6MHd0/5sNq1Yh6AVCoVB8N6H/aWwGy+TnxUVYDc/jlusJi9HokXXcGzyOd1vDnOBt5o5igzuqLd4LD+N491YinmN5v2kbx7q2c9uQc7mnqob3g2GO9rjtOT+6jmmauA2dH2dnxbcO9Ub+jQyu4p7IHAyPhx9n+rEsi19XvoRbVvK2uADNrObtrN+ieyfT5LmJX+1tQEa/4KPWejaZg/hexipu8VcQzLwFjzeDcDjM/+xZyuKWAMe4tnN7ThUhMRq33Ih0TeD+Oo2I51h+kpONp+FWXOH5RDxncWfkajzh+UhzK+/JrzPTP4af5OUC8NumZoRuYIbD/KWxiRFuN8f6M3ivYRsn6EuZb05Bdw0jallsDzciiICWyyW52TxV1wDAJVmZLI5EME2Tr3k93JX1Ab+qrcVC8DP/Lu4IX4VHbmSu710CGT/GG30NPfI5lms899dpRLVC5uoPolu7wWzA8p+HdE/i3ppt6MCPc0vRo+uRBXPxZviYu3M3H7S0MNOXwc8L7SnznvArmC2fcU9kDugGP870YVlW0hanWuBFaHoBTQh0XeeuwHFgRflpZiUiYzIyuIag/2Y83gx+uWcv8xu2ols1HOdp4ubsKD59K02e/8ITeZVf1dYyP1TC1/WN3JJXjFtsRrom4JIbEIPuoKX6KVzWeszc20BoaIEX0QMvoXknEc7+Ge7wv7D2/AZhNdLEKfxk7pNMn+Lj7aOeZvzosdxaNAgt8CJW6ypMfRxuNnJK05VsDdWzNeqmcOceasoH9f6HJnMJZH0MFdditDQg3R70z9cTfn8Rk8e7+F3Zp/xj4sM8suxjoh8v42c8z5ih03ngqbu59ar7WHt8ERFLY4xvFf4x9pqiQ+bPo2BHEZ/+41Miv/kNxshm3I05DFt0NkOnnkVO6djer4eiewQbYcdH8cO/Xl3LjEtn0JBpMuGQHXixH4G8ftNvuObt/2VrcGJfWdqrCGE7RI2NyU95hLAdKL8/fVhEIoZhhys0NKR/UqTYf5zJvgdjVH/wYNsx9/naQmICAWhtTe3/2AouMY544CqWzbzmwBvYBSdk+nlnzKgDWsa++mvKge0F7qyo5M+1ddSbJvmGzpZwBA/g1TQE0GRZmDFZe55f+/eJpEtvm1HYdqwBVkoasXRDCEJSJunSU+RJ0JGYP7Uc5zgxf2pEYaot6eiovql2dIfUdnR0mGlsS6y/AUQTbNUBlxAEpYy3KQm2ODIk5HX60iMgKm1ZLaYnImX8OLE+qW2W2A6p7ZLa16l1TNdOdp9DWCa/d8pNjRVK7at0ZRK2wK2lsb4LrJR1wlKPk2ivO107aRKskICwQPNGsdwaI9hBLTlk6gGOGfQh/2/9KRRsK+GzVz4j/Kv/xRjdgLsxl9HLvsvYWd9TI7B9SYIDK6XkuWv2MuPSGTRnRTlkyta42JfNgVUo9p3XsGfJ2gz9z5NsLzqsz6xJ5EA7sWoZrT5AF4JtETvosyFs4Y05RKE0t3Wyg/cdyXSUJmlzpFJlTMCM3Zck5kuVh/ZOVmflmh2kd6S7M12d2dEd0rWjmeZcIibt7Uxtq3T1MFP+O4RksoyZcC+YTk93+7uzfuione3y27938nbVP2ltc8cX6+oidwqpzmqn2w+2153OFksAXgleiYWGlyBbGAJAo5mNpsm2VQiEQFhaLBOUTjpeOa99TcKsPGnStiVlyqVRH8ykMZoPhLCvhBCQFRN00jzY1026YzfQhD0zUMTOOcfelHyOvGObB3u1Y9nJcW9PBky1obvneqI/Nc05DvdCeR2Vna7MxL7rru0dye1rH3WnXXpCT3TV2Vt5F8KGnz3ab5xXgPnNAe6prOo3E7nUJK5eYG5JMXcnLC0RlLJ7Hp1C8WUi9YYt5diIBjuOhdwXzChB2lZEGBXdiiWTl9EiqpGxt4gRWy4gu3h0z8tU9AxPFlaePXJjRi1EbNFfkRADO/d3f+e7b29kb/SfQDngA3KxHc8bgTJsZ3Y0MC8mk5lwPAwYj713nC/2GpJwPBh4PKbHH9PtyPmB4UBhTGdmmuPRwN+BOqAVaADqY69WIJiQlno+XdoGYCgwHXglRWZ1wrkXY2XWY9/qN6bIprMlUcfUBP2pelfFjg8BSmKyTnkWtiO2L3VKZ/8jCXa8CKyP9YHTpv9M0ZnYNk6elk7KcXR1t4/WdKNdEvN3VMeOjldjX4vT0uhKbbt014yfcffP4ZvPzaZgUttEWpcVgp2xGJIQbY8DrdirQYNdLlullfAyY/LBWJ5oynkrQU80JhcU0KjZr10u2OmCXS6GVPmTBmr6GhVC0Eu89BJc8m4VrVekWRtTofiSkBvYQb3fHvkUVhRPNIA30gRoSAEhw48n0oyGoNWdA9Ik6M4mN7ADiaDBX84+hyR0wiGNS/gsewbjl67niYmFFG0ewprX15Dz3eWU5A5n6GFn4s3uXzNnv6osXAjvvLCJn/9gHa/cFmDat6cRGBRlytitzP3dk/zioWf72sQBwL4GW/UEgT2KGOpKUNHLZN4wm+bLrwXgmNZFvJ9xLOdab/DmkxtpudJO56Fi+GQH/PfNcPN/w/LpyUqmfdzxuR7wwgtwwQW9pi4JFULQB7z0Epx/PkAxXF7Ztwt9dknvOQ8HloFi51eHETVL2FI4g7E1a8kTYyitfY8frqtgBj+Jy0gsROzBzlL+h0fGFdEst2ARZcH4aykI1FDr7x2HUifKZ9kz8D3xIF888CjmO/MB+/H0+GE/oOjQ3l8GTLH/VFTALx4axWtvZHHrBHvadsTVyvRvXc3ylZv72LqBwsFcQ8wJs1AcbJp//yhMPAKOOJKg7gNgl1ZCy5Wngu9ByADmuiH7Schtgg9nQMQFe/Mhfy9oFugWuEx4+wQwTKjPgdwG+78jY2nJeSA5DWDLSLj8L3En+Jpr7LWP+8OCIcqB7SGmCdf8ahtc/g6cHwVxVF+b1AUDxSkcKHZ+ddhSOIORNctYX3gEJ3/xf/xsw6GMFpchRPpIpHxrPEev+wlvjv02C8ZfS25gB7Wx0VtEbFevHmBicJxYwv3nPMqb2WDJ2OM1AdL8Uj9YGpCUltr/123yISbZn29Lj/Dp2r5f41Kh6Hdc9UP4wWw+vsYecV3GoczKfpB3Rz6atH4yAC4LXCHwpdl7ObfJ/p/ZkvzfIV2exLRJn3PEpdezbPmHgL3U2KJF9tJgfY2Kge0hixZB1ZLh8MslUJ7ovKZZyV+hGOBsLjyCmTUamWI4tfKLDp1XgL18QRkzKRPHJYUeuKLRHjqvbc7pu3IGrxfPZuIckAkbGUizH6x2r0ji2GOhrCyETguabl83UrMwI+pmQ6FIh/HFo2ixUXdBlFnZj/aJHZ/N/ojD5k2HK/4EQ7dRkcbn7QvUCGwPqagAHngTjkmYldcLo0sKRX9FCIM/bbg8PmmqI2aIWxBCY/K6d3ivoJJWVw4aGq3uzJ5akHR0T+RafAJedb7oNYHVH7ZrUiSxe/cOGhunogNCexwAKSwMtyASUk6sQpHEUHA/N5uW6tjNHgZr62YjCw++ExvKgJVXLYerfgBA6cL+8XlVI7A9pLQUWDMFaiRojfYC7b5V9nutEbQG2qb9RW3nNu3xvrycaYPOUgcW7acXYp9PKi9VPgR6Q0o+k6SpiyKYci6mt91UxsT01Hom2od9Lt4u0bb8IggEE9qukfi0yPh7UvIl5I+Xm1hPx+5omvTEOpFynPoBtTqQS60/Kemp/ZQ4bdSy7RWp00MTZVLbsgM9SeUnylkpx87/zqajBsG9035pDfiiETzhRnICOxm9ZxVH1NrldDb66pzfIP/BG8zmysU/4Gf/OZaixnXkBnYzpmkXuHbZ/eraCZlLaZs+69gVoW26bRTnqYYR+59JAACfaKDlHxqWtOunaRofL1vBl3x+6oCjpqaGpqY9GCJh9QHN5IF14zny3AM3wbavuOBUeP5/4a7rk6dFXHAq3HkdXHha2/90cqm67ryu7byj+/nfteVLlUmXr7P0jmS7c/6CU2Hxs7DwL/aqeV3p6q7eRJnENkptw3T1S23TdG3YXRu7sqMn017S6SgphJnzZ9NSfS1F1ALwbeOfPB+4Fipn739hPURYcNEPzo/vYNbXqFUIeohp2tvtnTv0av60Yl6v6++Uijn2FVXyaPv05qmQuQJKU2yqnA1Sa5/ek/K6q/dg5d+XdqmYA83TAGmnQ1veytmw51zw7IIxP4QNj9nnx/ywva7K2dB4JGQvtWVS69KTdu9u/Z3ypdZezilfWPtkx8kflnH8m02EsfdhdJONhsHx4teMEed2mf8j636q+JRdLCJKKwAlHMVQvs5NV7/CF0VfdMsOKmdDxbVkFj1Ivl7D9oo7OUN7j+naKu6OXsspmx7k2i9OZfKQw9j43kbueP0Wanwu5s27j5NOOql7ZSgOKCtWrOCEfzzB9KMKufGpqUw8bSLVo3aw8+gfoemCPy4+jcbVzTyQ9aC9PXPA3ko4O7Pt/9pNUF5sv5zz5QkPv1LTOpJZu8l+X17cpt/RmVpGomxXep20xC2inW26GwOxrZLH22k5WfZ2yYNy7d226hqhqra93kDQ3p7a2QK6JQTDY1tGI2F3tb399OETErbgDiRsy5yiV9OgeBBUVMPOqmR7N+8Enzd9fVLzODJOnXTdtnF3jb2ldVNLwhbnHfRJZ3qTZAoAYW//nemz81Ttsbc4T9pKvRmGlsa2Gddgd5Wt10mrqEk4HtS+bTq7hpw8Qth6E9u8Kx0d6U3so8Q6vDpmNvdq13K38SCPmeexQ5byn4zvcnrOTGTltVD6YPrfgQPM8qkw9RPg7rth7txe16924krhYCyjtfrb95D7we0c+gns3dddN51tmFL/H2wdA4mO6ru/7dBZvq50Hqy276M+nrUATl88lFZzOwBFHI6PIoo4lKO0n3aZf731Mgv5CRFaMAkCthOcX3I5c2Y/0HHG1HpWxm40spaBdwNs+R0zxGecon/A+9ZUIgiGfzKYu8R4Nr2/ibte/xkfnD6NrLxiGv/77h63g6LnrFixgtu0v/Mf+R0ufr+Bu7PLqBq9jYqZ/8VbW05mXv2l3GE8yB2G/cNsSdCEvXSwEPaxZcYct4TziaSmdSTjbA6niWQZKe3jWIgulmxLd9I60uvYmZTGvk1HTacjFZFgK4BpJduWTk86vaaZPJPc0ZeoPzVP1ARjH2ef768t7cqOgm503J7d0RuNtl0/3bWvO+3QnTz7InNnZA66sLjd9Sg5re/TSBZrPWdz3Nht1OzphcGQ/WT51OFM/WSrfXAAnFi1jNbB5p57mPz87QDsLoegGyTjcYcFjZnDCLo3IBhFVvNWmjKHI9kUOzbYOryF095eTMluuOSpUTx78U52lrXwrzPKGVwxjuxmFyG3SdD9HwSn4A4LYBNh98i4nsbsCCe+9wEluyXfeTaH5y4KsmtwM/8+4+uUVryH4BSymg2aMqNJZSce23oh7JYdyiQfgzs8up0ttsy62Jf2vuhdhzssiLhH4gpvRmAvPJ/YdmH3SGATy47I59xXl+AJapz6WjGvnlFBxAvPfHsqN/5xNcUVkiufyOOZy0JsK2vi32cOZfyGyVhYhNwmYffG+I9KVrPO+jElnP36B5Ts9nHxU+U8c8kOdg9u5V9nmAi+zrmvLaFkt4cL/+rir98NUVnSwr/OPIbSil1UlpZxzmtLKN3t4Vt/Hcyz391IRanFwlnHkd3gSqpj2G0RclvAJjzhMbjDWtr2dYc3x9pBIGJf1VuGfc45r1dQtjODC58rjZfz5snHMni3l7BbxvNlNm+lOXM4rvBmwu6Radu7K1vsfjsbwXlsG/cqb55yDQjIoIhGttPINsZzIdCFDy3bJnINZRYL+DEABUxgyOcZ7M2uxR2+lz35q+PXVVbzONaPWcPZr+2guMLHJU9l8PQlrewufYQRK69n+ehryfCspRWoJQcXFgusGXZx43bx+4YQlw3LJ/cn34Gvn4Ln//ZSv7OJ3PKs3vi0K3rIWRn/ZHvTETxzzCgKK8PMjm7g7+uOZV7LpdxtPAjAXdE53GHMQ9faftCFAF0kO42J7x1HQBfJe2U4MiIhXdc616OnOyfa60glneO5r0+W9+VRtCObzqFM1ZNOb6oj1508rv3wGHrDFgCXa9/KSac3nY6u7OtOO3Qnz77ICGFfO6bUaMT+7tL1Jh6shG/FRt6BLr6AHaX0yuBHQW0+RdVvAvcAT8EddxyQUdh9QY3A9oR77oHbb09I8GHvCHNpO9GmzAqWT3+EaR9fRVZzaTw95A7hDrsRCCSSsDtM2L2X5dMfYdzn57Juwj+Y9vH3yGoeuk86PGEPdsygq9Pyu2NjT3B0OnVpq1P6MtLZkJq2u3g96yY8w/SP5+BvLqY5s5ns5uxO2qFzQu4QIXctK6Y/ytjPz2Ht5BeZsWQ2Wc1D2+ncm7eNVYf+OW5Lbd5WPjv0CaZ/PIfM5pKk/nNkOmsDIG2bp9Z5f+vWEySSf19/PSsLHsMizHi+wzHiLhbI/0cBEzhK+ymS2Fa1AnQJkdgOrhmxcFwpLYTQqLFW8VeOAyCfCZzKPHYufZsj3rs6bb1HbjiDTWNeTWpXT9jDzLf+zeKCoQDk0shNxlPcHr02nv/aKhcuKfhdSZjjH1rLcY+vY9jlx3HFn2cd0LZSdM2K5cvZNPQ6Xt5wHn/NONVOjHmojvN6e/RaTtCWcKy2gjtdB3+ESaHoD9wTmc3t0Wu51XiM+6I/BOA7mdOpXHMlC4ddyxHbHuTI7Y8zcdXXiXgrAAshDTIbhtOUuxmwkEIS1SUrD9vOoD0aefV5bB3WSiCjhSM/HoIrqgMaWfUjacrdjBSxuQ1SJ6t+JM05W9FMjdLKIzj6w59SUDccT9jZHnca3H1un4/AKge2J2hawu3+BOBVmjI9LDzuLnaUfwgICmpHU1uwgYjRSn3hRkavO52G7J2Ymj0hSbdccRlTi6JbLnIay9g47nVy9g6nIX9rPE/U1UrdoI0UVI+nsHpiUp5EHen0CgG1RZ+TXz0epEibpyuZ7pSTeiz1CHWDNjJ80/FsHbWAnNrhNBRsTWqHxDxOOyXWMbXt0smkK3tf7K0pWktt0Rdd2uf0QWd9kirj2Ju3ZzR1gzaSVzuaugI7T17dCDaOe528PaMxIr525exPX/dGvwHouoExKIsKFgOQy2guEK/iE4VxxxTg+eNM6hIHOCWctFxjRCVoCDbIf7BA/j+C1NkncYbWZLt6O23lXC95e0YjTFfcvoqhn/HHc29lU+a0eHEjxA62SHuJLk3aDnRpIMQIzUT/2M0PxHAuuz6/tz71iv3kk8VvsGvyfeS9E+L8vIeoymkbxrrbeJDbo9dyvLaEBdYMZomlLPD+sA+t7T53RubwrjmN4/VlvGMeiSEs3vHM5s7IHBZZU7EQbLHKaCCTHJoZIXaxVQ5muLab47Tl/MX8BqbUGKXtRMbGbKUU6MLiWG0FOhYmGne65iGxnRsLjTtiDr5IsAHgBH0ZJho6FnNdj3JPZDbzrSMAOE5bnqQvtR5OHkgepPtFZHbaPD1tt8TynDqcoC9jvnkECFjgsa8Bpw7HacvteiacS+SeTuxMjArryp47I3PQYu9Fit7jg4/tV/np6pxok5NXStBjK7zcEbs59xBiiPU4G7VrGb5nKVcsPrifjdmPLKe0YmrsaCMMPwW29P7mI8qBTeHgjMBeBjwGuKgo/YRHr5rWRUaFYuDhIQeBHp/AZSHZWgJvTW+/ZJU3CJe8raEBS6xfUssXhGliBwt7ZMOCcXMQ0mLhuGu69bz1dlq58M03GXHZD/CX9s5TBcW+Y5lRVr85j6oZz2AuzOZnxi9YOST5CYLjvDrvuxqFTRdfapG8tE7qcVrbUmSitI+ta3uWBbOCj7NdliIR1JOFQFJPDgAaJhY6bSt+OJqdUlKtdo47srztfMy1Rcb0iyQdxNI7yp+cLjABET+rYWEhUnTLuEy6PMn2Jx8n69U6yJNcF6ecZFLbMVGTsz5qYitoiHieZFu6trfNnrYy294LrBQbJQKZUEcBiFj5HZfj6E20TKYpI5cGAniJ4EnS1+cObNFlUPWXA1KOioE9mMydC/OWwe4n40mmiHaSQaEYuOQwEh9F1MovGC0kUsCiKenXW80Igx77wp0hbqGVWl6Qp/XYBk1aLBh/bdeCwI2Vbi6vziR3+ulE66rbtoJSHHSaqjcjrBCTtrj4b9dUVpZ74jtZOjjOq06UBdYMFlhHcHf0qrgjZMYch0RnRMYjxduO90Wmu3pJcTeSncU2rHh6qiPmOEOp6SLhfKp88nmZcr7zkafU/MnpifZLiLdBZ7pT83RFqt6O83RWl47aq+1cal6Z5palu/a2LzPR/va2SERK26Uvvz0dtXFbXuemyCnLYcSeZd3Q37s4m8QEMuuoq/wL/WWTbrUObE/Z+Qro6wGIGK08d9HZfWyQQtH7uPDTyFYqWUY+YxEIdCnICKeXr8uCrYUSiWQjr/C0PDoWQnDwCJaaRA5vJrukgS/3shz9n6yikbi8WdwfuJrfl1/EFcsCuDvoEjM+rqJh/9BrsbS2Y/ulpz3eF5nu6pVJMvu7Cbz6uVX0jBE1Szhu/cFfPuuVs79PwF/NN1/IY5qwV+fuD6hPVE8RUPPvsQCEPU1E9dY+NkjRrxmgflSUEBYmOYxgL+uRSLYWyeTY1xScMYNa+TllzOQCXsNN3n7b8O7Y2SwYfy3ecEOnckLCZZ98yjxp8rgexnCbncorDjyablA66Xii0ss3/r4OoQmC++sHKhRfQSZVvUdj3jjWjLmEogwvQ/w+dAQ5LheDfRn2Ey9nVm3s5RIa2YaLQR4PQ/w+8jxusl0ufLoel8/QdXJcLtxCwyW0JD1CgoGgquRTfv3/hrFryAsMBdx92hJtqBCCHhICJp0Kz5z4AkuPuoyoEUwOf+ko5Ik0aan/OztPJ3k60rcvtiQeQ8e6U/N0FCnfWR06s6UzmXRlpbZN4vv9abvOyumsHTqS6ax+6XSkpqWzv7OyU8tKLK8710P8VJQIAbIoY4a4ub3OFPKaYFhNWwjBRl7hOXlCfC3YNAV0aYuFxoiaJWwpnEFuYAf1/iHpVQkwIwa3uwOIL3eI/4CiIexhdsNOHpk8lkfG+9qFEHwp6Whh1+4s+Kpo4yvaXuNbN3Ns03Kmt6xmZutK3HtjJ8pLAIhaFoZmf4hMS2JZZnxiuaurdcdS8jtYUmJKiSuWHolE2RYI0iANvrnxdb5Wfgwip3+EY6lJXD1EAkcAhz1+B2M3PEgwoxFdGGgYhGnq9fL2j9SF3xKD0/dFpqflpnph6WT6knS29IZ97estcCFjW6L2bzQydINsI4tiTy7DfMXk6kVIolh6NXiqCeOOTfCwJ3kASFyIiBsXJogIwaiXylAttcEQgYigNtxEq5m4PW5ntPXBgnFz0GJbxqbGwuZFG6jTs+M/dHe7m5jrtrebbYgUkzPx0F5oD8X+svOz93lc0/jXLok0vXxSav/ADl2+h+3T9nUHGIXiy01hZC+P7LiHyaHen+3fEz4f9EOOm3ULOe7ef4SiJnEdZARwL3D6lbez8P4bmGSaoIWJujagRUuIer4A6UKYuQjLj4gOQhrV6NFSTPcWTGM3WrQIhEQzcxHRYizXLoTlR0qB5dmAkBlgZiOEiRRhRGQwiBBCRIi6t+BqnYopgmiWH4GO5doJZg7CygLXLiws0Jow3VvRQ2PRwiPQ8RDV9oIIYZilSCwsTOzl8zUkFgKNqGs7UgQR0osRGYqMORyWUYlm5oH0IEUIadRg6bXokTIwc5HuXZie9WiRUkyjEs3KRosMRouU4jg5AsN24oSFkB5MrR5NuhHSF5taoQOCiGctupmPFi1GYqFhILHiLyvjU0R4KLpZGLc78b+l70EzB4FoBZmBpTXZLpEIoZtFWKIVRBTNsp+HW1ojaK2IaIFtowggpB+JRGpNdrsCUmtGs/yARtS1GcuoxYiWQnQQQroQ6Jh6DUILIcw8pAgjRQtGdAgWUYSIYkkNjFosohjRMgSafS4+QcFubw0DkyBCSCLeTzGCU9BkBlK0xuyXaGY+9sxYLW07ENNkz2kO27JaBAsTy70FYfnQwqOw3Jux9Gqi3jWY7i1EfR+D0YTtoO7GZHfSZ8BNYiCs46SHwdWW7jWaGe71MDwnNvM8MhQjNAZX0+noobEYZglYHqTegLAyMfVahPSgW9lICcu1/6FRX8MJG4byi1GVvDnh+4D9JV8YrePE5iVcv+dv/GHQt5mfaU8Geq4VvD4Xp/7zbcov7Lv9wxVAqInyjBb8gTDBrAj5rSaX137Ot+rf5G/DT+Pj1okA1Bh51LjUkmcKxXfq3+jceY3Y0xDRJOjdGAiIaNguX+qjLudxlwAt0qmubdmnszn3PI6MSnL6QRyBGoHtBfY2VPDq0kUct24J4YxPka4tYOzn6GUnj3H3Kb/EXg8m3VMEZ5UP5wbKjKUl7vDhkLq+jOggX3dtTnwEHkmTN/F8qp0WyRN5nfOu2Hsn1NGVJm+i/sTyojhzOIgPiDrzPBKJJKRHY+87q7PTNh21f7pVYczYsZZQFwdB8u1mOlsjxL+H2vVRZ7oGGCYQwMsy32QGmfUcGtrYoexnRecx5gOT8gtnkz9x4sEzUpFMsBG57UOWv/wMOUMXdSj2XO4pPDDoooHpxDr70+7veYUiAefm/JSmxVxT+3c+847m9pJrOKzexf+uykM3C9HMQiy9Bkvfg6XVYen17fRoVi6amYdmDkIzCzst09HVEYsmFrC+vIArxuVS4uv9HxE1AnuQaQibfPTBExxV/xih3vjO7WmYj0j431EITOp3qE6bw9NZ+alXS2K+7pKoP5197VdJST5Ov8JJ5+c60g/JdeosZCjxXHc+NZ21TaJtifboHch0ZU9nafvTR10R0UHmU+/LwNK8RDUfQWMQISMPw2qJO+WuSAPFDXtxm01ITxVoHSxZsI/oQDZBTmz5uN25KPB6xsU0rW7kexNLOaqpFO3QbAj0l3CerzACtn00noyNVYw5YX1ake/UvwkwMJ1YTUMzIwgsLNH2odOkicsM4ok2EzQyieoeDDNMVHdjCQNNmhhmkKjuJTVw3tEjY5uGiFj4jHNsH8TWI5X2Eo6WMNrlsc+JJLsSdXSk1wnHSXs+RSbdsZBWh3niOhE4+/TqMmK3iRUFITA1V0IdTEzNhW6FMcwQIVdWO73OSqtSaO1t68Jep51MzR3X5ehJ1Kub4Xa2tesfp06p5aToTW0rJ29ZcCfloV2EDD+TW+zPyka9mKzgHkY0SHRzbNwZ1WKObG/QmS6JZOZq2F7Y09DC3kM5sD2kNWJRsvN8/E3DiHo+JeL9DEtrsGeS6C0gIthfRk6nJ3a+s9A0tH1pOUNwkPxlZtI27Jc6+8eibcgy9lghPlyZ6JkmlpGYL12saqIuEuTTzbbRYmlmynk9WU4zQe9kRnhEI3k4NXU40Sk/dQjW6PLRB5FYts6cuYiIyXTyUCLieMqJbZvYN4l9YqWkQXIfOItmJ/Z3atmJi2prCTJmQppF0jWhWV20hTMEm2qbM4TrLC0EYCDMXPRoKXpkGEZ0JK7goRjh8cyP7cAlpSQUbkZKC68nGxH7Us5rhMNW220UdX9BKOMDoq51mK4KpGhCak2gBen4ukpoMy3a+bUTtxbOan0GRsGq18aw6qXDCdb7OO66OmYdMhE8nSyboDhwPP4Y4tQpnPrTQ3nojAayvlZMiTf9SOx36t/EF23iv4u/T7WrAOjcEerwuBsy+6PXMMPolr2QkDdihyO1xpypksb1XLn4B500hELRNVPyc5lSkJuUdl7gA84LfABAa3Yt/ro5B9UmgcAVlRy7SoNDDmrRHaIc2B4iai1GVBUBZ0DLGX1tTr+mq8cT3XnE0RPdtlzPZXrrbvdAcSDb2aEy115Cy7QiLF5/D40tq8jx5lCcOQq/p5ziwkuoy3Kxo0AypFZghMdjhMfvd3mJj8n+NvIpTg8t6TLPmBM3MPHUEXjcM8gsdMdn5yr6gJotRMOHsdvrwZdbxufZQUo6GZA/u/lDJux8g8rWEM2RCGHTwrLHtQhGTTIMg6BpYkqJW9PQBIRMK37bk+dx49E1msJRgqaJLux9liJW4kRKyPd6kFLSEjUJmWY8f4au4zV0msIRPLpOxLKISoklJX7DwKVp1IfDZBg6uW43uhC0miaBSART08h1u5BASzTKIK+HulCYsGXhNwwC0SiWlHh1HYHA0ARm7DgQjeLWNCwpaTVN/IZBpsugMRyhORLFpdkL4Ht0DUPTCEZN/C6D5kgkdmsvyDB0QqZJyLQIWxYZuo4EgqaJFvPDNSEwLbvt9FiiaUl0TeAzDEwpCZkmQdPEkpDjdmEIQUM4gjuh7Gy3C0tKjJjNDeEwkZjeqGXh0XVClkWWy8Cr63akVuxzWO7PICol9aEIraaJWxPkez1UtwSJSokuBBHLIhg18eg6uiZojtjtE4i2bRjkM/T4jPmGcCQ+RKAJexkpE0mm4SLX46KqNUjEtPsy02XQHIliaPbMDyPWhwCGEHYdTRNDE2S7XASiUUKmPTDg1XVcmiAQiSIBn2HQErXfO32cilOOJuz2rGkNMcjroSVqX5+BaBRTSvI8bgKRCMuq96AJwbTCAiwpWVK1B6TBZK4gNzqrO5+6XkcgGFkJ4T0mDO1797HvLRjgyAKNzUWSEdV25yo6pjcfdeyv7t6S6c8cyHZ2dmR54wj7i/y9Db/mlQv/F4+RvC3o/O07WVrrYv7hVnxL2Z58Ppz6tOQ83aXzWqmNZ91/D+fwC4dSMr5/LPfylSbUBJecTeO2bIxdBWx6sJjnCnZx/MZXOs02JjebMbldq3cGSC0JwgLR2VOWxEH8dHLpHpokkrCnrCWJO4T9FTPmCAKYFuj7GIJrxZxN7WAuYVXQtUjUspCxDnClWwbKkrj2tbJpiERNdF2L1z/1uJ28aeKK3fBgmqBpuPSex3BpQnB0ifOd/k9Ce4t7NCCwv0gkW0qgbFD/WMRZRZT3FCFYdKhFWGv7cVcovqwIBB9OkARj/urPj7m+nfMKMC4vi6gZIeiF96fIXrm5a81+kXD2613KNWl57NkwjH/fGubx87bx6DdXsfy5qh6Xr9hPYk5QZnE9/7VhNb8rCTOjPhan2QvqRXxUsQvnFdpiwjuLT+/sUk2IM+/vzisQd15h351XsB2ng+q8dhND03AljLwmognRK84rgMvQk+qfetxOPuasujQNl8vVK85rKnpwPBmN5/e63q6QSCJGx9uH9wVqBLYXCHpg0WGSk1ao+wHFl5t6n2TVKNvtMK0I4/OL08qVZeUwPms3G1sK+WKoZPx2SXFDz34IMxrPx9V6CFHXDjt+NsYbJVupNzdxhNxJKQE2e6biL/BQcGgrG+6ZhYlgmrsZ6rZAqVoL9qATCSAtyfvztuMrMLjsLxv42rF+AFpxo4XDZGdlsCNcjks2kR+M2DHtIkK7JTS6ioVuF9+dstuHFu1GfHiih5voYqfOPUiMd4fkWPbE+Q3p8qbbxcRJT40F7+pz48g4dqTG4ifOaUgXj9+RTR3pTUxP1Zk6j8OZG5FuuZrU+RyJ/dKZXYnlpJt34MwtSM2T2G+JcxT0BH0d9Z0jk9jXqfanzgFJvT4S3a3E+RyJ8yCcPLEJG9KFZubaT9WsIvTwUDytx/TJU0KB4N1DLEIeiwyjf9zUKAe2l9hUKhmpQgkUX1Kcpwv/nNn2IzNjUJhCX0aHeaYWD2HD5laEEPzniJ6HEmhmIW6zEHfKZl7vlv6Tp8ZfxZ8330Jp6AuiQpKV7+OFmcN4I7eAu91NZLnd0FxlP85WE7kOLk1VIGDPpla+VTOfyeeuxNmQzUcY3BAOtVLMBjL2zu50ckpP47sPRny4QvFlQyLZXGzxh70/R6vZzs2HvdrXJgHKge09BCw61KLsHQ23JbuWT6tCdBqG4JxPlOtOWld698eujnR2tw7dke1KpisbOmoToMN22Ze6drc++9tW+1teZ3lh/0NdFk+04qEDphXh0MKiTuXLMl3849PvcfYhvyfodbFoiuS4Vd2zuTvXkcMDlScweuIOdnnLIfQFGgFePXsKb5wzmB/vreUHTXVUAJmFbrKGqDCfg0qoCQLVCCFYec9hrH3Swxm/GoO8K4MTWv7CtmgRu1cbVJ5+JXpzEVds7Tyur6fx3QcyPlyhOBh0+/t7X7/qOhlXCNDCt+vOYHPFKor8RYTNcNrQsYONcmB7SIYOphVG19wEPfDeYZJZK0V8H4PEhwPpjhPTnAuzozzO+cQLuDtpXelNZ0siibpTbUnN09GHK12+jnR0VXa6c+nydLed0tnfVZ26qk9HMt3V21Fad9uvq37sbh4n7bMRFqtH2mlRK8KsomYKfZ1PkPIYHp45+z5OeOpEhuYfhznpDiIuV9Lno6Oyu9s2ANKzh0sie3glag/r7XI38vI5gzn77zsY9sxmnqpvpbWhleOuK2fqx3uwqmrRty8hOuZksGJT4XU3mGGwTNB0+xja0iApXdv9GVbpISCjoBltx7EfAc/ihzF2LifwzQfAlZGcR9B5WU6aGUZEgm22xnQb694iOvIYW6+ZYD8J54fNAN3Vpsuy7UxXn7hd0VY8Hz9JaPrl4Mpob29KOXanxPSm2hUjY/o2PKMkCx/YSd0x5fzz+0dhZQ9mlr4agLrGUv6SP5N3co/kqr3bELGVQBJv0pzjzm4u9+XGOfV4f28kFYq+JiIjGAluXJgwQghcuDCFiY5OhAgm9nsXrvh7gEhsR5zE9MQ0gSBEiCeK/o9TymbytSE/4fgRx/cL5xVQO3H1lFA0xOSHZ5DlG8/Q3GlkZwzG7y7A58rHZXjRhIZEIKWFaYWxpIklo0hpIqXE0LwYupsJ1ZmcuCGXBeOaWV9srzEoYg9cJSZjq9wcvy6LSn+QkXU+Ph7STEV2iBM35PF5cQsTqnzMH9eIQOeEdX7WFrcyoSqDtUUBJlb5eHNMLeuL7R94IXQ0zUDHQDh/IhbTIwDZ5l0c+0UGh+3w8MnQIAvHNiGxGFfl5fh1WbwztpENJSFAYEmLCdUZnLAum/njmlhX3IppRTGttrVyxlVlcOrGQt4e14CG4MT1Ocwf18z64nDsB0HgbHkqEIypcnPCOj8LxrWwodheT9f+sxhb5eGEdZnMHxdoqxca46o8zFrn5/PiIBOqvCwYFwAkx6/z83lxiMm7vSBgdWmQCVUe5o8LsKk4CgLGVLqYtc7PwnEBNpbY8UxjKt0cty6DheNb2VgcscuX9nI+Y6rczFrnY8G4AALBrHW+hLy2Rceu83LYdjefDA2yaGwrCPtaGFvlZtY6PwvGBdhYHImvnQoCCxNTRrGkFZswIIiaQcZUujl1YyFvja1DQ+PE9Tm8Pmo3nxcGMHQPujAQQgdhbxerCR0t9uU2tsrNyat9uKRgxdAgi8a12u0t29rU6QOLKNKKYsoIUTOIaQVAtuLRWijx6UwvGcmxQ6d2+zOysXYjRzx+BFL4GVlwTLvPidvlxxAunO1zx1S5OH6dn3fGNfJFUSsAuuYm05MHwMhdghM+cT4dgvuOXkE0UsZpTc8xMvokz+eezN3F1/H56kweKAoTiTZw1fqNDBrto3CUH7M6G4RMCOmTWI0ZWEE3whsBzUIIEK4oSIEVNpAhw34f8GA1ZmA2+NBzWtCyY9v4+sJ2XkCGDIQnigy67PWghUR4I0npVsD+AdB84Zgt0paVAqsl5iTG0qxmL1giXiZawle2JdAyg/G4Tj0/gJBghVyIjDDCEkTr/GgZEawWN1az15YHW29MR7r6aDmtCOx2Ei4TGdaRCDRXNG3bWS1uO19uAM1tIlwm7qIWLNPi4W98xt9PGcaOqUVsmlbAXRXPcFH987zhOYrrR/6M8U3rmVbdwh8+/0a3rqmObma6kukq3/7k6ekTrs70wv4/MTlQdh3McvuqDp3Rk5sl5xiSb9I6e8KXyltTLTYPlry4fDYPnHozbqPtprLIX0R5dvm+Vagfsa/+mnJge4EdDTuoaamhsrmSumAdtS21NIYa4+dzPDlIJPWt9WiaRo4nh3xffpJcjieH0fmjKc5smxTTk4vRsakj0unenzzp8jvtkEq+N5/izOL9rldn9lU2VyIQSe1X2VzJxr0baQw1YlkWWupyK5ZFXkYe+b78uG2JHKgvg77om76mO9eGM5KW2g8A6+v2sjV0WPzYG4Lvvq1hSPjjhNX8bXAtpzcu4qq9L7MkYzL3F38vPj2iXstlt9ve1UmTEkNCVBMYlsQtoUUDK3YD4ZbgjPeZgCElHiAgBJawfUcDCVLikhIt5tqENACBx5IgNFpiTqbPlIRi09U9lkVA122HSEr8UhISEI3dpNjrQYEhwSMhJEBIiRSCqDP6KsFtWbTEZlnr0ordcGqYmoYhJS4rTFhzExG2k+83JSHNLqc0bDE4YvGpT8cUAonAkAAWHgkTAhGE5mKHS9KsC1o1gRkrW5eSwohFo64R0uz2kaLtSaUWm7/iTIVxiN8rSImpa3hMuLX6IS6qf4M/DLqIxwadT0i4+On6TG5en0erS/L+FHuCzdc/swtfN0Qyerfgg0kWmwfbekfuFsxcI9g4uP25RBw553ziMSSf6w5O/qVjLWau1TDSzCnbn6dd++OU76/ermS+Kvbuj95UuiPTHTor23FytxXBG0faN6snlTQxvXREL5Tcf1AObAoHw4FVKBQHloawycNr9pIYqDVyt2DmakE060HCuf/XYd4HBn2HBwov6n2jeuuX6yvIAzt/yalNH3Jn8VU8m38GQ0KCD5fmUZnh463p/WeZnq5IdY57U6/jvL93yL7rPlB2Hcxy+6oOndGVTZ3dLDnHif3a1Q2UNwTfnW/fJEV1ePaEtnkIl4/NodTf2f7nAw/lwKagHFiF4svByuo6Xt8ZTQi3ACQ07/qIlwsiFEcCPLJrLgAXD/0FAc0HQI2RR40rvy9M7lv6mYNdGNlLYbQOkPzvrt8wIrKb/y68jE+9h/H8mixkII9/zhwW/4FWKBTpnWbTCjN7Ql6nq8AMRJQDm4JyYBWKLw+vblzGn1d/yNShFyGEIK8BaiIvkNmyhTPrQwRc/8FPmFbsLTdt/83ZhLTN8bVXdGxbZDyEC5AYWOhxedBj6zWK+INxgbPSo4mOHTOsERUGYWEgEQSFi4DuI8MK4bFCWEJHw8IrQyDBQuCSUVzY202KuEX2+ygGFoKQcBHSPJgIdCw7j4yiSxMNCx2JhYaGRUgY9ntpEdHcRIWGLi1c0kSPleXIOqtXypjtTo0EkjA6ltARWEghsKTAhSQkdDQp0YRESnDFbDAwY4EfTuy6FQvdsNNErBwAF1bns4abLuDFI2+xW0NKQuHmFIHEnyotJV7fOU4KXkhJSz3uqd5UGStZplt6rX2U6Qu9Ik2de9teicedmXxzmkLEjGBGQ7St39pf2rf3bZFILGlhyjChaIDWSB3NoRoaghXUNq3l4dPnMqVoZEdNNWDZV39tQKxC8NBDD/E///M/VFRUMGnSJH73u99x7LHH9rVZCoXiIHPm6CMYl5fH2S9ciNsYxHH6Odwc2klL9gvgAn9MLiN1Afx2kZmQuHB6Zmzmbdck6rCSkxNPdbLWftfE9lGXrd3WkynbJktitfSk8LZ6yC7S9llh56zKEgyrhEf33ktt82qWff/fSbOdD0QceE90puZNjLkH4nMdHEzT7ky9g92Z8r35TCmegpSyQ70NwYZ4PGRVoIrWSCs+w0dxZnE8hjzbmx2P75dIdjTsIBAJkOnKJNub3WabPx/TNCn0F6aNO0+sf2IMe2IdHZy6dlRHZ75H3C4h280TyTYGk+keRIEvn7yMfIr9xVQ1V7Jh70aawo1oegTDE4zrW1O9hmAkSIYrIz6/oTnczM6GnTSHmsnyZuE1vAgEGa4MWiItBCNBPC4PhRmF+D1+LMuiJdpCbUttXJdX9yI0QW1LLc2hZjyGhxxvTjzdZ/iQQuJ3+fEZPlpNe6Kp076JfZTtyWZk/ki7/mG7vnUtdbSarfGyWyOtSEsiNEFLpAVJm+7izGLyvNkMz8whvyiffO9kphRf1K/nOxxM+v0I7N/+9jcuvfRSHnroIWbOnMkjjzzC448/ztq1axk6dGiX+dUIrELx5cP5QV141+85aeqNvJP9N/ZmNzIsuIux4R2UWu0niin6ljAQxENIuAhqXmqMXPZouWzxDqUp4qMwfBYZI4Yw853fMnrODepHWqH4ivGlCyGYMWMGU6dO5eGHH46nTZgwgXPPPZf777+/y/zKgVUovrz8e/nnPGR5ed1oIi+wizp/WUKsZTJ50UaGhncjgEY9k9JwNSMiu2KP+sMIoF7PokX3kmEFadG8VOsFCCFp0vw06plkmc1kWwGaND9+s4WSaC0ZMkhRpJZcsxF37BF/hhVECGgVXqJCJywMTGE/8IoIF9VGHnVGDgAtwh4vzrTskZw8s4FB0Tp8VisZVggDkyg6Ic1DRBg0aT5qjAIk2LbLMJ6EEVif1YLPCtKqeQloPsLCHa9Xi8igQfORLVvwW60gIUMGyY024ZFhXDISt9ElI/GVHDwyEg+diAgXIeEiLNwENTe1Rg7VegGZsgUhoVnPiLeXQ52exXrv8LSxyHmBndT5yzkrlMX16z/i5MsOwIQ7hULR7/lShRCEw2GWL1/OT3/606T0U045hcWLF6fNEwqFCIVC8ePGxsa0cgqFYuCTk+UlHJAMisIefxkANa78DidtfcDhB9M8RTeo85dTErZo8UiGnfXNvjZHoVAMEPrRHNX27NmzB9M0KS5Ojs8pLi6msrIybZ7777+fnJyc+GvIkCEHw1SFQtEHjC8vYZbpIUt3kRmFoS06Q1o0ckzItiRlUXA7oaoSROI2z/F0mRLvKdPLpx53Rrt5QrLtv/NKkRfpHoZZiXG2st17IeN7GLQvt5sP17pVp3S6pLRtjrVfXE9CWmJssG7B4IhgKCY5lkV2WDCkRWdIi06G28Msy4vfCLUvR6FQKNLQr0dgHVJnJkopO5yt+LOf/YybbropftzY2KicWIXiS0qhL4MLRkgy12+hvh6u/vgIXLHVBfScFoySBu4bHMKdEeaO7EbuDGXyruniBCPMO1EP26XGJVqI6/Z4uLvIYKmEU7RWPrR0IlIjKAyqLZPvu1qY6w7E85tSY0vURaNukSkEI0WUsHCx0wJDmpzd4MHKM/kHEgOTIl1HANMNwf2uem6L5PCvsEmxpjPdsGcx51uteITJ21EPn1huxuvg1iwiQmOaYX/frYpE2CINLtOCvBf0EEbj2LBkiVvickcJRVxs1wUjTIsFmbXcg4/HIz5GiwgnGSHuDWcCkqNElKMCOs3ZOktMgSdsscsl2YWOCfiAqVoYQ0gsCTN1k7ctL1+YkCcshgqLKS4Xv3bVArBVz+fpliAeYTLXHWjXT/eE/YRbXdxa6SK6J4vIrrYR8nnD/o05ysNxQ8ZQltX9Hd4UCsVXm34dAxsOh/H5fLzwwgt885ttj5ZuuOEGVq5cybvvvtulDhUDq1B8dQivCRN4vhb02PaKVhQ0+z5dy2nFKGloG7K0BFiavXVqXgDhBHxKgZQCq9mD8EbQ3FGEYYEmEUbsvW6BqWEFXQjdQkZ1ZES3VxsyTGRER7jsGdkyYjvUwrCQUXu5HC0jDEhkpP0YgnCZyKiGiNkpXKYdfKpbEG17aCajmq3T1MAScRskoLnMuD2aNxyXRTijpCJuHwLQ7PrIqIaMGvZyXwEP0hLxLXGFL4xAYoVc8baTWBj5LaCB5gkjTQ2rMQMZciEtYW/ba0WRuLAafAl9YreJR3yKb+4JvdDzCoVioPOlioF1u91MmzaNt956K8mBfeuttzjnnHP60DKFQtEfcU9y476rtMPz4TVFBF4JQBSM0QZmhYnvNB9ICLwaQCDwfcOHe6Kb8JowLW+04J7sJvRxKH5OSuLp4dXh+H/faXa+ljdaCC0NgQ7CsPMQy+OUlZi/XdonbTr1Up3opiieIz34TvHZDnrMTvdhyeXa9bPPO8tvCd0u3xOrT1LeZcn6kdh2u8Az1UN4fbJtieWk0vJGC63vhmw7z/alafdwBzqU86pQKPaPfj0CC23LaM2bN4+jjz6aRx99lMcee4w1a9YwbNiwLvOrEViFQqFQKBSK/s2XagQW4Nvf/ja1tbXcfffdVFRUMHnyZF577bVuOa8KhUKhUCgUii8f/X4EtqeoEViFQqFQKBSK/s2++mv9ehkthUKhUCgUCoUiFeXAKhQKhUKhUCgGFMqBVSgUCoVCoVAMKJQDq1AoFAqFQqEYUCgHVqFQKBQKhUIxoFAOrEKhUCgUCoViQKEcWIVCoVAoFArFgEI5sAqFQqFQKBSKAYVyYBUKhUKhUCgUAwrlwCoUCoVCoVAoBhTKgVUoFAqFQqFQDCiUA6tQKBQKhUKhGFAoB1ahUCgUCoVCMaBQDqxCoVAoFAqFYkChHFiFQqFQKBQKxYBCObAKhUKhUCgUigGFcmAVCoVCoVAoFAMKo68NONBIKQFobGzsY0sUCoVCoVAoFOlw/DTHb+uKL70D29TUBMCQIUP62BKFQqFQKBQKRWc0NTWRk5PTpZyQ3XV1ByiWZbF7926ysrIQQhzw8hobGxkyZAg7duwgOzv7gJen6H1UHw58VB8OfFQfDnxUHw5sDnb/SSlpampi8ODBaFrXEa5f+hFYTdMoLy8/6OVmZ2erD+wAR/XhwEf14cBH9eHAR/XhwOZg9l93Rl4d1CQuhUKhUCgUCsWAQjmwCoVCoVAoFIoBhXJgexmPx8Mdd9yBx+Ppa1MU+4nqw4GP6sOBj+rDgY/qw4FNf++/L/0kLoVCoVAoFArFlws1AqtQKBQKhUKhGFAoB1ahUCgUCoVCMaBQDqxCoVAoFAqFYkChHFiFQqFQKBQKxYBCObC9zEMPPcSIESPwer1MmzaNRYsW9bVJCuD+++/niCOOICsri6KiIs4991zWrVuXJCOl5M4772Tw4MFkZGQwa9Ys1qxZkyQTCoW4/vrrGTRoEH6/n7PPPpudO3cezKoosPtTCMGNN94YT1P91//ZtWsXl1xyCQUFBfh8Pg477DCWL18eP6/6sH8TjUb5+c9/zogRI8jIyGDkyJHcfffdWJYVl1F92L947733OOussxg8eDBCCP7xj38kne+t/qqrq+PSSy8lJyeHnJwcLr30Uurr6w9s5aSi13juueeky+WSjz32mFy7dq284YYbpN/vl9u2betr077ynHrqqfKJJ56Qq1evlitXrpRnnnmmHDp0qGxubo7L/PKXv5RZWVnyxRdflKtWrZLf/va3ZWlpqWxsbIzLzJkzR5aVlcm33npLrlixQh5//PHy0EMPldFotC+q9ZVk6dKlcvjw4fKQQw6RN9xwQzxd9V//Zu/evXLYsGHyiiuukEuWLJFbtmyRb7/9tty4cWNcRvVh/+YXv/iFLCgokP/+97/lli1b5AsvvCAzMzPl7373u7iM6sP+xWuvvSZvu+02+eKLL0pAvvzyy0nne6u/TjvtNDl58mS5ePFiuXjxYjl58mT5jW9844DWTTmwvciRRx4p58yZk5Q2fvx4+dOf/rSPLFJ0RHV1tQTku+++K6WU0rIsWVJSIn/5y1/GZYLBoMzJyZHz5s2TUkpZX18vXS6XfO655+Iyu3btkpqmyf/85z8HtwJfUZqamuSYMWPkW2+9JY877ri4A6v6r/9zyy23yGOOOabD86oP+z9nnnmm/N73vpeUdt5558lLLrlESqn6sL+T6sD2Vn+tXbtWAvKjjz6Ky3z44YcSkF988cUBq48KIeglwuEwy5cv55RTTklKP+WUU1i8eHEfWaXoiIaGBgDy8/MB2LJlC5WVlUn95/F4OO644+L9t3z5ciKRSJLM4MGDmTx5surjg8S1117LmWeeyUknnZSUrvqv//PKK68wffp0LrzwQoqKijj88MN57LHH4udVH/Z/jjnmGN555x3Wr18PwKeffsr777/PGWecAag+HGj0Vn99+OGH5OTkMGPGjLjMUUcdRU5OzgHtU+OAaf6KsWfPHkzTpLi4OCm9uLiYysrKPrJKkQ4pJTfddBPHHHMMkydPBoj3Ubr+27ZtW1zG7XaTl5fXTkb18YHnueeeY8WKFSxbtqzdOdV//Z/Nmzfz8MMPc9NNN3HrrbeydOlSfvSjH+HxeLjssstUHw4AbrnlFhoaGhg/fjy6rmOaJvfeey8XXXQRoD6HA43e6q/KykqKiora6S8qKjqgfaoc2F5GCJF0LKVsl6boW6677jo+++wz3n///Xbn9qf/VB8feHbs2MENN9zAm2++idfr7VBO9V//xbIspk+fzn333QfA4Ycfzpo1a3j44Ye57LLL4nKqD/svf/vb33j66ad59tlnmTRpEitXruTGG29k8ODBXH755XE51YcDi97or3TyB7pPVQhBLzFo0CB0XW93t1FdXd3u7kbRd1x//fW88sorLFiwgPLy8nh6SUkJQKf9V1JSQjgcpq6urkMZxYFh+fLlVFdXM23aNAzDwDAM3n33Xf7whz9gGEa8/VX/9V9KS0uZOHFiUtqECRPYvn07oD6DA4Gf/OQn/PSnP+U73/kOU6ZM4dJLL+W//uu/uP/++wHVhwON3uqvkpISqqqq2umvqak5oH2qHNhewu12M23aNN56662k9Lfeeouvfe1rfWSVwkFKyXXXXcdLL73E/PnzGTFiRNL5ESNGUFJSktR/4XCYd999N95/06ZNw+VyJclUVFSwevVq1ccHmBNPPJFVq1axcuXK+Gv69OlcfPHFrFy5kpEjR6r+6+fMnDmz3dJ169evZ9iwYYD6DA4EWlpa0LRkt0HX9fgyWqoPBxa91V9HH300DQ0NLF26NC6zZMkSGhoaDmyfHrDpYV9BnGW0/vSnP8m1a9fKG2+8Ufr9frl169a+Nu0rz9VXXy1zcnLkwoULZUVFRfzV0tISl/nlL38pc3Jy5EsvvSRXrVolL7roorTLiZSXl8u3335brlixQp5wwglq+Zc+InEVAilV//V3li5dKg3DkPfee6/csGGDfOaZZ6TP55NPP/10XEb1Yf/m8ssvl2VlZfFltF566SU5aNAgefPNN8dlVB/2L5qamuQnn3wiP/nkEwnI3/72t/KTTz6JL+/ZW/112mmnyUMOOUR++OGH8sMPP5RTpkxRy2gNNB588EE5bNgw6Xa75dSpU+PLNCn6FiDt64knnojLWJYl77jjDllSUiI9Ho/8+te/LletWpWkp7W1VV533XUyPz9fZmRkyG984xty+/btB7k2CinbO7Cq//o///rXv+TkyZOlx+OR48ePl48++mjSedWH/ZvGxkZ5ww03yKFDh0qv1ytHjhwpb7vtNhkKheIyqg/7FwsWLEj723f55ZdLKXuvv2pra+XFF18ss7KyZFZWlrz44otlXV3dAa2bkFLKAze+q1AoFAqFQqFQ9C4qBlahUCgUCoVCMaBQDqxCoVAoFAqFYkChHFiFQqFQKBQKxYBCObAKhUKhUCgUigGFcmAVCoVCoVAoFAMK5cAqFAqFQqFQKAYUyoFVKBQKhUKhUAwolAOrUCgUCoVCoRhQKAdWoVAoFAqFQjGgUA6sQqFQHASuuOIKhBDtXhs3buxr0xQKhWLAYfS1AQqFQvFV4bTTTuOJJ55ISissLEw6DofDuN3ug2mWQqFQDDjUCKxCoVAcJDweDyUlJUmvE088keuuu46bbrqJQYMGcfLJJwPw29/+lilTpuD3+xkyZAjXXHMNzc3NcV1//vOfyc3N5d///jfjxo3D5/NxwQUXEAgEePLJJxk+fDh5eXlcf/31mKYZzxcOh7n55pspKyvD7/czY8YMFi5ceLCbQqFQKHqEGoFVKBSKPubJJ5/k6quv5oMPPkBKCYCmafzhD39g+PDhbNmyhWuuuYabb76Zhx56KJ6vpaWFP/zhDzz33HM0NTVx3nnncd5555Gbm8trr73G5s2bOf/88znmmGP49re/DcCVV17J1q1bee655xg8eDAvv/wyp512GqtWrWLMmDF9Un+FQqHYV4R0vi0VCoVCccC44oorePrpp/F6vfG0008/nZqaGhoaGvjkk086zf/CCy9w9dVXs2fPHsAegb3yyivZuHEjo0aNAmDOnDk89dRTVFVVkZmZCdhhC8OHD2fevHls2rSJMWPGsHPnTgYPHhzXfdJJJ3HkkUdy33339Xa1FQqF4oCgRmAVCoXiIHH88cfz8MMPx4/9fj8XXXQR06dPbye7YMEC7rvvPtauXUtjYyPRaJRgMEggEMDv9wPg8/nizitAcXExw4cPjzuvTlp1dTUAK1asQErJ2LFjk8oKhUIUFBT0al0VCoXiQKIcWIVCoThI+P1+Ro8enTY9kW3btnHGGWcwZ84c7rnnHvLz83n//ff5/ve/TyQSicu5XK6kfEKItGmWZQFgWRa6rrN8+XJ0XU+SS3R6FQqFor+jHFiFQqHoZ3z88cdEo1F+85vfoGn2XNvnn3++x3oPP/xwTNOkurqaY489tsf6FAqFoq9QqxAoFApFP2PUqFFEo1EeeOABNm/ezFNPPcW8efN6rHfs2LFcfPHFXHbZZbz00kts2bKFZcuW8atf/YrXXnutFyxXKBSKg4NyYBUKhaKfcdhhh/Hb3/6WX/3qV0yePJlnnnmG+++/v1d0P/HEE1x22WX8+Mc/Zty4cZx99tksWbKEIUOG9Ip+hUKhOBioVQgUCoVCoVAoFAMKNQKrUCgUCoVCoRhQKAdWoVAoFAqFQjGgUA6sQqFQKBQKhWJAoRxYhUKhUCgUCsWAQjmwCoVCoVAoFIoBhXJgFQqFQqFQKBQDCuXAKhQKhUKhUCgGFMqBVSgUCoVCoVAMKJQDq1AoFAqFQqEYUCgHVqFQKBQKhUIxoFAOrEKhUCgUCoViQPH/AasTs39XbBo0AAAAAElFTkSuQmCC", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ring_avg = None \n", + "if run_t_ROI_Inten:\n", + " times_roi, mean_int_sets = cal_each_ring_mean_intensityc(FD, roi_mask, timeperframe = None, multi_cor= False )\n", + " mean_int_setsF = np.zeros( [FD.end, mean_int_sets.shape[1] ] )\n", + " mean_int_setsF[FD.beg:FD.end] =mean_int_sets\n", + " plot_each_ring_mean_intensityc( times_roi, mean_int_sets, uid = uidstr, save=True, path=data_dir )\n", + " roi_avg = np.average( mean_int_sets, axis=0)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:53:59.909109", + "exception": false, + "start_time": "2023-06-20T08:53:59.909084", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Analysis for mass center of reflective beam center" + ] + }, + { + "cell_type": "code", + "execution_count": 284, + "metadata": { + "papermill": { + "duration": 0.076743, + "end_time": "2023-06-20T08:54:00.072146", + "exception": false, + "start_time": "2023-06-20T08:53:59.995403", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_get_mass_center:\n", + " cx, cy = get_mass_center_one_roi(FD, roi_mask, roi_ind=25)\n", + " fig,ax=plt.subplots(2)\n", + " plot1D( cx, m='o', c='b',ax=ax[0], legend='mass center-refl_X', \n", + " ylim=[940, 960], ylabel='posX (pixel)')\n", + " plot1D( cy, m='s', c='r',ax=ax[1], legend='mass center-refl_Y', \n", + " ylim=[1540, 1544], xlabel='frames',ylabel='posY (pixel)')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:54:00.077918", + "exception": false, + "start_time": "2023-06-20T08:54:00.077893", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## One time Correlation\n", + "\n", + "Note : Enter the number of buffers for Muliti tau one time correlation\n", + "number of buffers has to be even. More details in https://github.com/scikit-beam/scikit-beam/blob/master/skbeam/core/correlation.py" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.8e-05, + "end_time": "2023-06-20T08:54:00.154143", + "exception": false, + "start_time": "2023-06-20T08:54:00.154115", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### if define another good_series" + ] + }, + { + "cell_type": "code", + "execution_count": 285, + "metadata": { + "papermill": { + "duration": 0.076908, + "end_time": "2023-06-20T08:54:00.306452", + "exception": false, + "start_time": "2023-06-20T08:54:00.229544", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "good_start_g2 = FD.beg\n", + "good_end_g2 = FD.end\n", + "define_good_series = False\n", + "hdf5_name_extension=''\n", + "if 'rstop' in locals() or 'rstart' in locals():\n", + " define_good_series = True\n", + "if define_good_series:\n", + " if 'rstart' in locals():\n", + " good_start_g2 = rstart\n", + " if 'rstop' in locals():\n", + " good_end_g2 = rstop\n", + " hdf5_name_extension = '_%s_%s'%(good_start_g2,good_end_g2)\n", + " FD = Multifile(filename, beg = good_start_g2, end = good_end_g2) #end=1000)\n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( uid_ )" + ] + }, + { + "cell_type": "code", + "execution_count": 286, + "metadata": { + "papermill": { + "duration": 0.295086, + "end_time": "2023-06-20T08:54:00.604436", + "exception": false, + "start_time": "2023-06-20T08:54:00.309350", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Using smoothed image by SavitzkyGolay filter in the normalization of G2.\n", + "Using frame total intensity for intensity normalization in g2 calculation.\n" + ] + } + ], + "source": [ + "if use_sqnorm:#for transmision SAXS\n", + " norm = get_pixelist_interp_iq( qp_saxs, iq_saxs, roi_mask, setup_pargs['center'])\n", + " print('Using circular average in the normalization of G2 for SAXS scattering.')\n", + "elif use_SG:#for Gi-SAXS or WAXS\n", + " avg_imgf = sgolay2d( avg_img, window_size= 11, order= 5) * mask\n", + " norm=np.ravel(avg_imgf)[pixelist] \n", + " print('Using smoothed image by SavitzkyGolay filter in the normalization of G2.') \n", + "elif use_SG_bin_frames:#for Gi-SAXS or WAXS\n", + " avg_imgf = sgolay2d( avg_img, window_size= 11, order= 5) * mask\n", + " norm_avg=np.ravel(avg_imgf)[pixelist] \n", + " #print('Using smoothed image by SavitzkyGolay filter in the normalization of G2.')\n", + " bins_number = 1 \n", + " norm = get_SG_norm( FD, pixelist, bins=bins_number, mask=mask, window_size= 11, order=5 ) \n", + " print('Using smoothed bined: %s frames by SavitzkyGolay filter in the normalization of G2.'%bins_number) \n", + "else: \n", + " norm= None\n", + " print('Using simple (average) normalization of G2.') \n", + "\n", + "if use_imgsum_norm:\n", + " imgsum_ = imgsum\n", + " print('Using frame total intensity for intensity normalization in g2 calculation.') \n", + "else:\n", + " imgsum_ = None \n", + "import time" + ] + }, + { + "cell_type": "code", + "execution_count": 287, + "metadata": { + "papermill": { + "duration": 76.981197, + "end_time": "2023-06-20T08:55:17.588517", + "exception": false, + "start_time": "2023-06-20T08:54:00.607320", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "In this g2 calculation, the buf and lev number are: 8--9--\n", + "29 Bad frames involved and will be discarded!\n", + "971 frames will be processed...\n", + "Starting assign the tasks...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 20/20 [00:00<00:00, 40.53it/s]\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Starting running the tasks...\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 20/20 [00:06<00:00, 3.05it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "G2 calculation DONE!\n", + "Total time: 8.069 sec\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "if run_one_time: \n", + " t0 = time.time() \n", + " if cal_g2_error: \n", + " g2,lag_steps,g2_err = cal_g2p(FD,roi_mask,bad_frame_list,good_start, num_buf = 8,\n", + " num_lev= None,imgsum= imgsum_, norm=norm, cal_error= True )\n", + " else: \n", + " g2,lag_steps = cal_g2p(FD,roi_mask,bad_frame_list,good_start, num_buf = 8,\n", + " num_lev= None,imgsum= imgsum_, norm=norm, cal_error= False )\n", + "\n", + " run_time(t0)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 288, + "metadata": { + "papermill": { + "duration": 0.051688, + "end_time": "2023-06-20T08:55:17.642066", + "exception": false, + "start_time": "2023-06-20T08:55:17.590378", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The correlation function is saved in /nsls2/data/chx/proposals/2025-3/pass-317286/Results/0ae234d7-fb12-4f03-8cdb-d64561aa93f0/ with filename as uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_fra_0_1000_g2.csv\n" + ] + } + ], + "source": [ + "if run_one_time:\n", + " \n", + " taus = lag_steps * timeperframe \n", + " try:\n", + " g2_pds = save_g2_general( g2, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0],\n", + " qz = np.array( list( qval_dict.values() ) )[:g2.shape[1],1],\n", + " uid=uid_+'_g2.csv', path= data_dir, return_res=True )\n", + " except:\n", + " g2_pds = save_g2_general( g2, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0], \n", + " uid=uid_+'_'+q_mask_name+'_g2.csv', path= data_dir, return_res=True ) \n", + " if cal_g2_error: \n", + " try:\n", + " g2_err_pds = save_g2_general( g2_err, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0],\n", + " qz = np.array( list( qval_dict.values() ) )[:g2.shape[1],1],\n", + " uid=uid_+'_g2_err.csv', path= data_dir, return_res=True )\n", + " except:\n", + " g2_err_pds = save_g2_general( g2_err, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0], \n", + " uid=uid_+'_'+q_mask_name+'_g2_err.csv', path= data_dir, return_res=True ) \n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.3e-05, + "end_time": "2023-06-20T08:55:17.707341", + "exception": false, + "start_time": "2023-06-20T08:55:17.707318", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Fit g2" + ] + }, + { + "cell_type": "code", + "execution_count": 289, + "metadata": { + "papermill": { + "duration": 0.163419, + "end_time": "2023-06-20T08:55:17.958540", + "exception": false, + "start_time": "2023-06-20T08:55:17.795121", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The g2 fitting parameters are saved in /nsls2/data/chx/proposals/2025-3/pass-317286/Results/0ae234d7-fb12-4f03-8cdb-d64561aa93f0/uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_fra_0_1000__g2_fit_paras.csv\n" + ] + } + ], + "source": [ + "if run_one_time:\n", + " try:\n", + " g2_fit_result, taus_fit, g2_fit = get_g2_fit_general( g2, taus, \n", + " function = fit_g2_func, vlim=[0.95, 1.05], fit_range= None, \n", + " fit_variables={'baseline':False, 'beta': True, 'alpha':True,'relaxation_rate':True,}, \n", + " guess_values={'baseline':1.0,'beta': 0.2,'alpha':1.0,'relaxation_rate':1e-3},\n", + " guess_limits = dict( baseline =[.9, 2], alpha=[0, 2],\n", + " beta = [0.01, 0.4], relaxation_rate= [1e-7, 1e7]) ,) \n", + " g2_fit_paras = save_g2_fit_para_tocsv(g2_fit_result, filename= uid_ +'_'+q_mask_name +'_g2_fit_paras.csv', path=data_dir ) \n", + " g2_fit_failed = False\n", + " except:\n", + " g2_fit_failed = True\n", + " from pandas import DataFrame # need to make up a fit result, otherwise writing the pdf report becomes difficult\n", + " g2_fit_paras=DataFrame(np.zeros([np.shape(g2)[1],4]),columns=['beta','relaxation_rate','alpha','baseline'])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 290, + "metadata": { + "papermill": { + "duration": 10.75033, + "end_time": "2023-06-20T08:55:28.711559", + "exception": false, + "start_time": "2023-06-20T08:55:17.961229", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", + "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The combined image is saved as: /nsls2/data/chx/proposals/2025-3/pass-317286/Results/0ae234d7-fb12-4f03-8cdb-d64561aa93f0/uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_fra_0_1000_g2_fit__joint.png\n" + ] + }, + { + "data": { + "image/png": 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kGZmZmU4fT042DPOrVdm35OQKDduv/vnPfxrR0dGGJOOnn34q3H7q1CmjevXqRnp6euG23r17G7Nnz/ZrPC1atDAkOb2lpaU5tO3Xr58RHh5uZGVlufUco0ePNsLDw0tsT05ONiQZTz/9tMP2U6dOGQ899JDRtGlTo0aNGkb79u2NxMREp8f+/fffjccee8yIjY01QkNDjebNmxsTJkwwTp8+XdjmnXfeMeLj441GjRoZoaGhRr169YyrrrrKeO+99xyO9eqrrxrx8fHGeeedZ4SFhRktW7Y0br/9duPXX3916/VWVeW93wOF/e+y+G306NGGYZh/z1dddZXDPidPnjRq1aplvPnmmx4/b1nnryr2lYYRuP2lK/2SYbjeNxlG6f2lK/2yO32qK8ekr/ResPSXAABUBjbDcHYNFzgnKytLkZGRyszMdFpPJT/frJdy4IDzEQE2m7lqX1pa8IwGKMuNN96oyMhIvfrqq/ryyy916623avfu3eVOhQMqg/Le7yhbWecvMdGsMVWeBQukESP8FGAlQ3+JQEZ/CQCA7zCtD14LCZFmzjTrpdhsjgkq++rWM2b4JjEVCCtcvfbaaxo9erQaNmyoZs2aadGiRXzRAqCoKN+2Cwb0lwAAAJAkRk6hXK5eGUxKMuupFC2OHhtrJqZ8UeDX2fFjYszEWDAVEAasxEgA75R1/hhlCgQX+ksAAHyn/LWQARclJEh790rJyea0lORk80uWrxJTw4eXXBXQvsJVMC7BDiC42EeZSudGldr5epQpAAAAEEhITsGnQkKk3r3Neim9e/tuKl9ZK1xJ5gpX+fnePxcA+FNCgrR4sdSsmeP2mBhzO6NAAQAAUBVRcwqV3tq1JUdMFWUYUnq62a537woLCwA8kpAgDR5c+evnAQAAABWF5BQqvYwM37YDAKvZR5kCAAAAIDmFAOCLFa4CYZU/APAV+jwAAAAEEmpOodKLjzfrsRQvIGxns5mrAsbHO388KclcIatPH2nkSPM+Lo4i6gCCE30eAAAAAg3JKVR63qxwxSp/AKoS+jwAAAAEIpJTCAierHDFKn8AqhL6PAAAAAQqklMIGAkJ0t69UnKytGCBeZ+WVvrS6+6s8gcAgY4+DwAAAIGKgugIKO6scMUqfwCqEvo8AAAABCqSUwhanqzyxwpXAAKVL1Y2BQAAAKzAtD4ELXdX+WOFKwCBzNuVTQEAAACrkJxC0HJnlT9WuAIQ6LxZ2dQuP19KSZESE817iqcDAACgIpCcQlBzZZU/VrgCECw8WdnUjtGjAAAAsIrNMJx9JQfOycrKUmRkpDIzMxUREWF1OB4pq5ZUSor5Jaw8ycmuF2MHAlUwvN+tVFnOn7v18+yjR4t/IrCPuCovsQVURZXl/Q4AQDCgIDqqhLJW+XN15aoDB8xEFsXSAVR27qxsWt7oUZvNHD06eDB9HgAAAPyD5BSqPFdXrnr4Yeno0XO/x8SY9V0YTQAgkK1dW7LeXlGGof9v787Do6iyPo7/OgkEBBIJBEgICAKCskYWZcYgi6CgiAZcQAVxn9ER5HVjVBZl1HFUQHEZ3HAjOISAK+6BBFEhSBQFFyQIhLBDQhCCSer949ohe7qTTld35/t5nnqqu/pW97HGumOd3Huutm837Rg9CgAAgNpAzSnUeVWtcOVUPDElUSwdQGBwdfSoq+0AAAAAdzFyCnWec4WrMWNMgsrVKmzO6S6TJknh4dKePUz3A+B/XB096mo7AAAAwF2MnAJU8QpXkZGVn2dZZjrMeeexuhUA/1TV6FGHQ2rTxrQDAAAAagPJKeBP8fHS1q1mVb6FC81+9mz3v4fpfgD8iXP0qFQ2QeV8P2dOyRGhBQVmgYiEBLMvKPBCoAAAAAhYTOsDiim9wtWKFe5/B9P9APgb5+jRSZNKFkePiTGJqeILPyQlld+OBSIAAABQXQ7LcrXCDuqqnJwchYeHKzs7W2FhYXaH41UFBWaaXmam67WoKsLDG/xBXb7fPcHfr19BgVmVLyur/KR6UpIZGVq6P3SOsEpMpI9D3eHv9zsAAL6EaX1AJSqb7uIupvsB8HXO0aNjx5p96al8kyaVn6h3Hps8mSl+AAAAcB/JKaAKFRVLd5dlme3GG6XPPuMBDoB/SU0tOZWvNMuStm837QAAAAB3kJwCXFC6WPqnn1a+ulVlDhwwq/uxqh8Af5KV5dl2AAAAgBPJKcBFxae7DBlS8+l+7kzz+/zzz3XdddepS5cuatSokVq3bq1Ro0Zp3bp1Lv9ebm6uJk+erOjoaDVo0EC9evXSokWLqt3O3bYA/FtUlGfb1ZbDhw/r7rvv1rBhwxQZGSmHw6EZM2a49R1r1qzR+eefryZNmqhx48YaNGiQvvjii2q380QfDgAAEMhITgHVVNPpfu7UaHnuuee0detWTZo0SR988IHmzp2rPXv26Oyzz9bnn3/uYrzxevXVVzV9+nQtX75cffv21dixY7Vw4cJqtXO3LQD/FhdX+YhRh0Nq00b6y1/MSqcJCWbv7SnM+/fv1/z585WXl6dLLrnE7fPXrl2rAQMG6OjRo3r99df1+uuv69ixYxoyZIi+/PJLt9tJnunDAQAAAhmr9aFKrEZTueKrW7VoIV17rfur+yUnmwe/ilbJ2rNnj1q0aFHinNzcXHXs2FHdunXTp59+Wun3f/DBB7rwwgu1cOFCjR07tuj4sGHD9MMPP2jbtm0KDg52uZ073wn/wv1eM4F+/Zyr9Ukl+zhnwurOO01SqnhtKm+vVOr8zxqHw6F9+/YpMjJS06dPd3n01AUXXKD09HRt2bJFJ510kiQzGuvUU0/VaaedVjQyytV2Us37cPimQL/fAQDwJkZOAW6wLEvPP/+8unfvrgYNGqhjx45aujRRAwYU6l//6qavv364WtP93n7b1KAaNEgaN87si9ekKv1QI0mNGzfWGWecoe3bt1f5/UuXLlXjxo112WWXlTg+ceJE7dy5U19//bVb7dxtCyAwVDRiNCbGJKYef7x4YsqS9Lx27Oiu0aMbKCqqoxITE1VYWKhu3brp4YcfrpUYHQ6HHDVYXvWLL77QwIEDixJOktSkSRMNGDBAq1evVtafRbVcbSfVvA8HAAAIdCSnABdZlqUrrrhCU6ZM0fjx4/Xee++pffv2uvbaa7VgwQIdPHhQkydPLufhzZKUX+k2Z06+duzIL/F7VdWkys7O1jfffKOuXbtWGfv333+v008/XSEhISWO9+jRo+hzd9q52xZA4Ci9QERysrR5sxkxdWI0lSXpCklTJI2X9J4OHizbX5ZmWZby8/Nd2mrL8ePHFRoaWua489iGDRvcalcRd/pwAACAQBdSdRMAkrRgwQItXrxYb775psaNGyfJPIQMGDBAd955px577LGiv6DHx0ujRpl6K5deulKHDw9y8VcyJLWTZB7yHA5p0iQpPFzas6fkdL9bb71VR44c0X333Vflt+7fv1+nnnpqmeMRERFFn7vTzt22AAKLc4EIpxUrSk7lkxZIWizpTUmmv8zLC1Ve3gBNnnynrrzyMa1Zc1KJ6cuStHLlSg0a5Fp/mZGRoXbt2tXgn6J8Z5xxhr766isVFhYqKMj8DS8/P79oNKizb3O1XUXc6cMBAAACHckpwEXz5s1Tt27dihJTktS0aVNJUqtWrTRx4sQS7YODzap+zz3XW1dfvdbFX4ku8c6yzAPfeeedOBYTI5199gNKTHxTTz/9tHr37u3SN1c2zaX4Z662c7ctgMBVbAbbn+ZJ6iZnYsow/eXhw630wgsT9cILZetR9e7dW2vXutZfRkdHV92oGv7xj3/o+uuv12233ab77rtPhYWFmjlzpn777TdJKkpEudquPA888IDefNO9PhwAACCQkZwCXHDw4EGtX79e9957b4njBX8uQ/Wvf/2rwuLf48Y1Vv36vXTHHWaqnlNMjHkge+qp4q2rviV37JipxMRZGjfuX7rttttcir9Zs2bl/hX/wIEDkk6MdnK1nbttAQS2qKji7w5KWi/p3lKtnMv2/UuS6S+d05cTE01/2LhxY/Xq1cul3yw9pdhTrrvuOu3du1ezZs3Sc889J0nq37+/7rzzTv373/9W6z/nbLvarrSZM2dq1qxZ+te/XO/DAQAAAh01pwAXbN68WZZlqX379iWOz58/X5LUt2/fCs9duXKlLr+8njIz60k6se3YUU9PPVXymLS1ikhmSpohaYZSUv6pzz5zbbn27t27a9OmTWXqtDhronTr1s2tdu62BRDY4uJMwt0MmNwsU3OqfalW8//cn+gvLctst9wivfmmNHfuStWrV8+lbevWrbX2z3PPPfdo37592rBhg7Zu3arVq1fr4MGDatSoUYmRTq62c5o5c6ZmzJihGTNm6J///GetxQ8AAOBvSE4BLnCOitq7d2/RsXXr1hUlp6zia6qX4pymUt721Vdr1aLFWknOrbJpKg/JJKbulzS9aLpfeav7lXbppZcqNzdXS5YsKXH81VdfVXR0tM466yy32rnbFvC2lJQUjRw5UtHR0XI4HFq2bFmV5+Tl5em+++7TKaecotDQUHXo0EEvv/xy7QcbAIKDVbRSqXNUlLS3WIt1OpGcKttf7t0rXX21dMcdvdWixVr9+9/l95nFt9qa1ucUGhqqbt266ZRTTtG2bdv01ltv6cYbb1TDhg2r1e6hhx7SjBkzdP/992v69Om1GjsAAIC/YVof4IKuXbsqMjJSs2fPVrt27RQUFKQpU6ZozJgxWrRokebPn6+bbrpJbdq0KXNukyZN1KdPnwq/+7nnzLQWqfhKV6U9IWmapAskXSjpq1Kfn100PWbmzJWaOXOIpk2bpmnTpkmShg8frqFDh+pvf/ubcnJy1LFjRyUkJOjDDz/UG2+8UZR8c7Wdu20Bbzty5Ih69uypiRMnavTo0S6dc/nll2v37t166aWX1LFjR+3Zs6dWV4ULNM6VSm+/vasyMyMlzZbUTo0aBenIkSmSxkhaJJOkuklS2f5SaqK9e/vo3ntPTPWrjuXLl+vIkSM6fPiwJGnjxo1KTEyUJI0YMaJo8YqVK1dqyJCS/eX333+vJUuWqE+fPgoNDdW3336rRx99VJ06ddJDDz1U9BuutpOkJ554QtOmTdMFF1ygCy+8UF99VbIPP/vss6v3DwoAABAoLKAK2dnZliQrOzvb7lBstWrVKqt3795W/fr1raZNm1pTp061CgsLrZtuusmqV6+e9dxzz1X7u5cssayYGOcEl/K2cy2Z4QYVbCfaNmmSbEmyHnhgeonfOHz4sHX77bdbrVq1surXr2/16NHDSkhIKBOLq+3cbQv/EIj3uyRr6dKllbZZvny5FR4ebu3fv79GvxWI189d+fmW9dRTq6z27Xtb9erVt5o0aWpJUy2p0JJusqR6lvRcJf2dZTkcltWmjfmu6jjllFMq7C8zMjKK2iUnm/5y+vTpRcd++ukna8CAAVZERIRVv359q2PHjtb9999v5ebmlvgNV9tZlmWde27lfTj8E/c7AACe47CsSuYjAZJycnIUHh6u7OxshYWF2R1OwCookFJTzapXLVpI115rigVX9w4tvQoW4IpAvN8dDoeWLl2qSy65pMI2f//73/Xzzz+rT58+ev3119WoUSNdfPHFeuihh8pMzyouLy9PeXl5Re9zcnLUpk2bgLp+NVVQYKYdV6c/u/9+s+ppXJyZOgj4kkDsLwEAsAs1pwAfERwsDRwojR1rHsac9VtMgWH3Oaf5VVSHCsAJW7Zs0apVq/T9999r6dKlmjNnjhITE3XrrbdWet4jjzyi8PDwoq28qb11XfF6VO72Z7NmVV1TDwAAAP6P5BTgo5z1WypYjbxKzhEKkydXvpIfAKmwsFAOh0Nvvvmm+vXrpxEjRujJJ5/UggULdPTo0QrPmzp1qrKzs4u27du3ezFq/1HT/oxkOwAAQGAjOQX4sPh4aetWKTlZWrhQ+vTT4su1V82ypO3bzXRBABWLiopS69atFR4eXnTs9NNPl2VZ2rFjR4XnhYaGKiwsrMSG8hXvz954Q4qMdK8vk0i2AwAABCpW6wN8nHO6n9PcuWYEgcPhev2WrKxaCQ0IGH/961+1ePFi5ebmqnHjxpKkn3/+WUFBQYqJibE5usBRvD9r2NC9vsyZbF+xwnxPVpYUFUU9KgAAgEDAyCnAz1RnekxUlBltsGKFlJBg9ow+QCDLzc1Venq60tPTJUkZGRlKT0/Xtm3bJJnpeOPHjy9qP27cODVr1kwTJ07Uxo0blZKSorvuukvXXXddpQXRUX3Vnep3+eWmDtW4cdSjAgAACBQkpwA/5Jwe8+mnUkRExe0cDqlNG2nfPvMAxwMd6oq0tDTFxsYqNjZWkjRlyhTFxsZq2rRpkqSsrKyiRJUkNW7cWJ988okOHTqkPn366KqrrtLIkSP11FNP2RJ/XVF8qt/997t2zoEDJd9TjwoAAMD/OSyrugvVo65gqWTflpRkHsykklNjnLVc7rxTevzxstNmnJ8nJpoHREDifq8prl/1FRSYpHlmputTlp0cDlOPb/NmafVqpvzBO7jfAQDwHEZOAX6uoqkxMTHSW2+ZaXzlPehRYBiALwkONjX1JNcLpTs561HFxDBCFAAAwB+RnAICQOlV/ZKTpYwMsxpWJQuNsZofAJ9SUbK9sunLxe3dW/I9U/4AAAD8A6v1AQGi9Kp+kuur9H32GdNgAPiG+Hhp1CiTNHf2SwUF0nnnuf9dzhGit9wiHT1qkl70cQAAAL6HkVN+JiUlRSNHjlR0dLQcDoeWLVtW5Tl5eXm67777dMoppyg0NFQdOnTQyy+/XPvBwnZRUa61mzWLaTAAfIcz2T52rNkPHGim7Lk73c9p717p6qvp4wAAAHwVySk/c+TIEfXs2VPz5s1z+ZzLL79cn332mV566SX99NNPSkhIUJcuXWoxSviKuDj3H+iYBgPA19SkHlVp9HEAAAC+h2l9fmb48OEaPny4y+0//PBDrVy5Ulu2bFHEn0U72rVrV0vRwdc4H+jGjDEPdK6sgGVZpu3kyWZqDdNfAPgCZz2qSZNK1tKLjCxba6oyTPUDAADwPYycCnDvvPOO+vTpo8cee0ytW7fWaaedpjvvvFNHjx6t8Jy8vDzl5OSU2OC/KiowXBkKpQPwReUt/rBjR/Wm/DHVDwAAwHcwcirAbdmyRatWrVKDBg20dOlS7du3T3//+9914MCBCutOPfLII5o5c6aXI0VtKl1geONGU2eqKq4WVAcAbylv8Qd3R4iW5pzql5ho+ksAAAB4FyOnAlxhYaEcDofefPNN9evXTyNGjNCTTz6pBQsWVDh6aurUqcrOzi7atm/f7uWoURuKFxgeMsS1c3bvlhISpBUrzGpZAOCLqjNCtDhnQmvyZPo6AAAAOzByKsBFRUWpdevWCg8PLzp2+umny7Is7dixQ506dSpzTmhoqEJDQ70ZJrzMWSg9M7PiUQbBwdIdd5x437q1dNNNUqdOZhVAarQA8CXFR4hmZpr+a98+10dSFZ/OXHpkFgAAAGoXI6cC3F//+lft3LlTubm5Rcd+/vlnBQUFKSYmxsbIYCdXVr4qPXogM1OaPl0aN44aLQB8k3OE6FVXSc8/b465W4sqM9OMFmXUKAAAgPeQnPIzubm5Sk9PV3p6uiQpIyND6enp2rZtmyQzJW/8+PFF7ceNG6dmzZpp4sSJ2rhxo1JSUnTXXXfpuuuuU8OGDe34R4CPqGgajKujoViOHYAvq+5UvzvuMAl4EvEAAADeQ3LKz6SlpSk2NlaxsbGSpClTpig2NlbTpk2TJGVlZRUlqiSpcePG+uSTT3To0CH16dNHV111lUaOHKmnnnrKlvjhW0qvfDV7tuujBKjRAsDXFe/j3nhDioyseiTV3r0l35OIBwAAqH0Oy6rOujaoS3JychQeHq7s7GyFhYXZHQ5qUUKCGS3gruRkarQECu73muH6+bakJJNoktxb1c/hMHX6MjKotYcTuN8BAPAcRk4BKBIVVb3zsrI8GwcA1IaKpvpFRlZ+XvFi6QAAAPA8VusDUMSVVfzKU92kFgB4W/FV/bKyTP+VmSldfXXV5zqLpTvPY9VSAAAAzyA5BaCIcxW/MWPMNJaqElTOqS5xcd6JDwA8wbmqn9OKFa6dd8cdJWtSxcSYPjM+3pPRAQAA1D1M6wNQgqsrXDmLCs+ZYx70CgpYfh2Af3KOGqVYOgAAgD1ITgEoo/QqfjNnmge34mJiTBIrPt48mLVrx/LrAPyTc9SoVHWCqjhWLQUAAPAMVutDlViNBpJ58Cpeo8VZa8W5+lXpnsT5gOdMYME/cL/XDNfPvyUlSZMmSTt2nDgWGVl2xFR5WLW07uF+BwDAcxg5BbghNzdXwcHBevzxx+0OpYzs7GwFBQVp9uzZRcd27twph8OhF154ocbf76zRMnas2Tun8k2aVH5tquqOKDh8+LDuvvtuDRs2TJGRkXI4HJoxY4Zbsebm5mry5MmKjo5WgwYN1KtXLy1atKja7dxtC8A/+8vRox26//4XikaNJidLxZpUaskS709ppr8EAACBgoLogBvWrVunwsJCnXXWWXaHUkZaWposy1Lfvn2LjjVq1EhffvmlunXrViu/mZpacoRBacWXX3d1RMH+/fs1f/589ezZU5dccolefPFFt+OKj4/X2rVr9eijj+q0007TwoULNXbsWBUWFmrcuHFut3O3LQD/7i8bNz7R1tVi6fPmmS0mRnrySTPiqrZX9aO/BAAAAcMCqpCdnW1JsrKzs+0OxXaPP/64FRwcbB05csTuUMp49NFHreDgYCs3N9drv7lwoWWZFFTl28KFrn9nYWGhVVhYaFmWZe3du9eSZE2fPt3l899//31LkrWw1I8OHTrUio6OtvLz891q525bf8f9XjNcvxMCpb/Mz7esmBjLcjhc6+/K22JiLGvJEs//c9Bf2ov7HQAAz2FaH+CGtWvXqlu3blq9erXi4uLUqFEjdezYUc8880yJdmvWrNEVV1yhdu3aqWHDhmrRooUuvfRS/frrryXa/fjjj7rmmmvUrl07hYaGqmXLlho2bJh++umnEu1WrVqlYcOGKTw8XE2bNtWFF16oX375pUxsp59+uho1alR0bNiwYRowYEDR+8GDB2vQoEFauXKlzjvvPDVu3FitWrXSgw8+WO4/b1W/GxXl2nVztZ0kORwOOdypSFzK0qVL1bhxY1122WUljk+cOFE7d+7U119/7VY7d9sCMAKlv1y1aqWaNj1PltVYUitJ5feX0ipJwySFS2oq6UJJ5ndra1U/+ksAABAoSE4BbkhLS9O+ffv0z3/+U7fddpuSkpJ0+umn67bbbtOyZcuK2qWnp6tnz56aO3euPvroI82ePVs///yz4otVBv/ll1/Ut29fZWdn68knn9Qnn3yiuXPnKioqqsQD04wZM3TuueeqTZs2SkhI0Isvvqjt27dryJAhys3NLRFb8SkqkrR+/Xr17t27RFxbt27VHXfcoQkTJuidd97RgAEDNH36dK1cubLEua78btnl1y1J+SW2mJh89e+fr/z8kltt+f7773X66acrJKTkrOUePXoUfe5OO3fbAjACqb+8664JmjHjHTVsOEDSdEkl+0tphqRzJbWRlCDpRUnbJQ2RlFtuDT7Lssr0ixVttYX+EgAA+ApqTgEuOnjwoH799Vd17dpVK1euVMOGDSVJcXFxatOmjRYtWqRLLrlEknTTTTcVnVdYWKjCwkIdO3ZMN9xwgw4dOqSTTz5Zb775pgoLC7Vs2TIFBZ3IE1955ZVFr9977z3NnDlTjz32mO66666i4z169NBpp52mt99+W1dddZX27dun3377rcTD1m+//aZ9+/YVPWxt2bJFBw8e1KmnnqovvvhCoaGhkqTOnTtr8eLF2rhxo84991y3fte5/PqYMSZBZVkrJQ0qcd127JAaNCh7PTMyMtSuXTs3/hdwzf79+3XqqaeWOR4REVH0uTvt3G0LIHD7y4kTO+uUUxbr3HM3auXKc52/LGmmpMcknfhdqYek0yS9LemqMjX4Vq5cqUGDSvaXFaG/BAAAgY7kFOCitLQ0SdJDDz1U9KAlSSeddJI6deqk3bt3SzJ/DV+yZImeffZZ/fjjj9q1a5esP/9sHhQUVHRu8+bN9fvvv2vixIm66aabdPbZZyu4VMXcadOmqUOHDpo0aVKJv563b99eDRs21JYtWySZKSqS1KdPn6I269atkySdeeaZkqRvvvlGkvTggw8WPWhJJx4UoqOj3f5dSYqPlxITncuv95ZkYmnZUpoyRRo8uPzrWfz3PK2yaS7FP3O1nbttgbouUPvLQ4dMf3needE6Mdh0mqQOkibJjBgt+mVJDSVtUXGZmabI+pYtvfX882vVq1fVxdLpLwEAQKAjOQW4KC0tTY0aNdLFF19c5rNdu3YV1Sq56aabtGDBAt188826/fbbFRkZqdDQUN1www06evRo0YPOLbfcoiNHjmjBggV67bXXFBkZqbFjx+qhhx5SWFiYdu3apfXr10tSiYej4k4++eSi2OrXr180bUIyD1eNGjVSly5dit6HhobqvPPOK/Edzoew2NjYon8WV3/XKT5eGjVKSklprMzMXoqKks45xzxwFRRIq1adWLXKebz0lA9PadasWbl/mT9w4ICkE3+9d7Wdu20BBH5/edVVsfrvf6UdO3ZJWv/np+X/rnRyiXd33CHt3StJjSX1UuvW0uzZ0qWXVnC66C8BAEDgIzkFuCgtLU0tWrQo89f61atX67ffftOFF16on376SS+++GKZaSX79u3TDz/8oMsvv7zoWEhIiO655x7dc8892rFjh+bPn6+HHnpIDRo00L///W9t375dkjR79mydc8455cbUoUOHoth69OhR4qFs3bp16tWrV9EUmHXr1qlHjx6qX79+mX+u5s2bq23btpLk1u8WFxwsORwrdc019k5T6d69uxISEpSfn1/igW7Dhg2SpG7durnVzt22AAK/v2zfvq3mzpVGj97+5yezJZX/u2ZU1QkmMSWZulWDlJkpFftHLRf9JQAACHQURAdctHbtWu3cuVOHDh0qOpafn6977rlHXbp00ejRo/Xbb79Jks4444wS5zqnmRSfRlJcTEyM7rvvPjVs2LBoOorzr8sOh0N9+vQpd2vatGlRbKW/+5tvvimaoiKZYr/l/f66detKFAF253dL6927t9auXau1a9fq3/9eKzPFr/zt669rZ5rKpZdeqtzcXC1ZsqTE8VdffVXR0dE666yz3GrnblsAdaO/jI+XnnnGOQrIIalPBVv5/aXknAZttpYt1+qrr9YW9aHFt9qa1kd/CQAAfAUjpwAX7N27V9u3b1eHDh00ZswY3XnnnTp27Jjmzp2rDRs2aNWqVQoJCVHPnj110kkn6YEHHpDD4dDRo0f1wgsvaPPmzZJO1Di57bbblJ2draFDh6pt27bau3ev5s2bp/r16+vmm2+WZP7KP2jQIN1///3Kzc3VWWedJcuylJWVpeTkZE2YMEEDBw5UVlaWsrKyShT33bFjh/bs2VP0ELV9+3bt3bu3zMNWfn6+vv32W02ZMqXomKu/W54mTZqoT58+KiiofIqKwyHddZcppF5erZXly5fryJEjOnz4sCRp48aNSkxMlCSNGDFCJ510klauXKkhQ4Zo2rRpmjZtWtG5w4cP19ChQ/W3v/1NOTk56tixoxISEvThhx/qjTfeKBrJ4Wo7d9sCdV1d6i///vcOWrx4kL7++n6NHJmrfv3O0qFDlp55JksHDyZLmiBpoCIji4+Ycmoik7wydu+Wjh41xdLdQX8JAAACggVUITs725JkZWdn2x2Kbd5//31LkvXVV19ZN954oxUWFmaFhYVZY8aMsX7++ecSbd977z2rS5cuVmhoqHXGGWdYc+fOtWbNmmUFBQVZhw8ftizLsp5++mkrLi7OatGihRUaGmq1b9/euu6666xff/21xHdlZ2dbU6dOtU477TSrQYMGVtOmTa2ePXta//jHP6yDBw9almVZb7/9tiXJ+vbbb4vOW7ZsmSXJ+u6770q8L97Gsizr22+/tSRZSUlJbv9uZZKTLUuqektOLv/8U045xZJU7paRkfHnbyRbkqzp06eXOf/w4cPW7bffbrVq1cqqX7++1aNHDyshIaHa7dxt68+432uG60d/6fzdSy/9h/XCCwet5GTLeuMN1/rEhQvdv970l/bhfgcAwHMclvXnsjhABXJychQeHq7s7GyFhYXZHQ78QEKCNG5c1e0WLpTGjq39eOA67vea4fqhPCtWSINcKMeXnOz+yCnYh/sdAADPoeYUAI+LivJsOwDwZ3FxUkyMmdJcHodDatPGtAMAAKiLSE4B8DgexADghOBgae5c87p0v+h8P2dO+TX4AAAA6gKSUwA8jgcxACgpPl5KTJRaty55PCbGHI+PtycuAAAAX0ByCkCt4EEMdkpJSdHIkSMVHR0th8OhZcuWVdp+xYoVcjgcZbYff/zROwGjToiPl7ZuNbWlFi40+4wMc7ygwNSmSkgw+4ICm4MFAADwohC7AwAQuOLjpVGjpNRUKSvL1JiKi2PEFGrfkSNH1LNnT02cOFGjR492+byffvqpRGHjyMjI2ggPdVhwcNmi50lJ0qRJ0o4dJ47FxJgRqCTyAQBAXUByCkCtKu9BTDKjAkhaobYMHz5cw4cPd/u8Fi1a6OSTT/Z8QEAFkpKkMWOk0msnZ2aa44w0BQAAdQHT+gB4XVKS1K6dWVp93Dizb9fOHAfsFBsbq6ioKA0ZMkTJyclVts/Ly1NOTk6JDXBVQYEZMVU6MSWdODZ5MlP8AABA4CM5BcCrnKMEik9fkU6MEiBBBTtERUVp/vz5WrJkiZKSktS5c2cNGTJEKSkplZ73yCOPKDw8vGhr06aNlyJGIEhNLdsXFmdZ0vbtph0AAEAgY1ofAK+papSAw2FGCYwaxRQ/eFfnzp3VuXPnovf9+/fX9u3b9fjjj2vAgAEVnjd16lRNmTKl6H1OTg4JKrgsK8uz7QAAAPwVI6cAeA2jBOBPzj77bP3yyy+VtgkNDVVYWFiJDXBVVJRn2wEAAPgrklMAvIZRAvAn69evVxRZAdSiuDizKp/DUf7nDofUpo1pBwAAEMiY1gfAaxglAG/Jzc3V5s2bi95nZGQoPT1dERERatu2raZOnarMzEy99tprkqQ5c+aoXbt26tq1q44fP6433nhDS5Ys0ZIlS+z6R0AdEBwszZ1r6u05HCWnPDsTVnPmMM0ZAAAEPpJTALzGOUogM7P8ulOSFBFhalMVFPBAhupLS0vToEGDit4760JNmDBBCxYsUFZWlrZt21b0+fHjx3XnnXcqMzNTDRs2VNeuXfX+++9rxIgRXo8ddUt8vJSYaOrxFZ/2HBNjElOjRkkrVpgRpVFRph+lbwQAAIHGYVkVPSICRk5OjsLDw5WdnU09FdSYc7U+qeIElWQezObONQ9u8B7u95rh+qG6CgpMvb3iSai33y4/aUXf6Bu43wEA8BxqTgHwKucogdatK2+XmWmSWElJ3okLAOwUHCwNHCiNHWv2b79t+sDSi0jQNwIAgEBEcgqA18XHS1u3Sp9+aqbxlcc5qmryZDOiAADqioICM2KqvNGl9I0AACAQkZwCYIvgYLMdOFBxG8uStm83U10AoK5ITS07Yqo4+kYAABBoSE4BsE1WlmfbAUAgoG8EAAB1DckpALaJivJsOwAIBPSNAACgriE5BcA2cXFm5SmHo/zPHQ6pTRvTDgDqiqr6RsnU6ysooO4UAAAIDCSnANgmONgsiS6VfQhzvp8zx7QDgLqisr7R6cAB6bzzpHbtWLkPAAD4P5JTAGwVHy8lJkqtW5c8HhNjjsfH2xMXANipor6xtMxMacwYElQAAMC/OSyrvIWKgRNycnIUHh6u7OxshYWF2R0OAlRBgVl5KivL1FGJi2PElB2432uG6wdPKyiQVqyQLr+84tVNHQ6T0M/IoN/0Ju53AAA8J8TuAABAMg9UAwfaHQUA+JbgYLNVlJiSJMuStm83CX76UQAA4I+Y1gcAAODDsrI82w4AAMDXkJwCAADwYVFRnm0HAADga0hOAQAA+LC4OFNTqqKV+xwOqU0b0w4AAMAfkZwCAADwYcHB0ty55nXpBJXz/Zw5FEMHAAD+i+QU4Kbff/9dM2fOVJcuXdSgQQM1a9ZMY8eO1cGDB2v1d3NzczV58mRFR0erQYMG6tWrlxYtWlSt73rxxRflcDjUuHHjGv2OJ2MCEHjoLz0XU3y8lJgotW5d8nhMjDkeH+/WPxYAAIBPYbU+wA2WZWns2LFKSUnRtGnT1KtXL3333Xe644471KFDB82aNavWfjs+Pl5r167Vo48+qtNOO00LFy7U2LFjVVhYqHHjxrn8PZmZmbrzzjsVHR2t7OzsGv2Op2ICEHjoLz3fX8bHS6NGmVX5srJMjam4OEZMAQCAAGABVcjOzrYkWdnZ2XaHYrvk5GRLkrV48eISx1u2bGlNnjy51n73/ffftyRZCxcuLHF86NChVnR0tJWfn+/yd1100UXWyJEjrQkTJliNGjWq9u94Mib4Du73muH6nUB/SX8Z6LjfAQDwHKb1AW5YvHixmjZtqksvvbToWEpKinbv3q3BgwfX2u8uXbpUjRs31mWXXVbi+MSJE7Vz5059/fXXLn3PG2+8oZUrV+rZZ5+t8e94KiYAgYn+kv4SAADAVSSnADesXr1aZ511liRp586deuWVVzR69GgNGTJEF110UZn2lmUpPz/fpa0y33//vU4//XSFhJScidujR4+iz6uyZ88eTZ48WY8++qhiYmJq/DueiAlA4KK/pL8EAABwFckpwEXHjh3T999/r7POOksPP/ywWrdureuuu04nnXSSFixYIEc5a3yvXLlS9erVc2nbunVrhb+9f/9+RURElDnuPLZ///4q4//73/+uzp07629/+5tHfscTMQEITPSX9JcAAADuoCA64KJvvvlG+fn56tevn7p06aKzzjpLX331lebMmaMBAwbou+++K7OaU+/evbV27VqXvj86OrrSz8t7mHPlM0lasmSJ3n33Xa1fv77Ktu78Tk1iAhC46C/pLwEAANxBcgpw0Zo1ayRJ/fr1U/PmzXXqqadq2LBhOu200zR27Fh99dVXOu+880qc07hxY/Xq1cul7y893aO4Zs2alfuX9QMHDkhSuX+Rd8rNzdWtt96qf/zjH4qOjtahQ4ckScePH5ckHTp0SPXq1VOjRo3c+p2axAQgsNFf0l8CAAC4g2l9gIvWrFmjU089Vc2bNy/38/L+ku+paSrdu3fXpk2bytRa2bBhgySpW7duFZ67b98+7d69W0888YSaNm1atCUkJOjIkSNq2rSprrrqKrd/pyYxVUdBgbRihZSQYPYFBR79egAeRH9pb38JAADgbxyWZVl2BwHflpOTo/DwcGVnZyssLMzucGzTsWNHtWrVSqtWrSo6ZlmWhg4dqt27dxc9ZBR3+PBh/fTTTy59f48ePVS/fv1yP1u+fLlGjBihRYsW6Yorrig6Pnz4cH333Xfatm2bgoODyz332LFj+uqrr8ocf/TRR7Vy5UotX75czZs3V7du3dz6nZrE5K6kJGnSJGnHjhPHYmKkuXOl+HiP/AT+xP1eM1w/g/7Svv4S3sP9DgCAB1lAFbKzsy1JVnZ2tt2h2Gb//v2WJEuSdf3111uffvqp9c4771iXXHKJFRoaaq1evbrWYxg6dKjVtGlTa/78+dbnn39u3XjjjZYk64033ihqs2LFCis4ONiaOXNmld83YcIEq1GjRtX6neq0ra4lSyzL4bAsqeTmcJhtyRKP/RQs7vea4vrRX9rZX8K7uN8BAPAcak4BLnDWTxk/frw+/PBDvfbaa4qKilK/fv309ddfq2fPnrUeQ1JSku677z5NmzZNBw4cUJcuXZSQkKArr7yyqI1lWSooKFBhYWGt/k512lZHQYEZMVXe+E7LkhwOafJkadQoiUEHgG+gv7SnvwQAAPBnTOtDlRi2Lj344IOaNWuWcnJy1KBBA7vDqTNWrJAGDaq6XXKyNHBgbUdTN3C/1wzXj/4SdQf3OwAAnkNBdMAFa9asUffu3XnQ8rKsLM+2A1D76C8BAADgLpJTgAvWrl2rfv362R1GnRMV5dl2AGof/aW9WNkUAAD4I2pOAS7YvXu33SHUSXFxZlW+zMzy6045HObzuDjvxwagfPSX9mFlUwAA4K8YOQXAZwUHm4cqySSiinO+nzOHYugAkJQkjRlTMjElmeT+mDHmcwAAAF9FcgqAT4uPlxITpdatSx6PiTHHGQ0AoK6ramVTyaxsyhQ/AADgq5jWB8DnxcdLo0ZJqamm+HlUlJnKx4gpADB9Y+kRU8VZlrR9u2nHyqYAAMAXkZwC4BeCg3moAoDysLIpAADwd0zrAwAA8GOsbAoAAPwdI6cA+LWCAqb7AajbWNkUAAD4O0ZOAfBbSUlSu3bSoEHSuHFm364dq1IBqFtY2RQAAPg7klMA/BLLpqMyKSkpGjlypKKjo+VwOLRs2TKXz/3iiy8UEhKiXr161Vp8gKexsikAAPBnJKcA+B2WTUdVjhw5op49e2revHlunZedna3x48dryJAhtRQZUHvi46WtW6XkZGnhQrPPyCAxBQAAfB81pwD4HZZNR1WGDx+u4cOHu33ezTffrHHjxik4ONit0VaAr2BlUwAA4I9ITgHwOyybjtrwyiuv6Ndff9Ubb7yhWbNmuXROXl6e8vLyit7n5OS49mNHj0rDhrkfZOmCQtVp78qx4u+drys75nCU3Mo7VnoLCiq7L28LDi67BQVJISHlb/Xqma1+fbM5X4eGSg0amM35ulGjE1vDhuZ7AQAA4HUkpwD4HZZNh6f98ssvuvfee5WamqqQENf/r/GRRx7RzJkz3f/BwkJp1Sr3z0PtOumkE8mqJk2kk0+WmjYtu4+MlFq1klq2NFtEhM8ntljZFAAA+DKSUwD8Dsumw5MKCgo0btw4zZw5U6eddppb506dOlVTpkwpep+Tk6M2bdpUfWJoqLRkiXuBlvcvu7vtXTnmfO/OvrLXxbfCwoqPFd8XFppsinNfeisslPLzzev8fLP98UfJ/fHjJ7a8PLM/dsy8PnbMjF77/XezOTnf793r3rUOCTEZn1NOkdq2NftTTpFOP13q2lVq1sy97/OwpCRTp6/4dOiYGLPCH/WoAACALyA5BcDvOJdNHzPGJKKKP1uzbDrcdfjwYaWlpWn9+vW67bbbJEmFhYWyLEshISH6+OOPNXjw4HLPDQ0NVWhoqPs/GhJCVsBXFBaaRFVurnTkyInt8GHp0CGzHTx4Yn/ggLRnj7R7t9kOHDDJsO3bzVaeVq2kbt1ObF27mn3jxrX+j+dc2bR0DtK5sikr+QEAAF9AcgqAX3Ium17eaIA5c3jYguvCwsK0YcOGEseeffZZff7550pMTFT79u1tigxeERR0YipfdRw/bpJVmZnSb7+Zbds2acsW6YcfzPtdu8z26aclf7d3b2nQILOdc47Hk1VVrWzqcJiVTUeNIpkPAADsRXIKgN+KjzcPVdRRQWm5ubnavHlz0fuMjAylp6crIiJCbdu21dSpU5WZmanXXntNQUFB6tatW4nzW7RooQYNGpQ5DpRRv77JisfESGedVfbzw4eljRul77832w8/SBs2mGTV2rVme+wxM5qub1+TqIqPl8480/0C+KWwsikAAPAXvl29E2WkpKRo5MiRio6OlsPhcGup8y+++EIhISHq1atXrcUHeJtz2fSxY82exBQkKS0tTbGxsYqNjZUkTZkyRbGxsZo2bZokKSsrS9u2bbMzRNQVTZqYpNX110uzZ0sff2yy6b/9Jr36qjRxotSunZka+OWX0sMPS336SJ07SzNmSD/9VO2fZmVTAADgLxyW5W6FVdhp+fLl+uKLL3TmmWdq9OjRWrp0qS655JIqz8vOztaZZ56pjh07avfu3UpPT3f5N3NychQeHq7s7GyFhYVVP3gAPo/7vWa4fqi2rVulFSuk5culd981dbCczjzTJLeuvdasKOiiFSvMQKyqJCczcqo6uN8BAPAcklN+zOFwuJycuvLKK9WpUycFBwdr2bJltZec2rlTWr/e5e+utvKmOpQ+VlWbyto7Xzsclb+u7FhQUNl9RVtwcMn3ISHmWHDwidchIWbz8eXKfQFLplcfD1s1w/WDRxw+LL39trRwoRlpVVBgjjdvLv3jH9Ktt7q0AmBBgRmUVdXKphkZ9JHVwf0OAIDnUHOqDnjllVf066+/6o033tCsWbOqbJ+Xl6e8vLyi9zk5Oa7/2KpV0hVXVCdMuCooSKpX78RWv77ZQkNP7Bs2rHhr1EgKCzNTTYrvw8LMw05EhCnKW8NaJ3ZhyXQAfq9JE+nqq822d69JUs2ZY0ZXTZ8u/fvfZiTVAw9IkZEVfg0rmwIAAH9BcqqW/fHHH9q1a5d+//13RUZGKiIiwqu//8svv+jee+9VamqqQkJc+5/7kUce0cyZM6v3gxERpqCrO9wdvFdZe1c/c76u7Fhl++JbeccKC0vui78uKDjxvrDQvHe+Liw0dUecfyUvT2GhlJdnttpSv77537J5c6llSzP8KDra7GNipA4dzOZjfylmyXT/ZXdfCfisyEiTcb/1VmnJElM8/ZtvpKefNkmruXOlceMq/IMCK5sCAAB/wLS+WpCbm6s333xTCQkJWrNmTYlRSDExMRo2bJhuuukm9XU3iVNKVdP6CgoKdPbZZ+v666/XLbfcIkmaMWNGldP6yhs51aZNG4ate1vxRFV+/ontjz/M5nx9/PiJzZm0Onq07Pb772Z/5IiUk2OmjRTfZ2dL+/eb73FVixZSx45m69DB7Lt2NZuLyVBPcU5fqWhlKqavuMab01S81Vd6E9N8UOssS/rsM+n//k/67jtzbMQI6fnnpTZtKjyN6c6ex/0OAIDnkJzysNmzZ+tf//qX2rVrp4svvlj9+vVT69at1bBhQx04cEDff/+9UlNTtXTpUp199tl6+umn1alTp2r9VlXJqUOHDqlp06YKLvZfn4WFhbIsS8HBwfr44481ePDgKn+H//iqQyzLJK/27zfbvn3S7t3maca5bdsm/fqrtGdPxd/TsKEp4Nu3r9n69TPJq1qcKkjhX8/w1v3uzb7Sm+gv4TV//GFGUT34oPmjQpMmZrrfzTdTm9BLuN8BAPAcklMedtlll2natGnq3r17pe3y8vL00ksvqX79+rrhhhuq9VtVJacKCwu1cePGEseeffZZff7550pMTFT79u3VqFGjKn+H//hCuXJyTJJq8+YT2y+/SOnpZjRWac2bS+efb/7Cf/75LhXzdUdCgpnZUpWFC6WxYz360wHFW/e7N/tKb6K/hNdt2mTqT335pXkfFye98ILUubO9cdUB3O8AAHgOySk/k5ubq82bN0uSYmNj9eSTT2rQoEGKiIhQ27ZtNXXqVGVmZuq1114r93xXpvWVxn98wS2FhdLPP0tr15ptzRqTsCpeIysoSDrrLJOouvJKMx2whhg55Rnc7zXD9YMtCgqkZ5+Vpk41o19DQ82IqrvuqnLEKtP9qo/7HQAAz2Hcdy167733VFhY6NHvTEtLU2xsrGJjYyVJU6ZMUWxsrKZNmyZJysrK0rZt2zz6m4BbgoKkLl2ka66RnnpK+uorM8oqJUW6916pRw+TwPryS7PSVKdO0rnnSq++ah6qqikuztSUqug5zOEw5Vji4qr9E6gltdFXAnVKcLD0j39IP/xgRqbm5Un33CPdckulC2wkJZlafYMGmZGngwaZ90lJXoscAABAEiOnalVwcLCysrLUokULu0OpEf4yCI/bsUNavtw8AX38sUlWSVLjxtJVV0n33VdpYd+KOFfrk8pfMp3V+qpmx/0eKH2lRH8JH2BZ0nPPmWRVYaEZnfraa1K9eiWaVbS6Kf2l67jfAQDwHEZO1SLyfkAFYmKkG280CarffpP+9S9TMD03V/rvf81oqrvvlg4ccOtrnUumt25d9ud40PJd9JWABzkc0t//Li1aZBJSixZJl15qVmv9U0GBNGlS2cSUdOLY5MmVDroCAADwKJJTtSw9PV1HSk1VyszM5C9sgFNMjPTPf5pi6snJ0oABZkrKf/5jElb//neJh6qqxMdLW7ear1q40OwzMkhM+Tr6SsDDLrtMeucds3rq++9LF1xgpljL1JjasaPiUy1L2r7dtAMAAPCGELsDCHTDhw+Xw+FQu3bt1KNHD3Xu3Fm//fabTj75ZLtDA3yLw2Eqla9YYUZU3XuvtGGD2T/9tDRjhnTttVJI1d1WcDBFz/0NfSVQCy64QProI+mii0zdvyFDpOXLlZXV3KXTs7JqOT4AAIA/MXKqlv38889KTU3V3XffrejoaG3YsEGHDh3S/Pnz7Q4N8E0Oh1nFb/16UyelbVspM9NMA+ze3dSoQsChrwRqSVycGULavLmUliade65OCd3l0qlRUbUcGwAAwJ8oiF6LgoKCtGvXLr8v8kvBT9jq2DFT3HfWrBM1qKZPl6ZNMysDwqPsuN8Dpa+U6C/hw378UTrvPCkzU9Zf/qoOv32urTvrl1t3yuEwM64zMsxIVJSP+x0AAM/hya4WjRw5UvVKrY4DwE0NGkh33CFt2WKWRZekmTPNNBU3C6bDN9FXAl7QpYsZQRUeLsfqL/RJ9ymSTqzO5+R8P2cOiSkAAOA9JKdq0dtvv62mTZvaHQYQGMLDzQiqV181Cavly6U+faT0dLsjQw3RVwJe0qmT9MYbkqQOHz6jNbe+yuqmAADAJ5Cc8rBt27a51T4zM7OWIgEC1Pjx0pdfSu3bmzkn/fub2lTwK/SVgE0uusgsMCGpzws3a+uSdaxuCgAAbEdyysP69u2rG2+8UWvWrKmwTXZ2tl544QV169ZNSUlJXowOCBC9epnCvsOHm5pUEyZIt90mFRTYHRlcRF8J2OiBB0ySKi9PwZfFa2DXvRo71qxyylQ+AABgh6rXZIdbNm3apIcfflgXXHCB6tWrpz59+ig6OloNGjTQwYMHtXHjRv3www/q06eP/vOf/2j48OF2hwz4p4gI6b33pAcfNDWonnlG+uMP6fnnyxZRgc+hrwRsFBQkvf661K+f9Msv0pVXSh99JIXwn4UAAMAerNZXS44dO6YPPvhAqamp2rp1q44eParmzZsrNjZW559/vrp162Z3iC5jNRr4vEWLpKuukgoLpTvvlB57jARVNXn7fg+kvlKiv4Sf+eEH6ayzpCNHpKlTpYcftjsiv8L9DgCA55CcQpX4jy/4hZdflq6/3rx+6CHp/vvtjcdPcb/XDNcPfmfxYunyy818vnXrpJ497Y7Ib3C/AwDgOdScAhAYrrtOmj3bvH7gAWnu3BIfFxRIK1ZICQlmT3kqAJB02WXSmDGmU7z5ZjpHAABgC5JTXnL06NFyV5v64YcfbIgGCFCTJ5v6U87Xr7wiSUpKktq1kwYNksaNM/t27cxx+Bb6SsAGc+dKTZpIX38tzZ9vdzQAAKAOIjnlBYmJiTrttNM0YsQI9ejRQ19//XXRZ9dcc42NkQEB6IEHpClTzOsbbtDq+97XmDHSjh0lm2VmmsECJKh8B30lYJPo6BP1pqZOlXbtsjceAABQ55Cc8oJZs2bpm2++0bfffquXX35Z1113nRYuXChJouQX4GEOh/T446b+VGGhujw6QdHWjjLNnLfe5MnMYvEV9JWAjf72N6lPHyk7W7rjDrujAQAAdQxrBnvBH3/8ocjISElSnz59lJKSovj4eG3evFkOVhQDPM/hkJ55RodT1ivil2/0pq7SEH2mglJdnmVJ27dLqanSwIH2hIoT6CsBGwUHS//9r9S3r1kB9dprpfPPtzsqAABQRzByygtatGih7777ruh9s2bN9Mknn2jTpk0ljgPwoNBQrfjbWzqsxjpXKbpfsypsmpXlxbhQIfpKwGZnnqnC226XJB0e/3elfHSUkaUAAMArSE7Vog0bNig/P1+vv/66WrZsWeKz+vXrKyEhQStXrrQpOiDwNYntqJv1X0nSA3pI52pFue2iorwYFMqgrwR8Q1KSdEbig9quGDXZs0VvX/Asi0cAAACvcFgU8qg1QUFBql+/vs444wz17NlTvXr1KtqffPLJdofnspycHIWHhys7O1thYWF2hwO4rKDArMr34I7rNFGvKFPR6qV07ZOZOuZwSDExUkaGmdECe+73QOkrJfpL+K+kJLNIhGVJE/WyXtb1ylS0OmiLjjtClZgoxcfbHaVv4X4HAMBzGDlVi1atWqWIiAi1b99eeXl5WrBggQYPHqxmzZqpc+fOeuCBB3To0CG7wwQCVnCwWSH9H3paP6qzWmunXtFESZacJYzmzCExZTf6SsBeBQXSpEknFop4U1dph1qrtXZqnN6UxOIRAACgdpGcqkW33Xabnn32WS1ZskQLFy7U+vXrlZycrFNPPVUTJkxQamqqYmNjtXfvXrtDBQJWfLz02pJGur3FWzqmUF2k9zVS7yomRowE8BH0lYC9UlOlHcUWNT2uUM2WWbHvbj0mh1VQtHgEAABAbSA5VYt+/PFHnXHGGSWOnXvuuZo9e7a++eYbJScnq0+fPvrnP/9pU4RA3RAfLy3f2VO7x5mHrYS29yjjl3wSUz6CvhKwV3mLQszXTTqok9VFP2mU3q6wHQAAgCeQnKpFffv21RtvvFHmeNeuXfXxxx/L4XDorrvu0qeffmpDdEDdEhwsnfLsvVKzZmq07UcFL3jJ7pDwJ/pKwF7lLQqRqyaap9skSffqUUkWi0cAAIBaQ3KqFj377LOaM2eOxo0bpx9//FGSdPz4cc2ePVsRERGSpMjISO3evdvOMIG6IzxcmjbNvJ4+XcrNtTceSKKvBOwWF2cWh3DW4nN6SrfrdzVUP63VFZHJiouzJz4AABD4SE7Voq5du+rLL79UVlaWzjjjDDVs2FCNGjXSCy+8oEcffVSStH79ekVHR9scKVCH3HKLdOqp0u7d0hNP2B0NRF8J2M25eIRUMkG1T5F6WddLkuZGP8riEQAAoNY4LMu5Ngtq02+//aZvv/1WwcHB6t27t1q1aiVJSk1N1e7duzVmzBibI6wYSyUj4Pzvf9IVV0iNGkmbN0t/3o+w/373575Ssv/6ATWRlGRW7SteHL1/1Fat2t1RQYUFUlqa1Lu3fQH6GO53AAA8h+QUqsR/fCHgWJZ09tnSmjXSzTdLzz9vd0Q+g/u9Zrh+8HcFBWZVvqwsU4sqLk4KvvYa6Y03pMsuM8l9SOJ+BwDAk5jWB6DucTikxx83r198Udq0yd544HEpKSkaOXKkoqOj5XA4tGzZskrbr1q1Sn/961/VrFkzNWzYUF26dNHs2bO9EyzgQ4KDpYEDpbFjzT44WNLdd5sPExOlX36xMToAABCoSE4BqJvi4qRRo8wwgXvvtTsaeNiRI0fUs2dPzZs3z6X2jRo10m233aaUlBRt2rRJ999/v+6//37Nnz+/liMF/ED37tJFF5lRp//5j93RAACAAMS0PlSJYesIWD/+KHXrZhJUK1dKAwbYHZHtAvF+dzgcWrp0qS655BK3zouPj1ejRo30+uuvu3xOIF4/QJL0xRfSOedI9etLGRkSCxRwvwMA4EGMnAJQd3XpIt1wg3l9111mVAAgszrg6tWrde6551baLi8vTzk5OSU2ICD99a8mOXX8uDRnjt3RAACAAENyCkDdNmOGWbVvzRpp8WK7o4HNYmJiFBoaqj59+ujWW2/VDc7kZQUeeeQRhYeHF21t2rTxUqSADZxToJ97Tjp40N5YAABAQCE5BaBua9XKjJqSpKlTzagA1FmpqalKS0vT888/rzlz5ighIaHS9lOnTlV2dnbRtn37di9FCthgxAgzFTo31ySoAAAAPITkFAD83/+ZJNWWLTxw1XHt27dX9+7ddeONN+qOO+7QjBkzKm0fGhqqsLCwEhsQsBwO6Z57zOs5c6S8PFvDAQAAgYPkFAA0bmym90nS449L+fm2hgPfYFmW8nj4Bkq64gopKkrau1f68EO7owEAAAGC5BQASNK110rNm0s7dkgffGB3NKih3NxcpaenKz09XZKUkZGh9PR0bdu2TZKZjjd+/Pii9s8884zeffdd/fLLL/rll1/0yiuv6PHHH9fVV19tR/iA76pXT7rySvP6zTftjQUAAAQMklMAIEmhodLEieY1U/v8XlpammJjYxUbGytJmjJlimJjYzVt2jRJUlZWVlGiSpIKCws1depU9erVS3369NHTTz+tRx99VA8++KAt8QM+7aqrzP7ddyVWqAQAAB7gsCzWTkflcnJyFB4eruzsbOqpILD9+qvUsaOpq7J5s3TqqXZH5HXc7zXD9UOdYFnS6adLP/0kLVggTZhgd0S24H4HAMBzGDkFAE4dOkjDhpkHr/nz7Y4GAHyTw3Fi9BRT+wAAgAeQnAIASQUF0ooVUkrXv0mSrJdeYiUqAKjIuHFm/9ln0q5d9sYCAAD8HskpAHVeUpLUrp00aJA0ePZF2qHWcuzbpzX3JtkdGgD4pg4dpLPOkgoLpUWL7I4GAAD4OZJTAOq0pCRpzBizSJ8kFShEL+hGSdKxOc8pifwUAJSPqX0AAMBDSE4BqLMKCqRJk0yJqeJe1A3KV7AGKFXP3vqDCgrsiQ8AfNoVV0jBwVJamvTzz3ZHAwAA/BjJKQB1VmrqiRFTxe1Ua72jiyVJo3Y9r9RULwcGAP6gRQtp6FDzeuFCe2MBAAB+jeQUgDorK6viz56TKYw+Xq9pT8YRL0UEAL7NuXhEQoLZF44tNrWv9DBUAAAAF4XYHQAA2CUqquLPPtMQbVYHddSv6rkxQdINXosLAHxRUpKZCl18xGnn6FH6vn5DhWzeLK1dK/XrZ1+AAADAbzFyCkCdFRcnxcRIDkfZzywF6b+6RZJ02ufPMSIAQJ1WevEIp5+zmmjx8VHmDVP7AABANZGcAlBnBQdLc+ea16UTVA6HtEDXqqBeqBzffGMK/gJAHVTR4hGSObZQZmqftWiRlJ/v5egAAEAgIDkFoE6Lj5cSE6XWrUsej4mR/rukuYKvuMwceO457wcHAD6gosUjnD7U+dqnZnLs3i19/rn3AgMAAAGD5BSAOi8+Xtq6VUpONrNSkpOljAxzXH8zhdG1aJF0+LCdYQKALSpbPEKS8lVP/9Pl5s2bb9Z+QAAAIOCQnAIAmSl+AwdKY8eafXDwnx/07y+ddpp09Kj03ns2RggA9qhs8QinN/+c2qekJOn332s3IAAAEHBITgFAZRwO6bI/p/b973/2xgIANqhs8QjJHN8R01/WKadIubnS8uXeDRAAAPg9klMAUBVncmr5cqb2Aahzqlo8QpJmzw2SY/Ro84ZRpgAAwE0kpwCgKj16SJ06SXl5PHQBqJMqWzwiMfHPGn0XXmgOfvCBVFjo9RgBAID/IjkFAJUoKJBWrHTohzPM6Cnrf4srbrdCSkgw+4IC78UIAN5Q6eIRknTOOVKTJtKePVJamp2hAgAAP0NyCgAqkJQktWsnDRokXfW2SU7lLVuud948XGG7cePMvl07cxwAAklFi0cUFEgrVtfXttOHSZIK333fthgBAID/ITkFAOVISpLGjJF27DDvv1VP/aKOaqBjWnT1e0WJp9LtnDIzzXESVAACXfEE/bQ1F0mSvv/3e/R/AADAZSSnAKCUggJp0iTJsoofdeh/ulySNEaLNXmydPx4ee0M57HJk5niByBwlU7QL9dwSVKPP77RbaOzyiSomAINAADKQ3IKAEpJTS07EkqSFstM7Ruu5TqwPVfPPlt+OyfLkrZvN98HAIGmvET+HrXUGvWVJI3QByUS9EyBBgAAFSE5BQClZGWVf9w5ta+hjukivadff63Z9wGAP6sokf+ezNS+C/VeUYKeKdAAAKAyJKcAoJSoqIo+cRSNnrpMi9WhQ02/DwD8V0WJ9/d1oSRpqD5RfeUpM5Mp0AAAoHIkpwCglLg4KSZGcjjKfuZMTl3o+EB/H59bYTvJHG/TxnwfAASaihLv6xWrLLVSYx3RAKVo716mQAMAgMqRnAKAUoKDpblzzevSiadv1Uub1UENrGNaO/093Xhj+e2c7+fMObHUOgAEkooS+ZaCikZPXdn4fUVGuvZ9TIEGAKDuIjkFAOWIj5cSE6XWrUsej2jm0HsNzOipXfMWa/p0KSLCbMXFxJjz4+O9FDAAeFllifwP/kxOXdHoPe3dU858vnIwBRoAgLrLYVnlVQAATsjJyVF4eLiys7MVFhZmdziAVxUUmKkmWVnSL79IM2ZIvaxv9I1666gaKFJ79bujsSxLmjlT6tTJPGDFxfnniCnu95rh+qEuSkoyNaWKT93r0vqwNmQ1U0jhH+qsH/WzOld4vsNhEvoZGf7Vb3K/AwDgOSF2BwAAviw4WBo40CSp2rUztVHWK1ab1UEd9atG6AMtti6XwyG9+KL/PVwBQE3Fx0ujRp1I5EdFSfv2NdHnlw3UMH2iC/V+hckppkADAACJaX0A4JKSS6Y7tEyXSJIu1PuSKOgLoG5zJvLHjjUjR++448SqfRfpvQrPYwo0AACQSE4BgEtKF+r9QCMkScO1XA4VVtgOAOoaZzLfmZyKU6rClF2m3ezZZrQpiSkAAEByCgBcULpQ7yqdoxw1UQvtVW+tq7AdANQ1ziT9r+qoH9VZ9ZSvofqkTLuWLZnKBwAADJJTAOCC0kum/6H6+kRDJZmpfQ6H1KaNaQcAdVnxJL1z9JRzCnRF7QAAQN1GcgoAXFDekunOh64R+kASBX0BQCqZzP9I50uSztOnkswC0STzAQBAaSSnAMBF8fGmcG/r1ub9h7pAktRPa/Xui7upmwIAKpnM/0LnKE/11UY71Em/sDofAAAoF8kpAHBDfLy0dauUnCw9sTBahzvFSpIuDP7Q3sAAwIc4k/kRMSdptf4iSRqiz1idDwAAlIvkFAC4qfiS6U2uMFP79MEHtsYEAL7Gmcxvd90QSdKDAz5jdT4AAFAuklMAUBMjRpj9Rx9J+fn2xgIAPiY4WGp/g0lORX6frGBHoc0RAQAAX0RyCgBqol8/qVkzKTtbWr3a7mjwp5SUFI0cOVLR0dFyOBxatmxZpe2TkpI0dOhQRUZGKiwsTP3799dHH33knWCBQNe3r9SkiXTggJSebnc0AADAB5GcAoCaCA6WLjCF0Zna5zuOHDminj17at68eS61T0lJ0dChQ/XBBx9o3bp1GjRokEaOHKn169fXcqRAHRASIp17rnn96af2xgIAAHwSySkAqCnn1D6SUz5j+PDhmjVrluJdLG4zZ84c3X333erbt686deqkhx9+WJ06ddK7775by5ECdcQQM7VPn31mbxwAAMAnkZzyM0xVAXzQ+edLQUHShg3Stm12RwMPKCws1OHDhxUREVFpu7y8POXk5JTYAJTDmZxKTZXy8uyNBQAA+BySU36GqSqAD2rWTDr7bPN6+XJ7Y4FHPPHEEzpy5Iguv/zySts98sgjCg8PL9ratGnjpQgBP9Otm9SihXT0qPTVV3ZHAwAAfAzJKT/DVBXARzG1L2AkJCRoxowZeuutt9SiRYtK206dOlXZ2dlF2/bt270UJeBnHA6m9gEAgAqRnKpjXJmqwjQVoBouvNDsP/1UOn7c3lhQbW+99Zauv/56/e9//9N5551XZfvQ0FCFhYWV2ABUgOQUAACoAMmpOsaVqSpMUwGqoUcPM2Xl99+ZsuKnEhISdO2112rhwoW60JlsBOA5zuTU119L/OELAAAUQ3KqDnF1qgrTVIBqCAo68eDFUum2y83NVXp6utLT0yVJGRkZSk9P17Y/C9ZPnTpV48ePL2qfkJCg8ePH64knntDZZ5+tXbt2adeuXcrOzrYjfCAwtWsnnXqqVFAgpaTYHQ0AAPAhJKfqCHemqjBNBagm571Fcsp2aWlpio2NVWxsrCRpypQpio2N1bRp0yRJWVlZRYkqSfrvf/+r/Px83XrrrYqKiiraJk2aZEv8QMBiah8AAChHiN0BoPYlJCTouuuuU0JCAlNVgNrkTE6tWWOmrJDYtc3AgQNlWVaFny9YsKDE+xUrVtRuQACMIUOkF14gOQUAAEpg5JSfYaoK4MPatpU6dTJTVlautDsaAPA9gweb/YYN0p499sYCAAB8BskpP8NUFcDHUXcKACoWGWkWkJCk5GR7YwEAAD6DaX1+hqkqgI877zzp+edJTgFARQYNkr77zowwveIKu6MBAAA+gJFTAOBJgwZJDoe0caO0c6fd0QCA7zn3XLNn+jMAAPgTySkA8KSICKl3b/Oagr8AUNaAAWa/cSN1pwAAgCSSUwDgec5V+5jaBwBlNWsmde9uXqek2BsLAADwCSSnAMDTiienKqkRBwB11sCBZk9tTAAAIJJTAOB5f/mLFBpqak799JPd0QCA76HuFAAAKIbkFAB4WsOG0jnnmNdM7QOAspx1p77/Xtq3z95YAACA7UhOAUBtoO4UAFQsMlLq2tW8pu4UAAB1HskpAKgNzuRUcrKUn29vLADgi6g7BQAA/kRyCgBqQ2ys1LSplJMjpaXZHQ0A+B7qTgEAgD+RnAKA2hAcLA0ebF4ztQ8AynImp777Ttq/395YAACArUhOAUBtcU7t++wze+MAAF/UooV0+unmdWqqvbEAAABbkZwCgNoyZIjZr14tHTlibywA4IuoOwUAAERyCgBqT8eOUtu20vHj0qpVdkcDAL6HulMAAEAkpwCg9jgcJ6b2UXcKAMpyJqe+/VY6eNDeWAAAgG1ITgFAbSI5BQAVa9VK6txZsizqTgEAUIeRnAKA2uRcsS89Xdq719ZQAMAnUXcKAIA6j+QUANSmli2lHj3M6+Rke2MBAF9E3SkAAOo8klMAUNuY2gcAFXMmp9avlw4dsjUUAABgD5JTAFDbhgwxe5JTAFBWdLTUqZOpO8XKpgAA1EkkpwCgtg0YIIWESBkZ0pYtdkcDAL6HulMAANRpJKcAoLY1biz1729eM3oKAMqi7hQAAHUaySkA8AZn3alPPrE3DgDwRc7k1DffSNnZ9sYCAAC8juQUAHjD0KFm/9lnUkGBvbEAgK+JiZE6dJAKC6UvvrA7GgAA4GUkpwDAG/r2lcLDpYMHzcgAAEBJ1J0CAKDOIjkFAN4QEiINHmxef/yxvbEAgC+i7hQAAHUWySkA8JZhw8ye5BQAlOVMTq1bJx0+bG8sAADAq0hOAYC3OJNTq1fz4AUApbVtK7Vvb+ryUXcKAIA6heQUAHjLqaeaLT+faSsAUB7qTgEAUCeRnAIAb2JqHwBUzJmcIoEPAECdQnIKALyJ5BQAVMyZnFq7VsrJsTUUAADgPSSnAMCbBg2SgoOln36Stm2zOxoA8C1t20odO5q6U0ztAwCgziA5BQDedPLJUr9+5vUnn9gaCgD4pKFDzZ4RpgAA1BkkpwDA25jaBwAVcyanSOADAFBnkJwCAG9zJqc+/dRMXQEAnOCc/vzzz0x/BgCgjiA5BQDe1q+fFBYmHTggrV9vdzQBKSUlRSNHjlR0dLQcDoeWLVtWafusrCyNGzdOnTt3VlBQkCZPnuyVOAGUg+nPAADUOSSnAMDbQkKkwYPNa6b21YojR46oZ8+emjdvnkvt8/LyFBkZqfvuu089e/as5egAVImpfQAA1CkkpwDADtSdqlXDhw/XrFmzFB8f71L7du3aae7cuRo/frzCw8NrOToAVXImpz77TCostDcWAABQ60hOAYAdnMmp1aul3Fx7Y0G15eXlKScnp8QGwAPOOktq0kTat09KT7c7GgAAUMtITgGAFxQUSCtWSAkJZl/QroPUvr30xx/SypV2h4dqeuSRRxQeHl60tWnTxu6QAL9W1Fcm1tO+7gPNQab2AQAQ8EhOAUAtS0qS2rUzC1CNG2f27dpJWzoxtc/fTZ06VdnZ2UXb9u3b7Q4J8Ful+8qZq83Uvj1vkpwCACDQkZwCgFqUlCSNGSPt2FHyeGamdNfHJKf8XWhoqMLCwkpsANxXXl/5iUxyKmzDKi1LOGpTZAAAwBtITgFALSkokCZNkiyr7GeWJX2uwSpQkPTjjxIjbgDUURX1lT+ps7YrRg2Up8WTUlVQYE98AACg9pGcAoBakppadsRUcYd0staon3lDTRWPys3NVXp6utL/LKSckZGh9PR0bdu2TZKZjjd+/PgS5zjb5+bmau/evUpPT9fGjRu9HTpQ51TcVzqKRk/12vuJUlO9GhYAAPAiklMAUEuysqpu87GY2lcb0tLSFBsbq9jYWEnSlClTFBsbq2nTpkmSsrKyihJVTs7269at08KFCxUbG6sRI0Z4PXagrqmsr3Qmp4bqE5f6VAAA4J9C7A4AAAJVVFTVbT7WME3Xg2bkVH6+FEK37AkDBw6UVd58yj8tWLCgzLHK2gOoPZX1lZ9piCSpl77VkdDdklp6JygAAOBVjJwCgFoSFyfFxEgOR/mfOxzSzpizZDVvLh04IKWkeDdAAPABlfWVe9VC69VLktT/98+8GxgAAPAaklMAUEuCg6W5c83r0g9dzvdPzA2RY9Qo8yYx0XvBAYCPqKqv/PTPqX1Bn1GbDwCAQEVyCgBqUXy8yTm1bl3yeEyMOR4fL7N+uiQtXSqWowJQF1XWV/afZpJT+uST8pc/BQAAfs9hUWQDVcjJyVF4eLiys7MVFhZmdziAXyooMCtSZWWZ+ipxcWa0gCTp+HGpRQspO9tM7YuLsy1O7vea4foBNVNuX3n8qNS0qZSXJ23cKJ1+ut1hSuJ+BwDAk6i8CwBeEBwsDRxYwYf160ujRkmvvSYtWWJrcgoA7FRuX9mwoekXP/3UjJ7ykeQUAADwHKb1AYAvGD3a7JcskQoL7Y0FAHzN0GJT+wAAQMAhOQUAvmDYMKlxY2nHDmntWrujAQDf4kxOrVgh/fGHraEAAADPIzkFAL6gQQPpoovMa1btA4CSevaUIiOl3FxTlAoAAAQUklMA4CuKT+1jrQoAOCEoSLr4YvP6rbfsjQUAAHgcySkA8BXDh5vCvxkZ0vr1dkcDAL5l7FizT0xkah8AAAGG5BQA+IpGjUyCSjKjpwAAJwwcKLVsKR04YFbuAwAAAYPkFAD4kjFjzD4xkal9AFBccLB02WXmdUKCvbEAAACPIjkFAL7kwgul+vWln3+WfvjB7mgAwLdceaXZL1smHT1qaygAAMBzSE4BgC8JC5POP9+8ZmofAJTUv7/Utq10+LC0fLnd0QAAAA8hOQUAvsa5al9ior1xAICvCQqSrrjCvGZqHwAAAYPkFAD4mosvlkJCpO+/lzZtsjsaAPAtzql9771nRlABAAC/R3IKAHxN06YnVu175hl7YwEAXxMbK3XqJB07Jr3zjt3RAAAADyA5BQC+aPJks3/lFbNsOgDAcDiksWPNa6b2AQAQEEhOAYAvGjRI6tlT+v136b//tTsaAPAtzrpTH31EAh8AgABAcgoAfJHDIf3f/5nXTz8tHT9ubzwA4EvOOEPq0UPKz5eSkuyOBgAA1BDJKQDwVVdcIUVFSVlZ0qJFdkcDAL7FWRidqX0AAPg9klMA4Kvq15f+8Q/z+sknJcuyNx4A8CXO5FRyskniAwAAv0VyCgB82c03SyedJH37rXkAAwAY7dtLZ51lEveMLgUAwK+RnAIAXxYRIU2caF4/8YS9sQCAr5kwweyffFI6dszeWAAAQLWRnAIAXzd5simQ/sEH0qZNdkcDAL5j4kSpdWtpxw7pxRftjgYAAFQTySkA8HUdO0qjRpnXjz9ubywA4EsaNJDuu8+8fvhh6ehRe+MBAADVQnIKAPzB//2f2b/8svTGG/bGAgC+5PrrpbZtTVH055+3OxoAAFANJKcAwB+cc450993m9XXXSStX2hsPAPiK+vWlBx4wrx99VDpyxN54AACA20hOAYC/eOQR6bLLpD/+kC69VPrpJ7sjAgDfMGGCdOqp0p490jPP2B0NAABwE8kpAPAXQUHSq69K/ftLBw9KI0ZIe/faHRUA2K9ePWnaNPP6scekw4ftjQcAALiF5BQA+JOGDaW33zYjBLZskS6+mALAACBJV10lnXaatH+/9NRTdkcDAADcQHIKAPxNZKT0wQdS06bSV19J11wjFRbaHRUA2CskRJoxw7x+/HHpxx9tDQcAALiO5BQA+KPOnaVly0wh4CVLpHvvtTsiALDf5ZdLZ54pHTpkFpL46iu7IwIAAC4gOeVnUlJSNHLkSEVHR8vhcGjZsmVVnrNy5Ur17t1bDRo00KmnnqrnWWYZCAwDBkgvv2xe/+c/0n//a288AGC34GDpww+lfv3M9L7Bg81IUwAA4NNITvmZI0eOqGfPnpo3b55L7TMyMjRixAjFxcVp/fr1+uc//6nbb79dS5YsqeVIAXjFVVdJDz5oXt96q3THHdIXXzDND0DdFRkpffaZdMEFpibfxRdLCxbYHRUAAKiEw7Isy+4gUD0Oh0NLly7VJZdcUmGbe+65R++88442bdpUdOyWW27Rt99+qy+//NKl38nJyVF4eLiys7MVFhZW07ABeJplSddfL73yyoljrVpJl14qxcdL555rVrJyAfd7zXD9AB/yxx/SDTdIr71m3j/yiHTPPZLD4ZGv534HAMBzGDkV4L788ksNGzasxLHzzz9faWlp+uOPP2yKCoBHORzSiy+aGlRXXy2Fh0u7dknPPScNHSq1bClde62Ul2d3pF7DFGgAqlfPjJi6+27zfupUafJkRpYCAOCDSE4FuF27dqlly5YljrVs2VL5+fnat29fuefk5eUpJyenxAbAewoKpBUrpIQEsy8ocOGkoCBp1Cjp9delPXuk5culG28001sOHpTWrZNCQ2s5ct/BFGgAkkzy/t//lmbPNu+fekoaN65OJesBAPAHIXYHgNrnKDV83TmTs/Rxp0ceeUQzZ86s9bgAlJWUJE2aJO3YceJYTIz05JMmz5SVJUVFSXFxpu5vuerXN7VWLrjAjJ5atUr6/XevxO8rhg8fruHDh7vc/vnnn1fbtm01Z84cSdLpp5+utLQ0Pf744xo9enQtRQnAayZPNqNIJ0yQ3nrLZP779ZP69pX69DFbZKTdUQIAUGeRnApwrVq10q5du0oc27Nnj0JCQtSsWbNyz5k6daqmTJlS9D4nJ0dt2rSp1TgBmMTUmDGmhFRxO3aY1dGLi4mR5s41JaUqFRxsak6hUhVNgX7ppZf0xx9/qF4FNbvy8vKUV2wEBiNNAe8qKJBSU11M3I8dKzVvbjrU3buld981m9Mpp5hk1axZUufOXokfAAAYTOsLcP3799cnn3xS4tjHH3+sPn36VPiwFRoaqrCwsBIbgNpVUGBGTLm6REVmpklkJSWdOL+8qYDVmiJYB1VnCrRkRpqGh4cXbSTyAe9JSpLatZMGDTIz9QYNMu+d/WK5hg41HeiqVdKcOWbFU2ci6rffpMTEOjUFGgAAX8HIKT+Tm5urzZs3F73PyMhQenq6IiIi1LZtW02dOlWZmZl67c+VaW655RbNmzdPU6ZM0Y033qgvv/xSL730khISEuz6RwBQjtTUklP5qmJZppSKs7bvHXeUnQo4dqxJSpU+7tKIqzrI3SnQEiNNAbtUNNLUmbhPTKyknzvpJOmvfzWbU3a29M030rffmhFUAADAq0hO+Zm0tDQNGjSo6L3zoWjChAlasGCBsrKytG3btqLP27dvrw8++EB33HGHnnnmGUVHR+upp56ihgrgY7Ky3D/HsqTt26XLLiv72Y4d0n/+U/a4Sw9udVB1pkBLZqRpKKMsAK+qbKRp8cT9qFGVTPErLTzcDL0q9t9YAADAe0hO+ZmBAwcW/TW/PAsWLChz7Nxzz9U333xTi1EBqKmoKO/8TrUf3AJc//799W7x2jOqego0AHtUNdLUmbhPTZUGDvRaWAAAoAaoOQUAPiAuzky5q2QGmccUf3ALVLm5uUpPT1d6erqkE1OgnSNLp06dqvHjxxe1v+WWW/Tbb79pypQp2rRpk15++WW99NJLuvPOO+0IH0AlXB1p+tln1NkDAMBfkJwCAB8QHGxqQUneSVBJ1ZtK6C/S0tIUGxur2NhYSWYKdGxsrKZNmyZJFU6BXrFihXr16qWHHnqIKdCAj3J1pOmsWWULpLN4BAAAvslhVTZHDJAp8BseHq7s7GxW7gNqWVKSqaVSVXF0h8P1lf0qkpxcdsoL93vNcP2A2ldQYJJOmZlV94POZH9iotmX7l9rsngE9zsAAJ5DcgpV4j++AO8qKDBT7rKyzAiBffvKrsbXpo30xBPSlCmuPaAV53CYB6+MjLI1p7jfa4brB3iHc7U+ybUEVUSEdOCA631l8aRWRQkq7ncAADyHgugA4GOCg8uOaLr00pIJq7g40y442DyguTqSyvnANWcOxdAB+K/4eJM4cmWkqWVJ+/e79/0sHgEAgHdRcwoA/IAzYTV2rNk7H5ScD2itW5ds36aNdNddZoRUcTExlY8EAABfVF5NqPh4aetW6f77a+c368LiEQAA+ApGTgGAn4uPN3/ZL29k1SOPlH8cAPxFebX4iteEGjLEFD+vLYG8eAQAAL6C5BQA2Kh0fanqJo/KmwpY2XEA8AfO2lKlpy1nZprjiYkmOR8T4379PVe5ujogAACoPqb1AYBNkpLMilODBknjxpl96WXPAaCuKigwI6bKSzg5j02ebPZz55q9s66ek/N9s2ZlP6uKw2GmSMfFuXceAABwH8kpALCBczRA6UK+ztEAJKgA1HWpqZUXOy9eE6qi+nsxMdKSJdL8+ea9qwkqFo8AAMC7SE4BgJe5OhqgoMCrYQGAT3G11pOznbNAenKytHCh2WdkmOMsHgEAgG+j5hQAeJk7owGoFwWgrnK11lPxdpXV2WPxCAAAfBfJKQDwMndHAwBAXRQXV3mhc4fDfO5OTSgWjwAAwDcxrQ8AvKw6owEAoK4JDq660Dk1oQAACAwkpwDAy5yjASoqzMsKUQBgVFbonJpQAAAEDqb1AYC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BAN26dUNERAQCAwPxzz//YNasWfj6669x8uRJp+Xx9OnTAIBnn30Wbm6mT2WFChUM1tFJSUmBl5cX2rZtixdffBEVKlSAj48PYmNj8eeff2LevHn4999/MW3aNJQrV85kqe2rr76KFStWAABat26NXr16oVy5ctBoNIiOjsacOXPw559/YuDAgShWrBjatWtn1THv2bPH6HFl5v79+4iJicGWLVswY8YM5duVESNGmF3v3r17Sprp06cjICDAovw6+jpKSkpSvkULDQ21qTZDhw4dUKtWLQBA1apVAWi/lXrjjTeUNIULFza6brdu3XDx4kW8/vrr6NKlC3x9ffHHH39g+vTp+Oeff7B+/XoUL14c8+bNszp/trL22jHHmuvD0vNsj/vcHGvvDXN69OiBDz/8EAkJCZg+fTratGljUKvj+PHjyjeK3bt3h4+Pj8F20tLS0L59e+zYsQMAULZsWbzxxhuoVasWChQogOvXr+PAgQP49ttvDdZ1xL2XFde5PfKtq6Hh6+uLihUrYtWqVZgxY4bet1ilS5dGREQE3nrrLXh7e5vNk61xML1169YhMjISly9fhpubG4oVK4b69eujb9++aNq0aZYdk63s8dlp6zZ0NZkA7XVjTvrlf/31l6pjVBsbsltMM8aWz7cuXbogJiYGw4YNw//+9z8ULlwYZ8+eRcmSJZU09nqWsoYzzqe92eMY7HUenH0+7969i1atWuHWrVsAgF69euGVV15BQEAAzp07h7lz52LhwoU4ceKETftxxDNRVrtw4QJWrFiBb775BufOncP169fxySef4JNPPkGtWrXQt29f9OjRA35+fhZv+5NPPlF+/+ijj/RqXWamRIkSyu83b960eN/ZQVbeB1m5L1uue0veuXJLPDIlLi4OU6dOBaCtza5rzVaqVCl4eXkhOTk5y8pIFi9ejP379wOAss/FixcrNcg6dOiADh06qN+gNSVaWVFz6s0331SWT5kyxWD548eP9UYkMbWd9MutnYyV/j148EBZ3rZtW7PnQUSU3vPr1q2rN//WrVtm22s/evRIwsPDlfNtrE+L9J0fL1q0yOh2Hjx4IC+++KIAkFKlSllVuyA1NVXq1Kmj7Ovw4cNm02f2Tenbb7+d6TchulEQ6tevr5dWbY0Be11HpixbtswhJdS6bartcwqArF692iBNQkKCVK9eXQDtcKt//PFHpvt2RM0pS68dtWy9PjI7z/a6zzOyx72RmY0bN4qnp6cA2lE7li9fLgcPHpQdO3bIhAkTlA5Gw8LC5Pr160a3MWfOHCVPHTt2lIcPHxpNl5qaKjExMXrz7HXvOeo6N8Ue+dbV8qhevbpeh9nGpipVqhicu4xsvc5F1H0WdujQwWQn5/Y+pvSsiTn2+Oy0dRtJSUnKoALVqlUzm9/0o2eaG53L1tjgrJhmCUs/31xcXDLta8Ye14M1ssP5zMjS+8kex2Cv85Adzufw4cOVPHz66acGy1NSUqR9+/ZWPzeKWPZMlJ1rTqX366+/yqBBg6Rw4cJ658bd3V06d+4s33//vep3j6tXryq1ssqXL29xXqKjo5X9t2jRwuL1TVHzOZrZpKZGSVbeB1m5L1vfBdS+c+WmeGTK0KFDBdD2cXXnzh29ZbVq1RJA+76fFXTlQqYmS2vsZ8vCqYcPHyrBrVq1aiZHZbhy5YryYGgqaDsqkMTGxirLu3XrZvY8iIgy5HeVKlUyTZtR+iB75MgRg+U1a9YUQPvyaM5ff/2lbGfHjh0W5+PTTz9V1s9sXyKmH7LDwsLkt99+y3T9ffv2iUajETc3N4OXTTUvZfa8jkzRFfgBkDNnzqheLzOWPry/9NJLJtMdOnRISffGG29kum9HFE5Zeu2oYev1IZL5eXbUfW7rvaHWn3/+Ka+++qpB1XsAUrRoUZk1a5YkJSUZXTd9p5MlSpSwaHhce957jrrOHZlvHx8fAaCMbFeoUCH58ssvJTY2Vh4+fCiHDx+W1q1bK+vXr1/f5L7scZ2LiBQoUEC6d+8uixYtkn379snx48fl559/lg8++EBvGOHGjRsb7czTnseUkaOaEmf22WmPbbRq1UpZbqzgVERk9erVeveeuevY1tjgrJhmCUs/3/r372+X/drjesgoO5zPjCy9n+xxDPY6D84+nw8ePBBfX18BIM8995zJguAbN25I/vz5rXpuFLHsmSinFE7pPHz4UNatWyft2rXT+5zUPXe8+eabcuLECbPbSB8Hx44da3Eedu7cadF1pJax2GzppKZwKivvg6zcl63vAmrfuXJLPDLln3/+Ue4tYwXoffv2FUDbZUdCQoJD8+II2bJZ39GjR3H37l0AQEREBFxcjPfbHhwcjBYtWpjt7M4eVdqCg4MN5qXvkNTd3T3TbXh4eAAAHjx4YDbdo0ePcPPmTSQlJSEtLQ0AICLK8hMnTqBmzZrK3zExMTh69CgAoGvXrma3XbFiRfj7+yMuLg4HDx5E8+bNM823zp49e/Dee+8BAAIDA/HFF19kuk76avwPHjzA+fPn8e2332LTpk3o1asX5syZg5deesnouo8fP8bAgQMhIhg1apTSDMAS9ryOjLl69apSZbFu3booV66cxXm0F3NNFOrUqYPKlSvjzz//xC+//JKFudKy5trJjD2uDzUcdZ/bcm+o9eTJE6xevRpbtmzRiyE6N2/eRGRkJMqVK4e2bdsaLI+OjlY6nXzttdcsaqblqHvP0de5vfKdnJwMQBvPXV1dsX37dtStW1dZXqtWLWzduhUvvfQStm/fjgMHDmDjxo3o0qWL3nbseZ3HxMSgUKFCBvPDw8MxbNgwtG7dGsePH8eePXvwxRdfYPjw4Q45Jkex9LPTXtuYOHEifvnlF6SkpCAiIgLnz59Hnz59ULx4cVy/fh0rVqzARx99BHd3d2WgAnPxwdGxwVExzZF69epl8Tr2uB7UyInnMyN7HIO9zoOzz+fRo0eVJrh9+vQx2ZSsaNGiaNmyJTZv3mzxPix9JspunednxsPDA126dEGXLl0QFxeH1atXY8WKFTh69Chu3ryJWbNmYdasWahRowYiIiLQp08fgya96Y+5fv36Fufh1KlTyu+ZDd5lCUe9U2aUlfdBVu3L1ncBS965cks8MuXdd9/FkydPULJkSQwdOtRgeeXKlQFoP/NOnjxp1T3kTNmycCr9zV+7dm2zaevUqWP2xSZ9r/X2lD9/fuX39CNjmaIbCcvT09NgWXJyMubNm4c1a9bgzz//NDvaRVxcnN7fR44cUX7v0aMHevTokWleAODGjRuq0gHAn3/+iY4dOyIlJQUeHh749ttvUbRo0UzXK1SokN7LUO3atdG9e3d88803iIiIQPv27bFkyRKjI9BNmTIFp0+fRmhoKMaPH686r+nZ8zoyZuXKlcpDb0REhNm0MTExyktvRoULF9ZrH28NNcf3559/4uzZs3j8+LGqIGsPllw7lpwje1wfatjzPk/PmnvDkvOTnJyMNm3aYO/evXB1dcXo0aPRr18/PPPMM3j48CEOHTqEjz76CPv370e7du0we/Zsg35sjh8/rvzeqFGjTI89PUfde9Ze52rPnb3ynT9/fqUw5+WXX9YrxNFxcXHBJ598gu3btwMAIiMjDQpy7HmdGyuY0ilatCjWr1+PihUr4vHjx/jss88MCqfsdUz2ZMtnp722UadOHSxZsgSvvfYaHj9+jA8//BAffvihXhpXV1fMmTMHw4YNAwAULFjQ5D5s+dxUw1ExzZGqVaumKp09rgdL5cTzmZE9jsFe58HZ5zN9oUZmhZe1atWyuHDK2udpU9R+ttk7nVr+/v4YPnw4hg8fjtOnT2P58uVYtWoVrl69iuPHj+P48ePw9fU1iGeXL19Wfq9YsaJF+wSg9H8DAM8//7zF65viqHfKjLLyPsiKfdnjurfknSu3xCNj9u/fr/S7NWXKFKVALD1d4RQAFk7ZS/rAGBgYaDatLUHdFukfLpOSkjJNr3uoz1j74NKlS3jxxRdx8eJFVfvNWBobGxurar2M7t+/ryrdxYsX0aJFC9y9exeurq6IjIxE48aNrdqnTu/evbF161Z8++23GDp0KNq3b6/3rcnff/+tdPL22Wef6XU6awlHX0fffPMNAG1Jebdu3cym/eCDD7B8+XKjyyIiIgyGxLaU2uMTEdy9ezdL7htLrx2158he14ca9rrP1TJ3b1hyDY0fPx579+4FACxZskTvg9zd3R3h4eFo2rQpWrRogaioKLz55pto2rSp3ktg+pe34sWLW3Qcjrr3rL3O1Z47e+W7YMGCyrXQunVrk+kqV66MEiVKICYmBocPH9ZblpXXOQA888wzCA8Pxw8//IBz587h2rVrCAoKUpbb45jsydbPTnttA9DWsKhevTo+/vhj/Pjjj0hMTASgLaxr2rQpPv74Y73/n6mOv83J7HNTrayOafag5jjt9b+0VE48nxnZ4xjsdR6cfT4t+QywdGAKRzxPq/1ss3c6axQrVgylS5dGcHAwrl69ajZt+ncbSztTv3//PrZt2wZAW7hgbqCP7Cor7wNH78te170l71y5JR4Z8/bbbwPQFp6bqpCSvnAq/aA1OUW2LJxKX/U6s9EZjDVXSS/9tyDWCg4ONvjWOX/+/EoTucyC7N27d5ULNiQkRG9Z7969cfHiRWg0GvTr1w/du3dHxYoVERAQoJSGpqWlKSNtZTze9N8Mrlq1SvU3jGoe9q5du4bmzZvj2rVr0Gg0+Prrr9GxY0dV289M+/bt8e233yI5ORnbt29Hz549lWWzZ8/G48eP8cwzz+D+/ftYs2aNwfrp/6+7du1SaoK1a9dOeQmw53WU0ZEjR5QRl1566SWrXhLsyd7HZytHXjv2uj7UsNd9bglz94YaIoKlS5cCAMqVK2fyGyY3NzdMmjQJL7zwAtLS0rB06VLMnj3baFpLRsnR5UHtupZcm46+zu2V75CQEOWay6wKf0hICGJiYgy+aMjK61ynUqVKSm2wmJgYvcIpexyTPdn62WmvbehUr14d3377LVJTU3H9+nU8fPgQQUFBKFCgAABg9erVStpKlSpZdcy2xgbAOTHNVhlHGjXGnv9LS+TE85mRPY7BXuchN5xPYxz5TJSdPXnyBNu2bcOKFSuwdetWvdonJUqUwCuvvIIWLVoYrJcvXz7ld3M1II1ZvHixcl107NjRbK1hSznqnTKjrLwPHLkve133lr5z5dZ4tHbtWhw6dAiAtgmyqa4n0suqEfvsyarCKd3J0FWvM0X3T7JU+lLymzdvmm1XmtnDrz36olm6dKnRKvQVK1bEvn37cO7cOaSkpJgcYvLvv//WWyf9fF3V0zFjxuDjjz82ur6pKrYAUKRIEeV3jUZjtyqncXFxCA8Px4ULFwBov7nv06ePXbYN6H/j9O+//+ot01WLvHDhgqpmipMmTVJ+v3jxovJSZs/rKKMVK1Yov2dWvRQAli1bZnPtKHNu3rxpNhjqjk+j0Ti8IM3aa0ftObLX9aGWrfe5pUzdG2rPz82bN3Hnzh0AQI0aNcymTd9sIX3+AW11fJ1r166hfPnyme5bx1H3nrXXudpzZ698V65cWak1lNmDtW55xusqq69zwPwLuz2OyV7s8dlpj20Y4+rqarTwzh7NTMx9bloiq2Oaoznqf6lWbjif9jgGe50HZ57P9J8bsbGxZj8Dbt26pWqbjnyeVvvZZu90mTl06BC++eYbrFmzBrdv31bme3p6okOHDoiIiEB4eLjJl+v0tdZiYmJUP7cmJSVhxowZALSx+P333zdIs27dOnTt2hXz589HyZIl8cknn+Do0aPw9vbOtMsTR75TZpSV94Ej9mXP697Sdy5d/nJ6PErv8ePHRq/nzOTEwqnMi9yM0FVzu3fvntl0Z86csWbzejd/Zs0CHNlsIDMvvPACAG0hnK5TcmP27Nmj/N6gQQPl9z///FP5vXv37ibXT9+vVEbpXz5//vln8xlWKT4+Hi1btlRKqadNm4YhQ4bYZds6uo6WAcdVf3TUdfTkyROlFkNAQIDZJi5ZRe3xlS1b1qH9TWXFtZPVbL3PLWXrvZH+gzMlJcVs2idPnhhdDwCee+455XddE0G1HHXvOfo6t1e+0/fRdf78ebPb0T242drvnD3o7lsAerWmgOx1TPb47LTHNtR6/Pgx1q9fD0B7Tqzt/8Fen5tZHdMcLSv/l8bkhvNpj2Ow13lw5vlM3xwms+tFzfWUG5+JTLl06RImT56M8uXLo27duvj888+Vgqn69evjq6++wvXr17F69Wq0bNnSbK2P9AX46f/PmRk9erTeQC7GvrCPjo4GAGzduhXdunVDqVKlMGzYMLz22muq95MVsvI+sPe+7HndW/vOlRviUXrz58/HhQsXoNFosGDBAkRGRpqddOfp3r17uHLlit3z41DWDPE3e/ZsZWjFv//+22iaR48eSVBQkMnhT9MPE5pxWfrhvMPCwkwO5Xr16lVxd3d32hCr6YcuHzRokNE0qampUrFiRcF/Q2+nH6J7zZo1yvrmhoju0KGDks7Y0MuVKlUSAJI/f375999/bTqm5ORkadCggbK/Dz74wKbtmdKmTRtlH5kNgW6MmiHUHXUdbd68WUk7YsQIi/Ouhrn/t076c/C///3PZLrDhw8r6d54441M923tsO5Zde2ooeb6EFF3nm29zy1l672RmpoqPj4+AkCCgoLkyZMnJtNu2bJF2dewYcMMthMSEiIAJDg4WBITE1XnwZ73nqOuc0fmOy4uThnmNzw83OT+du/erWzj1VdftTi/aq9zNc6fP6/k+ZlnnjFY7shjsjTm2OOz016fv2rMmDFD2cakSZOs2oaIutiQHWOaNXlMf21nJiv/l8Y4+3xmZM1nuD2OwV7nwZnn88GDB+Lr6ysA5LnnnjP5GXDjxg3Jnz+/2c+u7PRM5Cj37t2TxYsXS6NGjUSj0SjHCkBCQ0Plgw8+kH/++cfi7R47dkzZTqVKlVT9fz///HNlnSpVqkhycrLRdLo4GhwcLOfOnbM4b1klK+8De+7L3te9te9cuSEe6dy5c0f8/PwEgHTs2FHVOunLarZu3WrX/DiaVYVT6YPGa6+9ZrA8LS1NXn/9db0gZUnhlIjIm2++qSyfPn26wfInT55I69atze4jKzRs2FAAiJubmxw4cMBgefqH0owPQ0ePHlWWDR482Oj2FyxYoHeMxh6oVq9erSyvWbOmxMbGmszvw4cP5fPPP5cHDx4YLHv06JG0aNHCqiCgs3TpUqPbTm/WrFnKPkqVKmX25dkUtS9ljriOOnfurKQ9evSoxXlXw9KHdwCydu1agzSJiYlSo0YNASAuLi5y4sSJTPdtzYOtPa4de7Jn4ZSIbfe5TlbdGyIiPXr0ULYzYcIEo2nu3LmjFGwDkJ9++skgzbx585TlHTt2lEePHhndVmpqqsTExOjNs9e956jr3BR75Xvw4MHK8sjISIPlCQkJEhYWpqT5/fffLc6r2uv8+++/N3st3bhxQzl/AGTmzJlG0znqmCyNOfb47LTX56+ImP1S6Pvvv1cK9cqWLWs0BtgzNmRlTLOWpZ9vmbHn/9JazjyfGVn7BZM9jsFe58GZ53PYsGHKtj/99FOD5ampqdK+fXuznwH2fCZq3LixU99zzElfQAdAChQoIK+88or88ssvJgv21HrppZeU7fbr109SUlKMprt//7688847StrQ0FCzhU7FixcXALJz506b8pcV7HUf6NKULFnSoftyxLuALe9cuSEeiTx9LtVoNKqfb3/44QclT1OnTrV7nhzJqsIpEZG6devqffjt2rVLjh49KmvWrJEmTZoIAKlXr57JgJpZ4dS9e/ckODhYSdOjRw/Zvn27HD16VCIjI6V27doCQPnprKB97Ngx8fT0FADi7e0tU6ZMkYMHD8quXbtk4MCBSt7KlSsnCQkJeuumpaVJlSpV9I5x69atcvToUfnuu++kS5cuAkCvBNrURR8REaGk8ff3lw8++EB+/vlnOX78uOzfv1+WL18uAwYMUEpejdWC6NSpk7KNF198Uf744w85efKkyenMmTMG2yhZsqT4+fnJa6+9JsuXL5f9+/dLdHS07Nu3TxYsWKB3LO7u7rJjxw6rzrvalzJ7X0d37twRDw8PAbTfzDiKpQ/vtWrVEldXV3njjTdk165dcuTIEfn666+lfPnySpqMNWN09u3bJ0uXLlWmTz75RFmnQYMGesuWLl1qdBv2uHbsyd6FU7bc5zpZdW+IiJw+fVoKFCigbK9du3ayfv16OXbsmBw4cEBmzZoloaGhyvJmzZoZ3U5qaqqEh4frHd+cOXNk//79cuzYMdm2bZuMGzdOypYta3AO7XXv2es6V8te+Y6NjVXOsZubmwwdOlTJ89KlS6VChQrK+qZeqDOj9jovWbKkBAUFybBhw2T16tVy4MABOX78uOzYsUM++OADKVKkiLKdF154QR4+fGh0O/Y6Jltjjj0+O+35+VuwYEFp0aKFLFq0SA4cOCBHjhyR9evXS7du3ZR1CxcuLMeOHTP5/7FXbMjKmGYtSz/fMmPP/6W1nHk+7fEZbq9jsNd5cOb5vH37thQrVkzZR69eveTHH3+Uo0ePytq1a6V+/foCQOrUqaOkuXTpkt427PlMlJ0LpwDtC3OjRo1kyZIlFtWwzszNmzeV2tsApGrVqvL555/Lr7/+qjx/jBkzRq+VTtWqVQ3+F+nFxsYKoK0ZnRPY6z7QpTNXOGWPfdn7XcDWd67cEI8uXLig1NTv0qWL6vXOnj2r95mYk1hdOHX69GkJDAxUDjzj9Oabb5otgMqscEpE5NSpU3ofEBmnfv36qdqOo33//fdKMxpjU7ly5eTs2bNG1z1+/LjSjMTYVLVqVbl27VqmD1QpKSkyevRocXV1Nbkt3eTl5SX379832EZm62WcjAW5kiVLqlo3ODhYfv75Z6vPuSXNWex5HX3xxRdKuhkzZlid/8yoeYBOfw4uXLggpUuXNnmMnTt3NvlNe/qCTTWTufzacu3Yk70Lp0Rsu89Fsu7e0NmxY4f4+/tnur8XX3xR7ty5Y3I7ycnJysuducnYObTHvWev69wS9ooZf/31lzz77LNmz1v//v2trgJuSeGUmmuvc+fOcvfuXbP7tMcx2SPm2OOz016fv15eXmbzX6lSJZMFUyL2jQ1ZGdOspSaPlhROidjvf2kLZ51Pe9xP9jwGe50HZ51PEZHo6GgJCAgwue++ffvKkiVLlL9v3Liht74l/w/A/DNRdi6cGj9+vJw/f95h24+JidErVDY1FShQQMaMGWPyixWdn376SQDIhx9+6LA825s97gM115k99mXP617EPu9cOT0e6b7k0mg0curUKdXrpaSkKLW2HVmZwhGsLpwS0fa7MXjwYClZsqS4u7tLQECAtGrVSn744QcRMV8ApbYw4Pbt2zJ69GgpW7aseHh4iL+/vzRt2lRWr15t0XYc7dKlSzJq1CgpV66cFChQQAoVKiS1atWS6dOnm2z3rPPvv//K66+/LiVLlpR8+fKJn5+f1KlTRz799FOlqr/aB6ozZ87IW2+9JTVq1JDChQuLq6urFCxYUCpXriy9evWS5cuXmyzVtUdQOXfunHz55ZfSrVs3qVatmhQtWlTc3NzE29tbypQpI507d5alS5dmek4yY0nhlIj9riPdN2aurq4GzZjsSc3/O+PD+507d+T999+XihUrSoECBcTX11caNWokK1euNLsvFk6pf1Gx5T7Pqnsjvbi4OJk+fbo0adJEAgICJF++fOLp6SmlS5eWrl27ynfffae66v2uXbukd+/eUrp0afH09JSCBQtKhQoVpFOnTrJ69WpJSkoyup6t9569rnNL2StmJCUlySeffCLPP/+8+Pn5ibu7uwQHB0u3bt1k165dNuVR7XW+e/dumThxorRq1UrKlSsnfn5+4ubmJoUKFZKqVavKoEGDjFZVd9Qx2etl2h6fnfbYRmRkpPTr108qV66snI8SJUpI69atZcmSJZkWPtozNmRlTLOWNZ9vatjzWcpazjif9iycstcx2Os8OON86ty6dUveeustk58B6ft0ydgs157PRNm5cCqr/PDDD9KnTx959tlnpWDBgnrnrkSJEma7M0lv2rRpAkC+//57B+fYvmy9Dyx59rZlX/Z+F7DXO1dOjUeHDh1S+nLr1q2bxevrarPny5fPZLcc2ZFGxMzY0UREucgXX3yBRYsW4eTJk/jggw8wYcIEZ2eJiChbYHwkUm/AgAFYsmQJgoODc95oWLlA7969sXLlSgDA4sWL8eqrr2a6To8ePbBmzRpcuXIFwcHBJtMxFhI5j+lxPImIsoH169cjKCgIhQsXxowZM2zaVvHixTFx4kR06NDBPpkjInIixkeirPfgwQNs3rwZAFC3bl0n5yZvmjdvHooVKwYAePPNN/HFF19kGgujo6MREBBgtmAKYCwkciY3Z2eAiMiUxMREDBw4EPPnz0fBggXRv39/tG7dGlWrVrVqe7oHDd1DJRFRTsX4SOQY58+fxzPPPAONRmOwLDU1FYMHD0ZcXBwAICIiIquzRwAKFy6Mr776Cu3bt0dCQgKGDx+OZcuWwcfHx2gsvH//Pv755x80b948020zFhI5DwuniCjbevDgAUQE1apVg7e3NwoVKoSUlBRnZ4uIyOkYH4kcY9KkSfj999/RvXt3PP/88wgMDMSDBw/wxx9/YNGiRTh27BgAoFmzZmjbtq2Tc5t3/e9//8OXX36Jc+fOYf78+fD390f58uWNxsI//vgDaWlpqFGjhpNyS0RqsFkf5XiHDx9G3759UbJkSXh4eKBIkSJo27Yt9u3b59R8JSUlYeTIkQgKCkL+/PkRFhaGNWvWqFo3MTERo0ePRosWLRAQEACNRmO0zfvu3buh0WiMTr/99pvZfSxevBgajQbe3t425d2W48xMYGAgOnTogKpVq6J06dLo1q2b0x4sPvroI1SqVAlpaWnKvF27dqF///6oUKECvLy8UKJECbRv3x5Hjx61ej9LlixBiRIlkJycbI9sUx6Xl+Ojzv79+9GmTRsULlwYnp6eKFu2LCZNmqSXJjo6Gm3btkVoaCg8PT3h5+eHevXqKX2a6Fhyz9sSn9VwRnxMTk7GqVOnDKYhQ4agTJky+OOPPwyWrVixAg0bNjR7/tWyd3w0dTxqpidPnuTYfedW5s7pmjVr0L59ewQFBcHd3R2FChVCo0aNsHz5cqPn9PTp0xg/fjxatWqF5557Dg0aNMDgwYOVgqkGDRpg7dq1RmtXWSIrYmHfvn1NxqKM8UhtjLM0vjnqWXHQoEH45JNP0L17d7Rq1cpkLKxbty5EBNOmTbN5n+YYe1a05DPLEeeJz5WUozi1O3YiG40dO1ZcXFykWbNmsmzZMtm1a5csW7ZMqlWrJi4uLnYfwcsS4eHhUqhQIfnyyy9l165dMmDAAAEgq1atynTdixcvKqOQ6dYzNrpQVFSUAJApU6bIwYMH9abExEST27969ar4+vpKUFCQeHl52ZR3W45TjT59+igje2zfvt1omhdffFE8PDyMTmPHjjVI/+qrr1o0WlNMTIx4eXnJunXr9OZ36dJFmjZtKgsWLJDdu3fLunXrpG7duuLm5iY7d+606Dh1njx5ImXLlpVx48ZZtT6RTl6PjyIiq1atEhcXF+nevbt8//33smvXLlm0aJFMnDhRL11UVJQMGjRIvvnmG9m1a5ds2bJFunfvLgBk0qRJSjpL7nlr47Mlsjo+6o7JmmnRokUmz79a9o6PthyPrSOnOXPfuZW9zunff/8tH3/8sTRp0kRKly4t3t7e4uHhIUFBQfK///1PVq1aJampqXbJc1bEwnPnzhnEoIMHD4q/v7+UKFFCUlJSlLRqY5yl8S0vPyta8pnliPPE50rKSVg4RTnWuHHjBIB88sknBssePnwoZcqUEV9fX7l3716W5+2HH34QAMqQwzrh4eESFBSk9yBgTFpamqSlpYmIdjjjzAqnMn4QZuall16Sdu3aSUREhEHhlCV5t/U4M7N//37RaDTStm1bASBTp061aXs6lj5wjB49WkqUKGHwMHrz5k2DtImJiVK0aFFp1qyZ1fn79NNPxdfX1+FDZVPuxfioLYT38vKSwYMHW53X559/XkJCQpS/LbnnrY3PajkjPmaHAhV7xkcWTuUutpzTEydOZHl+syoWGrN7924BYFAoozbGWRLf8vqzotr/kyPPE58rKadgsz7KkX777TdMnjwZERERePvttw2We3h4YODAgYiPj8fOnTuzPH+bNm2Ct7c3Xn75Zb35/fr1w7Vr13Do0CGz6+uqRjvCypUrsWfPHixYsMDockvybutxmpOamoqhQ4ciODgYy5cvh6urK6Kjo63eHgCkpKTg4cOHSE1N1fvdnMePH2PJkiXo2bMnXFz0Q2ZgYKBBem9vb1SqVMmmoaV79eqFhIQEuzWPpLyF8VFr8eLFSE5Oxrvvvmt1Xv39/eHm9rR7Tkfd85ZyVnxs0qQJRPvFJkQEjx49QpEiRfDOO+/ozRcRpdnKpUuXICIoVaqUTfnTsWd8zHg8lky2Ho8z951bZTynBw8ehIuLCyIiIkyey+nTpwMAzp07l+X5deaz4pIlS6DRaNC/f3+9+Y6IcXn9WVHt/8mR54nPlZRTsHCKcqRJkyZBo9Hgo48+MpnmmWeeAQBcvXpV9XZFBCkpKaomc06dOoWKFSvqvdQAQLVq1ZTl9jRkyBC4ubnBx8cHLVu2xP79+42mi42NxciRIzFt2jSTQ+lakndHHueXX36J6OhofPLJJyhSpAjKli1r8wPH5MmT4enpiWXLluHjjz+Gp6cnvvnmG7PrHDp0CLdv30bTpk1V7SM+Ph7Hjh1D5cqVrc5nsWLFUKFCBfzwww9Wb4PyLsZHrb1798LPzw9///03wsLC4ObmhsDAQLz++utISEgwuk5aWhpSUlJw69YtLFiwAD/99FOmhVuZ3fNq47MlckJ8tOb8q8H4SGoxFhoXHx+P9evXo1mzZihdurSq9KZinJr4xmdFdRx5nhg3Kadg4RTlOPHx8fj555/RokULhIaGmkyXlJQEAPDy8lK97T179iBfvnyqpkuXLpnczu3bt+Hn52cwXzfv9u3bqvNkjq+vL0aMGIGvvvoKUVFRmDt3Lq5cuYImTZrgp59+Mkj/xhtvoHz58hg8eLBd8u6o47x16xY+/PBDNG7cGN26dQOg/XA+e/Ys7t+/b9U2AWDChAkG35r27dvX7DoHDx4EADz33HOq9jFkyBAkJyfjgw8+sDqfuv39+uuvNm2D8h7Gx6diYmJw//59vPzyy+jWrRt++eUXvPPOO1ixYgXatGkDETFY54033kC+fPkQGBiIUaNGYd68eRg0aJDZ/Zi65y2Nz2rllPhozflXi/GRMsNYaFpkZCQePHiAV199VVV6YzHOkvjGZ0V1HH09MG5STuCWeRKi7OXkyZNISUlB1apVzabTfVDovnFQo2bNmjh8+LCqtEFBQWaXm6vCa68mezVq1NAbkaRhw4bo2LEjqlatitGjR6Nly5bKsg0bNmDLli04fvx4pvu3JO+OOM733nsPCQkJmDdvnjKvWrVq+Pbbb/HHH3+gbt26Vm3XGteuXYNGo4G/v3+maT/88EOsWrUKn332GWrWrGnTfgMDAxEbG4uUlBSDb9GITGF8fCotLQ0PHz7E+PHj8d577wHQNvtxd3fHyJEjsXPnTjRv3lxvnffffx8DBgxAbGwstmzZgqFDhyI5Odlo80jA/D1vSXy2RE6Jj9acf7UYHykzjIWmLVmyBEWKFEHHjh0zTWsqxlka3/isqI4jrwfGTcoJeGVSjqNrDhAQEGAyTWJiIiIjI1G6dGnUqlULANC+fXu9/lWSk5Oxb98+vPDCC8o8b29vhIWFqcqHucBepEgRo99w3LlzBwCMfjNiL4UKFcJLL72EL7/8Eg8ePICnpyeSkpIwZMgQDBs2DEFBQbh37x4AbRt5ALh37x7y5csHLy8vi/LuiOP8/fffsXTpUvTp0wehoaFKXnVV76Ojo7P0gePBgwfIly8fXF1dzaabOHEiJk+ejI8//hhDhw61eb/58+eHiODhw4fw9va2eXuUNzA+6u/n7NmzBi9JrVu3xsiRI3Hs2DGDwpHQ0FCllkWbNm0AAGPGjEFERITBObXmnjcWny2Rk+KjNedfLcZHygxjoXF//PEHjhw5ghEjRsDDw8NsWktjnKn4xmdFdRx9PTBuUk7AZn2U4+j6SjJXVXrGjBlITEzE+PHjlW8aNm/ejKSkJCQlJeHVV19Fp06dUK9ePb317FVVu2rVqjh9+rRBfwMnT54EAFSpUsWKI1dP11xCd+xxcXG4efMmZs6cicKFCytTZGQkkpOTUbhwYfTq1cvivNv7ONPS0jBkyBCICJYvX66X1549ewKAzX0JWMrf3x+PHz9GcnKyyTQTJ07EhAkTMGHCBLz//vt22e+dO3fg4eHBBwiyCOPjU6ZqQujiY8ZOa42pU6cOUlJScOHCBb35ttzzGeOzWjktPtrj/JvC+EiZYSw0bsmSJQCAAQMGmE1nbYwzFt/4rKiOo68Hxk3KEawe54/ISdLS0qRMmTLi5+cnd+7cMVj+zTffiIuLi3Tt2tXo+u+99560bt1aHj16ZLAsISFBDh8+rGoytr7Otm3bBICsWbNGb36rVq0sHg7W0uGB79y5IyVKlJCwsDBl3oMHDyQqKspgatmypeTPn1+ioqLk5MmTFufdnscpIvLll18KAJk4caLR/Pr5+cnzzz9v0TZttWLFCrPDTH/00UdGh2O2VXh4uNSoUcOu26Tcj/HxqZ9++kkAyMcff6w3f9asWQJA9u3bl+n2e/fuLS4uLhIbG6vMs+WeNxaf1cpp8dEe598UxkfKDGOhoYcPH4qfn5/UqVPH7LasjXGm4hufFZ8y93+y93nKiHGTcgIWTlGOtGvXLsmfP7+UKVNGFi5cKLt27ZLVq1fL//73PwEgffv2lcePHxusN3HiRGnatKk8ePDA4XkMDw+XwoULK/l77bXXBICsXLlSSbN7925xdXWViRMnGqy/bds2WbdunXz99dcCQF5++WVZt26drFu3TpKTk0VEpEePHvLuu+/KunXrJCoqShYuXCjly5cXNzc32bFjR6Z5jIiIEC8vL6vybk1ac27fvi1FihSR+vXrS1pamtE0TZs2lQIFCkhqaqpF27bF5cuXBYB89dVXBss+/fRTASCtWrWSgwcPGkzWSk1NFV9fX3nzzTdtyTrlUYyPyUq6du3aiYeHh0yaNEl27NghU6dOlfz588tLL72kt73XXntN3nrrLVm7dq3s3r1b1q9fL926dRMA8s477yjpLLnnbY3P6eXE+Cii/vxbgvGR1GIsTNZLu2bNGgEgCxcuNJkftTHO0viWl58VRdT/n+x1njJi3KScgoVTlGOdOHFCunbtKkWLFhUXFxcBICVLljT50D9z5kypV6+eJCYmZkn+EhMTZfjw4VKsWDFxd3eXatWqSWRkpF6aqKgok9+glCxZUgAYnS5evCgiIlOnTpWwsDDx9fUVV1dXCQgIkI4dO8rvv/+uKo+mCqfU5N2atOYMGjRI3NzclBpcxowcOVIAyOnTpy3evi0aNmwobdq0MZjfuHFjk/8jWyqm7ty5UwDI0aNHbck25WGMj1r379+Xd999V0JCQsTNzU1CQ0NlzJgx8vDhQ73tff3119KwYUPx9/cXNzc3KVSokDRu3Fi++eYbvXSW3PO2xuf0cmJ8FFF//i3B+EiWYCx8Kjw8XLy8vCQhIcFkftTGOEvjW15+VhRR/3+y13nKiHGTcgqNiA1j+RJlI71798batWtx4MABpWNLnS+++AKLFy/Grl274Ovr66QcUk61YcMGdOvWDf/++y9KlCjh8P317t0bFy5c4JC/ZDeMj+QojI+UkzAWkqNkdSy0BOMm5RQsnKJcIyEhAdWrV4e7uzuOHTsGLy8vZVmhQoXw8OFDvVFToqKiULt2bWdklXIYEUH9+vVRs2ZNzJ8/36H7On/+PCpWrIhdu3bpjQ5EZAvGR3IUxkfKSRgLyVGyMhZagnGTchLT45sS5TA+Pj64ePGi0WW6IWaJrKHRaLBo0SJ8//33SEtLs2mUqcxcvnwZ8+fP5wME2RXjIzkK4yPlJIyF5ChZGQstwbhJOQlrThERERERERERkdNkjyJdIiIiIiIiIiLKk1g4RURERERERERETsPCKSIiIiIiIiIichoWThERERERERERkdOwcIqIiIiIiIiIiJyGhVNEREREREREROQ0LJwiIiIiIiIiIiKnYeEUERERERERERE5DQuniIiIiIiIiIjIaVg4RURERERERERETsPCKSIiIiIiIiIichoWThERERERERERkdOwcIqIiIiIiIiIiJyGhVNEREREREREROQ0LJwiIiIiIiIiIiKnYeEUERERERERERE5DQuniIiIiIiIiIjIaVg4RURERERERERETsPCKSIiIiIiIiIichoWThERERERERERkdOwcIqIiIiIiIiIiJyGhVNEREREREREROQ0LJwiIiIiIiIiIiKnYeEUERERERERERE5DQuniIiIiIiIiIjIaVg4RURERERERERETsPCKSIiIiIiIiIichoWThERERERERERkdOwcIqIiIiIiIiIiJyGhVNEREREREREROQ0LJwiIiIiIiIiIiKnYeEUERERERERERE5DQuniIiIiIiIiIjIaVg4RURERERERERETsPCKSIiIiIiIiIichoWThERERERERERkdOwcIqIiIiIiIiIiJyGhVNEREREREREROQ0LJwiIiIiIiIiIiKnYeEUERERERERERE5DQuniIiIiIiIiIjIaVg4RURERERERERETsPCKSIiIiIiIiIichoWThERERERERERkdO4OTsDlDOlpaXh2rVrKFiwIDQajbOzQ0R2JiJITExEUFAQXFz4PYYlGB+JcjfGR+sxPhLlboyPZAsWTpFVrl27hpCQEGdng4gc7MqVKwgODnZ2NnIUxkeivIHx0XKMj0R5A+MjWYOFU2SVggULAtAGHh8fHyfnhojsLSEhASEhIcq9TuoxPhLlboyP1mN8JMrdGB/JFiycIqvoqmL7+Pjw4YIoF2OzC8sxPhLlDYyPlmN8JMobGB/JGmwISkRERERERERETsPCqRxu7969aNeuHYKCgqDRaPDdd99lus6jR4/wwQcfoGTJkvDw8ECZMmXw9ddfOz6zREREREREREQZsFlfDpecnIzq1aujX79+6Ny5s6p1unbtips3b2LJkiV49tlnERsbi5SUFAfnlIiIiIiIiIjIEGtO5XCtW7fG5MmT0alTJ1Xpf/zxR+zZswfbtm1D8+bNUapUKdSpUwf169d3cE6JiIiIKCtYWrN+//79aNCgAYoUKQJPT09UqFABs2fPNki3YcMGVKpUCR4eHqhUqRI2bdrkoCMgIqK8hoVTecz333+PWrVqYcaMGShRogTKlSuHt99+Gw8ePDC