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Last active July 30, 2021 10:49
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stackoverflow question "update dask array from continuously produced scattered data"
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{
"cells": [
{
"cell_type": "markdown",
"id": "87355ce9-7e93-4ba4-8805-cd0197063639",
"metadata": {},
"source": [
"# continuous dask array filling\n"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "3198c502-58da-4f66-ad99-2009d693cc53",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table style=\"border: 2px solid white;\">\n",
"<tr>\n",
"<td style=\"vertical-align: top; border: 0px solid white\">\n",
"<h3 style=\"text-align: left;\">Client</h3>\n",
"<ul style=\"text-align: left; list-style: none; margin: 0; padding: 0;\">\n",
" <li><b>Scheduler: </b>tcp://127.0.0.1:53643</li>\n",
" <li><b>Dashboard: </b><a href='http://127.0.0.1:8787/status' target='_blank'>http://127.0.0.1:8787/status</a></li>\n",
"</ul>\n",
"</td>\n",
"<td style=\"vertical-align: top; border: 0px solid white\">\n",
"<h3 style=\"text-align: left;\">Cluster</h3>\n",
"<ul style=\"text-align: left; list-style:none; margin: 0; padding: 0;\">\n",
" <li><b>Workers: </b>4</li>\n",
" <li><b>Cores: </b>4</li>\n",
" <li><b>Memory: </b>16.00 GiB</li>\n",
"</ul>\n",
"</td>\n",
"</tr>\n",
"</table>"
],
"text/plain": [
"<Client: 'tcp://127.0.0.1:53643' processes=4 threads=4, memory=16.00 GiB>"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from dask.distributed import Client, LocalCluster\n",
"#\n",
"cluster = LocalCluster()\n",
"#\n",
"client = Client(cluster)\n",
"client"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "96efd818-d1f3-4b7f-bfa3-1397673512e9",
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import dask.array as da\n",
"\n",
"import matplotlib.pyplot as plt\n",
"\n",
"from time import sleep"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "987092e1-690a-4f88-95d5-170949e2b16f",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<tr>\n",
"<td>\n",
"<table>\n",
" <thead>\n",
" <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr><th> Bytes </th><td> 6.87 MiB </td> <td> 781.25 kiB </td></tr>\n",
" <tr><th> Shape </th><td> (900, 1000) </td> <td> (200, 500) </td></tr>\n",
" <tr><th> Count </th><td> 10 Tasks </td><td> 10 Chunks </td></tr>\n",
" <tr><th> Type </th><td> float64 </td><td> numpy.ndarray </td></tr>\n",
" </tbody>\n",
"</table>\n",
"</td>\n",
"<td>\n",
"<svg width=\"170\" height=\"158\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
"\n",
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"\n",
" <!-- Colored Rectangle -->\n",
" <polygon points=\"0.0,0.0 120.0,0.0 120.0,108.0 0.0,108.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
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" <!-- Text -->\n",
" <text x=\"60.000000\" y=\"128.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1000</text>\n",
" <text x=\"140.000000\" y=\"54.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,140.000000,54.000000)\">900</text>\n",
"</svg>\n",
"</td>\n",
"</tr>\n",
"</table>"
],
"text/plain": [
"dask.array<zeros, shape=(900, 1000), dtype=float64, chunksize=(200, 500), chunktype=numpy.ndarray>"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"N = (900, 1000)\n",
"A = da.zeros(N, chunks=(200, 500)).persist()\n",
"A"
]
},
{
"cell_type": "markdown",
"id": "7641edde-c112-4cde-b676-2b65404df42e",
"metadata": {},
"source": [
"---\n",
"\n",
"### with actors\n",
"\n",
"\n",
"see [doc](https://distributed.dask.org/en/latest/actors.html) and useful [video](https://www.youtube.com/watch?v=vMaYjGI9wtU)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "529762d8-fe90-458e-aae2-404afc6c3f2b",
"metadata": {},
"outputs": [],
"source": [
"class Array_holder:\n",
" \"\"\" A simple class that holds an array and can update it \"\"\"\n",
" array = 0\n",
"\n",
" def __init__(self, *dim_sizes):\n",
" # could keep a trace of global indices here, may be useful later?\n",
" self.array = np.zeros(dim_sizes)\n",
" \n",
" def update(self, v, *indices):\n",
" self.array[indices] += v\n",
"\n",
"def array_to_holders(array, client=None):\n",
" \"\"\" Converts a dask array into a list of array holders\n",
" Each array holder is a dask Actor and corresponds to an array block/chunk\n",
" \"\"\"\n",
" from itertools import product\n",
" \n",
" def _init_holder(*dim_sizes):\n",
" future = client.submit(Array_holder, *dim_sizes, actor=True) # Create a Array_holder on a worker\n",
" holder = future.result() # Get back a pointer to that object\n",
" return holder\n",
" \n",
" # note: product is consistent with C order raveling/unraveling\n",
" return [_init_holder(*i) for i in product(*array.chunks)]\n",
"\n",
"def sort_global_indices(chunks, v, *global_i):\n",
" \"\"\" sort list of values and global indices by chunk and produce local indices\n",
" \"\"\"\n",
" indices = [get_block_and_index_1d(c, i) for c, i in zip(chunks, global_i)]\n",
" # compute linear chunk indices\n",
" linear_chunk_indices = _ravel_multi_index(tuple(i[0] for i in indices), chunks)\n",
" # group data by block\n",
" d = {}\n",
" for c in np.unique(linear_chunk_indices):\n",
" i_sel = np.where( linear_chunk_indices == c )[0]\n",
" d[c] = (v[i_sel], tuple(np.array(i[1])[i_sel] for i in indices))\n",
" return d\n",
"\n",
"def get_block_and_index_1d(chunks, i):\n",
" \"\"\" return 1d chunk index and local index\n",
" \"\"\"\n",
" cum_chunks = np.cumsum((0,)+chunks)\n",
" i_chunks = np.searchsorted(cum_chunks, i, side=\"right\") - 1\n",
" return i_chunks, i-cum_chunks[i_chunks]\n",
"\n",
"# pour data back into dask array\n",
"\n",
"def _update_array(array, holders, chunks, block_info=None):\n",
" i = _ravel_multi_index(block_info[0][\"chunk-location\"], chunks)\n",
" return holders[i].array\n",
"\n",
"def holders_to_array(array, holders, dtype=float):\n",
" \"\"\" convert data held in holders into a dask array\n",
" \"\"\"\n",
" return array.map_blocks(_update_array, holders, array.chunks, dtype=dtype)\n",
"\n",
"# utils\n",
"\n",
"def _ravel_multi_index(indices, chunks):\n",
" return np.ravel_multi_index(indices, \n",
" tuple(len(c) for c in chunks),\n",
" order=\"C\",\n",
" )\n",
"\n",
"def _unravel_index(indices, chunks):\n",
" return np.unravel_index(indices, \n",
" tuple(len(c) for c in chunks), \n",
" order=\"C\",\n",
" )"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "9062f193-d828-47e3-94eb-af8e133c34fc",
"metadata": {},
"outputs": [],
"source": [
"def generate_send_data(i, chunks=None, holders=None):\n",
" \n",
" for i in range(100): # long loop\n",
" x = np.random.randint(0, N[0], 1000)\n",
" y = np.random.randint(0, N[1], 1000)\n",
" z = np.random.randn(1000)\n",
" \n",
" # send data to appropriate chunk in A in order to update A:\n",
" # A[x, y] = A[x, y] + z\n",
" sorted_data = sort_global_indices(chunks, z, x, y) # sort data per block and loop around holders/block\n",
" for d, v in sorted_data.items():\n",
" # transfer data to holders\n",
" holders[d].update(v[0], *v[1])\n",
" \n",
" # wait for event\n",
" sleep(0.1)\n",
" \n",
" return 1"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "42158eba-c556-4f31-a0f8-d29bf38d134b",
"metadata": {},
"outputs": [],
"source": [
"# one holder = dask array block/chunk\n",
"holders = array_to_holders(A, client=client)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "fe8bf577-c2a8-4a3a-a834-cd306cf85e78",
"metadata": {},
"outputs": [],
"source": [
"F = client.map(generate_send_data, range(2), chunks=A.chunks, holders=holders)"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "ae136233-b99d-4310-b49f-09141de7d10b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"(200, 500) 5.151056189738967\n",
"(200, 500) 5.459626087183498\n",
"(200, 500) 5.267552799029476\n",
"(200, 500) 5.28387452448605\n",
"(200, 500) 4.92532960217818\n",
"(200, 500) 5.253322630993313\n",
"(200, 500) 4.877783304924502\n",
"(200, 500) 4.681980201813201\n",
"(100, 500) 4.553904416068045\n",
"(100, 500) 4.277281625953831\n"
]
}
],
"source": [
"for h in holders:\n",
" print(h.array.shape, h.array.max())"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "be68a282-c4d1-4de5-b446-252188628d2f",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(900, 1000)"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"B = holders_to_array(A, holders).compute()\n",
"B.shape"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "a25b53ef-498d-4099-aa98-c249a19105ba",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<matplotlib.colorbar.Colorbar at 0x7f8edd017ee0>"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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YqWicjWOlRGfiEuwJPPdcep6lM1mvXgwEVpemMr8HgGtX5hAnTqC9CPMy1d2NGkRjoHFlLuW1QHu1pCDjWoztFROqkUJl/TsHY4OTPapUbwWaE37y5O30uIn38r0LJwvf73U8zBza1vAJl8FORT+/yTcV95U8vjOnlpzHI/iDw1hex3OGutxpF0GslRVnH7SPhdj+mPo5GouwdTtN9FVWgnzvmokIYrROhOgshnjzvSPaiMTV2FDERdCBdOgdrdCrDOtOrvPcmWsGfETGQUigumpu8TjHYPIIgEMSLiGOfmXV5FVXpztaSffn3JRQAIiJoZRATcGW74yMbYbK/RQ5InTx7zV8AahNb3vMtPG4d/Xf/MHPOl9DQkkqIFXQjdkWphZ29KKprAS4eW02w82duBDosPX5J686PbPOkdBIHtFncKHQ3EXt8RsDRI0ol4LFOZ5c4m4A76aZyRaRMEK98kynsAhk/GN3ICvD8Ut+Ds131DV0D6WsCxcHeZjEtRjrtya04eBFJMbrrNvyzkVVpW9HEZRbAJRhqk13ENdStgOPLLjSkqEHGUgEOz56m1UDJ+YeHUVJgML+uQFtXM3xdEMvQ+vjQtTDYNWRTEuEF5Xo80oUOk8C0vfn3zlmOCn67wKawqfPKUfHiIGAv+tnjIXLE+4dVMekNURrvLtRS5W0A7qi6NJO2IWTkTMy5oyY+y4SiEb8etDyUCnl7qHQYAp4HU8rty6j/XDSuV8fGNik30oJ7Fxaaw1sLjf1ounNhxlWAgBsn03f++rbx1GZ7GoMdtRQrXE10IubNgWXqFWCiAQa1zxnMo2H/7ZStysNpYWx9baqGIS+U+GXmj2sLk0ZnGRA4fe2wuPnMPiEu/gEyBpE0RfOsN+o4kvOmSAYXklXXQ6wc9a8Z8TmOPo/Zo1VuaRe258NUyplEv8blXCW0mpc9bXx5V4i8bgBhY+eOLGS+UzAXTSij/HWWC5vWDMLHJud1hcvKhk70EKw42P8vfR4PFoiBc6ZSC6h5J6rYhAAGtd8iIUuvB0r+TpEQ9RuKO42rSme4NPnWx+gs1HTOYy8KCHPSP8wRFX0jfb1oOWhUsqAsqLV5QB+fZCyBnqegZtxOk/ULumQeuHIhqFMON3s8LE152cNk95WVSeHihYoJ+S3joc6iULnZlcvSV9i58lQww5/6WPfzhzz2IlVp1In4Z6ccc5LDU1l4/hkuF1B5XagvUSSjfWxXNhE9Dz0lrKRgKhEEH2hDSIVkMiyNMJ+ElLAXjU0ElNnn7hpVNIRlYwnVuPLKpq5/B+nD4Bwz63bTYNiKHyJ8upwTvre46HhPafnaT7kK1fmjZ9HSeZ1D4X6ueXhw3aSs3YzhQL4ewYDZTx2n0hfH7VKusJ1MB3C3/Vzy+25EAzkSpbtPR6ifKHmpEDqc7xhrrfJgzua6UTGxi4sAhzl0R6csKKr6OiHJwLRiF8PWh4qpUy0ru5CaDxIF0uAC4Wc1WBgLGhON7v9xrz9tn3JeAHlaexAS+O3oi9QWg8w8VagOLHJufld8+GSZ0NJwv/pW5/MHJeI+LaQp+Eq9phb3ERci/H0EzcAmFGkFCr0bM7tIWxGOHL8jib5Awkm2BdGOM8pdQBShdoO4A08VG9lqxoBOLFvQD2rxvtJmfmWjwvvHdZ/oxC7MtUFvDQxSJ4jZyZw3NNYK5Ew7guv8AQUDkqGsr9dyYUh8qR+Zmuk1xGE5MKHKytBhmXBQ3X+Hl4YQlFJ7WZgrA0bA+ZGCkgjEYKB7GQZJcRdDgCPDjtHQgOvdxlfErvKk4vse07I70GKSvSJkb4etDxUSpnTunim+tDRddfLM3LlyrxzEwBZehMJ4Vy21xmMDRBs+1pR2CE1F56B99sKctl+KjTocjYfmTwbESfVT4nhmXrNPA+ODxPcUr6l8EgXRY+Si29dPaSO70h6EY5+4+oBg18dXh2DLMvirmdJxCJ9VX3nPaOgitKmr42q1/Vw4qCKTDgDhu4lwUs2p5hC7N5mFeMLu/C6HmZeYRSuktThcVGxDk9i2jzs3lyKi587c60wEnGJnTzNE56rIO+avPvefDi0EZOIs+uevGuj+tAFf1meKY9EuLdLkENel71g29feOyV2Oab9qWfeBQANV3Fjzo10HsZO0SNnYfDmYi7FbsNldyuKp/zIU96XxJ1AK6Fb12ecr8kLDUUQD23AAgDwJEq7Ce/V6oUb7pUQTkRaUcwubhVmzCm5SIqmupwWoHBow5beXGgoxs3nzA3CaUfksVKCxVWOTiL7Pppze5ibT7PalPjKa5YkDmcLIwAUUsNIgZ/4yA10FlWTprgaa0XAN3xeuS3J1Pl0w7Xfm0BcjbH+YfN+tI+p5J7s+bmKme6Pq+MYkBZXnH/n2FDMFMiBLPbR25gYPC5WA09Ki1KsvVzpqXU/t7iZe//9+gCyLHXOA8BQVg0vrMqrnNPnzWBCV2L3D35wBkDqMecZ895m1VDM5CjQ8WnPHD62pg3ms6eva8VeXQ70Pcjjtt+NxFKM9PWg5aFUyo0rgdrcwzBfmSpmjtkGq2XDe81NIMQpcyGeHuR2ERNl1SKTcGKemCLhyUWv46G7EGqvfXtlPIPj8Wo1F7bJxVYctgdle0uE1+2sjpnNknyJxmwrFz/O44hu3W4aiSRXt673Lh1KzzVRWNzLz1OQQArHbJ5L72FRZR5tfjJmFOXYJfHSlzpxx/9m97Qg4ck5I5n8mMlmEUHsLK8mxooN3chAZuh0VMTROhHq9SQHXsbLXbs0k4EJKOknblcBTxoNg0aqCnR4M3YrWi553qld3FSfaWP6B2lHRiBN0vY2qzhxYgXV5fwy8vVdtWcPHV3H6+8e1Yyr7kJYCJXcjTzylEcQ2pjBlo/eMx1Izwx7OE7mdTwEYwNID6jeDFBZDQyrzrPXAICOieG5MsRy4CGciHQChSQY72eSP5feXyj0lOJabPy9eitAecncbFStVpnsamaAjQVyGbuYnjOPHJpze6jeMZVRa62h7pGDnE9Ynl1UYMvs4pYBffBE0u5esccrkk3X2kuUvJAZlgjJzKFtyNDThsmFRdsRiq0kaskjsz1R0fMg+4qiFo1H+RFCcvyYHZavp+5Gzbj/ea1HKcnsan5lGzzq6QxkW4bywiRyTPyWj/F3VVP93SdUsjRsRkObUFWmuoZBrC0FGrQu3wn0vQzH1PNxeeVxQWWnvxGgOt2B1/HQXq9j40NmR0bCxMVA4MqVeSdUcvaJmwDSyI/Wd2+leHjAvYiEQARvpK8HLQ+NUpahh9Km6ggWJZxMHu5yDyKuxdrb6xwJh3oH0pd6YXodD+1jIcbeDzLN8WcXt3DtypwBfTibswBALPDiubcyHjBhqHxjdQ+F6B0M08o/Xsp7o6FxPsNLspQ+VVLZsrM6pmADHsoLqe6R5W1yj7xogggAdP5o1vBo+Gbl98RuLC/6akpG+U6QXo8Uzio+IK3cnJ1Q3igpNLpXfn2QUYJ2CLv9lPveyEqMYLyv11FehEDHp2EIrl7G/P5zg/YTz76TOd5+ix78XbN6UFbizLqKGhHEj23pKMErwNRLG4E+x367pA2i6HnoLIY66ukfCDGYCVGb7mhve+t202goNXaghWg80uu6MtUFhNTHDycidDdqmag2Ey0wDN0uh6dkr03j5O8pqnK8W3kEX4wgg6nI6AngWvBAmuCqrAYj9xsoLSi8lBbP3mNm+8mxi4H2Bgn64Hxeu5sbALx0/qlMJru7EKK0EaQ9Mxi00J8N1XSI5EFXlwNE40lnOtvzZh5QUSabxGiIJEWGdQAotoGLa+3yTm0eLoWPPMwV5SjDjCGKnw25uKr4uNh5A4KVRp02YTRkYpJrVAuE9zJ2CTdo33z9TObvoxQ9cG+/vizQettqLOSAe3jysKikPJwM9TkKps3oWdn0OTs3wRkftBfIw+1tVnPL3bkUtcrNO/c4kLl8a9KNNsf+bkVCoC/9kb4etIyklIUQ/4UQ4i0hxJtCiH8qhKgKIaaFEC8JIS4m/0+x1/+yEOKSEOJdIcRn9nNCcSfQeJRrwQPpIgrHYgym0sq4vLFQgDvJ9OK5t/T3tifqdTydCAm2fM2eIGXnaltJYTCHT+ymPtvtqvbEaKFXlwOthF343V7XVCy8wIHEbsLEWQefOfdmej7JE59a2NG4adQONB5KeGXelAeq5gJMXmltScFINFnjfiRkuKdane44e4yQ8JFfRa8DgOlXVeIo2PaNRNvdiAiFkWgD8pvlP/4/h/jE0xcBqPtD3mdnTiqHhF0vh2yGQU1Agt2KrEEkx8Or5TdMshOm5ASIvoDoC5Qnepl2rK4uflxcDY64g2IMNkgcHlmWQ/nWw5KTo4oqHvFG+nrQMvQThRCLAP4agBeklE8D8AF8HsAvAfi6lPIUgK8nP0MIcTb5+1MAPgvg14QQI5mbxx9bRnNuDxNnNowQxzWOCUg9lmAx8YJHaLzudT0VLr4Z4KXzTxl/44uMvKTqcmDAAO1DSd1+M8ok2FxYo13y3F6vw68kpa+rKS+bxKXMCAcmCMbGuIE00QaYNLjyWoCvnX9a30PyNDaXmwgnIlURJoXGQ6lIYfP2uLM4Ja+Eu7OoYKS8gbDUZpNLnndLwj3V7kbNKCfPJPXYo7A7jHEpNXvYeF4ljsKJSCdo76YXCJC0r0xCfzJy8aQZedBavvSfBvj2m6f078vPbQFIk5r8emWoWlmWNv3U63XMIDzwxwnNbquKE8fNfAhPSMedwKgGLU/0NIWNR1miFOvksCxLwFcRVm+rany+q4sfkO6h7kJaMUuJdu6gCGbIbLoo3+8iVNNmhiXD70Y+6Im+AEBNCBFADXC+BeBzAL6S/P0rAH4h+f5zAH5dStmTUl4BcAnAR0f5kEvvL6D8ryexcXXSCHHsyQp6MVHJtOUFF3k/cTVGNB5h62lzIYiel1lkND2CizzAeiiwReZK0h06uu6ce1d5TeGCvbnQSCABSQ9cX2aOd+T4ndxkGZfZxS3AoaDoHtqeBvfqDU9KCmdxys7qWGH7RFfTHlGOjDablZUAs4tbmpee1zYyT0RsJvVoYCgpgbEDLWeDmxMnVlAqqfeRN73wzUSpzYVGzwkXE8cF8xjVhEeSdWlVpvG1zJOvO6tjzmQsyWCnYihSgh/oeoPtdAp3dbqTqT6kBOKnn7sAIPVIp84H6G9XnBQ2o6d1OUJ5PSksWg6GFnEBJlw0/bg6T1elXhGzqrdV1YZMBhLhZITjB0arVRhVpBSIpDfS14OWoZ8opVwC8N8BuA5gGcC2lPJ3AcxLKZeT1ywDoBKjRQA32CFuJr8bSdY/kpYeuxqzAMCfP/Wq+rulAIhhEZfN3/ENaitBElpwxMxoXE4VMuGwU+fVZIjK7cDokga4sU+Ok/LP5Y38bdhE9n14u37meDeuHjD4zrYimz+8iU89866i7lmetFcNDUV6+NiaM3FCCoA8FQ3RsBeX14IM3nn2iZvaO5c3HBvd2pTjz68ZYapt+Oxrs71z6ZmJHxoYqvMFdxpGgxva4FeuzKO9Xkcw3tfGavkn1DXXbgaGgbInc3gdL4uTCgmspg6BwbCwcgQiiFFeU1FXZTXQSj+P+peZeOO43uDEno7WOGZvt4z9xmtnAaQeKaceAqZh8bcZy6SvBrP6e35ugUlREc/a0qQRffLCFSr5NnIUbI36pcjAj9+7dGi02oN9SAwx0tcoIoTwhRA/EEL863s9r1Hgiyko7/cEgEMAGkKIv1j0FsfvMipACPFFIcTLQoiXo930ZvMwlG8SvnD+2T/6CQDA0b+nGBRaISTJtRJzkmRJYuNOWoXlYjFw/I5q99vH1GJbOLKB2gHlAdFi7h0McfnywQy2W+RBuj7X1RAJSEcw6WkqyXG3V8a1N9ubNj975eYUvvXGaefx4q6pSG9em82tfARSr9pVBdmfDTNe/IX3DmumRjTGJl2wDUuhb7Cd9mngCUxSvI3ZFuRZ9T0pJle0IYXy5EZhOgQ3zEjKFXa7knM8RxHXYohSjKnzQYoZS4FoLHI3LYrTPtjqYCxqmQud45i4d27T+4zWo8l6727UnIMIMi1jhxS6eGz9259buxkgGosMh0BINkHcmriTwb+XapqT3TmiGhf5u74u+e4dTGEOvkZLpUhHdZRnyRvYejeiEn3BSF8jyi8CePt+nNsovvlPA7gipbwjpRwA+BcAPgFgRQixAADJ/wRo3QRwhL3/MBTcYYiU8stSyheklC/446zQw/LCvFqII8fvGJ7j7pkBxEDg8v/GPdNs52yoClASS1sZ7xkW2V44HAvWuG2iCG+vTOZWKtkeqWS0O5fYXnpci51JO5Lasg/hS2OxDqYi1dS/IJR0YY+ZYzM8l5Qn91CNghspDEzPFRVMvaYSfRxiMbDKCeUxcWXEC1t2l8ZRne6gtdbQcJS32DZZL5Z7L/s+OofDjCdtRwFGa1N2Hbzvhd/2Mt4pz1GIcgQ58LB5LkT5cOpELBzZMGADu6cFebCy72WaYvFo68yppcK5eVz8NWtSupXbyOQCYg5JZNcN9/AzM/5KqgKUl5eLmtuoAFmq5cFnVrDzZIgnHr+FylTXGCFFvHGKcLiHz/fcqPdlP3I/E31CiMMAfg7A378f5zaKUr4O4ONCiLoQQgD4KSiL8FUAX0he8wUAv5V8/1UAnxdCVIQQJwCcAvC9UU+oPNuBGKTtH+NOYOCR6pcCfsfL9A/gnlnrRKgtbXejZrAGaOG4cGCuVPyW70yqDZOxY27mgtNb3synDrWPmSODSNlHjUg3D+JCWLqhsD1pJE3Jc+N9Rkh58hBV9n2zjWVS4JKX6Nt8Lp8vXpnsmgrOMhrBtg9Zkuhu1IwCj8GOGuqqEz857j150iJU68Z+GVeUxnCE53dTjng91spCVKIMpZBDMJxCRlACoBS7LEmtXGwWxtLStKH1rt9J33vx/NHMddmFTCThRAQxEGnTKctb7h9IcxU2J5jWs4jdfbvte9ebDzW/W8OD7F4MGxh889osAAU/2LmfcK9kQJB5QyF4HmTY5+1HIilG+gIwS1F98vVF61D/PYC/gfvU6XMUTPm7AP4ZgFcBvJG858sAfhXAi0KIiwBeTH6GlPItAL8B4AKA3wHwJSnlyHeyt1mFLElsM8jBJa7QWnc7y0kckaKnhE3ULkFUotyZeVEjMhTTKDPgAHe4nSd5o5Nc8vyH02GTOnT10vFBrj7SiAXiToDaDTUdmzy35juBSig6Nib9Tva9TMJsZ3UMohRrb8zV8MjuJWwnaslo6GqyxBMqbfrOAo+woKVjeaIHr+th7o98yCCnbaij+U9jVs3Ws6eXA2oduQbKck+XFBR516IvENVjNOf2tHKx22DK0DO0Xrhb1hDOqXPX9XFIrl2Zyy2akCWJC68dA+Aer0UOQB4nePHEWmbt5VU8aiGHhXnetOf22wuZtwqg6CWvFS2J1/GGDigeVfZZ0bdGUX3y9WU6jhDi5wGsSilfuS8nhhHZF1LK/5uU8oyU8mkp5X+WMCvWpZQ/JaU8lfy/wV7/K1LKx6SUp6WUvz30A5g3GGz7gJeG7HktIG3R/QBKcW5SYut2E/6urxM2YwdakD015yyvN4O3FeiNs5/5deQN2t7SzMvpMVxFIZWpLma+7/4ceyqLOimR8W4M3qwnMfdtH50jyuMhI7NzRnnhLqPAf8cTZnRNcuAhOt7R33M5c2oJ7aOhTsoQZQvIGkub/mc38NfnU1BA0t+uIK7GWP3RfKVgF8yU1oPC1pF58NOt1Un9PSl68uLIW6Wm+4B6Dn59kDsV3KuGGsLRbTWT4xC8JEX6PPkaFb6q2pyY30V3o4b5w5tDh65yWbo1nfldXsUjgKH9xGXfd3aDo9auNv+ekuCDnYqOXojtU70VZDxiv+UjrsUZTvi9SCy9kb6GyI8C+LNCiKsAfh3Ap4UQ//hezuuhqOirNdIQJpxQ9fy0wIoqg7gQv1YOPKeyI48uGo90yMQTB3l0s6ge486lnC51vsT0DwJNa/I6nk6qVDY8CGl6S4eOrmP9hXTT2j2IARUprH/EVFaNy8XGgCocyxM9VZbMryUWWP1EmqiRfa8Qxy4SDotErZKmZgHQyS5SLnt3GhDlWFO2AKA3Z240UtyuBk9cRm3XqJWpZzbxl57p0Q8rbIlrMSpTXZTXAtUfO0muxt2sQggOml7qxqVU2UVjEaJ2KXcquM2r5xiz0cZ2oM7fwOsTBU1Y78rNqaHtQLnkNQXKkwPfThoMJRi/V00hEnKIXAVa3UNqmAC/5xzX/+Qz7znfQx6x3/Zw9ombaV+RsfsDX6iGRPfe+0JK+ctSysNSyuNQ9RnfkFIWESGGykOhlDvdbDbctcBGpcRwZUcWly9CVze06nTHYE/Qwplb3MwtKZWRwMaHQk1rKi20gVigObenu8QF2z6aF9SizWtBysXGW/3GwKDQuYQwzv52Jder5ImaYTh5XgUZhcmEK3M8lZJdnLGQSYRaho+MIm/I46IsDmbCXOiIY5Ka+xqLDLy1XyXU26yiPxvC63mpB+/AtO0xU3QOrkk3tthwAbXHJEYJOReDqQj+uvu5kidqC0F1C0c2nBWO9CyJwwyotaZnWFpd47ZOq2vvzYfKa+0GGiLhU1Fsqc+09T2iCfLRIJ20/kdvP555D4fMonpsDEK4XyIhMJD+SF8PWh4KpUxSVCYNDKfE1G4Gqm2lp1oKBlu+gUHllQ4DQHh5DDJKG+f0tyvwOl6afLDAvWBsoAo9yrGGXAg75ZhyOBFlGuSXJ3rOEtXadEc1oymbHikZIzp/A79j50UJMVIMRWWw5Ylehm3QuBzg6Sdu5Bqh7kYNohQjSjBFMRAZTuwoVZV5IqTCQkU5ynhQ5ctZL+zcmWsY7FQKu+uRuFpTFvXHJrEpYpQAHFaeTQkuIE0oV6a6BoTjggv8xkDT88oB400zI8OrI3l5ORfC1pdvTMNjy2BucRP1mbbOLRCHGQDkWiUtyDqYloEHW77BYIkakY488u497WXOoqCCrahd0k5CtdnLUEkNyIxxlQ994/6pKylx34tHpJTflFL+/L2e20OllPXoJFrEjiZAPJS3F0TncKiwQqm8WJuYn9dHF1Ak/vq1wCDhG1VHlpcU7pUg+4qdQZALF4ISABiKs3FFVVONj6X4Gy3gDqNPAWn2nYzRzqXEQPDPYucVXTONFvFxXU2I+tuVjMJpnQzx5nuKzSgiYfZDpmGng3SUTzDT1UYrz5O1Obw8mWOPYiqtq9mMsu/jjy8r/JxuHZUkkzzx+C09UTy4XNzsCAB6Cw6mDVEh2fPhmD9g9WsIBdofUkbbmVTNEYpe5MUxI9/BPViCXuKN1PPmrCMevfDfi1AU8uMBU3GvLk2hs5t+Bvfo7So7OlfPgVXLgYeTJ28japecxl+PaMvx5AHlXHQ2aqhdLhlrtPlOCgly5sWtT9/PMaajFY6MWjxyP+WhUsqknKJ2CbUbgVETTw+Xh/KuUL0+086lTg2DP7pzSdGGw4Mqyi7ziRkk/d0yJG2w5HxEOdab+ccPXQKgFFGed3n9/XQOm+inSTlXjw2/pWhlkwd3jGSI1/GMBM0wBomGe3yJzjuTAJQiHX8rvde68RKDgfKSoBrWSJQOL922O9H1Z0PI5F7JNXVsepQ2o4V6fQhfGnTHXJEiZYzYOoytF475AybdTAbSWHOjNAriYvfkqJ7d0t+TQszjn+dCaEGaFK9Od5z888x7EjbL2SduYuX8vBqCa+UZ+KgxV7l9bbqj4Ra7GIcnSvM8eX4e7WOhsUZ3zihIcOHIxkic+7sRifvvKd8veaiUMldOlW0zIdA9lO1y5bf8TKa8vV7H809edR4/D/6gXhpxLVZZZofSq44pbyAY7xub8YWzVzJlq+pgaXtD8rY4xvqvXnkeQHHSia8HO1lEnkQwNlA9bxsRonqMrdtNIxkS12KjV+8wBgmHe6iisn8gxM4Z5uEtlY0Kr/nDmwYO6GqvOMrkcOP8rENw7JiMztziplZINg3PJYNF9Qzzqhnn/8BcX7Ul1RqWJyKp9L+8FuQqShdMxpkJFCEUUSc/evay8XNRfxBSqP2lRoZ/zpOx9sSaC+8dxmBKDc618f/ORi2XzVFeC5yjyMRAoLQROJ+1qycKgNxWnYCCXshI7dcAjiKPmtwPESLClyd6aMy2sPV0iP52xVjM1VVhZNWjRoS4pubx8Yf+6tvHcz/HtWE47pW3YTsbNdSmOwh3y4irsfaciaZGoagrXDv91E0AWU+9aPYdkKXT6SIKITU0E+6VtLFxTVQBFL7oonnlDbTMlcTF7M2H2F4Z18fcevkA1m9NaGO4n/aKrhaoQNYzJK9clGJtdFaXphBs+Qh2/KEDUO1CINFLmTIE06w/Z77nYz/zJgZTkZGIHEyHgCfRnw1zOcSby00jsqrcDtDbrOrf2RGCS5bbJk+/uxDqMV/6GhJl7Or//Phjy/BqIZZvTGsDTolmruDH3g/cbTZLcSbZTuvR9vjJIMqSxGA6dK6r8mtqjZY2AuPerF+bysX2eVQnm+r7vPWyX5EYrcH9v79N7j2JN987Aq+mFDHnkHKaze7pMJNVL20E2LvTwGCnoh82ZXnpYfNWgJvLTdRn2kaIP2rj7M5GLe1Qx7L5XsdDf1ZtmgrLe02+GagmNLF6rW6enyRJhs0ds4sPdBFGzkIpf2wj8zvCDJuX0vOlMH7YINMMVmh9rk4odpQxJWPIO59VpzvwW+mka7/lp4UXe37meVI/ZpdUVgJI61mFkxGqq9n7QedOCsfmY8tKOmePPFZ+LsKXuf28Jw4oJa5vh0M7B8sVnVwkeIXCdVfBjS2EG9duBnruHd8XrmpTvs4vvb+Ak4dUQtDOrfy3f+Er+vu9x0LVZtNuPZCsb8PJiIVZip88R9sg2uvKq4VonQjVpPfpEOXGQLNsZCBVZOq4hzyqo2vNm0q/X5EABjIY6etBy8OhlJPNURRauzzchSMbOsQW5VgvesryEo3IrijzvqNCfLK6wzw7Ttrv3E42RrIjvWqolVNrraFGEyUe2NbTIQaH+pkZbHLgFYZtdytcyZOXQSyAnY+oDTv9gyCDEfLkKe/MR1jhTzz7TmGLydYJZUy1x3MkxSO7GzVEjQidxRDV6Q6iRgRZkhh/N3ByTvP6MQPKQ69fLWU8q86CNIqMgvE+/MAcJFAkLuxVFBQpcHohAKeRHMyEkKdbGYrfuTPXMvS8otC8czjUc+/0uYVpfoFHiFGUHqcx29Lrzu5F/Ne+8Rcyn6OhNsvodQ+lDb+isUjfz/IdNV3HhkRcQvuanIzeZjXTcsBv+Th0dN3sUVML72uxiCmj9VJ+mPsp/4kJbRgXc2J1o5h7m9fIhBaEYXW9tF2onfQwSPtJSEdJyeBmNbOpzPaH6m8zh7aN5EnRhIW8eXYkwXgfQsK5YMmA2AaO8PqND4UQkdDRBGAmTwfTYQY2+f23TiOcSgwdU3528pOw+HC37IRLOLPFVcYMmPPtyBBwdkH7WJjB/KNGpIuMGlcDTL1UK4wCRBAbispVuuvCRf/hT/99BXvk4BbBlo/Sppq359cH8N5uZJQPMUa48Rs2WomiM82AYU4ET7byhFtrrQHRU3xgm0tdJPzYJ0/eRuW2avjFmTjcsGe49zkd6Yir33wnyzgBlMK+dX3G7FHTcRvu+yES962i777LQ6GU8yg9pfUgra13ZGGjVkn1BnaEgxyvdSmITOIh8dYH0+FITYhIyfVnQ2NTNWZbmDydwggU/q3fmnAmR4BszX9vL91EtsI/fGwN4W4ZUgDx1EAbLd2vYoRG+NKX2GbcaZt6GNXNwZ0yEoAUqrl8ovxKm772+HgRRF65ui3UzpGErpO30KSw2+7f7DcGWmHb+GXreIg7H3dsZKYsZOghvlaHV1XNjqhikIfmrkkkf/nf/e9QXWilbBpfGhBZOBlhMBWpZGu7pKrZcvo5yKOp4a3ZRjhR+nRfKefhmtvneh9dr6zEhlcfbPk6yWjbFRdt8vLlg5j4sIJAeFLyw3/5tcxraZ17Ld8wOARHEVefF5qMmvz9YckjT7lA7MVGCTFiJjzx+C2cfvqGs7jk5jVz6jLhXHwQpZxQIRjHSF1VfSR5yQSeqMtjeDQqfWysjqPUVAUiRZQgkv6BMO0sVh9oozB2oJXxom5em9U4sRyoBi1C5jc2yiP3cwfAHscDqGfCjdmZU0vGewZTEWrXlYLmRRDSl4piNdsrHPe082RoKMFh3iKgvMtSs4eoVdIK2/aIOSY98ZaJhwJp4UU4GSHuBujfqWEwowpWONSR1/GOG1YZCe21x7F787roZIB5zzLGOlH64Z6CalyUy/r1wDCAlZVAv89v+RnevFcNAZEmGTniUlsKjGfLFbSrc9s3/ujZzO+6h0KIsmIv8T7oNhwlPWQGRHDh0VdeD5L7IVKKR57yfsSmrr136RDeubiYy+f1Op72vAheMJrbdD3IQXbcE1fSnOJFsIZNCeLnZTM8KKxfXZqCDD0MdiqFk5SFhOGu6M5ijAebR+ETQqI63cHEW2qUPN9gXtczFnZe2TUxNVxRhm7RyDyZdy4uonYjMDzI+BmzjSdFH7Knmj5xepY+NoOGSAnalYV59LbBdKgSupHI5eByJdD6WBYGogQaebCyJHHixIpzZJEttEY4jkrXE95xR0HkNY4daN0Vc0CGnpNy2T4aGlFRbz5tAuUy0HE30HCerezs52TrocpkF2IgtFPkH2q7z7XvIarH+NInvlFYNOI54B/N3GHPwfak9zs2rEhUou9RmXWh0CQDCsNLzZ4ODYuy1fOHNxHXYgwKOn2Keo63sltG7YZSbDsbqQKkcyk7pv/yRAhvezk1mXrRc4ub5mRipkC8WohgbKAUqRQavyVK3aeeeRdTCztuXmcSgt+4egACwPZTKXTitz2MXVJN5vnCzvOU28eUp+rqCVFb9p3v7RxJeyYH4/1MArUo+gBUiOuChrxFc5O3j4aY+7Z7M1Qmu+oae75qR0rrJsHXORxR1PXMO50aYSpw4Xi53S+iNt3RUADHUXl/Yq5r6HzIa9y700BpxzTyNmTgopI1LwS51DvAZFy0bqcQQ5FStJWdTbXjUrsRoLel2ulqyC7BqMkgEeZN8g/++Z9B70h6L3mE6+/6mcS31/UKaayA4vqPkrQdXT7AM/oelBCtiaz8YKeiQ0M58JyDLEUodPOhzuEw43GR0GLiWXt6beeIUmxy4Onkl3dULbLeQbWwRM/T763fVO+r3QgQM69vbWlSFxmsLk3phV+e6BmJpLgTGMqCMtLE/fzWG6exudzMKDi/7RkhqR3yRvUYrTN9HSnQ+UbtEv7cR15G7UagPWD6P2+RH/jxW5ha2DG8bBsrjnpBOq24FGPigoPrmnwOlYs3P5KdaD37vcCpzFc/4faEDUPw3C5o0BglhHpb1aFd4IA06cjLqHmJc3SsY0QcefkAQBnd0rYZsfAEFXnl9sip8rSphG0opjbdQf+Tu7nc+aefuGHcD+45jwKbkRS1Me3N5jtEZJDsyTzdhWQ4g5AoNXtGhHvoDx2FJduezgHlOWB5nfbuVlSi7xFPuVBcUzm4RAey9fWUKaYkUTSuSjMPHV1Pw8b3GROCZe2j8Qgff+p9cCEqnc5WJ0pw+sQm/A2loFrHVWWh3812suMeACl93SHLKhRxNcgBkNt71+Ysk0LknlJ5KYVL+LX+5vdfQOdIqM/38CmlJI8cv2Mk3Kgr2fVL8xm2i51AlH0PcS1W8MnAMxKHQDJrryQhyhGuXVHl4jY+GYwNsPZR1qLSyhnYvTF4b+bKZBedjRoixrAhz9Ou/MzDJkVslVFXYvhtD7WlAFFL9Tah906+ke95+qvlwlLv/oHQSYGsfFt5tpTQs599Z6OG7kZNNz+yPWbqU2KIJ/U0lWENvopk5tA2yhO9ock4l3dfWQ2UUyBFxuDe+Jmscu3Nh9i63USp2YMcePo+DGt6f6/yga3oE0KcFkKcZ187Qoi/LoSYFkK8JIS4mPw/xd7zy0KIS0KId4UQn9nPCbmy3gDgbeTjs3E11ptn+cY0bl2f0WHj4IUU97SLIb7z1mPO49ktFddvTRj0ueCxveFGxGr2YxeK0Ca2J3bLsnS2WrSFNktvqwqvoyaEcFxx6rX8xk2Eq964egA7T5r9navLQUYBa4/YYTDyEnTkfemCCYbPk4EK90oGtMM9qsblIFP5dudHIn0u5CFyR0Z6KnoaTEWoLqeefJ5ikV52TUT12MBY6b1bz+Q/b5t6Kfoig4u7KJDESAj3ShChgCxLJ55O/VJGcdp+7tzr6BwJ8eK5t1CqqV7GRf2oNU6bQGP0nNZvTUBczHrQNg2zt1k1lL/oC4Q16WxVACB30G39ehoxkaGkJCmPkkcpvBlFPtAVfVLKd6WU56SU5wB8GEAbwL8E8EsAvi6lPAXg68nPEEKchWr2/BSAzwL4NSFEMVrupV5O/4i7Rn4YXzFv4/GQsCjxxqUIiwSAMFlwoxDbS5u+s4sWUbp4pppk8rlsmJ8n1ekOakd20XpF4ZyUHNx8jimWEa6bcEEOadhKzQghHUCnC8esTncUo4RFFWSggh0/d7yP3UOajDWdSx5mStFT70jfWBOinI6s1//HQNTzjTxBZVUlM6lnhOiLoc/Z9uhlWaJ9NMSZU0uZcVpcuLKk824fDXNn840i/+ZVVSv+0vmn0Nus4uNHrxpwjr0W9fNOokJ6TtVbgZOB4iVJvr/+oy/p38Xd1ADKcjoY1UWPHP/YHa1YuQFqH3X3zPZbvmH09tsXu0ju1+DU+y37/cSfAvC+lPIagM8BoHrNrwD4heT7zwH49WRk1BUAlwB8tPCocZrxlT0/kwAZpV8u4OZaAmohDguFXM3V80ReVxjaKMT2wVSEeNUqZPBU7wqb3UF0rtWlKe0dDAtB+50SWmuNDD7s1VLKmT/pNnRcXBO7TaUWa8XtVcOM23by5G2Ut7Oc8+5GDT/2uAkTUU/ivJJZ0fMyG9pWEN1DIYItpVBteKIy2c14apMzrXR0U/L/M09eV+1XWcFE0FKfRQ38ZVkOfc6uXhZjB1p45+Ki6g2cU1CRh33fePtg5nf7nYFH8q03TrNjxNoxccEpnN2Qh0mTN/u3X/9xreAp2W6IJ3HgaLbsf3VpSkEUpRjdA+Z77IInv+UDB7rDZwfehUgJDGJvpK8HLfv9xM8D+KfJ9/NSymUASP6nPpOLAG6w99xMfmeIEOKLNB022jWzv9JTIQspgTxaF/EdCQLIS5SGu2UdCh07sepkNrjgCBEK/Vq+8e1eAsMks2CZV8INDqdzkXdAIX1ey82zR9yjlOJOoBV1VFS+fj5wjs+yRfY9tNfrqhH/jvk8/JaPy5cPYudJleCxh7HyHhKiEiFMSAJ5FDFZiTMQypHjd+B1PFSXA52QDScjyEBm7q/NCgHcFaFvXDmc+R1BBXbIX7kdaI4zVQPyNWE7Dnt3GikrIRa5uQKXuCChUSh7QH4hljqGp1+TgVOERHchzBayMOGwWrhb1gp+5eaUieMLqcaQLU3l5k7kwMs8N9sBiRpqnBaPXO9XtzgFX3zAecpCiDKAPwvgN4e91PG7zEqRUn6ZpsP64w0EO77GF8trilPp8t64XL58EMF43wkBuMRv+bh2ZQ4DRzhf2vQz7I3STBeHZlT4mZvwKOIrOUSXzCYVilG7hJ949h39d1dRSrDjO/uCNGZbePO9I6hMdY1CDXsjcK+Rl8sCwOa5MDMr0KY4kXhdD93lBnxrY9i82KgROZUQTYIhzLaouYwoR4ZivHH1AGQg0TvWx9bTYaZHAyWc8qAGFxbppOclxo97saX1AL2DocbiKXnL1wQ5Dvy6ex1WVDMie8A1P7GoiMKODmUkMl51dVnNGtQQg6syUKq/E8vEBaHY3eG4GHUBVMTS9hA2stdNxya2ElWUkgNSuR2gMtl1TpkfpchoVPnTUNH3MwBelVLSKIkVIcQCACT/01O8CYCnhQ8DuFV4ZCkg/bQHwWAqGmlUD2DixEXjjwCmPKSAXx/odqFeLcRgKsok5/rbFc0c4BKMDQxWR5HYG0SXzLJm5uRJir7AO1973Hj93OJmrvJqrTUgKhF6m1Wt6MRAFDIB9naLO8PxczSuo6/6Q8tKjHBiuBGUZZmJSIZFGLwfhfCkoRg/c+7NBO/M9n8AgOiKwtLzoAZvO8gYJM0RZ59Lxo97vuFklGEZ2MwdEllWFY31awHiXv4asZsE6ff3vQzccfyp/O3DHTlSdrZX3V0IIcvZiAJI70FtumP83bXubXF55QRNAcDc6bUUX2YvpWMTW8muKO0dDNHbqmKzV9PccREJozf0vcqfFkrcf4IUugCArwL4QvL9FwD8Fvv954UQFSHECQCnAHyv8MhCGr609FX21ut4Q5WzsXlGSeQlCz7eKuO9b58AhETcCQrDPrtDWrhXwt5jyUKyHprtbY8advq7vk4QcXGVuRrHp6m/ez6eePyWkVAjr2/y4I7Oeud14uNeqQtv5J6esDzM2nTHCUUMKyaxh4vyxjmla6bx+Nr5p9V55NxPrvDpWrnHHzUiHJ7c0j97tVDTDKMkkiDF0bgcGJBZabqLHju36nKA77z1WL4HuxegfSyEb0MgjFnEr5V7pV7HQ7CZvq45t6cnfLiEww2k7KYWdlLlKCTGDrRQuxHg+SevIhjvq2clVN+OqB6jtOkX8rD1uSURku6umHjcPDLjjaZu357Uf6NtQrkC20Amp6qlcjvAtStzuteK9CVuXxk+eHh0+YDDF0KIOoAXAfwL9utfBfCiEOJi8rdfBQAp5VsAfgPABQC/A+BLUspCF0mEwunhxLU4l1pDkoc3czFoZ4TnllWj8upUVzVviYTuZEUj0ym82g+GHI1HTgWfy0vueWhcDXD6w9dQ2vQLG8/nVV75LR/RWKRHJJGQAt663cwULtjCvdKiDnYAcPwJs3dBZ6OGsOm+bhLe+Y6Sqny4qC3kPWk63pBmPBzHXvxxFQEZHr8UxlTkSk0Z89JGkG785CNaJ0OU1tNugf3tCgTzXgmr556lUdxUTwYQWOsmr58G90rjWmywDagR0NziprM4iitT8io3l5vYPa0qRyEF9u400DkS4tW3jyPqBCrykmnfDgN6KBCCDmznMS8ykwMv/Vty/yhXYE9d8esD47i9g2HG6O1neMIo8oGe0SelbEspZ6SU2+x361LKn5JSnkr+32B/+xUp5WNSytNSyt8eenzHzbbnzOVfgfleF8sinEx6wDpCRu8H42mz86fUou7Oqt4Qdjkox22p8bgtohxpD4LjfVFVojm3BxEKo7GRrMRoHQ/xzmtHMZiKcltOfuLpi87KK3/PNzBdW3m5MEouo/R1tvHba7ezHkuw7cNPPLxhbTs7B2WmM10eHBTXYviNQW73OzoOvwdb//MR7XXxniYktaV0nFFePmIwo7oFEvbPnQPXUASDq8wMhMsjBPJ7BfOEGa1lmqr+4598Q32+xdqh45Bx0efEEmR6SkkkjPaZJHnOgDHzL4Higtb+FJVXC+ExPrqrbwk5V0aTqh9iFznFvvBH+nrQ8tBU9NkSjaW4cuHDsbph8a5clNyhCKS/XcGZU0vG69vHkiYrdeVVlO8EiGox2sfCDNG9sxjqjl0bHwp1Ux/uwfDwWnqsUGIyws7qGGQgNZe4PNHTIeGwBfjtN08ByE6HjsYiQxHb1Ww6455DqRrmFQNZo8khEL+l+geHExEqG9lGRi6JxiMDR5xb3MTeY6FTgdVuKk8202oy2diuDne7n93TXtf2ynimP7XdgKeQseAYZMrvR226k3EEONRje4QUtdm9gun6uNdKa5nu58vLR1VRjKWU5exwyqN/Rym9YGxgzFsEFCxR+l56ntxg+ueUH1ba9FWFY9cbaVBtMDbQay7uBMaaqV3MwlpkyIf2t8ihF+5XPtDFIw9SbM9Bhl4K9OdU8uRVCIm+MFt6JhvvnYsZdh4AZan9XcWRFjNqkbtCfurYJUqxVujzT5mZavJkSs0eaqXsBiDpb1f2lU32up5unkOltEAaEgqZnyEvwrYJlw+2fNWcvSAy4YkcQHmoVAxCfF26xsnXhydDp38QYHVpCnOLm85BovQM+N5ovh3kFp3MLW6it1k1Orl1C/BSr+MZkQ0lJ4U0e6XYxo5e39mo5bbndNHL8gYvjFJS3LoyoZRWJFBbCjB5cAeiHOd3T2QUs3Aiwqefu4Bwt4yTJ28bgwzEdA97p1I6HBm6xtVAOxCHn1fJxmHr9YnH1evCvZKx5rgz5JqnOLJXnNMi9W7kAw1fPChx4coa7xt4hkdDSikPK7UpSDISxvubc3sZjDYaj1B7bmMknJor/FvXZwxFFuwobHiwU8HyjWkj3LQXNW/en5eRt9/rdTx0jrDOW4nhGsWou8LUw/OKpxxOKl5oXIu1R0f4Ot0718QQm9wfV2M8e/o6tp41X0sQBcd/adRRs5o9rzxu786T5kw5HgVQYtSeiEGfSck2Uh7NS14a2ntpclKKFLIo3wkwmIoQjPeNNWP0IA4FSuuBybV9Ldu6MA+GycOb9fnXBxqiicbVeK2t283cgQxeLUTcDYwE7jdeOwtAUUl5LxVa73ayjxfFkDNgi+0sUV5DSPM55zlDf1Lyp4V98ScunF9JSokvCj4K3hBP0bP4+x+fWXNitFu3m3j29HX9M8eFaUO7MEVu6QczoYEN685t5Uh5oolCqS4HRnhszLmzhGPDtldBhmuUnhl0XhxrpUQT9wYJa20dSbFIewPSfSDskivR1989miH6E2PF1e/30vsL+LnnzYkWedxeUYkM40YemV20Yp6r+p+UHymP7bMRGm8Vs3bIEw53y3rN2Ni9DBSFL+4Gmq3DDScXYi/kdTUk4fePFCdvQGWP7eJCcAFP4JbXglxe/bDcA5AtYLKjUS5SuJ8zJXlduPIPuwGRLR9o9sUPWzxLEeXxEV0hJFq+DjntxJyWONut6tW3jztHTAFKobiqBHtzIcprAWSguKilZg+i52lP0e6BYIvs+8oTTRSKCz/LY5u4PCKbXJ8HXVCfiMrtQH9/bNJRxecIDbkBsDcgYasEFdhK1IgKCrBA4pf/9ttP5b4GSCMJPSKMHb606edOXwEcTYMSpSB9ic5CMU7pwpxdHu/jjy0jGBtkWBc2HES8c86Ld7FLXFABr1aM6jHgydx1R0qU9k1/1iyP5wreXl/j7wU48B1zv9l0yrtpp0mVs08dS7nXIoghSjH6B9I8jS2jTpwfVaQUCKU30teDlodCKceWIlq9cECNpU8gClGOMHNoWydBuJWVZbnv0U4iiFWj+cRLdWXo9ZRsaYb8/Vk1lVn2fAx2KihvedpTdPVAsM8XcJeK5tX3Vya7GT4vyWtvHVfvdfSappacftvTfQwGEzGqzyuD9/q7RzPvGaUPsT1bDwCWb0+qz2rk9ygQOeWxwdhA88uLppkDyAwAtcdTDdu4ecNSOWw2+91skYmrAs4ujBGRwPs35p3NrEapBpW+hAiFkZQs6vmgC6ViodedPZmDaH+0bzS9kKh+qwquoPvCI63O8x33rMNE6FhFPWPofMjB4dfz5ntH9Ag0GXra4FOehrxmgv7uNx0OuH/whRDiiBDi94QQbwsh3hJC/OK9nNdDoZRJFn/XU+yH8QhRI0L3hFp4su9j/daEXrB5SR4AGY/MWQ3nS9UuMQm3MyPjmUiRbT4u45QA35sPMxEhV1wiFPp8Z76fZN4dHpBrMzcuq6kPxOelRazPw5cQA+FMHrWOqpPi2GFci9MWoiLtBuaSUrOXYWx4tTBt9cnus58YHZuSZZxrjlcV78MDGlZINGzjDpKyZ5uOx2XtY6FOOLqaQRGmTI4AJUnVxBfWC6PlozrdyXjZRp8Rabb4lIHUScnx94LCboW8UIqcBjvysjHiuBYrGK+fdnQDUmMXjin64ZlTS/qzOX3TPhZQ3Ae9u6Cw/8F0iGDbR7hXMhySO2tNfX90sjkxNgQZ1RfclMJ7lfuMKYcA/ksp5ZMAPg7gS0m3zLuSh0op3/qZyMhky9AzvMzZcbVACrE4FoLnvY6ssk+eQw6MQeFfZapreDAUQtLmtZ/bzpOhriaTgcTs99TGW/9I6IZgcoS3r/S6nk5iNS6zjVxyKyIeyrsSiJXkd7wbGFcgg51KhrFheLLsPpOCyOPkFglnDpDR4dfHhUM7rmdbn2mrHiqOBOHMoW2tjIhdcPjYGg4dXU/hBcu60rnRsw/GBhpTJtx4/LtuZkfUiIC3xjNe9l7XxK+JiWBXjcafyG/5aUtvs6pZSPw4f+lj3868tvFHaR6l1Ozp6MKvDxBXY0StkpGU839/InMMWk+aqZIcw+aaBzu+dkB0gy0aX7ar+qDMHFTXSZh5uFvWe+fcmWuFU1HuVe6XUpZSLkspX02+3wXwNhxN2EaVh0YpV1YDYJC9AdwrJo/R7lHh6voWbPsI2tnjLRzZAGIBr+vphcKTbUTLE+UYpUoS9ncCdDdqQ9kRJPXrgVFNtvbREKIS4dyZa7nVU67Jz9yr4N51+Pz+lJ8d9gPuTmpDR9gPERelDchvqUpCz291aQq16Q6aPz68n7C9BgBVwRc2I8iyxJ99/rzxt/VbpnIRUq2nW9dnUnjBsQG9rpeOjvJiNam752nceOuZEH/+I2kXAZ4M7S5kewS31hr6d5zJQccjB8FZKFSQ2PPC9DgE2f2j734i87qtZ0INXwx2Kjq6CK6mxoWzhUJWFEnHpfVE0YKXnPPeY6GxjilKtTvoiVKsnx/x5DlESHvntTeOp+/pi5EKnUaVffKUZ6mjZfL1xbzjCiGOA/gQgO/e7bk9NEq5NxeqBJojgUKLmGhMXMRAJfHsZkThROQsLKA+uU8/dzVTVHD2iZuIxtSiln1PKy7ymAY2HzQneeXiYcqej/PvHHO+HjALGkiJ5XFCXQrVECG1Qvfrgwxm7jIAJHnhapHYuP3Jk7dN/NZaZTYswHMCg6tj+hmR2AUzJK71QPLVV8/p7118adK/xNjgHiZdT2U10M/gxIkVpcR6fqag5H/9Z6ny48nQ8h1VNDF/eBPBeN8oHAFMxUveJh2b9+2g7+OCxBrPZ9iQnT2KjMMsZEQ4Ja88x/ZF8pHliR7CZoQzp5YybU15VOaaYG5TTF2Mjd5mVe9hwqI1a8mXkGWJjXW30b9b2QdPeY06WiZfX3YdTwgxBuCfA/jrUsod12tGkYdDKZNhjoXTW4s7AY6dWDV6O5Cipgc3M2Eqk6IqLUAluuyiAuqNQIs6U3tvY9mxwNRC/r2fednRkCZR5Ha4St6LiASkp7BHHk3n9VN2iddJw8aoXTIwc7/t6Y0zdqCVSc5RscB+xFYCly8fdHrnJByyyBjTZpSZ1nF16YDzOHavjzyx+dJcSKFwxkTYjFC+Y07euHJlPrf3SHc+VdJ8gCxBcSs3p9Tk9DNbEHFqlHhxCcfDRTlGZy11UdvrdVRWAuM1f/GjfwwRm8VTeYnOVjv/WZRsLzY2cyitE6rSsr9dgVcL8c7FxZESwoDZc6aodwn1hQl3yxDlGMc/ZbKKSCfE3WBoJ8hRRUogjL2RvkYRIUQJSiH/Eynlvxj2+iJ5OJSyVN6A7dHxh2q3ErQz9XZPYF2lxUKxorHrXAiT5FnzPCx4c7mZWwG3/bhpGHpzoWp4HgPHP3zTPF9KviTGZOXWpBFNx53A8GKLJlGQQraz8YCZ+Nu700DUKuXSkPYr1VtBYRNyV+FKuFvOZPDXb02YzIS+V8hhrc+08Vc/8Xu5f6esP3nWtoFzhcWkUPk9bC+nnhpXDnE11udLA2RdnPGd1TFITykXEQO9pawBLE+oRFym6c+82aDnH3/vRyC9tHhK9IWKNC1fxOt4RiRiQ0kZ4+mAcHTikzk6RXP/9KF4MrjlmTAGc0542bbse7mFJo2rwcgj3UaR+8i+EAD+AYC3pZT/n3s9r4dCKYuBQHu9rj06SvTYzWJs9oEhOVDC3ImU89w9FAJCDh0vQ1lpXhrKsWAbI8ujPOV1l5Me8P61+dxzPnR0HY1L2cw792LtJJyL+kfZeB6+knHhkQTRkIYJGQKvGuLQ0XU1iokp4d5CaEAuBJOQYrNZLPN/oM7FmcFnmyHY9o0EsH3/2+t1/L0/+LT+mXodE1WQmATkWdsGfX01nUpiF8hwRkMwkxqVcLdsdh9MzpcG1hJnfOHIRiYqAtQacK0bW0mWmj2taL2+6WDUbgTagZBlicrtACXLGNBn6NexHe+iMOZVHAImQ4i8ZVctCvGf9fr3JMJmhOZEGhk0LpeM1/w/f/yfG8dyJXLzKKd3I/e598WPAvjPAHyaDZj+2bs9t4dCKdsMgqd+/j39Pe9hsLo05ZyKUZ7o5dbE2x40pFB0OLYf8qAOl8UOxvuFZdh5TA7bEMjQ0+c8tbBjeGS3rs8YzItRKvUIQnBxlvkk7fCAOo/q1ZJOHIlQaAPBCwpsIUMQdwPcuj6jRjElSri06aM22zY2U2cxBDw1ZoiHr9Q/ePNJgcpk1wjByQM1KhjtopSdrLfElQlNKZ95KsvvFkGciSA4xplXoVaZ6kJaG5Rz2Un4wFpA5TBGbf3KcfjKZDeF6IQyiPVTKazTPRSicyQ0qIYfe/Et9A+EuviKe9Y2JdHreIg6Acp3Al1KDwA/9/xrGZhGlOPcXAPdktqNQEWlnszmPJJ13v1emiuwFex//fv/EQJ2/bwTXdGIqnsRKcVIX8OPI/9QSimklM/SkGkp5b+92/N6KJQyF+FLfO/CSf0z9TCgDL1rKkZ/uwJ4UvOARxHtMSS9lIHcClQAqeWOttz4HHmRpOztMDHcKxmeCTcE25v1wu5YvFLP1eKycYVlvHMa3pAQraxzRDV5F+VYYZXJxnElEYPxvh7qCsDZ+nEwpcZ3ZVgR1L/al/oeXbsyh5lD2+jPqgkTOgTveWl4upt42beC7Cy3HLjIvudkkHmjKxl66J9UhmeU4bRkZKfH2vrcbKW1n/YIn37uQv5nsQXY26oi7gSqQGktQPl6BbvLWT49wXPliZ4ekkqJUlHQPS6uxUAs0D8QYveJ9Pr/zavPmQnIIIbse9i708jCT4khH38vUAaiJDPOUWU10LzwzpFQ7+PyRC/zHAlmET0Pgwn1MKcWdkZqwH838oFuSCSEmBRC/DMhxDtJ1cqPCCGmhRAvCSEuJv9Psdf/shDikhDiXSHEZ4Yd32chYx4ty67as1twIhZY/0i4/0QAW0SuzUULh5SNK7zz6wPIvg+/5WsF4qrOjFolvcnLy6m3HXfNySe5lXFC6v4RlBwRcTrs0yVFZat+Y6CxbB6RkNDvwt0y9h4PdWWh3fqRxOt4uQnJ6nJgQC6cokZKkbMa9PfWM6msBk46HOC+54Cq2OOYNMEX9nBaF+YtKzH8+sBghHBsOU9oqC8X0fN0UyAg+5x7W9WMoiqtB8p4HQxRXrOSw6UYsiRRne5o2IPeX9r0C4t5RpH69cDghmd6fSd7Z/eJMNOQS79nLsTYh9K1NdipoHI7UB0SmbHlBT2yEuu/8YG3ghn2exUpP/gNif6/AH5HSnkGwHNQ5OhfAvB1KeUpAF9PfkZSyfJ5AE8B+CyAXxNCFFZMRDkhI+BogpIoNRe0IHyZmwjg4bCzDaPVkIWSgrYSJu+KV2aVqu5GO3z8j+gLNK6mDYjsrmAyEhp7pM2UMTDJAvnSJ76hkyOlqXxvSJTjXLxYBtLYtHZXNa/jGb8TlSgzKaR8J0Bp00/75tZiZ6l0sOMbkYCtjPJaTwJA/4SpKHtzaXh+4sRKpoSddyfjHrKrvab93t5mVa83DsNkKF0MbrOHHRDUxEc4lZo9ZQCTZz95cEdVrib3nxfLzD6uFBhdY8jyKpziWVoPNNTCWUSkzFx8eA79uaING2JzUTvzhCvYsBnp/RHsqGpczrF29WN20VcB5Xzxga+jjlcbLgJR7I309aBl6CcKIZoAPgWVXYSUsi+l3ALwOQBfSV72FQC/kHz/OQC/LqXsSSmvALgE4KOjntDs4pbG1mrTnWwTlEqcG766vOzqrQDj7wZqikRJNXAZTGWnLdsNWajSTZYl/MZALzLyrjhWTZuC47leLUT0WLoJZFmidTx0Jn1IwskIXsfT/Ok8A/P33vgkAKV067V8pUzXlNdzukhsyODAbJosFD0PpU2VfBtMRcZGsUuY6zNtlLbNe82NAaeQ2eJ1vKzCFhLrOyq8vnJlXtMU9cZl3cmop4WrPFtEwlmurwendkfzkKj1KEl42PK2herNUqkm46eaPWzdbhpGgucPqGqTPHNy1GxKmYuWRknXvP3Bob+4FkP0PCMHQok8V0UlL8axcxz169kZlys3p1C+E6TNl+rZZzCKvHNx8Yc2geR+Ycr3W0YxAycB3AHwD4UQPxBC/H0hRAPAvJRyGVBlhgCIs7YI4AZ7/004Sg6FEF+kCploV2F084c3sbY0qUOxzkbNnKqR4FHVO6Nbr+6hUPcAloM0uXbizHJuUk6fY5wo11YJK7cmnT0TmnN7asBraPagiDsmfYe8smFJn7gWo7tRMzwLm1mhsc2JjpHEc0ltKRg6n88pFsDej9Q5HDq6riZa13P6AlseT3u9rrBEFp1wj2z7bGiyKZLP9due3owGb1kKvT44+8GYl+dIqpKXSH+TpbgQ6sprXA/ASIzZkjEiyaburCpDMtipjNQmk0vtZuCEzWxFGFdj+C0fciwy8gx59DVZieFNZ406NxL0PKgYp7Sh4BSeEG4fDZ0OUdE9NK5jREhiFBreqPJB76ccAHgewP9PSvkhAC0kUEWOuK4is6KklF+mCpmgojC6DFMCJnxA3eTaR0Nj0d2NXL580DnqBwA+9cy76rM9xTgQ5QiIBXrzYSbJs7M6hrgWay8lj8/MvTLyZAgicSUYuWdB3oYdbnOKnKvUHHBXWNmZdN3InhcfWIux97Ly3G5dn8n0gSapTHZzS9F5OF1610zcGPBA8rn8+tdvTTirEP1e6pmTgjp2YtXZyIe8RP23WKD5rdRz5L24beql3ae7M5dWmpFw79TlqU4e3tZdD4PEa7YTk/b7KImXO8ghEhkDFDUifO7cD3SeQQRxYbEHj1rIcB38Fos+HIyTg9/y0duqDh1me/hr2ftgFwYBWXpnnoxatDKSSIUrj/L1oGUUpXwTwE0pJdVy/zMoJb0ihFgAgOT/Vfb6I+z9hwHk18MyqS4HzoIHQCW2+ObtPjUaTWbiLYbrWpsgb8TUt944rbt3SakWTTDeR2UlcPYkqE13EI1FWDiyMdJkYPLqNETiWNukKPmmK+qOZydCedEMv05RijNVe5R9p4oxV0TAFUP5ua3M372qYlL0tyu5k7tJqPufLnNnfO0875UbF6+qvOvuQpg2FzqikpDXrszh8LE1I8TOW1MceuC9uCdr5tq6sWE6CxTtcO+QnunEW4otYivYzeWmbnqvp5tYu88O0/OaTZU2UriAjAy/3n/1yvPpMfKmwVsc+WdPX9eGa+1c9ny4M7L5OfU9d5hsKmZpI8DNz6TvJ/jP7kEyiuTt03uVDyz7Qkp5G8ANIcTp5Fc/BeACgK8C+ELyuy8A+K3k+68C+LwQoiKEOAHgFIDvoUBkWaK2FKC7EOqEkIiEDvPmFjczyYFRRjaVJ3rYfopVC7GrFeVYJ0pcno1OciRwR7hb1gqAElWNywH8PV9Tds7NplV6XLHZ4erkG8HQ5kZ7JyNMLew4vT5bcfm7fgarDvbc3Fubh2sUQEB50XlJF5Ld2yn7oDzRg1cNjbB92GBNwrq7GzVl/GIBCInmhfyKLe7dx91At08luXH1gI44bl6bNWiEw4Zxeh1P5RiSA9zanjCStL3NKo4cv1N4DBJab3k4qO1d+mxIAxdXj2+SwXQWLqgkBAcK8adfHRJJsvtX2gjw+rtH9WdSZMaj0fK/S5Wpa+J6OJH2s3bBM64omEvRfsjjjt+LyA9yoi+R/yOAfyKEeB3AOQD/LwC/CuBFIcRFAC8mP0NK+RaA34BS3L8D4EtSyqHuI3lCuqF7NdKbl5Ifo8rYxQB+Y6Dq9XM4qHx8PG2gUcbRiFKsQ77WyRCCXdlv/+BZnfEPx/m4Is8I27aeCdXoJ2kuRv59aaZr0IG42IorGo+MLD3gzr4D2eG0dtUkedGFJeklqTdgf7tSyJ4IdvwUJ65nqX5k/IQH7J7LbkwRCtSvBThzIO0cJ0oxpmfMTnmN2ZYRcRw6uq5mJa4WP1PRF4hrMeo3fZw9tYSZV9Sw0LmPLuMnnn1Hv+7G1QNG1OI3Bhg70CquMnUI9y79toeoEZll0MmaDPwRvEPm7VLehEL8jecT6qQV9VSXA0PZzi1u6jVg9xXnVEsaGKzPkyler+OpAbQ067Dv6WPypl9FRVB5vVIalwP4u+lzHNZTez/yQYYvIKU8n+C/z0opf0FKuSmlXJdS/pSU8lTy/wZ7/a9IKR+TUp6WUv72KJ8x+aa66csX1IDG08dz5u0lYisXLnunQq04XQqDKFOyEhs46iiJCTnwDAyYknvk7URjEeBJAxNtXAmcYVtttm0sRv69vKyU49knzB4ZebzjiuVpvHD2CoDsIiZGAnn7k68HzpaQBK24oggZCaM5jqtRD23AsBkBUmDhm35m7BdJaT3QdKfDx9ZMzmog0T4W4uULJ9T1VCLIgadbPgKKE9yyiopuXZ9B2IwKB5KeOLGiK91aJ0NceO8wtn9cKZEbVw/gm6+fUZ+ZMHV41BK1Sti708Dq0hRePPdW7me4hNafi5FAWP2wMJ/yHC6jw6lvOupJFHh3ITSU7Z1kakzm+Mk157Vd5WyluBbrYhRb+kl/D78+0NEL0Q6FLzN5kmBsYMBNrZMhovEI4ozy4nPhmLuQDzL74oHI1tMp15e6UXHhyqF+PYA4mF8OPEw4n5iUy+QbiSVOFom/6+tyYC4iUIvPzhhHPFlhLc7GJ92hr6s6kYQ8HupcBygvqn0sdBY5UEj5xR/5fQDQSkyGHuBJ+PWB0cKSjNbWs6FTOZBitHFNlwJ24ex6A3Y9nDixgpXP9pxju0qbvpHAufXOXCF8MjNrhvV+y1ec4CGbx68PDKpXadN3Tmh2wUVFs+i8aoh/90ZaEEJGMw/HBrJ8dlGOtBeeC1sIiWMnVrUSln0foqKMDlEeSdk711WyJjMJ8pzOcnTNBPm5eqvkCe+H0ryUFF8xuPHjjymHQSa0RB6hhnsldBdU5d9nzr2p16Hd0fFeRXnBj5RyoXC6S9xJR7UTm4FjdO2jIRZmt5zHKZpoXCRbzyTJriSZFo1H+ND0zczrZOglo3/Sz2m+E2Q8ctpkY5eCfcMvQLa1Z2O2pb0o/7VsRdniS+pRfvmPf9z4fWVVYbZRu6RbWNavBbkl5cdOrOoxV8F4P+MpF02C4OE+iSzHSvltmpALTfa2YZZhnFTuIQPuicm2VKc7iNol9Nlb6XO5sqFoRxefWE1xSGFWprra8/RKsYHvUrHOMBybi+yrUUmiHOWPJpMC167MGZ4/rVVKwkaNSJ/jzKFto/BKz8tLdH4wNkD5TgApRmsLa7dnzeNCA4CcYJTHD/cBTxo5gVduHjFe74pQBzsVfO380xkDLRyDMO5WPsiUuAciNt2FlNzYWTdmd/sHB1FdDjLl1qNsUu4tkMfbfDsw56dBZbHzYBK+KO2y49JGAC/BBFvHLK9oyEw68gxsPnP/YlNvuPZRNRdQlGIdXi69GOvrIAm2fTWBe6JnXEf7WJhxLOl6rl2ZQ/S9SXUOu2VUNrPnm9ckn8J9LuRpcdogAD3Ze79SOArMITOHtrWXZePngKlsBntlBT1R8YlVzk0Ks7dZNRLARVKkvMhwE45MpfrAcO6u0caVrSk6x/VbE0arze6i+iwyzOFeSStDXqB18uRt1GfaBv770bOXjc+ePLiTMZ50vrVkqDAZONlXtQF7dxr6+VN/laJowhbd5S6HkXI38oHGlB+UcEI6Lea8ZNdgKkJ3IQtzjCL959IFTR7vzpOhM0PMJx2TlJq9XI/Oq4YYTIcaH7YXUXm9WKmQZ2AbiMGU6UVJkWSlI6F5tM25Pew8GWocOZyI4FXVubiug0cV/Hqog1cw3teJOOrl4NVCJ/fZOG7bQzDezyROZU6r0jxxhcykKO1CAlevCWB/FCzR9Zy4KIm/5ztZGLw61O6yV+T5x5GAGAgdAS0c2UDUiBBs+0YkduTfMqZEct17dxqayZE3MDbcK6VDGBzXRaXcnHJ2+fJBtNfrBnuFNwgDgD7r9kZC50tMpMFOJbOf42pscLt70zkMFVc70IPZ7pD3IhICceyN9PWg5aFSylxs6hDnvtq9E+zNL0KhmQyEv/ICABe2CWQ9gvJEz1lyOtip5I5WJw+/tqTKu21x4aWujPIwChGgPHJZkppjS83IS7dT782GVXQ3u0gYUYWrECDcLeuogno5iNX8KRbkCcWB6kFih6VF2CyQUNOSTTt/eNM9iTwRO7K6+lZ2Ks0oUpvupH1Ocs6PSsGjsQg3rmanoMiy1MySoaO6Evno2cuIO4FhtHXTo8Wu0U3uxs+mr6klNsHf9Qt7H5O4nBryrHUp9wiUM0rEAypSqy5nBxrYVDh+L8g4TX0/jY7yircOHk17oNOzvN+YMqAq2kb5etDyUClleoiiHGc8O9UlK9kcVvcrniH22x5kILWnSgmwS+8vFIZLwY6f9Qi2K0bJKVeersbsRtlvAPSmVYb/z33k5fRFDm9x4ZDyim1uqSuhxw3SYDo7mBMwW30a57eeFh3QhiYl7drgUws7mQ505Km6etxSb2VSboT/2Tig6HkGBPLs6evq/bUUnx3FKOnjJbQ2QCn2+hvFipEn0zobNWOiNwl/ljRNpEiidkl79nl4PRVYiIHIrLVgy9fPO9wr4fd+oJKHtGbpORNUltcpj4ur9ziQ71nbQuvdrw90Ip5yPN1koIEI4rR0ve9WJ3zfEVWPju/iNN++OqMNh6vB1X2RR4m+0YRG1POHS2Hp2IFWrrIh73Py9QBRPdvEnMROvnDczuWViSDWmLVXC4fScQizbFwJ0JsP0T8Q4sqVefzm918AAIy/G6A+pZQZx0apG9vG86Ex16+/WsNnzr2pfw52fJSTEmXa+LRoh2GQwpcYzISQOyUjrCyaZZgHHQEwetzy4gduIGVJItjyMxBO9Y5nQCCvv3sUlduBLkMeVUjZy7LEge/4+th7j4d6U7sw6O2VcXhdD42r+Z/nwp+HCa2hvH3sH1ewmd3XRPQ8BCf30F9LGltt+RqLpzV7N8qpvV5X0UfSQApQCeNhhUvUsnV8Win1qF3Se3MwFRk0zfHpNsK9UgY75zkMvu/4sFsZeqiOZc9F+hLBdLpGi3qN3JM8pK7yQ6OURc8zRtQLX+KFs1d02HxoIlszb7y/FOskBi0Ce/FR6TQJ4WB5pHYZeri6rkI8vilsvNeWvP7Ge0/10bmt2Au2p0OKcv2FdEy7LEl87fzT2gMLmxE6h0PF1bU2flH/gHNnrmkPVJbMyRCiqLN/jkzM7+L/9Mmv6Z/1qPlamCkddjVg6p/Oetm9g6EuQ+ZSuR1ouiIXr+sZyv7OxxXzgDBwGUg1XSPHo4yrsTH9ojm3pxUPyX4SUbroyRKjt/BmVXn18+m6PPn8DciKakJF0Uo4GWX5u6yKk0dsftuMOniTLREn0Ucl1myT1loD8mpdX5v2plkEd+v6DEQk9H584ewVY29ymma5lNzvcSuiYpFufaatlfZ7lw4ZuQwy7hwODLZ9hHdSo8+b8BdOotinPPKUhwjHl+ozbchIaK4tkMxXsx4IYcDVW4ETF+PFGMGOb/SH9fdSfiT3wHlYXp3uoLedDYVXbk7l1uPPLm7lNgeSoalIRF/oTdvbquqwmnuRohwjmk4hi8ZsC7LnF5bh2l7L+XeOGT/z84vapUwbU1vspNr2yjj+h/OfzryOG668Aaqi5xnw0zCKU38+1HRF47Oq2ftv08l0P4r5XQRjA+Oc7Eq8ndUxdN+aNH7XXQjhVUP1TGm2YU5nwbXvHHT+PmxGpnNQizXOL6Q1kZuGie74Rp8TUY4MlgeP2IKdNOqYei1tFDW1sGPO46unTA9KkgOM02wlAqUv9bXyfZi57oSiKEqxEa35LV+/v71eNxKeLobU3qm02Vc4EUFWVBc/I6qrREP56KOKBBDHYqSvBy0PjVLm0l6vO8PxE8fNYg7C5VyYIGAqJxueKB/dQ/9AmAmZeVje3aihdNvRe2Lbz02OrC1N5iYSgZTxMDG/C1mWxnl135jKJP1k3zM2IfGEt1fGM5EAQRF8A7joa3R+xCTgCS4+ZBVQRmowE2YwZFeRBZezz17T33sdT+OOjevmfRtGcbofe3B7ZRzhXslQ5Jw7Tok+npgkTDnuBuqZTkWKW91JYJG2ms5MHm13IdTNr2hwK0l/u6ING+c0Z64tVjML7bVKURD3MMmzpD4jlZUA3Z9MDfXWDcU6oTVB9EM7ueZK8PqNAYKxtCm/qyMjN6aV1QAnD90xorWoERmfVdQml86hUekbjle4W8ZjcywCuZ9eq0yON8rXA5aHRinzxSHKkTMcpwoslxfm6i7GlZMNOZDy7RwJMwaAO+S0UWlR1a8HRt/kvBDXLrwgr5y8hO2VcYhypPjGyef15kzcmnuwtmcXjA0y/QJcPW3Ji/J3/YxidTEJ7P7MnY0aRCjQ2agZ5c/DJoK/+V5aIBDXYoR7Cst2JUiHdZW7F8mDmsYOtDTe7DLqzhLovq/hmKgeI2qXIHu+rqijZkQ0uJULZ4uIMFsRCigsuYi9wT3MvVOhkfTtzYeGQ0HJPL4m9JQUBlVIX2JqYcfYU1GrZBhdG447fGzNMKa9udDosldZDTJwTmXDcw71pXPw254ylJYSvPDeYe1B5yUS71Ye8ZSHCM/+2wqZEm46uWWHrkJRsFxhOCnGomw+fR55Ry7j6M8kg1uPmg3bKQy08chwt6yNQmWy66xakn3faYz1hmU4nV0VOMxT5XLuzDVE49HQAZSUgCKFS/fub734TwGYdD76fB0WMwzU1S+hshqgv5okKZPrIw7tsK5yRTK7uFX4d9dzD3Z89N6dyMWbvWrohEcA9/zEzuHQyFfUpjuoTHWdJekAUD+453Q6igYgzBzaziRlS5eG08SCbR9T59W56ValVki+udx0Xq8IYvzVT/xe5vf2WDCevAOUkr55bVY7SrUbqgOka6ivVw3ht/zCySRFVaT3JI8SfaOJq9+EDD1cfO0IqjmVZJACXjV08kzzuJC8jJm8hMF0iCPH72Q8StEXqRJqqNJg21Pcu9ZUm8bCvf3GYGTuqj7nZMO6+ifTuebRnbjSKG36KE/0MpiybbwotKaNQSW/ZFT+z7/3ea2w7VC21uhnztU1wLQ3lz4f2VcVX0XsDpdwT4uu3y67HkXCZoTwAJssboXWRV3vXMNIF45soHMyjdQ6GzX0NqsZZULwg0vJDMtfrd+ayERCo5RyhxMRts+Ye8AexJA3okyGHv7ut39S/5w30Pe9S4dw7sy1zEWEu2UEYwM1eSZZY6SoNeWtG4xUhXv/ZbQk37/XiT6SrX9zyBkaR/UY/aQCyBWS5m0kW0EQDhtORhpv5V7CjasH4L1sJoy4so9aJdSWAsNTPXfmWsqxZQ/R63rOTczDdVIIw5JtJHSurqYzldvpMM6xiwEGUxH625UMxql5xMllDWbClGOr2y+aG5UUth3K2g3zSVwTWJoXAoggxsSFwMDdeec7nlSkto9ex0NtuqM9Lb8+cF5/XnLRlmBc9WMgj54bbrvVZVGZNJ3r8o1pA3bKa3sa1xKOt4P6JwWbAGNzdy1lNww6shOzcTVGqdnT687uN2J76H/543/oPG7RdOzz7xxzhpjV80mFX7LGdMLSNRXeVvoJzJKXOL9neeQpF8u5M9cAT2L7bKjwR0fhBCkGV0jKX1/UX4LjsHnlwsaMMiZjl1TxRWcxNBJitidKXlxeCFxfSb8/8eQtCAnUb1mQTXINeR6xC8vmMADHbgnjpHuk+wiw20TJJW+TMSMcDBP7ufCwPdjydQKINj4lpCqrAXbOKsw8+Ol14xh84jbHXrsbNTz+2DLiWmxAL2LZHXnk3W8SwjnD3TLkwHN69JVntsxj1mIEOz7q1wNjcvUTj9/KVBWSAs9LPNPnRQx1OHcmTYjqCTB9z6xSTR5U7aYyajZ0RUpYR3wzoeYJU67m8MyWsT6KjM0//M4nc/82qhB0s/c4g7xYApPWHj+PjNJPYJaixPldiwRkLEb6etAyklIWQlwVQrwhhDgvhHg5+d20EOIlIcTF5P8p9vpfFkJcEkK8K4T4zCifcf6dY/oh+G1PV+K5SpVtqUx19etFOYIMZK7nWaSwbUttKEQhsfd4OvGhaGBpUUvO5tweNp9LF+rV5VlIAQzGTEUrA4nSepDrEZcYSYLOMzPuyvqZ7hH3/P22qQDEfBeVqS7GDrRU72jrfg26gbGROM0wnIwgS9JI2pJx6B9JvR3ej8JVwKH7NcAc06Q/h2GTNlskb0ai8CVuXpvFzCvF64nzcfXnNSN052JjfNTFG/PagSXPlQ96tZNa3IvnFEzboOvXOHIQncPuAiYyDtwoEU9Y+hJiIDJtSnMno1TcUILLOxcDkeH+k7TWGk6jblMgZfPu8wn3LmLErwcr+/GUf1JKeU5K+ULy8y8B+LqU8hSAryc/QwhxFsDnATwF4LMAfk0IMVJrr2C8D6/rwV/ooLYUoNTsYfd0dlipnbnubVa1Z6Dx2Jw+BjKQerFMLewYiossNZW0kkJsXA0AKXI5taVN31kZ50r08E1fmexqbm9/NsxghOHcIFW4DPfsHUwndPPztD0/+rmIjhTVY0MBhHslRFcaGpawS3Ibr1X1hs5jnrhKtglztg1f60R2sxPWTInXvIQZoIwjGZX6TNsIzfk6IWM69R/fQJ7MfD9IS8PZNVRuB0rhCdWUfXZxC7Lna2+PPNdPPvMeAGV0uOEYO9DK9eJHha2GSSGkkTxDux+MvlZO0+v5Rok5JbCdfaZLEt252BnN1W4EziZIommep7eRwG3WMF8y1vZ1ueZH3rX8KYQvPgfgK8n3XwHwC+z3vy6l7EkprwC4BOCjww7mNwaKsVCN0d+uoLMY6rDFToxUrmbDmcPPFE8q4UIc483lplZcldvJ0FYhjSKIYGygK78MTm3iJnkdRcZ30dH4eXOvQbMOtqq5rUFFJCAjgf7745j/Az83YcnlyPE7mHwjyGz0DDeVKSvej4HExQKgjbt3MkJ1ugOv4xlGhGhhLuEYZ9QqmSO6ChIpVOpM99E1TgpIvUoyTrq/h4WLzx/ezHjeXOGvfyRUnv5AGM+zd1AxBEprigKXl1z8wzeecP4+D3cHADkEcuHSfCd7j/X4sQI2Dt1iux8MrWcyopTwi9k6504EYfw8sipveuj3WU4gUeilvSxF068PIGNVMEURDTFg7HtEey7cK8FvDLQh8c+akdE9yX1SykKIzyaowCUhxC/d62mNqpQlgN8VQrwihPhi8rt5KeUyACT/zyW/XwTA3ZGbye8MEUJ8UQjxshDi5Wi35Uwi2DXvpNjiJ7Oe083V4Q1syAN2MTx6BxNP1VIStNgz3kDyurgWo3wnwNy3/dzQD4BRbMJZB3kTVHjJ7cqPRVrR5vUt8OsD3Lh6AFvPZFkoNseZKyvy6OwiDrpXVDkok3svA4nuRi0T/vJp1yTEYqHwWm/6nKSsq9ydGxDef5mO5UruuQwkkOYiKquB5ii7mBDOgpYDXQxmQqMc+Euf+EZ6npEwoi6CNuxWnhmxvElOrbRxX7tvN6BgCvrc5twegm0f1eVA94wh790pVnMszcFOFKUdCVGnNh5Z9U92EbHnSYZ050nHuSa87rAZjTT1Xb+vVdKGpAga3Jfcp+KRBAX4OwB+BsBZAP9JghbctYyqlH9USvl88sFfEkJ8qug8Hb/LrHIp5ZeTuX8v+OPZjTG3uKkTH3oETqLY/oMnXsu8vigzTEIe8LUrc0NemRV7MfANM2jGWP1E5KSwASp7TDPzSERCmCel//Gn3lfNY3IUOyla14DJ2o3AVFh8msZ6gI23Z3Ox1jyJO2qAwPbKOIQEvHb2/bbnam9imxddxMMF3N3tZN83ogm6jnBS0RKHJfdc0psLC7usuYoc6P7yBOrf+fantZFsXPYN+IjWR2+rqmC5JDqw4RsRCm0A69cDPWAAMHFfUrzcEBC9zN/x4dcH2FkdQzihSqipZ8wrS6qIx4YHRCUq7B0tIoEgeYvGjRNLw6tO4062xQHH+V0O0DCxKXrEZrnbqUJ5cp+KRz4K4JKU8rKUsg/g16HQgruWkZSylPJW8v8qgH+ZnMiKEGIBAJL/6e7fBMDnvRwGYLLLRxBeLDFomhvvf/n+R0eaPM0lr/9x5nUH3PiljWPzDWPDA6Q4aHMPdiqZ/gEyEgZh/jtvPaZodZZiF31RqFBnDm2jP2l5PHyaxkyIsBmhsiaKJ1RDKRLeAezdy6ovgxQqicSVVWU1yEwO6S6EzpJcLjZdy1WJaQtvbjOYinSInMfS0TKkqb6NtdO5j59RkQWHNnhnN05ZIyO5d8osIKkeTUuew92yjg503qKaNk4iZ6F9NDSaJJECL0/0tML/O9/+NBqzLQTjfRw9sIFgvI9wMsqd4kL0ToIHyIgszG85Xw+odSB9qZkT7aOhmsaeeI0y9FI82pE4pyR49VZgOEBjlwKIOL2vpNxtims4GRnHJTbLfeczx2K0L2CWovrk64vsKCMhA/uRoUpZCNEQQozT9wD+DIA3AXwVwBeSl30BwG8l338VwOeFEBUhxAkApwB8725Ojjacyxuys9N2iO43BvAbA61MycMZNo7JxrZoA1bGUuWR1/KxcTWAiAQGUxH8tofSjsiltBWJ3/K1pyXLUimidUdoX4mwfktVpg0bbLl3KgSezm9iBKhMOHUAE0Ha25g8OZ68sqdEl9bVtXMeMxlCfu5B12zrGO6WMfvd/RlYCpH9PV+HtU6JlSFy9ewFssaUzn1zuQkxEAa0wQ0olftmYCH2CGxYxO4xIXdKOrKwq0EBtU5Jgfe3K7qdJh073C3j8uWDheOoajcDTe8kOuDj86rfCbWL1Z/H7pGLmWFPcCGIhzsMfF+U1oOUGpgYx/ZiDOml90aGHkQQY+XmFGrTHd07BADKswr60l5yTj7hXoRaHAz7ArBGUX3y9WV+GMeh7yk9OIqnPA/gD4UQr0Ep138jpfwdAL8K4EUhxEUALyY/Q0r5FoDfAHABwO8A+JKUstjEJfgpkdspUdNn/ES/PtBFBhTG8CIMuww5apUQtUoGfup1vNwG35TEsJUobUA++YB7M1xax0ONBUf1GJ0jIXrXsoMwh3VGixqRGbpWogwnFoDhVRdN6dCvd2XDBykWKgcpfMKpV3EnGOp1DmZCg3Xx6ecuoPVUXw1HZefeWQwzAwzWP9UbuulciisaiwqZJYDysmTf04aADH1RYhLIwZUtsddcZzHMLc2zGSmyLNGfUjfeRcOz1ylXoqSohl1753CojfvNa7MorwW49jvH9d/Js69Od4y+EkUdCG0JOmnPc74vBjNhCsXFaf7FFlpnnY2a7h0CpAMvDn1SRW53M8+xUEZN8g1fBvcFGeAyVCknWMlzyddTUspfSX6/LqX8KSnlqeT/DfaeX5FSPialPC2l/O2hZ5F4EURu171/mXcRtUvoHA3RnNvTYQy9/vCxtdyqH775aFHYjAdRihEmGWQbO3Ypg1GGd2pWQ5SdNVeey/YTdn2mpvnZkEYlHelkn58OK8uqiovDMT0HHi1L0sBC6bMy/SuSjUXenWuEFZdvvX8K3mYps5l4rwo9XLPnI7hSM6Zhk8IgqMKluADT2y2KFsgQkGdNicm7iWQABT8QXctoqMQSQ2KQT6ME3BEg51FThDK3uGnQ1EiZ07W7yqQJFuKKsD8bov1EgkPvpq1syeEgw5g7Udsh7aMpfk3OUn2mjeqtAOMTHYy/Gzj5ysOgNBI69v2XEZN8w8usvw/glBDihBCiDEUH/uq9nNlDU9FHMnNoW3/PF+LkG2oc+s7qWAbfvXltNrfqx8UK4J7a1GsBsKfKpsVAaIVHbS13VscgYjO8i8YjwyFyjUY6ck4Zy3AiynixhSE3gN3NOoQv9XnaXh0pTulLQ1mNva9mvolYefiDnQoGb7Kw01pgXCHZjX2kBxz+mofazQDlOwH+0se+reh/4wmNKvFwaqwUmku4V3JigJxOxp9Zbz7EN18/g7FLKb4KmBNAXM3uOdZbFC3UrwdOXrX3nfwioKmFnVy4K+6mpfZ5DZVkSUKWpA7xXYUW/PiNKwG2PpWupUP/SkETq0tT+N3/9L9NP9vyOHkClRyGaCu9t3yt6ud2Mkstc3mjlcnuyEliet6dtTq6h0LsrI5h93SI6tWyPhYJr3p05YfyIKf7KvfBU5ZShgD+DwC+BuBtAL+RoAV