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norlandrhagen/write_region_with_30m_risk_icechunk.ipynb

Created May 12, 2025 19:06
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write_region_with_30m_risk_icechunk.ipynb
{
"cells": [
{
"cell_type": "markdown",
"id": "7694f531",
"metadata": {},
"source": [
"## Example notebook to see if we can write regions with the 30m community risk datasets"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a7e0e679",
"metadata": {},
"outputs": [],
"source": [
"import dask\n",
"import numpy as np\n",
"import icechunk\n",
"import xarray as xr\n",
"from dataclasses import dataclass\n",
"import tempfile\n",
"from icechunk.distributed import merge_sessions\n",
"from distributed import Client\n",
"from typing import Optional\n",
"\n",
"import matplotlib.style as mplstyle\n",
"mplstyle.use('fast')"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "a3308796",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
" <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <h3 style=\"margin-bottom: 0px;\">Client</h3>\n",
" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Client-05053076-2f5f-11f0-9f30-0a70e1860ea5</p>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
"\n",
" <tr>\n",
" \n",
" <td style=\"text-align: left;\"><strong>Connection method:</strong> Cluster object</td>\n",
" <td style=\"text-align: left;\"><strong>Cluster type:</strong> distributed.LocalCluster</td>\n",
" \n",
" </tr>\n",
"\n",
" \n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"https://cluster-yhgbs.dask.host/jupyter/proxy/8787/status\" target=\"_blank\">https://cluster-yhgbs.dask.host/jupyter/proxy/8787/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" \n",
"\n",
" </table>\n",
"\n",
" \n",
"\n",
" \n",
" <details>\n",
" <summary style=\"margin-bottom: 20px;\"><h3 style=\"display: inline;\">Cluster Info</h3></summary>\n",
" <div class=\"jp-RenderedHTMLCommon jp-RenderedHTML jp-mod-trusted jp-OutputArea-output\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #e1e1e1; border: 3px solid #9D9D9D; border-radius: 5px; position: absolute;\">\n",
" </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <h3 style=\"margin-bottom: 0px; margin-top: 0px;\">LocalCluster</h3>\n",
" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">a76fb965</p>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard:</strong> <a href=\"https://cluster-yhgbs.dask.host/jupyter/proxy/8787/status\" target=\"_blank\">https://cluster-yhgbs.dask.host/jupyter/proxy/8787/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Workers:</strong> 8\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads:</strong> 8\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total memory:</strong> 30.14 GiB\n",
" </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <td style=\"text-align: left;\"><strong>Status:</strong> running</td>\n",
" <td style=\"text-align: left;\"><strong>Using processes:</strong> True</td>\n",
"</tr>\n",
"\n",
" \n",
" </table>\n",
"\n",
" <details>\n",
" <summary style=\"margin-bottom: 20px;\">\n",
" <h3 style=\"display: inline;\">Scheduler Info</h3>\n",
" </summary>\n",
"\n",
" <div style=\"\">\n",
" <div>\n",
" <div style=\"width: 24px; height: 24px; background-color: #FFF7E5; border: 3px solid #FF6132; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <h3 style=\"margin-bottom: 0px;\">Scheduler</h3>\n",
" <p style=\"color: #9D9D9D; margin-bottom: 0px;\">Scheduler-82b077ae-15c9-4087-a54d-9369fffae032</p>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Comm:</strong> tcp://127.0.0.1:38091\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Workers:</strong> 0 \n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard:</strong> <a href=\"https://cluster-yhgbs.dask.host/jupyter/proxy/8787/status\" target=\"_blank\">https://cluster-yhgbs.dask.host/jupyter/proxy/8787/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads:</strong> 0\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Started:</strong> Just now\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total memory:</strong> 0 B\n",
" </td>\n",
" </tr>\n",
" </table>\n",
" </div>\n",
" </div>\n",
"\n",
" <details style=\"margin-left: 48px;\">\n",
" <summary style=\"margin-bottom: 20px;\">\n",
" <h3 style=\"display: inline;\">Workers</h3>\n",
" </summary>\n",
"\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 0</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Comm: </strong> tcp://127.0.0.1:41177\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 1\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"https://cluster-yhgbs.dask.host/jupyter/proxy/41879/status\" target=\"_blank\">https://cluster-yhgbs.dask.host/jupyter/proxy/41879/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 3.77 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Nanny: </strong> tcp://127.0.0.1:33721\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
" <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-oo3eub43\n",
" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 1</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Comm: </strong> tcp://127.0.0.1:36679\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 1\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"https://cluster-yhgbs.dask.host/jupyter/proxy/43315/status\" target=\"_blank\">https://cluster-yhgbs.dask.host/jupyter/proxy/43315/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 3.77 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Nanny: </strong> tcp://127.0.0.1:46133\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
" <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-ranrer8i\n",
" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 2</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Comm: </strong> tcp://127.0.0.1:33999\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 1\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"https://cluster-yhgbs.dask.host/jupyter/proxy/37061/status\" target=\"_blank\">https://cluster-yhgbs.dask.host/jupyter/proxy/37061/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 3.77 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Nanny: </strong> tcp://127.0.0.1:44913\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
" <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-hyzxx6xq\n",
" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 3</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Comm: </strong> tcp://127.0.0.1:43749\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 1\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"https://cluster-yhgbs.dask.host/jupyter/proxy/42561/status\" target=\"_blank\">https://cluster-yhgbs.dask.host/jupyter/proxy/42561/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 3.77 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Nanny: </strong> tcp://127.0.0.1:34931\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
" <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-vpksg654\n",
" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 4</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Comm: </strong> tcp://127.0.0.1:35417\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 1\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"https://cluster-yhgbs.dask.host/jupyter/proxy/44079/status\" target=\"_blank\">https://cluster-yhgbs.dask.host/jupyter/proxy/44079/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 3.77 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Nanny: </strong> tcp://127.0.0.1:40483\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
" <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-v4n40ef2\n",
" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 5</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Comm: </strong> tcp://127.0.0.1:46747\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 1\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"https://cluster-yhgbs.dask.host/jupyter/proxy/44643/status\" target=\"_blank\">https://cluster-yhgbs.dask.host/jupyter/proxy/44643/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 3.77 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Nanny: </strong> tcp://127.0.0.1:34919\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
" <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-4dtx3fdi\n",
" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 6</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Comm: </strong> tcp://127.0.0.1:38817\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 1\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"https://cluster-yhgbs.dask.host/jupyter/proxy/33021/status\" target=\"_blank\">https://cluster-yhgbs.dask.host/jupyter/proxy/33021/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 3.77 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Nanny: </strong> tcp://127.0.0.1:36725\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
" <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-i7wb59a4\n",
" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
" <div style=\"margin-bottom: 20px;\">\n",
" <div style=\"width: 24px; height: 24px; background-color: #DBF5FF; border: 3px solid #4CC9FF; border-radius: 5px; position: absolute;\"> </div>\n",
" <div style=\"margin-left: 48px;\">\n",
" <details>\n",
" <summary>\n",
" <h4 style=\"margin-bottom: 0px; display: inline;\">Worker: 7</h4>\n",
" </summary>\n",
" <table style=\"width: 100%; text-align: left;\">\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Comm: </strong> tcp://127.0.0.1:41767\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Total threads: </strong> 1\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Dashboard: </strong> <a href=\"https://cluster-yhgbs.dask.host/jupyter/proxy/34609/status\" target=\"_blank\">https://cluster-yhgbs.dask.host/jupyter/proxy/34609/status</a>\n",
" </td>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Memory: </strong> 3.77 GiB\n",
" </td>\n",
" </tr>\n",
" <tr>\n",
" <td style=\"text-align: left;\">\n",
" <strong>Nanny: </strong> tcp://127.0.0.1:35429\n",
" </td>\n",
" <td style=\"text-align: left;\"></td>\n",
" </tr>\n",
" <tr>\n",
" <td colspan=\"2\" style=\"text-align: left;\">\n",
" <strong>Local directory: </strong> /scratch/dask-scratch-space/worker-t5mkv265\n",
" </td>\n",
" </tr>\n",
"\n",
" \n",
"\n",
" \n",
"\n",
" </table>\n",
" </details>\n",
" </div>\n",
" </div>\n",
" \n",
"\n",
" </details>\n",
"</div>\n",
"\n",
" </details>\n",
" </div>\n",
"</div>\n",
" </details>\n",
" \n",
"\n",
" </div>\n",
"</div>"
],
"text/plain": [
"<Client: 'tcp://127.0.0.1:38091' processes=5 threads=5, memory=18.84 GiB>"
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"client = Client(n_workers=8)\n",
"client"
]
},
{
"cell_type": "markdown",
"id": "22c3f570",
"metadata": {},
"source": [
"# read our 30m example dataset\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "e999ce68",
"metadata": {},
"outputs": [],
"source": [
"storage = icechunk.s3_storage(\n",
" bucket='carbonplan-ocr',\n",
" prefix='input/fire-risk/tensor/USFS/RDS-2022-0016-02_all_vars_merge_icechunk',\n",
" from_env=True,\n",
")\n",
"\n",
"repo = icechunk.Repository.open(storage)\n",
"session = repo.readonly_session('main')\n",
"ds = xr.open_zarr(session.store, consolidated=False, chunks={})[['BP']]\n",
"\n",
"# downcast to float32\n",
"ds['BP'] = ds['BP'].astype('float32')\n",
"ds['BP'].encoding = {}\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "dbc903f3",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"total dims: y 101538 x 156335\n",
"dask chunks: y: 6000 x: 4500\n",
"num y chunks 17\n",
"num x chunks 35\n"
]
}
],
"source": [
"n_chunks_y = len(ds.chunksizes['y'])\n",
"n_chunks_x = len(ds.chunksizes['x'])\n",
"y_chunk_size = ds.chunksizes['y'][0]\n",
"x_chunk_size = ds.chunksizes['x'][0]\n",
"total_dims = dict(ds.sizes)\n",
"total_y_dim = total_dims['y']\n",
"total_x_dim = total_dims['x']\n",
"\n",
"print(f'total dims: y {total_y_dim} x {total_x_dim}')\n",
"print(f'dask chunks: y: {y_chunk_size} x: {x_chunk_size}')\n",
"print(f'num y chunks {n_chunks_y}')\n",
"print(f'num x chunks {n_chunks_x}')\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "785a7982-a0e2-4106-976b-9202f3a1e05a",
"metadata": {},
"outputs": [],
"source": [
"@dataclass\n",
"class Subset:\n",
" xstart: int\n",
" xend: int\n",
" ystart: int\n",
" yend: int\n",
" region_id: Optional[str] = None\n",
"\n",
" @property\n",
" def xslice(self) -> slice(int, int):\n",
" return slice(self.xstart, self.xend)\n",
"\n",
" @property\n",
" def yslice(self) -> slice(int, int):\n",
" return slice(self.ystart, self.yend)\n",
"\n",
"\n",
" def __post_init__(self):\n",
" self.region_id = f\"y{self.ystart}_x{self.xstart}\"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "45a1bcc0",
"metadata": {},
"outputs": [],
"source": [
"def get_commit_messages_ancestry(repo: icechunk.repository) -> list:\n",
" return [commit.message for commit in list(repo.ancestry(branch='main'))]\n",
"\n",
"def region_ids_to_subsets(region_ids: list[str] )->list[Subset]:\n",
" #TODO: Transforms an input list of region_ids into a list of Subset objects\n",
" return subset_list \n",
"\n",
"\n",
"def create_subsets(*, n_chunks_x: int, n_chunks_y: int, total_x_dim: int, total_y_dim):\n",
" #TODO: We should be able to pass list of region_ids to generate a subset!\n",
" \n",
" # Generate all combinations with a list comprehension\n",
" subsets = [\n",
" Subset(\n",
" xstart=x_idx * x_chunk_size,\n",
" xend=min((x_idx + 1) * x_chunk_size, total_x_dim),\n",
" ystart=y_idx * y_chunk_size,\n",
" yend=min((y_idx + 1) * y_chunk_size, total_y_dim),\n",
" )\n",
" for y_idx in range(n_chunks_y)\n",
" for x_idx in range(n_chunks_x)\n",
" ]\n",
" return subsets\n",
"\n",
"# kinda verbose, but ensure we don't switch x and y or something\n",
"subset_list = create_subsets(n_chunks_x=n_chunks_x, n_chunks_y=n_chunks_y, total_x_dim=total_x_dim, total_y_dim=total_y_dim)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "c4d78545",
"metadata": {},
"outputs": [],
"source": [
"# 17*35 = 595 atomic units\n",
"# Check that we have the right # of subsets!\n",
"assert len(subset_list) == n_chunks_y*n_chunks_x"
]
},
{
"cell_type": "markdown",
"id": "581b9b3c",
"metadata": {},
"source": [
"# Create the template\n",
"We don't care about data chunking, but we care about encoding chunks!\n"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "26e4c31b",
"metadata": {},
"outputs": [],
"source": [
"\n",
"# we're just gonna match this to the dask chunk sizes for now!\n",
"ZARR_CHUNK_SIZE = (6000, 4500)\n",
"\n",
"# create the template kinda manually, we could probably do this with the input dataset :shrug:\n",
"template = xr.Dataset(\n",
" {\n",
" \"BP\": (\n",
" (\"y\", \"x\"),\n",
" dask.array.zeros((total_y_dim,total_x_dim), chunks=-1, dtype=np.float32),\n",
" )\n",
" })\n",
"# add x and y coords\n",
"template = template.assign_coords(y=ds.y, x=ds.x)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "bee4ca73",
"metadata": {},
"outputs": [],
"source": [
"storage = icechunk.local_filesystem_storage(tempfile.TemporaryDirectory().name)\n",
"repo = icechunk.Repository.create(storage)\n",
"session = repo.writable_session('main')\n",
"with session.allow_pickling():\n",
"\n",
" template.to_zarr(\n",
" session.store,\n",
" compute=False,\n",
" mode='w',\n",
" encoding={'BP': {'chunks': ZARR_CHUNK_SIZE,'fill_value':np.nan} }, # IMPORTANT\n",
" consolidated=False,\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "56c38450",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'PTX051ZG5ZHXGD1MT3E0'"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"session.commit('template')"
]
},
{
"cell_type": "markdown",
"id": "49c35d27",
"metadata": {},
"source": [
"# DELAYED WRITE"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c21ec2db",
"metadata": {},
"outputs": [],
"source": [
"@dask.delayed\n",
"def insert_region(session: icechunk.Session, subset_ds: xr.Dataset):\n",
"\n",
" subset_ds.to_zarr(\n",
" session.store,\n",
" region='auto',\n",
" consolidated=False,\n",
" )\n",
" return session\n",
"\n",
"def existing_regions(session):\n",
" #TODO: get all existing regions written to a repo\n",
" pass\n",
"\n",
"def return_non_overlapping_regions(session, input_regions):\n",
" #TODO: given some input region ID's, return regions are novel / have not been written\n",
" pass \n",
"\n",
"\n",
"def write_regions(session: icechunk.Session, ds:xr.Dataset, region_subset_list: list):\n",
"\n",
" # get all commits\n",
" commit_messages = [commit.message for commit in list(repo.ancestry(branch='main'))]\n",
"\n",
" # only split the region_id messages\n",
" already_commited_messages = [msg for message in commit_messages for msg in (message.split(',') if ',' in message else [message])]\n",
"\n",
" \n",
" print(f'already_commited_messages: {already_commited_messages}')\n",
" uncommited_regions = [subset for subset in region_subset_list if subset.region_id not in already_commited_messages]\n",
" print(f'uncommited_regions: {uncommited_regions}')\n",
" \n",
" # TODO: ADDRESS CASE WHERE NO CHANGES: IcechunkError: x session error: cannot commit, no changes made to the session\n",
" \n",
" print(f'writing {len(uncommited_regions)} new regions')\n",
" ds_subsets_uncommited = [ds.isel(x=subslice.xslice, y=subslice.yslice) for subslice in uncommited_regions]\n",
"\n",
" with session.allow_pickling():\n",
" \n",
" tasks = [insert_region(session=session, subset_ds=subset_ds) for subset_ds in ds_subsets_uncommited]\n",
" # we could persist or w/e here\n",
" sessions = dask.compute(*tasks, scheduler=client)\n",
"\n",
" # get new region ids in list for commit message\n",
"\n",
" ids = [subset.region_id for subset in uncommited_regions]\n",
" commit_region_ids = ','.join(ids)\n",
" session = merge_sessions(session, *sessions)\n",
" \n",
" session.commit(f'{commit_region_ids}')\n",
" "
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9bccb49c-c292-46b2-bde4-ada77cab4088",
"metadata": {},
"outputs": [],
"source": [
"initial_commit_messages = get_commit_messages_ancestry(repo)\n",
"print('We should have repo init + template creation messages: ', len(initial_commit_messages))"
]
},
{
"cell_type": "markdown",
"id": "20fca80b",
"metadata": {},
"source": [
"## Lets write roughly half of the chunks"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "efe6e56d-6085-4156-be54-0089ee0ddff8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"already_commited_messages: ['template', 'Repository initialized']\n",
"uncommited_regions: [Subset(xstart=40500, xend=45000, ystart=66000, yend=72000, region_id='y66000_x40500'), Subset(xstart=126000, xend=130500, ystart=48000, yend=54000, region_id='y48000_x126000'), Subset(xstart=67500, xend=72000, ystart=54000, yend=60000, region_id='y54000_x67500'), Subset(xstart=117000, xend=121500, ystart=30000, yend=36000, region_id='y30000_x117000'), Subset(xstart=135000, xend=139500, ystart=0, yend=6000, region_id='y0_x135000'), Subset(xstart=4500, xend=9000, ystart=84000, yend=90000, region_id='y84000_x4500'), Subset(xstart=90000, xend=94500, ystart=6000, yend=12000, region_id='y6000_x90000'), Subset(xstart=49500, xend=54000, ystart=6000, yend=12000, region_id='y6000_x49500'), Subset(xstart=117000, xend=121500, ystart=36000, yend=42000, region_id='y36000_x117000'), Subset(xstart=103500, xend=108000, ystart=72000, yend=78000, region_id='y72000_x103500'), Subset(xstart=135000, xend=139500, ystart=12000, yend=18000, region_id='y12000_x135000'), Subset(xstart=130500, xend=135000, ystart=84000, yend=90000, region_id='y84000_x130500'), Subset(xstart=18000, xend=22500, ystart=78000, yend=84000, region_id='y78000_x18000'), Subset(xstart=45000, xend=49500, ystart=96000, yend=101538, region_id='y96000_x45000'), Subset(xstart=112500, xend=117000, ystart=48000, yend=54000, region_id='y48000_x112500'), Subset(xstart=58500, xend=63000, ystart=36000, yend=42000, region_id='y36000_x58500'), Subset(xstart=81000, xend=85500, ystart=66000, yend=72000, region_id='y66000_x81000'), Subset(xstart=27000, xend=31500, ystart=90000, yend=96000, region_id='y90000_x27000'), Subset(xstart=13500, xend=18000, ystart=0, yend=6000, region_id='y0_x13500'), Subset(xstart=85500, xend=90000, ystart=0, yend=6000, region_id='y0_x85500'), Subset(xstart=4500, xend=9000, ystart=12000, yend=18000, region_id='y12000_x4500'), Subset(xstart=0, xend=4500, ystart=48000, yend=54000, region_id='y48000_x0'), Subset(xstart=27000, xend=31500, ystart=42000, yend=48000, region_id='y42000_x27000'), Subset(xstart=40500, xend=45000, ystart=84000, yend=90000, region_id='y84000_x40500'), Subset(xstart=9000, xend=13500, ystart=84000, yend=90000, region_id='y84000_x9000'), Subset(xstart=27000, xend=31500, ystart=72000, yend=78000, region_id='y72000_x27000'), Subset(xstart=72000, xend=76500, ystart=96000, yend=101538, region_id='y96000_x72000'), Subset(xstart=9000, xend=13500, ystart=36000, yend=42000, region_id='y36000_x9000'), Subset(xstart=67500, xend=72000, ystart=72000, yend=78000, region_id='y72000_x67500'), Subset(xstart=85500, xend=90000, ystart=42000, yend=48000, region_id='y42000_x85500'), Subset(xstart=121500, xend=126000, ystart=84000, yend=90000, region_id='y84000_x121500'), Subset(xstart=90000, xend=94500, ystart=84000, yend=90000, region_id='y84000_x90000'), Subset(xstart=148500, xend=153000, ystart=60000, yend=66000, region_id='y60000_x148500'), Subset(xstart=108000, xend=112500, ystart=18000, yend=24000, region_id='y18000_x108000'), Subset(xstart=81000, xend=85500, ystart=54000, yend=60000, region_id='y54000_x81000'), Subset(xstart=13500, xend=18000, ystart=6000, yend=12000, region_id='y6000_x13500'), Subset(xstart=36000, xend=40500, ystart=6000, yend=12000, region_id='y6000_x36000'), Subset(xstart=81000, xend=85500, ystart=36000, yend=42000, region_id='y36000_x81000'), Subset(xstart=27000, xend=31500, ystart=66000, yend=72000, region_id='y66000_x27000'), Subset(xstart=148500, xend=153000, ystart=48000, yend=54000, region_id='y48000_x148500'), Subset(xstart=144000, xend=148500, ystart=18000, yend=24000, region_id='y18000_x144000'), Subset(xstart=13500, xend=18000, ystart=60000, yend=66000, region_id='y60000_x13500'), Subset(xstart=40500, xend=45000, ystart=48000, yend=54000, region_id='y48000_x40500'), Subset(xstart=85500, xend=90000, ystart=72000, yend=78000, region_id='y72000_x85500'), Subset(xstart=103500, xend=108000, ystart=54000, yend=60000, region_id='y54000_x103500'), Subset(xstart=63000, xend=67500, ystart=30000, yend=36000, region_id='y30000_x63000'), Subset(xstart=49500, xend=54000, ystart=66000, yend=72000, region_id='y66000_x49500'), Subset(xstart=49500, xend=54000, ystart=42000, yend=48000, region_id='y42000_x49500'), Subset(xstart=63000, xend=67500, ystart=18000, yend=24000, region_id='y18000_x63000'), Subset(xstart=108000, xend=112500, ystart=96000, yend=101538, region_id='y96000_x108000'), Subset(xstart=94500, xend=99000, ystart=84000, yend=90000, region_id='y84000_x94500'), Subset(xstart=139500, xend=144000, ystart=12000, yend=18000, region_id='y12000_x139500'), Subset(xstart=40500, xend=45000, ystart=6000, yend=12000, region_id='y6000_x40500'), Subset(xstart=76500, xend=81000, ystart=12000, yend=18000, region_id='y12000_x76500'), Subset(xstart=27000, xend=31500, ystart=60000, yend=66000, region_id='y60000_x27000'), Subset(xstart=67500, xend=72000, ystart=78000, yend=84000, region_id='y78000_x67500'), Subset(xstart=139500, xend=144000, ystart=0, yend=6000, region_id='y0_x139500'), Subset(xstart=4500, xend=9000, ystart=24000, yend=30000, region_id='y24000_x4500'), Subset(xstart=126000, xend=130500, ystart=0, yend=6000, region_id='y0_x126000'), Subset(xstart=135000, xend=139500, ystart=90000, yend=96000, region_id='y90000_x135000'), Subset(xstart=13500, xend=18000, ystart=42000, yend=48000, region_id='y42000_x13500'), Subset(xstart=117000, xend=121500, ystart=6000, yend=12000, region_id='y6000_x117000'), Subset(xstart=148500, xend=153000, ystart=54000, yend=60000, region_id='y54000_x148500'), Subset(xstart=94500, xend=99000, ystart=72000, yend=78000, region_id='y72000_x94500'), Subset(xstart=58500, xend=63000, ystart=84000, yend=90000, region_id='y84000_x58500'), Subset(xstart=0, xend=4500, ystart=66000, yend=72000, region_id='y66000_x0'), Subset(xstart=90000, xend=94500, ystart=36000, yend=42000, region_id='y36000_x90000'), Subset(xstart=63000, xend=67500, ystart=90000, yend=96000, region_id='y90000_x63000'), Subset(xstart=22500, xend=27000, ystart=48000, yend=54000, region_id='y48000_x22500'), Subset(xstart=54000, xend=58500, ystart=66000, yend=72000, region_id='y66000_x54000'), Subset(xstart=90000, xend=94500, ystart=60000, yend=66000, region_id='y60000_x90000'), Subset(xstart=54000, xend=58500, ystart=60000, yend=66000, region_id='y60000_x54000'), Subset(xstart=108000, xend=112500, ystart=84000, yend=90000, region_id='y84000_x108000'), Subset(xstart=130500, xend=135000, ystart=48000, yend=54000, region_id='y48000_x130500'), Subset(xstart=121500, xend=126000, ystart=36000, yend=42000, region_id='y36000_x121500'), Subset(xstart=135000, xend=139500, ystart=6000, yend=12000, region_id='y6000_x135000'), Subset(xstart=76500, xend=81000, ystart=54000, yend=60000, region_id='y54000_x76500'), Subset(xstart=22500, xend=27000, ystart=66000, yend=72000, region_id='y66000_x22500'), Subset(xstart=40500, xend=45000, ystart=78000, yend=84000, region_id='y78000_x40500'), Subset(xstart=121500, xend=126000, ystart=30000, yend=36000, region_id='y30000_x121500'), Subset(xstart=90000, xend=94500, ystart=96000, yend=101538, region_id='y96000_x90000'), Subset(xstart=27000, xend=31500, ystart=18000, yend=24000, region_id='y18000_x27000'), Subset(xstart=153000, xend=156335, ystart=18000, yend=24000, region_id='y18000_x153000'), Subset(xstart=67500, xend=72000, ystart=96000, yend=101538, region_id='y96000_x67500'), Subset(xstart=121500, xend=126000, ystart=54000, yend=60000, region_id='y54000_x121500'), Subset(xstart=54000, xend=58500, ystart=0, yend=6000, region_id='y0_x54000'), Subset(xstart=81000, xend=85500, ystart=72000, yend=78000, region_id='y72000_x81000'), Subset(xstart=63000, xend=67500, ystart=0, yend=6000, region_id='y0_x63000'), Subset(xstart=99000, xend=103500, ystart=12000, yend=18000, region_id='y12000_x99000'), Subset(xstart=72000, xend=76500, ystart=72000, yend=78000, region_id='y72000_x72000'), Subset(xstart=108000, xend=112500, ystart=24000, yend=30000, region_id='y24000_x108000'), Subset(xstart=144000, xend=148500, ystart=30000, yend=36000, region_id='y30000_x144000'), Subset(xstart=72000, xend=76500, ystart=18000, yend=24000, region_id='y18000_x72000'), Subset(xstart=4500, xend=9000, ystart=66000, yend=72000, region_id='y66000_x4500'), Subset(xstart=0, xend=4500, ystart=12000, yend=18000, region_id='y12000_x0'), Subset(xstart=144000, xend=148500, ystart=54000, yend=60000, region_id='y54000_x144000'), Subset(xstart=108000, xend=112500, ystart=54000, yend=60000, region_id='y54000_x108000'), Subset(xstart=139500, xend=144000, ystart=36000, yend=42000, region_id='y36000_x139500'), Subset(xstart=139500, xend=144000, ystart=60000, yend=66000, region_id='y60000_x139500'), Subset(xstart=18000, xend=22500, ystart=84000, yend=90000, region_id='y84000_x18000'), Subset(xstart=81000, xend=85500, ystart=0, yend=6000, region_id='y0_x81000'), Subset(xstart=54000, xend=58500, ystart=18000, yend=24000, region_id='y18000_x54000'), Subset(xstart=49500, xend=54000, ystart=0, yend=6000, region_id='y0_x49500'), Subset(xstart=99000, xend=103500, ystart=84000, yend=90000, region_id='y84000_x99000'), Subset(xstart=117000, xend=121500, ystart=90000, yend=96000, region_id='y90000_x117000'), Subset(xstart=90000, xend=94500, ystart=18000, yend=24000, region_id='y18000_x90000'), Subset(xstart=135000, xend=139500, ystart=96000, yend=101538, region_id='y96000_x135000'), Subset(xstart=31500, xend=36000, ystart=90000, yend=96000, region_id='y90000_x31500'), Subset(xstart=130500, xend=135000, ystart=96000, yend=101538, region_id='y96000_x130500'), Subset(xstart=81000, xend=85500, ystart=12000, yend=18000, region_id='y12000_x81000'), Subset(xstart=135000, xend=139500, ystart=36000, yend=42000, region_id='y36000_x135000'), Subset(xstart=13500, xend=18000, ystart=96000, yend=101538, region_id='y96000_x13500'), Subset(xstart=27000, xend=31500, ystart=30000, yend=36000, region_id='y30000_x27000'), Subset(xstart=81000, xend=85500, ystart=84000, yend=90000, region_id='y84000_x81000'), Subset(xstart=63000, xend=67500, ystart=78000, yend=84000, region_id='y78000_x63000'), Subset(xstart=45000, xend=49500, ystart=24000, yend=30000, region_id='y24000_x45000'), Subset(xstart=22500, xend=27000, ystart=54000, yend=60000, region_id='y54000_x22500'), Subset(xstart=49500, xend=54000, ystart=24000, yend=30000, region_id='y24000_x49500'), Subset(xstart=76500, xend=81000, ystart=84000, yend=90000, region_id='y84000_x76500'), Subset(xstart=4500, xend=9000, ystart=36000, yend=42000, region_id='y36000_x4500'), Subset(xstart=22500, xend=27000, ystart=90000, yend=96000, region_id='y90000_x22500'), Subset(xstart=117000, xend=121500, ystart=12000, yend=18000, region_id='y12000_x117000'), Subset(xstart=67500, xend=72000, ystart=48000, yend=54000, region_id='y48000_x67500'), Subset(xstart=40500, xend=45000, ystart=30000, yend=36000, region_id='y30000_x40500'), Subset(xstart=76500, xend=81000, ystart=0, yend=6000, region_id='y0_x76500'), Subset(xstart=108000, xend=112500, ystart=0, yend=6000, region_id='y0_x108000'), Subset(xstart=45000, xend=49500, ystart=66000, yend=72000, region_id='y66000_x45000'), Subset(xstart=148500, xend=153000, ystart=96000, yend=101538, region_id='y96000_x148500'), Subset(xstart=94500, xend=99000, ystart=66000, yend=72000, region_id='y66000_x94500'), Subset(xstart=67500, xend=72000, ystart=24000, yend=30000, region_id='y24000_x67500'), Subset(xstart=144000, xend=148500, ystart=78000, yend=84000, region_id='y78000_x144000'), Subset(xstart=81000, xend=85500, ystart=42000, yend=48000, region_id='y42000_x81000'), Subset(xstart=117000, xend=121500, ystart=0, yend=6000, region_id='y0_x117000'), Subset(xstart=72000, xend=76500, ystart=