73qNHj5CQkKA3EREREVH2o6tZP3/+fFXpvby8MHToUOzduxenT5/G2LFjMXbsWCxcuFBJc/DgQXTr1g29e/fGiRMn0Lt3b3Tt2hWHDh1y1GEQEVEewmZ9ecyFCxewf/9+5M+fH5s2bUJcXBzeeOMN3Llzx2y/U1OnTsXEiROzMKdEREREZI3WrVujdevWqtPXqFEDNWrUUP4uVaoUNm7ciH379mHgwIEAgDlz5iA8PBxjxowBAIwZMwZ79uzBnDlzEBkZad8DICKiPIc1p/KYtLQ0aDQarFq1CnXq1EGbNm0wa9YsLFu2zGztqTFjxiA+Pl6Zrly5koW5JiIiIqKscvz4cRw4cACNGzdW5h08eBAtWrTQS9eyZUscOHDA5HZY856IiNRi4VQeU7x4cZQoUQK+vr7KvIoVK0JEcPXqVZPreXh4wMfHR28iIiIiotwjODgYHh4eqFWrFoYMGYIBAwYoy27cuIGiRYvqpS9atChu3LhhcntTp06Fr6+vMoWEhDgs70RElLOxcCqPadCgAa5du4akpCRl3j///AMXFxcEBwc7MWdERERE5Ez79u3DkSNH8OWXXxptrqfRaPT+FhGDeemx5j0REanFPqdyuKSkJJw7d075++LFi4iOjoafnx9CQ0MxZswYxMTEYMWKFQCAnj17YtKkSejXrx8mTpyIuLg4vPPOO+jfvz88PT2ddRhERERE5GSlS5cGAFStWhU3b97EhAkT0KNHDwBAsWLFDGpJxcbGGtSmSs/DwwMeHh6OyzAREeUarDmVwx05ckSvE8s333wTNWrUwLhx4wAA169fx+XLl5X03t7e2LFjB+7du4datWqhV69eaNeuHebNm+eU/BMRERFR9iMiePTokfJ3vXr1sGPHDr00P//8M+rXr5/VWSMiolyINadyuCZNmkBETC5ftmyZwbwKFSoYPFwQERERUe5gac36zz//HKGhoahQoQIAYP/+/fj0008xbNgwZRsjRoxAo0aNMH36dLRv3x6bN2/GL7/8gv3792ftwRERUa7EwikiIiIiolzkyJEjaNq0qfL3m2++CQCIiIjAsmXLDGrWp6WlYcyYMbh48SLc3NxQpkwZTJs2DYMGDVLS1K9fH2vWrMHYsWPx4YcfokyZMli7di2ef/75rDswIiLKtTRirtoNkQkJCQnw9fVFfHw8R+4jyoV4j1uP544od+M9bj2eO6Lcjfc42YJ9ThERERERERERkdOwcIqIiIiIiIiIiJyGhVNEREREREREROQ0LJwiIiIiIiIiIiKnYeEUERERERERERE5DQuniIiIiIiIiIjIaVg4RURERERERERETsPCKSIiIiIiIiIichoWThERERERERERkdOwcIqIiIiIiIiIiJyGhVNERJQj7d27F+3atUNQUBA0Gg2+++47s+n379+PBg0aoEiRIvD09ESFChUwe/Zsg3QbNmxApUqV4OHhgUqVKmHTpk0OOgIiIiIiIgJYOEVERDlUcnIyqlevjvnz56tK7+XlhaFDh2Lv3r04ffo0xo4di7Fjx2LhwoVKmoMHD6Jbt27o3bs3Tpw4gd69e6Nr1644dOiQow6DiIiIiCjPY+EUUS61f/9+tGnTBoULF4anpyfKli2LSZMmKcujo6PRtm1bhIaGwtPTE35+fqhXrx5WrlypavuJiYkYPXo0WrRogYCAAGg0GkyYMMFo2r59+0Kj0ZicfvvtN730x48fR4cOHRAUFIQCBQqgQoUK+Oijj3D//n2rzwflPq1bt8bkyZPRqVMnVelr1KiBHj16oHLlyihVqhReeeUVtGzZEvv27VPSzJkzB+Hh4RgzZgwqVKiAMWPGoFmzZpgzZ46DjoKykiWx6Pfff0fLli1RsGBBeHt7o2nTpvj1118z3ceuXbvQv39/VKhQAV5eXihRogTat2+Po0ePGqTdvXu36rgIMDYSkWNZ8myX3uLFi6HRaODt7W10eVJSEkaOHImgoCDkz58fYWFhWLNmjao8WfO8mtkzsKXPpUSUNdycnQEisr/Vq1crNT5WrFgBb29vnD9/HteuXVPS3Lt3DyEhIejRowdKlCiB5ORkrFq1Cr1798alS5cwduxYs/u4ffs2Fi5ciOrVq6NDhw5YvHixybQffvghXn/9dYP57dq1g4eHB2rXrq3M++uvv1C/fn2UL18ec+bMgb+/P/bu3YuPPvoIR48exebNm604I0SGjh8/jgMHDmDy5MnKvIMHD2LUqFF66Vq2bGm2cOrRo0d49OiR8ndCQoLd80r2oTYWHT58GI0aNUKdOnXwzTffQEQwY8YMNGvWDFFRUahXr57JfXzxxRe4ffs2RowYgUqVKuHWrVuYOXMm6tati59++gkvvviiwTpTpkxB06ZN9eZVqVJF72/GRiJyNEue7XRiYmLw9ttvIygoCPHx8UbTdOrUCYcPH8a0adNQrlw5rF69Gj169EBaWhp69uxpdvuWPq+qeQa25LmUiLKQEFkhPj5eAEh8fLyzs+I0KSkiUVEiq1drf6akODtHWlevXhUvLy8ZPHiwVes///zzEhISkmm6tLQ0SUtLExGRW7duCQAZP3686v3s3r1bAMjYsWP15n/wwQcCQM6dO6c3f+DAgQJA7ty5o3ofZL2cdo8DkE2bNqlKW6JECXF3dxcXFxf56KOP9Jbly5dPVq1apTdv1apV4u7ubnJ748ePFwAGU045d3mdsVjUsmVLKVq0qCQnJyvzEhISxN/fX+rXr292ezdv3jSYl5iYKEWLFpVmzZrpzY+KihIAsm7dukzzydiYfeS0+Jid8Nxlb9Y827300kvSrl07iYiIEC8vL4PlP/zwgwCQ1atX680PDw+XoKAgSbHyAdrY86otz8CmnkvJMrzHyRZs1kcOlZoK7N4NREZqf6amOjtH9rFxI+DvPx9Nm2rQs6cGTZtq4OamXyW4QIECePz4cZbnbfHixUhOTsa7775r1fr+/v5wc8u8UqXuOK21ZMkSaDQa9O/fX29+vnz5AAC+vr568wsVKgQXFxe4u7sr8/7++2/07t0bpUqVgoeHB4oWLYoWLVrgzJkzVueLcr99+/bhyJEj+PLLLzFnzhxERkbqLc94XYuI2Wt9zJgxiI+PV6YrV644JN85yfz58802mXBWfDTGWCz69ddf0aRJExQoUECZV7BgQTRq1AgHDhzA9evXTW4vMDDQYJ63tzcqVapk07XB2EiUe2TXGGnps93KlSuxZ88eLFiwwGSaTZs2wdvbGy+//LLe/H79+uHatWtW9+lo7HnVlmdgU8+lAGMqUVZh4RQ5zMaNQKlSQNOmQM+e2p+lSmnn52QbNwJdugD37rUDcPC/SfehPAtTpx7EwYMH8dtvv+m9LKghIkhJSVE1mbJ37174+fnh77//RlhYGNzc3BAYGIjXX3/daHOjtLQ0pKSk4NatW1iwYAF++uknqwu21IqPj8f69evRrFkzlC5dWm9ZREQEChUqhMGDB+PChQtITEzE1q1b8dVXX2HIkCHw8vICAJw9exa1a9dGfHw8Zs2ahR07dmDu3LkoXry4kobImNKlS6Nq1ap47bXXMGrUKL3+NIoVK4YbN27opY+NjUXRokVNbs/DwwM+Pj56U17Xrl07HDyojYW6l5ZZs2Yp85wVHzMyFYseP34MDw8Pg/S6eSdPnrQo7/Hx8Th27BgqV65sdPmQIUPg5uYGHx8ftGzZEvv37zdIw9hIlHvklBhpTmxsLEaOHIlp06YhODjYZLpTp06hYsWKBgVJ1apVU5aroeZ51dJnYB1zz6WMqURZyLkVtyinyqzK5oYNIhqNCKA/aTTaacMG++Qjq5vWpaSIBAcbHhfw+X9NeS5LSIh+PmJjY6VNmzZSoEABKVu2rPz8888mt69r4qFmunjxotFtlC9fXvLnzy8FCxaUKVOmSFRUlMyYMUM8PT2lQYMGSnVtnUGDBinbdHd3lwULFlh8Xixt1vfFF18IAImMjDS6/PTp01KhQgW94x0+fLhe3sePHy8FChSQ1NRUi/NLmctp1bJhQbO+9D766CMpWbKk8nfXrl2ldevWemlatWol3bt3V73NnHbuHO3zz7Xx8fLlywbLsjo+ZmQqFoWFhUm5cuX04suTJ0/kmWeeMdo8JTO9evUSNzc3OXLkiN78Y8eOyYgRI2TTpk2yd+9e+frrr6VixYri6uoqP/74o8F2GBuzB97j1uO5M5RdY2Rmz3adO3eW+vXrK/HHVLO+smXLSsuWLQ3mX7t2TQDIlClTMs2LiLrnVUufgXXMPZcyplqG9zjZgh2ik92lpgIjRmiLbDISATQaYORIoH17wNXV+v1s3Kjdz9WrT+cFBwNz5wIqB++y2L59+vt7KhqAH4AQXLmiTdekiXbJkCFDULRoMWzYcAu//PILOnXqivPnzyEwsIjBVmrWrInDhw+ryktQUJDR+WlpaXj48CHGjx+P9957DwDQpEkTuLu7Y+TIkdi5cyeaN2+upH///fcxYMAAxMbGYsuWLRg6dCiSk5Px9ttvq8qHNZYsWYIiRYqgY8eOBssuXbqEdu3aoWjRoli/fj0CAgJw6NAhTJ48GUlJSViyZAkAbXXu+/fvo1+/fhg4cCDq1q0LV1suKMpxkpKScO7cOeXvixcvIjo6Gn5+fggNDcWYMWMQExODFStWAAA+//xzhIaGokKFCgC0o/l8+umnGDZsmLKNESNGoFGjRpg+fTrat2+PzZs345dffjFak4XU0f1PQkJCDJYNGTIExYoVw61b2vjYtWtXnDt3DkWKOCY+ZmQqFg0bNgyvvvoqhg4dig8++ABpaWmYOHEi/v33XwCAi4v6iucffvghVq1ahc8++ww1a9bUW1ajRg3UqFFD+bthw4bo2LEjqlatitGjR6Nly5bKMsZGotwpO8dIUzZs2IAtW7bg+PHjqpoBmkujthmhmudVS5+Bdcw9lzKmEmUhZ5eOUc5krlQ8KspYzSLDKSrK+v3bUjPLltpWq1ebOp7aAryo/K37Uj0xMVHc3PJJsWKX06VtLIULLzGax7S0NHny5ImqyZS6desKADl27Jje/DNnzggAmT59utljfP3118XNzU1iY2NVnxdLak6dOHFCAMiIESOMLu/WrZsEBgZKUlKS3vyvv/5aAMju3btFRFuLYdq0aUotgoCAABk+fDi/qbGTnPDNl6lviSMiIkRE+y1u48aNlfTz5s2TypUrS4ECBcTHx0dq1KghCxYsMPg2dN26dVK+fHnJly+fVKhQQTZYWNUzJ5y7rFS7dm158cUXDeYnJiZKvnz59GoLNG7cWJYsWWJ0O/aIj+llFoumTZsm3t7eynVVr149effddwWA7Nu3T9U+JkyYIADk448/VpVe5/XXXxcAcv/+fWUeY2P2wXvcejx3hrJrjDT1bKcb4OGtt96Su3fvKlOPHj3Ey8tL7t69qxen6tatK7Vr1zbY/qlTpwSAfPXVV6ryk5Gx51VrnoEz+yxgTLUM73GyBfucIrsz00+sVekyyqxmFqCtmWWs83Vb+8EqXtzYXAFwCkCYQbovvzyLlBRv3LiR/tuwqrh790906WK43z179iBfvnyqpkuXLhnNo64Nv0Eu/zs5mX3jX6dOHaSkpODChQtm01lL9+3+gAEDjC6Pjo5GpUqVDNrx64b11fVN4ObmhnfffRenT5/GlStX8Prrr2PevHn4+OOPHZJvyn6aNGkCETGYli1bBgBYtmwZdu/eraQfNmwYTp06heTkZKUPoMGDBxvcE126dMHff/+Nx48f4/Tp0+jkqKqYeYCI4NSpUwgLCzNYdvbsWXh7e+vVFqhatSr+/PNPo9uyR3xML7NY9O677yIuLg4nT57EpUuXcODAAdy9exdeXl4GNaCMmThxIiZMmIAJEybg/fffzzR9erp4nb5GAWMjUe6TnWOkKXFxcbh58yZmzpyJwoULK1NkZCSSk5NRuHBh9OrVSy/Pp0+fNujrStd3X5UqVazKh7HnVWuegTP7LGBMJco6bNZHdme8AMf6dBmZblqnJQKDpnXA047MMxZqxcRo569fr98cMDVVu43r17V5bdhQOwUHa9d5up07AB4AKA2NRru8YUPt+jNmJAHI2DmyD4A4AIbNG+1RJbtz585YuHAhtm/frtdcZNu2bQCAunXrmt1uVFQUXFxc8Mwzz6jKhyUePXqElStXok6dOiYfRoKCgnDq1CkkJSXB29tbmX/w4EEAMNrpZnBwMD744AN8+umnduvok4hsd+fOHTx48MCgg1lA2ywzY+fxPj4+iIuLM7otezZZUROLAG0H6Lrlly9fxtq1a/Haa6/B09PT7PYnTZqECRMmYOzYsRg/fryqPOvcvXsXW7duRVhYGPLnz6/MZ2wkyn2ya4w0p1ixYoiKijKYP23aNOzZswfbt2+Hv7+/Mr9jx45YtGgRNmzYgG7duinzly9fjqCgIDz//PNW5cPY86qlz8BqPwt0GFOJHIuFU2R3xgtwnkpfgGMNa2pmWdoPlrn+rObO1RZmaTS67XkAyAdgB0SqYdKk6ti3zxc7dwK3bnkDyDg6SAIAb6OFaAULFkStWrXUHaAJLVq0QLt27fDRRx8hLS0NdevWxZEjRzBx4kS89NJLeOGFFwAAAwcOhI+PD+rUqYOiRYsiLi4O69atw9q1a/HOO+8gICBA2eaePXvQrFkzjBs3DuPGjVPmb9++HcnJyUhMTAQA/PXXX1i/fj0AoE2bNnrDsAPAd999hzt37pj8dgoARo4ciQ4dOiA8PByjRo2Cv78/fvvtN0ydOhWVKlVC69atMXToUMTHxyM8PByhoaG4desW5s+fD3d3dwwaNMim80dE9uPh4YF8+fJhx44dqFatGqpXrw5fX18AgLe3t8HoSQkJCXoFL+nZIz7qZBaLTp06hQ0bNqBWrVrw8PDAiRMnMG3aNJQtWxaTJk3SS5sxPs6cORPjxo1Dq1at0LZtW/z222966dO/HPXs2ROhoaGoVasW/P39cfbsWcycORM3b95UagDqMDYS5T7ZMUaqebZrkv7b3/8sW7YMrq6uBstat26N8PBwDB48GAkJCXj22WcRGRmJH3/8EStXrtTrv8nY86Ylz6tqn4F1MvssYEwlymLOak9IOZva0foy9gtlj9H6rOnTypJ11PRntWFDxlH7Zomra5AAkKJFz6SbnyhAPgGupJvXRIAlBv1T2dP9+/fl3XfflZCQEHFzc5PQ0FAZM2aMPHz4UEnz9ddfS8OGDcXf31/c3NykUKFC0rhxY/nmm2+MnPMoo/0OlCxZ0mifPzAxEkx4eLh4eXlJQkKC2fzv2rVLWrRoIcWKFRNPT08pV66cvPXWWxIXFyciIp999pk0bNhQAgMDxcPDQ0qXLi39+/eX8+fPW36yyCj2GWA9njt9s2bNkqAgbXw8c+aMMl/Xn8qVK1eUeU2aNDHZn4o9ZRaLzpw5I40aNRI/Pz9xd3eXZ599VsaOHWvQ35OIYXxs3LixybiY8bFr6tSpEhYWJr6+vuLq6ioBAQHSsWNH+f33343mi7Exe+A9bj2eO0PZLUZa+mynY2q0PhHtsQwfPlyKFSsm7u7uUq1aNaMj4xl73rTkeVVE3TOwTmafBYypluM9TrbQiBirS0JkXkJCAnx9fREfH29Q5VjHWO2jkBBgzhzbRtNLTdX2E5VZzayLF582l4uM1PYxlZmVK4H33jPdbDD9tgH9Zn9xcUDXrsby9DIAXwCfAdgJoDeAswC0VZ6jovSbHxJlB2rucTKO5069l19+Gb6+vvjss8+wc+dO9O7dG2fPntVrEkKU3fAetx7PnWUYIymn4T1OtmCzPnKYTp20zeQy9ttk6+irrq7GmtZp6fqOnTNHfz9q+7e6dcuy/qx0hUq6AjPjRb0LAEQAKAKgBIC1APxtbt5IRJTTLViwABEREShSpAhKlCiBtWvX8qWLiOg/jJFElJewcIocytXVMbWCOnXSdmBurF8oYzWz1PaDla7ZulkZ+70y30l7AIBtBvsTAQYMAL791n4Fd0REOUlAQIDSUS0REeljjCSivISFU5RjWVIzS21tKz8/dfvOWBNLbSftOrr9pB/ESdfheqdOxkcKZMEVERERERER5UYsnKIczZKaWWpqW6WmWjfSoNpmg2PHAvnyARMmGG4/JkZbePb229o+soyNFGhLX11ERERERERE2RELpyhPyay2lTX9WQHqmw1++CFQpozxNLp5n3xiuExXcLV+PQuoiIiIiIiIKHdxcXYGiLKarrZVjx7anxkLmnQ1rEqU0J8fHGy6cEhXqAU8LcTSSV+odeCA+Q7XTdEVXI0cqa3dRURERERERJRbsHCKyIhOnYBLl4CoKGD1au3PixfN11pSU6hlad9U6aUfKZCIiIiIiIgot2CzPiITrBlpMLNmg2r7pjLHlgIuIiIiIiIiouyGhVNEdmauUCuzvqnUsEcBFxEREREREVF2wWZ9OdzevXvRrl07BAUFQaPR4LvvvjObfvfu3dBoNAbT33//nTUZzuPM9U2VGY0GCAkxHCmQiIiIiIiIKCdj4VQOl5ycjOrVq2P+/PkWrXfmzBlcv35dmcqWLeugHFJGpvqmCgkB3nlHWwhlrlN1ANi9G4iM1P401kF6amrmaYiIiIiIiIiyAzbry+Fat26N1q1bW7xeYGAgChUqZP8MkSrm+qaqWxcYMUJ/VL/g4KcFU6VKGS6bNQsICNBu6+xZYNEiwzRz55rv0J2IiIiIiIjIGVg4lUfVqFEDDx8+RKVKlTB27Fg0bdrUbPpHjx7h0aNHyt8JCQmOzmKuZ6pvKlMFV5s3A126GPZVdfUq0LWr+X3FxGjX1Y0aSERERERERJRdsFlfHlO8eHEsXLgQGzZswMaNG1G+fHk0a9YMe/fuNbve1KlT4evrq0whISFZlOO8SVdw1aPH0wKsESOs70Rdt97IkWziR0RERERERNkLa07lMeXLl0f58uWVv+vVq4crV67g008/RaNGjUyuN2bMGLz55pvK3wkJCSygykL79uk307OGCHDlinZbpkYTJCIiIiIiIspqLJwi1K1bFytXrjSbxsPDAx4eHlmUI8ro+vXsuS0iyrtSU433m0dEREREZCk26yMcP34cxYsXd3Y2yAx7/nv4ryYiW23cqB2coWlToGdP7c9SpbTzicj59u7di3bt2iEoKAgajQbfffed2fQbN25EeHg4AgIC4OPjg3r16uGnn37SS7Ns2TJoNBqD6eHDhw48EiIiyitYcyqHS0pKwrlz55S/L168iOjoaPj5+SE0NBRjxoxBTEwMVqxYAQCYM2cOSpUqhcqVK+Px48dYuXIlNmzYgA0bNjjrEEiFhg21I+7FxFjf75RGo91Gw4as8UBE1tu40fjgDBx4gSj7SE5ORvXq1dGvXz907tw50/R79+5FeHg4pkyZgkKFCmHp0qVo164dDh06hBo1aijpfHx8cObMGb118+fPb/f8ExFR3sPCqRzuyJEjeiPt6fqFioiIwLJly3D9+nVcvnxZWf748WO8/fbbiImJgaenJypXrowffvgBbdq0yfK8k3qursDcudoXP43G8gIqjUb7c84c7ah/I0bo92EVHKzdPl8oiXIPRxRCp6aaHpxBRBtrRo7UjjjKAm8i52ndujVat26tOv2cOXP0/p4yZQo2b96MLVu26BVOaTQaFCtWzF7ZNItfpBER5S0snMrhmjRpAjFTUrFs2TK9v0ePHo3Ro0c7OFfkCJ06aWskZCxYUiM4WFswBbDGA1F24cgXr40bHVMIndngDBx4gSh3SEtLQ2JiIvz8/PTmJyUloWTJkkhNTUVYWBgmTZqkV3iV0aNHj/Do0SPl74SEBFX7d1QMIyKi7It9ThHlIJ06AZcuAVFRwOrV2p/r1mkf2NILDgYmTnya5uJFbU0GczUeAG2Nh9RURx8FETmyzyZds7uMhUi6Qmhb9qF2QAUOvECUs82cORPJycno2rWrMq9ChQpYtmwZvv/+e0RGRiJ//vxo0KABzp49a3I7U6dOha+vrzKpGenZkTGMiIiyL42Yq3ZDZEJCQgJ8fX0RHx8PHx8fZ2cnz1NTA2P3bu0LcGaioljjgXiP2yKzc2eqzyZd81tbajCmpmoLuUzVbtL1PXfxonW1tBhHiHJefNRoNNi0aRM6dOigKn1kZCQGDBiAzZs3o3nz5ibTpaWl4bnnnkOjRo0wb948o2mM1ZwKCQkxee4cHcOIyLFyWnyk7IXN+ohyAVfXzF8EWeOByPkc3WeTPZrdmSvszmxwhvQDLxBRzrN27Vq8+uqrWLdundmCKQBwcXFB7dq1zdac8vDwgIeHh+r9Z1XTYfZnRUSU/bBZH1EeUby4unQ3bwKRkdoaEmziR2Rflrx4WcPWQujMmhvqBmcAntb00kk/8IKlL3mpqdqYo4s9jx/r/81YROR4kZGR6Nu3L1avXo22bdtmml5EEB0djeJqHzBUyIov0hzZrJqIiKzHmlNEeURmNR4A7QvlqFFP/2bno0T25egXL7XviMbSmWpumHHABFODM+gGXrA0Xhjr+NjVVb9AirGIyDJJSUk4d+6c8vfFixcRHR0NPz8/hIaGYsyYMYiJicGKFSsAaAum+vTpg7lz56Ju3bq4ceMGAMDT0xO+vr4AgIkTJ6Ju3booW7YsEhISMG/ePERHR+Pzzz+3W75tiWFqqI1ztmLNLCIiy7HmFFEeYa7Gg07G2gnsfJTIvhz94qUrhDZ1j2s0QEiIYbO7zJobAvoDJhgbnOHiResKpox1fMxYRGSbI0eOoEaNGspIem+++SZq1KiBcePGAQCuX7+Oy5cvK+m/+uorpKSkYMiQIShevLgyjRgxQklz7949DBw4EBUrVkSLFi0QExODvXv3ok6dOnbLt7UxTA1L45ypbWRWq5M1s4iIrMMO0ckq7Owu51JTSyE9dj6aN/Eet565c6fr7DezPptsud90BT6A/j7Mdbhu747OTdUaSD8/MBDo29d8M8f0GIsou2B8tJ6ac2dNDFPD1jhn7PkpY61ORw54QZQTMD6SLVhziiiPyVjjYfZs898S2toHDhE9lbEGYyHchT9uwRf34I0keMhDzJ2ZAlcX67830jW7K1FCf35wsOkXI3s2NzRVa2D0aP35zZurL5gCGIuI8gprYpgatsQ5U7U809fqtKRmlpoaWEREeQ0Lp4hyoF27dqF///6oUKECvLy8UKJECbRv3x5Hjx5Vtb6rK1CrVhIOHRqJiRODAOQHEAZgjZHUSQBGomPHIOTPnx9hYWFYs8ZYOm0fFyNHjkRQUOZpifKq9C9eyxGBWwjEPRRGIgriATzRsWs+wMUFyJcP8PQEChYEChfWVjUKCgJCQ4FnngHKlQMqVwaqVwdq1gSefx5o0ABo0gSdFjTH5UqtEFf3JVyu3Rk3mr+CSy1eQ6fdw4F33wUmTACmTwfmzQMWL0b1U6vQERvRCtvRGLtRB4dQEX8hCDHwQhIA7ZtVZs0NTb3AXb0KfPKJZYVRply/bv7FLjExEaNHj0aLFi0QEBAAjUaDCRMmWL2/xYsXQ6PRwNvb2+jy/fv3o02bNihcuDA8PT1RtmxZTJo0SS+NvfNElNvZq+lwetY2q1Zb6LR7t7oBLz7+2LnN/myNR9HR0Wjbti1CQ0Ph6ekJPz8/1KtXDytXrtRL17dvX2g0GpPTb7/9pqTdvXu3qnRElLuxQ3SiHOiLL77A7du3MWLECFSqVAm3bt3CzJkzUbduXfz000948cUXM91Gp06dcPjwYfTrNw2zZ5cDsBpADwBpAHqmTwlAm65du3JYvXo1evTogbS0NPTs2dPoNqdNm4Zy5cynJcrLOnUC2rcH7jVIBQ6ZSJSSop2spAFQ5L8pM5UAmHsvSoErklx84NvPF/DNMAUEAAEBSPMPxJYxgagtgbiFAMQiEMnw+i8n9nP2rPZFzlTTmtu3b2PhwoWoXr06OnTogMWLF1u9r5iYGLz99tsICgpCfHy8wfLVq1ejd+/e6Nq1K1asWAFvb2+cP38e165d00tnzzwR5RWuruqaEauV2cAwuqbDGfuzUjvK6u7d6vIxfrzhPHt3yG6OrfHo3r17CAkJQY8ePVCiRAkkJydj1apV6N27Ny5duoSxY8cCAD788EO8/vrrBuu3a9cOHh4eqF27tsGyKVOmoGmGtpdVqlSxKH9ElHOxzymyCtsTO1dsbCwCAwP15iUlJeHZZ59FlSpV8Msvv5hdf9u2bWjbti1Wr16Nrl17pOsDpwWAPwFcBuAKYBuAtvDzW43Y2B5KPy8tWrTAn3/+icuXL8P1v5npt9mjRw9lX8bSUvbHe9x6Fp+7tDTtV/O6wqgnT57+buxvtfOePNFOjx8DDx48ne7f1//7vynu6gNc/vs+PPEAnniAgkiEL+LhBuvbmyTBC1cRjCsI0ZsuIxTn8CwuIxSpKr8n02gAPz/gzh3z/bl07Cj/zdMgLi4OAQEBGD9+vFU1ldq1aweNRgM/Pz+sX78eSUlJyrKYmBiUL18effr0wYIFC8xuR/eoZY88kfMxPlrP2efOmv6sIiO1NZwyM3YsMHmy9XnTaLQ1apctA2JjHTfKn6PiUd26dXHt2jW9jvYz2rNnD5o0aYKxY8fq1TDdvXs3mjZtinXr1qGL7h9EOZKz73HK2VhzisgGIoKvvvoKn3/+Oc6ePYvg4GBMmzYNnTp1QrVq1dCzZ0+8//77dt9vxoIpAPD29kalSpVw5cqVTNfftGkTvL298fLLLyt94GifBfpBW2vqEID6ADYB8Mbnn7+s17lxREQ/vPJKTxw6dAj169c32GZ6/fr1Q8+e+mmJKB0Xl6fN+JzIH8Begw5/BeVK3MfsCfFo0yAeiM8w3bsHxMUBsbGIOXELMcdjEQjt5IkHWIlkfI4zOIszCAYwDcCHAKoBGADgbeTDBTyDc3gW/6Ac/kIl/IFq+BOVcR9eSt40mqcvkqaa1mg02qY17dtr7PIyt3LlSuzZswd//fWXUhMgvcWLFyM5ORnvvvtuptvSmBp6jIiylK5ZtbGOzefMMV5rSW1zwCZNtAVLpmpmGRIAXwH4HMBZiATj6tVpaN68E7RRsieCg9/X63DdHhwVj/z9/REbG2s2zZIlS6DRaNC/f3+H5IGIcjYWThFZSUTQrVs3bN26FRMnTkSNGjUwffp09O3bFwkJCbh79y5GjhxpdL1UlT1furmpv0Xj4+Nx7NgxVU36Tp06hYoVKyrb1z2svfFGNdy8CQCnANSHu/sp+PlVxDvvuOk9xBUtWk3Zjq7AKeM2dapVM0xLRNmTrrnh08JoDRo29IKrqxeAILPrnt2dfiQsgSs6Iw3bURp90BCFcA4b8Ar+xeuogFv4G6/DBe54jAo4gwo4A+AHCIBUaBsXn0cZnEB1/Ia6OOdfH7UH1sCEj93T7VE/1qTvMD1jU6BLl7S1H9TWRIiNjcXIkSMxbdo0BAcHG02zd+9e+Pn54e+//0b79u1x6tQp+Pn5oVOnTpgxYwa/MSbKpgzjnPm4oLY5YJMmT7/sS1+grkujv64A6AZgK4CJAGoAmA6gL4AEAHcBjDRo7ueoZ0hrpKWlIS0tDXfv3sW6devw008/Yf78+SbTx8fHY/369WjWrBlKly5tNM2QIUPQvXt3FChQAPXq1cOHH36IF154wVGHQETZjRBZIT4+XgBIfHy8s7PiNF9//bUAkFWrVinz9u7dKwCkcOHCsmjRIqPrRUVFCbRPJZlOFy9eVJ2fXr16iZubmxw5ciTTtGXLlpWWLVsazL9y5ZoAkG7dpkhUlEjx4mUFaCnaR6r0kzZdr15TMt3mtWvatFOmTDFYRtlXTrjH9+zZIy+99JIUL15cAMimTZvMpt+wYYM0b95c/P39pWDBglK3bl358ccf9dIsXbrU6L344MED1fnKCefOEVJSRIKDRTQaEeDr/87dqnRxY+9/8woLsEg0SJUQ/CvN8Iu8V+gL+bfTSNlQ6jnV8dEHx43EJpHVq5/maenSW/+lH68sDw4W2bDB/LF07txZ6tevL2lpaSIiEhERIV5eXnppypcvL/nz55eCBQvKlClTJCoqSmbMmCGenp7SoEEDZd2Mbt3S5mn8+PG2nG5yorx6j9tDTj13GzZoY5s2vj2ddPPSx5QNG7RxJn26kBCRiRPTz8s8RqZfPyBAZOVKkdmz1T9Dzp17UaKitLHZFFvi0aBBg5R9ubu7y4IFC8ym/+KLLwSAREZGGiw7duyYjBgxQjZt2iR79+6Vr7/+WipWrCiurq4Gn9OUveXUe5yyB9acIrLS/PnzUaVKFb2OvgsXLgwAKFasGPr162d0vZo1a+Lw4cOq9hEUZL6mgs6HH36IVatW4bPPPkPNmjVVrWOsWrfuW8OwMA0aNgRu3QLMdWa8dasGqalP1zNXVZzNWsjekpOTUb16dfTr1w+dO3fONP3evXsRHh6OKVOmoFChQli6dCnatWuHQ4cOoUaNGko6Hx8fnDlzRm/d/Pnz2z3/uY1+E+H5AKpAf3CFwv/9LAagHwQuuKoJxVWE4o0lzRDaCSicmIjDZ85oO5Y6dw44fRo4cQL44w9tM8J0qqEGTqEGNqM9vsf/EI0wABrcvKmtJXX2rHUdD2/YsAFbtmzB8ePHzcattLQ0PHz4EOPHj8d7770HAGjSpAnc3d0xcuRI7Ny5E82bN1d7+ogoG7OkOaCpmlkAsGiRrgZW5jEyvVu3gFdeAYCaCAw8jFGjtIO4xsUB/v5AWJg2Bu/aBcycqe2zasSIICWP9m4aCADvv/8+BgwYgNjYWGzZsgVDhw5FcnIy3n77baPplyxZgiJFiqBjx44Gy2rUqKH3OdywYUN07NgRVatWxejRo9GyZUv7Zp6IsiUWThFZ4e7duzh+/LjyQqKjq2r98ccfm+z829vbG2FhYar2o6ZK9sSJEzF58mR8/PHHGDp0qKrtFilSBLdv3zaYf+fOHQCAn58f9u0DUlKKADBMB2jTxcf7KU1o1GyTyJ5at26N1q1bq04/Z84cvb+nTJmCzZs3Y8uWLXoPxRqNBsWKFbNXNvOUTp2AZcvuIiLiOICn8TEkBHjxxVQsXw4AH0M74ILhi51efEzfRFkEqX+dwZgmB1Hx3gHUwwG44x88h+N4DscxERNwGSHYovkfNo/6H3ajCZ4gfRNAvU2l659KvylPUlIShgwZgmHDhiEoKAj37t0DADx+/BiAdpSqfPnywcvLC0WKFMHZs2cNXppat26NkSNH4tixYyycIrJFXBxw4YL2JnV11fbNZ+73zJbrfrfyyzJLmgOaGmlw7lygc+e7APRjpJauud7TGGnIG7GxYRgzRn9uiRJA9+7agqmntM+QjhoJMDQ0FKGhoQCANm3aAADGjBmDiIgIBAQE6KX9448/cOTIEYwYMQIeHh6qtl+oUCG89NJL+PLLL/HgwQN4enraL/NElC2xcIrICufOnYOIGLSZX7hwIQAYHR5XZ8+ePQbD5Jpy8eJFlCpVyuTyiRMnYsKECZgwYYJFHa9XrVoVkZGRSElJ0SsAO3nyJADtsL3//gsAVQFEAkiBfrg4+d/PKrh+Xf02ibKTtLQ0JCYmGhScJiUloWTJkkhNTUVYWBgmTZqkV3iV0aNHj/Do0SPl74SEBIflOSeoWPEcAMFbb5VGzZpPX+CGD9fGx2+/rY2UFOMvdpbERz8cRjucwv/wPVriJ4TiCobI5xiCz3EbfliJV/AVOuG0kXVN9U8VFxeHmzdvYubMmZip/5YHQFs7tn379vjuu+9QrVo1/Pbbb0a2re1YxsXFRdVxEJEJ27YBERH2365Go19g5e6uHZBCxU/XfPnQxN1dO8/TE/jWU/tTN+XPr/+3lxfg7Q0ULAh4e6NTHW98OuEs3p4gADL2u7Twv5+mnyGBPQAMY2RMTMaCKQC4CKCUUiA/YgTg66s/EqA91alTB19++SUuXLhgUDi1ZMkSAMCAAQMs2qYunrL2PVHewMIpIivoakXd0rZ7AwAcPXpUKZzSfZgaY69mfZMmTcKECRMwduxYjDfWdsWMjh07YtGiRdiwYQO6deumzF++fDmCgoLw/PPPQ1tRoCOARQA2QNtxp5IS2s6Rn1dGsVGzTaLsZObMmUhOTkbXrl2VeRUqVMCyZctQtWpVJCQkYO7cuWjQoAFOnDiBsmXLGt3O1KlTMXHixKzKdrani49+frfQo4d2Xvr4WLeuICTE+Lpq4uPTZivVsBy1sBx94eXyAI3TdqE9NqMdtqA4bmAE5qEX5iEAwHM4grNIQCL0OynXFa7rFCtWDFFRUQb7nDZtGvbs2YPt27fD398fANC5c2csXLgQ27dv1yu83LZt23/HWdfscRBRJgoUAEqWBFJTtVNaWua/qxkmT+RpegB48MCxx5GBrmhpkusbeKvgOKT5FMbGa27ol3IKqQAm4X2koRRuIQC3EIA4+OMWAnATRRGLMAjUPUOmH8RCRNscMX1lzuBgYNIkex0VEBUVBRcXFzzzzDN68x89eoSVK1eiTp06Fn1ReffuXWzduhVhYWFsWk+UR7BwisgKlStXRkBAAGbPno1SpUrBxcUFb775Jrp06YI1a9Zg4cKFGDhwIEKMvIEVLFgQtWrVsmn/M2fOxLhx49CqVSu0bdvW4Nv79C9Fe/bsQbNmzTBu3DiMGzcOgLbZSXh4OAYPHoyEhAQ8++yziIyMxI8//oiVK1fC1dX1v9FpWuPq1XAAg6EdPeZZaGtS/QhgJfz8XJXnOzXbJMouIiMjMWHCBGzevBmBgYHK/Lp16+rdPw0aNMBzzz2Hzz77DPPmzTO6rTFjxuDNN99U/k5ISDB67+cVjo6PtWoBb731tGnNzZvAqFGe2Ia22Ia2GIxUhGEKmmAbKuAwgFSUwQ8YhQD8gnD8jNm4Dm1B482be+Dm9jQ+5s+fH02MtMVZtmwZXF1d9Za1aNEC7dq1w0cffYS0tDTUrVsXR44cwcSJE/HSSy8ZjDC1fft2JCcnIzExEQDw119/Yf369QC0TWIKFChgwVkmygO6dNF1YqeeyNPCKjWFWampwJMnwOPHpn8am/foEfDwobZgSzdl/PvBA+D+fSAxEUhK0v5MTETl1FQEAJibmoJn7t2Ay70beBfAywDWAHiEbzAQgLFPkVS4IBaBuI7iuIYg/IuSuIRSelMc/GGuv1Ct7bh6NRn9+pmPR8aeIQcOHAgfHx/UqVMHRYsWRVxcHNatW4e1a9finXfeMag19d133+HOnTtma0317NkToaGhqFWrFvz9/XH27FnMnDkTN2/exLJlyzI5FiLKNZzbHzvlVByJQWT//v1Ss2ZNcXd3l8KFC8uYMWMkLS1NBg4cKPny5ZMvvvjCYftu3Lix2RFa0tONDphxJJbExEQZPny4FCtWTNzd3aVatWoGI6hs2CACJAowXIBiArgLUE2ASL1RZHSjX6nZJuUMOe0eh4rR+nTWrFkjnp6esnXrVlXpBwwYIK1atVKdl5x27hwhK+Pj6tWGI/YBJU3GxzNwk8V4VRoVOyO//GI8PmZkbLQ+EZH79+/Lu+++KyEhIeLm5iahoaEyZswYefjwoUHakiVN58mSkVnJ+XiPWy/Pn7u0NJGHD2X/1q1Ss0oVcc+XTwoXLChjOnWSw28skZrudcUVLtIdjeRbdJFdaCInUVluIFBS4GIs2BlMSSggp1BJvsdLMg2jpQ+WSS38Ll5IVBUj08cjY8+QX3/9tTRs2FD8/f3Fzc1NChUqJI0bN5ZvvvnG6CGHh4eLl5eXJCQkmDwtU6dOlbCwMPH19RVXV1cJCAiQjh07yu+//26vM09ZJM/f42QTjYia+q9E+hISEuDr64v4+Hj4+PhkvgLlWBs3Go5Ok5GuKwB7d7ZJzpPT7nGNRoNNmzahQ4cOZtNFRkaif//+iIyMzDQtoG2iW6dOHVStWhVff/21qrzktHOX0+3eDWTeTZWgBX7GGExFE+zRztFocOmF3rg2cgbqti9qtFNjImN4j1uP58681FRtrdCYGGDUKG2f8Lo3NVekIAC3UBzXEYRrCMI1lMS/evWmSuCa2e3/i1D8ico4ipo4jNo4jNq4geKIijLegTuRpXiPky1YOEVWYeDJW1JTtS+AXbtqR3g3RqPR9l9w8aLxkWsoZ8kJ93hSUhLOnTsHQDsM9axZs9C0aVP4+fkhNDQUY8aMQUxMDFasWAFAWzDVp08fzJ07F53SlaJ6enrC19cXgHaQgbp166Js2bJISEjAvHnz8M033+DXX39FnTp1VOUrJ5y73CQ1FShVSjc8e+bpW/kcwMgHU9HyyVYAwD344tNCH+O5ha+j08sMXpQ53uPW47lTb+PGp60a1b6tueMRSuIySuEinsU5VMJfylQMN42ucxUlkFiuFh7WegFpjZogrG8YXD3Y8wtZh/c42YKFU2QVBp68R13tBPDbt1wiJ9zju3fvNjqyW0REBJYtW4a+ffvi0qVL2L17NwCgSZMm2LNnj8n0ADBq1Chs3LgRN27cgK+vL2rUqIEJEyagXr16qvOVE85dbmPqJU6j0f49cSJQtixw9iwwYYJ2Xm38jgV4A7VwFABwFM8hYdoXaPquukJIyrt4j1uP584yamqvA09rsL/9NhAZaTy9H26jIk6jGv5ALRxBbRxGJfwFV6TppUvQ+OBG2YZIqtMMj1u3R+1uz/BLR1KN9zjZgoVTZBUGnrwnMhLo2TPzdKtXQxmhi3Iu3uPW47lzDmMvcSEhwJw52ubGuhpW6Ze7IBWD8BWm4H0UQjzSoAEGDoTL1CmAn19WHwLlELzHrcdzZzldU7/r14HixbVN/UaNMh/rdOkDA4G+fU3XLPVCEmrgOJ7HITTCXjTCXhRCvF6av/JVg6ZjR1R8vyNQrdrTkjAiI3iPky1YOEVWYeDJe1hzKm/hPW49njvnyfgS17Dh02bG5mJYIG5iBkYjAtomoPD3B2bM0L7V8UWMMuA9bj2eO/swF+sysqR5oAtSUR0n0AS70Qbb0AS74YbUpwmeeQbo0AHo2BGoXx9wcbHL8VDuwXucbMHCKbIKA0/ek1m/LuxzKnfhPW49nrvsSU3tz0bYg+9LvAHfmL+0Mzp3BpYtA7y9HZ4/yjl4j1uP58451DYPzMgPt/EStqIjNqGV5ifkl4fKsqSA0rjZ8XWU+qg/XIv62znHlFPxHidbsLibiFRxdQXmztX+nrEige7vOXNYMEVE2VPx4pmn2YvGiF4Wra01lS8fsGEDULcu8F/H+0REOVGnTsClS9ra7atXA2PHqlvvDopgBSLQEd+hiMTh227rsbFAL8TDB963LqLMwnfxpFgw/m3SB/jtN/U9txMRGcHCKSJSrVMnYP16oEQJ/fnBwdr56QZAIyLKVho21MYqU630NBptvy0vNM0HvPMOsGePtkTrzz+B2rWBH3/M2gwTEdmRq6u224UePYBmzSxf/z680G1tZ3S+vxLFcR398DWOoCby4xFK7vkGqFcPqFlTW9s0JcXe2SeiPICFU0RkkYzfvkVFaZvysWCKiLIztbU/AW3/VJGX6uHAZ0chdesB9+4BbdoAU6eyZgAR5XiZFdZn5gEKYBn6oTaOoDZ+x1L0xUNNfuD4caBfP6BSJe1DYmpq5hsjIvoPC6eIyGLpv31r0oRN+YgoZ8is9ieg7VuvaVNt/1QNuhTHs1eicDF8oLZQ6v33ga5dgaSkLM87EZG9mCust9QR1EZ/LEUJuYp9L03Hw4L+wNmzQK9eQPXq2g6vWKhPRCqwcIqIiIjyDFO1PwHtiFYZOwy+eM0DZX75CscGfaXth2r9em2bmPh4g20TEeUUpgrrM1JbeHUHRdBo62gEJF7A+/gY9zSFtM2iO3fWNo3+7Teb80xEuRsLp4iIiChPyVj7E9COZGXsy33dvA7bBiJ1527Azw/4/XegZUsWUBFRjpaxsH7iRG1N0vSCg7Xz1UpCQUzF+ygtFzEZY/Ekvzdw9ChQvz4weLC2mTQRkREsnCIiIqI8bd8+80OsiwBXrgD7UusDO3dqC6gOHWIBFRHleOkL68eNM16z9IMPLO+j6h4KYZxmEur4nUdanwhtIP3yS6BCBSAykk39iMgAC6eIyO5SU//rUDhS+5P9YRJRdnb9urp0MTHA7nth2P72TjzxYQEVEeU+xvoVtbaPKhEg+log9vZbpi3pKl8euHlT26lf+/bA3bsOOAIiyqlYOEVEdrVxo36Hwk2bav/euNHZOSMiMq54cXXpRo3SxrQ274ehdsJO3HVhARUR5Q1q+6gyZsMGYDeaIPXYCWDSJMDDA9iyBahVC4iOtnteiShnYuEUEdnNxo3GOxSOidHOZwEVEWVHaodVv3Xr6e8nEIYX03biNv4roGrTBnj40LEZJSJyoox9VM2erW69+fP/+7KyvAc2VhoLHDwIlC4NXLgA1KsHrFjh0HwTUc7Awqkcbu/evWjXrh2CgoKg0Wjw3XffqV73119/hZubG8LCwhyWP8o7UlMz71B45Eg28SOi7MfaJivRCENz7ES8phBw4AAwYAD7USGiXC19s79hwyzri0r5svJiDeDIkaeF+hERwBtvAI8eOTTvRJS9sXAqh0tOTkb16tUxf/58i9aLj49Hnz590KxZMwfljPIa1R0K78u6PBERqWWqyUpAgPn1ohGGjrIB4uIKrFoFTJ/uuEwSEWUjlhbsi2in118HVm33w+63tiBt/ETtyl98ATRqpH1YJKI8iYVTOVzr1q0xefJkdOrUyaL1Bg0ahJ49e6JevXoOyhnlNWo7FFabjogoq2VsshIVpa7ZShRexJGIz7R/vP8+sHmzQ/NJRJRdWNMX1a1bwCuvAE2buaDkknH49YNtQOHCwO+/A889px0VlYjyHDdnZ4Cy3tKlS3H+/HmsXLkSkydPVrXOo0eP8ChdVduEhAR1O3v4EHjmmad/675WccRPFxf9n5n9rpt0w5Ck/z3j3/nyAW5uxn/my6ft2DHjlD8/UKAA4Omp/7NgQcDbW/vT3V3decwB1HYorDYdEZEz6Jqs6OzerW695D6DAc9TwIIFQK9e2mZ+1ao5IotERNlKp07awff27dN2fm5Jg46YGKDhx62w7fOjaLW4C3DsGNCiBbBoEdC/v+MyTUTZDgun8pizZ8/ivffew759++Dmpv7fP3XqVEycONHyHYqwqow57u5AoUKAn5/xqUgRbWlOiRLaqVgx7ZtTNqTrUDgmxniXKxqNdnnDhlmfNyIia1kU2xrMAc6c0X7r364dcPgwEBiY1VkmIspy6Qv2LSmcEtHG0YFTS+Pi6V/hOnQwsGyZtg8/gAVURHkIC6fykNTUVPTs2RMTJ05EuXLlLFp3zJgxePPNN5W/ExISEBISkvmKHh5Ph4jVPdU74qduSkvT/2nq97S0p1Nq6tOfuin93ykpT6cnT57+TD89evR0evxY+/PBg6fT/fvan8nJQFLS0xGdHj8GYmO1kxouLtoCquBgbY20smWBcuWe/ixcWN12HEDX70CXLtqHjPQvcboKbnPmZNuyNSIioyyKba75gG+/BZ5/Hjh3DnjtNeC77yzrZZ2IKAfLrEDfGKVf0sP50eTrr7WtCz77jAVURHkMC6fykMTERBw5cgTHjx/H0KFDAQBpaWkQEbi5ueHnn3/Giy++aHRdDw8PeHh4WL5TFxegenVbsp07PXmiLahKTATu3QPu3DGcbt8G4uKAa9e0n/DXr2sLy65d006//2643WLFtG31008lS2bZYen6HRgxQr9z9OBg7cubhV2jERFlC+Zi28yZ2oqukZHaiq4NG/rBdcMGoFYt4PvvtQt69nRe5omIspC5Av3MXL8O7Uq6XtZZQEWUp7BwKg/x8fHByZMn9eYtWLAAu3btwvr161G6dGkn5SwPypdP25yvUCFATQ00QFswFRurLai6elX7rfw//wBnz2p/XrsG3LgBbNumnXSeeQZo2VI7NW0K+Pg44ogU6fsduH5d97LGGlNElLMZi21xccCoUYYFVnPnVkOnDz8Exo3TjrX+4ovaLw+IiPIAUwX6mVH6JWUBFVGexMKpHC4pKQnnzp1T/r548SKio6Ph5+eH0NBQjBkzBjExMVixYgVcXFxQpUoVvfUDAwORP39+g/mUDbm6aj+1ixfXfiOfUVIScPKktiNJ3XTqFHDhgnZ43i++0HbiXr/+08KqGjW0tdsckNX0HQoTEeUG6WPbxo1A166GtQJiYrQ1BjaseQ8dwzZqm7a/8Ya2l2A27yOiPCJ9gX5MjLYgPy7Ogn5JdQVUItpOrFhARZTrsXAqhzty5AiaNm2q/K3rFyoiIgLLli3D9evXcfnyZWdlj7KStzdQr5520klM1A419dNP2uncOWDvXu30wQdAUJD2w/6117RPBQ6WmsoaVUSU86WmamsEGHvJ0nXuO+LtfPjfd8vg+nwtYNMmbV9U3bplfWaJiJwkfYG+p2fmffcB2sfWp8+JGrjOm6ddoCugcncHXnkli46AiLKSRsSSlsBEWgkJCfD19UV8fDx8HNxMjOzowgVtIdWPPwK7dmlrWwHap4d27YDBg4HmzR1Sm2rjRuP9tcydy76osiPe49bjucv9du/WtpLOzOzZwPC7E+Hy0QTt6Kt//cXR+3IB3uPW47nL24w9C4aEPC2YMvmc2FGA4cO1BVTu7tognP7LWMo2eI+TLez/BkpE2dczz2gLoDZv1tatXrMGaNxYWw3gu++0Tf3KldP28JucbLfdbtyo/bYsY78DuuYvGzfabVdERA53/bq6dKNGAc8uGYN7paprB7kYMsSxGSMiysY6dQIuXQKiooDVq7U/L17ULjP7nLjpvyZ+HTtqR7ru1MmyzqyIKEdg4RSRDZKSkuDq6opPP/3U2VkxEB8fDxcXF8yePVuZd+3aNWg0GixatAjw8NA2Mdm9G/jzT22nvT4+wPnzwNtvA+XLAytWAGlpNuUjs+YvADBypDadMYmJiRg9ejRatGiBgIAAaDQaTJgwwaI8JCUlYeTIkQgKCkL+/PkRFhaGNWvWWJ3O0rREeVGOjo+ZUDrtVeHSNXe8eGkp0lzdtD0Er1tnTZaNYnwkU/bu3Yt27dohKCgIGo0G3333ndn0GzduRHh4OAICAuDj44N69erhp59+Mki3YcMGVKpUCR4eHqhUqRI2bdrkoCPI/XJzjDRH19SvR4+nTf5UPSeKi/a5tGpV7QBAHToADx6Y3RdjJFHOwsIpIhscPXoUaWlpeP75552dFQNHjhyBiKB27drKPC8vLxw8eBA9evTQT1ypEjBvnnbEv0WLgFKltF9XRUQAdepo+6iy0r595r/cEgGuXNGmM+b27dtYuHAhHj16hA4dOliVh06dOmH58uUYP348tm/fjtq1a6NHjx5YvXq1VeksTUuUF+Wa+GhEw4ba5iZq+jcXAaI1NTDPa4x2xpAhwK1b1mZdD+MjmZKcnIzq1atj/vz5qtLv3bsX4eHh2LZtG44ePYqmTZuiXbt2OH78uJLm4MGD6NatG3r37o0TJ06gd+/e6Nq1Kw4dOuSow8jVcnOMtIRFz4ne3tra/0WKAEePavugMtNDDWMkUQ4jRFaIj48XABIfH+/srDjVp59+Kq6urpKcnOzsrBiYNm2auLq6SlJSkuUrP3ggMn26SMGCItqPfZFOnUT+/dfiTa1e/XQT5qbVq42vn5aWJmlpaSIicuvWLQEg48ePV73/H374QQDI6gw7CA8Pl6CgIElJSbEonaVpcyre49bjudPKtfHxPxs2iGg02klNjMuHR5L4TFXtH9262eU4GB+dI6fd4wBk06ZNFq9XqVIlmThxovJ3165dpVWrVnppWrZsKd27d1e9zZx27hwpt8dItax6ToyKEnFz0y6YPt3kthkjsx7vcbIFa04R2eDw4cOoUqUKDhw4gIYNG8LLywvPPvssPv/8c710v//+O7p164ZSpUrB09MTgYGB6NixI86fP6+X7u+//0bv3r1RqlQpeHh4oGjRomjRogXOnDmjl27//v1o0aIFfH19UbhwYbRt2xZnz541yFvFihXh5eWlzGvRogUaNWqk/P3iiy+iadOm2LNnD5o3bw5vb28UK1YMH82YAYwerR3d7/XXtR2kb9yI/VWqoEVYmNn9ZqS2+YupdBqNBhobhl/ftGkTvL298fLLL+vN79evH65du6Z846s2naVpifKqXBsfP/oIgLbLk/XrgRIllD0DaAHAF0BhAG0BPN3vE7hjf/+l2jYta9cCGzZYcVb1MT6So6SlpSExMRF+fn7KvIMHD6JFixZ66Vq2bIkDBw6Y3M6jR4+QkJCgN5FWbo+RGZnar1XPiU2aaPugAoD33gO2bTO6DmMkUc7CwikiGxw5cgRxcXF4//33MXToUGzcuBEVK1bE0KFD9fp3iI6ORvXq1TF37lz89NNPmD17Nv755x90SjdM3dmzZ1G7dm3Ex8dj1qxZ2LFjB+bOnYvixYvrPRxMmDABjRs3RkhICCIjI7F48WJcuXIFzZo1Q5Ju9L3/8pa+OjYAHD9+HDVr1tTL16VLlzBq1ChERETg+++/R6NGjTB+/Hjs2bNHO6rUF18AJ05gQlAQGicmIuTECUQ2bozFX3xhdL/piQjq1UtBiRIpAExP/v4piInRdn9lqu8pa506dQoVK1aEm5ub3vxq1aopyy1JZ2laorwq18dHPO3ct2XLCQAaAwgBEAlgMYArAJoBeLrf/A1qal+kAMjgwUi5fRspKSmZTo7C+EimzJw5E8nJyejatasy78aNGyhatKheuqJFi+LGjRsmtzN16lT4+voqU0hIiMPynNPkhRipZr81aiSZaCYt0D0nBgenoF69DLHxtdeQMmAAUkSAXr203VHYGWMkURZzdtUtyplYZVPkzp07AkAqV64s9+/fV+YnJyeLn5+fdDPRbCM1NVWePHkiixcvFgBy9+5dEREZP368FChQQFJTU03uc8uWLQJAZsyYoTf/n3/+EQCycuVKEXladXnBggVKmkuXLgkA+eabb0RE5Pz58wJAatasKQ8fPlTSXb161WBdZb+NGj2tX12jhvzz8896+80oKipKoH26UDFdFEAkOFjbXMYYa6pkly1bVlq2bGkw/9q1awJApkyZYlE6S9PmVLzHrcdzlzfjo6/vjAxN/P75L7atFI1GJCREJCVFRB4+FClfXqJUx0bIxYsXMz3njI9ZJ6fd47CwWd/q1aulQIECsmPHDr35+fLlM2iKtHLlSvHw8DC5rYcPH0p8fLwyXblyJUedO0fJizHS3H6NN5NW/wx5ERBp0ULkvyZ8xjBGZo2cFh8pe9EvsiUi1Y4cOQIAmDRpEjw9PZX5BQoUQNmyZXHz5k0A2tpDGzZswIIFC/D333/jxo0bkP86b3RxcVHW9ff3x/3799GvXz8MHDgQdevWhaurq94+x40bhzJlymDEiBF636aXLl0anp6euHDhAgBtdWwAqFWrlpLm6NGjAIDnnnsOAHDs2DEAwEcffQQPDw8l3e3btwEAQUFBhvvdsQMpP/4I9OsHHD+O0p06wdPDQ9lvRjVr1lTysmsXMHMmEBtr6oxq96cbNnj9em2tBHswV6U7/TK16SxNS5TX5MX4+PHHI9C9e/paTqUBeALQ7nfOHG2LPrh6AJMno+bLL+Owpyfw/fdAoUJmz2f6/dkb4yOlt3btWrz66qtYt24dmjdvrresWLFiBrWkYmNjDWpTpefh4aF3D5FWXoyR5vb74Yfa574RI9J3jl4TRYsexptvAi++qK1ZHx0NxMUB/v5AWNh/MfXSJQS98grw88/AggXaQSfsiDGSKOuwcIrISkeOHIGXlxf+97//GSy7ceOG0i5/4MCBWLZsGQYNGoThw4cjICAAHh4eGDBgAB48eKB8qL/++utITk7GsmXLsGLFCgQEBKBHjx6YNGkSfHx8cOPGDWXUHFMPeoX+e8E5cuQI3N3dlSrCgPZBwsvLCxUqVFD+9vDwMHj41D1w1KhRQzkWk/v9rwp4IRN9SHh7eyMsLAyA9iFixAhg/35tAdRbb2kfMJ7ShiMRbdXukSOB9u3/e/CwQZEiRZSHpfTu3LkDAEp/GmrTWZqWKC/Ki/Gxe3fT+12yJENhe6dO8K5RA2HHj2v7Spkxw+S5BGDQ/MNeGB8pvcjISPTv3x+RkZFo27atwfJ69ephx44dGDVqlDLv559/Rv369bMym7lCXoyRme23Uyftc9++fcD160CxYt6oXz8Mrq7Apk3AqFH6LfdKlABmzwY6dgyD2yefAMOHA++8AzRvDpQvb/zEW4gxkihrsXCKyEpHjhxBYGCgwTdTBw4cwL///ou2bdvizJkzWLx4MWbMmIF33nlHSRMXF4c///xTry8HNzc3vPvuu3j33Xdx9epVLFy4EJMmTUL+/Pkxffp0XLlyBQAwe/ZsvPDCC0bzVKZMGSVv1apV03sQOHr0KMLCwuDi4qL8Xa1aNbi7uxscl7+/P0JDQwHA9H4fPNA+CERHo8yiRdr2/v8VROns2bMHTZs2zfRcal0EUAoAlGGDJ0wAmjXTDttubSFV1apVERkZiZSUFL0XvJMnTwIAqlSpYlE6S9MS5UV5OT5m/Ha/c+cy8PfPkBkXF+zp1g1Njx/Xvl3Nnm32fF68eBGlSpUym8YajI+5V1JSEs6dO6f8ffHiRURHR8PPzw+hoaEYM2YMYmJisGLFCgDagqk+ffpg7ty5qFu3rlJDytPTE76+vgCAESNGoFGjRpg+fTrat2+PzZs345dffsH+/fuz/gBzuLwcI03tF9A+6zVpov199+49yJ/f9DNkTAygOwUXz59Hqe+/B375BejdG/j1VyBfPpPrqsUYSZTFnNmmkHIuticWCQkJEQ8PD6W9v4jIkydP5IUXXpAKFSrIkydP5KeffhIAsnXrVr11e/bsKQBk1qxZJrf/8OFD8fT0lDfffFNERM6dOycAZM6cOZnmrXjx4vL666/rzQsMDJRhw4YpfwcEBMjgwYMN1q1bt65eW3iz+01IEKlXT9s5gL+/yMmTGRYnyOHDhw2myZMPC5BxepSunwH9SdcPlTX9BWzbtk0AyJo1a/Tmt2rVSm/IXrXpLE2bU/Eetx7PHeOjGgnx8XK4enU5DMjhTp2Mxkrd9OjRo0y3x/iYdXLCPW6qz8eIiAgREYmIiJDGjRsr6Rs3bmw2vc66deukfPnyki9fPqlQoYJsMNVJpAk54dxlBcbIzCUkJMhvvx2WwEBjz4xPp6JFD8v9+49ErlwRKVRI++A4YYLB9hgjswbvcbIFC6fIKnk98MTGxgoAKVOmjDRr1ky2b98umzZtkiZNmoivr6+c/K+Q5saNG1KgQAGpUaOG/PDDD7J+/Xpp2bKllClTRgDI3r17RURkyJAh8sorr8jy5cslKipKvv32W2nUqJH4+vrKmTNnlP02bdpUvL29ZfLkybJjxw75+eefZfny5dK3b1+JiooSkacdKi5ZskRZT9cB6bJly0RE5PLlywZpRLQPRp6envLBBx/ozTe73y1bRGrV0j4MBAaKnD6d6fmLijJeCGV62ibAOhky5GsBIC+//LKsW7dO1q1bJ8nJySIisnv3bnF1dZWJEyca7C88PFwKFy4sCxculF27dslrr72mdMJpTTpL0+ZEef0et0VeP3eMj4b7NWnvXm2Qc3MTOXfOmtMt27Ztk3Xr1snXXzM+ZpW8fo/bgueOMdKSGKn2eVHZzOrV2hmuriKHD4sIY2RW4z1OtmDhFFklrweeH374QQDIb7/9Jq+99pr4+PiIj4+PdOnSRf755x+9tFu3bpUKFSqIh4eHVKpUSebOnSuTJ08WFxcXSUxMFBGRzz77TBo2bCiBgYHi4eEhpUuXlv79+8v58+f1thUfHy9jxoyRcuXKSf78+aVw4cJSvXp1GTZsmPLt2+bNmwWAnDhxQlnvu+++EwDyxx9/6P2dPo2IyIkTJwSAbNy40bL93r4tEhamfSAoXlwkwznIKCVFWxtKf1QWc1NJo9/oAk9HsdJ9S2zsG7HExEQZPny4FCtWTNzd3aVatWoSGRlpdTpL0+ZEef0et0VeP3eMj4b7NatVK22ge+UVNafXQMmSjI9ZLa/f47bguWOMtCRG6sqaMpuGDtUWUKWkiEjXrtqZ9eqJpKUxRmYx3uNkC43If0M+EFkgISEBvr6+iI+Ph4+Pj7OzQ9lBXBzQtClw6hQQHAzs3QuULm0y+caN2lH5AO2jhVpRUU/7IyDH4T1uPZ47Mic19WmHv8WLAw0LHIXr87W0I0H88QfA/kayPd7j1uO5I0vs3q19tFQrOBj4avw1tBlRFrh/H4iMBLp3d1j+yBDvcbKFi7MzQES5hL///9m787io6v2P4+8BFU0FdxRBscUtN3K3MMyrhmkqevNqaZbtm2bdimtZmr9sT8ub7WGLZCnaci21BJfcTbJ9xQ1xLUEoUeD8/jgOMjLgMDBzmOH1fDzmMcOZ7zl85sh8nfmc7/fzlb74Qmrb1lwHuF8/affuEpvHxZnLBjdvXrZfk5FRzjgBwCJJSVJkpNk9jh1r3keO7Kq9vUeZWfqHHrI6RACoNKKjzYSTzeZa+/R0achNYfpuWLy54b77zAV8APgEklMAKk6TJtKqVdIFF0i7dklXXimdOFFi87g4aedOczTUgw+69iuaNauYUOH71qxZo6FDhyosLEw2m01Lly4ttX1SUpIGDBigxo0bKzg4WL1799by5cuLtVu8eLHat2+voKAgtW/fXkuWLPHQK0BVYh8tunev4/b0dGnghhkyAgKkpUulzZstiQ8AKpvAQGnOHPOxKwkq+0S/gZ/do+ONI8yln5991rNBAqgwJKcAVKxmzcwRVI0aSV9/LU2fXmpz+7LBjzxS+tUxm02KiDCvogGSlJOTo86dO2vu3LkutV+zZo0GDBigZcuWadu2berXr5+GDh2q7du3F7bZsGGDRo8erXHjxunrr7/WuHHjdNVVV2nTpk2eehmoAvLzpUmTnE9hNgzpR1s7Lao5ztwwdap3gwOASsydkfb7/qyl6w49IUnKmzlL2rfPQ9EBqEjUnIJbmE+Ms1q82BwmEBAgffml1KvXWXcpqQ6VPWG1aJH5IQWe52vvcZvNpiVLlmj48OFl2u/CCy/U6NGjNW3aNEnS6NGjlZWVpU8//bSwzeWXX6769esrMTHRpWP62rmD57lSNyVSafqtWhsF5J2UVq+W+vb1SmwoO97j7uPcwV32en2LF0uuXZMytF591FsbtavfBLVc9aanQ4R4j6N8GDkFwDNGjpSuuUYqKJDGj5dycs66S0lXx8LDSUyh4hUUFOjYsWNq0KBB4bYNGzZo4MCBDu0GDRqk9evXl3ic3NxcZWVlOdyAolyplbdTrfR73+vMH2bP9mg8AOBr7CPtR450dQ+b7tZzkqSI5PnK37zNU6EBqCAkpwB4zgsvmJmmX36RHnjApV2K1qFasMC8T0sjMYWK98wzzygnJ0dXXXVV4bb9+/crNDTUoV1oaKj2799f4nFmzZqlkJCQwltERITHYoZvcrVW3h/jJpkPli41Oz4AgIOyFEnfpF56R1crQIaO3Xh32ZaHBuB1JKcAeE69etKbp4ZRz50rff65S7vZr46NGWPeBwZ6KkBUVYmJiXrkkUe0cOFCNWnSxOE52xmfeA3DKLatqPj4eGVmZhbe9uzZ45GY4bvO9mXKXlOv67j20oAB5hcoF2upAUBVUtYi6fGapb9US/V2rDXrRwCotEhOAfCsAQOk224zH193nXT0qKXhAAsXLtTEiRP1/vvv6x//+IfDc02bNi02SurgwYPFRlMVFRQUpODgYIcbUFRpX6bsP8+efSoRP3myueH116Vjx7wUIQD4jrIUSd+rCD2lf5s//Pvf0vHjng0OgNtITgHwvCeflM4/31xD/a67rI4GVVhiYqImTJigBQsW6Iorrij2fO/evbVy5UqHbStWrFCfPn28FSL8lMs19S6/XGrdWsrMlObP93qcAOAL7GUgPv9cKlI6shibTVrQ/D4ZYWHmdGn7lQIAlQ7JKQCeV7u29NZb5sp9b7/NsGpUiOzsbKWmpio1NVWSlJaWptTUVO3evVuSOd1u/Pjxhe0TExM1fvx4PfPMM+rVq5f279+v/fv3KzMzs7DNpEmTtGLFCj3xxBP68ccf9cQTT+jzzz/XZPtoFqAcXKqpFxAg3Xmn+fj5581FJQAAxQQGSv37S6++aiahShqZOuv52rLNmmX+8H//Jx044N1AAbiE5BQA7+jdW7r/fvPxLbcwXQXltnXrVkVFRSkqKkqSNGXKFEVFRWnatGmSpIyMjMJElSS9/PLLysvL0+23365mzZoV3iZNmlTYpk+fPnrvvff05ptvqlOnTkpISNDChQvVs2dP7744+C2XaupNmCCFhJiLSXz2mXcDBAAf49LI1Guukbp1Mz9/PvSQJXECKJ3NMFi2AGWXlZWlkJAQZWZmUl8FrjtxQurQwfzC9eij0oMPWh0RSsB73H2cO1SIe+6Rnn1WGjhQWr7c6mhQBO9x93Hu4En5+dLatVJGhrlKanT0GRcA1q0zNwYESD/9ZJacQIXiPY7yYOQUAO+pUUOaMcN8/NRT0h9/WBsPAFRWd9xhfoFasUL6/nurowGASu9sI1Pze1+iIz1jpYICpd/zjPLzrYgSQElITgHwrquukjp1krKyzELpAADl50spKVJionmf36KVdOWV5pPPP29laADg85KSpMhIKW6TWWKi4UdvqlvEAcqgApUIySkA3hUQIM2caT5+/nlp//4y7V7sCxxXvQD4OPuXpn79pLFjzfvISGnNRZPNBm+9xUhTAHBTUpI0apS5aPQa9dVG9VRN5WpUxgsaNYp1eoDKguQUAO8bMkTq1Uv6+29z1RQXlfQFjg8VAHxV0S9NRaWnSzHT+upoZGezr3ztNWsCBAAflp8vTZokna6ybNOTuk+SdJv+q9pGtiZP5mInUBmQnALgfTbb6aTUyy9Lu3addZfSvsBx1QuALyr+pek0w5Bks+n/Mu+QJGXNfkMpyQZfoACgDNauLf7Z8UMN009qrfo6qhv0qvbsMdsBsBbJKQDWuOwyqX9/6eRJafr0Upue9QucxFUvAD7H2ZemogxDeunP0crROQrO+EkPXLaJ0aIAUAYZGcW3FShQT+teSdIUPatqOum0HQDvIjkFwDr20VPz50s//lhiM1e+wHHVC4CvceXLULbqarFGSpKu05uMFgWAMmjWzPn2tzVOGWqqCO3VGCWW2A6A95CcAmCdnj3N1agKCqSHHy6xmatXs7jqBcCXuPpl6E1dJ0n6l95TkPG3JEaLAoAroqOl8HCzokRRuaqpOZokSZpa7Unl5xkstgNYjOQUAGs9+qj5ieH996Vvv3XaxNUvcFz1AuBLSvrSdKbVulRpilSIsjRcSxktCgAuCgyU5swxH5/Z176sW5SlumqT952eHbCMxXYAi5GcAmCtTp2kuDjz8dy5Tpuc7QuczSZFRJjtAMBXlPalqShDAZqvayWZU/vsGC0KAGcXFyctWiQ1b+64PbBhPb2smyVJ9+nJwu1MnwasQXLKx61Zs0ZDhw5VWFiYbDabli5dWmr7devW6eKLL1bDhg1Vq1YttW3bVs8995x3ggVKcued5v3bb0tHjxZ7urQvcPafZ8822wGALynpS9OZ7Mmpf+hzhWuPJOnAAaafAIAr4uKknTul5GRpwQLp88+lWrWk2ZqsE6quS7VGPbVREovtAFYhOeXjcnJy1LlzZ80tYcTJmWrXrq077rhDa9as0Q8//KAHH3xQDz74oF555RUPRwqUom9fqUMH6a+/zOLoTpT0BS483NxuH3wFAL7G2ZemM0eL7lQrJStGATI0Xm9Jku6+m+knAOCqwEApJkYaM8Z8vHevtE/N9bbGSXIcPcX0acD7bIbhbHF2+CKbzaYlS5Zo+PDhZdovLi5OtWvX1ttvv+3yPllZWQoJCVFmZqaCg4PLGCngxEsvSbfeKl1wgblyX4Dz3Hl+vvlBISPDrDEVHc2IKU/gPe4+zh0qQlKSOa1EOn0Vf7zma74m6Bedr9b6WZKtMIFFkt57eI+7j3OHyiIxURo71nzcVj/oB7VXgWxqqx/1i1oXtluwwExmwTW8x1EejJyq4rZv367169fr0ksvLbVdbm6usrKyHG5AhbrmGik4WPrlF2nlyhKbFb3qFRNDYgqAf3I2WnSRRumY6ugC/aqL9aUkpp8AgDuKLqLzo9rpYw1RgAzdpFdKbAfAs0hOVVHh4eEKCgpSt27ddPvtt+uGG24otf2sWbMUEhJSeIuIiPBSpKgy6tSRrjOXSy+pMDoAVCX26X720pB/qbY+0D8lSROUUNiO6ScAUDZnLrZjL4w+QQmqoVwW2wEsQHKqilq7dq22bt2ql156SbNnz1ZiYmKp7ePj45WZmVl427Nnj5ciRZVy223m/f/+J6WlWRsLAFQCgYFSaOjpn9+UmcQfrYWqpb8c2rJ6HwC45szFdj7T5dqr5mqkIxqhpZJYbAfwNpJTVVSrVq3UsWNH3Xjjjbr77rv1yCOPlNo+KChIwcHBDjeY/vrrL02fPl1t27ZVzZo11bBhQ40ZM0Z//vmnR39vdna2Jk+erLCwMNWsWVNdunTRe++959axXnvtNdlsNtWpU6dcv6fcMbVuLQ0caA4DmDfPrdcCoPLwtf5x1apVuv7669W2bVvVrl1bzZs317Bhw7Rt2zaHdikpKbLZbE5vGzdudGi7efNmDRo0SHXr1lWdOnXUr18/ffnll2V6PUWnlazTJUpTpOoqW4O0vMR2ACo/f+0jU1NTdcUVV6hFixaqVauWGjRooN69e+udd9456+8o7TNpRSs6fTpf1fS6JkqS7gx6hTp+gAWqWR0ArGcYhnJzc60OwycZhqExY8ZozZo1mjZtmrp06aIdO3bo7rvv1nnnnaeZM2d67HfHxcVpy5Ytevzxx9W6dWstWLBAY8aMUUFBgcbaKzy6ID09Xffee6/CwsKUmZlZrt9TITHdcYe0YoX02mvSI49I55zj8msBUHn4Yv84b948HTlyRJMmTVL79u116NAhPfPMM+rVq5eWL1+uyy67zKH9Y489pn79+jls69ChQ+HjLVu2qG/fvurRo4fefvttGYahJ598Uv3791dycrJ69+7t0uuxTz9JT5cMw6bFGql79YxGarGWaoRsNvN5pp8AvsOf+8ijR48qIiJCY8aMUfPmzZWTk6N3331X48aN086dO/Xggw86Pf7ZPpN6QlycNGyYOS0685uJMiY9qotzV0kdf5F0gVdiAHCKAZ927NgxY/v27cb27dsNScazzz5rbN++3di1a5dhGIbxwAMPGOPGjStsP3fuXOOjjz4yfv75Z+Pnn3823njjDSM4ONiYOnVqmX5vZmamIcnIzMys0Nfja5KTkw1JxgcffOCwPTQ01Jg8ebLHfu///vc/Q5KxYMECh+0DBgwwwsLCjLy8PJePNWTIEGPo0KHGtddea9SuXdvt31NhMeXlGUZkpGFIhvH66y6/DlQs3uPu49yZfLF/PHDgQLFtx44dM0JDQ43+/fsXbivptZ1p0KBBRmhoqJGTk1O4LSsry2jUqJHRp08fV1+SYRiGsXixYdhs5q23vjQMyTiqYCNIxw2bzXwe3sF73H2cu9P8uY8sSc+ePY2IiIgSny/tM6nXxMYahmTk33ufkZxsGAsWGEZysvnxFGfHexzlwbQ+H7d161ZFRUUpKipKkjRlyhRFRUVp2rRpkqSMjAzt3r27sH1BQYHi4+PVpUsXdevWTS+88IIef/xxzZgxw5L4fd0HH3yg+vXra8SIEYXb1qxZowMHDhS7wl6RlixZojp16uif//ynw/brrrtO+/bt06ZNm1w6zjvvvKPVq1frxRdfLPfvqaiYFBh4uvbUK6+U3hZApeWL/WOTJk2KbatTp47at2/vVq3FL7/8UjExMTqnyAjQunXrqm/fvlq/fr0yylAkquj0k43qpX1qphBl6apGq5h+AvigqthHNmrUSNWqOZ+4c7bPpF5z002SpCPPJmhgvxMaO1bq10+KjJSSkqwNDfB3JKd8XExMjAzDKHZLSEiQJCUkJCglJaWw/Z133qlvv/1WOTk5yszM1FdffaVbb71VAQH8Kbhj/fr16tmzpyRp3759evPNNzVy5Ej1799fQ4YMKdbeMAzl5eW5dCvNt99+q3bt2hX7D75Tp06Fz5/NwYMHNXnyZD3++OMKDw8v9++piJgKjR8vBQRImzaZS1UB8Dm+3D8WZf+/8sILLyz23O23365q1aopODhYgwYN0rp16xyeP3HihIKCgortZ9/2zTfflCkW++p9q5IDlD3A/EKbcOViElOAD6oKfWRBQYHy8vJ06NAhvfjii1q+fLnuv//+Yu1c+UzqLUtOXKF9aqbGBQd1pT4q3J6eLo0aRYIK8CQyEoCbjh8/rm+//VY9e/bUY489pubNm+v666/XOeeco4SEBNnsa9MWsXr1alWvXt2l285SkjJHjhxRgwYNim23bzty5MhZ47/tttvUpk0b3XrrrRXyeyoipkKhoVLfvubjRYtc3w9ApeDr/WNRt99+u3JycjR16tTCbSEhIZo0aZJefvllJScna86cOdqzZ49iYmK0fPnpIuXt27fXxo0bVVBQULgtLy+vcGRCWWORzMGlMTFS6wdGSpICPvpQOsuXUQCVi7/3kXa33XabqlevriZNmujuu+/W888/r5tvvtlpu7N9JvWG/HzprnuqF66KepNOj+A3DPN+8mSzHYCKR0F0wE1fffWV8vLy1KNHD7Vt21Y9e/bUxo0bNXv2bPXt21c7duwottJI165dtWXLFpeOHxYWVurzzj64uPKcJC1evFgff/yxtm/ffta2Zfk95YmpmH/+U0pJkT74QLr33rLtC8BSvtw/FvXQQw/p3Xff1QsvvKCuXbsWbi86nV6SoqOjNWLECHXs2FH33XefBg0aJMkcrTxx4kTdcccdmjp1qgoKCjR9+nTt2rVLkso3arlvX6lhQ+nwYbOS7xmF2QFUXv7eR9r95z//0Q033KCDBw/q448/1h133KGcnBzdW+RzXVk+k3ra2rXS3r3Sa7pBU/WYBmqlIpWmnWolyUxQ7dljtouJsTRUwC+RnALctHnzZklSjx491KhRI5177rkaOHCgWrdurTFjxmjjxo36xz/+4bBPnTp11KVLF5eOX9KcfElq2LCh0ytbf/zxhyQ5vSJml52drdtvv1133nmnwsLCdPToUUnm9BPJXGGlevXqql27dpl+T3liciouTrrzTmnzZnMeS2Rk2fYHYBlf7R+Lmj59umbOnKn/+7//0x133HHW9vXq1dOQIUP00ksv6e+//1atWrV0/fXX69ChQ5o5c6bmzZsnSerdu7fuvfdePfHEE2revLlLsThVrZq5xNQbb5jzTEhOAT6jqvSRLVq0UIsWLSRJgwcPliTFx8fr2muvVePGjcv0mdQb7GUAd6qVlmugBmmFbtBrelD/57QdgIrFtD7ATZs3b9a5556rRo0aOX3e2VWrihqS3bFjR/3www/F6grY65cUXcr8TIcPH9aBAwf0zDPPqH79+oW3xMRE5eTkqH79+rr66qvL/HvKE5NTTZsytQ/wUb7aP9pNnz5djzzyiB555BH95z//OWt7O+PUvI+iV//vv/9+HT58WN9884127typ9evX688//1Tt2rWdjjQoE3uxqaQk6dTUwfx8c9BpYqJ5z/QToPKpqn1kjx49lJeXp99//11S2T6TekOzZqcfv6obJUnX6w1V08kS2wGoODbD/kkKKIOsrCyFhIQoMzNTwcHBVodjifPPP19NmzZ1KIBrGIYGDBigAwcOOC10e+zYMf30008uHb9Tp06qUaOG0+c+/fRTDR48WO+9955Gjx5duD02NlY7duzQ7t27FRgY6HTf48ePa+PGjcW2P/7441q9erU+/fRTNWrUSB06dCjT7ylPTCWaN89cua9HD7M4OryG97j7OHe+2z9K0qOPPqpp06bpwQcf1KOPPupSPJL0559/qmPHjmrcuLG2b99eYrvdu3erU6dOuu666/Tcc8+5fHyncnOlxo2lY8ekDRuUtK+XJk0yp6XYhYdLc+awml9F4j3uPs6dqSr2kZI0fvx4vfvuu9q/f78aN25cps+k3pCfbw7UT0+XqhkntEcRCtVBjVCSlmqEbDazT01LM+v/oTje4ygXA3BDZmamIcnIzMy0OhRLHDlyxJBkSDImTpxofP7558ZHH31kDB8+3AgKCjLWr1/v8RgGDBhg1K9f33jllVeMVatWGTfeeKMhyXjnnXcK26SkpBiBgYHG9OnTz3q8a6+91qhdu7Zbv8edti7Zv98wAgIMQzKMtDT3jgG3VPX3eHlU9XPny/3j008/bUgyLr/8cmPDhg3FbnZjxowx7r//fuODDz4wkpOTjVdeecVo06aNUa1aNWPlypWF7b755hvjkUceMT755BNj5cqVxtNPP200atTI6Natm3Hs2LGKebFjxhiGZPx05b2GzWZ2l0VvNpt5W7y4Yn4dfOM9vnr1amPIkCFGs2bNDEnGkiVLSm2/b98+Y8yYMUbr1q0Nm81mTJo0qVibN998s/C9XfT2999/uxyXL5w7T6sKfeSNN95o3HPPPcbChQuNlJQUY9GiRcbo0aMNSca///3vs8ZX0mdSb1i8+HS/+bjuMwzJSNJw+lIX8R5HeZCcgluqesfz6aefGpKM8ePHG82bNzeqV69utGjRwhg1apSRmprqlRiOHTtm3HXXXUbTpk2NGjVqGJ06dTISExMd2iQnJxuSjIcffvisxyvpg4Arv8edti6LiTG/YT31VPmOgzKp6u/x8qjq586X+8dLL73U6Zdv+81u1qxZRpcuXYyQkBAjMDDQaNy4sTFixAhj8+bNDr/jp59+Mvr27Ws0aNDAqFGjhnH++ecbDz74oJGdnV1xL3bRIsOQjJ2B5xpSQbHklD1BFRFhGHl5FfdrqzJfeI8vW7bMmDp1qrF48WKXklNpaWnGXXfdZcyfP9/o0qVLicmp4OBgIyMjw+FWFr5w7jytKvSRb7zxhhEdHW00atTIqFatmlGvXj3j0ksvNd5++22X4rMyOWUYZgIqPNwwOmiHYUjGcdUwOjT/g8SUC3iPozyY1ge3VPUhmzNmzNDMmTOVlZWlmjVrWh2Of2NqnyWq+nu8PKr6uaN/9LKcHOU3bKzA3L/VRdv1tbqU2DQ5mRWmKoKvvcdtNpuWLFmi4cOHu9Q+JiZGXbp00ezZsx22JyQkaPLkyYVFq93ha+fOE+gjfUN+vrkqX5fxnVRvzzcqePlVGRNv0Nq1ZkH0Zs2k6Gim952J9zjKg4LogBs2b96sjh078qHCG+LipICA06v2AajU6B+9rHZt7et0uSQpTkmlNmWFKZRXdna2WrZsqfDwcA0ZMqTU+mpwjj7SNwQGmsn8ereNlSQdef5dRUaaC6OOHWveR0aa61EAqBgkpwA3bNmyRT169LA6jKohNFS69FLzMav2AZUe/aP3ZQ8wq52P1OJS27HCFMqjbdu2SkhI0EcffaTExETVrFlTF198sX755ZcS98nNzVVWVpbDraqjj/QxY8ZIkhp+t1pG0dUmZBZOHzWKBBVQUUhOAW44cOCA5s2bZ3UYVcc//2nev/9+qc1YQh2wHv2j97WeMkQnVF0X6nu10Y/FnrfZpIgIcwoK4K5evXrpmmuuUefOnRUdHa33339frVu31gsvvFDiPrNmzVJISEjhLSIiwosRV070kb4lP7ylNte4RAEy9C+95/CcvTjO5Ml85gQqAskpAJWffWrfli0lTu1LShLDrQFUSYEN6+mPqP6SpJFnTO2z2cz72bOpjYKKFRAQoO7du5c6cio+Pl6ZmZmFtz179ngxQqD81q6V3jhxtSTpar1b7HnDkPbsMdsBKB+SUwAqv7NM7UtKModVnzHamuHWAKqMpreNlCSNru7Y4YWHm91mXJwVUcGfGYah1NRUNStlvmhQUJCCg4MdboAvyciQPtA/dVLVFKVUtdP3JbYDUD4kpwD4hhKm9uXnS5MmnR5aXRTDrQFUGcOGSQEB6nRymzYk7tSCBebqfGlpJKaqouzsbKWmpio1NVWSlJaWptTUVO3evVuSOaJp/PjxDvvY22dnZ+vQoUNKTU3V99+f/iI+ffp0LV++XL///rtSU1M1ceJEpaam6pZbbvHa6wK8rVkz6Q811GcyF54YqwUltgNQPiSnAPiGEqb2rV1bfMRUUQy3BlAlNG4s9e0rSeqVsURjxpgrTTGVr2raunWroqKiFBUVJUmaMmWKoqKiNG3aNElSRkZGYaLKzt5+27ZtWrBggaKiojR48ODC548ePaqbbrpJ7dq108CBA5Wenq41a9ZQ3Bt+LTraHIG6QObUPjM5dfqKKDX9gIpDcgqAbyhhap+rw6gZbg3A79mHSC0ufdU++L+YmBgZhlHslpCQIElKSEhQSkqKwz7O2u8scjHoueee065du5Sbm6uDBw9q+fLl6t27t/deFGCBwEBpzhzpYw1VtmrrXKWplzZKoqYfUNFITgHwHU6m9rk6jJrh1gD83ogR5v369WTkAaCCxMVJby2ureXnmH2svTA6Nf2AikVyCoDvcDK1zz7c2n716kwMt/Zfa9as0dChQxUWFiabzaalS5eW2j4jI0Njx45VmzZtFBAQoMmTJxdrk5CQIJvNVux2/Phxz7wIoCKFh0s9e5rzmc/yfgAAuC4uThq+cKwk6Ya6C5XyeR41/YAKRnIKgO8oOrXvgw8knR5uLRVPUDHc2r/l5OSoc+fOmjt3rkvtc3Nz1bhxY02dOlWdO3cusV1wcLAyMjIcbjVr1qyosAHPsn9TIjkFABUq8PIBUsOGqnnssC4NWMtnS6CCkZwC4Fuuusq8P5WckszvYosWSc2bOzZluLV/i42N1cyZMxXn4j9wZGSk5syZo/HjxyskJKTEdjabTU2bNnW4AT5j6FDzfvVq6a+/rI0FAPxJtWrSlVeaj5cssTYWwA+RnALgW0pYtS8uzvwxOVksoY5yyc7OVsuWLRUeHq4hQ4Zo+/btpbbPzc1VVlaWww2wTNu2UosWUm6umaACAFSc4cPN+6VLzSnUACoMySkAvqVJk9NT+86YthIYaC6dzhLqcFfbtm2VkJCgjz76SImJiapZs6Yuvvhi/fLLLyXuM2vWLIWEhBTeIiIivBgxcAabTRo0yHz82WfWxgIA/mbAAKl2bWnPHumrr6yOBvArJKcA+J4rrjDvV660Ng74nV69eumaa65R586dFR0drffff1+tW7fWCy+8UOI+8fHxyszMLLzt2bPHixEDTlx+uXm/fHnhpvx8KSVFSkw07/PzLYkMAHxbrVqn+1hq+wEViuQUAN8zcKB5n5JiTl0BPCQgIEDdu3cvdeRUUFCQgoODHW6Apfr3N4eO/vSTlJampCQpMlLq108aO9a8j4yUkpKsDhQAfJB9ah91p4AKRXIKgO/p0EFq2tQs9rt+vdXRwI8ZhqHU1FQ1a9bM6lAA14WESH36SJK2P75co0ZJe/c6NklPl0aNIkEFAGV2xRVmcfTvvpNKuXgFoGxITgHwPTbb6dFTRaatoGrJzs5WamqqUlNTJUlpaWlKTU3V7t27JZnT7caPH++wj719dna2Dh06pNTUVH3//feFz0+fPl3Lly/X77//rtTUVE2cOFGpqam65ZZbvPa6gApxqu7UgbeWO63Za982eTJT/ACgTOrXN4ubSkztAyoQySkAvsmenFqxwto4YJmtW7cqKipKUVFRkqQpU6YoKipK06ZNkyRlZGQUJqrs7O23bdumBQsWKCoqSoMHDy58/ujRo7rpppvUrl07DRw4UOnp6VqzZo169OjhvRcGVIRTNVH6HP9C1XXCaRPDMGv6rl3rzcAAwA+MGGHeM7UPqDA2w2ANTJRdVlaWQkJClJmZSX0VWOPAAXNqn/1xkybWxuNneI+7j3OHSqGgQMfrN1XNrEO6VClao0tLbLpggbnKKVzDe9x9nDv4jfR0KTzcHM2fni4x/V8S73GUDyOnAPim0FCpSxfz8eefWxoKAFQ6AQE62tOc2ne5Piu1Kd+pAKCMmjeXevQwh6B+9JEkVkUFyovkFADfxdQ+AChRk2vM5NQgOa/NZ7NJERFSdLQ3owIAP2Gf2rd0KauiAhWA5BQA31U0OcUMZQBwEHC52UdepO1qqv0Oz9ls5v3s2VJgoJcDAwB/MHy4JKng8y90/chMVkUFyonklJedPHlSe/bs0U8//aQ//vjD6nAA33bxxVKtWlJGhrmcLyo1+j/Ay5o0kbp2lSSNru84wjQ8XFq0SIqLsyIwnIn+EfBBbdvKaNtWAXknFatlxZ5mVVSgbEhOeUF2drZefvllxcTEKCQkRJGRkWrfvr0aN26sli1b6sYbb9SWLVusDhPwPTVrSpeeKvLL1L5Kif4PsNipVfuevXy5kpPN4ufJyVJaGokpq9E/Ar5v90Xm1L7hWur0eVZFBVxHcsrDnnvuOUVGRurVV1/VZZddpqSkJKWmpuqnn37Shg0b9PDDDysvL08DBgzQ5Zdfrl9++cXqkAHfQt2pSov+D6gEBpl1pwJWLFdMdL7GjJFiYpjKZzX6R8A//Nh2uCRpsJYpSMdLbJeR4aWAAB9mMwwKtXjSP//5T02bNk0dO3YstV1ubq5ef/111ahRQzfccIOXonMfy4Si0vj+e+nCC81RVH/+ad6j3CriPe6v/d/Z0D+iUjl5UmrUSMrKkjZvlrp3tzoin0f/6D76R/iblFUFOr9/C4UrXYP1P32qwU7bJSebFwb8He9xlAfJKbiFjgeVhmGYy02lp0srV0r/+IfVEfkF3uPu49yh0hk50qzI++ij0oMPWh2Nz+M97j7OHfxNfr70TsjtujbnRb2qG3STXnV43mYza/ylpVWNEau8x1EeTOvzok8++UQFBQUVesw1a9Zo6NChCgsLk81m09KlS0ttn5SUpAEDBqhx48YKDg5W7969tXy58yWmAZ9gs52e2sffcqXlif4PgItO1Z3SZ59ZGwecon8EfFdgoHTuPWbdqSv1kQJ0uvI5q6ICZUNyyouGDRumw4cPV+gxc3Jy1LlzZ82dO9el9mvWrNGAAQO0bNkybdu2Tf369dPQoUO1ffv2Co0L8CrqTlV6nuj/ALjoVN0pbdhgTn9GpUL/CPi26Acv1Yna9RSqg+qtDYXbWRUVKJtqVgdQlXhiBmVsbKxiY2Ndbj979myHnx977DF9+OGH+vjjjxUVFVXB0QFe8o9/mJenduwwK042a2Z1RDgDM8gBC7VoIbVrJ/3wg/TFF9KoUVZHhCLoHwEfV726aowYIr3zjhKvWqp1wy9Rs2ZSdDQjpoCyYOSUl6WmpionJ8dhW3p6umVzcgsKCnTs2DE1aNCg1Ha5ubnKyspyuAGVRqNG0kUXmY8//9zaWFCiytb/AVWKfWof058rJfpHwMeNMKf2RWxdojH/MlgVFXADI6e8LDY2VjabTZGRkerUqZPatGmjXbt2qV69epbE88wzzygnJ0dXXXVVqe1mzZql6dOneykqwA0DB0rbtplT+8aNK9ycny+tXXt6QBVXsaxT2fo/oEq5/HLpuefMulOGcboYCioF+kfAxw0aZK4Y/fvv0jffSJ06WR0R4HNITnnZzz//rIMHD+qbb77Rjh079M0336igoECvvPKK12NJTEzUI488og8//FBNmjQptW18fLymTJlS+HNWVpYiIiI8HSLguoEDpVmzzBX7CgqkgAAlJUmTJkl7955uFh4uzZnD/H8rVKb+D6hyoqOloCCzQ/zlF6l1a6sjQhH0j4CPq13b/Cz60UfSkiUkpwA3kJzysrp16+q8885T7969LY1j4cKFmjhxoj744AP94x//OGv7oKAgBQUFeSEywE29e5sfDA4ckL75Rkm/ddaoUeYAgaLS081yKxSo9L7K0v8BVVKtWlKfPlJysrRqFcmpSob+EfADw4ebyalPPpEeftjqaACfQ80pLxo6dKiqV69udRhKTEzUhAkTtGDBAl1xxRVWhwNUjKAgKSZGklTw6XJNmlQ8MSWd3jZ5sjnlD95RWfo/oEq77DLz/osvJJl9YEqKlJho3tMnWoP+EfAT9kWqtm41L5YCKBOSU1704Ycfqn79+hV6zOzsbKWmpio1NVWSlJaWptTUVO3evVuSOR1v/Pjxhe0TExM1fvx4PfPMM+rVq5f279+v/fv3KzMzs0LjAiwxYIAk6WjSKoepfGcyDGnPHrMWFbzDE/0fgDKyJ6eSk5W0qECRkVK/ftLYseZ9ZKSUlGRlgFUT/SPgJ5o2Pb1AD4tPAGVGcsrD7EkiV6Wnp5ep/datWxUVFaWoqChJ0pQpUxQVFaVp06ZJkjIyMhxiePnll5WXl6fbb79dzZo1K7xNmjSpTL8XqJT69ZMk1d2xTtV08qzNMzI8HVDV5un+D0AZde8u1akjHTmiR/+5o1gS3z7tmQSV59E/An5q8GDz/tNPrY0D8EEkpzyse/fuuvHGG7V58+YS22RmZurVV19Vhw4dlFTGT4QxMTEyDKPYLSEhQZKUkJCglJSUwvYpKSmltgd8WocOUoMGqp6bo67adtbmzZp5IaYqzNP9H4Ayql5dRnRfSVI/rSr2NNOevYf+EfBT9ql9y5dLeXnWxgL4GAqie9gPP/ygxx57TJdffrmqV6+ubt26KSwsTDVr1tSff/6p77//Xt999526deump556SrH2Dg1A2QUESJdeKi1ZomHBKdp8rJfTulM2m7lqX3S090OsSuj/gMrnt8j+Ol/LdJlW6TlNKfZ80WnPp8r4wQPoHwE/1bOn1KCB9Mcf0ubN5kIUAFzCyCkPa9CggZ5++mnt27dP8+bNU+vWrXX48GH98ssvkqSrr75a27Zt05dffskHD6AinPo2df25KZLMRFRR9p9nz5YCA70WVZVE/wdUPr9EmHWnLtXqUqc/M+3Zs+gfAT8VGCgNHGg+XrZMEotPAK6yGYazcQVA6bKyshQSEqLMzEwFBwdbHQ5w2o4dUufOUu3aWvLGn7rrnuoOdVUiIszEVFycZRH6BN7j7uPcoTJLWVWgDv2bqJGOqLfWa6N6O22XnMzIqZLwHncf5w5VwttvS+PHS1FRSnrwK02aJIfPouHh0pw5/vlZlPc4yoORUwD8y6m6U8rJ0YgW27Rzp/kla8EC8z4tzT8/DACAK6IvDdDGWubiEf31RbHnbTYzic+0ZwBw06BB5v327bpjZAaLTwAuIjllkb///tvpyivfffedBdEAfsRed0qSUlIUGGhe/R8zxrxnKp/16P8A6wQGSs2vMaf2XXZGUXSmPVuP/hHwA02ayOjWXZI0SJ8Ve5rFJwDnSE5ZYNGiRWrdurUGDx6sTp06adOmTYXPjRs3zsLIAD9hn4tSZKVKVA70f4D1ou7tL0nqo/Wqqb8Lt4eHS4sWMbrUKvSPgP/Y1d6sFRerT50+X3TxCQAmklMWmDlzpr766it9/fXXeuONN3T99ddrwYIFkiRKgAEVwJ6cWrdOOllywV94H/0fUAlccIHUvLlqKlcbnl7PtOdKgv4R8B8/nz9YkjRQKxSovBLbsfgEcFo1qwOoik6ePKnGjRtLkrp166Y1a9YoLi5Ov/76q2xnLi0GoOzsdaf++EPatk3q1cvqiHAK/R9QCdhs0mWXSW+/rS5HvlCXe/pbHRFE/wj4kxp9uumQGqmxDqu3NmidnBfya9bMy4EBlRgjpyzQpEkT7dixo/Dnhg0bauXKlfrhhx8ctgNw0xl1p1B50P8BlUT/UwmpVatKbwevoX8E/Ed0TKDWnmMWRh+sZcWeZ/EJoDiSU170zTffKC8vT2+//bZCQ0MdnqtRo4YSExO1evVqi6ID/Ax1pyoV+j+gkrnMLIquLVukzExrY6ni6B8B/xMYKIXfZE7tOzM5xeITgHMkp7yoc+fOqlOnjq688ko98MADmjNnjlJSUnT06NHCNhdffLF1AQL+hLpTlQr9H1DJRESYtacKCqQ1a6yOpkrzRP+4Zs0aDR06VGFhYbLZbFq6dGmp7TMyMjR27Fi1adNGAQEBmjx5stN2ixcvVvv27RUUFKT27dtryZIlZYoLqEp6TB0ow2ZTZ+1QmE6vwsniE4BzJKe8aN26dWrQoIFatWql3NxcJSQk6LLLLlPDhg3Vpk0bPfTQQw4fRACUQ4cOUsOGUk6OWXcKlqL/Ayoh++ipL76wNo4qzhP9Y05Ojjp37qy5c+e61D43N1eNGzfW1KlT1blzZ6dtNmzYoNGjR2vcuHH6+uuvNW7cOF111VUOqwoCKKJRI9l69pQkrbr3UxafAM6C5JQX3XHHHXrxxRe1ePFiLViwQNu3b1dycrLOPfdcXXvttVq7dq2ioqJ06NAhq0MFfB91pyoV+j+gErInp6g7ZSlP9I+xsbGaOXOm4lz8BhwZGak5c+Zo/PjxCgkJcdpm9uzZGjBggOLj49W2bVvFx8erf//+mj17tstxAVVObKwkqc3vn2rMGHNgP1P5AOdITnnRjz/+qPbt2ztsu/TSS/Xcc8/pq6++UnJysrp166b//Oc/FkUI+BnqTlUa9H9AJdSvn3n/zTfSwYOSpPx8s8tMTDTv8/Mti67K8JX+ccOGDRo4cKDDtkGDBmn9+vUl7pObm6usrCyHG1ClDDbrTmnlSunECWtjASo5klNe1L17d73zzjvFtl944YVasWKFbDab/v3vf+vzzz+3IDrAD1F3qtKg/wMqocaNpU6dzMcpKUpKkiIjzZzV2LHmfWSklJRkZZD+z1f6x/379xcr2B4aGqr9+/eXuM+sWbMUEhJSeIuIiPB0mEDlctFFUpMm0rFjUimJXAAkp7zqxRdf1OzZszV27Fj9+OOPkqQTJ07oueeeU4MGDSRJjRs31oEDB6wME/AfF15I3alKgv4PqKROJfF/fyNFo0ZJe/c6Pp2eLo0aRYLKk3ypf7TZlxk7xTCMYtuKio+PV2ZmZuFtz549ng4RqFwCAqTLLzcfL1tWelugiiM55UUXXnihNmzYoIyMDLVv3161atVS7dq19eqrr+rxxx+XJG3fvl1hYWEWRwr4CepOVRr0f0AldWpqX/4XyTKM4k/bt02ezBQ/T/GV/rFp06bFRkkdPHiw2GiqooKCghQcHOxwA6qcU3WnSE4BpatmdQBVzYUXXqjk5GTt2rVLX3/9tQIDA9W1a1c1bdpUknllzP5BBEAFiIkxL/knJ0sPPGB1NFUa/R9QCfXtK8Nm0wV5P6qpMrRfzYo1MQxpzx5p7drTs6VRsXyhf+zdu7dWrlypu+++u3DbihUr1KdPHwujAnzAwIHmBdPvvjOHp4aHWx0RUCmRnLJIy5Yt1bJly2Lbo6OjLYgG8GP2b1JffmnWnape3dJwUHH935o1a/TUU09p27ZtysjI0JIlSzR8+PAS22dkZOiee+7Rtm3b9Msvv+iuu+5yusrU4sWL9dBDD+m3337Teeedp//7v//TiBEjyhQb4DMaNNDRFp1Vf1eqLtVqLdS/SmyakeHFuKqoiuofs7Oz9euvvxb+nJaWptTUVDVo0EAtWrRQfHy80tPT9dZbbxW2SU1NLdz30KFDSk1NVY0aNQqLtU+aNEl9+/bVE088oWHDhunDDz/U559/rnXr1rnxSoEqpEEDqXt3adMmacUK6frrrY4IqJSY1gfAv51Rd4qVqPxHTk6OOnfurLlz57rUPjc3V40bN9bUqVPVuXNnp202bNig0aNHa9y4cfr66681btw4XXXVVdq0aVNFhg5UKtndzal9/ZRcartmxQdVoZLaunWroqKiFBUVJUmaMmWKoqKiNG3aNElmsn737t0O+9jbb9u2TQsWLFBUVJQG21cak9SnTx+99957evPNN9WpUyclJCRo4cKF6tmzp/deGOCr7HWnPvtMEiujAs7YDMNZhQGgdFlZWQoJCVFmZib1A1D5jRwpJSXp26tnKXb1Aw4Ff8PDpTlzpLg468KrjHztPW6z2c46cqqomJgYdenSpdjIqdGjRysrK0uffvpp4bbLL79c9evXV2JiokvH9rVzB+Qv/UiBI4bpJ7VWW/1U7Hmbzewr09KkwEALAqxkeI+7j3OHKmvDBqlPH6l+fSW9fEiTpgT65edR3uMoD0ZOAfB/p6b27X03hZWoUKoNGzZo4MCBDtsGDRqk9aUs/5ybm6usrCyHG+BLAmPMulNt9LPCtM/hOftCbLNnk5gCALd17y7Vqyf9+aeeumoLn0cBJ0hOAfB7+dExkqRLtE7VdNLhOVaiQlH79+8vtvJUaGhosRWqipo1a5ZCQkIKbxEREZ4OE6hY9erJdmr6V1yDFIenwsOlRYt8/2o+AFiqWjUV/GOAJGmQPiv2NJ9HAZJTAKqAtX9cqMNqqDrKUTdtLfZ80ZWoAJt9qMgphmEU21ZUfHy8MjMzC2979uzxdIhAxetn1p2aMyJZycnSggXmIqdpaSSmAKAi/Bw5SJI0SMudPs/nUVR1JKcA+L2MAwFarUslSTFKKbkdK1FVeU2bNi02SurgwYPFRlMVFRQUpODgYIcb4HNOJacCUpIVEyONGWPOiGYqHwBUjB9bmsmpHtqs+vqjxHZ8HkVVRXIKgN9r1kxKUYyk0pNTrESF3r17a+XKlQ7bVqxYoT59+lgUEeAll1wiBQRIv/1mXroHAFSoeh3C9a0uVKAK9A99XmI7Po+iqiI5BcDvRUdLP4bGSHJed8pmkyIizHbwHdnZ2UpNTVVqaqokKS0tTampqYXLo8fHx2v8+PEO+9jbZ2dn69ChQ0pNTdX3339f+PykSZO0YsUKPfHEE/rxxx/1xBNP6PPPP9fkyZO99bIAa4SESF27mo9TUiwNBQD8UXS0tL5OyVP7+DyKqo7kFAC/Fxgo3TrXrDtVW3851J1iJSrftXXrVkVFRSnqVCHnKVOmKCoqStOmTZMkZWRkFCaq7Oztt23bpgULFigqKkqDBw8ufL5Pnz5677339Oabb6pTp05KSEjQwoUL1bNnT++9MMAqp1Y2JTkFABUvMFBqf3fR5JRR+ByfRwHJZhiGcfZmgKOsrCyFhIQoMzOT+irwGem9Rqr5piTF6zE9rnhJ5hWq2bMp+Hsm3uPu49zBZ336qTR4sNSqlfT771ZHU2nxHncf5w5V3vHjygtpoGon/lYHfaPv1EGS/3we5T2O8mDkFIAqo/nVMZKkf3dLYSUqADjTJZeYl+zT0qRdu6yOBgD8T82aqnaZuUjP0luX83kUKILkFICq49SUlQbfr9OYUSdZiQoAiqpbV+rWzXzM1D4A8IxB5tS+839dzsqoQBEkpwBUHRdeKDVqJP31l7R169nbA0BV06+feZ+cbG0cAOCvLr/cvF+zxvxMekp+vnldIDHRvM/PtyQ6wDIkpwBUHQEB0qXmUGpGBQCAE/bk1KpVEmVJAaDitWkjtWgh5eZKq1dLkpKSpMhIswseO9a8j4w0twNVBckpAFULq1EBQMkuvliqXl3as0f67TerowEA/2OzFU7t0/LlSkqSRo2S9u51bJaebm4nQYWqguQUgKrFnpxat046edLSUACg0qldW+rd23z8xRfWxgIA/urU1D7js880aZLzgar2bZMnM8UPVQPJKQBVS/v21J0CgNJcdpl5v2qVtXEAgL/q318KDJTtp58UuHdnic0MwxzIunat90IDrEJyysetWbNGQ4cOVVhYmGw2m5YuXVpq+4yMDI0dO1Zt2rRRQECAJk+e7JU4gUqjaN2plSutjQUAKqP+/c37VaukggJrYwEAfxQSUjhKdZCWn7V5RoanAwKsR3LKx+Xk5Khz586aO3euS+1zc3PVuHFjTZ06VZ07d/ZwdEAlZV8l5dNPrY0DACqjHj2kc86RDh+Wvv3W6mgAwD+d+jx6uT47a9NmzTwdDGA9klM+LjY2VjNnzlRcXJxL7SMjIzVnzhyNHz9eISEhHo4OqKRiY837TZvML18AgNNq1JD69jUfM7UPADzj1OfRAbbPVUMnnDax2aSICCk62puBAdYgOQWX5ObmKisry+EG+KzmzaXOnc2J/MvPPpQaAKoce90piqIDgGd06SI1aaI6Rrb6aL1sNsen7T/Pni0FBno7OMD7SE7BJbNmzVJISEjhLSIiwuqQgPIZPNi8X7bM2jgAoDKy151avVrKy7M2FgDwRwEB0qBBkqSXhn+m5s0dnw4PlxYtklycIAP4PJJTcEl8fLwyMzMLb3v27LE6JKB87Mmpzz5jfV4AOFPnzlL9+tKxY6xsCgCecmpqX5vfP9XOnVJysrRggXmflkZiClVLNasDgG8ICgpSUFCQ1WEAFadXL6lePemPP6TNmwtXTAEAyJxD0q+flJRk1p3q1cvqiADA/wwYYM7f27FDgQf2KSYmzOqIAMswcgpA1VStWuFQaqb2AYAT1J0CAM9q1Ejq3t18/NnZV+0D/BnJKR+XnZ2t1NRUpaamSpLS0tKUmpqq3bt3SzKn440fP95hH3v77OxsHTp0SKmpqfr++++9HTpgPepOAUDJ7MmpL7+Ujh+3NhYA8Ff2VaRJTqGKIznl47Zu3aqoqChFRUVJkqZMmaKoqChNmzZNkpSRkVGYqLKzt9+2bZsWLFigqKgoDbZ/SQeqEvvIqa++kvbvtzYWAKhs2raVmjWTcnOl9eutjgYA/NPll5v3K1eyAAWqNJJTPi4mJkaGYRS7JSQkSJISEhKUkpLisI+z9jt37vR67IDlQkOlbt3Mx1ytAgBHNtvp0VOrVlkbCwD4q+7dpQYNpKNHpU2brI4GsAzJKQBVG1P7AKBk/fub99SdAgDPCAyUBg40H3OxFFUYySkAVZs9ObVihXTypLWxAEBlYx85tWWLlJVlbSwA4K/sU/tITqEKIzkFoGrr1s1cKSUzU9qwwepoAKByadlSOu88KT9fWrPG6mgAwD/Z66Bu3SodPGhtLIBFSE4BqNoCA09frWJqHwAUR90pAPCspk2lUwtcacUKa2MBLEJyCgCoOwUAJaPuFAB4HhdLUcWRnAKAgQOlgADpm2+kPXusjgYAKpd+/cz7HTukQ4esjQUA/NUVV5j3n35KHVRUSSSnAKBhQ6lnT/Pxp59aGwsAVDZNmkgdO5qPk5OtjQUA/FWvXlLjxtLRo9LatVZHA3gdySkAkE5P7SM5BQDFUXcKADwrMFAaOtR8/OGH1sYCWIDkFABIp5NTn38u5eZaGwsAVDb2ulMkpwDAc4YNM+8//FAyDGtjAbyM5BQASFKXLuZKKdnZ0rp1VkcDAJVL374yAgKkX37Rh3P3KCVFys+3OigA8DP/+IdUq5a0a5dZ5w+oQkhOAYBkFkSPjTUfs0oKADhI+iJE26t1Nx/fuUr9+kmRkVJSkrVxAYBfOeccacAA8zFT+1DFkJwCADv71D6SUwBQKClJGjVK+uyEWXeqv76QJKWnm9tJUAFABSo6tQ+oQkhOAYDdP/5hFqP88Ufp99+tjgYALJefL02aZJY++UJm3anLtEqSUVgOZfJkpvgBQIUZMkSy2aSvvpL27rU6GsBrSE4BgF29etLFF5uPWbUPALR27envRuvVR8cVpHClq7V+lmQmrfbsYdVzAKgwTZpIffqYjz/6yNpYAC8iOQUARTG1DwAKZWScfnxctbRe5hemQVpeYjsAQDkxtQ9VEMkpACjKnpxatUr6809rYwEAizVr5vjzMpl95BX6X6ntYK01a9Zo6NChCgsLk81m09KlS8+6z+rVq9W1a1fVrFlT5557rl566SWH5xMSEmSz2Yrdjh8/7qFXAVRh9uRUcrKUmWltLICXkJwCgKI6dJA6dZKOH5def93qaADAUtHRUni4Wf5Ekj7REElSjFJUW9my2aSICLMdKo+cnBx17txZc+fOdal9WlqaBg8erOjoaG3fvl3/+c9/dNddd2nx4sUO7YKDg5WRkeFwq1mzpideAlC1tW4ttW0rnTwpffaZ1dEAXkFyCgCKstmku+4yH8+dK+XlWRsPAFgoMFCaM8d8bLNJP6mNftV5CtIJDdDnkqTZs812qDxiY2M1c+ZMxcXFudT+pZdeUosWLTR79my1a9dON9xwg66//no9/fTTDu1sNpuaNm3qcAPgIUztQxVDcgoAzjR2rNSwobRrF4UoAVR5cXHSokVS8+aSZNP/dIUk6aran2jRIvN5+LYNGzZo4MCBDtsGDRqkrVu36uTJk4XbsrOz1bJlS4WHh2vIkCHavn17qcfNzc1VVlaWww2Ai6680rxftswcQQX4OZJTAHCmWrWkm282H9uHDABAFRYXJ+3caZY/6RRvTu37V/AyxQ0vsDYwVIj9+/crNDTUYVtoaKjy8vJ0+PBhSVLbtm2VkJCgjz76SImJiapZs6Yuvvhi/fLLLyUed9asWQoJCSm8RUREePR1AH6lZ09z5b7MTGn1aqujATyO5BQAOHPrreY8lTVrpNRUq6OBExT8BbwrMFCKiZH6PdxXqlNHtowM6SwjZ+A7bPbCYqcYhuGwvVevXrrmmmvUuXNnRUdH6/3331fr1q31wgsvlHjM+Ph4ZWZmFt727NnjuRcA+JvAQGnoUPMxI/lRBZCcAgBnwsOlUaPMx4yeqpQo+AtYJChIGjDAfPzJJ9bGggrRtGlT7d+/32HbwYMHVa1aNTVs2NDpPgEBAerevXupI6eCgoIUHBzscANQBkXrTp1KGAP+iuQUAJRk0iTzfsEC6eBBa2NBMRT8BSw0xJzap//9z9o4UCF69+6tlStXOmxbsWKFunXrpurVqzvdxzAMpaamqlmzZt4IEaia/vEP6ZxzpN27pa+/tjoawKNITgFASXr1krp3l06ckF5+2epoUE4U/AUq0ODB5v2WLdIZI25gvezsbKWmpir11LT0tLQ0paamavfu3ZLM6Xbjx48vbH/LLbdo165dmjJlin744Qe98cYbev3113XvvfcWtpk+fbqWL1+u33//XampqZo4caJSU1N1yy23ePW1AVVKrVqS/bMLq/bBz5GcAoCS2GynR0+9+KKZpILPouAvUIGaNpW6dTMfL1tmbSwoZuvWrYqKilJUVJQkacqUKYqKitK0adMkSRkZGYWJKklq1aqVli1bppSUFHXp0kWPPvqonn/+eY0cObKwzdGjR3XTTTepXbt2GjhwoNLT07VmzRr16NHDuy8OqGqKTu0D/JjNMJi8irLLyspSSEiIMjMzqR8A/3bihBQZKWVkSO+8I119tdUReYWvvcdtNpuWLFmi4cOHl9imdevWuu666xQfH1+47csvv9Qll1yijIwMp9P3CgoKdNFFF6lv3756/vnnnR43NzdXubm5hT9nZWUpIiLCZ84d4Lbp06VHHjGX8jujdps/87X+sTLh3AFuOHxYCg2VCgqkXbukFi2sjqhEvMdRHoycAoDS1KhhrtwnmYXRyef7LAr+AhXMXndqxQqpSIIWAFCBGjWSLr7YfMyqffBjJKcA4GxuvtlMUm3ZIm3caHU0cBMFf4EKFhUlNWsmZWdLa9ZYHQ0A+K8rrzTvmdoHP0ZyCgDOpkkTaexY8/GcOdbGgkIU/AUsFhBwujA6q/YBgOfY606lpEiZmZaGAngKySkAcIW9MPqiRdIPP1gbCyRR8BeoFOxT+z7+mGnPAOApF1wgtW8v5eVJS5daHQ3gERREh1sodocqKTZW+uwz8wPCpk1S/fpWR+QxvMfdx7lDlZKdLTVsaC4e8cMPUtu2VkfkcbzH3ce5A8rh//5PevBBKSZGSk62OhqneI+jPBg5BQCumj/fXCHll1+k0aPNq1cAUJXVqWN+UZKkTz6xNBQA8Gvjx0s2mzm17/ffrY4GqHAkpwDAVU2amIUozzlHWrlSuu8+qyMCAOvZp/ZRdwoAPCciQhowwHw8f761sQAeQHIKAMqiS5fTHwiee05KSLAyGgCw3hVXmPdr10pHj1oaCgD4o/x8c8DUl62vkyQZ8+dLBQXWBgVUMJJTAFBWo0ZJp4pu6+abpQ0brI0HAKx07rky2reX8vP15bTlSkkxv0gBAMovKUmKjJT69ZP+MXeYjipEtl27tHZG5aw7BbiL5BQAuOPhh6URI8wiwCNGSF99ZXVEAGCJpCRp3m5zat++FxapXz/zi1RSkrVxAYCvS0oyr4nu3Wv+fFy1lKgxkqRd09+kn4VfITnl49asWaOhQ4cqLCxMNptNS11YWnT16tXq2rWratasqXPPPVcvvfSS5wMF/E1AgPTWW1LHjtKBA1LXrmaR9J9+sjoyAPAa+xenl7PHSpKu1Eeqpz+Vnm5u54sTALgnP1+aNEkyDMftb8qc2jdSi/XQXZmMVIXfIDnl43JyctS5c2fNnTvXpfZpaWkaPHiwoqOjtX37dv3nP//RXXfdpcWLF3s4UsAP1akjLV8ujR1rrp7y/vtS+/bSxInS9u3SsWNWRwgAHlP0i9MOddbX6qQgndBVer/wy9TkyUzxAwB3rF17esRUUVvUXd+pvWrpuPqkv6+1a70fG+AJ1awOAOUTGxur2NhYl9u/9NJLatGihWbPni1JateunbZu3aqnn35aI0eO9FCUgO/Izzc/DGRkSM2aSdHRUmBgKTs0aya9+650//3SQw9JH30kvfGGeZOk+vWlli3NOS4tW5q3Fi2kmjXN0VcBAeYvsD+22Tz7Alu1Mn8/AJTTmV+c3tJ4PaN7NV5v6RXdLMOQ9uwx28XEWBYmAPikjIySnrHpTV2np/VvXac3tSvjRm+GBXgMyakqZsOGDRo4cKDDtkGDBun111/XyZMnVb16daf75ebmKjc3t/DnrKwsj8YJWCEpyRwFUPTLVni4NGeOFBd3lp07dZI+/FDauFGaMUPatEn64w/pzz/NW2qqJ0N33eOPm4k0ACinM784LdBYPan7dLHW63z9ol91gdN2AICza9as5Ofe0TV6XA+ojzao2skfJbX1WlyAp5CcqmL279+v0NBQh22hoaHKy8vT4cOH1ayEXnDWrFmaPn26N0IELGGvm3LmvH573ZRFi1xIUElSr17SsmXm42PHpF27HG87d5rZr5MnzWFaBQWnb96Y+9Kwoed/B4Aq4cyPDPvVTMs1SIP1qcbpbT2sGU7bAQDOLjravEianl788+kBNdWnitVQfaJu3yZIetyKEIEKRXKqCrKdMW3IONXbnbm9qPj4eE2ZMqXw56ysLEVERHgmQMDLSio4KZnbbDazbsqwYWeZ4nemunWlDh3MGwD4GWdfnN7S+MLk1HQ9ouYRAYqOtjZOAPBFgYHm6P1Ro8zPokU/p9psUoJxnYbqEwW885b02EypGl/t4dsoiF7FNG3aVPv373fYdvDgQVWrVk0NSxlRERQUpODgYIcb4C9KKjhpV7RuitXy86WUFCkx0byn0DAAq9i/OEmny+V9qGHKVLBaaaeitVazZ5cxqQ8AKBQXZ47eb97ccXt4uHTNe0OkRo3MudMrVlgTIFCBSE5VMb1799bKlSsdtq1YsULdunUrsd4U4O9crYdidd2UpCSzrnq/fuYCgf36mT+zVDsAq5z5xem4aukD/VOSlHDZW65NhwYAlCguzqwKkZwsLVhg3qelSSNG15Cuvtps9OablsYIVASSUz4uOztbqampSj1VbDktLU2pqanavXu3JHM63vjx4wvb33LLLdq1a5emTJmiH374QW+88YZef/113XvvvVaED1QKrtZDsbJuir0m1pkjvOw1sUhQAbDKmV+cus65VpIUueUD6a+/rA0OAPxAYKC56umYMeZ94YjUCRPM+48+ko4csSY4oIKQnPJxW7duVVRUlKKioiRJU6ZMUVRUlKZNmyZJysjIKExUSVKrVq20bNkypaSkqEuXLnr00Uf1/PPPa+TIkZbED1QG9ropJZVds9mkiAhZVjflbDWxJLMmFlP8AFil6BenqDsullq1MheF+PBDq0MDAP/VpYt5O3FCevttq6MByoXklI+LiYmRYRjFbgkJCZKkhIQEpaSkOOxz6aWX6quvvlJubq7S0tJ0yy23eD9woBJxVjfFzv6zlXVTfKkmFgAoIEAaN858PH++tbEAgL+79Vbz/qmnpOPHrY0FKAeSUwCg0gtOLlokS+um+EpNLAAoZE9OrVwp7dtnbSwA4M8mTDCH+O/bJ73yitXRAG4jOQUAp5RUcNLqgr6+UBMLABycf77Up49UUGB2qAAAz6hRQ5o61Xw8a5b099/WxgO4ieQUABRRYsFJC1X2mlgA4NS1ZmF0vfIKRfEAwJOuu05q2VLav196+WWrowHcQnIKACo5V2tiSVJKipSYaN7bvwvm5zvfDgAeNWaM1KCB9Msv0gcfWB0NAPivoqOnHn+clVLhk0hOAYAPOFtNLEmKjJT69ZPGjjXvIyOl++5zvj0pybvxA6iC6taV7r7bfDxzpjnFDwDgGRMmmB/yDhyQXnrJ6miAMiM5BQA+oqSaWJI0alTxFf327jUXbjlze3q62Z4EFQCPu/NOKSRE+u47ackSq6MBAP9Vvbr04IPm4yeekHJyrI0HKCOSUwDgQ86siSVJkyZJhuH6MextJ09mih8ADwsJMTspSZoxg9FTAOBJ48dL554rHTzI6Cn4HJJTAODD1q4tPjLKFYYh7dlj7g8AnmCvd7c4fJLyatWRduyQPv7Y6rAAwH8xego+jOQUAPiwjAxr9wcAZ5KSTte7G3VTAz35952SpD/vebRsQz0BAGVzzTXm6KlDh6T//tfqaACXkZwCAB/WrJm1+wPAmZKSitfBe1ZTlK3aqv/bNn354KfWBQcA/q56dWnaNPPx9OnSTz9ZGw/gIpJTAODDoqPNFftstrLtZ7NJERHm/gBQUfLzndfBO6JGmqdbJUm1np6h/DxGTwGAx4wbJ/XvL/31l7lc84kTVkcEnBXJKQDwYYGB0pw55mNXE1T2drNnm/sDQEUprQ7e07pXf6umLjqxST/OeN+7gQFAVRIQIM2fLzVsKH311ek6VEAlRnIKAHxcXJy0aJHUvLnj9ogI6d//NkdWFRUebraPi/NejACqhtLq2B1UqJ7RPZKkNk9eL339tZeiAoAqqHlz6fXXzcdPPSV98YW18QBnQXIKAPxAXJy0c6eUnCwtWGDep6VJTz7pfDuJKQCecLY6do/oEa3QAFXL/Uu68kpzuXMAgGcMGybdfLP5ePx46cgRa+MBSlHN6gAAABUjMFCKiXF9OwBUNHsdvPR054vyFdiq6Z6whdpRq4dsv/5qVk7//HOpRg3vBwsAPi4/35xOnZFhXhyIjnZSsuHZZ6XVq6Uff5RuuMFctaKsxUoBL2DkFAAAACpEaXXw7D9Pf76+bB99JAUHm9+q7rjDeSYLAFCipCQpMlLq18+sed6vn/lzUtIZDc85xxw+X726tHSp2Tg72/sBA2dBcgoAAAAVpqQ6eA717tq1kxITzYzVq69KL75oSawA4IuSksyBp2cuQJGebm4vlqCKipJeflmqVk167z2pZ09zJBVQiZCcAgAAQIUqqQ6eQ727wYOlJ54wH0+aJK1aZUWoAOBT8vPNLtPZgFP7tsmTzXYOrrvO7IybNZO+/17q3l364ANPhwu4jOQUAAAAKpy93t2YMeZ9sTooknTvvdK4cea3qH/+U/rtNy9HCQC+Ze3a4iOmijIMac8es10xl1wiffWV2SlnZ0tXXSVNmSKdPOmpcAGXkZwCAACANWw26ZVXpB49pD/+MFfwy8qyOioAqLQyMsrZrmlTaeVK6b77zJ+fe0667DLXDwx4CMkpAAAAWKdmTWnJEikszJxqMnSotGOH1VH5tDVr1mjo0KEKCwuTzWbT0qVLz7rP6tWr1bVrV9WsWVPnnnuuXnrppWJtFi9erPbt2ysoKEjt27fXkiVLPBA9gNI0a1YB7apVM6dVJyWZi1OsW2fWpVq0SPrrrwqJEygrklMAAACwVliYuYpUrVrSmjVS587mdJPvv7c6Mp+Uk5Ojzp07a+7cuS61T0tL0+DBgxUdHa3t27frP//5j+666y4tXry4sM2GDRs0evRojRs3Tl9//bXGjRunq666Sps2bfLUywDgRHS0ucDEmSui2tlsUkSE2e6sRoyQtm6VOnSQDhwwp1c3bChdcYW5UMWuXRUaO1AaklMAAJ/EyADAz3TvLm3fLo0ebf78wQfmF6ZrrpF+/tna2HxMbGysZs6cqTiHCvQle+mll9SiRQvNnj1b7dq10w033KDrr79eTz/9dGGb2bNna8CAAYqPj1fbtm0VHx+v/v37a/bs2R56FQCcCQyU5swxH5+ZoLL//MwzZs2pxEQpJcVJcfSiLrhA2rhR+ve/pZYtpePHpWXLpNtvlyIjpY4dpfh4s5AV4EEkpwAAPomRAYAfatPGXOZ8xw7zir5hSO++K7Vvb17Rf+YZ6fPPpUOHrI7Ur2zYsEEDBw502DZo0CBt3bpVJ08VSi6pzfr160s8bm5urrKyshxuAMovLs6cgde8ueP28HBznYkpU6R+/aSxY837yEhzBl+JateWnnzSXFb1m2+kxx83i6cHBEjffmv+nJPjyZcEqJrVAQAA4I7Y2FjFxsa63L7oyABJateunbZu3aqnn35aI0eOlOQ4MkCS4uPjtXr1as2ePVuJiYkV/hoAlKBjR/Ob1FdfSQ8/LH3yiflNbNGi023CwqQLLzSnoISEmHVTQkLMqYEBAebwAvt90cclzYVp2FAaMsQ7r6+S2b9/v0JDQx22hYaGKi8vT4cPH1azZs1KbLN///4Sjztr1ixNnz7dIzEDVV1cnDRsmDlCKiPDrDF1+LA5I9owHNump0ujRpldaKkDKm02c8Rqhw7S/febC1UsX26OrGrTxqOvByA5BQCoEkq66v/666/r5MmTql69ujZs2KC77767WJvSpq3k5uYqNze38GdGBgAV6KKLpI8/lrZskT79VPr6a/P222/Svn3mraJ07Vplk1OSZDsjaWec+nZbdLuzNmduKyo+Pl5Tpkwp/DkrK0sREREVES4Amfn2mBjzcX6+OULqzMSUZG6z2aTJk82EVmCgi7+gQQNpzBjzBngYySkAQJXAyADAWvn5jlf4o6PL8AWpe3fzZpedbU49+fln6ehRKTNTBX9m6sDPmcrNPK5aQQVq3DBfAQX55i8uKDDvSyu8cv755Xl5Pq1p06bF+rmDBw+qWrVqatiwYaltzuwziwoKClJQUFDFBwygmLVrpb17S37eMMyyUWvXnk5oAZUJySkAQJXByADAGklJ0qRJjl+cwsPNor4u1ux2VKeO1Lu3efPE8auY3r176+OPP3bYtmLFCnXr1k3Vq1cvbLNy5UqH0aUrVqxQnz59vBorAOcyMiq2HeBtJKcAwAXluuKPSoGRAYA1kpLMWidu10Cx+Pi+KDs7W7/++mvhz2lpaUpNTVWDBg3UokULxcfHKz09XW+99ZYk6ZZbbtHcuXM1ZcoU3XjjjdqwYYNef/11h1p7kyZNUt++ffXEE09o2LBh+vDDD/X5559r3bp1Xn99AIpr1qxi2wHexmp9AHAWSUnmHP4yrXqCSsd+1b+okkYGnNmGkQGAe/LzzRFNJdVAkcwaKKUuc27h8X3V1q1bFRUVpaioKEnSlClTFBUVpWnTpkmSMjIytHv37sL2rVq10rJly5SSkqIuXbro0Ucf1fPPP1+4WIQk9enTR++9957efPNNderUSQkJCVq4cKF69uzp3RcHwKnoaHPEaEmDvW02KSLCbAdURoycAoBScEW+8mJkAFD5eboGCjVWnIuJiSmctuxMQkJCsW2XXnqpvvrqq1KPO2rUKI0aNaq84QHwgMBAcyrzqFFmIqpoF2BPWM2ezch/VF6MnAKAEnBFvnJjZABQ+Xm6Bgo1VgDgtLg488Jp8+aO28PDuaCKyo+RUwBQAq7IV26MDAAqP0/XQKHGCgA4iouThg2jVip8D8kpACgBV+QBoHzsNVDS052PQrXZzOfdrYHi6eMDgC8KDOTCKXwP0/oAoARckQeA8rHXQJGKF+mtiBoonj4+AADwDpJTAFACVj0BgPLzdA0UaqwAAOD7SE75iRdffFGtWrVSzZo11bVrV61du7bU9v/973/Vrl071apVS23atClczQrAaVyRB4CKERcn7dwpJSdLCxaY92lpFZc48vTxAQCAZ1Fzyg8sXLhQkydP1osvvqiLL75YL7/8smJjY/X999+rRYsWxdrPmzdP8fHxevXVV9W9e3dt3rxZN954o+rXr6+hQ4da8AqAyst+RX7SJMfi6OHhZmKKLz4A4JqKrIGSn++82C81VgAA8E02o7SljuATevbsqYsuukjz5s0r3NauXTsNHz5cs2bNKta+T58+uvjii/XUU08Vbps8ebK2bt2qdevWufQ7s7KyFBISoszMTAUHB5f/RQCVXElfhPwV73H3ce4Az0pKcn7BYM4c71ww4D3uPs4dYA1vfY7lPY7yYOSUjztx4oS2bdumBx54wGH7wIEDtX79eqf75ObmqmbNmg7batWqpc2bN+vkyZOqXr26031yc3MLf87KyqqA6AHfwRV5ALBeUpI0alTxlfnS083t1JgCAEdWJ/QBV1FzyscdPnxY+fn5Cg0NddgeGhqq/fv3O91n0KBBeu2117Rt2zYZhqGtW7fqjTfe0MmTJ3X48GGn+8yaNUshISGFt4iIiAp/LQAAACXJzze/YDkb82/fNnmy2Q4AcDqhXzQxJZ1O6CclWRMX4AzJKT9hO6Nas2EYxbbZPfTQQ4qNjVWvXr1UvXp1DRs2TBMmTJAkBZYwvjM+Pl6ZmZmFtz179lRo/AAAAKVZu7b4F6yiDEPas8dsVxb5+VJKipSYaN6T3ALgD0jow9eQnPJxjRo1UmBgYLFRUgcPHiw2msquVq1aeuONN/TXX39p586d2r17tyIjI1W3bl01atTI6T5BQUEKDg52uAEAAHhLRkb52jlLQiUlSZGRUr9+0tix5n1kJKMJAPg+TyX0AU8hOeXjatSooa5du2rlypUO21euXKk+ffqUum/16tUVHh6uwMBAvffeexoyZIgCAviTAAAAlU+zZu63c5aECg2VRo5kugsA/1TehD7gbRRE9wNTpkzRuHHj1K1bN/Xu3VuvvPKKdu/erVtuuUWSOSUvPT1db731liTp559/1ubNm9WzZ0/9+eefevbZZ/Xtt99q/vz5Vr4MAACAEkVHm0V809OdT1Ox2czno6Mdt5dURP3IEee/xzDMY02eLA0b5t8rswLwX+VJ6ANWIDnlB0aPHq0jR45oxowZysjIUIcOHbRs2TK1bNlSkpSRkaHdu3cXts/Pz9czzzyjn376SdWrV1e/fv20fv16RUZGWvQKAAAAShcYaK4uNWqUmTwqmmyyl9mcPdsxmVRazZXSFJ3uwkqtAHyRuwl9wCokp/zEbbfdpttuu83pcwkJCQ4/t2vXTtu3b/dCVAAAABUnLk5atMj5suizZxdfFv1sNVfOhukuAHyVOwl9wEoUGAIAAIDPiIuTdu6UkpOlBQvM+7S04okpqfzJJaa7APBl9oR+8+aO28PDze3O+k3AKoycAgA35eebV+UzMswvMNHRXH0CAG8IDHRtup27ySWmuwDwF3FxZv08PrOisiM5BQBuSEpyPq1kzhyuQgFAZXG2mivOMN0FgL9xNaEPWIlpfQBQRvaVn1h+HAAqN3vNFel00snO/nPDho7bme4CAID3kZwCgDIobeUn+7bJk812AADrlVZzZfFi6cAB1+pXAQAAz2FaHwCUwdlWfqrI5cepaQUAFeNsNVeY7gIAgLVITgFAGbi68lN5V4iiphUAmCoqUU/NFQAAKi+SUwBQBq6u/FSe5cftNa3OnDpor2lFLRQAVQWJegDwvJIuAjCKH95EcgoAyuBsKz+Vd/nxs9W0stnMmlbDhvHhAIB/I1EPAJ5X0kWAMWOkxEQuDsB7KIgOAGXgyspP5Vl+vCw1rQDAX7H4BAB4XkkrUO/dKz31FCtTw7tITgFAGZW28lN5r+R7q6YVAFQ2+flSSop5pf6FF0jUA4AnlXYRoCRcHIAnMa0PANxwtpWf3OWNmlYAUNk4m1biChL1AOCes43WL0lFrkwNFEVyCgDc5ImVnzxd0woAKpuSaku5gkQ9ALinvMl9Lg6gojGtDwAqEU/XtAKAysSdaSWS2R9GRJCoBwB3lTe5z8UBVDSSUwBQyXiyphUAVCbuTCshUQ8A5WcfrX/mxdCz4eIAPIXkFABUQnFx0s6dUnKytGCBeZ+WRmIKgH9xZ1oIiXoAKL/SRuuXhIsD8CRqTgFAJeWJmlYAUJm4Oi3kueek0NCKW3wCAHB6tP6ZC1JEREj/+pe5emrR7eHhZmKKiwPwBJJTAAAAsISri0DceScJKQDwhNJWoJ41q+JXpgZKQnIKAAAAlrBPKxk1ykxEFU1QMX0EALyjpNH6jOKHN1FzCgAAAJZhEQgAAMDIKQCoQPn5DH8GgLIqbVoJAADwfySnAKCCJCUVLygZHm5OWeHKPwCUjukjAABUXUzrA4AKkJRk1kwpmpiSzCK/o0aZzwMAAAAAiiM5BQDllJ9vjphyttKUfdvkyWY7VKwXX3xRrVq1Us2aNdW1a1etXbu21Pb//e9/1a5dO9WqVUtt2rTRW2+95fB8QkKCbDZbsdvx48c9+TIAAACAKo1pfQBQTmvXFh8xVZRhSHv2mO2YslJxFi5cqMmTJ+vFF1/UxRdfrJdfflmxsbH6/vvv1aJFi2Lt582bp/j4eL366qvq3r27Nm/erBtvvFH169fX0KFDC9sFBwfrp59+cti3Zs2aHn89AAAAQFXFyCkAKKeMjIptB9c8++yzmjhxom644Qa1a9dOs2fPVkREhObNm+e0/dtvv62bb75Zo0eP1rnnnqt//etfmjhxop544gmHdjabTU2bNnW4AYAvYnQpAMBXkJwCgHJq1qxi2+HsTpw4oW3btmngwIEO2wcOHKj169c73Sc3N7fYCKhatWpp8+bNOnnyZOG27OxstWzZUuHh4RoyZIi2b99eaiy5ubnKyspyuAGA1eyjS6dOnart27crOjpasbGx2r17t9P29tGljzzyiL777jtNnz5dt99+uz7++GOHdsHBwcrIyHC4MboUAFBeJKcAoJyio81V+Ww258/bbFJEhNkOFePw4cPKz89XaGiow/bQ0FDt37/f6T6DBg3Sa6+9pm3btskwDG3dulVvvPGGTp48qcOHD0uS2rZtq4SEBH300UdKTExUzZo1dfHFF+uXX34pMZZZs2YpJCSk8BYREVFxLxQA3MToUgCALyE5BQDlFBgozZljPj4zQWX/efZssx0qlu2ME24YRrFtdg899JBiY2PVq1cvVa9eXcOGDdOECRMkSYGn/nF69eqla665Rp07d1Z0dLTef/99tW7dWi+88EKJMcTHxyszM7PwtmfPnop5cQDgpsoyupSRpQAAV5GcAoAKEBcnLVokNW/uuD083NweF2dNXP6qUaNGCgwMLDZK6uDBg8VGU9nVqlVLb7zxhv766y/t3LlTu3fvVmRkpOrWratGjRo53ScgIEDdu3cvdeRUUFCQgoODHW4AYKXKMrqUkaUAAFeRnAKAChIXJ+3cKSUnSwsWmPdpaa4lpvLzpZQUKTHRvM/P93CwPq5GjRrq2rWrVq5c6bB95cqV6tOnT6n7Vq9eXeHh4QoMDNR7772nIUOGKCDA+X+HhmEoNTVVzSgYBsAHWT26lJGlAABXVbM6AADwJ4GBUkxM2fZJSpImTZL27j29LTzcnCrIiKuSTZkyRePGjVO3bt3Uu3dvvfLKK9q9e7duueUWSeaXovT09MLVpn7++Wdt3rxZPXv21J9//qlnn31W3377rebPn194zOnTp6tXr1664IILlJWVpeeff16pqan673//a8lrBAB3lGd06csvv6wDBw6oWbNmeuWVV8o1ujQoKEhBQUHlezEAgCqB5BQAWCgpSRo1SjIMx+3p6eZ2pgSWbPTo0Tpy5IhmzJihjIwMdejQQcuWLVPLli0lSRkZGQ6rUuXn5+uZZ57RTz/9pOrVq6tfv35av369IiMjC9scPXpUN910k/bv36+QkBBFRUVpzZo16tGjh7dfHgC4rejo0hEjRhRuX7lypYYNG1bqvvbRpZJcHl3asWPHigseAFAl2QzjzK9EwNllZWUpJCREmZmZ1FcB3JSfL0VGOo6YKspmM0dQpaV5v5g673H3ce4A/+Yr7/GFCxdq3LhxeumllwpHl7766qv67rvv1LJlS5dGl65cuVLbtm0rTOI7G1369ttv68svv3Qpie8r5w6Ae3iPozwYOQUAFlm7tuTElGSOptqzx2xX1qmCAICqjdGlAABfwsgpuIWsOFB+iYnS2LFnb7dggTRmjOfjKYr3uPs4d4B/4z3uPs4d4N94j6M8WK3PT7z44otq1aqVatasqa5du2rt2rWltn/33XfVuXNnnXPOOWrWrJmuu+46HTlyxEvRApAkVxeAY6E4AAAAAP6M5JQfWLhwoSZPnqypU6dq+/btio6OVmxsrMNQ7aLWrVun8ePHa+LEifruu+/0wQcfaMuWLbrhhhu8HDlQtUVHmzWlSljVWzabFBFhtgMAAAAAf0Vyyg88++yzmjhxom644Qa1a9dOs2fPVkREhObNm+e0/caNGxUZGam77rpLrVq10iWXXKKbb75ZW7du9XLkQNWTny+lpJhT+taulZ57ztx+ZoLK/vPs2d4vhg4AAAAA3kRyysedOHFC27Zt08CBAx22Dxw4UOvXr3e6T58+fbR3714tW7ZMhmHowIEDWrRoka644ooSf09ubq6ysrIcbgDKJinJXJ2vXz+z1lS/ftLdd0v33is1b+7YNjxcWrRIiouzJFQAAAAA8BpW6/Nxhw8fVn5+vkJDQx22h4aGav/+/U736dOnj959912NHj1ax48fV15enq688kq98MILJf6eWbNmafr06RUaO1CVJCVJo0aZK/AVlZ4uPf20tHCh1LixlJFh1piKjmbEFAAAAICqgZFTfsJ2xpwgwzCKbbP7/vvvddddd2natGnatm2bPvvsM6WlpemWW24p8fjx8fHKzMwsvO3Zs6dC4wf8WX6+NGlS8cSUdHrbPfeYCakxY6SYGBJTAAAAAKoORk75uEaNGikwMLDYKKmDBw8WG01lN2vWLF188cX697//LUnq1KmTateurejoaM2cOVPNnCwNFhQUpKCgoIp/AUAVsHattHdvyc8bhrRnj9kuJsZrYQEAAABApcDIKR9Xo0YNde3aVStXrnTYvnLlSvXp08fpPn/99ZcCAhz/6QNPDdMwnA3tAFAuGRkV2w4AAAAA/AnJKT8wZcoUvfbaa3rjjTf0ww8/6O6779bu3bsLp+nFx8dr/Pjxhe2HDh2qpKQkzZs3T7///ru+/PJL3XXXXerRo4fCwsKsehmA33IyGLFc7QAAAADAnzCtzw+MHj1aR44c0YwZM5SRkaEOHTpo2bJlatmypSQpIyNDu3fvLmw/YcIEHTt2THPnztU999yjevXq6bLLLtMTTzxh1UsA/Fp0tLn6Xnq687pTNpv5fHS092MDAAAAAKvZDOZxwQ1ZWVkKCQlRZmamgoODrQ4HqPTsq/VJjgkq+7oFixZJcXHej6skvMfdx7kD/Bvvcfdx7gD/xnsc5cG0PgDwgrg4MwHVvLnj9vDwypeYAgAAAABvYlofAHhJXJw0bJi5Kl9GhlljKjpaOrUeAQAAAABUSSSnAMCLAgOlmBirowAAAACAyoNpfQAAAAAAALAMySkAAAAAAABYhuQUAAAAAAAALENyCgAAAAAAAJYhOQUAAAAAAADLkJwCAAAAAACAZUhOAQAAAAAAwDIkpwAAAAAAAGAZklMAAAAAAACwDMkpAAAAAAAAWIbkFAAAAAAAACxTzeoA4JsMw5AkZWVlWRwJAE+wv7ft73W4jv4R8G/0j+6jfwT8G/0jyoPkFNxy7NgxSVJERITFkQDwpGPHjikkJMTqMHwK/SNQNdA/lh39I1A10D/CHTaDtCbcUFBQoH379umyyy7T1q1bz9q+e/fu2rJlS5mfd7bdlW32n7OyshQREaE9e/YoODj4rHG642yvrTz7VeR5c7a9tJ89fe48ed5cacffXOltDMPQsWPHFBYWpoAAZoCXhb1/rFu3rnr06OHV93lZ/lYl/36fl/W5ytQ/lhRjRe3D35z7+3Xv3l2bN2+mf3RTWftHyb33uS98DiotzorYh89B7u/nr39z9I+o7Bg5BbcEBAQoPDxc1apVc6nzDAwMLLVdSc872+7KtjN/Dg4O9th/kGd7beXZryLPm7PtZ/tZ8ty58+R5c6Udf3Nnb8MVL/fY+0fJ++9zd/5WJf98n5f1ucrUP5b0+ypqH/7m3N8vMDBQISEh9I9uKmv/eLZ2vvw5qLQ4K2Ifq9/nle28lWU/f/2bo39EZUc6E+Vy++23V0i7kp53tt2Vba7GVRHc/V2u7FeR583Zdn89b66042+uYo8N57z9Pq9Kf6tna1fW5ypT/+ju76N/tP7/FrjOk+9zX/gc5O7v431eOf9v8YW/OfpHVHZM64Nfy8rKUkhIiDIzMz129cZfce7cw3mDL+Hv1T2cN/dx7uAr+Ft1D+fNfZw7VHWMnIJfCwoK0sMPP6ygoCCrQ/E5nDv3cN7gS/h7dQ/nzX2cO/gK/lbdw3lzH+cOVR0jpwAAAAAAAGAZRk4BAAAAAADAMiSnAAAAAAAAYBmSUwAAAAAAALAMySkAAAAAAABYhuQUAAAAAAAALENyClXaJ598ojZt2uiCCy7Qa6+9ZnU4PmPEiBGqX7++Ro0aZXUoPmXPnj2KiYlR+/bt1alTJ33wwQdWhwSUiP7RffSRZUf/CF9C/+g++seyo39EVWEzDMOwOgjACnl5eWrfvr2Sk5MVHBysiy66SJs2bVKDBg2sDq3SS05OVnZ2tubPn69FixZZHY7PyMjI0IEDB9SlSxcdPHhQF110kX766SfVrl3b6tAAB/SP5UMfWXb0j/AV9I/lQ/9YdvSPqCoYOYUqa/PmzbrwwgvVvHlz1a1bV4MHD9by5cutDssn9OvXT3Xr1rU6DJ/TrFkzdenSRZLUpEkTNWjQQH/88Ye1QQFO0D+WD31k2dE/wlfQHPm7YQAAsQJJREFUP5YP/WPZ0T+iqiA5BZ+1Zs0aDR06VGFhYbLZbFq6dGmxNi+++KJatWqlmjVrqmvXrlq7dm3hc/v27VPz5s0Lfw4PD1d6ero3QrdUec9bVVaR527r1q0qKChQRESEh6NGVUT/6D76SPfQP8JX0D+6j/7RPfSPgGtITsFn5eTkqHPnzpo7d67T5xcuXKjJkydr6tSp2r59u6KjoxUbG6vdu3dLkpzNaLXZbB6NuTIo73mryirq3B05ckTjx4/XK6+84o2wUQXRP7qPPtI99I/wFfSP7qN/dA/9I+AiA/ADkowlS5Y4bOvRo4dxyy23OGxr27at8cADDxiGYRhffvmlMXz48MLn7rrrLuPdd9/1eKyViTvnzS45OdkYOXKkp0OstNw9d8ePHzeio6ONt956yxthAvSP5UAf6R76R/gK+kf30T+6h/4RKBkjp+CXTpw4oW3btmngwIEO2wcOHKj169dLknr06KFvv/1W6enpOnbsmJYtW6ZBgwZZEW6l4cp5g3OunDvDMDRhwgRddtllGjdunBVhAvSP5UAf6R76R/gK+kf30T+6h/4ROK2a1QEAnnD48GHl5+crNDTUYXtoaKj2798vSapWrZqeeeYZ9evXTwUFBbrvvvvUsGFDK8KtNFw5b5I0aNAgffXVV8rJyVF4eLiWLFmi7t27ezvcSsWVc/fll19q4cKF6tSpU2G9gbffflsdO3b0driowugf3Ucf6R76R/gK+kf30T+6h/4ROI3kFPzamTUADMNw2HbllVfqyiuv9HZYld7Zzhur0pSstHN3ySWXqKCgwIqwgGLoH91HH+ke+kf4CvpH99E/uof+EaAgOvxUo0aNFBgY6HClRpIOHjxY7MoETuO8uY9zB1/B36r7OHfu4bzBV/C36j7OnXs4b8BpJKfgl2rUqKGuXbtq5cqVDttXrlypPn36WBRV5cd5cx/nDr6Cv1X3ce7cw3mDr+Bv1X2cO/dw3oDTmNYHn5Wdna1ff/218Oe0tDSlpqaqQYMGatGihaZMmaJx48apW7du6t27t1555RXt3r1bt9xyi4VRW4/z5j7OHXwFf6vu49y5h/MGX8Hfqvs4d+7hvAEusmaRQKD8kpOTDUnFbtdee21hm//+979Gy5YtjRo1ahgXXXSRsXr1ausCriQ4b+7j3MFX8LfqPs6dezhv8BX8rbqPc+cezhvgGpthGIZHsl4AAAAAAADAWVBzCgAAAAAAAJYhOQUAAAAAAADLkJwCAAAAAACAZUhOAQAAAAAAwDIkpwAAAAAAAGAZklMAAAAAAACwDMkpAAAAAAAAWIbkFAAAAAAAACxDcgoAAAAAAACWITkFAAAAAAAAy5CcAuCyb7/9VoGBgbrlllvcPkZWVpbq16+vSy65pAIjAwBr0T8CgHP0jwBcQXIKgMvuv/9+BQYGKj4+3u1jBAcH66677tKXX36pDz/8sAKjAwDr0D8CgHP0jwBcYTMMw7A6CACV39q1a9W3b19NmDBBb775ZrmO9eeffyo8PFwtW7bUd999J5vNVkFRAoD30T8CgHP0jwBcxcgpAC6ZO3euJOnaa68t97Hq16+voUOH6ocfftCqVavKfTwAsBL9IwA4R/8IwFUkpwCc1aFDh7R06VKFhYWpb9++FXLMf/3rX5Kk1157rUKOBwBWoH8EAOfoHwGUBckpwA+1adNGNpvNpdv8+fPPerwlS5boxIkTio2NVUBAyd1Gdna2HnvsMfXo0UMhISEKCgpS8+bN1bdvX82YMUMnTpwobDto0CBVq1ZNS5cuVW5uboW8bgA4G/pHAHCO/hGAlapZHQCAivX3338rNDRUjRs3Ltz2+++/KyMjQ5GRkWrevLlD++jo6LMec82aNZKkHj16lNhm7969iomJ0W+//aagoCC1atVK55xzjnbv3q21a9cqNTVVDz30UGH7WrVqqWPHjtq+fbu2bNnC6isAPI7+EQCco38EYDWSU4CfqVWrVuGHAbuRI0cqKSlJM2fO1NVXX13mY65fv16S1LVr1xLb3HHHHfrtt990++23a+bMmapXr17hcz/++KNWr15drHBl9+7dtX37dq1bt44PFwA8jv4RAJyjfwRgNZJTQBWwY8cOSVLHjh3LvK9hGNqzZ48kqVmzZk7bnDhxQv/73/8UEhKi559/vtjQ7bZt26pt27bF9rMfb9euXWWOCwAqAv0jADhH/wjAm6g5Bfi5v/76S7///ruqVavm9D/4szl69Kjy8vIkSQ0aNHDa5uTJk8rPz1dOTo42btzo8rHtxzt06FCZ4wKA8qJ/BADn6B8BeBvJKcDPfffddyooKFDr1q1Vo0aNMu9//Pjxwscl7V+7dm1dfvnlysvLU3R0tIYMGaL58+fryJEjpR67Vq1aksw6BwDgbfSPAOAc/SMAbyM5Bfg5+5DsDh06uLV/0atdmZmZJbb74IMP9MADD6hRo0b63//+pwkTJqhp06YaOXKkfvvtN6f7/PHHH5KkRo0auRUbAJQH/SMAOEf/CMDbSE4Bfu6bb76R5F69AEkKCgpScHCwpNMfBpypXbu2Zs2apX379mnDhg3697//rdq1ayspKUkDBw5Ufn5+sX3sxyu6MgwAeAv9IwA4R/8IwNtITgF+7scff5QkXXjhhW4fo0uXLpKkH3744axtAwMD1atXLz355JPasWOHatasqd9//127d+8u1vb777+XJF100UVuxwYA7qJ/BADn6B8BeBvJKcDPpaenS5JatGjh9jHsy/Ru3bq1TPs1adJEkvmBw1kxzC1btkiSoqOj3Y4NANxF/wgAztE/AvA2klOAn6tevbqk8i23O3DgQEnSunXrij335ptvaurUqfr5558dtu/bt0//+te/dPz4cQ0fPlwhISEOz//66686cOCA2rZtq4iICLdjAwB30T8CgHP0jwC8jeQU4OfsV5X+9a9/KSoqSjNmzCjzMfr27avzzz9fKSkpOnDggMNza9as0WOPPaY2bdqoWbNm6tGjh9q1a6fIyEh9+OGH6tKli+bNm1fsmAsXLpQkXX/99W68KgAoP/pHAHCO/hGAt5GcAvzco48+qmuuuUa1a9dWamqqAgMDy3wMm82mG2+8Ufn5+YUfCuxuvvlmPfDAA+rdu7dsNptSU1O1b98+de/eXXPmzNGmTZucFqxMTExU9erVde2117r92gCgPOgfAcA5+kcA3mYzDMOwOggAlV9WVpbOO+88NWjQQD/88IMCAtzPbScnJ+uyyy7Tbbfdpv/+978VGCUAeB/9IwA4R/8IwFWMnALgkuDgYD344IP6+eef9d5775XrWDNmzFCdOnU0bdq0CooOAKxD/wgAztE/AnBVNasDAOA7br31VmVlZamgoMDtY2RlZSkmJkZ33XWXQkNDKzA6ALAO/SMAOEf/CMAVTOsDAAAAAACAZZjWBwAAAAAAAMuQnAIAAAAAAIBlSE4BAAAAAADAMiSnAAAAAAAAYBmSUwAAAAAAALAMySkAAAAAAABYhuQUAAAAAAAALENyCgAAAAAAAJYhOQUAAAAAAADLkJwCAAAAAACAZUhOAQAAAAAAwDIkpwAAAAAAAGAZklMAAAAAAACwDMkpAAAAAAAAWIbkFAAAAAAAACxDcgoAAAAAAACWITkFwC/NmzdPF110kapXr65HHnnE6nAAoNKgfwQAAJUNySkAlcaiRYsUFham+vXr68knnyzXsZo1a6bp06dr+PDhFRMcAFiI/hEAAPizalYHAACSdOzYMd10002aO3eu6tatq+uvv16xsbHq2LGjW8ezf+n68MMPKzBKAPA++kcAAODvSE4BqBT+/vtvGYahTp06qU6dOqpXr57y8vKsDgsALEf/CAAA/B3T+uBTtmzZogkTJqhly5YKCgpSw4YNdcUVV2jt2rWWxpWdna3JkycrLCxMNWvWVJcuXfTee++5tO+xY8d03333aeDAgWrcuLFsNluJNUC2b9+u4cOHKywsTOecc47atm2rGTNm6K+//nLrmBMmTJDNZivxtnHjxsK2KSkpLrVzV5MmTTR8+HB17NhRrVq10ujRoxUVFVXu47pjxowZat++vQoKCgq3leXfqajXXntNNptNderUKVdMr7/+upo3b66cnJxyHQf+q6r3j5s3b9agQYNUt25d1alTR/369dOXX35ZrmOWJfbyvM6z8af+0dX/x8qC/hEAAN9Hcgo+46GHHlKvXr20d+9ezZgxQ5999pmeffZZ7d27VzExMXr33Xctiy0uLk7z58/Xww8/rE8//VTdu3fXmDFjtGDBgrPue+TIEb3yyivKzc0ttf7H999/rz59+mjnzp2aPXu2PvnkE/3rX//SjBkzNGbMGLeO+dBDD2nDhg3Fbo0aNVLz5s3VvXv3Yvs89thjxdp36NDhrK/TFUW/7FxyySVO2/Tv3181a9Z0envooYfKHcO+ffv05JNPasaMGQoION1FunpOi0pPT9e9996rsLCwcsd17bXXqnbt2uWuNQP/VNX7xy1btqhv3776+++/9fbbb+vtt9/W8ePH1b9/f23YsMGtY5Y19vK8Tlf4Q/9Ylv/HyoL+EQAAP2AAPmDatGmGJOOpp54q9tzx48eN8847zwgJCTGOHj3q9dj+97//GZKMBQsWOGwfMGCAERYWZuTl5ZW6f0FBgVFQUGAYhmEcOnTIkGQ8/PDDxdpNnTrVkGT8+uuvDttvuukmQ5Lxxx9/lPmYzqSkpBiSjAcffNBhe3JysiHJ+OCDD1w6TlmtW7fOsNlsxhVXXGFIMmbNmlUhx504caLLr90wDOO+++4zmjdvbuTn5ztsd+ecDhkyxBg6dKhx7bXXGrVr1y5r6MU8/fTTRkhIiJGTk1PuY8F/0D8axqBBg4zQ0FCH90ZWVpbRqFEjo0+fPm4dsyyxl/d1no2/9I9l+X+srOgfAQDwbYycQqW3ceNGzZw5U9dee63uvffeYs8HBQXppptuUmZmpr744guvx7dkyRLVqVNH//znPx22X3fdddq3b582bdpU6v72qXFnU716dUlSSEiIw/Z69eopICBANWrUKPMxnXn99ddls9l0/fXXu7W/O/Lz83XHHXcoPDxc8+fPV2BgoFJTU8t1zLy8PB0/flz5+fkOj0tz4sQJvf766xo7dqzDqACp7Of0nXfe0erVq/Xiiy+6Fb8zV199tbKysipsqhB8H/2j6csvv1RMTIzOOeecwm1169ZV3759tX79emVkZJT5mGWJvbyvszT+1D+W5f+xsqJ/BADAt5GcQqX36KOPymazacaMGSW2OffccyVJe/fudfm4hmEoLy/PpVtpvv32W7Vr107VqjmuL9CpU6fC5yvCtddeq3r16unWW2/V77//rmPHjumTTz7Ryy+/rNtvv121a9cu9+/IzMzUokWL1L9/f7Vq1cppm9tvv13VqlVTcHCwBg0apHXr1pX797700ktKTU3VU089pYYNG+qCCy4o95evmTNnqlatWkpISND//d//qVatWnr77bdL3WfTpk06cuSI+vXrV67fffDgQU2ePFmPP/64wsPDy3Wsopo2baq2bdvqf//7X4UdE76N/tF04sQJBQUFFdtu3/bNN9+U+Zhlid2Tr9Of+kdP/j9G/wgAgG8jOYVKLTMzUytWrNDAgQPVokWLEttlZ2dLUpk+2K5evVrVq1d36bZz584Sj3PkyBE1aNCg2Hb7tiNHjrgcU2kiIyO1YcMGffvttzrvvPMUHBysoUOH6tprr9WcOXMq5HckJibq77//1sSJE4s9FxISokmTJunll19WcnKy5syZoz179igmJkbLly93+3ceOnRIDz30kC699FKNHj1akvmF7pdffilXgdxHHnlEhmE43CZMmFDqPvbaNBdddJHbv1eSbrvtNrVp00a33npruY7jzEUXXeS0yDOqHvrH09q3b6+NGzc61GXKy8srHLHkzu8pS+yeep3+1j96+v8x+kcAAHxXtbM3AazzzTffKC8vTx07diy1nf1Ds/0qtSu6du2qLVu2uNT2bAWtS5vO4O70ujPt3LlTQ4cOVWhoqBYtWqTGjRtr06ZNmjlzprKzs/X666+X+3e8/vrratiwoUaMGFHsuaioKIfVoaKjozVixAh17NhR9913nwYNGuTW73zggQeUlZWl559/vnBbp06d9P7772vHjh3q1auXW8d1x759+2Sz2dSoUSO3j7F48WJ9/PHH2r59e4X92xfVpEkTHTx4UHl5ecVGaaBqoX887c4779TEiRN1xx13aOrUqSooKND06dO1a9cuSSo2Dc1VZYndE6/T3/pHT/8/Rv8IAIDv4n9uVGpZWVmSpMaNG5fY5tixY0pMTFSrVq3UrVs3SdKwYcMc6qvk5ORo7dq1Disc1alTR126dHEpjtI+5DZs2NDpVfE//vhDkpxeTXeH/UtKampq4QiIvn37qlGjRrr++us1fvx4XXrppW4ff8eOHdq6dasmTZrkdHqMM/Xq1dOQIUP00ksv6e+//1atWrXK9Ds3b96sN998U+PHj1eLFi109OhRSaenIaWmpnr1y9fff/+t6tWrKzAw0K39s7Ozdfvtt+vOO+9UWFhY4es5ceKEJOno0aOqXr16uaau1KxZU4Zh6Pjx46pTp47bx4Hvo3887frrr9ehQ4c0c+ZMzZs3T5LUu3dv3XvvvXriiSfUvHnzMh+zLLF74nX6W/8oef7/MfpHAAB8F9P6UKnZ6/WUNm3kySef1LFjx/Twww8XXp3+8MMPlZ2drezsbE2cOFFxcXHq3bu3w34VNW2lY8eO+uGHH4rVXrHXOOnQoYMbr7y41NRUtW/fvlhio3v37pLKX7vFfsX6hhtuKNN+hmFIKvvIgIKCAt1+++0yDEPz589X/fr1C29jx46VpHLXVSmrRo0a6cSJE8rJyXFr/8OHD+vAgQN65plnHF5PYmKicnJyVL9+fV199dXlivGPP/5QUFAQX7xA/3iG+++/X4cPH9Y333yjnTt3av369frzzz9Vu3Ztde3atczHK0vsFf06/bF/lDz//xj9IwAAvouRU6jUOnbsqPPOO0+JiYl69NFHVb9+fYfn33nnHT322GO66qqrdO211xbbPz4+Xr/88ouWLl1a7GpvRU1bGTFihF599VUtXry4sCaIJM2fP19hYWHq2bOnS7/DlRi+/fZbZWdnO3zwtk/ZKU/h7dzcXL3zzjvq0aNHmb5E/fnnn/rkk0/UpUsX1axZs0y/89VXX9XWrVs1ffp09e3bt9jzI0eO9PqXr7Zt20qSfvvttzJNgbJr2rSpkpOTi21//PHHtXr1an366aflmhIjSb///rvat29frmPAP9A/FhcUFFTYh+3evVsLFy7UjTfeWOZRnVLZYq/o1+mP/aPk2f/HJPpHAAB8GckpVGo2m02vvvqqBg8erO7du+v+++/X+eefr/379+u9997TRx99pAkTJuiVV14ptu+MGTO0adMmLVu2zOny1HXr1i2c5lIesbGxGjBggG699VZlZWXp/PPPV2Jioj777DO98847hV/6Vq9erf79+2vatGmaNm2awzE+/fRT5eTk6NixY5Kk77//XosWLZIkDR48WOecc44mT56s4cOHa8CAAbr77rvVqFEjbdy4UbNmzVL79u0VGxtb5mPaLV26VH/88Uepo6bGjh2rFi1aqFu3bmrUqJF++eUXPfPMMzpw4IASEhLKdM7++OMPTZ06VX369NFDDz3kdNRV586dtWnTJhUUFLhdL6asYmJiJEkbN250+uXLlXNqP0ZRCQkJCgwMdPpcWRQUFGjz5s1OC9aj6qF/PP2++/bbb7V48WJ169ZNQUFB+vrrr/X444/rggsu0KOPPlosLleO6WrsZXmdrvDn/rGs/4+VBf0jAAA+zgB8wNdff21cddVVRmhoqBEQEGBIMlq2bGmsXLnSaftnnnnG6N27t3Hs2DGvxHfs2DHjrrvuMpo2bWrUqFHD6NSpk5GYmOjQJjk52ZBkPPzww8X2b9mypSHJ6S0tLa2w3apVq4yBAwcaTZs2NWrVqmW0bt3auOeee4zDhw+7fUzDMIwBAwYYtWvXNrKyskp8jbNmzTK6dOlihISEGIGBgUbjxo2NESNGGJs3by7TuTIMw7j55puNatWqGd98802JbSZPnmxIMn744YcyH788oqOjjcGDBzt9rizntKhrr73WqF27drlj++KLLwxJxrZt28p9LPgP+kfD+Omnn4y+ffsaDRo0MGrUqGGcf/75xoMPPmhkZ2c7jcnV97IrsbvTtjT+3j+W5f+xsqB/BADAt9kM41TBGMCHjBs3TgsXLtT69euLXd2fN2+eXnvtNa1atUohISEWRQhfZZ+Ws2vXLreKKHvSuHHj9Pvvv7NUOkpF/whPoX8EAACeQnIKPikrK0udO3dWjRo19NVXXzkUV61Xr56OHz/usIJUcnJyYcFVoDSGYahPnz7q2rWr5s6da3U4hX777Te1a9dOq1atclhVDTgT/SM8hf4RAAB4CjWn4JOCg4OVlpbm9Dn7ctuAO+x1fD766COv1nM5m927d2vu3Ll88cJZ0T/CU+gfAQCApzByCgAAAAAAAJapHJe8AAAAAAAAUCWRnAIAAAAAAIBlSE4BAAAAAADAMiSnAAAAAAAAYBmSUwAAAAAAALAMySkAAAAAAABYhuQUAAAAAAAALENyCgAAAAAAAJYhOQUAAAAAAADLkJwCAAAAAACAZUhOAQAAAAAAwDIkpwAAAAAAAGAZklMAAAAAAACwDMkpAAAAAAAAWIbkFAAAAAAAACxDcgoAAAAAAACWITkFAAAAAAAAy5CcAgAAAAAAgGVITgEAAAAAAMAyJKcAAAAAAABgGZJTAAAAAAAAsAzJKQAAAAAAAFiG5BQAAAAAAAAsQ3IKAAAAAAAAliE5BQAAAAAAAMuQnAIAAAAAAIBlSE4BAAAAAADAMiSnAAAAAAAAYBmSUwAAAAAAALAMySkAAAAAAABYhuQUAAAAAAAALENyCgAAAAAAAJYhOQUAAAAAAADLkJwCAAAAAACAZUhOAQAAAAAAwDIkpwAAAAAAAGAZklMAAAAAAACwDMkpAAAAAAAAWIbkFAAAAAAAACxDcgoAAAAAAACWITkFAAAAAAAAy5CcAgAAAAAAgGVITgEAAAAAAMAyJKcAAAAAAABgmWpWBwDfVFBQoH379qlu3bqy2WxWhwOgghmGoWPHjiksLEwBAVzHKAv6R8C/0T8CAFDxSE5VcmvWrNFTTz2lbdu2KSMjQ0uWLNHw4cNLbL9u3Trdf//9+vHHH/XXX3+pZcuWuvnmm3X33XcXtklISNB1111XbN+///5bNWvWdCmuffv2KSIiosyvB4Bv2bNnj8LDw60Ow6fQPwJVA/0jAAAVh+RUJZeTk6POnTvruuuu08iRI8/avnbt2rrjjjvUqVMn1a5dW+vWrdPNN9+s2rVr66abbipsFxwcrJ9++slhX1cTU5JUt25dSeYHs+DgYJf3A+AbsrKyFBERUfheh+voHwH/Rv8IAEDFIzlVycXGxio2Ntbl9lFRUYqKiir8OTIyUklJSVq7dq1Dcspms6lp06Zux2WfqhIcHMyXL8CPMS2t7OgfgaqB/hEAgIrDRHk/t337dq1fv17/z96dx0VV738cfw2goCjkrgiKmWXkxs+9QiFzq7wqWaZllpotWnq9bZS5pJV186ZlexaVSZaiZmWWBS6puWK7aWEq4q4gpChwfn8cGRnWAWaYAd7Px+M8Zuac75n5zHTP93o+fL+fb8+ePW32p6Wl0bx5cwIDA7npppvYsWNHke+TkZFBamqqzSYiIiIiIiIiUlZKTlVSgYGBeHt706lTJ8aNG8eYMWOsx1q3bk10dDSfffYZMTEx+Pj4cM0117B79+5C3++5557D39/fuqmeioiIiIiIiIg4gsUwDMPVQYh9LBZLsQXRcyQmJpKWlsamTZt4/PHHmTdvHsOGDSuwbXZ2Nv/3f/9Hjx49ePnllwtsk5GRQUZGhvV1Tr2FlJQUTVsRqYRSU1Px9/fXNV4K+u1EKjdd4yIiIo6nmlOVVIsWLQBo27Ythw8fZtq0aYUmpzw8POjcuXORI6e8vb3x9vZ2SqwiIiIiIiIiUnVpWl8VYBiGzaingo4nJCTQpEmTcoxKRKRs1q5dy4ABAwgICMBisbBs2bIi269fv55rrrmGevXqUaNGDVq3bs1LL71k0yY6OhqLxZJvO3v2rBO/iYiIiIhI1aaRU24uLS2NPXv2WF8nJiaSkJBA3bp1adasGVFRUSQlJfHBBx8A8Oqrr9KsWTNat24NmDdjL774Ig8++KD1PaZPn063bt1o1aoVqampvPzyyyQkJPDqq6+W75cTESmD9PR02rdvz913383NN99cbHtfX1/Gjx9Pu3bt8PX1Zf369dx77734+vrarGbq5+fHrl27bM718fFxePwiIiIiImJScsrNbd26lYiICOvrSZMmATBy5Eiio6NJTk5m37591uPZ2dlERUWRmJiIl5cXLVu2ZNasWdx7773WNqdOnWLs2LEcOnQIf39/QkNDWbt2LV26dCm/LyYiUkb9+/enf//+drcPDQ0lNDTU+jo4OJjY2FjWrVtnk5yyWCw0btzYobGKiIiIiEjhlJxyc+Hh4RRVsz46Otrm9YMPPmgzSqogL730Ur6pLCIiVc2OHTvYsGEDM2fOtNmflpZG8+bNycrKokOHDsyYMcMmqZVXQQtGiIiIiIiI/VRzSkREqpTAwEC8vb3p1KkT48aNY8yYMdZjrVu3Jjo6ms8++4yYmBh8fHy45pprilww4rnnnsPf39+6BQUFlcfXEBERERGpNCxGUcNyRAqhZZRFKreKdo1bLBaWLl3KoEGDim2bmJhIWloamzZt4vHHH2fevHmFrmaanZ3N//3f/9GjRw9efvnlAtsUNHIqKCiowvx2IlIyFa1/FBERqQg0rU9ERKqUFi1aANC2bVsOHz7MtGnTCk1OeXh40Llz5yJHTnl7e+Pt7e2UWEVEREREqgJN6xMRkSrLMAybUU8FHU9ISKBJkyblGJWIiIiISNWikVMiIlIhpaWlsWfPHuvrxMREEhISqFu3Ls2aNSMqKoqkpCQ++OADAF599VWaNWtG69atAVi/fj0vvviizSIS06dPp1u3brRq1YrU1FRefvllEhISePXVV8v3y4mIiIiIVCFKTomISIW0detWIiIirK8nTZoEwMiRI4mOjiY5OZl9+/ZZj2dnZxMVFUViYiJeXl60bNmSWbNmce+991rbnDp1irFjx3Lo0CH8/f0JDQ1l7dq1dOnSpfy+mIiIiIhIFaOC6FIqKgYqUrnpGi89/XYilZuucREREcdTzSkREREREREREXEZJadERERERERERMRllJwSERERERERERGXUXJKRERERERERERcRskpERERERERERFxGSWnRERERERERETEZZScEhERERERERERl1FySkREREREREREXEbJKRERERERERERcRklp0RERERERERExGWUnBIREREREREREZdRckqkkjl9+jSPPvooffr0oUGDBlgsFqZNm5avXUJCAjfeeCPNmjWjRo0a1K1bl+7du7NgwYJ8bb/77jtGjRpF69at8fX1pWnTpgwcOJBt27Y5NKaCvPPOO1gsFmrVqlXq+EVEwDn9Y3x8PBaLpcBt06ZNRcZz1113FXpu3vM3b95M3759qV27NrVq1SIiIoLvv/++wPctSVsRERERd6DklEglc/z4cd566y0yMjIYNGhQoe1OnTpFUFAQzz77LF9++SUffPABwcHBjBgxgpkzZ9q0ff3119m7dy8TJkzgyy+/ZO7cuRw5coRu3brx3XffOSymvJKSknj44YcJCAgoU/wiIuCc/jHHs88+y8aNG222Nm3aFBnPU089le+cjRs3Ur9+fZo2bUrnzp0B2LJlCz169ODMmTN8+OGHfPjhh5w9e5ZevXqxceNGm/csSVsRERERd2ExDMNwdRBS8aSmpuLv709KSgp+fn6uDkdyybmkLRYLx44do0GDBkydOtXukUrdunXj4MGD7Nu3z7rvyJEjNGzY0KZdWloal112GW3atGH16tVOiWnAgAFYLBbq1q3L4sWLSUtLK1X8UnK6xktPv537ckb/GB8fT0REBJ9++ilDhgwpc4xr1qwhPDycyZMnM2PGDAD69etHQkICf/31FzVr1gTMUWCXXnopl19+uc2oqJK0ldLRNS4iIuJ4GjklUkrz5s0rcjpGzZo1OXfuXLnHlfP5pVW/fn28vLxs9uVNTAHUqlWLkJAQ9u/f75SYFixYwJo1a3jttddKdF5B8QP8/vvvjBgxguDgYLy9vWnUqBF9+vRh165dJXp/ESleVeofHW3+/PlYLBZGjRpl3ff9998THh5uTTYB1K5dmx49erBhwwaSk5NL1RbUN4qIiIh7cO6/sEQqsQEDBtCpUycAduzYwQMPPMD//vc/unfvDkDNmjWpXr16id7TMAyysrLsauuoG6Ts7Gyys7M5efIkn376KatWrWLevHnFnpeSksL27du57rrrHBJHbkeOHGHixInMmjWLwMDAItvaE//u3bvp3LkzERER/O9//6N+/focPHiQlStX4uvr6/D4Raq6qtg/jhs3jttuu42aNWvSvXt3nnrqKa699toSfV5KSgqLFy+mV69etGjRwrr/3LlzeHt752ufs++nn36iSZMmJW6rvlFERETchZJTIqXUvHlzmjdvDsD27dsBGDJkCEFBQTbtjh49yl133UV8fDxNmzbl1VdfpXfv3gW+55o1a4iIiLDr8xMTEwkODi79F7jggQce4M033wSgevXqvPzyy9x7773Fnjdu3DjS09N58sknyxxDQTFdccUV3H///Xa1LS7+jz76iOzsbJYtW4aHx8UBo7fddptjAxcRoGr1j/7+/kyYMIHw8HDq1avHnj17+O9//0t4eDhffPEFffv2tfvzYmJiOHPmDKNHj7bZHxISwqZNm8jOzrb2YZmZmfzwww+AWUurNG3VN4qIiIi7UHJKxAESEhKoW7duvhsvMJM4jRs35ujRo6xevZpbb72VPXv2UK9evXxtO3bsyJYtW+z6zIKKhJfGE088wZgxYzhy5AgrVqxg/PjxpKen8/DDDxd6zlNPPcVHH33EK6+8QseOHR0SR44lS5awYsUKduzYYdf0G3vir1+/Pv/88w933303Y8eOpVu3bnh6ejo0bhEpWGXvH0NDQwkNDbW+DgsLY/DgwbRt25ZHH320RMmp+fPnU69ePQYPHmyz/8EHH2T06NGMHz+eJ598kuzsbKZPn87ff/8NYJNYKklb9Y0iIiLiNgyRUkhJSTEAIyUlxdWhuIXOnTsb1113Xb79p0+fNqpVq2bs27fPuq9nz57G/PnzC3yf7Oxs4/z583Zt9jh69KgBGFOnTrX7u9x3332Gl5eXceTIkQKPT5s2zQCMZ555xu73tDem06dPG40aNTL+85//GCdPnrRuw4YNM3x9fY2TJ08aaWlpJY7//PnzxqxZs4zWrVsbgNGgQQPjoYce0v9+i6BrvPT029mqSv1j3raA8c8//9j13jt37jQAY8KECQUenzVrllGrVi0DMACje/fuxmOPPWYAxrp160rVVn1j6egaFxERcTwVRBcpI8Mw+Pnnn+nQoUO+Y7t376ZWrVo2Iwbatm3LL7/8UuB7rVmzhmrVqtm17d271ynfp0uXLmRmZvLXX3/lOzZ9+nSmTZvGtGnTeOKJJxz+2ceOHePw4cPMnj2bOnXqWLeYmBjS09OpU6cOt99+e4nj9/Ly4rHHHuO3335j//793Hfffbz88ss888wzDv8OInJRVeof8zJyrQxoj/nz5wMwZsyYAo8/9thjHDt2jJ9++om9e/eyYcMGTp48ia+vb74RrPa2Vd8oIiIi7kLT+kTK6MSJE5w5c8ameG2OtLS0fMtM+/n5cezYsQLfyxXTVvKKi4vDw8ODSy+91Gb/jBkzmDZtGpMnT2bq1KlO+ezGjRsTFxeXb/+sWbNYs2YNK1eupH79+kW+R2Hx5wgMDOTJJ5/kxRdfJDMz0yFxi0jBqkr/mNfJkyf5/PPP6dChAz4+PsW+b0ZGBgsWLKBLly60adOm0Hbe3t7W4/v27WPRokXcc8891KhRo0xtQX2jiIiIuJaSUyJl5O3tTbVq1fjmm29o164d7du3x9/fH4BatWqRmppq0z41NZVatWoV+F61a9e2rnBVFitXriQ9PZ3Tp08D8Ouvv7J48WIAbrjhBmrWrMnYsWPx8/OjS5cuNGrUiGPHjvHpp5+yaNEiHnnkERo0aGB9v9mzZzNlyhT69evHjTfeyKZNm2w+r1u3btbna9asoVevXkyZMoUpU6aUKCYfHx/Cw8PzfZ/o6Gg8PT1tjtkb//jx40lJSaF37940a9aMo0ePMm/ePKpXr25X4XcRKb2q0D8OHz6cZs2a0alTJ+rXr8/u3buZPXs2hw8fJjo62uazC+sfly1bxokTJwodNfXzzz+zZMkSOnXqhLe3Nzt37mTWrFm0atWKGTNmlKqt+kYRERFxKy6eVigVlOot2Prf//5nBAQEGICxa9cu6/6cmir79++37gsPDy+0poqjNG/e3FprJO+WmJhoGIZhvPvuu0ZYWJhRv359w8vLy7jkkkuMnj17Gh9++GG+9+vZs2eh75e3G4mLiyuwjos9MRVm5MiRhq+vr80+e+N/5ZVXjLCwMKNhw4aGt7e30aJFC2PUqFHGn3/+ad+PWUXpGi89/Xa2Knv/+NxzzxkdOnQw/P39DU9PT6NBgwbG4MGDjc2bN+drW1j/2Lt3b8PX19dITU0tMOZdu3YZPXr0MOrWrWtUr17duOyyy4zJkycXWIPP3rbqG0tP17iIiIjjWQzjQlEEkRJITU3F39+flJSUfNMyxNYtt9yCv78/r7zyCt9++y0jRoxg9+7dxU5PE3ElXeOlp9/OfuofpSLSNS4iIuJ4mtYn4mSvvfYaI0eOpF69ejRt2pRFixbpxktEBPWPIiIiImJSckrEyRo0aMCXX37p6jBERNyO+kcRERERAfBwdQAiIiIiIiIiIlJ1KTklIiIiIiIiIiIuo+SUiIiIiIiIiIi4jJJTbm7t2rUMGDCAgIAALBYLy5YtK7L9+vXrueaaa6hXrx41atSgdevWvPTSS/naLVmyhJCQELy9vQkJCWHp0qVO+gYiIiIiIiIiIoVTcsrNpaen0759e+bNm2dXe19fX8aPH8/atWv57bffmDx5MpMnT+att96yttm4cSNDhw5lxIgR7Ny5kxEjRnDrrbfyww8/OOtriIiIiIiIiIgUyGIYhuHqIMQ+FouFpUuXMmjQoBKdFxkZia+vLx9++CEAQ4cOJTU1lZUrV1rb9OvXjzp16hATE2PXe6ampuLv709KSgp+fn4likdE3J+u8dLTbydSuekaFxERcTyNnKrkduzYwYYNG+jZs6d138aNG+nTp49Nu759+7Jhw4ZC3ycjI4PU1FSbTURERERERESkrJScqqQCAwPx9vamU6dOjBs3jjFjxliPHTp0iEaNGtm0b9SoEYcOHSr0/Z577jn8/f2tW1BQkNNiFxEREREREZGqQ8mpSmrdunVs3bqVN954gzlz5uSbrmexWGxeG4aRb19uUVFRpKSkWLf9+/c7JW4REXtpwQgRERERkcrBy9UBiHO0aNECgLZt23L48GGmTZvGsGHDAGjcuHG+UVJHjhzJN5oqN29vb7y9vZ0XsIhICeUsGHH33Xdz8803F9s+Z8GIdu3a4evry/r167n33nvx9fVl7NixwMUFI2bMmMHgwYNZunQpt956K+vXr6dr167O/koiIiIiIlWSklNVgGEYZGRkWF93796db775hn//+9/WfV9//TVXX321K8ITESmV/v37079/f7vbh4aGEhoaan0dHBxMbGws69atsyan5syZQ+/evYmKigLMUaNr1qwpcARqWWVlwbp1kJwMTZpAWBh4ejr0I0REREREKgQlp9xcWloae/bssb5OTEwkISGBunXr0qxZM6KiokhKSuKDDz4A4NVXX6VZs2a0bt0aMKexvPjiizz44IPW95gwYQI9evTg+eefZ+DAgSxfvpzVq1ezfv368v1yIiIulLNgxMyZM637Nm7caJO4B3PBiDlz5hT6PhkZGTZ/ALBnwYjYWJgwAQ4cuLgvMBDmzoXISPu/g4iIiIhIZaDklJvbunUrERER1teTJk0CYOTIkURHR5OcnMy+ffusx7Ozs4mKiiIxMREvLy9atmzJrFmzuPfee61trr76aj7++GMmT57MU089RcuWLVm0aJFTpqxoZICIuJvAwECOHj1KZmYm06ZNc8iCEdOnT7f782NjYcgQMAzb/UlJ5v7Fi5WgEhEREZGqxWIYef95LFK81NRU/P39SUlJwc/Pr8A2GhkgUnHZc427E4vFwtKlSxk0aFCxbRMTE0lLS2PTpk08/vjjzJs3z1qTr3r16rz//vvW1wAfffQRo0eP5uzZswW+X0Ejp4KCggr87bKyIDjYtl+0/R5mP5mYqES+iLuqaP2jiIhIRaCRU+IUGhkgIu7KlQtGrFtXeGIKzD5z/36zXXi4XW8pIiIiIlLhebg6AKl8srLMEVMFjcnL2TdxotlORMSVClswIjdHLhiRnOzYdiIiIiIilYFGTonDlefIANW0Eqm6KuKCEU2aOLZdUdQ/ioiIiEhFoeSUOFx5jQwobU0r3bCJVA4VccGIsDCzn0pKKnh0aU7NqbCwsn2Oav6JiIiISEWiguhSKkUVA42Ph1z3i4WKiyv9yKnCalpZLOZjYTWtSnLDpiSWVGUq+Ft6xf12Of0X2PZhxfVf9ipt/5hDfZ9I0dQ/ioiIOJ5qTonD5YwMyLkRystigaCg0o8MKG1Nq5wbtrxTDnOKtMfG2rYNDjaTbMOHm4/BwbZtRERKIzLSTBA1bWq7PzCw7Impstb8U98nIiIiIq6g5JQ4nKenORIJ8ieocl7PmVP6v8SXpKZVjpLcsJUkiSUiUhqRkbB3rzmCdOFC8zExsexT7krTP+Yoad+XlWWOlI2JMR9zJ7yKOiYiIiIikpdqTolT5IwMKGgK3Zw5ZbsBK01NK3tv2OLji05iWSxmEmvgQE1zEZGy8fQs+6IQeZW25l9xCfy8fV9RU6Sh5PWuNJVQREREpGpTckqcJjLSvJFx9A1HaVa7sveGLT7e/lEHYWG6mRIR91La1QBLMuLqxImCa1olJcHNNxd8fs7oq4KmLap4u4iIiIhoWp84Vc7IgGHDzEdHJG9KU9PKEcuy57Z8ueqyiIj7KW3NP3sT+ElJxU+RLkhh9a40jVpEREREQMkpqYBKU9PK3hs2e6fYzJlT+M3Up5/mr7Wi+isiUh5KW/PP3gT+0aNFj7AqSt56V2Ut3i4iIiIilYeSU1IhlXS1K3tv2MLDi05i5bxXQQzD3IYNsx1R1aiRuWmUlYiUh9KsBmhvAr9Bg7LHlzNKqyzF20VERESkclFySiqskq52Zc8Nmz1JrOL+ip/3+PHj5pZbTm2Wp58u3Wiq06dP8+ijj9KnTx8aNGiAxWJh2rRp9r9BHu+88w4Wi4VatWqVqd3mzZvp27cvtWvXplatWkRERPD999+XOi4RKZ2S9o/2JvDz9p+lkTNKy96phN9+W37943fffceoUaNo3bo1vr6+NG3alIEDB7Jt27ZSt73rrruwWCyFbps2bbL/y4mIiIhUUhbDKKpKhEjBUlNT8ff3JyUlBT8/P1eHUyL2rApVUIHeoCAzoTRnjnPiKkkB4L1799KhQwfat2/P5ZdfzjvvvMPUqVNLlaBKSkriqquuwtfXl5SUFNLS0krVbsuWLYSFhdGlSxcmTZqEYRi88MIL7Nixg7i4OLp3717i2MR1KvI17mol+u0OH4Zz56B69YtbtWrmVtQQTicprO/LWWU1K8sc+ZmUVHSNqYJYLGY/l5ho9rnx8eZIUnuUV/94yy23cPz4cW655RZCQkI4evQos2fPZuvWraxatYrrrruuxG3//PNPjh49mu+zBgwYgLe3N3///TeeWk2jQlH/KCIi4nhKTkmpVIV/mBWUxFq3zv6bqZLKuQ8tbNpNbjmXrcVi4dixYzRo0KDUyakBAwZgsVioW7cuixcvLjQ5VVy7fv36kZCQwF9//UXNmjUBcwTDpZdeyuWXX64RVBVMVbjGnaVEv93AgfDZZwUfq1bNNmGVO4FVkn0+PuDra/eW5ePLum01ST5kKTCBn1PEHGwTVBbLxde5n+e8Bli0yJwamJwMDRvCXXfZl+gqr/7xyJEjNGzY0GZfWloal112GW3atGH16tWlapvXmjVrCA8PZ/LkycyYMaPYuMS9qH8UERFxPC9XByDirnJWGswtpy7LxZspA3gTeBXYDQQCs4BIoB0wHHjCrs8zDPMGbOJE8361qD+kWxw0omLBggWsWbOGX3/9lcmTJ5ep3ffff8+NN95oTUwB1K5dmx49ehAbG0tycjJNHL1sokhF5+FhJpTOn89/7Px5c0tPL9eQPIFwiwVq14Y6dfJtkXXq8NNtl7BwZR3+PFWXozTgMI3watKIKXPrgYfHhdFXF/tHw9jNJZcEct99szhx4mL/WK/eE9a+r7jV/sqjf8ybbAKoVasWISEh7N+/v9Rt85o/fz4Wi4VRo0aVOlYRERGRykTJKXGuc+egb1/zBqygzdOz5McK2u/lZd7g5TwW9jz3vmrVwNvbHFWQ81jQ8+rVrX+2z6nLYo4aMIChwOfAdCAUeB64C0gFTgITC/hRDKDgAio5BYC//db8rCNHvAqdelhWR44cYeLEicyaNYvAwMAytzt37hze3t759ufs++mnn5ScEslr6VLz0TAgM9PsM8+dM5NSOc8L22fP64wMOHvWTHClp0Na2sXnBW1nzlyMJzXV3P7+O1/YVwHP5N15ELjNExo0YFDDhkSmH2ZVyjH+3b4ngU2uZ8qX8ZzgTnw4zNkL/eOJE+apdevm1OYrvn+Mj4eePcHLq3z+CZOSksL27dttpvSVpW1KSgqLFy+mV69etGjRwpGhioiIiFRYSk6Jc2VmmncSFZnFAjVrWqe8RPr6cuwyX/6bmMKszN95gKu5ikTSLMf50WjBR6ymOg9xBaOoyY+coC7HqccpLiEbT2ANUPTcwL59c54lAsElqrdirwceeIArrriC+++/3yHtQkJC2LRpE9nZ2Xh4mGstZGZm8sMPPwBwPG9VeBG5yGK5mDT39XVdHNnZ8M8/ZhIrJQVOnry4nTpl+/rkSThxAo4cMWtnnThhzoc+dIj3Dx1iOfARMHzHd7DjO9oCPYAajOd5anANYewxLuMvWnI8+zKuuOMyHllwnBSK7uiuv958jIlJxDCCnZbAzzFu3DjS09N58sknHdI2JiaGM2fOMHr0aEeGKSIiIlKhKTklzlW9ullkJDs7/5aVVbL9hR3LyjKTYOfP538s6nnuUQU5jznPMzIufgfDuDiq4IK6wNdAG+BVNgAbwICfMW/GWpLODl7Bk1es52Rj4SR1SKQe2/g/jlOXE9TlCA05TGMO0YjDNOYo9cm2XpoBgDmNcMgQs97KwIG2tbCuvLLk/1mWLFnCihUr2LFjR5FTYOxtB/Dggw8yevRoxo8fz5NPPkl2djbTp0/n7wujLnISViLixjw8oFYtc2vcuGTnnj9vTVTNGzqUNmfOMHzcOJI27WfHZ/vIYDfwB42BcZzBk+10ZLt57klgAdwGbMKfv2jJn1zKn7TkV0LYTSuyqAbA2LGwbBkMGxZg/eicBL4j+sfcnnrqKT766CNeeeUVOnbs6JC28+fPp169egwePLhswYmIiIhUIkpOiXN5ecGtt7o6ipLLzjanxWRkmNNc8kx9OXn4MDtGjODxfv3MP+OnpEBqKvu+T4Qty7mFduygGvU4Tn3LcWobp/HAoB4nqMsJOhTx0VlYOEgA+2hGEsHsphW/G63ZRWsm3nM5Eyb42qyklTNTbu9eiIkpfAXCHGlpaYwbN44HH3yQgIAATp06BZjT8gBOnTpFtWrVMAzDrna+F0Z5jBo1iqNHjzJz5kxef/11ALp3787DDz/M888/T1NHrEEvIu6rWjVo2pSTNWuy488/efzxxyEqirUxMPwzgJ1AB/7iI9rRnpb8yWXssW5XN9hNraN7iSCFCLZDTuIKyKAaO2nPz9U78f1bnahHJ47hSfaF40lJ5mqq9erlTA80lWUm8fTp05k5cybPPPMM48ePd0jbH3/8ka1btzJhwoQCp0GLiIiIVFVKTokUxMPjYt0pf/98h/ds2YJhGLQYPBjuuce6/4tx42ALtPnkC3ZnBpLWBJqFQdb582z68gSn/jzG+m9XMWvVf4r4cANIApJIZCPDcx86AftOBPE7rfmRdmzn/9icfCkA779vbgBNm5qjC1q1yp+sOnbsGIcPH2b27NnMnj0736fXqVOHgQMHMmfOHLvaLVu2zLrvscceY+LEiezevZvatWvTvHlz7r33Xnx9fYsddSAilcOePXvM/vFCPaWLCaK3AMigB78SyK9cZXNe3CewfvVKnnrmhgLe9TywFc5tte75iZokczWruZ5vjV7sIJTjx22z8snJ5uNvv5XsO0yfPp1p06Yxbdo0nnii6EUtStJ2/vz5AIwZM6ZkAYmIiIhUckpOiZSC54VMz9GjR637tm3bxltvmTdf3boZBAXlPqEa10Q2AhrR475m1Hm9B7NnmzNgcvj5QWpqNvU4QSMO0ZhDvIxBCH9yBbtoze804BjN2E8z9tOHbwA4BjQA7uI9riKNtfRgfdK1TJ1a1/reuWtWNW7cmLi4uHzfadasWaxZs4aVK1dSv359u9vl5e3tTZs2bQDYt28fixYt4p577qFGjRp2/roiUpHl7R/DwqBhw20cOfLWhRa2y/JZLGYfFRYGHTteS3W/LXn6R4P29ZIY1uFXDn77KyH8ypX8xuX8QxtW05vVAJygDnFE8C29WEVf/qKl9TO++sqcAW5PXaoZM2Ywbdo0Jk+ezNSpUx3WNiMjgwULFtClSxdrHykiIiIiJothFLV4s0jBUlNT8ff3JyUlBT8/P1eHU+4yMjIICgrCMAzmzp2Lh4cHkyZNomfPnnz88cdMnjyZsWPHEmSTobKVlWVbGyUr62Kh38LU4xhXsIsr+Y1qLCeQXdRjL/dznluAnAmUNwB/0oa19OBDgviBycAUliyZUmhR9bvuuovFixeTlpZWZAyFtfv5559ZsmQJnTp1wtvbm507dzJr1iyCg4OJi4ujVq1aRX85cStV/Rovi6r+2xXUPz7wwCROnuwJfAxMBsYCQTkLobJ4se2CD3n7x7Aw+OQTGH5hKKkHWYTwK+HEcz2rCScef1Kt568EfqEZ6wjlM5YDt3DzzbfSti1MmnQDtWvXBGDNmjX06tWLKVOmMGXKFGbPns3DDz9Mv379Ckw2devWzfq8JG0BFi1axG233cZbb73FPblG3ErFU9WvcREREacwREohJSXFAIyUlBRXh+Iy69evNzp27GhUr17dqFOnjhEVFWVkZ2cbY8eONapVq2a8/vrrJXq/zEzDCAw0DIvFMMwq7MVtzQ3MIQj5tsRcDeMu7BvClcaDdRcYmUdPFPj5I0eONHx9fYuNs7B2u3btMnr06GHUrVvXqF69unHZZZcZkydPNtLS0kr0O4h70DVeevrtCu4fFy/ONnx9xxpQzYDXDTCMoCDDWLLEvveMiyu8P/TkvNGVjcYTzDTi6Gk0L6RvBIzGjRONTz4x32/y5DgDMJ56aqphGIbRs2fPQs/L+0+mkrQ1DMPo3bu34evra6SmppblpxU3oGtcRETE8TRySkpFfzV0jthYc1U+MG+5SqsBR7iW9VzPav7FZwSSZD2W7emFR3hPGDTI3AIDyxSzVE66xktPv13hChoRZc9Uu5xzg4PN4ufF9Y91Oc4AVhBJLH34Gh8ursC6kW68yygWMZTTmP99ck99FimOrnERERHHU3JKSkX/MHOe2FiYMAGbFfkCA81FA0+cKHnSykI2HdnGQJYziGW04RfrsWyLBye630idJx7As38fsxC8CLrGy0K/nfOUJoFfi9PcyBcMZyE38CVeZAHwDzVYyHBe4FH2WC4H8k8vFCmIrnERERHHU3JKSkX/MHOugkYXLF/umFFVLz+0h1PvLyciZSnX8r11f1qjS6n1n/vg7ruhgELnUrXoGi89/XbOVVACv149OH7cLK5eVP/YiEOM4EPu5j1CMJfwy8bCEm7meR7nSFBHEhPtH80lVZOucREREcdTckpKRf8wc42CbsrsZbFA3bq2o68uZxf38QZ38x6XkGLu9PaGoUPhiSfgiiscF7xUKLrGS0+/nfMVlsC3v380uIbveZQX+BcrrHu/4XoazI6iw78jsFZrF8lD17iIiIjjKTklpaJ/mLlO3puyY8fg3/8u+oYsZzRBzuiCvGrwD8P4mAnVXqPd+W3mTg8PGDkSpk6F5s2d82XEbekaLz39dq6T0z9++y3MnGnfOVfxM4/yAsNZaJ3yR+fO8PjjZl0+TXeWPHSNi4iIOJ6SU1Iq+oeZe8mdsNq9G95+2zZZFRQEY8aYeabibH1tMx1XPWsOQwCoVg3GjoUnnzSzYVIl6BovPf12rleS4uk5mrOX/zCbB6q/g+e5swCkXNWdWu/Nw7Pz/zkvWKlwdI2LiIg4nv4cKFIJeHpCeDgMGwZTpsDevRAXBwsXmo+JidCqlX3vtexgF2KGLmPbq5swel0P58/Dq69Cy5YwYwacO+fMryIiUmaenubqe2D/7Lx9lmCm13uFjvX+ZiZPkoYv/r9sxNKlE3/1va/gYaciIiIi4hAaOSWlor8aVjzx8RARUbJzAgPhozFx9Fj1JGzcaO4MCYG33oJrrnF4jOI+dI2Xnn4792Fvnb6CCqkHkMQLPMrtLAQgo1ZdvP/7DNxzjyqmV3G6xkVERBxPI6dEqoiwMDPZVJIav0lJED49gtj/fG8Ow2rYEH79Fa69Fu67D06dclq8IiJlFRmZfyTpp5+afWFuTZuaNflyO0hT7uAjerCGnbTDO+0E3H+/WY9qy5Zy+w4iIiIiVYFGTkmp6K+GFVNsLAwZYj6398q3WMwbucRE8Ew5AY8+CvPnmwcDAmDxYuje3TkBi8voGi89/XbuL+/CEllZcP31hbf3JJP7eIM5vpPxSk8BLy9zmvMjj2gUVRWka1xERMTxNHJKpAqJjDRzSU2b2n+OYcD+/fDKKxCzqi7xd7xD1uo4s4jVwYNmsaucZJWISAWQu05feDgcOVJ0+yy8eJXxfPbiH3DLLZCZCVFRZkaruDmDIiIiIlIsJafc3Nq1axkwYAABAQFYLBaWLVtWZPvY2Fh69+5NgwYN8PPzo3v37qxatcqmTXR0NBaLJd929uxZJ34TcRd5p7lMnmzfef/+NwwfbtatCr4rnM+mboPBg80C6WPGwPjxZvF0EZEKxt6FSOu2bgiLFsG774Kvr1nMr107c1iqiIiIiJSaklNuLj09nfbt2zNv3jy72q9du5bevXvz5Zdfsm3bNiIiIhgwYAA7duywaefn50dycrLN5uPj44yvIG4o96iBXr1Kfv6BAzDwjtpMaraYxFEzzJ2vvmqOIihuCIKIiJspriafxQJBQXD11RC/xkKMz9388MYOjE6d4ORJuPlmsx6VVjMVERERKRXVnKpALBYLS5cuZdCgQSU676qrrmLo0KFMmTIFMEdOTZw4kVNlKGateguVR1YWBAebxc9L2xvcVW8Fb/1zO9XOnDbv4JYtg//7P0eGKeVM13jp6bermAqryZeTsHr4YYiJsZ3F16LpOVZ2mcoVy543TwoPhyVLoG7dcotbyp+ucREREcfTyKlKLjs7m9OnT1M3zz+U09LSaN68OYGBgdx00035RlZJ1eHpCXPnms9LspJfbu+fGEC7M5s5HXC5WaDqmmvgo48cF6SIiJMVVpMvMNBMTL34Yv7yUnsPVufKZc/xfdTnULu2Oc2va1fYtavc4hYRERGpDJScquRmz55Neno6t956q3Vf69atiY6O5rPPPiMmJgYfHx+uueYadu/eXej7ZGRkkJqaarNJ5VGaQum5GQbssrSmu+UHjP43wNmzcMcdMHWqYwMVyUU1+cTR8tbki4uDPXvMEVMFjSzN2TfswxvIWvs9NG9untCtG3z7bbnGLiIiIlKRKTlVicXExDBt2jQWLVpEw4YNrfu7devGHXfcQfv27QkLC+OTTz7h8ssv55VXXin0vZ577jn8/f2tW1BQUHl8BSlHeW/KXnqpZOcbBvySdAlr/vMZPPmkufPpp+HZZx0eqwioJp84R96V/DZsKHpBvpwVTdedagubN0P37nDqFPTtqxGkIiIiInbycnUA4hyLFi1i9OjRfPrpp1x//fVFtvXw8KBz585FjpyKiopi0qRJ1tepqalKUFVCOTdlYNaimj275LWoko94wsyZUKeOORfmySehVi146CGnxCxVV//+/enfv7/d7efMmWPz+tlnn2X58uWsWLGC0NBQ636LxULjxo0dFaZUcMnJ9rVbsgSgIWHffIfnvWPMxNSdd0K1apBr9LKIiIiI5KeRU5VQTEwMd911FwsXLuTGG28str1hGCQkJNCkiLW0vb298fPzs9mkcittLSrr/4z+8x+YNs18PmGCufS6iBtxVE0+TXuu3Ir4v0Yb8+ZBRAQEt/YhdtAHMGoUZGfD8OGwdKlzgxQRERGp4JSccnNpaWkkJCSQkJAAQGJiIgkJCezbtw8wRzTdeeed1vYxMTHceeedzJ49m27dunHo0CEOHTpESkqKtc306dNZtWoVf/31FwkJCYwePZqEhATuu+++cv1u4v5KUosqZ6n1sLBcO6dMMZNUAGPGwKJFTolTpDQcVZNP054rt7Awsyi6vUn6pCQYcqsHsf3eghEjzGGoQ4fCihXODVRERESkAlNyys1t3bqV0NBQ65STSZMmERoaypQpUwBITk62JqoA3nzzTTIzMxk3bhxNmjSxbhMmTLC2OXXqFGPHjuXKK6+kT58+JCUlsXbtWrp06VK+X04qhNy1qCZONPflvUnLeT1njjniyubAf/8L995rzg284w7doIlbcGRNvqioKFJSUqzb/v37y+MrSDkp6ShSwzC3e+7z5Ns73iN76G1w/jwMGQIrVzo3WBEREZEKymIYJakmI2JKTU3F39+flJQUTfGrYmJjzVl6uQsEBwWZianISPN1VhasW2fWamnSBMKuycZz1EhYsAC8veHzz6GYWmjiWhXtGrdYLCxdupRBgwYV23bRokXcfffdfPrpp3ZNfb7nnns4cOAAK+1MLFS0307sU1DfZ4/mTTP5Pug2mm5aYvZ/K1ZA797OCVLKha5xERERx9PIKREpkYKWWk9MvJiYio2F4GCz9srw4RdqsFzqwdJ/vQeDB0NGhvm4a5crv4ZUUc6oySdVQ+6+b/x4+8/bd9CLFptiONh5oNn//etf5puIiIiIiJWSUyJSYnmXWs+Zyhcba85cyTuyICkJbh7qxbKhMdCjB6SlmQ3T08s7dKlEVJNPyltO33fzzfafYxiQaalGj+RFGDfcCGfPwk03mcNLRURERARQckpEHCQry5zyUtBE4Zx9Dz3iTdbCRdC4Mfz8M9x/f8EniNhBNfnEVUpaJN0w4M8D3qybsBj69IF//oEbb4TffnNuoCIiIiIVhGpOSamo3oLkFR9vTuErTlwchFvWQK9eZkbrzTdh7Finxyclo2u89PTbVQ05I0XB/hz7woUwbNAZ6NvXHDl1xRWweTPofycViq5xERERx9PIKRFxiOTkErTr2ROefdbc8eCDsG2b0+ISEXGGyEhYvBiaNrX/nCZNgBo1zBMDA83aeyNHQna20+IUERERqQiUnBIRh7C3XrS13SOPwMCBcO6cOfzgxAmnxSYi4gw5RdJXr4a6dQtvZ7GYq5qGhV3Y0bAhLFkC1avDsmUwa1Y5RCsiIiLivpScEimDtLQ0PD09efHFF10dSj4pKSl4eHjw0ksvWfcdPHgQi8XC22+/7fDPK64GS76bM4sFoqPh0kvNu7s77yxw9MDp06d59NFH6dOnDw0aNMBisTBt2rQSxZaWlsbEiRMJCAjAx8eHDh068PHHH5e6XUnbilRFVaV/9PQ0Zym//bbZreXtA3Nez5lzcfEIALp0gVdfNZ9PngxffVXi76H+UURERCoLJadEymDbtm1kZ2fTtWtXV4eSz9atWzEMg86dO1v3+fr6snHjRoYNG+bwz/P0hLlzzed235xdcok5vcXbG774At56K9/7Hj9+nLfeeouMjAwGDRpUqtgiIyN5//33mTp1KitXrqRz584MGzaMhQsXlqpdSduKVEVVrX8sbJpfYKC5PzKygJPGjDFr7hkGDB8Of/1Vos9U/ygiIiKVhiFSCikpKQZgpKSkuDoUl3rxxRcNT09PIz093dWh5DNr1izD09PTSEtLK9fPXbLEMAIDDcO82zK3oCBzf2amYcTFGcbCheZjZuaFk+bMMRvWrm0YBw7YvF92draRnZ1tGIZhHD161ACMqVOn2h3PF198YQDGwoULbfb37t3bCAgIMDIvBGFvu5K2rah0jZeefjtTVe0fC+3nCnP2rGF07Wr2ge3bG0YJfi/1j66ha1xERMTxNHJKpAy2bNlCmzZt2LBhA2FhYfj6+nLZZZfxas5UjQs2b97M0KFDCQ4OpkaNGjRs2JDBgwfz559/2rT7/fffGTFiBMHBwXh7e9OoUSP69OnDrl27bNqtX7+ePn364O/vT506dbjxxhvZvXt3vtiuvPJKfH19rfv69OlDjx49rK+vu+46IiIiWLNmDddffz21atWicePGPP300wV+X3s+N6cGS1ycuTJVXBwkJprHgoPNFf2GDzcfg4PNFa8YPx66doXTp+GBB2yWvrJYLFjsXa+9AEuXLqVWrVrccsstNvvvvvtuDh48yA8//FCidiVtK1JVVdX+sW5dfwYPrsOCBTfStOlu29GimIuUxsdDTIz5mOXlbQ6tatgQdu6Ee+6xe/k/9Y8iIiJSWSg5JVIGW7du5dixYzzxxBOMHz+e2NhYrrzySsaPH8+yZcus7RISEmjfvj1z585l1apVvPTSS/zxxx9E5prnsXv3bjp37kxKSgr/+9//+Oabb5g7dy5NmjSxuYGaNm0aPXv2JCgoiJiYGN555x32799Pr169SEtLs4kt95QVgB07dtCxY0ebuPbu3cu///1vRo4cyWeffUaPHj2YOnUqa9assTnX3s8Fc+peeDjcdpvBtddmEhubyc03Z3LgQCZwcTtwwNz/aawB8+dDtWrw2Wfw6ael/m+S188//8yVV16Jl5eXzf527dpZj5ekXUnbilRV6h/zf25sbO4kvUFERCbNm2fy6cbGZC5cSKaHh/n49ttkZmZaN2dR/ygiIiJuw9VDt6Ri0pB2wzhx4oQBGFdddZXxzz//WPenp6cbdevWNYYOHVrgeVlZWcb58+eNd955xwCMkydPGoZhGFOnTjVq1qxpZGVlFfqZK1asMADjhRdesNn/xx9/GICxYMECwzAuTu947bXXrG327t1rAMaHH35oGIZh/PnnnwZgdOzY0Th79qy13YEDB/Kda+/n5hUXF2cAdm179iQaxtSp5tSWhg0N49ixfO9XmmkrrVq1Mvr27Ztv/8GDBw3AePbZZ0vUrqRtKypd46Wn3079Y0Gfu2SJYVgsuac8298/JiYmFvq9c6h/LD+6xkVERBxPI6dESmnr1q0AzJgxgxo1alj316xZk1atWnH48GEADMNg8eLFXHfddQQEBODl5UW1atUYM2YMHh4e1nPr16/PP//8w9133833339PVlZWvs+cMmUKLVu2ZMKECTZ/VW/RogU1atTgrwvFdLds2QJAp06drOdu27YNgP/7v/8DYPv27QA8/fTTeHt7W9sdP34cgICAgBJ/bl4dO3bkjTe2AMVvf/0VAFFREBICR47Aww8X95/AbkVNe8l9zN52JW0rUtWof7T93KwsmDAh72y9juTuAxs12sKmDZvY0qaNuadbN7Zs3syWLVtsPs/R1D+KiIiIO/AqvomIFGTr1q34+vryr3/9K9+xQ4cOWWuXjB07lujoaO69914eeughGjRogLe3N2PGjOHMmTPWG5/77ruP9PR0oqOj+eCDD2jQoAHDhg1jxowZ+Pn5cejQIXbs2AFgc7OU2yWXXGKNrXr16tZpFGDebPn6+tK6dWvra29vb66//nqb98i5KQsNDbV+F3s/N69atWrh69uhwGN5HTvmBd7AO+/ANddAdLRZnKp3b7vOL0y9evWsN5S5nThxAoC6deuWqF1J24pUReofbT933To4cCDvkVpAB+urw4ch7R/oGRMDHTvCpk2wfTuMHp1vipyjqH8UERERd6HklEgpbd26lYYNG+KZp9rthg0b+Pvvv7nxxhvZtWsX77zzDi+88AKPPPKItc2xY8f45ZdfuPXWW637vLy8eOyxx3jsscc4cOAAb731FjNmzMDHx4fnn3+e/fv3A/DSSy9x7bXXFhhTy5YtrbG1a9fO5mZp27ZtdOjQAQ8PD+vrdu3aUb169Xzfq379+jRr1gygRJ+b15o1axgxIqLAY3lZLIlAMHTvDg8+CC+/bBZK/+UXKMONWdu2bYmJiSEzM9PmBu+nn34CoE2bNiVqV9K2IlWR+kfbz/3qq4KOrAFs+8c8uTC47z647z4SExMJDg4u8P3LQv2jiIiIuAtN6xMppS1btnDw4EFOnTpl3ZeZmcljjz1G69atufnmm/n7778BCAkJsTk3Z/pH7mkluQUGBvLkk09So0YNazHcnL82WywWOnXqVOBWp04da2x533v79u3WKStgFv8t6PO3bdtmUxS4JJ+bV8eOHdm0aQsNGxY9pa9Roy0MHJhr2srMmVC/PvzxB3zwQYHvba/BgweTlpbGkiVLbPa///77BAQE0LVr1xK1K2lbkapI/aPt5zZpUtA3sZ3WB1t4440tbNmyhS2bNrGlbVtzb5cuBBT8BmWm/lFERETchUZOiZTC0aNH2b9/Py1btmTIkCE8/PDDnD17lrlz5/LTTz+xfv16vLy8aN++PTVr1uSpp57CYrFw5swZ3n77bfbs2QNcrHkyfvx4UlJS6N27N82aNePo0aPMmzeP6tWrc++99wLmX98jIiKYPHkyaWlpdO3aFcMwSE5OJi4ujpEjRxIeHk5ycjLJyck2K1EdOHCAI0eOWG+q9u/fz9GjR/PdfGVmZrJz504mTZpk3Wfv5xakdu3adO3aiddfhyFDzH25a65YLObrBx6AZcugSRMICwPP2rXN+lP/+Q9Mm8bK+vVJP3eO06dPA/Drr7+yePFiAG644QZq1qzJmjVr6NWrF1OmTGHKlCnWz+jfvz+9e/fm/vvvJzU1lcsuu4yYmBi++uorFixYYB3ZYW+7krYVqWrUP+b/3LAwCAyEpKTcfWBtwPwMi8U8PmaMudopYK5a2qEDbN5sJunvuafA33vlypWkp6erfxQREZGKzZXV2KXiquor1XzxxRcGYGzatMm45557DD8/P8PPz88YMmSI8ccff9i0/fzzz43WrVsb3t7eRkhIiDF37lxj5syZhoeHh3H69GnDMAzjlVdeMcLCwoyGDRsa3t7eRosWLYxRo0YZf/75p817paSkGFFRUcbll19u+Pj4GHXq1DHat29vPPjgg9ZVrZYvX24Axs6dO63nLVu2zACMH3/80eZ17jaGYRg7d+40ACM2NrbEn1ucJUsMIzAw90pVhlGvnrnl3hcYaLY1/vnHMJo2NQwwmtetW+wqVjkrAxa0UtXp06eNhx56yGjcuLFRvXp1o127dkZMTEyp25W0bUVU1a/xsqjqv536x4L7x5zV+mxX7Lu4b8mSAn7MF180G9WubRh//13g7928eXP1j+Wsql/jIiIizmAxDNu1Y0TskZqair+/PykpKfj5+bk6HKkgsrJg3TpITobdu2HatLyrV5kjCAAWL4bIY2/BvfdCw4bw11/g61vuMVdVusZLT7+dFCY21ly1L3dx9KAgmDMHIiMLOCErC3r0gA0bYOBAc4ipuJyucREREcdTckpKRf8wk7LIyoLg4IJWr7qoQQOY89/zDH7iSmoc/BOefdac6iflQtd46em3k6LkTtJbpzJ7Fr6fX3+Fdu3MBl9/XeYVTKXsdI2LiIg4ngqii0i5K3hZdVtHj8Ltd1VjzMHpAJx75gU4ebIcohMRcR5PTwgPh2HDzEdPT3NEVXAwRETA8OHmY3CwuZ+QEHPlUjCHXZ0/77LYRURERJxFySkRKXfJyfa3/Zjb+Ik2VE8/xe9jXnReUCIiLhAbay4YkTdhn5Rk7o+NxZwDXb8+/PYbvPaaK8IUERERcSolp0Sk3JVkVfRsPJnMTACCls4l6+BhJ0UlIlK+srLMwVAFFVjI2TdxImTVvgSeecbcMXWqObRUREREpBJRckpEyl3Osuo5xc+L8xn/4ge64Gukk/zQc84NTkSknBQ3xdkwYP9+sx2jR0NoKKSkwJNPlluMIiIiIuVBySkRKXeenjB3rvncvgSVhScxRw00Wf467NvntNhERMqLvVOck5Ox7TjfeQe2b3daXCIiIiLlTckpEXGJyEhYvBiaNrWv/bf04jsi8Mw8B08/7dzgRETKgb1TnK3twsLgttvMIVWFzQcUERERqYCUnBIRl4mMhL17IS4OFiyABg0KH0llsVh4ueGFmivR0fDHH+UVpoiIUxQ3xdligaAgs53VCy9AzZqwfj18+WW5xCkiIiLibEpOiYhL5Syrfvvt8MYb5r68N2o5r+98vTvcdJNZRXjq1HKNU0TE0Yqa4pzzes4cs51VUBCMG2c+nz5do6dERESkUlBySkTcRmFT/QIDzf2RkcBMc+U+Pv4Yfvyx3GMUEXEku/q9vB5+2Bw9tWULfPVVucQpIiIi4kwWw9Cf3KTkUlNT8ff3JyUlBT8/P1eHI5VMVpa5OlVysllrJSwsz8iBoUPhk0/g7rvh3XddFmdlpmu89PTbSWkU1u8V2h8+/DDMng1du8LGjfYvfyplpmtcRETE8ZScklLRP8zEpTZuhKuvBh8fcx32evVcHVGlo2u89PTbiaPExpp1zw8cuLivaVMYOxbaNjzMvyYE43nurDl6qm9f1wVaxegaFxERcTxN6xORCiUrC+LPduNEcCicPUv2Oxo5JSKVT2wsDBlim5gCSEoyS+5F3t+Il8/dB8DxCao9JSIiIhWbklMiUmHExkJwMERcZ+HhveMBOPDka8R+muXawEREHCgryxwxVVy+6QUe5Qw+1Nu1kXXTvi2f4EREREScQMkpEakQ8o4i+JjbOEEdmmXt5b1bVxIb69r4REQcZd26/COmCnKIJrzFWAC8Z00nK1Ojp0RERKRiUnJKRNxeQaMIzlCT+YwGYBzzmDjRbCciUtElJ9vf9nke4yzedDm3np9ejnNeUCIiIiJOpOSUiLi9wkYRvM79ZGOhH6vw3r+bdevKPzYREUdr0sT+tskE8Db3ABDw9nQnRSQiIiLiXEpOubm1a9cyYMAAAgICsFgsLFu2rMj2sbGx9O7dmwYNGuDn50f37t1ZtWpVvnZLliwhJCQEb29vQkJCWLp0qZO+gUjZFTaKIJFL+ZIbALif10s02kBExF2FhUFgIFgs9rV/nsfIoDoNf18L8fFOjU1ERETEGZSccnPp6em0b9+eefPm2dV+7dq19O7dmy+//JJt27YRERHBgAED2LFjh7XNxo0bGTp0KCNGjGDnzp2MGDGCW2+9lR9++MFZX0OkTIoaRfAq4wAYxbs0vSS9nCISEXEeT0+YO9d8bk+C6qAlkI9rjTFfTNfoKREREal4lJxyc/3792fmzJlERkba1X7OnDk8+uijdO7cmVatWvHss8/SqlUrVqxYYdOmd+/eREVF0bp1a6KioujVqxdz5sxx0rcQKZuiRhGsoi97aMklpHDtvoXlH5y4jEaWSmUWGQmLF0PTpkW3y+kXG85+HKpVM0dOrV3r9PhEREREHEnJqUouOzub06dPU7duXeu+jRs30qdPH5t2ffv2ZcOGDYW+T0ZGBqmpqTabSHkpchSBxYPXeQAAj9fmFb/2ulQaGlkqlV1kJOzdC3FxsHChOSgqMNC2TWCgmcTqPzYIRpuLRPD00+Ueq4iIiEhZWAxDd3IVhcViYenSpQwaNMjuc/773/8ya9YsfvvtNxo2bAhA9erViY6OZvjw4dZ2Cxcu5O677yYjI6PA95k2bRrTC5gqkJKSgp+fX8m+iEgpxcaaq/blLo4eFASvzjzJgPuawpkzZvX0a691XZCVRGpqKv7+/hXmGi9N/whw1VVXMXToUKZMmQLA0KFDSU1NZeXKldY2/fr1o06dOsTExNj1nhXtt5OKJSvL7OaSk80pz2FhZgIfgL//xmjVCsv583wzdT3Vwq+xPS4OoWtcRETE8TRyqhKLiYlh2rRpLFq0yJqYymHJM/zEMIx8+3KLiooiJSXFuu3fv98pMYsUJe8ogrg4SEyEAXfWgdtvB+DIlHnExJgzW7KyXBquuDmNLJWKyNMTwsNh2DDzMXfiKXZbcxZWvwuA89OfISICgoPNxL6IiIiIO1NyqpJatGgRo0eP5pNPPuH666+3Oda4cWMOHTpks+/IkSM0atSo0Pfz9vbGz8/PZhNxhcJuzL5tbRZGrxO3hEnDk3VTJsWaPXs26enp3HrrrdZ9hw4dytcXNmrUKF+fmdtzzz2Hv7+/dQsKCnJazCKFiY2FIUNgSvpjZGPhBlbSkj0kJZn71ReKiIiIO1NyqhKKiYnhrrvuYuHChdx44435jnfv3p1vvvnGZt/XX3/N1VdfXV4hijhUbCz0fqQD67mGamRyD28D6KZMCqWRpVKZZGWZU54NA/6iJSvpD8D9vG4twzdxokaTioiIiPtScsrNpaWlkZCQQEJCAgCJiYkkJCSwb98+wLwpuvPOO63tY2JiuPPOO5k9ezbdunXj0KFDHDp0iJSUFGubCRMm8PXXX/P888/z+++/8/zzz7N69WomTpxYnl9NxCFy35S9wX0AjOBDwNBNmRRII0ulslm3zrYW36uYI0lH8S41SccwYP9+s52IiIiIO1Jyys1t3bqV0NBQQkNDAZg0aRKhoaHW4r3JycnWRBXAm2++SWZmJuPGjaNJkybWbcKECdY2V199NR9//DHvvfce7dq1Izo6mkWLFtG1a9fy/XIiDpD7pmwZg0inJq3YQxc2A+imTGxoZKlURsnJtq+/oh9/cil1OMVwFhbaTkRERMRdeLk6AClaeHg4RS2oGB0dbfM6Pj7ervcdMmQIQ4YMKUNkIu4h981WOrVYymDu4CNu5yM207XAdlI5pKWlsWfPHuvrnJGldevWpVmzZkRFRZGUlMQHH3wAXBxZOnfuXOvIUoAaNWrg7+8PmCNLe/TowfPPP8/AgQNZvnw5q1evZv369eX/BUXs1KSJ7WsDD17jAWbzMON4lXcYA1jytRMRERFxFxo5JVJG//zzD9OnT6d169b4+PhQr149hg0bxsmTJ536uWlpaUycOJGAgAB8fHzo0KEDH3/8cbHnfffdd4waNYrWrVvj6+tL06ZNGThwINu2bbNpd9ddd2GxWArdNm3aVOhnvPPOO1gsFmrVqlXm71mcvDdbH2Gu2ncbH+PF+ULbScWnkaXur7L2jwA7duxg0KBBBAQEULNmTVq3bs3TTz/NP//8U+r3LK2wMAgMhNyl0d7jbv6hBh3YybV8T1CQ2U5ERETEHVmMoobliBQiNTUVf39/UlJSqnR9FcMwGDRoEGvXrmXKlCl06NCBH3/8kX//+9888cQTzJw502mf3adPH7Zs2cKsWbO4/PLLWbhwIe+88w4fffQRw4cPL/S8W265hePHj3PLLbcQEhLC0aNHmT17Nlu3bmXVqlVcd911APz5558cPXo03/kDBgzA29ubv//+G8/ca5hfkJSUxFVXXYWvry8pKSmkpaU57ksXICvLXJUvKcmcwudJJgcJoCFH6c+XrLL0JzAQEhNtl1yXoukaLz39dqbK3D/++uuvdOzYkSuuuIInnniC+vXrs3btWmbOnMmNN97I8uXLS/yeZZWzWh9grbf3FvdwD+8Qw214L4khMtIhH1Xl6RoXERFxAkOkFFJSUgzASElJcXUoLhUXF2cAxqeffmqzv1GjRsbEiROd9rlffPGFARgLFy602d+7d28jICDAyMzMLPTcw4cP59t3+vRpo1GjRkavXr2K/Nz4+HgDMCZPnlxom5tuuskYMGCAMXLkSMPX17eYb+IYS5YYhsVibmAYc3nQMMBYwHDDYjGPS8noGi89/Xamytw/PvnkkwZg7Nmzx6bt2LFjDcA4ceJEid/TEZYsMYzAQLMfBMNozw7DACPL08vI3H/QiIszjIULDSMuzjCK+BmkGLrGRUREHE/T+kTK4NNPP6VOnToMHjzYum/t2rUcPnzYYX8NL8jSpUupVasWt9xyi83+u+++m4MHD/LDDz8Uem7Dhg3z7atVqxYhISHs37+/yM+dP38+FouFUaNGFXh8wYIFrFmzhtdee82Ob+E4kZGweDE0bWq+zpnaN9iyjKUfpmm0gIgLVOb+sVq1agDWWmU5LrnkEjw8PKhevXqJ39MRIiNh716Ii4OFC2FOXAeMq6/BIyuTOVe9RUQEDB8OERHmiNPYWId+vIiIiEipKTklUgYbNmyw1qI5ePAg7733HjfffDO9evXipptuytfeMAwyMzPt2ory888/c+WVV+LlZbumQbt27azHSyIlJYXt27dz1VVXFdlm8eLF9OrVixYtWuQ7fuTIESZOnMisWbMIDAws0ec7Qu6bsokfdeGfppdR0/iHAdnLiY+HmBiIjzenAYqI81Xm/nHkyJFccskl3H///fz111+cPn2azz//nDfffJNx48bh6+tb4vd0FE9PCA+HYcPMxy1dxwMwLPVNmzp8SUnmNEAlqERERMQdKDklUkpnz57l559/pmvXrjz77LM0bdqUUaNGUbNmTaKjo7Hkrkx7wZo1a6hWrZpd2969ewv97OPHj1O3bt18+3P2HT9+vETfZdy4caSnp/Pkk08W2iYmJoYzZ84wevToAo8/8MADXHHFFdx///0l+mxHst6UDbdQc4w5emrNPQs0WkCknFX2/jE4OJiNGzfy888/07JlS/z8/BgwYAAjR45k7ty5pXpPZ8jKgts+ieQQjQggmcEstR7LqUs1caKS9iIiIuJ6XsU3EZGCbN++nczMTLp06ULr1q3p2rUrmzZtYs6cOfTo0YMff/wx32p1HTt2ZMuWLXa9f0BAQJHHC7q5s+dYXk899RQfffQRr7zyCh07diy03fz586lXr57NFJ0cS5YsYcWKFezYsaNEn+1Mq+rfTl+mE5bxDQ05zBEaARdHCyxejKb7iThJZe8f9+7dy4ABA2jUqBGLFy+mQYMG/PDDD8ycOZO0tDTmz59f4vd0hnXrIDGpOm9yL1N5mvHM41NutR43DNi/32wXHu7UUERERESKpOSUSClt3rwZgC5dulC/fn0uvfRS+vTpw+WXX86wYcPYtGkT119/vc05tWrVokOHDna9f94pKbnVq1evwL/+nzhxAqDAUQMFmT59OjNnzuSZZ55h/Pjxhbb78ccf2bp1KxMmTMDb29vmWFpaGuPGjePBBx8kICCAU6dOAXDu3DkATp06RbVq1Yqd5uJIWVkw5vlWLKYLXdnMUBbxCg8B5s2YxWKOFhg4UCv4iThDZe8fH3/8cVJTU0lISLD2bT169KB+/fqMGjWKO++8k549e5boPZ0hOdl8fIuxPMkz9GAdbfmRn2hXYDsRERERV9G0PpFS2rx5M5deein169cv8HhBf9l31LSVtm3b8ttvv+WrvfLTTz8B0KZNm2Ljnz59OtOmTWPatGk88cQTRbbNGQUwZsyYfMeOHTvG4cOHmT17NnXq1LFuMTExpKenU6dOHW6//fZi43GkdevgwAFYwB0A3M5HNsdzjxYQEcer7P1jQkICISEh+ZLunTt3Bgqua1WSPtdRmjQxHw/SlFjMoaLjeLXQdiIiIiKuopFTIqW0efNmmuT5F71hGLzzzju0adOGkJCQfOc4atrK4MGDefvtt1myZAlDhw617n///fcJCAiwFiEuzIwZM5g2bRqTJ09m6tSpRbbNyMhgwYIFdOnSpcCbusaNGxMXF5dv/6xZs1izZg0rV64s9AbVWXJGASxiKC/xb7qymcvYzR5aFdhORByrsvePAQEB/Pzzz6SlpdlMT9y4cSNAvkUhStLnOlJYGAQGmtOZ5xnjuZVPuZ2P+A+zSacWFot5PCys3EISERERKZghUgopKSkGYKSkpLg6FJc4fvy4ARiAMXr0aGP16tXGZ599ZgwaNMjw9vY2NmzY4PQYevfubdSpU8d46623jO+++8645557DMBYsGCBtU18fLzh6elpTJ8+3brvxRdfNACjX79+xsaNG/NteX388ccGYLz11lslim/kyJGGr69v6b9gGcTFGYY5PsowvqSfYYAxlanWfTlbXJxLwqsQqvo1XhZV/berCv3j8uXLDYvFYnTr1s1YtGiR8e233xrPPPOMUatWLSMkJMTIyMgo8Xs6y5IlhmGxGIaFbGMXrQwDjDuJNvdZzONSMlX9GhcREXEGJaekVKr6P8xWrlxpAMadd95pNG3a1KhWrZrRrFkzY8iQIUZCQkK5xHD69GnjoYceMho3bmxUr17daNeunRETE2PTJi4uzgCMqVOnWvf17NnTeuNY0JZX7969DV9fXyM1NbVE8bkyOZWZaRiBgeaN13AWGAYYu2hlQLYB5v6gILOdFKyqX+NlUdV/u6rSP3733XdGnz59jMaNGxs1atQwLr/8cuM///mPcezYMZt2Je1znWHJErNPfIKZhgHGd4QbQUFKTJVWVb/GRUREnMFiGDmLCYvYLzU1FX9/f1JSUvDz83N1OOXu6aefZubMmaSmpuLj4+PqcKQAsbHmqny1jNMcoQE+ZHAVP/Ob5SpAq/UVp6pf42VR1X879Y/uKSsLNi/eR7dhwVgMg6zdf+F5WQtXh1UhVfVrXERExBlUEF2kFDZv3kzbtm114+XGIiPNBJR/YG1WY64KNpilBAYqMSXiTOof3ZOnJ3Qf2gxLr17m64UfkpUF8fEQE2M+ZmW5NEQRERGpwpScEimFLVu20KVLF1eHIcWIjIS9e+GyhwcD8FirpSQmKjEl4kzqH93cyJEApL32PsHNDSIiYPhwiIiA4GBz1KmIiIhIedO0PikVDWmXCuXoUWjcGLKzzWxV8+aujsjt6RovPf124tbS0znfoAnVzpwmjLWs5+JSfRaL+ajRpUXTNS4iIuJ4GjklIpVfgwZw7bUAZMcu0zQWEamysnx8WWK5BYC7iLY5lvPnyokT1TeKiIhI+VJySkSqhsHm1L4fHl+qaSwiUmWtWwev/nMXALfwKTVJtzluGLB/v9lOREREpLwoOSUiVcJXPoMA6HJuHfU5at2flGSu6qcElYhUBcnJsJ5r+ZNL8eM0g1laaDsRERGR8qLklIhUellZcM8zweygA55kM4AV1mOaxiIiVUmTJgAW3scsjD6S94toJyIiIlI+lJwSkUpv3To4cACWYk7tyztSQNNYRKSqCAuDwED4kDsB6MW3BLLfetxigaAgs52IiIhIeVFySkQqvZzpKTnJqd58Qy1OF9pORKSy8vSEuXPhb0swcYTjgcEIPgQurtY3Z47ZTkRERKS8KDklIpVezvSUn2nDHlriQwb9+KrQdiIilVlkJCxeDJ/VuQvIWbXPIDDQ3B8Z6croREREpCpSckpEKr2caSwWi8U6emoQy6zHNY1FRKqayEh4MfFmsnx8uZzdbHv1BxITlZgSERER11BySkQqvZxpLADLLiSnbuQLqnFO01hEpMry9K+FZ+RAAP5v9yI8Pc2FIeLjISbGfNRCESIiIlIelJwSkSohZxrL/qbdSKYxl5BCBHGaxiIiVdttt5mPn3xC7OJsgoMhIgKGDzcfg4MhNtaVAYqIiEhVoOSUiFQZkZGQ+LcHxo0DAJgf+aWmsYhI1danD/j7w8GDzL1lPQcO2B5OSoIhQ5SgEhEREedSckpEqhRPTwgY3R+AwJ+/0lQ+EanavL3JHmxm6Ifycb7DhmE+TpyoKX4iIiLiPEpOiUjVc911Zpbqjz8gMdHV0YiIuNRPIebUviEsxpPMfMcNA/bvh3XryjsyERERqSqUnBKRqsffH66+2ny+apVrYxERcbHfmlzHUerTkKNEEFdou+TkcgxKREREqhQlp0SkaurXz3z86ivXxiEi4mKNA71YzBAAbitgal+OJk3KKyIRERGpapScEpGqKSc59e23cO6ca2MREXGhsDD4rv5QACKJpRq2faLFAkFBZjsRERERZ1BySkSqpg4doEEDSEuDjRtdHY2IiMt4esKw18I4SBPqcIo+fG09ZrGYj3PmoAUkRERExGmUnBKRqsnDA/r2NZ9rap+IVHGRt3jyzw23ALZT+wIDYfFiiIx0VWQiIiJSFSg5JSJVl+pOiYhYXTbZXLXvthrLWRR9hrg4c0FTJaZERETE2ZScEpGqq3dv8zEhAQ4dcmkoIiIu160bNGuG15k0bq31JeHhmsonIiIi5UPJKQc6f/48+/fvZ9euXZw4ccIh77l27VoGDBhAQEAAFouFZcuWFdk+OTmZ4cOHc8UVV+Dh4cHEiRPztYmOjsZiseTbzp4965CYRSqMhg2hY0fz+ddfF91WyszRfaT6RxEHs1hgqFkYnY8LX7VPRERExNGUnCqjtLQ03nzzTcLDw/H39yc4OJiQkBAaNGhA8+bNueeee9iyZUup3z89PZ327dszb948u9pnZGTQoEEDnnzySdq3b19oOz8/P5KTk202Hx+fUscpUmFpap9TObOPVP8o4gS3mHWnWLkSzpxxbSwiIiJSZXi5OoCK7KWXXuKZZ54hODiYf/3rXzz++OM0bdqUGjVqcOLECX7++WfWrVtH79696datG6+88gqtWrUq0Wf079+f/v37290+ODiYuXPnAvDuu+8W2s5isdC4ceMSxSJSKfXrB888Y46cysrSHBYHcnYfqf5RxAk6dTKroB84AKtXw4ABro5IREREqgAlp8pgw4YNxMXF0bZt2wKPd+nShVGjRvHGG28wf/581qxZU+LklLOkpaXRvHlzsrKy6NChAzNmzCA0NLTQ9hkZGWRkZFhfp6amlkeYIs7XtSv4+cHx47B9O3Tu7OqIKo2K2keqf5QqzWKBQYNg3jxYulTJKRERESkXmtZXBp9++mmhN125eXt788ADDzBmzJhyiKp4rVu3Jjo6ms8++4yYmBh8fHy45ppr2L17d6HnPPfcc/j7+1u3oKCgcoxYxImqVYPrrzeff/UVWVkQHw8xMeZjVpYrg6vYKmIfqf5RBBg82Hz87DPIzHRtLCIiIlIlKDnlIJ9//jnZ2dmuDsMu3bp144477qB9+/aEhYXxySefcPnll/PKK68Uek5UVBQpKSnWbf/+/eUYsYiTXag7dfyjrwgOhogIGD7cfAwOhthYl0ZXKVSUPlL9owjQowfUrWuOKP3+e1dHIyIiIlWAklMOMnDgQI4dO+bqMErFw8ODzp07FzkywNvbGz8/P5tNpNLo2xeAS3ZtIu3ASZtDSUkwZIgSVGVVUftI9Y9SJXl5XZzOt3Spa2MRERGRKkHJKQcxDMPVIZSaYRgkJCTQpEkTV4ci4hJZTZvxh9eVeJJNL761OZZzaU+cqCl+ZVFR+0j1j1JlDRpkPi5derEjFBEREXESJaccKCEhgfT0dJt9SUlJZforelpaGgkJCSQkJACQmJhIQkIC+/btA8zpJHfeeWe+OBISEkhLS+Po0aMkJCTw66+/Wo9Pnz6dVatW8ddff5GQkMDo0aNJSEjgvvvuK3WcIhXZunXweaY5ta8fX+U7bhiwf7/ZTkrP0X2k+kcRJ+rTB2rUgH374MI1JiIiIuIsWq3Pgfr374/FYiE4OJh27dpxxRVX8Pfff3PJJZeU+j23bt1KRESE9fWkSZMAGDlyJNHR0SQnJ1tvxHLkXlVq27ZtLFy4kObNm7N3714ATp06xdixYzl06BD+/v6Ehoaydu1aunTpUuo4RSqy5GT4in5M4qULySkDsBTYTkrP0X2k+kcRJ6pZ06zHt3SpuYWGkpVlJumTk6FJEwgLA09PVwcqIiIilYHFqKhzLdyMh4cHu3fv5siRI/z000/8+OOP7N27l+zsbB566CH6XSi4XFmkpqbi7+9PSkqK6qtIhRcfD/0jznCCutTgLG34iV9ok69dXByEh5d7eC7h6Gu8KvWR6h+l0vjwQ7jzTmjThtjpPzFhAhw4cPFwYCDMnQuRka4L0RV0jYuIiDieklMO4uHhwaFDh2jYsKGrQykX+oeZVCZZWeaqfG8d6E9/vuI/vMj/+I/1uMVi3oQlJladUQLOSE5VlT5S/aNUGidPQsOGkJlJK3azh8tsDlsuDDBdvLhqJah0jYuIiDieak45yIABA6hWrZqrwxCRUvD0NP/6v4r8dadybr7mzKk6iSlnUB8pUgHVqYPRMxyAQeRftU8LRoiIiIijKDnlIMuXL6dOnTquDkNESikyEm6Y2xeAHqylJmbh7sDAqjcqwBnUR4pUTLvbDAZgEMsKPK4FI0RERMQRlJwqg7yFdouTlJTkpEhExBH6PHgFRvPmeHOOLx5ZQ1ycOZVPianSUR8pUvH92mogAN3ZSCMOFdpOC0aIiIhIWSg5VQadO3fmnnvuYfPmzYW2SUlJ4e2336ZNmzbExsaWY3QiUmIWC5YLhbnDz35FeLim8pWF+kiRiu+Sq5ryA13wwGAgywtt16RJOQYlIiIilY6XqwOoyH777TeeffZZ+vXrR7Vq1ejUqRMBAQH4+Phw8uRJfv31V3755Rc6derEf//7X/r37+/qkEWkOP36wZtvwldfFd9WiqQ+UqTiCwuDF/wG0zV1M4NZylvca3M8Z8GIsDAXBSgiIiKVglbrc4CzZ8/y5Zdfsm7dOvbu3cuZM2eoX78+oaGh9O3blzZt8i9JX9FppRqptFJToW5ds7rv3r3QvLmrI3IJR17jVa2PVP8olc3Xr+yiz0OtOUc1GnCUVPwBrdana1xERMRxlJySUtE/zKRS694dNm2C996Du+5ydTQuoWu89PTbSWWUGhSC34HfGMZCPmYYAEFB5kqmVSkxBbrGRUREnEE1p0RE8oqIMB/j4lwbh4iIm/C701y1b27PpSxciBaMEBEREYdScsoJzpw5U+CqU7/88osLohGRErvuOvPxu+/MddLFodRHilRAgwYB0HDbSoYNPqsFI0RERMShlJxysMWLF3P55Zdzww030K5dO3744QfrsREjRrgwMhGx29VXQ7VqcOAA/Pmnq6OpVNRHilRQnTqZlc/T0mD1aldHIyIiIpWMklMONnPmTLZv387OnTt59913GTVqFAsXLgRA5b1EKoiaNc26U2COnhKHUR8pUkFZLNbRUyxd6tJQREREpPLxcnUAlc358+dp0KABAJ06dWLt2rVERkayZ88eLDnL2oiI+4uIgLVrzcIqY8e6OppKQ32kSAU2eDDMmweffWauaKp5fSIiIuIgGjnlYA0bNuTHH3+0vq5Xrx7ffPMNv/32m81+EXFzOXWn4uJUd8qB1EeKVGA9ekDdunDsGHz/vaujERERkUpEySkH+emnn8jMzOTDDz+kUaNGNseqV69OTEwMa9ascVF0IlJiXbuCjw8cPgy//UZWFsTHQ0yM+ZiV5eoAKxb1kSKVgJcX3HST+XzFCtfGIiIiIpWKxVCRD4fw8PCgevXqhISE0L59ezp06GB9vOSSS1wdnsOlpqbi7+9PSkoKfn5+rg5HxDl694bVq0kY/QoDVo3nwIGLhwIDYe7cyruMuqOv8arUR6p/lErt00/h1lvhiivg999dHY1L6BoXERFxPI2ccpD169dTt25dWrRoQUZGBtHR0Vx33XXUq1ePK664gqeeeopTp065OkwRKYmICAD+nB9nk5gCSEqCIUMgNtYFcVVA6iNFKom+fc3VTHftgt27rbs1ulRERETKQskpBxk/fjyvvfYaS5YsYeHChezYsYO4uDguvfRSRo4cybp16wgNDeXo0aOuDlVE7JTV06w7FU48FrJtjuWMOZ04UTdh9lAfKVJJ+PlBz57m888/B8wkfXCwmc8fPtx8DA5W8l5ERETsp+SUg/z++++EhITY7OvZsycvvfQS27dvJy4ujk6dOvHEE0+4KEIRKan1ZzpymlrU4wTtyF+s2zBg/35Yt84FwVUw6iNFKpFcdadiY81RpBpdKiIiImWh5JSDdO7cmQULFuTbf9VVV/H1119jsVh45JFHWL16tQuiE5HSOHi0GmvpAcB1fFdou+Tk8oqo4lIfKVKJDBgAgLFuHU89eKrABU01ulRERERKQskpB3nttdeYM2cOw4cP5/cLBULPnTvHSy+9RN26dQFo0KABhw8fdmWYIlICTZpAHGbdqQjiimwnRVMfKVKJXHophIRgycykzcFVhTbT6FIRERGxl5JTDnLVVVexceNGkpOTCQkJoUaNGvj6+vL2228za9YsAHbs2EFAQICLIxURe4WFwS8NzbpTPVmDJ5k2xy0WCAoy20nR1EeKVDIXpvYNYEWxTTW6VERERIrj5eoAKpOrrrqKuLg4/v77b3bu3ImnpycdO3akcePGgDkqIOcmTETcn6cn3DOvPSdvvYQ6nOL/2M4WugBmYgpgzhyznRRPfaRIJTJgALzwAjfwJZ5kklXEPyk1ulRERESKYzGMgioFiBQtNTUVf39/UlJS8PPzc3U4Ik51sOtgAjYv43Ge43keB8wRU3PmQGSka2NzFl3jpaffTqqEzEyMRo2wnDhBD9ayjvxDSC0WCAyExMTKlcTXNS4iIuJ4mtYnIlKMgNvNulOPdopj4UKIizNvtiprYkpEpFheXlhuuAEwp/bljCbNodGlIiIiUhJKTomIFOc6s+5U3V/XM+zmc4SH62ZLRCRn1b57m66gaVPbQ4GBsHixkvgiIiJiH9WcEhEpzlVXQYMGcPQobN4M117r6ohERFyvb1/w8sIv6Xf2/r6HdcmXkZxs1pgKC1MSX0REROynkVMiIsWxWCDCnNrHd9+5NhYREXfh7w89egDgufJzwsNh2DA0ulRERERKTMkpERF75CSn4uJcG4eIiDu5MLWPFStcG4eIiIhUaEpOiYjY40LdKTZsgDNnXBuLiIi7uOkm83HtWkhJcW0sIiIiUmEpOSUiYo9WrSAgAM6dg40bAcjKgvh4iIkxH7OyXBqhiEj5u+wyaN0aMjNh1SqbQ+ojRURExF5KTomI2CN33an4eGJjITjY3DV8uPkYHAyxsa4MUkTEBXJGT+Wa2qc+UkREREpCySkREXuFhwNwbHE8Q4bAgQO2h5OSYMgQ3XyJSBWTU3fqyy8hK4vYWNRHioiISIkoOSUiYq8Lyanav/2Aj/FPvsOGYT5OnKjpKyJShVx9NdSpAydOkLV+IxMmXOwPc1MfKSIiIoVRckpExF4tW5JRvynenKMbmwpsYhiwfz+sW1fOsVVBa9euZcCAAQQEBGCxWFi2bFmR7ZOTkxk+fDhXXHEFHh4eTJw4scB2S5YsISQkBG9vb0JCQli6dKnjgxepTLy8oH9/AJLeWJFvxFRu6iNFRESkIEpOiYjYy2Ih+YpwAMKJL7JpcrLzw6nq0tPTad++PfPmzbOrfUZGBg0aNODJJ5+kffv2BbbZuHEjQ4cOZcSIEezcuZMRI0Zw66238sMPPzgydJHK58LUPv91n9vVXH2kiIiI5KbklJvTyAAR95LRPRwoPjnVpInzY6nq+vfvz8yZM4mMjLSrfXBwMHPnzuXOO+/E39+/wDZz5syhd+/eREVF0bp1a6KioujVqxdz5sxxYOQilVDfvuDpiX/Sr7Tgr2Kbq48UERGR3JSccnMaGSDiXi4bEw5AV36gBvnrTlksEBQEYWHlHJg4xMaNG+nTp4/Nvr59+7JhwwYXRSRSQdSpY+34br/kCyyWgpupjxQREZGCKDnl5jQyQMS9eF7ekjN1zbpT3fPUncq5GZszBzw9yz82KbtDhw7RqFEjm32NGjXi0KFDhZ6TkZFBamqqzSZSJd10EwDjm68AyJegUh8pIiIihVFyqgoqzcgA3XyJXGCxUKN/OAADasfbHAoMhMWLwc5csrgpS547asMw8u3L7bnnnsPf39+6BQUFOTtEEfd0oe5Uo1/jWfbhaZo2tT2sPlJEREQKo+RUFVSakQG6+RLJJTwcgAnt44mLg4ULIS4OEhN101XRNW7cOF9feOTIkXx9Zm5RUVGkpKRYt/379zs7TBH3dPnl0KoVnD/Pv3y+Zu9e1EeKiIiIXZScqqJKOjJAN18iuVxITlk2/0B4l38YNszcpWkqFV/37t355ptvbPZ9/fXXXH311YWe4+3tjZ+fn80mUmVdmNrH55/j6Wn2jeojRUREpDherg5Ayl9pRgZ4e3vj7e3t7NBEKoaWLaFpU0hKgk2b4LrrXB1RlZSWlsaePXusrxMTE0lISKBu3bo0a9aMqKgokpKS+OCDD6xtEhISrOcePXqUhIQEqlevTkhICAATJkygR48ePP/88wwcOJDly5ezevVq1q9fX67fTaTCGjAAXnoJvvgCsrPBQ38HFRERkeLpXwxVUGlGBohILhaLdfQU8fGujKRK27p1K6GhoYSGhgIwadIkQkNDmTJlCgDJycns27fP5pyc9tu2bWPhwoWEhoZyww03WI9fffXVfPzxx7z33nu0a9eO6OhoFi1aRNeuXcvvi4lUZNdeC35+cPQobN7s6mhERESkgtDIKTenkQEibio8HD76KF9yKisL1q2D5GRo0sRcLl1TWZwjPDwcwzAKPR4dHZ1vX1HtcwwZMoQhQ4aUJTSRqqtaNejXDz75BD7/HLp1c3VEIiIiUgFYDHv+pS4uEx8fT0RERL79I0eOJDo6mrvuuou9e/cSn+sGuaDaUc2bN2fv3r3W14sXL2by5Mn89ddftGzZkmeeeYbIElQpTU1Nxd/fn5SUFNVXkappzx6z8G/16nDyJNSsSWwsTJgABw5cbBYYCHPnVrwiwLrGS0+/nVR5CxbAiBHQvj1c+IMZVJ7kva5xERERx1NySkpF/zCTKs8wICjIrDv17bfEnrqOIUPM3bnl5Ior2vLpusZLT7+dVHnHj0PDhmbNqb//hmbNlLwXERGRIqnmlIhIaeSqO5X9XTwTJuRPTMHFfRMnmqMGREQqvXr1IKeO5RdfEBsLQ4bYJqbAzO0PGQKxseUfooiIiLgXJadERErrQnIqdUV8vpuu3AwD9u83p7OIiFQJN90EgPHZCiXvRUREpFhKTomIlNaF5FTtX3+gBv8U2zw52cnxiIi4i5zk1LffceJAeqHNlLwXERERUHJKRKT0WraEpk3xzDxHNzYV27xJk3KISUTEHYSEQIsWeJzPoBffFttcyXsREZGqTckpEZHSylV3amDtOApYKNPaLCjIXJlKRKRKsFiso6cGsKLY5krei4iIVG1KTomIlEVEBAC3N40DyJegynk9Z07FXDJdRKTULiSn/uXxOR5kF9hEyXsREREBJadERMrmuusAqL/nB5Z+mEbTpraHAwNh8eKKt1S6iEiZhYeDnx+Nsg/Rhc1K3ouIiEihlJwSESmLFi0gOBgyMxlYbz1790JcHCxcaD4mJioxJSJVVPXq0L8/ANGDlyt5LyIiIoVSckpEpKwujJ7iu+/w9DQHCwwbZj5qNICIVGkDBwJwxe/LlbwXERGRQnm5OgARkQovIgLefRe++87VkYiIuJf+/cHLC377Dc+/dhMe3srVEYmIiIgb0sgpEZGyulAUnR074ORJ18YiIuJOLrnEuqopy5e7MhIRERFxY0pOiYiUVdOmcMUVkJ0Na9e6OhoREfdyYWqfklMiIiJSGCWnREQcIVfdKRERyeVf/zIfN2yAo0ddG4uIiIi4JSWnREQcQckpEZGCNWsGoaHm6NLPP3d1NCIiIuKGlJwSEXGEnJoqP/8MR464NBQREbeTM7Vv2TKXhiEiIiLuSckpERFHqF8f2rUzn8fHuzQUERG3k5Oc+uYb+Ocf18YiIiIibkfJKRERR9HUPhGRgrVvD82bw5kzZoJKREREJBclp0REHEXJKRGRglksFwuja9U+ERERyUPJKRERR+nRAzw8YPdu2L/f1dGIiLiXnKl9n38OWVmujUVERETcipJTIiKO4u8PHTuaz+PiXBuLiIi76dEDLrkEjh6FDRtcHY2IiIi4ESWnREQcKWdqn5JTIiK2qlWDm24yny9e7NpYRERExK0oOSUi4kg5yalvvwXDcG0sIiLuZuhQ8/GTTzS1T0RERKyUnBIRcaRrroHq1c2aU7t2uToaERH30qePObXv0CFYt87V0YiIiIibUHJKRMSRfH2hZ0/z+cqVro1FRMTdVK8OkZHm848/dm0sIiIi4jaUnBIRcbQbbjAfv/zStXGIiLij224zHxcvhvPnXRuLiIiIuAUlp0REHK1/f/NxzRpIS3NtLCIi7iYiAho0gOPH4bvvXB2NiIiIuAElp0REHO3yy+HSS80RAd9+6+poRETci5cXDBliPtfUPhEREUHJKRERx7NYNLVPRKQoOav2LV0KGRmujUVERERcTskpERFnyElOrVwJhuHaWERE3M2110JAAKSkwKpVro5GREREXEzJKRERZwgPBx8f2L8ffvnF1dGIiLgXT0+49Vbz+aJFro1FREREXE7JKRERZ6hRA667znyuqX0iIvnlTO1bvhz++ce1sYiIiIhLKTklIuIsOav2KTklIpJf167QvDmkp6ufFBERqeKUnBIRcZaculPr15t1VURE5CKL5eLoKa3aJyIiUqUpOSUi4iyXXgpXXAFZWfDNN66OptJZu3YtAwYMICAgAIvFwrJly4o9Z82aNXTs2BEfHx8uvfRS3njjDZvj0dHRWCyWfNvZs2ed9C1EqrjbbjMfv/gCTp92bSwiIiLiMkpOiYg4U+5V+8Sh0tPTad++PfPmzbOrfWJiIjfccANhYWHs2LGDJ554goceeoglS5bYtPPz8yM5Odlm8/HxccZXEJEOHaBVKzh7Fj77zNXRiIiIiIt4uToAEZFK7YYb4KWXzHoqhmFOYxGH6N+/P/1z6nrZ4Y033qBZs2bMmTMHgCuvvJKtW7fy4osvcvPNN1vbWSwWGjdu7OhwRaQgFos5emrGDHNq3+23uzoiERERcQGNnHJzmrYiUsGFhYGvLxw6BAkJro6mStu4cSN9+vSx2de3b1+2bt3K+fPnrfvS0tJo3rw5gYGB3HTTTezYsaPI983IyCA1NdVmE5ESyJnat2oVnDzp2lhERETEJZSccnOatiJSwXl7Q69e5nOtRuVShw4dolGjRjb7GjVqRGZmJseOHQOgdevWREdH89lnnxETE4OPjw/XXHMNu3fvLvR9n3vuOfz9/a1bUFCQU7+HSKUTEgJt2sD587B0qaujERERERdQcsrN9e/fn5kzZxIZGWlX+9zTVq688krGjBnDqFGjePHFF23a5Uxbyb2JiJPk1J1ScsrlLHmmVRqGYbO/W7du3HHHHbRv356wsDA++eQTLr/8cl555ZVC3zMqKoqUlBTrtn//fud9AZHKKmf01KJFro1DREREXELJqUpG01ZE3FBOXaRNm+DECdfGUoU1btyYQ4cO2ew7cuQIXl5e1KtXr8BzPDw86Ny5c5Ejp7y9vfHz87PZRKSEhg41H7/9Fo4edW0sIiIiUu6UnKpkNG1FxA01a2ZOWcnOhq+/dnU0VVb37t355ptvbPZ9/fXXdOrUiWrVqhV4jmEYJCQk0KRJk/IIUaTquuwy6NgRsrIgTykCERERqfyUnKqENG1FxA1pap/DpaWlkZCQQMKFQvOJiYkkJCSwb98+wOy37rzzTmv7++67j7///ptJkybx22+/8e677zJ//nwefvhha5vp06ezatUq/vrrLxISEhg9ejQJCQncd9995frdRKqknNFTH3/s2jhERESk3Ck5Vclo2oqIm8qZ2rdypTmCSsps69athIaGEhoaCsCkSZMIDQ1lypQpACQnJ1sTVQAtWrTgyy+/JD4+ng4dOjBjxgxefvllbr75ZmubU6dOMXbsWK688kr69OlDUlISa9eupUuXLuX75USqoqFDwWKBNWugiH+TiIiISOXj5eoAxLG6d+/OihUrbPbZO22lbdu25RGiSNV0zTVQuzYcOwZbt4KSHWUWHh5uHRlakOjo6Hz7evbsyfbt2ws956WXXuKll15yRHgiUlLNmpmjTL/4Al57DXQtioiIVBkaOeXmNG1FpJKoVg1yFivQ1D4RkYKNG2c+vvcepKe7NhYREREpN0pOuTlNWxGpRHLqTq1c6do4RETcUFYWxHv35XSjlpCSQvaHH7k6JBERESknFqOoOREihUhNTcXf35+UlBTVnxKx18GD0LSpWVPl0CFo2NDVERVK13jp6bcTKbnYWJgwAQ4cgIm8xEtM4rdqbfktZieRN1uKf4NypGtcRETE8TRySkSkvAQEQIcOYBiwapWroxERcQuxsTBkiJmYAojmLtKpyZXnf2LukHXExro2PhEREXE+JadERMpTztS+pUtdG4eIiBvIyjJHTOUex3+KOizgDgDGMY+JE812IiIiUnkpOSUiUp6GDjUfP/8cjh93bSwiIi62bt3FEVO5vYpZGH0wS8nan8S6deUcmIiIiJQrJadERMpTu3YQGgrnz0NMjKujERFxqeTkgvf/RDvWEkY1MhnLW4W2ExERkcpBySkRkfI2cqT5+P77ro1DRMTFmjQp/Ng8xgNwL28SUP9cOUUkIiIirqDklIhIeRs+HLy8YOtW+OUXV0cjIuIyYWEQGGguYprXUgZzkCY05jBhR5aUf3AiIiJSbpScEhEpbw0awI03ms81ekpEqjBPT5g713yeN0GVZanGm9wHgMdr88o5MhERESlPSk6JiLjCXXeZjx9+CJmZLg1FRMSVIiNh8WJo2tR2f2AgdHlnLFSrBhs2wI4drglQREREnE7JKRGRcpSVBfHxsOj0DZz3qweHDsE337g6LBERl4qMhL17IS4OFi40HxMT4cbRjeHmm81Gr77q0hhFRETEeZScEhEpJ7GxEBwMERFw253VeS31dgAOzIx2aVwiIu7A0xPCw2HYMPPR0/PCgfFmYXQ++giOHnVRdCIiIuJMSk6JiJSD2FgYMgQOHLi4733MVfvqb1jOig9OuigyERE3d/XV0KkTnD0LM2a4OhoRERFxAiWnREScLCsLJkwAw7Ddv4NQfqQtPmSwceIisrJcE5+IiFuzWGDWLPP566/D7t2ujUdEREQcTskpEREnW7fOdsTURRbr6Kl/nYxm3bpyDUtEpOLo1Qv69zcXkIiKcnU0IiIi4mBKTomIOFlycuHHPuJ2MvGkGz+QtvX38gtKRKSieeEF8PCAJUvM1ftERESk0lBySkTEyZo0KfzYYRrzFf0AaLvj/XKKSESkAmrTBkaNMp8//HD+udIiIiJSYSk5JSLiZGFhEBholk0pyPvcBUCzNR+iwlMiIkV4+mmoWRM2bjRHUImIiEiloOSUiIiTeXrC3Lnm87wJKosFVjCAc7XqYElKgm+/Lf8ARUQqiiZNzFFTAI8/DufOuTYeERERcQglp0REykFkJCxeDE2b2u4PDISFS7ypfucwc0d0dLnHJiJSoTzyCDRqBH/+CW+84epoRERExAGUnBIRKSeRkbB3L8TFwcKF5mNiornfWkflk0/gjz9cGaaIiHurVQumTzefP/00nDrl0nBERESk7JScEhEpR56eEB4Ow4aZj56eFw507Ag33WTWnJo82YURiohUAKNHw5VXwvHjMGGCiqOLiIhUcEpOiYi4i2efNYtQffopbN3q6mhERNyXl5c5pc/DAz74AN57z9URiYiISBkoOSUi4i7atoU77jCfP/GEa2MREXF3PXrAjBnm83Hj4KefXBuPiIiIlJqSUyIi7mT6dKhWDb75Riv3iYgU5/HHoV8/OHsWbrkFTp92dUQiIiJSCkpOiYi4kxYt4L77zOdRUaqjIiJSFA8P+PBDcynUXbvg3nvVb4qIiFRASk6JiLibJ58EX1/YsgWWLnV1NCIi7q1+fVi0yFxhIiYG3nzT1RGJiIhICSk5JSLibho1gkmTzOdPPAGZma6NR0TE3V1zDTz3nPn8gQfgmWcgO9u1MYmIiIjdlJwSEXFH//kP1KtnTlN5/31XRyMi4v7+8x+4/35zWt/kyRAZCSkpro5KRERE7KDklIiIO/L3v7hi39SpcPKka+MREXGRrCyIjzdn7MXHm68L5OEBr70G77wD1avD8uXQpQv8+ms5RisiIiKloeSUiIi7euABs0B6UhIMHarpfSJS5cTGQnAwRETA8OHmY3Cwub9Qo0fD+vUQGAh//AFdu8KSJeUUsYiIiJSGklMiIu7Kx8e8A6tZE775Bh591NURiYiUm9hYGDIEDhyw3Z+UZO4vMkHVuTNs22Zms9LSzBMef7yIYVciIiLiSkpOiYi4sw4d4IMPzOcvvQTR0a6MRkSkXGRlwYQJZvmovHL2TZxYTK6pYUP4+mt4+GHz9fPPQ79+Zi0/ERERcStKTomIuLubbzbrTgHcey9s3OjaeNzE2rVrGTBgAAEBAVgsFpYtW1bsOWvWrKFjx474+Phw6aWX8sYbb+Rrs2TJEkJCQvD29iYkJISlS5c6IXoRKcq6dflHTOVmGLB/v9muSF5e8N//wqJF4OsLq1dD69bQsSPMnl30h4iIiEi5UXJKRKQimDLFXHnq3DkYPBj27nV1RC6Xnp5O+/btmTdvnl3tExMTueGGGwgLC2PHjh088cQTPPTQQyzJVYtm48aNDB06lBEjRrBz505GjBjBrbfeyg8//OCsryEiBUhOdmw7br0VNm2CG24AT0/Yvt0cUdWsGfTsCW++CcePlzpeERERKRuLYRQ0YFqkaKmpqfj7+5OSkoKfn5+rwxGpGtLS4Jpr4McfoXZtczTVQw9BtWoO/6iKdo1bLBaWLl3KoEGDCm3z2GOP8dlnn/Hbb79Z9913333s3LmTjRdGow0dOpTU1FRWrlxpbdOvXz/q1KlDTEyMXbFUtN9OxB3Fx5vlooozeTL06gVhYWbOyS5Hj8Lixebyf7mHXjVoYGa7inkjXeMiIiKOp5FTIiIVRa1asGKFuTT66dPmX/3btTOLpUuxNm7cSJ8+fWz29e3bl61bt3L+/Pki22zYsKHQ983IyCA1NdVmE5GyCQszF9uzWIpuN3OmnSv45dagAdx/P6xdC3//DS+8AKGh8K9/lSDDJSIiIo6k5JSbU00VEbHRrJlZc2r+fPMG6/ffoU8fsy6VpvoV6dChQzRq1MhmX6NGjcjMzOTYsWNFtjl06FCh7/vcc8/h7+9v3YKCghwfvEgV4+kJc+eaz4tLUIGdK/gVpFkzeOQRc5rfa6+VOE4RERFxDCWn3JxqqohIPh4eMGoU/PGHOa3P09O8I7vySpg+Hc6ccXWEbsuS5y43Z2Z77v0Ftcm7L7eoqChSUlKs2/79+x0YsUjVFRlpzr5r2rT4tnav4FeU6tVLeaKIiIiUlZerA5Ci9e/fn/79+9vd/o033qBZs2bMmTMHgCuvvJKtW7fy4osvcvPNNwMwZ84cevfuTVRUFGDeWK1Zs4Y5c+bYXVNFRNzAJZeYQwvGjDGTVPHxMG0avP66OfWvXTtza9sWWrUyV62qwho3bpxvBNSRI0fw8vKiXr16RbbJO5oqN29vb7y9vR0fsIgQGQkDB5qlob791pzGV5jcK/iFh5dbiCIiIuIAGjlVyTirpoqIuLG2beG77+Djj80iLYcPm7WpnnkGhg6FkBCzXlXHjvDuu66O1mW6d+/ON3nqc3399dd06tSJaheKyhfW5uqrry63OEXElqenmWwKCbGvvd0r+ImIiIjbqNp/Rq+Eiqup0qRJk1LVVMnIyCAjI8P6WgV/RdyMxWImogYONJdL/+knc/vxR/Pxn3/MmiqnT7s6UodJS0tjz5491teJiYkkJCRQt25dmjVrRlRUFElJSXzwwQeAuTLfvHnzmDRpEvfccw8bN25k/vz5NiNGJ0yYQI8ePXj++ecZOHAgy5cvZ/Xq1axfv77cv5+I2GrSxLHtRERExH0oOVUJOaOmynPPPcf06dMdGKWIOIWPjznEIPecluxsSEw0E1Xt27sqMofbunUrEbnWmp80aRIAI0eOJDo6muTkZPbt22c93qJFC7788kv+/e9/8+qrrxIQEMDLL79snfIMcPXVV/Pxxx8zefJknnrqKVq2bMmiRYvo2rVr+X0xESlQzgp+SUkXa0zlZrGYx8PCyj82ERERKRslpyoZZ9VUiYqKst74gTlySitSiVQQHh7QsqW5VSLh4eHW5HtBoqOj8+3r2bMn27dvL/J9hwwZwpAhQ8oanog4WM4KfkOGmImo3Jd/zt/X5swx24mIiEjFoppTlYyzaqp4e3vj5+dns4mIiIiUp8JW8AsMNPdHRromLhERESkbjZxyc6qpIiIiInJR7hX8kpPNGlNhYRoxJSIiUpEpOeXmVFNFRERExFbOCn4iIiJSOViMogp2iBQiNTUVf39/UlJSNMVPpBLSNV56+u1EKjdd4yIiIo6nmlMiIiIiIiIiIuIySk6JiIiIiIiIiIjLKDklIiIiIiIiIiIuo4LoIiJuICsr/8pToNWoRERERESk8lNySkTExWJjYcIEOHDg4r569czH48cv7gsMhLlzzWXURUTEVkFJfiX0RUREKgZN6xMRcaHYWBgyxDYxBWZSKndiCiApyWwbG1t+8YmIVASxsRAcDBERMHy4+RgcrP5SRESkolBySkTERbKyzBFThmFf+5x2Eyea54qISOFJfiX0RUREKg4lp0REXGTduvw3U8UxDNi/3zxXRKSqKyrJr4S+iIhIxaHklIiIiyQnl/7cJUsgPl43XCJStRWX5FdCX0REpGJQckpExEWaNCn9ufPmqaaKiIi9Sf6y/DFAREREnE/JKRERFwkLM1fgs1hK/x6qqSIiVZm9Sf6y/DFAREREnE/JKRERF/H0hLlzzeelTVCppoqIVGXFJfktFggKMtuJiIiI+1JySkTEhSIjYfFiaNrUdn+9euZmD9VUEZGqqqgkf87rOXPMdiIiIuK+lJwSEXGxyEjYuxfi4mDhQvPx8GFzi4uD8ePtex/VVBGRqqiwJH9goLk/MtI1cYmIiIj9vFwdgIiImH/VDw/Pvz9n37x5xb+HaqqISFUVGQkDB5ojSJOTzf4wLEwjpkRERCoKJadERNxcTk2VpKSLNaZys1jM46qpIiJVWWFJfhEREXF/mtYnIuLmVFNFREREREQqMyWnREQqANVUERERERGRykrT+kREKojiaqpkZRV8rLD9IiIiIiIi7kDJKRGRCqSwmiqxsTBhAhw4cHFfYCAMGwYxMfn3z52r0VYiIiIiIuIelJwSEangYmNhyJD8xdIPHID//jd/+6Qks72mA4pIVaLRpSIiIu5LySkRkQosK8scMVXQKn6FMQyzkPrEieY0Qd2EiUhlp9GlIiIi7k0F0UVEKrB162xvquxlGLB/v3m+iEhlljO6NG9fmTO6NO/+nNGlsbHlF6OIiEhVp+SUiEgFlpzs2vNFRNxZaUeXgjm6NCvLKWGJiIhIHkpOiYhUYE2auPZ8ERF3ptGlIiIiFYOSUyIiFVhYmFkfxWIp2XkWCwQFmeeLiFRWGl0qIiJSMSg5JSJSgXl6moV7wf4EVU67OXNUDF1EKjeNLhUREakYlJwSEangIiNh8WJo2tR2f1AQPPKIObIqt8BAs71WohKRyk6jS0VERCoGL1cHICIiZRcZCQMHmvVRkpPNv/aHhZkjo557ruD9IiKVXc7o0iFDzISTPYXRNbpURESk/Ck5JSJSSXh6Qni4/ftFRKqCnNGlEybYFkcPCoLbboOYGNv9gYFmYkqjS0VERMqPpvWJiEiF9dprr9GiRQt8fHzo2LEj64pZWuvVV1/lyiuvpEaNGlxxxRV88MEHNsejo6OxWCz5trNnzzrza4iIk0VGwt69EBcHCxeaj4mJ8MILBe9XYkpERKR8aeSUiIhUSIsWLWLixIm89tprXHPNNbz55pv079+fX3/9lWbNmuVr//rrrxMVFcXbb79N586d2bx5M/fccw916tRhwIAB1nZ+fn7s2rXL5lwfHx+nfx8RcS6NLhUREXFfSk6JiEiF9L///Y/Ro0czZswYAObMmcOqVat4/fXXee655/K1//DDD7n33nsZOnQoAJdeeimbNm3i+eeft0lOWSwWGjduXD5fQkRERERENK1PREQqnnPnzrFt2zb69Oljs79Pnz5s2LChwHMyMjLyjYCqUaMGmzdv5vz589Z9aWlpNG/enMDAQG666SZ27NhRZCwZGRmkpqbabCIiIiIiYj8lp0REpML5//buP6aq+o/j+Oty+SGR9yaRhIDiSiUVRRBSE6b+AVFqNttyS5O1VZTNNbcKM0vR6dZmm6Z9N+c0ak3N5o9St+YW+QPzBwaZ5o/UCgIUf3JRUxTO94++0Je4CJx74Vwuz8d2t+45n/Phfd879233fc89n0uXLqmurk6RkZFNtkdGRur8+fNuj8nMzNSaNWt05MgRGYahoqIirV27Vnfu3NGlS5ckSfHx8fr000/19ddfa/369erRo4eeeOIJ/frrry3GsnTpUjmdzsZHbGys914oAAAA0A3QnAIAdFm2hjXf/8cwjGbbGsyfP19ZWVkaNWqUgoKC9Mwzzyg7O1uSZP/fevGjRo3S9OnTNXz4cKWlpenLL7/UwIED9fHHH7cYw9y5c1VdXd34KCsr886LAwAAALoJmlNdAKtRAUBTERERstvtza6SqqqqanY1VYPQ0FCtXbtWN2/e1O+//67S0lLFxcWpZ8+eioiIcHtMQECAUlJS7nnlVEhIiBwOR5MHAAAAgLajOeXjGlajmjdvnoqLi5WWlqasrCyVlpa6Hd+wGtWCBQt0/PhxLVy4ULNmzdI333zTZJzD4VBlZWWTB6tRAegqgoODlZycrF27djXZvmvXLo0ZM+aexwYFBSkmJkZ2u10bNmzQxIkTFRDg/p9DwzBUUlKiqKgor8UOAAAAoClW6/NxrEYFAO7NmTNHM2bM0MiRIzV69GitXr1apaWlysnJkfT3z+3Ky8sbrx49ffq0Dh06pMcff1xXr17VRx99pGPHjik/P79xzoULF2rUqFEaMGCAXC6XVqxYoZKSEq1atcqS1wgAAAB0BzSnfFjDalS5ublNtnuyGlVQUJCkf1ajqqurU2JiohYtWqQRI0a0GMvt27d1+/btxuesRgXAas8//7wuX76svLw8VVZWaujQodq5c6f69esnSaqsrGxylWldXZ2WLVumU6dOKSgoSOPHj9f+/fsVFxfXOObatWt65ZVXdP78eTmdTo0YMUJ79uxRampqZ788AAAAoNuwGYZhWB0E3KuoqFB0dLQKCwub/ExlyZIlys/P16lTp5od8+6772rdunXavn27kpKSdOTIET399NOqqqpSRUWFoqKidODAAZ05c0YJCQlyuVxavny5du7cqZ9++kkDBgxwG8uCBQu0cOHCZturq6u5vwrgh1wul5xOJ+9xE8gd4N94jwMA4H3cc6oLYDUqAAAAAADgr2hO+TBWowIAAAAAAP6O5pQPYzUqAAAAAADg77ghuo9jNSoAAAAAAODPaE75OFajAgAAAAAA/ozV+mAKK9UA/o33uHnkDvBvvMcBAPA+7jkFAAAAAAAAy9CcAgAAAAAAgGVoTgEAAAAAAMAyNKcAAAAAAABgGZpTAAAAAAAAsAzNKQAAAAAAAFiG5hQAAAAAAAAsQ3MKAAAAAAAAlqE5BQAAAAAAAMvQnAIAAAAAAIBlaE4BAAAAAADAMjSnAAAAAAAAYBmaUwAAAAAAALAMzSkAAAAAAABYhuYUAAAAAAAALENzCgAAAAAAAJahOQUAAAAAAADL0JwCAAAAAACAZWhOAQAAAAAAwDI0pwAAAAAAAGCZQKsDQNdkGIYkyeVyWRwJgI7Q8N5ueK+j7aiPgH+jPgIA4H00p2BKTU2NJCk2NtbiSAB0pJqaGjmdTqvD6FKoj0D3QH0EAMB7bAZf+8CE+vp6VVRUaMKECSoqKmp1fEpKig4fPtzu/e62t2Vbw3OXy6XY2FiVlZXJ4XC0GqcZrb02T47zZt7cbb/X847OXUfmrS3jOOfuPcYwDNXU1KhPnz4KCOAX4O3RUB979uyp1NTUTn2ft+dclfz7fd7efb5UH1uK0VvHcM6ZPy4lJUWHDh2iPgIA4GVcOQVTAgICFBMTo8DAwDb9z6Xdbr/nuJb2u9velm3/fu5wODrsA0Rrr82T47yZN3fbW3sudVzuOjJvbRnHOdf6GK4IMKehPkqd/z43c65K/vk+b+8+X6qPLf09bx3DOWf+OLvdLqfTSX0EAMDL+LoHHpk1a5ZXxrW03932tmxra1zeYPZvteU4b+bN3XZ/zVtbxnHOeXduuNfZ7/PudK62Nq69+3ypPpr9e9RH6/9tAQAA5vCzPvg1l8slp9Op6urqDvt221+RO3PIG7oSzldzyJt55A4AALjDlVPwayEhIfrggw8UEhJidShdDrkzh7yhK+F8NYe8mUfuAACAO1w5BQAAAAAAAMtw5RQAAAAAAAAsQ3MKAAAAAAAAlqE5BQAAAAAAAMvQnAIAAAAAAIBlaE4BAAAAAADAMjSn0K1t375dgwYN0oABA7RmzRqrw+kynn32WfXq1UvPPfec1aF0KWVlZRo3bpwGDx6sYcOGadOmTVaHBLSI+mgeNbL9qI8AAHRvNsMwDKuDAKxw9+5dDR48WAUFBXI4HEpKStLBgwcVHh5udWg+r6CgQNevX1d+fr6++uorq8PpMiorK3XhwgUlJiaqqqpKSUlJOnXqlMLCwqwODWiC+ugZamT7UR8BAOjeuHIK3dahQ4c0ZMgQRUdHq2fPnnrqqaf07bffWh1WlzB+/Hj17NnT6jC6nKioKCUmJkqSevfurfDwcF25csXaoAA3qI+eoUa2H/URAIDujeYUuqw9e/Zo0qRJ6tOnj2w2m7Zu3dpszCeffKL+/furR48eSk5O1t69exv3VVRUKDo6uvF5TEyMysvLOyN0S3mat+7Mm7krKipSfX29YmNjOzhqdEfUR/OokeZQHwEAgCdoTqHLunHjhoYPH66VK1e63b9x40a9+eabmjdvnoqLi5WWlqasrCyVlpZKktz9otVms3VozL7A07x1Z97K3eXLl/Xiiy9q9erVnRE2uiHqo3nUSHOojwAAwCMG4AckGVu2bGm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A+vTpg9jYWJQrVw7//PMPpk2bhq+//hoHDx50Wx6PHDkCALj33nvh42P5VNaqVctkHb3s7GwEBwejS5cuePjhh1GrVi2ULFkSFy9exJ9//olPP/0U//77L9577z3UqFHDYqnts88+iwULFgAAOnfujKeffho1atSATqdDUlISpk+fjj///BPPP/88KlSogK5du9p1zJs2bTJ7XAW5ceMGzp49ix9++AFTp041fLvy0ksvWV3v+vXrhjTvv/8+ypYta1N+nX0dZWRkGL5Fq1SpkkPfDHTv3h1NmzYFANSvXx+A8q3Uiy++aEhTunRps+v26dMHycnJeOGFF9CrVy+EhobiwIEDeP/99/HPP/9gxYoViIiIwKeffmp3/hxl77VjjT3Xh63nWYv73Bp77w1r+vbti7fffhtpaWl4//338eijj5rU6ti/f7/hG8WnnnoKJUuWNNlObm4uunXrhnXr1gEAqlevjhdffBFNmzZFUFAQUlJSsH37dnzzzTcm6zrj3nPFda5FvvU1NEJDQ1G7dm0sXrwYU6dONfoWq2rVqoiNjcUrr7yCkJAQq3lyNA7mtXz5ciQkJODUqVPw8fFBhQoV0LJlSwwYMADt2rVz2TE5SovPTke3of/mFlCuG2vyLj98+LCqY1QbGwpbTDPHkc+3Xr164ezZsxgxYgQef/xxlC5dGkePHkXlypUNabR6lrKHO86n1rQ4Bq3Og7vP57Vr1/DII4/g0qVLAICnn34a//d//4eyZcvi2LFj+OSTTzBr1iz88ccfDu3HGc9ErnbixAksWLAACxcuxLFjx5CSkoIPPvgAH3zwAZo2bYoBAwagb9++CAsLs3nbH3zwgeH3d955x6jWZUEqVqxo+P3ChQs277swcOV9oPW+tHxm0bP1WbmoxCNLLl++jClTpgBQarPrW7NVqVIFwcHByMzMdFkZyezZs7F161YAMOxz9uzZhhpk3bt3R/fu3dVv0J4SLVfUnBo9erRh+eTJk02W375922hEEkvbybvc3slc6d/NmzcNy7t06WL1PIiIoff8Fi1aGM2/dOmS1fbaWVlZEhMTYzjf5vq0yNv58VdffWV2Ozdv3pSHH35YAEiVKlXsql2Qk5MjzZo1M+xr9+7dVtMX9E3pq6++WuA3IfpREFq2bGmUVm3pu1bXkSXz5s1zSgm1fptq+5wCIEuWLDFJk5aWJg0bNhQA4uXlJQcOHChw386oOWXrtaOWo9dHQedZq/s8Py3ujYKsWrVKAgMDBVBG7Zg/f77s2LFD1q1bJxMmTDB0MNqoUSNJSUkxu43p06cb8tSjRw+5deuW2XQ5OTly9uxZo3la3XvOus4t0SLf+loeDRs2NOow29xUr149k3OXn6PXuYi6z8Lu3btb7ORc62PKy56Yo8Vnp6PbyMjIMAwq0KBBA6v5zTt6prXRuRyNDe6Kabaw9fPNy8urwL5mtLge7FEYzmd+tt5PWhyDVuehMJzPkSNHGvLw4YcfmizPzs6Wbt262f3cKGLbM1FhrjmV17Zt22TIkCFSunRpo3Pj5+cnTzzxhHz//feq3z3OnDljqJVVs2ZNm/OSlJRk2H/Hjh1tXt8SNZ+jBU1qapS48j5wxr60eGYRsf/zsCjFI0uGDx8ugNLH1dWrV42WNW3aVADlfd8V9OVCliZba+zb1eeUs2VlZWHu3LkAgAYNGuCNN94wSePr64s5c+bA19fX1dkDAKSnpxt+V/MNsf4b1oyMDKP54eHhKFWqlMX1/Pz8DN8e/Pvvv0hKSjJJoy857dGjBwYPHmx2OwEBAZgxYwYA4OTJk3a1h/3444/x+++/G/al/xbUVo0aNcLOnTvxwQcfWP0mZOvWrZg9ezZ8fHzwxRdf2PStCeCa60hfWw2Aob2xOzz22GPo27evyfwSJUpg1qxZAJRaMF988YWrswZAu2snL0evDzW0us/VUntvqNGjRw/s2bMHzz77LJKSkhAbG4sHHngAMTExmDBhAoKCgjBt2jRs3boVFSpUMFk/NzfXEHsqVqyIBQsWwN/f3+y+vLy8EBkZafjbWfees69zrfJ99epVAEo/Tf/73/9QqlQpfPHFF7h48SJu3bqF3bt3o3PnzgCUfnJ69+6N3Nxcs9vS6joPCgrCU089ha+++gpbtmzB/v378euvv2Ls2LEoU6YMAKVvhW7duuHOnTtOPSYtaPHZ6eg2goOD0b59ewBK3w4JCQlmt5OQkGD0DWbeuKKWVrHB1TFNCwMGDCiwrxktrgd7eOL5zE+LY9DqPLj7fN66dQvz588HANx3330YPXq0SRpvb298+eWXCAgIsHs/zngmcreWLVviiy++QEpKCpYvX46uXbvC19cXt2/fxsqVK/H4448jKioKr7zySoF94axbtw4iAgDo3bu3zXm5cuWK4XdLNTILM1feB1rvyxXP5gV9HhaVeGTJ0aNH8eWXXwIAxo4da3KN6/ud+vfff+163rDVvHnzIMoge2anCRMm2LS9Qtmsb+/evbh27RoAIDY2Fl5e5svQoqKi0LFjR6ud3WlRpS0qKspkXt4O2Pz8/Archv6l7ubNm1bTZWVl4cKFC8jIyDA82OsDNAD88ccfaNKkieHvs2fPYu/evQCAJ5980uq2a9eujfDwcFy+fBk7duxAhw4dCsy33qZNm/Dmm28CAMqVK4fPP/+8wHXyVuO/efMmjh8/jm+++QarV6/G008/jenTp+Oxxx4zu+7t27fx/PPPQ0Tw8ssvG5oB2ELL68icM2fOGAr5WrRogRo1aticR61Ya6LQrFkz1K1bF3/++Sd+++03F+ZKYc+1UxAtrg81nHWfO3JvqHXnzh0sWbIEP/zwg1EM0btw4QISEhJQo0YNdOnSxWR5UlKSoaP/5557zqZmWs6695x9nWuV78zMTABKPPf29sZPP/2EFi1aGJY3bdoUa9aswWOPPYaffvoJ27dvx6pVq9CrVy+j7Wh5nZ89e9bsy3tMTAxGjBiBzp07Y//+/di0aRM+//xzjBw50inH5Cy2fnZqtY34+Hj89ttvyM7ORmxsLI4fP47+/fsjIiICKSkpWLBgAd555x34+fkZBiqwFh+cHRucFdOc6emnn7Z5HS2uBzU88Xzmp8UxaHUe3H0+9+7da2iC279/f4sv1uXLl0enTp3w3Xff2bwPW5+JClvn+QXx9/dHr1690KtXL1y+fBlLlizBggULsHfvXly4cAHTpk3DtGnT0LhxY8TGxqJ///4mL9d5j7lly5Y25+HQoUOG3wsavMsWznqnzM+V94GW+9L62dzez8OiEo8seeONN3Dnzh1UrlwZw4cPN1let25dAMpn3sGDB+26h9ypUBZO5b3577//fqtpmzVrZvXFJm+v9VrK+41J3pGxLNGPhBUYGGiyLDMzE59++imWLl2KP//80+poF5cvXzb6e8+ePYbf+/bta7ZWgTnnz59XlQ4A/vzzT/To0QPZ2dnw9/fHN998g/Llyxe4XqlSpYxehu6//3489dRTWLhwIWJjY9GtWzfMmTPH7Ah0kydPxpEjR1CpUiXExcWpzmteWl5H5ixatMjw0BsbG2s17dmzZw0vvfmVLl3aqH28PdQc359//omjR4/i9u3bqoKsFmy5dmw5R1pcH2poeZ/nZc+9Ycv5yczMxKOPPorNmzfD29sbr7/+OgYOHIh77rkHt27dwq5du/DOO+9g69at6Nq1Kz7++GOTdvv79+83/N66desCjz0vZ9179l7nas+dVvkOCAgwFOb07t3bqBBHz8vLCx988AF++uknAErtmvwFOVpe59ZqlZQvXx4rVqxA7dq1cfv2bXz22WcmhVNaHZOWHPns1GobzZo1w5w5c/Dcc8/h9u3bePvtt/H2228bpfH29sb06dMxYsQIAEpNP0sc+dxUw1kxzZkaNGigKp0W14OtPPF85qfFMWh1Htx9PvMWahRUeNm0aVObC6fsfZ62RO1nm9bp1AoPD8fIkSMxcuRIHDlyBPPnz8fixYtx5swZ7N+/H/v370doaKhJPDt16pTh99q1a9u0TwCG/m8AoHnz5javb4mz3inzc+V9oOW+tH42t/fzsKjEI3O2bt1q6Ot48uTJZls06AunALBwSit5A2O5cuWspnUkqDsi78Olmup7+of6/LUPTp48iYcffhjJycmq9pu/NPbixYuq1svvxo0bqtIlJyejY8eOuHbtGry9vZGQkIA2bdrYtU+9Z555BmvWrME333yD4cOHo1u3bkbfmvz111+GpoqfffaZUaeztnD2dbRw4UIASkl5nz59rKYdO3asoap4frGxsSZDYttK7fGJCK5du+aS+8bWa0ftOdLq+lBDq/tcLWv3hi3XUFxcHDZv3gwAmDNnjlHhqZ+fH2JiYtCuXTt07NgRiYmJGD16NNq1a2f0Epj35S0iIsKm43DWvWfvda723GmV7xIlShiuBX1TN3Pq1q2LihUr4uzZs9i9e7fRMlde5wBwzz33ICYmBj/++COOHTuGc+fOGTXV1OKYtOToZ6dW2wCUGhYNGzbEu+++i59//tlQjd7Lywvt2rXDu+++a/T/s6eZSUGfm2q5OqZpQc1xavW/tJUnns/8tDgGrc6Du8+nLZ8Btnby7IznabWfbVqns0eFChVQtWpVREVF4cyZM1bT5n23sbUz9Rs3bmDt2rUAlMIFawN9FFauvA+02pcrn1kK+jwsKvHInFdffRWAUnhuqUJK3sKpgprQFkaFsnAqb9Xrgtqqmmuuklfeb0HsFRUVZfKtc0BAgKGJXEFB9tq1a4YLNjo62mjZM888g+TkZOh0OgwcOBBPPfUUateujbJlyxpKQ3Nzcw0jbeU/3rzfDC5evFj1N4xqHvbOnTuHDh064Ny5c9DpdPj666/Ro0cPVdsvSLdu3fDNN98gMzMTP/30E/r162dY9vHHH+P27du45557cOPGDSxdutRk/bz/1w0bNhhqgnXt2tUQELW8jvLbs2ePYcSlxx57zO1t2rU+Pkc589rR6vpQQ6v73BbW7g01RMTQb1KNGjUs1urz8fHBxIkT8dBDDyE3Nxdz587Fxx9/bDatrX0GOOvec/Z1rlW+o6OjDddcQVX4o6OjcfbsWZMvGlx5nevVqVPHUBvs7NmzRoVTWhyTlhz97NRqG3oNGzbEN998g5ycHKSkpODWrVuIjIxEUFAQAGDJkiWGtHXq1LHrmB2NDYB7Ypqj8o80ao6W/0tbeOL5zE+LY9DqPBSF82mOM5+JCrM7d+5g7dq1WLBgAdasWWNU+6RixYr4v//7P3Ts2NFkvbx9OlqrAWnO7NmzDddFjx49rNYatpWz3inzc+V9oNW+XP3MYu3zsKjGo2XLlmHXrl0AlCbIlrqeyMtVI/Zpya7CKf3JKKizU/0/yVZ5S8kvXLhgtS+fgh5+teiLZu7cuWar0NeuXRtbtmzBsWPHkJ2dbXGIyb/++stonbzz9VVPx4wZg3fffdfs+paq2AIwdGQLKC9TWlU5vXz5MmJiYnDixAkASim4lh1+5/3G6d9//zVapq8WeeLECVXNFCdOnGj4PTk52RDgtLyO8svbEXpBTfoApbM4R2tHWXPhwgWrwVB/fDqdzukFafZeO2rPkVbXh1qO3ue2snRvqD0/Fy5cMHRe3bhxY6tp8zZbyJt/QKmOr3fu3DnUrFmzwH3rOeves/c6V3vutMp33bp1DbWGCnqw1i/Pf125+joHrL+wa3FMWtHis1OLbZjj7e1ttvBOi2Ym1j43beHqmOZszvpfqlUUzqcWx6DVeXDn+cz7uXHx4kWrnwGXLl1StU1nPk+r/WzTOl1Bdu3ahYULF2Lp0qVGnZMHBgaie/fuiI2NRUxMjMWX67y11s6ePav6uTUjIwNTp04FoMTit956yyTN8uXL8eSTT2LGjBmoXLkyPvjgA+zduxchISEFdnnizHfK/Fx5H2ixL1c/sxT0eVgU4lFet2/fNns9F8QTC6fsGq1PX83t+vXrVtP9/fff9mze6OYvqFmAM5sNFOShhx4CoBTC6TslN2fTpk2G3x988EHD73/++afh96eeesri+nn7lcov78vnr7/+aj3DKqWmpqJTp06GmkHvvfcehg0bpsm29fQdLQPOq/7orOvozp07hm8EypYta7WJi6uoPb7q1as7tb8pV1w7rubofW4rR++NvB+c2dnZVtPmHZUt/wfufffdZ/hd30RQLWfde86+zrXKd94+uo4fP251O/oXFkf7ndOC/r4FYFRrCihcx6TFZ6cW21Dr9u3bWLFiBQDlnNjb/4NWn5uujmnO5sr/pTlF4XxqcQxanQd3ns+8zWEKul7UXE9F8ZnIkpMnT2LSpEmoWbMmWrRogf/973+GgqmWLVviyy+/REpKCpYsWYJOnTpZrfWRtwA/7/+5IK+//rrRQC7mvrDXj9S5Zs0a9OnTB1WqVMGIESPw3HPPqd6PK7jyPvDEGFbQ52FRiEd5zZgxAydOnIBOp8PMmTORkJBgddK/m16/fh2nT5/WPD9OJXb4+OOPBYAAkL/++stsmqysLImMjDSkS05ONlo+d+5ci8tu3bolpUuXFgDSqFEjyc3NNbuPM2fOiJ+fn8XtONuuXbsM+x4yZIjZNDk5OVK7dm0BIKVKlZLbt28bli1dutSw/s6dOy3up3v37oZ0cXFxJsvr1KkjACQgIED+/fdfh44pMzNTHnzwQcP+xo4d69D2LHn00UcN+0hMTLR5/bi4uALXd9Z19N133xnSvvTSSzbnXQ1r/2+9vOfg8ccft5hu9+7dhnQvvvhigftOTk42pI+NjVWdZ1ddO2qouT5E1J1nR+9zWzl6b+Tk5EjJkiUFgERGRsqdO3cspv3hhx8M+xoxYoTJdqKjowWAREVFSXp6uuo8aHnvOes6d2a+L1++LL6+vgJAYmJiLO5v48aNhm08++yzNudX7XWuxvHjxw15vueee0yWO/OYbI05Wnx2avX5q8bUqVMN25g4caJd2xBRFxsKY0yzJ495r+2CuPJ/aY67z2d+9nyGa3EMWp0Hd57PmzdvSmhoqACQ++67z+JnwPnz5yUgIMDqZ1dheiZyluvXr8vs2bOldevWotPpDMcKQCpVqiRjx46Vf/75x+bt7tu3z7CdOnXqqPr//u9//zOsU69ePcnMzDSbTh9Ho6Ki5NixYzbnzVVceR+4al9aPrMU9HlYFOKR3tWrVyUsLEwASI8ePVStk7esZs2aNZrmx9nsKpzKGzSee+45k+W5ubnywgsvGAUpWwqnRERGjx5tWP7++++bLL9z54507tzZ6j5coVWrVgJAfHx8ZPv27SbL8z6U5n8Y2rt3r2HZ0KFDzW5/5syZRsdo7oFqyZIlhuVNmjSRixcvWszvrVu35H//+5/cvHnTZFlWVpZ07NjRsC17Cl7mzp1rdtt5TZs2zbCPKlWqWH15tkRtgHPGdfTEE08Y0u7du9fmvKth68M7AFm2bJlJmvT0dGncuLEAEC8vL/njjz8K3Lc9D7ZaXDta0rJwSsSx+1zPVfeGiEjfvn0N25kwYYLZNFevXjUUbAOQX375xSTNp59+aljeo0cPycrKMrutnJwcOXv2rNE8re49Z13nlmiV76FDhxqWJyQkmCxPS0uTRo0aGdL8/vvvNudV7XX+/fffW72Wzp8/bzh/AOSjjz4ym85Zx2RrzNHis1Orz18Rsfql0Pfff28o1KtevbrZGKBlbHBlTLOXrZ9vBdHyf2kvd57P/Oz9gkmLY9DqPLjzfI4YMcKw7Q8//NBkeU5OjnTr1s3qZ4CWz0Rt2rRx63uONXkL6ABIUFCQ/N///Z/89ttvFgv21HrssccM2x04cKBkZ2ebTXfjxg157bXXDGkrVapktdApIiJCAMj69esdyp8raHUf6NNUrlzZ6fuyRs0zi5afh0UhHoncfS7V6XSqn29//PFHQ56mTJmieZ6cya7CKRGRFi1aGH34bdiwQfbu3StLly6Vtm3bCgB54IEHLAbUggqnrl+/LlFRUYY0ffv2lZ9++kn27t0rCQkJcv/99wsAw093Be19+/ZJYGCgAJCQkBCZPHmy7NixQzZs2CDPP/+8IW81atSQtLQ0o3Vzc3OlXr16Rse4Zs0a2bt3r3z77bfSq1cvAWD0zYuliz42NtaQJjw8XMaOHSu//vqr7N+/X7Zu3Srz58+XwYMHG0pezdWC6Nmzp2EbDz/8sBw4cEAOHjxocfr7779NtlG5cmUJCwuT5557TubPny9bt26VpKQk2bJli8ycOdPoWPz8/GTdunV2nXe1L2VaX0dXr14Vf39/AZRvZpzF1of3pk2bire3t7z44ouyYcMG2bNnj3z99ddSs2ZNQ5r8NWP0tmzZInPnzjVMH3zwgWGdBx980GjZ3LlzzW5Di2tHS1oXTjlyn+u56t4QETly5IgEBQUZtte1a1dZsWKF7Nu3T7Zv3y7Tpk2TSpUqGZa3b9/e7HZycnIkJibG6PimT58uW7dulX379snatWtl/PjxUr16dZNzqNW9p9V1rpZW+b548aLhHPv4+Mjw4cMNeZ47d67UqlXLsL6lF+qCqL3OK1euLJGRkTJixAhZsmSJbN++Xfbv3y/r1q2TsWPHSpkyZQzbeeihh+TWrVtmt6PVMTkac7T47NTy87dEiRLSsWNH+eqrr2T79u2yZ88eWbFihfTp08ewbunSpWXfvn0W/z9axQZXxjR72fr5VhAt/5f2cuf51OIzXKtj0Oo8uPN8XrlyRSpUqGDYx9NPPy0///yz7N27V5YtWyYtW7YUANKsWTNDmpMnTxptQ8tnosJcOAUoL8ytW7eWOXPm2FTDuiAXLlww1N4GIPXr15f//e9/sm3bNsPzx5gxY4xa6dSvX9/kf5HXxYsXBVBqRnsCre4DfTprhVOuuOfUPLNo+XlYFOLRiRMnDDX1e/XqpXq9o0ePGn0mehK7C6eOHDki5cqVMxx4/mn06NFWC6AKKpwSETl06JDRB0T+aeDAgaq242zff/+9oRmNualGjRpy9OhRs+vu37/f0IzE3FS/fn05d+5cgQ9U2dnZ8vrrr4u3t7fFbemn4OBguXHjhsk2Clov/2QuyFWuXFnVulFRUfLrr7/afc5tqRqq5XX0+eefG9JNnTrV7vwXRM0DdN5zcOLECalatarFY3ziiScsfrOQt2BTzWQtv45cO1rSunBKxLH7XMR194beunXrJDw8vMD9Pfzww3L16lWL28nMzDS83FmbzJ1DLe49ra5zW2gVMw4fPiz33nuv1fM2aNAgu6uA21I4pebae+KJJ+TatWtW96nFMWkRc7T47NTq8zc4ONhq/uvUqWOxYEpE29jgyphmLzV5tKVwSkS7/6Uj3HU+tbiftDwGrc6Du86niEhSUpKULVvW4r4HDBggc+bMMfx9/vx5o/Vt+X8A1p+JCnPhVFxcnBw/ftxp2z979qxRYYSlKSgoSMaMGWPxixW9X375RQDI22+/7bQ8a02L+0DNdabVvqxRWzil1eehlsfkrnik/5JLp9PJoUOHVK+XnZ1tqLXtzMoUzmB34ZSI0u/G0KFDpXLlyuLn5ydly5aVRx55RH788UcRsV4ApbYw4MqVK/L6669L9erVxd/fX8LDw6Vdu3ayZMkSm7bjbCdPnpSXX35ZatSoIUFBQVKqVClp2rSpvP/++xbbPev9+++/8sILL0jlypXF19dXwsLCpFmzZvLhhx8aqjaqfaD6+++/5ZVXXpHGjRtL6dKlxdvbW0qUKCF169aVp59+WubPn2+xVFeLD9Njx47JF198IX369JEGDRpI+fLlxcfHR0JCQqRatWryxBNPyNy5cws8JwWxtd2yVteR/hszb29vk2ZMWlLz/87/8H716lV56623pHbt2hIUFCShoaHSunVrWbRokdV9sXBK/YuKI/e5q+6NvC5fvizvv/++tG3bVsqWLSu+vr4SGBgoVatWlSeffFK+/fZb1VXvN2zYIM8884xUrVpVAgMDpUSJElKrVi3p2bOnLFmyRDIyMsyu5+i9p9V1biutYkZGRoZ88MEH0rx5cwkLCxM/Pz+JioqSPn36yIYNGxzKo9rrfOPGjRIfHy+PPPKI1KhRQ8LCwsTHx0dKlSol9evXlyFDhpitqu6sY9LqZVqLz04ttpGQkCADBw6UunXrGs5HxYoVpXPnzjJnzpwCCx+1jA2ujGn2sufzTQ0tn6Xs5Y7zqWXhlFbHoNV5cMf51Lt06ZK88sorFj8D8vbpkr8ZkpbPRIW5cMpVfvzxR+nfv7/ce++9UqJECaNzV7FiRavdmeT13nvvCQD5/vvvnZxjbTl6H9jy7O3Me07NM4sznpU9NR7t2rXL0Jdbnz59bF5fX5vd19fXYrcchZFOxMrY0URERdTnn3+Or776CgcPHsTYsWMxYcIEd2eJiMhtGBOJ1Bs8eDDmzJmDqKgozxsNqwh45plnsGjRIgDA7Nmz8eyzzxa4Tt++fbF06VKcPn0aUVFRRssY/4gKB8vjeBIRFTIrVqxAZGQkSpcujalTpzq0rYiICMTHx6N79+7aZI6IyMUYE4lc7+bNm/juu+8AAC1atHBzboqnTz/9FKVKlQKgFBSOGTOmwHWSkpJQtmxZk4IpgPGPqLBg4RQReYT09HQ8//zz+PDDD7FgwQJ88MEHOHjwoN3b6969O7p27YrQ0FANc0lE5BqMiUTOcfz4cVhqWJKTk4OhQ4fi8uXLAIDY2FhXZo3+4+Pjg+zsbMPfH330EQ4cOGAx/Y0bN/DPP/+gcePGZpcz/hEVDj7uzgARkRo3b96EiKBBgwYICQlBqVKljB5MiIiKE8ZEIueYOHEifv/9dzz11FNo3rw5ypUrh5s3b+LAgQP46quvsG/fPgBA+/bt0aVLFzfntni6efMmfHx88PbbbyMtLQ0LFy7E6dOn0aBBA7PpDxw4gNzcXIuFU0RUOLDmFBUpu3fvxoABA1C5cmX4+/ujTJky6NKlC7Zs2eLWfGVkZGDUqFGIjIxEQEAAGjVqhKVLl6paNz09Ha+//jo6duyIsmXLQqfTmW0Lv3HjRuh0OrPTzp07re5j9uzZ0Ol0CAkJcSjvjhxnQcqVK4fu3bujfv36qFq1Kvr06eO2h4x33nkHderUQW5urmFeUlISunTpgkqVKiEwMBBhYWF44IEHDH0i2GPOnDmoWLEiMjMztcg2FUPFOSbqbd26FY8++ihKly6NwMBAVK9eHRMnTjRKo/b+3bBhAwYNGoRatWohODgYFStWRLdu3bB3716T/ToSk9VwR0zMzMzEoUOHTKZhw4ahWrVqOHDggGFet27dLB6/vedA65ho6XjUTHfu3PHYfRdV+c/p0qVL0a1bN0RGRsLPzw+lSpVC69atMX/+/ALP6ZEjRxAXF4dHHnkE9913Hx588EEMHTrUUDD14IMPYtmyZdDpdDbn0xXxb8CAAarvP7VxzdaY5opnwokTJ+KTTz7B0KFDrRYUtmjRAiKC9957T5P952XumVDt/8nWzzO1+PxIHsudvbETaWncuHHi5eUl7du3l3nz5smGDRtk3rx50qBBA/Hy8tJ8NC9bxMTESKlSpeSLL76QDRs2yODBgwWALF68uMB1k5OTDSOS6dczN9JQYmKiAJDJkyfLjh07jKb09HSL2z9z5oyEhoZKZGSkBAcHO5R3R45Tjf79+xtG+vjpp5/Mpnn44YfF39/f7DRu3DiT9M8++6xNIzedPXtWgoODZfny5UbzExMTZciQIbJw4ULZsGGD/PDDD/LUU08JAJk4caJNx6l3584dqV69uowfP96u9al4K+4xUURk8eLF4uXlJU899ZR8//33smHDBvnqq68kPj7eKJ3a+7dXr17Srl07mTlzpmzcuFGWL18uLVq0EB8fH1m/fr3JNu2JybZwdUzUH5M906pVq2THjh0SHh4uFStWlOzsbJuPV+uY6MjxODpymjv3XVRpdU7/+usveffdd6Vt27ZStWpVCQkJEX9/f4mMjJTHH39cFi9eLDk5OXbn0xXx79ixYyZxx9L9pzau2RrTivMzodr/ky2fZ7bg8yN5KhZOUZEwfvx4ASAffPCBybJbt25JtWrVJDQ0VK5fv+7yvP34448CwDD8sF5MTIxERkYW+ICem5srubm5IqIMbVxQ4VT+D8iCPPbYY9K1a1eJjY01KZyyJe+OHmdBtm7dKjqdTrp06SIAZMqUKQ5tT8/WB5HXX39dKlasqPrBtHnz5hIdHW1n7kQ+/PBDCQ0Ndfqw2VS0MCYqBe/BwcEydOhQu/Oa//69cOGCSZr09HQpX768tG/f3mi+vTFZLXfEREdf/jdu3CgAzL4UqqVlTGThVNHiCefUVfHPHEv3n9q4ZktMK+7PhGr/T478PwvC50fyRGzWRx5v586dmDRpEmJjY/Hqq6+aLPf398fzzz+P1NRUrF+/3uX5W716NUJCQtC7d2+j+QMHDsS5c+ewa9cuq+vrq0w7w6JFi7Bp0ybMnDnT7HJb8u7ocVqTk5OD4cOHIyoqCvPnz4e3tzeSkpLs3h4AZGdn49atW8jJyTH63Zrbt29jzpw56NevH7y81IXP8PBw+PjY373f008/jbS0NM2qwlPRx5iomD17NjIzM/HGG2/Yndf892+5cuVM0oSEhKBOnTouHU7eXTGxbdu2EOWLTYgIsrKyUKZMGbz22mtG881NVapUwZw5c6DT6TBo0CC786llTMx/PLZMVapU8dh9F1Vt27bFjh074OXlhdjYWIvn7/333wcArFy50uXn1J3PhJbuP2fEteL+TKj2/+TMZ3w+P5InYuEUebyJEydCp9PhnXfesZjmnnvuAQCcOXNG9XZFBNnZ2aomaw4dOoTatWubFFDoO208dOiQ6jypMWzYMPj4+KBkyZLo1KkTtm7dajbdxYsXMWrUKLz33ntmh9W1Ne/OPM4vvvgCSUlJ+OCDD1CmTBlUr17d4QeRSZMmITAwEPPmzcO7776LwMBALFy40Oo6u3btwpUrV9CuXTuLaXJzc5GdnY1Lly5h5syZ+OWXXxx6Oa5QoQJq1aqFH3/80e5tUPHCmKjYvHkzwsLC8Ndff6FRo0bw8fFBuXLl8MILLyAtLc3sOvbcv6mpqdi3bx/q1q1rdrnamGwLT4qJeqmpqVixYgXat2+PqlWr2p1PxkSyhvHPPFvvP2txTU1M4zOh+zFWkidi4RR5tNTUVPz666/o2LEjKlWqZDFdRkYGACA4OFj1tjdt2gRfX19V08mTJy1u58qVKwgLCzOZr5935coV1XmyJjQ0FC+99BK+/PJLJCYm4pNPPsHp06fRtm1b/PLLLybpX3zxRdSsWRNDhw7VJO/OOs5Lly7h7bffRps2bdCnTx8AysPN0aNHcePGDbu2CQATJkww+TZ1wIABVtfZsWMHAOC+++6zmObFF1+Er68vypUrh5dffhmffvophgwZYnc+9fvbtm2bQ9ug4oEx8a6zZ8/ixo0b6N27N/r06YPffvsNr732GhYsWIBHH33U7FDx9ty/w4YNQ2ZmJsaOHWs039aYrJanxUS9hIQE3Lx5E88++6zdedRjTCRzGP8ss/X+MxfXbIlpfCYsHBgrydPY39aEqBA4ePAgsrOzUb9+favp9B8gloaYNadJkybYvXu3qrSRkZFWl1ursqtVdd7GjRsbjdTUqlUr9OjRA/Xr18frr7+OTp06GZatXLkSP/zwA/bv31/g/m3JuzOO880330RaWho+/fRTw7wGDRrgm2++wYEDB9CiRQu7tmuPc+fOQafTITw83GKat956C4MHD8bFixfxww8/YPjw4cjMzDTbvEqtcuXK4eLFi8jOznaoiSAVfYyJd+Xm5uLWrVuIi4vDm2++CUBp9uPn54dRo0Zh/fr16NChg9E6tt6/b7/9NhYvXozPPvsMTZo0MVpmS0y2hafFRL05c+agTJky6NGjh8P7ZUwkcxj/LLPl/rMU12yNaXwmdD/GSvI0vErJo+mbZpQtW9ZimvT0dCQkJKBq1apo2rQpAKBbt25Gfa1kZmZiy5YteOihhwzzQkJC0KhRI1X5sBbwy5QpY/YboqtXrwKA2W+WtFKqVCk89thj+OKLL3Dz5k0EBgYiIyMDw4YNw4gRIxAZGYnr168DUNrOA8D169fh6+uL4OBgm/LujOP8/fffMXfuXPTv3x+VKlUy5FVfJT8pKcmlDyI3b96Er68vvL29LaapVKmS4RvbRx99FAAwZswYxMbGWr1OrQkICICI4NatWwgJCbFrG1Q8MCYa7+fo0aMmL0ydO3fGqFGjsG/fPpPCKVvu3/j4eEyaNAnvvvsuhg8fripP5mKyLTwxJgLAgQMHsGfPHrz00kvw9/d3eL+MiWQO4595ttx/tsY1SzGNz4SFA2MleRo26yOPpu8ryVoV6qlTpyI9PR1xcXGGb2q+++47ZGRkICMjA88++yx69uyJBx54wGg9rapw169fH0eOHDHph+DgwYMAgHr16tlx5Orpm67oj/3y5cu4cOECPvroI5QuXdowJSQkIDMzE6VLl8bTTz9tc961Ps7c3FwMGzYMIoL58+cb5bVfv34A4HAfA7YKDw/H7du3kZmZqXqdZs2aITs7GydOnLB7v1evXoW/vz8fLKhAjIl3WaoVoY+JagY1sHT/xsfHY8KECZgwYQLeeustm/KVPyar5ckxcc6cOQCAwYMHa7JfxkQyh/HPPLX3n71xzVxM4zNh4cBYSZ6GNafIo9WvXx/VqlVDQkICJk6ciNKlSxstX7RoESZPnownn3wSsbGxJuuPGTMGR48exbfffmvyzYdWVbh79OiBr776CitXrjS0jweA+fPnIzIyEs2bN1e1D3tcu3YNa9asQaNGjRAQEABA6SAxMTHRJO17772HTZs24aeffjJUUbYl71of51dffYU9e/YgPj4erVu3Nln+xBNPuPxBpFatWgCA48ePq24OkJiYCC8vL8M3e/Y4ceIE6tSpY/f6VHwwJt71xBNPYNasWfjpp5+MmqKsXbsWAFR9w27u/p04cSImTJiAcePGIS4uzqY8mYvJanlqTMzKysKiRYvQrFkzzV68GRPJHMY/U2rvP3vjmqWYxmfCwoGxkjyOEHm4DRs2SEBAgFSrVk1mzZolGzZskCVLlsjjjz8uAGTAgAFy+/Ztk/Xi4+OlXbt2cvPmTafnMSYmRkqXLm3I33PPPScAZNGiRYY0GzduFG9vb4mPjzdZf+3atbJ8+XL5+uuvBYD07t1bli9fLsuXL5fMzEwREenbt6+88cYbsnz5cklMTJRZs2ZJzZo1xcfHR9atW1dgHmNjYyU4ONiuvNuT1porV65ImTJlpGXLlpKbm2s2Tbt27SQoKEhycnJs2rYjTp06JQDkyy+/NFn23HPPySuvvCLLli2TjRs3yooVK6RPnz4CQF577TW795mTkyOhoaEyevRoR7JOxQhjYqYhXdeuXcXf318mTpwo69atkylTpkhAQIA89thjRttTe/9++OGHAkAeeeQR2bFjh8mUl6MxOS9PjIl6S5cuFQAya9YsTfbJmEjWMP5lGqVVc/+pjWu2xrTi/Ewoov7/ZMv/0xaMleSJWDhFRcIff/whTz75pJQvX168vLwEgFSuXNniC8BHH30kDzzwgKSnp7skf+np6TJy5EipUKGC+Pn5SYMGDSQhIcEoTWJiogCQuLg4k/UrV64sAMxOycnJIiIyZcoUadSokYSGhoq3t7eULVtWevToIb///ruqPFoqnFKTd3vSWjNkyBDx8fGRgwcPWkwzatQoASBHjhyxefuOaNWqlTz66KMm87/++mtp1aqVhIeHi4+Pj5QqVUratGkjCxcudGh/69evFwCyd+9eh7ZDxQtjouLGjRvyxhtvSHR0tPj4+EilSpVkzJgxcuvWLaPtqb1/27RpY3G/+b/vczQm5+WJMVEvJiZGgoODJS0tTZP9MSZSQRj/7lJz/6mNa7bGtOL8TCii/v9ky//TFoyV5Il0ImbGUibycM888wyWLVuG7du3Gzq81Pv8888xe/ZsbNiwAaGhoW7KIXkqfRX1f//9FxUrVnT6/p555hmcOHGCQwGTQxgTyVkYE6mwY/wjZ3F1/LMFYyV5IhZOUZGUlpaGhg0bws/PD/v27UNwcLBhWalSpXDr1i2j0VQSExNx//33uyOr5GFEBC1btkSTJk0wY8YMp+7r+PHjqF27NjZs2GA0ahCRrRgTyVkYE6mwY/wjZ3Fl/LMFYyV5KnaITkVSyZIlkZycbHaZfuhZInvodDp89dVX+P7775Gbm6tqxC97nTp1CjNmzOCDBTmMMZGchTGRCjvGP3IWV8Y/WzBWkqdizSkiIiIiIiIiInKbwlG8S0RERERERERExRILp4iIiIiIiIiIyG1YOEVERERERERERG7DwikiIiIiIiIiInIbFk4REREREREREZHbsHCKiIiIiIiIiIjchoVTRERERERERETkNiycIiIiIiIiIiIit2HhFBERERERERERuQ0Lp4iIiIiIiIiIyG1YOEVERERERERERG7DwikiIiIiIiIiInIbFk4REREREREREZHbsHCKiIiIiIiIiIjchoVTRERERERERETkNiycIiIiIiIiIiIit2HhFBERERERERERuQ0Lp4iIiIiIiIiIyG1YOEVERERERERERG7DwikiIiIiIiIiInIbFk4REREREREREZHbsHCKiIiIiIiIiIjchoVTRERERERERETkNiycIiIiIiIiIiIit2HhFBERERERERERuQ0Lp4iIiIiIiIiIyG1YOEVERERERERERG7DwikiIiIiIiIiInIbFk4REREREREREZHbsHCKiIiIiIiIiIjchoVTRERERERERETkNiycIiIiIiIiIiIit2HhFBERERERERERuQ0Lp4iIiIiIiIiIyG1YOEVERERERERERG7DwikiIiIiIiIiInIbFk4REREREREREZHbsHCKiIiIiIiIiIjchoVTRERERERERETkNiycIiIiIiIiIiIit2HhFBERERERERERuQ0Lp4iIiIiIiIiIyG1YOEVERERERERERG7DwikiIiIiIiIiInIbH3dngDxTbm4uzp07hxIlSkCn07k7O0TkIiKC9PR0REZGwsuL32/oMSYSFU+MieYxJhIVT4yJ5AgWTpFdzp07h+joaHdng4jc5PTp04iKinJ3NgoNxkSi4o0x0RhjIlHxxphI9mDhFNmlRIkSAJTAU7JkSTfnhohcJS0tDdHR0YYYQArGRKLiiTHRPMZEouKJMZEcwcIpsou+inbJkiX50EFUDLGZhjHGRKLijTHRGGMiUfHGmEj2YENQIiIiIiIiIiJyGxZOEREREREVUZs3b0bXrl0RGRkJnU6Hb7/9VvW627Ztg4+PDxo1auS0/BEREQEsnCIiIiIiKrIyMzPRsGFDzJgxw6b1UlNT0b9/f7Rv395JOSMiIrqLfU4RERERERVRnTt3RufOnW1eb8iQIejXrx+8vb1tqm1FRERkD9acIiIiIiIig7lz5+L48eOIi4tTlT4rKwtpaWlGExERkS1YOEVERERERACAo0eP4s0338TixYvh46OukcWUKVMQGhpqmKKjo52cSyIiKmpYOEVERERERMjJyUG/fv0QHx+PGjVqqF5vzJgxSE1NNUynT592Yi6JiKgoYp9TRERERESE9PR07NmzB/v378fw4cMBALm5uRAR+Pj44Ndff8XDDz9ssp6/vz/8/f1dnV0iIipCWDhFREREREQoWbIkDh48aDRv5syZ2LBhA1asWIGqVau6KWdERFTUsXCKiIiIiKiIysjIwLFjxwx/JycnIykpCWFhYahUqRLGjBmDs2fPYsGCBfDy8kK9evWM1i9XrhwCAgJM5hMREWmJhVNEREREREXUnj170K5dO8Pfo0ePBgDExsZi3rx5SElJwalTp9yVPSIiIgCATkTE3Zkgz5OWlobQ0FCkpqaiZMmS7s4OEbkI733zeF6Iiife++bxvBAVT7z3yREcrY+IiIiIiIiIiNyGhVNEREREREREROQ2LJwiIiIiIiIiIiK3YeEUERERERERERG5DQuniIiIiIiIiIjIbVg4RUREREREREREbsPCKSIiIiIiIiIichsWThERERERERERkduwcIqIiIiIiIiIiNzGx90ZICrscnKALVuAlBQgIgJo1Qrw9nZ3roiIiIiIiIiKBhZOkVN5esHOqlXASy8BZ87cnRcVBXzyCdCzp/vyRURERERERFRUsFkfOc2qVUCVKkC7dkC/fsrPKlWU+Z5g1SqgVy/jgikAOHtWme8px0FERERERERUmLFwipzCVQU7OTnAxo1AQoLyMydHm3VzcpQaUyKm6+nnjRpl2/6IiIiIiIiIyBSb9ZHmCirY0emUgp1u3Rxr4udIk7uC1t2yxbRgLf9xnD6tFGp5e6tvtujpzRyJyHGFNQ4U1nwRERERUdHHmlOkObUFO1u22L8PR2pmqVk3JUVdPp580nKzxfw1s1ascG0zx99//x2dOnVCiRIlEBISgnbt2mHbtm1GaTZs2IBBgwahVq1aCA4ORsWKFdGtWzfs3bu3wO3buu7+/fvRvXt3REZGIigoCLVq1cI777yDGzduGNIkJSWhS5cuqFSpEgIDAxEWFoYHHngAixYtcuxkEBUShbW5syvy5UhNVy1t3boVjz76KEqXLo3AwEBUr14dEydONCzXIg6pib8AMGDAAOh0OovTzp07DWk3btyoKh0RkS0Kionp6el4/fXX0bFjR5QtWxY6nQ4TJkywaR8ZGRkYNWoUIiMjERAQgEaNGmHp0qUm6Wzdl5pnSyLyHCycIs2pLdhRmy4/R5rcqV23XDl1ebl61fhvfQHX66+bvuj17u26/qt2796N1q1b4+bNm1i4cCEWLlyIW7duoX379tixY4ch3eeff46TJ0/ipZdewtq1a/HJJ5/g4sWLaNGiBTZs2GB1H7ase/jwYbRs2RInT57E9OnTsWbNGjz11FN455130LdvX0O669evIzo6GpMnT8batWuxYMECVKlSBc888wwmTZqk7UkicrHC2o+d1vkyVwhVWArllixZgjZt2iA0NBQLFizA2rVr8cYbb0DyfCg4GofUxl8AePvtt7Fjxw6TKTw8HBUrVsT9999vsv3JkyebpK9Xr57jJ4eIih01MfHKlSuYNWsWsrKy0L17d7v207NnT8yfPx9xcXH46aefcP/996Nv375YsmSJUTpb9qX22ZKIPIgQ2SE1NVUASGpqqsmyxEQRpajH+pSYaN++Hdm+2nV/+00kKkpEp1OX3pFJpxOJjhbJzrbvfJjTqVMnKV++vGRmZhrmpaWlSXh4uLRs2dIw78KFCybrpqenS/ny5aV9+/ZW92HLumPHjhUAcuzYMaP5zz//vACQq1evWt1X8+bNJTo62moacg1r935xVtB5yc5WYoor44AaWudr5UrT7ZUpY3nbOp2yjiucOXNGgoODZejQoXatrzYOqY2/lmzcuFEAyLhx44zmJyYmCgBZvny57Zknp2FMNI/npfBTGxNzc3MlNzdXREQuXbokACQuLk71fn788UcBIEuWLDGaHxMTI5GRkZKd5wPGln05+mxJzsF7nxzBmlOkuVatlP6bdDrzy3U6IDpaSWcPR2pmqV334kWl/ynA8nEoZgDQWZmCANy2ui8tmjnmt23bNrRt2xZBQUGGeSVKlEDr1q2xfft2pPx3IsqZqSIWEhKCOnXq4PTp01b3Ycu6vr6+AIDQ0FCj+aVKlYKXlxf8/Pys7is8PBw+PqZd5P3111945plnUKVKFfj7+6N8+fLo2LEj/v77b6vbI3I1VzR3toeW+bpbA8s4Ll65Yj4uunpwidmzZyMzMxNvvPGGXetbikP5qY2/lsyZMwc6nQ6DBg2yK58AYyNRYTJjxgyrzXeDgoJw+7b1Z0VnUBsT9fm01+rVqxESEoLevXsbzR84cCDOnTuHXbt22bUvW54tGROJPAMLp0hz3t6WC3b0f0+fbn9HuxER9qezZd2ePZV+oipWNF4WFpb3r64Advw3zfxv3rQ883YCsF7woqd/XxERZGdnq5osuX37Nvz9/U3m6+cdPHjQ4rqpqanYt28f6tatqyrfataNjY1FqVKlMHToUJw4cQLp6elYs2YNvvzySwwbNgzBwcFG6XNzc5GdnY1Lly5h5syZ+OWXX0weno4ePYr7778fqampmDZtGtatW4dPPvkEERERJtsjcjdnN3e2l1b5Mm4yrT4uqi380iIubt68GWFhYfjrr7/QqFEj+Pj4oFy5cnjhhReQlpZmkl5NHDLH0fi7YsUKtG/fHlWrVjWbZtiwYfDx8UHJkiXRqVMnbN261Wg5YyNR4dK1a1dDE9yZM5WYOG3aNMO8nTt3FvglXX7uiIn2OnToEGrXrm1SuN+gQQPDcnuofbZkTCTyIG6uuUUeSk2VTXPNO6KjHW/CoW+GYqnJnbVmKPasm52tNAdcskT5+dtvlprA/E8ACHDKzLKLAjwqQJAA1QX41STNuHH67Sf+t52Cp+TkZLPnqFGjRlKjRg3JyckxzLtz547cc889ZqtW5/X000+Lj4+P7Nmzx+b/jbV1jxw5IrVq1TLK/8iRIw3Vt/MaMmSIIY2fn5/MnDnTJE1cXJwEBQUZHSM5H6trm1fQeXF2c2d7aZUvy9tRFxcrVKguv/76q5XtOx4Xa9asKQEBAVKiRAmZPHmyJCYmytSpUyUwMFAefPBBk1ikJg6Z40j8/fzzzwWAJCQkmCzbt2+fvPTSS7J69WrZvHmzfP3111K7dm3x9vaWn3/+2ZCOsdG1GBPN43kx73//U2LiqVOnTJZdvHhRHn30UQkKCpLq1QtfTBSxr1lf9erVpVOnTibzz507JwBk8uTJZtdTsy81z5aMia7Fe58cUXD9dCrUNm/ejA8++AB79+5FSkoKVq9eXWAHgosXL8bUqVNx9OhRhIaG4pFHHsGHH36IMmXKaJq3nj2Bbt20H5pcXzOrVy+lJpa+aQhQcM0se9b19gbatr37d06O0mzx7Fnj9YEkAGEAos3kehiACgAuAfgNwJMAjgG4e84nTVKmyMgmeP/93Xj4YWtnQREZGWl2/ogRI/Dss89i+PDhGDt2LHJzcxEfH49///0XAODlZb7S5Ntvv43Fixfjs88+Q5MmTQrOgMp1T548ia5du6J8+fJYsWIFypYti127dmHSpEnIyMjAnDlzjNK/9dZbGDx4MC5evIgffvgBw4cPR2ZmJl599VVDmvDwcNy4cQMDBw7E888/jxYtWsCb495TIaVv7mwaNxQ6nbLc3ubO7s6X5ZpVSVATF4cP/w1PPvkkjh07ZvazqEmTJti9e7f1TPzHUlzMzc3FrVu3EBcXhzfffBMA0LZtW/j5+WHUqFFYv349OnToYEivJg6ZY2/8BZQmfWXKlEGPHj1MljVu3BiNGzc2/N2qVSv06NED9evXx+uvv45OnToBYGwkKsySkpIQFhaG6GjTmDhs2DBUqFABly5dwm+/Fb6Y6AhrTfXsbTKo9tmSMZHIg7i7dIwcs3btWhk7dqysXLlSAMjq1autpt+yZYt4eXnJJ598IidOnJAtW7ZI3bp1pXv37jbttzCUijtSM8vRWl0rV97tzPfuNu4X4GEztQPSBfDNV3OgjQBzLNQ0yBXgjnzzzR25c+eO3Lp1R3777Y4sXKj8vHVLmX/nzh2reXzvvfckJCTE8E3SAw88IG+88YYAkC1btpiknzBhggCQd999V91JsGHdPn36SLly5SQjI8No/tdffy0AZOPGjVa3/8ILL4iPj49cvHjRMO/OnTvy3nvvGb4xK1u2rIwcOZLf1DhZYbj3CyO1tUlN44brOwZ3Rr4s15wqOC5GRSk1UmvXbiOvvTbHbK3X3NxcQ9wraLKkRYsWAkD27dtnNP/vv/8WAPL+++9bPUZzccgSW+OviMgff/whAOSll14qcPv58wVAbty4ISKMja7GmGgez4t5999/vzz88MMm89PT08XX19eoRlWbNm1kzpw5ZrfjrphoT82pFi1ayP33328y/9ChQwJAvvzyS7PrFbQvtc+WjImuxXufHME+pzxc586dMWnSJPTs2VNV+p07d6JKlSoYOXIkqlatioceeghDhgzBnj17nJxT7fXsCZw8CSQmAkuWKD+Tk5X5zlxXv75xf1QC4BBCQhrhtdeU2gZ3vwg6CiAExjUH6gP408LWNwHwxZNP+sLX1xcBAb7o0MEXzzyj/AwIUOb7+vri5MmTFvP4xhtv4PLlyzh48CBOnjyJ7du349q1awgODjap2RQfH48JEyZgwoQJeOutt9SdBBvWTUpKQp06dUza9uuHSS+ov4FmzZohOzsbJ06cMMzz8fHBG2+8gSNHjuD06dN44YUX8Omnn+Ldd9+1Kf9ErmKpH7uoKGW+2vhTGPNlfiAMJS4CjcyscTcu3rwJdOgAHDlSHx988CeqVFE6V89r06ZNhrhX0GQpLur7N8lP/qsyZq1GE2A+DlliS/zV03/LP3jw4AK3by7/+toHjI1EhZOI4NChQ2jUqJHJsqNHjyIkJMSoRlX9+vXx55/mnxULQ0xUq379+jhy5IhJ/1f6/vfq1atn13bVPlsyJhJ5DhZOFTMtW7bEmTNnsHbtWogILly4gBUrVqBLly5W18vKykJaWprRVBjom9z17av8tKWWriPrAsYFXF9+eRXATbz7blVMnZr/RS8DQElERwPffKOkf/DBkv/NN6cJgN0FTu+/v9tiVW09f39/1KtXD5UrV8apU6ewbNkyPPfccwgMDDSkmThxIiZMmIBx48YhLi7OpnOgdt3IyEj8+eefyMgwPuYdO3YAAKKioqzuJzExEV5eXrjnnnvMLo+KisLYsWMRGBhotfNPKh42b96Mrl27IjIyEjqdDt9++22B62RlZWHs2LGoXLky/P39Ua1aNXz99dea583RgnFncTRf5gfCUOIioHTsbdwyJQNeXiUBAFeu6OcpcfHsWaXpdd4CKn0TFjWTpbj4xBNPAAB++ukno/lr164FALRo0cLqMRYUh/JTE3/1srKysGjRIjRr1symF7Vr165hzZo1aNSoEQICAkyWMzYSFR5Xr17FzZs3zQ52kJGRgZIlSxrNK1mypMlzk15hiIlq9ejRAxkZGVi5cqXR/Pnz5yMyMhLNmze3a7v2PFsyJhIVbuxzqphp2bIlFi9ejD59+uDWrVvIzs7G448/js8++8zqelOmTEF8fLyLcuk59AVcTZv6Y/hwX6xfvw6NGjVA+/YNcfJkKLZsAXbsCMGUKWlITr5bABYcnAal1oA5JQA0tbpfnQ6YMQN45RXzyw8dOoSVK1eiadOm8Pf3xx9//IH33nsP1atXx8SJEw3pPvroI4wfPx6PPPIIunTpgp07dxptJ++DyaZNm9C+fXuMHz8e48ePt2ndUaNGoXv37oiJicHLL7+M8PBw7Ny5E1OmTEGdOnXQuXNnAMDzzz+PkiVLolmzZihfvjwuX76M5cuXY9myZXjttddQtmxZAMDw4cORmpqKmJgYVKpUCZcuXcKMGTPg5+eHIUOGWD13VPRlZmaiYcOGGDhwoOHhuyBPPvkkLly4gDlz5uDee+/FxYsXnfbgmr8fO63l5NjX15+j+dLXwHrpJeDMGQDwB+CLgIB1eOutBhg2rCEOHAhFSgqQmhqCF1/M/yWHEhf1fV899xwQGqrkqUSJEmja1HpcLEjHjh3RtWtXvPPOO8jNzUWLFi2wZ88exMfH47HHHsNDDz0EQH0cAkzjIqA+/ub17bff4urVq1ZrTfXr1w+VKlVC06ZNER4ejqNHj+Kjjz7ChQsXMG/ePACMjUSFmb+/P3x9fbFu3To0aNAADRs2RGhoKAAgJCTE5IvftLQ0hISYf1Z0ZUwElAKszMxMpKenAwAOHz6MFStWAAAeffRRBAUFATAfEzt37oyYmBgMHToUaWlpuPfee5GQkICff/4ZixYtMun/Se2+1DxbMiYSeRi3NiokTUFFn1N//vmnREREyNSpU+WPP/6Qn3/+WerXry+DBg2yut6tW7ckNTXVMJ0+fZrtifOZNm2aREZGCgD5+++/DfP1/QicPn3aMK9Ro7ZW+pxSP3388d1RBPP20/L3339L69atJSwsTPz8/OTee++VcePGmbTLb9OmjaFPFHNTXvqRYfRt/21ZV0Rkw4YN0rFjR6lQoYIEBgZKjRo15JVXXpHLly8b0nz99dfSqlUrCQ8PFx8fHylVqpS0adNGFi5caLStzz77TFq1aiXlypUTf39/qVq1qgwaNEiOHz9u43+NbOVpfQmoiYs//fSThIaGypUrV+zeT2E5L+b604uKcm1/VnlHOH3xRfNxce1afZ9Tp/Pk1Xxc1DL/N27ckDfeeEOio6PFx8dHKlWqJGPGjJFbt24Z0qiNQyKmcVFEffzNKyYmRoKDgyUtLc1imilTpkijRo0kNDRUvL29pWzZstKjRw/5/fffDWkYG12vsNz7hQ3Pi3m2PCu2bdvWYp9TWlETE0VEKleubPF5L+9ogOZioohyfCNHjpQKFSqIn5+fNGjQwOyopLbsS6TgZ0vGRNfjvU+O0ImYG5+HPJFOpytwtL5nnnkGt27dwvLlyw3ztm7dilatWuHcuXOIiIhQta+0tDSEhoYiNTXVpBoymerduzdCQ0Px2WefYf369XjmmWcQGHgU58+Hmx0hyx5RUUqzGnc3D6KizdPufTVx8cUXX8Q///yDpk2bYuHChQgODsbjjz+OiRMnmm2CBSjNsLKysgx/p6WlITo62q3nZdUqpTlc/piib2bnzn6t8ktIAPr16w0gFMBnANYDeAZKX1ThRmkLY/6J9DwtJroKz4vtzD0rHj16FOHh4QWvTFRI8N4nR7BZXzFz48YN+PgY/9v11WlZTuk8M2fORGxsLMqUKYOKFSti2bJlyMgIR69eyotX3lOf/2+1zp4FnngCiI8Hqle3rTkPUXF24sQJbN26FQEBAVi9ejUuX76MF198EVevXrXY71Rha+qck6M0pzMXO0SUuDJqFNCtm+Mxwd5mg3kp34PMBBALoAyAigCWIX/BlDPyT0TFixYxyxXMPSuyYIqIihPWnPJwGRkZOHbsGACgcePGmDZtGtq1a4ewsDBUqlQJY8aMwdmzZ7FgwQIAwLx58/Dcc8/h008/RadOnZCSkoJRo0bBy8sLu3btUr1floprY9WqvP2zKKKjgY8+AkaPVgqcHLlDWZuKtOZp976amlMdO3bEli1bcP78eUP/H6tWrUKvXr2QmZlpsQPrwlRzauNGoF27gtMlJjrWr5S5mGVPnMnJAapUsT3GJSYqL5ae8KJJxYOnxURXKSznRauYRUTqFJZ7nzwTa055uD179qBdnjeS0aNHAwBiY2Mxb948pKSk4NSpU4blAwYMQHp6OmbMmIFXXnkFpUqVwsMPP4z333/f5Xkn5cGoWzfzL1re3jBbs8oW+lGv2ByGyLKIiAhUrFjRUDAFALVr14aI4MyZM6hevbrJOv7+/vD393dlNq1KSdE2nTmWmg3aE2f0o/vZGuO++w545hm+aBIVJc6q2aRlzCIiIudjzSmyC0vFXcPcN3620umUl7e8owUS2cvT7n01NadmzZqFUaNG4eLFi4aRkb777jv07NkTGRkZFvudysvd58XZNaf0NZ0sxSJ744xWMQ7giya5h7vv/cJK7XlxVs0mZ8UsIrKOMZEc4eXuDBCRZT17AidPKi+US5YAH39s+zZEgNOnlW8liYqDjIwMJCUlISkpCQCQnJyMpKQkQy3SMWPGoH///ob0/fr1Q5kyZTBw4EAcPnwYmzdvxmuvvYZBgwapKpgqDFq1Ul609AU1+el0SpPhVq3s2/6WLdYLkOyNM/oY99tvQFiY9bSWXiD1X7G99BKwfr3S2frGjcrLKREVXvqaTflji75m06pV9m/bWTGLiIich4VTRIWct7dS06FvX2DECOsvoNY40pyHyJPs2bMHjRs3RuPGjQEozZ0bN26M8ePHA4BJc+eQkBCsW7cO169fR9OmTfH000+ja9eu+PTTT92Sf3vom8kBpvFB//f06fbXEHBms0Fvb6B9e+Crr5S8Wsq/tcImEeVFtEMHoF8/pRZZlSrKy21OjlJYxUIrosKjoEEcAGUQBHvvV1c0dSYiIm2xzykiD2JvPy0AcPiw8mLGzoOpqGvbtq3V0UfnzZtnMq9WrVpYt26dE3PlfD17Kk3bzDWRmT7dsSYyyuh62qUzx1r+n3hCOQZb6EcwLVMGuHLFeHvso4rIvWyp2WRPU2RXxCwiItIWa04ReRj9C1zFiratN2mScW0CIip68jcFTkxU+lRxtCDG2c0G9Szlv1s327elL5/MWzAFaNNkiIgc4+yaTa6KWQBrZxIRaYWFU0QeKP8LXHy8+eYw5vDFjKhoy9sUuG1bbWpKOrvZYP595c9/QS+attCiyRAROcbZNZtcFbNWrVK+9GvXzrRJMRER2YaFU0QeKu8L3Pjx6mtT5X8x4zd+RKSGpVqbUVHOHynP2oumPfRNhj77jDGPyB1cUbPJ2TFLbYfufM4iIlJHJ9Y65iCygMOEFk45OUr/DOvXK834ChIfr3RCrPUQzlR08d43rzidF32cSUlRajW4sh87c8POO4oxjxxRnO59W6g5L/rCHcC4D019gZVWhd7OiFk5OUoNKUuxSKdTYsu0acDLL/M5i4oPxkRyBAunyC4MPIVbQoJSvdweWj8UUtHCe988nhfXyfuiWa4cMGCAUlPB3qcZxjxyBO9989SeF3MFztHRjg/ioAVrhVobNypN+OzBmENFGWMiOYKj9REVQY6MPiOiPDiNGqV0QsyR/YioMNE3adazdwRTvfwxD3BfzTCi4qZnT+W+K2z3nLlCs7w1nuztqB3gcxYRkSXsc4qoCHK08+C8QzgTERVmlvqVKVNG+akmDupj3rvvsnNjIldzxiAOjlDTl5QjXwICfM4iIjKHhVNERZCaUWrUcOSbQSIiV8k/gmliInDhArBypbqBIvTi4gru3JiIiq6cHKXGlLlamHkHlGnZUpsRRPmcRUR0FwuniIooa6PUxMer24aj3wwSEbmKudoX+kKrjz+2f7v5RzgloqJryxbrAy7oazxt367Nl4DmnrM4uh8RFVcsnCIqwszVJkhOBsaOdf4QzkREhYG3NzBiBJs6E1HB1NZkSkmx/iXgN9/Y95y1ahWbFhNR8cUO0YmKuPydB+tZ6kRY/yA1fbr7+30gItKCvqmzpZintiN1NsEhKtrU1hjXp7PWobu3d8HPWYBSOyolBTh6FJgwwTQenT0LPPGEUuu9evXC02k8EZHWWHOKqJiy9o3fihXKwxarlRNRUcGmzkRUkIIGlDFX48lSh+4FPWcBxrWk4uKs93UVF8faVERUtLFwiqgYs9TsD2C1ciIqetjUmYisUTOgjC01y609Z5kbEVAtDtRAREWRTkRtZXaiu9LS0hAaGorU1FSULFnS3dkhDemHUM4fGfQPZStWKA9bVDzx3jeP58Xz6WMfYL4JDmMfmcN73zxPPy+rVimj9uUtPIqOVgqmHI0DOTnKF372Fkzp6XRKofqxY0oH7fmbFVrbv7lmiERa8PR7n9yLfU4RkUFBQyjrdMqIVd268UGGiIoWfROc/C+kUVF3X0j5UkfkBNnZQOXKyu863d0SYa1/1+kALy/Tycz8nl5e6FHdC9fKeyHrthf8grwRVtYHukU+QII34OOj3Px5f/r4AH5+lid/fyAwEEeOB6L+mQDci0DcRCBuIAgZCEEGQpCOEriFAAAFj96gH6ghKgq4dOnu/KgopfaXuZh1+TLw8sumMU6fnojInVg4RUQGaodQ3rLFfCfrRESezFrnxuZqUvCljkgj5865OwcmdADCnLDdegDWWlmeAy9kIASpCMU1lMZ1lMI1lMY1lMZFlMN5VMAFlL/781IF6FAa8l9vLfomf6++qvQbWlANLX161g4lIndj4RQRGdgyhDIRUVFkboRTS82d+VJHpAFvb2Dfvrs3mIjl3wtabi1tbq7ye26u6WRpfm6uUv0oJ0ep4aX/ae73O3eU6fZt81NWFnDzJlLP38SxQzf/qzd1E0G4gWBkIgSZyulALkKRhlCkoRJOqzqFd+CD86iAE7gHx6UajqMaTnxwDyJQDZm4F9esFLOxZjwRFRYsnCIiA1uHUCYiKurY3JnIyXQ6oHFjd+fCZUJygO5VlMLtvHHFCzkIwg2UQDpKIB0lkYbSuIZSuI5SuI4wXEU5XEQFnEcFnEd5XEAFnEcZXIUvshGNM4jGGbTBZpN9pqACktAI+9EY+9EYSWiE46hmqG3FmvFEVBiwcIqIDPRDKOd/YNLT6ZQhkXNylKri7HOFiIo6NncmIi3pRwTs1Ut5rjJU7II3MnUlkCEl8EI8UL06cPQoMGGCstzSEFa+uI1yuIgonME9OAGl3tTdKRIpiMB5ROBndMbPhvWuoRQ2ozU2oi02oi0OoAFSUvhAR0Tuw8IpIjKw9MAE3P375k2gQ4e789nnChEVZWzuTERaUzMAg169eqbpypa92wn6HfjhLKJwFlHYhRYm+wpGBurjIBohCY2QhMbYj/o4iNK4jm74Ht3wPQClsOr2nEeBkv2Ajh0BX18nHDkRkWU6EUvl8ESWcZjQos1cx79lygBXrpim5TDrxQvvffN4XoqujRuBdu0KTpeYyJpTxRHvffN4XtRROwJo/nQtWwLVqlmu6V4Qb2SjMfb/V2dqI1phC0oi3bBcwsOhe/JJ4OmngQceuPuwR1QA3vvkCC93Z4CI7LNhwwYMGjQItWrVQnBwMCpWrIhu3bph7969qreRkZGBUaNGITIyEgEBAWjUqBGWLl2Knj2BkyeVl60lS4AffshAVtYoAJEAAgA0ArAUwN2HolGjlIcnS9skInI2Z8TFUaMaISxsqZl3swwAo6CPi6NGWY51jItEZI5+AIa+fZWflrpJyJ/Oz0+ptQ4UVG6UDuB1AB0BlIUyBuEE5MAHe3A/PsRreAw/IgxX0RLb8ClG4ALKQXf5MjBzJvDgg/g9KgqdqlVDieBghISEoF27dti2bZvRXgYMGACdTmdx2rlzp1H6/fv3o3v37oiMjERQUBBq1aqFd955Bzdu3LD5HBJR0cFmfUQe6vPPP8eVK1fw0ksvoU6dOrh06RI++ugjtGjRAr/88gsefvjhArfRs2dP7N69G++99x5q1KiBJUuWoG/fvsjNzUW/fv0MtQDuv78nMjJ2A3gPQA0ASwD0BZALoJ9RnyuTJ1vfJhGRszgrLv7xhxLvdLp+eWop9ASgxMUBA2rg33+VWJednYv/+79+BW6TcZGIHGGpaWB0NPDUU8CHHwIiVwDMAtAQQHcAs81uKwc+2IGW2IGWGI1piMFv6IslqO63Au3OnUMzAAsBSOPGmHrlCtq3b4/ExEQ88MADAIC3334bL7zwgsl2u3btCn9/f9x///2GeYcPH0bLli1Rs2ZNTJ8+HeHh4di8eTPeeecd7N27F999951GZ4iIPI4Q2SE1NVUASGpqqruzUmxduHDBZF56erqUL19e2rdvX+D6P/74owCQJUuWGM2PiYmRyMhIyc7ONkoHLJG7YzKLADECRAqQbZj32mvqtkmei/e+eTwvhYMz42JYWKRUrKiPd0q6kJAlUqaMcVz08oqUb77JVrVNxkXPx3vfPJ4X18nOFklMFFmyRPmpDykrV4pUrJgrQO5/8emSAJBeveIkMVFk0SKRsmUl37Pd3UmnEwny7yDlQ0Mls3NnEW9vEUDSAAn385OWjRpZzdfGjRsFgIwbN85o/tixYwWAHDt2zGj+888/LwDk6tWr2p0ccjne++QINusjcpCI4IsvvkD9+vUREBCAe++9FytWrEBubi7q1auHyZMnO2W/5cqVM5kXEhKCOnXq4PTp0wWuv3r1aoSEhKB3795G8wcOHIhz585h165dhnSBgSEAeufbwkAA5wDsMsw5fFjdNomoaCuKcfHq1XNISNiFxESgXbvV8PMLQUZG73x98Q1Ebu45PPnkLqxaVfA2GRfJFTZv3oyuXbsiMjISOp0O3377rdX0W7duxYMPPogyZcogMDAQtWrVwscff+yazBZRzoyJlpoG9uwJ/PuvDomJOixZAuj/7XXrKukqVrzbqbr5PAM3snaizn2PIGjtWuDvv4H/+z+U0OnQ+vZtbE9KQkrv3sCJE2bXnzNnDnQ6HQYNGmQ03/e/jtZDQ0ON5pcqVQpeXl7w8/Oz/SQQUZHAwikiB4gI+vTpg9GjR6N///5Ys2YNqlatigEDBmDevHm4du0aRo0aZXa97OxsVZMtUlNTsW/fPtStW7fAtIcOHULt2rXh42PcurdBgwaG5fqfdevWRlSUT75+DRrotwSdTqlGfvmyum0SUdFVlOPikSOH0LYtcOPGIYjUhmnvCHfjor4fPrWxlshZMjMz0bBhQ8yYMUNV+uDgYAwfPhybN2/GkSNHMG7cOIwbNw6zZs1yck6LJnfGxLwFVw8+aLxM3Qijt5Gd7Y+cHGDj6WpIeHQhds85AP+oKADAwRUrgJo1gZdfVoZz/k9qaipWrFiB9u3bo2rVqkZbjI2NRalSpTB06FCcOHEC6enpWLNmDb788ksMGzYMwcHBajJGREUQ+5wicsC8efOwfPlyLF682NBviL+/P1q3bo1XX30VU6dORVBQkMl6mzZtQjs1wz8BSE5ORpUqVVSlHTZsGDIzMzF27NgC0165cgX33HOPyfywsDDD8rzpxowBevVSOt5U+lwJ028JgDL08ZtvqtsmERVdxSEunj17BXfumKbLGxf1/fCp3SaRs3Tu3BmdO3dWnb5x48Zo3Lix4e8qVapg1apV2LJlC55//nlnZLFIK2wxUS8iQk2qOjh8eCcqV87F2bP6Og214O2t1G660qABcOCA8hD466/KKDoNGyIhIQE3b97Es88+a7LFKlWqYMeOHejRoweqVatmmD9y5EhMnz7dpmMgoqKFhVNEDpgxYwbq1atn1KFt6dKlAQAVKlTAwIEDza7XpEkT7N69W9U+IiMjVaV7++23sXjxYnz22Wdo0qSJqnV0VoZ4ybtMp9NZ7HizZEkdXnkFyMrSf2mmbptEVDQVh7ioVFSwFs+UZfqaCWpjLVFhtH//fmzfvh2TJk2ymCYrKwtZWVmGv9PS0lyRNY9QmGJiXq1aAVFRwNmzyDPQw106HRAUNAJXrjwLYDiAsVAGwolHTs6/AIA9Hd5C3/dDgYEDgcOHgWbNgPfew5wlS1CmTBn06NHDZLsnT55E165dUb58eaxYsQJly5bFrl27MGnSJGRkZGDOnDk2HwsRFQ0snCKy07Vr17B//368+eabRvNzcnIAAO+++y68LYwJHBISgkaNGqnaT/6mIObEx8dj0qRJePfddzF8+HBV2y1TpozZb+yvXr0K4O63+nnT9ewJdOum1AbYvfsqXn8d8PIKQ1ycYau4cOEKVq1S0lraJhEVTcUlLoaFlcH58+ZqPF3976eS7vBhwNe3DC5fLnibRIVNVFQULl26hOzsbEyYMAGDBw+2mHbKlCmIj493Ye48Q2GKifl5ewOffJK/VrxC/3dAwCBkZl4CMAnA5/8tfQDAqwDex6JFFTF16kPwPnAAePZZ4IcfcGD0aOwB8NLgwfD39zfZ75tvvom0tDQkJSUZmvC1bt0a4eHhGDRoEPr37482bdrYfDxE5PnY5xSRnY4dOwYRMWlLr++TIe+wuflt2rQJvr6+qqaTJ09azUd8fDwmTJiACRMm4K233lKd//r16+PIkSMmfRUcPHgQAFCvXj2z6fT9F6SkKOmuX6+Xd6u4c+cInngi29AZsLltElHRVFziYsuW9aHTHQGQv6+Xg//9VNJNmgQcPlwfe/cewfLl1rdJVNhs2bIFe/bswRdffIHp06cjISHBYtoxY8YgNTXVMKkZgKA4KCwx0RJ9rfiKFY3nR0UB8fH4b8CHNwBchhLfTgLYDuAagGBcvNgEW7YAKFsW+O47YOZMzPmvsG3wihXAjh0m+0xKSkKdOnVM+pbSnwv2w0dUfLHmFJGd9N90Xcoz1MnevXsNDxxiro70f7Sqqj1x4kRMmDAB48aNQ9zd6kuq9OjRA1999RVWrlyJPn36GObPnz8fkZGRaN68ucV0OTnAzJnzAUQCaJ53qwC+ArASo0b1QbduSmFW/m0SUdFUXOJiz549MHu2Eut0uj55ahyYj4siX+HJJ1di5co+hlqljItU2OkLVOrXr48LFy5gwoQJ6Nu3r9m0/v7+ZmvJFHeFISYWJG+t+JQUpS+qVq2Ab77Jm8of+kJ34BSAZQCeAxCI9ev16+nQLHYQFo0Zg2Z37qDe9etAhw7A6tVAx45GeT106BAyMjIQEhJimL/jv4KsqP86WyeiYkiI7JCamioAJDU11d1ZcZtbt25J2bJlJTw8XBYvXiwJCQkSEREhTz31lACQcePGyalTp5y2/w8//FAAyCOPPCI7duwwmfLauHGjeHt7S3x8vNH8mJgYKV26tMyaNUs2bNggzz33nACQRYsWWU3XpYuSDlgkSsXvvFOMAKUFmCXTplneJnkm3vvm8bwoiltcDAkpLaVKzRJggwAFx8XSpWfJunWMi0WJp937AGT16tU2r/fOO+9I5cqVVaf3tPPiLO6OiSIia9euleXLl8vXX38tAKR3796yfPlyWb58uWRmZhrS5Y+JiYkiwEEBJgiwRoB1AnwoQLgATQVIN4l1YWFLBYDM+uwzkUceUWb6+op8841hP999953odDpp0aKFLFu2TNavXy/vvvuuhISESJ06dSQrK8up54Oci/c+OYKFU2QXBh7F1q1bpUmTJuLn5yelS5eWMWPGSG5urjz//PPi6+srn3/+udP23aZNm/9ehMxPeSUmJgoAiYuLM5qfnp4uI0eOlAoVKoifn580aNBAEhISTPaVP12lSg0ESDDzAib/PayMFKCC+PhY3iZ5Jt775vG83FUc46Kvr5+UK6cuLvr6Mi4WJZ5w76enp8v+/ftl//79AkCmTZsm+/fvl3///VdERN5880155plnDOlnzJgh33//vfzzzz/yzz//yNdffy0lS5aUsWPHqt6nJ5wXV3FnTBQRqVy5ssWYmJycbEiXPyZmZ4uUL/+3AK0FCBPAT4B7BRgnQIaFWBcjQLAsWpQmkpUl0qePskCnE5k1y7CvDRs2SMeOHaVChQoSGBgoNWrUkFdeeUUuX77s1HNBzsd7nxyhE7FSn5TIgrS0NISGhiI1NRUlS5Z0d3bIxTZuBNSMbpyYqPRPRUUH733zeF4oIQHIMxiXRUuWABZaRpEH8oR7f+PGjWhn5kM7NjYW8+bNw4ABA3Dy5Els3LgRAPDZZ5/hyy+/RHJyMnx8fFCtWjU899xzGDJkCLy81HVX6wnnhQq2apXSYTpgfkQ/c3Q6pc+q5GTAGznAsGHAl18qCz/4AHj1VedklgoF3vvkCBZOkV0YeIq3nBygShXrww8bHkzMD0JDHor3vnk8L8RC++KJ9755PC9Fx6pVwEsvAWfO2LaeIdaJAGPHAlOm3N1gjx5aZ5MKCd775AiO1kdENtMPPwwoBVF56f+ePp0FU0RUfLRqpRTK54+JejodEB2tpCMi8hQ9ewInTyqFTUuWAOPGqVsvJeW/X3Q6YPJkYNQo5e/YWOCff5yQUyLydCycIiK7WBt+eMUKGEakIiIqDlhoT0RFlbe3Uguqb1+gfXt16xw+rNQozcn5b8bUqcBDDwHp6cpDYmamk3JLRJ6KhVNEZLf836YlJipN+VgwRUTFEQvtiaioK6iWqN6kSUpT5ypVlJZ88PUFvvkGqFAB+PNP4Lnn1HdkRUTFAguniMgheb9Na9uWtQKIqHhjoT0RFWXWaomac/as0qn6qlUAIiKA5csBHx9lFInPPnNqXonIs7BwioiIiEhDLLQnoqLMUi1Rc/SVo0aN+q+J30MPKaP2AcArrwDbtjkrm0TkYVg4RURERERERKrlrSVaUCfpIsDp08CWLf/NeOkloE8fIDsb6N0bOH/e2dklIg/AwikicqqcHKVDzISEfB1jEhEREZHH0tcSrVNHXfqVK/97FszVAbNnKyumpCgFVXfuODOrROQBWDhFRE6zapXSEWa7dkC/fvk6xiQiKoZYYE9ERU1EhLp0M2bkeRb8NUR5ICxRAti8GXjzTafmkYgKPxZOEZFTrFqldIB55ozxfKOOMYmIihEW2BNRUaR2BD89w7PgnzWBefOUmdOmKZ2lE1GxxcIpItJcTo7SnYC5EYJNOsYkIioGWGBPREWVrSP4GT0LdusJvP66MmP4cCAtzSl5JKLCj4VTRKS5LVtMX8DyMukYk4ioCGOBPREVdbaM4AfkexacNAmoXh24eBGYOtWp+SSiwouFU0SkuZQUbdMREXkyFtgTUXGQdwS/4cPVrZOSAsDXF3j/fWXGRx9ZD5hEVGSxcIqINKe2Y0y16YiIPBkL7ImouNCP4PfEE+rSG54Fu3cHHnoIuHULePttJ+WOiAozFk55uM2bN6Nr166IjIyETqfDt99+W+A6WVlZGDt2LCpXrgx/f39Uq1YNX3/9tfMzS8VGQR1j6nRAdLSSjoioqGOBPREVNzY/C+p0wIcfKr/Pnw8kJbkim0RUiLBwysNlZmaiYcOGmDFjhup1nnzySaxfvx5z5szB33//jYSEBNSqVcuJuaTixlrHmPq/p09X0hERFXUssCei4sauZ8HmzYGnnlLaOr/6qvmO+oioyGLhlIfr3LkzJk2ahJ49e6pK//PPP2PTpk1Yu3YtOnTogCpVqqBZs2Zo2bKlk3NKxY2ljjGjopT5Ki9ZIiKPxwJ7IiqO7HoWnDwZ8PMD1q8Hfv7ZJfkkosKBhVPFzPfff4+mTZti6tSpqFixImrUqIFXX30VN2/etLpeVlYW0tLSjCaiguTtGHPJEuVncrIyPycH2LgRSEhQfnKUKiIqylhgT0TFkbVnQbOqVgVGjFB+f+01IDvbVVklIjfzcXcGyLVOnDiBrVu3IiAgAKtXr8bly5fx4osv4urVq1b7nZoyZQri4+NdmFMqKvQdY+a1apUyrHrewViiopSaBXxBI6KiqmdPoFs3ZVS+lBSlj6lWrVhjioiKNnPPglaNHQt8/TXw55/AvHnA4MFOyhkRFSasOVXM5ObmQqfTYfHixWjWrBkeffRRTJs2DfPmzbNae2rMmDFITU01TKdPn3ZhrqkoWbUK6NXLdJTgs2eV+atWuSdfRESuoH9J69tX+cmCKSIq7kxq05csDYwfryx8+20gI8Od2SMiF2HhVDETERGBihUrIjQ01DCvdu3aEBGcyV9akIe/vz9KlixpNBHZKidHqTFlrn9L/bxRo9jEj4iIiKg4WLUKqFIFaNcO6NdP+VmlCrA64kWgWjXg/Pm7o/gRUZHGwqli5sEHH8S5c+eQkecbiH/++QdeXl6IiopyY86oONiyxbTGVF4iwOnTSjoiouKGffERUXFirTb9E339sKv7FGXGBx8Aly65PoNE5FIsnPJwGRkZSEpKQlJSEgAgOTkZSUlJOHXqFAClOV7//v0N6fv164cyZcpg4MCBOHz4MDZv3ozXXnsNgwYNQmBgoDsOgYqRlBRt0xERFRWWag+wqTMRFUVqatP3XtYLct99wI0bwOzZrs0gEbkcC6c83J49e9C4cWM0btwYADB69Gg0btwY4/9rp52SkmIoqAKAkJAQrFu3DtevX0fTpk3x9NNPo2vXrvj000/dkn8qXiIitE1HRFQUsC8+IipuVNWmP6PDXzEjlRmff86R+4iKOI7W5+Hatm0LMfeVw3/mzZtnMq9WrVpYt26dE3NFZF6rVsqofGfPmv+mTKdTlrdq5fq8ERG5Q0G1B3Q6pS++bt3YeToRFR1qa8kfqN0HtcNfVfp9+P57DutMVISx5hQRuYy3N/DJJ8rvOp3xMv3f06fzBYyIig/2xUdExZHaWvLlKwcAzz+v/PHZZ87LEBG5HQuniMilevYEVqwAKlY0nh8Vpczv1o0dAhNR8cG++IioONLXps//ZaWeTgdER/9Xm/6FF5RvLjduBA4edGU2iciFWDhF5KCMjAx4e3vjw0I4zG1qaiq8vLzw8ccfG+adO3cOOp0OX331ldvy1bMncPIkkJgILFmi/ExOVpaZ6xB48eJ0vP766+jYsSPKli0LnU6HCRMm2LTPjIwMjBo1CpGRkQgICECjRo2wdOlSu9PZmpaoOGFcVM/evvjS0xkXiTwFY6Ipm2rTR0cD3bsrM2fMMLs9xkSiIkCI7JCamioAJDU11d1ZcbuNGzcKANm8ebO7s2Lit99+EwCyZcsWw7zr16/Ljh07JD093Y05M7VypYhOJ6I0Yrk7KfOSJSgoVFq3bi2DBw8WABIXF2fT9mNiYqRUqVLyxRdfyIYNGwzbWbx4sV3pbE1bVPDeN4/nxRjjonrZ2SJRUebjnz4GRkcr6fJKTk6W0FDGRXfjvW8ez4sxxkTLVq5UYmDeuBcdrcw3snGjsjAoSOTqVZPtMCYWDrz3yREsnCK7MPDc9eGHH4q3t7dkZma6Oysm3nvvPfH29paMjAx3Z8Uq/cuZuRczZcqV0qVz5bffRM6fv2TzA8ePP/4oAGTJkiVG82NiYiQyMlKy/3vrU5vO1rRFCe9983hejDEu2kZfOJ+/gEo/z+QlTURyc3MlNzdXREQuXWJcdBfe++bxvBhjTLQuO1skMVFkyRLlp9lQkZsrUr++Ehw/+sjMYsbEwoD3PjmCzfqIHLR7927Uq1cP27dvR6tWrRAcHIx7770X//vf/4zS/f777+jTpw+qVKmCwMBAlCtXDj169MDx48eN0v3111945plnUKVKFfj7+6N8+fLo2LEj/v77b6N0W7duRceOHREaGorSpUujS5cuOHr0qEneateujeDgYMO8jh07onXr1oa/H374YbRr1w6bNm1Chw4dEBISggoVKuCdd94xe7xq9murgjoEBnS4dk2HDh2Axo1t3/7q1asREhKC3r17G80fOHAgzp07h127dtmUzta0RMUN46JtcdFaX3zLlgFhYab98Ol0OugsddaiAuMikeswJlqPid7eQNu2QN++yk/9wDg5OXn6Id2kQ+6wEcqC//3PpFNSxkQiz8fCKSIH7dmzB5cvX8Zbb72F4cOHY9WqVahduzaGDx+Ob7/91pAuKSkJDRs2xCeffIJffvkFH3/8Mf755x/0zDMk7tGjR3H//fcjNTUV06ZNw7p16/DJJ58gIiLC6KFhwoQJaNOmDaKjo5GQkIDZs2fj9OnTaN++PTIyMozydv/99xvld//+/WjSpIlRvk6ePImXX34ZsbGx+P7779G6dWvExcVh06ZNRuuq3W9eIoLs7Gyr05kz2QCyVZ1vfafAR46oSg4AOHToEGrXrg0fHx+j+Q0aNDAstyWdrWmJihvGRdvj4uOPZ+PYsWz89ls2Fi5Ufn7wQTZGjzbth2/VKnv+K8YYF4lchzHR9pi4fHk2KlfORrt22ejXT/lZI74PbgeXAk6cAH76yZ5/hUWMiUSFgJtrbpGHYpVNxdWrVwWA1K1bV27cuGGYn5mZKWFhYdKnTx+z6+Xk5MidO3dk9uzZAkCuXbsmIiJxcXESFBQkOTk5Fvf5ww8/CACZOnWq0fx//vlHAMiiRYtE5G6V5pkzZxrSnDx5UgDIwoULRUTk+PHjAkCaNGkit27dMqQ7c+aMybpq95tfYmKiAFA5JVtp2qeflOMqWTLOfLVvM6pXry6dOnUymX/u3DkBIJMnT7Ypna1pixLe++bxvNzFuOjcuGiuqZ89TVgYF7XBe988npe7GBO1jYlvYbASDDt2tHj8jInuw3ufHGFcjEtENtmzZw8AYOLEiQgMDDTMDwoKQvXq1XHhwgUAyjdCK1euxMyZM/HXX3/h/PnzEBEAgJeXl2Hd8PBw3LhxAwMHDsTzzz+PFi1awFtft/k/48ePR7Vq1fDSSy8hO/tubaOqVasiMDAQJ06cAKBU0waApk2bGtLs3bsXAHDfffcBAPbt2wcAeOedd+Dv729Id+XKFQBAZGSkzfvNr0mTJoa8WJKTAzz+OHDxYqTVdHmlpSnNAdu2VZfeWlXvvMvUprM1LVFxwbjoeFy8GxMBwDgu/neK8MILwM2bSlPA2rUtbsoqxkUi52NMtC0mGsc/UwkIwUTMgdevvwJ//w3UrGk+oR0YE4nci4VTRA7Ys2cPgoOD8fjjj5ssO3/+vKG9/vPPP4958+ZhyJAhGDlyJMqWLQt/f38MHjwYN2/eNHzYv/DCC8jMzMS8efOwYMEClC1bFn379sXEiRNRsmRJnD9/Hvv37wcAoweEvEqVKmXIm5+fn6HqMKA8YAQHB6NWrVqGv/39/dGhQwejbegfRBr/18GTLfvNLyQkBI0aNTK7LK8ZM4A+fZSQpH/5Koi+iV9BypQpY3iIyuvq1asAgLCwMJvS2ZqWqDhhXDTdb34FxcVNm/K+mJl/VLt0Cfi//1N+j4iwuCmLGBeJXIMx0XS/+eWNicbxz1QyfLAGj+Fx/AB89RXw4YeWE9uAMZHI/Vg4ReSAPXv2oFy5cibfWG3fvh3//vsvunTpgr///huzZ8/G1KlT8dprrxnSXL58GX/++SeefPJJwzwfHx+88cYbeOONN3DmzBnMmjULEydOREBAAN5//32cPn0aAPDxxx/joYceMpunatWqGfLWoEEDoweEvXv3olGjRvDy8jL83aBBA/j5+ZkcV3h4OCpVqgQANu03v02bNqFdu3Zml+X3+efJePfdKgV0jn6X2hey+vXrIyEhAdnZ2Ubt/g8ePAgAqFevnk3pbE1LVJwwLpruNz9b4iKQDKCK1RT29MXHuEjkGoyJpvvNz9aYOBcDlcKpZcuAqVMBL8e7UWZMJCoE3NmmkDwX2xMroqOjxd/f39APgIjInTt35KGHHpJatWrJnTt35JdffhEAsmbNGqN1+/XrJwBk2rRpFrd/69YtCQwMlNGjR4uIyLFjxwSATJ8+vcC8RUREyAsvvGA0r1y5cjJixAjD32XLlpWhQ4earNuiRQujNvK27De/tLQ02b17t6opKytLsrNFfvtNJCxMuz6n1q5dKwBk6dKlRvMfeeQRo6F81aazNW1R4gn3/qZNm+Sxxx6TiIgIASCrV69Wve7WrVvF29tbGjZsaNM+PeG8uArjYsEKiotffLFbAP2U5ZS++BgXtcF73zyel7sYEwuWNyYaxz9zU5b446bcCS6pBMDNm022Z0+fU4yJ2uC9T45gzSkiO126dAmnT59GtWrV0KtXL7z66qu4desWPvnkExw8eBBbt26Fj48PGjZsiKCgILz99tvQ6XS4efMmvvrqKxw7dgzA3Xb+w4cPR2pqKmJiYlCpUiVcunQJM2bMgJ+fH4YMGQJA+capXbt2GDduHDIyMtC8eXOICFJSUpCYmIjY2Fi0bdsWKSkpSElJMRp95cyZM7h48aJh9JXTp0/j0qVLRv0MAEB2djb++OMPjB492jBP7X7NKVGihMk+CtK+vVJTu1cv5W+lmd9PADIBpAMA6tY9jNWrVwAAHn30UQQFBWHTpk1o3749xo8fj/Hjxxu217lzZ8TExGDo0KFIS0vDvffei4SEBPz8889YtGiR4dtMtelsTUuulZmZiYYNG2LgwIF44oknVK+XmpqK/v37o3379oY+QMg2jIvaxMXGjYFJk4CzZwtq5mwcF9PSDmPSpBWoW5dxkagwYEy0PSaqiX8lywL/1uqJalvmIXdJArxatQIA/PTTT8jMzER6uhITDx8+jBUr+KxI5DHcWTJGnoul4iI//vijAJCdO3fKc889JyVLlpSSJUtKr1695J9//jFKu2bNGqlVq5b4+/tLnTp15JNPPpFJkyaJl5eXpKeni4jIZ599Jq1atZJy5cqJv7+/VK1aVQYNGiTHjx832lZqaqqMGTNGatSoIQEBAVK6dGlp2LChjBgxwvCt3HfffScA5I8//jCs9+233woAOXDggNHfedOIiPzxxx8CQFatWmXzfrW2cqVIVJS+ZkBliyO3JCcni8jd0V7MfVOWnp4uI0eOlAoVKoifn580aNBAEhIS7E5na9qiwtPufdhQc6pPnz4ybtw4iYuLY80pOzEuahcXV668OzKf5RpTjIvuxnvfPJ4XBWOifTFRTfzriJ9FALnsFS6rlt0WEZHKlRkT3Y33PjlCJ6K262Giu9LS0hAaGorU1FSULFnS3dmhIiwnRxmVLyVF6WOqVSuAXzS5j6fd+zqdDqtXr0b37t2tpps7dy5mzpyJHTt2YNKkSfj222+RlJRkMX1WVhaysrIMf6elpSE6OlrdeVm6FHjzTX0G82bW/E9rywpKY27y8rK+LP/k7W35dx8fZTL3u68v4Od396f+d39/ICDg7k/9FBSkTMHBys+QEKBECU36EvFUq1YBL70E1f3wAUBiovpRTMlxnhYTXYXnhRxVUPzzRjZSEIGyuIxO+BkPxndC9ep8VnQ33vvkCDbrI6JCzdubL1rkXEePHsWbb76JLVu2GHVYas2UKVMQHx9v3w4zMoB//7Vv3eJGp1MKqEJDTaewMKBcOaB8edOfJUq4O+ea6NkT6NZNKaA/exZ4+WXg8mXzTV10OiAqSnkpIyLydObi36VLd5fnwAfL0Rsv4nP0RQIGxnUyLIuKAj75RNkGEXkOFk4REVGxlZOTg379+iE+Ph41atRQvd6YMWOM+trQ15xS5fHHAf2w3fpShrylDVrNszbl5lqfn5urTDk55n/PzQWys5V52dmmv2dnA3fuKNPt28qk/z0rS5lu3bo73bypTJmZwI0bys+cHCUvaWnK9N9IUKqULg1Urnx3qlIFqF4dqF1b+d2DvlLPW0AfGKj0xafTGf/b9ZXlpk/3qEMjIrJKH/82bjQumNJLQF+8iM/RA6vxAr5AFgIAKIVZvXoBK1awgIrIk7BwioiIiq309HTs2bMH+/fvx/DhwwEAubm5EBH4+Pjg119/xcMPP2yynr+/v9HQ2zYpV06ZyDIRpQArNdXydOUKcPEicOGC8c/MTODaNWUy1zQzIACoUQOoWxdo0QJ48EGgYUOlKWIh17On8rKVv6lLVJRSMMWXMCIqilJSzM/fhgdxGlGIxhl0xk/4Fj0AKB8hOh0wapRS+4qF9kSeofA/iRERETlJyZIlcfDgQaN5M2fOxIYNG7BixQpUrVrVTTkr5nS6u31RlS9v27ppacCpU0rTSf2UnAz8/bcy3boFHDigTAkJyjpBQUDz5kpB1YMPAg88oDQdLITyNnVhX3xEVBxERJifL/DCMvTBq/gIfZFgKJwClAKq06eVWMnuIYg8AwuniIioSMnIyDAMvw0AycnJSEpKQlhYGCpVqoQxY8bg7NmzWLBgAby8vFCvXj2j9cuVK4eAgACT+eQhSpYE6tVTpvxycoCTJ4HDh4E//gC2b1em1FSlJ/HERCWdTqeMZ96rF9CnD3DPPS49hIKwLz4iKk5atVJqiJ49a9rnXgL64lV8hMewBiFIRwaM+xy0VOuKiAqf4jsEDhERFUl79uxB48aN0bhxYwDA6NGj0bhxY4wfPx4AkJKSglOnTrkzi+Qu3t5AtWpA167AuHHA2rXA1avAwYPAF18AzzyjFESJAPv2AW+9paS//37gww+VGllERORS3t5KB+eA8SC1ALAP9+EfVEcQbuJxfG+yrqVaV0RU+OhEzI35QmQdhwklKp5475vH81LEpKQAP/4ILFsGbNigdACv16IFMGyYUqPK19d9eaRCgfe+eTwv5AyrVpn2uQcA8RiP8ZiINeiCrlgD4O4IpsnJbPbsSrz3yRGsOUVERESUV0QEMHgwsG6dUlA1c6bSjk6nA3buVGpY3Xsv8NlnSgfsRETkdD17Ki2zExOBJUuA+HglLC/DUwCATvgFpXGVI5gSeSgWThERERFZUq4cMHSo8jZ09izw7rvKvFOngJEjgcqVlTekK1fcnVMioiJP3+de377A+PHKCKZpUXXwJ+rAF9mIwTpERSnzOYIpkWdh4RQRERGRGhERSj9UJ08Cn3+u9E915QowYQJQvTrw5ZfGTQCJiMip9LWpSj7ZGQAw/ZGfkZzMgikiT8TCKSLyaDk5wMaNyojwGzcqfxMROVVgIPDCC8DffyvBp1494No1ZV7LlsD+/e7OIRFRseHtDUQP7gQAiDjwK7y92KUykSdi4RQReaxVq4AqVYB27YB+/ZSfVaoo84mInM7HB3jqKaUwavp0oEQJYNcuoGlTYNQoID3d3TkkIioeWrVSvjg4dw44dMjduSEiO7Bwiog80qpVQK9epiO2nD2rzGcBFRG5jI+PMoTUkSPKKH65ucq45w8+qPRNRUREzhUQALRpo/z+yy/uzQsR2YWFU0TkcXJylPdAMVNrWz9v1Cg28SMiF6tYEVi6VHkxqlABOHgQaNYM2L3bpdlgc2ciKpYeeUT5+fPP7s0HEdmFhVNE5HG2bDGtMZWXCHD6tJKOiMjlOnYEfv8daNAAuHBB+TZ/5UqX7JrNnYmo2Oqk9DuFLVuAzEzDbBbYE3kGFk4RkcdJSdE2HRGR5qKjga1bgUcfBW7eVNobv/ee+SqfGmFzZyIq1mrWBCpVAm7fBjZtAsACeyJPwsIpIvI4ERHapiMicooSJYDvvgNGjlT+HjMGePZZ5cVJY2zuTETFnk53t/bUL7+wwJ7Iw7Bwiog8TqtWQFSU8gxijk6nVFpo1cq1+SIiMuHjo3SO/tlngJcXMHeu8vJ09aqmu2FzZyIiGPqdkp9/ZoE9kYdh4RQReRxvb+VdDzAtoNL/PX26ko6IqFAYPhxYs0apTbVxI/DAA0ppkUbY3JmICED79oC3N3T//APvMyctJmOBPVHhw8IpIvJIPXsCK1Yog2PlFRWlzO/Z0z35IiKyqHNnYNs2pU+Uf/4BunUz6rTXEWzuTEQEIDQUaNECANAJvxSYnAX2RIUHC6eIyGP17AmcPAkkJgJLlig/k5NZMEVEhVj9+sDmzUDZssD+/cDAgZp0ks7mzmTJ5s2b0bVrV0RGRkKn0+Hbb7+1mn7VqlWIiYlB2bJlUbJkSTzwwAP45ZeCX/KJCo3/mvapKZxigT1R4cHCKSLyaN7eQNu2QN++yk825SOiQq9yZWD1asDXF1i+HJg40eFNsrkzWZKZmYmGDRtixowZqtJv3rwZMTExWLt2Lfbu3Yt27dqha9eu2L9/v5NzSqSR/zpFj9H9Bl/cMZuEBfZEhY+PuzNAREREVOw8+CDwxRfK6H1xcUDdusATTzi0SX1z55deMu4cPSpKKZhirdLiqXPnzujcubPq9NOnTzf6e/Lkyfjuu+/www8/oHHjxhrnjsgJ7rsPKFMGJa5cQQvsxFZdK6MKqiywJyqcWHOKiIiIyB0GDVKGiwKA/v2BpCSHN8nmzqS13NxcpKenIywszGKarKwspKWlGU1EbuPtDcTEAABmPfEL+ycl8hCsOUVERETkLh98ABw5AvzyC/D448Du3UD58g5tUt/cmUgLH330ETIzM/Hkk09aTDNlyhTEx8e7MFdEBXjkEWDpUtT69xecPDkJW7YonZ9HRChN+VhjiqjwYc0pIiIiInfx8QGWLgVq1lTGNe/RA8jKcneuiAAACQkJmDBhApYtW4Zy5cpZTDdmzBikpqYaptOnT7swl0RmdOyo/Ny7F95XL7F/UiIPwMIpIiIiIncqVQr4/nvl544dd5v6EbnRsmXL8Oyzz+Kbb75Bhw4drKb19/dHyZIljSYit4qIABo0UEZDXbfO3bkhIhVYOEVERETkbjVqAMuWKb9/8QWwebN780PFWkJCAgYMGIAlS5agS5cu7s4OkX3+G7UPv/zi3nwQkSosnCLSwI0bNxAfH49atWohICAAZcqUQd++fXHt2jWn7jcjIwOjRo1CZGQkAgIC0KhRIyxdutSubc2ePRs6nQ4hISEO7UfLPBGR52JctCNtx47A888rvw8ZwuZ9pImMjAwkJSUh6b8O95OTk5GUlIRTp04BUJrk9e/f35A+ISEB/fv3x0cffYQWLVrg/PnzOH/+PFJTU92R/SLDE2NiUlISunTpgkqVKiEwMBBhYWF44IEHsGjRIqN06enpeP3119GxY0eULVsWOp0OEyZMsLjd33//HZ06dUKJEiUQEhKCdu3aYdu2bY4cpnmPPKL8/PVXGA3XR0SFkxDZITU1VQBIamqqu7Pidrm5ufL4449LqVKlZNq0abJhwwaZPn266HQ6GTt2rFP3HRMTI6VKlZIvvvhCNmzYIIMHDxYAsnjxYpu2c+bMGQkNDZXIyEgJDg52aD9a5YkKJ9775vG8GGNcdCBPV6+KlC8vAoi8845NeSbX84R7PzExUQCYTLGxsSIiEhsbK23atDGkb9OmjdX0anjCeXElT42JiYmJMmTIEFm4cKFs2LBBfvjhB3nqqacEgEycONGQLjk5WUJDQ6V169aG7cfFxZnd5u+//y7+/v7SqlUrWb16taxatUpatGgh/v7+sn37dq0OW3HrlkhQkBJPk5K03TaZxXufHMHCKbILA89d+oe+5cuXG80vX768jBo1ymn7/fHHHwWALFmyxGh+TEyMREZGSnZ2tuptPfbYY9K1a1eJjY01eQmzZT9a5okKJ9775vG8GGNcdDAuJiQoL1P+/iJ//606z+R6vPfN43kxVhRiYl7NmzeX6Ohow9+5ubmSm5srIiKXLl2yWjjVqVMnKV++vGRmZhrmpaWlSXh4uLRs2dKu/FjVpYsST997T/ttkwne++QINusjctDy5ctRunRp9OjRwzBv8+bNuHDhAh5++GGn7Xf16tUICQlB7969jeYPHDgQ586dw65du1RtZ9GiRdi0aRNmzpzp8H60yhMReTbGRQfjYp8+Sl8pWVnACy+wOQqRh/P0mJhfeHg4fHx8DH/rdDrodDpV627btg1t27ZFUFCQYV6JEiXQunVrbN++HSkpKXblySL2O0XkMVg4ReSg7du3o3nz5gCAc+fOYe7cuXjiiSfQvn17PPbYYybpRQTZ2dmqJmsOHTqE2rVrGz0cAECDBg0Mywty8eJFjBo1Cu+99x6ioqIc3o8WeSIiz8e46GBc1OmAmTOBwEAgMRFYuLDAfBNR4eXJMREAcnNzkZ2djUuXLmHmzJn45Zdf8MYbb6haN7/bt2/D39/fZL5+3sGDB+3arkX6fqe2bgUyMrTdNhFpioVTRA64desWDh06hObNm2Py5MmoWLEiBg0ahKCgIMybN8/st0ibNm2Cr6+vqunkyZMW933lyhWEhYWZzNfPu3LlSoH5f/HFF1GzZk0MHTpUk/1okSci8myMixrFxXvuAeLilN9HjwYuXy4w70RU+Hh6TASUuOjr64ty5crh5ZdfxqeffoohQ4aoOwH51KlTBzt37kRubq5hXnZ2tqEWl+bPivfeC1StCty5A2zcqO22iUhTPgUnISJL9u3bh+zsbDRr1gy1atVC8+bNsXPnTkyfPh2tW7fGgQMHTEZ5atKkCXbv3q1q+5GRkVaXW6tCXVD16pUrV+KHH37A/v37C0xry34cyRMReT7GRQ3j4ujRwOLFwMGDwGuvAXPnWs0TERU+nhwT9d566y0MHjwYFy9exA8//IDhw4cjMzMTr776qqr18xoxYgSeffZZDB8+HGPHjkVubi7i4+Px77//AgC8vDSuO6HTKU37vvgC+PlnwExNNSIqHFg4ReSA33//HQDQrFkzhIeH45577kHHjh1Ro0YN9O3bFzt37kSHDh2M1gkJCUGjRo1UbT9/Ney8ypQpY/bbpatXrwKA2W/K9DIyMjBs2DCMGDECkZGRuH79OgClqjUAXL9+Hb6+vggODrZpP47kiYiKBsZFDeOiry/w5ZfAgw8C8+YBL74I3H+/5fREVOh4akzMq1Kl/2fvvsOjKtM+jv8mCQk1gdBDAsEuUqUICEgREBTBgCLsCgjW1RXWtfEqVVbUtYCLuiIoKhIRCNjASot0kCjY1hIEQuiQJi3Jef84TGDIJEwy5Uz5fq7rXDNz5pkz9xyYOzP3PKWhGjZsKEnq27evJGns2LEaPny4ateu7dIx7EaOHKkDBw5oypQpevXVVyVJHTp00EMPPaRnnnlGDRo0KNPxXGIvTjHvFODXGNYX4FavXq1+/fopLi5ONptNS5Yscfmxa9asUUREhMt//FDcxo0bdcEFF6hWrVpO73f2a5anumo3a9ZMP/74Y7H5Buxj9Zs2bVriYw8ePKh9+/bp+eefV40aNYq25ORk5eXlqUaNGvrLX/5S5udxJyYAwYG86OG82KGDdNtt5vWJE0tvC8DvBGpOLE27du2Un5+v33//vVyPf/TRR3Xw4EFt27ZNO3bs0Nq1a3XkyBFVqVJFrVu3LtcxS9WtmxQWJv36q7Rnj+ePD8Aj6DkV4PLy8tSiRQvdfvvtGjhwoMuPy8rK0rBhw9SjRw/t27fPixEGt40bN6p+/foO+wzD0KxZs9S0aVM1adKk2GM81VX7pptu0uuvv65FixZp8ODBRfvfeustxcXFFU286Uy9evW0YsWKYvuffvpprVq1SsuWLSv6EFWW53EnJgDBgbzohbw4bpw5vG/pUmnDBolcCgSMQM2JpVmxYoXCwsJ0wQUXlOvxkjkBur04tnPnTs2fP1933nmnKlWqVO5jligmRmreXEpLk9askc5ZvRCAnzAQNCQZixcvdqnt4MGDjSeeeMKYMGGC0aJFizI/V1ZWliHJyMrKKvNjg8WhQ4cMSYYkY9SoUcaXX35pfPjhh8aAAQOMqKgoY+3atV6PoWfPnkaNGjWMmTNnGsuXLzfuvPNOQ5Ixd+7cojYrV640wsPDjUmTJp33eMOHDzeqVKlSrucpT1sEHt77znFeTORFL+bFESMMQzKM665z/THwOt77znFeTIGeE++8807jn//8pzF//nxj5cqVxsKFC43BgwcbkoyHH37Yoe3SpUuNBQsWGG+88YYhybj55puNBQsWGAsWLDDy8vKK2m3bts2YOHGi8fHHHxtffPGF8dxzzxm1atUy2rRpY+Tk5HjvRNx3n5lDR4/23nOA9z7cQs+pEPTmm2/qt99+09y5czVlyhTvP+G770oZGc7vK2kixtImaDzfY86+/9x9Jd137vWS9oWFFV1uPN0lelinTvp08WK9PWeO6teooXYXXaQNTz2lFvv3Sx99ZD4mPNxxi4gwt7OvV6hgbpGRzi+dvO6UlBQ9/vjjGj9+vA4fPqzLLrtMycnJuvXWW4vaGIahgoICh1VRysqV5ylPWwDBxT63yrBhw/Tpp5/q7bffVv369dWuXTtt2LBBLVq08HoMQZsXx42T3nnHnNB33TpzuB8AvxboObFDhw5688039dZbb+no0aOqWrWqWrRooXfeeUd//etfHdree++9RZOaS9KCBQu0YMECSVJ6eroSExMlSZGRkVq+fLleeukl5ebmqmHDhrrnnnv02GOPqUqVKl46C5I6dZJefln6+uuiXQUFUmqqlJkp1a8vde5sfjQHYA2bYRiG1UHAM2w2mxYvXqwBAwaU2OaXX35Rp06dlJqaqksuuUQTJ07UkiVLlJaWVuqxT5w4oRMnThTdzs7OVkJCgrKyshQdHV16YJ06mV1og8xkSVMkZUuq6IsnjIyUKlWSKlZ03CpXlqpWlapUMS/tW0yM41azplSnjrnFxJReAARKkJ2drZiYGNfe+yGE82KaPHmypkyZouzsbFWs6JPMGFruuEOaPVvq2VP6/HOro4F475eE82IiJ/qRXbukhg3N6tPRo0r5vKpGj5Z27z7TJD5emj5dSkqyLsxAx3sf7qDnVAgpKCjQ0KFDNWnSJF1yySVleuzUqVM1adKk8j1x377SxRcX319SXbS0eun5HnP2/efuK+m+szdn+87dCgslw9DGLVvU7PhxVbzqqqJ9Kix03AoKzlyeveXnn7m0b6dOmdvJk+bluU6eNLesrJLPj6sqVDhTqLJv8fFSYqLUuLF52bChFBXl/nMBCBkbN25Us2bN+BLmLU88Ib31lvTFF+aPPldfbXVEAEpBTvQjCQnmZ9udO5X63AYNmtyj2NeKjAxp0CBp4UIKVIAVKE6FkJycHG3evFlbt27V/fffL0kqLCyUYRiKiIjQ559/ru7duzt97NixY/Xggw8W3bb3nHLJ//2f27H7o0116yrpL3+RTi+D61GGcaZgZS9KnTghHT9ubseOnbk8dkzKzZXy8sxL+5aVJR09euby8GFp/34pO9s8bkZGycMtJbNnVVycdOGFUrNm5ta8udS0qVStmudfM4CAt2nTJiXxid57EhOlkSOlmTOlCROkL7+0OiIApSAn+pmrr5Z27tTGF7+WYfQodrdhmB9/x4yR+vdniB/gaxSnQkh0dHTR0rF2r7zyipYvX66FCxeqcePGJT42KipKUfSiceDVVQ5ttjNzUFWu7NljHz8uHThgFqrs2759Znfn9HRz27FD+vPPMwWs1asdj9G4sdS+vflHvlMns2DFX3Ag5LH6qw88/rj05pvSV1+Zk6V07mx1RABKQE70M506ScnJapZd8nQjhmF+JE5Nlbp29V1oAChOBbzc3Fz9+uuvRbfT09OVlpam2NhYNWzYUGPHjlVGRobefvtthYWFFS3ZalenTh1VrFix2H4EsYoVza7NpfV8MwyzgJWeLv38s7Rt25ltz54zRazkZLN9dLT5Bemmm6QBA8z5rfwAE10CCDoNG0qjRkn//a/05JPMPQUArurUSZLUQesUrnwVlPJVODPTV0EBsKM4FeA2b96sbt26Fd22D70bPny45syZo8zMTO3cudOq8BCobLYzc1FddZXjfYcOSVu3SmvXmiuerFtnDhX85BNzu/tuqXt36eabzUJV7dqWvISUFDHRJYDg9Oij0muvmXNP/fqrdNFFLj2Mgj2AkHbFFcqvEq1qedlqpm1KU6sSm9av78O4AEhitT6UEysxoEh+vvTdd9LSpeYMkt9+e+a+8HCzT/SgQdLAgT4rVKWkmE95bnazL1DIRJflx3vfOc4LfK5vX2nZMrNQ9fTT521Owd47eO87x3mBvzKu6yPbZ5/qAb2k/+jvxe632czcmJ5O8b48eO/DHWFWBwAgwEVESFdeaa4ilZZmDgN86ilzX0GBOS/KvfeaQ1EeeMAcyO9FBQXmFzBnZXf7vjFjzHYAELDuvtu8fPNNc9GMUtgL9mcXpqQzK1OlpHgpRgDwM7ZO5iqnV+vroh8ti+47fXvaNApTgBUoTgHwrEsukcaOlbZsMYebPPOM1KqVORH7f/5jrv53xx3mfV6Qmlr8C9jZzp7oEgAC1vXXm+NO9u+XPvywxGYU7AHgLKfnnbox9ms1iHNMjPHx9K4HrERxCoD3XHih9MgjZqHqyy+lbt2kU6ek2bOlSy+V/vIX6fvvPfqUrk5gyUSXAAJaRIQ5Mbpkzj9VAgr2AHCWdu2kiAhVOrxHO1b9oRUrpHnzpBUrzKF8FKYA61CcAuB9NpvUo4e0fLm0Zo05V0phoflpoFkz82f93FyPPJWrE1gy0SWAgDdqlJlfv/xS+u03p00o2APAWSpXNqeekBS+fo26dpWGDDGnSGUoH2AtilMAfKtjR3NVvy1bzJ+nDEN66SWzSPXVV24fvnNns1v2ufMI2NlsUkKC2Q4AAlpiotS7t3l91iynTSjYA8A5Tg/t09dfWxsHAAcUpwBY48orpUWLpM8+MydL37FDuvZa6c47paysch82PNxcfUoqXqBioksAQeeuu8zLN95wOjE6BXsAOMfV5qToFKcA/0JxCoC1evWStm+X7rvPvD1rlnTFFdIXX5T7kElJ5oSWDRo47meiSwBB54YbpHr1zInRP/qo2N0U7AHgHPbi1PffS0eOWBsLgCIUpwBYr1o1acYMadUq6aKLzPXNr7vO3FdOSUlmZywmugQQ1CpUkEaONK/PnOm0CQV7ADhL3brm503DkNatszoaAKdRnALgP7p0kb79Vhoxwpww/e9/l+6/X8rPL9fhwsPFRJcAgt8dd5iXn38u/f670yYU7AHgLPZ5p9assTYOAEUoTgHwL5Urm3OnPPOMOebk5Zel6693ax4qAAhqjRubQ6SlEidGlyjYA0AR5p0C/A7FKQD+x2aTHnnEnDC9cmWzN0CHDtLu3VZHBgD+6e67zcs33pBOnbI2FgDwd/aeUxs3Ol1MAoDvUZwC4L9uuklKTZXi4qQff5T69qUHFQA406+fOY/Kvn1OJ0YHAJzl0kulmjWl48elb76xOhoAojgFwN9deaW0dq1Uv760bZs0cCC/cAHAuVyYGB0AcJrNxtA+wM9QnALg/xo1kj75RKpaVfrqK+nOO80VVgAAZ5w9MXp6urWxAIC/Y1J0wK9QnAIQGFq1khYsMGfwffttafx4qyMCAP9ywQVSz55m8b6UidEBAHLsOcWPnoDlKE4BCBzXXSe99pp5fcoU6fXXrY0HAPzNXXeZl0yMDgCla91aioqSDh6U/vc/q6MBQh7FKQCBZdQoadw48/q990rLllkbDwD4kxtvlOrUkfbuZWJ0AChNVJTUtq15fe1aa2MBQHHK106dOqVdu3bp559/1uHDh60OBwhMkyZJw4dLBQXSzTdLW7ZYHRHcQF4EPCgyUhoxwrw+d66loaB8yImAD7Vvb15u2GBtHAAoTvlCbm6uXnvtNXXt2lUxMTFKTExUkyZNVLt2bTVq1Eh33nmnNm3aZHWYQOCw2czVqK69VsrLk264Qdqxw+qoUAbkRcCLbr3VvFy2TMrNtTYWuIScCFjEXpxav97aOABQnPK2F198UYmJiXr99dfVvXt3paSkKC0tTT///LPWrVunCRMmKD8/Xz179tR1112nX375xeqQgcAQGSktWiQ1b24OX+nbV8rJsToquIC8CHhZy5bm5OjHjzP0OQCQEwEL2YtT27aZP3jK7Ji/cqWUnGxeFhRYFh0QUmyGwdIE3nTzzTdr/PjxatasWantTpw4odmzZysyMlJ32JeC9mPZ2dmKiYlRVlaWoqOjrQ4HoWz3bvODRUaG9Pe/Sy+9ZHVEQc0T7/1gzIvkRPidRx6R/v1vafBg6b33rI4maJETnSMnIqDEx5ufI1euVMqhazR6tPnx8uy7p0+XkpKsCzFQ8N6HOyhOoVxIPPArX35pLp9us5nLAXfsaHVEQYv3vnOcF/idDRvMwn3VqtL+/VKlSlZHFJR47zvHeUFAGTRIWrRI2//6tJq/+6jO/XZss5mXCxdSoDof3vtwB8P6fOjjjz9WYWGh1WEAwefaa6Xbb5cMw1zN7/hxqyOCi8iLgJe0ayclJJhzTn3+udXRwEXkRMACp4f27Vq4oVhhSlLRvjFjGOIHeBPFKR/q37+/Dh48aHUYQHB6/nmpbl3pp5+kf/3L6mjgIvIi4CU225mf+BctsjYWuIycCFjgqqskSS2Pr5PkfFCRYUi7dkmpqT6MCwgxFKd8iBGUgBfVqCG9/LJ5/emnpe++szYeuIS8CHjRoEHm5YcfSidPWhsLXEJOBCzQurUKw8JVX3uVoF2lNs3M9FFMQAiiOOVjaWlpyju9EoRdRkYGY3IBTxg4ULrpJik/3xzel59vdURwAXkR8JKOHaV69aSsLOmrr6yOBi4iJwI+Vrmy8i5sIUm6ShtKbVq/vi8CAkJThNUBhJo+ffrIZrMpMTFRzZs316WXXqo//vhD1atXtzo0IDi8/LK0fLm0ebO5tMo//2l1RDgP8iLgJWFhZsH+1VfNoX19+lgdEVxATgR8r0qPq6RfvlEHrddC3VzsfpvNXLWvc2cLggNCBD2nfOx///ufUlNT9cgjjyguLk7btm3T0aNHNXPmTKtDA4JD/frm/FOSNG6c9Ntv1saD8yIvAl5kH9q3ZAm9SQMEORHwvbAO5qToV2l90ep8dvbb06ZJ4eG+jQsIJfSc8rFq1arpwgsvVIcOHawOBQheI0dK8+aZPajuukv68ksV+6QBv0FeBLyoSxepZk3p0CFp1SqpRw+rI8J5kBMBC5xesa995DdKrH1S6RmRRXfFx5uFKfsaEwC8g55TPtSvXz9VqFDB6jCA4GezSa+/LlWqZBao3nrL6ohQAvIi4GUREebQPolV+wIAORGwyMUXSzVqKPzkcf2y6DutWGH+zrlihZSeTmEK8AWKUz70wQcfqEaNGlaHAYSGCy6QJk0yr48