tutorials/Tutorial_ImageNet_Example_All_Metrics.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "bukochgPFg7s"
   },
   "source": [
    "# ImageNet Example All Metrics\n",
    "[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/understandable-machine-intelligence-lab/Quantus/main?labpath=tutorials%2FTutorial_ImageNet_Example_All_Metrics.ipynb)\n",
    "\n",
    "\n",
    "This notebook shows the functionality of the various metrics included in the library. \n",
    "\n",
    "For this purpose, we use a pre-trained PyTorch ResNet-18 model and ImageNet dataset.\n",
    "\n",
    "- Make sure to have GPUs enabled to speed up computation.\n",
    "- Alternatively, on OSX you could you MPS acceleration, more about MPS [here](https://pytorch.org/docs/stable/notes/mps.html).\n",
    "\n",
    "If you have access to another hardware acceleration supported by PyTorch, add it to `choose_device` function. List of all supported backends is available [here](https://pytorch.org/docs/stable/backends.html)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [],
   "source": [
    "from IPython.display import clear_output\n",
    "!pip install torch torchvision captum xmltodict quantus\n",
    "clear_output()"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2022-12-14 14:23:42.073314: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",
      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import torch\n",
    "import torchvision\n",
    "import quantus\n",
    "from typing import Union"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [
    {
     "data": {
      "text/plain": "device(type='mps')"
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Choose hardware acceleration if available\n",
    "def choose_device() -> str:\n",
    "    if torch.cuda.is_available():\n",
    "        return \"cuda:0\"\n",
    "    if hasattr(torch.backends, \"mps\"):\n",
    "        if torch.backends.mps.is_available():\n",
    "            return \"mps\"\n",
    "    return \"cpu\"\n",
    "\n",
    "\n",
    "device = torch.device(choose_device())\n",
    "device"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "mGhP4bTuoWYF"
   },
   "source": [
    "## 1) Preliminaries"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "XqKzag4VFjHT"
   },
   "source": [
    "### 1.1 Load datasets\n",
    "\n",
    "We have prepared a small subset of ImageNet images which can be downloaded at: <https://github.com/understandable-machine-intelligence-lab/Quantus/tree/main/tutorials/assets/imagenet_samples/>. Please make sure to download the contents of the folder, that are, the inputs `x_batch.pt`, outputs `y_batch.pt` and segmentation masks `s_batch.pt`. (A description for how to download the full dataset can be found here: <https://image-net.org/download.php>.)\n",
    "\n",
    "If you use Google Colab, you might want to add the following:\n",
    "\n",
    "```python\n",
    "# Mount Google Drive.\n",
    "from google.colab import drive\n",
    "drive.mount('/content/drive', force_remount=True)\n",
    "````"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 2,
     "status": "ok",
     "timestamp": 1665166640500,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "g_uHdc9Pg2ra",
    "outputId": "0e0512f8-2c0c-4031-eec8-d27d309c2430"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17 matches found.\n"
     ]
    }
   ],
   "source": [
    "# Adjust this path.\n",
    "path_to_files = \"./assets/imagenet_samples\"\n",
    "\n",
    "# Load test data and make loaders.\n",
    "x_batch = torch.load(f'{path_to_files}/x_batch.pt')\n",
    "y_batch = torch.load(f'{path_to_files}/y_batch.pt')\n",
    "s_batch = torch.load(f'{path_to_files}/s_batch.pt')\n",
    "x_batch, s_batch, y_batch = x_batch.to(device), s_batch.to(device), y_batch.to(device)\n",
    "print(f\"{len(x_batch)} matches found.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 191
    },
    "executionInfo": {
     "elapsed": 5,
     "status": "ok",
     "timestamp": 1665166693504,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "aAR67-cnOS67",
    "outputId": "2eb2278e-107c-4cf5-ed82-78139891e02c"
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 1500x300 with 5 Axes>",
      "image/png": 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otmng4YGHBx6++9LAvwP/fjX94K+EvtY29F2yq533/g59rqrl91e84hX8wi/8Aj/yIz/CL//yL7Nnzx6cczzvec87KSJ7e5TPefWrX82DH/zgkx6zsrJy0s8vvfRSfuiHfojf/d3f5T/+x/940muLCO95z3tO+mynuu6dRW9729v44R/+YZ70pCfxohe9iP379+O951d/9Ve5+uqry3H79+/nk5/8JO9973t5z3vew3ve8x5+7/d+j2c84xn8/u//PgCPeMQjuPrqq/mzP/sz/uqv/oo3velNvPa1r+UNb3jDHIrfpxtuuIFLLrlk7rMPfvCDXHnllSc9/kUvehFPfepTGY1GpRY91wPfcMMNzGYzzj//fN7ylrfwuc99jt/5nd/Z1qdpdXWVa6+9lv3797O0tFR2XzjnnHPmjvPes3fv3jnhPtCpaeDh277unUV3Nx4+FT3lKU/hxS9+MX/2Z3/Gs5/9bD7wgQ/wl3/5l7zrXe+a4+G2bdnc3OTaa69lz5497Ny5c+46m5ubvPvd7+Yxj3nMNp4e6NQ08O9tX/fOorsb/56uvtyzZw/j8fikUe/8Wb7W6er1gW6bBh6+7eveWTTw8MDDXw0a+Pe2r3tn0d2Nf+9sXrsrbOi7BHj6Suid73wnj3rUo/iv//W/zn1+7Ngxzj777PL3xRdfzD/90z+hqnNo7xe+8IW58y677DIAdu7cyWMe85g7PJ6f//mf521vexuvetWrtn132WWXoapccskl3Pve977N69xWauDJrhtj5J/+6Z9OKSRORu985zu59NJLede73jV3v5e85CXbjh2NRjzxiU/kiU98IjFGfvInf5Lf+Z3f4Rd+4RcKWr5nzx6e9axn8axnPYu1tTUe8YhH8Eu/9EunZLhzzz13W9rigx70oFOO94YbbuAd73jHScvfvuVbvoUHPehBfPKTn+T666+naRq+7du+bdtxb3nLW3jLW97Cu9/9bp70pCfxkIc8BIAbb7xx7rjc/HhrBGKgrz4NPPyNw8OnopyynyNM119/PQBPfvKTtx174403cskll/Da176W5z3veXPf/fmf/zmrq6tDmd3XkAb+/cbh39PVl845HvjAB/Lxj3982zU+8pGPcOmll5bddk5Xrw9059HAwwMPDzx896WBf79x+PfO5rW7woa+y3o8fbnkvZ9DfgH++I//eJtQfdzjHseNN97In//5n5fPJpMJb3zjG+eOe8hDHsJll13Gr//6r5da6D4dPHjwNsdz2WWX8UM/9EP8zu/8zlzZCJgT5b3npS996bYxqyqHDx8ufy8vL58ylXErPelJT8I5x8te9rJt6PbW+/Qpo839Yz7ykY/w4Q9/eO64/rjAFNI3fdM3AV0a7tZjVlZWuNe97nXSNN1MCwsLPOYxj5n7Oeuss055/Lvf/e5tPzkV8C1veQuvfe1rAfj+7//+kx4L8N3f/d28+93v5l/9q38F2Jad+/fv5+1vf3tJHwZ485vfTAiBxz72saccz0BfHRp4+BuHhw8dOnTS53nTm94EUHbQefSjH31SHt63bx8PfehDefe7380Tn/jEbdd5xzvewdLSEt/7vd97yjEM9NWlgX+/cfj3jujLpzzlKXzsYx+bc1w/97nP8YEPfICnPvWp5bPT1esD3Xk08PDAwwMP331p4N9vHP69s3ntrrCh73YZT094whN42ctexrOe9Swe/vCH8+lPf5q3v/3tXHrppXPHPfvZz+b1r389P/ADP8BP//RPc9555/H2t7+9NMnLSKdzjje96U1cddVV3P/+9+dZz3oWF1xwATfeeCMf/OAH2blzJ//jf/yP2xzTi1/8Yt761rfyuc99jvvf//7l88suu4xf+ZVf4Wd/9me59tpredKTnsSOHTu45pprePe7382///f/nhe+8IWAMf4f/dEf8f/+v/8v3/qt38rKyspJHS2w+twXv/jF/PIv/zL/+l//a5785CczHo/52Mc+xvnnn8+v/uqvnnLu3vWud/G93/u9PP7xj+eaa67hDW94A/e73/3mhM2P/diPceTIER796Edz4YUXct111/Fbv/VbPPjBD+a+970vAPe73/248sorechDHsKePXv4+Mc/zjvf+U6e85zn3OZc3RF60pOetO2zjOxeddVVBdm/4ooruOKKK056jUsuuWTuOuPxmFe/+tU885nP5BGPeARPf/rTuf7663nd615X5nKgO5cGHv7G4eG3ve1tvOENb+BJT3oSl156Kaurq7z3ve/lfe97H0984hN59KMfDcBFF13ERRddtO385z3veZxzzjknlQVHjhzhPe95D9/3fd/3NU/X/kamgX+/cfj3jujLn/zJn+SNb3wjj3/843nhC19IXde85jWv4ZxzzuEFL3hBOe509fpAdx4NPDzw8MDDd18a+Pcbh3/vCK8dP36c3/qt3wLgb//2bwF4/etfz+7du9m9e/e2cd1lNvSdsVVeplNtI7m8vLzt2K1bMGbaup32ZDLRF7zgBXreeefp4uKiftu3fZt++MMf3rZloqrqF7/4RX384x+vi4uLum/fPn3BC16gf/Inf6KA/t3f/d3csX//93+vT37yk3Xv3r06Ho/14osv1qc97Wn6/ve//zafp/9cwEmf4U/+5E/027/923V5eVmXl5f1iiuu0J/6qZ/Sz33uc+WYtbU1/cEf/EHdvXu3Aqe1peR/+2//Tb/5m79Zx+OxnnXWWfrIRz5S3/e+983NaX9OYoz6ile8Qi+++GIdj8f6zd/8zfo//+f/1Gc+85lz93vnO9+p3/md36n79+/X0WikF110kT772c/Wm2++uRzzK7/yK/qwhz1Md+/erYuLi3rFFVfoy1/+cp3NZrc77q+E7siWrYD+1E/91Em/+4M/+AN90IMepOPxWM855xx9znOeoydOnPhqD/duTwMPGw08/OXRxz72MX3qU5+qF110kY7HY11eXtZv+ZZv0de85jXaNM3tnr917fTpDW94gwL653/+51+18X690cC/RgP/fmV0uvryhhtu0Kc85Sm6c+dOXVlZ0Sc84Qn6+c9//navP2zFfmoaeNho4OGvjAYevmto4F+jgX+/enQqXrvmmmsUOOnPyebyrrKhRfU2ctK+Duk3f/M3ef7zn8+XvvQlLrjggrt6OAMNNNAdpIGHBxro7ksD/w400N2bBh4eaKC7Lw38O9BdSV/XwNPm5mbZ/hOstvWbv/mbCSHwL//yL3fhyAYaaKDToYGHBxro7ksD/w400N2bBh4eaKC7Lw38O9CZRne7Hk93hJ785Cdz0UUX8eAHP5jjx4/ztre9jc9+9rO8/e1vv6uHNtBAA50GDTw80EB3Xxr4d6CB7t408PBAA919aeDfgc40+roGnh73uMfxpje9ibe//e2EELjf/e7HH/7hH5aO8AMNNNCZTQMPDzTQ3ZcG/h1ooLs3DTw80EB3Xxr4d6Azjb6uS+0GGmiggQYaaKCBBhpooIEGGmiggQa668jd1QMYaKCBBhpooIEGGmiggQYaaKCBBhro65MG4GmggQYaaKCBBhpooIEGGmiggQYaaKA7hQbgaaCBBhpooIEGGmiggQYaaKCBBhpooDuFTru5+Bt+4kqcM5xKROzH2e/lM+dwzuHS9/Y7eCIidox9Z9dx4hABBHCCSz/5mgCCku5gnwvUCpV3OC94D84J3oH0xutEQB3WwSoSY0BRggdUQR0eQXCUQShEjYS2ZRYDqoqKs2NwCCAOvBcQBRRRQUVQFdoIqgqqxBhooxIjRBViGl2MkdJVyw4lqkI6N6qkp4ZymFJmoZuXiIgd4RCQ/jla7pFG2V2ozGqHOarmIzSNSfNhnLwBmJTzbGzd/bqLCqqOfguxiG67nn0t3C5p/6jeNSWWC+XnV9y2+7gyIb0x5HP636WffBfViGrojTc9s6b1EmN6p5H/+PsfuP3nuAtpaOY20EC3Tachie4y+ucvNaiARwgoMTG0AxCIStKt0XSlKqpCJ80E57IUlizuQU0X599VIojDpcPQSNbEqkpE8f2ZEgEUkawLkmLLOibLWWm55ebr+V9//S7OXjhEPRI+c/P5XL92FrtG61z1TQe5575DRF1jNlvkYzfcn3+45Tw0wJIc4+FXHOJe+zdoQ8U1h3ZxeHY2j/z/fRsX7D0H56vOUkjPrB4k2phi0TOu6M0ooKJohMrZfIkIKnaNojadHYOCiCJOcBFUQEXsMAVEiaJUaZ6I+Z5ic4ogTtKY0iuIijizV2y6IzGaTaMIURVJdojP44kRVyXbRmMap8NlKyO9e7ugS+9ZwClCTLrUbBZQ1EGMmmyzbH2kV5jebaGYbCXpXr3GmH7pHZ8eMBKpnD2HF0dMi1Z76woVRCKCI6itLZWsp4WI4nBIiKhzNjCnSB5EGnsQ5bzd9akZ6AygX3zuv2ff2TtwKCIes2vtO+fy2rTPnYC4nn2d309meHVoFgLJQBIneOcIUXESzU5Vj/FiWvcxAiHJCrtuz+IhCQGUeXsdsj1ktqcrNqQWm10To+RrgzOZkN9m/549W0sSz6g0SLHpkvWvik/XiFIxXt7Lpff7Zs4+755EUaazdVaPH+DgDTewdvgAs/VjxnpEurUraAwY/2d7v7NzM8UYuu/LM5N8ncSv6Vk9sLbZcs2hI0wEmG5wnwvOZ2lcp/tpeX/9uQPFuXwPP2cj51+NH23uzJ+gt1Z685bmMb8DzTa8jYAY0+zrzNabeqIGlMbGoun9qhCicZSIprFKkjFldMT8DOV9K4jY+yMm2W9jyv4aCFHBxES3nrMvlJ8hhIBzjp/7td/hTKVXvf45BOz9eAVii1TpXaggskAIipMGXGusJ4KoxwdP7TxN3CTSot6jWqFRcAjj0RI7d+7lwKGbaZkxdvZe1FcE1yBMkNCYHNAx3o+IIRAQIg2oQ1hhVC1QVUIlkaWlJUQ8XkZEVxGIhNAiGtG2ZdZu0MomYdoi6qGCoAIytncSWzMBQoOieD9CW0FiiyMgEokoOEeIgaCCamV+v1O8q3BR0BCJ0hJjoJIx4j2tn6HqMR6AxZURm5MN4izg06JrYzDpX42JISIacXi0rRCniGtxtLYcHYTQEKJDcQQ1+TdyFaqOqIrzSmgDtRshST9pnNFowPmaiorQTojegdRUKIRJknQeEY8SiQSEETG2IBGNEDUAAecrIg6NFeOqsjlKPmKrM/BK0yoaRoyqRVSmzGTDdF4ruCi41lP7BVrvcOLxrTByQqubNBJx1Zi2iTQtNBoR3+AIOHXU3icftTK+jy0xNAhC5cbMouns2ld4Z7zZKmg1IsTAdGMd72pwFegE71pwDg0OZBGlZtYGhA28CsQ6mSANTqa8+pf/4Hb56A7tapeFiQkbsvVQAKniuNMJmKQNk52bFZwBTMnmKErVgJdsqmUopKf0on0SUCRGJAguGW2u2EIJjHGeWswYdi4rPMpxdp7iiHiXVKg4xHmQijYE2hjNUFLpDPhsZebnU59Ap4gDE0oKbRRihDYk9Rftc42dwitKJl3YVIQUm7Gb9+65ioJn/pgOUJFyLTtuO1xjizKWzzvDIxmivRNODhR1Zkr/OW6PpGew3uGe9nKy+yXAS/Jz2vrZDm+Zg1D8rYwz9W1kSOBdTIATBWTqGyHiHC4bSTEmntA7/jwDDTTQQHeAnIUb6IB+A5kiFAehOCEaIRkVyfaH5IiYwxuLbFM1vSVi0s8wEiVAAmMoet1l2ZmcSyU7siTQIusvSRJZkBSIObF+lE9/+uPsGR9jcanlwOpuDs52oDGDNZE2zlBVXNVw4c6DXHNsH4fXR5yIu/n7axXvIhftXeXScxpGR9f4/z7muOKyb+JeF57LjsUVM0bFpYBRmiEFL0JQRSUWnQEJmFJoo+KhB3iYYnDiyvEu6YqoCt50uYFCQiUQBCqynSGIVyI97eHSfFaCJFzKiblsuHykx/tAX8da4Mt0k0SQyhxSyS+jm2l7x2A2V4yoLRG7dbbZks3VV6heDBTLD6uqiHN2z+REI4J4bO0gSEx2g0ughoCk9adOIIB3LgEVZuwqKeCY1m1fIYuU8F73PE4M5IzRPH00mV7J2U1zEAwmuW0GOgNoXDlGVZUCrD7Zzh2gYAFbn8BHCsbX2dPRgCdN61w74ApsDr13RI09a84n8MnuYTLC45zfZruJZBs/AxoWQDYgIgFKkq3PvIakXDv/iHhEXHHuDOjC7OXOCLTTy7Mo4EBCkWP2teIQnGRodcqBm7/AsUM30zYzQjtlOlklbm7iJVKPfVrs6ZpqdluMIY0tX7c3cXRgSAeiaVm7ZE72WkB9EahaLPiNBd5HoxH1qEaD8TnSt3Vj+TfPMZhDLOnllSBnD5ARDLiNMa+FDPgUYdzzGVxaM1LetQFCtc1JdvRF0OzfJKqy945PvKqopgB8sEQDpOq9G0k2cL6C2+a72DMkFvcu2dYGFKsjKw1ijJ0feQZTkwA0L5XZ/S4QYqCqDHhqZhHHiKqqIM5omRGkRXyLVun5UfNrtUbbGieOqhK81Cwt7GBptMrG7ATTWZP4qCXoFPGt+ayxotLa1mEI1JVHfaSNLUEmaO1xrsL7GmSEk9qSOjAd14qniQFxkdp5QnB2bBQCLYLiaWg1UInDaUWIwfRDxHSoBFQCbWwNjBFQ55Dk3zpaVFuijBFfme6QGgXaBF42IeCdw+PwlRDatvjmpKCZc5Wt2xBTooiitESneF8To0PVgjJehFYFU1LKaKQILVViqYnOaLEgTgoDEaKm9ehMl7sZWgVEDNDyCShvoyn42puuC1GpK1sHMSrRW1AwtI4ah9caVWdBGW9gnCW/eFQbpA4Ev8lUW4ieqBWqQq1jagF1ESc1lQaQKVJ7WhnRhgqnLT5EnIJXkCAErRFX4VRoY4P4xJ84xNfUTthspuAtACRewIUEQlWo1khr9oxTRXRGCI2BT4yRRnEqRB8J9cTAwHaM80oUs4kcarbRadAdAp4y9aMvFqXpMpxg/jNIIltNqQU1kRiCCXBDyvKVFWcH4g0tynKpZ2ynoJsCIVnMGbBJxpQtXqUm4Bz4jH05wTUmYKtKjIkFhJiinBYNdN5T10KNJ6oSWjPYQwEjtBOmQIj2PCEqbVDaVgkxElQISVBlRpoDMoreyE/oEsAlzIvvk73MTmnGrV8VEKrAVfnjk1KnGNNxBVTbnslkhvepR3NnATBzVy3TJ93ncurns4Ozw9YD4oqjJmXc+R0ZsEQBocptMpBJBjUT0DfgTgMNNNCdSC0Bok8ZAV1gx4Bv+8s5y7AtWUjkTCgzOruspE4HlVCGJqDBvEFUOueyAPtgwFUMIObECUnHJWkce9eMqjgJrE9W+ad/+hST1c+zb3mVzdlOvrS2h/VZRdCI0oK0ZKnufODsHcc5f9ch1mfns9l4Dmzs4hPXBUY+cOHudS7aO2V59Rq+8PlNDp+4D/e99DLOP2snVeVxaQzickaY4Ht6TsUMJlFnWckevBpQowlw6nAYy1gyuW/nihooImKOnRNXnFGzY0w3+ShlIBI1G0IgEU8ydpNtIChIBgxSdnkeD2b44ZNxl510OlAw20olS9w5okjKDkoBkn4GU8pc6ACKlO2VQEUpVyM5HVKcdtCUTGUImh3fy2wBEKUsRQScGcr5GJcdfEP8bL0l3CljGxnwQpxhCTGv/bQ+8w2ykXmG00JVszgaWUabS+CMFDzQbOcENIrLjlYsOI8BTwa6kXm4ZJwYeeeTRRzTvwY2FNApZ+uTLpttdaU3h2bT5PEVZFvSO9YIuAxBdnHYnO1if2G84LuAXQYnVIGYMohcWucCWqV7R0rGkmQXyrL3orZMjh5gIjkPyta3VSJ4nPfJBs7gC5jbXWEOg+YlVICS/PxaAJ+QnjM7IAnsFUmZSBEnUIWI947KeSRUjEYjRnWFVp2MLvwJJZuIcj9H78Zs7X5iQFhnV3cZRtoba+zZsfn1daF7y1JK2TPqk8wy4RZCl80vyRnTAlJGNNqz9oFIShZtXnX9SgFJoVvygrBxxZ4sjZGSESf2E0Kg8v60Hde7itrYQnRUHqI0KQnCIxFCaGnjhLoWIhVQmRMvgSY0kEAA0Zw94i1b05vTHuKEAweuZ9Zs4nyLJ1oea2jNH9axAQOxJuoIg9s9xAovDtXW7pH8aBElxoaqciYFJKIxUBtEQBtCAjMdUdsiyzO3GTIYwE0Rb281AjjTE06FRg2A8tFR+REaFe9MV4VgfG8BsJiccJ+yhASJnjATqnpEaKcIEWlT7m5sMQDUZBDOQTAAWr0SaZN4iYhEy26KIwN4VHEuyb2YpUhD1BkwsrUqARVPm7LKDGwhiQbBi0djl0gTCIjr9LQQaHVCG5QqyRWRBu+FqBWoR1xFcFOaNiCxQqPHuTGxUaRSqgpGboHJegLqVRi5BSrnCK6lrhaYNmsoDeJ9eiejVEVlKHSUBucBX0G0rGfViMZIS0MgUkkNOJzWSJvwELXAYohCEyNeoKIlhA28U0iBA8QRgtp7FSFKoNWpgfRuxCwHN2OgEqjdwmnx0WkDTy6V0UFSVK4Dn7LwyMcVwClHD7LtgKXuFvAlGXiGJNlLj1JkMpIykvrpqv2smWKlqFhacQIDbGzgUap0Pde7Li4pApeiuc5SkXPJW5RIJZqMADs3aCQELGoalZAEadSWEKANkVYx8Km1krmoloETk5AXtgvVrZ8U5qb/zN2Rc2m5vWPKsdmmzP/2D9F8pe0ZOn2wq//dVlvupOPbEp3qDr59JVKM0i10MgBL5957mv8O8uoZGtugOEO6t4Zj6MCnnKIMKTNNO6HTP1bSsV5MuHufS0DP/GhNScvv2NU+p3w8f3zv9+1v6BT3ONXFykfd+zrlNU5x361n3N549ZRHbv305FfW3n9P9/nvCN3e/PYCi937ih0Pz1HfYcvXvi3268vDLWM41Tz32PwOUWcCbx+znM7E5sqL7RfuHB5O8Y56YzbZf5LnzE4uagbeGUr2vmJnr6eHdpIzkRLYkf3R5CBkwMQn0COondPnEjVcAKcO+sCWuG5NSdZ5Slehbm6t5HkVQTRAdp9VmbRTrr72cxy+9R/YPTqMoty6upvDa4toCCaXNFC7lM/lFK/K8sIqF+85xKH185iuejRWHFjbzT99SVkaec7edYwLdh5m56JyzdHIRz61yhWX3Yt7nX8u47rGqbNsJ58ctYTMWJZSBqRMhrcYsBRI80m2WboMbpfWSM6ezlMoYMBUnrLOpbfP06eayufKCpOeM0ZXwjOXuVQM3eQDOzFjWy06mW0vyem7kuEiYxuf9JWVEEq6XqJk35SHSTaKxJxRlcv/kgyUfGXKPIomkMD1+TvZhS6XGKbyUOnKAtF5uxAiMaNsebHb60HVyvCcpmzkXiaI6ftUkninSOmvLtX1iPF4hHOKSsr+SXzUtZkwIMmlTDLj+SzhDBAUhznwYDya1qRiwVSbxTyfViIClHVkhm4nSzqd11PgaU6dz+AI5ZiSEaedFar98xOwZD5CblWR/QL7TiUSU3mVc5ZtlCsIrCQuXzeCBntutUoFjQouprVgzqk5vTZu80kzKJWVI6BVAXK0rxx6gXKzPbvMHgOu6C/9NM+Kb2z8dV2jbUtd19SjETG06Xibt852jQX0t+xQDxpI6K29q1yeGA3U6mY3T60mxrBnitF4sCsh7OSPCAl4ojjSSboBWvy1DGiBpsoSeweaArZSSgL7vkNX6dKtna6EUnvflfUjkrJU0rqIJpez3g1fhn3xtSRxLb72iDagLR6Pr0ZW7SIBX1cgjoCksld7P44xUT1tFEbOdGyUYMraRQIGaGmcGECikcp5nCgxCk3MGZLG+zFEVDyIp4ngcSWHtKLGxTplC+VssppWnGX0qoJYppAFfSxbT9RBayWE4hwzsWSLoIK4Cg1tCjhZ6SAywjuH+BbRxqqQqBC8JXlgvB6z/FH7NogjSsQ7seOTn9w2ARcV5yGKEENMQbQMVOZgl8OJUmmwVisSCBJotUFjlbKNhTa2qDqcCpV3VDICTSX5qmhsEAmgoej7oAHEE6JHQ7CSOmMFIoFGI7VUaIBWGxCPasR7yyKPYhlwQSIxyb9GlUoMi0AtuyoGyyVW5/EacBpBalQcwTnUjZkhNCkYIzFSi2UfBxytM/BNQ8rK8sanLgQQR9vavFXeZKeKJ0rFLCojaRFaiDVoRRRXWgyJ64IJDk8MZkP4kSeqEFyLR5EYiAohVKbnCZb5dFoG/R0EnvpZTF2WU3ejfm+mOfCiGCySHilNUrGe803olG9PV0iyUIoxWO6TVgRZeab+C87hRaiw2nCk+xzRkrjuUsQxRqVLJQYfPa0q3puSiKVXEzTBeC9GyCV2bYBW7RjLcLLUdIutGNps+UzzgMjJcBlNUYktn7LV7TqlfC56PwNB5S303kkXmcyUwSTtnSPKNuAp0uGE5cpK6ap0KuBJTnNBnpp0Li3YPukDT+neJRq8ZdyqbAPbep/l37va814Upzf07ND7LBAwZ8B/xc/3taDOKJwDLTMgKZ1xMEdCijyf/D1qXjTzFuj8BbLjl0HBDFpng+RkqMLJPup/rPlZesdvPaYc2LtH/9HzcFy3ducesYAe6Ts3f/E8L8V+TYsir5NiC5ZAfc+K7bPK1hHnMpqSkZDudSrOz7Zo/wHy/OZDdP7jraUG2vdYe6PK83uS6Uvfn3xM/eUwd4/eG9NtzNX7JfegOenVs1OartSb85NRWfG5PGgOobt7kEtZKDkTKb+m/M419brJOTPF10p6TeiyVQubazcFuawqgjmbUbuAf1o83gnEdL0E5Jvz3K2SztWLxNhww43Xc90XPspZ/lqWq00ObJzLDas7mEwriAawVJVSV6FYCFDhXMv5K4e5fuUIhzf3EYJD/AJfWt/Hws0V/8+OBRYWbuWshaMsjBpuONbyqc9NuPXYOg++10XsXVqx54oQXScagtABNargzCiMSOprpd16EitxI0WJy7sobpZkH4/sTvY5pgui2XnSW6SRnEGRgMAMKosdKKnMvwAD2UkovV+SPE4OYWdZUYC1kqWQLiHay4LL6yD9r7MLcg+afG7OxspPn35RBSe4pP1LNhikyHB3ts2ZS9li9MbsrNdWXpXS8XIG1gQFtTLDFK7t9FC0UW9OpsyahvPPOoszmeqqpq5rxEW6zkWCeJfmEkBKZo2ktaD9d2Gok9V4kd5fAmBy1phP8+gQorqyVkqW2ZzW7LJVlH7pVI/ne+PqsMFurXdBupyhk4+BDDSW0jGXLeKYgr4piJ1rWYsZkkaXMoQ6u1TB5/mRUuqrqbUGCYTRVG4i1oyt6F2XxqHleQKanFpbfAlVLzZhCqZLzsSy57Y2Ha3ZBKJUtcNXNVU9QivrBaOxTZmB0usz59P5kqohKiAB2gVEtWe0N5IAPOZLIKHLsIylz5oWnZhBv9J3NpU4FZ3ZtwcL8ETP7u1dLwq5tNsya7K+tXNikmsuZTIVe1tzIDjbVg6NUsyg/B40ndODws9IErVS16YJ1CLUvkKi9TWu/BiaCstsAnEtUWZECYiroTEbznyomiDgXCQkEDhIi6hlLBHND3TeirddVMRXVh7pWtQHVCvwFUGC3YME74r5obUIhveY/9tmcCqGpIeS1I/gpTZflxaVYGs2tFj5vWBtaEZ4WrMQBEKIjKSi1gq0Yta2eFcRVGiyXtMGiS21X0xZbxn0bJPNqqBTqkqZtW0BZ9Q6FqHOsmwg4CvL2CI6vI6IWid5FYkuMo0NPpUYi/oEfHmINqeVgBIQ540XsLIyzSC3RPBKG1vG4i3Zy3Xlo41OUQ1UrsLrGI8yC9ASS5KJF58SXxLgE9XASQEvU5xEghea1kNQ2jBJoF9MoI+g5L5akjK+KpCKEAx89wREW2YxErUmSE0IFhxwAhICMTS42rJNA44gWN+qNtLEBucNoAoKgsf5EdpWxBa0qk3uRcv6Fo1IyJnWULnKZICAxgZPldaVoqPT67F4+qV22lP2kORIBE2AFPN+jhTB1zO6kuIT7DOX8uG77/s/CXXrKcti3JX/dAqxc6JMqIWk0gOk6CBITItPLM27CaZUjRe0U1jaUmHNwkNUYoAQYJZ6NrVB0GCCtQmkTKdcbsCcMV9mTHP3oP6czon/fBjFG04XOKnrdTL53Ont/kflt9CPPmw/tRv37fhk2zLadR4Ass9kyyHZQMnKrX+ozn1WUvaLEiW9S912bmr8UAzxbCyfbM7M3tXud+L2yEzKZFO6n1J6AqXhYzRfpLcCz2yFCT3jHpuH+RFL9963ftdbNrdZSpmBm978a5q7zkHqHD4t74veZNNNukhvzLJtcevcb/kYoUN58qdbcg3n1nf6bwE1t5ZNbgGLeyVF3bNsuXTPcM9N6OcGnGXnNupmPY+nyIe8Tq3WaV7Ybrn8KRk3bpE3rjeDvSmUXmYc0vuuN6dbbzQnktP0dyIgz3Q2mrtnOyn63rtm/17lkbfJJ80pPCen3NAYtgZpE7Mn2F22Av5nFokTNHRrGrJMM4nnc98hiSnbyR4yZ/DMsU/ix67EpMsO8NkxkwxmUPR0NuAEchsVUE2bNyjSJqUmwlQDNxy6lX/+zEfY5a5nZXycyWyRm1d3c2RzhIZoOsk76soKd4rslwYNkYXqCOftOMyNa3tYm41RhFgtcOvmIp+44QT/z+XK/sXj7Bi3LI9vZfHwlM/fOOXo8Q0ecsW9uHD/LqqYnBqPRXUTL2kGo3K5Vk8f53nKrn1QW4GO5Ehp37aRZEonLRj7wE3qWpSv7SA36J7LrVPrV1nkR8wAnJVZme8sXaUeGDjttKBIaq10UvJtKm1w2WHt6cdk3AOlL0cHTrqSMdOJYxtvP1xhoK8kXz3rXCnrLB/nek8p5EVDcuI1ZUsLLmXn5VLH7Bjlkg5FzVHD7hnFnDEVcAEqB0dXTwBnnYp9zghyXnCVT7awlU9EyfJLUk8Rnasu6IxkA2vMNjYHF80gTtLb3ic7RQpY4dP6LvZ7AhWcSGqISwGUsprWVBslXVft9AQZPBI6IZoyblw2iHK0Jo1Mc3lV4hl6azLZBh3u0Q2iA0Cs92qIOqenRQ30FJcztwwYidrYXKlLAHkRVAX88uLKGjfQPo/bmaOXs8zUXD07zBpz5x55QkvlG7yz8jXvwVcRnLV79pKye8TyBzLrSeobJ0Sci+m90vFG5sUUWZGihNPMlX5Yeb6wzQ6KzZWzqtIaUwPXrNRKyxz3g659+7VktNk029xEe4YYA7ZpUH/ddJo69x3L2Wa5T9aczeQkvRvTvbkqxJNzO89cEur0LlL6QhRiGxM4I9ZOjQZcQ4hTckWhARC2OUJQB9RWDi4TcJGZWsZI5SxDx7CoVB6ngVYtI8lVGMikoVvLDmJsQGNqwh3wbpx0e2vglXcGXuFSL6LWMrHEU6mVebUaUK8EsexYF7s30jpHJIBaibgtoTapKk/tRiZPYrSsNQekjcZ8m8AKVzGdNWjKpHJSY5mPTSnDNQAtIuqorMCcVoQYA96PEG3TmCoCiQ+T/145qJwisSYGsyfGJB0eoZFIlIhIIARBdERnSUWiKOpaNM4I2lBrhU+ByhgFFQNbQrDMcIkzKlWic5YNFCWrXLRtqTD9FMQhElCXMrbUUVHhmOFcg7b2fmxcEScVXqK9j5gqvmJDLlMmNIQwQ6MnUlEtVGiISACnNTEo3lcEZ+1/QvQpiylQOYzTYoU6JbgpITaIGxPVZktTNrWBaS0iTdruwuOC+Qfixmhu+xCtt2VVdbLy9ui0gaeSDVAYEMwiyh54Z8iawMpgVAc0Zb9ExDreO2fGdNngga4kDmTbv+W/25wMTYos/2XGWgafHNYpHlHUYE/LRlK1ZmSRVHZnDbtEITqBVmgDhCCEDDpFe+QYlRCUJthOLP3smfykUhSrcrId3UotP0nRpyntO6XFaT6JPJ5PDSZPHCilVjr2HL3bpHmv5DaPO9nsb3FBb/MSfQdWcyQmf9OLcOZeWnZsP96cP8xmsfScUSklIXNjVDNa8rzY9eJJlG5RoZ2xp1vvLERcAaTOfHVppDHyxWuu5ROf+ARA99a0Y8AcGOw/z8lWUI8le15Kf/akc6KS+9IJgHSjnvE0t4S3vrst4yk3T45Yd5/8OF2D0HmE8yRXLQItX6sbSLaDe6PsDaE/Sz2myOBazyHLBmU26ksWRDYUu4GbMTEnLeaN0TyObs121+8jwtobSzk2Rc7zUU5c7+a9Z9H+dTTNze2scDnF7wCExGe55CKPZQv1BV3/WdRkqP3eK3PKOikjAL13tT37tr/W+8vSHIx73/s+POD+D+iVNpyJpIh3lvmBItlRSt+ZEWhrxyc+0nxEWurOCVLkYNZTsSwhh5J3qLGGvimC6FI/IrCeQXkdx3xeMtA8ZrRI4MZDh/jEx/6GpeZf2LF0DFHl+GQnt5wY264u0Yxcj8M7ofKAWhq4U0/0jloqzt99hIsmG1x7fJmgqbShrrhpdcRnbhD2XbGbpZWbGS80LIzWWF64iX+8JfK//iFy/8sv4f4X72OkQrQolLmgPSA8O302V8mghwIsBdVSZmdFXwq+SLXSeyj3T+rKGMlHkLMc5he92I550MveS5TL4GIvj6knGyUq4iUv31wnmZyNZJMhc2WS6Y52juvxEUpGmzT1ZQrO+jEhdq8COkkGGUBzD6JoMsunesu5ZMJcuVmeuBuPE9fp47mgZpqMbP8h5qxGcxwczvp1iYI42tBw062H2dg4zplOvnJ4V4HEtJFNMtUlldqll+wKiJPXYgcUODHHrIt8GWArqWWEpPKP0guKLEN7cyyAJMstla8YAJv+TQvcp9y+2LNxSuZ50pHWU8WlNWUWt5G9R3t/qaRrjgfEwPSySYukxulWHkTeYS7Z+96Bulhkl1N7VqexzJtlMUULZuZu3Biw2elBKVlKufQsyijNdCcXNc2v7SJmjeCd2nPmTGdXVbhKrJSm8KHDuQVqX1PXI8SnbElR6qomqtI2gc2NDUTVmgHTksFir5D7r2m0Xbz6wjY3l7dSOCuzDBKL3Ww7dTs02vyY3BaitmmjpW5NZPs7qfn02raEUXPFiPo0Z/1FlPUyOGeAqkYp5ZSWiVWBaq/1ikt63HoMeZcyeZESGDpTyQlIdFTi0egJArhAVaLVATdWCErtFlBxTHWShKKnGtW0TUiwSYW2lfmiLljpqRN8et/SM26dj0QaQivUrkbU+hQrrYEs4mii0rbgo4OqJjQe72wnUdGWCmOJKEpwLTCz3UCT7RBUQTyamnx7GYGLtHHTSkdjRF1gFgzcwVeE0NCEhlYzcOOT/Q2tCtOZsCCC6hTfKxtvZxPEN9QLowTotkiSAwHwOmYkY3BTnCohOKpgfaRaNmhlDdwYDZHKCwRvG5QETc3MrU+UhpQ57BzOjdEITQjUY4hxYpVL9HauD2Jlb9pYplD0EIQoEXUV0Xmisx31nFN8NFksETwVEq0lgBJMTgngGssI0jqxcCo1dZmXRmjEyvNCW4I5TdgkEvCuQhQ8Br7HaOOtvFCJo22VGgdhagi0n9FoSxusr5PHI7FB3QxX1VSt8WBkbMCaThKgXOHjyMoNvZUZGoBXGcTXKqPxEkGEVpVWp1iGqwd1OCpq+WpnPPWo60WQqXMARHrfp7+ddL9T9IgUoZ6jL6Dbzofu2C2jmP+z5+CW2m7pIBwTylYal53bFIewMWLRuYxp5R3pQlCa1srpgvZ6O0XQ1pDbk5VxbRlY3/3rzWMnZXXOOT3VtXpX1ZMdlwzpDISxxZi9retFLVGS7aM/DdoKgt3O2SU9mj6gRPkspxTPZyid5Hqaj593uufL6EjllPMOdTHmi7HRH3OJH82tl34GgC1LtYy6Uz7pmUMxRv7vxz/GG37ntzl77+5iyHTpzcYIXrJDarMRyzz1zbsO3CQp3Ry76xyP3tpPRmcph+wbLXTrxo41XhO69Zujt8VRki0yIQ3ReH7LOumPMz1PBxZmodTbBSuPJDlRQWUrW7B9baeIsnSGlOQBIcW3iz3DO0d/uySqnNVj44ua7LBsPDvKDIjLPTCSkVzW+nzuoZb79yKQaRy5l4OUq6TZLTJYyjQL83I/O0Idt0jp8+tSIKKLNmtxqiQjFnQOqnGRdmUg2ud1G3vpG1jmNFFObpNuLeX5zmO1ceasJumOSZc6dOg4Vz7qMdzvvvcFztzt2AVSWq1lI+WuLkBOfjCDSMACUVmfdhcwJ1DRkHRi4XkK8GA9D/J6smNyX6ReJIDksxbHNGkfxAlfOnqED/5/7+fs5ovs3XUY5yZMm0VuOH4Wx6a2DbTqmBAjlTR4As5ZrxNxMZXhO8a1Y69b4+I9x1gL+1lvl8zBqRwSdnDtEfjfX/R8+/2VsxaO4dngnrLGyF3NZ27Z4BOfajhwbJ1/dd8LOWtcm55zac3HhIr4DDqBpIBCilMl49Em0QA1W8tZ/+b1mAsI+tlCvbCS8TMwB8okw9Qyf/KnuXQtfZffa+bD9C5txzmbeeuTSSdS83ZoedHk60sCm8tYpLxP1w8supQM2WMzEzWS1kByINT0dLajsiPfFYzlZ+12rMrbwhM1VTSVmelmK8uflL1qU2P9UrJPHjwQlcmsZTppOfe8c1haOPfkjHMGUVV5y5rum1riUhltEfVdPzKxDMQs61XTzsu56TpgYFPmZk+WfxlUMjneyzxz3aISyXLAdoL0CTxoQwuqhCKku+CiFCDIAJhury4bf18DZT2SecJsffvLtjK3a+dsqRwjEO9t56UMjqRMjagCboaTyLheYWXnMssrS1TeEaPQto7NjQkbkw2m0wmhTXamNskXsayMqKl0OaGiFTVKk+a4Imo0gDC1/nDicC6mnanSGtcxbuwZLexCUFbGFbv2nEM9UnYsLzNe9CwseFztmbYNqyeOM9k4Rj1a4bw9F3L04DpHjxwhzDaSbdMBxjbmfgmggvrO/nHmXJudLHifezAlEM9J2nnTeMuJIJrcvZTNQJoP69NWXjMlkJvm3qVzKD2nLJMrvU5799rZB6QefSRZasOSshYo5VapJxdVgk5jqX44U8lpk0q3KlRsnURahABURBHbUCIfo0IliwQaVAMhANKg4mhDTFl7NRWRRqfEGAgYzzvxKUvdU4kBoSKp1wtKGxqUUDJu2hhsRzS1krTIiFoWqb2VR7poPZOCBkJscS4mXeOx3UM7I9oRaeLEghvO44OBo6oRb0eWjQGQtvhTgg3PAvMVdeVApjR6BNyO1KcwMKqVwAwctpZCi1fTZa1CUIfGgNO0RtPupoGGVqZoFWhDgDBCQ41QUWV7R4WZWmttdSmrMwZiqPDVyMD02QxXzbD+Wg6VGg1ChUekJkpFq4qjsQ3KcIzFWbmiVjjvaaNHmZbNzgz6GhFSw/Mpps0rAqIejbWBry4FB8QxixNcbPFqmVE4iC4SdUbUKVEiMQpRU7PzCEhFEGUWNhGJ+KpCqHB1RNwEYYpExesiXmt8smeiVmgjNLPWACpxLFSLzKZL1jRfRtbsXDdQ1wABcRUV1u/KOc/GzLbx9LVQOUG0xaXsdOcWEGlPi4++LOBpW/SkR2ajaRJgtmh8Mn4zUp8XUj5GyjW769u//etKUa69/2wbV3eeOUbW88KEaerL2d03Nfv0OQKcU0BRZgmIaQLM2kgIqTZXc4TPOjYVx5h+eVfPqc2RfdkO5kt2oBWz/LMjt7WJEv2MkO67uWSOXvZId317IeWbGDkZqGXzevL3uZVO2vS7d9eT9VHq3amc0WVpzV8rA1Igqcl3fs6tsFNeLB2A1e9noWjvWrB19rOZ27nSPaCp57VqMrBz9DDb9dmJLhl922blzCNVqOuKf/Ut9+XBD7gslS5a2rmLtg4cQuV9imCl86QzixRK2Yit/0iIVv+T69czPwcJxZgUSeBf7NUyuvxys6GTBIVPYEEuK+u9rWyI5z4DJMDC0RnuUbNxSAeQpHXSanaRzaHJgJYTpfI1QopmIqgTglVU9xg9AzYUp9FJZWCTs62svfdUYqnCObMAsc0OSCnqKpbObOVnSf4RIUQkpzHEmFJ3HZ6cjmtj8d7S+0nGWp5SAw+8NZsUm+/suKnGZChZT7omGZ+ipnCdpK2zBXKTU5dAozyfTswAEO9oU815Butsd6LUYy8ZqDnx1rvcPDfPXcp4TZMjqa9GznwopV8F9DNjS503RZIblOaV6J2VP6frpaOtPl1s1xwFYsoSyQEH8cqnPnMt6k9vN467kmLM24rTNVjOpVZZamUHFQOQjR9yujbkrF5KslsusTL28+k+uUN5jHYNl3ggxgSuuLyUM4hrkdNZVG49dpD/9b//mqXZFzhn1wG8W0OicHhtDzev7mAyFTwjRFLZkIu2w2zaMBmpoPJ4bO0vVsoFO45z88aEMNmF+DGqHpWWIGdzzdoO9ly3wrdcOmJh4RYW5QTnieL9jVxzMPDF62f81dE1HvqAi7lw3w7GajZK1/cplhKu7Pj4KKkUL61BZ0BwrT45wjHxAhgPmjGV9t4i94UKJL7AnF3jqrzzk/VRKDrLSaqcS6u4KFY1PedS/5cM9vQzWvK7F7CWAS4tC1svJpPp9VjrAiiaSkDMwLG10c+jK9mrxAQqp5cvvSxzydHsDlQpmU7Odg5MxSkmf126upPSzJx0r9ILSEqela3zNmUzS8vmNLK50dAEZe/uBUbOpwzzM50ivnIJsIxd0lIS4C479skBzHoiO/iSACrr2xKKbVT6+UTIJWdI3rGsYkthZ/dWk371zluP0pjWdan7TLtZ9abWpezHqC0q2SrIBZnemhPnXfTSM0enCfDqQIuEfiOSdr3qV2RFEs+EDihzFaGNTJqI+IDfMeFE2OTE8RbvPLt37Wa0MmLnTs9KHNHMatrGo8HRNi0aAkGVpmlSyw9lFjaYTmZojIzHNaNqRD1eoI0ti0s7GY0Wmc1mII1lmnklhEhoIuOxZ1eAcy49h8msYba5jl80zXNg9VbaY4Hjx44wmUyoRovUoyW8q9m5uyaMbuLs8/azuPtcbr7hIGEyReIM1QBpV0IHaUMCLfs9FGCuJzNinLdl8npQIEQrD3Le5Kkm0ElSACPbMF2PqJyJaH/nHloigtTJDlTL9iiDKaPJ9n6ykxOoVeRYySbOpXbJzFFnCkUcQZs7xk5fY4o+rUksOzhidlqjkYhaj59oc2iNqkPS15HoGiAiGlAmRPVUbkwlFV7G+BCZCUx0hgCLUlOltd9GRV1lcj0xo1ePi57QWtPvkdQ4twgyTiV/OXu3xmAlKwGMyW6LqkxiY1I9KlXKjnJ+zCxMaKRFoiO2ivfOgLYYU5lZxLm0RvGMqgVm7YRIg/PeygKjNdEOknjeB5yMiSwQ3QxxM8t0UoVWGVXjNE61DLB2RiR71krE7HOJNbQ1Ej3Op/LPCJpt7gjeVbQYf4RUHhvVAQ21JH5qK6KPdg11qHMJ7I3mu0Soqwqn5v87tfLIJkwQX1FXCwSxRvMxBKJGHDPLtKrNph25mhgEbQVr/NWgOiOIWMmlAFVAY8pWrTyttjhtqVMAyMWcDdYmXVGZTvAOtAEaA+W9aeAQaxRv8+NmiLQ4WmKsER3j6zEqM6JTmnYTQkXlwI+EONsENnFB0dbKC7WempwIY8bVmKaZwSzZfU5odJaAb8viOx06beCpn+rbZSS5uQyl5O7bdxSrjpwy4gTEuxTNZM5bLyUmfdsho+ZJIPaBnXTWvMevPaBDOsPaJaNYNe/QYQdocnYt1TS7zKmhOEJQTSV1qYcTWpqKi7NIQ1HhMl+y1TMHKVkNW9CJkvKK5nJy0wU952srzZfz9WR/uk7+tmsi2VMLt3HdAlJ9hbbbycbe/73L0ui+m3/lnfMYkwVrpZPboR2lK53Lf2fw7mRA0PwaduStwI1cyQYpZxcjPfcnMAOwAGHl1r2XcAZTZrvQNsRmw9Y9ANZdxTlvjn9ITmfm7dQPodu5T1JWYX63tn1nTD038i5DUdoeT2syJhMFBencm5DLBUSKs5uBqGhNAMrGA0GyK5TMWk1YBEABxdW2WE2KK2qkX2aZeSVHM8ERGkuJzs0UA5KUER0+loCQHOETgUiw3TR8klNRwOUtbOnElGSz0EhF5tevRiTGJGNiOcc7h0rAhRSRRg3sEymgU6m3UUGkpZX0nGnwFrC0OQhq6cwmI23dt9KazAiAeKwAynUZHklGORGiWEoyCcQKaWtXmzZJu3bYvPnyzmz9WRAiO69ZPSS3KG3TWxpg55KyBIIYKNEZu4qQe+1o6BxrjWLvLvUpyXJCAbNG7LouOdsx9Q0400kSUBizcpNeCVamaKBKsggTwJbkelovIYEL3VQaPwsQHTk1r9PTYLvH5JQdwRpf5sWcAJtWIzfcepD/9ZEPMl6/mkv2HqSWE6jAerPC9cfO4vjaAiF4a/wrQu3Ai6Ny4KS13hJJLyMNyBjnlD3Lh7l491FmJ85lGjwxOlrvqXGMxzu49tgSo+tbHnhxy8I4MNZ19uxYY9Ffx46FGVevTfjwZ+DyC8/lfhfuYWVBzHBWUHUpCyNniWUQpbM3BCvXKYBdMhpzi/co4CO0OcMkcXpFp1OrlBtSpJJILwMqQjDjWfO7STxjctMlEDnbHt16l/QOzeFMPJ0+Uu1eGy7DtClXLq0R1azbtDifJSNHpdeWKRsoiYehZIzkZ57nInuIGGPJ8rGqnr7ezWs5lXpoypBPc16GlLM3WticNRxbnXL27iXGoyploAneC2c6jbyjkmSPOlsDli3WZSXlgCn5h54CSvaJc9bENgfXin3ifQnYme3c2X8lcJY8/pgaVVqvKWs1Ucols/DAbu/Vld9BEG9Zk+TMGZfAQvL6KwvbAlyqaAwIDi++eAmZCghW7pmysVNAZ7SwyCREfO1ZrpZY31jlwOEpk80p6+sbOIns2LlGVVfm+GmDd8Ku3bvZteNsFhaWaJqGUVWzXFdsbG4Q2zVkNmV554gYRiwujlDX0oZVglc2NSJVDW6EyIjpdEo7nbG+voH3gpsGNqcNiqdprRSpDbYr1OLSDqbH19mcLRLdCO+E9c0ZB2+9FXHKueft5dj+45y7/zz2nrObzeObbK6u0YZZCZJpXhfas1M0y58UmBGzNQpYndZHLgX01byLl3Wt5gzElJ/mK19cICd5swBbiz71DQM1+zD2bLfSF1eL7aWJp3MbC+eTB10C6q4D0Eofrbx5w5lda7dzeQ8bG5u24VQbi7+m0VF7AVrEVZa5pJY1WInHy4hZBO8rfOVopzMqF0EnKEIMVmI3IvVnrBSnLVDRhkBrBjDRKZVPDB492kbGMiqyu6UhaEWUmto7QpwRQ0XtrCuc6RchOojqzSaUmMAO0zNNUKKrkSigjfE6jlaFECuceoQWJzNbM7pE05ot2KiCtowEnChRHK0ozo0twzBaZ6agMekhJcZA7XzSVSabRBqib/Hqix8QZJb8iQpaA0sM2Gst68yNaNRTuxqiUEuNhgQ6gdk4lTKLLbUfo+pSaZvDeU8gMmsmuCqtex0joTIbMZW2i4ORB3TDsrzVWymaFzRMUZ0xqkeWPSoxvUNPqNTsm9jQhsaCO+KofIVjAdERTduANrjYYFlrHucqFAgEoraM3AjvRsZ3pM0LolJV5hMELFgeo+BjRNtAqwFfLeJdJDKlxSUXr6JtA9Ay8hXEGa4CH6DSkT1fbSV1bZjhfEUTp6gPxrPqcG6Eo0K8MKPFc3o6+MvKeDoZldKM9LvVEmd/JJcrmSVUMITMtOmY7ahHJ8D6z9N3+AvmVYCYFB1KjobFHyjKvdsZLYnSlA3RNd+UZBylpndpWCF/l+8fyiVOMSHzv7j0+KRZSvYdc/1HTgmZ5Ofu3VBT2vHWOZOtx/Zd3c5AOZ1yvpPRqTLdtt/3NM65DercS7t4f2b65Xeh/2y3eV+Z+yxHW+aPL0uAYq5JKh3KByRnvryxDLzcDaKtyTRJc5DKwTBvwHZiMNTdjOEEsPS8kFy2pRTcwPhMnaVKuFjSgCUBFSmBN90//SakiExOg7e04uy2+AympFIMSWOxjBwDii3zyXVNS1Mz394IjUdSSUIH+WjGHcruNhAJkspBMsjWm7QCeEjnzGXD3q7tUvqsmfY5w0DEgKt+tDqPMYu07IQIWXaZoZ3bU0guw/DpGZzY5JdrpawXUlZXr2+TFM81lcWI67IfooF9BlDnTJPeucXpyVl+Xflg5knbMiWgqYOmZIcGhRiofM53yiU5pCwv49zMntIrDbIn6rIP866pBlq5zmVNO7yRdgANqIF9CrnhsqZ1E5XexgpdYWnElee/Lbl7plDu15e3njbKDl5+senv2H3cIc5WGu4F8s50mpx7ivNAKp/L7z8BK9ppkqJPEx8oShMjX7jlFj76iY+zuHkt5591CFetgs7QWHF4fYUDJ5bR0Dm2VQJ8nSjONViadpPAjEBVWcbdqBLwyvk7j3G0mXBossyktST2UTWm9p7od3LdiXsyuslxn3MD1SiwpAGYcA93E+N6xnVrU66+dsrxjQn3unAXF+xeYsVVRKHwYJenkcG6xEcpvVlUU8ZYmitsrpxoAb5zrzYy32PydpuG0P5cpmuIFoDebp8lVyxjiap47XY1lHTfYpskcaVJfotIAaiMlzMPdhm7rqfTisWgPZ1ItsO6Zum2bJJAzAcWQFPLA+Yyu9zfwuX6m7xec7BIIYYUvBBKIKhNfTpCY8/eqHLWrjHjcYWoKwBzDGe20wpQedsS3ZwuV4KcLvFbErn2ZrJNXfg6vy2TVdbrI8noZLhIkovemSPfBcoSMNUbi3Mp0yTZ4TnFOa8h+mskNWLNfTJjKgFS6XaGNvDIFfuyk+Ou6CHAsqTK+0+BxZwrneSJNUq35w0etIqsTTeYbE5ZXFikqj3OLeNkAZFFkIgSmTWKbfO+QDUaE8IimzMPHlbXNtnYOMi5553L6voqzeZh4uwE49Ey551zCfjAgcNHOXDwmDVxVsfOnQGRijZOOHF8lfX1TUQgxBnOQVVVLC8toyq0rdLMZkQCm5tfYn1jA43QNk3KGgosLY0YL4yZbE64+caDrB3fYP/+szlrz1nUS7vZOL5JO90ktI3JGyHZDd38dWyTLB3xOMkAZHpvGSfMvJmyolQV53ynS5K+RVNwIQUpSnP7tFY6i1uIklqjmJon9+aK1jCnOyuNJcucsrZIWliMdy0InPoaneFm9HQy6QKhMVA5pXHgnMeFkJr6R0KyXZxUaLRSOE/ESSSGJukIT9CGGGd4qckbb1XOEWiZ0YIXQrTAu8MyuENo8F6sqX7tLZCkljkcXYv3ltmE1MbbsbHAsArO12gbrARVjc/aEBDJZbUtUQS0toTEVDbmnKcKLmWVBqhsUy3nPbGZoLn0MrG194powDuzz5tgmdeeSMsslRpWtg6ila9Zzr+CjwaIegfB49Qan5OaZceYAphg8iMIlVtA3IhpDARH6lkUEQKikShC9FKEWyuWwSUEVFqiNmh0VgrpPWA79YXWm6fkWqI0NMxSj72IU6UWh5cKEKIPhKiI90DNbLbGyAUi1sdLUgaaq0Yg0Xa6QywLLFZYf8spaEvbCl5qA/QqBbw9f9Ld1vy9wjqKt2gMaFCiCuLBpZ1DbadMA/uDRFSb1K/TMW2mJmedo1GHUBufSk3bQrFAXGW7/kbra4ZXfBWtqb0KjjGztIZua4+fPn2ZwFNfOmTHIBtbOV/W5XGnU3opo1BAGBWLPBejrXfNIu7yVu7FOdHe1+mYrDxFig4LxY0xAR2lD1TZfaJGW8zZotZ8vi3SKJTzyz1zSVBvPuZVem9+hA7sKM+o81M4d05/0k5Nfduuf688Gf2rlXNKRKI31Wx5lNOk/jnFAE33mD+uOzAbQHeEtj7itnv0dZz0zbJtI577y+UIbzcwsnJXuoijXS/OzWnM8kvzFpMx1dKf6dTxTUypwZKN3uzeqO0vkgqTAC0QlQZJkbcUUUvRMgN1rawrhkDeUttuF5M9mYyh/o5pOclQTCz3F5XZpFLWVt6AwIKiyRBW8M5KX0zhZT7VAlQYQpwqSCRtJ5v6hgidzNCoyfAC8k4+Yh6QpfGmzMZ8rhNUg5UHZW1LV7Zkz5AcVcn36l5BPig7XHkNmqzpNVslOY8p86AzAJNSyGUV+Vmy4U5vWW8BSruVmrMUMhiX5JhC3j0pP1DeUjpnz+SMDLtedooo66FE2ZOQKjI0y9aioVwBcud5XZMK0e7KmV9j3wGzz526lCGZ5lBDisbZYDv5nX4vDnTHAWc6+ZQRlvVhAVSlAzPJwF5ZhxlkSAahZE5P7yPNcc5s6QMNsTTnLQlUdpWQAJL0QpsY+eKtt/DR//txZO1q7rHzZurRYasej5GN2ZgvHd3JsWlNlOwA27ybzPHUlVB7c0CFaEC089TiqZzDV8reHcc5b3qUtWY3m23acUcE52pEYBJX+OyB/bQhcJ9zWhZqZRwD0HCuHKLyE2460XDrrRscXdvD0fP2cvm5e9i5NC7zEkjlbnTl8hlwyStU0rqXktlh/Jn7QhlHZlDH1qj25ovcID8v4WzfOJcLDchZSBaosxfjyjXsnfVXbRec6wUNNAPxW0ittNBASe1ka15DqcTQepRLAinn5XPUnFlaFlS+eBKdJjeziC9AqCmf1AsrZXo7VwJzLg0iX242CxzfnLJrqUJlxKhSlsYLnTjQJFuKcDnTd6Ycm8OTGK30Uyz2s02m64FOxqcGVFGeOQnh1NjVeMHWonNJb6VqgZAbVaf3ErUDHIvNU9SyZdZozmIt7zUdnXqtZLkSQyxBH1v1XSZOBg5dAsOK7s1yWpWUNoVllbsS0BHvcAsjEOHwkcOEtU2ct63Tb7n1Zru/mvyezRpaDayvrTJeGDMej6kqT+UrFsZLLKxvIJWjmc3wXrj1wK2snjjGQtUw29hgunGCtWMRXMP6bMrho5uEGKhHY9bWI1U1pqoWqaslvFM2p5uEFkQCs3aTthF8NaZytu15O2vZ2JixsLBEDC0xtDRNw2SyzmRSs7i4wvJixeKyY7wYOXL8BKvrG5y1+2zq5RHVeMRk43jaOEAQrAxSc0sDMCfPSSmNzLovy6aO6xNg7cEMGbdFctg1xQuIAUf9clwwGZ5li7151wXRcja0kDY70LlsTYvrpTGkRvJAqtcWRFPQp/iNZzatT2YIlk3jnSfQJts3gSZ5Nz+XbbjEo06sbCZEYgvOWT+oKA4vAXFph1dxWCZ5Q0QJOksBNXPVJQoujlKwriaIp4kNzsVUyWjwTYxTVCqUCkeNo04+rlI5QcUlQAsql5uBW0NpEy0RpbXy+5R1KIBXTTu8BiRGvBd8JbTB+lE5DLSMGgna4MTjpLbNvZyVGLcaiKKpUsBkgtmXFkgmRANvVFCxHdk0Ck7HoNYL0jbVbC1PzivBW/ZPSDJHXVNaC8TYmK2hjohLAVEDpMzXgai2mcrCaNn8u2R7xxDS2CKoBcaCGBA4oqJyY5owAQm2FipJvQsjrrXX3raNlbamfmbOVbjK+CeE1N4i9XlCPMGBVAa65cBMSJmpTWwR3QAVquTDNrEBapSKECJowLvsKVSpjUUy5Z3DpYCHE4dUgTZA08JoVDGbNZ1uoU1Z1lZamrcrFK1QmZgcDx4Nrc2zCO1pZiyeNvBk9YtZwfXcjBKl0WLslBK07HCRY36pfCdm4Zn5LJXYGGvZT6/7YkbkC/wT8727yIltd5hOTV15u8wNOy9vjVx8yuSslnNS9gNptxYkO9V2W83On3lpaWa2gyCqvU97znYfnOquofOXSqnoc+aius456GX7lBP7TobOn9t35rJzOTfYZHTk5qbbjNTTCEEIUvre9A8/+ZnFrdkyju2HydyfPYdZyiHJcOuPpX9NnVPU+Svze7WLbisdcJYd654lLuX9dWRbTaZbqOum9YwnLSV2paFtMhJz6n3Mjnp/eWq06Gav70Z+Scr8ujRZkY1c5uamBDrL0VCcXhJYlCJ9eXP1DqeQsi5K0+P0cXav51aDmFCPMZZ7ilK2584nlAy2nvNELhEsaJEdXHZBTI5BzljM2UbZIXUZNKM7Pjfq7Peeo8xTt5OdAN3e6nmeszEfu7UJ9OshynjLe6WX4Snln+ykul7G5Hw0vHvDxdBEuvXSu1wHeqWfIthJSktTnyYLA4SkDQwoomzxHCUboFA0hupc5n3Z/KAAYJlHe+NJxlX+1/g0ly5085YN9JzxdncgJ8abIUbatkUEal9bo+l+47Uy51mXpJWYlpSDlBHTgVRF5m0VvEk+zK/FPGOW3n31LQf56N9/Ao5fzT123sq4PoGEgLiWJixwy9oeblndwSxaRM2Lw2ne9t3WV10JoyqVP1dKVRugVDnBe4uY76w3OWfHrdywdg4yWwE84ipIu+IEhUmzg8/cMqNtJ9z33IbFago0+Djj3JVVFv0XWFw7xnWr5/PJEye4+ehx7nvhudzznJ2Mna3BLHMg8yJlTqyMJBYTpUihVKooqUda59hTdq+xpe3601jeQ05qKAB6li9ABhhz+ZOolfT5lPFQxBSaBKXttONFLNhGZ29oyjayrCdKJlQnUzvZmjuld6JIOnHYWx9ZHvV3Psuz58qatNNCsPXrvdjWzskQK7adpFKdlJ232TQgMBr1ysaKjdTX69LN7ZlMycEXl4DLJINz2bbJNpd0RLcTXJnyLB/FAkdZV2bmV81OVC6lyn0Xs77qbBvLlnXzQTPpsnhzPyAn3dqYAyBLtDb/YwazVRDML5OQehtK1pnay3rCk7ufRRHwnqUdK2w0mxw+doRJO6GqrPnvbBZomoB3NcdPnGA2mzCbNXjvaZoG72vqykrJK1cRgrI5neKDZUvPmob1zXU0toxrz2hhhTCbMJ0q4mtC21LXFXt372FjY8p0OmFzMqWqNlle3kGIU0ajitbBbBrRWDGZBFQ3bO5joK4r2kZZGHsmkymbkwDqCaFiYWGBECKTZgPdjIwXRrRNbr5fW//Y6GlmGywtjhEVFhZGSFBzRCNmj8Zkc+h82CfLqxKcSCW6pHLUDO51wKA5wPZZzkbtvdJMOWidbJe8Lp3vsu00ZIA6g0gmG0oqQm/pWM9UB9EVGYZg5V1nMAkjyw9XRV2wps2xRtQjzsrGrLF2sOwmLAhmLJoSGapou4ZpziK37JyoNVAh4vEqOFUk5B2aHV1+oyc2WeSlAJpk29R6SInWEFuCRCvvE+vBY3qyJUqk0RYRT+44aEFWK9FyElEaIhVRK0KTAGIXCSqoOmoZ4RUMyPTF3rBSw2yPGwgVndKkLeNjTNkxzvplQSRooPajtOYM+HZBgdZAEmqIdScPVYkh4LyCt2NiSHnL6o0PtcZJZVlARMRXxGAbGjhv8tfKkceWuqctlfM0IZgqcUKkpU07RhqQliyoZCvY2haa0BC0pXIjKhEqFF+NaGYBF9OmKWpZ9hIFz5iI0ETjfaWF1LidXA6Z7YwCzgacD9ZkvXWggviK0AZG1YgYHJWASAs6s5YlsbYeikFRMVCxxewH9bbzZYyWmZcDTNZ/rQWxFhTqPG0TcBqphFQGBrabnQdmeAk4V53K6d9Gpw085dyhzH7FrcpOWwltSXd8sngM7EzuS9rdIGcCZG9QbR47R6JYdh0S3jmwSTqmrAuEshCUBMzFZLAmwytH4SVnPSVFn8tlcckJSUbefLuA/Ew9J/s2kIagsmX+ExOWLW9SVKj3XbZiNWeG9ZR9EQoluwB6r4J8epm3uZFvdSTynLNlTjsjYq5EbYstd9KSshIY7+bpZCQnmVP7bX6A2UjujJSTX0h6f84ZRlvXSQYL0rxaw+aEzifjLj9bBiS0Nx9IN08lMig5c8wiiypbJ/kMpdLYpTNnc5/JKjUkCpozhPKazC3+DOnPJVrdI6eUTqdINAGr6bzOMcr3jBSUiXRccpqUHI21+e3kQzpcu/fsJPdmyt/l89InCUjT8i7LBYoRZadpid6nZWfXlPS8xSZ3vZefj8k/kpy3XqaXds8g2chPHmLOKjJx0IfMjL9zfzbS92VsQunzIP0JLHK3G58gc2u2GIf0Cxu6SHdXypOzMXr5Ggl8LfIrz2WRF6BqWWv5PE39vnJQoswzyckmR1elICFCnZ6nV7rXex77NTtQ5eKYFshGgAFN+X4hPWOWpFk8mFzs1nDPtTtjKZcLxtgwm03tOcdLjOo6NcAWm8fEX3nnouys2xKx7Jsug4nMoKU5s2adrOndJpkomvgzGV9BI9fceoj/838/STx2DZftOsjy+BDEDRTrJbUxXeHGY3tZnSyh6qzRKELtBck9nVxkcdRSeYCK2jVUrqZ2Dlc7fF3jvaPykbOWjnL2wmGOThcJjNN20ZE2BkKMhBY24xKfunE3Icx40D2UsTuAVDMLNCxMqf2EJb/JNcfXuO7GTW46sM4DLzmXb7pkPzsWR2lSjJ8sFZ0EGqd5zP1Rsr2giZmLVbTFeYuWpamux59b1DjkbIGciSZFnmVbwV6LBXk8khOnbFylZMlsHsssopMlZPtKOlsnaiq/tWfI2YzZzikJRJqfLJld0NPBOSexn+XarbWtMtOJlWhYiVlnm2m+roqBU22kqoTlhYq6VdZnkZG0NCGyOK7xBTFLcupuon6dV0QsEBKzrCStL9eVpWcHC7LM03KcJHDIJ/Bds+7J72QLAFeyqbIuzYEBVTSkoExvLcckm7OtaT1N6QH1HW/kMZXsupy9l2VNlrkxrZKerYZ3iPeMx4tIZQ7f5vombWhwGji2tsbqxjpra8dp2waHp6prNicbhDawvr6Jk5qF8SLeO3bu2InzjtGoZmG8RIzKdDqjbRtCbGhCm+bT/jObwkI1YzRyOD+hCTOmzRTEMZ2t0YbIxkZkdW3Crl3LHD9xgvW1dbz3qQlzy86dOxgtjFlc2ImTio2NE4Q4Y8euccpQsqbAMQRiNNAMjZw4MeGCCxfYuXMnS0srHDhwkJtuOsDSyhLjhUXWJptsNg2zqe1cNRrXLI6XWBwvsry0AkFp20BsGrtHG8sq6dtIIdu+Kr31oOT2IlvNeU3ndT2jevZH1sHSP77TGbaGXTGzejfMVkW3Fsu6duWC2lvDZy6t4n1tkss5yyQKuUS1TX6FIo2g6tHa43zEi5VBhWQP5USOWnKxowAVbUwljyoIIwM6YmO8bnexDFEBjQ2iEY+W/qq+qsDXeFchQfEVWJP+TdSb7teQNv6pFGlBtaJpFaTCaUhBY1unMXQ2IdKWPp+mi6y/UasKGhAUV+z8rDii9XqtG2vriscy1GHkKsueih6nHqdKpEXEUVWCaEOMDSoeDSM0emahoao1ZZGYzRNjJIaIkxEjscbnEp2NrxqljWcmOImWQcYoNbQPacMeA701asr6UlxIGy5IoJXSGBRRjw9ja5wugZlu4lza2khqRDyVCiMVZq1tOkJVUYuB0nYRA/ZG1TIxzGjV2gyIKPVoRO1gc7JJ1BkWJBoRQ4tVhtjuo+Ksj2pIm5+5qgE8VTVCdESbSykB6sgszDA4PveDE3tuV+Nqs5+n7cRkW2s+nJca5yxRr65raFKfymCbhcQc8HSWwSdqPWhPh04beGqjbWebI98RUiobBNcPCkqX+mlaqTid+KScNC3mbJOkrAGyYaZAmqTkfRUENR9gu+EkJYqhpyiEVhOiWZlxSyS2gbwzSG682m8UXZENNFciOk5CeZ40SnJcbk6oKnNCHQz46lpJaddTL9UZaszuppbdXhAzKMVDrt0u1+9CkqVUcV74lyGyVWx3uR697/onF6S8T3NaY+6b+dK5L99Z2+roz33X+7inLk9qXOZV4eaUWf4uOQH9nihihrntNitp++DO8Cobgyflaa83pZ73L5JKr9gaMTyjqVvDRpp4y7pMtNF2GotqkdDSkFnz1u2UrcRjdsrI9f4ZuE0OKjkiS3mJ2jtm63vPfJzXRAc6FGRgjlyPO4ujltZx32iKvfdmtnB/ffQgqT5wmWYpZ0ZZFEU7R7NvjHXYiP2aHHzJEeu0iArYnaOMyUsr4Gq6SlnH2a8qg01Akmydm57rKl30sXyn88ZoECsJ0tyPoecY5vIK6Z7GDI003NILqLiJxUVNc2iuZF4XQVOfg94LUI0QbXtsWzZdPqwSU2kBHeAtKdZXAOLux96nlrmxbMWu3KM/r5qboALzxm0HFpzp1MYZFZ4Ykr7UaJG6WNsDpK2ztbzzXFJs59uzp7cn3W6E5vB3vJfxAuOl1FOIzFfp3WvkiweO8MGP/T3hyBe4dPfNLC/eitM1bOvyQBuXuWVzDwdXV4hiuybG5DSrmNHnEEZVy45xwFdgfZu8RVMrz2i8YgCUjyDKUn2cc5cOcGCyj+PtMoEWba1ZaRNa2rYlBGGj3cUnrg/MouPh91TGHKL1geUq4H2Ll4Msj9dZPrLJF49FPvrPLTcdPsbD7n8RF+3ZWXivgO9l7VDmqZ9NDcwtIiv/7UrUNE22knCrxJ55NdvUdrvLlcu6/Pu8zjbwKCYZs32tZFA8uwHizPywhuZ2LZd66BQQLC0Uc1jzYsAyzF0njIRenDEVB4paiWJeO0oCK6I1kXUK4hTvlJEXjq1O8F5YWR532VdBSulWVTkqp1a+ROSa669Hw4zRwjKXXnxexpzSeNK7cSeZiDOM6mqEuMpcM+m1mChytcuiFen3JCUrEbLmKuyY/jGQQUtVT+5hKE6srxKmv63kqdPNIWbAstMZed31y7fzGHLpVd7gAmy7cZMMmnRlzswVQnqGIpO8sLi8DJVjczZltV0nBmW8tMj62joiFcfWjvOlm25i1kyZTCZ4EXbv3Mk1192AiLKysmhlJT6ytr5K01qj4xBb9u87m/FoAxFP20ZiEKq64vzzL+DE6nGq2hO1oW2Os7ZxnEocn/vspzl2bI2FpWXcSLjgwnOJQWnamtFogWmzjpea8y+4gBNHN6wEdPU447pCtOHE8Vs4cfw4KyvLjMcL7Nq9m9GoYjQ6wYnVo+zftx+AtpmBwLFjx7j+hmv50o3Xc8+L74n3NQsLi9Tes7G+xrFjJzhx9Dg7diwRdUpVO3bs2m1Npn2FwzNeWmSBRWvaHmA6nRJn5qx3OKMkF0pSdkwqnUl8moN3MXa6vMSyegZ6Ml86GZh6FJlsNCfXV1AqRmI+K1UlqKb+4tn2sbVs/aagBDpOs1TnrqLIDMtbSYCTKqIzbCflAFIhWhEVmlQaXWmye0Kk1jFoTZDGmm6LlKwv0YDEKdUIa/4dKqCiMuTWshdTgENiwLmZZZBXHkLAVTaXbVC8WNCzSjtaWmkbNCG1BcnRZhegdYhUltHjDOgIWtMGC+dFbcF7vHp75lTCJgJtjAYeBQPBbBc5y6wjRKY6Q8cOvCe0ER/AtQ5HhUg0uwKPUtGGKd5r2fwwpPUSpU3V6D7Zona+WXrmuzixQLPzriRCBFpw3vpaNRFSj6VKxHa90xmqjfl8arteotZE3YuDYGvcSwUSS5DGtY7KO1qd4r0BfSILeFUkCjHCTCFWFRpmtLEtmaMR63sV1eGrZfzIE9oZzjlq5/FaoWKZaVYWp0SmVD5S+4rYCsGLZXmJVXrhzHfzNIQQkeAITUC9Q6pI0JYggbadMa7H1sYgCqa7BfGBJk7wlenrBkGiZ0krlAapwVUVsfbEmZohUQshOpCuv20nOG6fTht42pxMqesarWywJW1S+nIkgU7F/ZeiUC0C3qUUFycwGVVSFGzxUk2RKWlXuWDXUGs+7L3HV5K2L8dSA8VSuFWVtp0RgyfGFjSwMK6oqpxG3KXSQ8p+cVJSSKU80PyYsqNalD6UiNPcpCq9z+z7fhPsnDwRc9TOLp6ET76rFjwrkoy5UzTvmo9czB/Qz9wKsX9EF2nLETDJBkZWOMK2Z9vay2lraV/6cNtQbhukki3HdBlK3X3p8L2esSXl+8676gzSvDald1xXumX2fyznC/13Yc8fse1A5xqyCykyrfP3PuOpMyILKJRBipQGVqKc2PuI0SIZefedkhXW62/Sf7VO0lb2WQYVO2J+rnIJXBmXUNLD8xrXGHugYTKj5hBXTbxhnppLjbxLH7kMinQiJckeSYazHbXt/Wkeiys80WHLWkCMvKunLbp0tzydYmvLkYx877q1KFtulj4nR42ZX9t2TyVG1+1IXB5o7ipl8dv7y+Buhop0jm+7XYhy2jGlP4M1ggSScUk2OjUVQKamLBm07Qph0/bbdJ3D8nHZHChgU16CUeb1SPe6UwRFEpKfs6XSO9JO/sS0LmMGN5NXFrVzkTMglkFml97d3YV729kxXL1irEqgCROiVkRGVNiuMOTMhAxCZSAzplXlzDiyAEdPkPZlbfrTnBBNb02wd9ui0XP14WN88O8+wtrBL3DFWQfZs3gIF08gBKJExMFktofrju1ltV0CsV2TolPG4qicNc2vRBA/ZXEhUo8EFzy1q8ygyxmUPtkQIeIlsm/lAPs2z6HZ2MWJVtEATWhoY0torc9cE1qOtsv836tnjGUP33ypUMej+DhNgAaMqhOMZJ3l0ZR/OXQ+N928zgcnkW+594Xc64LdrFS5z0T3Dqx0zSY6Qgcuqaa5julbsf86Aw+sDKU33diStqBTT1jmV5INAWMmimLrCQjBIWppSWZ+yRxoqGrjreiV3CbPseyGXt55x4+a1kOqerZ/zWArsiQ/S9YXkdhloEqnPxN3oqnEAMBXMBo7prPItImEyqRP29oAFkZ5Gpy9cwfNdJPRqOYe5+2bszezN2yxzTOfk5U22XImY0NIm3FIbmORX6BlUov0AB16GZvq6KoB8s5iKaM1ieKQZXy0dYmYo2I2awp0qpXmkc7P+tzkZMr4zWPq22Sq5IbeTqz/SIySmvqagxeTnRQlgveMl5ZYXF7G1Y4jxw5y4OaDnFg9webmlPWNCeecs58dO1dYWz3CkaNHCW1kOptRecfa+hrTyYTx2KLvvhIQz65du9h79h6aJnDkyDFOHD/O2sYEX1WIa2h1xmi8iIhy0y3XMRpX3HroOAcOHKTywv69uxAi9Xg3o9ESzlWcvW8nm+uO6ayx9yOrhNiwuTlhceEm2tBy7nn78T6wuDhm3/7diBNWdy0znUyYTtY4cmSVWTPDi6euHeuTE4yqMYePnmBtbQ3vHegIJyM+97lrucc9LmD37t1sbKxzy60HOHr0GDt3rFh54EQ5euwYQk3tx7Szw+zYsZO1o8cYLy4S28jOHbtZWt7FdGNCs7EJGWAg4BQCsWR2h2RdO6l6NlHolQjLXLasadaARssYi+o7O05AcVY6kkqkLLMt50Haqs9lPg7pClUk9f2yWk6SSXFGU+0WkMZbsAdo3YzobY6tiXbaqMerAYLOdimuxKM42hhsM4zUU7RBgQoXHRIbvKtSPySbu7ZprD9XyvJwKkQCrU5RGqjGiLfG0UK0853dp6pqfD1GZEQIM8R78u6iQQMhtOSSNbRBnWWIOwxMCtJS11Z+F9OxQgVqYFTrbAdq7zxOI7UXAg6NHtv0wSOxppnMUO+oXU2ljqCOIA71LaR1FVIZl8aUVa2KRgEZlcb0USM+9RyMQVH1tlmKG6dSXrGgXEp08ZVD4wyoqWUB74R6ZQWdNSwtnEUksLZ+lBhmiLb4bJcmHkGUyjsqamICFz2CxhmusvcfxJ7H+zG1gzibIrbTUjGkQgh45+zcEBCtaNvIRthEvKOdTPBjT3QV65OGGKYGcLmqA9Ncg0eYGcpHrBpr7K2eynkUK982bKKiXqgRibSxTQEqGFUebRXxzoIfUaCNKFOcTJFYExrrjYfPPmKwyoHW4UY1TTOhorXdPpVUqSa2JuIMJ1/1jCfbQjtnPNg22ZZ55HKPFulKwZzP6KRZSgpoMMVl9oIkJ6xn/QTIWjOXfoToDKVNQtOJpD2IEqoXFKk9vraobN7SvG0Dm611wV9YqAkiNBqp1RwyMxiT8a2df5xLNLIjlW09MAS2D47Y/+eKFuycnDlV/iaZ7fkedmEv2jVqTDo+xC7NVXvnd9kn9p8c1c5jkWS4bvVpVbqjvOscNZITljMjLEDRRTyKU9ibl/6/879rtkxP8f12misj3AJm2ZNkh5zCwGX+MohhT17WWDZIS9o/GejQco0MOlpVSoJINalX6a6uZOc8KeP+xG7JcLr7AE82DV6s/0fuulCa0RajN+9ekZyZZNxGEbqmsrarQ14nUpp59AzT/G8KT/dT9UPIfA459TbzYxADmkUcPoEIW99BBs5Kea701nruG5SaqibXO9WT57F0oJemHV9cPzNOXUlbFDrnK19LUVsHIkivaZ2UDITsPNAbd0/mbFkylg3SGfgZ7BJNsFB6DyE15vWFL+wGOetOskOmhbWL75qzGOw9hOJG5L58klxE0WjK3mUZrliab2qZbDqZnFVkYHXmmjSu3Ncg5n4b2Xu1McTQJB3g0y6GucE85MxTETMy6OmLvAOdZokquQTNHjTEiIaYghSZl2ORM64PFERzmLdnfJ6ZtDlZZW16lAW/TGDE5uY6EKl8jVZLgEK0krBWzOEvGS3iUqZLLKBGnjYhNd1PoJR9lvPGunfmgUY91x86wh/9xfvw04N8075V9u84hNN1rN9I3klrmRuOnc+htbOY4Gy9Vpb1NPJVCfYgSl0JO5YqRh5EHFVthrs4Z46jOmJQWhWIjj07jnPR7BCrs3M5Pl1i1ra0oUnZTpZ2H9oIUtG4PfzdNSPwykMvhTHHaasWqVpkCuiMe46uZ8fCOlcfOJfrjgb+9tNTjq6fywPuuZ+zFq0xqkRHdJBaWdjMFMEQAQf9HZ5I0FRMfVP6LJ+wUN+TWaa7ckpUOjKVNGb9Yk1WY6+vB+TOlZZ1lLRk5jPtoILcb6//WX63OZTQ5cImGDqJ7gw+5TNyplwJkgnknS2LkZJuYqU3KegY7XmiKksLFYtju3YbwHtHXaXd0RwFaPYJsH/gFfchun7poMkrl7Md023PfJJe8CY3Wc/2TwSXnfpkF/bsvNzQOZPxr12nZPK6rEO6+2W5mfVcZ4kmOZrXVwzdWuvbOGVZaBcnVUVTrWcEGm2MDWJERaxnX1WzsLxEm6L3QRzHNtaZzDY4eOhWPv8v17C+scnuXTs466wdHDx4gCNHjrK4uEQMwokTG7RtZHNjwqiuGe1Y4NDBW5jNpiwsjdi9ewVfB/7xnz/OsWPHmWzOEGouv+w+HD++zsbmBjEozq8iLjCdbuArx64duxmPxjjnmc6UhTHc54qLiBGuve4IRw4FbrrpGpaWx4xGFdNpw2i0k9FoF8ePTjhr715WTwREam49cJCrv/gFmrZJgD8cO3qUzY11duxa5h4X3oOqGrG+NuVYs47guegeFxJiy2wWcOIZjXaze/cKN99yI+vr6zjxLCyMueFLXyLGyP595+JkzIFbj3Hg4BF27VzmvPPOpQ0zZkcOsrKyk4XFRfyoYnHXIlFamsmMPbv2sbmxyWRtwxpBZ/tXm25plNIbY3Tj5y1+hCQb0fnUyzXbF6ZPclAphEAp0c8BDwww6DZQ8BYYNOFX1rBLoHlXKnJm0rgdW0NlqQjJ341REOetusRbtmiFFCAjByHUBaitlDVMW8uSilYyGxG8GyGihGBNuWOYEbQ1QEADkmwlUAOaYsUojsFXpttDoKo9tYKrBK0cszDD0yLeoxLsXjrCEaiqhqZt8b4GVxPaTWIzpSWHIpUQa7TxVCnwLB6CGIgZRJE6lctV5lR5HFVQNM4Qn6tKRmY5hmh+nY+00liAKtpnI19Tq+mKtp0ilVilCQ7fekY4pkyI2TOUYFmWarvPi5i+tc3KPKFVahmlZe1ow4wmGF5QuQq/4AhTA5atRDJYqXOwyi6VhoASW/B4lBrvPaoN1cg2EYjRwDsni6g6mjBF4pRRPbId5hJYt1CPQHwKPrUGvsZAmK4ZKBSnSFURxDMTRyRQSyBgGzF4BXEV0wjqHSEGYrBNJWpqXIg0GghuRlUtEtSllLkZUZqyC6ULiveOJlp/MUJAYwO0ONeiUXGxZjSuUCe0zcx2TgRUZ7Z74HgEwdM2kUhLFKhqB7oJukHTnp4lfdrAk/iaiG0Zqs4iaM5Zx3uLfnfAhKWzJYVa0AAzEqDvzGoHDKLFWbBswiTQVAq0IwKVd4ycw7lslIF3ZmxbKhvUlaDqTBAkYzAGZdK0BO8Y1VXZUlhT47Hcj8oWqtIXf/kvKyPpDB+j7WVW1jC1ewEGZkHnmGXDstygXNf1Pp+vs05f5GtJd6AWJWDOXclakjkooAeo5CyAXl8AumfuGh33vVu2AUnzwFPPIEqD6s/i6YAz3TFdaVf/mvmzXqvobCKTZyM3SZYUypH+l+U+6VjN52RrykqRsqNeXGnNznq3xnXr+70blNvlN23ryeOSE5W2YaA0Is1zl0CA3FvMpR07vHgE6/WE5t4O5tRvt/4zsBO7dVjWSrfq5vgtlfCKpi1gcyQ/GvAR6XoJdLsBkRpWSnHApGdsa7TSBpX8LnuTkoCImBr9uVwLk/qq5bWcdxpKD1H+sWmSIoMMGEpbWquNKztMDtK85fsmR05JPTvyuu2M/GwQloyuuS6ddlAfNCuXzl5hkht5HUdNW806N8fTIrmNeD5fk+GeX1BXOtQHFjugVyxDJTFXfi7Vrtw4O1JOnOkDn5q/i0Nc3vHInGc3JzNyqbTJdquwc6mfk103qKZyJqFr1U5vhc3zbHa+A1/29q5fUzp67Go2J5vsXDmPHSsXorFhY23KyC/Agk/zmtZRTIaUestqcBbn9lGtcSXQLbBQGDDGBDI4IORNLRSPMouRz954C3/5f/4vbBzm8r2H2b/jEMJxlKkBLWLGzeHV3Vx3bCez1jFyVdqBJa0uh6WRO0flhcV6xM4dY8RrWX/GS7Z2Z00uY7BznEzZv+M6Dqzu5ebVc5hSEdqW2ApNzCWpYqVXVc1U9vGpG5dZXLiV+5+/wMLoMCJrqFZogNi07Fs6zMp5LQuHIl9aV/7xas+xNccDLt3DBbsXWXQ9CE4snT4Hr3KpWBKmxGSxqJNU2mZCQpNy7+Ae7MO0FsVZfZMdrlAAJtM3XkHFm5oPGXpNGVjJViod5AXUM6dHnUsgpKrtnJNstQJuqLkbUXK+sXbAc3rADjLJdkf/ieZNGxetuXkBUZL8cBiIEoOARHxlO/ZF1RLRtnIKSf3IIuqFOl1HhLKDoKrNM9pbzmc0BUg5JzalXcAsy9XyGKVcLVvAnf3RqSEtsn9OhyZZbzsmdbaL9HVYOcveUTkmrbuSFSudnutAss7mjLRYow+Pqz3VaIRUFY3CettQjzybGxusra2zvrFhDrB3XHzRZVxzzXXcesshbr75Znbu2mFrMSpn793Hrp07mc1m7DlrNwcPHOLY8SNMJhssLi1YYKmtmU08i6P9hKVFRi5wyy0385nP/Av3uOge1NUi6pUQIhtrLeIWuejCe3Ds6Am8jJlsNMw21UpvCezbt4dLL92LczU7dy6xc8ce2jYya2aMxwssLS7ThsCBA7ey96xdiI9sbq5zYlUZj8eIRHbt2sPS4g5WT6yxunqco0fXWFlZZta0LC8vMhp7NibrLC8tMh4tEELg+PHj3HzrTdRVzXg85siRw4zHI/btO4fQRo4dP8Z0tsbZe/dSySJHj0xZP3EL+887i6ZtWFkRNjc3aUOgriqm7RS8IGPPzpU91MuLTNfWaCYzK/Ur5e0yx8iGWSb+6tkexR/JJRPab3qvKYtJU++rrsVC1ytKitEdk/PisouS7Le83s50O7qqRkSpCBHEqSVYKEisEFlA45SKQM7yFgxgEvX46K0/Do5KRigB76uSkei80oRZAodmqJ+lLJYxbatEqaic4nSDCs9YlnBNpG02cTjUVYhCGwNeHTQNdQ2jukY17fEuFW3QpE8VVxl/xNZ42VMhMWVrkRpqR49zNR4/By6iLapWBhdxBFHGEvDaWqa6VExbs+la3aAWZ6Vg3uOkRaOB1YplVXm/SBus72NEbKfFGJmFFnU1isenQIZEbyWBbkqUKYrgNKLSWMNxrZlNlEo8VC3RNURmNDQ0WtMcmuKjMztJAKJlgUtEZMQsztC6gtQ30kkNzrJDrO3PzGJNcYq6EaJpOwdxBsJ7pWkibbDd9iq3jGMM2hDjFPERjYEYWmrvoVWitx5hOKXVlii2viTCyC/gXcUsR600EglIFVmohTBrrQqndaA1GpVKFkyfx5B6atWERqxkUhx4cLXDtRUjv5PQRLS2HepAqVwNOiLGYP2uGpDaMllDsiddhDi1MVWjFbvu6fDR6TJc01i6lkWd1OokPVB1m1Frcqi8d52jrl1fjZTwZCnG0SLNzgveWa1vbjjuq4QTJ+Ni5IW8I4P3wsgng893u+y5JNhyE7ax8+CUECzTx6kjUhXgJpftdWHfXmqoKqGf86kn+1WKwylzKj/7ZFqOstTmmL7ImWKprCkbjDFd0eUGbZRonmXgd+PJAF6H+5gUzwa39hx6mTvEnj20wQy77KzK3JHd7/3nzgbR1rko/+l58pqESd49TWTL8VuMpHxmWh/ZButTybAgBYR1/vm6Z1C6nT768FkXxSmllgl56hxUE3hWTJR3erBny+s5z0O//1H5/e5EkksNpXt7ySnoJj+bmlJeXi5VyjsulN5MiaflJLeCZCwjBQOZM7ihx4uU+yl0TfPL/JvTYfaQpCZ4nfFS1lDqZxDTMdbnwsY9Z9xk0IrOCNLeO89ZgQkj6py9AqKXEZfVVvq6JMM/G1WQUpkzP0iO+HVZBPkB+n2ztvW7ohvj3CvNDkjKxMpt9gr4XOYwRzF0y3Xtu+xM2qNZU0yHdu+67GakKVfGHOOcJZeFUcjTK9Z7o+/wBE3OZ+zv0meRQ0nnR7VeBR18nMuatYzZOSH3bIy5D0IqQSlZBaRssjy63pz2dxM80+nY8X9kXO+m8ucQ2k3adg3nIhubx2jbkN5ra0EZCYxGO1DxCVivGY8WLaMiYlhz7OSyokgCnQIKIQVzNBKAjbblc1+6mb/60MeYHTvEvfee4B67j+HlcMqUIAFHFZO4k2vX7sHRzWXA2z5AYmVnFpRyRG+ZQaO6Zmm0wa4VA6g0tuTt1wnB+N1ZpnXlnO2cgmNptMG5O2/ghmNncbRxSPRI6uHgpMK7iK8rqspKAVq/j3+6ydbZ/c8TFiTQ+nXqUWTWzggaWKgPcO99m6wsrHPDauTmg5FJM2P9ov1ctn+BHaPKIv6pr5jZHTZfognUyY3HM8CSwHpEUglwp7ds+nO5q1HJSuvpq1yRbwlDirQYf+edg8R4qQio0utIkpna50v7zall+0Eux5ScwJldUjphncfW6QnDk7SAJQIZQ+uOzfo16es8vJxl46oAsePvKm2xrmg35p5NYI5TJ+Mz8LW1bPBMJicmSzULxmylzI0/6b/S9NPkWeyVLJdm3gV0Uk6iEtIGG1nedXK+7IIlObupJx9jAsbK7nRJD+W1IzmLLY9ecFXNaGEJP66IEphOG44cP8rq2jrTmTnGefc28crq5iajegd79+6hbWccOnyQm286yMqOZXbsWOLmW78EOOpqBDiapmV9fZXxwsh2sGsb1jaO0+qU8XjE8vKY5WXPWXt2cvjwUcbjETG2qAacFy44az/ilFmzwdLKiOXFZSaTKYo1/a7GnlsP3UobYHFhEXUtTXsCBHbuGlOPlHPP3cWunbtYWzuboC2f+MTHOXLkGLNZy65dO1lcrNE4YfdZi+zds5O6vicHDh4wB9/B+sYJgo5ZXlrmwIGjjEcLNM2MyWTK4uKKObTqGI/GHD58hBMn1llZXqZtI44Fjh2dsnPnmF27dlJ5x/GjJ6hHFUcOrSI6IsYNNjbXQYWq8jjxtLFleWkRqsjSnmVCs0CYhgS4N4R2SoxWeRFjypZ0Wno+gUIgBSltzcay/owxsz1Vlp+asGrTupNkmGWZoraIcvVY+kSKbXkm08LiTmYBYhPwKYAXIzityCETLxBik0DfgKIpM8b8Wp92SlMFbcyfs24+rQUHEELb4EbWE1FbpdKaFhKbVrhgPTSjWKaVIxrwEiF6K1e34F0qp8ThoieKTzsJC7Yj2Yg2pB3LEAtKiVU4uTQq9dEAm9gYkCKOytUWuMjZvrE2WyHYc3cVNPbj1Sdgx/wzQteWJ6pQu5qgkdaButrK6oLpNJWAOuvNJCp4qWjVdl1zztOGES0NIo3p4WhlfuoiIZWaVjiUBUQta8+ph+iKnhIdmx8nDd4rVdqsxLSOJ9Las6oFVM1C8fgYkThDqmT3q7dqDhcRqQzIchZ4b50BfxJneJf64Hln5YXR7OdKXGqfsIAXA/5iFWijWg8qCSgtVlbpaVUJmg26ChVHSFmI3ldWWi3Wt6nyDg0NIba4akzbemJjumdU1WzGGU5qHA3Wo9cRbBtGKlfhPDRtwyyknl9YByrnQXVELuE+HTpt4ClqsAg5mFMgpGXZM0ZwqTmZOQg5kq04QkigR7SJsubgaimJCW2vXeq1lAzUrjGqCaaSNeDbBFZl1xm6lE+zRjxYup5PDbCiEp0joBYZ16zsk2GYDcp0Cdv9tZvEfO0sFjOul4VpdlxtJJ3hV/zpdP0shHFp6/h8pLfr50yHfsaNOZB5bFoi/OUY1WTpdanYUsArO7ZV2JhGmqCEVi29sQbrsK/UlS9OdWctdnMPOQxuk2PNVh25R1KJbGpyykuks1MkqkLbD2ikvjwWFTa4x6Xoe0wlNfNk5Tjl1YmJhPn7iKVIqilTgeTIdM507nVjxncGHJObGrtdXqQHNClaHPlcc2XvIZnJZ7jCBDqPQnLJQgJMcsQYSaUfKVKVny89Wx9QhQ5UyDUcGXzRLTtRlkgqpJ3NLBNIy5oBcslJbxqzOaPSm9+0NPuJh5HuXWcnyH6NyTjKwC+99yTde7U0pO69Z/An7dCQQcr8VJK2fs58mEGQMoZe5DpvZeyQVKt+G2tF53/vOxblmgVZk34wsjs931dtO3Itz0nZ7a04z5JNvnQd7f8CuXFj/0Yae0BYvrKWmTROKkZpHyhKBgdi6IaazNBoW39bFoPg1KUoX+z4TLJD3htkqgHKUxmiph26+5D7vPzZKk3M4ZMEpJ35pM0R1MHm5s2sbUzZ3DjK0tICzi125dlhinMTQpywOVshygiJSj1axrmzWfBLBixl0EmzbklvW0135L5dUSOr0yn/fP3NfOgTn6Y5doR7772Zi3ffSu1WCWyCYoEj5yCOObZ+Abce30eI1kjZlpBFBMU5VDy+9ow8uMr+XRpBXUPAWU8DTWWQufTPV+CqJHcjQsu5Ow5y8Y6DHG0vYgPrLbGQxuKdIJWnEo/3oFRMZT+fu3VERc199rWIbxFacIq6gMbA0niVi6vArsWW61c3OLoa+OyXRqxNdnCP/YvsXRqxNLbgUZQUEFPMWUutTorqy7wu/bVnRqLmtIK+LMu6sdhZ9GwaY5vU/sN4oldW1efjDraxTztbMOvl/JfrAJtke+WzslhL8YV0jQ6gKK0J0hBESaV03cNKfiQ1aVuaVxf+lXK42TlSzpNkWZielvnvsthJ/Jt3x7s7kCClUt+S07R7h+WlF02SdIX1L+1SEaWnl/tysfuH3qd9jddlMdmsx9iVf4v0x5MynZXSexFNPXpIYxGPOqjHI/xoTAROrB5nY7LGdDJjfWODppkxnU2ofMX62hQnnlkzI4SW8ajh+Ko1Ft939rkcPHCAE8c3aGYzlpbHTDbXCKNFKj9CVVlcGjMe14zqERubViJ24vgqO3fu4KyzzsJ7Z7s5oXgv1HXFeGGR9fU1fKU4qWhmLU3T0o5anFecr9hYn9GEFj+qqKiZTmBxvJvxeMz6+iqzCtrQcuLEcTY212lnMz7xyU9y4sQagqOuxxw7us7aqsN7x3g8pqpqqqpiNB5ZWbmLqNa0bSAEaJqW2fQEyysL7D/nbAPBogVoFGXPnrMQ8ezeuZsQA+PxiIXxAiLCxuYmk0nL7l072LV7NyJw6OBBxAmTySZ1PWLHjp0cOHCIWbPBqPaM6po9e/YiKowWxoxGI0SXmG5MmUw2kBCgiRDFmkmXtgVJXacKki6Arsm/68JCGYDKIqafORdTtnr29brgsCvrPqrMbwR0BtLqsTWaMKOqR9YTDEcrU6ILWL+zYDwTHCG01stLatRFokS8TvFalex6qazESWMqY1SPugp11m7CSfayDVhqY0uIDq8jWk0+mHM4GtCAi4LzznY+FU+MnuCEWpxdO2B9htAEXhngL0GI0dGmVFKznL1V7ziljTML3Fbu/0/dnzxbkmTpndjvqKqZ3eG95++5e3hEDqisQhaqCr1oAQF0U3pBaeGKItzxv6VwReGiIRQ0StBooIuorCGHiIwIn950BzPT4XBxVM2uR2Z1B1pAMNJEfHx3sEGHc77zfd8xL2UBT6nxW8GHgKZsm1PzD1JFiVAKIXiiJhaerswos1kwFOssFzOoBJx0Nbau1jpOUUk4H0lTQvwW9YVMomSPakAoZHV0LlDUCCbO15jfOQNUtEPyjEgi5WzxpwiFzuLzYvGOE+tCaIVtD8ETVYhFcWpG5g5jADonFJ0ouRB8j6OrQFIlkORs3d8wlpkVUr3ZAtTupoIBRM45Ah5XOhwecwATVCOx1HVZiu3VYt3lcjGijiPU9ToZm8opE2qddBWc9syz0PuemI84vD2nbKXjMc1kSpUVmgZeXIWHNBuQ2hXUz7gsULqK7QhakhF+cvodwsg/dHxv4KlJULxUBpFUecdl8iJ8kpQsCwrW+jNlM7BzztN3jr5zdEHwYiyqziteqKBUNTCvydoSbfApw2Gt8rglsWy/ijoz8MaM9opasLiWzNrVycXfl9Pn8j8tObrQuLefldV3YM1pW6KmICtqvFyX3baLmuYa9LlaWcpq0pFykTza4lwHoBo9cWFnLPdc13NbDgt2pjkzRq0TGlLl94Rg57Su+RbxXl7r2lLTLrRUXy+DooRLIZx1CYDWFr0Fp1PMTLHUjicQgmMYHEGM9nmB+31nDNnnSvWgsjHm62NULn3CUi6coy0s3ju8eEJwdEqVe6jdt/r8pSZazZS4ifwWoIIG8LVgr/67jrWW8BX97j3/AR4VORGMdbBMHbkQWtb50jrqNA+0+sMVRJIVR2gIzMLCWQLpdS7Wd1+M11YrrbKa+vqWJTVzS1qw044KZrROW4h5l/j23oZjtfO4kJW2RLoF7OZ7Ull07tM14BLE5uL87e7ZZ4lUPw6hVrPqWKgMECeuJqNaZW3yycIsFUi6rPS1tXQBp7TNxfrncl+boexF0pDzMl5trbDNW4uxvBpT6RMfNqn3qgJki4yjjX1dpXMLA6yutyYBaqPIzqmJIdupAxeeLfY+alck1SblktpuuADZ1tTafenT8dSS2vZZdR1cULHvJqCyJLCixrCx7iJrQUB+d9H5wR4xPhNLZM4d6FjPfQDNFLJR4TVT8kycR9L5iO92BLdFgCnskCHU1re2/qPNO8jYQr0MJnsikxWejmf+7d/9in/z7/+G6f4b/vTlEz+7fY9378iaUSkEJzhn7aGP6ZbfPP2Ex7i3RMNXR0bv6jO1lrtd11ni5xw+VLNx5yihylzF9mwVCK4jEGqRos3BzHZz4I9ff8Pb9AXfHF6QiwEU3ve2X9cCVueVVISinnN5yX/4OpFT5E8+O9PJjGME1PwztNC5E59df8PVEPnqMPJh6nn7sec4C1+8yPyju8D11tMF1p1Zl1Wh6WZtfWtokL2KFQWyeXbZFKPNpuZvuKR0uq4PcjEHtKwMoMbQdbTyysUcXxb6CrJX8Gtd4mT5eTvdArX77rruqYJc5oU1Dm6naV2r6s8amNGk/2gNFn5fZFrn5AIk13hvCf7LshfYnr1e38qY+MHbwwB1pax70gKSN5MSZJE/F/QCWCwrYGRGqMZwa3Hn8hu0wsMFxPfJ/9tfL9bPixjL9sO8nF8ppjLQBk6JkMUkdV3f0e82nM4ncML94z3TPPP4+IhqZo6JaRxxzjHPhWM8k5PWDk4eHwbO00TfWZIozvGjH/+Y8/nMOJ55fjxQcqGkyGbjUTVmUpwjXR/xvqPrevquZ5omjqejdZrKhaurG2KceXx8QHVP8D3H49GknRqY40To7DNTjjw/H3g6WDzqfc/V9pbNZmC77XBhy263MQDUCY8Pj3zz9be8f/dA3/WEvmN/tUMQ+r4HUfquY5onxulICKH6yEAXTAJjnbdttjvnSGlmmkZizATvuLm5ZppGRBznyVhP3kPKEyEEXr16QYyRaYp8eP/RkmXn+PjxI8PQc3tnANcwbIANjw8fudpf88unL9nttlzf7NlseoLfUJyH4Oj3W+JYcEVI84mUZgMoxNQiqi2Od3XS6ydj6btNh9zFQmGjbLVMaBHUGjNeAlA/bODpw+M96GwyyY1CCIgv9LXjmEnVK1BcAA246g2EzhYziTPeUylkyQiF3hmoUdTZ/9dkzEO1lZmX/aW4ag6uM0mLGdg7jyap8SRQlOArkyoLxZvuukhC3UxwCpOSUu2uWZSclexkKSgbUYTFS8mIAmWRmhfF/CUpdn0OHAYcmTh+srGpVCCl+kLlXOMFY3t56aB4Y93l6lOvVL8mi++teYHJ8KIWCt2yxzgEzY5emoVOQbzFI6VgIBgdjgEnAdyMajJ2kDOwpuRM0Nr5L5n3mqga18FpZaUFxAsxz4CBguqKsdPMzQrvAl48pImYR1IRhB7ve4J9AkUdWSBKwonHl9rlr4h16c1q4JurjZ1SsNjXWf7idWUzCq1ph+A0GdtOC6qOrKYYAAN+c8u2ug3O9xYr1jivpIz3Nh9jFkQD4j2+M5AozolUMqUknAs4UbKYjNSpIxcDI135ffv77x7/SdYWQqWXX4BC/5B3z6U8RFXBV3meg673DJ2n89TJYaDC0kqxxlbidKF+t9/bMtUqMZZQUQOplohZKJJ1rbi1/1vPd6V4r8nTP3zYAL+ggF98hrYgsp3pwkow/ylBKwazTmpb0NeEevEzkcuTtj/KJ0EDtKKDBZTy6c++k1iCJRa5CLkIKZse1znIyYA+5xulrt7vBvItAWl97jUAKu3/W8ACF63nbXlMBUNpAe89OWWOU2TOLBW0UIzsf9WZL4jdKfeJ39ZFHFvvtdTODLUrWo2GTU9emObEONv3KwWcEnxh5x0b7wneLdJFa9/OksA3gc5yLxuoRJOOXnjWlAuwSn/42nRYR7jDODsqJhPR33mFjV+pY3ox8m45+hIs1L/XQalaqlSP9cX1uLw/i0eWq2blTtaX63c8zCpI1ObuImpTWbp8t3+v51Wrcdqs/7UmZvUJNzBtAX0aYNJyOkPWF7/ci+s20KKNRgvMRcoCzGilYzVgbentttyTdY0oLcmqn70QAmjJoL3eXa6ll09oAT71ExkMSwJMTTjUAve23jSgEGjdU+TiyxvbzYmh0Zb71GCzPmDn6vXKyu+0e7uOA6seSc1GSz3XRlRuo8xVZqFFMgqob8DQugY1qHK5l/UmNLWPra0OdHWAs7+4BaRrnb0M1NQK6H0q+fwhH6f4zEZ6NCVymdjuOpxkVCdScaTi0TwC1rK7lBGXHaHfI65wGh9J6tiEgZRnlITU9TzlZLKWTghASonHceTf/82X/L//3V9xfn7g59cf+Ee3bwnuI22seHFLISrLFe9OX/DN+ZqkHeoLyQudGriEt4qed/aGVrzyg+A7b8WtYglh25OdAxcEF5x5PrR9W6zw8Pr2np9NH5j0Fc9xAAdBAkJtgYzJ94NYC+OShaf5lr/8cubh/MxfvJkYOOFlItduPYrD5xM3fWbzcuTmrNynzOH4Bb+abng4Rr64C/z4rufaHNERrWuRrOupAU8r8tRAnMUImrYW1uAZK/40GRVIZRZTizJlXQO0vW4F8C+/m4J1A/xuQaSue+2ElnVG671d1pEGX1eAo87Fy0+ztTAvNgFaz5e67opWGaK9uIJG7c7oxTSW2hxhNW2wtbbu0xWMkeV6Wd55gUH9wFPWdhhY24ofWmPWFse5BYBfg/hVsGL3u+0HIha+27MXGpOp1PGzsLUvwChorGNFW8ekei6ltC6xAtXQ3zmTmvjOg3ckTPo6uUzOM4+nZ9zkeHp6Yp4j79+/p+8GECHGyNAPDN2ONI9st4HW9WyOib7r6fvA8XgClJgim23P7Ytb5mnm4eGe4+lA0UwIQu/M2ylrpuv8ssbP88z5dGSOBmodnk+IQMoz9/cjd3e3y94cvOf0eKLrHM7DZhgYho0BfsW8eE7nI0+HB168uCbGyOPzR4Y+MI6ROCu/+fVXeOfph46u73DOAPY5TghCjsoUI13oKVnpwpa+7xmnEeeUfujp+1tA+PjxA6fzmeA9L1/eGRssWQfvVGYAxskxaM/5PJFyYr/b0XUdIQxc31xxf3/Pdrtls9lwPo+8ffeBF1NkGHpOpzOPjyeOh4j3QoqFeY6E4EE8IXR0nXDtr9nsrwnikXOByZHnWItWLYagjjvqOuJqAbJ8Mifb0cack0sm0wVAJcYE1xqDf6f294M87g8Hts6hOTGnExICfR/Ybwe86xDN4DLJn43VpL1JxkqiSCCWjAQDRJJWIADBrN+xphqajYChIEURD6VKQsVBwCO1uKlakGKBanC+slSq0sMpOJOjGYXKmEPiFckFyRmPkkq0+FisMxoVZNVsEjdbTDJUg3pTRTgSDi2u7h2Zot5UPLmgZIpk8yTUjjL3+JDxcoJQkCxosY57Qo8WT3BCxsCN5LLt5c7ji+C1J6cOUUd2xnLqtOBIKBEnxvQRkZr3JxBXlTPUcy5IsLKOLLUM89xKRGadKES8dDj1eLX3oNkUOQ5EPKna9KNQopBzB8GR6vMwMkqPOI/zkSLOAD0fyaVQJFnRTk1mkTXSdaFaRWR7VBQD6AU0nS2exwMdJXlwnixKECgpmUpAkvlyFlc9VD2qaixKKRRmplpM2IQBysysJyMTidIJTHkC3y2z2Klt3d45UvJQekQcqSSQjDfZEK3lm3zPXfg/CXgqFxWpSyqwmd7KGtC0k67UngJ0zuMdeC8EJ3TOKoyittmaieXlJ4slItq6ma0LX1abuCWbvtY215ZUVSCBSyBhTdfWMPDyL/aPSzbHpz+pYEyVd0jNVES0AnDURfTy9QbWeKdLgGc5VE0UqeyHC3Pc9TzkE9mIIlX6V6+1cJG06vr/9Xl8wmjAAKA5GvikmNyt1PaVvRdiLNaBIVBlCet1JIU5JkSEITg8UJxjnsyzRULzf7EQM2fHOBdiSsRslawQIOfMnJWobjnvkqFMCYqy3wxWOa9PO+Or0Vvd3BogQV1YSmGOERS6vjIbijJnJamri48BRFELpIL09n6nUhPuCrDUz13utV6AIzQMbE2Gi/7uvf6D6GxXT7GBQ22ZKMuYboBEXViXSzItb1ts1zlQ31JaNbaOnQY48CkTTGSVGVCfzRJ+1/NZAShZ5k3RC4ZKvRBXwcJcuyDl0uCgUlltRgFuio6iZWkv3Sr+RvmtF7HM/5WVtJx7vWxXfWpqOMWivVzYmI2F0DpR6bIu5upltEhUmkcUWJXKGUTmRVaQrgZjVt2mLTRLskoFnrTJaitI09Y9u1LrolK0BYcXSUhDUhtbq97g9j6pn+9aNiqubpYV6KssizX5aw0hVtZXad+xnI91ZzHiha73rqx7SDs3rVUacbqKui8T6WUerv9lnZ9WUaTWsfRJstqeS73YH3qwuxxa6CTj/ETXzziJpBzo9JYggfM0gh5J6R05n4j5xGZzSygCeUuOJ7vn3ZbzdEKYMZPKRNLCdtiR0onODXz78ZF/84sv+Ztf3XN+fuSPrj/ys1dfMvi3FEwiL96KAM4pIj1P0xt+ffqCp2mwMS2uBl++ertYpRdvstPOW3fNrqroWmHGNrhSAaqe0A9WgXQW4Ng0ME+N4M789PV7Pkw/JZ1vKDVIErVCRi6YN8LFJqvS85he8K9/+Zrj+cT/4fMzTt7bWFcL+hTIZWTwyh9d/z2fu4mvDs98ff4j3sUrng6Oj889//hHe17vgwWIGPDpoMrOMAAbm2+LA14pC734U1EcdYjXAgu2tjY/Ja2fW5wiFXizny2Z4CKNg4t5cZkwsq49qD1DzesLq1jGZsnFnrbUoNo51xM2pkJNUOpniKzXv8Zzn5xKZS3Vtexyq6GJMepvroZdLX76bn2ntGjKpJk/9ENFKSWbOXq1ilDcWlSpoFCpcYY0ZrLWNV0AWsfQyAK3VcCveTc1oEDXTXO9T6V2NFUQKRd7dMGAe29sdm8V/qywudqTSoQyA8rT0xMlKcfTGRGI88zpfCbFzHg+EGNis93SBcdpOtOFjq4LQKYUZRc2a1Kkha4P9EOocWXh5uaK6+sdp9MzSGYcZ26uX/Lh40dymgBh6AdKKXTdhjgrqo67u1ecTiPnaWSeMl0XeHh84vpqy267sVg3QC4z05x4fj5QsuJDYDyP3N3dkfLIdtMjCH3Ych5HQtiQU+bd2w+cThOb7cAw7MglM54TMZ5RlM0wkOKZ0HtevXrJ09OBYTBpW8mJKc48PT2y3Q14Cdzc3DEMG969f8u7d2/ZX71gPJ8qs8BYWB8+fmDoN3ShZ54z83Qw4Kk7gSjTPJEeJ0rJ3N7eEGMh50ScJ+Y5ESPEaeLqasc0Rs7nkS4E+mFD8InNNqDlgXyd6buBpIluN7C52kGG8/HEPI60uWkeklqFHRYLteKOCEvetjD66vyWWnhqs7SmURdx9A8/hs5FGTWQ54BPIK6Q5kRJE2Fj8zY4cG6PksglgyQ0CNmZNGoWY5d4Mko1yVaHQSBK54N1US0FY+ZAIRjDSCwXdNojxeF9zXdzLZRmk9QhVIaiFd+12DqfXc27sgCVSaMgJERnozgRbO0tEecLzQuwc47gHSVX4AQoGvCugzLZMy7JGERqa5wLvXXBK4WgJgHUQO285mvxO9Udx7TqMUUbVcViuSIBcqgG5GYNk8pssW3NAyRYAdh2QgclgAiBwfZgsThHnBngZ50sni8Op8ayShSQQskZL52BU9KZakqT7XtF6GWDasGTiTmBdHgfUJRMMtwjZULu0OLJXkk6E+3BgU9IUroSEDEAKflosWsKdd+2jnNW+zWco5bRllhCJZB1Rnwy6aKAKwOiAdMdmLxTJZFztHvsAqX0xBxrgW8El5DgSbkjObVYLIJUYsfisVkcqfq9FTUfQCmWBxQfSZqRCvT9bx3fG3jSmgjg/ZogLIDK+svV/2sskNbRqUknWsKeK6tHhMWU0gZMY1FVFsrK6uSSdWK/3EXysVb7ZKkmtfSrLpAX61oDMy4gm4uLFVzrqicsHbScXEo5FB/8+n+XUkAaINV8XVh+1iRb/1DG0xby9T3rgtyuvxE22pWtH6/8DvAkDlXHnGaKWhJfqOa+NbwNwTSyy3OqrI6chTknzjHjEHonqPekIpxnG3i4jiAmdyvqOMfMeTK6XhZLXp1me+Y1GVjib8yAcMqOLldZhDPkK+bCHBNdCHRdR9FMTAZ+xFLI2VqnI8I0pkVGlCrDdTEZrhFzEuuO4J19x1LZXXZFezZlYW59GgpX7JtyAUB98tz+EICn3zve2nwt60u04Fz4BHhZEIn6ISXrqtW/mHuglJwR7w0U+T1MMGONFTPads3PpbJ26ncu0re6ziznopf3Wpefr8F5WUwPc51jqoXUks5lDVkTtQY+ibaxXyWA0rTZ7TbYGGvikZYsOGQBL1sg1YyxV/NsA09K1ca4i+FiPpsNJNEFfGmJaFOzfHeEta9sY7/JiJsnlrYkdnkG69rQmGriXV26VrALaSuQvabUc5TqzecWsC4hrYuWpeptBGAmiGuhAq2JrNqmtXRqchnUI+Lt/5xYi93FKOKSZbpkzuvTWHJmrVKAFuxeFhLaJ1QwcAGclCxUSSk/+GNm5nR+h58nuv4JxOPPW8bzkd3VG1KM5HTPNL0lxhNCQcoJLTMhvET8nlmFlM7M6YTmMx7H8fxk1bAeUMcp3/I//c1HfvH3T+gU+fH1PX/86ht23VuU2ej03kIbFwLeOaZ0x5fPP+Xb51vzQkDoOg94nDi8Nxq8F6EEb3uNWCOSzineFQuEcsZknOBdQDpjqTaPNBUrZogzz5FeC2/23/L5i0ee3U+IyS/rg2YDb7JasD2XTCqFqIVYhMd4w7/+25ecHpX/9k8T6j6ajD9n8wyThNeC08yrbeHVTeHV44m//fAT7g9XPB4Gvn144s//6Jafv7qidwX1ELFwwHwjKqOzrTMNWK3HUtyABQxoE1AbY7GBS/IpM3QJIXID0OVirDdQqv79ciAV6jqhJqcpoN61pYeL6kDFovUTOlGLpVY2k3loNvZUEWOjNnyrFJM9LNfYrrvNz4s1zjuppq4Arhofr9+sl+fQKtI1UPv0zv4wD/PKqXFraau6GKNBK+N/uTYwOK0yQluwvFTcFaSs96IWy4wJfrHvLnumLOGO1jV79XI0MMESVgXnuL59CU75+PjA83jmcHzCOTidRg6HE/M0E9OMqjL0HdM0czgdSQlurm85j2de3N5wt9uz31+RkhmExzQj4tjvrnAyEOMIqjw+PJknjo4cj4+M00jOib73xDhxGo9sNztubm44np/JRTiPoyW1XcBL4Dye6PqACwNXV1vO54k8Jz68O6BqgI0qPD+d2e12fP7mFQAfP37gxYuX5JwYz0dyOnN1taHvB1Lu+Pbb90znGeeVl6/uyNXo9+XdDc51VgCvsvTz+YTzyjiN7PY7UJMovbjbcz57NpstMWbiPJknri/c3d0yTQnU8+LFNeN45nB4REXMKqLboEXYbjZc3Wzpe0ecC+dzJCdhHCN9PzAn87NJ88zzw5ExZs4x8fLFC0yJYOtJniMPTwf2+x2Hs+PmxTXH81t2mx3b7ZYpntkMPUO3ZXN3hT/1jE9HNM6Ia4U0iy8a83vNP/K6brU9VxqfsSWntkDkyhwQUXLzsfkBH13nyQJjKfSlWCKliidaIRyh7zo6a/mO+IyTDhFL9oMTA5PKTC/BPI+Z8N4KCWa10iE61Hk5U1KhuJ4sSkmZwTlwpfrighQzq8gp4vvOSByVqNo5A6iMVaAE9cRsXmilZAML1C2/gmQKCZVgz0UdLhgTKeaIcxtEPEEgouSSTU5fDJzJqhQS3heCBqT6JiUE1Y6gXX2tASZZEyl6BtdZjO4yoasgk5rct0hn2IChlzifK/jSoQmUjCyYQmJSxbvB4gdxZnWhxs43uM0kxblkYkyIAx8guGJSYhVEczVmb3EHVizRgve232qphYBKYli6a6uSSsLXJikiiqTSXCTM3Lz4+v5gQ8hlgoIvHUblyGhMFDOrrvLNjEipLPeCaGeZiERKKORsxBDv1IC2okQU+gE0wBwRDWTXUSQYE9yZVLLreiYySkC8PSPJjQ0bECeUPIJ45ikSOoeTQEaZKWRJIODpvtc8+t7AU9d1tKTTEitjo3jvP0lmfK1utn9bQleTh2LBRxQhO8UrZKcEWIha6/5Y1s5zNaAoFxtyA19aMHKRNl/mx+shunoDyPqZLO9oSQr1BlZn+ODMqLThJS1YAkKog4oGZNWvcmY0jLQFuX1NCyVqRYuVj7V8qtJYjVVjW6+vrslLQgkXKfH68Z+ATmrdCGMRSjZpT7lInlfTOrXuP0HwvlKuM6SsjLEwJWHoPIojpsxhVmIjmE2J4MAHT1Z7/ay2vZQGVuSFW/TJc7lkuUwpk4ux4bw4plSY5kguSlIDmaxQ7IhZmXOpQNpaIWyHmV+u0inXguy6cGllf1xWXqSxalC+u/8t1cPF82h9Yn9Ih1SAcBnMbd7mKm2pyeBiItmSogoiN+ZKQz8taL3smnMxJ7XNi/UzzOtAlo6RKtSODCsQs0BKy2fanw4qu/Gyqlt11pjRaG7fWRkvQmNMNoZQmz/1SS9muGaiLS0xdGZwbJLOCnCqGpOpXqNDK2mh1iDUwKy2STXwSepkbcmaYvKu77KpLg93kTyCfeayMF2+uOUeTirjq0nu7NoWY9iWlDTTd5FF2mPVSSsoUK+LtuYKGJBX781CO5a6idekpwWcNUlaOFeqVZ9fz700jpRVY7QGbTboTIZNMYpDlkLwZi5dHBfr1Tom7IzWxLwVHFry3XaGRXoCS3J6aZj7h3L0msEVYjmQY6HvelJ8R0pfczzsmEqmC5nOWUXTuZ55fG9gzq5j093QhyvOcSTHmWl6BzEaK0mUp6dHno6B//jVE1+9U+Yx8sXugT95/Zb95h1SRhCluIy4ofo1JZCBx/Ezvj68ZkqhNgqxAF2ddcDxmD+k1u50YE1GfFGCM3lBzDOFCc9AFzq8czhv88U04e4T1qET66DVh8Qf337LY/4TPp6urcDhIIv5USpCT8c0GuPgPJ/N3LMI43zLv/qNVR3/xc939PItIspcTWJzKYQQET+x7+/5pz+aubue+Ju3r/j7+894f7/l/cOXfPjJFX/xJz/ibuOhWOEEJ3SeauwKzSCpAbComqq3Bpq0IFVanLOshnU9dPUjKrgsWhVxK/DdPNk+kfjVjzGPtE8HvIirvk91XjWArAZRy3tZY5xSivlvWJS9xj5SKUqwnPvlek7d64UVx1rOptKeWkOEdRWHSmuiCvj4NPIxc1T55MN+uEcr1uBqgwpaScvMZRXbaxtjuHVWWgqoLdhk/bPtZw1Egk9vRSsau1oczjmbrBWF2vTHBqKDIdBtNgybHbmDw/GJczohUZjjiBPPeJ4ZzxPilGEYEBHGcWKcMl3Y8Oazl7z+7CVaZq5fDLx//45f/foXFnuVzH6/J6bMN28fOB3ObDfmFXVz/YIPH+8BmOeJ/X7Pq5ef8fT8XJn4wjxHTucTm81Aypmr3TWIcH//kf3VnpgSqrC/2hO8kPNEf7VjCJ7TeWQzbPjyq98aw2k88uVXx7Yx8Kf/+HNUlfv7wDxPvH/3hHdnUir0Q4/bed79+j05F66vbzgdD4zjgb7f0YWO4+nEZtgAcHOz5+H+iZQz2+0W74VpmjidRjabLVf7K6b5hJLIOTFPZk7svXIa7wFji1ICx9PEi5uO66s9T88HHh8faKDrdvsC2FLklm74jP3+mqubwPl0z3x+ZLOB8vEdh2cr8oUQ2O22iLjqh6OczyfevX/LixdX9GHDfn+NUri52YN7ZjNsKCnz+Y8/Z3w8MB3PlGky8LrGiqoFF4RmuWBhhlviDofFRSUXvG0EJtFbBmpZVB4/5MN5Y+QlVbJkOt+jIpxLglLofGBOMGdFSWwGj/SC3w0MYcA5z1yLQkUtBvIqFaiyVa/rjBWZkkAUOt8TxWLcwIxqRDXiGoAtrfmAAR4ue4ZdZ/lrMgaTuowTK7yLC0QSM9ZdDc2UnEGEkk0eKuLpnSPrjCZZ/BejGtsKNTmbdxmnkxWNSqCIja2SZ2NkSsT5Kn8vuT5zQcQvjE8vgUWBkIw9m/AQxBiRRem9B5SkhaSJIhmJQHL4AEkVDYKUvKxpzW9L1FV2fSTgyDnig0dzrpLTtDCuk2akU1IuNU62+6JaOxEWhy+OlMU8rVxvZQBNkCeUwFwCjo01DZRM0VgLtp2xK+npgpDySJZCJ2ZHo9GMzVUcuXRmTeCVklP1d8p4Qs1HMyVB1xmr25WAoycDSaaaMwSIDpcCzg0mj/MGOlXOLF56KAPMGc2zFcdzBDrLu5LgXQWYiuLoUOdAMzmbikScILOAeLL+Z2Y8gTBH0/wGqarU4Oh78+cRnJn/SSSEQBcCwfuq280XAUtN3jKUinJnZ5UuL6UGlk3f3yQda6Bh69KaFLddw12ASSuccwEYseZuTdrDRXDmmmlpZfwEMRDEiQVXzpmXRQvwRATnm0LXAr0FY6oMHzvf9qd9l7ZrUAC3yMaWBbdASYVc8/xSA7CFRn5R6dQ1olwr/ReHqjLFwpyEpK2y3wLCFURw1RDRaIyAOMZ55hQLU6qmZD4wF2U8j4zZWQcqb2BTjgWXlVwXZKP3rd+yPhPW715wPzv3GGGqwICrrBPnOxIm61u6NqGLd5fRD2XBQuzDV0hJFLogDL1pnLuGtyzJ9eWYYgWnLu7fMqYaCNrAC/jOmPzDORYMo6wBLwBaqs+DUl31KrJfgbxKUlmykKJQDbO9CLnkWt2mbl4sIN8nv1QvkNr2UFbgqkm7Fi8m6jOTTyW+NjUV2qa5DAQb01ID7uZ314DeNRmy9aidgzhfWUyWFLRA3qbEmlDZ0LZxZma/FcZZmEY1SWxAUb2MxhxaTHAX2t2FTNF+sP5en1VLGpaxWv+y9JV0DaCuk6OucWXp5mdVElcNxEv12miP0s7hkudnz6cUqwTZIysLmGeyOgMy7TFWlpjqkjDWl1UgeDVyt/PKFfBtzEW/VEXtfdaZo5TKrBEDq1x7XqyCuuX3tpw3CWQ9fPOIqTe5jT+77D+gyetGvFyRS2DKk1Xe8kzMR0o5GXHfb4hRiHNBdGbYBPAT5XRgmu4ZPr+llBMpnpimAyk+o8nR9y/59hD4xd8nfvvskUn4LLznT199w8vdWwIHq6IGjzihx5tXhAQO8RVfHr7g3WnLnH3dLz3Be2PDOJDgaiBnt9w5kzxrqR1k1BJGp96MxvvO3ufcUgQyVlz9AFE6yWQcQTx322/58f43jOlPeY4DRT0iBoVSO9v6EOiyY1RqZ61s7ar9LX/5q4mcR/7lz++4ch9xNZAvVGA8zhCOuM7zs5fvubsS7t52/PVbzzfHLf/uV0d+8/Zv+Zd//gVvXl7ZvhozWgFd3+KOYvhT1gajtEW1rWt1PdGySKBFakdAtBJZGueSKkWroE6hrkUYVnMJMi33re2A2siG7Xauy/AnBuArktGKgG1Xtx4BjiLmFVSSSRUs4aQmx1pZjBdAWjuHUhDvF9C8ZIsfpHoqgu3fgnUSWtZrtSto/oxSE1b/e43Lf1iHiELJNYYwr45F4Fif1+VVNO/KdveU1prdrV3EWqGixSW1MNQKNA2gKq1whMUzpe5ZRRzSBfrNlrDbMKaJaXzmw2/fMU4TMZrhrXfCeTwzjZHNsOU8nthsNsxzZBi2fPHmxpK3PPP89J5f/vpviXFiPE2EcI04GMeRcfwS74XtZmAzbHh+fmK/u+bd+48cDieu9jv2+x0PDx+5//jI+Tyz2fbs91u22y2lKPcfn+n6wLvzhwrICill+n7geXrm3btvefnyDqUwTTPvxwnvOp5lYjNck3NhjiO73UA/bCgl8f7De7wPzPPI4+MzQ79htwuIU87jmaJwe3uHcx7nPM/Pmf3+mv1+S8qJN/trrq+3lj+EnuurW0rJjPMJ74WXdy94en5k2GwQUc5jZp4zL17cMnSZYRgYx4kPH47c3FyzGTbENHF3t+fDh3e8e/8N282e/e6anOE8PrDbncH1/MXP/wn/7L/+b/npP/oxU5z56qsv+Xf/01/y5a/+ipurPcOmJ2cbR+N0pu8HvHc8Pz1zGo84B8fDCfaeLiaGvuf+4xMpj9y9vGF/dcWHwwe2w0COQtftyVM05hd1ji4NTFiKBKXkOtaqu2NluLe4kLqmrHvyD3wO5y0igSaUxnuyC8SYKVNk01levN10pFmJUUhTws8F7UB8xzDAsOkpUQl9R0pmMu0UQmf+mROwGTo2V9dkFcvDyohGk4KV7BmGgZTMC0kxpluQ3tgpsaBDVysvAmKu3TnZ2lxQKILiySWR1RFLqLGk7T/4RCq1Z3R2IJkss5VI1DyJOtFaULSiZWeBNLgdkRkCKDOuTHgZTGZnnGBASGTzR9KI14QjIXh8McNvs4PsgAl1iuaC6ozmma6ygXLNW9Ic6VymFyvkiHo8PV69Sf9KIjpFnRhT0xfUF4KKscxKx7bWiGYKaF+NugvqCsqZrhugJFBHKYEggiMimmms/SyextQvZUJcImoCMQ86KZ0ZeEtByLZvRev+l7Qz1lA2YkvWRPPcc+JrvJ8hKOoSUT3iurqnmNl4VjXJZc6WYsyJuYBSGzmECdEOxBExg/ExRQrJzNdLXPwu7SjoLIQS6LYDD48foVc6Z3bpLhlDLTsFF7/XNPrewNNhSuQsaKk0SfG4rHS5EDx0wTofhOAIRYyiVxMAFX+RAFnSo6X5hzSZnvkNDX01zKoV+zVMAlVvk4DMJ5nFAjJdlufamtZYSdVTqm62C4mAFtzZL1flcaLOzE9FqoeVBQbidOm4Rw1+3PIZa5apUD1l8hIoZTXvopr1k4qz6qw6ci4LoYQKOrXKX4MC6jeuweEFuNXS0BaIFpQIjFmYsjEi8mLA3MAdA5DUeXBqAb5NWeYCY1RSlbOllDg5x1TckrS6qvPNzeQdS3yl6GJaC5dAz1pBtcOkbTOy5OBLRdR5PI6YS90w12d9qQlXdctnrX/K8n3BiTGylvaeilY55wpA1BEm1Lao9T5X42FRaShgfZYmIwRZGC1/EEczvm5JyAIYrPJBM3E1QMqqKFXKtvzs08ttrLWia/XKnmG919r8KkxqZf5kFb4RqZ2rXO3OtAi87IxyBZ6rxAZ1F+COkXRaS1/WpwZUVtWFlwU0xhQGLCkLWOMqomZD3dq3QmUeVRDpE/vMBbSmXkNdy3xbrcR8YlShyoe9c1UeXAOsxnpwK3jUkqkFcZKWFOpFNtIANwNodGH2rdKyy+SCtt5qE6CuQL4sN7slgmZsWAVK9R4YJRi3XrIZxDb5RxtD6xih/rJKqCz38jKnbeylRfbmTPbWsCMntq74anJcvFvVPlLXlDZe6nhtneucWHcUY8e1znltzLXxt47jH3qVtR1WZbNnZ3JhT8qQqtdE523PjXMmV/q993uEa5AtpUw8vf8NZz2QYzWFVsesHe8/KL/4pue3jwFNkZfhI3/x40deX90TZDavPufw3oAYH4TilFJ6Pp5/zG8Pd0xJCOJJ3opH6gz8qY7Zdu9pz3jVAzgpoLP5LbgO6Y2BZXuvLqNWdLYA0QnGZAu1QUekdyfebP+eb49veJpfGZtOqG2dsWQdh3cd3nc254sSVSkxEfM1/+rvClPq+Od/krnu31d5Kajmyjz2qCYcZ15u3vHP/lHk5VXiF29/xDeHa45T4X/864+8un7kH//4lrur3oC14slYd8uugqCuFeAaWLBuRmhuRSaLXVC1okhRSzBY4O9lP2p1qQVHr5x+rdJebTGO6irj8/YaoVaEXVu9oK0/y0TRshiHX5aT2osMA3EswLQFA0iQCh63/bd+RwXGNJdlbOQC0zzX9SngfbD12DcAGpRmpmufszZeUXL+gSetwAr+sSzArYCoNS7+5DU0TtQFs7YoKlXWrFWuzmoq3tbepVKkrTjARWLvyCK4EOg3vSV/FM7nA3McQRMOM8rOs53SaTpSNDLHkdPpQFFHzsI0n2vRKZpP03zm/uGBj+8emaZESvDm80AIgf56w9BH5nnkdDxx/+ER5ztyCnTdwGevPmeOZ47HA3d3d5QcuNoXUhlREofDA1234e7ulqKw213x/PyM944XL26JcSQXZ15J4wwK0zwy9AM3N9fM82Qd45wy9D0xKiKRYbPh5uYFfefRsidnJcbE6XzEebi6MrDq48ePdF1PmhNd3zOOR46ne7wXrq9fMM0nvPecT1MFoCyOHM+Zq6trnNvw8d2Zj/cf+OJHn5PzGTRUIKZwe3vF1X7HnBKlKMfjmceHe4L3bLYDJTtStIJymnuOB9jthP/jv/iv+Ys//7n528kVr19c8/a33/DX//HfMmjieD4uQ9A7x+l4IqbEfrfnzevXnMYzMUYeHj8S44muGwi+Y3+14f7+nt1ux/H5Gb0CDcrQBULnmaeZEiOkfLHHWjyYy8qGb2PX9mStO78s4LitYfqDrwPlJPi+g2wrcZlAQrGcF08vHuc7jtMJV6yhlqpnnEYs4+opJyXmiBdI3UjUUvcmx5YrTg+JrIV+8MS9kCUgDvZ9ZzLxDFZZUOuaWAPb4D3B9zgfDOCQAG7DMFxRciamEXWFmQORmVgyTjJZCylrTQkKFEdGGeNU5fHOGFnFEUnGMHURr+ZRlZbwVFE/V6N+QVymSEGKVF+7GZoBubBYHaovJu30gRRjzdUr40Y6spp8uPMBp54SFS8BkbCOHy0MoSNFoes6omaCK3iXah3W4dQAHecFX7sKUvPgnAOoR1PBkelVqoG2kHDkssXJYPK5Uig6M2tmLpGus32vV3B4A2BdQijVsNuYQUjG+4y4aB0Mk6LFL6wpk1w6itoemJnx4lHvTd2TrEjR6m+OYg0RvDGYzNaj2OsJOG/d3NWBIU9VyaIFyQHve5QJJZFQlC2WBlvn1KyWh7d8xnvQdKbrTBae6axjoxRcNP8+p9P3mkffG3iKc6r5UEtzbKjlrGilw3knELwFCKUswgutlXqtyGTzECpFKdLAJyVJhiTW+rgURH31c2ABj5TCRSP45bj02Fmkfu3fYsGadXAz36nmuyIIfmE2NVmd4NToTa52TFuNb3XZwBewovqclFQTZbVJlWuQYJVBC8iaBE2KopoqSdxM57QCMAsb6TLZXf60BcICrk8DrQXg0WYEbeavRYvJnFh12CtzBFLOlCwLcBajMsZMKhjTQ9WkCQ2dq+9r1Q7TKa8JXAumL3Ll37kOLl5/Wblrf6oqMRniWi4+97vv/f1JY02OPEv1tWCyx4RC0Qoqts9YT7R9V8nrZzfvoXWTbM/mDyDQ/X3HkulojXFtPLgavLYAolCWyvXyi9XsfUUSKsBUZQELiFhZLu0XVMZrDUJa1egSAHSWW7NIuGqmqtVDwaQdzsAg5UI5ohdBDTSDSxtSrYIuC9Bir5U6vlkSOAOZ3fJae9sKzi1NFNRAmYVG035XCzQbf+i73lWVjERTPKKyVJ4bXPc7rC4UyFiHtvpevRyHLTFfZYWtEcQS1tVL/8TIU9qcs8TOiSWQDuuesiSJFXingY/SBHO2Pbb5bZIOu/9ZdZX21hNRhNYC3tVnKDSeVZMLtSRL69+NTWdrmqPIp/fHAOJ6Cs5GLTRAtK2JjZ1FXRNb6twy9D+MeSwE81SQiCeQs0O1q91zIt478iyUEmwtl0wp0Itju9kzpYlpfGTMTzjZEnzPYTzx7ZPwm28mPh48mpWr8J6ff/aOz6++JoSxsn8E8dV3qXab9dJxyi/59vgjHqctKh7xgteLPdO1p6CoWkVwAZhVSUXx3lhPSsR3AR88lFpxK5mMx7nO4gvX1hhrI2xrTEaYueo/8LL/mo/nHce8pVTGUsrZTHZTJKZIyYlSO7yOU6ZkY+mUcs2/+bVS8sw/++OZF5tnHJnkPDFl5jThc6FkM0zfd0/8ky/g7trxt+8+56vDDU/jnsOU+KtfP/HFy4Ev7jYM/cDCWVIgau0W1GKJJraqkuIMMZtJ7SLRrcvMZWSjVaLagv6GWhvwY3FFi1Gkva1+jtTPbB5tZVGx1RVoWS8aEFwXhAYDtv0XWP0tq1yrrMmk1gYSbS2QYpJorVIGLubzFBNznIk5khH22x1BB5uzdf2oiztgQFVrLhFTJEUFrv4zz7r/3Edjrdqabo+kFmaBVpi1YsgKsDW267LHUKoyoI2ei3tuX4Mhy5Xn2/aXYt4ceI/bDrhgxcfj+cAcZ56enpnjxND3gPDw+MB+u6eUxPl8MlPhkhiGDeApJbLddDinHI4PnN6fOByOzHNhnoXTUXnz5g1dEDbbjhhnA3p6j5aBnIXrqxt2+w0313u224GP9xPnsXA6nbm7fYNsoR9u+Oq3vyHGxDQWHh5O7PZbXr++4+7lC969e8/xeGSz8dxcXxn4