870 lines (869 with data), 371.5 kB

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://www.kaggle.com/datasets/adarshsng/heart-mri-image-dataset-left-atrial-segmentation\n",
    "\n",
    "import nibabel as nib\n",
    "import matplotlib.pyplot as plt\n",
    "from pathlib import Path\n",
    "import pandas as pd \n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Conv2D, MaxPooling2D, UpSampling2D, Concatenate, Input\n",
    "from tensorflow.keras.models import Model\n",
    "import tensorflow.keras.backend as K\n",
    "from tensorflow.keras.callbacks import ModelCheckpoint\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Inspect the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "Example_train_nii_path='imagesTr/la_011.nii'\n",
    "Example_label_nii_path='labelsTr/la_011.nii'\n",
    "Example_train_nii = nib.load(Example_train_nii_path)\n",
    "Example_label_nii = nib.load(Example_label_nii_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(320, 320, 120)\n"
     ]
    }
   ],
   "source": [
    "print(Example_train_nii.shape)  #shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = Example_train_nii.get_fdata()\n",
    "b = Example_label_nii.get_fdata()\n",
    "max_area = 0\n",
    "selected = 0\n",
    "for j in range(a.shape[2]):\n",
    "    temp = np.sum(b[:,:,j])\n",
    "    if temp>max_area:\n",
    "        max_area = temp\n",
    "        selected = j"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1d5431afd00>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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3kSOKus/z2OuM/NOc1KC5IkrCcDkHcnZ2Vrne39XNEd/hjIaHh0sEgMOjr4OiN/fxKmOoe35dFOF/40jqooZclIMx97lydf3MkeMg2ajru59X17IztfPM0ar7mftWR0Fm51XnpHLLoDB/VycjfJafl6+te1a+7yBH599d9v3Tntm0P3v7ojupV199Nb7ne74n1tfXY3l5Ob75m785fvu3fzuWl5cjIuLf/Jt/E+12O97//vfH8fFxvPe9741//+///Re7G6VdFk3kyGiQURsk6E8T3PysOoORHUd2KpcpXp3DqYtCXJBQ54wvQ+OXKeOg/riE2XklGz8bRRwQ/cfgDw0NRat1kTs5PT0tczE0NFQc1NnZWbRarQrS5/51+Smemak77mGnR19xulyb5YZnDzoAl88x4h5/pgvzul1m6LMcvxbjWDdXWd5yPzx3g/qYHXtei0FRkh1ebpl2z07mMgdWBzCu0vJ9830uK7ap09vL7MAXKwJ7vbZW7xrOws7OTszOzj71dxl9YuDqlMJGIAumjdRVnpmfbWXJ9ArKmyu+BjkVK0tWpLpcTnZYeT4i4gmDHRGFkhsUTbrlfmcj5d+dn5+XP3kMvv/w8HDJVZ2fn8fR0VGcn5/H2NhYjIyMRLfbjdPT04rBfJqTGlSFRyXh6elpnJ2dlXXCwVpWsvFl3XJpfN1z+D30pnNzud/c1wUhee0cSdRFIYMctJtlra5ApM5YZ0q37r5182QZHiRDdU7FcliX8/T1g+6br4t4ktrMQBGnmseawWeez0Fj5PP8m3zva2iS/1xte3s7ZmZmBn7/uj+7z/kVkvQR/dMmsoHIRrUOvfF7/9/XDGqXOQtTJRF9g8bnuWUDnB2Sn1mnnFbaHAG0Wq04Ozsr0QvXZKOeW3ZKdYbB/bTx6vUuqECiqJGRkRgZGSnGvN1ux9nZWcX5DA0NVQxhXrv8d6a07Izcp5yTs8PAYDmfll8H4TmvK9RhrPy7Ts7yOBxt2qnYAeaW5azOkGfnc5k82dkzJ75PvhfNc5yfW/f/LHMuXMkyRR9x9lk/uQ+6nsFJ7kMdCLjM8dSBxIh4gtbOzqdOLwc946u9vW6dlA2gjU2d0c9oygbPRmkQ8vE98n35nHvUGVSMMgbZ965DoDbwVnyutcLmvAefESn5WTzP/aT/nrds2K3YdYbZ/7dzHRoaqjgOnBTRhiPbTqdTvnd/65w+c5GLXTIVijxk6rFufdvtdqEYPSc4NZec18kP4+D/uShnEFXoecwGNoORQc3zWFfuzd91OuDxP83hed6zw6hbo7o2CFQMioj4DWtTFx0BLuwo6pgRj8cOx8/0PLhfeXwGO3Vr+jSw+1ra6z36et07KYydk8SDEFddSJ+dT50juoriZQfD5+12u5TYc8YhdFimetzvrIx2PDa0Vq4ceWUnzr9dbee5yGPBcdUZMDvAPLfut6MUn/Hoe2TjWof6bfiz43TUQ79xknaUNBuwvL45asrNjoq1zOuUcy8eZ56znAujZeM2qE+5/xhP38NtkJPi2kFOlGtZt0HzVBfx0eoKIOrkuM4g54jKepYjGQODPBc5kspgw99xrzwn1i2vX57vOsf1Z3E2r2cHFfE6dVI5D2PU6Sgjo/zLEJ8Rkz/z37nVGRVfD/2IgyL/gsOB3hoeHn4CueWqKq4xRWJjkyNL+lKXtzAF57nJSDYbSK6jT3UtRxI5cuSz7NQwPDiVPA/OUQFOyGkNDQ2VOX6a0b3MYdV9XoeE8z2JsrJTzhFObnXOvu43dRGG+5Wdbi5UqTOwvkddG0Qv8rejyzwH7guN77MjqRtH3T2QDTsjRzVZnpwbrYuE/JnnmPvWMSt5XS3Pl8nYVexHnuPXu2Nye906qYgnK7HqjGw2uBagHL1wz9wy+qozFnXGECeFwJO4Pz09jdPT0wpFYcOc+5vpzExr5SjKTtuf1xm0uvH7+TlKGKSA2bBkhJmj3byOjG9sbCyGh4ej1+uVubKh4XrmAgc1PDwcIyMjTziFvFbZyIDOc8vjHARqBv02A4ZBTsoUcJ2Rz+MwYIh4MkpzFOF+18lGXX/qIoe65vXk/5m6zs4yP8dzYlBTF70ZcGVglftsapY193rXRa1ZFut+X+e0PJ4MHOvymIPyuNnu1H32em2vOyeVhdEKmQU2G+dswIwIryoUWXCzQPuPhZXIyVSJ++GNknyWKU0beyO9ywxKNgTZiQ/KL9A8TvfL9/PnfJc5e48jR2bcp9PpxPj4eIyOjkav14uTk5PodDpxcnJS+kJEOjw8XOi8PC8811FdRtuDIqocdeSWDWw2vnURxaCW5cX3y5SWn+F749Ad9Q6K0DJVmR2nr8v723ju+fl5bUFCRJT1IH/kDdxZvur6iI7UgaSsF/w7G3vG6Xkd5Cx8/0FOMP+eazL4qXNUnpvcx9zsjOuuez23152TghrLyggitbBFVI1sPngzG5ws0HyWlWEQjZQpAvb/5D0/rkKk7+RTjM4zvZYdQEQ8oeh1ie2sVNyD3z/NAOS5HOTgGMfIyMgTzsj0nO/puep0OjEyMlKq+nLLzohroU3zGvsaf2YqlXtcll8ZFAXVASF+7xxKnfPKzvCyXI77cpmR81zivPjMv7Mxz2vs9RkUdeTPrIOm5FwBl59tYOZtI+iJ5SpX9uV75f7k+fJ3diaWZa9Nt9svxHB/LffZbvh3GXgMmoPc96sAm9dje105qSyU2RBHRKmiy5+DwFutVkUJBimyWzbuGNKIvlNg38/p6WmcnJwURHh2dlYcEoba5dd1xoHW7Xbj6OioRBJWojx+vq9zvJ4zO7xBkZ/nJUcK3LPO6Dryc5EETsVHJEX081fn5+fl9ycnJ5WXVZKzw6jktQGYYFjcF0dV/HsQCq5rRttZHoj8DBKyPLlAJtOMLu64yjMdueUoIKIvP3VybBnIkXCOPvKbAfI966Iv1ibnR+uKawwU6Her1Spnd5pxoKGv3n+XW557y/sgh8baO5eJzmZHbvnBhnieMtVXt1Z8Zoalrs9Pi6LqIsjrHHm9rpxURvAR1b0WIPW65LWjFW+0xIgMeo9RjpaIFIz+IqLkQ9h7ZKPi6j73wfTIyclJMVqjo6PR6XTi6OgoDg4O4vDwsJIPMvpztGXjl/NUWTlzhJgVGUeRqauci2AsdfM0iLrwGuZ8E1GnqzZZ27px5DWi1UU/+bd1yu2x2anVRT7Z2Hnd/X/vmfL1jClH4IOKECxv1gE78EEAI89XHneOBgbNWV3ENzw8XMkD2WA7msqRN+NCjk0PG8wMDQ0V55W3cUREiaTzHNaNzS0f6YXc05+6NYmICvCwruU1qwNHGRRmJ2WgldsgR3SdHVTE68hJYYAxbJkes2Bn6i8iKnkdrnURQ11k4me7IaA4LIzN0dFRQVhETDgoIieMME6J/UFHR0fRarXK607GxsYq9+eeeT9TLrFGWeys6gynWx3dUIcSrZB+nq/LOQ3Tjxhsb5DNz3Zk4SgBQ1K3zylTl3VOrC7q9HrWjYXfGRTUXc//Pd82uH6Oo2CAQI6m+O1lz6tzFnVjz20Q0r9Kq3vmICbAgI7xePz5kGJaHd3Ob+qcbs6RcU8XJWW5dkRZt475cwMCR1UGhXWRZ47i+M4RrJ/rvmZwWQdCXi/tdeOk7ETyJlcUnWR6Hf2AIcjRhmmZjCZzRGK048il3W6X/FNEFKfk3MzR0VHFOJk6yBw4SkeOZnJysiDvXGadczB5jMzdIMpmkOF2y05qUIQEBeZ7ZcNi9Ojvc96ort8RUUuz1EUx2XgapboPngs7K/525JIdUZ6funFFRMmxZXrHDrYugjPtyW8yQKiLiPg739PXu79Py4dFxBPyVNcsu7nVUX84qpxvzWPJFGSW/7xpnb+v4qjzlhX3gd9kmvj8/DxGRkaKjckyWOeEDNosq3URrNcuy/Xrsb1unJSRhg2zEZuT7g7Zoda4nhwHSMw5n7p8jcN8Cy5RkftGbopnnJ+fx/Hxca0iRcQTfYIiOTo6Kg53YmLiieio7l6+X9380RyF1tF9g1qdoRqEfPNnNkLZmFsh3fK9s3NF6d3yvesM66D7Mgc5iqmLNnBUdai7bvx53TyGQXOQ16fOsOVr6ua/rk85or7sHnU01mUGs64PyA5OrI4CQ0fy3qZMkz1N5nLk4d/lCO/k5KTkkHNk7wi9jvrNkVIGm+5LpvXq5tzA+bL59v+fthbXob0unJQXPdMVCBzRC8KOUed35pidnzo9PX0iUsj0gYU3R1ZQhTnnFdGnE09OTioOtY67N23nPAaOtw4VD2qOGCzE+TrGdhUkze993VVbHQK2wc39oQ3q12XO1LLBnzrnlltO5LuZ3qmLmnLf6ygm+maHlCM399/3u2zt6+bMRrNujPy7ztHXUWB5TJcZxTpD7rFxf/SxLhLMa2bd5LvszJ9GaTNv2AuA38nJSRwfH8fx8XHJezEP2Un5uWZm6iIh/nZ05fFkx5ud3WXtaU7surXXhZOy4uSQ2BVzw8PDlcoc/86C4NMfbJQyAsrCicMwhUT4j/Dzf5AZFBhl546Y6v6AxgaVluc5GWSwBzkSc/U2Utkx16G8qzimbIB9j7r75zXI4+NanHy+b53BHxS5uB+D+uk58fW5NDs/qw4d57FmsFC3fhkQ5WfW9XnQGOuaZTo/I9/bn2WKNDuzQZG1n1E39qdF7zQzJLn/dlB1+xBNdWabAbgdHh4ulbTIJP3ONoW5yc7CtB9jzFQh1+aCJ/qfx+e5ze0qoOE6tNeFk3IYXEfF4QRoRCKOqFhQn9qQz/3j2B2H3Dgf04ART0Z0OCCcE4LItShGRs2DjLOjQMbkdhnyt1HMtEXdverQc+5bHeXDMxyRZVSXlZPnO9q7ShsUmWRl9ryYPrpqc4RXF4HVOW+uy1GEI7A6hJ/pSEftAIc6+ajrb3YgdQ7d11wmA7mPdRGPqz8vc5p1DsoMQl2/6s46ZK7RwwwictRyWbl6RL8ikGPLer1eZY8W9iHrEmPKeSyvXwbS2C3LEM8mogTY5mPFmJcMhvK4+TftOjmua++kRkdHywLbyNqJ2EhCwUGxUbzgYgQUpdPpxOjoaLRarZiYmCj39c53C0euXMu0Hd9F9Pdl2THVRRNZkazAdQ5qkFH3bzPKq6NOaHWGMEcb+bqsnBm50phPz1tOrNdFXHVRmxFmjpoypdJu91/7UfcMN/qXKbk6+qUOVHjPV/7c5cRcVxch5/4Mog09F3zP30+jv3xdfm5dVJcjSt/f85ydb53jqZPZOrnzmPL/B0VqmQXJFF3dfdFxip34f51hN2B0+Xsd4GOsfgUO11tOiNSwbd1ut5K3trxFVDc7ey3rgIVtVl17Fp3XtXdSFjonVLOB4jcg0PHx8Wi1WiWsp+zZwgOK4hknJyext7cXBwcHFTRWR48g2AgLu/ztBLORHGR0PNY64+iWqZY6lDuIehqEyi/7XV0f6qKCus/q+mfFy+O6bGx1AIXfEDmbamF8lpEMCvidUXcd8MiRoj/zODyGunnOn9X9zo44V0piqDKTYLlmPBntZ4dTt+aZOvN1dZuF69a/DtXXAY4cmeS+eMx+Ro7csk45yvJ985iZm6Ojo4jovx/Km/4dCXuO8jzwf8uIwaIbsgpItqzm+2Y60OPJaYoM4K5TdHXtnVQ+hNWt3b7YKDs+Ph5jY2Nlgebn58vbXfkdjuT4+Dgi+mXrdmAkUQ8PD8txRjY8KFfekW7Fz6ct+Nq6UyVolzmvy5qNt51iHc2SURaf58gk3ztHTXXNCjno95mmyU6iruDjaVSSqTQj0fwM+uPf5VeHeMwRTx7UW2ccMUY+PaOuj8yR7839eE4GRQAl+sm96pxQbl47Pyc7+Rx95Hv4mYNaXTRlI3lVYFY3jrzZti6yGzQG65xBbkS18MHnDNZF+vnZ+fvcBzv4rE/5qKgMMGznMliFIszyxN8Uatmxcs9nuV1rJzUxMVFCXVNgnMqAcxodHY3z8/PY29uLmZmZuHXrVgwNDVU217Zarco5ejQE5/j4OHZ2dmJnZyeOj49r6RAE1cKRDZ+jPKPyQfTGn6UNMtyZenD/L7tXHR3pZvowU4B198sGn/9jDOgTv2X+M83BtXyenUp+vtc1z3ueg2xI7DSQMXKWlplMC9oZ2nnk/rpl58d9cVBQ1QAprsl0Zo5cPM46J5/7l+fDzeAnO5GnOZ3LPq+j67I+0Z/LqM5BEYOBEIURnU6npACwARFRyUlbbusiLm8/cb/8b+Y32yvfi/vXsQS2Hfl3zAfpA4MN26e6fJ5bnq9nwYFdaye1tLRUKTwgPB4bG4vJyckYGxsrAri7uxuHh4cxPz8fy8vLcXp6Gq1WK46Pj8tC5NMKer1e2SOxt7cXm5ubxVg61B60oPk7f29j8TQnNSjiyPeKuFr1lPs6SKHq+jnoN1f53veqQ4fZGToq5RUmGWXme0OTGN3msVvxiXQwRi5+QRayouMYvJfGv81RSN3YfZ+6tfRvM7Bw8pxrXRbtiCs72kyjef7r5ig7skGOYRA96OZxZJnzmAdFTIP6mx2rQcEgx0LrdPqvfrHs2CnkfVtmbhzhGpDaaWcQ5RNV7DjrmJfc70Egw/0xRci1npMczXGvQczEVdbjS92utZO6c+dOzMzMlJMWWKBOpxMTExPR6XTi+Pg4tra2Cm8+OTkZnU6noCa/kpzy0oiLRWRvxMHBQezs7MT+/n5B0XZQecH5OxtiWlbSbNSehhLrWp0xzsiL39UJ4qCWKYyroGX3x4jbxg7j4v7m/Wum+eocm59l6gNls6PyZ76ee9tp8P3JyUkZPwbJDgrH6A3fEU8e5ppzGDyvLoqz4+L5zJtf5cL9baTyutZRbDlCyw4yo/dMt2WHfdk96tYqR12OCI30666tGxNryL3rKLe68+5yVBwRpQI3yxp2hUjfx1UZ3OQCmwy+MhgY9J2jYjs+7+XMwDgzGYOASN4e4+vy3D8LDirimjupl156KRYWFp5AT6btjo+PS7EDC7G1tRUHBwext7dXqdoxjUJlz8HBQezu7sbe3l4F9WUHlR3LZeG0BdToLAuYDUmmskxbDELsbtnIZEUf1OqMX0T96RJ1SsjnHnfd3NhB5Vdx8KwcSXk8HodRsZ/v8TLvpndM65Gj4AxFzlikf9yH0z9suJgX3nfljdym4RwFGEETHdlJ8bkrIT3muv1keV48b3UnnGQDn6MKfue9gLllWUE+68BRjvL4rI4SHtQsnz5aqM5RZR06Pj6Og4ODIle5bD5HxURCpor5LIOQOtrRIMf7JOvmuu6MSu6T55XreYblhf9zH66zXJkO9H0GMURf7natndTS0lJ5/QUKfHp6WskdHR0dxd7eXpycnMTIyEhsbm5GRFQ25kVUHQMG8fT0NI6Pj4uxGFRxVqfIgxbY19hRGGFnFJQVPCt2NiymfeoUNhuvQdFRRmn+3EYOw3uVwgZ/lvlxFB9HUZezuYzyy8/JlZc4ITsMR9LZOfm1IF4f/5b+2AAx9wYdnj+vS7vdrkRs3CMb3+xI/cqZbAgHUUZ5DXMElPvKXNjA+hBj3z+DnjpdoE91Ru8yZzQIUNXJluc460lupAHynkP/O4NAgz3WOs+Hx27d5XNk3E7Bb5jmOvqQ0xmWHTsh66lpYdbMwDrToXU0YB5zXftyOLJr7aRefvnlCuJksYl8aEa9u7u7lXc6RVSFIKLP/ZteqUMWdTQGrY7+83dGxZmG4c9lilsXzbnlqCZXDhqBDbrHIGoIB8DfGRVmpJ1RsY2flaTX65X1zGPg/74mz7kV2JV8GCzOb/T7viw/jqBzybGdmx1yPu7KaNXNaJ25ohLr/Pw8jo6Oot1ul2IfxkfU5n4ODw+X0/CRVQOEOieMTJlO5Nle7wx+soE1AGEu0L28380GlDaIRsyFJ1l26gBU/iyDvhxt8B33o88nJyeV6Cg7KD8nv10h2wD+NmXtz7Pe5fwU9/Q68ly/usdj9vp7z5QPH/DLYA24HDnhzKybdmRfqYjqWjupT3/6009U46GYp6enBXGSP4iIIpRU9vkVHTn8tkHJ+w6sYFnABjmv7OjqIrC663xvvjNdaENg4YqoVzTGV/d7Wja0NkSOUlwa7j7knFN+lnMred4YG8/MhjAjzpxL8HU5SiN/iUz0er3K+4gi6qu6qBjFSNjR1kW6eZuB+4UBGh8fr1zb6XRiamoqpqamotfrxeHhYem37zM2NlYcGTLsTaB1+R0bp4yaWWcXAjBvGNEsNx4rYyA6GCRr+bO6jc6WuxxV1EUMuWV2oe632eHaWHtOPCZfy9+DjHd25JmliYjKfe2QmH87elN3eR68FcYRsMfJ+aN+kWod2MtO1HNXp1N1Y/9StGvtpMgzsYgZVbh5cW0kvRA2rqZ+er3+6wKy4A1aJN+3LgKz8UVgLYw5x2CjY6eaha1uvHXOzo5pUCRWh4LzHOY+eZzZsbkvnsv8XIMO99XPNGo39TIIJNQpIt9ndBzRj6DIW0RcnG4Cvby3t1f21DG+brdbDjHOFBMy5HuT44roHxQ8OTkZ4+PjcXR0FIeHhxUqNc8hhszAwXJnZEyESNSQaat8tmSOigZF2Z7Ty2SRZpmqy6N5HRwNWVbzfTNAqAONXhM+c6TFZ1meDbb8jDqd8RjtpLjfIHreDEREvUw7d87vrIsGMvwf4EZU1Wq1isxlIJvXr46atb38ckZV19pJmaONqE5iXfTAb/hT56Bs+I1Q6oxO3b9pOWq6DIVk5IPyWuGzsNRFUZlCqWtWioy2LxtTdlhZoXOOy1Sm6YW6A3iZX6IA01A2goNePsnzXHVpOXD/ub4uF2m6jogrIsoJI3yOXFBUkefReTXuzfi5v8eLg/I5kPQ5U6k2WNBKPKvValVybN7HRaWq5Ye+5lNXvKYZKGUqy83rlnNTdmo5iq47xT+3ujn2OHhmXdRU9x19cK6mbjx2kPk5nqvL+pq/c1+ys+90OpWI3vKVI3Rf67VFxgxOoLB96o1zcXld8rpZVwcBFn73xW7X2kmZX3eFjSczOyXnmiL6k58dlA1ZFkqu8/URT+afspE0OslUge/vMleeP4gyoWVFqWuuLDMazA6Qv+uUMxsF/8ZVeJ7zPK82YNwHp2DaIyNgxuC+1OUbBoEBqDErle+PA+JzjAYKfHp6Wii/kZGRODw8rCTo7WzzehhA5NJzR+518841yCkyzMZNgxXkFufl/tvAOUfFmHiG9/N4TeykckGJZQbjf9nev9zqmAmvr/V0UM4sN8tPNrj5N/k6Rye5ZeeYr627p5/barXK27qZR5yXddPUXF6DPD4ARrfbrQCp09PT8kJVZNhymufCYCrrYJ29qBvfF7tdayeVoyUUKCu8qSJQBcJh9JCpCDsNWp1Dysg9L1Z2aIMclRuIqo5izM7BCjMIwWUDeBlytWPhmTasXFv32pNc6cS1oDrTFh7X0NBQ2XxtytXOqNVqlWQwY8iJbht898sG3kUk3Dc7RwANxooqUYz61NRUdLvdQgViKOwEkS+eQV+NpNkmAXXI/EAHct92u1o8YYrRAMBI2s4VWRobG6vMVz45g/46uqujqtx/61cdLef/Z9rSTsiymPtGnpnfDjo9xM/DWfOsrLN1IIyxXAb6DAoydVzn8PK4PH/+f3ZSvpcpvvy5gUuOfpH3brdb6OOsy5anujHQz8vs1iA26YvhuK61k/KEIYwOe4mwIvobQ6nqw8C6WqaOBstcr1t2Tpfx8vke/k3+w/cWJCtg7kdGska8KKNLUvMYcuWfFQSE7bGAwHCkRu4ZfTvSJc8CTZZLa3l2zoMwLxRIZFoCB8d5jCgl43JC3330nFpxLSM0qkZHR0djYmIiJicnK29wBhkz1hytWkZsJE9OTmJ/f7+gXQzxxMREjI+PV07CjqjKNydj+3vGhVwfHR2VIqFOp3/CQl57U4vuq53qIOfA9a1WqxSkDKKAHWnZqWcAxR/e5WQnDdDk9Jdut1upkrNxdKRrmTegHQTsrAsGXzn3Zzm3TJmt8XO9jlxr2jZHY+gE0Vaeo16vV7bbYNcM+ByF5203BhdeZ55bZy8cvQ9yQleNoK/SrrWTGlQgYWqAP0aVmd7KkRTfG704arDwZId0GXKwgGdjkJ0ULVMOGYlZWDJnz/1yDsCC6Pt7fBiyTPf4GdzfO+/tdGzAMMIYQj/fNKGfaSPPb0dHR4tx9zqhlDwnUyARUan0zHkVOy1kCEeFYmMoe72LvSfT09MFxUKRHR0dlfwPBjaiHyF5HakyZWzIJ9snJicnY2hoqDgaxtZqtcr+vYmJiUr1qufU0Stl/d1ut8xVpnMsA/wWdM4YKLxwboOxdzoX1Ymc6sI6Ef3i/Jl/KF7m1fk0ns/zxsbGYnp6unx2dHQUBwcHlXyh6cAM5EwTWs/sON3q9Ck7IHQvR5lcn+lIF18BRvjMfSKqtaNiznge82fnZRnz79iu0Gq1Ym9vr8IkZYp2eHi4wjrYMdLqGJ1st75YUVTENXdSdR7fIXs+TcC/NdKiXJ3vbTgxVhkN+T6ZShjUMkoycjFao1l4s8CazuFzR0QuQvC8MMZc9us5NaJlHvN3NEdM9MlCH9HfFgCqGx8fr4zZtJ3XzuNiPRxJ1SW67QgZFyc/2HGaNqRk27QZ6+1+4/SOjo7KCRSTk5Oxt7dXUKwN8cjISIyNjcXR0VEt6sTp4JRxChzFxfzt7u7G/v5+cQQYEhc6cC0VfIzJc2tnZafs+2DMPRd2UpkGdsQFAJycnIyJiYk4P7841Hlvb6/cZ1BOsS76Yq6Pjo7i9PS04vwYG4dH2xZY5y9jIAbJtO+T+1cHJDM9mGXbtgnw4DHQ7Pjq+sRcA9aIMG3D6tYr4iLfOjc3F6Ojo3F4eFhAjovDaC5kcYRVJ8N14LwOzP952rV2Uub7WUDTfKA4hMHhsScc42ZqLSNgI4ZMi/nPZZx8jgr8Gwty/kPLkYqNhemqrEiMxQgp03f8H+Ofoy8afaqjAZkvogMOYAX5np6elv1B2Tk78vFGa57jajvuw7qwEXZiYqIorV8S57lz1ElElHMyOeKBZvTzeSbz7XwRJ+/jjB2RmGayDHm9+Y7CjIODgydescAJ3kNDQyXn5JPi870ALKb3rAsGdabs+K3vGRFPIH3mnL5G9PWK+3q+GHvebAx1x3N4Nc7R0VHs7u5WdNxjo3+W2fw8xuLfOELKhrYuxwUwdMs0me9t22G9zaDRIME0YZ1DRB9GR0cr10O3miWwvrPFgW0Uh4eHsb+/H8fHx2Wu7OANXnJfMvitA+tNJBX9fRY56nHJpRXbjqIOeUX0jZk3RGZaLyOF7KjqnE+d0+Jvo62IJ8uheUZOzPNb0245aQqix4H61Hc7ZfrNeE2D5IjRCW36xtyDfB0dcMRQt9stBt9OOkdSGU0y5kwDOnrICf+Dg4OKsyQCY1x21GyMzeAFx2kjCBLmvD7QrCviRkZGygHHu7u75Xw438sGjHXi/vzGxQJ8NjR0cTTR1NRUjI2NVXJajIk+0pi7sbGxCq1qhEyOh77lSCmi79jqnDkRJy8G5RroT5B+dn52gH6uczQ4KSJS60+n0ylrnqMw07d+JvLM+Ou+yzrG95YTg2M+d7/skDzf3Mt2ibmoY354RpZLA2mvmyOsiCiOit+MjY2V64eHh4sss35s/rVO5q0Q2Q5mYPzFclAR19xJUYYbEU8YLSKoHHlEPJlMNUpySF2X+HS7jNqrawhcFvI6molmFJbv5VA9K1UWKIyoFdP7cuykeG5Gddko5f5AVWEQyad4DKbWbFh6vV4lz2RlZk0dPZlChO4guhgbGyt5IRwJL730ddBPRtZ53vwSOa/D0dFR7O/vx8jISIyPj1eADdeSX/Lp+awPv7GD5/PR0dHiPEDHXmNeRTMyMlJ5EWev1yvXei0xSHxHhJZzV/zWRseygUywfi7GsXPc2dkpdC1rhwMclOPMc2Onbefj6+xs6n4DeEHOPA63umIHWo78/Hf+vs5w50iOa9DHiGrhU6ZSafnepn39HHTahSS2L/zO1Zvj4+NxcnJS5AIWgrlFv7J9ynKc5z+PIc/dVdu1d1LOyWCAmFCjBQy3z7PKPDKL4vDfgsMED+Kw/XddyxFdRBXNYgQuc37uQ86V5TxURBQ6iHu7VNW0HffMqNDPwzCZz/Yc4XimpqZifHy8QiNYKTL9w9qZJjLdcnZ2Fvv7+8Up++V0Bh6Hh4cxPT1d6MShoaFysPDIyEgBL14LxmOwQ3PxCWvlZ+3v78fQ0FAsLi4Wo+OqQPp9dHRUqM9sdDNY8tr4944ycs7AemCAZcOFbJgCotLPNKb/b7myc8/97fV6lfvv7OyUaIqIsY5dyJRhjixzVEseptfrlegMg5t1OTMCdY7M62zg6H9bJ54GUu0ssqP3ejGHfm5OP5gONBXM93lO6xgAnsEfv07GLAXAzlEyumInlcftaJT19BrYqXps2Z4+rV1rJ+UEMajN0QXoESF2lBDxpNOwwWBhyI/YaNdRf3XfD2r5ekcNCLAXMiuL78OYzCnboLk/zjMRWfowVf/eim3E7YiJfrm4YGJiImZnZ6Pb7ZbT51utVsnTQAlmJMk852iEPkH5YDANHkx7UFU3Pj4ek5OTpeSdiAOjxnyAHE3vYtgz3878c7+Dg4Py3dDQUElIt1qtmJiYKMfS+FrW22BhbGyszCuvh7HTd9k4a3N4ePgExchzWCdvB/AzQcyTk5PlGKbT09MS8XU6nYpcZJn3GjGPrVarYtyg2yge8WZt5tWJfvqIAwVkQkFBFS8sLBQZALjwOwMEzxU6kil0IukcPSGTNDuJbFy9vvyxLanL3ZqWdS7K97UTq4vKmBf6gPxE9EEM800eCloPXcPxIIO+l/UmR7uZFmU9c8TJOAZFVVdt19pJkRswVWI0gZNirwkCiZDkSbWikLA+PDwsVJN/G/FkGbg/y82/ZWHrSq0x+lyT/zA2mpEb90O4bTT8e5f9QsPQshMiArIROj8/j5mZmZifn49er1fyP+32RfHC6elpPH78OLa3t0s1n50ARpU+2GBH9CNkR3k4WKIi6MFMiWHgJiYmyt6pjY2N2N/fj9PT01KyHRGFErZSorBEBq6Wq5MvckIYTt+TcmznrYgC7FC5N3LASzbPzs7K9TT2w4B+I6Kcx5apWa+1n2tkPD09HTdu3IhOpxMbGxuxs7NTUDfrajCQjZIdxMHBQSXnGdHfNsDp7paDHNWzdq5AZD6Oj4/LuuPUe71eyTtGVB1LruozoMv5QNbBUVRu+XProKPYHOU4mvI9MvDJBR3ZNjki47fQ446QAIHWH4AOlabtdrts7KXgB7ZjYmKijA+dR8awo167zCAxJo91EGNVl96oa9feSSF8CDoDrzPe7XY7jo+Pn0jgGhVgpMk5nJ+fFy7fPDhRBP1w5OFn10UFDsOzUDvJaWeWKQc/A0HEGEZUqxIztedx5gIJ/990GwqNQN+4cSNu374dIyMjsbe3F7u7u8UIrq+vx+PHjyMiypuTMTYnJyeVPI/75eiV75gnSo0nJiYqeQ2iApQI1G6wMDY2FsvLy5WKT+YNB4DCe/0intwozXUoNMbXjjij1JGRkbIeh4eHTxjBuiiZtbdxwHnlYgr6ZEOJcQFs2CiTuyPSIwomN2Hay1GNX/cQUT0I1WvJbwEKdvp29qaTbDDpA/eHpkfO0AeiTr8ckjXlWiJNryVzBsjl/qZ3kbtBFCH3yLSWnS3GGr32WmX2JhvtbLzRTVP6dmzMOXKWWRPWgd+4kAI5Yf2mpqYqe/wODg6KvAPwTPtDE1vnnL+k/1dhmeratXZSNrQujsgLnRFQpivs9TGUh4eHRdGgP+ykbLwinnxleB0Hnq/DWPoa3wP0mlGZ722DOkhAEWCU0IlyIzNTH4wdQYXCwQBvbGzE/Px8TExMVCgBIgzmbWpqKoaHhyulxJ3OxaZbK47nHmrH/cZhcX/G6yIIToPg5Anot/Hx8XjhhRfi4OAgPv/5z8fW1lbp2+joaBwcHESr1SoOBxrG2xcyFRtxYRgmJibixo0bsbS0FNPT09HpXJycvrGxEQ8ePIidnZ1yPTQLkR9re3h4+ISMjI+Px8zMTKysrMTo6Gjs7e1VChIw7tlQuSwdA24aCic1PT0dQ0NDsb6+Htvb28XRtlqtQo2aOjNthhOzUTKYsgMnYvb4+YzkvnPJOCr6imPzdgZoSeYk9wcjTn+sV4OoPfKnGdj6Ho56aJlWz9Qbv7GeGlB7/ursRW4G4Ny7roQ+jxk2gHn3iRSMiXk3KMZW4Py5jgjObzc2sMv55Zx3ey0O61o7qYh4wik5euAzFsBImMm3h+e30EqgTZBeHRWQhfRp/6/7zsi1zml5HBhQLz73MFUYERUl829Ns2Q+nfuOjY3FxMREiWAwKFSUbWxsFPTNdeQfZmdnK3tuPFd2lOSrbBT8f6i9jOpRVCIU3wcji5E+Pz+PqampmJ6eriiFjRjz7ryZc2Sjo6MVGtSR0sjISCwsLMTKykrMzs6WPSijo6Oxs7MTa2trxRA4V4RDhFJ29IyTXl5ejueff76sLZuHofdwJK1Wq0SRLn2nr5YBGvQkLwEdGRmJpaWlGB8fj8PDw0qEYhl0sYMBjp1aHdq34WZ8ln+vjSvTHC1GRKEhI6JscOYasxM0QA66YRowo/tsRPm9afSss2ZMrMfWyZyvyY6FzwxI3dBNR2C+T2YlmA+DV9sXQJ7tCwDB+aexsbHK6RQ+Bgx9YW6hXe2okXXnkVlLr9HT2rV2UpmuA1lm58AEOcLw5zQEhAIANstZeHO0U/fvzDtHDK4Myg7L3/s3OF7+rouEPD6UwEqVoz+aaRh/5nwUDmpsbKwUG6yurpbPiLqsUDT2ZpiWtLFxXoL+2jjY0JnWwUl5XERrbGylxJ5cDhEXRhLwkfN0GGjyKc7lYJBxcKaY+Jt9TFQCOjIcGxuLubm5kluBVma9QK4UgJyenhbnPzc3F+Pj47Gzs1PyVkRPlKZHRHE+RJk0/u3kOQCDQoy9vb1S0u4I1jIKkgYAMif0xUjc10Ln+aWTzG3uB/01hW2wiZw6inMek/nMKN46aT0zTWoKH0BrZz8oKjLDwTw5Z2V95zocSKaZMxtiatTjNN2K47KTygUY/MZjgT4F8HE/WBE/xw7atKidk6N7Fyoxp3bsT2vX3kkhWEwQ/2ZC+T8KieFisREgIyDTPvzGyMVooQ5NGVW5n7Q65XCuyAIQ8eTpAFY2nmNFdITEPRlDVibQKobbhQo2IPSBecGQ4TC4F3QML6RkCwCHpS4sLMTi4mJsb2/HvXv3YmNjo7IOuV+mtbIjdzTl6IeclnNU9InIzHkQ5tqGu9frFScxNTVV6ErTUnZ+VNvRL58IcH5+HuPj4zE9PV2ODCJXRzTjJDR9I6Jhbubm5mJ2djYmJibis5/9bBkr1OHk5GRBvxgcnCjrh9PnfMCxsbFYWFiI5eXlmJiYiLW1tTg4OCjl9d74iUH2POPQMZzQhnmvF7LInFPhiXx7PSP60b6NNY7x/Py8UhTlXI0LkUyHOsqzrhn0EJECwiz3Zih8PWNwpV6WY/qeI7cMYK3zXOP72RnSL+fXWV+vl2na7Jzpt3N8djKAhro8tvuYx2NAj5PK9HkddTqoXWsnFREV4505eiYVgeWVCBMTExXDTXPlmSkCUw/c04LjxakrJc3NTsgKzD3sqCIGl8z7dxkVuX+OxDIdYlrNOaLDw8PY3NwsRgFEbMPFfXDqvV4vtre34/Hjx3F8fFyoqampqXJy+Bvf+MZ405veFDs7O/GHf/iH8ZnPfCY2NzcrxsR9ZbwR1aON/HlG5DiMsbGx8jp2ciHz8/NxcHAQ29vb5Uy5iYmJaLVaJQrr9XolOpyfn4/p6enY3NysODDm+OTkJHZ3d2NnZ6fM//j4eMUxHx8fx/T0dMlbQSsODQ2V6xm7ZWdvby8ePnxYPpuZmYm5ubly8GyOhAAaVLxadjHAOP2Dg4MYHR2Nubm5eOmll+INb3hDMcaf+tSn4uDgIMbHx8sfTqvgeUSUPk1jdnY2bt68WaI5Awb0CwdlmWZdcVCsPcdP4UTQbwpppqenIyIqG5nzKQw5b4n856pRqGv203FtHcXnPI712UyHbUNdFFrH4AyyE/mznMpAL3FMAEPGUAdMcz+84d3A3syIC9W8pugDDTrX/TLzYPvnyuNB7do7qdy8+K6CylVFNAvC+fl5iRT4bQ7NMSSu/LHTqBNIIxMrpQ29+290Qh9zdOaoKtMxdWiF32duHeEjeY+wUu7LKdMR/Q2VzCkl0JQhc5golAEIn+jTlYsTExOxvLxcCigODw9ja2ur4qh4pqkjj91UJ83zgMLOzs7G6OhoyVM9fPgwNjc3Y29vr0RMERenSJycnBTntrS0FEtLS9Fut2N1dbWU64PgaXt7e7G9vV0KKUzpzczMRETEwsJCLC0txcTERDEErdYFrz8zM1OZa2SVSklAEZWp09PTlXWx7ECnIQOmh4g4DKSYIyK8ubm5EiEOD1+8sZe9VEQyEVH2gyGf09PT8eKLL8bdu3fj/Pw8tra2Ynt7u+QH6ZcrRU0JGWjgfE3b8pucI3KexRWL1j1HQcw7ss+8tdvtAqScexzkZLjO9zNtnwFoZly43mtoB8jauN+ZyvcYiUKJ7gzm6q71XMMu5TwUfch9ItqkeaN+t9st0TXz4T7anrbb7coWgkHtdeOkHHKyAOxvsjCa3qvjjUlKmzpjoagA8nH2Fjh+b07efSHP4ErETBvmKAkhp+8oqg1/pgnd50xVghqZE3buR0SJmhBS7+eJiIphMFIl+U9/7Hz39vYqlNXGxkbcv3+/GMuhoaF47rnn4vz8PB4/fhxHR0extbVVKU5g7BgsU3R2Yqw/48RAdjqdmJubi3a7XQoC1tfXo9frFUPItZOTk7G4uBg3b96M5eXlUkjQ6XQKnTYxMVGicZL3GxsblcrI2dnZmJqaivn5+YiIyuZeaDzWAWcAJeL5Q+FPTk5ia2srHj9+HFNTU6VKknZ0dFQqCYk+MBoGJRglqOxHjx6VtWcdLFs823ukcK5TU1MRESVntri4GLdu3Yqtra149OhRrK2tleo7ohmAC+Ml7wfgyUUbyDbVaTjr8/PzQkmyYT+XQWO4ucbbG5h7/9/3mpycLLRuHZA0mGB8LlTKuk1/MkMC6M3Ojd/7d8ioT9gws4N+OjfF9XmLhWlg9N35JSIfUiQGFFzL/+kPFC82Ad2wLUNHkPurtNfspH7rt34rfuInfiI+8YlPxIMHD+JXfuVX4ju/8zvL971eL370R380/sN/+A+xtbUVf/Wv/tX4uZ/7ufiar/ma8puNjY344R/+4fjVX/3VaLfb8f73vz9++qd/ugj9VRuThzHOiTsrGlQfC+nfgjYpl66j3OwgMg1ogeH/Rix85uOJMgr2Pfh/nePiOxLxjgztIBE+UJKTm3ZsKKILCXZ3d8vJ5RYyfu8oj+dEPFmkQR4Ix9fr9YqhHRkZiampqVhZWYmVlZWYnp4uuR8QNzkkHJRfLRARA+cg072coE0END8/H4uLi7G+vl76RXHHzMxM3L59O27duhWTk5PlmZSXY5xwODg+XteBY1xeXi6GlZLw3d3dEjFRNGJ5srGi/4wXOT44OIjd3d3KyezcE8PiAgNTTwY17Xa75NmIgLe3tysRN9ExkRXRI2CBqkfWGXo4Isq+JiJM61ymnKE/AQx+3QlyacCCPpKPs7NxROb5pCDGBRk0ImlHiqxNtgOZqqNPptJYEwNEnECOyvI90WGaK5B5ju2AK48jolC67jPzjV7aRnE9QM1bPhx9W7dypTSRlF9QOTc3V3kPGrYk54Kv0l6zk9rf349v+IZviB/4gR+I7/7u737i+3/9r/91/MzP/Ez84i/+Yrz44ovxz//5P4/3vve98f/+3/8raOl7v/d748GDB/Frv/ZrcXp6Gt///d8fP/RDPxS//Mu//Jr6kmkhRxHtdrtMpnl7SoRt9M3pgz5z1GBEMaiKbhCFl5FLpgvdrFgIlvvJGMkhgYodIdFPxmH6Lieke71eheJj3jB6zAF9833Ji9gYmlpEEA0IQLN5/xPPv3nzZqytrZVigtwchbqhzN7vAxcOohsaGoq5ubkYHr54YeHs7Gwp8CA6mJ2djfn5+ZicnKxEXigiqDMDjW73ogx3c3Mzer3+pl2KLTjD7/z8vBRa5Mq3LAOmhvi/Hb6BB69CAWj4WCM7bj8DWT44OIhHjx6VggT2VtH/iCg5xlarVSgaO779/f24d+9e3LhxoxhpG0vTX5YnR8JZnx3ZOP9G7pT1oCLR1agGqqbvkFWzHTg6ilX42wUHBn/0Neu35Zy1Mm3mvYpZr5kPfotM83nWQdsSF3jk16zUMSt+luUXJ2KKHj3CYRGlo9v8ATQxPuwO889zARfb29uxvr4eV2mv2Um9733vi/e973213/V6vfipn/qp+Gf/7J/F3/pbfysiIv7Tf/pPsbKyEv/tv/23+MAHPhB//Md/HB/72Mfid3/3d+ObvumbIiLiZ3/2Z+M7vuM74id/8ifj9u3bV+6Lo5vMd5pPZpJJ1OUKQH7jY1uM0M2/1+VL7CBREAu4OVl/hmDZKdlxWeizMbPwZc6XhpKTwDeS4dnQHDZ4Pq/QxtIJY55jysmONxtwO+qhoaGYmZmJhYWFmJ6eLkh2dHQ0FhcX48aNG6UfHgv3xFF6/lnjubm5YrxMMXC0DjmndrtdHCPjcik9hn9nZ6dEdBH90m3mMJ99eHZ2Vq6JiBLBR/QjI5ex21DbqFsWMiXsSN6VV442WGvnObJ82mkcHh7GgwcPKhWtEf2joxgzc8t6G5RsbGzEq6++GlNTU+UUAtN6ZiWYD0AR8+J+gtLn5uai2+2WQ2vn5uZifn4+2u2LXCGnm9A/64ojDVNUgBl0CSNM5O0N6pY1bAbrYIeQATHsCfOT15V+mk6zQ6pzZIzJzjhTi4MocK83v8/2E1nOYAHAYqBqUMrvcG52mmwcp8/kLFutVjx48CCe1r6oOanPfe5z8fDhw3jPe95TPpudnY13vvOd8fGPfzw+8IEPxMc//vGYm5srDioi4j3veU+02+34nd/5nfiu7/quKz/PXt5OKiIq51FRtYPhyQtqJM/idjqdyqvAEeKIqPzGJa0ZwfHbHLUZbfEbC7DpPRunTD9a8OvQmJ0vp5K7zJrIkfuBwvlTVw5rfryuuUorJ6AZf0S/9Nn7hXq9XiwsLMTzzz8f5+fnsb6+Xtm3YQTHvDMGkt4LCwsRESUSQz7I6RweHsbMzEyFg4e+QllPTk6Ko9nY2KiUl9tBeIzIg6k3xuTcINGLD2K1k8rRR3ZUrIWjVD4zMLD88H87OdM1GFc7U9YKwIfMmA63MeRUkfv375cDhtFP5hcD5T5bbx358R25Luve7OxsLCwsRLfbjdXV1UINZuqZSB+5tI4NDfVfvmkQlaOuzGwwZ9YzVwpaPnP0SrO+sram9ehzthuOrAHoXt86J2Vg6Gv9e2wba5P7nYswuKfH4UjR1YHYA5+l2Wq1CvD4wz/8w9o5qjz/qb94De3hw4cREbGyslL5fGVlpXz38OHDuHHjRrUTQ0OxsLBQfpOb0WhExM7OTkT0K9Gc/+H3UDQ+Kse8vb0/lUEsBgrDsTo4Qf5Nc6LRiMZcdEQVBWXUw982VhnpGAlF9A0lEZ6dFd8jfIyf87iITk5OTkryEoPqYgiMK8qfhZd5dGMspg25F04A1A7lR79Ar/Pz8zE+Pl4MOfuoTIHwDJwvf+bm5mJqaqrQe0RNlJiTmyK/QjTtN9oeHx+X3Mze3l6sr6+XqMjjNb2JMtIw+Lnwww1D6KjGaJdnZPoqr4XRvuXAtJIBDc+DLXDVK9dRmGCZIr9GzsMyhh4CBDgM1o7QTjq3XLzgqJ1Scyg9X+PzNX38kmXNEZALQrARnChjBqKOEfHn/M096yrmiKginiwbj4jKZmaiLdbJ13K9/2QAkp1FpsT9tyNfMzuWS8ZhYOr78Hvsov+4eMRn+7G+AEuqXK/SrkV130c/+tH4yEc+8sTn3r/BxFO6GhHFCPklYJmq86bAiCibDE9PT4uxs3G3I6sT5ixAPMuGKgubBccVa5lX9jiNOjEopi8x5OzPmZubKydUb29vF2PtDbxuRus5sqO/GBVTLEZkVnDGAG2wvr4eu7u7JYfRal1UYI2NjZUqs52dndja2ipr4udS5EDBhTeykkdiDshpDA0NlaIFlBDKhzXf3t4uFWlHR0elOjE7AKgo5MxHCKGY2fhgQLLB8ZwPMkJ872Y6uI6+4ZrMAOQoz46y3b6o0mI8do6ZwnYk54gc48QYkTGDFo+Ze5l+sxwzvxRAIT9UgrInzUyAIxwDil6vf+YczhTGxRWMzskwvqyPyLoLDaybBpZ2BO6vHVN2Br7OOdw8d5YB+mr60rpnGayLspFbKF/LhSNE5pKI1KfzQPOyR5D70J+ICyaFytentS+qk7p582ZERDx69Chu3bpVPn/06FF84zd+Y/kNHDLt7OyihJfrc/vwhz8cH/rQh8r/d3Z24u7du4XrRMngkW3wI6I4LowNyAsFYn8Fpwd0Op1yiCUe3xv8XPFCY5GthI5sbGCzgHAatIXWKJrfZYrAFJArh1qti+TyyspKvPDCC3Hjxo1ykGq32y2vYNjb2yuOAeE1MreA0odcSYkToJzURhmQYCfGHBwdHcWjR49ieno6lpeXS/J9Y2MjVlZW4rnnnot79+7Fw4cPY2trq1BNOCgKH6ARWq1WbG9vx8bGRmxvb0e32y2vJtja2orz8/NyxBCyMjQ0VDYcE5kSNXkNvWZGmRg3yx/Xen1M3TkvYiOf1zBHTZkCdCRmmiffw1RjBjp2cqyLZdkRHfciLwEosm7guNER5JgT4l10Yv2gb+4Lzz46OoqHDx8W6nV/f7+iH0TjnCFpqo5ozpWq9O3k5KRsLbAMA2hZW9OWfumiCytYTzfLfp5zIk8cpkGpDTnNjsmVkmZteCZOiTHYOTgCtv3ieZmGRNb91gB+w7MYy+TkZCXfTXELRSkwVdi4o6OjyrMua19UJ/Xiiy/GzZs349d//deLU9rZ2Ynf+Z3fib//9/9+RES8613viq2trfjEJz4R73jHOyIi4jd+4zei2+3GO9/5ztr75s2TNAumjSd5iFbr4hQBKna8VwDj4Anc39+PXq9X9rBQkn54eFieUxcq28AjBBFPJj4RMAsti+7iDH6PoFuBnbcwdUDRB5TMwsJCvPjii7GyshKnp6exuroaBwcHcXp6Wjao3rt3L/b29oqTNNI2/ehkKI0IFUF06I8jRLkBEqzT+Ph4dLvd2NraiocPHxanuru7G4eHhzE7Oxuzs7Nx48aNuHHjRmxubsbx8XFMTU2VpLfPVsQA+aRw6MbNzc3yegfybMiCE+2MOxczMAbW02vs8eZmQ2BHYrScrzcwyUUu2UjwjCyDprQyjeVn11FAlkm+8+8BZzinnF9CviOqBQvn5+flHEP+MLe+vzeAMgdbW1tFRnm3W0R/+4Hlz3NhJ2MbwG9wNvSB6O/o6CimpqZiZmYm2u12kS2ex0ZWTiZhXok87dRwzgYLzmFzPfd1tOlmW2Wgk4EU824mw+uATltevbZEc9wPh+c3QPCdo0YcIKd1EBScnZ2Vl4+ScmFdmbOrtNfspPb29uLTn/50+f/nPve5+P3f//2S8P6H//Afxo//+I/H13zN15QS9Nu3b5e9VG9729vi27/92+MHf/AH4+d//ufj9PQ0PvjBD8YHPvCB11TZFxEVAWByUAAmwpRFr9crIX2ueMpefXp6umzY5E2pLvV2uaWpRjuUiOqRPjzbQufjQ3LyclCU5Oe22+1CfUF/UkAwOTkZ29vb8corr8T9+/fj6OgoJiYmYmlpKe7cuRNjY2Px8ssvF3TqKDTTeRFPnrE2MTFRMfA4LvplSjLPOULKUUQ4kb29vVhdXY3x8fFyAsLMzEzs7e1V3k3EvBGJQiv41OuIeIJ2Q2kd8TK/Hn9W5DqUidw5Ee21x3AY3bsZlfq5zJ33o+Schp1njtxZKztC7p+T5s4D4RihwX2d5Z9rfR/6kakq7msj7rHnKAD5sMN0ro6o33LpE2QcwfN/G2qiL0eNOMgcmXpMRNp57awXnlMAHHOGXtMvR92eb+Ql5zAtA35+ncOyXA4ak+2Lm8GZG3MUUT1thv1/vJGbIjW2RMC24IQdJNSBu7r2mp3U7/3e78W3fuu3lv9Dw33f931f/MIv/EL8yI/8SOzv78cP/dAPxdbWVnzzN39zfOxjHyuDioj4pV/6pfjgBz8Y7373u6PdvtjM+zM/8zOvtSuFO4WvtsEwJZcRS0SUE7FpGBLnFtjTw14RDBn0AL/xKQEWFv9xTsyC4PAelGVHlVG7Ix6MNYURfh340NBQbG1txYMHD+Lll1+OjY2N6Ha7xbHMzMzEnTt3ot1ux6NHjyqb7eh/zjm5X6Y+oAWZa9M9poaMynxfjA65EGhXomJOIUfQI6pl2dkIZKqs2+2WHIRLbI1uHX0jDzlqYr0sYznRj5zkSMFRhx1TpuZsvDMtZsOYqRevjek6OxM/34bLxRP5d34uxiVv3rZzygDL43WU5u/cH8+v1xfn4jUyqOPIKPfTdiGinwtCB+xsKZLinq50xLg6+mYNXDaP80OWzZxYDlzVaWdDn1xBaV3kXgZ7Bi/oUZ4bO6WsF/QBWs5jzqCMe+Ck2u12ye8eHByUaIk1gqUi2sVeGvRcpb1mJ/Ut3/IttR6Y1mq14sd+7Mfix37sxwb+ZmFh4TVv3K1rCBWVVEbCRh5WbKq6XDEGyiXkJ2dCxRn5C8bNdebdESyOTvICWEndn4zGsmJbebODwshDffn13KC+zc3NeOWVV2Jzc7Mo09HRUayvr8fMzEy88MILcffu3ZiYmCi5HISOzXmZSnHY774a2eYciIsMKELp9XqVA21JwOL0d3Z2yskXRG4+FQPnbnorl+4y36w3jjgbDRsif55PbcgOwQbV0TEy4pyOZTE7QtOpOSrKqDbPa100xvdGrJmK9v1YT+Q4R9T+3mAlPzs76xw11UWjHquvz99lw+o5d+7URVKATnIq4+PjMTs7W94tRpVnu92O3d3dQjdT2YvDIWLN+WLWELm2c+IabAF9oqiH39gW2L74c8blk+W5r5kbMwyeMxyjZceN/nEN82nQ4DXJW3UApthgbEe73S6gwKfzZ3D0tHYtqvsGNZxU3nxqeiyiKihMrndVM3kUXuCkTH+Q+I2olv1G9KsMSbr7FPVs0PiO/njTX+ajMTIZGWMseAkezslKsL+/X/IxrVYrpqamyv3YuMkRQJOTkzE1NRWPHz+OtbW1Mja/hZMx46xd/YQDgbLkdzhRcopGgt1ut5JLM4V6cHAQq6ursbu7G9vb24VGtWHwWmCMfEYgaw3yJ+rGSdVFG6x1pu5slP25aR6j8oiqYTYtx2c+HYK1rotijJRzLodm58o9HNnbgfMcfm+jZL2wcaLxfEchGWg5r+H+o5fZETlayuPJDt0MiefaNHRmUQxmOFGE467a7YuNwegkJe04AeaD9UOnMcCeI4OUXDGLPcJxEqUZvHiOuaerBnFSzLEjN+YHMIgt8JpQ6EEBCDbRTpDfZ3CWgVd22pYZF4G534AfR4+XBTtu19pJuVrIDsoUDJNqFB5RfWMn0VK32y8Bz8Jih0MU5gotjroBNRCZ2ekgwLy2HGRkigyn6dOs85+IquONiFK5Bz3J9XDEhOcnJyext7cXa2trZaPzzZs34+bNm0WYcMiUBGcqMB9/Yp4/CyfOiT8+5aHValVeAUHfqazc398v0R1zzbhJzjpK2t/fL9Sr83/w444QrIA5MsbIZqdqp2bFzbQXsuI1csThOcyVcNwzon/SAWM0pZMRL9/ZqbpoJVOOdlbIveciRzIYe/pjB5OdVEbs3Dc/03/yNZm1AGBkWbPDdWRq3QBUAZjQ59HR0VhZWYlOp1Nel4IhBzzSH9YQeUc30QlX6aHn2CjmkcIM2BqzM8wneuv7kF6gEMRyAMDjOfwfOUSvOJILAMPvsI88j/tn+hqaj3FBy0N558INR/KM3/Nyfn5+pRPQI665k/Jk0EAS7AnKNAXXIOQIvytZIp48Pw0HEBExOTkZMzMz0Wq1yiGaExMTMT09XQ7dhDpkoXh3z8zMTCkuoAycPSVWZhyGTybAmET0EQ9cOoYMIWu1WuUeVraRkZGYmZmJ3d3dePjwYYms/PrziYmJsqEV45TpiByqYySM6CYmJopyE3ERtTEG7ss7nnhdR0SUz46OjopDpbrKkSdzYcoBcEBRhVGbKWEbR+eAcpTgfBFRmiMlO1r6wLPoL58bTFkuDYqQTcCTKVQMDWuRaSkf6WPjE9GPSDwG1rPdHlywYcdURwXihDPdaBoR2XY1rufKwNHPt3Ol2TlbR9ED5zsz3UZl3sLCQiwsLMTGxkY5YaTT6cTMzEw5aZ77IdNEIcxxjtZPT/tvOzBtjAyhy8ikQU92DtyHP3UFTAaJEX1nat11pMxnpiM9p6QtDJBN6XldM8DGvlDFxxq73Bw5IO98lXatnRQe3IbZyHHQROYFc7RjQ2AFdtSVKY/JycmYn5+Ps7OLg0S9lyQiYm5urpR9n51dnO3Gvi0XZWS0acPhaI7xeF+XDVyuyPNeB6Kq+fn52NzcjIcPH5ZjgG7evBlzc3Px3HPPxejoaCmoMIqy0DufYyCQ6UEXJkT0TwqJiBIF+QV6zD8bN3klAxGa97wwVzZkuZrMEYwjhZzjyNWI/M5RCIpnqgSZsuPkcwo2mH/fN9PCzB3raNnmGXxumWFe6BPUFc2o1rk3O0vT30bbjgJNuXleTWfRZ9/b1V04EMbMeJCxOoAwyEFZH/wd1/g79O7g4KActTQ/Px+Hh4fx8ssvx9raWvR6vfJiyVarVQ4Jdl4nAxrW0pG6ga436dIvgyrrhfXFdJ4jHyI9U80RUaHT8/mSRJEwOwZFWVeRKTs65ANQDL0P08KzfPwRQB37RQWvGYQvWQn6s9ScY0JZyIuY48doZME3RWgltINCiRzpILwsNEfC7OzsVJwcr4VYWFiIVqsV6+vrZR+PFR3jbsFkkTEY5p6NaJ0sBX2jUEZYNugYjsnJyRLFsMEann5qaipWV1cLTdDpdGJiYqJECnDcdmAWbAAAAo0i8PI8fo9SGWUyHz5eiH6Sc3MC1kDE9Bnr6JyHgQD9r6NTkakcOfBsGxNyDDyXa7wlgTlkreib7+NosNfrFYrWBsU5EsZj9MzzM8XIXDmfwvNNhw8NDZW3Bxu9+xQC52+NrD2/Oe/qhL6jMzvjQXkKO2uvGzrrPphOxEhSTLS3t1dsBvu2Xnnllbh3794TR2h5O4v7SxWhaSyDAD7nmZYp24xcUcm8MCdel0zD1rE82BtHnjgp1sPRNfJqh5rtIJ/bmZJ3N9Ak7807xnwEnasxscNQmM7bXdautZOKeHLDLAa+3e6/vymj3vx7GzFQSo4OMIBG+TQQv53AzMxM2TfAmWYbGxsVQ45i5tyClTsLqKMDPvM4IqJigHByVmqcX7fbrVTqHB0dxcbGRrTbF4nUqampctpDRBT6cH9/v8JH03cUx31hfXieaS+2A6BA5PWgOX2mHg6YuefffOd1zXLBfJt+4jqjXBsMz6XXyr8zMMCxRFSLIJhLGw/TNK7YovKRnAWVj0bFKLmNY10+gES46cV2u3r6A/LOcwBGnU6nFANl49vtdivvBzID4D/WOc9lvhdjZXyZ2rNjsywZQOR18fd21o6K2Oh9//792N3dLXNhXXEu1XKE4c7sDetjIOR18xoZYFu3eQZ9cf7Nsp0ba0y6wWARm8J9XHDhyA5Z5X70DwrTeT6cEkEB/TXjtLe3V/qFTvtABW9LuqxdayeVUQiLkBFG5lAj+vkQh7fOBXiRjPK51sgcR9Nut2NqaqrsWB8eHi6Gn8jDymuDiCLxt40qz6xD/Zl6oHFPo6KIfsmsE/FG5xzCSqnu3NxcJUJBGDPn72aBtbNn/g8PD8uhsAgwBpJNuzb8zmXk8dtR1Tlzz58VPaNvnmN5otXlqhi3o5I8/45eQNZ2Ut73YyfPeIlkcrRhg2GkasPsyJYxQdFQJRYR5VUuFLOwf5A9L3borBMnOBjY5UjKfTKqxwkBVKCs+ZvCAlOvzovmeXaU4znASFuvWMfj4+OyvWFjY6OcYcl9eDZzb9nie78Q1OMyM+PXqHuOLFOWX8Ca2RzLWJZt5NW/Z3y2CZlFMD3L397v5Xyn15EcWY7AYUzoZ6/XK2sJCOt0OoWF6Ha7lb1TT2vX2klFVMPtjNgwPFZm5xZ8TcSTJaFeeCuI/+2FHx8fj6WlpZidnY2IKGfR8XZTFiUbU4yJj0ay4Pi5eey+jw0sz3AxA/PkPJzRPPc6PDwsxos3bEJTRkThns0pM6cuPc9Ogfln419Ev8QXhwqic6GATz/wmlpxHfVmKtV9yHSJKbG6+TUq9mem6UzdZIPg/GCmXDJoYhwofHbyNKJscj25L7wo0NdzHWvDNd5sCY0L1Wiw4RJoImnfE1nzWttB8Z2jeaJl8rMUIfn18URu/NtRhQ20808ZBPJc1ubw8DA2NzcLiOQ75M9Vd3UOyjS0PyO6aLfblaIm7mMw50jM/XQEZJnKMpojQ0fT3o/kCDSzHFyDXprGNAh1/5Erv32C48o6nU7lgAUXpXl+M4PztHatnVROIGMEnNw2/+lwGp41CzkG27vLnQ9yXiGi+hoGCg/Oz8/Lmyd3d3djZmamXM9iu7oKRTTSRsl8rl6mq4zCsvFFGI2kof+s7DhH5on78g4lnBWvR+/1euVUi4gnXwIIqqpDhhbeqampJ8Zqg+0cnelR06FWUtMrdnB87ki7jiaqm0tkzHk9PssVfjkHhLMhiVwXGecTUpBlHI+di+kfnBDOxa8smZ6eLpQezgwnwjNM8XmP2+npadkn5O94BpQNr8fAybEWGcEzTubEzowog/JoKjk3NzcrjopXp+zs7FQiVq+1TzEwiBnEoJycXLwZ1u8xIzpivumvDbcdlKtKydt6WwnHfTkizKwAADVTh84NuXgKvTUAtS10hJfpYbMBtAzu64CYHRp2D2CJ7g0PD5eXlzInduAcK8dWkAzQntautZOyIEZUIwu+s8e2oeN7KIeTk5OYmZmJ0dHR2N/fL8JgA4JxcmHD+fl5TE9Px8LCQoyMjMT6+nqsrq6W5DpOC/TgjZ3cEwEjJPZ3RqQIuaMAC1qmvjAeEdXXFfAbOGGiJ0cIvO6cazBWGD8biLwR2nuhTGtgDDh1nHwE80hxRkTVIdBH0KFzBUaRNvqORIwkUfTsEP2sTN04AjdQIJrLlDN9hFoz7UPz+FljDAGUMWvl0n1e7kh+EAqPqrTZ2dmyrtyP/gMQbHAcbSHLGEfWnGdFXLADyJ1lwvfP+ujfm95kDnBG+/v75aQRXpHCpvTt7e3iHNgjRzk5+wJt7HmemxkM1oNiAz4z6wAbgLzzbAyzARQb6zkN3P2JiBJB2PBn+s+5H8tIBmDYoVarVSIXdBUHi7w6F8VvTWParjiysS2wzeTe3l4zaJ8VG+x3d3cr5fnZFj2tXWsn5QWN6B+PPzExUUFADsnb7XZMTk5GRFSMKyhvdXW1KHur1Sp0BL89ODgoaJf9FLyk78GDB7G1tVWENSJK2F8nkAi7CwhMNWTKysYMoeBzK6D/duLVSWloH5wESurXmYAs6ePk5GRBfru7u5U3Fxu5oTQ8F2fpkyNOTk7KPTidnQgMo2Nki+FB8Y3IaChxdtweN33CmRh923g4cjXVwXhcFsxzaXYKrCNGxg6Nk9wx3jgj9tPxHVVnOCjni3BSfO9SZAwBxs65ETuJTCuiC1xrKhb5YNzITjZ2nj++Pzk5KfvdPH9DQ0PF0S4tLVUc1+HhYanq5P+7u7uxtbVVnJd/u7+/X9nnZRDiaDcDERtWZJ4x0B8KRTj4GOflCIhI0zk45M5ziu6bfssUP0DN+SwXMZG7xaEfHx+XghdsQN44bD1g3KyTiyJw8GNjY+UUeq4DPExNTcX09HQMDw9XXpSJzeTt2JwEA1A3VXmVdq2dlI0z/2fSTQMY0YMQETpTCCcnJ3Hjxo1YXFyMiCjIHYOAMcZIcM3W1lahKEZHRwvSc3UNBsMKgRCZCgKdRVSreAZFTza0+TvPkY1jq9UqQh5R3WOEouA8Ii44Z3brR0Rlv4XnENrJiXnTVqYs9vf3S2SJ8XYlG8ntbrdbUTwMiekRnsE8eDOhy/1pGAfTKvk3zK2VEyNn+q3b7da+JBBHzbx5kyMbpmdmZipREWcZTk5OxvT0dMzPz5eSXjsR/5/r6JtPg8eI5gQ+EXve9Ms8ojOOltrtdnEY9AGD7zwDTtJ6iUxBBR8dHRU5Z+4NuohS2CJhPcIJbG1txerqamxubhZAs7m5GWtraxUAlU99ccSALNkpIwN8x2feFjA1NRXLy8sVtibiIsq8f/9+7OzsVKIFU8Kmv3Keyk7KuSQXXNE363Cr1SrOOSIKBWtdcY7Y7AoUrmXAKRLOBXUKhXEcHR3F7OxsWVPKzqnsA2Ty2h6nMNgecJX2unFSCIPRQsSTbzNl0yiOw3kp7gNyQNAxwM4D9HoXrxfnDbdcD3KJqO7JqesXgsqJE/7D+LgP/885FYS3Lgrw3FgwcQ4YafqbIy7TEygXRglhZSxEGpOTk5VKtoj+gbP8jWFyBJvBBmNDcZlz5x4YW3bQpoENEjAUzI0j8UyVuh9eL0cINOgzV4AaDJAnImcxPj5eKkBxUj5VwEUrk5OTtblTz4VROzkJ7olRcIRpCgiHGtEvgnAExdoyRxQIOLdiKis7FebOMuDjzLw3ri7HjBw46pidnS37D9E/3tY7Pz8f6+vr5e3TOzs7EdEHnJZz+mYn5jX36SXMByBiamqqAn6Ze6IaAIflOjMkjrSyvvlYJtaBubE+E4F7u0DO0QKYYZjymE1/M9fuB28hiKjut6Q6cnZ2thJZOyd1cnJSjjnzhm76eJV2rZ2U+fyI6nlf5CtYTJT19PS0kuBkYgmVz8/PS7m4+dazs4vTJGZmZsrvXYaKEXCfLGDuR3ZIdjoIV11URPPz8vf5MxsxF5LgHLgmO7uIfgkuc4Lx4v52VI40cIQ2WDwHQ0g/qCqzkyXS6PV6pVjDPLudjdEhSpXLsjHm3J/PuMaOB9lxqT00F5FHvo5rkBP4e96xgzMyZccfv96A++CoQMReVyN7kLIBh4+K8njdX8ZXV3XnqNtG1bmkDOoMHJz3tcM3sHAxDfIBoHBuw2NgHpBJDO7ExESJ0nBcq6ur8ejRo3j8+HGRA+TXaxzRj+7dX+cmSRNQaAUYa7cvzpbkKKVer1ciODt9PwM9GBkZKU4vryeykMF1zofSNwM6g0b33SCCc0UZk3NDvn+dHYD5cYQJcOWYODseZAGnRaOQI9u1Qe1aOyk3h8XORxm9ERVBr5jyGxoaeqJqDeTc6XRKGfb29na02+0nzmEzWkcJM9XmRckoYpDDyf+3AbHSWaH524bEwuxEOf3OfbKyGlGabsKYZirC1T92qNATfrU0UYLHwKkU9BnngFHFubl/Lghg7ETKjkDynDN/cPA4SdByp9OJ7e3tyhmLzGlEVBy+TykYHx+PhYWFWFxcLHlLOym/YsVzhUGGQjLi5bnOM2F87ESM0k0nITeWTTtz/s7GhufynSnmLDesRUQVuDhv537a4dlJOCqwXNu4AUpYcyhSIlDLOPki+mu5zGPiMxxodrwYaw5ApuVqPs858pvzmYBIzxtFR9Yfzw+N/jt3xe/cd5yk88TWe8abAYejMgBYjn57vf6WFYpQuH+OlohmAX5fFZGUDYYT1+aDcU5486mpqWi1+sk90AuHxlJVRSLSic/h4eFSmm0qDcUytUI/TBNZudwy9WQDwDP4nb93lJIbCpVRnQWI++ZCDPfXRRHZYYLM7JRz3/1bSqTJ06AYRuw4QYwbY2STJ1WTdkB8TnRmOjHPN0jYOaI8TsbFy/G2trYqDgFZIK/kZHDEhZGZnp6OpaWlWFpaKo7IDnp0dLQ4LOQRJWYcdsx5bW34GKurrGwsTC9lnakzSr4+oh8JEPH6+0yvYnCz8WeNMjDy/50TwcFk2bfTsP4wvxSdAHSci6PIgwg066PnyjruKLTbvdgnNjx8cfLK7u5umTM7RGTb1BZzYaDoSNZjqqNC63J9zHf+nSNEfostxB4YBBtg48ydqzVwMFtApS4nlbj/PNcVwTh377N6WrvWTqouLEZRcEJUirGI5+fnhcemogjUShUKiX8bR1ALNBSK6AovL6odiiuALBxGbq62sbL4396fhbIdHx9X+GsbIhsQ/h3RF6D8nVEWCpPzFb4GSsxOmf6ZXsHwYJhxJLu7u2VNPJ+U8YL+2HBpZGhjBQoFqZJI9z0j+ifAU8rtPT5svCb5C01yenrxAkbyPKbqZmZmyskidrCciD8/P18Sy54/IqXp6emYmJh4ArEbsMAK5LweRsL0MH87urNM8hs7HX9vectVgBh2ZMGVpZZdRyd2LLlIqS5qt7Pjvq58RVYi4gkDjLw6v8c1IyMjsbGxUXQZCtlUcqaA3U87Bwo0ut1u2axrEGGHtb+/X3HA2CacJrJnewYzYUdqB5WrAU0Vuq9c44Ib7IO3fJjajIhCH/NZXUTuKCkXafA96+lcIPLY7XZja2urknK4rF1rJ2W0SQNZ7+zslE2HEf2jeqCPoHTYl3N4eBh7e3sREcWQYjwxeFSZ5coUJ8xNo5hKYsNspvSMYKx4jkjyPe1IMG6mFSMulJpSX4wX9+K5psy4Lw4bFIoQYviMqCkWwAkxb+x1OT8/r5xcAAqLiHJaPEYZZXZRB4KO0TFlZ6oW5Ef1mQ0+41pcXIybN2+WfUTj4+OVfS1f+MIXymtCkB9yj+yhYy8S5zJOTU0VB8V8Q+tNTU0V+tgG0wYYo0sU5eQ0spwpMgAShs7lyZ7DVqtVCn9MfWJMPJem0hx15X1N9MWG3ZSf80n0n79ZSxtAnFY+dcQ0e2YjnM9kntCPs7OzcvbjxMREvPGNb4yZmZmYn5+Pl19+uWyu393dLU4Kg23dMX1sKuz8/CI3u7W1VUDR4eFhbfGHI2C/U822wnPk+WFeMptgm8Lz+LcdreUg04jMJ/3gPvTDTsrryvwYkET0q6UBkswB+X3K1XPK4aqv6Yi45k6KAbt01hU2KEBEP5RncTCaXmz2HVD6bKeAIpuKIEKK6NNpFkILPgoG6qijBgYpvv9w35xLyHw1Y/eJB/QTo0BxQ6aTGK9PG+DgShSbZ9MXKDKXGLM2rA97OjLdynzZ+GC4ye9YuHPU6nVm/qHk2u12zMzMxIsvvhgvvfRSMd6t1kWl1szMTDFIEdV9VFDBOChKw2dnZ8tJ8Tg1DuQlQmPeJiYmKlGJoyHOwKOgx8YLasTH21iOkT2cegZGHHHEWvlsNUeYRtiOpB01ubzdiXhHZTawjIV5RFadM8ynRNjAOt9Bf+r0gHkkskO/KSvnpYYTExMxPz8f9+7diwcPHsTq6mpE9F+j4giPMblQwuwIToMNqswF4zOdxzqyBuRsAI4+o5Bn2aH4BY3sBaOZJqVPVN0CSMx2mKq23tjpOKoievIpNOfn/dd2IIOcz0d1IeuG/OCYqfCjhN9szdPatXZSEVEoOFAOVE12JiA00yFWfOgoqvigGTAgUH/kF5zsRgiMNGmm8/yZcwI2YqbrMoedczh2nv53RJ9iMRWCkcCZgFyZB+bLyM25m5wDs2HEgaFkRCg4HsYIPeI5goLB0WQun2vdt0yPYXS9OZbxzs3Nxc2bN2NycrKcpOF5ZF9Hu90uToU+U0LOe3JwVDMzM6XCjLl1GbkpMa+7KRT3IUfKzIORsI0AhoA1ZNzOddhYZurOp0ggc8y1o1QMk/MfmcpG1lxgk6MhxhJRpentcOmnAZ/Bl+/L/ZgfnxxhBgSwcPfu3VKoguEk78yzWA/6wrybzsZh82z319FkLjpivD5tJesRfUduicBdOMT8GwibTYK58L0BD3byGeCzLo6c6e/Q0FApOsN5MiZyUWylcJTHOvhVNjjbnF+7rF1rJ2WlhTYhOWpawWgfY4f39x4U0KZLqWkYyt3d3fJm2Yi+I8l7UTJtZxqFz1EKCzXNhgoBsxMyZYTzygYOZWAcdbxyvreROvOLcIEcmQ9vyOQPYwEk5EgMRWPcPJsyb4y9x4WzZdxeIxsul3TzTKi9brcbjx8/LjkuZAMHycZbHJOdFPfwiQ/8hsM1TYfkQgLkzzJgmcxREOvn6MvFK6wjsmE62EiaPVZ2QhhU5xNN3XjuvQY57+ho2yDNNJepWMudnaPHRv+MsC3zzJ0LfOwEcpk8a0tV5Y0bN8pacXKFN5y6otd2wZGc19FG3UAQG+OcH+NEJgCn1knri22T7Rvr5MgR4Od8scGBacu6XFWm8ph3oiY+szNlHPTFdCXz5QIMR7wOJK7Srr2TguLjLbcIgCfb6AZlIn9goaPB5ZoiQ3n39vaKI0R4EEqea7Rrp1RHq0VU37lkaofrcs4p04ERfbSXhc/jQllMe9pA8RsbLiubk77MB/fnOzsf+ujIE1SHgFsJnCMwbWCKj/Whb37rLfSaz7qbnJyM09PTWF9fj8PDwyIHrDGIu9frFWNGNOToiE2NRFSmQqEonXvxGtoxee2YF9OiyISrGEH+VnRTUNmZ4FwBCzagNlgGZ6Z3HPl6Le28uY+BjN8ybTrWMssexEEMgOXe+msH7+caRNkgc+3Z2cUmdApylpeXo9vtxu7ubimmsO6ZQoNms8POURFG2RQaEQbyxZxwrYGzI06ABblv1pn5yLlvbAr6YbnzGuFwnFu27aHf6J3X1sUNBlHOPfrelhufO+i1Zg7Q46e1a+2kut1ueQdRPt6/zmC02+0ycRgIFAojg7KSLwEtorwIPTxuHco0GrYDNLVhWsHfZ0WJqL64LqK6p8W0Cfd0wjvfH67diM5GwE6qDh07x+RGf6EorMyOJPks348ybkd3bByk4s6KY/7ejp3PKBrpdC72Ob366qtxcHBQih4cRfA89jM5x4NhBtS4eswyZATL/KOgGCtTv87hgaBdnMKBodzPTsrggGc4T4fB8v2Ya1O3njdH9T6twhGa55/xsn4AEHJsRPGmnA18stzYsdTJleWez5lHvgNYOpqPiELtUZ353HPPxf7+fqyurpYCHztUdMLArG6ecl/trIgWuJcjKcbJekFTU22cC1bsqGE4bAvs+Cjq8nOcZ/XaAggNCnu9XvneAL9OzzPQMejChjrqYw4HrfWgdq2dlE8AsCHNyJHJr0P6VvZ2u10q+fgMtO79LZROG3W4KseLkJXQTs1Ix0bWaIm/nccxMsFIGrGCnJx3QtH8OZVfRr38O6Jf5QS1AR8NZWKaBVQJKqeiB6TnE6xzRAloMN3ACddO0kf0XzNhtMu4qSTCwHS7Fy9Xe/z4cTx8+LCMg7PuXFSDUXNup9PplDyUKRh+571erCffu2KNdzRhYHy9N0aj6PSJSqt2u13OXjPlggEgMc38ZkrUxgQZxZE5GshvPHaUZjZiYmKiEuVlR0j07Xwu+un+O8q3fuZmfWXMprKsNwaFnc5FlRnywHFF8/Pz8Za3vKW8LdtMAXYFPcoOOuukWZAMSB0FOdJi7sgvIWNUnuZ1xmlxXxyRjT7AgzHYrhgwskXCFCT9d34au5nlKBcZIafOd0dUzxccHx8vYzXdaLByWbvWTgolh1fOEYaNfUZjecczwt/r9cpmPTuDw8PDgnptSLivnaHpDCu6ox73DUNkRbXg0T8rN0aKexjZ2ejCWbfb7VIaPT09Xaq/TGtaUSP6SV8Qed0hs0NDQ4WeGB4eLk7JAIJ/543OzIUNt40O9yfyYezMtdeTA2npPyeEtNvt2N3djYODgxgZGSlFEqC/oaGh8hyQLlETTpnoirl2MzDBYQFyTN2ZjgJZYhgwaAZRzA15COTDwIA1z69EwFiQyDZl635RaQXtfXBwUErvMaimlc7Ozso+Qego7sW6Z9qQOarL2Tp6x8Eybud6MJY49JyTs6NgfFCA7M0jqtvf34/Jycm4c+dOHB8fx+rqaimmgSlBfh1B2bgyJp/ZaQeLE8399NwzZihmNrkz1zlPjY47Wna1YKabXW7O9dga1hsQxVsI6Csy5D7bWaGLjqaJrgAP9JF1o/+2hxmsDmrX2kmNj49XHBSCaT7ZFEtEPyHtDW2mLzCarmgyDUcegjOrfE//zuiT7wjtnTg2b51REL+x4eJ7Uy1efCcwcVIYZPYF4dhtGH0iAH2xsYh48s3FEdVkq9+uyli5Lv+e9UEhhoaGyr4jaDCqiBgjhwMDMHBu2UAgD2xD6Ha75YijiCjFH+RvLD8gW1fu2eHyjMPDw+LITHHyh2bja/oOp4zMGXWyx2R7e7vkeTC8yAuH1J6fn5eDjjG2Ef3XwtMvy5mjAM/3+fl52WdGLotqrG734rT3qamp2NraKgYOGSYv3Gq1SnGJ98gZ2Zs+h9Z1EQONNXYBRn4VCX2wMzPAY3+iz/jb29uL6enpeNOb3hSPHz8u+UooVtbE9Kqdi6MmU9QR/S0qTgdwHXYBMOTtAwAN05dc6ypGnmNal4Zzcs4SeTUVx7oQtZnyN8DOEaLnBl3hPswX/eL5nhcDK8ZwlXatnRTJbxvK09PTguDMvbNgoBQEIr9aAIoADntmZqZ8z7l+2eHVcayOinB2jgTshJxPQvnoj2kNX5cpMgSAMdl5EUGxD2xra6u8Dh50hjHFsTPOnMwHSblhRDjLjLnFWRphIchEN71eL8bHx2N2djZmZ2eLQaRIgbnjnUK8dC9vIyCnZCXPeQZTSUZxmaIi8iSSwYGg0Da2Hh9GESTOmhNZ2OA5IgdxkjPhSB8KgbydggIhoqCIqJyuwjxFROWMRMvD+fl57OzsxM7OTgEwfheV36fG/Yioe71ebG1t1b5Zd2trK05PTwt1NTMzUynfx3APDw+XiB46DkrVuoDRZS6sy67E9dpahwxc0Ytut1tOjVhaWoo3velNce/evXI2o6lOU588F2dh2g6ZyDag7t/uP3Zqb2+vrCk5KWQmpwkcpSGPBhztdrtUOSPbAK5M3zq6MpipS4lk4J1zscy1Uxl2TA4Wcl71ae1aOymElgmBzomoVsA5/MyRAotkB4JhZo+MK6TMfSM0+Qj6iCcPes0OjL+9+L4mUweu/qpzZvzW+yuIQoj+ut1uOQ2CnfmcHZeFBnoPAUYZHNEZJddFEQhl3muFEaXPCO3Q0FAcHR3F9vZ29Hq9yl41Xi9+enpa9jJBO3B/DhXNRQQk8TPyzY4KRB8RJcfDng7e64TcZWPKfOMsqADFOCIj0DlEK5YP1gn6hgo/042Uyw8PD5cDQ+knaJxCok6nUzmT0m899nzwf5zH8vJy3L59u7zPyc5vd3e3ABFOaYEmXF9fj729vRgZGSkHvS4sLMTc3FxMT09Hq9Uqe9RwyN4A7fdiWYYccZlS53tTaxk0Eg2Se0M+dnZ2yll/L730UqytrRVHCEXFGF1YwPr72eigAWnW45xuoG+cutLtXuRPkW+iYOTcFaucP8r8w4oAQJz/w0H5RH3YFYBUpibtuNx39NUVgrAMpv2sFwBN1g4bg+xfpV1rJ+Uz9aBPQMJMXEYiEX1BzvTa0NBQQdNEAVzvd6TwTAwsRtYVaM5RRPSdTVZADC3/t8A752X0lPMxpjysNDybZ2BA9/b2KlSBIzD6CF2Un+dIgmv4DUplLt8JYwSfSIvIx04eoxjR36EPWncllB32yMhIQe4RUYpfUFg4dzth53fyXJIIZq3rTnr3/VgbPrfysw6WHRwQ1U9Go8gkTgfHgdFyAY2jRNbRAIVI2dWGRI0uJTeQYR5nZ2djaWmpGM719fV4+PBhmT9yN+gGJ73s7e0VeUMODJx4e67zmdCD09PTBQy4ahAj6wpQ/+18MGvIvCCzlkP6vLe3FwsLC3Hr1q14/vnnY2Njo5LXdJTuKjXsTnZWjrYyY2JWxetMP+vYFtOl0NXDw8OF3aFIyIVJ3iyPnuD00BdspJkTxopNcgSEHDEPyA7f0V/PAfYXYOSXMvI8A97L2uvCSUVUowgoI4TSwmHajFwMv+UNqyRRWYT87iicUQ6JMXp2Uggp/eO3Ntx2fHZkOKlMK9qB5edEVDfdRfT3PlmIPQ8gRwwKeRkftGtBZjyuDLMAR/QPr0URABE0C7vzDjyP+cbgtlqtYsCIClkPI01Hcka/GP3M+Xt89CHTiFCSNlR853mkHxQXuLEmpl0iomKQLZfIHmvX7faPHgJAsD6OcE1LMt5ut1vK+IlYqCTzGtB3cpnkC3nG+fl5mQfON0Sebfi63YsDewEUzoUyLowWNCfrNzs7+8QJH71eL6ampoq8QcO65NwAL+s8OpBPywDMzszMxMrKSiwvL8eDBw/KAbLcC0ceEUX3s47yJ4Mf/461hFHw98jiwcFByfPwm0xt48A6nU4BO9g89AYdNh1NY20B3rY5AB0fdMtYvPfKYzcAxz5iV02FO1B4Le1aOylHS0wWE2lhMi3IHyaYPEJE/3BaUB6GzVEKgmYEjmIiHBbATOnxnEzzGfVlQ2ZenL9NTYJcjcoxWowP5Nbr9SqnMSB0TvQ6dOc7xuPoBcV17idHljhGUHNEtYDAFBgKZuRPVIeRIxLY2dkpvycqzo6UCkYoMs4Zcx6D6x2Fmkt3AQ1G38jee51MPeGgfVRUnTy4yMVzyivST09PK06J37Hp2EcYsX5UW5I/AWSxT2xhYSGWl5fLnDJu+nJ+fl7ebgtS51BVzsKDkoQGdPRK1I6TIgqcmpoqzhDdIrrHeENPzs3NlT8cR8ZxVJaPunW3jjjKyWXQ6PvY2FgsLS3FwsJCcYqg/kyp2yizVhkoGvzYYfLHsm0wybUGTb4/8nR6elpYCPJYRLLIgyvq0AXbRb8pgCgX/TWNbyBgat9FOIAc+o+usJ6sN/PvHNZV2rV2Ukwm9EnePIchQggcwhoNg+aMdpls89um3DD8mQOPqL45l4ahMppwAYJRCE4yJ9v9HBdM+HBHjLAFAUHjNxzzA32CA3dCE6TliClz047QXCTAvRzROofn5/p75hz6xwlk8joRUYoumE+UArBxdHQUu7u7hX6qo2rzWmCUmBfnRxwBR0TJVRrx5wiNuTc4MNjBufFbSqXJIeCkOAzXRSg+0ivn2Y6Pj8t7riIuTnjY2NiIjY2NODk5KccD3bx5s0Ri1g9yXVyztrYWGxsbcXZ2Frdv346lpaVot9vlvg8ePIi1tbVyqr2jCbYBdLvdWFtbi9nZ2bhx40ZMT0/H6Ohoof4MIjY2NkqeC5na3NyMw8PDmJycjFu3bpV7GGzYIPN8O1/LnxmD4+PjUrW4tLQUc3NzhR1A3njdD2tItOqogufy/6zvpmnRMQNo7JlliftAga+trcXu7m4pI/dm7fHx8eII7Ggouyf6on9mh1qtVomQPS7LsvfwwWBho5xuwD4ZhHU6nbJXCucVEcXRPa1daydl1GoPbwcUEU8IMH+gSTAQLC4KggFD+KAnnBcxTRfxZJTEZ86VEUV4Mb1Hw1SB6ST3xYifP66iA0H75GSa+xjx5AGafIYQIeCMlz8uawbN2kB4EyKI3OiXMRIJUlRBJaKjFBcZjIxcvIsJ5c0R3e7ubqytrZWXFTLOXLzgHAAojz00c3Nz0Wq1SkQwPT39xCvgiVhAtXt7e7G5uVlO0Z+ZmYkbN27E5ORkoahYfw7kJNIbGRkpFW+dTqectu5yXke2yK2r5g4PD2N7eztarVZ5T9rR0VFMT0/H3NxcdLvduHHjRty9ezdmZmbKuHPBD3N/cnISa2tr8fDhw+j1ejE7O1voqP39/djc3Iz79+/H/fv3o9vtlujO9BHOZ39/P+bn52NiYiKWl5djenq6fI/B3Nraiu3t7bI2POvg4CA2NjZiaGgo1tfX4/bt28VhQos5j2SgiaMyPWzKFvnpdC6qGpeXl2N+fr6sSavVKsUJABacF7KLbXEekv+jG/wNgCOqQR4AjqxtxIUR39vbi9PT09jd3Y3Nzc1S5o/dA1CxXcMROc9gHnFYrLufnenJzLxAtzofZwoUZ4v8cB9sAK84yoDqKu1aO6mdnZ3ioT2pNkwRfWfmfJHfI8Oi4XwcJXFPBBKEmDfgmjLib18P0sgFFHak2dFmXt3j4ZqIajk1TgB6p9frn7XHNSi1aURHGHZWpg35rfdt+B5EtFCP7HvyNdA8EVGiIyjS/f39sv8MmpXkvKMa9r1gzPjjvvpInjxvOXpDDubm5uLFF1+MF154IaanpwuFMjY2Frdu3Yr5+flKzseA4/T0NDY3N+PRo0ext7cXExMTsbi4WF5ljlJC90xOThbw4XE5FwV6ZRzImnMbVDaaImq1WqXYgoqwmzdvxsjISOlPRFQoLWSWOeT1FktLS5VXWpycnJTje/yadtYdh5ppMp69tLQUN27ciPn5+WJEceCcAEEFYESU/V/I7u7ubrz66qtlLl944YUYGxurvLMI3bRjZ35ctOIIgL1xN27ciKWlpVhfXy9gyxGvCzrQDwAUz+R7sxSmkp1Pcjm7QSMVrawTwJn/E/lE9Kv1jo+PS66RteAdeXZsyBER/fHxcTnAwBvqGZ/PErTdMUC1LLkykLkxtY+sZLs2qF1rJ7W5uVkWGsF2EjUbetN9ma9F8dm3YQE2vw1n73JYfuvn8n8rrnM+pg5ZLNAxQu57IVQWFJwrykeD/rKzRtksrA7Puc7PQTnNJ/M7J/SNxKkmIgEOwsPgo8T81vSiaUYMU0T/5GwUnCpO6CLyNlA05DWI3sibQNWwbnZUExMT8dxzz8XNmzdLJdXQ0FAsLy/HyspK3Lp1q+QriAx8igFl5yMjI7G0tBSzs7OxsLBQiT49r54Db6r0SxtzIYX/MKcRURApMumciSNs9p5hIDMQMQ1KDpHoiSKJdrsd8/PzFcc4NjYWjx49Ku/HAtH7mYuLi/HSSy/Fm9/85rh9+3ZhLmgnJyexsLAQS0tLsb+/XzaFb21tRURU9lEdHx/H+vp6BQhkecYYM75sD5ybYVztdrtUGRJBdTqdQuma3rb8ZmqX++F40CmYGtsoR1QUGEGlmzJkHHzH59zXBh/QRs7J+Wr3D0CLjnGkEb9j3sxCMY9EVERK2Dvf27YRW2GK3c7wsnatnRRcK+gIgWDwzkE4EgK9GVUw8T5qxCjchpjPnS9yTiUnco3oIp58D1NEP5LCiVro+B3fO4pz2B5R3cSa0az7HPHkjm+utXABAhz9+TqcIagMagl6wBVC3Mdlq06g+tQDEJlzXkRjbHIl38ScYpChAjlnkeQ897RsIC/kmCKi7HGanJyMGzduxK1bt2JmZiaGhoYq8w1thGOZmZmJ5eXlQpc5XxpR3YZgQ8ccMT4nqi0bmQbm2aaW7fhdhGL5cHRu0MZ9oHJA1kStjImcF1TTxMRE/OEf/mH8yZ/8SekfMsieqTt37sQb3/jGuHv3biwsLFTOX2y1WmUT8OTkZOzs7FQKVhyJWNf29vZiY2OjgvKRT8sy8mHjyb08VxFRxkt0TFTK2uNAyf+ylvwxdZ6f5yjMzAW6ATgADMN+sK7MhVkRcpTogam9/OoiU8U4yrwVgrnm/mYfzE4BksiBejuD9Yv5YC3M0ly1XWsndXJyUpAbigVqqDP0EVGZuPydEaivR7GNBlyVhaBCQbgIASNrR8M9EVQbEZ5h5I0hQUCdn3GUlXNwrvZzRZSfY7RnGsBVYcxNHb3Iv9mrdOPGjbI3wsYi56m8Dnw+Oztboi0UlbWgP1b+iCgbQefn58umVysDz7Vh9lgjouR2ut1uOaNxZmYmbt26Fbdv3y6bJz23GBEcEJVnk5OTxaA54Y6BslEkujVYsuN05J/BFfObN1Pi2LnGgMaVll4THIXBHDQiZeCtVqtExYeHhzE/Px/Ly8vF0D18+DD+6I/+qDyfflKUsLCwECsrK7GwsFCMvo2gHZHpYfTaYITrTk5OYnt7OxYWFkr04wjfDIadsWXI80Of2VdEIxeJrHNgcHYyfi5j4nvLnaOkDAzJV0KVowsUU0VERX6sC15z5INIqtvtv1zV9CJ2BPYlR1vuO585wucZ3krhaNVsBePDyX5V5KQwKplqY3FtdHNEEVE9+p+EHwjVqCHnhYxoURqH8HYkLi7w/RBklAQ0beWyQPEb0wVEbX6uc04R/T0W5olzDgcFjujnJ+DE/UZOjJuFC856cXExlpeXY2ZmplzLGBBY5/2cezNK5nOiEVMsLgOnsIBiA/5ttNjtdsvpFYwfxcMJEHG12+04ODgoBunOnTvx4osvxuTkZKW4gTFT6ML1VIa12+3KSQBG7Y6IWH8bTVPQrDVy5EgLIGRD53GbUTAAQY6d6OYaGzocMGXf0KGt1sUpB5woz9uJOVUCw84aUQwwNTVVjlpyLoX+ICPoA6d0W6/39vYq60hf2ajtPJBpPwPY7Iw9bq5DnnGk5A/n5+cLa0DVpdkbAyGvrR2ZDTf9sv5CsVJ6jyxBtZPD9QHA6DP9pxIXAEy/MrNiHTBl6dJy9N3yCIAFoBmwcj/sBzlo7AsAEn3OwcKg9rpwUhhRFtwIxAUTXhAWwwuH8rCHAGHPih3Rz9+gkCiaN0fSH3I7ViCebb7chsPCxJiyEeI3RtEIF/OD4DMnKBoCTb89D0QBrkZz2I7wDQ0NlTzC0tJSTE1NxdHRUXlPD8bOzhrDBUXh08EZZ96ZbtoDCmtmZiZu3rxZKsVMk/JMHCWbUolaUCaUudPplH4sLS3FW97ylnj7298ei4uL5ZzDrNQYCHJQN27ciFarFVtbW7G2tlYoK96O68jIcmcK2K9B8doi2/QZWcw5DgyAx8eaIVvIGXPM7+y8Ma5ExCMjI8Xxbm9vx/b2duzv78fCwkKZ65WVlXj7298en/70p0t+g+OQZmdnY35+PmZmZkrZu19WaQdDJIODjuifuO/PXM6MMyG6MOVvgMNcm2EweOVeACT0anp6Oubn50uVXUQ8safPTI2jFzvHDJrtzHACdvq53y4r536uUCWntb+/X8DlzMxMAYgGsdhHl7wDXAF4/C6iT4MS3XrDMb/nt8wpeTF0z8CQ76/SrrWTYhHzPhYrfw7zjextNI6Pj0tymENMI548X4/nZDTmSMz0gdEf+3VwXPyeBDyf02dHSjRTjhh1jAxCz7Nz7syIiz5j2JwrYX9RRP8tuKYz4brn5uZifn6+VGpRrry2thYRUaIb52YYGwZ5aGioGCHmhBwSRoccyPn5eclDkjDH8PmEBAx5RJ8SzjQpsoGCDQ0NxQsvvBDveMc74hu+4RtieXk59vf3y5luVLERSVIsQR6l3W7H9vZ2rK2txebmZkREeTMwa5ojKq+VFZiIkQjBEQ/GaH9/v8gWuT/kGmouIp4AGwAOnLIpZegvRyIYa66hUIWXjXJI7Nvf/vZYWVmJP/3TP43Pf/7zZeP0wsJCkRH2NpHXYUsCjpyGHLCOfrUKRR/oPaX8GP6c7CeiyJGk2Q8cBxEyoJJ9ZZOTkzE9PV2q7Xj1PNEmOslePfQJ/UXO7cywU44m+cwg02sREWXubYucZ9rY2Chga25uLoaGhio5WY+dPnU6ncKOwJj4eC0i6dnZ2SL3yMr4+HhxRthKO2ZT+uiOX3FylXatnZSRH0gxc60R1cQzeZZMgXS73XIWlnM3CAfIgufZUbGxDuOSaR1HUa5Qw3jjPFAQhNSIx47HnL/7Y8QM0sZh+mQC0HlOXqPA/ImoRpooCBsgb968WTZ3bmxsxKNHj2JtbS1OTk4K9cZ82njw+gTmgkgBQ7i1tRUHBwelMow9Sa1Wq5w00W5fVO6tr69XIj2iw/39/djd3S3r4cQ264jjOjg4iBdffDG+6Zu+Kd761rfG+Ph4PH78OB4/fhw7Ozvl1IR2+2LzJweunp6eFjoM9Do0NFSMg0//tvFhnh2pe65NvxiZZwPn70w3AwRwJD7UFUDTbvdPxMDQUd3l43K8YdhUEIaJ/Amn2OP8AHycx+dqPoNJG3CcLOxIu31RSci2BcrMzVB4Myl9Q1d4hiMIb+9grtAlX28qyzq0t7dX3rnFfJF7NCtQRz/iOP1/1pFnHhwcxOPHjwtIJLpxPtDshBsnkBC9oguAGOdHHUFl2o4TTbjOQDizNtZb5haZHxsbK/Ln0n/0/6oFFNfaSRGeM4H838Jgj80k0UA/LiJw0YQpQzsYDH5ElMV3yOwoBWEiUvB5d0Zd3idjtJPza4w788uDoi3z4IyHceZnusJocnLyif1iKNPIyEg562xoaKicjg3ynJubK8lnnxsG2mNPkY+6YV55Cd3Gxka5j6NTDBIHzlKqjvJFVDeQdrvdmJ6ejtXV1YqzZezM1Zve9Ka4detWHB0dxRe+8IXY29srzpiy9Vy84JLuiKhENI68odZM7aLQRBAABdN3OFg7CBecIKuAh4gqJeTXhtgYerOldcT38rFG6BSnGqBDBoO7u7uxuroaOzs7lf4ZiPA8HDh0oukiqPZer1fkY2lpKe7du1dOvjDAsnOwnuR8swt/TIm6iAQ9yCe04DhhGOgDOTiDP1NlNuLYBX5Pn+gfc8MJHQAz5IHTxKHDsR2sOX8TgZrGxFGbKiQCd3NelDQBgJoqQZzm+Ph4BawxLopK0P3h4eHY2dkpzIhtzFXbtXZSRusoTKb6cqjvqjs7MK7h9/43EwsSYZEd0qIojuicJ8E5oFjmm41w6atzEnZAEdUScMbC84wEnTA2D49yRlRLRe14eY6PTiFvQnI3IipHD1GOzJ4W7mHaESplf3+/HELKwbE2zuxRMbqP6G9cdP6Oz/mTo0aoGqJV+sI83b17N+7cuRPn5+fx4MGDomgehxUxIkpujVe5WPZc6YVDJUdgEMX6OQoybZWpQQAHBtDFORgtxsy/iTj8LL/6g9/yfD8DWSDqnJ6eLpE088weqlbrYqOtZQm5531m6ApGlzGZBucz9BWH1Gq1KgfYRlw4VRyarzGwzDpuQ0xD3xk7a4zOEOEgF5ahHM1k4Oh1ZG6cx3Z07UiSaMTVn9Cv6BuykvNKFH6wpQMHA9jCSdA3nC7zn23T0NDFaSrYKec6eV0MYJoI22NDPg2UM5C4rF1rJ8XL4VzQEPHkgaw0DDS/z4lMO6iI6ll8CANGC8Rlo8Gz7fAcESHcNiqgVTsi/9vRnHMqRiUYFB9JY1rLe2WsoNAfvhdzx/8ZJ2hsZGSknFjAaw0wMJOTk6UyCerBB6xicJhTHJUjYaqmyPugWCSFs8P2vJMvMaLG4fM2ZRelRFwAna/5mq+JhYWFcubf+fl55V1aOBycGrkg0KLXm3nl3EOc7v7+fllvv4iQ6wxG7ITtpIzUI6r7rkwDM3bLDM9hDUwV8py6eeb+5AYnJibKPEPLoYtsrqUakj7yHQ7VxtsA0nLOHFsvHQl7nhyxRPQjODtbnsGYuFddFZwddESUHBAFA+RHea4dop1iLpYxAHBqAifkMRFtUv5vqs6b1x314Gx81qULnoicMsgFsLGWBnrOjfsYLvoDOMdmAFCwbwBH09v89qvCSUHX2PPDBWd6LAtDRJ9rdh7KyCgrCCE4aAeDaBqN6Mk5KzsJI0EbSztEruM+rtYiZHeewM/3PbPyZySJkEEJmdcHgVmYrMzQbEZzUAM+7iiif1o9e25ooK7Nzc1SyMJZZSgH1IajY/fH6+b/cy1j87UY9aGhobhz50685S1viampqULxYSgxTNlhm5bDcdFM72BUWCc7LtbUERRr5nU1VWpDZhkySDPNCLAwEieaBXiwni4gMSrnPsjvzMxMocg5zQN6mOIIDO3R0VFFLpAr5oj/M076jTF1Lok5xxBCb0KVMy/WddbD/2YeGLcjV/QFe4L+QQ+32xdvf15cXCzFCMw568P4uK9PkHHFMDJihoPvWA9yfRFRChZ6vV55FYxzsaxnPtnecuV1ta4b+PC9wSu6CwCNiKKTXk8DQ5ycKx2tI3x+lXatnZSjIYf7fBdRPbPKVJsXCSW0Y4AaAmUgVCBiJ6wRBIQAJY6ovnnWfKzpthz9ZGROH53fiehHZDzbQg8a9onZNBKx3W63vJKds8GMrDxG0KCTw1B/PmEBasSoFqcFEmdtMDgknilicHl0PvGbdbDjBUlG9IEFr+Te2dkpu/DpH/M5MzMTX/u1XxtveMMbKntLTCHaIaC4rKWT/I6MWFfmmj/IF9dihB2tGJHbmHtsvk+326+2BIEzFoyvC3EcZbEGVBGypgAMGxnkyi+cBFwgbxwnRV93dnZKObkBi7d/IN92LAZU9Jdx+fU53kBqnWfe7AAdkXo+rfv0D2CUc7mcPzg8PBy7u7uFbnTky9rbruBcM1MDkLLtMH2LUyS3Q998Uj8nxrtSEuqc+7FR3XPkQgk7MuyfwT9nGr7wwgslimT/IZQvfWM8sDgGv1m+7bgua9faSSGAKDsC7GghI0PKSK2soCAWOeICKbCf5+zs4nXTbChkoUmeOiJz0tXKBpJG0b1J0wbHaNDRk51ajm7y74wenbSO6J9ozhFAVN+Q8Eb4QUMRfWTb6/WKQeSMM5wUThInBV1BGTaniKNsp6enBZUNDQ0VpSShi4NiI2i73S6v38AZR/QNDa9a6HQ6pdKObQUYeiiS4eHhWFpaire97W3x5je/ORYXF0vCmvkl6jEVmwERhszr49/yO8blyDZTT85R0EeU3idt9Hq9yvl4lnsMKRG7i3giogA0HNEg9E8uhINKcRLkE3nG5ORk2X/Die5Qfp1OJ7a3twtYOTs7K9Ensp7nwgyIqXjoQvTIuVMMn50a4Mcsg3/LGOucJ+dBGrR5uwhga3R0tJzcTp/sBE3JM0bWh+dBizF+5qfb7ZZc7/n5eamO7PV6sb6+XqHdqYwlv2tgDZh0wZIZnxyR58im17vIv92+fTu+9mu/Nu7evRudTqcUSRHFQ807VwYIdvoD5weYump7zU7qt37rt+InfuIn4hOf+EQ8ePAgfuVXfiW+8zu/s3z/d//u341f/MVfrFzz3ve+Nz72sY+V/29sbMQP//APx6/+6q9Gu92O97///fHTP/3TMTU19Zr6gnEwqsKIsbudkNgGhXxJRJRogFwVRoHIA7TsV0K0Wv2SZhS01WoVAadf5qIxBPzbxoC+8+zsqEyXOAp0GXc+v4xrccwoGL/nsFSiFHIG3tPVbrcrb/rMeQOMFYUOoCacJgliHD8GJKKfT6RwAsCAc8CAUA6LUsGFQzlCu7qYw1SC8y+U7y4tLcVb3/rW+At/4S/E8vJyhdZgzU9P+2fJ0S+QOWtj4874jOBN/RpM4SR8GgjzbqcCQgX48G+/JZp74GBM7+ViD4z30NBQ2YiL8aePRLaskfNTjIWIAhkiZ0L+AZ1gzxtO33lZnJd1wnkR5JVDiqHZqSZD3tFtqv0cTZny8n2RL3JfzoG6EIjjsfiDg/WZeDnXgr632+2iy0RCOHZsDWDDlYfoIBWwm5ub5cT5paWlcg3Ah5PucUBmQNBVFy9hNw1QkA8AJLLS7V6Ukz/33HPx0ksvxezsbGxsbMTW1lY8fPgwHj16FOvr67G5uRnb29slR42dgrlgTfws5P4q7TU7qf39/fiGb/iG+IEf+IH47u/+7trffPu3f3v8x//4H8v/c6nj937v98aDBw/i137t1+L09DS+//u/P37oh34ofvmXf/m1dqcoJouAYmM42MyJQUPQIvpHzCNUOCRQC4iBiYa6IB+DwIL8jdyMSnu9ftLR+ZKIKJU4TqbnzW45kvLnIyMj5ZwvCyMIi31FoD/uA1I8OzsrGyKdOGUOfWo4a+nIiZfW4SxcGNBut8sp1lT/uSIOcMBhpew1m5qaivn5+dje3o6IC8Wl0g5KEGOCEXShg6uwKJtmz9DNmzfjDW94Q7ztbW+LN7zhDTEyMhK7u7vFuCIPbBRlozJ7tzB+pulAziBqIiGDFFB0pl89t0acjoRcJeqIxlSRNwxH9CkzoifLI47O+7+4F8+nxN8U9tnZWSU3hnOEbsXR2OBDF0VEZc8VDsVo2/1HrnMOMyfhM2PB+uSqOT/XOSgcNzm0vb29smGck0RmZ2dLAQOyhAxeVggSESUnylw7KsO58Id8KHp6fHxcToIHqE5PT5eXfroAywCLeXTe1OvF/NhG0rzfCTmBjt/e3o5XXnmlbNheX18v84W8IKfooGl/ZIvPrxpNvWYn9b73vS/e9773XfobNnrWtT/+4z+Oj33sY/G7v/u78U3f9E0REfGzP/uz8R3f8R3xkz/5k3H79u0r9wX0bToP4dvY2KgULWCEMUJGXHh9+FsQZURUFpTvfAoD9BaK7oSoaYtc2OBkOlFLRPUFjQibaSZXLBGJ0d+8v+P09OLUZgyFd9Pv7OwUJ5UjMO7NGB0J+CglKrgQbM8XwAQBXl9fj7GxsVhcXKwYa+7HOoHSFxYWyvFKnU6n0JOMDaMD6uc9RKaosuPb3d2NW7duxdve9rZ429veFktLS4VSMeJGNqBG+RzE75yGaSTWiLUmynduCFRtaph7IY8YQfP59Ic+RUTlVQx+dkS/9B8DhHGE5qN0m/FiYJDtw8PD2NraqkQ8Q0ND5X1F9B+ZNG1GWTrHSXH4qyMd05c0Ss15FrpM9MDL98i/4PgBO8igqxpNozM/jJf5dwEMJ3QMD18ceLy4uFhAFQ5yb28vdnd3S/FAznkZ/NbpEFQ40Th2xO8bA3SyB3FhYaFEVC4ocrSGXbHNYo6xFdg5ZImoztG/N+ru7e3Fw4cP41Of+lS02+24d+9evPLKK/HgwYPY2NgoWzsYmyv8mF9ArUEwtucq7UuSk/rN3/zN8mKzb/u2b4sf//Efj8XFxYiI+PjHPx5zc3PFQUVEvOc974l2ux2/8zu/E9/1Xd915edgDOw0fJ4URgr0yDUR/SQynzlUzvw1QghtFtFXMgSJCMm8OM+JiIow8AfDgiGx8bWzgoZkYTGUKDKfk8SlXygHSW1en8FmVyuwKQQoLu7pPRnMM3+jpBgunA/OAidOP7rdbjktHDoWQ0cekBPNR0dHy5taUQAiMwR/amqqbDAlaiTx74ILjPTdu3fjpZdeilu3bsXo6GhBzSSsXYyCg8WROtKJ6Dsx03p8zt82GC6g8Pow13zOsTtE7KZXnZB3QtwyZdoxJ/OJ4GzQbVgs6xykaopvdHS0nAcHDW6jc3JyEjs7O7G9vR17e3sFQDJHPAvdZF4iorI5ljGQb+t0OjE7O1vycxk4WcdtnJ3nopk6Rc+QQZw+L3Z0PohIa3t7u+i8nYNtiT+jD+RyWbtM76Iv3qCMPMJS8DJO/ngdofZoyBbz4Y2+yALygH2BITFl+fjx4/i///f/FnC7sbEROzs7sbW1VV4KCoh0ZGodcJQLoM97zAa1L7qT+vZv//b47u/+7njxxRfjM5/5TPzTf/pP433ve198/OMfj06nEw8fPowbN25UO/H/58gfPnxYe08QA40jV1wVhMGgGgbunwlhgxmRBMiYxr0ctpu2w5AjDBH9XJPzFEbddclUGw4XbWRUYadA1JK5ZvPNRlVc1263K6dQ2whgWHx6Bs6MA1upZLQRc67MEYX3ZzgCjOgjS/ISW1tbsbCwUMk1oXRjY2Pl1QsUB2AoMZo4LXKYlLFTJGFE6Mhvenq6vC7C9BTO3qdYHB4elvlYWFgooMfRcqvVqtBlOa/iuXHUb1ooR9aABpwANCQgIEdlyI73o5j29RohnxFPHrnFPfgtBhnKjhwaDgbdsiFlDXd3d0vfbYiRf2TfFC0gxvQc4KzX6xUZppLNp/PnvWB1+uY14XOKOQAHzN/w8HCl0IfvvXkZZ4k98dYS5tB2xeOCacg5SezW4eFheVW87QMyB1WOvps+A3TYKdNP8tGsCTqS7Q4MALZibW0ttra2Sv99NBg5eObV+V2fpmL2in+bZrysfdGd1Ac+8IHy76/7uq+Lr//6r4+XXnopfvM3fzPe/e53/5nu+dGPfjQ+8pGP1H5nOg10jbLgrTHwCBx8qQ2pcwYouh0SRQY+AcGIwbuwbZytII5YnLz1M+iLlQ1EidJbKU0V4Gy4P9EIrxJHwHgFR0aOnFbtQyPh6qGHKISwYNJflCCiX76NcXekghOYmpqq5Oh2d3djdHS0FL3Q54goPDz9IOKjQMNJYBtmjMDR0VHJL7Tb/VcgECXiZCP6h7J2u9XjaUZHR8vc4SzJITBmjL9BDcYjOyjW3nlS+m0aF6PjaA2aizyJn4/8IgdmFHCWPNv0pg0MYyTvx+/n5+fLJlPnPbjeYAlHaiNlMIjzRSc9d9ZvaMbt7e1YXV19ItmPUfVY0B1T2TQ7S9YE+iwiKudFuliDNzw7X+fiCUduLp7CeGdHZbnya016vYsqPo6BQsYB58gVkTRO0o7Yc2Ca2RWAjmpsywAVOG5SBsxXr9er2BDsCOCBHDz6a4DN2nqdnta+5CXob3zjG2NpaSk+/elPx7vf/e64efNmPH78uPKbs7Oz2NjYGJjH+vCHPxwf+tCHyv93dnbi7t27JYSG9wSdcG4beZfx8fHyKu+dnZ2yKOZlTRlg3EwTuCLHJ3gbtaD0OfS3gQJhISymKp0MpsGr+6wuHAT/577ej2QkyG/h0qleQjDZoEiEgcMAEePwiU5x1mzmpPkoFmg6nASVhS4yocjF+batra1yckVE/7Uhm5ub5agk7gMipAqr262+ft0OuNPpxAsvvBCzs7Mlr4AjZS25JwUhERHb29vl1OeI/jE+7FdZWlqqIEaU1qjS2wMwqERR7KHxPicqFYkkncvgD58DtpxfsKGngs8ImggbJ2jDwXqgQ8gAICPiwokvLCxUim0yrY4TswPHsObNzxgyO1Y7UGhdmADAhZ2BaW6aqc0cNaKXpAdgWyKinKx/dnZW5DiDNfrpPB7zZ9BjR4atwOijqy78gFa9detWodRgNDY3N8v4bCu8ncAHBtvO2J7xnJwq8HFGOFdOhWE+AULeTI3eef8aVYfIkc9MRV6u2r7kTurVV1+N9fX1uHXrVkREvOtd74qtra34xCc+Ee94xzsiIuI3fuM3otvtxjvf+c7ae2B8c0PoCB0Rgu3t7YI6eIkdDgWFg2cGhWBQUWi4cPP8VJiZyuO+NCdRXURAojTTdjSiiYjq6QKgFO//ciTW6fTLxTlOn/LgiChhOWePmS7BgfNKjXa7vxcJp+ATyzGgs7OzJTrBeUVEiUTJRzDXlLzPzMzE4uJi5bUbXM98n56exurqanE2+/v7JQdAf61EIDciR9aS6iter37nzp342q/92njuuecq73hCWaByeImmi23Yd0WlE7/pdDoxNzdXDOjQ0FDlTdHOKyBHrupzsYT32lD5NTw8XCqrHCVzD+YE9M6YXP5PhRzAABCWaSjujcxsbW3F+vp6eX8S/dnb24tXX3011tbWyuZsIrr9/f3Y2tqKkZGRyincvV6vIgsY852dneh0OkUuydWYJcC5YIzZl+diDZgFAA26bDrdzAl9wrETRQESvJ3l0aNHlUo1U6LIiQsCWAvWCWfAteT6pqenSxERwI6ohc2zt2/fjuPj41hdXY379++XIiKzPbaROc1gQIONZD6wIc7JGTzwf5weQM/2CLnhmCzGnFklZIw+AVi/ZDmpvb29+PSnP13+/7nPfS5+//d/PxYWFmJhYSE+8pGPxPvf//64efNmfOYzn4kf+ZEfiTe96U3x3ve+NyIi3va2t8W3f/u3xw/+4A/Gz//8z8fp6Wl88IMfjA984AOvqbIvIio0RkSU/TpszPQOdTsphOPs7KxUIC0tLcXy8nLZxb21tVWUmWSx0SJJem+oBEVZOHBQ3hfk8+xwrBgQjJ8pAhbbEZbpAlMIIGyX3vsEDPqEgGFkiWKc0DSl4gQv1J5R+vz8fIyMjMT+/n7h05l31sr0HA4ZxQLJkhvCePiECygw02ZEAi4uodycNZqfn48XX3wx3vjGN8bt27fLWkZE2Y/y6quvlrLaTqdTXqg4NzdXSVI7b3RwcBAbGxuVQg9kzBEK42Mc/HHkhgw7GnO+gHHhzFhDnuN8FWsGbcVc2hlgkJ1P4RkbGxuxvr5eTupYWFiIu3fvxvz8fJl7G1VK+Hm1yfz8fCWKYm3YrgFYYzxQ8T4olbXHmTAfi4uLpTSbaP74+Dimp6crBQ4AKFOt9IV58skaNviUW9+/fz/W19cr+SYXu1g3neeK6J/3l1kR9MgOACqOPkClLS8vx8rKSty6dStu3LgRDx48iIiLApOdnZ24d+9eKbDhcOfR0dEnaGfLh4s0ADSAQRdhOGfKpnwiK+fnkGuej07BOiHrZpAIOr5kJei/93u/F9/6rd9a/g8N933f933xcz/3c/EHf/AH8Yu/+IuxtbUVt2/fjr/xN/5G/Kt/9a8qkdAv/dIvxQc/+MF497vfHe32xWben/mZn3mtXSmGzzRHRFRQJaEpm3Hn5+eLUaZCZ2FhoVJqSniOUYTionnBcUjkhbwfAgWJiMLTgwBN+0T0ud466sU0oYUOVIpx4TpeEudCB5rRdsTFiwnpC4Jrw4nSOU8Axddut2NxcbE4KugRo282IbJ5FCTJPZ1zYa6h15zPiejTmzbqEdXT6jHGzDNv8H3uuecKuveBp5RKf+5zn4tXX301hoaG4saNG3Hnzp3yriworxxxnJ+fx+7ubmxvb5dNpzZMyIeNgyszHUlZmb1HinERnXkjr4266UXnBDBCgAAiV2TDTn17ezs2NzdjY2OjnHo9Pz9fKiJ5NQtOb2NjIx48eBAPHjwo0TMyjC6YFgOk+UQT9NY5RUAbyJ8xwoAsLS0VnedFk1D9PAcDio3AGeFkmB/WBKfBeu7s7MT6+nrZ4uB8En0xBQgz4fyygRMRCDozPz9fnDX0+fT0dKXIhN/DXExMTBQd4G8qQR09joyMlP4wBzhCl5djW0yhe2xmbJhvZAYQAdhkvbA3zAXAPrNDEdX9WZe11+ykvuVbvuXSpNf/+B//46n3WFhY+DNt3K1rGDrTc3kjJX/w4N1utxgdFgc0QVSEMKM4/B7lMieLADqJmROpNKIdc+kR/dMjjNoQEqiFXLkV0X9HFkifPSR2ZDgb0PPY2FjMzMwUp+BCDMaXnYTpS5AgFJvf7YPxI0908+bNuHnzZjmYlOgGw+MiFZ+wzLO9p4jqQKJHFCI7cRvx2dnZeO655+L27dsxNTVVEF5EFKppfX09VldX4+TkJBYWFsq7sgAzRHj018YuImJrayvm5ubKHLq4BWfk/CZGAhTqiIF7eJO515vvuI8PbgUosU7IsalHI2nkmrLi9fX1UlYcEeWAU1gSStBhKLrdi5JkgznGj2wi6879UtU3PDxc8hXMM4bZ8o+B5DPug4F+9OhR2QCOPuN80R9H3ejF2NhYYRtwTpRX43Rz/ow+MD5ytlD4jhJYe9gJoliKg8ifA9pgJnBSBwcHsbm5WcaDHBDF5AKobrdbOXAAuYqI4sRxgswH47KdweYR5WY7aluG7CFPLrpA3pgb04re6vG0dq3P7ovon6RNEh8PjhE0B41TIPfAAnCdFdjVLnxmh2NE5WRvRJWLzWE3xtgnTJgSyPwtxi4nHjFyfrVFRL+sHWXGuPt9Sq7Qs/FAoBA2KrOcbDV1acqScfO7iKggOIf7PsbJToqycOYV9IUxcIGF+W+MWK7sGhm5eAfS8vJy3Lx5M2ZnZ+P09DQ2NjbKuHmZXbd7sX9raWkpZmdno9PpVE6Bx7mZ9kP2ZmZmioHEOGEQHHVhID0my4UjKxwhBitXjeKomDuDI68j8mkHhfEiib+zs1OOtuFUDfKLGCKDLsbfarViamoqbty4EcPDw7G9vR2np6fFUJr2Rt6RP1e0UdDjpL/n0U6PqIX5AGQsLCwUuXKpNfLnOXbui5c1Pn78uNDUpiGdbzbdDTB2NSPRDjlh7M3h4WGZG9N8jAl6LOICGBCpsj4GnaOjo4UZwqGT82UTfEQUhuD8/PyJKMpO2xEuVY7YE6pcidiJkJ1/Io2CfDhXaCYA2YXdApxdpV1rJ0VY6VJZDIMTrqbSqKxh4oz+aZlH5g9RGjQbz3BIi3F1ZZ8rzRzGR/TfAYWxwiGgyAgsfeE66MpcdoxDQLERZpwUikyhBMqLACNwKESv1yt7UoaGhkrCl2ojKwt9ZBzkLDY3NwuqhRrECJl2QElMcWEoTH9hECL6Qs8f5o8/HCWzvLwcMzMz8ejRoxI1eQ/M3NxcGRsUnylaqDCX3ZLz4Dq/ioSxRfTPLHMSmXk1IHDlFvfPYMlOz3ku5s80N3JtkIAsMAaMkV8zj/OAKqSQBjSOIev1eoXmJB/B1gI2jgPKXGnqfmbGA8Rth4ZccvoCOsw87e7uxubmZpl7oimiPpw498IJ7u7uxr179+Lzn/98PHr0qFSxuVwf4GWb4OKBrC9Uyi4vLxcwR+5ydHQ0VldXy3wy/m63W/J6OJOZmZmykRy54fgz5B6HyNaRW7duxeLiYnS73XIQ7cHBQWU8TlXkfCYyyQG7yIlzlrmQJ9tLA2znAc0KtNv9rRVXadfaSVnAQSQoEQtiGgvUQ9IUDpu9QxhLHAfN0RKOAwSb0TO/j+gbEhYE5xMRFZSOABDZeXMfiMPloRH95KQjNofbRFFQFkblOHWMh5E6goMim5bCQVOpyf2hw4j4tra2Kkb44OCgKBInmrtKCoVhrlAY76jHYJkHByFjCFzG7PUjAqRoA0qL6G1kZCTu3r1bDlt16S/rQ5ThnADOe3V1NWZmZsqcQykbXdqY2YF5DnAajBGZtuFmXRzlInNExlDQGWC5am97e7sCfsweUJQDZbi+vl7mlC0KrVarVM5OTEyUKlByLuT/6PfMzEy0Wq1i5JAX9Mgn5ONIGAunibCpFKoZveZ7aDOqcNFxV1Q6Kn7w4EF88pOfjM9//vOV6kJTX8y3C1rQJ+eTiaKgSG/cuFG2vZydnZVKwU9/+tNx7969ePjwYYyNjcXy8nKJjtj2MTQ0FLdv3y5rjKPlLEmDtuXl5RgeHo75+flYWlqKycnJIrcG36yt9Y3G/ACMiK4pknC+l7ym7YRtInpHn7HDzL1zoZnGHtSutZPCaztXFNGPsMypmtpy0tmllEabpv6gPzL6pdKPiYe+MjVC/ur09LRC3xmhgJaIhIiiUFAUO1dlueCBceOwI6I4X+feyBvgWDCMFqKIaliO44aigZLA8OMwSaZvb29X0CtbAOwoQI7O29Bf1i07KO7p8dJH6NBc4AKAIEpg3Kzn+fl5KdOmQu3hw4exsbFRqvRwGnYOjmQ2NjZKMQD0H4AFmXJezwbYig0tS6UVa+EcK79nLok4WUfkjznDIJN3oSCAc9fIa7nKi6pVNj6fnp7G1tZWjI6OFlqNSIu8yYMHD+L09LSUTvN2ZtaAdWd9vUZQR0RjLlI4PT0teafV1dWyTxGAAtCj/B2DaJ2HymaODg4OisN45ZVXSsQCKGT7hCN8nkX+DJ3ADgHgqPIcHR0tThxjfevWrVIhuba2FqenFyftLy8vR7fbjZdffjm2trai1WqVPXhUHA8NXZzKs7y8HOfn5zEzMxMrKyuVaJl8Lvm1PI5M8wGaoCAdyTvvnvPqZ2dnZVsGhR2AXebdwBcZANgh11+yEvRnqVHFxYvtIvonhrtSBaQI/USif39/vzgJDq5kYUz/ETFhVJyQ5HcucnCeiWt7vV75G6NCdAcn7ERxRD/vxXWmxnAYUJxU1yFARluUhzphDe2HkCLERl4RF0UuvLICJWRT4cnJSbkH+4gQPMqf2bfFqw7Yh+UqNRwo4/cZhPSFPoLOXd3HPDEm1rndbpc3xb766qtlbPPz8zE/P1/ui7FZW1uLz33uc7G6ulqc2fn5ednSwPlkjjr43vkkqBkQeC6S4XemPTAMpgWRJxyjFRxjHdF/nQyJf/IIOBHoGyJVCg7yO5OgnSgkevOb3xw3btwohpZIY35+Pnq9XqyursYXvvCFuHfvXnS73XjjG98Yzz33XKysrDzx8j2Dshwh4myN8jGcUGWPHz+uFB6Mj48XSgqK0iXljnZ47sHBQakGvH//fjx48KBsOsWOrK2txdraWimiYm5ZF6+nc4TOKcIwIAPMA7mqycnJ+OQnP1kABnJ69+7dshZveMMb4s6dO2VrR6vVKmBvaGioFF4APh48eBBra2uxvr5eIk5vwAcwMIeumoXyNVh3rnp+fj5mZmYquVQiVxionF8CwKHfgIrXUjBBu9ZOCv4UJEQJeUT1zZMRfUPGYiHEbE4dGhoqSVNQL2ggor9zG2GHfiPygR4AqZl+6XQ6JQcU0T/qxYluOzZXduFknMPiyCCoBJK0oCEiG4wgdJfPCoOm4Rl8nmmflZWVuH37dkxMTMTJyUmsr6/HZz/72UJ1EUEyrk6nUzbtTk9PFxoMqtVnKLrAgmiGaAyjinGAgweR81nEkzmOs7OzUuBBscQXvvCFaLVa5fULHNnCqwbW1tbiU5/6VNy7d69cj/GiL0ahGEDKkHd2dioFMQYedZQTfTfF6TEiFzlPAKgZHh4uVGXERWS8sbERDx8+jK2trRK9k/y2Hvj0koj+WX0Y+OPj47h//34pxb9161bZV9jtdouB+vznPx/37t2Lo6OjeP755+POnTtlSwKRVkT/1GvmBBBm+hqHxG/RI29E55pM9e3t7RUZhlojT0ZU69wadGerdbHJ+/z8PF555ZVYW1uLR48exdHRURkv82ewx5zbVtAow4/osxFEVxxa+7a3vS1GR0fjC1/4Quzu7sbLL79cTjl/8cUXy7zs7u6WqNiVvwC5ra2tePToUdy7dy9effXVWF1dLVE46+szH5kzdB1dYdO+0xXDw/1DqSkmAkQgkxsbG3H//v3Y3t4u9pXvsb+2b3xPM9C8rF1rJ+Xk9eTkZEEuLojwxjaQkMsqMTwYOBtzQnwqBjEKx8fHJXpD8XBg8OWmdBxqG1UTgbiBrM/OzioVOaAanyV3dnZWcS4827kJnIKpL3+P0kPnGRUR4TjXdP/+/Xj06FH0er2YmZmJsbGxsokaLhznRPKc/BJG3cYcY8vvoRGy8eY9VBF9ms9ryNxxIgSOz/Qi1WjMJ8b/1Vdfjc9+9rPx+c9/vmwMharhoFnnEw1eUEgOHmVcIFgAEdcig6wtTiuiemI0hjFXWnE9jfXjKCWMBdGgwRr9JNdAFAPwAZ0zZgoqiFbIb1I0s7GxEd1uN1ZWVuKNb3xj3Lhxo3JcVUR1i0Qu0omI4liOjo5ie3u7gE7T3M5XRkTZIgFlxd47IkfuzVYLqFhHlb1eL+bn52NsbCxWV1djdXU1Njc34+zsrJwggsygBzhfaDV0yUyNq4bpI9sT0IWxsbFYWVmJnZ2dePXVV+Px48ext7cXzz//fKysrMTp6Wl5mSDFEUQyyN/W1lY8ePAgXn311bh//36JoGmuqswbZ3Gs3usEvUq/AbBTU1Ol0hXAhb0gBwczEhFF9l14wnfoMrbSQOmydq2dlKtGIvrFBCiJqTXzskQBUCwYRhAuCNjJ94jqad/cyzkOqEOX/kb0q7W4B3+joBi6XO1GI/KgzJS9FNAQRE/8ltyNuWD+T/8RXJAOxiOiX92EMpKfAWlCCRltUkJMct30oqseHTEODw8XcMG5fxhE+oURRWnswGiOaohyvXYkpVE2DCc0yac+9an47Gc/G3t7e+UtrGwARVZwPshdRFTWCYpnZGSkkrMhwkY2udZ5SMbr0lwMMZ+72s3K7go4chZLS0vx4MGDcnYl8gHdxV4gU83T09Pxhje8IVZWVkoVXbvdjsePH5dCB86tQ75I2N++fTtu3bpVOTIMqok8lAt3XOVIlRxnxJGwd0RAxESuDIPJXCKDW1tbJdd5fHwcQ0NDRV8MODHCERGbm5vxyiuvxOrqanFQc3NzRfYZE/Puyj4+Zz4AT0RtrD96x747fjs3N1derAqtiTPa3t6O8/PzUoAyNTVViml4x9ODBw/i8ePHRT+J9Fxcg9yadQCIAgIMRgFUXE9Rx/b2drEnpkF9DBi2zlWLpjTpB8/xuZ+XtWvtpBA6kDoCiGHMexBMS4FKQJeOLHBshOsoipPSEX20YscDkoyohr44ERddsHCu8rMxd+6FKAqUz+9yKaedIxEDhoEkMgfQYnh8LcbPhQCU+FIUAd2E0XIuD4eCg2KOmCcqhKBo6S/PwiDaIBORmPZiPKZlmWdfDzUBNUOCHfR9//79eOWVV2JjY6OAAPJnNpZGzE7s40hxON67RpUcSgmNhSNy6X5E9fBaQAtrQTLe5+E5YmeeIyJu3LgRN2/eLCDGeYTNzc149OhRMXBEBLOzs/Hiiy/Gm9/85jg6Oir01+rqajx48KA8jypNb/RdWVkpUS7OibkhAQ9IInmOI0H/eC0Ie6ZcYNHr9YpBxTlCVQEUzs7OCj3GW4Hb7XZ5qy0NYDQyMhI7Ozvx6NGjePnll+Pg4KDk26anp0uuEpqbSIk+ZHDJmpj2pwiCXN709HSF4ZmcnIybN29Gq9WK9fX1khPj7FDkGnsBI/Do0aN4+PBheTNut9st+V+of/TGxRuAOxyE5RowC4tihwSdbVCQy9Cdc3WRBc/j5At+58Kop7Vr7aRQdJxIRJRKPCbDNB+LDvo1J8pv4MK9kdF7Tvb398sJ0igi947o87k2Pk4eI+AYZ3Jk9MtGHSMMkjINxXMRAE4JMJ3k6jEc0MTERDmT7vz8PDY2NkoSGyWjKIP5pSrMr1mPiCLoPI9XDUxPT1e4cGgH6CtXK6IcrgRbWlqK6enpyp4MHA10kOlL2tnZWTHqIGg+Bz0+fvy4RLy7u7sVFHrjxo1YXFyMoaGh4sw44smRLXmpiCjOmPWH5oi4UFzoRZ9zBjDg6CBXQ7lalIrImZmZmJ6eLnJnzt9ULqCAU7QxBOQCccwPHz4sp0ewn2ZiYiIWFhbizp07xdFSds/5lryTbGlpKVZWVkpCHSPobRGAMW+TwAHTH3QNqpgIjlNJYEWgcV1oQ1SD3phuo7INGSVqbbfbpQqt0+mUQpmdnZ2y140o6uzsrOgB4MGFL66M9ckW/I3ztSygAzgpdBF9evz4caytrcXs7GxERCUSgjl58OBBOVOQQ3tnZmYqDso57YmJiVhZWSkVheSPsAcGXowHoEiU7WictUP+6CO/i+gzR7a/llHLxFXatXZSTlKa7oKXdmWfkSfOh6jHBjoinnhtgCkWDnG088IY838LCYYUtG3FgpsHhUf0T7l2CTP7I6ampopA4CTz+W3c1/QUdBV5i1u3bsXy8nLZ9wP3ToTQ6XQqyul+MY8IbK/XK0cjTUxMxPz8fMltmOJykQF0DdWVUCNzc3Nx9+7dcogoJwGsr6+X30Y8mQz2M9iTg6O049/Y2Iitra14/Phx4drPzs5ieno6RkZGyqu5QfQcLdPtdosjAzw4ke4yY6Ne8ore7+Z9c/zechBRPYST6jNXrhnk8Dzn6bjWm7AdJdLnsbGxePnll0uuaXt7O9bX1wtixzFxgO7CwkI899xzcevWreKwvCGa8SBHjMeUp090wEn5La87OzuVsxcxalwDCGO9HY26ghB9JK/GvHo99/b2SuSyuLgYS0tL5agkckfYFaIvaGcoSjZ901/00NsyMNgRFyCSg3DJz/JiTSpfAYrkx3u9XtkUv7a2Vs7q41qzItB4yDX95hiptbW1sjbkOjnDlDGZqXBRk+leF3t5/p3nQh582gjrgq26SrvWTgraCyfjiCn/mwaCgPpyxJGPwcHJudAARBQRBXWwkdGRGBEGSAMjhnKigHZuCFNEdf/I9PR0eRGgE5I0K6epBVdZkXcgWmBTrd/wyT1RMAsR/YHCMbXmXBYCzVgdIdBvDGtEvxSbeXJpvPckgap51w9RJIrJWhhhQw3RP06NYC6oPORkAAyAkSIGFoDhsmLz9jwDFEmURo6LqAgK0rQu64Mim6pkDgFOjtgcdXutoMcw+Bg9IgNABHP98ssvx/b2dvzBH/xBbGxsFBmYmZmJl156KW7duhUzMzMR0T99H+TsYghXuiLTlqPMbCBTROvQVxh8wJedO/JELmRvb684SFgFZAdgwBoS3UDHYehXVlZiZWWlnPQNuOA8wKGhoZiZmSmnO6DnOLqNjY1yrBSOhrkxxUbURWk5OVT6yNuoWTPGv7+/X/a2URTkQo6IKJV+gBjGAcAdHx+vPamDzdHeskOunRM4zs7OSoSJbgJM0WlkkAicClM7Jz/bbMDT2rV2Uj4mhMWJ6FMzGFIjXOdrmCj/25V+CDNHzsNjk8MCKRHuu0zXzpDKIlehIaD0i3FkKonCAoTAiAxDQEWRHRSv4KDCzlVKjMtzw1hQdBsX52BI8oKo+N5RAcUjzLXnnShhZGSkRF2g07Ozs3j55ZdjbW0tIvp0onOAjhwjouJgQb1Gr0SKjx49KvRVRBQldMGG1xaDiwL6BAMoOkdyOSKOiHIUDsaCCkU7Fn5vJwX9R9TpnA6Oycf+uGIz4sLB7OzsVKhDR/WUuYOeoQFfeeWV2N7eLqXnL730Urz44ouxuLgYvV6vIPgs45ZhZAk5cg6WeQRgAFh6vV6Zf+taRJTkPKAPB2F5jahGL3aG1kuADGtHjpcS69HR0XIq+fj4eNy6davsD5yamiosCjoKzbu7uxuPHz8u1Xbki3jBKvv2fHzbG9/4xvJiT37D2mLHmJeNjY0CoNg+AguA4wFcMTcGCeTbnC/0O+PYUEw0ZpoYJ+oqV/oMCHTUd35+Xhye91MiM+gvzMBV2rV2Ui51dNiJsoLyIvqRgLlQ52JAYi4wwMHwOUaEChtHCtwbg2CkDM1AdZKNP4aN59lwgeZIvju6i+gfuwQlR+5qbm6u5GTIY0T0z5MjbPcGPiJJn0QNtWU0xHj5HDrLRtPUFc+2I6PknNxTp9OpVGdxP8bKyxyJ4hB6U2YZgHjeHz9+HPfv3y8VX5Q8O1/HPECxYcgjLiJEog/myhFERJTCEfrS6128MuXBgwdxdnYWN27ciPn5+eLoADkYU8sZ6w8Ayo4m07k0R7rkEzAY9MkRDJHv7OxszMzMlBzZ3bt34+1vf3u88MILpSKN0wvou+faOaHsJBzh0R8+Yx2pOoS+dy6Y0zKI2pl/F14YsGXWxFs+7NBYJ+so8sv5e3fu3ClRNg0n4CIkCpGgU6enp2N6ejo2NzdjZ2enUMfsLUIf2CgNIKFQBx2jOtM0LLnaXDBFzo/qVsa6ubkZq6urZYxEP1DavV6vALVcjTgyMlLZt2gmCEoU22TbOz4+XjZ840SZb++PJAp8WrvWTsqJOpQDRUWwXDDB9xF9o+nvED7TFqYMHRkZRZvjtYMyyiXHk8tVnTvjWvoHTQPtZWUhqoF/5norHobJ80IUZQW348v0ZsSTrxdxRAEFQO4ENOUycaJU+jE9PV32qOAs9/f3yynjIECeRUFGt3txBBG/8bqgWPTVxSrcPyIqiI81wjiZFp2ZmSlKRJ/JxdmR4wjJ/zD/jIv1wahl5+IIzBWDGGqMhkEYzYaKqK/dbpcomTlhDMicI2hvbWi323Hnzp34uq/7unjLW95Syp6JQKGvyZOA2B3lMK/0P1eoIbuO+jCYRBPINsYw7/diXakSzc4pg1ae4+cin8hCq9UqFBZGdnZ2tjgQolI7Xww2Bn5hYaHMA3rhKlcc1e7ubtnIy5mFlqvR0dGyiZmyfErAI6JEZXaYyPzx8XHZnBsRxdEAgJEHR0Knp6flSCmYg9nZ2ZJmmJ6eLqXy5A2dHgH0khPudDqF8gcUYgNdDv9V4aQIS63cRDQRVZSHotQpuytQECgMqyMAJ2wxUNnARETFUdlhmBt3BMhi8hs7K8bhceForNwoGhEbUYOF2I7VTpq+OrdiZEwfoKT4rZ2x83su/Uc5aDgBECSUCErFPZx891wzh/wx9cJ8m750pVxEFCOEw3XUFhGFw5+fny+KRqSLA/ApDlAnzhV5HUC0ftW6ldW0jA0tsuj1QHbg/lut/ssLoZ74jv5k8OOkNfPKaS2Tk5Pxpje9Kb7ma76mnAvns+oAAF5j1oF7GYXbKZrJQNYpYKCaj3FCyzmSzDlCnIdP4Xe1Gg7JfWTNybnwPGwDFY6wF9D0RN1mbs7Pz4vTwRmRuwIEev6ZOxwPbxDgNArsGWuay/NJDWDT0HHGCUgkWjE4dgk+zYcEDA0NVfJophx5BQ1FRVDdnU6n5PcyUEF2KU7qdruVamnW07T9Ze1aOylorkw5GM1kao0J5DN/h7JH9JGXKRIog4xEmfRMgfBvhJSqL0dj/nfOL5hec/IZRLO5uVmqi7xvgX5lysf7EpzDiIiKo4GbZgc+KJLfueTUkReOxJETc8B30IIoORs9I6KgTxpInPwGnzE2OyuUExnwZlAq/s7OzgrN6ONy4OonJyfLC/4oVPH35M0wQqZXmEsbZhdzbG1tlfwi1YRQx6yd6UfLo+eT3zmycHUn0Y2pNkf+NNPgjvLu3LlT3sDrXBBO1ethPbD8mipnTixr6BVyDMWFc4d2Zs0ZF/dCllkH0H9+Brpt+WAc6CxFTewpIkcKgKLK0fvVcK5UKjIewM/U1FR51QYRC2sJcOR0DTbTIjd8z5p7LtBnA0UAGs8ECOTzOp1acORJROiiCqp2YSHY3O5tIiMjI+WN1WZybFdxTDjoiAuQRATs9bqsXWsndXx8XBLSJIFBtUbkNiCeSIQrop+zwhDY4OP9cVB1xhklQRAwNPzWjpO+gPz9/4x8nauI6L8PiFdcg+YIuV0ZdXZ2VvYKObqB2sj5KlfW0SfKSk0ruWDCuTfm28UDNM8Tx0rlUn/Gy++538nJxRt9UWTKkl1ujKHG6YFwmUtOkFheXo7nn3++vCJhb28vHj9+HJ1OJ27duhU3btwoHD3Pc+FGRJ9q2tvbK4YU58EYQMLMk18nMTc3V94/5Y3n3MMlvIzP+VQX6xDh8TlAxIU2BjqmR5lr5HxkZKTkGNiz5LJjnsFaoWPk8HxIcAZ+9IcojM2uvKMLAIDxZ/zouQGn6UAzJDzTBtm5kpyzJCfnY7wAOhhSHBSRJkDTwIX1p8qX4hTnbKG2zFA4mkDPKFawbcpRMef8oYtQtuRRKbjy+YmshWUTZ8iWA+ad76EBd3d3y4s9XciFoyKqxyGxTmYDkDfnkL8q6D4SlZSbMslU8DhfZMrLC2Rlwih5n5OTvEZFTLopr7wXij8sPELFH0dbGFQXBWBcXCwAeic8B/G6Aozng3hxvPDwIEkiG/rtIoxc8msq04UdzuVE9Is5XDod0XdSrkQyNYFhoJrPe8XskGyAuC+GkNMxTk5OSsKbqDAiyhE+zz33XCwuLhajjaF64YUXYnZ2tlBOzBHrbCABEKLv5IFoOAXWHAS5tbUVa2trBSB4MzCGK0cpzvFg5LwZGkfE+lnGDLqyw8vgg7HYWLJh1LkEl9278MBsg2la/0G21tfX4/79+7G6ulrm2vuOaDgurjVtyfozTu/NMe3r+RkeHq68xZa3NrPvCyeKbrnqEvvg09edPsjpAUe4zJvPn0Q3cUau1GVNnJPlLcjPPfdc6a+BMg3dMfAz0LD9Q6at696/trGxUdaEEz0AHDA0ppoNsm1zkUMDFzYtP61daydFCMoEMIG9Xr+qhMiCjXggIS8ci+mEP5Pt71BERw0gKATNfHtEP/Q1d4+w88evn+B3GCPTbY7khob6r4DHsLVarSf2RkFNuOQXZ3h0dFT6i4LkN4QaGUX0jQTKQxFFRFQcrJ1jRPUkBpfb2sD4tzZqjB0nhjI4EuD/GGrnzKAR/WK4iCi8PuXwExMTZR5A0c77uIrTNJijdvriz3AuKPr9+/eLoeCEcWTMEZkNCoaQOYVKZH7oH7KBHvCZozqDGUcKFIs4AjNFDjWW5cLFGIwX8ME1rNnh4WE8fPgwPv/5z8cXvvCFePjwYaU8O4MDDCZy4hJ9A01kjmdiSJFznK0r+F544YVYWVmJxcXFYktcWWg9dtEE9oF58PhsR9hHBaCEdoZmhk4nZwPNiF3CObGhGhqacnjrD9EpNqIuFWKQh54xH1DQ3I+cN3ueoCbRRespG8fzvQ1cbA8BZzjsp7Vr7aRANbkcFWHMh3g6P0HyEeVCwFBCFtTUnhfRyIBFjYiKI0LgMZY4CBsjI7F2u13yNRgR52wwFhYAnBwOGMdhI5IpTUcDOHFoRKIcCghc6ZjpTZcjm3rL1B1G1bkDkKkjh4io5JVs4Jln+mtqkfEZXDBenwLNu3mMWHH2nU6n7APyWCL6uTx/Rp8weBzV5NyJc0eMCRDAXIyOjpZyXcsqDpq8C+MH6VKS7aiFeWAuvAb0286TAh4MOkcvZUNsqgzZJnJ37pF7QSXbWURc7Hl69OhRfOYzn4lPfepT8YUvfCG2trZKXwEm1mfT66wDcwQQYq5c2DGI+kMvocTIr6LfExMTZezIlufQDpt1tmyenvaPZuLEFA7r5RQUb6RGn3BGbPj23ixvcodSzakLAK/nLBcSZSBhJ4djJDpyEczs7GwpcME+WO+ca/Pn7pfBDc/KWygGtWvtpJh0l1STb2Exc57EKDOiz9Wy8HC4psci+u+hiqhGXKYXoEryXhL6Uec0ENi8gDSMgY9D4pkYQAscDojf5GfTbKhyXorx4uj4DNRN2aqNt/NFfJadlMftSAtDZ3oKwTYtaoPKMxgDQMGAhHtgMMlLYbCIBhkbrxqhjy5gsLEy5w7oIdL2yfT0D0BgI9Fut+Phw4cFEHFUjg0P12FgTONGRIliDZicL8xRvKMiogwaBopoxy+exEGcnp6WYhIMooGJixOQH/pzdnZWXk3xhS98Ie7fv19OO8BYmeI2DWZ2gmczZssG/7Zj8zzkarednZ3iVBk/INFzasPr51kPTcNvb2/H/fv3y2ttoCtdQDE6OlrO1KMyj7wYTh7gieyY3alLKxjMGZC6AZqxg9iUnCMnajXQ43uieIM5tpN4W0DWW2+lQf+u0q69k8I4obhGo6aNLHSgDRtCOxQnmnMIb7ScnVAW5szR0pzboCQaxbHjcZUff1xBh0BlWtJoPjsnmgU6IirOxUnQTqdTOaGASAdqBiG1wNsQ29DixBwZ5Plyn/g3c2B+21SfqVHW1rQtRsGluf6MfKarlLxmRtXONxgcWMnJESKfNpbOkdihLi0tVfZl5Xxgvp7+E3k4b8h1dlhUiNFvKCdHdZQeUxhitO58D/eMqFKzlnmvX7d7cTI5m6o5HDWiD4agc5EN1jzrkGWbvrg/njNTd8gPc0ZUFxFx8+bNyutVWANApwGC84aMH0aHwhiOKOIdVdDqrA/5JQogTM8PDw9XKHtHjOiCnZTBsoEDfXN07VylWRHPpeUOR8I9Tk5OyukwOJ6IKFFfRFRe25N12MU8jtqe1q61kzJiteGP6O85cISBo0JhTZ+BXFGYiCqaNtqPiIoxc7Rmw+bfRESlnxFRkCdOyqXecL0YfhtD+gbt4Mo+KCj6YCF1szPI9CH7TugHkR7PpY+MCQMHUqrbt2JFQPG4f44AeQ79ZF6NCu0Es/FnQ6RpVo/Fez3qqFk399l0IgYFapk+2Viap8eZ82/oVZzZ0dFRyY0wh85PZdBjQGCnF9EHHDwbmd/Z2Sl6MzU1Vajydrtd0LtZApC0qUYMoZF6rmyFisQgUSjBkUG8mp1ybpyYz7y08fTzHSV4jAYRBoushalAnnd6elpeikiuJ6JPsXIKBuvkvVvQ+y76wUmx+XZ7e7s4XketRN8U8IyNjRUaFxuBjPhvrwHz7L2M/MbMhmUn0/TWHcAJf3q9/vYV5LFOZxgLbx4/Pj6O8fHxcipGRJ965t9QkV81TioiKkbZ+5xQloioHMdBkYGRFsgTIcawRlSNjxc+G007ypyHMq9t5O2Fz/w3VKAFyt8TYpNLgu4CJTtnRp8zErZT8JhNp+RoyDSneXoba4yQo4gs5I4W+Z3L7XNfbIBMYUVUj8JCDrzj304dhIqxoT9EVY5KjDBtDBw9Gl1jNDAiJJs93zil8/PzctIG70BaXl4ur5NgLG6WHwylwRp9tYMyHYXR9N4k9ofxwj3nqsh7Wd7pm51FjuAd5XD69iuvvBKPHz8ulZ2dTv8dSbyE0Xrphj4bNLDuzo0ZGPK5DTPRETZhdnY2VlZWYnl5OaampgrV6erD7e3tEh3bUSHTgDvm1UcTAShw1uQuOXWFvC82iajJm4Ej+u9rMojIIJ01Qi8Mil3k4D1L+XrkMyIqZ0MaSBqwAbLNUAC4+Y0pa3Sk1Wp9dZSgm9KgufKIwgOQCCcdjIyMlJMaWHBPuiMjGyuH0l58OyPzxrm6xbSFoyIE3BSVn0t/aDlvwjMYJ8pQ1+wUuBdCwz05SsU5nnzSgjf0ZoqV+cjGJqNvO0wnfLnPIKrS/XZFYET/yB1yUOwXgfeP6J+J52INv34lo1PWiM+QGxto5hbg4O8wTDkiwOBwbhtInFMPSJx3u91KtSHzaqqHOfGcmQbEaVE+fXBwENPT07GwsBA3btwo+8a2trZq5cTr5GIiPue7bNDo5/b2djx69CjW1tbKQbLkcDhDkqiE+XVkxDobIKHj2SBb74gSAXvca2ZmJu7evRtf93VfF29605tiaWkput1ueR3G5z73ufjc5z4Xq6ur5SWZrkB1DtB5UlcUc8qIKTuXiudcLTplOttyZNATEZU1ADRhS6wX6JxL6bND5xnZWXFeI2N1Tpo+sX7cH3DIeH2YAHYuA5nL2rV2UmNjYyXZ7XyAOe52u12qbfb392N+fr4smhEQCW9ODI7oI1SE33kgV+f5PDY7EPP59MXHB3Ev51MwNFA0Ef2KLBsMfk8uxfej/BVHkSNFI01XaYGceamiz0zDiZBQRwAd5dBX0Kr38qBMKJ937+MwfHIGhgijQ7NxcuI2Izw7AyroQHhEMSBs54ByJJWLHVBeDI/PsaNKC6fH3xhiF+KYnz87OytlygcHB7G+vh4LCwvx/PPPV95fRn9MYXpOHd05N4c88Cciyl6h27dvFwdFFGBgQv8wSkSeOTIxRW4jyxj9dufNzc1CoSG7yAJ7s0x7W/YdSdp5oaOmxfnM518ODQ2VFwH+xb/4F+Od73xnvPDCC9HtdmN1dTU++9nPxp/+6Z/Gpz71qXj48GFxUNYFA0McpHM8PN99R0aInj//+c/H2dnFwcNUVWLkkY26vBNzYgBhKg/w5Oo+GrS8P7NTciEMzdSmwRgFFOvr67G5uVlO7OBVPRRaDA0NldNb0BnspvcVXtautZMaGRmpJFrhTh1mE35iTNbW1opBdrEAobvzARYwGwdHIY4YcDAIpNG9kaGF3EnKiKgIiBfRfDpjdAk9CdccXTpacZI7or+/xrmYTB3wx5EPjrEuPxDRjx7odz6J2xGX8xjeQJypLlMWnvucm+Lvk5OTcqr07OxsZe5arf5+MkrSHTUyb9yL/5tqYhwYA2+epGKNeWPucj6P4gRHSORL2edHUQXbDHCQ5AMy/YpTIFLhrDj265yfn8f8/Hw899xz8YY3vCGWlpZieHi4vBLi4OCggDzWmHHyf9OcrAXyxZo4auS16Jubm5XDUdExgA19ZYzcGyBhMOH8HPewgzIVzO+JdCcmJmJxcTFeeOGFuHPnTrTb7bh371588pOfjD/5kz+Jz372s8VBkVtx1BJRPU/TBt40do62xsbGKrkujjaj9HxsbKxsMibqtx47v55ZCkePrq7kc/rsissMMI+Pj0uhh6Mm57q87wy54vU3vH+L1wTxahoYDfqDvbIuXNautZOK6CMBFhB0hdCaU+31eoV3xtDyOUpnI+V8TkQ8gUxM3xnVO+di6subXR1Z8P+MkDKViZH1iQQowOTkZDFqjMehtsN1jCXRhKNKBKfdbpdkaEQUR8pc25BQys1+Ix+syjyaKkWBQWigdOf1UC7PCWP1etnh85ucWD45uTguCzRtSoJrUXobNwOG7KTcN0fmjMF5G2TFr33odvvFAn4WFODe3l68+uqrcXZ2sadrYWGhlCSbMvaePsZKhRVJfBdITE9Px+3bt+OFF16ImzdvFgflk84dARitGzj49BKAiEEfUdfR0VE8evQoHj16VE4swOByTxxz3UGuOHGuobks3UDA+UpTtV4zZJUXfm5tbcVnP/vZ+OxnPxuvvvpqoSTZwIouOkI3ILOxRU6QcXQbHWGtjo6OYm1tLY6OjuLx48dFJpeXl+P27dvlvWOmxUzReY0MqLK+ANRZM+QDpgZmZHh4OHZ3d+PBgwext7cXrVarspeL+SXSBWhQMHJ0dBQjIyOxublZHBNv6mZtOfHdRSxXadfaSdkwOTJCITOl4t9jlI1inZw0GnRyHuNoJbZC8HscgZ0oykKljKOCiOorMYgwfM+cJ3MFFPs7UAzyMn7VOsJratEUSUSf8/f+ETtEeHOENCLKbylPhfqi385jIJwoifNRjjKd16DlwgkLOfPjxu85K9CvynD0Z4TpSC4iKnJEs6EwkDClw7x4fTBmjBlUz1iMVKGYeNvq3t5eQaiWE2SI3AAIfWdnJ9bX10uBBBVsN2/ejDt37pTozMl+jFWd8XAk7rlj/jCSjoJbrVbs7+9XKt0s0wZcdWsIpZcjNxtpR+X8vo6h4DoS/ePj43F6ehr3798vOagHDx6U6AkgayqPexi4OsJzFRtjxJGjbzgjdGJjY6Os/8jISHn/FOfj+fgpABaUmiN07BB9MqND29nZKdEszoZzEXHY6+vrT4y70+nE7OxseXGij2HzOkHhbmxslMhxdna2lOUvLi4WB5b197J2rZ1URt5eNITdZZUIdERUjKiRGlGRhd3OzWE+fbCimApyItJ0jwXaaAihNKLntxg4BMMhv1G8N9mSE3EEBe/Ps00BmoLEMHiMVibPjaMFGxlX6jHnPJf1oM/8LidzPc+mn3xfHJEjMveZPArrhDxkJXeUwzO8fgY1dlp855JgZAbqxbLGmEdHRys0MP06PDyMsbGxcoDt2tpa7O/vx9bWVszOzhYDZYR7enpazr6j2nN7ezvOz89jYmKi5J/u3LkTKysrMTIyUpwa5x16Ph01mS5Dnuyg6HueH5w+1LTf+oqxMy3stfbcWjbNONipub8GlwAjV59Bxe7s7MTnPve5ePToUXFQRHUuPjAla531//mttw44qm61WiVfxEEDzIlfucE6QtfljdG8SZjjlTJI4poMGE5PT2NjY6NUKyJb0IMcRO2cswulzs7OyjFGOFyDXN5qTNQOUOXtv+wjW1xcrLz24yrtdeGkIqqnAFg5nPS1wLh0NCM0GzILmx1KRFSEgM13Robc1yjTOSNTA/C/ODr6Zadn42wUzT08roj+QZMkjjFmZ2dnlYodOzHPLc/PJdSeZ/qGckX0qaC66ru6ecxraoNDw0jlajbosWxY+F2OjDyXyASf+4/XH4PLZ8w/EUpEv7DEhRaMO+cP6BcVUEa9GG87mp2dnVhdXY2NjY2YmJiovDbBuUqiMApQer1eeTX4c889F88//3ysrKzExMREyf9wij7jxFnZebNunMjAd8whjpX1dI4OVoAcBol4vxae/IQBBn0gkjBQdC7TQMnOIwO/nKM5OTmJ1dXVOD8/j/X19UJ3uso0IgpFjL7nSJ958OstkH3mwpQ3eTjLtfXIm+RxXOg1JfPb29vlTdE5LQF7gmPimScnF2/Y5VRznyhihgGbERFlnfgte6CcGiBaHRkZKc/zsV1mUTLFiGN8WntdOCkS9TY8GE4m0ZxyRF84HK6bRnKOy8KZOXqEh6PzqTYkZ2MDl/NIruZxiSyLDO2G43L1Xx39BGrkOxTcL9nLJbCmEnJE5jJ25ol+4RhRPt4LxHNRbvJwpmRYp4h+wpexoZhOymfenc8x6j4WyxGnKUrOTas715D7eF6ysapzUp5vG5sc8SEnds4otqkkO6nDw8OYmpoqTvD09OINtltbW5UImuiAuWW+RkZGYnFxsZzyzUGqY2NjpYKQSj76hIw5uubfXj+vmcvFkQciLjaaU5TBa3QAYOimgWKdfnot3U9XgdqxuY/si8PBtloXVaurq6vFkYD+DXp5nqs/LbOZcs76iAybIcAJoSNsM2B9/QZgSt4N2IaGhgpoIZpGbigIIhcEiMJB+d78zdzxfHLblueRkZHY398vEdjMzEw5hYI+5jc4oMOWG8b0/2vv34M0u6rzfvx5+6qe6dvcewTSRAgHMpEEWJFFh4q+lKWSwIrDRX84tmOL2AWFPKLCJSoQwcaQskU5VUlcKaL84USkKiZUSCGTYEGBhSWCGUSkMOiGR0geeQY095m+zXT3TPd7fn/M7znv56ze5+3uuWi6Z/aq6uru9z1nn31dz1rPWnsf6zzTrUuRVQ1S3qnNd9DEQ2Cl6pEp5G/p6XhQfZw/Y1RUTozv+BpbL1TupCzIDXvBeA8FD4z0s2yRO3iZyoQhHyxVU5MZ7DRg0PL25PEzPFFJT9KiZQyGgGHl5DpLrdcRbNmyRZ2dneVZZgYw0jTuR7fHViZjchGUY796HKnc/NvGg98RRXrY/W1jxtYevdvYBwQaGycGCSs1x0PtTfr0bcb+IghY8dKrlloAbqD1Sy6pvDhWBqcrrrhCmzdvLqk9xxMk6fjx4zp69Gh5+oTbQNCw9+06ktLzM71WuPHTY+SYyalTp3Tw4EG9+OKLOnjwYBlfovHGmJoB0v1tA9Rti/Qz4y1kK9yGGEOzMWuLfmpqqlx/XiednZ1lHM/9kYqvRqERyZNXmLpfFEWZ0fma17xGV155pTZu3FgmVfnVGEeOHKm8Q8vtssfL1/64XV471is0Vq2X3BYavhazEadPnzkJxbSu1/b4+HgJ8E4KOXHihObn58uXItJL8nN47h89UEmVV7K0k1UNUtyZT2rM1rXUCl57cnnx0VWlJeoBjxQds+Y82A58+/UG3tTGGAYnNA/ftDXhrDyelcZEBnpstCqpLAiAVjrcLc4Fx5gSs6VoiVIxUwHS+pdUUQhOXPEelG3btqm3t1eHDx9Ws9ms7MBn37JsWu6puBNpDYsVkK1Fxi08Ps6KcyzOQm490kQGFfeTlZnFi41ZZaRy3UZuDCYwuu7R4yLN29nZWe67Ghoa0tatWxds1HTfuC1dXWdeYb5161Zt3bq1ctTP1NSUjh07Vr5A0kaSDQe3M55ywpguqcm4fubn50uQnJ6e1r59+/SjH/1IP/nJT0qqyMrb/cx2G+w5F7x/zkqOa4Melsczzi/GJR0n6e3tLY1JK3wbjj09PRofHy/XpJOBXIZBObIy/u116g3xjnExs87vhbr22mu1adMmdXZ2lqeMe+/nsWPHKs/y2qUn6fVHdsEeC70Y3+c+4trhGNjrsuHmsXIfSSrZFY+Z+44bdr0nkLp3enq67EvPORuui8mqBikPglM7vbA9cT2JObjc/5Hi3b1QqCysZKJlRoCUVDmJ3YNKt5o0iC0MBowlJeNSVn5xw3BRtE6Al1qLJXoe9JBcL++xYXluE5MaSIGQ0yd16R+n2XZ2ttLQp6amSuuVacuRMrFl7TrwuVL11ROkKfwZz2N0H9ujmZiYUGfnmc2HBh4qSr7unPOFQMRxZx/7Hs4XK3OPN2khetUeM44n427ubwOu93tRAUmtEzDsifi1Dz6Lj+8GOnnyZOlt05O3uJ0GWG418NyJFLhpSs+BU6dO6ZVXXtGPf/xj7d69u6QoreipKK0UPdei98b+dX/ZmCT9SGOAYBo9dVv4pssYb3GGrNtM2o0nsPi5XHNM5vDnZleom6zQuanf33d1dZX7izyuDCn4WRx7z0XOLxoWpN08Fwz2Ntg9pqRYqfvsYXKbDVPJ/coTl9fd3V32FVPczQjYSCbF3k5WNUiZR3WHx0YzxuGOjseKkPKRqouAyoR0DeMYtKJTNJ/rQE/EA8UYCz00K3Ae2WSrhYrb99KKdkKE60QQIMXCeBK9Flr19DBIL3jRGvx476lTp8o0XvPW9jClFqXofrfi8HdeGFzwpLYspF9oeNhDtWU3MzOj8fHxygkJpGzsfXphGrzcXnrXEaRotUfLnd5rpG3Y9mj48DoaT34WE2FsqRIg6dna8neMy8+LZxpGo8sGiNkGz38/i94sFZf3yR09elQvvfSSXnjhBb3yyivlOuEmXtLV0Qjg/PPapVHAuW+FSYPBaz5e5/VBCsog6TnqswRtKNALIlC6P1JzhULDkAzH9PR0eQSV15Tv5XujyDR4rRu4qGOi3uG6dNt9P6l7xn9Jv9K49b5IHonW399frjHPTc+rwcHBMnPU/esMU54+sVRZ1SBFS9+8boxjkErixkfy+e5ITnguJFsXVEheDPYSSB8SuFwfUkg8VZzWkp9jofIgneQ2uX60mnyCgkGI9efE88JnRlUEN6m1yAgkXLQGSFvzXAwUUlOWOFENEqQhaYUytuDvWAcCsK8lXUHLkQrN7eTn/okWK+cUqbpID5PWIwUYFTEVXVRGngMcD8ceOb4EGs9TJpTwBJVobEVa1c9h/Rkfiu31vVZQJ0+e1N69e/XSSy/ppz/9qY4fP156OQzgc92yPcwk9Xym5W1D1CDvvnTbUiAhtc5V5Os46K37FIWZmRlNTk5W2BiOKQ0+ev9x3dCoISi4bVNTU2XyBseSiTneW0fvxvOdbbdwjZPGc3muQ2QoXIa/c/lmhdiv9MK838s0vql1szTHjx/X4cOH1dPTo/Xr12vTpk1l4kVc5+1kVYMU3V+6tFQk/PE99Eg86KS+PCE4eCml5v95mjbTKr2QohdDXtl1slXLiUxlaE/K17s8ApkDnwTHWIbbTcog0ntUPl78bBOVMJ8rtSghKxNb/myfhXEmtjs+yxK9SNbF37OulHgqAik1GjIpg4MUHo0Q15FgG5Wa2xVpZbaDfU0vM0UT0uOPIEJDwgqX/Ufw9rz0M6h8Y3/7OsahfL3nro/k+tnPfqYXXnhBL7/8sg4dOlRmEJpp8NmBHivPURocbgtP2Car4P7wOEVv1OPgehqgeKYc1729x1OnTpVHSdmDsNJm2QRYri0afHGeENiazTOnjRw5ckTz8/MVo9WnONgjjmum0WjF9CieZ25XKjnIXiSNDreHcypmtrJNNKbdPh8Y293draGhIQ0NDamrq0vr168vqcvNmzdr3bp1ZfZgs9navrGYrGqQYhpjV1dX5dXX0UL0JGJausUdb2XL+ITFA8gFSm/JlgHBkJ6L1FrsHlSXxww/3+vfpJoY//HzvZi5kKjcyZ9bAXd0nEkftsUTLbNIx/j+aLnT82IKOfuKi5MLO1JHMc5C6o9UmOtuBcPrqOgILMzWdF/zewaYI51EDysqcQrBKQIn7yXQsb9pcJDWondM8LQi8Tgza4uxFFLI7nN6nqbLCdRuOxkDGhOMlfGkl3379mnXrl167rnn9LOf/ayke7hGZmdny+Qbrh/2MVPGmWVGhiNS0o6Fcmy9Zhx/4+ZX9wMNO6bTE/SpQ/xMg4jXFRW+vUZ6Cmyndc3k5KQajYYGBgbKtG6/i8oGBueRDQIaHjRyDEZSK7btz2OMKjJONF7ssbpdc3NzlQSkqGdcH6fVG4xGRka0adMmzczMlG2kXnX/LSarGqSk1psxPWmKoigpOE4Yusump2iFeSD5qvRIBZGzpSXmH9MSUkuRR5rQHoYH3ovLz4kKk/SOFQIniY8kohtukDWtx4XpSUxPjoqZGT60Tl0fKjFJZZ+7Ta6H62mQZEaaAYlgyISRGFxn/1kBUWnTozOly2usiNwfTJ6g1csYAD1gt5/zItJ+7jv/RC82WqOMkXmxUwG4PgxQc/7Ozc1Vss0IHFa2LodWNQ0V962fxYQdnt7heclYmH9LKjP5/t//+3/60Y9+pEOHDpUxMBoMNs68Dli+f3vu0Bjz890H3IMYvQwqbQMUNz/7Ol87Oztbenv+LsZ+PU7+iYYGjRv3MT1OKn6vGUnlgb8+fWR+fr48QshGBo0Q6yYatNRTNNCKoqgAleck45iMpblMGxIxYcZZptYBDAE4IcnreM2aNVq/fr0GBga0bdu2ykZpvrWizuCLsqpByvscpJYFw4UhVeMeHgxaNKQMh4aGykGPmXT0AEgPcNOtwc7X27W2BeP6kEokgFiBuU6kV6Iioyfohc1JycltDpjH5LttVA6e3J5AVBaMa7lNMc3VO+X9zAguUWjBRW+PytFKWdKCunMcOemtLJyOu3bt2rJ/fT+9H1rPUXFGT9L18TUEp0gfc9zdt/yc1IvBo9FovTCSlBGtXadQx/iD9+PQWKDXXxRFCZAujyeypLxmJlvYu+nq6tLs7KyOHDmiv/mbv9Ezzzyjv/7rv9aRI0dKZczxJX3klHIaUHHueQ772kijkkKNRp3Xr48Q8qtnaASSenNmqNesk7AY/yJ9y5heypPhaQtuO2l4AxPnS1dXV/leMZ/EwSQvhjJSAE2jM64R18t0tueNjSWyHFwPnZ1nMqedKcp55Wunp6d19OhRTU1Nad26dWo2m5XXdpAdGRsbKz3VpXpR0ioHqcnJyXKyeyB89AopE6l6tD6PLKFV0Gg0KhRJXEBeALRYXA6D8lSentB8FTwXFukJK0hbnV48UjV+Q2+p2WydG+iFQ16aVrQXCL0DKmPXyZuHvSAZf5BUBnRtGdNKd33s2sc4hq1oLiT3MQ0IAgYNDitNW25esGyLvQzuu6FF6efQm6KHGOmk6A1z8Rsw3BZ6mRQqSC9wl22Zn5+veCv+jPXxj8vkcwmM3M9Gb9N9QSqZXjfjIxbOY/9MT0/rlVde0QsvvKDnnntOe/bs0eTkZElfu2xp4Vt1Pce48Z5nGNIb8fMNWKTAPFaknCRVAGpgYKAS+KcHnIoDm5GxIWZlzXE1+NML5pFUrjO/o1fkMbGecf94M6yNX46N+4Rzl6wEwYs6hX3kLD2Phen+GNNzmY4x2cj1/PEaO336tCYmJsrzIsfHx8u1bZBmbJRU32XjSdHillSZFNwBH+MiUvXYFal62gIlKmErNXpMdH0jLUXrw4rSCpu0AhWOrShSIh5kKzguIj+fNJefwx3vBFkqLC6GGPPyBCZdZSVmD8CAQpffVhv7lTEFKmf3v5/DcZFaE5oxAnpYBEhntfEUCMehvEAZg5FaGxBJm9BytlChkTqjh8X68XpSar42Klt7s+xzXkvFQ6OEc4oxKK8R30evLbbR95ky9pxnHxjUT548qYMHD+qFF17Qj3/8Y+3Zs0fj4+ML4j1eL6QlSS95XvsaGgs0nhxDIdC4T+jhk94bHh7WwMBAWZ7Hgl6lgcLzwYrZ93gO+95oyJDRoH4w4FPpu1+ijvDa9DyMXjkNmUgfR53lNnDsXDeuM3rf9Goi1ex54LMgueY5vtY9fNOy14VPXPcJ6QbLywqkyNNH+soTgYuMytgg4ckitWiYlOucsrCpLBgH4ESylUJPhanSXGzRapaqaaLRkqe3E5WYpMrbVd1GX0tl4cUY+W7G4dy3TF/nYvLCttdI657WaqSUIu0XjQUq+BiHIt9vq5Bt5WkI3rBpC95tYAyHCjAaHJEupJLnuBAwXGakizkv+RwLvbJ4Hb2BSGO5n1i/2Bb2ufvHAEWvmXOKAOU32P7kJz/Rvn37yhMayDL4N89zcz3Zf1LrtHz2j+sa6VkaAvT+DVD9/f0aGhoqz9LkOiYo2qCx98pTNuKaI5BZ+XK9xDHj2LlPzU7E9UJWgcaDnxvH2W2lfuEciXOR1F1cX2QSuH4J/I7ve/zienFM3LG9I0eO6NChQ+UZgj6Zn6fBkKFaiqxqkHKHkd+0EnW2jCcVLRcOtlQ9d4uDLLUOEqVF7GfzOtdFUoWKomKxdeL32RBcUlaFlStpMEtU8FHxu04xRscJHj0+9g0TF1IB1mazWdkES0PAVJOvpQKzAuUE9Vi4XEq0YtkeUiSuL/uRYJfi+A3w7gPXL1qs/o59GxV+bFMKZKPBQ2XAzzlnKRGsYtn+4dyM3hqNOBpL0bL12vB97rtjx47p5ZdfLt9ey6Nt+LoU/nANxP7zvGNfREozGmbsD8+dnp6e8qSNwcHB8oR5ezb0gOxRu65879r8/HzpCRAsCOZU3NHjZ6yKn9GYYbu55jhfYpzV7ea401Mi8MS+jkxSHGvqLl/vMXc9XT8ahGSRDGiHDx/W3r171d3drU2bNml+fr5MmuCcs4e2FFn1IMUDYcn52/KxNcVAJRUorbHI/0sLrWAPFrNofC0/o7KQWly3X6XsrD4CCOksTlBaUVJrUqaeTxqHSo8Lyl5mKtDv+tpStFJnrMJWERW661kUxQLKxEBCw4Dp06TFoqVMwCAVYqueNEJM5PACc1tIQdIzivEP0lYpiil6Tey3lCfIzyM4x2sd2Ha5Ecg8/rRuaUSR3uNzKVwjntuRUqIBd+rUqfJ9Vvv27dPLL79cvubCL8H021kNsCmv3eVbOHcjfet1SQOB7eS6dWKMPSifERf3idHT895Gxovpgbot7B/Pd8dbPRctPPmCgMv5wXpET5lz1was6+v5FsMN1BOkB6NHTMPIIEFvmwZaNN5puHp8nGTCjD8bMa773NyZDGaXwdN2bCwsRZb2asT/vzzwwAO66aabNDAwoM2bN+vd7363du/eXblmZmZGO3bs0IYNG9Tf36+77rpLBw8erFyzd+9e3XnnnVqzZo02b96s++67rzLYS5Xu7u4S2a0cnY5tBekgNPlh0hjuPKeDx/0FnuS0OH1qBD0JWjUcTFpwrp/PurIid9A1VU6k76IVxne+eCOgj8FhmSzPlpOPLnHKtz0Tp78S3N0HMWEjAr7/dp8a3LwAeSQPYyeuU8rytqL0ODebzZJeMJVAT4qg57EwVeH+MuXDvnQ/c6xtpfOMO/dh9JQZyCatIS2k76Ll7Dqzjo4FcC6xvtFrdjyOwXcqLq8HKyn3OWObnteSykSk48eP66c//al2796t3bt369ChQyqKM++qWrduXcVriQBiYZupWN3nbquNQlLoDvR7XHjigSm+wcFBDQwMVNa/n+sAvg8+jfEy9xlP54jrzmI62yeNez4Y7GyEemuGy4vZfNyPxX5xTM1GLPWDfwgsHGPXl3O4zoDna4J8rfu0r6+v7FvXx6//8Bzp7+8vY34G5Y6OM2dljo+Pa//+/eWJIwYxryNuql+KLMuTevzxx7Vjxw7ddNNNmpub0yc/+Undfvvtev7557V27VpJ0kc+8hH9+Z//ub785S9raGhI9957r9773vfqr/7qrySdWUx33nmnRkZG9L3vfU/79+/Xb/7mb6q7u1t/+Id/uJzqlArTR8Yz5TtSUx5IWplS6wQKHwYpqUR4BsUJErRSmBxAatDPpTKw2+zv6fVwYRlQmFFD7p1WEFNlqXD8fKYy+764z4QUHIHb4+XTm0ltmsPnwia/bcBvNpvl8f6SShpWUkVhWDG4LqQkomfgMZ+YmChfqzA3N1cJAHMcvDDtuZrq8RhTEXpM3b9W3qbIPNaRxqUnkvLOLdGT4LWktEg9G4BJPUYaj14CPRH/ZmzRytkAbBrGY+qNpuPj4zp27JgOHTqkQ4cO6ZVXXikzaq2kCfbRcnd9pBZt7nYQRKzgYwzNv113nktpZmJgYEDDw8Ol4ednR4OMRjD7SlI5t61PzBRwvFwvejmcjxyPaHDTSIyeC73ORqNR6jCCEpkAeqQ0bqhvOOY0fnyv60fWxxue/VqXSGO6Dp5TBjnG5mgEzc3NaXJysoz/ul0sMxoAdbIskPrGN75R+f8LX/iCNm/erKeeekq33HKLxsfH9Z//83/WF7/4Rf3iL/6iJOmhhx7S3/t7f0/f//739da3vlXf/OY39fzzz+sv/uIvtGXLFr35zW/Wv/7X/1of//jH9fu///vLyp/3IJiOsJKTWu8qsdKhh0IPhx1Mi9OUGF1iUjvRgrYyY2CYVAt3cUstz8HZMUwZpnBxkO5gOxjMjbErqZUyGz0BTxTGDzjBCUp8lXSj0VB/f38ZDHZ7abVTwdsAiLSi68EEBPZZpDM51pOTk5qenq4sPiqOOE/cvzFwS2VEb4zf2fJkBiP7n8YQPR4vataR3g+ND0ukPCO9GMEx9hPHNho1VE5W8nx1zdTUVJlWfPjwYR0+fLh8a609VvePrXt7444NR9rRyp9z3m2n1xTbTqPPnpPr6Xb09vZq/fr12rBhQ5kB6EQhzyvHpJjSzwQGf8bXpPPkbgIM55if7xRye2ORdbAnZHFdCOKk8lyneMahx9eAQ13FPmSMix4zdQXBUqoeaNvZ2VnGzL152K9+7+pqnepjw4Gv3SiKovS8eIqG9RwPVXBdlyLnFJMaHx+XJK1fv16S9NRTT+n06dO67bbbymve+MY36uqrr9bOnTv11re+VTt37tT111+vLVu2lNfccccduueee/Tcc8/pLW95y4Ln8HUUksoXtpFLjpMoWh/R2qU1Re5banlNtG79HQFOqm7w9MThYotxG/8mZWMlSoD25OPht7b2oyUUuXG3395Fims2bSmpXFzkpZ2qbbHF7P6SVB4w6XaSn2af81gfL0R7MKSaIldOa9p97Bdc8lQKxwn4Aj+CDIGOm57jYk6BgYVcPsc7AgcBkl5wrEcEY4I1502cX/6bnjHL9nfRo7HyssfE46G8gdSGyPj4uA4ePFi+e8rAYm+HdKQVtMfZ3/OV9PRQeHq760YvluDKNeP+IK3sGIfpxggU9HrYx+7fmOQQvR3OJaafk0qzcROpX69xepmky73GvK7IYkQvJsYN2RayPZwnBDa+YoTz3WtyZmamfI43PvvFlbOzs5qYmKhs0eD6ND1sMDZw9fX1lSelk02SWud6XnCQajab+vCHP6y3ve1tuu666yRJBw4cUE9Pj4aHhyvXbtmyRQcOHCivIUD5e3+XkgceeECf+cxnFla+q7U/SGodIupFxIGJC9eD64lJj4tUE70XLvaokKSqoogKziBEF9wLxRMzUor+28BgBUClR8uQis194kVHz5HxIccS3AecgO4P95WtIfZHtDKpUKKFz/4mNemFExMWohfhBWVrmWPEFGoCt+tpSscnlLj/bCRYkUVrPo4T+9afub5UJOyf6LlxsdOzdn9H6jACH+tPOosK0WMfjQXHUzo6OsoTv31enGORU1NT5VuAufGzo6OjfNU64zvuQ9fFMTF6UT6Fgac1MF5Ib58xK48H+5z0pJU9vX33IV+JY0DwfLMBRjC1ECii52+qi6GFSLG6vTRIvC7cbveX5x3nDj1wrlfO9+g5RxqZBqz3oBH4I+D41e5+3RDnHQ+9JQDTsKWB6v/d/1zXZAGoI9vJWYPUjh079Oyzz+q73/3u2RaxZLn//vv10Y9+tPx/YmJCV111laRqENaTL3aKhdYnlUWkAjlpUgpXqmaeUYERDKLVR5ByXWN8wWJl7udScTO2JVVPHPCkJ0XovvD/0aukkiZF43iUn8vd6vQ+SKfanTfN0my2kh5oOVlZxDFMWYVuG5M6XPdUn8c+NbjPz8+XVh4XsYHEbebcoGFDC9ZjG+OQ9OQj6LGM2N+eq3HhRm+N4EwqJVKm/p7eIl8GaY/p6NGjOnbsWEmfksYriqJyTp8Vk71ZgrnrcuLEiYqCdh/Pz8+XgOG5TYCjZxLXJ9eZr3O9rGBtwNhaJytBQHTfux8YE6UuiEqfNJqTn5jIw7nCZxGY47ygEeT/CUgpvUChAc1rvVb9PLeZc4hrxGBrY4eZj+5TGxkeQ5d36tSpShw56j3uc2PYZKkAJZ0lSN1777362te+pu985zt67WtfW34+MjJSvvSO3tTBgwc1MjJSXvODH/ygUp6z/3xNFL6emBJpEtI/XDicRL7PnUhFR0/C10fXnZOBHgAtL5cVKaUUzWQqTGopJE8KWmiSKu2L2WOsJ+vP/UVUXlS2vp+T1wrbr1ZgP3ssvBhsUdOSJM/vrDMvFmnhsShU3uxfKiyDFEExWtoEYY6fFaKzyPwdvTl6QQR5t5MWKoEpBWj0Ni38m/3NBct5GY2AaHzQi47GU7PZrJzpyLdAO538yJEjZczJWZ6MizDzq9FolP1vb4r1NUCZOoqJL64X1yoBikqcbTK4co+NQdM0v39IjfsZ7kPSw14XrhfnEA0BjyfXtF/q19/fX753KuoXttn9R/CKySYccyY8cM6wrjRu+EwadDR+IhtEStPPpn4zxRffGee+Jc1pgzEaWKwjn825eUE8qaIo9KEPfUgPP/ywHnvsMV1zzTWV72+88UZ1d3fr0Ucf1V133SVJ2r17t/bu3avR0VFJ0ujoqP7gD/5Ahw4d0ubNmyVJ3/rWtzQ4OKjt27cvpzrq6OioHCnvDraysydAOsiSousYc2CbI/1E194LwovNg5VSllGhepKZSrHCt6Vqft08dip4Gy1rWk58Lik8el1O2aWX5nbZqmLbXV8rFlMBDqozpuD+Juhy0VLRejES9Am8zCL09SnvIeWduVyplc1nZcAxpXdJg8Z0SRxTGhEEVI5t9PbcRxyXSOsQGBzzic+iIqayc5n2NLzVQVKZej85OamjR4/q6NGjGhsbK70oJiTQ63efmRp0fIJj6DnA48jcDwYjtpeGHJ8RPaxGoxVHo9caKVaPo8Vr32BKqsn18lgwZMD+ZBusnNesWVPuxbIBF8V19lqxQreHwjXofiQ48XnuGxo40Vj2nPD65QbmomgdNUXA8300avy3k5MYO/IzuM2Hm6Idl3RdmShBQ5xrM+raOlkWSO3YsUNf/OIX9dWvflUDAwNlDMmvBB4aGtJv//Zv66Mf/ajWr1+vwcFBfehDH9Lo6Kje+ta3SpJuv/12bd++Xb/xG7+hP/qjP9KBAwf0qU99Sjt27Eh6S+2kp6enPGbfVpctXql1zhQt1nhum4UdFi1ZDzC9MmbveNJ4kvGZEcxofUit1wkURVGefWWLlK/MkKrJIPZoIp1Ei9Bt5qS2p2ZFPTc3t4B2dN/YA2KsxMBDsJEWvuDRC4MLZGZmRo1Go/L2TlOBtK7m51sbrlnf6JVw8dCrpEfkBe96GHRoHNDbokflNlmB04r39R53Z4JxHjEWlaJoSQd6DN0WW//cs+Z+Z73pmRMovd/Fhpw9IM+xY8eO6fjx42UsynSc9/hYWdlompmZ0dTUVPmOKM45ZqlSIn3sdnHNpaherxdSjVxH7nuvde794jxIxZpiXIYen8eY93Fuepy9xul1RmaACQPuQ8fLaEx6zOnZu16cO3UgG+k+A4W/4zqI843zxnOLG7w5hqb6XK9Go1Em4DiRyaBk44Cb0p2ZSYMqlc2ckmWB1IMPPihJevvb3175/KGHHtL73vc+SdK/+3f/Th0dHbrrrrs0OzurO+64Q//xP/7H8trOzk597Wtf0z333KPR0VGtXbtWd999tz772c8upyqSWkqFjfZE8uBRgZl+Mn2QGkSpmtXHhcMsJD8r0jrRhXW9uHnXk95xqkajUR7EODk5WTmu3/XhYmB8gPx1pCRtvVGRUXG4DEkLAMrlUUHSi3JQ1NdY+TPbiEqBlmP8jHWg4iiKorTq+LZSKklaZC4relMGSAuVOWkwAwlPzLAympmZqXji9sJIadAbi/Qh5xf7m16TrzUoO7OOTABpL19PmojemKn3sbGxivFz4sQJTU1NVd7zw82W0pnX4Ph0a3v0jN1E6ohzkMo6RZ2R4qIXYRDzZ/S4/VwbOB0dZ+JqblPq/D2COBUk1zC9ivimWFOgHN+ZmRkdP35cjUZDExMTpUHFtWOAMpAywcRCoGBfMrmDa4JMRtRbFrIJcb5x/XHexHUiqUwjN1PipArPKesUHoDgeetxmZ2dVV9fXwmwBHXO0aXIsum+xeSKK67Q5z//eX3+85+vvWbbtm165JFHlvPopNgjiWBBRe6BJZh1dnZWdj17EjCbjVystHDfBssjf8xn0YUnj26v068ROHr0qCYnJ8u9KKbQ4rEh9FAcJ+HmOcYu7I5LLQvRi56Tg4uV7fcEpmXq+IB31XufFI/y532maTo6OkoKyXXxNdxbQ6VFgJqamqrs0YkKxn3vsplm7YUWwTjlwaRoFIv7nBSj7yPgeqHTqvc8pPdB+sQK0EYFvZfOzs6yv502TgXk+eXxJQ3rjbjj4+Ol0cP08Y6OjsqL9Do7O8vECcapIhXqfmR8xWMYvSN/HmnWGLPy3Iqej+eBvfKurq7yhInOzk6Nj4/r8OHDJZh7zDlP/AwyC5yjBHr3A+N9UisRw/1oj8F9R0OZcWCCtNvDcXM7XT/eQyYnztcUVVb3WQRE6nFSxqRIXQ/2fVEUlXdRuU0OCbjNPL3DeorGrAFqqccireqz++yak9v2wiZomW4gmNgLISdNhSUttD486Q1unDCRZ+UCJADYkuzt7dXAwIAk6ciRIxUqhYHVOClJ39ELiQF0utVRoRoEPPlobca4F613c/J8NxaVc6PRKFNRbQjwjEJTEYybcR+Lx9QKwJt2T5w4UQIQ6TuOGReglQ8DvKYaU56L1FJCXmh+DmMGKRox0mzRG490DOcLy4sg5fb29fVpYGCgPJaGioMeB2M7fhHdK6+8omPHjpWK1RSiM7V4Bp29xdOnq2ciEpCjxW9l1k5hkuqMWzB8HWkmr8/olfHZXrs+HaHZbOrYsWPl3HWf2DuI/WwlS5DiuFjsLXg8zaZQuZKC5v6pFKsQ12Fc45xb0SGggePfsd/js6KR5e+iXvEcn58/kyl59OhRnThxogRr6YzzQSPMBpg3czNGOTd35mWjfX195Ziz37q6uipU4GKyqkFq7dq1ZezGCs/xA3o+Vh60zKQzA8f0UIIa6bFocacsEtIVvse/bZ1K1Vese+KbiuErt6WFyR1xktNK5TN9baRerARiuW47y/L1BiZTk/7xhLVSZXzInpPpAD/TllSc7AQpKlpSVP7OZXGCk9bx//QcrfQZvLchQPqJcQD/NhgwlhkXOQGKYOQ6U/FQQUvVDZ8EYCvauPGWAEoDw5bqyZMnNTY2pkOHDunYsWOVbEiPl9R6hYmViu/lUTw0dAhmMcEhZZyxfwwGjGmwfzwH3Fecj76fnxPMu7q6NDQ0pPn5eU1NTZX14n0cG46t16zLJa0W+9kS2812WOyxcvsGaWHOiVScaKnSzquKn0eQi94dQcqeoteR99Ux9u+1xaQpsyLSmQMCfOgCWQobsjZaliKrGqT6+/vLRebGd3d3a3JysjzWwwqJE4u0mBMHvNBNG0RlYkvBi51CpRiTFajoqHwnJiZ07Ngx9fb26vjx4+UbhX2/VKUxqcTpEUkLLShav7TmuEhsJdG6pGfmNvkwSR6+a1c9btxk2X19faXXRVefAOH2WVn4ewfprTRjUJ6Lm/0hVU/yoPLk/1ZCDFJHr4R9ZmMnpUBZJ/cbxysqB19DA8jfux9MezUareN8eDKBQZO0qNPDx8bGyqQIH+9j5cJsN/e3FT7PiovUra8jvcf5SGXPeWixQiJFxOuiV8lyDHAWrzFb7471Dg8Pq9FolIkmnCOsR1Ts9rTcnkhz0TCkziDjYCCzx95sNst6xIxUP9vzNOVNna0sBnIpY5vSbDYre+Q6OjpKbyjGpmkY2esnSzM3N1eeqep+JwNCZmIxWdUgZQXos8OazWaJzkZrBnqlheeyUeEwsJ/yiOhpESg8QDwfLwKVLRFP5I6OjvJ0YU7uWH60QggGUotuSA04y6PrTq+BQEWL2/XzsTOk+Do6OsqAqtORaRnyBHSplYnFRSu1vE/XxbEYB/p5xA2TAWhMuD0eGy80KlpSb+4nGhAeb8+dSN/6f1K//JwKnSAVPVmXGekeL14qa8490kvss2azqenp6fIwWKeIT05OVjIVmWHmfjP9x/irhcqM8zh6nYy3kkKmIqTX77a7rRwDPotj4FgVDZpGo1Eq0+7ubq1bt079/f3ltaaHqQg9B+i1pVgTrgN7DTRqbBDQMHbZPonDVB8TBmKCCY2H2N8poZG0VImAXPecSEVTB9GYkVp0vPuCcTk+S1Jp9Fj/2ehtNBrlGYBLkVUNUvPz86WFZkvSnpLUekdNpBKk6i5yKxkvAsYYUkFvAgP5dHpUvb295YRmVosnrQfanog9DSoFcvTcgBrpSUkVa9+TjsrccSEqd7bLHpfb7EXlhTc/P19pp0GKrwZ3XUzteHHTgrew7zo6OsrnHD9+XGNjY6WF5oXiFG+XF+MVXOxOHCAoW4lQebk/GQOMMRN7VgYLzxUqac6pdkqGVreVLTM4PRcJ5FTWfp5pGZ8Eb4Ci5ertCfaSnKnHeUTK1fPWVC49T/aHFY7r5rFhH1HBRQ+XfU+DyNe4DwlQNpD8TPe1M80856wAOzo6yrT6OAZsjz0mjzOByv0iqfIqm+jRui6+xus9euwpA4cg3c5L9+exLanvI2sS7/XnsTyOje/jFoA4Dl7/Xk+khD2f2B9mJJrNZhmnviw8qbm5ufJtnLOzsxobG9Pg4GCZux/3EdFiIMVFhUmenpY4rcjU5LJwH40D1D6hnZYgAdHP42Sm9U9wMTB5QVmR09Nx3xhAolKkwqTHaS6dIHXixInSm7LF7MVN7851yoZu5AAAS2NJREFUNX9dFEWF8iA9ZLDj+WlTU1M6cuSIjhw5Um7ATvUPLTOOI2kGe1xUCjQOiuLMq0RsoZPqdH9GOtKJGDQCKH52pFNIfUWvwuPkWBENBEkL4jg2ekzppd455bJ9rRNyHNuzpxuVPvs7/hDQ3D++h4wC44JU4Ex2IBAQRLi+aOx5frLP+Z3bfezYsXLuSa23WntMCLo04qi0I+XtgL+z1eg9mcXxOrMhaYOUoE4K331SB1C85myFbSJYRRqWetHrIrJEHR1nMkCHh4fV19dXrkXrRJ4wEg0wjxWNadfD1y1FVjVIOahXFIWmpqY0NjamRqNRglZ0Nal8SA/RsvAkjlSAVH1lM70O7mWh0jSnWxRFGXPigrdSl7Tg1ROMi/iZtlR9jRWAJxgP6SRISSq9D9e70WhUXnBnD4VJGI1G9dRsX8tz8Bg/4bl4ply4EF0mwW56eloTExPlfp7Z2dlSAXlB2GKmlRsXoSc8qRVJlW0GTGP3uDLmYfDl+HE8+LoHxjlt1fOooJgk4HG3MeCynWrOPnfd7P2RSjKlx31fpJUZ0zMtxcwqKxQqExpiNN4IuG5DvM99w71BXh/0om0QESRcNoGJbEE88y7GvqxAed5gzN6Mnp0lJj+Q9uQ8c/8RuFwvJ5v4GdQpEWRSns5SaL6zFc4l/h09MKk6vtRr8/PzZVyZ8WVJZYzap+dTn9DolVoZwlILtMjoLCarGqQ8sfn2SO8d6u3trXggXvT0NDxxqfCiWy61gtpSNQbkAXXyhZWcPSgvmDVr1qjZbGp8fHyBdyC1EiRoXdDa4vPoSaUoSbfRi5AUIzPamBVG8OMio9VrRWNlPz8/X3nLLikfJlNEpea2WamYrvIxLNxbZSXng09pMNCooGJyn3qc+GZmUzsxrT7SP1S+NmpYpucPfwgEpi+jx+HvKMyW8/eco/4+vpmV93t8GXvidQZN9pl/k96mAcM14TnKGBSNvlhnzkmvA6nKZLCtnP/RA6VFzueQPrSwX1gW100cOxqA/u3raARZuZqNMEDxFRa+n/+zzyMwUVIUXDs5G1CroxHpPRGoJC2YawR9vp3YNDLjpdLC+eytJdYbS5FVDVJ79uwps/h8MvHk5GS5S1xauNFXanlL0eoirxrddVJpkY/2by8cqRUjsrUnqaS/vLC8+59WPRW5y2PGWQRRP9+KinWz8qHFTyvPbaX3QauLlqvrQivbHpUTJVyHkydPlhYn+83l8GV5tvhPnz5dngvm7EHvXGc2IPs8KjM/kwBverG7u7tU5NwjQ4/VZVPR2CCgceIfegukaqOytKLmnHJZHAN66e5Lxytdd9fNnnLcfOnne06lKB5mp7E+VsaSSqPLa4QgYc/aHmTMICVNzsQD9jPpZsZTOZbsa5cdx4ogwvXj9tjYYf+kqPWU8UOwprFm6i9Fefu6CPKUaCywvufTo0p5UylKkR6z68SxMysltWhZb4twmMHzlGudOpCp6pKS2xHqZFWD1MGDB3XttdeWmWT9/f0lEHCySFXlEykPLgZOPKlqsdEjkxZumktxz5LKwezt7S1fpW6LzOnypF0Yj+IufSoAPt/P4qJjYNLfpegFemO814rJE4mTl8kO9jzctzwXz+3kQndyhOMpXvDuoyuuuKKMA9iDonHhOscFSFrXY+Z7165dq/7+/rLO09PTFYvPHlx8lYSfa8/QxosD+kzFd//RSm80Wm+VjYaBpJIepjfF2FgEMJcxNzdXxpkYe7N47GI/+V4aQAx0m5Wgt+6x5Bpx29nPbm/0xGM96D0x6ch18xzjtRSuPXqABDrGlVw/vtiTFDTBJK5B389xYEq5PUUaH3V0XjupA63zLSndFCUFUidOnKgYdDZYTPHaiCPD43ViY8dGl+fFxMREuY9qMVnVICWd8U6cLOHNo36nDZMi3JneAMhDOrloTEV5kscJHTMGSZdI1WNq/DmPb7J4MphH9yKP3Dn3H0QLWWpZ41ywpOr8d91C4EKiux6tfz6PlKWtIwMF+5dWvZMeTO95fNiXTKSIAOVnRDqCfeDxdl/5NPl169Zpw4YN5buT/GI307T2BAcGBsqjnughWPmSY+cbSb34DDhMwKB3QkXHcaHXxJMKDJgEKQP92NhYmc3K+U0vOhWYj2Dp+02/0PP1PGb2FkHcRkYqy4tjw3MyXT4ByuPFuRuNLI65+zXexz72mms2m2UWamQheEYjQZRxMI8Xfzw+vnY5gBTXXrv/z7eknkd9Qh3BsfTpE6T0vb69Nugp+3v3r6lnz3UbVn/zN3+zpHqvepDatWuX3vzmN+uaa67RiRMnSm9Fqu7m90K2tZziiK2cTQ1RcUrVEwioqL2ArNgJUgzGeqCcgWZr1JQW94PwOQSWCDi2xqWq9UaPi9YoPUpmakVKLkWt0bKm90QwY19ZGUtn+GxvYjY4mJrzNe6LkydPLoiNsO622ugh8DorDm9u3bBhgzZu3Khms6l9+/aVJzH4qKSenh4NDQ2VbaEn460E9IA8Lzjern8qcE5rnqfbs32MG9JAIuXn67zdotlsloeqkjpkPd037L+U5U/GwEaPx5heOgHIHq+VELMG/VzPUSu1CFA2YOiVsH4RaGmgsX9jCjiTi/w3T0Qgk0LgIWXqMunhct4R6H1v9M4uptR5ZrFeXteeG+4XzwWPs/VWbC/7gHNIao0NPVUbOEuVVQ9Skso09Onp6XKfBzOtOGk8yfm91LKavLANGFZ4kXKJ4ol96tSpSpBaUhmnMRgZfHzEkCkyZpmRfrMYoLh4qUw4eUjj0Kpmfbl3iUAgtagoT2D3IxMupJbn6B/f56wfP8sKpNlslvSsy+GJCaYP7el6bDxWBCIrP55kbmPBXt7hw4fV39+voaEhXXXVVerr69OBAwd0+PBhjY+PVw50JSB4Drie0Yq32KiJQWCPp2lLHuzK9hDgGB90f7k+kfKkV0+K0IZB9IQtBggaNO4vUpW+NsZ0aX17DjEWV0cXcz8SwYxZYJGyi8K+MnXr8bMXyris19jAwECZjGOlyuQIesBuH2NOvo66JHr09MZWiqR0FT9zezyeHAePoRPP3B98S7N1ipkFGqVSK/7sFyhabIguVS4JkOru7tbAwIAmJycrh4py0nOScUHFheSONu9uq4AWg7TwzZOSSrBJeVuc4J7Y3PRKeollxwwmLuJms/qGS1qhUvWV8XFB0dOh10QFZM+CbaDFH0HMdF9M43XZtMYNJr7H9J4Vi8fM8S9abrTE6dFQmXd2ntm8PDk5qb1792pubk4jIyPq7e3Vhg0bygN+Jycny344efJkuaA6Os4kCNjis9dJq9M/PJGD3oP7zpZo3KDMmBb7zaDNDd4eX46zAd5eFuc5x9v3eL6b4nLZzNzjGvAaMji4vJgGbkaAz3IszuMQFX5kF2j4xLkYKWf3EfvJ93peWJny7QO+LyY/0POifnBbY1/SC2ab+Tsl/I7jdDEk1sU6y99FFsZ0qQ18n5rjZCeppRO9Rubm5ipUq8fdCWNLlUsCpJ544gkdPnxY119/feV9O6Q23MEEJam1oAhUtHDpsVh50oqIFi1jB57YXV1d5UAy5uDg49zcnI4ePVoBRFqNdJ9TvHKc8KQarPijRxY5f/cVQYfg5fJIv9CL8OSNwW/2pSetFbuVNLP7eN4iM+oYmGXquPudCtvele87fPiwjh49qn379mnDhg3q7+9fQO3ypW208j0faH1HkPIzmQHn/o1bAJxdyBMheAisvXb3I8fA5dh44MGzjO9F9sB1jnQcxeNk+jAmC3EteR6wfu5r14HgwmsJRqxbqj7x+aSpSe3RO7NX7aA+D8xlHM1Ggdci9UKsr8eegMr1R6kDnRQtfbHpQNeBIMV+cJv9t6933xdFUXllD4GcdKlUfzDvUuSSACm/bZQ0Q29vb0k30ToylRRBxYvYE9OL2dcwscILzeXSeiCnzZiPPYS+vr4yZuZBpZVLCs7fkWqRFmbm+TqXGb2jWJZUfQNsfCavJRjTQyC372u5T8ggED0wb1i20rNC5gKxZ8GFQQXocWEatZ9BGtW0hF89MT4+rmPHjqm/v7/cmEyrmt6Pn2ngoqJynbjgGMeJfWODiZ6U50g838xzgePna90v9vSHh4cr6foENoK3pAUekRVGyqBiWn70IFgnzgmXQW/E88HGRfSso7cUKT5/77K4l89zwVtQooFgcPEGaN9LSpXeQvSMLIxFca3RAFht4nbSuKXBTeaCRifj7F4XpvEIUpE2llqHCSw3HiVdIiAltSaaO9LvdIn0F70VKgBPfMZYCGTR/eVA2prjc2LMSzqjANauXVtRUqYbSKv5Pi9EWjtxcUQakyAUY1EENVJ0/k6q7gFLAZRPnrC17YnMGFoEQ1tf3Avkv6lYCWb0XFw/LiBmE/lee1B+QaDUinmQ3pmcnFwAAp2dneXmZI9hpKioqDxG7Ps43q4bAZEbqj329HZJx7nunp/uF5dpK9ZWrfuDCQluC+cA57uF84R0ID8n9RXXg1R9VUNUUu0MLM7z6GV5Ltn78TxIZSR6PnncvMVjamqqLNd9T8Mzrh/XK9LTrBMV/VLkYtN7SxWOL/UkGRP2oVTdCE3DPK6dmBi0VLlkQGp6elqHDh2SVM1Eo5KNNIivkaruKL0DqXqAKS01LwQf2UM3OS5iU0u2VLmQvE8nxhz8N5/PSc74F79rx+VTmca4kYX95/8d/7GX4n5xwJpBcz/Lv61wTVPFPiUla2uLfU/vIkVbMj7V39+vNWvWqNFolIF0poMzUM9yuLmQXg+tedaF9Yj9yL8ZF2XcaW5urrJ/ikaA+8tWZwQQjwHryzhKau8R56TnI8WKxB4wy6WXRfqWY2SF7/uigeH54bYS9KNBZQAlkBqsDdA2KHyfqV7/2MjhG64j/UyDgKwK59359JhWGkDVeY6RFWCYJI4Z6UHPW0tqHqX0zWJyyYDU/v37NTY2pp//+Z+veElSlfs2d03rUGpZzk6PJuUXhemZVNSOERBYosVFj4lWtetE5cFUZAsnjuvN9hKI46SI1mnk2N0/3m9GWtMLms/0TnRbuHyJmSesy/DfPM2cYOp+9L1Mvady4Y+tOwfoOzo6KmeM2aq2JUhgZj96POlxWclGT4lbDDxGztik8nYbvLCZyuzvfU4h55SBwGndpEL9DCdpmCZk3IW0GuvEuUAalnPC1xEkPMeZ6ec20pq2kcAsToutaNaNSitlTNHz9tj7vDieOek5yCw/7sFzP1AYMyPAE6TaCa+p846W62mtBKEx6bVKCpwxWq6DaLhE2tbGRTSUliqXDEhZDDa2yknfOaWYHkiKK/e99hyYhEFKRmp5Mw5+M3WaHptUPW1Aak1wLn5eS7Chl5LyjKRWOniKuoieFsHQdfSryv1uHi540mz2MPx9pPn8vakpChU1FSWTEmhxs5+kVhKKA+QETipItp0WMRU4Fa+tcWZ10aOmRxzHk4qWY+K5Q5CiUeC+l1on5jMjzTE1no0YDZToeUbl6HZyPqU+p+JhG6JFHdvocpxwwQxVi/uUwBNBM85dxtO6u1tvh3Y59DTjaRJkPeihcY3RiCNL4Z/UGLF/KSmgWsnglGofPV2pxSZIKmP4fIeXaXH3V6SQo261Ub5cqk+6xEBqenpaTzzxRPk6ab7qIC5CAw47mMBDeoEWrv92dhmVig+bZNlW4FIr046Km9aFLU7XhwokUl0um58TKEhNUfESGPy9U/gHBgY0ODhYAhQVCWMFETyl1kJllhoVu7TwlAOXGy1/WvO00jo6OsrDhK1gaUU3m82SCrLlZzEAxX6xweHv7JnxNGe22fV1eY1GowRMt4+p4y6fCjZVnsuile8MNdN7nK/MGO3q6tL09HRpFDCmRJqGyp1eLOcXDTiCL+tur9lnZnpvot+Wa0nROwYWr62+vj719fVVYkruN3uMniupkx9i1iXXnucX28t1yfZEWo+0H2UxwFotkgKq6DG7j+yh86QUGq2SKvNLqhpzUXctVy4pkJKqAVlm/UgLU5m94OkxmDryQpBULhgG9wlSTHcmRUEPgdw3LToHo11vK0sryrm5OY2NjZX0Ii1lxp1I91FBcUIRoE6fPl2ed2iAcn95/0ncwBytJlqh/ptKgH3ve/niNPcFqZao2GgYkHYwOJFudF+6zR4Penwsl5a8jRB6zxQDrSlBl+1kDdNvzAZznQYHB0tPwPWOno37yCAnqUz+iFmHro/npNTyvN0WUi6MIbhsgmGUxZRvT0+P1q1bp+Hh4fLN0kePHl1wnFjcWEtF6JiS51yz2ay8qNDtcJ0ZeOd4Rm87Ak5kE9jvKUouKu92spK9paVIqq00CtxX9GqjIRWNGxoH1lkdHWfO6ktlES9FLjmQkqQTJ05ocHCwMgnZ2Ywh0PK1xZoavOhJxMXOOAVpIoKSBy0GHqXWe2+sKNeuXau1a9eWz+Wrv2kFp+qWiuVQiuLMS/98Xp3pPSsKKn5a+17kTAdOWaiWSNtIKmkrelyuKxUwDQtad05jj7EH0qG07pisEONQNjBsZHDc2Q6XHWMmvsaglEq2cIxr7dq1pUI2dWJP2PVx+faIqKgtbIPrRWrQ10TajlR1nLdUNva6Im3D+dbX16ehoSENDg6qo6OjfGml22SgJnB63tkA4MtBmXzDOec1QQOOXlQcU4KR28w5T5ajTlazd3Q2QmaBrEjUT5xb9EJpQNo4IgUdPduzkUsSpOwpmed359PK5cQ2MPj9KLOzs6XlR5qQi4dgQG6f+0y86EhnebH5fystl0l+vqOjo7RaTSfGxU9vhlQiLUkuZCpoH/njPon7G+iN0HMyZcNJGhUFQZr0o5/nZ7jvXddYX5Zlg4KxIytWUp2RoiTIcFHxnVK8ntmAFN9PQ8Z7cTyG9KA8Z0xHOuDP8wCpNF13euAxDhXpJh5y6zFJKYRIGbPMqJD8vedy3BvnU04MLMePH9fExIROnjxZKZ9p9aSHSaXSs5QWnuRCQ4zzM9KI0RtKGT+kWev6c7V7R+ci9EZpXEhaYLSSZnWfec+ef7zGOI5nI5ckSEkLU8qt5BjrofXoU9TtcUlVqokWBLOuojKWWouEAVlLBC0qQ8YI/Iyurq7S0+nu7i5PeI/PsrJn5qJ/02I3nWXvIQazCcyMsdDziW2tE9J3BA5a7zw9gjQZy2DchgBF5ZmidwgqNkyYhEBQZ2yMkvJI4p44JuqQhvW8M33quWQvwqBi5e3n0POMXlZkB1wXZwpamcQ2UFIGRYwhuB1Mebcne/r0aY2Pj5cUzsTEhCYnJ8vEIWZ8GahJ9dDrNIC7HinjSqomXUQvL8651O8UKLGslFwugEU9EddAHBN6taR0o5FBXeJTZs5WLlmQ4qvCpYXWVbSmmfknqdwVzaB3XRotvSzSe36mBzYGalmOn+XvbKFL0tq1a8vXshssqLiLohXwdwDfioELzUrHYEZLNrruUiuRI9JYVvZWdATdlNUUKTT2O5VaZ2dn6S3GmBd/CDCuA+OMKaDws+PmzziWboeFi47Uo/vZxypZWE96jj6rbM2aNSVwMjmH1KHF4xEzCumpu77ux1T2lOtOmjAVm6EHS5Aifc2DgGnEeG3Y4GNckBtx7YHFmBIPFo6Gn58TGQF6fykFGz2mCHzRGIr3Xi5CD4przr9pTFOPeuxp7Hrdcu4ePnz4nPrzkgWp2dnZyo50WodWsNFSdFplV1dXCVI8B5DKmnSVy+zo6Ki8ZoI0k/df0fojfUaPz59z4fteD77U2q9Er8SvRGA8iHEF191KwJYxrWlbzJ54UvW1DyyL7XA/UOlaIfgzx9tSKawGRAfgCRoxQ5OercfCRkakyPz86BXH+KDbwvsi9UZqg5txY4yMgCq1FrSVuJMoSK3GOkSlGsHT6cCeG57nFlKJVOz83p/5b+7/sqHjOvoEhxMnTiyot71D72Vyn/hIKvcfz0h0/MuvEzdAeUyZ6UrKnXOQHmFkMFJyLhZ9CtxWu3CuU2/QmPGcinRoNNIZSkm9GeBs5ZIFKUmlQvT5XmvWrKmkL0fEN83W19dXKmcrblMUXghUSr7Xx9UzycGAyHRnZmTxCCBSf6Q5fN6d1PLsPIm8KA0OVBou3+X5f4JfjEUw8MkJl/IOaV25HBsGvpZtcR9ZuTN93Iop7r3i+NCqjsFZJ0AQJGk9MxXb/Wqrj/E5enAWxhKjZ8r+cfmk69wvkcZ1nT3HSJHFORAzpTx3TCG6HD8rziXWxffScOE42jjwOLCf/Jk9Hm/vcLkGEu+n8TrwfD9x4sSCc9sajYbWrFlTeoGkltkmGwup+sZ5SWuf/Rj/5hxdqlxKAEUhped177XD+exrPD6efzbCGas6deqUfvrTn55z3S5pkJqcnCwPdb3iiiu0efNmbdq0qUwxp/fAoKwVORVxKqGAbyb1C/T6+vpKT8xvhjWVSE+FFKHFz6PFbkBsNlsp3Xx9t6lIBupdR3/HOFy0nOlR0IqKcbtoRVlZEBhNY3EDNJW2lZXfq0SgJ7XgerOeVkiMS7gvmKHnupN+dd0sVoIEnq6urjJxJu4ncp/5PmfseV7QgGAyi9vgcWP8y/1hj5JxJ9JrVBS+P9UWqUqn+tlR3G++jrScqTyXyX6y2Avkq0lcD99/8uTJCi07NzdXfkbrnPPEr3SIlJ7rvBQPKFL6EVBSny1HLkWAYn/RsKmjPxkDpq6xge71QJbgXOWSBinpDO3n1x97ky8D2N4waSvOHhM9KamViEFF5IXZ09Oj48ePlwd9kppzOrczwCKVJC18cy4XaQym+1orF8axqFio4FgulYOB1h5JLJ8AESczqVJTovZY/MM+tYfJ1GJLDIDTGo7xNysrnt/GjbLR6nP7I2jQArcS7ezsLKlIj62NGdeXAWOOoeeJ28LnkYJk9iXptZSkEiZ8r8uhd8/rUoo9xmVI5Zw+fVonTpyoUHNxXPhySVOBnp8+bdwJRe4Dp5d7DOKcdFaiPdJUneP/MbGk7loC3bkC1KUuUe9I1b137GdStTxd3kah/5+YmDgvdbvkQcrAQVrOlN/atWtVFEUJVIx3RA+C1BNTlnkSQFGcOR7JdBppIC/GaA37e3pO/jz+zcQM1s0KnEkVXJBRidF7pOKI5UaAo9JyOU7Y4H4eWuhS65QB7r+KAXmXyWeSarL4PtOGPOw2ejCkhiz839carD1m3s/kbDnuu2IWn+cMY5zsG/5NWsyfex5ERct7aCjw2a4/U7LZf7RiI/XFTdHRCPP3POmeQFwUrcQHKiYrK9aLczHOJ5ZLUFsMdPy5y1sMeNqtg5TXcDmDWTQOpeo+xZg8JbXijqdPn64k1EhaYDCerVzyIMWMOityH0I6MDCgoaEh9ff3V+giKgipGiBk/CButDRVNTU1VXoNpqQklZY5U995L5WPtNC6iZOHNBgVKAPHMdjORA0qFj7D1xK0YiyA4JbyhAgu8b7FlBUVckyeMJAYGDm2USKoWlxnWoqnT58uYylU0vaaolcntWJJ3AzMZxBwIojxd8qbin3qucv5HJN56CExsYdlMgGBoO7fzBK1kAa3weE9UhSOZ5wjfn708KKRxvq6zDrQSH0e7+d1S73+cpNoDMekp2i8WjzPpqeny0OOOUfOl1zyICW14jqONTk+NDAwoOHhYQ0PD2twcLAM+tuSllqL14kI9DjIrQ8MDJQKi/caqJhyPD8/XyoBL1zGMvxDa52LicqF4Mv7pIULkMqro6N13MxioBE9EoKdfxiUj1w0M+GokHwvYzSpmA5Tzu250AOgd+l2UEhh2jsg4Bj4TPU6+8xCj5PxMKbSp5Rd7Id2Xh4NFo8dxzb+uDyCZvS4YgyUIBXr5PsZozIwmRJmYou9LlKZvp5GWPSiCNpMVvIYpijm6A2djbS7j8r3cvWipGp2JIX/09uyXmVSjf82bXw+5LIAKSs9x4imp6fLdNjp6WlNTU1pcHCwPOqFi9uLyVa7rVaCARdl3KU/OTlZUkkGKi9mLlxuniXNRQqNizharBHYqHAYo2IyA7MKpYUWp6lMKlCWE5UmhcrRMbqenp7S8o8vFEx5rQQkeh1MwXc/MTuOiRMsy0Dn+ntRdXW1Dmu1guaxV+wTP8PAG6k+toE/0Sp1GX5G9Gik1gZWesoEcNYlUrPuJ4II+y6OGb00e0l8N5MlnoEY28i3DPBzKrZIYbr8mDAS7+E84Xx0X6SkHejE7y5XgIoUa2QEbJBwHGggpQ4XOJ9yWYCUVFUOp06dKlPTJWlsbEwTExMaGxvTxo0bNTc3p4GBgTIhwBlrMd4T6TBmvjQajZI6GR8fL/e0SK304bm5uQWndtMC9bVREUutmA3bF8GJdYl1tTcQ4yTkm/k3r3H9rMhcBuMwESDdFt/rvnACBxWSwYkgEJMiXI8UOPi6qMBMuxLQ7d35Lbe+z3UyXcvEFXp0Ni5InRIgIyWa6tNUnSRVyrDQs+SJGxbeT4CK84l7ulx/ZlvGrEzSiBEQXZcUHcx6MZYX20rQSinKOD/bKcUU7Rr/vlwBaTFJgT51nsfPuspj5ntS2wzOVS4bkCqKonJiRPQupqenNTExUR6UuX79+vKQV0kLrN6ocBhvoHLyPoKJiYky9do/zAZkOc6Yi9l3dZYMrU/G1ahUuI9KOqOs7OFEZeM2MH4VFRC9lZhIQPBzGc7ystVl8Hd/0iOLyRj0Xu1FWnG6XfYAUq/kcD28TcBi79jtYkzMC5F1jDSd74v7uzwPqFwpBgnGjTi+0YvnM52swtNROE4EHoKn60kvml4QP4seCzNdnd3nuZqaF1xzcb6wzqQ/uW7YZ6xHNMQIhhxHXh91QJaFEr1bf5ai+C2eL54D3LpzvuWyASmLFxq5cC/Ozs5OnTx5Unv37tXJkye1cePGShyKCivGF3xNb29vZbGR7qLlS1rFys28PGMuHR0dlRRd15tenZVTBEyCFCdctHRTi5f3kq4ihcM3d9q69zUsJ4KaT14wPeRy7JUxcM/sNZfnPmBc0NfzhGy32X0ekwlM7Tn92tmXpPhsJZIqYx9GejJmI3IsOG6cc5GOJL2aSs7hGY30gOLmW86NmBkYQYXXR/CJip8eeSyrztPh9Ra2k/f6Ofw7AiPrXHdtBqXlSRxn6ot4nedwKhRyvuWyA6nZ2dnyxAZPci9sJ0GcPn1aBw8erFA8pk545AsVmK1c//bp1FZAfo6tc1r7UgsUYmzL6fGMYdBaJmhFeifSRb4mKqhIQRHA4/f0mHjKA11/eh3Ry3I5trwYw4tWtPvE7aRyovXue+yd8aWDvo8UZfQ2mIIevSVpYUIHn0nFbpAyYERDgIrWBg/3lTH+xliN7/d40MOOr0wnoPu+GDeKSp6Sog4jbcf5xXIISLyeUkfT1dHO0fBK1T2C32IUYJaFUufBco1Fb5Weu9f/hZDLDqTscRD56SlIZ0BnZmZGY2NjJeh4b45PCLAi8cCxDCsfKmu/IM8gyBRfX+tyqKCsfK3IXb4nBPe3kB5KKVIu7NTkit5TtIKt7O3t8HQJl2nA5zFEjG3w6By2lyBCkIqKiArIfzvJgR4rFx1pKlKLEUSYERfjdfRSfA/bTbrXn7EfCHws3/1BmpRUK+dopKkN9BF4U2AfASTlcXANUDFZomUdFZilHTClrom0XAQoS5wDnOMstx1IZmkv7fovZbRI1XjqhZDLDqSkFlBF78EUnL2D2dlZjY2NlQpkzZo15TljtprbpRkzbf3UqVMlTeN4Ey31mBZNL85CwDDIEZwi7cFUeCpHSuwD/s1YDC1+e4r2Blg/JjfEPqcyJv1Gj9bZZAYc9wGVP4WesPvU7TYIsy0ug+cD8icCisWgxhgdDQWPgcvnYjZI0tNl/MttoPHEvUjM6qN3zHkShcZJBKiUskkBUCwvReOllFYsk2PFsuJ1EZxSytCf01OOFn6Wc5douMR5EcEsleF7vuSyBCm+vtuKQ2p5JVLLKp+ZmdHBgwclqTyg1pt/G41G5QxALjZ7X+RurdgZM/H1kip0GF1pqWXJR6+KXH6MEcQYCa8jNcc6sBx6A/FAUdIuLNteIfvB/6cSI+ghOL5ihcP0bi8K96mFyrrZbJblsmwrfoIMx56ZcpEypfflMTBIuY0GPPYNQd20aBxbpvBHIGJsLeVFRUlRZKnrUzRpBI2ogFKKKuUtETDifFzMc+L6SQEgQTJ60/zN+qT+zrK4tOvLlAd+ofv3sgQpqfr2VdIp9qYIIjMzM9q/f3951p+kcsOvFWgMqtPDYbzLae+NRqOMK/h/WtYsywqNEyRulGSAPfL2qbR5x4sY7OR3Bg2DHd/7REvW37v9cVOq60M6z16mKTiDE69z2R0dHZU+inRmVGL0pHwfaciiKErA5f1MYGC/ExypIOl9sa4patZ93Wy2TogwTUcwijRailajRGVPSfWL/4/0dlT6vMefx7hEBDECTDuwjNsGuE58bQTXOmBeTElmcDp7SfVtnWecmpvnUy5bkKKFHBWMaScCx+zsrI4cOVImPQwPD5enZpvGk1Sx+q0Q7AF1dXWVr4QwQPp1BrFu/E0qy0qeGVsENz+TipLeB59NLzJlPfv5EfQ8KWNmj1T1RgkmfLaFm0xNrxq4qOAY9Pd93Evm9hAsCdAE6dhmxqcIzAYV76Fas2ZNCaiM57lvY/+5DgYhJjjEbEX2T5wDUdqBQ+p3HEvOk7rr43X8zTrUKbD4DH8fT8Dw96TNo6e0mCzn2izLkzpvmdLOUDpfctmClNRSdqTbTDH5rbikcObn5zU1NaVjx45JOqNg/Gp3UnwxeG0vxOU484+Uj4XgRgXGEycMWLRuo3djq5WegX+z7Jg6Hr3K+LmkigJnIgqzy6iArNCdbGHvyF6YFRZT/KMlTXotghEpT6l63JLrasVIAPLfLJ+xJj/riiuu0Nq1a9VoNCqnMHARM5ZIz41jnKLfouLneEYQSCn96NlyjFPgQk85peCpiHgvn8v6pRQX2xPrHdtXF39NPTP2WQaniyvWRRdaLmuQshcSqQZ7VVYuTJSYmZnRiRMnKqnXzWazzPyj8pRaIHXFFVdoenq6Qg86048vT/Q9FlIkUeFw4y0BhRl/rKOFioGvUzfQRAVG5UbFwuQPfk4PNBV/S5XLpIO4n4cxDoKapEq9CZQEIoNQjO24DgZzZiq6PXFDsRManObOeFVMfiFYtFOydTGfOuXMfkwBGstNgVDq7/j8OoCKUkfzxZ9oHEUvrZ20864yUF08ebX6/rIGKdJUppm4V4nKmHtpHAy3JzEzM6Mrrriicpq6VD2523EQ0m6SyngMLX7/Zuo2lbiFgemUtUoPI+V1+X+mUPsz/m5nDUeJsRqpSmlFYItAxbRr9hNjGbyG4MTxiiDLvmAmJJMnYrailapPeDYY2ZNaDJTq+q/Og0n1f50Cj2MYJQUy7Z6fknbgQU/Jv6N3x++ZtJLymOoAKM7FDEoXVzgnM0i9SmIlwz0vXvy0vu0R0FOYmzvzsjx7SjMzM5UU9e7u7ori4z4hg41fVU8FS0/H9aCyltJ7Wvw5rVeCUrTEJVUUfCr1miBCsEvRmr6GissxKypUA0ZU5u08OY4HacWo3Gmtx7qTko2KMp6W4bGIB7ymPDU+n785HpQ6j2Q5i76d55Si65YKONFzjc+KhhHvpTHFMSeQp+reDoCWCqhZXj15tccjTQLXyAMPPKCbbrpJAwMD2rx5s9797ndr9+7dlWve/va3L3D1P/jBD1au2bt3r+68806tWbNGmzdv1n333XdB8+wXEytH/k2gklp7a06ePKmxsTEdOXJEBw8e1MGDB3X48OHy58CBAzp06JCOHDmisbExjY+Pa3JyUtPT0xUgYNqzYzUGNWaIRSoyJVTC9GTixtSorEmdRa8ilpPyfniMj0HZ9KLL5EGsBCapCqg2BGgE8HN6MfZs/BJFgzwVpfcmOSPT/cs+pmHiNzhPTU1pYmJCExMT5dhNTk5qamqqfMU5N9BG+jC2K1JdKe+qDkBYBufqUujC6OHUgWU0SGgQ8P8IXpxPnM+cK563TCxJGUfR+6wzrLJcnrIsT+rxxx/Xjh07dNNNN2lubk6f/OQndfvtt+v5558vD2KVpPe///367Gc/W/6/Zs2a8u/5+XndeeedGhkZ0fe+9z3t379fv/mbv6nu7m794R/+4Xlo0vKl2TyTGpzae0SvyckCfBOl3xDb19enqampMlZl5eg4FeMMLtOgZarJdJcVAPf2RICKGXdS1eNgHIr0m38Y4/L/BqdUjMNKI2ayReUjVbMRWU8qo6joSN35eKBIe9LLiiAc947FZzAe5XjS/Px85UghKsaYiBAVfcrTi+ARPZGlUqYRlFJlpLyfOGZL8Z7iM3xf9BA5t1J19/OZKcn5Fj2zlFcf+yZLFklqFOcwGw4fPqzNmzfr8ccf1y233CLpjCf15je/Wf/+3//75D1f//rX9Y//8T/WK6+8oi1btkiS/tN/+k/6+Mc/rsOHD5f7V9rJxMSEhoaGzrbaSWk0zhx2SqpIai0ob8i1UqW35c2pTlXmRk7/uJtdhi1OK02fDs7nOnWZi94A4Dr6s5h84D1YfFadYiFoMYbQDqx8f6T5XG/WMZYrVQ9KZV9IqvRZ3OOVii3F7xmX8nMNSDHrj4kdVKhuryW2MdKKUVJAzj6P16VAZTEAi/Vs53XFMuqWfTsw9Fil2s99cHUef13727W3DswyiF06Mj4+rsHBwdrvzykmNT4+Lklav3595fM//dM/1X/7b/9NIyMj+uVf/mX97u/+bulN7dy5U9dff30JUJJ0xx136J577tFzzz2nt7zlLQue44wqy8TExLlUOylFUZTZdwbKGBT3QjWFxe8nJydL5Wfl65MGYlZTpDkc52D2WtwH5KOUIlC5nlz8KUqNdWViSDyBwT8uJ0VRMS6WUoq0miOIRe8uRU2yLfG4p1QcKCYxxL1I9qSYcFEHwIzJ8ZqU8cL/o9RRcLwvpYBpOKTAsu65BO0UtVg3N+rqHunC6LmnxiD13HZlx7qlQKhdHTNQXR5y1iDVbDb14Q9/WG9729t03XXXlZ//2q/9mrZt26Yrr7xSTz/9tD7+8Y9r9+7d+spXviJJOnDgQAWgJJX/HzhwIPmsBx54QJ/5zGfOtqrLkhjUl1ppzrT0qfh8j4HU3zuhwq+rl6reTyoo7+fFI3b4Hh8pDQjR03FcRlLSu0iV5eenlHFMNoiAwv5ivILP4d409kUs131rMWinjhDiaRIxSN/O+yFwtvOgPC9S4EZJ0YF1yjQFkqny4vesd5wDvD5FraUUfxw/gl2qHtHDrvu7rk2xffGalMe5GLBnsLq05axBaseOHXr22Wf13e9+t/L5Bz7wgfLv66+/Xlu3btWtt96ql156Sddee+1ZPev+++/XRz/60fL/iYkJXXXVVWdX8XMQekFWCgYfp6Mz/dkv+vNeKyoBaaHiY9aapApIOWYV6TQeQ8TkDysunp0X25Lyevi9lXpUvPQuoqLwPa537LeUwqPiZYJF9GLdxpi0wLIjdRZjS9FbSln+7QAhAk8K9GNfxv6Oz/BvXpPylFin1HNopEQDgtfHZ/J3pDXZxjrvczkgUQc4qT5L9VPquyyXtpwVSN1777362te+pu985zt67Wtf2/bam2++WZL04osv6tprr9XIyIh+8IMfVK7xAa4jIyPJMkybvVrijbAWLgZ7QJIqQEUgsPJ0Rlqz2Sw9GitvAhUVb53Hw8y5uky/qIBcPr9LUTX+HWlI7muJCRCp57pse0z8jOBLrycCVaQbo1cUg/L8O+VRRMWf8izYjnhPSpbqIbC8lJJPARGBNH7eTlKAEQG1Hbilyopl1AFvXTmptsU+ifVJlZcB6vKWZYFUURT60Ic+pIcffliPPfaYrrnmmkXv2bVrlyRp69atkqTR0VH9wR/8gQ4dOqTNmzdLkr71rW9pcHBQ27dvX2b1L4z4ZXwUKrn4/qKU5UklLKkCPKbvTCPGk7BTCtjvo6o7a8+eBPcARcufAOXsuwgubIPLjJ4HvQ/3DUEsWv0xmcHfRZCS0i+3i9e4fnF8Up5S/B3vb6fsUl5CHeXE9kaJHks7SYEK217XjlS94z3tgDfem3oGx3mpkgKiOi+xrr9Zh/h3lktflgVSO3bs0Be/+EV99atf1cDAQBlDGhoaUl9fn1566SV98Ytf1C/90i9pw4YNevrpp/WRj3xEt9xyi2644QZJ0u23367t27frN37jN/RHf/RHOnDggD71qU9px44dr6q3tJhwodtTYmq4Ex2kqoJMeQj0zLjoDFL2zmIZvo6v/IjKhycvRJBqNpuV8wRTpzkQLFhnelCsS8oTIS1mRWbw9XUEKqnlhTLeF0HeUudxtPue5aeC/amy2il813mpCjIq1Trlm6pLOyXeTiKI13kgqf5L9UHKk4lJOnWgmZrv0sL3o/k3+6jOGMngdHnKslLQ66ywhx56SO973/u0b98+/bN/9s/07LPP6sSJE7rqqqv0nve8R5/61KcqKYZ/+7d/q3vuuUePPfaY1q5dq7vvvluf+9znFngvdXIhUtDrxEreoOTFxANjCTTO+uOiazablevj5tiYZefPXa77JYIQQSYCHL02JiLE9HU/i2UT9Fx/X9PO6mV/WVJ140ZdApUB2eVboqKLXhjbQzrV/eSxYdyKQoMktpnPX4ySihQnQTHVd3WeV909UdivBOboSdWBcAoMFlMHqb1f7LN21BzPmkxRzu0kA9SlK4uloJ/TPqmLJa8mSFn58Hw7KgMuOCvGuh32VsIxe84L12X7c3oAdcf50LqPtJrBNNaVCo11JXjEfU60hHldVNgGGXpzTGzg/bGfDMjsj5QSjJ5rtMJjKn2zeeaVGVHB+vroLbE9HDvew2tIVRIYDcjRq4nAwmctBkx8vo0JflbnhURp52m1ExpGnDOcY6kyaCxxbOOz23l0WS5NuaD7pC4HKYrWq72pVLjYonfE3ymvJy7k6H1Ehev74rloVI68NypAC8vjPiyW6b+jRU76LNY1Agefxx8+J5brfqBiZ9kpSio+L2Yppjza1PjG/9vFXVJeUF35dbRd/L9OCdd5q3UeHenCunvr6rJYnVg2vcbUuKbKNKCmjI9UW1J1yHJ5SgapJUqdxR4VsRde6iRu029Uaqkjj+oURKRIokWa8naotOIzeHQR69punwz7Imby8btUHaP3GBMcbBBESjIFXHXeTWpDcOyDxbyNVP/XfU6PksZDHVjHOqTGZbH60Auq84bqnpO6Po5B3bOjgRKfV/fM1HdsB/uurg+yXL6SQWoZQoUpLXwthRcdjyey0mLiRcri5YbWFA3k8trdl/JQIrilAI30mj+jp+UyohKJyoXfxWvjEUasC5W4KaFURmGdRAMhlk96MUqM48R72Yb4PP5dZ/0TUFLewrlI9GLblR1BLYJGyoiIYNjO81lKjKkOBDNAZWknGaSWITG9mpttHXuJ+3yYTUeKxOX4ZYpxI26kUeooHAIV6ceYhh49OoKZP09Z/4yL1Xl8KSXDOrM+KWHd4rueeE30jOo8k5ggQbCKCREpTzL2f+zDlKT6rx1wpf5OlbNYn/HvOg8w9dlygKSO0kuV307qPKzF+jbL5S0ZpJYpUQmm3porteIr0UthOb6eb/71RmFel/otLaQBaflaYuyMnt9i9WLSA8sgeLEesRwCeSw7gi69P15PzzTGmBajukjHxusJdBGkYtYm+9u/U8q+7jmpOtZJXXnnU4mnvE56r3XUaCpbMbICS6E63c4MTlmWIhmkzkJSNFj0PKjwpOprJqTqe3bie3gWs1bp0S1mrcf9R1Ep1ykKtytm+bFsptv7GpcX41pR4ce2uS95mnZ8bmwblR8BOnpzdYCSoprqvIM6oGinaJfraaTKPhfgqxvXCN4R+FNzxt/Fvq+jGuvoRT4vA1SWpUgGqXMQK7jTp08vOFU8SmdnZ+klMUuPZ/C5DAKftDAzMKaBx9TylGfH+tJTiZ6bxWWlAuVS1SuLJ6nXSaPRKJM1imIhDZhSaGxz/I730TOKEpVivLbOKKDXzOcsJnVlxXamvqtrV919bEsdKMbyedpI6hmp59R5kdETToFRXV3Ot4eY5dKUDFLnIFZitMh53h3ByP8zmYIWfypZgBRYCiyoGKKC4GG0kbLhSwRdjuvp3y6TQBg9jVTmXspDSdF4qeewnPg691TWXEoBLuY1xeekvC4bDwSp6LVFSXlh7YCprg1R6kA/lsf+XSwVPNVHvC963LG+ZAkiqLGPUt7YctqeJYuUQeqshcrN/0fL0hL5+qhoDV5U7JIqKeIuJypLKn6mvdOr8vFEKXqmTnnQe4kAFdvsclObgX19ytqPStFlRgu/jlZqp/yiAmxHG9Yp4lRWZOrepVJty5HYH7HM1Biy3ikQS7UjNU/9d+z3OL8j2KeyP1P1zZJlOZJB6hwkWov+HcGoHTikXlQXFTWfF2kXg0PcS5QKhEc6LsamosJJAafLarcxlvVnP9E6J+0XFX1KkUbqbCnglLom5TXWKdo4timaK9X+c5E6UE49IwVksd+jlxuflSo3dbKJr08ZYTEOmyo/PiNLlqVKBqnzJClrPNJhUbnS24kg5e8jINArifGcdlZtO0WfUsa8n7QdPciUEmI7vXGZ/eC2Rjop5YXWAWgddZaS5VzLPqj7fKmKts4oqbu/HaD6vroyoleTMm5SZUavXKpuho6SKjNlZKQkA1SWs5UMUhdAUlZ6XRac/09Z6bwuUm1xs218furEi1i3OqDx9dy7xWfH61hvxp+46ZlWPalB3pvyIpcDDu2AIHob/HwpXlGqHnUAGMEiAsNS2xDrm/Ji/H/clF33nNSci0ZUnfGSGo+ljEsGqCznIhmkLpDQq/D/qWuYGZcCK4NJPJcuKnZ/Fr2uqCQJOKmsuZSir6OFUl5hinZiff1dPEqJ+7HoJdZ5BbH8doDL/+s8hJRyTl3X7v+lPHcpfRnvS4FT6hnRoKGkaMA6Sc0ry2JJGVmynG/JIHUBJdJfKcVgj6fuhAgDT0oBRM8mAls7wFgsrTvWP0pK6dIiZ/IE2+CNy6yzhYkasez4eVS6Me2+jirzd+1oqsXAqk7aeaXtvmv37LrvSQ3XPafuudFziiAUvdhY55RkgMpyoSSD1AWWOi+A/0cQqrOS471UQqn4F++N9NpSvIbFrO0oPELJ/0fgYFtSAXcCVaSkvI8sBeSpOArbWOc1pvp9qQp3qdRdOzo3ZTzE+2MSQ1EUFbp3KbRgnacVx6AOuJfa/gxWWc63ZJB6laROMdZdd7bfp4TeTSyjDjjbKeAYM4pK1wo0RWf5lPOU4vX1PLYppq/XKftU39T1VQrI2