bJx0/bm08cIq8CPjAwIHm5eLFUkGBtbGgVOREwCI2m3TVVZKk8E3r1bWrNGSI1LUrQ/kAX6E45WU7d+4sU/uMjAwvRQKEoL//3eyLvXu39NprVkeD07ydF1evXq1+/fopLi5ONptNS5YsKbV9SkqKevbsqdq1ays6OlodOnTQZ599VqbnBPxa9+5STIy0d6+0dq3V0eAcfFYE/MTpoX3aUPqKfQC8g+KUl7Vt21Z33nmnNm7cWGKbrKwsvf7662ratKlSUlJ8GB0Q5CpWNHtNSdJTT0l5eSookFaulJKTzUs6Efiet/NiXl6eWrRooRkzZrjUfvXq1erZs6eWLl2qLVu2qFu3burXr5+2bt1apucF/FZkpNS/v3n9nKF95ETr8VkR8BOne05p/Xpr4wBClM0wDMPqIILZ4cOH9dRTT+mNN95QhQoV1KZNG8XFxalixYo6cuSIfvjhB33//fdq06aNnnjiCfUJkGWes7OzFRMTo6ysLEVHR1sdDlCyU6ekyy+XfvtN2/8yVX1WPabdu8/cHR8vTZ/OXAKu8sR735d50WazafHixRowYECZHnfFFVdo8ODBGj9+vEvtyYnwex9+aBao4uOlP/6QwsKUkiKNHi1yohsCLSf6CjkRAenwYXMBCUk6cECqVcvaeAIQ7324g+KUjxw/flxLly5VamqqduzYoWPHjqlWrVpq1aqVevfuraZNm1odYpmQeBBQ5s6VbrtNh1VDF+h3Zal60V32RfwWLuTLmCs8+d73RV4sT3GqsLBQiYmJeuSRR3T//fc7bXPixAmdOHGi6HZ2drYSEhLIifBfx49LtWtLubnS+vVKybhKgwZJ534KJCeWTaDlRF/hcyIC1mWXST//LH3yidS3r9XRBBze+3AHxSmUC4kHgaTgZIF+rdJcl+b/oMkapwma7HC/zWb2FkhPZ9LL8wm09355ilP//ve/9fTTT+vHH39UnTp1nLaZOHGiJtkn3D9LoJwXhKghQ6T33lPhPx9Wo/nPOvSYOhs50XWBlhN9hfOCgDV8uPT22+a0EJMnn789HPDehzuYcwpA0EtdG67/yzc/YPxDL6qWDjjcbxjSrl1SaqoV0cGfJCcna+LEiZo/f36JhSlJGjt2rLKysoq2Xbt2+TBKoJxOr9p3InmRdu8u+bdJciKAkGWfFJ15pwCfozhlkWPHjjldbeX777+3IBoguGVmSilK0hZdqWrK1aN6psR2sI7VeXH+/PkaNWqU3n//fV177bWlto2KilJ0dLTDBvi9Pn2kqChV2vO7LtNP521OTrSW1TkRCEn24tTGjVJhobWxACGG4pQFFi5cqEsuuUR9+/ZV8+bNteGs5Upvu+02CyMDglP9+pJk0xOaIkm6Ty+rvvaU0A5WsDovJicna8SIEZo3b56uv/56rz8fYIkqVaRu3SRJN+jj8zYnJ1rH6pwIhKxmzaRKlaSsLHPuKQA+Q3HKAlOmTNE333yjb7/9Vm+88YZGjhypefPmSZKYAgzwvM6dzflTPtN1+lpXq5KOFxWqJHN+lYQEsx2s4cm8mJubq7S0NKWlpUmS0tPTlZaWpp07d0oyh+QNGzasqH1ycrKGDRum559/Xu3bt9fevXu1d+9eZWVleebFAf7khhskSQMjPy6a/Pxc5ETr8VkRsEhEhNSmjXmdoX2AT1GcssCpU6dUu3ZtSVKbNm20evVqvfbaa5o8ebJsJX1SBFBu4eHm0uiy2fSE/iVJGqXZqqu9RV/Opk1j4l8reTIvbt68Wa1atVKrVq0kSQ8++KBatWql8ePHS5IyMzOLClWS9Nprryk/P1/33Xef6tevX7SNHj3aQ68O8COnewa2y1+jGsbhYgUqcqJ/4LMiYKFz5p0qKJBWrpSSk83LggLLIgOCGsUpC9SpU0ffffdd0e2aNWvqiy++0I8//uiwH4DnJCWZS6P/Fn+N1qijonRSf9Mrio9nyXR/4Mm82LVrVxmGUWybM2eOJGnOnDlauXJlUfuVK1eW2h4IKomJUtOmCiss0LIxn6lBA8e7yYn+gc+KgIXOKk6lpJhps1s3aehQ8zIxUUpJsTJAIDhRnPKhbdu2KT8/X++8847q1q3rcF9kZKSSk5O1atUqi6IDgl9SkrRjhxQz8UFJ0tjoV5T+/Z98CbMQeRGwgL331IFPtGOHtGKFNG+eeZmeTmHKSt7IiatXr1a/fv0UFxcnm82mJUuWlNo+MzNTQ4cO1aWXXqqwsDCNGTOmjK8CCHCni1PG9u0aMTBHu3c73p2RIQ0aRIEK8LQIqwMIJS1atFBkZKSaNGmiFi1aqGXLlkWX1atXlyRdffXV1gYJBLnwcKnpEwOktxqrQnq6NO8d6e67rQ4rZJEXAQvccIP0zDPSsmUKN/LVtSsfB/2FN3JiXl6eWrRoodtvv10DBw48b/sTJ06odu3aevzxx/Xiiy+W52UAgS0uTkbDhrLt3Km22qjl6uFwt2GYQ6DHjJH692cINOAp9Jzyoa+//lqxsbFq3LixTpw4oTlz5qh79+6qWbOmLr30Uo0bN05Hjx61Okwg+IWHS/b5hF58kaWCLUReBCzQvr0UGysdPsyEv37GGzmxT58+mjJlipJc7BKXmJio6dOna9iwYYqJiSnHqwAC34ELO0iSOmid0/sNQ9q1S0pN9WVUQHCjOOVD999/v1555RUtWrRI8+bN09atW7VixQpdcMEFGj58uFJTU9WqVSsdOHDA6lCB4DdypBQdbS4TvGyZ1dGELPIiYIGICKlPH/P6xx9bGwscBGpOPHHihLKzsx02IJDtijeLU+1VegE/M9MX0QChgeKUD/30009q0qSJw75rrrlGL774or755hutWLFCbdq00f/93/9ZFCEQQqpVk+66y7z+wgvWxhLCyIuARU7PO6VPPrE2DjgI1Jw4depUxcTEFG0JCQlWhwS4p8PZxSmjxGb16/soHiAEUJzyobZt22ru3LnF9l9xxRX6/PPPZbPZ9PDDD+vLL7+0IDogBP397+YQv+XLpbQ0q6MJSeRFwCK9e5v5b/t2c6UI+IVAzYljx45VVlZW0bZr1y6rQwLc0nJESx1XRdXSIV2sX4rdb7NJCQlS584WBAcEKYpTPvTKK69o2rRpGjp0qH766SdJ0smTJ/Xiiy8qNjZWklS7dm3t27fPyjCB0NGwoXTzzeZ1Jn21BHkRsEhsrGSfWJveU34jUHNiVFSUoqOjHTYgkIVXilTuZa0lSR3PmXfKZjMvp01jMnTAkyhO+dAVV1yhdevWKTMzU02aNFGlSpVUpUoVvf7663r66aclSVu3blVcXJzFkQIh5B//MC+Tk6U9e6yNJQSRFwEL3XCDecm8U36DnAj4j1o3mEP7elRxLE7Fx0sLF0ourjEAwEWsHexjV1xxhVasWKE//vhD3377rcLDw9W6dWvVq1dPkvlrmP3DBwAfaNdO6tRJ+vpr6ZVXpClTrI4o5JAXAYtcf730yCPSihVSXp5UpYrVEUGez4m5ubn69ddfi26np6crLS1NsbGxatiwocaOHauMjAy9/fbbRW3STg91z83N1YEDB5SWlqbIyMhi82EBQe30vFN/vXCdEqabk5/Xr28O5aPHFOB5NsMwSp7hDShBdna2YmJilJWVRddtBL6FC83hffXrSzt3mitZwSne+85xXhCQDEO68EIpPV364APpxhutjijgBMJ7f+XKlerWrVux/cOHD9ecOXM0YsQI7dixQytXriy6z2Yft3SWRo0aaYeL85MFwnkBzmvPHqlBAyksTDp61FxMB6XivQ93MKwvwK1evVr9+vVTXFycbDablixZUmr7lJQU9ezZU7Vr11Z0dLQ6dOigzz77zDfBAv7qxhul2rXNn8SYewVAqLDZGNoXArp27SrDMIptc+bMkSTNmTPHoTAlyWl7VwtTQNCIizPnJy0slDZutDoaIOhRnApweXl5atGihWbMmOFS+9WrV6tnz55aunSptmzZom7duqlfv37aunWrlyMF/FhkpDRihHn99dctDQUAfMpenPrkE7MnFQDgjNND+7R+vbVxACGAsSsBrk+fPurTp4/L7adNm+Zw+6mnntIHH3ygjz76SK1atfJwdEAAueMO6d//lpYtk3btMtcHBoBgd8015lxTe/ZIW7dKV15pdUQA4D86dJDmz5fWrTt/WwBuoedUiCssLFROTk7R8sQlOXHihLKzsx02IKhccon5Ja2wUHrjDaujAQDfiIqSevY0rzOsGQAcnd1zit6lgFdRnApxzz//vPLy8nTLLbeU2m7q1KmKiYkp2hLoVYJgdOed5uXs2VJBgbWxAICvXH+9eUlxCgActWwpVawoHTok/fKL1dEAQY3iVAhLTk7WxIkTNX/+fNWpU6fUtmPHjlVWVlbRtmvXLh9FCfjQwIFSjRrmsL7PP7c6GgDwjb59zcuNG6X9+62NBQD8SWSk1Lq1eZ2hfYBXUZwKUfPnz9eoUaP0/vvv69prrz1v+6ioKEVHRztsQNCpWFG67TbzOhOjAwgVcXFSq1bmkJVly1RQIK1cKSUnm5d0JAUQ0uxD+yhOAV5FcSoEJScna8SIEZo3b56ut3flB2CyD+376CNp715rYwEAXzm9at/u1z5RYqLUrZs0dKh5mZgopaRYGh0AWIfiFOATFKcCXG5urtLS0pSWliZJSk9PV1pamnbu3CnJHI43bNiwovbJyckaNmyYnn/+ebVv31579+7V3r17lZWVZUX4gF9w6CVwsKmM9h2k/HxpzhyrQwMA3zj9Y1W1dZ9p7+5TDndlZEiDBlGgAhCi2rc3L7dvl3JyrI0FCGIUpwLc5s2b1apVK7Vq1UqS9OCDD6pVq1YaP368JCkzM7OoUCVJr732mvLz83Xfffepfv36Rdvo0aMtiR+wWkqKivUSeOjn072nZs0yV+8DgCBXcGVbHQyrrRhl62qtcbjPvkDVmDEM8QMQguLipIYNzc+EGzdaHQ0QtChOBbiuXbvKMIxi25zTPT7mzJmjlStXFrVfuXJlqe2BUJKSYvYG2L3bcf9rR25RlqKl334zu1QBQJBLXROmTwr7SJKuV/FV+wzDXCsiNdXXkQGAH+jUybzkcyHgNRSnAISkggJp9OgzPQLOlqcqStZQSVLhTCZGBxD8MjOlT2QO7btBH5faDgBCjn0BqS+/tDYOIIhRnAIQklJTi/eYOttMnR7al5IiHTzom6AAwCL160ufq5fyFa7L9ZMa6/cS2wFAyOnRw7zcuFFirl7AKyhOAQhJ5/v1f6uu1BZdqbBTJ6V33vFNUABgkc6dpWrx1fW1zKEr5w7ts9mkhASzHQCEnIYNpUsuMeedYmgf4BUUpwCEJFd+/X/d3nvq9dedj/8DgCARHi5Nny59ohskORanbDbzcto0sx0AhCSG9gFeRXEKQEjq3FmKjz/zpetcNpu0usFQGZUrSz/+KK1d69sAAcDHkpKkXtPNeae6aYWqKFeSmSsXLjTvB4CQRXEK8CqKUwBCkr2XgFS8QGW/PeWlaNkGDzZvvM7E6ACCX8+/XyajcWNF6aSWPviVVqyQ0tMpTAGAunaVwsKkn36SMjKsjgYIOhSnAISspCSzN0CDBo77HXoJ3Hl6aN/770tHj/o6RADwLZtNtuvN3lNdcj5R164M5QMASVKNGlKbNub1r76yNhYgCFGcAhDSkpKkHTukFSukefNUvJdA+/ZS06bSsWNmAwAIdqeLU/rkE3PyXwCAiaF9gNdQnAIQ8sLDzZ7aQ4aoeC8Bm0264w7z+uzZFkQHAD7WtatUrZq0Z4+0YYPV0QCA/zi7OMViOYBHUZwCgPP561+lyEjpm2+ktDSrowEA76pYUbrxRvP6++9bGwsA+JMOHaRKlaTMTHPBHAAeQ3EKAM6nZk1pwADzOr2nAISCW24xLxcsYGgfANhVrCh16mReZ2gf4FEUpwDAFaNGmZfvvisdP25tLADgbb16SdHR5opU69dbHQ0A+A/mnQK8guIUALji2mulhg2lI0ekxYutjgYAvIuhfQDgnL04tXKldOqUpaEAwYTiFAC4IixMuv128zpD+wCEAob2AUBxLVtKsbFSTo60aZPV0QBBg+IUALjq9tvN1fu++kpKT7c6GgDwLvvQvj17pLVrrY4GAPxDWJjUo4d5naF9gMdQnAIAVzVqdKYr95tvWhsLAHhbVJTUv795fcECa2MBAH/CvFOAx1GcAoCysE+M/uabUkGBtbEAgLcxtA8AirMXp9atk3JzrY0FCBIUpwCgLAYMMOcZ2L1b+uILq6MBAO/q2VOKiZEyM6U1a6yOBgD8wwUXSI0bS/n50urVVkcDBAWKUwBQFlFR0l//al5nYnQAwS4qyizKSwztA4CzMbQP8CiKUwBQVvahfR98IB04YG0sAOBtN99sXi5cyHBmALCjOAV4FMUpACir5s2lNm2kU6ekuXOtjgYAvIuhfQBQXPfu5uW2bdLevdbGAgQBilMAUB723lOzZ0uGYW0sAOBNkZHSTTeZ199/39pYAMBf1KoltWplXl++3NpYgCBAcQoAymPIEKlSJen776WNG62OBgC8yz60b9EihvYBgF2PHuYlQ/sAt1GcAoDyiImRBg0yr8+aZW0sAOBt114rVa9uDl35+murowEA/3D2vFP0pAfcQnEKAMrrzjvNy3fflQ4dsjYWAPAmhvYBQHGdOpn5cdcu6ddfrY4GCGgUpwCgvDp1MucaOHZMev11q6MBAO9iaB8AOKpSRerY0bzO0D7ALRSnAKC8bDZpzBjz+owZ5up9ABCsevSQatSQ9u2TUlOtjgYA/MPZQ/sAlBvFKQBwx+DBUt26UkaG2ZsAAIIVQ/sAoDh7cWr5cnqVAm6gOAUA7oiKkv72N/P6tGmWhgIAXnfLLeYlQ/sAwNS6tdmr9OhR6fPPrY4GCFgUpwDAXffcY/Yo2LBBWr/e6mgAwHu6d5diY6X9+6XVq62OBgCsFxEhDR9uXn/5ZWtjAQIYxSkAcFedOtJf/mJep/cUgGBWocKZoX3vvWdtLADgL+y96JculX7/3dpYgABFcQoAPGH0aPNy4UJzOWEACFZDhpiXc+eaPagAINRdfLHUu7dkGNKrr1odDRCQKE4BgCe0aCF162bOwUKXbgDBrHt3qU0b6c8/pRdesDoaAPAP991nXs6ebeZHAGVCcQoAPGXMGPNy5kwpL8/SUADAa2w2acIE8/qMGdLBg9bGAwD+oG9fqVEj6cgRhj0D5UBxCgA85YYbpAsvND+UvP221dEAgPdcf73UqpVZiH/xRaujAQDLFBRIK1dKye+H67fep+eemjHDHOIHwGUUpwDAU8LCzsw9NX26VFhobTwA4C02mzR+vHn9P/+RDh+2Nh4AsEBKipSYaM7sMHSodNXMkTquKGnrVlZwBsqI4hQAeNKIEVJMjPTzz9K8eVZHAwDec+ONUvPmUk6OWZAHgBCSkiINGiTt3n1m3yHVUrLMRSN2PjrDosiAwERxCgA8qVo16bHHzOtjxzIhJoDgFRYmjRtnXp8+XTp61NJwAMBXCgrMzvLORu69LHNi9HqpC1SwZ5+PIwMCF8UpAPC0MWPMCTF372YlKwDBLSlJuuIKKSvLHN4HACEgNdWxx9TZtqiN1usqReqUdo573beBAQGM4hQAeFrFitLTT5vXn35aysy0Nh4A8Jaze0+9+KKUnW1tPADgA+f7aGfvPVV3yX+l/HwfRAQEPopTAOANgwdLV11lrmRlnzQYAILRoEHSZZeZK5XOYI4VAMGvfv3S71+gm7VftVX5cIb0wQe+CQoIcBSnAMAbbLYzQ/pmz5a+/dbaeADAW8LDpSeeMK8//7w5QToABLHOnaX4ePPjnjMnbRX1frU7zBsvv+y7wIAARnEKALylY0fpllvM2TL/+U/ns2YCQDC49Vbpkkukw4elV1+1OhoA8Krw8DOLlJ5boLLfvvDf95hDn1eskL7/3rcBAgGI4hQAeNPTT0uRkdJXX0lLl1odDQB4R3i49Pjj5vV//5u59gAEvaQkaeFCqUEDx/3x8eb+Pnc3lPr3N3eOGiUdO+b7IIEAQnEKALypcWNzrWHJ/GDy88/WxgMA3jJ0qHT55dLBg9J110lHj1odEQB4VVKStGOH2Tlq3jzzMj3d3C9JevZZqUYNacMG83MgveiBElGcAgBve+IJqUULad8+qXt36ddfrY4IADwvIkL6+GOpXj3pu+/MHgP0FAAQ5MLDpa5dpSFDzMvw8LPuvOgiadEiMz8mJ0tTplgUJeD/KE4BgLdFR0tffCFdcYW0Z49ZoEpPtzoqAPC8Cy6QPv3UzHurV5u9qVhGHUAo69ZNeuUV8/r48dL771sbD+CnKE4BgC/Urm3OO3XZZdKuXWaBaudOq6MCAM9r0UL68EMpKkpaskS6916GsgAIbXfeKf3jH+b14cOlTZusjQfwQxSnAMBX6tY1C1QXXWROUNC9u5SRYXVUAOB511xjDmEJC5NmzZLGjbM6IgCw1r//LV1/vXT8uDnsefduqyMC/ArFKQDwpbg4aflyc6L0334zC1R791odVVBZvXq1+vXrp7i4ONlsNi1ZsuS8j1m1apVat26tihUr6oILLtB///tf7wcKBLubbpLs76V//UsaOFDautXamEIQORHwE+Hh5qzpTZuaK5q2bSs9/7yUm2t1ZIBfoDgFAL6WkGAWqBo2lP73P7NAtX+/1VEFjby8PLVo0UIzZsxwqX16err69u2rzp07a+vWrfq///s/PfDAA1q0aJGXIwVCwJ13Sk8/bV5PSZGuvFK64QZp3Tpr4woh5ETAj0RHSx99ZM7Pt3ev9NBDUmKi9OSTrHCKkGczDCYBCGSrV6/Wv//9b23ZskWZmZlavHixBgwYUOpjVq1apQcffFDff/+94uLi9Mgjj+iee+4p0/NmZ2crJiZGWVlZio6OduMVACHst9/MoS8ZGVKzZtL8+eYy7H4s0N77NpvtvHnx0Ucf1Ycffqgff/yxaN8999yjb7/9Vutc/AIdaOcF8Lnt26WpU6X33pMKC819V14pXXKJWahv1Mi8tG8xMZLNZm3MLgi09z45EfATJ09Kc+eaedG+inOVKtKll0oNGpg97c+9rF3b7H0VFmbmx3Mvvclmk6pWPW8z3vtwR4TVAcA99l/Dbr/9dg0cOPC87e2/ht15552aO3eu1qxZo7/97W+qXbu2S48H4EEXXmj2oOraVdq2TWrSRGreXBo82NwuvNDqCEPCunXr1KtXL4d9vXv31uzZs3Xq1ClVqFCh2GNOnDihEydOFN3Ozs72epxAQGvaVHr3XWniRLMn1dtvS998Y27OVKsmVa9ufuk6d7PZnH8RO73PkPRnnrlIYESEVLmKVOavbfffb07kHoLIiYAPREZKI0eak6MvWCA99ZT5WbC0vGilCy4wf1QFvIjiVIDr06eP+vTp43L7//73v2rYsKGmTZsmSbr88su1efNmPffccxSnACtccom0cqX04IPSZ59J331nbo8/LrVpI916q9Spk/lrWa1a5he2AOhNEEj27t2runXrOuyrW7eu8vPzdfDgQdWvX7/YY6ZOnapJkyb5KkQgeFx8sTR7tjRpkjm0b+fO4tvBg1JOjrmVg01SFXfjPHjQ3SMELHIi4EPh4eZnvVtuMXuY7tpl9qjPyJD27HG8PHSIlU8R1ChOhZjy/Bom8YsY4FWXXCJ9/LF0+LC0eLE57GX5cmnzZnM7W4UKZpGqenWzS0B4uLlFRJg9CkpTWlErJcVcTTBE2c45N/YR7+futxs7dqwefPDBotvZ2dlKSEjwXoBAsImPl26+2fl9f/5pfkHLzTWHABYWSgUFZ67bhwWeY/VqacIEs+fU2ezv4kmTpC5dXIwvMdHFhsGJnAj4WFiY2Xu+efPztzUMMw/aL0vIiR7FD6PwAYpTIaY8v4ZJ/CIG+ERsrDRqlLnt3y8tWiQtXGjORXDwoPmF7dQpc4WXzEzPPvfJk549XgCpV6+e9p6zYuL+/fsVERGhmjVrOn1MVFSUoqKifBEeEHoqVzbnXSmDggLpL7dJJS3MbrNJf50lpT9u1vNRMnIi4OdsNhIZghLFqRBU1l/DJH4RA3yuTh1zvpOz5zz580+zS/fBg+aKLgUFUkGBCk4W6Ifv8nXksKEaNaQmV0jhtnP6DpyvG3gJXzhCQYcOHfTRRx857Pv888/Vpk2bEnuTAvAvqanS7pIqUzJT4K5dZruuXX0WVkAiJwIArEBxKsSU59cwiV/EAL9QubK5nVUYTkmRRo92/FIWHy9Nny4lJVkQox/Izc3Vr/aVb2QuBJGWlqbY2Fg1bNhQY8eOVUZGht5++21J5ipUM2bM0IMPPqg777xT69at0+zZs5WcnGzVSwBQRq52Js3MNOv6qanm9fr1pc6dzU4IJe0PdOREAEAgoDgVYvg1DAgeKSnSoEHFO0VlZJj7Fy4MzQLV5s2b1a1bt6Lb9l6fw4cP15w5c5SZmamdO3cW3d+4cWMtXbpU//jHP/Tyyy8rLi5OL730EotEAAGkhFkJivnlF3M6qXML+kOGSMnJwVnoJycCAAKBzTCY8j+Qnf1rWKtWrfTCCy+oW7duJf4alp6erqZNm+ruu+8u+jXsnnvuUXJycpk+dGRnZysmJkZZWVmKjo72ymsDULKCguJfsM5ms5lfrNLTzdue6iXAe985zgtgLXtOzMhwPorZZjOn9Tt82PXFruyzHZRW6Oe97xznBQhNvPfhDnpOBTh+DQNCk6vzq/zrX9Lrr4dWLwEAoSc83MxfgwaZRaWzC1Bn3y7LT7KGYT52zBipf//gGOIHAIC/oucUyoWqOGCt5GRp6FDPHpNeAuXHeQH8g7N5+BISpDvukCZMKP9xV6xwPpE6733nOC9AaOK9D3eEWR0AAKDsXJ1fpSzsP1WMGWMOkQGAQJOUJO3YYRaT5s0zL9PTpYsvdu+4rk64DgD+qKBAWrnS/HFz5Uo+58E/MawPAAJQ587mMLyS5lcpL5ZbBxDowsOL5y93C/re+EEAAHyBlZ0RKOg5BQAByD6/inRmOJ7dubfLg14CAEoSiL/A2wv6Zc2PNps5LLBzZ+/EBQDeZF/Z+dx5Su0rO6ekWBMX4AzFKQAIUElJ5vxQDRo47o+PlyZNcu/Y9BIA4ExKirkqXrdu5rx33bqZt/39C05pBf2S2NtNm8Zk6AACT0GB2WPKWQ97pnKAP6I4BQABrKT5VR5/nF4CADwr0H+BL6mgn5AgPfywmTPPFh9f+gIRAODPXF3ZOTXVdzEBpWHOKQAIcM7mV5FKXla9JPQSAFCS8/0Cb7OZv8D37+/f+SMpyYwxNdUcvly/vlmMDw+Xpk51vh8AyqOgwNqc4uoUDUzlAH9BcQoAgpS9l4CzZdVvvdWcL+bcyTGnTaOXAIDiyvILvL8vplBSQb+k/QBQVv4wCbmrUzTUqWPOH+isiGZ1gQ2hheIUAAQxegkA8AR+gQcA19iHQJ/b09Q+BNpXw4XPt7KzzSbFxkojRjgvoknWF9gQWihOAUApguEXI3oJAHCXq7/As5gCgFDmT0Og7QtBOJviwX770KHij8vIkAYOdH5MXxfYEFqYEB0AShCoq1IBgKfZf4EvaZEFFlMAAP+bhLykhSAaNJBq1nT+mNLmKWWVP3gTxSkAcCLQV6UCAE+y/wIvFS9QsZgCAJj8cQi0s5Wd58xx3mvKFazyB2+hOAUA5zhfl2yJX4wAhJ6SfoGPj2eIBwBI/jsE2j6Vw5Ah5uX+/e4fkzkG4WnMOQUA5wimVakAwJNKW2QBAEKdK5OQx8dbPwTaE8Ux5hiEp1GcAoBz+GOXbADwFyymAADOnW8Scsk/hkCfr4hWGn8psCH4MKwPAM7hr12yAQAA4N8CYQi0K/MIlnafPxTYEHwoTgHAOViVCgAAAOXlbBLy9HT/KEzZlVZEW7TI3Py5wIbgw7A+ADhHoHTJBgAAgH8KhCHQ55tHkDkG4UsUpwDACfuvSaNHO06OHh9vFqb4xQgAAACBrrQiWiAU2BA8KE4BQAlYlQoAAAAAvI/iFACUgl+MAAAAAMC7mBAdAAAAAAAAlqE4BQAAAAAAAMtQnAIAAAAAAIBlKE4BAAAAAADAMhSnAAAAAAAAYBmKUwAAAAAAALAMxSkAAAAAAABYhuIUAAAAAAAALENxCgAAAAAAAJaJsDoAAAAAAABCQUGBlJoqZWZK9etLnTtL4eFWRwVYj+IUAAAAAABelpIijR4t7d59Zl98vDR9upSUZF1cgD9gWB8AAAAAAF6UkiINGuRYmJKkjAxzf0qKNXEB/oLiFAAAAAAAXlJQYPaYMozi99n3jRljtgNCFcUpAAAAAAC8JDW1eI+psxmGtGuX2Q4IVRSnAAAAAADwksxMz7YDghHFKQAAAAAAvKR+fc+2A4IRxSkAAAAAALykc2dzVT6bzfn9NpuUkGC2A0IVxSkAAAAAALwkPFyaPt28fm6Byn572jSzHRCqKE4BAAAAAOBFSUnSwoVSgwaO++Pjzf1JSdbEBfiLCKsDAAAAQOArKDBXmsrMNOdN6dyZXgAAcLakJKl/f3Il4AzFKQAAALglJUUaPdpxqfT4eHMYC70BAOCM8HCpa1erowD8D8P6AAAAUG4pKdKgQY6FKUnKyDD3p6RYExcAAAgcFKcAAABQLgUFZo8pwyh+n33fmDFmOwAAgJJQnAIAAEC5pKYW7zF1NsOQdu0y2wEAAJSE4hQAAADKJTPTs+0AAEBoYkJ0AAAAlEv9+p5tBwBwDyunIlDRcwoAAADl0rmzuSqfzeb8fptNSkgw2wEAvCslRUpMlLp1k4YONS8TE1mYAoGB4hQAAADKJTxcmj7dvH5ugcp+e9o0frUHAG9j5VQEOopTAFBOBQXSypVScrJ5yWpUAEJRUpK0cKHUoIHj/vh4c39SkjVxAUCoYOVUBAPmnAKAckhJMT8EnP3rVHy82YOAL2IAQk1SktS/P/OcAIAVyrJyateuPgsLKBOKUwBQRvZu0+f+OmXvNk1PAQChKDycLz0AYAVWTkUwYFhfkHjllVfUuHFjVaxYUa1bt1Zqamqp7d999121aNFClStXVv369XX77bfr0KFDPooWCFx0mwYAAIA/YeVUBAOKU0Fg/vz5GjNmjB5//HFt3bpVnTt3Vp8+fbRz506n7b/++msNGzZMo0aN0vfff68FCxZo06ZNuuOOO3wcORB4ytJtGgAAACiNJ+YwZeVUBAOKU0HghRde0KhRo3THHXfo8ssv17Rp05SQkKBXX33Vafv169crMTFRDzzwgBo3bqxOnTrp7rvv1ubNm30cORB46DYNAAAAT0hJkRITpW7dpKFDzcvExLKvrMfKqQgGFKcC3MmTJ7Vlyxb16tXLYX+vXr20du1ap4/p2LGjdu/eraVLl8owDO3bt08LFy7U9ddf74uQgYBGt2kAAAC4yz6H6bk98u1zmJa1QMXKqQh0TIge4A4ePKiCggLVrVvXYX/dunW1d+9ep4/p2LGj3n33XQ0ePFjHjx9Xfn6+brzxRv3nP/8p8XlOnDihEydOFN3Ozs72zAsAAoy923RGhvN5p2w28366TQOAbxQUsEoggMByvjlMbTZzDtP+/cuWz1g5FYGMnlNBwnZO/03DMIrts/vhhx/0wAMPaPz48dqyZYs+/fRTpaen65577inx+FOnTlVMTEzRlpCQ4NH4gUBBt2kA8B+eGhIT7Mq6cM7LL7+syy+/XJUqVdKll16qt99+20eRAqHBm3OY2ldOHTLEvOQzKQIFxakAV6tWLYWHhxfrJbV///5ivanspk6dqquvvloPP/ywmjdvrt69e+uVV17RG2+8ocwSJsoZO3assrKyirZdu3Z5/LUAgYJu0wBgPU8PiQlWZV0459VXX9XYsWM1ceJEff/995o0aZLuu+8+ffTRRz6OHAhezGEKFEdxKsBFRkaqdevW+uKLLxz2f/HFF+rYsaPTx/z5558KC3P8pw8/XVI3nPUtlRQVFaXo6GiHDQhlSUnSjh3SihXSvHnmZXo6hSkAOJsnVqEq6bilDYmRzCExnnq+QFbWhXPeeecd3X333Ro8eLAuuOAC3XrrrRo1apSeeeYZH0cOBC/mMAWKozgVBB588EHNmjVLb7zxhn788Uf94x//0M6dO4uG6Y0dO1bDhg0rat+vXz+lpKTo1Vdf1e+//641a9bogQceULt27RQXF2fVywACDt2mAaBk3hxy580hMcGkPAvnnDhxQhUrVnTYV6lSJW3cuFGnTp3yWqxAKLHPYVrCLCyy2aSEBOYwRWhhQvQgMHjwYB06dEiTJ09WZmammjZtqqVLl6pRo0aSpMzMTIeu2yNGjFBOTo5mzJihf/7zn6pevbq6d+/OL2IAAMAj7EPuzu3ZZB9y5+4QaIbEuKY8C+f07t1bs2bN0oABA3TllVdqy5YteuONN3Tq1CkdPHhQ9Z105WDhHKBs7HOYDhpkFqLOzpXMYYpQRc+pIPG3v/1NO3bs0IkTJ7RlyxZ16dKl6L45c+Zo5cqVDu3//ve/6/vvv9eff/6pPXv2aO7cuWpw7gQ6AAAAZeSLIXcMiSmbsiycM27cOPXp00ft27dXhQoV1L9/f40YMULSmWkgzsXCOUDZMYcp4IjiFAAAADzGF0PuGBLjmvIsnFOpUiW98cYb+vPPP7Vjxw7t3LlTiYmJqlatmmrVquX0MSycA5QPc5gCZ1CcAgAAgMf4YsidfUiMVLxAxZCYM8qzcI5dhQoVFB8fr/DwcL333nu64YYbii2oY8fCOUD5MYcpYKI4BQAAAI/x1ZA7hsS4pqwL5/zvf//T3Llz9csvv2jjxo269dZbtX37dj311FNWvQQAQAhgQnQAAAB4jH3IXUaG83mnbDbzfk8MuUtKkvr3N4cIZmaaBa/Onel5cLayLpxTUFCg559/Xj///LMqVKigbt26ae3atUpMTLToFQAAQoHNMJx9bABKl52drZiYGGVlZdF1GzhLQUFwf0nive8c5wVwZF+tT3K+ClWw9Gzive8c5wUITbz34Q6G9QGAh6SkSImJUrdu0tCh5mViornfUwoKpJUrpeRk89Kd1a4AwFsYcgcAAMqCYX0A4AH2XgLn9kXNyDD3e+LLWEqKuTz72atgxcebkwLzRQ+Av2HIHQAAcBU9pwDATQUFZtHI2SBp+74xY9zr5WQvfp27PLu9+OXJ3lnB4JVXXlHjxo1VsWJFtW7dWqnnWbP+3XffVYsWLVS5cmXVr19ft99+uw4dOuSjaIHgxSpUAOA99KhHMKE4BQBuSk0tXjQ6m2FIu3aZ7crDF8WvYDJ//nyNGTNGjz/+uLZu3arOnTurT58+DhP+nu3rr7/WsGHDNGrUKH3//fdasGCBNm3apDvuuMPHkQMAALjGF9NJAL5EcQoA3JSZ6dl25/J28SvYvPDCCxo1apTuuOMOXX755Zo2bZoSEhL06quvOm2/fv16JSYm6oEHHlDjxo3VqVMn3X333dq8ebOPIwcAADg/etQjGFGcAgA31a/v2Xbn8nbxK5icPHlSW7ZsUa9evRz29+rVS2vXrnX6mI4dO2r37t1aunSpDMPQvn37tHDhQl1//fUlPs+JEyeUnZ3tsAEAAHgbPeoRrChOAYCbOnc2Jya3L5F+LptNSkgw25WHt4tfweTgwYMqKChQ3bp1HfbXrVtXe/fudfqYjh076t1339XgwYMVGRmpevXqqXr16vrPf/5T4vNMnTpVMTExRVtCQoJHXwcAAIAz9KhHsKI4BQBuCg83V8yTiheo7LenTSv/RMDeLn4FI9s5J8swjGL77H744Qc98MADGj9+vLZs2aJPP/1U6enpuueee0o8/tixY5WVlVW07dq1y6PxAwAAOEOPegSrCKsDAIBgkJQkLVxodrM++9es+HizMJWUVP5j24tfgwaZhaizu3F7ovgVTGrVqqXw8PBivaT2799frDeV3dSpU3X11Vfr4YcfliQ1b95cVapUUefOnTVlyhTVd9IlLSoqSlFRUZ5/AUAIKCgwf9HPzDR7fHbuTP4CAFfRox7Bip5TAOAhSUnSjh3SihXSvHnmZXq6e4Wps4+9cKHUoIHj/vh4c78nniMYREZGqnXr1vriiy8c9n/xxRfq2LGj08f8+eefCgtz/HMYfvqbsuFsQgcA5cbqUgBQNgUF0sqVUnKyedmxIz3qEZzoOQUAHhQeLnXt6p1jJyVJ/fvT4+B8HnzwQd12221q06aNOnTooJkzZ2rnzp1Fw/TGjh2rjIwMvf3225Kkfv366c4779Srr76q3r17KzMzU2PGjFG7du0UFxdn5UsBgop9dalza7721aUotAOAo5QU573yhwyRnnuOHvUILhSnACCAeLP4FSwGDx6sQ4cOafLkycrMzFTTpk21dOlSNWrUSJKUmZmpnTt3FrUfMWKEcnJyNGPGDP3zn/9U9erV1b17dz3zzDNWvQQg6JxvdSmbzVxdqn9/vlABgFR6Qf+556SHHjJ7U3l6OgnAKjaDMQsoh+zsbMXExCgrK0vR0dFWhwPAR3jvO8d5AUq3cqU5hO98VqwIrAI8733nOC+AewoKzCHPJa3KZ7OZhahff5XWrvWfHvW89+EOek4BAADAq1hdCgBcl5pacmFKMntT7dplFqYCqaAPlIYJ0QEAAOBVrC4FAK6joI9QRM8pAAAAeFXnzuYQlIwM5/NO2YeolLa6VEEBC0IACA0U9BGK6DkFAF527hLABQVWRwQAvhUeLk2fbl4/d/lzV1aXSkkx51/p1k0aOtS8TEw09wNAsLEX9M/Nl3Y2m5SQUHpBHwg0FKcAwIv4QgUApqQkaeFCqUEDx/3x8eb+klaXsq9Yde78KxkZ5n7yKYBg425BHwhEFKcAwEv4QgUAjpKSpB07zFX55s0zL9PTSy5MFRRIo0c7Hwpo3zdmDD1SAQSf8hb0gUDFnFMA4AXn+0Jls5lfqPr351cvAKElPNz11aVcXbEqNZUVqwAEn6Qk87Mi8+0hFFCcAgAv4AsVALiPFasAhLqyFPSBQMawPgDwAr5QAYD7WLEKAIDQQM8pAPACT3yhYtl0AKHOvmJVRobzYdI2m3k/K1YBABDY6DkFAF7g7hLArPIHAKxYBQBAqKA4BQBe4M4XKlb5AxDKCgqklSul5GTzsn9/VqwCACDYUZwCAC8pzxLALJsOIJSV1GtUknbskFaskObNMy/T0ylMAQAQLJhzCgC8qKxLALPKH4BQZe81em5x3t5rlF5SAAAEL4pTAOBlZVkCmFX+AISi8/UatdnMXqP9+zO/FAAAwYhhfQDgR1g2HUAoKkuvUQAAEHzoOQUAFisoODPsr04dlk0HEHroNQoAQGijOAUAFkpJMYeynN1joGbNM8NYzi5QsWw6gGBFr1EAAEIbw/oAwCL2yX/PHcpy+LB5GRvruJ9l0wEEq86dzRxnL8Kfy2aTEhLoNQoAQLCi5xQAWMCVyX8rVZK+/FLav//8q/wBQCALD5emTzcL9vQaBQAg9NBzCgAs4Mrkv7t3m1/EhgwxV/vjSxmAYJaUZPYObdDAcT+9RgEACH70nAIACzD5LwAUl5Qk9e9/ZpEIeo0CABAaKE4BgAWY/BcAnAsPN3uLAgCA0MGwPgCwAJP/AgAAAICJ4hQAWMA++a9UvEDF5L8AAAAAQgnFKQCwCJP/AgAAAABzTgGApZj8FwAAAECoozgFABZj8l8AAAAAoYxhfQAAAAAAALAMxSkAAAAAAABYhmF9KBfDMCRJ2dnZFkcCwJfs73l7DoCJnAiEJnKic+REIDSRE+EOilMol5ycHElSQkKCxZEAsEJOTo5iYmKsDsNvkBOB0EZOdEROBEIbORHlYTMoa6IcCgsLtWfPHnXv3l2bN28+b/u2bdtq06ZNZb7f1f3O2tn3ZWdnKyEhQbt27VJ0dPR5Yy2P870+Tzy2tHZlvc+VfWff9udz6InzV9r9nD/HdoZhKCcnR3FxcQoLY2S4nT0nVqtWTe3ateM9XUJMnnycr/+ucP7Kvr+kc+jP568sj23btq02btxITnTC0zmxtPt5T7vWzpt/V3xx/kqKyZOP4++ye48jJ8Jd9JxCuYSFhSk+Pl4REREuJdDw8PBS25V0v6v7nbU7d190dLTXkv35Xp8nHltau7Le58o+Z2388Rx64vyVdj/nr3g7fgkrzp4TJd7TpT2fJx/n678rnL+y7z/fOfTH81eWx4aHhysmJoac6ISnc2Jp9/Oedq2dL/6uePP8lRSTJx/H32X3HkdOhLsoZ8It9913n0falXS/q/udtXM1Nk9w57k8cQ7Lep8r+3x5/tx5Piv+D3L+UBre0+49n7/+XeH8lX2/lefQ6r/LOMNf/k/ynubvijvtOH/eOz5gx7A+BL3s7GzFxMQoKyvLq7/mBDPOoXs4f/A3/J90D+fPPZw/+Bv+T7qH8+c+ziFAzymEgKioKE2YMEFRUVFWhxKwOIfu4fzB3/B/0j2cP/dw/uBv+D/pHs6f+ziHAD2nAAAAAAAAYCF6TgEAAAAAAMAyFKcAAAAAAABgGYpTAAAAAAAAsAzFKQAAAAAAAFiG4hQAAAAAAAAsQ3EKIe/jjz/WpZdeqosvvlizZs2yOpyAc9NNN6lGjRoaNGiQ1aEEnF27dqlr165q0qSJmjdvrgULFlgdEkBOdBM50T3kRfgbcqL7yIvlR05EKLEZhmFYHQRglfz8fDVp0kQrVqxQdHS0rrzySm3YsEGxsbFWhxYwVqxYodzcXL311ltauHCh1eEElMzMTO3bt08tW7bU/v37deWVV+rnn39WlSpVrA4NIYqc6D5yonvIi/An5ETPIC+WHzkRoYSeUwhpGzdu1BVXXKEGDRqoWrVq6tu3rz777DOrwwoo3bp1U7Vq1awOIyDVr19fLVu2lCTVqVNHsbGxOnz4sLVBIaSRE91HTnQPeRH+hJzoGeTF8iMnIpRQnEJAW716tfr166e4uDjZbDYtWbKkWJtXXnlFjRs3VsWKFdW6dWulpqYW3bdnzx41aNCg6HZ8fLwyMjJ8EbpfcPf8hTpPnr/NmzersLBQCQkJXo4awYyc6B5yovvIi/An5ET3kRfdQ04EXEdxCgEtLy9PLVq00IwZM5zeP3/+fI0ZM0aPP/64tm7dqs6dO6tPnz7auXOnJMnZqFabzebVmP2Ju+cv1Hnq/B06dEjDhg3TzJkzfRE2ghg50T3kRPeRF+FPyInuIy+6h5wIlIEBBAlJxuLFix32tWvXzrjnnnsc9l122WXGY489ZhiGYaxZs8YYMGBA0X0PPPCA8e6773o9Vn9UnvNnt2LFCmPgwIHeDtGvlff8HT9+3OjcubPx9ttv+yJMhBByonvIie4jL8KfkBPdR150DzkRKB09pxC0Tp48qS1btqhXr14O+3v16qW1a9dKktq1a6ft27crIyNDOTk5Wrp0qXr37m1FuH7HlfOHkrly/gzD0IgRI9S9e3fddtttVoSJEEJOdA850X3kRfgTcqL7yIvuIScCjiKsDgDwloMHD6qgoEB169Z12F+3bl3t3btXkhQREaHnn39e3bp1U2FhoR555BHVrFnTinD9jivnT5J69+6tb775Rnl5eYqPj9fixYvVtm1bX4frd1w5f2vWrNH8+fPVvHnzojkI3nnnHTVr1szX4SIEkBPdQ050H3kR/oSc6D7yonvIiYAjilMIeufODWAYhsO+G2+8UTfeeKOvwwoY5zt/rFpTutLOX6dOnVRYWGhFWAhh5ET3kBPdR16EPyEnuo+86B5yImBiWB+CVq1atRQeHu7wy40k7d+/v9gvFCiO8+cezh/8Df8n3cP5cx/nEP6E/4/u4xy6h/MHOKI4haAVGRmp1q1b64svvnDY/8UXX6hjx44WRRU4OH/u4fzB3/B/0j2cP/dxDuFP+P/oPs6hezh/gCOG9SGg5ebm6tdffy26nZ6errS0NMXGxqphw4Z68MEHddttt6lNmzbq0KGDZs6cqZ07d+qee+6xMGr/wflzD+cP/ob/k+7h/LmPcwh/wv9H93EO3cP5A8rAmkUCAc9YsWKFIanYNnz48KI2L7/8stGoUSMjMjLSuPLKK41Vq1ZZF7Cf4fy5h/MHf8P/Sfdw/tzHOYQ/4f+j+ziH7uH8Aa6zGYZheKXqBQAAAAAAAJwHc04BAAAAAADAMhSnAAAAAAAAYBmKUwAAAAAAALAMxSkAAAAAAABYhuIUAAAAAAAALENxCgAAAAAAAJahOAUAAAAAAADLUJwCAAAAAACAZShOAQAAAAAAwDIUpwAAAAAAAGAZilMAymz79u0KDw/XPffcU+5jZGdnq0aNGurUqZMHIwMAa5AXAeAMciKAsqI4BaDMHn30UYWHh2vs2LHlPkZ0dLQeeOABrVmzRh988IEHowMA3yMvAsAZ5EQAZWUzDMOwOggAgSM1NVVdunTRiBEj9Oabb7p1rCNHjig+Pl6NGjXS999/L5vN5qEoAcB3yIsAcAY5EUB50HMKQJnMmDFDkjR8+HC3j1WjRg3169dPP/74o5YvX+728QDACuRFADiDnAigPChOAXDZgQMHtGTJEsXFxalLly4eOeatt94qSZo1a5ZHjgcAvkReBIAzyIkAyoviFBDELr30UtlsNpe2t95667zHW7x4sU6ePKk+ffooLKzk9JGbm6unnnpK7dq1U0xMjKKiotSgQQN16dJFkydP1smTJ4va9u7dWxEREVqyZIlOnDjhkdcNACUhLwLAGeREAP4iwuoAAHjHsWPHVLduXdWuXbto3++//67MzEwlJiaqQYMGDu07d+583mOuXr1aktSuXbsS2+zevVtdu3bVb7/9pqioKDVu3FiVK1fWzp07lZqaqrS0NI0bN66ofaVKldSsWTNt3bpVmzZtYkUWAF5DXgSAM8iJAPwJxSkgSFWqVKnoA4LdwIEDlZKSoilTpugvf/lLmY+5du1aSVLr1q1LbHP//ffrt99+03333acpU6aoevXqRff99NNPWrVqVbHJLNu2bautW7fq66+/5gMHAK8hLwLAGeREAP6E4hQQQr777jtJUrNmzcr8WMMwtGvXLklS/fr1nbY5efKkPvnkE8XExOill14q1p37sssu02WXXVbscfbj/fHHH2WOCwDcQV4EgDPIiQCswpxTQIj4888/9fvvvysiIsLpH/3zOXr0qPLz8yVJsbGxTtucOnVKBQUFysvL0/r1610+tv14Bw4cKHNcAFBe5EUAOIOcCMBKFKeAEPH999+rsLBQl1xyiSIjI8v8+OPHjxddL+nxVapU0XXXXaf8/Hx17txZN9xwg9566y0dOnSo1GNXqlRJkjn3AQD4CnkRAM4gJwKwEsUpIETYu2k3bdq0XI8/+xewrKysEtstWLBAjz32mGrVqqVPPvlEI0aMUL169TRw4ED99ttvTh9z+PBhSVKtWrXKFRsAlAd5EQDOICcCsBLFKSBEbNu2TVL55hCQpKioKEVHR0s68wHBmSpVqmjq1Knas2eP1q1bp4cfflhVqlRRSkqKevXqpYKCgmKPsR/v7NViAMDbyIsAcAY5EYCVKE4BIeKnn36SJF1xxRXlPkbLli0lST/++ON524aHh6t9+/Z69tln9d1336lixYr6/ffftXPnzmJtf/jhB0nSlVdeWe7YAKCsyIsAcAY5EYCVKE4BISIjI0OS1LBhw3Ifw7507+bNm8v0uDp16kgyP4Q4myBz06ZNkqTOnTuXOzYAKCvyIgCcQU4EYCWKU0CIqFChgiT3luDt1auXJOnrr78udt+bb76pxx9/XP/73/8c9u/Zs0e33nqrjh8/rgEDBigmJsbh/l9//VX79u3TZZddpoSEhHLHBgBlRV4EgDPIiQCsRHEKCBH2X5puvfVWtWrVSpMnTy7zMbp06aKLLrpIK1eu1L59+xzuW716tZ566ildeumlql+/vtq1a6fLL79ciYmJ+uCDD9SyZUu9+uqrxY45f/58SdLIkSPL8aoAoPzIiwBwBjkRgJUoTgEh4sknn9Rf//pXValSRWlpaQoPDy/zMWw2m+68804VFBQUfVCwu/vuu/XYY4+pQ4cOstlsSktL0549e9S2bVtNnz5dGzZscDqJZXJysipUqKDhw4eX+7UBQHmQFwHgDHIiACvZDMMwrA4CQODIzs7WhRdeqNjYWP34448KCyt/jXvFihXq3r27/va3v+nll1/2YJQA4DvkRQA4g5wIoDzoOQWgTKKjo/XEE0/of//7n9577z23jjV58mRVrVpV48eP91B0AOB75EUAOIOcCKA8IqwOAEDguffee5Wdna3CwsJyHyM7O1tdu3bVAw88oLp163owOgDwPfIiAJxBTgRQVgzrAwAAAAAAgGUY1gcAAAAAAADLUJwCAAAAAACAZShOAQAAAAAAwDIUpwAAAAAAAGAZilMAAAAAAACwDMUpAAAAAAAAWIbiFAAAAAAAACxDcQoAAAAAAACWoTgFAAAAAAAAy1CcAgAAAAAAgGUoTgEAAAAAAMAyFKcAAAAAAABgGYpTAAAAAAAAsAzFKQAAAAAAAFiG4hQAAAAAAAAsQ3EKAAAAAAAAlqE4BSDovfrqq7ryyitVoUIFTZw40epwAMBS5EQAAOBvKE4B8EsLFy5UXFycatSooWeffdatY9WvX1+TJk3SgAEDPBMcAPgYOREAAASzCKsDAIBz5eTk6K677tKMGTNUrVo1jRw5Un369FGzZs3KdTz7F7APPvjAg1ECgG+QEwEAQLCjOAXA7xw7dkyGYah58+aqWrWqqlevrvz8fKvDAgBLkBMBAECwY1gfAtamTZs0YsQINWrUSFFRUapZs6auv/56paamWhpXbm6uxowZo7i4OFWsWFEtW7bUe++959Jjc3Jy9Mgjj6hXr16qXbu2bDZbifOBbN26VQMGDFBcXJwqV66syy67TJMnT9aff/5ZrmOOGDFCNputxG39+vVFbVeuXOlSu/KqU6eOBgwYoGbNmqlx48YaPHiwWrVq5fZxy2Py5Mlq0qSJCgsLi/a5ek69dZ5mz56tBg0aKC8vr9zHQPAJ9Zy4ceNG9e7dW9WqVVPVqlXVrVs3rVmzxq1jliV2d17n+QRLTpRc/3cqC3IiAACBj+IUAtK4cePUvn177d69W5MnT9ann36qF154Qbt371bXrl317rvvWhZbUlKS3nrrLU2YMEHLli1T27ZtNWTIEM2bN++8jz106JBmzpypEydOlDoXyA8//KCOHTtqx44dmjZtmj7++GPdeuutmjx5soYMGVKuY44bN07r1q0rttWqVUsNGjRQ27Ztiz3mqaeeKta+adOm532drjj7i0+nTp2ctunRo4cqVqzodBs3bpzbMezZs0fPPvusJk+erLCwM+nS1XNq5+nzNHz4cFWpUsXteWcQPEI9J27atEldunTRsWPH9M477+idd97R8ePH1aNHD61bt65cxyxr7O68TlcEQ04sy79TWZATAQAIAgYQYMaPH29IMv79738Xu+/48ePGhRdeaMTExBhHjx71eWyffPKJIcmYN2+ew/6ePXsacXFxRn5+fqmPLywsNAoLCw3DMIwDBw4YkowJEyYUa/f4448bkoxff/3VYf9dd91lSDIOHz5c5mM6s3LlSkOS8cQTTzjsX7FihSHJWLBggUvHKauvv/7asNlsxvXXX29IMqZOneqR444aNcrl124YhvHII48YDRo0MAoKChz2u3pOvXmennvuOSMmJsbIy8vz+LERWMiJhtG7d2+jbt26Du+H7Oxso1atWkbHjh3LdcyyxO7u6zyfYMmJZfl3KityIgAAgY2eUwgo69ev15QpUzR8+HA99NBDxe6PiorSXXfdpaysLH311Vc+j2/x4sWqWrWqbr75Zof9t99+u/bs2aMNGzaU+nj7kK/zqVChgiQpJibGYX/16tUVFhamyMjIMh/TmdmzZ8tms2nkyJHlenx5FBQU6P7771d8fLzeeusthYeHKy0tza1j5ufn6/jx4yooKHC4XpqTJ09q9uzZGjp0qEMPAcm9c+opf/nLX5Sdne2xYUMITORE05o1a9S1a1dVrly5aF+1atXUpUsXrV27VpmZmWU+Zllid/d1liaYcmJZ/p3KipwIAEBgoziFgPLkk0/KZrNp8uTJJba54IILJEm7d+92+biGYSg/P9+lrTTbt2/X5ZdfrogIx7UGmjdvXnS/JwwfPlzVq1fXvffeq99//105OTn6+OOP9dprr+m+++5TlSpV3H6OrKwsLVy4UD169FDjxo2dtrnvvvsUERGh6Oho9e7dW19//bXbz/vf//5XaWlp+ve//62aNWvq4osvdvuL2JQpU1SpUiXNmTNH//rXv1SpUiW98847pT5mw4YNOnTokLp16+bWc0veOU/16tXTZZddpk8++cTtYyFwkRNNJ0+eVFRUVLH99n3btm0r8zHLErs3X2cw5URv/DvZkRMBAAhsFKcQMLKysvT555+rV69eatiwYYntcnNzJalMBZpVq1apQoUKLm07duwo8TiHDh1SbGxssf32fYcOHXI5ptIkJiZq3bp12r59uy688EJFR0erX79+Gj58uKZPn+6R50hOTtaxY8c0atSoYvfFxMRo9OjReu2117RixQpNnz5du3btUteuXfXZZ5+V+zkPHDigcePG6ZprrtHgwYMlmV/ufvnll2ITvZfFxIkTZRiGwzZixIhSH2Of/+TKK68s9/N66zzZXXnllW5PJIzARU48o0mTJlq/fr3DvEz5+flFPZbK8zxlid1brzPYcqI3/p3ORk4EACBwRZy/CeAftm3bpvz8fDVr1qzUdvYP0PZfrF3RunVrbdq0yaW2cXFxpd5f2tAGTw0F27Fjh/r166e6detq4cKFql27tjZs2KApU6YoNzdXs2fPdvs5Zs+erZo1a+qmm24qdl+rVq0cVorq3LmzbrrpJjVr1kyPPPKIevfuXa7nfOyxx5Sdna2XXnqpaF/z5s31/vvv67vvvlP79u3Lddzy2LNnj2w2m2rVqlXuY3jrPNnVqVNH+/fvV35+frEeGwh+5MQz/v73v2vUqFG6//779fjjj6uwsFCTJk3SH3/8IUnFhqG5qiyxe+N1BltO9Na/kx05EQCAwMVfbgSM7OxsSVLt2rVLbJOTk6Pk5GQ1btxYbdq0kST179/fYa6VvLw8paamOqx2VLVqVbVs2dKlOEr7wFuzZk2nv/wePnxYkpz+sl4e9i8saWlpRb0hunTpolq1amnkyJEaNmyYrrnmmnIf/7vvvtPmzZs1evRop0MwnKlevbpuuOEG/fe//9WxY8dUqVKlMj3nxo0b9eabb2rYsGFq2LChjh49KunMkKS0tDSffhE7duyYKlSooPDwcI8e193zdLaKFSvKMAwdP35cVatW9WCUCATkxDNGjhypAwcOaMqUKXr11VclSR06dNBDDz2kZ555Rg0aNCjzMcsSuzdeZzDmRG/8O52NnAgAQOBiWB8CRnx8vCSVOoTk2WefVU5OjiZMmFD0S/UHH3yg3Nxc5ebmatSoUUpKSlKHDh0cHuepISzNmjXTjz/+WGweFvs8Gk2bNi3HKy8uLS1NTZo0KTZMp23btpLcn8fF3vPqjjvuKNPjDMOQVPZeAoWFhbrvvvtkGIbeeust1ahRo2gbOnSoJLk9x0pZ1apVSydPnlReXp7Hj13e83Suw4cPKyoqii9hIYqc6OjRRx/VwYMHtW3bNu3YsUNr167VkSNHVKVKFbVu3brMxytL7J5+ncGcEz3973Q2ciIAAIGLnlMIGM2aNdOFF16o5ORkPfnkk6pRo4bD/XPnztVTTz2lW265RcOHDy/2+LFjx+qXX37RkiVLiv3y66khLDfddJNef/11LVq0qGh+EEl66623FBcXp6uuusql53Alhu3btys3N9fhQ7h9+I79S2t5nDhxQnPnzlW7du3K9IXqyJEj+vjjj9WyZUtVrFixTM/5+uuva/PmzZo0aZK6dOlS7P6BAwf6/IvYZZddJkn67bffyjQc6nzcOU/n+v3339WkSRMPRYZAQ04sLioqqihv7dy5U/Pnz9edd95Zrh6KZYnd068z2HOiJ/+dzkZOBAAgcFGcQsCw2Wx6/fXX1bdvX7Vt21aPPvqoLrroIu3du1fvvfeePvzwQ40YMUIzZ84s9tjJkydrw4YNWrp0qSIjI4vdX61ataIhL+7o06ePevbsqXvvvVfZ2dm66KKLlJycrE8//VRz584t+gK4atUq9ejRQ+PHj9f48eMdjrFs2TLl5eUpJydHkvTDDz9o4cKFkqS+ffuqcuXKGjNmjAYMGKCePXvqH//4h2rVqqX169dr6tSpatKkifr06VPmY9otWbJEhw8fLrXX1NChQ9WwYUO1adNGtWrV0i+//KLnn39e+/bt05w5c8p0zg4fPqzHH39cHTt21Lhx45z2JmrRooU2bNigwsJCt+ckcVXXrl0lSevXr3f6RcyVc+rJ83SuwsJCbdy40emE9QgN5MQz77Xt27dr0aJFatOmjaKiovTtt9/q6aef1sUXX6wnn3yyWFyuHNPV2MvyOl0RzDmxrP9OZUFOBAAgwBlAgPn222+NW265xahbt64RFhZmSDIaNWpkfPHFF07bP//880aHDh2MnJwcn8SXk5NjPPDAA0a9evWMyMhIo3nz5kZycrJDmxUrVhiSjAkTJhR7fKNGjQxJTrf09PSidsuXLzd69epl1KtXz6hUqZJxySWXGP/85z+NgwcPlvuYhmEYPXv2NKpUqWJkZ2eX+BqnTp1qtGzZ0oiJiTHCw8ON2rVrGzfddJOxcePGMp0rwzCMu+++24iIiDC2bdtWYpsxY8YYkowff/yxzMd3R+fOnY2+ffs6vc+Vc+rJ83Sur776ypBkbNmyxe1jIbCREw3j559/Nrp06WLExsYakZGRxkUXXWQ88cQTRm5urtOYXM2JrsRenralCeacWNZ/p7IgJwIAENhshnF68hMgQN12222aP3++1q5dW+yX/ldffVWzZs3S8uXLFRMTY1GECFT2ITp//PGH2xP1etptt92m33//nWXTUQw5Ed5CTgQAAN5CcQoBLzs7Wy1atFBkZKS++eYbh0nCq1evruPHjzusJrVixYqiicOB0hiGoY4dO6p169aaMWOG1eEU+e2333T55Zdr+fLlDiusARI5Ed5DTgQAAN7CnFMIeNHR0UpPT3d6n33pbaA87HP6fPjhhz6d2+V8du7cqRkzZvAlDE6RE+Et5EQAAOAt9JwCAAAAAACAZfzjJy8AAAAAAACEJIpTAAAAAAAAsAzFKQAAAAAAAFiG4hQAAAAAAAAsQ3EKAAAAAAAAlqE4BQAAAAAAAMtQnAIAAAAAAIBlKE4BAAAAAADAMhSnAAAAAAAAYBmKUwAAAAAAALAMxSkAAAAAAABYhuIUAAAAAAAALENxCgAAAAAAAJahOAUAAAAAAADLUJwCAAAAAACAZShOAQAAAAAAwDIUpwAAAAAAAGAZilMAAAAAAACwDMUpAAAAAAAAWIbiFAAAAAAAACxDcQoAAAAAAACWoTgFAAAAAAAAy1CcAgAAAAAAgGUoTgEAAAAAAMAyFKcAAAAAAABgGYpTAAAAAAAAsAzFKQAAAAAAAFiG4hQAAAAAAAAsQ3EKAAAAAAAAlqE4BQAAAAAAAMtQnAIAAAAAAIBlKE4BAAAAAADAMhSnAAAAAAAAYBmKUwAAAAAAALAMxSkAAAAAAABYhuIUAAAAAAAALENxCgAAAAAAAJahOAUAAAAAAADLUJwCAAAAAACAZShOAQAAAAAAwDIUpwAAAAAAAGAZilMAAAAAAACwDMUpAAAAAAAAWIbiFAAAAAAAACwTYXUACEyFhYXas2ePqlWrJpvNZnU4AHzEMAzl5OQoLi5OYWH8vmFHTgRCEzkRAADPoDiFctmzZ48SEhKsDgOARXbt2qX4+Hirw/Ab5EQgtJETAQBwD8UplEu1atUkmR/GoqOjLY4GgK9kZ2crISGhKAfARE4EQhM5EQAAz6A4hXKxD1uJjo7mixgQghi65oicCIQ2ciIAAO5hcDwAAAAAAAAsQ3EKAAAAAAAAlqE4BQAAAAAAAMtQnAIAAAAAAIBlKE4BAAAAAADAMhSnAAAAAAAAYBmKUwAAAAAAALAMxSkAAAAAAABYhuIUAAAAAAAALENxCgAAAAAAAJahOAUAAAAAAADLUJwCAAAAAACAZShOAQAAAAAAwDIUpwAAAAAAAGAZilMAAAAAAACwDMUpAAAAAAAAWIbiFAAAAAAAACxDcQoAAAAAAACWoTgFAAgqq1evVr9+/RQXFyebzaYlS5a4/Ng1a9YoIiJCLVu29Fp8AAAAABxRnAIABJW8vDy1aNFCM2bMKNPjsrKyNGzYMPXo0cNLkQEAAABwhuKUnytrD4CUlBT17NlTtWvXVnR0tDp06KDPPvvMoc2cOXNks9mKbcePH/fiKwEA3+jTp4+mTJmipKSkMj3u7rvv1tChQ9WhQwcvRQYAAADAGYpTfq6sPQBWr16tnj17aunSpdqyZYu6deumfv36aevWrQ7toqOjlZmZ6bBVrFjRGy8BAPzem2++qd9++00TJkxwqf2JEyeUnZ3tsAEAAAAonwirA0Dp+vTpoz59+rjcftq0aQ63n3rqKX3wwQf66KOP1KpVq6L9NptN9erV81SYABCwfvnlFz322GNKTU1VRIRrfxanTp2qSZMmeTkyAAAAIDTQcyrIFRYWKicnR7GxsQ77c3Nz1ahRI8XHx+uGG24o1rPqXPQSABCMCgoKNHToUE2aNEmXXHKJy48bO3assrKyirZdu3Z5MUoAAAAguNFzKsg9//zzysvL0y233FK077LLLtOcOXPUrFkzZWdna/r06br66qv17bff6uKLL3Z6HHoJAAhGOTk52rx5s7Zu3ar7779fklnUNwxDERER+vzzz9W9e/dij4uKilJUVJSvwwUAAACCEsWpIJacnKyJEyfqgw8+UJ06dYr2t2/fXu3bty+6ffXVV+vKK6/Uf/7zH7300ktOjzV27Fg9+OCDRbezs7OVkJDgveABwAeio6O1bds2h32vvPKKli9froULF6px48YWRQYAAACEDob1Ban58+dr1KhRev/993XttdeW2jYsLExt27bVL7/8UmKbqKgoRUdHO2zwXyNGjHC6IqN9W79+fVHb3NxcjRkzRnFxcapYsaJatmyp9957r0zP9/XXX6tv376qUaOGKlWqpIsvvlhPPvlkqY+ZNWuWbDabqlatWuy+5cuXa+TIkbrssstUpUoVNWjQQP3799eWLVvKFBdCU25urtLS0pSWliZJSk9PV1pamnbu3CnJLLYPGzZMkpn/mjZt6rDVqVNHFStWVNOmTVWlShWrXga85Hz5KicnR4888oh69eql2rVry2azaeLEiS4fPy0tTddff70aNmyoSpUqKTY2Vh06dNDcuXOdtt+4caN69+6tatWqqWrVqurWrZvWrFlT7vgBAAACET2nglBycrJGjhyp5ORkXX/99edtbxiG0tLS1KxZMx9EB18YN26c7rnnnmL7+/Xrp6ioKLVt27ZoX1JSkjZt2qSnn35al1xyiebNm6chQ4aosLBQQ4cOPe9zzZs3T7fddptuueUWvf3226patap+++037dmzp8THZGRk6KGHHlJcXJyysrKK3f/qq6/q0KFDGj16tJo0aaIDBw7o+eefV/v27fXZZ585HWYF2G3evFndunUrum3v9Tl8+HDNmTNHmZmZRYUqhBZX8tWhQ4c0c+ZMtWjRQgMGDNCsWbPK9BxHjx5VQkKChgwZogYNGigvL0/vvvuubrvtNu3YsUNPPPFEUdtNmzapS5cuateund555x0ZhqFnn31WPXr00IoVK9ShQ4cyxw8AABCIbIZhGFYHgZLl5ubq119/lSS1atVKL7zwgrp166bY2Fg1bNhQY8eOVUZGht5++21JZmFq2LBhmj59upKSkoqOU6lSJcXExEiSJk2apPbt2+viiy9Wdna2XnrpJb3zzjtas2aN2rVr51Jc2dnZiomJUVZWFr2oAsSqVavUtWtXPfHEE0W/si9dulTXX399UUHKrlevXvr++++1c+dOhYeHl3jMjIwMXXrppRo2bJheeeUVl2Pp16+fbDabYmNjtXDhQuXm5jrcv3//foehqJL5XrjooovUtGlTffnlly4/FzyL975znBf/52q+sn8sstlsOnjwoGrXrq0JEyaUqfeUM+3bt9eePXscCqPXXXed0tLS9Pvvv6ty5cqSzJ5bF1xwgS655BKHHlTlzbfwLt77AAB4BsP6/NzmzZvVqlUrtWrVSpLZA6BVq1YaP368JBXrAfDaa68pPz9f9913n+rXr1+0jR49uqjN0aNHddddd+nyyy9Xr169lJGRodWrV7tcmMIZM2bMKHX4XOXKlXXy5Emrw5QkzZ49WzabJtmYVwAAji9JREFUTSNHjizat3jxYlWtWlU333yzQ9vbb79de/bs0YYNG0o95qxZs5SXl6dHH33U5Tjmzp2rVatWlfrl6tzClCRVrVpVTZo0KbYq2k8//aTbbrtNiYmJioqKUt26ddWrVy/9/PPPLscEwHP8NS+6mq/scXparVq1FBHh2GF9zZo16tq1a1FhSpKqVaumLl26aO3atcrMzCzaX5Z8S14EAACBhmF9fq5r164qrXPbnDlzHG6vXLnyvMd88cUX9eKLL7oZGSSzB1CbNm0kSVu3btXf/vY3vfDCC0VDMSpXrqzIyMgyHdMwDBUUFLjU9twvOiXJysrSwoUL1aNHD4cJnrdv367LL7+82HGaN29edH/Hjh1LPO7q1asVGxurn376Sf3799f27dsVGxurpKQkPfvss8V+Rd6/f7/GjBmjp59+WvHx8S7FfvZr+OabbxyG9P3yyy9q27atunXrphdeeEG1atXSnj17tGzZMuYKAizir3mxrPnKXYWFhSosLNSRI0e0YMECffbZZ5oxY4ZDm5MnTzpd9dG+b9u2bapfv36Z4icvAgCAQERxCnBDo0aN1KhRI0nSN998I0kaNGhQsZUMDxw4oBEjRmjlypVq0KCBXn75ZfXs2dPpMVetWuUwX05p0tPTlZiYeN52ycnJOnbsmEaNGuWw/9ChQ7rggguKtY+NjS26vzQZGRn6888/dfPNN2vs2LGaNm2aNm3apAkTJmj79u1KTU116IHwt7/9TZdeeqnuvfdeF16do/vuu095eXl6/PHHi/a9++67Kiws1JIlSxQWdqYj6K233lrm4wPwDH/Ni2XNV+7629/+ptdee02SFBkZqZdeekl33323Q5smTZpo/fr1KiwsLMph+fn5Rb1Wz87BrsZPXgQAAIGI4hTgIWlpaYqNjS32BUwyCyv16tXTgQMH9OWXX+qWW27Rr7/+qpo1axZr27p1a23atMml54yLi3Op3ezZs1WzZk3ddNNNxe4r7cvY+b6oFRYW6vjx45owYYIee+wxSWZvv8jISI0ZM0ZfffVV0WqRixYt0kcffaStW7eW+QvguHHj9O677+o///mPWrduXbS/Vq1a+vPPP3X77bfrrrvuUvv27UudIwuAb/lTXixLvvKE//u//9Mdd9yh/fv366OPPtL999+vvLw8PfTQQ0Vt/v73v2vUqFG6//779fjjj6uwsFCTJk3SH3/8IUkOxSVX4ycvAgCAgGQA5ZCVlWVIMrKysqwOxW+0bdvW6N69e7H9OTk5RoUKFYydO3cW7bvmmmuM2bNnOz1OYWGhcerUKZc2V3z77beGJGP06NHF7mvfvr3Rtm3bYvu3b99uSDJee+21Uo/dvn17Q5LxzTffOOz/+eefDUnGM888YxiGeQ7q1q1r/POf/zSOHDlStA0ZMsSoUqWKceTIESM3N9fpc0ycONGQZPzrX/8qdt+pU6eMp59+2rjssssMSUbt2rWNBx54gP+XXsR73znOi3P+lBddzVdnO3DggCHJmDBhgouvuGT33HOPERERYezfv99h/9NPP21UrVrVkGRIMjp06GA8+uijhiQjNTW1zPGTF32L9z4AAJ7BhOiABxiGoe3bt6tly5bF7vvll19UtWpVh54DzZo10/fff+/0WKtWrVKFChVc2nbs2HHe2GbPni1JuuOOO4rd16xZM/3444/Kz8932L9t2zZJUtOmTUs9tn1uqnMZp+dJs//qf/DgQe3bt0/PP/+8atSoUbQlJycrLy9PNWrU0F/+8pdix5k0aZImTpyoiRMn6v/+7/+K3R8REaFHH31UP/74o3bt2qV77rlHL730kv71r3+VGjcA7/O3vOhqvvKWdu3aKT8/X7///rvD/kcffVQHDx7Utm3btGPHDq1du1ZHjhxRlSpVHHqKuho/eREAAAQihvUBHnD48GEdO3bMYbJxu9zc3GIT7UZHR+vgwYNOj+XJYX0nTpzQ3Llz1a5dO6eFpptuukmvv/66Fi1apMGDBxftf+uttxQXF6errrqq1OMPHDhQM2fO1LJly4pWlJSkpUuXSjKXTpekevXqacWKFcUe//TTT2vVqlVatmyZatWq5XDfk08+qYkTJ+qJJ57QhAkTSo1DkuLj4/X444/rueeeK1ZsA+B7/pYXXc1X3rJixQqFhYU5necvKiqqKEfv3LlT8+fP15133qlKlSq5FT95EQAABAqKU4AHREVFqUKFCvriiy/UvHlztWjRQjExMZKkqlWrKjs726F9dna2qlat6vRY1apVK1rpyl1LlizR4cOHnfaakqQ+ffqoZ8+euvfee5Wdna2LLrpIycnJ+vTTTzV37lyHeUpWrVqlHj16aPz48Ro/frwkqVevXurXr58mT56swsJCtW/fXps3b9akSZN0ww03qFOnTpKkihUrqmvXrsWef86cOQoPDy923/PPP6/x48fruuuu0/XXX6/169c73N++fXvdf//9ysrKUs+ePdWwYUMdOHBAM2bMUGRkZLFJhwH4nr/lRVfzlSQtW7ZMeXl5ysnJkST98MMPWrhwoSSpb9++qly5siTnefGuu+5SdHS02rVrp7p16+rgwYNasGCB5s+fr4cffli1a9cuep7t27dr0aJFatOmjaKiovTtt9/q6aef1sUXX6wnn3yyzPGTFwEAQMCydFAhAhZzLBT3wgsvGHFxcYYk4+effy7ab59bZdeuXUX7unbtWuLcKp7Us2dPo0qVKkZ2dnaJbXJycowHHnjAqFevnhEZGWk0b97cSE5OLtZuxYoVTude+fPPP41HH33USEhIMCIiIoyGDRsaY8eONY4fP37e+IYPH25UqVKl2P5rrrmmaP4VZ5thGMZ//vMfo3PnzkadOnWMqKgoo3HjxsbIkSON33777bzPi/Ljve8c58U5f8uLruarRo0alZh/0tPTi9o5y4tvvPGG0blzZ6NWrVpGRESEUb16deOaa64x3nnnnWLx/Pzzz0aXLl2M2NhYIzIy0rjooouMJ554osQ5+M4XP3nR93jvAwDgGTbDOD1ZAVAG2dnZiomJUVZWVrGhGSju5ptvVkxMjP7zn//oq6++0m233aZffvml2FA2wN/x3neO81J25EUEA977AAB4BsP6AB945ZVXNHz4cNWsWVMNGjTQ/Pnz+QIGICAVFEipqVJmplS/vtS5s3TWCGCXkRcBAABgR3EK8IHatWsXTVoLAP7IlaJTSoo0erS0e/eZffHx0vTpUlJS2Z6PvAgAAAA7766bDAAA/F5KipSYKHXrJg0dal4mJpr7z24zaJBjYUqSMjLM/We3BQAAAMqC4hQAACHMlaJTQYHZY8rZLJX2fWPGmO3KqqBAWrlSSk42L0+edLxdnmMCAAAgsDCsDwCAEHW+opPNZhadYmKKF6/ObbtrlzkssHNn1+ekcjZMMDzcsSBV3mGDAAAACBz0nAIAIESlprpWdFq50rXjffDB+YcH2pXUY+vcnlIMGwQAAAh+9JwCACBEZWZ69njTphXfZy8uzZ8v1a5tPmedOiX32DrX2T24+vcv38qAAAAA8G8UpwAA8CFXVsXz1fHr13ftmF27SnPmmIWmkgpK5w7Hs7O3HzKk/PNHnT1ssGvX8h0DAAAA/othfQAA+Igrq+L58vidO5tzOtlszu+32aSEBLMgNH36mX3ntpHOX3jyxMTmnu7pBQAAAP9AcQoAAB9wZVU8Xx8/PPz8Radp08x2SUnSwoVSgwaO7eLjzSF3vlC/fvHV/VjNDwAAIPBRnAIAwMvOtyqeZBZ4yltocef4pRWdFi50XCUvKUnasUNasUKaN8+8TE8354LyJnsProMHvdvzDAAAANZgzikAALzM1VXxyjunkrvHT0oyC0yuzFUVHl78GPbhgaXNSVVe9h5ct94q3XJL8ePbe4adW0gDAABA4KA4BQCAl509V1KSFmmyxsuQTYUKU6HCiq4njgqTatqksDBzs7l2/eK9YfrgrOMUKkwFCle+IpSvCJ1SBeUrQnFPRUiLI6SI01uFCkXXwyMi1DUiQoqMlHIqSn9ESRUrmluUk+uVK0tVq0pVqyo8MlLTp9s0aJAZmjsFqnMnVo+Pl55/XnrwwZJ7hrGaHwAAQGCjOAUAgJedvSperA7rCv3gvOHvp7cyanB6O68vTm+eFhGhpKpVlRtbVRlZVXU0v6qyFKMjqqGjtho6bNTQEZnbIdXUPtXVPtXVftVVtQbRmvOWTfv3m+epY0dp7VrHHlze7nkGAAAAa1GcAgDAy84e9vaxcYO6aoXCVCibDIWpUOEqVO1ahua8UahwW6FZbSksNDcXrhcWGHrk4UJlHymUZChcBQpToSrolCKUrwrKV2x0vv45Ol9hhfnSqVNSfr7jdurUme34cenECfPS2fVjx8zt+HHzBebnS0ePqrKO6uJzX/x5elEV7I9S+Mi65qRSCQnSsobqmpBgTiYVf5mkxsrMdK071FdfnX9YIgAAAPwPxSkAALzMvireoEHSPlt97TXOdKWyz6m08DUpvF/5jh8mqWMN8/iS4/C3ouO/KYV5ek6m/HwpL0/KzXXccnKko0elI0ekI0f0y6YjSlt+RJF/HlEtHVRd7VM92z5VNXIVfuqEtHOnuTkTGal+DS7RfF2un3SZftTl+vH09ROq6NB0ypQz1+PjzXPOPFQAAAD+z2YYnp66FKEgOztbMTExysrKUnR0tNXhAPAR3vvOuXpeUlLMVfXOHqKWkCBNm+aZIoq3j++OggInE66f+FPav9/cuXu3OTZv507z8rffpJ9/PtM76xwnVUFb1Upr1VHr1EFr1VEZii+6316Umz9fql2bHlXwDnIiAACeQXEK5cKHMSA08d53riznxWmRxoPFEm8f36cKCsxi1Y8/6rv3f9LGt37UpfpJTfSDaupwsea7FK81ulrL1EdL1VcHVdvpBOv0qIKnkBMBAPAMilMoFz6MAaGJ975znBffONMzzFCidqiD1qmj1qqD1qmFvlWEzlShCmXTOnXQR+qnj9RPP6iJJNuZYY4LKVDBfbz3AQDwDIpTKJdg+DAWVL0LAB8Jhve+N3BefOfs3P3DD2fmmaqsPLXVJnXXcvXTR2qlNIfHbdcVekMjNVd/1QHVUWys9P775up+5H6UF+99AAA8g+IUyiXQP4w5m5eFoR7A+QX6e99bOC/WWLlS6tbN+X3x2qUb9LH66SN113JV1AlJ0ilF6EPdqDc0UsvURw3iw8j9KDfe+wAAeEaY1QEAvpaSYq5odXZhSjKXeB80yLwfAOD/Onc2f1iwD9U7224l6L+6V9drqepqn+7Wf7VRbVVB+RqoFH2iG/SNrlSL3Z9o0ECD3A8AAGAhilMIKQUFZo8pZ/0F7fvGjHGcPBcA4J/Cw80er5LzApVdtmI0U3frKm1UM32nFzVG2aqmlvpWH+sGpaqTku9ZRe4HAACwCMUphJTU1OI9ps5mGOYK5qmpvosJAFB+SUnm5OYNGjjuL2keqe1qpgf1ohorXc/qYR1TRV2ttVpwoKuy2veWNm/2ftAAAABwQHEKISUz07PtAADWS0qSduyQVqyQ5s0zL997z+xNVVKPqsOqqUf1rC7Ub3pZf9MpRSh28+dS27bmAb//3qevAQAAIJRRnIJXFRSYE9YmJ5uXVg+ZqF+/7O387TUAAIoLDzdX3hsyxLwcNMh5j6pzZSpO9+tlXaqftbfXMCksTFq8WGrRQnr6aamw0BfhAwAAhDSKU/CalBQpMdFcSWnoUPMyMdHaCcdLmzxXMvcnJJjtJP98DQAA19h7VH35pRQbW3I7m03KT7hAtZe+JW3bJt14o/lLxNixUu/e0t69PosZAAAgFFGcglf4akW8svZqKm3yXPvtadPMdqzqBwCBLzxc6tFDev1158P8zs39BZc20coxS7ThrtkqqFjZrGw1by59+qnPYwcAAAgVFKfgcb5aEa+8vZpKmjw3Pt7cn5Tkmdfg7eGAOTk5euSRR9SrVy/Vrl1bNptNEydOLPNxvv76a/Xt21c1atRQpUqVdPHFF+vJJ58s9/Pk5uZqzJgxiouLU8WKFdWyZUu999575XiFAFA2peWr8+X+Dz8cIZvNpogIm7p1D1P7maMUcfxP2STZDhzQ+j59pIcf1ohhw2Sz2Urc1q9f73B8ciIAAMD5UZyCx/liRTx3ezU5mzw3Pd3c74nX4IvhgIcOHdLMmTN14sQJDRgwoFzHmDdvnq655hrFxMTo7bff1tKlS/Xoo4/KOKsqV9bnSUpK0ltvvaUJEyZo2bJlatu2rYYMGaJ58+aVK0YAcNX58lVpub9du3GS1jnZaqm6qqitJD33nMalpWldSorWrVvnsNWqVUsNGjRQ27Ztz3lOciIAAMD5RFgdAIKPt1fEO1+vJpvN7NXUv3/JS4lLZybPdSc2Z+3shbNz47MXzuy9s+wKCswiV2amORF7586lx23XqFEjHTlyRDabTQcPHtSsWbNcC7oongzddddduvvuu/XKK68U7e/WrVu5n2fp0qX64osvNG/ePA0ZMqToeH/88YcefvhhDR48WOGuvDgAKAdX8pWz3F9QIE2deqGkC89pvUrSQR3VE7qn5pWaWThKF27bpgsfeEBavly6+GKz1apVOnjwoJ544gmHHEdOBAAAcA09p+Bx5VkRryx80TOrLK/BMAz997//VbNmzVSxYkXdcstFMoyFkgolNZX0VFFckuNwQHd6WNmHkJTXrFmzlJeXp0cffdRjz7N48WJVrVpVN998s8P+22+/XXv27NGGDRvKHS+AwHFuXrzooou0cOFCFRYWqmnTpnrqqae88rzlzYsl/12ZLckmaaRmHbpJ619Nky67zGzcpYv0ww9mq9mzZbPZNHLkSIdHkxMBAABcQ3EKHlfWFfHKyts9syTXX0OHDoa6dRus0aMf1NVXD9PkyR+roKCxpBGS5kg6ImlM0ePshbPVqw0tWJCvgQPztXt3vqQz2+7d5v4FC/KVn59f/hdxHqtXr1ZsbKx++ukntWzZUhEREapTp47uueceZWdnl+uY27dv1+WXX66ICMdOmc2bNy+6H0BwMwxDgwcP1oMPPqhhw4bp448/VuPGjTVixAjNmTNHR44c0ZgxY5w+Lj8/36XN05z/vciStFBSD0mNJUk7ChtKq1aZE6Tv3Stdc42yUlO1cOFC9ejRQ40bN3Y4AjkRAADANRSn4HFlWRGvPLzdM0ty7TXceqtUv/4crVq1QCdPztJrrz2sZ565VtJ4SXmSHpI0SVLlYsf/8stVuuWWCpJK3m65pYIqVKigHTt2lP+FlCIjI0N//vmnbr75Zg0ePFhffvmlHn74Yb399tvq27evw7xTrjp06JBinazXbt936NAht+MG4N/mzJmjBQsWaNasWXr44Yd17bXXavz48crLy9NDDz2kSZMmqXLl4nlx1apVqlChgkubp/Oi878XyZKOSRrl2K5OHXOyqtatpYMHldy7t44dO6ZRo0YVOwI5EQAAwDXMOQWvsK+KNHq041CJ+HizMHX2nEtlZe/VlJHhfN4pm828v7w9s+xKew233io995xkGDNkDt0bKkk6fFiSapxuWU/S7U6PXa1aa0mbzhvDf/8rxcXFlf9FlKKwsFDHjx/XhAkT9Nhjj0mSunbtqsjISI0ZM0ZfffWVrr322jIft7QhNe4MQwQQGGbMmKGmTZtq6NChRftq1DDzYr169XT77c7zYuvWrbVp0/nzouT5vOj878psSTUl3VT870psrPTVV1Lfvpq9dq1q2my6qU4dp8cmJwIAAJwfPaf83OrVq9WvXz/FxcXJZrNpyZIlpbZPSUlRz549Vbt2bUVHR6tDhw767LPPirVbtGiRmjRpoqioKDVp0kSLFy/2eOznWxGvvLzdM+tszl7Dr79KycmSYRyRtFVSv3MedXpCKf1LkmMQ9uGA8fFVJbU871alSktFRka6/0KcqFmzpiSpd+/eDvv79OkjSfrmm2/KdUxnPQEOm1U7pz0IAASPI0eOaOvWrerXzzEvFpyeaO9f//pXiROAV61aVS1btnRp83ReLP535TtJmyX9VTZblCQnf1diYvTd88+brQxDUQMGFM1BZUdOBAAAcA09p/xcXl6eWrRoodtvv10DBw48b/vVq1erZ8+eeuqpp1S9enW9+eab6tevnzZs2KBWrVpJktatW6fBgwfrySef1E033aTFixfrlltu0ddff62rrrrKo/GHh0td3x4ppaWZN8LCzmxn3y7pegn3JYWF6fdu4Vq7IUw5eWEqULhOqYIqVq2grtdW0KVpFaQfIqUKFcwtspTrFStKlSpJlSubl/bt9O3w8HCHlZ1WrrT3pPpVkiH7XCRnzDx96bicuM1m/iJ/xx3SZ5+tktRN53PbbVKnTulKTEws1/kvTfPmzbV+/fpi++3D+cLCyl67btasmZKTk5Wfn+8wx8q2bdskSU2bNi1ntAACwa+//irDMIrNvTRzppkX27Zt6+xhksxhfeeuFlqS9HTP50XH3rKzT++9w6HH77mrq6akJJutWreWtmyRbrxR2rBBOl38JycCAAC4huKUn+vTp09RTxZXTJs2zeH2U089pQ8++EAfffRRUXFq2rRp6tmzp8aOHStJGjt2rFatWqVp06YpOTnZY7EX+flnaetWjx828fTmIEfS4tObp1SoYBaqqlaVoqPV9FS0PlO0vlW+HpF0vd7UVdqpw4rV/5StZXpNhqRm1dK1K6eKjqq6JJvsP5BPmCBJ5x/WV7eu9MEHUt26cVq58syXoc6dPdMrbODAgZo5c6aWLVtW9H9DMpc+l6T27duX+Zg33XSTXn/9dS1atEiDBw8u2v/WW28pLi7O48VPAP7F3ivqwIEDRfu2bNlSVJwqbS47K4f12SUlSdddd0L1689V7drtNGtW06Kcm5Jy7jDvEwoLm6uLL26npp9+IrVtK/32m3TLLdKnn0oVKpATAQAAXERxKsgVFhYqJyfHYejAunXr9I9//MOhXe/evYsVts524sQJnThxouh2mVZze+EFczKmwsIzW0GBZ2/n55vbyZPSqVPm5ur148elP/+Ujh07sx0/fib+U6ekrCxzy8hQLUm9JF0j6d+SNmidhmqdLpY0X9JgSe9J6p/TRXdJiouIVE6VevrpUH1lqr72qp4y1EB/qJF2KFF/qJH2KE4Fp9+O9qGJr7xizn8yaFDxOa+mTze/RC1btkx5eXnKycmRJP3www9auHChJKlv375Fkw6vWrVKPXr00Pjx4zV+/HhJUq9evdSvXz9NnjxZhYWFat++vTZv3qxJkybphhtuUKdOnYqe09Xn6dOnj3r27Kl7771X2dnZuuiii5ScnKxPP/1Uc+fOLXE4D4DgcMUVV6h27dp68cUXlZiYqLCwMD344IMaNGiQ3nvvPc2cOVN33XWXEhISij22WrVqatOmjdsxuJMXJemjj5YoO/uwnnvujqJesykpZi52rK0tUWHhYf3yyx1KWV1LSR9+KHXsKC1fLo0ZI738MjkRAADAVQYChiRj8eLFZXrMs88+a8TGxhr79u0r2lehQgXj3XffdWj37rvv/n97dx7eVJn+f/yTtnQRaGUtlBaKyioCZV8sgkoRhAErA8IIOq7M6EjlN46iiKKOjI4LuIAiIqJD5SsUcEEFtGyCQIHihriBlFJWtaUghbbn98chgdC0dElykub9uq5zJXnOc07uHDmPzZ1nMUJDQ0s9zyOPPGLIHMPmtOXm5lYoHr9RVGQYx48bxuHDhpGVZRg7dxrGli2GkZ5uFC5eavyjzlvG3/Wy8RfdacSokRGiIKOmQo2Rijc2K8EYbatl1JCMmeZ3mfNuJxVi7FQLY7GGGi/Wnmhs+sc849OnM4yayi9R3WYzt0WLDKNZs2Yu/7tIMnbt2uX4OOnp6YYk45FHHnH6mMePHzfuv/9+Iy4uzggJCTGaNm1qTJw40Thx4oRTvfK+j2EYxtGjR4177rnHaNSokREaGmq0b9/eSE1N9dB/KHhbbm5u9b73K4nrcsa6deuMzp07G6GhoUadOnWMiRMnGsXFxcYdd9xh1KhRw5g5c6ZH37+q7WL//v2NmjVrGnl5eYZhGEZhoWHExrpquvsbUk1DyjPi4sx6xpIlZgMtGcbpz0mbWL1x7wMA4B42w6jEevGwhM1m0+LFizVs2LBy1U9NTdVtt92mpUuXOq26FhoaqjfffFOjRo1ylP3vf//TrbfeqhNn9xg6i6ueU3FxccrNzVVkZGTlPpAfs/+KLjn/km7v9bRw4emJ3wsKtGHJAaXckCOz35S5xWqvmukXxWu34pSlUJ0q9b12q5m+VVtlqIs2qKe+UA/l2uooNtacYJ4f3uFNeXl5ioqKCth7vzRcl+pr1SqpPFNhpafL7Gk1dar04INSSIi0cqV0xRUejhBW4t4HAMA9GNZXTS1YsEC33nqr3n33XafElGQu5b1//36nsoMHDyo6OrrU84WFhSksLMwjsfoj54lzz5SfPXGuJCksTLuLm2qTmpZ6riAVqbFyNO/Bnbqy8Q7p22/1+/pvVbB9h6J1UPH6RfH6RYP0keOYb4022pDVUz8+0FOt7rhCatHCMx8UAAJcTk4F6z3wgPT11+YSr3/9q/n89FBCAAAAuEZyqhpKTU3VLbfcotTUVF177bUl9vfs2VMrVqxwmndq+fLl6tWrlzfD9HvJydLQoc4rN7marLxx47LPU6xgZStWQf1jpb5XSZI+SpVGj5bq6bDaaIfa6Wv10BfqqQ1qqR/UVjvUVjukZ+ZIz0i65BLp2mtVNGCQ1gVfoX1Hwtw6eToABKrzteF2335r9rJKTLQp+JVXpDVrzO6tjz9u9qYCAABAqRjW5+Py8/P1448/SpISEhL03HPPqV+/fqpbt66aNm2qiRMnKjs7W/PmzZNkJqbGjh2r6dOnK9nRfUeKiIhQVFSUJGn9+vXq06eP/v3vf2vo0KFaunSpJk2apHXr1pV75SC6sZdfUZEUH29Obu7qbrPZVGKIXlnDSOrrkCNR9ff2n+vCHRvMSdtPy1dNrdTVStUobW3yJz31QoTO+qcAVAn3vmtcl+rrfG34uRyLVgQvlYYNM4f3bd0qXXaZp0OFBbj3AQBwD5JTPm7VqlXq5yJLcdNNN2nu3Lm6+eabtXv3bq1atUqS1LdvX61evbrU+nYLFy7UpEmT9PPPP+viiy/Wv//9b6dk1vnwx1jFlHuOqtMqlNA6flRfPLFS3zz9oQZqmWJ0ZgxKriK1UMMV8texCr0qUY2bBNGbClXCve8a16V6K60Nd8WpXX87WVq8WOrZU1q3TgoK8myg8DrufQAA3IPkFCqFP8YqLi2t5BxVcXHnzFF1Tv2yEloLFkgNGpgJrHvvlQ4dkiRDHbRdw7VQN+ptxesXx3E/6mI9pfv1WZOx+u8LYfSmQqVw77vGdan+XLXhpXH8gLB2r4LbtZHy86WZM6Vx4zwfKLyKex8AAPcgOYVK4Y+xyikqOv8cVWcrLaF1ww1SamrZX5JsKtblWqcxekt/1ru6ULmSpL1qomd0n/rNv11DRzFJLyqGe981rktgsLfhn34qPfHE+eunp0t9v3zBbMijoqQdO8o/iRX8Avc+AADuQf9ywIuCg82lxkeNMh/PN7wuOVnavdv8gjN/vvn43HPSM8+c/9d7Q0Faqz66Q6+pibKVoueVrRjFKlvTlKLeN8ar+N9TpdxcN306wDesWbNGQ4YMUUxMjGw2m5YsWVJm/XXr1ql3796qV6+eIiIi1Lp1az3//PPeCRZ+xd6Gt21bvvo5OZLuukvq0sVsa89aiAQAAABnkJwCfNzZCa3ERPO7TUX7Ox5XTU1Xii7Sz7pDr+pnNVf94kMKmvSg1KyZNGmSdOSIR+IHvO3YsWPq0KGDXnrppXLVr1mzpu6++26tWbNGO3bs0KRJkzRp0iTNmjXLw5HCX1VoBb+1wSqaOcucb2rBAumjjzwbHAAAgB9iWB8qhW7s1ihrFb+KCFahRilVLzWZqqjsHZKkE7Xr6+fxL6jVIzcoOMRW9TdBteRv977NZtPixYs1bNiwCh2XnJysmjVr6q233ipXfX+7Lqiayqzg91nC/1OL958zfxD45hupZk2PxwnP494HAMA96DkF+JGcnPPXKY8ihehtjdH0277WHXUX6mtdqvCjh9X2idH6rPZQLXst2z1vBPihbdu2af369briiitKrVNQUKC8vDynDYEjOFiaPt18bitHLj87W+r0/hQdr99U+uUX6bHHPBsgAACAnyE5BfgRd82ja7NJ9epJjz4WpNd+vV6dtFWTNUUnVUP9T7yvXndcqq1/n13x8YOAH4uNjVVYWJi6dOmiu+66S7fddlupdadOnaqoqCjHFhcX58VI4QuSk6WFC6UmTc5f1zCkY7ZauksvmwXPPit9+aVnAwQAAPAjJKcAP5KYaA4PKeuX+gYNpLfflqZMMeudW9dmO5Nzsj+eUqge12R10lZtVDddqFx1mnm7jKv7S7t2eebDAD5m7dq1ysjI0CuvvKJp06YpNTW11LoTJ05Ubm6uY8vKyvJipPAVZy9aMWlS2XUNQ5p7eLAO9bneHBd4xx3mIwAAAEhOAf6krKEk9kTUK69If/mLNHmy61/1Y2PNxJWr+c+/UTv10nr9Pz2j44qQ7bNPpcsuk5Yu9cwHAnxI8+bNddlll+n222/Xvffeq0cffbTUumFhYYqMjHTaEJgquoLf5yNfkGrXljZulMo5pxkAAEB1R3IK8DOlDSWJjTXLk5Od69p/1Z8/33zctUtq0aL08xcrWM/p/6m9vtTB1onSsWPSdddJTz3FMD8EDMMwVFBQYHUY8CPlHXZ9YduYM92snnpKKi72XFAAAAB+IsTqAABUXHKyNHSotHatOUl648bmkL/g4JJ17b/qn608X6J+0iV657ZPdc0nKWq5Yob0wAPmuuizZklhYW75HIAn5Ofn68cff3S83rVrlzIzM1W3bl01bdpUEydOVHZ2tubNmydJevnll9W0aVO1bt1akrRu3To988wz+sc//mFJ/PBP9mHXpa3gZ7OZ+xMTJXUaJz35pPTdd9J770kVXE0SAACguiE5BfgpV0mn8jrflyj7+cf/s4akl/V3tdV0jVfIvHnSTz9JaWlSw4aVDR3wqIyMDPXr18/xesKECZKkm266SXPnzlVOTo727Nnj2F9cXKyJEydq165dCgkJ0cUXX6z//Oc/uvPOO70eO/yXfdj18OHOc/tJZ4ZhT5t2+keEyEjprrvMBNXUqeavDeVZ9g8AAKCashkG43RQcXl5eYqKilJubi5zrfiptDTzS5RUvtF6SVquBRqhC5UrNWsmLVtW/klWUG1w77vGdYFdWpo0fry0d++Zsrg4MzF19rBrHTggxcdLJ06YY64r+2sDLMW9DwCAezDnFBCgSpu7ytXQQElariT11BfaFXKJ9Msv0pVXSjt3ej5QAPAjpc3155SYkqToaOmWW8zn//mPt8MEAADwKfScQqXwS2H1UVR0Zu6qAweke+8tu35dHdF3MVepwb7tKqgfo5DP1yi45cXeCRaW4953jeuCSrGvUFFUJG3dKiUkWB0RKoh7HwAA96DnFBDg7HNXjRpl/pB/Pr+qntruW6GvdanCDu9TTtsr9dErv3g8TgCodpo3l0aMMJ8//bS1sQAAAFiI5BQAh/IuhX5YDXS1VmqnWiq2aI9a/a2fPnpt7/kPBIAAV1QkrVolpaaaj0X/vN/c8X//Zy44AQAAEIBITgFwsK/iV55Fow6oka7UZ/pRF+si7VKrv1+pooNHPB8kAPiptDRzDvR+/aTRo83H+KEdtD9hoFRcLD3zjNUhAgAAWILkFAAH+1LoUvkSVPvURFfqM+1WM11U+IN+/9NY8wsWAMCJfYXUved0Ms3OlkZue8B88cYb0v793g8OAADAYiSnADgpbRW/0mSpqYZqqf5QuOptXMa8KQBwjqIiafx4ydUSNIYhrVWiMkJ7SgUFZ34hAAAACCAkpwCUcO5S6M8/X3b9L9VBd+sl88VDD0lr1ng8RgDwF2vXluwxdTZDNj1+8vTcUzNmSLm53gkMAADAR5CcAuDS2av4/eMfZc9FZbNJK2JvUfGNY8xhfTfcIB086NV4AcBX5eScv877GqLcJm2kvDzplVc8HxQAAIAPITkF4LzONxeVYUjXD7dp3eiZMtq2Nb+J/eUv5lgWAAhw5VkJ1VCQcm78l/li5kzm7wMAAAGF5BRQRfn5+QoODtYzPrjKUm5uroKCgvT8WePy9u3bJ5vNptdee61C5yptLqrgYPNx2jTpikE1ddWRd1UYdoG0cqX0xBNV/ASmo0eP6l//+peSkpLUoEED2Ww2PfrooxU6R35+vlJSUhQTE6Pw8HB17NhR77zzTqXrVbQuEEgCpV0sr/OthGqzSXFxUotJI6XISOmXX6TVq8s8J+0iAACoTkhOAVW0ZcsWFRcXq3v37laHUkJGRoYMw1DXrl0dZTVr1tSGDRs0atSoCp/v7LmoUlLMsnM7R6062FZ/LXjVfDFlipmkqqIjR45o1qxZKigo0LBhwyp1juTkZL355pt65JFH9NFHH6lr164aNWqU5s+fX6l6Fa0LBJJAahfLo6zep/bX06ZJwbUizGHRkjR3bpnnpF0EAADVigFUQm5uriHJyM3NtToUyz3zzDNGcHCwcezYMatDKeE///mPERwcbOTn57v1vIWFhhEbaxjmgL6Sm81mGPNr3ma+aNjQMLKzq/R+xcXFRnFxsWEYhnHo0CFDkvHII4+U+/gPP/zQkGTMnz/fqbx///5GTEyMUVhYWKF6Fa1bnXDvu8Z1cRaI7WJ5LFpUsu2MizPLHdavN3dccIFh5OWVei7aRd/AvQ8AgHvQcwqoos2bN6tdu3Zav369EhMTVbNmTV1yySV6+eWXnept2rRJI0eOVHx8vCIiItSwYUNdd911+umnn5zqfffddxozZozi4+MVFham6OhoJSUlaefOnU711q1bp6SkJEVFRalOnTq69tpr9cMPP5SIrU2bNqpZs6ajLCkpSX369HG8vvLKK9WvXz+tXr1aV199tWrVqqVGjRrpsccec/l5161bpx49krR3b5SkOpKuleT8voYh3XLsBeVf1N6cGH3UKKmwsJxXtCSbzSZbaeNhymHx4sWqVauW/vznPzuV//Wvf9W+ffu0cePGCtWraF0g0ARiu3i+95VKroSani7t2mWWO/ToIbVsKR0/bo6lLgXtIgAAqE5ITgFVlJGRocOHD+vBBx/U3XffrbS0NLVp00Z33323lixZ4qiXmZmpDh06aPr06frkk0/0/PPP6/vvv1fyWd9KfvjhB3Xt2lW5ubl67rnntGLFCk2fPl2NGzd2+iL16KOP6oorrlBcXJxSU1M1e/ZsZWVl6aqrrlJ+fr5TbGcPXZGkbdu2qXPnzk5x7d69W/fee69uuukmvffee+rTp48eeeQRrT5nzhP7+9aqFScpVdJsSVmSrpKU71T3hCK06q53ZdSqpcI1a1Q4aZIKCwvL3Dzl66+/Vps2bRQSEuJU3r59e8f+itSraF0g0ARiu3i+97ULDpauuMLQn/9cqMsvL5RhnNMWFhWpcMwYFUoqfOONyv4nOC/aRQAA4FOs7roF/0Q3dtOvv/5qSDIuvfRS4/jx447yY8eOGXXr1jVGjhzp8riioiLj1KlTxuzZsw1Jxm+//WYYhmE88sgjxgUXXGAUFRWV+p7vv/++Icl4+umnncq///57Q5Lx9ttvG4ZxZpjHjBkzHHV2795tSDLeeustwzAM46effjIkGZ07dzZOnDjhqLd3794Sx579vunpZw9LMd9XervE8L70dMNInzz59P7zb7t27TrvNa/M8JUWLVoYAwYMKFG+b98+Q5Lx5JNPVqheRetWJ9z7rnFdzgjUdrGs9z1Xenp6+dvFVatK/dx2tIvW4d4HAMA9nH/aAlAhGRkZkqTHH39cERERjvILLrhALVq00IEDByRJhmFo0aJFmjFjhr777jvt379fhmFIkoKCghzH1q9fX8ePH9df//pX3XHHHerRo4eC7cvhnTZ58mRdfPHFGj9+vFNvo+bNmysiIkI///yzJHPoiiR16dLFUWfLli2SpE6dOkmStm7dKkl67LHHFBYW5qh35MgRSVJMTIzL9zWMQjVpImVnS1JzSRGSfnbUtdnMlakSE6Xjnf+pzV98IS1fLnXsKM2aVeqSVWe/n7uVNfzl7H3lrVfRukCgCNR2saz3PVfnzp0dsZTq7ruljRsVs2KFdMUVZdetJNpFAADgK0hOAVWQkZGhmjVr6k9/+lOJffv373fMYXLHHXdo7ty5uvPOO3XPPfeoQYMGCgsL02233aY//vjD8QVo3LhxOnbsmObOnat58+apQYMGGjVqlB5//HFFRkZq//792rZtmyQ5fWk624UXXuiILTQ01DGcQjK/dNWsWVOtW7d2vA4LC9PVV1/tdA77l7OEhATHZznf+0rm+zqtPBUs1apVSx1feUVq21bKzJR++EEaMcLlGc4dCuIu9erVc3yxPNuvv/4qSapbt26F6lW0LhBIaBdLvu+5atWqpY4dO5YoLyqS1q2TcnKk9lfdrbYbNyrk7belxx6Tgtw7EwPtIgAA8CUkp4AqyMjIUMOGDUv8ir9+/Xr98ssvuvbaa7Vz507Nnj1bTz/9tO677z5HncOHD+ubb77RiLMSNSEhIbr//vt1//33a+/evZo1a5Yef/xxhYeH66mnnlJWVpYk6fnnn9fll1/uMqaLL77YEVv79u2dvjRt2bJFHTt2VNDpLzlbtmxR+/btFRoaWuJz1a9fX02bNpWkUt/3s8+kZ5815zyXzPeNjTUTU/YpY1avXq1+/fqdOflf/mJuLuzatUvx8fEu91XFZZddptTUVBUWFjolwL766itJUrt27SpUr6J1gUAS6O2iq/c9V4l2sQy7fvlF8atXS+WsX160iwAAwJcwITpQBZs3b9a+ffv0+++/O8oKCwt1//33q3Xr1rr++uv1yy+/SJLatm3rdKx9GMjZw0vOFhsbq4ceekgRERGO4SL2X51tNpu6dOnicqtTp44jtnPPvXXrVsfQFcmcBNjV+2/ZssVpcuDS3vdf/+qiffu6KD29i+bPr+Ny5Sn78JXNa9dqc3S0NkvafPvtZtk5m6eG9V133XXKz8/XokWLnMrffPNNxcTEqHv37hWqV9G6QCAJ9HbR1fuey9Eunt6eemqzpJLbRF2nGEm/PDbX5XmqgnYRAAD4EnpOAZV06NAhZWVl6eKLL9bw4cP1z3/+UydOnND06dP11Vdfad26dQoJCVGHDh10wQUX6OGHH5bNZtMff/yh1157TT/++KOkM3Of3H333crNzVX//v3VtGlTHTp0SC+99JJCQ0N15513SjJ/he/Xr58mTZqk/Px8de/eXYZhKCcnR+np6brpppvUt29f5eTkKCcnx2lFqr179+rgwYOOL1dZWVk6dOhQiS9hhYWF2r59uyZMmOAoK8/7jhrV1+V1ql279pn3ePFFc0jfW29JDz0kNWtW7uv90Ucf6dixYzp69Kgk6dtvv9XC08usDxo0SBdccIFWr16tq666SpMnT9bkyZMdxw4cOFD9+/fX3/72N+Xl5emSSy5RamqqPv74Y7399tuOHh7lrVfRukCgoF0s+b6unN0uFhVJ113n+nqm6z49qcVqsHqhin5/ScEX1nbaT7sIAACqDevmYoc/Y3Uaw/jwww8NScYXX3xh3H777UZkZKQRGRlpDB8+3Pj++++d6n7wwQdG69atjbCwMKNt27bG9OnTjSeeeMIICgoyjh49ahiGYbz44otGYmKi0bBhQyMsLMxo3ry5ccsttxg//fST07lyc3ONiRMnGi1btjTCw8ONOnXqGB06dDD+8Y9/OFa3Wrp0qSHJ2L59u+O4JUuWGJKML7/80un12XUMwzC2b99uSDLS0tIq/L6uFBaaq/bNn28Y6Z8VG8V9rjCX8hsxogJX2zCaNWt23lX+7CtguVqx6ujRo8Y999xjNGrUyAgNDTXat29vpKamVrpeRetWF9z7rnFdTLSL5WsXz+a8+um5W7HxnVoahmTs+NecEsfSLlqPex8AAPewGcbppXGACsjLy1NUVJRyc3MVGRlpdTjwUWlp0vjx0t69Z8r6N9yuTw53kq24WFq1ymOrUMEzuPdd47qgslJTpdGjS9//gKZqqh7UwdZ91HDHau8FhnLh3gcAwD2YcwqAR6SlScOHOyemJGnloQ56tfgO88X48eaYFgAIUI0bl73/LY1RsWxq+N0aafdur8QEAADgbSSnALhdUZGZd3LVL9MwpIf1uHJtF0rbt0uzZ3s9PgDwFYmJ5iqnNpvr/ftssdoUlmi+WLLEa3EBAAB4E8kpAG63dm3JHlNnO6z6etiYYr546CHpt9+8ExgA+JjgYGn6dPP5uQkq++uI0aeXQF282HuBAQAAeBHJKQBul5Nz/joz9TflNmkjHTkiPf+854MCAB+VnCwtXCg1aeJcHhtrlnd4ZJhZsHatdPCg1+MDAADwNJJTANzufHOoSFKhamjvbad7T734onR6KXQACETJyeaUUunp0vz55uOuXdLQodKqXc30a3wnyTBUvOQ9q0MFAABwO5JTANzufHOo2GxSXJzU+sFkqWVL6fffpVdf9WqMAOBrgoOlvn2lUaPMx6VLpfh4qV8/6bnd10mS0scvVlqalVECAAC4H8kpAG5XnjlUpk2TgkODpfvvNwuee04qKPBajADgy85d8XSxzOTU5SdW6ubr8/TYY1JqqrRqFYueAgAA/0dyCoBHnG8OleTT8/vqxhvNwpwc6c03vR4nAPgaVyuefqu2+l4tFKaTGqiP9Mgj0ujRZq+q+HjRmwoAAPg1klM+bs2aNRoyZIhiYmJks9m05DzLSOfk5Gj06NFq1aqVgoKClJKSUqLO3LlzZbPZSmwnTpzwzIdAwCptDhVHYkqSQkOl//f/zOdPPy0VFloRKgD4DNcrntocvaeuk/OqfdnZZi8rElQAAMBfkZzycceOHVOHDh300ksvlat+QUGBGjRooIceekgdOnQotV5kZKRycnKctvDwcHeFDTicO4dKcLCLSrffLtWrJ/30k9mtCgACWGkrntqTU4O0TKE6Mwza3sMqJYUhfgAAwD+FWB0AyjZw4EANHDiw3PXj4+M1/fRkP3PmzCm1ns1mU6NGjaocH1BZRUVm74CcHKlx45rqc/c9CpryiDR1qjRyZOmzqQNANVfaiqeb1E371FgxytFV+lQfaZBjn2FIWVlmu9q3r3fiBAAAcBd6TgWo/Px8NWvWTLGxsRo8eLC2bdtWZv2CggLl5eU5bUBlpaWdWYHKPmdKh9fu1qnwWtKXX0rLllkdIgBYprQVTw0FaYmGSSo5tM+utF5XAAAAvozkVABq3bq15s6dq/fee0+pqakKDw9X79699cMPP5R6zNSpUxUVFeXY4uLivBgxqpNzV6Cy+yanrl44caf5YupU7wcGAD6irBVP02RO2jdUSxWkkmP4Sut1BQAA4MtITgWgHj166MYbb1SHDh2UmJio//u//1PLli314osvlnrMxIkTlZub69iysrK8GDGqC1crUNkZhvScJqhAodLnn5tjUwAgQJW24ulqXaFfVUcNdUi9tN5RbrNJcXFmrysAAAB/Q3IKCgoKUteuXcvsORUWFqbIyEinDago1ytQnbFPMZqrm80XTz/tlZgAwFedu+LplClSka2GPtBgSWeG9tl7V02bVsqiEwAAAD6O5BRkGIYyMzPVmLEA8LDyzIXyrP6f+eTDD6VffvFsQADg485e8XTyZLM31dp65qp9Q/S+JHN+qoULzWQWAACAPyI55ePy8/OVmZmpzMxMSdKuXbuUmZmpPXv2SDKH240dO9bpGHv9/Px8HTp0SJmZmfr2228d+6dMmaJPPvlEP//8szIzM3XrrbcqMzNT48aN89rnQmAqT/7zB7XUbwlXmuP8Zs/2fFAA4EeSk6VXvr9SRlCwWuhHrU/9Rbt2kZgCAAD+jeSUj8vIyFBCQoISEhIkSRMmTFBCQoImT54sScrJyXEkquzs9bds2aL58+crISFBgwadWW76999/1x133KE2bdooKSlJ2dnZWrNmjbp16+a9D4aAVNoKVHb2OVOi/nV6YvTXX5dOnfJegADgB4LrRsnW3fx/ds/jnzKUDwAA+D2bYbiamhgoW15enqKiopSbm8v8U6gQ+2p9kvPE6PaE1cKFUvLgk2aW6uBBadEiugT4EO5917gu8LrJk6XHH5duuEFKTbU6moDFvQ8AgHvQcwqAV5W2ApXTnCmhodItt5g7Xn3V6zECgM+7+mrz8dNPpeJia2MBAACoIpJTALzu3BWo0tNVcs6U2283H5cvl37+2YowAcB39egh1awpHTokffWV1dEAAABUCckpAJY4ewWqvn1dLH9+0UXSgAGSpD2TZik1VVq1Sioq8nKgAOCLQkOlK64wn69caW0sAAAAVURyCoBPKSoyk1CpqdKCOubE6GGpb+im0SfVr58UH2/OWwUAAc8+tI/kFAAA8HMkpwD4jLQ0M/nUr580erR04zuDtU+NFa2DGqYlkqTsbHNCdRJUAAKePTm1Zo1UUGBtLAAAAFVAcgqAT7Cv4rd375myQtXQbN0mSRqnVySdWeEvJYUhfgACXLt2UsOG0vHj0oYNjuKze6AyHBoAAPgDklMALFdUJI0ffybxdLbZuk1FCtKVSlcLfS/JrJeVJa1d6+VAAcCX2Gwlhvad2wOV4dAAAMAfkJwCYLm1a517TJ0tS031kQZKkm7Sm077cnI8HRkA+Lj+/c3HlStd9kCVGA4NAAB8H8kpAJY7X5Lpbd0oSRqpBZLOdK9q3NiDQQGAP7jqKkmSsXmzHv7H7y57oDIcGgAA+DqSU4AbHD9+XFOmTFHr1q0VHh6uevXqadSoUfrtt988+r75+flKSUlRTEyMwsPD1bFjR73zzjvnPe6zzz7TLbfcotatW6tmzZpq0qSJhg4dqi1btlT6PSpyznOdL8n0gQbruCJ0iX5SJ22VzSbFxUmJiec9NQCL+Fu7KEmZmZm69tpr1bRpU0VERKhu3brq2bOn3n77bad6q1atks1mc7l98cUXLs+9bt06DRo0SHXq1FFERIRatGihxx9/vMqfV3FxUqtWshUXq8W+VaVWYzg0AADwZSFWBwD4O8MwNGrUKK1Zs0aTJ09Wx44d9eWXX+ree+/VxRdfrCeeeMJj752cnKzNmzfrP//5j1q2bKn58+dr1KhRKi4u1ujRo0s9bubMmTpy5IjGjx+vtm3b6tChQ3r22WfVo0cPffLJJ7ryyisr/B4VOee5EhOl2Fhz6ImrX/2PqZY+0GCN0Lu6QQu0TZ01bZoUHFypywbAw/yxXZSk33//XXFxcRo1apSaNGmiY8eO6X//+5/GjBmj3bt3a9KkSU71n3zySfXr18+prF27diXOO3/+fI0ZM0YjRozQvHnzVKtWLf3000/at29f1T+wZM47tXOn+muFlmpYmVUZDg0AAHySAVRCbm6uIcnIzc21OhTLpaenG5KMd99916k8OjraSElJ8dj7fvjhh4YkY/78+U7l/fv3N2JiYozCwsJSjz1w4ECJsqNHjxrR0dHGVVddVan3KO85S7NokWHYbOZmpqict2QtNAzJyApuaixaWHze88EzuPdd47o488d2sSzdu3c34uLiHK9L+3yu7N2716hZs6bxt7/9rVLvXS6LFxuGZHynli7bz7O39HTPhRGIuPcBAHAPhvUBVfTuu++qTp06uu666xxla9as0YEDB8rsLVRVixcvVq1atfTnP//Zqfyvf/2r9u3bp40bN5Z6bMOGDUuU1apVS23btlVWVlal3qO85yxNcrK0cKHUpIlzeWysNGWKNHLuIBVG1FJs0R4lx7geNgPAN/hju1iW+vXrKySkcp3NZ8+erWPHjun++++v1PHl0revjKAgtdL3aqo9LqswHBoAAPgyklNAFa1fv17du3eXJO3bt09vvPGGrr/+el111VUaPHhwifqGYaiwsLBcW1m+/vprtWnTpsQXpvbt2zv2V0Rubq62bt2qSy+91G3v4eqcZUlOlnbvltLTpfnzzcfdu6XJk6URN0UoJHmoWXHBgnJ/LgDe5+/tYnFxsQoLC3Xo0CHNmDFDn3zyicvk0l133aWQkBBFRkZqwIABWrduXYk6a9asUd26dfXdd9+pY8eOCgkJUcOGDTVu3Djl5eWVK57zuvBC2bp1kyRdpU9lsznvtr9mODQAAPBVJKeAKjhx4oS+/vprde/eXU8++aSaNGmiW265RRdccIHmzp0r27nfECStXr1aNWrUKNe2e/fuUt/7yJEjqlu3bolye9mRI0cq9FnuuusuHTt2TA899JDb3sPVOc8nOFjq21caNcp8dPoiNXKk+fjuu1JxcbnPicCyZs0aDRkyRDExMbLZbFqyZEmZ9dPS0tS/f381aNBAkZGR6tmzpz755BPvBFsNVYd28e9//7tq1Kihhg0b6t5779ULL7ygO++807E/KipK48eP16uvvqr09HRNnz5dWVlZ6tu3b4l/O9nZ2Tp+/Lj+/Oc/a+TIkVq5cqXuu+8+zZs3T4MGDZLhaqK9yrj6aknSo4krXfZAXbjQ/AEAAADAFzEhOlAFW7duVWFhobp166bWrVure/fu+uKLLzRt2jT16dNHX375pWrVquV0TOfOnbV58+ZynT8mJqbM/a6+5JVn37kefvhh/e9//9OLL76ozp07u+U9yjpnpSUlSVFR0r590rp1Up8+7jkvqpVjx46pQ4cO+utf/6rrr7/+vPXXrFmj/v3768knn9SFF16oN954Q0OGDNHGjRuVkJDghYirl+rQLj744IO67bbbdPDgQb3//vu6++67dezYMf3zn/+UJCUkJDj920hMTNR1112nyy67TP/61780YMAAx77i4mKdOHFCjzzyiB544AFJUt++fRUaGqqUlBR9+umnuvp0YqlKrr5aeuIJNd25UruzDa1dZ1NOjrkaamIiPaYAAIBvIzkFVMGmTZskSd26dVP9+vV10UUXKSkpSS1bttSoUaP0xRdflPjSUatWLXXs2LFc5y9rjpN69eq57AXw66+/SpLL3gOuTJkyRU888YT+/e9/6+6773bLe5R1zioJC5Ouu06aO9cc2tenj4qKzKXR+RIGu4EDB2rgwIHlrj9t2jSn108++aSWLl2q999/n+RUJVSHdrFp06Zq2rSpJGnQoEGSpIkTJ+qmm25SgwYNXB5z4YUXavDgwXrllVf0xx9/KCIiwhHTDz/84JSwksx/pykpKdq6dat7klM9ekgXXCAdPKjgb79S377tq35OAAAAL2FYH1AFmzZt0kUXXaT69eu73O/qF353DV+57LLLtGPHjhJzsHz11VeSXC9nfq4pU6bo0Ucf1aOPPqoHH3zQLe9xvnNW2Q03mI/vvqvF7xYqPl7q108aPdp8jI+X0tLc/7YIHMXFxTp69GiZiYyCggLl5eU5bTD5e7voSrdu3VRYWKiff/65zHr2IXpn99Cyz3dVWt2gIDf9KRYWdqY36cqV7jknAACAl9BzCqiCTZs2qXHjxk5lhmFo9uzZateundq2bVviGHcNX7nuuuv02muvadGiRRppn4tJ0ptvvqmYmBjHZMSlefzxx/Xoo49q0qRJeuSRR9zyHuU5Z5VdeaVUr5506JBmjFilvXLucZCdLQ0fzvwqqLxnn31Wx44d04gRI0qtM3XqVE2ZMsWLUfkPf24XS5Oenq6goCBddNFFpdb57bff9MEHH6hjx44KDw93lF9//fWaNWuWPvroI6eeeMuWLZMk9ejRo1IxuXT11dLHH5vJqQkT3HdeAAAADyM5BVTSr7/+qp9++kk//fSTbrvtNo0aNUrHjx/XnDlztG7dOqWnp7s8rnbt2urSpUuV33/gwIHq37+//va3vykvL0+XXHKJUlNT9fHHH+vtt99W8OmxbatXr9ZVV12lyZMna/LkyZLML9+TJ0/WNddco2uvvVZffPGF07ntX5bK+x4VOWeV1aih4uTrFfTaLI3QAq08JzllGObKVCkp0tChDPFDxaSmpurRRx/V0qVL1bBhw1LrTZw4URPO+vKfl5enuLg4b4To0/y5XZSkO+64Q5GRkerWrZuio6N1+PBhvfvuu1qwYIHuu+8+x5C+0aNHq2nTpurSpYvq16+vH374Qc8++6wOHDiguXPnOsWUlJSkIUOG6LHHHlNxcbF69OihjIwMTZkyRYMHD9bll19e5c/t0L+/Tn9A6eRJKTTUfecGAADwJAOohNzcXEOSkZuba3Uolvnoo48MScbYsWONJk2aGDVq1DCaNm1qDB8+3MjMzPRKDEePHjXuueceo1GjRkZoaKjRvn17IzU11alOenq6Icl45JFHHGVXXHGFIanUraLvUdFzVtW2Zz81DMk4rLpGiE4aZkqq5Jae7ta3heF/974kY/HixeWq+8477xgRERHGBx98UOH38bfr4in+3C4ahmHMmTPHSExMNOrXr2+EhIQYF154oXHFFVcYb731llO9qVOnGh07djSioqKM4OBgo0GDBsZ1111nbNq0yWVMx48fN+6//34jLi7OCAkJMZo2bWpMnDjROHHihFs/u1FUZBgNG5oN4OrV7j03XOLeBwDAPWyG4a41jBFI8vLyFBUVpdzcXEVGRlodjiUee+wxPfHEE8rLy3MawgHPe+d/Rep7YxM10gEN1DJ9LNeTX8+fL40a5eXgqjl/u/dtNpsWL16sYcOGlVkvNTVVt9xyi1JTU89b1xV/uy6eQrvoA0aPllJTpUmTpMcftzqaao97HwAA92BCdKCSNm3apMsuu4wvYBZo1CRY7+rPkqQb9E6p9c6Z9gYBIj8/X5mZmcrMzJQk7dq1S5mZmdqzZ48kc0je2LFjHfVTU1M1duxYPfvss+rRo4f279+v/fv3Kzc314rw/Rrtog+wr/zHpOgAAMCPkJwCKmnz5s3q1q2b1WEEpMREKb2BOdnxMC1RmE447bfZpLg4sx4CT0ZGhhISEhyTT0+YMEEJCQmOuYVycnIciSpJevXVV1VYWKi77rpLjRs3dmzjx4+3JH5/RrvoA+zJqU2bJBKsAADATzCsD5VCN3ZYLW1hsbr9ualila2hWqL3NFSSmZiSWK3PU7j3XeO6wKe0bCn98IO0ZIm5MgQ8hnsfAAD3oOcUAL+UPDxIfwwxe0+N1AJHeWwsiSkAAc6+at+nn1obBwAAQDmRnALgt1pMOp2cCn9PC944rvR0adcuElMAAlyfPubjunXWxgEAAFBOJKcA+K+uXaXmzRV84phG1PxQfftKwcFWBwUAFuvd23zcvl06etTaWAAAAMqB5BQA/2WzSSNGmM8XLCi7LgAEithYKT5eKi6WvvjC6mgAAADOi+QUAP820hzapw8/pIcAANjZe08xtA8AAPgBklMA/FvHjlKLFtKJE9Ly5VZHAwC+4fLLzcfPP3cUFRVJq1ZJqanmY1GRJZEBAACUQHIKgH+z2aQhQ8znH3xgbSwA4CvsyakvvpBOnVJamjnSr18/afRo8zE+XkpLszJIAAAAE8kpAP7v2mvNx2XLzDlWACDQtW0rXXihdOyYPnt+u4YPl/buda6SnS0NH06CCgAAWI/kFAD/d/nlUmSkdPCglJFhdTQAYL2gIKlXL0nS6ic/l2GUrGIvS0lhiB8AALAWySkA/i80VEpKMp9/+KGjmPlVAAS000P72uWWPim6YUhZWdLatd4KCgAAoCSSUwCqB/vQvtPzTjG/CoCAd3rFvt76XJKLrlNnycnxQjwAAAClIDkFoHoYONCcHH3rVi17PYf5VQCga1cVh9RQjHLUXLvKrNq4sZdiAgAAcIHkFIDqITpa6tpVkvTZfcuYXwUAIiJk69JFkpQo10P7bDYpLk5KTPRmYAAAAM5ITgGoPgYPliT1/u2DUqswvwqAQGK7/MzQPpvtnH2nX0+bJgUHezcuAACAs5GcAlB9nJ53qr9WKFQFZVZlfhUAAeH0pOg3xK5TkybOu2JjpYULpeRkC+ICAAA4S4jVAQCA2yQkqKBeY9U6kqMrtForlFRqVeZXARAQevWSJEXu/Va7D/6qtd/UVU6O2QYmJtJjCgAA+AZ6TgGoPmw21Rhm9p4arA9Lq8L8KgACR4MGUqtWkqTgjevVt680apTUty+JKQAA4DtITgGoVoIGm8mpa/WBbOcsnc78KgAC0umhfVrnelJ0AAAAq5Gc8nFr1qzRkCFDFBMTI5vNpiVLlpRZPycnR6NHj1arVq0UFBSklJQUl/UWLVqktm3bKiwsTG3bttXixYvdHzxghauvlkJDdbF+Vp/onU67mF8FQEDqbU6Krs8/tzYOAACAUpCc8nHHjh1Thw4d9NJLL5WrfkFBgRo0aKCHHnpIHTp0cFlnw4YNGjlypMaMGaPt27drzJgxGjFihDZu3OjO0AFr1KpljleR9NmED5SeLs2fL6WnS7t2kZgCEIDsPac2b5YKyl4sAgAAwAo2wzCM81dDeZw6dUr79+/X8ePH1aBBA9WtW9et57fZbFq8eLGGDRtWrvp9+/ZVx44dNW3aNKfykSNHKi8vTx999JGj7JprrlGdOnWUmpparnPn5eUpKipKubm5ioyMLO9HALzjxRele+4xk1Tp6VZHU6144t73dNvpDbSJ8GmGITVqJB08aPaeOj1JOqqOex8AAPeg51QV5efn69VXX1Xfvn0VFRWl+Ph4tW3bVg0aNFCzZs10++23a/PmzVaH6WTDhg1KSnJexWzAgAFav359qccUFBQoLy/PaQN81rXmvFNat076/XdLQ4Fr/th2An7LZjsztI95pwAAgA8iOVUFzz//vOLj4/Xaa6/pyiuvVFpamjIzM7Vz505t2LBBjzzyiAoLC9W/f39dc801+uGHH6wOWZK0f/9+RUdHO5VFR0dr//79pR4zdepURUVFOba4uDhPhwlU3kUXSa1bS4WF0vLlVkeDc/hr2wn4NfvQPuadAgAAPijE6gD82fr165Wenq7LLrvM5f5u3brplltu0SuvvKLXX39dq1evVosWLbwcpWs2+7JlpxmGUaLsbBMnTtSECRMcr/Py8khQwbcNHix995304YfSiBFWR4Oz+HPbCfits5NTxcVSEL9PAgAA30FyqgrefffdctULCwvT3//+dw9HU36NGjUq0Uvq4MGDJXpTnS0sLExhYWGeDg1wn2uvlZ55Rlq2TCoqkoKDrY4Ip/lr2wn4tYQEKSJCOnJE2rlTatPG6ogAAAAc+NnMTT744AMVFxdbHUa59OzZUytWrHAqW758uXoxQSqqk969pago6fBhc4Uq+CR/ajsBv1ajhtS9u/mcoX0AAMDHkJxyk6FDh+rw4cNuP29+fr4yMzOVmZkpSdq1a5cyMzO1Z88eSeZwu7FjxzodY6+fn5+vQ4cOKTMzU99++61j//jx47V8+XI99dRT+u677/TUU09p5cqVSklJcXv8gGVq1JAGDDCff/CBtbGgVJ5qOwG4YB/ax6ToAADAx5CcchPDMDxy3oyMDCUkJCghIUGSNGHCBCUkJGjy5MmSpJycHEeiys5ef8uWLZo/f74SEhI0aNAgx/5evXrpnXfe0RtvvKH27dtr7ty5WrBggbrbf1EFqgv7v/uzJkUvKpJWrZJSU83HoiJLIsNpnmo7AbjAin0AAMBH2Qy+GbhFUFCQPv74Y/Xu3Vs1a9Z0lGdnZ6tNmzbKy8uzMDr3y8vLU1RUlHJzcxUZGWl1OIBr+/ZJTZqYy6gfPKi0NfU1fry0d++ZKrGx0vTpUnKydWH6E3ff+9Wl7aRNhF/IzZXq1JEMQzpwQGrY0OqI/B73PgAA7sGE6G40cOBA2Ww2xcfHq3379mrVqpV++eUXXXjhhVaHBgSmmBipXTvp66+1ceqnGv78SJ2bjs/OloYPlxYuJEFlFdpOwEuioqS2baVvvpE2bJCGDrU6IgAAAEkkp9zq+++/18GDB/XVV1/pyy+/1FdffaXi4mLNmjXL6tCAwDVggPT119r1ynIZxsgSuw3D7FiVkmJ+T2NRP++j7QS8qGdPklMAAMDnkJxyo9q1a+viiy9Wz549rQ4FgF1SkvTss7r8+CeSDEm2ElUMQ8rKktaulfr29XaAoO0EvKhXL2n2bDM5BQAA4COYEN1NhgwZoho1algdBoBzJSaqsEa4YpWtNtpRZtWcHC/FBAfaTsDL7EngzZulU6dYJAIAAPgEklNusnTpUtWpU8fqMACcKyJCeR36SJIG6JMyqzZu7I2AcDbaTsDLWrY0J0X/4w999vx2xcdL/fpJo0ebj/HxUlqa1UECAIBAQ3KqCvbs2VOh+tnZ2R6KBEBZLhyRJElK0nKX+202KS5OSkz0ZlSBi7YTsFBQkNSjhyRpyf0bnFYvlc4sEkGCCgAAeBPJqSro2rWrbr/9dm3atKnUOrm5uXrttdfUrl07pfGXHmCJoIEDJElXaLXCdcJpn+30FFTTpjEZurfQdgLWKu7RS5LUQyXnnbKvaJqSwhA/AADgPUyIXgU7duzQk08+qWuuuUY1atRQly5dFBMTo/DwcP3222/69ttv9c0336hLly7673//q4EDB1odMhCYLr1UatxYF+TkaFj9dXrn8NWOXbGxZmIqOdm68AINbSdgrS9r9lRHSb203uV+FokAAADeZjMM+29kqKwTJ05o2bJlWrt2rXbv3q0//vhD9evXV0JCggYMGKB27dpZHaLb5eXlKSoqSrm5uYqMjLQ6HOD8br5ZevNNFf+/+7Rm8NPKyTHnmEpMpMdURbjz3q9ObSdtIvzJu3OOKvnWCxWsYjXWPu2X6wn35s+XRo3ycnB+hnsfAAD3IDmFSuGPMfid1FRzxt/27aXt262Oxm9x77vGdYE/WbVKqtOvgzroSyVrkRbLddfR9HR6Tp0P9z4AAO7BnFMAAsPVp4fyffmllJNjbSwAYKHEROnLmua8Uz1dzDvFIhEAAMDbSE55wB9//OFydalvvvnGgmgASJIaNJA6dTKfr1xpbSxwibYT8I7gYKnNLT0llZx3ikUiAACAFUhOudnChQvVsmVLDRo0SO3bt9fGjRsd+8aMGWNhZAA0wFy1T598Ym0cKIG2E/CuLv8wk1OdtUU1dNJRHhsrLVzIIhEAAMC7SE652RNPPKGtW7dq+/btmjNnjm655RbNnz9fksT0XoDFkpLMxxUrpOJia2OBE9pOwMsuuUSqX1/hKtCGl7dp/nxzjqldu0hMAQAA7wuxOoDq5tSpU2rQoIEkqUuXLlqzZo2Sk5P1448/ymbvKw/AGr16STVrSgcPmpOiJyRYHRFOo+0EvMxmk3r2lN5/X51PblDnUd2tjggAAAQwek65WcOGDfXll186XterV08rVqzQjh07nMoBWCA0VOrXz3y+fLmjuKjIXL0qNdV8LCqyJLqARtsJWKCnObRP69eXXQ8AAMDDSE65yVdffaXCwkK99dZbio6OdtoXGhqq1NRUrV692qLoADjYh/adTk6lpUnx8WbOavRo8zE+3iyH59F2AhayJ6c2lFyxDwAAwJtsBpN5uEVQUJBCQ0PVtm1bdejQQR07dnQ8XnjhhVaH53Z5eXmKiopSbm6uIiMjrQ4HKL/vv5datZJCQ7X0jV913Y01dW4raB9FxqTAJbn73q8ubSdtIvzSsWNSVJTZXXTPHikuzuqI/A73PgAA7kHPKTdZt26d6tatq+bNm6ugoEBz587VlVdeqXr16qlVq1Z6+OGH9fvvv1sdJoAWLaSmTaWTJ7XwnjUlElOSHGUpKQzx8zTaTsBCNWtKHTqYz+k9BQAALERyyk3uvvtuzZgxQ4sWLdL8+fO1bds2paen66KLLtJNN92ktWvXKiEhQYcOHbI6VCCw2WyOoX2djiwvtZphSFlZ0tq13gosMNF2AhZjaB8AAPABJKfc5LvvvlPbtm2dyq644go9//zz2rp1q9LT09WlSxc9+OCDFkUIwOF0cqq/Vpy3ak6Op4MJbLSdgMVITgEAAB9AcspNunbtqrfffrtE+aWXXqrly5fLZrPpvvvu08qVKy2IDoCTK6+UYbOpnb5RjLLLrNq4sZdiClC0nYDF7MmprVulEyesjQUAAAQsklNuMmPGDE2bNk2jR4/Wd999J0k6efKknn/+edWtW1eS1KBBAx04cMDKMAFIUr16UucukqSkUnpP2Wzm3MCJid4MLPDQdgIWa95cio6WTp2StmyxOhoAABCgSE65yaWXXqoNGzYoJydHbdu2VUREhGrWrKnXXntN//nPfyRJ27ZtU0xMjMWRApAk2wBzaN/VWuFYnc+x7/TradOk4GDvxhVoaDsBi9lsZ3pPrV9vbSwAACBghVgdQHVy6aWXKj09Xb/88ou2b9+u4OBgde7cWY0aNZJk/vpv/7IFwGL9+0v//reuj1yhibWLlZV9JlcfG2smppKTrQsvkNB2Aha7/HJpyRJp3TrpvvusjgYAAAQgm2G4WkgdKFteXp6ioqKUm5uryMhIq8MBKu7kSaluXenYMRVlbNPaox2Vk2POMZWYSI+p0nDvu8Z1gV/74guz91T9+tLBgyoqtmntWtEmlgP3PgAA7kHPKQCBKTRU6ttX+vBDBX+6XH3/1dHqiADAGp06SeHh0uHDWv7S97r16Vbau/fM7thYafp0epMCAADPYc4pAIEryZx3SsuXWxsHAFgpNFTq2lWS9H/3rHNKTElSdrY0fLiUlmZBbAAAICCQnAIQuOzJqXXrpOPHrY0FbrNmzRoNGTJEMTExstlsWrJkSZn1c3JyNHr0aLVq1UpBQUFKSUnxSpyALynudbkkqZc+L7HPPgFESopUVOTFoAAAQMAgOQUgcLVqZY5XKSiQ1q61Ohq4ybFjx9ShQwe99NJL5apfUFCgBg0a6KGHHlKHDh08HB3gm76O6i1J6u0iOSWZCaqsLJpKAADgGcw5BSBw2Wxm76k5c8yhfQMGWB0R3GDgwIEaOHBguevHx8dr+vTpkqQ5c+Z4KizAp/1Qv6faS2ql79VAB3VIDV3Wy8nxblwAACAw0HMKQGCzD+1bscLaOOBXCgoKlJeX57QB/qxei7r6WpdKknppfan1Gjf2VkQAACCQkJwCENiuusrsQfXVV3QJQLlNnTpVUVFRji0uLs7qkIAqSUyUMmuWPrTPZpPi4sx6AAAA7kZyCkBgq1/fXEZdklautDYW+I2JEycqNzfXsWVlZVkdElAlwcFS61vM5NTlWue0z2YzH6dNM+sBAAC4G8kpALAP7fv4Y2vjgN8ICwtTZGSk0wb4uy7jzeRUZ21RuP5wlMfGSgsXSsnJVkUGAACqO5JTAGCfPPvjj1knHUDguugiqVEjheqU1k/P0Pz5Unq6tGsXiSkAAOBZJKcAoGdP6cILpV9/lb74wupoUEX5+fnKzMxUZmamJGnXrl3KzMzUnj17JJlD8saOHet0jL1+fn6+Dh06pMzMTH377bfeDh2wls0m9TZ7TyUcW6dRo6S+fRnKBwAAPI/kFACEhEgDBpjPly2zNhZUWUZGhhISEpSQkCBJmjBhghISEjR58mRJUk5OjiNRZWevv2XLFs2fP18JCQkaNGiQ12MHLHc6OaXPS06KDgAA4CkhVgcAAD7h2mulBQukDz+U/v1vq6NBFfTt21eGYZS6f+7cuSXKyqoPBJTLLzcf16+XioulIH7HBAAAnsdfHAAgSddcYw5p2b5d2rvX6mgAwBodO0oXXCD99pu0Y4fV0QAAgABBcgoAJKlBA6l7d/M5Q/sABKoaNaRu3cznDO0DAABeQnIKAOyuvdZ8/PBDa+MAACsx7xQAAPAyklMAYGdPTq1cKZ04YW0sAGAV+7xT69ZZGwcAAAgYJKd83Jo1azRkyBDFxMTIZrNpyZIl5z1m9erV6ty5s8LDw3XRRRfplVdecdo/d+5c2Wy2EtsJvowj0HXsKMXESMePS6tXWx0NAFijZ08pOFj6+Wdp926rowEAAAGA5JSPO3bsmDp06KCXXnqpXPV37dqlQYMGKTExUdu2bdODDz6oe+65R4sWLXKqFxkZqZycHKctPDzcEx8B8B82mzRokPmcoX0AAlVU1Jk5+FassDYWAAAQEEKsDgBlGzhwoAYOHFju+q+88oqaNm2qadOmSZLatGmjjIwMPfPMM7r++usd9Ww2mxo1auTucAH/d+210uzZZnJq+nQzYQUAgSYpSVq/Xlq+XLr9dqujAQAA1Rw9p6qZDRs2KCkpyalswIABysjI0KlTpxxl+fn5atasmWJjYzV48GBt27atzPMWFBQoLy/PaQOqpauvlkJDzeEsO3daHQ0AWMP+t8TKlVJRkbWxAACAao/kVDWzf/9+RUdHO5VFR0ersLBQhw8fliS1bt1ac+fO1XvvvafU1FSFh4erd+/e+uGHH0o979SpUxUVFeXY4uLiPPo5AMvUqiVdcYX5fNkya2MBAKt07WoO7/v9dykjw+poAABANUdyqhqynTMMyTAMp/IePXroxhtvVIcOHZSYmKj/+7//U8uWLfXiiy+Wes6JEycqNzfXsWVlZXnuAwBWs6/ax7xTAAJVSIh01VXm8+XLrY0FAABUeySnqplGjRpp//79TmUHDx5USEiI6tWr5/KYoKAgde3atcyeU2FhYYqMjHTagGrLnpxas0ZiCCuAQGUf2kdyCgAAeBjJqWqmZ8+eWnHOyjrLly9Xly5dVKNGDZfHGIahzMxMNW7c2BshAr7vkkukFi2kwkJWqgIQuOzJqQ0bSNQDAACPIjnl4/Lz85WZmanMzExJ0q5du5SZmak9e/ZIMofbjR071lF/3Lhx+uWXXzRhwgTt2LFDc+bM0euvv65//vOfjjpTpkzRJ598op9//lmZmZm69dZblZmZqXHjxnn1swE+jaF9AAJd8+Zmor6oSEpPtzoaAABQjZGc8nEZGRlKSEhQQkKCJGnChAlKSEjQ5MmTJUk5OTmORJUkNW/eXMuWLdOqVavUsWNHPf7443rhhRd0/fXXO+r8/vvvuuOOO9SmTRslJSUpOztba9asUbdu3bz74QBfZk9OLVsmFRdbGwsAWIWhfQAAwAtshn22bKAC8vLyFBUVpdzcXOafQvV08qRUr56Uny9t3ix16WJ1RD6Be981rguqrffek4YONYc7lzE3ZaDi3gcAwD3oOQUAroSGSv37m88Z2gcgUPXta67c9+OP0s8/Wx0NAACopkhOAUBpmHcKQKCLjJR69jSfM7QPAAB4CMkpACjNoEHm4+bN0oED1sYCAFZh3ikAAOBhJKcAoDSNG0udOpnPP/7Y2lgAwCr25NSnn0qFhdbGAgAAqiWSUwBQhuKB5tC+PTM/1KpV5orqABBQOneW6taV8vKkTZusjgYAAFRDJKcAoBRpadLQWWZyKmrjJ+rf75Ti481yAAgYwcHS1VebzxnaBwAAPIDkFAC4kJYmDR8ufXioqw6qgaKUp8u1TtnZZjkJKgABhXmnAACAB5GcAoBzFBVJ48dLhiEZCtIHGixJGqkFMgyzTkoKQ/wABJD+/c3HjRul33+3NBQAAFD9kJwCgHOsXSvt3Xvm9du6UZKZnArTCRmGlJVl1gOAgNC0qdS6tVRcLH32mdXRAACAaobkFACcIyfH+fUq9VWWYlVHv+tafVhqPQCo1hjaBwAAPITkFACco3Fj59eGghy9p8ZqXqn1AKBasyenPvlEjjHOAAAAbkByCgDOkZgoxcZKNtuZsrc0RpI0SMtUX4cVF2fWA4CAccUVUo0a0u7d0k8/WR0NAACoRkhOAcA5goOl6dPN5/YE1Q611RZ1Ug0V6ga9o2nTzHoAEDBq1ZJ69zafM7QPAAC4EckpAHAhOVlauFBq0uRM2TyNlSRNafGWkpMtCgwArDRggPlIcgoAALgRySkAKEVysjl6JT1dmj9fGpE2SkZwsOr+sEnaudPq8ADA++zzTn32mXTqlLWxAACAaoPkFACUIThY6ttXGjVK6n1dQ9muucbc8dZblsYFAJbo2FGqX186elT64gurowEAANUEySkAqIgx5sToeustqbjY2lgAwNuCgqT+/c3nDO0DAABuQnIKACriT3+SIiOlPXuktWutjgYAvM8+tG/xYskwrI0FAABUCySnAKAiIiKkP//ZfM7QPgCBaNgwsy385htp/XqrowEAANUAySkAqKix5qp9evdd6Y8/rI0FALztwgvNifgk6ZVXLA0FAABUDySnAKCiLr9catZMysuT3nvP6mgAwPvGjTMf331XOnzY2lgAAIDfIzkFABUVFHRmYvR586yNBQCs0LWr1LmzVFAgzZ1rdTQAAMDPkZwCgMqwJ6c++UQ6cMDaWADACvbeU6++yuqlAACgSkhOAUBltGwpde8uFRVJqalWRwMA3nfDDebqpT/+KH32mdXRAAAAP0ZyCgAqy957auZMqbDQ2lgAwNtq1TrTDjIxOgAAqAKSUwBQWWPHSvXqSd9/L/3vf1ZHAwDeZx/at2SJtG+fpaEAAAD/RXIKACqrdm3p/vvN51OmSKdOWRsPAHhbu3bmCqZFRdLrr1sdDQAA8FMkpwCgKu66S4qOlnbtkt54w+poAMDjioqkVavM6fZWrZKK7zjde2rWLIY4AwCASiE5BQBVccEF0sSJ5vPHH5dOnLA2HgDwoLQ0KT5e6tdPGj3afGw58XoV1K4n7d0rffSR1SECAAA/RHIKAKrqzjulJk3ML2avvWZ1NADgEWlp0vDhZlN3tp/3hevFo381X8yc6f3AAACA3yM5BQCV5Bjasjhc34+YZBY++aR0/LilcQGAuxUVSePHS4ZRcp9hSK/qTvP5xx+bw5wBAAAqgOQUAFTCuUNb2j1/i/YEx0v799NzAEC1s3ZtyR5TZ/tRl2i5+stmGPQgBQAAFUZyCgAqyNXQllMK1aNFkyVJBY/9R8rPtyg6AHC/nJzz13lFpydGf/116dgxzwYEAACqFZJTAFABZQ1tmacx+l4tFJZ3WMXTXvB+cADgIY0bn7/O+xqiE9FNpYMHpZQUj8cEAACqD5JTAFABZQ1tKVKIpugR8/lT/5Wys70YGQB4TmKiFBsr2Wyu99tsUuO4Gqrx9lzzxezZ0sKFXo0RAAD4L5JTAFAB5xva8o5u0FYlqEb+7+bYv4ICr8QFAJ4UHCxNn24+PzdBZX89bZoUfHU/6YEHzILbb5f27PFajAAAwH+RnAKACjjf0JZiBevPelenal0offGFdM89XokLADwtOdnsDNWkiXN5bKxZnpx8umDKFKlbN+n336UbbzTHQwMAAJSB5BQAVEB5hracirtYQe+kmi9mzTI3AKgGkpOl3bul9HRp/nzzcdeusxJTklSjhrmzdm1zLPSTT1oVLgAA8BMkpwCgAso9tOXaa6R//9ssuPtuacMGr8UIAJ4UHCz17SuNGmU+Bge7qHTxxdKMGebzKVOk9eu9GCEAAPA3JKcAoILKPbTlgQek66+XTp0yH8uzFjsAVBc33ij95S/msL7Ro6Vff7U6IgAA4KNITgFAJZRraIvNJr3xhtS2rZmY6tlTWrRIMgyrwgYA75oxQ2reXPrlFykhQVq50uqIAACADyI5BQCVVK6hLbVrS4sXS3Fx5pez4cOlq6+Wvv7ay9EGjjVr1mjIkCGKiYmRzWbTkiVLznvM6tWr1blzZ4WHh+uiiy7SK6+84vlAgUAQGWm2gc2bmyv39e8v/f3vUn6+1ZEBAAAfQnLKx3nqS9aiRYvUtm1bhYWFqW3btlq8eLEHogcgSWrZUtqxQ5o0SQoLkz77TOrYUfrHPxjm4gHHjh1Thw4d9NJLL5Wr/q5duzRo0CAlJiZq27ZtevDBB3XPPfdo0aJFHo4UCBAdOkhffmkmpSRp5kypfXvpgw+kY8esjQ0AAPgEklM+zhNfsjZs2KCRI0dqzJgx2r59u8aMGaMRI0Zo48aNnvoYAGrWlB5/3ExSXXedOQfLSy+ZiatXXmGpdTcaOHCgnnjiCSU7jbEs3SuvvKKmTZtq2rRpatOmjW677TbdcssteuaZZzwcKRBAatWSXn7ZHNbXtKk5DnrIELNn1aWXSmPHmqtNfP45CSsAAAKQzTCY/MRf2Gw2LV68WMOGDSu1zv3336/33ntPO3bscJSNGzdO27dv14bTq4WNHDlSeXl5+uijjxx1rrnmGtWpU0epqanliiUvL09RUVHKzc1VZGRk5T4QEMg+/VQaP1765hvzdfv20rBhUuvW5taypZnQ8jH+du+Xp93s06ePEhISNN2+DKOkxYsXa8SIETp+/Lhq1KhR4piCggIVFBQ4Xufl5SkuLs5vrgtgqbw8syfpokXSvn0l9wcFme1gXJwUGlpyCwk5szzq2cumnruEalVce610zTXnreZvbSIAAL4qxOoA4F4bNmxQUlKSU9mAAQP0+uuv69SpU6pRo4Y2bNige++9t0SdadOmeTFSIMBddZWUmWkOb5k82Rzy8uWXznXi4swvaI0aSeHhzltoqPkFLijI/EJmfyxLWftvv93swRCA9u/fr+joaKey6OhoFRYW6vDhw2rcuHGJY6ZOnaopU6Z4K0SgeomMlF54wdz275e2bDmzZWSYCatvvzU3qzRsWK7kFAAAcA+SU9VMeb5klVZn//79pZ7XVS8BAFUUEmLOO3XDDdL//mf2otq5U/ruO+nQISkry9y8YcSIgE1OSWYPq7PZOxWfW243ceJETZgwwfHa3nMKQAU1amT2Urr22jNl+/dLW7dKR45IJ0+W3E6dMuud3fnf3QMBEhPdez4AAFAmklPVUHm+ZLmqU9qXMIleAoBHNWggpaQ4lx05ciZR9dtv0okT0h9/mI8nTkgFBeaXseLiM49lOd8XtwsuqNJH8GeNGjUqkZw/ePCgQkJCVK9ePZfHhIWFKSwszBvhAYGnUSNp0CCrowAAAF5EcqqaKc+XrNLqnNub6mz0EgC8rF49qVcvc4NH9ezZU++//75T2fLly9WlSxeX800BAAAAcC9W66tmevbsqRUrVjiVnfslq7Q6vcr4EhwWFqbIyEinDQB8UX5+vjIzM5WZmSnJXMU0MzNTe/bskWQm28eOHeuoP27cOP3yyy+aMGGCduzYoTlz5uj111/XP//5TyvCBwAAAAIOPad8XH5+vn788UfHa/uXrLp166pp06aaOHGisrOzNW/ePEnml6yXXnpJEyZM0O23364NGzbo9ddfd1qFb/z48erTp4+eeuopDR06VEuXLtXKlSu1bt06r38+AHC3jIwM9evXz/Ha3uvzpptu0ty5c5WTk+NIVElS8+bNtWzZMt177716+eWXFRMToxdeeEHXX3+912MHAAAAApHNMNw9gyTcadWqVU5fsuzsX7Juvvlm7d69W6tWrXLsW716te6991598803iomJ0f33369x48Y5Hb9w4UJNmjRJP//8sy6++GL9+9//VnJycrnjYulkwLWiImntWiknR2rc2JxTNzjY6qjch3vfNa4LEJi49wEAcA+SU6gU/hgDSkpLk8aPl/buPVMWGytNny5VIPfr07j3XeO6AIGJex8AAPdgzikAcIO0NGn4cOfElCRlZ5vlaWnWxAUAAAAAvo7kFABUUVGR2WPKVT9Ue1lKilkPAAAAAOCM5BQAVNHatSV7TJ3NMKSsLLMeAAAAAMAZySkAqKKcHPfWAwAAAIBAEmJ1AADg7xo3dm89AEDlVfdVUwEAqI7oOQUAVZSYaK7KZ7O53m+zSXFxZj0AgOekpUnx8VK/ftLo0eZjfDyLUgAA4OtITgFAFQUHS9Onm8/PTVDZX0+bxi/3AOBJrJoKAID/IjkFAG6QnCwtXCg1aeJcHhtrlicnWxMXAAQCVk0FAMC/MecUALhJcrI0dKj35zphfhUAvsDKtqgiq6b27eudmAAAQPmRnAIANwoO9u4Xn7Q0s7fA2V/KYmPNYYb01gLgLVa3RRVZNbW0JBqJfgAArENyCgD8lH1+lXOHsdjnV2E4IQBv8IW2qLyrof7wgzlB+rlJtFGjpNRUEv0AAFjFZhiuRucDZcvLy1NUVJRyc3MVGRlpdThAwCkqKvkF62w2m/nFatcu9/7yz73vGtcFgcqqtqi0OLKzXc87ZbNJdetKv/7qer8r9gUtykquce8DAOAeTIgOAH6oIvOrAICn+EpbdL5VU+0JqYr8JMtE6gAAeA/JKQDwQxWZXwUAPMWX2qKyVk2dMkU6cqTi5yTRDwCAd5CcAgA/VN75VcpbDwAqw9faouRkafduKT1dmj/ffNy1S2rRomrnJdEPAIBnMSE6APihxESzN0BZ86vExpr1AMBTfLEtcrVqalWTYyT6AQDwLHpOAYAfOt/8KpI0bRrLoAPwLH9pi+xJtHNjPB+bTYqLI9EPAICnkZwCAD9V1vwqZ68uVVQkrVplLpO+atWZiX1LKweAiihvW2SlspJopfGl5BoAANWdzTAqsm4JYGLpZKD8iorMyXRzcsyhIYmJ7v2iU9b509Kk8eOdV9OKjZVGjTKTUueWT59e9hdJ7n3XuC6A59s6d3DVJsbFSTfcULJNjIszE1O0iQAAeB7JKVQKf4wB5VNacuh8SSB3vffw4eVfOt3eS6Csng7c+65xXQD/UVoSrTLJNe59AADcg+QUKoU/xoDzKy05VJ4kUFUVFUnx8c5JsfKwT168a5frL2Xc+65xXYDAxL0PAIB7MOcUAHhAUZHZY8pV+t9elpLiuXme1q6teGJKMmPLyjKPBwAAAABvIDkFAB5wvuSQp5NAOTnWHg8AAAAA5UVyCgA8oLzJHU8lgRo3tvZ4AAAAACivEKsDAIDqqLzJnYomgco7YW9iojl3VHZ2+SdEl87MOZWYWLG4AAAAAKCy6DkFAB5gTw7ZJz8/l81mLlNekSRQWpo5yXm/ftLo0eZjfLxZfq7gYHNFQPt7lYe93rRpvrf8OwAAAIDqi+QUAHhAWcmhyiSB7Cv/nTuPVXa2We4qQZWcbK4I2KSJc3lcnHTffWby7GyxsZ5dQRAAAAAAXLEZRkUGfAAmlk4GyictzVy17+ykUlycmZgqbxKoqMjsIVXaBOv2oXi7drlOdpU2FLC8QwTPxr3vGtcFCEzc+wAAuAdzTgGAByUnS0OHVjwJdLaKrPzXt2/J/cHBFSsHAAAAAG8iOQUAHlbVJJDVK/8BQGVVpocmAAAIPCSnAMDHeWrlPwDwJFfDmmNjzfn4mNsOAACcjQnRAcDHeWLlPwDwpMos4gAAAAIXySkA8HHuXvkPADypqMjsMeVqyR17WUqKWQ8AAEAiOQUAfiE5WVq4UGrSxLk8NtYsZ4gMAF9RkUUc3KGoSFq1SkpNNR9JegEA4H+YcwoA/IQ7Vv4DAE/z5iIOzGsFAED1QHIKAPxIVVf+AwBP89YiDvZ5rc4dPmif14pepQAA+A+G9QEAAMBtvLGIA/NaAQBQvZCcAgAAgNt4YxEHb89rBQAAPIvkFAAAANzK04s4eHNeKwAA4HnMOQUAAAC38+QiDt6a1woAAHgHySkAAAB4hKcWcbDPa5Wd7XreKZvN3F+Vea0AAID3MKwPAHxUUZG0apWUmmo+MrEvAJi8Ma8VAADwHpJTAOCD0tKk+HipXz9p9GjzMT7eLAcAeH5eKwAA4D0kp/zAjBkz1Lx5c4WHh6tz585ae56lZ15++WW1adNGERERatWqlebNm+e0f+7cubLZbCW2EydOePJjACintDRp+PCSK1FlZ5vlJKgAwJScLO3eLaWnS/Pnm4+7dpGYAgDA3zDnlI9bsGCBUlJSNGPGDPXu3VuvvvqqBg4cqG+//VZNmzYtUX/mzJmaOHGiXnvtNXXt2lWbNm3S7bffrjp16mjIkCGOepGRkdq5c6fTseHh4R7/PADKVlQkjR/veg4VwzCHq6SkmJMMM1wFADw3rxUAAPAeek75uOeee0633nqrbrvtNrVp00bTpk1TXFycZs6c6bL+W2+9pTvvvFMjR47URRddpBtuuEG33nqrnnrqKad6NptNjRo1ctoAWG/t2pI9ps5mGFJWllkPAAAAAKoDklM+7OTJk9qyZYuSkpKcypOSkrR+/XqXxxQUFJToARUREaFNmzbp1KlTjrL8/Hw1a9ZMsbGxGjx4sLZt21ZmLAUFBcrLy3PaALhfTo576wEAAACAryM55cMOHz6soqIiRUdHO5VHR0dr//79Lo8ZMGCAZs+erS1btsgwDGVkZGjOnDk6deqUDh8+LElq3bq15s6dq/fee0+pqakKDw9X79699cMPP5Qay9SpUxUVFeXY4uLi3PdBgQB39qp8Bw6U75jGjT0aEgB4DCuRAgCAczHnlB+wnbNGsmEYJcrsHn74Ye3fv189evSQYRiKjo7WzTffrKefflrBpyeo6dGjh3r06OE4pnfv3urUqZNefPFFvfDCCy7PO3HiRE2YMMHxOi8vjwQV4AZpaeYcU2cP5QsOLv3Lms1mrkSVmOid+ADAnVy1ebGx0vTpTGIOAEAgo+eUD6tfv76Cg4NL9JI6ePBgid5UdhEREZozZ46OHz+u3bt3a8+ePYqPj1ft2rVVv359l8cEBQWpa9euZfacCgsLU2RkpNMGoGpKW5WvrMSUJE2bxmToAPwPK5ECAIDSkJzyYaGhoercubNWrFjhVL5ixQr16tWrzGNr1Kih2NhYBQcH65133tHgwYMVFOT6P7dhGMrMzFRjxgkBXlPWqnx25yagYmOlhQvpXQDA/5xvJVLJXImUIX4AAAQmhvX5uAkTJmjMmDHq0qWLevbsqVmzZmnPnj0aN26cJHO4XXZ2tubNmydJ+v7777Vp0yZ1795dv/32m5577jl9/fXXevPNNx3nnDJlinr06KEWLVooLy9PL7zwgjIzM/Xyyy9b8hmBQHS+Vfkk80va889L0dHmHFOJifSYAuCfKrISad++XgsLAAD4CJJTPm7kyJE6cuSIHnvsMeXk5Khdu3ZatmyZmjVrJknKycnRnj17HPWLior07LPPaufOnapRo4b69eun9evXKz4+3lHn999/1x133KH9+/crKipKCQkJWrNmjbp16+btjwcErPKuthcdLY0a5dlYAMDTWIkUAACUxWYYZQ0qAVzLy8tTVFSUcnNzmX8KqIRVq6R+/c5fLz3dt3oRcO+7xnUByuavbd75cO8DAOAezDkFABZITDTnkCpl4U3ZbFJcHKvyAageaPMAAEBZSE4BgAWCg82l06WSX9ZYlQ9AdUObBwAAykJyCgAskpxsrr7XpIlzOavyVd2MGTPUvHlzhYeHq3Pnzlq7dm2Z9V9++WW1adNGERERatWqlWORCQDuQ5sHAABKw4ToAGCh5GRp6FBzhaqcHFblc4cFCxYoJSVFM2bMUO/evfXqq69q4MCB+vbbb9W0adMS9WfOnKmJEyfqtddeU9euXbVp0ybdfvvtqlOnjoYMGWLBJwCqr6q0eUVFtJUAAFRXTIiOSmECUCAw+cO93717d3Xq1EkzZ850lLVp00bDhg3T1KlTS9Tv1auXevfurf/+97+OspSUFGVkZGjdunXlek9/uC6AP0tLk8aPl/buPVMWG2sOFbSyxxX3PgAA7sGwPgBAtXHy5Elt2bJFSUlJTuVJSUlav369y2MKCgoUHh7uVBYREaFNmzbp1KlTpR6Tl5fntAHwjLQ0afhw58SUJGVnm+VpadbEBQAA3IfkFACg2jh8+LCKiooUHR3tVB4dHa39+/e7PGbAgAGaPXu2tmzZIsMwlJGRoTlz5ujUqVM6fPiwy2OmTp2qqKgoxxYXF+f2zwLAHMo3frzkqp+/vSwlxawHAAD8F8kpAEC1YztnOTDDMEqU2T388MMaOHCgevTooRo1amjo0KG6+eabJUnBpUxoM3HiROXm5jq2rKwst8YPwLR2bckeU2czDCkry6wHAAD8F8kpAEC1Ub9+fQUHB5foJXXw4MESvansIiIiNGfOHB0/fly7d+/Wnj17FB8fr9q1a6t+/foujwkLC1NkZKTTBsD9cnLcWw8AAPgmklMAgGojNDRUnTt31ooVK5zKV6xYoV69epV5bI0aNRQbG6vg4GC98847Gjx4sIKC+N8kYKXGjd1bDwAA+KYQqwMAAMCdJkyYoDFjxqhLly7q2bOnZs2apT179mjcuHGSzCF52dnZmjdvniTp+++/16ZNm9S9e3f99ttveu655/T111/rzTfftPJjAJCUmGiuyped7XreKZvN3J+Y6P3YAACA+5CcAgBUKyNHjtSRI0f02GOPKScnR+3atdOyZcvUrFkzSVJOTo727NnjqF9UVKRnn31WO3fuVI0aNdSvXz+tX79e8fHxFn0CAHbBwdL06eaqfDabc4LKPo3ctGlmPQAA4L9shuHqdyigbHl5eYqKilJubi5zrQABhHvfNa4L4FlpaeaqfWdPjh4XZyamkpMtC4t7HwAAN6HnFAAAAHxacrI0dKi5Kl9OjjnHVGI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Hjx6IiIhA8eLFcfbsWcyePRvffvstTpw44bI8njlzBgBQvnx5eHiYPpWVK1fOso5OamoqfHx80K5dO7z44ouoXLkyChUqhFu3buHUqVP4/PPP8c8//2DGjBmoWLGiydLa119/Hd9//z0AoE2bNnj11VdRsWJFaDQaxMTEYM6cOTh16hTeeOMNlCxZEu3bt7fpmHfs2GH0uCx58OABrl27hl9//RUzZ87Uv0156623zK53//59fZqPP/4YAQEBVuXX0ddRUlKS/q1ZqVKl7Kq90LFjR9StWxcAUL16dQDat1BvvvmmPk2RIkWMrtujRw/ExsZi8ODB6Nq1K/z8/HD8+HF8/PHHOHv2LFatWoXAwEB8/vnnNufPXrZeO+bYcn1Ye57VuM/NsfXeMKdXr1744IMPkJCQgI8//hht27bN8tbp6NGj+jeIPXv2RKFChbJsJz09HR06dMDmzZsBABUqVMCbb76JunXrokCBAoiLi8PevXvx008/ZVnXEfeeM65zNfKtq5Hh5+eHKlWqYPny5Zg5c6bB26syZcogIiIC77zzDnx9fc3myd44mNHKlSsRHR2Ny5cvw8PDAyVLlkSjRo3Qt29fNG/e3GnHZC81Pjvt3Yau5hKgvW7Mybj89OnTio5RaWzIbjHNGHs+37p27Ypr165h+PDheOWVV1CkSBGcO3cOpUuX1qdR61nKFq44n2pT4xjUOg+uPp///vsvXnrpJdy+fRsA8Oqrr+L//u//EBAQgPPnz2Pu3LlYuHAhjh07Ztd+HPFM5GwXL17E999/jx9++AHnz59HXFwcPvnkE3zyySeoW7cu+vbti169esHf39/qbX/yySf636dMmWJQy9KS4OBg/e83b960et/ZgTPvA0fsy9pnDbU+T3NLHDLlzp07mD59OgBtrXVdq7WwsDD4+PggOTnZqWUj33zzDXbv3g0A+v1+8803+lpjHTt2RMeOHZVtzJaSLGfUlBo1apR++UcffZRl+ePHjw1GGDG1nYzLbZ2Mlfg9fPhQv7xdu3Zmz4OI6HvFb9iwocH827dvm22PnZKSIuHh4frzbayNbcZOjRctWmR0Ow8fPpQXX3xRAEhYWJhNtQnS0tKkfv36+n0dPHjQbHpLb0ZHjx5t8c2HbnSDRo0aGaRVWkNArevIlCVLljikZFq3TaV9SgGQqKioLGkSEhKkZs2aAkDc3Nzk+PHjFvftiJpS1l47Stl7fVg6z2rd55mpcW9YsmbNGvH29hZAOxrH0qVLZd++fbJ582aZNGmSvuPQWrVqSVxcnNFtzJkzR5+nTp06yaNHj4ymS0tLk2vXrhnMU+vec9R1booa+dbV6qhZs6ZBx53GpmrVqmU5d5nZe52LKPss7Nixo8nOy9U+poxsiTlqfHbau42kpCT9YAE1atQwm9+Mo2GaG23L3tjgqphmDWs/39zc3Cz2JaPG9WCL7HA+M7P2flLjGNQ6D9nhfI4YMUKfh1mzZmVZnpqaKh06dLD5uVHEumei7FxTKqM9e/bIoEGDpEiRIgbnxtPTU7p06SLr1q1T/N3j6tWr+lpYlSpVsjovMTEx+v23atXK6vVNUfI5amlSUovEmfeB2vuy9VlDjc/T3BSHTBk2bJgA2j6s7t27Z7Csbt26Ami/5zuLrkzI1GRNjblsWSj16NEjfVCrUaOGyVEWrly5or+ATQVrRwWQW7du6Zf36NHD7HkQEf3Q3dWqVbOYNrOMwfXQoUNZltepU0cA7ZdGc06fPq3fzubNm63Ox6xZs/TrW9qXiOmH61q1asn+/fstrr9r1y7RaDTi4eGR5Uumki9jal5HpugK+gDI33//rXg9S5TczBnPwcsvv2wy3YEDB/Tp3nzzTYv7dkShlLXXjhL2Xh8ils+zo+5ze+8NpU6dOiWvv/56lir2AKREiRIye/ZsSUpKMrpuxg78g4ODrRruVs17z1HXuSPzXahQIQGgH6mucOHC8tVXX8mtW7fk0aNHcvDgQWnTpo1+/UaNGpnclxrXuYhIgQIFpGfPnrJo0SLZtWuXHD16VH7//XcZP368wbDATZs2NdpZp5rHlJmjmgxb+uxUYxsvvfSSfrmxAlMRkaioKIN7z9x1bG9scFVMs4a1n2/9+/dXZb9qXA+ZZYfzmZm195Max6DWeXD1+Xz48KH4+fkJAHn22WdNFgDfuHFD8ufPb9Nzo4h1z0Q5pVBK59GjR7Jy5Upp3769week7rlj1KhRcuzYMbPbyBgHJ0yYYHUetmzZYtV1pJSx2GztpKRQypn3gdr7sudZw97P09wSh0w5e/as/p4yVmDet29fAbRdciQkJDg0L46QLZvvHT58GP/++y8AICIiAm5uxvtjDwkJQatWrcx2YqdGFbaQkJAs8zJ2NOrp6WlxG15eXgCAhw8fmk2XkpKCmzdvIikpCenp6QAAEdEvP3bsGOrUqaP/+9q1azh8+DAAoHv37ma3XaVKFRQrVgx37tzBvn370LJlS4v51tmxYwfee+89AEDx4sWxYMECi+tkrK7/8OFDXLhwAT/99BPWrl2LV199FXPmzMHLL79sdN3Hjx/jjTfegIjg7bff1lf3t4aa15ExV69e1VdPbNiwISpWrGh1HtVirilC/fr18cwzz+DUqVP4448/nJgrLVuuHUvUuD6UcNR9bs+9odSTJ08QFRWFX3/91SCG6Ny8eRPR0dGoWLEi2rVrl2V5TEyMvgP/gQMHWtUcy1H3nqOvc7XynZycDEAbz93d3bFp0yY0bNhQv7xu3bpYv349Xn75ZWzatAl79+7FmjVr0LVrV4PtqHmdX7t2DYULF84yPzw8HMOHD0ebNm1w9OhR7NixAwsWLMCIESMcckyOYu1np1rbmDx5Mv744w+kpqYiIiICFy5cQJ8+fRAYGIi4uDh8//33mDJlCjw9PfUDEJiLD46ODY6KaY706quvWr2OGteDEjnxfGamxjGodR5cfT4PHz6sbxrUp08fk03GSpQogdatW+OXX36xeh/WPhNlt07xLfHy8kLXrl3RtWtX3LlzB1FRUfj+++9x+PBh3Lx5E7Nnz8bs2bNRu3ZtREREoE+fPlma7mY85kaNGlmdh5MnT+p/tzQolzUc9Z0yM2feB2rvy55nDXs/T3NLHDJl7NixePLkCUqXLo1hw4ZlWf7MM88A0H7WnThxwqZ7x5WyZaFUxpu+Xr16ZtPWr1/f7BeajL3Rqyl//vz63zOOdGWKbmQrb2/vLMuSk5Px+eef48cff8SpU6fMjl5x584dg78PHTqk/71Xr17o1auXxbwAwI0bNxSlA4BTp06hU6dOSE1NhZeXF3766SeUKFHC4nqFCxc2CEz16tVDz5498cMPPyAiIgIdOnTA4sWLjY4o99FHH+HMmTMoVaoUIiMjFec1IzWvI2OWLVumf9iNiIgwm/batWv6L7uZFSlSxKD9uy2UHN+pU6dw7tw5PH78WFGQVYM1144150iN60MJNe/zjGy5N6w5P8nJyWjbti127twJd3d3vPvuu+jXrx/Kli2LR48e4cCBA5gyZQp2796N9u3b47PPPsvST83Ro0f1vzdp0sTisWfkqHvP1utc6blTK9/58+fXF+J069bNoPBGx83NDZ988gk2bdoEAIiOjs5SgKPmdW7sIVGnRIkSWLVqFapUqYLHjx/jiy++yFIopdYxqcmez061tlG/fn0sXrwYAwcOxOPHj/HBBx/ggw8+MEjj7u6OOXPmYPjw4QCAggULmtyHPZ+bSjgqpjlSjRo1FKVT43qwVk48n5mpcQxqnQdXn8+MhRmWCi3r1q1rdaGUrc/Tpij9bFM7nVLFihXDiBEjMGLECJw5cwZLly7F8uXLcfXqVRw9ehRHjx6Fn59flnh2+fJl/e9VqlSxap8A9H3cAECDBg2sXt8UR32nzMyZ94Ha+7LnWcPez9PcEoeM2b17t74P448++khfEJaRrlAKAAul1JIxIBYvXtxsWnuCuT0y3gRJSUkW0+se5jPXNrh06RJefPFFxMbGKtpv5lLYW7duKVovswcPHihKFxsbi1atWuHff/+Fu7s7oqOj0bRpU5v2qfPaa69h/fr1+OmnnzBs2DB06NDB4C3JX3/9pe/E7YsvvjDo/M4ajr6OfvjhBwDaEvIePXqYTTt+/HgsXbrU6LKIiIgsQ1tbS+nxiQj+/fdfp9w31l47Ss+RWteHEmrd50qZuzesuYYiIyOxc+dOAMDixYsNCk09PT0RHh6O5s2bo1WrVti2bRtGjRqF5s2bG3z5y/ilLTAw0KrjcNS9Z+t1rvTcqZXvggUL6q+FNm3amEz3zDPPIDg4GNeuXcPBgwcNljnzOgeAsmXLIjw8HBs2bMD58+dx/fp1BAUF6ZercUxqsvezU61tANoaFTVr1sSHH36I3377DYmJiQC0hXTNmzfHhx9+aPD/M9WhtzmWPjeVcnZMU4OS41Trf2mtnHg+M1PjGNQ6D64+n9Z8Blg74IQjnqeVfrapnc4WJUuWRJkyZRASEoKrV6+aTZvxu421naQ/ePAAGzduBKAtXDA3gEd25cz7wNn3nKVnDXs+T3NLHDJm9OjRALSF5aYqoGQslMo4CE1OkS0LpTJWsbY02oKxZikZZXzrYauQkJAsJb/58+fXN4WzFFz//fdf/QUbGhpqsOy1115DbGwsNBoN+vXrh549e6JKlSoICAjQl4Kmp6frR87KfLwZ3wQuX75c8RtFJQ95169fR8uWLXH9+nVoNBp8++236NSpk6LtW9KhQwf89NNPSE5OxqZNm9C7d2/9ss8++wyPHz9G2bJl8eDBA/z4449Z1s/4f926dau+5lf79u31wUrN6yizQ4cO6Ud8ePnll236cqAmtY/PXo68dtS6PpRQ6z63hrl7QwkRwXfffQcAqFixoslafB4eHpg6dSpeeOEFpKen47vvvsNnn31mNK01o97o8qB0XWuuTUdf52rlOzQ0VH/NWaqqHxoaimvXrmV5weDM61ynatWq+tpf165dM3hQVOOY1GTvZ6da29CpWbMmfvrpJ6SlpSEuLg6PHj1CUFAQChQoAACIiorSp61atapNx2xvbABcE9PslXnkUGPU/F9aIyeez8zUOAa1zkNuOJ/GOPKZKDt78uQJNm7ciO+//x7r1683qHUSHByM//u//0OrVq2yrJcvXz797+ZqPBrzzTff6K+LTp06ma25Yy1HfafMzJn3gSvuOXPPGoDtn6e5NQ6tWLECBw4cAKBtYmyqa4mMnDkCn1psKpTSnQxd0yVTdP8ka2UsFb9586bZvnosPfSq0dfMd999Z7SqfJUqVbBr1y6cP38eqampJoeM/OuvvwzWyThfV8V03Lhx+PDDD42ub6oqLQAULVpU/7tGo1GtaumdO3cQHh6OixcvAtC+qe/Tp48q2wYM3zD9888/Bst01SAvXryoqDni1KlT9b/Hxsbqv4ypeR1l9v333+t/t9R0DwCWLFlid20oc27evGk2GOqOT6PROLwAzdZrR+k5Uuv6UMre+9xapu4Npefn5s2buHfvHgCgdu3aZtNmbJ6QMf+Attq9zvXr11GpUiWL+9Zx1L1n63Wu9Nyple9nnnlGX0vI0gO1bnnm68rZ1zlg/ou6GsekFjU+O9XYhjHu7u5GC+3UaE5i7nPTGs6OaY7mqP+lUrnhfKpxDGqdB1eez4yfG7du3TL7GXD79m1F23Tk87TSzza101ly4MAB/PDDD/jxxx9x9+5d/Xxvb2907NgRERERCA8PN/nlOmMttWvXril+bk1KSsLMmTMBaGPx+++/nyXNypUr0b17d8ybNw+lS5fGJ598gsOHD8PX19di1yaO/E6ZmTPvA2ffc0pfCtjyeZob4lBGjx8/NnodW5ITC6UsF7UZoavWdv/+fbPp/v77b1s2b3DTW6r+78jmAZa88MILALSFb7rOxo3ZsWOH/vfnn39e//upU6f0v/fs2dPk+hn7jcos45fO33//3XyGFYqPj0fr1q31NYFmzJiBoUOHqrJtHV0HyoDjqjs66jp68uSJvtZCQECA2aYszqL0+CpUqODQ/qScce04m733ubXsvTcyfnCmpqaaTfvkyROj6wHAs88+q/9d1xRQKUfde46+ztXKd8Y+uC5cuGB2O7ovKvb2K6cG3X0LIMuby+x0TGp8dqqxDaUeP36MVatWAdCeE1v7eVDrc9PZMc3RnPm/NCY3nE81jkGt8+DK85mx+Yul60XJ9ZQbn4lMuXTpEqZNm4ZKlSqhYcOG+PLLL/UFUo0aNcLXX3+NuLg4REVFoXXr1mZre2QsaMj4f7bk3XffNRigxdiL+piYGADA+vXr0aNHD4SFhWH48OEYOHCg4v04gzPvA2ffc+aeNSyx9HmaG+JQRvPmzcPFixeh0Wgwf/58REdHm51030nv37+PK1euqJ4fh7JlyL7PPvtMP1TiX3/9ZTRNSkqKBAUFmRzGNONwn5mXZRyWu1atWiaHZL169ap4enq6bKjUjEOQDxo0yGiatLQ0qVKligDaIbQzDn/5448/6tc3N9Rzx44d9emMDaFctWpVASD58+eXf/75x65jSk5Olueff16/v/Hjx9u1PVPatm2r34elocyNUTIUuqOuo19++UWf9q233rI670qY+3/rZDwHr7zyisl0Bw8e1Kd78803Le7b1uHZnXXtKKHk+hBRdp7tvc+tZe+9kZaWJoUKFRIAEhQUJE+ePDGZ9tdff9Xva/jw4Vm2ExoaKgAkJCREEhMTFedBzXvPUde5I/N9584d/bC94eHhJve3fft2/TZef/11q/Or9DpX4sKFC/o8ly1bNstyRx6TtTFHjc9OtT5/lZg5c6Z+G1OnTrVpGyLKYkN2jGm25DHjtW2JM/+Xxrj6fGZmy2e4Gseg1nlw5fl8+PCh+Pn5CQB59tlnTX4G3LhxQ/Lnz2/2sys7PRM5yv379+Wbb76RJk2aiEaj0R8rAClVqpSMHz9ezp49a/V2jxw5ot9O1apVFf1/v/zyS/061apVk+TkZKPpdHE0JCREzp8/b3XenMWZ94Ez92XpWcMSS5+nuSEO6dy7d0/8/f0FgHTq1EnROhnLaNavX69qfhzNpkKpjMFi4MCBWZanp6fL4MGDDYKTNYVSIiKjRo3SL//444+zLH/y5Im0adPG7D6coXHjxgJAPDw8ZO/evVmWZ7x5Mj8EHT58WL9syJAhRrc/f/58g2M09iAVFRWlX16nTh25deuWyfw+evRIvvzyS3n48GGWZSkpKdKqVSv9tmwpcPnuu++Mbjuj2bNn6/cRFhZm9kuzKUq/jDniOurSpYs+7eHDh63OuxLWPrQDkBUrVmRJk5iYKLVr1xYA4ubmJseOHbO4b1seaNW4dtSkZqGUiH33uY6z7g0RkV69eum3M2nSJKNp7t27py/QBiD/+9//sqT5/PPP9cs7deokKSkpRreVlpYm165dM5in1r3nqOvcFLXyPWTIEP3y6OjoLMsTEhKkVq1a+jR//vmn1XlVep2vW7fO7LV048YN/fkDIJ9++qnRdI46JmtjjhqfnWp9/oqI2ZdB69at0z+AV6hQwWgMUDM2ODOm2crazzdL1Pxf2sqV5zMzW18sqXEMap0HV57P4cOH67c9a9asLMvT0tKkQ4cOZj8D1Hwmatq0qUu/55iTsWAOgBQoUED+7//+T/744w+TBXpKvfzyy/rt9uvXT1JTU42me/DggYwZM0aftlSpUmYLmwIDAwWAbNmyxa78OYNa94EuTenSpR26LzWeNez9PFXrWNTcjq10z6MajUbxc+2GDRv0eZo+fbrqeXIkmwqlREQaNmxo8KG3detWOXz4sPz444/SrFkzASDPPfecyUBqqVDq/v37EhISok/Tq1cv2bRpkxw+fFiio6OlXr16AkD/01XB+siRI+Lt7S0AxNfXVz766CPZt2+fbN26Vd544w193ipWrCgJCQkG66anp0u1atUMjnH9+vVy+PBh+fnnn6Vr164CwOBNi6mLPiIiQp+mWLFiMn78ePn999/l6NGjsnv3blm6dKkMGDBAX+JqrNZD586d9dt48cUX5fjx43LixAmT099//51lG6VLlxZ/f38ZOHCgLF26VHbv3i0xMTGya9cumT9/vsGxeHp6yubNm20670q/jKl9Hd27d0+8vLwE0L6JcRRrH9rr1q0r7u7u8uabb8rWrVvl0KFD8u2330qlSpX0aTLXhNHZtWuXfPfdd/rpk08+0a/z/PPPGyz77rvvjG5DjWtHTWoXStlzn+s4694QETlz5owUKFBAv7327dvLqlWr5MiRI7J3716ZPXu2lCpVSr+8RYsWRreTlpYm4eHhBsc3Z84c2b17txw5ckQ2btwoEydOlAoVKmQ5h2rde2pd50qple9bt27pz7GHh4cMGzZMn+fvvvtOKleurF/f1BdpS5Re56VLl5agoCAZPny4REVFyd69e+Xo0aOyefNmGT9+vBQtWlS/nRdeeEEePXpkdDtqHZO9MUeNz041P38LFiworVq1kkWLFsnevXvl0KFDsmrVKunRo4d+3SJFisiRI0dM/n/Uig3OjGm2svbzzRI1/5e2cuX5VOMzXK1jUOs8uPJ83r17V0qWLKnfx6uvviq//fabHD58WFasWCGNGjUSAFK/fn19mkuXLhlsQ81nouxcKAVovzA3adJEFi9ebFWNaktu3rypr60NQKpXry5ffvml7NmzR//8MW7cOINWOdWrV8/yv8jo1q1bAmhrQucEat0HunTmCqXUes6191nD3s9TNc+bK+PQxYsX9TXyu3btqni9c+fOGXwW5iQ2F0qdOXNGihcvrj/wzNOoUaPMFjxZKpQSETl58qTBB0PmqV+/foq242jr1q3TN5cxNlWsWFHOnTtndN2jR4/qm4sYm6pXry7Xr1+3+CCVmpoq7777rri7u5vclm7y8fGRBw8eZNmGpfUyT8aCW+nSpRWtGxISIr///rvN59yaZitqXkcLFizQp5s5c6bN+bdEyYNzxnNw8eJFKVOmjMlj7NKli8m3FxkLNJVM5vJrz7WjJrULpUTsu89FnHdv6GzevFmKFStmcX8vvvii3Lt3z+R2kpOT9V/qzE3GzqEa955a17k11IoZp0+flvLly5s9b/3797e5yrc1hVJKrr0uXbrIv//+a3afahyTGjFHjc9OtT5/fXx8zOa/atWqZh+g1YwNzoxptlKSR2sKpUTU+1/aw1XnU437Sc1jUOs8uOp8iojExMRIQECAyX337dtXFi9erP/7xo0bButb8/8AzD8TZedCqcjISLlw4YLDtn/t2jWDwmRTU4ECBWTcuHEmX6jo/O9//xMA8sEHHzgsz2pT4z5Qcp2psS81njXs/TxV61jU3o61dIVwGo1GTp48qXi91NRUfW0yR1aecASbC6VEtP1qDBkyREqXLi2enp4SEBAgL730kmzYsEFEzBc8KS0EuHv3rrz77rtSoUIF8fLykmLFiknz5s0lKirKqu042qVLl+Ttt9+WihUrSoECBaRw4cJSt25d+fjjj022a9b5559/ZPDgwVK6dGnJly+f+Pv7S/369WXWrFn6qolKH6T+/vtveeedd6R27dpSpEgRcXd3l4IFC8ozzzwjr776qixdutRkaa4aH6Lnz5+Xr776Snr06CE1atSQEiVKiIeHh/j6+kq5cuWkS5cu8t1331k8J5ZYUyglot51pHtD5u7unqW5kpqU/L8zP7Tfu3dP3n//falSpYoUKFBA/Pz8pEmTJrJs2TKz+2KhlPIvKPbc5866NzK6c+eOfPzxx9KsWTMJCAiQfPnyibe3t5QpU0a6d+8uP//8s+Iq9lu3bpXXXntNypQpI97e3lKwYEGpXLmydO7cWaKioiQpKcnoevbee2pd59ZSK2YkJSXJJ598Ig0aNBB/f3/x9PSUkJAQ6dGjh2zdutWuPCq9zrdv3y6TJ0+Wl156SSpWrCj+/v7i4eEhhQsXlurVq8ugQYOMVk131DGp9SVajc9ONbYRHR0t/fr1k2eeeUZ/PoKDg6VNmzayePFii4WOasYGZ8Y0W9ny+aaEms9StnLF+VSzUEqtY1DrPLjifOrcvn1b3nnnHZOfARn7bsncjEjNZ6LsXCjlLBs2bJA+ffpI+fLlpWDBggbnLjg42Gy3JRnNmDFDAMi6descnGN12XsfWPPsbc++1HjWsPfzVK1jccR2lDpw4IC+j7YePXpYvb6u1nq+fPlMdruRHWlEFI7LSESUgy1YsACLFi3CiRMnMH78eEyaNMnVWSIiyjYYI4mUGzBgABYvXoyQkJCcN8pVLvDaa69h2bJlAIBvvvkGr7/+usV1evXqhR9//BFXrlxBSEiIyXSMhUTOZ3o8TiIiF1u1ahWCgoJQpEgRzJw5065tBQYGYvLkyejYsaM6mSMicjHGSCLne/jwIX755RcAQMOGDV2cm7zp888/R8mSJQEAo0aNwoIFCyzGwpiYGAQEBJgtkAIYC4lcwcPVGSAiMiYxMRFvvPEG5s2bh4IFC6J///5o06YNqlevbtP2dA8XugdJIqKcjDGSyDEuXLiAsmXLQqPRZFmWlpaGIUOG4M6dOwCAiIgIZ2ePABQpUgRff/01OnTogISEBIwYMQJLlixBoUKFjMbCBw8e4OzZs2jZsqXFbTMWEjkfC6WIKFt6+PAhRAQ1atSAr68vChcujNTUVFdni4goW2CMJHKMqVOn4s8//0TPnj3RoEEDFC9eHA8fPsTx48exaNEiHDlyBADQokULtGvXzsW5zbteeeUVfPXVVzh//jzmzZuHYsWKoVKlSkZj4fHjx5Geno7atWu7KLdEZA6b71GOdvDgQfTt2xelS5eGl5cXihYtinbt2mHXrl0uzVdSUhJGjhyJoKAg5M+fH7Vq1cKPP/6oaN3ExES8++67aNWqFQICAqDRaIy2Z9++fTs0Go3Raf/+/Wb38c0330Cj0cDX19euvNtznJYUL14cHTt2RPXq1VGmTBn06NHDZQ8TU6ZMQdWqVZGenm4yjblzqtTixYsRHByM5ORkm7dBlFFejpE6u3fvRtu2bVGkSBF4e3ujQoUKmDp1qkGamJgYtGvXDqVKlYK3tzf8/f3x3HPP6fss0dm6dSv69++PypUrw8fHB8HBwejQoQMOHz6cZb/2xGglXBEjk5OTcfLkySzT0KFDUa5cORw/ftxg/sqVK/Hiiy+iePHiKFCgACpXrowpU6bgwYMHNu1f7Rhp6niUTE+ePMmx+86tzJ3TH3/8ER06dEBQUBA8PT1RuHBhNGnSBEuXLjV6Ts+cOYPIyEi89NJLePbZZ/H8889jyJAh+gKp559/HitWrDBam8oazoiFffv2NRmLMscjpTHO2vjmqOfFQYMG4ZNPPkHPnj3x0ksvmYyFDRs2hIhgxowZdu/THGPPi0r/T9Z8vliDz5aUI7i0m3UiO0yYMEHc3NykRYsWsmTJEtm6dassWbJEatSoIW5ubqqPxmWN8PBwKVy4sHz11VeydetWGTBggACQ5cuXW1w3NjZWP6KYbj1jIwVt27ZNAMhHH30k+/btM5gSExNNbv/q1avi5+cnQUFB4uPjY1fe7TlOJfr06aMfNWTTpk1G07z44ovi5eVldJowYUKW9K+//rpVIy9du3ZNfHx8ZOXKlSbTWDqnSj158kQqVKggEydOtHkbRDp5PUaKiCxfvlzc3NykZ8+esm7dOtm6dassWrRIJk+ebJBu27ZtMmjQIPnhhx9k69at8uuvv0rPnj0FgEydOlWfrmvXrtK8eXOZP3++bN++XVauXCkNGzYUDw8P2bJlS5Zt2hKjreHsGKk7Jlum5cuXS2RkpLi7u8srr7xi0/GqHSPtOR57R0Jz5b5zK7XO6V9//SUffvihNGvWTMqUKSO+vr7i5eUlQUFB8sorr8jy5cslLS1NlTw7IxaeP38+Swzat2+fFCtWTIKDgyU1NVWfVmmMsza+5eXnRaX/J2s+X6zBZ0vKCVgoRTnSxIkTBYB88sknWZY9evRIypUrJ35+fnL//n2n523Dhg0CQD9ssE54eLgEBQUZfPgbk56eLunp6SKiHZLYUqGUucISY15++WVp3769REREZClAsSbv9h6nJbt37xaNRiPt2rUTADJ9+nS7tqdj7UPGu+++K8HBwWYfQM2dU2vNmjVL/Pz8HD7cNeVujJHawmIfHx8ZMmSIzXlt0KCBhIaG6v++efNmljSJiYlSokQJadGihcF8W2O0Uq6IkWp86X/jjTcEgNy7d8+m/KkZI1kolbvYc06PHTvm9Pw6KxYas337dgGQpTBGaYyzJr7l9edFpf8naz5frMVnS8ru2HyPcpz9+/dj2rRpiIiIwOjRo7Ms9/LywhtvvIH4+Hhs2bLF6flbu3YtfH190a1bN4P5/fr1w/Xr13HgwAGz6+uqPzvCsmXLsGPHDsyfP9/ocmvybu9xmpOWloZhw4YhJCQES5cuhbu7O2JiYmzeHgCkpqbi0aNHSEtLM/jdnMePH2Px4sXo3bs33NyMh0tL59Rar776KhISElRrBkl5D2Ok1jfffIPk5GSMHTvW5rwWK1YMHh5Pu98sXrx4ljS+vr6oWrWqU4eFd1WMbNasGUT7QhMigpSUFBQtWhRjxowxmC8i+uYpt2/fhoggLCwMAFC4cGG4ubnB09PTpnyqGSMzH481k+54cuK+c6vM53Tfvn1wc3NDRESEyXP58ccfAwDOnz/v9Py68nlx8eLF0Gg06N+/v8F8R8S4vP68qPT/5MjPFz5bUnbHQinKcaZOnQqNRoMpU6aYTFO2bFkAwNWrVxVvV0SQmpqqaDLn5MmTqFKlisEXGQCoUaOGfrmahg4dCg8PDxQqVAitW7fG7t27jaa7desWRo4ciRkzZpgcDteavDvyOL/66ivExMTgk08+QdGiRVGhQgW7HzKmTZsGb29vLFmyBB9++CG8vb3xww8/mF3nwIEDuHv3Lpo3b250uZJzaq2SJUuicuXK2LBhgyrbo7yHMVJr586d8Pf3x19//YVatWrBw8MDxYsXx+DBg5GQkGB0nfT0dKSmpuL27duYP38+/ve//1ks1IqPj8eRI0fwzDPPGF2uNEZbIyfEyIiICBQuXBhDhgzBxYsXkZiYiPXr1+Prr7/G0KFD4ePjY1M+GSNJKcZC4+Lj47Fq1Sq0aNECZcqUUZTeVIxTEt/4vGg7S58vSjFuUnbHQinKUeLj4/H777+jVatWKFWqlMl0SUlJAGDVQ++OHTuQL18+RdOlS5dMbufu3bvw9/fPMl837+7du4rzZI6fnx/eeustfP3119i2bRvmzp2LK1euoFmzZvjf//6XJf2bb76JSpUqYciQIark3VHHefv2bXzwwQdo2rQpevToAUD74HLu3DmbO8cFgEmTJmV5Q9q3b1+z6+zbtw8A8OyzzxpdruSc2uLZZ5/Fnj17VN0m5Q2MkU9du3YNDx48QLdu3dCjRw/88ccfGDNmDL7//nu0bdsWIpJlnTfffBP58uVD8eLF8fbbb+Pzzz/HoEGDzO5n6NChSE5Oxvjx4w3mWxujlcopMTIsLAz79u3DyZMnUa5cORQqVAjt27dHREQE5s6da3M+dftjjCRzGAtNi46OxsOHD/H6668rSm8sxlkT3/i8aDtTny+2YNyk7MzDchKi7OPEiRNITU1F9erVzabTfTjo3sIoUadOHRw8eFBR2qCgILPLzVXTVatpXu3atQ1GF2ncuDE6deqE6tWr491330Xr1q31y1avXo1ff/0VR48etbh/a/LuiON87733kJCQgM8//1w/r0aNGvjpp59w/PhxNGzY0Kbt2uL69evQaDQoVqxYlmXWnFNrFS9eHLdu3UJqamqWN4tE5jBGPpWeno5Hjx4hMjIS7733HgBt8x5PT0+MHDkSW7ZsQcuWLQ3Wef/99zFgwADcunULv/76K4YNG4bk5GSjzSAB4IMPPsDy5cvxxRdfoE6dOgbLrInR1sgpMfLSpUto3749SpQogVWrViEgIAAHDhzAtGnTkJSUhMWLF9u8X8ZIsoSx0LTFixejaNGi6NSpk8W0pmKctfEtLz8v2src54stGDcpO+MVSTmKrslFQECAyTSJiYmIjo5GmTJlULduXQBAhw4dDPpOSU5Oxq5du/DCCy/o5/n6+qJWrVqK8mEumBctWtToW5979+4BgNG3RWopXLgwXn75ZXz11Vd4+PAhvL29kZSUhKFDh2L48OEICgrC/fv3AWjbvwPA/fv3kS9fPvj4+FiVd0cc559//onvvvsOffr0QalSpfR51VWvj4mJcepDxsOHD5EvXz64u7sbzLfmnNoif/78EBE8evQIvr6+dh0D5S2MkYb7OXfuXJYvR23atMHIkSNx5MiRLIVSpUqV0teqaNu2LQBg3LhxiIiIyHJOJ0+ejGnTpuHDDz/EsGHDFOXJWIy2Rk6JkcDTL4wxMTH6WNikSRMUK1YM/fv3R58+fdC0aVOb9ssYSZYwFhp3/PhxHDp0CG+99Ra8vLzMprU2xpmKb3n5edFWtny+WMK4SdkZm+9RjqLrt8dcdeiZM2ciMTERkZGR+rcvv/zyC5KSkpCUlITXX38dnTt3xnPPPWewnlrVsatXr44zZ85k6UvgxIkTAIBq1arZcOTK6Zqk6I79zp07uHnzJj799FMUKVJEP0VHRyM5ORlFihTBq6++anXe1T7O9PR0DB06FCKCpUuXGuS1d+/eAGB3PwHWKlasGB4/fozk5GSD+dacU1vcu3cPXl5efGggqzFGPmWq5oMuRpoavCCj+vXrIzU1FRcvXjSYP3nyZEyaNAmTJk3C+++/b1W+MsdopXJSjNTlpWrVqlkK5+vVqwfAvn5kGCPJEsZC43Q1FAcMGGA2na0xzlh8y8vPi7aw5/PFHMZNys5YU4pylOrVq6NcuXKIjo7G1KlTUaRIEYPly5Ytw0cffYTu3bsjIiIiy/rjxo3DuXPn8PPPP2d5m6FWdexOnTph0aJFWL16tb6NOwAsXboUQUFBaNCggaJ92OLff//F+vXrUatWLeTPnx+AtnPDbdu2ZUk7Y8YM7NixA5s2bdJXN7Ym72of56JFi3Do0CFMnjwZTZo0ybK8S5cuTn/IqFy5MgDgwoULBl9wrTmntrh48SKqVq1q8/qUdzFGPtWlSxcsXLgQmzZtMmhmsnHjRgBQ9BZ927ZtcHNz0799B7SdJ0+aNAkTJkxAZGSkVXkyFqOVykkxEtBeAydPnkRSUpLBlyBdcyl7BodgjCRLGAuzSklJwbJly1C/fn2zBUG2xjhT8S0vPy9ay57PF0sYNylbE6IcZuvWrZI/f34pV66cLFy4ULZu3SpRUVHyyiuvCADp27evPH78OMt6kydPlubNm8vDhw8dnsfw8HApUqSIPn8DBw4UALJs2TJ9mu3bt4u7u7tMnjw5y/obN26UlStXyrfffisApFu3brJy5UpZuXKlJCcni4hIr169ZOzYsbJy5UrZtm2bLFy4UCpVqiQeHh6yefNmi3mMiIgQHx8fm/JuS1pz7t69K0WLFpVGjRpJenq60TTNmzeXAgUKSFpamlXbtsfly5cFgHz99deK0ps6p9ZIS0sTPz8/GTVqlF3bobyLMTJZn659+/bi5eUlU6dOlc2bN8v06dMlf/788vLLLxtsb+DAgfLOO+/IihUrZPv27bJq1Srp0aOHAJAxY8bo082aNUsAyEsvvST79u3LMmVkb4zOKCfGyF9++UU0Go00bNhQVqxYIVu2bJEPP/xQfH19pWrVqpKSkmLTPhkjSSnGwmSDtD/++KMAkIULF5rMj9IYZ218y+vPi0r+T9Z8vliLcZOyOxZKUY507Ngx6d69u5QoUULc3NwEgJQuXdrkg/6nn34qzz33nCQmJjolf4mJiTJixAgpWbKkeHp6So0aNSQ6OtogzbZt2wSAREZGZlm/dOnSAsDoFBsbKyIi06dPl1q1aomfn5+4u7tLQECAdOrUSf78809FeTRVgKIk77akNWfQoEHi4eEhJ06cMJlm5MiRAkDOnDlj9fbt0bhxY2nbtq2itGoUSm3ZskUAyOHDh+3aDuVtjJFaDx48kLFjx0poaKh4eHhIqVKlZNy4cfLo0SOD7X377bfSuHFjKVasmHh4eEjhwoWladOm8sMPPxika9q0qcn9Zn7PZ2+MziinxsitW7dKq1atpGTJkuLt7S0VK1aUd955R+7cuWPz/hgjyRqMhU+Fh4eLj4+PJCQkmMyP0hhnbXzL68+LSv5P1ny+WItxk7I7jYiRMZGJcpjXXnsNK1aswN69e/WdVeosWLAA33zzDbZu3Qo/Pz8X5ZByKl1183/++QfBwcEO399rr72GixcvctheUhVjJDkKYyTlJIyF5CjOjoXWYNyk7I6FUpQrJCQkoGbNmvD09MSRI0cMOlYtXLgwHj16ZDACyrZt2/SdrRKZIyJo1KgR6tSpg3nz5jl0XxcuXECVKlWwdetWg5F+iOzFGEmOwhhJOQljITmKM2OhNRg3KSdgR+eUKxQqVAixsbFGl+mGiSWyhUajwaJFi7Bu3Tqkp6crGrHLVpcvX8a8efP40ECqY4wkR2GMpJyEsZAcxZmx0BqMm5QTsKYUERERERERERE5XfYowiUiIiIiIiIiojyFhVJEREREREREROR0LJQiIiIiIiIiIiKnY6EUERERERERERE5HQuliIiIiIiIiIjI6VgoRURERERERERETsdCKSIiIiIiIiIicjoWShERERERERERkdOxUIqIiIiIiIiIiJyOhVJEREREREREROR0LJQiIiIiIiIiIiKnY6EUERERERERERE5HQuliIiIiIiIiIjI6VgoRURERERERERETsdCKSIiIiIiIiIicjoWShERERERERERkdOxUIqIiIiIiIiIiJyOhVJEREREREREROR0LJQiIiIiIiIiIiKnY6EUERERERERERE5HQuliIiIiIiIiIjI6VgoRURERERERERETsdCKSIiIiIiIiIicjoWShERERERERERkdOxUIqIiIiIiIiIiJyOhVJEREREREREROR0LJQiIiIiIiIiIiKnY6EUERERERERERE5HQuliIiIiIiIiIjI6VgoRURERERERERETsdCKSIiIiIiIiIicjoWShERERERERERkdOxUIqIiIiIiIiIiJyOhVJEREREREREROR0LJQiIiIiIiIiIiKnY6EUERERERERERE5HQuliIiIiIiIiIjI6VgoRURERERERERETsdCKSIiIiIiIiIicjoWShERERERERERkdOxUIqIiIiIiIiIiJyOhVJEREREREREROR0LJQiIiIiIiIiIiKnY6EUERERERERERE5nYerM0DZX3p6Oq5fv46CBQtCo9G4OjtE5GQigsTERAQFBcHNje8yMmJ8JCLGSOMYH4mI8ZGUYKEUWXT9+nWEhoa6OhtE5GJXrlxBSEiIq7ORrTA+EpEOY6Qhxkci0mF8JHNYKEUWFSxYEIA2mBQqVMjFuSEiZ0tISEBoaKg+FtBTjI9ExBhpHOMjETE+khIslCKLdFWuCxUqxIcKojyMzS+yYnwkIh3GSEOMj0Skw/hI5rBhJxEREREREREROR0LpYiIiIiIiIiIyOlYKEVERERERERERE7HQikiIiIiolxs586daN++PYKCgqDRaPDzzz9bXGf58uWoWbMmChQogMDAQPTr1w937951fGaJiChPYaEUEREREVEulpycjJo1a2LevHmK0u/evRt9+vTB66+/jlOnTmHlypU4ePAgBgwY4OCcEhFRXsPR94iIiIiIcrE2bdqgTZs2itPv378fYWFhGDFiBACgTJkyGDRoEGbOnOmoLBIRUR7FmlJERJTjTZ8+HfXq1UPBggVRvHhxdOzYEX///bfF9Xbs2IE6deogf/78KFu2LL766isn5JaIKHtr1KgRrl69io0bN0JEcPPmTaxatQrt2rUzuU5KSgoSEhIMJiIiIktYKEVERDnejh07MHToUOzfvx+bN29GamoqWrVqheTkZJPrxMbGom3btmjcuDGOHj2K999/HyNGjMDq1audmHMiouynUaNGWL58OXr06AFPT0+ULFkShQsXxhdffGFynenTp8PPz08/hYaGOjHHRESUU2lERFydCcreEhIS4Ofnh/j4eBQqVMjV2SEiJ8uJMeD27dsoXrw4duzYgSZNmhhNM3bsWKxbtw5nzpzRzxs8eDCOHTuGffv2KdpPTjw3RKSunBYHNBoN1q5di44dO5pMc/r0abRs2RJvv/02Wrdujbi4OIwZMwb16tXD4sWLja6TkpKClJQU/d8JCQkIDQ3NMeeFiNSX0+IjuQb7lCIiolwnPj4eAODv728yzb59+9CqVSuDea1bt8bixYvx5MkT5MuXz6F5JCLKrqZPn47nn38eY8aMAQDUqFEDPj4+aNy4MaZNm4bAwMAs63h5ecHLy8vZWSUiohyOhVJERJSriAhGjRqFF154AdWqVTOZ7saNGyhRooTBvBIlSiA1NRV37twx+qXLWE0AIqLc5sGDB/DwMPya4O7uDkAbY4mIiNTCPqWIiChXGTZsGI4fP47o6GiLaTUajcHfui9bmefrsM8UIsqJkpKSEBMTg5iYGADaPvViYmJw+fJlAMC4cePQp08fffr27dtjzZo1WLBgAS5evIg9e/ZgxIgRqF+/PoKCglxxCERElEuxUIqIiHKN4cOHY926ddi2bRtCQkLMpi1ZsiRu3LhhMO/WrVvw8PBA0aJFja4zbtw4xMfH66crV66olnciIkc5dOgQateujdq1awMARo0ahdq1a2PixIkAgLi4OH0BFQD07dsXs2fPxrx581CtWjV069YNlSpVwpo1a1ySfyIiyr3YfI+IiHI8EcHw4cOxdu1abN++HWXKlLG4znPPPYdff/3VYN7vv/+OunXrmuxPin2mEFFO1KxZM7PN7pYsWZJl3vDhwzF8+HAH5oqIiIg1pYiIKBcYOnQoli1bhqioKBQsWBA3btzAjRs38PDhQ32azM1TBg8ejH/++QejRo3CmTNn8O2332Lx4sUYPXq0Kw6BiIiIiCjPYaEUERHleAsWLEB8fDyaNWuGwMBA/bRixQp9mszNU8qUKYONGzdi+/btqFWrFqZOnYrPP/8cXbp0ccUhEBERERHlOWy+R0REOZ6S0aCMNU9p2rQpjhw54oAcERERERGRJawpRURERERERERETseaUqSatDRg1y4gLg4IDAQaNwbc3V2dKyIiIiIiIiLKjlgoRapYswZ46y3g6tWn80JCgLlzgc6dXZcvIqK8wtYXA3yhQERERESuwuZ7ZLc1a4CuXQ0LpADg2jXt/DVrXJMvIqK8Ys0aICwMaN4c6N1b+zMszHL8tWa9tDRg+3YgOlr7My1N7aMgIiIioryGhVJkl7Q0bQ0pY30M6+aNHMkvL0REjmLriwFr1rO10IuIiIiIyBwWSpFddu3K+oUmIxHgyhVtOiKivMwRNY1sfTFgzXqsDUtEREREjsJCKbJLXJy66YiIciNH1TSy9cWA0vW2b2dtWCIiR2LTaCLK61goRXYJDFQ3HRFRbuPImka2vhhQut727awNS0TkKGwaTUTEQimyU+PG2lH2NBrjyzUaIDRUm46IKK9xdL97tr4YUPtFAWvDEhFZh02jiYi0WChFdnF3B+bO1f6euWBK9/ecORxe3NESExPx7rvvolWrVggICIBGo8GkSZOMpk1KSsLIkSMRFBSE/Pnzo1atWvjxxx/t2qYxR48eRceOHREUFIQCBQqgcuXKmDJlCh48eGDXfpRulyg7cHS/e7a+GFC6XrNmyvKRnWvDOiI+Wps2o61bt6J///6oXLkyfHx8EBwcjA4dOuDw4cNZ0sbExKBdu3YoVaoUvL294e/vj+eeew7Lli2zKR1RduXoJmzOaCJnzT6y20BBf/75J1q3bo2CBQvC19cXzZs3x549ewzSWBO77NmPjpLnvb59+0Kj0Zic9u/fb9sJISKnYqEU2a1zZ2DVKiA42HB+SIh2fufOrslXRrm9vf7du3excOFCpKSkoGPHjmbTdu7cGUuXLkVkZCQ2bdqEevXqoVevXoiKirJ5m5mdPn0ajRo1wqVLlzBnzhysX78ePXv2xJQpU9CrVy+b92PNdomyA0f3u2friwGl6zVrpk5tWFfGYEfER2vTZrRgwQJcunQJb731FjZu3Ii5c+fi1q1baNiwIbZu3WqQ9v79+wgNDcVHH32EjRs34vvvv0dYWBhee+01TJs2zep0RNmRo5uwOaOJnLX7yE4DBR08eBBNmjTBw4cP8cMPP+CHH37Ao0eP0KJFC+zbt0+fzprYZc9+AOXPex988AH27duXZSpWrBiCg4NRr1499U4UETmOEFkQHx8vACQ+Pt5sutRUkW3bRKKitD9TU9XPiy37WL1aJCRERPsRr51CQrTzc4v09HRJT08XEZHbt28LAImMjMySbsOGDQJAoqKiDOaHh4dLUFCQpGY4oUq3acz48eMFgJw/f95g/htvvCEA5N69ezbtx5rtknqUxoC8yNK52bbNMPaYmrZtsy8fxuJcaKjlOKdkvdWrRTQa7ZQxnW6eLftwZgx2RHy0Jm1mN2/ezDIvMTFRSpQoIS1atFB0TA0aNJDQ0FDV0pF9GCONU3JedPElc0xUGl8scfT2bd1HVJSyz4ZMIcYhWrduLSVKlJDk5GT9vISEBClWrJg0atRIP8/e2KV0PyL2Pe9t375dAMiECRMs5okcj/GRlGBNKVKNu7v2rXqvXtqfajfZs+VNl9rt9efNm2e2mnCBAgXw+PFjaw/Nbrr9W7J27Vr4+vqiW7duBvP79euH69ev48CBA1Zv05h8+fIBAPz8/AzmFy5cGG5ubvD09LRpP9Zs96+//sJrr72GsLAweHl5oUSJEmjVqhX+/vtvm46JyBbO6nevc2fg0iVg2zYgKkr7MzbWck1VJesprQ1rKj526aLB1asaAAUAaOOjM/tMcUR8tCZtZsWLF88yz9fXF1WrVsWVK1cs5hMAihUrBg8PD5vTMT5SduDoJmzOaCJnzT4yxsjevTUAMk9PY6SOM5pG79mzB82aNUOBAgX08woWLIgmTZpg7969iPuvKq+9sUvpfgDrnvcyW7x4MTQaDfr3759lGWMfUfbEQinKEWwpXHLEw0j79u31VYPnz58PAJg9e7Z+3v79+w0+KJU0WRERpKamKprsdfLkSVSpUiXLl5QaNWrol6shIiIChQsXxpAhQ3Dx4kUkJiZi/fr1+PrrrzF06FD4+Pg4dLvnzp1DvXr1EB8fj9mzZ2Pz5s2YO3cuAgMDbd43kS2c2e+erS8GlKynpPCqbdv2+PLLfZg8eR9GjtTGRz+/2QD2/TftB6CNj0pjcHaNj2rH0vj4eBw5cgTPPPOM0eXp6elITU3F7du3MX/+fPzvf//D2LFjbUrH+EjZhaObsKm1fXPPctbsI+Mz5Lx58/9LYTxGKn1hoUaMfPz4Mby8vLLM1807ceKEyXUtxS5b92Prc2R8fDxWrVqFFi1aoEyZMgbLGPuIsjEX19SiHMDV1S5TU7M2/chcPTo0NGtTPluazVjTPPDLL78UAHL58uUsy27duiXPPttWNJoCAlQQ4HeTTVa2bdsmABRNsbGxFs+XueYpFSpUkNatW2eZf/36dQEgH330kdXbNOXMmTNSuXJlg/yPGDFC34zG1v0o2W5kZKQUKFBA0tLSFOeXTHN1DMjOlJ4bW5vX5RRZj+/L/+7Py0bi7i0B2gqgjY+ffPK7ye1m1/hoayw15dVXXxUPDw85dOiQ0eWDBg3SH6enp6fMnz/f5nSMj+pjjDTO0nlxdBM2NbZvqfmxrfvQPUMCl400/dPGSC+vAlKhQgX5/XfHxshatWpJxYoVDWLCkydPpGzZsgJkbaackaXYZc9+bHmOXLBggQCQ6OjoLMsY+1yD8ZGUsFz3m8jFrHkLlXGkKGs7GF6zRluzKuO+QkK0tRyMNYGJiYmBv78/QkNDsyzr0GEojhwpCeA2gD8AdAdwHteuFUWXLsDkyUCFCtpq2bVq1cHBgwcV5TUoKEjZQZlhrhmLrc31Mrt06RLat2+PEiVKYNWqVQgICMCBAwcwbdo0JCUlYfHixQ7dbrFixfDgwQP069cPb7zxBho2bAh3DgFJLtS5M9ChgzZOxcVp7/3GjXPHyKS6mqyGtVJjAPgDyBofgaEAnsbHyMju6NfvPIoWLZolZZ062Tc+qhVLP/jgAyxfvhxffPEF6tSpYzTN+++/jwEDBuDWrVv49ddfMWzYMCQnJ2P06NFWp2N8pOxCadM0W5uw2bt947HtaS39Vaus20da2tPPgI0btc+QixaFZnn29PYeiueeK4lff72NP/74A927d8f5846LkcOHD8frr7+OYcOGYfz48UhPT8fkyZPxzz//AADc3Iw3rFESu2zdj63PkYsXL0bRokXRqVOnLMsY+4iyMVeXilH25+oSblvfQllTU8qWTirr1asnL774Ypb59+8nCpAvUw2BpgIsNrr/4OB0+emnJ/LkieVJCXM1ARo2bCj16tXLMv/kyZMCQL7++murt2lMjx49pHjx4pKUlGQw/9tvvxUAsn37dpv2o3S7T548kRkzZujfsAUEBMiIESP4lsZGro4B2VlePzema7LWE+BFI/OzxsdSpZrKmDGLjdZMTU9PVxQbnR0fbY2lmU2aNEkAyIcffqgovc7gwYPFw8NDbt26ZXU6xkf15fU4YIql86KLH8aev3TPYMZqwitlz/aV1tJPSVG2j5UrM2+vnnh5vSirVxvW0t+4MVHy5ctnUAu/adOmsnjxYqPHqFaMnDFjhvj6+uprJD333HMyduxYASC7du3Kkt7W2KV0P7Y8Rx47dkwAyFtvvWV034x9rsH4SEqwTynK9mx906W0g+FGjazve0pEcPLkSdSqVQuAYX8DU6eeA+ALwxoC1QGcMpqPa9d2oHv3fMiXz/J06dIlS6fBrOrVq+PMmTNZ+hbQteOvVq2aXdvXiYmJQdWqVbO00dcNzWtr31VKt+vh4YGxY8fizJkzuHLlCgYPHozPP/8cH374oU37JSLjjNdkFQAnAdQyskbW+Hj5cnV88skphIUBK1ca9t2ydesORbHR2fFRjVg6efJkTJo0CZMmTcL7779vVV7r16+P1NRUXLx40ep0jI+UXTi6zz17tq+0lv7evZb30bMn0L17xu1pY2RKSi107Qr88svTfv1KljwHX19fg1r41atXx6lTxp8hd+xQJ0aOHTsWd+7cwYkTJ3Dp0iXs3bsX//77L3x8fLLUgrIndindjy3PkbraUwMGDDC6b8Y+ouyLhVI5yPTp01GvXj0ULFgQxYsXR8eOHRWNFrFjxw7UqVMH+fPnR9myZfHVV185IbfqsXX0KqUPI3v3Wt8R5r179/Dw4UOUKVMmy6iAn36aBKBQpq0UApBkYg91ABxEiRIHsX//QRw8aHqyt3lKp06dkJSUhNWrVxvMX7p0KYKCgtCgQQO7tq8TFBSEU6dOISnJ8Jj37dsHAAgJCXHadkNCQjB+/Hh4e3ur0hkyET1lvJn0PQAPAZQxssx0fLx6VfvFLeMIq3361MHHH2vj38cfH0Tx4gcBPJ2KF9fO37//IM6dCzI7qIQl1sRHe2Pp1KlTMWnSJEyYMAGRkZFW53Xbtm1wc3ND2bJl7UrH+EiupnR0T2dv35ouIMztY8UKbSG74YtPwxiZ8cVnUlISChUyjJGFChVCUlKS0Q7Xdc33lEyWniG9vLxQrVo1lC5dGpcvX8aKFSswcOBAeHt769PYG7uU7sfa572UlBQsW7YM9evXV/RSgLGPKHthn1I5yI4dOzB06FDUq1cPqampGD9+PFq1aoXTp0+bHDUiNjYWbdu2xcCBA7Fs2TLs2bMHb775JgICAtClSxcnH4FtdIVLXbtqC5MyfrBbetOle1Aw1lfUnDna5dHRyvKR8QHFy8sL+fLlw/ffb8bBgzUA1ATg999SXwAJmdZO+G++MQUB1MXNm8DDh4b9Yllj06ZNSE5ORmJiIgDg9OnTWLVqFQCgbdu2KFCgANq0aYPw8HAMGTIECQkJKF++PKKjo/Hbb79h2bJlWdrWK9kmoL02W7RogYkTJ2LixIkYOXIkOnbsiPDwcLz99tsoVqwY9u/fj+nTp6Nq1apo06aNTftRst1hw4YhPj4e4eHhKFWqFG7fvo158+bB09MTgwYNsu3kEpFRxmuyegHIB2AzAG18DAjww+3bgLXxMS6uIN57ry5GjwZmzcpao/X2bWDsWKBoUeDu3afzM/cHqHZ8tCZt5vj46aefYuLEiXjppZfQrl077N+/3+CYGjZsqP/9jTfeQKFChVC/fn2UKFECd+7cwcqVK7FixQqMGTMGAQEBVqVjfKTsyNF97tmyfWtr6Zvah/EaV09jpEgNXLlSE7t2+aFZM8DX1xcJCdoYqeuD6tChBCQm+iIszFi/pwXRuXNdZZk14eTJk1i9ejXq1q0LLy8vHDt2DDNmzECFChUwdepUfTprYlfmuGfNfgBlz3sZ/fzzz7h3757JWlKMfUTZnKvbD5Ltbt26JQBkx44dJtO8++67UrlyZYN5gwYNkoYNGyreT3ZpC2zP6FXmRtWzpu+pjNsZPHi2uLkF/dcu/m8jfaZcyTCvmck+pcz1i2WN0qVL69voZ54yjriSmJgoI0aMkJIlS4qnp6fUqFHD6Cgl1mxTN/pLxn5atm7dKq1atZKSJUuKt7e3VKxYUd555x25c+eOzftRst0vvvhCGjduLMWLFxcvLy8pU6aM9O/fXy5cuGDzuc3rsksMyI7y+rkx3WfLbAG08bFkyb8lJUUbO99917b46O6uLE5n7MclY3+AjoiPStNmjo9NmzY1mZfMj2XffvutNG7cWIoVKyYeHh5SuHBhadq0qfzwww82pWN8dIy8HgdMycnnRa3+rkz3i/o0RgJ/65//EhO1fUotXHglwzOv8Rhprt9Ta/z999/SpEkT8ff3F09PTylfvrxMmDAhS39O1sQuY8+FSvejY81zZHh4uPj4+EhCQoLRbTH2uU5OjgPkPBoRYz3pUE5w/vx5VKhQASdOnDBZVbVJkyaoXbs25urasQFYu3YtunfvjgcPHiBfvnxZ1klJSUFKSor+74SEBISGhiI+Pj5LlWJnyzhyiVpv0tLStM3vrl0z3q+URqN9GzV7NvD22+ab+j3VDdqaU18A2ALgNWj7Uilmdq1t22yvKUXkKAkJCfDz88sWMSC74bl5OkIVYLwma8YmMtHRQO/etsVHa+lid2xs7hjlkLIvxgHjcvp5sSa2mbJ9u7YpsiUZn/8aNeqGffuUxciMcQ7InSO8Us6W0+MAOQf7lMqhRASjRo3CCy+8YLbt9I0bN1CiRAmDeSVKlEBqairu3LljdJ3p06fDz89PP2XsbNHV3N2fdgbZrJk6H7ZK+p7K2kmlJfMBXAdQFMDbAFbA3BcuU/1iERFld9b02aJt6mJdfLSVrj/AL76AXX1NEVHepEZ/V9b2i5qWBly6pDxG6uLchx8a9m/avLn27zVrlBwpEZFrsU+pHGrYsGE4fvw4du/ebTGtJtMnoa5yXOb5OuPGjcOoUaP0f+tqSuVm5vqe+vRTYNQo47WoTAsAsBEA8NlnQIkSwLlzwKRJ2qWm+sUCtF+c+JaLiHISpX22aL+gBeDatY1WxlTbvf32098z9zVFRGSOvf1dWdsvqnY/T58hlTLW5/i1a9r9qtFhPBGRI7FQKgcaPnw41q1bh507d1ocxaxkyZK4ceOGwbxbt27Bw8MDRYsWNbqOl5cXvLy8VMtvTmFdJ5WW6apUDx/+9GGjWjXTna4DMNGJJR8miCj709VktZTG1Bc0S+ulp1v7ciArfkkjImspiW3mKBl0R0fpqH9KiGjj7MiR2udbvuQkouyKzfdyEBHBsGHDsGbNGmzduhVlyhgbbtvQc889h82bNxvM+/3331G3bl2j/UnldcaaB9rygGBqVMDOnYFLl7R9B0RFaX/q+gHo2jVr4ZfuCxSrXxNRbmGqSYwxGo120lXeNdUERildF8EDBwJbtrA5HxE5h6nnv8yF40pH/VNK17xv1y51t0tEpCYWSuUgQ4cOxbJlyxAVFYWCBQvixo0buHHjBh4+fKhPM27cOPTp00f/9+DBg/HPP/9g1KhROHPmDL799lssXrwYo0ePdsUh5Ei2PCCY628gc8EXoH17ZqwGgG7eyJH88kREuYexL2grV2pjZ0a6WDpzpvGCLF2FX2sLq+7dA1q2ZJ8rROQ8SvpFtdQHVUbWxD01a2AREamNo+/lIKb6gPruu+/Qt29fAEDfvn1x6dIlbN++Xb98x44dePvtt3Hq1CkEBQVh7NixGDx4sOL95vVRE5SMzhccDCxZAty6ZX1/A7aMzELkTHk9BpjDc6MuSyOsGlv+yy9Zm8UoZc0oWkSmMA4Yx/NiG1Oj/mUWGgoMGGC8P6nM/vjjae1/XewEOFofOR7jACnBQimyiMFEnWGBTdEOkW45XVSU9u0akbMxBpjGc5M9ZCysunnTsHNzSzIOqc4vZGQLxgHjeF5st2aN8T6oBg4EKlQwLFiy9OLU3x/w9jbclq6W6d27httnP6akNsYBUoIdnRMpYE0nldZS2jxQ7X4GiIhyi4wdEaelaUdNNfUlLbOMfa6wNioRZQfWjPpnbnQ/EcOCJx1j8zgQBBG5CvuUIlJIaSeV1rLUf4BGo62irXsjRkREpulG+APY5woR5VxK+qACTA8eERz8tEaUEuzHlIhchTWliKxg77DAprZp7i0XoK2NBWj7n2LbfyIi80zVbjWHtVGJKKcyVrMqLU07oIM1dDVHJ00CWrTgsyYROQdrShFlA6beculGngK0fQY0b67tf6p5c44aRURkjq526x9/aPtUMYW1UYkoN8hcs+rWLdu3NW0anzWJyHlYKEWUTZhqHghoa1Flftuva/vPhwUiIuPc3bVv+xct0hY+ZW7Ol7E2KmsDEFFuokbtTz5rEpEzsPkeUTaSuXlgWpq2+Ymxznp18wYPBh4+1NayYjVrIqKslA5WkXEUPzaTJqKcTNdnqdJBH4wR0RbejxypbR7IeEhEjsBCKaJsbNcuy/2h3L4N/N//aX8PCQFmzwYCAviliogoI0ujWZkagp1DpBNRTmSuz1JrcIRSInI0FkoRZWPWjgZ19SrQvbvhPH6pIiLSMjVYxZo12i9umb+0cYh0IsrJTNUS1Y3Kd/eu8m1xhFIichT2KUWUjbE/ACIix1LSTJpDpBNRTmWsz9KbN7XTtm3AhAnKtsMRSonIUVhTiigbY38ARESOZamZNJuuEFFOZ6qWaLNm2mfNJUtMP2tqNNpn0caN2e8eETkGa0oRZWO6/gCArKNGWSPjlyoiInpKaZMUNl0hotzI3LNmxhFKf/kFCAsDmjcHevfW/gwLY018IrIfC6WIsjldfwDBwfZvi1+qiIgMKW2SwqYrRJRbmXrWDAnRzge0XUFkrlXKLiKISA0slCLKATL2B7BsmXZ0PVtqTvFLFRGRIV0zaVMxVaMBQkO16YiIcitjfU/Fxmq7fmC/e0TkSOxTiiiHyNgfgLe3dUP8ZuwPgIiInjI3bHrGpisAsH07+1IhotzLWN9T27ez3z0icizWlCLKgaxp0pfxSxW/QBERZaWk6Qr7UiGivEhp1w9btgDR0dpCLNaaIiJrsFCKKIcyVs165Urtl6iMdF+qOnfW/p2Wpn1g4IMDEdFTppquAOxLhYjyLqVdP0ybxkJ7IrINC6WIcjBdNetevbQ/u3Y1/qVKVyC1Zg3f9lPutXPnTrRv3x5BQUHQaDT4+eefLa6zfPly1KxZEwUKFEBgYCD69euHu3fvOj6zlC1ljqkA+1IhorzNUr97xrDQnoiswUIpolwm85cqXZO9NWv4tp9yt+TkZNSsWRPz5s1TlH737t3o06cPXn/9dZw6dQorV67EwYMHMWDAAAfnlHKKXbuU96VCRJQb6frdA5QXTLHQnoiswUIpojwgLY1v+yn3a9OmDaZNm4bOuqqBFuzfvx9hYWEYMWIEypQpgxdeeAGDBg3CoUOHHJxTyimU9qWiNB0RUU5kTV+mOiy0JyKlWChFlAcofdv/xRfsa4ryjkaNGuHq1avYuHEjRAQ3b97EqlWr0K5dO1dnjbIJpX2pKE1HRJRTZe53b8IEZeux0J6ILGGhFFEeoPSB4O232dcU5R2NGjXC8uXL0aNHD3h6eqJkyZIoXLgwvvjiC5PrpKSkICEhwWCi3MtSXyoaDRAaqk1HRJTbZewiokULZeucPs2XnURkHguliHKIxMREvPvuu2jVqhUCAgKg0WgwadIkRes+fYv/J4DWAAoC8AXQHMAeI2scxdWrHdGlSxC8vAqgcuXKmDJlCh48eJA15dGj6NixI4KCglCggPm0RNnJ6dOnMWLECEycOBGHDx/Gb7/9htjYWAwePNjkOtOnT4efn59+Cg0NdWKOyZStW7eif//+qFy5Mnx8fBAcHIwOHTrg8OHDireRlJSEkSNHIigoCPnz50etWrWwcuWPRvpSSQIwEkAQRPLD3V2bTuk2f/zReFoiIkdxRIwcObIW/P1/NFJo/zRGAvkxbVotNG/+o9GXnYyRRASwUIoox7h79y4WLlyIlJQUdOzY0ap1GzcGihc/CKAJgIcAfvhvegSgBYB9GVKfBtAIwCUAc+Dntx7du/fElClT0KtXL4Ptnj59Go0aNcKlS5cwZ84crF+/Hj17Gk9LlN1Mnz4dzz//PMaMGYMaNWqgdevWmD9/Pr799lvEmaheOG7cOMTHx+unK1euODnXZMyCBQtw6dIlvPXWW9i4cSPmzp2LW7duoWHDhti6dauibXTu3BlLly5FZGQkNm3ahHr16qFXr1549CgqU18qnQEsRZEikZg4cROeeUabbsKEqCw1AUxtMyoqSs3DJyIyy1Ex8t69XhCJylQwpY2RQCSATQDqAeiFq1ejsgyswxhJRAAAIbIgPj5eAEh8fLyrs5KnpaenS3p6uoiI3L59WwBIZGSk4vVr1WotQAkBkkXbi5QIkCBAMQEaZZg3XgAIcF4/b9s2kTfeeEMAyL179/TbHD9em/b8+fMG+zKWlnKunBgDAMjatWvNpuncubN0797dYN7evXsFgFy7dk3RfnLiucmNbt68mWVeYmKilChRQlq0aGFx/Q0bNggAiYqKMpgfHh4uQUFBkpqaKqmpItOna9NNmBAlK1eKhITo4ma4AEESHJwqq1cr3yblDowDxvG8ZB+OjJH+/trYp42FG/57hozK8Fz5NEYCqRIaKpKayhiZVzAOkBKsKUVkJRHBV199herVqyN//vwoX748Vq1ahfT0dFSrVg0fffSRQ/ar0WigUToWrxHnz+/B8883Q0hIgQxzC0Jbe2ovAF3NkHz//fTTp4qLAwoXLgw3Nzd4enrq5+fLp03r5/c0LWA8LZGjJSUlISYmBjExMQCA2NhYxMTE4PLlywC0tZz69OmjT9++fXusWbMGCxYswMWLF7Fnzx6MGDEC9evXR1BQkCsOIcdzVXwsXrx4lnm+vr6oWrWqotpsa9euha+vL7p162Ywv1+/frh+/ToOHDgAd3fgwgVtuho1uqF794wDSPQDcB3Xrh3Q1wRQsk0iyltyY4y8d+86oqMPYNs2oFattdB2D9Et0xa0MRI4oB+RjzGSiHRYKEVkBRFBjx49MGrUKPTp0wfr169HmTJl0LdvXyxZsgT//vsvRo4caXS91NRURZOjPH78GOXKeRmMnPLZZwDg9V+KE//9jABQGMAQABcBJOLSpfX4+uuvMXToUPj4+Oi3GRERgcKFC2PIkCG4ePEiEhMTsX698bREjnbo0CHUrl0btWvXBgCMGjUKtWvXxsSJEwEAcXFx+gIqAOjbty9mz56NefPmoVq1aujWrRsqVaqENezh3ybZLT7Gx8fjyJEjeOaZZyymPXnyJKpUqQIPDw+D+TVq1NAv1/2sXLkKRo3ygIhBSt2WAAAjRwInTijbJhHlDbk5Rp45cxLNmgFJSScBVAHgkWkLhjEyLk553CWi3C9zxCAiM5YsWYKVK1di+fLl6N27NwDAy8sLTZo0wejRozFz5kwUKFAgy3o7duxA8+bNFe0jNjYWYWFhamYbAFC1alXs378fGk06mjXTlkenpKRi9OgD//WDcve/lGHQ9jHVCUA5AMD77wMjRozAnDlzDLYZFhaGffv2oVOnTihXrpx+vrG0RI7WrFkziGFJgYElS5ZkmTd8+HAMHz7cgbnKO7JbfBw6dCiSk5Mxfvx4i2nv3r2LsmXLZpnv7++vX677Wbhw2Qw1pPQpdVuCCHDlCiByF888Y3mbRJQ35IUY+ejRXQBZ02WMkYB2AB6l2ySi3I+FUkRW0NWo0D1MAECRIkUAACVLlkS/fv2MrlenTh0cPHhQ0T4c1Wxo+PDheP311zFs2DCMHz8e6enpmDx5MkT++S+FruLkJQDtAZQAsAqTJgUgLu4AFi2ahnPnkvDrr4vh7v5fykuX0L59e5QoUQKrVq1CQEAADhw4gGnTpiEpKQmLFy92yLEQUfaTneLjBx98gOXLl+OLL75AnTp1FK1jrnl0xmWPH5trRv10WWqq8m0SOdrOnTvxySef4PDhw4iLi8PatWstDpqSkpKCKVOmYNmyZbhx4wZCQkIwfvx49O/f3zmZzmXyQoz09ga8vDR4/Bgw/o5Ig9BQ7QA8SrdJRLkfC6WIFPr3339x9OhRvPfeewbz0/4bbunDDz+Eu660JhNfX1/UqlVL0X4yV2NWS//+/XH79m1MmzYNCxYsAAA899xzGDNmND7++GMEBATj9m0AeA9AAoKDY9C7tw+++Qa4erUJgGLYtKk/AgP74KuvmqJzZ+C9995DQkICYmJi9E31mjRpgmLFiqF///7o06cPmjZt6pDjIaLsIzvFx8mTJ2PatGn48MMPMWzYMEXbLVq0qNG38vfu3QPw9M190aJFcf++sbf39/776a+f4++vbJtEzpCcnIyaNWuiX79+6NKli6J1unfvjps3b2Lx4sUoX748bt265dBuBnKzvBQjRe7iwgVAo8lYMPU0Rs6ZA7i7K98mEeV+7FOKSKHz589DRFCmTBmD+QsXLgQA1KtXz+S6O3bsQL58+RRNly5dctgxjB07Fnfu3MGJEydw6dIl7N27F//++y98fHxw8WIdbNsGBAbGoFatqpgzxwezZmXsyFd7fLdvn9R35BsTE4OqVatm6TtKdy7YHwBR3pBd4uPkyZMxadIkTJo0Ce+//77i/FevXh1nzpzJ8oX7xAltX3vVqlXTp7t69QyCg1MzDYGu65NPmy4gAChRojpOnjyDlBTz2yRyhjZt2mDatGno3LmzovS//fYbduzYgY0bN6Jly5YICwtD/fr10ahRIwfnNHfKSzHyxo0zWLEiFcHBBikBAFOnVoO/PxAdDRQtqmybRJT7saYUkUK6N1i3tdWJAACHDx/WP1CY68smOzTf0/Hy8tJ/0F++fBkrVqzAwIED4evrjWbNgMqVg3Dy5Em89VYSRHwzrLnvv58hALQd+ZYrF4RTp04iKSkJvr5P0+7bp00bEhLi0GMhouwhO8THqVOnYtKkSZgwYQIiIyMVbU+nU6dOWLRoEVavXo0ePXro5y9duhRBQUFo0KCBQbo33liNzz7rkaEmwFIAQQC06W7fBrZt6wRgEYKCVmPRoh7QlQVk3iZRdrRu3TrUrVsXM2fOxA8//AAfHx+88sormDp1Kry9vY2uk5KSgpSUFP3fCQkJzsputpfXYmR6+mpcutQDu3ZpOzWfM2cpzp0LwldfNcAHH+i3CmARxo5djU8/Nb1NIsoDhMiC+Ph4ASDx8fGuzopLPXr0SAICAqRYsWKyfPlyiY6OlsDAQOnZs6cAkAkTJsjly5cdmoeNGzfKypUr5dtvvxUA0q1bN1m5cqWsXLlSkpOT9em2b98u7u7uMnnyZP28EydOyKRJk2T9+vWyefNmmTVrlhQrVkzq1q0riYmJ+nS//PKLaDQaARoKsEKALQJ8KICvAFUFSBHt1zCRadO0aRs2bCgrVqyQLVu2yIcffii+vr5StWpVSUlJcej5IOdgDDCN50bL1fFx1qxZAkBeeukl2bdvX5YpI2PxUUQkPDxcihQpIgsXLpStW7fKwIEDBYAsW7bMaLrBgxdKsWJbBdCmA5bpY+PTKVyAIgIslEmTTG+TcracFgcAyNq1a82mad26tXh5eUm7du3kwIEDsmHDBildurT069fP5DqRkZH/3QuGU045L46UF2Nk5nTmYuTgwea3STlXTouP5BoslCKLGEye2r17t9SpU0c8PT2lSJEiMm7cOElPT5c33nhD8uXLJwsWLHDo/kuXLm30gQ+AxMbG6tNt27ZNAEhkZKR+3t9//y1NmjQRf39/8fT0lPLly8uECRMkKSkpy37Gj98qQCsBSgrgLUBFAd4R4I7Bw0RUlMjWrVulVatWUrJkSfH29paKFSvKO++8I3fu3HHouSDnYQwwjefmKVfGx6ZNm5qMjZnfvxmLjyIiiYmJMmLECClZsqR4enpKjRo1JDo6Osu+MqcrW7aGDB0aLQEBmb9siQCJAoz4L5aa3iblbDktDigplAoPD5f8+fPL/fv39fNWr14tGo1GHjx4YHSdR48eSXx8vH66cuVKjjovjpZXY2SNGjXE3z/aSHx8GiPd3Mxvk3KunBYfyTU0ImbqixJBW/3az88P8fHxKFSokKuzQ06wfTugZPThCROAFi20o6iY6J+TcgHGANN4bghQHjO3bQOaNXN0bsjZcloc0Gg0Fkffi4iIwJ49e3D+/Hn9vDNnzqBq1ao4e/YsKlSoYHE/Oe28kGMwPuZtjAOkBDs6J6IsGjcGQkIAS6PxTpumfdAIC9N2fE5ElBfFxambjsjVnn/+eVy/fh1JSUn6eWfPnoWbmxv7iySrMD4SkSUslCKiLNzdgblztb9bKpgCgGvXoB+Rj4gorwkMVDcdkdqSkpIQExODmJgYAEBsbCxiYmJw+fJlAMC4cePQp08fffrevXujaNGi6NevH06fPo2dO3dizJgx6N+/v8mOzomMYXwkIktYKEVERnXuDKxahUxD+hqnawQ8ciSQlubQbBERZTuWapdqNEBoqDYdkSscOnQItWvXRu3atQEAo0aNQu3atTFx4kQAQFxcnL6ACgB8fX2xefNm3L9/H3Xr1sWrr76K9u3b4/PPP3dJ/innYnwkIkvYpxRZxLbAeVtaGrBrF7Bli7a5niXsEyD3YQwwjeeGdNas0dYYBZ4W1ANPv4itWqUt7Kfch3HAOJ4X0mF8zLsYB0gJ1pQiIrPc3bWFTFWrKkvPPgGIKC8yVbs0JIRfuIgob2N8JCJzPFydASLKGdgnABGReZ07Ax06aGuXxsVp4yFHJyUiYnwkItNYUyoH2blzJ9q3b4+goCBoNBr8/PPPFtdZvnw5atasiQIFCiAwMBD9+vXD3bt3HZ9ZynXYJwARkWW62qW9eml/8gsXEZEW4yMRGcNCqRwkOTkZNWvWxLx58xSl3717N/r06YPXX38dp06dwsqVK3Hw4EEMGDDAwTml3MjciHy6v+fM4QMGERERERERKcPmezlImzZt0KZNG8Xp9+/fj7CwMIwYMQIAUKZMGQwaNAgzZ850VBYpl9P1CfDWW8DVq0/nh4RoC6TYJwARkXm6wSPYfIWIyBDjI1HexJpSuVijRo1w9epVbNy4ESKCmzdvYtWqVWjXrp3Z9VJSUpCQkGAwEel07gxcuqQdZS8qSvszNpYFUkRElqxZA4SFAc2bA717a3+GhWnnExHlZYyPRHkXC6VysUaNGmH58uXo0aMHPD09UbJkSRQuXBhffPGF2fWmT58OPz8//RQaGuqkHFNOwT4BiIisoxsSPWMtUwC4dk07n1+8iCivYnwkyttYKJWLnT59GiNGjMDEiRNx+PBh/Pbbb4iNjcXgwYPNrjdu3DjEx8frpytXrjgpx0RERLlPWpq22bNI1mW6eSNHatMREeUljI9ExD6lcrHp06fj+eefx5gxYwAANWrUgI+PDxo3boxp06YhMDDQ6HpeXl7w8vJyZlaJiIhyrV27stYAyEgEuHJFm65ZM6dli4jI5RgfiYg1pXKxBw8ewM3N8F/s/l87KzH2OoKIiIhUFxenbjoiotyC8ZGIWCiVgyQlJSEmJgYxMTEAgNjYWMTExODy5csAtM3u+vTpo0/fvn17rFmzBgsWLMDFixexZ88ejBgxAvXr10dQUJArDoGIiCjPMVEx2eZ0RES5BeMjEbH5Xg5y6NAhNG/eXP/3qFGjAAARERFYsmQJ4uLi9AVUANC3b18kJiZi3rx5eOedd1C4cGG8+OKL+Pjjj52edyIioryqcWMgJETbaa+xisoajXZ548bOzxsRkSsxPhKRRtiOiyxISEiAn58f4uPjUahQIVdnh4icjDHANJ4bUko3uhRg+MVLo9H+XLUK6NzZ+fki+zEOGMfzQkoxPuZejAOkBJvvEZGq0tKA7duB6GjtT46WQkSk/UK1ahUQHGw4PySEX7iIKG9jfCTK29h8j4hUs2aNdljfjKOohIQAc+fygYKIqHNnoEMH7ShScXHaPlIaNwb+G4OEiCjPshQf09IYO4lyKxZKEZEqdFWvMzcIvnZNO59vuoiItF+ijA1rzi9cRJTXmYqPfOlJlLux+R4R2S0tTfuwYKyHOt28kSPZlI+IyJg1a4CwMKB5c6B3b+3PsDDtfCKivEz30jNjgRTw9KUn4yRRzsdCKSKy265dWR8WMhIBrlzRpiMioqf4hYuIyDi+9CTKG1goRUR2i4tTNx0RUV7AL1xERKbxpSdR3sBCKSKyW2CguumIiPICfuEiIjKNLz2J8gYWShGR3Ro31nY4qdEYX67RAKGh2nRERKTFL1xERKbxpSdR3sBCKSKym7u7dgQUIGvBlO7vOXM4khQRUUb8wkVEZBpfehLlDSyUIiJVdO4MrFoFBAcbzg8J0c7nkL1ERIaUfOEKCdH2KRUdDWzfzv6liCjv4EtPoryBhVJEVkpKSoK7uztmzZrl6qxkER8fDzc3N3z22Wf6edevX4dGo8GiRYscvv/OnYFLl4Bt24CoKO3P2NinBVJpadovVZa+XCUmJuLdd99Fq1atEBAQAI1Gg0mTJlmVl6SkJIwcORJBQUHInz8/atWqhR9//NHmdNamJcqLGB+tY+kLlwjw8CHQsiXQuzfQvDlQqlQiOnZkfCTKiRgjrWfupeeKFYC/v+FzJZ8hiXIeD1dngCinOXz4MNLT09GgQQNXZyWLQ4cOQURQr149/TwfHx/s27cP1apVc0oe3N2BZs2yzl+zRjvKVMZOfUNCtF/IMteiunv3LhYuXIiaNWuiY8eO+Oabb6zOR+fOnXHw4EHMmDEDFStWRFRUFHr16oX09HT07t3b6nTWpiXKixgfraf7wpU5Pvr7A3fvaqeMrl+/i19+WYjg4Jpo0KAjNmxgfCTKKRgjbdO5M9Chg3bQh7g4bZPmO3eAt9/O+lz53nt3MX/+QoSGMkYS5RhCZEF8fLwAkPj4eFdnJVuYNWuWuLu7S3JysquzksWMGTPE3d1dkpKSXJ0VA6tXi2g0Itr3/k8njUY7rV5tmD49PV3S09NFROT27dsCQCIjIxXvb8OGDQJAoqKiDOaHh4dLUFCQpKamWpXO2rS5DWOAaTw3hhgfbZeaKrJtm0hUlMgff4iEhGSNmdop/b9JBNDGx+7dIxXvh/FRfYwDxvG8ZMUYqQ5Tz5WMkdkP4wApweZ7RFY6ePAgqlWrhr1796Jx48bw8fFB+fLl8eWXXxqk+/PPP9GjRw+EhYXB29sbxYsXR6dOnXDhwgWDdH/99Rdee+01hIWFwcvLCyVKlECrVq3w999/G6TbvXs3WrVqBT8/PxQpUgTt2rXDuXPnsuStSpUq8PHx0c9r1aoVmjRpov/7xRdfRPPmzbFjxw60bNkSvr6+KFmyJKZMmWL0eJXs15y0NG0NAJGsy3TzRo40bMqn0WigMdXJigJr166Fr68vunXrZjC/X79+uH79Og4cOGBVOmvTEuVVjI/WxceMdLVMe/XS/p7x7b8hzX/TUz/9pK2NqgTjI5HrMEbaHiN1zD1XajFGEuU0LJQistKhQ4dw584dvP/++xg2bBjWrFmDKlWqYNiwYfj555/16WJiYlCzZk3MnTsX//vf//DZZ5/h7Nmz6Jyhrdq5c+dQr149xMfHY/bs2di8eTPmzp2LwMBAg4eCSZMmoWnTpggNDUV0dDS++eYbXLlyBS1atEBSUpJB3jJWuwaAo0ePok6dOgb5unTpEt5++21ERERg3bp1aNKkCSIjI7Fjxw6DdZXuNyMRQWpqqn7avj0VV6+mAjA2aR8qrlzRVslWy8mTJ1GlShV4eBi2UK5Ro4Z+uTXprE1LlFcxPloXH01N2phpncyF+6YwPhK5DmOk/THy6XOldRgjibIxF9fUohyA1S6funfvngCQZ555Rh48eKCfn5ycLP7+/tKjRw+j66WlpcmTJ0/km2++EQDy77//iohIZGSkFChQQNLS0kzu89dffxUAMnPmTIP5Z8+eFQCybNkyEXnazG3+/Pn6NJcuXRIA8sMPP4iIyIULFwSA1KlTRx49eqRPd/Xq1SzrKt1vZtu2bRMACqdYfXXrTDWa9WxpvlehQgVp3bp1lvnXr18XAPLRRx9Zlc7atLkNY4BpPDdPMT46Lj6anm7/lzZSAG3zP0sYH9XHOGAcz4shxkjGSCVpcxvGAVKCHZ0TWeHQoUMAgKlTp8Lb21s/v0CBAqhQoQJu3rwJQPumZ/Xq1Zg/fz7++usv3LhxA/JfPWM3Nzf9usWKFcODBw/Qr18/vPHGG2jYsCHcM41rO3HiRJQrVw5vvfUWUlOfvhkqU6YMvL29cfHiRQDaatcAULduXX2aw4cPAwCeffZZAMCRI0cAAFOmTIGXl5c+3d3/etINCgqyer+Z1alTR58XbR6AwYONJgXwdH+nT2tHTmncWJ2hfc01/8u4TGk6a9MS5TWMj9bHR1PS0oAuXYJw/bq5JipZxcUpS8f4SOR8jJHqxMinz5VBZtMZwxhJlD2xUIrICocOHYKPjw9eeeWVLMtu3Lihb3f/xhtvYMmSJRg0aBBGjBiBgIAAeHl5YcCAAXj48KH+w3zw4MFITk7GkiVL8P333yMgIAC9evXC1KlTUahQIdy4cQNHjx4FAIMHgIwKFy6sz5unp6e+KjCgfYDw8fFB5cqV9X97eXmhZcuWBtvQPWjUrl1bfyxK95uZr68vatWqpf+7enVg6lTg2jVjqZ+GoGnTtJOpEfmsUbRoUf1DUkb37t0DAPj7+1uVztq0RHkR42PW/WaWOT6a8/nnHujaFdBolBdMBQZaTsP4SOQajJFZ95uZkhipe668ft3DqkJ7gDGSKLtioRSRFQ4dOoTixYtneRO1d+9e/PPPP2jXrh3+/vtvfPPNN5g5cybGjBmjT3Pnzh2cOnUK3bt318/z8PDA2LFjMXbsWFy9ehULFy7E1KlTkT9/fnz88ce4cuUKAOCzzz7DCy+8YDRP5cqV0+etRo0aBg8Ahw8fRq1ateDm5qb/u0aNGvD09MxyXMWKFUOpUqUAwKr9ZrZjxw40b97c6LKsYgGEGcy5dg3o2lU7RLqtBVPVq1dHdHQ0UlNTDdrvnzhxAgD0QxsrTWdtWqK8iPEx634zsyY+xsbGYtWqMLz1lrlOz58KDdXWNLWE8ZHINRgjs+43M2ufITWaMMUFU4yRRNkXC6WIrHDw4EHcunUL9+/f17/lSU1NxdixY1G5cmV06dIFW7duBQBUrVrVYF1dFeaMVaMzCgkJwfjx4zFr1ix9VWfdmxONRmNyvYx569Chg8G8I0eOoEePHvq/jx49iq5du2ZZ9/DhwwYdWVqz38xMVb3euhX49FPg1q2Mc7NWvdY9XAweDDx8CPj6WrV7AECnTp2waNEirF692uD4ly5diqCgIDRo0MCqdNamJcqLGB8tU9p8D9A2hQkLAzp00A4E8csvwJw5pmtOzZmjrOkz4yORazBGWmZNjLxwIQijRysrtAcYI4myMxZKESl0+/ZtXLlyBeXKlUPXrl0xevRoPHr0CHPnzsWJEyewe/dueHh4oGbNmihQoAA++OADaDQaPHz4EIsWLcL58+cBPG2vP2zYMMTHxyM8PBylSpXC7du3MW/ePHh6emLQoEEAtG+SmjdvjgkTJiApKQkNGjSAiCAuLg7btm1DREQEmjVrhri4OMTFxRmMmnL16lXcunVL/6Bw5coV3L59O8sDQmpqKo4dO4ZRo0bp5yndrzEFCxY0+hBSty7wzjvaL1dbtmib6pk/35vwf/+XDCARAPD776dRrdoqAEDbtm1RoEAB7NixAy1atMDEiRMxceJE/bpt2rRBeHg4hgwZgoSEBJQvXx7R0dH47bffsGzZMv1bSqXprE1LlNcwPtoXH81xdweaNdNOjRvjv5pTmwA8jY/PPXca6emrsGoV4yNRdsQYqX6MrFtXW7N+1y5tX1GBgcCdO8DbbzNGEuU4rulfnXISjpqgtWHDBgEg+/fvl4EDB0qhQoWkUKFC0rVrVzl79qxB2vXr10vlypXFy8tLqlatKnPnzpVp06aJm5ubJCYmiojIF198IY0bN5bixYuLl5eXlClTRvr37y8XLlww2FZ8fLyMGzdOKlasKPnz55ciRYpIzZo1Zfjw4foRWH755RcBIMeOHdOv9/PPPwsAOX78uMHfGdOIiBw7dkwAyJo1a6zer62ioiyNliIClDY54kpsbKyIPB2lxdjIfImJiTJixAgpWbKkeHp6So0aNSQ6OtrmdNamzU1ySgzYsWOHvPzyyxIYGCgAZO3atRbXefTokbz//vtSqlQp8fT0lLJly8rixYsV7zOnnBtHY3xULz5akpoqUqIE42N2wjhgHM/LU4yRjJF5NUYyDpASGhFru4ijvCYhIQF+fn6Ij49HoUKFXJ0dygW2bwcUdxnwH41G2wl6bKw6o/ORcjklBmzatAl79uzBs88+iy5dumDt2rXo2LGj2XU6dOiAmzdvYtq0aShfvjxu3bqF1NRUNGrUSNE+c8q5ISLHYRwwjueFiBgHSAk23yMip2vcWFvAdO2a8lGlRIArV7TVtE3U+qY8rk2bNmjTpo3i9L/99ht27NiBixcv6vvACAsLc1DuiIiIiIgoMzdXZ4CI8h53d2DuXO3vGo1168bFqZ8fypvWrVuHunXrYubMmQgODkbFihUxevRoPHz40OQ6KSkpSEhIMJiIiIiIiMg2LJQiIpfo3BlYtQoIDrZuvcBAx+SH8p6LFy9i9+7dOHnyJNauXYs5c+Zg1apVGDp0qMl1pk+fDj8/P/0UGhrqxBwTEREREeUuLJQiIpfp3Bm4dAnYtg1YtgwICDBdc0qjAUJDtU3/iNSQnp4OjUaD5cuXo379+mjbti1mz56NJUuWmKwtNW7cOMTHx+unK1euODnXRERERES5B/uUIiKX0g13DgDe3trhfTUaw76mdAVVc+awk3NST2BgIIKDg+Hn56efV6VKFYgIrl69igoVKmRZx8vLC15eXs7MJhERERFRrsWaUkSUbZhq0hcSop3fubNr8kW50/PPP4/r168jKSlJP+/s2bNwc3NDSEiIC3NGREREjpCWph0FOjpa+zMtzdU5IiIWShFRtpKxSV9UlPZnbCwLpMiypKQkxMTEICYmBgAQGxuLmJgYXL58GYC26V2fPn306Xv37o2iRYuiX79+OH36NHbu3IkxY8agf//+8Pb2dsUhEBERkYOsWQOEhQHNmwO9e2t/hoVp5xOR67D5HhFlOxmb9BEpdejQITRv3lz/96hRowAAERERWLJkCeLi4vQFVADg6+uLzZs3Y/jw4ahbty6KFi2K7t27Y9q0aU7POxERETnOmjXaLiIydg8BANeuaeezRj6R62hEMt+aRIYSEhLg5+eH+Ph4FCpUyNXZISInYwwwjeeGiBgHjON5oewiLU1bI+rqVePLNRptVxGxsey7VG2MA6QEm+8RERER5RLsL4WIyNCuXaYLpABt7akrV7TpiMj52HyPiIiIKBdYswZ46y3DL18hIcDcuWyWQkR5V1ycuumISF2sKUVERESUw+n6S8lcG0DXXwo78iWivCowUN10RKQuFkoRERER5WBpadoaUsZ6CdXNGzmSTfmIKG9q3Fhba1SjMb5cowFCQ7XpiMj5WChFRERElIOxvxQiItPc3bXNmIGsBVO6v+fMYSfnRK7CQikiIiKiHIz9pRARmde5M7BqFRAcbDg/JEQ7n/3uEbkOOzonIiIiysHYXwoRkWWdOwMdOmhrjcbFaWNi48asIUXkaiyUIqIcJy2NDxRERDq6/lKuXTPer5RGo13O/lKIKK9zdweaNXN1LogoIzbfy0F27tyJ9u3bIygoCBqNBj///LPFdVJSUjB+/HiULl0aXl5eKFeuHL799lvHZ5bIQdasAcLCgObNgd69tT/DwjiyFBHlXewvhYiIiHIqFkrlIMnJyahZsybmzZuneJ3u3btjy5YtWLx4Mf7++29ER0ejcuXKDswlkeNwyHMiIuPYXwoRERHlRGy+l4O0adMGbdq0UZz+t99+w44dO3Dx4kX4+/sDAMLCwhyUOyLHsjTkuUajHfK8QwfWBiCivIn9pRAREVFOw5pSudi6detQt25dzJw5E8HBwahYsSJGjx6Nhw8fml0vJSUFCQkJBhORq3HIcyIiy3T9pfTqpf3JAikiIiLKzlhTKhe7ePEidu/ejfz582Pt2rW4c+cO3nzzTdy7d89sv1LTp0/H5MmTnZhTIss45DkREREREVHuwppSuVh6ejo0Gg2WL1+O+vXro23btpg9ezaWLFlitrbUuHHjEB8fr5+uXLnixFwTGcchz4mIiIiIiHIXFkrlYoGBgQgODoafn59+XpUqVSAiuGqmHZSXlxcKFSpkMBG5mm7I88wjS+loNEBoKIc8JyIiIiIiyilYKJWLPf/887h+/TqSkpL0886ePQs3NzeEhIS4MGdE1uOQ50RERLbZuXMn2rdvj6CgIGg0Gvz888+K192zZw88PDxQq1Yth+WPiIjyLhZK5SBJSUmIiYlBTEwMACA2NhYxMTG4fPkyAG2zuz59+ujT9+7dG0WLFkW/fv1w+vRp7Ny5E2PGjEH//v3h7e3tikMgsguHPCciIrJecnIyatasiXnz5lm1Xnx8PPr06YMWLVo4KGdERJTXsaPzHOTQoUNo3ry5/u9Ro0YBACIiIrBkyRLExcXpC6gAwNfXF5s3b8bw4cNRt25dFC1aFN27d8e0adOcnncitXDIcyIiIuu0adMGbdq0sXq9QYMGoXfv3nB3d7eqdpXV0tOBx4+zzjfXZt/eeRmXGZtHREROwUKpHKRZs2YQEZPLlyxZkmVe5cqVsXnzZgfmisj5dEOeExERkWN89913uHDhApYtW6bohWZKSgpSUlL0fyckJCjf2blzQOXKtmTT8TIWWCmd3NxM/8w4ubsb/u3hoZ3n7v70dw8P7ZQv39Ofnp6mJy8vwNv76VSgwNPffX2BggWf/ixYULuchXFE5EpCZEF8fLwAkPj4eFdnJdtITk6WSZMmSaVKlcTLy0v8/f2lZ8+ecu/ePYfuNzExUd566y0JDAwULy8vqVmzpkRHR9u0rUWLFgkA8fHxsWs/auaJsifGANN4brJifHRMnij7ymlxAICsXbvWbJqzZ89K8eLF5e+//xYRkcjISKlZs6bZdSIjIwVAlknRefnrLxEgT0zJgEwCpBIgXoD4A9ITkHsO3m8iIG8BEvjffmsCEg2IuLuLFC0qUr68SL16Iq1aifzf/4mMHi0ya5bIsmUif/whcvKkyN27IunpjJGkWE6Lj+QarClFZCURQa9evbBz505MnDgRtWrVwvHjx/H222+jXLlyDm0e2blzZxw8eBAzZsxAxYoVERUVhV69eiE9PR29e/dWvJ1r165h9OjRCAoKQnx8vF37UStPRJTzMT4yPlLOl5aWht69e2Py5MmoWLGi4vXGjRun71oC0NaUCg0NVbZy+fKAkfsNgLZIRY35GZfZ8lM3Zf7b1JSenuWnpKWh11tvYeeRI5g4YABqlS+P42fP4u3PP0e5//s/TOvXD0hLA1JTtT91v2ecHj8GnjzR/tRNKSmGvz98aDg9eIDOx47hYHIyZhQsiIpPniDqwQP0ApCelobed+8Cd++aPm8ZXMuXD6PT0hDk5YX4x4+Bzz/X/v/KlwfKlGGMJCLrubpUjLI/lnAb2rZtmwCQlStXGswvUaKEjBw50mH73bBhgwCQqKgog/nh4eESFBQkqampirf18ssvS/v27SUiIiLLWy5r9qNmnij7YgwwjefGEOMj42NelNPiAGC+ptS///4rAMTd3V0/aTQa/bwtW7Yo2k9OOy/OkK1iZHq6hL/4ogSVLCmpx46J7Nolsm6dyJIlIjNniowaJdK7t8iLL4pUrSri7y8CyMuAtAckAhCfTEVxGzw8tPtp3lxkwQKR/ftFHjxgjMzDGAdICY6+R2SllStXokiRIujUqZN+3s6dO3Hz5k28+OKLDtvv2rVr4evri27duhnM79evH65fv44DBw4o2s6yZcuwY8cOzJ8/3+79qJUnIsodGB8ZHynnK1SoEE6cOKEf8TkmJgaDBw9GpUqVEBMTgwYNGrg6izlWtoqRGg36DRiA6zdu4EBSEvDCC0D79kBEBDBmDPDpp8Dy5cCWLcCpU8Ddu1j27bfY4euL+StWAM89p+3fqnNnoEYNoEABrE1NhS+Abtu2AUOGAA0bAgULot+lS9q4N3++tuaWqTyBMZIoL2KhFJGV9u7dq38gu379Or777jt06dIFLVq0wMsvv5wlvYggNTVV0WTOyZMnUaVKFXh4GLa6rVGjhn65Jbdu3cLIkSMxY8YMhISE2L0fNfJERLkH4yPjI2VPSUlJ+gImAIiNjUVMTIx+1OZx48ahT58+AAA3NzdUq1bNYCpevDjy58+PatWqwcfHx1WHkePl+Bg5ZgxmfPwxQrp3BypW1Hasvno1cOwYkJSEk7Vro0r58vB4/33gpZeAgAAgLQ01zp3T7mfECKBIEaBlS5zcuhVVKlZkjCQiFkoRWePRo0c4efIkGjRogI8++gjBwcHo378/ChQogCVLlkBjZPSSHTt2IF++fIqmS5cumdz33bt34e/vn2W+bt5dBX0BvPnmm6hUqRKGDBmiyn7UyBMR5Q6Mj4yPlH0dOnQItWvXRu3atQEAo0aNQu3atTFx4kQAQFxcnL6Aihwj18dIjQZ3k5LgX64c8OGHwKZNwM2bQGws/GfP1u6nYEFtn1dbtuDuxYvwj4kBevYENmzQ9pNlZZ6IKHdgR+dEVjhy5AhSU1NRv359VK5cGQ0aNMD+/fsxZ84cNGnSBMePH4evr6/BOnXq1MHBgwcVbT8oKMjscmMPLEqWAcDq1avx66+/4ujRoxbTWrMfe/JERLkH4yPjI2VfzZo1g5jpAHzJkiVm1580aRImTZqkbqbymDwZIzUaICxMW/A0ahQ048Zpm/utWQNMmgTN48fAihXaKSAA6NULaNNGUZ6IKPdgoRSRFf78808AQP369VGsWDGULVsWrVq1QsWKFdGrVy/s378fLVu2NFjH19cXtWrVUrT9zFWYMypatKjRt0b37t0DAKNvwHSSkpIwdOhQDB8+HEFBQbh//z4A4PHjxwCA+/fvI1++fPDx8bFqP/bkiYhyF8ZHxkciMo0xEvAvWhSoVAkYNw5F163D3YQEoGVLIDoauH0b+Pxz3Pv8c23aK1e03aezcIoo12PzPSIr/PnnnyhbtiyKFStmdLmxt1RqVb2uXr06zpw5k6XfgBMnTgAAqlWrZnLdO3fu4ObNm/j0009RpEgR/RQdHY3k5GQUKVIEr776qtX7sSdPRJS7MD4yPhKRaYyRRmLk5ctI/fRT4No1YP16oEcPnMiXT5t2/nzg+eeBnTtN5o2IcgeNmKvLSwQgISEBfn5+iI+PR6FChVydHZcqX748SpYsid27d+vniQjCw8Nx8+ZN/YduRomJifj7778Vbb9GjRrw9PQ0umzTpk1o27YtfvzxR/To0UM/v02bNjh+/DguX74Md3d3o+s+evQI+/fvzzJ/xowZ2LFjBzZt2oRixYqhWrVqVu3HnjxRzsEYYBrPzVOMj4yPeRXjgHE8L4YYIxXGyJYtcfzAAVxOTYX7o0famW3bAh99BNSsqehc2CItDdi1C4iLAwIDgcaNAYZo+zEOkCJCZEF8fLwAkPj4eFdnxaXu3r0rAASAvP766/LHH3/IunXrpGPHjuLl5SV79+51eB7Cw8OlSJEisnDhQtm6dasMHDhQAMiyZcv0abZv3y7u7u4yefJki9uLiIgQHx8fm/ZjS1rKmRgDTOO50WJ8ZHzMyxgHjON5eYox0oYYef26yJAhIh4eIoCIRiPSu7fI1av2nQgjVq8WCQnR7kY3hYRo55N9GAdICRZKkUUMJlqbNm0SANKnTx8JDg6WfPnySalSpaRr164SExPjlDwkJibKiBEjpGTJkuLp6Sk1atSQ6OhogzTbtm0TABIZGWlxe6YeKJTsx5a0lDMxBpjGc6PF+Mj4mJcxDhjH8/IUY6QdMfLcOZGePZ+WFvn7i/z8s+LjtmT1am15V8YCKV0ZmEbDgil7MQ6QEmy+Rxax2qXWlClTMG3aNCQkJCB//vyuzg6R0zAGmMZzo8X4SHkZ44BxPC9PMUaq4OhRYOBA4PBh7d9DhgCffgp4e9u8ybQ07eCAV68aX67RACEhQGwsm/LZinGAlGBH50QK/fnnn6hevTofJoiIMmF8JCIyjTFSBbVrA3v3AqNHa/9esACoVw8w0heXUrt2mS6QArR1pq5c0aYjIsdhoRSRQgcPHkT9+vVdnQ0iomyH8ZGIyDTGSJV4egKffAL8739AiRLAqVPagqmvvrJpc3Fx6qYjItt4uDoDRDnFzZs3XZ0FIqJsifExZ+DoUkSuwRipslatgOPHgX79gI0btU35rl0DpkzRtrlTKDBQ3XREZBvWlCIiIiLK5das0fad0rw50Lu39mdYmHY+EVGOU7w4sH49MHWq9u9p04Dhw4H0dMWbaNxY22eUqXIsjQYIDdWmIyLHYaEUERERUS62Zg3QtWvWvlOuXdPOZ8EUEeVIGg0wYQIwf7729y+/BF57DXjyRNHq7u7A3LlPN5V50wAwZw5rlBI5GguliIiIiHKptDTgrbe0HfZmpps3cqQ2HRFRjjRkCLB8OeDhAURFAZ06AQ8fKlq1c2dg1SogONhwfkiIdn7nzg7ILxEZYKEUERERUS7F0aWIKE/o1Qv45Rcgf35gwwagWzfFTfk6dwYuXQK2bdOWaW3bBsTGskCKyFlYKEVERESUS3F0KSLKM9q2BX7//WnB1OTJild1dweaNdOWbTVrxiZ7RM7EQikiIiKiXIqjSxFRntK4MbBwofb3KVO0taeIKFtjoRQR5RppacD27UB0tPYn+0ghoryOo0sRUZ7z2mvAiBFPf//7b9fmh4jMYqEUEeUKHO6ciCgrji5FRHnSrFlAkyZAYiLQsSOQkODqHBGRCSyUIqIcj8OdExGZxtGliCjPyZcP+OknbeD76y+gb1/FHZ8TkXOxUIqIcjQOd05EZBlHlyKiPKdECWD1asDTE1i7Fpgxw9U5IiIjWChFRDkahzsnnZ07d6J9+/YICgqCRqPBzz//rHjdPXv2wMPDA7Vq1XJY/ohcjaNLEVGe06AB8OWX2t8nTAB++821+SGiLFgoRUQ5Goc7J53k5GTUrFkT8+bNs2q9+Ph49OnTBy1atHBQzoiIiMhlBgwA3nhD+6ayVy/gwgVX54iIMvBwdQaIiOzB4c5Jp02bNmjTpo3V6w0aNAi9e/eGu7u7VbWriIjo/9m787io6v2P4+8BBFdQXEFwqSw111yuWpha6rUyEy3TfrlkizdNzVupLe5pm6VlWpZl5XJNRbu3bPEm5lqpSalZVxNTEXdjccEYzu+P0yDIAAMMc2bg9Xw8zmMOZ77nzIcTfpr5zHcBfMTrr0s//SR9+63Uu7e0datUoYLVUQEQRSkAPs6x3HlCgvN5pWw283mWO4cz77//vn777TctWrRI06ZNy7d9Wlqa0tLSMn9OLshqPp98Ys5tkZ8rl0gr6PNXtsltybXcnnMcy28/r83Pz9wc+1mPOTZ//+z7WbeAgLy3MmWkoCBznhDHo2O/XDmpbFnzMYC3OQAAmf9/WLlSuuEGadcu6cknpblzrY4KgChKAfBxjuXO+/Y1P/dmLUyx3Dnysm/fPo0bN04bN25UgIvFixkzZmjy5MmFe8Fdu6SPPircuSicgACzQFWhgrlVrHj5sXJlqUqVy49Z90NDpVq1zElyy5Sx+JcAALhFeLi50sMtt0hvv20O6WMuScByFKUA+DzHcuejRmWf9DwiwixIsboUrmS32zVgwABNnjxZ1157rcvnjR8/XmPGjMn8OTk5WZGRka6dfOutZu+dvDjr7leQ57O2ydq2IPuGkfMaVx7La8vIyLmfkZF9326/fMxud76lp5vbn39e3nf8/Oef0qVL5paWdnn/4kXz0SE9XUpNNbfCqlbNHP9bq5b5WLeudNVVl7fwcLO3FwDA+3XpIvXrJy1bJo0cKX3zjWs9kAEUG5thuPIOF6VZcnKyQkJClJSUpODgYKvDAXJlt5ur7CUmmp8do6LoIeUOvpgDbDabVq1apbvuusvp83/88YeqVKki/yx/IBkZGTIMQ/7+/vrqq6/UpUuXfF/HF+9NiZeRYRanLl6ULlwwt/PnzcLUuXPmY0qK9Mcf5nb27OVHx/6pU9KJE2ZRKz9BQdLVV0tNmkhNm17e6tWjWFVKkAec477Aax0+LF13nfn/h3/9yyxSoViQB+AKekoBKDEcy50D+QkODtauXbuyHZs7d67WrVunFStWqH79+hZFhiLz85PKlze3osjIkE6fNqvcx46Zj0ePSr//Lh04YG6//2721Pr5Z3P7+OPL51erJt18s5mUOnWSGjemSAUA3iAyUho3Tpo4UXriCemOO5j0HLAQRSkAQImQmpqq/fv3Z/4cHx+vuLg4hYaGqk6dOho/frwSEhL04Ycfys/PT02aNMl2fo0aNVS2bNkcx1FK+flJ1aubW7Nmztukp5tjhn/5xZwz7KefzMe9e83eVitXXp7c/soi1fXXM2QEAKzy5JPSe++ZXy68+KI0ZYrVEQGlFkUpAECJsH37dnXu3DnzZ8fcT4MGDdLChQuVmJioQ4cOWRUeSqKAAHOYXr160t//fvn4pUvSjh1SbKy0fr20eXPOIlX9+tL995vbNddYEDwAlGLlykkzZ5or5bz0kjRkiJmXAXgcc0oVoz///FPHjh3T+fPnVb16dYWGhlodUqEwFhgo3YojB5AfUapcuiRt324WqNavlzZtMucycejQQRo4ULrnHnP1P/gUcqRz5Ed4PcMwV+KLjTVXxXF8aQC3IQ/AFUxu4Gapqal6++231alTJ4WEhKhevXpq3Lixqlevrrp16+qhhx7Stm3brA4TADyO/IhSKzDQLDw9/bT01Vdmr6nFi6Xu3c1hglu2SMOGmSv89esnxcVZHTEsQI4EPMxmk2bPNicljYmRvv7a6oiAUomilBu99tprqlevnt555x116dJFMTExiouL06+//qqtW7dq4sSJSk9PV9euXfX3v/9d+/btszpkAPAI8iOQRfny0oAB0hdfmHNSvfKKuWLfpUvmZOktW0q9e1OcKkXIkYBFmjaV/vEPc3/UKNdWXQXgVgzfc6O7775bEyZMUNOmTfNsl5aWpgULFigwMFAPPvigh6IrPLpdAqWbO3IA+RFwwc6d0ssvm0uUO96e3XWXuUJUixZWRoY8kCOdIz/CZ5w5I117rbni6uuvS489ZnVEJQZ5AK6gKOVDNmzYoJdfflk7duxQYmKiVq1apbvuusulczdv3qybb75ZTZo0UVwBv3klmQClGzkgd9wbFIu9e6WpU7MXpwYOlF59Vapa1drYkAN5wDnuC3zKW2+ZPaaqVJEOHpSCg2W3Sxs3SomJUliYFBVljvSD68gDcAXD94rJp59+qoyMDLde89y5c2revLnmzJlToPOSkpI0cOBA3XLLLW6NBwAKozjyI1CiNGokLVki7dkj9e9vznvy4YdS48bm8D6+TyzRyJGABR56SGrYUDp7Vpo/XzEx5sKqnTubo607dzZ/jomxOlCg5KGnVDHx9/dXYmKiatSoUSzXt9lsLveUuvfee9WgQQP5+/tr9erV9JQCUCDuzgHFnR89ifwIj/j2W2noUOnnn82fe/WS5s6VwsOtjQuSyJG5IT/C57z/vvTAA7pQJUxVzsYrTUHZnrbZzMcVK8zF+pA/8gBcEWB1ACWVt9T63n//ff32229atGiRpk2b5tI5aWlpSktLy/w5OTnZ9Rd87DGzy2teHBm9KG2ufD7rz6485+wxt2PONj+/7I+O/fw2f//LjwEB5pZ1P+uxwMDLW5kyl/eDgqSyZc0t636FCmY7wMt5S34EfEa7dtIPP0gzZkjTp0uffCKtX2/2prrtNqujg5uRIwGL3HefjOeeU7mEBP2fPtICZZ+3zTDMt/yjR5vfDTCUD3APilLFKC4uTjfeeKMqVKiQeSwhIUGNGjUqWKGnkPbt26dx48Zp48aNCghw/T/1jBkzNHny5MK96IYN0k8/Fe5cFF1AgLmqU4UKUsWKUkiIFBxsPl65Va0q1ahhbjVrStWrm0UuwAOszo+AzwkKkiZNkvr2NXtNff+9dOed5jwoXj7hNQqOHAlYIDBQv/X6p66ZO0ZP6mW9ryHKUPbKk2FIhw+bc0116mRNmEBJQ1GqGPXo0UM2m0316tVTs2bNdN111+n3339X5cqVi/217Xa7BgwYoMmTJ+vaa68t0Lnjx4/XmDFjMn9OTk5WZGSkaydPmmSuYOGqwnwbeOU5WX925Tlnj7kdy23LyHC+b7dfPubYHMfs9ss/O7b0dHPLup+eLv355+Xt0qWc28WL2TdH3OnpUnKyuRVGSIhZoKpTR6pb9/JWp47UoIE5VMSVnm5APqzMj4BPa9JE2rTJnP/kgw/Mx8OHzf//kp9LDHIkYI2drR9SqKbqOv1Pd2m1YtTHabvERA8HBpRgFKWK0f/+9z+dOHFCu3bt0k8//aRdu3YpIyND8+fPL/bXTklJ0fbt27Vz506NGDFCkpSRkSHDMBQQEKCvvvpKXbp0cXpuUFCQggrbY6Z378KGjMIyDLNQdf68uZ07Zz6mpEhJSTm35GTz8dQp6cSJy1t6+uU2//uf89eqVMmcBLJRI3Nr00Zq29Y8DhSAlfkR8Hllyphzn9SpY67SN2WKdOiQNH8+w7hLCHIkYI3q9StqjkZogqZqnF5QjKIl5Sz4h4V5PjagpGKi82Li5+enY8eOWTbReUZGhn52TIj6l7lz52rdunVasWKF6tevn61LeF6YoK4UyMiQ/vjDLE4lJpofbn7/3dwOHTLnCYuPN3t0XcnPT2raVOrQQWrf3ny86iq+sS9B3J0Dijs/ehL5EZZ75x1zGXO7XerWzZyBly8KPIoc6Rz5Eb7IbpduiDyprYl1VV4XdIv+q3W6vIK5zSZFRJhvi5lTKn/kAbiCnlLFpGfPnirj5m8rU1NTtX///syf4+PjFRcXp9DQUNWpU0fjx49XQkKCPvzwQ/n5+alJkybZzq9Ro4bKli2b4zggPz8pNNTcGjZ03ubSJWn/fmnvXumXX6Rdu8wVoX7/XfrxR3ObN89sW6OGWZzq2VO66y7zusBfiiM/AqXWQw+ZQ6vvuUf66iupY0dpzRq+xvdh5EjAOv7+0sQ51bWgz4N6TG9orF7MLEo5vm+dNYuCFOBO9JTyIevXr1fnzp1zHB80aJAWLlyowYMH6+DBg1q/fr3T8ydNmqTVq1crLi6uQK9LhRt5OnpU2rpV2rLFfNyxwyxgOQQESF26mJPz3nWXOaE6fAo5IHfcG3iN7dul2283e7zWqSN98YU5zBrFjjzgHPcFvuyLtw7q1n9cowDZ1Urb9YNaKTLSLEhFR1sdne8gD8AVFKXc6NChQ6pTp47L7RMSElS7du1ijMg9SCYokLQ0c+ny//5XWrnS7EHl4OdnLlVy//1S//6s9ucj3JEDyI+ABxw4IP3979K+fVKVKubyUNdfn+cpdrvZLDHR7FwVFUUPgIIiRzpHfoSvy/i/++W3eJEO/e1uHXjhY/JjIZAH4Ao/qwMoSdq0aaOHHnpI33//fa5tkpKS9M4776hJkyaKiYnxYHSAhwQFmXNLPfecFBdnTpo+Y4bUqpU5d9W6ddKQIVK9etLzz0unT1sdMTyA/Ah4wFVXmb1W//Y36exZ6c4788yxMTFmKu7cWRowwHysV888Ds8iRwLex2/sU5KkOt+vUKfa+yhIAcWEnlJudObMGU2fPl3vvfeeypQpo9atWys8PFxly5bV2bNn9fPPP2vPnj1q3bq1nn32WfXo0cPqkF1ChRtuEx8v/etf0ptvSgkJ5rFy5cwi1ejRUoMGloYH59yRA8iPgAedOmWujBofb1aavvwyx6p8MTHmqOor3wU65kxZsYIhKq4iRzpHfkSJcMcd0mefSY89Jr3+utXR+BzyAFxBUaoYXLx4UWvWrNHGjRt18OBBXbhwQdWqVVPLli3VvXt3n5tonGQCt7t0SVq+XJo5U9q50zzm52dO2Dt1KvNOeRl35gDyI+Ahu3ebvVZTU6Xhw6U5czKfstvNHlFHjjg/ldWlCoYc6Rz5ESXCl1+aw6IrVzbnUS1XzuqIfAp5AK6gKIV8kUxQbAxDWr9eeuUVc7Uoyfyf/qRJ0qOP5vhmH9YgB+SOewOv9u9/mwtMGIb01lvSI49IMtOuk3VTcoiNNacBRN7IA85xX1AiZGRIV18tHTwoLVwoDRpkdUQ+hTwAVzCnFADr2GzmJ6PPPpO++UZq0UL64w9zKF+zZuZk6QCAwrnzTmnaNHN/xAgzz8qc1NwVrrYDgBLL0ZNfkubPtzYWoISiKOUBFy5cUIJj/pws9uzZY0E0gJfq2NFc0vztt6Vq1aRffpG6dpUmTDDHmhSB3W72DFi61Hws4uXgRuRHoJiNHy/de6+Uni716SPFxysszLVTXW2H4kOOBLzAAw9IAQHmQhK7d1sdDVDiUJQqZitWrNC1116r2267Tc2aNdN3332X+dz9999vYWSAF/L3lx5+2FzO/K9hJpo6VerZ01xJqhBYXcp7kR8BD7DZpAULzBVQT5+WevVSVMtURURcntTc2SmRkVJUlGdDRXbkSMBL1Kol9epl7tNbCnA7ilLFbNq0afrhhx/0448/6r333tMDDzygJUuWSJKYzgvIReXK5vwnH34olS0rff651Lq19OOPBbqMY3WpKyfzTUgwj1OYshb5EfCQ8uWl1avND1a7dsl/+DDNnm0+dWVhyvHzrFlMcm41ciTgRR5+2Hz88EPp/HlrYwFKGIpSxezPP/9U9b9WEmvdurU2bNigt99+W1OmTJEtt68oAZjuv9/sKl2vnnTggLmS1F9vyPNjt0ujRuVc7ly6fGz0aIbyWYn8CHhQRIRZiffzkxYvVnTgp1qxQqpdO2ezFSuk6GhrwsRl5EjAi9x6q1S/vpSUJH38sdXRACUKRaliVqNGDf3000+ZP1etWlVr167V3r17sx0HkIuWLaUdO6Tu3aULF6T77jOrSX/+medpGzfmvty5ZBamDh8228Ea5EfAw9q3l/75T3N/2DBF35qsgwfNVfaWLDEf4+MpSHkLciTgRZjwHCg2FKWKya5du5Senq6PPvpINWvWzPZcYGCgli5dqm/+WgUHQD5CQ80V+p55xvx59mzzG6tjx3I9hdWlvBf5EbDQpEnSNdeY45jHjpW/v9Spk9S/v/nIkD3rkSMBLzVkiDnh+dat0q5dVkcDlBg2g0HpxcLPz0+BgYFq3LixmjdvrhYtWmQ+Vq5c2erwCiQ5OVkhISFKSkpScHCw1eGgtPvkE3NYX0qK2Y160yYpPDxHs/XrzUnN8xMba34QQ+7cnQPIj4DFsibI9eulm2+2MhqfR450jvyIEqlvX2nlSmn4cGnOHKuj8XrkAbiCnlLFZNOmTQoNDVX9+vWVlpamhQsXqkuXLqpataquu+46Pffcc/rjjz+sDhPwPb16Sdu2SVdfbY4z6d7d6cp8UVFidSkvRX4ELNap0+UVTh980BwaDa9BjgS8mCN3fvQRE54DbkJRqpiMGDFCc+fO1cqVK7VkyRLt3LlTsbGxuuqqqzRo0CBt3LhRLVu21MmTJ60OFfA9110n/fe/UliYtHu3dMcdOd4Y+PuL1aW8FPkR8AIvvmjOcr5/vzmkD16DHAl4sVtuMXvqJyebvfcBFBlFqWLyyy+/qHHjxtmO3XzzzXrttdf0ww8/KDY2Vq1bt9bTTz9tUYSAj6tXT/rqK6lyZXOFvr59c0x+Hh0tVpfyQuRHwAuEhEjz5pn7r7wibd9ubTzIRI4EvJifn7nojuTyitAA8kZRqpi0adNGixYtynH8+uuv11dffSWbzaYnn3xS//3vfy2IDighmjQxJ0AvV076/HNzAsqMjGxNoqPF6lJehvwIeImePc0ZzjMypKFDpfR0qyOCiidHbtiwQT179lR4eLhsNptWr16dZ/uYmBh17dpV1atXV3BwsNq3b68vv/yyoL8KUOLY7dL31wyQJGV8/oXsx09ZHBHg+yhKFZO5c+dq1qxZGjBggH755RdJ0qVLl/Taa68pNDRUklS9enUdP37cyjAB39ehgznhZECAtHix9Pjj0hXrN7C6lHchPwJeZPZsqWpV6aefpAULrI4GKp4cee7cOTVv3lxzXJyYecOGDeratavWrFmjHTt2qHPnzurZs6d27txZ8F8IKCFiYsyO+n8b3Eg/qKX87Ol6ruFyxcRYHRng2wKsDqCkuv7667V161aNGDFCjRs3VlBQkNLT0xUQEKD3339fkrRz506FO1k1DEAB9eghffCB2Z369del6tWlZ5+1OirkgvwIeJHq1aWJE6WRI825pe67T6pY0eqoSrXiyJE9evRQjx49XG4/a9asbD9Pnz5dn3zyif7zn/+oZcuWLl8HKCliYsyZIhzfey7WfbpBO9XjjyW6ue8/mBYCKAKKUsXo+uuvV2xsrH7//Xf9+OOP8vf3V6tWrVSrVi1J5rdcL7zwgsVRAiXEgAHS6dPmB6vnnpOuuUa6916ro0IuyI+AF3nkEbPH1G+/Sa++Kk2YYHVEpZ635ciMjAylpKRk9tQCShO7XRo1KntH/H/pXr2sJxWlTapj/K7Ro+uqVy964wOFQVHKA+rWrau6devmOB7FWvSAez32mHT0qPTCC+aHrLZtpauusjoq5IH8CHiBwEBp+nSpXz/ppZfM/FmzptVRQd6TI2fOnKlz587pnnvuybVNWlqa0tLSMn9OTk72RGhAsdu4UTpyJPuxo6qt9eqkLorVvVqqFw+P08aN5jQRAAqGOaUAlCxTp0o33mgu1TtgQI4V+QAATtx9t9SmjXTunDRlitXRwIssXbpUkyZN0rJly1SjRo1c282YMUMhISGZW2RkpAejBIpPYqLz40tkTnh+nxbn2Q5A3ihKAShZHBOeh4RI331nzpUCAMibzWb2kpKkt9+Wfv3V2njgFZYtW6ahQ4fq448/1q233ppn2/HjxyspKSlzO3z4sIeiBIpXWJjz4yvUV2kKVFPtVlP9lGs7AHmjKAWg5KlbV3rnHXP/hRekdeusjQcAfEGnTtIdd5gTqDz9tNXRwGJLly7V4MGDtWTJEt1+++35tg8KClJwcHC2DSgJoqKkiAizdp9VkirrM5n/NoZVWiJmHgAKh6IUgJLp7rulhx4yZ6X8v/+TTp2yOiIA8H4vvCD5+ZlLTW3ZYnU0cJPU1FTFxcUpLi5OkhQfH6+4uDgdOnRIktnLaeDAgZntly5dqoEDB2rmzJlq166djh07pmPHjikpKcmK8AFL+fuba0FIOQtTS/8awjc4aIn8bRkejgwoGShKASi5XntNatjQHOT/wAPZl00BAOR0/fXSkCHm/rhx1sYCt9m+fbtatmypli1bSpLGjBmjli1basJfKy0mJiZmFqgk6e2331Z6erqGDx+usLCwzG3UqFGWxA9YLTpaWrFCql07+/G4iDv0Z/lglT91WNq0yZrgAB9nMww+pSFvycnJCgkJUVJSEl2x4Xt+/NFche/SJemNN6QRI6yOyOeQA3LHvUGJdOSIdPXVZt7ctMlcPAK5Ig84x31BSWS3m6vxJSaac01FRUn+Dz0gvf++uXLpW29ZHaJXIQ/AFfSUAlCyNW8uvfKKuT9unMTEqwCQt4gI6f77zf0XX7Q2FgDwIv7+5vR7/fubj/7+Mld7lqTly81iPoACoSgFoOQbPly66SZzqfPHH7c6GgDwfk8+aU6e8p//SHv2WB0NAHivzp2lWrWkM2ekL76wOhrA51CUAlDy+flJc+eaX2etXCl9/rnVEQGA17LbpfWJ1+lw696SpIwXX7I4IgDwYv7+0r33mvtLllgbC+CDKEoBKB2aNpVGjzb3R4yQLlywNBwA8EYxMVK9euYX/322jZUk2T9aos/fPpT3iQBQmt13n/n4739LKSnWxgL4GIpSAEqPiRPNZVMOHGCeFAC4QkyM1LevOc+5JG1TW8Wqk8ooXb8Oe00xMdbGBwBeq1Ur6dprzS89V6+2OhrAp1CUAlB6VKokzZpl7r/wgrRvn6XhwL02bNignj17Kjw8XDabTavzeVMYExOjrl27qnr16goODlb79u315ZdfeiZYwMvY7dKoUdKVazK/oHGSpIc0X5MeOy273YLgAMDb2WyXJzxfvNjaWAAfQ1EKQOnSp4/UvbuUliY99ljOT2DwWefOnVPz5s01Z84cl9pv2LBBXbt21Zo1a7Rjxw517txZPXv21M6dO4s5UsD7bNx4uYdUVl+pm3aqhSrovO46+qY2bvR8bADgExxFqbVrpePHrY0F8CEUpQCULjab7LPnKKNMkPTll9o9JYZv/kuIHj16aNq0aYqOjnap/axZs/TUU0+pTZs2atCggaZPn64GDRroP//5TzFHCnifxMTcnrHpRZlzS43U6zoRf85jMQGAT2nQQGrTRsrIkD7+2OpoAJ9BUQpAqRITI9W79RpN+/MpSVLApGd0dd105kqBMjIylJKSotDQ0FzbpKWlKTk5OdsGlARhYbk/t0J9dUD1VU2n1XLne54LCgB8jWPCc4bwAS6jKAWg1Mg6ie8rekKnVFUN9as6JyxS376iMFXKzZw5U+fOndM999yTa5sZM2YoJCQkc4uMjPRghEDxiYqSIiLMaVGuZFeAZuoJSdI1/54p/fmnh6MDAB/Rr5/k5yd99530229WRwP4BIpSAEqFKyfxTVFw5pCUCZqsMsYljR4thvKVUkuXLtWkSZO0bNky1ahRI9d248ePV1JSUuZ2+PBhD0YJFB9/f2n2bHP/ysKUzSa9ryG6GFxdtt9/Z1gKAOSmVi2pSxdzf9kya2MBfARFKQClgrNJfN/UcCWqlurroIbqXR0+LCbxLYWWLVumoUOH6uOPP9att96aZ9ugoCAFBwdn24CSIjpaWrFCql07+/GICGnRynIq+9Qo88CLL7JIBADk5t57zcd//cvaOAAfQVEKQKngbBLfCyqvaXpWkvSspqmsLuQx2S9KoqVLl2rw4MFasmSJbr/9dqvDASwXHS0dPCjFxkpLlpiP8fHmcT36qFSxorRrl/T551aHCgDeKTpaKlPGzJV79lgdDeD1KEoBKBVym8T3XT2o31VH4UrUo5qb52S/8G6pqamKi4tTXFycJCk+Pl5xcXE6dOiQJHPo3cCBAzPbL126VAMHDtTMmTPVrl07HTt2TMeOHVNSUpIV4QNew99f6tRJ6t/ffPT3/+uJKlWkRx4x9194waLoAMDLVaki/f3v5j69pYB8UZTyIRs2bFDPnj0VHh4um82m1atX59k+JiZGXbt2VfXq1RUcHKz27dvryy+/9EywgJfJbRLfSwrSZE2UJD3t94KiWqRYEB3cYfv27WrZsqVatmwpSRozZoxatmypCRMmSJISExMzC1SS9Pbbbys9PV3Dhw9XWFhY5jZq1ChL4gd8wuOPmz0ANm6Utm61OhoA8E5Zh/Ax3BnIE0UpH3Lu3Dk1b95cc+bMcan9hg0b1LVrV61Zs0Y7duxQ586d1bNnT+3cubOYIwW8T16T+H6kgfpV16pqxin5vzHL47HBPTp16iTDMHJsCxculCQtXLhQ69evz2y/fv36PNsDcKJ2ben//s/cf+kla2MBAG91551SuXLS/v3SDz9YHQ3g1ShK+ZAePXpo2rRpio6Odqn9rFmz9NRTT6lNmzZq0KCBpk+frgYNGug///lPMUcKeKfcJvENiwxQ0uOTzR9eeUU6c8bzwQGAr3jiCfPx3/82J5wCAGRXsaLUs6e5zxA+IE8UpUqRjIwMpaSkKDQ0NM92aWlpSk5OzrYBJUVuk/i2feUeqWlTKTnZLEwBAJxr3Fjq2lXKyJDefNPqaADAO2UdwpeRYW0sgBejKFWKzJw5U+fOndM999yTZ7sZM2YoJCQkc4uMjPRQhIBnOJ3E189PmjrVbDB7tnT8uIURAoCXGznSfHz3XSk11dpYAMAb9eghBQdLR45IW7ZYHQ3gtShKlRJLly7VpEmTtGzZMtWoUSPPtuPHj1dSUlLmdvjwYQ9FCVjszjultm2l8+elGTOsjgYAvNdtt0lXXy0lJUmLFlkdDQB4n7Jlpd69zX2G8AG5oihVCixbtkxDhw7Vxx9/rFtvvTXf9kFBQQoODs62AaWCzSZNm2buz5snUZAFAOf8/KTHHjP3X3+d1aUAwBnHEL7ly6X0dGtjAbwURakSbunSpRo8eLCWLFmi22+/3epwAO93661Sx47SpUuXh/MBAHIaPNiczHfvXum//7U6GgDwPrfcIlWtKp04YU5kCiAHilI+JDU1VXFxcYqLi5MkxcfHKy4uTocOHZJkDrsbOHBgZvulS5dq4MCBmjlzptq1a6djx47p2LFjSkpKsiJ8wDfYbNLzz5v7771nLuULAMgpJEQaMsTcf/11a2MBAG9Upox0993mPkP4AKcoSvmQ7du3q2XLlmrZsqUkacyYMWrZsqUmTJggSUpMTMwsUEnS22+/rfT0dA0fPlxhYWGZ26hRoyyJH/AZN90k/f3vkt0uvfii1dEAgPcaMcJ8/OwzivgA4IxjCF9MjJSWZm0sgBeyGQaTACBvycnJCgkJUVJSEvNLofTYskW68UbzG64DB6SICKsjsgw5IHfcG0DmpOeffy6NGiXNmmV1NB5HHnCO+wL8xW6X6tSRjh6VPvnEXFinlCAPwBX0lAIAZzp0kG6+WfrzT2nmTKujAQDv5eiB/d57UkqKtbEAgLfx95f69TP3GcIH5EBRCgBy8/TT5uP8+dLJk9bGAgDeqmtX6brrzILUwoVWRwMA3scxhO+TT6Rz56yNBfAyFKUAIDddu0o33CCdP88kvgCQGz8/aeRIc/+NN6SMDGvjAQBv06aNVL+++Z7y00+tjgbwKhSlACA3Ntvl3lJz5kjJydbGAwDeauBAKThY2rdP+uILq6MBAO9is0kDBpj79CgFsqEoBQB56d1bathQ+uMP6a23rI4GALxTxYrS0KHmPj1LASCnIUPMxy+/lA4ftjYWwItQlAKAvPj5SePGmfuvvipduGBtPADgrUaMMHsDfPml9PPPVkcDAN7l6qulTp0kw5Def9/qaACvQVEKAPIzYIC5lO/x47yJAIDcXHWV1KuXuf/qq9bGAgDeyNGj9P33mX8P+AtFKQDIT5ky0lNPmfsvvST9+ae18QCAt3rySfPxo4+kxERrYwEAb9OnjxQSIh08KK1bZ3U0gFegKAUArnjgAalGDen336WlS62OBgC8U4cOUvv20qVL5gIRAIDLypWT7rvP3F+wwNpYAC9BUQoAXFGunDRmjLn/wgt0uQaA3Dh6S82bJ6WmWhsLAHgbxxC+mBjp9GlrYwG8AEUpAHDVP/5hdrneu1f65BOrowEA73TnndI110hnz0rvvWd1NADgXW64QWrRwuxRunix1dEAlqMoBQCuCg6WHnvM3J82zVw9BQCQnb+/9M9/mvuvvSalp1sbDwB4G0dvqQULeD+JUo+iFAAUxKhRUoUK0g8/SJ99ZnU0AOCdBg2SqlUzJ/NdudLqaADAu9x3nxQUJP30k7Rjh9XRAJaiKAUABVGtmjR8uLk/eTLfbgGAM+XKSSNGmPsvv0yuBICsqlQxV+KTmPAcpR5FKQAoqCeekMqXl7Zvlz7/3OpoAMA7DR8ulS1r9gL45hurowEA7+IYwrdkiXT+vLWxABaiKAUABVW9uvToo+Y+vaUAwLlq1aQhQ8z9l1+2NhYA8DadOkn160vJydKKFVZHA1iGohQAFMYTT5jDU77/XvriC6ujAQDvNGaMZLNJa9ZIe/ZYHQ0AeA8/v8u9pd5919pYAAtRlAKAwqhZk95SAJCfa66RoqPN/enTrY0FALzN4MFSQIC0caO0davV0QCWoCgFAIX15JNmb6nvvpO++srqaADAOz3zjPm4ZIkUF2dpKADgVWrXNgtTkjRliqWhAFahKAUAhVWzpjRsmLlPbykAcK5lS+nee8398eOtjQUAvM348ZK/vzkdxPffWx0N4HEUpQCgKJ56ylxdautWae1aq6MBAO80bZo5ROWLL6R166yOBgC8x1VXSfffb+5PnWptLIAFKEoBQFHUqiU98oi5T28pAHDu6qsv9ywdO5ZcCQBZPf20OfH5p59KP/xgdTSAR1GUAoCiGjvW7C21ZYv0+edWRwMA3unZZ6UKFaTt21n+HACyatBAGjDA3GduKZQyFKUAoKjCwqQRI8z9xx+XLl2yNh4A8EY1a0pPPGHuP/209Oef1sYDAN7kmWckm0365BMWhUCpQlEKANzh2WelGjWk//1PmjPH6mgAwDv9859S9erS/v3SggVWRwMA3qNhQ6lfP3N/2jRrYwE8iKIUALhDSIg0Y4a5P3mydOKEtfEAgDeqVEmaMMHcnzRJSk21NBwA8CrPPmv2llq5Utq92+poAI+gKAUA7jJ4sNSqlZScbHbBBgDk9PDD5mpTx49LQ4Yw6TkAOFx/vdS3r7n/yCNSWpq18QAeQFEKANzFz0+aPdvcX7CA1VMAwJnAQOmDD6QyZcwJzxmmAgCXTZ9u9sDfskV68EEK9yjxKEoBgDvdeKO5eophSKNG8UYCAJy56SZp3jxzf8IEKSbG2ngAwFtcc41ZsPf3lxYtkp5/3uqIgGJFUQoA3O3FF6Xy5aVNm6Rly6yOBgC809Ch0siR5v7990s//mhtPADgLW69VZo719x/7jnp44+tjQcoRhSlAMDdIiKkcePM/TFjpIQEa+MBAG81c6b54ev8ealXL+nkSasjAgDv8PDD5vtISRo0SPruO2vjAYoJRSkAKA5PPCE1biwlJkp33MEKUwDgTECA2aP0mmuk3383J/i9dMnqqADAO7z0ktSzp3TxonTnnWaeBEoYilIAUBzKlZM+/VSqUUOKi5PuvVdKT7c6KgDwPqGh0r//LVWqJG3YID32GPPxAfBJdru0fr20dKn5aLcX8YL+/tKSJVLz5tKJE+YXncnJbogU8B4UpQCguNSvb37QKltW+uwzafRoPmgBgDONGpmf4mw2af78y3OpAICPiImR6tWTOnc217zp3Nn8ucjrOFSsKP3nP1JYmLR7N190osShKAUAxelvf5MWLzY/aL35pjRrltURAYB3uv126YUXzP1Ro6R166yNBwBcFBNjjj4+ciT78YQE83iRC1ORkeYXneXKSZ9/fnmuKaAEoCgFAMUtOlp6+WVz/5//lFatsjYeAPBWTz4p/d//mWNeevc251M5d67Al3H7EBoft2HDBvXs2VPh4eGy2WxavXp1vud88803atWqlcqWLaurrrpKb731VvEHCvggu92sozvrDO84Nnq0G/JQ69bSokXm/htvSH//u7R6Nb2m4PMoSgGAJ4wZIw0bZr47ue8+6fvvrY6oxOFDF1AC2GzSO+9IN91kzpsydqx01VXSa69JFy64dIliG0Ljw86dO6fmzZtrzpw5LrWPj4/XbbfdpqioKO3cuVNPP/20Ro4cqZUrVxZzpIDv2bgxZw+prAxDOnzYbFdk0dHmqqWS9OWXZvG+bl1pwgTp0CE3vADgeRSlAMATbDbzW60ePcwPVj17SgcPWh1VicKHLqCEKFtWio2VFi40C1InTpiF/auuMvPoxYu5nlrsQ2h8VI8ePTRt2jRFR0e71P6tt95SnTp1NGvWLDVq1EgPPvigHnjgAb3yyivFHCngexIT3dsuX2PGSPv2SU89JVWvLh09Kk2dalbfb79dmjfP7EH17bfman1X5Ex6ksLb2AyDWXeRt+TkZIWEhCgpKUnBwcFWhwP4tpQUKSpK+vFHqXFjafNmqXJlq6PKky/mAJvNplWrVumuu+7Ktc3YsWP173//W3v37s08NmzYMP3444/aunWrS6/ji/cG8Cl//il9+KH5gcuxFHrt2tKtt0rXXSc1bGg+Xn217AFBqlcv9x4LNpsUESHFx5sLWrmLr+UBV/Jjx44d1bJlS82ePTvz2KpVq3TPPffo/PnzKlOmTI5z0tLSlJaWlvlzcnKyIiMjfea+AIW1fr3ZIzM/sbFSp05ufvG0NLMA9fbb5gvkplIlKTBQF+0BOpNSRmn2AGXIT4ZsCvCXqlWXKlaQmSgdsu5faeJEs+d/PnwtP8IaAVYHAAClSqVK0qefmhOg//yzdOON0vPPS7165f0/f7jd1q1b1a1bt2zHunfvrgULFujPP/90+UMXgGJUpow0dKh0//3S++9L06aZVacPPsjezs9P9pDq2nC2nC6onC6qrC6onOzylyGbDNkkQzIO25TcxqbKlW36I8mmtEs2BQZJVSqbKdgwpLN/SJfSpP0zlqt9j8puLWD5imPHjqlmzZrZjtWsWVPp6ek6deqUwsLCcpwzY8YMTZ482VMhAl4jKsoseCckOJ9XylEQj4oqhhcPCpL69TO3//3PzJN795rdso4dM7dLl8wvRSWVlRR+5TXsko4V8HWTkooeO/AXilI+ZMOGDXr55Ze1Y8cOJSYm5vstl2TOlzJmzBjt2bNH4eHheuqppzRs2DDPBAzAuYgI6bPPpC5dzMJU797SDTdIkyeb3a4pTnkEH7oAHxIYKD3yiDR4sLRmjbRnj/Trr9Ivv5iPKSkKPHtc9V251k7zoYqTp2ySQv/ab9rzT5WNkGbPNqdxKW1sV/y/yDG44srjDuPHj9eYLCuCOXpKASWdv7+ZJ/r2vVzcdnD8c5k1y709NJ269lppxozsxwxD+uMP2Y+fUtdOf+rU8XQFyNz8dXncnp8M1aghrVjxV5z5Daa66ir3x49Si6KUD3HMlzJkyBD16dMn3/aO+VIeeughLVq0SJs3b9ajjz6q6tWru3Q+gGLUooW0f785WeXs2dIPP5jzTLVpI02ZInXvnmdxym43J8xMTJTCwsxv30rjt/lFxYcuwMcEBZmF/N69Lx8zDOnYMW377IRGPHRRZl8pc/NTxl/9pC5vkrLt5yZFlXT6r7moVqwoXYWpWrVq6dix7F0nTpw4oYCAAFWtWtXpOUFBQQoKCvJEeIDXiY4288SoUdmHEEdEmAUpy/KHzSZVqaKNP1ZR7PF82p6QNtqlTsXRowvIA0UpH9KjRw/16NHD5fZZJ6mUpEaNGmn79u165ZVXKEoB3iA01By69/jj0iuvmBP4bttmTobeooXUrp0571SjRuZjWJhksykmxvmbntL6bX5h8aELKCFsNiksTDcMCdPRybkPoZHM4n2BJvU1zMuPHm2Osi4txf/27dvrP//5T7ZjX331lVq3bu10aDMA8z1Yr17e+aVhQSZjz+2LT74QRXGhKFWCFWa+FIk5UwCPq1ZNeuEFczWVl16S5s6V4uLMLavgYKWWq6Zrj5fTSpXXeZXXRZU1J6o8YpPRx6bEVjaFhdvMT1FZN2euv96cPLiU4kMXULLkN4TGMAq3ylTW5dzdPkmxh6Smpmr//v2ZP8fHxysuLk6hoaGqU6eOxo8fr4SEBH344YeSzEUf5syZozFjxuihhx7S1q1btWDBAi1dutSqXwHwCf7+3pknnMxI4NS+fcqxYEREhNS/v7laH1+IojhQlCrBCjNfisScKYBlatQwe0w9+aS0dq05UeXPP5uP+/dLycmqmJysJnldY8dfmyvOnCl6zF6ED10A8hpC06ePOYymsNy2nLsFtm/frs5ZlgdzDEMeNGiQFi5cqMTERB06dCjz+fr162vNmjV6/PHH9eabbyo8PFyvv/46Pe0BH+XKZOyhodKkSTmfP3JEevnlnOcklNLhzXA/ilIlXEHnS5GYMwWwXM2a0v/9X/ZjaWn6fulvGjkk+a8+UuZWTheyzZXipww9+U9DDa4xtO9/hpKTDIWESNdcI/n5mZfKyDBrXMf8wpWxvuR0v+ZDFwAp9yE0GzcWrSjlak8Db9SpU6fM94DOLFy4MMexm2++WT/88EMxRgXAU1zpSSrlP795VkYpHd4M96MoVYIVZr4UiTlTAK8UFKTfghrrOxeaVrJLK5533sVauqIHwcyS0/2aD10AHJwNocmvp0BuinU5dwDwkLx6kj74oDRxYsGvWRKGN8N6flYHgOLTvn17rV27Ntsx5ksBfJer39LPmpX9zYZkfgjr08fcnD3Xt68UE+OWMAHAKzl6Ckh5Lm6ajUeXcweAYhYdLR08KMXGSkuWmI/x8VKDBkW7ri8Pb4b1KEr5kNTUVMXFxSnur8mPHfOlOIajjB8/XgMHDsxsP2zYMP3+++8aM2aM9u7dq/fee08LFizQE088YUX4AIrI8S1/Xh+mcvvQlFevAMdzo0cXbhJgAPAVjp4CtWtnPx4ZaU7nFxGR/XhEBPOlAChZHD1J+/c3H/39iz482ZeHN8N6DN/zIcyXApRuxbWylET3awClR17Lts+YwZLnAEofhjfDShSlfAjzpQAozpWlJLpfA8if3e77hZvclm331uXcAaA45fXFZ24Y3gx3YfgeAPiY3OYD6NWr6Nem+zWAvMTESPXqSZ07SwMGmI/16jEnHQD4OoY3wyo2I6+uN4Ck5ORkhYSEKCkpScHBwVaHAyAXdrv54bCgXa+ly92v4+NzfttFDsgd9walSUyM+S36lfnF8W15af1wQh5wjvsC+KbcesMWppcseQCuYPgeAJQQrsw5deW+42eJ7tcAcme3m8OGnRW8DcPMI6NHmz02ySMA4LsY3gxPY/geAJQguXW9joiQVq40N2fPldYeDgBcs3Fj9nnsrpR1sQQAAABX0VMKAK7g65P45rWylJT3cwDgjKuLILBYAgAAKAiKUgCQRUyM85XtZs/2rZ5EeXWxpvs1gIJydREEFksAAAAFwfA9APiLYxLfK4eoJCSYx1ldCkBpFRVlFugdc9BdyWYzV2iKivJsXAAAwLdRlAIA5T+Jr2RO4mu3ezQsAPAKjoUUpJyFKRZLAAAAhUVRCgDEJL4AkJ+8FlJgsQQAAFAYzCkFAGISXwBwRX4LKQAAABQERSkAEJP4AoCrWCwBAAC4C8P3AEBM4gsAAAAAnkZRCgDEJL4AAAAA4GkUpQDgL0ziCwAAAACew5xSAJAFk/gCAAAAgGdQlAKAKzCJLwAAAAAUP4bvAQAAAAAAwOMoSgEAAAAAAMDjKEoBAAAAAADA4yhKAQAAAAAAwOMoSgEAAAAAAMDjWH0PAAAAAIBiYrdLGzdKiYlSWJgUFWWu9gyAohQAAAAAAMUiJkYaNUo6cuTysYgIafZsKTraurgAb8HwPQAAAAAA3CwmRurbN3tBSpISEszjMTHWxAV4E4pSAAAAAAC4kd1u9pAyjJzPOY6NHm22A0ozilIAAAAAALjRxo05e0hlZRjS4cNmO6A0oygFAAAAAIAbJSa6tx1QUlGUAgAAAADAjcLC3NsOKKkoSgEAAAAA4EZRUeYqezab8+dtNiky0mwHlGYUpQAAAAAAcCN/f2n2bHP/ysKU4+dZs8x2QGlGUQoAAAAAADeLjpZWrJBq185+PCLCPB4dbU1cgDcJsDoAAAAAAABKouhoqVcvc5W9xERzDqmoKHpIAQ4UpQAAAAAAKCb+/lKnTlZHAXgnhu8BAAAAAADA4yhKAQAAAAAAwOMoSgEAAAAAAMDjKEoBAAAAAADA4yhKAQAAAAAAwOMoSgEAAAAAAMDjKEoBAAAAAADA4yhK+aC5c+eqfv36Klu2rFq1aqWNGzfm2X7x4sVq3ry5ypcvr7CwMA0ZMkSnT5/2ULQAAKA0sNul9eulpUvNR7vd6ogAAIC3oyjlY5YtW6bRo0frmWee0c6dOxUVFaUePXro0KFDTttv2rRJAwcO1NChQ7Vnzx4tX75c27Zt04MPPujhyAGg+FG0B6wREyPVqyd17iwNGGA+1qtnHgcAAMgNRSkf8+qrr2ro0KF68MEH1ahRI82aNUuRkZGaN2+e0/bffvut6tWrp5EjR6p+/fq66aab9Mgjj2j79u0ejhwAihdFe8AaMTFS377SkSPZjyckmMcpTAEAgNxQlPIhly5d0o4dO9StW7dsx7t166YtW7Y4PadDhw46cuSI1qxZI8MwdPz4ca1YsUK33357rq+Tlpam5OTkbBsAeDuK9oDn2e3SqFGSYeR8znFs9GiG8gEAAOcoSvmQU6dOyW63q2bNmtmO16xZU8eOHXN6TocOHbR48WL169dPgYGBqlWrlipXrqw33ngj19eZMWOGQkJCMrfIyEi3/h6AL2POFO9E0R6wxsaNOXtIZWUY0uHDZjsAAIArUZTyQTabLdvPhmHkOObw888/a+TIkZowYYJ27NihL774QvHx8Ro2bFiu1x8/frySkpIyt8OHD7s1fsBXMWeK96JoD1gjMdG97QCgNOHLToCilE+pVq2a/P39c3zAOnHiRI4PYg4zZszQjTfeqCeffFLNmjVT9+7dNXfuXL333ntKzOUdYlBQkIKDg7NtQGnHnCm+gaI94FlhYe5tBwClBV92AiaKUj4kMDBQrVq10tq1a7MdX7t2rTp06OD0nPPnz8vPL/t/Zn9/f0nmhzUA+WPOFO9H0R6wRlSUFBEh5VL7lc0mRUaa7QAAJr7sBC6jKOVjxowZo3fffVfvvfee9u7dq8cff1yHDh3K/GZ//PjxGjhwYGb7nj17KiYmRvPmzdOBAwe0efNmjRw5Um3btlV4eLhVvwbgU5gzxftRtAes4e8vzZ5t7l9ZmHL8PGuW2Q4AwJedwJUCrA4ABdOvXz+dPn1aU6ZMUWJiopo0aaI1a9aobt26kqTExMRsy58PHjxYKSkpmjNnjv75z3+qcuXK6tKli1588UWrfgXA5zBnim8YM2aM7r//frVu3Vrt27fX/PnzcxTtExIS9OGHH0oyi/YPPfSQ5s2bp+7duysxMVGjR4+maA8UUHS0tGKF+SErawE/IsIsSEVHWxYaAHidgnzZ2amTx8ICLENRygc9+uijevTRR50+t3DhwhzHHnvsMT322GPFHBVQcjFnim+gaA9YJzpa6tXL/BCVmGjmw6goekgBwJX4shPIzmYwRgH5SE5OVkhIiJKSkpg/BaWS3W5OPJmQ4Lyrtc1m9giIjy+ZH8DIAbnj3gAgDzjHfQGcW7/enNQ8P7Gxvt9TijwAVzCnFADkgzlTAAAA4A4sEAFkR1EKAFzgmDOldu3sxyMizOPMmQIAAID88GUnkB1FKQBwUXS0dPCg2Z16yRLzMT6eghQAAABcx5edwGUUpQCgAPz9zfH9/fubj3yLBQDwBXPnzlX9+vVVtmxZtWrVShs3bsyz/eLFi9W8eXOVL19eYWFhGjJkiE6fPu2haIGSjy87ARNFKQAAAKAEW7ZsmUaPHq1nnnlGO3fuVFRUlHr06JFtRdKsNm3apIEDB2ro0KHas2ePli9frm3btunBBx/0cORAycaXnQBFKQAAAKBEe/XVVzV06FA9+OCDatSokWbNmqXIyEjNmzfPaftvv/1W9erV08iRI1W/fn3ddNNNeuSRR7R9+3YPRw4AKOkoSgEAAAAl1KVLl7Rjxw5169Yt2/Fu3bppy5YtTs/p0KGDjhw5ojVr1sgwDB0/flwrVqzQ7bffnuvrpKWlKTk5OdsGAEB+KEoBAACg2Njt0vr10tKl5qPdbnVEpcupU6dkt9tVs2bNbMdr1qypY8eOOT2nQ4cOWrx4sfr166fAwEDVqlVLlStX1htvvJHr68yYMUMhISGZW2RkpFt/DwBAyURRCgAAAMUiJkaqV0/q3FkaMMB8rFfPPA7Psl2x9rxhGDmOOfz8888aOXKkJkyYoB07duiLL75QfHy8hg0bluv1x48fr6SkpMzt8OHDbo0fAFAyBVgdAAAAAEqemBipb1/JMLIfT0gwj7PsuWdUq1ZN/v7+OXpFnThxIkfvKYcZM2boxhtv1JNPPilJatasmSpUqKCoqChNmzZNYWFhOc4JCgpSUFCQ+38BAECJRk8pACgihqYAQHZ2uzRqVM6ClHT52OjR7smX5OC8BQYGqlWrVlq7dm2242vXrlWHDh2cnnP+/Hn5+WX/mOD/17JghrP/qAC8EvkRvoCiFAAUAUNTACCnjRulI0dyf94wpMOHzXZFQQ52zZgxY/Tuu+/qvffe0969e/X444/r0KFDmcPxxo8fr4EDB2a279mzp2JiYjRv3jwdOHBAmzdv1siRI9W2bVuFh4db9WsAKADyI3wFw/cAoJAYmgIAziUmuredM+Rg1/Xr10+nT5/WlClTlJiYqCZNmmjNmjWqW7euJCkxMVGHDh3KbD948GClpKRozpw5+uc//6nKlSurS5cuevHFF636FQAUAPkRvsRm0AcX+UhOTlZISIiSkpIUHBxsdTiAV7DbzW+bcusJYLNJERFSfLz014gHn0UOyB33BnBu/XrzW/n8xMZKnToV/PrelIPJA85xXwBrkB/haxi+BwCF4KmhKQDgi6KizA89uSzuJptNiow02xUGORgAnCM/wtcwfA8ACsETQ1OystvNNw+JiVJYmPlBztd7YAEoufz9pdmzzWEiNlv2ISSOQtWsWYXPY57OwQDgKUV9z0d+hK+hpxQAFIKT1bCL1C4vTFQJwBdFR5vzltSunf14RETR5zPxZA4GAE9xx3s+8iN8DXNKIV+MBQZycozXT0hwvuS5u8br5zZRpaOngScmqiQH5I57A+SvOHp6eioHu4I84Bz3BSgYd73nIz/C19BTCgAKwTE0Rco5Z4o7hqZI5puKUaOcv6FwHBs92mwHAN7K39+czLx/f/PRHR+CPJGDAcBT3Pmej/wIX0NRCgAKqTiHpkhMVAkAeSnuHAwAnuLu93zkR/gSJjoHgCKIjpZ69SqeSciZqBIA8lacORgAPKU43vORH+ErKEoBQBE5hqa4GxNVAkD+iisHA4CnFNd7PvIjfAHD9wDAS0VFmd2sr5wPwMFmkyIjzXYAAADwTbznQ2lGUQoAvBQTVQIAAJR8vOdDaUZRCgC8GBNVAihp7HZp/Xpp6VLzkRVEAYD3fCi9mFMKALwcE1UCKCliYsxlz7OuMhURYfYQ4AMXgNKO93wojShKAUAxsNvd+4aCiSoB+LqYGKlvX3Np86wSEszj9AQAAN7zofRh+B4AuFlMjFSvntS5szRggPlYr555HABKI7vd7CF1ZUFKunxs9GiG8gEAUNpQlAIAN3L0BMg6NEW63BOAwhSA0mjjxpx5MSvDkA4fNtsBAIDSg6IUALgJPQEAwLnERPe2AwBkxyIS8FUUpQDATegJAADOhYW5tx0A4DKmjoAvoygFAG5CTwAAcC4qylxlz2Zz/rzNJkVGmu3yQk8AAMiOqSPg6yhKAYCb0BMAAJzz95dmzzb3ryxMOX6eNSvvVUrpCQCgtLuyMH/pElNHwPdRlAIAN3FHTwB6AQAoqaKjpRUrpNq1sx+PiDCPR0fnfi49AQCUds4K87VrM3UEfB9FKQBwk6L2BKAXAICSLjpaOnhQio2VliwxH+Pj8y5IsYgEgNIut8L8qVOunc/UEfBmFKUAwI0K2xOAXgAASgt/f6lTJ6l/f/MxryF7EotIACjd8irMu4qpI+DNAqwOAABKmuhoqVcv8wNSYqL5RiAqKvcPXvn1ArDZzF4AvXrl/+ENAHyd3Z49fyYkuHYePQEAlET5FebzYrOZX4zmt4gEYCWKUgBQDBw9AXKT9UPX8eOu9wLI65oA4OtiYswifdacWK2aa+fSEwBASVTYgruri0gAVqMoBQAe5uxDlyvoBQCgJHMMY76y12h+c6bQEwBASeZqwb16denkycs/R0SYBam85uwDvAFzSvmguXPnqn79+ipbtqxatWqljflMopCWlqZnnnlGdevWVVBQkK6++mq99957HooWQFa5zR3lCnoBACipXJ0zpTCLSACAL3N1decjRwq2iATgLegp5WOWLVum0aNHa+7cubrxxhv19ttvq0ePHvr5559Vp04dp+fcc889On78uBYsWKBrrrlGJ06cUHp6uocjB1DYiSrpBQCgpHN1zpRq1egJAKB0cazu3Lev+Z4w6/vIrIX5wECmeYBvoijlY1599VUNHTpUDz74oCRp1qxZ+vLLLzVv3jzNmDEjR/svvvhC33zzjQ4cOKDQ0FBJUr169TwZMoC/FGaiSnoBACgNXB2e/Npr5uqmriwiAQAlhWN15yunf6Awj5KAopQPuXTpknbs2KFx48ZlO96tWzdt2bLF6Tn//ve/1bp1a7300kv66KOPVKFCBd15552aOnWqypUr5/SctLQ0paWlZf6cnJzsvl8CKMUKMycUbzYAlAauDk+uXZueAABKp4Ku7gz4CopSPuTUqVOy2+2qWbNmtuM1a9bUsWPHnJ5z4MABbdq0SWXLltWqVat06tQpPfroozpz5kyu80rNmDFDkydPdnv8QGnn6oeu116TatbkzQaA0sMxZ0pCgvMhzgxjBoD8V3cGfBETnfsg2xWz3BmGkeOYQ0ZGhmw2mxYvXqy2bdvqtttu06uvvqqFCxfqwoULTs8ZP368kpKSMrfDhw+7/XcASiNXJ6p87DGpf3/zTQcFKQClgWPOFInJzAEAKE0oSvmQatWqyd/fP0evqBMnTuToPeUQFham2rVrKyQkJPNYo0aNZBiGjuQyuU1QUJCCg4OzbQCKjg9dxY/VSQHf5ZgzpXbt7McjIszjDGMGAKDkoSjlQwIDA9WqVSutXbs22/G1a9eqQ4cOTs+58cYbdfToUaWmpmYe+9///ic/Pz9FREQUa7wAcuJDV/FxrE76zDPPaOfOnYqKilKPHj106NChXM+555579PXXX2vBggX69ddftXTpUjVs2NCDUQPIKjpaOniQZc0BACgtbIZR0MXJYaVly5bp/vvv11tvvaX27dtr/vz5euedd7Rnzx7VrVtX48ePV0JCgj788ENJUmpqqho1aqR27dpp8uTJOnXqlB588EHdfPPNeuedd1x6zeTkZIWEhCgpKYleU4Cb2O2+M1Glr+SAv/3tb7rhhhs0b968zGONGjXSXXfdlevqpPfee2+21UkLylfuDYDiQx5wjvsCgDwAVzDRuY/p16+fTp8+rSlTpigxMVFNmjTRmjVrVLduXUlSYmJitl4BFStW1Nq1a/XYY4+pdevWqlq1qu655x5NmzbNql8BgJio0t1YnRQAAADwPRSlfNCjjz6qRx991OlzCxcuzHGsYcOGOYb8FYSjMx0fvoDSyfFv35s71lq9Oin5ESi9fCFHWoH3jwDIj3AFRSnkKyUlRZIUGRlpcSQArJSSkpJt0QRvVNjVSR2/16uvvqq+ffvqzTffdNpbavz48RozZkzmzwkJCWrcuDH5EYBP5EhP4v0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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "if run_one_time:\n", + " if cal_g2_error:\n", + " g2_fit_err = np.zeros_like(g2_fit)\n", + " if not g2_fit_failed:\n", + " \n", + " plot_g2_general( g2_dict={1:g2, 2:g2_fit}, taus_dict={1:taus, 2:taus_fit},\n", + " vlim=[0.95, 1.05], g2_err_dict= {1:g2_err, 2: g2_fit_err},\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= g2_fit_result, geometry= scat_geometry_,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '_fit',\n", + " qpi_analysis=True)\n", + " else:\n", + " plot_g2_general(g2_dict={1:g2, }, taus_dict={1:taus,},\n", + " vlim=[0.95, 1.05], g2_err_dict= {1:g2_err},\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])),\n", + " fit_res= None, geometry= scat_geometry_,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '',\n", + " qpi_analysis=True)\n", + " \n", + " else: \n", + " if not g2_fit_failed:\n", + " plot_g2_general( g2_dict={1:g2, 2:g2_fit}, taus_dict={1:taus, 2:taus_fit}, vlim=[0.95, 1.05],\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= g2_fit_result, geometry= scat_geometry_,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '_fit',\n", + " qpi_analysis=True)\n", + " else: \n", + " plot_g2_general( g2_dict={1:g2}, taus_dict={1:taus}, vlim=[0.95, 1.05],\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= None, geometry= scat_geometry_,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '',\n", + " qpi_analysis=True) \n" + ] + }, + { + "cell_type": "code", + "execution_count": 291, + "metadata": { + "papermill": { + "duration": 0.234143, + "end_time": "2023-06-20T08:55:28.948579", + "exception": false, + "start_time": "2023-06-20T08:55:28.714436", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The fitted diffusion coefficient D0 is: 4.177e+00 A^2S-1\n", + "The fitted diffusion coefficient D0 is: 1.833e+01 A^2S-1\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "if run_one_time:\n", + " try:\n", + " if True:\n", + " fs, fe = 0, 6\n", + " #fs,fe=0, 6\n", + " qval_dict_ = {k:qval_dict[k] for k in list(qval_dict.keys())[fs:fe] }\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict_, g2_fit_paras['relaxation_rate'][fs:fe], \n", + " geometry= scat_geometry_ )\n", + " plot_q_rate_fit_general( qval_dict_, g2_fit_paras['relaxation_rate'][fs:fe], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ , path= data_dir )\n", + " elif False:\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict, g2_fit_paras['relaxation_rate'],\n", + " fit_range=[0, 26], geometry= scat_geometry_ ) \n", + " plot_q_rate_fit_general( qval_dict, g2_fit_paras['relaxation_rate'], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ ,\n", + " show_fit=False, path= data_dir, plot_all_range=False) \n", + " else:\n", + " ##plot log_q, log_rate\n", + " plot_q_rate_general( qval_dict, g2_fit_paras['relaxation_rate'], \n", + " geometry= scat_geometry_,uid=uid_ , path= data_dir )\n", + "\n", + " plot_q_g2fitpara_general( qval_dict, g2_fit_paras, \n", + " geometry= scat_geometry_,uid=uid_ , path= data_dir )\n", + " except:\n", + " pass\n" + ] + }, + { + "cell_type": "code", + "execution_count": 292, + "metadata": {}, + "outputs": [], + "source": [ + "if track_progress:\n", + " if settings_dict_['run_one_time']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='run_one_time', progress='stop',start_time=None, stop_time=time.time(), verbose=True)\n", + " if settings_dict_['run_two_time']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='run_two_time', progress='start',start_time=time.time(), stop_time=None, verbose=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2e-05, + "end_time": "2023-06-20T08:55:28.951373", + "exception": false, + "start_time": "2023-06-20T08:55:28.951353", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# For two-time" + ] + }, + { + "cell_type": "code", + "execution_count": 293, + "metadata": { + "papermill": { + "duration": 0.09029, + "end_time": "2023-06-20T08:55:29.141606", + "exception": false, + "start_time": "2023-06-20T08:55:29.051316", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_fra_0_1000\n" + ] + } + ], + "source": [ + "define_good_series = True #making sure that the 2TCF takes ALL data into account -> this should be the default!\n", + "if define_good_series:\n", + " good_start = 0\n", + " good_end =md['number of images']\n", + " FD = Multifile(filename, beg = good_start, end = good_end)\n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( uid_ )" + ] + }, + { + "cell_type": "code", + "execution_count": 294, + "metadata": { + "papermill": { + "duration": 4.251569, + "end_time": "2023-06-20T08:55:33.393743", + "exception": false, + "start_time": "2023-06-20T08:55:29.142174", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 1000/1000 [00:04<00:00, 208.52it/s]\n" + ] + } + ], + "source": [ + "data_pixel = None\n", + "if run_two_time: \n", + " data_pixel = Get_Pixel_Arrayc( FD, pixelist, norm= norm, ).get_data()\n", + " \n", + " ### With another normalizaiton by using roi_intensity for each frame\n", + " #data_pixel = Get_Pixel_Arrayc( FD, pixelist, norm= norm, mean_int_sets = mean_int_setsF,qind=qind ).get_data()" + ] + }, + { + "cell_type": "code", + "execution_count": 295, + "metadata": { + "papermill": { + "duration": 11.132962, + "end_time": "2023-06-20T08:55:44.530064", + "exception": false, + "start_time": "2023-06-20T08:55:33.397102", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "100%|██████████| 20/20 [00:01<00:00, 10.60it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total time: 1.922 sec\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + } + ], + "source": [ + "import time\n", + "t0=time.time()\n", + "g12b=None\n", + "if run_two_time: \n", + " g12b = auto_two_Arrayc( data_pixel, roi_mask, index = None )\n", + " if run_dose:\n", + " np.save( data_dir + 'uid=%s_g12b'%uid, g12b)\n", + "run_time( t0 ) " + ] + }, + { + "cell_type": "code", + "execution_count": 296, + "metadata": { + "papermill": { + "duration": 0.500428, + "end_time": "2023-06-20T08:55:45.031827", + "exception": false, + "start_time": "2023-06-20T08:55:44.531399", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "if run_two_time:\n", + " \n", + " show_C12( np.nan_to_num( g12b ), q_ind= 1, qlabel=dict(itertools.islice(qval_dict.items(),g12b.shape[2])),\n", + " #N1= FD.beg,logs=False, N2=min( FD.end,10000), \n", + " vmin= 1.00, vmax=1.25, timeperframe=timeperframe,save=True, \n", + " path= data_dir, uid = uid_ ,cmap=plt.cm.jet)#cmap=cmap_albula) \n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 190, + "metadata": { + "papermill": { + "duration": 0.119291, + "end_time": "2023-06-20T08:55:45.152574", + "exception": false, + "start_time": "2023-06-20T08:55:45.033283", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Total time: 0.052 sec\n", + "The correlation function is saved in /nsls2/data/chx/proposals/2025-3/pass-317286/Results/0ae234d7-fb12-4f03-8cdb-d64561aa93f0/ with filename as uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_fra_0_1000__g2b.csv\n" + ] + } + ], + "source": [ + "multi_tau_steps = True\n", + "if run_two_time:\n", + " if lag_steps is None:\n", + " num_bufs=8\n", + " noframes = FD.end - FD.beg\n", + " num_levels = int(np.log( noframes/(num_bufs-1))/np.log(2) +1) +1\n", + " tot_channels, lag_steps, dict_lag = multi_tau_lags(num_levels, num_bufs)\n", + " max_taus= lag_steps.max()\n", + " \n", + " #max_taus= lag_steps.max() \n", + " max_taus = Nimg \n", + " t0=time.time()\n", + " #tausb = np.arange( g2b.shape[0])[:max_taus] *timeperframe\n", + " if multi_tau_steps:\n", + " lag_steps_ = lag_steps[ lag_steps <= g12b.shape[0] ]\n", + " g2b = get_one_time_from_two_time(g12b)[lag_steps_]\n", + " tausb = lag_steps_ *timeperframe\n", + " else:\n", + " tausb = (np.arange( g12b.shape[0]) *timeperframe)[:-200]\n", + " g2b = (get_one_time_from_two_time(g12b))[:-200]\n", + " run_time(t0)\n", + " \n", + " g2b_pds = save_g2_general( g2b, taus=tausb, qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0],\n", + " qz=None, uid=uid_+'_'+q_mask_name+'_g2b.csv', path= data_dir, return_res=True )\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 191, + "metadata": { + "papermill": { + "duration": 0.336093, + "end_time": "2023-06-20T08:55:45.495206", + "exception": false, + "start_time": "2023-06-20T08:55:45.159113", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The g2 fitting parameters are saved in /nsls2/data/chx/proposals/2025-3/pass-317286/Results/0ae234d7-fb12-4f03-8cdb-d64561aa93f0/uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_fra_0_1000__g2b_fit_paras.csv\n" + ] + } + ], + "source": [ + "if run_two_time: \n", + " try: \n", + " g2b_fit_result, tausb_fit, g2b_fit = get_g2_fit_general( g2b, tausb, \n", + " function = fit_g2_func, vlim=[0.95, 1.05], fit_range= None, \n", + " fit_variables={'baseline':False, 'beta': True, 'alpha':True,'relaxation_rate':True}, \n", + " guess_values={'baseline':1.0,'beta': 0.15,'alpha':1.0,'relaxation_rate':1e-3,},\n", + " guess_limits = dict( baseline =[1, 1.8], alpha=[0, 2],\n", + " beta = [0, 1], relaxation_rate= [1e-8, 5000]) ) \n", + " g2b_fit_paras = save_g2_fit_para_tocsv(g2b_fit_result, filename= uid_ +'_'+q_mask_name+'_g2b_fit_paras.csv', path=data_dir )\n", + " g2b_fit_failed = False\n", + " except:\n", + " g2b_fit_failed = True\n", + " g2b_fit_paras = g2_fit_paras * 0\n" + ] + }, + { + "cell_type": "code", + "execution_count": 192, + "metadata": { + "papermill": { + "duration": 11.971538, + "end_time": "2023-06-20T08:55:57.468178", + "exception": false, + "start_time": "2023-06-20T08:55:45.496640", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n", + "No artists with labels found to put in legend. Note that artists whose label start with an underscore are ignored when legend() is called with no argument.\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The combined image is saved as: /nsls2/data/chx/proposals/2025-3/pass-317286/Results/0ae234d7-fb12-4f03-8cdb-d64561aa93f0/uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_fra_0_1000_g2_b_fit__joint.png\n" + ] + }, + { + "data": { + "image/png": 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", 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", 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "if run_two_time:\n", + " if not g2b_fit_failed:\n", + " plot_g2_general( g2_dict={1:g2b, 2:g2b_fit}, taus_dict={1:tausb, 2:tausb_fit}, vlim=[0.95, 1.05],\n", + " qval_dict=dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= g2b_fit_result, geometry=scat_geometry_,filename=uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '_b_fit')\n", + " else:\n", + " plot_g2_general( g2_dict={1:g2b,}, taus_dict={1:tausb, }, vlim=[0.95, 1.05],\n", + " qval_dict=dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= None,\n", + " geometry=scat_geometry_,filename=uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '')\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 193, + "metadata": { + "papermill": { + "duration": 0.054888, + "end_time": "2023-06-20T08:55:57.524735", + "exception": false, + "start_time": "2023-06-20T08:55:57.469847", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The fitted diffusion coefficient D0 is: 1.975e-01 A^2S-1\n", + "The fitted diffusion coefficient D0 is: 2.563e-01 A^2S-1\n", + "The fitted diffusion coefficient D0 is: 2.739e-01 A^2S-1\n", + "The fitted diffusion coefficient D0 is: 2.396e-01 A^2S-1\n" + ] + } + ], + "source": [ + "if run_two_time and not g2b_fit_failed :\n", + " D0b, qrate_fit_resb = get_q_rate_fit_general( dict(itertools.islice(qval_dict.items(),g2.shape[1])), g2b_fit_paras['relaxation_rate'],\n", + " fit_range=[0, 10], geometry= scat_geometry_ )" + ] + }, + { + "cell_type": "code", + "execution_count": 194, + "metadata": { + "papermill": { + "duration": 0.245365, + "end_time": "2023-06-20T08:55:57.835965", + "exception": false, + "start_time": "2023-06-20T08:55:57.590600", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The fitted diffusion coefficient D0 is: 2.960e+00 A^2S-1\n", + "The fitted diffusion coefficient D0 is: 2.753e+00 A^2S-1\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "if run_two_time:\n", + " try:\n", + " if True:\n", + " fs, fe = 0, 8\n", + " #fs,fe=0, 6\n", + " qval_dict_ = {k:qval_dict[k] for k in list(qval_dict.keys())[fs:fe] }\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict_, g2b_fit_paras['relaxation_rate'][fs:fe], \n", + " geometry= scat_geometry_ )\n", + " plot_q_rate_fit_general( qval_dict_, g2b_fit_paras['relaxation_rate'][fs:fe], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' , path= data_dir )\n", + " elif False:\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict, g2b_fit_paras['relaxation_rate'],\n", + " fit_range=[0, 26], geometry= scat_geometry_ ) \n", + " plot_q_rate_fit_general( qval_dict, g2_fit_paras['relaxation_rate'], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' ,\n", + " show_fit=False, path= data_dir, plot_all_range=False) \n", + " else:\n", + " ##plot log_q, log_rate\n", + " plot_q_rate_general( qval_dict, g2b_fit_paras['relaxation_rate'], \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' , path= data_dir )\n", + "\n", + " plot_q_g2fitpara_general( qval_dict, g2b_fit_paras, \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' , path= data_dir )\n", + " except:\n", + " pass\n" + ] + }, + { + "cell_type": "code", + "execution_count": 195, + "metadata": { + "papermill": { + "duration": 10.49927, + "end_time": "2023-06-20T08:56:08.336783", + "exception": false, + "start_time": "2023-06-20T08:55:57.837513", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The combined image is saved as: /nsls2/data/chx/proposals/2025-3/pass-317286/Results/0ae234d7-fb12-4f03-8cdb-d64561aa93f0/uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_fra_0_1000_g2_two_g2__joint.png\n" + ] + }, + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "if run_two_time and run_one_time:\n", + " plot_g2_general( g2_dict={1:g2, 2:g2b}, taus_dict={1:taus, 2:tausb},vlim=[0.99, 1.007],\n", + " qval_dict=dict(itertools.islice(qval_dict.items(),g2.shape[1])), g2_labels=['from_one_time', 'from_two_time'],\n", + " geometry=scat_geometry_,filename=uid_+'_g2_two_g2', path= data_dir, ylabel='g2', )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.1e-05, + "end_time": "2023-06-20T08:56:08.338611", + "exception": false, + "start_time": "2023-06-20T08:56:08.338590", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Run Dose dependent analysis" + ] + }, + { + "cell_type": "code", + "execution_count": 196, + "metadata": { + "papermill": { + "duration": 0.100158, + "end_time": "2023-06-20T08:56:08.560280", + "exception": false, + "start_time": "2023-06-20T08:56:08.460122", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_dose:\n", + " get_two_time_mulit_uids( [uid], roi_mask, norm= norm, bin_frame_number=1, \n", + " path= data_dir0, force_generate=False, compress_path = cmp_path + '/' )" + ] + }, + { + "cell_type": "code", + "execution_count": 197, + "metadata": { + "papermill": { + "duration": 0.085135, + "end_time": "2023-06-20T08:56:08.667038", + "exception": false, + "start_time": "2023-06-20T08:56:08.581903", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "transmission: 1.0 exposure time: 0.399997 [s]\n" + ] + } + ], + "source": [ + "try:\n", + " print( 'transmission: %s exposure time: %s [s]'%(md['transmission'],exposuretime) )\n", + "except:\n", + " md['transmission'] =1\n", + " print( 'transmission: %s exposure time: %s [s]'%(md['transmission'],exposuretime) )" + ] + }, + { + "cell_type": "code", + "execution_count": 198, + "metadata": { + "papermill": { + "duration": 0.056217, + "end_time": "2023-06-20T08:56:08.766145", + "exception": false, + "start_time": "2023-06-20T08:56:08.709928", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_dose:\n", + " N = len(imgs)\n", + " print(N)\n", + " #exposure_dose = md['transmission'] * exposuretime* np.int_([ N/16, N/8, N/4 ,N/2, 3*N/4, N*0.99 ])\n", + " exposure_dose = md['transmission'] * exposuretime* np.int_([ N/8, N/4 ,N/2, 3*N/4, N*0.99 ])\n", + " \n", + " print( exposure_dose )" + ] + }, + { + "cell_type": "code", + "execution_count": 199, + "metadata": { + "papermill": { + "duration": 0.056837, + "end_time": "2023-06-20T08:56:08.876104", + "exception": false, + "start_time": "2023-06-20T08:56:08.819267", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_dose:\n", + " taus_uids, g2_uids = get_series_one_time_mulit_uids( [ uid ], qval_dict, good_start=good_start, \n", + " path= data_dir0, exposure_dose = exposure_dose, num_bufs =8, save_g2= False,\n", + " dead_time = 0, trans = [ md['transmission'] ] )" + ] + }, + { + "cell_type": "code", + "execution_count": 200, + "metadata": { + "papermill": { + "duration": 0.084866, + "end_time": "2023-06-20T08:56:09.015565", + "exception": false, + "start_time": "2023-06-20T08:56:08.930699", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_dose: \n", + " plot_dose_g2( taus_uids, g2_uids, ylim=[1.0, 1.2], vshift= 0.00,\n", + " qval_dict = qval_dict, fit_res= None, geometry= scat_geometry_,\n", + " filename= '%s_dose_analysis'%uid_, \n", + " path= data_dir, function= None, ylabel='g2_Dose', g2_labels= None, append_name= '' )" + ] + }, + { + "cell_type": "code", + "execution_count": 201, + "metadata": { + "papermill": { + "duration": 0.044648, + "end_time": "2023-06-20T08:56:09.085824", + "exception": false, + "start_time": "2023-06-20T08:56:09.041176", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_dose:\n", + " qth_interest = 5\n", + " plot_dose_g2( taus_uids, g2_uids, qth_interest= qth_interest, ylim=[0.98, 1.4], vshift= 0.00,\n", + " qval_dict = qval_dict, fit_res= None, geometry= scat_geometry_,\n", + " filename= '%s_dose_analysis'%uidstr, \n", + " path= data_dir, function= None, ylabel='g2_Dose', g2_labels= None, append_name= '' )" + ] + }, + { + "cell_type": "code", + "execution_count": 202, + "metadata": {}, + "outputs": [], + "source": [ + "if track_progress:\n", + " if settings_dict_['run_two_time']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='run_two_time', progress='stop',start_time=None, stop_time=time.time(), verbose=True)\n", + " if settings_dict_['xsvs']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='xsvs', progress='start',start_time=time.time(), stop_time=None, verbose=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:09.152401", + "exception": false, + "start_time": "2023-06-20T08:56:09.152376", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Four Time Correlation" + ] + }, + { + "cell_type": "code", + "execution_count": 203, + "metadata": { + "papermill": { + "duration": 0.09842, + "end_time": "2023-06-20T08:56:09.356039", + "exception": false, + "start_time": "2023-06-20T08:56:09.257619", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_four_time:\n", + " t0=time.time()\n", + " g4 = get_four_time_from_two_time(g12b, g2=g2b)[:int(max_taus)]\n", + " run_time(t0)" + ] + }, + { + "cell_type": "code", + "execution_count": 204, + "metadata": { + "papermill": { + "duration": 0.06727, + "end_time": "2023-06-20T08:56:09.438027", + "exception": false, + "start_time": "2023-06-20T08:56:09.370757", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_four_time:\n", + " taus4 = np.arange( g4.shape[0])*timeperframe \n", + " g4_pds = save_g2_general( g4, taus=taus4, qr=np.array( list( qval_dict.values() ) )[:,0],\n", + " qz=None, uid=uid_ +'_g4.csv', path= data_dir, return_res=True )" + ] + }, + { + "cell_type": "code", + "execution_count": 205, + "metadata": { + "papermill": { + "duration": 0.074563, + "end_time": "2023-06-20T08:56:09.560723", + "exception": false, + "start_time": "2023-06-20T08:56:09.486160", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_four_time:\n", + " plot_g2_general( g2_dict={1:g4}, taus_dict={1:taus4},vlim=[0.95, 1.05], qval_dict=qval_dict, fit_res= None, \n", + " geometry=scat_geometry_,filename=uid_+'_g4',path= data_dir, ylabel='g4')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:09.597732", + "exception": false, + "start_time": "2023-06-20T08:56:09.597708", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Speckle Visiblity" + ] + }, + { + "cell_type": "code", + "execution_count": 206, + "metadata": { + "papermill": { + "duration": 0.091965, + "end_time": "2023-06-20T08:56:09.794479", + "exception": false, + "start_time": "2023-06-20T08:56:09.702514", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_xsvs: \n", + " max_cts = get_max_countc(FD, roi_mask ) \n", + " #max_cts = 15 #for eiger 500 K\n", + " qind, pixelist = roi.extract_label_indices( roi_mask )\n", + " noqs = len( np.unique(qind) )\n", + " nopr = np.bincount(qind, minlength=(noqs+1))[1:]\n", + " #time_steps = np.array( utils.geometric_series(2, len(imgs) ) )\n", + " time_steps = [0,1] #only run the first two levels\n", + " num_times = len(time_steps) \n", + " times_xsvs = exposuretime + (2**( np.arange( len(time_steps) ) ) -1 ) * timeperframe \n", + " print( 'The max counts are: %s'%max_cts )\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:09.814905", + "exception": false, + "start_time": "2023-06-20T08:56:09.814881", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Do histogram " + ] + }, + { + "cell_type": "code", + "execution_count": 207, + "metadata": { + "papermill": { + "duration": 0.072564, + "end_time": "2023-06-20T08:56:09.992027", + "exception": false, + "start_time": "2023-06-20T08:56:09.919463", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_xsvs:\n", + " if roi_avg is None:\n", + " times_roi, mean_int_sets = cal_each_ring_mean_intensityc(FD, roi_mask, timeperframe = None, ) \n", + " roi_avg = np.average( mean_int_sets, axis=0)\n", + " \n", + " t0=time.time()\n", + " spec_bins, spec_his, spec_std, spec_sum = xsvsp( FD, np.int_(roi_mask), norm=None,\n", + " max_cts=int(max_cts+2), bad_images=bad_frame_list, only_two_levels=True ) \n", + " spec_kmean = np.array( [roi_avg * 2**j for j in range( spec_his.shape[0] )] )\n", + " run_time(t0)\n", + " spec_pds = save_bin_his_std( spec_bins, spec_his, spec_std, filename=uid_+'_spec_res.csv', path=data_dir ) " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:10.031751", + "exception": false, + "start_time": "2023-06-20T08:56:10.031727", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Do historam fit by negtive binominal function with maximum likehood method" + ] + }, + { + "cell_type": "code", + "execution_count": 208, + "metadata": { + "papermill": { + "duration": 0.080963, + "end_time": "2023-06-20T08:56:10.222574", + "exception": false, + "start_time": "2023-06-20T08:56:10.141611", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_xsvs: \n", + " ML_val, KL_val,K_ = get_xsvs_fit( spec_his, spec_sum, spec_kmean, \n", + " spec_std, max_bins=2, fit_range=[1,60], varyK= False )\n", + " #print( 'The observed average photon counts are: %s'%np.round(K_mean,4))\n", + " #print( 'The fitted average photon counts are: %s'%np.round(K_,4)) \n", + " print( 'The difference sum of average photon counts between fit and data are: %s'%np.round( \n", + " abs(np.sum( spec_kmean[0,:] - K_ )),4))\n", + " print( '#'*30)\n", + " qth= 0 \n", + " print( 'The fitted M for Qth= %s are: %s'%(qth, ML_val[qth]) )\n", + " print( K_[qth])\n", + " print( '#'*30)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:10.255723", + "exception": false, + "start_time": "2023-06-20T08:56:10.255699", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Plot fit results" + ] + }, + { + "cell_type": "code", + "execution_count": 209, + "metadata": { + "papermill": { + "duration": 0.045892, + "end_time": "2023-06-20T08:56:10.408180", + "exception": false, + "start_time": "2023-06-20T08:56:10.362288", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_xsvs: \n", + " qr = [qval_dict[k][0] for k in list(qval_dict.keys()) ]\n", + " plot_xsvs_fit( spec_his, ML_val, KL_val, K_mean = spec_kmean, spec_std=spec_std,\n", + " xlim = [0,10], vlim =[.9, 1.1],\n", + " uid=uid_, qth= qth_interest, logy= True, times= times_xsvs, q_ring_center=qr, path=data_dir)\n", + " \n", + " plot_xsvs_fit( spec_his, ML_val, KL_val, K_mean = spec_kmean, spec_std = spec_std,\n", + " xlim = [0,15], vlim =[.9, 1.1],\n", + " uid=uid_, qth= None, logy= True, times= times_xsvs, q_ring_center=qr, path=data_dir )" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.6e-05, + "end_time": "2023-06-20T08:56:10.476055", + "exception": false, + "start_time": "2023-06-20T08:56:10.476029", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Get contrast" + ] + }, + { + "cell_type": "code", + "execution_count": 210, + "metadata": { + "papermill": { + "duration": 0.099953, + "end_time": "2023-06-20T08:56:10.680532", + "exception": false, + "start_time": "2023-06-20T08:56:10.580579", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_xsvs:\n", + " contrast_factorL = get_contrast( ML_val)\n", + " spec_km_pds = save_KM( spec_kmean, KL_val, ML_val, qs=qr, level_time=times_xsvs, uid=uid_, path = data_dir )\n", + " #spec_km_pds" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:10.698770", + "exception": false, + "start_time": "2023-06-20T08:56:10.698745", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Plot contrast with g2 results" + ] + }, + { + "cell_type": "code", + "execution_count": 211, + "metadata": { + "papermill": { + "duration": 0.096136, + "end_time": "2023-06-20T08:56:10.905433", + "exception": false, + "start_time": "2023-06-20T08:56:10.809297", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_xsvs: \n", + " plot_g2_contrast( contrast_factorL, g2b, times_xsvs, tausb, qr, \n", + " vlim=[0.8,1.2], qth = qth_interest, uid=uid_,path = data_dir, legend_size=14)\n", + "\n", + " plot_g2_contrast( contrast_factorL, g2b, times_xsvs, tausb, qr, \n", + " vlim=[0.8,1.2], qth = None, uid=uid_,path = data_dir, legend_size=4)" + ] + }, + { + "cell_type": "code", + "execution_count": 212, + "metadata": {}, + "outputs": [], + "source": [ + "if track_progress:\n", + " if settings_dict_['xsvs']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='xsvs', progress='stop',start_time=None, stop_time=time.time(), verbose=True)\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='save data and report', progress='start',start_time=time.time(), stop_time=None, verbose=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:10.922696", + "exception": false, + "start_time": "2023-06-20T08:56:10.922672", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Export Results to a HDF5 File" + ] + }, + { + "cell_type": "code", + "execution_count": 213, + "metadata": { + "papermill": { + "duration": 2.206983, + "end_time": "2023-06-20T08:56:13.236872", + "exception": false, + "start_time": "2023-06-20T08:56:11.029889", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "md['detector_mask_file']=detector_mask_path+detector_mask_filename\n", + "md['det_mask_dict'] = det_mask_dict\n", + "md['polygon_mask']= polygon_dict\n", + "md['roi_mask_file']= fp\n", + "md['mask'] = mask\n", + "#md['NOTEBOOK_FULL_PATH'] = data_dir + get_current_pipeline_fullpath(NFP).split('/')[-1]\n", + "md['good_start'] = good_start\n", + "md['bad_frame_list'] = bad_frame_list\n", + "md['avg_img'] = avg_img\n", + "md['roi_mask'] = roi_mask\n", + "md['mask_outliers'] = mask_outliers\n", + "if mask_outliers:\n", + " md['outlier_threshold'] = outlier_threshold\n", + " md['maximum_outlier_fraction'] = maximum_outlier_fraction\n", + "md['setup_pargs'] = setup_pargs\n", + "if scat_geometry == 'gi_saxs': \n", + " md['Qr'] = Qr\n", + " md['Qz'] = Qz\n", + " md['qval_dict'] = qval_dict\n", + " md['beam_center_x'] = inc_x0\n", + " md['beam_center_y']= inc_y0\n", + " md['beam_refl_center_x'] = refl_x0\n", + " md['beam_refl_center_y'] = refl_y0\n", + "\n", + "\n", + "elif scat_geometry == 'gi_waxs':\n", + " md['beam_center_x'] = center[1]\n", + " md['beam_center_y']= center[0]\n", + "else:\n", + " md['qr']= qr\n", + " #md['qr_edge'] = qr_edge\n", + " md['qval_dict'] = qval_dict\n", + " md['beam_center_x'] = center[1]\n", + " md['beam_center_y']= center[0] \n", + "\n", + "md['beg'] = FD.beg\n", + "md['end'] = FD.end\n", + "md['qth_interest'] = qth_interest\n", + "md['metadata_file'] = data_dir + 'uid=%s_md.pkl'%uid\n", + "\n", + "md['beg_OneTime'] = good_start_g2\n", + "md['end_OneTime'] = good_end_g2\n", + "\n", + "psave_obj( md, data_dir + 'uid=%s_md.pkl'%uid ) #save the setup parameters\n", + "save_dict_csv( md, data_dir + 'uid=%s_md.csv'%uid, 'w')\n", + "\n", + "Exdt = {} \n", + "if scat_geometry == 'gi_saxs': \n", + " for k,v in zip( ['md', 'roi_mask','qval_dict','avg_img','mask','pixel_mask', 'imgsum', 'bad_frame_list', 'qr_1d_pds'], \n", + " [md, roi_mask, qval_dict, avg_img,mask,pixel_mask, imgsum, bad_frame_list, qr_1d_pds] ):\n", + " Exdt[ k ] = v\n", + "elif scat_geometry == 'saxs': \n", + " for k,v in zip( ['md', 'q_saxs', 'iq_saxs','iqst','qt','roi_mask','qval_dict','avg_img','mask','pixel_mask', 'imgsum', 'bad_frame_list'], \n", + " [md, q_saxs, iq_saxs, iqst, qt,roi_mask, qval_dict, avg_img,mask,pixel_mask, imgsum, bad_frame_list] ):\n", + " Exdt[ k ] = v\n", + "elif scat_geometry == 'gi_waxs': \n", + " for k,v in zip( ['md', 'roi_mask','qval_dict','avg_img','mask','pixel_mask', 'imgsum', 'bad_frame_list'], \n", + " [md, roi_mask, qval_dict, avg_img,mask,pixel_mask, imgsum, bad_frame_list] ):\n", + " Exdt[ k ] = v\n", + " \n", + "if run_waterfall:Exdt['wat'] = wat\n", + "if run_t_ROI_Inten:Exdt['times_roi'] = times_roi;Exdt['mean_int_sets']=mean_int_sets\n", + "if run_one_time:\n", + " if run_invariant_analysis:\n", + " for k,v in zip( ['taus','g2','g2_fit_paras', 'time_stamp','invariant'], [taus,g2,g2_fit_paras,time_stamp,invariant] ):Exdt[ k ] = v\n", + " else:\n", + " for k,v in zip( ['taus','g2','g2_fit_paras' ], [taus,g2,g2_fit_paras ] ):Exdt[ k ] = v\n", + " \n", + "if run_two_time:\n", + " for k,v in zip( ['tausb','g2b','g2b_fit_paras', 'g12b'], [tausb,g2b,g2b_fit_paras,g12b] ):Exdt[ k ] = v\n", + " #for k,v in zip( ['tausb','g2b','g2b_fit_paras', ], [tausb,g2b,g2b_fit_paras] ):Exdt[ k ] = v \n", + "if run_dose:\n", + " for k,v in zip( [ 'taus_uids', 'g2_uids' ], [taus_uids, g2_uids] ):Exdt[ k ] = v\n", + "if run_four_time:\n", + " for k,v in zip( ['taus4','g4'], [taus4,g4] ):Exdt[ k ] = v\n", + "if run_xsvs:\n", + " for k,v in zip( ['spec_kmean','spec_pds','times_xsvs','spec_km_pds','contrast_factorL'], \n", + " [ spec_kmean,spec_pds,times_xsvs,spec_km_pds,contrast_factorL] ):Exdt[ k ] = v " + ] + }, + { + "cell_type": "code", + "execution_count": 214, + "metadata": { + "papermill": { + "duration": 0.24575, + "end_time": "2023-06-20T08:56:13.485609", + "exception": false, + "start_time": "2023-06-20T08:56:13.239859", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The xpcs analysis results are exported to /nsls2/data/chx/proposals/2025-3/pass-317286/Results/0ae234d7-fb12-4f03-8cdb-d64561aa93f0/ with filename as uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0__Res.h5\n" + ] + } + ], + "source": [ + "export_xpcs_results_to_h5( 'uid=%s_%s_Res%s.h5'%(md['uid'],q_mask_name,hdf5_name_extension), data_dir, export_dict = Exdt )\n", + "#extract_dict = extract_xpcs_results_from_h5( filename = 'uid=%s_Res.h5'%md['uid'], import_dir = data_dir )\n" + ] + }, + { + "cell_type": "code", + "execution_count": 215, + "metadata": { + "papermill": { + "duration": 0.072672, + "end_time": "2023-06-20T08:56:13.561092", + "exception": false, + "start_time": "2023-06-20T08:56:13.488420", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "try:\n", + " from pyCHX.chx_generic_functions import append_txtfile\n", + " outp = default_dir+'%s/%s/'%(md['cycle'],username)\n", + " append_txtfile( filename = outp + username + '.lst', \n", + " data = np.array( [ outp + 'Results/' + md['uid'] + '/uid=%s__Res.h5'%md['uid']]))\n", + "except:\n", + " print('ERROR: unable to append output textfile for this uid.')