njL7/Y7NZmC/u2aaZlKC4Lc8Pj6x3QVev76l64XH52d++/Vv6MLA89Mj+/2efuiMBZTg+tqSzWHw5ksXenzoGPoNYB0Ac4LT6YkXt1f0g93vEBzeO7a7DWhhnCZO4zPOKU+Pj4SuY5xOhGASoK9++47j6cTLl69JSQldx+1mSx+Gup46cAPd4AhhT5xHbm5uefHixRIYpJx5fn7m7Ydv2ewHpvMTfbfleDrXOC2RkilT5jny+GTJuneemBLn8wM31zdsNoX0NDPNI046tpsdp9MH+hA4OmOE9SEwbDek80iZjfVYSoYmHb4c9zWQW+MyaDOhBeHyA9+KtSbvwQmaCtbcqzB0njDUFvWlgJqPUnbm7zXnhMYCcWIXrsgxQDnTDUJRU9Oc48iRgsOjZaLojHTgug0UxzQlypQMHHGClogPA1MRci6kOBlI1Dmcc6RoBI1cMr7SCrKtHMYe8jOlJDRbro1AJ8Fit5JwmExcRYkx47C1w7uCOPNQzdQ8Xa1DfS7J9iQBXGWllronBPMp0uoRpsXjCCDe6CQlQrC9JEsyuxoS1htKsWZBzqR5HgPsan6rqpQsBNlYAavaNRSiFZDo7BqjMX1DXXOLz6gviEuUVPMeCWRNZBLBOzQXMj3kgVgcnowPxTrhZiHngYBY99UgqItomkiajKHrHEMSciyUkMguG8ZQyRVmR9GTklK8gTwiCZMABsY4W5xcpPrJZcQL4gq9N6aXQyAroe+JdqfwYnJIxWS1vR+YU2Su/nRd7SZfijPmkuzwXonxaIbxWOxt8f685DKbMDClRFEhE3GdxXQuZyD9g3Pn8vjewJOrlRWpfkfGDHKLSWjzbaAYcq+i4IOlFDXQ1wtJilUta+pZvQscCRWxrmTFkVP97CD40BLklXb8nSWh/tmkMOvfRVqFnYvEpP7MWVeeqgRYEhTX3t0itlYtKmsyVUqpMjipibH9ikWqP4R5PaSYrZKiQiy2eUihdn5SrFPtRSvhGoYawHQBcQgX1yDrf1zcg4UcoY1dUhYttdafrwa8FrilZJPWDEaFmAx0UtdAhrpZ2EigMVlaALV+9u8DgX73+Ide16ojnwBY+ruf+yno9CkA1JgdUoGmghVj2sbWjJatsyJLIN4+zzxjGqum/vDCqLOxRf6gjzaoWODTZew2UKgIC5PHXtmuuv4psnzOOh7KUs1XtbFlr3YWAC+3sX6vsqwH7Tt+l2pdPYa0VO8teyYiWjcmm7MLWwgLDJriUit925IpS3RU9Xc6US7BulzOK2m5WNVMO+tGdBHcKzUpawiYNAZDk75Vdp3qAsQ1WfCyYunFN8pC4qbeXPseBZGCdy2Zaz8oCzj1KRC1fGC9wFoFX45LeYbB39ZFydY8V1E9VUexFkzV06UAmSaJbafYUDq9ZL7VdROBVEq9ttptrF2ztHS7frfW63OgFeBYEm/aHF3ujrEmWqdB1erjxwIyyfLc6xvqM2/yRMEvfio/9MO7GoDVsR+LGoXczTjv8KEjRetoYpLOQkonYnhEpg1zmomT0nVXhLDjGB2/ud/wm2+Vw8FBnvlseOKfvPmaH129pQtPiDMGoHPe/JZELKD0Ssk73o8/5e3xljmFur/X7nP1WboMGipAiFb5axMXKeSRwWdjNokAhZjOFtRrNqP50NP1vhaEDDRytXOOBA/FmFWdFF5t/p7fPr/kMStzhpILx3niNM+czydSTpSYOM+R0zwzxojmghfB4TnmK/7ya8esPf/8j77lzf6BlAvHOaHuDDkhuyonFOh6zxcv3nKzn/n84TW/fPiCD6ctz6fAb95NPI8ntHj2G8/NbiAIzE2SItViwGMmqWrpmgXlQhF7xt6ByzVmEYBaTEos8ZfNeVeB37qHwQJYtKLZkuSJoLmCFsLFyivrmlFYYq1SX+O0spoWoJxPwC9te4LWIAq7KGPpKHMqxDijZAukg1+AlFwy4hxpHJnTTKDgVBi6oZLmTNqsxWwaUqmV+qKUGElp4ocOPJkIoMVTxgwpGm31ruCercWNRV8l1tJCGK3PS5emEm2TWj11bL8qtWPc2lFZIASkN9AkexjjzOP9PcfTgaLK4XDEh8A8ZU6nk8lR8zPn0wFxjs1mQymdye808fbdW66u9vRdx/3DPSlnxjHiXGC33/PixR2vX93xdHjP+3ffklIm52x+RqHji88/N38TIjGfefz2Iykpw2BeMfN8ogsDb99+QBC8D/TdFu8HMxT3gRgn9vuBnAq5RHIuBgzvd5RcmOYzHz68ZbPZEoJ1oBKXiHni48d7K6rmxG7f47xyfX1DKTPzHKkCee7vH1AKMUYDhIJnEzacz0fMs6bKe6QQJ2tvnnKk5I6u96QYiXMmphknjv3uhjEe2O17np8f2W63iHhCGNjvTZ672+04Hc8Mw4bb21v6fuA8Wjc+CnQD7PYbdlcdv/z13zJstlztrnh8fOZ/+av/yPv333J8fkKkEHYwDAag7/orUkzMMbLbbXl+PtB3PedpJM4zfd9zOo1M00zXB7x3fPmbr/jRF5/jvZCrgXXKibkfKFLwnWd7tWceE9PxYS38VWkwVFVDLbRZM4LabGjJJdzvTpgf2BEqyKIqCwByjid8cDgfCL5nnow1JEAsiSC2d+UEOUZiNyH0xFmYorF6vAfnB5Mfy0wXCsErOSY0jUYQSImcYmV2B0ryHJNyTMlyyeKQXNhtQdUacFwfBe9nfA9usFip5IBzVzgCOU/gjDiSSiKRTdGimV6su56qsV+SgGYINf7OODQ7HJbPqhMKnkCg2c0kDYASAojMOB8pmgzcESHgcerxtZucSKm2Fp5YMMBMlaCK5mjAKw5VXxVCxl5SVWu4KYJ2RuTwvoci5n2UKzZRDPiKCrka5fjGmHet8Bospqw0YS/JfJp8poin6AxMZouazDLAyB0j83yqlh3mO5XJaA643OGdNcWSHBD8sk9mkhFSage9UkYk2BoSS6ZzlcQjYOxIQVPARH6R7Gx/dZgVkhRBZGJ2M+qgpIBna006Akgp1gnPj/gecupwpaejt/GgsjDcpWIxqjOOjKNDCHRijPeZQiqJDo8JJ79fdvy9gScvQuc93q9yBgNtGgVfqui/ELxbXPobmLME/uGSbdQSrRVAKFjLvhiFmKxDVV9gI44QhNXh47tHq8a3xHFNKqXSBBrVvIFKi3lxLSU1jyYLjGsopY3qzxr0VMCjZJOzmck1oIZexpwXk8yYlDkWuuzs7y2hKzbBg3PsB9h1gsfaLRrRTZiTkhKgheCtevJdc9DfOWrC1QCknMqnP18qldqiILuW4sjZks85ltqdANtAaoBjKC20qtpKcl9Bok9OZQEUFrjik9f9vk5wq0fOKp1czKS/J7DFclZQcjNyXwM3Ox+3SCkuj2ZgXYolLQYw6DKWv3Oyy/X9QaSuKxpRgSZZrunSZ6wlJ1J/NWmlxQgKrHO2+f00yVsDmcvCumuf18ZaQ0/dej9X7MmqvXXha2bYubTK8AofN7BMnC36lyGLLsBaWMCGBnKglgA1kEZrAITIOuYaAHUBxNRe7hcAkayyuMsBDhWwkZqctfanrONXHK09eP2wNdm4+HyoLERZGaatWlh0nX9t+dT6bVbnWr21apryCahLS2oWNtIKLKqKMYtce76VRYVine2q/G1Z19fXNJC7SGsDvjaJsIJFCzbtfWVhs2JnL27x06KA+rqteJuA5WISKrYmr5hSA9PqOr8gewvU1Daktkwu7/tDmL85l1q1zHipzLpihZhZE320ceGdB6z6rB7m+UQq9wzdLbOMKCMfn5Xf3Ht+863jcHKQR15tHviz19/yo5v3hGAJi6trvvO1O20Fbx2Op/iaXz1/zvvzQGxghho4KSqLt9rlnmxYaVnGRiiZQTJFkgVqY2RME1T5QecCQQqqCc2elNSo3QAS6y5vcUnOhevwW27Da75OjtPkmOfCmGaezyPTOJOKdc6LMVFqfFGkGp6iiAuc0w3//ish5cx/8yfwavdIIVdqu1LkzN41TVvAd0eu+8KffDbxYhf56uENv3684ePphvvjyP/8q0debAt//rNXvNoPVsFFlwJeKZBjYUpKYy3YjA/4UuWJFcRp4zs1MMeVhuAiRhU1YHxZk7RhsixVKXHL+p5FMGqzMRsVkNIW5MbbZJ2z7X9t8i1r+gqEKxWdp54VVBDUilyZOc8UzGg2z7ZaeefJRcg5MU335Jzp+y1dSQTtqm2DJa0xzZzjjPOekpXjeGQ8vCOVwl/87PP/303A/wyHdXpeGX9LDKWgWi0kXHMObfe9+uOpImKv0XrfTdaiFXiqa3e2ar9WOY7UrpJ+s0G7QPGeMU7M55HTaWQ8nRjPoxUcq9fH/eEZJ47dfkfJmc1my+F4wknEe88cI3FOlAIpKTlFptGecddt2O02iIPtdmBOI/cfDpzPE8OwQTA/qdef3dH1jnmeeXoaOZ0Lp8OIcx390NH3xoLIU+Lh4ZFXr19xPp9q0VqZp5njEeZ4IqWJnJXNZkPwjmk6MY0zm80WJz05n3l8PPLq1UtC6BiGDYWCc57rqytySRzP95TjSPB7pvmMdwZsnccJESu8j+dI3we60FFdi9Znqcpuv6cLJnXqFVLKaHF0nTEzFcccqZ33NvR9z8u7wcB015HyjLgJ7wPDsCFF2F/d8PR8oOsndtsdMRZ7XXCoZh7u3/I//pv/F19+9f/hiy9+wuF54u/+5hccn98hjKgWnp6fbL0oVijLKXNzc8P5dGaeI9tNoZRELokYIRdP3/folMl5JqeZ9+8/0nUO3wX2+x1dzIR5JqfI1dUVxQnaefxuCymSY6TEbIl5WWNlG9etECYYk3vNMX7Ih9cAKZDxVb0zg0biBE4T0hlYY92xM0IA7QgMFI3GYJlmgrhFIu99MbKoN4Amx4QSoQhlSsx1z3dSc7NUZVz9lqfjSCyJNE90mGyr5DM+OEQ6yEd2mw1lSvjsEW9MLOc60hxIueBD7VKrU7XEyWaYnaUCaBnRGYJAMIDVrFs8Ts1GgqyIr4QRpVpLKEmNMVUk4xF8CQiNkNJiSiU4R9LedpLSoTKYvN1BZiYgdOIM8CqRUhJBtuZlhOIKSDXyDtKZXUixJlkZwxmky8ScyFJIZLyAL8HyDTxkmHMCb91vwTHHXHMV84NKJOBsUr1srFAJQipmCbN4V9JsNQy8wVXKTBacDjYuKGhlNi37pQreG34g2pEKePE1h0ggEZLg1aRyUxGyt5jL2Iw19nW2B6QiSAkIPSl6nFd61xngFav1gMuUaiCf1djlpQLugkczBj75RMB8pMR1tlVpLX5W7+8g/feaR98beArO0YWarHvFe/NC8s4qsU7U6F8Slp+1oAesq4FJNpqHEjVIWpPdUk20cszEZOaa4ULm4Vrno5ZgsCZzl/TNlg8CLKIXsY5tXnz1d2reH/a9FZtiQd8btbk0CRE0GV2TGZWipCLErEunEBDmnEjZWk23Ll6aYEzKlCwgkCodEYFcMikWgmRcMO19TJl5LuQsdF7oVKt5LEviJN+5B/WC7TtzIae1RalcJMeXS3urkBlg5oipkEuVrGimFFmCHLT5brWJtXzI+vUXye0K6kiVAX3/4x9iOX3Pd69AkZoUsDQzQ6oHTNHa9chdvMvqu0XV7l9ucbSu47aCF6gtXK4+wx/2dmnHkofXXwWqN0cd83rxEy0VeCrLHKUywWR5sCa1WmV3Nifkor2ozaEqAGseY/VrnPjlrNY526SqbbRULxQRY6g0z5IFfBJEvH1+9UMxMKXW8N2lMPciQUKXgN5XEH0BnJZqvtYkQStQtLICRIRKFrD53AysG6jXGIOscru2/kkFsdqzsCS6Nhlu46smfG7pWCB1rcq1Tev6fw0md/Vd5nHU7p/W7nH1vC+eHM3g+xJ0KsXYRloTUEql49rfHdowOLvOGkC2aZR1BarL8j3GnDLAbE2abDOu0jepQJDoUqgw8lI1rpTWBeq7M00uYdC1mECTFzYux8oJg7oG1Pttz/6HP4OLBoM/Emv7eoSSO1IsjB66LlvQVwYLllBSngg8EwWcDzwcHL/8Br556jmdO0oauesf+NPPv+aLm28Y3Bn1xQIzL9WftHZ5FTFD6PwZ3xzf8OXDFVNcO0JS98ekBRFvPmpaPRXrkzJjU8VVHxAnhfN4YjweoKSl0OMRM9EUxUmmuK5KtorJpEUJobO9OHtKSXQauev+jg0vKOnGJOQKnXdoCOSpSU3MbN8j5okhxarZ4slaGMuOv/r2NWOE/+7nwo9uDkxM6xgTJeUZ1USvEfKICyc+2yd24ciuf8Ev79/wjVxxPMHT+yeO8QP/+Ee3/Phuh5TaSFKtg06MmSnXYNg5XNdV7zetqHXdZCpoPk82sp03iwPnMJPUtv/Kxfgobc3WyjqtZbXWMTcbVmTrjy7rkW0Fsni81bcs6xPV+7DhigtL2NU1pVhVVOs35pxqZThyOL1lmieKBttrpDB0N8zxxDR9RAT67Qv6vK2djVxlYCUeDx/58PjAZrNjPk28//Ce49NbznPiv//n//y/1HT833U4CYh6FnPlxSvSkptCqs087PXNTN6Y2GqgrrOCmvEB2uuqJ0fdUxu7VZzg+w1h2NBtNhzGMyUnHp4eOR+emWdjCAmOXJQ5Jjpx5KzMaWKeEzkrofptxZg5HE8cj0dKMUPskm3PHIYd19d7GnttnEa++fprYixshms+e/OC169ekWJkuxsoOnM8PfPx4z1oYLu94e7uiuPxwDxNxGhrec6F3e7aZD4+MAw9z08H9lfXeC/opHTdQNd5vOt5fnpEJBM6QSSj4ri6MibcfrfjPJ4MyM02JlM5kVIkxYzQkdK8SA1Vlc1mYBxHhmFHnBPznPAuEfsJ79USfEyyUkohppl5iuz31zjv6TqTJ49TZrPd4qQjRWWOmaE3JnBKmbvbF2QdeD5Q91vhxYsrxvHA4XSgHJVp2lFSqgwOYZwmnBxIKfPLv/87ur7KNnMixcjxPNMNV4QQ2O/3lJyZ5tGuNyW8N4ldYzZ2nSdVfylB0CDMY6Trek6nmTlGNpuO8RTrvq/s91tevXrFcRgJoce5Qu89YRiY4pmSrXO2XwKHhoE3ULxcxIr/KXH+f/ljTIkyF9Q5Splww4j2wjR5gt9YISJ4Nn4ml0yQYPsxAabmVxvItsERvOCdxU9aMtoFzmlmJHI7WCcyCdYBIqtjnC1+GscDA8phOkMs9Hgoit9A0kRMEDzGgiq26/pzQMQ6kxcdq7+eR1CKGrgaQrB/06HY3u+8kU6KWBxQiqeIdYJ1zsyuQ19NwzVT6IyZVAscaDKWTTDOjC18ueYWkUJGiodkrLGsVFZUMa9UMTZYweMwfzbNuYJkjqwZkYzzIKX6SjmHaqqkEEfnOwPMNKMEhA1oqibaVcGPUNRDMUAXF81LT8yDzVU0IecOYYPWBitm3+JBA4oDB1kMZC7ZPKs9VEmbR129J87i+ayRAASxzneZDike85acyaEDPyzML+cDmqvVCB6n2XRIUgE9pygepz2hiDWGCKnmCQEtPSlFxLGwRiUkNM/gBSXgSrKCcKdoEMpcbC0lk4sn+C0lKS4rQR0UIfR75jJ+r3n0vYGnPgTz2jCCnXV881qBJ8u0BME5u3gtBZwBFV4caE26WFlDK5XYFqSASdEEQ1GdFPrgGYLQuULtTljbFF6CERU1ukRjUFiGigk8LA1cg2NDCKvngFysiPXflti2RMn+XqgsCecoBeaopGxShCW9sYzREuSiJoMQhy81iddFiU9RmKISo/3MVzPV3GR8JZPVUfAkLfTibIKpLmnYJ0wVTGpk9kvm8aRSPQB+35ou9lusUsFSDPwzw1ddQDlobIUVqFrvS/2oC5YSevEo+P1f/X2P/xTQyS5Hqgk89ZHKp2Cdmpwh1bNyFRBo35VLIVWWRikNMa8JAPU5Sakm879PHvbDPRrLo1GcQRZfnjaBrJOOLIDGwjgrTR6Q6/3MNMkJjfUnDeMw5GDhoyhVj63fGQtVBrAEH9qISXU8WWjdEluRS1vqNblaYM3mc1KvZoW26lxe/hQal7EAvgGIjaUkUj29BOSiKxoXAJRINQ1cQU671hWZWZgH0iRlbRTqp9dFu77GfLq8mbrej+9cR2PyNHCu+SQ5DGyl2BUuBtwLGIOBeBdV9wakmQS4Qmq1KCntMzGafDNet9eUygKV5Wa3ZhJQQcSL119Ol/YsL5be6jd18TqxKyq4C1mcrGNMauWlJgrrWK7BcxtnrOsDF393lyf0Qz5yMFZqdviu0PcTwkQpiTIHos8II5kOVUfWAinT+YE5PXE4nxjzK379bseHh4FTDOQ58ma45+ef/ZYvbr6mcyfEFZPVOSrYXoBEEMG7DSKe99NP+OX95zyPfd1ZDYhoErJiRT7bR8VVOaSHYnKBnBKiCZ9n5umB4/OBOJ9ZVJOxgMvkPNCRiNnjZDKSTQW/QlDrcuMzrvQU7UEzL8I3vOy/4t1xy7G4xUTUewPSpmj+i0ghBPM/6PqhViqFFAsxO8bs+cW7jjx7/k9/Hvji9oBKR3IviOLxs3CaletrkBDpwxXb4cDWH/jZzQc27pmu/Igv8y2P5YZv7ycenh/5+uXMjz/b8NObAdViwFMyLyoXvBmUYmy2oiZBdGIelbaXKfMcURE6CbYHtX26mep7oMYqFofUG+tAU4tvlJgVTcZ88lmr8ariSlmms6sAle2nDVyvjE3HwhA3wL9KZS0IhNwAfCEEb+dREoend5znTAh7gg8oJ+4Pf0+OkcHv6fqB8fxEnCIfMebIeMqk6cQ3335JnjMhbBCUnC0GK3y/auv/X49UUN/WNqnMVZNSGAu/7pFFsa5HXKxfFXzKTVKslJStyFsTeWv8YCa3KhA2W9ymYyqZeTrzfHgmponzOHI6j4znGVXFe880T6QUibOSU2G72XM6j+w2V8SUGceRaRq5udlze3vL0/Mjzplv2zAMdINnnE8WN2bl6eHAMOyZxxNXV3u2+47MiOuFD/cfiFMm5cj11UuGfoMqPD0/cHW9M/mdFs7nka7rqun5iWka2WwGNluP6kSMEeesY9Vnn73mdIikGNlsBzabgdPpBGT2VztKUT58fG8d3ULHPE2mWphmHh7v2WwHht7UCNNY8N5zfX1tbE+f6TrHMGzwPtP1HdOY8CFQSiQnA/n7zuLz/e6KeTbAphThfDpXs3OH8874DiVwPk+ows3NTd27lLsXN4gI0xw5TWeen5/wPtD5wDyOy17pZMf9xw+ICDc3LwihJ8fM8+FE13V03Ya+t1b1OSXSPNtenSIpnpnnjr7bMGx6RBzDsGWeJyQYm8eM64VhM6BF6fueEAIxRabRCo7DEHh4fGaaZ3abK16++gwlmc8QljeSzLPXuWQe5KUWfOscsH3fbD7WgtkP88go2SeySxAiwSVCN5Czp98GfO+soURnBs55gpxnUh4N4K9FgNBBjBHvB7OxUWXwAe8852AytHMyewNJqebQHpWOKSfOcSKehekckXNmu7si5URKZ/phR4oF8kTnnZFBpCdNGS2RWCLjeCKXiJYBzY6cjvigdJuevtuQaxw19MGkosmAnYA3w2sx5rEPjpINwMmaCNJVwqvJ170qJQne9cacUWMOO/FI8WSJZLT6LGEd1HF4nTE9kcWpTjwqPYmhdopzINlY95jkulOPdxsb4+IQ3eCdoiVSkpmWO/EkNWaOlEJxydhFPiwKD8U8kLTJ/6sM0KvDqUfyDpEeHKQ04iTjcSCejCNqquPdARFqpz4xzrSBaRR8af7WvXmeesFpT8yK+IBTayBB8SSEUsxo3ZhK5q+kkixnwFXGWQSNiPM4OluXUvWR6isTL1lDMycG1PXeE7XUszIPrVAU5yBLYkoRmO3zsqdIgGKfmVCSOIKrkvn4/ebv9waeutAq0WrAB4rXagTc2AUtzWxARKngiwjFtepN23StsuZqgqOlmkVqrQQ6wDk6b8jt0mGqeYioLFW8JcNpVUH7dntm1OC3oo/S/F+Wd1Zw5fJiq0xAdU2MbL9XMwGv1X/VUqVsgvdmIihidahWMMyuUMQTkwUMXld+QpN/pQrkCEL1ca0BZsWvqmGU98FoezlfXuKaWcsFUCYGYnlPNTLX9T1aU2DFgm01eaNKMkaYA69SF0QbkA6pLK2W6pZPvlgreOicVBqNXj4ZWO5n4yc0WcwKwsnFNa2J9T8MWolcjKnv3A/BwM72CW556DXRVqqPhiX01oHQKnWpYIGstm5jrSuH3Vu/AGyXksM/kOS1Hmv6Xufoxf+K2GRtP3PLc78EY8vS5tzaJtg9aMbNFe6orIlgUr5i1ZPL57n4T1wAD/UHdUzJSsRaQJ8VWFK1Vt4LmKOCZV2lwkptQFWfM9XlmTaGjRYTMDnx9TLqqKkft5xnG7sVSDJgt47T0iClizv7+1g0UlkM6xlXaqxtSiZxs89pgIiZdSomD6017kqruuj5dTG2SwWOrWOJYP9upuIORzMNKZWxoKXU9zWocIHryCnZdS4zuvlUrefWfmTG7yu13owqbZyUIvasJONcqOt4ZajZp9G2pKK6WMTY+iJ1HlbJ4wIetTELXutzxajraxfDer+kysUQM7gEcJdg1g/76EKtANJRSmKeM94rQ6dsBkXjbJfpAAol2XgqvjBOHe9PN3zzuOHptCHNnhJnXnTv+LMv3vLFzXs2YbI9w5k0cRnJPhAUXG3J/Dy/4e8/vOa3z1tiMkbo2vQDnDfmEIJV9yq7rJRIniNxnolxwmnGpzPDMJFyqqBjIeZUu7Uo4EyO6TKasgVUPhA0W5ddVyg+IUlqpdEh+pE321/w648bvh5fMmZbz0qKxDla5dBXh7jg6PrApguIGABUykyHoNJB3vLN8+f8q79x/F//u39B19/wft5Q5oR3hX0qvJAd/+7f/iX7Xvhv/sWGV1cj3r3ni93I5vMHBnnD3+dXvM83nOPEr7498/H5zOPnV/zk5YYgJv3rg8cHa3PclpgWLgksnRqj6rI2WudHixXU/HyRIORsQHFXfcGyqpnAGm2IGCs4VD09phjpfE8ogYSx2L0IsSRQCMHTKdDkt23vbd6eLVhqC4G2vZkW0Fiy7BzeD/jumoGCyIbt/orzceT09I21IHcO8ZGHb0/cPxzQrJTgQbYMzljGoQs1Dsv03sxR4w+cLWFH9SosNlG17W9Ys5a1y7Nb5HXIyh4WoBq40eKexU5BWHyyRIX+ao96z/3TI8+nI1qE8/nM4/MjqDKNkb7rQeA8mvF0zmYO68Qzz5ku9JzHM+M0stvvcGHgPJ6Y48x2uzXwxTtiTKQ0U4rJJre7gVwyXRjY7jbElHCjsumveTocGMeJ66trhv4F43SmaKzJGozjGec8z0+PTPPMdrMF5/AusN28YJ6Uw/GEFmNidb3neDownU050LyupilSCmbcnWYDdr09gy54ZBc4nc6A4+VLY9vN88jQ74z51feklNhttrzavUSLMarevn2L74R+sHvXO/Oxubu7o5RIKTPTNPP69R2H05nQCbebFzw+9IynSD94Unrm5sXOADdgGDbMMaKaOD2POBeYpsJ+v+Xq6oZpPIMWQgh0fc88zZzPZ7abDcfTEecT5/HMMHTs9ialkYri7/dbTucn9vsN33z7lq7zvH79mpgip/ORcTxRtHC1v6bvN8yz+XflkjmPR4IPbIYN5/GA8+C9p+s8OWtVPXhyhinOfP3N14QusN127Pdb+k1Pv+tJx7O1hm8DteVq2uL8yp7J/yXm4P/+Q4fqqacO0UDneiQZ41jwaMqkecajeL/lPE/kHCkukzHJapnBZSGoI8813fdK3/VI9FyHHaPM1hCqZIY+4KRDfE8/OI7TiSK101vXkWchlkx2yinODLNj3+/p8Awi6FyYNZNzJOvIFCemKZIlkeZIT8+ms5jC5OiKhICjI40zMhbQxLDtwQd6Ar0TnDOqbJHAVFmpQ+hxGihxpkhCVAjSoWpglRAJUkwiV8LCgTbWXUZTqXY+vt43bO+QQqSAd6gGhmB7ek7RYk3xJtFTgU7NhFw7PJCLkHIka0T62vCoCF31e+3E03rFejHrjtaUQbMSnK8qAjHQH6myVcFhTNCkGXGZJnlzzlPyZJ6swFhiXe8tsnIFKKZwwnXmZ+oVrWu5987kb2ISO1ccXh1BPAQHIaMk5hRRDXh6UGv25py38ejM/7KTANlTilDyma7rCBlETbKZUSQUsgR0LvS+Q8h4DylF89bKGfE93g1kLURNpsZwhZgnSlGCbMgav9c8+v4eT76x52qFWSo2pFIBJqA+kBaxXrZHt1iktX5dTTFbUlByJhWpJqYsoFTwBqAs3Al34emBLElisw9v7bttk26wgwKpghyXFnafJhyXxBoLpuWTn2mt5qWC0SJV6byzgNHXJLlUpLdWFBHzipjmTKwLdYuPSqOXqlYGmAlzmkmyMaBMDdoHk9x9Ur9fYr01VWxglj2j9QpULxLUmgi0h59L9b1yal3/LnxlRAp+YXu0O/0p7GSRsVw8d1nYIS14Wl9fgY6WdLI697TBsqS8l4/nO8nhkhRVedWKWlXvjIvOSQ2gbHfJMAOjfJZSqqF9WQJqe4FbN0dq1bb+eJ0Hq/TqD++Qi6wcSxR1DWDV1Xm9MFnWQNc1wLcOOKkMHAMXKpuoAjWt26ExCvMC4Ji6qTKpGvOqjnurntvmQ11vrLpus7fNfWkJUH22l0a6WhedUr28lkWjft+yVrgaSDS/kkrVKIJ1/KmLgkngWP1LnELJrHDUilK1sYGsa5Bc3G6pnkPuYti06mKhmYVXYEgrc6nO3paNLsb7NIaYLs/IOoJqBZPq/zezz3Yv6+1wNCZS9W6Stqa018vF65uE4/J7QTUvoNMCTzWwsrLkRJtcpH6HVrPxujY0o/hCxlYmAxOd1LFQTZZtfq8eKAsA1RYNWVlOi31gHdS+jptPx5SB5X8QKWu09a4binWiqZKYrIHQewgRLbb3ZAn4LpDmifPseTi/5Lf3bxinjnkOpDRz1z/yX/3oPT+++5bOP9FZ29e6t7sqna/PT5z5D5Yrfnv8Of/x8ZZj9EQ1A2OTTGKSHJWqvzfmm2QDQOM4k+bIFGdEFS8ZlUQXoJSJczxDiTgROoIZbwejnMc5oSWB9LhSiCXjtaeEnsJcYdqZ7DoKcNP9lpf9FX+bNsyjgRKaM7FW1J0IPtTrdW1E10R21+OdcjUE/ujzG17uJv4f//d/z//QD7z8vOP96UzO1i69Cz0v9p6rl/8d7Lf86nnLMyM7viJPH7neB/7s87dcuyP/4e2PecsNMgtPJ+U//ubIh4eRz++EN7c3bAZLYNt8i6XuPGqAGFQAv50/zkzRl58bo0uiSeZdMNBpnBJowbseF+y5znFkmidj7SpMKRF2xrI4TyP9MLAN9vpxPnP/fOb25oZQu92E4HC5rkGFKq+ua9wCQNU1ViFpoWjhPGdmPPvrH1Gyoho5PD3z9Dhy/rBjHpWDG5Eu0MuGwd/Q9RbgOulBk8VQ4pk1kdWkJE4E/A9/HzYeeyu6sWytpRVG6n1rnotNet0Y+UqpjWns09oHtM9zzopobuiYUT6+f8fj4YnTOJKTUooZXKc003fmMXQ4Hsg5V5aR7SUpTUxTtmRYzNj48PzEbr9jGAZSzpyOI94bo0fEsdtfMU+Rx/snxnNksxvYDP3CiN3tbjidR7QI2+2OaR4tcdTMNJ/48OEjOWZ2+2uur695/dlnfPjwgbuXt0zzkdPpkZvrW5xzXPuBlBJ91xNT5NWrW3KJDMPA8TjWDncb6/aVZ3b7GzbbDU48h+cTp+OJu5e3bLdXvH37gaenA1oS1zdXhC6w80Lfd8Q5cv9xZNj09P2Ww+Gpmjw7RDJdFzgdn3HO8+18oAs9w7DD+563b+8Joed8fCKmhHdbbm/vCEG5f3jmcHjiqTwTuo6+Hzg8HwnBsd9fEUJP33UcDs+M04mr6x3Be56en3j/4R2qyt3dLS/urkAKx+OJ3T5Y4ice7wLH4wHBcTw9cjw8stttuH1xgyB0vq8ySvPlMpP2DMzEaDLk6+trlEyMkePxYMVGVfCBGStYHx4PbLdbxvNMP0zc3d5SsvL+/T2n85H5euYnrz7H9548phr7uYv8ZQ3OVLP51P2Aj06LgUCut852ZIoIYevR5JnOZwKRvt+QcmTTC1k6zkXpvJCYiDlT8gw+sQ0dQ513Y04VfIL9AKnricWhPpBKxzzOzFPC5w3OmAL0rmPuJyaJuN4jped4Vvb9BkFIxaPR1fqAAzwSHERPiRaj5hTJXYf2gCiZEaFjzjaWxMGmsirnrMzzjBfHJDMMnpQVYq7A6cgQBshCcEq/8Wy2W7IY23mQAGUkl2JKnuyMSS1qHkbOI4Rq8WIFZBBiDkTvcVnpGIi5dU6sXrAKyVtO7jXQi+BIpJhImklSSF4tPnQQywyU6lEVKEUp4kmLH2hA8kiQgmgH2dM5yCGTis0bUQiho3hlLnmJWpv8XAqUavWSNDH0HW7JdyCEWmRN5tMXxUBKxJGyqyzm0fydCUZAKVU6r6HW2AcDqLx1Jy3iEemRYKwtkcroAVM+dY4xRyQnvGbIG84xsbvdmkReW44WCN2WOI2GE3ix/ni9R0f7yCIRkcSuA4qQ44TO32/+fv+udkuifSGRuwAxvlvtWr1+1sSlvaItNZ8calX0IJWiJhZUeWcVe8XbQ6ysI8SoYJcMg8vsoZS0SDykVrrBNKuL+0nTwevF4sflx333JloVIdTuVgBd8HhvLISSc93AwVgX5u90mhKnsfolrXdpGYDNrLzdoFKjtyBG3e0FgjcKL7rK5laPpfqH2FS0C3R2j7zii1S/Iq2gkaWc1l3FPie1z7Ay5sK+0AbotARUGz384osBqQbPDqpPBZVBZGRDLc3Lpl4za/crVsxqSdD/14avUANdNRBkYTZIS/JX0MlAKV3YI76iEFKBJCOv5RVgaE45UpOuBszUpN2LEJx9TpAGgPyhQU/r4tdATzBQ1FUJtriqlTGXdZa2OrqGCmIfsMhrwIyhi5W2rfJYvZouZWLOXVRvYQGcln9Ug2lrXuBr8quI88acsEuoOm7BzLyzVfkaCLsAIdXbpwXuwgL+SgM1nMFHvnYfsSS2mZ/nZewIUmXrupznhdvSUqleGTSXQI+riOWnsjqBKmGmroFSgTxdADW7X42RF5fnVhGwej6lnrO0J7yAVk1+toDhmnHOLzhaA5NKyXWqXwKNlVnqmtTDmJ6NC2hvyBcgrS4V5+bUY7fLxpNWZLw448/ZkmKeCSZhtltR6hpvUs7Kcmu+QUWrmlGWuS3I2nHQqDOfzklpH6fLv9uYa2vOD/3IpUeCJYLFHdAyEvw1g9+hOKb0gOqRJOD8HiVwTnvePW95f3jJOW0YY0LnIy/Cgb/4/B0/vvuKzh8JrjL+nBHCDfTVit4J6hzoDQ/jj/mbd694d4Rxtj1NtNh87zqcD/SV/TprxhfQHJmSMk/JWkxrIZCRKhOjzJzPB2I+EVxAvY2l4iDGM6XK0awDW0ay7cHOWTczgiIScZLRFBfg9PXmV7xwd3wcXzHGymKl4IIjhIBzAUchJ29AWCdcDwP7Xcebuz2kA/Phl/z62yOvP/spH8/w4TdvUcwT6uXNlq0T3n/4ho/3Hxn2A493f8T13TXz08C//n/+JX/2pz/m//J//hE/e/1b9tsn/vrd5/zmwxum0nOclfFj5uHkOIwHfvbZjhd9MGPQEi2YLnPtxFfXUR9wwZuEhUBOmblEzvN5BepS5jh+YI4zu901RqsXghso4tjttsQycxrPqBN2YYvmwjSeSSVxGmdO0zNpe8Wu2zHFJz4cHnFB2PZ7nDMAzIvDqZrcTq1o1oKrxsxCM8c541LmGI98/PDI+fjM0/MTz4dHcpyZzzObfsC7G7a7zpID6XDOKsm5smVN7m6ytKBK54wVGxByyoQ/BObixR6R61qo6MIQbXFIi5tLZTY1Kfmy/7CyoAzgN1l1zorfDIwp8uH+A09PR+bZpHWCdaXbbHYcDpHj8cjz88HYf+LIOeHEMwwbJmbMA1CYUqTvt5SSOR5GRKyyvttdMU2zSdsGk65tNxvSfkM/9KQ88/T4TEwzL15e8fHjO+vGVRKn44HNZsMpmTFtSpHPXn++sAUeHx45n87c3NxwPJ55fj5z++KO8ymRS+H29gYtJ+7v7fzvTw8mPQ2O7W5gt7sxRkiwOXE8TByeP/Dy1WvevX/g5voaFB4fHxj6HlWl7zsgmxx3minFDLiLGjDz2as3/OjzH/PLX/+9tY1XuNpf0/mR4APzPPPm888Y5xPTNHN3d8PQG5OplFyZSiNznHDecXX1iq+++pquU4Z+z4sXrxj6jmmaeH460vU9/dCh0vH8/ETOiZyNYfzZZ6+IaeJ0NtPwp4cTce5BMtvNFTGOjOOJn/70R2bQXkx2uN1ecT6deXiy+94PG26uXvL4+EiOCeeCeVKJsR1yLkxTpMlrz+eREDJX+6Gax5tEUgtM08Tj0wNvPvsJz8cDT4cDoHTOsZfOJLxaCxJlHee2r1MZPj/snTiUjPgO6R3iTFJasjFHptnMpVNxfHg6sdl17Pa9hVKTQyUzxsJud4PmjOtnRJRUwd5SFFSIOcE41m7uO0r2SBYkOVwUuqQgnUkjYyR0Djd4KxRFYQgdaZ642t9SitJ5851CYDwXQgUwvBNSmYllYjydGK4Gum0gR0HPs3UfFWPUzjnw5ExamcfMfrPn+Xyiv94yjhM+CcOm4zBNxAA5294wnCLdNrG9vjZJtfb4sKEw4cUYTMXNFFfFxhXgytG6Y3dVwjVhku9SMINrZ13fshSSK+A6U+ZoRpM1W3FOya4g3iEV+DOfWDNATy0Xqc1LnGZKCag3soJmh8iAd3tKLohL9D5AqrF0TpDs+7x4M0/H1zzKoXSk4o3p1gm+zBRN5q3lPLN4i1u1srZcqsFowLkNKhnJnhACRZxdixRautVscLR4u3ZJDH3Co5QoxiLvTS5XshBki3Od5TwyIWUiFWuwMB8SrrdYb5oLAwIyQ4nVczCg5EVKZ77eQtJo+Yp2iPOEwf2vzJ6LefR9J1xjEiEtAaneNwuURCvGLxX4S1+Uy+pNw4guwwTvPZ1q7ZhXWSuusmtUSGpeSOOcDNWsXd5acxnXpEF2tpYvV9maqya2IkK6WNjk4gxWuQe1iPTpAtg8T1w7d2f+Sb6ynNprXJUpmJm1dWqJWcja/JEEWhtRCxla/cuSV11vjnPQdULnjBWkTfOpLVlvDAOtANLK5Ki5Fw5H5wUNanS5Yt9UahLebGdKA/Sw4KZU2M3V1zWwEZq/AMtZt/Teg6HX3s4ZMlkFScoMtHby7cyNmSSEpcNh/VxbF2kAQrs37XDOLd2AUlGEXIEGXQANoaFj9s7gLsbo8onNSLWBXbIAeq1KV0M8XAUtO+cWM/2WEMsnKOAP91gBo+rjhAWrzYfIIes1NyykPfeFSaIL4PQJRNg8RnwDmm2+e+9rpzPz+dBqiuza37Eva/PNeVdpt1I7Y8oK6qiNlyyVkVjqCNWCqLk5WcHCujpcjprL8L0xERVjxi1zpr2jjYcCoSbRFutbYED9mZ3Q4hxnTJzarc/XkkczyKbew/YgVkbU5Rk28EpQzUaqqpLeBiBdIuPtjFs3JANtDFAujb2mDSxqzJX2bEudf+t3azNS1zXhMVCmINnml0km1852bWyszMJwcZ/MJ2sBGZv5Mfbsm+yttM9TLCCrHVHXO6OmwxfzQnAX+wg2+5e1gzY+ndGZF8X5sjBYZ5TG2Pp0ZflhHzdXn1Fkx/PhnpifGHrFBQhBQROaNyCerIk4jzxPO94/v+Td4Y7T3JHSGcbMq81H/uxH9/zR3Xs24YQEM3/FV7mAxDouzO/H9iU4l2t+8eELfvnBKtxzNtDRe0fnOoLrzIeIYOMuF8YUyVNhms1YyYoZQsKheeaFV7YBELFuUBjwGkuBJRFpnWwMFAudo/hAKbON2aQEEZJYC3kATZGr7swf76759bcDh8nVphmK046Q1ewDnNC5zMYJWz3xxy967p+/4e/+5y/57d/+LdJdWSVTTuyuX3B192PCbuDdb3/DL/7y1/zsj3/Gi8++QLuJ4+Edp8OBu/Nrbq5u+Zf//f8N74S//jby0xcTr24z/2wz8/n+W/76wxW/fdpyyIF3B89xPnF/zPz4tuOnL7cMPUiBcYw8HR7x4tlsNgz9wOA7vPeUmEjpZB3K8lzB58T5+C1Pp6/RNHIvA31/ZVJ6zAh1u/0Rgwt0w57tdo8j8fz8keItzhjnA123QePMNBzJYn4/T6eDtXJ3hY3r2A7X9J3JGxzm9Zlz5jzPTPPI8XDg8PzEl2/fMT89k+NEUqqBrRC6QBd6dnd7HGrmzqLWTVbm6kuFxSfF2kWXOi5LjW+dsqyPy5r3Az7M+Nn2g+ajaOcd1q1UWywkoKXWfFq0JdVYnGUNtr9bfCXOI97z7v03nGPidBqJs4Ekw6YjpYlxnJimmZzXwlAXHM4FvAuMY0LEE7pC1wXGxyNXuxumeca5LTFGum1gnCZKLux2G87nI10fePf+ffX4svfe3r4iVo+QXCZ6J+x2W7RkjocjKNy9uiNOiY8fnkgpc/Nix93LF2w2Pc+HZ3KazXtJJ0pOzNNEjj3OKcPGEePIy8+umaZYrzdzPH4khECK0Rg2Ttjtt+Q085OfvGGeJ+4fPzJsBuZppu+F5+cHbm5ueHi4p+sGVOH+4xMpZ26ub4g3kfN45nQ6EqP5O51OY41nPDknHn7xSC5WmPns8zfWfavriFNkjpHz6VQ9DAe++vIdzgW22w0xzpQ8orqh3wReffaG43EkxsQ0Rbpug/cR74WHhye+/vqtyep2O66uN+yuNsQ4shkGtHj6fgsaePvtI6lMDH0g7GCeR7q+I58zXTAj9du7W7bbLR/vPzBPM13nceJwvWMzbOh8x/v3762TXRjY7XaAkGuhvUk0r6533Nzc8s037xinM+KV3ieewwnfbxl8oKuFyqI2xkz+awGXJeE/bK1d8U1J4syWI1ef016QZB3ISnZo7tjt7tjue8bDRwZJSNiz226I0TyDFId3Fq+lnOhkoJTM9ibg/BUxOtIpW4OAqgIqUogys73amEgqRvrOM4Sw5msugPfkoPQUnItIcMQMsxNS9mRVut6RojK6yDwd0OkMsmMaYR4jw+BxrlCioMXGxDhnPIExJzofGHwgMlGySejNhzDhQ1fBW2WKZ3IZCU4o/RXeb/GuQzxoiOAsL89Vi+TUoc7k01oKWYQiDnIk+GKeTRRKBlGHo6OUHkM0Z4JrOWQmFcUXNXNzNWsC0Q6XA7nYPhKTEvBkCllHSswMXTDzgAxaYo2VHWhA00zOM6E1pam5rpZCwTOXgk4J73rE9VAmUknEYt0ERRTvHRmpHXWjMYm1By1WfFMxlpgfas7SYvzeMtecq/G5Q/xcZXSWI+EnnAQ68aRkXsZOlVBqUwJ1BgI6k/F5AXKiJIff9hAKvkSynqFMdW8fmDNIEeJo7FgXOoIMwGzAlARK+H558PcGnhqIsyb0xkJwrXIvUoveawIFLEnMCly04wJUWFhJa3JMpXAnsYFxjokxGv28GQbXGpF5El0I6Bq7Ser/FWUBS35/UcyQnE+YXBfHYnrMxfnV614AtfbdS/JmjINpjuTcPtfuWkt+zRurgh/tO3WVtziDNWtCud5P1TXtbPl/wRgruSLnSwc+7H4NIeDEMae0gCQGf1nytzB8aDRvFgmVa9SM9p7aBtNX4KgBPUHMQNTYQMZ8aEwqX6hTZxk+gFRWm1vAhcbsKBegUZNoNjZDS9qrhRiJlvw2QK7BRVTWUgMNV8DMctDVo0moVQc1VsaiO6/j0mNMp+C0+cbTcLtL/OWHfLTxosVa59r9qhKv0rwmZJEDLABnAWt5m1lnhzS+v4E4FdA0I8A2/xpIa3psKYJUduBy/6sj+drxjaUi7JsPS50n0sAiMDkcQOUcWUvp2qECEPEL+F2wsdUYk40s5C473lVQAvENhlmeqausj5zz4r9EHQOtaUED65wY0O3qC7RKdpvfQgObll91XhVt8mWpCaRWgEwvHlw9M20rH+bdVJ3+c028SlkBolzSMjRLqR5O7tJy3ebuyqBaZXwLa7WYt5BVJQulZCsKiFgHjQomant9XWtLBaOk+TKxrlfiBVl6MtmY0wJmblgo3nqYoCYFsnsgFQRsRYZ1fWgglLSX1RvrCsu5LBNVmnb+YmL8IRzOgi0XHEPY4/zMrCMlJzq/geDJSci64Zxe8eHwGe8Pt0xzxxxnXBx5vXnkn/7kG35y+5GhPzQSnjUIEetcYqbGijoPeBAllcCvHl7yv3xzxf0hU3Kq7w100jP4rvowwoTtMTEn4hxJswEOJus0MDXUOXIzFF7fBIauI+cBLZlSTOrRDE4hgjN2oassSIenkMklQ6V9o5DV5IZaAoWRH9/8ijfDHV+fPmNMxuwQtQA25cJV33G97djqI+//+l/zJv+Mx+cz42nmH//Tf85w9wbRDOORD998zYevv2b74orr3YYXP/8z+usXJL8FjYgI4+EjH9OJ8/aB+Tzx8rPPmNKOdx8GXt1d8fktXL8o/JOhY9cnfvURPpwzz+fMOE68fxr4MBZ+etsT8pESz2gerStZ19H7jozgc0E1M81nng8PzClaZJGPHE5viacTXZc5j48c5SM+DIjAXCbKHElhz3yvfPbmj+mv39ANgfuHj6T5hMhMd3PHw+Edw35HKZG+v8L7HSo9cT5yShPbbqTvNvgukKPJ5h4fH/n1b77k6fREHEecWoGuC55Nv0H82qBEnMOVRVxWQW5qAwytkjIDK6keeEkKvhhgkwEtuRYDhVx++MCT+Ti5WoQr9XorE5VWxFwLMQb7r7Fpyasv33cPFQMWT6dnTuPI4/MJwdP3JiV5fHrAOUcXAtPZ2K0xRjYbGIYe7x0pRsbxzDBsSbkwTSZBu394z2azxbtAF4SiiXka2e93xDiR88z58UA/bJlTJKbIHCe+ff7A3e0LA4QLnE7GXupC4O7ulmmcefh4REvhs89egnic8xyP9zw/f2S327HZDByflY/vH+i6ju12x/EwElM0jxQch+czfbelpBNJIn03MI2zsaRV2Q0b5tmu7TweLHFygZxKlZlN3Nxc03We3W7L6TTy9DRxfXXD7YsbuuDIeaTve7wIY7Lntd1uQGr7+NKz2/U8Hx6Z55FSJuaojPOZeUp0oSflzNBv8MHz4sWe6xfXpBQpWfHOzLtLyXzzzTvO5xPXNy94cfuSHDOn8zOlqDEWY+LVq5dMU2SeJ5wXjofnykTs8X6g73u22xsOx2djXIWN2Wk4Y771fUfME4fDPU4CIkrXGyg8TRMK5GTA0qtXL1EF52Zb58bROp4GT0ozqpm+63h+OrDdbug6qd26I3aDKjharIBeqtecxy8BWDPG/yEfk3pjDJ0jIRjgiDc7FYd1Kw/dhuvrPTf7PeP0DCqU4iE6NBdCyBCUHD0OJZYZ10EfPL0PeAopmj9S0YSmxDwJJZlPocdaraQ8IRLp/IY82/pX1Ay/LSY3TzPvPKkUsigEZZproSIqOY1kMtINnMfZOo+WgOtMTptnhxLoXMAX89jUUph15Op6y9OHA+c5ktOIDIm+73FJ6QdP6M2naTw+M58MgD33Z5wbUBxhs4EONkNHL4Gu21lhmeqNTCRqppRIo0GIC4iEJc8N4q1Aq4DzBvxEiy+KCK52fRNRA5oUcpot/quG0q7aC6BmURHU43NgzJYHZxlRHFmHKnXPOJfpnCdmMKL4aP/Pjk42pGxkGU/BS0IlGjO4tjOcE0QnOElmJ0RtvOHMmzZpIhXrVpiyAsbgElfwnauMskCuYBxAUutYh1hzMOeMASvOg2RmIkVLZUtHhFwba7WufZ40JoYeSj5TsuAloNIUQZ5UMsPG1gjrNGveUqELjGWsueP/9vH9GU81FwVqe3n7d/tvq4rKEsj+XmPdT441ybF/rj4by/+pVbrnZB4GuTQxl+W8BqwY+6klNsCSQNs/qEliTZeXYPb3n9EKV63ZSHOoX1MdfuczLhlS7dYXteodRQhiMp1Gr24+CA1waZ9hnqE1OaLmnVoTVG2mZpa0N/+kywQ7llIN+poPSu1+J4Yiq/eG2KsBXo2lJM7Oz2GMJkc1LWVlBqxd67RuQoJ3dUepDIbgWltmew4eGLwxjiwnXa9VtYJan5jdmHa8XD4DNYYMyNLxq7E/iijBX4Iqv/t0nKzn9DvPXCowWVEWY77oMqhFFI8w1LbiBrYC4poS6A8ncaXdJ12ADPPosAW59o20QLjqF7XqKhewVY3ZhrjaUaJCl95YhfayhsytcoG2Xqzgof29NG3V5ftozEGWZNOkdvb5qVhr01TngHXPM4BHS/kESFzmhq5gzOVAuDSpto/SCnS19cjVCnNjerGAyFLHh80xsyd0SxW6StSW66pMrwvQasF6KogLzUfMzrG0BK0BeXJxTfVbcsm1w6RedKmz55ZLk9Lmun5wUT030KcBrI0L1rrZgJLLulY6jEWaq69LqfN9kWO1vy4PWip2dwm4VYmlkyqhlOWcKCbnMr9K22Bb587M2g9wMdu1k6ex1xoYuPhstd/q9do8V3wNYEwaBFo7R/3QA16ArtuD3DKIs5baat1b5uiREtDkSHPH8/SC98c3vHt+wXkK5Djj9YnPds/8V1/c88XLd/T+Ge8vGJ/irFopJo3QOqahkIvnm+fX/IevPufre8+UJysWeLFmAd6CrFCDslQyMam1PE5p7WTpHV4tSesceOnpBmG/A7JVvhOCdcBVOuerxLmvk61Kb9t6UCBm6qDONBlpUUfWRNLCdnjgz978mi9P13yZt8RS50nJ7DcDHFoP6wABAABJREFUNxvlegA5j2z7PX/3m/fsXr/hj/78L+j7PaNC0kguyv71a/a3VxwPT8zjyGazQZ1duysJj2c/BOseNp643l6x7Qrj+cjj24+8/bbnr1T50z96g9vv2A1X/PRVz+aovH/K3B/OPJ0Tj4eRL68dr7eBL2523O23bDbBkl7vSbmQ1KrJKfP/pe7Pni3JsvNO7Lcndz/TvTemnFEFoKqAKjaLTZFsamyZkXqS6b/Qv6gHPcjaaKYHka2GSRwNYFWhCjXkEJERcYcz+LCH1Q9ru59zIzOBAnpgwNMyIu65fty3b9/T+vb3fYtpHBj6Ezn3lHxYmLhDPwKBIhD7E8Zksh1w7gpHwIjlsN/Thi2SC6djT8lHgus57geOwwNv9yfIhqvrj/D2Bbs1nMYDwzTy6vQ1rWswzjFNE/040Y+jZlIUoe02GgDkCg4JmFLOYHrKEHRXO+bE4rtYRyNkHq9ngF/XNAVRqaXoPnBeUHv37R3nPTpc0YFSwTdN2yKV+QRUEP98/jxfy2Jidz5KBdp0fLO66A+GKU30w8g0jbRNyzgO9L2yZ3TN5fGhxTqv6y2E4/GgErtBGVHGKKgQfFM3DoQYNTAdh4GU1a+nH07knPEuYEypmbocccp1vs0cT/s6X3pSyjShxVo9xzrD9U3H6dSTS8SQ1KDcgzFrxkGlNpv1lqZRX6eUIt57mqYFq0klcla23Wq1nmtN4wKra+aHhweaEDDWMAwRayPOBb1vzqzXGzUcDg3WKfBiLUxx5HhSiZHvLac3t7x5fctqvcFQmKZRyxQTPnhybkkpE8IaKZ7TKbJeaUBdihCCo0jCA8YJ43hCRLQujGDshHOGtl0pIDZF9sMe7xS8jSmTM0zTxDRpRrzT6aTZ5iYhpR5nIt6PtF2LD1bfR0wMw8R606rZetGkLJLRTORGzysiBOd0rLEOa62ysUpRmZ8xjNNICCrJi1HleGA4HA4E7zkc91xfX5OmRIzCm9cPyKbn+dU1Bg2MZ3WBGPWHLMuO+vs9E2dJdfNZgfLGW1xoiJPGh9Z4gg3sditSPHG6e01oQ11fTwynI9uuxTlDLiPiEsYliBDlhKGjGMeQ4hyYgHVIcdrGHDgXkJRxznNMR2IxWKteZ47MetUxpYHTfYTQsmoLORhKgGxHTAMmNYzTgBXLJnQIjmmKNK0nlbr5lC3Hw4C1llRGjKi82ljBBcvhGPF0BNNyShPdqiVFjQ/63CNeNOtdAuc6crQ8jCNdq9L8aGB4GNhtGrx1rNoVTaNycIKuL0REvQzFIt4zjgljG5x3WJtqFkRlWGY7IWXCWyGhWTE1fq3raduSiyWLehsS/DLPWKPZJrEJSZBJmtEOj8KkCckjxjrEFGVlYchVbZOK1HXLrECwdXNzxNuJIgPG+CozdYg4bCp4HVoxniq5BEzCOqMyN+Mq00o1RTrkZ7AeX5xurIrUchmSVc/iUjQeiwa8LsSZIljnKGJr8h4HYnEEJBesbZjiiT5PiHUUPE4CkhPFqr2QygIHrEbFqgzKE9mqSfkcV/xNx+8NPJ2PGTj4lt/8vmNGDZTOcof6sTlLseYAah6QnDEEp4weymxFq7vpuovKEiqeuRbn+833sRe/MXMkOT9W/We5/FHpRb83tiDMO1h60eA8jdfFkZkzVlWTcgx1ET0HgApu1NARbzWcre2mAgEsLDLhHASWojtjeRm/TX3aOYceeIMGd0Zw1TNBGUdajvPTQzAW6wSKOQfaVeK2ZMgyFTgSlc8YUMlGFeqVWmhr0Ix4NXiAmc8xB9Ayv/L6XmSpcFlqcg6uzz/PjLtZKiaAVL+J+ZiDyhnTeFdCOQf/poIsM6A1M5qMqVbH9vzZ/MWFvcHv3z7+Sx+XXVQXtZpJJKN66Qr9Mz+RGjlXCMbMHUkBEufUl0cw9bx63aXC0fdtSx0wZ+BSr6t/15ZjquPPzGzjgk1nzxxEg7LP1KPpgpWDtnnNAqlPdwZpyvKeZvBqNgC3NTvUGaWojYFChSv12a3uyKlJ93wdjabM0odmo/L5Xra2zVp/Fdid616Zc/oFW4HPOfuijo36eal9be4Ds3RubsplBmAqU88aq0HJBUA1G4jr+7JcMgEvAbp5HCql3rfW8yI/XbyT5glOFIAwBrHmzACsfxlmwNrWersAp+aHQsFmisrmKKITaqVMi7CAnDObThYA7wwbGRQ8n4FkOVfa0qIL8xjFxXv/+3EYa9QgN0Wmk8eUgDGeKTruHoRx6EjyhNvxGW+HFftBDR8bjnzv6o4ffPAFL64faMKheixV6aPRDKam7vzpYkcDvlQSp7HlF19/wK/ebumz0R0y5+tCrab6zXOqbJURxKKLQmUAOoJVU1lvdX4M6M5suypquloMzgQNsC0YZzQbZs3QaEQwNgCahyVn1JOs6By3zPoV4LRAsIAkvvfsFf+g/5D+i8+4ix4rwvWm5fm24cnWkPu3vPzdr9iur7j68COa7VPo1kQMRiIyjeQ0ISbj2oYr/xyJJ/rTnsPbr9ldPWNMJ+5fv+ajp1tWuxuOpdDnxH6/p2lUWpTTwPHwwH/891/y5A/+iLZd0a6v2IQ1m+eeTWv5/O2J4xFOU2Hfrbg7ZT56uuKzZ4Fu7Wt7zxQxahQdlVE2jQ+M0wGD0BhPlomYD8QIxUa872ic111yO6IZgxtEMqfjPcN00uxhxfLwsOdwPDBMQ51QO9I00fo992+OjKOmdDcijG6sgWNS09xSaI0Dp1kr3dwTDRVk0b6Yqcz1UnQ3TtftdTjQjj8zVV3d6DRF+26WUqV2NUvQzLD8e8B4ksrwUiZsHd/qz1T3zRkUvxybHq1bRJYNvGUzUNS/TIzl1J8wxpJT5jQd6PuelAveNRXwByFXc1tXwRNl5iOWJrQ4bxiGI8Yo+NT3A23batArEyJqzj+Oo5qNJzXe0HEg4W1D27aMY6/93jVAIfiAdRC8GuLGqFn5/JxVMmqm6Jmp2wRNVjBNg5o1r1ZMY0+MUccDa5ASsd7jvCWEpgItEedNBU5UarharxnHgVKEnAuno/pVtd0K52w1I89LgiTnLUUyh/2RwwHGUVittoChaT1N29GfBgA227VK+1IihG55185ZctZsezMbJXhfrTOFqSS6VYtfeULo6PuegjCM0zJ3a5YtbS8hBGLMGBzDMNK2nY6vvmW1MuQkxJiYpiM+GI6nB7z3tE1X/ZpGSnF03QpNjtRRinA8nAhNq964VpnNIqn61+p7DiHUta5ugsWYKFLUG8wa2rbDGENrPYdDj/cNBsfrr/ekvnC9XuOqTycGKDWjm7XL2sNebES+j8eqNZgsiCSMM2DVd7JrG80cNhnG6cTDPlFy4jT0dAJiA9Y5XGM5xUJXlLcUp0hwEKSDohvu4zipr9a8YWgdOTmstyRjMNaTc2ZKGaqHmCk6hzIJxoyaDUwMY4w0rSXmrBt4BbwIxQmlaTCTxdjCFDWuLkml0KmodK5xXrPBW4u3DSVNgGCcZ0oZsRljHOtuQ+MCx1PPZKBMI11jCKuG9foai2PsB8QUTv1EypG2VRBapkIymUPMDNODsg53W6xTH+fGB1JW6Z0Tq7Ya1f9FnG6yFFFg3YqrErK+rkU9kgMZoVirSZO8B5T5b22p0k8ATzaQfcRJAus1/rUOYyK2mp+nFEjJ4J3TATwXxLSIOIo0GodbzdxMLMsms0HwFIpRhnmMCSeWUmpyK+uxplGvylJoTKOZf0W3XgueUrwGDnVMUNsXSyoZKJQ0YZs52HXYakFSAGsLViYsLbk4VDRpMcVinPpIuaYhmaJrLJRVTVEli+ra1d8pp6iWKDYvmfoKTR3n/+bjbwc8LUDNMiSyhBcXgIIGBHNAt8A8y+QpsJg1L7vVnEGnM+NJ/7eYBRm0CyZRJ2fjamBRlmDtrIe/LLh+li8+X5gENZC+DETyDO5U82Ff2RtzED6zRtQMmHPjMjWwMbpL5Ry4dOEXZAzBgFwEwHMQadDsdabSyzSlsdSFHY/AGjVIrtKFrMZ/WbQWlnRwZuaHadOTyiAwqDn2Im2Cs5YSre9g6sKwmhCbWnYjM1uq3mNeOS2AZGWeiFmKMdfVvMsxf20+zpkIz1DUu+coA30OOs9t6oIvo3VjzkGmWarhbwguq9u0yh41oJ79uqzVulje+/LHXK9zEPvX3+J9OGY8SDX5ymgpBbJYsgFx2nbO4Ent1wVmd3hDBU8qE0oWmHaWZNZ3efHuL6Wks6eEmPn7F/eZy3lZl2bGsOqHVdZlanY0V/3bSmU92bkdyOwfJec2h05kl/VRuyq4c6a0y2yGcw+aTcdnKqmRMyg2g07OmqW8WiEs44qxaro/g+Kllm+W5CnTyVZGUrqoi7luqWOh1AmhVB8mu0g2Knal2StmEGlGVmcAawG3Fkhqqa9FwjdL9S4+g5kNtcA+9VNzruJZFlPnAN1dt8tcUEcejPHMBu7vXk3P0zKLWEr1j8lFdKiv7UWWgcsuYOK8aLUzmIk89n+q7VVHwRms8Jfd+b0+DqcvaVoN+mIaamYVz8ND4M3bjsF8SLY3nCbHacpMU2Rje/7oyR0//vglN5s3NGakWJUxFmOZfWJUUjz3ySpJLYkxtvzu/mN+9voZt0OLGIe3+v5KURmeSFaWbSm4IkxkSi5kDMFavLOa9dWCtyoz8qg04bpLdF44RqX0e6+/M1Vap5s4cZ4AyDnVINlC3Vl0VtcQubZ7I8qCEKuz3c7v+UcffcFt/wF/tV+z7hqe3HS82Dje/vov+OLLr3jx2Q949uIjpGmxriMbi+SRNB443r+mKRlDpNtdYawjnZRNZI6Z4+0rjDeUsfDmbuCDjaFdrfFNSzYNLgRunr0grAIfuT/ii1//Ja++esl2s2V3lZjil7Rtx9X2BdffvyZNhl+/vOM4jgxx4HYY+Op+5A8/vOKzZ2uerTyQyDlxON7RDydiSnWMCpQyMcWeKU0M00TTZKQM9JOnkBkOR8x1AuOweeRuGBmnCZICB8fBYdng2WFwasQ6AtMIiPoqikHIaBZEqyAjVv0oC/r+RX1MpIjKBWyFm0RB+CJA0nE8S8GIIUtZwPl51VZQc1gkqxxXhCSF2bOziGDFMPb9/+p98m976DLGUuaEJmZ205zn0noYuySZhfMG7aNsd8ZU6Uddv1rtJsMQ8b5RxkwaGKcesORc8C7gfUOekiassTV1d9Gd6iZ4lWClkb4fCKEh51K9vHTTo2kDpY+s15sKUFS7i2IxJuCcZxgGNusV203HOE2MvRro5pLpWo8PDZgIURjHSCng1p1Kfn2hRKFrG7qu4/7ujqdXT/jq1UtEevUIs5nD4cg4RdrWs1qvaNvANEW8F/rTRM6FtjN4r15i19c7jifDOKjkVlaFYRzw3nLqjxirEifvm5oEwyybuohm3jaIppWvlgzOq+dLyiPWZdbrjtNpQkQ4HU/sdtdkkzTpSiq0vkEQ2rZjs9kwThPO67s59YNKA1MmNCtub28BYbPe0ARPLpmxH5Gslgd9PwBqlZBS5Pr6itOpV0C/XRPTqABkSTx59hQRZS/FNFWPKrcs3UPTKGhnLbEyqbwPi/RPQ0XBB0cpynBMKdXNKF1PpmQ4nY44NzPWLcF5Tv1IKacKgnSYrJmzTZ1r5tgGlM3+Ph9r78CqnGs+hr7HMhLsWkENb3gYRyQL0QRiypATnevo1jte3b2lNK3GF2ZNcZbGd8qcyyNRCsG2DNNElgnfWHLqccaC7xjJ+GCZTpOyPQVlr6WCcw2nPrLZtbjW4WwA12Ik4WKhCy2xnSjpgBSVrhWEEkdMKljv8JXpZr2j84GhT+QC0zQSWg/eIc7gg7YnyUqw0Ix5gSKGSKa1AeNa+jFic6HxDcfTAwYF1eLUk2NBcsC7jGsCD7d3WBLTsMaFliasiE1DsWAmw6ZbY3PRtUbjwAXd/CwZkYyzflE1qd+kJs0pyVBCoviCw2AlVDN7BQ5FLEYaLJ5S2dPOODKRUs3Mgw2UYsGokXnGIMYuUXmxmVgixVj9PILLai7vbFdjEwMkRJIC/bbRjdu6KlWJudX3agzGZuI4YX2rDHJjMKL581IueDSBGGZUaCplHM3i1+rqpk5xdZFemSut6xATaELDyq8wLlCMYYoTh+MtTgaSGZlIiKvgVDXSX191TCXixGHFkPFQHK7iA7/P8XdgPOlxyRZaTKcvNpAXuYue8RhFmCMkqP4MVCnVJegg50BKrz5f6SIwNfPVKgPnnYeWy39cRLMXgcjlP1TqpjfMOZGLIGLrAGGwjsowKsvumjVG6YfzzlPdDaAuKhT8UWpmMQbnbH1Wanwm58WDUYDL2cvrVaCpPK4/XYCZCtqc68ZRAzJT3aTMu/U+MxYsM2vn3abySH6kFVMDy6XQtQxnAGguQ7l4z2dZ3fldLeW/ACHLo7bx+LzHP+uzXWa+mB9vARow9dkfP8t3HQtGYAzeajAmKLNC9a9gqv/Et5Wq/J4d7X045n5SRCWZKQuSDcVKzVpVz5oXtkuN1nduVQ5jSq4hPQtoQq2vswzsApqQM9NwZqHM582+TYrIKwBl3QwgvPP+zPzdsgCmS2bKefhY+o3FkB/1m/mRZpBcs8C55Ts6LpeaWcNe3Ev7mQLMZrnY7El3+bTn9jT/Y/75LM97DJiea9mYubefx9PZ5Hvud8quqp5SwgIGlZpS9hJmnWVpSHk0/FZYZ3kHs/m7tbZe71IuWLPNCAvTak7+IDI/6MXTyyUYeWYuUArGuYvsqAalP509X6jtYQ40jZPlGd0lYDjXJQYqG87VTIjUe9UKYM78dFnbhVn/fyHRu3yM9/QQmTiNb3C2Q2zD/T5xOlgOp6f0fMAka4bJ0Q+RnBPX9sSPPnjDDz56yZPuLd6mC69DhVGR+gorEFAyYFTvn6PlzekJP3v1CV8fVhSsGl8aq5lhSiYXAyWfJeyiRvGNU9aL9ZZmnvOM7mjrZg6YlHhx5TVDDUrLd169RjRfr7brUt9ZTBMl5bpH4jAuYHFq6EpUMA3OiQaq2b0l88H1G/74gz20HxJWDV2AN7/5c+7evObZJ9/n6Yd/iGsCqSY2iGlE0oE0DcqcyLBq1lgXGIcTOY6QEo0D3zXsDz2rqzU3zz/Gth2r9ZrQrLGhYbIe3yRs8ITdFT/66T/j66+/IFjomg7vr7m/f+Dlb35O3098+uEz/vmf/Cmv9oXfvekZouHV3cR+uOXl7cQfvWjZtkJLxNmW4NaYLhD7vfqtEIlFd1RVpmw1CIoAV0y5hVAY80gpI3HSrJQ2CxiH2AZBF+5IBbuzMMmEdx5KXvzcJEcKQhxjpQUL1uiOck5Cdup7MjMpRSIiRWUFuWCrN2PKoqmv04gVIZZEjPP4rdcoqZAkEkVI40hJWeU8FRDLUYD/+//KvfJvd8zPU6gg0jwpiCGLAhs6F2mW0mVx9s7atsh5/TUDQohhGvVdxpS4urrizZuB1XrDNCWCD5xOQ11PFpwD7x3rVUfPQEoa0OaSiTERQmC73XJ7e8vxmGmahnEc9Z5FuL29o5TCer3ieDwu7HdjDU3bcDzudU0bAj60OiNYCMHjnacIdKuG1WrNq5dfczxm1qsVzhrCegMCb97cEqeR3+0/X/yUdrtrjqcjzkc657i62nI8HohTxAdf1+bK2JnGjPOWlDKn/kApCi6pzFA3RaIUvLcc9oOaqQ8nxnGoadYLOUOaMqfjG6angjWOh/t7BDXIt87QGI8Uw+k4AIY4RlLMDP3IZrulXXlWtuX+/p5xGNlsNzqXO4sMyn4ax8hq3XE8PmCHwGa9YbPasT8cOIwDTaNSRQ2WhVIs41AITeDUn2jbFh8cuSQOxwPH45EPPviQcRi4uo46/xZDHjOnvq/JWyzbzZau64gxcn880jVtnfPVCxSgbVvuH26RAVbdWoH+rOw07wMhOE6nA1e7Hcf+wDRpPahsspBEGGNkE1SSPG9Kqdd+wVbvz8uN5/fxWPsr+pgRCmmIiNc6MDlT2gnb6Aa+xaphuLMUUf+9HIWcPYUJsW3NLGwYswIDkgsyKhs1BWFKBeMKYiPGV6kLI6XA/XFUSVjOZCDmzDhFPJnWBWUz2YC0gZQ0M5k1roJNDlMqMNNYcI0CAVMmBINYoBha30I2dKsN46RAedMaXKMeS2lSWa369hmSibigoJkP19jgkM4TvBBPajAeGuoY4Zmy0E8jhULjM4YTUxpwOA6niRAMkwHjBmwrxJKZNhOb4AlemZA2NJrYxIWKERRl9KSa0a6aY5ealbmUgskz61O9LFXNYDWRkBgiK2DQNYmtfsbWY6ukH2sgQCIuY6/6e4ERjS1KtljRjZhgG7UQqOB/tjVBmm8weCxVUVFUypakUCpFxBhHwmGz4FzBMoKZMK4hSyHnqE+tmju8cwTTIdaSZCIxKnDkW3xusFlZUM6tMa7jenfD05tnuKYju0DMwt3ta053L+mHrxlLr7t4aoqFJWFMo7iDWGzdABSbsI05Yxt/w/F3Ap5mpsz873d+ywIIvYsDCZhlR3xx/1AWUylLIHexyY6ImQkpS+A6e5BcXPkCQzoHbt9V9vOpF0HdfJRyBtLQIMnVQs0ZduSdKO7dwXIJqqjAlK+77EYZkLNcpUrQl+DN6BeW0HFmb80eLpflXlxozFznNbg382eg2psLAMGcvXPOsdk362kxFp6f7/KFMPvpPPrGN/79rpPWNyVuZ+BpIbh9S1kuTerngPi7yvzoO+a8O/hd1/zm51Z3FR6dM0ubHj/io+D+78lRa1KlCiKzwkE9deq7tfVPqUCGpfZ3q5g8aEYS0LY9f1+p4JU1d1k/5d3g/4LhYozqpau8zlZTcb2neo8pwDOXHO0fcmm+Wn+vuo0KelhF3mfgBZXJFWZPtTOKofJBZeSUen0129eBX2oQgMzfnUHOx0iFMbNORHcuFGDhLOV7p82p4fqCttRuXIP4S5iulr9UtqJWbvWPMigAWMHwGUzLtf+aOdEBOjksQ4XozvMMqHExxuju5tyuzQJsndlTWZMy4eo7ampWpjNrTYfVOkfYxSYdh9aHtQ6s1YUns9xLx3oF+Cr3sJzf0SXgZ5YxUrAyZxDU/xcwDSjmUtI7v0u7tL9iFmj9G9PA+3hYcYwZXBC8fU5Kz3k7tEx8SJY1wyQcciTHyJOm54cfvuGHH37Bpr3Dm4yxkZKV2VRMVs6Z0fdWDKQ0ULLHGgUGxrzi1/cf8KuHJ5ykJVfgOVfJJiYi4vHo+7NmlnGCCw2NdeB0MTT7gPmiCz5rPLEcuVpPRBk0a0/NZANQbEJMQZIgRnfV1XuCxR/MmoDB1vHL1v5W5SA568K+fne9avngKtKnW9bXL/j5z37J3e0dn/zJT3Gra2xoEBypREhCyRMlJqDBBgNNIhkhT5EyJSgG7wLZGpxvebJa8/LlPfb+no+fPocQwLeIa8AEjE3ENNEUwa/WbHc32DKx2qxZ+YbPPvmIvo/87uWXvP7yJb/6f/0/+NN/9A/53/74J/zuVeHN/USfM1+96TmeIrsu82ztuW7W4HqcCBJWynDIlnbVEUft92MMtL7Du5ZUPLkUpqOpjP2iAbgocyijMgrBaiZCK9X7C5V4CExFNNNYa5lSQeLEJJlxmBgmaFHfqf1pIMoEw7j4xZWYmHJiSIncj5rdyRSmqLT+nHIFm3UzTnIiAxTwUhhKwi3sVkGyU4kZhfecLAHM4yjLBsjM0NYP7bL2mmc8MbNM3C4sWb3OPH2c56FS4Hjak1LkcOhp25bd9oo3b99Wf5hA2zYYY1it1uz3D4gI2+2WaYoYIxyPRSVVxhJj5u7uDu89282OruuYpolhGOlWK1arjv1hTwjqP3ZzfUPwDa/fvuZwOJBzwjnLhx98xFgNfXe7K4wRxqnneDzQ9wnvVux2TwiNcDwe2e+PNE3DMCjIteparp9d1WtmTscjfX9iu12xWq/rWi9jjKXvTzjn8UFHdpXcdYSg12tCy/XVEzDQ9z0IpByBQk6RYTjSdiu22x3jOEHSgH2zWTOMA9aqTM15x6tXr2iyyn9TamnbHU2jc2CcMjc3T3Stb3V9pDK8lvX6mtPxyLNn15r98XjA+4ar6y0pCiV5nHU87O+wvrC77kjR8/BwYJpGEOHJzROMbcil4L2hCc1iMh6Cpetu2Kx3dV3V4GzDGAdSgvV6izG60XQ8njgc91rPqxXrzYrtao1zntPpBIh6B1nHk5unTNPE6TSXWRlRx+MJ7y3OW16+esnNzY0yeHJh//DAw/6W7UZBS1kJGB1zltSUXCga/oaN4v/Sh2lv1GzaFMo4MsRemXWNpxSLDELTBUQSQzzStQbv1WtHbGHMd5iyB8nY9oaHY8809vgxsGrXunlbRkQS682OnFVGFacJJ4nGZZrGEbYtx159ygaxnO6OmFYTBjR+Rc6wadbkkgibhpRQIBVHmRKtawhOM0RH11CM0Pia7iUEDtNEsw74KVNSRHD4sEXMRIoRcRYfWhxW2ZDGYptqEG8cyTRMSSAbvMD2yZZ4umOsWeKmWPtSu8JZh3cZHzJPnm6heKZpwInF+YBvPYfTA9kKJzeQekvjW7qVwdhI26is11qv80AWsigzad226lGUJ8QZbLF4F6oJv9XENbFK+cWQrCXFUG0yehpvybRIseQsVYKWWDAGkyCrQfcSD8ikCDsr0qSDfTZqyF1EN3GsLwomWt0kNNFUEkChyATGqfytKEhnXKjWAqWqpRLZjDQepmgxriPLhMWw7tZYHPu+kK3HuhXOXmOkwRnh1VdfETrDsw+fcfPBp3z06Sc07ZZiAtZ7JEfevvqcP/8Pf8Z0+zXBQDGJ0Sa88eRpxHhDZlQGbXKMJROTJnX4fY6/M+PpO48FRKg/z2BS/XOJBXWeBZTxZAApF6Ko+TpFZW95Bp7eAWEuj/N9Lj6b24Kcg5dLT5hH37wY9DRAstoAKjo6G1vP3zX1vO+AMeYIDCrgpIN9qUp+DaydYdmpN1B9rmb5nTwq66WxsKkBqP5QYShzluLx6M/56vN1Zs+avx7A0YUPF7VaA9536nM+V68/v2PDt7+lbz/+pwA4j0C5GRj8ay73XSCYWaLP+u4qHfhvW4b3/RCpzl8LIDS3jXOfUOT+sp3reSWXR4COMp4UPFoMIh8BMhf/vvxXBWbMBdBnzBnSnPvf/P0icrZfqmWxRig15ba1+kyz7Epfn8VRd5mNxRNqsR+9aQxV4z3Xx3yNel9jVIPtH/kP6DVnU34FqA1Udpw11Tx7ZmBddpWF8TNLAmeADbBnidwsvdC+Wvs6c0bCMlc/7wK/57F3hhMVVCvCmfEyj6fAbJKmEszCGSj8NskdFaQzXLh/aZsq5zHh8tnPoMBZVm1qZidQgMzIjFbqLmCpINpccZqq1pz9gyuoZ8RwDtSowP0M6gkVEdFJ5hL0RIGubODvQbwKQKxtZDw1DOOKQ3zO6AJ9tMRJ06NTep6sjvyDD4/88Uefs/a3dTGogKK1pQKWNbOWsVASRSZKrrI5GUnS8vL4CT9/8ym34xbJDmNhTAVjC95odrXGQ8ASUaNnbyzeO92F9EYzsQAwZ3PNZDK2gMkjmyB0RojOYa361ORikAjJzGBqwJhJ2VbVnNq4gs0GhxARQtCset5rWvpS+7Ekoay29NP/kX/zZ7/k57/4j/zoxz9mipE/+of/iFG22NCptD5FYklQIiUO2rcbS04REZ3niwiEBmtQGYTfEtotzhtuXnzMX/zHf8f9/T3PP/6UGEdIUYEc17BabRj7yIubhtWLZxzvXvPw1W9pnj8jtQ2ha/n+H/wh3//kD5DU8x9+9jO++tf/HT/+6T/mxbNP+OrNwMPJkkvkoXecouG2Tawl0EqmTL0al6aApaGYj3FGzQViciqJkYybNK26MYmcFEhO08gwqYm6NYZhHIj9QJKCMzBOI845plHT2ceYyBLxBaZJ5QhxLAqcG4hTQgikPLA2hpHKQIuamS7lQlPQ9ODWIWRc3WHUfl1QYwSw3lImzZY4IfhiyVRAWtTvU22h3m9/GADNDOuqr4jOaWfwqe6WF13HMHu8UNdTZV45mmUtXGYWukCmaCaqIiq9QaVzUgrjMBIn9UhyTgGa3W7H9fU1x+NRQZkmEEJYGK7WWELjsdYwxYGUpwoq6zz35u1rdrsdAG3T8Pr1a1brNev1mtWqYxh6Yhy5vXvNhx9+TNuo7G6/P5Jz4unTFxxPe+5uH3j79oAxnnHo2WxWdG1HExrWmw3TOPKw39OEoJ5NKWOdIwRLTONiLG6tgjsiwvX1rhqdq5+SlIQRy/E4MgwTUxyQYmiCZnvM3pISPHnylKYJ9P3A4bBHsrLxpBzYXe1IeWCz3eFHYbVeAQ7nHG0TMAj3D/cM/QnnHf1womkDq+0zSo6klDidTrRNIcbMy5dv0QyxgsjEOJ5YrTZ060BOmSdPbvDB8/r1G46HHuc8280W5wyH0wnDBKZwc3PFJ59+wK/+6pekKannU2jZ7lasuhVfv37Lm9f3hHbF9dVVrTOVAzrnCUHLiils1i3TNDId99UDDD7+6EPGMXJ3d0AEdrsdp35gGAaaNnB1vWUYBt6+ueXjjz9hvbqmP406TkyG/UNPcIZ+mJjSiLEeR1vtR+r8bljWQ+/zcdvf0Q8JZzyh8RSzwltLaD1pUinS1B/ogmO7XavxvvdMOZLFEELL9U1DGwKjgA+BrlkzDYVTH2mCpe97bF/YbRxpivj1mvthwlC4CpbGCM3KEwc12jYpUhqYsmbAG4ujBMAV2uAoUuiaFWKCMk1jIiWLTYlYEmMaaUNDikJKmeE4MpRI7y2tWGxS836MrrOHaWAsQvCBm82W4UGzUrZry2rbsr3eYdyaKTr6/cT+7o6mtXTdBhst0zSy3V4TVg37U6Q/Tdjg2XQN/TBxGibN/tiuGcaJbWhxdDQIIdYNn9Ey5ox1gkkeolB8Cy4p+xZhOg3kxilbthh819I6T0maIc4ZjzdqrF8AserdBYIzK1LKTCXjgqonpKjfUdesSKVQyojkoAlUvI7jJY0Er5s3ORpwnoglJ4dxosCSAecaJIpmqWsMdhxRFndDMStSydiiW+XFGFwQSioYE2ryp6ji1+IxdFhpsLbDmOpdlzUxR+N3eLPj7nbg/s1rNl1Lngp/+KPv84N/8A959tGH7NbXBKcG79YBFp5erxiOe/783+0xZWDIE8bU+2fB2ky01QcLwZpAiYmc4u/Vj/5WwNN5t+UCzrgAc0qpQdLFLvK8m32JUcjsoXKxYyOC6viXc+rfRf09dNE6sy5mb6nzYZdg6Vxa83uiBhoXvgtYmQXYmZczc9B7GVyZd76pQZpSzufnDk5321WyZTB+BppkYXMs31+u8d1lN8sfF5IXfeL6/W9Ka9593hkcmgGtbzLB6vWRi3f3+L1esoIeQVyGx15TnIGzy5+/u4Tfds67ZfufDvZ88/uzRvUxeFJ/dVEuliK/+1zv83G5aNV/sbRnzU5YYcsKwij7yFbQFawpysWppnpzVkWMOZtOz4DCRf0gamIvVJZJZQGZutg4S1SrbHUu7wwgVirkjE08Krd3M6StGZOcBjFzcrk5I+W8m3y+gFRfpfM95tcq9dkWfyXnlH3FGXA1lZ01g0am+jwhVj2fzNl7CCqtvJZTQTVzgaTX56ljlsDiK7GMjbXRLZnmZO74MxB8IW+7AGuE+T1V37U5UGF+Rxd994LlNB/6KmfwD8Cq8TRnPydT28m5jZ2fU1BwSNlsSu3HqizOVHmnMpHMUiy7yJHNIs3DqCxBAbnKRqWyNmobVK++OtZalUdll0GqR4yZ5ZNnsO/88/t/lOiJU8fdacvXxxsO05ZxtIxpoCQhMPDh6shPP37Lp8/f0tg7hIS3DmRE352tQaU+dy6jgvVF22gRg5WGw/QZv/j6D3h1uKZIwFTAr/H1nWAxdoXxllgKTqTKyD2dMxjvNY3x3BaxmJJJRRkvSpg68uwq4FxBSm0D1Wy6GAV6s6FmHvQ4m4lFvVZsSTjnSQhN8IQQ8NbjvNNriCEW8F3HUf4x//oXW3Z/9N/wTz78B/zln/85Tz79FOMCznpigjHvsdnXrLMF4zy2+q04UZbQkHLN+Ocw7Yr16ilts8aEDm8EZws//uk/41c//xndaoMtA2/fvuLTzz7jyBXGrwgU3rx+y2cfvyDcPOM3P/8Fv/zFz/ln/+2/4PrJRzgy4zQRpeWn//Af8/L1a/7yZz/n408e+MFnP+DVQ8Px1HEaE6lkTtGTmw2TSeTYcvv6rzi9+itKjAxTIk0PGDGMUT2/cpkwURhjJslIEasL3JKrhYACF1KEBsNYara5xUcDUgXXS7EEI0zFYnwhxKRyAaqHi7FIzkxWMyVNFnxdyxWBhIL1IpFiDSIZK+oDZo1mMyoimCh4p14SoXpHapAQUTkEagZb3v9ebKx5tHo1pbp7GFCJ6+zTqRNYJbKS08WGjyjDh2VOgnm9e3V1zXB7pG0cpYykONEER9u1xJgqiwXW6zXGwG9/+1uoXkWH/almizJ473Be55xS28P2akvfHxHJuODppOPhfs/xcOTm6Q27qx1t01BEqj+UxznHettwON5x2DtiilhrGMfI51+ciFPi5vpZNRIWTsdAjIVxzFhjGftE03ZqmF3NrOcx+3iasNay2Ww4HY4459is1iDCcBp0PAieEFqGaeD6ekMuhb4/0STHqlMz7Jx0fdNnGAdl92w2G7a7DTEOSBG61YY4Zfq+54vPP6cUy3CKWFNwPmOBwfWAqDlzzrRtIKeJu7dvsNbTNB2b1ZamXfHkyYq7uzfEqWCso2s7rC1M08R46sE4Xr/S73Vdy5Obhs12o1nu9gdyLuyuOoxJ3O/f8urVLTllfBDCqlVZ5bHn4W4PRhhHoWm6ynBUuWA/DOScmKKQc6Jk6NOEq5Ks+/sj4zAwjYmbJztCAzk5vv76DTH26vVVMqfTgc1mg3/xIfuHA11rub6+ppTC29e9JiSyjv3pSB9v8G2DkKpXrCYhMJXkPXuAvq+HxbEJHdOphzRgDSrjPCqr09tAGxqKZOKYCX6FFcvK27rxZ0nZMSWdE+2ka+dV6JSpEwshbGiCoYwD3kHrYbdac39/x3EaMK7D20Amcf/2DddPrrm52tEfLEki26srXLPh2I80xdOuW1yx9GNmKolxiuzvDjVLmyBRiFiGlMBaNex26iF2ykJbzatzSZCTknl8ICbhKEemvicOJ5p94Vl5yvVux9VVy3EQhkGwbSAlmPrElA2hXTHFHtdkVo0lTYYshlQsUxKGqce3juwN/TER7+9pGsvKe+KUOMQeawJt09K2HVkyDw8PtG2j2TAxFArJNsjkmIYTBp2fnBXdaHMZEwRrEuvumuA7SskEH0FGLIJbrUAylsyURpCClYY8ZbDqF5tEKI0joXYBwWvykhJdXZdGChZrGwyZCR3/yGDR7HgpFsARfAdGkyz4Ki/PCFIsU65sbzEYcTiTcajlgSBgCtOYMbbFNx2rted03PPlF19zvfP0x4gxge3uhg93V/zhH/8pH3z0KVdXO1ahIRiH87o+Nk7omg1//Id/xO9+83Ne3d3Ty6TgIhZXrM7bxpCtYSoJVxMnuP+5s9rNkq8zV+Ax6LQwE4q8o/Orkd4FyFSRiwu68BnQmI8lQ0kNmErdra6hGO9SUS6ZG1q2dy74nccMIr376bxTP8te3vn9O+ypR2VZ/tMsI4oUG+w5bcs3Ap1L6dm7n13ec7nvUmdmAfIEo54bcgESXjzjd5X/XYDnMUvlnTJclP6x/847QCAsbJTLe3279O3by/WobBdgzyUb7BHDgjl4N48e+dvq8VvBonfYXueg6Z3yybnMf19AJ2CpE2NUvppFNPg3RgMPlH4tRrkmMwQ0YyQGA85oZp5SmD1/tEIqI2AB7RYx6IJtnMW1LO/IXbh9GxYsgPlrdm7pZjbYPsNmsyRvgQlnLMaokfGcVWZm7dhqlK+ZVMziWbb4RFmHqcba9qJcUjSLkt6+Sm+XMdBWU+tzhgkoF95HsnjE6UPMz1llcDPoZA3WqckhIjVNq6tgm9SskLZ+JrpQK1kDlDq+IDpqzWadl71a5hozFaQy5py6u54/e2ddYGGcbdzOzKV6lzoez8DdDFxoC1AAUfuiNdWs0jqsm/9dJYiVKWcF9RaoIJbhgmGCvvfZh+oSfFyIUpzLudC5qlfBZQ/WZA7zdFRle5eO8+/xkdNPeBhXvO4b9tOGMRpKSpChcz2f7u75rz6948XuK+CIIaKsiVL98kWty4pFZND3J5qFDnGI9bpgKy/45ds/5Lf7j4gmEOY6Nypzc06wLpDTDDyi8hanHlDOClinLIQqy8uiqdhLLIwScb5hE4TrqxYRS6ZBSlQT6iI4o4tosdr/co6kqJnyjHe0bUPjGzCCty3eKvOglLJkOfNhx+R+wH//H3a8PiRSGXn5i5/xh3/8fW4+/Zjb40Q0jbKpiyVJ1oWm1c2jvEjrC6n6jFkbKMbTdC3Neof1G6zTurXWsL4O/OCHP+LzL37DZt3xm998we1+4o9/8o+V7SK6YL/d93zw/An/l//r/40xjYxRvWRab3E2M0ZLFtjurvnBD37I2zdv+d3P/iMff/8HXK+uuT9qRrA+O3KC3njc6nvcfP8F2+vP+OLn/5b7lz9nf/+GNE2kMQFZd3+lKEBUx1qXC5FcN12M7m47gyk6T+aFtVbft9QxVByx9jOTdOy3BkKROq5bss201gHVgBqqV0ZZRihnNctPFnBikJLAqGeGF02nYCRgigb4knQ8FhGsjIB6Tjl5NBK8l8e8QSBzxqB5oS41rbw5r2vmoW/23VPcqVolzOmNqWOgaPATC/T9wM3NE97ef83btw/c3+7VR8fqXKheTQPTONTMTurtt1qp1KfvD4Cw222ZphHvG5LJPDwcyFmzWomo+bTzlmfPnyOSGfqe/jRwdXWDdx0imeAN97dHnAs83B8pecJ6h7Mt1kVC43nz5iXetWAcTeO5vtlgMFXW9YBxG0ITSDlydXWFtfBw/8A0JU5Tz36/58mTGx4eHnDGsFlvcM5xPB45xRPXT55wOp0WqZ6IUHJh/3DEWR1LVqsOJHLc94zjoGyWMtXMeIHTKZGT0LYN290ND3cPBB/AGJpGDYTjFLm+vmaaInd39/THoW6MqTT1wETTNmy2wv39PetVg209OelUPo2R7WbDbnuzlLPrOm5vbzkc9uwf9jRty3a3Y5p67u/uORzv2W23rNc3iLQ4XygZ7u7uEVFj8pgmQkg87N+Qck/bqpE1GF48f0GWxDAMldEYGacBYwzbzYYnNzfEOPHyq69Zb9as2h3b7ZowJfWryUJKkdvbEe9WnPoTL1/1DP1EKQ3jMNIfR8rVmrbtcL4hFdFM0VKqNch589u+53NxvD1oZnDnGKdJ2ZhGfS+32zXWNUgSUh6Ycs3c6hzOV0/eYpikgLH4psWYQB5HxE5YV7DWq2Ss9EwSGfYnrsRwvXlGe/2UV2++po8QyojvPN3Y4QmkqJlOTfBkk/EWWtvgsjAcRk4ykYoC1oWCXwVShBhHomTKFFmFhjFO5Kj+Q64Y0hjJ3iPWMkXBisVlzYouRRhNJhnDwziwyp6nNDR2jTWORMQ2js31htxPuKYjuAnrJqyFUQ5ICqzXG2JOpKJ9bbu6opQJIdFsWqYIWRJxGLEC7XbFcf8AOZFSJljDMIzc7m/ZbVeUNLG7uuZ4HFlttvh2hTXCcDphJGFMYcwHitXNitgJm9U1iDClkSY0eAe+C0w4sAXrlIEtVjTrnBQkJtRV2dNaD0SNV4wnJ0MqEfERxNMUj6HQWIEsGElgM0OKYFek3FBcC5LVzFwKtgjiTc3UXMjicDis9eoNlxPGBcQHxAQ9PxlEHId95OuXe15+dYcpa3ZXT7m6ekK7Cnz46Wd8/MnHPNnuWHUdrXfqKw1Yp2v6LPDs6VOef/ABv/36lxQxeLuCFPGh0Tk5RaZ0oNiGUFUZ6ffcwv1bAU88mthnacwcgVdIYg4G5kBrWbKYi2sBy7x5DgrkG2C3YY5r6hJQ/7vIVFXPWhbW8A4g8s0neecOFV44x7MX553lLqb+tESKXP79+Mg1spnpowvwJudAaZawzXU1swzq0u7MzvjG5c9Q0lL/M663nPtuyCmPvvvNC79zE/Ot/9SfL0AX87g51Eud/Z8WcGZ+icij78w1aOozXBZ1KeE7PytYKRemy4+BJHO+6fLFb7pSzeWo7evbwLB363BGP+Yn+nuENy1HNUpbgA9LzeB33lk9M3rONXApqprZPmJROmc1SjVIFUaAkdknqEJXs0StMp/mjekZRzLm7OOkY4jgrLvIvvZOZ6+Ig4UawFRfHzkLtHI9efYqugQml/LYi0YnStc35gIUqfdSI1hZDMKR2Sx9lnVZrJWlH5qq57augmMzEH8J6FYWDzVgNRWcKjUoq15+Kl+zFtBA3linAeJi9H82SKy6DTXiNqYa0Bbm0VeW+7v63XlUOzOizjvKXNTdDEEqtKiX8ToYLO2mtiXrl7F/ltLN9WSNY7b0rs0Bayo+VIsjRgNWKjPKzmC7mbcCFOizWBxmyQrK3ErmDH/nxqLvxOldNdiuOzsV+DLGfcso/v4dXxxecHcKPPQwTYLkCc/ITZf43s0DP/rkc54094gcKYwYI7PdNgZfAWQ1MRbRTQr1OnZY46rp+g1fHH7MX779iEPqMNbWvliTBxhluWSU4VPE4JxXoKGy/gSQlEglKahVNOW2Ai9WU58HxwaDMxPDNDClY21zWQmOomO2yZX1IoL3DaH1VRLk8dUU1NYxLOeC5AQo2/CYn/Bv/8Lwu9cDbrXlt//5F7Rm4upJx9u7W7J/ShZLKRGKqJG5ZLwYSs1/KzmCRARlT1jjsN5jm1DbqiDGAWq4ahA2N0/ZHh84PdzzT/7P/xLfrMB6iik1m5llGifGPnO9ahViNRqYBIlsuoaYC7EY+slxfzvw9OkVSSxffvU5Hz078eHqGr+J3A3C/dgypJZUhGy2+Cd/wh//8w/53p/8lFe/+QVff/FL7l/9jtP9W/WzEXAl4ajjXBZCBa+dqdlOrcUXCA6yyZpJZ5mLK2ui+mnAvK6p7e1CnutRf4hQBGc0YHGSEWO1/VGlm9ZpJsJcQX9DHbvmDciEyRaqNxkiGJxmAcORDQTz++22/hc9tHMg5GV8FjJiazKJXJBZPlyZxHNgfh6Tz5YVIjMwlesa2NI2HfvjnhgnNdnNBusbhuFEKRHv3XnzLmW8D7SNej/lnNQM3DtCCMQ4MU0jm81O2VKzZ6ixszUi1hlS0iDbe88wHjGGJSudC0KcMpv1Gtes8c5RsoIcbdfw5DrQ9wfaruF4PCrAlXI1QLfc3t7jvSPFuMjYmkYBmGYcmeKEc46rqyv644lpmvDe07YtM3v56upKJYfTRNd1HI8npjGRxsQ0JnI6kEtazMdTinSrDoPF2YamXeNDgzVC3/ecTidNl17rzBqD8Y77uztC09A0AWMavPd03ZoYNVi1wdC2gc22paSItYEUo2aSI3PqjxXU8xXYSTjnePHiAw6HIylNpDSSc2K7XdVntAzDkVxGckpcXd3Qti3TNLE/qH+T946ubdms1yr9stpuxqnn/v4Bax2Tm5jGkc16S9s2HI8nhrGnaRqePn2BFEPKmWkaOZ0GEIuIxftA17WkKHRdw+Fwx7rbIQLjNFGKpe9VYjle66aDXdYG502+7/JkfZ+OpjHYoKnoE11