3LUL+SfSms6Ry/LA89F/+F5mQPY/NcDcifJmhStVn2im3teeNxAUeRcYuBtg7FaLU7I1cIno/P18fMxKFwzVnF7dGbujj1wcjhZB+y4f0ZEZx1K8Fupw6GO87sVC/7Wnsdv4PfKz8WKSmIDvCXl7FSSJCARlIjB1o4WBzB9e/eyR3hFie0DoR5biwVaToi6GDYCFkrqdF7z90dB3Lt6a0spxb3NSwiFcLh46B8nd9g0nC7yGgmBDbG2P3ve3lD1PyWveSXP8rf+MVVsR2V1I5dkQu/M1fHOm11770X93z5+1HHponZTRmvxHcV4UMmFAIeRPxm6mXZDTkJnjgLq313ik17ZcU8iiehkshz/9h/vsoVHd56VrKsc7gjxIuioFwYqJjB1oZhZzXOyFqRKjdzv6N97fwLru5pmI+9aRWfkw9g7xyYFe0QTjsIPRx6f2FoQqZF7FQiC0jAXgSn3vmvPsc2VxAoHhytl/wN3r/reszBn7PceqgHDnvM5+5Z1P7SCFTXmbrdhOyr3oZ15aCTMLYaLlqYdTk2fttD43LAU6cWDH+zq+dIkv1B4nSRpCfVE/WGI9y9Fs7HmTfNwuM2N/um9wnnvIPQx4apczFNavtbsVVkHD6w9cAAPJJE4/V0EmCn9bGu87iBBEK+Lu+sUiefsIs3+XVbkVE+bz5gACw8sn8933qx94AAPh+VmkRLCGjNIPPw0Xa0NxLnlvcVMkttggJj3ZVpMW1tLy2ahmG1gk1OICGzgLJhkqShcScIf45Sbhbzk1e8XLb2cUtzYWt3Qg0/k3PYBg8pK+BFT3IgZfCObHAv3rlef03Ok8h0wQgFfP4pfxnZBsy17XxsmFORwQU66K85SiOSWbuFRYrRSaVMpyI4LeBcKEH4ct0Egpvucocg8aVQENIUT2G30e2fwbz4mlggr/rQ3R8DKbD/B40yRpz9VAmI+wqMMoz0Hcr+2BfPFB5KJUyl9pSkGlK5EpskGW1lWjs8GiI9mX3Od55Q2W4iQzfXq8jrsaZyRiyHGPqzLqxSN5+9TgA4Mi/LbasPMk4tbCT8ebIE8tjI1By7PfePgPArTCHVT0NpqJMgstmEuQdm0ulbCaKDOkEeOfiolaecS02ihWqt4IMrQ5IFYPwJSYupPddV1ZeD7B+YxJbt5v41DPvonMkHdZK0068jndXE5CPTm86f0/nSfbqhbNXUL/pq+KfBLvNSxhyY+2KhvjggHd/cCyTrOTGvTLVVfcz0RR2NElRk7/nA0JmnIG9U6HyQreCDJuHR4VikFIbKZHMqwnz+nVMXAgQjUeY+36am5FlaXjMPIFM9yzPA3Z5y/dV7lOZ9f2Wh0Yp20kYenidRdV8Z+ZltkEdlWFkWe2MNiV/XNhcJoF2LAsFTFwI0DsY6gQUoBTG9q6piCgpd+Nn06cYbPkZpgZPMrqavMuShFcNtZflVUNjwxAksl+M0A6zB4P8bmqjyuZyM9eTkCx8znyGND13l8cnI4HtsyGCbV+H0ZXJLjoLEbzEa/7WG6ednx3XYuw+ERrhsYtFA5iJ5Xcumpz/vCY/L184gdbJUHl6Of2tySuO99FlLGpkk8JceptVdT9zQurORg1CqjXm76XsFVvRu6oZ+XqSJakjOEokG1DDWOisrts+qyiBK58080EykDoKEOxz6J7lecBFwwb+NMtDo5S7C6FBHyLv52c+9DoAYP2F0a3mqNiTzczgTV0al9WC2D6rXsP7wsqBN1ICL5yMCst59fl2PaOnRcwWtGthjkon4mIbpbzzz+sbYUuw7aP5TlAIufHnYDAArPcU5Q/CiUiH0b2tKmRJIh6hpB4A/Fb6+Vq5WEZy97WU/2vTAEcZucWVmXGNiVd8/d8eB5BGOJxKKJKE4v0UurdRI1JdCCtqOK/L2BrnIs3yaDuCM4tnfINZY5Sl5yyIC+8dhghiVFfMvTmMa20f/27KtvPkEXwxgsiS1IuUcMrf/sGz+s6QZ8uttIsHSpbXNSsuT2YObRtNzFsnQ2PyxajCFxB5WsNKwoM9D/3tShquJwublK+x8X2JwamO/t5QfA4+qEsWjmwY5c0LRzacr3PdP4KHwokIO2dCldDJWbhxLU00Ng8OL0iwsek8KTIE/P7zqk+iUXIj2ZzbM15j9K4oSNLlyY89+27md2TMdYQTerq6T/qyMOKxW5a6EmNF0tuqauXJjS05ADL00EzWnBRpVLNwZCPlo49gNFyz9zhso/nooacTvqSMjQR7KJyFK/z4d9O3xikS+ymzfqDy0ChlUhKuCjpBVT+HszXwduUVVza6n3DyEh3GORqrAMDP/u//QG3e5O90Djy8KlSwQhoLiDwtV8NyLv3ZEJWVQHvlJDzEp03Ck3cyEmYPjgQLH9ZzdvnGNMTVNNxevZCdai2COG1ryvilNjw0mA4RbOZ/Hp3r9sp4bjb+M+fehIjT+01Ki+cHymvBSEbWpSAAOClWdkEKL7TxkrXxmXNvGq/xd/1cpyAPTrGleiC/YIUbWbtU206M3a2XPWAc5p2zoVbMJMs3ptFLRq/tFyZ7/DHVQteYZp7s3z/3kZf170gZ82IZGchM4YrtENlDDe5JHmHKxVJUw1/EtQXMkJSOw7tp6WbkhNexxiqAevDrtybwj7//cbV5pYDfGBie2/zhTVSXA61gnS00pdCKvohV4RKe8Bl/L1sF5RqS6bc9XVDBFd7geLZJj7/nG8cMWVGGE2NkNK1hg18H06FxvbmDOHNK3L92/mlIL93Q5fWEssgMQH82dI5vyhNuSILxvmIcWFWftRuBfsYiFOhfUIU2XjXU6+hr55823hONR9opKE/0RirH5uJ1PHQ2au5+F32xL4YBUd242OvOTnyX17KQ087Z7NqqLKQGapSmUSSX3l/IdMKj/Mhvft+k+laXA6x/OHTT35Lf2fejaOLPfuURfHEfxfaYXErlf/yNP5P5HR8zpD0cwQod2GqNWiXDW1+5OaUVY2k9wOCOqaiopwI1WfE7ZhLJFpsOBijGRWWyi90nQqMdYu6Io4HA1jNptzES6cBCo7FI9bYIYsUFdTit+52CwTcrxyCHtejU72fKu7Ia6Ab0LlYGicGHdR1zbACvFhqGJNwtQ0Yig6N3jg3SZ+xJbXDzEkyc4zu7uOVso5ortLun1D2zvXS/7endOCoMBWQjA3oOxN458uRt59/15zKWz0fPXtbf87XPHaYiBU2RaNQqAUI6W6CSTB7c0fuJ7nf9egC/MVAFQ93h/VbuWR55yqNJYaMYT2Go04e3DU/I63gZ6+wqr95cbmoP5cDxBEeVqpPbyHidJ9VgyrZnTCXm3FgZeuif7iBmms/moJLi4aXkUbtkKBPyFgZTkcZEa9MdnbRxherUdpHOlYQ8e1GKM94H3TsqaOBhvGtyOKD6jUw2s2F4XhN++5oAU3m7FLGrvwbxYV1CU8Z5UrMIbgoaA32PpFfQrzdRqHS+fn2A3ZZplJ9/8mru56gPSJry5Cj8qB5rwyoHXuEE59p0J3OuNoOl+cdKqV5/J+0d0ZhtpdBQAgtwLvUbv+uenDKqxGWZ5iekQDhhNoziU8tdHm/7aIioVUpzQkK1DvihySOlXCwUdnUOh7oFILfi/q4PxCq8W781gf5KUh5djnDy6SXItazX8uzp65nfkYfCebnt9XpaCRXnd8maW9zUD0mWpS5yqS4HmXA0apdQ8pKJzgdaKvts6xghjd4OAAxFyjdwdayvqGR75UKGhKFwWZKCvDqbhVG/HiBqlbQirt0MND9Z9IUxOZxe4+/6uHlt1ig+IXxzmPc4jObEE2wy9JxNhnhIyXnfncUw42VyPN+uSAt3y8Y9mnrCnLKtj09wly9RWQnQeKWmm9cDSiG++vbx3Gva74ABIE0Mfvq5C+oz+mm1ZaU8gJxJlXaw46czEFs+KqsBBgkczRNprbWGNthxLc54onnTY7gBIK/Z1cfab3nohqx9Z7MHJOuitOkbVZ222P1sAJUz4a1g76eMCl38ew1f6LBKSEz/hMIW4600bCKIgjYtLTbZVyW1wcFs5v71d48CyGb1M17F2yzZ4AHdnpsKtbo0lalGevyxZUx/bCXbxcyTWvHvrdWxcGTDwERnF7dQua0+x+hal5Pt7WzUVNUnS1jxBUMeCe9pK2ITsnFJ6SPKEyZFzDemLEvD2NBr8niueQMCgHycWf+dpmjcSpV6dTkweLu6xJndIrsNKHISUyLMTnS2hRsZvzGAiNXxebKpNx/qUUfhblk1f7IofbzPcmO2ZRRxnH3iZm5Y7ypA+cZrarKQLEtUVtR62brdNIwbv0dRI0JvLtSsDzvaqE130ujH1cqV7Y25xU10NmqZxlKTB3d0ZFheC1SF5ZuqIGVzuamiuUqEwU5FPytjoC2Dych79jazOSWvtr88wr7lEftiNAm2Aty6oDaP3fBFlGMEN7JJp+pyYHhodla6u1EzeJp8E/m7PjqMZTO3uIlTc3eGtnQkRX/p/YVMw3Cv6+mH2ZzbA6TA8o1p49w2Lk2jN6+42RnFAjjxtBMnVoxNU5lJjQ0ZqfYi9e1Q436oQIUbHl2McTvIbdNI17d7Y/TEiqsCUN/3Ix0njk4SJcaGb97ugun5Gkm1HLwxjy4nA4nmhSADc+WJXK9Aeuo+cGpf5nWOHbS6NKWNkM2guPjHx3MZIlRMUZ3uaMXFYTonxFOOjejCZivI0DPuVWejZkQ/5rFU0QdROV1VnoAJPfRnQ6wtTWLr6RSO6yZefl7xjSynxSnhs8qQk+I3Wu0OacZ0r/KB95SFEL4Q4gdCiH+d/DwthHhJCHEx+X+KvfaXk8mu7wohPrOfEwonIkT1GCKIM4R32feMRAWVlXYXzKo3TuMhTIpCfhujisbTBvLltQCVUog33zuC9nq9kH7TX2pomhpR0EhhctbA3rWm9gLH3w0g+x5EL+18JkvSXW3msNBXrswbBsVV3ixLEv6eD9n3jeQfNzy6p0HNvL98c3c3aqpTWqLsz525lvks1zSUzPkk9z3cLRcm8GxvU/fvsOa/PfF40j88uT92MpUgIhuCqqwE2DkbovF9856JIMbk60EGwy1tqcb4dI+jVgkLRzb06/jasIejVqc7ZrJTmMaEw1hUpMSlu1HTDolgCpU8UC6y7xnKy8neSO4VtQCoLQVOxoPsK4VsF83sJ/H4n//8S5ChpwakFhTf0D624S4XhEIybDDBvuVPAab8i1D9Qkl+CcDXpZSnAHw9+RnJJNfPA3gKwGcB/Foy8XWoGF5R6Dmx09pSkOLPTCnl8Sn3HkvaRW75CMb76MxJPRrHlv5sqBNJYwdahfQbv+Pp7PHguOo566pMi2uxxuF2T5vQC434cTVwd/X+rd0wewLneZ625y0Gwjm5xO8IE97YSENI4Uug42uFc/6dYxnFPJhRc+l4OOp1PO0hDRt0yTm+E/O7BsTBy5a5Inrv0qH0/KDGFHHMljxXOwIgyqFN/5Khh61nwwwzo3dQTUgRA6G9z+Ub04hW1Jrja2OmacI2yqCpcw52FCZNBm8wFRneNY1rconX9TD1L9K10dmoDe2eqOffUa6XBrbWB7oFQGcxzGD7NGAg3Ctl5izahpELXz/+ro939hYKz8/rekYvGa/rjVScNfVaUKiw9y0fdExZCHEYwM8B+Pvs158D8JXk+68A+AX2+1+XUvaklFcAXIIatDpU6OHPfi8wsvjNuT3UZ9qorAboLIboz6oxN6PesMpkF+FkhHC3jKAjsLTsDsuAtCJsWDMe6achWNwJ9jUynXC+7W9mMU4yTJyX7DcGqnovMn+vPc8h1KEPPXvF+fvewdDov2EUoiS9mHtbVY15n3/nWKbSrX00NGCmuBZrD6myJjKsFr6JORzR6ZZzqXQuRcQNNt372hLD00txptpz+lW3ESuaWCJLijI5+z313sefMVk08KSGr3jRDmH/Rb1XhjXciasxln8inTJTWg90gq20EWS85mC8j9ZaA3OLm/D2fMV7poGtjl7Y3Jh98/Uz2gBTco32FylpXg9A3j5fP9F4hG++fqawdDquxugf7Rk/F1XgEg9/87kfQsLvA+4p//cA/gYAftvmpZTLAJD8TwHySNNdhRBfpOmw0a7paax9NER/u6JbP+6sjqG9XjfC37gW5+KHNmGe08x6c2FhA+1nP/5+zkEtfPtIO8P5nDm0PZKhoMKM1snQSAqJSqQN09y303OMWiWViT6ewiyGDElGvPr28UI8F0hLul1Z9Wgs0j0HZOQZm3nyTcYQsbz79rEQtWXzWWwuN1GfaWf4rhTGukqt8/B90fPQfCf9zM6i2Z8ksPpcbDzv3tijzDdc+6h6L3nqWti95wVAGmYpEO6teh2vsMxc+oqKOegGmJjfxWA6RKVh3kOKyFaXphCNR5mcjH0f4yQwosKjKPSNvfPZ51+H1/G0ko7GIw3fHDjipkpOHtzJdMOzmRV5+8/G5yu3A83DJ7En5NyLiHi0rwctQ5WyEOLnAaxKKV8Z8ZguDZFRVVLKL9N0WH8865UG4/1M1y5A4Wp5Hb9IXLPPSKZeMxWHHWLnUptioTnF1VuBs6HP+q2JkXpic6W2ujSFQ0fXMbe4ifp4qhBXPxHpgZS2uJq3DwsBi/BcIC3ppqy6bVyuXZlTw2vfK6P5VNoro/yZtJiDvHgKof3GQMNHXNrrdWcFp9f1nDh5e70O0fO0p6YLdSoxBp9Q2DHBGZzJMsYYkUSvzFN8LiWa6VzIPECX8eKG771Lh5w0L8CEbYg3HNdidwtUS+JOmpwd5fVcCBIqbQTwOl7aFyNQbVLDvZKxd377B89mMGpa93YSkK7VhvzGLgZOJVw0KJfyQ72DYYY9MuqknA+yjOIp/yiAPyuEuArg1wF8WgjxjwGsCCEWACD5n9o33cQ9TncVpTizaWlDdDZq2FkdK5644RCvozqx8TBIDESG7lPUh5c4xbwnBZCthBvG3LChjlvXZ7C6NJXJ1F++fFDNDXR4317Xw9hFM8HDGQJFFp7KmQHkDvaUIv0bQUlRu4TW8dAYN7+6NJVRaHQdkaObW1GVl21MKyuBfr2sxBh7fAuAMhyi52Hs/UDnFQjOMFqjnkunOQeJ0uhbYTw9b9sDJpjGgFuYB+hqpM8NX3ktQGMiq7iBLIuE940epaqyqKqRII3qcpBLURxMhxlly/uujNKMiYwbGUpSvMSrBtTz2zuljmV3d9NwSrK46Tk3rgZmG9FwP2mvfcoHFb6QUv6ylPKwlPI4VALvG1LKvwg1sfULycu+AOC3ku+/CuDzQoiKEOIEgFMAvjfqCT3/5FVnYsGYinA5MJJ8XOzOWiRxLYZ4N1V6YxcDY3MQVLL7hLkgixgGM4e2IcpxBjdtr9edWXUu9B7aAIRr2ptSliSkMLmvgFJgtOABhbvHG6n3zkPByddNrPXS+ws6ZHX1bgh2fNWQKPlbXkEIHaMXUUcxt2fIMVtOByMGAzFi7CKL3nyoJmY4piyPOs+welhFVf31Wlq+y8R+3iRxJ0B3QWHuQxOWjsrD/myIvTuNzIAEW6QwFeLQuX8Abm/kJ6AJf+8uhDg+5e7+VySNqwHKtawXq6ezJ0q/t5awUizO+jdeO6shDg7nUHc3Ia09moSWtC4IosuTIi78vuSDnujLkV8F8KIQ4iKAF5OfkUxy/Q0AFwD8DoAvSSmLQbtYqN6yPU/DB5xXa3vFrow1cW9tb5MLnzrMFdrCkQ0DKjGayiesBQqPeQi7tV2Ht17KJKhK6wFaJ8PC0m0qPqEEEOGaeZuSh4uuZkc7q2OGoiJlX5nqYutZ5gVtBxADAX8y28OAlGLYjLSHUlT0IQOJYydWce3KHIJtRcNzRQlhM8p45KVNH7vvJ8U1j6mm6YOpyPT2kz4deQNbbWiErxkSCtmlbw5zzYsQgCz1yjWVm6SyGuR6c825vdxJ1ySj0ApJyOu3oTN7FBnJje3JkY7LjWbreOiERUhp1i5W1NBXxyWXNlQjLfv8+JrwxgaFe5SEIhSK+EobASqT3aEJ+H3JB9VT5iKl/KaU8ueT79ellD8lpTyV/L/BXvcrUsrHpJSnpZS/PfwspOotmygVvzHAzpOh9sRcXjHH7/w9H/2munvDei+4hAo7gKSLloNeR+ExnWN9po2oVdKeAu+xQIqcRlHltazkCo9ntstrQYaWxHm3RQNBRRCjtB5oZW+E2UIirqix9xGjvzUuJ8mjqcjoxQEAlceLKwLJA6JN216vZ6oIvY5neOR+Y4DBVISFs2nZMyk+DnnI0IOcSJX0J595L/c8SusBdp4MtXEeJkXd3foT6d+KsHq/5Rdi9TurYwbG7SqmGMyEBmvjf/j0P8msF8K2XRxkrxYabTIBZVREOc7QAim5arNNyCEY5oVWbgeIS/mOQ1SLMT6VNcqc3uiCtFxCrA5S/oPpEJNj+4Msh8qfBqX8wxSOS8r1CoLxvrPVI9Ge+GaQsz3trVKobSs1l1BYPPP99LVc4U28xdpRMraAGAi01+tGIm7QzG4Y3WAmp2Vl+bFU0fIwsD8bZmr+8yrvyGvmjcTzKsYghe594E31tWFrnQz18WNLWbXWGgZOyCVvcCdtKJ7E4kIb8+a12aH4u/CkPs4fvpHfMIcM4eDp1r5aTbqEPws6d1eDoGhcfabtofNENMe4iSpoKz8e5v+1b/wFiHFTeXcXUpaOXx8YkaOLatc5HCKoJscgzHZsoPM0eWyT6AcTzt+TYeodDFHeSg6brCMyKBPzu4hrscG5L2KT5MGM5BQQNZSgIRGK3ErEuxGBDzD74kHJe5cO6ZBy/Ng25C3lHdvhc/d436DFPP3EDY0TcmjB1ciE81iBNNmw/hG3t7P9FOtoxhKP5GVdvpx24BqGcVKhCBejQCI598qqWSBih9l2ouyFn1D1PDxkzDMCXKJWCaWntjF2oGV4czZG2Jht4ff/+GnnVO9hhQx2H2yXJ2bcg77A7HfNZxR3g8xxijDewU5FPyv7Xtk/u/i0ec2o6P4annOsIDfqhUGMDFcxEJe9O41MMu35J69q2IwrWnr+BF9F7VJuPoWkMdtK1wNhtolBIEPqKhvnxRncsHGjStcqI4FjJ1a1Qem+nlWY3Y0agm3fWazVWmvoe0lJwOp0RyfTfRq8mkBDo6zpfcmfUkz5vgspu+2Vca0cyAPWI9EHnqbFiFJshG6yEhd6yJzHCpgKf7+9hIcJGY5gbIBg2zf6Y9Df+AYnpd6bC9O+zRsBTpxOmRJAChOMXQxQWg/w7TdPAcDIYTuQlgXv3Wlg704D0Vhkvp9xsltrDUT1uJBmaIvX8VQCNNn4pfVAZeKHFeSUJdY+Zj4j7m3RMyKow9V9rbISQPjKu6Z7pfssWBGErMQZT4hHJPVrQSaJZ3v99Nwef2wZwatKGX/6uQuAkEarSltsD/fVt4+nsJkndWMp2hM8ierCoTkk0bmRXoMNR5EhjVqlTGKWJyVt9pPLqbh2ZU6vZe7tk4hSjHAiws1rs5m/Aem9JAjM6OGcU6LtSqretTyCL+5OKFTjZcLk2blYGu3HB86wyejElghP0HGcjDyWF866K+EAtUiFL518VSDlU4Z7pYwyoL/pSqakLSOnuAEKRyNv/MVzbxkKZO9UaNwT6mfBxet4GVM/cSGA72cXdvtoOri2sjwc96Pw8tyZa5lhpHEthux7iFolBGMDDGZCY9OSMbR7Rrh6N3c3ajrCsbFMm1rodTz05kP4tdDwrm0M3mgPWrAD2sdCyNArHFZAcun9BR2dfeO1s4AUha0qufBoaPLgDhCnhUJkuDnXNxyP0JzbM6IXDklww/HpT5/PfB4p9bLlLeclJf36INN0i4TWsqsqsnLN4qI7Kk+nXlOc6ZMnbxuRS14e5r5S5B4p5Xzxgjjjqeq5et+xZnZVQ43TZd5TiSAj4cwe105kE1Z5XawIj3v5woncQpVb12cgI4GJ+r0nH2RZAlIYjBASYnC8dP4pQ4HkJTT5Bo9rMexqlu2zoSrGcODB5JX15kMjWee6T7Thzr9zTEc1nLVCyiTcKxkbrHYzQDgZYexSkBkz5cIMZ78boHtchdKEPwurJwo1mKfPGTaF2oAHkvtgN6riuO3G9UkAWYyUlCIvl7Y9U35exu94Ay2G40ffYknnO4F6hpZhlWWJndUxeL3h0d3Xzj+d4TWTMfe90bzOPPaLMbAgMQpG8yL79BK4h8vmc4ozffnyQQMC/M2f/dt6LXOP3tUT5m7lEXwxRMgLogdNuoTzSCcuBIi7gZqXN93JeE6y56M23dEPjntee3ca2qulEChv83J8dncrVfCuXgWtXv5sQZJSs4eJtwJdykwyygLjwzL54qSE5uTBHWPhNA8rZcpD3GDbz0zgoDCW7oWteHWyrhIZ9ynYUk2KBuPZ1Sp2Ar2R4lqsPeISg4kIt6R+v0DSjCjHQK7/WF+PsSqXkrXhm6OGiEbp6vPsEo5J032w6XXd7dRg1G758DrZakOCdDj3WWOiSRK5tOk78dDcBlqPh/pZ6Qb9UkCUYqPIBMjCMbyrImHCh4+tYfl8mvvgdMr2el0n3KghEYk94ZwbFnIIbM539VZgRK+941nHob7kZZwpFxzzF773n2tjxaME16zKu5ZHnnKxkGLhD9qvDzTsUJ9pa5L9ys0pDKwFQR5PZ6OmH5zteRE9TIYePvXMu0ZD+DyRfV+HXa6pGb33UyI/9xL4xh/sVLD9VJipBBx1gaWTvtUxuRe7dbsJwcJYwkS5Mg8nIkyeS70lPoFDhp4abfVqqnB4CayeaJE8h3AyUqPrHQowrsaG16cZMXkUPk9ibnET2yvjTgNZu5HSE2XoYft6yg6IDph8ZiA/ow+YnrBwDESwhTc8ah9NK+DyjIct5F2qUV6j46DSA8IxB5Nn4GWmnWdew86ZMOGb12YRTkY64hpYnPooVr//5utnjN9zmigANBfTNUcOAeHJuoWutb5dieDOU90sDOXoYEhRlAjFyD2w9yXywbAvhBB/SwjxjhDidSHEvxRCTA57z0OhlOPQAxxtOqN2SUMV7fW6tqjNd4JMSEUL4OTJ25nwFgCmzqv30nDIb71xWuN2riYnRhKkoOEP91a4lxA1IqcnLCrpvD0xEJpqpbP+QmLsQMu4BtpgouehNt0xOnMBQO1IljFgJ6Qoe1+d7mQmcET1GK2j6etd4Wo8aW4Mnhgkz6mIFeEs3Y1FbiN1AOhPM25zyzc2M0+K1S+q++MqSqCScu4J+yMki/ISSuFeCaVNf/SZjuxcR00m07NzcaRdVZNex3PmTIxjTiRRhuW1k/fPG0txoWfqomRuvqdw5v6NYraJcR4MOgrG+3jh7BUdgbqM1/FTtyF/WNM/Hoyn/BKAp6WUzwJ4D8AvD3vDQ6GUAXOxlJo9Z8XVYEb1Mth9Kt9yXr58UCd5fuHDr+rfb55TD/57F06andn6Aq2OsvxcEZJXSsqEQyHV5SADNrkSHTEnNFDCpufrY8uShLypKGF60UuBvTtqlppOItJwz0qcoUNRu0b7fFwG4dyZa6rXr6sPuoNdwRNxlGChaIAnFslzIlaEXx9ky8KTzcgVDb+nLmiIV9LZVXVaKcZqjlteiTdNyCZpzLacfSu4iFKsr5efLym+wVSEYNfsPaIrKFlRU6nZg1cLcfLkbVVAM0IJNRduWOl+8lCeFGZci93Ta5jIgYfKSpDp7UIMFpocwuXFc2+Z952tMSFZwU/yv9fxnGvLxfGeObSNcLeMly+c0BGoDemUJ3q4cmUeTx/dV+uckeVBYMpSyt+VUtLN/Q5UL6BCeSiUsp0IGuxUUiqQpZzjWoyFxdFq+v/VK887f997KZ2ILMtSK7rDj61m2RQbZfhtDys3p3QSp7sQatCbFpxNyC+vBcbQTudECKTZfyNxl6wErTy4p2CtEk1dshJ6XmK3PvH0Rf278+8cMz7TFsJpaUq3nYgD1OZ2FWdw6CBql7QHrDcpQUC1WCfmVm5OacXi5Uy3KDV7mY0uKpEBzwBA+YYyDDajQ78nWUejlPjyiIc/N674evOhkZiNOwGefuKGUdT0o8evIO4EqrFUKHI7o/Hr44MEuGdtRxTV6Q4aJ7YLmxPZ0psP0TpiQmxBO98Lfen8U8ZznWUsFCmynn9ci1Gayipgu+x64kJgNLUiod7JgIJE+tsVVG8FetbmfZfRPeVZajOcfH3xLj/xfwtgaIXzQ6GUuVAiyOt4EKGALEnVKY2xBZavKN6jnQ13Zb65zP2RUgAdNqWeh+E3rh7IeFFxLYa/kNDypsNMMQstOFtxcBzV5QXS62mjR7fSIgpIoRWjnaAj5TsM2yRPlnjMGfFkhqJEUAxN6c6TaCeb3OzspRvPrw80M4EMAE/mvPr2ca3YycsKd8vGvaVCk8FOJWNEXFglUe5chgRAYVk1CcfqXTQ4zf4ox07a5e7AVD7ffP2MPuZnf/zVDCw0/q7iVPPre+f3HkvPucCz7ibdEmlSDqC89byIgcQwMo0IncXQ2UuFhBsxu22mfX7NuT3Iy+r19Cy5U0CyfTY0h/72BUqbvtE7mRyl7qHwvtcQABhdIavzXKM2w8nXl/mhhBD/TgjxpuPrc+w1/xcAIYB/MuzUHgql7MpOx7U4LVMuSWMjEjxhZ8Mp801C2WrCqlZ/NAmzTisMdvLgDtpHw0yoDZgYG++SRsmrzMgcL+vVk1TeTxXF1MKOwketO2+H56QYubcNpBl2nhgrajfqqlqrTncyk3rnFjdRXU5HbZHCtj1PUYmcPaMpBPVbvqI4Tvf0fa9MdTOcYlc/5XAy0pxnXmhil9xycYXGQLZVpEtIcdA93dpIP5M8OR45dW8q7FT23X2fqQiCyyBUn/FvXn0u87fd0yFkJAylQ8nfYX0oXGut+m7VnHbeF0ZfDcDdxzg+3smdXjNKi1zK1+ysjmEwE0L4EuFkhJlD29opsAt9+BqSZVk4uWe/sM8oInD/4Asp5U9LKZ92fP0WAAghvgDg5wH8BSnl0CM+FEp5VOHecl45rNf1tJfZWiRKjXmZ/SW1+bZuN+F1PWeyiTA2u7kOCS/jJvpQnjfWm4l1mLm53ETUiDT/WfgS1eUg4/nmZX2DO6a35be93PaTADLl34ePrTkVyurSFLoLYerhJwp7sGxymmXPzxS5UCTQmG0haqjR8lG7pO+7C8PNY0q4WB2lW0qBE85bvx5ofNfzJbyOh/k/NDf99RvuKjIuZGB1sylm+HWPFXbueRCUOhHp9DjtKkbX8E+X0qH3Ebxjv8+11ig6Kq2rSkRZlplKO1cSN9wr5SazeQ6DjBeH2iorAQZJnk8XdSX3k0MUo45L45Grq5jofsqDwJSFEJ8F8DcB/FkpZXGjl0QeSqWc5yXwTUOJsekfWL0SqrH2MsOJyMiSk4KlzTW3uJlJcIlBCh0AwNbNicxm45VUftvD2usHjL/7LV9zkkVJlShTmElhO/VHkJFAZSPLmc7Dfe1oQAq1Mexz4ufCJa/kFUjhIH6suBZD9nyj+RLHUstrijv++GPLGbzWZij8V59M4bQibNcOwfsHQsMIt4+mBUS9zSriWoyVT6bvOXnyNqo5HvSoQh5rZTXIYOjOarNYoD8b5lZ4kuQN/yR4x56gThFU3vuCbT9zPuF4ZFS+Fc3MyzsPzgPXk14SZcsjx958iL3HQxw6uo5ozM04IqkuB8ZzJEoqRQr+rm8kkLdeUXsmL09wz/Jg2Bd/G8A4gJeEEOeFEH932BseSqW8n56pmx8r7gjGE0KcSlZdDrCxk34OKWJZkgamKn2Z4dmSIvf3fET1WHsB1Nc2akRofuQORFnN3At2/HSRO2L/7adCp1dQ1DtBn0stRn+xj7gaw9/1lbfKrvkjH1XtLokdQMbCBXmQB+1iYvDmSySl9UDfm0vvL2SqH/l5+I0B/tYf/kxmg9mVdAAy44OEL52ULBf1kc61s1EbmVPsEjKKvbkQ4W7ZZKIUNMcZxuzgLJ1gbKCVWHRYHX/rdnNfdDvX+UjWMvbYidWRBwKIfjr1PGgJfX/pmvz6AMf/pfvaqQy7iHvfXQiN50iUVDpfO0rqJ/sqL09wz/IAlLKU8nEp5REp5bnk668Oe8/Qpy+EqAohvieEeE0I8ZYQ4v+e/H5aCPGSEOJi8v8Ue88vCyEuCSHeFUJ8Zthn+K27B/I5NJE3rdiWxmU1VSLaSi1+XnLrzKkl+Hs+KqsBGrMtI/Gmy72DGCISRnOk1aUpY6IxJdFsj9jreqguB7rQ5ZPPvKexTrt3AlcylECZW9yEDBUjIhqP0F41Ddp33lKJI6KkEcHfBXkUkfQrk13D6xaRMEj/j/0vkfb+XZ5N1Cph7EArs8E4f9hWsppGyH7PvWi7e5wtw8qt9yPhjeGOAoec8vowc5ZOuFdCd0El5zh/l4yZ3VPE9btwMjRazHKRgXTi3CRkIIJtH8HYwIBRuoeS/iFJ/O7VQkTtEq79XDL84B7bo44iPwwsOT34g4Ev7kZGMck9AJ+WUj4H4ByAzwohPg7glwB8XUp5CsDXk58hhDgLNTbqKQCfBfBrQohCZntUQyYhYYsLi9MXkXiBrmnFroXdOhnCq4UICkJNehiXV2cRjUXozYVorTUyiTdAYZ3Sl6jeCowEk6soxS60iKux2pj9tGewPcmEhCuZ7373DCCkwsM9qRNn5OHxjl/DhqqSUJ9jV6e93lZVh9KNq9l2mu//ed94rSuM3bvTMJJ1mQ5m1jFdGO745P56jfBRWCSkUOYWN0eq2Jpd3BqphJtDTvzcg21fwxIcj03XpsiUNQPKc/TrA8MYZ85DCqPFrEsqq4FzLBUZiHAiKaVPFr2RlEsiOxklBjJRlCfns+0470ZsdpHoeQqfv4thFfuWBwNf7FuG7laphOLSUvIlAXwOwFeS338FwC8k338OwK9LKXtSyisALgH4aPFZqIREZSVAsONrBTx/eDMdmJqDqfltD2I9v/+EvYhpE8addCI1hd18gUihIA3Cz4KxQUa58UIBABhMxoZnQhQiviHsQgsAOimzH+pPNJ5ypV1Jmt7BUCfoSEEU4Z2cjmb3orY9WPnhFPekDaxnuCVKl4ex3DDK0IPX8TB5cMfAx/OgCNtT2Vkdc46oyru2rWezY7nIgK0uTWlFmlcKLWJg/eoU/txHXk6vZ0j1XDDeNwxbOBnqKc8cj6W1KfueUdYsyrG+n1G7pI1xXnLblpmXiXUUIRjvKwhmXDondhuQkzUv7+Rvxjq5RxEpRVMXr2XhrDyxk7B8cC85ObT2ZSVGUA/hv3Ufxz7lyAe6yb0QwhdCnIeaWP2SlPK7AOallMsAkPxP2mgRAB8adjP5nX3MLxIZO9pVib3efIiwGaFzWPEYV25OwXOQ0blE9djALl0eAd/Y3Juh4aYUdgvLCekcCY1uZ7bnZo8CovMQpdhQ4Lwlogvn1NVjeWOjXBOgRyg9lT0ffsvX3ntvswqv6+lkjlZWQmLyPcfxPInZxS2jG9nMoW3dmJ7GOgHpRl5khT2UMIzGI8379fd8eD2RGUVve8kaunCclh1JeLVQ454uz8suNOHnRjL+WjlD//IbA0hP5Rl+8/svqOMNhIat8rDfcLesDVuw5WcuwmVUuBKXYdoLWvhS0/7yps/wJCwArL+QYLV9XxugqBHh4g1VXs+NP619ziOfObIFALj858zroxFojSsB/IQFxJVWXkvWlU+aMxrtKksg9cD9todoq4zO4fCHl+BL5IMMX0BKGUkpz0GVCH5UCPF0wctd2iJzaVLKLxMZ2x/PWkUpVDIur21gnrh6wkqR7XoFADJIw8nyncD5XrsPgTEVhC1uPtVEDjw3fcqT2uuxN2b1VuBUHkC2G5hd0m178Jy7u/h7keG9x9VYY8H686TA2kcTj2XAeLOxwNrSpHFenOYUU+k183I5uyOuqiILv+Vj42bC+z22mwvPcIlrcao4hYQoK9zexVUmPLZxJa2iJMZMfTH1LrmnGVdjg7Ww82SYKWF3zZMjKlqw7ec+Ly6ua3X9zohOmMGVkdARHU8Gc0bF5csH9TOrTXcMWpnROzphL2ms1pMYf1e9lucHdJGIJ83GTIkxbp0I9TWMH0w97XghgeZey/bCoPvm8ta5NI7v6MTlDy3BB+y3eOSByr7SvFLKLQDfhMKKV4QQCwCQ/E9g6k0AfJLjYQCFT8LLaf5SlMktrQe5M+LsFocAsPMH2YRH+2iow0mOFf/5j3zPeJ3oC3iJpddTQdYDIxFR2k69BvIKKIzUwjabvTEpAZc3s06EQuPQdkk3GQAyPIOdCmZeUZ99/eedh8sVWZKQZZnB4uln7pXpTV6QcOtu1BA1Ih2h+H/cNBSrq9qRRLNApIDse5g+slXY5JwrNmKFcOod9zSDHR9o3H0byLw5iDalrUjyYJA8D5F3PZSV2Gi3SWuxu1cxaGWuGX5AEinEArunC+5Bsl5typ32HoU0Rl/RZ2US1MyJeO/SIZ2Qp6Igfh/oeHab2x+KfFCVshDiALWbE0LUAPw0gHcAfBXAF5KXfQHAbyXffxXA54UQFSHECQCnAJhazpI49FC7qUaIF2E4RjvMmdAst2VxBm9xSJue6DckUws7mdaDJL9702xjKMsyowi5Z1FZDbBzVmG8VBoOABuf6OnPcomrc5oxs44pLxnIwlH3pWYPyzemNfdz/cPpsaniirwpnmDjYTzffDYWTz9fvnzQHBk/YhKRZPeJ0FCsrnaoed3mXP0SAGUE95MYmpjfRdiMjPVDieb/66e+mnk9QS96jqKlNMkrnz+8acAyedWGxCDhvTQEq+wr8hA//tT7+ntqt8mvPa9PMz+Xw8fWDNpjHpOCPHObcueRErVgmRfPveV8f9iM9Fr32x42ng8xc2gbP3lWGZVoLDLOrzrdybQBvd9yPyv67reMsqMWAPyeEOJ1AN+HwpT/NYBfBfCiEOIigBeTnyGlfAvAbwC4AOB3AHxJSlkcrwqVyOttVQvH8wR7BTiqA3wsbfrGpucQxuZyE5tbyovqrtTxVz/xe7rUlPOZXQkgGxfuzYUoT/QgfWks4Lm5HZQneti+PJk5RnU50AlKm48s2NDIomnPnOlBIa5tfLxqiNLPqWpC8qZ4go1vzsodUxm62COAaTgKq9wS4fPd+DFdkU4w3kc83d+XkpUlif52Bf6uj9pSANHzDIzUvofcY7ZnzP2/3/pp47W1pQDbF1QSTs9RtJQmeeUrN6cMWMFuxENTr2XfT4cL7KTRhsZVc4xSc25PUxw5FMOTh3nCz4VDTH5jgMpr6nmSYqSoKDMJRkhNvbSlvBbgpfNPGb/j7/eSaIogn/VbE2psluP8XBWnPwwRsRzp60HLKOyL16WUH5JSPpvUc/8/kt+vSyl/Skp5Kvl/g73nV6SUj0kpT0sph3ZFcoUIrmKK6LH90aHKm6aiXr4xbSgCwgxlSeLvfvsnnckz2fcyFX2RXdxQiZwbY+XmFPrbFcS1OFOa3DvW0wvUDve4B9der+eGckUcVEp4xd0A65sWxpeYf165CGThot1W1mOzn0teqM3bpt6+k3q4vKkNXafuQVGOEO6WIXu+UrKNAUQ5zk7SFlLRvBjjQsTKm+8shpCVGFPPpt3TyIi4+mHYTXa4wQHUsF2Cmj75zHvOawXSZCwpbt5jYm5xE+W1QE+C9usDyFDx03UExnpPuCIirxYaUEFe0s9v+SOxeOg5Rq0SWidDlDZ9DHaUYcul/0nh7Fni1cJMgZU9TSTcKxm/e/yxZQMKG6VXyX2VPy2Y8g9NLDpUaSNwzmvbbzFA66Qj6ccUXqYDW47wBScikQkRXV3LbNk7ZXaYk31fQzVFEzOA7ESHPPG6noYTOEbuLbGGSOeDNKp4LvW2iEnAvbTeVlVvXgrv6bkQDpgXan/ttz6qknOlGHEngIiEgbdy2COcjHDo6Hqmki9qlYDdIFthKAV6c6FRPSc9c9TR6tJUxtsmI2ZjpHTtBOvkdU37wzeecP4eyGLMPEEtBBAe6Wb+xo1gZaKHv/SxbzuPPXYpyGDD5FwIX+poTkRC4fcjFF3wVrRex9Msmrgea3jFxvvzDLALtyZ4r5nkd554/JYB+a23G7h8+aCOFGwHg+9NJ/voPsgHGb744QtLFAlphteu4g8gVQr099nFraGtOwEYI5vC8XjflUl5SS07FOcbn7ym8rZQTIJY4ZQE1bTWGs4m+c5pHQUSV2MnnMCbwVCz/zOnlgy2AXnttpdGSrg3HxoVfzTJYvzdwMmI6BwOlfFKbpf0JbZuN7V3a58nn5ZsYKQjlggD2bFTeWE9QUyNqwG8aohD3zRhHXFqz/k+IDWgRutJy6mg8z/7xE0A6h7mJdwAtT56m1X8o+9+Qh3P6lXB5xnqa0gcgXKzp52E+vxeYZGVPt9KpBp3ndkCYD4L6UttHG2832WA/ZaP0qYP4csM7FKfaatcC1SCj8vmclNh0DlKL2aGJS+pes/yyFPOF+LBioHIQMN5oZTuQzweQQQxdl+ZTYdWtr1cDmm5kSrhuBpnwrEiDNd57tQh7ULSVznxWji2TJ5R+5hKBkrPTFpVJruQDtsjB15uY3QutaUAENLZR8Km3pGif+diSh23vQG7zSIZQE4RI6rU7ukQ6OR7MjL0DAy+qDcEKSOuTG02g/18XFTHYUIGs3U8RNwNcONnpckr36yi1Ow5HYLODQUbSJGG6LahpvO/8N5h/btClolFvduPIdL87IkeWmuNTJGV1/Uyz1f2fMTVGDurYzoJTOJstlQgUSPCYEpNkSeDTvCJDQXZ8tL5pxBOmDMMZw5tKxhrIhra3Ole5ZGnXCBxRUJEAuW5fMyYkiQukaFncIypoMRV6sutvR7Kej3QyShaSDMvZ9tpkvCScPIm+kluMC/7bQvHXHkJs31dpNDtbnh8cnH36ACQwugjQcrKpt65PDYyhKQUvZMmnEIGkBSXjRfmtSyl+5/p95GjoFzKyC4ysTe6MeCT7SC/PnB68PWZtuEp03kaZdFbCl/lDoGe4Mxe5xr4qT+fOQWzi1tOlgmJq0AmT0QlclLpuCETsXr+IhRqmG3B8Sly0ueS02xJlOJCw0Ly+GPLaUOkgcicq7sBVXqv1m9NaE99WHOne5ZHnnKxSF9mHgJV5wU7vk6SAO6sPQBjNE4w3h86LVoPZT0a6vCZPIWNjw0Q7pWMRaW7Zs1nj+vqiaHeJJ1JSxpVxUtOi2TjQ9bxmWcnHSXK9jRi56lZI5hkJUZzbi/zHGgzkkIiZUTDAfJojP1J8w/k9Y+96t5smWq85DnT50wt7BjGiERjnUz7xDtlJ6eZK/XWCXU+3YUQjauBLroIJyPdM4MiDRsKEZHIbQwvpNkhz04mumTUsU6y56t1K2RqRC1aovTU8y/qZmcbVkB5uHmeoRx4wGZZV8HmyaX3F3Q0JksyrX6k4QWPDVfsefv7vorEB7vM+k9KyPvlHOFgvJ+bWOOjccLdMp49fV3/LHqephG5NjbJ6ScVDigjNYKKP5QDR81Q2VZqLvH33ElLElfJadF4HpL9dtDiZa7U74DPoiPhGX7C20m5Lb5kvn51aco5RYUUmY0bR+0SqrcCtI5kz70x28oYNnrO2y2FfW8uN50GqLdVzTS0ynBrO56+B3rTJ0rcb/loHQ8x9iOpYtx6Nll7k5FTgUlf5pa6SwGcOLECQN1DV24g2PL1eZSaPWPtAkqJcWWbOQcpdGQxCi3RFpeXL8tSV9IC2ZxGXIudyXNbeDRGNDsedRAskalETWCzosT5fnnxefJB5yn/iUhe8xUXJQdQi9jf9SEGQjcK4gMXZSXWNKL6+yUDmiDlU57oaay1PNGD7PmGQaAJJUTfIaVW1KCmqOCjNt1BfaZtDIwEsgkrLZ4c2gzH30ubnhtJzLFQJ6l2VsdGqpgKd9XQWFLKSy9mN7/r+sJJ5clx40JJwu6hUG9QSkr5e76z6b2e/sEgp/KdwNlRkEcvriEJcS3WMIvs+QbNjq7hzpU0uqCCoup0xw1TMC/ZZgcEWz6uXJlHZaqLcLechYw8NS6JlE/MPHpS5tF4pJUttUkd9swqt82ka1HD+SLRfa5oArlNSXSIKKcVhjzxaXO1gRSWELNKYdN1UUK66ajIJbkbA5QrUo729YDloVXKeTzMvHAiGo8Qj0WQJZk2CiI+7pL5kFvHQwPnJEXPQ9QiQr5N37HHuxNWCZher00p6mzU0L05ZgyMBNwc7cpkF4hVM5yiJujRWAQZKOVN13Xy5G3InlJ8pNBGpdnl9XcYhi9WJnqGcXH1kQha///23jxGkuy8E/u9iMirMuu+prq6p7tnpufouYdDakhpRS65FElplxQWPriA1rSxawK21tD6EijIMOA/FpAXxtowbBkgVpJpey2C1goiVxKlpShRApeXhjPDUU9Pz3T3VN/VXfeVlVdEfP7jxffivRcvIrO6hzNVw/wBha7OysyIyHzxve/4fb8vPWfjvRMj0FpMX88eV3c2zKSPSmMdw6tTQxIK3JxgzzPeF0ijj2DHR2ujhsmFnfxGBr1l3mIHcB6/s+mWMLU97Gi/pDbQKxcd6mvJ2/N3xpEOb2qcxujcZ3ZL2lou08e2jdmTgLvr0H6da+iBDep6qsOQC59Gl95ygJHpfcNR4DXB18Wf1c7ZwdbmvWLoKReBRHbkTjlWu77O49XpQja/Vy9ojF0I0JiRlXr95lbvM0DqQT0354vJ4xfvP5ReS0+7YXWPb3x+F17bLVy09obsuNJD1s5WVd2Egwjh6IZOnxpiGzSWpNQ9LFGOcz1yPifvTnbT0g11Uaswh+27j4TKwOh0Kt0IPHrmJkpjHeVx6V4pv09vp5Ll8XY8ZwVNlKWCX3dWSrH2dioZRkdtWb5O7+wMtv3MmKqxub0MU8VGv7oGg5al8ee0y+x309l8tqwrp5iYaeEqkAZbfuby12+Nq9mTjN5OJZdxwUbSNuQ6mIZamWwbEYy/55tdegshRmsdhLvl3EaR9kKYya0f5D49EIbNI30gUpF2pXC176tdXw9t2Yg98fB1Z8jLN87Oo2FmrBS/d3U5UKkHVsnKwCM88+hVAO7qeN7kakDmYLmAN7IgjY4d4m7fGVXGpzLRdnZ0hZPaDSQoqyntKDSVxzu5Y+bLa4EKy/k5LEnJn/XEfTugrif1mjUoMSSeoGJ5h6X1oJBhoIMlRVnQprwaqGue/JHZNHDh4qJxc+vHLco9Og3Vjg/qJhshCcS1GKIcZxgdHUeNNByPMPJmxdiId1Ya6E1GAxdrXeDQnTdRpgCufbiHYLSbGt7Ei7dzqlwfyXTQ2Up0OUVJwMy/88ZfWg/UhmIbcoa/6ysaamezamz4dvQDAFsvyrw5R5rBltzo2PhXp1q4fmXWoMhVruZrpd8rhoW+AeDve0rhigIyDBlXb0vrAcYuBMboJR3U9Z2erd9MhzLyYnvm0avovrDnNGLBSIhXLpx0zrIDZGW5aPjnW+dkbrp9VXpbbExc+bnOVhWTjhy6UUAjgdOn7xg3JefuRqb3IToeRq5KUX7q+mjMNjNjgrozqTyl3T3HeGL2tjqeOk4lUkYzr6JfRA9zgTxSx+jOhspotJLMkCjFiKZlHjpo9NKOQwd3WE9d6LKV9nPIS4xgskDmFjczFMbyeCeXSdM8FTq/c7tYK7oC88c3Cz1MBofuvNaZAkhdz6ifTB/bxsR9O8op4c+BC599P/8B9LeDHV9tAr3pECf/jft5vEHn9RDkOQV2WiSciOAFsbof22ptpt9J+1iYK+h1rxga5QGgROJ75gQEIF0AXk96wYzx80G2Xbqavo4LTIrYrqU/XrlwEp3NqtNAcc7ZNctuEPDNE9Ujw7t65tm3nM/nUNkf6alOMAYb4qWleamjkRSy2G7ur4+AKjHiZ1PDvrdad44JcnF3AWngKxPttJVY29nYI138t9ZySQypvtHoKQx9U+DPQGlyWGkb3pT4BqVeWmCMdktpx2GyDnTaVNySdLbKZNuQrdQRtwJEjQjtYyH8po/6UqAKt3rRl2sJ88c3+zZS5DWuUJnQ/tPZXA/TBV7reQ0T67fGDc62bRDzUmkuQX0gK3rktbyMEuLVv+c+13gyv6FJhMJ5P7HSng29HV3/HvS0UOXLSWt/TnfvXYEwLPQNCq8a5jYjANnddvtsmPVstJfHFu1LD2v1PJ0rd+W6QdRY9BxvwHh9wgJpXR9VudNXlmSXFxtHzh0yov0Sbv7BKeMx24DZaZlHz9wEkFXXchlgNnTMGWZPgHwy88BWzkZUItz8Oev9YiHFdca19msthaFvCuWS/LzyvFA9f5s5Z4dtpI5vsCz27w8z/Oo86mM0Ehvay+FeKRVFSgzxnRuTwIh8jj7NRpfO1LngQaNneHT2hqhvViKSUqN6RMfNS4M0TFQm2xnRobyoLW+ggLjPbNSKa3FGehNwG3vdkxWRWQ8aW9xxGuC9l6YBQYU6L+wIebVQMTFqNwLc/nDavduPfXQQDAt9A4Jv6jylq/H5XSV1+cTD153P0XfqvDAdMLm+NmfXa3mYauxndAjUWPSuj/pMM3e2W2k9QGculDejSIszfpJDY+O4+sHsTbPtqD5nhplqOcILFxfdN49Wibc1o9lDKZJKNd4