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:13.616508", + "exception": false, + "start_time": "2023-06-20T08:56:13.616483", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Create a PDF Report" + ] + }, + { + "cell_type": "code", + "execution_count": 216, + "metadata": { + "papermill": { + "duration": 0.069555, + "end_time": "2023-06-20T08:56:13.800176", + "exception": false, + "start_time": "2023-06-20T08:56:13.730621", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "pdf_out_dir = data_dir0\n", + "\n", + "pdf_filename = \"XPCS_Analysis_Report2_for_uid=%s%s%s.pdf\"%(uid,pdf_version,q_mask_name)\n", + "if run_xsvs:\n", + " pdf_filename = \"XPCS_XSVS_Analysis_Report_for_uid=%s%s%s.pdf\"%(uid,pdf_version,q_mask_name)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": 217, + "metadata": { + "papermill": { + "duration": 0.555317, + "end_time": "2023-06-20T08:56:14.398855", + "exception": false, + "start_time": "2023-06-20T08:56:13.843538", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Cannot find /nsls2/data/chx/proposals/2025-3/pass-317286/Results/0ae234d7-fb12-4f03-8cdb-d64561aa93f0/uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_ROI_on_Image.png\n", + "Cannot find /nsls2/data/chx/proposals/2025-3/pass-317286/Results/0ae234d7-fb12-4f03-8cdb-d64561aa93f0/uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_waterfall.png\n", + "uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_fra_0_1000_g2_two_g2__joint.png\n", + "\n", + "****************************************\n", + "The pdf report is created with filename as: /nsls2/data/chx/proposals/2025-3/pass-317286/Results/XPCS_Analysis_Report2_for_uid=0ae234d7-fb12-4f03-8cdb-d64561aa93f0_2025-12-11_16-51-36.pdf\n", + "****************************************\n" + ] + } + ], + "source": [ + "# cheating here a little: the function argument 'False' hardcodes the absence of the form factor fit\n", + "make_pdf_report( data_dir, uid, pdf_out_dir, pdf_filename, username, \n", + " False,run_one_time, run_two_time, run_four_time, run_xsvs, run_dose,\n", + " report_type= scat_geometry, report_invariant= run_invariant_analysis,\n", + " md = md )\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 218, + "metadata": {}, + "outputs": [], + "source": [ + "if track_progress:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='save data and report', progress='stop',start_time=None, stop_time=time.time(), verbose=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:56:14.401737", + "exception": false, + "start_time": "2023-06-20T08:56:14.401715", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Attach the PDF report to Olog " + ] + }, + { + "cell_type": "code", + "execution_count": 219, + "metadata": { + "papermill": { + "duration": 9.582586, + "end_time": "2023-06-20T08:56:24.099192", + "exception": false, + "start_time": "2023-06-20T08:56:14.516606", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Append _R1 to the filename.\n", + "The url=https://epics-services-chx.nsls2.bnl.local:38981/Olog was successfully updated with Add XPCS Analysis PDF Report and with the attachments\n" + ] + } + ], + "source": [ + "if att_pdf_report:\n", + " lops=0\n", + " while lops<5:\n", + " try:\n", + " update_olog_uid_with_file( uid[:6], text='Add XPCS Analysis PDF Report', \n", + " filename=pdf_out_dir + pdf_filename, append_name='_R1' )\n", + " lops=5\n", + " except:\n", + " print(\"Failed to attach PDF report to Olog...try again in 10s\")\n", + " time.sleep(10)\n", + " lops+=1\n", + " if lops == 5:\n", + " print(\"Failed final attempt to attach PDF to Olog!\")\n", + " " + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:24.102253", + "exception": false, + "start_time": "2023-06-20T08:56:24.102228", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Save the OAV images" + ] + }, + { + "cell_type": "code", + "execution_count": 220, + "metadata": { + "papermill": { + "duration": 0.048241, + "end_time": "2023-06-20T08:56:24.267903", + "exception": false, + "start_time": "2023-06-20T08:56:24.219662", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if save_oavs:\n", + " try:\n", + " #os.environ['HTTPS_PROXY'] = 'https://proxy:8888'\n", + " #os.environ['no_proxy'] = 'cs.nsls2.local,localhost,127.0.0.1'\n", + " update_olog_uid_with_file( uid[:6], text='Add OVA images', \n", + " filename= data_dir + 'uid=%s_OVA_images.png'%uid, append_name='_img' )\n", + " except:\n", + " print('failed to update Olog with OAV images')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 0.051775, + "end_time": "2023-06-20T08:56:24.384387", + "exception": false, + "start_time": "2023-06-20T08:56:24.332612", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### giving file permissions .." + ] + }, + { + "cell_type": "code", + "execution_count": 221, + "metadata": {}, + "outputs": [], + "source": [ + "#data_dir0" + ] + }, + { + "cell_type": "code", + "execution_count": 222, + "metadata": { + "papermill": { + "duration": 3.970212, + "end_time": "2023-06-20T08:56:28.528102", + "exception": false, + "start_time": "2023-06-20T08:56:24.557890", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#staff=['fluerasu','lwiegart','xmchen','jgoodrich']\n", + "#\n", + "#current_dir = !pwd\n", + "#respipelines_path = data_dir0 #this is actually the current directory..\n", + "#for user in users + staff:\n", + "# !setfacl -R -m u:{user}:rwx {data_dir0}\n", + "# !setfacl -R -m u:{user}:rwx {respipelines_path} \n", + "# print('Setting rwx rights for user %s to:\\n %s \\n %s \\n'%(user,data_dir0,respipelines_path)) \n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:28.531315", + "exception": false, + "start_time": "2023-06-20T08:56:28.531290", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# The End!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "celltoolbar": "Tags", + "kernelspec": { + "display_name": "Python 3 (current)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.6" + }, + "papermill": { + "duration": 202.500649, + "end_time": "2023-06-20T08:56:29.773278", + "environment_variables": {}, + "exception": false, + "output_path": "/nsls2/data/chx/legacy/analysis/2023_2/petrash/ResPipelines/XPCS_SAXS_2023_auto_test_v0_09f3d800-0018-4ee8-8fb3-4bb082ec26db.ipynb", + "parameters": { + "cycle": "2023_2", + "run_dose": false, + "run_two_time": true, + "uid": "09f3d800-0018-4ee8-8fb3-4bb082ec26db", + "username": "petrash" + }, + "start_time": "2023-06-20T08:53:07.272629", + "version": "0.15.0" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/pipelines/old_pipelines/XPCS_SAXS_auto.ipynb b/pipelines/old_pipelines/XPCS_SAXS_auto.ipynb new file mode 100644 index 0000000..e59bf55 --- /dev/null +++ b/pipelines/old_pipelines/XPCS_SAXS_auto.ipynb @@ -0,0 +1,4329 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 6.9e-05, + "end_time": "2023-06-20T08:53:08.428761", + "exception": false, + "start_time": "2023-06-20T08:53:08.428692", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# XPCS&XSVS Pipeline for Single-(Gi)-SAXS Run\n", + "\n", + "## Overview\n", + "\n", + "* Setup: load packages/setup path\n", + "* Load Metadata & Image Data\n", + "* Apply Mask\n", + "* Clean Data: shutter open/bad frames\n", + "* Get Q-Map\n", + "* Get 1D curve\n", + "* Define Q-ROI (qr, qz)\n", + "* Check beam damage\n", + "* One-time Correlation\n", + "* Fitting\n", + "* Two-time Correlation\n", + "\n", + "## CHX Olog Logbook\n", + "CHX Olog (https://logbook.nsls2.bnl.gov/11-ID/) [requires VPN offsite]\n", + "\n", + "## Setup\n", + "\n", + "Import packages for I/O, visualization, and analysis." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 1.299622, + "end_time": "2023-06-20T08:53:09.794917", + "exception": false, + "start_time": "2023-06-20T08:53:08.495295", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Imports and environment setup\n", + "\n", + "import time\n", + "\n", + "_xpcs_notebook_start = time.time()\n", + "_xpcs_cell_start = _xpcs_notebook_start\n", + "\n", + "import glob\n", + "import itertools\n", + "import json\n", + "import shutil\n", + "import sys\n", + "from time import localtime, strftime\n", + "\n", + "from pyCHX.chx_packages import *\n", + "#from pyCHX.chx_xpcs_xsvs_jupyter_V1 import *\n", + "#from pyCHX.chx_generic_functions import get_roi_mask_qval_qwid_by_shift\n", + "#from pyCHX.chx_generic_functions import RemoveHot,create_multi_rotated_rectangle_mask\n", + "\n", + "#sys.path.insert(0, \"/nsls2/data/chx/shared/CHX_Software/packages/database_processing/\") # Need a better way to include these directories\n", + "#sys.path.insert(0, \"/nsls2/data/chx/shared/CHX_Software/packages/AutoRun_functions/\")\n", + "from database_processing import *\n", + "from AutoRun_functions import *\n", + "\n", + "%matplotlib notebook\n", + "plt.rcParams.update({'figure.max_open_warning': 0})\n", + "plt.rcParams.update({'image.origin': 'lower'})\n", + "plt.rcParams.update({'image.interpolation': 'none'})\n", + "\n", + "%run /nsls2/data/chx/shared/CHX_Software/packages/environment_management/chx_analysis_setup_test_pyCHX.ipynb\n", + "_base_path_ = _base_path_pass_\n", + "print(colored(\"--> overwrote '_base_path_' as %s\\n\\n\"%_base_path_,'cyan'))\n", + "hostname= !hostname\n", + "if not 'saturn4' in hostname[0]:\n", + " enable_olog_attachments = False\n", + " print(colored(\"WARNING: currently running on resource %s => attachments to Olog are NOT possible!\"%(hostname[0]),'red'))\n", + " print(colored('To enable Olog attachments, this notebook needs to run on saturn4.nsls2.bnl.gov\\nFile -> Hub Control Panel -> Stop my Server -> start server and spawn to \"CHX staff @Saturn4\"','yellow'))\n", + "else:\n", + " enable_olog_attachments = True\n", + " print(colored('hostname: %s -> Olog attachments should be possible'%hostname[0],'green'))\n", + "\n", + "kernel = sys.executable\n", + "print(colored(f'sys.executable : {kernel}','green'))\n", + "\n", + "\n", + "_record_xpcs_cell_timing(\"01 - Imports and environment setup\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:53:09.798341", + "exception": false, + "start_time": "2023-06-20T08:53:09.798316", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Control Runs Here" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Run controls\n", + "\n", + "scat_geometry = 'saxs' #suport 'saxs', 'gi_saxs', 'ang_saxs' (for anisotropics saxs or flow-xpcs)\n", + "\n", + "\n", + "roi_auto = True #False if True, will automatically create a roi based on the roi_type ( iso/aniso etc), currently only works for SAXS\n", + "fit_peak = False #True\n", + "\n", + "analysis_type_auto = True #if True, will take \"analysis type\" option from data acquisition func series\n", + "qphi_analysis = False #if True, will do q-phi (anisotropic analysis for transmission saxs)\n", + "\n", + "isotropic_Q_mask = 'wide' #'wide' # 'normal' # 'wide' ## select wich Q-mask to use for rings: 'normal' or 'wide'\n", + "phi_Q_mask = 'phi_4x_20deg' #'phi_4x_20deg' #'phi_12x_30deg'\n", + "\n", + " \n", + "auto_bst_mask = True # True: if custom 'XPCS_beam_mask.json' does NOT exist in .../cycle/user/masks, create a default polygon mask for beamstop\n", + "force_compress = False #force to compress data \n", + "use_local_disk = True\n", + "bin_frame = False #generally make bin_frame as False\n", + "bin_frame_number = 4 # ignored if bin_frame == False\n", + "para_compress = True #parallel compress\n", + "# run_fit_form = False #run fit form factor -> to be removed\n", + "mask_outliers = False #!!\n", + "run_waterfall = False #True #False #True #run waterfall analysis\n", + "run_profile_plot = False #run prolfile plot for gi-saxs\n", + "run_t_ROI_Inten = True #run ROI intensity as a function of time\n", + "run_get_mass_center = False # Analysis for mass center of reflective beam center\n", + "run_invariant_analysis = False\n", + "run_one_time = True #run one-time\n", + "cal_g2_error = False #True #calculate g2 signal to noise\n", + "run_fit_g2 = False #run fit one-time, the default function is \"stretched exponential\"\n", + "fit_g2_func = 'stretched'\n", + "run_two_time = True #run two-time\n", + "run_four_time = False #True #True #False #run four-time\n", + "run_xsvs= False # True #False #run visibility analysis\n", + "att_pdf_report = True #attach the pdf report to CHX olog\n", + "qth_interest = 7 #the intested single qth \n", + "\n", + "use_sqnorm = True #if True, use sq to normalize intensity -> what happens if both are true or false?\n", + "use_SG = True #if True, use the Sawitzky-Golay filter of the avg_img for normalization\n", + "use_SG_bin_frames = False #if True, use the Sawitzky-Golay filter of the (binned) frame for normalization \n", + "\n", + "use_imgsum_norm= True #if True use imgsum to normalize intensity for one-time calculatoin -> else it's doing what?\n", + "pdf_version='_%s'%strftime(\"%Y-%m-%d_%H-%M-%S\", localtime()) #for pdf report name\n", + "run_dose = False #run dose_depend analysis\n", + "\n", + "\n", + "if scat_geometry == 'gi_saxs':run_xsvs= False;use_sqnorm=False\n", + "if scat_geometry == 'gi_waxs':use_sqnorm = False\n", + "if scat_geometry != 'saxs':qphi_analysis = False;scat_geometry_ = scat_geometry;roi_auto = False \n", + "else:scat_geometry_ = ['','ang_'][qphi_analysis]+ scat_geometry \n", + "if scat_geometry != 'gi_saxs':run_profile_plot = False\n", + "\n", + "rawdata_link = False # linking raw data in a user sub-folder [sub-folder needs to be created first]\n", + "\n", + "print('scattering geometry: %s/%s Phi-analysis: %s'%(scat_geometry, scat_geometry_, qphi_analysis))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.8e-05, + "end_time": "2023-06-20T08:53:10.127948", + "exception": false, + "start_time": "2023-06-20T08:53:10.127930", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### For 'manual' runs: specify uid" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.065196, + "end_time": "2023-06-20T08:53:10.259283", + "exception": false, + "start_time": "2023-06-20T08:53:10.194087", + "status": "completed" + }, + "tags": [ + "parameters" + ] + }, + "outputs": [], + "source": [ + "# Manual run setup\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "uid = 201401 #changed 29 May 2026 to an existing Eiger series - AF\n", + "\n", + "#####################################################################################################################\n", + "md=get_meta_data(uid)\n", + "username = md['user'] #this will be dynamically asigned as a parameter\n", + "cycle = md['cycle']\n", + "try:\n", + " users = md['user_group']\n", + "except:\n", + " users = []\n", + " \n", + "q_mask_name = '' # do NOT specify, will be created based on Q-Phi mask used and become part of hdf5 filename\n", + "track_progress = False # IF run by papermill with progress tracking, will automatically switch to 'True'\n", + "\n", + "_record_xpcs_cell_timing(\"05 - Load initial metadata\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.7e-05, + "end_time": "2023-06-20T08:53:10.259418", + "exception": false, + "start_time": "2023-06-20T08:53:10.259401", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Papermill inserts into the cell below:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.060502, + "end_time": "2023-06-20T08:53:10.383808", + "exception": false, + "start_time": "2023-06-20T08:53:10.323306", + "status": "completed" + }, + "tags": [ + "injected-parameters" + ] + }, + "outputs": [], + "source": [ + "# Parameters\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### creating directory for saving output data " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Refresh data-session metadata\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "# Data security modification: username for file creation is now the data_session. Should we fix this in the papermill level?\n", + "md=get_meta_data(uid)\n", + "username = md['data_session']\n", + "\n", + "_record_xpcs_cell_timing(\"09 - Refresh data-session metadata\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Create results directory\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "default_dir = _base_path_\n", + "data_dir0 = create_user_folder(cycle, username, default_dir if alternate_directory is None else alternate_directory)\n", + "md=get_meta_data(uid)\n", + "uid=md['uid']\n", + "print('The current uid for analysis is: %s...'%uid[:8])\n", + "data_dir = os.path.join(data_dir0, '%s/'%uid)\n", + "os.makedirs(data_dir, exist_ok=True)\n", + "print('Results from this analysis will be stashed in the directory %s' % data_dir)\n", + "uidstr = 'uid=%s'%uid\n", + "\n", + "_record_xpcs_cell_timing(\"10 - Create results directory\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### set up progress tracking" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Set up progress tracking\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if 'process_id' in locals(): #if process_id has been inserted by papermill\n", + " settings_dict_={'run_one_time':run_one_time,'run_two_time':run_two_time,'xsvs':run_xsvs}\n", + " prog_dict_file = get_progress_dict_filename(uid,md['cycle'],md['user'],default_dir)\n", + " track_progress = create_new_prog_dict_run_XPCS_SAXS(prog_dict_file=prog_dict_file,process_id=process_id,settings_dict=settings_dict_, verbose=True)\n", + "if track_progress:\n", + " print('going to track progress in %s '%prog_dict_file)\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='Load data and compress', progress='start',start_time=time.time(), stop_time=None, verbose=True)\n", + "else: print('Not tracking progress...notebook is likely being run outside of papermill')\n", + "\n", + "_record_xpcs_cell_timing(\"12 - Set up progress tracking\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.610795, + "end_time": "2023-06-20T08:53:11.060747", + "exception": false, + "start_time": "2023-06-20T08:53:10.449952", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Resolve source data files\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "sud = get_sid_filenames_v3(db[uid])\n", + "data_fullpath = sud[2]\n", + "\n", + "print ('scan_id, full-uid, data path are: %s--%s--%s'%(sud[0], sud[1], data_fullpath ))\n", + "\n", + "_record_xpcs_cell_timing(\"13 - Resolve source data files\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.8e-05, + "end_time": "2023-06-20T08:53:11.060904", + "exception": false, + "start_time": "2023-06-20T08:53:11.060886", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Don't Change the lines below here" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.6e-05, + "end_time": "2023-06-20T08:53:11.131323", + "exception": false, + "start_time": "2023-06-20T08:53:11.131297", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "* get metadata" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 1.388821, + "end_time": "2023-06-20T08:53:12.578892", + "exception": false, + "start_time": "2023-06-20T08:53:11.190071", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Load metadata and detector list\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "taus=None;g2=None;tausb=None;g2b=None;g12b=None;taus4=None;g4=None;times_xsv=None;contrast_factorL=None; lag_steps = None \n", + "\n", + "md = get_meta_data( uid )\n", + "md_blue = md.copy()\n", + "detectors = sorted(get_detectors(db[uid]))\n", + "print('The detectors are:%s'%detectors)\n", + "if len(detectors) >1:\n", + " md['detector'] = detectors[1]\n", + " print( md['detector'])\n", + "\n", + "_record_xpcs_cell_timing(\"16 - Load metadata and detector list\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.070582, + "end_time": "2023-06-20T08:53:12.652922", + "exception": false, + "start_time": "2023-06-20T08:53:12.582340", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Find beam center\n", + "\n", + "if 'eiger4m' in md['detector'] or md['detector'] == 'image': \n", + " reverse= True\n", + " rot90= False\n", + "elif ('eiger500k' in md['detector']) or ('eiger500K' in md['detector']): \n", + " reverse= True\n", + " rot90=True\n", + "elif 'eiger1m' in md['detector']: \n", + " reverse= True\n", + " rot90=False\n", + "print('Image reverse: %s\\nImage rotate 90: %s'%(reverse, rot90)) \n", + "try:\n", + " cx , cy = md_blue['beam_center_x'], md_blue['beam_center_y']\n", + " print('(cx,cy) = (%s,%s)'%(cx,cy))\n", + "except:\n", + " print('Will find cx,cy later.')" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.8e-05, + "end_time": "2023-06-20T08:53:12.658217", + "exception": false, + "start_time": "2023-06-20T08:53:12.658189", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Load ROI defined by \"XPCS_Setup\" Pipeline" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 5.1e-05, + "end_time": "2023-06-20T08:53:12.726548", + "exception": false, + "start_time": "2023-06-20T08:53:12.726497", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "#### Define data analysis type" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.061195, + "end_time": "2023-06-20T08:53:12.843922", + "exception": false, + "start_time": "2023-06-20T08:53:12.782727", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Select analysis type and ROI mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "mask_list = check_roi_masknames(_mask_path_+'ROI_masks/')\n", + "iso_masks=[];phi_masks=[]\n", + "for m in mask_list:\n", + " if 'phi' in m: phi_masks.append(m)\n", + " else: iso_masks.append(m)\n", + "\n", + "if analysis_type_auto:#if True, will take \"analysis type\" metadata\n", + " if scat_geometry != 'gi_saxs':\n", + " if md['analysis'] in phi_masks: # specific phi_mask has been requested by data acquisition\n", + " qphi_analysis=True\n", + " phi_Q_mask = md['analysis']\n", + " print('will be using specifically requested Q-Phi-mask: %s'%phi_Q_mask)\n", + " elif md['analysis'] in iso_masks: # specific iso_mask has been requested by data acquisition\n", + " qphi_analysis=False\n", + " isotropic_Q_mask = md['analysis']\n", + " print('will be using specifically requested Q-mask: %s'%isotropic_Q_mask)\n", + " else: # no exact match with existing mask name -> fall back to preselected mask for phi/iso\n", + " qphi_analysis_ = md['analysis'] #if True, will do q-phi (anisotropic analysis for transmission saxs)\n", + " print(md['analysis'])\n", + " if qphi_analysis_ == 'iso':\n", + " qphi_analysis = False\n", + " elif qphi_analysis_ == '':\n", + " qphi_analysis = False\n", + " else:\n", + " qphi_analysis = True \n", + " else:\n", + " try:\n", + " gisaxs_inc_type = md['analysis'] \n", + " except:\n", + " gisaxs_inc_type = None\n", + " print('There is no analysis in metadata.')\n", + " \n", + "print('Will %s qphis analysis.'%['NOT DO','DO'][qphi_analysis]) \n", + "\n", + "if scat_geometry != 'saxs':qphi_analysis = False;scat_geometry_ = scat_geometry \n", + "else:scat_geometry_ = ['','ang_'][qphi_analysis]+ scat_geometry \n", + "if scat_geometry != 'gi_saxs':run_profile_plot = False \n", + " \n", + "print(scat_geometry_)\n", + "\n", + "_record_xpcs_cell_timing(\"20 - Select analysis type and ROI mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:12.847398", + "exception": false, + "start_time": "2023-06-20T08:53:12.847376", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Load Data" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Load detector images\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "try: # preferred: load images as dask_array\n", + " imgs,img_md=load_dask_data(uid,md['detector'], _mask_path_+'pixel_masks/',reverse=reverse,rot90=rot90)\n", + " print(colored('SUCCESSFULLY LOADED DATA AS dask-array!','green'))\n", + "except:\n", + " print(colored('COULD NOT LOAD DATA AS dask-array, reverting to slow data loading....','red'))\n", + " imgs = load_data(uid,md['detector'],reverse=reverse,rot90=rot90)\n", + " img_md=imgs.md\n", + " print(colored('COULD NOT LOAD DATA AS dask-arry, falling back to slow data loading....','red'))\n", + "imgs\n", + "\n", + "_record_xpcs_cell_timing(\"22 - Load detector images\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Apply image metadata\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "md.update( img_md )\n", + "md['number of images'] = int(md['number of images'])\n", + "pixel_mask=np.ones( np.shape(imgs[0]))\n", + "if reverse and not rot90:\n", + " md['beam_center_y']=np.shape(imgs[0])[0]- md['beam_center_y']\n", + "if reverse and rot90:\n", + " xc=md['beam_center_y'];yc=md['beam_center_x']\n", + " yc=np.shape(imgs[0])[0]-yc\n", + " xc=np.shape(imgs[0])[1]-xc\n", + " md['beam_center_y']=yc;md['beam_center_x']=xc\n", + "if rot90 and not reverse:\n", + " raise Exception('ERROR: somebody still needs to figure out the transformation for reverse=%s and rot90=%s!'%(reverse,rot90))\n", + "print('Beam Center: xc: %s yc: %s'%(md['beam_center_x'],md['beam_center_y']))\n", + "\n", + "_record_xpcs_cell_timing(\"23 - Apply image metadata\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### create aggregate image of OAV images" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Aggregate OAV images\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "save_oavs = False\n", + "found_oavs = False\n", + "for d in detectors:\n", + " if 'OAV_image' in d:\n", + " found_oavs=True \n", + " \n", + "if found_oavs:\n", + " try:\n", + " save_oavs_tifs_v2( uid, data_dir )\n", + " save_oavs = True\n", + " print('successfully created aggregate image from individual OAV images')\n", + " except:\n", + " print('Failed to create aggregate image from individual OAV images -> OAV images will not be attached to Olog.')\n", + "\n", + "_record_xpcs_cell_timing(\"25 - Aggregate OAV images\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1e-05, + "end_time": "2023-06-20T08:53:14.325272", + "exception": false, + "start_time": "2023-06-20T08:53:14.325262", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### load detector mask" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Load detector mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "detector_mask_path = _mask_path_+'pixel_masks/'\n", + "detector_mask_filename = 'detector_mask_%s.json'%md['detector'].split('_')[0]\n", + "json_open=open(detector_mask_path+detector_mask_filename)\n", + "det_mask_dict=json.load(json_open)\n", + "for kk,k in enumerate(list(det_mask_dict['masks'].keys())):\n", + " if kk == 0:\n", + " det_mask=np.array(det_mask_dict['masks'][k],dtype=bool)\n", + " else:\n", + " det_mask*=np.array(det_mask_dict['masks'][k],dtype=bool)\n", + "\n", + "_record_xpcs_cell_timing(\"27 - Load detector mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:53:15.500297", + "exception": false, + "start_time": "2023-06-20T08:53:15.500273", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### load beam mask dictionary and re-create polygon mask for current detector and direct beam position" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.087476, + "end_time": "2023-06-20T08:53:15.656345", + "exception": false, + "start_time": "2023-06-20T08:53:15.568869", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Load beam-mask configuration\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "beam_mask_filename = 'XPCS_beam_mask.json'\n", + "mask_path =default_dir+'%s/%s/masks/'%(cycle,username)\n", + "try:\n", + " json_open=open(mask_path+beam_mask_filename)\n", + " polygon_dict=json.load(json_open)\n", + " print('loading user specified mask from %s'%(mask_path+beam_mask_filename))\n", + "except:\n", + " if auto_bst_mask:\n", + " if scat_geometry == 'saxs':\n", + " print('automatically creating a mask for beamstop and streaks')\n", + " polygon_dict={'masks':{'partial_mask':{'x_off': [0, -80],'y_off': [0, 0], 'wy_left': [20, 0],'wy_right': [10, 36],'wx_up': [20, 0],'wx_down': [20, 0],'center_radius': [0, 0]}}}\n", + " elif scat_geometry == 'gi_saxs':\n", + " polygon_dict={'masks':{'partial_mask':{'x_off': [0, 0],'y_off': [0, 0], 'wy_left': [0, 0],'wy_right': [0, 0],'wx_up': [36, 0],'wx_down': [36, 0],'center_radius': [0, 0]}}}\n", + " else:\n", + " raise Exception('failed to load user specified mask from %s'%(mask_path+beam_mask_filename))\n", + "\n", + "_record_xpcs_cell_timing(\"29 - Load beam-mask configuration\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.071073, + "end_time": "2023-06-20T08:53:15.731017", + "exception": false, + "start_time": "2023-06-20T08:53:15.659944", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Define polygon mask\n", + "\n", + "print('polygon masks: (could edit dictionary entries to modify mask here)')\n", + "polygon_dict['masks']" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Define polygon mask\n", + "\n", + "polygon_dict['masks']['partial_mask']['wy_right']= [8, 26]\n", + "polygon_dict['masks']['partial_mask']['wx_up']= [8, 0]\n", + "polygon_dict['masks']['partial_mask']['wx_down']= [8, 0]\n", + "polygon_dict['masks']['partial_mask']['wy_left']= [8, 0]\n", + "polygon_dict['masks']['partial_mask']['x_off'] = [0, -63]" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.8e-05, + "end_time": "2023-06-20T08:53:15.731673", + "exception": false, + "start_time": "2023-06-20T08:53:15.731655", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "#### re-create multi-polygon mask:" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.129297, + "end_time": "2023-06-20T08:53:15.924466", + "exception": false, + "start_time": "2023-06-20T08:53:15.795169", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Build polygon mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "polygon_mask=np.ones_like( det_mask , dtype = bool)\n", + "if 'rmask' in list(polygon_dict['masks'].keys()):\n", + " rmask_dict={}\n", + " for aa,a in enumerate(polygon_dict['masks']['rmask']['angles']):\n", + " rmask_dict[a] = create_multi_rotated_rectangle_mask( pixel_mask, \n", + " center= [ md['beam_center_x'], md['beam_center_y'] ], length=polygon_dict['masks']['rmask']['length'][aa], width=polygon_dict['masks']['rmask']['width'][aa], angles=[a] )\n", + "\n", + " for aa,a in enumerate(list(rmask_dict.keys())):\n", + " if aa == 0:\n", + " rmask = rmask_dict[a]\n", + " else:\n", + " rmask*=rmask_dict[a]\n", + " polygon_mask*=rmask\n", + "if 'partial_mask' in list(polygon_dict['masks'].keys()):\n", + " partialmask_dict={}\n", + " for ii,i in enumerate(range(len(polygon_dict['masks']['partial_mask']['x_off']))[:]): # [:] use all elements in list; [:2] use the first two elements in list, etc. to create masks\n", + " partialmask_dict[ii] = create_cross_mask( pixel_mask,center= [ md['beam_center_x']+polygon_dict['masks']['partial_mask']['x_off'][i], md['beam_center_y']+polygon_dict['masks']['partial_mask']['y_off'][i] ], \n", + " wy_left= polygon_dict['masks']['partial_mask']['wy_left'][i], wy_right= polygon_dict['masks']['partial_mask']['wy_right'][i], \n", + " wx_up= polygon_dict['masks']['partial_mask']['wx_up'][i], wx_down= polygon_dict['masks']['partial_mask']['wx_down'][i],center_radius= polygon_dict['masks']['partial_mask']['center_radius'][i])\n", + " \n", + " for i in list(partialmask_dict.keys()):\n", + " if i == 0:\n", + " partial_mask = partialmask_dict[i]\n", + " else:\n", + " partial_mask*=partialmask_dict[i]\n", + " polygon_mask*=partial_mask\n", + "if 'window_mask' in list(polygon_dict['masks'].keys()):\n", + " try: # center_circle has been renamed to center_disk at some point -> with try this works on old and new environements\n", + " window_shadow = ~create_cross_mask( pixel_mask, center=[md['beam_center_x'],md['beam_center_y']],\n", + " wy_left= 0, wy_right= 0, \n", + " wx_up= 0, wx_down= 0,center_disk=True, center_radius= polygon_dict['masks']['window_mask']['center_radius'])\n", + " except:\n", + " window_shadow = ~create_cross_mask( pixel_mask, center=[md['beam_center_x'],md['beam_center_y']],\n", + " wy_left= 0, wy_right= 0, \n", + " wx_up= 0, wx_down= 0,center_circle=True, center_radius= polygon_dict['masks']['window_mask']['center_radius'])\n", + " print('using \"create_cross_mask\" for older python environments')\n", + " polygon_mask*=window_shadow\n", + "\n", + "_record_xpcs_cell_timing(\"33 - Build polygon mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.915534, + "end_time": "2023-06-20T08:53:17.094650", + "exception": false, + "start_time": "2023-06-20T08:53:16.179116", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot detector and beam masks\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "fig,ax = plt.subplots(1,3,figsize=(15,5))\n", + "plt.suptitle('detector mask: %s\\nbeam mask: %s'%(mask_path+detector_mask_filename,mask_path+beam_mask_filename))\n", + "\n", + "plt.subplot(1,3,1)\n", + "plt.title('detector mask')\n", + "plt.imshow( det_mask)\n", + "plt.subplot(1,3,2)\n", + "plt.title('beam mask')\n", + "plt.imshow(polygon_mask)\n", + "plt.subplot(1,3,3)\n", + "plt.title('combined mask')\n", + "mask=polygon_mask*det_mask \n", + "plt.imshow(mask)\n", + "mask_copy=mask.copy()\n", + "\n", + "_record_xpcs_cell_timing(\"34 - Plot detector and beam masks\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.07127, + "end_time": "2023-06-20T08:53:17.274749", + "exception": false, + "start_time": "2023-06-20T08:53:17.203479", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Display metadata\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "print_dict( md, ['suid', 'number of images', 'uid', 'scan_id', 'start_time', 'stop_time', 'sample', 'Measurement',\n", + " 'acquire period', 'exposure time', \n", + " 'det_distance', 'beam_center_x', 'beam_center_y', ] )\n", + "\n", + "_record_xpcs_cell_timing(\"35 - Display metadata\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.6e-05, + "end_time": "2023-06-20T08:53:17.276413", + "exception": false, + "start_time": "2023-06-20T08:53:17.276397", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Overwrite Some Metadata if Wrong Input" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:17.336854", + "exception": false, + "start_time": "2023-06-20T08:53:17.336832", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Define incident beam center (also define reflection beam center for gisaxs)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.060425, + "end_time": "2023-06-20T08:53:17.715880", + "exception": false, + "start_time": "2023-06-20T08:53:17.655455", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Fix beam center\n", + "\n", + "if scat_geometry =='gi_saxs':\n", + " inc_x0 = md['beam_center_x'] \n", + " inc_y0 = imgs[0].shape[0] - md['beam_center_x'] \n", + " #1147 ,1550\n", + " refl_x0 = md['beam_center_x'] \n", + " refl_y0 = 1600.645 # calculated for an incidence angle of 0.32 deg \n", + " \n", + " print( \"inc_x0, inc_y0, ref_x0,ref_y0 are: %s %s %s %s.\"%(inc_x0, inc_y0, refl_x0, refl_y0) )\n", + "else:\n", + " inc_y0 = md['beam_center_y']\n", + " inc_x0 = md['beam_center_x']\n", + " \n", + "# if md['detector'] =='eiger4m_single_image' or md['detector'] == 'image' or md['detector']=='eiger1m_single_image': \n", + "# inc_x0 = imgs[0].shape[0] - md['beam_center_y'] \n", + "# inc_y0= md['beam_center_x']\n", + "# elif md['detector'] =='eiger500K_single_image': \n", + "# #inc_y0 = imgs[0].shape[1] - md['beam_center_y'] ### Changed this...not clear why\n", + "# #inc_x0 = imgs[0].shape[0] - md['beam_center_x']\n", + "# inc_x0 = imgs[0].shape[1]-md['beam_center_y']\n", + "# inc_y0 = md['beam_center_x']\n", + " \n", + " \n", + "# print(inc_x0, inc_y0)\n", + "\n", + " ###for this particular uid, manually give x0/y0\n", + " #inc_x0 = 1041\n", + " #inc_y0 = 1085" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.06776, + "end_time": "2023-06-20T08:53:17.787324", + "exception": false, + "start_time": "2023-06-20T08:53:17.719564", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Validate experiment metadata\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "dpix, lambda_, Ldet, exposuretime, timeperframe, center = check_lost_metadata(\n", + " md, md['number of images'], inc_x0 = inc_x0, inc_y0= inc_y0, pixelsize = 7.5*10*(-5) )\n", + "if scat_geometry =='gi_saxs':center=center[::-1]\n", + "\n", + "setup_pargs=dict(uid=uidstr, dpix= dpix, Ldet=Ldet, lambda_= lambda_, exposuretime=exposuretime,\n", + " timeperframe=timeperframe, center=center, path= data_dir)\n", + "print_dict( setup_pargs )\n", + "\n", + "_record_xpcs_cell_timing(\"39 - Validate experiment metadata\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.595578, + "end_time": "2023-06-20T08:53:18.574809", + "exception": false, + "start_time": "2023-06-20T08:53:17.979231", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Apply detector mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "show_img(np.array(mask,dtype=int),image_name = uidstr + '_mask', save=False, path=data_dir, aspect=1, center=center)\n", + "mask_load=mask.copy()\n", + "\n", + "imgsa = apply_mask( imgs, np.array(mask,dtype=int) )\n", + "\n", + "_record_xpcs_cell_timing(\"40 - Apply detector mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.7e-05, + "end_time": "2023-06-20T08:53:18.574944", + "exception": false, + "start_time": "2023-06-20T08:53:18.574927", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Check several frames average intensity" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 4.5e-05, + "end_time": "2023-06-20T08:53:18.651470", + "exception": false, + "start_time": "2023-06-20T08:53:18.651425", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "#### Load ROI mask depending on data analysis type" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 4.591728, + "end_time": "2023-06-20T08:53:23.364728", + "exception": false, + "start_time": "2023-06-20T08:53:18.773000", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Load and align ROI mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "roi_date = 'N.A'\n", + "\n", + "if scat_geometry =='saxs':\n", + " ## For auto load roi mask\n", + " if roi_auto: \n", + " general_path = _mask_path_+'ROI_masks/'\n", + " if qphi_analysis == False:\n", + " fp = general_path + 'general_roi_mask_%s.json'%isotropic_Q_mask\n", + " q_mask_name = isotropic_Q_mask\n", + " elif qphi_analysis:\n", + " fp = general_path + 'general_roi_mask_%s.json'%phi_Q_mask\n", + " q_mask_name = phi_Q_mask \n", + " \n", + " f = open(fp) ### load json file\n", + " tmp = json.load(f);f.close()\n", + " mask_dict=json.loads(tmp);del tmp\n", + " roi_mask0 = np.array(mask_dict['roi_mask']) \n", + " old_cen=mask_dict['original center'] \n", + " ## NOTE: new_\"cen below\" is actually ignored: function is hardcoded to use setup_pargs['center'] as center ####\n", + " # as the roi masks were not created using the physically correct orientations of the detectors, we'll need to fudge something here...\n", + " if \"eiger500k\" in md['detector']:\n", + " setup_pargs['center']=center[::-1]\n", + " if \"eiger4m\" in md['detector']:\n", + " setup_pargs['center']=center[::-1]\n", + " roi_mask, qval_dict, qwid_dict = get_roi_mask_qval_qwid_by_shift( \n", + " new_cen=[0,0], new_mask= mask, old_cen=old_cen,\n", + " old_roi_mask=roi_mask0, limit_qnum= 180,\n", + " setup_pargs= setup_pargs, geometry = scat_geometry_,\n", + " ) \n", + " ## undo fudging:\n", + " setup_pargs['center']=center\n", + " \n", + " else: \n", + " if qphi_analysis == False:\n", + " if isotropic_Q_mask == 'normal':\n", + " #print('Here')\n", + " q_mask_name='rings'\n", + " if \"eiger4m\" in md['detector'] or md['detector'] == 'image': #for 4M \n", + " fp = roi_path + 'roi_mask_%s_4M_norm.pkl'%roi_date \n", + "\n", + " elif (\"eiger500k\" in md['detector']) or (\"eiger500K\" in md['detector']): #for 500K \n", + " fp = roi_path + 'roi_mask_%s_500K_norm.pkl'%roi_date \n", + "\n", + "\n", + " elif isotropic_Q_mask == 'wide':\n", + " q_mask_name='wide_rings'\n", + " if \"eiger4m\" in md['detector'] or md['detector'] == 'image': #for 4M \n", + " fp = roi_path + 'roi_mask_%s_4M_wide.pkl'%roi_date \n", + " elif (\"eiger500k\" in md['detector']) or (\"eiger500K\" in md['detector']): #for 500K \n", + " fp = roi_path + 'roi_mask_%s_500K_wide.pkl'%roi_date \n", + "\n", + "\n", + " elif qphi_analysis:\n", + " if phi_Q_mask =='phi_4x_20deg':\n", + " q_mask_name='phi_4x_20deg'\n", + " if md['detector'] =='eiger4m_single_image' or md['detector'] == 'image': #for 4M \n", + " fp = roi_path + 'roi_mask_%s_4M_phi_4x_20deg.pkl'%roi_date \n", + " fp = roi_path + 'roi_mask_%s_4M_phi_24x_15deg.pkl'%roi_date \n", + " \n", + " elif (md['detector'] =='eiger500k_single_image') or (md['detector'] == \"eiger500K_single_image\"): #for 500K \n", + " fp = roi_path + 'roi_mask_%s_500K_phi_4x_20deg.pkl'%roi_date \n", + "\n", + " \n", + " roi_mask,qval_dict = cpk.load( open(fp, 'rb' ) ) #for load the saved roi data\n", + " print(fp)\n", + "\n", + "## Gi_SAXS \n", + "elif scat_geometry =='gi_saxs': \n", + " # static mask \n", + " fp = default_dir + md['cycle'] +'/masks/uid=%s_roi_masks.pkl'%ss\n", + " roi_masks,qval_dicts = cpk.load( open(fp, 'rb' ) ) #for load the saved roi data \n", + " print('The static mask is: %s.'%fp) \n", + "\n", + " fp = default_dir + md['cycle'] +'/masks/uid=%s_roi_mask.pkl'%(ss)\n", + " roi_mask,qval_dict = cpk.load( open(fp, 'rb' ) ) #for load the saved roi data\n", + " print('The dynamic mask is: %s.'%fp)\n", + " # q-map\n", + " fp = default_dir + md['cycle'] +'/masks/uid=%s_qmap.pkl'%(ss)\n", + " #print(fp)\n", + " qr_map, qz_map, ticks, Qrs, Qzs, Qr, Qz, inc_x0,refl_x0, refl_y0 = cpk.load( open(fp, 'rb' ) )\n", + " print('The qmap is: %s.'%fp)\n", + " \n", + "## WAXS \n", + "elif scat_geometry =='gi_waxs': \n", + " \n", + " fp = default_dir + md['cycle'] +'/masks/uid=278c0df1_roi_mask.pkl'\n", + " \n", + " roi_mask,qval_dict = cpk.load( open(fp, 'rb' ) ) #for load the saved roi data\n", + "\n", + "roi_mask2 = roi_mask.copy()\n", + "\n", + "_record_xpcs_cell_timing(\"43 - Load and align ROI mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.291226, + "end_time": "2023-06-20T08:53:23.656043", + "exception": false, + "start_time": "2023-06-20T08:53:23.364817", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Display ROI mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "#roi_mask = shift_mask(roi_mask, 10,30) #if shift mask to get new mask\n", + "show_img(roi_mask, aspect=1.0, image_name = fp, center=center,vmin=0)\n", + "\n", + "_record_xpcs_cell_timing(\"44 - Display ROI mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 1.24473, + "end_time": "2023-06-20T08:53:24.902640", + "exception": false, + "start_time": "2023-06-20T08:53:23.657910", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Correlate sample average image\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "img_choice_N = 5\n", + "img_samp_index = random.sample( range(md['number of images']), img_choice_N) \n", + "avg_img = get_avg_img( imgsa, img_samp_index, plot_ = False, uid =uidstr)\n", + "if avg_img.max() == 0:\n", + " print('There are no photons recorded for this uid: %s'%uid)\n", + " print('The data analysis should be terminated! Please try another uid.')\n", + "\n", + "_record_xpcs_cell_timing(\"45 - Calculate sample average image\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.470349, + "end_time": "2023-06-20T08:53:25.374747", + "exception": false, + "start_time": "2023-06-20T08:53:24.904398", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Display sample image\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "show_img( imgsa[ 5], vmin = .01, vmax = 10, logs=False, aspect=1, #save_format='tif',\n", + " image_name= uidstr + '_img_avg', save=True, path=data_dir, cmap=cmap_albula,center=center)\n", + "\n", + "_record_xpcs_cell_timing(\"46 - Display sample image\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.3e-05, + "end_time": "2023-06-20T08:53:25.377076", + "exception": false, + "start_time": "2023-06-20T08:53:25.377053", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Compress Data\n", + "* Generate a compressed data with filename\n", + "* Replace old mask with a new mask with removed hot pixels\n", + "* Do average image\n", + "* Do each image sum\n", + "* Find badframe_list for where image sum above bad_pixel_threshold\n", + "* Check shutter open frame to get good time series\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.195835, + "end_time": "2023-06-20T08:53:25.642595", + "exception": false, + "start_time": "2023-06-20T08:53:25.446760", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate photon occupancy\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "compress=True\n", + "photon_occ = len( np.where(avg_img)[0] ) / ( np.shape(imgsa[0])[0]*np.shape(imgsa[0])[1]*md['number of images'])\n", + "#compress = photon_occ < .4 #if the photon ocupation < 0.5, do compress\n", + "print (\"The non-zeros photon occupation is %s.\"%( photon_occ))\n", + "print(\"Will \" + 'Always ' + ['NOT', 'DO'][compress] + \" apply compress process.\")\n", + "\n", + "_record_xpcs_cell_timing(\"48 - Calculate photon occupancy\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.059335, + "end_time": "2023-06-20T08:53:25.703430", + "exception": false, + "start_time": "2023-06-20T08:53:25.644095", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Define good start\n", + "\n", + "if \"eiger4m\" in md['detector'] or md['detector'] == 'image': \n", + " good_start = 0 #make the good_start at least 0\n", + "elif (\"eiger500k\" in md['detector']) or (\"eiger500K\" in md['detector']): \n", + " good_start = 0#100 #5 #make the good_start at least 0\n", + "elif \"eiger1m\" in md['detector'] or md['detector'] == 'image': \n", + " good_start = 0 \n", + " \n", + "if bin_frame:\n", + " bin_frame_number=bin_frame_number\n", + " acquisition_period = md['acquire period']\n", + " timeperframe = acquisition_period * bin_frame_number\n", + "else:\n", + " bin_frame_number =1\n", + "print('first frame to be used: %s\\nframe binning: %s'%(good_start,bin_frame_number))" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.4e-05, + "end_time": "2023-06-20T08:53:25.835315", + "exception": false, + "start_time": "2023-06-20T08:53:25.835301", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### change compression behavior if necessary" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.067655, + "end_time": "2023-06-20T08:53:25.963892", + "exception": false, + "start_time": "2023-06-20T08:53:25.896237", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Set compression behavior\n", + "\n", + "#force_compress = False\n", + "#use_local_disk = True\n", + "print('force compression: %s use local disk: %s'%(force_compress,use_local_disk))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 19.133555, + "end_time": "2023-06-20T08:53:45.099043", + "exception": false, + "start_time": "2023-06-20T08:53:25.965488", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Compress detector data\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "imgs_=np.ones(md['number of images']) #just need to fake an array of appropriate length for the compression routine\n", + "\n", + "\n", + "# if not use_local_disk:\n", + "# cmp_path = '/nsls2/data/chx/legacy/Compressed_Data'\n", + "# else:\n", + "# cmp_path = '/tmp_data/compressed'\n", + "# print(here)\n", + " \n", + " \n", + "cmp_path = data_dir0[:-8] + 'Compressed_Data' \n", + "if bin_frame_number==1: \n", + " cmp_file = '/uid_%s.cmp'%md['uid']\n", + "else:\n", + " cmp_file = '/uid_%s_bined--%s.cmp'%(md['uid'],bin_frame_number)\n", + "\n", + "#force_compress = True\n", + "filename = cmp_path + cmp_file \n", + "mask2, avg_img, imgsum, bad_frame_list = compress_eigerdata(imgs_, det_mask, md, filename, ########## NEW: mask -> det_mask\n", + " force_compress= force_compress, para_compress= para_compress, bad_pixel_threshold = 1e14,\n", + " reverse=reverse, rot90=rot90, nobytes=4,\n", + " bins=bin_frame_number, num_sub= 100, num_max_para_process= 500, with_pickle=True,\n", + " direct_load_data =use_local_disk, data_path = data_fullpath, new_path = '/tmp/' ) \n", + " \n", + "min_inten = 10 \n", + "good_start = max(good_start, np.where( np.array(imgsum) > min_inten )[0][0] ) \n", + "print ('The good_start frame number is: %s '%good_start)\n", + "\n", + "FD = Multifile(filename, good_start, len(imgs_)//bin_frame_number )\n", + "\n", + "\n", + "uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + "print( uid_ )\n", + "plot1D( y = imgsum[ np.array( [i for i in np.arange(good_start, len(imgsum)) if i not in bad_frame_list])],\n", + " title =uidstr + '_imgsum', xlabel='Frame', ylabel='Total_Intensity', legend='imgsum' )\n", + "Nimg = int( md['number of images']/bin_frame_number )\n", + "\n", + "# mask2 = mask * pixel_mask * Chip_Mask\n", + "mask_copy = mask.copy()\n", + "mask_copy2 = mask.copy()\n", + "\n", + "#avg_img *= mask\n", + "\n", + "show_img( avg_img, vmin=1e-1, vmax= 1e2, logs=True, aspect=1, #save_format='tif',\n", + " image_name= uidstr + '_img_avg', save=True, \n", + " path=data_dir, center=center, cmap = cmap_albula )\n", + "\n", + "_record_xpcs_cell_timing(\"52 - Compress detector data\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Linking Raw data in 'rawdata' folder [folder needs to be created first]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Link raw data\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if(rawdata_link):\n", + " #data_fullpath - h5 file\n", + " #filename - cmp file\n", + " rawdata_folder = data_dir0[:-8]+'rawdata'\n", + " h5_linkname = rawdata_folder+'/'+cmp_file[:-4]+'.h5'\n", + " \n", + " #print('The raw data directory is: %s'%rawdata_folder)\n", + " #print('The hdf5 file is: %s'%data_fullpath)\n", + " #print('The cmp file is: %s'%filename[:])\n", + " #print('The h5 link name is: %s'%h5_linkname)\n", + " !ln -s {data_fullpath} {h5_linkname}\n", + " !ln -s {filename} {rawdata_folder+'/'}\n", + "\n", + "_record_xpcs_cell_timing(\"54 - Link raw data\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "tags": [] + }, + "outputs": [], + "source": [ + "# Update load/compression progress\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if track_progress:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='Load data and compress', progress='stop',start_time=None, stop_time=time.time(), verbose=True)\n", + " if settings_dict_['run_one_time']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='run_one_time', progress='start',start_time=time.time(), stop_time=None, verbose=True)\n", + "\n", + "_record_xpcs_cell_timing(\"55 - Update load/compression progress\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:45.101921", + "exception": false, + "start_time": "2023-06-20T08:53:45.101899", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Get bad frame list by a polynominal fit" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.071967, + "end_time": "2023-06-20T08:53:45.251004", + "exception": false, + "start_time": "2023-06-20T08:53:45.179037", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Set compressed-data range\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "good_end= None # 2000 \n", + "if good_end is not None:\n", + " FD = Multifile(filename, good_start, min( len(imgs_)//bin_frame_number, good_end) )\n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( uid_ )\n", + "\n", + "_record_xpcs_cell_timing(\"57 - Set compressed-data range\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.067784, + "end_time": "2023-06-20T08:53:45.324256", + "exception": false, + "start_time": "2023-06-20T08:53:45.256472", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Optional refine start frame\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "re_define_good_start =False\n", + "if re_define_good_start:\n", + " good_start = 180\n", + " #good_end = 19700\n", + " good_end = len(imgs_)\n", + " FD = Multifile(filename, good_start, good_end) \n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( FD.beg, FD.end)\n", + "\n", + "_record_xpcs_cell_timing(\"58 - Optionally redefine start frame\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.44143, + "end_time": "2023-06-20T08:53:45.767239", + "exception": false, + "start_time": "2023-06-20T08:53:45.325809", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Identify bad frames\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "bad_frame_list = get_bad_frame_list( imgsum, fit='both', plot=True,polyfit_order = 30, \n", + " scale= 3.5, good_start = good_start, good_end=good_end, uid= uidstr, path=data_dir)\n", + "\n", + "print( 'The bad frame list length is: %s'%len(bad_frame_list) )\n", + "\n", + "_record_xpcs_cell_timing(\"59 - Identify bad frames\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:45.769771", + "exception": false, + "start_time": "2023-06-20T08:53:45.769749", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Create new mask by masking the bad pixels and get new avg_img" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.069057, + "end_time": "2023-06-20T08:53:45.916919", + "exception": false, + "start_time": "2023-06-20T08:53:45.847862", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Save frame intensities\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "imgsum_y = imgsum[ np.array( [i for i in np.arange( len(imgsum)) if i not in bad_frame_list])]\n", + "imgsum_x = np.arange( len( imgsum_y))\n", + "save_lists( [imgsum_x, imgsum_y], label=['Frame', 'Total_Intensity'],\n", + " filename=uidstr + '_img_sum_t', path= data_dir )\n", + "print('number of bad pixels masked: %s'%len(imgsum_y))\n", + "\n", + "_record_xpcs_cell_timing(\"61 - Save frame intensities\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:53:45.920912", + "exception": false, + "start_time": "2023-06-20T08:53:45.920888", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Plot time~ total intensity of each frame" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.225016, + "end_time": "2023-06-20T08:53:46.212031", + "exception": false, + "start_time": "2023-06-20T08:53:45.987015", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot frame intensities\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "plot1D( y = imgsum_y, title = uidstr + '_img_sum_t', xlabel='Frame', c='b',\n", + " ylabel='Total_Intensity', legend='imgsum', save=True, path=data_dir)\n", + "\n", + "_record_xpcs_cell_timing(\"63 - Plot frame intensities\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.1e-05, + "end_time": "2023-06-20T08:53:46.214725", + "exception": false, + "start_time": "2023-06-20T08:53:46.214704", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Get Dynamic Mask (currently designed for 500K)" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.8e-05, + "end_time": "2023-06-20T08:53:46.289744", + "exception": false, + "start_time": "2023-06-20T08:53:46.289726", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# NEED ALL Detectors! There are 3 bit-depth levels!\n", + "### check Dectris documentation: 16/8/4 bit(?)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.067637, + "end_time": "2023-06-20T08:53:46.423218", + "exception": false, + "start_time": "2023-06-20T08:53:46.355581", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Build dynamic detector mask\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if \"eiger4m\" in md['detector'] or md['detector'] == 'image': \n", + " pass\n", + "elif (\"eiger500k\" in md['detector']) or (\"eiger500K\" in md['detector']): \n", + " if md['eiger500K_single_cam_acquire_period'] <= 0.00015: #will check this logic\n", + " if imgs[0].dtype == 'uint8':\n", + " print('Create dynamic mask for 500K due to 9K data acquistion!!!')\n", + " #bdp = find_bad_pixels_FD( bad_frame_list, FD, img_shape = avg_img.shape, threshold= 15 ) \n", + " bdp = find_bad_pixels_FD( np.arange(Nimg), FD, img_shape = avg_img.shape, threshold= 15 ) \n", + " mask = mask_copy2.copy()\n", + " mask *=bdp \n", + " mask_copy = mask.copy()\n", + " show_img( np.array(mask,dtype=int), image_name='New Mask_uid=%s'%uid, aspect=1 )\n", + "\n", + "_record_xpcs_cell_timing(\"66 - Build dynamic detector mask\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.9e-05, + "end_time": "2023-06-20T08:53:46.423875", + "exception": false, + "start_time": "2023-06-20T08:53:46.423856", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## SAXS Scattering Geometry" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.065967, + "end_time": "2023-06-20T08:53:46.625511", + "exception": false, + "start_time": "2023-06-20T08:53:46.559544", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Setup center args\n", + "\n", + "setup_pargs['center'] = center[::-1]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 1.376382, + "end_time": "2023-06-20T08:53:48.007758", + "exception": false, + "start_time": "2023-06-20T08:53:46.631376", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate SAXS circular average\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='saxs':\n", + " outlier_threshold = 5.5 # change here, if necessary\n", + " maximum_outlier_fraction = .1\n", + " \n", + " roi_mask = roi_mask2.copy()\n", + " ## Get circular average| * Do plot and save q~iq\n", + " mask = mask_copy.copy()\n", + " hmask = create_hot_pixel_mask( avg_img, threshold = 2e8, center=center, center_radius= 100)\n", + " mask =np.array( mask * hmask, dtype=bool)\n", + " \n", + " if mask_outliers:\n", + " hhmask = outlier_mask(avg_img,mask,roi_mask,outlier_threshold = outlier_threshold, maximum_outlier_fraction = maximum_outlier_fraction,verbose=False,plot=False)\n", + " mask =np.array( mask * hhmask, dtype=bool)\n", + " \n", + " qp_saxs, iq_saxs, q_saxs = get_circular_average( avg_img * det_mask , mask * hmask, save=True,\n", + " #qp_saxs, iq_saxs, q_saxs = get_circular_average( avg_img * det_mask*mask , mask, save=True,\n", + " pargs=setup_pargs )\n", + " plot_circular_average( qp_saxs, iq_saxs, q_saxs, pargs=setup_pargs, show_pixel=True,\n", + " xlim=[qp_saxs.min(), qp_saxs.max()*1.0], ylim = [iq_saxs.min(), iq_saxs.max()*2] )\n", + " \n", + " print('Removed %s hot pixels.'%len(np.nonzero(hmask-1)[0]))\n", + " roi_mask = roi_mask * mask\n", + "\n", + "_record_xpcs_cell_timing(\"69 - Calculate SAXS circular average\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 2.431654, + "end_time": "2023-06-20T08:53:50.439550", + "exception": false, + "start_time": "2023-06-20T08:53:48.007896", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Validate and plot SAXS ROIs\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='saxs': \n", + " qr = np.array( [qval_dict[k][0] for k in sorted( qval_dict.keys())] )\n", + " if qphi_analysis == False:\n", + " try:\n", + " qr_cal, qr_wid = get_QrQw_From_RoiMask( roi_mask, setup_pargs ) \n", + " print(len(qr)) \n", + " if (qr_cal - qr).sum() >=1e-3:\n", + " print( 'The loaded ROI mask might not be applicable to this UID: %s.'%uid)\n", + " print('Please check the loaded roi mask file.')\n", + " except:\n", + " print('Something is wrong with the roi-mask. Please check the loaded roi mask file.') \n", + " \n", + " \n", + " show_ROI_on_image( avg_img*roi_mask, roi_mask, center, label_on = False, rwidth = 600, alpha=.9, \n", + " save=True, path=data_dir, uid=uidstr, vmin= 1e-1,\n", + " vmax= 1e3, #np.max(avg_img),\n", + " aspect=1,\n", + " show_roi_edge=True, \n", + " show_ang_cor = True) \n", + " plot_qIq_with_ROI( q_saxs, iq_saxs, np.unique(qr), logs=True, uid=uidstr, \n", + " xlim=[q_saxs.min(), q_saxs.max()*1.02],#[0.0001,0.08],\n", + " ylim = [iq_saxs.min(), iq_saxs.max()*1.02], save=True, path=data_dir)\n", + "\n", + "_record_xpcs_cell_timing(\"70 - Validate and plot SAXS ROIs\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:53:50.443489", + "exception": false, + "start_time": "2023-06-20T08:53:50.443467", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Time Depedent I(q) Analysis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Calculate time-dependent I(q)\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='saxs':\n", + " slice_num=3\n", + " slice_width=2\n", + " Nimg = FD.end - FD.beg \n", + " time_edge = create_time_slice( Nimg, slice_num=slice_num, slice_width=slice_width, edges = None )\n", + " time_edge = np.array( time_edge ) + good_start \n", + " if slice_num*slice_width >10: # doing circular average from sparsified data\n", + " qpt, iqst, qt = get_t_iqc( FD, time_edge, mask*det_mask, pargs=setup_pargs, nx=1500, show_progress= False )\n", + " else: # if we only need a few images, circular average from dask.array is faster\n", + " qpt, iqst, qt = get_t_iqc_imstack( imgs, time_edge, mask*det_mask, pargs=setup_pargs, nx=1500, show_progress= False )\n", + " plot_t_iqc( qt, iqst, time_edge, pargs=setup_pargs, xlim=[qt.min(), qt.max()],\n", + " ylim = [iqst.min(), iqst.max()], save=True )\n", + "\n", + "_record_xpcs_cell_timing(\"72 - Calculate time-dependent I(q)\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.1e-05, + "end_time": "2023-06-20T08:53:52.730777", + "exception": false, + "start_time": "2023-06-20T08:53:52.730756", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## For fit one peak" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.071287, + "end_time": "2023-06-20T08:53:52.881893", + "exception": false, + "start_time": "2023-06-20T08:53:52.810606", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Fit SAXS peak\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='saxs':\n", + " if fit_peak: \n", + " q1 = 0.162\n", + " x = q_saxs\n", + " y= iq_saxs\n", + " aind = [ find_index( q_saxs, q1 ) ]\n", + " w = 50\n", + " xrange = [ aind[0] -w, aind[0] + w] \n", + " cen, cen_std, wid, wid_std, xf, out = fit_one_peak_curve( x, y, xrange ) \n", + " fp = data_dir + uidstr + '_qIq_fit.png' \n", + " ax = plot_xy_with_fit( x, y, xf, out, cen, cen_std,wid, wid_std,\n", + " xlim=[0.01,0.3],xlabel= 'q ('r'$\\AA^{-1}$)',\n", + " ylabel='I(q)', filename=fp)\n", + "\n", + "_record_xpcs_cell_timing(\"74 - Fit SAXS peak\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.073766, + "end_time": "2023-06-20T08:53:52.961597", + "exception": false, + "start_time": "2023-06-20T08:53:52.887831", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate scattering invariant\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_invariant_analysis:\n", + " if scat_geometry =='saxs':\n", + " invariant = get_iq_invariant( qt, iqst )\n", + " time_stamp = time_edge[:,0] * timeperframe\n", + "\n", + " if scat_geometry =='saxs':\n", + " plot_q2_iq( qt, iqst, time_stamp,pargs=setup_pargs,ylim=[ -0.001, 0.01] , \n", + " xlim=[0.007,0.2],legend_size= 6 )\n", + "\n", + " if scat_geometry =='saxs':\n", + " plot_time_iq_invariant( time_stamp, invariant, pargs=setup_pargs, )\n", + "\n", + " if False:\n", + " iq_int = np.zeros( len(iqst) )\n", + " fig, ax = plt.subplots()\n", + " q = qt\n", + " for i in range(iqst.shape[0]):\n", + " yi = iqst[i] * q**2\n", + " iq_int[i] = yi.sum()\n", + " time_labeli = 'time_%s s'%( round( time_edge[i][0] * timeperframe, 3) )\n", + " plot1D( x = q, y = yi, legend= time_labeli, xlabel='Q (A-1)', ylabel='I(q)*Q^2', title='I(q)*Q^2 ~ time',\n", + " m=markers[i], c = colors[i], ax=ax, ylim=[ -0.001, 0.01] , xlim=[0.007,0.2],\n", + " legend_size=4)\n", + "\n", + " #print( iq_int )\n", + "\n", + "_record_xpcs_cell_timing(\"75 - Calculate scattering invariant\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.7e-05, + "end_time": "2023-06-20T08:53:52.964961", + "exception": false, + "start_time": "2023-06-20T08:53:52.964934", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# GiSAXS Scattering Geometry" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.052256, + "end_time": "2023-06-20T08:53:53.088428", + "exception": false, + "start_time": "2023-06-20T08:53:53.036172", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot GISAXS q map\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='gi_saxs': \n", + " plot_qzr_map( qr_map, qz_map, inc_x0, ticks = ticks, data= avg_img, uid= uidstr, path = data_dir )\n", + "\n", + "_record_xpcs_cell_timing(\"77 - Plot GISAXS q map\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.9e-05, + "end_time": "2023-06-20T08:53:53.116316", + "exception": false, + "start_time": "2023-06-20T08:53:53.116287", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Static Analysis for gisaxs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.081684, + "end_time": "2023-06-20T08:53:53.277810", + "exception": false, + "start_time": "2023-06-20T08:53:53.196126", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot static GISAXS ROIs\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='gi_saxs': \n", + " #roi_masks, qval_dicts = get_gisaxs_roi( Qrs, Qzs, qr_map, qz_map, mask= mask )\n", + " show_qzr_roi( avg_img, roi_masks, inc_x0, ticks[:4], alpha=0.5, save=True, path=data_dir, uid=uidstr )\n", + "\n", + "_record_xpcs_cell_timing(\"79 - Plot static GISAXS ROIs\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.068521, + "end_time": "2023-06-20T08:53:53.349071", + "exception": false, + "start_time": "2023-06-20T08:53:53.280550", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate time-dependent GISAXS profiles\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='gi_saxs': \n", + " Nimg = FD.end - FD.beg \n", + " time_edge = create_time_slice( N= Nimg, slice_num= 3, slice_width= 2, edges = None )\n", + " time_edge = np.array( time_edge ) + good_start\n", + " print( time_edge ) \n", + " qrt_pds = get_t_qrc( FD, time_edge, Qrs, Qzs, qr_map, qz_map, mask=mask, path=data_dir, uid = uidstr ) \n", + " plot_qrt_pds( qrt_pds, time_edge, qz_index = 0, uid = uidstr, path = data_dir )\n", + "\n", + "_record_xpcs_cell_timing(\"80 - Calculate time-dependent GISAXS profiles\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.1e-05, + "end_time": "2023-06-20T08:53:53.353582", + "exception": false, + "start_time": "2023-06-20T08:53:53.353561", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Make a Profile Plot" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.068581, + "end_time": "2023-06-20T08:53:53.493133", + "exception": false, + "start_time": "2023-06-20T08:53:53.424552", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate GISAXS waterfall\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='gi_saxs':\n", + " if run_profile_plot:\n", + " xcorners= [ 1100, 1250, 1250, 1100 ]\n", + " ycorners= [ 850, 850, 950, 950 ] \n", + " waterfall_roi_size = [ xcorners[1] - xcorners[0], ycorners[2] - ycorners[1] ]\n", + " waterfall_roi = create_rectangle_mask( avg_img, xcorners, ycorners )\n", + " #show_img( waterfall_roi * avg_img, aspect=1,vmin=.001, vmax=1, logs=True, )\n", + " wat = cal_waterfallc( FD, waterfall_roi, qindex= 1, bin_waterfall=True,\n", + " waterfall_roi_size = waterfall_roi_size,save =True, path=data_dir, uid=uidstr)\n", + "\n", + "_record_xpcs_cell_timing(\"82 - Calculate GISAXS waterfall\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.070595, + "end_time": "2023-06-20T08:53:53.568310", + "exception": false, + "start_time": "2023-06-20T08:53:53.497715", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot GISAXS waterfall\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='gi_saxs':\n", + " if run_profile_plot:\n", + " plot_waterfallc( wat, qindex=1, aspect=None, vmin=1, vmax= np.max( wat), uid=uidstr, save =True, \n", + " path=data_dir, beg= FD.beg)\n", + "\n", + "_record_xpcs_cell_timing(\"83 - Plot GISAXS waterfall\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.9e-05, + "end_time": "2023-06-20T08:53:53.570297", + "exception": false, + "start_time": "2023-06-20T08:53:53.570278", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Dynamic Analysis for gi_saxs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.068646, + "end_time": "2023-06-20T08:53:53.712641", + "exception": false, + "start_time": "2023-06-20T08:53:53.643995", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate GISAXS 1D profile\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='gi_saxs': \n", + " show_qzr_roi( avg_img, roi_mask, inc_x0, ticks[:4], alpha=0.5, save=True, path=data_dir, uid=uidstr ) \n", + " ## Get 1D Curve (Q||-intensity¶)\n", + " qr_1d_pds = cal_1d_qr( avg_img, Qr, Qz, qr_map, qz_map, inc_x0= None, mask=mask, setup_pargs=setup_pargs )\n", + " plot_qr_1d_with_ROI( qr_1d_pds, qr_center=np.unique( np.array(list( qval_dict.values() ) )[:,0] ),\n", + " loglog=True, save=True, uid=uidstr, path = data_dir)\n", + "\n", + "_record_xpcs_cell_timing(\"85 - Calculate GISAXS 1D profile\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.7e-05, + "end_time": "2023-06-20T08:53:53.720709", + "exception": false, + "start_time": "2023-06-20T08:53:53.720682", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# GiWAXS Scattering Geometry" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.068797, + "end_time": "2023-06-20T08:53:53.860284", + "exception": false, + "start_time": "2023-06-20T08:53:53.791487", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot GIWAXS ROIs\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if scat_geometry =='gi_waxs':\n", + " show_ROI_on_image( avg_img, roi_mask, label_on = True, alpha=.5,\n", + " save=True, path=data_dir, uid=uidstr, vmin=0.1, vmax=500)\n", + "\n", + "_record_xpcs_cell_timing(\"87 - Plot GIWAXS ROIs\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.7e-05, + "end_time": "2023-06-20T08:53:53.867728", + "exception": false, + "start_time": "2023-06-20T08:53:53.867701", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "* Extract the labeled array" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.184571, + "end_time": "2023-06-20T08:53:54.121427", + "exception": false, + "start_time": "2023-06-20T08:53:53.936856", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Extract ROI pixel labels\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "qind, pixelist = roi.extract_label_indices(roi_mask)\n", + "noqs = len(np.unique(qind))\n", + "print('calculating correlation functions for %s Qs'%noqs)\n", + "\n", + "_record_xpcs_cell_timing(\"89 - Extract ROI pixel labels\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1e-05, + "end_time": "2023-06-20T08:53:54.121592", + "exception": false, + "start_time": "2023-06-20T08:53:54.121582", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "* Number of pixels in each q box" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.258516, + "end_time": "2023-06-20T08:53:54.467645", + "exception": false, + "start_time": "2023-06-20T08:53:54.209129", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot ROI pixel counts\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "nopr = np.bincount(qind, minlength=(noqs+1))[1:]\n", + "roi_x = range(len(nopr))\n", + "plt.semilogy(roi_x,nopr,'ro',fillstyle='none');plt.xlabel('ROI #');plt.ylabel('number of pixels in ROI')\n", + "\n", + "_record_xpcs_cell_timing(\"91 - Plot ROI pixel counts\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 1.3e-05, + "end_time": "2023-06-20T08:53:54.467774", + "exception": false, + "start_time": "2023-06-20T08:53:54.467761", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Check one ROI intensity" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.514916, + "end_time": "2023-06-20T08:53:55.063776", + "exception": false, + "start_time": "2023-06-20T08:53:54.548860", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Check ROI intensity\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "roi_inten = check_ROI_intensity( avg_img, roi_mask, ring_number= 5, uid =uidstr ) #roi starting from 1\n", + "\n", + "_record_xpcs_cell_timing(\"93 - Check ROI intensity\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.3e-05, + "end_time": "2023-06-20T08:53:55.066661", + "exception": false, + "start_time": "2023-06-20T08:53:55.066638", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Do a waterfall analysis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.06989, + "end_time": "2023-06-20T08:53:55.215259", + "exception": false, + "start_time": "2023-06-20T08:53:55.145369", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate waterfall analysis\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "qth_interest = 2 #the second ring. #qth_interest starting from 1\n", + "if scat_geometry =='saxs' or scat_geometry =='gi_waxs' or scat_geometry == 'gi_saxs':\n", + " if run_waterfall: \n", + " wat = cal_waterfallc( FD, roi_mask, qindex= qth_interest, save =True, path=data_dir, uid=uidstr)\n", + " plot_waterfallc( wat, qth_interest, aspect= None, vmin=1e-1, vmax= wat.max(), uid=uidstr, save =True, \n", + " path=data_dir, beg= FD.beg, cmap = cmap_vge )\n", + "\n", + "_record_xpcs_cell_timing(\"95 - Calculate waterfall analysis\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 4.682422, + "end_time": "2023-06-20T08:53:59.904224", + "exception": false, + "start_time": "2023-06-20T08:53:55.221802", + "status": "completed" + }, + "scrolled": true, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate ROI intensities over time\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "ring_avg = None \n", + "if run_t_ROI_Inten:\n", + " times_roi, mean_int_sets = cal_each_ring_mean_intensityc(FD, roi_mask, timeperframe = None, multi_cor= False )\n", + " mean_int_setsF = np.zeros( [FD.end, mean_int_sets.shape[1] ] )\n", + " mean_int_setsF[FD.beg:FD.end] =mean_int_sets\n", + " plot_each_ring_mean_intensityc( times_roi, mean_int_sets, uid = uidstr, save=True, path=data_dir )\n", + " roi_avg = np.average( mean_int_sets, axis=0)\n", + "\n", + "_record_xpcs_cell_timing(\"96 - Calculate ROI intensities over time\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:53:59.909109", + "exception": false, + "start_time": "2023-06-20T08:53:59.909084", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Analysis for mass center of reflective beam center" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.076743, + "end_time": "2023-06-20T08:54:00.072146", + "exception": false, + "start_time": "2023-06-20T08:53:59.995403", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate ROI mass center\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_get_mass_center:\n", + " cx, cy = get_mass_center_one_roi(FD, roi_mask, roi_ind=25)\n", + " fig,ax=plt.subplots(2)\n", + " plot1D( cx, m='o', c='b',ax=ax[0], legend='mass center-refl_X', \n", + " ylim=[940, 960], ylabel='posX (pixel)')\n", + " plot1D( cy, m='s', c='r',ax=ax[1], legend='mass center-refl_Y', \n", + " ylim=[1540, 1544], xlabel='frames',ylabel='posY (pixel)')\n", + "\n", + "_record_xpcs_cell_timing(\"98 - Calculate ROI mass center\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:54:00.077918", + "exception": false, + "start_time": "2023-06-20T08:54:00.077893", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## One time Correlation\n", + "\n", + "Note : Enter the number of buffers for Muliti tau one time correlation\n", + "number of buffers has to be even. More details in https://github.com/scikit-beam/scikit-beam/blob/master/skbeam/core/correlation.py" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.8e-05, + "end_time": "2023-06-20T08:54:00.154143", + "exception": false, + "start_time": "2023-06-20T08:54:00.154115", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### if define another good_series" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.076908, + "end_time": "2023-06-20T08:54:00.306452", + "exception": false, + "start_time": "2023-06-20T08:54:00.229544", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Select one-time correlation range\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "good_start_g2 = FD.beg\n", + "good_end_g2 = FD.end\n", + "define_good_series = False\n", + "hdf5_name_extension=''\n", + "if 'rstop' in locals() or 'rstart' in locals():\n", + " define_good_series = True\n", + "if define_good_series:\n", + " if 'rstart' in locals():\n", + " good_start_g2 = rstart\n", + " if 'rstop' in locals():\n", + " good_end_g2 = rstop\n", + " hdf5_name_extension = '_%s_%s'%(good_start_g2,good_end_g2)\n", + " FD = Multifile(filename, beg = good_start_g2, end = good_end_g2) #end=1000)\n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( uid_ )\n", + "\n", + "_record_xpcs_cell_timing(\"101 - Select one-time correlation range\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.295086, + "end_time": "2023-06-20T08:54:00.604436", + "exception": false, + "start_time": "2023-06-20T08:54:00.309350", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Build correlation normalization\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if use_sqnorm:#for transmision SAXS\n", + " norm = get_pixelist_interp_iq( qp_saxs, iq_saxs, roi_mask, setup_pargs['center'])\n", + " print('Using circular average in the normalization of G2 for SAXS scattering.')\n", + "elif use_SG:#for Gi-SAXS or WAXS\n", + " avg_imgf = sgolay2d( avg_img, window_size= 11, order= 5) * mask\n", + " norm=np.ravel(avg_imgf)[pixelist] \n", + " print('Using smoothed image by SavitzkyGolay filter in the normalization of G2.') \n", + "elif use_SG_bin_frames:#for Gi-SAXS or WAXS\n", + " avg_imgf = sgolay2d( avg_img, window_size= 11, order= 5) * mask\n", + " norm_avg=np.ravel(avg_imgf)[pixelist] \n", + " #print('Using smoothed image by SavitzkyGolay filter in the normalization of G2.')\n", + " bins_number = 1 \n", + " norm = get_SG_norm( FD, pixelist, bins=bins_number, mask=mask, window_size= 11, order=5 ) \n", + " print('Using smoothed bined: %s frames by SavitzkyGolay filter in the normalization of G2.'%bins_number) \n", + "else: \n", + " norm= None\n", + " print('Using simple (average) normalization of G2.') \n", + "\n", + "if use_imgsum_norm:\n", + " imgsum_ = imgsum\n", + " print('Using frame total intensity for intensity normalization in g2 calculation.') \n", + "else:\n", + " imgsum_ = None\n", + "\n", + "_record_xpcs_cell_timing(\"102 - Build correlation normalization\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 76.981197, + "end_time": "2023-06-20T08:55:17.588517", + "exception": false, + "start_time": "2023-06-20T08:54:00.607320", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate one-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_one_time: \n", + " if cal_g2_error: \n", + " g2,lag_steps,g2_err = cal_g2p(FD,roi_mask,bad_frame_list,good_start, num_buf = 8,\n", + " num_lev= None,imgsum= imgsum_, norm=norm, cal_error= True )\n", + " else: \n", + " g2,lag_steps = cal_g2p(FD,roi_mask,bad_frame_list,good_start, num_buf = 8,\n", + " num_lev= None,imgsum= imgsum_, norm=norm, cal_error= False )\n", + "\n", + "_record_xpcs_cell_timing(\"103 - Calculate one-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.051688, + "end_time": "2023-06-20T08:55:17.642066", + "exception": false, + "start_time": "2023-06-20T08:55:17.590378", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Save one-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_one_time:\n", + " \n", + " taus = lag_steps * timeperframe \n", + " try:\n", + " g2_pds = save_g2_general( g2, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0],\n", + " qz = np.array( list( qval_dict.values() ) )[:g2.shape[1],1],\n", + " uid=uid_+'_g2.csv', path= data_dir, return_res=True )\n", + " except:\n", + " g2_pds = save_g2_general( g2, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0], \n", + " uid=uid_+'_'+q_mask_name+'_g2.csv', path= data_dir, return_res=True ) \n", + " if cal_g2_error: \n", + " try:\n", + " g2_err_pds = save_g2_general( g2_err, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0],\n", + " qz = np.array( list( qval_dict.values() ) )[:g2.shape[1],1],\n", + " uid=uid_+'_g2_err.csv', path= data_dir, return_res=True )\n", + " except:\n", + " g2_err_pds = save_g2_general( g2_err, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0], \n", + " uid=uid_+'_'+q_mask_name+'_g2_err.csv', path= data_dir, return_res=True )\n", + "\n", + "_record_xpcs_cell_timing(\"104 - Save one-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.3e-05, + "end_time": "2023-06-20T08:55:17.707341", + "exception": false, + "start_time": "2023-06-20T08:55:17.707318", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Fit g2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.163419, + "end_time": "2023-06-20T08:55:17.958540", + "exception": false, + "start_time": "2023-06-20T08:55:17.795121", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Fit one-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_one_time:\n", + " try:\n", + " g2_fit_result, taus_fit, g2_fit = get_g2_fit_general( g2, taus, \n", + " function = fit_g2_func, vlim=[0.95, 1.05], fit_range= None, \n", + " fit_variables={'baseline':False, 'beta': True, 'alpha':True,'relaxation_rate':True,}, \n", + " guess_values={'baseline':1.0,'beta': 0.2,'alpha':1.0,'relaxation_rate':1e-3},\n", + " guess_limits = dict( baseline =[.9, 2], alpha=[0, 2],\n", + " beta = [0.01, 0.4], relaxation_rate= [1e-7, 1e7]) ,) \n", + " g2_fit_paras = save_g2_fit_para_tocsv(g2_fit_result, filename= uid_ +'_'+q_mask_name +'_g2_fit_paras.csv', path=data_dir ) \n", + " g2_fit_failed = False\n", + " except:\n", + " g2_fit_failed = True\n", + " from pandas import DataFrame # need to make up a fit result, otherwise writing the pdf report becomes difficult\n", + " g2_fit_paras=DataFrame(np.zeros([np.shape(g2)[1],4]),columns=['beta','relaxation_rate','alpha','baseline'])\n", + "\n", + "_record_xpcs_cell_timing(\"106 - Fit one-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 10.75033, + "end_time": "2023-06-20T08:55:28.711559", + "exception": false, + "start_time": "2023-06-20T08:55:17.961229", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot one-time correlation fit\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_one_time:\n", + " if cal_g2_error:\n", + " g2_fit_err = np.zeros_like(g2_fit)\n", + " if not g2_fit_failed:\n", + " \n", + " plot_g2_general( g2_dict={1:g2, 2:g2_fit}, taus_dict={1:taus, 2:taus_fit},\n", + " vlim=[0.95, 1.05], g2_err_dict= {1:g2_err, 2: g2_fit_err},\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= g2_fit_result, geometry= scat_geometry_,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '_fit',\n", + " qpi_analysis=True)\n", + " else:\n", + " plot_g2_general(g2_dict={1:g2, }, taus_dict={1:taus,},\n", + " vlim=[0.95, 1.05], g2_err_dict= {1:g2_err},\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])),\n", + " fit_res= None, geometry= scat_geometry_,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '',\n", + " qpi_analysis=True)\n", + " \n", + " else: \n", + " if not g2_fit_failed:\n", + " plot_g2_general( g2_dict={1:g2, 2:g2_fit}, taus_dict={1:taus, 2:taus_fit}, vlim=[0.95, 1.05],\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= g2_fit_result, geometry= scat_geometry_,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '_fit',\n", + " qpi_analysis=True)\n", + " else: \n", + " plot_g2_general( g2_dict={1:g2}, taus_dict={1:taus}, vlim=[0.95, 1.05],\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= None, geometry= scat_geometry_,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '',\n", + " qpi_analysis=True)\n", + "\n", + "_record_xpcs_cell_timing(\"107 - Plot one-time correlation fit\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.234143, + "end_time": "2023-06-20T08:55:28.948579", + "exception": false, + "start_time": "2023-06-20T08:55:28.714436", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Analyze one-time relaxation rates\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_one_time:\n", + " try:\n", + " if True:\n", + " fs, fe = 0, 6\n", + " #fs,fe=0, 6\n", + " qval_dict_ = {k:qval_dict[k] for k in list(qval_dict.keys())[fs:fe] }\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict_, g2_fit_paras['relaxation_rate'][fs:fe], \n", + " geometry= scat_geometry_ )\n", + " plot_q_rate_fit_general( qval_dict_, g2_fit_paras['relaxation_rate'][fs:fe], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ , path= data_dir )\n", + " elif False:\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict, g2_fit_paras['relaxation_rate'],\n", + " fit_range=[0, 26], geometry= scat_geometry_ ) \n", + " plot_q_rate_fit_general( qval_dict, g2_fit_paras['relaxation_rate'], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ ,\n", + " show_fit=False, path= data_dir, plot_all_range=False) \n", + " else:\n", + " ##plot log_q, log_rate\n", + " plot_q_rate_general( qval_dict, g2_fit_paras['relaxation_rate'], \n", + " geometry= scat_geometry_,uid=uid_ , path= data_dir )\n", + "\n", + " plot_q_g2fitpara_general( qval_dict, g2_fit_paras, \n", + " geometry= scat_geometry_,uid=uid_ , path= data_dir )\n", + " except:\n", + " pass\n", + "\n", + "_record_xpcs_cell_timing(\"108 - Analyze one-time relaxation rates\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Update one-time progress\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if track_progress:\n", + " if settings_dict_['run_one_time']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='run_one_time', progress='stop',start_time=None, stop_time=time.time(), verbose=True)\n", + " if settings_dict_['run_two_time']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='run_two_time', progress='start',start_time=time.time(), stop_time=None, verbose=True)\n", + "\n", + "_record_xpcs_cell_timing(\"109 - Update one-time progress\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2e-05, + "end_time": "2023-06-20T08:55:28.951373", + "exception": false, + "start_time": "2023-06-20T08:55:28.951353", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# For two-time" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.09029, + "end_time": "2023-06-20T08:55:29.141606", + "exception": false, + "start_time": "2023-06-20T08:55:29.051316", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Select two-time correlation range\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "define_good_series = True #making sure that the 2TCF takes ALL data into account -> this should be the default!