NSiQUIjEp8wNjcKHBuYBxBeMM67CC7MkEpunEob9jZQ3r1ZZRCmMasEETS41jz5RPbK46Spl4c/fA8ZTZ3Vyz2V0xxZG3X73hk+99BtlwvD/hnaGxgX4ckQhDHhARGus4Ze2vzjtssOqIVwO5bDzFB3JJTEW3K1NWYKhxAbdeUVIGivohicFbDxmGcdL1RMmkqRBJlCIMw0D/6kQfJzAB5ztodVWe88TheM8UTzSNq2vVAYylxIS36NxiNZuik4KkxDQW9scjN1crjuNJJY0iTP1ACBOSAjIlcps4nR6I08jUZxgnTBPI1pKl4J2hbTzH24nNbs39/Z7JPjDthBB0TCxjIhpYJQ9NQ3QGY1fYmr1T0LVMwePF4DLq44aQ0aRkzpoqd/ak7NGNPd0gcBbIhgkdb4zYqjgpmrGyqBTVCuSUEC+YrEk7VEHgdM1qLTEHnFlhi0NiYhxHgutwJtCEKz75ZEvwlmdPn7G73vFweEvXGa63HbuVrqOCt7i6KWEMYI0mbNm0PHv6nI3fcDjdYYOCZcJIEUcujZapWFJWuT3u9+u/vzfwVJilKQsXSGnas65+BpokcwYENKC5ZEBrgCggTgeuS+DpYtBZDIDnDGVLNjYW/xk9T4MnU+nd9dMLxtMl4KWT+xzkzrHlY3DlDC5QF5/n31R2ERegmYFvbrTNYJP+rwuE2dvJ8E221hnN0d+UM/Bi1Hy9XAAlj4qJ6PVEatkeM7QeFe3iO/NznOvsHOA/Bmke70BcMlIuana55fwKDYKY/M55lwWR5Wvals5PPx/uInBULK/KhR6d+01q7jfe5zv1/c3yzE9hlvdwedUlY9Nl+eRxHb/f06UeZ1mYgitzBsQFU5tf7rwonftHBZtmFuKcXEBBltmPY+6L795R+0CpfWVh7c1YFMKcZc6a2WBYPzPmov/NXarW+7xYycuuryxZ9dSbSyfxnIsynS6AyQW6lbP5NMxDWK2jC3ZhxaU00JzRkhlEsbWDcgbRqEG6MxbshWSvgkGX5RcjZ3CF2bDdLOOfQRQVtLXMRZlQs7eRdRYrAqLZvkRsNfu+HNtqYF4rUXfdayDD5ZaAvq96FrPx91IXcpb9zVVTlndVNyIq6KYyY4szleXkdLKc25jUgOpsIK51KsYruGbshWhwrleW97FI8OZ3WoOyeawwRtlSNb9R/d3MYjxL7UzNrPctg/h7d7zct4yTZZx0i7yxiWernj98sef7N69Yta8wpaDEec20okl/9b0U0bTppWRSqa1eDNaomW1xO277H/Kf737I27KlOFfHCLOw+XThU6qaLepCzigzeKxMSCNRTahzJuWosrjqO+OcJXiPw7JqLHm65ZRPiIk1K1auAKY7g4zSYEOLsx7vNP27sVUWbS1S1NtmYUljSLzgz/9qzZ//6kTYrBjefkm8+4of/OQz7u++Jq0+o9gVJenC2cwbGaVmXJt34Mk4Q61Fj1ivbC+x5FIwJmKTaPuugMxUDM+ef0QaJ27fvuXFx58hdWGXJVEipBwYsyZpeLJuaGIhZpVtrIJl1UIsjq5rcNZw93BP6xuunzxleHhLHl7x5Krjh88T98dXvHx4yiFfM4ohZ8OUGsLu+/zhTz/hD370Y46v/5Lf/Ic/4zc//yVSEiITIgbnGgXMxGCK4E0hS9GMReJISVlr1hRcmdd2siSNcKUySmcWqRGV5WFIkilYGmMqmOewIsp0sAZvDcmCx1cw36rkztXJxbpFOWxA2W8ElFBnlmQvc3bMy3Xhe3vILE+va1yjLAgps5+mVb/CcsHqrvU9c4hlHs8q47iUunFkLbFKYtbbgG86+uOBlBMUqeCQeprMYMlmu0HEaEY47+m6jn44YQw8PDwsmwjD0AMsAJTBMk1T7SdS57OMcwpS7/d73r59Q9d1bDZrpkklc21niGlAciQ0ln44cDgUgm/IcSJnEApt22h2WxHG+4lDP9I2HW23whg1/M4p1fIpQJNTJjQBZyzOOURKZSMJ4zByOh0JTcPV1Y6+N3ivst2cI9apUXYIAazWj8Ey9BMpn2jCic12q6+w1LUo2jydtYQmUKTgvcOYQi4TbdORswbtN0/WjNPIqe9JaSRGXXunmLA2AOoLKSjjOgRPCLA/HBZvrmHodb43DnBMccDZlqHXcT6EoNJfU5msJZNzxnlPTOo1JKIgYYqFpg3EmPC+4XA4qh+fMYxTzzj1dbPB4JzDe0uKyrB23iPFkZMQ44hx+twxqhyoW3UUCsNwpJSE91bZMVPk/uGBsLvGh07HT84qiPP4/f4eb/t75CDkYvC2wRmD9Y6UCzGOiI00K08X1nRhhWA4nAayjTR+TTKW0KzoJKrpeI6MeWIYjqxWAeuEpgkIO5wPbNbCKCNGYH//ls3VjnW35e2bI6+++pr1+hpjHWOMGGcZx0guBueFpm0x3hMwUHTDz3kPMWqCBmtxzjNOI1ISuW5gdm1H0zUYGnIu0CiPxVUvpBQnhn4klYxMgjeOxnsQ9aE6Hh6IU4/zFtMErAlkaRHJkBXA8vi6kaBr5CY4zdZcIlPRfl2q4shbZcFOWX3CcjwpA1IizjWM/UgaJ9ZNy+lhwDjHNA76bKcDNrW6lmktkg1Tn+maLSKOVFShMMTI/tDTWEsIkc12zcPxQDk4cJZus1Y2b6PsLyOFxnsNvY0myBCTcGbA5EiRhDOOnDy2GEqAbMDiaYxXDyiqR5WAN6pqyGKxtsWK1Y3C0JCMbsw0Xk3ig/GQM8f+gEii9RlXRRa7qys222tMhtCsuX76nKZrWK070jhifOHmyY5VF+iCw1sdPyWmRf0C+pd3hk3bsXINA0oI8M5iiJQUKVJ0jV/B+WwM2fx+ffjvaC4+72KfA5Ezk+cSSKqL/HIJINSBZqY9vXvlC+bDt4XzFZDju+GD+U7fVfKLvxedhlk+e3zVMxjzCPT5G4/vAH6W3/0eZa8AwPzD4nxjHokdH/1LY7PHrKLZ+eWyNIvU5LKEFwDUZcawb5i18836P+/EPQamHgNd8zUvgbFzKSzfZCrogrPS/StKNd/aGvvoOZdvfsuH31Xj32hhNRD/xmu+rK93dmTmXcf3fKNGj3ldblBp1yy9gpp9ZQbezpl1LqvzkUTRqCzAGPPIW0PQhZhwsUCTeVFtKsNkBixYABapAcQl0CEVMJlZdsJjWWiu35vb3xkskoXdMfs7GXMee2agawayTPVfmiWF87Neylrndriwb6w9Z66rz3Qu+9l03LqzQfrM+JqvP9eX4SxrNLNkToRioaDeW6ZomvrzeFVw1lVvllwB2XIGiOpLMtYuejmLUY8o4xbwaebDzCV59x3P45AxlV00X6sav0vR7GFaF26RM86COOOs1oF1i6+TzOgQYGxZ3rv+7d5pBwtCufT/meFyeSg9+KLv1j5ban/WNi5Yd65/UzPsqURwfuD39zgMAinhEbah8NHVge89+5oPrr6gMw9kGQGV1bnlWayymwSKJJUxlTo3G81007gV1q25nb7HX93/gJenJ8ps8vNCpHZCCqZoRkSpCy5jXM2IqEHOEDPFFFxOxCLkUgimEIwjOI9xBo9gCuw6z3oVMHmLkaCgEwmswYpRFkhRXw1b16jzPCWSyCWpSXNxnFmwjkLLL37b8OXbG7wfyUPm5//uP/HHf/SEcXpgajaI7SipkFMiUyp4K5Q0kUvBYnDOYIk4W4C2AtBFg0kjTCmDCMEbjFV5WCmRgqPr1rz44EM+/+2vOa1WdDdPEeNJtjAmwcdRWU8ps7727NaWKcM0hZqCXMHX41Aw600Fu8BZxwfXVwzHPaeHB1JjeL7J+PyKtzEh1hFsRKQQc8KUEb+daJ4/47Orf0raH/j6d79DqFLrnBV8FKk8SDWib2qiF4PDGY/Ygq2yMN1UqkC8F7xYBd2MUXBITE0tXcjG4kXfeSrz+GIqOA/eOUzWcdrUxXOuO22KtQvUcU+VnXW+cGBmvzsLZLuU730+ctZ5VrKp3nbzHHZe1ZUye3fOAJNZACYzr5MECnM/tBSjQOj9cGSYRtb2ijhOHA57HWPRtpsiDP2EdR4BDvue7XZLCJ6cM+NYWK1WGCP0/YmuU+Po0+lE13U6Zjh1oJXsCE6Dw7atgHYqTGPCuYarqw4R4eHhiDWW7Ao+rCnZEnxQL7NpwnlHKcowkmgX5UOMmrEqBI+I0K1amsYjooB2ThPr1RpjAiVn2qZhGAZSjghFmUQp4XImJpWXHg5H2iYQGkcplvVmVTO49aRS8EZAIqtVq4b63uJDR4qZ/nTi+voaNRT35JRpVi3GCqFxDH1mGCeg0LY6Xig4p5mq5hTkiKPvj6xWDc47vFNJfc6aGdJaw37/wDCOrFcbmmbF0I8L0DgMAzlXyawdWa3WjJNnGie22xVFInGaCKGhbTv6vqdIVrlOSVijXluCkGIhpkScEtYalTRPER/UNNg5XWus1oFYRvb7Y/Xy9Yx5BKMZ9XKGcVQ2XcnQnwbubw8VONVy5yz004nEmlxanJyZTn9fjtdv97qRYqBb7UAMzgVKhDGOJBlYTYESIrmbaNo1KU4kD12rYHzGk1OipAgYJOs8Nw2TAiPFMZTMsB8IknECbdcyTYX9/ZGuabi5fsJpiqQiNKsd6XCgaxQIm3LSDIwOTGtwvgHxGK/vEiC4QCmRSKFtHX08VqDfkW3iIe6ZTokmWry1iHckY3BdCyaRh6RG2c7gmhXBCv3xNf2gpv3TOGrCj5Dpbk4IhmmK2j9EWK9b2tUaE1pdzcYBY0TbUGPBBKyYat1TEDmx2TXELOQScBmUKVqIKZMpFOfY9ye8V5818QVDoowF5wzetEAglkwkkyQyOYt3umGdp8Igkf7U0/c9u+sNKfWkWJj6iVXX4NadrkuwGEdVSRQyFuNWBN9STE8i412DKUY36nwgS8IUlTg6HM614CzBWkKdCaIVxNTMe7nOkTnCFFk1Lb1MDMOEt47pkIn9gdJNNO2KTz/9Hq7pVK6Jo1ltuPngA9bbjiZ4ptPA4X7D9e6G4HS2F4mQdS51oOztOWt4LkgcCSbRektCY4eYMsUkXIhY0YQlRSyWTE14/jcevzfwdBkQPjaWPgd9ZwiEJYgHHu1ELTKyCwbC73v/ix/OoMEyYf81YNPFd8+x1AXMYWqBHwE5jwdD8x1lPcvIvuPe3/2rx9e5RC7e+dJZtricDBX002DMLLGBNWcACKiShW8pVJFvfjZffgaovvHnZT1cAIwXYM3lVWeF0WOGklz8NS+7zMVdv6VYRsVBhhmgMBe/s+/Unbm4k17fXN7ybziW715c853LP7qQvPP79/pYylllUHNMiVlAJwWc1CC78huW93J+zrnhPfbKmjPbzZdegKH5JZpqDAsKQlDBrNlr6HzligKZGR9iobEoArWweuYWBNQUqfU+ogbD5+vObBdzBrAMuCrPOHMl9Gwt2+zDdO5T1lbTdUVA9DNjLsCXyg6ZN3NmEE3mKpg75rlzzEzSM4tHqsks5AV3yZrFy1SfHuMqawiyrd5uaOp4MwfIcu6virHPAY0BdGcWdDedJSis0rzL4dbO478yOy7L75wGyMpCUUCviHr0KLNN/zeXf9exp1SmxfntzCwvlla3DM11zviu8bRUH65yMR4viQDPF2Vh2JnqI/Voo+P9PowYWidcdRPfu7rne0+/ZNd+ibNvoSjDyVSRqZrQF8oCPE2V6YIuQutuZ+sbmmZHL9/jr97+Cb89PKcQ1Mdp1tJkSKLSuRhzbXea5Y4sxBzVTDUXxpjBZCgJqW5dzuji1dXu6x1cdR0//INrNqsHJK+1TZaClXptMtlEJLFsqIgpyhrKmVyBJ4pgTNF0x6Jylvs+8G//c+bnv/1LPnjxAZ9/8VuebleEBqaYMKtOA3WJGvRIIsmELQZywUjCmYjNiSQZ6xps2GoAmQdMVvlSsQGxAd9VQ21XR0yjEqn1dsfV1Q1vX7/k490OcVZ3Q7NhPCXusHSt49OrG662gVVjOMnI/f7Eun1G2wjBGlYhsGocQxRSKThruL66Buu56++4PXbcrD2frk5ctT3r7o3KD8QgaY8xhlwcL1sh/p9+wpe/fsaf/6dfcNzv1TPLVvN/sRTRvmyLBVEmnAJIkwK1gjLArFDwCJN6K5WoY9Jioqvgc0BwIhWgpiafceTiEavAHRZtFLHowGll8ZuyRucKzWKXleGGQYwsmKgKwd0CSr3Xxwwo1Xnl7KEnFXCa/67j4rzckZnVuUzaCkSgmV0LwjBN9ONILBOf/+5z3t7uOe7VyyfGAe8cTdsxjRPOoowIo3NLkYx3yoxJx8hut2G1WpFSogntIrUdxwFBaJsVp5w5DT0bZ+m6FeMoFZgtNK1nt9vy8HDPMIwEH3Den7PFFZ1LShacDwjK1uj7I+M44FwDwNH0WOvYbrcKDiWVcqcYQYT9dMKHGkRloQnqBWXrpk+wHsWJPTlPXF09wfuGXCJN06jhfkxY5yklcTqNlApUNU2g7RzOeu6nI6UIbddw+/YegBB8rT/D6dhjjJqE9/1B531nWLsGjM6JbbshToWc4Hp3QypRswimxPHwoGsiY8lJEDJd17FarxmHSMlFJXxtAwIpjXjvGKeelKalncQ0kHNkHCZSKmw2G5y3WHG03ZphUDASoGk6NVYvmc1aZXspFVKKHI8HfDBavlLY7/ccDidOpwEpViU2om2573uMtaxWa4ZhYBojki2n40jKEeet+vOVwmnoVepFxlNtGzhvZr3vUjuisrgb7xiOI77p6hpZWX9NaSm9JcbC1D9gw0DbNsRBiCdDtiPiHGWMSMmEzqkk3QjONKRokWAZUySferY+4K0hi9CuNtx/dWA6Dbz44Cnb7YbTaaANHu884zBRSsG7htYLTmDdNhQJZILOUVIwXkFnSZAn7fdtaLFiSCTGMTKmk7LxWDMNERu8bmg5S9M1TFNLPvSYed0hBWM8/ZCIUYFRm0qVugmbjcG3FggUhO3VmqurJ4wxcby/YzjdMw0juUDbNXSNx9kOm4UYJ8Qmhmki5xXWrJAy4huD5Az9gOTEUBPLTJWBHCcFhVIqNMGCZFIybK62DPsHTNfQekPXQBsMRjpKTGCE40FZndYVimlJQ5VCV6aa94LkRJHqOygG6xWML0mwTtcaksDbjmEyHPoBYqSzCtK0XafjVBMoRhNqBKdzXcmGUgxtaJHpyPF4oguF47Hn4eHIbrOrmYEjwXbsrnastxuasEJE2GyvuHn+IevrG10TSmS3uWGzDmw2nVojmBr35Flp8Sjao+TE6bCnlIQL1LVXqVJCp7L66sWIsagiM39rt3n3+Dsynt4Fbs6L9nnn+AxdzOHe+YF+H1nDeQfoXQNp3Xm92KR/53fffq2zad03z5kleI+CrfOlLwLyy3LP4I+cv7AcdrmNAnKPeTTv1t13DbaPpT6PzzEy3/LMgLJGvlG19hKIuWCb2QoczORtDVDrecttzfJcywLo4rP5czDVSHzeoZsBuceSHy1nWa5hpGYPe7f6uKyf+vyWJSy9rAqRyy/XBRnvAILLwu0xQHYJLZ5/Z5Z6+ta38iiS5Zzi+D2fL/U49yd977OsShdpM3vROzXEdKa2s1oXSw+rYNUsHbs0hDfojm1FXRaGjKnAhGIIysyxtdNZc24DF3DD4vVBOQMOAueEbguQUoPTZchY3iSFM/izJHSrL97Ue2SRM+Rh9PszK2c+Z/4qdXFojVOatTWLWbax5uIz1PepHue+85hVpNnezgCRM+b8TKIyOjHgDcowKLpYy6X2JYN6ahkD6ESrzA+vIFL9eR69ZnN8UPmVlGoqbKTuwGtwiZmzKJ0ZRvM7k1onpj7Yct1ah/NYaoyy32a2E2h/WcbRChQZqmyKWvc64AEVnKIgYs/jFxfziShwVtCAbZbVLf2xekDNLBZhBjIUBDuP+Qvk+d4eXYi8aCM/eH7LR7tf07mvMXKCkilMS3s3kpX9JYJgazrx2i6sGklaZ3HeE7odNH/I68OPeBk/5FQaxIEzRT2ApJDJ5BSZUtQhXZSBaouAxBq8CFmK7t6ifjOumq4645Zx31nHqmtZd/Bkoyabxrc1i5nBVO8bk5N2dK/vDQspj+rBkiMxCZpqr0AWskRShlh2/NWrHYd4RVhlwuqKr3/37/jpT7/PECd8u8Y2HSKxetElyCMmKWOJXHA242QkT0dNwtBu8cYgpmXMA8Eo+FOMVcq8zXizQwi1ndf2ZwxXT274/Mtf8/0SmYaRl1//imc3z/ns44949fol1lheXXVsV57Gw1dfvuRf/at/xT/95/+cf/CTH7FdNWw6wzZZjhP0U2HoBx5OJ+7u91gH/SD0Q8+173m9/wUfPpv47A8sV2uDkQEhMEXLv//853z+u7f86Z/8hLe3V/z250fAklxdgQqAwwaHzYKIw7qAxGkBlU1Wer2p/njG+GU+KdlW7xCW8cZpRhqVzxk082ix4J16u5V0Hiy8XsuJUHwdFEvGOK/5Gur8YeYkLbZgjSEXHUMvE1W8r4dU9gcyWy5WL74KiitLGOYhcJl368Q3z3tSUIaCaNrsIuq9M06Rbr2i5IiUwuEw0nUtTdNWYEPlNk3bcDqqFGp7tabruiX1u/eO4/EAQNduuL664u3tm4WZEmPEWMh5YrNd0YSGvh8wRmW0q6cd/XBgv7/ldBq4vromxkJ/GmnbhhBaUoxqpt+s6U89OSXaLhAaz2p1rQknrKdt1CfqdDqCyZSibIYYJ6QY1qs1KSaMFfrTAd941uuOrusYhwkM5GKRxlEkMQ49OU6knBSQqXJ87wJNE+i6hn44MI4jQz/ifWC9XrNZr9nv73n58iUxJh4ebrm5eQIYcpK6AWM4nQ44Zzge96y3a8xig9ERY6QUGMeBlB37hwdW65UGtEUNoXPOlAyr9VqZXqXgg8EFyzhOKqdrO7bbLfv9ntvDA6fjgRcvngNwf3+Hd46+n9hsdA3w7PkNMRaGPiJAzlJjokzJmW7lMSaBaShloltZutWO0ylyOqqvzdREUtLso8MQidOJtmlwTmi7tkobhWmckALDoGBYSjqwRFuz6okmeUGSvmPlv1ZG3/vPfLIMxCg4NiqRjYkpTbhgyTKANcRk2dAh4hlGOA4jthQcEeME2xjGIWJdS0tHP+yxZFarNdIEUrH0+yM+KpPGtkEZaWZit7ui70/c7QdcgvE4kvyIbxoSmVwiMiW877habdg0a4ZkKFnBfFvBGbGGhCBGGatrv+E09sQcyXGiDAWDQzqYyNhTwTtPsSrJbZo1vckcTwPEjDWJ1rcMY6aUkSyFQsG5mrAmZ1arjt3VhtDu2Oy2NM2K/NAznBKvX92Ts7L6dusVdBOrK8E3K7ocGI6GKSbG44Gbm2u61ZbDcGDsJ9IQyUmY+pFVa8AlYh65vrnRDdmSsEXoj3v2w0SfB4bTiSat6bYd09jTGstq3REHZew/+/CKse85Dg+sdhssHb7ZICgwvT8duXn6DMlwOJ1ofUuQRLYKhjnXkHIk5YwjkMYekyesN2AdVgwer9lacyYVg7OBlQ1McWToj3gHw3FfEykM9KeR4/4eYy1BLKuV5+rZU4xvuPnoBavrDbtuhxHHzbNnbG9e4EPL/rTHOZ2Rr66eEHxdE6dIdaGtsVk+b7aXzNifOByPDLFoW6EC3sbgsieJJ7tCLuCxBGNx5n9h4OnyOJu7ypJKfWE5AO9at54X+38zAHX+zrvnXhhEf8s57/zqr7/evFgy8+fmEfZ3LvNFIDkDD+ZbwKczSlOBk+8AMfgmoPTXn3P5rChb4AIYKubbxIuXgFepfkUKKizx30WgeHmPJc35O8f5HrPMqa6B6sKolG8+b03WhbyDjJnvfEkX9ffOKY9hvMcnyMUaejlLLs/7dgDw0V0v2CiKU8w/X/5VA+N3mWPv8XFZUq1XsxhfOzuzTsy5HRiLGFHDu/qRyuY0kC9SKtJ89isyVo2fNTOeIduLt3MBUmkZzLkw5rL7SD13lsSJYrlzRibO/U7Tdl+8mBnQqbtnrp5btyv0cheKDAVRzoCKiIIdrtaLArr6fUF17nYGV6op+MwA9dbXnWFdrOmAPt9oNsmVRU6n7L1zkKbAjsIjWXIFfDyWTDGGRFZJEIrrFQMlW4wR/Ayu5UysyJw1ghq8KwChXhz6TCmXBfQplybry59mGRPndjLf49IzTTP2VdkdVDCzyg0rUGVQ/bq9ePelPvfCQzOygGzqH6QZCbUP6vOUIpQsiC0UU6WiC1hoatu4kPWKUPLsbaXjQpghRqt/2Eesp/f7+NHNkR++2HPVfA58iTE9lFRlHIIQydgl42SRRMo1MC9GJWzmDDe7cI3pfsKr4w/5+e0Nx8kruGkFbx0pRWIsxAo6lZw0s5goQCpkStZFH6JMmGJ0oWmlgq8l46vU1RrUryFnHg4HjsfXCoLZlfoI2fr+ospiqk8rQktOE+OYmNKJlBNRHEEcsWRKsRQZSdHx1UPHL3/XUIA/+uNP+P/+v/8/PP/wGc5YYgZjmmoYfqc+CnFAyoCwxhXIZY/kop4d+Q5rPARPyQXLClMKxRVIgisJGwxTr94W7eoakabyzDImQWMcXWj47V/+kvV2xS9/9nNet1/w5uUrPvzej5imkd/d9+x2Kz66dnz82cf8k3/6T5VZKAaL9gNjhOIKFss0eoYxEocHQmgosfDr1y/5aNfw6tcHvv78Cz769IdAQlwLOWHMwKpJvP7qJePDA5/cPOVw5Xh4MBRvkBwREYJ49QwyRcFoIi4AUuWoxiFWwFqceMRGMFCKpziVBdtSwRClMmHMBF7F9EEc4tT/Tgp4p54xuYAJHpMUkZEqqxR1rMfZQlQUQcErZ5ax1OIQb76xtngfj1IDbJnHtWo9UOoOmq5S3JI8RUTZIfMYVSoyJeI08EXnxJQnjsc9h+NEu24JrSc0jqurFVPM3N8/AOqpN00TzgZefPCC4Df0xxPjkLi62i2sJu89m80aYxz3+3tCE3jy5AkPDw/EGEkpsbvaUErheLxfvBSbtmF/95ZhOIBYDvvMXTmw2W5AhGEYMcby8HAiBM96veazzz5iGHusNYzjyP7hwDiNFXAqWBN4/fqO7XZD23qGcaRbtWqWvdnwcH9PU1OriyRyTtzd3eG9Z71aM/U9IoYPPnzK7e0dITTEKep8WbIyeo4HUi6aVe5qx3q9JZcIFAX0To40QQjqyWVN4OF+z8cff4JgyTFSSiZOiavnz4lxYuh7NpuWbt2y2ezI2ZKz4NyaIpmcR7a7DTdXN9zd3/Hw8MBqpQBVzomH+wOQMVZlhm3bMAyR+7s9pUSePX/Kxx9/yP1Dx/XNlsN+z831lt3uhrdv9D0djwfalbIvbAg48bRdVzcQoJTIatVRJOG9pz8NvHl9zzAMdO2KzWarIJ0L7B96phhZr7dMznI8njCmEJod4ziQE5xOJzbrNeOoLDJrk64VCzRNS/CWJrSQEkjRdj+vKx8RBN7PY3O95eF+j3ih8w1TGplKTzAWwkgwHaVYpsoOiRQo4ETopZDHjJuKetlNhZIqYF8KU5wwNjLEhEsGZ4W+9JQc2e62TFPE+I7VkzUxTxTrcSvPw+0rVttEMRljdSxNKZPwDG5FtEI8PBCMo/Ed2SSmMlDSXrOrESjFQba47DGmwTWeKWYOx4FNu2JKhSkWpv2JtSmE9RUhrBj6ialkOmcILuCblmlStlVJQhqEQSa8fwAiXdNys1oT2g7jPT40pOIoCZAJSs/pMJFSxK49u+2KYSic+omm6zj0Rw79PdNQsK6h7dbY0DD0IyUJ/RTZ7Twlj7z++ius1+Qd1hpiFCTCqtlgTEc2ka5bU4aB2Eca29CuWowNtJ0nrA393Yn9uKexGdNHmlDY399y9+aeu/0Dq9WGPE3K8iqRrulYt1ua9VazBRphGvYgGck9JnjG6YRf7fBbzzCd5sUoJVlijJyGB+5vvyZPJ5puy37f0wVPjonQNFzvtjSNp1uv6NZrnn3wCTdPrrlab7jePcN3a1abDU27wljLWDqaLmBixJDxwZNiVl8/Z2jaVqVyxVGSZu7LKdGfjhyOD8SSyKaQTSJLofGWnCLZGpKx4AzZRKwXTPz9tHZ/J+DpAldZfp73ZtRE2CzBVD2Dd8Je3gUBzp/zLZ+/+9kZ+ngcM9TJe96hv7xqHeAe3e0CHLIzhWgGmBbGg0Zf9p0vLyyPb32Mi0VQ3bYyFaT5xhPNW1oXn307lHF5o+9YYF0svGosxqXnk+7wW4wIjuoHMzMWLi8r58tdOi99gwVUWWmzPGsuu3H6/AtoJRpInpkI+iy601ED+4sLL4HvOzVxCSTJRRkfn1PPlHfZX+ZR3c5ZtB6fwTeANlPPVSzkm2/m98AN35/j4iU/YrDZGuhfoHwzU88I1ZdHGQsC5MryWp59XjBUUObSu8JYN6M3QGWwXGSOO/dRWcYRa2db6bmP1TIWtG9V0Eskn/voRdt61K9rJi7NvqV+GTOIvPhCzberQ4Cyv2aQhaWfzI3HGlOBKf1fGU9qoO1nMM+WucAsq7x6jzmZgFnGqprKtEbnBvDGVxClaPBVhODUuSdjyFRDYAMUrRNjdWQsMnuJWJzMbXjeVRRm0ywzvzcRUgXGXPWEmp9vBuNn4MBq7njmkcoYU83b6yMalvdnZ18nM8sT9b3kedeTWVxnzx5XFdyaGRaX46Ot70MEZTmZKjWBmo18rq8z87LYs6m6NZClqCGyVVDy/d9jPR8//fRntPY1OR+gHIiF2i9jBQMzlKzMIPGUbIl5fufgsrKDJDR4PKVseX14zl+8XfO7N7rr3jiHEJmmTBxH4pQY46SZ34yAVF6SjJQSkTKSBbIxmvWlgInaFidJSIkKhFI4SiFUA05K5md+4CcfX/HJhxt9QCPkkkgZynRAxOGtMEVhyoFhXBPzRmV1UZMXTykxjDAmyxA9L18Hbk8TLrS8efWGt1+95I/+23/OGO9xriG018TUU3LPFDPkAW8NMVjAYXNkogJ3udTMfREbJ7wvyiabanstA8PUY/tX5OEt0/Qcv/2ENnRMKdGnCTMNXF9d8etf/JLnHzzhR//on7D2K9a7K5qwIknm7mHgV2/VK+35NvCjn/xXAAyTtt1VI8rmGgx9KmTjcKGFcM3Dw0vieMDnxM//6i3/mx//M2z6Of/5L/6Sf/xf/5CuTSAjTgzf++wpz57c8OqLAzbf8YOfvODXvxp4e9eTaUDUtN4Vr3WB16xMRrA51/EiaI+zgpiMLxbJpYL7hVL7Gc5SUqGYSfu+6LqjmLQA2sYKRWZpQgUyJUPNFqa5Us6ZNl3RrEwiBqx6CinubDHO/L1gTJSso1ERZQiWmo0uVxawqRPdzIya56hSDf11KLOYKjulVJmxwBh1XzpOmc8//woEmsazPzyoRKbpGIaJrluzXq/JOTGNA23Xsttt6U9HMJbVesXpeOLu9oH1as1qveH2/sDt2yO73RprHV9//Ya2Wam0x1tevPiAV69ekmLBVFNdgHHcc7W7oe97ELA2cH1zxaeffsSpP3E83vP2zStO/Ymrqyuur6/Z7baUBzXl9sHx4vlz1us1q/Ua79TI++3bt5yOJ4ZhwhhDGgaurq5IaaRIJhWIyXI8FVJy+GA57E9MU+Lt6zuapqVIputWrNZbVqsdb9/cIlK4vXtdvRPVyygER9s5mnaLMcIHHz7jeDhRxND3RzVi9vBw/0BOwvE4qKzsODGcRkLjGadXhNDVzHiGKU70/YnNw4mcCqfjESma4W2KEyEUVhtP115xOJwYThHndG4LjSUlwxRHUkzkmLl9eyClTNta3r69I2UB41ivO+5uNctgSiP9YtIeuHlyw+3tLVPMOBf4zW8/V5DEW7pOZXMP+z3WGja7De2qBQv74y1NaOlWnq5dKUhgLSUJMWYFuepzzGsFF4Svvv6c58+e8erNG57vdiC2SqXn3mHI73kfnibBdS2TZLATxQnGtkxFCNmRpdX8Cimr942N6ps0ZbCw3m25u30AgdY4SAOhcYxZZZ5SKhtlUraMOGG9ChRXaNc3DKdeDb5TT3Cep89eMLQdKWWCaYhj0ux1zhOL42EQjv2RjddNAbEJKIzjhA8NuVhKVL+zgqW1nmAMyQt7nxiPiakk8B05C7ZMSErKcGodU9fhnQMioVOD8FzjOofOXyUeadonrLo1+RSR3YQxLWG9ZRfWdK9eYYKjJE+WhmHMJCk094XOQ+whHoS+HPHWEnvNuoeNGNewudnSdp48QJp6nHPEmNSLMhgmU/BO5Y/dZg1F2KyCZqaNRyiJMUWMgc1VwNnMkEaG6ZanNy3j0SPSkMoABqLRHbGvv/yK65sdBocL0K1bVqs1OVlOfc/d/kG9GUths+1IubBrV6Ryok+RFZF9OkG25Hii7Tq8M8S4B4mIa2i2V3z65EOcqO/jFHturlesupar3TXbqyc8efEJV9sNEgub9YbQalZN33iKMVxt1uq95h2SB0iJEidljTpHsIAPzF6CiJDTxHDaM4z3iDshXhM/+ED10MsUK+AC1q2RbDkMx+pV9TcfvzfwNAeq3w46wRKwyvmn807yu6DL48KdiQ+z8Ot8zgIXXLB7zuIxc/Hv+Rpn6OAcup5veymZm2lllrMf0Sy6V9hEA8c5LPo2P5CZIXIp7bp8glnP/20IxcKaKo8+/AasNF/nzMQpLKnqayQmzH4BZnkJc9lmPEEDXL2rnYPWOS6uUeNjeFCWeikVfZG6M3cGqeZAUQPZBaAxmvWQy7oAznqoWiWmfnaBEsnFP+Tys+UdnYGu2dNkuYehghEXFVqfpYbKy2/UPrGW+ZK5NpfW6LPM7egMwpnlrL8vbAmg+ulUeZd1SkO1FnchOXoEF1/Uh5rJGmxx1cS50hHMDDFVA25M7VcFMWc51vwuZwaN1u3Z2trM4FI9f27zZm7PZX5XsjA65j5nqDRtUcbQeedsBoukfj6DSJoyfDGplvr72cX8YgR5JPOt/3YVHHHO4p2aUzvn1aPJXpimG1MDCC6uUZ/L6JNb5vZ1vhfGaCAms1RKs18oNR0NPKq0aX6v2eRK6JrBIDXqnvF2I4VUlIlV3s20Wcs71/eSNWxpKxUYqzDPvIO0gHIYrXur73A2EDZLPT02/V12NZf7at+asTxb28jSFutfGd1JE6E+u/ZqNc62FSAumulQKthd9Nq5VAaVdoCa9VVmztQ3B9338Mj9X3AiAT2ljFVOHxAyRgwpK2ssUY3WRXfhi2jWMCkGYwqDPZJKZP/lG74cvuZ17rg9KomkbTskJ9JJg9IpDpRcfb9sIYDuihU1KnemEEg0XtNKOzK+hSZYChONF1qj5+X0gC1HDIXt5ns8f/JH/Hf/+nf8i3/5z/g3//4/8fmrO4LrsL6ha3YY14AzpGKI08SUhCl5UhZiSZToGCdhHzNDbNi6iQ+v9gQyq/aKn/36V7z49GOMnEh5xLYbbR+nB3KJmga6TBTXQTmRcyKZCmZIxJBogDLck/KEmBUihmwzYj2S1aA0GMEWS0yCzQa7+ZBJIjlFXErQtDz56AVvX71m98FHrLYbXGjJxhKToR8Sb+562tax6xxXrSdLJnlLP2ZszSYjRUiTQcTSra951m24D5Y3X3/BRM/2es2/+U//mX/xf/ivMfcn/oc/+//z05/+iKtWTVZvnm754Z/+AS8//xVffTnwkTvxwx8/49e/8bz6otcFJ1KDwYQxUcefZFDT/5nRrhn8kgimWE0e43Xt5UvBZWUsucaRBAXis+AK4IJeo5S6VlMNvXqEgDg1li/GU4gYG7EyG54mpEBG6Z46fguUiMOQ/x704QI1C6CCT/PfzunoKkVNoA1W+3fNJquyaVvHS6Nm0dXjTMSQipAEmqap2dUaUsocDnvapmO/PzCOJ7puhUElWZvNmt1uy9D3vBoO7LY7Qmg4HnratuOzzz7Fe8err7/m0z/4kLZpuLu/Y4qZ3W7HNE1cXW158+YNX375Cu8DQ69G5Ovthq4NWGu5vb1js1oTwprjceThYU/beookmqbFWcf1zQ3OOe7uDuo7hmGUxDge+frVLdZaurZVSeAydzva1Zrd1Zbbt6958/Y11jhu7+7YbDY8uXlC0zTEOFagp2e73QFC27TKFIuR+/tbnPNc3WxZrRqszzw87NUfyTmV5+XM6Tiy3ra8efsKHxwpGlLKyNCz3qz47NPPGMeBtvNMY+Zqt+Xu/g3OOdrGYp1j1TUYZ3m+e8bYD3SrjsNe2ValCMdDT06F4AGTGcYjzsLNi+e6SVv9I9+8ec3Ll6/44MVHdN2K06ln1W3Z7Fq817VK349M44j3Lc4GTRYhPZA5HQ+MY0+MmefPXzAMIx9++CGHw55x6LHestpsCM0agOP+gdA2mvmw3ZJjIsWM6XR+D6HRjYYKHh2PB0QK1lWpN3A4nLi5fsL+cGDTBNa+w88b+DPAmt/zndxka0KLwjCUMwEBAduAs2Ciss2nhG1049WajCXTOQhA0zbK8C41BX1OGDxDLOp7ZgPiIJfIOEXk9R2yKWQbmBKUOOlm8XbNs5st02mgEcfoHQlL27Y8ffGC+9MJYzIpCcKE2IZYDEKjiVZsT7KFVBImGFrTYVNEJBK8Zb1ZcxpPOhabgpGRFA15bGs2Rm1nnYfVpsEEQ1MsJUEbApP1YDJxcrhtS8aw39+yvnJs3Q2N8VzttrwMa+I0KbuGotLEaMmHxHSMYD0r55RJmITSeYwbsdM94RRxssJZy2bX4ZuWYz/gV57oBOMc3niGMoAYxn6AsXD94orTccRaZZjaBE3KiBHuHt4APc46grlGBHzjSFMi+BXPX6zZPzwQo8qRG+9ovRqC+1azsb5YX5NKQawnFZgeJsZYCKsNoXEcTg8wjXgTeHh7T/PiOQ/HE8NR2akfffQZm+0Tdust0zTRNQ37wy2ffvYRXdMSvOP6yTO66yvaZo1fO6zXZAzWFlIZMc7ROA3ylQFfE8Rk9cO1zpJzXuIjUOlfjIP6jKWCKwVNSKjflWIxxld/L4vNBUmFIEZ9GH+P428FPNUM2PWobJUFsTHLpv7l/3q8S588gw/LdzkHTRdUCs5ONOeg+FyG83a4pmCfA6FL36ALX5BZFlOvZ+e/z1jNRYnOFtuLL9FFWL4Ek5dn1s/UBkOfcQErDGcfk2/c5YywmIuama8x18Jj8EqW78rlPZYHrzuVpqo450VarbZHeIlZPn708+XznjN+mUqhr2cYXXAurA7OOxiLJ1MFd8y7zWB5jlIRI/1fqiH6pYrt/JSmSt9mcEODLoNV+Y45g4hKRddCWpnvodWo714NmIvRrE/z21R6+xlArHc6Xxc5o8N/r47akozKo0rtL7P0C2bQoHonzQBjDRSgSsukqKnf0q+WnqnXReUPXBhHGmPPQMk7De7sO6RHQdO6FsmckxZQU0rPAGhZrj0DSsrmOy/uF3CE2govgB1TszqcW/UFIHIuGrMX0AxAWmPUKNkq6OSs/m9nAM/mM4AutW8sMtPH45sGXgppmiUjUx1nLFCZTsYKBo8pWVPOSlaT3jKPDQu2B7hqfK5tVJlPYGqgNjM01dzdUiowprK82ZC9AkbGLdnr5msaKRWskcpKquC888v4Y6yhiFnqc2Y6zYxJC9ULxi7NC3vObKfpWOa8eJfziMo8C4KtQ6aCStQ2oWwqqVLfXAGtGXLWrD7VjLgUkExN6PwtfeX9O756c8RajxBAHLlQvfUqEJsVeEvGYYslFU8qDilOIc6SSdkSi6umllek04mb8Jdsm7dsggZG1nmGlWaEElINhhPWwMqV6iUYcabgraFrCuuApgYmEVzBksCqQSVlIKaRMQ2UGElJCJ3hB3/w3/D/u3/LX/zyxP/zvx95e3iC8wG8rR5K6ksxCog0CuZaQxQw0mq7jYaxJKwR/uQ6YbZCQtkfh/sDH//Bc/ppwhQN2E/DiRgPlJIZM1jncWFDJCCiTD9JB0o8Ymwm5QkkkckUMyDJk0gk2yho4lEaeumxOcA40bsjLqgJcEEzB17dPOHNV69589Vrnj3/iDiNGJuYbML3mcEkHtrIw/qabaOSRGf171TUwLPxEJwwlIIzsA4NzYsXBG9J4z1vvn5Nt17zZ//hl/zL/93/nvD2nj/7H/49P/3pj3myDRgiH3+2JawbjnvD578eGKdbPvv0CSEXXr2OlAjWq//bkgXT1snbgBhdbIoYgrXgLWZSCbBINRK3M5hkwcysT+3fySQdf7RidN1lZ/bmnKlW27SzujWkDDtZxmFslZhRhWoiSK5R+Xt+qKF4uSDo1hmgyu/0pFIZqvbRhgtWg9LluziVvUthjCNC1gxlezWWPh5ONG3L4aEnxVp/pdC0LVfhCu+dmnxbR/CelCIYQ9e17HYrbm/f1DVz5nB4w13K1aMoQpX3fnX4kiZ0HA49YFitAm0bmMae/nTAuZYPP/iQaeopJdN26uO12Wx0TBgHpnHSDG7rNauuBaDrOooIx+OBHPVNb7ZbLbMIp9OB7a6jbT0pTeqJ1DT0p4muWYPAOI2MU08pysCxzjKNA13XctgfsNbhvSM0jlXXsd6sOB5O5D4znCZOxxHvPKEJGKNgQds0eN/x9nXP6TSCyWw2DaHx7OM9zivQtt3uGMaB6+srTqe+zjGJ1TqQRXj75hW7qx2n04GH+3v1s+o6RKAJjQIFkvEBrm+uyCny+vUbrLWs1xtygd32ihgTkjWz7RQHymEiBA3rQvDkktjve9p2Rc6Z1UrBc1jhQ8C5xJdfvsRaCCGwWnWsV2uOx5N6bxWhaVqsbWjCimlUJk7bdHgvlJyZpqEy3zratsUCTfAYU2p2Lp1r26Zjvd4ieSJXNk+RXCXVVc4f/mdxf/lf7JDGwGSw4khS1N/LOBrnoThiSXhTsxj6CN6Rhowr6tMlecSatLTjOBWmXiqw77De41sDJoJkXA40JjCNIw/HI5vVFhsNwbSMw57D7VueffQBxaqv2GZzjY2Orltx3O/pj3e0bfkfufvTX8uSLLsT+20bznCHN7h7eERGZGZlJqtY1ayJze4mqRakRhP6rD9SgAABEjQAAhqQ0BRAUAKbU7PI5lBVWTnFHB7u/t67wxls0odt59zrkUkxi81uRupEuD9/dziDHTM7ttdea23atkOKV4YThmIsYZrU2NyqL1PrDSkJSTLeO9qxIMZT5kRM6qNmvGFKkXg8021uCHlCbKZtPMSAmIY46zxhRXDFIsXixgJxptvcMY8HJGX2XcspOF68eJ9Pbl9xGidynjFmJoaRGCemMDPGiblMjNNA129ZLDacaygFhqdA1zSEeKZtd7imofUbSAqAbvd7CkaTWeIJYcZ6YRoTwyEyDk9Y53HtRCgT3glPb54Q62gay3YTcQYkqqR2DjMxF27v7jgPgX5zS+MdrhGkqFn6FE7Y1tBtNqRoMWbDptvineV0fKC0HcN54M3bB8R4Ous5vjkR88Tu5hZvHTddx7PbLU3bUYrHGod3cHfzkq5rwGS2N3e4rsN1DTYLWJXElVKIMULI2JQxzhBTIcas9gbekEMkxFDjpEIWoQRlvocwa2LEOZK0xAjGJKy1zDFVSxAoCUCQ4hCEmfBrjaO/9Cj//2WM/Zdhf/xKr5df9R4LuHH9+V/rAGvA8i5r4TrI0ED4UrXqOsSpC60r0EtqlvydbWXqXNpiQQ6vYaTrv9evlov86zqI/pXeQ9+4Zm2XK5fk9SxZbANWtpMCTxeQbj0tuZxlXs9P/u3tW5b9ffP8LrDQOxrtKyrXyjbhmzuvTK0r4ClXHOv6PIR666SQTKYszi2lyiCL1lDKKNMBqEVuNCLX21SZd3n598J4+bdc7/+/bVdAj7O6aC3r2FjkXmaVRV7GXUXzFvNmUcC5iF3BFK0QpgabtrITS93vckwjVgNkuT4lZaWsJviy+AJR93FZpBc005Sp3gDUVNo1ormAnmv5PDXSV/+gajAuS2OsMHL1rLlAEPqO0QC9NoGgD1NvLXb5IxbnHNaYWlEvV7NwQ5ZFEphXsOkCWJcV4JFl5yxyMrOCfmKrau/qtG2pshIpGrRhIWmyrRggG1Iu1di9Bm2i1cWonlglZaiG8gswQ20nCqt00K7AU6kDMGvbrh2qmhOK0fv2jdhvAa7ebdfFWH6ZhC7gj3pkXbVHgTVVUFilgrnOxxkLa58QNY8q1Wy89tXL+L/yWKl/MN9uav/19t/9ifqJFFsq88EwVeabSToGY4GQVWI5J63wkhOI6AI/RktOgRf7xN/6G9/hRy8Nhp9A+lO2vdC1Lb53NEagWPWEsmkdG4bFo0zNwwWIQc08xzgyDhMpKAstZbuy6nIWJFcvOREODz/hp3/6/4LQ8f/4b/8uH3/cMspWPSqwWHEq3zNCsIbGejUrN5CKQXLQMVIsgcxOIrs2YI2WhX96OrHpO7wVYjR0dgMI83wmlkxIhViEho7Y3GqG+fQKqeBYiAlnMykp8weZCcVRYs+cZozNiHG4YsEZiAVnMl3K5DRroiMX5jwjYSbFmX634cvPv+R7P/wREiN939GKY79tuLvrudt4DlPicXBsvM4lApRsmAokKYhkLAUvkdM4I96xv73hvZcf8uqLTxlOr+mef8Df+yef8Hf+s/81Yhr+5f/wc370ow+53UPXCLvblsNbCFPm008GHt4ceflix3sve968mTWjHYPqVNF5QrKp48qQWFitdd6QCzCv65KauMkZsYJZEgY4BeuoYDyygu8irExWoYGaWDClqGTCOAXFC+rpZND91DVGBvj1kq3/UbcUUwXwruY1WOdqABFPKQkxiaXaY0HBNV1H6fMhLl5uZC3VbbV9vPdYa9lsNpyHE2apODZNzHMg50LTekJQud5m0zPPI75pMEY4DydCGOg3PSUnjocnQkrc3twyTYF5mrDOM09ayTCGxGazUbZVDoSoPk7ea1XEw9MRY4X9fs8wjAzDmS+/OuKc5cXzF4xurP5FE8M04n3Dq1evaJqGlBIUwXnD+Xwgpcw8B6wVuo1DJJGi+lblUior6pYY1Qw7Z5X7xxhJMeGc0qq32xtiSJzPZ8QU+s5weDrqPSnQ91uc8/r8rtL+ECJhFmIUchL6boPYRN83eO/Z9DsOhxPTWNjvHdYV5qCAWoxqpp2SVqbcbPY8Ph7Zdls++u73GMeBUrQaYE6R43EgRq3geTBHvPc8f/GMnAqHw4mHt4/sdjvaxiNWC6SkPFFmw+k4AAVrhZQhJYOzDdaqzMrUiqbn40C36ehaR6oeb09PKhdURnwhhsjhcFTp4KCy4b7ZEEPQPiravsZYjAj77Y7T6VS9yBKlaPLKe6FttSpfGjIhqrec1KRzzpmUk1bT