diff --git a/.gitignore b/.gitignore index 26e3a2d..843a187 100644 --- a/.gitignore +++ b/.gitignore @@ -176,3 +176,5 @@ test_output_1/ /.venv_jupyter/ examples/test_output/SimID_* +/examples/notebooks/*.py +/examples/solver_output/zarr/ diff --git a/.openapi-generator/FILES b/.openapi-generator/FILES index 19737aa..add12d9 100644 --- a/.openapi-generator/FILES +++ b/.openapi-generator/FILES @@ -1,102 +1,103 @@ pyvcell/__init__.py -pyvcell/api/__init__.py -pyvcell/api/vcell_client/__init__.py -pyvcell/api/vcell_client/api/__init__.py -pyvcell/api/vcell_client/api/admin_resource_api.py -pyvcell/api/vcell_client/api/bio_model_resource_api.py -pyvcell/api/vcell_client/api/field_data_resource_api.py -pyvcell/api/vcell_client/api/hello_world_api.py -pyvcell/api/vcell_client/api/publication_resource_api.py -pyvcell/api/vcell_client/api/simulation_resource_api.py -pyvcell/api/vcell_client/api/solver_resource_api.py -pyvcell/api/vcell_client/api/users_resource_api.py -pyvcell/api/vcell_client/api_client.py -pyvcell/api/vcell_client/api_response.py -pyvcell/api/vcell_client/configuration.py -pyvcell/api/vcell_client/docs/AccesTokenRepresentationRecord.md -pyvcell/api/vcell_client/docs/AdminResourceApi.md -pyvcell/api/vcell_client/docs/AnalyzedResultsFromFieldData.md -pyvcell/api/vcell_client/docs/BatchSystemType.md -pyvcell/api/vcell_client/docs/BioModel.md -pyvcell/api/vcell_client/docs/BioModelResourceApi.md -pyvcell/api/vcell_client/docs/BiomodelRef.md -pyvcell/api/vcell_client/docs/DataIdentifier.md -pyvcell/api/vcell_client/docs/DetailedState.md -pyvcell/api/vcell_client/docs/Domain.md -pyvcell/api/vcell_client/docs/Extent.md -pyvcell/api/vcell_client/docs/ExternalDataIdentifier.md -pyvcell/api/vcell_client/docs/FieldDataReference.md -pyvcell/api/vcell_client/docs/FieldDataResourceApi.md -pyvcell/api/vcell_client/docs/FieldDataSaveResults.md -pyvcell/api/vcell_client/docs/FieldDataShape.md -pyvcell/api/vcell_client/docs/HelloWorldApi.md 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+pyvcell/_internal/api/vcell_client/models/simulation_execution_status_record.py +pyvcell/_internal/api/vcell_client/models/simulation_job_status_record.py +pyvcell/_internal/api/vcell_client/models/simulation_message.py +pyvcell/_internal/api/vcell_client/models/simulation_queue_entry_status_record.py +pyvcell/_internal/api/vcell_client/models/simulation_queue_id.py +pyvcell/_internal/api/vcell_client/models/simulation_status_persistent_record.py +pyvcell/_internal/api/vcell_client/models/status.py +pyvcell/_internal/api/vcell_client/models/status_message.py +pyvcell/_internal/api/vcell_client/models/user.py +pyvcell/_internal/api/vcell_client/models/user_identity_json_safe.py +pyvcell/_internal/api/vcell_client/models/user_login_info_for_mapping.py +pyvcell/_internal/api/vcell_client/models/user_registration_info.py +pyvcell/_internal/api/vcell_client/models/variable_domain.py +pyvcell/_internal/api/vcell_client/models/variable_type.py +pyvcell/_internal/api/vcell_client/models/vc_simulation_identifier.py +pyvcell/_internal/api/vcell_client/rest.py +pyvcell/_internal/api/vcell_client/test/__init__.py +pyvcell/_internal/api/vcell_client_README.md diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index 517d23f..f5d6924 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -16,7 +16,7 @@ repos: hooks: - id: ruff args: [--exit-non-zero-on-fix] - exclude: 'pyvcell/api/.*\.py' + exclude: 'pyvcell/_internal/api/.*\.py' - id: ruff-format - repo: https://github.com/pre-commit/mirrors-prettier diff --git a/examples/empty_mesh_subdomain0.vtu b/examples/empty_mesh_subdomain0.vtu deleted file mode 100644 index ad49f3c..0000000 --- a/examples/empty_mesh_subdomain0.vtu +++ /dev/null @@ -1,35 +0,0 @@ - - - - - - - - - - - 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- - - yAAAAAsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsLCwsL - - - - - diff --git a/examples/fv_solver_workflow.ipynb b/examples/fv_solver_workflow.ipynb deleted file mode 100644 index 226f7ea..0000000 --- a/examples/fv_solver_workflow.ipynb +++ /dev/null @@ -1,85192 +0,0 @@ -{ - "cells": [ - { - "metadata": { - "collapsed": false - }, - "cell_type": "markdown", - "source": [ - "# Run a VCell PDE simulation from solver input files\n", - "1. Copy all files from solver_input directory to a temporary directory for solving\n", - "2. prepare empty solver output directory, copying in the functions file\n", - "2. Execute the Finite Volume PDE solver" - ], - "id": "29a6cffd5df3cb63" - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": "### In this example, we are using the Model instance as an example, as the get input files endpoint is not yet implemented.", - "id": "90320a7fbc22bb09" - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:45:19.505612Z", - "start_time": "2025-02-26T17:45:18.607619Z" - } - }, - "cell_type": "code", - "source": [ - "from pathlib import Path\n", - "\n", - "import tempfile\n", - "import shutil\n", - "import os\n", - "\n", - "from pyvcell.data_model.simulation import SbmlSpatialSimulation\n", - "from pyvcell.data_model.sbml_spatial_model import SbmlSpatialModel\n", - "from pyvcell.simdata.postprocessing import PostProcessing\n", - "from pyvcell.simdata.vtk.fv_mesh_mapping import from_mesh_data\n", - "\n", - "\n", - "def get_temp_solver_dir(solver_input_dir: Path, temp_dir_prefix: str = None) -> Path:\n", - " # prepare input dir\n", - " temp_solver_dir = Path(tempfile.mkdtemp(prefix=temp_dir_prefix or 'pyvcell_test_data_'))\n", - " for file in solver_input_dir.iterdir():\n", - " shutil.copy(file, temp_solver_dir)\n", - "\n", - " return temp_solver_dir\n", - "\n", - "\n", - "def prepare_output_dir(solver_output_dir: Path, functions_file: Path) -> None:\n", - " # prepare output dir: clear contents of solver_output_dir\n", - " for file in solver_output_dir.iterdir():\n", - " if file.is_file() and not file.name.startswith('.'):\n", - " file.unlink()\n", - "\n", - " # copy functions file to solver_output_dir\n", - " shutil.copy(functions_file, solver_output_dir)\n", - "\n", - "\n", - "# define input dir, output_dir and spatial model\n", - "solver_input_dir = Path(os.getcwd()) / \"solver_input\"\n", - "temp_solver_dir = get_temp_solver_dir(solver_input_dir)\n", - "functions_file = temp_solver_dir / \"SimID_946368938_0_.functions\"\n", - "\n", - "solver_output_dir = Path(os.getcwd()) / \"test_output\"\n", - "\n", - "model_fp = os.path.join(solver_input_dir, \"TinySpatialProject_Application0.xml\")\n", - "\n", - "# define editable spatial model and simulation instances\n", - "model = SbmlSpatialModel(filepath=model_fp)\n", - "simulation = SbmlSpatialSimulation(sbml_model=model, out_dir=solver_output_dir)\n", - "\n", - "# TODO: replace below with simulation.get_input_files()\n", - "fv_input_file = temp_solver_dir / \"SimID_946368938_0_.fvinput\"\n", - "vcg_file = temp_solver_dir / \"SimID_946368938_0_.vcg\"" - ], - "id": "67917a6259f62909", - "outputs": [], - "execution_count": 1 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:45:20.572514Z", - "start_time": "2025-02-26T17:45:19.970063Z" - } - }, - "cell_type": "code", - "source": [ - "# job_id = 0\n", - "# sim_id = 946368938\n", - "\n", - "result = simulation.run()\n", - "job_id = result.job_id\n", - "sim_id = result.sim_id" - ], - "id": "ffc949c0c6ff6844", - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "initializing mesh\n", - "numVolume=200\n", - "\n", - "mesh initialized\n", - "preprocessing finished\n", - "pdeCount=2, odeCount=0\n", - "error opening log file \n", - "simulation [SimID_190714333_0_] started\n", - "temporary directory used is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/\n", - "sim file name is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/SimID_190714333_0_0000.sim\n", - "**This is a little endian machine.**\n", - "[[[data:0]]]\n", - "numVolRegions=1\n", - "Region 0: size=200, offset=0\n", - "# of active points = 200\n", - "Constant diffusion/advection in region subdomain00\n", - "numUnknowns = 400\n", - "\n", - "****** using Sundials CVode with PREC_LEFT, relTol=1e-07, absTol=1e-09, maxStep=0.1\n", - "\n", - "----------------------------------\n", - "sundials pde solver is starting from time 0\n", - "----------------------------------\n", - "temporary directory used is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/\n", - "sim file name is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/SimID_190714333_0_0001.sim\n", - "[[[data:0.1]]]temporary directory used is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/\n", - "sim file name is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/SimID_190714333_0_0002.sim\n", - "[[[data:0.2]]]temporary directory used is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/\n", - "sim file name is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/SimID_190714333_0_0003.sim\n", - "[[[data:0.3]]]temporary directory used is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/\n", - "sim file name is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/SimID_190714333_0_0004.sim\n", - "[[[data:0.4]]]temporary directory used is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/\n", - "sim file name is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/SimID_190714333_0_0005.sim\n", - "[[[data:0.5]]]temporary directory used is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/\n", - "sim file name is 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/var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/SimID_190714333_0_0046.sim\n", - "[[[data:4.6]]]temporary directory used is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/\n", - "sim file name is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/SimID_190714333_0_0047.sim\n", - "[[[data:4.7]]]temporary directory used is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/\n", - "sim file name is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/SimID_190714333_0_0048.sim\n", - "[[[data:4.8]]]temporary directory used is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/\n", - "sim file name is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/SimID_190714333_0_0049.sim\n", - "[[[data:4.9]]]\n", - "Final Statistics.. \n", - "\n", - "lenrw = 4089 leniw = 50\n", - "lenrwLS = 4046 leniwLS = 10\n", - "nst = 217\n", - "nfe = 277 nfeLS = 189\n", - "nni = 273 nli = 189\n", - "nsetups = 106 netf = 6\n", - "npe = 5 nps = 378\n", - "ncfn = 0 ncfl = 0\n", - "last step = 0.044432\n", - "\n", - "temporary directory used is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/\n", - "sim file name is /var/folders/yy/8crj8x7x5_3b86f0js6_0bn00000gr/T/SimID_190714333_0_0050.sim\n", - "[[[data:5]]][[[progress:100%]]]" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Simulation Complete in Main() ... \n" - ] - } - ], - "execution_count": 2 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:45:21.608766Z", - "start_time": "2025-02-26T17:45:21.488432Z" - } - }, - "cell_type": "code", - "source": [ - "from pyvcell.data_model.vtk_data import VtkData\n", - "\n", - "vtk_data: VtkData = result.vtk_data\n", - "dir(vtk_data)" - ], - "id": "9c4eafeef220244c", - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "subdomain0::s0 VariableType.VOLUME\n", - "subdomain0::s1 VariableType.VOLUME\n", - "vcRegionVolume VariableType.VOLUME_REGION\n", - "vcRegionArea VariableType.MEMBRANE_REGION\n", - "vcRegionVolume_subdomain0 VariableType.MEMBRANE_REGION\n" - ] - }, - { - "data": { - "text/plain": [ - "['__annotations__',\n", - " '__class__',\n", - " '__delattr__',\n", - " '__dict__',\n", - " '__dir__',\n", - " '__doc__',\n", - " '__eq__',\n", - " '__format__',\n", - " '__ge__',\n", - " '__getattribute__',\n", - " '__gt__',\n", - " '__hash__',\n", - " '__init__',\n", - " '__init_subclass__',\n", - " '__le__',\n", - " '__lt__',\n", - " '__module__',\n", - " '__ne__',\n", - " '__new__',\n", - " '__reduce__',\n", - " '__reduce_ex__',\n", - " '__repr__',\n", - " '__setattr__',\n", - " '__sizeof__',\n", - " '__str__',\n", - " '__subclasshook__',\n", - " '__weakref__',\n", - " 'get_vis_mesh',\n", - " 'get_vtk_grid',\n", - " 'get_vtu_file',\n", - " 'mesh',\n", - " 'out_dir',\n", - " 'plot',\n", - " 'times',\n", - " 'vtu_files',\n", - " 'write_mesh_animation']" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 3 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:45:22.553721Z", - "start_time": "2025-02-26T17:45:22.546396Z" - } - }, - "cell_type": "code", - "source": [ - "from pyvcell.data_model.plotter import Plotter\n", - "\n", - "plotter: Plotter = result.plotter\n", - "dir(plotter)" - ], - "id": "270fb145d066515d", - "outputs": [ - { - "data": { - "text/plain": [ - "['__annotations__',\n", - " '__class__',\n", - " '__delattr__',\n", - " '__dict__',\n", - " '__dir__',\n", - " '__doc__',\n", - " '__eq__',\n", - " '__format__',\n", - " '__ge__',\n", - " '__getattribute__',\n", - " '__gt__',\n", - " '__hash__',\n", - " '__init__',\n", - " '__init_subclass__',\n", - " '__le__',\n", - " '__lt__',\n", - " '__module__',\n", - " '__ne__',\n", - " '__new__',\n", - " '__reduce__',\n", - " '__reduce_ex__',\n", - " '__repr__',\n", - " '__setattr__',\n", - " '__sizeof__',\n", - " '__str__',\n", - " '__subclasshook__',\n", - " '__weakref__',\n", - " 'animate_channel_3d',\n", - " 'animate_image',\n", - " 'channels',\n", - " 'concentrations',\n", - " 'get_3d_slice_animation',\n", - " 'get_image_animation',\n", - " 'mesh',\n", - " 'num_timepoints',\n", - " 'plot_averages',\n", - " 'plot_concentrations',\n", - " 'plot_image',\n", - " 'plot_slice_2d',\n", - " 'plot_slice_3d',\n", - " 'post_processing',\n", - " 'times',\n", - " 'zarr_dataset']" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 4 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:45:23.645710Z", - "start_time": "2025-02-26T17:45:23.643460Z" - } - }, - "cell_type": "code", - "source": [ - "def get_plottable_indices():\n", - " import numpy as np\n", - "\n", - " nchannels = result.zarr_dataset.shape[1]\n", - " valid = []\n", - " for n, i in enumerate(list(range(nchannels))):\n", - " x = result.zarr_dataset[0, n, :, :, :]\n", - " any = np.any(x)\n", - " valid.append(i) if any else None\n", - "\n", - " return list(set(valid))" - ], - "id": "b0e6cfacc683112d", - "outputs": [], - "execution_count": 5 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:45:25.006899Z", - "start_time": "2025-02-26T17:45:25.002262Z" - } - }, - "cell_type": "code", - "source": [ - "indices = get_plottable_indices()\n", - "\n", - "indices, result.zarr_dataset.shape" - ], - "id": "7b7198e6f5ac7366", - "outputs": [ - { - "data": { - "text/plain": [ - "([2, 5, 6, 7, 8, 9], (51, 10, 1, 1, 200))" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 6 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:46:52.922225Z", - "start_time": "2025-02-26T17:46:52.918918Z" - } - }, - "cell_type": "code", - "source": [ - "ids = result.get_channel_ids()\n", - "s1 = result.get_channel('s1')\n", - "time_index = 3\n", - "data = result.get_slice(time_index, s1.label)" - ], - "id": "23d49b1d1860fb61", - "outputs": [], - "execution_count": 9 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:47:19.433218Z", - "start_time": "2025-02-26T17:47:19.430809Z" - } - }, - "cell_type": "code", - "source": "data.ndim", - "id": "9fead4a1cdb805f4", - "outputs": [ - { - "data": { - "text/plain": [ - "3" - ] - }, - "execution_count": 12, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 12 - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": "", - "id": "a5d1a83cf25c6bdc" - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:39:04.351488Z", - "start_time": "2025-02-26T17:39:04.348938Z" - } - }, - "cell_type": "code", - "source": "channels = result.zarr_dataset.attrs.asdict()[\"metadata\"].get(\"channels\")", - "id": "21313dd0422d860", - "outputs": [], - "execution_count": 8 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:39:04.987379Z", - "start_time": "2025-02-26T17:39:04.984662Z" - } - }, - "cell_type": "code", - "source": "result.zarr_dataset.shape", - "id": "fac44205ee12e940", - "outputs": [ - { - "data": { - "text/plain": [ - "(51, 10, 1, 1, 200)" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 9 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:39:05.430347Z", - "start_time": "2025-02-26T17:39:05.428487Z" - } - }, - "cell_type": "code", - "source": [ - "x = [1, 4, 5, 3, 6, 35]\n", - "y = list(filter(\n", - " lambda v: v % 2 == 0,\n", - " x\n", - "))" - ], - "id": "8de0fd4910cde22f", - "outputs": [], - "execution_count": 10 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:51:23.172432Z", - "start_time": "2025-02-26T17:51:23.168664Z" - } - }, - "cell_type": "code", - "source": [ - "from pyvcell.data_model.result import Result\n", - "from pyvcell.data_model.zarr_types import ChannelMetadata\n", - "\n", - "def get_channel(self, label: str):\n", - " getter = filter(lambda c: c.label == label, self.channel_data)\n", - " c = next(getter, None)\n", - "\n", - " if c is None:\n", - " raise ValueError(f\"No channel found with label '{label}'\")\n", - "\n", - " if next(getter, None) is not None:\n", - " raise ValueError(f\"More than one '{label}' channel found\")\n", - "\n", - " return c\n", - "\n", - "\n", - "chan = get_channel(result, 's0')\n", - "chan" - ], - "id": "8db5176214e263cf", - "outputs": [ - { - "data": { - "text/plain": [ - "ChannelMetadata(index=5, label='s0', domain_name='subdomain0', min_value=None, max_value=None, min_values=[0.0, 0.46464902525928864, 0.8645283094836882, 1.2086677413467835, 1.5048356119673365, 1.7597188998511473, 1.9790726293721292, 2.1678494351600985, 2.3303119254238944, 2.470127966880844, 2.590454410151291, 2.694007931394946, 2.783126654512909, 2.859822652607626, 2.9258276388928546, 2.982631884935937, 3.0315178958838414, 3.0735894595873883, 3.1097965069383324, 3.140956504205041, 3.167772893474702, 3.1908512206258255, 3.210712523706638, 3.2278052464365286, 3.2425153456691467, 3.2551749434363484, 3.2660698450139596, 3.2754460609589935, 3.283515272280462, 3.2904596743707386, 3.296436069055237, 3.3015793718980273, 3.306005727062094, 3.309815063098956, 3.313093396640947, 