U9LBed25dfdu1j/um51yQu8N9WH/H4p/dKO2ov1TI1najyyZDmfkkHqVZTUgl9MEfnaxRROpG5IIcZrU89NlVvnmcTfqVMjXAY9vuj1RUXMpJBIOy2lD+r+jxJBKrUpObYn5YXUfZ6q51L61/emTtc/G4neUV0bzkUyMGW50JJB6gLLYsorfp6KnfDvpVj7S6lL6hntrqmTSCP6dzuvYTFP8mxBaKngtBRZ6rXnqqRT99eNRzs6Mhor/HwxT4pSF9dbitR5XVmynItkkHoVZTGqr52CWExxpcpaLO602D119W2nxOoAKnp4dSBQR0supy11tFS7WIy/pwdXNwYxVlYHEHX31xkZETziQcIRpFLgkwKp1HPaje9SY03LnV9ZspyNZJB6lWQpVmmKWqrznlJeVqqsVOwlVZ9UzCdVdopWpKQUf/w8nmgQFXBMJ1+qMkz1A+nGurPtYup8PBWdtCPLikAcwYvSLh4Y6yupjNulvKJUGYuVW/ecxaTOm283nzNoZTmfkkHqAkqj0Tp1oR0Ftpi1u5i0i4nQQ0jVr06xtgPEdnVPXRsBKgU6rMtiFFiqnVF5xjrEI6BiW+pAPx7822g0yhPr6wAj9p+9x3Z0XaqtEaxT9V9qmXXPWWx+pYB4KddnyXK+JIPUBZSiOPMqjK6urraeTVRudZlvVCop5RHLS9GH7a6pA9EodYkPbEMdVRcVOyWVKNDOS4z/1z2XdSaYRQDwhmLf6+/jOYPxmKe69ixGpbUD+7r/F/OiliLLBZpYT9KidfecTX3qysi04uUtGaReBfEp5ItJOwXOa5b6+VLKWk55UVLe2WJlzM/PL3j54XKlrm6x3HaUZOr6eA2/p3ezWLuXKmc71hf6uYtdfy7e29nUJ4PT5S31b6jLkiVLlixZLrJkkMqSJUuWLCtWMkhlyZIlS5YVKxmksmTJkiXLipUMUlmyZMmSZcVKBqksWbJkybJiJYNUlixZsmRZsZJBKkuWLFmyrFjJIJUlS5YsWVasZJDKkiVLliwrVjJIZcmSJUuWFSsZpLJkyZIly4qVDFJZsmTJkmXFSgapLFmyZMmyYiWDVJYsWbJkWbGSQSpLlixZsqxYySCVJUuWLFlWrGSQypIlS5YsK1YySGXJkiVLlhUrGaSyZMmSJcuKlQxSWbJkyZJlxUoGqSxZsmTJsmIlg1SWLFmyZFmxsiyQevDBB3XDDTdocHBQg4ODGh0d1de//vXy+5mZGe3YsUMbNmxQf3+/7rrrLh08eLBSxt69e3XnnXdqzZo12rx5s+677z7Nzc2dn9ZkyZIlS5ZLSpYFUq997Wv1uc99Tk899ZSefPJJ/eIv/qLe9a536bnnnpMkfeQjH9H//t//W1/+8pf1+OOP65VXXtF73/ve8v75+XndeeedOnXqlL73ve/pv/7X/6ovfOEL+r3f+73z26osWbJkyXJpSHGOsm7duuJP/uRPirGxsaK7u7v48pe/XH734x//uJBU7Ny5syiKonjkkUeKjo6O4sCBA+U1Dz74YDE4OFjMzs4u+Znj4+OFpPyTf/JP/sk/q/xnfHy8rb4/65jU/Py8vvSlL+nEiRMaHR3VU089pdOnT+u2224rr3njG9+oq6++Wjt37pQk7dy5U9dff722bNlSXnPHHXdoYmKi9MayZMmSJUsWS9dyb3jmmWc0OjqqmZkZ9ff36+GHH9b27du1a9cu9fT0aHh4uHL9li1bdODAAUnSgQMHKgDl7/1dnczOzmp2drb8f2JiYrnVzpIlS5Ysq1CW7Um94Q1v0K5du/TEE0/onnvu0d13363nn3/+QtStlAceeEBDQ0Plz1VXXXVBn5clS5YsWVaGLBukenp69PrXv1433nijHnjgAb3pTW/SH//xH2tkZESnTp3S2NhY5fqDBw9qZGREkjQyMrIg28//+5qU3H///RofHy9/9u3bt9xqZ8mSJUuWVSjnvE+q2WxqdnZWN954o7q7u/Xoo4+W3+3evVt79+7V6OioJGl0dFTPPPOMDh06VF7zrW99S4ODg9q+fXvtM3p7e8u0d/9kyZIlS5bLQJaTyfeJT3yiePzxx4s9e/YUTz/9dPGJT3yiaDQaxTe/+c2iKIrigx/8YHH11VcX3/72t4snn3yyGB0dLUZHR8v75+bmiuuuu664/fbbi127dhXf+MY3ik2bNhX333//cqqRs/vyT/7JP/nnEvlZLLtvWSD1W7/1W8W2bduKnp6eYtOmTcWtt95aAlRRFMX09HTxO7/zO8W6deuKNWvWFO95z3uK/fv3V8p4+eWXi3e+851FX19fsXHjxuJjH/tYcfr06eVUI4NU/sk/+Sf/XCI/i4FUoyiKQqtMJiYmNDQ0dLGrkSVLlixZzlHGx8fbhnDy2X1ZsmTJkmXFSgapLFmyZMmyYiWDVJYsWbJkWbGSQSpLlixZsqxYySCVJUuWLFlWrGSQypIlS5YsK1YySGXJkiVLlhUrGaSyZMmSJcuKlQxSWbJkyZJlxUoGqSxZsmTJsmIlg1SWLFmyZFmxkkEqS5YsWbKsWMkglSVLlixZVqxkkMqSJUuWLCtWMkhlyZIlS5YVK6sSpFbhK7CyZMmSJUtCFtPnqxKkJicnL3YVsmTJkiXLeZDF9PmqfDNvs9nU7t27tX37du3bt6/tWx1Xs0xMTOiqq666pNso5XZeanI5tPNyaKN0YdtZFIUmJyd15ZVXqqOj3l/qOq9PfZWko6NDr3nNayRJg4ODl/QkkS6PNkq5nZeaXA7tvBzaKF24dg4NDS16zaqk+7JkyZIly+UhGaSyZMmSJcuKlVULUr29vfr0pz+t3t7ei12VCyaXQxul3M5LTS6Hdl4ObZRWRjtXZeJElixZsmS5PGTVelJZsmTJkuXSlwxSWbJkyZJlxUoGqSxZsmTJsmIlg1SWLFmyZFmxsipB6vOf/7z+zt/5O7riiit088036wc/+MHFrtI5ye///u+r0WhUft74xjeW38/MzGjHjh3asGGD+vv7ddddd+ngwYMXscZLk+985zv65V/+ZV155ZVqNBr6sz/7s8r3RVHo937v97R161b19fXptttu009+8pPKNceOHdOv//qva3BwUMPDw/rt3/5tTU1NvYqtaC+LtfF973vfgrF9xzveUblmpbdRkh544AHddNNNGhgY0ObNm/Xud79bu3fvrlyzlHm6d+9e3XnnnVqzZo02b96s++67T3Nzc69mU2plKW18+9vfvmA8P/jBD1auWcltlKQHH3xQN9xwQ7lBd3R0VF//+tfL71fcOBarTL70pS8VPT09xX/5L/+leO6554r3v//9xfDwcHHw4MGLXbWzlk9/+tPF3//7f7/Yv39/+XP48OHy+w9+8IPFVVddVTz66KPFk08+Wbz1rW8t/uE//IcXscZLk0ceeaT4V//qXxVf+cpXCknFww8/XPn+c5/7XDE0NFT82Z/9WfGjH/2o+Cf/5J8U11xzTTE9PV1e8453vKN405veVHz/+98v/s//+T/F61//+uJXf/VXX+WW1Mtibbz77ruLd7zjHZWxPXbsWOWald7GoiiKO+64o3jooYeKZ599tti1a1fxS7/0S8XVV19dTE1NldcsNk/n5uaK6667rrjtttuKH/7wh8UjjzxSbNy4sbj//vsvRpMWyFLa+P/9f/9f8f73v78ynuPj4+X3K72NRVEU/+t//a/iz//8z4sXXnih2L17d/HJT36y6O7uLp599tmiKFbeOK46kPqFX/iFYseOHeX/8/PzxZVXXlk88MADF7FW5yaf/vSnize96U3J78bGxoru7u7iy1/+cvnZj3/840JSsXPnzlephucuUYE3m81iZGSk+Df/5t+Un42NjRW9vb3Ff//v/70oiqJ4/vnnC0nF//2//7e85utf/3rRaDSKn/3sZ69a3ZcqdSD1rne9q/ae1dZGy6FDhwpJxeOPP14UxdLm6SOPPFJ0dHQUBw4cKK958MEHi8HBwWJ2dvbVbcASJLaxKM6A1L/4F/+i9p7V1kbLunXrij/5kz9ZkeO4qui+U6dO6amnntJtt91WftbR0aHbbrtNO3fuvIg1O3f5yU9+oiuvvFKve93r9Ou//uvau3evJOmpp57S6dOnK21+4xvfqKuvvnpVt3nPnj06cOBApV1DQ0O6+eaby3bt3LlTw8PD+gf/4B+U19x2223q6OjQE0888arX+Wzlscce0+bNm/WGN7xB99xzj44ePVp+t1rbOD4+Lklav369pKXN0507d+r666/Xli1bymvuuOMOTUxM6LnnnnsVa780iW20/Omf/qk2btyo6667Tvfff79OnjxZfrfa2jg/P68vfelLOnHihEZHR1fkOK6qA2aPHDmi+fn5SudI0pYtW/TXf/3XF6lW5y4333yzvvCFL+gNb3iD9u/fr8985jP6R//oH+nZZ5/VgQMH1NPTo+Hh4co9W7Zs0YEDBy5Ohc+DuO6psfR3Bw4c0ObNmyvfd3V1af369aum7e94xzv03ve+V9dcc41eeuklffKTn9Q73/lO7dy5U52dnauyjc1mUx/+8If1tre9Tdddd50kLWmeHjhwIDne/m4lSaqNkvRrv/Zr2rZtm6688ko9/fTT+vjHP67du3frK1/5iqTV08ZnnnlGo6OjmpmZUX9/vx5++GFt375du3btWnHjuKpA6lKVd77zneXfN9xwg26++WZt27ZN/+N//A/19fVdxJplOVf5p//0n5Z/X3/99brhhht07bXX6rHHHtOtt956EWt29rJjxw49++yz+u53v3uxq3LBpK6NH/jAB8q/r7/+em3dulW33nqrXnrpJV177bWvdjXPWt7whjdo165dGh8f1//8n/9Td999tx5//PGLXa2krCq6b+PGjers7FyQaXLw4EGNjIxcpFqdfxkeHtbf/bt/Vy+++KJGRkZ06tQpjY2NVa5Z7W123duN5cjIiA4dOlT5fm5uTseOHVu1bX/d616njRs36sUXX5S0+tp477336mtf+5r+8i//Uq997WvLz5cyT0dGRpLj7e9WitS1MSU333yzJFXGczW0saenR69//et144036oEHHtCb3vQm/fEf//GKHMdVBVI9PT268cYb9eijj5afNZtNPfrooxodHb2INTu/MjU1pZdeeklbt27VjTfeqO7u7kqbd+/erb17967qNl9zzTUaGRmptGtiYkJPPPFE2a7R0VGNjY3pqaeeKq/59re/rWazWSqH1SY//elPdfToUW3dulXS6mljURS699579fDDD+vb3/62rrnmmsr3S5mno6OjeuaZZyqg/K1vfUuDg4Pavn37q9OQNrJYG1Oya9cuSaqM50puY500m03Nzs6uzHE876kYF1i+9KUvFb29vcUXvvCF4vnnny8+8IEPFMPDw5VMk9UmH/vYx4rHHnus2LNnT/FXf/VXxW233VZs3LixOHToUFEUZ1JCr7766uLb3/528eSTTxajo6PF6OjoRa714jI5OVn88Ic/LH74wx8Wkop/+2//bfHDH/6w+Nu//duiKM6koA8PDxdf/epXi6effrp417velUxBf8tb3lI88cQTxXe/+93i537u51ZUena7Nk5OThb/8l/+y2Lnzp3Fnj17ir/4i78ofv7nf774uZ/7uWJmZqYsY6W3sSiK4p577imGhoaKxx57rJJ+ffLkyfKaxeapU5dvv/32YteuXcU3vvGNYtOmTSsmPXuxNr744ovFZz/72eLJJ58s9uzZU3z1q18tXve61xW33HJLWcZKb2NRFMUnPvGJ4vHHHy/27NlTPP3008UnPvGJotFoFN/85jeLolh547jqQKooiuI//If/UFx99dVFT09P8Qu/8AvF97///YtdpXOSX/mVXym2bt1a9PT0FK95zWuKX/mVXylefPHF8vvp6enid37nd4p169YVa9asKd7znvcU+/fvv4g1Xpr85V/+ZSFpwc/dd99dFMWZNPTf/d3fLbZs2VL09vYWt956a7F79+5KGUePHi1+9Vd/tejv7y8GBweLf/7P/3kxOTl5EVqTlnZtPHnyZHH77bcXmzZtKrq7u4tt27YV73//+xcYVCu9jUVRJNsoqXjooYfKa5YyT19++eXine98Z9HX11ds3Lix+NjHPlacPn36VW5NWhZr4969e4tbbrmlWL9+fdHb21u8/vWvL+67777KPqmiWNltLIqi+K3f+q1i27ZtRU9PT7Fp06bi1ltvLQGqKFbeOOZXdWTJkiVLlhUrqyomlSVLlixZLi/JIJUlS5YsWVasZJDKkiVLliwrVjJIZcmSJUuWFSsZpLJkyZIly4qVDFJZsmTJkmXFSgapLFmyZMmyYiWDVJYsWbJkWbGSQSpLlixZsqxYySCVJUuWLFlWrGSQypIlS5YsK1YySGXJkiVLlhUr/z+T0jsbuk8xfQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(Example_train_nii.get_fdata()[:,:,selected], cmap = 'gray')  #choose which axis?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1d5434786a0>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(Example_label_nii.get_fdata()[:,:,selected],cmap='gray')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "DataProcess"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "Main_NII_Path = Path('C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imagesTr')  # it should be the complete path\n",
    "Label_NII_Path = Path('C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\labelsTr')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n"
     ]
    }
   ],
   "source": [
    "if Main_NII_Path.exists():\n",
    "    print(True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "20\n",
      "20\n"
     ]
    }
   ],
   "source": [
    "NII_Images = list(Main_NII_Path.glob(\"*.nii\"))\n",
    "NII_labels = list(Label_NII_Path.glob('*nii'))\n",
    "print(len(NII_Images))\n",
    "print(len(NII_labels))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "Image_Series = pd.Series(NII_Images, name = 'trainImage').astype(str)\n",
    "Label_Series = pd.Series(NII_labels, name='label').astype(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0     C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "1     C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "2     C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "3     C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "4     C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "5     C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "6     C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "7     C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "8     C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "9     C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "10    C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "11    C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "12    C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "13    C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "14    C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "15    C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "16    C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "17    C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "18    C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "19    C:\\Dpan\\py_project\\Heart_Mri_Segmentation\\imag...\n",
      "Name: trainImage, dtype: object\n"
     ]
    }
   ],
   "source": [
    "Main_Data = pd.concat([Image_Series, Label_Series],axis=1)\n",
    "print(Main_Data['trainImage'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import cv2\n",
    "Image_List = []\n",
    "Label_List = []\n",
    "\n",
    "for i_image, i_mask in zip(Main_Data['trainImage'].values, Main_Data['label'].values):\n",
    "    reading_Train_nii = nib.load(i_image)\n",
    "    reading_Label_nii = nib.load(i_mask)\n",
    "\n",
    "    X_Images = reading_Train_nii.get_fdata()\n",
    "    X_Labels = reading_Label_nii.get_fdata()\n",
    "    \n",
    "    max_area = 0\n",
    "    selected = 0\n",
    "    for j in range(X_Images.shape[2]):\n",
    "        temp = np.sum(X_Labels[:,:,j])\n",
    "        if temp>max_area:\n",
    "            max_area = temp\n",
    "            selected = j\n",
    "\n",
    "    Selecting_Image_1 = X_Images[:,:,selected]  #normalization\n",
    "    Selecting_Label_1 = X_Labels[:,:,selected]\n",
    "    Selecting_Image_2 = X_Images[:,:,selected-1]  #normalization\n",
    "    Selecting_Label_2 = X_Labels[:,:,selected-1]\n",
    "    Selecting_Image_3 = X_Images[:,:,selected+1]  #normalization\n",
    "    Selecting_Label_3 = X_Labels[:,:,selected+1]\n",
    "\n",
    "\n",
    "    Selecting_Image_1 = Selecting_Image_1.astype('float32')\n",
    "    Selecting_Label_1 = Selecting_Label_1.astype('float32')\n",
    "    Selecting_Image_2 = Selecting_Image_2.astype('float32')\n",
    "    Selecting_Label_2 = Selecting_Label_2.astype('float32')\n",
    "    Selecting_Image_3 = Selecting_Image_3.astype('float32')\n",
    "    Selecting_Label_3 = Selecting_Label_3.astype('float32')\n",
    "    Image_List.append(cv2.resize(Selecting_Image_1,(128,128)))\n",
    "    Label_List.append(cv2.resize(Selecting_Label_1,(128,128)))\n",
    "    Image_List.append(cv2.resize(Selecting_Image_2,(128,128)))\n",
    "    Label_List.append(cv2.resize(Selecting_Label_2,(128,128)))\n",
    "    Image_List.append(cv2.resize(Selecting_Image_3,(128,128)))\n",
    "    Label_List.append(cv2.resize(Selecting_Label_3,(128,128)))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n",
      "(128, 128)\n"
     ]
    }
   ],
   "source": [
    "for i in range(len(Image_List)):\n",
    "    print(Image_List[0].shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1d543420880>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "figure,axis = plt.subplots(1,2,figsize=(12,12))\n",
    "axis[0].imshow(Image_List[0])\n",
    "axis[1].imshow(Label_List[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Image Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def preprocess_image(image):\n",
    "    # Normalize the image to the range 0-1\n",
    "    normalized_image = cv2.normalize(image, None, alpha=0, beta=1, norm_type=cv2.NORM_MINMAX, dtype=cv2.CV_32F)\n",
    "    \n",
    "    # Convert normalized image to 8-bit (0-255)\n",
    "    normalized_image_8bit = np.uint8(normalized_image * 255)\n",
    "    \n",
    "    # Apply histogram equalization\n",
    "    equalized_image = cv2.equalizeHist(normalized_image_8bit)\n",
    "    \n",
    "    # Enhance details using Laplacian\n",
    "    enhanced_image = cv2.Laplacian(equalized_image, cv2.CV_64F)\n",
    "    \n",
    "    return enhanced_image"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(60, 128, 128, 1)\n"
     ]
    }
   ],
   "source": [
    "X_Train = np.array(Image_List)\n",
    "X_label = np.array(Label_List)\n",
    "for i in range(X_Train.shape[0]):\n",
    "    X_Train[i] = preprocess_image(X_Train[i])\n",
    "X_Train = X_Train.reshape(X_Train.shape[0],X_Train.shape[1],X_Train.shape[2],1)\n",
    "X_label = X_label.reshape(X_Train.shape[0],X_Train.shape[1],X_Train.shape[2],1)\n",
    "print(X_Train.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "def unet_model(input_size=(128, 128, 1)):\n",
    "    inputs = Input(input_size)\n",
    "\n",
    "    # Encoding path\n",
    "    c1 = Conv2D(64, (3, 3), activation='relu', padding='same')(inputs)\n",
    "    c1 = Conv2D(64, (3, 3), activation='relu', padding='same')(c1)\n",
    "    p1 = MaxPooling2D((2, 2))(c1)\n",
    "\n",
    "    c2 = Conv2D(128, (3, 3), activation='relu', padding='same')(p1)\n",
    "    c2 = Conv2D(128, (3, 3), activation='relu', padding='same')(c2)\n",
    "    p2 = MaxPooling2D((2, 2))(c2)\n",
    "\n",
    "    c3 = Conv2D(256, (3, 3), activation='relu', padding='same')(p2)\n",
    "    c3 = Conv2D(256, (3, 3), activation='relu', padding='same')(c3)\n",
    "    p3 = MaxPooling2D((2, 2))(c3)\n",
    "\n",
    "    c4 = Conv2D(512, (3, 3), activation='relu', padding='same')(p3)\n",
    "    c4 = Conv2D(512, (3, 3), activation='relu', padding='same')(c4)\n",
    "    p4 = MaxPooling2D((2, 2))(c4)\n",
    "\n",
    "    # Bottleneck\n",
    "    c5 = Conv2D(1024, (3, 3), activation='relu', padding='same')(p4)\n",
    "    c5 = Conv2D(1024, (3, 3), activation='relu', padding='same')(c5)\n",
    "\n",
    "    # Decoding path\n",
    "    u6 = UpSampling2D((2, 2))(c5)\n",
    "    u6 = Concatenate()([u6, c4])\n",
    "    c6 = Conv2D(512, (3, 3), activation='relu', padding='same')(u6)\n",
    "    c6 = Conv2D(512, (3, 3), activation='relu', padding='same')(c6)\n",
    "\n",
    "    u7 = UpSampling2D((2, 2))(c6)\n",
    "    u7 = Concatenate()([u7, c3])\n",
    "    c7 = Conv2D(256, (3, 3), activation='relu', padding='same')(u7)\n",
    "    c7 = Conv2D(256, (3, 3), activation='relu', padding='same')(c7)\n",
    "\n",
    "    u8 = UpSampling2D((2, 2))(c7)\n",
    "    u8 = Concatenate()([u8, c2])\n",
    "    c8 = Conv2D(128, (3, 3), activation='relu', padding='same')(u8)\n",
    "    c8 = Conv2D(128, (3, 3), activation='relu', padding='same')(c8)\n",
    "\n",
    "    u9 = UpSampling2D((2, 2))(c8)\n",
    "    u9 = Concatenate()([u9, c1])\n",
    "    c9 = Conv2D(64, (3, 3), activation='relu', padding='same')(u9)\n",
    "    c9 = Conv2D(64, (3, 3), activation='relu', padding='same')(c9)\n",
    "\n",
    "    outputs = Conv2D(1, (1, 1), activation='sigmoid')(c9)\n",
    "\n",
    "    model = Model(inputs=[inputs], outputs=[outputs])\n",
    "\n",
    "    return model\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "checkpoint_callback = ModelCheckpoint(\n",
    "    filepath='best_model.h5',  # Path where the model will be saved\n",
    "    monitor='val_loss',        # Metric to monitor\n",
    "    save_best_only=True,       # Only save the best model\n",
    "    save_weights_only=False,   # Save the full model (not just weights)\n",
    "    mode='auto',               # Automatically decide to minimize or maximize the monitored metric\n",
    "    save_freq='epoch',         # Save the model at the end of every epoch\n",
    "    # verbose=1                  # Print messages when saving the model\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "def dice_coefficient(y_true, y_pred):\n",
    "    intersection = K.sum(y_true*y_pred)\n",
    "    return (2.0*intersection+1)/(K.sum(y_true)+K.sum(y_pred)+1)\n",
    "\n",
    "def dice_loss(y_true, y_pred):\n",
    "    return 1-dice_coefficient(y_true, y_pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import train_test_split\n",
    "train_data, val_data, train_labels, val_labels = train_test_split(X_Train, X_label, test_size=0.2, random_state=42)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n",
      "6/6 [==============================] - 16s 2s/step - loss: 22.6533 - dice_coefficient: 0.0069 - val_loss: 0.4614 - val_dice_coefficient: 0.0010\n",
      "Epoch 2/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.2490 - dice_coefficient: 0.0078 - val_loss: 0.1212 - val_dice_coefficient: 0.0081\n",
      "Epoch 3/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.1139 - dice_coefficient: 0.0103 - val_loss: 0.0608 - val_dice_coefficient: 0.0398\n",
      "Epoch 4/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0457 - dice_coefficient: 0.0974 - val_loss: 0.0353 - val_dice_coefficient: 0.1857\n",
      "Epoch 5/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0332 - dice_coefficient: 0.1894 - val_loss: 0.0331 - val_dice_coefficient: 0.2085\n",