54000, yend=60000, region_id='y54000_x72000'), Subset(xstart=126000, xend=130500, ystart=78000, yend=84000, region_id='y78000_x126000'), Subset(xstart=45000, xend=49500, ystart=84000, yend=90000, region_id='y84000_x45000'), Subset(xstart=31500, xend=36000, ystart=54000, yend=60000, region_id='y54000_x31500'), Subset(xstart=126000, xend=130500, ystart=30000, yend=36000, region_id='y30000_x126000'), Subset(xstart=49500, xend=54000, ystart=60000, yend=66000, region_id='y60000_x49500'), Subset(xstart=108000, xend=112500, ystart=48000, yend=54000, region_id='y48000_x108000'), Subset(xstart=81000, xend=85500, ystart=6000, yend=12000, region_id='y6000_x81000'), Subset(xstart=76500, xend=81000, ystart=96000, yend=101538, region_id='y96000_x76500'), Subset(xstart=54000, xend=58500, ystart=42000, yend=48000, region_id='y42000_x54000'), Subset(xstart=76500, xend=81000, ystart=36000, yend=42000, region_id='y36000_x76500'), Subset(xstart=117000, xend=121500, ystart=78000, yend=84000, region_id='y78000_x117000'), Subset(xstart=144000, xend=148500, ystart=12000, yend=18000, region_id='y12000_x144000'), Subset(xstart=85500, xend=90000, ystart=18000, yend=24000, region_id='y18000_x85500'), Subset(xstart=9000, xend=13500, ystart=42000, yend=48000, region_id='y42000_x9000'), Subset(xstart=58500, xend=63000, ystart=30000, yend=36000, region_id='y30000_x58500'), Subset(xstart=58500, xend=63000, ystart=60000, yend=66000, region_id='y60000_x58500'), Subset(xstart=144000, xend=148500, ystart=48000, yend=54000, region_id='y48000_x144000'), Subset(xstart=112500, xend=117000, ystart=96000, yend=101538, region_id='y96000_x112500'), Subset(xstart=49500, xend=54000, ystart=30000, yend=36000, region_id='y30000_x49500'), Subset(xstart=40500, xend=45000, ystart=12000, yend=18000, region_id='y12000_x40500'), Subset(xstart=22500, xend=27000, ystart=84000, yend=90000, region_id='y84000_x22500'), Subset(xstart=22500, xend=27000, ystart=42000, yend=48000, region_id='y42000_x22500'), Subset(xstart=36000, xend=40500, ystart=0, yend=6000, region_id='y0_x36000'), Subset(xstart=112500, xend=117000, ystart=30000, yend=36000, region_id='y30000_x112500'), Subset(xstart=36000, xend=40500, ystart=66000, yend=72000, region_id='y66000_x36000'), Subset(xstart=0, xend=4500, ystart=24000, yend=30000, region_id='y24000_x0'), Subset(xstart=153000, xend=156335, ystart=54000, yend=60000, region_id='y54000_x153000'), Subset(xstart=9000, xend=13500, ystart=60000, yend=66000, region_id='y60000_x9000'), Subset(xstart=58500, xend=63000, ystart=54000, yend=60000, region_id='y54000_x58500'), Subset(xstart=103500, xend=108000, ystart=90000, yend=96000, region_id='y90000_x103500'), Subset(xstart=153000, xend=156335, ystart=84000, yend=90000, region_id='y84000_x153000'), Subset(xstart=67500, xend=72000, ystart=66000, yend=72000, region_id='y66000_x67500'), Subset(xstart=130500, xend=135000, ystart=72000, yend=78000, region_id='y72000_x130500'), Subset(xstart=4500, xend=9000, ystart=30000, yend=36000, region_id='y30000_x4500'), Subset(xstart=54000, xend=58500, ystart=36000, yend=42000, region_id='y36000_x54000'), Subset(xstart=144000, xend=148500, ystart=60000, yend=66000, region_id='y60000_x144000'), Subset(xstart=153000, xend=156335, ystart=0, yend=6000, region_id='y0_x153000'), Subset(xstart=112500, xend=117000, ystart=84000, yend=90000, region_id='y84000_x112500'), Subset(xstart=18000, xend=22500, ystart=12000, yend=18000, region_id='y12000_x18000'), Subset(xstart=22500, xend=27000, ystart=30000, yend=36000, region_id='y30000_x22500'), Subset(xstart=139500, xend=144000, ystart=84000, yend=90000, region_id='y84000_x139500'), Subset(xstart=126000, xend=130500, ystart=96000, yend=101538, region_id='y96000_x126000'), Subset(xstart=94500, xend=99000, ystart=12000, yend=18000, region_id='y12000_x94500'), Subset(xstart=36000, xend=40500, ystart=24000, yend=30000, region_id='y24000_x36000'), Subset(xstart=27000, xend=31500, ystart=54000, yend=60000, region_id='y54000_x27000'), Subset(xstart=99000, xend=103500, ystart=48000, yend=54000, region_id='y48000_x99000'), Subset(xstart=148500, xend=153000, ystart=24000, yend=30000, region_id='y24000_x148500'), Subset(xstart=135000, xend=139500, ystart=24000, yend=30000, region_id='y24000_x135000'), Subset(xstart=36000, xend=40500, ystart=48000, yend=54000, region_id='y48000_x36000'), Subset(xstart=0, xend=4500, ystart=72000, yend=78000, region_id='y72000_x0'), Subset(xstart=31500, xend=36000, ystart=42000, yend=48000, region_id='y42000_x31500'), Subset(xstart=4500, xend=9000, ystart=42000, yend=48000, region_id='y42000_x4500'), Subset(xstart=13500, xend=18000, ystart=24000, yend=30000, region_id='y24000_x13500'), Subset(xstart=58500, xend=63000, ystart=96000, yend=101538, region_id='y96000_x58500'), Subset(xstart=63000, xend=67500, ystart=54000, yend=60000, region_id='y54000_x63000'), Subset(xstart=108000, xend=112500, ystart=12000, yend=18000, region_id='y12000_x108000'), Subset(xstart=0, xend=4500, ystart=0, yend=6000, region_id='y0_x0'), Subset(xstart=121500, xend=126000, ystart=48000, yend=54000, region_id='y48000_x121500'), Subset(xstart=63000, xend=67500, ystart=48000, yend=54000, region_id='y48000_x63000'), Subset(xstart=144000, xend=148500, ystart=90000, yend=96000, region_id='y90000_x144000'), Subset(xstart=144000, xend=148500, ystart=96000, yend=101538, region_id='y96000_x144000'), Subset(xstart=54000, xend=58500, ystart=24000, yend=30000, region_id='y24000_x54000'), Subset(xstart=144000, xend=148500, ystart=0, yend=6000, region_id='y0_x144000'), Subset(xstart=63000, xend=67500, ystart=66000, yend=72000, region_id='y66000_x63000'), Subset(xstart=148500, xend=153000, ystart=36000, yend=42000, region_id='y36000_x148500'), Subset(xstart=27000, xend=31500, ystart=78000, yend=84000, region_id='y78000_x27000'), Subset(xstart=108000, xend=112500, ystart=6000, yend=12000, region_id='y6000_x108000'), Subset(xstart=112500, xend=117000, ystart=18000, yend=24000, region_id='y18000_x112500'), Subset(xstart=112500, xend=117000, ystart=90000, yend=96000, region_id='y90000_x112500'), Subset(xstart=153000, xend=156335, ystart=90000, yend=96000, region_id='y90000_x153000'), Subset(xstart=4500, xend=9000, ystart=78000, yend=84000, region_id='y78000_x4500'), Subset(xstart=31500, xend=36000, ystart=12000, yend=18000, region_id='y12000_x31500'), Subset(xstart=40500, xend=45000, ystart=96000, yend=101538, region_id='y96000_x40500'), Subset(xstart=22500, xend=27000, ystart=78000, yend=84000, region_id='y78000_x22500'), Subset(xstart=148500, xend=153000, ystart=84000, yend=90000, region_id='y84000_x148500'), Subset(xstart=31500, xend=36000, ystart=84000, yend=90000, region_id='y84000_x31500'), Subset(xstart=76500, xend=81000, ystart=60000, yend=66000, region_id='y60000_x76500'), Subset(xstart=63000, xend=67500, ystart=96000, yend=101538, region_id='y96000_x63000'), Subset(xstart=121500, xend=126000, ystart=24000, yend=30000, region_id='y24000_x121500'), Subset(xstart=72000, xend=76500, ystart=66000, yend=72000, region_id='y66000_x72000'), Subset(xstart=45000, xend=49500, ystart=72000, yend=78000, region_id='y72000_x45000'), Subset(xstart=27000, xend=31500, ystart=96000, yend=101538, region_id='y96000_x27000'), Subset(xstart=63000, xend=67500, ystart=6000, yend=12000, region_id='y6000_x63000'), Subset(xstart=121500, xend=126000, ystart=18000, yend=24000, region_id='y18000_x121500'), Subset(xstart=0, xend=4500, ystart=90000, yend=96000, region_id='y90000_x0'), Subset(xstart=0, xend=4500, ystart=18000, yend=24000, region_id='y18000_x0'), Subset(xstart=22500, xend=27000, ystart=96000, yend=101538, region_id='y96000_x22500'), Subset(xstart=0, xend=4500, ystart=30000, yend=36000, region_id='y30000_x0'), Subset(xstart=130500, xend=135000, ystart=36000, yend=42000, region_id='y36000_x130500'), Subset(xstart=18000, xend=22500, ystart=0, yend=6000, region_id='y0_x18000'), Subset(xstart=18000, xend=22500, ystart=66000, yend=72000, region_id='y66000_x18000'), Subset(xstart=40500, xend=45000, ystart=18000, yend=24000, region_id='y18000_x40500'), Subset(xstart=45000, xend=49500, ystart=12000, yend=18000, region_id='y12000_x45000'), Subset(xstart=144000, xend=148500, ystart=42000, yend=48000, region_id='y42000_x144000'), Subset(xstart=76500, xend=81000, ystart=66000, yend=72000, region_id='y66000_x76500'), Subset(xstart=94500, xend=99000, ystart=24000, yend=30000, region_id='y24000_x94500'), Subset(xstart=121500, xend=126000, ystart=6000, yend=12000, region_id='y6000_x121500'), Subset(xstart=90000, xend=94500, ystart=66000, yend=72000, region_id='y66000_x90000'), Subset(xstart=121500, xend=126000, ystart=60000, yend=66000, region_id='y60000_x121500'), Subset(xstart=0, xend=4500, ystart=54000, yend=60000, region_id='y54000_x0'), Subset(xstart=130500, xend=135000, ystart=60000, yend=66000, region_id='y60000_x130500'), Subset(xstart=54000, xend=58500, ystart=72000, yend=78000, region_id='y72000_x54000'), Subset(xstart=94500, xend=99000, ystart=36000, yend=42000, region_id='y36000_x94500'), Subset(xstart=139500, xend=144000, ystart=42000, yend=48000, region_id='y42000_x139500'), Subset(xstart=13500, xend=18000, ystart=18000, yend=24000, region_id='y18000_x13500'), Subset(xstart=135000, xend=139500, ystart=72000, yend=78000, region_id='y72000_x135000'), Subset(xstart=99000, xend=103500, ystart=30000, yend=36000, region_id='y30000_x99000'), Subset(xstart=99000, xend=103500, ystart=78000, yend=84000, region_id='y78000_x99000'), Subset(xstart=103500, xend=108000, ystart=24000, yend=30000, region_id='y24000_x103500'), Subset(xstart=112500, xend=117000, ystart=78000, yend=84000, region_id='y78000_x112500'), Subset(xstart=148500, xend=153000, ystart=78000, yend=84000, region_id='y78000_x148500'), Subset(xstart=63000, xend=67500, ystart=60000, yend=66000, region_id='y60000_x63000'), Subset(xstart=18000, xend=22500, ystart=90000, yend=96000, region_id='y90000_x18000'), Subset(xstart=13500, xend=18000, ystart=84000, yend=90000, region_id='y84000_x13500'), Subset(xstart=85500, xend=90000, ystart=66000, yend=72000, region_id='y66000_x85500'), Subset(xstart=112500, xend=117000, ystart=12000, yend=18000, region_id='y12000_x112500'), Subset(xstart=81000, xend=85500, ystart=24000, yend=30000, region_id='y24000_x81000'), Subset(xstart=112500, xend=117000, ystart=24000, yend=30000, region_id='y24000_x112500'), Subset(xstart=139500, xend=144000, ystart=96000, yend=101538, region_id='y96000_x139500'), Subset(xstart=45000, xend=49500, ystart=36000, yend=42000, region_id='y36000_x45000'), Subset(xstart=18000, xend=22500, ystart=96000, yend=101538, region_id='y96000_x18000'), Subset(xstart=130500, xend=135000, ystart=6000, yend=12000, region_id='y6000_x130500'), Subset(xstart=85500, xend=90000, ystart=96000, yend=101538, region_id='y96000_x85500'), Subset(xstart=121500, xend=126000, ystart=66000, yend=72000, region_id='y66000_x121500'), Subset(xstart=94500, xend=99000, ystart=78000, yend=84000, region_id='y78000_x94500'), Subset(xstart=67500, xend=72000, ystart=42000, yend=48000, region_id='y42000_x67500'), Subset(xstart=36000, xend=40500, ystart=12000, yend=18000, region_id='y12000_x36000'), Subset(xstart=40500, xend=45000, ystart=36000, yend=42000, region_id='y36000_x40500'), Subset(xstart=49500, xend=54000, ystart=84000, yend=90000, region_id='y84000_x49500'), Subset(xstart=144000, xend=148500, ystart=6000, yend=12000, region_id='y6000_x144000'), Subset(xstart=27000, xend=31500, ystart=84000, yend=90000, region_id='y84000_x27000'), Subset(xstart=9000, xend=13500, ystart=18000, yend=24000, region_id='y18000_x9000'), Subset(xstart=13500, xend=18000, ystart=90000, yend=96000, region_id='y90000_x13500'), Subset(xstart=54000, xend=58500, ystart=78000, yend=84000, region_id='y78000_x54000'), Subset(xstart=49500, xend=54000, ystart=78000, yend=84000, region_id='y78000_x49500'), Subset(xstart=72000, xend=76500, ystart=42000, yend=48000, region_id='y42000_x72000'), Subset(xstart=36000, xend=40500, ystart=84000, yend=90000, region_id='y84000_x36000'), Subset(xstart=27000, xend=31500, ystart=12000, yend=18000, region_id='y12000_x27000'), Subset(xstart=18000, xend=22500, ystart=6000, yend=12000, region_id='y6000_x18000'), Subset(xstart=139500, xend=144000, ystart=78000, yend=84000, region_id='y78000_x139500'), Subset(xstart=45000, xend=49500, ystart=90000, yend=96000, region_id='y90000_x45000'), Subset(xstart=67500, xend=72000, ystart=12000, yend=18000, region_id='y12000_x67500'), Subset(xstart=130500, xend=135000, ystart=54000, yend=60000, region_id='y54000_x130500'), Subset(xstart=112500, xend=117000, ystart=66000, yend=72000, region_id='y66000_x112500'), Subset(xstart=36000, xend=40500, ystart=36000, yend=42000, region_id='y36000_x36000'), Subset(xstart=40500, xend=45000, ystart=90000, yend=96000, region_id='y90000_x40500'), Subset(xstart=148500, xend=153000, ystart=0, yend=6000, region_id='y0_x148500'), Subset(xstart=31500, xend=36000, ystart=0, yend=6000, region_id='y0_x31500'), Subset(xstart=99000, xend=103500, ystart=66000, yend=72000, region_id='y66000_x99000'), Subset(xstart=90000, xend=94500, ystart=12000, yend=18000, region_id='y12000_x90000'), Subset(xstart=112500, xend=117000, ystart=36000, yend=42000, region_id='y36000_x112500'), Subset(xstart=103500, xend=108000, ystart=48000, yend=54000, region_id='y48000_x103500'), Subset(xstart=130500, xend=135000, ystart=66000, yend=72000, region_id='y66000_x130500'), Subset(xstart=99000, xend=103500, ystart=60000, yend=66000, region_id='y60000_x99000'), Subset(xstart=9000, xend=13500, ystart=66000, yend=72000, region_id='y66000_x9000'), Subset(xstart=126000, xend=130500, ystart=42000, yend=48000, region_id='y42000_x126000'), Subset(xstart=45000, xend=49500, ystart=18000, yend=24000, region_id='y18000_x45000'), Subset(xstart=49500, xend=54000, ystart=48000, yend=54000, region_id='y48000_x49500'), Subset(xstart=67500, xend=72000, ystart=36000, yend=42000, region_id='y36000_x67500'), Subset(xstart=139500, xend=144000, ystart=54000, yend=60000, region_id='y54000_x139500'), Subset(xstart=148500, xend=153000, ystart=12000, yend=18000, region_id='y12000_x148500'), Subset(xstart=58500, xend=63000, ystart=6000, yend=12000, region_id='y6000_x58500'), Subset(xstart=58500, xend=63000, ystart=72000, yend=78000, region_id='y72000_x58500'), Subset(xstart=4500, xend=9000, ystart=60000, yend=66000, region_id='y60000_x4500'), Subset(xstart=144000, xend=148500, ystart=36000, yend=42000, region_id='y36000_x144000'), Subset(xstart=0, xend=4500, ystart=60000, yend=66000, region_id='y60000_x0')]\n",
"writing 300 new regions\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/coiled/env/lib/python3.11/site-packages/distributed/client.py:3357: UserWarning: Sending large graph of size 24.60 MiB.\n",
"This may cause some slowdown.\n",
"Consider loading the data with Dask directly\n",
" or using futures or delayed objects to embed the data into the graph without repetition.\n",
"See also https://docs.dask.org/en/stable/best-practices.html#load-data-with-dask for more information.\n",
" warnings.warn(\n"
]
}
],
"source": [
"import random \n",
"subset_list_half = random.sample(subset_list, 300)\n",
"\n",
"repo = icechunk.Repository.open(storage)\n",
"session = repo.writable_session('main')\n",
"write_regions(session, ds, subset_list_half)\n",
"\n",
"half_msgs = get_commit_messages_ancestry(repo)"
]
},
{
"cell_type": "markdown",
"id": "59bbc4b6-1099-493c-abb7-b5c470e5ca4e",
"metadata": {},
"source": [
"# check RT"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "78d98cf8-b613-4484-9c79-c8f57385eab4",
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"</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 63GB\n",
"Dimensions: (y: 101538, x: 156335)\n",
"Coordinates:\n",
" * x (x) float64 1MB -2.362e+06 -2.362e+06 ... 2.328e+06 2.328e+06\n",
" * y (y) float64 812kB 3.267e+06 3.267e+06 ... 2.213e+05 2.213e+05\n",
"Data variables:\n",
" BP (y, x) float32 63GB dask.array&lt;chunksize=(6000, 4500), meta=np.ndarray&gt;</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c16b5879-f92c-49c7-9743-ae0c8dabe6c6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c16b5879-f92c-49c7-9743-ae0c8dabe6c6' class='xr-section-summary' title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>y</span>: 101538</li><li><span class='xr-has-index'>x</span>: 156335</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-aa26cda2-3499-4d80-a1aa-f49a8b79a3b8' class='xr-section-summary-in' type='checkbox' checked><label for='section-aa26cda2-3499-4d80-a1aa-f49a8b79a3b8' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.362e+06 -2.362e+06 ... 2.328e+06</div><input id='attrs-f102180f-217e-4c5a-90c7-c60b438ab812' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f102180f-217e-4c5a-90c7-c60b438ab812' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5e45ca7-0931-43bb-a93d-3aee6b09b035' class='xr-var-data-in' type='checkbox'><label for='data-b5e45ca7-0931-43bb-a93d-3aee6b09b035' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([-2362380., -2362350., -2362320., ..., 2327580., 2327610., 2327640.],\n",
" shape=(156335,))</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.267e+06 3.267e+06 ... 2.213e+05</div><input id='attrs-0fc95688-ee8f-423a-96d4-54f7c8a126ed' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0fc95688-ee8f-423a-96d4-54f7c8a126ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0216f2a3-764c-4875-a695-44ca709d0855' class='xr-var-data-in' type='checkbox'><label for='data-0216f2a3-764c-4875-a695-44ca709d0855' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([3267390., 3267360., 3267330., ..., 221340., 221310., 221280.],\n",
" shape=(101538,))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-949890d6-d550-4bc7-9fe9-7cb820c948ef' class='xr-section-summary-in' type='checkbox' checked><label for='section-949890d6-d550-4bc7-9fe9-7cb820c948ef' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>BP</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(6000, 4500), meta=np.ndarray&gt;</div><input id='attrs-b4fc9b5b-8f02-4eaa-8b33-7ec065f65b32' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-b4fc9b5b-8f02-4eaa-8b33-7ec065f65b32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d7bfc7b5-ffc1-41a0-9eb3-0aadb35b0845' class='xr-var-data-in' type='checkbox'><label for='data-d7bfc7b5-ffc1-41a0-9eb3-0aadb35b0845' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
" <tr>\n",
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" <th> Array </th>\n",
" <th> Chunk </th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" \n",
" <tr>\n",
" <th> Bytes </th>\n",
" <td> 59.14 GiB </td>\n",
" <td> 103.00 MiB </td>\n",
" </tr>\n",
" \n",
" <tr>\n",
" <th> Shape </th>\n",
" <td> (101538, 156335) </td>\n",
" <td> (6000, 4500) </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Dask graph </th>\n",
" <td colspan=\"2\"> 595 chunks in 2 graph layers </td>\n",
" </tr>\n",
" <tr>\n",
" <th> Data type </th>\n",
" <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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" </tbody>\n",
" </table>\n",
" </td>\n",
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" <line x1=\"48\" y1=\"0\" x2=\"48\" y2=\"77\" />\n",
" <line x1=\"55\" y1=\"0\" x2=\"55\" y2=\"77\" />\n",
" <line x1=\"62\" y1=\"0\" x2=\"62\" y2=\"77\" />\n",
" <line x1=\"69\" y1=\"0\" x2=\"69\" y2=\"77\" />\n",
" <line x1=\"75\" y1=\"0\" x2=\"75\" y2=\"77\" />\n",
" <line x1=\"79\" y1=\"0\" x2=\"79\" y2=\"77\" />\n",
" <line x1=\"86\" y1=\"0\" x2=\"86\" y2=\"77\" />\n",
" <line x1=\"93\" y1=\"0\" x2=\"93\" y2=\"77\" />\n",
" <line x1=\"100\" y1=\"0\" x2=\"100\" y2=\"77\" />\n",
" <line x1=\"107\" y1=\"0\" x2=\"107\" y2=\"77\" />\n",
" <line x1=\"113\" y1=\"0\" x2=\"113\" y2=\"77\" />\n",
" <line x1=\"120\" y1=\"0\" x2=\"120\" y2=\"77\" style=\"stroke-width:2\" />\n",
"\n",
" <!-- Colored Rectangle -->\n",
" <polygon points=\"0.0,0.0 120.0,0.0 120.0,77.93878530079637 0.0,77.93878530079637\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
"\n",
" <!-- Text -->\n",
" <text x=\"60.000000\" y=\"97.938785\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >156335</text>\n",
" <text x=\"140.000000\" y=\"38.969393\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,38.969393)\">101538</text>\n",
"</svg>\n",
" </td>\n",
" </tr>\n",
"</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-a6b7a507-18cc-460a-a408-0f89e9887e19' class='xr-section-summary-in' type='checkbox' ><label for='section-a6b7a507-18cc-460a-a408-0f89e9887e19' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-0bc84fe9-645c-400c-9104-4cd698e7a405' class='xr-index-data-in' type='checkbox'/><label for='index-0bc84fe9-645c-400c-9104-4cd698e7a405' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-2362380.000000001, -2362350.000000001, -2362320.000000001,\n",
" -2362290.000000001, -2362260.000000001, -2362230.000000001,\n",
" -2362200.000000001, -2362170.000000001, -2362140.000000001,\n",
" -2362110.000000001,\n",
" ...\n",
" 2327369.999999999, 2327399.999999999, 2327429.999999999,\n",
" 2327459.999999999, 2327489.999999999, 2327519.999999999,\n",
" 2327549.999999999, 2327579.999999999, 2327609.999999999,\n",
" 2327639.999999999],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=156335))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><input type='checkbox' disabled/><label></label><input id='index-b1b02694-87a3-44e0-a0b0-f654b65eb01f' class='xr-index-data-in' type='checkbox'/><label for='index-b1b02694-87a3-44e0-a0b0-f654b65eb01f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([3267390.0000000037, 3267360.0000000037, 3267330.0000000037,\n",
" 3267300.0000000037, 3267270.0000000037, 3267240.0000000037,\n",
" 3267210.0000000037, 3267180.0000000037, 3267150.0000000037,\n",
" 3267120.0000000037,\n",
" ...\n",
" 221550.00000000373, 221520.00000000373, 221490.00000000373,\n",
" 221460.00000000373, 221430.00000000373, 221400.00000000373,\n",
" 221370.00000000373, 221340.00000000373, 221310.00000000373,\n",
" 221280.00000000373],\n",
" dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=101538))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-353e9ce3-c568-4030-9a59-d185124a6ac8' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-353e9ce3-c568-4030-9a59-d185124a6ac8' class='xr-section-summary' title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
],
"text/plain": [
"<xarray.Dataset> Size: 63GB\n",
"Dimensions: (y: 101538, x: 156335)\n",
"Coordinates:\n",
" * x (x) float64 1MB -2.362e+06 -2.362e+06 ... 2.328e+06 2.328e+06\n",
" * y (y) float64 812kB 3.267e+06 3.267e+06 ... 2.213e+05 2.213e+05\n",
"Data variables:\n",
" BP (y, x) float32 63GB dask.array<chunksize=(6000, 4500), meta=np.ndarray>"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"rosesh = repo.readonly_session('main')\n",
"rtds = xr.open_zarr(rosesh.store, consolidated=False)\n",
"rtds"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "f1a7fb66-efd3-40ed-b628-cab68c486030",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0xfffe4411a110>"
]
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"\n",
"rtds.isel(y=slice(0,90000), x=slice(0,120000)).coarsen(x=10,y=10, boundary='trim').mean()['BP'].plot()"
]
},
{
"cell_type": "markdown",
"id": "d6385e9c",
"metadata": {},
"source": [
"## Write all the regions \"fill in\""
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "872b6c8a-e043-4489-8222-4a7d26585524",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"already_commited_messages: ['y66000_x40500', 'y48000_x126000', 'y54000_x67500', 'y30000_x117000', 'y0_x135000', 'y84000_x4500', 'y6000_x90000', 'y6000_x49500', 'y36000_x117000', 'y72000_x103500', 'y12000_x135000', 'y84000_x130500', 'y78000_x18000', 'y96000_x45000', 'y48000_x112500', 'y36000_x58500', 'y66000_x81000', 'y90000_x27000', 'y0_x13500', 'y0_x85500', 'y12000_x4500', 'y48000_x0', 'y42000_x27000', 'y84000_x40500', 'y84000_x9000', 'y72000_x27000', 'y96000_x72000', 'y36000_x9000', 'y72000_x67500', 'y42000_x85500', 'y84000_x121500', 'y84000_x90000', 'y60000_x148500', 'y18000_x108000', 'y54000_x81000', 'y6000_x13500', 'y6000_x36000', 'y36000_x81000', 'y66000_x27000', 'y48000_x148500', 'y18000_x144000', 'y60000_x13500', 'y48000_x40500', 'y72000_x85500', 'y54000_x103500', 'y30000_x63000', 'y66000_x49500', 'y42000_x49500', 'y18000_x63000', 'y96000_x108000', 'y84000_x94500', 'y12000_x139500', 'y6000_x40500', 'y12000_x76500', 'y60000_x27000', 'y78000_x67500', 'y0_x139500', 'y24000_x4500', 'y0_x126000', 'y90000_x135000', 'y42000_x13500', 'y6000_x117000', 'y54000_x148500', 'y72000_x94500', 'y84000_x58500', 'y66000_x0', 'y36000_x90000', 'y90000_x63000', 'y48000_x22500', 'y66000_x54000', 'y60000_x90000', 'y60000_x54000', 'y84000_x108000', 'y48000_x130500', 'y36000_x121500', 'y6000_x135000', 'y54000_x76500', 'y66000_x22500', 'y78000_x40500', 'y30000_x121500', 'y96000_x90000', 'y18000_x27000', 'y18000_x153000', 'y96000_x67500', 'y54000_x121500', 'y0_x54000', 'y72000_x81000', 'y0_x63000', 'y12000_x99000', 'y72000_x72000', 'y24000_x108000', 'y30000_x144000', 'y18000_x72000', 'y66000_x4500', 'y12000_x0', 'y54000_x144000', 'y54000_x108000', 'y36000_x139500', 'y60000_x139500', 'y84000_x18000', 'y0_x81000', 'y18000_x54000', 'y0_x49500', 'y84000_x99000', 'y90000_x117000', 'y18000_x90000', 'y96000_x135000', 'y90000_x31500', 'y96000_x130500', 'y12000_x81000', 'y36000_x135000', 'y96000_x13500', 'y30000_x27000', 'y84000_x81000', 'y78000_x63000', 'y24000_x45000', 'y54000_x22500', 'y24000_x49500', 'y84000_x76500', 'y36000_x4500', 'y90000_x22500', 'y12000_x117000', 'y48000_x67500', 'y30000_x40500', 'y0_x76500', 'y0_x108000', 'y66000_x45000', 'y96000_x148500', 'y66000_x94500', 'y24000_x67500', 'y78000_x144000', 'y42000_x81000', 'y0_x117000', 'y54000_x72000', 'y78000_x126000', 'y84000_x45000', 'y54000_x31500', 'y30000_x126000', 'y60000_x49500', 'y48000_x108000', 'y6000_x81000', 'y96000_x76500', 'y42000_x54000', 'y36000_x76500', 'y78000_x117000', 'y12000_x144000', 'y18000_x85500', 'y42000_x9000', 'y30000_x58500', 'y60000_x58500', 'y48000_x144000', 'y96000_x112500', 'y30000_x49500', 'y12000_x40500', 'y84000_x22500', 'y42000_x22500', 'y0_x36000', 'y30000_x112500', 'y66000_x36000', 'y24000_x0', 'y54000_x153000', 'y60000_x9000', 'y54000_x58500', 'y90000_x103500', 'y84000_x153000', 'y66000_x67500', 'y72000_x130500', 'y30000_x4500', 'y36000_x54000', 'y60000_x144000', 'y0_x153000', 'y84000_x112500', 'y12000_x18000', 'y30000_x22500', 'y84000_x139500', 'y96000_x126000', 'y12000_x94500', 'y24000_x36000', 'y54000_x27000', 'y48000_x99000', 'y24000_x148500', 'y24000_x135000', 'y48000_x36000', 'y72000_x0', 'y42000_x31500', 'y42000_x4500', 'y24000_x13500', 'y96000_x58500', 'y54000_x63000', 'y12000_x108000', 'y0_x0', 'y48000_x121500', 'y48000_x63000', 'y90000_x144000', 'y96000_x144000', 'y24000_x54000', 'y0_x144000', 'y66000_x63000', 'y36000_x148500', 'y78000_x27000', 'y6000_x108000', 'y18000_x112500', 'y90000_x112500', 'y90000_x153000', 'y78000_x4500', 'y12000_x31500', 'y96000_x40500', 'y78000_x22500', 'y84000_x148500', 'y84000_x31500', 'y60000_x76500', 'y96000_x63000', 'y24000_x121500', 'y66000_x72000', 'y72000_x45000', 'y96000_x27000', 'y6000_x63000', 'y18000_x121500', 'y90000_x0', 'y18000_x0', 'y96000_x22500', 'y30000_x0', 'y36000_x130500', 'y0_x18000', 'y66000_x18000', 'y18000_x40500', 'y12000_x45000', 'y42000_x144000', 'y66000_x76500', 'y24000_x94500', 'y6000_x121500', 'y66000_x90000', 'y60000_x121500', 'y54000_x0', 'y60000_x130500', 'y72000_x54000', 'y36000_x94500', 'y42000_x139500', 'y18000_x13500', 'y72000_x135000', 'y30000_x99000', 'y78000_x99000', 'y24000_x103500', 'y78000_x112500', 'y78000_x148500', 'y60000_x63000', 'y90000_x18000', 'y84000_x13500', 'y66000_x85500', 'y12000_x112500', 'y24000_x81000', 'y24000_x112500', 'y96000_x139500', 'y36000_x45000', 'y96000_x18000', 'y6000_x130500', 'y96000_x85500', 'y66000_x121500', 'y78000_x94500', 'y42000_x67500', 'y12000_x36000', 'y36000_x40500', 'y84000_x49500', 'y6000_x144000', 'y84000_x27000', 'y18000_x9000', 'y90000_x13500', 'y78000_x54000', 'y78000_x49500', 'y42000_x72000', 'y84000_x36000', 'y12000_x27000', 'y6000_x18000', 'y78000_x139500', 'y90000_x45000', 'y12000_x67500', 'y54000_x130500', 'y66000_x112500', 'y36000_x36000', 'y90000_x40500', 'y0_x148500', 'y0_x31500', 'y66000_x99000', 'y12000_x90000', 'y36000_x112500', 'y48000_x103500', 'y66000_x130500', 'y60000_x99000', 'y66000_x9000', 'y42000_x126000', 'y18000_x45000', 'y48000_x49500', 'y36000_x67500', 'y54000_x139500', 'y12000_x148500', 'y6000_x58500', 'y72000_x58500', 'y60000_x4500', 'y36000_x144000', 'y60000_x0', 'template', 'Repository initialized']\n",