3.3159147442093833, 3.318342811684955, 3.3204324190688848, 3.3222307472028985, 3.3237783954804136, 3.325110308262511, 3.3262565611040666, 3.327243030756797, 3.3280919902688684, 3.3288226072577833, 3.329451381681153, 3.329992508925992, 3.3304582042897954, 3.330858983947237, 3.3312038967537685, 3.331500730374292], max_values=[1000000.0, 860708.5246360124, 740819.2773145201, 637629.2827339853, 548812.9316127491, 472368.0904034841, 406571.45450651087, 349939.81298965536, 301196.45115257107, 259242.6574680288, 223132.68273596506, 192052.55096306966, 165301.6251619423, 142276.90008935967, 122459.33067687316, 105402.1856464801, 90720.96893099579, 78084.72460158466, 67208.59467102581, 57847.41433373618, 49790.1903524703, 42855.27127819924, 36886.33756848544, 31748.833062745594, 27326.93706062633, 23520.972065736176, 20245.151059817374, 17425.622965488277, 14998.834644244487, 12910.078918978035, 11112.267824331771, 9564.881034230177, 8233.031844932595, 7086.700699681477, 6100.04424378967, 5250.8218429657045, 4519.888740215109, 3890.768569727798, 3349.2792497615246, 2883.2155525613225, 2482.071044954987, 2136.8020763317495, 1839.6266317778427, 1583.8456523303514, 1363.6934077750684, 1174.2060237272628, 1011.112422367222, 870.7368498443896, 749.9144657532594, 645.9216917774937, 556.4142695350445], mean_values=[500000.00000000006, 430354.49464251864, 370410.0709214147, 318815.24570086243, 274407.2182241792, 236184.9250611906, 203286.71678956892, 174970.99041954466, 150599.39073224773, 129622.5637979974, 111567.6365951872, 96027.62248550024, 82652.20414429814, 71139.87995600591, 61231.12825225584, 52702.58413918237, 45362.00022444572, 39043.89909552203, 33605.8522337663, 28925.277645120146, 24896.679062681855, 21429.231064709908, 18444.77414050456, 15876.030433996015, 13665.089787985999, 11762.113620339813, 10124.208564831202, 8714.449205774627, 7501.059079758395, 6456.6846893262145, 5557.782130200425, 4784.091306801051, 4118.168925329845, 3545.0052573723037, 3051.678668593173, 2627.0688788549764, 2261.6035415134174, 1947.0445010734547, 1676.3007402543858, 1443.2696654784238, 1242.6980776316473, 1070.06416644645, 921.4769374043233, 793.5868721603339, 683.511115191187, 588.7677375544962, 507.2212074380988, 437.0336540243645, 376.62266236862837, 324.6264478371489, 279.87288513273455])" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 14 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:51:24.419177Z", - "start_time": "2025-02-26T17:51:24.398107Z" - } - }, - "cell_type": "code", - "source": [ - "import numpy as np\n", - "channel_id = chan.label\n", - "np.array([result.get_slice(channel_id, int(t)) for t in result.get_times()])" - ], - "id": "4c2abe912538c473", - "outputs": [ - { - "ename": "ValueError", - "evalue": "No channel found with label '0'", - "output_type": "error", - "traceback": [ - "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[0;31mValueError\u001B[0m Traceback (most recent call last)", - "Cell \u001B[0;32mIn[15], line 3\u001B[0m\n\u001B[1;32m 1\u001B[0m \u001B[38;5;28;01mimport\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;21;01mnumpy\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mas\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;21;01mnp\u001B[39;00m\n\u001B[1;32m 2\u001B[0m channel_id \u001B[38;5;241m=\u001B[39m chan\u001B[38;5;241m.\u001B[39mlabel\n\u001B[0;32m----> 3\u001B[0m np\u001B[38;5;241m.\u001B[39marray([result\u001B[38;5;241m.\u001B[39mget_slice(channel_id, \u001B[38;5;28mint\u001B[39m(t)) \u001B[38;5;28;01mfor\u001B[39;00m t \u001B[38;5;129;01min\u001B[39;00m result\u001B[38;5;241m.\u001B[39mget_times()])\n", - "Cell \u001B[0;32mIn[15], line 3\u001B[0m, in \u001B[0;36m\u001B[0;34m(.0)\u001B[0m\n\u001B[1;32m 1\u001B[0m \u001B[38;5;28;01mimport\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;21;01mnumpy\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mas\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;21;01mnp\u001B[39;00m\n\u001B[1;32m 2\u001B[0m channel_id \u001B[38;5;241m=\u001B[39m chan\u001B[38;5;241m.\u001B[39mlabel\n\u001B[0;32m----> 3\u001B[0m np\u001B[38;5;241m.\u001B[39marray([\u001B[43mresult\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mget_slice\u001B[49m\u001B[43m(\u001B[49m\u001B[43mchannel_id\u001B[49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;28;43mint\u001B[39;49m\u001B[43m(\u001B[49m\u001B[43mt\u001B[49m\u001B[43m)\u001B[49m\u001B[43m)\u001B[49m \u001B[38;5;28;01mfor\u001B[39;00m t \u001B[38;5;129;01min\u001B[39;00m result\u001B[38;5;241m.\u001B[39mget_times()])\n", - "File \u001B[0;32m~/Desktop/repos/pyvcell/pyvcell/data_model/result.py:189\u001B[0m, in \u001B[0;36mget_slice\u001B[0;34m(self, time_index, channel_id)\u001B[0m\n\u001B[1;32m 185\u001B[0m times: list[float] = self.get_times()\n\u001B[1;32m 186\u001B[0m return times[time_index] if time_index is not None else times\n\u001B[0;32m--> 189\u001B[0m # def plot_concentrations(self) -> None:\n\u001B[1;32m 190\u001B[0m # t = self.get_time_axis()\n\u001B[1;32m 191\u001B[0m #\n\u001B[1;32m 192\u001B[0m # fig, ax = plt.subplots()\n\u001B[1;32m 193\u001B[0m # ax.plot(t, self.concentrations.T)\n\u001B[1;32m 194\u001B[0m # ax.set(xlabel=\"time (s)\", ylabel=\"concentration\", title=\"Concentration over time\")\n\u001B[1;32m 195\u001B[0m #\n\u001B[1;32m 196\u001B[0m # y_labels = [c.label for c in self.channels if c.index > 0]\n\u001B[1;32m 197\u001B[0m # ax.legend(y_labels)\n\u001B[1;32m 198\u001B[0m # ax.grid()\n\u001B[1;32m 199\u001B[0m #\n\u001B[1;32m 200\u001B[0m # def plot_slice_2d(self, time_index: int, channel_index: int, z_index: int) -> None:\n\u001B[1;32m 201\u001B[0m # data_slice = self.slice_dataset(time_index, channel_index, z_index)\n\u001B[1;32m 202\u001B[0m #\n\u001B[1;32m 203\u001B[0m # t = self.zarr_dataset.attrs.asdict()[\"metadata\"][\"times\"][time_index]\n\u001B[1;32m 204\u001B[0m # channel_label = self.channels[channel_index].label\n\u001B[1;32m 205\u001B[0m # channel_domain = self.channels[channel_index].domain_name\n\u001B[1;32m 206\u001B[0m # z_coord = self.mesh.origin[2] + z_index * self.mesh.extent[2] / (self.mesh.size[2] - 1)\n\u001B[1;32m 207\u001B[0m # title = f\"{channel_label} (in {channel_domain}) at t={t}, slice z={z_coord}\"\n\u001B[1;32m 208\u001B[0m #\n\u001B[1;32m 209\u001B[0m # # Display the slice as an image\n\u001B[1;32m 210\u001B[0m # plt.imshow(data_slice)\n\u001B[1;32m 211\u001B[0m # plt.title(title)\n\u001B[1;32m 212\u001B[0m # return plt.show()\n\u001B[1;32m 213\u001B[0m #\n\u001B[1;32m 214\u001B[0m # def plot_slice_3d(self, time_index: int, channel_index: int) -> None:\n\u001B[1;32m 215\u001B[0m # # Select a 3D volume for a single time point and channel, shape is (z, y, x)\n\u001B[1;32m 216\u001B[0m # volume = self.zarr_dataset[time_index, channel_index, :, :, :]\n\u001B[1;32m 217\u001B[0m #\n\u001B[1;32m 218\u001B[0m # # Create a figure for 3D plotting\n\u001B[1;32m 219\u001B[0m # fig = plt.figure()\n\u001B[1;32m 220\u001B[0m # ax = fig.add_subplot(111, projection=\"3d\")\n\u001B[1;32m 221\u001B[0m #\n\u001B[1;32m 222\u001B[0m # # Define a mask to display the volume (use 'region_mask' channel)\n\u001B[1;32m 223\u001B[0m # mask = np.copy(self.zarr_dataset[3, 0, :, :, :])\n\u001B[1;32m 224\u001B[0m # z, y, x = np.where(mask == 1)\n\u001B[1;32m 225\u001B[0m #\n\u001B[1;32m 226\u001B[0m # # Get the intensity values for these points\n\u001B[1;32m 227\u001B[0m # intensities = volume[z, y, x]\n\u001B[1;32m 228\u001B[0m #\n\u001B[1;32m 229\u001B[0m # # Create a 3D scatter plot\n\u001B[1;32m 230\u001B[0m # scatter = ax.scatter(x, y, z, c=intensities, cmap=\"viridis\")\n\u001B[1;32m 231\u001B[0m #\n\u001B[1;32m 232\u001B[0m # # Add a color bar to represent intensities\n\u001B[1;32m 233\u001B[0m # fig.colorbar(scatter, ax=ax, label=\"Intensity\")\n\u001B[1;32m 234\u001B[0m #\n\u001B[1;32m 235\u001B[0m # # Set labels for axes\n\u001B[1;32m 236\u001B[0m # ax.set_xlabel(\"X\")\n\u001B[1;32m 237\u001B[0m # ax.set_ylabel(\"Y\")\n\u001B[1;32m 238\u001B[0m # ax.set_zlabel(\"Z\") # type: ignore[attr-defined]\n\u001B[1;32m 239\u001B[0m #\n\u001B[1;32m 240\u001B[0m # # Show the plot\n\u001B[1;32m 241\u001B[0m # return plt.show()\n\u001B[1;32m 242\u001B[0m #\n\u001B[1;32m 243\u001B[0m # def plot_image(self, image_index: int, time_index: int) -> None:\n\u001B[1;32m 244\u001B[0m # # display image dataset \"fluor\" at time index 4 as an image\n\u001B[1;32m 245\u001B[0m # img_metadata = self.post_processing.image_metadata[image_index]\n\u001B[1;32m 246\u001B[0m # image_data: np.typing.NDArray[np.float64] = self.post_processing.read_image_data(\n\u001B[1;32m 247\u001B[0m # image_metadata=img_metadata, time_index=time_index\n\u001B[1;32m 248\u001B[0m # )\n\u001B[1;32m 249\u001B[0m # plt.imshow(image_data)\n\u001B[1;32m 250\u001B[0m # plt.title(f\"post processing image data '{img_metadata.name}' at time index {time_index}\")\n\u001B[1;32m 251\u001B[0m # return plt.show()\n\u001B[1;32m 252\u001B[0m #\n\u001B[1;32m 253\u001B[0m # def _get_mesh(self) -> CartesianMesh:\n\u001B[1;32m 254\u001B[0m # mesh = CartesianMesh(mesh_file=self.solver_output_dir / f\"SimID_{self.sim_id}_{self.job_id}_.mesh\")\n\u001B[1;32m 255\u001B[0m # mesh.read()\n\u001B[1;32m 256\u001B[0m # return mesh\n\u001B[1;32m 257\u001B[0m #\n\u001B[1;32m 258\u001B[0m # def get_3d_slice_animation(self, channel_index: int, interval: int = 200) -> animation.FuncAnimation:\n\u001B[1;32m 259\u001B[0m # \"\"\"\n\u001B[1;32m 260\u001B[0m # Animate the 3D scatter plot over time.\n\u001B[1;32m 261\u001B[0m #\n\u001B[1;32m 262\u001B[0m # Parameters:\n\u001B[1;32m 263\u001B[0m # channel_index (int): The index of the channel to visualize.\n\u001B[1;32m 264\u001B[0m # interval (int): Time interval between frames in milliseconds.\n\u001B[1;32m 265\u001B[0m # \"\"\"\n\u001B[1;32m 266\u001B[0m # # Extract metadata and the number of time points\n\u001B[1;32m 267\u001B[0m # channel_list = self.channels\n\u001B[1;32m 268\u001B[0m # channel_domain = channel_list[channel_index - 5].domain_name\n\u001B[1;32m 269\u001B[0m # num_timepoints = self.num_timepoints\n\u001B[1;32m 270\u001B[0m #\n\u001B[1;32m 271\u001B[0m # # Create a figure for 3D plotting\n\u001B[1;32m 272\u001B[0m # fig = plt.figure()\n\u001B[1;32m 273\u001B[0m # ax = fig.add_subplot(111, projection=\"3d\")\n\u001B[1;32m 274\u001B[0m #\n\u001B[1;32m 275\u001B[0m # # Set labels for axes\n\u001B[1;32m 276\u001B[0m # ax.set_xlabel(\"X\")\n\u001B[1;32m 277\u001B[0m # ax.set_ylabel(\"Y\")\n\u001B[1;32m 278\u001B[0m # ax.set_zlabel(\"Z\") # type: ignore[attr-defined]\n\u001B[1;32m 279\u001B[0m # sc = None\n\u001B[1;32m 280\u001B[0m #\n\u001B[1;32m 281\u001B[0m # @no_type_check\n\u001B[1;32m 282\u001B[0m # def update(frame: int):\n\u001B[1;32m 283\u001B[0m # \"\"\"Update function for animation\"\"\"\n\u001B[1;32m 284\u001B[0m # # Define a mask to display the volume (use 'region_mask' channel)\n\u001B[1;32m 285\u001B[0m # mask = np.copy(self.zarr_dataset[frame, 0, :, :, :])\n\u001B[1;32m 286\u001B[0m # z, y, x = np.where(mask == 1)\n\u001B[1;32m 287\u001B[0m #\n\u001B[1;32m 288\u001B[0m # volume = self.zarr_dataset[frame, channel_index, :, :, :]\n\u001B[1;32m 289\u001B[0m # intensities = volume[z, y, x]\n\u001B[1;32m 290\u001B[0m #\n\u001B[1;32m 291\u001B[0m # # Initialize the scatter plot with empty data\n\u001B[1;32m 292\u001B[0m # scatter = ax.scatter(x, y, z, c=intensities, cmap=\"viridis\")\n\u001B[1;32m 293\u001B[0m # ax.set_title(f\"Channel: {channel_domain}, Time Index: {frame}\")\n\u001B[1;32m 294\u001B[0m # return (scatter,)\n\u001B[1;32m 295\u001B[0m #\n\u001B[1;32m 296\u001B[0m # # Create the animation\n\u001B[1;32m 297\u001B[0m # fig.colorbar(sc, ax=ax, label=\"Intensity\") # type: ignore[arg-type]\n\u001B[1;32m 298\u001B[0m # ani = animation.FuncAnimation(fig, update, num_timepoints, interval=interval, blit=False)\n\u001B[1;32m 299\u001B[0m #\n\u001B[1;32m 300\u001B[0m # return ani\n\u001B[1;32m 301\u001B[0m #\n\u001B[1;32m 302\u001B[0m # @no_type_check\n\u001B[1;32m 303\u001B[0m # def render_animation(self, ani: animation.FuncAnimation) -> HTML:\n\u001B[1;32m 304\u001B[0m # return HTML(ani.to_jshtml())\n\u001B[1;32m 305\u001B[0m #\n\u001B[1;32m 306\u001B[0m # def animate_channel_3d(self, channel_index: int) -> Any:\n\u001B[1;32m 307\u001B[0m # ani = self.get_3d_slice_animation(channel_index)\n\u001B[1;32m 308\u001B[0m # return self.render_animation(ani)\n\u001B[1;32m 309\u001B[0m #\n\u001B[1;32m 310\u001B[0m # def get_image_animation(self, image_index: int, interval: int = 200) -> animation.FuncAnimation:\n\u001B[1;32m 311\u001B[0m # \"\"\"\n\u001B[1;32m 312\u001B[0m # Animate the fluorescence image over time.\n\u001B[1;32m 313\u001B[0m #\n\u001B[1;32m 314\u001B[0m # Parameters:\n\u001B[1;32m 315\u001B[0m # image_index (int): The index of the image to visualize.\n\u001B[1;32m 316\u001B[0m # interval (int): Time interval between frames in milliseconds.\n\u001B[1;32m 317\u001B[0m # \"\"\"\n\u001B[1;32m 318\u001B[0m # post_processing = self.post_processing\n\u001B[1;32m 319\u001B[0m #\n\u001B[1;32m 320\u001B[0m # # Create figure and axis for animation\n\u001B[1;32m 321\u001B[0m # fig = plt.figure()\n\u001B[1;32m 322\u001B[0m # ax = fig.add_subplot()\n\u001B[1;32m 323\u001B[0m #\n\u001B[1;32m 324\u001B[0m # # Set title\n\u001B[1;32m 325\u001B[0m # title = ax.set_title(\"Post-processing image data 'fluor' at time index 0\")\n\u001B[1;32m 326\u001B[0m #\n\u001B[1;32m 327\u001B[0m # @no_type_check\n\u001B[1;32m 328\u001B[0m # def update(frame: int):\n\u001B[1;32m 329\u001B[0m # \"\"\"Update function for animation\"\"\"\n\u001B[1;32m 330\u001B[0m # img_metadata = post_processing.image_metadata[image_index]\n\u001B[1;32m 331\u001B[0m # image_data = post_processing.read_image_data(image_metadata=img_metadata, time_index=frame)\n\u001B[1;32m 332\u001B[0m # img_plot = ax.imshow(image_data)\n\u001B[1;32m 333\u001B[0m # # img_plot.set_data(image_data) # Update image\n\u001B[1;32m 334\u001B[0m # title.set_text(f\"Post-processing image data 'fluor' at time index {frame}\")\n\u001B[1;32m 335\u001B[0m # plt.show()\n\u001B[1;32m 336\u001B[0m # return (img_plot,)\n\u001B[1;32m 337\u001B[0m #\n\u001B[1;32m 338\u001B[0m # # Create the animation\n\u001B[1;32m 339\u001B[0m # ani = animation.FuncAnimation(fig, update, frames=self.num_timepoints, interval=interval, blit=False)\n\u001B[1;32m 340\u001B[0m #\n\u001B[1;32m 341\u001B[0m # return ani\n\u001B[1;32m 342\u001B[0m #\n\u001B[1;32m 343\u001B[0m # @no_type_check\n\u001B[1;32m 344\u001B[0m # def animate_image(self, image_index: int) -> HTML:\n\u001B[1;32m 345\u001B[0m # ani = self.get_image_animation(image_index)\n\u001B[1;32m 346\u001B[0m # return self.render_animation(ani)\n", - "File \u001B[0;32m~/Desktop/repos/pyvcell/pyvcell/data_model/result.py:156\u001B[0m, in \u001B[0;36mResult.get_channel\u001B[0;34m(self, label)\u001B[0m\n\u001B[1;32m 153\u001B[0m channel_data \u001B[38;5;241m=\u001B[39m \u001B[38;5;28mnext\u001B[39m(getter, \u001B[38;5;28;01mNone\u001B[39;00m)\n\u001B[1;32m 155\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m channel_data \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n\u001B[0;32m--> 156\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mValueError\u001B[39;00m(\u001B[38;5;124mf\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mNo channel found with label \u001B[39m\u001B[38;5;124m'\u001B[39m\u001B[38;5;132;01m{\u001B[39;00mlabel\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m'\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n\u001B[1;32m 157\u001B[0m \u001B[38;5;28;01mif\u001B[39;00m \u001B[38;5;28mnext\u001B[39m(getter, \u001B[38;5;28;01mNone\u001B[39;00m) \u001B[38;5;129;01mis\u001B[39;00m \u001B[38;5;129;01mnot\u001B[39;00m \u001B[38;5;28;01mNone\u001B[39;00m:\n\u001B[1;32m 158\u001B[0m \u001B[38;5;28;01mraise\u001B[39;00m \u001B[38;5;167;01mValueError\u001B[39;00m(\u001B[38;5;124mf\u001B[39m\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mMore than one \u001B[39m\u001B[38;5;124m'\u001B[39m\u001B[38;5;132;01m{\u001B[39;00mlabel\u001B[38;5;132;01m}\u001B[39;00m\u001B[38;5;124m'\u001B[39m\u001B[38;5;124m channel found\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n", - "\u001B[0;31mValueError\u001B[0m: No channel found with label '0'" - ] - } - ], - "execution_count": 15 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:34:26.641478Z", - "start_time": "2025-02-26T17:34:26.639056Z" - } - }, - "cell_type": "code", - "source": "next(iter([1, 2, 3]))", - "id": "a3ca927959df1a14", - "outputs": [ - { - "data": { - "text/plain": [ - "1" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 2 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T17:10:40.120858Z", - "start_time": "2025-02-26T17:10:40.116709Z" - } - }, - "cell_type": "code", - "source": "[(channel.label, channel.min_values) for channel in result.metadata.channels]", - "id": "e0072378aa30539c", - "outputs": [ - { - "data": { - "text/plain": [ - "[('s0',\n", - " [0.0,\n", - " 0.46464902525928864,\n", - " 0.8645283094836882,\n", - " 1.2086677413467835,\n", - " 1.5048356119673365,\n", - " 1.7597188998511473,\n", - " 1.9790726293721292,\n", - " 2.1678494351600985,\n", - " 2.3303119254238944,\n", - " 2.470127966880844,\n", - " 2.590454410151291,\n", - " 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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 8 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T16:04:46.889042Z", - "start_time": "2025-02-26T16:04:46.805459Z" - } - }, - "cell_type": "code", - "source": [ - "plotter.plot_slice_3d(time_index, channel_index)\n", - "# result.plot_slice_3d(time_index, channel_index)" - ], - "id": "fe324720745ce5e7", - "outputs": [ - { - "data": { - "text/plain": [ - "" - ], - "image/png": 