rJ38b7ZcKc7vskRUZXRv9BJoY9uZkw8VptlG5HaA61UI0KzcWf0IrOEcpq4Epmt+/eNr5PuFeySwMWlom+mZFvpQa1TcbXfsDyJfvBKThVl1zA1yj83wd1NJvvPI4/v7zPzSP1cmyZvTCKPlkvNf2nVGn7nX4YAsgYWwe9vR0vtfiVtpha9dRXLnqu8aw0DcY+IvKa47YvjOqpC7PvXkiDYvXggy3+fifiMwXz2CPKE/EKK7Fsisq8axdFLDmWh3U9ZxeNuf4Gi9XDTZBb6eC9kKIFx6/rEI04ZMUdCkIz+xhpkHixZXHO6hNtdBcqxfeoJxL5s9D57zyY7zBcIGTIUqx4TH4u36h+JOg1CgZA2K1j8lF6yuvBRDlCAvjO0ae2Gt5eP7skqn61seF0ZkARWqAnftCtDdqalPWqZK6UWeKpp2DtiMm9hLDsSi30UH3JPM0q6N6pKbHqGM51hn5lNlwbYhKlOs8GM8rR/jqX6QzjkUvlerUU1RcGK1MtgdWcHNRIqNmKRV4qkSgSqzuYXuTYgzSWDUIjnTziBDihBDiL4QQrwshXhNC/Ery+JQQ4htCiIvJv5Paa35NCHFJCPGGEOITBzmhqFkqFgXiPGZNei+883Znwgy3+cYnyVgM+uReLljpinRF+MRj53P/xkMkbZTWA6M9XMf3XntQhWjBWiAFXRyFkzyluGqtC39P6g6r4p0WrucZIpsbCgAisT3U9SCCGK9cOGm8hnqe4dVFo5HxudmiNiSyI6vgEchLjVjjSnbpdWdCjL5SwaXLC4riFmz7iGsxXv/jMwZ3vHqrWMbVYALUBruz9NSEC7yR6N6kHYltXtaE3XMYOtuvp2kPbsG2DauoRGp6jBK5cnRgAsjMFmTwxlQe6Tk1WWxDTd1US9nf9Y004qNPXYONzmYVIhKFXn0RRJymXVT3Zk5/AiO3seqgoMEE7g+lyD2AEMB/TUSPAXgBwC8LIc4C+AKAbxLRGQDfTP6P5G+fBfA45Cy/3xRCHOhbu3/KbJ4wvN1YwN/3ELcCbN8ZPVDX0k6yADj98YGzsugmev0X1tdffirzGBvMvLydf0bu+v2GRSrj7CjKxK0gw4UVsQzdi0I5PXdrT7kw3qsUG97hqRP5Ggyu19euB9h8Juzf/ppU/5XYzIR1HolXunM2NFJGXACzJ6q0F0JnfpFfKyKh3lMXVMob0QTIjXJsbi/TMcgiOtU7HuozTfz+i+9Tf7OjM87/Bzs+YkdtpHIncEpRGobVIwS30g3IZVBd9Y7KZBv1K0Gq13G8iycevo7gpUbmuXnvC0iOcTQaGUMQzr95PKNJ4e/6CBuRCvG9lpdba+G1M7O4pbxjPXXWuBQ4veC8AuHbgqOaviCiZSJ6Kfl9F8DrABYBfAbAl5KnfQnALya/fwbAl4moQ0RLAC4B+ACKYNF1dFlJIBv66M0Tg5Lz9eO0znSwcGIDr35TMg2oVDz/LvftWoExykn19CehHhfebC1ZW32Ob6I8485Gm4+VlweeXNhxetYUeiht+hnvtbKS8rWDRg+i42Fpad753sFO+vrGbFOdc+tEkmMfH+x7mP92YpSTgi3XDnQvXxVj+8SOSuxGS4Xwa8knkJ9KcnotyU+Ob40Ycqj897nvyPPaWWkYXrbopep7zdMher1APQ4AO9ey+VNARgquxiDuYqwWpRxiUUhxO/bnXtqqrH1unc2q7FZN1hH1PNzYGc+kvvohGg1RXgvQmYmNzZa9WV7n0agU1OfvIa7FEDslZ0qD6Y1rNydkqs0y3nsPhehNh5l0Tt5cxrcDRzZ9oUMIcQrAswC+D2CeiJYBabgBcO/xIgC9Ancjecx+r88LIV4UQrzodc3dUJDpgdh8WxcG0R1mUNfH7SvTqUF3EOvZA++3U3N+26ul1X+/6WXSB3rrdUbK8uRgGs77J0PVXMEVb71pYHN5DHEryHjctRuBIXTP6MylHXXhXqlQx1c36Hur9cwG0k+ylI3YnZ9JDEbydFWwcjBFKuOdXA9c11nO63AMRruIazFOnFpNKYqNCPFOWpiKazEqE22sfMi9IVKJZE42WSLd7QqeePh6qqNhfWZ5mi0MFvRxtW/7+54RFU4u7KgNvjLRVmyTWx/VROmTaODk6RWn1CzT6HT6XmlTih3l3TNey5dpgqmusbHwWunZ3ZPaRxBXY4TjUSaq4s2fIxXq+pkIkMRginpvCwhATIP9vA0QQvw3QggSQsz0e+7ARlkI0QDwrwH8UyIqYnO7EmmZKyOiLxLR80T0fFw1K/MkzNySi29ro/5iusgrtwN86ImLxt914zW5sKM8M0FwEuvbC5K07tqp2RPQix9xWz7GY29s6ldQYHerFXlzzP07X4WMGbZFgs2n5ftGWzK8tT2qyp0gYzC5gm2HvNVbgWKF5LUL/8JzP8o/cQcmF3achpRKVLxxOuhrna1qrgCNrbPsQtSRn+H1K7OoLwUqRWU3wDgnauipkb0Aou2pzfvcmydUq7A96aNfTrTwfEdiIyrcXB5TReLuWi2XbeKP9HB1aa5wXNqyplQYNuSEGp0jrIOPGVzTxogt7Ki1wkwS3vzJSyOexmwT5dUgE5XxhhLfTu9Tl6MAmJ99sO0bqcW8wv1d4R1KXwghTkAOl84m5h0YyCgLIUqQBvlfEdHvJw/fEUIsJH9fAMAN7TcA6O12xwEUJlX9lsmSeOLh64VtzK4QnUVMJv4mQHc6wnfOnTH+3psO1Y20vTSRdkTph/FIebiiHOfSuFROcFKjTyVvZKcqGC6am2oJTxb79kNCpQPyQs6PPHUhzZsm/46fD5QH4tJ6ZtgcWL3YF47GGeEmAPijl55Wv/MxRChUXpANPTMjtt+aUEZPlCOzseRmNuRm9JtzyIWwfkwDAy0fwbYPrxqieTqElzP5yxWi6vl6KpHcHLTN++rSHOpvBWgdD+GP9Jw1CZuhwjzmymQb/p5fnMKwUKSNnGdczTdIz51KVJhbZ8SnWyrCa/0w23uub/7+lPxw91brTi46byh6VJNnYMv3awV5z2TwuFgcd4t3MH3xPwP4VQxo4gdhXwgAvwXgdSL6F9qfvgbgc8nvnwPwVe3xzwohKkKI0wDOAPhB0TGimmRJcOh37s0TmQYSf99Tn1DuvDOPsPVkfvMJ99zH1Rh+O12kiu0RC7WgBpkgErcCOb6m4KNmD8ElN0ldX4asyQ1dZFAZ33r1UVAlljnTJHTePhs6JRJt5KUC/KYPCgidqaxXytS52lRLHaO0lUptsqFnZgT5pH3+wqQDJp7RIPxhG62NGkQ5NgpieTQvNnbkE8LxSHl29cc2nc8vmsxhG1Y9DcCpiGi/lKlJBNs+okUzMmn/QBq2zmZVdhfazT73IL4zEOUtecromwF6OxUjpeZCuFdSBdZ+qoJ+kPV6+b6w176/76Ey2c41sMbsyNFINWG93TgA+2KGU63Jz+cHPoYQnwZwk4gGDjkH8ZR/GsA/BPBRIcQryc/PA/gNAB8XQlyEdM1/AwCI6DUAXwFwHsCfAPhlIiquojEl61v5YvDRSGzcPcInjEzvm4Ym8WT8kR4qE+1CMXt9N+83SyyP/+vVQjm+puCmZg+hMx+qEE/n20YjcX6RsUBEhqG/1/zxzdytvTrVyk0FiCgthOmozzTROSU9IP1G0VMmdpMPlUkNF6Cul/kO9P8PpNOr6wNfNhse8jZONna2MRgk5WGDqX98rkUTXfTcajgeZZwHjoJsVFYCiHKs8q46dXNQDOJEcB6fpQOap8K+Eqz6+iqSjOUUEBfqgkYPJGQajp2Nkel9LJzYQDQSp4XKjueUqgVST1pJ8b6dGDR1IZfrGqdak58v6m8lhPgzIcQ5x89nAPw6gP/+IKc2CPvi20QkiOgpInom+fljIlonoo8R0Znk3w3tNf+MiB4kokeI6Ot9zyK5T/M4vTo4ZKdIYH99BHEtzlR7xXIVna3qQB4ZexhFlLi8CdZFE4oZesGDyoTqVKtQqxnQipbJJqNTk2zo73XnxqTT7bOLTzaVTGcKsLdWGuuo5hh1LUkhST+Eq8nn/A/Srjf+DviGJm2MEnvRJ06t5jajUJjmcvOMmg49vWFHHjOLW84GHY5mbOEbfcPnc+X0FotD8SZTvRUM3B1pHKPtoTMnJ3/zGtxZaRibnX3O+prq5+3qcBl7l7KfzoygpTSPracedGOu3ztcqOP8dvN0iLELcmr49GhTbWr8PVElVlK1eoFaBGZ+fZAN/CCQzSM00E8/ENHfIaIn7B8AbwE4DeBHQogrkKncl4QQDtHsFIeuoy8PijrlYAhkRMYLRpLbgxvZ6OR5qzZ3ssh4c9s3G6/nHruSGWWlh6x8LnaxyM4R5hmjQdSzRCyLT/pxOV/qytuzt+ZKh/CN9vef/6HzBuc8pevzj0biVOAnFkZd4PqVWfSmwlwP0Wv6uZ1vjLnFTYzP72YaKbhdF5AGg2azudToJVnMtWsIcS1GbaplFEE5wlpamofXFaBkOXZOZPOjbOyDHT9XGCiuxnj+7JI8j3qkvlN9s4tGI8MI6muK0wuTCzsQZXm+s9/zndx4fdQXABw/ueY8J0PAfy6biPfanmHM+d7JK+TuPJpMDU9GXomuQHt1RA19oGQCCeeoRSRAoaciVFGJBhLaPzDiAX/uEkT0N0Q0R0SniOgUZL3tOSK6XfS6Q2eUXXk1EYmBZ9Lp4jFAlmo1yOBGLmLVbgaZDqLjT+Rr55578wSChhy4Gmz7eOn1U8bfuWWV6Wx8Lhmd5LzzsoZWDqInQR7QuGhNm0iMjDdAyOvinP6bN5/I3OAAIC7X0xBeS6MEo105ViopVpU2AiPKYO/T9Z6ANI46VYoNum6oVm5OGswH9mD1dl1RSfPLerQQNsy1pYfTrY1aLkuAFtrgAQ12VDb2eoC91TpmFrcQjkWpwXFshD9886T63fWdei0vV6s6aPQwcS6Q8wu7HlobNay+EBkFZ9uR4OLsjaszTkOqa6a4hs/qzSI6Bio4Qm44ugAWrwXO15MvC+4coVLHz9zXbwfeLk/57cbhMMoinerMnpo+gYB8yugAMGy94859MlxSr3Usqn4VfC5i8cQSPVxc/7NjhR5qvCY9zGimZ4aZb6Wje8LdcmZB6/nPkWuBs3uu92wq1HPsm+bri/jUe2esaROJkYnqkTJez59dkuG4tYm5vF6XFy0qEcbe0hpbkhzH5MIOwt0yaidlCsXf9zKt7Xa1nidJuyC6Av7NKkRZGli7CYE9RNI6+gBpiHSGh86u0I3u1MsBVq7KEDs3ZE42HDZCuiAPb0qcirN5t5X5LDfSafg0xLXYKSN68vQKwr0Suh+W63FucRP3/2H29XYUyPnc0ljHMKScYrKjSXXuiWfLqa6ieXlF7CkbI9fk96jn6+01YatD3jMOllN+ew4pPeac8CTFoTDKpVKohMLZWNnTfdffFzp3y92HQ5VzUxMMPuZuFeYbmENcUYmKdTYSGI0TD4bYXB5D7UbgVLI78ZiMTMo3y+p1j565iTixY3kTiDvzoUp7hE82EY5FhoGceFUK2DPpf/nD6WoRsbvzaeJVs5HEEMhnyc7EcL14/rQcLtrHQAAyf2rTmajjY+2nUj4054jZ8/t7p88BKB5lxfWCqILcgiWVCb2pULVre1pkJcrSQ1QNCla32yDYeDYE+YTKSpAJmSt3AuksaEl1O72Vl1fm9EvuzD+kbf8uuChxV5fm4Nd7aO1VUFmR+tDX/m7uW2RqC/bmGo3IMWB50WTeiC/bwbB1Mxjc8GOncjw7o2R993ka4PeGo6198WNHr5su7LgWG3lA3UPg3bI+00w9S4+UiAp36O0kY2c4TB+5FshCjCUeQx0fnevZkHkQMe3W8TCTUgm2fEW70yvGFy4uojspF1Ze3lSEAuFeCf5IL6WXaQaSR97HtRi0UZGTWbjwlvct/twGwolI8rMFGRtBv6KU7mXqdKvGbFNOpHbQmTiHKgRlvOHf/cFPFR8QcsOq3Qiw+0iYKVjqvFqjmy85j+py+v3m0QP7MQ10dOayeh6d+RDXr8xiZnFLrctBBXJ0j9lu4mFNiR+cf8B8vCdy1+JTj1zDyPQ+oqaUTnUxFGxjVtTYwveKHkHwxq3fj4D0pHV9EtvByJtIwuwXu7mpPUvmvamzrHpiIEfhrjAUuR8QHhl5QPYQdI1d+uG4qqzXrmWNAxtn/vL37w+dPEvR8ZTnpt+A0WjkVFmr3XCPt2eEE5G6wWzjy8fhvGnQ6BkhHl9nHOZvCPUlOUKePbhoJ3vtumjM1u0xeC1PbhS80DUvhKMEDksND4YF3ifaEH5609ldZfoQzErJ3ULM58TX6yqW8t/s/DobYN3Q8s1dGusoDqutgeISt4nbAX72yTfS882Z8gGkLdourN2cKGzmYIjATDuIcozKSmB47V7Lk4L9F7PnSyVC/UF3WurVN+43qJyuQiKFxQJMQJqfd+XNeeO+dW3a2Jj3HgzdMxAHlPEsr8qRbtPHtuGP9HI1XwAYHvcgDS8DgzAcBzUwksqv6lpLdntdHHv/ZKiMS1GRbKQPXUhfWPYN6OpK6j3aUpuB6HiGx6bes5PSmmzoBjPcK0ldBUtEv4hv2jwtR8iz9xRsBsqg2scvjXXg1UKI5PMcP598FiQwPr8r5yEmNzWHpeFEpDaT8nVpBCcarVzq38KJDdzZHlUL15VCGZ/fVefEN5ihsZx8v3a4u3BiA6LjKQPs6v7q7VRyOax5HuzLv/e4+j2T0tA2LJcIfD/YE9mrV8qG8aaup86X18LP/pSUhG0+5m433FlpKK7w6dN30lO1CuIuw/bUI9eKm4oEFdI69YJndSkpUlu1Dj39F47LlJuek9ZTfKxh050NsfNoiPXlMfjXaoZDVKT62NupDNQkMzCGnnIBtHDFb/qSbcFqX1boogyb9hr9S9U1LuICm+y1PcM7Ka0HEJR6WIagegJDAL0SH7gZoT6W9cxsj0MXlclbgBwe9qZDI8+nL+gH59fkXLrEAOpt3nt71Uxul1usO38zAX8vDYdb3zBz+3oBdvn6lBSITz5+FWp7SWNPLdW4NtKEWlMMhZ6z3VgfMADINIWoRIWcbRuV24EqBPO57T5SkG7I6QISoShsnGCEu2Vjk20dD43Pq3FJK0D3PIiOh+9eOyUbR8JUeMg8uJxSIoIYS0vzav1zQby8mpV25Q/71TfuN0ZmMVRthoSKUMrjHRkFeumwhfCr6XfPRe9wzOywyzRedcyctJ7i2348NKduk0B3JjQcIj3i0RuNxub2MDa3N1CTzMB4hwt9g+JwGGVBqRxgPcpt1gDg1khI+u5FKTa6zXR+r12lj6uxwUroTYcgIT2sY/ev923w0JE38RowQ7rc8UWakdINvz/AHEAdvKBFJHBpWea2a1OtjJfpyge3FiVPuDMfImpEig3jf3TDeJ7imjrYACqXGAvU/2jU8MJU9qTjofFmyWDAcLpD5y6LUKhNk/m01PGdnO25xU0ntatzX6i61/Q8p/3cjCHUICoRKKDMJibI/Tp7k715e1J5l3sPaeceS8ejs1U1DE2mmJZ8cFyQtdd/dzbEyedvpNcy2TY2F9eaU7Kp5VhFKN3tCsafWwViOWyhdjPA+vtCp1BVbyzO3aTyxrip1xZIktqdszrNcPfGKHZWGs40z91CxPFAP+80DodRRhpK1m4GRqOAHd7raMw20ZhtqpvfNWePQV2/cDoxswX8pq9y2vf9VXZBlteCDN2Hb3z2shuzTVVU8jv5x+RJF5Mvufmd4V7J8LQGhaj3lHFvbdQKRVz0999ZaSg6IbNh8rjQFFCWE67tpasvZCePBI0eqBJj76HQaPLgz02spBvhzF97uP8XrgCQfFobHBVM/kiyDqL9Ui7V0c4L2nzazlZVTq92DZrNEUoikc9G4OOVNn3EbVMxLdjyjcJZ0YZuHzBv87i2llLJlHysVSB0eczU9YxOSjXde9tXnrEr1xxX41wWjZ0GdBnvPKohO2M8TJi55GNze8rjtumddw3Cj7155G5xaIwyo7UYGpVqMd41eMfq8VBgb7WO/ev5FeVMocbhgbNBYLZAXEsX4e2fzS7I7owpeKQXrbozIc4+fAPN2w1F9i9tm8/RixXfe+1BAJCTO9qesYDZu1WeqZXKKNL1cDUa8M3HnkZpI0D9SoDbL5sdnzuPHoChYHFHizRAEAu1Udgt1Xr+l/Omm4/JaRd54Khg8+mUKmmIFWn5e/IACDJypLYBv3NjcqAqfxGDg40Np3NcBi2ciIxCNm/ojCJpyu5mVR1DT6/ZUV19pplhQESvjKvX6kVzXveljUAZwXA8QvVWgMZs05jlOAi4AYQ3OGW8k2hwfH43pRpqu7iewlp/Jqk9NEwVxbcTAoM1jvzkNo9osHfRuB24DYWln9BP5F500jlzekHGLgh5rfwKcmmsgw89cVGlJEScJeaff/M4oD20dyZE9eSOMrh5hRfb+9CpXkC2AHhQpbXeVIjyaqA8jd5UiOapdJS7nid0Vbn1KKOfkLsLc4upQcybixiNRmryiV644mad8njHCI855bX4IRm+u6ZkpA8IqQ2SwFSbGyxNtHBiw9jw7CjO5jXr5zMyvQ+vGjqLwzrKF/J5zCTSY3gX8id579/KGrHWYqheu79TyzBPelOhMoKl9QDhwy3srdbdrCWfckW6uAGEQk85PPWZpirg67S8+mW5xo/dv24wdtiZOoiux11hWOgbDIU97lrutTSZGo5PP/eKs8VTLwoFzfRSjQ4sK2QtGgvV26ngO+fOqC43m+vLN6HNX26u1Q2Dq4eSeZoIDKPwoVHKdOPkCk0ZhifvYJQwdBYDbxyNSwEeeEA2w+gsgu07o5l5bToMrz75zlZuThZWzr2Wp8Jzmxe7uTyGTzxzDt3tCkq6wNOb0vi89Zb09uORwYwrF9y4C1LnyBa189oKcccfuZNr0Ku3AsS1WHmf++sjEB6hEkROg6YogSfCjMF0cdt5XejfrxLr6iNJQF3PYJ4YIvJ7PnrTYUYwX6+NUCSMuk9eWpAdHv/bJiuHi30sfZo3ufrkz10pvI57xtAo9wcL83htDyPXzJujMduESHLGohwZIdvXv/G8+p09ZlGJ0DoRKuqQyzsTlQgUemr2nW4gp49tq/Pxm35ua7UeivMOr8Tgy3HG868uS00EvgnzOJouDQ+DUtbQ2BRJMcdreRlKkb3JfOXjv+k8HiAHBOjYeyhUBi9D3SsQpWev3t/zDXGb0k2TZsbe+eTCDuJarHK0+k3KlKs/feUJAGZkw5uMyrUmOhQ67IEIXstD6W/JENtF4RuknZePd/3KbKYhicEeZmk3vf5ov4SNnRHDoHltD43ZppESs6l6OysNNQaMwd+z/v3aRUZ9fmQRasvaOVrDeDk/Ho5HCLZ9Z42nH2fbjnR702GuRrIeUenpK3/Pz1USvCsMc8qDof2gNGZxNcb+/eYXubdaB/kEEcR48vRNuUASj8PQ912WC1pxY7Xin5FTvB6o5/CcPTaQYxcCrN8aVxzoqB4ZBS+9Ih05GgzY06Sul/H82cOhEmUKhrrXFVfMhW7nO6uNLK81rsVoL4TG+9iE/v/gG/955nWMrSfzDRJV4oFFYWpTLdl8M2d6fLanfuKD1zG3uJkvrORRX61rwCy4hbtlI0Vg83CpETmP52oKEl0hP0tBRjNKXoHPpdlhRDql2EhfiTiZafdqdnPQMXItQPxzKcMkGO2i13AbQqWsFgm1rnW4Csetp1rwqmEmkiltmHKk4XjkbBrp1ynJI8X0CCiPX25HVOycRY0I4XzO6Ji7xJFlXwghflsIsSKEOKc9NiWE+IYQ4mLy76T2t18TQlwSQrwhhPjEQU6myPtaOLGB8ngHFHp47cXToBIpj8MYSjoemTQeLeVh5BQ1apWdI+1X7NILOHHNPUapH2zvCAAQya/Dq4W5ymQMW6KyNJbmW3XvjVMtXttD5XbglJTIE4+xH9e9yGDLz20Bbt8ZQXc2NFJKTLHTcfn6vKr4O2HNTvxPXvh2/nM12PxxzufPH9+UQkWONEpnPjTSCuW1QKqZdX3Fpy2C1/JUK3wedAfB3/OVwes3kX3/fsn3jjcrGJvbQ7hbzm1lHpnfMxTWbNiaMgAQb5URtwNFwWQKnyu6HH0jyGhTnFiQkQdvhixhy+CRYrIzMMq8PqOj0k01tNk5m1vczLCr7g0Dpi4Oafri/wTwSeuxLwD4JhGdAfDN5P8QQpwF8FkAjyev+U0hxGC9lzngZorl61MqZRGNRohGYsXKYE1ZhmHQkhu7iIu6fWe0cNqDq2VXB9OHFKxFN/2ilYpImCM6GpcDfPhx2QI8iHi+jd5OJZNLZCPtj/QQV2N07pNcbL0brHorkENNE8Oln2veWC1ARhW2YeBIhEoEUY4No375jVRKkkNUu3g5ci1wUqg4bP2d7/2McRwXXOp60UgMUY7Upiy23Z+vbsi6M+GBhHDiWpxZJ0oZ0JFz1Wl6egTCG7zRRJR8X1SJ+zIRmmvuGXmAWXjU02q8bjiPHDWi3KjIpUvCei+8GZ5784Txd/29eJPTr0u4fALu7CW5XtY27n4grROEo2uUieivAGxYD38GwJeS378E4Be1x79MRB0iWgJwCcAH7uUE8yb0Ni7msDIcKK8F6K6YnuXZh28Y+ha82Pkx3fvtzsjQzm/6iork8vwUrEW7/rwWwnaFysGxuHl5vIO9B0N869VHM29VJKrfry+fypJLHLxlXrvucXDukwuR68+HqN0Icuf5FWFrTx7HH+mBup40zqyJG5DaGFduTmamnwDSK3LxX22P7c6NScNL1zdUe4oyQ48eiiQndYi9ATZHXUvkCXmbMO2QC1moOqhxyXmWxjro3BeqXLjqnNO7Rx0eIqcheMOypVtt7W3AvG47raYXxckbLLfOY7+KZGMBIE4uxVivgtR1hXslVVAGTG4zCWD7pVnEreDA9Ly+eI/llOeJaBkAkn/nkscXAeixy43ksUI0agcTGvF3/YORyEkaKN3QnL+4iO5sKMOxBCJKB6fa3i91PUT1tMB46fJCrjeRxzWtXZchMRcNXzwvxyb11vNlJeNJ8710761I6Y0Xdue+cKAb7PmzS8qAth/sSOZAwYagzqeUjuPiXGu0X1J5bZ2619mqqtRBXI4x+Ur28wsaPYwlOh3cWOHiZHuL+8pj1r3HovzmIOp/OlxsDn1ax/GTawAJZSDZU7zvk2b4zvWAf//9L2bej3PMzAji7832unWjBaRpCN6w1m+N476/TK+v+UDo3PgYDz90C/Wl9Bh2pyTrUldWUn0Vu7vvjZU5jFwLnAVTHVzzMYqEluPCBeXSRpDZmFlvpn0sPNg08z74SeEpuwIR51UJIT7P02G3V5IFkTcW2hogmpdPA+TEBxujT8sCA3sKXstTi0LXQhh/7WA3bZ6xY46xTXdrPyi9IS40cQ6zqHqd4ScXNDjoi15P7wwiOP7i+dOZVl6buTH91w4ls56HqJo9fxcr4WeefFNdD5UJm89kP79wr4SdsyHqVwLVWOHiZPd2Kmk6Qtuo4naQ0S1RjQyjkZFP7ut5JSH02YfTNma9u/DG9WmU19IxRyzEc+nygpM3///9tWQJFel3RCMx4JGRw54+to29TnHb/9jcHm5/ODI2Up1JYad13rx0DM3TKQvC0KQA0IkSLZQ5qa8SbPuYfXrFfM5mVeV8uTuVIXwyPgNRifDc+8znuNCbCgvn8dm1lHvCUU1f5OCOEGIBAJJ/+du6AUBPKB0HkB0WBoCIvsjTYf3RJL+a1xIW9zcqDH34Ki/EdcsI1k64mx/6FWqMPF9OWKNPSLHpbhkDm3iA/bjKfFzRE06hJK/tyXDQqoxzeqcoN5x3/E89+2rmsfX3uz+fyoY3kFDQv3v9IeP/XlV6cxPnsq9tngpz5/Ixj5c9QXuj6m5X5ISSpvn3xqXA+A44dSMikSsLKSKR31kYmwXAvQflxHIRxIj2S4aqm46iAbAnT69k1vv6rXGjIOoqVHK0ENUjOUHGymPnpXWYBdGbDlFdDhTVjvPE6vXjUS6fGEi7UxkUCUT7JeWNU8dXkSFQ3OzFqRVma+T5avcEIiCKB/t5h3G3RvlrAD6X/P45AF/VHv+sEKIihDgN4AyAH9zbKbrhUhazoRYii7okRlCXAdXhyhP7u74KzznP5+97IA+Y+UHWmKy/Ty5ymy+sU6504w6kxnv62Laz0MXHpRJlWmqDLV8u4uQa7Y6xIu0QRqkpMrP1vv7yU+rvfr2XSdXooW97IZSc8IKmCCBrPON2gKgRYeuJ0KnFu3Zzwlmg7WxWUV4NMpxaIN0sqUwZT98QBNJAPoFuZKl3Y3N7as3o60D3zG2KWfWOr65zaWl+oG5Bzv/WZ5oZY6jeV1tPpZq5fnS2w7H71+UghCT60p0HpZ+doyPdXgjl1JcCDMJ91lMvzdPuz3xiIpX81D1j3em4dW1aDi84WPPq4DiqnrIQ4ncBfBfAI0KIG0KIfwTgNwB8XAhxEcDHk/+DiF4D8BUA5wH8CYBfJqK+q9KVM9RpboYmRPI7t2XmeVNFuyvvwHYVn0V49GNFo5E5p84jxGNyoa19wNGQ0hXw9/xUsS05D33cPWnCO5znnjgnc3MZNbLkszFGOWndfOFEpP7mVcMMHYy9Z/Yala6yhtZimJmtpyNqljKpmubpMDsKyfoeR64F8Mbd3FLbO49mU0Ojj0X6xTOpx65r9+oMAy40NS4HfSeq2FAylZYnWV0OsLPSUJuKONZS66BU7ykjef3KLCp3ZMpE9ATaD6VGxWt5oK6PhW9lpTVLYx1UJtoYn99VBcE8ZwGAmlwDL7sx62yHW9emjY1YjKSfk9LPdozG4mEFeS3wnELsTMt/i4yziz5oyOtumHnouBqrDV2/tuqtAL2GlBJ1RYj3jKNqlInoHxDRAhGViOg4Ef0WEa0T0ceI6Ezy74b2/H9GRA8S0SNE9PVBTsKVM9RpboYmhPb76BuBIV7EJHUgtS2uEJLDMJ23LOKsd8vH0g2/Xw1RvpUVQGfjKcZ6iPUuK+3S+Fz0a+DFuPVEjheX/N1j49DxUL9m3uRqkGXOxGMgzQ/vPJNd3HoXFSC9W2YQuPJ7bKhcNx97jv6+h/37Q5QuuXOARakdfSzSV76XjpFio6IL6gBpZx7r+HIXX9GUGPYu8+oT9JhkdEh6X4RoLTVk3e2KwS3uzIfoblckd17j2vP3svyRZPJKsplOL+xIgf6tqqEFYUdQOjikH5lMI8Q8auDIYpqeI206TWnTB0RW3Q8Abm+lm7nTk05SKvNnpfHePxmiMtHuSxdVL6/FgCA8f3bJafjJMcW+fSyU9NfRCHEsjCk39wwCENNgP+8wDlVH3yDQw3Mu0vHNxyR1HSxwA6QKVjY4HZFH4tcN/+RkE525MHMDsfGM2wHOnLllVOld58JwheAusCfH0pd5YI9EF1RnBI2eKsA98+hV9bjdwEElwt6ZEH7Th+eQHr3vgbQzy2Y0cNGLNx7O27ryxnqhzeUJia5wNkEYHqUWEikti8SAdOZDxYTR2Qsj0/sZLq0NvWuPuj5KuxrHN4fhYbd0M5heyXxg3UvUGQ0G/TPxTPUo8fjJNaPDUXcqdOifj9Dy073JCCDhLFCT9jz2pEUsN2WdOjpTSzfEzla1b1MN579rUy2ABF6+kp+f12F3R4a7ZZnaedsSzARQPNjPO4xDa5Rtr9Xf8xE0eio8593ca3lGagCQRQTXrmoLyjCikVjdULa4T/VWgIlzaQFkri49qKiVz2x489Ixpwawq3efjcagvGBbRNwu6LB3xoZb92T0m/6VCyf7HiuqW6mbBMvXp9S9wZ7m2PkAJ0+vGNehb1wcCegGTVcg625XMH980zBS/YR15JPS699YlV6n7q0yE+bW1rghDpQHplyJIDboV762Z+RFJK6mn2C0m20u0tCbjIyJN0BixBMjpUdVN67OZGoOehTH7Bj9OS6BL94M9VSWa6gDefL1eqro1TfuN56TJ0wlyhFeePyyioCYNRHtlzA+v9t3vetFd4OK93YlmAnvuULfjx2611oa68jed82o8G7uagSI9ku4ujRneC7PPXal8Hh8Q7VbMjXBhaz2sRB795M6H67EEyVyoEl464LtTU8+qRWFEk+IjYZ+Ha4iJt98VCbDuPcTgxl02jKjX0OK1/IMGVTGztkQV5fmjOtYnE3Da/ZU43aQq2p358ak6sbUPWc9XVHa9JVH/NGnzxuvp56XO4WkvVFzrhX7u2PjQaGH1kZNeXonP3I189p+CBq9gWb9jc7vofRo2oDRWgxVDUAfsTV9bFsZaRFLj5+juJnFLay/P8TUyybP197Eg9Gu2gx5RBgfq+i7t1NcgIwM9A1QF4Oirq8YGbWbZjPS9p1R2TdQQH1jVO4ERofuoMNZB8JRzSm/EyiaCAKkBHu1aDzKDI50QfdcXnr9VHq8gs+ZDb9eNebUgahEae44iNM5gl3f2ADY67G7EY00QeIJuTyGzDTonjBSKJyTs7mhB4XLeNmFsupUy/CG4lpsUO/YeLpulqtLc2rz4eYAAJisa5X3WuiMNnTPTQ/He5MR9l6SNYG//PaTANLOSABqCokL5FOmoULnUzsH4Sae3oWLsgfKbuLQoX+XlZUA8arpfXK0ZXuXOysNNNfqRsGbawDRWCIwFQs0KulGRZ70+JlfvP6WjAI3npVrg1N1VCaDnWFsEsmNENXlwFPykHtfrdyczBh4OzIId8vOcU2txVBFPfxdk08ZL941SqozH2L62Lb67FyR211jaJTzMci4dkAuRNHx8MJjbwG6jqylUcAeqt1Zp5o1BoiA7FSDCGJQx5eCNnF6M/sjPQg/nQo8f3wT3ZnQyLVyqsVVsR6k5VfXptDBnohuaLiIM4iiW57xAtKCXe9qI9PmqzNj2Hjm3iwOjrkuihO3AoNHPcgMNs6JRqMRxud38fofnun7GkZRDn+8VjCrL3Ecrr8oIyX29nXlM/277MyFoFEzSuFoSx+gq6cfuC5hFM9IgLo+nj+7ZNDlmFfdm5Zcb5ujrqfqcvPnrEERpy3l1PMyhpk370HSSXmdtlwb4O+6MdvMeEeu969MtrFxZ6yvaNPBMaBB/kk1yjpGpvcL801UifG91x4ElUk1h9j813CvBEHZAaG8MGxtZFfhxq4QT8ym+grkQbUCR/slUJxSiu7cmERlJUDtgfQYnGqxpRTz2rFLG1klrryZaIBpaLqL8j1dxRybtZAHvUtt4pEN1N8yP0edGZMZU6UxaQ7a1uzve9g7E6pLH4QGtX1nVFHKbA+U14fruvkYund2dWkOM4tbED5l1gg7DrwuWFDKbqjQo7687ktdjEqPgBh6yonXpt54AZgTbKJGhPpM00gHBNs+gtEu/JFerhgXfwacO1bnzZOy19I1rsPFailq6Xal9/ZW64Z3lNfS39msHnjKzkAgAHE82M87jENnlPfXRzLeY30pcKY4dG6pHQLr3rDdTmvr6cbtoC/J337NzlnN6JEwvJjOXJhRgRNkGg3RFZlNg3NyM0+vHLigwWFs0QJurtX7dg8CplFYvzWO5ikZQrIH5dd7qqWYup7xnqS1186dXUVps3hgrQ7eePjS7eKT8Cl30Khf74E6vpGS4fXh4v+SkB6i7Z2t3ZxA/UIJm8tjxr6oF/1ExT09BJDGW5A7JafTM/XXc+rLpm8Kn4CtbE5aZ84wmmt1w7CG45GU+Nwv5eo/8+ect1mHx9vO1FJ8Rj6fnSe/3iuMQMS2NqFd26hLYx053fxSgKgeFY/K8n4MHus75CkLIf6LRMr4NSHEP+/3/ENhlBcaW7l/q0610DwdysWekOJ5oeh5XCrJwoF6jmZkXXPGdEhVs6yx0tWvShtpgUrvZnPBZeBJmKwAEYlMOoPzfXksEfVazburXQ/gVUNT6N+ikenpnXAiMm60IslSHeu3xpUHRWsVxQnm99TBntXy9SnE5cRQlSOIWIbrLsPKE4y9WuikEwJyw9l7UnrPVctI8gZne3UfeuKi872eePh6Jn/Ok1c4BNf3RV1zgTp+rl4xAPjbvjMlt/7HMi9dmWgbr2cusU2Z9NcDxNUYDz24rLxewM2c8fd8o7mGoQqVSSTn8kiba3XnOojbaWpp8kcBgi15DLpmsld058KOcisTbcS1WG3oUdJ45bU89HYqqN32FFOImVXBlp+27bMxPoDUwmCgd4R9IYT425DqmU8R0eMA/qd+rzkURnl5b0L9LnxSqQFAFr24iFQ7tienIZQIDzxwO1NoiKtW8c1aIHn99tF+yaDgNS4F8Js+1m+No7ISQERCDhpdbsCv93JbRxls4EXHy6UMxbVYpTNExe0l8A1li8no3l3rRAixUcb88U2leKd7y3PfkW2/BuNhJBW+d+nzGqwRh4cS1+LUKGp/d3mPXLA6fXwV5ElPdO9kjJGrgREGr35QGu24FTjphIBsg+eNrW0ZSYauPQIA3zmXzTeXNn2VZ9U9Wnvyysmvma/T01xFhWZ9k/JantoEdx6TqZnOVtVo0GDDp3/PoifU+1y6vICoEzhrAPydR43ISfXjQiVHcnkzKPvpNG8+HSKckMcIJyKp0Z1EtPrarSyaXjd76byh16f3IbpCvdY1HSWciFJ9EH2c2Hr/esPAIIAoHujnHvGfAfgNIuoAABH17YA5FEZZB0VCpQbYoIXjEfxdH/vrIyqnN1ZO8416+KwLy8Q1k2tqL+ryeEdtAHohYe+hUC3ezlwI8gm1GwEooEzKofBaKrI4yOfgtTxjYXFOmTo+dndTI6Pob11Pet3H2oWFu2gkxsrKGHYfyQqzr3xIXkf3fNqwQD0PXi3MHVIb7pXUfEL9ptAV+Ngo+rsaPa/Ae9TZF1SRG5LNLydPXvv88c1Mnr+8GmTa4IGs58faIwxXfUKnWLk8Wi5kXv20+fjoeLqWVPEzyXG42v39fQ/UiDB5TkvvJB9nZ7OaoUw2Hpa0s2DLV4aaC862mBVj95HQ2NzmFjedOWTefPRNKOO0FOSFvZZnUN70e0lv7Y/7pN2aa/WBCoYu6QU9GnxbMHhH3wwrWiY/nz/AUR4G8LeEEN8XQvylEOL9/V5w6IwyIHNctRtyhp4IBfyRXqYd9pULJ+FVQ9RuBsqjEJXInIEWxIVSf93tipkbTuAK8eIn+4f5utHSQ8n2ch3lVTndOKqnhjB2NDkAZvGHuj7CvRKqT8sb1ta01Z83t7iJv/34hczfhE9GA0D1VqCijDz5SvG06bmfOLWKjkMkTPe8qstZ2cxBwS3DmxencOfGJDzLE6UcexHVI3zkKfOaWbI0GO062S2uxqKPP/Oa+t2eZAMA/+H7f2C0RDOCTXksV8EuGonl5Oef33BSBm3KJBu3cCJSDon3gLnuHnpwOWNMO/Ohemzl5iR++uRbyhNnw8+bj74J2Z9NUV44rsUGnY4jErsg6tLVGAS2TjJFAqInR3cVtZ/fEwbPKa+xomXy80X9bYQQfyaEOOf4+QyAAMAkgBcA/LcAviKEc9ZK+n70LlA+bFROHaf7/rtfwYmvC1z/1ODn41XDbHeVoIGLZJXJNvB6A537JFe2n8Tlgc5jkONPtFV4d+LUqnN+mr8vxfVBkopXXgvQmZNiQFyQCxq93Aktg8Kv91B+s1bYfZYHYY2cD0a76gau3QjUAFp1rJFeIR0PkOJCe2d6qkEnD9XlQEU5jdkm9lbrKK3LqCaPpie6AiIWKlKo3A4QPtDKnNMzj14dqPOxCH7Tz6QMGpcDIyefPUGC6HkDU0VLm770/pO1z8f0971C1s6gqKwEzkGnpbGO4QQB0gGwi83l8Y6zYxCQqQ9bRMsFf9dHcH8Tnc0qrv2nv/pDInr+AJeQwbg/Qx9sfLr/EwH86c7v3PXxhBB/Apm++Fby/8sAXiCi7ATbBIfKU77+KXJ6gqIUZ3Kb1amWMoR6rrh607yx8rrHALmrd2cSTYm7NMhA2nbLITeT9e2BqroHPjK9b1TFXQYZSBgJLD0akLo5dIZEuFcyQssi8GfFeUAOZ6NmKWOQ+3X3Mey0he5RdSez31v9xVpufp8LtXsPhkBcvFHOLW6aaafVOkobAXrTIRafSWVYM4M5y2bjQue+dMir7um/cuFkpuh40DFZrhxuoUEGUF4pFQ4msLncvclIFsZIYOHERtp4MhIbjSNMmbNZQDrYY9WL2Z250JnP1f09fh/PQYO0DTKzPfw9fyCDDAC1B3YQXy7Oex8Y7wz74g8AfBQAhBAPAygDcFeyExwqowzAOcWZel6m+so5TVGOQJpnPPlTKzhxalUZKZualnlvyxsRZOpu6NVrOzRnWhgAKemZGGcuIrGRq880UZlsy86p5IbgoszYhSCXXpWBowLNBaeidl69EMPGh2+GPG+sOtVS7IRBtKtdo52ArFFqb9SwczZEY7StNgTd0LlG2PsjPSenW++QnHpZHp9rDjpF0WAH5IgGMWwDYhcdi5p9gm3f2ZXmgh722+c0+exq4XH0Bg02nlwYu311SnXziSA2Gkd4I9ILo3Z+l9N9djGb87leLVSpkUjjYfP7DOKZM0WxtJv9rJzGv+Nhb7WeLyt6VyBQFA30c4/4bQAPCCHOAfgygM9Rn/TEoTDKNqfzIHlJ6voGC2P5+hSuX5ntqzlg58LU+wmz6EddD8dPruHq0lzmhjU8HofBZHWt5lpd5dr0GwKQ00HY01S82AE5mSISfceul8Y6Tm+kyAsWoUDgp09ob9QMZgAXAfXvafOZ0FmM5I43PQIqrwZS/yDZEPp1NUb7JdB6+tmzl63fwNxerHfYuUBJmkdNUk7+7Tf804YrzxmOR6CybOWu3E4nc7ueq/PeGy/LtcFDFu7cmMz1lO1Isnk6NDesWqQoldy8UsRNP/vwjdycrWuad9wK1Fp2Fb3H591TfVxoL4SZiTWuYp4/k99pedcgvCPSnUTUJaJfIqIniOg5Ivrzfq85FEbZ9tZs48c3v24EmAtsczP9fW8go7a5PIbpFxMtgj7ezY2rM6oa7Gp3BmBUvPk5enFtZnEL1eXAmFRh32Ds8HsWzzlPcnRk3l181HnSvZ2K09MtEoOngFQqgBGOpWL6nCPublcMWcfKU1uZ9+KONz0C0j8XF2o3A/j1niHWrqcb2NvnGzjY8ZVhKhpZBKSpFsW5Tv5dvzVeOKJIh9+Uxdc8rztqRDIlkniN4V5J5rF9chpAHtt16fKCitL0SeA67EhS9GQTkhpU2/GNDbd6K0DQyl/f5988jrmpHecmzUbdnl7jN/3cbk1XMdTFn2YUjcYC5MYwiKjTXeEnTbpTCPHJpIvlkhDiC32frxmSxqXAnDKRGGndWDMXuHNtVL3WqyY3QuyeZWdj/fmkSaCAosPsBC5eRCOxW/jdI1VhV0pe2tvuvjSD9kKI61dm1SLnG8w2zpwG4dzb7TsT8v0qkfE55U2qoK5vDPsUMD9fv+nnGnodergoopRbyu23v/DcjwwD231lIve97Jy3zfPVPcPeqKQeulIZLoRjsnnE1dSjvy971i4PECjWAjGel6RkOELTtUAYH336vBFdUJkg9vy+BVkjSkvWXGnTl52RPhnGc25xEyMLiRh/cj+Mz++CvNQ7bh8L0V4IjXOc/7a53m5dm85u0tripYqZm47qUeHwYsDkdO+vjxgb3iDqcOrYBYOC7wUEgGIa6Oedxo/lioUQPoD/HcCnAJwF8A+EEGfzz4LUoqpMtLH3UIj99ZG+RZUPnH0LUT1Sr43bqe4xG3ARZz1hl66x8fdNX3U4uboBXfze9kZNVftFKPDUI9cMEogxDsoyNr3JyDCiDDa61E3kMju+0ZhStLgvfu+UCiVbGzWUr2taCfUIq5tZj8YwVrZYjOa1cZHxj1562uDI8mfl+t5sb8dOu1CJ1PHzhnwy8miBnAfl725yYQdUSr1T9qzvW9jCzOJWrt6CC3nqcOXxDpqnQql210mjtD//0dnMdbjSNIPog/QmI7mBtz3DeK7cnMxszNt3RiFCkemyZJqfKMWKu57X2AQgw2BSuWmPVDs4v173pDlitNlI0X5JOS2V1ez60AvyBzHadw2inzhP+QMALhHRW0TUhUxwfyb32Sxj2fYMRgIvYr4h+Evlf/WxQQz2NPymj/pME+RJL0VvI9U9QDuXKEoxepOR6nB64IHbzpuXRWv4ptIr4hRQRgwcgpySobywz795XKUZ/H3P7O7qiowhp0qMuBqjeitwahfE1ViFkq5BAC6Pjb3X0qbvpBU+euamMjp83t3F1AP+6NPnUbseOI2PnULh0fbGNSVeUb+bsjcZZYWQSBZlRSftUuS8LV8rG+fl61NYuznhZEY0Lrq51nrzi77phOwQtAL5HR2wHTgajQq7A3mCjL/vgSqxYQCN9ImWstMlCRiiHMNv+qBeath1tTp4pETvVaOJ67RigaWlecx+10/rI6M91bTF9689pAKQOXcRCZWy0Ne4XpDPa2p6u/EOFfoOjB8LT1kI8e8B+CQR/ePk//8QwE8R0T/RnvN5ANwZ8wSAc2/7ibz7mEEf+ssRxHvxmoDhdR0lPEJE2VDvAEj4w+5+/izWiOiT93K8g+BtbCY34HIXDOufdMV8EQCEEC/eKxn8MOK9eF3vxWsChtd1lCCEePFe3+OdNLIHxY8rfXEDgK6sfRzArR/TsYYYYogh3jP4cRnlvwZwRghxWghRBvBZAF/r85ohhhhiiJ94/FjSF0QUCiH+CYA/BeAD+G0ieq3gJV8s+NtRxnvxut6L1wQMr+so4b14TQqHQpBoiCGGGGIIiUPR0TfEEEMMMYTE0CgPMcQQQxwivOtG+aDt2IcFQogTQoi/EEK8ngxE/JXk8SkhxDeEEBeTfye11/xacp1vCCE+8e6dfTGEEL4Q4mUhxB8m/38vXNOEEOL3hBAXku/sg++R6/ovk/V3Tgjxu0KI6lG8LiHEbwshVhI1NX7swNchhHifEOJvkr/9r/0E5Q8liOhd+4EsAl4G8ACkzuiPAJx9N8/pAOe+AOC55PdRAG9CtpT/cwBfSB7/AoD/Mfn9bHJ9FQCnk+v23+3ryLm2/wrA/wvgD5P/vxeu6UsA/nHyexnAxFG/LgCLAJYA1JL/fwXAf3wUrwvAzwJ4DsA57bEDXweAHwD4IGSvxNcBfOrdvraD/rzbnvLB2rEPEYhomYheSn7fBfA65E3yGUgDgOTfX0x+/wyALxNRh4iWAFyCvP5DBSHEcQC/AOBfag8f9Wsag7zpfwtQcopbOOLXlSAAUBNCBABGIPsBjtx1EdFfAbBVsg50HUKIBQBjRPRdkhb6/9Jec2TwbhvlRQDXtf/fSB47UhBCnALwLIDvA5gnomVAGm4ArLZ+VK71fwHwqwB0AYKjfk0PAFgF8DtJWuZfCiHqOOLXRUQ3IUfWXwOwDGCbiP4tjvh1aTjodSwmv9uPHym820a5bzv2YYcQogHgXwP4p0TkVs5Pnup47FBdqxDi7wJYIaIfDvoSx2OH6poSBJCh8f9BRM8CaEKGw3k4EteV5Fg/AxnCHwNQF0L8UtFLHI8duusaAHnX8Z64vnfbKB/pdmwhRAnSIP8rIvr95OE7SRiF5F8enXwUrvWnAXxaCHEFMpX0USHE/4OjfU2APM8bRPT95P+/B2mkj/p1/R0AS0S0SkQ9AL8P4EM4+tfFOOh13Eh+tx8/Uni3jfKRbcdOqrq/BeB1IvoX2p++BuBzye+fA/BV7fHPCiEqQojTAM5AFiUODYjo14joOBGdgvwu/pyIfglH+JoAgIhuA7guhHgkeehjAM7jiF8XZNriBSHESLIePwZZ2zjq18U40HUkKY5dIcQLyefxH2mvOTp4tyuNAH4ekrlwGcCvv9vnc4Dz/hnI0OhVAK8kPz8PYBrANwFcTP6d0l7z68l1voFDXhUG8BGk7Isjf00AngHwYvJ9/QGAyffIdf0PAC5ASt/+35CMhCN3XQB+FzIv3oP0eP/R3VwHgOeTz+IygP8NSdfyUfoZtlkPMcQQQxwivNvpiyGGGGKIITQMjfIQQwwxxCHC0CgPMcQQQxwiDI3yEEMMMcQhwtAoDzHEEEMcIgyN8hBDDDHEIcLQKA8xxBBDHCL8/209YnHlHrbAAAAAAElFTkSuQmCC\n",
"text/plain": [
"<Figure size 432x288 with 2 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.pcolormesh(B)\n",
"plt.colorbar()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d91869c2-099a-4612-bd52-ab86fce981e0",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"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": "3.8.8"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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