\n", + "if define_good_series:\n", + " good_start = 0\n", + " good_end =md['number of images']\n", + " FD = Multifile(filename, beg = good_start, end = good_end)\n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( uid_ )\n", + "\n", + "_record_xpcs_cell_timing(\"111 - Select two-time correlation range\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 4.251569, + "end_time": "2023-06-20T08:55:33.393743", + "exception": false, + "start_time": "2023-06-20T08:55:29.142174", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Load two-time pixel data\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "data_pixel = None\n", + "if run_two_time: \n", + " data_pixel = Get_Pixel_Arrayc( FD, pixelist, norm= norm, ).get_data()\n", + " \n", + " ### With another normalizaiton by using roi_intensity for each frame\n", + " #data_pixel = Get_Pixel_Arrayc( FD, pixelist, norm= norm, mean_int_sets = mean_int_setsF,qind=qind ).get_data()\n", + "\n", + "_record_xpcs_cell_timing(\"112 - Load two-time pixel data\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 11.132962, + "end_time": "2023-06-20T08:55:44.530064", + "exception": false, + "start_time": "2023-06-20T08:55:33.397102", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate two-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "g12b=None\n", + "if run_two_time: \n", + " g12b = auto_two_Arrayc( data_pixel, roi_mask, index = None )\n", + " if run_dose:\n", + " np.save( data_dir + 'uid=%s_g12b'%uid, g12b)\n", + "\n", + "_record_xpcs_cell_timing(\"113 - Calculate two-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.500428, + "end_time": "2023-06-20T08:55:45.031827", + "exception": false, + "start_time": "2023-06-20T08:55:44.531399", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot two-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_two_time:\n", + " \n", + " show_C12( g12b , q_ind= 6, qlabel=dict(itertools.islice(qval_dict.items(),g12b.shape[2])),\n", + " #N1= FD.beg,logs=False, N2=min( FD.end,10000), \n", + " vmin= 1.00, vmax=1.25, timeperframe=timeperframe,save=True, \n", + " path= data_dir, uid = uid_ ,cmap=plt.cm.jet)#cmap=cmap_albula)\n", + "\n", + "_record_xpcs_cell_timing(\"114 - Plot two-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.119291, + "end_time": "2023-06-20T08:55:45.152574", + "exception": false, + "start_time": "2023-06-20T08:55:45.033283", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Derive one-time correlation from two-time data\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "multi_tau_steps = True\n", + "if run_two_time:\n", + " if lag_steps is None:\n", + " num_bufs=8\n", + " noframes = FD.end - FD.beg\n", + " num_levels = int(np.log( noframes/(num_bufs-1))/np.log(2) +1) +1\n", + " tot_channels, lag_steps, dict_lag = multi_tau_lags(num_levels, num_bufs)\n", + " max_taus= lag_steps.max()\n", + " \n", + " #max_taus= lag_steps.max() \n", + " max_taus = Nimg \n", + " #tausb = np.arange( g2b.shape[0])[:max_taus] *timeperframe\n", + " if multi_tau_steps:\n", + " lag_steps_ = lag_steps[ lag_steps <= g12b.shape[0] ]\n", + " g2b = get_one_time_from_two_time(g12b)[lag_steps_]\n", + " tausb = lag_steps_ *timeperframe\n", + " else:\n", + " tausb = (np.arange( g12b.shape[0]) *timeperframe)[:-200]\n", + " g2b = (get_one_time_from_two_time(g12b))[:-200]\n", + " \n", + " g2b_pds = save_g2_general( g2b, taus=tausb, qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0],\n", + " qz=None, uid=uid_+'_'+q_mask_name+'_g2b.csv', path= data_dir, return_res=True )\n", + "\n", + "_record_xpcs_cell_timing(\"115 - Derive one-time correlation from two-time data\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.336093, + "end_time": "2023-06-20T08:55:45.495206", + "exception": false, + "start_time": "2023-06-20T08:55:45.159113", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Fit derived correlations\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_two_time: \n", + " try: \n", + " g2b_fit_result, tausb_fit, g2b_fit = get_g2_fit_general( g2b, tausb, \n", + " function = fit_g2_func, vlim=[0.95, 1.05], fit_range= None, \n", + " fit_variables={'baseline':False, 'beta': True, 'alpha':True,'relaxation_rate':True}, \n", + " guess_values={'baseline':1.0,'beta': 0.15,'alpha':1.0,'relaxation_rate':1e-3,},\n", + " guess_limits = dict( baseline =[1, 1.8], alpha=[0, 2],\n", + " beta = [0, 1], relaxation_rate= [1e-8, 5000]) ) \n", + " g2b_fit_paras = save_g2_fit_para_tocsv(g2b_fit_result, filename= uid_ +'_'+q_mask_name+'_g2b_fit_paras.csv', path=data_dir )\n", + " g2b_fit_failed = False\n", + " except:\n", + " g2b_fit_failed = True\n", + " g2b_fit_paras = g2_fit_paras * 0\n", + "\n", + "_record_xpcs_cell_timing(\"116 - Fit derived correlations\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 11.971538, + "end_time": "2023-06-20T08:55:57.468178", + "exception": false, + "start_time": "2023-06-20T08:55:45.496640", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot derived correlation fit\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_two_time:\n", + " if not g2b_fit_failed:\n", + " plot_g2_general( g2_dict={1:g2b, 2:g2b_fit}, taus_dict={1:tausb, 2:tausb_fit}, vlim=[0.95, 1.05],\n", + " qval_dict=dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= g2b_fit_result, geometry=scat_geometry_,filename=uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '_b_fit')\n", + " else:\n", + " plot_g2_general( g2_dict={1:g2b,}, taus_dict={1:tausb, }, vlim=[0.95, 1.05],\n", + " qval_dict=dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= None,\n", + " geometry=scat_geometry_,filename=uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '')\n", + "\n", + "_record_xpcs_cell_timing(\"117 - Plot derived correlation fit\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.054888, + "end_time": "2023-06-20T08:55:57.524735", + "exception": false, + "start_time": "2023-06-20T08:55:57.469847", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Fit derived relaxation rates\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_two_time and not g2b_fit_failed :\n", + " D0b, qrate_fit_resb = get_q_rate_fit_general( dict(itertools.islice(qval_dict.items(),g2.shape[1])), g2b_fit_paras['relaxation_rate'],\n", + " fit_range=[0, 10], geometry= scat_geometry_ )\n", + "\n", + "_record_xpcs_cell_timing(\"118 - Fit derived relaxation rates\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.245365, + "end_time": "2023-06-20T08:55:57.835965", + "exception": false, + "start_time": "2023-06-20T08:55:57.590600", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Analyze derived relaxation rates\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_two_time:\n", + " try:\n", + " if True:\n", + " fs, fe = 0, 8\n", + " #fs,fe=0, 6\n", + " qval_dict_ = {k:qval_dict[k] for k in list(qval_dict.keys())[fs:fe] }\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict_, g2b_fit_paras['relaxation_rate'][fs:fe], \n", + " geometry= scat_geometry_ )\n", + " plot_q_rate_fit_general( qval_dict_, g2b_fit_paras['relaxation_rate'][fs:fe], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' , path= data_dir )\n", + " elif False:\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict, g2b_fit_paras['relaxation_rate'],\n", + " fit_range=[0, 26], geometry= scat_geometry_ ) \n", + " plot_q_rate_fit_general( qval_dict, g2_fit_paras['relaxation_rate'], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' ,\n", + " show_fit=False, path= data_dir, plot_all_range=False) \n", + " else:\n", + " ##plot log_q, log_rate\n", + " plot_q_rate_general( qval_dict, g2b_fit_paras['relaxation_rate'], \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' , path= data_dir )\n", + "\n", + " plot_q_g2fitpara_general( qval_dict, g2b_fit_paras, \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' , path= data_dir )\n", + " except:\n", + " pass\n", + "\n", + "_record_xpcs_cell_timing(\"119 - Analyze derived relaxation rates\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 10.49927, + "end_time": "2023-06-20T08:56:08.336783", + "exception": false, + "start_time": "2023-06-20T08:55:57.837513", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Compare one- and two-time correlations\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_two_time and run_one_time:\n", + " plot_g2_general( g2_dict={1:g2, 2:g2b}, taus_dict={1:taus, 2:tausb},vlim=[0.99, 1.007],\n", + " qval_dict=dict(itertools.islice(qval_dict.items(),g2.shape[1])), g2_labels=['from_one_time', 'from_two_time'],\n", + " geometry=scat_geometry_,filename=uid_+'_g2_two_g2', path= data_dir, ylabel='g2', )\n", + "\n", + "_record_xpcs_cell_timing(\"120 - Compare one- and two-time correlations\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.1e-05, + "end_time": "2023-06-20T08:56:08.338611", + "exception": false, + "start_time": "2023-06-20T08:56:08.338590", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Run Dose dependent analysis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.100158, + "end_time": "2023-06-20T08:56:08.560280", + "exception": false, + "start_time": "2023-06-20T08:56:08.460122", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Run dose-dependent two-time analysis\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_dose:\n", + " get_two_time_mulit_uids( [uid], roi_mask, norm= norm, bin_frame_number=1, \n", + " path= data_dir0, force_generate=False, compress_path = cmp_path + '/' )\n", + "\n", + "_record_xpcs_cell_timing(\"122 - Run dose-dependent two-time analysis\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.085135, + "end_time": "2023-06-20T08:56:08.667038", + "exception": false, + "start_time": "2023-06-20T08:56:08.581903", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Print transmission\n", + "\n", + "try:\n", + " print( 'transmission: %s exposure time: %s [s]'%(md['transmission'],exposuretime) )\n", + "except:\n", + " md['transmission'] =1\n", + " print( 'transmission: %s exposure time: %s [s]'%(md['transmission'],exposuretime) )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.056217, + "end_time": "2023-06-20T08:56:08.766145", + "exception": false, + "start_time": "2023-06-20T08:56:08.709928", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Print dose\n", + "\n", + "if run_dose:\n", + " N = len(imgs)\n", + " print(N)\n", + " #exposure_dose = md['transmission'] * exposuretime* np.int_([ N/16, N/8, N/4 ,N/2, 3*N/4, N*0.99 ])\n", + " exposure_dose = md['transmission'] * exposuretime* np.int_([ N/8, N/4 ,N/2, 3*N/4, N*0.99 ])\n", + " \n", + " print( exposure_dose )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.056837, + "end_time": "2023-06-20T08:56:08.876104", + "exception": false, + "start_time": "2023-06-20T08:56:08.819267", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate dose-dependent correlations\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_dose:\n", + " taus_uids, g2_uids = get_series_one_time_mulit_uids( [ uid ], qval_dict, good_start=good_start, \n", + " path= data_dir0, exposure_dose = exposure_dose, num_bufs =8, save_g2= False,\n", + " dead_time = 0, trans = [ md['transmission'] ] )\n", + "\n", + "_record_xpcs_cell_timing(\"125 - Calculate dose-dependent correlations\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.084866, + "end_time": "2023-06-20T08:56:09.015565", + "exception": false, + "start_time": "2023-06-20T08:56:08.930699", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot dose-dependent correlations\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_dose: \n", + " plot_dose_g2( taus_uids, g2_uids, ylim=[1.0, 1.2], vshift= 0.00,\n", + " qval_dict = qval_dict, fit_res= None, geometry= scat_geometry_,\n", + " filename= '%s_dose_analysis'%uid_, \n", + " path= data_dir, function= None, ylabel='g2_Dose', g2_labels= None, append_name= '' )\n", + "\n", + "_record_xpcs_cell_timing(\"126 - Plot dose-dependent correlations\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.044648, + "end_time": "2023-06-20T08:56:09.085824", + "exception": false, + "start_time": "2023-06-20T08:56:09.041176", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot selected dose-dependent correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_dose:\n", + " qth_interest = 5\n", + " plot_dose_g2( taus_uids, g2_uids, qth_interest= qth_interest, ylim=[0.98, 1.4], vshift= 0.00,\n", + " qval_dict = qval_dict, fit_res= None, geometry= scat_geometry_,\n", + " filename= '%s_dose_analysis'%uidstr, \n", + " path= data_dir, function= None, ylabel='g2_Dose', g2_labels= None, append_name= '' )\n", + "\n", + "_record_xpcs_cell_timing(\"127 - Plot selected dose-dependent correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Update two-time progress\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if track_progress:\n", + " if settings_dict_['run_two_time']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='run_two_time', progress='stop',start_time=None, stop_time=time.time(), verbose=True)\n", + " if settings_dict_['xsvs']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='xsvs', progress='start',start_time=time.time(), stop_time=None, verbose=True)\n", + "\n", + "_record_xpcs_cell_timing(\"128 - Update two-time progress\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:09.152401", + "exception": false, + "start_time": "2023-06-20T08:56:09.152376", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Four Time Correlation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.09842, + "end_time": "2023-06-20T08:56:09.356039", + "exception": false, + "start_time": "2023-06-20T08:56:09.257619", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate four-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_four_time:\n", + " g4 = get_four_time_from_two_time(g12b, g2=g2b)[:int(max_taus)]\n", + "\n", + "_record_xpcs_cell_timing(\"130 - Calculate four-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.06727, + "end_time": "2023-06-20T08:56:09.438027", + "exception": false, + "start_time": "2023-06-20T08:56:09.370757", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Save four-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_four_time:\n", + " taus4 = np.arange( g4.shape[0])*timeperframe \n", + " g4_pds = save_g2_general( g4, taus=taus4, qr=np.array( list( qval_dict.values() ) )[:,0],\n", + " qz=None, uid=uid_ +'_g4.csv', path= data_dir, return_res=True )\n", + "\n", + "_record_xpcs_cell_timing(\"131 - Save four-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.074563, + "end_time": "2023-06-20T08:56:09.560723", + "exception": false, + "start_time": "2023-06-20T08:56:09.486160", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot four-time correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_four_time:\n", + " plot_g2_general( g2_dict={1:g4}, taus_dict={1:taus4},vlim=[0.95, 1.05], qval_dict=qval_dict, fit_res= None, \n", + " geometry=scat_geometry_,filename=uid_+'_g4',path= data_dir, ylabel='g4')\n", + "\n", + "_record_xpcs_cell_timing(\"132 - Plot four-time correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:09.597732", + "exception": false, + "start_time": "2023-06-20T08:56:09.597708", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Speckle Visiblity" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.091965, + "end_time": "2023-06-20T08:56:09.794479", + "exception": false, + "start_time": "2023-06-20T08:56:09.702514", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Prepare XSVS analysis\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_xsvs: \n", + " max_cts = get_max_countc(FD, roi_mask ) \n", + " #max_cts = 15 #for eiger 500 K\n", + " qind, pixelist = roi.extract_label_indices( roi_mask )\n", + " noqs = len( np.unique(qind) )\n", + " nopr = np.bincount(qind, minlength=(noqs+1))[1:]\n", + " #time_steps = np.array( utils.geometric_series(2, len(imgs) ) )\n", + " time_steps = [0,1] #only run the first two levels\n", + " num_times = len(time_steps) \n", + " times_xsvs = exposuretime + (2**( np.arange( len(time_steps) ) ) -1 ) * timeperframe \n", + " print( 'The max counts are: %s'%max_cts )\n", + "\n", + "_record_xpcs_cell_timing(\"134 - Prepare XSVS analysis\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:09.814905", + "exception": false, + "start_time": "2023-06-20T08:56:09.814881", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Do histogram " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.072564, + "end_time": "2023-06-20T08:56:09.992027", + "exception": false, + "start_time": "2023-06-20T08:56:09.919463", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate XSVS histograms\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_xsvs:\n", + " if roi_avg is None:\n", + " times_roi, mean_int_sets = cal_each_ring_mean_intensityc(FD, roi_mask, timeperframe = None, ) \n", + " roi_avg = np.average( mean_int_sets, axis=0)\n", + " \n", + " spec_bins, spec_his, spec_std, spec_sum = xsvsp( FD, np.int_(roi_mask), norm=None,\n", + " max_cts=int(max_cts+2), bad_images=bad_frame_list, only_two_levels=True ) \n", + " spec_kmean = np.array( [roi_avg * 2**j for j in range( spec_his.shape[0] )] )\n", + " spec_pds = save_bin_his_std( spec_bins, spec_his, spec_std, filename=uid_+'_spec_res.csv', path=data_dir )\n", + "\n", + "_record_xpcs_cell_timing(\"136 - Calculate XSVS histograms\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:10.031751", + "exception": false, + "start_time": "2023-06-20T08:56:10.031727", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Do historam fit by negtive binominal function with maximum likehood method" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.080963, + "end_time": "2023-06-20T08:56:10.222574", + "exception": false, + "start_time": "2023-06-20T08:56:10.141611", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Fit XSVS histograms\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_xsvs: \n", + " ML_val, KL_val,K_ = get_xsvs_fit( spec_his, spec_sum, spec_kmean, \n", + " spec_std, max_bins=2, fit_range=[1,60], varyK= False )\n", + " #print( 'The observed average photon counts are: %s'%np.round(K_mean,4))\n", + " #print( 'The fitted average photon counts are: %s'%np.round(K_,4)) \n", + " print( 'The difference sum of average photon counts between fit and data are: %s'%np.round( \n", + " abs(np.sum( spec_kmean[0,:] - K_ )),4))\n", + " print( '#'*30)\n", + " qth= 0 \n", + " print( 'The fitted M for Qth= %s are: %s'%(qth, ML_val[qth]) )\n", + " print( K_[qth])\n", + " print( '#'*30)\n", + "\n", + "_record_xpcs_cell_timing(\"138 - Fit XSVS histograms\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:10.255723", + "exception": false, + "start_time": "2023-06-20T08:56:10.255699", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Plot fit results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.045892, + "end_time": "2023-06-20T08:56:10.408180", + "exception": false, + "start_time": "2023-06-20T08:56:10.362288", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Plot XSVS fits\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_xsvs: \n", + " qr = [qval_dict[k][0] for k in list(qval_dict.keys()) ]\n", + " plot_xsvs_fit( spec_his, ML_val, KL_val, K_mean = spec_kmean, spec_std=spec_std,\n", + " xlim = [0,10], vlim =[.9, 1.1],\n", + " uid=uid_, qth= qth_interest, logy= True, times= times_xsvs, q_ring_center=qr, path=data_dir)\n", + " \n", + " plot_xsvs_fit( spec_his, ML_val, KL_val, K_mean = spec_kmean, spec_std = spec_std,\n", + " xlim = [0,15], vlim =[.9, 1.1],\n", + " uid=uid_, qth= None, logy= True, times= times_xsvs, q_ring_center=qr, path=data_dir )\n", + "\n", + "_record_xpcs_cell_timing(\"140 - Plot XSVS fits\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.6e-05, + "end_time": "2023-06-20T08:56:10.476055", + "exception": false, + "start_time": "2023-06-20T08:56:10.476029", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Get contrast" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.099953, + "end_time": "2023-06-20T08:56:10.680532", + "exception": false, + "start_time": "2023-06-20T08:56:10.580579", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Calculate XSVS contrast\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_xsvs:\n", + " contrast_factorL = get_contrast( ML_val)\n", + " spec_km_pds = save_KM( spec_kmean, KL_val, ML_val, qs=qr, level_time=times_xsvs, uid=uid_, path = data_dir )\n", + " #spec_km_pds\n", + "\n", + "_record_xpcs_cell_timing(\"142 - Calculate XSVS contrast\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:10.698770", + "exception": false, + "start_time": "2023-06-20T08:56:10.698745", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Plot contrast with g2 results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.096136, + "end_time": "2023-06-20T08:56:10.905433", + "exception": false, + "start_time": "2023-06-20T08:56:10.809297", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Compare XSVS contrast and correlation\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if run_xsvs: \n", + " plot_g2_contrast( contrast_factorL, g2b, times_xsvs, tausb, qr, \n", + " vlim=[0.8,1.2], qth = qth_interest, uid=uid_,path = data_dir, legend_size=14)\n", + "\n", + " plot_g2_contrast( contrast_factorL, g2b, times_xsvs, tausb, qr, \n", + " vlim=[0.8,1.2], qth = None, uid=uid_,path = data_dir, legend_size=4)\n", + "\n", + "_record_xpcs_cell_timing(\"144 - Compare XSVS contrast and correlation\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Update XSVS progress\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if track_progress:\n", + " if settings_dict_['xsvs']:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='xsvs', progress='stop',start_time=None, stop_time=time.time(), verbose=True)\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='save data and report', progress='start',start_time=time.time(), stop_time=None, verbose=True)\n", + "\n", + "_record_xpcs_cell_timing(\"145 - Update XSVS progress\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.4e-05, + "end_time": "2023-06-20T08:56:10.922696", + "exception": false, + "start_time": "2023-06-20T08:56:10.922672", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Export Results to a HDF5 File" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 2.206983, + "end_time": "2023-06-20T08:56:13.236872", + "exception": false, + "start_time": "2023-06-20T08:56:11.029889", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Assemble and save result metadata\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "md['hostname'] = hostname[0]\n", + "md['kernel'] = kernel\n", + "md['detector_mask_file']=detector_mask_path+detector_mask_filename\n", + "md['det_mask_dict'] = det_mask_dict\n", + "md['polygon_mask']= polygon_dict\n", + "md['roi_mask_file']= fp\n", + "md['mask'] = mask\n", + "#md['NOTEBOOK_FULL_PATH'] = data_dir + get_current_pipeline_fullpath(NFP).split('/')[-1]\n", + "md['good_start'] = good_start\n", + "md['bad_frame_list'] = bad_frame_list\n", + "md['avg_img'] = avg_img\n", + "md['roi_mask'] = roi_mask\n", + "md['mask_outliers'] = mask_outliers\n", + "if mask_outliers:\n", + " md['outlier_threshold'] = outlier_threshold\n", + " md['maximum_outlier_fraction'] = maximum_outlier_fraction\n", + "md['setup_pargs'] = setup_pargs\n", + "if scat_geometry == 'gi_saxs': \n", + " md['Qr'] = Qr\n", + " md['Qz'] = Qz\n", + " md['qval_dict'] = qval_dict\n", + " md['beam_center_x'] = inc_x0\n", + " md['beam_center_y']= inc_y0\n", + " md['beam_refl_center_x'] = refl_x0\n", + " md['beam_refl_center_y'] = refl_y0\n", + "\n", + "\n", + "elif scat_geometry == 'gi_waxs':\n", + " md['beam_center_x'] = center[1]\n", + " md['beam_center_y']= center[0]\n", + "else:\n", + " md['qr']= qr\n", + " #md['qr_edge'] = qr_edge\n", + " md['qval_dict'] = qval_dict\n", + " md['beam_center_x'] = center[1]\n", + " md['beam_center_y']= center[0] \n", + "\n", + "md['beg'] = FD.beg\n", + "md['end'] = FD.end\n", + "md['qth_interest'] = qth_interest\n", + "md['metadata_file'] = data_dir + 'uid=%s_md.pkl'%uid\n", + "\n", + "md['beg_OneTime'] = good_start_g2\n", + "md['end_OneTime'] = good_end_g2\n", + "\n", + "psave_obj( md, data_dir + 'uid=%s_md.pkl'%uid ) #save the setup parameters\n", + "save_dict_csv( md, data_dir + 'uid=%s_md.csv'%uid, 'w')\n", + "\n", + "Exdt = {} \n", + "if scat_geometry == 'gi_saxs': \n", + " for k,v in zip( ['md', 'roi_mask','qval_dict','avg_img','mask','pixel_mask', 'imgsum', 'bad_frame_list', 'qr_1d_pds'], \n", + " [md, roi_mask, qval_dict, avg_img,mask,pixel_mask, imgsum, bad_frame_list, qr_1d_pds] ):\n", + " Exdt[ k ] = v\n", + "elif scat_geometry == 'saxs': \n", + " for k,v in zip( ['md', 'q_saxs', 'iq_saxs','iqst','qt','roi_mask','qval_dict','avg_img','mask','pixel_mask', 'imgsum', 'bad_frame_list'], \n", + " [md, q_saxs, iq_saxs, iqst, qt,roi_mask, qval_dict, avg_img,mask,pixel_mask, imgsum, bad_frame_list] ):\n", + " Exdt[ k ] = v\n", + "elif scat_geometry == 'gi_waxs': \n", + " for k,v in zip( ['md', 'roi_mask','qval_dict','avg_img','mask','pixel_mask', 'imgsum', 'bad_frame_list'], \n", + " [md, roi_mask, qval_dict, avg_img,mask,pixel_mask, imgsum, bad_frame_list] ):\n", + " Exdt[ k ] = v\n", + " \n", + "if run_waterfall:Exdt['wat'] = wat\n", + "if run_t_ROI_Inten:Exdt['times_roi'] = times_roi;Exdt['mean_int_sets']=mean_int_sets\n", + "if run_one_time:\n", + " if run_invariant_analysis:\n", + " for k,v in zip( ['taus','g2','g2_fit_paras', 'time_stamp','invariant'], [taus,g2,g2_fit_paras,time_stamp,invariant] ):Exdt[ k ] = v\n", + " else:\n", + " for k,v in zip( ['taus','g2','g2_fit_paras' ], [taus,g2,g2_fit_paras ] ):Exdt[ k ] = v\n", + " \n", + "if run_two_time:\n", + " for k,v in zip( ['tausb','g2b','g2b_fit_paras', 'g12b'], [tausb,g2b,g2b_fit_paras,g12b] ):Exdt[ k ] = v\n", + " #for k,v in zip( ['tausb','g2b','g2b_fit_paras', ], [tausb,g2b,g2b_fit_paras] ):Exdt[ k ] = v \n", + "if run_dose:\n", + " for k,v in zip( [ 'taus_uids', 'g2_uids' ], [taus_uids, g2_uids] ):Exdt[ k ] = v\n", + "if run_four_time:\n", + " for k,v in zip( ['taus4','g4'], [taus4,g4] ):Exdt[ k ] = v\n", + "if run_xsvs:\n", + " for k,v in zip( ['spec_kmean','spec_pds','times_xsvs','spec_km_pds','contrast_factorL'], \n", + " [ spec_kmean,spec_pds,times_xsvs,spec_km_pds,contrast_factorL] ):Exdt[ k ] = v\n", + "\n", + "_record_xpcs_cell_timing(\"147 - Assemble and save result metadata\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.24575, + "end_time": "2023-06-20T08:56:13.485609", + "exception": false, + "start_time": "2023-06-20T08:56:13.239859", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Export HDF5 results\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "#export_xpcs_results_to_h5( 'uid=%s_%s_Res%s.h5'%(md['uid'],q_mask_name,hdf5_name_extension), data_dir, export_dict = Exdt )\n", + "export_xpcs_results_to_h5( 'uid=%s_%s%s_Res.h5'%(md['uid'],q_mask_name,hdf5_name_extension), data_dir, export_dict = Exdt )\n", + "\n", + "_record_xpcs_cell_timing(\"148 - Export HDF5 results\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.072672, + "end_time": "2023-06-20T08:56:13.561092", + "exception": false, + "start_time": "2023-06-20T08:56:13.488420", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Append result path to user list\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "try:\n", + " from pyCHX.chx_generic_functions import append_txtfile\n", + " outp = default_dir+'%s/%s/'%(md['cycle'],username)\n", + " append_txtfile( filename = outp + username + '.lst', \n", + " data = np.array( [ outp + 'Results/' + md['uid'] + '/uid=%s__Res.h5'%md['uid']]))\n", + "except:\n", + " print('ERROR: unable to append output textfile for this uid.')\n", + "\n", + "_record_xpcs_cell_timing(\"149 - Append result path to user list\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:13.616508", + "exception": false, + "start_time": "2023-06-20T08:56:13.616483", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# Create a PDF Report" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.069555, + "end_time": "2023-06-20T08:56:13.800176", + "exception": false, + "start_time": "2023-06-20T08:56:13.730621", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Determine PDF report name\n", + "\n", + "pdf_out_dir = data_dir0\n", + "\n", + "pdf_filename = \"XPCS_Analysis_Report2_for_uid=%s%s%s.pdf\"%(uid,pdf_version,q_mask_name)\n", + "if run_xsvs:\n", + " pdf_filename = \"XPCS_XSVS_Analysis_Report_for_uid=%s%s%s.pdf\"%(uid,pdf_version,q_mask_name)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.555317, + "end_time": "2023-06-20T08:56:14.398855", + "exception": false, + "start_time": "2023-06-20T08:56:13.843538", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Create PDF report\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "# cheating here a little: the function argument 'False' hardcodes the absence of the form factor fit\n", + "make_pdf_report( data_dir, uid, pdf_out_dir, pdf_filename, username, \n", + " False,run_one_time, run_two_time, run_four_time, run_xsvs, run_dose,\n", + " report_type= scat_geometry, report_invariant= run_invariant_analysis,\n", + " md = md )\n", + "\n", + "_record_xpcs_cell_timing(\"153 - Create PDF report\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Finish report progress tracking\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if track_progress:\n", + " update_prog_dict_run_XPCS_SAXS(prog_dict_file,process_id,progress_key='save data and report', progress='stop',start_time=None, stop_time=time.time(), verbose=True)\n", + "\n", + "_record_xpcs_cell_timing(\"154 - Finish report progress tracking\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.2e-05, + "end_time": "2023-06-20T08:56:14.401737", + "exception": false, + "start_time": "2023-06-20T08:56:14.401715", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Attach the PDF report to Olog " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 9.582586, + "end_time": "2023-06-20T08:56:24.099192", + "exception": false, + "start_time": "2023-06-20T08:56:14.516606", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Attach PDF report to Olog\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if att_pdf_report and enable_olog_attachments:\n", + " lops=0\n", + " while lops<5:\n", + " try:\n", + " update_olog_uid_with_file( uid[:6], text='Add XPCS Analysis PDF Report', \n", + " filename=pdf_out_dir + pdf_filename, append_name='_R1' )\n", + " lops=5\n", + " except:\n", + " print(\"Failed to attach PDF report to Olog...try again in 10s\")\n", + " time.sleep(10)\n", + " lops+=1\n", + " if lops == 5:\n", + " print(\"Failed final attempt to attach PDF to Olog!\")\n", + "if not enable_olog_attachments:\n", + " print('Olog attachments are NOT possible as this notebook (or the papermill that is calling it) is NOT running on saturn4.\\nConnection to Olog is blocked by firewall, so we are not going to waste time trying.')\n", + "\n", + "_record_xpcs_cell_timing(\"156 - Attach PDF report to Olog\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:24.102253", + "exception": false, + "start_time": "2023-06-20T08:56:24.102228", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Save the OAV images" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "papermill": { + "duration": 0.048241, + "end_time": "2023-06-20T08:56:24.267903", + "exception": false, + "start_time": "2023-06-20T08:56:24.219662", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Attach OAV images to Olog\n", + "\n", + "_xpcs_cell_start = time.time()\n", + "\n", + "if save_oavs:\n", + " try:\n", + " #os.environ['HTTPS_PROXY'] = 'https://proxy:8888'\n", + " #os.environ['no_proxy'] = 'cs.nsls2.local,localhost,127.0.0.1'\n", + " update_olog_uid_with_file( uid[:6], text='Add OVA images', \n", + " filename= data_dir + 'uid=%s_OVA_images.png'%uid, append_name='_img' )\n", + " except:\n", + " print('failed to update Olog with OAV images')\n", + "\n", + "_record_xpcs_cell_timing(\"158 - Attach OAV images to Olog\", _xpcs_cell_start)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "papermill": { + "duration": 2.5e-05, + "end_time": "2023-06-20T08:56:28.531315", + "exception": false, + "start_time": "2023-06-20T08:56:28.531290", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# The End!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Printing benchmark data\n", + "\n", + "_xpcs_notebook_elapsed = time.time() - _xpcs_notebook_start\n", + "_xpcs_timed_total = sum(xpcs_cell_timings.values())\n", + "\n", + "print(\"\\n\" + \"=\" * 80)\n", + "print(\"XPCS NOTEBOOK CELL TIMING REPORT\")\n", + "print(\"=\" * 80)\n", + "for _xpcs_label, _xpcs_elapsed in xpcs_cell_timings.items():\n", + " print(f\"{_xpcs_label:<65} {_xpcs_elapsed:>10.2f} s\")\n", + "print(\"-\" * 80)\n", + "print(f\"{'Timed cells total':<65} {_xpcs_timed_total:>10.2f} s\")\n", + "print(f\"{'Notebook wall time':<65} {_xpcs_notebook_elapsed:>10.2f} s\")\n", + "print(\"=\" * 80)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Complete!\n" + ] + } + ], + "metadata": { + "celltoolbar": "Tags", + "kernelspec": { + "display_name": "Python 3 (current)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.14" + }, + "papermill": { + "duration": 202.500649, + "end_time": "2023-06-20T08:56:29.773278", + "environment_variables": {}, + "exception": false, + "output_path": "/nsls2/data/chx/legacy/analysis/2023_2/petrash/ResPipelines/XPCS_SAXS_2023_auto_test_v0_09f3d800-0018-4ee8-8fb3-4bb082ec26db.ipynb", + "parameters": { + "cycle": "2023_2", + "run_dose": false, + "run_two_time": true, + "uid": "09f3d800-0018-4ee8-8fb3-4bb082ec26db", + "username": "petrash" + }, + "start_time": "2023-06-20T08:53:07.272629", + "version": "0.15.0" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/pipelines/old_pipelines/XPCS_WAXS_auto.ipynb b/pipelines/old_pipelines/XPCS_WAXS_auto.ipynb new file mode 100644 index 0000000..5980178 --- /dev/null +++ b/pipelines/old_pipelines/XPCS_WAXS_auto.ipynb @@ -0,0 +1,5064 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "c5175e16", + "metadata": { + "papermill": { + "duration": 0.018735, + "end_time": "2025-02-21T22:31:56.930587", + "exception": false, + "start_time": "2025-02-21T22:31:56.911852", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "# XPCS&XSVS Pipeline for Single-(Gi)-SAXS Run\n", + "\"This notebook corresponds to version {{ version }} of the pipeline tool: https://github.com/NSLS-II/pipelines\"\n", + "\n", + "This notebook begins with a raw time-series of images and ends with $g_2(t)$ for a range of $q$, fit to an exponential or stretched exponential, and a two-time correlation functoin.\n", + "\n", + "## Overview\n", + "\n", + "* Setup: load packages/setup path\n", + "* Load Metadata & Image Data\n", + "* Apply Mask\n", + "* Clean Data: shutter open/bad frames\n", + "* Get Q-Map\n", + "* Get 1D curve\n", + "* Define Q-ROI (qr, qz)\n", + "* Check beam damage\n", + "* One-time Correlation\n", + "* Fitting\n", + "* Two-time Correlation\n", + "The important scientific code is imported from the [chxanalys](https://github.com/yugangzhang/chxanalys/tree/master/chxanalys) and [scikit-beam](https://github.com/scikit-beam/scikit-beam) project. Refer to chxanalys and scikit-beam for additional documentation and citation information.\n", + "\n", + "### DEV\n", + "* V8: Update visbility error bar calculation using pi = his/N +/- sqrt(his_i)/N\n", + "* Update normlization in g2 calculation uing 2D-savitzky golay (SG ) smooth\n", + "\n", + "## CHX Olog NoteBook\n", + "CHX Olog (https://logbook.nsls2.bnl.gov/11-ID/)\n", + "\n", + "## Setup\n", + "\n", + "Import packages for I/O, visualization, and analysis." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "dbbb9045", + "metadata": { + "papermill": { + "duration": 7.105932, + "end_time": "2025-02-21T22:32:04.056390", + "exception": false, + "start_time": "2025-02-21T22:31:56.950458", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/nsls2/software/common/jupyter/kernel_envs/beta/.pixi/envs/default/lib/python3.12/site-packages/databroker/v1.py:75: UserWarning: In databroker 2.x, there are separate notions of 'server' and 'client', and register_handler(...) has no effect on the client. Likely this is being done for you on the server side, so you should not worry about this message unless you encounter trouble loading large array data.\n", + " warnings.warn(\n", + "/nsls2/software/common/jupyter/kernel_envs/beta/.pixi/envs/default/lib/python3.12/site-packages/pyCHX/chx_generic_functions.py:827: SyntaxWarning: invalid escape sequence '\\m'\n", + " text_string = \"%s $\\mu$m\" % scalebar_size\n", + "/nsls2/software/common/jupyter/kernel_envs/beta/.pixi/envs/default/lib/python3.12/site-packages/pyCHX/chx_correlationc.py:893: SyntaxWarning: invalid escape sequence '\\i'\n", + " g_2(q, \\\\tau) = \\\\beta_1[g_1(q, \\\\tau)]^{2} + g_\\infty\n" + ] + }, + { + "name": "stdin", + "output_type": "stream", + "text": [ + "Olog Password (username = shall3): ········\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/nsls2/software/common/jupyter/kernel_envs/beta/.pixi/envs/default/lib/python3.12/site-packages/pyCHX/chx_specklecp.py:1557: SyntaxWarning: invalid escape sequence '\\G'\n", + " P(K) =(\\frac{M}{})^M \\frac{K^(M-1)}{\\Gamma(M)}\\exp(-M\\frac{K}{})\n", + "/nsls2/software/common/jupyter/kernel_envs/beta/.pixi/envs/default/lib/python3.12/site-packages/pyCHX/chx_specklecp.py:1634: SyntaxWarning: invalid escape sequence '\\e'\n", + " P(K) = \\frac{^K}{K!}\\exp(-)\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[32mrunning on: hpc004 environment: standard\n", + "\u001b[0m\n", + "\u001b[36msetting '_base_path_' as /nsls2/data/chx/legacy/analysis/\u001b[0m\n", + "\u001b[36msetting '_base_path_pass_' as /nsls2/data/chx/proposals/\u001b[0m\n", + "\u001b[36msetting '_mask_path_' as /nsls2/data/chx/shared/CHX_Setup/Detector_masks/\n", + "\u001b[0m\n", + "\u001b[32mRunning Beta or custom Pixi ipykernel, NOT reimporting pyCHX!\u001b[0m\n", + "\u001b[35m\n", + "environment dependent settings and patches:\u001b[0m\n", + "using \"%matplotlib inline\" for plotting\n", + "\u001b[36m--> overwrote '_base_path_' as /nsls2/data/chx/proposals/\u001b[0m\n" + ] + } + ], + "source": [ + "\"\"\"\n", + "from pyCHX.chx_packages import *\n", + "%matplotlib notebook\n", + "plt.rcParams.update({'figure.max_open_warning': 0})\n", + "plt.rcParams.update({ 'image.origin': 'lower' })\n", + "plt.rcParams.update({ 'image.interpolation': 'none' })\n", + "import pickle as cpk\n", + "from pyCHX.chx_xpcs_xsvs_jupyter_V1 import *\n", + "import itertools\n", + "from pyCHX.SAXS import poly_sphere_form_factor_intensity\n", + "\n", + "from pyCHX.chx_generic_functions import get_roi_mask_qval_qwid_by_shift #why is this needed??\n", + "\"\"\"\n", + "\n", + "from pyCHX.chx_packages import *\n", + "%matplotlib notebook\n", + "plt.rcParams.update({'figure.max_open_warning': 0})\n", + "plt.rcParams.update({ 'image.origin': 'lower' })\n", + "plt.rcParams.update({ 'image.interpolation': 'none' })\n", + "from pyCHX.chx_xpcs_xsvs_jupyter_V1 import *\n", + "import itertools\n", + "\n", + "import shutil,glob\n", + "from pyCHX.chx_generic_functions import get_roi_mask_qval_qwid_by_shift \n", + "from pyCHX.chx_generic_functions import RemoveHot,create_multi_rotated_rectangle_mask\n", + "\n", + "import sys\n", + "import json\n", + "sys.path.insert(0, \"/nsls2/data/chx/shared/CHX_Software/packages/database_processing/\") # Need a better way to include these directories\n", + "sys.path.insert(0, \"/nsls2/data/chx/shared/CHX_Software/packages/AutoRun_functions/\")\n", + "from database_processing import *\n", + "from AutoRun_functions import *\n", + "\n", + "%run /nsls2/data/chx/shared/CHX_Software/packages/environment_management/chx_analysis_setup_test_pyCHX.ipynb\n", + "_base_path_ = _base_path_pass_\n", + "print(colored(\"--> overwrote '_base_path_' as %s\"%_base_path_,'cyan'))\n", + "\n", + "from scipy.ndimage import gaussian_filter\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "a588459d", + "metadata": { + "papermill": { + "duration": 0.025352, + "end_time": "2025-02-21T22:32:04.785338", + "exception": false, + "start_time": "2025-02-21T22:32:04.759986", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#%matplotlib notebook\n", + "%matplotlib inline" + ] + }, + { + "cell_type": "markdown", + "id": "617bd05b", + "metadata": { + "papermill": { + "duration": 0.019929, + "end_time": "2025-02-21T22:32:04.825096", + "exception": false, + "start_time": "2025-02-21T22:32:04.805167", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Control Runs Here" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "118a89dc", + "metadata": { + "papermill": { + "duration": 0.027828, + "end_time": "2025-02-21T22:32:04.872407", + "exception": false, + "start_time": "2025-02-21T22:32:04.844579", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#scat_geometry = 'saxs' #suport 'saxs', 'gi_saxs', 'ang_saxs' (for anisotropics saxs or flow-xpcs)\n", + "#scat_geometry = 'ang_saxs' \n", + "scat_geometry = 'gi_waxs' \n", + "#scat_geometry = 'gi_saxs'\n", + "\n", + "\n", + "roi_auto = True #False #True #if True, will automatically create a roi based on the roi_type ( iso/aniso etc), currently only works for SAXS\n", + "fit_peak = False #True\n", + "\n", + "analysis_type_auto = True #False #True #False #True #if True, will take \"analysis type\" option from data acquisition func series\n", + "qphi_analysis = False #False #if True, will do q-phi (anisotropic analysis for transmission saxs)\n", + "\n", + "isotropic_Q_mask = 'normal' #'wide' # 'normal' # 'wide' ## select wich Q-mask to use for rings: 'normal' or 'wide'\n", + "phi_Q_mask = 'phi_4x_20deg' ## select wich Q-mask to use for phi analysis\n", + "q_mask_name = ''\n", + "\n", + "force_compress = False #True #force to compress data \n", + "bin_frame = False #generally make bin_frame as False\n", + "para_compress = True #parallel compress\n", + "run_fit_form = False #run fit form factor \n", + "run_waterfall = True #True #False #True #run waterfall analysis\n", + "run_profile_plot = False #run prolfile plot for gi-saxs\n", + "run_t_ROI_Inten = True #run ROI intensity as a function of time\n", + "run_get_mass_center = False # Analysis for mass center of reflective beam center\n", + "run_invariant_analysis = False\n", + "run_one_time = True #run one-time\n", + "cal_g2_error = False #True #calculate g2 signal to noise\n", + "#run_fit_g2 = True #run fit one-time, the default function is \"stretched exponential\"\n", + "fit_g2_func = 'stretched'\n", + "run_two_time = True #True #run two-time\n", + "run_four_time = False #True #True #False #run four-time\n", + "run_xsvs= False # True #False #run visibility analysis\n", + "att_pdf_report = True #attach the pdf report to CHX olog\n", + "qth_interest = 7 #the intested single qth \n", + "\n", + "use_sqnorm = True #if True, use sq to normalize intensity\n", + "use_SG = True #False #True # False #if True, use the Sawitzky-Golay filter of the avg_img for normalization\n", + "use_SG_bin_frames = False #if True, use the Sawitzky-Golay filter of the (binned) frame for normalization \n", + "\n", + "use_imgsum_norm= True #if True use imgsum to normalize intensity for one-time calculatoin\n", + "pdf_version='_%s'%get_today_date() #for pdf report name\n", + "run_dose = False # True # False #True # True #False #run dose_depend analysis\n", + "\n", + "\n", + "if scat_geometry == 'gi_saxs':run_xsvs= False;use_sqnorm=False\n", + "if scat_geometry == 'gi_waxs':use_sqnorm = False\n", + "if scat_geometry != 'saxs':qphi_analysis = False;scat_geometry_ = scat_geometry;roi_auto = False \n", + "else:scat_geometry_ = ['','ang_'][qphi_analysis]+ scat_geometry \n", + "if scat_geometry != 'gi_saxs':run_profile_plot = False" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "bc44b2ee", + "metadata": { + "papermill": { + "duration": 0.026894, + "end_time": "2025-02-21T22:32:04.919305", + "exception": false, + "start_time": "2025-02-21T22:32:04.892411", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "('gi_waxs', 'gi_waxs', False)" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scat_geometry, scat_geometry_, qphi_analysis" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "3ba1bdda", + "metadata": { + "papermill": { + "duration": 0.02576, + "end_time": "2025-02-21T22:32:04.964735", + "exception": false, + "start_time": "2025-02-21T22:32:04.938975", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "taus=None;g2=None;tausb=None;g2b=None;g12b=None;taus4=None;g4=None;times_xsv=None;contrast_factorL=None; lag_steps = None " + ] + }, + { + "cell_type": "markdown", + "id": "a8bbcd0f", + "metadata": { + "papermill": { + "duration": 0.020334, + "end_time": "2025-02-21T22:32:05.004947", + "exception": false, + "start_time": "2025-02-21T22:32:04.984613", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Make a directory for saving results" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "8656761e", + "metadata": { + "papermill": { + "duration": 0.024332, + "end_time": "2025-02-21T22:32:05.049678", + "exception": false, + "start_time": "2025-02-21T22:32:05.025346", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "analysis_path = _base_path_" + ] + }, + { + "cell_type": "markdown", + "id": "6036f3b1", + "metadata": { + "papermill": { + "duration": 0.020017, + "end_time": "2025-02-21T22:32:05.089263", + "exception": false, + "start_time": "2025-02-21T22:32:05.069246", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "## Load Metadata & Image Data\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "c059ffb6", + "metadata": { + "papermill": { + "duration": 0.020549, + "end_time": "2025-02-21T22:32:05.129578", + "exception": false, + "start_time": "2025-02-21T22:32:05.109029", + "status": "completed" + }, + "tags": [] + }, + "source": [ + "### Change this line to give a uid" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "9d597a7b", + "metadata": { + "papermill": { + "duration": 0.026177, + "end_time": "2025-02-21T22:32:05.175612", + "exception": false, + "start_time": "2025-02-21T22:32:05.149435", + "status": "completed" + }, + "tags": [ + "parameters" + ] + }, + "outputs": [], + "source": [ + "uid = 224788 #224776 #'968c2e34' #(scan num: 169004) (Measurement: 1s x 600 fr. Trans:0.013043082284207138 sample: TaS2 )\n", + "cycle = '2026-3'\n", + "\n", + "roi_auto = True # True #False #True #if True, will automatically create a roi based on the roi_type ( iso/aniso etc), currently only works for SAXS\n", + "run_two_time = True \n", + "run_dose = False " + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "fbf118c1", + "metadata": { + "papermill": { + "duration": 0.025138, + "end_time": "2025-02-21T22:32:05.220910", + "exception": false, + "start_time": "2025-02-21T22:32:05.195772", + "status": "completed" + }, + "tags": [ + "injected-parameters" + ] + }, + "outputs": [], + "source": [ + "# Parameters\n" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "901dffe2", + "metadata": { + "papermill": { + "duration": 0.025687, + "end_time": "2025-02-21T22:32:05.266300", + "exception": false, + "start_time": "2025-02-21T22:32:05.240613", + "status": "completed" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "# Data security modification: username for file creation is now the data_session. Should we fix this in the papermill level?\n", + "md=get_meta_data(uid)\n", + "username = md['data_session']\n", + "\n", + "CYCLE= cycle #set in the auto analysis pipeline from metadata\n", + "path = _base_path_ + '%s/%s/masks/'%(cycle,username)\n", + "outp = _base_path_ + '%s/%s/'%(cycle,username)\n", + "#outp = outp+'%s/'%username " + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "656cf5c2", + "metadata": { + "papermill": { + "duration": 0.026556, + "end_time": "2025-02-21T22:32:05.312620", + "exception": false, + "start_time": "2025-02-21T22:32:05.286064", + "status": "completed" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'/nsls2/data/chx/proposals/2026-3/pass-317365/masks/'" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "path" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "60395e6f", + "metadata": { + "papermill": { + "duration": 0.392629, + "end_time": "2025-02-21T22:32:05.725289", + "exception": true, + "start_time": "2025-02-21T22:32:05.332660", + "status": "failed" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Results from this analysis will be stashed in the directory /nsls2/data/chx/proposals/2026-3/pass-317365/Results/\n", + "/nsls2/data/chx/proposals/2026-3/pass-317365/Results/\n" + ] + } + ], + "source": [ + "data_dir0 = create_user_folder(cycle, username, default_dir= analysis_path)\n", + "print( data_dir0 )" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "8c5f761e", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The current uid for analysis is: 224788...\n" + ] + } + ], + "source": [ + "#uid = uid[:8]\n", + "print('The current uid for analysis is: %s...'%uid)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "03a989b7", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "scan_id, full-uid, data path are: 224788--dd56684a-f48b-4251-89e6-6572a4aabfad--/nsls2/data/chx/proposals/2026-3/pass-317365/assets/eiger1m-1/2026/10/08/7a9f07a0-43ab-4014-9ea9_2050_master.h5\n" + ] + } + ], + "source": [ + "#sud = get_sid_filenames(db[uid]) #this does not work anymore -- replaced with the following\n", + "import glob\n", + "def get_sud(hdr):\n", + " start_doc = hdr.start\n", + " return (start_doc[\"scan_id\"], start_doc[\"uid\"], glob.glob(f\"{start_doc['data path']}*_{start_doc['sequence id']}_master.h5\"))\n", + "\n", + "sud = get_sud(db[uid])\n", + "#-------------------------------------------------------\n", + "\n", + "for pa in sud[2]:\n", + " if 'master.h5' in pa:\n", + " data_fullpath = pa\n", + "print ('scan_id, full-uid, data path are: %s--%s--%s'%(sud[0], sud[1], data_fullpath ))\n", + "\n", + "#start_time, stop_time = '2017-2-24 12:23:00', '2017-2-24 13:42:00' \n", + "#sids, uids, fuids = find_uids(start_time, stop_time)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "000b2977", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Results from this analysis will be stashed in the directory /nsls2/data/chx/proposals/2026-3/pass-317365/Results/dd56684a-f48b-4251-89e6-6572a4aabfad/\n" + ] + } + ], + "source": [ + "data_dir = os.path.join(data_dir0, '%s/'%(sud[1]))\n", + "os.makedirs(data_dir, exist_ok=True)\n", + "print('Results from this analysis will be stashed in the directory %s' % data_dir)\n", + "uidstr = 'uid=%s'%uid" + ] + }, + { + "cell_type": "markdown", + "id": "6c4ebecc", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# Don't Change the lines below here" + ] + }, + { + "cell_type": "markdown", + "id": "31b77036", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "* get metadata" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "fb53fd49", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "md = get_meta_data( uid )\n", + "md_blue = md.copy()\n", + "#md_blue" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "5dc314fb", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#get_detectors??\n", + "#md_blue['detectors'][0]\n", + "#if md_blue['OAV_mode'] != 'none':\n", + "# cx , cy = md_blue[md_blue['detectors'][0]+'_beam_center_x'], md_blue[md_blue['detectors'][0]+'_beam_center_x']\n", + "#else: \n", + "# cx , cy = md_blue['beam_center_x'], md_blue['beam_center_y']\n", + "#print(cx,cy)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "dca54e84", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The detectors are:['eiger1m_single_image']\n" + ] + } + ], + "source": [ + "detectors = sorted(get_detectors(db[uid]))\n", + "print('The detectors are:%s'%detectors)\n", + "if len(detectors) >1:\n", + " md['detector'] = detectors[1]\n", + " print( md['detector'])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "b730f1bf", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Image reverse: True\n", + "Image rotate 90: False\n" + ] + } + ], + "source": [ + "if md['detector'] =='eiger4m_single_image' or md['detector'] == 'image': \n", + " reverse= True\n", + " rot90= False\n", + "elif md['detector'] =='eiger500K_single_image': \n", + " reverse= True\n", + " rot90=True\n", + "elif md['detector'] =='eiger1m_single_image': \n", + " reverse= True\n", + " rot90=False\n", + "print('Image reverse: %s\\nImage rotate 90: %s'%(reverse, rot90)) " + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "6c0f5af5", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Will find cx,cy later.\n" + ] + } + ], + "source": [ + "try:\n", + " cx , cy = md_blue['beam_center_x'], md_blue['beam_center_y']\n", + " print(cx,cy)\n", + "except:\n", + " print('Will find cx,cy later.')\n" + ] + }, + { + "cell_type": "markdown", + "id": "5f4b798a", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "### Load ROI defined by \"XPCS_Setup\" Pipeline" + ] + }, + { + "cell_type": "markdown", + "id": "c3fa8c51", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "#### Define data analysis type" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "c6441c3e", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "Will NOT DO qphis analysis.\n", + "gi_waxs\n" + ] + } + ], + "source": [ + "if analysis_type_auto:#if True, will take \"analysis type\" option from data acquisition func series\n", + " try:\n", + " if scat_geometry != 'gi_saxs':\n", + " qphi_analysis_ = md['analysis'] #if True, will do q-phi (anisotropic analysis for transmission saxs)\n", + " print(md['analysis'])\n", + " if qphi_analysis_ == 'iso':\n", + " qphi_analysis = False\n", + " elif qphi_analysis_ == '':\n", + " qphi_analysis = False\n", + " else:\n", + " qphi_analysis = True\n", + " #for other analysis type, in case of GiSAXS, low_angle/high_anlge for instance \n", + " else:\n", + " gisaxs_inc_type = md['analysis'] \n", + " \n", + " except:\n", + " gisaxs_inc_type = None\n", + " print('There is no analysis in metadata.')\n", + " \n", + "print('Will %s qphis analysis.'%['NOT DO','DO'][qphi_analysis]) \n", + "\n", + "if scat_geometry != 'saxs':qphi_analysis = False;scat_geometry_ = scat_geometry \n", + "else:scat_geometry_ = ['','ang_'][qphi_analysis]+ scat_geometry \n", + "if scat_geometry != 'gi_saxs':run_profile_plot = False \n", + " \n", + "print(scat_geometry_) " + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "e25b6005", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'gi_waxs'" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "scat_geometry" + ] + }, + { + "cell_type": "markdown", + "id": "be0201a4", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "* get data" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "89ee2a94", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[32mSUCCESSFULLY LOADED DATA AS dask-array!\u001b[0m\n", + "The data areg2: dask.array\n" + ] + } + ], + "source": [ + "\"\"\"\n", + "imgs = load_data( uid, md['detector'], reverse= reverse, rot90=rot90 )\n", + "md.update( imgs.md );Nimg = len(imgs);\n", + "#md['beam_center_x'], md['beam_center_y'] = cx, cy\n", + "#if 'number of images' not in list(md.keys()):\n", + "md['number of images'] = Nimg\n", + "pixel_mask = 1- np.int_( np.array( imgs.md['pixel_mask'], dtype= bool) )\n", + "print( 'The data areg2: %s' %imgs )\n", + "\n", + "#md['acquire period' ] = md['cam_acquire_period']\n", + "#md['exposure time'] = md['cam_acquire_time']\n", + "mdn = md.copy()\n", + "\"\"\"\n", + "try: # preferred: load images as dask_array\n", + " imgs,img_md=load_dask_data(uid,md['detector'], _mask_path_+'pixel_masks/',reverse=reverse,rot90=rot90)\n", + " print(colored('SUCCESSFULLY LOADED DATA AS dask-array!','green'))\n", + "except:\n", + " print(colored('COULD NOT LOAD DATA AS dask-array, reverting to slow data loading....','red'))\n", + " imgs = load_data(uid,md['detector'],reverse=reverse,rot90=rot90)\n", + " img_md=imgs.md\n", + " print(colored('COULD NOT LOAD DATA AS dask-arry, falling back to slow data loading....','red'))\n", + "imgs\n", + "\n", + "md.update( img_md );Nimg = len(imgs);\n", + "#md['beam_center_x'], md['beam_center_y'] = cx, cy\n", + "#if 'number of images' not in list(md.keys()):\n", + "md['number of images'] = Nimg\n", + "pixel_mask = 1- np.int_( np.array( img_md['pixel_mask'], dtype= bool) )\n", + "print( 'The data areg2: %s' %imgs )\n", + "\n", + "#md['acquire period' ] = md['cam_acquire_period']\n", + "#md['exposure time'] = md['cam_acquire_time']\n", + "mdn = md.copy()" + ] + }, + { + "cell_type": "markdown", + "id": "ddf40320", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "#### Load Chip mask depeding on detector" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "103208bd", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1065, 1030) (1065, 1030)\n" + ] + } + ], + "source": [ + "if md['detector'] =='eiger1m_single_image':\n", + " Chip_Mask=np.load( path+'Eiger1M_Chip_Mask.npy')\n", + "elif md['detector'] =='eiger4m_single_image' or md['detector'] == 'image': \n", + " Chip_Mask= np.array(np.load( analysis_path + '2017_1/masks/Eiger4M_chip_mask.npy'), dtype=bool)\n", + " BadPix = np.load(analysis_path + '2019_2/BadPix_4M.npy' ) \n", + " Chip_Mask.ravel()[BadPix] = 0\n", + "elif md['detector'] =='eiger500K_single_image':\n", + " #print('here')\n", + " Chip_Mask= np.load( analysis_path + '2017_1/masks/Eiger500K_Chip_Mask.npy') #to be defined the chip mask\n", + " Chip_Mask = np.rot90(Chip_Mask)\n", + " pixel_mask = np.rot90( 1- np.int_( np.array( imgs.md['pixel_mask'], dtype= bool)) )\n", + " \n", + "else:\n", + " Chip_Mask = 1\n", + "print(Chip_Mask.shape, pixel_mask.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "9356a70a", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "use_local_disk = True\n", + "import shutil,glob" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "bfabe491", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "save_oavs = False\n", + "if len(detectors)==2:\n", + " if '_image' in md['detector']:\n", + " pref = md['detector'][:-5]\n", + " else:\n", + " pref=md['detector']\n", + " for k in [ 'beam_center_x', 'beam_center_y','cam_acquire_time','cam_acquire_period','cam_num_images',\n", + " 'wavelength', 'det_distance', 'photon_energy']:\n", + " md[k] = md[ pref + '%s'%k] \n", + " \n", + " if 'OAV_image' in detectors:\n", + " try:\n", + " save_oavs_tifs( uid, data_dir )\n", + " save_oavs = True\n", + " except:\n", + " pass\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "6933c511", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "suid--> 224788\n", + "number of images--> 3600\n", + "uid--> dd56684a-f48b-4251-89e6-6572a4aabfad\n", + "scan_id--> 224788\n", + "start_time--> 2026-10-08 14:31:37\n", + "stop_time--> 2026-10-08 15:31:40\n", + "sample--> none\n", + "Measurement--> 1s x 3600 fr. Trans:0.11471480224059148 sample: none \n", + "acquire period--> 1\n", + "exposure time--> 1\n", + "beam_center_x--> 639.0\n", + "beam_center_y--> 624.0\n" + ] + } + ], + "source": [ + "print_dict( md, ['suid', 'number of images', 'uid', 'scan_id', 'start_time', 'stop_time', 'sample', 'Measurement',\n", + " 'acquire period', 'exposure time', \n", + " 'det_distance', 'beam_center_x', 'beam_center_y', ] )" + ] + }, + { + "cell_type": "markdown", + "id": "0a669f95", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## Overwrite Some Metadata if Wrong Input" + ] + }, + { + "cell_type": "markdown", + "id": "ce920d5f", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "### Define incident beam center (also define reflection beam center for gisaxs)" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "fe78bd16", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "441.0 639.0\n" + ] + } + ], + "source": [ + "if scat_geometry =='gi_saxs':\n", + " inc_x0 = md['beam_center_x'] \n", + " inc_y0 = imgs[0].shape[0] - md['beam_center_y'] \n", + " #1147 ,1550\n", + " refl_x0 = md['beam_center_x'] \n", + " refl_y0 = 1550 # imgs[0].shape[0] - 673 \n", + " \n", + " print( \"inc_x0, inc_y0, ref_x0,ref_y0 are: %s %s %s %s.\"%(inc_x0, inc_y0, refl_x0, refl_y0) )\n", + "else:\n", + " if md['detector'] =='eiger4m_single_image' or md['detector'] == 'image' or md['detector']=='eiger1m_single_image': \n", + " inc_x0 = imgs[0].shape[0] - md['beam_center_y'] \n", + " inc_y0= md['beam_center_x']\n", + " elif md['detector'] =='eiger500K_single_image': \n", + " inc_y0 = imgs[0].shape[1] - md['beam_center_y'] \n", + " inc_x0 = imgs[0].shape[0] - md['beam_center_x']\n", + " \n", + " \n", + " print(inc_x0, inc_y0)\n", + "\n", + " ###for this particular uid, manually give x0/y0\n", + " #inc_x0 = 1041\n", + " #inc_y0 = 1085" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "12a2c484", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Beam_center_x has been changed to 639.0. (no change in raw metadata): \n", + "Beam_center_y has been changed to 441.0. (no change in raw metadata): \n", + "uid--> uid=224788\n", + "dpix--> 0.075\n", + "Ldet--> 790.0\n", + "lambda_--> 0.968323949025307\n", + "exposuretime--> 0.999997\n", + "timeperframe--> 1.0\n", + "center--> [441, 639]\n", + "path--> /nsls2/data/chx/proposals/2026-3/pass-317365/Results/dd56684a-f48b-4251-89e6-6572a4aabfad/\n" + ] + } + ], + "source": [ + "dpix, lambda_, Ldet, exposuretime, timeperframe, center = check_lost_metadata(\n", + " md, Nimg, inc_x0 = inc_x0, inc_y0= inc_y0, pixelsize = 7.5*10*(-5) )\n", + "if scat_geometry =='gi_saxs':center=center[::-1]\n", + "\n", + "setup_pargs=dict(uid=uidstr, dpix= dpix, Ldet=Ldet, lambda_= lambda_, exposuretime=exposuretime,\n", + " timeperframe=timeperframe, center=center, path= data_dir)\n", + "print_dict( setup_pargs )\n" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "eb156bce", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'uid': 'uid=224788',\n", + " 'dpix': 0.075,\n", + " 'Ldet': 790.0,\n", + " 'lambda_': 0.968323949025307,\n", + " 'exposuretime': 0.999997,\n", + " 'timeperframe': 1.0,\n", + " 'center': [441, 639],\n", + " 'path': '/nsls2/data/chx/proposals/2026-3/pass-317365/Results/dd56684a-f48b-4251-89e6-6572a4aabfad/'}" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "setup_pargs" + ] + }, + { + "cell_type": "markdown", + "id": "5943add6", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## Apply Mask\n", + "* load and plot mask if exist \n", + "* otherwise create a mask using Mask pipeline\n", + "* Reverse the mask in y-direction due to the coordination difference between python and Eiger software\n", + "* Reverse images in y-direction\n", + "* Apply the mask" + ] + }, + { + "cell_type": "markdown", + "id": "fdf76e7c", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# Change the lines below to give mask filename" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "bb6a7c48", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "\n", + "mask_name = 'Feb26_2021_1M_WAXS.npy' \n", + "\n", + "mask_path = path\n", + "roi_path = mask_path\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "b7a0e315", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "data": { + "text/plain": [ + "'/nsls2/data/chx/proposals/2026-3/pass-317365/masks/'" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "roi_path" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "fe6e2df5", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "mask = load_mask(mask_path, mask_name, plot_ = False, image_name = uidstr + '_mask', reverse= reverse, rot90=rot90 ) \n", + "mask = mask * pixel_mask * Chip_Mask\n", + "#show_img(mask,image_name = uidstr + '_mask', save=True, path=data_dir, aspect=1, center=center[::-1])\n", + "mask_load=mask.copy()\n", + "imgsa = apply_mask( imgs, mask )" + ] + }, + { + "cell_type": "markdown", + "id": "6cdc3f47", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# Check several frames average intensity" + ] + }, + { + "cell_type": "markdown", + "id": "d697d578", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "#### Load ROI mask depending on data analysis type" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "1002ebe7", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#%run ~/pyCHX_link/pyCHX/chx_generic_functions.py" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "d2a3044a", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "True False normal\n" + ] + } + ], + "source": [ + "print(roi_auto, qphi_analysis, isotropic_Q_mask)" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "id": "e1a1ffb7-515b-4e46-9efe-5939692d896d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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bt07OO++8oO2rVq2SwsJCWbt2ravJysqScePGSUNDQ6BGg27r1q1SVFQkZWVlcuzYMZk4caK0tbV15iEDAKI1uDRopk2bJuvXr5fevXsH9bbWrFkjd999t1x33XWSk5Mjjz/+uBw/flw2b97sao4ePSqPPvqoPPjggzJ27Fi58MILZdOmTbJv3z557rnnOuuQAQDRHFyzZ8+Wq666ygVPR5WVlXL48GEZP358YFtCQoLk5eVJeXm5W9+9e7e0tLQE1eiwooacvyaUDi3W19cHLQCAyBPbGT9Uh/f27NnjhgFDaWipzMzMoO26fuDAgUBNfHx8UE/NX+N//MneS7vvvvvCeBYAgKjocVVVVckdd9zhhvZ69ux5yjqdsNGRDiGGbgv1WTVLly51Q4z+RY8DABB5wh5cOsxXW1srw4YNk9jYWLeUlpbKQw895O77e1qhPSd9jH+fTtZobm6Wurq6U9aE0uHGXr16BS0AgMgT9uAaM2aMm0Sxd+/ewDJ8+HA3UUPvDxo0yAVTSUlJ4DEaUhpuo0aNcusaenFxcUE1NTU1UlFREagBAESnsL/HlZKS4iZRdKTXYaWnpwe261T35cuXy+DBg92i95OSkmTq1Kluf2pqqsyYMUMWLFjgHpeWliYLFy6U3NzcEyZ7AACiS6dMzvg8ixYtksbGRpk1a5YbDhw5cqRs27bNhZ7f6tWr3dDi5MmTXa325DZs2CAxMTFdccgAgG7C5+mMhwik0+G155Yv10isL66rDwcAol6r1yIvydNuAt2XmYfAZxUCAEwhuAAAphBcAABTCC4AgCkEFwDAFIILAGAKwQUAMIXgAgCYQnABAEwhuAAAphBcAABTCC4AgCkEFwDAFIILAGAKwQUAMIXgAgCY0iXfgAwA3ZLPJ+IL+Xvea//0NiK/c9ckggsIx4tdxxc2Xdf7/lvY4eshvh4+kZgY8cXEiNfSKuL5xGtr4/+zGyG4gDMNKnf/P3+duxe7TwVe5Py1hJc97Z54bc3///8T3QrBBZzBUJILKr3tmSC+hHjxJSaK19ws0tQk3r+bxGtr7/CCx1CTGZ7+v+mdDmHFHx7dDpMzgC/q016UfyipR2JP8WVnyvvz/leG/6lS/m/O/4hk9vlPmMXHuaGmkz0e3ZiGVOiCbofgAr6oji9iOpTkeeL7pFGSq0XavB6SeMQn4u9l6a3/TX0AYcVQIfBFfdpj+s8QYJt4n7S54cG+v6uXPb/PkH6t+6Rdhws/DS+vXf9iZ5gQCDeCCziTHpebdNHugsu9t+W29QjuZTGzEOgUBBdwJk723sd/3tX//DoAXwrvcQEATCG4AACmEFwAAFMILgCAKQQXAMAUggsAYArBBQAwheACAJhCcAEATCG4AACmEFwAAFMILgCAKQQXAMAUggsAYArBBQAwheACAJhCcAEATCG4AACmEFwAAFMILgCAKQQXAMAUggsAYArBBQAwheACAJhCcAEATCG4AACmEFwAAFMILgCAKQQXAMAUggsAYArBBQAwheACAJhCcAEATCG4AADRHVwrVqyQESNGSEpKivTt21euvfZaeeedd4JqPM+TZcuWSXZ2tiQmJkp+fr7s378/qKapqUnmzp0rGRkZkpycLJMmTZLq6upwHy4AINqDq7S0VGbPni07duyQkpISaW1tlfHjx8snn3wSqFm1apUUFhbK2rVrZdeuXZKVlSXjxo2ThoaGQE1BQYFs3bpVioqKpKysTI4dOyYTJ06Utra2cB8yAMAQn6fdn0505MgR1/PSQLvssstcb0t7WhpMixcvDvSuMjMzZeXKlTJz5kw5evSo9OnTRzZu3ChTpkxxNYcOHZIBAwZIcXGxTJgw4XP/3fr6eklNTZV8uUZifXGdeYoAgC+g1WuRl+Rp9xrfq1cv6bbvcekBqrS0NHdbWVkphw8fdr0wv4SEBMnLy5Py8nK3vnv3bmlpaQmq0bDLyckJ1ITS8NOw6rgAACJPpwaX9q7mz58vo0ePdqGjNLSU9rA60nX/Pr2Nj4+X3r17n7LmZO+taQ/Lv2jvDAAQeTo1uObMmSNvvPGG/O53vzthn8/nOyHkQreF+qyapUuXut6df6mqqvqSRw8AiKrg0hmBzzzzjLz44ovSv3//wHadiKFCe061tbWBXpjWNDc3S11d3SlrQulwo46ZdlwAAJEn7MGlvSLtaT355JPywgsvyMCBA4P267oGk8449NOQ0skbo0aNcuvDhg2TuLi4oJqamhqpqKgI1AAAolNsuH+gToXfvHmzPP300+5aLn/PSt930mu2dKhPZxQuX75cBg8e7Ba9n5SUJFOnTg3UzpgxQxYsWCDp6eluYsfChQslNzdXxo4dG+5DBgBEc3A9/PDD7lYvKu7osccek1tuucXdX7RokTQ2NsqsWbPccODIkSNl27ZtLuj8Vq9eLbGxsTJ58mRXO2bMGNmwYYPExMSE+5ABAIZ0+nVcXYXruACgezFzHRcAAOFEcAEATCG4AACmEFwAAFMILgCAKQQXAMAUggsAYArBBQAwheACAJhCcAEATCG4AACmEFwAAFMILgCAKQQXAMAUggsAYArBBQAwheACAJhCcAEATCG4AACmEFwAAFMILgCAKQQXAMAUggsAYArBBQAwheACAJhCcAEATCG4AACmEFwAAFMILgCAKQQXAMAUggsAYArBBQAwheACAJhCcAEATCG4AACmEFwAAFMILgCAKQQXAMAUggsAYArBBQAwheACAJhCcAEATCG4AACmEFwAAFMILgCAKQQXAMAUggsAYArBBQAwheACAJhCcAEATCG4AACmEFwAAFMILgCAKQQXAMAUggsAYArBBQAwheACAJhCcAEATOn2wfXrX/9aBg4cKD179pRhw4bJK6+80tWHBADoQt06uLZs2SIFBQVy9913y2uvvSbf+ta35Dvf+Y588MEHXX1oAIAu0q2Dq7CwUGbMmCHf//73ZejQobJmzRoZMGCAPPzww119aACALhIr3VRzc7Ps3r1blixZErR9/PjxUl5efkJ9U1OTW/yOHj3qblulRcT7LxwwAOAzuddjEfE8LzKD65///Ke0tbVJZmZm0HZdP3z48An1K1askPvuu++E7WVS3KnHCQA4PQ0NDZKamioRF1x+Pp8vaF2TOnSbWrp0qcyfPz+w/vHHH8vZZ5/t3g/7Mg0Uaerr691wa1VVlfTq1aurD6dboE1oF54r/53fH3391tDKzs7+Ev9iNw6ujIwMiYmJOaF3VVtbe0IvTCUkJLgllIYWL9An0jahXWiTL4LnCm0SzudJODoS3XZyRnx8vJv+XlJSErRd10eNGtVlxwUA6FrdtseldOjv5ptvluHDh8sll1wi69atc0N/t99+e1cfGgCgi3Tr4JoyZYp89NFHcv/990tNTY3k5ORIcXGxe+/q8+iw4b333nvS4cNoRrvQJjxX+P2x/pri877svEQAAP6Luu17XAAAnAzBBQAwheACAJhCcAEATInY4IqWr0PRj7oaMWKEpKSkSN++feXaa6+Vd955J6hG598sW7bMXa2emJgo+fn5sn///qAa/ZzHuXPnugu/k5OTZdKkSVJdXS2R1E76iSv6bQPR3C4HDx6Um266SdLT0yUpKUkuuOAC95mg0dwmra2tcs8997jXCz3nQYMGuZnM7e3tUdMuL7/8slx99dXu/PT35KmnngraH67zr6urc5c46UXIuuh9/ZSj0+ZFoKKiIi8uLs5bv3699+abb3p33HGHl5yc7B04cMCLNBMmTPAee+wxr6Kiwtu7d6931VVXeWeddZZ37NixQM3PfvYzLyUlxfvDH/7g7du3z5syZYrXr18/r76+PlBz++23e1/72te8kpISb8+ePd7ll1/unX/++V5ra6tn3c6dO72vf/3r3nnnneeeC9HaLv/617+8s88+27vlllu8V1991ausrPSee+4577333ovaNlE//elPvfT0dO9Pf/qTa5Pf//733le+8hVvzZo1UdMuxcXF3t133+3OT2Nh69atQfvDdf5XXHGFl5OT45WXl7tF70+cOPG0jzcig+ub3/yma8SOhgwZ4i1ZssSLdLW1te6JV1pa6tbb29u9rKws98Tz+/e//+2lpqZ6jzzyiFv/+OOPXdBr4PsdPHjQ69Gjh/fss896ljU0NHiDBw92v0x5eXmB4IrGdlm8eLE3evToU+6PxjZR+sferbfeGrTtuuuu82666aaobBcJCa5wnb92IvRn79ixI1Czfft2t+3tt98+rWOMuKFC/9eh6NeffJGvQ4k0/q9zSUtLc7eVlZXu8x47todeKJiXlxdoD22vlpaWoBodEtALvq232ezZs+Wqq66SsWPHBm2PxnZ55pln3KfQXH/99W5Y+cILL5T169dHdZuo0aNHy/PPPy/vvvuuW3/99delrKxMrrzyyqhuF79wnf/27dvd8ODIkSMDNRdffLHbdrpt1K0/OeO/8XUokUT/WNKPydJfRH3CKP85n6w9Dhw4EKjRz4bs3bt3RLVZUVGR7NmzR3bt2nXCvmhsl/fff999Cas+R370ox/Jzp07Zd68ee5F6Hvf+15UtolavHix+4NvyJAh7oO99fXjgQcekBtvvNHtj9Z28QvX+eut/sEUSredbhtFXHCd7tehRJI5c+bIG2+84f5aDEd7WG4z/YqFO+64Q7Zt2+Ym6JxKNLWLTjbQHtfy5cvduva49A12DTMNrmhsE7VlyxbZtGmTbN68Wc4991zZu3evm8SjPYbp06dHbbuECsf5n6z+TNoo4oYKT/frUCKFzubRoaAXX3xR+vfvH9ielZXlbj+rPbRGh1h1xs+paqzRoQs9fp1RGhsb65bS0lJ56KGH3H3/eUVTu/Tr10/OOeecoG1Dhw51H1wdzc+Vu+66y33T+g033CC5ubluptudd97pZqJGc7v4hev8tebDDz+UUEeOHDntNoq44Iq2r0PRv1a0p/Xkk0/KCy+84Kb0dqTr+oTp2B76BNMXcX97aHvFxcUF1eiHGldUVJhtszFjxsi+ffvcX8/+RXsb06ZNc/d1ynO0tcull156wqUS+r6O/0Oro/W5cvz4cenRI/ilUP/49U+Hj9Z28QvX+es3fOiQrA5R+7366qtu22m3kRfB0+EfffRRN5OloKDATYf/xz/+4UWaH/7wh252z0svveTV1NQEluPHjwdqdDaQ1jz55JNuKuuNN9540qms/fv3d9OjdSrrt7/9bTNTeb+ojrMKo7Fd9LKA2NhY74EHHvD+/ve/e0888YSXlJTkbdq0KWrbRE2fPt1N4/ZPh9dzz8jI8BYtWhQ17dLQ0OC99tprbtFYKCwsdPf9lxCF6/x1OrxelqKzCXXJzc1lOnxHv/rVr9w1K/Hx8d5FF10UmB4eafRJdrJFr+3qOJ313nvvdVNaExISvMsuu8w9+TpqbGz05syZ46WlpXmJiYnuyfTBBx94kSQ0uKKxXf74xz+6a2f0fPUSkXXr1gXtj8Y20RdffV7o9Y89e/b0Bg0a5K5pampqipp2efHFF0/6OqKhHs7z/+ijj7xp06a5a8J00ft1dXWnfbx8rQkAwJSIe48LABDZCC4AgCkEFwDAFIILAGAKwQUAMIXgAgCYQnABAEwhuAAAphBcAABTCC4AgCkEFwDAFIILACCW/D/8tlK/VJ99tQAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "img_choice_N = 1\n", + "img_samp_index = random.sample( range(len(imgs)), img_choice_N) \n", + "avg_img = get_avg_img( imgsa, img_samp_index, plot_ = False, uid =uidstr)\n", + "plt.imshow(avg_img)" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "id": "c8f47bc3-b883-42a8-aaa1-86d67b05f517", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "avg_img_gf = gaussian_filter(avg_img,2)\n", + "\n", + "\n", + "roi_mask = np.zeros_like( avg_img , dtype = np.int32)\n", + "\n", + "cutoffs =[100, 99.95,99.9, 99.8, 99.6, 99.3,98.5,97, 95]#, 90, 87, 82, 75]\n", + "width = 0.3 #30% filling\n", + " \n", + "for i in range(len(cutoffs)-1):\n", + " cutoff_high = cutoffs[i]\n", + " cutoff_low = cutoffs[i] - width*(cutoffs[i]-cutoffs[i+1]) # width is 50%\n", + " #print([cutoff_high, cutoff_low])\n", + "\n", + " # avg_img_gf_temp = avg_img_gf.copy()\n", + " # avg_img_gf_temp[np.logical_and(avg_img_gf <= np.nanpercentile(avg_img_gf,cutoff_high), np.nanpercentile(avg_img_gf,cutoff_low) < avg_img_gf)]= 0\n", + " # plt.figure()\n", + " # plt.imshow(avg_img_gf_temp,vmax = 5)\n", + " # plt.title(str(i), fontsize = 20)\n", + "\n", + "\n", + " #set ROI = numebr\n", + " roi_mask[np.logical_and(avg_img_gf <= np.nanpercentile(avg_img_gf,cutoff_high), np.nanpercentile(avg_img_gf,cutoff_low) < avg_img_gf)]= i+1\n", + "\n", + "plt.figure()\n", + "plt.imshow(roi_mask)\n", + "plt.colorbar()" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "id": "8b62e4d6-927e-45f1-a064-50fd5ab9233c", + "metadata": {}, + "outputs": [], + "source": [ + "qind, pixelist = roi.extract_label_indices(roi_mask)\n", + "noqs = len(np.unique(qind))\n", + "qval_dict = get_qval_dict( 1 + np.arange(noqs) ) " + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "12409169", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(1065, 1030)\n" + ] + } + ], + "source": [ + " \n", + "# fp = path + 'roi_mask_%s_1M.pkl'%roi_date\n", + "# #fp = path + 'roi_mask_Jan31_1M.pkl'\n", + "# fp = path + 'q_mask.pkl'\n", + "\n", + "# roi_mask,qval_dict = cpk.load( open(fp, 'rb' ) ) #for load the saved roi data\n", + "\n", + "print(roi_mask.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "a0095150", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "\n", + "if False: \n", + " qval_dict = {0: np.array([1]),\n", + " 1: np.array([2]),\n", + " 2: np.array([3]),\n", + " 3: np.array([4]),\n", + " 4: np.array([5]),\n", + " 5: np.array([6]),\n", + " 6: np.array([7]),\n", + " 7: np.array([8]),\n", + " 8: np.array([9]),\n", + " 9: np.array([10]),\n", + " 10:np.array([11]),\n", + " 11:np.array([12])}\n", + " fp = path + 'mask_SNO_online_analysis.npy'\n", + " roi_mask = np.load(fp)\n", + " print(roi_mask.shape)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "949e78a9", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#roi_mask = shift_mask(roi_mask, 10,30) #if shift mask to get new mask\n", + "#show_img(roi_mask, aspect=1.0, image_name = fp)#, center=center[::-1])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "id": "a21c5fb8", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "img_choice_N = 1\n", + "img_samp_index = random.sample( range(len(imgs)), img_choice_N) \n", + "avg_img = get_avg_img( imgsa, img_samp_index, plot_ = False, uid =uidstr)\n", + "if avg_img.max() == 0:\n", + " print('There are no photons recorded for this uid: %s'%uid)\n", + " print('The data analysis should be terminated! Please try another uid.')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "id": "2f873cb8", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[639, 441]\n" + ] + } + ], + "source": [ + "#show_img( imgsa[1000], vmin=.1, vmax= 1e1, logs=True, aspect=1,\n", + "# image_name= uidstr + '_img_avg', save=True, path=data_dir, cmap = cmap_albula )\n", + "print(center[::-1])" + ] + }, + { + "cell_type": "code", + "execution_count": 43, + "id": "65b984e8", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/nsls2/software/common/jupyter/kernel_envs/beta/.pixi/envs/default/lib/python3.12/site-packages/dask/array/core.py:1714: FutureWarning: Can't acquire a memory view of a Dask array. This will raise in the future.\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "show_img( imgsa[ 5], vmin = 1, vmax = 10, logs=False, aspect=1, #save_format='tif',\n", + " image_name= uidstr + '_img_avg', save=True, path=data_dir, cmap=cmap_albula,center=center[::-1])\n", + "# select subregion, hard coded center beam location\n", + "#show_img( imgsa[180+40*3/0.05][110:110+840*2, 370:370+840*2], vmin = 0.01, vmax = 20, logs=False, aspect=1, #save_format='tif',\n", + "# image_name= uidstr + '_img_avg', save=True, path=data_dir, cmap=cmap_albula,center=[845,839])" + ] + }, + { + "cell_type": "markdown", + "id": "a6f0a10d", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## Compress Data\n", + "* Generate a compressed data with filename\n", + "* Replace old mask with a new mask with removed hot pixels\n", + "* Do average image\n", + "* Do each image sum\n", + "* Find badframe_list for where image sum above bad_pixel_threshold\n", + "* Check shutter open frame to get good time series\n" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "28277a33", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "The non-zeros photon occupation is 0.1986900041022836.\n", + "Will Always DO apply compress process.\n" + ] + } + ], + "source": [ + "compress=True\n", + "photon_occ = len( np.where(avg_img)[0] ) / ( imgsa[0].size)\n", + "#compress = photon_occ < .4 #if the photon ocupation < 0.5, do compress\n", + "print (\"The non-zeros photon occupation is %s.\"%( photon_occ))\n", + "print(\"Will \" + 'Always ' + ['NOT', 'DO'][compress] + \" apply compress process.\")" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "id": "7b715c46", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if md['detector'] =='eiger4m_single_image' or md['detector'] == 'image': \n", + " good_start = 5 #make the good_start at least 0\n", + "elif md['detector'] =='eiger500K_single_image': \n", + " good_start = 5#100 #5 #make the good_start at least 0\n", + " \n", + "elif md['detector'] =='eiger1m_single_image' or md['detector'] == 'image': \n", + " good_start = 5 " + ] + }, + { + "cell_type": "code", + "execution_count": 46, + "id": "c2a3a338", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "bin_frame = False # True #generally make bin_frame as False\n", + "if bin_frame:\n", + " bin_frame_number=4\n", + " acquisition_period = md['acquire period']\n", + " timeperframe = acquisition_period * bin_frame_number\n", + "else:\n", + " bin_frame_number =1" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "5c8816dc", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#force_compress = False\n", + "#force_compress = True\n", + "#force_compress = True" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "f0850531-1367-438a-a033-5a16bfba9a9e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'/nsls2/data/chx/proposals/2026-3/pass-317365/'" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "outp" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "id": "65f65783", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Create a new compress file with filename as :/nsls2/data/chx/proposals/2026-3/pass-317365/Compressed_Data/uid_dd56684a-f48b-4251-89e6-6572a4aabfad.cmp.\n", + "Using a multiprocess to compress the data.\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "d0e05f9365df401082154f9d482f6d93", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(IntProgress(value=0, description='Fetching:', layout=Layout(flex='0 0 auto', height='16px', wid…" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "ename": "AttributeError", + "evalue": "'numpy.ndarray' object has no attribute 'md'", + "output_type": "error", + "traceback": [ + "\u001b[31m---------------------------------------------------------------------------\u001b[39m", + "\u001b[31mAttributeError\u001b[39m Traceback (most recent call last)", + "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[50]\u001b[39m\u001b[32m, line 18\u001b[39m\n\u001b[32m 14\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 15\u001b[39m cmp_file = \u001b[33m'/uid_%s_bined--%s.cmp'\u001b[39m%(md[\u001b[33m'uid'\u001b[39m],bin_frame_number)\n\u001b[32m 16\u001b[39m \n\u001b[32m 17\u001b[39m filename = cmp_path + cmp_file\n\u001b[32m---> \u001b[39m\u001b[32m18\u001b[39m mask2, avg_img, imgsum, bad_frame_list = compress_eigerdata(imgs, mask, md, filename, \n\u001b[32m 19\u001b[39m force_compress= force_compress, para_compress= para_compress, bad_pixel_threshold = \u001b[32m1e14\u001b[39m,\n\u001b[32m 20\u001b[39m reverse=reverse, rot90=rot90, nobytes=\u001b[32m4\u001b[39m,\n\u001b[32m 21\u001b[39m bins=bin_frame_number, num_sub= \u001b[32m100\u001b[39m, num_max_para_process= \u001b[32m500\u001b[39m, with_pickle=\u001b[38;5;28;01mTrue\u001b[39;00m,\n", + "\u001b[36mFile \u001b[39m\u001b[32m/nsls2/software/common/jupyter/kernel_envs/beta/.pixi/envs/default/lib/python3.12/site-packages/pyCHX/chx_compress.py:161\u001b[39m, in \u001b[36mcompress_eigerdata\u001b[39m\u001b[34m(images, mask, md, filename, force_compress, bad_pixel_threshold, bad_pixel_low_threshold, hot_pixel_threshold, nobytes, bins, bad_frame_list, para_compress, num_sub, dtypes, reverse, rot90, num_max_para_process, with_pickle, direct_load_data, data_path, images_per_file, copy_rawdata, new_path)\u001b[39m\n\u001b[32m 159\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m para_compress:\n\u001b[32m 160\u001b[39m \u001b[38;5;28mprint\u001b[39m(\u001b[33m\"\u001b[39m\u001b[33mUsing a multiprocess to compress the data.\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m--> \u001b[39m\u001b[32m161\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[30;43mpara_compress_eigerdata\u001b[39;49m\u001b[30;43m(\u001b[39;49m\n\u001b[32m 162\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mimages\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 163\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mmask\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 164\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mmd\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 165\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mfilename\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 166\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mbad_pixel_threshold\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mbad_pixel_threshold\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 167\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mhot_pixel_threshold\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mhot_pixel_threshold\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 168\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mbad_pixel_low_threshold\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mbad_pixel_low_threshold\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 169\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mnobytes\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mnobytes\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 170\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mbins\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mbins\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 171\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mnum_sub\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mnum_sub\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 172\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mdtypes\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mdtypes\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 173\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mreverse\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mreverse\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 174\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mrot90\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mrot90\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 175\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mnum_max_para_process\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mnum_max_para_process\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 176\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mwith_pickle\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mwith_pickle\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 177\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mdirect_load_data\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mdirect_load_data\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 178\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mdata_path\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mdata_path\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 179\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mimages_per_file\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mimages_per_file\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 180\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43mcopy_rawdata\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mcopy_rawdata\u001b[39;49m\u001b[30;43m,\u001b[39;49m\n\u001b[32m 181\u001b[39m \u001b[30;43m \u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m 182\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 183\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m init_compress_eigerdata(\n\u001b[32m 184\u001b[39m images,\n\u001b[32m 185\u001b[39m mask,\n\u001b[32m (...)\u001b[39m\u001b[32m 196\u001b[39m images_per_file=images_per_file,\n\u001b[32m 197\u001b[39m )\n", + "\u001b[36mFile \u001b[39m\u001b[32m/nsls2/software/common/jupyter/kernel_envs/beta/.pixi/envs/default/lib/python3.12/site-packages/pyCHX/chx_compress.py:297\u001b[39m, in \u001b[36mpara_compress_eigerdata\u001b[39m\u001b[34m(images, mask, md, filename, num_sub, bad_pixel_threshold, hot_pixel_threshold, bad_pixel_low_threshold, nobytes, bins, dtypes, reverse, rot90, num_max_para_process, cpu_core_number, with_pickle, direct_load_data, data_path, images_per_file, copy_rawdata, new_path)\u001b[39m\n\u001b[32m 295\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m direct_load_data:\n\u001b[32m 296\u001b[39m detector = get_detector(db[uid])\n\u001b[32m--> \u001b[39m\u001b[32m297\u001b[39m images_ = \u001b[30;43mload_data\u001b[39;49m\u001b[30;43m(\u001b[39;49m\u001b[30;43muid\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mdetector\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mreverse\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mreverse\u001b[39;49m\u001b[30;43m,\u001b[39;49m\u001b[30;43m \u001b[39;49m\u001b[30;43mrot90\u001b[39;49m\u001b[30;43m=\u001b[39;49m\u001b[30;43mrot90\u001b[39;49m\u001b[30;43m)\u001b[39;49m\n\u001b[32m 298\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m 299\u001b[39m \u001b[38;5;66;03m# print('Here for images_per_file: %s'%images_per_file)\u001b[39;00m\n\u001b[32m 300\u001b[39m \u001b[38;5;66;03m# images_ = EigerImages( data_path, images_per_file=images_per_file)\u001b[39;00m\n\u001b[32m 301\u001b[39m \u001b[38;5;66;03m# print('here')\u001b[39;00m\n\u001b[32m 302\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m copy_rawdata:\n", + "\u001b[36mFile \u001b[39m\u001b[32m/nsls2/software/common/jupyter/kernel_envs/beta/.pixi/envs/default/lib/python3.12/site-packages/pyCHX/chx_generic_functions.py:3601\u001b[39m, in \u001b[36mload_data\u001b[39m\u001b[34m(uid, detector, fill, reverse, rot90)\u001b[39m\n\u001b[32m 3598\u001b[39m imgs = \u001b[38;5;28mlist\u001b[39m(hdr.data(detector))\n\u001b[32m 3600\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(imgs[\u001b[32m0\u001b[39m]) >= \u001b[32m1\u001b[39m:\n\u001b[32m-> \u001b[39m\u001b[32m3601\u001b[39m md = \u001b[30;43mimgs\u001b[39;49m\u001b[30;43m[\u001b[39;49m\u001b[30;43m0\u001b[39;49m\u001b[30;43m]\u001b[39;49m\u001b[30;43m.\u001b[39;49m\u001b[30;43mmd\u001b[39;49m\n\u001b[32m 3602\u001b[39m imgs = pims.pipeline(\u001b[38;5;28;01mlambda\u001b[39;00m img: img)(imgs[\u001b[32m0\u001b[39m])\n\u001b[32m 3603\u001b[39m imgs.md = md\n", + "\u001b[31mAttributeError\u001b[39m: 'numpy.ndarray' object has no attribute 'md'" + ] + } + ], + "source": [ + "import time\n", + "t0= time.time()\n", + "\n", + "use_local_disk = True\n", + "\n", + "if not use_local_disk:\n", + " cmp_path = outp + 'Compressed_Data'\n", + "else:\n", + " cmp_path = '/tmp'\n", + " \n", + "\n", + "if bin_frame_number==1: \n", + " cmp_file = '/uid_%s.cmp'%md['uid']\n", + "else:\n", + " cmp_file = '/uid_%s_bined--%s.cmp'%(md['uid'],bin_frame_number)\n", + " \n", + "filename = cmp_path + cmp_file \n", + "mask2, avg_img, imgsum, bad_frame_list = compress_eigerdata(imgs, mask, md, filename, \n", + " force_compress= force_compress, para_compress= para_compress, bad_pixel_threshold = 1e14,\n", + " reverse=reverse, rot90=rot90, nobytes=4,\n", + " bins=bin_frame_number, num_sub= 100, num_max_para_process= 500, with_pickle=True,\n", + " direct_load_data =use_local_disk, data_path = data_fullpath, ) \n", + " \n", + "min_inten = 10 \n", + "good_start = max(good_start, np.where( np.array(imgsum) > min_inten )[0][0] ) \n", + "print ('The good_start frame number is: %s '%good_start)\n", + "\n", + "FD = Multifile(filename, good_start, len(imgs)//bin_frame_number )\n", + "#FD2 = MultifileBNLCustom(filename, good_start, len(imgs)//bin_frame_number )\n", + "\n", + "###For test purpose to use the first 1000 frames\n", + "####################################################################\n", + "#FD = MultifileBNLCustom(filename, good_start, 500 )\n", + "#FD = Multifile(filename, good_start, 500)\n", + "############################################################\n", + "\n", + "\n", + "uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + "print( uid_ )\n", + "plot1D( y = imgsum[ np.array( [i for i in np.arange(good_start, len(imgsum)) if i not in bad_frame_list])],\n", + " title =uidstr + '_imgsum', xlabel='Frame', ylabel='Total_Intensity', legend='imgsum' )\n", + "Nimg = int( Nimg/bin_frame_number )\n", + "run_time(t0)\n", + "\n", + "mask2 = mask * pixel_mask * Chip_Mask\n", + "mask_copy = mask.copy()\n", + "mask_copy2 = mask.copy()\n", + "\n", + "avg_img *= mask" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c34d275a", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "try:\n", + " if md['experiment']=='printing':\n", + " #p = md['printing'] #if have this printing key, will do error function fitting to find t_print0\n", + " find_tp0 = True\n", + " t_print0 = ps( y = imgsum[:400] ) * timeperframe\n", + " print( 'The start time of print: %s.' %(t_print0 ) )\n", + " else:\n", + " find_tp0 = False\n", + " print('md[experiment] is not \"printing\" -> not going to look for t_0')\n", + " t_print0 = None\n", + "except:\n", + " find_tp0 = False\n", + " print('md[experiment] is not \"printing\" -> not going to look for t_0')\n", + " t_print0 = None\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1f9bf809", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "show_img( avg_img*mask, vmin=1e-5, vmax= 1e3, logs=True, aspect=1, #save_format='tif',\n", + " image_name= uidstr + '_img_avg', save=True, \n", + " path=data_dir, center=center[::-1], cmap = cmap_albula ) #plt.cm.jet )#" + ] + }, + { + "cell_type": "markdown", + "id": "c596e158", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## Get bad frame list by a polynominal fit" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fc61a5d8", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "good_end= None # 2000 \n", + "if good_end is not None:\n", + " FD = Multifile(filename, good_start, min( len(imgs)//bin_frame_number, good_end) )\n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( uid_ )\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4fe1f522", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "re_define_good_start =False\n", + "if re_define_good_start:\n", + " good_start = 180\n", + " #good_end = 19700\n", + " good_end = len(imgs)\n", + " FD = Multifile(filename, good_start, good_end) \n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( FD.beg, FD.end)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5e5c7006", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "bad_frame_list = get_bad_frame_list( imgsum, fit='both', plot=True,polyfit_order = 30, \n", + " scale= 8.0, good_start = good_start, good_end=good_end, uid= uidstr, path=data_dir)\n", + "\n", + "print( 'The bad frame list length is: %s'%len(bad_frame_list) )" + ] + }, + { + "cell_type": "markdown", + "id": "2c68c888", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "### Creat new mask by masking the bad pixels and get new avg_img" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d4c55005", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "imgsum_y = imgsum[ np.array( [i for i in np.arange( len(imgsum)) if i not in bad_frame_list])]\n", + "imgsum_x = np.arange( len( imgsum_y))\n", + "save_lists( [imgsum_x, imgsum_y], label=['Frame', 'Total_Intensity'],\n", + " filename=uidstr + '_img_sum_t', path= data_dir )\n" + ] + }, + { + "cell_type": "markdown", + "id": "bf5a5a41", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "### Plot time~ total intensity of each frame" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ef04b86e", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "plot1D( y = imgsum_y, title = uidstr + '_img_sum_t', xlabel='Frame', c='b',\n", + " ylabel='Total_Intensity', legend='imgsum', save=True, path=data_dir)" + ] + }, + { + "cell_type": "markdown", + "id": "e3a3a40d", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## Get Dynamic Mask (currently designed for 500K)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3d439707", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if md['detector'] =='eiger4m_single_image' or md['detector'] == 'image': \n", + " pass\n", + "elif md['detector'] =='eiger500K_single_image': \n", + " #if md['cam_acquire_period'] <= 0.00015: #will check this logic\n", + " if imgs[0].dtype == 'uint16':\n", + " print('Create dynamic mask for 500K due to 9K data acquistion!!!')