/BZv03zCOS3u4qzTZytGK7+GQjYwmYQxhYIlDBmbXE2QaV8KMWBiXSs3DSHomsVLxpkEzpCIhGFg125w4uuaLnIaJuKsfb+53TCZmVN4oru5I1rPeYzkOZAPAuasidDG1HWOV4l6Tspb9wYvDWWaaMXRFAW8iqlVLp2FYDinCjCIYxqTxsY5Y0rCOpXyxxxp0OSj8Z7G9pSUSKMmnc7BYo/C880tmYbzU2I6J7qbe3a3lmfvvSSME6e3E5Izm7bFesdxHngYnpiZyOi1aRU+TZKNqWc4Tdjkcd7zeJw4Dw/MKXBfK7+GKVBMxniPa4WSNCEe50DXtjij8+8UAtM40u53OO8x4jA0kISUIwmD3bQ0ybHxHpv1nloX8V1bqwBqRb1dt6fZdnzx1Rv6/ob9pqUhE4YTpzdvGFxDu9nj2i3iHR999D3Oj2/ZNy03tzuss9zd3rLdblVSbgz73Q19v6HvPJvdBuO9nr83GImUEpEoFBw5ewWa5hFi0Pu/2J3INdlGtGgAfi1YlKJG12MYOU+DPlbFY7Hqe7dYq0qpKhpROxMK6deElP4SjKcLOPNLFdauXrsGC341gPLLINOvAqxWsOjfAxWQK9Dpl45zBTytYeYaFF6uMekHrr5/CZre+e4KXl194Z063sunyi8X8yuLqeT1S78M5F37o6zvUd7Bkd65TlglLwsT7IKwfHM/rIvGUg2PfxXwVCgUo54/v/qOfONkatD/zbffOf5CNV8C72+097vHh7wEibJ4IQg2CwYt4Z0l6cJhNe25HDKWqz0tRA0qVLfeu7L8v7LNfqkdlr7yK9vgN2OzRqtX59rP1aBVVkaXQWqAfwEDQRGQklLVcVtIi+mpSvdsbfd15MoyN1DZBFCwFYypoFd+t79JpawV+SZjThk5S2ZYu8v1OCtXcgTForQLmupNVPvwwuxaANJSqnSsrGDPtaxVRCVI1qhM1YjgrCjjyTiMNRgjlaGwgDDUYMpUWup15cNrCEZYDnXxNVIm0sL4oc4b1ug151z0BlL0nshyGXrRKWeMGLAoJ0ASizmIukVVWWShCoiVZlwqiGDq69ZqWXVnFHwTWUaqWcfeAjgvckhZZZesYJrUygXrFMQFYKyTFKt89/JuBbhl/Y6pQJNQYGGOrWNcVjPeb85vl8ju4oml7DDdD7kGfb8BA/pf/2wH4kmysNwsCY29tX0s0UDKWtAjFmV06r2OSIaA0EhgY2YOX39NbL5C5OdsuiMPc9CKljaoIbgxFXBMlJqRNiWxSH6MNVgrGBxIIeZAjIGctU/lshjcF3KpEqGs49bIxHD6nPf2/4lSu1Opflx1rhehOE9EsFlXvmNlXWLU5WxNRJDYdJm+y8xT4HwcyNKx6TvMPCNOaLuOkBVIymK0Ip04bLMDv6GRwpzOpPlIxmFNi+RZR020FCLFRAV5i3qZOKvyrizKzkxlRswAx1q5MWuQWSaVPHbNltvbBiuO3e2ebnPDtt/juoZDMIxvA+1geByE33rWVckM6uODso8W5nNjEn/xk3+F29/R93s2u+f88K/8NT7/7BOcheNw5P/5D2b+t//V3+Tn//pT/sHHf8bv//UfcHNzw7Nnd3z16ad46zmcA4/HgrUzH3ynp2kNb19NzAdDkQZKQNB7QzFrNd1cz8MuVemy+nwVU4vJlCrprcAxdpl/F750layYWmE3KwuyXLMgQfudU9/AnMCKqzOfoZREoXoKlqws22/5tjy3BB0LmaRrw0LNGujcnqvnU87Ls+8yQeUcdY2Sc2WA5lrpVbBVom0EzucBiqFtGnKe1v3GVMiDGtWKqFeQlh8PGKtzpPctp+NAiDNhnigZHtJBwWcR0jQB1ApXKmcbxglB8L4lzJMyb6TgS0NKhbdv3tTnhND6HmMt5/MMZB4eH5jGwM3tDQCbzQbnPNM4Mc0TeU70m25N1PSbjpwyoZZ/H4eRcZrZb/dYZ4ghKJvRacGPDLRtSwiRaTqz3ewBMFbB7Tdv39L6jpTVD8Z5DbKctYScsdbSdS2bTa9SNCN45xBr63NeAaEwBzabrXodTRPjNLHf65rCeU+IkRQzkUiOMAwzTVNBMe+Yp5EYlRFjjDJTS4bT8YTzHkGYp4nGe0REzYjPA/M80XYNKWlVubZrtE3Gme12z8PjA01jVz9KEUPbdZzPAzJoGzRNS066phqGgfNpJGdl3sUY8U54eHzk5uZGE23WEcJESjCOgVJUtmScwExdr0Ws8bUPZqZZy89bB6mEKmuorL9SKoP327tlAeNb8pyxxWBLwNiCEUuYAmIhlYSVRgt6pETJKlNPGIZZMLZHsgcSxalXZQ4J33h8Z0g2kYPQ97eUkpliwDqPLULJCdcYUp7pmo7sEnMO2FiYxkKcIiCMpzP7uy3iMs43SLHrvXUiBJHVH6wpXj1FS0BM0cqKlVUfc1bPpqZWL40Wm8GLwWXosiUVgzdOK7+miZxj5aMKQQLZJZI4pnkm5Jl2u2Wc4eHtkefbO/rW0XvHs/0GH27IoaVxnpALx9MjcT5BSXjfYbKnMep1GkImIohtanEBz9M5ch7OpBg5DULTdbjScp7OTCFgbKJtPcUqM8vkzG6/pyB0RUGjZrOhlwzFUpLBty2UwjhNlBLo9h0xDIQIbbehYDkdD0AhBZ1DwwzdvqPbbLRwQoY8DpACve8o3mEsOAnMw5n3XjzjyzDR2sx+d4txjr7f4L3hdDzimo7dbo9QaDqP61t80+KNRVIhhol5PhHF0DUbfOMoIZGCjrd5GAhxokjEMGMNeNfh3Zbiq9dgSWQjSHYkYzmcRoZzQGgRAuSEKxkpClIXaxFbnz8lIynTlF8POP4fxWtcpSP/I/exbBpjyNXrlyDk+lhXceG/gwn1y6DOWq6WRQJS3vnsCqJdA0L1ob6mqi5nC1TmwfWhfu0g5pdBHlMp7e+wIFjAystrS3U6PeelvQyrx1VFJC/kgSXCvTq5BSejVCZI+SXJ4doEy+VfX165BOnrfVhf4wqEugpGdW9XgFv97Der3Rm9vuVWaCDv9ePXizCTgaweEUtQvF7xVd+A6gFzoaovQNulHZYLuJzzcs0XCdo1yPobJrerUYPKxJSRU8oCPC1SQpW3iNE7pm1QS9mzMIYWUGaZZMzlNVSCZYog1VMnL+OudkwNXKpYYjG8R9kyxpjKmqkgwrroLvW/XCtzgar9LotzBZyqTLAey2LqUl7vkzKbLt5OyzhZmIELMrEEB2IM3iy+TnpKtgJP1uoiztlrnyytIrcAMSpvq0inXE0rC9NpAZmq7xZUf6X6/gKyIQ5BfQJK0jYyVd6aqixPNde5juMqqazAF6JBh5YgR+ngAMVU9poyBqs9vOq/TQWgRAEEWcoBXjGYcklVepNgYWCW2mfqA8ka/V5ewL58mQd0d9oOpko2bZ08FjqvsIB6LC2GZXHg07Y2moSr7Vvb+0Iv008mECfXh35nmvq2b1NyFPGk6kmwelblQhRHSfWeZjV7DllIRdT/RiFfcsoka7QE8XnE90/EPGpG01ZfvlglnCZfxgkF6wSqfNmUqOAQIIQVqF6yaFrZNFXJrVCyJZcqQydjTGLTGRprNBhLRs+zZKIRvFVJlsWTcyaKSrhyKZAqW7AkrM0QM9tupneFr756rQE0kb6TtUvGODLHTKQypsTRdnua/o5iW5XXJc3Qi/UgljzNOg+UomBVypACpXjUXkfnj5zBOcglgoy1tQuNFW53dxxCwNie589esL+/Zbu9w/iOiHCYEy5FbAPOJyZgyoVND+/vqQCf3lMtFiC0rSUnePn+hyyActP3+A++T9du+OyLXyDxgVfnDX/208zT8Y5f/OmnjOMv+K/+zh/w27/9Q372ZwfKVLP30XEchNevR1xjcF4ZrTFWD6YSr1jUy/O1zm2l4IqQrGHxalxl0OJZpHZZAi5Dkax9SAqSoRhl8mRRK1qzsCoRhcmrtE9yRsSQvVUgHsipqFx8rRL67R/JF8C88p2KrM9lqryuZK0MpBVlL2uuC/u3qLdTzhQLVENf6zwUZcnElLRC3RgY87B6eORcNIliDGFWmNc60BnVME+BUjLOtJoJT4VpTmy6HUYs1qm0HCmEqMCUMvNEGZUpY4xDjCGXWjnJNTix5BwRUfPzOUXazun7XhOJXdvT+Jbz+YSxlpSzskSqZHwcZrqu48WLFzSN583br3l6OtQ1jK79jNEKlDFmvM3M81gNyRseH5/o2k6BsjgDomOLolLDlJjGia5vqodToOSgxs2+43g8UHKmbVu6rlXz7Kjs6xAM3nekrIHk1mzqGrcQwkzbdsrqCQoMlAJhnhnTRDUHgKECYWLUf6dCrDllUlTASav1Cl23wXnHNE10Xct2tyHnxDiOTGFkGLQq7v39PdY6hiEyjXNds5jKWJs5jxNt26k06zSSokqJpkkBrBCyrhGs0XnVGcZxQFDjemOXQjFGwXgy0zTqMjoLISWKE5CG/c09MdaqlBVUlSufz+t1xbd16zY7nLXM5QwpYWymWMOUM8UXrERcDDjXkbPQOEcskSlOmOwoqdB0Rg26Hdgm0UmhGME48FuPF08omVIcMQRiVpaRySrlaq0hpsTx8QnTC9b1mJSIYyLnrNKsnJCkcVYeoVhlwLn6vBjjyJxmSgSPR/JS9ACwmkjNKSHWIc5g4lz9NSO5qKSu7zrGKTCPE1K0yEAhYI0mgI3xIKqu6KyHVBjngX5/S6HhPE9shkeVo8tM23ma9z7g8PDINEVOw5nhNFJixDuHdxvSCCSV9Y/jSMBiiyGPE75ruNnvCG3gdDhxOo+M00TTOEqKah0BNF1LNB5rCyYnMOodZZxju9kyjif2z26YxkycilaDNJYpZlKaMMyUkjCzJ00Ru/XMKRHjTEyB1nW0jeV0PnI+nnl8PDE2I1vr6IzgupbUWvqbLZmZ8jRT4sQHL9+DFNn0O87DSIxaxTnFQtMITeMUcHaaiHY1WE8xkxLMYwBvaXz1sDUOMb4CTg1hPlEkkMOZNA34tme/N/pMSPpszuK1f0+B4+GRQkIsSC3e0xgQInM05OKwzhBSwFpb451fbwT/ewFP70jX/gNs35S6XZsay695IWso8285p3dlcOuH61F+Ofh4JyBZAZTLd9YXfgUA9qtCmcIvYSvvAlQLKwD4pl5FFvnOgihRwairz+R8vcMl8FW2xqVtLleqpKwrH5pSgRr5xiUue1wD5m9gbOsvl0huBXeu3nt3lxdwjAoVrcboXI5/FaNrMFwfUkpbTTXDamvAY8jFUkoNTuoia9ln5goAWYCmxUvh6jqUMVVhshXkW87jsq+ru/UbBD5JXZxpOWtfgaZUM6Sy/JTFZ6su5kUhn5j/bWNILrgmGugaI1f+b1pFLNd+UYV5xPrVFcCqfXKBZBbQaa2mWEytgKgZGc3+SzXVNiubxdTv2gpmLPwgvWVSS3VXGd0aJFUYSGo2HwV/lG14aRdjNLuz+DoZKzrGKvi6tBdcAMtFPpfyxYzyUs2uStlMbRXjanVBBed0dzra1ZdLtOx8prKU9Dpy5TOJqJ9ZyhrYYQxWstpFoeaAuRTE6mfMCuOUCvRczS9Gq/fZClbZZWF4dX4Op0EQFg3rL2NscVBa+4ks10idby5SODFSfbLM2pZGlNmwVrhbWJwVmFNpbQ3L6o6WwO4iiy5rz9fvsIJ66+u/AQErgGAJoFk+UelRloJjqe6X6rWkKgFY+nfGloytjFCVSkUwogy3UhRUCZbiCkYc1CBXK1UaMIWU1Ass17FlF4zeFIzJ69xZQH8X1HiaWoFSoGAgKRAZ08g8JcZQiEmU/WhVeh1S1nMss5bsNaD+ZRVkNsq2kpy57eB7zx3eBHbbDtn1vPr8kX67JQukkJQqXxS0S1mD4bbZY7o92IYyF8Q6oKFYS4pHNeOXDCQoljBbSnFgHGINrvE43wJaWMB4jwAxJ86nE/vtBtc53t+8wPktqdli254klhQv7VRKIonKZazJRG/58gz7HrYtdQyqb1qkwqq54fmH38fEga+/+oQ8TtzuniH2PYbhwJsvP2Y4fs2rpxfI7W/z4nf2/MVP/hm/9Ref8Pw7v8+Pfu+P+Pl//49pWvVdmmfh1dcF6yI3O8fNM8/T25kUCxiLrazEUpmjykbUgKmIJYvBFJ05M6V6PFVGc1K/PUlq9Lo8TwxqPCwYimkoTCrhQPt1AUw2ZAJgcFKYigZheV21ac8XKcQLrflbu+UKCpdyWY/kNSGYFEwr+TLHowD7Zc1Sv5sVnst1rp/mSNN1nIcjIUyIoDI7FIgJSdcpKWaCJHrXEHLQRCdCCBEpFjGOGEaOx6eazFHW7jRHutYS5siQRrz3gBYjEBGenp4QMXjnSGlSw1pj9HNVXtS1HW3XczodGYdR55KceXh75uXLDxjHgWlSiRxR/dasszjf8PD2UeV0OeOd0+eutbRtR6xgzn634/buhtPpQMEBQuPb2p76XJmmiRDO9XupVrbz7HZbpjHgnOXZ81ugcDoeKWT6TYtzHmPBWMPpNDGOM9bp86rr1WQ5hkzTNIhRFphIYLfb6HwWEqUUmkbbzTcNXafVyJzVOSlnbbOF4ZSyzqlt22JtQ4wT3rcYG3Vtbw273bYyiyDME7ZW/cu54J3l/tktX37xJTmrVDAGoe1abIGYkj4tYlKZ4zCoBUNB2UxJZZMlw75T4/nhfFLpc+OYw4yJ4L167XRtrwyd8bEWFFFfwca3bHc7nj9/zvE0krPh6TjybLOrLPn6lF4rDn97N5uFkCJFIjR1/W+FOBesN5AF37QYp3NUSIGpRIyz+NaSykB2kSlmTLZsTYNrDal6tZkipHnGJKNBkVjEoNLvYjHFMQVNykwh0GA5lxPd3RbXGpBWn+XGME4zzgqTCMZbXAFntFJrkzMhKhPZGmXxTyUTy4yz4J0llYBlom1MfT6DkVafvQgSZ1rnGOJRozhxRNH2MFLwTqC0ODLeGAITmQHcjEjDOM18/dUrQp4Jw4mSCmMonOfI6XzWSphGcMZijdOqu22DNVqlEpPIMeGt1cqQxydsZ7m7v9ViCzHiKFgpbHYbUtakbooZ4wrbvifOk1atbRU4LRniFDmfBoZ5pjcbUozEEsEaHX+dpWk7MoZxnIhpoqRASREpifPjA3PO5Bh58f5HbJs7BcIBKZk5z8QCJkbmMPLdjz7i8eENH37wHe5u36NtWtzjgc1ui289W+vY9h1iLGKdGnjHmSwQJVGKQ6xTRphRn1PiuT4fEkkiQQKxBEwuxBmmcSIWsO5EmwrWFExjkMaSBcbxzMObrygMULRaqrWeECb1Z/Vr3VssmgjLRMoiJfp3bP/ejKf/Oap5CQvq/+t8eJFRLKjFr/6e1Srey1fW48hSPn353FXQ9M61fnO/V2DQujiQFVp552NrMM2y6Lycy/LlC7RxvdUKMFcBkxGpzADqQhyW4HQNtoxQfT7fORvNOi9V8PTQ5t+GOK2ndwEArs9OWICX61crdTz9svfOej+v2rFcvVyRq9Wn6fr+Z+Bwivziy0e+fHMiRLjdOD76zi0vnnWIjVUCYNcF2rKlK9DpwtTJFVqprI+re3ANOr57+xeQ4p1P/UZsC7BoxOCssMjOLAvzbgnqF9CgAoLV56DiNpfM95XHmBWjfjwChlyBmQVglMpMkorEazbT1p653OtrieySLbwaXnoNFUHKZQGH7ApwKaigYLU1ej7qu3TtnaQLfWUGlmqaL9U0vQZUtU+sptrLuUk13JYqv6v+UatX09IvLhOLhkdXpb+Xtluq5BnRCnamGpUrq6jKJeoFF7MYzyp7qroX1aEiLGyhQqbkBFmZXsXoOMyo7rABYq1OAQVbb2hmAR21jSis0kG9hxVEYPFgMirhqu138UyCBfRWBpVVduLVtbIwJkoNXKvR7qXipgKItoKTts7CZdGTL48EqceqvUTZkToPXeaqd+fqtUKf2Atgiqx9+tu+5QzFGEqsJdiNzpWuZC2kIGBzJhYtr26LEMkUyUrTLyq0tCljXaZIy+uDsNsWnDNYH3HGIJWPaIwjS6I6aqES9MpYFBSUqYCfPmcy+QqARCojTtDqZ8UgJHDQiGWeRqZ55vWpkEyn7A2xagKc1UPNFJT+LYaGghVDMgVLYEOky4Xd4ZH+HIhthzERMQ0hZox1xFK0mkuYsG1HSUYNmp2CKMZACWfyeKCkjLEb0uJcj5CKJWeP4FX+IqVmBjVDakQraDqjldikFGyJ3Nze0PZb3j488Me//UOe39/xL74qpNJgMlhJYDylWGIqui5JkRhnCC2HEHk9WJoGJKuJuxHwXhBTOFb6WCzw8ccf89//sz/hP/sv/hbf/8HvcXNzz/OXH/DV63/J5x//mJvdHZ+/nTjOt/zdv/8L/uu/c88H3/sBX/7rZxweP2a7EcYszFMiJuEhR7Y7z939hsfHkRBrMqAomJ2LMlNTnhEyWZJWoisGKanOFxUOzahPXRGK1fnKoAvwIiqdo2RsiWi9p1yBKfXigFKzZ1qcYg1TC1fMyQImYX8DpHYAKSUtwJAVfiMbClHBp1qtWCXl6JgtOiKvGf8ZHe+pwGkcVQRt1HNxu91wPJ5o24YUC3EMOO9Vqmlg07fknNntdjSN43B4S99vaJqWYZxIKeMbxzQp0NN1LTHMnE4jzqtsCiKPj09st1s2mw277U1dG2nl1MY3HI5nnp5O3Ow3CIWHxyf6OXJzu8NYVGpZADyPD0+M08Buv2W323I8Hui3W7bbnmmamOeG3XZPzpnD8Yw1QtM6mral73vevHmLNYXD8ZGcYg0wi1ZeFPXjefbsGSUXNpsd4zDx+HCgkNnfbPDOYq3j6enIF59/UZ8p1eQ8RU7xRL9tSSnRdVucGzge1bsqJTXRPp0HjIWXL5/x1RdfElPmxfPnDOPINFf5nFUZ3DSNtG2vFWQlM08jhULbdZVFBHd394zzRJhmci50Xcvp/ETft7x8/z1OpzNPjwesdczTxHk40/iGnBU4iHHmdHyk7z3jFOlEDcat81jr2LcdD0+PpJJorLbjNI4Mw6jAkSi7O+bI4fjEbrun32yYpjM5JS3Z3lagrZrTl6JSf2scyahP3G5/Q7+5o2335OKxBlqbcI3HxDqifxUx4Fu4hTAyDkEN65sW5xpy1oIzuoZSqWGxhphGYmWEWyyCxwjMwwEvHSUVJHgKQmMbpilxPsw0nSPGSIkzpQRubhpc0/D21UDJhmgKc5hrYgmIAykd8W5DKYan44mYDU3nMd2WGfAFpCQKoVbEVEmdcwXvEhJnbKjzz6z86JIhp0CZqAxLZb0XscxEjmEgpoBpwGw6grNEAW8crWtorKOThsY4cg4UKwiRML7lPDxgc0t5k0gxMp0ipwHGlAlpZswjQQKugc43lDkTSNBEEoKzDmegNzqnJUkEGwlTYJd6dvs9MSbG8yNzmnGuw+AwsXD4+sDd/R2+F2yn66rGtsxTxqTIXbvl8HgmzJFsjvgXd9jGEcbAaTjy9dsDu36LSXB7+5yQEm/ffsm270ip4E3L8emRMA784PsbnEuM08hmv0GsZecbxFm8Fwgz3/v+dxmOM9t+w/72Fu97rO/ouhbfNpQykVIgEmriPmOJzGHGoR5vhhbbKGg8hoFxOJKj+q8JkRAG5nmEIIzDkZTPFCkMp4EcMzjYmFu6VkHk8/GJ+XzGF4cUoTBSyqTFRMTj87VNjsNkzYZ49x9aardMCOuCv1SfBNagpDoQfCNwlxXAuXx/yeLrvha5xIJALEbDC3laynXAe9mNWaug6KJXd1fWwGQ9l6sTMldB7mLeuQS31+COeed6rxvhemaUy8v1V10UXE5lvd6rIHqV0FwFT8uFLCDYZe+6E7tc16+6r1dsDVMX/JcA+AJ0XV9Fvj7t6wYq715hru2u2msNSpcS8Ev1t2tZ4NJEBsj2GsxZwplL5LiAX2VtO9VBZqQWUUuUoovPlByffXnin//ZJ3z2MDFGXWRaGbn95JG/+lsv+N0f3dM2IPkCIJV6QhZlV+S1zauJ9eL7UopmWYuKjeQ6eK2nvEi+bLmAd8s9+rY/MN/ZqhePiIIPi+R0lXXVQDIvYEQpaIUqvfeLhVmpDB8jBidLeWsFZFwFPbXtFDBxohUzohTEioIV8Es463VbipEasKJV8eogEqma87z0Xb1Pi1zLAM6ogaNUpswyek2dSIyaUOkckBXssNbW4+i1mPpdBWEWkKju01wqt10zm7Qvl7W361DUgJ4FqKqg2/V/1amnXp9KVqjZ8XXYrD/0c7lcflNZ3+LTJizeEzWsoVTZHElWVtXKXqqgshGjfWKpVFhQcE907hRtkLVfqLeKglymaOnvi+ltZcjY2pDKk2E5YeHi76ZgkLKb7PLMKKzPBX1GWFXQ2erntexr7S+Ln1A1JjbLSBescfV5sYDz2nczv+yz923dxKq3lkGvP+VCowNV/XQM1NJ2kA0ZS6rjPBtLSoI1hV5GNm0hSMtwMtzeWJytYBFUBhNriXtbvZ5yqYBgSco0LRWkXZhwS5KjLGByQJypxze4ktU8VgCTmcfAq8PAnG4ovsNYj/WFaBxdAScFk2AUR5GslRkN3BG5T6/4wH3Jzp4x7YFd81c4jIk5zFjnSKned3FkCeSgYKlBENtgxBKHMyV+RZiGyhozmrXLKv+ypiOVhDhLSSPOQownKDPWdJVyX+WPaFlia4SUE3mM9Dfv8+XXb/m//V//G7b7e377v/yv8b5VPyRLlcMWxDRQDDlBDAljJyYnPJyFZ1vBOWUGLYpmZ4XWwzQJ1m34wz/+W3z/B79P13ec5xmxnsYKz1+8x9MYeJpe8dt/9Ee0+Q/4v/wf/3f88OPPefms5/3f/h1O//gNw3ym74wyqkIhzYanh5nbW7i5bzg8nAmzV99+1FS2xKRj0hTIyrDLVbKd6/2VbBSXzOo1tsyLMReMFbIYSlEWprFJSzWLMvqKqSuEBAmpfcuRiyYasik6/FMiFQ1Ekvn2j+PFK01lZHXNQy2WUoRCZLFNWJIKul5LlBLg8lRR02sUUG68ZZ4GjDHKXkLwruHp4QEjjuE8kZJWdxvGSauPGcP5fOLZs2eM48TxeMLYgvfV78kYZS1IQgx4o20/zcqoeu/FM1zTaBn0ELHO0DUN5/OJeZ7Z7/dsNz3OW8I8s7/ZMw4Tp8ORmBJhSvSbDd/58AbrhPO5UabW+UgMiS8/f0XMM7vthsenM6fDiaZpaNsW5z3n04m3b9+y3e6wRmWCMWS6vsU5w37X8/R05nQ8q5+Kc4R5YrPd0PaObe4Yx0FlJY9nZVmS6Tcd59MZUC8kYyxtNR9vm572dkPbwm73Qv1zKHjvcE9qsK0y2I8YxzO+8exvb+g3HYfDiXEY6/yUKEXZVG3bVble5PA0qKl5KkxzoOSEsep51bYdxmZSCnz5+Rfsbm5xrmGz2WKtr+N3wrf6rGtcz/H0xM3tnrbbEeYAUtlX6H3sNx0pqjHx6XQGoO86QkzKDpvVx7PrPDGN5Cmy6TpiUgZV0yoY1zSeGCPDMGrl2FLXEs7RbW64ufmAVJ9R1nqKcQQR9Y2NeV3f/ZIq5Fu2tX2Ldw3TecLgcDTkkjRBVoQ5J2JMkNULqfFajdU3yjCMGPLQ0HpP01ic65iniTIHKMJ2tyfkxGk4YQq0Hbz38o7N9pbT488Zx5kpT2QPORp2jfp+xZgRZozxdH3LHHXuFVcwpmCIIIkoo5ZlEqe/p5HZqNTKSYONhpyCAmQFZcy7RExB/RdrEQPXOg7Difk845ueaCzkiHOLJ2qNq4zHNVvG05GYA+dTQmRgPEzEUZNkiOd8mNSjsgSySWy9w2WV4Zdi6LotVhJjmchmQnxLWxyNVUmgs4JznpQKj69fQ7PFd3uM7YmxEGJmszHsbjqcS+z3G/quISE8vh2xJtEYT4iZmCNd1yON4Wef/pxzOWvCJ0TilBhOM4dwxplEngtt3+Ocw3UeB2w2t9huy+cff8KXr79ms2noXKZxI77b0nQdvtkoMFgKu7s77u6E7e6GZt9jbUPnjRqcW8jBaCI5JWW758LMSAojZdZKkN2mo2m2ZHEYLAmrQNU4MT494m1EDMwxMqcRjCEbz5wiZS500uNMjzEdMSfePLyqlQ49OWRcMsQyakxktaBKTu5i0WD0WR2Yf61x9JdgPF2QhWuDZeUIXAChJZxiZYYsgEtZv1+dELkEjEtImK+YA9f7452/l0oIy+eX/V68f/RTiwXGO9sqJ1o+V4Pw+pu5kuws+7Lyy7PhejVlkZ8sMVLN1i140nXrXe1GarB/AZ8uwM/y2nW7lVLbZAnSpbw7Sa8gU7qAR7Wply1fQ0plAYXebbN3ZGOywIJl8Sdeg/rlHi1eK+8gT7+yvRYIaAEWLr9fGnNBeC4/BSGL8MXDwD/6s1/wyesTM15N0nKuJXdHjj/9lGQmfv9H36GzC5h5dfwrBpQSMzSnZSrgJdXfqtSAWuo1Xs71AugV4HqNm5fr/g3ZFi2uWRPEhVQlNEvAr+we1BdICiarOfiVw8casCvAVH2BxGIpFbiQldmzAoAV7It10ZFSql5Ti7Snjgs907VVU0pr1rdkze5expYu5gsFZyorp+5qYTytAFOdExaQRnExhUPMcm8XxEyWh2dldBiVd8kSAQorhd/Icg4VQBJFJxfWEUb9llYm39LF6zWtiLUtXKZPBV2NKKCz4DBL115YYXmperS2hV3PT6xAqZUGq0+As9fz5nI6l3ndCNU0WlbGwjKuFxBOx3EFerJWD1JJVsLGVOerCkCIVLBnkcWW9Z7YXM+1KOtrNVgXLuDcFWgIKgvL9QZXCJxSEpBqIHcluVvuO7p/BSPXgbAgixf0+9u85YIaHNS5WhypJM2yLqCAFJpcmAykIpjia/W/ApJrW0buti3znDkNtUCAoEby67NIH2hLkkSD/4LNnpxaTseGYXDMMeFsYbsL9P2MM7H2eUPKXfWUcArmYNY5OKWINZbbmxsgYdOEIRBxTCXpeRhDYy1eIhIzphQ288AP7S/4o9/6gg8/OuCbAXHwyeP3eHgs6m8VA14mvDcYCdg80262hCrFFtGS6Jt9Tx5nle3WcRniwBQTLqi/iXGifVqELOpdIaUjZ0fOgrdASYScVU4sGfBMw4k4nfnOD/8qzQ9+G2ccrRPUDt6olxasslGqrCqYggkROc88SuZ409MZTYpIXYsYMp3XOStkoGy5e9YxJ3AygTtju2fcPxP6zY6f/cWP+ezzz/nrv/+HfPT9P+T/8L//b/mDP37L/+Y//9uUH77Hn/z5T7CtsN+2nI+BedRzeXoMbPaGu5sND8dInHKVhpWqxW0wYkiSlKVRk3m5WJ2PqhSPYhFnVdZuy6Ufi0qLF7c2Kyr1sraA1XFqrbIExCqlX5zRSk3WI2J0AWsNxjS/EQBySOrflNdkS1mLbQA6j4nO1Yt9QmFZgegauVST4SknznNimCPWO0pOF0arGI6nA9Y5wpRWaZzK4TxWjLIArSXESNdvEJk4n58QI+x2N5xOx1o4w2NcrZQK7Pc3iIHz+QQV7GrblnEYGM4n+l4ZB8YYvnrzJXf3t+z3ew6HA+fhjDUtu/0th3LAN5Z5Hnj9xVvOp4Gbmz339/d873svORwOzPNICBP7/XOapmGeJ8bpjHVC07ZY59ntdjwdlMXw9HQgZ4gx8+bNG3JSw/V5nghBK/JN82cIWv1vu9niXEvbwNPhiddvvkQOmaZp2W465lkN0513hDnRd4bnz58zjgOffvo51rq6BihYZ/C24Xw+Vx8l9UN6fHygTtD0/RbJ6sOVc+Lx8ZH33nupgGxMbDdbNtsd0zQxTWesBessr776Auc8TdvSNC2lWN68esQYT04nYgp0nSc5XbMN54E5JDbblpwNw6iV7rx33N3dcz6NfPXqgRACbdex3e7o+555mhmnERAa76FINWQP3NxsySkzTBO73Q7v1YMIUcBcvbhqGXe0cuCLl9/l2bP3efv4BrEDt/tbrG1JFchovdHqskntM349oc5/vM1Kg6HQbhzn85nT0yNN0+CKx9GBNAxhRFKg946cI+Ok3lmus1gH/aYhjwnXOjbOEMfMPM9gDc/2H5BTIbx9AsDbhtefP3LuB60023oKgSmj7KeYVZKKJnZdazC9Jxwiki1ltrrs8pkiM5hEiQYpQis6pgUhpwJp1DncZFKOxHImYSg24bzBm4aQMokIxTKGgmk8rnMkm3HeIiZTa8bVuU7nm9xmwpgYjpGmvWOKltN44jwNiJ3UM3WaiZMyo2xj8MYTJRPIlDzSeIcXy5wCMDGHQGc2xCnRda2CrZsN43hk0+p43fV3uJt7XAO20wIogcA0H2sFScPxSavWdptNLV7RcDyOdJuel++/TxiP+CiQHQXDhx884/A0cJoeePP0SD/O3D9/QTYwTgOnaeT5dz7kMBzodj2tb+htpoRILjNzOPLsw3uarqN5+QHb/U7b17UqexS1HCg5MOdECjM2ZQX9XFS/tTgT5jN5TuRcgf1bUB1Jo5X7imOKM2MMCEJnhBxGhsMTXbdHbEOxVabnerzrcMUyDke++uJzDsOJkg2qIGqxxem9B5Co/c62xCxQAhlNQPw627+H1O7dh/sit1giKbnEFGuAdO3TJOuCtmbqr0Aes4BO12ASiwyMy+cLLIbAq2/R1aJjAZauY6u1QhzXkrzlNX7pfJaaUsCVV81lW3yE3gngZIGxrtvqcu5laZR33r8c93LNFQyrMZHOxv+uoKj86s9cvWzqCRagxmcrQQzhl4rxSYbV6eda+sSF5bGc2Tu9ooKKolzxd8Gs9f3ry7/sR8PN5WYbSrGMc+Cnn73ms4eBCad0/RIwRYOZYCxPc+AXnz/y/ef3bJ53V5BFPZQYlQjoL5d338XZdJ/l3bcurXrJ7r/TTizAym/AVrujrbIHisoQzQISXOGG11LXbEUTzCVr+dFSyLZUjw5W4OXdoVLNaWv2Ohf1JZBcmTo519hfqlH4gqpcxtbiy20WFowUBYqkAp52OU+t1mGrpxNcMi8XvVxlW0hZWS8ppwpUXcBuWWSXcvVn4fYt84MxVXZ3MQNXj1up/atm9SmQsgJgZmH5VXBkaeOlX0pdeC2gzXU7CldnWMftMqdJZQUsmNaCuq3eWdV3q9TAvwL/ZZ2/dMQt2fflnhhjWMzHc8n1HmgQZIQV1c7WqqQpF0qKGCu4kki5VONIi2ApV+ywdd60Rd+jyh1hfZ6sU4OBqtNhDcHS2mga4JaqL69Gt0u7GbFKNxarfaGCTeuz5p3Z69s9hoWIw5GK+qNJKTREbsqZ1h1pzECOliM3jOWWXHSMuOLUr8GASVkXYcby5VcjEQ3SWm9JkhCbFFQvoH3BoqLPRMmWw8OGn/645WevOg7xQyIOSSPv79/wV3/wyEfff6JptcS7E+W4ZVE6fM7VPLp4RPZ4c0c5w85HxhIJxWt2djEEL5k0eYyZyRZaa/mgHPgbP/qK3/39z8FHKIWQHP6kBSZcNhQjhFwgQiBohtZ6coCYZ0zb0/Rb2r4nkwmhZulNg5kP+BJpNh3HVwc68XgjxJIoxZNtj8kFSUJJEE2GknQuMOCMA9eRKDwd3vLi/gWu29FR2DiH9YYYHd5qxvFKMI9W64MpJ2yYCYPwcAzctg3eoPNKUdB/YfSpj5uQ40ycJowROtuw2214/fXnPLu75f33X/DjH/8bvnj5Pn/8t/9zvnxz5B/9y7/g9773c370n3R8edrw6auJ1gq39y0PbydisRRxDGMmY7i523M+T4So85vYgjivcssqyy1ZqwIZ0Wx7RiW7RaBxjoxFJIOxOAzGNVhnKEZlyA0GjMNUc3asymJ1qonVg85iUPPUYg2kpKbVKzDz7d5yqlJgLr6W5Qr0L4iCtEsipkLBpXqb6eumMsgs1lskV/ZmyQzDxBxGTscTfbfhGEf6Xqu1zfOMc4ZhGChdy77fkXPCGsfpdKTkTNdvaBqVgjVNS99vOJ9PlJLxfjGeHTXrDez3e+Z5JsaItZbNdocgHJ+OTPNM03TEkPn4409pmgbvW2X2xUDbCilNiLS0zYa22dH3LfM084uf/0RzMVlZtsPwpM8kEdquYZ5G5lnNlL/44kustWz7DX3XK6OmZM7zmc2259mz95imga9fv8E6h2CqRA7evnnLOAXO54n9fs+z+3u2uw3ee06ngXEY1WS9rpOdt3z66ae8efPIfn9L13WVlVRLrqfIs7s7BIO1lseHR8Zppm97RISnwxHvLB9+9JFW/sxa2W44n2oPKXz55SNGhKZtCCHj8Wy3W6ZpxojldBpwRtkd43TGBSGXwPE4c3Nzg3MtpUz0fUffbomz4fD4qEBRA+fz15RSaJyv1eo8x+OJGCNd29NSPWBiIoRQpZdqzt53Pfv9vvpx6bi/ub0FYJwmYozr+qnfbGmajoeHI863vHjxgt/7nd+ldTs+//xT5uEVpajJuz6WLd/2Z7BLlmwK3huaImSj4A3FIsUhMdO3PTEUcgwIhhQL4g05FNJ5pN31pK7gG8sURrq2Q7CMceLNqy+xxUIFqM+nzKmAO0x0fUvOhbbZMp8nJMIQA763zMMJmzvaTotWdNuW4TSSxZKyrnVyKggNpXimHAjzjCMTQ8BZTyKRSiAbmMNIsbpGnc+Zzrd0255hmohiGOZZ+7gIXdcgxuK9x+aESUIYdb1im0gqEVymlBGPp0xqDB7TSOsLRVL1QYvEOWPblnESYik437FthRQmcgAjLZ1tYAo0TYs3Dd60NG3LMJ3JpbC9v6PESKNcfG3b45F0OtNsGs7TmfPjgZKEpt1qoYAYGE5nYojs7l4wHk8YCs+f3fKUlLn93nsf8tkvvqJxhvv7Dd0sTOEMIbHpNuzu7/jss8/ZbW9oXKtjHsGLp/WOYjP4hrbfsb29RRy04mhbj3MeJ3pdcxmJKSorMgdCnJnHkVIiTd+y3T0jz8J4TPjW0G2cJhqeBnJOOByl6DN4OD9xHh9IRpiMZTyfyGPWMer1GS5NR3aG43jATyc+/finvPrqK/WpKlmZfdKRswKJOc1a1KUEtX/Iyqbqm45Qfj1I6S8JPC1ZZA2ETJWmrbp7uYA4sn7uG6BRDVguJrsXfxlb/Vnk6nAaiFwAnAUuurCWlo9KPQX9kGYSS/3O5cOrtGq5HC6il+V3BZ4u/jSXOOYyKdoFVbvaN6WoUSQLgLEsKDSaVyLPu5DFBW65tMflsPpvc30OV5+7hKYV6KnMi8vuL0BTXlCmy2VzCX9ZKxS9A15dne+lahc1MF6OCytDCbiATBc2l7Iplpj/GpnQz+RVdnk5rF3aCximyOevj4SgC0+9KEspSbOvWTDZcDgknp5GvvNcTdbWo5QFNljOtZ5vuT7fyzmtX1rb6wogrH/eycz8mgb4//G3pW9V76+iAKrN2j8uGO5loMnCjCsKyCjDTT9rrJqGi1isqGH5EkZpKXbFPkpdYJvaR5UYo6wrLSVdPYuoErcK8Bm7MJPKxWC65MriqXexdkorgq8yrQVnskbBp1IZSrJOQIsETplTWTUPCnzUz8gKOuUVCFVvp7KOs0Vat4LgZmFQgVQ/Hal+JXUVvcrAFsbdBYSp0ryilG2VtHEBhwsavBdYvHpKLqvc8QLw6o0z1StKf72AOBeBn8JNuQisvlKZnFVCY4wyEKiAjZIyKvhsimYpRS6Jhkw1i5caIF+eC1IldMa4q+DwCuhDZYHWqhPCtexQq9UpqElmDdqgVN+sCxh2nTwoVLaFoMwIq4a0VEN3rR6kx9WyHf8hxtf/tFsS9VgqWEzJ3DDzTN7w4c0rvvPdA/tt4PDW8OWrPT9++pBX+QWz8aQidb5Uueeub7nfCa9OWibcikFsUIPJOswsCtaLKPBgxfDmdc+f/MMb/vztBxzMLaO/x1hHSMLDmzek08+462Hz3SNjAiGRRKvlaNGHXKWxiRwdebbE8Q2/991b/vTzzOdHpblLvXdOlLdvnOcDc2Rfjvzw5hN+9IOBuzvLKYyE2WBtQZhxdEQM1lhsEfV6ES1Tvu1vODFSgo7VlGaOb99ACEhKOh9ai6dnmEYePn8FOdLfbchZMDnhpSMYg+RIzkmx0JTJknG+rnvE4RsB23F4GgnDgWiEz159yv/iD36P+5cv+Bc/fUPb3FRfNkO109bzKgUTI9lmYrQ8ni3jnceJmg6LoN44dc6Zp5HTNPD6q0/45Cc/4e7FS26ff4SThs1mz09++hOe3d9gcuIv/vRf4JqGu/ff58O732F+PvODPzhyLh9i/mJmjkLfwu5lIWRPzg5sXUuVzI6Akw5xLYVUx3Qt7mBy9SrSuSjlQAgzOk4rVFZ00QpFrQNkpsRMTpGIMJHUTDzPWsmrFHKKKyMi18IIVGP2RNLqTSKArcVEvt1brlSnIlKLbSwJjQVUXNZRl++8s45EZXoYwziOzFlB1YKyh8dhZp5ntts9T49PdY40KwtnmiZyzji3QUQZouOk1eLEFB4f1Pj79m5PDIHj4YjzDZAYhkGBCu+5u7/lPBx5/fo1bdvSti3DPHN+8xZrPX3X4ZwyZuYp03c3PB2e8L5wd3uLccLpGChZmKbM6XhcvY1yVukXIjjX4qzDe2U7KbtKq9J5B3Mo3N7cVA+rxDjNlDxVv0Ehpcjnn39MKdB3PfOcmOeAiCHGyHa7oRdL3/V0fcfh8IgZADY46/Se5MI8Z6x1jMPIs2cvyOmB03hmGM4qs3GG0/nIpu90TJ4HRCyNb7m7uyemxDzPdE1P2zU8PDxgTUOYkzI0ugbf+NoGgnNaQZACKal8PZdCSpm+2xJCxHurga9puN3dajXDGDkeHwBwTnh8fKrV5TLDcAKBtvN4p16RMc+EONG1HSOZ8/mo82A1KB+HzOl0IsaZ7a4nxMD5fGKz3ajUMxeOx4NKXZMCVVIE33uo8tDdvuf9Dz7gD/7g9/mjv/YHvPrqaz778hecxhNZMj6jTNVvOegEYFodp0Oayc7hxSARNerOE82+JdvM6TyR8ozNDtM6nNdkV3EtIYJtWqTdICESxoAplt6px5brWx1zxiMijHMkkclj0OpuxuLFYq2Q5pFpjDSt4ZxmPBDmhLOOjffM40jXORpjSTTqDmShkDHJkquU0lAIRatSxhgJAcQ1xJyx1nD33p7xNNcki5CmiZIizaal6QzjcaJrBIfuO5fIMD7SidDkWyQvigGhpJneGUxU+et5nEgh0W57Yh5IJmNsoRGV8ZYQcQa23UbnuJgwpcPjMR5817LdbOla4TxNxCkzh0SOB/WJnJcCPg6XW3bNM2IYiVMh5YE3b9/S9z3eO4bzE05GXJ45v5lwBU7DSMozrfU0vmBc4vT0wPsffMDx2HA4HAk5YnwhhhMv3/stUjbsWsftruXu9pb9zS2mceAs4i12KzTWwWyRqD6aC5Msxcw0T0zjCTGJkCOH8xkotJJpNhlrHM51xDhjTKFxopU6iz5jrAhTmJjGI3EeyBSCaRknSLHgU8SZTNdYvG/I2TDGE+d55NMvfkZIR5Ko028qHmMigQmIkNXXMidNVqeUyVPB+obebX+tcfSXA57eAT9KDWJqGXthzfqbhU0k7+I2l/0spryX31cgC1gesKbubwEw1sF/vV+pQFENlq9ZAStj6OpYS6BUv8oCQCxVq9atXAFpCxaxghKstO5roKyIAk7rLuo5qI/RlVZtDWTl6nyvr6+swTOA0dJDLKDYen7vYFjlV9g/lXWBo+ygy/FLDRopl6BtMd1+536thsHLO+VXAy3fEGcLiyKkLqgW+Vq57HIFA1dPJlm/LKItlimMIfEwRGbU9DovbI4CSbKa+mXhmAxP00yBWh2krKBJWZtM27EsbXjV9Ms7S+C6wGmL3PC6cRZMTipQ8+1/ZMLSEM4IrqIFMWeKKVi0/+esWUYdEKWCE2oSXXJBjNegi1IZZHUwmlr96gqUkWouvgjBFsNuSlnHrFneEVm9KwCuGY1mKQiwyMVQCVgqF7mcE9EKC8vpSJXMCcgVsLCYWINS0hXckNoHyjqxCLoTQQ2NxVRGjrEKbhlTzarL2k5m7SVyBYjU/iMLIKWys9UfrF5X1knlMm6uetTSb98Fht8dbxcA9er95T7IcvwF0rl8zpZlLFVZXWWnaYVkvadSFww1967zta0phurxpMXL6hznDGR7AfAFlbQZQWWKa8PonFNBTBGlgEtt2wWYsxURzQZyNhWoRAFJqVKUBRytwNsK6BmLs3YF0qQaVZuVXWXenfe/xVsyHsRRMnhJ3JUTP3z2ih/98Gu2L2asFLYbx34fmf+iML2Fs9yp3r9UNqBEnt8ZXjzv+embR14+i7hWgcYiKqmz1WuHAqlYYnCE0vLxTzv+9PUHfNn8loIeouLUaBxR7mjP7/Hix5GnuSOnibubgWfvjxSJCh4uz4ECIR85Dl/w9rHnZ1/1HOatLuSNU9DWCNloZaoX6cTfsH/OB+8/8uzlI3cvIk3jmbIlFq08Z1zGuwaDJ4SMiCHFSN8IXiwlatlyaxv63XOa1iNhQsSS00yMatCcm5623fHy9hklB9L0RJgi1vZ437JYi4UQcdngrFf2ZFF5QUkTzGec6WidMB/e0jrP9PDIv/zn/5S773wHs/sIw4hIRM3FvUqQjUeoRvBEUgqMo+c0FDY77QNS5ylJ8PT2M/75P/knfPb5x5SU+NnPf4HrO/7wP/3rbG9e0rdeDYPPZ7wtnI9v2XYbwlOgf/YhP3kaeHN+y3d/sOHxlDiMO8bTiKSJ3W3H8ZSY40SahFQSOY00NoA9M4dECYmQMiUlcokQ0WqzWQPQHJOCSkH9S8yCiyueD1J9FRNEwJekQHjJ5JL0w/XZLUXXA2bZQZ1HxS4SXfut94cBVVJHyVwwsrrizWrNr/P8kiYzVcqcQPLFO5TCHCMxg3WOfrNhDlrW3FrH7e09IQ50fQsiPD0NSC13D1rco21alaIap1Ks88jpfCDMWc2vxwnn3fo8QEQZS85RSuHw9IS1GrS0jXolgVY2s9aSU1TfI9dyeDqqgb7x7LY7Uko8HVTGF2NEiqFp2zWGmOdAjDPWGmzvOJ9HrPM45xiGQatMpQjUzH0FTLquxxiVhjlr8Y1m6VPQymsPbw4UDH3b4RYZWcyczwPOWWKM5ByZA8SQefv2yPGoLAjnPM5Dv/FV2p7o+qZWj9MqdnMIzHMklyO77Q4xlqZp1CtLDL7RyncpJYZx4Nm9p++VkdK2nlIK4zAyzwEkc39/xzgpq8CIo+9VvidEXR9Zw93dDSLC4XBmGEaMQEwBEWX/jlOidRvapsM7yxxGQAsvpFzYbTfM88w4TVAE7xT8CkGZy03