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yend=6000, region_id='y0_x103500'), Subset(xstart=112500, xend=117000, ystart=0, yend=6000, region_id='y0_x112500'), Subset(xstart=121500, xend=126000, ystart=0, yend=6000, region_id='y0_x121500'), Subset(xstart=130500, xend=135000, ystart=0, yend=6000, region_id='y0_x130500'), Subset(xstart=0, xend=4500, ystart=6000, yend=12000, region_id='y6000_x0'), Subset(xstart=4500, xend=9000, ystart=6000, yend=12000, region_id='y6000_x4500'), Subset(xstart=9000, xend=13500, ystart=6000, yend=12000, region_id='y6000_x9000'), Subset(xstart=22500, xend=27000, ystart=6000, yend=12000, region_id='y6000_x22500'), Subset(xstart=27000, xend=31500, ystart=6000, yend=12000, region_id='y6000_x27000'), Subset(xstart=31500, xend=36000, ystart=6000, yend=12000, region_id='y6000_x31500'), Subset(xstart=45000, xend=49500, ystart=6000, yend=12000, region_id='y6000_x45000'), Subset(xstart=54000, xend=58500, ystart=6000, yend=12000, region_id='y6000_x54000'), Subset(xstart=67500, xend=72000, ystart=6000, yend=12000, region_id='y6000_x67500'), Subset(xstart=72000, xend=76500, ystart=6000, yend=12000, region_id='y6000_x72000'), Subset(xstart=76500, xend=81000, ystart=6000, yend=12000, region_id='y6000_x76500'), Subset(xstart=85500, xend=90000, ystart=6000, yend=12000, region_id='y6000_x85500'), Subset(xstart=94500, xend=99000, ystart=6000, yend=12000, region_id='y6000_x94500'), Subset(xstart=99000, xend=103500, ystart=6000, yend=12000, region_id='y6000_x99000'), Subset(xstart=103500, xend=108000, ystart=6000, yend=12000, region_id='y6000_x103500'), Subset(xstart=112500, xend=117000, ystart=6000, yend=12000, region_id='y6000_x112500'), Subset(xstart=126000, xend=130500, ystart=6000, yend=12000, region_id='y6000_x126000'), Subset(xstart=139500, xend=144000, ystart=6000, yend=12000, region_id='y6000_x139500'), Subset(xstart=148500, xend=153000, ystart=6000, yend=12000, region_id='y6000_x148500'), Subset(xstart=153000, xend=156335, ystart=6000, yend=12000, region_id='y6000_x153000'), Subset(xstart=9000, xend=13500, ystart=12000, yend=18000, region_id='y12000_x9000'), Subset(xstart=13500, xend=18000, ystart=12000, yend=18000, region_id='y12000_x13500'), Subset(xstart=22500, xend=27000, ystart=12000, yend=18000, region_id='y12000_x22500'), Subset(xstart=49500, xend=54000, ystart=12000, yend=18000, region_id='y12000_x49500'), Subset(xstart=54000, xend=58500, ystart=12000, yend=18000, region_id='y12000_x54000'), Subset(xstart=58500, xend=63000, ystart=12000, yend=18000, region_id='y12000_x58500'), Subset(xstart=63000, xend=67500, ystart=12000, yend=18000, region_id='y12000_x63000'), Subset(xstart=72000, xend=76500, ystart=12000, yend=18000, region_id='y12000_x72000'), Subset(xstart=85500, xend=90000, ystart=12000, yend=18000, region_id='y12000_x85500'), Subset(xstart=103500, xend=108000, ystart=12000, yend=18000, region_id='y12000_x103500'), Subset(xstart=121500, xend=126000, ystart=12000, yend=18000, region_id='y12000_x121500'), Subset(xstart=126000, xend=130500, ystart=12000, yend=18000, region_id='y12000_x126000'), Subset(xstart=130500, xend=135000, ystart=12000, yend=18000, region_id='y12000_x130500'), Subset(xstart=153000, xend=156335, ystart=12000, yend=18000, region_id='y12000_x153000'), Subset(xstart=4500, xend=9000, ystart=18000, yend=24000, region_id='y18000_x4500'), Subset(xstart=18000, xend=22500, ystart=18000, yend=24000, region_id='y18000_x18000'), Subset(xstart=22500, xend=27000, ystart=18000, yend=24000, region_id='y18000_x22500'), Subset(xstart=31500, xend=36000, ystart=18000, yend=24000, region_id='y18000_x31500'), Subset(xstart=36000, xend=40500, ystart=18000, yend=24000, region_id='y18000_x36000'), Subset(xstart=49500, xend=54000, ystart=18000, yend=24000, region_id='y18000_x49500'), Subset(xstart=58500, xend=63000, ystart=18000, yend=24000, region_id='y18000_x58500'), Subset(xstart=67500, xend=72000, ystart=18000, yend=24000, region_id='y18000_x67500'), Subset(xstart=76500, xend=81000, ystart=18000, yend=24000, region_id='y18000_x76500'), Subset(xstart=81000, xend=85500, ystart=18000, yend=24000, region_id='y18000_x81000'), Subset(xstart=94500, xend=99000, ystart=18000, yend=24000, region_id='y18000_x94500'), Subset(xstart=99000, xend=103500, ystart=18000, yend=24000, region_id='y18000_x99000'), Subset(xstart=103500, xend=108000, ystart=18000, yend=24000, region_id='y18000_x103500'), Subset(xstart=117000, xend=121500, ystart=18000, yend=24000, region_id='y18000_x117000'), Subset(xstart=126000, xend=130500, ystart=18000, yend=24000, region_id='y18000_x126000'), Subset(xstart=130500, xend=135000, ystart=18000, yend=24000, region_id='y18000_x130500'), Subset(xstart=135000, xend=139500, ystart=18000, yend=24000, region_id='y18000_x135000'), Subset(xstart=139500, xend=144000, ystart=18000, yend=24000, region_id='y18000_x139500'), Subset(xstart=148500, xend=153000, ystart=18000, yend=24000, region_id='y18000_x148500'), Subset(xstart=9000, xend=13500, ystart=24000, yend=30000, region_id='y24000_x9000'), Subset(xstart=18000, xend=22500, ystart=24000, yend=30000, region_id='y24000_x18000'), Subset(xstart=22500, xend=27000, ystart=24000, yend=30000, region_id='y24000_x22500'), Subset(xstart=27000, xend=31500, ystart=24000, yend=30000, region_id='y24000_x27000'), Subset(xstart=31500, xend=36000, ystart=24000, yend=30000, region_id='y24000_x31500'), Subset(xstart=40500, xend=45000, ystart=24000, yend=30000, region_id='y24000_x40500'), Subset(xstart=58500, xend=63000, ystart=24000, yend=30000, region_id='y24000_x58500'), Subset(xstart=63000, xend=67500, ystart=24000, yend=30000, region_id='y24000_x63000'), Subset(xstart=72000, xend=76500, ystart=24000, yend=30000, region_id='y24000_x72000'), Subset(xstart=76500, xend=81000, ystart=24000, yend=30000, region_id='y24000_x76500'), Subset(xstart=85500, xend=90000, ystart=24000, yend=30000, region_id='y24000_x85500'), Subset(xstart=90000, xend=94500, ystart=24000, yend=30000, region_id='y24000_x90000'), Subset(xstart=99000, xend=103500, ystart=24000, yend=30000, region_id='y24000_x99000'), Subset(xstart=117000, xend=121500, ystart=24000, yend=30000, region_id='y24000_x117000'), Subset(xstart=126000, xend=130500, ystart=24000, yend=30000, region_id='y24000_x126000'), Subset(xstart=130500, xend=135000, ystart=24000, yend=30000, region_id='y24000_x130500'), Subset(xstart=139500, xend=144000, ystart=24000, yend=30000, region_id='y24000_x139500'), Subset(xstart=144000, xend=148500, ystart=24000, yend=30000, region_id='y24000_x144000'), Subset(xstart=153000, xend=156335, ystart=24000, yend=30000, region_id='y24000_x153000'), Subset(xstart=9000, xend=13500, ystart=30000, yend=36000, region_id='y30000_x9000'), Subset(xstart=13500, xend=18000, ystart=30000, yend=36000, region_id='y30000_x13500'), Subset(xstart=18000, xend=22500, ystart=30000, yend=36000, region_id='y30000_x18000'), Subset(xstart=31500, xend=36000, ystart=30000, yend=36000, region_id='y30000_x31500'), Subset(xstart=36000, xend=40500, ystart=30000, yend=36000, region_id='y30000_x36000'), Subset(xstart=45000, xend=49500, ystart=30000, yend=36000, region_id='y30000_x45000'), Subset(xstart=54000, xend=58500, ystart=30000, yend=36000, region_id='y30000_x54000'), Subset(xstart=67500, xend=72000, ystart=30000, yend=36000, region_id='y30000_x67500'), Subset(xstart=72000, xend=76500, ystart=30000, yend=36000, region_id='y30000_x72000'), Subset(xstart=76500, xend=81000, ystart=30000, yend=36000, region_id='y30000_x76500'), Subset(xstart=81000, xend=85500, ystart=30000, yend=36000, region_id='y30000_x81000'), Subset(xstart=85500, xend=90000, ystart=30000, yend=36000, region_id='y30000_x85500'), Subset(xstart=90000, xend=94500, ystart=30000, yend=36000, region_id='y30000_x90000'), Subset(xstart=94500, xend=99000, ystart=30000, yend=36000, region_id='y30000_x94500'), Subset(xstart=103500, xend=108000, ystart=30000, yend=36000, region_id='y30000_x103500'), Subset(xstart=108000, xend=112500, ystart=30000, yend=36000, region_id='y30000_x108000'), Subset(xstart=130500, xend=135000, ystart=30000, yend=36000, region_id='y30000_x130500'), Subset(xstart=135000, xend=139500, ystart=30000, yend=36000, region_id='y30000_x135000'), Subset(xstart=139500, xend=144000, ystart=30000, yend=36000, region_id='y30000_x139500'), Subset(xstart=148500, xend=153000, ystart=30000, yend=36000, region_id='y30000_x148500'), Subset(xstart=153000, xend=156335, ystart=30000, yend=36000, region_id='y30000_x153000'), Subset(xstart=0, xend=4500, ystart=36000, yend=42000, region_id='y36000_x0'), Subset(xstart=13500, xend=18000, ystart=36000, yend=42000, region_id='y36000_x13500'), Subset(xstart=18000, xend=22500, ystart=36000, yend=42000, region_id='y36000_x18000'), Subset(xstart=22500, xend=27000, ystart=36000, yend=42000, region_id='y36000_x22500'), Subset(xstart=27000, xend=31500, ystart=36000, yend=42000, region_id='y36000_x27000'), Subset(xstart=31500, xend=36000, ystart=36000, yend=42000, region_id='y36000_x31500'), Subset(xstart=49500, xend=54000, ystart=36000, yend=42000, region_id='y36000_x49500'), Subset(xstart=63000, xend=67500, ystart=36000, yend=42000, region_id='y36000_x63000'), Subset(xstart=72000, xend=76500, ystart=36000, yend=42000, region_id='y36000_x72000'), Subset(xstart=85500, xend=90000, ystart=36000, yend=42000, region_id='y36000_x85500'), Subset(xstart=99000, xend=103500, ystart=36000, yend=42000, region_id='y36000_x99000'), Subset(xstart=103500, xend=108000, ystart=36000, yend=42000, region_id='y36000_x103500'), Subset(xstart=108000, xend=112500, ystart=36000, yend=42000, region_id='y36000_x108000'), Subset(xstart=126000, xend=130500, ystart=36000, yend=42000, region_id='y36000_x126000'), Subset(xstart=153000, xend=156335, ystart=36000, yend=42000, region_id='y36000_x153000'), Subset(xstart=0, xend=4500, ystart=42000, yend=48000, region_id='y42000_x0'), Subset(xstart=18000, xend=22500, ystart=42000, yend=48000, region_id='y42000_x18000'), Subset(xstart=36000, xend=40500, 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ystart=60000, yend=66000, region_id='y60000_x117000'), Subset(xstart=126000, xend=130500, ystart=60000, yend=66000, region_id='y60000_x126000'), Subset(xstart=135000, xend=139500, ystart=60000, yend=66000, region_id='y60000_x135000'), Subset(xstart=153000, xend=156335, ystart=60000, yend=66000, region_id='y60000_x153000'), Subset(xstart=13500, xend=18000, ystart=66000, yend=72000, region_id='y66000_x13500'), Subset(xstart=31500, xend=36000, ystart=66000, yend=72000, region_id='y66000_x31500'), Subset(xstart=58500, xend=63000, ystart=66000, yend=72000, region_id='y66000_x58500'), Subset(xstart=103500, xend=108000, ystart=66000, yend=72000, region_id='y66000_x103500'), Subset(xstart=108000, xend=112500, ystart=66000, yend=72000, region_id='y66000_x108000'), Subset(xstart=117000, xend=121500, ystart=66000, yend=72000, region_id='y66000_x117000'), Subset(xstart=126000, xend=130500, ystart=66000, yend=72000, region_id='y66000_x126000'), Subset(xstart=135000, xend=139500, ystart=66000, yend=72000, region_id='y66000_x135000'), Subset(xstart=139500, xend=144000, ystart=66000, yend=72000, region_id='y66000_x139500'), Subset(xstart=144000, xend=148500, ystart=66000, yend=72000, region_id='y66000_x144000'), Subset(xstart=148500, xend=153000, ystart=66000, yend=72000, region_id='y66000_x148500'), Subset(xstart=153000, xend=156335, ystart=66000, yend=72000, region_id='y66000_x153000'), Subset(xstart=4500, xend=9000, ystart=72000, yend=78000, region_id='y72000_x4500'), Subset(xstart=9000, xend=13500, ystart=72000, yend=78000, region_id='y72000_x9000'), Subset(xstart=13500, xend=18000, ystart=72000, yend=78000, region_id='y72000_x13500'), Subset(xstart=18000, xend=22500, ystart=72000, yend=78000, region_id='y72000_x18000'), Subset(xstart=22500, xend=27000, ystart=72000, yend=78000, region_id='y72000_x22500'), Subset(xstart=31500, xend=36000, ystart=72000, yend=78000, region_id='y72000_x31500'), Subset(xstart=36000, xend=40500, ystart=72000, yend=78000, region_id='y72000_x36000'), Subset(xstart=40500, xend=45000, ystart=72000, yend=78000, region_id='y72000_x40500'), Subset(xstart=49500, xend=54000, ystart=72000, yend=78000, region_id='y72000_x49500'), Subset(xstart=63000, xend=67500, ystart=72000, yend=78000, region_id='y72000_x63000'), Subset(xstart=76500, xend=81000, ystart=72000, yend=78000, region_id='y72000_x76500'), Subset(xstart=90000, xend=94500, ystart=72000, yend=78000, region_id='y72000_x90000'), Subset(xstart=99000, xend=103500, ystart=72000, yend=78000, region_id='y72000_x99000'), Subset(xstart=108000, xend=112500, ystart=72000, yend=78000, region_id='y72000_x108000'), Subset(xstart=112500, xend=117000, ystart=72000, yend=78000, region_id='y72000_x112500'), Subset(xstart=117000, xend=121500, ystart=72000, yend=78000, region_id='y72000_x117000'), Subset(xstart=121500, xend=126000, ystart=72000, yend=78000, region_id='y72000_x121500'), Subset(xstart=126000, xend=130500, ystart=72000, yend=78000, region_id='y72000_x126000'), Subset(xstart=139500, xend=144000, ystart=72000, yend=78000, region_id='y72000_x139500'), Subset(xstart=144000, xend=148500, ystart=72000, yend=78000, region_id='y72000_x144000'), Subset(xstart=148500, xend=153000, ystart=72000, yend=78000, region_id='y72000_x148500'), Subset(xstart=153000, xend=156335, ystart=72000, yend=78000, region_id='y72000_x153000'), Subset(xstart=0, xend=4500, ystart=78000, yend=84000, region_id='y78000_x0'), Subset(xstart=9000, xend=13500, ystart=78000, yend=84000, region_id='y78000_x9000'), Subset(xstart=13500, xend=18000, ystart=78000, yend=84000, region_id='y78000_x13500'), Subset(xstart=31500, xend=36000, ystart=78000, yend=84000, region_id='y78000_x31500'), Subset(xstart=36000, xend=40500, ystart=78000, yend=84000, region_id='y78000_x36000'), Subset(xstart=45000, xend=49500, ystart=78000, yend=84000, region_id='y78000_x45000'), Subset(xstart=58500, xend=63000, ystart=78000, yend=84000, region_id='y78000_x58500'), Subset(xstart=72000, xend=76500, ystart=78000, yend=84000, region_id='y78000_x72000'), Subset(xstart=76500, xend=81000, ystart=78000, yend=84000, region_id='y78000_x76500'), Subset(xstart=81000, xend=85500, ystart=78000, yend=84000, region_id='y78000_x81000'), Subset(xstart=85500, xend=90000, ystart=78000, yend=84000, region_id='y78000_x85500'), Subset(xstart=90000, xend=94500, ystart=78000, yend=84000, region_id='y78000_x90000'), Subset(xstart=103500, xend=108000, ystart=78000, yend=84000, region_id='y78000_x103500'), Subset(xstart=108000, xend=112500, ystart=78000, yend=84000, region_id='y78000_x108000'), Subset(xstart=121500, xend=126000, ystart=78000, yend=84000, region_id='y78000_x121500'), Subset(xstart=130500, xend=135000, ystart=78000, yend=84000, region_id='y78000_x130500'), Subset(xstart=135000, xend=139500, ystart=78000, yend=84000, region_id='y78000_x135000'), Subset(xstart=153000, xend=156335, ystart=78000, yend=84000, region_id='y78000_x153000'), Subset(xstart=0, xend=4500, ystart=84000, yend=90000, region_id='y84000_x0'), Subset(xstart=54000, xend=58500, ystart=84000, yend=90000, region_id='y84000_x54000'), Subset(xstart=63000, xend=67500, ystart=84000, yend=90000, region_id='y84000_x63000'), Subset(xstart=67500, xend=72000, ystart=84000, yend=90000, region_id='y84000_x67500'), Subset(xstart=72000, xend=76500, ystart=84000, yend=90000, region_id='y84000_x72000'), Subset(xstart=85500, xend=90000, ystart=84000, yend=90000, region_id='y84000_x85500'), Subset(xstart=103500, xend=108000, ystart=84000, yend=90000, region_id='y84000_x103500'), Subset(xstart=117000, xend=121500, ystart=84000, yend=90000, region_id='y84000_x117000'), Subset(xstart=126000, xend=130500, ystart=84000, yend=90000, region_id='y84000_x126000'), Subset(xstart=135000, xend=139500, ystart=84000, yend=90000, region_id='y84000_x135000'), Subset(xstart=144000, xend=148500, ystart=84000, yend=90000, region_id='y84000_x144000'), Subset(xstart=4500, xend=9000, ystart=90000, yend=96000, region_id='y90000_x4500'), Subset(xstart=9000, xend=13500, ystart=90000, yend=96000, region_id='y90000_x9000'), Subset(xstart=36000, xend=40500, ystart=90000, yend=96000, region_id='y90000_x36000'), Subset(xstart=49500, xend=54000, ystart=90000, yend=96000, region_id='y90000_x49500'), Subset(xstart=54000, xend=58500, ystart=90000, yend=96000, region_id='y90000_x54000'), Subset(xstart=58500, xend=63000, ystart=90000, yend=96000, region_id='y90000_x58500'), Subset(xstart=67500, xend=72000, ystart=90000, yend=96000, region_id='y90000_x67500'), Subset(xstart=72000, xend=76500, ystart=90000, yend=96000, region_id='y90000_x72000'), Subset(xstart=76500, xend=81000, ystart=90000, yend=96000, region_id='y90000_x76500'), Subset(xstart=81000, xend=85500, ystart=90000, yend=96000, region_id='y90000_x81000'), Subset(xstart=85500, xend=90000, ystart=90000, yend=96000, region_id='y90000_x85500'), Subset(xstart=90000, xend=94500, ystart=90000, yend=96000, region_id='y90000_x90000'), Subset(xstart=94500, xend=99000, ystart=90000, yend=96000, region_id='y90000_x94500'), Subset(xstart=99000, xend=103500, ystart=90000, yend=96000, region_id='y90000_x99000'), Subset(xstart=108000, xend=112500, ystart=90000, yend=96000, region_id='y90000_x108000'), Subset(xstart=121500, xend=126000, ystart=90000, yend=96000, region_id='y90000_x121500'), Subset(xstart=126000, xend=130500, ystart=90000, yend=96000, region_id='y90000_x126000'), Subset(xstart=130500, xend=135000, ystart=90000, yend=96000, region_id='y90000_x130500'), Subset(xstart=139500, xend=144000, ystart=90000, yend=96000, region_id='y90000_x139500'), Subset(xstart=148500, xend=153000, ystart=90000, yend=96000, region_id='y90000_x148500'), Subset(xstart=0, xend=4500, ystart=96000, yend=101538, region_id='y96000_x0'), Subset(xstart=4500, xend=9000, ystart=96000, yend=101538, region_id='y96000_x4500'), Subset(xstart=9000, xend=13500, ystart=96000, yend=101538, region_id='y96000_x9000'), Subset(xstart=31500, xend=36000, ystart=96000, yend=101538, region_id='y96000_x31500'), Subset(xstart=36000, xend=40500, ystart=96000, yend=101538, region_id='y96000_x36000'), Subset(xstart=49500, xend=54000, ystart=96000, yend=101538, region_id='y96000_x49500'), Subset(xstart=54000, xend=58500, ystart=96000, yend=101538, region_id='y96000_x54000'), Subset(xstart=81000, xend=85500, ystart=96000, yend=101538, region_id='y96000_x81000'), Subset(xstart=94500, xend=99000, ystart=96000, yend=101538, region_id='y96000_x94500'), Subset(xstart=99000, xend=103500, ystart=96000, yend=101538, region_id='y96000_x99000'), Subset(xstart=103500, xend=108000, ystart=96000, yend=101538, region_id='y96000_x103500'), Subset(xstart=117000, xend=121500, ystart=96000, yend=101538, region_id='y96000_x117000'), Subset(xstart=121500, xend=126000, ystart=96000, yend=101538, region_id='y96000_x121500'), Subset(xstart=153000, xend=156335, ystart=96000, yend=101538, region_id='y96000_x153000')]\n",
"writing 295 new regions\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"/opt/coiled/env/lib/python3.11/site-packages/distributed/client.py:3357: UserWarning: Sending large graph of size 24.15 MiB.\n",
"This may cause some slowdown.\n",
"Consider loading the data with Dask directly\n",
" or using futures or delayed objects to embed the data into the graph without repetition.\n",
"See also https://docs.dask.org/en/stable/best-practices.html#load-data-with-dask for more information.\n",
" warnings.warn(\n"
]
}
],
"source": [
"repo = icechunk.Repository.open(storage)\n",
"session = repo.writable_session('main')\n",
"write_regions(session, ds, subset_list)\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f9a24fd0-2faa-4ad3-ab9d-695d34c5afb3",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.collections.QuadMesh at 0xffff28495bd0>"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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J5ysKQvLscA49SiioUGsiTN0eZLeLYHkJaNQBpUhhAoBOF4gjwBAo2+nFwgBqlEA06n6khYeHx4saCgxqF+4ShZtKu7ipcMPJzre+9S089NBDGI1GaDQa+NSnPoWXv/zlU+97/vx57Nu3b+y2ffv24fz58zO3nyQJkiRxv29tbe3Njt8kcF4Z+/tcG0hTJMsLWH0lR9QFNAugwhXs+0oHg8N16IUWoBSCbBH5d54CDwN6XBxRZk4jhq5E0Iyh+5plaAaEa7l9QuheH6wSk68HAKQidSkn1aas4pRndQGglnVLYIQg34809wsD8LgCneVgg6Epwwkgy4EohF5ogfVGYEEAeaYLHleghkOIdhuy08Hb6u8hLxGIXH1B/uF1P/4eHh4eewWfs3P9cEMNygBwzz334PHHH8dXv/pV/NzP/Rze+9734oknntiz7T/yyCNot9vu68iRI3u27SthT1Udxrf/bjwxKk2J9DAOde4C1GILKmSonQfmnlIQCaACBn5+HWKkwDa6YLkC2i2I++6CfP19yO4+BB0FUPN1sFQib0TgaY54PUdW48hrAkwpBAf2gc21yVwcReTvEdwpNwCKclV5v7UCrxKRgeD0leeA1tB5DkgJpBk9ljMgTV0oIhp1gHOwTAKVCGjWESwuOiKlh0PwuAKYie+MMzDOnNn5LeLd3vTs4eHhMQO//du/jePHj6NSqeD1r389/vIv/3Lmfb/zne/gp37qp3D8+HEwxvDhD394230eeeQRPPjgg2g2m1hZWcE73/lOPPnkk9fxFVwZN5zsRFGEO++8E695zWvwyCOP4FWvehX+7b/9t1Pvu3//fly4cGHstgsXLmD//v0zt//BD34QnU7HfZ06dWpP9/8Fg23jLpEeV75i3PliWBCAD1KIRCFZALQAFr47QOPkAPLwEqrfPgPdrkNbdYUxiEEGpgAE3BmTo/NbYGmOsJth7pkRKqsJ5NMniKDEIRBF0ElCREXroozmdo6P+XcAQCcJwBmYeQ1WhVG9HnmGohC8XoMejqCHI6DXJ/VHayDLSOFJM2CrBzUcFp4gKamjKwzAgnC8+8uQLsaZIz1v4e9yXx4eHh43C6xBeTdfV4s//MM/xAc+8AH8yq/8Cr72ta/hVa96Fd72trfh4sWLU+8/GAxw++2341d/9Vdnrr1//ud/jve///34n//zf+ILX/gCsizDW9/6VvT7/avev73CDS9jTUIpNVZ2KuOhhx7Co48+il/8xV90t33hC1+Y6fEBgDiOEcfxXu/mDYFt6baemLKa4jqyalUkB1rYuDtCvA5sHeUQSYzml0+YB2mwTh/y/EXoPENw5+1gaQ7NquDn1qC7PeTdLsTCPFgYQi83EHRGwHeeBqtWSWkZJUCWkcE4zWhUBGfQim/LDNISBfERgsZY2NeTZ5AbHfBqFYxxaK2gs4xeSxBA5znYcES+oDQDS1JShLIMvNmgjeQ5VCohe70isFDKYuI7ADBN5mmASm3uoPGphOcL6pN7cLY8PDw8rg7k2dnFINBreOxv/uZv4md/9mfxvve9DwDwu7/7u/iv//W/4iMf+Qj+2T/7Z9vu/+CDD+LBBx8EgKl/B4DPfvazY79/9KMfxcrKCh577DH88A//8FXv417ghpKdD37wg3jHO96Bo0ePotvt4uMf/zi++MUv4nOf+xwA4D3veQ8OHTqERx55BADwC7/wC3jzm9+M3/iN38CP//iP4xOf+AT++q//Gv/+3//7G/kyXlDYED81MoTQqCcsIvOuzjLkDYHFb49w+kcrUBHQeGoTuj+g0Q5JAhaSgsKaDWAwBOo1iM0+kGVQgwHAOOT6BgAgGCVgi/NAu0VqSxiS0iJEoSylKT1/mhK5mWypt78HAbQhHRAcvFYDhIDc3IQAaJuWDGljiM5zap8Xgvw7Q+og04MhBSjGldK4DHuQOJgweT4lY/RYee0y8ATIw8PjpYA0TfHYY4/hgx/8oLuNc44f+7Efw1e+8pU9e55OpwOAuq1vFG4o2bl48SLe85734Ny5c2i323jlK1+Jz33uc3jLW94CADh58iQ4L2S5N77xjfj4xz+Of/Ev/gV+6Zd+CXfddRf++I//+MWZsXMN4FEEFgQuxM8pPEqDRxH0cAi5voHRnIBmQPN5DaYA+e0nIV55L7C6Cbm2hmBhjqaWg0gDCwNKTM5z8GaTyMfcHGRni0zI65tgi6T0qLV18GOHga0eERKtoVMyKjvyM4NQ6JRUGz1KSIEx5IfXavSzbXeXijw8AHTGoDtbYLUa2Cih58tyCk6MIug8c94d0agYckMlNS0lESE6SEVJqxx2uEN4AuTh4XG9oXY5G8t2Y0024syqcKyurkJKObXx53vf+94178fYPimFX/zFX8Sb3vSmG7pW31Cy83u/93uX/fsXv/jFbbe9613vwrve9RL1WmgFZZSNMni1Aj1KwPevgCsNGTGAMbROpgg6KVhcoYDAjU0EK8vmQRxqfQN8ro38efIxiXYbkJJydIYjiFYTOHYQ8pvfRbB/Ger0BtQD94B1h2BSAmEI2ekULefWJ8O2l7MAMycrCqGGI4gwcHO1WN2UsZQmX47WhQKUUQChTlOobhfclNL4yjIRoiiEOn8JKk0hu9ShZfeBG5VIZbnzPFm1h0jQ7sbmzfL8eBLk4eFxLdh9qCCRnclGnF/5lV/Bv/yX/3I3u3bNeP/7349vf/vb+Iu/+Isb8vwWN51nx2M2VJaPzaSCUmDLi8iffQ68VoNansPGfU2kTWDzXo7292Ms/vvHACHARxlw13HoTIJtbpER2eTbBAcPODLE5+eQnzxNT8g4BAD1ww9ADnKwl90O0RmCrW8SIen2ip2bMAS7nw3h4VEEBAHUcARerUCNklLycwCdpFBpCi646fASRdggZ6T2gMp3ot0CGjVgo0MepDCgUprx7GgpnfmZcQYeBlBZPmZc3mlJ64qYMtPsLeLd4/cxf/ckyMPD43JQ4HuSs3Pq1KmxUMFZvtWlpSUIIa668WenePjhh/GZz3wGX/rSl3D48OFdb2838GTnRQAWhNTqbeZesTimQL+FOfTvWoB65T4EA4nhSojO7QzxJiBjjc17gdZbX4v4L54ABkMy+1YrRCKUAp+fI8NvGEI+d5IIU7cHMTdH5aUD+6AziXBzBPnN74LPzYEtLdCIB84gOx033BOAIxUAxoiOIy/alNuShLxHpvQGqWh/qhUyRWcZhQdGERGXXt9tl3FFLem9QdGSPtcGGyVU0lIhYDrTJtvfywNKd39S+FhprPw87vVP3DZGgkqP8yTIw8NjL2HnTV4JURThNa95DR599FG8853vBEBlp0cffRQPP/zwNT+/1ho///M/j0996lP44he/iNtuu+2at7VX8GTnZobtYBICLAzB2k1qx5aULNx9+SI27hIY7tc49icSlbUc6uUhggGw8lcMtX94FhvPHsKB88eA1U3aplRkVq7XoFbXoJWG2LdMk9Ibdchz5xFUq2DtFpWYhgn06XUANJlcPk3bEQvzCPatQG1sOmJTdIsVQYLOM8NYyWwck38njonMmPBBJgSVrxhzxmdlFBvaAQWAgghVtwe+MA9kGfTCHPhmDNZcBFJjsi51qrkSVp65zrDy364J0x5nCd7YKSy8VWMEqFTqu1wLvCdCHh4vHUjNIPUuQgWv4bEf+MAH8N73vhevfe1r8brXvQ4f/vCH0e/3XXfWZKNQmqYuCy9NU5w5cwaPP/44Go0G7rzzTgBUuvr4xz+OT3/602g2my74t91uo1qtXvPr2w082blO2HWGS2nRdOWdJAVrtaAuXITsdDBYuRP567o40Oxj654AS/8iQPP5OeQ1oPVchrV+Hd17JBa+W0fl/CqpOoJC+FijDr60CL3VpXKYSTYWjQa1fFdiQEkiPNUK0O269m0Arj3c3aaVS1C2v7MgLNQUU4ay33kldgoP3Z/CBdUooXES5hjYTitLGlx3FefIT5+BmJuj3+fa0HYwqQ0btNPYGQfjRuDV4/u4pygRGJciXb7dYlqpb/J2c9uskhjgiZCHx60GuUuDsryGcRHvfve7cenSJfzyL/8yzp8/j1e/+tX47Gc/60zLk41CZ8+exQMPPOB+/9CHPoQPfehDePOb3+x8tr/zO78DAPiRH/mRsef6/d//ffyjf/SPrnof9wKe7NxEGOtmmlAj1GAANRhAvPJe8Gwe6mwCKEA92cSZwxFec8dJfOPdd2H56wqVNSAYSlT/qI3mUEOMyPSbP38KotkEX16CvHAJ4thhmpBuvDvQGqxWpe6qNAXCEHo0gu71IRbmXTu6WJiH3OgUOTZllBZjGyjIONtGLLSURScW4Pw5vFqBtknKZnssCAHOqOQFQCepMxnrNAXPJZW25ptgF9aguhJMwJWyXMdWeR/L6spewyhQ7vhMPsfl/E3258upRGa/3xr+9Nhjxkp0jPtxGXsEe+HiyaXHrYqHH354ZtlqslHo+PHjuNL88JtsvjgAT3ZuKrjyjzXRGkMtr8RQZqGHlNCtBtiB+5AsANnhBA/d9SxOdBYRrwGt728hXaxBxgL1cxmi9RGFBhrPi+x2AdvVpDXy02cQHNhvJpdTGzo4c0nKejiiaei2C4xxIDUjGcIAHBXqEsvyglyUlBWXomyVloiTusNYkX5svEi8VoPOc1J9bJCgELRP9rm1gur1wVsN8Iag15XlUO06dCggajWwzQ55hNx+pJOH+vqpOmNPoQvCV3qt5WMz5vuZ4TFyU+Rtq7wNbFSa8oTybOrrewt/1xUJnV/APTxuHijNoXbRjaVuQpJxs8CTneuA3ZSwymqOXeTUcAherVJqsNRQJ05Bvv5e9I9IHNq/gb/+b/eisgY0z2vwi5uInz0D1mxAN+sAB9j6FvLNzWL7SpNf5tKaG+wJraGlhNzcJCIkFXSagtkOqlYDGA4R7F8BJCUW84BGNMhez7V5a8UBmCGgioOHpoZsSlGQZnHXrMjWsWGCRiol307xD29VGR5S2YxFIViFjNYsDIE4BE8yDPfVEIZzwPOngCynfSoTiCnt8LvCpPenrLKUiA0g3TgPur1kli7v2wTs3x3hmRLWOJYIjcIjNZUAlfbbeqt2QogAT4oA+r/2x8HjeuJGlLFeKvBk5yaDW6S0gpZwBmUoSi3WoQCfayFZjKBjhQtf348j/y0FGChLr1EDS1MgCsH6A2cM5lEElaaOOKhu1/2s04w8OllOZSWtITsdiGYTLIrAAcj1DfLHRCGAEMHiItRgANmj9nM1QVDKGTdukecMYKbUokzLOOOQvT5NQ1d0u1YaLGSApMdzYRQcsyDz5UUqvQUB1FzdHC+NaJNSpcXRQ9Drm/T68iJfx+3fXhEe68/hDGCGZJTLZeZ8lgnINi9PGZPlrTLhmxGAyILQbXfbY0tep8n9duWw8mOmPgEvVKKrgCcFHh4eNxM82bkO+IL65LWrO2UFwt5kTLry4iXwxTbUVhed4wJBPQVrpTj/hjoOP9oHH2TQl9bAGnUarJmkVKpaXQe0gmg2IXt9iHrNjJswxCcZgTvlgJOSFFegBgOwnAgQr1bJqDwYQnW2wBcXoNaG4/teWmjdqAbGC6WqRDqYJTAgszIYG5/1FQRQw6EjemWlQjeqYP0EiELIWojw/Bb06jpw7CD46ibys+cpX6daHb/O2ePSlVVuymWmyRlhPBLuGDj1qzy3C8Uw18lj6J7Hbr/k17H30XnmghaRU5bQ5NR5FpSm0s8a5TELpdTpSSJ3OcxSjMplPBtVwDiVNB1hnniMJ04eLxUoXFtHVfnxHtPhyc7Nhkn/Boq8GLFvBbISQb7uXrSel9CiCvXGDvgICFZ75FGJY5ofxRgZjLe2nMlXdrtuEeWthjMcg3FXKkNuJpGbLitmS0jNBnSSQK5vkMcnnVImGTPL8mIelSE3ztcDo3LYeV5pCl6tumGevFEvSkB2YYxpFITOM/LjCA5s9RCubwLNBtjSAmQtBFbXHXlSwyFl9WT5tak5O3hMWbUiUiLABNwibn01kyMqxgkPppOQkneLjoceL8XZxygNCEZde1FUlLYMGWJCkLKXjLY/xw4xs7Pssg/abswmYzkvzq8td1ZJQXR5SiZbSg0G13zhYFUvAAgOHYTuD6CPHUQ+XwE0MDgQIepI1L5xmi4MopBiDfoDAKAIAw+PFxC7DxW89sfe6vBk5yaFIwoAJSAvzAO1KiAYslaAtVcIZE0NJCEWLmnoSgicXKWZV1EEVGLoC6tgtSpEowHWblG+zlwb8tRpMCkRHDsCCIH82ecc4aEn58VCbUzDjIeQGzQaIj93fub+TpZNrDkZGA8dJP+OpOGfjEP2aagnzFW+tou5pv1wi9byErRSUI0qtUMmCfTaBli9BtENwZYXKZ9nswPebkHbganXoursgOiAMyBXVMYqdURxY6q2qgyMQsW4AuzgUqt6Xe45eOF5ss9pCZP7mbNiYZ6SIVQmVler0EzszO7UMbs/Vo0CnCol+wPwSgzOOFQyMvepjD99ibzsZN/K983PnEWwsgx2fhVRpwp18RLCv/EKVJ/rQG1s0rw1+/615NJu+goz3zw8PG5+eLJzHbCrjJ2SeRSAa69GlgEJB8urGM3TBzE/OkDji3U0zlAQH2s2oC6tgR8+UOTaMJqTBaXA2k2odh1CHCUDcqtGychxBSwKi9lSnJnurAHk5iaCxUXalBDgjTqkMTuXUQ7sYwJFOQWgBb4UOjiuWADgjEprRl2y38sLu0OrCR2TB0aeOAl+121gWU5t6Z0t6KjwzrA0Kx2HPVJ2Sp1SYJzUKVaMs7DqDhgndUwr54MCZ1DDdPwcT/p2JpQbW7pyyhErTN9aafrZqm9xxak7NozRls+sUjdGdK72mEyava90rC4DS6xpnxMiwsPxsqjsdsefvkx0dmA4n/Qz6eEIbGEO6dEFqLuWUf/mWajV9bHndcfbkkLbXejh8QJg97OxvLIzC/7I3IQYK3HYWVEA1IVV5I0Im3cyjO5IoCSHfW+ztQ7UpTUqVWgNBAJscZ5+BpCfO4/8+VNgUkJXIyAOoZ54mrabjNyAURYGtHhqDR5XECwuIl9bA5QGb9ShJhag8R1X23ws9vW4biwDt3hLCRYEZL5WmgzPWm9b+Ny2NjbB0hwsySCOHqI5XTUaJIooBGs2wFotIiHBLrn8LP9MucRkQxXL7eGlBZhXTW6RzRGKK2ML6TaUTdQTWUBMCDDOnLdF5xlUlhOxMZ4XXokLU7jNaCqnUJefZ6fkZHKfLnesyg+blsM0uR2r4AWBK7fZfXUZTPZh5dcwWe6dkktkyZGW1A1ny7jRhS4qJ9aRnzwNNRiAR5HzU43t08S+siDcfVioh8dloMB2/eUxHV7Z2WPs2YehJQ6m60jn1I0UrvagwgqCOIcIFJqncgSDHHqhBd6sg11cRf7sc2CvvR/Dg1VUzw8hnssRRBElKG90ycuzsTmm0hTKDAOLY1J5qlUKMmy3qS29s+XMpNOudnkU0SDOPBtXZIyqo1VeEB7GiSAoDRtqKObb0GZA6LTp7vaKGxklO6vTZ8EXF4DhCPrQCvRTz0H3+tCvvAdCSehOd7Yx9xrVifL2tASVsDBe6lCpLBbQMnFlpmXOeKgmjcTTn7BQxcC0O/4QtAjzSgwWRZBbXTr+QkDUa65LjldiKDM3zL3My5WDZu1DaV/Kx+hyZbHJ1nprtC8fx3IX35ihfdr27Ht01nmbRrjsa9UKPK5QCTeOKbLAPFalKXUXrq251wQhwAHwZhM6zyG3uu4ipPw/7s3THnsJr+xcP3iyc7OhFBjHQyIDrBI578nocBuyrsAkR36pCmU+s+W3v08f6NUqgoMHoDKJsCvRO1pHu9NGur8FnimIXgK21gGLQuSr6+Nt2VpBDQZOndBZDl6vUUu4G6w5g+iU5p2wKAKT0ikOk6UfaEWLdSkASw9HYGbh1sORUSrk2GLqOrNCAV2LwJeXKOk5isCGKfmLpAQ/c4nMppNkorwYTiM10zJ53IsaV3donwoiYw3JgGm7L3mS3PT2vFBhiu1MPP8E6Sm/fp3TyAsaw8ELQqwUmbINaORGFWqUuI42FlScQXkmadgJJgjPZctiU9QXFoRjpTYHY4y3RIdUrClRAbPO26ysotL+qWREcQrLi5QxZR7Lq1WgUQPW1iCaTSLajIEvL0FdWqX/RRfsSeqT3e7kxU2Z/Fzubx4eHi8sPA28GXCZMgF1H5mBoHGM+GIfYsiguiHqpznyKoPojhDcdhQAeSHUGnVZ6YAhbTLIdhXhxhDiOyfANrtAIJBfWkWwvAjeaIAJgWB5EWJhnoiKEBCtJk1WZ4xKQiarZ2zRL5Up1HBY+IMY21aqKJew6DYzosL4g5hZrFmtCr44DxaF4GEwpn7oPCMD8/lVsDSHPLBIypBSwPomqVRSUtt9JSZFrKzszFJPJjG5YJdVg9J2tpVpyq+ZMUd0GOe0cIvSQqmL4EFbnpq2f2PqiFVAzPiLcpnHEhv7dzUcFuWvOAYLg+mlrB3AKkazyN+OUIojGAtUpBdZEJ/SdnWWu7LfrG3OHMlR2nYZstcHdeqN3HPxZgMYlH07kjoPL1wiQ71WLuhSS+lM9tPOjUWZ6Njj/tbo7/kymMdlYUMFd/PlMR3+yNwMKJcFTJnCJR0LAXnPUeD4IbBqBZ1724g6DPGFAMMVDSY1soUakOcI7roDgPHgfOMJhH/2dbSfTdA7VgcyieEP3gNdJ7MsC0LkFy8BoJZ2nWbke4FZxC0B4Qw6Tcc+7N1uTyg8ajAwixmnURLGB7FtsbKjHPLcqR46y+h5uj333HyuTaSr1IauOlvAwhxULQJTCqhXqQ2+3QRe83Kw/StQS+0iAXoaISn/XCaak7fNyqQp3+5M2UW3E1ypzhiXg6Dw9sAoM0Js2zdHeiZRKtM4JWk4HAt1tI+Xvd54J1EQOg/UWClrSiLzLFJRHva6bb/KuIxSVI4cGHsfTRLHkrKpkpHrzJq6Tc5mltAmn7e8j/kzJ4hMRxFEowHV6SK/tAphSlbBoQPkH6rXIBp1U4It2v7d805Rsd7C37WN0JSVyW2E8wbDk6+bC0qzXX95TIcvY91M0NTCTIFrzBhNI2zdXkPSriPqzqN6KcfRP3kKLAzQf/3tqJ7qIV2pUVt6lgMPvQrBxS2o0+coLPBLjyN6yw9ANWPEl4ZggyEwSsAi8jKo/gB6q4vgwL6CfHDQz1FIAYLNZnEVXJ7TVYJoNgulolqB6vbGjbzuAx8AhCEAGQU/5zmZlO3PWgPWU5HntEBICbEw58y+TGpozqHOX4TKcog0hTo0D7HVBV/fJH+StmbhbLx9eEp79szfgW0lkvIMM6dS2O0apaqsXKluFyyOzUwwbo4BAFaadVXqUKOnZOM/y9JzG7iQQjOrbHy2GvmGXKu/JdClsEcmxhfisZEWZmK9ff1jhONyKtkMT025PDVGFC5XSruCr2onXVLTPEW8WgVv1KGHI1J6zPZkt0tltouXwA/sgzp3YXxb1v/DwrFjN7NUam5jnIEF1OXIwxhvq78HkBKfG/2nK+7/9UKZ5PhBpx4vBXiys4fYbcs5fWNgYUwSfhhAPXAPBisMeR2obAK1x05AHz0A9dRzOPk2juazc2ieUhDDOsLVPniSIzvQBnv2edquVqie7ACDIdLbVoDTZyEOH6QP9LgC3m4CYQi1uk4zpzgHq5nZWEliuolSQHCS/o3R0wX8GWgpSQmyC3QUQfUHZFg2Cy4AlzcDbl4r544caCnpvnlOZGeUkJG0DuitHmUHHV4Bu7ABnkvoOIAOAiJ5ADSnIEXV7YELY7bmppxUOs7biME0c+ukR0fxsUXNzt1yg0yV6UCT0nUWaTP+gsITS5k35WnwdFCc54dCAbOxv5dLPjyuuLKP7TICMJbODF0MXnX7aaIAbP7PpDna3td6ihgnss3NOR3L9plUNXbqqbGv5QrempnbuQaM+YLsptMUqtuDGiUQjboj51b9YrUasiOLCAEK6Oz1nZfMeqO0lECWbyeBE3AKniXBQFHiBPC2yt93ZPDz2Sf25DVfCbM+p/zsrxsPtctSlA8VnA1Pdq4XrsEAass1ynQksVoNg4MVpHOAjIHeQYb8J+5CdV2h/9ADqB3qINknULtUh4oFsuUGwotdQGvwo4eQP38KPIogn3oWvNFA8Ffr0ADy508BoHKXXssgDh0A37cE3euDCYH84iWIRqMgCYrKJ2K+DdXZIqPrxJW9GgwgKjFYTIGGrBKDS0kL/hQ1RWd6ahmChQGU2Q+d566kJtotgAtozknF2uy4/eVhAHCO6PwW+ZuiCGi3wAZDaGtqtl1RZYJyuVRg2z1kfh67n/0SwjV62tfCyqTDLm4lssKisBiGarcXBBC29VkIYDS++DOuCiOz4AA4zQszxGTMA2Q6nuxrpY43XqQ4u3MxrujYfXbvQUMSXB6OUYmmdl/t8H1eJnfbtmE7tq4QemhVrrFE6qv9PwtC4zHj1HV411FAL4M/8Sz9TyQJxF99D8p65aIIrFalROeuSSpnRTr1zP0dK5kSsddKFcZrs/+8EuzoNewFGbnSBZlXeW4sdj/13JOdWfBHZq9xtcZN+xizWGkpqZ2Yk9oRDBTiDSDaAob7NGSFIV5LsPLldeRSoBJnGC0wDFZCJAsRsuUGeHcECIHg9uPUOislcHAf+JGD256aN5vIT56G7nSBNEO+ug5eq0ErBZ1lgJQU8BdFUFs98GbThORt/3CWGx3kFy6SORgw3hzlCEC5LMKs+ZgVoXjuKlhrmoAuJbVNJwkQCCBNIbpDKEPW+FwbbHEerFqF3OpCnTgJ9AZg7SaRnmrJ3GrNusYk7I77tPNlPDhMCDoXJS+Ne7zpVrPEQGU0l6r8WnRqzOVRSMbqMKCFMwwKIhkEYGFIc8dMSzl1pYVjC/r4aAlt8olKpSb7p5IJGCDjsiVDKk3HFJppRmur2DEhXLCjDSsUjbori00eryveZt/fJZVoJ/8r1t9U3r+xn69BAVLJiEpZlZj2QWqorz9B3VrtNtgr7gE/sA86zSB7fcjOFtTahiM6yig6Yynn06CVa3uHpNdfHkHxtsZ7KSWaMbBqFW9vvY9KXFPw9tb7wOMK3t5631W/XourUZ6neY88PF7M8MrOXmMnXoRZjwFcpw3jDEhTBEOJQ//pBM7+3buRNRjijobmDPqZk7jj/1aDXlpAvjREVg8wWgpQ+fTjkEKA33c3WH9EBt41kJm3N4A4fJBIzbnzYzkwqj8A40ZBAcZSkrm5GhXtFhljp2XggK7+easB9Idu0Yfg1MlVNYNFgaJLKaBZRPZ3G9kPACyOadxDmlGGjBBAq0Fm5CCgMpf1xgiO4OghIJfQnS2wpXm6XznFudQ6b5WNMb8NsF3hmSgjOfIh5ZhSsm2cgNZ0BW/Kgk7xYWzMNM3CgJQvxogYSUleKgCqMz6XiQUVIlhJQousSZ+2gYHlMRxMlMgcLNGZnmFD5bmsUISMmsWMidyqPbxa3ZZoXNrI9uO3k+6osrpV9uGUfTlTzMnueF9r+zzjTtmBVlDfeAIAhRjKTgfBZovIPwrvlE3DLnbdvIdKytis102vSYPZtnWjlFJ5a0L9EQJvq/5DfG74f7qb3956H3SWE1luNvD29j8GwsA1FKheHywM8Nmt35/5kq+VuHil54WFBIPcRTDgbh57q8OTnT3CnlwFWfWh1IYcfusE8vUNLH/tMEQ/Rd6uIOibIZqcQ1dDMKmR1yhNOTh6mML0BIN85gTEK+6BWJhH/uTTEI0GZK8H0W4juP04zcQyi69YXoRao9wd2dkak+fVYOB8OrbEJhYWiYhMjI7IL60CzJCPLnUKOeOyXUgDKjtpZGDCloo0tNbglZrpAuMA52BmIVEbm6TYVCNqFQ4EMEqg+0QS9NoG2MIccOQg5FMnqBw2SkzoXuiurFkcQ6dZUfKB3LbgkseFF3O1UJSpyotyuUuMRmKEE14fajdnUfG6WVxkJiEIoHv94hjXapCXVovH23EHgVGGIKicVdpPe17cflkSZBUYXSqBFTu2bVEul/nod3NXU8a5bKnmMjk3M1HueLvCY8fmrlkCe6Xnm/H3bblNEI5QqcGgIKLVCoQQxft7hpF97NjOUKos2bGjO5DnlJckigwmnabkT5MS4Axvq/x9UtPm5shbtDDnTPtsvm3M7gzIMko27/Xxtuo/LAzoe+R5svB+nhcGvox1/eDJzvXAtVxxMg5Rr1H7tdKkkKQZWKOO0Q/ehcZXn6OyFluB/sb3oIySEFSrSO9cBpdAvCkxuP8g4gtD8KdPke/m9AXIzhYAuDZlFoXIn30OotmE7PUhlhaJWNRq1Go+MYPImjj1cATRCMAadVIhWg3AzM5SwyEgFYKVZeqECkPoe46DDVLwbp/8NcasrNPMlXSseqCGI/AwoEGmtar5IKfuMKsK8edPgzfqZr8YVK8PfugA7fOZ89BbPRp8ujAHtdmBqNfA6jXoLIPa6hUlnjCACBtQJTIzdaGavJK/zDnVUoLHJiFYcYCDVJssJ4UniqCTFKxNrfR6lFCH2fIilQrrNTq+C6RKWVO38/iMdf4UBuJtnhGbWTMtE6dEpp3vhXG4YasTPiGAiAaEgCq3uJcTmCeVnFlt+5c5tjPNzvbPbuzDxON3+lzlhxmSq/OsCFe0T+3SljUGrz6C2jfPbOtWG3vuydb9yZDISTCTJJ5n5LmSEsyqgPY9YVPFGQev1ei9ujhPRMekZufPPY/g+DFD0ANAa7B6Fbo/HCftewyv8ni8mOHJzvXANRAdHkVgZnFGLiE3NyGOHcHz7z6IwV0pjmXHUP3v3wW/sAEcO0JlmnoV8ukTiNp1hN0AWTNC2E3BpASOHoD85nfdUzhVZ2GeEoeFgOx2KZtHa2CLZPuymsFrpLKwapVMyq0mXZUmpO4gisDjCs3OMj6X/NIagqUFyI3zEEcPIT26gEgpMhTb0o7t8LELdxhAmKtaPd9EPl+DCgXC9SH46QtE8vatAI060OtDJymQpOD7V6BaVQoY7PVIUTKkwcb8QylSVKIQSEtKRZKYQ8/GzgN0Mbn8cqrFmBeo3NVl288BapuPY9ghoKxRpxJfYNSDWpUCEKUkAlgzc7QEpSJDaxMHMN6W7s6PnSI/STTK+1V+P062t1szcjJObt2Q0ykZRWySDE9i1nv/Cm3k2x4/jchM3r/8Gqf9bdYulhOkzf1sJxqvVqFbddS+cXqsxDROeqYT3yv5d+g+5ldrLreRAHleDC01Pi6dZTQ+pVqh94OUgJQIDh0EhkOoTWPI56apYQe5Q3sBT3quH0wu+64e7zEdnuzsAXZdwjLmTeQSqtsFX16iD70kxeCIhKhIZPUYtQP7oC+uElmoxMiffBrBHbch/8YTCI4ehnh6iHx9A+L2Y8DmFoKVZRccWA6fy8+eh5hvgy0vAowh/95TU3eLt1tAHNMVZSBooZ5rga1v0lXpVuHh4NUK+MI88tNnINc3wGs1qLk6wvUhRfMzRh/gaQqmIhraKSV1XC0uQFcjqChA73gdtQsJRoshor96Esp8wEMIqFYVnHOwzQ6RAqXBkgysR4ZTMAY069QRJgRYkkCvb9JzmfZvSybUKBlbsFznFQ9oBAWz5TW2jWTYK/SCCBVBeSwwC2T5MVFIi1ZEnWoQHBAcejAEsoyOy3AI1euBt1tQW33wSkzKkMkjsu8TYMLXUn4N5WTiWSTAbGdbIvLE63Pt0iahWjSb0GnmRk5cNaaRxstdFJRIj31dPAymtpJfU1NAaX/sCAsA0FkO9Z2noH/wVRB/+d0pD7v67q9tzwsU5SZgrByq0hQiiuj/JI4L4pxljnzprS5dcJiSrEpJpdJTn/D6wZOevYcvY10/eLJzo2EzW2A8A1EEvdWFynLI21YArqE1oAUgT5wkA3GWAVJBLMxDV0IE+1ZoIvrr70V0hv6em6GGlvBYZUdudGBHT0BpoN+HmJvb5r0R7TbQqENHxRBLeWSJtmmyR3SSgtWrCOZakEf2AWcou0clI8huF2KYgV0k1UfzCRKgFFCtQO2bw9r9TagIUAHAJMC0GR2xtEgL3doGKTnn18mkXKuSX2ezAzYYEGlgjILiLq6CzbWh4wBsq0sZQcbcCcGJOCT2Kti8NEt0BHd5OGVDs1YTHUiTBKO8HVPGsvOfAJDSVKvB5QltdIpN9YdgC7HL5lFbPdpmljuyUW7ZpqefvqxtU6TsPk4aqK0SZbZvu8tUmrocHgCuxdr6jlgUgVUr294rO8Y1tIi7AERenJdthONayccUE7QdZCv++ntg9SoR3/Jz7HWJyBBnxklR5MbIzqKIlD2poZFTSdd0KNoSp06S6eTvBYb38+wd/CDQ6wd/ZHYJp+qUr6Sv8kpTmdA+vrgAtjhPpQ0AOuBArMC4hkg0xOI8BaKtrtMH4soS9NMnofctAq+4E2KUQ69tQDdrEI0GlazM4i37RXePzjMqg/UHkBdXXalENJsAgODgAbDFeehIQEcB9InTYEkOPsjABxkQhmCmxIU0g16eh2yEyI/vG7vyZ1letKHb0EEAaNSgl+cxunsf1u5voncUWH6si7ijMVwBRnMc7W9cApIEuhbTax4OqYylKF2ZzbdNOnHP+HDIW8IYJ8Kz1gFy6V6vznJqg+c01d2SC7qDKuR/UVI17EI/Y24VUJQuuFkk7W1uAryULh0amQkLtCZVKSnU0d7GmAutU3ZER8l4XC4/jU2Pt9/LZZ3yPo4RJiJozE2cV1Q2mwwwtIu6GRcCIUzZ0dwcV8aff/Lnq8W0/c6zsbKZ8xVNKx3uYHtjf54Y2zA2pd7k8MgSKb1uMOrcWEt9ntMxt/EPRtnTwyF5+kzH5s1AdCx8q7rHzQ5PdvYKV3mlaaVrN6Moz6HWN2g21OH9SH78tVi/t4K3v+LbqH+1Bllh0PsWKayv2UB++gwwGJKnJsnAL2xA/+W3gEMrYLmC7A/Amg2g3XQpugCVmwAAgYC8cBE6z6jEpRWZlRvU6SQXmtCVCDoKyBNw+iz4Wgf80gb0xVUiIhmNbkj3NcCkRnChg+Do4WKhGQzp6jSgERLQGnxpAXJ5DtlSHRd/IMLW7cDCEwrJYgWXXquRNTVWHj1Dyk+jDtYdkPqwMA+5QOZk1axAN2tAmtEAzBHti+psuTletsuJxUXirTblMBYaT4RtX7bnLM9dBxVmqCezoEzmjiMWllzoIrAPmkpC2hAM3qgXSlJEM6xgPBvUoqzdPro05SmZOdsw1Tg7kWVktxUE5J8q5eeM5eHYjrzOFvQogR4MyN+SjLbPedqD8s62m62yU/YPTeme2+n23J/zDGJujkh+u01ZSebrhfC9bIP1U5mOR0gaRmpjDHSaQWU5ZfyUSmA3Gzzp2R00GNQuvrRvPZ8JX8baa+yU6Jjv9sNcpSmCdgtot5As13DxgQDpgsbXLh3BgS91kM1XoEMB1m4RadiqQl1YBd+/DIwSWiDjCtT3nnGTy/XmFs2+yjPwWo08OGEAPqwhv3ARwaGD0J0t5+exXVdODaoGpDYcOQje6UKtb4BVTOt2mjlVQDMGFXDoWgxVawInT9OhGI3AFuZp/6oV6Eigd/c8sjpH9zBD/byGSBja39mAbFbQ+n4dK3/dh97YpMW/2XBXtQgCsEwCSoFv9KHa9SLAjzNnmtYwC2SSFAnMQGH+tFPZVbFQUmYKKQeqP6BSThAYcmIJ0ZUXF9e+PeVcy84WHd8ockTK7Z9ReVgQuEXOlTQAk1WkqBQn5Xiwn1E23EiLmW86Xnh1yvtmW/I5Q7lMxkNmFlVzP6sCBQF1zlWrRJCuU+dPeZ+t8nHVC/yVuiINcZQl7xmAcbXoer6+yecEnPnZvdYZ/qybHd7Pc23wZazrB39kXmiUruDo12L6tB6OkByZR+9ghNGdCd7zf/lz8P+4BB1wBN0UKiSTbnp4HuzOY9Cvvhu6USUi0aqB1asQRw5TS3O7BdXr0QIJgHEOPRxR7T8IEBw8gPzseTLvOnMuh+p0oeca0AFHXgsgK4LaY0cjuso03VousybLEX/1SURfexosVxBn1gqC0etDxwHUMnlo0pUmhosC3cMMwQhoPz2E5sCz/+siNu+uIe5oBCfOgbWbpCLEEdT6JmXmtOvg59ehTp2BXl0D7/SJwIUBWBwXQy7TzIXu6SyHbeu1+6wGA+jhyFw1l8yiZjG3JSsb8gdb8imdu23nc6bRt5iHxG1itIWU0P2ha8W3AYg6yx1ZdTDqkCU6rqxWWpTHSlXmtrGUZM7GR0OUSkJu1IV5rS7Pxn6V1QRNRmFt2t5ZEM5+/btFufXfLvoTt+/08dPgQhInO752+PjrggkDsz1PM1W8mxxe5fG4WeCVnV3gWv6RrWeESeVi67UZSGhD9OrnMkTVDB/9ix/CHWcSDPdXUVlNIbZoTpEYCeC5MxQ0ZlvFswys1QKSBHxpEXqLJjizKIKwKkWeQw9HrlsJWkFudBAsLRAByDLwpQWoKICqCETrZttp0RKLMACrVMgk3B8AgwHNxZqbA3oDKsWVUpBlswoVcXTuqGDxax00I46oJ9A4OYIKOQYHNSoXGZgC+gcYFpbngdMXqM29P4BMUwTLi7TvIxqDoYZD8K0t8uDUakQcAJfZAxQGY+flMfkmYGYeUhS5IafWgGwJw5hCMzmFfIJklId1jpENa0ZWyo3M0EpRO7yZ32VLbiw0SdK0IZplZUiwTUguD/Esd4CVvThjXVql/XP7VvL3WMPvVN/LhJJQzo7Rw6E7NirJxoII9xSz2tInb7+WTKvLPa0oBTfu8bavCTf6+fcAXuXZOZRmUPraS1G7eeytDq/svMDQSkMNR2PBb6JRJxJRqwIAzrw5QjoM8bJfepJasDczBOt9sGEKHZO3I33d3UiPLQGtJvTyPCk2WQbd7SE/e46uvO2E5iQpPBl5TmMV+kRQRLtFV+5GUdBzDfBBiqCbQpy5BHF2FbD+l/k2WK1G3U+CIz+2j0gOQJ1OzTqlK8/N0VylagWiO0T3eAVpi+HSG+YwXAow9xencPKtNZx7UwWN5xmapzWq6xKyAmghnFcBJgE5P7qMfL4GFgTghw9Shk6fiB8LA5eZM3b1aweCAoDWYCGV+dxCndGYChbHGFPXzJW0mypuCcQEuXEqEN3oyASz860sWSpNO4fWZt6YMqoPN+cmM63wepx0AGNEp6w+8bjiuqjsfpfHV7jntPs0uf8z3pv2tTliVyY+pWM09phrMOVfEdOyg8rkYzdlplIH5MznnvZcHruC9/NcGdJMPd/Nl8d0+CNzI6EV1HBInUWH9kEvthF+41nwHLj3/34SbHkRtfMJgl4KjFJgMIQWDHyYITrbRdBJgM0OIDXYfBvq0ipYqwnRbFICs+C0uAZB0QllAszsHB4WhZQynGfUAcI5dMDBVzukpnR75NEZjgAugDgiZWijA57mlL/DOLWhD4ZgS4sAZ+DLi0CridHhNkYLDEwCgxVg6zaG5957DAAwOCyxdZfChddrXHhtgPoZgK9uQr7mHuitLu1jtQIVcohuCr1/yfgsTCkmTU2pSo8pI2MLuiUsStNg0LDowrIluclhoeXzAxSmYPez+3Oh9LgympRkctamTGTMyiwg/xPj5pzY0hSj+zJeDEQdK9mY/bPGVEdwBDdG66DwaE0MDC0nHbNyOa7czWQHnJYN0OXXP8P8u20eVHmb1wNXk9FzJWg17nsqkZ/JsRm7fi6PbfCEx+NGwJexrhHX9A/LuGstBmM0AZlxCr7b6EDnOfjKEo79+uOUcVONEFzoUKkqjqCX5sByhXyuCs0Zgq0RMNcGAiqb8CUaPWA7nxjjbp6OzqjkoE2IHQBorcCM7CnuvA0YjqACDvX175FiI6XL9gCjwaSQkkgCY+CrHSp9VStU3qhTlgxjHHL/PFQkkDUE8gqQN+hl53WN+bvXsPbsAvb/BUcwUFABQ9rU6B1hyI8sI/jGMxj8yMtR/9Y5sPk2ZMzBayHE5hA6jshcbDwoMF6TsZZkIQypMFk1UhblLtM1BW3mYyEcVzBQlH5oQZ9Y/MvQyhl4dYmo2DRbu02V5RCtCKrbhWg0YIeDkh8ocKGJ5TLcJKEYW4CdosRcuWxsSKklNmMKxUQacrl0ZcgTzMwwd5v9PqtsNI3YlJ9zL8pAl9veTtSdWfex59qcO6u0Uppxtjf77jETvrQ1Hb6Mdf3gyc4LCMaZWwiZEBQ0B1CGDGg8A3oD6PvvBE6v0qIeBm6Ug1pogilFJa1RBh2FNA5hi8pM0JRBg+GoUBUYA4sj6qIakN+CVWKgWhpVUK9AxSFEkpHJuNmkFmOTu4NqBWptHdjqUju7UYUwHJGfp1XcD4MhUK9itFJF0hbQHODmIjqdk2CS4fX7nseho9/Af8CPYuWvOHim0f+JLiqPthCs9aCSBGKk6LVs9RAMGwgudWk0RELzwpAkRLryfOwq3SkUGXljnIJi2rrtfC66zXhoSovaWAqxuY/5w/STqqcM2rQkKA6IK2kFnaaUY8Q5nTNLTmxXWKmEVJSdpCMvsG3tgS1HTeyP4EXTaUmFskGHzphcCtDjUURzvEShLumJbcwiCZf9216RhCupOZNeo2mYsS82/NKqaHb0Rplseni80FDgULsouOzmsbc6PNnZDa7h6o/bCdJCgDcbUBubtKk4ppbe44cgzq1T5stmD3quAawsgCU5xEYPSCiAEMORK40gjuj2asW0oRsVIM3A9i1DtaqQ9QjB2gBsq0fenmYVOgrA+wnYRhciyyiErx6TgbdaBebbdFsYUIkrjqE7W6RMmOAzFsfQ7SZYltGU8yCAbtUxWhAYLjCoGJARER00c9RaI8Q8xzua38T5h9rYfG0VnGkM8ghf+6EAi99uQTxbBPyhWYcYZBjcuQguNaL/cQLs4H4wMzl6cjgjC0JT0qEQQRrNQOU6q0iVvSfMqiqlnJzy9ibNujONs/ZvdrucSlYQAqKcoaP1uFpmby91SYFpZyAuyNf2SdZFdo8GhMn2yZUjOSzg29vhS/tvJ6Q7pelq3tPT7rMTn8u1KCaT9y9v40rbmqFM2ZwgGvw5ZXiqx3XDtuG1Hh4vADzZuQa4EtZVfmhrpcFcezOjbJy5NvldGnVKG+6PkB9egvjOCVJgTl8gv0y9SuRmvg1sbgGVGOrCKli9CsYYUK0gXyLlR6x2wdIMCDNSX1pVyEoA1q4i6A+AkQJb34LeN0+LZZbRcE0AeP4sAFKbOABdj6GqMfjL7qB9mQhdY4f2QwtK49X7F4Bzl8AGMUSiUdkERvOkN0SbAqlm6GuGoQzxwf/lfTj/Q3PoHdaQKynCao7aV2sYHFCYO3wQ3aUA0XoMfnETLBQYLjex+CffRz4YgK2um04mk7Brs2DscbbJsqXbVGerKBVNGHGZwPZyySxj7OXO+TbSY7rBpASikAhVKTiQDMnMmZjHfCRA8dpsmc56bJSmqpQs8mecQdoYmt3vZaVqKkkTztO0V3Of3M+zylxXs73JVvBZZGnW7TOIqR38ObaJyRKWL2XtKcq+Ngs/amIcUjPIXZSidvPYWx3+UuaFgFk8GWeUk1KtgnFOqk7DDK5UCp0f2EcdSEPzIWwGg6qEykVgDNjoANUqdKdLqoXSgNbQlRB8mEFWQ7Ow2uGRGvzCBuILPQRn1woFSHCwYUYLsBBg7SYZeNst513AKIGqxhA9avmWnQ6V4YyZk8UxZLsK1hsBzQayxTpYpQLVrCGrMcw9OUD7OYlDv/FXuP0/reLe/9czwFDgi8/fBb7Rx/z3Usw9yVB/IoZSpAJdfA3D2b91BFvHOHQoiABKjcZpGhkh5ubAWuR7sSSAl3JpdJ450qBGiQsSVGUzsz0t9jFZPq5+oDD0Xq576XLnmcUxER3GqFRlwxGj0BAcWy7RzsTMS+bpsmfG5tk4v5dWLvsGoIWbRREFMXJWZN9MjrmYaFUHQO8hYDxPaC+xW7VkohNsqmdn8vargD1WU706nujsDqX3rptztgO8lA3M1rOzmy+P6fDKzm5xpau/iQ971/JqwuaQpND7FjE60ED3EEfj4BLYN58E4hj5mbPk7alWSQkAAKmgLl6iUQNKkVLR6xNRQUYnVCry5PT7VDLJc7CNLpAklI8TBFBzdchqgGCLfCyyXQVLJHhvSIuqpGnjTGuoOATvDhDceTvyp5+l8pUQlOFzbh2614e66wiiZy8iP7oCPswQJAAfZIg2A4jbjmJwrA15zzyWv8oxWGkiPyhQ/cZJVM4vYuP+OSw8GePU307QbA8xyOYw/z0NlpISoqMA0TeeBZufo5KdS0Lm4FVTFmTBuGpjzOBqOCISABTelbJicIVz5xbAKy2sE91Tlui4MRBA0RGXS5cXNLkNW76y5Sc7IJKVB3SW28hLHVXWqGz9SoxzaEigpA6NtY1LCWZLffm4qrQnmGVsvlrsVLW5Crgp526e2UuwvHK5c3Kt52uCLFIidHbZh5TVnZcy0QEAvcup59onKM+EJztXiW3/jFf6QJgi5+ssA282wJSiBWqrj+yuNlYeH0F0h1CCxkKw4agoeVmvRyzAOSNjLUDpu5wBl9aojXx1Hdp2KkUR9HBIoXZhSIRpMITevwRZDZA1Q2SNENUzXWStGExrxJ0+WBBAM0YkKaUvSAm9vongjtsK1ag/hF7fBFtZIlIyGEB851mwhTnMfy2DFgzRxS5ULUb3aIjBPoBnADiwdVsVjeAQoos9LPzZCWR3HsD8V6oYLcVon9FoPj+CjgIkxxcQP78BLRV0Zwuw3hutwVsNqF7feHSK7hpWMiLTgi7Gp2VbsjCxuLkJ5uZDmoeMWvVnlYGKB7q/O3Ox6YpTnS7FANgRFUpTJECSOhI0NhLAkJWxDB8B9zhHnMzrU2kKUa+510+lM5pn5o6JJUXMTtcu2uXp+QsPz56Rkj1uFXfbnLWtnZS3rvDatoVG7mafb5YS2OW66XZSkr1aXM7PdpltvoW/y6lALynC6fGCwdPAa8VO5XlWpOFqk+LLogi6P4DqD6DWNoAgQPPJDQRf/jby7z9LC2OS0NBOxmkxUgrpXQeAWhXqyD6ou46YFnMFZnN0alVaDKWiRGTTxcUqsQkTzIF6HXm7AlkJqHShgeHhJlTMwXINvbZeZMUEAdjFdSI1m1uQm5tQ5y5AzbegFlvA8gItzpsd8G4CHNoHVqtCXVzF6HAb+XwNycEW+Oomop7GyuM5Fp/Icez/eAqtZweQFQHZrgJxjGC1D5FoNE/SYp7OhdCMIZkLMbx9gV5DFNKAzzyn186MVyhN3eR2FoU0XmKUjF+9syL4j05Lqb28ZCwuY8zTMc14W1Z8DHlgQQjeaoDVqk5hcR/eAR1zPRgWZSw2XmpyE80tEeGsUHWMcuM6yrRySqHN9mGmpGXvD1Zqyzev0XYDAij+FgQ7K2Nd7n0/zUhcbmHfLcrlrMn9mWWMnkW4pviyxhOqr3C+d7KvNwMu100HbB/muhewx2lWfEEJvFp12VHuvY+XrsIjwXb95TEdXtl5IWEMocp0O/FmA7o/QP7MCfCYppHb8hCAYrSAEGALc8jrAfK7FtE7GGLu6RFEFJkFlAOtJtDZotbwNKVFLjMzl5KU1J+MSIKsBpAVDmhARzSqIehm4JkiUmHnXw1HYAtzpCqYsgrfvwIFkNqTS7B2kxbsXCKfqyI4r6AeuAfhZgKe5mAKSO/aj7mvrwEBd6WpvB4i2kwABVeGWf7yJci5Gi6+poGkLVC5CDCpEa+NoFcWgBOnyaPTaABZTqqOHcNgBoE65YMz6Jyu0GmBL3U3SQmtSiMT6A9wmTrW2CtLBGhaV5Y7pyhC/QDY/BtLvFzJ0ig7sj+AqNeK57am44DmZ9nXBFF0dNmPMK0UtdunKaVUW2KjlBskCju5XUoihqb93O0vC4tjYQgfK5exLncVfrkr9bIqYu5LpEqMkcpdlUdmKTVXqaSUJ8Hbx6pSJMG07dmso21RAy8W7NYwfjVPVT5Ws4iOee/aiwplyuO0gZfmdbjSu8vKeZGOUHtB8NJ8R10jxq42dvohYT44eZVGQTjfBGNQm1tgc236p7f3q8SApunbzIxOUCbPpnJhgLRNc556h2MgjiipWHDoi6tQ3R5gp5IvzIHVamBzbbB6DYxx6vgCEG6lYJmmDJxUI+jlCDdHYKa7R3a7RU4PACgJtm8ZYmmRBocqBZZK6AuXoJs1IM2QLzcpALFWBR9lSJYqYOtbCE6cB5OaiM4gofDEUQItGNL5CvrH6rTNJAWSDOJCBwf+6yksfvYpiO+fRPX8CLIagHV648fVkAudpuPdTCY4UJlWch4GTtEpjj03H8SF4uHMyPZvSm+/6p32AWyuYO22VDKC2uwgv7hK58EMJ4VURD4BiBYRRF6rUbCkfV+kGe172ctjiVIUUgdaklBsQdV05wlOX5wXJKf0OC0lpWPbUROG+JRVHEt6lJ1ivpP39pVKeuZnS6Z4tXL5x10OlystTRKoHW5/W1L0LOJk/mbfCzsayHmzLdQTqkn5PX+5ktFYGveEgf9K0Hl2xXKUbRoAKyVY21LzzaKMedwy8MrOteJqriQ1GYl5XHFmUNZsUDZNlrnSAn2wUqeOGo6oTGEUH7W2Ds4Y2rmCqgRIlqtIj8xDMwYxXID4/kla6C+t0e4NhsiPLiN47gKpHQtz1Iae5YDUiLYyDPeZgaQRh6qGEJ0h8vUNChXMc0rUNVPHEYbQS3PQQQCeZJDPPgexsgwVBWBphrQdIm0to/bEOfDz66hmErpdB85dghhkyNsVhOdXoZcWgFNnIWOG828IEK8Dra8bD1Bgh28ySoZeW4foDIFzF4E4ovlRgEuDZlFo2s8L47GynVWmxMPimEp61mhsz8eMc+o8LbPuN2shK70frOoCM5YDYQAEAgyC1B3BXXmJ2flcZeN6Kbla57l73aLVBBOl51eUkq3z3KRKG6NxFDoCWCZ208pUrqx6tTk7s17/lBIQ44yM4pzBJjlfVZv7LCKzGwP05UjSlP0fS+je6f5ey35dB4yNArHlpSsoVCwgVVIPhyXSP/0B24zdlyOmE7eV33c8iogcGzXIGpfLF5m3epu62qVBeTePvdXhj8wO4f7hrqJu71qAAbBaDXzfEhjn4HNtagFvNaEX5ugDwLVOk5Tu2qlNW7LKcuRnz4GduQhxYRNiIBE9fQHR+S5ULKBuPwy+slxc0Xe60IJBL7QAxiDna8gPLwFhALG6BZZLxOsZmNbgmQIfpER45ubMhyJzCoPOcmAwBBum4OdXgW6fhnH2+mC5AtpNVM/0EIwk8sNLyO7YD5w6D5ZQmz3vDMBHEul9R0kVWlkCU8Dc9zUOf+S7UPNk4NXnLwK5xObr9kPO10iZ2twiRWNgBn+aMp8d/ulQWojch3r5Q9iUpsp+FXeeJuZDFZu8zFX8xCJpt2t9OzDqHQAa25EXAYByfYNKUd0ueLtFnXRRSCXLWhXMxBGwZgO82UCwvIhgZYnKYnFMio6Zg0UZOcpsWxUBiUq5Upqb5m6GnBbpzbo4XpOv62pRXuCm/I+UyxOWOFytWlBsbMIPMs2EO3n/bZtg0x8zZf/Lpcyrbs+/CRSKsS68nagm9n/Fvpdn+aHKquaUx2+779SdU46MqzQl8l3y1k16d251L48C2/WXx3R4ZedasIMPC/pWupJNU+gLq9B5BtFsQHV74G0TAri4QMGBcQzV7QLliczmg8RuS2vy1TBNHg+cvYDw9DmwxQWkd+xD9NwloDeAGg4RPnESqFeRH11BcHoVo5cdgLptBZozRF9/BmLfErC+SYF7cQzeakJryu2hMRMxdJLQGAuT86OzjDw9jJG/Z5AASQqWpAilRLrSRPzMBVIzAOhWAyyXYJlEXq8iqERgcYjK+SHCXgi2MA92fh3QmsZO5DnCnkLvaB3VaojwG8+SelMtPADMzqFKEvMhLrYvVgCgNFSakPFUj5eoti2QJuSPPirk9A/x8ikWYmw7Vg1y2T/1GmC8RLLbdfcX9RqCxUVSerKcuuSMr4fZUo/ShecmDJ0SBMYBU/ayRIEJQecMIIIDFI81sBPT2QxusWfdL6XjWS4Jlv+2o+eapYZM+qZQlOCmlp54oZ7pfLv/ZibJm1Uqww7LWDcjduhtKgf/2UG5dJymnLcZx2kqIZymdpX2pTzGZJvqV7rfra7seFw/eGVnB9iRV2eiMweA+6Dl9ZorrYjFBchLa+ArS1RuWN0go20lhtzcBGBmZU1TKhinq/bNLUTPrUFvbbkp4OriJfBMITuyCNSN+VlKoD9E8NRp6MEAlVObiM5sIuimkC87BqxuQO9fIrWg1aSQQ8HBYsqDYWFI5RXBaZ+y4gPJLczDEQX/AWD9BOK/PWZGTIRQzQoNKdUafLOL+MIQfGMLbGsAsbqF6EwH6sw5yAuXoEcj2Pbs2l98HwAQXegSoZlIXVXDYqbRWIlh4hyVrxIdOTDhfGOdN0FAZR+Tau08DtO+jDqkyyR0onTjwv9AJS3RbII3GgiWFmhYKkDHpN0kYmJHfJjuMkQh5QmZyAG9Tu8LZJm7DeVyFmPjP+tiQVbDEWwX4LYr9OugOmxTcEpEgVerY8+5jThcab+mKDHu3JcJkBBE8CwpzrfnvEymVV/2tdjnfiFVmuvl+9nJ55e9q/F77QRlf5tVEGdu+0r+qsuVK29x2ATl3Xx5TIdXdq6AbbLpla6MSrIvC+iqXI8SWnjjGHJ9E2J5kRaDcxepyymKoDpbLsLeLczlMQGG/OgkIW+GyWnRpZk+4lvPEDlp1GjoZ7sFOw4CgwTY6gFSQmx1IW87AHnnIYgT52j4o0lG1qMEbshkaRHlVWql1oMB3a/Xp+2bEopeoJ+DlWWoA4vgqx3w7gi6ElKn1sEFsL96Arpeg7zvNvBhCn7mEnitBtnZAquatnnOgcP70HiuD6xvFunGeU7HaZQ4hWLMh1Iua1iyoyamgUcRlYAAaMbAGQdfWiCikWZ0bCW9HhbHpKKUxzpoXWT3lM2bVsEzJMmOq9BpSonPYUDbsWUmIZCfPYfg2BF6PmMch5R0vzwH4piSriWV/cC52Ufz/ohDQGi6rzTnqjwclHMqUVbiwutk1B2dZ6bESnO4dnrVP/5G3+7NsapZkT4dFKoLANnrEeExi+E1TRefou6Ut1EMUUUx+2oadvCcOx4KukN/ylXhhV7g7eeLIaBuvtxOHz55wTG57Vm4CTxNNxO8Z+f6wR+ZvYD5h7XqjZtorhUY5zS/ynTQiDZ5aPLnnqcyR0b5N2OdQkAxkqFUrrBmVmdiVUauD03ODufU3TMc0e9aQ+2bp3BBRdk7MGUqlkmwUe5UGW1zeMyCDsBlvLgAwyQBbzbJV1KrQjfrjijkc1UaXGqCCNEbQC7UkS43oBumrf7+u8Dm56ACBr7Rp/0BIFaWoFsN2pdGDflcFaIzgOp0i6vz0oew+12r8St7+8VKmSn2PoAz/rIoAm82wPctkYJSscdUkSHTqFasVgNv1OmY24ybibEKY+MnQuqOsl1iLIrIm2NIpvNljUa06EsF1KuutR9CABUTJ5AZc7PgTr3TSUJEyipH3JS3jK+LBUHhZbLEijHn/7LjKNx7a5IoXqZ8sw2TSlq5fFjqwpr0xqjhsDBmm/+Xse1cSdG4wsJoVayrUSVmYpo3aKfY7QL+And0uXNRLje+ECTkKp/jLfxdt7xv50bgt3/7t3H8+HFUKhW8/vWvx1/+5V/OvO93vvMd/NRP/RSOHz8Oxhg+/OEP73qbLwQ82dlDuIVECLBKDD4/B3ZgH6kWQkANBkRGAgEeV1xrsirVxp1iYK9QbQlmTAbWRfeOeRykNG3YEqrbM+3nLfDz68XimOfUBh2GYJkEHyQU0ucUIjPTKQpJ3TEmW9aoA4KDNxuQdxyk7QlB7eJmseWphFrfAAsCqFoEdfwAWCIRP3MB+tlTCJ45C/bUSSBJED11DurCRTIQW5IlTBdaPYYYZEBna0zutsMqXQvtLEOqJToTsrmV1nWWIV/fIC8MAL22AYwS6K0u+ZGEgNzoUMZQq0FdbIdWiLyWzsmYMdY+l+mi42HgTMqkKIVQ3R7UKnXKyY0OEUrTNaWrcTEOZG2DPDzDIXQcQJtxE3ptg3xTrsuKFSbkICATtC1tMUbnWRHZVsnIZPfQHC4bTHhFI+ks30zp/V4mAc7UaglhSeHUthvRno8dtCZPxSTpmFQGzMXGnnhrygqS+XnseE2+B/aCoEwzXL8AmDwXO/ZWuQfsgKjuIW5VwqOwy9lY12BQ/sM//EN84AMfwK/8yq/ga1/7Gl71qlfhbW97Gy5evDj1/oPBALfffjt+9Vd/Ffv379+Tbb4Q8GTnMtjRP9TEB5MaJXT1OkrI4Le+CbWxCRbH4AvzYLcfoUW7EhcZKMaT4oK4lO2sKV1xa0Xpu2kGPUqgen26iteKzM9ZTiUfEzTHlhaKMpRJUtZK0dDRagV2eCirVIpZUyVjK6vXSNUZDGl+13AEvTwPWQmg55rkscmNMjRKINb7lPkjFTRn4Bs98LVOQSoGQ1rgjbpC9yV1Suc5WHdA+TFrXfCtIS3Wohjz4HI4pNzut5hYGFSWU6nGLMZj3TRhiGBhnkhellMoYk7dZywMwefnyHPDGdR8C7JRoeDDRq1QUUrnxC3uhqRav45K02LhTeg9UU5kLo8BYVkOvbpOSk0UQQecSlsKZESPY9pP025vQwtpP7RTfQCYVG0iNbLXJ5JRrRYEx8J0+k1VVy73Xi/97NS2iQ43l0yNQoGDpgwip/rMWkxnEayr8BntiSpRKoXN/PsEGSp3Ee3mOV80ZZ0b7K25FVUevctOLH0NZOc3f/M38bM/+7N43/veh5e//OX43d/9XdRqNXzkIx+Zev8HH3wQv/7rv46f/umfRhzHU+9ztdt8IeDJzrXgcle/5nfZ69NcKk5dS3o4grxwCVCA7vag+gPqzJqbo02WylXQinJJwrBYXAFSb2xZp/TdjaHgzJTGMqhzF8AS00FlfR55DlQrkPMNahkHgFqVFlKACE25E4NzsHYLaqtL7dDrW4ieuwT95AlSe7gANregVxagGjHyk6eBuRbyRljs78YmvQ5QmUenGe2HmbYOTgQEOalT8vRZ6PUN6MHAkAE1pgRcNu+ktACVOzrGrsbN+AYWBoAxC+u+6XCKI0BrMo9LUr4AAKEg74wlhea5XNmxvBiXy1VKE8GMIvBaDbxWgx6NqKTUbLquNgSkBKqz56mcpwAdhdBRQMQny12HHltZcq9DXrxE5FJKKiva42qiA3gYFJGqjBXKo1GRmInpt3H9297f0xSUchfNpNJh4N5DE94m0WhcUZWbdtvYYybP+5XIETC2DzuGJaoTpbCyMd6SaVYi5dOef0d4gctWtxJuJdKzV1PPt7a2xr6SyagOgzRN8dhjj+HHfuzH3G2cc/zYj/0YvvKVr1zTa7ge29wL+P+wGRjL1ZmCbRK+MSOPeWyiCGqrB7YwDwAQxw6Dra6bgY6KFj/TSgzTvWKv/lkUQhpFBkIUC1QYzFxkWETZLKzUDQRT2oIQ4EcPk5KgFFQ1hOYc2OgAfZPYy9lYmUSPaEo6q1aAVoNut6m9WQ4EgnKCOIesF6F4YiSRHFskU3FME9TVKIFWRp3KMlJWAOdHQZ5Dnb9Ei4Yp60EWbeKuVbhcVpj0U0wsiM7XM+H3cXO1sswZkhEGNFZDSmCUgB8+CGx1of/6W8CJ02Mzruzi5jwwRgmyioYuBRtS55TpyKvE0P0hncOY/DwIiEih2QCfa4MZ1Ypt9QDBoGoR9MYmqVBGObOeHl6t0rmw5S272JYXX3e8iHjZ82zTl1kUurlYU/OH2Ph7evI4T05SL6sdLAjd+5kIFXO3j91/8ueJ27a1iJfP8yySUO76utqSTPlxpdc/6/7OnzTZvXWF7U/+bRsR9Lgq3CqEZy9w5MgRtNtt9/XII49Mvd/q6iqklNi3b9/Y7fv27cP58+ev6bmvxzb3Ar4bawqm/tOUP5CYGTiZ01gCHkXgzSbUYGAWIAHV64G1mmB5Dh0GYHceBUYZqSemo8cadG2brKjXqASmaPHnUQRWrUD3hwUtNYu/UyfKybdmThaLYzLFZjnNzMpyUi0Yg1psQdYjhGc3geGITK9mYCWVaUB+nTynNmmtgUP7kC7WwBfq4IMMyV33oXKyA5w6C30HBQXmtQAhQMqSYIjPbRFh6vZo8Y9CRxJUf0BqjlEgdJrBtVPnOXRCV9OuG2RywZvWkVNGuTPHPYQVZRvOyRdjg/gAsGYDutOlEl8uqdvNhKrpNIM+d4FKQs2mSzaGmR5u/VK2+4cFhSJHwWx2cCeVb8TCIpGr0QhsOIJuVKlk1WpAhwLIFVCtUDmvRiGCuhqDKQV0e8BcyyRvKyI6QQC5uUnkuaSm2IRpKDI783rNeZ8gSuTFermmKGblrBp3myFSbko8MEas3GiF8uMYh+wSeeeRgJ70pVxtR5PZT/u/c1WJzNNwmcdue+8BheJT3kddDqccD7Tcdt/y784UfO2770Gwn90v1jyeverGOnXqFFqtlrt9VrnppQRPdiawTdEpLQA2wIxXQ/BGHTrPwftDumLfvwg+bFL5iDFaFAMBtbZBQxazHCrNSm2/RgqPIkBp8GoENteGWFqEOnsOvN0yHhdVDIoEjPpiFhE7v0lKiPm28/G4ydibHXq8LSkoBd4PwQd1qFYVvNsjgpSmgGZESjijtuz5OSAMkS83IWsBxKOPIbjrDuTLTWgGDO6cQ9yuAgzgowxMAfyBlwPDDHlFQLSr4OcvQWc5eKtBao3p9GJhSCMfTKu0HgyoLDbMi1JV+ZjLYuHUsrhtG+mZPGeWFFqVRUpS2kwHFKvXyA/DGHWwlTJw1GYHfK7t9scG85EaE5hQRwadk1dKKw1mO/IA8EadSpVKOUJqS5fOqxPHZBaXJsgxy6GroZlxxcASQ5D2L9Ju2edVmh7HKYqAxTGRbM6LgaG2gy7PwOMKrOGcCQGEnJ7PDg7VypQYU/cep8M4PiHdng+LckmH/hiOL+ZaARAUpxCERSzDxOK/rQSEEsm6XPu42cfJURf2fbInKskVtkEXP2HpdeTjxGtsn0pBj2ZEh1aXIXQeLzmUS1HX+ngAaLVaY2RnFpaWliCEwIULF8Zuv3Dhwkzz8Y3Y5l7Al7Eug7KM74hOJaZ03DAkM3CFupdks+q8GuzgPug7DkO3TUnJKDnKZOKwUqidTlOKSVeKAvoA8HaLOnnS1E3KBmAC78w/gpW8BQev16D6A1q4JA3ChNLQ/SGZl6Wk/VAauj+AOnUWvJeQssQZdYsB4K0GvQajsuitLSIymUL6jgeRP/UM2Fe/BZ5r8ERBVQRkLYCKQ/CUjMfpvibCfg6+RRPTWSncTfZ6RtnKnNfEGo51f7it/b50IuhYTYTUbSvllRaYycXFLYqCg1UqRK5s+F4lNmUgRapObkpEgaABllo5w7HsD4iozLVdrs2kf4qFQZF5Y0p0dv9Eu+3CGfVgSOczzUiFy8eN16pZId9OHJJJWilS6rQG0tSoSQGVQoVwKpUemoBGQxbs5HVtj09easW3ylYQjOU7lX0ok0Rk/NQUCtaYn8ced0PubYmGxbE7lvS8YUEOJj1X5vFj5SrboWjf/5OdWJZQzeiQEu32ttdwVZh4znIEgjIXC+54jD2sVOpj4+8bD48bhSiK8JrXvAaPPvqou00phUcffRQPPfTQTbPNvYAnOxOw8qedC8OjaOzqlkUREMeQ5y8UGSjVCpUYzOKVHmiBr3UBxsDm5wCA5mFpBd5qQPV6JaWCrqzVcEQqwdo6LZppCp1mTvqn9nLjAbFXv1FkrtiVSQAuOl10TioSpKS2aevRMCZcbHZom1lOZSXjA7FmWkgFub4BlkmoWCD67GMAgPyHX42sKcAUkFcEdV6lOYJeCjZKwaSC2ErAtIY8eYZIXJZD9vpuIVLDES145sNemPLKtPj+aQvC1JlOJZQXbQurzOg0o86wzhaVqvp9oD8gcpck44TDeJlEszm2X7LTMUQiKFSzkiLCYtOazzlNMR8RseSGVOosB0YJebK0hjpz3o2GYGkO3umDXdoAyxV4xxi1Aw7WT6iMZVrO+VwbCIMiewkoyoFS0T7YDixHrjNDlEslPEbZQ8x0bU2eA/faSos846zw3rDxtGSrCPEoIgWjVPJRg4Ej+rzcHVZq4bbbddufNEbbc88mRnqU9sP+306qJs4HtwNc1thc8omVwwfH3pszGhkYZ0Vnnld1rgterP6dGzEb6wMf+AD+w3/4D/iDP/gDfPe738XP/dzPod/v433vex8A4D3veQ8++MEPuvunaYrHH38cjz/+ONI0xZkzZ/D444/j6aef3vE2bwRuaBnrkUcewR/90R/he9/7HqrVKt74xjfi137t13DPPffMfMxHP/rRbQcsjmOMRqO93TkjwZPyUQeyHMHtx+gqfDiCuPM2qEYFPJeQBxagBcfg/kMQ2QHET56HWpkDP32RiFAlLgZZmtopXTGbhdV8KKr+gDJZen0I0/rNopAWiLhSlLOE6WBijK7uhQCrV036sQkcROmqvN0k1UgqaGOMRhAU5STTJUXqj6L8l2oFwZ23AxtdhN99GlorBMeOIAsZgoGCijkgNZRggCyuWsPVPpmeKzEpRVJBbnUh2i1TJuE028p4jBg3wy8NQdtWBpn0OczqxNp27opF1/7s/maULp3SIsyisFBnBkM3BZzFkTMBB9UK1GaHJprbQaRSuTb48vbVYEBXEUEA6OF4W7aZ2K6H5NHCKDEpzpSpw4apux8lKpNiw0YZEbJ9i2CdnmvZt6TGwZIeYUpVklKZmSUiAq6MBkZlONtlxhDAnslyW3n5+1jpapKAlFQcZ9g19ykbma3CWW5LH1Pj9PhIjqkeLWZHhaDwSpnHUAmrIJ/T3hvl7cwiHJdVXma8D8up59O6udxzzpgg7vHSxl6Vsa4G7373u3Hp0iX88i//Ms6fP49Xv/rV+OxnP+sMxidPngQvpbOfPXsWDzzwgPv9Qx/6ED70oQ/hzW9+M774xS/uaJs3AjeU7Pz5n/853v/+9+PBBx9Enuf4pV/6Jbz1rW/FE088gXq9PvNxrVYLTz75pPudsWt/c8wCMzkkfK7tOpE0Y5ArbQQnqIMqr4eIJA25TBZiVC4MwNe2oOeb4Bc3iVysb9KHX55Td8r6Ji0ItjQCkOJjQ9+0Bq9WIHu9Yo5TXHG5Mcx2tdircjsoEnDTwO0AT2a6hWA6n5x/RZAaxGpVYMgKdSIyfpFqBfr8RcheD8E9d7oP/fz5U4j2z2O0UoFmAAcRHb6xBV2vga1tQB3ZB543oE6eNgeSQzTqLv2X1cycsCCgERRaGRPtjBC4ktl4anx/SRGYpgZpxcG4cosjbzbJzJskrnynen0a7bC4QKoLZ2ABhUMil1CbHbBGHXxxAercefKgdMbHeNCumI6sUeLGgABw3VGWZKjBALzRcOfBpVrnxjwcBmDzc7S+CwY+zKDjACyTQCZN9xUZ3Hmt5l5zcXy0K2PZsqROU6fuOL9OmhEJMv8/2pV+NOxiPEYSy/8bUzqn7DlyZV+jWro5VbOIqlNIMF6ugtx2n/Jz2uGrzgc39nfhyNBlMY1Q7xTTynZllcfGO0x2Cno1x+Mmw8MPP4yHH3546t8sgbE4fvx4MXz4Grd5I3BDyc5nP/vZsd8/+tGPYmVlBY899hh++Id/eObjGGPXzejk5E+zGKPdpDbtUECcOIfsyHEEAHQcQguO/LYDGBysIOpK8LUtbLzpMOb+6xNQxoCrSwF3LApd+Ju98nXqQxCAmWGUNpcGoJKHSoxqxTgRO85J3bEG3CAoqRQRqQKMEo9Rq5E6kEsw3aeFrVYDhkNa/BIGJiL6AFYaOk1I8bn7GFgoIEE+B9npAADEahdBLUQwyJC2I4hU0b6nGZEkM+LAqSOGnGnbqWbSn237t+4NiQDYGV9TFpBJ/802zCgX2N9pUTSlpsGA2qBtgGIUgjcbUJsdIIro2I8SoGqISlJS44YjiIV5Kv0NBsVVe0m9sPuj0pTKgtZQXqvRuWdU/tFZBh5UC5Ulz51qhyx3xERVY/CRmYMWh2D9EXWM9frgjTqdM6tWcQ7XXg4UYZEwRNfcpiHBrIfHmq4BuNDEvKS2lIeeWg9PqWy3feRERov8mOlYu3PIw4DUMKuc2u3maoz0sODKpKBsVLf75LYxxSQ8ExN/u+L77TKPnfr4CWXSd115zMKNUHZeKripPDsds6AuLCxc9n69Xg/Hjh3DkSNH8JM/+ZP4zne+M/O+SZJsC1jaCXi9BkQhVC0CnngW/PungLk2qk+vIr3nEFQUQAfMtF1zJO2AjK5ag60sQb3yLgDFlZ5WdEVf7sQCxq+Gy5OsrU/EdrLwuFK0TVslqxIXJYixjhkyQaNWA7IMqlWlRaxFKbxw2T4MzJAhR5xqpHawJAPLFcRqF7LTgWi3wV53P/TGJuJnLgBaIxjkCC/1SDkyeTJiowds9cCqFfDFBTK+1qrg1SoZlKUEW5gz86DIa6RGyXiZYsYCcsXyFb14d/9yLkzZv8OqVTKGD4fQvT7k+iZcavUoITIBkJG3EhNhk4patEeJIS1TMl7K3WDmu/NQJQmVB026MeOcyIYlGrmEXls3x9KYpQX5obQQ0EFAqk5ZseGctgkAluiYKy4qs5HPi8aI2LKXuS1JabDocOTSvskQX+Qa2ddUNiuXy4JjBvGSd8U9ttSdZsl9QXQKNWqMNNrNTZKFMvm1re3WzF5W9ErH3s2Tm5JJdTlMazWfiYm/26TvHb1XPa4rXoy+nb0KFfTYjpvmP1IphV/8xV/Em970JrziFa+Yeb977rkHH/nIR/DpT38a//E//kcopfDGN74Rp0+fnnr/Rx55ZCxc6ciRI1fcFzE3B7RbkIeWwbsj013DgPVNoD8glZ8DYiShIjLrpi2GfL6Ozbs5Lr55H/JGSAF/UVjknwSlkpMhPUDpSlATAdCjxOXo8CgCr1aKWUImmA8AJTQDxQJqMl0QmWnr1Rh6vom8EUEut6BrZpRBr4/8wkV6rsGg8BPVa45IsWEKfnYV+TMnAACy0wFLJJVX2g3wJ08i2ErAeqajiDHoeoXyY+xsrs4WdJpCXlwtDq6U0OubkJumvMfZuFHVohzaNmletn+fogBZ4yxNODdlQPOzPc5yq+sWyvICqfsDyM4WBf5ZQpnnboo5bBlxmnF10lNSut0t/hmFLDqCyrgzG9up7nqUkHJ07gLYRpcUmzw3re7cjLYwJMcYpK0fh3FebLts7nWlS0O8hkP6Mp167r2V52OvY9Lg6xKDpwQQuucqnyJrNC7PySqTzpIqVP5/2IaJ28fI0eVKYyXD9DXjSh6xiddMnZW7zPzx8PDYc9w0ZOf9738/vv3tb+MTn/jEZe/30EMP4T3veQ9e/epX481vfjP+6I/+CMvLy/h3/+7fTb3/Bz/4QXQ6Hfd16tSpK+4Lq1Wh4wCiN4K+uAqtSjOONrcQnutAnDgHFXAwqZFXgHCgMTxQQeOUxsL/8WUMlwNkdx4Au/0IpLlapy4rMgQr2xJuFYhSDXQsjE1wyk+xxk9zNY4sd2oMXb1ntFBHIS2oJpNF1WPwzCw0qQmX27+C4PgxNyDUJgCPtUnnOaAUguUlt1/qG08gf/Z5yGYFyYN30SiDUQJUq1CNKtgog6oX4VUsimjwKWhmGBgFHtpSi+r1qUw3OesKmEkcyj+XyxYAHKGx3iZmOpVYo07hjLIIn+NRROpdufxkiY/JBALn0EkKNRi4Dix6HpM4vFPFwJEqTeW7qAjd0yPTAWbLfw2aJM84p+9SU9u51pR4bSIB3PtF66Kl3M7MMuTXLfjmue37zx6HSSWkTCrHZltNOwcT56c8OmMyPsB1JpnjIBoNmtdVGmYLYEKdnHJs7espdWxdyWC8bfbXtG1e7vZyaXWnas00glTeZw+PGfDKzvXDTREq+PDDD+Mzn/kMvvSlL+Hw4cNX9dgwDPHAAw+Mtb2VEcfx1adHMgb1vWfcBxZv1CmMLgzAjxykzqZaFSpkECMg2tJoPtsFP7eG+v4FJG97EPOffwr64DIgNYL9K1Drm65Dxoa3AaAPxsCm+dJCbJNvVTIqVIpqpVi00tSkJTMw2zEWhWAjImSMcVrsOl2IrR7ys+fAfuA+aM5JpTI+Dd2oFP4ga2qtVuh1JwlQr1EwoYGYmyNC9ZVvInzwPqQLVVQGbUr9FQzJ4TmE60OwA/uK1nbQwuU6cFKbjkwmWDfgM7/KK+GJdmd7LJ2BW0qwdgvattWjWLiZEODtJhFPISAW55FfXKUWcSmhe32wOKIST57DmmXVKAGvFM+/044alaakXtksHGNC1sMR7ZtR9FTPDFO1qlKWA1VQrEFn4MgBq9XcRPrieBDJsUTSdumRN2nKTpXapOnljHtwJr8DGDufk5hF/Gi7vHyDO85jviBrMp54rsl9ttuwPjgX4TBDvZkVTLht/Mi0/S4HE16tUjPl/pcLR/QowZb5zXl+KUED19Q+Xn68x3TcUGVHa42HH34Yn/rUp/Bnf/ZnuO222656G1JKfOtb38KBAwf2dt/KV7lGnWBzbeQrLaiVOaiLq6g+uw5ooHmiB35+nRSX7zyNyrke1PEDYP0RWKcLefESWJU8N24RAmjBDIKx0DltvCz2n9x2hSHPKYfH+jVKYX0IiMDwRh1MCORraxQyyBjys+cg5ubAuyM62/ZqWilK6OWctleJgVqVppRnGfk56hWwUgqn3NwEtEKwvAj+xAlUvneO1B2twYYZtGBI9tUg58fHFox1UWnlSldMiLHp4Fd3gkqLEOPgYQDebtG0dqPkYEQdaTCDWIOlBYhG3R13VqV2fj0YjhlxoRRUpwvWaoIfPkjGWtMRZyfMT5KFK+2rlmY+mPHGuM4687rztTUyHAtO50AIMk0PR8D6Js0S6/YoG8gMfLUT5Mefy7Sb23Zv2xqfFe8xizEiY8c/lBSdydc3S83a5nEpqzqTJR37Hpg4f8BlyEDZaDzleaeWjcxzTC2BTu7ztKfcqUF5h7imYaQvJUzzv+1BKfDF5tvxys71ww1Vdt7//vfj4x//OD796U+j2Wy6IWHtdhtV0xb8nve8B4cOHXKDzP71v/7XeMMb3oA777wTm5ub+PVf/3U8//zz+Jmf+Zk93TceRWQODmNqS55rQs83kbZCoB2imh1F/3gblUsj8PPrNBYiDOiqZK0DlmXQKwuQJ07CzmXSyXgmC7PzmUBX4s4YKjh0UmqfHiWwoxWgNFQygrCdNlFU+HjMfUSzSaWpKEJw6CB5UJIEDDF0JOi6QZOZNT+2D2KQgg0S2kaSE9mJI7DuELoeb+suyS9eoh96PYj23dCVCHkzQrQxAt/oUfnHhOmNmUlL5RY1tvhe40JQ+kBUaUrM3Rq47XGRFJzIqhWgVoNcXYdot9xsLDJHDyHm5hxRhNaUERQIIEkg5tvQowSi2XRloKv9ICaDLshnZZKwWRCQkdh4s1wYYKDJ72X8TbZzTGc5WEUVSdpKFUNTAVJ1yuMT7O2Tv09RcIpDOv32ma9rrM1fg3E18TubSVJmLmizbr+a+47dxahLE/cTjQaZ1K1CeB19Ni81heJaMTZ3TRXq6bbBth4eV4kbquz8zu/8DjqdDn7kR34EBw4ccF9/+Id/6O5z8uRJnDt3zv2+sbGBn/3Zn8W9996Lv/k3/ya2trbw5S9/GS9/+cv3bL90n5ScYN8KJQq3WzThOxSQVY5kTiA50ETUyZC1IuhWAyoZQSuTkLx/AfK2A7Tw2sV4q+fi+3mjTqblLHcm0TKsz4V2RrnRCsyUrnhcKf6cJGRaNRk9EAKs3SJ1wBprOYdcmUf+9Imi5VoqYDiCigVG++vQldCV0QAYw3EM2ayCv+wOBAenK2dsfQuyGiDojMAG1OGDwZB8RhMkiQzawgxMrbjbtnXxjD3BhFficleA5Tbq2ChYEZWjrElXtFv0+nNpyOAB8iXZjimgMCRrTSM/QiolOt/LDLXgsjBKgzJjIXReDF/VUhqvjrn2sPPQYBRG+x4xs8Vcp5VRcWwAoVMBpxyjyZLV1GNq7ldWdWaWh2wL+kSXnJ4gW2OlL6PguURq67WKwrF92NGxnHh901DuBJu2SNruQIpE2INF1HdgXTtsSdN47tzFkPE67bXSdrPCKzvXDzdU2dlJMNFkoNFv/dZv4bd+67eu0x7RuIi38HchOH4Mcl8b4vwGXV03GwBjkBGDSDSi9RE0Y7TID8l8y9st6OV5qEhA9FPIbz3pyhVqSMm8fGGOyiTdnhveqczVOROgWVdxpQgcBJyHxw53tAuhJTf0owJjwhldEQRAJUL+vacgXkGJ1PpNrwTWBq5lWddiiH6GoKfBugNSQyoxfWhnGXVkRQHY6maxEBvwKIL6gXuRMyA8v0UqyAb5e7SZ/QROc7sAgOUZeCWG7A+cT0fUa4X5uzxF2mJat81kScOYjVmtBrm5CTE3Rz4dW85RCmzfEhGIjQ51PbWakBcuQexbRn7mLIJDBylbqNsDUFKJhiPAmKhhS5CTQXU7UQRK2S+udXs4Ams2ip+rFSJqtoyolOtqsyMfylk5iDkRS/M+0ErB5jrZ8g15H4ouqLFU44ljaPdxltIz+VptNs5Y+cuVI8vjOoTZH7h9siNQ3ClNEndcy6W0acdw+82WFG6/3xjRvkx2jrJdjbuFVx12h1Jp2H5G2GHJaqjGz991VuJuFHzOzvWDvxSZAXn6LMTmgP6pDh+AbtbAVzuIN3JEXYnR/hqGB6tggwS6VUNw5CBdXac5RD9F3ooLSdaacI0x1ZIAO7zTtUeHND5BJaOxriJXNjGmVBYEZtaVKXnZvwlBpGMwJH/HcARx792A1DTxPJVAKIDhiPw4SQ4+NJ1HUUQkqtunbp+Qpqnz7gh2jpK9Ug6OHga/7SjAGbbuqGH1TfuQLxSDNVkQ0P2DgGZxKRpRoZWCaNSduuHygQR3asmOyifWOG7zcIKAzOPVaqF62LTizS2gP4Q+f9GcAwW12SFylaYIjh4mJS8h9US02whuP05GbaWdSVlubppOsu2TwK+ICZOr9dLoNKMMolaTiIvWRHTyYigor8TFcbKPtQNiOXOGZKv+TfO3TI5+GCM55d9L3U7b1JrJkD6gGPBZuiKffG4HRvOqphp3ZSltenIRs9ue1Z1lX9/kaxp7ghn+Kq/E3BwovecsoVHJyEUiWAVuqqq7A7zYfDse1wc3RTfWzYLyPwWLQhoVMF8He/oU/dMNBojPX4J+9d3oHq+hcXKI9PAcgs4I6sAC+HeepYW+24OQ0rUE6yF5QuTmJqlEZnEunity4x8QBhDNJgUQmrEKLM8hjamV11tuICglJ6dUuoojIjqZMR0zGgnAkhS6GlHbOQKwzS4F5ZlZS1AA746gA+qoYvUapTQrQxj6A6dCiLtuh3z6Ocj982DfeArZ8fvBc43BCkd+JkAQBNBbNADVGqjZwhwwIF8Er9VoNpchVlpKqOEI3Ji3WRCST8pe3duFr6Q8WFiDMwBSNNIMskfKjGg0oEcjIhCcQZ6/SOSm14NoNMBqVajhiLxF65tUStI0JJRXq5Anz5h5YSkRKEOC9HA40/9xRZTUHTscUw+I7LJmg1rjs5y6wMxUeAAYS0R222IUQjgxJX3qyI2SuuOOYanLhQl7n0L5GRvtUFJ7nDJkUVbdJk3I9sdS+7dKx5UVO+LBdtDZ+7l9sGSmVOacDBt0nV564jVOYqe3ebzw2GYuL5Hyae+rW5ikemXn+uHWfdfsErzZgFxqgqU52MpSsfjkGfJaiGhLQoUcKuCQ9Qji6TNgi/NAGEB2u+AH90McoJEWrFajlm3AJN9SHgpv1GmMQJa5LivbJu2u5NO0WPCYKV0YY6pOU5cnA4B8KLZDp9kglUCYrBbGwHIFcFPqymiIJNMa2OpCtWh8Azpb9D0gs7Xzu0hJZZ3X3AtZDYGX346wk2K4yFE/r5G2BOTBJSrHmH1XvT4wGIK1mqRQaQVkOZl/bXihuS+v1chUbV/nNFhFQQga4cA5RKMB2etRyvPcHIKX3QV2aD/k+gZkf+AMqIXqwFzytE6IKGqjBPEGzWPj9Rp4rQaxtEiJ0kqTsdh0j42ZTXe6YE5mBEURlBk7gSQllU9rOodpVpx3Mzer6BTTcOnLNlOnPL/KHiOjPuk8K1SNMmksX0mXWsDL52SyhLhNzZpxnpzvx3ZLTfM4la7i7Uy38mPd89t9C8Lp6ky5s2vyOE/Ad0S9OFD2ec306kye91sEWrNdf3lMhyc7JXxBfbL4RSkkSxWagbW2AaD4sIy/dwaVR7+B6PQGwm6K8PtnqO5fiaFrVfAfuA+qVYVeaCE4sA+s3USwvGg+tAOaBL6+CdXrU/nFtIxblQaAIxtOvRBmtpZdAEuZPS59Oc+LTh3zs44EjbxgjCZqByZNdzgEtrrkY4kj8H4ClubIL625chRMSYg16kSgpALvJwg3yOOQN0JEWxpKAFwCeTOiKe+NOlRnC2K+TfthDLR6lBBhcAt7XqgGJqnYLtLbvCIGPK4QKbG5QCagTzSbpMYB0HEpPdh8t3krajgCcgler0EPBlC9HpjNH9LaHR+tFSksQQAITsRkOHSG3GsyTJaUinLZRw0GRPSkUWtsOKA05cnyF0jt0f1hcQxsm/VE99OYOXjivcRtOncUAYwXs8kmj/kOiYQlT2OEYvJ3A1fOst6iUuige55yaU2rcbXpGrFNmfK4qVH2LY7hFiQ5Htcfvow1C9UKat86i87rDqP9vKDFr9yyW6PZWeLEOajDK4DUwNmLwL5FsFxRuSgMgVoVen2DCAPghkFCKwr0U5rKR5WYlJN6DUwpsLxY+PRg4IZRAqT2qDSlrhatKUTQTLLOz54nYsU5EEWQzSqY1jQxO02ha1WwLSr3EIGRplSmoE6cRLB/hQy+jRowBJloKzFgOtRYbwRUIiDg1GqeK2jG0Lk9RiPXSI8v0ziN21bAOyOw3hB6s2NMvrzoIgLc1T+3rdUl7wX5nahM4whQ1QzOlJIMuXkOVqsiOHwIUAr52XPgpTDDSdggOhrNEEJudU35RoExOgc6y6BHCZEiraiMNZEFZI23V/SKlFEqFQEwXUAVyF4f3BAfjcwpSHabYwSmnEkjJbgZF6EdASgSot3TllWacou/vV1xsJCZ2IQJpaj8nLO+jx1g5UzGs2AjHcrHRfZ641PLpxnSr0S0drIA7ibmwONFjbfwd41fzN6kUGC7ChXczWNvdXiyMwVMCOQHFxGcW0fzmS0ypxq1wfprWKsBdeIURfx//3kMf+heVL7fL6ZRAzR2IAzBajUoY5C1XVl2VABbqpMXhHGwfcv0OM6h88RNNhcL82SUtea9NKXp22lGZCgnr4daW6cPdFtyiwRYrij4L6cSEktSUls4p+9RRIvb+ib4gX1mflNExAtwIxLc4ig4JSYrBS0YoIHRcgjNgTxm2Ly9inhTQ3OgcVYgfOLp4srcgEcRld+EIBKkNFSWTyzMxXcxN0elvygiM3EYkKlXa6Begzp5xk2Gn7watCMk+L4l5CdPk4rR6ZphnKbtO8+hOl3wuRZYpUIBfgApOE7xKIhEocqMj1YonpSPL9zG9zJ2P0sybV6SnVulNBjGzZg2bdqRCFnytUyi7LWxCcOlNna6CzdeHQYIVlKISu3p5Q65ScLhSNg4wSiXn8ZGP5QSjLedH9O9ZROU7TanzkKb7M7bCRGaePwLkanj4XGt8J6d6wdfxpoBMUiBXCJZqUOYFF39+vtJYQlDIEnB7jyK0Zvvw/CH7nWPcwm7nAO23GJmHnHTMQSQRwWc0fDJjQ55N/Ic6uRpSs4FyFcjTDuxWRhZQAZmxsyUa9vNlOfg83Ok9ggODEdgqQTTGjzJwGybcpKaXB7zYZ/nVK6qxPR8WlP5xs5ssj4S23o+HIGtdSCfeBpMavBMIWlxVDYVGp/9FsQIGC4yaEE+Q/3gy8Fe9TI6po0GguUlsFqNjNC1KqkpksZGMDP2AigWRR5FQL1K3VFxRI+pVimrZqEFHRCRmXkeF+bAlxbo9QC0feN3GRs1wBnUVhfIc/ClRQQL885bM7noj3WGlLwuxZtgSsdRmeiUy1lhQLEC9n1j7juNaDjVRivqVrGEFKRaufuUwE3QZXl2FeNsLFdorFRaIiljmTkTJS5LpCYNw5OpzO54TYLxIpX6csfXPl+5k2yaX+NK5a2dluM8PDxuSXhlZwqsBya9Yx827gqxfu8RHPxCFZvHq2jiOILnLwJBgOGRNrRgyKscze9v0ciGZhMsDCBX1yACmgCuBgOn5qj+gNqJAWplThJnuNXdHpEXk5WjUxPSl5uclyw3c7CMoVOqooW7VgWCAGo4gqhWyD9UCcGSDFoIqNPnwBfnSZGxPok8p8GhdlJ6IID+kMiEUjQNXXCw4ZAI3nBEpENrBPfcgfyxb0PcdzcWPvJN4A33A3mO5qkMw5UAYU9ROUuDzL8PvBxKUMcX36JBpsgysDCEWJx3k9BZeaEHaBGLIugwoBlRI0PMZAhoDfnd70O025RNlIzGTyTjRGr6A7AwgGi3ofoDN9TVmaMbdTp+YQDdqIL1E6BWBe92XUmnrKRMhvfNVHYmyj1jnU5BTOdPcAATQzmteXiK8dipNjaZemKIqlOrSoF6Tt1xhKkgDswkThcq0HiWDjRzZEOlsnheSxTLSgkr5pVdluiYbU+erzEjeWkfiFRNOa5jD/YExuPFj92ajL1BeTa8sjMNjINdXEd0oQuRAEwC2VIDSZtBRRxq/wJG9x5E1hToHgloQf/es2CV2HkftNJQq+tQgwG00tR2bRQMNRzSYmuHcoIUB90fOhKie30qbaQpBQCa4DM1HFInliE+9FibUWJmF0kFhCFUNQSkhvrGE6QijUaQl9acZwUAkQ4bJpiktPiaUDtWr1F+S5ZRNo/tyGIMmtEiqL73DOTfeADBuU3wo4excU+I2oUcTAGd2yMkSzF6x+rImzHydgSx2oWumGNUq0K3GpS23Gq40omYm3MKmEpGtE+CQQcc8sJFV6ZjppVZdophpQCVTcA4gqUF5BcuwiYPA8a3Yyagu/TfPHdeIpbk5EkSHHz/ClQyQnBg/7YJ3TrLHYHYhnJ5paRKWNKhS0nPajBwZvOySXeMnJQX94m2bvceKCUZj+2XLaHZkEGb31TK7QFAZNooPbBql90uxklLmehMnSo+obw4UmnM0ADGohd4tTqmzNjSYxnbJqKXDc3FH/CSx614DPboNb0Y8nZ8gvL1wy34n3HtsP8MjDPItQ1qk8419v+PDqInTlJy8ndPkweGAfXTQ0RdjcbJvjO8ailpsGTp6p9XSMERzaa7mtVKm64kM+U8z8HqVXdVrLKcTMtaEyEx//Au2t62HtvJ1yaQjlqjc0BJiAubYF3yn7jFWisqxdnU3cUFKgdxTq3YUhXbs/Oashyq26XHaEX5MAGHuO8uiLk5xM+sQrdq0JUQ80/n6B8IoAKG+e8O0T0SQEUMshpADHIkRxeQzVWRLzaAUEA/e5JCELMc4vBBAIC6+wjYncfceVG1CKoSgY2oRV9vbdEojNICXFYJxPIiRLtF86zabSJDppwYLC4CWrv8HMYZkZ8kJbI3HNHXFoUyBgf2A2Y6Oq9Wi+h6Q0S2jSKY8sE8lpxcShy2HWKM820ZOZbkOOJSJk3l+05RlcZCBMtdUrbMZMMuw6AwjHNGpVWAZppZT1Np38teoJ0agl2JLAihspwCNKtVl1rMo6gYz1E+PmUyOtEi7/Zp0tDs1Z1b8xjciq9pBnzr+fWDJzuTKEvw1QhRV4OvdiA3OmAS6D50G8SFDmTMEVzooH4uhTi7TsFz820gy4urfsC1lLvEXHuVW60UV9J5TmnDYUhlKnPl7RQLzp0i4VqfTd4KuCl3SeWSil3CchAgP32GFpdej1rHzYLmShYAdCjAhgkF2tmgOsaoPd0oIi74MMvdbToKIDc3IZda6N/Wwrm/sYi0wTH30a9ARQzRuS3s/7OLiDdoQQ2ePoPgv38T4f98AqIzpO1pRaWxagWIIohGg9rgL6wVp0Rq8FEKMIbgnjsh1zfI15Rsb00Njh4GwgBsaaEIqwtCUsP6QzKIBwGdIxPamK+uk4elPyBFLaesIrXVg9rsFCM9bMrzFLVj2vtoGvGZOmiTbf+AmhaNXyYxY4RjwquzTRUptZ7zdgssiiBWllzqthoOXVClznJKph7riiuV0+z+2TZuQ0Smkb6xx9r9MOnRTIiiM8sQOR5F4FUalVIe/Oheb4n8XVUnXPk4enh4vCTh//snUZb9nz+L6qUU+eElbP2vrwXTQP1Pvg519hzitQTq3AXwVJESIIkIjMn9hhS4wLxyyUEWHUpaaahOlwyyiiZu6zxzXUsQnNQYs1AAdgFj5K0xGTU6y+n+lZjKJFtd8JoJyJubo9IV50SyUiJP6PfBT18kpaRcurJGZiFQ7tKxIXd47gyVoh58BUYHqlABQ3VVA8y0FwfAyXfuw/P/ywqi/9/XUDm1BbXVgzh2GOyu45Dfe5oW11ffg959y84ore84CpZKaGOoFq+4B2xrQM9VCaFDgeD4MajBAPmZs2MLWHBgP3SrTmSsP3DeK7EwRwpVOdPHhji6zBcNFscmOZuM2XyuVQTz5ZlLd7bnzMESm7KvZgpmjWtwqkXpq6zobNtm+bYSeWImVbrs15nsAlO9Ph3L0YhKm1kOrTRkp2MM77xQ92CM4iVyUSZcjuCUvTQT2TrltnnXbWbIi8ryQikzpIlxGivh9pmVwgdL5bjy8dt2XGbhJaQQzIQnfDc19C5LWF7ZmQ3/zjdw9dyyspPliJ67hM6dVVQvZmg+nxDpYBwqFtD334nw1DoN4TQzr8oLDYCSryYkdcB+2HAG0Wi452d2BlJUmgJuM15cerPJqtGqGABq/Cb2OyTl6WCUkBplS1FRWAQOCgGtFC10o4Q8OSbFWY9GlM6rNXSSuBKDVaaKfauAn111+z9c4og3csQbEmd+/rUIewqDwwqDwxKdn34d5He/T11RYQBVDcErMfKFOob7q9CcQS21Mbp7P/gohTpzDnJzE8HiIvK5KtR8ncpsUVC0zFuYBSw4sB+IQshmBahV3THWaerGQLip6FadUfQaea0G2R/QuVKUV4Qso+6vem2MzIwl/E7CmmpNCehyeTNjZarJ24FCLZncXun948pQdv9MV9m0Rd15bIKAjkGakZpoAgbte5GFIW1XcKfejLWUW2Wl1Mk2OStsrPQFFKMpJqdXl0piOs+cEjem4JRSmKcd67HF+zJkxocJGnjCd1NDo7ievKavG/0CbmJ4slNG2STJGfjSAnSni+rFHJVTm8haAfTtR8CiEHwkkSxXiVikWUE+0qwYYpdTcrDs9ZFfWqUPdzszqjzMEyDSkSRkaO6Tn4FVYsrskZIWIZNNY9vA3dBLwJVCaFCkUUUW52nhCsPC32NKZrSvKWyInJaSvo8SCilkJmyvHHCXZ8UE8CQFwgDByYsIuzkaZ3IwqZFXOWQFOP8QB08YUFVY+OoF8myszNF+nTgHdsdRsP/+dUSdHGmLg3dHqJzuoH/3Atbf9SpSb44fQNYIkTdj6FCAr/cgv/ldSJNZBBDJCe68HXp5HtnRJahYOKIGgLrc0pSCGJMiq8hNY48iKh8CUFs9IoVpSsc4MWpXONG0OKX12ZWKZk3tBrCtHGQ9KEkyrghOJP1uI1j28ZPPU1KOHImw27IqkiGsWhaztVgUkapVoWNl318sCgvSUlKZxmZoTWAmeTMqEA8D8pVZpWhyG5y7uWlOpbqcGlFWvy6DqS30Hh4eLxn41vMySu2uvFaj9u2NTVT+27cg8wzpDyyh/+AcFqohZDUAT6j1Ww2HLml3MjRNGf+Otp+1QkAszNO8rcEQLF6Eev4UESFz5auSEYLlJVp07IJkCUpJmRgvI2hSlux9KzHQHxbdVbYUJQSZoc1U80nYhR8AeXrCAEgz9zoAQJuWcUQRIEcIL/UANBBsJRje20LUAaIthmQOEEkIdLZocf36E7AUQexfwuY/egjdIwy3fewU7S+AaCNF2qxi8LIVqJij8fhZJLevQP/1t5CjFEhYbROBbNTJ7MwAFXGwjFQvFobQSVooU1LSObKlxiwvOucGA/AwMJPQMzo+AHl5rDm4vLhPqglTWq6LY3gZWXnCizN5fxtkOTkGws0eS1Pab9tazoKiBMU4wAojr1baGdPpwdqohLKY1yaNN4szMF5MoueG7E1OPncBgIb8uJBBbQZ0TiEiqnQ+SCkyhJ9x+j9SmrxplhDpbLw0doVS4RXhlQ2PmxgKDMwnKF8X+MucSVjfgUlBVkNSacA4tGAIRhqinyC61EPliTPQi/MQS4s016k00oECAE0mSflKXQjg4IoJ9tNmoTblERMMZ03E0Br5hYtUcjIzsLQhLmMLr6CZWywIXEgfstwRCOsPotlUnEplaepKWjS/qjAmO+N0EFAn1ihxPgpmiATsjK5AAAoIV/vIWzGCkQbTQNjTuO13v4/lxxUpTRMLXzZfBVMA00B2dAndexeRf+8psL94HHPfXMdgX4DKxRHy508h+vozY8dS9nqQ6xvmeNI2s1YEzRl4pqDjgEpQEWXxuCnxpfA8CE6zw+w8siAAb7eMPyoq9hkFAZmc2TVGQK4QdlcmNJNlHpfOPRnIVyJCY0RDmZEOk56evIgjmNwH6xNzZmhz3FyXHjdz2+yQWMCRYS0lVJaPlZ3GSB7t4LbXWT52ZdI4eX/XKWYzdUoZSGWU84IsAZs0RXt4zMKLYVyE78a6fvCfDpjIX7AfnsYbEiwtAIxj8Ld+AFvHGGQIgDGkyw3qIAoF1MYm+FwbrNmAaDYdWWFm2KJoNcHiGDyuAEf2g41MQrHWCM5vFh/8rqvFLGZJaTij7bpCyX/AmbsKL8v/AGjha9ZpQdeKxlGYcgWYaTMOabFXo6Tw/OSlhc6QKrsIcWuyFmaR6/Wha1UgoOfPGgHCbg6eArLCMPyB29D8/HeKrjKtSJkRAvzPv4bFvziHximN8OlzqH76r9wpkN9+EnNPDhCcoY4subnpfB/uu9IIjh6GqoZIlmKkLQExzMGkoqycXFKpzbZYM+a65IrwvBIBsn4rU6KTnQ6dL3NeHNEp+2zKP08k9JYXcedrKak0Y96cyc4rjBOpMVO09bGYYzlGQCbfwxZjuTvaeLuMKmkIMMKQxlCEgfOPqVKis0tiNu3y5XTlydJd+ViVy1Hu/V32QJmp7GXSpNPUPfckgXEjUwz5ciTTvm5PeDw8PKbgJf/JsC1oinHwVoOC/WpVwLTDjuY5VAgECZDsq0NFHOmhOchaRIrAfBtqeR647TANkWTcDb/UWUZt360G2FqHAvrmm7QAb2yWRkGEhU/BLHDCeEuckiIVtFKFGVnp4ne7gA5HQLtFs6sy0+4eCKDdJE9KrUbKR7XqruxZqevKdjFBKdhEXRtCyIQoxhRwTi3rIwoh5KmCGEm0nk+hAmDj7hCy2x07vHauV7C4CB1HmP9Pfw20GtsWaPHtZ5CfPE3lvBLs7+w190G3G1BxiLzCoQJADHOIi1uAlMXIDYDOgy4RBbsw2wVWSqjhkFraO1ukgKEgVo50xPF4C7T924xgQWU6ncpGW/pTMfZhmkm5jMmsm7Gfy+nFdrtl0mEICh3QCaVEq6ITTWkaEqtJhdNZ7s5b2aTsFE5rOC4Zk8vqV/lx3Ly/irIVc+qM22+zXXu/qf6k0nkYu32S4EwzLk8/sJf/u4fHDYAPFbx+eEl7diaJjvPBZDn0gWWwnK5+2f4VNE5nGC5FaP9/HwNvGtJQryFfaUFLiWx/Cyri0JyhemmFhnLaeVI5zbbKL61CNJukksQRdK9PQzeNcXhsaGOWm/A+K9drU4IwZZmxtmPuyhOsQlk8Og7AekN6fBybVGTqNNKVEGiQasFGiVM0LKFipluLhWaUhBCm64fKXjyOqWPL5PQgSYBqhOrzm8gX6tCCIxgAlQ0J/gP3gV/cBKIQ+bPP0eG4ZLq41ki5yZ98euw8BIuLyNfWwF53P1SuwNY3SMm57SjkcgtiZQHDpQqqp1PIagBZYQiGGuqxb4MfP0bkZTAAC0I3msPOwnIEwbTu6yRxyoVWemzauQ2+g1bUdm47hqwIMeF52mbavUyJpei0mjARl/N0BJw3ZrLVXSUjV9orbi4TIuX2ExLGxxSMlz9ZiaAwBj0ckaF7MHD7b9UtaAWYgZ5uQnlJuZk8DjQrBE6hcftaJn6W6FmiY0jPNpP3pAdoklxOKx1eyZvjvTvj2Mkx87jusF1Vu3m8x3T4y5sy7IdumoH1hlDPnUbyiiMY3LGA594pEAyB5EdfBbm5id7rjiF/+ln8/9n782BZsuo8HP32zqEqazzzPXfqe5umobvpplsg4NcgG+TXCH4Sklq2+elHWAIRhAYLHJKJQGFka3hWSChkgUwIPfMkh2TJCh640ROWbR7SVVtCkmmMmGnobnq43Xc88zk1V+Ww9/tj7b1zZ1bWGe7Ut++tFXHinFOVlblzZ1autb/1rW+5z65CtNrgYYLSag+DBRdiaQ7yO+4Ar1WJ86OQEnKgQ3IGnS6tvH0/LUuH4lC4rkoXOaavFhjL6J8A1io6USJ4gwERikslxLMVk7KQ9UClzRQHpdOHLHlIamWgWSeez2Aw/k3RaYpySWnQ+FneSxyn+wxjqpgaxXAGMWrnI1TPD8CeOQ9Zr1KQpLlIynipXMzNWJpH8t2vhPPcKsSXvwleq8E9ehjhsVn0DwcQ1RLiqoPWy2aRlDlYIuGEAu6Rw0C/j+T8ipkXKYSaT54iMxrNAGkg8aCc4cRoIUiNSoBx8KBM5eu2o7bSNRn+SsE9pZ18kaigrQZsp7zM53IpolR5mZH+j1LYzqSD9FzqtJF+jzFDQoakNiaav8NrVYhOJyXZWwG1SUdZAVamgWee3zSB5ySFpLHbLSEKUoD514uqwiaWk0+d9sFtOmdTu8Htpg12frD5dvojV27OHAd8pgEASF51BzrHfOy8xAOLGIINgdGMg85bX4XKsx0491A3bykk3DPriBslzP2vC2BnLyIJCBEx3IUoTiuDwghyMCSBN86Aeg28WlErW+LhyMHQVGBpHR3jyDRvRghLm4TGnpy7AFQDCM8hHobjgG13jEKxDHxEtyygd7wKJiWkJvJqcirGEQsARpRPl3GTZo3azvchPdXAVEqwWMAdJmBRAhxdogaeSQJeq8I9dpSCElCLB2dhPnMY9+QJiHoJXmtodIvES29BcnEFozkfwzmOuO6j9mwXic8gPAa/I+AMBMTiLM2TcsLco2o2GYaKlE0pPUPKjeNx3R77nnBdw4sR/T7tJwj2LkW3BQa1c7Z0evQ9o/lDk6qx7GthB0A64NFBjh1o5EUPCwMCxtJ0l05fqmvJfJ8QMZ3iUteJuR6lYbW+T1480KocG0sR5b5j9rxlzj8vFlgwb/b7hcea2tRewDYlKF89u3nTWHY5sXIYurxadLrgALxnVrHwtMTq978I5TWO2YefxM5334aZ//k0EJQht3aAo8tIXnoEGCXYeHkFlcNlVM/NwG2PoInAWuHYOFrGqKWBUNPf7lAfJ5XiSgnIGt5X5eaKkGzSD5ynv6UEqwRw5ucgOYf3uW8CtxwFHAfJxRU4t54AOEM8E4APE4R1juqZBNJ3aUy9Pky/LKtyzKARrktpLj0mPc7hiLbzHPB+CMQCoukhrrpwO6EKJkhvCJ4HVANI34VbrwKdHuKLq5nrIWarYKME4uuPU/uIpUW0TlRRf7QEt5+AzXDwUEAyhspajNJKj4I2l0OWHIitbfBKxfCm4HCqHmMWeTsJCVnw/UzFkc0nkUkCqKog09YAoDlIrIaeauy0EzHusAtvvXFC7273Ke1LpxpVCwUnVUrOI0NjZt0zGidnnkul3vU6dYL3PMPLknEEViIki/k+3EadPlcugYWRCZZkbFVFqbHKJBzj8QBKgsGk+ay+V0isjzMAlqSCNbfmvYI04STNn6lNTdsLoRILwGUHLNNgZ7LdtMsiQ/y0KllMr5/RiET+hkNs/aNb0b6VKAjtf3AbqueHEIcXlTYJqfqWnlnDaM7H4BCwczupK/POkHotxbFp8SA0uqOdFlepKc6pCagOXkq+KQ3nvp8iPFBk25h+pBDkfAHVGZxKqlkUU8uJwIdsVuHcegKiWka0WAOPBNZeU4ffFYjrJfDugEjMHqE7RmdHixBypip1EjXOCjnHoExIT68P9PrgbcVv4YDTD+Fvh5CMgXUGVFUmJVAJEB6qo3+yQefvuXCPLAMA3MV5RG+4lwImh8GZbYIvLyJ68WGMGhyj77oLwwUPYYOB/e1XIMoO3F4EfnEdbIfItCxRaIbnGVK16f+lhBbVxaeAJqI5tNEWkwqy0QQ1/7rJKlNduvOpqEzQki9Jt8zWzbHTQpnmlvZr2nLl6Pb+7N/qn/S3JpxbaUqDCsbUcJaVS9SqpFalcXkuVe4JAdRrEMeWEJ1YBDu8RNfe4XDm58Aqlcz8ZHpX2eerv2c2EdkiJptgLa9lZAVxYwGNhfxMbWo3gk0JylfPbuqnhKmssdVqddqgWsHg1S+GOxAIVoGZJwWiKsPGyytgQkCubVC10k6HtGB2QlQvAEkJEB4nFV4nWy7OPResUlEIj0dOMwxNibRQ6AoEEWSTnZ30Ae9Ysv16tavTMVpDJY6pg3inSwHJxXU6p0oJcBjc7T5YGKP5bIykxMCEpO2BNLDRrSV04KUFCxmj1xiDc3SZWjJw0qqB1AJ1ksq+hYC73oHTHVIVmKneogAqLnFI3yFRQiHgLi0iObmM0YyL0bEmkEiwSgWyXsFoNg2+vG6CyqqAe/IEvGfXwWJFgt3YQjRbBt9owanXwUrUUFSORml6Lo6zAYnmo0g5FmDYzlMq9WpeouaY1DRzHEUobCORD3RyvJZM+kkRpO3X9X7Nb6t6ywQPVtoqX8JuB24Q2UAHiUj7rClyuq5Uc5eXkHS7dJ/WaxDNCoTvgiUSoloCmnXwmSZdPz2HrguuNZ5ygSBXDWwnijLmLB/0jfUJsz+bq3S7qjYNqqY2tRes3bzfXuWIMs0F1f+8UiEUYsbBcNbB4c910DnO0TnO0HqpgAiIUMwOLULMNuAeOwrvyQtY/PwOGs9IlJ/dppTQYAhnbtasYHm9DjbTBEo+UKumQYQqI2c+VT/JITlpp15PV/6MpXwJNX5WCQwJGYwhXltHsr4J0e6ALy9R8HR+DWx9mwjEJQpivHYEf0c5CMXlYc06iRKaUmUV5NQqFPwAlLIqq95gjYDSGhX6DSFJsVkFPDLwIV1uem5BSGA4Ag8TOBGdt2gEVA5fqyKcKcEJBZKyA762hfjcebBBCGco4A0kyn//FJgE6p/8e4i5GuB7kC6l13gQEKoTlCkA8zywZoOuqU5TGaKy0tnxXBqTxYkZM40qRBEhb5JUrinAS7k4u/bCspEHW2AwF1CZNGVeW0cHDwWl45oLpoOBonRYJsgwvylI4tUKXT8VtOp7S45GcJcWgXqN0q2jCHHdg3QY2OnzkJ4DuTBDnwkC8FqVAiOtJWWbRULWpOqiwCUTmOUvQ67EfqLtIxi5pB5Z+0hNTu36tjGJkevULqsv1mVWct3odvMGO0hX42PpB84hLqxg5m/PQHJguBTA6wBJAIhAoP1iapqYnH6OUJ5+nxz/2YtY+IvTgJSIz5yjwGUwpCaLDieSa1Aip9zpQna6FBw0G2C1KjmNoAxWCYigXC6BL86Dzc+B+T747AyS77wDvFEDP7pMxGBBujuG/BxHSijOAV9aJE0c3cW7pyq+YgGvG0EyUPWW70HWKykXiHElQuiRmm6cpOmydgeQAny7Z6rDxEITw5OzSI7MQVbLSOaqkJ4DNowgd9qq6ky1l5CAMxQQFR/DxYBK1SslDBY9+K0Y5QtdoFalDubVMrxOhGA9QnT3SVS/fI6uVywAz0VSTknV/kqHnLBujaG7dSeJapqpUlqMwdHq2Eq8LoPKaLKxlT4RgyHkcKT4VxFdb4UMmdRnEbKT398k4b9cMJTR8pHCKGsDyBJ6LaHCIhJwRqPHDjDUuEW3SwjPUPVYc0l5GgDk0hyShQZkJUC0UEVptQfvW2dIi+hbT4JttQGRQGxtU4pQEZ0z5G2VrjX8KT0+q3Q9Mx9WisvmJI3NV9Ec77ZNPrC8HJuiOy9Ie+FwdlLezqX9PN9ncP3aTfvNlXEEp9nIKrdqTkQYQo5GSFbXsfCVDrZvd3Ho4Qtgd3TgbbmQDOB3vZic3Lefpc+rhpJyRMRk97ZbidMjBAUwvg/eqBPBM4qAUsqTQDVAsrZOQZAqz+YzDQoOahXIoAS2MIfRXcfBRzGSE1TNhH4/DeWtu9xpNqgfVUCKx8l2C2xjB+j00LulCne7j6jpI66qXko6bVUu0Y/rpB3AgzLt2/NoO10C77kUUPiE4DAhAQEktRKQSISzxOtgh5ew8k9egpU3HUH3znmIsgOvFeL0g3Vs3Ouhe7yMpF6GOxDwtvqE0IxGhKzNV+A+twavNYIzjCHnGuDlEqKZMmTJQ/m5bciZGhG4hyE5YCmJz6RSZzKMiH8VhiZto22s/LvwRlFBxmiUBneRasugdXvyQUxRcEMHsTbLBVf2sfQ+1fa6VYdp2aDHmnfcuWPmeTMADAIDAKxUguj3U76XpaDNukOEcyWAA/6ZLeD0OcS6RQeA5OIKZKsDMRiQ4nGnQ/MRxUTmtsQxDWFZixxKpaSdn/NJFW1F/0+Y10K7XERml+s4talN7YVhN+239r+2/ijtAQWkkvZCZgjB7OtPgEngwvcewY/f+b/wyn/wBPpLjJCO++6gh3m5DOy0iMDLOLC1AwBIWi1yJiAOEIQAOl1CSpIEmJ8ltMdz4BxaokCDM8i5GVpl1yqQLkc8X8HoxCy8rQGc7T54GFPDyj45GiTCCOCRM6PeTqxH5dI8KEMemoecrUNyBukwhDUOt58gPDpDTjxKkCzOEBenUadASwdBugdWkqTBj07BqZW8tzMCixI47QF4GMPtRsAoQuvueWzfm8DrSVTO9TCc99F5UQXlu3bgvm4LUYUhnCuBCdD8CAFZrUD6HkZzHuR8E852H+FMCWy7A36UAr3k648hfuo0zXklQHL2HBBF4KpySAqRthxQ1XBSO3POjTPOaBXt4hS1grBud4ECNMXW3Jmwk8L9Zn7HUSadw1zPVAnaLRjy5eoZcb4xQb6c6rLSH2JKewiCusRT2X6sWpWMEDyxCjYIgU4XSacDp9mAMzNDwoNJQi01KhVqyeETqd7Mkesi6XYpPafbjNhzmVdKtsyu5jJaR0XBoz2v+wxALimNlT/WNJ31grIXCqoDXC6qMy09381u3tJzAGIwyHAamEupAzEYqgdxAkiGw/+vL+LpP7oTrbiCl9RWsfGlWxDNVcCEBLv3JeDPXFC6M3GKjHR7afd0peUio5g4ElFEiIjDwG85iqRagpg5BKcTQsxVCRmSEuK5c4hfdQcGSyWUdmLwTh+yWgYbUXuGpEeBlBwNzTk5S4sQS3PgF9YgVtbovI4cQlz14XSGGM5yJPfOg4cSW3eVUT8bY/SyBWzc66D+nET9rA+3FUIu1OCe3YAMfLAwzCo5S4nk9HPEQer14UQxZKMCJAk6L50FT4Dy2hBwOHZewuFvAI3TA4RzAc5/f4xybYSFygAXv7qME8+GuPi6EoQLRNV5VC+E1N9KSERVhotvmMPMMzFGTQfxdx5D9bkO3NYIAqSjI30XDCq90x/Q/Gq9H83HglUKbSkHw6WO7sZZFjkx63WZkKM2XcDtNgcF5OKJ+8wL41kpM6fZJE0g1TsNnKUq0Kpju0wScN8i1efUlTM8NHssAMCYkTKQiphMY+Cp3lKopAK6EaE+QlJ7jzimIGYwTLk5eaFLLa2gkEZDokf6fdu1E7wUkAnAHDXfSVqmbkQM9bEcq0x9t2to735aoj6169ik+rmcz0+t2G7qYAeAcgIpCVTGRamABO5jVTTv6eM/P/1qHBrGGM2V4UQCpQublOJhMeB5kLN1sN4QqFXhSIlka4dSV5wRh6fTJTQCAGv1IOcaSMouwqaLsgClliTgrgvwWhU8FKisjsAHMQkAqpU24myqA6B0B0ol8FYP8cYWBVu1GpAIOO0BpO+isp4guNgngrBfxcbddAuEswJ4liFsuIAAmJAQh2YJaZmpg+90yIm5LhAnqRpyFAGjEKzsA1JiMO9g7vEBorqH0w8uQ3KJpS8Rz+b89wS44zc38fTb5rHZryMYAjxK4O8A9fMJBnMOpMsgPAdn/k8PkIDXASqfXsfoNcuoPbmNaL4K/4nzYHOzYJ4HIYRBl2SSkOaOVql2HMgkBKzVjkwSsDgmp291Nt8VNcj9LzLpsF2c516OV7d1UOPinktByFCYyjfTmiNRMgM5h5/poM64Kv92raozjwIWI5yoKrOKlKuThAJHhXiyZoOQPiEgN7bUnIVwqhUTNEiln6OPT0R6Qp+cWs0EloQwBoT+mFYZlq5OLlDRwVqqcaQakFopvrHARYrM4mVqU7tceyN/K2IZ7b3h1K57u6mDnVPiIXyP93+nZFDAWhlTuwD94Dz54W/h//cPX4bZYIDesSb8ToI4cOAu1OGcvkiOQgiwbUDutMCOHUa8vpkSTBkHMKKAhDOIbhcySeDWKnDbQ7DEh/A5Sqs9CN+FqJTA+z6czoBSLlttyHoVMvCBjTDTv0gbn59DstSAc3adGoiqEnf0B2ARiQcGFx04Wz3IwEfiVeEOAb8lUWpxVDZiCAcUcHAOHrlwV3YgKyWIhSb4To9QK9UNXROfme8Bm9vA/Czmv9FDOOPj2X8CNJd2cPjfOlh5bQM7t1UhfAk8dwG3/lcfznOr6L3qJC6+roL5b5Ejrl2I4AwTsEjA7fmIbhniRR9cQXxhBbUjM9j+jnnMfm0bYqdNWi+NOnh3hPjMOXXtmElRgdEc2+0tpEgJtNJqdXFgmyQeuFsqxXbm+m8LFWKcuoxzx0nTqFKqtJLSYuIcrFKB6PeNSF+m47muLtQtJ3QqUkhIXbUXEyGbSWpHgjg27zHfhwSl0fjiPFAJEC3W4HRHYNtp+bq0O47rKdFVYYlaXao0lQhD8DK1GoEuCMi3j7BJ1rn9ijBMW2PYYoO7WAbxmdpNbZeawnq+qremooJXz25azo42u18RHG4QAe772Ydutwf3/1zFyt8dBVPIh9dVXbZBFUyo10xPK6kFAR0nU47LfBLoY64H99ASsLUDPoiQBC5GMx7xd3Z6hD44HCxMgCiBnK1DNMpIqiUkOzupoq8yrgTinM2uOhCjnldRDARlxGfOkxDcVg/Dk3NI6mUM5xmWP/L3CLYEhAuUNoZwhgI8EhjOOUgCB2K2BrbTxXAxgJippno+UpLzCkMiAEcx5Mo63NMXUfn2OljM0QiGGC0EmHkqwuBoAj5iSF72IhIOlFL3ikRwrotR08HZB1w89TYfz/zTCqK6wIv+o0T/5UfB77sD7kYPc3/+JPDsefDjR+iDWzuQK2vZlBAUP0ojGYpDYxCBJFE8p8RwRy795hlHffa1rRWcjPFWkoT4M2qMRv8GIFRNE4x1pVmBGB91uXeh9XT0taJDqiBAV0qp1h+sVMq0DBEbWxAlD94T58A7QyRb22nwBWTmLpNe4mkKC1KQ9o4S0xSjYYZbRMPNPpzthqE2UiNUdZ2+npNSYYYLNA10bmo7JR56wQU6ANI81uX8TK3QbmpkR1vafJFDhBGQpE0RM+Y44COgt+ygcqFPCMn2DnEspAAbjiAWZ4kQfPYC+NwMfY5ziPMX6CFdCYiUnIRgEZWYixcdQfmZTZQ9l8qnS5RK0qkLNkoguQ/hO2DReGWIRos0b0iORhD9PpxKAFarIjoyA75QhxxEGJycgdeLIXyOI59to/V/fScqF0M4Q0XU9Tg6hzwwAQiXg3eHiG5dQlx1gFXlWDWnQzlMChi5aYkBxnDr7Rfx3UtP4m/6/wc2Xh6ANwcIAwfC5+jdOYuGlFi/x0WwAQyO1lBqJWDSQf3bDngMLP9tC+zpM/Abdci5BthgBMw0AdeBXF0HW5iDOHsBvFED1HVi5RLkcETpwlzlld1J3Djqy3GIl/LZPHJRJB6ogxY9XiXaKLXKtQrInWaTurvrBrIauVItRUyQ0OsTmuVwMO6m3esByDg028mB0nlyHPClBQoQnzkLzM1ArqyR7o6UKdHbngcb0bK5QkoHSP9NPBxqF5EPWDIEai22aAtp5qdSp7SK5nca6EzthWqXSzKeIjsT7aZHdrRJIc2DmQdlyNEIzrEj1OmaNsD2W+9D/6hA/VwMFiUknBdF1NBTSMjZOkaHKhAVH3jRcUqp+B4gBJy5WdrNKIRz7Ijp+swPLcE9t0FO3OVgYQw2isF0ufeQStmTb34b3vlt4PNfozH6PngQEHnV4WC+TxVZ/QGSrW1yEiXq/cRi5Tx2OihtDeHuDOAM6Fxn/9c5eDsDLHytAxbGGM46iAOGxtN9RDUH8WwV/eUSvG5CZeGKFK05H0yRZ2VEq3uZJJC+h4Y/wjF/C8/8FNB/QxdzD5dx+4kVDBdLqJ4dQJZ9gAE8kggu9OAMBWa/BTghMPtkBPG1byHpdiE2t8FGMcTqGsLDDcTzFYjbjwNSQoyGWYfHOY3D9zIdue2+V5rg+7zZHg7ZDnooXSRNt3YtOkld6FWKKrcfKVIUxzTn1C1GNDFboT3M9caCCVYJEJ85D7mxSddYaejIUYhku5WWu1spOTO3WmvIVj9WY2Cem/bDUnMgLXQtQ/C20Tj1mj1W4tZF5vhOrab+ZJnjTm1qB7UXivjg1A5u02AH2VUlcxwivDJGrRRYyuWZ/cRXAE/A3wnB2wOwzVam2oQNIzgjhX64io+xuQ05oDSAuzhPXBuXHvyi3SVNGVfp3ehu1LoLtUiQrK4jfvo0ACB+5llw34d7yzHwmSZYUCYhQt8HK/ngy0uQhxfhzMzAPXEcqASQcw24Wz04622gVILTGpA2UCLBd3qQO23w9RacjQ54P0Tt7AiLf78D6TLUnmmDhzFqz/Xgbw/BNnYguz1Cm3TJsm6H4fv047mI5yv42lPH8Z/O3o/ve+k38e++409Q+uFV/KOlJ3D+H0nwKAHfaKG8AZS3E/CVLZS/+iyqF2IsfGOA0lrPEKDFaIj4yafBF+fhtkZwv3EaYdOndh0ApVe0CQFerxkBRJ0SyTji59MmBTk2SVqmaSupkRs7jeX7qTSAMrvtCfOUSrRKNZpztom7UhjejRZYNMFIrIjSis8jdlqQgwEJEFpaVHo/+bkt7HxuEZhNNZYV9BieXJHAp/ptB6h2s1welFV1mm++i3uSlKc6OVMrsOsh0Hm+FJR/53d+BydPnkS5XMZrXvMafOELX9h1+4ceegh33HEHyuUy7rnnHnz605/OvN/tdvGe97wHx44dQxAEuOuuu/DRj3700gZ3hWz6rbfMrEA178FotkiTCpj9qgu3RarEsteHHAzJMUupgiRguFxFXPMh1jcghSAOCQDUqsQ96HTpN2eEQmzvQJY9sKEq9XVVKqs3oA7Urgd3cYHQoEoF8ZF5DO89AbY4D9RrYI0a5Pwskrk6kgoFHCh5hBTFggIoIUkNudvH6rtegdX7VSdrxtJ2EKMI/moHfLsH91vPga9ug/dDOO0hRMmlhqFLC+j9o7tonnRJNAAZhojufRFQr4GHCUpnfQjJEDghKmyEv7z7v+APHrsfs486iGZKkDttLD2yidpjm5ALMxCtNipffhbOFx4DC2OjT2TMdSGqPtjiPIKnN5Go1JUzM5M6SM+D7A+QbGxmnaMtrpdHJq61FenwFJVMW4EPVY0paQN1f4AzsEqFqu1yn2VaIJClLSwMugOYoFQHIbxRM8KXOk0lBwOI4YhEAy0+UH5eTdrJKp83/2vlZqHuM31Okzg1uaAvExzq1JY6HxHFNG/qnITmOAFp2T3jKTKrzKnVdi99n9pNaddDoAPgedHZ+cQnPoH3vve9+KVf+iV8+ctfxr333os3velNWFtbK9z+c5/7HN72trfhXe96F77yla/gwQcfxIMPPohHH33UbPPe974Xn/nMZ/DHf/zHeOyxx/CzP/uzeM973oM/+7M/u+S5uVybBjuwnCHjEMMRld6ePAoxU7Ue9Azstlsw/03VONOh1gSsXDKkTXR6kA5DUuKIq9TYUYYRZLsDd2mRSsdf83LI5QW4LzoBdtstqq+UgPz2aVIkDiMgisHCBPHmJgC1eo1i8KAMHF0CH0RgsUQ8W8XwtgXIOjUndc6uwn3mAjnH4Yiaco4i43RklYIT4QGNMwnE+RVKh3R7kNUy0OsB61vUNNPzSEAwTiAqPpxeSNU5h5uonm4DroutH7yLqqKkxPY/vRcr9wfYefUyRnNl+NvA8P+zjNVRA/f4LfzcxdcCj9Ww9Lkd+OsUyIjHnoI4cx7im9+GiGLEa+vQ5FmnXjfXx73lGMAY3NUW4qefhbi4atKCuteVu7gA2emSFozjpC0Jii/4lbt5Lsf20+8JaUqLKuASYGNbCUGmqRwdXBDPRZVm6zYOej8qVZtq11hpLSGVmrIiQNvl5OkOxgMFTRhWFVNm7hk3Qpf0WQvtKSr3Z9kO8GNzZKW+MmNgaf+zPGmfcWY4TTroSbrdVDZhalPD9RPoPF/2oQ99CD/+4z+Od77znQaBqVQq+P3f//3C7T/84Q/jzW9+M973vvfhzjvvxK/8yq/gFa94BT7ykY+YbT73uc/hHe94B97whjfg5MmT+Imf+Ance++9eyJGV9OmwY4y00zRc8HmZxHNBhCek31Ynl+Fd7EFyTlpy3BOnc2HI6qyAuD0YjAJDBZd6vbsucQl6Q/Aohi8PYR0qESarW8DcYKk06EHdZ86astaQCXmUCvRconSXwqJ4evb8L/2DPggQvnJdbBWD9hpA+USZBghabWI6zMaAWUfGI4g1jepsgvA8ue74LEEP3bYlGmzYZTyWVQVUPLcOchKCUnVB+8MIWsB3NYQbLOF8//XizCcZcChReCu2zBYYJAOsHUnR/eoh8WvjbDzEkJ2nonL+MyffycqqwA7exFsfRui16fSZM27sR3f6XNg9Zr5Nz5zDuj26B8pIPp9k75iHs27DCnwNOk0Ky2S7zJ+3dheGj96Mx1whxHE+gaSVpsCYyEUUZwb0UcZxdTvSs2pKQm3jyNIYRoAqSaHIaWsdMpMEZEzaE2B2d3J7dSbPpZB3PRxHSsw0kGR9T6bEGBlfqs+ZDqwKlRitgIjHSiJwSAb5ExTWVPDdRjoSHb5PwewMAzxpS99CQ888IB5jXOOBx54AI888kjhZx555JHM9gDwpje9KbP9a1/7WvzZn/0Zzp8/Dykl/uqv/grf/va38T3f8z0HGt+VtJu6GuuN/K1ZrRAh4TSrQJzA+9oz1IZApwHiGNF9t4GPEtK+cenBLNpd1fOHEfpw+iJw6FY4I4n2m16GxhM70IqyScWHs9mFqJYgV9aQdHtwhiO4Rw4Do5AcdlCmgMenS8OqFUJ/2qTLwwchbTsYgj1zFpKT8q0MIwqWPOoCTtosVAIvZ+pgm9vkyOpVJGUX5Ys9rP/DZcx/rQ08fpq0UEoliJ0WtZuIYrB7bsdguYqkxOGtACIowdnqAJ6H0SyQBBJnHlyA1wV4DJTPSyQ+Q38ZcEc+GqeBU0/dgRlvgOoFoH42huwNqEx/goMXUQzuukSQtSxeXYOzdMcYGiKjCLxSAfM9JNstImwrBWLDH7Ftn2jKVTOLgLuvcdiohgpQeEBSBjKMDDpjeCoy7eJuqrO0cCasNFC/P85tYRxJp2OCkHxvLZMSs0UBLbRGCgu5UdVXAKzO5zkSsjpmPmAi7aAJujrmf8ekeAvnzDLu+xCjoTlncA5eLo0pqE/txrE38rfuWXp+3QU6uDzejf48ALTb7czrpVIJpVJpbPuNjQ0kSYJDhw5lXj906BAef/zxwmOsrKwUbr+ysmL+/+3f/m38xE/8BI4dOwbXdcE5x+/93u/hH/7Df3gpp3VFbLq8sUiWAEim3/PAlhchVcsHKSREtwu3M6IUUncAsbYBMRyR40kSEhBMEoBz1B55BsFaBK+XIJoNgHMriGcCSIdDNALAYYZzwmpVoFoBXIcCm1EIXFwHH0RwX/piKltf3zQKzNhpG4VbLTgnoxhscZ5WucMReE2l36IIrKM0e44fwfC2Bay/dgHDeQ+9W2ootQRGixXw2RlKjzgOEXwbdbBaFSyRWL/Pg/AYRrfMgCUJ4qUm4Lk49tdDeG0GyQGvJ3H41Abm/7+PwutLHPr7EIkPQAIv+dc7+Itzd6B3BKj+zbfBlJPZlbeRiLGUBACwMB5zlNSdnVAw3VZB9tL0id0B/LqyonMvQhu08KASBGRBYErKAaRE5DCidJTjZOcuL2YIAA43OlL5zuK2SGHm77wejm5JoXk1uUUDdCCk929VO9oVaRqhycyHrT+kA0Nbm8dOzSXJWBuJvAmrnQoYp551KsVmBzovuAquKTq1q+0WzFyPgc6VtOPHj6PZbJqfD3zgA9f0+L/927+Nz3/+8/izP/szfOlLX8IHP/hBvPvd78Zf/uVfXtNx2HZTIzvazErVV9od1RLAGIm7aX6DFBBlD7wXUsVKvUYl51JJ74chZLcHMRiCl0vwPvdNuHEEZ2YGmGmCJRLuhe2UfNxsgs3PUvqgXgbfaQGOg2RzGzKO4C7OA4Mh4osrcGZmTKNGcedJ8GEM8fXHqOy2qvRxNraMDgs8D2x+FvL8Ctj8HCAAGXiQnGHu0S76R6ivV/2RZyEPzSO+sAL38CFCCeo1SNeBXGxCeg6Of/iruPCT96G/VMLS/w6xc0cFs49J9I6UIB2AR0Dz6RHks2fBa1XUzo3gbXTBRAPSYWi9chmtxxlO/vkgrdzixagGc6lkPOOcbFMNVu3UhpQkcigGaTos7wzTA1wCqnM1kKD9conyva0Yp4qzasVoHYnhiKqnGFcBBjMtFgi1UB+3Gp4yKcGCABgMzPvpEFI0iCmBzMzr1naTnO1YYCkk3ZcqMDFojJrbDLpi9HeSguM6aaq1SMH6Mu2qIzxX+l663tKy16HpoEajPNd9kHO5woDqs2fPnkWj0TAvF6E6ALCwsADHcbC6upp5fXV1FcvLy4WfWV5e3nX7wWCAn//5n8ef/umf4vu+7/sAAC9/+cvx1a9+Fb/5m785lgK7VjZdGuRXjHEMtrEDSAk+0wRvNugB++q70TlRhgjoQR2vb5Js/4DK03mpTCmkcglJr2+4BPHWNuLTZ8C/+C3Ez51F/PSzdKzDS1a/IiC59TDE4XnwoEzcgsEwbYOgndrcLKTrAM+cNeOVSQJW8gkh0g/rKIJkjMQL222w/gDDJaoYczY6kA5DeX0EuUjcJKfZgNhpEeG1PwCTkhCfQYT1H70PUQOQHEhqHgYLDEng4uJ3x4AEnCHgbQ+I1ArAf/Ii8NwF+H/zdQRPbyJYDzH/NcBb70GORmCcmwameWeZX6HbJGUAaTNSIO2GHdJndOm0KcM2ZN3JTvm6NxtVMdVJGvHIkXQd6ktFEgY80+rErmoyxGQlCjmms7MPfpPdlTyjrWNXZWl0SevohFGmy7w5BqN+Xjbak+n6nlNczs/NQS0f0IzdY1fTpsHJ82Zv5G+9/gMd4IpVYzUajczPpGDH93288pWvxMMPP2xeE0Lg4Ycfxv3331/4mfvvvz+zPQCcOnXKbB9FEaIoAufZ763jONTL8HmyKbJjQfD6ISs6XaDdQTIcwV1eAvdcdA+XwSQwWijBPZ0GKaZ5ovrNKgGYxQUwDiEh/RJ+5DAQKlJpFBN/oDOk9FYswObnwAYDes86BiRV34zmfAQKbWKcgTfq1K6h3QGSBLwSINnagaOaMTKFCATn2ogWSE25/uePQiYJksEA/qEliH4ffH6OVvGjEdDqwAnrkC4HDyWO/F2IznEf3WMl9I9KPH2rh1v+m4TfHiIpOZBPPksptkoA2R+klUOtNnwpUSktABdoJSAGgwwyM8l4qUwdzC0V6/jiyviGjoOk1aJu4Y5DpdNWGkcHCpm0yEGczqR00zV0XBpdpNRkDGAI3ZSTK0kEIyPAmQrA09QP3X80J06tRlIDiYAcDMA91/TZMtVOust4LhAyKItVlVXEi8o39hzra2URn5mDse+K3aeO7v20u/xB536MkyNJ4DPZbgFSmHTydWXPN69sajeVvfe978U73vEOfOd3fide/epX49//+3+PXq+Hd77znQCAt7/97Th69KhJhf3Mz/wMXv/61+ODH/wgvu/7vg8f//jH8cUvfhG/+7u/C4ACrde//vV43/vehyAIcOLECXz2s5/FH/3RH+FDH/rQ83ae02Anj+xwDlatQI5Cgvk7XYBx1J7tYufOBvyW0jxRDyNeKhtNmGRrG7xSMVC7LeHP7r0DfKsLceEi+C3HIB0GliSqQzcH36D0mJxrgIUhxPYO3KVFxGvrVGU0GkEuL4CHlmAeZxTohCFVmwQBdVuvVSF3WnRSrgOIBKw7hL++Dcw0EHe7RnUWcQK87MWQz5w3rQjETgvu9hzAAb8r4f/vJzC/fhyPv7uO23/yC3jy978Tpe0E3jOrkK02WKMOOQohNrcpBaVF4pIE4tkzCLq9MZ6OXuUXcXO474MfP0J9rwreE2FoPsd8D+6Rw1R2rrhMGdLr5QoJWudi9n2J+zmQA8ulsOxAQwpBqUCNdCUWb8ZK4xGfJUuITnp9cFGme8q6P00K0CrZJ6VikW5jz2VGEDBbQq5NLx4yrSAyp8is8SZjqbI0qHKynz/AXBa1lEi2tuEePYL4/AUApNUkB8Pi9OmVDjz2s7/9Hq+oam1qL3y7xtqnP/zDP4z19XX84i/+IlZWVnDffffhM5/5jCEhnzlzJoPSvPa1r8XHPvYx/Jt/82/w8z//87j99tvxqU99CnfffbfZ5uMf/zje//7345/9s3+Gra0tnDhxAr/6q7+Kn/qpn7q2J2cZk/JyuN8vPGu322g2m2i1WvgnM+/KOAjebABRjM73vAyNL55Hcu6CKVdly0vYevUSmk/14Jy+iGRziwIa5RxsVdcMpwDA4MFXIfEZgrUIpTNbQLtDCrhBGeL8RWrEWA2Aw4tgsUC0VIe70QNrdxGfvwB3fh5Jqw1++61gG1sQrTYJwAlBOj4q/cNcjxSVPZdUm7tduLffRpVZ3R61nwjKQK9PQRwA3HoM8slnTU8jFpTpPIIyNZNsVMC22jj3T0+gc98IwVMlHPnbIfynViA2tshpzs7Qw9ZxqFKs20PS7hBqEKbd48287PFgdup1sKAMGcdZheQCc+fnIbo96mWmy9M5M+jOWLBjk2lt4u6EMZkWB7n0yiU7l/yx8sFTnkxsjdlwabx0jcIcJ9XOsQIFjdZkyvqtY2vFYRmGk8niu417r21z49ZpXYMI7VYFZaWwxgQNJ4yBq27we5kOlt35eaNjBdA9d01QnqJ5vJRA+Eper6ntarGM8Nf4r2i1WhkezJU07ZeO/79/yVRbXoqJwRBnf/L/eVXH+kK1FyiZ4fLtB5tvz/AHWKkEFgRIOh3q+v2SQ3BuPYGk24NMEoyOzWA4yyA8bgIdgHgmuhpIqu7RTq0G+bqXY/Dgq8BefTeiCkdUYQibLmS1TE45iiBX1kzLB9HugrV6kCUPkgHJbNq5W/SpmSPb2oFQJehiOKJAJ7falYMhRKtN4mlBQChUuwMEARFEAx+QEqxRp58upZ0070MOhkR0HY0gN7eoAsp1sfTVIQ6d8pH4wM6LywBjqYqyw017Ad3Ly52bJZVbPbZ9IiI8CKgCrdMFjhUT5Hilkik55s06iQmWSzR2u8KmQARP93LaK3AZ45hcCSsIdMx49Pjygoj5ubP6X5mO4Opvm0Nji/zxIEiJzCABvqTXN5pE5jjWtbJ7WU3kzux1jlaQaOvoFKW+9nptbAz23xb/bbdx6rmK7SBaldzn7WpVZzHHAS+Vieenvrfcav+xp+1XsmBqLzzbT1fzvX6mVmg3bbADIG0Q6TgUcCzNwJ2fR+XPvw5/c4D4qWdIGND3MZp10XwuhtPJdn12mk2wUgm8UoFTrRgFW3ezj2CVStW9voA7lOCxhGQM/NAS6dnMzSC+6wSwMEsPp1oF0Qxxg9ytHjDbJAJlktAqPIoMCjWWerDOCVBihEoBGZwD/T5QKpGg39IcNQl1OKkocwa+MAfGOUH5pRLNje9jcEsT6PXgX2xDqMNUV2MSOXQciB2l5zAcQbY6ipMjCW3RCISNiuzjIcwqASFUveGY3D+g0yuqqqesKucGA8jhiITxtMCecpYTy853CyjMJtnUzRUrYdeIohVocN+nObNSUpltYAVveuxCEkpjBQL6b3N/qOsgLKFAU2E4IHK5SbfayIuF+GQ4T/bvovPK/51/TRORdcBWhL5Z5z5WgWVvpyyTDtXzp+a00OwAQ4rC++yqVGep74IYUdqMe+7egc4BFgtTm9rUiu2m/Qb919YfZf4XrQ7iRhmoBmj94/vAV7YAAHxhDuKlt6B9woEzEOBdS8PFpVJv1qhRr6wwJIRDSjDFOo9mA3idBF5PAAyAw4A+qQfD85CUXfRfPAdx/z1AnMB/4jziiovhsSb1tvJ9MK38qtIV9moeIHTJBBQglAquCzbTBEYjJJu0ik2WGpAzDeqo3u2Rpo/DwefnEF9YgYxiuIsLEFvbkL0B+q96EaRDvKCt71zE+msEoqZA9YlNRXxWVUKjEPHFVYAxiMGQ1JHjKPuA3udKU6fQxJElItGq87SdUaozFNGKvlwCU1wpbjWDBDAeBCCHGExCd+zXbaLt5XB3CpyW3fySKWHHvFCeXQ6uAxCjdM2JlFy0vSHcDwYUFAUB/WiNHZekFpJuj1qS5ObFLkGfWKVlc3SK0mG7oGdFQZweQ9E1shcnu5mt3DzGCbM5enaQYV+Ha6G3YyFsuhqN+36Kptmm78FpwHMTGLsCP1MrspueoGwcQxzBf/IiohcdQljn2PkHJyCdk6h/7BF0X3sMo3mge8yDt1MzejAyjqj0OU5SXZNOhxzzKEJcceH2IjAhwcMESdkBP7dGAoQA0B+AxwJJmSNq+vDOhIjXNhB8FYTGCEEtINY30oAHME6q0IH4HqFAoxHEyhqV/PrE1XFWd+iBuTWgFJhCZ8A53OUlkwKTSYLkdS+HKHGUtkLIOEZcZuADDpYAUgU2SacDp9mkTuiAKi1PESeT6stV5+x6PZIEjHPw7XZaeg9kUlMZB+a6wGBIaFBCrTd4pZJFdHSwUioBo5GZP5mgmMOj59LJEmMz57GX47HPdyzYShEPUyrvKx0aYSEaIvs5M0d6HIyPpewyTTB95bx9n65HJE1AyJz0MyIMzX0iwyhzDTMppwnXT/PV8oHlGKHZvG7NYR45KuIsWee3HxsLuuxrYb2edLvmb01ONohW0Wf1S1dCdTm3zwzq5npELM8fKzdnhTbl6ryw7Qrp7Ext3KZLBeWUnZkZoFqBd3YT9fMxWrdylLYVZ8ZlOP4XA9TOR2jfXoVz6y3m40m3i/jCxTRtAFAA0e/D2xmBReph7nF47Uh1sKbXxNYOnG6E0n//AtxuDKnKYePVNYhWG6LTpc7qgnoVJZ2OSeEUmnYQnCHpdonr4xNfA+US4ufOUsf1ThfgDHxxAXxxnojLqlUFq1SAV94Fb7OH4Hwf3rfOgJVKCLYSlDYZZh6n5oqsUafmpsMR9WoCTB+xTGpNIwT7SV+5Hik4A6b03l1apH3nmzwa/gej8UupEIqAtJKskn8wTilGzyPkRGvyaORiP0jBflNY+ZSNzcvx/bRhpi3QF1OFn0axRBQbh5txvpqHY3/W4unkg0qNAtrdyXUFnBZv1J+RcXpvGrJzPuCwgjP7XDPtJSYgOCZwnCABkK3MSv/PIEf6fIpSWrblxzCJ1GwhO/rvsUVEwWf3PP4ky30mwwmzjlP4/bYC8l3v1+cj0JkiTlN7AdhNfZfavVNEt0e9pQZDVL52HnOPJ0jKHE69Dq8r4AxjCIehfZKjfc9C4QMnI+TmuuBhDP7MOXjrXbBYQvgcbKZpOBYsKIP3RnCaTTjDGGx5iT66tAg+01RpDR+8WoEYDFNHNWFVyVUllVDBhx6j6HSAbp8qs8ol1TtLEiITlAFdtl0JwBbnAQEkjQA8jAmtWV5E/bEteF1g6X+t0z63d0iI0K7uya2KM+mYffAOmOMQD+jCCqB4Jskty2Cvvsfsy6nVMvMs+30KdoSg8y+VIKLYIG28RM1YZRQT50mbKrPnnmsCCPuacs8lRMRxSG1YWwFCkLGC1bd2asz302o3Kz3EXI8CRcYNsqJ/xlClgiotmt5cIGYhJqZaL9cKIu9obT2f/Tj9vNkBUqZ/1i7zpPWnmOPQPeR65lpronYm3VUQHFyq2QG0CMPiPlsFtt/txiyHNpl53u0jNqqTf+16sSmSdOVsSlC+anZTBzu2Mc8lTRopIba2Uf3zr6P+5Qtgi/OIahyi5MIdJvC6wGC+INApE8nT6Ne4DoTvUoVXM4DTo6aNYq4GrlRb5WCI5PGnwBbn4ez0IVXaQS7OUuBRIdVjVgngVFUaq2C1DaSlxEm3Z8q9CUXglOqpV4nbEUXk6OdmqLN4uwvMNgnS7w+QnD4DZ7sLMAbW7gOMIX78SUjGUD+bQJw5T2McjQyawD2Xyr1tRMBKYwlLIHE3E6Mh6RwplV9eqcC5sIG1V9VJWToIwJoN8IV560MSMihRIBPHQBzDqVXh1OvgjRoRnZV6qOj3adx6PK4V0KgAhPs+yQ0wTimlhDrA74rq5KqYtCM31VAq0AFjFFRbStA24pIJSpBzatrp260cYKfGpOkTlUdzzFSpqjtNHDcoiu5CrgId7vs0Z3kSNQrQm3zaaZcg0Eal7J5W5j6xqsoAQjjGiNJXyNHnFys6NT35AxbCFEfpnFwqqjFpnmz0bC8y+NRuPLvGXc9vJpt+iwC1og4ht3aQbG2bvkOyTuXfM491MFj0IR2Gw5/dRnUtAddBjbYkIW6MUrZFFMNZ2QIqAZKSAzgMTi8CX90G6sT7YZ4Ld3kJ4vxFyJV1wHHgvugk+rfOYHRiltSMpSRVYuXA9HjNb42sNBt0fKQIiS5RRyJo/ztt4uV0uqbNgtjcogAIQLK2bip33LU2pbz6fThzs2BCoHqub3R97H5i0M4cWWeokZPMVO9F/hyOqIqs2wc/sgxICWcIsKPLNK9xTGrRen/VClgUmzYJ+rzhuUi2WxCdDkS3Z8QOdSWMDCOIfh9JtwvmulRRV62AVVS6SzUVZUFAfxeUS5tAU6FD9jlmghEV+Ml+H06zAcaVVo7l0PI6NPb+DerEOJWcF6SYTFClf+xSdhsNkYKQL4V+ae6ZCT70eEYjcz+ZsdiBj0XcHjMbhShSV1b740FgdKykkFSKbc0Xc73s/WShPpdr+VTUGKG+4JzGjr0ffoy+hgcgPZsgdS8U0dr/VbVpsDW1G8Bu+rv4lHgodUZh+tAXYQi2vg14HlUkOQxOPwY7v4bao2vUysAyEcVG1Iz5PmnFbFJFl9sNgUTCWdmC2NgyDzIZxRCbW1QtkyRgOx3Iko/gYh+lMzsGCUjanbTDOjD2EHTqdRWExOR4XS9FL8y5hUCtSts06hBb24jPX6QHa3+Q8heERPLsGcjVdVI9TlSLgnYXvEOcHHdpkUpmA1Li5ZWKKYs3qIEWW8ylM/ZSNBaDASEftQrihTohNZHE9nfMwzl2BHDdDLEUANAhJIrPzSgUhvSCeFAmlEsHLhbfRCNQPAjounkuXVPOCPmqVcFrVSrP7/Yo5VgumbYUxhj1djLaNnZFjw6QVMDBalWITkfpGlkIhzUnOhCxq7Qy5F3dA0sd25zLBGJvRr2Y7S7MByATyMow2tdnMsfOVbEZorJLwZ0h9su00o7ptKTD0/tW7zqx2lfE0e7oS/bEJ/6fCf4Yz5Sg72YaadLjKjzvPGfLStfta5xF+9jttWuRQpqmqa6ZSXn5P1Mrtps+2LHNNCQEtYFINjYJWVjZRuPRLbBIELel2yPxPcsYZ+BBQO8L6jvEfB+iXqZUlJSITi5C3ns75E4brFLJtj1o1CFbHbAwAt9oITzaBHyfUIdJBF9drlpRgoHdnulSbTgfQhJnZTQC4hh8pgnUqoSEgBxNvLEFEcVw5udSZ+e5dO61Gjk9AKxDAotCCS3KOIbsDYj3E1OKRERxJiVgKrOUA91LU8SoN5dLcLrUAyouMcRlBvg+ZK8P9+gROPU6kcqDMjDTAFuYg9jcStNSpRKY71MgaK3itcieKdNXqSzRakN2e9TjC4AcDCBaHTDGqf/YYEioCmNj+8uMXZldkWZEIHUKS6ZaSWYFnwtgmZUWNKlBxum6Jen2NgnZHFfdG/p3hkeVR35y91MGaUrSlie7OnSWK0+39qHRI0hJujK+TwiOfl8vEDgjFDOOaBt1n9hSAnuhOmNNRm2bwHlhjrN7mnU3VCMX2NnBTeaY9mv5/e1Fpi5Cd/aD+EzthWlTzs5Vs2mwA0J3jPOzYHrmOIifeRay3UUyW4GzvgO2vASxvUPEWMtkkhhuiEwSUkQuEU8jrpcwmi+DCYD3RmC1KqQi0Borl8jRMob+XcvoHSkBtQopA+uOtZaTy0Dwo5CcqV4FS0FBD+NwalXTCkOsbVBJe0QrZB6QErLhAym+ijPbBMKI+C4zTQqAuj2IrW3afyLgLMyDuS74PKXbRBTT/qQwKYG8Zosu8S9yIIZMPRgCO22AMbAoQfzio3AiiZ2XMvRfMk+BHWNg5RKSnR1gu0VpOs8lBy0FRLdLXJs4pnSV3ZjVccAVGsWDshFP5PU6mG5k2u1R8BNTqktGEfhMg+Z6MIS7tJhN5+j7Rjn+sdSNDniiGGIwNHwaHVxnrpvF2bCrxShdqNJfDs/wfsy2gNHQGRNxtLYx93peIVojjho9kcII32lOUUYVu+Ac7cDNBFYKaeS+T5/nDE6tRj/1OlX3qXucVyqGW2Tv2z5X+37RpnvSmf/VPAAwwVWRyTgaS7VmNxC5fyd4EyuYKQwkJwUo0xTR1KZ2TWz6TbPMriYSYWgcCgvKcM9tUOl2GILPz6WVHIynD1Mp6UGdKNXaZgPSYXC7Ibx2BPep89SeYaZGTs9+iCcJxGCA3h0L6C8pdMFTkPlolPIZcqtJKSRkPxXxMyt9taJOuj3qch3FhHqEIWSrk5JARyMkvT6cWpVOZ2mBeCs6ZaYQrKTTIYTKccCbdYh2h7ZRgR33fSp1dz1Cmzx3zIk4c7OZiiAz71b1jUaO4rkqxNkLcM9vYutuwBkB7eMu4luWgDCEaFMqy/Q34tTQEUKatIhJk1jtF4Tqik68LELqZBhC9vsQO22I4Si70k8SIkHrsnpOpe48CNKgJJ8eU/eFQd70OctUtdc0LbWqpvQ9WER+5UEA5nmGTM04B1Qll+Zoab6VThNlRBD1vWKlx9ILwNOgqoBbIsIQYjRMScwF1V2ZAKso5SKFSSkK1bxWCgF4LjWuDYnAjySrbKy5VgAyooJ5zk2+L5atW1PY4NMa34FIzwUIi319M1pH+vwnoTr5NNRegQ/bWyZhai9wmxKUr5o9r8HOBz7wAbzqVa9CvV7H0tISHnzwQTzxxBN7fu6hhx7CHXfcgXK5jHvuuQef/vSnr8h4eLkEp1oB9304NQpIeBAgvrgCuC5VWrmUErIfyBp6T1ot84AmB8ThbHYhSi7415+kVEhQhtSpDL0aDwJq6wDA68QAAyoXQ0jODWIjwpBUcPNNIO3VtsWDMOfk+0AYUem66xJiMaTxa46SaQrZ7xOqoixe30Cys2NxOKjsPV5bp3ENhpD9ATld3zMPfZkkpjmldvDOoSXiMRWlDGTaWZvG4sG9sA3GOeROG8lsDLcHhHXA3exSFVXVLgeXNKe1ilETlqNRNpVk8V4y5FydYrIqmcz8KvVqg6Zoi5QmkZVisrkcmYacytHq1ExGKyY3B3QvlDPpKxlHVPruewb5M4l5xrIKyoxlOC2ZwKYAKcmjMYYkPSHoMfOiRRmtPlwmaNO8mgmO23DPXJcCNiEBhbbpdKlupWDPTea88uXYVkCx32DA5u0cWDenANXKXH8bpbNRHhu5KzLN+coFQFey3H5q17cxefk/Uyu25zXY+exnP4t3v/vd+PznP49Tp04hiiJ8z/d8D3q93sTPfO5zn8Pb3vY2vOtd78JXvvIVPPjgg3jwwQfx6KOPXvZ4NJzOalWIAZF2tVCeuLhKK9GREn6zkB0TjOT2hfUtiHMX4a62wGeaFCjMVcE3WwDowcgrFapIiSIKosIElZUY3s4AePwZs5LVx8xD+rxUTrfJPfClkGC+Rw0fHQfx5iZYEFA1ktoPLxHJWI6oakt0exDrmxC9/lj1i96fOU5QRqJ4LjowzKBLiuvBm3XAcyGHo0KIf4xvIiXgOhj9H3dg7Ydfhuq3PfROJlh4NEIyW0H7/hMp0gIA7Q5EQH2yRLsLqTp+2/u2ez7ZZOkxErA1JhlRDzA5GILNzoAvzFGA4bqpg7QQFRMkWM7QaTYNQVrfI1oPqchEv2+0guBafZM4J4QOUGTf9HzAWPq/CqoM4qPOPfMzydmyrGSAedn10uuqA0IdgFi8pNwEZn8DRl9K9PuGMyY10hbFJrjTaNjYOAvGps/P5jBdihWKKO7/wxlUyw6si1Sk7WPmz7FoHu3XCtGzqd04NuXsXDV7Xr8xn/nMZ/BjP/ZjeNnLXoZ7770X/+k//SecOXMGX/rSlyZ+5sMf/jDe/OY3433vex/uvPNO/Mqv/Ape8YpX4CMf+chljeWUeCiF512lsKu4CgDA52YpjRBFSOyOybnVluk/VK1Q8LK8CPgexKFZiHtvR1RzIWfrcE+eIEemAgxNLHZ2Bqg8vgb25Jm0JDi3cqRB8rSCxUqBgHHS52Gkp5J0OuRsHU5oVbebPpTtihLHgVSIBZCmWfIrbC1uyDilHJzZJgU8OT6IbVqwMROg2GZVMdHDnEHUyyhdbAMSSEqAvzDA2is98G+dRmkrSomtrgfUa+BRAlH2U5RBO8scxynTc8lClMyxLSfNOKMmmVEMcfY89RE7fgSyWQdrNCjIEZJSZzbiZvF5RK9Pga/FwzGoU/qBdCqShHhLAPGNopjahqgqLOJMETmc8VwKxiA+PB3PBMc4ibSsg6QxtCKPUBSYXfpudH8sdE2T13mFEDjNW2OcU9Wb4urYwXIRMpU96AHTUEBa0m7PR/4cC45jAtkJxQL265k5tbSR8mmuSRygfNCcHewuZf9Tm9rUCu26Wh60WoR4zM3NTdzmkUcewQMPPJB57U1vehMeeeSRyzr2G/lbqZpKkzdt+XgAYn2DCKxhCqczx8lUFznNZppqAMAOH4JUJerRXICo7kFyhrhpESalIOSDMTjHjwEXVoGyT45A71s/SPN8Aamqw6TIVECJbs+Qkp25WZPaslNLRhiNcYhen1JwiQDiOCXOFqQjeLlkpSxiMJv4qlbnZn44A/dcctpK1XmSk9cQP6QAa9TBtzoIl+pY/OIOFr8aw/1KDXOPCcT3vRhee2TmX8YR0OuDr++Ad/oZvk6mhNuuespVP2WE8ixisI1YsEoFst2FvLAKttNGcu4C2MK8SSFRQJMNWmyHbxDCHPnWnHvOMirRcUzl/1FEwpeOQ6k3ocnRmhOi5p4zCsIKzEa6xgITa7x54vJuAYXtmA2iZ1Ug2WRpEzwrYrjNHePlUjaVaKeYJjn3PZx+UQVXvnx9T+0eG/Ha7XjW99SIOhZtZgVwmUo7e4xJKjY55encRDbl7Fw1u26CHSEEfvZnfxave93rcPfdd0/cbmVlBYcOHcq8dujQIaysrBRuPxqN0G63Mz+TzDxUlMgcHMdo2/BmA/HFFcgwVEGNB16rEelSC6PpruexxUu5sIrwECkmC5+DScD9xmmItXVIoQjNQRlyvono2Cxw5BBVQs3Pja3uCh/cyhnoknHtrHiD+EXJdss4L5vsCSB9INtlzDowyuuZaMelODe6X5ccjbIpjlxDR5ujYjdbLNo3pKAy8O0dyFqA9kkfouyh+tknUNoG2rdwCM8BO33eBAPc94F6DWJ1g+a9gICb5+JkjmmNVf9tOovrcvlalcrtB0OjhMwbNYjVNSPy58w2U12avDigsr3K7u0xZLraRzFkt0dzHyfE/ZKCkByVbqNT4tmAZ8K+6ZfVT6ugQqgwNTVxuKqZblGAlS/DhiITq/SbGAxJN4mRsKdOmQHIBD2XbJpEnP/uqECC+36G3J8Zc24fmaCk4P6xA5ddU1Q6yLE+N7a9QpIKEa5pCuvGtWka66rZdfOtefe7341HH30UH//4x6/ofj/wgQ+g2Wyan+PHj49t80b+VgCqC7KUkMMh4q1tJK1WWuWheSWjEan2ei6hIeo12oHVCBSA3NwCjhwCSwQgAL8VgSWk1ZKpHokTsHYPbmsIFka0ct9pQVptCiY1WVRvZt7Xn0nWqI8VDwKqylLbZj5ni8ipVANgBSS6ikgr/lpBgBhSJZeMI1ql5wMNzV/Qn8mv9G3TZcL1GnF/zq2iejFGXPPAqhUsfLUH4QJJxYHs9sCXl0yTULm+SVpC7S4Fdmos+X3n52xX02NVpes8KFP5ecmH2NymajDFYZJRTFIDjmORhQtSR1p7aC9hPJWC1KX8jFNQwIIy4FqNYJME4MwEkcaZ6tRa7lro3xlSsUWazej+HMRsboodnOcq02wTg4FKxbFMZZve39i4L9HsxUDReyaoLKiyGv9ATkE699745jl0x0odm3HZaekitWmd+iwiZU9talPbt10X35j3vOc9+O///b/jr/7qr3Ds2LFdt11eXsbq6mrmtdXVVSwvLxdu//73vx+tVsv8nD17dmybU+KhtCmoEIY8aZtdwQLXIXVdwDx0mENNOqFQFBmGYIwDq+tw2yOUvn0R0mEQHkNyxwlq/jk/S9B9q01Cg+0e5NoGtYm441awW49leCe7wtnWw1YqZwcoMqyq/hojSCoNFDulYyMygLUidtOWCLZjLCJGm3HE0bgTKUJUrDSJaHWoAmwwQOXZHfSXPES3LePMm6sAA7w2oV5iY0sFhFQWrlEmTf7l5dK4896vg5BpGbFOFSbdHpKNTUKddApQjZv5XhrkaO5HvrImxw+aNB49tyIMiSPGOPhMk+43IYBSmvoRYUiK0wDds0IS2mNzR4r0gDIH5AaV2StA3DOdkgtSxpqBFgQ8zPXoHBQ52Q5KimQKDurkeRCYfewLWdtj/2MpPjZesm8LQurP5L9bhjyu0RurnD8feGYQp6KU9tRuHJsiO1fNntdgR0qJ97znPfjTP/1T/M//+T9x66237vmZ+++/Hw8//HDmtVOnTuH+++8v3L5UKqHRaGR+JhmRlGMi8VoPE2dmhgTstFmpA/0w0g+kpNMhLoWQQFAGq1XBLq4jObYApx8hqjkQPk272Gmn3AqHA8MRVd0kAny7B5xfM2RjE0ztZjmiqxQSSAShOgW8B+N8d3nAyyQBL5WpTD1f2eR6BoLX5dv2WDLQux1Q2b9z49EpBeb7kOdXUFmL0L61DLcPzD6p9u+5pvKLcQZWDcCbDUrBSUqvQa2cTTC2G+9jwlzmV9rM9wkxcT1qRmpI0JJIw7mqmXwZcmZu7CDTQj70deOVCuRgQMFwfwDWrANBAAxHhU7brrAzCJzV8ypDSM4FPHlnrC7G2DFsdK6oUqow/WOhjkWpPTEamq7v3O4uX0A8Lgx+9jBbisGuoJz8gb33nyWFp9//DMlZ3z9WMDSWirIQHvu9TOCZXxwUzfPUbhybBjtXzZ7Xb8273/1u/PEf/zE+9rGPoV6vY2VlBSsrKxjo1SqAt7/97Xj/+99v/v+Zn/kZfOYzn8EHP/hBPP744/jlX/5lfPGLX8R73vOeSxqDTmFp06tNbTwIwLTgnnogxefOj7WL0MZcD6LfJ84MAAxHEK02kpKDwXIAlkjwUIDNzmS7PAuJZGOTyrg3toAwBJufTcehypfTA01OzXDdHkJzPyY8wCdVl9irTttp6oez6QWlt1clxZmWAUC6zT4cSIa06ThIen1ASpS/9hxq50Mc/Z8dsEQianhAJQBqFfCFOfCFeSRb2yaNRMTdtDqN2YHBAZ1EpkRdkX75scNgQRlS9eNijTpV6ikEwTgqxkkzx0pFZK5Pnh+SDzTi2ARLLCgDjCNZaACeV+y07VSNTezV21ljKxQwzJ548YRYwdlEonl+W+vvSY1UNQKY+e4VBVuXUlaeR17YLjo32AW9msTXATJl/rv1fjPBohUg2dpU+rumNi7U3Dlw0D61qU0NwPMc7PyH//Af0Gq18IY3vAGHDx82P5/4xCfMNmfOnMHFixfN/6997WvxsY99DL/7u7+Le++9F5/85CfxqU99aldS815mBzynxEMZIq8YDBCfOw+AHrbu0SMAkJal5xwOr1bSflKDIWmiOA5EyYHwOOp/8U30j5QhN7fgNKhvExFPYyI6u9q5MUppKaE9GYbZFb0U4w9m5VSF0i0pRFQsy3AW7H3kHtx5x8aDwED1IoqJQGtV9IzZJOepH96W8zREZu0Q4hilxy7AWdkCk0Bc5hBnziui7gCIIvBKhUQGVXWWGZvScOG+v3tLgAnjzad2+NFlZPRsalUKTFVvMvUhE0TI0Sg9LiM1ZU1KH+senk/xKE0lGcWmApAPQ9ODrMgmtUXIpBp10LUbf2o39ECn+HLVWoWf32u/RfekdvZXCL2QcZTphWYCil3uycKAZ0LqyCYR2/8XBv2wUNF86iuXBhtDgYqC4qndeDatxrpqdgAPcOVN7qNF61//9V+PvfbWt74Vb33rW8c3vgQ7JR4aQ3cAZB4qvFKhYOTWW4BEwF1aRLy+Ob6d51ID0FKJfh87QqkpxuC1Rig/vYHeG+5CVOXo/j/uQuVcH/KL3wBzSfjPqVYghyMkrRbcagVsboacem+AIhtb6UoBmVjv7fFg5J6bCt35PvFEbEVeoJgjoPk8+kFv/W+vRvdCdvIVPGY86pjMdYEwInS224NkRxGsjYjLUvIht3cgVb8wOaRxmdYTjgNAOSHbue1nZWxfU10ezTgRz3daVJ7f70MKCafZgFzfNMGl6f+lzp+5aVdtM0+79U7KmRgN4S7OQzYqYL0hMpycHBfJOHZTZRWZ62F4OUVjKDq2DkzsAMXmhdlB0h7bTtzvbrbb+wdEN/LtImyZhvx+d/3eWN8Fu2QfUN8FwTOd0TPFBYwDMgJgfUf0fZ7TEjpwADq1G8YuVwX5RlFQfvbZZ3Hq1CmEYYjXv/71lwVmaHteg53rxQw5eZLFMfjyEjWdDMpAow6oSqfMg5dxiDCE4/tgQQBZ8qmL+ZFlRCUXnVcvw+8IlNoCXjcG+9bTgCXipmFtd36eEISQGnAyX61M9xEcGtvDGTDXM5VXpmmi4gswxUvJOATLiRmeAWeQSRr0pIeegO7s4QCFFTAACl3SonoAqqfbYBs7iFstuPUa9bbSzkalfWh3PEP41Mfmnrt7h+uCsbJaFej2iDvlcCo/r9cgt3bAa2USCIxiqgbTZf8VJSgZKAVum2QKmIB0P8d3Dy0B1QDSYWAj6ullro12liqQ0TwgjSzIRF2LXCokgz7k7l97W9ovH3e09nHz6az9BCH7DXgmzI0+t0vdRwY92oOnVHhcpPNqgh5rnvOl+IawnBNrLESKrGOYbaaoztRuIvurv/orvOUtbzF0Ftd18fu///v4kR/5kcva73SpsA+TQgKui3htHbJBVTEmnWXBz7pDNFyXHPSFVdWEM4LTj+AOJEZNB8MZDmeQkOPSpcOKsyCHI2CmQY6106UU2GAIraGyq7Jq3nZLH+XQGnv1a69OcxMx5vQYV32x9MNd83aKCK+58Yw5Yu0sVDCVdDqkBKxSN2xtC3KmQQ0/B8PxYEyTOwuIwiaQO0hbAMYhWm3wmSYFmh2ldeO5dM5zM9D9qUSuFQav12nbPAl1t2MzbkjfPAiIGB5FQJyA90NCt0ajDK9DB6o6XWY7VXtOzf6tNMpuzj7jkItQBljIYt4ZX+79aW+yGxH6EoMl81PEVVPXYGz7XMBqBzr258fSUToQ1b8ncIIyAZKdcrTPeYrs3Pg2JSjjF37hF/DGN74R58+fx+bmJn78x38cP/dzP3fZ+z3wt+cd73gH/uZv/uayD3w9W16ATMZRmrpZ2yIHV69m0A9eKqcIjebBqAor2eqAX9hA5UwHjW93sfD5dfChCnRynBnme9R/K4ohBZU986rqQi5TXsC+bBfoO1P9kYPNCzV91L4yD3itNBymaSLm7gIW2s5Uz3EeMdCbxhE1XlWvM9+DOLIAtrGlypRVa4E4yirvFnErLLTDPsbE4EOSIrVTrYDX60C5RNc8ighla3fBKgEQx2DNhintNxwnpc2TFzO00YCi4+fTW6xcopJy1Y+NBeW01FzNi73/TApQVwApkT6bjJyRUSgyi7OUKYPW700Ifib+X2QTODBjmxWMcU+dIttyHBydQuK+D6deT19XvB7mONn9W+Ms0i3KlIgrhMcu5Tf3RA75MT9aNLBAlHEsnTVFdqZ2E9ijjz6KX/u1X8Phw4cxOzuLf/fv/h3W1tawubl5Wfs9cLDTarXwwAMP4Pbbb8ev/dqv4fz585c1gOvN3sjfWkxgdBw4zSbi1TWg26MUikJAuO8TkTgISAFYKcQyx4HY3jGEY77VARxGBNvHTxMClDPR7xMqNArJ0TFGZc1hRMiO6gq+p8S9toLVK3OcVDxQpyJyPJWxtga51aZMEhMAaofEPReQcnwFazvIooe3nTaykQcAbKZJaNHRZfDz69SEczgicrIUhpRruCmTAkFr/6ZXka4i0wGBbnzKuNFRYo0a8a50sFsuUSUe55DbLch+n9JaNkHb4RQIuZ4Jgs25aYQpX3WkAhdDfE8SJK0WBVW+BzCG+OJKSlLPBYa66s5W0k6nPxdEac7IpGBYisw9YdCGS0Vwnk/LpxBVo1ERhkg6nTSw0/dyQSBlCPu5wMvm6wDWvaWOq18z7+VQH/vvPGpkFheTlLCndkMaAy6v6/nzfQJXwNrtNhYWFsz/lUoFQRCYdlKXagfm7HzqU5/C+vo6/vN//s/4wz/8Q/zSL/0SHnjgAbzrXe/CD/7gD8Lz9umEr1PThGVa4aUBQPzMswAA96UvhuQcLIzg3nYr4qdPZzgszPfJAUsSu2Ml1fF6cRZMCDjPrkC6rkFpnHqdkABLBVdsblPTyZkGZE8pLZsyVaUjo2H0g5TjMq2eG2X/z2xireIL0lD5IInGADN2mFL3Ao0d8zlkA0rreJqLYbRLFpvgvgdx+iy1aNjaMQ6MgiqOpNulOWfj2iy2GaTC5abTtv4M930KUhJB6JqUFGQMR5D9AcAYRKdrUlNic4vGPxoBUUyBnuOkWj9JApmEZlzcY9m5l2lQZwILhUIkdkosjg2y4x47SpWB1pzq+SpU2c3/beYg57iLuC96nxqRKEodXQ73Zi+7WvsF9SejwIOa/abpxvTYBuGZdE9Zc2IH93nRwQyyY3afRXHySsn2PSHFlK8ztZvP/vzP/xzNZtP8L4TAww8/jEcffdS89gM/8AMH2uclEZQXFxfx3ve+F+9973vx5S9/GX/wB3+AH/3RH0WtVsOP/MiP4Kd/+qdx++23X8qurx8reLi4Rw5DVEvo3lpH5eIQ7lYPTrMJoQISGUeQg4GBx02jw1IJLI7BdrrEwZASYPRg480G0B+AA0YADlKAnbgF4tmz5kHMXI9aVHS7Bz+XvONSr9nVWCkvYfL52w7ZiBwySxW4yDHkOCPkIJJx56lXsSo15dTrkHEMfm4N4siSIQfr8TLOKH01GhG3xZScT56G/EocQIqkOJyuC2cUrEQRMBSQCqUB48YxpulLFXCpKjCm1ap10IMUKRCRxRfKoQ06Ncgcx1xf5qiGpsMRZLsLfohWOjwIsqmsSaY5TJqobZGaC7knlqO3EZ0MWdzSicncU1cS4bEDNzvgmfR3/uO6zHy34EAKMMcnvSTVZ2wshWQRwO2xjQWPVqpp1yoq67cJYHLbZNKLVzHYm9p1bJdbPn6DlJ6/4x3vGHvtJ3/yJ83fjDEkB9Tduqyn1MWLF3Hq1CmcOnUKjuPge7/3e/GNb3wDd911F37rt37rcnb9vBpzHLBSqTAlwjfbqJwfgIUJ4rmqEf7LOPxYVRCp1+Jnn0O4VMfojsOI7j4JMAZWCVL4u+Rnyr1FGCJ57NvE+9ArRYdTZc8lOpaxVJUWtitYsReuZK3tmOdmScwaiVGvZXg9ufGOwfVqG6daScem0oEAEG9sgXf6lFZi1heZcaPvY/gSe938MhVFNC+pSqq0wzyJBzLOKX3mOEoriY5no2n2ql0miSEQI46NwrMRBrTSGToQYVYlnh6bJhyLiHSXZBwTdycm1MwOdOxUZkYoUOv8WKX4hc7b/mxRqtFC0PT/mYBNB882/8YmAF+KTUqR7YJWGdMBQxHHBtn5MkGtOj/T+02fp61wXTQ2KzgHrPvaIqSPpZDznDH7/0lB1TTgublsSlCGEGLPn4MGOsAlBDtRFOFP/uRP8Ja3vAUnTpzAQw89hJ/92Z/FhQsX8Id/+If4y7/8S/yX//Jf8G//7b898GCuB9OaO2IwNA4rY54HpzdC92QVLBEQM1XjQG1+BlQwwTwXTq0GtxMiKTvwvvwkWKMO2R8QD8dxCLEYqmaijIOXynCXFsF9Pw0cVHqF+/7++TraihzcAdNf+sGsO7znH/KMM/BSeby0u+hhnZtT7rnp+YMCkGRnB8x14Z44TqmkMMrtIu0/tJtqbaHTlGnfK4Ni9PsAY4YMzkqlVNAvjiFHI+pFpcT+9BjMbynS98NQtT8oZ+bI1iTKozvawWnuDeMMrFwCb9Qp2OEcydZO9lTsPlIqMNPOO6NxtFvgkedQFQQv9hyPBbH5wOZSnbTNQdrteu5mOdIzy7XVsINxMRhAqCa2AMaUxm1EbGyMmpBsXUtTyVVAYraRsuxws0jrnvZC4EhNbWpXyGxC8tmzZ/GLv/iL+Lmf+zn87d/+7SXt78BprMOHD0MIgbe97W34whe+gPvuu29sm+/+7u/GzMzMJQ3oujCVapG5SinZH4B5LkYn5+BEElHdR/lcC6xRpw7pVvm2GLbgNOqmn5FzdhWVbhM7b7kbpe0E/l9+GcnrXg5nGMNxONDppBwhh0OOQtJ46RERV4yGpqkh4wzyUmHugjTKfiytzElXz0bAjzNK00hLe0U7QcvZ2mW4AEzqhAUBZK+fQVeoxDoG6/UoTaj6TxnH4rqAHVgdcC7yZehSSLA4pmPFMRK1bx1QsVIJGI0KUxXMVY1Aozjlb3mMepwFSl3ZcWi8GhGxjluIAjgOGOMkRSAEWNODMz9LBPmc2VwPExzn0Alb42UMXcsjOgXzqdNZmetXVLVX8NmDWiaAzY9pH/e9VqrmtSpxs6zAT5+7U6+naCRnYG45FYPMEZonnZeNYKYBLcwYM+lB24rmPJ+iK0rbTVGeG98uF525AZCdb3zjG/j+7/9+nD17Frfffjs+/vGP481vfjN6vR445/jQhz6ET37yk3jwwQcPtN8DLxV+67d+CxcuXMDv/M7vFAY6ADAzM4PTp08fdNfXhVEzUNWrJ4ozJarM95Asz8LrhGD6IecqR27zQHyPYPFEtTQAiNy6so7GE20Ez+3AOXYE7t8/DggAQTnbBFGTZFXFF3SJstL7MUjLpdglPDA1auDMzUAKqhDTqbVM+TTjxEGyj2M9tO1y84y8vua3RDEFBonqEB6UAdcFr9fSCjJGVVSQMoNmXMr5slKJStqV8B8cB0iy6ArtQlLwpQITd2HOODqn2TCVaRrhYRqpksI0JDWNY9W102M32iy2U1fpmKTVpn+PHKK0aE7HRc+pqQi00yvIplb0e0X9qfKVQfq66KotO5WVUWLeB2q3L8s5/gwqlUea9nH/6iDGpIALAoVEVVTyUjklw+vzslNNk+QJbO6TNX5bHXlsrotQnPzYCjluU7tZ7LIqsdTPC91+7ud+Dvfccw/+5m/+Bm94wxvwlre8Bd/3fd+HVquF7e1t/ORP/iR+/dd//cD7PfA36Ud/9EdRLhf34LmhzE4r3HqMiMitDpyLWxjNlcBHAqXzbbBYgFWC7IMvUQTOSgA206SHripPB2OQjFHfLMaAr3wL2NrJcDHEiHpqycGAHsBRDF4uqXYOFl/iWkyDRgR8j7hIUpoO6EyNCQCcaoUEALXmjg3pF/AaAJhSbxmG4EGZfubnqBM2Z9QWIowg+wMzP4wzVUW1j0BnN5MCjHP6cahhqFRpKD3mTMpJzbe7OA/R65tAGLHF43FdSuXpa8m4SW1lzlunm3RXcjtwYFZVX7lEhOc4AepVyLnGePlzHNG9khe303wgXSk0KUjI3UtZ5C2nv6SDnj3Ivwe23bgxl2BmjsIow1vKH8Pmb+kFTn48+WuTGWMuQKWX06Bw4oIkf75F51kU6E1tajeB/f3f/z1+9Vd/Fa973evwm7/5m7hw4QJ++qd/GpxzcM7xL/7Fv8Djjz9+4P1Olw0Fdko8BK6rdADIJ06D1apg5RKS8xdR2hqhtN4HkxLSc4wGi9Nspg/R0ZBKlpVDpTSMAD+7CjYYQXR7xtGaPlvqoefU64AQ4DNNuC++ld4qlQiez+vfXEXT5899HzwIIAdDCkzKJQo6uj1DdGb1mvmco9Ad5rmZbu1GUVYRcbWjZ75PqsSVAHK+SXylZgMQAjKOIQZD+oznmqo0bXs6311MB01aNLJopW4dyKA/Ot0mk4S6rMeR4TIxXyEtaozM9Qz3SgdQJgBhPNug1Ep/0CHVeUURpOdAlH04MzMZFJC5hAAatChHet2XAGXOsZoAzOJqjbWWuFSbhFYUIRyXmKbVwV7S7RJ6l9duyhHDocjimeueH+Ok79wExCnDz7L3MYlDtV/OzhTpubFtSlDG1tYWlpeXAQC1Wg3VahWzs7Pm/dnZWXQ6nQPvd9oba4KJMMxI5stWmwKOWg3s/CYgJcTCDJgQhPg0m2AlH+6hJYjtHUhG+i9ur2YIyQCASoDo+Bw8KdB5xRFUn+3AvbBhuBjM9UiYcHuHHOtgCN6ogTEOoQiWe5bWXgGzUQEWBETQHY6oaoqxFNkAiJ/CLei/UQPr9sBcl6qToKdRmlQQb9Qgt1smcJGDISAk5DNngXKJ+CphRKXXqsElGKeqtH7f6NdczjyI0dDoAuVTPnYKS4vQAYDY3IJMEjizTSTbLTNPMo5Nywhd3ZNHbZjjgHmlDBcscy01kTVJACHBqxWg5FP6MpHgowhsfhZMo4KxSo1xBth+VQcKKrjKC93taRbHSo97YvBx0GuQR0muwn1M11JxaDTPCiARyVw1nh6DjJW8A7ea0ebHXfSatqJAJjc3e0kjFM5lnsMzDXZubJtydgAAjLFd/78UmwY7E8zuhi6TxJBPxWAAt0YphWgugL/RA59pQHS6ikgr4MzNQqxv0OpyfRPOLUeBXt/wN9ydAWQtQP0rK4gPz4AdmgfWNtLgynUyD2RnZgaolhREbqEPecd8qSmdvNmcBc4go7TMXPNTuE86JYRQuZCtNlWWRRFYnMA5dgRSBWxQJdvMczMOndeqkKMRBUVxDKGidcY5CS8y1TeMcfCAmm4iQaqlYs/DpdqklIJx+AIsCAy52DjCKKbAz3GQtDsU6FiBqF2VlqaDkpTDY8rNi4YkwbiA6HbhlHxgtgnW6gBBGclsDQ7nEBcuEtoWxWAOFN/I2rc67pgw4F5zlUtbZdon2AHKpQQr9vGvROC0j8/ntZWKGsHqYJaCU0zuij5pDicFOXbaMi+NsBuBOb9v+/eE85za1G4k+7Ef+zGUlCDvcDjET/3UT6FaJVX7kbWAPohNg519mF6h69YEcB2wMKZy8m9Q7pD7PhFTBwPE6xtG6A4AxMVVItsCwGBAVT+HZsFU9VXyjSegya1SyGzFDaO+UMnqunqoEv+Ae9m+Wpcc6Ozy4NTnJMMQSb8PXqlQSb7vg1UDE8DwmaZBrpjvI1nbgLO8RFVEjgP38CHIThcyjg0nRHZ74Avzqb6Qza1wHCr3Vq8xz6X2DEqBWL9ml6tfSTMpIZ1qGwzgVCtIlHgk932TWnOqFZiWEw6H7EeZlJXtrKTgmeBhIudIbcvLJUp/DobUnwuA9Cgl6szMAFKm+7BJvfo88ojMfgMdm9Ccr9zS212qs80jFHYAUbT/gxxrlwBKL1i47xMnzNaCchzzfSWULttgNrOY2CvgsebOBDQFlWWZ1yfZJDRnGujcsHa5JOMbgaCcFxQs6nb+9re//cD7nQY7+zVGCrpOdRbxc2fh3nE7wAH35Amg30e8tp4GQ0CGlMoYo1RQt0ctJOKEqms2toFZilZN5Yg6lv4spIDYaWW0XUju3jfb7Lk63PW0ctC6Jsi6HgVZVm5UhhGV0zuqMsxRDtUjFEb2++D1Oni1ArnTSpGeKCLuku+DJwlYpQKm0liQEjh+BOzsBQpyAMjhCHxhDmi1CbnwfUpn6fJqS+L/ij34LQemWyokvT6lo4QEA8CDMkS/DxGGcJeXkKytUwCkV/Ay2zW7SMgvU9ZcoLOTvikI2Wq1wYYjSmkeWoAoqSq4WhUYDCEi5Zjzqaxd0il7nb85/n62O4jtQpKe+P8lHkujMyYFqfej9KAAAHFE6JjWyfJ9MLWd0PcXihcSdok/vcAz3yVbeTofIE0s/88HNpNQnSmyc+PaVEEZf/AHf3BV9jtNAO/TGGdg9RqSrW16odOD5ByiWTVNQm2dHf0w4pUKOfSYyLCaCMtXthC/5BjcZy7QdkGgOAOMxOjsh5mbTf/sWXZ+gLx+UXmsScUMhtm0RhwR3ySKkbTaimwrAM8Dm2mSA3Y4paXCEMxVJG/VCBWMgc80aV/tLuRohKTXB+v0SMRvpJy65wJRZJAbGYZGDwVS0P9XKmVnnXdm3nJpDzEcUXWYrtLb2gHzfTi1KniJpAOESm1l0j77Jd0WvZ6oFJruh9YbgMUCyUyFUCRJFWVGWdrm2qhj7ZvAfTnoyUHNRnJ2u1cvg5CbEQuEQil1ub/vETLpemnlnB6PS5wdQzAv+q7JYp0qu/ItI+yo96/OaazFxm5IUUHFV+bvKYfnxrIpQfmq2fSbsk+TSQJwDvf22+AuLlAKIRZgiiTKSn6qLgzAPbRk/haDAUSnC1atkNPijAIAAJibgTs3CzEcEbxeKlHpeubg9HDMaH7kpef1e5dKGM2ZCENyCrYGi0vdt4XuJ6S0SjAYEtoDmE7uvK4QIM+lruFSknaQ0tVhqi+XM9sERiPEW9sqyCLHLlXzS82TspWBhaVZc0XMciqmYiyK4TQbJk0FwFTdGUsSJJ0O8T2EIORnMMiILe7r2BPORSYJ9egCpQchBJxeCOGrqiLPA1xXBWHpsQrVjq9GJc9B95fn+eSqn8Y0h/ZC7vbh8BlnFOiUSuDNRqqKDYA3auCVCmlI1WomfcqDYGwObY2oorHbqKAdzGUENnfjORWdc/789f92oDhFePZv08Dwprbp1Z9gmpwMIE0vVQLE8zVgpgnEMZy1bXIyvgc5CqlKSJcl9wcKhYjSXk+MUUl1FAO9PpydAZUUq1SR/uxYNUgOzaGAKOt4dTntFX34JSLzsGeeS+eoy8ltTkciSNek14eUAqgGQFA2VVUAiIS8tUOVXd0enFoNyXYLot2FUV4WguaIsexD3UYDpKXUfCXNRuP0S3aXd5EKDYrRMKufE8cQ/T6NUyNQRaXsRQ/cXZw28zzSa6pWIJt1QAB8EAPdvuFEyShCRn9pEpp0pR3jfvaXd/T2/7mxZXR8JiEaRcdX3JgigUZ7PuRwRM0/k4SQRJUa1RICYIoHx9IS/iLyv93rrHCM9vhz921hkHI5acGpA780Kwpai7a5GouE3YY1FRW8ajb9puxmjIMHAXiNNGSS02eQBC7CI01ABS8sUq0AhGoNYMrViUTqHFokZKfbo/5LHqEbYnsHrD8AW9mAiGK4J46DL8ynpdrW6lcoyXsNk8swyvAQ7BL5K3bqqtUA9/00CBuOwIPAEHVlHFEAtNOiNJ1umKkch2x1KPCR6hsYxaY/Ea2wlZhgjXhLTq1GSJDvm5Jho42Scy42p+KyTQc5qreZ0OX+JSIoC90GAlCB2PjXxg5QxWBg1J5ty5zDPtALQgUYzWu5BCYleH8EFiWIt7apt1MYQje0NM6ZZRWq9xU47Mcu5bN5R1+0vzGu0gQS826HsaqubG0nLcYpFQoHKc09K0eEOIphWp7OVdpQSyvkU046yC5sgmqfS0GAOfF7uhdCtZsj3u1zUyMruv/zPKj8/8+XTdNYV82m35JdzKlWwGtVsGbdVGu4/Qj9wz7i4wsQM3VIzoFRSH2cVINB7vtIul3IwRDxeeLkGA7B9g512S6VIHfaQL0Gd2EOEAmS44sZVIE+qAIajRao/dhkaL3/K4102PL5RmE2ny7RqadOF6zkExKhlI9ZtQJWLlMqJka3qLkAAOiHSURBVEmQdHsUsAVBWo4bRhDdnimjBgA5GGQ7vBc5h6sA3xs13SSh5qw7bTjzswYxkWEExixlaHtIeUdmp2rsFMc+x22ctpSkYcQYtSbp9cHOXgQUp0pozR1bQdkKqvKq1WZMB12x7oVO7deKkKbd9s34OGI5YfwGpVE8HP0dcefniVxfq6XtW4YjRfR3jICoHI2y97e65w0HiqVd7AudZdF9aqNMRd/P/cxl0T2zV4pvaqlNSgvarxUhPdP5vaFsGuzsZkyJ5fk++NwMAMBZ2YbkDKLkYLRcRXSoBuiKGNWjKJPesB5mydY2rfpbbbBKQBVZYYTkxGHAdRHXPDDdW8qMgatdSbNiZ46TlmzDCkou61wnPJilSInXOiVlB2COQ+Rd14Xs9YE4oS7dngs5U4PY2IQYDImIrPkwg4FJ9TBfVX0ptAhhRGktS4XYnL8eqprnA3d/383UOYkoNn3NIAWdk3qfcYak1aYgJL9a1NdJIyx2WsU+xh78ksz+FKkbUUQpq602pQa99LxtNWl9T+jy/oyast7v+EH3DmCKHvyXixAV7C+TqrXK5ife27n55KUyVfxpJHI0JL6XJD6VbgciBgMT4CTdrgli9P1tiPF2k087aM210dgVsZrkMIvmbz9pqfz7U4d8cJsU2BQhPNc6qLzcFNYlIju/8zu/g5MnT6JcLuM1r3kNvvCFL+y6/UMPPYQ77rgD5XIZ99xzDz796U+PbfPYY4/hB37gB9BsNlGtVvGqV70KZ86cubQBXgGbBju7mUq/yI0tgDG4h5cRnzkPHkm0T5RQWuuhf8iHPDRP6r+DAVVyWNU5RSiAsAi4GI0gv/gNhMfn4LZCiM0t6KoRs6oFjPMyTsCG16/El1HxHnZ92OYcj3NoyayEZRgSl6hcAqoVRCcWAZE6DO65ps0CP3KYUgcqcEu6PRPASZUyyjhxIBM8MN+juc0788sxG7FRzl8KmelzZQIa1atsklOzW41MtAkkVXOO9j6kpCBwcxtydR3iGJHfebmUFXvU+7DmJRNA2f/b49jNIRcFJvZnLjW1ZR/DvCzNGMfI1fb2Oth2vez5cUK48oGxaLVJjTtJ4DSblKpyXfBqJdXd0empfLXjbnOwn/PbzSalTyYFqPb215hLcsNZUaBjv643Uwura2bPQxrrE5/4BN773vfil37pl/DlL38Z9957L970pjdhbW2tcPvPfe5zeNvb3oZ3vetd+MpXvoIHH3wQDz74IB599FGzzdNPP43v+q7vwh133IG//uu/xte//nX8wi/8wvPaV3P6bdnNXJfKqh0H8S1L6N93HJACtdM9NJ4bQQQ+mACi+QrpwjiOyvmrdI9KO3GVtjHGOLVH8FzI4Qju4gL85zbBnzlHX65aDcz14C4vFSq5UtdvMe64djPGUxKzelBmKriArGgaML6qth4MPAioZ9NolAYyJfpJ5upweiHYQPWN8lywSgXyZS8mzZxGhVKEnkvdp9XK2/SpkoJK9C3eidb+4ZUKRL+ftrPIzcGeAdue00RjoKar5HSdeh28XMo27syV7NvBRobnsx8naQUiOiCEkNQvTAd9rgs+0wCrBAhny6rLOTMcsXxwmD+n9PDWnEmrd1aR07Uh/qJV7uVC/fY+rVRDIcm64HiGp6P4ZTowtUv/TWprNDTCj6xUAq9WkLRaNB+ulwZIMpVeuGQex35TU/tJT+32dwEvaGq72KQAseC1TCNXdx/95V7A9qEPfQg//uM/jne+852466678NGPfhSVSgW///u/X7j9hz/8Ybz5zW/G+973Ptx55534lV/5FbziFa/ARz7yEbPNv/7X/xrf+73fi9/4jd/Ad3zHd+C2227DD/zAD2Bpaalwn9fCpsHOBDslHkKys4Pk4grEsUNw19tISsopffMp+M9uwj29Aq+TYLDoQ6vZIiHCsq7M0VoeYyJi+gHlOETIDag6hB07TNU1QRnxxRXzEd0hXFcFYZL67iSTIptisYME+6FpOSBDzsw9DLjngjfqNF7fp6CwGgDlEkSzAiYEeG9EwoKg4IyVfPDeCLxeA2sTsVY7dqdWo/RYko5ROzyTtgNMmsZuy5DXCbrkbvAqMNVNJLnvG2Qu6faoRLlUMvOoBetMoGLNqU1e3ZOnkfubgt1qqrjNGFCpACUPcmEG4R3HwGMBvrwEpvqRGa7JhP4x+aDQRk3spqT2XOTnZszxX24aK3+cgsDJBLlFKJlMK/LMtQCyWleWGY5bFBPxPIzgzs/DmW1Cc3IKA+dLCST285midNSkQHgC6jDxtamN2x6Bud1I10YL99VI90raNUZ2wjDEl770JTzwwAPmNc45HnjgATzyyCOFn3nkkUcy2wPAm970JrO9EAL/43/8D7zkJS/Bm970JiwtLeE1r3kNPvWpTx1scFfYpt+UPUwThpOFOiQH3Be/KF1BzjUQNunLMLzrKOTtt5ADUZUcBv7MQ6OKayLaXdKU6fXBen3whTkkDeIdsIU56v6tHtJa5ZVgdm54BQdCMqxVayYoyDs66/9MmsB+WDgOZByDLy2ALy9RdZrngoUxIKXqJUXHSLpdYKYB0ShDLs5CXFwlXpPrwqlVIYXqOTVBwM088BmD6PdTLkUB4deQSfdjBZC1UBVjuhGsDlaSVtukPfSxNWpl/rfJwHukA3e9bkYp2qM5HAwoECx5cIYx/PMtlcZkaZsNKc18j5VvT5iPseDsAPfRRORjv6hGdiCTEQy9iUawrHnT7UTyY8iQ9xmnayYFVQrGMS0mSj59jy3CvH2MTP81G+G6XMunxew0SlHKLv93PviZojr7s4LrNxbcpG8o9LqsFjjXrsTpSpWet9vtzM+kflIbGxtIkgSHDh3KvH7o0CGsrKwUfmZlZWXX7dfW1tDtdvHrv/7rePOb34y/+Iu/wA/90A/hH//jf4zPfvazlzlDl27TYGcXOyUeQtLpgF9YQ1JysHObg+GtcxTQbO+AtXpoPtZCVGHYfqmP3sk6+LHDRjBPjIbUOypHptVtBEwFSBwT12CmTkKFejUx2zQPM8YZHFX2nHS75vV9VXgUBC+ZBpEFZrggdomtNiW+ppEEMVuDLLmIZ6tg3QGV44cRwBjcI4fhvvTFkJ4DZ7MLlkgjzS/DkET5VFoKjGXnySaISkHl6PmS39y5HgjZyZ17XhfH7n0FxZOSSWJKm3WAo9MoY+0+7HnPpTHNqjGXSsqUksdUFSaHI6DVBl/dhvPcKtDuQO60IPp9JL0+3U86tVaU8mFpKbp9P9m/L9lx2s47z3/Y7TP27wnH1XILdvd4jVLpxURGKVntx6A79j2ivmtiODJimLxWhZQCSbtjAlsbNdzvOA9kec5NUSpqEk8o/3nbpgjPga3oWaGrIHm5BDY/B0hJAc8LzI4fP45ms2l+PvCBD1yzYwtB9+gP/uAP4l/+y3+J++67D//qX/0rvOUtb8FHP/rRazaOvE17Y+3D5GAIb3sAIMDGy3wcXX0pxLeeguO6YBsCo9lZxBVArjAMbptHsNMGNG8j19rAdFjWAY9Gf1wXIvAQVzyUgjLEhRXwZiOt7HJdQhc0slDUlbnImK5ycYzzMA7PcaCbUwIpipEJiHKVKFojB4ARC2R94ufwkkctDlY3KXBp1CBmG0YbBtstoFaBe/gQkrUNChoGQ0X2ZRRA6WNYDkc3zywMzi7XAeXOzf6fqyao+mEXb24SV4kxQ2y1580ee4Zki2zqyFSl5ZEJwDSsRBQD5ZL5X3S7YKUSGOeUxpSSEEArIGSOOVjuFO1SdCiEzxqLhWCZv/cb/OQRmfznitJje/F+ivaR4+pkkLE9xqrTk7SdErgMQ9J0CiPiY0Vpk1qN6tA15MXnlbf9zpfaLjPPe+2zKOWVDzD3M8ab2SbwcqSQhM7alZNMPfc2t+h194UXSJ49exaNRsP8X5oQsC0sLMBxHKyurmZeX11dxfLycuFnlpeXd91+YWEBruvirrvuymxz55134u/+7u8OfC5Xyl54V/H5MMbALqzj8OcHkC7QfmmTnO9oBARlzD4ZY/bxBLVn2gie2qAHqVq155EXU6HFlHaNkIDvAWGI0WwJg0Me5FwDot/PcHYgJZxadRxlAYr/1+hBUfWNOS9LIVbzVfTYLOdnGoO6HjX6rFUh+wN6WGxug43IcfD2QFVjVQ1xlg9DyLIHtLuA70Gsb1IptRTE+XGctIeW5r/kxlzUUHOiHeRhr86fl8omqGKOQ/wcTmq6IorpOicCTq1GqQ8pzZjygU5292z3FTyQohZIhQllklDKJYoooFFwuhgMVQNUOa6gbVUT7XrKNvqk7k/GGfGwVJf3A89j5oT2Qbrd7fXcXGX4EzaCxnja1FMHq0VSBHbKS7eOqFTIiTEKHKVKWdrIkf5MZqx7pCYnHbtoOxtpy6RSiuYj/3/+ftoNCZraxEAHoIpGKJ4cALovfNILk3FMLW/4NXSTV4iz02g0Mj+Tgh3f9/HKV74SDz/8sHlNCIGHH34Y999/f+Fn7r///sz2AHDq1Cmzve/7eNWrXoUnnngis823v/1tnDhxYr8zccVtGuzsYTqVJY4dgtMdoXZeYDiTPkBltQx/cwThMfD2AHJrh9oiDAakCIycg9Gf08gMZ5Sq6A9QXu0hrHIkFR/i9a8YGwsrl8j5FqVqJjyIjQNkueorVqBrYu/OGjPzfVMOLQdDiE7H8JZYUKaU1WBIJfqtNqBTc4mgvlgAqSx7LikQuy4pUzcbpH+SJLTKlgK8WlGHTR/+V0wsUc0BV+fjVIl0rNEzg7hJmVFKNl3M9UrcKpHW86QJzQZF0NvbDl3Nu+7vlVE5zq/MNQdHleEzx6GKNcBUqmmEzdh+eSUsW55u1J6vNRmzyCalFtU8alK4CEOTtsvzeTKcHWm1oXAcQuliChilFOTUhDSBpg5yuecWIyrA/lNGewVA9vPATqEW8Zfs1G3+Ol9JTtGNaBOQTo2qG7TacdIef4yBz86QKKpG16+BPR/tIt773vfi937v9/CHf/iHeOyxx/DP//k/R6/Xwzvf+U4AwNvf/na8//3vN9v/zM/8DD7zmc/ggx/8IB5//HH88i//Mr74xS/iPe95j9nmfe97Hz7xiU/g937v9/DUU0/hIx/5CP7bf/tv+Omf/unLnqNLtem3Y5+2dV8TouyhvJUg2EzQ/pH76WEbJQhnfXg9Ael79MUQErxUNoJlvF5PNUEKHoAyDCH7ffDVbcx/o4Oo4cF/ejWj7yAGA+JuAOOidkAxumND/6ps2tbryZBqLV5CRr/Gcib5Lz0rUfpJttr00+/TGIUAgjL1yaoEkJyDvfiECRLkaAQ2NwPEMQkQSgnR7lJVl1VOPXY+eQLnAc0OTkwaIckp5ApJPJhuD+7yEr1ncXZ0abpBgjR3xO7BZAWYE6/TBIdmuClRnAYzQiq5AQlwZsra7VL4SYjMbno13HMJrfPcFGUs4Btdll0qD6hgHzpoYb4Hp1Yl0UA1FxktFCuI13w57vuZJqAQ6nr69B6pVacViIYDlOfY7DXuoh/9th3UIov8ZZ4Pk1JT9v7y34cpsjPZ7GtgBTqaJwjG0opGoYLghTlCoKuVjIjnjWg//MM/jN/8zd/EL/7iL+K+++7DV7/6VXzmM58xJOQzZ87g4sWLZvvXvva1+NjHPobf/d3fxb333otPfvKT+NSnPoW7777bbPNDP/RD+OhHP4rf+I3fwD333IP/+B//I/7kT/4E3/Vd33XNz08bk/IaUs2vA2u322g2m2i1Wpmc5m72Rv5WrP/0axEHQPNZAa8To3/Iw+wnvwrccStGixUkZY7q6Tbk02cM9wSMQ4yGJDA4zPW8gmr8aVJHDDh5FNFsAG+zh+RbTxH60Gwg3tyk7S2NGeZ6aYuIgzzo9IM2hz5k+CpWigPQpeFUKq75IjKKqVpBK0HrfQH0cOAcqFagK4YwGEJ2KJUFgFJYXqp7IjtdxWFxx3p/ZcZ+GQ90I9TouZAqnWhzg2xdHKdWo+BLSogezbnR3rFIyfZ5T5rrQv5J0Xv2Z6CCM42qlUqEpiXpdbH1ZPbSXDIl5raz9dwxvSBbLfv5dp5aF6qonNyp1SCjuLjUPB8QSNW3Tr/t+0haLdMCpgh5Nb/34iFpU9tpHkies2V/3kZRbd5Ohu91pdDMm92KvhuMg/keNWlWfEG2tAB0ujCVV54HsbEJvjCPqNfCwzt/dCCfcVDTfunF/+rX4JQuXXgvGQ3x1K///FUd6wvVpsjOPuyUeAiH//sZxDWge5RDlDiC9Ri8UQff6sAZCcQVjsHROvjSIgnoWattaa8SWardoKXrid8jIX0X3teeQfKtp6gkO47SVSqzuofrNNgkXs5uZq9W85wJmQq6abE1u/RdRjGVX9eqlFLxXMhRSOPSTtlxIBdnKcBpdyDOX4Tc3IbY2qFAJ4qp27QuhUwEZLdnhPqoOeMuHI9LsTzkrxEuLdrHOGnb5JyQ1k1iPgVlBiWoVIjUmlPr3XWu7df2QggsXodWlBadzniqMaO9JNN0jf6sHp/NzbLQPYCCG3OfFaVp9oNmXI7t8vlMutf+iKPaPOT2oRu5ZhBUKSgw1SlD3wccDqfZNIGSLQIp48igdwZ5mYSs6N9FyFwy3sQ2n0a2CwIyrVFsVNBGbqZpqv2b9WzMy2wwteAygU5QBkYh0GxAtwgSh+eBu2+/9uO+xjo7N5NNq7H2abLVwfE/78H55jMAQMq/hw8BUQz//A76h5fAYwmUPGqAORoRTO65acsBUIWPreFC+eIIWiCOzTTAen2wZgNcQas8CJQwoTUeIQFYK9CDGONZJ6JXtJaj1BUKGaE6KUh236pQYh4hMYgiiF6fRAM3W4DjIFnfVO+HRLjtpfMgkwSi108DKxtputJmIzeMA1BBgWo5wXwfckAyASZA1QrIjgMoojJNFQP3K4CUaR+0g6IgRWiB/R6sNJsyVioVEyX19rriLkkgRY7obaM5rpdxmjwIqGeUamBrjmftb89zyVsOITzw5633ZMHhDaHbLjHX/xcc06QezQuMGqiqffEggFTfL12ZxUvldH/6nIrGng+G7LftBYkD5XxF5hrrz4k8/yp7ApnzzLy+G0p4s1l+PszLVlqzXIIUttyDavArJXENVRqLX9ggLmI1wNRuDJsuFfZpSasF9+w6kYT7fTjVCnU773SB/gCNJ9oAQJ2phQBzKY7Mr8btztrc99PSc8boC6b/H9CDVqi+UZNUZCc9aHc1O21lI0NFfJJEUE5b8zmSxPwwxg1HRw6G4NUKdTgXpInDqxVyovNz5pxN2sxKA2Xe08e/kqtY6yGY0ReSupt5mCG8Opok7VAfLh38mZW+R9wi5nuTUaj9jGeX922EwHB3GEtVpAv4Xzpo1O9lUB4rRadbcojBIKvuneNpXbJ6rH0fXep1tNCaA6EaE9KCOvULUIDnNOqp6rIK9OzKxEwgZQcTBWho4fH1HFqBVhECa/cDy485s8/893wSF+xmtwJ+DqBQUNVihXEl+eE4gOuadC6RlDmY/o4DkG0rtXUthv88EJRvFpsGOwew+PwFoNmAMz8HHD8CVAMSKtveAd9sw98egm3s0MbKUcL34M7PZzgD2kQYQgxHJA7X7VGl0/mLYJy6a8s4Ap9ppuWQNhw+KT2yT6dgVwoVBRoGYi+nJYsyjoxzlHGsSjNpbDKODedGG3NdOM0mMBiCeR54tZLpacVUsJdpXyHF/p3sQR2glaaz3zNBQRzBaTbT1FG/b7g9WmWXB2XI4YjKwMMo7Tc2aUz5a3IQ529tK+M4FXK0+FSF+9OpUpktpdbnaPhHltQAACP2qJWktUzCgVS6i8Y/gbA78WPW/S1GQ7iHD8F9yYsy27gndylhzR3DVL7pShsrNWynaXW6a+z+s5EY6zyK5sVINShkTqOJmRSjlabK8HMmBSz23OUDyKL7bWrjposTOKcgp1YBW140zWNR0vplMaXbB0OgRG1urqlN01hXzabfjH3aKfEQ/TEYIrllGfKZM8Q/SRJSZd3aAfv2c7QKKJWIe6LSDqLfT0u1HQdOs2nSCU6zAV6hxpisUQO77RZs/9+vBAA4MzOQzTqlxTS5Vv8u0hQ5qDFe3NFXr0p1dRRShMrwQISEjCJTio4koTQVY0C9hujlt0LGMSEjSQI5GCBpdwyqoPkoYjgy6IkJtHZRds6P88A26TNqTEm7A+Z7cOdmiVSuNHX0GHUFFy+X6AHKs6rPE1f6ed7QPsZokAHNZ0qSlPwOjM2TLQaZUWVOEtOJXZPiue+TSKGqRHJqNeJhuW6qZ6OQrEvuN5Y/p32gYPn0HUCyBeHhhmndAoCaydbrk49lITrc9026VfccY64L3qiB+V5amagrFm3ZBY0IWUGxOYxFYLavlQ5sTO80O9WoAyxrLsx1U/yrwhYGZoImPLJv9lTWLvOiER1zXyUJFUSsrBudMzkcpirkCrmV/QEQJ6YAY2ovbJsGOwc0ORjA2emBVQMka+tmtZ/0+ia4kW1KaUGQcB6vVcFLZWo8ODNDr6u+Sro9AADIagXtO2bg9SRWf+pVwMIsmBBU/ri0MAapFyEgByErG42YSmW8MzuQloBLabRe9DEI5RmaB7sUVBYthyNgMITTjYATRzC6+wTEi48TJ0GnUZRD0KiB5k+kk7z/h8slp1omHU8Kuo4qFUQ8pDohPJwgcAB0vYGMTg+9MJlXsy8Oi/0xCw3QaTaTTpxkNoyvSq55qZxeI/1+RpuGGXhfDIaE8NhIpHbMB0UNigKcXVCJsUCHcThzsxAvvx08FNRcV1nyjSeoEnC3Y1sIpeGe6YBFNQMVg2GKLjqk1G34M/o7lj/3/PlYhHIbgbFbW5jgK6ecbV9je07yiNzYcSfZzUhknsDTAuOmtQvzPFq8qepPJIIWK75HUhhl0vti1QrJZoxSusE0jXVj2E32rbg8OyUeQrK1DbQ7qeovADkawWnUSS9nMARjPNNPRQ6GpgmhGAxM+kOvOvjcLACASYnyRoT+Iod0ADCGeL4GUSkZITnaYe7hehlmhLWU0F/GkiRtd2HxPozeiXoYO80GnPlZUvp1XaBWgdMdgrX7KD23CWdlSx2MZ8asG5va56S3269dDUJz0u5QOkM7JEVe5gvzGQkBg9blxBknpn0OEsTlV/dSGFSsMD1V1OfHTg3qv/Pq1EliAjgAxjno96D4VWNO/1LTWna61ZoPXipnrqVGP5KtbeDzXwP739/I7Ir7PuLVNbiHluDMzBSmiU2g5XDSU/I9q4eYBCuXTGWO4XLlxqWrtPT+MhVadqBjpYXzLTg0l0oLG5p9KdRI3zMHamI7NrVZNM/Mt/37RjUbyct/b1yXnklJYng48D0wXX2pg+BRCFYuUWXo+iahOZqfeE3P5Qr8TK3QbvBvwZW3U+IhxGvrkIuzJDt/54vhHD0MNj9LXypV0ZPs7FAaR32hmOMgaVPTS7uahDVqQBiaL53bj1DeEaifTSA9B+5WD0xKyK2d1NFdzhcw/+BTnBv9t0kN6FVxogTudG+qgpWrjGPIXh84tEjVC90+rYY6XYjzK9QiQlseRcmRL00Z7vPxgLadXKdD/Bwt3DccQQ6HhpTMK5W0MzbjhI4ph23SRTlncxDuy5i6cs7yq37thA3JNi8mqFOgGe0XvQ0zv41Sc5I2xTTow27Oc7+IQlG6hfExvRwxGmbSg86J43CPHsm8DwDx6hqSnR2IwWAyyqdW8TKMyOFx6sMmo4iCIM3J0iiMbblU08SUnnWNx8Q6pdUSIp8KsxW31RxPRHUsh549NEuRu9x4DoomviBNk9kzBR8KIbPoBNCtesIIGI7ofogT0vsKykZqAnaAC0BO01g3hE2DnUs01upB3nYMADC6/RBGJ+Yp1QTAlCUPBgS9c55WXznUVVcmCdz5eSAok2hdJQDiBM5WD82vbcEdCIhAIQsuB6tT6wm7wma36g4zzglkS/237gtkBzypQ1KkzgkBlnnIRhGtlqQkvQqHAzttIvsBY6mJsbSIRdZkrmf6ij1fxj0XfKaZCjh6LqV32l3TzkJrDVFlh0dq0J5LlVyum67ynbSzeSYA2cvyxHErvTFxPwX8nfzrpprLWtVqqF6GET3Y4zhF3ezrNYFzYwKy3UjyExw1gIzGjN2nzBZNjJ95FgjKcI8cHt+3Pk1Nqrc5VCZoV2lTPY9RTErntapRBs9woHL3pi2PkA+A7L8N+d4m3ed4T0xVAQFIgytNbLaQicLgxT7GXgGYHuuNjuwARgEbgGqYq6olGaPUVVAGq9foHlffLVN8wTmJntrpdE0tuMZprCmyc/Xsxv8WXGF7I38rBSkA2DAEe/Y84sDB9h0ldF6+ZCBTViqZlb5u8wBHPcRtdeAopjSClJS2WqhBVnyUV/tIyi6k54Bvtgk5AdLP7TMYGEt15R98QhIyo0X+pExVa+0vul49qR5W9n6Yp0TbNrepqkF3Zo+iTMnzWJBjO2fHgTM3u3uV0TUymSSQ/QE5lVLJoB28UQN8H3xxgZwV52CVQDXrJL0auC6lR7QOkVXybNIgE/hWu5lNPlZ/ZB2zHQztA/kzD3HGKNARKt1jXe+JJPhcYJM5Xg6py1xrKbL3g9rG5jyJ0RCZCiVN/nUcyI0tiO0duEePwF1ahHu4uCtzJj1WLmXJ2pKQSuJkKZ6ZOpZehOT3kUkby1S2IbP6NxpOGL8W1ufT/aeijyZNbAlD7paWzAvljaVuboLgJm9S93djDLxeUwFhiujIJIHs9Yl+oL6b4tgSPfv6JMEA36PvAaf96MVaHo27mjbl7Fw9u/m+FVfAZJLQw/LcKuJ7bgUPBernYrRudSCXF8w2htQrhSFDUm8ftZor+ZCb2+RwEoHhiVn0jgVgYQy+tgO3NQLbakOsbUxuRrefoGfCNiSalw9+hFlR69J4/WDVK3C9GjVqy6p7OYQkeFjnvNUxCpEIK73CPRfM9yDa3bQK7HlEdmSSpAq9OhDwXHpottqU1+90qQS92zMpEd5sEOlROUKuu2trRV6ryudSKpwMz6uAdzOGlBW9DtA1Kkplqcat9vWm93dBBvaqrtrjfeY4RtNI/29+W0GSjCM4x48h2dmhoZ6/gGRzC/HFlWKuDuOGmA3GSCU6SSgQZdQuhDFOwTxjioAejacrrIDSBBQFaaaJperWZ8z/msvDWOY1uxy+CP3KB7v5gCeP9hSdw2XbdRpE2efNyiXI/gC8UUNGPFBLD3CqsmKeC/b0uZSbA1C6Exh/1k6RnRvCrs+79zq2U+Ih4gisrEH0+vDWu0gCB4M5B4kPhPMVqtSJY8B1UzKvDnriKBWJ0ykfACiXMFjyUDvTB86ukDDhM2eBWgW8XsuoMGsbc5hFzqXgf9vpUvpCKSInybhKrw3ZM1J61X2rGGfgtRrgcCJexzFEi8jb2qHyckmle6wmh/n9Og6lh6QAe8lJQkyuRJXVFTBdfi5abcgwoiahUdq2A7Eqn+dcEc+p4oOUpqOU4A3reh3Q+djlz4wzA9Ob9y2Hav6nP9Kd2MKRUmCsOknzZjTEr9NvV0LiYII583MmqORBkHLZ8n3RLIetvwd6jGPfC8aNcjGvVVNOjj4PzsyqXTs1Vq0YRDMfMNpprLGAYg/nbxAaNeciDNOg15YQUMhOXgxyDM3LHTOfxipEhC6XVJ7f1/VmLKt3JLs9MKWFxThPdXUAWqxEpFVl0HaFbpp0pkY741gRlAXgXh/Poqldnk2DnUuwU+Ih8+DCxja8boywybD0lQjtkz5clY4R3Z55yJqqD7WyY65HK9VEwaZBGc3HWmi/qILud78U4vA8pZYGQ8iluWKnc6kPn3zAoZyGFGJcU0KTkZMkTTfolao5NyrjlZHqsaRWUEz1ngFg0kFmt7rSSSNdpRLky18KUfHNXF0vK0kZhmmwoRyVJp+nvcTUqnBEFXm8VqXVo+qnNXYu+7l29ipfizDaSIbN49B8lQIeiTHOKP3mUC82E+joNI4iXXPVMyxTJZQbVyZFdQnGS2WIVsfIHkyqejHoz2CY4esYcrg9JiANihSaY4jPFoIplTgjK5UQr60DHnE7RL8/Mc1Kh0iJwLYulB6n/bsQaclxkQqDGcvsIMb8tsY0Ec2ZZDcofyeT0iuV6Pun+1zp55laVJlnC1fInu+BVQKIbo+CHVWpZyQfRkNThn5tTuYK/Eyt0G68O/8amg4SSufbmH0iwtadHkYzDHJ53jyMNQ9A9Ptw5mbTChdd5RNF9KUbjiDKHhKfQTgMwlMkxqAM+e3ThQ0RL9nsh54FqQPIOhC9rf23zdfgzAgL2nNCgU9sVk/M84yWCffctPWCDrZmGth6wy1g33oa3VsqkAtz9Po+V9BXzSykzFQlKR0WqXSDzBgTMYb40MNWZkrGD2KZcmilhaOJtjo9lufEFOwk/dOG9PVnlBPQY9ZIG3RlkLpPM9fACpL3cRKFL4vRUDmSERH5FVHeqdUy+9YpxXhtHWJjE06zSZpQvlc4Jvu4rORbZfMUVBuVb0lNZ52ZGdLFirMVOGOBwQS+kUZibK6PCYBznB59PU3Flo3ITAr2VDBjUmc2YXq3wNa2Av7RjWJjJfsW2T2TohWkFaafVZpPSLIgDqFAGh2yCOvXGmGecnaunk2Dncs05jjA1g6SMoczArweEM9ViYzMGcHs6sGZbLfAfB9OrZruIBEEu/b76J4I4ESA30kQzijRs2fPkcjZFXT4WlHXcG+U1grjnMjGYyeZhfTpQ4roKWXq9BP7NUUQlJJScn62QibjpIMyBgsMF37qPvQOcySzFTMus81VtLGWDzmziaM0fDYmBifjCHI0MlC4TBIqbXWyKIjdKmAvM8fz3BSS10iZquYprECiQdKPRtns8+OM0nMZQUHlSBXB3i4F574/dg10ZeGe52EHRoyn5H41Hmdmhl6//TbglXeBzc2MozbWfCStlqlytKu4Cg8dRdT3CIAuq2eua5Ad0xfp0GKaaiwi1E84p+LTtQjeVhm6Pf+FgYoOmgoqrYzEg5Xqymss7VuE8AZEdgCYwBNKy0i02qbizZZWAJAuGECBjdjeMdSCTGBvpRSn9sK3G/TOv7r2Rv5WOPU6rTo7HcRr66j93VPgISBcwN3up8KBUJC7UkwWgwESK70lRlTSjChG47E2gvUIvWUXTK9EiqD6vF3qA8x16cuc6OoZehjofkFjpba5gEAmqlWGLpGWqqJHlXtKq/eXHFF3cJ3+M86UcSRPPYvKKh3DGQF8sIci8RW2PVdvOUTLdox29QxzSaU13wSW+V7WEe0zeMvyQ5gij8dEdFdIhG4DYcivNm/D+qwhxWqOgurubVa/qgJPhsR3sTWERBhmSsJ5EBh+j9NsmPul4ARo1+q74lQrgE+qzs7Rw2Cvvgfi2CG4L70NSbMCyTnio/NIvuseOqdX32OOCUYl/rxSARjpGolJpH01x6LVNn3OGOeUNs61P0ElgGik+khj95t2okX3Yb4y0r5PYAU1NiE9/x6yDtZOleXJyIyzwu7oE0vQJyxSbiizkDQwbqQ0ABCio2Q/jM6SLbOh0D6oZ5ctwmkHOldDuHTy+VyBn6kV2jTYuQQ7JR6CDCPzkOelMrA4B55I+B2J0eE6fXkU1G6+LPbqLk6DIe00WRyDCYlgK4HXjcEPLamN05LlQjvoA0yPSZEySTBQQJOVwVlxlYs+ln546uPq/WnHpCqSbBPdrglw8uXljDPMfu48Fr4eIgoA3h1lH9BXOeAx1Tp7mX3OdjmyMpPysfaLhOaVAiFvYkVV4eFU8MI0z0a9prs082aDXs/zRHR1j5We1IEOM5A9BTw2UmSkEuLIBNqaUKs5PLzZMKRgEYZAHIM3i3tU8aBMPKBKAO77lI5aWQO7/SQQlAEBwGFInnwGzsoWiWe6HN7WAHjlXUjKLtwXnTCl/8zzwDhV74l+f/f7gvFUb8X1IMNQVctxEgN1FIrp+3DOb4L7fpYTYwcH+Yqmve7LCRVQecJyRkfJCpLyPCkb2Zl8urvwfy4hhXrdm4WcmdQrAFYuURf7ZgNStesBQGmskk+oZrdH2zqp2nme3J1B0a5hKmuaxrp6tjsOPLVCeyN/K5W2zjSBlnJyLgfXsgwOg3PyFsRPn6Yu2mGYthbwfaoKiNOcPi+XwI4uY3ikAWcQAxUH7nNrSFZWi1cXu5WT7qfUVAqAeaYcU44SsERAJikvYUwET3MQrAAFUHL3ngsxEBCjIbgUkH3qJ6WPJfXQ1X4MSVsFWiIMIc6cRzlOcOwro4z2yXVle1S6ScHNPOqAUUYxEItUK0bzd+DsfR0BQkMcUnZl5RKlXpIE0D1/GDc9o/IPZa0zIoUwAY79nq7CSzodOPU6WLkEJygjabUhBwPTLBRSAq4LXksRK70iTrpduEHZoJfa3KVFQg6HQ8i5GbBD8+CeAxap67rdAV9ZB04cgRASO991HKXtBCyRYLUS3NMr4Asz1HR1eQkYhUT+1tWAoO9NUZWivjYypLlmLqFTjqgQOjYaAaopqHjuLEQYwj16BHJ1HZBsnJszYf+F18zmtGEcbcmko8yucoKF1r7zYoX5v/Vxxyr+9L6uZOn5dWQpIVzNBxL6nmiVZFXtZnpfLcxRJ/MwMhpLqd5SDqEDTKqa5vYK8iWn9rzZFNm5RGO1Kuk1BGUiTK5toXZ2BLcvMFhy0X/JAlVctVqG7MkcJ1uVJAWcZpO+pL0BhMsgOYO/E0HON4sJkepzmdcuBaY2kLvqAWUFGMz10sadBatX7rlUcq5SC0m3a6BhEap0VaeTQXuMyq71v4wjChoVJ0Rs72D4ilshDy9eN6XnBzEjL6BKidP0Ed91PvPGS2UKgH0f0FwnRxHWPRdoNoBKQPuXwuj5gLP0BxTkAGnQQzvnKvUmqLKLKx6N5xKh13Hg1KoGgZJhBFatqK7hIZKtbUpfKlIxQIG4Mz+b6UqOSgXwfbDZGcBzkFR8CM+B1BUyqrltNBeg/0OvQm+ZI6opBxYnSI4uQrocKPuIz5xDrLSmbC6RCXQmIC06+NL3GfOUEOTiPNhME3JpDvz4UTjNJuLzF6wLOaFybrfvX/512JtkA5s8Kmg4O3kemEYbFBJoHHwBN6fw+3KNkNFrbrkAzqQfGTPtIUSvb4jpYBxiY4tQHpbtW6Z7Dpp0Y+4a5GUdrrpN01hXzabIziVast0yYnhJrw+32QCPBJxIQg4keCThHFqkKo/+AE65RHwWxcVxghnIfp/gdNeFWGzCHSTwn1kDRiMk263xg+ZLYa2KlV2tCIa3q3QUiVOn1lLURVDKQPEEDJTuukQ6Vm0U9IOGucRN0V2zDZrl+Gr1qk/DWslqEm0YQgyGcE99EcIq6c48mK6CMdcjQUOro/Ylm0JsTNCIVIjRoFuWY6L5HF95U/8tIrZyVoJEYvo5Qam/SsbArCo4XqkY4q0MQyVpABNwabK46PWp9xVg7j0kghAcxgCHHvyO3kZKIE4gpTCaNTJJqHTcCjySjU04h5epEi+OAKXILRdmID0H0uNwt/tgw4iCHcYQP30afnsJPgAenwRPALcbQToczjCEdBgQxYQSKXSr8DoVrMzNXOp7yXFI2VsISN8FS0pgrR4hZbMzQLuTaU9RiIgUVHwVBrD5oCuvr8SKRSXte30sEBI6T2Ed8wausiq0DKqcDfqY5xJSYxaSVCQBqOca99PvAaBKzK3+fpYeGv2dInPc94DRNTrHyw1YpsHORLvBQv6rb2/kbwVzPepyLiTkYEi6Ot0eOSjO4IwEJAcGdx9FfOthhZ64kCcOA8eXIV9ygtIcM03qeRWUwTtDsFgA5RKS7da+HHx+FQKgeBWSd6ZWOavuAi0VIjO2L+uhanMJ0sojAadRN1VcuoTY7E/9jJGbbQcgpelybUPyVzvQAWA4KZr4eln7slbh9updhKFZIRqegU2UtIzkDFQ5bKmU3f9wRA9o3wELqYmlHI5M+bYuTQeQiudZpeoAUtI758SrchwSTdN6JIIqWuK1dRJR3G4RotImzpUW6MsEOlvbSodIwrnlKNzbb4OcaSA+eQhgDLw7hLfSTnsQ1QIgEXDmZhGvrgEzDdS+tQF/awQwwOmOKC3cGQKjEKLTRXxxBajX9n+d7GCeM3KEJZpvFiXUfDcMITc2gdGIKiT3WSU3dpyigGeP4GMitwbjqS8gRQ13C+wm7e+GMb1QKLhG0iJuJ+1O+obSU2KOQ98XIdJtc6lGu7Rfv8+0btjUXvA2vYoHtFPiIXKQvkekScdB0mpD9Ppwv30OzpAeMP1DHsKGg+7JADh5FHJpnpyPy5FUfYxeeRvk4qzpIwXG4D29guT0c/T/QdJR2g7woM7A5XkujtpnpuTYegBQw0jrgaw1YPL7U8RqFpTNAyOT6tErXCHBfI/KkA/yML8Sph1+HF/+MXOpCFpRsvQBrefVcwlRyGvlqPEY4jBnFIgY0jEndCWhVauMY4MAMc4pALVXr4BZ3TJXHbOk0mOqJB26F5C1EhbdHtx5ErWUcYSk0zGpICOmqYerg6igTPuKiQchAw/SYWC9IQU465s01pkaHcdzIY8fhnPnS4DtFmTZAxMSwuOEvAxUZ+qdlkmPyUpJEb4P4OhdQiadZoPOrdUG2l2gNyAxQcdRvZGGZhGQ582MWT51VVT1VPSxXBqqSAHZvGeRzvNigvtOT9kcohvE7OKGzDPISt/qFiTUDodSWVIh0aYlhKWbZcx6ZpnAM7m2jUDZFfiZWrFNg51LsFPiIWL0qy8Br1Up9cAZgme2UF4bwR1IjBockgHRfBVsawd8bQcA4K134XYiSN+FLHuQWzuIn3waYqeVohl7QOOZ120EZh8PtmygYqEuVmAzliKzq0es48gkgeh0lFpwqvVipwRsVEdEsXmoj61ukwTu4gLcxQUSl7uUlfYlGptUfXZA00iKRm5MabrmLwVBOieKPzA27/rzOgBl3HCAwBnQH0DutIyIoT4ulIyA7ugNKDSuXAKqAbVFUIETK5cp0PY80xcLYQQ5Cqm/kBRU1eL7cBcXrImiMfEgSDt2A0h2dhBfXIHc2gHaXbAwhndmA4giCvJPHKGPb+wg+cbjiJ98GrzTRzxfgTw0T9+lRMLthuDdIVivj/j8Rarg2txUJykVYqXmpUhV3EZ0FErGfR+oVWCanrY7tB+P1HMLW3rY36uCe3BXQb+CNJMtEJlXRi4MgjSayi0NJH1/HGRBcKPxdYDM3ICp9iD6utl8G8eB7KfcHY1E21WTmfk0u5dmIcJLZSK6Xyubcnaumt2A34RrY6SX0yVy7vIi2IuOI9naBlptON98Bs2/fQbV1RheXyJsuhjecwtkncQEw6UahkslsCfPgG21jYMUw1G2L5D9oJr0YNPoyT5KmTP7Up8z1VeckVNgaVn0pBTSGOcGICKrao2QaY8gVfVLsnsJp1SaGCiVyAG714ZOxhQXhHgkV+brwDgzKAqv11PxOymIJ1MuUQCS70MGEOKSWA1arTljjgPZ6kBut9KS2nyPK22cEcLjUysEeB5QCajserZJxy5TpZVotSFHI8Sbm9T3rdcnZVnt6D0P7onj4PNzqaMplQjlyVUJsoV5oFoBEglEMTAcAeUS+MoGWESK4e5ttxIPp9eHt9EDixKwMAHvjSiVGydUOZO755NHnwA/dmR3MUGZVr45y4doKho1CuTWNuh6K5RLblAQxRfnaZ9sF0kAK+ixK6oKScO5+2jSPk1q0wrgCltEqPMy3J1d7EDPgRegjSGhUvVvs9uBRCl3jSnJA0rz8nThkV8Y6vnPC0DG0Z5zfiVtWnp+9Wwa7FyinRIPmZ/48SfpQdxsQBxdBGvUAYUUlFeHCD79FQwWXXTumkPcKCMJXIR1B4PX34XnfvQkwtfeBaarkmx4fJ8pqkLuzj5sTKbe4svQv3a7giwHAlZqRiYJRK9P5dH2ilcpE2thtyJ1WD1+aP6QIrYabZer+fDWHJoRqQnvpci7n/0BhF4hEWn5axCkD1Cl92FWi/mANhG0AtXjYowCkH5fBY0JBYYJlZMzzscDHQAZroJWW3Yd0rfp9ZFcXCHURY0v6aXEX81jcpcWwOdnDddGk6OdmRmDsOjzcl90Eu5tJ4GSR6k3z4Gcb9LxFAdJnD4LHFmi/XnE8UG3DxF4RMp//CmwQUhl5mEER8sXWBbP10gvR82XqfSzTN/X8fkLcBq0D9lXlVt6+zgGm2mqey5Mq+WA4qBcWqJzdoDCxjVa0muQDZ4ygdEeHJ/CBcwe6atCLZ4bKIVlW4Zfo8n72hQPEIwj6fWp35vvG9kHe6GWQa5VA1nme5lg06lVMLUXvk2rsa6AnRIPASDyMra2IUAPtqpIEJ+9AAmg+V+/jvjVd8AZRIhrLuKAYWvRxeCwgPfXX4MEiAfk+xnyp7H96H4UVZAUWaaqwVrFJGm3a72KNBwbrepqO20V9KTpLZndr9QaO+MBlYHqbQQoUSv6iDoOyzxycBXM9CxSAcbl7cxC5KSgKr25WdL50A9n7cCSxASBGeMMvDFDDQoVeV0KCWbzohgDQDwEAAoNEoqDI9PS85BSUlDcHiYEZMkFyjNwmnXEjz8J99ASWCUAWi1zLZxqJW0Y6qoqJp/SXe7iAgUwvg/XdRGvkyAfPJc4NqUgHSfngO9DVEpgYYz49sNwv/AY2JFlQAjE65twX3QCfLNN4n6zTQp2o4gkG4CMfo974jiw2TWI2MR7Qwctrge2vAhs7Sh0i3hS0C1RBkNgcQ7Y3M6Q78eqD1EQAOUWJbbAnZ2GzpYxC7NP7jHIJLegUNvYVUF2gDXGD7K+65lWJtcQibhmVpTWl4LuUylNtR71deMmBcs9Nw1GdcpLL3J0B3q9S0epgw+JsC76fTDOkPz/2fvzaEuu8jwcfvau4cz33KG7b4+SWrOQZAmBkeHLCvgXYcHHcqzPiUywlyEE4+AYBywHHFg2cuzkY4UEgx1IFNvLJs4Co2h9NokdJlkOIQQZWRIyo4Rmtbr79u07nXvmGvb+/nj33rWrTp079J26W/Wsdde995wadlWdU/up933e5+2N8XLaCRTVWDuGPY3sfPWrX8WP//iP4/Dhw2CM4XOf+9yay3/lK18BY2zkZ25ubncGvA406QHoRhyfPG3+F/0BnP/zt+gdrgJCwgkk/A4w+TjH4A0vB5+oY/h3XpbuIbUWNlB1tdH17bJL8556KrVD9aldZYV9ajsmtWFVlmTNCbOtE2wCBcZMV/GdvmnrqICJxGwjzETlOgkpkQIII4gV6u+UO1nrlJO6gcuKT4SgUkkIZUzpMCOc1GO3iI4WHJvKE9UMEafmqRqp3YV72aWm0sm99BjcI4eIpHU6lMbSndGjGOj2gGGA6OwCohdehPRcYKIB98rj5IgcC2AwBOv0zbgkY5BlD3A5xEQZ3refBT96mITGpRLcQ7MUXeoPgOUWMLufiFUmjaARPX+CiItYIwJjwTk8C1ErITq7kGigGKPI0fQEUK+S74/vj6RuR1JVln4npfeghROiY/viZH7MJdbbzhIa633rn+SzgyTikxL4j8NFFNUZiXTpys0gNO1ZTOpbp7ZSD3VmQ2qR/CafupdhrFyW9wSFXmdHsKdkp9vt4qabbsInP/nJTa33xBNP4PTp0+bnwIEDOzTCUbye37nm+3Z6S9/I7MqK6p8/jMpzLQwnGOonQxz4RgtBg+PFt1+HxZf5wCWHaEPr6UfOsQrLrCtFurdQVqQXJz2fsmK+xFnUao6p0lXGdj+b9gJGbupm7JbYmZVLqfXGlZpuFfQUVzapMhmFKte/xX1ZKQ5erVKJt5rARaj6WlkRMwDmxsxLZfB6zaTyUKsQMVGRDOZ5FnGSyW9DcEavoREfA1Rq3R8Ai8tkSljyyJ2YcSI0Dod79Ajc/fsghgMq9wYAocZQ8uFechTuZZfS9peWIV0HLIghNLF3HEpF6dPRJvLDwhg4ehDSdSB9F2K6TsQmVp47i4tgQYjw4ASi02fgzo5+p7nvI1pcRHR2ITm+NRCfPA2+0IJ75eXA9KTp8C56PbDVLpEsDkVIE0Ke5x4OJOk9W4OlI0L2OprM2N+fPA2OLYrOSyfbQmUAiQeMFYFNWRlkycDFiJzUoAzUdzeiiLCudNRC5FRLDsCc11REzbrP2Nc+ey8rcOFiT9NYb3zjG/HGN75x0+sdOHAAk5OT2z+gDUITHjuSk4f7xX3ky+MkOWbGGeLv/wCH213IXg+y08XU6lF4L9uHypkBZMkbsd5PYVy+fq11cpANteunRVMNZk3EIrA6QtvbsG7uydNmuoO4/YQ8Yp2v/V80mdLGYL4HdIl4MM817TW2FebYkwgUL7vrTqDrQgoADjkga71If0AVe65rysNlZjdOjXpIoVJWBMYhM7+yBzaI0ik9k9pg0I09AXVTzpxjyQSYozQy/QH4oVmyzBcCcChV5V59OS282qFz7/twpqdUhVag+liR/w5cF2h36HrO7gcTgrZbrdJ4V1okgpZlwGEQUzWwSIAttiAOTALMBXv6RbCZKSJRAelz3JkZYBjAXR0C114JDKn5qF05Y9JLzjr+S4qgOJOTlEZrVsFPL5rUHD98kM5b1QFbWAEadUUuMp3k9edaJKkjbZoJAHCtBq9S5H7G7fHIGAmZskqos8vSdymzPjA68dqpLNuj5yIjOllCl9x3El8usmYgnyk5HI5UtTKeEJ10VM0F8yl1xRwHIoiTlPNu22AAWxYZFwLl8bggKevNN9+MQ4cO4fWvfz3+7//9v2suOxwOsbq6mvrZCtYjOHnLp0q2GaeyagCsUgFvNBA99QzKf/4w2LefAnvyBXpPl9VmS18tr5Zsx+vcUtw1oJ9w7Cclc+PIEUqPPDnKnAqrjE+FXi/PK0R77AAggXa1Slb+U5Pgs/vI6ZflRIO2AYwzap0QhAnJs0SqW4HU6TglCOYH9wMln6rVKhVznYxgVd+YtZ6k26dUnu9RdZJLHjvGP8eUrMvk/GTOOUUxeJL2GgYUwVhchmx3ED39LJGTkqscjh2qonJd2mYsSDejry/niF48CUQRlYIHIRGdwRDRiyep9HxxEfHSMqKTp8F6Q0iHtsuCCGLfJPW9khI4dIDSW5zE03bqlq20wVpt0v/YlTGWZmVdQioF3EMHKSURBGCDALLdMdEpxIImxXoZcnYGsuKTqaD1XdLVWbRr9Vq5lPTlUqLzcVFMs16mdBxIoqbZ9exUzZrfK62pyzywXJRaHaSjYfY50xExc170fZbxhJDaJBDp+5v+Hop+35DY1H00Uym3K9hKCqtIZa2JC0qgfOjQIdxzzz145StfieFwiD/4gz/A6173OnzjG9/ALbfckrvOhz/8Yfyrf/WvtnUcOmLzeufN9EJmghxHiMwXcTiAWyoB9SqGN1+G0guTiJ99Acz3Ia4+BmehDfHiKVPxpNsZjI3eWE8hut3DepN2aqK1iYgUqSal2V49doheTwAyCFJh+pEnI2ufdkjZPI1BVQw1G4hm6nBfmIdsNigSMjc/cozbASlIsGun0LZr+5QWi2j8FR+yUQY/s6xaLqiy8ogiFdoHh9WolxTCkErCfY8eRXpDSrcIcn81epg4HiWCtvZJyKRdhBFIJ8JlZ3KSNDbK4A8AoqefIx0NANHtUTVUHEOcXqJmmQf2E+EBEL14kgTD/Uwne4CIA+dgQoC3BpAVn8YSSWViCCJxkrx9AED0emTLz11KRzBGn/t+jlgfOZ/b9AVAPH+WvmtnFyFPnYGMY7j7ZyhS1h0inp2E89wcRa16fUilT5JC0ndMRW2kIMNLTZCcej25Dg4HA8ZGVEfSldbn30RSsw8C2cgNbWjkHOtt2A8iF2NUZwRSmD5t+jOgjzsv5Z1KSQIJgdEPN9BEMTIaPi1ilnEM99AsojOnUeDCxwVFdq655hpcc8015v/XvOY1ePrpp/Gxj30M//W//tfcdT7wgQ/grrvuMv+vrq7i2LFjWx6LJjzc903ZqjszA3C2ZprLhOQ7XfBGHc4DjyAC6REGt16F1nEPpdU6Jr9dhvz+04luJbUR0tvoJxCaqDeRr7cqOtJl69bNN3OjpcUzQkrHIVO2MAKkZXBnSJH95KqqTDKEjVXKJBwt+RCTNYRNH+zYfvJekRJ8sgm52oYYDLc9lSWz5arbtd04JidTxiB9F7wzIJKj7Oo1UtfW9ymtEwuK7nBOfaQ6PRJrZ6MZmuhISdvWlV5apCxInGzaQ/QHpsuzDCOIfh+OlGBxhYiV58E9fBDRqTlDYpnvI5o/C3f/PnDOqbWDgnvkMOTSCuJ2Ys1vru3xo4h9F/Lhb0O+8kbgscfBrr+KlonVZ836jMk4TnpzxarCZkgeKY5qXKp9UsZN/Pb+GWfgzQnES8twpifJRXlxGWi1wYYlyOkJ8H5o/HZEt0dRM4cDaqIz4/LJJoB5LpijxNNCEJFVxJVxn9IgduUUktRvKmJjPQhoh3I90er39f0kFd3NVi5aDx72trPp0YsCVgRZqipNXipniGOy7Ci5Eam/qbpRE0NL62SqR2E+Z/H8ws4eWwZFGmvncEGmsWy86lWvwlNPPTX2/VKphImJidTPdsI2AYwWFyEHQ3pqBml7Xs/vNKSHuR6V1yqSET33fGo70mWonYkRNBiGB+tgnCF+1cuA40fNjdF2rbXD2imn3vVgTRgjBlvZCEombKzXZ5xRJKrdSYXl1xJJ5tmzM9elp2uP0ifSZVi9vEqpFZdDtjtg1cr2h5PXmDS3A/rmzLsUmZHDgEiJEgybJ1KHg5VUW45IRWt6PTLj66mKLSHAvLQWyrR3EDLpeK5haalM93VBpenSavcg+31KaT1/Auj2IFfb5nMWdzoAQAQeMCaGzPXgNJtAFBmi4zQaFPGIY/BbrqcO52UH7NYfAotjOEcPg7d7FNWJ1XGq8x4tLQOSoifGC4dzSrkNh5BCQGgDxSwhzX4e7M+wkGbsYAz84H5IKSBblMZmgxBytQ155mzidB1YAmQ9wcYxRS/DSP2EYJybVh064gMg/R20Iy5WuilL2Ix+JFWiPhoZTU322WXN4V/kM52uEs1otvIqPnWaSp8vXqmoNizc3C/ZzdeBlUrmGtiaIB0tsjVju4IijbVjuKAiO3l47LHHcOjQoT3Z93r6HZvo6EiQUDdbXi4Bl18J+cSzxlen8rUnsPCTL8P+P3qYvoTXXYnewTLYgRJqlWvBH38eUj3hapOs1A0ubzIYE7HIfTLO09rYN2p7faH6zbgqpKyXRVJ5ZmseZIxca3YA9ETtOGC9AKWzDLFPJcGsNwQO7APaneRJdjvuO2y0Mem2w3EoxVMukf5kOKRzJWTypKknVMcBen2gVqPz0yBNF1ZWaSLVUQfTrJNIkp6cjVDZiuqkIwHqM2JNlLrPFZS2wVReqfPjHj2CeG5+JEXj7J8h/c7JU6nXWa0KfvWliKsq2uhyCMboacpzTdVW/MxzcK66HIgARAHc/TOIzi5SM9mST+PhVB3GG3UiQFKQ/0m/b8aXlxrSxyWFhOh0KRpTKYPFAphqknDaCyGffRE4Qg152TOkQ0oIFX2ObYNPGUbgtSq154gFeWIpfxfJBJAXccyKiq1ojIF1jeyKTTsypJcx181LRPQjpOdiTWFlNVHMG3lgM59nezn1/eK1KlitaqI0/OorgBOngKdOmJ5oulAiN6V4UYbLXnrYU7LT6XRSUZlnn30Wjz32GKanp3HJJZfgAx/4AE6ePIk//uM/BgB8/OMfx/Hjx3H99ddjMBjgD/7gD/BXf/VX+PKXv7xXh7AmsmRIEx4AgOuif6wBb+Ja8Ae/DQCIWy1M/dGDwCtugPz+M4DL0Zvl8DoS4dU1TIVHEdd8OI88AX5gP91AV1aTLr/Zm91mb37mpjJ6M002aWl4ghCs4likJl2RwnyPnIIdh7QNeRUosQDKJchTZxDfcDnc5R4qrgP31CLiU2fgTE8mT/zbCBkn0YWdgAxDsDCE7PbASj6R1+GQqsuMloNE0ghCoFZRzQw9EzGQ+oZu9AkCpvJKqomTs7RHUJb8Mm7Kce3znrIdUODVKhALKjs/OapTcK+5EuLZF0bWjdttuIdnITn52EjO4LYDRA2KQopGGWwYAlLCufQYmUZqk0QVqYyVqaEz1USsfXFKJfBKBeh0ACGTCc3Wl4k0ERdajyQlRKcD3qhTyrhG6TrZWgWrVSHPLIDXqsDsPogXTibEk3EwB+nPqMMRt1qJc7SQyWcnFgl5lmln8GwlYtYgcERPYl03U85uFTYASB4+slHTiziqMxq9Sp8TU1ml0/pWKhIApdq7PVVtFUA0SkC/n9qmiVzmRNW45wKjX5cdQZHG2jnsKdl5+OGH8aM/+qPmf62tedvb3oZPfepTOH36NF544QXzfhAE+JVf+RWcPHkS1WoVP/RDP4S//Mu/TG3jfIcmPPHKCvz/+RCA0cijeOQ7AIDV6xpoH5con2Xw2kDYLMPpR+CHZnHqjYfg9ST2/c0y3FYD8cnT6Rv/ORKd1M3U1u3kCSdz9mXf6BGTmFBHNMB09YSVgw8CsDCCDELwYYThoQnEVQfuE32wm64BziznimC3BJWr31FEZB6oPXbkcGhICz1FQoXlGTWp1JEZ30nSI0IqspiU1+p0FB2GpIlZT8Dm2JCeXHXlFmeJo2wUklGhIi4yjiF6PXNtdbqUlUuQgyFFH4chWL0GLCdVa7xSAbvsGOIfPA1207UqvQZEdR98EJNpn+eARQKyBMTfewrulcfJpNBzIXs9uPumASEhej2I1ip4qQyAjDhFf0D2B3mu4hZMGqJEjtEyCMDrdchhAN6oJ+RKSqBSQXxmHnw4BB8MTVSHPvvq86vOJbkdu3DqdSVejZIIm+MQcVP7F8NwxO/GLnXWy9mGgCPl6jnR2ZT4OPXdHLWKuOhgpf9sE0YZI0lHaW2TtLxz1PlwDs5CnF0w55xxBjzyvfT9zuzKuhbWedaWB7uCraaiCrIzFkzKXexffx5gdXUVzWYTrVZr2/U754L1TAoN1BfV2TeDF3/6Shz5o+9h6e9fh+YfPwh3/z7IIIRQOotzIgU5guTc14DUzYX5eeJMpCZaLeaUQUiTrE4RqJsJn6C2CGJqAkwItK6fxMQP2pCcw2n1gE43nWbZDow5tpHJ5Ry3pdMpTNkD6NYQxktI3ZidqSZYo07aJNcl87tYkIZG6aGg3KRNibYmRnZqhFlGdI6TivCYcluHGw8SoUSevF4DSj6iU6ORHF4qA5yRmLnZNHb8casFXq0ifsU1RGKcxPdHOgzC5eCRACQohQTAbQ3MMohjclpm3LSyQBAYAbVorRqCw30frFpFvLJizmsqXaF0GUak6/tUSqxed6aaybITE0AQIJ5fAOOMbB+WllMpMTCefEb1tXU4mOfRuCuqC7YmPJyT9mmNz8u4yrFU6mpcCnoNcbJebjP+WhcS9HnTFZ/2+dJpc5tIptJPKvXJJhoQyyvG4woANYG1OpnnVbnZ5DKSIb4i/2xH5ww9L/3QP/7/wvHL57ydOBjgW5/64Hkzv51PuOA1OxczUjd2VSkQnZnHwY/N4+l7b4J8hkH+41fD60o0v70I9uzw3G98eTfqMWW99g1XhpG58ZpIg0ovGIGsbRyoy0OlMK+LLhEaLiTk9AQqZ0KsXDcBrydQrrjwTkTrG8ltx/Fax0i9i+L198m40VHYqX3zNKiPU/1tR1IAUCVaLBKhNkD6Fk0CpCQvGiCdruIMsHor6RQiGDcltYbU2KJ2309aSDicJhHXgdNopCqr3EuOQq52INRruleVeN0tiGouJANin4EJwBkKOAMBJiR56TAJyRi4FlxLibhWolL0bjLhYDAkLdIwhO5SLfoDOFNNyE7XPFXrGBxXUTJbvyOVgFgMhsZ3yqnXiaDVqDWL6HThXHKEvIYqZao0q1E0TbshJx3c43RaRAowv6wanzJKd0hJpCeOKSXp+/Q5VqTfJk1Gb6MJlVWNKK3vRLpykSWfOztdo20atJ5nm+0Yziuo82YijE46XW7sLzhLny8FXq2CNYncgrGUhQGLIkqxa/IDJBYacTySGr1oz/FLDAXZOU/hNNUTqSoxz4aqZz5XQfcgUD8ZovyDM5CNKqUcOuGO3gSNP4geEyzrelNim/hf8LKb3UBClowIk57OxNIyWK8HHwcBDrSP+uCRB96fAF+dQLzc2tUbj27jsJabtZnYRCbUndVZYFRXwVR6iwFU/u26RHyEgOwP0jdwu9EnkBAaNbmKIDCkyyaGprWBMhjU5JRcjiX5AUWxITq8qjo8uy5at1+LsMpIR8Y4Om9+FVgECA9gApAc4BHAJIfXiSAZiOxwCf8HpxBcdYhSZwGl0FggKBKktD20Q0qxySCEHA7hHj5IUR7XBXddmqS0XYOtFdKfcUnVWlxVVIluL/l7MIQzVSZzym4PcjAEGwzJ2ToMKRqa0R8xy19He0AxTxHRWECutkl/NRgSceTC6L+ciYbRfoz13rHSKdl0VvLRSadSZBynhMn2Z2ychudCh6mKimMi9XZxA+OQcZB6yLLPK+OMoqWtVcSdLrWFsSNhcUw6OZakh41A3Y6k7cF5LTQ7O4cLvvT8YkXcagFCwGk26capvnTu/n1wD+xH40/+GpPPxCi/sAJx+gykqsrZrIvyWIwp8zbmgdaY7Fy5Xc5uQs1BQIRG9aESVhpHN+/TT+rx0jJYpw8eCHhdidJiAOmOSTntBKwKKeZ74BP13Mot5jiJT0qeZsKqxrFLWekt6yYdBKRVWVqhSEe3B6y26alTT3p2REfbBKjzCzUJaC0OGRqSL4yecEUQGA0Q81wl8pWJjgUWyZGknenccACDKY7hJMPZf/YaLL7zRyA5g3QAyRmGkxzCZYAk0hNVqPw9qrmQnGFww1FIj0O4HE57QMRotQ90espgkErqMRxS5Mpz4UxPQXa69JkZDklDJAVEr0ftKzLXCbBSqk7au4ZXq5SiU93Oqd2FoOUAyP4AbN803NkD1B27VE6Ijk0qGKNeXFGMeO4MWKUMuI7p4cYch9y/Z6YhOp0Re4WxehpdRq3IKiuVwBsN0hzp9zMVZyk3aWSipBch0v5ByvNI6c2yVW1as6VWgGx36PMDJCkri9zYpo7Z7+WentOi9HzHUJCd8xlSYv7N1wNQT5yOQzdelyaG+iMvAiurGLz+ZvDuALLXUyZn59Y+wmAtPxtbP2D56uibhu31oydze7Jmvp+kVaRIxKMAEEU06bY7cLoBGs+00T1chtMdJjez7fTaWQPM92mSjEdbYnDfB29O0MSH0Zy/2caYMuOUr4dKK8k4Jg+YOKZmnfqGG8fkj6NSJiYSoK9tVuyqy2ct7xciRdxEhihipa8bTQC8XoN76CD44YNwDx8CE4DwAekAfluiNhfBb8coL0WISwCL6D3hATyUkA7pdYxOR4LsA6SE9Bx4p1sQExWgXAJTvdbAOWSvDzlQhoeCKqhkt0+Tv+/DaTbBHIeiennnWHni2BoM0/2aMyI1miw0JyBWWvRQUCoBK6sQ7Y5Z3pBQpa3SKSqn0QBcB87MNAmUSxQ50qktMiOMqB3IBj6jKULluub6il7PpFbMdpjqD6fGZWtJLlZhclIV55jULOPM9K8yUZfseuq+xyfq0HYLKZE+QJ8V5Z1jP3TYv9WKye9duucU2FkUV3GbsJbQeK331vLqYftmsHRrCPfIYWokaU26rFw21v3Vvz0JceIUfVkjy41VE55z+bKudRPNVmchuVHofRpTLpMOAE0e1QpNDvomonww7G3IMAKfX8Fgtoq4pNYtlcB1T7Gd9Mhh1FdHqFJVLcodIY6xWPfJOmXYaOkusk7UOkoj+n2I5RXlFh2aaJkpVbdTHTpqo912rQnULmk224gT4sR8L0kdCXpdBiGF9vsDyGYDlb/6DnhIaaq4xCBcKikv/c1TEEqQzGLA7wjwUMJvheCBAI8EhO+ABzHAAOFyhM0ygiOTAGOQ1RKk6yR9uzTxUIRMxjGd//5AWfqHJno1Et0BSDTsOEYIDocn5DoWRFi5ei1U1WTlEuSRA9SCxXHIsLFcSpXnyyCAGA4Qr6zQOoMhMNWk9OJqhwTLQlXNhRERVPWZTwmPkYnu2Z8LIDGLtMwJAZgIFF3ktJ/OuLToxQL7/Nj3EeOdM8ZIkU+Sl5JOAeuImV0gAMA8HNj3MKYqFbXuS2185w82Ayblln8K5KMgO9uElIfOOayrf2zIlRYmvuWRbmdmCnxmmibj5RXE8wtY+rnXoP2a40AYQgzpCy501U+m2eQ5Yb0IT2pRNvq/1rRoIafnAuUSRH+QhKL1ezonH0XKZThG5YUWJr+/CtYdkKbF4XDqte1L1a1xbDIKIVY7YBMN8Okp1ZQ00eDIMIRot8freazzo9svGP2M9bQohUiR06yviiFL1nZTIXsQ4TE370xlWNZlG6CwvhZKM65Ih04/xjFYt4f4lqtRXhZwhpSm6h500NvvYPW2ayFdoLwcg8dA+XQfXptsA3g/SqqzOENcUtvmAA8EtQDpDcH6QzJa7PUhez3yUYoFRU3s8QtJfcO0F8/Ssmmia45dt01Rn33EwlT+weGIlUMzAGrGOtkEVttg/QDssmNJKbmqegOoCo35fqLZ6nQhOl2g3TViZNntKTfqiEro49iQeEM6rain3ZLAvk6i24MUlgO6JkQqUqWjcvb32Yic9zqqs5MRD+vhgByQkwqlcSRPBuTlxEqlxCAwVilf36PUroo86/vNCCG1UvB7ks4q0lg7hoLsbDPyCE+WxLye34kf8396TXLkNBqIV1Yw+1AXcjBE/PyLEEsrVIqrwu4HvnYW/Z9bxos/fSXc2QOpSS0lvNzsF9bS4qSwAX8d83r2RqH/dl04L7sS7pHD9OTe65NIt1RKRXvgOMDzpxA1SpDVEkRDdUSfnqT00XaHl3O2JYKAJuIwNBMuAJNyyDPmM9vKbE+POUs+GecYCaNb62b1PqnX7Rtz+s3UWIy3D+M0qdvXzVT9SEU0Y2AYwDuxiPrzfdRPRnACSUJkIRFMMDgDCb8do3o6gHz423DnVyEe/R6cZ09BOhzlU2247QA8lPBWFRnklOaSZY+iLYMhRLtNQmmtp4kFNRFV4xPDAWS3n6Q5AcTdHpXE6zSHinhlzQYpBUjaHTlU16nbhzy7CDQngP4ALAjBD80mPdLsJ31FUJ2JhkmB2OX5bLJJ50wkuhrGeTr6Zpf/Z78fFolNERv9mqX9kcNhOnUFpPtm7Sbs9M5OEQF9nMz6bgyH5jOviZ7+/Bu94HAIVi6ZCsKUNm44TCr2rJR7NtKam9Laa1JZYFtQkJ0dwHoRnvvFfWMjAoYYcfXk73I8+XtXYOlnX0mhdkmheV4uAf0BKl6I/d8aIrz6SHpDKjoBYPtuiDlfenNTsPQ6qRSWPbGGEdDtIZombxfdk0gfr0lH+B5ko4b4hivQPVJC9/Im+GILveNTCC/ZBzbZhFOvUaRkB48NUkB0uhCtdjLhrIec8ZDGxk3OjVmUmSoQHZEzk4hJc7hGswHAaDz0vuyeSYbsZkTRRjtlPclqLQhzXSKdJuoTQA4DyHYH7tk2vHYMSMDvSDROhHCGgNeT8Od78Fb6cI8cRnhwAvzmazG8+TJIl0F6DsLJEqW0yg5YJOG0emARVWORo7MDZ98MtYhQkZG41ULc6QJQZoX62IZDOPU6RXUkOTzbkSrTJFRdM6OdEYJaBbgu2P4ZoFYBO7CPROCVMpWiDwMw16Vt6BSRw6Hdqul8DMGnJuEePUIRgmoFUml9tOmi+RxnPvPrRlbHiPw1hG1VYEf18h4odgPZByGb/GwTUu7RQPL5t6rPTJrKTu2rXn2sXksiZfY9UBMcHSXj1N/PfI/OA1Kjq7G28nMu+OQnP4nLLrsM5XIZt956Kx566KE1l7/vvvtw7bXXolwu48Ybb8TnP//5scu+613vAmMMH//4x89tcNuEguxsI8alo8bBvfyysZGgeLVNT5fDCHHgYP/bngfbN003WNcFLj2Mpz4yjf2VLvyHfgDnoe8b51kNXRmVykNvFuvdxNRN19wsrJtgSqyp0zbDAN7cKuTSCrQHiwwCCtXXKqYTdXigjjO31uD2BPzVCLLTxen/l4fWFWXE+ybAZqbBMjqmbUF2olI32Ljb29j5yNkOAMRLKyMRGJsomidMO82hBcqMWZO5TBp9Ks8ZMJ6kyPTYx4mjrRJdXq/R+45qyOp7Km3kUcRlMIS/0EV1IUbjT74B76++iYlPP4j6vX8N8a3HwU+eRXx0H6TLMTxQQ1x2EJcdDPdX4T34ffjzXXL8HsZgsYT8wXNUjeU4QKUCGYaqQaqg42KJGRwUcRbDAWQQIO50EHc6qYqb1GQnEw2V6aHFOWlpAIiTp4ngDIZArUpVYA4HBkOwmWlqFNmo07GrBw3WqFNvrVIJYmkZ8cFpMn1s1IlAOQ45f2uxOmOKrFveMHqsVgTBTlflfVYYZ4nxplV5Zb5P2ssnSzi2G9kIZXY/dpn2juw+fc5ShNZYPlB0hpdLJhWpTSlHIstqvIZACpnSQ+l9muX3AnuQxrr33ntx11134e6778ajjz6Km266Cbfffjvm5+dzl//617+Ot7zlLXjHO96Bb37zm7jjjjtwxx134Dvf+c7Isn/2Z3+Gv/7rv8bhw4c3P7BtRkF29hDRM8+Nf9M86TE4Z308+deXofuy/VROGQuwIIZ4noS9T33wRjz/q7eA75tO1rcnN2BzlUz2ctaNZeQ9xs1NxdaM2NEGE63gpOOQQyqvZp5LNyclAEYYqeokSnMIj8MZArUv/C2Gkx7YzBSC6RityxlWr65DTlTB7E7GO3TDNdGptW7qG9g3r9eIqKrScBO5yaag7M1qcbn22FHuw9bgyDdHER1TxaK1IpYWSI/T+JD4PuB5RBhLJRNJpOW0Bw6DdDmcXgz38EEizlYlXby4BPnQdxCXHIroMFAUZxAj+uFrISoenBcX4PQCEj9LAXge5Nw80O8jXlpGvLJCnjW6lB+AGAzNhKQr1pjrUQrX2n82XatTHCYqIARFraIIfLJpRMryzFmIqQmIfU3Iw/shFxbBZqYQzZ+liijtjlwpJ+X6/T74E89BVH2gP4C4ZBbiskNgJd8092W+T93iLTJjTO+saJuZxO20ppqIGVeCbR3FsSrEjNhfSNInZfRZ24JxkRo7irQWAdrqvrMp3DgmR2z7e2I9DNh+PLYIWX8OjAdYtqKyUoGpXrTSYYaI7kDE6nzFb//2b+Od73wn3v72t+NlL3sZ7rnnHlSrVfzhH/5h7vK/8zu/gze84Q143/veh+uuuw6/9Vu/hVtuuQWf+MQnUsudPHkSv/RLv4RPf/rT8Lwd1lluABf/lTxPsV4U6H5xHyAFnLOrmP42cPhrEWrfnU9y9b0+9v0tcOo/X4FDD0YIJxQxajTSG1JPMptqf5C5qY11EdapMnsStaIhI+6m+ilqSJ2ttXeGntC0cRuEhNsJUVkUaP/4zWASeOath8ADjku/2ENYYehcMQF4niEQOwFzE7QJ45jzQAukU1AapiS2UoFxhTUCZWmeUAEYrxdTfaX8Y4yZoJCqfYE7cpO3U1S5ZclSEGloTpDgW/nZIIooUlGtqhJwAbG0DHAHLIhQevwkRS0cByKMwH0f7oH9AACnOQHJQaQgJqLDYoG4xMF7AaJj+yF8IrZ83wzE/FkyfBsMTXWVGA4QdzpJ/ys7jef7CflS0RQdwTRkLkewLoUkIXwYJh3jtfvxwQO0kBAQFQ84fhRiskEeVocPAVLSOQrJrwiNOtyjR4BLD0N883uQnS74/ArYD56nNGevB9kfIFpcNAJq7vvQnlIiCEb0OPo7Yzsl67RuSsPDePr4bJ+Z7SI5mYeU7MNOauIfN/lvdSxj9IDM9ZLqTv2/IrOplLCVJh7x/AJSy3JFXgGkCOWGx7aD2K401urqaupnaLlF2wiCAI888ghuu+028xrnHLfddhsefPDB3HUefPDB1PIAcPvtt6eWF0LgZ3/2Z/G+970P119//RbPyvagIDvnO4IQMw8vovpCG3JxGat3vgKn3nINTt55GSae7mH1Uoba0yson2HovOIocOnh3El5W/rn5GkEMk98uWWherLmjNIl+6eBSoXe0hO1pMlIRhHQH8A9tYjmI3No/s1JVJ9rY+pxgf2PAAs/VEV1IQYTICt4gDxZtlO/s53QE4SbNDHMNhYcKUc36QHVuFKXVEeRMmbkqQiPjtRovVPWY0kTXeY4lCrkVGGEKDZpHjkcUgXVygqlAXwf0XPPQz71AqLTc5CtVUOgRBAgmj9L/19yCE4g4AQCfiuE+9D3wUMBrxNBVH24J87CWe4APSqr54065Gqbjk3pJzR5sdtaAEhKhoNQueByavPgcEMcnXrdRLZsEsl9H7xSNkQEJZ8IHue0fqsLPrcE5+Qi2NwC2InTQHMCct8kRL8P2R9AzM0T8ej2SO+zQr3n4lYL0clTJIZVxnWi31djEimSbPQnOlpga140ych4Jun3pK5gRELotEdMtnT6XJGd7HM/ixvaED/3CKt1XrJjSRkI5mih9D1GG1Cabcikq7z5/GevBVunr9i4Qo2dxDalsY4dO4Zms2l+PvzhD+fubmFhAXEcY3Z2NvX67Ows5uby+xHOzc2tu/y//bf/Fq7r4p//83++iYPfWRTtInYZr+d3bljTo8vZnc6kcb6d+uYiBv/PfsQOsHJNFXEFePyfTeHaD36XND0rFFLfli9oTmQgBXOTStInJm2FxLQrtZzjAGeXaPLRxl8uGbjJ/oAmo0bdlKDLThdsooba6QCty0uon45RPdEhV+VyibwlHIcmG8ZHK6S28el3XRO3TBWUufl6LolYB5ZhHJA+PyzxEUnWtzQFnG7szGWQQpB/iGr/YG7sKlJjC1jNvvxyYqxWqYALgejsApjr0W/HgdMl914+NYl4YRFOswnR6ZDRo3I4jpdbcK6/CmwQIn72ecTf+j7Ya28BGAApIW66GrwfggcRoK6RrJYQP/0snMlJ0uj4HuLlFrk+a4M3W5Cq0g8iCMAcFQlxlD6LJ005U5OfbgiqGtMijsGkSw7kYQj4PrDaJgHr/imwkgd0u1T6/bIr4Jw8i3imDuf0EpzJSWo8yjjc/TXIfh9sGAKuC/eaKyFdDvnMCURnFyiS6rlkU1ApkyFixqwu+znKTt5CNbnUzVlFEBv/IK1d0udFBHGaUGwllWVtJ/uQYlpmWO+nXtdpJMvT6ZyRlyJm1BfN1qIlLWpG12O+T33erHGPtHBBQvztY8kea/59bmuHuFFsV7uIEydOpBqBlrQz9y7gkUcewe/8zu/g0UcfBWM7E3U/F5yHj8IXPzbrxyODgJyThQTaXRz842/B7wDLLwOCqRgsYoAQiJ9/kUzQNqPPyYMlitzUOC2dgv2/2WYcA1KVga606IauNDrgLDEcDAISKvcHNKmfWYT//RdRXhKIfYa46oGF6qZnPE3UE7sqLdWi7HM2VRw9uHNenlerVGFm6QP0DVdjJJTOmUV0bL8WDi2gheOQgNb3oauHTHWJjvRUqLM5K5fo/4kJQMSAcrLm5ZJpFSH6fbrmWrgcx3AuPQZ+7DClnlSlFACIWhnshmvAXnUjeBDDXR3C6QZEdAYB5NPP0Wmo+GBhDOe6q814ICQ16VRpKR0FkXFM5EGRVl4qJ1U36jMiVlqIWy3IMKJUmtXyQsbpZpwyjExEDEFAEaIJSvOKqg+5bxq8VoXTGUDONOGcOEvbUQ7W/OXXQU41IC89RK+vKBdnAfAD1LYFUoIxTo0kO13yZ1LRymykCkBKWGuXUev3xHCQJh5WOtiU12cjDnmT80ZgpWjtyIyt+bI1R/ZvvU5uSf1mxmCvCyS6Ga29su8pMmOzYO1DDIZmXTulnhJ2W+tlz3F2HOdllHgTmJiYSP2MIzv79u2D4zg4c+ZM6vUzZ87g4MGDuescPHhwzeX/z//5P5ifn8cll1wC13Xhui6ef/55/Mqv/Aouu+yyrR/cOeLCvqIvAdwv7jOhcuZ7kBN1hLdcBeEAtZMM03/roLTIqRxWh7jXi0BsECnfl7ztWTco+yYxIsLUEQtlMChFUn0j45jEyYwboSrCkCYo5Y8hhwHgeWh85ywq8wF4EIMvd5OO6oYMWDdsPZHXa2REuFUCqI93k9tgSpgtuj1zPgCYiW7E/l+dQzBmRN0AksiN1iDE1HOM1apgs/tJcKmIC6/XiORUq1TaXSnTT6MOubAIABDLK5BCklam11OGgjT5Rc88ryYagcHl+xA98ZQhIM61V1IJ+fOnwAcBeC+A0xmC9wLqadbqAv0B+P59wMkzYGFMbSPCiPxtFEHTnaiTSCCJRsGTbuFiOCCfHBX1E6sdUwXFyiWIlurSLqVJ3+lIgIxjsmoIQrBKBej26TNXrwGxBG8PEBxUxOeFk2DzS4gum6XGpJzBveYK8F4AxBLSdyGm62ATddrOGSJFKJfAGnXErVVjIaDHwBzHpEjsidcmNgASTUq2n5b+bQuxs9VF9u/s53T8BzL1O6t3sj+jqe+3Pa4MAVl3nxtBhoAYgmvpnLIRJENqcqocjQ9VZh96rCMPYuv9vVvY5Wos3/fxile8Ag888IB5TQiBBx54AK9+9atz13n1q1+dWh4A7r//frP8z/7sz+Jb3/oWHnvsMfNz+PBhvO9978OXvvSlzQ1wG1GksfYAzHE2lc7SiNttoHk5ukdKWL4lxKWfYwgmHPQYMxoYAKNf8k0Njo/ewDZwIyOCI3JvFubmCOuG5XCi2rGq0ImpY7XjN1X3b9XagLlA1adoTxzDbVfIq8V1SHAaKcfoUglSCsh+nxoq+rpBJDVI5Z5LTrgq7XPOOMd1ZWBpD+y0lYVUU0vtJqyqsKRKdSCOzf1MhhGdB9ehcuh2h5abmUb83PMAAPfSY3Q+w5BSQLP7gU4XvFaF9CNjtgYpwCpluPUaomuOQUYx+CACkxLx33sFRCjgVUqQz50AaygX424fLAwhllfApiZNRVc0N09Ec/YAEEZAtQQENOro5Gm401PkpyMFpW2UMFmG1F/KPXQQ8dlFAERq3KlJyNYqERzdbNN0FydxtQxC8znQbtAyDCmiValA9vv0fyzAuj2AO/AXukClDA5AHNpPDUtXWoqUSGBpBczz6Inw1Bki6ZzEznJxmSKRLCGjAKiCTRcEmI+MBGB/J+P0tZeJf4793U19j7PpKkvbk3p9M7CIz4hWRiTbTSK16bTXmveZc4iE2vsE6LOeLSEfaR9hjSe1DKxrkhlLrnHguY57B7DbncvvuusuvO1tb8MrX/lKvOpVr8LHP/5xdLtdvP3tbwcAvPWtb8WRI0eM7uc973kPXvva1+KjH/0o3vSmN+Gzn/0sHn74Yfze7/0eAGBmZgYzMzOpfXieh4MHD+Kaa67Z3YOzUJCdXcZW2krwUhnsO0/DPXg9Dj3gYPUSDiaAiWck4hMvbs8Az/XLrm5WjCdPYkxnwcyN2bP2wVVkRk0eKlxPFVbUK0gGIZEWzgDfh5yeAG8PgNYqPaFrfY6QkJx0LPzaK0hI2qgBi8uQ+yapNUCtSoLYdluNk6WjKeOOP68yZb1zlFnGRHWy+8g8OYogoNRHbGkRtBDTdaE9iZgicMz3qJdVtUK6ICnAZvdDnDhFDTSbKnLx4mnwIwdp/eUVACDNjO8bouFMTyG++hKIsgOnF4K3h2DdHpyqD1FS0TOXU8sS1b5EVktAJIDlFdW/SiKePwtIQemk1VVKQwJUei4E3AP7IMOQyKfy0dHglTJkGCI+3QKvVBKhcGsVzuQkGRG6dJyitUrpN8chYqhEy7pnGSu5VFElBAmja1WKGi0sgh2ahVxcgpw/S0RICvBOH3J5hZyRez3SvglJFVnzi6Q92jcJvHiGUoWNOtDvA0IkKSZ1vfIiEPqzZqd4k2pFGI2K3TJEd7LXka7UZ2srkzJLPv/2ayYSZZOEnM+7SWfpY90ugpCJnNI+1Hj1kEzampkx63Hoz5QdKc1NV60VsbnA01fngje/+c04e/YsPvShD2Fubg4333wzvvjFLxoR8gsvvABuWVO85jWvwWc+8xn82q/9Gj74wQ/iqquuwuc+9znccMMNe3UIG0JBdi4giOEA7qFLUX9iGavXT4NHQG0uQv2JJYjtuvFsZDIfs14qTK8Fo/bNRt2Y9A1FBAFpHYbDpJ3BMABYCXK1TU/tvgfZ6SK++hK4y11ApbWMOJeriiUBEud2+tQ9fKqB6Jqj6B0so3ayT72bOmWwgDxfdGm3STdocsHTTse2cV3ix7HJcyRHnyTzWjwYMaYUqqReR8YsIa4WYjrU5FBGEaVZfvA0nH0zlNLxyHQy9l3Sz7wYInrmOTiTk2DTk9RVfqJB5dg6qtIfAN/4NvB3b4Z0HbBhAHFmAa7rIn7+BNhN15IovN0hF+IwAltuQxyYpJRVGAKMwZmeogqmOIZY7YBPACwmjRCGARk0Kl0ZK5XAOZkAyjimyKVOaTXq4NNTkP0+xGCIaGmZ+iNJaXRKkJIInEqLUmk8RXy441DH80qZIkKrHXO9xcnTlPar16gdyPGjkABYVEd8YALOqg8srSC48VL4z8zTZ7JWJWNE1eVcnJkHP3wQ4sTJJMrAkk7d2Yo7fc2zREgvZx4SLCsCI7Bd6zt5DhEUTQ40gUiZWaoxmO+q2r/tRDwq7t1CdMmGFj3r8vIoBOCkCI4mWfocZ3WFWfNBIHNfXIvMZCNle5LGkuZ+cc7rnwPe/e53493vfnfue1/5yldGXrvzzjtx550bf2h/7rnnzmlc24mXHo09D7AZl2UNp9EAcz0MrtyP1k3TaD46B68n4fYEuldPm+XyRJEGG/nybkGgl+1nY0o/LV2G9h1BFBm/CyNC9T0qPQ8CI2SVgyGY50GUHJpsARUNUl9qIWGcmAdDBMf3gx2aRdwow13po32Uo3VVVWlgOOlaJupgtQr4RAOsVqFJt1IGL5fA6jVy0y2XyLBQnRNWLhmCYp6Kx5XaZquysnqDTLRo5ImTJSTHjjzpNBYAQPmKMHuCmp2hiM/0JKTLwcIY4vFn4Fx+GaWz1PjFaodEvmpbvFQm4vgjN1KaJ4ghSz5Fg9R15fMrkI5DHcA5Iwfi4RD8zDLk9IQ5vzKMAMYQd3uQUYh4aZnK1DtdSu8EAZx6naIyUUQaHjVhcd8HpKC+aVJSS5FG3boOklyOXSV0NudQlR/3++C1KvgEpdlYtaIiSqTp0ZVNzPcB14HodMEmGmBL1GxW7GsinCgBrTbi44cQ+5zsEELqCC/nztK+mlTlIucXjBA8FZHI2AKk2qhYr2dh9Cd2+nirUZz0Dkb2b48v9br2tlH7H6d523Illh6XHclU3wkt2AaQMs60SY99PNnUln0vykX2/GZT8HuQ0tqrdhEvBRSRnQsEMorgXHkZxCCCcD2s/PBBLN4I8NBFb5ajwjImZeOwzpfYDqPnrgvkv5cJeWe3wRwfYpiIMEUYgXFG6YrBkFpGqGgGRQTq5rjR68PtBGDtXup8aIdcTQC4SlUNLp1C+xIPnSM1MAFEXapWg+dR2bKIgapKeXS6Ji0Ez1MaIOqSjFgYh2epqj1012uwRDsw9lxqbxSlPUjpMSyNU6oU2aQpVJWRVbopjWuuMgMESKvFAfbD1yPmHO4whJibB6YmyDAvjhE9+TR4qQx+2VHIs4vmKV30enAP7Idod+BMTkEMI/AXlbfMoQNEJF2HyrenGpAPfxvyh64D6w2pgi6OEZ08Bafbg5SUkpS9HonDfZ/+H1LfKNFum8kpVpEpGcdgGSGp02wSoVCRIAyGJLSulEmbo4TrmihBKBdpU4EVgsXqcxpTDy7GGZGqeg1iaQWy1wM4I8+fqQbYHIm2+XIHruegd/MxlM4OUPneafrMSEnrAABj1EzUbnVifSdkpInBKMGxkVfWrf+2t7etk24OaRnRt6jPF5Gu0eijIeLWA4x1IJsbazZFDCCV6mZeomNTxQha96fb4MjYOgae9ONL+fDkCbvzxpA3Pq1Z2oIMssD5gSKyc4FA9Pv0JPm1xzD5p38L4THEZYnWFdRWQVfqrCcaXM8tdF2r9HWqP3JFlVpom1lHlwoDSNI2+jgG1MFY/89fmCMTvOUWZH9AAlXO02Fbz4N/qgXJARYDPAZ4AAwngahZhmxUgLIPsa+JwdEmon11VfbOk4olld4gN2FVLcWUuZnn0t9WlRrjLGVmlz12PeHZZcO514hZPj4mpWb91qmwOLnZA4AMqCIqrnqIKy5kyaNIVXcAp9WHe/gg3EuOQgwHiJ54Kt20EkA0f5ZIy/wCeKsHTJHWJ378Kdq+nthPnoF75eXoXtYAen3qjg7AqdfJiLDToQ7lUBGWiTpFwyzCJyzhrm3rDylIPxQEEN2eKRWHEJSmC6hZJ7XLUJ81LdbW9gW6usnzqGWD71EVH+fKdZh6JvHpSYpOBSHpuQIiRNGlByDrFbhPvojqw8+StUF/ANnvA9UKVV297LLE/wbjJ3xhtS1IXs4X02aXGTEL3Obogk5R2SlmE92xiIF9bCOEbSMpnozmbOS9vPWthylbmGzO11peOFKkvj/meDYwxtztpTa9i+GSXa7GeimhIDvnOWwxc7y0DIAiGG5PQFRjBBM0mTuz+ze0vQ1Vao2rwlqvpDUVmRBJugcqKjFuHSgHVFV1BCSRG6H8UUSnC7HSIh2PLl8WIonucKpgkkvLcAIBHgEsAvpHBKQD8EAgapYhKh7imo+o5sBZ7dOEFoaQK6skfBYxpcmGqrUAZ2nBMOfKzdeqwlEtK7KeHranTnIKR5809XIpTyBBWhRmpYbs86pThKLXU+kVUJuGmo/wFVchPDgBtriM6OQpyGXyh+HVKkSvN9IwVhOx6JnnIc8skHne5ZeSmHdqkqIyB/Yh2tdA7bk2Bi87YiJebHoSTqORlEfriWYwVCaRLJVatUus7YlQr8vrNbr2vk8arHqNtDxSQrQ7tN3hkKI8YUSESqfBZqYBIagNhZBUdu84tLzvUX8soQTMzQng9Fmg0wUmGmBRDNbpU3l+HIO/eIaE8kLS9XdduE+fgrzyGDVM5Xx0IrcjAealxIIhRSTs6z/Oq2a7oci5bkmSKnE3u7ciltmHmGwFmB5vdje21keTtzEPUCPnx7r32I7dZnnVhsN8z8Y8ZJixjTuX2ShUDvkaEXHvApjY+k+BfBRk50IC43Cuvxqrf/dKTPzfZ+F0HcRVAXlrC8+/7bLt2Uf2ZrbRL3vOeqknxTxbdutmoytrWKViunHL4ZBEtSrNJINQlVu7YFUVganXaFJjjITLpRKisoOJZ/vgIcD7HF4PiGouJGcIJytwOkM4AwE2JO8X1qAoBDgHun3I5RZFGKBurr5HP7ozeJW6s3MllOW1qjqcdCrCLjXPpqr0pJM6V/p9NRExzkHlzkS4yEE5xySRMTAhwSQQV13EPkdUU5ENKMsCIGltoHQQ7v59I9cjXllB9PSzkPMLiDsdRM+fgHPkEBDFcOdWwBZbKM210b/pEohDM9Q/SxsUKkdkpkTjot83LRDscWvyk0rlaAO7kk/nOYroWp48RWNurSZd2hmD6PWMM7WO6hCp8em1OCYNUbtD10v9LVbblKZjDEyRIzm/AP7EC5BLK1R6Xq+RjUEYIr72UqA/IFI8GIK/cIZEzYycrE30wWreCS1UzhgIZq+/OW5Lh7KjsB9iFFHQUR5gNPo0zgF6ze1rAbOOtOUcZ9Yfxyyvo5vWNvR3RAwHlBbVgm7XSndZx7Nhoph5MBs9zEQDtF40vMCFgYLsnOdICZmlAFvpoPZ8F49/8HIIV8I/3EX/xQYO/5/++uHhjSD79LapqiPr5p9Tap2NKKRWHZJux/R28n2wSgWs5NMkFwtyu51q0vK9PvU6qpTJ3M33TNrLXwnAhxHcAeD2gYnnIvhf+y6CKZ/0LbEEDwSCw03Ek7RtGYZArQrUq2DNCXpyL5VoEjOGcJL+r1SorJlzKlW2IxdWOiD1NJx3zJoI6Ju+nhDjmCbyMEql9vQ2dSrLVABNNuG2BpAM8Bb68Do0IYQ3X7HmOY/OLox9L2634TQacPfPIHrhRWC5hei55yGWlsHaPTiDGHxxlcZ9cAZ8Zhp8/z7w5gR4cwJiMKR9M07XhrMR6/9s5ICVSpC9PpERIYAghHtgP4nzfR+y11fEk8533O3RNUcSTSAS5CXaKsCkvuRwSNd0coLe6w8gpyeJDAFEtCplcooWks7rM6coldbuEMEx5F1FKh3HlL9niai+VqkooCJCtteL0fbsgiA2FcWxOoNnzUg35KGTo3/JfpZt0bCd/sumgg3hsqJlUkhylLYjaEp/ZfZvi5vtB4pz1Q5Z+94TklOksXYMBdm5QKBvSqu3HkPrmjoOfxVgMUNwqob6Mxx8GMFpTuTegDaFjND4XMO42i6fOQ499asJyr3kKHmmZPYp4xii10O83ILodGmCD0OKTrjK50U9rQOg91dW6akbINIjSV/jvriA1avqOPi/zmLqCYHqiQ7iV1xD0QaXQ/guBjMeukfLcJbawHBIpnjdHuB5EEvLiDsdVRLPzQ2WVcpAqYTo0CTguVRd1OsBStuTa2WvJ4+MhiAlpMxG0lI3/PTEki3nhxSQKy1IxuAMIkTNEpzvPYfKUwvgoQCfqMO95Og5Xce43SZND2hyd48cpmjLkRn4zy9AzC8gev4E6V58jzxpGEe83KK2CUFAFVmdbpLOAJIu4GriN2m/IaWoZH+AaGGJUpedLuJOF6xUIiF7TC1HICQR31ioDvCC+lIpMbloqz5Y2lxSSvCZaVXRpoTnrgv53AkiuUIRXlXhxlTTUDkMKIpYKVOatD8wqVbTkNVy7DXtHzTBV1455vLmGN1lS7+3PXWS2Z4eq51uSguUkZAQ+3OdSTNlNjqSkstGRVJ2DnmRTjttJAVkFBo9HK9WTTd4874VeTEE8hzP3YjB525E2vLGUVRj7RiKaqwLAGuVqb/2//0R9GYZnOfmaBJRT8ypsPlWsJH1c/LfjLOUN4eZrJdWwGamgJWV/E3pEvQgNP2QtM4CoIiObm1gCBBj9ISv2hAAQHkhwtlX70P9VAT21AmwGy6H8DiqL7YR1X1MPLEC6TlAtwd5YJqiNCF1uOYHD4CdXaR0hvJqQUAOxHAdBE0fTrsGnFkgV+aMI2vWCdecxxECxMlwz1G/VQrLRCmCPpjUZCC/dFkKqhTiCyuIj5Brqbz8COJHvwt3eATwfcQHphBfMQsWC/CvfhPO9BSlha6+AmxpBdGZ+ZFrkCqfdj1qmNlqgVer6B8oofHUAKLfh3voIKInn4a7f1/qM+fU62C1KqIz86mO3QClsYRVQcUcIkA6uuBMToJFIbWLKJUBKUhrVCmnTAS1izIcnhhQqvRivNwiHxnXJdIaCVPNxZTeCGUVyTlzlv4PI8jDB4BT80AQAwtLRKo7XSI+iiDoVIoUkYlcyV6YTqUwMtg0pMLWotiGfMDod3W7IzxSpK5prhYlZ9+2n45BVptnr2NtM7cU3Dr21DFmUkrZiiqm2m/Ah/ne2+dOe09lx5+L7LgtEXYe4dl17JHPzksBBdm5wPG/P//+se9pcXPu5DsGeQ6wG1uRj9w89PY0ZEziX6aiMboCR6+fWO7TxMLrNZrIoghxp0Nds3XZchQBsJo9xrEiDrSN8ostlOZddK6YAKvXENU9+K0IfKEFL6ghrpfhzq1AHN6HwWwNla99H/L4UbDugHQ5TUp1yP7AeHzIwRBMSrj9SchnTpjeViM39BjjI2yZkLtuEErHAEPWdGdzORyOPK7lRpHqVcQVIhVRowT/2qsQ1ymFxZ95ESXHwfCHLkV02ysxLHPwQED4HPySJspf7xtdj7lO9v4svZXoD1B9sQe5fwpsaQWy04V75eVAr08dxxeWyL15cgJiXxNscTmVouC+Y01mFO1j9RqwlIhQpeqZ5TSbiFstuDMziFuUMkNELSVgWRWwlCYqifqIbg8IQurU3pwAhlTVRQ07IyJPKlpgnJPPLBJBiqhfm1BiaJ0Sy2vnIPvpdKWxFbD/zklnJikf7Dhyv/85JCX73c+txNrMfo0WLUmZ2VGZvLFwT5kyavIoJEV1HP0dSpqT8kolv/hh/IA2FP3ZszRWgR1DQXYuYoyLCK3VrsLoTDYq9su5cRjbdkBtw3qKVZVVeVoSk6IRwpAAVvLBGIN7xXGg16c0h/JYMWJFzmjS6vYhjs6CDwKg1YY8NIPaM20EVx/GYMbF5IMnIc4sgHW6VL0mBVavmQCLgfj116P2TBuoV8CGIcRMEywg40NwB+j1wECToLfQAXwfQqfQ1BhyS5HHnCMpJJyJBomrg9D45hhiGkXWRDHq55MSTzocWG7B7w8QXH4ALJaIHn8S7swMghsvRe+1V8MJJCQHJGeoPbUM8cSzwCuuAx7+LtiB/XAuO4L424+veando0cgzi5CPvY4um+6BfVW1zgnx8f2w3lujtKRrRbcZoNSR9cch3RdSM8B+9YTJoUCwBBd3h2NMvBSGfFqmyrIlBeS6FNpO2cqBcY56WiUmFmq1CdA+hv9lOtMNSmS1WhAdLpwpichllYgTs5BbRBYaVFUbXoK4tQcWJm2Z8wtg4CIqO5ZliUuKhoJqxprJNLHLCdijHmo2IzIdiuwor+6JUPe2MeOa40xjphvSgEwT2mEMtvUY7EiPlLwlL4LAF2jKFJ981SKsFZN7AccBzIONn7+cqrKTBsZ6xh2G1tNRRVprPEoyM5LEHkkaIQAbSQcnLecLhW1IhhJmwUVFh8Ozft2ZY6eCIwuA6DfUWxKhHkQUqVMV4lV7ZYKUoDPLVBj0XaHBGmcwwvqmHjoBFBV7ro16puFShndWQ4WA1NPhmBSgg1DxI0KpMvhnl1OGm1KSeLUIAQETab62PRNcmwELSeFxRyHSIqUNMlWyqpUm8re83xaxj11syiCPDAN6VCptGQAAyClgLfQRX//FHgoUfveWYjTZxD3ehRl6YeI4xhipQVxei43RWF35I5ePEnux9OTEA6AehXR40/C2TdJHcLrNWpDsbRC6aSlDmSjAt7qIjo8Re0sAMRn5gE4JuXKyiUwqy+TTnHp9JV7YD/ipRXqDadJsCLUWohsInwAdOUehEwiQkwZHnKGeHEpnSoRnHRiAFi3DzEcwPE8kypjytbAtDSxron5vAKm7Ug2YpG0jsh41+R9x+xoy3aTnkwEJyX8tb+femzjiPu4cVnVWLQoS62TdTw2kTA71acjvHr/JlWtpir9ECAFRIt6qI08aOSNcUz6yvydvW7WecJu8p6tiowLsjMWhUC5wHiiM666Sy+z1s1Y599zJn8j5ISl1dD/h5EpDQZA5cLtNmS3ByytqHYS+gmakzBWV285DlVp1SpgqveTbK2CLSyBH5pNKk76fRI+xwKllsTBP3wMlacWIJ94FqJeBhxGN9lKmbp2D4YUOq/XVIPLDmmHlCAy1RZDYcSDJXO+pJBgFeqazXSpsurYnX868+9i5uk5lpAlB04vAo8k4h99BcSVRzE82IA7ECj9xUOQZQ/9/+cGhLf/MJ2Lp56Hc93VEP0+nOkpSvXosQJwr7ycRKIVqlbi1SpEv4/o9Bwm/nYe0WQV7qGD1IWeMSKk+vqeXYSYPwv5g+eAXg/u3ArAOcTCoul9pD8funWFjGOIMIIz1YQzOQn3kGpXMVQ91DSpUGSQlUqIWy3zWdHmizIIVAQwTEiR45CmzffBSiU49Rq48gfS7zPPNVElqZqQUkNaZYZo+Salel8x2i/PVOWZ9/IvaP7rG33/XGBpYrLCYUN09OcvSw42Oh5rWbsqMSse1v+nSJddCq7K0I0WJ062yes1cNVyRFpp8NQY8qDvZ9mCALXOmqm+Ahc8CrJTwCC3/802fNlNN+UcF2Uw8mAxP+qJTz9Nm1LrMCIX6SCgv1VaQXb71CvJcyFWOxD9AcQLJ4FGjVIaKt0ll1ZIfzMxYdoMwHVRPROBXX4M8Uwd8auuQ1z1wCIBZ5mqrFCtACWfWkkIaRqTmtJjwESuNgz9FKlKnlEpA75P2hWrPNksbvmT6P/Ne75PxOz0PI273Ye72EFc5ggnShAuQ+3bZxDd9krE3/0BKvd/C16LhOyi14OoldTkPkC8skKtGbS2ot0hXZVKH+lmmwCA1Tb4kM5P9MRTQBgTgVwlA8BYtYcw6Z12B3KlZdyFRRAYouseOgj3skuTSI/rUhXW/FlqVaGqsLRAmVcqSZ+tyUkiu55Lbtws8fhhKtLFfZ/WL5WRVLeREDTl8KwFzwq6b5shyeZjK6lDu1VhJ4OACJAlsDWfcZss2H9vd9XVehgTjc39bG1FLG1XVyH5/NrHnXzPreiP+m07UI8ty1fNXzdciLGRSHXO9ch1gN5BFNVYO4cijVUAAManYLZl4zzto6Ge4Eyu3TI2A5D0kWJMNfpUT3yRSq34PrikCYyVS5BSgAkOOJyaRjoc8syCSokMwSebkAMyJUO7Q0+DjgN4LqpPnAVabTjTk5AzdQifo3e0hvr3+iRUrZHrsjMXUal7LKgPhdIXjdNdjDzZZ9MTzCOdiCpnJ93IKnm+aG2IKmtmlTLQ68EWvppJQk8KQUC+N4MhIATK9TL4Qgvxi6eAK4/D/cuHiUx6LvDXfwtWKgO3XIu47MKrlBGvrMBpNBC32yZdFM0vpCYJ0e8naZggBF9qA7GAe/llRB4cB5icgDxxyojImUsVdTII6bxLARkl23SaTTqGMAS/6jgAIHr8KUAKk76SUQj3qisg5xcoyqcIkhYXyyAgUbkQRlPDfZ+qdPTnSEcPVd8smb0msMvErc8iZypNmeimGGcQ/cFIdCR1ffX2M8L9vFRh9rOT+rxsJ8bsd8TB2Z74s5/bDY5rpGRdQ3/37UiSqlwD9H0oIRkpx+16DUxF2GQQGnfudc0PNzhm+/ucqnbczQqnohprx1BEdgrgfnEfvhx+dvSNcxQo54aL1ev2U1rKzEyBW3bwJrWAJNQORmZ/vNGgDtiNuhGnsnKJnvi1T08QGE8V2R8AUUT+K70e/d/pUhqs2SDyEgk4vQi1Z1fpPSEhyi76sxRR0JO1/cSfe57GPcmDbqJOvQ72Q1dTZGdA3cMRC2CqSePRxmmMGZ8YVq2mtm+b0dHEwalnlesSETlxhtyPj18KWfKoki0iwuE0m2C1CpxnT4MJCdFuw52ZMSJpPj1JpMdKy2Sf+OPVNhnt6XPQahNxAxn70bVixhdJdHtGkMxcD9z34V5ylNJQngfZ7YEtLkNMlIEfuZEctX0fzsEDcK84jviZ58y1dhoN2jeAaHGRfHy6fWry6rpU8VcqIe72iKCpFiNGO6a8cFKu1TnpnVTn78y5tyfG3Oq4bKokL8KTByuNsyPIbHusENkex2b1Q2uRKb2brH5H7VvqSJy6RjryxpSxqDHY5Mz4G23meNdeNO2YvBc+OwV2DkVkp4DB/eK+NSu1cjFGCDhi8pV6XT1d68iOytubTtiOA9MXKo5NGbH23pFxrFo2ONQZW4l8EUaJfkYbkElhvF6Mb0eJ2hFIZToXz04iqvlweyEQS7CVNlCtQFZL6B2uAgzAQPVjEhJSRMkxbQZaCHnkIPoHqqh2h8lEoiu7jAaBJS7AUlKExHoy1xEHff6pjUZE56DZAISEe2A/TfwLK0SioCqgLNLhnWkiimNEi4tw9++DOLsAsdIaOTZN7HQ5OG1MEZpWm6JrjEO2VuHU64bo6FYetpEc833SVAFwDx+i6rsm/e+cOAsMA8jjRxE//rSJ4jhHD9N58DxlNjkECyMiZKq9BJT/koxjwFdP6jFSvZXs65ZqV6DSKjJGEm1QuiITadRakihUnye9wTENeG2SkI00rBXZ2YxG5hwxdiLPinez4xqHNd7PFf7aHlzW9bANJ8118FQFlkpdpcaaHafeZvbvDXxXx1Zg7aJup6jG2jkUkZ0CKaxlYLgh2OLELKzIjonc6LYBOq3l6/+pEaYMI6qIMVVbQnU9H5AJXBjSJMjIj0cKYQhR6uldjY2iPyr9EUYQp8/AefoU/MWeSsWo1JnrIJyuIqowlBcCmky5VTqcnZA2Qnz0cZY88FhCljzquq47eivNCGPciGw10TEaITtKZBNFj3RLbKIODIaQrVVaJ6SmmtHZxaSfkB5OFEKePmP+1+0jRL+fREAyMERHCoh2GwhDRIuLYGVq2yGHQ0g1KbGSDzTqgOuaflxGA6PcqhHHiE6rjvbtDqLTqgHnyXk4+2aofxdjQH+A+NQZsFoVvFGHMz0FVqYIH6RMUlaOmnTjJHqYRSr9ZAlyTVUQS6rrTGVQNjVlXU+9rN5O6v3NEoe9EsTmpatyIrOp33nrp16yNE3674wQOFvRph2T7f0w3zdEJ+72kgjPuIq2DYwtizzBtvXm+vvYLsht+CmQi4LsFBjB/eK+cyM9G3160k/HSq9j0lk5HbGd5oSJAgBIzMWEBIJQPelHgNVA0jYd0+OSUUgCUiHAy6VEBKnSU2yxBeE7cBY7iA9OQ7ocUdVB4/kBnFXVwZvllOVuRsip14ljCJ9DPvEspOtA1lSri6lm4h2k21P4HpXaa5FwdpOqEs0Ib8MI8DywRh2Y3U/nyXPhHjsMZ6pJ6aP9++DU63BnD4xEJJx6PTnXY3yDnOkpAKAqLc4pOuM6RGBc5XbrOERKKz7gOkYkrNOQzHWJKJ2ZJ5GxqnZjnEHOzoDN7oM4sp+I2qnTwESDvJF8JRZ3XbByiXphWZ5LdsqKVyqGJPNSObcnlS2e1REc7rn5hCSTntKT4sjkmCUO9t95UZvdmkzH7GfEUTkvBW0ToE0QDK3L0emhrNmoreUzXkSW4N80f5WS+q2VS6MPMZljyf5o8mqONe/4UaStLnYUZKfAWGyK8GRvgtm/sxEfq+zUPNVVKjTpM55M3roSijOj32HlUvIkHSnjNyWQFWFEERGV9tGTl2nB0B+oFJkSR2pPnzBE2PQRT9bA+0Py5+lEcF9cAF9eNeHzlFHauYBxsE4fiCWiW6/D6g3T9L8QkGfOgtWqyQSgiIN2FJYi3fVcR3QSJ98BlcSvtsktuNeHbFRIE+Sqc1cqIV5aBlwX0Zl5U2mlz0/c6aTHm3OczHEM4ZHdHuRqG3JpZdRl+LIjVJbeH5i0EPNcxCsrEL0eohdepPLh/oCe3KMYzoH9YIstyJIHFkREoABKvTFGx1JSUb4eVeLJMDLaJilk0rhVl6RrEXw2ypd1C9daqIwmx5xvVZqejfZk/WRGdC7rfV7G6Uq2mwSNGUOuS3L2Z7PCaVuInKPPGXFY1ylCK11IDYBjFcWhiC1yCIl9zdZ6fRzRyUagcgnpLqGoxto5FGSnwJrYUlrLvtlnQv/6b6F0Nlz1t7HLfxnnEMsrgOuATTapnFgJE1HyqepKCormqEocZ6JBZc39QaLTYTxJ4Uhh0lj6PRlGkL0+qt+fh3Q5RK0ECAHvbAdiZoI0JCp9RuPapMvYSBRIwu3HWD1eRlhlEJP09CqjCFKb4EmpSIBMVaQRsbO0OyqyY6DJW7MBMdkgvc4wgHjxFKWT+gPwRiNJIepLNaYSz509kP7/0mNUIaYEwMkxKjGy9kMJQ7ClVcj5BcSLSxDDAZWaK8NJ/Vv0epTiGgYUteEcqJTBekOwzgCi04V7yVHIVjsRbvcHFNWrUmQJXO2bKSPCwZBIYBSlWwmMSTvak70dcbCriaiBaNI8U/s6jZy7PM1N3vcgi7zJdacm3LzJ3CZudoGBTdzGFR6Mw7jl8tJhNoE3ZFImjX8B+h7IjLAcSTRndDf5r5vjBNLb2sh12mno7/tWfgrkoiA7BdbFOae1NNbRthhCom90ZjU1yXR7QH9A+g17GU9N1kIiuOYI2MwUZBiCl8rkySJF0kzUjiypG7e5EXIGrZlxFztgsSqjbrXBgsiYFur1x7aFWO/49TrDAMLj4BFQnY/AV1V0xSYtjkMaISkoqsUZpVmUMR6koMorQaZ3jHNax3HADs0CnIO/eAZyegIQytV6og7nsmOqDDsyaa21EJ2Zhzt7gH4O7CdtTRwDngtHmSxSdQxXvkYctoiUua65tgDSnkRSwGk2TYorfvEUVXQNhuSarZdnDGxygtYJAkoD9nq0P8bIjBFIkVgphDEBtCv59DW0n/aNE7Y9NhV5zNNuaOJjohbjoh7ZSX0PIwYjsD6/Kc1RHrLpq42msazvXDZ6NOLenDEZ5fU6PcAIAZkVJqd2k1QlZl/PWxYARiI9NpHbaxSanR3DeXB1C1woWJPwrCe4zDw52V2RU+7DWsAYCzOBy/6AUlP66b3kA+USaVPKZYAz+E+cpJSWVa5O+6JWDNBPi8i/QZr9BwH4ap9SKb0+2Nllej2KkkqRc4UWKM/OoL/fhXBBHjRlj45LGR1SM0uhmoMKk47R44BKZ+lWGcy10nvVCumAqiXIAzNYumUGwXXHwBwH0RNPQZw8bSYO0e2lyeM46JRivQZ4HuKVFSrvl5L6EwFERqRMxuR5VPHWHyTX1IKO5rES+eHEKyuQcYzoqWcAKSGaNaDkwb3iMtIhOY4SNAtyyY5jel1FsqS6Nub6q7YCI+XkpuoqTk3Cphowp9RcaAflzGSv19F9nHJFyluZQLdjG3nbzKlGy0sDpdY5V53ROIKko2Vaw6W0U069RulsHaEc5zuTiURlx76WNodWl6mU2br3rwIXPAqyU2BT2K5qLQApomMbC5qKHSFMtZUcDE2ERSyvULQHoBRTENJrUUQi1yoJU5nvg3keGOMJYcik0ehmx4BYQKyQCV/87AsQC0uQ/T5Epwthde7O2t5vFsxxEFd9MEH59bDKicSpiiIyElQ3csapdFxFbMz+ObWz0JEv5vtgzQk6R80GpO+ie1kDcBgmv9+Bf4pKyd0D+yGDgHQ5KjqiPYPcw4fg7t9nWkPYEK1VcjFeWgE4g3vJUTUWuj6i3yffG6WXAWN03TyPyFc2RcaIxPKjhylltW8GvFSGu596Z0UnT4FFqk2H6miPPqW6pBRUweY4yUQoyHVZt4LQ7R20V8voRRid8A10JMiuGLJITNZbx67Os0vY7e1l97ll8rKVKIQtHM5EOvIiMOttZ80xZv7PE3KTDkq95rojxMZchywJzUSm9PjHjiMvyrYR7HK0hwFb0+zs6mgvLBRkp8CmseG01hoVHnZPIkCZCdoprDgmMfFQ9aXSxnM6auM4QElVKg3Ir0asrCa6Gt+jJ0bfI+1GMFpGLYU0miGzP/uJD1Al58w4JqsVN3G21OHrY3NdgAFRhSGsMThDQakyPT6tUZDSlJvr30aDoFM7di+obg9gDKLkgXcHqH9nHmy1S9/w5RZkFCKaP0vpASBpAaEQnTqNeLkFdtVl5IgM5W4M5VMjBNjMFGlrBkPq52VVOkndFysIwDwPfLJJKacozo0c6VSQKbcvlyB7faqgchywLpXdo9unc+K51MizXiNTSctkUSgBtxgMzWSpq/yMxiZTDWTDEG6rOivb3sBOtdikXH+mtRnmCBHJ0/CkTsQGdDzZNOg2pMNsA72RFFMOAcz9e+0d6I2NbDv3OpgUo0h+4jj9ObW3paO01kNIbmTKjtwoAfSGHJf3KqJjR7PO9adALgqyU+CcMZbwZKtRxixjTNsyT2amekrf0IKASEtoERbfBzrkucE85eNi60U8j/xaVOprpLzWqjQhjUAt9Z5Jc8TUlyv3JrmJp77EIM1D2PDAQ8BflSjPD4FVqoCSUpiojtGcxBS1gDUh07klHyId8SHDPRd8fomiXkGI4RWzkA99m1yTp6fAKxXErRaRE1WarcFLZcgoRPztJ0wUzHjqAHQe++ocNycSYuD7lCbUzsUO9R0TyyuUgnOdlKEjL5Xh1Kpg+2aS9FSXHK/jbg989gB4c4KiN12qUgPnhmBhSP5Dot1ONEp+IrQWgyGllqxS87wJcSS1pT6PWUfvEeJifUbsydPsY1wfuJx1zd+7MbFmollrpX1GyuizwuT1KsfylrOO0d6+GAwpLauNA+0JW0jwUjlpwArrGmb2kUt0ziWaZh/v+aSxKrBlFGSnwJaQS3jWqPbI3pzsqqBsGSigIjw9ck/mk02VIonoSX+iTsZ1qkSb16pGtAqVRjHVOnoMOeF1SGlaJZjX9NN8pgLE7u21YdjEbnICTABxCSitxuB9i8DZEQZF0mS/T32lTGpPmkgTAJPm0320oKNBjRpYLKgBaKdLE7lqnCmGAzj1umqcSedDDAdwjx6Be2gW6A9MVIe51GqCNRtU1t7pEknhjIiPNRYaTwQZUdNWlEuIzsxTyk2X0ysTxei554FqBfH8AsRqB6xagXvsMOTiEul9lHeSnGrQ9ayUIXrK+FE1go1X2yYdR3qhhDSL4SCls8leR/szmCJBWQ1T5rNsxLwZwa4tXLe9ZZLP2JgKrXU+NylsZeLN7D+VjtPmlHnVS3mkLO97NG6cme996rut/qbIoTTGkxDSVPVBaab034wzisZa12tkrJmHrbxmruuO297eLqIoPd85FGSnwJax4bRWRlRoXrYmcu65ZrJIrRoE1EvK8+BMTwLDIdhqhzpt6+7VjIFPT1GUoVyiiZnzRM8xTogbWx2v7RtkziRoO+6mfufBqjAzWp/+AG4vgteTkJyBdwdkyBdFFMFyHNPyIO50zSSaevJWN38ZhDBVWIyZUms5HCJ+/Ck1Bjqm6OwCnSM1/rjTSUXPACA+PQexsEgmfirC5BzYR5ET/dQNQK6ukr9NfwA2NQlWKSdRImX4yFzPpLZMKkJFQthEnciUbpHBGTA9Cd0iQw4D8tPxXLB2j7bpOIhfcQ3Eof1J6wplwsirVZXa46nPTeozlJmgU+LktdJbdvWdHfGLQoBx0zxUV8vp9cZFNTY0ga6lK9kGvc8I4dPR1cx7a+43S3jWStNtACIIqDIws/9Uqw+dMtSpbJtAWddHjyervRoZ17gI1Wav13biXCuw7J8CuSjIToFtw7qEJ0+0aDmoAsmNK/VUrCo2EMWUmtJpE6aiC4yBT9RpQtYNP88uQupIAGB6Q42MRZLXj/7b/JYCqUiTlfZK/ax5uGzEGVq0O3BW+/C6Al4nAvoDyNWOscO3n0B5pZzWOOhUi6UrMukuvU/HAYSEM9WEt9hF6ZGnAQDuDIl/Ra+XnHtrXLr8W08ucbtNb3hEHKFSiEyfN98HLjtCRO3ANLBvigilrsZS51ubD5pz3e8TGapWAIfDmZ6E6Pchnnme9Du1Cq0bRdTYtD+ga90fwOlH4Asr4JUK2RDE1P7DGFEqUmiTkxRyrtkIqbYq9YwLr2ppkq3csj879mfELmcfmTg3Ep1Zi+SsF1VZC+utl4lgjby+2f1uMhIlwigRlasf7vu5LSR0dIdxlpAf/X4mgrfh8e1BJKfA7qG4ugW2FSNRnnFVEPpmVq3CmWqS9oInXb41yeGeS0/P/QGgyYvK80NKJVj1Ad+nidT3khL0SoWaWqreWXmVRqkJyNYmWJMnDVeml8k7tgxyWwgAYGeXUfvBEryFPpEIS4yMWJiUE+JkMh0xuANM+bkWc0J57pi0HedgqsJJRpGJRmQnXV6tElGxTAbN30FI57pSplRWFBHxLJfAWh1KNzFmCEzc7dEYfZ/STGEEZ3KSrnOjAafZJBLKGMApiuXOHqCu1ipFJYfktSIHQxKWd7qQ/QH4YhtiaVm1z6D2HWAsKb3X6SM7YpVzbVIeO5aA2byvPot2ZMeO6JlSdJYuec56+WQ/T2t9VsYiL8qzVR1JRtw7si9Yn11b4LvZ1FuW3G1gfU009edehBH9rdYVQUBRoHLJnFftzZMSjm9kf9noTkaQvuXzfA5gUm75p0A+iq7nBXYEpoO69SRKaSAk/3tu0sDRjk74HkR7kBje6ZLURp1+uy5kvQK20oZc7YBN1BG98CIAgNeq5LTsOIDDwct1qtYCoB12AT0xIk2+9E3Ompjsips8g7mRdW1kb54AWKkE0e6ADYZUJuq6FNXRx69SUoynQ/oj6TP9mjJEZMZgURjhL+sNIU7NAYwnYmNGEYhU93IpwRp1sCAwUXBn/wwgBKK5eTjNCVp1/wzi1ovAahvuwQNELIUE6wcUoRoMzLmIV1YAWBEiBV4qg2uDQKHG73k0/uEwqUrT3cuHQyKzAORKC6xSpso8RXahiR5nEH2V3rMbmOZMWKnWAGoZW7eSV5KdbXmQTS/a6+WS3M3qvNYY/5YxjnjJTLHAuO+G/breTt5r2X3kfWfsddQy+rNuR1xt0i8FT1K5NinbwPGNHUt2XHsV5RHqZyvrF8hFEdkpsGMwER7rSXJEAFku0cQmyGeG75seNaDjKo0VCyAIqb1CHANVKlNGPyFGQpdAD4dEcjhXnc7JeViHxEeIi32DHJf+sDVH9ut56+TdLKWA6HRVFIWql+SQohdSSDAr8iTDxMTQpFVszRCILJp2CKocHY5D5oIlH1htmw7mzPXAXM+E/IXqgcVVRCw6PZfSR5AZoIQzQV3FtRDZnZmBe+RQQqqGQ+pIfuYs4qVlOI1G2tQxC3PuJJWxa5LjcCJ+mjyUfDo3cUwaHm0yJ8hzifnKiFFK8llSVVgbQvY6mkuW1orl6ni0SFx/pseUbY+MZbtIy1Ym4Zw0bfJWQtRyo5h54xinLVovopMZRyr6NSaikhWTb3ic2XFlx5EX1d2DiE6BnUdBdgrsKExayxJBAurmJSTQqJEnjuNQp27P0ta4VLnDDuwDm6jThBgE4CfPQrou4maFhMhBCFatUoVRvw9eq6qWCpJEsrUq+JFDyojP8uPIS61prBHGHgn/56VMsvoHLa6cqFMZ/XBoBLwAEZe41TITOK9VwSvl1E1dRmF6glLhfU0KjCeQngRc12h1ZBRSt3fVk0praUQQwKnX07oIgCIzuuxdi5qfP0EuxydPI1ZCZtnpAkFgoilxuw0pRColljpVQUDkhTG6vpUywDnik3OqPYCkfUoJZ98MeL2eNPkcDMlrp6qu+3BIT/jqWq1bbaPPdbbaCpnIWUazlVo3+9mxX4M1GW9wLJvGViZiOzqTQw7WdFEeF9VZb9ns8pnI6ch72e2o5cZVi9mvbZjsjnkQyf0e7zKKNNbOoSA7BXYF94v7kididVPh9RoZ3gVhotXpdMmUTpnG8alJyGop8c1pTpDBXRQBMaUxTHfr5gScRgMolWC7Cxu3ZcvNd8TpVmPcTXzcU+wGYIuwtcCXVcqmMab28gHjRrMjrO7jdvWJOYf2ZGsZFjLGidSFIWR/QORPnUt9Tni5RERIOSbHnY7pEp8a93BIGh0VQXOmp5IWCfU6nHqdyM1gCKfRIE8UgMhauQT3qitSr/NSmbqa16oUpQkCoN0hM8FalUwhVVdzqftjxTHEaoeiguUSXU8hqDEolFBVtRsYuVZ5k5Y1cZr0FKNGsbaHS7YjejZFZRsPpkTs1jJjx7BXyF5frUnKOc7UOpv57K+37LjzkSUamfWzxNMW7uemD7PbzRvfWp+TvYruFNVYO4bz6JtY4GLH/fG9+HL4WTPhyCAASj5NYuUSUEtccVm5BL5vmkzp2mQeKDmHLLmQB/chONAAH4bU/dpx6GnfVROe8qlhpRKwb4oiCUIAlbLRnxgtzkZu5Bu9GWZD8mstrwiaCCPl8kxVKDpCwut1anWhfEXsVFrWM0Rqjx2oyInV6Ztxmrjd/fuMPkoGAfUbGwzBXNe4FmfHrNtBmJJ2tS6vVYmMuS6RhCiiqJxOD6nUmHjhJDUkbTbgXnIUvNkwDtfU40xVUnkuWLUC3myQHqvXp9dLPumRyiXS9OhjjmIw3wM/NKvEyJkS4/WiDzJp7ZDS7YwzHLRf09dAT7LW5ycvYnTeISdVlOuvk10+DxnSbV7L24b9Xl6UJ2df2UjNuKhaKrqT5xOUTZuNDC/H+XqvUDgo7xjOg6tb4KWGLwefoclhepJccisVYGaKKpNKPrUlOHoQ7VccQTw7qfoiDcEWlsDaPbBBCB7GCA7UiMzoG1inRz2i9IRa8hFN18jh1/cgXU56krwb2ziSAozeJNe6KWb0PRq8VAZvNGiRIKRolqoaksOh8gniViVWTALrRiN3ArC1PNDRHN1eQ1d2KTE3pKSmn5IiGUyRDKl1MMqjx1Eu0kb/1OuRoWOnS406u32K9vT7NK44Jvdq3RvLdc26vF6HGA4Qt1qIl1YQnzyN6OwiTJNTVT0GRcagW3poU0QhgDAkghYEFOnR6Syl15IrLWpEaonIR67pmL+zhCYbFciLFuhIUK4ex9aB5WlSzhfkaGmy0Z2R5bdCBLKi/3GpKvtvtT87Cju+vUQSnRpL2Ox1stEcO1qas/0CFw+KK1pgT/Dl8LNAp0dERbV5kBM1xIemgShCXPVROTMEBCCO7Ld0KTFpRBwOFgpIT5nwtTuIW6uQrVVKkwAQh2YgHXUD7PXBVrsQ3R6cgwfgNCfST7Q2SVnvRqee4nM1AmPWFQGZH0olUo5bqya6ZPdlEqY1hQBigbi1SmmgvLQVrHScqczipmwdDifyoBqdQrWIYJyb1htSUHd50zjVcVJCZeZ6VOpbrUIMBySiVtVWcjg0hoGiP6Doi+p5Jbq9ZEKKQvBKBVzpkuRwqIwDA3JlDkISblfKRLyG1ONKhhG1oPAp+if7A0pZeS7k0gr15zq4HwDAyyXTSX29SFxexRUtMpomsQlBtlIpL9Kw4WjHXiIzvnVJQl5EZKNkYKsaI6SJ54h3EcZfw9zU2Lif84TcFA7KO4fz4woXeEniC2fvwRcXfo8mvZKHqEnaDjE1AR5EEC4DHwRgkQCrVsmLJYoA34fkDG4noBQXAHguGQsqUTIrlcAXWvCeOUPvl0pUps45TaCVcvJUl/fEtxZ0Gi5PhDrm5s51R/NY0MRsmdXpiI7ZvPHRceFOT4HVKuBqvGbfea69eiJgnHQtg2ESveHUJR1AMu5YT+T0O15ZGRshkUGYMgjkpTJdE9X3SkYhRLdHOiytC7KiAmIwJDF0s0mpR8+FlOTHI5XRIFRbDNonVX/JXt9EgpjrGn2T6A+o8m4Ygk9NkrBZVauZc5mTJhlJd1iCebukXJ8nuzFodrJNRRMU+cm6Up+XyNHubCgqon+vR+7y1l3vnGwkoqqWsyMxeVoe+3duyiz7fT9PiA6AIo21gziPrnKBlyq+8MLHASnh9EJIxsDPLoMvrsJtDSFLHiAEgitnISdJ0yFePIXSqRZYqBplTk7QBFoqkV+MKutGFEOuJj4vzPdoYu/1gSjKv8GPyeuPLLNZaLIhEl1LKkxvC6dVry/4HulWgtA4H2cbTabs8bWWRwq66UUREYYwMv2GZBglZdzc6pwehim3Z2MAaGmJ5GBI4nCPSsRJwJwQFD5RVxEd8v7h1SqZQvo+VZKpdhVxl3qdyQFFhkyPJG0aqX2DuI4MqbQc50R4OaPKsiGlN835tU3lMpEw2yhwZLK2kDIa1G7V2ShQdrKUIr3s+TR5bhDrtonI00FtVLi8ke9LNp2VF73JEJxU+i2HwKXGl73m1rZyIz32Ns938lpgQyhMBQucF/ji3/4WAOD2H/5XEPunwLsD8FYXYqYBNgjhn16FqPoY3HAE5W/0gG4fstoEq1WA1Q4JZBmjdecWYKp9fA/xJQfgvDAPSAleqRh3XlYqgVklx18O7k2N6fX8zvED3ugN0H6qjQUVS8QCYkjeQLoUnDkWkYkFpYt8D2LurFkGUL44unLLvjFbEQrAmvBzlgGQCJqhSRZVJDGfDP7iVst0SreXhxIEM98Dq1TAuiXEKyvUvoFzMMYpNRnTNqXrErF0vaSnldbZqFQbL5cSsue6EL0ekYchXSMwIorMcSAWlyh6VHXBhYBorYI36hSpEyqCNRjSeWBeqlt9Km3JqF1GXipynLmguU4q4rNm76Xstb+QkT2OjURpzuX7sca6I+7UORhJYWUIqb2PVEoyqyvS69u/dwlM0M9W1i+Qjz19BPnqV7+KH//xH8fhw4fBGMPnPve5ddf5yle+gltuuQWlUglXXnklPvWpT+34OAvsHr70N3fjS9/8V0BrFRgOEdV96s80GILFEqdf4wHHDpI2Z0C9peB75NdSrUCWHIqGeB61kLj8KG2YMdM9HABVOjXqZLTXnMi9qWmPoLyfzUJXMyGKDBExJEaKlOsv81ygVkm6iwOAFNQ2w7bCz4hi7YkdOsrD+OjkMCLOJjLBa1USJPf7OSRHkSlfnbdymcTkE3UiOq5LeipVNi6DkK6LlESQQCX0UpXbw0o5SUsjBClNqTx0GwhtIaCctuVgqDRIKp20bxIII+PIbSYuRfSMviqj3TAmjVkNS6aqymhGtLmj3VYj0yDWRAo2kxbdK2xmbOsJwG3kketx640jGeMw5v1c/dwYwmI/EOT2AMuOfzevYZHG2jHsaWSn2+3ipptuwj/5J/8EP/mTP7nu8s8++yze9KY34V3vehc+/elP44EHHsDP/dzP4dChQ7j99tt3YcQFdgtfOPOfRl5748F/huP3CYiqD6dcApTXilxtgx08ALRWwZpValIZxYgOTSKY9FF5oUVl7QOq0mIlErtiog7OGMTCEkUQNoFxhGckGqT1HbpJpeAj7QykyJR8hxGY6v2kO6HLON0BmtbR21QRCKuZal75dErPYt5kJnUExlICZcf3KXIWRqobOZEMOVkHiwTQ7gL1KmmkqhUqJW+rbuqc03qua/pyMd+n8+y5hpzIgPp1GT2OaojKSiXS8OhhAuQOXalQBK/Xg4xjOPUa4sefhnNwFmJ5BanEZDZiZhGe5FyMNuvMmwSl4AmpsZbP9hsz7VBswrXXUJGMkXL7kcXGv5ennUmRgrzjzHt/I+utt+8cgmS3oRmLbGSIWe1gRh4ANkHAClwQ2FOy88Y3vhFvfOMbN7z8Pffcg+PHj+OjH/0oAOC6667D1772NXzsYx8ryM5LAF+Y+48jr91eeytNjMstSn8MQ8iKD9bqIKp5CJoOKo4DyAhsYgJypUW6E8eBdDkRnjJN0tsBTYLySI8UHIyP3jhpYk2iA1ofw8ol8EZDdW9nCSmyUlMpomRNIkl6JdPTSU/kelJX64gwAgtC8GqVup/3ehCdDqSQcA/N0vqNOqWkIgGp/G+gPX16fcDzKIWlq71UewcTnXKJ3BiXVyETN+k4pvc8N0lhlUsUxdFRJddVKTJBmqB6DTKKKBKk2kWYkn59Suw0kzWBcc81KQwTYYpjAHEq5QakSVLudbPbFmT3tVXCs5X1c9ZNGSpmyM1YoqO3Ne61zURjMlG3Da2/kf3mkZX19EV5Ymt7XfM+x66Z9UlsbV9FYGcsLijNzoMPPojbbrst9drtt9+O9773vXszoAJ7ji91/zj39Tde9X44gwj150n0DM8Fc1XKIUwmRLayCtRrJiWyo8iJ4tDLMpVWIaFwBPQlNTXVKZx1JoVEY5K+aYswomowaZVLy3T7DkqlCUCSB4/TaJA5YK9HkZiOqnqbqJOpnyYs7Q7Y1CSRxWFAXcuDEHC4KUvXKTE5HJJZooriMF1mrnU92kdHV42pajLuuUSgpKCI0PQkmCqlB2MQKy1I3XDUdSGHMZibkI3UcUITIIsEqrQUc7mJ3BjRuBW1WTNyYImU14yCrIVziXqsBSlS0T7abLplSvb/bGXTmgTIJgTnGsk6l3XyztE44mNp2caKx/P2v0eRna22fCjaRYzHBUV25ubmMDs7m3ptdnYWq6ur6Pf7qFiNFDWGwyGGumIDwOrq6o6Ps8De4wtPfmTktTdMv1P14aLJTZR9OJ4LeXaRJt1thOn6nsW4cL8djWHklcOaE2BBQKRhnYnWvqnrbQCgMvAxAkydrmKuRxVTWnei03wAEa3+gKIzrkMRHSAhQJ4HKA2NlCoFVS5RVZYF2/9GBgHguZC95JyLMKJxKs8lMjoMSFAeRmDKcVqnx+D7EPNnwZsTtEwQUGTPTW5pJl3IPENeZJxEbqgNh1Wmbk5Nmgxkz102OmKu2Tix8rjJMktu7Ne2KpC1Uja2MDuvzHycwWJeX7CxrTDW0ueslYbaCrkbt/w4gXN2/9nvhH3udepPpzt3qNVZgd3Deaye2x58+MMfRrPZND/Hjh3b6yEV2CN8cen38YW5/4gvnPwP+MLJ/4AvP/QhfOG5j+GLS78/NkK0I9jg06Xs9pOb7Vo39rU0E0LSpG9vwyrT5r6fTOw6stTrUaQnCCH7feV1I4FKGayvela1u7Qc50AYIlpcBALaj6mG0sMIgqT3li57DxOhtu6uzjw3SX1JPeGqUncdoRgMIRaXIVdXwapViE6XjBqVhofxzORl6zQYT6I4SpuUmvgZT4mZU81M1bmzPXdyr4PebxbrXXM9yW5HFMEiviPEZgPNMsc13Mzzs8nd93rnQUfbspGhrSKblrK2myKv2YhQ3hgy5HfXsEcC5U9+8pO47LLLUC6Xceutt+Khhx5ac/n77rsP1157LcrlMm688UZ8/vOfN++FYYhf/dVfxY033oharYbDhw/jrW99K06dOnVOY9suXFBk5+DBgzhz5kzqtTNnzmBiYiI3qgMAH/jAB9BqtczPiRMndmOoBQqMxyY0DuO6h48sn5nU7ffMNvQNXZvlqeaX9uQkw4iIiRYquy50Hy90+4CIgZKn2npMUxWc58E9dJCWExQxEmFkSAP1QQvV34J+lD6IlVVpeaanlwwCiioBSusTGNdnPqPMDaUyUlQeS7rhqCGH6kd3izfRjSgkV+eSasaa8SpK/a3GbxPOlM7F0kCZc2z/zrmmBnnL5m0nT0C7WWTWH9EZsaRqzxDDnL5T4/7P7Um11v/6te0mOToqo0ldRpQ80kh3XHTNGu+6hovbCQlAbOHnHLjOvffei7vuugt33303Hn30Udx00024/fbbMT8/n7v817/+dbzlLW/BO97xDnzzm9/EHXfcgTvuuAPf+c53AAC9Xg+PPvoofv3Xfx2PPvoo/vRP/xRPPPEE/v7f//ubH9w24oIiO69+9avxwAMPpF67//778epXv3rsOqVSCRMTE6mfAgV2A5stUU9VC6mITKqcfC1k9DgmNaa9Z+zybiB5ugbMBG+qvWJBqTMdMRkOk+hMpawasvpENoZDQDVxJcM/Du77pkxemwoy30uEypFubEpmhtowUUeioJyhpW6xodNtvk+9uJZXSNysS9NVc1c65iRdZY5TkTpNTJjrETFSmhaTYtOTpE0e43TFW14Z/4a6bVvLm9/j0ih562+UFKwTVdLETJNde/sjZdj2ZzHvGC0iNq4CMG97KbJkk5KNEKQ8ZM+ZFKPjXet8ZtJXWVK7ppfSNkNrdrbys1n89m//Nt75znfi7W9/O172spfhnnvuQbVaxR/+4R/mLv87v/M7eMMb3oD3ve99uO666/Bbv/VbuOWWW/CJT3wCANBsNnH//ffjp37qp3DNNdfgR37kR/CJT3wCjzzyCF544YUtnZ+tYE/JTqfTwWOPPYbHHnsMAJWWP/bYY+aEfOADH8Bb3/pWs/y73vUuPPPMM3j/+9+Pxx9/HP/xP/5H/Lf/9t/wy7/8y3sx/AIF1sVmfHlGmlHmiZI3MgFk9BA6SsI8S6KXo0PRE54YDlKb0329UPapgo3TTVmWPSMuhsOhy9fN07XqqwU9qemUnOuSMSIAxjkRD6uhqW6CapyPPY80QcpTiblWxVapBLG0TBEiLXy2U1F2+s7W1Yx7TU+UmclfRuHapHM9oWze9bH2OXai32TkIxVpsQiEJhb2xD1SqaaX1aRbRbdGIjfZ8yqF0j+NSZNZkZa8fmJZs8dzimRlozN2WnCcRihvjNlltxpR2yOsrq6mfoZjNIlBEOCRRx5JFf5wznHbbbfhwQcfzF1nXKHQuOUBoNVqgTGGycnJzR/MNmFPr+TDDz+Ml7/85Xj5y18OALjrrrvw8pe/HB/60IcAAKdPn04xwePHj+N//s//ifvvvx833XQTPvrRj+IP/uAPirLzAhcHcjQDa2pDbNhpCF3Crp+2c1IYdtWR2YRlsqcnJ16pULqpSmli1umDxZIq3AAiOkFIImXVz0qEEcRwYDxomHZdrlaNrsCZapLpIGNgvkcEiyuypDq1g3GTvmJl8kGS3b7qGh+Q5QDnRJSEJFKkOrsbEbH2wclMelJIIlwZcmJXU6U0KhvQuqw7OeZpRfTr9jL6/ex762Gd1Jm5tpoQqRYa2fXs97lqDpsiIZoQ6murz1te5MbSg9l/5w8/JzK02ePPprHsc5GnybFezzOYXGu8OwIJbE2zQ5s5duxYSqv64Q9/OHd3CwsLiOM4t/Bnbm4ud51xhULjlh8MBvjVX/1VvOUtb9nTzMqeVmO97nWvg1wj7Jbnjvy6170O3/zmN3dwVAUKbD/GVmethc0+3dtVJHqy1zdwISFZokMxqQfHAWSYSkPoJ9zkaVwRBM8BkyXqRxbHlMqqlCEWTkH0enAmJ0mbk51kta9REBA5AkwXdvgeEJB+RhsownEAxiCCIUUMYgEJ2i6r10jcHFGJOyuXAM6oa7rnqqiQY9qAZMXdpkcXkgl4lBzq9E7GtNGO9NjaD2m5MedNqDlka1w6i8Yzek3XxQaXSR1DxjxRm16ORDYy19OU2Fv/28tmDf6Yo/5na5sa0jrJtUiNQf897rhtMqPHoN/PXofsMWVfzyOhu4WtuiCrdU+cOJEiFqVNmqZuF8IwxE/91E9BSon/9J9GjWJ3ExdU6XmBAhc11kp7ZG/YWaT0CulJjd7TndS95MkcSAtyM+sl6SCW/EQxlY27DmTFA4KIuo6DuqYz10sRAOb71CJDD0WnsoQg8iMEdCd67lWs8UiTGoEUNAcyTsQniowhoU6f8VqVokC6pUS2ckiPSetUzDkY7TZvUjcWUcqmgFLbtraRO6GuRVazOhEtNRrn2bMORkrLzfppwS79qcmxTbYERdj0+eNM9TnLpLF4+tikkGA+B6I02TOO3Po41bp5njdZfdQIsum/1PFZ74/7rmSjanmEJ7W7dXyGzmNsVJ+6b98+OI6TW/hz8ODB3HXGFQpll9dE5/nnn8df/dVf7ble9sJMSBYocAFiXe3OmNTFSKoh+3fOe3ZXaCN2Vl3KzRO+Hb7P7I9XKtQotVKmaEoUg/UDyFoZouRBVpV+R1VgmVLxaDSyA8cB44koVreeIB2RZ0rGZRip7clEw6N/dARGkyUtru50iQAFAYQyIcwejz5+cy71cSoyYwtw7eoq+3e2oivvXI+24tiA4DYVAXHSaaHkAEbXG7eNTOTG/nykBOwAXQe7YazDTRTQbNcSepvfnBl9lCEwjqMau2Z8iywBuH2+U6Xg6rd9/lK6o6z+xiJOG0aeFshKy41sM0/kvBsQ2/CzCfi+j1e84hWpwh8hBB544IGxhT8bKRTSROfJJ5/EX/7lX2JmZmZzA9sBFGSnQIFdxIYIj5VC0khFObLLA/nh/NRiCfHRpeFAEmmxK3OMpodziNYqZK8PKQVkyYX0HMiyCxbG4O0hWG8I2e4k5MTep5koGeJOhwiOagbKlFmgXSXGPNekzMAZ/TjcCKtNd3SlFxL9AXntDAfJdsZMgHbUZoTc6XSWIjSG4KjISjYKkedBk/VxMcQls4/csakKMX3uN40xZCj1GcohUFLZA8goJJ1ULJLzLpXppBKUa68jI3KPRUJ8AHOt9L7M/plKqfqeEXnnuTfbKcBsI1Z7m6m/syk++7O/nnZq3LYx+nCxm6RnL6qx7rrrLvz+7/8+/st/+S/4/ve/j1/4hV9At9vF29/+dgDAW9/6VnzgAx8wy7/nPe/BF7/4RXz0ox/F448/jt/4jd/Aww8/jHe/+90AiOj8w3/4D/Hwww/j05/+NOI4xtzcHObm5hBkq0J3EUUaq0CB8xR6MjDl59ZNOttpO/u+fSNPTSqZXkjp6AWlsrjHTKqJVatJWoNzsGEIRA5YEBl9ATXvFHBqVcSdTiplJAZDKkVXHjgUvVEO0aovFhwHukUEpCoRh4reWH20JGKKRmhtDwBEEZxGA7FqF0Hpn9FUkp2iS/nwIJO2UudPhNKKtMjc6Jc5j5kGq3bULHv+7etlSNa4snZzPBtIZ8l0a4hcYbrdmd1xkjJ/q6eY0UwJAa6r3qKElIpQtfXgICdyKQ3hYZxbqSiujCylafiqj8XWQI0IkaVu1YH069m/reNeMyW1AdIzopPKbv8ix5vf/GacPXsWH/rQhzA3N4ebb74ZX/ziF40I+YUXXgC3zDpf85rX4DOf+Qx+7dd+DR/84Adx1VVX4XOf+xxuuOEGAMDJkyfxP/7H/wAA3Hzzzal9/a//9b/wute9bleOKwsm11IIX4RYXV1Fs9lEq9Xa8xxigZcuRsTK1g2auUl7A/2ejGMiDfUaOQa3VjOTeUbQmSfKTO0uLbw16ROdxnFdSjGpSihWLkNOT1ATUEdNUAJgw4AiLb0+tZCIBRAEEKudZDxqHEx574h+H06jod6XiZmgbhUBmOgNAJUe4SbywFwXoj9IIj12BZWO3GQmQLucWp8v4zOUFSBn1tXExJCFLNHMVPHYRMPWRI0ry84iaXORo1FZA3YV2sh7rmcRkbRJooGKxJg0o+5Er1KOAFTVm0vXTKq0VRxbFXSKoOrXAGivJN2qwybxOmK5kbTdWD+jcZEepD/n+v3s+ckaDWbXiWSIr+C/7+icoeelv3f9++A65y4mjuIhHvjuvyvmtxwUaawCBfYAY9NZdvg8jskZuFKGe8kR8EOzwOQE2GQTvNFIVcWsG/rPTCB5E0eqOieKiOioSU7ONCkl4avJyXXBhCCxctkj3U61QsLjwdBsT6pSdBnHFPWJYzj1upoAwySiA0AGIZkZqpYSjHPToNVUiKlJNSmTV2TDccx+zPFmiUSG6GSjDCbVZ2tR9CSPdCpKRyVMRE0T1TGpqux5tvUiWS2QbS65ke3pdfJckfM+AybypN/X5oy6zDyO6Tx7LpjvU1d5xoyJo03CYbX8AGPqmllhEvv6WVEuTXTyDAtTzts5Ua+U9iiH6KT0aFlCD1DvtzWiafa5WjMytBPYo3YRLwUUZKdAgT3CCOGxnjqNlsbzwA4eoPfLvrmZsWoFrFYhH5RSKd/lNavfyZTn0i6T6IaJDPi+eVI3fjZCJKkrzkkbICQJl4OYOsdLCQQhVUvZ+9CTjKrMobScKoPXOhH1vpm0hUzpeWRA0Q47paJ7aDFLz2SLfLPnNnuc9vHrv1Pl6FJAqD5f2ShbXlQMWuyso0s5RMYmIFqrkzsWKyWVS9wy0AQulUKz9mmX16e2pfepSI6MIvrbaHNi81k019UmCFrHY8iDnRrkqeW41ePMbjxrjkGJ27Ml/Kljs/7POyc2Ac2mDfV6xrHbJkfjKrnGReQKXHAoyE6BAnsIQ3gyGg/zZBuGQH8AWa8AgwAYDCFrZdOegTcbYB51Ldfrp2A/5WtYk2fqyZYz8HIpqahRJd36b+ny5OlRV2CpdJOs+NSNHCCiYjsZZyCDgDQceqK10lBUru6lSZmdXlLbFkFARoQqLSaDIE1EshU2FrlLuQjbT/gWKdBj456bSkllHYVTnkR2yjATGcirNNLEL+Vsrcelq9rySqyzGEeEssTWSo+a626REilU5CyKiIQaMumReSNLxMtwuEm3Se14rcmNIa36HCjNl06TWeRXnwvGWfIZtq5LlrytmXrUY0E6FWWTpdT11fogO2pka6TUZ2c320UUkZ2dQ0F2ChTYY6QIj4oO8EqZXIalJK1MPwDCEKhWqDdV2bNKhFkS5cmmPbKTJUu7y5pycO2noxp/Ms8DP7AfUGZk0nHAWl2a/MIYbBilSs5ZZwAMhkQ8rChCdiLJjbpo7YeufIqikWVkFKYrftTxiCCgKIEt4h1XsQYrKmC9nvXUsYmgTo3ZE7IdHRqp1LLJzzhobZTep0pXmmvDVAuNTaZQ7Iq77Lq62sxETbJRP6HShlKSXsv3iIT5nklL6evH1GeC+T60a7YWliNOi+dpYMnnVPQHhizpMdtjT0W9bEJpLTsSLbOOMRvRWasKLnXd7AgdsLEGvDuBjZSWr/dTIBcF2SlQ4DzA/eK+dFjdccAYB649ToJgxgBPmehpfxsA8H2wStloI3It763ogp4QeLlE5EhHFRxrGc8lZ+JejyInrVWwZ04A9SrdTBmDXFwistUf0E+vB7HSMg7J5onc+skTDtO+qTIolZ6wn9hjqsKCnkwVOdMVXiII0k/448rEx4iI6cRZ4lWbBGXXt3U/mqDZER/dZFRrfvR+MvtiVvNRgNJzdgonW+G1GaSiIVkBu0WooCqvjECcMUov9qk3mhZ/SyGI2GoxcRQRadHEVBNlFXEjA0od5eGptBcvlwyhTaWr7LTqGJKXqoDLaHiyFW/6OA0Bcj3wSiV9/FKkPnMmmlcppyJOu5nG2ovS85cKCrJToMB5gvvjewGo8l6HGl3yzhB8bolSWbUSZMkDX+2D9YZJpEMb+wHpCIWCEYcqQz9eLlG6wug1KAXBfJ/8dEJrAmMMfGqS3nOVVkdKsIkJmizaHch2B6LdoQksI/zME6BqmGiMLoHWKSPOjAuyIUia8OindpXyyHYsT7UusI+fdqheSIiISRnaE68tEs9UCYkwShO5zHaMW7CVIslGFpgiGKmIhSU033RUYYPl0bZvEOOMrrMt6AZII+Z7hgAZ4uu5pMdSonDdyZ75PkWFnMQpOW63KRIXRUl7EMAQcgCj0T+LfNCOx2uu6N8xkR0k0Tv92eHlEvjsPrCZqRTR4fU6rWd9Z+haqvSVLVgvcMGjIDsFCpxPYJwm8EqZUkLzCzRhTNTBWt2k7HswTJ6YhwFNSMoBV7dsYI5joje8XKIScmUSB8eh7uHaTE6VDMvBMCEHKqVlWjswljQA9VRV1ESDNDY2qckjArDIjTlUln7NJhaZqjQANAGr0mdYRCilQ7E1MyzdHHVkfPZpt1IY6RSMpf1BOvKQWwmn11f7zkaGUiX/KlVka0m0huecowqZlF3e63oshvj4iUhaR3AMcdRETLtb64orh5PuqlKmUvQoAi+VU0RNG1fa51uGUWIuWCol+h0VFTPXUqXc9HVLpbTyzi0y10N/DzgDm5kCuAOoz7YRhvf7tKJKSYrQSp/qVOQGieS2odDs7BgKslOgwHkEGcdEXGpWt/FGHWh3SUDcHtCEpHxM5EQNKPmQg6ExbgPohm9aPihthekdBaiokFpWp7KEIG+dKCJBqquiO75Hk1oQAS6H5JzGIGSyTGZSt6MII5Edi1SkRMqcpfoyaZ2Jmei8dOkz44xEykASSdERmmzp9jjhtlo3N70GGOJovG/08nrbOvVkNpu4IZt92xopHVlTkTvtPG2XZtMuxutvcmGRMrNeltBpomalyegcq2iV1uzoa8EYpBRAFFGqlFME0K60ipeWVbUe7c8WW2sRttDVc5w63OsxiF4vOa/qHJnIWPbYtF5IV3OpKGBKZ6OrCT0XrFIGP3KQPvu6Oa1IUo6GjKsom9a7ySiEGAxHtr1r0ORyKz8FclGQnQIFzidIQU+cserw3WxQ9ZXn0U8Y0o/j0CTUpcmeaf2NeiLl9Rq9XiFdSyIOpggOU6kh7YAs9d9hCFbygZKf6IAWl4FqlUiOlGBBmEyMSvth/GjyoiZ2OidTqZSKtth/JyubZYTy74GlazEpKFv0myU6SIjJSDTJOu/2ejJnLKnybfv47EnRHoeblG+bMfieKZ1nFdX41EonwlHd4aVIV2RtdNLNiI9t9+1sGbsp0dZkzOHp8UgJVi4DrgvR6dJnR19rFeFzZg9AtNt0bksl8EY9OS9KW6VTXKLfT8q+zUJEJEW/nxDXPOhzbpFXEyHyXCJcUoBXyhR98j0TiRIrLch6JSF4vk+kc2YKzux+Y3YJgHQ91rnjZfK5KnDho2gXUaDAeYT7xX24vf42+qdUgnQYJOdgUQQIRumEKAK0KFmVBxsvFCEpCuN7ZPKnGnDK/oDIkS4zNoRDTR6xgASSdgE6WsMdsMkmefzoCH/Fp2qsSpnEyYwp3U9iu29XxOjfJOpVB5oiNF4yQevu5kBapOs4YIjNkzn3rEaU1vZShneMp6NHY7Q4Jl1hR3ikAOCMEBv7mOxtpSIlQqbcoJO0lQ/GOKQ6vyZlqFJJkBJxp5PrQbMlqGPJlsubEnFVDSa7/SSy5qq0Zrtj0lqkyRJEaISA6A8gllfADx+CXFyiiGS1anbL989ALC5B9PtkTAgAUpJxZGps6/eMsx3HnXodcadDZEqlNFnZVw1hQzj7ZyB7fTBvCLZ/BvLkaeD5U3SMSogfdzpAp2O26c4egOz2jMuzEYoHAST2oPR8K+sXyEVBdgoUOM/AyiVgtQ05MwUA4Asr9EYsKTLQH4CVVEVLt0fkRhnBsZI0XakRx0AUQbQ74JNNE9XRQtOU8ZudcrFKkAFQmswh92QWUgSIlmcUAQpCIIxGiIGtqzB/Z6I2tkjXTLxcpYlcj0rLtWkd42AeM+kxW5tjR4usAYxEd1Ipp4xwmcaotsdGy+bXIiC2SBmIk/J5xwFEUu0k+n26DlFkWnJoMz/d88toXdInc+y+NwMpZNI5PiZ3a00OAIoEsokJqsRjSaoTngvZpeiL6PXgTE9RmqrfB1eiZLTbcKcnzb6iF0/CnT1A+8lGdLCBprhjltXEx6Q47WhYTA1sme9BTjXoM3v8KOLvPQXHp/SiHkveNnmlQuk2OKpXnATYbup2tqq7KcjOOBRkp0CB8wyitUp6HSGArtakSGBCaXfUEzfzlT9OoHspMaDkUcRFSqDTBTyPiA5AJKY/oKiObrkQhEafYSBl0o/KTQwGARDhAqgyq6/KjIekF8oa8gFWVGOc1wnUpKX9aQxRS7QwFDXRJ2eMiNj623ZIHluKnyI46egTkDkOK1WWXSdZzjGibwQw+hWpfHq4EvEy3zftNBBFNDWpY81LnW0XZBQmmiApIGN6jVcq9FkqlYAyiEiXy4DvQ3a6iFdWwCuVdDQGpNXRiJ4/kfz9xFOp5aIz86n/N0NwxuF+cV+6t5xVMcUcB/HcGTiTk5CeA+ly8Pku3COHIDtdQ3Cz49D/v57fmTI3pGtbqD0uBhRkp0CB8wxfDj+LN172y1RxFSrzPtelv8slsEYNWFpJlfLCVy63JZ9SS9qaP4qASOkwokiVdat1eNKck3EOKYSl1xDQDEO6SeoFnuqGPoxoH1FsRYlG+02tBbs8WNpeOjLR1NheKVroSsQoTOlkspGdJG2W7gRud0RPXstvnqmRJXFZDZI5XiYBbml21Hnkvg9Wq1BETQtwdaWTlImANxP12nbSo0gObZsIsm7Kql2twRmlP1uriFdWzDJbwXYQnHHbfD2/k6JMoWploqNRzQZExYf75IsmUqmPZ73tGsKj7QzELkZ2ijTWjqEgOwUKnI8olYCuSiVUKkQshCCC016hiqlYGE8UJhQZaXdIyBzFqplnBOa5EN1eMgF7LolRB0NKY6lmmqky55DSLJKrCE5NER6tQ/EdsFgCYUhi55yJOVUKnJ3IMRp1kcrDxvZ40X/r6IgIAsiIjAV1JY/RCmUiONlWACkPlzGC5BQBy0nL6WWy7r4mijMYGo0MALBSiaqOVmMjdGWlEpGiwZBE12PKwncLotczhJNXyvS5a04AZxc2tZ2dIDUb2efr+Z1w9++jc6+q3FgUwZ1boUrG/gDR6blNjZGVSsbEclchJLaUiiqqscaiIDsFCpxnuL3+NrDjR8H6nCI6nkvRGs4oRRV6YFLS5BpStEaGIRn+aV0OU6XE2u1Wt1nwVIRIdRWXYZREOhADfUV6PA9YbYNNT9LEzDnYUFVh6b+FpF5dVsNOjUR/k05pjeh26I3EP0WXIjNu+l3Z62cFyUBCmhKi4iW6nnHIeOXQSxkhcw4hsomRFkkzz016c+nxa61SQBEoXq+ZZpoyjkkwvtseLhqZ/VLkSlUj1WuGGGSxF2Rmo4jOLsBpNiF7PfBGA9GJU3CvueKciI6dJnOaTWAYrrNGgQsBRTKyQIHzDHI4BOsOk5QSZ0C5lAiGtbeN4yTLCEkTq/ZvGQypiSizyAXn9KQqJYTVx4qiJaEx7aMeRzERq2EIuFYoX4XZpecQgfJVJ3Y7nWMLgW0n4xwtj51SyjYPTUWaVIUU99ykEktvP0V0RqMiKcdjva3M+9ly87yKq2zKy1Ts6EiU9pBRY5dCJFVqQUBaKSEhh8O038vIB2D3SZA+1/Hi0rrLpvQy5wE0iZFBQHYNvgf3issQPf6k0RNtlqiZ5bfQtuOcYFsHnOtPgVwUZKdAgfMMXw4/m1TDGOM5qzLG9xOfHcehSqhej0hIf6AMBgN63RAACdHpIF5tm9SJFDLduVpVs8jBkNJg3T7Q7QKrVKLLAkUwhACLBC0jBFXw8NHmjOb/bAprDc+YPBNCO6IjwijRuCQLpPQ5edtca7/2Po0nTbbyKrMP00/JKuMmATJV/EhtERAnESax2jHnOLd6bA9hi8EvVPBGHXIwRHR6DtFTz2zLNlmlDLkXmp3CQXnbUaSxChQ4DyH7A9W/iiqoUFIRlNUelYK3iYCI1Y5JF8Wr7VRzT91hmsqM1UQuBWSUiH+1L05ScSSBABBS0v4dBwwg3Y7rUOm5RhQnBCszSeYSHev/kX5VObqVrKaH1okBJGXgWnS8nhg6u//sWFNGg3kExESM0tEmKRIXXr0tAEnJvEPpOM5LJhLH3CTNZkTTY8Z2vuL1/M7zLq0VzZ8deW0rY9TpLCF3MY1VaHZ2DAXZKVDgPIToD8DiGLxegxwGYKJK2plhQHodnWoCVGTBp0hOFEIMB6YjOGBpWhS5SfWSSpnoqW1JluhwlL6Euy5V6UiqONKNRxFFEINhrhA4V69jQ+q2Bep/Wyuj0lt2emnEW8c6Nv332JSDXsc+3qygWZesZ0rZzdgYB6+UEXe66eNjHIwnERwZx1TN4zgqbSiAy4+Br7RJQ3J2Ae6Rw4hOzaUqo/YUGxRFn28pLI0sqdkuMna/uA8/yu7Y8nYK7D3OjxhqgQIFUvhy8BnI4RCi1aaKq8EACEOIdps8bZSJn9BmfnqCVRDDgbHTB5AiNFJImgjG5PjNpB1Gxj9HtjtUCq9L2QVVYo2L6KSaf2qilffUmZdeyupwkKRXbEKiG2UaQrRWSsh+LxMt0g1T1yxBVyXkcbtNERvrdeiSe91yoFSmdFu/D6GMAgcHa4iO7kN0dgHc9xGdPAX3wD4w3wOvVuEePpQQ1L1IbeURHWsc43xpzlds5/j+e+uPt21b66JIY+0YCrJToMB5Ct39WXR75F7bJot8oczRjPZDikRkbJd750zw98f3mpfGTgjSapioIAZDiuZEMdDv008QJE0WzarpKEyqTFv/Lql+Q1bjy7wJ3iY6mmDY1Vr2Pm0/ndzmo9noVWZ/Ou20ZgVXdj2mOmsr8qWbU5rKNxUt4VdfAe/LDyOsu3AvPQa+bwYAEC8uQwYhaU26PZN+dJoT48ewm8ghQOc7ybngIbFFsrPXB3D+okhjFShwnkJrBmR/AF4uAUDiNqwriJS/jJmoLbM9O7pyf/yZZLvrEB47BfB6580U/fBciu64qsxat0MAcglCqsSccUpVcWphwTg3nba1yV82hWQIjEVSGGcQYbriy0R2rDL31Hhy/H3M6ya1F49qiNIHA4DE0bYw2USbPNf0U2I+B29OUHpPmyAGIZzrrwb/2vfQ/Xs3oPTnDwEAnKkm4qVlyNkZ4PlT1K8JgOh04TQaAOeIW611W1XsJs5HrU6BAhtBEdkpUOA8himrDamyx5Rp60orwER2smJf5vuJA/E57NNACtLlBIGpNhJBYH7ykIrwQBMCNymft6MvtpeN5Zmjj4OXqPN2Vk9jR3P07xHilU2TaZLjeukSdmA8ociU9WrC6U5PmUaU4NRpm3GOaG4e/R+7Ge6RwwCA9g8dgKiXsfCWm1F9bhXuJUfhXH81MD0J58rjYL1hks46QF2443YbcasFXiqDVyq7W/5cYO9QpLF2DEVkp0CB8xz3x/fix7x/ZMTFAEj8ahnnaaLAfd/oRMAoCvHl8NNb3rdOi4l2h1Ja2bRTTmoIUMZ7UUi6oyA07SnsMROJYUY/o8mEFNKsj5in+jvl96eyojpjxpOKglnLjfW8ycDuii2lIJG46uXF61XA99B50w1ofmcJ0clT6Lz5R+D2BfgTL2D6Gyu5/bONVkdS125WKlGaEOTdk00p7gW0MLmI6uwwhACwhaq83SyTv8BQkJ0CBS4A6KolXabMmNX80KVoS6pTNyP35DU1KBvEl8PP4sf8nwagtDtAQibGkQo9bsu3RmuQWKkEU/OuU1zWskBsojimdYMiOrr8O9tNfVy1V6rKKDNWu3rKpAQ3CBmFiJeWE6LCGcAZ5n7icvAIYCsdiL/7ckz+5ZOIFhfxxXVIwuv5ndRws9OlKJhKXWn7gLxmnAUKFNg4CrJToMAFgPvFfaSf4cJM/jr6kUzyVg8qziDD7QtpG2FwtoR7PcKjIydBaDQ6cjg0BEhXVAFISI1ez963qc5Cet08V2a1rdTf0mpJkWovYS+/DttR29FjdBoNsAP70Hr5LIaTHF5XoLIoULvvrxEBeODE72xY42I3tpRRSH5JjmOiRucD0SmiOruAohHojqEgOwUKXCDQwuLXO29OkQERRqZaifk+mCWc3a5JUk90P+b/9GgriBxBtPktBcB0hZgP4yljCZGliJIdZQTFKU1Npp2DFjGPiJNtb5yMT46JFiGGBCwRNEv7/Kj3RkrebXgu5JmzqJ2cQP2EhPzGt1LnKvv3RmCTHgBU8Zb3eoGLEwXZ2TEUZKdAgQsM98f3qiiPVYXEOPhEBYxxxCsrxkl1J57Gs32kUqTH6iuV9b5JRVSENFEqm/ikkNHQ0HFm3Id1eXo2qmMbBxqBcaZ/lu7nZfX1gkw6qmt9TkKQ0oiXlgEA/G+fhOj1tvVcj9uW3aRyt1FUYhW4kFFUYxUocAHi/vjexMvG9ahKSkjErdUdFbR+OfjMWGKhfX7sqiidamKcGQKR0uOso/nRERlN6AzRUSmpzVSa5fW7SpWcW67Nevu8XCKhdLUKAClnao0vdf7LrpKA+8V9Zn+7TT5ez+8soks7CSG3/lMgFwXZKVDgAsX98b1EeuKYOp5b6RyAiMlO7VfDkBD6J1WiDag0lU2+cgwLbSKTLbG2NT2aKJnUE3KiQcmKI2ksm9gY/Y7SPjHXo3J03eZBLScGQ/ByCYzT9sRwkD4XexjpsAnPdo+jiODsDaQUW/4pkI8ijVWgwAWOLwefwY95/4gm4hyn5J2GbQ6Y0r2sUfotwijtAZQxE7TTU7rv1EhzUctscMRIMKMn0tsyf9tRHm1qGMeAZBCDiCqgVDRHBiGY65KzcRxTb6zzcFLZSoorj9yM215BhHYQcovRmUKzMxZFZKdAgYsAXw4/S39IsSuT0f3xvaMppJzIji32Za5noivcc5P1XZfK0XX0hfGkGslselT8bJedrzkOrSMaQ1BS67sutbIAyCVaKsGz44CV0r2xzsdJ/1yiPOfjcRQosN0oyE6BAhcJdiKdsRY0wRrR8NiuxXk9rzLuyYxziF7PEBI7zZXbKd02Uhwnas5qfcaMxWxTR5KCEHI4NN5FzPfh7JsBpER0Zp56kwXBeU8QNlruvtHj2CuN0EsOhYPyjqFIYxUoUOCckUc8siTE1spoV2S1oFnGaTQgo4haUtjNQddIF+X25LK8h7TTMfcYRBilt5nR80ghwcsliMGQ1vU9IIrAmg0gjJIeVVF4wUz4dhpqK2MuiM4uQgiAbSFFeh6mV88XFGSnQIECW0ZKD2Onl5TjsS7jZg6Sxpt2qwbdX0qVfadK0q2S9Vy/GyQES2t+dJ8qHbHRbTSyeh8AqR5Z3PfpvZj6jbGlFbBqxYzjQpvwtzreC+14CxQYhyKNVaBAgXOH3ZjTcjTONvlMuSMzbhp7pjqOg4wQjUmhet10Ns9r9GkLm3WZu+NQOkoIMN+DCCPat9YP6RSV+m28d+KYCFelAkgBd/8+xJ0O4sUlAMXEX2AXUKSxdgwF2SlQoMA5I0sA8vx1zP+aZHAGSCInvFwCGFNmfsoF2nMpjaQag9rbtXaU0uOYSBLjgMNpG5z0QLxcglrIRI7s8nUdXSKRNIMcDMGPHgYadZMKK4hOgd2AFGLLPwXyUZCdAgUKbA050ZXU23kGh6pbuOj36X3HAaRqbsqIDOmu7Sm3Zg31+kjncynIEyeO6eYfkg5IxjF4pWxSZCMiaCnAKmXI4RB8ZgrodCFePHVBaXQKFCgwHoVmp0CBAtsGO7JjTPt0V3ZaAFIQ2eCOA16pQAYBoH1uhASgozgyTZSyURxghPAAIIITx0SokJAt3YCUe26yfhQaE0HZ68OZPQCxsHhBVFwVuAgh7c//ua5fIA9FZKdAgQJbwv3ivpTBHwBLnJyB5Vos+n3IMFJl4iwxU9Ol4Ep/M0JmbEKltqlTVIBKg7meieDwUpnSUULCqdcS8qO7qVfKYI6DuNNBdOp0QXQK7B2KdhE7hiKyU6BAga3DKiNPpZasqiv9HvN9sFIJMrB0M1FSmZWIjIOx3ji2m7KMk9d4pUImhY4DhCFkFKaqsGQUma7n3PfBKhXI/iAVQSqIToECFx8KslOgQIEtQ3diz3rtZHtdGf1NYFVmZSq6aJl47QahenmrYSe9wFRVFQdiQY07JZWRA4AYDM26IoyAoEXl5ihIToHzAFIC2IrPThHZGYeC7BQoUGDbYbQ041o0pKQ4SVWVKQOnjYyUpttgjkNeOC43DTvBOUSnA16tgk9OIDozr3cCZ6KBuNWyBwkA+NLg01s72AIFtglSSEh27oRFFmRnLArNToECBbYNdgort2dV8qYpH9d+O7ohZyrSo8rPjeeO7eUTq1SU71GpOgAwlcqCEhxPTlI3c88FK/nmPdMwtYjmFDifoHu6beXnHPDJT34Sl112GcrlMm699VY89NBDay5/33334dprr0W5XMaNN96Iz3/+8+nDkBIf+tCHcOjQIVQqFdx222148sknz2ls24WC7BQoUGDbkNsmInkz+duK5BiCZHU7HxsRsntqOQ7pf3wfzFNkJ47J8VhKyOEQ8coKZBSCNxoQnS5Ev2+2XxCdAgWAe++9F3fddRfuvvtuPProo7jppptw++23Y35+Pnf5r3/963jLW96Cd7zjHfjmN7+JO+64A3fccQe+853vmGU+8pGP4Hd/93dxzz334Bvf+AZqtRpuv/12DAaD3TqsETD5Eot7ra6uotlsotVqYWJiYq+HU6DARYPX8ztzdTbZvlkjy1jOxsZlWa+rCVPWG8dqCQHXhewPAIeD16qQYUQprl4PzPdTqSvdNqIgOgU2it2YM/Q+Xsf+P3CZt/4KYxDJEF+Rf7apsd5666344R/+YXziE58AAAghcOzYMfzSL/0S/uW//Jcjy7/5zW9Gt9vFX/zFX5jXfuRHfgQ333wz7rnnHkgpcfjwYfzKr/wK/sW/+BcAgFarhdnZWXzqU5/CP/pH/+icj28rKCI7BQoU2BakCIQVUh9pEJoTdpdCjhAd0zdLiZh1lRYAq/UEGRCKIKBeWIMhWL0GOJyairppWWJBdAqc19jlNFYQBHjkkUdw2223mdc457jtttvw4IMP5q7z4IMPppYHgNtvv90s/+yzz2Jubi61TLPZxK233jp2m7uBl5xAWQeyVldX93gkBQpcfPj/Lf8+fqL5VktkbCmR4+R3VpsjpQSTLNOVXK0QJakt5jiQLIYUMbgMgAhALMCqLoJ+BwDAWYS4Rd/vcGHO7OO/t/4YQPHdL7A56M/LbiRBIoRb8hSMQA8B2c94qVRCqVQaWX5hYQFxHGN2djb1+uzsLB5//PHcfczNzeUuPzc3Z97Xr41bZi/wkiM77XYbAHDs2LE9HkmBAhcx1rthRzmv5XSVWHOZnvX30PrbKriy0Ww2N7CDAgXy0W63d+wz5Ps+Dh48iK/NfX79hddBvV4fmd/uvvtu/MZv/MaWt30h4yVHdg4fPowTJ06g0WiAMbb+CruM1dVVHDt2DCdOnLjoNEXFsV24uJiPrzi2CxO7dWxSSrTbbRw+fHjH9lEul/Hss88iUH5QW4GUcmRuy4vqAMC+ffvgOA7OnDmTev3MmTM4ePBg7joHDx5cc3n9+8yZMzh06FBqmZtvvnlTx7KdeMmRHc45jh49utfDWBcTExMX3c1Jozi2CxcX8/EVx3ZhYjeObTeiguVyGeVyecf3Y8P3fbziFa/AAw88gDvuuAMACZQfeOABvPvd785d59WvfjUeeOABvPe97zWv3X///Xj1q18NADh+/DgOHjyIBx54wJCb1dVVfOMb38Av/MIv7OThrImXHNkpUKBAgQIFChDuuusuvO1tb8MrX/lKvOpVr8LHP/5xdLtdvP3tbwcAvPWtb8WRI0fw4Q9/GADwnve8B6997Wvx0Y9+FG9605vw2c9+Fg8//DB+7/d+DwDAGMN73/te/Ot//a9x1VVX4fjx4/j1X/91HD582BCqvUBBdgoUKFCgQIGXKN785jfj7Nmz+NCHPoS5uTncfPPN+OIXv2gExi+88AI4Twq3X/Oa1+Azn/kMfu3Xfg0f/OAHcdVVV+Fzn/scbrjhBrPM+9//fnS7Xfz8z/88VlZW8Hf+zt/BF7/4xV2PXNkoyM55hlKphLvvvntsjvVCRnFsFy4u5uMrju3CxMV8bLuNd7/73WPTVl/5yldGXrvzzjtx5513jt0eYwy/+Zu/id/8zd/criFuGS85U8ECBQoUKFCgwEsLhalggQIFChQoUOCiRkF2ChQoUKBAgQIXNQqyU6BAgQIFChS4qFGQnT3Gc889h3e84x04fvw4KpUKrrjiCtx9993rmksNBgP84i/+ImZmZlCv1/EP/sE/GDF6Oh/wb/7Nv8FrXvMaVKtVTE5Obmidf/yP/zEYY6mfN7zhDTs70HPAuRyblBIf+tCHcOjQIVQqFdx222148sknd3ag54ClpSX8zM/8DCYmJjA5OYl3vOMd6HQ6a67zute9buS6vetd79qlEa+NT37yk7jssstQLpdx66234qGHHlpz+fvuuw/XXnstyuUybrzxRnz+81t3tt0pbObYPvWpT41co72skBmHr371q/jxH/9xHD58GIwxfO5zn1t3na985Su45ZZbUCqVcOWVV+JTn/rUjo+zwIWDguzsMR5//HEIIfCf//N/xne/+1187GMfwz333IMPfvCDa673y7/8y/jzP/9z3Hffffjf//t/49SpU/jJn/zJXRr1xhEEAe68885Nm0m94Q1vwOnTp83Pn/zJn+zQCM8d53JsH/nIR/C7v/u7uOeee/CNb3wDtVoNt99+OwaDwQ6OdPP4mZ/5GXz3u9/F/fffj7/4i7/AV7/6Vfz8z//8uuu9853vTF23j3zkI7sw2rVx77334q677sLdd9+NRx99FDfddBNuv/12zM/P5y7/9a9/HW95y1vwjne8A9/85jdxxx134I477sB3vvOdXR75+tjssQFkwmdfo+eff34XR7wxdLtd3HTTTfjkJz+5oeWfffZZvOlNb8KP/uiP4rHHHsN73/te/NzP/Ry+9KUv7fBIC1wwkAXOO3zkIx+Rx48fH/v+ysqK9DxP3nfffea173//+xKAfPDBB3djiJvGH/3RH8lms7mhZd/2trfJn/iJn9jR8WwnNnpsQgh58OBB+e/+3b8zr62srMhSqST/5E/+ZAdHuDl873vfkwDk3/zN35jXvvCFL0jGmDx58uTY9V772tfK97znPbswws3hVa96lfzFX/xF838cx/Lw4cPywx/+cO7yP/VTPyXf9KY3pV679dZb5T/9p/90R8d5LtjssW3me3i+AID8sz/7szWXef/73y+vv/761GtvfvOb5e23376DIytwIaGI7JyHaLVamJ6eHvv+I488gjAMcdttt5nXrr32WlxyySV48MEHd2OIO46vfOUrOHDgAK655hr8wi/8AhYXF/d6SFvGs88+i7m5udR1azabuPXWW8+r6/bggw9icnISr3zlK81rt912Gzjn+MY3vrHmup/+9Kexb98+3HDDDfjABz6AXq+35vI7jSAI8Mgjj6TOOecct91229hz/uCDD6aWB4Dbb7/9vLpGwLkdGwB0Oh1ceumlOHbsGH7iJ34C3/3ud3djuDuKC+WaFdg7FKaC5xmeeuop/If/8B/w7//9vx+7zNzcHHzfH9GJzM7OYm5ubodHuPN4wxvegJ/8yZ/E8ePH8fTTT+ODH/wg3vjGN+LBBx+E4zh7Pbxzhr422plU43y7bnNzczhw4EDqNdd1MT09veY4f/qnfxqXXnopDh8+jG9961v41V/9VTzxxBP40z/9050e8lgs/P/bu/+YmP84DuBPS3d+3EKKwxYduhnlcsT5lZYvyfyejfkRJvNzGG1tZpb5OafZzB/+oNY/GubHxIgrM78aCSFRolXEV4uQcPf6/mE++5bCqevDp+dju6197n2fvV597nN77n2fz73//RdOp7Pe//nDhw/rfc2LFy/++GME/F5vZrMZBw8eREhICN68eQO73Y7hw4fj/v37f8WagQ1p6Ji9ffsW1dXVaNu2rUqV0Z+CMzseEh8f/92FgHUfdT+QSktLERUVhZkzZyI2Nlalyn/ud3pzx6xZszB58mQEBwdj6tSpSEtLw40bN+r9Jc+m5une1OTp3pYsWYLx48cjODgYc+bMQUpKCo4fP47CwsIm7IIaw2azYf78+bBYLAgPD8exY8fg7++P/fv3q10akUdxZsdD1q1bhwULFvxwjMlkUv4uKytDREQEhg8friyo1hCj0YhPnz6hsrKy1uxOeXk5jEZjY8r+Je721lgmkwl+fn4oKChAZGRkk+23Pp7s7duxKS8vR7du3ZTt5eXlyurAnvSrvRmNxu8ucP3y5QsqKircen8NHToUwNfZyt69e7tdb1Pw8/ODl5fXd3cq/uhcMRqNbo1Xy+/0Vpe3tzdCQ0NRUFDgiRKbTUPHzMfHh7M6BIBhx2P8/f3h7+//S2NLS0sREREBq9WKpKSkWouu1cdqtcLb2xsOhwMzZswAAOTn56O4uBg2m63Rtf+MO701hZKSErx+/bpWQPAUT/YWGBgIo9EIh8OhhJu3b98iKyvL7bvVfsev9maz2VBZWYns7GxYrVYAQEZGBlwulxJgfsXt27cBoFmOW0N0Oh2sViscDoey4rLL5YLD4WhwLSCbzQaHw4E1a9Yo286fP98s55Y7fqe3upxOJ3JzcxEdHe3BSj3PZrN99/MAf+IxIxWpfYV0S1dSUiJ9+vSRyMhIKSkpkefPnyuP/48xm82SlZWlbFu6dKkEBARIRkaG3Lx5U2w2m9hsNjVa+KFnz55JTk6OJCQkiMFgkJycHMnJyZGqqipljNlslmPHjomISFVVlaxfv16uXbsmRUVFcuHCBRk0aJD07dtXPn78qFYb9XK3NxGRHTt2SMeOHeXkyZNy9+5dmTJligQGBkp1dbUaLTQoKipKQkNDJSsrSy5fvix9+/aV2bNnK8/XfU8WFBTI5s2b5ebNm1JUVCQnT54Uk8kko0ePVqsFRWpqquj1eklOTpYHDx7IkiVLpGPHjvLixQsREZk3b57Ex8cr469cuSKtW7cWu90ueXl5smnTJvH29pbc3Fy1WmiQu70lJCTIuXPnpLCwULKzs2XWrFnSpk0buX//vlot1Kuqqko5nwBIYmKi5OTkyLNnz0REJD4+XubNm6eMf/LkibRr107i4uIkLy9P9u3bJ15eXnL27Fm1WqA/DMOOypKSkgRAvY9vioqKBIBkZmYq26qrq2X58uXSqVMnadeunUybNq1WQPpTxMTE1Nvb/3sBIElJSSIi8uHDBxk3bpz4+/uLt7e39OzZU2JjY5UP7z+Ju72JfL39fOPGjdK1a1fR6/USGRkp+fn5zV/8T7x+/Vpmz54tBoNBfHx8ZOHChbVCXN33ZHFxsYwePVp8fX1Fr9dLnz59JC4uTt68eaNSB7Xt3btXAgICRKfTSVhYmFy/fl15Ljw8XGJiYmqNP3z4sAQFBYlOp5P+/fvL6dOnm7niX+dOb2vWrFHGdu3aVaKjo+XWrVsqVP1jmZmZ9Z5b33qJiYmR8PDw715jsVhEp9OJyWSqdd4RcdVzIiIi0jTejUVERESaxrBDREREmsawQ0RERJrGsENERESaxrBDREREmsawQ0RERJrGsENERESaxrBDREREmsawQ0REf61Lly5h0qRJ6N69O1q1aoUTJ064vQ8Rgd1uR1BQEPR6PXr06IGtW7c2fbGkGi4ESkREf633799j4MCBWLRoEaZPn/5b+1i9ejXS09Nht9sRHByMiooKVFRUNHGlpCYuF0FERJrQqlUrHD9+XFkFHgBqamqwYcMGHDp0CJWVlRgwYAB27tyJMWPGAADy8vIQEhKCe/fuwWw2q1M4eRy/xiJqwV69egWj0Yht27Yp265evQqdTgeHw6FiZURNY+XKlbh27RpSU1Nx9+5dzJw5E1FRUXj8+DEA4NSpUzCZTEhLS0NgYCB69eqFxYsXc2ZHYzizQ9TCnTlzBlOnTsXVq1dhNpthsVgwZcoUJCYmql0akVvqzuwUFxfDZDKhuLgY3bt3V8aNHTsWYWFh2LZtG5YuXYrk5GRYLBbs2rULTqcTa9euRadOnZCRkaFSJ9TUeM0OUQsXHR2N2NhYzJkzB4MHD0b79u2xfft2tcsiarTc3Fw4nU4EBQXV2l5TU4POnTsDAFwuF2pqapCSkqKMO3DgAKxWK/Lz8/nVlkYw7BAR7HY7BgwYgCNHjiA7Oxt6vV7tkoga7d27d/Dy8kJ2dja8vLxqPWcwGAAA3bp1Q+vWrWsFon79+gH4OjPEsKMNDDtEhMLCQpSVlcHlcuHp06cIDg5WuySiRgsNDYXT6cTLly8xatSoeseMGDECX758QWFhIXr37g0AePToEQCgZ8+ezVYreRav2SFq4T59+oSwsDBYLBaYzWbs2bMHubm56NKli9qlEf3Uu3fvUFBQAOBruElMTERERAR8fX0REBCAuXPn4sqVK9i9ezdCQ0Px6tUrOBwOhISEYOLEiXC5XBgyZAgMBgP27NkDl8uFFStWwMfHB+np6Sp3R02FYYeohYuLi8PRo0dx584dGAwGhIeHo0OHDkhLS1O7NKKfunjxIiIiIr7bHhMTg+TkZHz+/BlbtmxBSkoKSktL4efnh2HDhiEhIUGZwSwrK8OqVauQnp6O9u3bY8KECdi9ezd8fX2bux3yEIYdohbs4sWL+Oeff5CZmYmRI0cCAJ4+fYqBAwdix44dWLZsmcoVEhE1HsMOERERaRp/VJCIiIg0jWGHiIiINI1hh4iIiDSNYYeIiIg0jWGHiIiINI1hh4iIiDSNYYeIiIg0jWGHiIiINI1hh4iIiDSNYYeIiIg0jWGHiIiINI1hh4iIiDTtP8s9R1f1C/wUAAAAAElFTkSuQmCC",
"text/plain": [
"<Figure size 640x480 with 2 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"rosesh = repo.readonly_session('main')\n",
"rtds = xr.open_zarr(rosesh.store, consolidated=False)\n",
"rtds.isel(y=slice(0,90000), x=slice(0,120000)).coarsen(x=10,y=10, boundary='trim').mean()['BP'].plot()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.11"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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