      "Epoch 6/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0340 - dice_coefficient: 0.1842 - val_loss: 0.0261 - val_dice_coefficient: 0.2725\n",
      "Epoch 7/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0266 - dice_coefficient: 0.2870 - val_loss: 0.0199 - val_dice_coefficient: 0.4382\n",
      "Epoch 8/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0274 - dice_coefficient: 0.3276 - val_loss: 0.0393 - val_dice_coefficient: 0.2620\n",
      "Epoch 9/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0269 - dice_coefficient: 0.3301 - val_loss: 0.0263 - val_dice_coefficient: 0.3609\n",
      "Epoch 10/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0223 - dice_coefficient: 0.3826 - val_loss: 0.0182 - val_dice_coefficient: 0.4633\n",
      "Epoch 11/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0246 - dice_coefficient: 0.4302 - val_loss: 0.0232 - val_dice_coefficient: 0.3268\n",
      "Epoch 12/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0255 - dice_coefficient: 0.3293 - val_loss: 0.0200 - val_dice_coefficient: 0.4220\n",
      "Epoch 13/100\n",
      "6/6 [==============================] - 15s 3s/step - loss: 0.0203 - dice_coefficient: 0.4268 - val_loss: 0.0173 - val_dice_coefficient: 0.4838\n",
      "Epoch 14/100\n",
      "6/6 [==============================] - 29s 5s/step - loss: 0.0162 - dice_coefficient: 0.5250 - val_loss: 0.0133 - val_dice_coefficient: 0.5996\n",
      "Epoch 15/100\n",
      "6/6 [==============================] - 42s 7s/step - loss: 0.0148 - dice_coefficient: 0.5816 - val_loss: 0.0125 - val_dice_coefficient: 0.6564\n",
      "Epoch 16/100\n",
      "6/6 [==============================] - 41s 7s/step - loss: 0.0125 - dice_coefficient: 0.6534 - val_loss: 0.0118 - val_dice_coefficient: 0.6858\n",
      "Epoch 17/100\n",
      "6/6 [==============================] - 16s 2s/step - loss: 0.0113 - dice_coefficient: 0.6930 - val_loss: 0.0109 - val_dice_coefficient: 0.7152\n",
      "Epoch 18/100\n",
      "6/6 [==============================] - 13s 2s/step - loss: 0.0108 - dice_coefficient: 0.7126 - val_loss: 0.0100 - val_dice_coefficient: 0.7182\n",
      "Epoch 19/100\n",
      "6/6 [==============================] - 16s 3s/step - loss: 0.0105 - dice_coefficient: 0.7214 - val_loss: 0.0112 - val_dice_coefficient: 0.7514\n",
      "Epoch 20/100\n",
      "6/6 [==============================] - 37s 6s/step - loss: 0.0100 - dice_coefficient: 0.7442 - val_loss: 0.0105 - val_dice_coefficient: 0.7234\n",
      "Epoch 21/100\n",
      "6/6 [==============================] - 36s 6s/step - loss: 0.0107 - dice_coefficient: 0.7312 - val_loss: 0.0115 - val_dice_coefficient: 0.7287\n",
      "Epoch 22/100\n",
      "6/6 [==============================] - 36s 6s/step - loss: 0.0109 - dice_coefficient: 0.7164 - val_loss: 0.0112 - val_dice_coefficient: 0.7247\n",
      "Epoch 23/100\n",
      "6/6 [==============================] - 37s 6s/step - loss: 0.0110 - dice_coefficient: 0.7204 - val_loss: 0.0100 - val_dice_coefficient: 0.7267\n",
      "Epoch 24/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0100 - dice_coefficient: 0.7421 - val_loss: 0.0083 - val_dice_coefficient: 0.7742\n",
      "Epoch 25/100\n",
      "6/6 [==============================] - 40s 7s/step - loss: 0.0083 - dice_coefficient: 0.7773 - val_loss: 0.0082 - val_dice_coefficient: 0.7908\n",
      "Epoch 26/100\n",
      "6/6 [==============================] - 38s 6s/step - loss: 0.0084 - dice_coefficient: 0.7833 - val_loss: 0.0090 - val_dice_coefficient: 0.7830\n",
      "Epoch 27/100\n",
      "6/6 [==============================] - 38s 6s/step - loss: 0.0081 - dice_coefficient: 0.7756 - val_loss: 0.0070 - val_dice_coefficient: 0.8139\n",
      "Epoch 28/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0072 - dice_coefficient: 0.8109 - val_loss: 0.0068 - val_dice_coefficient: 0.8278\n",
      "Epoch 29/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0068 - dice_coefficient: 0.8250 - val_loss: 0.0061 - val_dice_coefficient: 0.8373\n",
      "Epoch 30/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0065 - dice_coefficient: 0.8277 - val_loss: 0.0058 - val_dice_coefficient: 0.8487\n",
      "Epoch 31/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0065 - dice_coefficient: 0.8359 - val_loss: 0.0060 - val_dice_coefficient: 0.8412\n",
      "Epoch 32/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0066 - dice_coefficient: 0.8250 - val_loss: 0.0053 - val_dice_coefficient: 0.8622\n",
      "Epoch 33/100\n",
      "6/6 [==============================] - 38s 6s/step - loss: 0.0060 - dice_coefficient: 0.8416 - val_loss: 0.0057 - val_dice_coefficient: 0.8497\n",
      "Epoch 34/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0059 - dice_coefficient: 0.8497 - val_loss: 0.0080 - val_dice_coefficient: 0.8428\n",
      "Epoch 35/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0058 - dice_coefficient: 0.8504 - val_loss: 0.0049 - val_dice_coefficient: 0.8672\n",
      "Epoch 36/100\n",
      "6/6 [==============================] - 38s 6s/step - loss: 0.0053 - dice_coefficient: 0.8592 - val_loss: 0.0060 - val_dice_coefficient: 0.8648\n",
      "Epoch 37/100\n",
      "6/6 [==============================] - 38s 7s/step - loss: 0.0059 - dice_coefficient: 0.8537 - val_loss: 0.0067 - val_dice_coefficient: 0.8411\n",
      "Epoch 38/100\n",
      "6/6 [==============================] - 38s 6s/step - loss: 0.0070 - dice_coefficient: 0.8248 - val_loss: 0.0056 - val_dice_coefficient: 0.8537\n",
      "Epoch 39/100\n",
      "6/6 [==============================] - 38s 6s/step - loss: 0.0059 - dice_coefficient: 0.8491 - val_loss: 0.0052 - val_dice_coefficient: 0.8667\n",
      "Epoch 40/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0054 - dice_coefficient: 0.8589 - val_loss: 0.0048 - val_dice_coefficient: 0.8757\n",
      "Epoch 41/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0048 - dice_coefficient: 0.8739 - val_loss: 0.0043 - val_dice_coefficient: 0.8814\n",
      "Epoch 42/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0047 - dice_coefficient: 0.8760 - val_loss: 0.0042 - val_dice_coefficient: 0.8939\n",
      "Epoch 43/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0043 - dice_coefficient: 0.8865 - val_loss: 0.0038 - val_dice_coefficient: 0.8990\n",
      "Epoch 44/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0042 - dice_coefficient: 0.8903 - val_loss: 0.0036 - val_dice_coefficient: 0.9030\n",
      "Epoch 45/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0040 - dice_coefficient: 0.8964 - val_loss: 0.0036 - val_dice_coefficient: 0.9055\n",
      "Epoch 46/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0038 - dice_coefficient: 0.9003 - val_loss: 0.0033 - val_dice_coefficient: 0.9118\n",
      "Epoch 47/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0038 - dice_coefficient: 0.9006 - val_loss: 0.0032 - val_dice_coefficient: 0.9134\n",
      "Epoch 48/100\n",
      "6/6 [==============================] - 38s 6s/step - loss: 0.0039 - dice_coefficient: 0.8990 - val_loss: 0.0035 - val_dice_coefficient: 0.9051\n",
      "Epoch 49/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0044 - dice_coefficient: 0.8925 - val_loss: 0.0045 - val_dice_coefficient: 0.8820\n",
      "Epoch 50/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0064 - dice_coefficient: 0.8522 - val_loss: 0.0072 - val_dice_coefficient: 0.8538\n",
      "Epoch 51/100\n",
      "6/6 [==============================] - 38s 6s/step - loss: 0.0060 - dice_coefficient: 0.8543 - val_loss: 0.0051 - val_dice_coefficient: 0.8729\n",
      "Epoch 52/100\n",
      "6/6 [==============================] - 38s 6s/step - loss: 0.0056 - dice_coefficient: 0.8551 - val_loss: 0.0049 - val_dice_coefficient: 0.8600\n",
      "Epoch 53/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0048 - dice_coefficient: 0.8766 - val_loss: 0.0039 - val_dice_coefficient: 0.8965\n",
      "Epoch 54/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0045 - dice_coefficient: 0.8858 - val_loss: 0.0040 - val_dice_coefficient: 0.8978\n",
      "Epoch 55/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0044 - dice_coefficient: 0.8873 - val_loss: 0.0038 - val_dice_coefficient: 0.8951\n",
      "Epoch 56/100\n",
      "6/6 [==============================] - 38s 6s/step - loss: 0.0040 - dice_coefficient: 0.8923 - val_loss: 0.0034 - val_dice_coefficient: 0.9085\n",
      "Epoch 57/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0036 - dice_coefficient: 0.9085 - val_loss: 0.0030 - val_dice_coefficient: 0.9205\n",
      "Epoch 58/100\n",
      "6/6 [==============================] - 38s 6s/step - loss: 0.0033 - dice_coefficient: 0.9130 - val_loss: 0.0033 - val_dice_coefficient: 0.9176\n",
      "Epoch 59/100\n",
      "6/6 [==============================] - 40s 7s/step - loss: 0.0033 - dice_coefficient: 0.9152 - val_loss: 0.0029 - val_dice_coefficient: 0.9241\n",
      "Epoch 60/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0033 - dice_coefficient: 0.9139 - val_loss: 0.0028 - val_dice_coefficient: 0.9229\n",
      "Epoch 61/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0032 - dice_coefficient: 0.9161 - val_loss: 0.0030 - val_dice_coefficient: 0.9251\n",
      "Epoch 62/100\n",
      "6/6 [==============================] - 39s 6s/step - loss: 0.0035 - dice_coefficient: 0.9125 - val_loss: 0.0034 - val_dice_coefficient: 0.9116\n",
      "Epoch 63/100\n",
      "6/6 [==============================] - 38s 6s/step - loss: 0.0034 - dice_coefficient: 0.9135 - val_loss: 0.0029 - val_dice_coefficient: 0.9225\n",
      "Epoch 64/100\n",
      "6/6 [==============================] - 39s 7s/step - loss: 0.0032 - dice_coefficient: 0.9143 - val_loss: 0.0028 - val_dice_coefficient: 0.9289\n",
      "Epoch 65/100\n",
      "6/6 [==============================] - 28s 4s/step - loss: 0.0030 - dice_coefficient: 0.9237 - val_loss: 0.0027 - val_dice_coefficient: 0.9284\n",
      "Epoch 66/100\n",
      "6/6 [==============================] - 13s 2s/step - loss: 0.0029 - dice_coefficient: 0.9227 - val_loss: 0.0027 - val_dice_coefficient: 0.9305\n",
      "Epoch 67/100\n",
      "6/6 [==============================] - 13s 2s/step - loss: 0.0030 - dice_coefficient: 0.9230 - val_loss: 0.0026 - val_dice_coefficient: 0.9315\n",
      "Epoch 68/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0028 - dice_coefficient: 0.9266 - val_loss: 0.0025 - val_dice_coefficient: 0.9364\n",
      "Epoch 69/100\n",
      "6/6 [==============================] - 13s 2s/step - loss: 0.0027 - dice_coefficient: 0.9299 - val_loss: 0.0024 - val_dice_coefficient: 0.9338\n",
      "Epoch 70/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0026 - dice_coefficient: 0.9310 - val_loss: 0.0024 - val_dice_coefficient: 0.9361\n",
      "Epoch 71/100\n",
      "6/6 [==============================] - 13s 2s/step - loss: 0.0026 - dice_coefficient: 0.9306 - val_loss: 0.0024 - val_dice_coefficient: 0.9381\n",
      "Epoch 72/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0027 - dice_coefficient: 0.9306 - val_loss: 0.0023 - val_dice_coefficient: 0.9380\n",
      "Epoch 73/100\n",
      "6/6 [==============================] - 13s 2s/step - loss: 0.0025 - dice_coefficient: 0.9344 - val_loss: 0.0023 - val_dice_coefficient: 0.9391\n",
      "Epoch 74/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0025 - dice_coefficient: 0.9345 - val_loss: 0.0024 - val_dice_coefficient: 0.9355\n",
      "Epoch 75/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0025 - dice_coefficient: 0.9334 - val_loss: 0.0024 - val_dice_coefficient: 0.9397\n",
      "Epoch 76/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0024 - dice_coefficient: 0.9390 - val_loss: 0.0021 - val_dice_coefficient: 0.9420\n",
      "Epoch 77/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0023 - dice_coefficient: 0.9387 - val_loss: 0.0021 - val_dice_coefficient: 0.9419\n",
      "Epoch 78/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0023 - dice_coefficient: 0.9398 - val_loss: 0.0023 - val_dice_coefficient: 0.9432\n",
      "Epoch 79/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0024 - dice_coefficient: 0.9386 - val_loss: 0.0022 - val_dice_coefficient: 0.9392\n",
      "Epoch 80/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0026 - dice_coefficient: 0.9346 - val_loss: 0.0023 - val_dice_coefficient: 0.9422\n",
      "Epoch 81/100\n",
      "6/6 [==============================] - 15s 3s/step - loss: 0.0025 - dice_coefficient: 0.9361 - val_loss: 0.0024 - val_dice_coefficient: 0.9372\n",
      "Epoch 82/100\n",
      "6/6 [==============================] - 15s 3s/step - loss: 0.0025 - dice_coefficient: 0.9326 - val_loss: 0.0021 - val_dice_coefficient: 0.9442\n",
      "Epoch 83/100\n",
      "6/6 [==============================] - 15s 3s/step - loss: 0.0024 - dice_coefficient: 0.9395 - val_loss: 0.0021 - val_dice_coefficient: 0.9438\n",
      "Epoch 84/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0025 - dice_coefficient: 0.9383 - val_loss: 0.0022 - val_dice_coefficient: 0.9412\n",
      "Epoch 85/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0024 - dice_coefficient: 0.9378 - val_loss: 0.0021 - val_dice_coefficient: 0.9455\n",
      "Epoch 86/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0022 - dice_coefficient: 0.9428 - val_loss: 0.0021 - val_dice_coefficient: 0.9449\n",
      "Epoch 87/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0022 - dice_coefficient: 0.9425 - val_loss: 0.0020 - val_dice_coefficient: 0.9457\n",
      "Epoch 88/100\n",
      "6/6 [==============================] - 15s 2s/step - loss: 0.0021 - dice_coefficient: 0.9453 - val_loss: 0.0019 - val_dice_coefficient: 0.9507\n",
      "Epoch 89/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0021 - dice_coefficient: 0.9466 - val_loss: 0.0020 - val_dice_coefficient: 0.9481\n",
      "Epoch 90/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0021 - dice_coefficient: 0.9456 - val_loss: 0.0022 - val_dice_coefficient: 0.9456\n",
      "Epoch 91/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0021 - dice_coefficient: 0.9459 - val_loss: 0.0019 - val_dice_coefficient: 0.9490\n",
      "Epoch 92/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0023 - dice_coefficient: 0.9434 - val_loss: 0.0022 - val_dice_coefficient: 0.9417\n",
      "Epoch 93/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0024 - dice_coefficient: 0.9402 - val_loss: 0.0022 - val_dice_coefficient: 0.9468\n",
      "Epoch 94/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0023 - dice_coefficient: 0.9420 - val_loss: 0.0021 - val_dice_coefficient: 0.9447\n",
      "Epoch 95/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0023 - dice_coefficient: 0.9426 - val_loss: 0.0026 - val_dice_coefficient: 0.9396\n",
      "Epoch 96/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0024 - dice_coefficient: 0.9410 - val_loss: 0.0022 - val_dice_coefficient: 0.9423\n",
      "Epoch 97/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0023 - dice_coefficient: 0.9408 - val_loss: 0.0024 - val_dice_coefficient: 0.9409\n",
      "Epoch 98/100\n",
      "6/6 [==============================] - 14s 2s/step - loss: 0.0022 - dice_coefficient: 0.9444 - val_loss: 0.0019 - val_dice_coefficient: 0.9502\n",
      "Epoch 99/100\n",
      "6/6 [==============================] - 13s 2s/step - loss: 0.0021 - dice_coefficient: 0.9453 - val_loss: 0.0019 - val_dice_coefficient: 0.9493\n",
      "Epoch 100/100\n",
      "6/6 [==============================] - 15s 3s/step - loss: 0.0020 - dice_coefficient: 0.9483 - val_loss: 0.0018 - val_dice_coefficient: 0.9529\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.History at 0x1d68cf6dff0>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Instantiate and compile the model\n",
    "model = unet_model(input_size=(128, 128, 1))\n",
    "model.compile(optimizer='adam', loss='binary_crossentropy', metrics=[dice_coefficient])  # the kind of loss matters\n",
    "\n",
    "# Print model summary\n",
    "# model.summary()\n",
    "\n",
    "# Train the model\n",
    "model.fit(X_Train, X_label, epochs=100, batch_size=10,validation_data=(val_data, val_labels),callbacks=[checkpoint_callback])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/1 [==============================] - 0s 250ms/step\n",
      "(1, 128, 128, 1)\n"
     ]
    }
   ],
   "source": [
    "X_predict = X_Train[11,:,:,:]\n",
    "X_predict = X_predict.reshape(1, X_predict.shape[0],X_predict.shape[1], X_predict.shape[2])\n",
    "with tf.keras.utils.custom_object_scope({'dice_coefficient': dice_coefficient}):\n",
    "    loaded_model = tf.keras.models.load_model('best_model.h5')\n",
    "prediction_mask = loaded_model.predict(X_predict)\n",
    "print(prediction_mask.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1d6911ca230>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x1400 with 3 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Training dataset testing\n",
    "figure,axis = plt.subplots(1,3,figsize=(14,14))\n",
    "axis[0].imshow(X_Train[11])\n",
    "axis[1].imshow(prediction_mask[0,:,:,0])\n",
    "axis[2].imshow(X_label[11])"
   ]
  }
 ],
 "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": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}