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jG06qHY4pvKd//vOfJ/fcc08gXSQiUmq86sS3Ico/yoJrzoKGxn3gniEPsSSbnwAibEk2SZCWZNtS8ZZky77PSkWcZDscjkmwaNESyR8WNVD8pYHvcDwLJ9UORw5GlRqHYOHsgaYXuze8p1X0pGqUKf4yVFKdhqLTtNe85jXh/il6LaL961//OrwXIiypiEi2iLGTbIfD4XAUhZNqh6Ok3AOZAd7TREIhYcg9VHa7DhSJQjtxGw3unUjza1/72nBfLcmGYJNkCtBPW5KNlMdJtsPhqBrN+FQ7moSTaocjBUU1//mf/zl5wQtesFjkEt/k+++/PxCoZZZZJpQab4okFSHVHqkuBsgt95YGuJ8i2Pz85S9/GRpgJ8KSbNxHski2rn1Rkg151+sOh8Ph6D6cVDscGaXGIdUPPPBAcPFAp0vU+t57702efvrpEJVeZZVVZghZ3bCEeZxe20n1ZIDkUjpe5eO535Zk4zlOA1TEtCSbAja26E9Rkm0t/OQu4iTb4RgOnmnAp9rRLJxUOxwZ3tPWDQKC/cMf/jC4fKCbfuMb31i61Pg0SEehs0iXR6qrBSR3ySWXDA3QNyzJZheDpvLrKqcukg1GkWxZ+Ol91r4vXe3RSbbD4XB0A06qHYNH2nvaWqwRnSRCzWvLL798sG9rmuQU+T4nXvUCCciLXvSi0ABVM23S489+9rPQADsZlmRLb29JNk0e2dYn+z//8z+DxIjvgdA7yXY4HI7uwEm1Y7AYVWpcUUQs80hUIxkRGUgbKBOF9kh1M2Cngl0LOb5QQdOSbGRCNEDk2pJsItsgLRlRaXbIOURcpe3TxWicZDsc3ceiZIlGEhX5HkdzcFLtGCRGeU+ToEZ0GkBsVl111alLjTfl/uGkuh1AlF/ykpeEBog4W5L91FNPhQZIdJQeG6ItKZEl2fQ3ouPpSDZwku1wOBxxwkm1Y1AY5T3N/x966KHkxz/+8Yz846UvfWmrhBq4pV73QKSZvkMD6PGlx+bnT3/609AAOyEi2elKj+lIdlGSrcRH+xkOhyMuNFH8xdEsnFQ7BoNR3tNsu+M9TVIiMg+s8n7wgx9EEfl1+Uf3gQSE9vKXvzzcozTJRkdNE9Dy834i2VrUOcl2OByOuOGk2pEMXe6BhpVS4/ye6nvLLbdcKPCiv4sFLv/oB7hXSEBor3jFK2a01JBrHEUg2mq89/nPf/6MHpufchPJI9lpdxFr38dPEWzJRRwOR/NgpH6mEU21o0k4qXYMxns6Hcnj/xRyIUKIrhXvabk7WEu9tuHyj36De4cEhAbRxr6RxR2aakWz/+3f/i154oknwnvZSRHJRvOfJtm279ootvoP9oDWIzutyXY4HA7HZHBS7RiM3MNGpykxjtyDiDQFPyjyYkuNxxT59UTFYSY+EsV+1ateFe4p/VRJj5BsZEqPP/54uO8Qa0uy07rsUSSb58NWfHSS7XA0hz948ZfewUm1Y1De0/ybiB/VEvn3sssumyy99NLPifTq/zHIP1xTPRxkFfiRBISGTzp90pJsCDZE+7HHHgt9HGKtxEf+xkm2w+FwNAMn1Y7BeE+z7Y12Gu9potJ4T0M8shCj/KPIe2I4XsfkGFU10/ZNJCC0pZZaKvRzdl4syeYngAhbkv03f/M3lZFstNkuO3I4JvePfqYBD2n3qW4WTqodvYG1ykvLPSAZyD3wD8ZLmFLjaFa7QFJdUz0cTNLfFJ2mocWm7yt6LaL961//OrwXMiypiEi2+s44ks3PtLNIOvHR+6HD4RgynFQ7eu09zb8fffTR5JFHHgn/X3HFFZNXvvKVYyf/mOUfo449hkWAY3pMQ07p+yLNr33tawMhtiQbgv2rX/0qvBdCbEk2yZKjSLaeL541PWeUbM8qROMk2+EYDddU9w9Oqh299Z4mKn333XcHAkFEDrkHGtMiiFH+YY8lfVwxRdYdk6PIwqksILcveMELQgM8L5KIQLSpIEoD7N5Yko0biSXZchrJItl6j41mO8l2OBxDgpNqRy+9pymeAaEmikZkevnll1+MEIxDTCTV5R/DQR2kOg2i0zje0ADPkKLY/OTZoQGsJi3JpiBNEZIt+0on2Q6HY0hwUu3olfc0k/qDDz4YnBAgD29+85tnSkWXQUzyD8HdP/qPNu4fz8mSSy4ZGiCh15JsCtLQZPWnIjQi2YKTbIejOHjS/+DFX3oHJ9WO3nhPU5WOwhkUyiBpC7kH29eTIOZIddYxxXS8junRJrlEAkIRJBVCYrfHJj1SgZQGcNGxJDvt9S6SrX5pSTbP6U9/+tPgxc3fW5IN0Rf5djgcjq7ASbWjM2BCJopmvafVnnrqqeTee+8NkzW+08sss8xUnrr63BhIqss/hoMm5B9lgQTkxS9+cWjg97///WIk++mnnw4NELm2JJvINrDl1O3imHwH3HjSmmxr4Sd3ESfZjl5hUZI8s6iB/tz+FDYoOKl2dNp7mtcoNU7Eiwn8LW95y8w29rSQnKRtpIkESWb/8R//ERLP0raAMSwCHJOjC/eP5wwiTAMkBFuSzQKXBtgpkh4bog1BB3bBCmlWP5YdZloukuUu4iTb4XDEBifVjqjBxKvodFruwfYx3tO/+93vApGm1LgiY1VAFRjbhogDREN6cQE3E8g1VmgghuN1TI8ukUUkH+QtKHeBBZ/02PxkwUsD9FORbBudtpFsmjyyrU+23usk29EPLNGIpprvcTQHJ9WOzpQat97Tjz/+eCCY/Pv1r399KHpR9YQam/yD82UBgV6cRQSLCkgL10LAtYFoYLpEtaMbiFH+URZIQGgvf/nLw/mkSfaTTz4ZmkBUm/cRySZqnUW080h2uhiNk2yHw9EmnFQ7OuU9TdIUpcZxI2DiJhmRybgOxCL/oAQ1gFCzeFBBj1e/+tUzv8dnmAg21+dHP/rRYtXziGSnC3s44kQMi7gqQX9DAkJ7xSteEc6PhGLJRH7729/OWPjxXhaC0mPzUxpsJ9mOvoEn/ZkGir/0a0SJH06qHZ3xnqYS3F133RU0nC972ctCdURFtupA2/IPrsXDDz88E4kmAXPZZZeduT6A6/K3f/u3YQseUq1teFueWtXz0K1CVkSyrR2aIy70lfxxXizuaPRhSPUKK6wQJF6KZrMD88QTT8z0bZFsdmiqItmMG/YzHA6Howo4qXZ0otQ4ZcZpTIhvfOMbQ9Sr7gmxTfkHCwf04hANyC9b6BAMHVcatiCHNKvpwh406zksOzSRbCWROdpDH+QfZc8Vgk2EGms9XoNoq7/Sd0nMZWHJNYFYW5ItedM0JFvuIk6yHU3jD6537h2cVDuikXv8+Mc/Dv9mcrWlxkUumXiRe1ByvAm0Jf9gK5yIPNG7pZZaKpBpqkMWsdRLvydd2AN5iAhL2g4NciOCbfWtjuYwJFJtpV2CJCA05E28x5JsCDZEm10Z/g5irUWkzSHII9lpdxFr38dPEWzJRRwOh6MMfNZ0RCP30JYvRJKfRFQhk5BLJlgSEsuUGu+a/INrQTQeTTSTO/aA2Jap0EYVFRWJRls7NCWRqf3kJz8JTeRGJNtGBR2OphYQ9DkWlTTGBZ4RcggsyeYnYGywJJvFd5pk6//pKLaOhbHGemSnNdkOR1VYlCzRkKa6/wv0mOCk2hFNqXFFhvndAw88ELZ80QGLXDaNJiPVNiIPgaC8uqpBFolaThrZTDs1kAxpSTb6VhsVFMmGcA8hmto0hhSpnuRc1Q9pJO3yfCp6bfMIbKKuJdlWJjWOZLPYt2XVnWQ7HI5xcFLtiMZ7mkkKecLChQsDmWMiXHnllVtLqGuKVOPcgdyDcyci/4Y3vOE5W+JAiZt5x6r3TAo+A+JBQ4IzKipIJF1khcYCYAhEsG4MXf5RFvyt+qBccdRPIdo2UZc+a0m2dcNxku1wOKqAk2pHq97TdiLjdYgl7XWve11obU5Udcs/lID56KOPhgmf6LQKaIwizKMIV5XHm44KWsJCkxWaZCWKYtNIgnSUx5BIdR3nCrmlH9I0pliSzQKWBtgFsyTbLgynJdlyF3E4RsETFfsHJ9WOKEqN33fffcG/Fqy66qrJC1/4wpaPuF73j9///vdB7kEkDbkHCZiqipgHeyzpCbuJCTxNWNhtsNvuaL+l/7blqWnpcuoORxWR6nGA3DKWaDyxbjj8TC8MLclmh6woyeanTXi0JNu6izgcjn7DSbWjVe9pokiQSwg1xIv3xECo65R/sB2N3ANijcwCuceoBEw7kY861nHvqRrcrxe96EWhAc7H6lpteWo02CIrtqiHY3F4pLpepN1w0gtDazn5F3/xFzP9Ne3rPopkM9ZZS1BbVt26iwzhHjtGo4lERUezcFLtaM17mgQ4Sm8DiCVkU1uzMaBq+QefhdRDfttEpyliU+bvYy6rDglR8RlbnloNdxdb1ENyEf7tetThkeomItVlF4ZIz/J2X+TrLpJtJU5ZJFtjHuMf4HlgsQmhZ5GZ1mQP4Z47HH2Hk2pHK6XGscpj2xWZAOQS3S6TmSI+MUwwVZJUorhEp1k4MKGinx4n97DH0bUS1lnlqbOKeuBNPsqlYWjo0j3u4wICCciLX/zi0PTcWpJtfd2JXNvdFxaVguQf9lwh1PR3voP3WqlIuqS6k+z+g97/h46VKWdhOHfu3OTcc88NARICI5tsskkyZ86cMM6XwVVXXZUcd9xxyW233RaeMYIrq6yySvLxj3882XrrrZOuwkm1o1G5h5U+YONGiWIVGSnictFF+QeTKRIXzvmVr3xlsvzyy5eSPxQl1W1Hqkchq6gHDi+jyqlnaVuHgiGcr3auYgbk1/q6Y31pSfZTTz0VWjqPAJJtK5Ta+8nr9HFFsq2lqJNsR6yg76+33nrBnYsd1i233DLsNp966qnJJZdcEl5feumlC30WZHqfffYJfXr27NlBBkl9hKuvvjqQ7U996lPJUUcdlXQRTqodtXpPa5JQYRPkD0wQK6200nNWtppglfTTNuxW7iQTGn9HIZeHH344nDP2gCwkyqLod8dMqrOuLcSDJiu0UdpWIiKyYOwzYoze1gXZaXYJSD4kcQKSOKnv2jwCdqIsyU6PielItpPsoWGJ5JlG3D+q+Y4jjzwyEGdI8JVXXjlT2fjYY49N9ttvv2SXXXZJrrvuurGfww71Jz/5ybCwhECvs846M7+7/vrrk4022ihEwz/0oQ8VJukxwUm1oxa5h41OM/EQqdUWT57ThSXVMWCayDkSFyLyaMQZfJB7TFpevYz8oyukOg1IgnVpIIEsXU4d0IduvfXWxSLZfSqn7qS6W0gXT0qT7CeffDI0IHkI3u/I3Wy/tSRbfaAIyVbio153OOoA89m8efPCv0844YTF5rJ99903Of3005MFCxYkd955Z5BwjALjN7u2G2+88WKEGqy99trh9Ysuuii54447nFQ7holR3tMk+dxzzz3h95QZptR4XhQ6VlJdNnLOZPrDH/4wDBxE45G4TON2UUb+0RcQxbDaVrYeb7nllvA6hNuSFRZqItiQFXcW6Qa6IP+YNo8AVyMtDCVvYvcKbTVSKOUSWEccPcdFSXaWu4iT7PjRJU31TTfdFHJgqB1BheM0tt122xBEuvjii8eSapt7MAqxuICVhZNqRy3e07xOqXF0UhCht771rTMEKQ+xkeoiVnYWvI/JErkHf5slcZkEfdBUV7HtzjUlQsJOhyUrKqdOWXsVrBHJhrh0ibgNKVIdS+5EXeDc2JGjkUsBmUaDSk4B/ZdoNv3WOuKIZNvFYRbJTvtk632WYKerPfb5WjvqBTvNgHk8C3r9rrvuGvtZq622Wujn11xzTYhup+UfV1xxRbLssssma621VtJFOKl2TARrlZeWe+DyQKSWn2hh0RIXqbAXG6kuI7uwjiZMoqzmJ5V75KHP8o9pyArnrHLqJDzacuoQCisVsaWpY8SQSHUsuRNN31ukIkSz8xxxWBxy/yHWlmTrWmmcVf/OI9lpn2wn2ZFhET7VDdyDRUnIZVpxxRUzf33vvfeO/QgWfoDxNgt6/fHHHx/7WfTlk08+OXnPe96TrLvuuskaa6wR/p6dx5tvvjlZc801k2984xuLJfp2CU6qHZV6TxOZvv/++8PvWG2iiSqTaKfviE3+MQpMhiwikCikHU2qPI5RFRXzXhsCFOWjITHifolYy1VE/ucM1GlnkZgQS99vAn2PVI/z5c5yxLEkmz7M2EJ0e9QOjJNsR92gXwIWg1lQjtRvfvObQp+3zTbbJN/97neT7bffPkhLBMZwEhWr2OFtC06qHZV4T6NzZcWLhpqoNFv0DP5l0DX5hwrYPPTQQ+EavPGNbwyDQdWTk8s/yt83kQ8WdbY0NST75z//eWhpr2FaLNGRIRCcvmmqx0HkNk/zz7VILw61AyOSbXdgLMlmV6wqkk1AwH6Go/tAC10kIt0UvvCFLyQHHnhgstVWWyWHH354GKeRRx122GGhkcyITV8X4aTaMbX3NIQFzRWZ7+imIZeTkJPYSPUoMssiArkHtm+s0nH3IHpU53EUgZPq8aWpkeqIYKe9hiEn1gataWeRock/hpRUWraCpKLTtNe85jUzOzDWepI+DEYVUJqGZCvx0Ul2TYmKSTcSFSVlJBcgC7/73e/Cz+cXmAOx3dt///2DDvtb3/rWzPNADtL555+fzJo1K7n00ktDJPud73xn0jU4qXZM7D1tfZj5P7IHTNwnHXxjJdXp47FyD0zw0arVSb6KylB80isGFny2oIds0ESykTDRJCuxziJ1R1aHtCjqg6Vek2XZ7Q6MvN0VvWZMsgWUGI8syba5BJOSbBFsyUUcwwHyJCDHpTT0+lJLLTX2s84444zwk6qJ6X5E30IawvxK0qKTasdgvKdt2e2qIrWxyz/4SSLGgw8+GK4BZJoEi7qJQR+Lv8TsNUzURSRbyWPStVqiQn+v694PgWwOTf5hx9AqAAEhEZwGGKstySaPQLkEODDZvos2dhzJVhK6SDa7c7ZwTVqT7SiLJZpJVKyg+AtyTvD9738/8/d6feWVVx77WSLgBCmyoNcldeoanFQ7MsFgyiBqvafVGKgh1GyjQyrf8IY3VBKpLWth16T8g2uB3zZaXCYkFhFEMZs+jnHvi+XadRVcQ7Y6aey6WF2rItnacqfPWz22JSqTYkjyjyEmKtZJPumPtoCSzSWg4UxEswm7ItosKtMk247HNoqtYIstRuMku9/AkQOyi4sIUWTmPwtkG2CLLbYY+1mqRkpxlyzcfvvt4SeSpy7CSbWjsPc0/ycpDy9mBk5Wr8gfmpY5NAUdD16yP/jBD4JMgAEBzXiTWtvYXFGGhLSu1W65Q64tUaGogQg20cOiRQ6GSqqHZqlH32nyfNO5BAQGLMm2Cbvqu5ZkC06y68MzDWiqqwCLsN133z056qijkt122y2UKZfjB2XKCbLhN72KKfxCBUYaMg/KjgskJ2KZd9ZZZyXbbbddsvnmm8/87sILL0zOPvvs0F/4uy7CSbVjBorIZnlPk6BAMiKEAoIBoc6z1+mL/EPERlnT02rGp4VHqtuH3XIno94SFUg27jc0wPNhI9lswTuehUeqmwX970UvelFogJ1GS7Jt38XByZJsW2dgWpItdxFHt3DIIYckV199dfCSVnEW5JA4ddCnTjnllMXez442Usmnn356sdch1ZBpkhSJbJOYSI4AwTpFryHvVF/uIpxUOzJLjVvfUh4KiCW/p/PzQNUxOcREqiFLcoRglU6mcp4GrK1IdZqUaDfB0R5RIdfASkV++tOfhgbQYFtnkSzni6EQTRGxIUUwY3M7YVzDrUmVbum7lmQz7osQWetJ+q7dhRlFstndYzsfq1HmDkuyiZIz72CnFtN1abZMef3PelVhFhZW1157bYg6E02eP39+CC7svPPOyZw5c3ILw6TB/T/vvPOSTTbZJDn99NNDlBtJCf1q0003TfbYY4/wu67CSfXAMcp7mtco5EJiAQMwWzsiD3UgFlKN3IOHXPZByy+/fGuEuqz8wyPV7QKygUSIxr2wziIQFiqTqSy1fIaZmFTMY0ikGgzhXGMl1Vl917ri4G6kpMe09aTdhYEMWQtVS7KJhluXF+YaLaaIfJ5zzjnh2Shb08DRDlhcHXHEEaGNw+GHHx5aFugPu+yyS2h9g5PqAWOU9zTJWcg9qKRE4gtZvZNoRLtEqlUR8oEHHgj/Ri9OpKbtiTCvemKaQA+JoHQB3A/IB41InS1LLZJNU44C5AQSDvpOrodKqrskASIyyRiovBktEEWy7S4M+lpLsnWecg5B8qE8FEWx5W0sbe4Q0Yz7h6NJOKkeIMaVGieSJmK53HLLhW27Jia/NhPyuBZIXCDRrMbJboYA8f+2o79Z1yXrmFxTHTeyylKzK2JdRXT/brzxxsWSHmMrp962Z3MX0bamumrryTTJZkdTdmkqoqQItg1MSP4BqWbBWXfQ4s4770yuuuqq5LbbbgtNC4FJx0rOlQgs8gc06OxKkVTHaywoHMOGk+qByj3w3SWRACcLogoqNS7bOAZPkhGbHCTailQTlcfdA7kH+kIqO3FNFElpW47i8o9+Qr7XesZ4LvF7pd+xK0S1TppNHFOre9eobgwxUk3Utu1drzp3YRg/pceGaLPrJ/BvNNv0Y5Vip5/bojR1Ab0vrhJVgDlz9uzZySOPPBK04CTdEYz50pe+FCoA3nLLLTO+4cV8qptYZA3nGYsBTqoHKvfAxYMJW9vMDITIPdDRsfKmsEnTW5VNk2rOncgKunH+jd82FaE0yMfim13Gp9rRXWiLnLbaaqvNuDMokm0Tx+x2O63pcurTYmiRau0O9vV8GXvokzQS1lRECTJNn6UvswP6ve99LznxxBNDnoqkdcw5VTtJWUCCkS+uuuqqoWGNCcGfBHvvvXcg1FT9I9lOz92ee+6ZHH/88cm+++6bnHbaaRWfgaNL6NZI7Kis1LgiJgz0GLozUDRZJbBtUs3i4r777guJN0RPkHuko/Ix+UMXkXa4/KNfSLszKHFMJFvb7ZKV2HLqsUdEhxap1vn2lVTnFVFiTIU8Y0fK7ie7oG9729sWSwSnz0J811133dD4fZU7MZ/4xCcq+RzOg8RKnksWBnYh+7nPfS4599xzkzPPPDM55phjZp5Zx/DgpHqg3tOadBnciFozACL3mLbUeBdINXIPzptICm4myD1s9nqsxWhc/tF/jEpQtIljdrtdSY/os/GNVcEa6ywSG3kdWqR6aOcr2ERF+uGOO+4YGpFi8nWYdyDc5BAsWLAg6JKJWkNgm6pYWxSXX355uI/4M8shRWARgOcyXs2XXXZZsJkrZKnXgDTDZ4Rm4aR6QN7T1kuUqBeAUFPQBOlD29GtJkg1kT0i1FwPzOXZCswjHLHIP8pEqh3dRlHXj6ztdhaLimKr6uOPfvSjQGhUxAOSXUU59WkxtEj10El1em4hiEGwZ5lllglklX/jZ40PMvk+sRFqgDwSULMgC7wOqcZ32TFcOKkeaKlxaTOJFpBwEQPqlFuk5R5E5cd5o8Yq/9BuQ5alXgzH6pgck94/7r0SwFRO3TqL/OpXvwpJViI01lnEVstrCkMj1SKXTqr/COYhdlpkp0f+zhprrBFarEATDvKKnOh1douKwi31+gcn1QPynkbuwGqbyRZ9G5ZIMVkA1RWpxhoPuQc/R8k9mjqeSVCUfDip7j6qIJqQGBFnwJhgkx7RttJstTwIdrqQR10YWuR2aOebPu80qWanlN8h/+gKmD9AXlKlFgjsGDmGCyfVA/CeBkRosf5RWVg0YLhexEAY6ySxeJISoeYzy3puxxqpHvUeR7dRV9EXJCBLLrlkaAA3BhHsdLU8eQxDstFm1+Esomd8KH02j1wONVItu9IukeqqwXDehKVeBNPXoOCkuuelxq3sASKN7osKiTLAj4lUK6JexTHZEuucN3KP4v6hzx5PLNfI3T+GgaYqKRKNVjl1wK6VJdlYodEkKxHJ5t9VRFuH5oYx1Ej1OFJdp5Ve1dACQK4laeic2kz2d7QPJ9U9lnsg85B1EREqZA+yKtLgrkEvFnBc05JYK/fgvPEonWRLu2uJirEcq6N7QAJCEQ8V8oAgiGQjGyHxkQQyFawRyYZoTLIIGJqmeuikOn3eklJ0KVJNFVSgqpFp6HVqHRTFM16YpXdwUt0j72lbapwJ8MEHHwyvZ7lcWJ/qmMA5TEMMrcxl2WWXDVKXSSfuWOUf/GRSIsHMTlb2eIdCVvqGGO6dPIZpKqdunUVk44e/PdKQdDn1Isc/NJI5tPNNV5FM94kuyj/Y7QRUPc2CXieI4xgunFT3QO5ho9NoJe++++7kF7/4RdhaYyBAFxlzEp7FpPKPtNxjlVVWKS33yDqWmK4R9x1/V5JNITUcH/eW85z2XB1xQLkQMUG+1zRyEnjWiF6LYDPW0ADPniXZeUU8hhapHrL7R5aOvIukepNNNgn374YbbgjViG2BF8bliy++OJzrpptuWvATl0j+0Ij7xzCesVjgpLpH3tMQLQgXDzgFIqiOmJdk1Cf5BwM0cg+iaejFiRRUUZErtkg19/3mm28O95cBHW9XtuUhOPgR63jRy3MdiBo6uoUY+to4QBzoXzRAPxTBpv3sZz8LDbCwt84iWKcNMXI75ETFUaRajhkxYd68eaFtvfXWydy5c2deZ06lcM1ZZ52V7LrrrqGCoubXAw88MCwsP/CBD3g1xYHDSXVPvKfZiqUxgL3xjW8M2shRUaCY5R9ljgm/7XvuuSdcGwoJvO51r6ss+hWLplo7E5AXjon7izUgr9PkRwyZ5n34kAPkIYpiQ2xEaBxxo2vRW/qVLafOos9KReiXSoxWOfWhRaqHtoiIKVJ96aWXJnPmzJn5P7u5YPXVV5957dBDD00222yz8G/83JFOqpaDxXHHHZcsXLgw+fa3vx0Kps2aNSvIDZmDkBsee+yxhY+LJ6AR94/av8Fh4aS6A7BWeWm5B36fRKeZvJiwkHsUGahilX8UJdUM1gx8GPKThChXkyoRQ6Sa+86ADaHmeGbPnh2iO/w/7UcMmSFCSNlfeRJbqzT6h0g2W/lDm+C7gBg01dOCXSJbTj3tLGJ9fAkE8H+VU+9rnxwyqc5KEm+SVBNBvvXWW5/zun1N8qVxIPH9tttuC+XU58+fn1xwwQWhZPmee+6ZfOYzn4mq7oOjHTip7rD3NLou9NMQLBKKSEgsur0Ys/xDhDEPuJkg9yBCy2TMQqIKuUdsmmqSEX/wgx+ECYj7yjlCPMYdDwO/rNK4Vkos4yfVvmhcZ6t9hah3ncz1AW3vilQN+hQSEJrKqdOvf/zjH4eIIISbf9Po45AS7az0qU8OmVRnzUly/2hC/rHzzjuHVhQQZloe6J9f/vKXQ3M40nBS3UHvaRulZev1LW95S1gtl0Gs8o9x1nFEYonccm2QeiD5qGvibVP+wXmyYOJes1hi+9zeq7wy5enjFaGRVRoLEZFsGuWrbelqRbLrWKQ4iqEvRDLv3CQBgVST/8Br1lVEfZKxTX2Sn13OERhioqIki1mkWl7PXUpUrANeprx/cFLdMe9pVvjIPdgyZaIhSot2tiy6Jv/gNRYSRFkhgGjZVB2uLrQRqU6fp2Qt6PvG7SqMI2NyC6FhsajS1SIztnQ1ESSRGaKHdVTVc/RT/lEEeqboVyouA2yfpLEbRwOMc5ZkN1FOvSoMMVI96py76P7hcBSBz5Qd8p7GLg7bOH5HlJY26SAds/wjTWKJarCQwOlimoXEJMfSZKTa6uMhsm9+85tnzrNMmfKix5suXW0TzPhpq+pBxG1VvSEQvzYwFFKdl6iYVU7dOouwuFQCWZcWfkN0/9DcknVfJP8YevVBL/7SP8Q7Cg0Mo7yneZ0MYyaTqjyYuxKpJnKKDIJrQCEX5B5NRXuaTFSExKITh0RQkQvJR/o8ix7HpMebTjCzVfVUWQ/t66QFPxyOspFbotFI2yRvQ4NtSbZd+CkRl34ZWyLuECPVoyQvkn/EaKnncEwDJ9WRDLgk51nvaTWis0QvGYSwUaPUeBXbntaOL0ZSbWUQaCtZSHD+TaPua6Tql9jgce5E4SG1WcdRNFJdV1U9+qJIti34Ies+kWy37pscQ49UjwMLONrLX/7ymYWfJdnkDKicut1dgXC3eV2HTKrzLPWUxDpU/NFSr/4+2a/U5/jhpDpS72l+R1RQnsPLL798IDdVTgx8V2zyD50fdkeQuLQMomtl00eBhRRJl0TjidiQcJqnMaxD/lEG1i1Ex26Ty7Ks+7QtPyQiMS2cVE+28HvVq141U05d/ZLxg58URmJ3xTqLQOaavM5Oqp9LqhnzhiSHcQwDTqpbnFQUnU7LPdC2InkgO57BH1KJjjWG6oV1Q8b8TIiURMZQv82JqAiZnQRM/tjlsQOB/R0FXUZpQrMIQN5xNSFXSRf8sF7E/LTWfZbMQICGQBqnwRCuTx0k05ZTJxEXUidiTWM8paXdbvhZ96KdY7HVb4eAIqR62FiikeIvXqa8WTipjqDUuPWexk7qrrvuCsQaGzQi1HUl4DDYxUKqOY6HH344EDKQJ4Pog/yDiC4Rau49VbnQUBdx7mhS/lEWbMnTX2Xdx6JBtn0i2iLjtspjWzsQsaJvPtV5aKKiIuOb+hogiGGdRazbDf1XfbKO6qOMIUMi1KOSMyXbaXq3wOFoAk6qI/Ge5v+PPPJI2KpkEMK/Fd1gnYhF/kGUE904Ex4RJKLV0yZixij/4B4/8MADwV+cpEB2ICSnGIe25R9lwHGws0JTxFAVHtNkholVxCd2B4cmMBT5RxtyCIgyeRnKzSBwYfXYtpw6OypWwjStTGGIpJq5blSkeujOH4idG/GpHsY6PRoMewaLxHvakkqICFHaJrbGYpB/kOxGZJ4oEgSMa4NsoO3jqlr+wT3G3YPt6EmqQJY5jrZJdRpMqnhtq4w8iyZFsWlYRdJExkWy+1y2uq3obSyI4Vx5/pBe0VRO3ZJsFr802y8h2fy7bL8cIqkeZSMo2dsQ+rpjWHBS3XKpcVshEFK53HLLNTb4MtgpmtCW3EMWbaoKieOHft8XUo2Ok0UTC4dJdeKxyz/KgN0IS2aYYEWwWViy8FDZalvlMbbFQtXo+/nFnLhny6lLwoSXsrWTtP2S6LWkIkXyBIZIql1TXcD9owG983BGlTjgpLrFUuNIAfBYbcsyri35hy1yQlIRUVtZK8Xmnz1NNJ/7j5yHxYNdOEyCLsk/yoBjZnKlycEBWzRbRl3JZQCig3SkaxX1yqAri6OuR6pHQb7XNFlK0i9HlVNXy/Jtd1K9+OsspIdOqh39hJPqmqDotCzT1llnnRlCTRIXpBKCQAQO/XQbCVttyD8gSMg98oqcNF3FsK5INVFpzhN5CxMz+ukqJpEixxLLtZsEcguhUeyHZ0gkBr0r/YZCSFb3SmNx1nV7rtiJZpXQjl0X+yW7TcoTyCqnjqzEJj3yf97f10VgWVKNzIb77yXKHX2Ek+qaS41DCmQTB4hMU2qc9yEDgDi0NYk26f7B+ZKI+eijj4aoLSST7f80YotUa1ehDNgmRj/N5EGy6Yorrjg14SsShe4jGaOvKLkMqRQTMa4wSnqU7lV2aiLZXbTu6/JiqCxkI9pVpPMErG97upw6u3D8nr/h51CKI+WRaqQfwEl1Q4mKjkbhpLpm72m5GSB5QAYAMSAqjeShqPND3c4WdW9Ncu5EbSFCJPlAqPMqacVGqsu6f5Bwd99994W/WWGFFYKkoQryUOQzuij/KAsmaBYqqqjHbo+kIvIkZuGmLXmR7C5Z93WZbA6FVI/zbWfMs1IRzhfJww033PCccupd32GZlFQPuZqio79wUl2T97SM/jWg3H777WGgRVNLoY8YohWWwNZFqtEdInUhWo82EV/mUd8VG6kuKv/g/kOmkShA4NBPM2FWeRzjLNeGQKrzdK9IiVTsQyTbbskzgdtiHzFa97n8oz9gDGBHhca5XnvttUH+RT+EaNviSNZZpE+ON3mkmoUw8Ei1R6r7iPhmlp6VGie5RZ6oVUYuq4AGuzoILOdOxBDJB9+TJ/dIQ9cmJlI97liIQCH34F4vueSSQSNftX6yCKkeOtLFPljIKVIoTTZNZFzvncQirQ4MjVQP4TztfYVUE1BRcST1TRaC6LOBHG/U+JuuXifmRet0Jbj8w9FnOKmuyXsaEi3JA1hppZVqL+ZSFnVFhXXuRKnLJunFlqg4Tv5BJJRzpR+87nWvS5ZZZplaJsEymupYrl3bYGHDzhBN1n0iMvxkEfTYY48tRmQg2V7prX4MyQ1Dz6PO1xZHYoeFa2HLqVvHG5VTt84iXQHzYp6dHhg6qV4UypQ3YannY1mTcFJdg/c0jg933313iJQhAWDAjFHTqUG+Sls9W2adqDxyjzKawa7IP2ziZROWiE6qq7Pue+UrXxn6ly2lbokMbg1Wj92Ua4NHqofn16wxT6QZMK/klVNnHrHOIjE7iihSnYZrqh19hpPqikuN24ImJCPyXkh1DOXA65R/WE/macqsx0iq08fCYgmdOERsXOJllcdRlIw4qR4PuYXQsEiTdZ8i2SQU0xRRE8muomR1HoZGqocSqS5b6Ia5AxkZzcqY1Defeuqp0GzfVDn1mHIFmPOyjkekevBlyl1T3UvE8wR2XO7B1jJECwJtC5po8IuFJNZBYC3JZJCHZE66tRcbqU7LP4ggoZ8m6ZSI5/LLL99o9v4o4jUEMtaEdR/g/komwk+sMGlcY1XTUyn1qq77kBZDPN99db2ounqklTEBW0493TdZ5ItkMw+1uXDJ8+Z2+Yejz3BSPYH3NLByD/xIKUgB4U6XodbEEWOkugr5B4M6hBq5RxUkM8ZERR0Pdnl4jPMaCUecb9PH4fKPZsA2e9q6TyRGW/PszEDGtR3Pzyo0r0NYHPXNUq/Jkuz0MZr6JiTVemQT2CFXQAVrRLKrXABWoan2iorNlCl3NAsn1SXlHjY6zeuQLBwFWJHPmjVrZstOiJlUTyP/kNwDXTGD96Ryj9gj1ZqE0MizeGIywy6PiFAbx9H3iopdKFkt6z6RbGvdR/+wmtcy1pku/+gnqibVFvQVIr40cliUK2ATcpUszwLQJj3WnZCbtxvhkWpHn+GkesygoGIu1nsaMHAhA2CAoKoWpJIEpzRiJtWTEljkHiQjktg1rdwj75hiIYa6bxBqpAHc5zY8xssUf3E0Z92H44u17uOnrPuA9SAetx0/NFI9hPMEdnezyVyB17zmNc9ZAJJET7MJudplyZq/JoUKoDmpzgdPezPuH44m4aR6Au9p9GsPPPBA+Pdyyy0XJB95E0QXSHWZY2NwRu6B5vQVr3hF8N6uUhsZU6SaRDVNQHXa5RWByz+6Y92H5lUEO23dx3a8SHaXPYinxZAs9TSWtaEhTy8ACRJJvpROyFWBpEl2WcqcsycqOvoMJ9UpWKu8tNyDiBTaaeyN2OYlGZFJsmnbujbkH5AFiMFDDz1Uq6Y4BlJtXVyUqMi2f5sEyOUf3QD3CXJCy7Luk32fyLgIDyTGI9X9RJ3yj7KAKNuEXHJh8nZZIL3WWaTMomCUjaBrqh19hpPqgt7TNkJLZcAVV1yx0Eq+D5FqFhNoionaMhAi96grytA2qWaSQdbD/WYLlS1KJpm2iWqZSLUjbus+IoUiMTZSqCRHIt15SV59AH3YNdVxAMkH8xlNuyw2IfeJJ54IjbGFPiySPa4K6ThSzd92qZBNLVjUkKWex1gahZPqMd7T1n+Z14jQInsoSmDqLAXeBIG1FnIkIiL3qNMLtU33DyYTzhViTWSawjVE5kGXSHXbx+oo7kFMX0tHsCHZ7IZBYhTJbtq5oU4MKSIfO6nO22VhjrOuNzTmAho7eJIyiWQTfLD3cxyp5v2xXw+HYxIMnlSP8p6GSKrU+KQJeTFHqkcRfq7F448/njz44IMzco8yi4kuRartuaadTGKz+HNS3S8QKXzZy14WGglld955Z0h85h6KxMi6Twllcm7oKvQsOanulusN50F+gCLZdiHIrq3VYzOnZpFq+jU1HZqSfhB5nzt3bnLuueeGiDvPzyabbJLMmTMnzGdlcNVVVyXHHXdcctttt4Xnkmg9lXQ//vGPJ1tvvfVEx+fFX/qHwZLqcd7TWGQheSCxgwHl9a9//UTbsTFrqvMILOfMuXMNmLyxkGsqqaRp9w8Gf86VyGCWtCUWN5IyBKTtY3VMB0iJSAxEWwTGOjeoXLVIdhuONJNC/bNrJLOuMuVdgXyvaZIy5VlLqj8S6WY3xjqLEKmu284PEBRbb731koULF4ZF65Zbbhnygk499dTkkksuCa8vvfTShT4LMr3PPvuEY549e3awL8Sw4Oqrrw5k+1Of+lRy1FFH1Xo+jm5gkKR6lPc0/ydiSeSS6BAkC73ZpOAzGUxjJtX22BgkkUCwwmcgQjveZOnbJiPVDPg/+MEPwiCPc8NKK630nHONJfpbJGI+lMhfX5GWRfAsKPIn5wYbJbTlqlkIimS3XUlvHFz+0Q8wVrKrQgPqnzQt/rAipSGj+/73v5+su+66Idqtv6kTRx55ZCDOkOArr7xyZpf52GOPTfbbb79kl112Sa677rqxn8O5fPKTnwwLBQj0OuusM/O766+/Ptloo41CNPxDH/pQYZIOFiVLNGSpN4znLBYMjlRneU+rQa5IRuShZzWOu0cVyRSxkmor/0jLPSDTuBc0PfE1JbeAjODkwvegnV5qqaVGlv5uW/5Rxqe67QWAox4wqb/4xS8ODci6T0mPPL80RRRFsmOz7usryRz6+dr+iTSCwmjMIcy3Z511VvKtb30ryDAA8olDDjkkRJLXXHPNsPNSJUiunzdvXvj3CSecsJhsc999901OP/30ZMGCBUFuhYRjFG699dYQbd94440XI9Rg7bXXDq9fdNFFyR133FGKVDv6icGQ6lHe0wCHh/vuuy+8h6gQrapBkM+JkVTr/LgmRKeRQLAtR3S+6YqBggrs1EVi+Vw8xtHXsSXJwgnikYfY5B82ypd3TG0fq6OZCC4LfnShSiqz1n22kh7WfdJjV13kYxJ4pLr/0HyHdR9976STTkr22GOP5IorrghRXaQZn/3sZ0OjP0KsN9hggxARrqJf3HTTTWHXlXkc+WIa2267bciXuvjii8eS6qLPyyTR90Wuqe4dBkGqGcQVnc4qNQ6ZJnLJw/PWt7618q0pIsJtRzqzoEEetwEGQWQuJCQ2KffIgmQ4VYOBnMUDURIGehYP4wbMWKK/bqnXf0xDNvkbFsI0VdKTdR+NBTMNELkWySai3fTzPjSSObTzzdKRc+6Mt+yAoj3eYostQqT6e9/7Xmg33HBDkFkcdNBBlXw/O86A+TwLeh1iPQ6rrbZaeE6uueaaEN1Oyz9YKCy77LLJWmutVcmxO7qN3pNqG51Oe0+zkuXhIxuZFTWaWqI6VYOBBVIfE7gWTz755Mw1wiqP5IsYiFkdkWqy1LnXbAtCOqiEWWSSi03+4e4f/UWV940xx+pdbZEPGs8+TWTcWvfVTf6GFqluskx57MmZzLWAfjZr1qzQPvGJT4T+qfmoCrATCfIKlOl15FLjQI7CySefnLznPe8JmvA11lgj/D3He/PNN4co+ze+8Y2JuMMzrnfuHZ43VO9p6YfBKE1tFWBgIUoaC7gu99xzz0zRCbkNxAJVMawCfA6+qiTKcB/KJp7GKv8YhbaP1TEd6hiH0kU+yB+xRT4IMPCcyLpPkWwkJlUfz9BIdZtlymNbSKiaYtqalv6JVKPKJHSQZz0pSz8kU0WwzTbbJN/97neT7bffPkhLBBakJCqWtedz9BfPG5r3tK0OyAOHppaVaJ2IKVGRJEwkEEQMcLzgOsQWQakqUm2tARnE0daV9UeNLfqr48g6nqGQlL6iKbLJ5/M80NidknWfSHbaus/qsauw7huaHGJovtxA811aWiRS3TWf9S984QvJgQcemGy11VbJ4YcfHhIS8Y8/7LDDQiOZEZu+MuBpb8b9w9EknjekUuNIANBQsdXURHXANKkWwW8DfDe+miTp8e/ll18+RKevvfba1qUNdZBqu3iYxhowNvkHoH+zy0I/ZnsfsgP5iW0B4CiHtu6bte6DLLAYtXps2aJp214km2DEJNHXoZFMztfOQ0NA2Uh11dDnS26Sho6jSP0FbPf233//oMPGwUTnhFz0/PPPDxKWSy+9NESy3/nOd1Z6Ho7u4XlDkHvw/0cffTQ0JgEehia3a6x1XRtbgFwX7OOYGNnOJTpP4gWo02mjrURFnFw4X/rEtFrx2OQf2KghZdH2piKKRH40kcSyK+KYDG2TL6LR5JjQ1OcUxeYnelWate7LKlWdh6EVfxGpHhLySLXGrbpJteSMeTptvY7scxzOOOOM8JOqienzYT5HGkIAh6RFJ9WO5/Vd7sGEQHSayYBVKZrapkqkZhVZaZpUoxmjwAkrdvxDWVDYLdwY7f44JpW5LQPOA29UBkwit9xrLR4mRSzRXx0HEWr6+zLLLBNIDxF5lQtWNTO0sUQatWVflOw42kWsWmMW4jR296x1nwp9yLqPcUUEW7snXTrPujBUUs1cl77HihzXPQcTOAIUnMmCXl955ZXHfpYIeJ5MVK/zLJSFW+r1D8/rQ3SarRz+TbKD3WbDQoqEPLYzWZFSaryNwc1GqpsC10Pe2/w7LxkzJr33NImKDNZEC1Sti0G1CieXJis85oFrITs07h/bjQzk9GsWSmjjeQ9Ra/o7BEgaWXZnuA4i2LQ6HG4c06MLZDPPuk/k2lr3sXsikk2T/Gpommqu0VDOVcgLIDUVqcaRgzGS8Y95gQCLBbINgLXfOCixneIuWbj99tvDT54Hh+N5XfeeRleKdyRyDjyWGfR5oInosUVJ9AQtlKqQtQENLk2RV+u9PS5iy2Afm91fWUkKZJLdCM4DTSieoVURk7Yj1TbZEnBuLBrSkXyOU9U/mQTY/rS6WJxe5PbSpZLWQ0LbuyFVWPeRCG4L0GRZ9+mZinnxUCXakv3FeM5NaaoJHOy+++7BE3u33XYLZcoVHadMOfMFftO28AsVGGnIPChQI5CciGUeVSG32267ZPPNN5/53YUXXpicffbZYQzl70phUTOJip6p2Cye13XvaQ3MvMa/WQnjR8wWJdERIpZVl0CNmVRz3qzMGbyKeG/HKv8oQqohIUQiHnnkkRAFq2Px1GaiIn0Z6Q73kr4MSRnlvmAXAFk+xZKJ2JLWvI8FlxIe67BQc5RDl68/Y4217mMHyUpF2EERCHqwaKRvE9Xu8nmPAmNHFa4pXQLzc1ZieFOkGlBc5uqrrw5e0irOwpiHUwdz4ymnnLLY+3/5y1+GYJySci2phkyTpEhkm53C1772tUFmp+g15J2dcIfjeV0tN24te6TBJSKCppbfoTnF9zKGgbopUm0T9HjA2Y4ad/4xVnssQqqJiBFtYCAk8opdXh02TW1FqtlC5/y4Dkh3ODdIySiJwKh7jTQKFxSa1cVCsvUTsACFXEOy7Za9o350Qf5RBpwH0UGarPuQZ0GmeW7pg/IJpn9aPXafJEpD1FSPi1Q3kdfEWIa7FVFnosnz588PfWvnnXdO5syZk1sYJqsfn3feeckmm2ySnH766WFcJnBFMGLTTTcN5df5XXlQM6OJZ70f40lX0LkZkw4u3bQa/2ewZqDmQWJLh4cnFtRNqvlc5B6Qas6f6DyTUxHE6v4BwcizICTaRQSXgjrIfnD4qGt7tWn3D76HyLu00ETfIbhy+aii+EtaF8uC1FbbQzZES1fb4999IXwxoovyjzKQWwjEirFacj1Fsq11H5FMK1HqsnxiiKQ6T1PdZKQasPN2xBFHhDYO+E/TskA/3WWXXUJzOHpFqoGItAiW5CBs/TNQxxblqJNUIxFg1czPJZdcMmQzlzl/JQXGNPBbImtJnEqrs4Dgde510WhDFyLVbIUjXYJwQGCJvksnXWeZcqLR1kJNW/YiO7bank14bFtW1Vf0feGi/okkgsW/+h2LZNvvrHUfxLqrbjYxja1N7ibHQKpjhhd/6Sc6Sar14D722GPBs5d/QyQhITEOttZSr0oQTUTuwaC93HLLBZ1X2fO37haxDPxZx8S141w5Z4gmyZd1V8JsUlNtrQ+zou9F7mtVfR+pCY0Fi6rtieyQMKmkSbZwRXSIQHY5mhgD+ib/KHueLNKw7ZN1H4EC9TvrZiMy3oXFnQIWQ3o2RpVll6VekaIrDkcX0UlSjZ4Wn0kiekzsDM5EqmOdjKq21LN+zGgRkXtMKndpw+6vrI0d0Q2i8RDPIsmXdRxLnZFqtryxwuN884rV2Cj0uH5e5bHaanvkKPDsQW6kxaZKJ03RRCU86rl0FMdQSHURSz2uAcSLhhUoY17e4o5Ftgh2bHkAQ7MPtMGjNi31uoKeK74GiXhGnxIgWgmhJqJHuW3pa2NFlfIPSzAhMMg9INaxRdGrItVMnCSGsGgigxvLvCZJR53yDz6TnRakFdxDou95Wvj0cYxKVKxzAcBiBl9seWPTH0V05Fes97k3tqOqxQNjqPoS0OJOfY98EprIuM0DaJPQOqleHIwXLHp8PHD0FZ0k1SRXseWHhtgWMCkSxesyqVZEk8+pimDGUNwk75jY6iUKynYvNka6320cS9XXB1KAfpqIL9IJCPWobewswpwXzW4KfB8RJxq+2CoE4t7Yk8Ej1ZMv7qica/XYJK4jD5RlpPpe09Z9TqqfS6rZxRrS9RiFZ9yZo3foJKnmgbQEi5VvzNq1aUk1f/fAAw8EgklEU44QVR5bTKRax8L5QsAgnErYaxp1RH+Z8NldgQgg9WC3ZdwkU2eiYlVIe2PbxDOa9ca2mlj3xh4Wqa76PPmcdB6ALCPVZBnJ+Gn7Xt0RUyfVz0K+5U3Y6TkcbaGTpHoUae0bqa5a7hF7pFpV2AAFJDjfNiekqokq0iV2G/i8FVdcMZDqqo8jFmu2dOIZfdj6YiPh0vukxY5NE9sG+k6qNdbUdZ7S99NI3kY6lreDwi6LSHYdybYa851ULx6p7nsfdwwXvZi99PAyeMao1ZqUVDPwU6K6zmI2sWiqIV3YZxGRF5gQ256Mqlp08PdU6yJSy6IIp5q80vHTRqpjhPXGFtGRJhaCbTWx8saGaCMbifm8qkQsi6GmzrOpZ5tFGjub2t1kB8XqsZVsSz+z1n1V9L0hR6qzzhlS3YaML1Y0U/zF0SQ6SarTA50iW20Tw6qIKwMx5BKSaQuA1IEY5B8QLKK3LCLYwsVvHD1kDNHzKiLVlAhnt4GJnKgYcpZJdxtiln/U7Y3dhfOaBi7/aAbsjNjqoulkW9qPfvSj0PfSMqUq7eX6ClvtOA3JP/rexx3DRSdJdVtlwJsgrgw6EDB0twzkyB/q9GFtW/5hi9eQdERBF1VVi4lUT3ostvojyXyUHJ8kalVmEuoi+Szqjc3rDz/8cC+9sdsmm00hpuhtVrKtPLHpe1QyVTVTWffJYpIE6i6da9uRai1geM4dXvylr+gsqVYp67T8I+YKkONIP5FaIracB1IPWt2DcZsLEitvef3rXx9cXVR6PhZSPY1Ptao/Ary1sYCcFF2Xf0zrjQ3BwZudPuHe2N1GzIsHa91H36PKaZZ1H0CmpEh2nqPNkEl1esHLvEZwwT2qHX1GZ0l1l+Qf1vZvnN62afu4NiLV9nyz5C1NFFwpikkkFVa+wy4D+ulpqz92wf2jLtBHSFqlz0BksJOUFltRxT54Y8dMNqtEl4gm4zFyNJqs+0SyZd0nRxt2TkSytcDr0rnWTaq9RHkKixoq/tKv6SB69IJUxx6pHkWqkXvgVww5YECmOmKTZXebTlQkUsH5MiHl+TO3LUmZhqiin0bugS6TyZXzq4LcddH9ow702Rt7KKS6q+dprfvYdeI8INUi2Na6Tws89bk+yZQmJdUqUe6Weo4+oxfyj65Gqn/+858H+QOLARwRiMA1PfE3majIpIN+mu18Sg8j+cg635hINbARp1FgYuX8INZIWZZbbrnK7ueQ5B9NeGPHqOvs82LIgmcp9gVOEcgtJG3dJ4KtxR2gcqoSlWl9Jtl5yZkqUe6k+lm4+0f/0FlS3aVERR0j+jwNOgyyOFywvbjKKqvMuCA0jSYILGSBc+Wc+T6i8WTet3lMZcDxjCM8aHzRTzPRjju/aVCkouJQyFkRb2xFErvkjd33xVGslW+rtu5jcf3II4+E4AmEu07rvpigHWOXfziGiHhmkimgCTFm+QfEDJKIJo9oJnIP5A8QsLaqBeq46lyQsJAg+ZKJhQgF+uJxg2pspNruiqTBMUKmSUrkPnJ+6H6rRlGd+ahjHRrSkUT6IpFEFaBJe2OLZLdFcroqiygLnpm+nyPANpOxjrGPcR6SKakILcu6j58x7qJUGal2Ui0wVjfxHPT/WYsJnSXVdlDuUqT65ptvDj/bkns0SWCpoIe+GC0diWbY5RWJCMbk/mEXRGkgNeD8WCBByJg4606Oc8I8OdgVkje2ks4UwYbgcB8hObxPJIf7WmUF01EYCqnmPNse99ogmDYXwNpGQrCtdR+7KIpiF7XuiwnMw9zfdD9WpNrlH44+o7OkukuJiopQS0uI2wXZ5DGgLk21LceNNzMa6qJkISb3j7zor9WHL7300mGBVCcZKvrZHqkun3Q2zhsbEiCS0zdv7DbQV/lHGc9maxsJZN0nPTbjJ62LCbecc16JcuCR6mfRhE+1o1n0glTHnKhINBPypczn2bNnR7VSr1r+Ye3kiPDhfqGJo+wxxZioaMupc5ycH1H4Jo5B3z/ufU6qq/PGTpey5n0Qa5GcKr2xhxKp7kuiYpUVFa11H9AuiiLZSrits/9VBSfVjiGjF6RaW02xkWq28+66664QhWAgQVMWm3dulQTW6sUZ8JFDTLJ1HmuiIv3r3nvvDREkIpzop4kiNQG31GvHG5vG9eTZtSSHn4D+bb2xp9mqHwqpHlKkelKfavIzsO2TdR9Suqz+Rz+1rjZNSZUmIdUKLDmpdvQZnSXV6UGZaHUs8g8GUrK+lYQC+WIQZGJmwIlJI1eV/ANXBfynq9CLx0aqtWC79dZbg5sEmlzKxzd5H8tEqh3VgmvK4omGjEne2Ep4fPrpp0MDvEcJjyQ/lnkGhrIYGqKmeprzVSItDatO680OwSYRkgZY7FupUhuuNhxfFrl3S73FwdPexCM/jFElHnSWVJepWNgkbHETBkHkAQx0DIIghmO0UFnwSQksEySLh4cffnhmAfGSl7xkqmOKjVRzz7ivAGnAMsss0zh5zSPV6aifyz/a88aGZPPcYx9Js97YvLeoy0/fF0Y810PRpddRUTHd/7Dus6XUcSKiiYxb674mFjMu/3AMGb0h1TFEqonWIvfIKm7SZJGVsuAYJyH7RKU5X2QuDNgsIKqIQsTityx/bRHqGBJMXf7RLW9sxgR5Y0OqratDOoo4FPnHUCz17LnWeb5Eha1UCZmF+p9cbX784x+H/mb12PTHOo7LSXVxePGX/qGzpDo9GPAQs2JvAwxkyD0effTRMHBlJa/F7FDCsZUl+wzU6KfRUUMmVlxxxcqiTzFEqpkYcC9hW5/j4b62Sag1Mbv8o3ve2DaKaL2x0wVAhrIYGpL8I49g1gX6FYEN2qte9aowhuYVQLL5ACzyqsj34fu4v6M01U3loTgcbaCzpDoW+QdEHrkHA5aVe2QdX8yR6jLHxdYiBU8YPCHTWJJVSebaJtUM/vhPkxyElIVItaLVbSNdUTFNxFz+EResq4O8saXFtgVAeJ/GCHa62iwIVTeGlqjY5gJCbiE0rD8J6thFXjofQHIlFnyTLAbyLASBF39JYVFDkWqfDhpFb0h1G/IPJkcINZMghv7IPfIGopgL1BSVf/Ce+++/P5BqtrzRTzP41nE8bZFqm3BJsiUT0e233x7FYihNRPLIs5Pq+L2xFUVkx0ckW6TjlltuCZFGJTxOSnBiRdtEc8jnyjypAkiARZ5INj+xC6VxzHYnBSJcZCGkeSQrQRL5B9HwmBL1HY6q0Sv5B2SiiUGM70HqgeSD78U67mUve9nIv4mZVBeJ8hO9Re7BVuKSSy4Z3C/qsgecNnly0nuK7vChhx4KE8Iqq6wyM/HEEv11+Ue/kC4AwmIOgo10DJJjCY60sBBtSHmX77NHquMBOyI05QNY60gWfBBt5jpbZZRGUKVspJo5JEZf7TbR/qziqBqdJdVpWM1ynV7QyD1IzmPyK5OcFzOpZgAkMpsHKstxzlzbptwvykpSpgHndffddwdbKiIyRODtPe0aqY7hWB3lISKywgor5Hpjs5Cv0hu7aXBeQ9JUd8npJMs6Mq/KqKz7tChMF2BLnzP3nEh1U3Z6RODnzp2bnHvuuWFhyrFusskmyZw5c4L3d1mQsH700UcnV1xxRahTwDViJ3ObbbZJDjjggFrOwdFN9IZUN1FVkYGFaBLEmu1bym8XHTCrrlzYhPzDJmAycdvobd1oihwy0KOfhsAQIXzjG9/4nK3LJgn+KDip7jdsBDeL4ORpYa1tWllv7KYxFIcTIba6BGXA3KZ+BVRlVP0wbd0Huda55rl/NBGpJv9lvfXWSxYuXBh2kLfccstAik899dTkkksuCa8j6yuK7373u8m2224biDoOUKuvvnoIqhGI+epXvzoVqXb3j/6hV/IPUIeu2nox8z1IH9guK4OYExWz3D8YQLUdPSoBsy40QWRtBB49PIUVsgZ8EdW2t62dMPcbo/oXzyiyK1pWGWtkWfLGtlHs2BIe9UwPhVTHLv+Ypsoocg6rxyaqLdgFHwtD7jeketoaBkVw5JFHBuI8e/bs5Morr5xJjDz22GOT/fbbL9lll12S6667rtBnPfDAAyEazTlcddVVyRprrLHYvf3+979f23k4uonOkuqmItWQS4gXCWw8nJDLSbKXY7bUSxNYHAnQT7Pix9lj+eWXb3wLs05SbTXxRFZmzZo1Q1bG+WbHTqqdeHcXZfqXLWPNc4JTjRIe8Y2n6X3SYrdVYc9CfbMvRLNP8o9JrfuYI2TdR+SaYAU7fwShiAzPnz8/edvb3hb6Jju8dY6hzNfz5s0L/z7hhBMWm6v33Xff5PTTT08WLFiQ3HnnnWHndRz4G+bBb3/724sRavVh5o6p4EN179Dpkc0+nHVolll933TTTYFQM3Cw8p3UDijmSDWDA5Md1w79GeW4GZyQQtDamBTqItVox5F7QKiJPnBPRxFqHQuIgaza7fNRUXXHcCCnBra0meTXWmut8Nyym8YzhC82gYEbbrghRNaIaEPC2+gnQ5J/NJU4HwNsMi3AanWllVYKUW0WdpdeemnYXSGCTGAKyQT6ZHlXVwXmayLm5P6QG5MGMg5w8cUXj/2sn/zkJ+EYea423XTTSo+zq+AeHnbYYclyyy03U/SKyD9jzCR47LHHkr//+78Pnv7kijAXMyd/7nOfS7qK3kWqq4gEywmClTaDBYPDJMkNXUlU1LGhEfvZz34WZB4MfGzdtYU6SDXREwg125Bo7YouGGKp8FiUMLd9nI7JUNVOSNob21bYS3tjW6kIk1oXy3bHiqFF5e39RSqCxvrAAw8MjboGaJGJVJPo9/nPfz40+txWW20VEgqrAJJFgPY5C3qdReY4IBHhfIhQwyu+853vBNLOHM7cscMOO8w49wwBXdKqt4nekOqqSCsRWm4q26fTyD3qOr46oGOCUJOIiGa87eQayEWV1wpnDwZSBkkSTEn+Kkpg9L62dxmKHO8QIoB9RR3yoqwKe5BqkWyeCxpgnBPBrssbe0iR6iEtIAQFtdJ9RxWG119//eTkk08OcywaZVqVjiDstAJ2lrOg1x9//PGxn8VCQM8Fuz+QRouDDz44Of/885N11113EImKrlUfAKm2kbsqNMtEcVjpsiJjWwNrq6o0iLG6f0CkNamyBcO2TgwTniQp08I6mBA9YUWMvrTsseiz2oRNmCTSyATCwMb50NhmdflHd9HEfaMvW0cHnIxEsNPe2NaXuCpv7CERTZ1rHzXVZc+Z3UEAgebeU9uBtv/++1f6/SqglJdULwKP/KkIHwBf//rXwzh79tlnB1s+Am5Y85155pnJ1ltvndx7771T72THjs5p1VtEp0l1VYmKTGZsY1D4g4mDrZ28le6koKNUHX2ddvBD3oLMRQS26nLjbcs/0E+zSEITj5QFjd0kbggxyT+4JpwTiyEWCcq+516icaN/SR8/pMm8L2j6+WP7na1cmvXGVtIjP/U+JTxa67SyGFKkelQhlL4iz6daZLcpn+oqoPmHQB1yhO233z78n/5/xhlnJA8++GCotnviiScmRx11VOnP50loYkpZ1JBWnZ3giy++eCyp7rtWvTekelJ5hZV78MAj92BLoq5jjIFUE53C3QNCxjYvgwSLirblDVWSaiIR6KfRkxJFYNdhUpIZi/wDQsLqXtZU2ACq1LUIkIr4XH/99SFxSKWuvZJZ/IjBXcZ6Y0MmrFQkyxub/sX7ixLHIVnqDSkqP45UK1JdhZRyFPT5eQmQOo4ic7w+i5/bbbfdc37/wQ9+MJBqIrR9h2vVB0Kqs9w/ysg/rHVc1XKPWEk1RJpzhli/+tWvDvpiCDVo+9iqItVM/Pfcc0/4e+7ptDZOMcg/IDUkdHAMVLREqkNf59jQwdP43R133BEmDgg1/VtbmEQaJROxFdAc8aDtnZA06CNFvLF5n5WKjNoNGlLynpPqZyGSWzepZk4DWPtlQa+zaBwHvYfPzJo/qGsAVGWyPJDqNbG4XCLIH3FkyQLylb5p1dvEIOUfDOzcfLZveFjobE1IH7KKrDQFe84M8raAjQb9tiOx05JqzhEJD5IWSCS7DlWseNuWf7BdxkDE9yP5gFRnXRuOkz7GtePceRYg1kSwaWTd03gfOxSKNDK4DSFy2AXEfB+KemOrhDUt7Y3tkep+gzEny+6zKfkHOm2Ql+im15n/xkEyBwUm0qDfN7FQiAGuVR8wqR4XqWZ7nCgmyXl0EB6cuuQesUSquSacMzrcLIlLjB7aZQuu2AqQTOScIxrjqo+lSXA/yJImSgChySsnP2r3RtFpIGs1rpG1VoOoi2Dzs23nl6GibfnHJN7Y8sdmXKVPiWTbEtZ2ATckojlUTTXjTh6prpuArrnmmqG/EZllR5Z5wIIIKNhiiy3GfhbyBPos8ybBKOR2FpJ9ZGmMi4uqG3jeFyVBC10kIt0HrXrb6PTTbh9crY5HkQ60pzfffHMg1Fj88NA0RajbItUMZrfccksYGNDhYoeTPucYnUnKRM/ZhuYcmdCReqy22mqVEeqyx1IVWCQwsECoISTcNxaO01RUZBHJjgzRHLbdmHC4XpBo+geDLgVCyOAm2s91jU2S0Gd0iVTneWNTfZVxlQp6yy67bOi79CMWb/RnTey8hgStzxjSAkLIS5BuSlNNgGD33XcP/95tt91mvlfWb2h+11lnncWS6XC1QAZ50EEHLfZZjLe4VPBc8ln0WeHqq69OTjvttPC8fuxjH0v6jqa16qCrWvXeRKq19Z1FDHkoICdE/XhfFTrbLpBqqy0e5c0cY6TaEtlRCYbIGThH7jEyHu5r1Wg6Us3gzTYlWn/uGRESuccUQZHj5JpaazXpZRXFZgEKsVaBEEWxmbQcjjLe2Ix5SqZFf0qESkmP1hubHaY+EdAhWurlkeqmNNXgkEMOCaSXABoLOwIISB+pFEzuySmnnLLY+3GHIjqqJFwLCpBce+214fOwm6VACe9HB8y5EkkliDMpuhKz6JZWvV30hlRrZZmWf6TlHm1WCiyyfV/VYM4gwUCCtpjIpMhT3nHp72LBuGNKnyNbcEzKdaBJ9w8ixrjR8F1pa8d0FDorKj3pQjGtl4UEaSvfFgghEiFJCc9RVyOrMaLLkeqiCzj6DOMx/Yyxuglv7LYw1Eh1VhJ0k5Z67FJChOfOnRv0uvPnzw/9aeeddw6a3TJ2uQQVLrvssuSLX/xi8o1vfCNYwRFYINq9zz77JJtvvnkyBLhWfSCkOj3gpiPBEAN0tqySkXtAUtp0PeD4mDgZbOsaaIluoiVDL8sExSJiXPnhGOUfo4istQQseo7ToAn3j3SRGszv00mWRQq7VFH8ReRG38/1FsGm4fgg1wcbxW6izHWfwX3rOwHT80x/kWMNhMv2r6q9sdvCUEl11jjQlPzDBgmOOOKI0Mbh8MMPDy0P9DuVW68cHYlUd0qr3jI6TaqzSCtaVAZqHBPuv//+8Do6v7ythqaPD9RFqpmMWERwDdhCYbuqyPfELv+wYKGE/zSLB1kC1j1p1S3/IGJHdJpo8KgiNUUJc9XHySSJUwyN+4E8ReSHLTpt06m6o8pcD4lMVIEh6NfTxV+sNzZjlvXGpn9V4Y3dFoZKqkfJP5rMYXJUr1VH7oK+nDLl2nUYpVWfN29ecPJg1yCtVcc6j8/Cp1rqgT5o1XtFqrlZPLyqOAcxYUXFBB9bgZoqI+ZMVOhfsZPjOzhnIvNFEbP8wxINdFvyuFxppZUas9upU/5Bf2XrjGgdVe3YTcnTYBaNVNcpJeC+ILOh4frAAs5W4EOOQ7Nb/pCgKhNH+4y2F/51Y5yl3ihvbNok3thtYWiaau3CjkpU7FJFRUd3tept4nl9e6iJdMjpAoIS05bhpFUfRwHNOFFOooVEColylh24YpR/WKJvreUgZ5xjkwuluuQfEFG20riHDCwUdBlFqsqQ6iYjGCzgaBybvItp1ruYPqkodt8S0qpCXzXV0xR/SWv9tUsyyhsbsh0DkR2apV5e4ZcmLfW6hmaKv1QD16oPgFTbqBxRTAnf0eiwlRjbBFU1qWaCgZQR7STKifvFJBHwmOUfyDyITrMlzANMFL5pB4qq5R/WjYZrT4lX7MiK/m3R9zXd//k+tvFoLBBYLNgothLSOGdFGSHaMUYZ28CQSPUk55neJVH/UrPe2LxHJLut4kZDk3+MiswTqYaUeSXXbqMzWvUW0fkeTmQa71O2GJSo2ER1xLZJ9U9/+tNw3kxS01oExij/0LkQhWfyLKMRr+tYqrg+fAaLBCZ/omsQ6qLRm6z7m+f+EYM+l0GTHSOaTUhTY7vPRhkh2JChGKKMjviJZrp/EVzQAo5FOEEWJf6yiGvaFnJopFrOW3maanarYpyXW0X7w7SjYnSaVDNJo+dhFUykj8ESssLDHZPso0qZBX9LAibnycqfyO20VnIxyj9ISNQx2ZLqbaAq+QcuGiRZMuGjGcWmqEw/lfxj1HHEOmmlE9LyKvApGinbPiIjsZ5T1fBIdTXe2CQwW29s+pi1hZQ3Nv2rzoTaoZHqvEg195w52vXUjiGg06QaEs2DLLkHlmSxkcMqI9Ws9pF7IPtgQoCUVRF1iUn+oUiukhuITrdJqKuK/lrXEvoqfbYssSjz/hgi1UUq8NE06YpgQ7b5+fDDD4eFowh27Oc0LYZAqpsimjZRdplllgkLWisVsVIkKxWp0hvbNdXPQqS67/27z5pqxwBINVZfZKBq0KojEbBKTENeScjBtoYI3+te97owUVQ1QMUi/4BwQjwhoEST2ImIQW87rfxDVR+ndS0pQu5jkn8UBcfM/aZRbYudJhFriDZSJxpgQQkZgmR3vTjIEFFXpLrIXEHeCU0JtZZkyxubRZxNeJxmx3NokepxpLoptyaHo010mlTbgipASRDpqoqxYBLSz7mhCyQKz/mVSWorCiY4WpuLESY2ovBYtJGEhEwAa8S2if408g/ej80hdodVVH0sYpfXB5JJP8eiScVB2KFR5Jpnm2eBxjVVFBsC1PUkqCFFqts8T5tQK29sLeJoLIJpep+tBlnmuDlX3u+k+o+7rG0ljEYLppMmYh/dia9Uig9+8IPB6xq7vibR7Vkoha5EqoseHwST6DQJXQzo6KeJztV1bG0QWOuEweQjj20VFImBVE8S/WVHgXvHDgO6TQj1tF7NZUh1lyLVRbWyP/rRj8JzgGZWyY6WAHGdpZXt4gQ+BFJd1lKv6UWc9camf0G22TljYSxvbCU8jnue66ycGyPySDXXgUh1XXOXw5GF008/Pdj1YeTwkY98JNlpp52eU6W4DvSSVPchUm01uGyb0THqdEVg8G+awHIdcDCBFDHgQjxVcavOgit1y2OYQCjowk/04FgdVnHvyhDmvpDqrGug6DRQFFsEiCRQyDe5BiI/tBgTl4dMqmM+zzxv7LT3+jjXGifVzwaHmJPdozoL8T4HXceZZ56ZnHTSSaHsOd7Xn/zkJ5P/83/+TyDYa6+9dm3f23lSbQtiaPu3y5FqeW6TrMe5UcCmjKn6pGDwb/K6EQ1i0cCERYQIhw9LfGLReZcls0y4yFaYRCihjka4agLRRfePugCxofGMyPFBUWxb4tpGsVm4De06xYKu6Yyn8cZ2Ur14iXJ3/3A0ife85z2hIZ+FXBO5Puuss0LhGgwQPvzhDycf+MAHZqq3VoXOk+ouRarHWdfZyG3TJdabjFTbSoJ5SZddI9X8jvLJlGVlcTdr1qzKH9YiRLBv8o9JHR8oo5u3jc/iTQS7Sd/icfBIdfxIe2OzGyWCnfbGFqkmUhtLH2uDVKuaopPqDAxvmG4ccIyjjz46OfLII5OLLroo+frXv55ceeWVoVT6wQcfnGy11VYher3++utX8n29ItVdjlQzOEM0yUoncotLRJMDsQrn1AkRT5L3mGxGJV3WVRp8EoyTotjFEBMH51XHBOLyj+m28RXFhgBZ32Ii15KUlE1GqwpdJ5t9jVQXda2RNzbEWiSbMR3ceOONoY9pwVenN3bMpNrlH462+eE222wT2k9+8pPkmGOOSU444YTkW9/6VmhUAd5tt91CcuM0+v/Ok2o7CXUlUTFNzkjKI6mNCDsRNrYZm55cFVGpC9wTbOXYjodwop8eNcjGFKkeRfCtDSCLIbzD63KhKGOp53juPSRJRYkq+BaLYNNY7NG4dzaKjcNIExjKIqjPiwfGd6v3h0zT71ioEcF+/PHHQ5M3tvpYXwoc5ZFqLS6cVDtiwDXXXBPkIPPnzw//5/kjEHbLLbck+++/f/KlL30pueSSS4L0dpCk2qJrlnoQRqzBSKxiW7EOyUAM8g80dRBPovBEptFPjyOeMZHqvEg1USnOC4LGQogFUZ2TY199qtsAZJkkUlo6GY1FrtxnIAIiP01EGPtArkZhSDpjnkEcQpici3pj07pqDZlX7EaaaifVGfBhuhGwK3nqqacmJ598cuBbPI8YCBCVfv/73x8WvuRGzJ07N/nHf/zHZM899wzkexJ08+nNQeyRagYb+UFDxEhoY3BlskY/3Wahk7os9bAD5DzRT5eJwsfk/pFFVClGQuSd3xGdpqhEG8eRByfVkyejsWNjo9g2wmij2NNaJA4lgjs03XjWAqIpb+w24ZpqR2xjzeWXXx6i0pdeemngIARTdtxxx+Tv//7vk7e//e2LvZ9kd+Qg5EUtXLhw4u/tPKm2A864RMAYwICDZODmm28OxPpVr3pVsvzyy7cevak6Uk2HJikM/TSRl1VWWWXGB7bo8cQo/+B4eOggWZAqZCxNJZMOpfhL2yCXIV19T44i1lINkiCCDSGf5hkeyiJIBVGGgFFR+bQ3tqwhaWlvbBvFrnIhVzWYdxU4snD5xwh4mfLawOKV6DNjK2YIH/3oR0NBGMmzRv3dtddeO1xSbcHDzCAUq/xDEydbzQw+05Ssrhocj0jjtASf63/33XeHLRcGUohn2ShFjImKTBp33nlnIFdoc9ldaEpza49jVFTT5R/VwkYYSWSRpZpINoWLaCyW6ROKZE+669R3wkm/bDuA0AQYR8ucq7WGlBxJuyVWjsR77EKuztoFZcH4mFeiHDipdjQJdn623nrrEJXeYIMNCv/dgQceGArFTIpekWrAQx0jqeaYkAvwk4lz9uzZM4VOYkuinGbSYwBFZ8yWH5UR0RNOohGMMVLNIoGJg4mPYjxtkQOXf8RjqUY/F8GmIXcqUhgkDZd/9AsatyYhvVaOhB0YciSi1yLZOBfQeB+7ZCLZBC7avLZOqsvDh+n6wDMCBykLPKxpgyXV6UGkCWu4smDixS6Pnxwf28sxEeqqSKx1MXn9618ftlEmHeRjItUiSvQryDSSnTYmrzJadEf94FrzHNPo60SxLflRYRA5j9godvo+DYVUDyVRsUrrQOaLcd7Yep+VijTtjc05Z5Fq11Q72sCnPvWpoJveZZddRr7vtNNOS66//vrklFNOqeR7O0+q0yAqyuQWC372s58FKQSEDKKJpVyd1nWTYho9OgM9BQ9wMqnKxSSGREXOi0zhhx9+OPwfYoQfbVtw94+4Qd/H3YYm8qMItiQj9CV0sbJeo0/FtIVfN4YWqa56ATHOG5v5hgaa9sYmmJKl+fZI9Qj4MF0bIMtgHKm+6aabQrVFJ9U5YIKiklrbsAltRAzwQWQSJckphuMr6qE9DixgWDQQpWYQRz89jXG6nTxobZFqJivOiwmKyYBoiy2j3gacVHcHlvxQqt66PUCucY+hqbx1U8mubSMvmtk3NFXkJu2NTRK8te2zzjXaLanLGzvv3spSL7bdWYcDEOSsckzqPKlODwxEqtuWfzCwYSPHJMqESUKbVvAxylMmlVtANNFPE4nAKQH9dJWds8nS6RYsejgvkoXYciWhFM/KtomqE+buwro9cP/k9gDBtlv4LOL4vaLYXfUszoNHqusF84z8161zjfqapGzaLYFgV9HP+K5xmmqXf2Q4fzTh/uEOIyP77fe///1SzmTj0K8R2/gtt6XdY/BCP83qhwgVkg97HDq+2CaXsh7fJO2hn+Zc3vCGN4Rzrfp85EjSJCA3EGruHzY8JAopat42mfVIdT/APYJg0NDn88zxPD3wwAPhd9az2CaiEfWOacyYBEOx1MvzbG7TuWbUbom8selrRJTL3iPGG5qTakebWG+99Rb7Pz7V6dcEngdkqwQypnH76D2p1opbnplNgQGFMsf4MvO9RKezMk+tdjmmKFTRSDXniXaazmhlLXUdU5ORarKF77vvvsz711bU3MJJdT+hrXmgKKOIDySISLaeNxFsWttypEkwJEs9ENO51umNPWoRwfcgCRyC7KcslvBhulJcd911i82FNscgC4yhm2++efL5z3++smOIh9XVEHFtatJBV4xdHtEmVuPoivOSMuzxxUiqR0WqOU9kLWwhEtngPOusAtkUkeU7iBLiN8z5sFBI6/+6EqkW2j5WRzlY9w/rWczzCNlRwiOJzjRAFHua6GIbiG2Hbkikepw3Nv1MJNt6YzOniWDn2UOOItXIBNu2+3MMAz/+8Y9nxhmq42677bbJ5z73ucz3EqTAUKFqnhgPq6vQUg805VWNZg25AKvxIr7MsZZSHxeptudJwRqs5eqOPDSRqIjMA7kOEwmTBhHqLCuqNpMm0ygSqXZ0C3mWeiqNTlt22WWD3t9GsRVdZGKwJdSbtlMrCrfUixOyfaTJG9smPI7zxs4j1XLBgbzXPTbxbMydOzc599xzQ4CE49tkk02SOXPmTFVkDceelVdeOeRKrb/++snVV19d6XE7qgMyVOHTn/50CPzZ15pA50l1Oopo5R91A93jvffeGwZQSo1jcTRu4JjUZaNujDouImNE4vldkz7NdUeqWSiQpMBgzL1DG543CXYlUu3yj36DnRQIAk3RRSWisVNGA0Su5QrBrlIsi62hRKo1/3SFVKfBoowgEc16Y9PX6HNpb2ztWOZpquu204Pwop1duHBhSJrfcsstgxzz1FNPTS655JLwOpHLSUB569///vdJLfBhujZAqttAL0h105FqKxegTDXRTWkiix5frJFqe1wMpmjEiYSVPc+qjqmu+yj/cO7liiuuGBYK446lbaJahoy0fayOcpik+IuNLgImfslEID2QCpo0soou8iy3ASWzdZVo9jlSPa03tkCxI8ZsSDb9DdLN7ua0dQvG4cgjjwzEmUrFV1555QyJP/bYY5P99tsveBVbvW1RnHzyyeHvINZf+9rXajhyR9/QO1Jdd6SaqCZyAVbrTFBvetObSk1SsZNqTQZs/6GfZoJO2wI2eUxVk0NbqIYBn0I1RRYKMUaqs45pCFHAPqKKioqMQ0p05DnGElJRbKuRhXDYKHZTxG8oVSOnLVMeO7K8sQkwQajJu8EX++KLL07OPvvsML6ywJumuu44MFfNmzcv/PuEE05YLCq+7777hsIeCxYsSO68885klVVWKfy57PoccMAByYYbbpjsuOOO9ZBqt7urDIxjNMwGKDNe5tmjb1YVwOsFqbbkok7SSoIeRJOBA4siNI5lJ6RYSbWVfzAZo59mAUEEF2lLGxGXquUfPDREpxksyyZacixt3zNLqplI7r///vCTKFC6/HXbCwBHOVR9v+ivLIZp0siKYKeLgtgodp0LZz3LQyLVfYhUjwN9Bp01pJq5gv9T+Ix+R7U6rgVRZCxKN9poo2TjjTdO1l133TAGVwG+gyAX38eYngbJati/QvTLkOq99torzIEnnnhiODdH3Hj1n+S3SjxsSqbaS1Jdt/zDlqsmEs6DS1GQpsuB1wkdF9t6SD445yKyiK6QarYg0U+TiY5OkIIuZVeybRNVDRAM9ExaqlQGSQIkDYkUxabZdxRDXZMAuzJoTWn0YxbO0shS5ZWmPiSCDSGvkhTq+RkC0RwSqQY2URGC/fGPfzw0Itgk70N4ec8//uM/hsY8+u53vzs544wzpv5uAl0A16Ys6HWIdVFcdtllyXnnnZccccQRYTFQG6n22EdlQOo26v9NoXekumr5B1FpHkYmHZJ/kEFMY2LfZCLlJEAfxzYyCwcm1TZRleMGxAHJDveS3QUSVsqSl5hItRY9JFZCfiBI7KJAklRogSg22/3apm1LR+uITxqhojI0dtx4LkSwaRAhmi1trZ2QaTBE+ccQSbWF+sw73vGO5KSTTgqyuyuuuCLonlngVQH6KsAaMAt6nZ2ZImAM3XXXXUPhtk984hOVHKNjOOgdqa5SXsGWEmSMyCA6RSK302rkYoxUk+CEDglAvtZYY40oSJg01ZM6BvB3DLgklfJZRCxe/OIXT3wsbUd/VWKYa8G5QIogRJwTTeeLZpz7ZyOQsbpBONonnGyXsvNG4zjYzRHBtqWtsUWzUeyyY+GQiOaQznUUqaYvAVnvEdSg7b777pV9t76D/pkFBcFweyqCQw45JBDwa6+9tn5rSo9UtwbGNcaxquuF9IJU24lIF2ha+QfbPRBNySBY7VYx4cVmqcfCAf00ySaAiTUGQm0npElINdeX+8d9ZLCFhE5j69RmpFpuM9qCZCsVckMft9ZdNE0sRCAhP0QgFcWWG4T1NKZ1sTJf39D2Lojt5yzAaCSXsWgj0Ux6bOtXbKPYeYRmqJHqGMqUx0Sq67bUqwp33HFH8uUvfzl5//vfH6Lrju7ijjvuCDIeNPVYAQsXXHBBkCYRcKJfIvFBP18VekGqq4xU83dsnUNg0KcigyAiGMvxVQktHAAJJpx3LGQ/7UhSJuJD5J2FAvpwJnwkO9MSx7ZINaSG3RJIDUSHaAvRE64JfUgSGf1b/YrXrNesdYOgWU9jFXOgMcgMgfTEitiuPc+N3Qlha1x9SJIRck3Y5hfBhmxnkckhRW+HdK6jSLXyPuok1fpsfVcaksSlq+SmQZDiIx/5SIheVlm2OhdMJ01MKXGs1xvH8ccfH3Txu+2228xr2AOj5WdeRX7EHIhDDC5uVS2iekuqJ4lU81BCYCAfOCpQRanq7Z8YSLX12dbCgYEpZlI9SeSdSBvWOlVMbG3IP5gMsIGiX5Iw+qIXvSgkW9J3rGWXJDI0TSy8h4EDkqYotnWDsJ7GkCOuG8m49HcRbEhS1Vtjju5Gca1fMVXKGGOJYotc//SnPw2N99HP1I9UTa8L51gVnFQvTmjrJNW4PoC8ZEK9Pq6yHu9j/icIsd122y32OwI0gPFY5GsS32tHc8BxBm4j60dwyimnhHmRRRNkmvu5+uqrJ1/60pecVFvYQXpS0kpSFwmJTBSQDjJ+6xj82ybVNopry3JrwusyqabyI5Z5AHePaUrTth2ptsmVqtYpbSs/WQzZiCD9CS01WkDuJ6RGRNtO8JwHLe1pTH8QyeY60vLIkaO/8o8yYMHFQo+mBZ0WafQnCDeJafQ1m+g4hD40JPvAoprqukCUERBwyIJeJ0hWNFnfFrSxoF/jeV0Z3Ke6NhCFht9YXHXVVaEvStOPxeJaa6014yBTBXpBqi0YxHiwi0aqmQwY+CEkbHVykZkk6kKbiYpMchA1iHU6iiuyFYMsRdCENI5Ucw/ZgibSWpdziUh1E2WW2UFg14B+TH9k14TvhZTYBERIjSLKEG051DB58D5FtLMWTIpg6yefQSOJiMRcW5lP5AgiL4Kdt8XvmA5dJWEcN5MVTVX3bBT7qaeemnkv/+b99Le+yo0kWevjueWdr8aSpiPVa665ZpCwMYczv6WJ1Pnnnx9+brHFFiM/hzkxb3FLVBpv7fXXXz+5+uqrKzx6R11gDLI8kAUeCyzK2VsFAoElotpVoXekGkA2ipBDWzUQRwQexiIJN9MeG2iavJJchH6agQ/SRUdKA5LUtUg1Dw33EELJwAqhrqOAxTRJk0XBeeI/TbQZAg2hhqTwOo1FHxMIgwMkmma10fQtCLjKBNukWEuw1WwflEQE8Lck5tJEjkSytcWvRDWR7Gnt1oaOvkkj6Hv0RZWnJorN9jqNRT0EiGblRvSnviTN8twMRfqh881aZItU1xmppg8ReTzqqKOCfha7Pn0fZcrZgV5nnXUWK/xCBUba1ltvncydO7e2Y3O0Bxb3yDuESy+9NMyNG2ywwWLvQ+5bZd5cL0h1eiLi4R5HWtnGYVWL9hbywBZ7E5G3otHXqmBdMCA+kM68SlYx2MblEdksMGCz8uRnVZaHeai7UiEyDxYHEGXIBfcJgiFCzfeK+MpjmOQxpDyQFBaDLBJJxKAx0YjUEBEUWdFnZUWx7Za1omyWHNktfpuoZu3WaFUXDRkCuij/KAP6B32IcQhpHaQnLTcC9GslPLLr0tVFBs/SkHZyxpHqcUmC0wIbPCLIN998c9htY0uf4MStt94adp7R0lowzhLAUL9rC0v0+7FvFexMHHPMMck222wTdhn4N/PSlltuudj7mEPH6e0HR6rTIGIHScmbvIjasr3OgE21pzzT+DogotJEpJoFAx2GJDQmKbRnoxIvYyjFXTRSzaDIooiVJyb9bN3VOQHXSaohqqyomYDoi9j/SIqjqHJ6K5kcgHvuuSdcGxYT0kZzryUFYZtdW+0QXZFjCM0kUWya3eLn2tuiIbJbs6WvvfBMOXSVRBaBnh31Dys3Uj9iV4Q+zMLQWj/ys3bP4ApR1rGo62gzUg3YncRXmqjz2WefncyfPz/0mZ133jmZM2dOo3O8Iw7sv//+yTe/+c3QF2iA5ETGHIFFFzuvO+64Y2Xf20tSzcMt32ULSABRW4gGkRPkHnlR27qPr27yyiQF6SR6SQVBOtK4CbsL8g8mZiIQuJeweKpbAz/qWKq6Tyx8WARSIZEVs40k67stqef80ZBDOohoE9nW+/g3TWRFMhG+B8LC3zEBcc1EVmwU27ZxUWyuv7Vbs0VDbOEZ9JS28MyQyMZQ5R9lHDHYQSOpmKaFoXZCrLyJviOSHXsBoyGS6izpThOaatuP8BymjcPhhx8eWlHgDFHLbpJHqmsDASSkP2jqmYvgCuipLUhIxaP6fe97X2Xf21v5RzpRkYcb8sLED6FAV9yWfq9OUp2uIsjCAYugIogtUp2WynBs9957b1gUEfmgoEvdEZD0sVQ5sLIVzvmo2qNcFCyJtYSa19hh0fmPywFgksGKjyZttEi2LeIBUVEUW9pokWpLsMdFsdNFQ6xMhIUATcmVXYw+1okhkOoi52gXhsBaP9J/0T9SwIh+ZKPYse2GKAdiKGBMyMplaUr+4XBkgcUcuxV5QAqSloNMi16Q6jQYcEUEGMCJdGC1BtHG8YJqc21OXnWRaks6IVtEMcsMZkxoRLZjgY0OWylLG4uiKkk1n4GeD3IAiVW1R0tk5cai7+W+sOqGWEAksAwsc/5Z2mhW7+lS1JB1vQ/JiI1iS46SjmKr8IyNYvN3KjzDe/MKzxBxFMnusoZ2WvRdUz2pd3Pa+lH9iIUaEihajLshQ4xUtyn/cDhiQS9JtR5uomU2cWvVVVddzAi8LdRBXtnqh3Qy6UxKOmOVf7C7gH6YqFVRKUtdxzLt9bFuJXkJiWlrKu2ycI+JOk9b0MbanxFV5phErGk2qkwUUFIRRQNtsqP1wbZRbEuybXIl9y9deIY+q2dUUfOhFp7p86Ji2mh8uoARY6hNmLX9Vs409KM63IDGYUjuHxoD8kg197tuVy2HIw/MLTfccENISmXuyQJ99NBDD02qQC9mrfQgrcmY5C8imwzCbJW3Mbg2Eam2hUKmKVwTq/vHQw89FM6HREtKi7aBKiLVRIdxK2GRQOSNJFmVGbcOH/becW+JUNNf0FxDqqsGz8tLXvKS0DgGSqGLYNtoIBFARbH597hkx6KFZ6ShpanwAu+z5dP7Hukagvyj6oIoLMIYD2jaDRHBtpp++o4IdlPONENy/9BclnVdGfO4/kNZYJSFu3/UBxbdH/7wh5Ozzjpr7NztpHoM5PzBZI1LAWQkpoe6qogwnQQJAaRTulySxiaFNNVNFDgZB45BdkeQvlmzZlXqJdm0FSKyDaLNPOiSII1KSARonpGJ0F/S5VbrAt8PYaYRVeZ4RbAhKxTYoRFdF8HmuIpY9uUVnpGGlsVguvAM1pf4GUPE+QyOJ2+rucsYAqnWOdYxFmsRRuPZkqZfJJs8Exr9xkax6/BXt449QyLVWTtLRKoh1X3u1444cdhhhyVnnnlmWEiTiMi824S2vzekWhE/tv9UvQuZAJHb2KBI9TTklb9HEgHxZNCCdE2bYd1EgZOyns2Ae9gmoS7imT0KWPZwr/gM7pPcMkYlJOLSAQlg0meXpYns+bxoYDqqLJJty5lzf5CJTGvZly48Y8uny2Hk+uuvX6zwjG8tdwNNLhzSmn7rTGNzCOSvrih2FYu1SbTjfYxU67pzjZ1U58DLlNcGrBV5pqv2oR4MqUYXSjIiW8cQASJayiCPDZZwTDKIs6VGR2GbHoKGfroK/ak9rrYmBJUS5RwhaEx+MUxOk8g/eC+7CGi6kB6xk8BK2RLqdEIi/Ri5BxM/A8I4b/EmkbbsI3nURrEhwLLsq6rwjIgz712wYEH4bKLWKoHN90HEeY+SK2PoL2UxhEh1W2STa5p2prFVQq0TDn1briKTLtaGSqrzNNXu/OFoA8gWN95440YJdW9INQSaSko8wOhCGRSxHovJHs5Cg88k29gQGKK4TAwQG7boq5qINQlwXG0kifEQSD9MhUuis5xvDDrvsvIPkWPOCaJHhBpyPCohUcmmqhDJNYh5YobgpqPK6Fi5ZypJLaIikg1RsfKnMlFsrhffSeSe62uJkb7Pbu/TYsmjGIchkOpYzpFFnvVX53lLVwnVYk0Emz5VdKx2Uv0sCI6wW9D2PY8SPA5NaKoHqtteqmEy3StSzSAJcSGJiwspu660V3UssOS1KBj8iXgS+ayr6EldBU7KnBv3Ev00ExkkTb9vG2XkH5Bjou3sJJBERUKikkDzEhI5VyWbsliiH3dpIrJRZQBRsYVnICrow5U0Rt9NW/aNKzwDFOXnGeAz5O2t78uyCNRxIVEZCtGJETGSTZ4xFu80nrn0Yg3pFk1VSa3kKO/5HEUyhxip7nuSsSNO7LLLLslnP/vZEOhpokBcr0g1gxsSCFsGF8QaqVYUuOjxSdrCYoHBn6hnHQOVlX80BasN59yQSGjbtS2SP438wyYkaicBjEpI5NzxF5fDyTTJprFAln0iKhBrkWybNCbZBi1t2WcJNtdVfth8XtqyT8RI2/u2fLq+zxYMocUiq4kpijv0c0wv1oi0KoLNwpd++Mgjj4S+qn5EFNvu7MW4eGiDVHMd5P7hcDSNAw44IMzF6667bnL88ceHqphNjD29INWAi5Um1X2IVNtKkGyjEfWsS5rRNIm13trIdihoYs8tRlI96lhIkGWBwHuRKMiiLi8hkd/hbEGUnkmav8F1o2/IKmcumYi17EN7KYJNVFnPMZFC5Fz8H6kJSFv2pQvPpC0CRbDT3ydS33bhmS4Qztgs9eqG9XPHRUpVSbVg43mnpe0fR1nMDYlUM77Tr9tKsu4E2t+E7S1wkwKYV2ywwQYzyctZzyXPMHNxFegVqZ40Etw0ikaEpTFmcfD6178+ROHqnJCajPDbiG6et3ZMpHqU/IPX0GBiNQc5JtoOOR6VkKgIPfeY90KoYyu1XHfSmCz7JNfgp4o1MQBCULh2XCO00ezQsIuRlew4qvCMLAKxWtP3KfqIJSVN3ycniKZLTA+BVNdpqdcEbFVSQBRWBNvaP6rvEBBh16Tv5crzSLWqKTqpdrQBxnULxn52LOtGb0i1ReyR6nHkVRFMthmlMdZAXieaIrEklCF34Psgk6we6/CGbkL+YaU5RKsgfvJUzktIxDWDZFNF6FdcccXB6C/HFfCQZR+RbJx87Pt4jeeASXrSwjP2+2zZa1t4BtjII9/XZ7LbFPq2cGCBR1OirooYaSeEvsS4wIJOsqO2d0TqgJ6z9BjGjhRwy8t8ePGX+tAWb+glqe5KpDrr+IhsQNIYmBmAFZ2LNYGybCd/4IEHZvyXZTE37nhiSFTMItWQYxISIWYsDJCvjEtI5L0kJFIulcgpUfq+TbKTQslgkFgICmDrnb4iLav0rGUt+/IKz9iy19xPW3iGY9DuQ55+tir0jXBmoc9aY8Z0+qL8rhnDGROU+Ehfsjswem9Muv6qI9Ui1R6pdgwJvSTVsScq5h0fg5As1eQa0WQEs85ERbZeIJNslzKZEKEeN6HEKP/QsTBJQqghx0hXVGRIRX2yCDULJSZbwL1tq+R6zIDYKofgFa94xUw1VK475ETJjtaVgf6UtuybpPAMEhO+k8bf2MIzVj9b1AWiDIZAqodwjnaMoD+SR6CiSVk7IjaKzb+7eG3ySDXyGOCkegTajxc5KkZvSLUdjGKXf2RFhNkmRD/NAAyRaMNSrS4SS6IYBJTElTJl42Mi1TZSjVuHyDFuHaraNiohEX0XUVYWEvwNxMzx3H4CodZCxeYQcD1FZMkvYMLOsuyD5IpgE1UuY9mXjmIrmoiLi1wgVORGkXMVuuG4pqnIF8NuTN3oc6R61Hnaokn0a/q33RFh94rxIWZ3mlFwTbUjZlx55ZXJP/7jPya33XZbmC8oWX7yySeH311xxRWh7b///qE2RBXoDam2UDW2WCPVVp7CZMrkjIaaQRRJhLx+m0Yd8g+7WEA7jJd42eOJiVQTYULbWzQhkdfuu+++GctAIvTIGRyLg8FO/aRIFB/yzAKNNsqyz0axVQgmy7JvXBRb+ln6r1wglGCZLnQjUjTJfe5ipLIohhapzls8MHYwgdOsrp8+bN1pGC/UlxhnYl2MjJN/uKZ6BPq/lm4Ve+21VzJv3rwZFxrktTaAwTxz3HHHhXF9n332qeQ7e0mq9YDHHqlGEnHnnXeGiZlBE/10m4SrSvmHTbZksUCxGghOGcSUqChAqLlXEOqshERLqLm/JCQS2YTUpS0DHclzLPPoJxDTaS37RLC5XzTAoIr/cNqyr2wU27pALLfccjNRc1uRr2zhmSEQTq5lrMSwrYh8Wtcvdxr1I+zAaPRxLdgYR2OqFJpnISj5h5cpd7SBb3zjG8GfGqOHr33tayGgle6j1DeBUF988cVOqtNIT0YMQrFGqjWZE02D+KPhXGGFFVp3gKgqMmwdMaZdLHBMbW+No/MlwVITxGqrrTZTajtPPw2xQ0MuyQvkq8+EaRJYn25IAguVaQtFWMs+EkGJTCiiTEtb9km6oa12m+yYdhPJs+zLKnSTLjyjqLlIdto+se0+3gS08Ow7pvGpTrvh2Ci2XSDGVCmU86V/p++tyz/Gw90/6gOSDxarl1566ciKihBryTmrQG9IdRoxyz8UyWIChkyzUophsqlC/kF0Al0s+lg5YkyzWFCSWluwCYmAyU59K49QQ954SHnP8ssvP1OwxPEsuKfYKiKnqdOnW4b/0r3Lso+WttCDYDP4TmPZlxc155lPR81F6G3BnxjGgbogeVTfkWcxVxYqKkPD010LRC3a7ILNRrGb3u0UqU5D8g+vqOhoA9SBWGeddcaWKOf5IgBYFXpNqkWEYgGT7EMPPRQiZYCJlyhmLJhW/sFgD6Fm8FeJ7mkn0TZJNYQLnS8gwQgpSzqKmSbUTHIkzEGuiLyWlbwMAfQPZDHokiGWRAqa2KWRcweN+ykLPZFeCDeR8yot+2zUnK19G8VW4Rn6iiLlsUrWqoCel76jroTM9AIR0qq+pH4sDbMI9jTJs0XB85B1rh6pHgOGj0UNLDIHHA1fogD/wNWpyoVob0h17PIP6WsZ/FgZMYHHpq+dRv4BmUQXy2dAJlkwVHVMTZNqJiz8iamSqORR+hekOs/hg9dYMP3kJz8JkxqRV4/Q5JemZ8JlhwYnj7ail1kWelmWfUQBp7XsA/QlS4rY2hehV1Tv9ttvD5FrSVP6VHhmKPKPJlxOrMwJlxwWqkqepTEO0ZQ8K+lRHUmD9Pesucwt9RxtgsAeu8yjqpqyo45MExOFqhAXq6sQdou+7YGcyRMiAaGASGApd9VVV0VF+ieVfzCBQKZFJiGgVQ6iTZNqlQ/HrYMJi/OBfPHwASKL3E9JBYhqqmAPkxkTGJZ5fS9NPM1zwAITjTm7NG0/m4K10LPJhzTIChFmFk1ENPIs+/Ki2HmWfdraJ0GNZ4g+B/GB3HOt2NGCiNvy6bEtxMvAExXrA/3Qyo5YtIpga3eEIAH9VwSb/ltFFJs+nzXeaaHoiYqONrDddtslBx98cPLJT34y+cIXvpD5noMOOigEON/97ndX9r3dHaFL2Na1ORGxtQBJY6CzlnIxar7LRqqR17DKg3QwSEMmq/ZWhYA0Rao5H1a2PGRMTpIl8P0Qa1a+2F1JGwsRYgHB30GsschCQz0E4lAWXC9JabiulGePGdayj+fUWvbZKCAERY4i9JFJC8+oz9B/GK9ULITvg2zTpLGVFruqwjNNIYYAxxD8uLnGjEs0Jc/aKLZ2YbSwm7aQUZ6mWvIP37EbgQFLM+rG3nvvnZx77rnBMu/mm29Ottxyy/A6Er8vfvGLyQUXXJDceOONIXD2kY98pLLv7Q2pTg8GtgBMG6SagRVtLXZIRDNxwLAFPxjQYiPVZTTVRNIgoOhSGbjZxq9jEmnqOtnzQf9KtBJotwNwnmy1yvaKBRNkS+A1XEIgWZCttt1cYgEElOtCNAtZTNcK33Afuac0RQFl12e1rEo+lGVfmcIz6uPSHdtiIexw2WIhRLJVeMaWT4+9v3GusR9j2+4fdYD5z/bfUYWMbBS7yLyphWIeqeYauC+/ow3Q766++upk5513Tr773e+G4i/ghhtuCA1suOGGyZlnnllpMLA3pDqmUuU2gsvglOVsoAhoF+UfqijIgEqhjjrdLTgmosB1whaowa1EGts8/TQPIOfO/eV1SDiLN0iWjQKp8AiTWUy+sk2Ba8SWMwtLBjgWll2PWtkooLSs1rLPJh9KF01LW/ZZgk3fUVSPZ49Fm41gc+14xmj8XuXTrfZbfsc26hgbhhSpTicwxwKOSRaQ2oWRvEmBApp2RdSfeH/W+YxyOoG885zEsriIDUs0ZKkXXy9sDsy9WOqRz0ZlRcZm+ixjKYQae9yq0StSzUOvKJCVfzQJtm3RjRLxHFWSO0b5h2zB8si+SBJJfFnR9zpQp6aa80G3ilYW0oNJPOczilCrAiYPJ0SZBZM0g0S3FcVUAho/idLyHhFsEtFinHCrBH0byzwWLEzOXKeulF2expFByYc0zl1WTZJt0OgLIiEswLlOsqDUuCX5iPXEVuEZEZ10+XSRI55ROUCofHoMxGZIlnoxXO8isIWMAP1JBFu7Iqr2a3dFtAuTV01ROzpNLKLZyZk7d27Y6idhnmDGJptsksyZMycESIqA87zssstCEZCFCxeGhSpzHJa373nPe5Jdd93V82Q6jDe96U2hNYFekeo8+UdToFQxJamBIp6jjq/uCOwkyIugcx2J5qIphiBAqJuIvtZFqvlMtO5EZYimoKsiImgjiekKiUwgROiJSHMNeEjTOxC2EAj3V0UbbOERJihNZExSXU4+y4KtJIk2nd2MIWz7W19hkg8hzPKnph/Isk/3n/cRxYfIEPXGgtJKjtTvixSeUbn2LAcI62NMa2vXZEiWel09TxZjNLsrIpJttf1yqBFpzpN/1K37J3i13nrrBSJMDQF0swQ8Tj311OSSSy4Jr+u5GoXPf/7zyVFHHRWOlQDA2972tvDc3nTTTUE2cP755ydXXHFF9TtArqmuDfQLFlcHHnjg2HvPguqaa66p5Hv7NZsbNBmpZhAlGskqmQkLwsmEOQoMQgwIsSGLxDLpozcmm5tkPBIumyJJdZBqyA67CUwYRI4hx1pM2JLjdmLkXiHpUUSxSAVMIhsk5NFUeEQE226zQniU7Bbjtv0kxX/4OfRKkiy4eF5oacs+3X/AYo6+Qh8rYtk3qvCM1c5aH2N9L2ARKYINOWqKAA5N/tF1pHdFiAjbKDbjmcDr+PoTJdaOFGPAuHlwWhx55JGBOM+ePTts78t56thjj03222+/ZJdddkmuu+66sZ/D4gDytdtuuy1WO4Jdnw022CAktPFdn/3sZ2s9H0d14L4TrBgHct8WLFhQ2ff2Vv7RlKbaEjQGlKLb3DHKP7ISA5mIiToSdSUZkU7a5MRYtfsHpPjOO+8MBIZz4ZzAqIIuTB4QaiKwRD0mKWpjC49oglKyGxMSjYebwV0Eu+3yw5NKn9RXYipsFJNlH9F7Fqn0OUgA5IPJW5ZnZS37xhWekfbbFp4hQk6DiNvy6XVKdPpCNod6nvRN6+vO807kGjJNVJpdWlwWkFCsvfbaob8RPa5rvmA8njdvXvj3CSecsJiV67777pucfvrpgSwx3q+yyiojPwtrtSwwVh999NFBAnLOOedUTqq9THn7gAtUuVvcK1JtoYtUp/yD1TpkC2LNxEVUruhgGpOPtoUithwXky4ReK4lg9K4cp91QNeziuuEdIUFAuenBMtR+mmAJhaZiCQ9RKmrmqCwV6TRR2XZBsm2yW7SYUN4Ytb0cW2RxgAi/1UV/+mrtSB9DMkR91WWfZKKpC37RLLpM5MWnknvmrC4lO6fe0cD2tanQcirHJtiG+vqQp5vc58ghxoAqSZZm50ZIrrs2H71q18Nv7vjjjuSHXfcMXnnO9+ZbLzxxpVaaSLNgNgjtWJ3OI1tt902PGuQ/HGkehSkxdXOkqM/+Ld/+7ewEGTxVxV6S6rrjlQz6bEyZ5LAd5ct3rbIYpXguCB5EEmSNYicMvm35dpgvbMnlZxwjSGpRIKZ7BhgmRDGJSSif5YGlh2IurYyIc+2cIOS3SBYTFg0RbpFsmPyKFZp9rqvU9fB84S3OffbSsSsZR8R/qxkV6BdDCUfTlN4BvJMY9dFFpEqFKLCM3y+LTwzDVG0u0B9R18j1VnQ/IrsEWJy2GGHhWIb3/ve95IddtghjFMkENIA/f69731vkGZMCwIkgPkpC3pd/viTgsR8UFVAZTF4pLpSpPXzaOHz5D/wHIJm/Nx9990rO4ZekWpLMupKVGTAhEyTlCibMCanaUh/bAMw2yEQACZwFgxtRl2mJdX8He4KnE+ZhETuMWSWv4EoNuW1mk52415YgsXuiGQCkomwQGijD3H9cE6BVDN58ix0XRNeB7SokxfwqEVqlmWfLTyTZdnHT6KENsm4TOEZFkMQIpq29UWy7aKuiMXaqGug8+s7hkiq7dhMf1pzzTXDv7fYYouQCEaS3+WXXx5+akdrWjDugDxLV73Ojus0+NKXvhR+qniII1489thjM/9mrCGvRJU904DXEAx917veFdxjqkKvSHXdiYoQHDSjTDrTVhC0pDqWrULOiw7IBKgCKG1PgmWrPFoQgeN+QUQhH9wv+sWohET+BkkP1wLSikykTXcOSJj1KOZclOzIpEJTQpFIdhPWdSrnjmyAqCkLj1j6cUygjxHFZ2dLi7q0Y8wopGUbeZZ9LOwlE+HfZQrPpKPYtvAMY56NYstijXOwFmvjnhH7XX3H0Ek1kO86fZ6++/73vz803k8frgIiS3kLeS1ckTpNiq985SuhgAhjHBH4SrGooUj1gKLhzxiewDNI4ZdTTjml0WPoLamuOlLNhKJktSoIZ5vFacaVU+e8lMDXNnSNy5JqBlwSVEgIVMVHJT2KXKT10/yNPMb5G5JUYiIB1lNW7g6SiVhdLBFFEWwmtarPwS48mDBZeAyFRExi2wjxhXiyqJtm4ZHexeA+2F0Mtqlp8hRWZc+0TMQ+A+kodtqyj0WdktNs4Zl0oRBJk/IKz4jM972f6Pr2/TzHkeo8wit7xy6Aqnt77bVX6N8Qs7IST0e7wFaRwEDT6BWptuShqkg1gyTRQBL2GCiJyFWhrYqFVGsLHw0lEyiDIAuIWLTek0SqIZno7bi22P+RDGg1p/pce378DduS/B67vKJFA9oCxy53BxZ5lmDRILySG0iHXUUpayJQLDxYrCBPYNCKoZ/EBhbz9EGepbq8uiHP1rKPe677bz2FRXhpRO+KWPaNKzwD0oVnrDTJFp7h74Yi/7DjyxBQJFJdF/TZ9MMs6BhUnKsMWAwj92Bc/fKXv5xsvfXWUx6to2l84AMfSNpAr0h11aRVVeGIxkgzOskDWtfxTQv0mkz8TMJMfpwfiwcQG6nWpDwK1rGE6BwVEonUjUtIZGteSYwsmvibriFNsCA4imKj/6dx3rZ0dtkiIEQpiVDTb5Zffvlay9N3GbLZZNuZa0RV1bqfJSvbsJaNNIi9CK8WWbSsKLZdeIJRUWwVCmHRKmmSoua2z/E9yjvpO9l0Ut0cqZZlJ/0sC3qdXccyIMC00UYbhf58+OGHJ3vssUdSF9xSr36w6MKFhiADY3MekCdVgd6Sag3+k8o/mJSYGNF/1ZGwp0G3LVLN9hxeuXQ4orJEdK0FVyxbmEUj1fweZwUIshxLmPDtdnc6IVFFe0hi7FOincgzDZkS91g6bBFtwAJRMpFxpdNlLaiKY23YK3YBKpTE+IFEg12ENhan1rLREl6aJby28FARy768wjNpaRKkSlFs62CipEf6Ztd82ItA12YIFUTbJtWyuuN5y4JeZ+4uCojXhhtuGH4i/fj0pz9d0dE62gBuNF/84hdzdzNsANFJdQbSkxcSkElIK5OAInJMjHVscdvJq2lYeQQRR1b8Oj9L9mMon12EVEvjS0SOyRrSNy4hkXuL1RJ/QyStbZeTusB5q5S13CTkhwzRsTpc64mt/qnoP1FO3jOp280QwAKchTj9MaZIfprwMsHYKDb9AdBH9L6iln1COtlRDiZECelzkBTkSHyGTbC1hWfKJHDGCo9UL66prtOKFYcRFmYkzjL+M+6n7dTkQFIELDzx0ubzPvjBDwYy5ugujjnmmFAFk7652WabhQBTVUqDUWifNdWIslULZX2FxphBkWhnXUUs6rL8GwV5L3N+kkdIHxkD2Z8kUdFG3FkcaKt9VEIiURQGYf4G4kMS41AmQe47OQE0q8OFZCvxTBFM+gZEkegikyOEuilrwa5Bicz0t5iL39hFFoSX8ceWMVelRemnRbJl2Ve28AyNPidJFc8on6cINv3O7pzY8ukxyM/KYqikOn2+igzWGalmkY+/8FFHHRXKi1OmXCSeMuUETdZZZ53FCr9QgZGGRtraqHG8EC/yarbffvvkpJNO6mT/czwL7iHzFQmneV7mdaDXpJpoZVHSKoswIioiEHUOCE2TV3t+svbKkjq0LUspE6mGBEBkFHGHJIxLSIT8EKWnX0Cm2R4f6uCZ1uEqgqnS6YpgimChR0OTO9TrlQcWHTxbXCfGja64G2iMzKq0SLOOMhBe7WRMYtmncdgWnlGCrXy4+SkfbhFxkeyu7CINkVRb2WCT8g9wyCGHBMs7quIxhq211lphUXjrrbeGvpq2U6OfkT/DPGhx8MEHJ7fcckt4hnkmPvShD2V+32mnnVbtCbimujYgBV1vvfUaJdS9J9U8IAza4wCZUGIRESakAHVLH5pMVMQijmguUcdx5zeNL3STiYpsH6Oh5joSiWDiHVdyXBXteB3yA0lwPAsWWUQSIVj0F3YBWOlDiLRlD7kRuZq2yl4fYKtJMng3sb1YF3hWsiotimSzy6VKi4pgW8I7yrIPCQjg3/QnW3jG7pwwRimKbX24beGZOmwiq8IQNdVZC4gm5B+ARf61114bos5nn312Mn/+/DAu4U88Z86cwhIspB86Hz4nD5WTakdtYExpoxJ0r0h1eqBlYBsXqWayIHLJoM9Kl8mkiQG7KVLNYCGdZxF9eGzyjzTJV3KhqvipOt2ohER+hyaYCAaDcN27EF2G9ermWVDZV8iOdNjWro2orLVrGwroU2gvIZnqh32TxqQrLeb1AQiv+gDPlR1DaEQtef4AfWRU4Rm03DTGKnZGbOEZpErWh1vVRGPI/Rgnh+grON+sBUQT8g+B5+6II44IbRxw86BlkeU2CLO7f9SHd7/73cnJJ58cxp8m56Z4RqMaoETFLHs4qy/mfUQ7m3Q0aIJUk+GPJWAZf+1YI9UcDwsf5B5MskQjVMUvnZBoCTWLKnRyEAEmf/6miYqDXYSkMfTJtFe3io6oyp6VidB4jiCXcpKAGPWVWMhpBv05UV0WaX3vU5bwEnxQH5BsA7tF+aLbwjO8T0WzyHfgd1me2FmWfei4rU2kLTyT9uFWFJs+2GYUe4jyjyxS3ZT8w+HIA4snZEGUIf/qV7/aWCGYXpNqS1xtNENEi61FHnomxaajbHVqlxnY2ZJWZJYoWlHHhlg11ViULVy4MAzWbOlB+sYlJPI3TOhEX4m2obseyrZsWUBQtADjeUgnsI4qnQ6pUgRTiW48byJX/OwL6eR8GTs4X86LpMQh9inbB9K+6MisaHanSPkLQlnLPvld0+TDnS48Y0m9yqc3fW+GSKqznu1pCq8MCh6prg2bbrppeB6vu+66mZwrxqusZ5Mx5nvf+14l39t7S700qVZFOIgWkVsqnbWxfViXzIKIENFGJhsmlbJRtNjkH7qnbLVzH4l2ycxfuxBZhJqtYkXIWKFiJxerDrNNaMeG60tksGyBI/oLxJlmE90gV1YTq6p+vI8FbBfvhXZKiJiySGNhNxTyVNQXHfLMGEuSEE1gkc//JRNhbJrGso8tf7uwg1SLZIvUWxcbWhPynCGS6qyFizTVHql2tAXItO2nso/NQpXzUa9I9TiJBZns2OzI+aFNolWHpR6ERoUniAqxOis7uMcm/1DRCCZaJDry2h2VkIgbA1FXQFImiXeO58IWv9GOTdkqi6MS3dDESiIA2ZFEAHJjS6d3gYAo2RfCyKKOaGkXFwZNAD0tfYoxjuePfqZ+YD2qRXZV3XMSy748H26rxZaLDdIQWz69jn43NE019yhPU02wqi87VLXBI9W1gWBRG+gdqWaiU6RDEWgiTEzmNPkzt+38UHVEmIggCwY+jwiaSriWRSzyDythARCZcYSa39liJuin0QE7ngsWc/QXCAckow7HGyLf6LJpkgjIl1iRzCw/5JiTNyHTLMYdo+0F6UtWdobrEM8n13KUZR+NZ7ZIFDsv2VE+3IyB9HMRa5rtd3UUnhlSpFr3IE9TzT0YwnVwxImlSpanrwq9I9UWethJKiJKxsAdSylqTQDTklcRSbLrmYiI5qrQwiSIQf7BIggJCxMv94wIfFaFRJuQyHUkOs3igr+BUE8Tde0zIIeSQJEENsmORhUSAemwLbmChCnZkfvYdjSYcQPJB+QMqRiyD0d+YjRjLQQVQp3e+udeck9p8qiWZR8/rWWfXWjx/0kLzzBuQOgtqc8qPMOxqn9C6iftd0Oy1Ms7V5Wpd+mHY4joNamWtEIaSCbFmAa7shUfs86PqBDRISaqKmy92pZ/sG145513hkGZCCfRJkz5rX46XXIcmQEkHB01k2ds9zkmsECBUHPNsC2D3DRNXPk+lbG25AqCw0/03dJ4W0/spu8px0M0n+Nlkdb27lbMYEcJBxjGHxb2RcYha9nHc63qnjTGNJrV48uyr2zhGRvFFqlnt4HFu5WJpJNsafS7MhKGIUWq80qUA8bvtp1Yoseihiz1XGLSKHor/yBiKVE65AyiFdsDPg2pRjeNxhOSVGXCZZvyDyY2CB+TnTTvyiJnYUQjimQnLM6fSCLRV94/zod7yIA8QBK5tzFFXdN+yNzntJOE3B9EsuvehcAu77777gvPFLtbLiPKhpVcsd3Pwn6SeyNrPJq1bRTplR5fCy0a/UFj3qjCM6PKp6vwDO/LKzzD7olI9rjdEyfVzwZHRjkIORxVY5qgi636Oi16R6pV6INIlyQDJEPFSLQmlX9Y8ll1wZq25B/WU5uJmYgzx8A9ZJKWH7KNXvJ7/oafK664YpAyOEaTRO4v13caiVCdsNZpyy23XFhU2WRHfpJcmS6bXVX/Z/wgWskYIjvKIRW1KXutiE6TeFi1X3eeZR/NWvaliw+lZSIi2jaKzevWqk8/5cWuJFsbxYZwI03h/LS4s6RecFL9R/DcsssY47wbFTyKXBnSVZeb+ttek2ouzB133BEiXAzyRC4VmYsRRSo+pqHy3JZ8Vomm5R/cMxISH3vssTCRsnXMFq8iThzP7NmzF7Nq06QKGLSVxOgYHUnsYjVJJZ1xj1lEWk9saXAhOrZs9qQ7NpYkVuGG0mdwrViksVgjusy1qsuaNK3HJwoqgg3ZVvEhJCfS4+dZ9k1aeAZpiki2pCmqJqljU7VIHfNQSbU01THkLjmGg2cicSzrFamWpReTLA4Y8sqMmVSjJy1TxY3MdQarsn7CMco/WFCghYYkaWLm3lmdpCY5JkkaOmCKb5DYxuu8B0JOY4KTZ3JXvZCrBNcG4kNhFyXpxuiuURSQJOwRadLgimBD7miKXopcFZ3YtesBWaIvqlqnI/ta6RnkGuMc06TenXtKFJSWLj5kLfsUUS5q2Teq8IzGH6Qp6cIzSFOUAzAEMj2OVPM68p0uLd7bgpcp7x96RaoBkQxt79XhBd2GphrijdyDAVxV3Ory/2xK/kG0CU24HCikeU9XSLSTlFxBdB1WWmml8D5FsJnkIFryQhbB7nPJ7DxwrdilgXBAKrhWbRQ5qgtWg6sKe+nS6eyAsLiSTCStx08v7vgbT3QdDcYrFZdiccO1avPZShcfspZ96g8AglfWsq9o4RlbPp1+CCiPnC6f3jfkeXJ7ifL+gv49d+7c5Nxzzw2LVxaum2yySTJnzpyQuzYpkNuxOGcxtv766ydXX3110lX0Z5b9E6zNmq2o2FVSjZYP8klnYwucRUOdk1gT8g9IMYsEFgvoZnGAGFchUZUwVdiGv9Ox2m1a64WsqBX9QMSKCa7vEUiuEddKJd3r7jMxAKJDv6DJm1ikyro6iFjJqk0LVp4zJgXsBYe+w1GkomSM1ypt2Sd3DxFs7WjZfsB4QIBimsIzIs68j+vDGARxlzQFwtBE4ZmmoWuSXqyLVHsuQgF0KFINB1lvvfWShQsXhqTyLbfcMjxPp556anLJJZeE15deeumJPvujH/1oyGPoA3pJqvMqKsYGjk9bjlmDLFvRbLPyeyJCEKS6Ubf8Ay00NoB8D3IEol1W7qFjsPfRulZQphziVER7SdSKLWqIldVBSh5Aa6J0cZOAHGrBQgSXhVhMxKcJpL2JuSYi2LYfQL7YMYGEQ8KQFg3tWhUF/UluQ8guWNTGfq2y3D0kE7GWfRBgkWz6xDSFZ7RDythGv7Ll023hGVs+vau6/bxItWSXTqr7hSOPPDIQZ3KcrrzyypmdiGOPPTbZb7/9kl122WWx0uBFcfLJJ4e/g1h/7WtfS7qO3pFqiy7IPzQ42YGJwRsJAzo9oihUgGQQbgKaHKqOVCsJjMQyuSowgY0j1LiC4PagiaqoTZONWkGWWGVrQrXyAAYGEewqXSTaAOfG4oNrjdwDMjF0KJmMpn4gUgXhEfg/z6GS3PoQSayjRDuRqCrdhtroB+iiiYpZVxlkYxpv00mvZaLYzDXqO/ytlabIyUYkm3+LfKrYDWNQV/penqaahSpw+Ud/ItUsqufNmxf+fcIJJyx2b/fdd9/k9NNPTxYsWBBqTGA2UBTYVh5wwAHJhhtumOy4445OqmOHtulijVTbqLCiIyofTYSVAXZS39dpj6tKUm3PiUmNc1JCoiL16QqJ1omBaDKJY9MM0lzDtDxAMhHrIqFJsI1iI9NAiw8mcjT3TS3Cugb6AVvxRFwBDkH0h3SSGyRHyY515S90Acp9QFLE7g9R6j6ApEIkLDTrjZ6V9CqSTb8ZVXiGfgRZZ/yEhKSj2Cp4pMIztny6larZ8ukx9708Uq1ItZPq/uCmm24KC08CEwS30th2223DHH/xxReXItV77bVXGFtOPPHEMIf1Ab0j1ekIyiS2dU0hLU+xyXttVoCsciFii9TonETabclxG53hfiF7YYJDf1h1YmZaHiAXiXSxEUusYnXN0K4G2jYWHwx4vu06OjJC3+K5YvCXX7dNcqMf2NLpcpVRRb+uRWknBdeDyBMEETelaRKRYkbaG90mvaYt+0SwIdu28AzXCKcdSLUWHqMs+9JONoyPIti277HTpij2uMIzsZBq11QXwxINuX9U0WNITgYExLKg1++6667Cn3nZZZcl5513XnLEEUeE3SMn1R0BA1+skWq7rchgSpKLrSbY1gBaVaSa6A+EWvpeJTGkHT7seTKhcR3kCkIyVJ3boWkXCW3RimTLPSBGuz5rA8fxEc2PObLVNtCzEs3nGkl+lJfkRp+1LhJylSHSbSv6dWk3oww4X7T5LHDJyof8DQU26VWWfeoH0kXbCp+MHRBqNNv0HZrdhUtLRbIKz7ArSVPfs4VnlGAJEbfl09tOuB5Hqj1SHQ+QNlEgLQvMIePALgrIy+vS648//nih46GP7LrrroHrfOITn0j6hN6T6i5EqlmhaduZ6BnEre3jmpZUs31KQiKA7KHvHaefhoRrYdFWkp0tNqLJTVrsmOz6rBMDx4GGuq8Er8oCOGzhQ6jHJahCvNOuMlps8bzStJthvZD7AIgcfYvrxrM75MJKacu+rAqfAgtbyC5jVl7hGY19o6LY9D129Wi835ZPTydYqv+1sdB3Uj0cSNKTZw2pXYnf/ElWNw6HHHJIIODXXntt7wJBg5B/QEBiPlY6lyb7GAYiBvZJFyI2yRLJBOdEBGYcoaZACStmXkPuUXWlyEmQntxiseuzlnldcWJoC9w3otNIeiYtpW1dZbjWyLS00LJeyES5JRPpatIr58IWrtx5XJv/LLifVhdNP0AeQyIn8wyLbv7PmGAXW0Us+0YVntFOmhJtbeEZvpPFImOt+qiVptQJ96meEosaSlRclIS+UyQi3QTuuOOO5Mtf/nLy/ve/P3nHO96R9A29I9VdkX+gvdOWChPwqquu2vp23rTyD2mh0a0qyZLBXhNGXkIiBJxEQd5LZIy/jQ1Zdn0i2E3a9TGJEkUkit6nxLE6wHNPf+Qecd+QMUxLNrjH2s1QwpndzVBEXC4SSnrtQuEd+jC7SxyrFsOO/PGb5xCSix6UviDrRhpjIA1wHUWw+fc0hWfYDUknWIpk2wTLdOGZOhZ4HDeLhfRnu6Ve/6AFkpxd0tBC6vljqjzDET7ykY+E/vn5z38+6SPiH+mnBBMEN1IJcTHpFRmQAQNyLIR6UvmHbLeYWJB6IEcYl5DIoMwkLqcTItRd2EK3+lt04rJpS1fzq9quj+sESQSxRPNjhZXH0B/RE9Yh07FeyPRznm31BZEclblWFDtGb3TkLPfff//M7pJHGfPB805EGoLBzgVSMWCtGyHdkofwM73Ykiaf/jNJ4Rk1JVgil+N4RLDp90SybR6ACs9UJRPjOLM+yy31+mepp+BNXjKhXl/qT89CHngf4zLj5XbbbbfY7+izgGdLEexJfK/bRu9JtR2wYtCcWq0xZJoElLpLgtcdqYZIQKiZSIjaMKmMS0hUpAcSThIUpCeG+zMJmLRs2WJFLqu061OSHZMw0XwmR0c+6WHRSsSsSXmMyDNNJMcutugXtmS2Sqe3vdhnDKLqH2SfnI4YSX9MfYvt63EWgyxOrCY/z7KP51gkm8juKMs++3pWFJuINE0Jlio8w3faPABbeGaae61IdRou/+gfCOIA5vks6PWVV1650OfZ3IA0eFbwvO4qBqGpBkSr2yRttviJokEcExNabPIUlU8vEt1HC22jp+iP7ZYmSBNqiDSEGmLdt0p2XLsq7fr4DAiPdPfoXPOSRRx/nNAZ4CE/bVeU5D5Bumg861klsyFRtthIkztWVnoFoWvDE79LgEgTRePnqMquRS37VIgK8ssznnaWsZZ9oEwUm3FIn8V38lxYRxEt8FR4hsYCr8xuzjhSPU4K4GjGUq8KrLnmmqF/MF4wdxPYsTj//PPDzy222GLk5xBI1AIxDaLS6667brL++usnV199ddJV9I5UAyZR3TgNTG0SV7aiSf6BWNExIUYMoNruiDFSDUaRak3IbC+mExJFyPVZ9jMkYeD3eFZDwvuKtF2fEtykvx1n12flMXX4dfcN1gaOnQ+ihLGAccj6EtuS2SxMaeliI3VqUjkGJErsgEyawDkk2KTEaT2705Z9cpZJR5Rl2SfJkMblSaLYSrBkkaniV+nCMxBkW3hmnDc/x57VZ7z4S//Afd59992To446Ktltt91CmXKNT5Qph9+ss846ixV+oQIjbeutt07mzp2bDAW9JNWjCqy0FTnjJwOx1Xa2fWx5sIN3VuRCCWBs32QlJIqMpxMSicxBwocqYSByyaRGY6ElYp1l18e14Xr1QR7TBLiGKlDA4qNtW8oyJbOzNPnsatFfJBOp0rqRZxT9NBIESDzPYhcSKdsk1Eg+2FmrerFmI8qjLPsgMHoffcFGsa1lX1YUO23Zly5+paJHVrZmC8/QsnJC8iLVXC9IWEx5QtGiI5Fq2eARQb755ptDkGittdYKO6i33nprGKNOOeWUxd5Pn2LhTsBgSOj9SGrlH02DwYmJnsGH7cL0VnSspNoeV3qylV4VEgjZkz/yqIREO4kTvWASH7pukwlnnF0fgFgxYMWSExAj6FcU36CvdnGxltbkQ6q12LLWjZIMTVO+mn7EgpjdDwgaGkjvV/mA5BKhhlDXvbOWtuxTKXORbAgMTaXM1RcIaExj2ZcuemSj2FamZKPYctXKk3804ZuNjIYI6LnnnhueEY5vk002SebMmVN6J4Hx9/DDD0/mz58fgkUk0hFh5bWujSd1jlP4SnPNzz777HCtuOY777xzuOZ5hWGGhiUW5QlcOgwGIw0gbG/izzhr1qzGihgoKssqjcGIyFnWdzNQ00nRXLKlGAtIiOP42c6x5JeoqSYYXC9YrY5LSGSQZmGB1IVrAAn3qNjowR3NGotABjE5xDRh19dFKMmOa8WOSZ9svBRF1GKL509QgluZCp+QIJ5FyBILYkhiG4WLulamnfmEcavNqpIqZW4rfAppyz71hTzLPou0TCT9nbIJpM9I1qHv5HeyqrQ7kjg30F9ZANTVvxgX0d8uXLgwLHSImjIW3HbbbeGZ4HVV8B0Hzm/27Nlhp5C/gSvAGWjo0W+55ZZAHqsEOx6P/vxXybI7119N8OHT/iF53UteGI1Pdd/Re3bTdKSaAYzOq6gsE31eYlmskWoNhPa4WL1LC80gyhZoetsxTagZhCGIRBS8SMl44Gtrq1AyOTRl19c12ATOvibZpa0bWcxaaQALVVmmKemVyT+LyFiLQaJ4yy+//OD6TBlAYCHUzBttE2rAvVIpc/oCwQrbF2TZl5X4Wtayz0axs2wClewI+PdNN90U/s33b7bZZkH+UXek+sgjjwzEGTKMvlf6bfS9++23X7LLLrsUtmPbe++9w3O0zTbbJOedd95M0GfPPfdMjj/++GTfffdNTjvttNrOxdEv9D5SzTYnmmYGxmmSS4rASiPQq40rNsExMiCw1ZTOpm0TJCBCWNZYY40woTNY8n+2nCEvDLK2oAtIE2oGW5IXJH3xraF8cC3ZvkRHyzWmL3CN00jb9alS6LR2fV0DfQ65B1o9IrZcr6HpN9OSIe1ocO9tNT+kARAwxkCIIhI0dpicUBcj1LHr84H1R6cpoiztftaOxrRRbCQeaGmZH/iM73znO8lXvvKV0P94L/PfFVdcEXZgq+5r9Gc+X1auJNlacM+Ye9DB28S5LDCGMDcxTzMG28UTiwiSSVlAECSrsi7ATKT6Aw1Eqk/3SHWTGEykuu5oMBEgCDUPIqt6EpDGDSYasGKNVDOpMDgx8DB4Kho4qkKiJDdEU7n2DHhM8o7xLgxMelyvPGlHUbs+6S1p4zL4uwb1SRYXnJ80/UNDusInJEc6bAIJNEAEjzGJBRgRTpoT6nxI4sbYxmKtKclglf7o6d0tu6NhLft4biYtPCMSTv+jTzEm8TySyIZcgrEIeRHa8E033TQ05BpV2IESGWfsY55NE2qw7bbbhjHi4osvHkuqL7/88nDOyEfSuxGMnVjEkYB32WWXBe2wwzFIUm0nDUWK65R/YIHEKpDBhoGYyHOd1QubItWcE5O1ou5ZCYmWUPM60VYIIsSQAa9PGtc6y2gzIRJhKRpxHWXXJ9cAkkPz7Pq6CCJULFwhPuw6sQPimuDFE9yUbEYfQLIl9wgA0YFgD2VHoywU+RSh7mowIJ34mmfZZ+0bIbtlLPvoR0B/A7E+4IADgvSC/sV8gTTj0ksvTU488cTQ3v72tyc33HDD1Ocnlx+CPFnQ6xDrKj4LUl3ksxyO3pLqpiLVDDBEGdF1KlEKzVvZ44stUs2kDCDUTNJoocclJBIJgyAymTNYM6i6720+bEXJKspo59n1cT/Sdn1MotyjLhFSdPkQHhYPfSsYVDV47thZYoFrSwdn7WhIGtA3PXpZEM2lfzG2EQyoOjGtLaQt+1TlU4VnGB+Yw1QERvaNacs+O/bL+g/wDDJfKILN2EPjGUWP/OUvfzn0QyK9Vckn5IyUJynU68zLTX5WabBWaUJ82zuBb9wYDKmuOlItVwuRSCIbk2y1x0aq2TamwhoguZCt5XEJiQzUEER5cXsEcTS4TkRcIYp1EMQidn3Woo0JN2ZNMhpXCA/PXJlKdkOFLYLD4lbb2qqsl/ZBxu1nyImvPB9cL0BghPG8j+CeQp5ptgiM+oMtApPW5VuZCHMEeTeMIbpWko/IoUYyQb6TOYRWFaQZz5OSaHeUcaPJz3I4BiX/qJK48oAxCEMmmeDJpJ+URMZCqhkAIdNEFbhmDJJELNIRijShZkJicUF0gkkbIj6kCXlSyzzuOf2m7gTOtPbWWrThNkKzdn3aCo4FTPryercE0ZF/vehfPKtZmmBLquSDLC02zz+NSLd1kOizBSbnz1jOMwChHpIncVYRmCxdPrse6g8QcWSB/C0RfRZjNuBywQUXhL/B2s699cfDZ8r+ob+jZU2RagYaJnkGDDKbIZHTkh7JLdoC54KVm2wAmXAZOJW4kufwoaIb0pLHniXfNtC4cp11vZpOgsqyaBPBtnZ9kC5FLdFkt7VIksWgCE9ftuTrAvcR7Sf9C8IzLuLK7oQtna7EV0gVzzYt5gXXtCBSzwKE6yVXo6EiPTZIl68dDS249F7mPeRkSnak/1x00UXJJz7xifAZaKvrItSyzyOolQVJUziOJj/L4RgEqa7KYYNBQ9ZyTEZkFVcxybcdqZbdFppCJk6S5fg3IJLFsVnvUl0LNLqY7bPNB0H0QScftkQ7W6kQnhiuF8diE5pk18dEqkpqilqqeltTkSeSXZEl8P1cr7K5CkNdsBFBnCS3I534ijQpyx9d5bK14OqqzMsuQIZOqLPAc2clZCQ3soupiDTyj6OPPjoEmNZff/3QH6g+yJz4ve99Lzh/1AUFsjimLOh15RI09VkTwfXOvUMvSXU6sqaSqpOCKDcTFhMXZIhJvqqITZukWlpVJlCsj6R7E3FiECUyL7skzplj5VrwOhMRJLxvtm1VggkJckhyGFER+k6MSWGj7PoUtWzCrk+LVxqRsFHFkxzPTvw4vXA/uF6Kvk0Drj3SNprV3qpSnsplSxYQuy7fgnOADHL8BEdiWODGDHTSBAS0AGH8oi8wz/K6Clbx+7XXXjs8u+SKVNEPs8CcA5i7sqDXkYs1+VkOR2+Lv0BkVBgDUFmJlTfFTCZ1HYCAsk1adZltth8h6xtttFGjUR8rY8F5gmilLQbAMck9QvIPyA0TrMz3iUa4Zi4fXCscUZiAIKMMzF0hHhZyDKA/oAnXkEE0VASbCXRamQifywIEkqjFqy/YipVphwRDEOsuX29LV9MflMClQiPqD4wVMeZWICnimXRCXd5mMCuJkwIvO+ywQ7jXuBjJTYP5dp111kn22GOP4PVcV/EX9PDpwmmTFn9hd8w6lNRe/OVnv0pev1P9xV8ePOMfkte91Iu/NIVu7t2VxKSRah4mjOyZOCjmwsNbddKOzapuMiGRgRISv+qqq4ZBxZr/A8qQc77veMc7wiBFJApyJf03AxqTuSXdjmdBAQYGdcgH1xKC2EVCDSBIbJMyQTFRsphigUl/YBuYcsE33nhjIMST9gf6HhMhhJoFyKxZs5xQj4AkWDyDSDJ4jusm1JY841iz+uqrh6IZJNwyPkC2OZ6bb745FOhALhLT+ECgAELNc0j/ckI9GtxPEeosjT7P/E477RT63YIFC8LuBff/S1/6Upg3eC1PVjENIOy77757+Pduu+02o3tWmXLGEcYpS6jnzZsXnIMOOuigxT4LecuOO+4Y5rVdd911sdyrAw88MCwc3/e+91VKqB39xiDkHxBXlfEtClatSsJjQKnLdcD6aNedZa/yzgx0TMSKbFmj/3RCopJQWGDwGtt6DDwMNlwjmraBGXj67hZQBGTRE0Ghz0E+uGYxRu2qtuuz/aGMXR+7Suya8Fk8Z5D2rmp1m67CyW4B41NbnvBZhUaky09btKk/tHGsRCSRKbBQY9zzolTFpIEqhJPOH2IhTeVCxrVLLrkkLLAAwac999wzNNnV1YFDDjkkVG9kAUcOAIs7SD2l0+lnFGyxoD/yzNAP0jjuuOPC+Xz7298OxJsFF1Fd+gufDVGvDb3TCTgGwX7KRKqlgWUykKazzohGU2XUVY2OSY+JjeizrPNk7p+ukKioNtFIJkIGVyX0yPNW1ktEgWj8LQOwdNhDizZaCzi2+IhSD61Udtquj+Q3KwuwYOFBv2QCJhpOv+rLAqQO8Jyin2Y7Wv74sSxi04VGuKeSiViLNsYQJTtWIRsaB64VJImxCMLkGv3R4L5Rqp3gSVZlSX639dZbhzEOQg2hzUJdmmot5q699tpk7ty5ydlnn53Mnz8/zDuUEp8zZ04pq1L6IhaAJFryOdgCsrhnYfCZz3xmUDaLjunRS001p2Rt6lhxM7CjWx41gPM3aJwhRjygDCh1R1XYLoO0rrnmmrWRdw2S6MPJYoYAcR3SJcdtdFBRbVb2DI5ci1Hby5AjTZ5WdyudJSS779EhWQxCLtBPd7XMcRVI2/VpF8Ta9UEGFdEnwkWyrBPqfHANkS/wjEEE6GNdyWlgbFWREZqCCJAjEfE6SqeTIMwzyfdAqJuQyHQZLIyRrbF7ROAlbZNKwGDTTTcNz+yFF14Y5lTHFJrq9zagqT7LNdVNIo4QRwPyD0Vj8wZt64Qh4tnEFnTdkWpluvP58tUeVyFRiwt000x2RZIzmbTkFmDLZPNTZbKJECmC3ab/cdWwEX2ug4oiDBlpuz4VGaHJrk+gz3jRoNHgGqqCaxclMgQn2LWhSTakMQI5Gk07HyLZ07rkyJaxqSTOPhFqFmxpQg0pI+mQXAqkEhtuuGFrx+pwxIpekuo0bFXFLFKtBBYGeyaruqvcNUGqIXpIWNgqVmIOE9Yo/XRaD8ziAk1ZWbKT1t1CqIiuWULFJKuIZR0Rqja249lpIKIfo2Vem+De6l6rX7JDo90MyA8RRdn1VUGo+gRIDotc/ONf8YpXhMTALi9ArGwIuQ8kTQtwEW3A86T+ULZ0On0MDS1EmrHP+9NocA/YzSSgQhAlnZjH4mTzzTcPyYvnnXdestlmm3W6D8aCJXqnE3D0llTzwGvStlUVrZxDGfTSDDP4jqtCVjXqcP8Q0YOsEB0mSsPPcYSaCY3MaVWLZAKfFnyH1Vla/2OIFE2JTAzkXfK7pT8RPWTRwPET3YlF3xorWMBCqLnnSrATkVIFtzrs+roKFWdiJ23SRW7M4FxUOh35DwsIW4RInuW2CBGLr1HPGQlreOxr7HNCPRrszkKokWwRVMIaz4LnFULNfTnnnHOSrbbaqld90OGoEoNgAFnRYHkIk0ylDPo2tgerjlRbXThET4lM4xISIeBEdiC0WdneVSBdtU2JbUpiotmyyJDsWCdEm2DH4oOs8S5tx7cBkZ10kRKkH7Q0oWKxK0mNCDZ9YyjXmT4GoeY56ZuLTB4YfyB1NMYqFuFadNnS6XZXw47byLAIlMjdaGiJ0pP0MQg1P9H5srtowfWEUDNPnnHGGTOOHw6HY8Ck2so/tNXFZAUhYhBps4hJlaSa8+G8OD9ICkSvSEIiZBpNI5EdCHVTCYU2QmUT2yBWKovMFrB02LFELIkaQqg5Zk+wGw/6HdEuSDX3W1XZxhEq5A7T2vV1fTseskN+h8opDwmMUyyiaCzCbREixgfGCcC4QF8goADp5v8Q6rZsBrvmpU+kGklR2qkICQ1JiewmnnzyycHP2ce5CsFGehPyD5eYNIrByT8YiInkEhVDz9d29KcqUs1kw3nxOQyQbBUrMi1CnZZ7cA2Qe8jtpM2KfzaxTfeJyLWNWBKRUsSSaHcbEUuOS5UoWYylIzuOxWFdZEhOLVoERyXRabJvLGvX11XIrQeS2HdbxkmKENE0RkiHrcRXyUm0U9fXRde0ICAgRyiCL+k8Iog0ummI9Ve+8pVgVeeE2uEYMKnOilSj55SGl2hZDFWSRAynIdVKSOS8iNBIv2wrJKYJNVEfoq38jE2+wP3C4YCWLjCighJMliJTTJ5N7DTQd+x1blp/32XHimks4Oi3RB9pLIIhBFaHTf9AVmLt+rrqLqPSy5BGrlddRae6Do0RjOHaBSEyTctadNH/+m7pWRQs1iDUjP3sguC+Y8E8ieQDLfvxxx+ffPSjH+3ksxQ7lmgoUdHvXLMYBKnWgCCJg9Vzto1pItW2UI3Oi4ljXEIiURwi1ESqNajGOmimC4wgvZAOWxpLvUeEquptXxYoRMrRFyJb0HV25MPaMhJpZfekqkUbuxosBGl5dn1tLLqmBefBNaO/IcOCCDqKyYrsLgiyBisT0aKLMVLJjm3tdMVCqNn5YQcoLStiMQKh5npRSZAy4LHODQ5HjOgtqdZAQFQLQgQgQpRTjWlLcFJSLZstInUqVMN5WclHOiHRRltVfr1LEzfnQVIpjcQtti5l1acGmDClw55WEmDlC3wv19mTn0aD+yJtP5Fl7lVdE3Parg/LL/UFu+iK3a6P42Whq+fSd0FGg3sN8SOgwPPONdOOZLp0uhZdtnS61ebzcwj6a+YM5RKRC4JE0ILr8653vSvMD0cffXSy9957O6GuG6537h16S6rtViqRC0BkKyZCPamlHlEGuQIwcWB/Ny4h0UZ1+lKgBI01EwNNFdsg2Sw0SHJj0uUc5SRC0mOZSYJJCPkCkS4+A//WLkQ8Y0nibDrBjntLxJIGaYDc2+TXWO36WLBRWAOixy4Ix+fIB2MZO3TsPKYJ9bhFF4Qyrc0HfI6i2ARf2u4TdRFqnk85yVgwxm255ZbJPffcE0pzH3jggb27Bg5HE+gtqSYiS+QHkDkOoayramGTkWqbaIkOWtGGUQmJ6DMZLJlIIBxNlF9vs2Ib11LWbDRkGzQizIpgj7Nmg5BBDlm4II9RaXdHPpiYlSzLAiTtd9vGoit2uz6IIZHBtM2gIxuMb1wvFQtiLCu60OX5ZWFNW3rppWe0+TQtxLHjU59Q6fSuy0QY/xnL2MWBTHPuFry+9dZbh2f34IMPTg499FAf6xqCF3/pH3pLqhkkiUoTxWDC6gOpxlIMKQKDPIlyir6MSkiEHDJYEqGB5BDV7nu0lfODPNO4PkyWkolYazZFpvhpI11MMkxCRL+lO/RJZjS4vvi+c5145thSjwlF7ProN7ZP1L2rhfabccnLaBcDzzLjH5Ie+teb3vSmqcYyq81PJ0TbPmFLp3dN+iVCza4t1p9EqS2YF7bZZpvk9ttvT/bff//kiCOO8LHO4ZgCvSXV2J0h+2AQhBxpgIkN0jyPItXa7kS6wcSriNa4hEQGUgg15z+U4hFpqJgMTdZsIthkudNUTAISzjUkEgbcfaFctJXdAgh17PKFtu36bOIrzzHPc9fIWtOwuQ3TOMkUTYimTyjZUYWpAH1bC6+ycrKmwZyi8vYEBpBE2ePlHCnmcssttyR77LFH8g//8A+dj8p3Dh6p7h16S6oZcDVRpYu/xARpn/OOjYUAAyMDPMRQGe7jEhIhi+g0gZPD51qzsQXKokuTpi0mwfuIXvlW/GjQByGG8hCHHHbNK7ppuz6uGUWNiIJC0LhmseV5xAbGOORrLHa4/oxndZI/2yeI7hKUkHSInyqdzvxiS6fHtAMoQk3/Rb7G4jG9g/nud787ueGGG5KPfexjyXHHHeeE2uGoAL0l1RaK4MYYqQYMxlmk2lZ+hORRCCIrITFdclyDPpFDNIeQAMdzgXaSCYdkTxEdTYxEX2XBKB12V72P604WI2InmVXXUdauDzKVlyQ3KtrKAplns+jfDhVcM2RFLHx5DtHqN03+GEcp8kSTdEgLL7TdNO1+iGS36TAjf3j6LmNbOh+EheN73/ve5Jprrkl22WWX5IQTTnBC3RY8Ut079HZET5MfJq8YI9UAIpd2/2BARAsnL2kiJuMSEjk/Jm2i1BAdJu0Y7cNiAteMiD5RMCVx0ldEppjMRaaYXC2Ziiky1RbR4Tqgbe0jOazSrs9eszrkC30E14xkc643O21I+tomf1nSIZvsyE8Wm3Id4l43uRjXNeNYSNommd1+N1H397///ckVV1yR7LTTTsnXvvY174cOR4Xo30xYMhoc47ER/YPoMYCr8qMSEvmZRaiJPhCdQEft9m/FwATDNSPyxDVm0tY1U2ISkxJkSjpsRaaUwMTfNZHUFguszWAsRCcmuz4Ws7JwlF2frSw5pGs2DbhmkEOuK8ml7NLFeM2QBdFwYeLZsJ7Ych3SzgbjBGNGXQtQEWq+m6i6rFYFjo/I9CWXXJLssMMOySmnnOJzhMNRMQZFqmOWf0CKpbckKkrEC0eAIgmJeI+in0MjTEQ7nZDieC5smXYmRGwXs66ZJVO8R0ltSl6iKRlSUc2+ujjQR7lm9Leh2wyOsuuT/IpnmIgmC136DZISKksO9ZoVhV2EEG1Nk8NYAXlm0URjLOe+q09oZ8OOFZDsqnIQpDvn+7QISduqUm78ggsuCPZ53/jGN3q5u9QpLGrIUs8lJo1iUPIPSEHMhB/9NIOiChogN7AJiVmEmvezrczvGUiZhBzFigJJWlOmQIkiUyxe6E+KVhKhorEoyopWdh2QQq4ZEVoWbZx/H86rTrs+FlwQKcC1or/JvaJvPvFVJ9jxLHV5ESL3GBqLcZ4b6bDZ5dFYwVgiHTYL90mi8cwRkrAx5qQJNdeUcuPf/OY3Qwnyc845x/ufw1ETekuquyT/AJBqBlxIsbY6xyUkUm4XZwL5cXtp4+J+ygAtMJPQNEltKofM/bMFZxStJKKpCDYTbIxb2GUWIZAcztcxWnNLBJJ+APg/Y4+1ZrN2fRArx7NOR5BO+lhaD9xlMA6wu0PjPCHVItlYpdLkna9WRFImQk0ejWR/doxh/thrr72SM888M9l4440Dse5DQnFv4FHk3mFQpDpG+QcTCJEtQERD1a5EprNKjvM7kmHQ9jIhk1zXNSuzNsAihOhQHa4oTIja+lW0UjpsvpfGJMlkCZFHW9kFPSMLBbbi6YfTLkKGAiRFd955Z5Bj2Z0QNPxWh00fofiL7ProG5DtvhDJSYqUcE36Li1irLDFqZBTqV9Y73zGJ+uTnr4eKoZjvbvT8wQFXU499dRk/fXXT77zne/0VprmcMSCQck/JKWIJVoIKUYHJ6jk+KiERJsoBjEjMjGUJLlJwXUkog+xZXIi+bPOycU6BEAONGlCspkAaSo2oUkzxu1YJnf6J+Sfawbhc4wG9xoZFwQ6LcfiHhex65McoM6ktpjAmKaqf6PyG/oIzhO/choFuliIpUunq+qmFl7sSPJ3BFZsdck0oT7ooIOSr371q8naa6+dzJ8/P5rACwvOq666KrnttttCYx7UOD0JmAsPP/zwcI6MWciw0I3zWuxj1hITnrMjXvR/xP4TFBUkItI2gWHwYKBUMhMRCfRwiqTnEWp0rWyPEgmToX8sC4RYAXmBGEJoGWCJUDe5CElPmnKNUBRbEgHJAYhexTD5KarPVrEqeDpGA1IIoabPjSu4NMquTwsvVfrU+/pojwmh5ppx/p5k/UfvfEnK6EcqnQ7J1o4XfYc5jLGEcSOLUH/6059O5s2bl8yePTu5+OKLo3p+58yZk1x44YWVfBbXhXN85JFHwi7vVlttFeQwX/rSl5Lvfve7oVokz5DD0RR6TaoZnLX6jaWqIsQZ2yNIFWQawoLtkiYYDY5pQk3Ugr/j+NEaQqodo0G0kEUIZCcWKzPrGsHxSVfJT0Wl5HFLg4w3STJ4XpigiJoiS0Cr71vG40HUmb7G9eOaET2swq5PlT6JSioBtgslsouA/g+hJroPIaJ1/ZyqBORZ+mr6FUXA6BMUqaKPAMaMBQsWBN9porOrrrpqMnfu3OTYY48N/77sssvCGBITIMEsOjk+mpK+J8Hee+8dxqttttkmOe+882bm+T333DM5/vjjk3333Tc57bTTkmjhgereYYlFk+65dGTQ1ulBViinvOaaa4YJqQ0wEGoSwUdUJA9pAsSabSteZ3vP6m3xrWZS5TXkHgyyjuJuFV2IgEkOoAg2CyxApFgRbPpFnYsCIlz3339/2FJWIZy2d3W6AO4XC17uDYS6yi3ndAKsdrPUL1SIqO3F4iRjMzIAiCI7OMolcRRb8EKUkRExZmCTd8wxx4T3sMvFTuZrX/va5Prrr+9EUjHReVnKlgG7OZwfRJoIvt0Z4vMIPHF9GM9iywVBGvajp36VrLjNgbV/173fOSZZ+uUvDBF8R/3odaTaou1INREFaS3TCYlEtZSgQrNlkJlQIdVECyE5MW3jxQquNVFDCEhX3CrScgBry6aS6XIHkLaySr2tLbbhFf/KTexMVtwLdp2qjgpmJcCKYKtfqBCR+kXsCyEID4SahS+LXQigYzwICkGotcNJ32BsQwbIYg5iTSABEKTh9Q022CDY6NH6Zrd6+eWXh2dirbXWeo7UikXnFltsEQrcEK3feeedkxjRiE+1o1EMRv4hgtAGqWalrIREiDERaVshkYl4jTXWCJOMbLdULABAsom2uhXSeKBN51pz77nWXYzqq0AETQVnFMG27gBEKInAQKam6RtWJqNKbF2LfLYBCC2Rfa49hZrqtsbLKpEt6VBX7PosoeYclJztGA3ybyDKzBUQaLugpv/RFyHUBBFOOumkZOHChaFyIoQSTTW7swRo+pTUTsI+YIGRBV6HVBMscDiaQq9JdV6iYtPbdUQYlPBFlCGvQiIDH42IAlFttvEYBJECMHkjARGRosUekWoSXGu8XpH5cF2YeGLTEk4C+gW7EzR2N3AHSOtt6Ruy36JflCFSfB59DZLTBZlMLCBiKFcGCHXTunPbL4j05unzkQNYn/Q27y19DULNuFa26NKQAZlmDmFuYA6xxJhx7+tf/3pywAEHhAU4rhrIQpA57rfffqEfoLfWDmifgOQD5O1E6nXmhWjhkereYTCkumn5h7bTiZxC7hgMIdbjSo4zCLICZ5JU5Tr+rUilJVJMkiLYQ04m41riVEG0pu/JdegPVURC5bHpGxApIs0s4iBSimBDtvOIFHpWCDXRQ48aFgMkBoID0YHQ6rluGywkWYzTrF0f/ULFRdq06yO3AULNT0+0Lg7uG8+0+lqaUJ9xxhkhWY8F99VXXx0ItQVzxA477JD0EYxfIM8tScEFcpgcjqbQa1JtyUSTkWpF/7CJQuqhKlcq6MLPdIVE6TMx8we20AaTtiVS2u5VRIpER6IYItgMJkOJNlotMFF8tMB9i8gULY8tIkXfkO8xZMsmtOk5oN+wXcz1I2EW2YdjNHh2WbzhvqCFcox9LcuuT1HsNuz6INJ33HFHGBe7kuMQA1Qxl/Gc3RC7M8l9pdz4rrvuGhbDEGqP/Dsc7aPXpLqNSLW8aon+kdVOtBmkS45bzaqNfkGg0QLnSReYxCFANM5FkUomTD6DpkglrWlLtibBNUYLDGkYuhaY85b9FpFAron6BcUVaEpog0BBDOVWUcb+bajg2VX1OrTuPKNdKMxi7frkky6C3YRdn60umS6G48gHzycLOMbyLEL97W9/O/nYxz4WrieSjyEmeyppnz6WBSRtoC23r7FY1FCioktMGkX8s0JFaCJSzYR79913z0SaIXqKTItQp+UeEGPcA5CJ8PAzWReNGnFOIs98PoUClLCkSCUkXe9hK7AvpJOtPyKtTNbucZtPpJToKB22ktkAETB+x8TdV7lMFeDZ4rnm2nXdGYX7rF0va9cH0SYZjlaVXR99C0LN4td3Q4pDFqrS61t5EXPIRRddlHzoQx8KYzoRap7xIUKRea5XFvS6y9ocTWJw8o86ItWKNKN9YwCUV+04/bSNtDJAMvFMOlmr7DWNSCURcxFsoh40WfXxXVYK0DUQYUN3zr0kOp3WEToWB+QZ4iyrPvoBUR76CNEwmiKV9A1+5wuUP4I+xjNKn0NmQ7S1LwvTtF0f/SFt4zipXR+LXgg1cjXkb1w7x3jg+ES+DIR61qxZiwVYeH5x8/jABz4QdkuIUDPWDxUErgA7w1nQ6yyCo4VHkXuHXpPqJuQffB5RLLKryyQkQqSZrCHWbN2xNVsVkeFzIPU0ohhMcGmrPlXrUkSqC1vZ1hfYpQuTaYFtcl26sIgilUzkSnTs0+5GWUAI2Q2BbLJwQw/c18UG99jaOLKlbnc3ytj1kRgGoaZ/QahHlWt3PHds4/kjQp0m1JDonXbaKSyAr7zyyhCEGTI22WST0G9vuOGG0D9tgRfmVawEmec23XTTVo/TMSx0g0lFKv9AeqBJl4mDCYTvsZKPrIREBgCIOO+re1vUWvVB3JksNUkiOaFZz+NYrfq4VshZ7G5AtFq5iEAfxLeb+wxhIrqj5LqswiLSYZMkRZNjBP2CBUxXdzemKaE9NKtBzhPCTJP7kHTYLMKy7PqQGkFwLKEmQhhbJbvY/fXleZ6WY1133XXJjjvuGK45FnnIBIeCefPmhUYZdkqwC8ybXJOzzjorJGyee+65M8GhAw88MPRXovqx9kFGkyY01cMYteLBYEi1IsVVRaqJNDPpStMrXdu4hER5KUNWGBirLGlcBAzKTJQ0VvMi2DFb9XE90RiSbEekFUJdp1tBXwCxQSbDvR0nL7KFRfAQ1u6GdYyQxEhEKsbFV9V+yrK1HAqhLmLXR+6GotjWrg9iTV9jnGPxRh9xjIeCLFxnCHXaIu7GG29Mtt9++/B75B/IQrqMSy+9NJkzZ87M/1m0gdVXX33mtUMPPTTZbLPNwr9Z0LHTxhiUxnHHHRcK3ZC4iRSGa0O0nwUKc/Kxxx7byDk5HIMg1XYi5N8QiipINVEFbNwge0RjmGzGJSTyOoQV6UUsXsppqz5NlDFZ9UEMudYQfggd17srUpU2wYKJXRQih1iYMeEUvXfp3Q0cIyQDUMTSSgHoG3lesV0DyXVaLHuBkudCsjG5zNC/VOmTvqH+g9SIa1i3XV/XwbVjfGNRAiFMS2puueWWZNtttw3zCWTUEs8un/Ott976nNftaxpjxoF+eNtttyWHH354Mn/+/OSCCy4IO2977rln8pnPfKbxoFVpuKa6d1hikep49xAQWciicO2114YBfvbs2RN9HpcKzamt2seWukqO5+mnWYkTMYSodoEYpq36JJlp2qqPSRndORM3mlYm8aHqe8uACCvEEDIMKUazX9W9SlfuU5+HDEiH3VUbR/oZ141zdPu34mBc47rRF1jA0f8UsQZ12fV1HTw/jG/MBRBqWcQJ7JZsvvnmYfyl5Pi6667b2rE6qgXjy49/+qtkpS0OrP277r74mOS1r3hhiOA76ke8zK4GMHhNGqnm79hSYgtK5WIh6Ewk/E4TSJpQs43OwAnBIerFllTsxDAGqz4IDpFW+X1XSQz7DGRJXDeIYR2FNrIq92nxhc+6vNYVwWbRGXt/TxfDsYWXHKPB2MB1A4yJyIdAEbs++sZQNPppcG0ItDAnIflIE2p+9653vSs8xxdeeKET6p6iEZ9qR6PoNalOkzAGcOm3JtlKZ+JlspVPrSQf0k+nExIZONnaY6LuaiWxNqz67HVzf9vyE7U0rXUTw3TlPts3ZMkGaZDLDD9j3KFhYcDCl3NwR5ly141xkTEPQm232vPs+mjT2vV1HepvjK1ct3TCNcGbLbbYIkT8v/Od7yQbbrhha8fqcDjKIb4ZrkYw0BMxLgNlsyNFIFq63HLLjU1ItBWxmDj6MlGXseqD0E1CovgMKtfxOTby5RgNNK1MxupvRAHb7BsqOEPf4NhoTZbGLpskJoITvQYzogWciKF8+YvY9TF+posRZdn1ITXr486UIvvqb+nKueTdQKjZcfrmN78Z7OD6eB0cf0J/1beDxaBINYSjjKUegz2RP8gzEVMizUUSEknwg1STiMiEk+fn2mUUtepTJGqcVZ/06vJJ5rqlt0Qd2cD6jgVcLFaD3HfuHY2FKAtSkShbGhu3COt53DR5kC8wC78sguPIBnIOxkURQ+5jGUxq19d1SGJEP+c5TV83zhsNNdfhnHPOSbbccksn1A5HxzA4+YdI8ahBmvegDYUcKyu7SEIiSZFEvRgUeT8ykaFsaVqrPpEoCDbXgklTVn1sBzNRWucTrifRaenVmXBsaV7H6Eqe9FWuPwSnbUeZLLBIsi4zSoKlXyALwHtcJIrFF2SjbjLBohdiL1/gPi586wDPtbTAVSxEitr1SULEIj1GCdE40M8h1DyzWTsiBBMg1DwXZ5xxRnD8cELtcHQP3RudKqqqmEeqIXhEr+SJLKIyrkIikVq2Q9naZIJAQ92H6EoVJMoSbKI1KostDTbEkAgmEycFdLo4aTYNa9EIsWEh0oUFHASJktU0zoH7niZRnIeilFVo9NNgEQKR57nOKrThyAbPMLkOSq6rekckz67PeqVbCRHv68K9U00D+nuWNIs+jyczc84pp5wSCpo4oR4AFjWUqOgKk0bRe/bC4CRnDltVUVXlLNiKJJpAtIRBm2SvIhUSeT/RGwgketKlllrKB8U/getsI1Ha6qVBpmmACRqpwFDdAMqA6wi54VoSuVM/7RpYdFoSBfnQAgyCQVMymzT6Wc9tUfAcQ6Zxr7Hl2h3jgZyLXTiuf5ZbRdVg/GSxSENeliUhsnZ99I0YrRxl08jcQbGvdI4ICZsQaiRcX/3qV0MFwNjOweFwFEfvSXVepDpv8COREQkDhR+yEhLThFqJdRAEt+IaDQiSHAGkL2SBw+tc/9tvv712q76ug4Ub143tZFxRVlhhhV5cI54pZB80qhhmJbPxHqJ8imKXiVLy/LJDguwD8gWhnoagDwnSnucVKGl692uUXZ9kInXscJQFidwq2Q6hTierc12RfLBzcvzxxycf+chHnFAPDR5F7h0GRao1yKZJNYMz0g3IM6bsDNzjEhJt1IsBn0Gz7QSxroCJkEgr1xC5ByS7Cau+roNoHQs/CCe7IeyK9HUStslsWFrSZ+gbRClpkhCpfxA5zbsWVrMPKedZdYlRMRA0gFDHpD23dn2MISzQtQBL73C0ZdfHMypCTbCFY0hH/nH5IDmRUtq77bZbb59lh2NIGKz8A/A6ejYSliBwRK8YiJWQyM8sQq1CMEzyRL2YpH0buRjY7uR6MzEy2UhfWLdVX9fBNSFCDbHGlgxSPRTwbFFRk2ajlDTrGKOKjnaHA0LNAo730m/kMe8YD8gpixGuLYQ6xlL02r0YZ9fXpNMMx3DHHXeEXSX6G99pwQKRwi7kRBx99NHJ3nvv7YR6oFjijylajh5hsPIPRa8geQyyEGp+2uh0FqG2pbOJlBDZ9kl6PGxkf5TVYBmrPpGoLiToTQMicfQ5COXQi+Gki4ooSkn/QJdKk1sEjeebnAcSI3lW+yCVaQJcN0hf15I5R9n1yWmGcxHBrlpixnhFhJrvhlCn5YD0RazyCMocccQRyYEHHuiE2uHoEQZFqkV+IcbodxngmHiJmDJZj3P4IJEKcsN29NJLLx2aD4jjIUcVCoAQMSKyX5QIj7PqA0SpRLC7MvkXBedLpJV+xnVLbyMPGTyfyIJoRCm1w2HdIgCRVvoIi5K+L8Cq9D3nWUJDHUORnmnt+tJOM1qAVVnxk3wcCDXzA4tfFn4WkPqtt946zCEHH3xwcsghh/j8MXS4prp3WGKRtBE9BROpNNSQMLblGGyJJLCFTkIiA5sl1CLTdsAjQkp0ARDxIvLlGA+2QJlEVOKdyaaKyH7aqk8LISLc8sLuevEYtt+JFjLRZxWLcGSDZ5tFM1FDCCEkR8OcqvbRF2OUM7QN5HD483NtiFB3lVCPAn3B2vXxbzBNIiwLfuYWiDXzA0Tegu+AUN9yyy3JAQccEGQfvmsyXNBHfvzkr5I3b3xA7d/1wys+l7z2lS8MgS1H/RhUpFqDJ5MurgmvfvWrMxMS7WDHa0gW2DaEjBPV9lLGxcAEgw4YjSHXmmhiVZGZUVZ93Csa28AiUDHabeXB9jlIjaRJjmLkhmghhBoXEWwatQCTW4Sq9nFNtcPRpf5RF+hzui4Q6r7miYyz61MiLItyEexR/cMSauaVNKFm/Ntuu+0Cod5zzz2dUDtm0IhPtaNRDCJSTWOrj6gfYNBD7zYuIdG6BjDAsv3eN3lBXWCrkwg1Cxh2AyDVTYB7hqyHnQUmSb4fQE5FsGO26qMfEimkv9LniFD3MVpYByAvuKNAcvC9xsUnDZ53SJMqOqp/QCDVP4hWxto/6gLJnnjG0+cg1EOVyaTt+liQgbyCROyCQKhZxGX1OYg2hPraa69N/v7v/z454YQToutbHOPcuXOTc889N4w7nN8mm2ySzJkzJyQHl8FVV12VHHfcccltt90WFq8sRuhPH//4x0Ok3rF4pPotG9Ufqf7BlR6pbhK9J9UqHY5FG4SYAYToFS4To/TTTLYUdGFg8Ep/5QBh4ZoDrltb3t10bWvVx70HsVr1We05xJ9FnHspF4N85nnes6KFZfoHz7ktONPn555rIAcVpFPsigyVUOf1D0WxWbRprqB/MHYwr0CoswIHLO6ojnjllVcmH/rQh0Jxl1jGGnuM6667brJw4cKQAL3WWmuFHQtIMWMkr5M7VASQ6X322SfMo7Nnzw4LDK4PEXqu5ac+9ankqKOOqv2cOkOqfwKp3r/27/rBlZ9PXvsqJ9VNofekmomWB5tBkNLhN954Y/LKV74yRBXyCLW1L+u7H3DV4FrLojAmHTDd3Fr18W8Qi1UfETIWcURRq9SeDwEqJEQUOstxoWj/kB0b/YOkZGDLYtP6tGvAOROdpvgIhJqIoi/i8mHt+uhzAn2COYW+ArFmPiEo8773vS+59NJLk5122ik59dRTo3yeSZaE6EKCIf/KQ8E7e7/99kvWWWed5Lrrrhv7OVwTSDRzKtFq/k64/vrrk4022ihcEyRtRUl6n+Gkur/obwjmTyAqzSBHJEEkGrKsSn7phEQVJuG9kHAGS0exCRo9JolOJDlBqGNKBIvZqo/JhsUf0Va2W+l3vogrBrbqWYzQ/+hz6ap1RcH1hlDQGDOyymKzWGQ7W/2jbr/jpp5XFr5cOyfUxez6eEaRfLAwp7+ww8G1/OhHPxoW5e94xzvCQoUo7w477JCccsopURJqxp158+aFfyNLsYnd++67b3L66acnCxYsCDkKLLhG4dZbbw1SmI033ngxQg3WXnvt8PpFF10UrpuTakef0XtSzYQBSVFAnkEP4nzDDTeEiRGnCCZiiDdRVhJUeA/boESoHONhi+EgWyCZM/Yt5Fis+iD3EGomZrdpLAfuFwtgCAvPa5UJxLYsNpIS+oX6hxJh6UOSETHOdOW+Wd0+x82167PEpUrQF3heIdQsznleCcBQoAoZBdrpc845J7yXRQp94tvf/nbQKMeyayfcdNNNQd7CebCoSmPbbbcNz9fFF188llQXTWqddNHbV3iiYv8wiJHUJiSuttpqMxFKtKs0JmVIIMRmVGESR3a0g4REBueuFsNJEyhLsEl6ZKFlI5RVWfVJB8w1zEusc2SD5GG2MyGDTPjsQNQFyBEWmjQlwsoPm0gvjfFDMqKYdPppMAbSnwkgsAhhrHNCXQzsbiIzQhrEboYirgRk2NH8+te/nnzsYx8LpBrJIGMGyX80RbA//elPJ29/+9uTGMAOD2BRlQW9DrEeB+ZV+tM111wTottp+ccVV1wRrgmabYejz+j9aArhQxetqAHRJQZEGiSayZlJUUlKbGGxlQdBZJL0LdFiUda+aM+zrPrkFFGlVR+SAvomJA0dcLpQhGO8bp/oGIS6yQWwktRoLIQgWFqEEa2kQaj5vXTYsYwhEGockPA/h/iTCBsr+Y+VUBM8YHeL6K4FzzF2eRBqpA4XXHBBCNBwrS+55JIgffje9743I0GMAexUgDyJo15nfhwHovAnn3xy8p73vCdE7NdYY43w91TmvPnmm5M111wz+cY3vhH9Dmbj8Eh179BrUk0EcP311w/k6J3vfGey1VZbJRtuuGEY7CBCJOkcdthhyYc//OEQJYQgSUdJU5KSion4gPDc0tlEdvsaZYVw2JLYsmKjb5AhT7NWfchFihBs9Nu4o0i24DKj4kCrqlLTbZfP5l5DJmh4YkunL5JN4z1E8Nqu+Amhxh4U0u+EuhyYP1TAikRE7nXaepWkvtNOOy3MN9/5zndm7jP6a6LXNCQjMVmyKlk7L/dFi1XVdxiHbbbZJvnud7+bbL/99kFaIjCvkqhY1p7P4egiek2qIXxUr0LT9s1vfjM0BgoiCQyObNcxEeIjCulmoCTiChnXpKgkJVXbYnKk9bUwQhHY6pJMzpCFvoMIJTsXtLQVG5FTWhGrPkVZWaBBqOuULfQJXHPINAsZ5Ddcu9ieQavTZwwRuWYMkYyI+60+wnk0sbPDtUMqw64cEXRyHpxQlyPU3D8CB+kCVhDqgw46KPna174WEvLmz5+fS1K7XuF1HL7whS8kBx54YAheHX744UEeg1UjgSsayYxE7R1/xBINaaq7vXfcPfSaVEOg8cZk0CMqTQRBLa0bgyQp2QjCw9YVTRpbiCTkmgkSUkT0iQgmk2OfbLbGTc5sGZLkxDWCUMeWfNMEFH2kIXmxVn1WAmCt+vi/7MuYdOl3MUWtYu93PHNsJXfFqYLng8gcDWKmREdkRPKFZtxQBLuugkSQPhbAjF/0Qwh1bMVHYgX3TTaXzAU4SKUJNRppHDSwpCOhr0vEWcdKYCkL8uUusvDHdm///fcP49q3vvWtmT5GnYLzzz8/mTVrVrAXJJJNAMvh6Ct6TaoFBkK27NiigyCzYibqTLQanRzyDybB9dZbL9lyyy2TzTbbLEQa+TursUVXp+iTyh0TfWKiZ3KEZPeVKNkEJxYrEJu+nmvVVn1MMPQj9PpDr1hXFraqKc8kpLBriXUsqLTDxfkwbmgcYZFKo39AeiHYWoRNC74LmRHfw3dDcJxQF792JOixGGLsR+JmCTXj4Wc/+9ng57zqqqsml112WZA5dAkqVsNiNQt6nd3bcTjjjDPCT6ompvsYfRlpCBF/khadVBv0u0zIINGt2WkKEE1873vfGxJGSKIgkYQJjKgi/yZ6jWn95ZdfHiZtspfZxtp8883D+xhQeZ2qUzQlsUGa+EmkmwRHyJUi2H1xEOFcmZwhAixGIDaxRwpjseqjfxCdhlCrHzJZi2QNZZdj2n4H0SShs+uyBQgHiwMaUgLtcnCOLBxoes80fukihXwu4xHFhJxQl7t2jOuM9VToTBPqY445JpT2JrhA9LVKO8emwDgOSDbPgl7nuRsHEfC8nUu9jozG4egzBkOqybyGUEOs0VKLzLA9u/vuuye77bZbmNzQxKHBZjuLv9l7771D5jIE+13velew1WKAtUlsdnuXSUwuEUQlFcHuaqEItKGykeLcsczzybkY6CP0CSREkoHQP7Ks+vq0CKu6wmRf+116lwMXHSVJW790CJucRIr0EUgh146/7+u1qwuK7nMPdO3ShJpy3EcccUSI/GMV11XvZeY1yC6yNKLIyPkskG2ALbbYYuxnca0AxV2ycPvtt4efBBscz8J9qvuH3pcpt4AoE4EeR265JExqkHAi2FdffXWINPJ3q6++eiDYyERUmtbCukSIUCmCqQg2k2gXCDaaOgg1kz0WhEz8XTjuGECUmmtHJJJtVpvglLbqg0ACCJMIdlf6SB3gmZF9Gc9Yeut9KNdAfYSxiD5j+wgEO8vOUTpg/oYoa5oUOkaP++jPqV2QFd3n9yeeeGJIxqOgGJ7MIpNdhcqUs3tLmXIt2vLKlKMfpyHzIFIvsNuLxINAAoEpdniFCy+8MPwOIOVCmz508Fw+9pNfJausu1/t33XntV9IXuNlyhvDoEj1JODyoIEkaxmCTWRCntZo6YheQ7IhnVkEm79FAsDkSNQXoEVWBHtSn+O6QSSV6AWTNBOI2yGVW4ywdQqxJpFxVHQmbdWnPjKJVV8fwOJVFeu4bmn7siGCZ5A+oii2+gjuJ4pgIxdhrOKZ5b3ogNOyBUcxh5Qs/Tm/P+mkk5J99tknLJAh1H0YExmjKEpDnhGLMIqz4EvN/+lXlFq3ZcVx9fjMZz6TfOADHwgWgvb6UJKdJEVAYiJzItI3Ra8h7xgHOP5Eqp9okFS/2kl1U3BSXQJcKjw70dAhEeGnvD7ZOoNgs4LPKoIicq4ENmlsmRgVwWabN4ZJkEgNERsmFfR0yBYcxUB0lSgr0WdIDeSmKGwfgTxp8Wat+thq7utWPucLoSbZEzLNpOxYHNbOkT4i5wYihPQLItxOqCf38M5ySOH3FC7ZddddA8GkFLmS/Pry3BF1Pvvss0MiOgs0yqrPmTPnOYVh8ki1rtOpp56anH766UGTztzInEa1xT322CN8puOPcFLdXzipnhBcNgYjEhsh2NgFMdnpgUEeAsEmyptFsNEoK4It8kRCkrb/iU42TZ44LnyA0YND9knCcR/l4mC7XqV/WYxM49/NvbBWfVq8pa36uuaEUSS639diQlWDPsJ1YxwhuiiJiIpWKYrtybDFqkyyYCU4kibUVEn86Ec/Gog0hNoXe45p4aS6v3BSXQG4hESecQ+BYONXyhYsYKtQBDvL0krRb0WwFXlSdJIoNhNk3QQbGQJewEwuJFhCqH0yLg6iXES7ILlMzFW7AUCeZMOmxVsVLhExgP4PoSbKymTDNrSjvP6cCLWqwjL+aGhXMqwSHT2C/Vyb0Kwqk/ye8fyDH/xguLZIPtiFdDiqItWz3lE/qb7jOifVTcJJdQ2AYBPRYEAmSYNJDhDhgGCjwcarOItgK/Jko5MQNbv9X7WtGFIFMt6JtDK5EGV1y7xi4J4RJcROkUUIxQ/qdvEgmiuCjfZdj7Ct+NmVBRFyF0ghUVb6HcfuKE6oWYyw65XWn/NM8zzTT2wyLAnTGktU7GqI4JmhiBUe4Tw3BBHShJpE9Z122ilcL8ZzdlAcjirgpLq/cFLdwMSH4T0Em6xoEmEA29sQbNrb3va2TKIMwVYEm2ie3f4ngl1FkQgWAJAaPp9oDHKVvmp265yY24ruq+KnXCLYcQBdsOrjeJHLcB2JEnbVmqwNkKwIoea5HefMQ59g8SUdtvI5rFafxXTXPcAnKXnPjhLPrZVR8XuKuWC/CuHGWhUnEIejWlL9y2TW2g2Q6ush1Us6qW4ITqobBNGim2++ORBsLIjYdgRsd+MFSgQb79AsnSy6a0Ww7fa/9LVMjmX1tUTCIdREPpmUsxxMHEkuUWGQIqmTiRlS2HZ0v0tWfRwjyUwQOUhNF4tntEmo77zzzvD8kjjHs1sUyufQQkylqDWWSIfddl+uExBqXCmI1LOzlCbUyPhwsmChDKFO+zc7HNPCSXV/4aS6RQKEIT4G+xDsH/3oR+F1JjQ8PiHYa6+9dqZOFhKsCDbb5wCiRKSPCHaRSRHNJVFCjqOsS8XQAVlVCWOuNVr52KJ8o6z6tAhry6qP3RoGePoopMaTYYuDKDOEGjJchUMKORzqI3YsYZGjfoIFaF/AOEuxE3Zy6HvpcRLd9HbbbRfOGd9mrOEcjtpI9VoNkOobnFQ3CSfVkRAgIsYi2CTPAEjPZpttFgj2euutFwh2mgQxyTIhQrClr1X2v6KTaWKupDqIIPZRvNdRvsIkPrXoLGOXy1irPhqLsras+tidISG2Kf15Xwn1OP/zSfu2regoKRGLHvUTorcx7HRMAqLTRKk5H3Ja0oT6hhtuCEVKiFxTj4BCXw5HHXBS3V84qY4M3A6SBkWw8YsGRFY23XTTQLA32GCDQErSk5smRelrbQKbItgQaiI1/D3b7kySjvI+yl2tMCmrPhZh9JUmrfpEakiWg1D3KQJaN1gIQajpe1Skq9snmR0sxhBJiVQZ1hYlIpod+4JSQD9NMjHjHYQ6HWhAlodDE6D+wNvf/vaWjtQxJFK96tvrJ9W33+ikukk4qe6Ah6o02ERIARPDxhtvHJIc+Zllk6Uyx5AnG3UCeFDjtOA61vK2byxc+uSj3IRVn00Mo+9CqOmDjuKLOQg1P9voe6oMq35idzqkw64iaboukEjM7h/jJHKOdH+m4h85Lci6qDdAhUGHo044qe4vnFR3BCImlEqn3XbbbeF1on0bbrhhINhUrMqyyYIs8UApKUmQQwRRbKKHjvH6c/TTXK8+og6rPj4DuceTTz4Z+ia7I31OgqsaEGlIH/cGZ550hbumYYsS0VfkShSrZ7rkRoxvEOr0Yo6y7kjsuL5Y6DGWOhyNkOrHIdX71v5dt994bPKapZxUNwUn1R32RhbBZuuS15gw1l133SARQSrCJEdiDv8nor3LLrsELSaEiQi2dYgggqhy6S4JeRZcJyQ4LFRwARiK/pyIvJxEJrXqsw4pXDf0+32pANkEkHoQoYbwMQnHmEwM6ZcO2y7E2AWTk0hbunkWcuz0QaiRfKQXhDzX73znO8MigXGUMbNrci5HN+Gkur9wUt1xcPvQSTMpIBFZsGBBIDNEAyGBTCpMGvvuu29yxBFHLDZp8D7pJpkUpZuUBRsku8uJSVVFuYi6EWGFUA4RLLysvraIVR9RfXID6FexOqTEDHaVINQkJ+KR3IUqk5KcaSGmsun0E+mweYaaGE8YEyER7OQRoU4TasZFCDWylm9+85thp2+o45yjPVK92pr1k+rbbqqOVLOInjt3bnLuuecGWRXBEnbI58yZExL3i4BnDh94Kk8vXLgwVHEmIIgL2Xve855k11137fRuppPqHoFbSWSVIjMnnXRS0AADJgvs+YhYv+td7wpkOT2BqECEEthkwcakpAh2UxNiDNeRCD+N80cD7PKYYlZ92unAcpD3vfSlLw0TSFcS2mIAi2AINSQVQs017Bog1Nx/RbHVT5g8FcFmQq6jX2DZSBSaPgmhTifEUrAJQs0C4Oyzz0623XbbQYxrjnjQRVLNjhk74RBhFvlrrbVWyJNBisrzzOtLL7302M855JBDkqOOOmpm93e55ZYLY8RNN90UgggkCeO+09U510l1D3HKKackH/3oR0P08CMf+Uh4mK6++uowsdGRZ8+eHQg20RlWl+kJhS6hCmw0VWATcYJk97XEsZJDWT1z/SDUsehDu2LVR7/gd9j0IfnwCHU5Qo2Gmt2Avuj36QvkdUivj6wFIAWij8jSsYroFFIjdkgg7xDq9MTMQpnIGsT7zDPPTN797nf3chxzxI0ukmqRYfgDHu6SiR577LHJfvvtl6yzzjrJddddN/ZziHQzb+y2226LuRjhzoOzGRHwgw46KPnsZz+bdBFOqnsEbuWhhx4aOj4etlhD4RYg8sN2CzIRHgi2ccBqq602Uy6dv8ki2EyIquYo4gTRVAS7S9Za46JrRLg4T9cAlwP9hMgkhEYyImvVR1+BOPn1zAdJf0SoIdS48/Bs9VXaop0OOc7IW19R7LIJsYAxiv4HOYdQp7Xc5KFAqJF1EXj4wAc+4ITa0S6pXqMBUn3z9KSagBzjEc8rO+DIIS2YK9mdvOOOO0L+wqQ455xzggQELoIFaxfhpLpHYDKmGiPkBgKdFeXidjN5o2nCqg/iLVcQHhTkIUSxSWjMItj8LZMXTcScSUwRbJwiukiwIYI4AbD44DzYdu/iecTg4U2lP/pDmjjF6hARAygmBKFmYccExfUZAlikS4fNuKXpSAmxSnQcR37pZzj05BFqkhYh1EzUX/3qV8MOnhNqR1voGqm+9tprQwE6ajPgQpYGmurDDjss+fSnP50cfvjhE38PRem4NswN2iHvGjxs1CMQBfzWt74VyEtexj0TCRMW25477LBDIEEQayLYeLR+5jOfCY2ODbmmYeXF3+lvaRAnWWtBsJFL0DgGaWubqtJXxcSOBzjnw3YUGi+fcIuDRRmEmutofZQpkEOzVn0ksEGibCnsSaz6+gRFf9CrozEksj8UcN+xCaQRFKBv0Ff4yeRNQxMtgk2fST+bvBdCzdhDlCw99iH1INgAoZ43b160hLqKJDAL9K5HH3100KeSuImcjWAJVSMPOOCAWs7BUQ5LdCSmyfMFkENmQa/fddddU30P8izQxTwSwSPVjgC6AeTnqquuCgSbSDeRI0AFN+QhEGx0nllEGWIliYi8a9n6V9Z/rMUhLCFkoZAlgXEUkyywEBvnUlGFVV+fwM4ICzoRahaijmcTp7UYU9SKSLTGFEgn148dJsYWCDXE0YIxCas8XHy++MUvJnvttVeUz3dVSWACgRISMCHqEB7INM8b8hier6xoo6P5SPXbZu9T+3fdessXkz/89/8NUeYsFIlg4x7G87PPPvsEDXUW6Wb8eutb3xrmg0mBTzz5X3vssUfy5S9/OekiPFLtCGCiISKE/IPGJHbNNdcEgo2byDHHHBMaA7sINg+QCDYDNb+jEf1WBJvEIRrvk7a2rjLYk0QIITQihDH6AHeBECJZKKoBZluP60xLW/UpMjnKqq9PgDSqSirSq6F4oBcB4wULDBqLehZvkhMRdaXxHsg3P1nspwk176VSIoT6H/7hH6Il1ODII48MxDkvCYwaA0WSwADnSzSa60GQZI011pj5HddLrlCOCPBsoeOowS4uyHPkUCDkN38KqE2Cr3zlK4FQsxv1yU9+MukqPFLtKKQ3vv7665Pzzz8/EGxIMmCbXwSbhMesSDSRErlDQMLshKkt3TY8KbVlDCCEQ9GwVgXIMBFCSAoa4GkjrEWs+rK2/rsKzhVCzflAqMlFcBQDi3aSDtFJC1xHrifBgO222y70Fyol8ozjz49zQax9p+okMCLzRKqR8/FvR8SR6rc1EKm+9YtTa6pxE8Om9+CDDw4LwDQIhrAbsuyyywbLyrK44YYbgvMHXINcr6233jrpKtoPFzqiB6R3/fXXD+34448PFRwh2BSbQaNII/JIVAiCTWREkWii30sttVRoTHgi2PKvVdY/EeymktfQWDLAsAhgAoOsOYqD+8ckX+X1004GLW3Vh76UpoRYbf13Qa8/akHC8Xv/m4yE8gzT/4hQ83/GEiZj5A3okrHUY7z58Ic/HIhArIQa4M8LoWZ7Pk2oATIOnjckeeNINc4maKjZMXRCHTeWWNSMpprvmRbaOZEdZhoyO3h+areoCHDcIjjHc4zko8uEGjipdpQCZJlCMjQ0Vmj+RLDJqqdBekgMgmDzPkWimeiIbtN4gESaiNpBNJj4iNiJOPH+qoFOET9MPhv5ipdkLwe23cnQ5p5y/SYZRMdB/YBG0qi2/mk2IRYCroTYGOREZXZIINRcP/zeHcWhaC6wEX4S+ZBNnHfeeSHRGmkN+PrXvx5e144aWuXYqrVVmQSGRIRdHwIbyKuQ70HakWjhaERyuu+KOMpCftJ2d8hCry+11FKlPpfk4Y022ig8r7iGoKXuOroxEzmiBJEiNIC0z33uc2GyE8HGB5ZGRJFtWCY1LHmIREOa+Kmsf7Z8iDShwYZg09AFEsGTF/a07hBEPyHTbBuj/2KiGrLjxDRl27luXL8mEgrTjjPW49jq9bXbAdGO1apPtm8sALh+Qy17P43tIGMMz3KWZIbxiPGHCZrJmYjXRRddFCRr7LDR2G1DtxkT2IUBjIVZ0OuMXePAghcQLGABgU7bgqg914ikSEcE6Ij4FgkSyNPj6/WVV1658Gey20RiIj/Jd8COrw9wUu2oBBAb/GFpVEJiG5btWCIlZ5xxRmiQCBFs9FOQM0gTkSObvEY0D4LNT2QADz74YIjoKYJdtnwpkRsmGx5eiDpZyrFFq2IHEQV0c1x7CGG69HNTgMiPs+qDbMkhIpaFkyQzsn2rI8I/BJcZuaSkkzrJ3SAKe+ONNyYf//jHk+OOOy6MSZBHkv0YjyDXZSNpXUsCsxF6iDVl2LHl4znBmo8qkiw2kL9NYtPnGCbWXHPNMAc/+uijQbrGM2jBQg1sscUWhT6PfrrxxhuHz/vgBz8Ydr37AifVjsrBZMbKlsZWLGW/RbCpmERjwGewh2DzcDGhQIggHXhU0tiylP2aiogQbYaQKII9LlrKZxAdhHQRxWQlHaO1X6wgKgiZRjbDPYNQ1yHLmQQQZisnslZ97HawGIvBqs9W+oNQu+SoPOlUYZws20EWV1Rho0DFhz70oZDjYfX2jCs892WiaF2FLCoJTiDF23777cP/WWgS2OCZuP3225MTTzwxVN51tIyO+ESw+7f77ruHPkN5cSRVGk9ZtBIwoEz5Kkbzr3wrFnHkOQjosgmuMSbSP0mAjDnnoSycVDtqBQ/LCiusEBoZ+BA0EWxWtzQINdtAEGyINkSIv4P8Qp5pTKgQJQgKBNvar4lgQ1bswwnRwhGAbWOi4BSx6WpyW1uEGrkHejmiFGy5xxrhj9WqT0mxeZX+HMUINfeURXq6MA7P+Pvf//4wye+0006BSHbtGa8yCUyfxU9cUNIgKgipXrBgwZRH7RgamL+RTmFUgMsH8iIkSbfeemvYGUTuacHYyyKOMTAtQbrlllvC/E4QjYVwFk477bSki3BS7WgMkBgeRjwoP/GJT4ToJ+SahvbxwgsvDFFQtNckFZG9ToRFBJsHl2bt12hUYaJBzlUunYcVQs1EhVSAzPo+rYbrBtcYMohmma12CE1XkgE5Ti3G0n0FGQutCas+kjq5hvTprEp/jtGATEKoybnIsr3k9Z133jlYx1Ehlkm9i7tQVSaB6T18ZlafprgV4FlwOMqAMZPdIKLOyIqQUzE38AwiLcrLCciTKBEo43Py0FVSHY1PdZUlWpVJKk9lpARsQfCa21fFB7ogjg6Qa5Ic8cSGDBHde8c73hEINttFRKnSEwXvQ3etao7yNxa87Hh5MNixNceOAEQG27IukpU00lZ9yAYU5bZV+qqIdNKf0fEzEUGoy+YBDB0shvFl5nmm/7FAsiByjV3et771rVDoBElZrAmq4wBRIZDAwj+r0iFz4GGHHRYSuZjDRoGxk214qjKyqEvjrLPOSt73vveFXScvAtOuT/Xjj/0yWX3WXrV/18I7vpQs9ZrpfKodHSPVVZZoZcsBNwoGJ/6GLVc6Ew1yxbaDVy6LF3RHCDLkGpKNRRQTKKSOfoFEhIqPTLJposzfsiBDd227NZFCRbD7VECkDnCt0aAT3eVZRLbTte30IqB/WKs+bbFXYdVHZJE8Agg1409bSZ1dBQEWCDXzAjZw9MP0oo9kRAgiiVEQ61h0/tMWf2F3LZ0EVqb4C88vQSSeX/og1SizinhQofHkk0+u5Xwc4+Gkur/4s9hKtFKNB69RdDpf+MIXQrSMAaAo9t5770CoiV6g5+GzMBfHYonPpoa9I15AeJkUmDTRSRJtIZMdL0u0XPvss0+wViO58YQTTggERgSaSZZCCUzGRGKo8sh2J6QQOzgmJSI5TDZobpXU43h2O53oFRMyW3kM/H0k1Naqj76Epy+NfxNRZncLEoPulEx3+mB6ByQP/3975wJt5Zz//6/LzJiL5bIMJhL6Gw3DYFCpcYlKroMuIkoSUkSkIvcot1JqSlS6UD5p/xEAADMWSURBVDTTCNViMEihaVaGjJVqjEn6DWMGM1iY+q3Xx+9z/k9P+3T2OXvvZz/72e+X9ayTffbZZ5+9n733+/v5vj/vD+cZ5xdC+rDDDpOgrie8dl1Qc/7lEtS8l/NaZyeT9/dKFtTRJjCgCcwXeHU1gTVr1iwMHjx4o9tiEchnHO+J3Bb9JA5+WLbUOfcvvPDCRP42UQd8dpX6ENVVqS7miFYM8YgB3lioWEa3DJmuRUoAgoEPSX6nqLyte6aK0eiI4Pbt++bNm1sFmstoqMP2g6CJ/iwNT24R8Q8t7CW+7U9VMqsCMh94ffD643FiIYLArNaKPueVJ85gJeP8iQ4m4pzJFdVH0w4Ld4Q571VpifOrNEFNpZodkrjtj0UwgpFKK5Gc9GBkxVbD347VjWKS79ZGm8Diu7XYQEhW6t69+ybeUxbH9KMgovkMbNGihe3gchssSkhwGDJkSBn+SrFJpfrnl5b8d728dLQq1QmyZSWMaAXEVF0sWLDA3nh5Q4p78KhmsFXIm8q8efOK+BeIJHBRQ6e/e+VpcmBHAjHIaF7EDx9IWEaiFhB+ls55r0qyI8IHFOcECyyqkVQl2dFATHGOVBOIGBIBENQ8RjSTVqugBsQwXnyEMRNB+QBk0cWijjSUF1980axpNDz6Ag27GoKaZkQsHxLU9V/U0ZTIuUhKTy5BTYMzgprnBHtYVgR1tAls6NCh9nfxHoeopgmM97d87Y9eLOAzbsSIEWZl4r2RHgmq3XyOSlCnBMaUry/9USkDZrLC1lka0ZrPbdEhns9tifSC4KMiTcYlAofKDAkf7Go8++yzVsXhwI9JkyM+bD6oXSgSN8XBQs4n9HGw08GBf5sPIxZmlTQCu5CEBUQN28ns5oi6o/o8Nx2rGSKGcxCrB0K80u0I5dit5BykOREPcDxFAEFNox52LxbFTzzxRCazvjl/brrpJjvqwt/jaoNzcuDAgXYIIZJj6yyNaC3mbYn0b5eSS0vONaOHaWqkGs3l2ECwiPDhi1+fA8GIuEZkI7bd6hGd0EeVDMGETcQProew9hHYac1pLmRKHWIxV0OY2HxUHwKbiWA+6Y7zhwp2qaP6siioWdzRSO7xcg67TdgVmLiGpYv4PE2jFNkgKc+zStVVJaqLOaK1mLcl0g1eQ4Q01eqpU6fWVAep9iCeOai+PvPMM3Y9/Jdsh3JQoSZBhJhFLEcusPlZcl453FfrVUkOBBIC20VTJQtsrAwkDWB1IQNYPQb1g3OBSjXvJVRNsc14HjaLe45SRPVlsTGW920sR/EcZgQ1r9fhw4fb63T+/PmKRBVCpJqyi2ohGgL+QJI88EfXJlYQ2jTscDCWl+tT2UZgU/nioDLmAptKmOcxu6+Wg2qaV7CpTtL0Q8IDHm+qlginStry52/AR44wRKzExz6LzYPYw7PPjhcJItjKvOmVams0qo+8ao5iRPVlTVBToeaxYpHrQ0mij/GoUaMso5mcanzBOk9F5lAROXNsncURrcW4LZF+WrVqlfd1qRqSGMBBHBUNsghsGoL4fw58swhsLCKIdRc+/CzWIQ4ENlVrBBPi1PNgPRmCI81NatxvegpYPCCoVfmrH4g9GhKpROca3e5RfR7XF/Xs01zL4ZYiTxKp5B2PhoDdiF0SBDUNePEmPB5jFsGMRaYXAjtXfJqiEEKkka2zNKK1mLclsgtimUo3B9UwrCQusMePH28Hgoe0GAQ2aTIufBDYJBNwUG2jao1g4ivxa2SjI7aoYHMbacopJumEKX/8LVRXtbisH4g9nl+yqFmMIKjrqjhHPftRSxHni1uK6orqy6KgxjpDdTqXoCbhgwY7qv7EwpFbL0QW2UI50pmj7KKaxAaobWSqX47vM8nbEtUBFVsf/nHnnXfaljRNjviwmTjGQVWRMen4tJn8ibBGDCFOae7j8GQILCIIJkQDFU0qll7Bdk9/OUAIEgeHaENQl/O+VCKIPXYksHIgghHU9R3dHrcU+Y4Hux0cPD8syFxgZ+05wr+PoMbPT2EjnoXOY/zggw/agCcsIQhqdo+EEKJSSNXwl0JHtEaHvyAios1XGv4i6gPpDpx3LrCp8AKixwU2qSMIpXjCA+IhGr2G4HZ7ko9LTyoSjJc3GcpEv9HAi6BOU/W8EuAx5PnnfYOGQ96j6iuoN0d8QeY56ZwjiGs/Xyo5SYS/CR8/77+8DxOdFxfU5M4z6Y9FB1nzcZ+1EJka/vKXD8IRP+tX8t+16LUxocleP9Twl4TYMksjWqkYdu3a1YR6nz59asQMsJ2IwOnWrZsEtagTfK+IJxqlGArDwQQzPuj58O/SpYtt6TOcgUEUnLe+PkVwcY4RU8e5S1WTihsLu9WrV4fFixfbyHWELr7SUq1ruV1+BweijKEkEtT1fwz5MEJQs2NRbEEdjepjB42pevwO7EWcLwyYYRLewoULzXriEx4rTVAzQwBBTdEjl6DGfnXRRRfZ3/30009LUIvqQGPKM0fZK9XFHtFKpYexrOTHsoWIkOBDEVFEbBO3RbVJiEKSH7yCzQ4KUAVu27atebDbt29vto94ZZHqN6LIfbUs/gCh6xXsXD9XqF0hV0OdqBueL947aC4kuYNdsyRj8XgOsUr4+cL7JFRSVB+PIYKa92UEc3QIk/+NpPEwKZW/h+FNFEyEqIpK9YHfFBRLyaI/3atKdbWJah+ccNttt1kVEOsGHxbHH3+8VQrjw1w2J6qBigjXofGMLVXECpFp/IzSDkSx4KVDJRFxTbWaCjSXEa+HNQSBTZxfriEgLpg4PxFMVCUBO0mhw0OiYpDXEWKw2iPcGvIYMtqZ54bngli3copXzpdoVJ/v6EWj+vha7Cp6MSxU7BBSLEFIxAU1w1zYPcSnTqY8uztCVIWoXv1BOOKABET16/eGJntLVFedqBaikuFlRFUYgc3B+HREBdVhmhtdYCN8cglsego8CztakfQKNgI7H1HHVjtChsog1UzEYJqEVqUJah776ATOtBCN6vvkk0/ssjRF9UUfQ9I7eAzjgpqovDPPPNNSaGhKjPfTCJFVJKqzi0S1EEWGlxRVYnZKENg0XeHvR9weeeSR1uRIHjbiJ5fApiLpFWzPXEcgeQW7ti1/fgfNYFhMqAzut99+qRODaSdqV0AM8uGX9scwGtXHcw/ljOrjMcRu57uEuRYl2Dw6depk1ic81HU1oQuRRVHd6qeXlPx3vfTGWInqBJGoFqKE8PJCoOEbxYeNmMBLjcggxs9HqtPImEtgU5F0gc04Z9/y91QIBDZincxsz//FLoUvtZLTIsrZUEcSRy67QiUQj+pD4EJSUX3e2EkSU222GXZxTj/9dFsoMimxefPmJbs/QqQRiersIlFdBt/4zJkzbSJb1DdOE08+4MOdN29eePzxx63pEssBHl6qkmeddZalnqghLZ3wUqOSyHOHwKZC51YPhAXiGpsIkWK5xJxv+SOyqWYDgprziP/ntkhNiOf/ivpFvrHA4fVU6Y/h5qL6fNejmFF90ejB2ho7Sb2hvwXmz58fWrduXZTfLURFiur9+5T8d720fJxEdYJIVCcEggdvLULYE07ID3711VdzJpzUBqN7hw0bZh+EeBCZOkZlirHbNLvxIUX1hzQKkV542eGFpVELgb1gwYIaqwdZ0i6wSbDJJXq4ro++doHN9TwVgq9qTsyPqG0mV0JFFqBijcD2KjY7G4D9ws+ZhjbGxtNmPHowLqhJymFKKY835z2JT0JUIxLV2UWiOiFcDLds2dIadHz4B1ncAwYMsDxjvLd1QaWbajWZ3j6WHYh5O+6446wCTn73rbfeWtK/RxQPXoJYOxDWeLARHC6U2T53gR23dCAEsStQWUUUsfXPuQEIGirYWETK3bRWCWOzedxyDSXJIsWO6ouOb69tOA7nKo26LPznzp1r8ZNChGoX1ftdXPLf9dKbv5KoThCJ6oSnRjIqnczghk6N3BwPP/ywWUCwABD1JioPXo6IHBZeDMRAYHvzGRVUF9icS507d7Zq9PPPP2+DaADREm1a4/YQiYgd3/JHPImwkQ+dBSq7PlkX1MWO6uPnV6xYYYv52sa307TYoUMHu212ZRDXaX2ci2HRywVFD4b78NombpO0E1G9SFRnF+0PJwDWDD642cqPC2ro2LGjiWq8toWIasQ54GkUlQligy15TwhhQUZ+L2KEZsfhw4fbwfU42JVo0qRJzc/jr6fiyuFNa3hq8Qqz/c8WPeKHCjaCietXq6BmgYsFp5p96PzNDBzi4DGIRvVhLeKoLarPByEhPrGO5BLUnG8nnXSSCfdHH3001YIawdumTZsaix6vQSx6kydPDk888UTeFr1c9O7duyaLXogavukjFhki3VlRGYEtevfK5sIvR1gXAiOwgSgwUfkgPhC9CJEHHnjAFktU0dwrjU8WSxGRZYMGDbIJpJ72AFSkqa5xfmEvojqCKGKB99Zbb4UXXnghLFmyxKaXUqGrFlhsLF261AQ1Ff5qFdS5IBmEx4TGWfo+sMOQHMLijEoXuyI8dghpLB+cOz6xMy6oqWAjqNkxYagXi8Q0P8633HKLCWcsetz3WbNm2Wvqrrvusr+/Z8+eDbpdXrtY+y644IKi32chRLpQpToB+ACC+GRIxy/nA6oQ7rnnHvtKhUVkD6wg119/vfnx2dXAD4xFhDzsMWPG2IGIRrxgEUEcuNChuoj3moOfIw3CUyHw1yIiqFZ6BTurja4uqPGwU3Vk90jkhmxrbDEc8ag+DuD8oopNldf7RHyBj6Dm+tOnTw9nnHFGqgU1f9+9995r/x47duxGf8sVV1wRHnzwwZoFRX12E3mNXXXVVeYh79q1a7jvvvtKcv+FEOlAleoE8Hzh2oSK58Z6c1pDGD9+vPn02IalaimyBVUzhmVg3eDDnZQX0hMQAmxRL1y4MFx++eUmnn/1q1+F9u3bh3322Sdcdtlllo3taQ9ApZvdDOxC3AZeT/6frX+287ErUbFDGLnHNguw/e6Cmuq0BHX++K4HFWnsMuA7JpwnQ4cOtZ0QBOicOXPMQ83OCtYJpiamWVDna9EDFrP1gdcfu0Djxo0r2n0VGYF+lwQOfo9IDonqDMAwBd68+eCaNGmSVSNFtkCwIH55rvkaBXHTqlUrS5JZtWqVbVkPHDjQKs/333+/xZghFsgwJ26Rqpz3J1NppDpNyggCm+QGzh+EALdFrjAH/2bRV6l9zVFBzWLDGztF/WABh4imkss55+cMhQGq1xMmTAjdunULa9assTQidgMq4ZwphUWPeQIshocMGWKLuHLhthvux+agyZ3r8VkihGgYEtUJ4FuJnkMcx6uB2267bb1vm8567B4IJewfPlhBZAt804hCBOHmoKns8MMPDyNGjDDfNOkW11xzjVk62MJmkh2CksYpmq/YtnfRw8/iuUbA48FGSFCd5NxCSFG9pqJHNZuqXiWIJeBvJFmH1xkJH15pFfW3sfHcI6CxQFC99nMGPzKLORr8gB0Vhhvhy2aRdtFFF9mCzgfQZN2ix7nGIhZP+tVXXx3KCTtXLLDvuOOOmsVDLmsZ6VE0PdOnIRLCK8mlPESiSFQngOdJU73JhV8eTXHIB2Lz2rVrZ41AN9xwQ+jXr18R7q1IK/XdQkfwUEVE8NBk9vrrr9t5wnlG41iXLl1MYJ933nnmy2bRFxXYeGWZLHjkkUeaiCJRBFHkQ4uwnNCshic7rQKbijuCmr+NnO/6vsbEN5BBzXMdFdRx7zALesaTjxw50rz6PO4s6Iilo4KNpzjaSJtlix5zCRDg2PLKHWHJwphFNr0U559//iYLG/72iy/+JtqN5ynqJxdC1A81KiaAR90R4ZULvzy+rb85+PCi+YWvbNfRwCbE5gQ51W6O6667zhoTienD/0rUGQfCgXOKJkc82eyc8HM+SIaDyhtVakQUTWhU+DhIKfEcbKqUafDQuqCmUk3Gd21VSLF5WPSz64HgRFDHYxhpYMRixHUQb25F47ocLOr4HlXuahhCxDk3evTocO6556ZmauSFF15oC2nsY6SZYA9ziOVk0XTOOefY614kSEqLEaLhqFKdAHgPiZ3Cl8pksTgkOAAfTPlAZZo3P26PKiOVISHyBcGDOMZjScWZ84itYRZ1VKx79OhhFWwq2XwQ+xAZ/1maYfl5miWxmmCnQHjzwYxFhai+N99803Kxy1WZpDLtgppquwR1w6DZkKxpstNzCWrODexn7IQwIIWki1wLKnYJ8n1/q2SLHtVgovN4jdx5550hLfCcTJw40Z4/dqtWrlxpl2PpookSC48+R4QoHInqBGD7r2/fvvZvxotHExVoLqP5BQ9rNKqJVAc+iKgiROFN/8QTT7StfCbq8UaZhqqgqEw4d2gmu/LKK80vTdV51KhRJpbnz59vAoHvE4mGJ5tt/ajAZrGIz5uFY4sWLUyMU4187733bAcGgY3gopqZlMDm9eWCGn94IZPwqhl2wXjuiNbjvYmvUdixQFDj08XugNWjUt+LimXR43oUTnjPJ62HSrUf/fv3t+uw8PTLkoSFMLtU7ODwuqZ5FzsIr0v6cbB7iYSRpzpzyP6REHzoEHlHkgIihAYePHc091AlILUjCuIFDyMfbFH44Fq8eLGlNpD6wJtiLqZMmVLSv0dkDwQRvmm27y+99FKbpoc95De/+Y2duzSacc5x7mIRofKI3cOnO1LF4yDpAJ8m9hBsIlQ7OXz0NWkjfIDXNvq6EPi9iBYiBLG6eOOcqB889zRBU9lEUFOpjoK3mKZXHmusBDfeeGPFCupSWPR8GmUu6EEgFrMc8Fw98sgjNoyGXgl2lCjS4HcXQhTOFhvS2mGUQagQMBGPLXW2yvGoHn/88bZtGt+eZouOD6ru3btvJJDZmqdiWBd6WkWx4Fyi0syYdHzYnnuN5eOII44wgU1sFykPuYQVuyvuwWaKISCoEdiIcr565nGxBDURgYh3UX94rtgJo9p66KGHbtK8x04AgppGVRZg7LZxLlQyJNxwLlJ9JzGHBt+46GZHkR2Q+gx/iYKQPeaYY8Kxxx5ri9Rywd/ArhINiyyC2Y1gMS2Sgx20v676e2jdtHfJf9fCVfeFJk13tudZlB6JaiFE3vB2QR4xQzCoYD/11FO2jYyYZrQ1dgAOttNzCWwWlohrDip20aQRRDACuyHNbFROEdR4WqkmIpBE/eF5QTzyHCCoPfUi+vwxCAWBSGIENrVKF9TR3UTi5Fgocl77386iYcCAAWbR4+92+Ns5SD2hWFIpohqwptDLg+2LfgqRLBLV2UX2DyFE3iCUEcDsmLCLQmWPjFsE9oIFC6zxiT4AqnmIa6rYeLJdYGMjwJfKgeeZCjiVUb5ycD12cBDY2KLyiSOj+s32PIKaiiI/J+oPjz+Cml0Dnr+4oOb5wiaAOOzVq1emBHUxLXqVgD+38edYJMcWG6yqmcjvEcmRnXdEIUSieBLI2WefbVUvPKT4NUkNIbKPpiiqxlT+hg8fbrFq0Y0xGt/YdqYiShWQ2DsENZVwvJ40OVJ9xipFNTwXiHquw1Y2W/YS1A2DpJaooI5nFfP4E7nGQBei4shfzpKg9vPxueees5HrWF5IwkFUs4Bk0cbiUAghNofsH0KIosJbCjYBttDxYDO50a0exNvhv2bLnH/nEmZ4or2CjdjztygEPBVsrB0IIG4T/yvpBQhqpRc0DBYxPI48Fwhqpu/Fnw+E9Ny5c8OZZ54Zpk2bVhQPvCgf3pvDfAP6d0Ty9o93V2L/uKDkv2vhqolhj/8n+0dSZKvUIFIDoopKJWOhEUA0sfXs2dOi1gqBARJYCKiSHnfccUW7v6J48NxQ6cP6MXXqVNseR1iTqY5QpmqN//rggw+2c8SFsYOfl/OF7xM7RooHQhqbB9vtDLBgi56GKyrUXE+CumGQM+2CmrH0cUGNpQarB4Ka5kSEmAS1EEVCkXqZQ6JaFB28l23atLFUExIZ8NayzT958mQTQKtXr27wbffu3btWK4BIp8BmUUVsF55UovWI5uN5pLmQ6W4MkUE448VmGE1UYCPgiMXDK43Axk7CxEYSKKhgc2A1+ctf/rJR/ruoG6/08xzxuiRzPAoLFpoRsfYQn0hqUblHbgshRJqRqBZFh7HENKy1bNnSBM+sWbOs2QcBxbY+FeuG8MADD1iTFIMLRGWCKGvXrl2YMGGCeaWJ52MgEhVRRjuTjoC3msl8DKNB2DnE8HFeLVmyxP5NHjaCm10RJsRRvSbDnQmRLObkbKsdvOievUyFGmtNFB73fv36mZAm9hOvfHyaohCiEDaEsD6Bg98jEkP7eKLoea+kAsDYsWM3ani64oorbPuYwQc0l9Un7xXbAEKrbdu2lkBw3333leT+i+TA5oGI5mCKI4IZDzYDZxidzLHrrrtalZTdDuLeLrroIqtUU9Emfg+obOML9hQRdkI4sKC4B5s83koeTlJMPC2FRQcV6rig5vEkQo7XKhYrnpP4NEUhhBCbIlEtigrVRapgTZs2tQ/sOGTckjJAznF9RDVDJqhIIrRqGyUsKhdsHthAONjRwC+N7QCBPXHiRDtciDPtMer9xQ+MwOZAEOIT9ixsbCEc+PAR14hsfrZaBbbneXtzJ2krUbh80KBB9ngzcY8EjPjwF1H5MFBMU3dTgHbTMofsH6KovPbaazVbyrnwyxHW+TJv3jyzkAwZMsS2/EW2QSQffvjh4fbbb7fGREQ2l2H5IInimmuuCXvttZf5ssnIxsPvVg8fJIOFBFFIXB+DaBCLxKNR4abRkdtFfFeTRcQnTmLtwKMeb+7kMSJOjh2mVq1aWXOpcoyFECJ/VKkWReXdd9+1r/Gx645fjsDJB5rP+vTpE/bdd99w9dVXF/GeikqAoTI871ShfQqdW0RmzJhhB5VnfL+kjWAP8nQYDqwiHKTQYHvwcemcpxx4vKlgc3C9rGUvxwW1D8hx64zD4oJeCGw4LGhYrGCZEUKUkCpa1FcLEtWi6B/eUNuWsVe+2IbOd8oZApyhDEoeqC4QzuQiM9CFhkaqz3DAAQdYvi7VZhfYNNJxcH7RCInA5qt7qTlIt+BgWh7nH+IakY2diANrCb8Liwi2iKwIbBamCGqq/KSnxAfkIKiJORwxYoRZtubPn79JEogQQoi6kagWqQVfLYkQDJ4gTk1UF4hn7BtkXVNpjoJIbtasmVlBsAXRmEhVmwORzUFzHY12COwOHTqYUHSBTXWbA+8/otMr2ET+ceDxRnxSwcYmgfWkEvnss89qBDWPJ39PXFCPHDnSqtR8n7jDuM9aCFECNiRUqVYxPFEkqkVR8bQPPsxz4VnCdW0ts01NdB7JBHfeeWcJ7qlIO/jnicirq6mQ7yOOSYe58sorzdaBqEZg48fHG8wuBykjCOwTTjjBhLILbM5ZDhfYXsFmaA0Hghq7BBVsvlaKwKaxF0FNrjuCmfsfF9T4p/FRswvACHKNeRdCiIYjUS2KCk1hUFtCh1/epEmTzd4O11u2bJlFqnXq1Gmj7/nIawSDV7DJrxbZo74pHVyfc6t///6WGIMo9so1nmwqsVShaWJEYJ900klWvfXfg32EJkgORKlXsPnK4Ukj/AwCNK3TBbnv7PTQxMlIZF5HcUFNLCV+dfoVeGziolsIUWIsR1pkiXR+IoiKhSYo8MEScfxyvJ35sG7dOjtygbgm81qIXCCUGXfOcBmaXcmwJiKOCjYebQ7EN0kXCOxTTjnFhsm4wKbhcc8997QDceri2uP6uB4Vb8QoAhtPdhrgvrLg5Ot+++1nj0FcUJNBTW481Xkq1PHrCCGEqD9bbKimTCmRyPAXqnhkVTMCmSzcuOgmTo8qWn1yqqNQlWYr/9hjj61JhBAiX3jLY1jM3LlzTWAjKrFIIJJbtGhhg2Y4GjdunLNSznVdWHssH9fDi+xJIuVqquW+8drCfoWlI57Cw30lMYUhOlT0aQBm0SCESA52j959+39C6917lPx3LVwzJeyxzy5h+fLlJf9dQjnVosggJvr27Wv/pkLoHmq4++67TVAfddRRGwlqJjDSdDZ48OCy3GdRXXiF+bzzzjNhzU7ItGnTrFpNzjrDTxCkWIs4Z2mCjNYeGNeN4OYcxkZCNZjbQ6j/+c9/tt0ThC1j2KkWJymoqVAjqHk95RLUjz76aLj44ovDbrvtZosJCWohysWGEDasL/2hTsVEkf1DFB1i8KggL1q0yOLLfvGLX1gs3iuvvGLb5JMmTdro+h9++KHFo+F/FSJpgU0zbLdu3cLZZ59tkZBEyhHVR5Mj4phGPnZYsIecdtpplkTiFWwWkQhUDhI2OJexiPzjH/+wKvZbb71lqSM+Lh1LSal2iLBWsYjl/iH644L6scceC7169bL7gqDWICUhhCguqlSLokOUGdvKiBHyqvGxIqp79OhhH/x77713ue+iEJuAUCaVpnPnzmHmzJkmjrGHILY5f2+++WabCMpwFCLo2E5lCqGDpxpPNpYndmM8cYNM7BUrVoSFCxfawpKx6bWl4zQExDyvKxYELGLjTcAIaoa58Pqjoo6gppIthCgz7ICV+hCJIk+1EEJsBt4isVaw+4LIpuKL1QMQsfivqWDTfJtrYAxjwalcI9KpZBMXCcT4eQXboygbIqixfCDcaTqML1i570899ZQN0WHB8Mwzz9Q0EwshyumpXhdaNzq35L9r4dqpYY99dpWnOiEkqoUQop5WC3ZiENjswtCwCPiTEdh4sxlak0tgU9lGYPMzpJEgij3KD3GNyEZg5xMliDinQk1TMGIaUR0HEU3lHdsJFeqGNgcnFQN422232S4BWeM0fjJ+nh0C7DX5QCIQtp3HH388vPzyy+G9994zDzy+97POOstSYNKS0iKqXFSvWBda/+ickv+uhe9PC3v8WKI6KSSqhRCigSCKsXXMnj3bBDbTGIEmQU8RIVEk18AYBDa+ayrYCGzEOiCAvYLN1MdcAjsqqBHz+KPj13vhhRfCGWecYSKSfO7mzZuHtEJDJ4k+CGEsNPRhvPPOO+HVV1+1Pgwuz8c2Rj/HsGHD7LHAhoO/nMf2pZdest2G1q1b22OBLU2IciFRnV0kqoUQogggdJkASZMjw2aotgKDV2hyRGAj6nINjOFtGIHtUX0IQO9P8Aq2j1nHToKgpiqLfxoLSlxQ0ySMJYXLabwkizvNuBhu2bKl2VXcDkP6yoABA8yjns+AJyrdPC4kD/kgKnj77bdtZD3PCSlDt956a0n/HiHyEtW7div571q4brpEdYJIVAuRkq3rKFTphg8fblU1qp/4YRFPp59+uo3jFumGKvSSJUusgo3AXrVqlV1O1fXEE080iwhCMVeeNW/JVKB90IzH8nFdfv6TTz4xDzWiMZpE4vB7EfGIb0a0+9TRSsi2Z7Fw8MEHFz3bHh5++GGzgFDZp1lUiHIhUZ1dJKqFSMnWtUNlsWPHjibUSZtATOPDff311817u3LlypL+PaL4AnvZsmU1FhGyrGGHHXYwgU0Fu02bNub9jQtk3p4R0T7NkXMC8GtzrnmzIz8LDFziNhGqZHBTnU07+NP5+/GE5zq3WZhed9114frrrw833HBDg3/Pm2++aWKGxYnvBAhRVlG9y9kl/10L/2eGRHWCKKdaiAIhXg3hXNvWdc+ePfPaugZyjalGU5mmseyII47YSJzVNv5dpBcEMIsjDiwOb7zxhllEaHScPn26HXinO3ToYBVshDC+agQ2B7YPhCCxfHzl3OBcoAlv1qxZ1pRH1fuwww4L99xzjy3yuG0mjlYCDNwBHp9c+OVUqwuBIT5uxxFCiFIgUS1EAVARZCIkjB07dqNotCuuuCI8+OCDNmGP2LN8tq75GUQRoisqqF2ckSohKhdEMvnVHFReGXrkAhuBzMFuRPv27a2CzVcaDfFHI8Y5n2g45HYY9ILQxO5BDjUHMOWRijZHJTTkufc8PgHS8cvJCi8EFhzA4ypEKpBRIHNo+IsQBUCqAF5Qtq7jXlDAxgFUE+uCsdZ4qLGKnHDCCSW5vyI9IIwZwnLNNdeYX5hmuhEjRoSf/vSnJrK7d+9u/l+u8+KLL9aMRXeLCOKbnRBGjzPUhUUXKSCkfnDeYT3q1KmT+fzTbHdgaA3UtgDg7wR85A1l/PjxljPO9EzG0AshRCmQqBYiJVvXWETY1qdCTZLEI488Ei677LLQt29fEwWkQ4hsglBGEA8cONASRPDk33HHHbbzQSQcsOPRpUuXMHXqVPPY47emAfKkk06yxIsZM2aYRYSK7siRI+3cowp+/vnnW9NitcKChNcRj/GkSZNCo0aNyn2XhBAZRfYPIVKydU0jFSCkaHbEpx2FiibNbjRFiuyC+OO8YcHGBEZ2Ldq1a2eNh1Rb2c0glo9x6XjwWWxNmTLFBDc/SypI//797Xj//fetSTLNNhC3TNU2uh2bC+Alry9YZrB7YNMaPXq02WiESAcbaJRJ5veIxFClWoiUbF17Jfr+++83sfTQQw/ZOGx8t926dbN/IwpoUBPZhd2KXr16WQMj0XhE8lFpRVDz3LNrQVoGFW3OCRplzznnnJxDYkgIoQEyzXie9Jo1a3J+3y8nk7s+EJvHYoTXFakh/fr1K8K9FUKI2pGoFiJFYgqwfkyYMCF07drVYtfIIp42bZqlO+DfHjduXLnvqigh7GpQlaZCjQXIs6wRzcTnXXjhhWHBggWWZoFdhGEm+Yw1TyvkUENtyTZ++YEHHpj3bVKhb9u2rX1lQUJTqBCpYsP/NSqW/Cj3H1pdSFQLkZKta78tvtJgFue8886r8daK7LLXXnvZRET80J4/HQcRTRMjjY2VLKiBaY/EBuIPx6oSB8sTnHzyyXndHpVpUlO4PV4z+MuFECIJJKqFSMnWtV+H28wllBBRwCAQkW323XdfG1FeDVCJpxkXGC/uC1HPeqfJlxzuaCQlMZakolClj8LiluE3DErq3LlzmDhxYsUvOkSGSaJSLRJFjYpCpGTr2iP5akv5wD8L0SxsIbLAtddea55xKvRMEKVRFxvMK6+8YtGApHZEoYGTXgPsHfFmXrzmW221lTVzknySCxo7hRCi2EhUC1HEreuDDjqowVvXROmRN7xu3ToTDFQro7jtI1cethCVDFV5xpXfdttt1qDLOPcdd9wx9OjRw8aU15auE8cXpEQIcju1IVEtUsF6VZKzhuwfQqRk65rKGhMVyR/mtj755JOa71HFQwiwlU2jmhBZg9HsN910U1i5cqUNq6EKPXny5JyCmjQPXidxccz/c3ldhxBClAJVqoVIydY1XHXVVVax4/ZI/WjRooVdn8xqqm/Dhg2zfGIhhBCVywb+27A+kd8jkkOVaiGKtHU9dOhQy6tm6xpRzdY1nmrGjufLt771rTBv3jxLddhpp51s0AdNV1S7GXU+ZMiQkv4tQgghhGgYW2zQXpgQQgghRCLsv//+4a9vrQ2tt+tY8t+18OPZoUmzRmH58uUl/11ClWohhBBCCCEKRqJaCCGEEEKIAlGjohBCCCFE0sh9mzlUqRapZ+rUqRYld8ABB4Svvvoq53VIx2DgA819H3zwQeL3sRr5/PPPw3XXXWcpJTRrNmrUKPTs2TO899579b6tp59+2ibhkZZCsyZ53e3atQtz5swpyX0XQgghio1EtUg95557bjjuuOPCG2+8EW6//fZNvo/QvuCCC8L69evDXXfdZcJMlJYvvvgitGnTxgZz/Pvf/w6nnnpqaNy4seUKM5xm9erVed/WqFGjTEDPnz/fBPoZZ5xhOd7ECp5++uk2JU8IITLH+vWlP0SiSFSLimDChAk2HOKWW24Jb7/99kbfI34OwY3w7t69e9nuYzXB88DuQMuWLcOKFSvCrFmzLJebRQ07BVSs84HrDho0yKrTxBK+9NJLYebMmfb197//ffjOd75jU/bqI9KFEEKIciBRLSoCsp5vvPFGq5D27t275nKGqCDwENzjx48v632sFr788kubCgljx44NP/jBD2q+x0TIAw880EaqL126tM7bQogzPY+qN1ncUY488sjQvn17m4D3hz/8oQR/iRBClNlTXepDJIpEtagYLr/8crMWUMF84IEHTGwhsBFljC1u2rRpue9iVUAV+eOPP7bHm+cjTseO32SvMqymLqhE5wMeayGEECLNKP1DVAxbb711mDhxYmjevLmN8167dm144YUXwkEHHWQVUpEMr732mn095JBDcn7fL//Tn/5U520xcn377bcPzz77rFW3o9VqnlsmSvrodyGEyAwbNoQNSXieVa1OFFWqRUXx85//PPTv3z/885//tOQJEj8Q2ghukQzvvvuufd19991zft8vZ1R7XWy33Xa267DllluGY445JrRu3TqceeaZ9vXoo48Ohx12mAnrb3/720X+K4QQQojiIlEtKg6q0kTsAY2Jhx56aLnvUlVB2gd873vfy/n973//+/b1008/zev2SPgg+QOLB9YSmh75uu2221oqyG677VbEey+EEClBnurMIVEtKo7rr7/e/NRAFTNf8SbSCYkhJLfQmIhlBNHOV5oX2Y1AdAshhBBpR6JaVBT4bLEL/OhHPwq//OUvbdCIcoyTxdM+Pvvss5zf/89//mNfqTTXBU2nV155pfniH330URvwQ6Wbr7Nnz7bLn3zySatkCyFEpli/ofSHSBSJalExkPJB2gdV6jFjxliE3g477GCxbkuWLCn33asa9thjD/u6Zs2anN/3y5s0aVLnbU2bNs2+nnbaaearjoJf3qvULKaEEEKINCNRLSoG8qjJpT7llFNs6t4uu+xiExaZpMhExa+//rrcd7Eq+NnPfmZf//jHP+b8vl9OXnVduACnYTEXfjmNqUIIIUSakagWFQETE5mciKWAyrRz/vnnW9waMW8jR44s632sFlq1amVid9WqVWHZsmWbfB/bBpx88sl13tauu+5qX2sb7uI7EHvuuWeB91oIIVLGhvWlP0SiSFSL1OOV6K+++ioMGzZsoyg3UkAYYU7kGgNg3nnnnbLe12qAx7pv377270suuaTGQw133323NRmSN038ocMExmbNmoXBgwdvdFv44mHGjBnhiSee2Oh7jz32WHjooYfMFoI9RJSOzz//3JpCf/zjH4dtttkmNGrUyEbN07NQX9hVuOyyy8z+w3AfvhKD+a9//ask910IIdKCRLVIPePGjQsvv/yyDX1BxMX5yU9+EgYNGmSNc3369CnLfaw2rr32Wns+Fi1aZMNZunTpElq0aBEGDBgQfvjDH4ZJkyZtdP0PP/zQrDvvv//+JqK6U6dO4b///a9Vtsml7ty5s33leyyobr755rDvvvsm/BdWD1988YUlrfA4k7xy6qmnhsaNG4fJkyfbxMzVq1fnfVs8zwz0GT16tGXH8xyyu3TPPffY+fLRRx+V9G8RorKGv5T+UKxeskhUi1SD53bIkCE10xTjzWwO16HKRkoEOceitFDNfO6558LQoUMtr/q3v/2tDXvp0aOHear33nvvvG6HnQaeLxJdiNRbuXJlmDNnju04nHDCCfZ88tyK0vYqsGht2bJlWLFihT0fr7zyikUdfvDBB1axzhcq0jyHNJiyiOK2sG7169fPbluTT4WoXLSjVTdbbPDAXyGEEFXFl19+GXbeeefw8ccf22KIynS8KRU7D573qJ0nF+xCYM1iAczUTRqJo8k9VL+pVK9du9Z+pxDVyv777x/++uaacMTWHUr+uxZ9PT802W/3sHz58oJ3tJh6ywKcSFt6mSh+vPrqq7Y7yeV751lMYUeLRTwLcH6GAW7cPw4E++LFi8OOO+4YKhFVqoUQokphciWCumnTppsIaujYsaN9ffzxx+u8rQULFphdhw/bqKAGKlHYe7D5zJs3r4h/gRAiCbSjlR8S1UIIUaWQmgOHHHJIzu/75VSrk7wtIaqBRDzVRdrRotkcSN/yAWCAACY+9fnnnw9Lly6t87bY0Xr44Yet4Z1+KXa2nDvuuMOq3tOnTw9///vfQyUiUS2EEFUKNg2IJupE8cvxyyd5W0KI9KAdrfyRqBZCiCqFtA+g2TQXjIyHTz/9NNHbEqIqqJCcau1o5c//r7sLIYTYLGxvPv3009acw+Fd7w3t96YDnnx10lPWrVtnw3DI5Oay7bffvsj3XgiRFj4L/w6LNzyVyO9hUBfNkbnIp4FRO1r5I1EthBB5QpYzQ2mKQbwDnkxnPuDIdCZKMIkOePdGkvGeCx/sQ9Z0krclRJbBRpEkLmQbina08keiWggh8gQRTFMOw2k4GJ9OXFxDiHbA0/3uDTuXXnppGDNmjDUATZkyJZSSPfbYoyYPPhd+ORmySd6WEFlm7ty55b4LokRIVAshRJ5cffXVRbmdujrgZ86caR3wt99+e0kzncmhBjKqc+GXs5BI8raEEOlBO1r5o0ZFIYRImLR0wLdq1Spst9125rlctmzZJt+fPXu2feX+1MXxxx9vE09ffPHFTeKwqOaTDLDVVlvZpEwhROWgHa38kagWQoiESUsHPJXyvn372r8vueSSmioR3H333fb7jzrqqI2mKZJX26xZszB48OCNbospa127drVM2z59+oSvv/665nsDBw60ARHdunXTNEUhKgztaOWP7B9CCJEwaeqAv/baa8Pvfve7sGjRorDPPvtY9Zzfy7Q0BjFMmjRpkwZLpqBhYYkzatQom7r261//2oS3jx9mWhq3jVAXQlQW8R2tgw46qGg7WjtHFtlZ2NFSpVoIIRImTR3w22yzTXjuuefC0KFD7f4Q74eo7tGjh1WNSCbJl5122smiBhk3TMV6zpw5NjSC5ksuL3WaiRCi+GhHK3+22NDQgFUhhKhyEKRUV+r7NtquXTvLu544cWLo1avXJt+ncty2bVs7nnqq9Fm2QgixOb744otw9NFH2w4Wwji+o8UO1d6RBThZ+zfeeGPo3r37JilG7Ha1aNHCKt/EC8Z3tLitSl2Aq1IthBAJk/UOeCFEttCOVn7IUy2EEAmT9Q54IUT2+O53vxtuuukmO+rihhtusKM2EM6jR4+2I0uoUi2EEAmT9Q54IYSoRuSpFkKIhD3VJGeQ8MHQl7/97W+bdMA3btw4fPTRR2Ht2rUV27AjhBDVhirVQghRIqq1A14IIaoReaqFECJPnnzyyXDzzTfX/D+iGOhkd2jkOfHEE+3fynQWQojqQaJaCCHyhAoyEVJxopdxnfp0wNPMQyc9HfCMLKcDniiq7bffvqj3XQghRGmRp1oIIYQQQogCkadaCCGEEEKIApGoFkIIIYQQokAkqoUQQgghhCgQiWohhBBCCCEKRKJaCCGEEEKIApGoFkIIIYQQokAkqoUQQgghhCgQiWohhBBCCCEKRKJaCCGEEEKIApGoFkIIIYQQokAkqoUQQgghhCgQiWohhBBCCCEKRKJaCCGEEEKIApGoFkIIIYQQokAkqoUQQgghhCgQiWohhBBCCCEKRKJaCCGEEEKIUBj/C+rdooJw74CuAAAAAElFTkSuQmCC" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 9 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T16:04:47.016831Z", - "start_time": "2025-02-26T16:04:46.955140Z" - } - }, - "cell_type": "code", - "source": [ - "plotter.plot_concentrations()\n", - "# result.plot_concentrations()" - ], - "id": "91402b136f6021fc", - "outputs": [ - { - "data": { - "text/plain": [ - "" - ], - "image/png": 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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 10 - }, - { - "cell_type": "markdown", - "source": "|## extract the vcell simulation dataset from the tarball (compressed to save space)", - "metadata": { - "collapsed": false - }, - "id": "4b69965b59dd9af5" - }, - { - "cell_type": "markdown", - "source": [ - "## read vcell simulation results metadata\n", - "* `PdeDataSet` contains the metadata for the tabular simulation results (e.g. state variables, shape, time points)\n", - "* `DataFunctions` contains the function definitions (name, expression, type, domain)\n", - "" - ], - "metadata": { - "collapsed": false - }, - "id": "61b06bfdb3479c67" - }, - { - "cell_type": "markdown", - "source": [ - "## write the vcell simulation dataset to zarr including:\n", - "* metadata\n", - "* numerical datasets from stored data and evaluated functions\n", - "* ... masks for domains coming soon (e.g. cell, extracellular, etc.)" - ], - "metadata": { - "collapsed": false - }, - "id": "cb456b125c78df83" - }, - { - "cell_type": "markdown", - "source": [ - "## Open and display slices from the zarr dataset as an image\n", - "* no masking for domains\n", - "* different colormap and scaling" - ], - "metadata": { - "collapsed": false - }, - "id": "84d2b666c214cb87" - }, - { - "cell_type": "markdown", - "source": [ - "## Open and display slices from the post processing dataset as an image" - ], - "metadata": { - "collapsed": false - }, - "id": "c5ff68f1950d1514" - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T16:04:48.143025Z", - "start_time": "2025-02-26T16:04:48.139714Z" - } - }, - "cell_type": "code", - "source": "len(result.channels)", - "id": "89880cd4416c1324", - "outputs": [ - { - "data": { - "text/plain": [ - "5" - ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 11 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T16:04:51.216509Z", - "start_time": "2025-02-26T16:04:48.354577Z" - } - }, - "cell_type": "code", - "source": [ - "from IPython.display import HTML\n", - "\n", - "result.plotter.animate_channel_3d(channel_index)" - ], - "id": "8e6924aee12e66b3", - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Any mask: False\n", - "got shapes: (0,), (0,), (0,)\n", - "Any mask: False\n", - "got shapes: (0,), (0,), (0,)\n", - "Any mask: False\n", - "got shapes: (0,), (0,), (0,)\n", - "Any mask: False\n", - "got shapes: (0,), (0,), (0,)\n", - "Any mask: False\n", - "got shapes: (0,), (0,), (0,)\n", - "Any mask: False\n", - "got shapes: (0,), (0,), (0,)\n", - "Any mask: False\n", - "got shapes: (0,), (0,), (0,)\n", - "Any mask: False\n", - "got shapes: (0,), (0,), (0,)\n", - "Any mask: False\n", - "got shapes: (0,), (0,), (0,)\n", - "Any mask: False\n", - "got shapes: (0,), (0,), (0,)\n", - "Any mask: False\n", - "got shapes: (0,), (0,), (0,)\n", - "Any mask: False\n", - "got shapes: (0,), (0,), 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"end_time": "2025-02-26T15:43:08.807596Z", - "start_time": "2025-02-26T15:43:08.804174Z" - } - }, - "cell_type": "code", - "source": [ - "nchannels = result.zarr_dataset.shape[1]\n", - "len(result.channels)" - ], - "id": "3abc850392901f87", - "outputs": [ - { - "data": { - "text/plain": [ - "5" - ] - }, - "execution_count": 19, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 19 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T15:56:33.579396Z", - "start_time": "2025-02-26T15:56:33.576430Z" - } - }, - "cell_type": "code", - "source": "result.metadata.mesh", - "id": "fa12d8f17356ce05", - "outputs": [ - { - "data": { - "text/plain": [ - "MeshMetadata(size=[200, 1, 1], extent=[10.0, 1.0, 1.0], origin=[0.0, 0.0, 0.0], volume_regions=[MeshVolumeRegion(region_index=0, domain_type_index=0, volume=10.000000000000034, domain_name='subdomain0')])" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 13 - }, - { - "metadata": {}, - "cell_type": "markdown", - "source": "@", - "id": "cc29a947b4aa6010" - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T15:46:05.921362Z", - "start_time": "2025-02-26T15:46:05.918528Z" - } - }, - "cell_type": "code", - "source": "valid", - "id": "a022f87c0501f42", - "outputs": [ - { - "data": { - "text/plain": [ - "[2, 5, 6, 7, 8, 9]" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 26 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-20T01:48:49.716620Z", - "start_time": "2025-02-16T11:34:44.620934Z" - } - }, - "cell_type": "code", - "source": [ - "# animate fluor dataset image over time\n", - "fluor_index = 0\n", - "result.plotter.animate_image(fluor_index)" - ], - "id": "51a527f967f11749", - "outputs": [ - { - "data": { - "text/plain": [ - "" - ], - "image/png": 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" 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"source": [ - "post_processing = result.post_processing\n", - "post_processing.variables[0].stat_var_unit" - ], - "id": "5d14bb8707d8744d", - "outputs": [ - { - "data": { - "text/plain": [ - "'uM'" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 5 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-20T01:50:56.311511Z", - "start_time": "2025-02-20T01:50:56.065811Z" - } - }, - "cell_type": "code", - "source": "plotter.plot_averages()", - "id": "4384c512de40a38e", - "outputs": [ - { - "data": { - "text/plain": [ - "" - ], - "image/png": 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" - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "execution_count": 6 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T15:19:34.087093Z", - "start_time": "2025-02-26T15:19:34.078687Z" - } - }, - "cell_type": "code", - "source": [ - "import numpy as np\n", - "\n", - "\n", - "x = np.random.random_sample(51, 10, 1, 1, 200)" - ], - "id": "972f7dd13f2ea8e9", - "outputs": [ - { - "ename": "TypeError", - "evalue": "random_sample() takes at most 1 positional argument (5 given)", - "output_type": "error", - "traceback": [ - "\u001B[0;31m---------------------------------------------------------------------------\u001B[0m", - "\u001B[0;31mTypeError\u001B[0m Traceback (most recent call last)", - "Cell \u001B[0;32mIn[14], line 4\u001B[0m\n\u001B[1;32m 1\u001B[0m \u001B[38;5;28;01mimport\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;21;01mnumpy\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;28;01mas\u001B[39;00m\u001B[38;5;250m \u001B[39m\u001B[38;5;21;01mnp\u001B[39;00m\n\u001B[0;32m----> 4\u001B[0m x \u001B[38;5;241m=\u001B[39m \u001B[43mnp\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mrandom\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mrandom_sample\u001B[49m\u001B[43m(\u001B[49m\u001B[38;5;241;43m51\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m10\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m1\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m1\u001B[39;49m\u001B[43m,\u001B[49m\u001B[43m \u001B[49m\u001B[38;5;241;43m200\u001B[39;49m\u001B[43m)\u001B[49m\n", - "File \u001B[0;32mnumpy/random/mtrand.pyx:385\u001B[0m, in \u001B[0;36mnumpy.random.mtrand.RandomState.random_sample\u001B[0;34m()\u001B[0m\n", - "\u001B[0;31mTypeError\u001B[0m: random_sample() takes at most 1 positional argument (5 given)" - ] - } - ], - "execution_count": 14 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T15:18:25.567281Z", - "start_time": "2025-02-26T15:18:25.565478Z" - } - }, - "cell_type": "code", - "source": [ - "\n", - "\n" - ], - "id": "7d37f27a06f65c9e", - "outputs": [], - "execution_count": 12 - }, - { - "metadata": { - "ExecuteTime": { - "end_time": "2025-02-26T15:18:26.410738Z", - "start_time": "2025-02-26T15:18:26.408014Z" - } - }, - "cell_type": "code", - "source": "x", - "id": "b2040bd8b3027676", - "outputs": [ - { - "data": { - "text/plain": [ - "array([], dtype=int64)" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "execution_count": 13 - }, - { - "metadata": {}, - "cell_type": "code", - "outputs": [], - "execution_count": null, - "source": "", - "id": "4d9456f0f24e0a09" - } - ], - "metadata": { - "kernelspec": { - "display_name": "pyvcell(poetry)", - "language": "python", - "name": "pyvcell" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 2 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython2", - "version": "2.7.6" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/tests/fixtures/data/SmallSpacialProject_3D.xml b/examples/models/SmallSpatialProject_3D.sbml similarity index 99% rename from tests/fixtures/data/SmallSpacialProject_3D.xml rename to examples/models/SmallSpatialProject_3D.sbml index e9bec44..aca70de 100644 --- a/tests/fixtures/data/SmallSpacialProject_3D.xml +++ b/examples/models/SmallSpatialProject_3D.sbml @@ -5,7 +5,7 @@ Exported by VCell 7.7.0.15
Exported by VCell 7.7.0.15