\n", + " #bdp = find_bad_pixels_FD( bad_frame_list, FD, img_shape = avg_img.shape, threshold= 15 ) \n", + " bdp = find_bad_pixels_FD( np.arange(Nimg), FD, img_shape = avg_img.shape, threshold= 15 ) \n", + " mask = mask_copy2.copy()\n", + " mask *=bdp \n", + " mask_copy = mask.copy()\n", + " show_img( mask, image_name='New Mask_uid=%s'%uid, aspect=1 )" + ] + }, + { + "cell_type": "markdown", + "id": "ce55f229", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# Static Analysis" + ] + }, + { + "cell_type": "markdown", + "id": "662ed9c2", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## SAXS Scattering Geometry" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "22fba359", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "setup_pargs " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f61bae69", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='saxs':\n", + " ## Get circular average| * Do plot and save q~iq\n", + " mask = mask_copy.copy()\n", + " hmask = create_hot_pixel_mask( avg_img, threshold = 1e8, center=center, center_radius= 10)\n", + " qp_saxs, iq_saxs, q_saxs = get_circular_average( avg_img * Chip_Mask , mask * hmask, save=True,\n", + " pargs=setup_pargs )\n", + " plot_circular_average( qp_saxs, iq_saxs, q_saxs, pargs=setup_pargs, show_pixel=True,\n", + " xlim=[qp_saxs.min(), qp_saxs.max()*1.0], ylim = [iq_saxs.min(), iq_saxs.max()*2] )\n", + " mask =np.array( mask * hmask, dtype=bool) " + ] + }, + { + "cell_type": "markdown", + "id": "fdcfc2d6", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## SAXS to fit the form factor" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "26a75b7b", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#%run -i ~/pyCHX_link/pyCHX/SAXS.py" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dfd5e62c", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='saxs': \n", + " if run_fit_form: \n", + " qp, pq = q_saxs, iq_saxs\n", + " fitp, fitpe, q_, fitq, result = get_form_factor_fit_lmfit( qp, pq, \n", + " guess_values={'radius': 1180, 'sigma':0.05,'delta_rho':1e-9, 'background':5e-5, \n", + " 'qpower_scale':5e-10, 'qpower': -4.0 }, \n", + " guess_limit = { 'radius': [1000, 1500], 'sigma':[1e-3, .5], 'delta_rho': [1e-16, 1e-4], \n", + " 'background': [1e-6, 1e-3], 'qpower_scale': [1e-16, 1], 'qpower': [ -5,-3]}, \n", + " fit_range=[0.005, 0.03], \n", + " fit_variables={'radius': True, 'sigma':True, 'delta_rho':True, 'background': True,\n", + " 'qpower_scale':True, 'qpower':False},\n", + " fit_func='G', qpower_bg= True )\n", + " \n", + " r,sig=fitp[ 'radius'], fitp['sigma']\n", + " radius, sigma, delta_rho, background, qpower_scale, qpower = (fitp[ 'radius'], fitp['sigma'],\n", + " fitp['delta_rho'],fitp['background'],\n", + " fitp[ 'qpower_scale'], fitp['qpower'] ) \n", + " bk= qpower_scale*qp**( qpower ) + background\n", + " ff= poly_sphere_form_factor_intensity( qp, radius=radius, sigma=sigma, delta_rho=delta_rho, \n", + " background=0, num_points= 20,\n", + " spread=5,fit_func= 'G' ) + bk\n", + " #report_fit( result)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d146dbdb", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='saxs': \n", + " if run_fit_form: \n", + " fig = plt.figure( )#figsize=[8,6]) \n", + " ax = fig.add_subplot( 1,1,1 ) \n", + " plot1D(x=qp,y=pq,ax=ax,m='o', ls='',c='k', legend='data', logy=True) \n", + " #plot1D(x=q_,y=fitq,ax=ax,m='', ls='-',c='r', legend='fitG_bg', logy=True)#, logx=True ) \n", + " plot1D(x=qp,y=ff,ax=ax,m='', ls='-',c='b', legend='fitG_bgA', logy=True)#, logx=True ) \n", + " #plot1D(x=q, y = bk, ls='--',c='g',ax=ax, lw=1, markersize=2,)\n", + " #qpower_scale, qpower\n", + " plot1D(x=qp, y= qp**( qpower ) * np.exp( qpower_scale ) /1e8, ax=ax, m='', ls='-', c='k', legend= r'$q^{%.1f}$'% qpower) \n", + "\n", + " txts = r'radius' + r' = %.2f +/- %.2f '%( radius/10, fitpe['radius'] ) + r'$ nm$' \n", + " ax.text(x =0.02, y=.2, s=txts, fontsize=14, transform=ax.transAxes)\n", + " txts = r'sigma' + r' = %.4f +/- %.4f'%( sigma, fitpe['sigma']) \n", + " #txts = r'$\\beta$' + r'$ = %.3f$'%(beta[i]) + r'$ s^{-1}$'\n", + " ax.text(x =0.02, y=.1, s=txts, fontsize=14, transform=ax.transAxes) \n", + "\n", + " ax.set_xscale('log') \n", + " #ax.set_ylim( [1.00, 1.15 ] )\n", + " ax.set_xlabel(r'$q$ ('r'$\\AA^{-1}$)', fontsize=18) \n", + " ax.set_ylabel(r'$I(q)$', fontsize=18) \n", + " #ax.set_title( 'uid=%s'%uid, fontsize=18) \n", + " plt.tight_layout()\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0e29ea93", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='saxs': \n", + " qr = np.array( [qval_dict[k][0] for k in sorted( qval_dict.keys())] )\n", + " if qphi_analysis == False:\n", + " try:\n", + " qr_cal, qr_wid = get_QrQw_From_RoiMask( roi_mask, setup_pargs ) \n", + " print(len(qr)) \n", + " if (qr_cal - qr).sum() >=1e-3:\n", + " print( 'The loaded ROI mask might not be applicable to this UID: %s.'%uid)\n", + " print('Please check the loaded roi mask file.')\n", + " except:\n", + " print('Something is wrong with the roi-mask. Please check the loaded roi mask file.') \n", + " \n", + " \n", + " show_ROI_on_image( avg_img*roi_mask, roi_mask, center, label_on = False, rwidth = 840, alpha=.9, \n", + " save=True, path=data_dir, uid=uidstr, vmin= 1e-3,\n", + " vmax= 1e-1, #np.max(avg_img),\n", + " aspect=1,\n", + " show_roi_edge=True, \n", + " show_ang_cor = True) \n", + " plot_qIq_with_ROI( q_saxs, iq_saxs, np.unique(qr), logs=True, uid=uidstr, \n", + " xlim=[q_saxs.min(), q_saxs.max()*1.02],#[0.0001,0.08],\n", + " ylim = [iq_saxs.min(), iq_saxs.max()*1.02], save=True, path=data_dir)\n", + " \n", + " roi_mask = roi_mask * mask" + ] + }, + { + "cell_type": "markdown", + "id": "73ff9615", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# Time Depedent I(q) Analysis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "eee26117", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='saxs':\n", + " Nimg = FD.end - FD.beg \n", + " time_edge = create_time_slice( Nimg, slice_num= 3, slice_width= 2, edges = None )\n", + " time_edge = np.array( time_edge ) + good_start\n", + " #print( time_edge ) \n", + " qpt, iqst, qt = get_t_iqc( FD, time_edge, mask*Chip_Mask, pargs=setup_pargs, nx=1500, show_progress= False )\n", + " plot_t_iqc( qt, iqst, time_edge, pargs=setup_pargs, xlim=[qt.min(), qt.max()],\n", + " ylim = [iqst.min(), iqst.max()], save=True )" + ] + }, + { + "cell_type": "markdown", + "id": "775edaea", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## For fit one peak" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "91d403d2", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='saxs':\n", + " if fit_peak: \n", + " q1 = 0.162\n", + " x = q_saxs\n", + " y= iq_saxs\n", + " aind = [ find_index( q_saxs, q1 ) ]\n", + " w = 50\n", + " xrange = [ aind[0] -w, aind[0] + w] \n", + " cen, cen_std, wid, wid_std, xf, out = fit_one_peak_curve( x, y, xrange ) \n", + " fp = data_dir + uidstr + '_qIq_fit.png' \n", + " ax = plot_xy_with_fit( x, y, xf, out, cen, cen_std,wid, wid_std,\n", + " xlim=[0.01,0.3],xlabel= 'q ('r'$\\AA^{-1}$)',\n", + " ylabel='I(q)', filename=fp) " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "45392cfd", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_invariant_analysis:\n", + " if scat_geometry =='saxs':\n", + " invariant = get_iq_invariant( qt, iqst )\n", + " time_stamp = time_edge[:,0] * timeperframe\n", + "\n", + " if scat_geometry =='saxs':\n", + " plot_q2_iq( qt, iqst, time_stamp,pargs=setup_pargs,ylim=[ -0.001, 0.01] , \n", + " xlim=[0.007,0.2],legend_size= 6 )\n", + "\n", + " if scat_geometry =='saxs':\n", + " plot_time_iq_invariant( time_stamp, invariant, pargs=setup_pargs, )\n", + "\n", + " if False:\n", + " iq_int = np.zeros( len(iqst) )\n", + " fig, ax = plt.subplots()\n", + " q = qt\n", + " for i in range(iqst.shape[0]):\n", + " yi = iqst[i] * q**2\n", + " iq_int[i] = yi.sum()\n", + " time_labeli = 'time_%s s'%( round( time_edge[i][0] * timeperframe, 3) )\n", + " plot1D( x = q, y = yi, legend= time_labeli, xlabel='Q (A-1)', ylabel='I(q)*Q^2', title='I(q)*Q^2 ~ time',\n", + " m=markers[i], c = colors[i], ax=ax, ylim=[ -0.001, 0.01] , xlim=[0.007,0.2],\n", + " legend_size=4)\n", + "\n", + " #print( iq_int )" + ] + }, + { + "cell_type": "markdown", + "id": "7bb9b2ba", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# GiSAXS Scattering Geometry" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a12871c2", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='gi_saxs': \n", + " plot_qzr_map( qr_map, qz_map, inc_x0, ticks = ticks, data= avg_img, uid= uidstr, path = data_dir )" + ] + }, + { + "cell_type": "markdown", + "id": "67839050", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## Static Analysis for gisaxs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "808448b6", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='gi_saxs': \n", + " #roi_masks, qval_dicts = get_gisaxs_roi( Qrs, Qzs, qr_map, qz_map, mask= mask )\n", + " show_qzr_roi( avg_img, roi_masks, inc_x0, ticks[:4], alpha=0.5, save=True, path=data_dir, uid=uidstr )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "60b41cfe", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='gi_saxs': \n", + " Nimg = FD.end - FD.beg \n", + " time_edge = create_time_slice( N= Nimg, slice_num= 3, slice_width= 2, edges = None )\n", + " time_edge = np.array( time_edge ) + good_start\n", + " print( time_edge ) \n", + " qrt_pds = get_t_qrc( FD, time_edge, Qrs, Qzs, qr_map, qz_map, mask=mask, path=data_dir, uid = uidstr ) \n", + " plot_qrt_pds( qrt_pds, time_edge, qz_index = 0, uid = uidstr, path = data_dir )" + ] + }, + { + "cell_type": "markdown", + "id": "09f51336", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# Make a Profile Plot" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fe74c076", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='gi_saxs':\n", + " if run_profile_plot:\n", + " xcorners= [ 1100, 1250, 1250, 1100 ]\n", + " ycorners= [ 850, 850, 950, 950 ] \n", + " waterfall_roi_size = [ xcorners[1] - xcorners[0], ycorners[2] - ycorners[1] ]\n", + " waterfall_roi = create_rectangle_mask( avg_img, xcorners, ycorners )\n", + " #show_img( waterfall_roi * avg_img, aspect=1,vmin=.001, vmax=1, logs=True, )\n", + " wat = cal_waterfallc( FD, waterfall_roi, qindex= 1, bin_waterfall=True,\n", + " waterfall_roi_size = waterfall_roi_size,save =True, path=data_dir, uid=uidstr)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c8128339", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='gi_saxs':\n", + " if run_profile_plot:\n", + " plot_waterfallc( wat, qindex=1, aspect=None, vmin=1, vmax= np.max( wat), uid=uidstr, save =True, \n", + " path=data_dir, beg= FD.beg)" + ] + }, + { + "cell_type": "markdown", + "id": "c07716ee", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## Dynamic Analysis for gi_saxs" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ab125276", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='gi_saxs': \n", + " show_qzr_roi( avg_img, roi_mask, inc_x0, ticks[:4], alpha=0.5, save=True, path=data_dir, uid=uidstr ) \n", + " ## Get 1D Curve (Q||-intensity¶)\n", + " qr_1d_pds = cal_1d_qr( avg_img, Qr, Qz, qr_map, qz_map, inc_x0= None, mask=mask, setup_pargs=setup_pargs )\n", + " plot_qr_1d_with_ROI( qr_1d_pds, qr_center=np.unique( np.array(list( qval_dict.values() ) )[:,0] ),\n", + " loglog=True, save=True, uid=uidstr, path = data_dir)" + ] + }, + { + "cell_type": "markdown", + "id": "49477900", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# GiWAXS Scattering Geometry" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9ad8fc3b", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if scat_geometry =='gi_waxs':\n", + " show_ROI_on_image( avg_img, roi_mask, label_on = True, alpha=.5,\n", + " save=True, path=data_dir, uid=uidstr, vmin=0.1, vmax=500)" + ] + }, + { + "cell_type": "markdown", + "id": "396ad9ab", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "* Extract the labeled array" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4677f6b4", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "qind, pixelist = roi.extract_label_indices(roi_mask)\n", + "noqs = len(np.unique(qind))\n", + "print(noqs)" + ] + }, + { + "cell_type": "markdown", + "id": "e9b7a358", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "* Number of pixels in each q box" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "840c4c56", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "nopr = np.bincount(qind, minlength=(noqs+1))[1:]\n", + "nopr" + ] + }, + { + "cell_type": "markdown", + "id": "88d33c7e", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## Check one ROI intensity" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d51a42af", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "roi_inten = check_ROI_intensity( avg_img, roi_mask, ring_number= 1, uid =uidstr ) #roi starting from 1" + ] + }, + { + "cell_type": "markdown", + "id": "1bd2b253", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## Do a waterfall analysis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "26ce4a19", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "qth_interest = 2 #the second ring. #qth_interest starting from 1\n", + "if scat_geometry =='saxs' or scat_geometry =='gi_waxs' or scat_geometry == 'gi_saxs':\n", + " if run_waterfall: \n", + " wat = cal_waterfallc( FD, roi_mask, qindex= qth_interest, save =True, path=data_dir, uid=uidstr)\n", + " plot_waterfallc( wat, qth_interest, aspect= None, vmin=1e-1, vmax= wat.max(), uid=uidstr, save =True, \n", + " path=data_dir, beg= FD.beg, cmap = cmap_vge )\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fd5aa9bf", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "ring_avg = None \n", + "if run_t_ROI_Inten:\n", + " times_roi, mean_int_sets = cal_each_ring_mean_intensityc(FD, roi_mask, timeperframe = None, multi_cor= True )#False )#True ) \n", + " mean_int_setsF = np.zeros( [FD.end, mean_int_sets.shape[1] ] )\n", + " mean_int_setsF[FD.beg:FD.end] =mean_int_sets\n", + " plot_each_ring_mean_intensityc( times_roi, mean_int_sets, uid = uidstr, save=True, path=data_dir )\n", + " roi_avg = np.average( mean_int_sets, axis=0)" + ] + }, + { + "cell_type": "markdown", + "id": "fca10e39", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## Analysis for mass center of reflective beam center" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3750e1d1", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_get_mass_center:\n", + " cx, cy = get_mass_center_one_roi(FD, roi_mask, roi_ind=25)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "78648a30", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_get_mass_center:\n", + " fig,ax=plt.subplots(2)\n", + " plot1D( cx, m='o', c='b',ax=ax[0], legend='mass center-refl_X', \n", + " ylim=[940, 960], ylabel='posX (pixel)')\n", + " plot1D( cy, m='s', c='r',ax=ax[1], legend='mass center-refl_Y', \n", + " ylim=[1540, 1544], xlabel='frames',ylabel='posY (pixel)')" + ] + }, + { + "cell_type": "markdown", + "id": "c17c4322", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## One time Correlation\n", + "\n", + "Note : Enter the number of buffers for Muliti tau one time correlation\n", + "number of buffers has to be even. More details in https://github.com/scikit-beam/scikit-beam/blob/master/skbeam/core/correlation.py" + ] + }, + { + "cell_type": "markdown", + "id": "5272bc94", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "### if define another good_series" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5c167ee4", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "good_start_g2 = FD.beg\n", + "good_end_g2 = FD.end\n", + "define_good_series = False\n", + "#define_good_series = True\n", + "if define_good_series:\n", + " good_start_g2 = 1000 #399\n", + " good_end_g2 = 2000 #1486\n", + " FD = Multifile(filename, beg = good_start_g2, end = good_end_g2) #end=1000)\n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( uid_ )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3cc0b157", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#use_SG = False # True #False #True\n", + "#use_SG_bin_frames = True\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bf48fc5b", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "scrolled": true, + "tags": [] + }, + "outputs": [], + "source": [ + "if use_sqnorm:#for transmision SAXS\n", + " norm = get_pixelist_interp_iq( qp_saxs, iq_saxs, roi_mask, center)\n", + " print('Using circular average in the normalization of G2 for SAXS scattering.')\n", + "elif use_SG:#for Gi-SAXS or WAXS\n", + " avg_imgf = sgolay2d( avg_img, window_size= 11, order= 5) * mask\n", + " norm=np.ravel(avg_imgf)[pixelist] \n", + " print('Using smoothed image by SavitzkyGolay filter in the normalization of G2.') \n", + "elif use_SG_bin_frames:#for Gi-SAXS or WAXS\n", + " avg_imgf = sgolay2d( avg_img, window_size= 11, order= 5) * mask\n", + " norm_avg=np.ravel(avg_imgf)[pixelist] \n", + " #print('Using smoothed image by SavitzkyGolay filter in the normalization of G2.')\n", + " bins_number = 1 \n", + " norm = get_SG_norm( FD, pixelist, bins=bins_number, mask=mask, window_size= 11, order=5 ) \n", + " print('Using smoothed bined: %s frames by SavitzkyGolay filter in the normalization of G2.'%bins_number) \n", + "else: \n", + " norm= None\n", + " print('Using simple (average) normalization of G2.') \n", + "\n", + "if use_imgsum_norm:\n", + " imgsum_ = imgsum\n", + " print('Using frame total intensity for intensity normalization in g2 calculation.') \n", + "else:\n", + " imgsum_ = None \n", + "import time" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "79b70152", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#np.save( data_dir + 'norm_SG_per_frame',norm)\n", + "#norm = np.load( data_dir + 'norm_SG_per_frame.npy' )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2ddf0ca2", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_one_time: \n", + " t0 = time.time() \n", + " if cal_g2_error: \n", + " g2,lag_steps,g2_err = cal_g2p(FD,roi_mask,bad_frame_list,good_start, num_buf = 8,\n", + " num_lev= None,imgsum= imgsum_, norm=norm, cal_error= True )\n", + " else: \n", + " g2,lag_steps = cal_g2p(FD,roi_mask,bad_frame_list,good_start, num_buf = 8,\n", + " num_lev= None,imgsum= imgsum_, norm=norm, cal_error= False )\n", + "\n", + " run_time(t0)\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9f570b03", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "lag_steps = lag_steps[:g2.shape[0]]\n", + "g2.shape[1]\n", + "lag_steps" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9e9fa0c1", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "lag_steps.shape\n", + "g2.shape" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a92fae2c", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_one_time:\n", + " \n", + " taus = lag_steps * timeperframe \n", + " try:\n", + " g2_pds = save_g2_general( g2, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0],\n", + " qz = np.array( list( qval_dict.values() ) )[:g2.shape[1],1],\n", + " uid=uid_+'_g2.csv', path= data_dir, return_res=True )\n", + " except:\n", + " g2_pds = save_g2_general( g2, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0], \n", + " uid=uid_+'_'+q_mask_name+'_g2.csv', path= data_dir, return_res=True ) \n", + " if cal_g2_error: \n", + " try:\n", + " g2_err_pds = save_g2_general( g2_err, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0],\n", + " qz = np.array( list( qval_dict.values() ) )[:g2.shape[1],1],\n", + " uid=uid_+'_g2_err.csv', path= data_dir, return_res=True )\n", + " except:\n", + " g2_err_pds = save_g2_general( g2_err, taus=taus,qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0], \n", + " uid=uid_+'_'+q_mask_name+'_g2_err.csv', path= data_dir, return_res=True ) \n", + " " + ] + }, + { + "cell_type": "markdown", + "id": "fa949d59", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# Fit g2" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0168bfe7", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_one_time:\n", + " try:\n", + " g2_fit_result, taus_fit, g2_fit = get_g2_fit_general( g2, taus, \n", + " function = fit_g2_func, vlim=[0.95, 1.05], fit_range= None, \n", + " fit_variables={'baseline':False, 'beta': True, 'alpha':True,'relaxation_rate':True,}, \n", + " guess_values={'baseline':1.0,'beta': 0.03,'alpha':1.0,'relaxation_rate':0.0005},\n", + " guess_limits = dict( baseline =[.9, 1.3], alpha=[0, 2],\n", + " beta = [0, 1], relaxation_rate= [1e-7, 1000]) ,) \n", + " g2_fit_paras = save_g2_fit_para_tocsv(g2_fit_result, filename= uid_ +'_'+q_mask_name +'_g2_fit_paras.csv', path=data_dir ) \n", + " g2_fit_failed = False\n", + " except:\n", + " g2_fit_failed = True\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2b87c00a", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "scat_geometry_" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f9d7a7d5", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "scrolled": true, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_one_time:\n", + " if cal_g2_error:\n", + " g2_fit_err = np.zeros_like(g2_fit)\n", + " if not g2_fit_failed:\n", + " \n", + " plot_g2_general( g2_dict={1:g2, 2:g2_fit}, taus_dict={1:taus, 2:taus_fit},\n", + " vlim=[0.95, 1.05], g2_err_dict= {1:g2_err, 2: g2_fit_err},\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= g2_fit_result, geometry= scat_geometry_,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '_fit')\n", + " else:\n", + " plot_g2_general( g2_dict={1:g2, }, taus_dict={1:taus,},\n", + " vlim=[0.95, 1.05], g2_err_dict= {1:g2_err},\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])),\n", + " fit_res= None, geometry= scat_geometry_,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '')\n", + " \n", + " else: \n", + " if not g2_fit_failed:\n", + " plot_g2_general( g2_dict={1:g2, 2:g2_fit}, taus_dict={1:taus, 2:taus_fit}, vlim=[0.95, 1.05],\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= g2_fit_result, geometry= scat_geometry_,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '_fit')\n", + " else: \n", + " plot_g2_general( g2_dict={1:g2}, taus_dict={1:taus}, vlim=[0.95, 1.05],\n", + " qval_dict = dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= None, geometry= scat_geometry_,filename= uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '') \n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f9845b40", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_one_time:\n", + " try:\n", + " if True:\n", + " fs, fe = 0, 8\n", + " #fs,fe=0, 6\n", + " qval_dict_ = {k:qval_dict[k] for k in list(qval_dict.keys())[fs:fe] }\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict_, g2_fit_paras['relaxation_rate'][fs:fe], \n", + " geometry= scat_geometry_ )\n", + " plot_q_rate_fit_general( qval_dict_, g2_fit_paras['relaxation_rate'][fs:fe], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ , path= data_dir )\n", + " elif False:\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict, g2_fit_paras['relaxation_rate'],\n", + " fit_range=[0, 26], geometry= scat_geometry_ ) \n", + " plot_q_rate_fit_general( qval_dict, g2_fit_paras['relaxation_rate'], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ ,\n", + " show_fit=False, path= data_dir, plot_all_range=False) \n", + " else:\n", + " ##plot log_q, log_rate\n", + " plot_q_rate_general( qval_dict, g2_fit_paras['relaxation_rate'], \n", + " geometry= scat_geometry_,uid=uid_ , path= data_dir )\n", + "\n", + " plot_q_g2fitpara_general( qval_dict, g2_fit_paras, \n", + " geometry= scat_geometry_,uid=uid_ , path= data_dir )\n", + " except:\n", + " pass\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "32a424c0", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#plot1D( x= qr, y=g2_fit_paras['beta'], ls='-', m = 'o', c='b', ylabel=r'$\\beta$', xlabel=r'$Q( \\AA^{-1} ) $' )\n" + ] + }, + { + "cell_type": "markdown", + "id": "005a569c", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# For two-time" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4b34762d", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "define_good_series = True\n", + "if define_good_series:\n", + " good_start = 0\n", + " good_end =md['number of images']\n", + " FD = Multifile(filename, beg = good_start, end = good_end)\n", + " uid_ = uidstr + '_fra_%s_%s'%(FD.beg, FD.end)\n", + " print( uid_ )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "45eb1a84", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "scrolled": true, + "tags": [] + }, + "outputs": [], + "source": [ + "data_pixel = None\n", + "if run_two_time: \n", + " data_pixel = Get_Pixel_Arrayc( FD, pixelist, norm= norm, ).get_data()\n", + " \n", + " ### With another normalizaiton by using roi_intensity for each frame\n", + " #data_pixel = Get_Pixel_Arrayc( FD, pixelist, norm= norm, mean_int_sets = mean_int_setsF,qind=qind ).get_data()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a2d45d67", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "scrolled": true, + "tags": [] + }, + "outputs": [], + "source": [ + "import time\n", + "t0=time.time()\n", + "g12b=None\n", + "if run_two_time: \n", + " g12b = auto_two_Arrayc( data_pixel, roi_mask, index = None )\n", + " if run_dose:\n", + " np.save( data_dir + 'uid=%s_g12b'%uid, g12b)\n", + "run_time( t0 ) " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "972ed654", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_two_time:\n", + " \n", + " show_C12( np.nan_to_num( g12b ), q_ind= 2, qlabel=dict(itertools.islice(qval_dict.items(),g12b.shape[2])),\n", + " N1= FD.beg,logs=True, N2=min( FD.end,10000), \n", + " vmin= 1.00, vmax=1.3, timeperframe=timeperframe,save=True, \n", + " path= data_dir, uid = uid_ ,cmap=plt.cm.jet)#cmap=cmap_albula) \n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d6b70dba", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "multi_tau_steps = True\n", + "if run_two_time:\n", + " if lag_steps is None:\n", + " num_bufs=8\n", + " noframes = FD.end - FD.beg\n", + " num_levels = int(np.log( noframes/(num_bufs-1))/np.log(2) +1) +1\n", + " tot_channels, lag_steps, dict_lag = multi_tau_lags(num_levels, num_bufs)\n", + " max_taus= lag_steps.max()\n", + " \n", + " #max_taus= lag_steps.max() \n", + " max_taus = Nimg \n", + " t0=time.time()\n", + " #tausb = np.arange( g2b.shape[0])[:max_taus] *timeperframe\n", + " if multi_tau_steps:\n", + " lag_steps_ = lag_steps[ lag_steps <= g12b.shape[0] ]\n", + " g2b = get_one_time_from_two_time(g12b)[lag_steps_]\n", + " tausb = lag_steps_ *timeperframe\n", + " else:\n", + " tausb = (np.arange( g12b.shape[0]) *timeperframe)[:-200]\n", + " g2b = (get_one_time_from_two_time(g12b))[:-200]\n", + " run_time(t0)\n", + " \n", + " g2b_pds = save_g2_general( g2b, taus=tausb, qr= np.array( list( qval_dict.values() ) )[:g2.shape[1],0],\n", + " qz=None, uid=uid_+'_'+q_mask_name+'_g2b.csv', path= data_dir, return_res=True )\n", + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "67c32875", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_two_time: \n", + " g2b_fit_result, tausb_fit, g2b_fit = get_g2_fit_general( g2b, tausb, \n", + " function = fit_g2_func, vlim=[0.95, 1.05], fit_range= None, \n", + " fit_variables={'baseline':False, 'beta': True, 'alpha':True,'relaxation_rate':True}, \n", + " guess_values={'baseline':1.0,'beta': 0.15,'alpha':1.0,'relaxation_rate':1e-3,},\n", + " guess_limits = dict( baseline =[1, 1.8], alpha=[0, 2],\n", + " beta = [0, 1], relaxation_rate= [1e-8, 5000]) ) \n", + " g2b_fit_paras = save_g2_fit_para_tocsv(g2b_fit_result, filename= uid_ +'_'+q_mask_name+'_g2b_fit_paras.csv', path=data_dir )\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "00ead5e3", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#plot1D( x = tausb[1:], y =g2b[1:,0], ylim=[0.95, 1.46], xlim = [0.0001, 10], m='', c='r', ls = '-',\n", + "# logx=True, title='one_time_corelation', xlabel = r\"$\\tau $ $(s)$\", )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "41dd1085", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "scrolled": true, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_two_time:\n", + " plot_g2_general( g2_dict={1:g2b, 2:g2b_fit}, taus_dict={1:tausb, 2:tausb_fit}, vlim=[0.95, 1.05],\n", + " qval_dict=dict(itertools.islice(qval_dict.items(),g2.shape[1])), fit_res= g2b_fit_result, geometry=scat_geometry_,filename=uid_+'_g2', \n", + " path= data_dir, function= fit_g2_func, ylabel='g2', append_name= '_b_fit')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "81c2ced7", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_two_time:\n", + " D0b, qrate_fit_resb = get_q_rate_fit_general( dict(itertools.islice(qval_dict.items(),g2.shape[1])), g2b_fit_paras['relaxation_rate'],\n", + " fit_range=[0, 10], geometry= scat_geometry_ )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6248dc75", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_two_time:\n", + " try:\n", + " if True:\n", + " fs, fe = 0, 8\n", + " #fs,fe=0, 6\n", + " qval_dict_ = {k:qval_dict[k] for k in list(qval_dict.keys())[fs:fe] }\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict_, g2b_fit_paras['relaxation_rate'][fs:fe], \n", + " geometry= scat_geometry_ )\n", + " plot_q_rate_fit_general( qval_dict_, g2b_fit_paras['relaxation_rate'][fs:fe], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' , path= data_dir )\n", + " elif False:\n", + " D0, qrate_fit_res = get_q_rate_fit_general( qval_dict, g2b_fit_paras['relaxation_rate'],\n", + " fit_range=[0, 26], geometry= scat_geometry_ ) \n", + " plot_q_rate_fit_general( qval_dict, g2_fit_paras['relaxation_rate'], qrate_fit_res, \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' ,\n", + " show_fit=False, path= data_dir, plot_all_range=False) \n", + " else:\n", + " ##plot log_q, log_rate\n", + " plot_q_rate_general( qval_dict, g2b_fit_paras['relaxation_rate'], \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' , path= data_dir )\n", + "\n", + " plot_q_g2fitpara_general( qval_dict, g2b_fit_paras, \n", + " geometry= scat_geometry_,uid=uid_ +'_two_time' , path= data_dir )\n", + " except:\n", + " pass\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "181b70ec", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "scrolled": true, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_two_time and run_one_time:\n", + " plot_g2_general( g2_dict={1:g2, 2:g2b}, taus_dict={1:taus, 2:tausb},vlim=[0.99, 1.007],\n", + " qval_dict=dict(itertools.islice(qval_dict.items(),g2.shape[1])), g2_labels=['from_one_time', 'from_two_time'],\n", + " geometry=scat_geometry_,filename=uid_+'_g2_two_g2', path= data_dir, ylabel='g2', )" + ] + }, + { + "cell_type": "markdown", + "id": "3d2777a2", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# Run Dose dependent analysis" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9c14dcf2", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#run_dose = True" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "86951873", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_dose:\n", + " get_two_time_mulit_uids( [uid], roi_mask, norm= norm, bin_frame_number=1, \n", + " path= data_dir0, force_generate=False, compress_path = cmp_path + '/' )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3ef1b0e8", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "try:\n", + " print( md['transmission'] )\n", + "except:\n", + " md['transmission'] =1" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e3dc29c5", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "exposuretime" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b93c76ad", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_dose:\n", + " N = len(imgs)\n", + " print(N)\n", + " #exposure_dose = md['transmission'] * exposuretime* np.int_([ N/16, N/8, N/4 ,N/2, 3*N/4, N*0.99 ])\n", + " exposure_dose = md['transmission'] * exposuretime* np.int_([ N/8, N/4 ,N/2, 3*N/4, N*0.99 ])\n", + " \n", + " print( exposure_dose )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e4f57b13", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_dose:\n", + " taus_uids, g2_uids = get_series_one_time_mulit_uids( [ uid ], qval_dict, good_start=good_start, \n", + " path= data_dir0, exposure_dose = exposure_dose, num_bufs =8, save_g2= False,\n", + " dead_time = 0, trans = [ md['transmission'] ] )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2d741513", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_dose: \n", + " plot_dose_g2( taus_uids, g2_uids, ylim=[1.0, 1.2], vshift= 0.00,\n", + " qval_dict = qval_dict, fit_res= None, geometry= scat_geometry_,\n", + " filename= '%s_dose_analysis'%uid_, \n", + " path= data_dir, function= None, ylabel='g2_Dose', g2_labels= None, append_name= '' )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dd53d1c1", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_dose:\n", + " qth_interest = 5\n", + " plot_dose_g2( taus_uids, g2_uids, qth_interest= qth_interest, ylim=[0.98, 1.4], vshift= 0.00,\n", + " qval_dict = qval_dict, fit_res= None, geometry= scat_geometry_,\n", + " filename= '%s_dose_analysis'%uidstr, \n", + " path= data_dir, function= None, ylabel='g2_Dose', g2_labels= None, append_name= '' )" + ] + }, + { + "cell_type": "markdown", + "id": "e440d00a", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# Four Time Correlation" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a8e66e8e", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_four_time:\n", + " t0=time.time()\n", + " g4 = get_four_time_from_two_time(g12b, g2=g2b)[:int(max_taus)]\n", + " run_time(t0)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "80ee9c40", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_four_time:\n", + " taus4 = np.arange( g4.shape[0])*timeperframe \n", + " g4_pds = save_g2_general( g4, taus=taus4, qr=np.array( list( qval_dict.values() ) )[:,0],\n", + " qz=None, uid=uid_ +'_g4.csv', path= data_dir, return_res=True )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f0006075", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "scrolled": true, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_four_time:\n", + " plot_g2_general( g2_dict={1:g4}, taus_dict={1:taus4},vlim=[0.95, 1.05], qval_dict=qval_dict, fit_res= None, \n", + " geometry=scat_geometry_,filename=uid_+'_g4',path= data_dir, ylabel='g4')" + ] + }, + { + "cell_type": "markdown", + "id": "19a3c18e", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# Speckle Visiblity" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "079c20a4", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_xsvs: \n", + " max_cts = get_max_countc(FD, roi_mask ) \n", + " #max_cts = 15 #for eiger 500 K\n", + " qind, pixelist = roi.extract_label_indices( roi_mask )\n", + " noqs = len( np.unique(qind) )\n", + " nopr = np.bincount(qind, minlength=(noqs+1))[1:]\n", + " #time_steps = np.array( utils.geometric_series(2, len(imgs) ) )\n", + " time_steps = [0,1] #only run the first two levels\n", + " num_times = len(time_steps) \n", + " times_xsvs = exposuretime + (2**( np.arange( len(time_steps) ) ) -1 ) * timeperframe \n", + " print( 'The max counts are: %s'%max_cts )\n" + ] + }, + { + "cell_type": "markdown", + "id": "33ee44d5", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "### Do historam " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "048bf69f", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_xsvs:\n", + " if roi_avg is None:\n", + " times_roi, mean_int_sets = cal_each_ring_mean_intensityc(FD, roi_mask, timeperframe = None, ) \n", + " roi_avg = np.average( mean_int_sets, axis=0)\n", + " \n", + " t0=time.time()\n", + " spec_bins, spec_his, spec_std, spec_sum = xsvsp( FD, np.int_(roi_mask), norm=None,\n", + " max_cts=int(max_cts+2), bad_images=bad_frame_list, only_two_levels=True ) \n", + " spec_kmean = np.array( [roi_avg * 2**j for j in range( spec_his.shape[0] )] )\n", + " run_time(t0)\n", + " spec_pds = save_bin_his_std( spec_bins, spec_his, spec_std, filename=uid_+'_spec_res.csv', path=data_dir ) " + ] + }, + { + "cell_type": "markdown", + "id": "77febffc", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "### Do historam fit by negtive binominal function with maximum likehood method" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "38c4cc09", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_xsvs: \n", + " ML_val, KL_val,K_ = get_xsvs_fit( spec_his, spec_sum, spec_kmean, \n", + " spec_std, max_bins=2, fit_range=[1,60], varyK= False )\n", + " #print( 'The observed average photon counts are: %s'%np.round(K_mean,4))\n", + " #print( 'The fitted average photon counts are: %s'%np.round(K_,4)) \n", + " print( 'The difference sum of average photon counts between fit and data are: %s'%np.round( \n", + " abs(np.sum( spec_kmean[0,:] - K_ )),4))\n", + " print( '#'*30)\n", + " qth= 0 \n", + " print( 'The fitted M for Qth= %s are: %s'%(qth, ML_val[qth]) )\n", + " print( K_[qth])\n", + " print( '#'*30)" + ] + }, + { + "cell_type": "markdown", + "id": "984ef974", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## Plot fit results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ffac43ca", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "aee62337", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_xsvs: \n", + " qr = [qval_dict[k][0] for k in list(qval_dict.keys()) ]\n", + " plot_xsvs_fit( spec_his, ML_val, KL_val, K_mean = spec_kmean, spec_std=spec_std,\n", + " xlim = [0,10], vlim =[.9, 1.1],\n", + " uid=uid_, qth= qth_interest, logy= True, times= times_xsvs, q_ring_center=qr, path=data_dir)\n", + " \n", + " plot_xsvs_fit( spec_his, ML_val, KL_val, K_mean = spec_kmean, spec_std = spec_std,\n", + " xlim = [0,15], vlim =[.9, 1.1],\n", + " uid=uid_, qth= None, logy= True, times= times_xsvs, q_ring_center=qr, path=data_dir )" + ] + }, + { + "cell_type": "markdown", + "id": "a58d26ab", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "### Get contrast" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e5cbc516", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_xsvs:\n", + " contrast_factorL = get_contrast( ML_val)\n", + " spec_km_pds = save_KM( spec_kmean, KL_val, ML_val, qs=qr, level_time=times_xsvs, uid=uid_, path = data_dir )\n", + " #spec_km_pds" + ] + }, + { + "cell_type": "markdown", + "id": "99bca18f", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "### Plot contrast with g2 results" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5582f99f", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if run_xsvs: \n", + " plot_g2_contrast( contrast_factorL, g2b, times_xsvs, tausb, qr, \n", + " vlim=[0.8,1.2], qth = qth_interest, uid=uid_,path = data_dir, legend_size=14)\n", + "\n", + " plot_g2_contrast( contrast_factorL, g2b, times_xsvs, tausb, qr, \n", + " vlim=[0.8,1.2], qth = None, uid=uid_,path = data_dir, legend_size=4)" + ] + }, + { + "cell_type": "markdown", + "id": "c0f2e36e", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# Export Results to a HDF5 File" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "dcd6242c", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "md['mask_file']= mask_path + mask_name\n", + "md['roi_mask_file']= []\n", + "md['mask'] = mask\n", + "#md['NOTEBOOK_FULL_PATH'] = data_dir + get_current_pipeline_fullpath(NFP).split('/')[-1]\n", + "md['good_start'] = good_start\n", + "md['bad_frame_list'] = bad_frame_list\n", + "md['avg_img'] = avg_img\n", + "md['roi_mask'] = roi_mask\n", + "md['setup_pargs'] = setup_pargs\n", + "if scat_geometry == 'gi_saxs': \n", + " md['Qr'] = Qr\n", + " md['Qz'] = Qz\n", + " md['qval_dict'] = qval_dict\n", + " md['beam_center_x'] = inc_x0\n", + " md['beam_center_y']= inc_y0\n", + " md['beam_refl_center_x'] = refl_x0\n", + " md['beam_refl_center_y'] = refl_y0\n", + "\n", + "\n", + "elif scat_geometry == 'gi_waxs':\n", + " md['beam_center_x'] = center[1]\n", + " md['beam_center_y']= center[0]\n", + "else:\n", + " md['qr']= qr\n", + " #md['qr_edge'] = qr_edge\n", + " md['qval_dict'] = qval_dict\n", + " md['beam_center_x'] = center[1]\n", + " md['beam_center_y']= center[0] \n", + "\n", + "md['beg'] = FD.beg\n", + "md['end'] = FD.end\n", + "md['qth_interest'] = qth_interest\n", + "md['metadata_file'] = data_dir + 'uid=%s_md.pkl'%uid\n", + "psave_obj( md, data_dir + 'uid=%s_md.pkl'%uid ) #save the setup parameters\n", + "save_dict_csv( md, data_dir + 'uid=%s_md.csv'%uid, 'w')\n", + "\n", + "\n", + "###############Only work for Randy\n", + "try:\n", + " md['beg_OneTime'] = good_start_g2\n", + " md['end_OneTime'] = good_end_g2\n", + " print(md['beg_OneTime'])\n", + " print(md['end_OneTime'])\n", + "except:\n", + " pass\n", + "################################\n", + "\n", + "\n", + "Exdt = {} \n", + "if scat_geometry == 'gi_saxs': \n", + " for k,v in zip( ['md', 'roi_mask','qval_dict','avg_img','mask','pixel_mask', 'imgsum', 'bad_frame_list', 'qr_1d_pds'], \n", + " [md, roi_mask, qval_dict, avg_img,mask,pixel_mask, imgsum, bad_frame_list, qr_1d_pds] ):\n", + " Exdt[ k ] = v\n", + "elif scat_geometry == 'saxs': \n", + " for k,v in zip( ['md', 'q_saxs', 'iq_saxs','iqst','qt','roi_mask','qval_dict','avg_img','mask','pixel_mask', 'imgsum', 'bad_frame_list'], \n", + " [md, q_saxs, iq_saxs, iqst, qt,roi_mask, qval_dict, avg_img,mask,pixel_mask, imgsum, bad_frame_list] ):\n", + " Exdt[ k ] = v\n", + "elif scat_geometry == 'gi_waxs': \n", + " for k,v in zip( ['md', 'roi_mask','qval_dict','avg_img','mask','pixel_mask', 'imgsum', 'bad_frame_list'], \n", + " [md, roi_mask, qval_dict, avg_img,mask,pixel_mask, imgsum, bad_frame_list] ):\n", + " Exdt[ k ] = v\n", + " \n", + "if run_waterfall:Exdt['wat'] = wat\n", + "if run_t_ROI_Inten:Exdt['times_roi'] = times_roi;Exdt['mean_int_sets']=mean_int_sets\n", + "if run_one_time:\n", + " if run_invariant_analysis:\n", + " for k,v in zip( ['taus','g2','g2_fit_paras', 'time_stamp','invariant'], [taus,g2,g2_fit_paras,time_stamp,invariant] ):Exdt[ k ] = v\n", + " else:\n", + " for k,v in zip( ['taus','g2','g2_fit_paras' ], [taus,g2,g2_fit_paras ] ):Exdt[ k ] = v\n", + " \n", + "if run_two_time:\n", + " for k,v in zip( ['tausb','g2b','g2b_fit_paras', 'g12b'], [tausb,g2b,g2b_fit_paras,g12b] ):Exdt[ k ] = v\n", + " #for k,v in zip( ['tausb','g2b','g2b_fit_paras', ], [tausb,g2b,g2b_fit_paras] ):Exdt[ k ] = v \n", + "if run_dose:\n", + " for k,v in zip( [ 'taus_uids', 'g2_uids' ], [taus_uids, g2_uids] ):Exdt[ k ] = v\n", + "if run_four_time:\n", + " for k,v in zip( ['taus4','g4'], [taus4,g4] ):Exdt[ k ] = v\n", + "if run_xsvs:\n", + " for k,v in zip( ['spec_kmean','spec_pds','times_xsvs','spec_km_pds','contrast_factorL'], \n", + " [ spec_kmean,spec_pds,times_xsvs,spec_km_pds,contrast_factorL] ):Exdt[ k ] = v " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "64abe3e2", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "export_xpcs_results_to_h5( 'uid=%s_%s_Res.h5'%(md['uid'],q_mask_name), data_dir, export_dict = Exdt )\n", + "#extract_dict = extract_xpcs_results_from_h5( filename = 'uid=%s_Res.h5'%md['uid'], import_dir = data_dir )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "984d51ec", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "from pyCHX.chx_generic_functions import append_txtfile\n", + "append_txtfile( filename = outp + username + '.lst', \n", + " data = np.array( [ outp + 'Results/' + md['uid'] + '/uid=%s__Res.h5'%md['uid']]))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "52f43be8", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#g2npy_filename = data_dir + '/' + 'uid=%s_g12b.npy'%uid\n", + "#print(g2npy_filename)\n", + "#if os.path.exists( g2npy_filename):\n", + "# print('Will delete this file=%s.'%g2npy_filename)\n", + "# os.remove( g2npy_filename )\n" + ] + }, + { + "cell_type": "markdown", + "id": "08d47d01", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# Create a PDF Report" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b23bdc5f", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "pdf_out_dir = os.path.join(_base_path_, CYCLE, username, 'Results/')\n", + "\n", + "pdf_filename = \"XPCS_Analysis_Report2_for_uid=%s%s%s.pdf\"%(uid,pdf_version,q_mask_name)\n", + "if run_xsvs:\n", + " pdf_filename = \"XPCS_XSVS_Analysis_Report_for_uid=%s%s%s.pdf\"%(uid,pdf_version,q_mask_name)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f7003c3a", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "#%run /home/yuzhang/pyCHX_link/pyCHX/Create_Report.py" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "16b715a2", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "make_pdf_report( data_dir, uid, pdf_out_dir, pdf_filename, username, \n", + " run_fit_form,run_one_time, run_two_time, run_four_time, run_xsvs, run_dose,\n", + " report_type= scat_geometry, report_invariant= run_invariant_analysis,\n", + " md = md )" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "89569620", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "da88ffd9", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## Attach the PDF report to Olog " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "793df528", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "pdf_out_dir + pdf_filename" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "79d24e9b", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if att_pdf_report:\n", + " lops=0\n", + " while lops<5:\n", + " try:\n", + " update_olog_uid_with_file( uid[:6], text='Add XPCS Analysis PDF Report', \n", + " filename=pdf_out_dir + pdf_filename, append_name='_R1' )\n", + " lops=5\n", + " except:\n", + " print(\"Failed to attach PDF report to Olog...try again in 10s\")\n", + " time.sleep(10)\n", + " lops+=1\n", + " if lops == 5:\n", + " print(\"Failed final attempt to attach PDF to Olog!\")\n", + " " + ] + }, + { + "cell_type": "markdown", + "id": "e1422486", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "## Save the OVA image" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f11ec741", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "586a0a83", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + "if save_oavs:\n", + " try:\n", + " #os.environ['HTTPS_PROXY'] = 'https://proxy:8888'\n", + " #os.environ['no_proxy'] = 'cs.nsls2.local,localhost,127.0.0.1'\n", + " update_olog_uid_with_file( uid[:6], text='Add OVA images', \n", + " filename= data_dir + 'uid=%s_OVA_images.png'%uid, append_name='_img' )\n", + " except:\n", + " pass" + ] + }, + { + "cell_type": "markdown", + "id": "2f03cb20", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "source": [ + "# The End!" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5573e9eb", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + " \n", + "\"\"\"\n", + " \n", + "users = {'fluerasu','lwiegart','xmchen','tsutter', 'clindenau'}\n", + "\n", + "respipelines_path = data_dir0[:-8]+'ResPipelines/'\n", + "\n", + "\n", + "for user in users:\n", + " !setfacl -R -m u:{user}:rwx {data_dir0}\n", + " !setfacl -R -m u:{user}:rwx {respipelines_path} \n", + " print('Setting rwx rights for user %s to:\\n %s \\n %s \\n'%(user,data_dir0,respipelines_path)) \n", + "\n", + "\"\"\" \n", + " \n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "42c8b685", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [ + " " + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "6999728c", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e7ea8679", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "20ede443", + "metadata": { + "papermill": { + "duration": null, + "end_time": null, + "exception": null, + "start_time": null, + "status": "pending" + }, + "tags": [] + }, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4c3dddb5-19c1-4327-8e04-b1d6ebf63848", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a2c96e3b-72b1-48b1-8248-0174514ea951", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f8cd530a-e7a7-4479-81ab-981eeb34e035", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b1dd8a49-1c5a-4294-b0de-8291f6c6695e", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ad476827-9e2f-46d9-87bc-b5bb2e74ea21", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "CHX 2026-3-1", + "language": "python", + "name": "chx-2026-3-1" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.14" + }, + "papermill": { + "duration": 11.3765, + "end_time": "2025-02-21T22:32:06.264090", + "environment_variables": {}, + "exception": true, + "input_path": "/nsls2/data/chx/proposals/2025-1/pass-317365/AutoRuns/XPCS_WAXS_2025_v1.ipynb", + "output_path": "/nsls2/data/chx/proposals/2025-1/pass-317365/ResPipelines/XPCS_WAXS_2025_v1_f6954047-a994-4a6c-b6e3-417d9bb56ab5.ipynb", + "parameters": { + "cycle": "2025-1", + "process_id": "f6954047-a994-4a6c-b6e3-417d9bb56ab5_0", + "uid": "f6954047-a994-4a6c-b6e3-417d9bb56ab5", + "user_group": [], + "username": "pass-317635" + }, + "start_time": "2025-02-21T22:31:54.887590", + "version": "0.15.0" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/pyCHX/_xpcs_pipeline_geometry.py b/pyCHX/_xpcs_pipeline_geometry.py new file mode 100644 index 0000000..9ef5283 --- /dev/null +++ b/pyCHX/_xpcs_pipeline_geometry.py @@ -0,0 +1,435 @@ +"""Private geometry helpers for the unified XPCS notebook. + +Coordinates in this module are in the oriented analysis image: x is a column, +y is a row, distances are millimetres, and q is in inverse Angstroms. +""" + +import pickle +from pathlib import Path + +import numpy as np +from scipy.ndimage import gaussian_filter + +MODES = ("saxs", "gi_saxs", "waxs", "gi_waxs") + + +def resolve_geometry(metadata, notebook_value): + """Start metadata wins; otherwise retain the editable notebook value.""" + mode = metadata.get("scat_geometry", notebook_value) + if mode not in MODES: + raise ValueError(f"Unknown scat_geometry {mode!r}; choose one of {', '.join(MODES)}") + return mode + + +def _positive_number(value, name): + try: + value = float(value) + except (TypeError, ValueError) as exc: + raise ValueError(f"{name} must be a finite positive number") from exc + if not np.isfinite(value) or value <= 0: + raise ValueError(f"{name} must be a finite positive number") + return value + + +def _setting(metadata, explicit, keys, name): + for key in keys: + if key in metadata and metadata[key] is not None: + return metadata[key] + if explicit is not None: + return explicit + raise ValueError(f"Missing {name} in run metadata; set {name} in the notebook") + + +def surface_q_maps( + shape, center, dpix, distance, wavelength, metadata, incident_angle_deg=None, inplane_angle_deg=0 +): + """Calculate calibrated q_parallel and q_z for one oriented detector image.""" + angle = _positive_number( + _setting( + metadata, incident_angle_deg, ("inc_ang", "incident_angle", "incident_angle_deg"), "incident_angle_deg" + ), + "incident_angle_deg", + ) + azimuth = _setting( + metadata, inplane_angle_deg, ("inc_phi", "inplane_angle", "inplane_angle_deg"), "inplane_angle_deg" + ) + azimuth = float(azimuth) + if not np.isfinite(azimuth): + raise ValueError("inplane_angle_deg must be finite") + pixel_mm = _positive_number(dpix, "pixel size") + distance_mm = _positive_number(distance, "sample-detector distance") + wavelength_a = _positive_number(wavelength, "wavelength") + x0, y0 = map(float, center) + if not np.isfinite([x0, y0]).all(): + raise ValueError("Incident beam center must be finite") + alpha_i = np.deg2rad(angle) + phi = np.deg2rad(azimuth) + reflected_y = y0 + np.tan(2 * alpha_i) * distance_mm / pixel_mm + reflected_x = x0 - np.tan(phi) * (reflected_y - y0) + rows, cols = np.indices(shape) + # This is the same grazing-incidence convention as convert_gisaxs_pixel_to_q. + alpha_f = np.arctan2((rows - y0) * pixel_mm, distance_mm) - alpha_i + theta_f = np.arctan2((cols - x0) * pixel_mm, distance_mm) / 2 + qx = np.cos(alpha_f) * np.cos(2 * theta_f) - np.cos(alpha_i) + qy_lab = np.cos(alpha_f) * np.sin(2 * theta_f) + qz_lab = np.sin(alpha_f) + np.sin(alpha_i) + qy = qz_lab * np.sin(phi) + qy_lab * np.cos(phi) + qz = qz_lab * np.cos(phi) - qy_lab * np.sin(phi) + factor = 2 * np.pi / wavelength_a + return { + "q_parallel": np.hypot(qx, qy) * factor, + "q_z": qz * factor, + "incident_angle_deg": angle, + "inplane_angle_deg": azimuth, + "incident_center": (x0, y0), + "reflected_center": (reflected_x, reflected_y), + } + + +def _edges(values, valid, requested, count, name): + if requested is not None: + edges = np.asarray(requested, dtype=float) + if edges.ndim != 1 or len(edges) < 2 or not np.isfinite(edges).all() or np.any(np.diff(edges) <= 0): + raise ValueError(f"{name} must be strictly increasing finite bin edges") + return edges + selected = np.asarray(values)[valid] + selected = selected[np.isfinite(selected) & (selected > 0)] + if selected.size < 4: + raise ValueError(f"Too few valid pixels to derive {name}; supply explicit bin edges") + low, high = np.quantile(selected, [0.02, 0.98]) + if high <= low: + raise ValueError(f"No usable {name} range; supply explicit bin edges") + return np.linspace(low, high, count + 1) + + +def _rectangular_rois(q_parallel, q_z, valid, parallel_edges, z_edges): + labels = np.zeros(q_parallel.shape, dtype=np.int32) + q_values = {} + for z_lo, z_hi in zip(z_edges[:-1], z_edges[1:]): + z_band = valid & (q_z >= z_lo) & (q_z < z_hi) + shared_z = float(np.mean(q_z[z_band])) if z_band.any() else (z_lo + z_hi) / 2 + for p_lo, p_hi in zip(parallel_edges[:-1], parallel_edges[1:]): + selected = valid & (q_parallel >= p_lo) & (q_parallel < p_hi) & (q_z >= z_lo) & (q_z < z_hi) + if selected.any(): + number = len(q_values) + 1 + labels[selected] = number + q_values[number - 1] = np.array([np.mean(q_parallel[selected]), shared_z]) + if not q_values: + raise ValueError("No populated surface q ROIs; adjust the q bin edges") + return labels, q_values + + +def build_surface_rois(q_parallel, q_z, mask, parallel_edges=None, z_edges=None, parallel_count=8, z_count=3): + valid = np.asarray(mask, dtype=bool) & np.isfinite(q_parallel) & np.isfinite(q_z) & (q_z > 0) + p_edges = _edges(q_parallel, valid, parallel_edges, parallel_count, "q_parallel edges") + z_edges = _edges(q_z, valid, z_edges, z_count, "q_z edges") + roi_mask, qval_dict = _rectangular_rois(q_parallel, q_z, valid, p_edges, z_edges) + + # The legacy GISAXS profile functions accept [start, end, width, number]. + def profile_args(edges): + count = len(edges) - 1 + return [float(edges[0]), float(edges[-1]), float(np.min(np.diff(edges)) * 0.8), count] + + return { + "roi_mask": roi_mask, + "qval_dict": qval_dict, + "parallel_edges": p_edges, + "z_edges": z_edges, + "Qr": profile_args(p_edges), + "Qz": profile_args(z_edges), + } + + +def surface_profile_args_from_roi(roi_mask, qval_dict, q_maps): + """Derive legacy GISAXS profile ranges from a validated saved surface ROI.""" + selected = np.asarray(roi_mask) > 0 + centers = np.stack([np.asarray(value)[:2] for value in qval_dict.values()]) + result = {} + for index, (name, map_key) in enumerate((("Qr", "q_parallel"), ("Qz", "q_z"))): + values = np.asarray(q_maps[map_key])[selected] + low, high = float(np.min(values)), float(np.max(values)) + count = max(1, len(np.unique(np.round(centers[:, index], 8)))) + if high <= low: + high = low + 1e-5 + edges = np.linspace(low, high, count + 1) + result[name] = [low, high, float((high - low) / count * 0.8), count] + result["parallel_edges" if index == 0 else "z_edges"] = edges + return result + + +def build_waxs_rois(image, mask): + """Preserve the WAXS notebook's smoothed-intensity percentile bands.""" + smoothed = gaussian_filter(np.where(mask, np.asarray(image, dtype=float), 0), 2) + valid = np.asarray(mask, dtype=bool) & np.isfinite(smoothed) + if not valid.any(): + raise ValueError("No valid WAXS pixels") + values = smoothed[np.isfinite(smoothed)] + cutoffs = [100, 99.95, 99.9, 99.8, 99.6, 99.3, 98.5, 97, 95] + labels = np.zeros(smoothed.shape, dtype=np.int32) + q_values = {} + for high, next_high in zip(cutoffs[:-1], cutoffs[1:]): + low = high - 0.3 * (high - next_high) + selected = valid & (smoothed <= np.percentile(values, high)) & (smoothed > np.percentile(values, low)) + if selected.any(): + number = len(q_values) + 1 + labels[selected] = number + q_values[number - 1] = np.array([float(number)]) + if not q_values: + raise ValueError("No populated WAXS intensity bands") + return labels, q_values + + +def _read_saved(path, array_key): + path = Path(path) + if path.suffix == ".npz": + with np.load(path, allow_pickle=False) as loaded: + return {key: loaded[key].copy() for key in loaded.files} + if path.suffix == ".npy": + return {array_key: np.load(path, allow_pickle=False)} + if path.suffix in (".pkl", ".pickle"): + with path.open("rb") as stream: + return pickle.load(stream) + raise ValueError(f"Unsupported saved input format: {path.suffix}") + + +def _orientation(saved, explicit): + orientation = saved.get("orientation", explicit) if isinstance(saved, dict) else explicit + if isinstance(orientation, np.ndarray): + orientation = orientation.item() + if orientation != "analysis": + raise ValueError("Saved input must declare orientation='analysis' for the oriented detector image") + + +def load_manual_mask(path, shape, orientation=None, geometry=None): + saved = _read_saved(path, "mask") + if isinstance(saved, dict): + _orientation(saved, orientation) + if geometry is not None and "geometry" in saved and str(np.asarray(saved["geometry"]).item()) != geometry: + raise ValueError("Saved mask geometry does not match selected scat_geometry") + data = saved.get("mask") + else: + _orientation(saved, orientation) + data = saved + data = np.asarray(data) + if data.shape != tuple(shape) or not np.isfinite(data).all() or not np.isin(data, [0, 1]).all(): + raise ValueError("Saved mask shape or values do not match the oriented detector image") + return data.astype(bool) + + +def combine_detector_masks(saved, shape, detector): + """Validate and combine the components of an analysis-oriented detector mask.""" + expected = detector.split("_")[0] + actual = saved.get("detector") if isinstance(saved, dict) else None + if not isinstance(actual, str) or actual.casefold() != expected.casefold(): + raise ValueError(f"Detector mask identity {actual!r} does not match {expected!r}") + components = saved.get("masks") + if not isinstance(components, dict) or not components: + raise ValueError("Detector mask must contain at least one mask component") + combined = np.ones(shape, dtype=bool) + for name, pixels in components.items(): + try: + part = np.asarray(pixels) + except ValueError as exc: + raise ValueError(f"Detector mask component {name!r} has an invalid shape") from exc + if part.shape != tuple(shape): + raise ValueError(f"Detector mask component {name!r} does not match the oriented detector shape") + if not np.isin(part, [0, 1]).all(): + raise ValueError(f"Detector mask component {name!r} must contain only 0/1 values") + combined &= part.astype(bool) + return combined + + +def _radial_q(shape, center, dpix, distance, wavelength): + rows, cols = np.indices(shape) + radius_mm = np.hypot(rows - center[1], cols - center[0]) * dpix + return 4 * np.pi / wavelength * np.sin(np.arctan2(radius_mm, distance) / 2) + + +def validate_roi( + roi_mask, + qval_dict, + shape, + geometry, + mask=None, + q_maps=None, + center=None, + dpix=None, + distance=None, + wavelength=None, +): + roi_mask = np.asarray(roi_mask) + if roi_mask.shape != tuple(shape) or not np.issubdtype(roi_mask.dtype, np.integer): + raise ValueError("ROI labels must be an integer image matching the oriented detector shape") + labels = np.unique(roi_mask) + positive = labels[labels > 0] + if np.any(labels < 0) or not np.array_equal(positive, np.arange(1, len(positive) + 1)): + raise ValueError("ROI labels must be contiguous positive integers starting at 1") + if not len(positive) or set(qval_dict) != set(range(len(positive))): + raise ValueError("ROI q-value keys must match every populated ROI label") + if mask is not None and np.any((roi_mask > 0) & ~np.asarray(mask, dtype=bool)): + raise ValueError("ROI contains pixels excluded by the analysis mask") + if geometry == "waxs": + expected = np.arange(1, len(positive) + 1) + actual = np.asarray([qval_dict[i][0] for i in range(len(positive))], dtype=float) + if not np.array_equal(actual, expected): + raise ValueError("WAXS q values must be ROI indices 1, 2, ...") + return roi_mask, qval_dict + if geometry == "saxs": + if any(value is None for value in (center, dpix, distance, wavelength)): + raise ValueError("SAXS calibration is required to validate ROI q values") + maps = (_radial_q(shape, center, dpix, distance, wavelength),) + else: + if q_maps is None: + raise ValueError("Calibrated surface q maps are required to validate ROI q values") + maps = (q_maps["q_parallel"], q_maps["q_z"]) + for index, label in enumerate(positive): + values = np.asarray(qval_dict[index], dtype=float).reshape(-1) + required = len(maps) + if len(values) < required or not np.isfinite(values).all() or values[0] <= 0: + raise ValueError(f"Invalid q values for ROI {label}") + selected = roi_mask == label + for coordinate, q_map in enumerate(maps): + observed = np.asarray(q_map)[selected] + span = max(float(np.ptp(observed)), float(np.ptp(q_map)) * 0.005, 1e-5) + if not (observed.min() - span <= values[coordinate] <= observed.max() + span): + raise ValueError(f"ROI {label} q value disagrees with calibrated image orientation") + return roi_mask, qval_dict + + +def intersect_roi_with_mask(roi_mask, qval_dict, mask, geometry=None): + """Apply a later dynamic mask and keep labels aligned with q-value keys.""" + selected = np.where(mask, roi_mask, 0) + labels = np.unique(selected) + labels = labels[labels > 0] + if not len(labels): + raise ValueError("Dynamic mask removed every ROI") + renumbered = np.zeros(selected.shape, dtype=np.int32) + values = {} + for number, old_label in enumerate(labels, start=1): + renumbered[selected == old_label] = number + values[number - 1] = ( + np.array([float(number)]) if geometry == "waxs" else np.asarray(qval_dict[int(old_label) - 1]) + ) + return renumbered, values + + +def load_manual_roi(path, shape, geometry, orientation=None, **validation): + saved = _read_saved(path, "roi_mask") + _orientation(saved, orientation) + if isinstance(saved, tuple) and len(saved) == 2: + roi_mask, qval_dict = saved + elif isinstance(saved, dict): + roi_mask = saved.get("roi_mask") + if "geometry" in saved and str(np.asarray(saved["geometry"]).item()) != geometry: + raise ValueError("Saved ROI geometry does not match selected scat_geometry") + if "q_values" in saved: + qval_dict = {i: np.atleast_1d(row) for i, row in enumerate(np.asarray(saved["q_values"]))} + else: + qval_dict = saved.get("qval_dict") + else: + raise ValueError("Saved ROI must contain a mask and q values") + if not isinstance(qval_dict, dict): + raise ValueError("Saved ROI has no q-value dictionary") + return validate_roi(roi_mask, qval_dict, shape, geometry, **validation) + + +def plot_surface_roi(image, roi_mask, q_maps, path, uid): + """Plot calibrated surface coordinates without changing public plot APIs.""" + import matplotlib.pyplot as plt + + fig, ax = plt.subplots(figsize=(8, 7)) + ax.imshow(image, origin="lower", norm="log" if np.any(np.asarray(image) > 0) else None) + ax.contour(roi_mask, levels=np.arange(0.5, int(np.max(roi_mask)) + 1), colors="white", linewidths=0.4) + for key, color in (("q_parallel", "cyan"), ("q_z", "orange")): + q_map = np.asarray(q_maps[key]) + levels = np.quantile(q_map[np.isfinite(q_map)], [0.2, 0.4, 0.6, 0.8]) + if np.unique(levels).size > 1: + ax.contour(q_map, levels=np.unique(levels), colors=color, linewidths=0.5, alpha=0.6) + ax.set( + xlabel="detector column", + ylabel="detector row", + title=f"{uid} surface q ROIs (cyan: q_parallel; orange: q_z), Å⁻¹", + ) + fig.savefig(Path(path) / f"{uid}_ROI_on_Image.png", dpi=140) + plt.close(fig) + + +def plot_roi_index_rates(rates, path, uid): + """Show WAXS relaxation rates by ROI index without implying a calibrated q.""" + import matplotlib.pyplot as plt + + values = np.asarray(rates, dtype=float) + fig, ax = plt.subplots(figsize=(7, 5)) + ax.plot(np.arange(1, len(values) + 1), values, "o-") + ax.set(xlabel="WAXS ROI index", ylabel="relaxation rate (s$^{-1}$)") + fig.tight_layout() + fig.savefig(Path(path) / f"{uid}_Q_Rate_fit.png", dpi=140) + plt.close(fig) + + +def plot_xpcs_correlation( + g2_dict, + taus_dict, + qval_dict, + *, + mode, + geometry, + filename, + path, + append_name="", + ylabel="g2", + g2_labels=None, + g2_err_dict=None, + **kwargs, +): + """Use ROI-index panels for WAXS and the existing plotter elsewhere.""" + if mode != "waxs": + from pyCHX.chx_generic_functions import plot_g2_general + + return plot_g2_general( + g2_dict=g2_dict, + taus_dict=taus_dict, + qval_dict=qval_dict, + geometry=geometry, + filename=filename, + path=path, + append_name=append_name, + ylabel=ylabel, + g2_labels=g2_labels, + g2_err_dict=g2_err_dict, + **kwargs, + ) + import matplotlib.pyplot as plt + + count = len(qval_dict) + columns = min(4, count) + rows = int(np.ceil(count / columns)) + fig, axes = plt.subplots(rows, columns, figsize=(3.4 * columns, 2.8 * rows), squeeze=False) + for index, ax in enumerate(axes.flat): + if index >= count: + ax.axis("off") + continue + for series, (key, values) in enumerate(g2_dict.items()): + tau = np.asarray(taus_dict[key]) + y = np.asarray(values)[:, index] + label = g2_labels[series] if g2_labels is not None else ("data" if series == 0 else "fit") + if g2_err_dict is not None and key in g2_err_dict: + ax.errorbar( + tau, + y, + yerr=np.asarray(g2_err_dict[key])[:, index], + marker="o", + markersize=2, + linewidth=0.8, + label=label, + ) + else: + ax.plot(tau, y, marker="o" if series == 0 else None, markersize=2, linewidth=0.9, label=label) + if np.any(tau > 0): + ax.set_xscale("log") + ax.set(title=f"ROI {index + 1} (intensity band)", xlabel="delay (s)", ylabel=ylabel) + if index == 0 and len(g2_dict) > 1: + ax.legend(fontsize=7) + fig.tight_layout() + fig.savefig(Path(path) / f"{filename}{append_name}.png", dpi=140) + plt.close(fig) diff --git a/pyCHX/tests/test_xpcs_pipeline_geometry.py b/pyCHX/tests/test_xpcs_pipeline_geometry.py new file mode 100644 index 0000000..aa1db39 --- /dev/null +++ b/pyCHX/tests/test_xpcs_pipeline_geometry.py @@ -0,0 +1,493 @@ +"""Synthetic checks for the four modes of the unified XPCS notebook.""" + +import json +from pathlib import Path + +import h5py +import numpy as np +import pytest +from skbeam.core.correlation import multi_tau_auto_corr + +from pyCHX._xpcs_pipeline_geometry import ( + build_surface_rois, + build_waxs_rois, + combine_detector_masks, + intersect_roi_with_mask, + load_manual_mask, + load_manual_roi, + plot_roi_index_rates, + plot_surface_roi, + plot_xpcs_correlation, + resolve_geometry, + surface_profile_args_from_roi, + surface_q_maps, + validate_roi, +) + +SHAPE = (64, 80) +CENTER = (40.0, 8.0) +PIXEL_MM = 0.075 +DISTANCE_MM = 1500.0 +WAVELENGTH_A = 1.0 + + +def _saxs_roi(mask): + rows, cols = np.indices(SHAPE) + radius = np.hypot(rows - CENTER[1], cols - CENTER[0]) + labels = np.zeros(SHAPE, dtype=np.int32) + labels[(radius >= 8) & (radius < 14) & mask] = 1 + labels[(radius >= 18) & (radius < 25) & mask] = 2 + q_map = 4 * np.pi / WAVELENGTH_A * np.sin(np.arctan2(radius * PIXEL_MM, DISTANCE_MM) / 2) + return labels, {index: np.array([np.mean(q_map[labels == index + 1])]) for index in range(2)} + + +@pytest.fixture +def synthetic_inputs(): + rng = np.random.default_rng(31415) + mask = np.ones(SHAPE, dtype=bool) + mask[:, :2] = False + mask[-2:, :] = False + image = rng.gamma(4, 4, SHAPE) + q_maps = surface_q_maps(SHAPE, CENTER, PIXEL_MM, DISTANCE_MM, WAVELENGTH_A, {"inc_ang": 0.4}) + return mask, image, q_maps + + +def _mode_roi(mode, mask, image, q_maps): + if mode == "saxs": + return _saxs_roi(mask) + if mode == "waxs": + return build_waxs_rois(image, mask) + result = build_surface_rois( + q_maps["q_parallel"], + q_maps["q_z"], + mask, + parallel_count=4 if mode == "gi_saxs" else 6, + z_count=2 if mode == "gi_saxs" else 3, + ) + return result["roi_mask"], result["qval_dict"] + + +def _validation(mode, mask, q_maps): + common = {"mask": mask} + if mode == "saxs": + common.update(center=CENTER, dpix=PIXEL_MM, distance=DISTANCE_MM, wavelength=WAVELENGTH_A) + elif mode in ("gi_saxs", "gi_waxs"): + common["q_maps"] = q_maps + return common + + +def test_metadata_geometry_precedence_and_missing_surface_angle(): + assert resolve_geometry({}, "waxs") == "waxs" + assert resolve_geometry({"scat_geometry": "gi_waxs"}, "saxs") == "gi_waxs" + with pytest.raises(ValueError, match="Unknown scat_geometry"): + resolve_geometry({"scat_geometry": "invalid"}, "saxs") + with pytest.raises(ValueError, match="set incident_angle_deg"): + surface_q_maps(SHAPE, CENTER, PIXEL_MM, DISTANCE_MM, WAVELENGTH_A, {}) + + +def test_surface_q_calibration_matches_existing_conversion(synthetic_inputs): + from pyCHX.XPCS_GiSAXS import convert_gisaxs_pixel_to_q + + _, _, maps = synthetic_inputs + reflected_x, reflected_y = maps["reflected_center"] + _, _, q_parallel, q_z = convert_gisaxs_pixel_to_q( + *CENTER, + reflected_x, + reflected_y, + pixelsize=(75, 75), + Lsd=DISTANCE_MM / 1000, + dimx=SHAPE[1], + dimy=SHAPE[0], + lamda=WAVELENGTH_A, + ) + np.testing.assert_allclose(maps["q_parallel"], q_parallel, atol=1e-12) + np.testing.assert_allclose(maps["q_z"], q_z, atol=1e-12) + + +@pytest.mark.parametrize("mode", ("saxs", "gi_saxs", "waxs", "gi_waxs")) +def test_synthetic_geometry_manual_fallback_correlation_and_hdf5(mode, synthetic_inputs, tmp_path): + from pyCHX.Create_Report import export_xpcs_results_to_h5 + + mask, image, q_maps = synthetic_inputs + roi_mask, q_values = _mode_roi(mode, mask, image, q_maps) + validation = _validation(mode, mask, q_maps) + validate_roi(roi_mask, q_values, SHAPE, mode, **validation) + assert len(q_values) == roi_mask.max() + assert not np.any((roi_mask > 0) & ~mask) + if mode == "waxs": + np.testing.assert_array_equal([value[0] for value in q_values.values()], np.arange(1, len(q_values) + 1)) + elif mode in ("gi_saxs", "gi_waxs"): + assert all(len(value) == 2 for value in q_values.values()) + + mask_file = tmp_path / "mask.npz" + roi_file = tmp_path / "roi.npz" + np.savez(mask_file, mask=mask.astype(np.uint8), orientation="analysis") + np.savez( + roi_file, + roi_mask=roi_mask, + q_values=np.stack(list(q_values.values())), + orientation="analysis", + geometry=mode, + ) + loaded_mask = load_manual_mask(mask_file, SHAPE) + loaded_roi, loaded_q = load_manual_roi(roi_file, SHAPE, mode, **validation) + np.testing.assert_array_equal(loaded_mask, mask) + np.testing.assert_array_equal(loaded_roi, roi_mask) + for index in q_values: + np.testing.assert_allclose(loaded_q[index], q_values[index]) + + rng = np.random.default_rng(22) + images = rng.poisson(image + 2, size=(16, *SHAPE)).astype(float) + g2, lag_steps = multi_tau_auto_corr(2, 8, loaded_roi, images) + assert g2.shape == (len(lag_steps), len(q_values)) + assert np.isfinite(g2).all() + + metadata = { + "uid": "synthetic", + "scat_geometry": mode, + "mask_source": str(mask_file), + "roi_source": str(roi_file), + } + export_xpcs_results_to_h5( + "result.h5", + str(tmp_path) + "/", + {"md": metadata, "roi_mask": loaded_roi, "qval_dict": loaded_q, "g2": g2, "taus": lag_steps.astype(float)}, + ) + with h5py.File(tmp_path / "result.h5") as result: + assert result["md"].attrs["scat_geometry"] == mode + assert result["md"].attrs["roi_source"] == str(roi_file) + np.testing.assert_array_equal(result["roi_mask"], loaded_roi) + np.testing.assert_allclose(result["g2"], g2) + assert len(result["qval_dict"].attrs) == len(q_values) + + +def test_saved_inputs_reject_orientation_shape_labels_and_bad_q(synthetic_inputs, tmp_path): + mask, image, q_maps = synthetic_inputs + roi_mask, q_values = _mode_roi("gi_waxs", mask, image, q_maps) + values = np.stack(list(q_values.values())) + mask_file = tmp_path / "mask.npy" + np.save(mask_file, mask) + with pytest.raises(ValueError, match="orientation"): + load_manual_mask(mask_file, SHAPE) + assert load_manual_mask(mask_file, SHAPE, orientation="analysis").shape == SHAPE + np.savez(tmp_path / "wrong_mode_mask.npz", mask=mask, orientation="analysis", geometry="saxs") + with pytest.raises(ValueError, match="geometry"): + load_manual_mask(tmp_path / "wrong_mode_mask.npz", SHAPE, geometry="gi_waxs") + np.savez(tmp_path / "bad_shape.npz", roi_mask=roi_mask.T, q_values=values, orientation="analysis") + with pytest.raises(ValueError, match="shape"): + load_manual_roi(tmp_path / "bad_shape.npz", SHAPE, "gi_waxs", **_validation("gi_waxs", mask, q_maps)) + broken = roi_mask.copy() + broken[broken == 2] = 3 + np.savez(tmp_path / "bad_labels.npz", roi_mask=broken, q_values=values, orientation="analysis") + with pytest.raises(ValueError, match="contiguous"): + load_manual_roi(tmp_path / "bad_labels.npz", SHAPE, "gi_waxs", **_validation("gi_waxs", mask, q_maps)) + values[0, 1] += 10 + np.savez(tmp_path / "bad_q.npz", roi_mask=roi_mask, q_values=values, orientation="analysis") + with pytest.raises(ValueError, match="orientation"): + load_manual_roi(tmp_path / "bad_q.npz", SHAPE, "gi_waxs", **_validation("gi_waxs", mask, q_maps)) + + +def test_detector_mask_components_reject_broadcasting_bad_values_and_wrong_detector(): + saved = { + "detector": "eiger500K", + "masks": { + "pixel_mask": [[1, 0, 1], [1, 1, 1]], + "chip_mask": [[1, 1, 1], [0, 1, 1]], + }, + } + np.testing.assert_array_equal( + combine_detector_masks(saved, (2, 3), "eiger500k_single_image"), + [[True, False, True], [False, True, True]], + ) + with pytest.raises(ValueError, match="identity"): + combine_detector_masks(saved, (2, 3), "eiger4m_single_image") + saved["masks"]["chip_mask"] = [[1, 1, 1]] + with pytest.raises(ValueError, match="component 'chip_mask'.*shape"): + combine_detector_masks(saved, (2, 3), "eiger500K_single_image") + saved["masks"]["chip_mask"] = [[1, 1, 1], [0, 2, 1]] + with pytest.raises(ValueError, match="component 'chip_mask'.*0/1"): + combine_detector_masks(saved, (2, 3), "eiger500K_single_image") + + +def test_dynamic_beam_mask_keeps_roi_labels_and_q_values_aligned(synthetic_inputs): + mask, image, q_maps = synthetic_inputs + roi_mask, values = _mode_roi("waxs", mask, image, q_maps) + later_mask = mask & (roi_mask != 2) + updated, updated_values = intersect_roi_with_mask(roi_mask, values, later_mask, geometry="waxs") + assert np.array_equal(np.unique(updated), np.arange(len(updated_values) + 1)) + assert len(updated_values) == len(values) - 1 + assert np.array_equal(updated_values[1], [2]) + validate_roi(updated, updated_values, SHAPE, "waxs", mask=later_mask) + + +def test_saxs_final_mask_reindexes_q_values_after_hot_pixels(): + import time + + notebook = json.loads((Path(__file__).resolve().parents[2] / "pipelines/XPCS_auto.ipynb").read_text()) + cell = [item for item in notebook["cells"] if item["cell_type"] == "code"][41] + state = { + "time": time, + "np": np, + "scat_geometry": "saxs", + "roi_mask2": np.array([[1, 1], [2, 2]], dtype=np.int32), + "qval_dict": {0: np.array([0.1]), 1: np.array([0.2])}, + "mask_copy": np.ones((2, 2), dtype=bool), + "avg_img": np.ones((2, 2)), + "det_mask": np.ones((2, 2), dtype=bool), + "center": (0, 0), + "mask_outliers": False, + "setup_pargs": {}, + "create_hot_pixel_mask": lambda *args, **kwargs: np.array([[0, 0], [1, 1]]), + "get_circular_average": lambda *args, **kwargs: (np.array([0.1, 0.2]),) * 3, + "plot_circular_average": lambda *args, **kwargs: None, + "intersect_roi_with_mask": intersect_roi_with_mask, + "_record_xpcs_cell_timing": lambda *args: None, + } + exec("".join(cell["source"]), state) + np.testing.assert_array_equal(state["roi_mask"], [[0, 0], [1, 1]]) + np.testing.assert_array_equal(state["qval_dict"][0], [0.2]) + assert len(state["qval_dict"]) == state["roi_mask"].max() + + +def test_surface_saved_roi_works_when_auto_bins_have_too_few_pixels(): + parallel = np.array([[1.0, 2.0], [3.0, 4.0]]) + q_z = np.array([[1.0, 1.0], [2.0, 2.0]]) + mask = np.array([[True, True], [False, True]]) + with pytest.raises(ValueError, match="Too few valid pixels"): + build_surface_rois(parallel, q_z, mask) + roi_mask = np.array([[1, 1], [0, 0]], dtype=np.int32) + q_values = {0: np.array([1.5, 1.0])} + maps = {"q_parallel": parallel, "q_z": q_z} + validate_roi(roi_mask, q_values, roi_mask.shape, "gi_saxs", mask=mask, q_maps=maps) + profile = surface_profile_args_from_roi(roi_mask, q_values, maps) + assert profile["Qr"][3] == 1 and profile["Qz"][3] == 1 + + root = Path(__file__).resolve().parents[2] + notebook = json.loads((root / "pipelines/XPCS_auto.ipynb").read_text()) + source = "".join(notebook["cells"][43]["source"]) + assert source.index("if manual_roi_file is not None:", source.index("elif scat_geometry in")) < source.index( + "build_surface_rois(" + ) + + +def test_surface_plot_uses_report_filename(synthetic_inputs, tmp_path): + mask, image, q_maps = synthetic_inputs + roi_mask, _ = _mode_roi("gi_saxs", mask, image, q_maps) + plot_surface_roi(image, roi_mask, q_maps, tmp_path, "uid=synthetic") + assert (tmp_path / "uid=synthetic_ROI_on_Image.png").stat().st_size > 0 + plot_roi_index_rates([0.2, 0.4], tmp_path, "uid=synthetic") + assert (tmp_path / "uid=synthetic_Q_Rate_fit.png").stat().st_size > 0 + plot_xpcs_correlation( + {1: np.ones((4, 2))}, + {1: np.array([0.1, 0.2, 0.4, 0.8])}, + {0: np.array([1]), 1: np.array([2])}, + mode="waxs", + geometry="gi_waxs", + filename="uid=synthetic_g2", + path=tmp_path, + ) + assert (tmp_path / "uid=synthetic_g2.png").stat().st_size > 0 + + +def test_beam_mask_configuration_is_geometry_specific(tmp_path): + import os + import time + import warnings + + root = Path(__file__).resolve().parents[2] + notebook = json.loads((root / "pipelines/XPCS_auto.ipynb").read_text()) + source = "".join(notebook["cells"][29]["source"]) + mask_dir = tmp_path / "cycle" / "user" / "masks" + mask_dir.mkdir(parents=True) + generic = mask_dir / "XPCS_beam_mask.json" + specific = mask_dir / "XPCS_beam_mask_gi_saxs.json" + generic.write_text('{"masks": {"generic": {}}}') + specific.write_text('{"masks": {"surface": {}}}') + + def run(mode, manual_mask_file=None): + state = dict( + default_dir=str(tmp_path) + "/", + cycle="cycle", + username="user", + scat_geometry=mode, + beam_mask_config_file=None, + auto_bst_mask=True, + manual_mask_file=manual_mask_file, + os=os, + json=json, + time=time, + warnings=warnings, + _record_xpcs_cell_timing=lambda *args: None, + ) + exec(source, state) + return state + + assert run("saxs")["beam_mask_source"] == str(generic) + assert run("gi_saxs")["beam_mask_source"] == str(specific) + with pytest.warns(RuntimeWarning, match="gi_waxs.*empty"): + assert run("gi_waxs")["beam_mask_source"] == "generated:gi_waxs:beam_mask" + with pytest.warns(RuntimeWarning, match="waxs.*empty"): + assert run("waxs")["beam_mask_source"] == "generated:waxs:beam_mask" + with warnings.catch_warnings(record=True) as caught: + assert run("waxs", manual_mask_file="manual.npz")["beam_mask_source"] == "generated:waxs:beam_mask" + assert not caught + + +@pytest.mark.parametrize("mode", ("saxs", "gi_saxs", "waxs", "gi_waxs")) +def test_report_renders_selected_mode_and_roi_image(mode, synthetic_inputs, tmp_path): + import matplotlib.pyplot as plt + + from pyCHX.Create_Report import make_pdf_report + + mask, image, q_maps = synthetic_inputs + roi_mask, _ = _mode_roi(mode, mask, image, q_maps) + plt.imsave(tmp_path / "uid=synthetic_img_avg.png", image) + plt.imsave(tmp_path / "uid=synthetic_ROI_on_Image.png", roi_mask) + plt.imsave(tmp_path / "uid=synthetic_fra_0_16_g2.png", image) + plt.imsave(tmp_path / "uid=synthetic_fra_0_16_Q_Rate_fit.png", image) + metadata = { + "uid": "synthetic", + "scat_geometry": mode, + "sample": "synthetic", + "start_time": "now", + "stop_time": "now", + "Measurement": "test", + "incident_wavelength": WAVELENGTH_A, + "number of images": 16, + "count_time": 0.1, + "frame_time": 0.1, + "detector_distance": DISTANCE_MM / 1000, + "feedback_x": "off", + "feedback_y": "off", + "shutter mode": "auto", + "beam_center_x": CENTER[0], + "beam_center_y": CENTER[1], + "beam_refl_center_x": CENTER[0], + "beam_refl_center_y": CENTER[1] + 20, + "mask_file": "synthetic", + "roi_mask_file": "synthetic", + "bad_frame_list": [], + "transmission": 1, + "beg": 0, + "end": 16, + } + report_type = "gi_waxs" if mode == "waxs" else mode + make_pdf_report( + str(tmp_path) + "/", + "synthetic", + str(tmp_path) + "/", + f"{mode}.pdf", + "test", + False, + True, + False, + False, + False, + False, + report_type=report_type, + md=metadata, + ) + pdf = (tmp_path / f"{mode}.pdf").read_bytes() + assert pdf.startswith(b"%PDF") and len(pdf) > 3_000 + + +def test_unified_notebook_preserves_parameters_and_shared_correlation_cells(): + root = Path(__file__).resolve().parents[2] + original = json.loads((root / "pipelines/old_pipelines/XPCS_SAXS_auto.ipynb").read_text()) + unified = json.loads((root / "pipelines/XPCS_auto.ipynb").read_text()) + assert "# Parameters" in "".join(unified["cells"][7]["source"]) + for index in (7, 12, 22, 52, 89, 103, 104, 112, 113, 148, 152): + assert unified["cells"][index]["cell_type"] == original["cells"][index]["cell_type"] + + def without_timing_record(cell): + return "".join( + line for line in cell["source"] if not line.lstrip().startswith("_record_xpcs_cell_timing(") + ) + + for index in (103, 104, 112, 113, 148): + assert without_timing_record(unified["cells"][index]) == without_timing_record(original["cells"][index]) + + +def test_all_input_cells_are_numbered_and_papermill_timing_survives_injection(): + import re + import time + + import nbformat + + pytest.importorskip("papermill") + from papermill.parameterize import parameterize_notebook + + root = Path(__file__).resolve().parents[2] + notebook = nbformat.read(root / "pipelines/XPCS_auto.ipynb", as_version=4) + cells = [cell for cell in notebook.cells if cell.cell_type == "code"] + assert len(cells) == 104 + for number, cell in enumerate(cells, start=1): + assert re.search( + rf'_record_xpcs_cell_timing\("{number:02d} - [^"]+", _xpcs_cell_start\)', + cell.source, + ) + assert "parameters" in cells[2].metadata.tags + assert "injected-parameters" in cells[3].metadata.tags + + injected = parameterize_notebook(notebook, {"uid": "synthetic"}) + injected_cells = [cell for cell in injected.cells if cell.cell_type == "code"] + assert 'uid = "synthetic"' in injected_cells[3].source + assert "_record_xpcs_cell_timing" not in injected_cells[3].source + + recorded = [] + state = { + "time": time, + "_xpcs_parameters_start": time.time(), + "_xpcs_parameters_recorded": False, + "_record_xpcs_cell_timing": lambda label, start: recorded.append(label), + } + exec(injected_cells[3].source, state) + prelude = injected_cells[4].source.split("# Data security modification:", 1)[0] + exec(prelude, state) + assert recorded == ["04 - Papermill parameters"] + + +def test_single_roi_two_time_path_without_one_time_result(): + import itertools + import time + from types import SimpleNamespace + + root = Path(__file__).resolve().parents[2] + notebook = json.loads((root / "pipelines/XPCS_auto.ipynb").read_text()) + calls = {} + + def save_correlation(data, **kwargs): + calls["csv"] = kwargs + return kwargs + + state = { + "np": np, + "time": time, + "itertools": itertools, + "plt": SimpleNamespace(cm=SimpleNamespace(jet=None)), + "run_two_time": True, + "g12b": np.ones((16, 16, 1)), + "lag_steps": np.array([0, 1, 2, 3]), + "FD": SimpleNamespace(beg=0, end=16), + "Nimg": 16, + "timeperframe": 0.1, + "qval_dict": {0: np.array([0.01, 0.02])}, + "scat_geometry": "gi_waxs", + "scat_geometry_": "gi_saxs", + "uid_": "uid=synthetic_fra_0_16", + "q_mask_name": "gi_waxs", + "data_dir": "/tmp/", + "fit_g2_func": "stretched", + "get_one_time_from_two_time": lambda _: np.ones((16, 1)), + "save_g2_general": save_correlation, + "get_g2_fit_general": lambda *args, **kwargs: (_ for _ in ()).throw(RuntimeError("fit failed")), + "show_C12": lambda *args, **kwargs: calls.update(q_ind=kwargs["q_ind"]), + "plot_xpcs_correlation": lambda *args, **kwargs: calls.update(plot_q=kwargs["qval_dict"]), + "_record_xpcs_cell_timing": lambda *args: None, + } + for index in (114, 115, 116, 117): + exec("".join(notebook["cells"][index]["source"]), state) + assert calls["q_ind"] == 1 + np.testing.assert_array_equal(calls["csv"]["qz"], [0.02]) + assert state["g2b_fit_paras"].shape == (1, 4) + assert list(calls["plot_q"]) == [0]