raWbLPAfM2bLbbUC0OmDTWD0fEVJSTyhjTPV/CgznE869RiTy6uvC12+e8/f+/md8/IufM00nrESMa8hzqfNnuSoq9O3cxnkgJjXgd+I0qWUMMSWcM5QyYr3DN4aUCiUnWtupMtno/D1OEw090WZyiOQUSBXY9NZyPB10bV39xbIk9WcTg83q8yaifm22EcQ4TlOiKcImzjjfMY2J1nhiGLCdpaQaExUgRWxJOOc4Pg1ImXFdg3Uwp4Qxll2/I6bMfH5L12VEBkqJeOcI6HxspTrd5ogzEcnzui7XmcaTojCPka5tcM4TUyLmWWOJrG2UscQS2W095zARE9hG2GwaxlNAssc7T8yJzb4jHkYsWtlOWgNW/Su93eBkJudIt+k4nwa8d2AMsRQ63xMmYThpEDo9vmF3u2cukTKN9LkFgdPhgBjLHGe+fvuWftNhs+X49ombu1usLzStJaXAZtux2e2YSiKmovK5xmOM53vf/YiN79nd3tNvN1RDXZIEcp50fCQDyZJtxLlWpX4pczyfGIcBcQnfebpmo2ttY5jTRGcdTdcTqtdxSfp8jXNgOk8Uk5jygJBxNpOiIRQtgBKYkbah6TuoSeQiQgiFr1694vXj1yAzkuJlvS6Zwoigz+hcWnJKlKXATBZOp5G8+fXG768NPC2yhDUYXM5HLtI1U6U2y+usYE5+Zz9w8YphwaikWsWuASKXwOUb56JyKf1LgwdZAaBVenf1Pbns9htAWLn8LCsOsr5m4J1jVxyFcvX6u5CDRlP23YOsQb18Y1I1FYC7PvByDDELgHftV1Qw1bhqqdC2/hsFt8oip7k6P431y/qF9apXX4HFP4J3t1IuHjVXe3zHK6q+dl0m/vrYl3/VVqvB7zXYs4BsSylGqVGPel9oZZJRDLNz67JMS80WMjVathlxRo2rUXhiWar9qqGw9OXra12C8rX3VAAqf+MeFb1QvS5dFX+jjb6dmyzIn7l4WtnrwQFXYC31dukITLmsRvMiahIuKddxryacVhaWymVOkCqbWxO2yErFNiKYpTLRCiZWHl71m1kq04k1K2uuxh2102t/sqKebt7U45rKklkmkqs2kCq5k0VuisoUStYMsNRGUMWaWU3EF3merO/ly3XW/n1pzmWsqUeZgm1qwr2c+gqUVHBWan+StZ0v+GypyOl6JZXddBnWl5tmjYI4KoFZGJPVSUVWaKZ+fxlnUvXhFzmh3lNbJXBVUFpSvT8LmFsZV3l5mCi1WQSyWYBeVGZXDcTXe3F1/erZpV5UUgGq9TwFSlnkilRmRVni0nrMC0NSA1JTs8daJY1qKq7gYQ1a4eq+/gZsxmGTYc+ZDQ98uH3F97/7lu2LCWd1rrNtorvPvHzxxNOj4RRm3soNZ9pace3Is22DWI8zj7x3e4CSiLOCzcbo/OocNaBx/Pwne07DHT/7esvX8pwxq8RKLKQ1x2l4Iy/4h59Zmq+OtGHgb3z4NS9fWrI5VmajKGBApm9zBXRvefzEcooejLKVKBqMOevo5cxv5a/40Uef8cM/OuG7mbYDbFMN/oFSaL0ym+ZxYBoyRSIxRwqOWAx5HsnJ4NoN2/093nvScCClmThOQMBIQ3FOx1uaIc2kXLDW0PgefEsazkicsHmmaRzOanCuMnZ9zkmOGDSrG6cnDHe8+OgDPvvZn/Pp16/53g/OxDgRppFcDMV03L74iGcf/jbWbShitIpNTMxT4OkUuN8I1ljislaZnvi//5//T/zjv/8POZ+egIRYi/HCL/7iT/mtH/1VNts92Qqtc5QYicOZKMLTqy9omg943H7En3/+NX/8WwPbzcwXn31KyS1ffvKa3c0jsVheffGKeVR2kRFoO0e3aUklM749M02hPoeBFOvz/DIbSk4MJWKloQMQq+/lgkhSVp2Vde0CRcFnCtUkr1od1ERGZXvppuOe9E466du91fl2Ac9Z+s0y0VPWRB0LwE4t1nC1yBBjcY36Mx0PT5UVFWk7T9c1nF4/IMYwTYFcjaBFFJTpuo4YMzFoC8aYlFUTKijVKlsp50QphZS0IpsAMSW6vqfrWgUY58DxcCKmqCb4kvHOquFsjEwhaWBTgYXzcK4JLMFWRlHOhThFfAVp1GtIWanOaxUlsOqDI7n6UXWkFJimkXEcMdaw2285PB4gCTFOmFjbL0NOhe12p2BXCKQ4473jNAzknGl8T8oK1Ji5ME8TgsOIV5+eccQE9W8bNxtijJrMsJZcEiFMpKgA7BwmSsn0/QaRQqrMIDUU1+dzSpF5HolBvWq8E7z3+Ea943IOHI9nDoczzjYYq8zOthU2my0U4XyeMEnNoMMccFZllDkXYgprQSCtWudJRmjF0bQNxjjimOszUhmIzjliTJSkbCpb5ZQxBcopAApe6jnWWIOEZHR9WIuKNE2LFcs8TRyfHik5Mk6Bf/QP/wGSJ273G9pGq2eFHGl9gxEhpUAm/c85Gv/S2zzPOOuIOZAkYYvFG6deggjDpEBSTNB2G9I8YM2MLSpZj3Gi2zbYDGk640zG2AxNIUoihlyfWYHOF0qcaW0hG1cLOhjiEChzIBfwVmjbnhgzREOcIs/vtoT67ErGEDL4UmVnqUA10acUjPHEImQrCJYQNPHhWmg8JJNojIUpKbuXrGbTWGXEj54RLUgQ01xXkA0OSzIbSsqU5BAarMmkPJAlEnJmLpF5jgoaNRvePBxwRv0gT9MEJuMl0zpHSBPnaSSZrOCkVYZ9KQabHOfjE7ublmajY+h0HhiHAS8d0QqH44noEtvdFr/zHM4HhvMDZoxaXS5Fsjj6Z3c4PP1+y/zwhHPQec/t9jm2QLvxSAP7+4+YRwjzxPe/+yFfPzzSWs/z588JMbLbtuxfPsfjaXyrc3qcQRLn6UhME74Ine8AD1YoaSK7RLGWIBCzEIZEh6ERoeRMYx05zQwJ4jyToxaTMSdonWUeR2LIRBOZwpE8nGidw/oNvmtVreDAde2qqlCPwcxxPvDTT3/BcQ4gnllLmmtVZOeIOdPYQmO1ep46tUxkIrmunc7h9O8aQsBfCni6/lMXAlKJEWbJMF/ef1cytgSXl39rgFPW180SEL5zvDU8upzIN9YWa7Cmf2lrfANAeUfiVi6gwvW+r8GQbybAl9/Xa5GFNbDstqz/1sOXq3aCRTKySI2W9rJG5UaLxmkF0Wrwf/E6yZQ1RaY/s84flwdr1gVLXgP9bzIkLt/WAPJKLCbv+lytweKVt80iUStX76+h7jcBq3qg9b4tbVEWCOobpFpZGEhLoF2QUplNxtA2DucbzBgpRCRnSElZXEZZT9moIfK2ccqeKYsp5+WELqH5IunS3+wVlLj6lZXLOUplNK0AgMAS5ZZlofir2uBbuRXU2FURC7PKUS8AJGs/XSI77ZN58WaiQKqG0SIsZeotspLh7BX4RKnVC0sFKla2oKwVzPT+155hWMeLKzovmAosrDOEgCmXvmlkkerq9+wyiOqf5V4raaqO4QU9oai55YL4LH5OLEwfqRIwUN8bfXBfdv/NMt5LZ7h41OVlkBWzAkiKWQplkZLJNaOx7mfxu2IBatY3L59Zrq6Cd0aqibdZ5ugFSCu1LeTyveV4lQlUMBfmqVwDbubqPqXLV0W0Wlht1wrngFHQcJl2lc2mwNMyhBbPKJa+VswK2iu4J+v15kwt4y6XcQgrKGyNlidfZZBOF86LxxMVcCql9rn6xxj7DV+yb+/mEfZ54KP+c14+/5r33hu4e29GfK0MVpJWj7OF588DLr3l6zeR8cFwzhsSmY2Duxa+fHXSICXNNeOlba7VRFXWRTZ8+eWeP/mLD3lb3uet3TE7z5yhkYLNhZhRVi2GJ7flQEeXJ7Yc+eSLxIcfe15+v2BMgqILZ3IhJU9JPb2HOzsjZqJIwJgJgwcKJkVuzNf84P4T3vvBiXY/ICQQB0WLHYgRUtmSUkPnHJNN3D67YQxBK2elFobMdm8gZvWpywEnLVkMkcpeToIzRavYUZjnM2k8EFOhtS37/XNis8P4typPKRNCqOCsMq2MWMQa+q7RbHGMnJ9e84uvfkFjHClOhNOZv/j8z5nnSDgPKiczLf39C37wR3+bH/zR/4pkepBMygo8PZ4mTneOjde+nSIwHPnxv/5TNt7TbffkEsklE/JMOp745/+f/zenIPS7jpubPV1jVIJ1s6ekwPTqp9hnH/GTN7f84MWR735vz5//+A1hLvjG89kvvmJ/t2Pftrx6OpATYAtTCOQ509+07HYNMSRyLBib1UutKKiQRRTYt4YmG/WDykkLWBT1/SsYinUYMr7OPbZWaRTjVE4Y9VlSRJ/ZxVS2UJ18i4hKIZeF0Ld+M2qiLFJl1Qqq67NP1mdkrgVPcs4k9KdFn9GxRKIYYiqrD49KH5RpMk4Hbm72fPLx52oaXB8qMWrFvBi1GpmpZdnP5xPjGJinwP39PW3TEGPAOquyR1gToWK0H5VccN4zDFNdy1qMsaQYtCy5cVhrKngV2Ww36lFkBN96NUW21ePMCI1vKKUQwkzf98BS0MOSSiKmSN93WNfhnNNsezF0fU/JmfP5zMPDQ33+JCATwgQizGEipcRmu1kBHxFL55xKja3Vdk7al13ruLltMWJ5/mLH6XTmcBjIRSWAD28PGOPo2k4D7hg5j2cg0zYtOSuAkFtIUauPgiNFmOaBZ/f3hBCYpkjb9BjTMI2BvDAmbtrKwvL0faxMS2GeR6apUMqkzy1jVXo0ThQy3jt2O23nMhZSgu1Gr7kw46whFj2PWNS7KWVwrsFIVF8+Z4ghEEuV+IXIJUGthp7zHOi6Bmu1/UJIhHki5YD3yi52FbSa5xlOQowQ5hO3u462vVNPMFG2ohUFj5FyVSDq27n53JBCwUhLQdeMktUbSRKUnIlzxLcNxhbavsGj7NBhgJQavPUUJhrvKElIyZFRs/kSI04cKWUkJVJKiHUrqKfM9Iw3TtdDJZHTrD5vSZgPE+6loWsMw3nG2has03goRU3IGR1nRSBKQKLh/BhQxq7eh2wiSMA0gG0YJwvGMw1n5inijMVbZVIbsVAUMvRtg00WsiU5mFIkJksqRivTGqvPi1IQoyB1HhNShDQEml5ovWd4nDjHyE3fEEtkmjJzyMR00DFXHHkuxGPi2d1zYko8Pk3gAiKRznludz25JOKc2fU9Js5IObPZNsTs2fjn3Ow2jENkHgO3z/Z0+y1Pr9+y3zlC6bl79owwDDTOc7Pd45xQbKa9ueN8SuTDI912xz5FCoW75p6ubekaZb1psaNIijPDeGIOA8fjkRBn7m/vaUTtBXLUan7SW/xuj+88KQvhAASPbTyZEZIhzYlpemI4HSEHtaUBNk1HGGaKbZDGkSYhjhnXgbEa99nW0zVdJbBkDJmSVdb+6qsveTw+VDauJYulEEASYRyhWF17SUOOBpFYFTKZTFC/xl8TOP71gaerIAqoXknXK/YFbIEL66i+TlkX+kvQZJYQcvF1ErB8w2vjOvi6fvlKVlIqoJGLqVm0GsRc4BNW0KEipFJ3qXTBS1AKFfQADeCW36ufklw+tp7fmn1b6Alch4L63WvihZYT1T81MaQZeGvUJV4u5shqyFzIWUilULLKYdQ3tSK/asJATtWjpaRfYkEsUrCMqZ3qAsksDlcLTHN959bfFwBsvQ32qn1rEHlFBL8057sRnVkMMlkAG11s5SVwv4ooNZTRQPXGW551loe3Z7KJ5KLlJY1EkhTakkjZsLGFXa+OqwuLZT12pQwWFmtWqe2iE+3qP32hTSx38JKRvCr3WuTKr+f6ur/F2+X+ZR13pNpZdVwusjkFV5WhIkYZT1JEPYZquxpzQduWXdiiHiUiYJ2s71uNZi9MuaJMk7T4BFUTQJbbb+r5rOCDjiMnV5b/5arCXFkqay6SXQ1gsrACWyt2akwNlFcEkVJ0Ub34s1HBi6V6XYG6r6J+MgsguwDwFLgatVdTX92dqBQYQBZZGqs/FcIq/Xpn9C0Urwo+Ldu7klQdfWY9Hz1/sdeSxxVdWqVmCthXwFtqwFMpbYs/nlC9mcSuAPuvMvE1dR6UrNdZTL3eClgpoCwgliQLq0ErYi7z9ZJ0uDCuKtOzguvWGiQVsiSEhUXGen+MNZgKzi/BhFbauhibq+RwuSZZQSr5DUGNm5L5TvMpP/jwK15+/4nNLiO2BvO1LxqjpZ13+0jvM6498sVw5Gm84UzDlBtyifz0FxMh9qTphN2qTIYi2r+LIyfL6ST87JNbvs4f8dA+45gtSKpjIyJZ72+2mVgSGEvCEaqh6U/idxj/yWu++4mw22QNblIhRMt5NnRdw+/+9sQfvvcFU0hahScLJQpiZlyXue0nvvPyid3djEGBSW816HG2wUhmmrf8yT/7ih/9zg/Z9D1iHPf3N4wp0N60/Pif/Zgf/t5vUayn5EjJAyk7ijE4v8HkM/MpgtOMbZwT4/GBcTiDCO3Wc393T2lvmDrDsUwMT4EcJ6xtaF2LNY5cEsPTA4+ffczT4cx0mrFhJKeoxv4kGnFkJ5AsLWqSTZyIX33Jv/l7/w3b2xu+99v/BUMq+BxJGI7nyGnI9K6a8OdCs7nld3/3r/Gz/+GfY3dewRwpZKvMmPvzzL/5s5/z2c9f8bF5xc2u5dntnrePD7Tdli1fMZ1PfHy85+dvvuYPPhh4+d5z/sl/9xXbraPd9Dw8HLm/2fLs/VuOryfmPIMU0piY88TmpuHFB884vDkxxUkB65J1cSMo/d8ILQ4pFkvW+NLUZ0n2FLGkMut8bqvkt74vLFOIVQsDMUQEazKIjulcigYz5dsftIJaBRRk9SC6mIiXyvgy69xXKpiopOCCKQrypwJDmEFs9fppCGFmHCeOh4GMrgGtFYJJxDiv7CVQWdQwDGC0CuYwnhnOE862pJSZ5hnvTWWvNBhjGccz8zyz2fT0fc/5NPD4dKBtG/b7LYenIwZP029IsXo3DROutThX2UoUNpuOUtRjzVnH4XzEWsE3js1mx/msvknTNCNSaDtPKXA8nvDeczicSRVAE6NV2vq+p5TCcD6TU6prAWGeZ7zzNE2D4IihcD6PNI2adZ+GAWMs3jnO5xPTHOi6jjAHvn46QSm0rVuTbdZaNRrPYJyr3qSWGGasODY3W5XLjSPTdOZ8HvDOkTM416khexGMONp2QwwKxIU5czqPNN6Ti+BcZBpH6ITNZoN1hhiiVotMMJwD8zwoiOcNt3e3vP76NSnONI2laTzeNczzAkomxDbqm5ag61p84xinSUGqDCFo4Nj1G84pEWKs5ekrW60UUszkpMoCKMxzqObwhmEc8Y1jt+sx4kmx0LiGEBMlF1KY1UTZG3KKpJC0CIRo8lOiMs6/7XXtJDcgM8YW0lwQK8QUSCViWkOYZgqZpm0pIeBE2TxzmXFNwYkwnSa8M4xZ+09OufrXZXJW6XjnW0oQTC3w5GuMW+aEiGVOaJxr9Dk2zAMtBUpHCpmcAvv9ls3e44sQwglLxmaPyRabG0KecK4QU2QOM45Eax3WWfzGKbtr03MeAsY5pBTmEJnmGWcstlXvTGuNVm1tN+SSibn6j9a4aZwHzDjjrFbZpTgQBUtzBI9jOgVsdgrYzgOdaAXmXIpWapwT1kJMMykW+n7P3f0LUiikOVLiyBTOJIHO9gQDxmVsU7CpqBLCCpu+pe+2lKEwTANtc8v9vueLzz9jHgY67xmfDgzSsms6vvfBd/jyy1dAYXN7Q9e05BJpup5GEjd9x3bTY5zKhjW/LLomQMjMHM5vCOOJIsLpNDEMI33XkUJkNhNjSozjQCSQjom7OLLf3OCksGkU15jHM7FMpDJhGkeMgWk8kmKmcR1dY5mHgRQiuURMbgiHmXlO4BKzjKTRs93fUdDkd46ZbBKZwMPTA19+9gW21Mi+GKxxxJLIRC36UhyODikOI9pXyT0heQUwXdTn/6+x/aUZT3AV+HwjwrqwbC6fVXAIvkmDXj1OrmKqIuWXgoDrIOcCXF0HZ/W9CrQsxKcVTLlGR5YDcvE6WRgSBtbYcZELIotMpay7uGZcaIwpa7Z4YSWtvlALiGWoi7IFwKv/1WSUEYMplalR5UKqx11KpUtlmyhlOCVdZK0StRqc5byYNddJammfUshVkmTUp/Pq7i3B88J4uW77BTvQBilZVvbF9ScXhtf6pfV+vXMr1+8sx0KUCVJkPYM1tJVFwgNsW8OHz3d88tUTORY1PTMOKQ2mZqhdMbzcOJ7tNxem2dJf3gEFLyCbSoHkG1dyvS0NTKWEL71Kv2+WNvoNAJ2uNw24C8Uu3ku1zSuIIdrxtV9W8CBXgFINUU2dOUSBgWqYqkDBhQm0DiIEyQugpeMrxQp+1T/k2i/qALNSZbZGTcJNAWvUk+lyf42ey+IfI9TzttXI8AJ4X0z+q68TVMnmCoOu+134PZV8o+Dw+vrVOZeaualgNtV4fGGTvTMAatuqD5zurBTUAPv6I4t5vrma994BtCsIriUG6/Vc3kVMbbOLnExYWJRLpTo9hOql9dtlxc6k+izVanBcgCooNWC6ANeltgmiQK4xjpLjpU0RvYG19dYzKqxmk7AkC65YUEtlq4UFlrXhDGWdb6Xo95MUBaltqWw5izWusp2uWXtXFQjrFUkFIn8TgOP33S/4K9/7jI++O2J3AdzluVRNc9Zg3buM6Qq3dxPff/E17quJp9HTi+Pl7j3+9PgljomvfhF5et2SKBjnaQSyGJ4OiU++7Phk+A6HbsdULNkKCYMv6gsQnXr6UKBUJhvUwNg63sodT+eOn376grYUJCUkDGoJsHvBR/eJv/0cut2XWDlgxSqTN6Keck3Cisf6qF4WUnDOsmlbGr8hlSesTHh74nvf/w6ehGRDiIG2aZinxM9/8nOGecD4jjnMpHTGjwda37Dtdxxff8Xp9edITtjO05CZwonpPFNCplhH03YQj4jMeCa8y0jTkpzKXA6PB15/9jl5DpAiPhdC0YVaQwPWIVblyE4gO4+xiwwokuOMK8IwDPz0n/4D/tof/Zcc347Y1pJMZgyRt08z91uLtYA1pNzxN/+Xf5Of/5t/Tb/rdE6zOlmKKTx/kTmdM4cf/wWvjxNTGJkTPL/tOTw8YgB7OvDY7/jz18/4wf1nfPidZ/yr9i1vXh25f35D23Y8Pjyyu9lx937P41uYg3qMlBA5P0F3J7x4/5avHw6kaYa6vihSEKfzritOJzFvVYZXEpIEEYexDslanUyMWY3s1dPJEJukVQ6LxXiDSTWxlDURR610l+XdOfPbuqVc5YUr6KRs4JyhSFIpc9G+nusaaEm0BrTAwFi9tRrfQIlM40yIM9M0cjyf6NqWMAViikzTiHMqoVlY8W3bkEqibzrevHnL+ZzI2bDddnSdR4BhGNluN8QYCGGkcZ7dtiOmwOPjA/1mw85tiXPg7dsHbm9u6Tc9x8MTMSetYlgs4zSz393g247T8cDT0xHvHV3fISYT0sTrNwdgAVmExlvu7u5Wb6sYZvY3WzbbjjAPbLc7nHeEeaDvWkox5NhpINQIKWXOw0DXb0kpM07KxGm95fb+jsPhkcPpSQGwMHE4RNqmYb/bqk9TCHSNZ46RYZgBbbOm8UjfA1J9pgaGYQKg32yJIXA4HnDOselbcinMsxp3b7ctprJRh/HEbrdhREFH3zTcelslfx6xWtFunmZSdIzzSAgzKUZyEnbbW25vdsQ0aJGEw4ElX3cezogIN/sd292NGh/HRBl0XbbbbRjHkbcPJ6xVlubt/S2DEaZ54nQ64byl4JimWYGrKv2lWKZRWZ4pz8pqN4K1nmEITKMwDYmb2w5nPcMwYm1LMQ7b9gxhJL955Hwe1Qy9REaTuWm3NGIxudpEfou3lGYKCVd0LkoRYtYxPE5njNMVjY8ZglGATSzjnEmmIA58tuSpMKWEmIxrwZiMTY5IIdlZfVeNR2Zdfxmr69k4DRjR6phIS4jCWCugYYVNyZynEeM91gr32x0pTrx6M4DxmlQ0ljAIOSvZoVihZIPETOtb2s1O52PpSJKIJtE2cHo6Mk8zGKdguAV8opCIGTqzxUlmTkGT8gZySsScCMeJm+0GZxzGNFib6V1PAQ5vR5z1ONeSTKLMI85kQpw5HQuI+gc+e/4C6+85ns7EoFWWTdMxhiNtX9lFMfGdD77D28eRr19/ifeZu/v3sE3D0+vXpMmQSmbT7vji41dQhO6jDWIbTk9HYjjSb+95/v5HiANrIy+e74kRNtsNxjtEGnrv2TSJlAJ953DtjhCmGjMIzjUKiE2J0+vXxBzw7YbGOsy2o21a0jTyZnxAvPpEjuNIngNnI+Rx5jxFTLaUlLBkSkmYxmO7LVks55CYhwOtG8hzh83CNA3QOgRPDJFxHjkfjmCEF+JoXIu4RCiT+uJ6w/H8hl989jNlwdXVtxYy8RWPmSllVDZjccpyTurbWCp4mkykhExr/yepavert0vFjQuPhqsA8Vq2dNl+GanIvAt86Kd+xWLiSqpzYT/lq7eXs1gCnqv6bZXOubCPjHwjy75m2+WX4kb9bN3M1Y/lg0sQma8AL3Ml/6kxkFbrulxKjrmW31I6UzFqIrYEihbwTjt0dlKBpUIskBNrJiPloou+2gapVKPomiUrxZANSC4kuQ4il5/fbOsL+0rj1AuKre+++5NyCd6v93x93y54pP7LoijFCpIJ9f7o65IzGyf84L0Nf/Zzy9vHWCviJKBRyKTAzhd++GLDs12noMpyiFUieOlvi9BJCVZXoBnlHYPrS4njenKSVtzzEuz/Bm1ykb8tzD5T+V+mAgz6iiFX1pBUtoutBt1mlePVHmMgZ6ttldXwUCnyF0AvV+bQStzJiSQZSr4MHYNmAytbUSg4o/3PSQVSzFK1UWp2uErBquY45wsgaKt51SK7ZAHDVuBwYTmVFXC1crmr12Ck4jlLxTuzZgAXE1yVpqkHxtr/5er7te31t8skkjN1IpAF4dXPmKV169/y7j8MiZSqlK3OgVIBpUW+eGGvsd7ztZjBgk5cOnK9B5UVWHTkS2V9LTLqUhTUqfC2Lk6WflVQZpQpWNQU+tokdzWWN9VA/KpPGux6btf36MJ+A6yoP0EVxmbdlf4EnVSX/RmDta7KEfS4uTZ6qfdI0P5kjdVqd+HbH7T+rd//jJcvT9gmXcHfAJo9Jum4UJ+yhPGWflf44W8deHY/cjxCZ3oam/gr33uDcUqx/upNx08+3UK5I5rqpxAh5o7Sbau3mz5DnfUIUefQUhAClAZEaKTgUV+JnBxnEcS3nO2FXdeUmc5OiNtwLIWcH2n7hCsz3hWysWQKJuncEqN6SRljsKbFNx3dpkeSLvAbZ9hsHX/9D9/j8fxbvPpXf8rXr77iwx/8gNlYbp4LH374oZrojyMhRc4lc9tvaTae49c/Z3r6mu22Jw8GcRZvVSpSovpR5Xzi4e3n7PdbiDNvPv8Fw8MD8fHI6enElKArCtLmxtHaho23GHEgFieFEgWK+p7ZXPCSSaUyKq0nJEPrCoevPuNwOmJdr6xBpZlyOE5MqcUbC2QChu/84Hf57T/8Y179/Gc10A3YRn0QvXXcPR/IP0588P4LNt0GSOTpTOcsr16/5dkPz4Qp8PXTPV8dXvPB/ZkPv7fl4eGJw+sDty9uefbynjdfn9l0hvtnGx4eT8yD0uljTjwdJkyx3N1teXooKgVC2U0k9bdJ4hCJCF6nnQxiCxRl9yAGa2UtWLAUOliCUJ36jDJMRBfgZSk0UdlBpgglGr7tm4hFFu+mZU6XUkEn6vyrVgjruqMsT0Q1/09iuLnbMw0DjfeMk1YBnKaJeQqczxPPnz0jTIXt5pbj8Yg1EEkYY+h6TwwzXzw+Eea0Ghn3fUcpiZgym37D48MTzluaplWDb2Nouoau7TmfThgr3N09YzhPmrFPs7KvYuJ0PuK9R4zlPAxMj0+0TcNms+V0OnE4vMZZPebtd/d0/ZY3b9/StpYUZg6HJ2JUSVcpiWkOeGc5DSfePLyh8R5S4kG04Ic+m3TeTwW2mz3OOZq2JYZUTbfVPHy77ZmmiZjT6mU0jlNNfhj6zZYUI63VhFIIEaQwTmN97gtt23Kzv0Wk8PD4yJs3b7HGcX//Aii8ffOGtm0REWLKHI9HYlR/xJQSp+OJzWbDNAXatmWeJ0rO+lOEruswxjAOI13fM4+B1m/AA0TOw1NlJntM9Y1MaaZrPSIOjDCOk3p69b2yMLqOaTqRYmC76bXqIIbXr7/WMuyuwVjHPAWG86jl6l1DmFU6GeZIwTPPAZeF7Axd1zEMAyVDLLDb7bC24b3338ealveef8Af//Hf4Pb2Of/iT/4lf/bn/5Tz6S2kN7hG5VqzNOrnxZI6+fZu8zTS9R1koYQJ17cYt2FOkRIGrTbnoeBUmoljGDM5OabxTI4Tt9sNxdrKGCsEwDcWiOqPZixDOJPCoFUQvWeaZsiFkDN93+JMIZaA8UIm01hLZywxnpnjAdfsaNs9IZyZw4BvLMY2pGwYp8gkhjlZ/Gxoeot4ZeK5rqE4mKbAHAPbux1zHsh5JsZ5TSdihVQZFkUKtkAOI0hRhmUx5DmTp5lUMkOI7JuGpnPElClJcKbFOGFsEmOM3Nzf8fT0ljnMdG1DzDrneWfZ39zQti22aeg2Oz799HPevHnDdrOl7x0iPQ+PE+fjgXj7hv12w8efnCBA/9zQNJbgPQ9vn3gSNIlmC4fjibcPD2x2e0yzwVrL/e0NvmsIDHz99Ir7/T2+87gG2l5lj3M4wzwhCGE+a9vOytJsrCOVBNYSbWYGsunIpaGzLZ1PSEmc5sh5GvDNrKBrGLGtI6fC0+HMMMS6Jo4KZhqHy5YwHYkmM00nTJxoihZkKAUSupadw5nhdCTEE1vf4uhALCFOWDMhxRKyIQ2Bz199zuPTK0oWomjhBGuEjCMXnU9yjlo4pIwUq8qXEkFMwpSZnqIkhV/Tou3fG3h6V2Z3FdS/s34vlSEjlGrArF+TFTxagqOFVrL6By2ZeL4p/7o6WrkEkO9m4YWLMfflCysEUQEny1KF71oOV/fJEhPqfhdQClmOd32Z5d0Yzl3AH1DJkDVSj1fZElJWKYyRWmZX1DRbM/q5BvFZDeicUn0bq9puFv1/yqSolP2UhZgNsf4ec1FgSskllbqtwbbazVSwi2tD8oUxdXFyeoc5hrabVgS73L8VvvpL0t2LLHdsAYpYbgRZFOU3UvjefcOPvrPjnw6BFARDJKOGh1YSL296fvjRPY1bQKYa9IrigFfYkpqilXqvr8DLyzVc2mHdpPbjZe9X7/2mVMWiXMagNbKaNOt9rFXFUIndAjrVUVLBQVl28w47zhpIJVPEViCvMqDqgFmBD6oX2Sr1y1QFJABu6UkVkLKVuaPWoqXK0TTgUL8gZbGYUsGgxYS2gi/UvuXMco+1tHvSSYlUslbzSgrgXNhAZe2L11ZRxurR7SrVWva2jNlfPZ0uymONIXSCLoDYi6yxlEVql1n6rjL/dIiWCqpp0wmeQqzAUDbLXVw8sxZGj7aBMaaCWXI1ZiukX5mV14zFJWuzmKmbykZaJIZSpb9Swa2lT4lRYDKXS/svJc51HxWEMixnh4jB2sqsQlhMaBcfGPXAqg24zKtXZv62AlBqgK7lD8Xai5zuSlq4XuQCcrE8NX4zxu/L773FSSauoE+pP1WCQ8q6IKj9IBXBWkO/z/h+4sV7qB+RecWH3x8oxjBF4Wss4+uXjNMNB98xmR5nTvgS1CRY1GzSiGBLwhhhzFpFUn2StAVj0TlEvSMAY5EU8VnveXIF5cIZjG0RmSlicC5jJePqc00c5BiJwVcJt0qrfePYbjq6dsM0qgfK/qZhu7nn3/xJ4OVH95Qycx5OOGu4M44ygC8QpwPT4S05J7qSmN58RjO2xOENpgQa6Qh5QFLHdD5Q4lH9hiTDfOarh8/45DgwvTlwfBogCZ33NL5j0ziM0UV7LpqptlLLlRNJUySGmRQCUyrY6ofgRCV6BqPGocYRjo98/dUnvPfdPySO8wq8TqlwGtSjqwhqRsqGP/xP/4i/+8knNN2WOUzEOGgVSKPtOs4Z00Z2ty03N7cMT294ev2GcM5I2TJMkTfHhp+9vuW+f83v/E7L42d7Pv3yiddfPnF71/L+8x0PjyemOXJ7u+XEmTAt/nqZ42lgU3ru7nY8HUZOQ4BUtHCFy5BGSjEYcQoa5UViK4jV+5uLqMzECCoBV1C4SKlrhKxyu2wqEKmL3ySmynpVhvtt31JWTw21AqgVXyWpRQKgbCcopTKU6muIegFmKbRNQ06RQuI8nckRxmnE+4btxvD6zQPDMNJ1W54OjzrHOkMZIykV4twwhRljVMY2TzM3dzusV5mWAMfTke12w+k8EOPAdrtlHEeG8wAi3OxvmOcTn336KVC4u7sjxkRO6vnkG09OhfP5jHOW+/t7zueBh4dHnPNsN3v8/5e6P3uWJcvOO7Hf2oO7R8QZ7pBzoQAQA0EMHEBZS90mvctMetJfKzM96KFpJph1N8VuNrtJoFEACjXmcO89Q0T4sIelh7XdI05WgaymYESWZ968J+NEeGx339P61vd9K3rmeebx6R1ffNFxe3PDvJwpWpsHVMAHk/DciDSza7EKXy4wnWZTAGixCnrekXLh+Gw+NDEGxJmXXQiOGCMA8zTjoq23obfiCDHa/HY+T8zzwn6/5+ZwYI6BlBacOJZUefv2NTEETscTKSklL3gXcX1HLco0jhyPz5Ra2e0PiGqTu5mP1bwsqAqvX71mf9gxjker7CceHztySoTQkiaxIhKZ5pGUMt4HXr26xwcYxzPjuDCeR27vDgyDVdibpolcEiE6tAreCyUvFCrzk82Z4jpO5xNw5uZw4HAY6LqO8+lEQRmGPTH0nE+TxQ7iCSGSlrzJLZ3zqApLUlQCcRD6rufu/o63H33GJ598ymeffcJ+f8NPfv5j/sf/6b/nB//bnzPPj0Tv6cMdw26Pc0rJSpVKqnUrnvRdPdxOmKjUXFGdoc6ompRz1x0o00KaJrq9MTtTylAKNQj9rieNmfF8YtgfSDJzc3dHyZVlNo9DEcXLnp4b3ODoesecM6lVECteyTrjB+E8nyltvalFiCq4mhifP3DXdUhR1AuncSJ6AzRKhZoNIPAecEotE/s+0PcB4cTp9J5xhqSVg9sh6lnGSpqN+aY64WQgZ2O477qId5UqlTnNrfBT288VyEUoC6R5pHQKzmN+YR4HDLvIuw8f4MEzLgvaOcYy4aLSd579zYF9f894WpjPHyglgyvsb+/ofOQ8LqRFmdOOMe/48t0z3aB4duQE33z5JS4UpBuYRXl1u2eWiU/evGF8HjmeH/n0ds/N7VtC7OiDMp6eSTITo2cYBnaHnUkh5zMlF+Zl5Dw+shxPfJa+YLe7h2IMzRJAfEB2e/xhR3h1Z76FyRFwhOAYpzNzsqpzOcFhuKHvOooriI84tUR2afK64G2PkEZl0QydVaSWOhCGnrpMDRhSUM+8jDycvmK3jwz9Hbvhlugj1Ex0Ay70LKpM5wcezg8UWZBOzT95sTbkKizi6ZwnyoDWjPeRVAqpGAnDU4k4ailQinmK/QrH3wvj6Zdt2y04XX+3hfRbkL7KzK49nlbW0otAXjDaPVdAE8IvBPvXH1kNkxs4soJPWxDpjCXYqhu2rJls5ANE1xDG2i7a5HIXeZ78Hd99+X/dJGSyyue4ZPRlDZhWwKuBHWtQZJs6y/zlWqilUHwhBI8PHu+tvb5zEJv5bhVKscU3l0oq1cpVViFXJRcDlIwtJc0TwYJJ1fX2t3tXja+gLdu2CtSEFXS4PIs1qH75/H9FAOoF46g9J4WCb2yyjOK474U//P4rfvjhzM+/XlpgWpBauesrf/jbb/j41Z5N8LECl2tHvDp/SyJuf/OiqS34vXpt/dlOtYIjv24Cu8th/ddB88vZnvnKlMFYKNrAKO/8hQnWqtut4FOzqsC3aopFbdFZ788Kfrx8xFbZZQOZ2qsr10mcx1ERpxsAbLI/G7wrtIKs4q3WB2FjJa3j+DL/bL2X1ajcN8REffOXA6uc1B54bePU7sgFEF+5M/bxtb+sfl/XglL4pZ1EVsvy9u4rKZuNNLed69KdpTFZVgbASpxy25i8TCb2/ESaV8oVk4s14Lu6qq2qW137wQoSGXPNfnTt3Wp+SVVXqlG7rdIgj4rzUFv+0vvKVjmPFcAyFltzkdqA/BWI2m5bu78VBddEymLX6qxEH+q4AEwNIHXOb75Rrkka67pmuO2bAK489b774JNzejFn3kaLbXakTZxeKqg3dkjz/RFRYqxUFxh8JOWTeWw5IVGNwi+O7APRRbJ6nO7IajXrXAWl4tSRxSQhVR3eVSJQqYg6vKfNDVbyG1uabE52zpSQEox160AHRzd4vJgEwEcheofzMCqUBRADjmMf2HU9+35HEMeoShRP9ZVpGfjLvz7T7z7wz//ZP+fNm9fEEDktI+QnltkkcZ1v880yIfOR0/Q1oZ5x3qp/hcOecXzi9PTIdJpI08J4PPL08IBopZeeKMJu19PfDBz6Huc9wRvLyPlgTEwnuGpyFKmOBaVqIjXpShbBd54sZtjpxJhWfRzwaeGbH/8l3//df8rTKLhqGeVUlIfjwqubjtCSVUvxvPrsc/w+8pc/+HM+fvWa12/uzDyZjAuBf/QHv4u4Djd4vvd7v8df//t/w1KUN1/8Frv7NxzPE0+z56fPd/z2eMvHH5/4vT98y7vHE8uYeHiaubm/53DoeXo8IVU53A6cpZhps1i1m+fniZo7Djc9jsp8zAhW7p62kUYrUj3gqGYICJltv+TEb2xnbYzZgGu+bgWViNNiAKszYE/Eoyha83e8HtblUKBKYy02nwRBTFqnWGEMXdfHde9rc2HwjlwbIx4zFl6S+dqdx5Gn5xM5G3DixJg5pWTmaYZWgXKcEl3fmTxqTngf2O8Gumhzec4F7xyn85kQIn0fmaYTtRmK16o8H49A4e7ultvbA+M4Mk25VVxTPjw80Hcdn376KTnPLMtICJ7DzS1UYZ4XSs10nRkXf/nlN3Qh8tEnrynVSqFP08T5dOJ0OjbZliVJ7NodQ7fDeZNlqiZCGOj6gdh3lpTNmZQLh8NAjDZnztPCMOzo+o5pOjOt/x89p/NI1cLd/S3jeeT9+5n9YUcMHeM0kUvm4eEB7zyxC8zzif1+4CbuyaWwzAvzMnNzszcgyzmeTydATQKDrVXeC1+/+zn6TSHGyH53QDDvrdN5xIXAviqn8zMfffSW3W7g9mZP7HqOz8+wCDc3txwOkFPheDqTsjGWbm52TFMip0pKE6owzSMxOnbDASeR4+lsMvXgKcV8xIIGPvrkI07nM8fjyVhi3pJtuQrehW17sSwLpUDsjY1zGAwI9cHMiJ8ev8S7mZ/+5Ae8f/+B0/GZGAqdrwzDQN9FaoUYe6Jv60KT9V9XbvwuHueTsd+GCN3esbiEREGy4qn0sWMeK4GO5BK+j0wlUXPGR0+8uSGPM8c54bqeh+cT0TlctHhPUpPT+Vu8mD+Yx7MLPbku5OCZcya6Hu8Hk/xpoJRCLo5cgefM/evKPD4R4gGha/GtoMEjoSI54/JErgtaMuN0JseKk0RehGXySB+Zz8rT+4llTKgqQaKxIKPDdSaN976nD8J5OiMEfEiknFAX0T6gp8xhGKBklmUkHgYONwNpKhzPI0/HZ8Q7TmlmWTIhGCOoaiX0HYf7G8oE8zTx/sPXdLuOhHCejrjdgaSFsN8jDhZJPJxGPj4EPvr0c86nGUKEWJFDx947tO/o5MCHr3/OFx9/wnLKOLejd5HpNCKd5+7wivP0xK4fOMQD3kXmNJLnRE5WzbPzPWOdWLLi5plSF/AFKri+Q7IS+xte331MXUZSWsjLQqoFIgz9QC6BiqfEnlQTznc42Tfix8KSFxDz4HJacDVQqidmS8cjypQqaTkxjQtKR9FK1Zk+Bm5jT8yCL+DKiBfbx9WsTLXws6+/YRwXVAKlzm2v15MToErnFVdmtMwmKnDeAEPNlLSQW1I4hh5X3d+ZfP/28fcCPF0O+dbfL0M+Xrx69Z4VoFpjtavJZwU84FuA1C/55m/hVS1gvQK4mgTIZB26/X4Nbtd4FV5KhWjnvjYJX9u04fNX82XlpYTIr5Ihri50NdVr561XoJu71uFhwZhi2vVaM5IzwTm8d5uUZH27oxIa9daJUARyBVdts1pqJat5KNV6fa/F0Lg2+a9qn4qxGJRVtKhbsL1e7XUgd31si8gL4Oc6yNwQjBevqVom3YiDlaoBR+H7bw780y/uOT59zXGyDUfvC3/wxSv+yW++Itpj/uUV5l4saHY9VeUXfrWBbZuL+BW7qYEta59e//trw3ha+y+C84KvsgEmFwlW2/iKb15J5k2yxusr7oZKC4LbPWk3PuDQVvL6+l6tRvIX0ols8jDfQBdVxeFatUcQscDWN0TYib+wcDajcduwbKB0A0o22a5cwMK17Zs81vm2mDbUtaEd2gCrrVZdYz1WNV35xhK7+l67vlXuu8I6brvvKBvgI9Kqu20dySaB9Zyy3WRYwehqg3WTCa/Xoeu1rA9P2vmdVdiSdZ5RzMuoAVFbRqo9E9EW62AMIV1ljyKslYdW4KlWk7hcrtaZPEpA8KBQ1KrM4cTshxrLaZV1Wj8DM7Bv7QYLUNs11baoOd/a3trr1DbEmy+XNAbFxiAz1tMvMFNZAc/1fC0Z4Kzu4HcdfHKNGWfeV3b3tbb+wSb2xFGN6i1q1cCaRMlLIPjIUhNeqrH8qkOrB3VoNX+ZEgKJSlcCrq4gXwNpN8DLQ8mod+052jdnVQoVH4RAwVHwYqbYpQqitjkWKjVG6/rOW8a/JVUQaYmYxdoYHUM30MWeLvSgztYup3TO8zc/P/ODH5y4u/kR/81/839mPI48PL6nLGekzOTZyqX3955YInUuSHoklwmRzDIr87zgTzPvH9/z8OGZh/dnxtNE5x2f3u057AaGbiD0kaHv6fpI8GHbVzSMwCQ9OVGykrKSS2VeKvMiFPVQDIQqhSZ/wPzafKXoQt9FvvnRDwjBo3UBZ1J6FeE0JVIpGzDhgzDcfszv/ck/493P3zEfT+y/9yn9sMOFTPrBj/n9P/xDTo+P/O1Pf8LHn3zET//qwJwTv/HJKw4H5cOkTCnx7hj42fs9+08e+OL3Bj770St+/MNHKonzcYQhcHO353heyFLY3UQYC2WpSAjU6pjHRNXCbt8TxTGOJouTCllsT+TUNfVgNamwqzZ2Fa6LfDht+wfvCCLbIlydtCIIqyy4rtMz3/XxC2sFoGKV7XQFlNp8izHJc6mXfWLLCFY1D6w5Z+aU0CSkZWEeF8YpWwXHJbHMC7lkTqdj8yUKnMeZ2EemuZBzoe8D07QwLwkQdrsdfd+TS6YTWx9yyQxDbwFtXtgNPd4HzuNEzolXr15RSmKeJuZuYdjtQcw4t+TKfneD80JKM3d3B8bziFbh9PyEc5797gDS8+79O4a+53waOS0L57898+r+hsNhTxcCp/MJ5zyH/S1aizG1xJFTwQcDd+b5TNd3xD4gznOaJrvZbZ3M2ZhepSjzbPKm0JK3MVoV5HEaScvM7e0BEc/h44/JqTTpYWK337EsS9s3V/q+Z5rOnE5ndKf0Q0/X7cgPM+JgmoyBIK2YRW6MJUuKwG63o5ZK9JG+3yPYnuXOGwtsTdS8f/cBHxy1VkIIeBcYhj3v3n2g5MQ4jfR9z9APOBcoudr8UxUvgW6wwPPm5g4fPF3siF0gzTO5JttbiWPoOmLouL+NdKHjeDwyL4lptj7ig62xJVsiqZSKj5G+N5bW6XQkp5mh6xAq77/5GSGG5gkVyLnS+Wj3vvkPnc9PRC8QOiKDpba+27gTzlmSRRDUWVRXFqXmjNaFTgPEyJwKuS6EGMzkf1Ii5vkUd4GQPd71aJ6BSskLTjO++ZPSLeANTBfxiBS8CiU3NYJ6Yqm4WukilBBZFiMe1GqABosFL74GVHPzflQWV6jByAmnaSGmivpiMi3tEDpKTjgvvPvyg+2pFFjtEjDfoUN09PsbqIJXRYrivaN4R63CeJ6RGolBzHRarYpfFzv62LGMo9l01EAMikSsyJZ6yAbW6gjThzNazG9ot9uzf70naSUdF6asVhk1mE+b7gLCgf1uQIiUktgfdviuo7+7sfiuVpMOzgsfv33LqZ/NXoQRH5XucEPoO97sPmLoA7GLqEBaZuZptB1stNd3NZM0s0xPFF1IZaLvBrqaYZko44IUj5BZ5mdSXnDF9mU1VFQFzYk8ZXKd6ePA6zef85SfecwjJSVqrqSiqI6EINTkKNIRnKc6YRoF0ULJxp7NZJwIu+5gTCnJqGRSmelCT61CygvffHjg9HwyiXLwJFWWqjjfgWQoiaAOLYVaJ0I0b17PYKBbSZYgcsZLV8nb+v2fOv53AE9X4MAv+e32+oqtrP/dgt32vhfAQ/tpO+FLvx22Dn8JloBfuDi5+mmVyq2J+PX7r0EjA5xWbsEVi0lon2++AXIBn4wtdQlmL4CTbo24gFH2k79iNG13cDUqF9t8r1e12htsr8u1l5K7CuJtMqlVkbzKctb3rYwFA29W+VAQ85cKHkoRUq0kNRneSqq4VFmxayuynll/6abOSWtLe+hrUFm/9b7t42oXre2xXiazNchYgaoGCjUp1uopVVXoPfzx99/y5YeR/+UnJyQHfuPNgX/2+7/FoRekWsWl1WAd1uD0pTRuDfivQvurzKJuG8Lt3lzhZ9sokCuvo+/4Yrkdze9qNdz2YllWVq8RBb8CTWswL+uzxu7HaiIsYoBkY9Ap5uehStNBXN/dtU9ULmDdygB0mxTNNWdxL8V8orhUfRTEXmvsoCBr5SQLiBu90KRzurp40WCOtQ0XKS/tfKU0kFX0apxe+ilcgPELY/FyaUqrArfeoHWCWL9V5MV5t2BiDbAa2q1X79AWxKOr19GFYWiqksukYuPIKCQGurgm33Xtfa2tjRm0sTC3yeZqjms9uqKb2fc2IVwdgmCVpqzNWmUD5GoDylwVC6jlutreOl20Utmtjznx232TFdV3cvEYw4Do9XmugLawJgxkW4CcdQJjTsmlxb6hdWt1y+2qV3npr82hrMbr27yjYuPEsCCr8Kq057YCs8WKMTihagF3GdO1rkwLJYn5PmXnkRIQKk4NRErVIz6boWwVpAQzTKVVMfRm3q4UtIZWxMLo/dvtFquI6bXSyQDELdFieKwBjkWzAbniCR6Cd0Qf8U5aZalKdZnTOJPF8b0vPiIGZZpGQh+ZlxMlzeyGDqlWkS02ODpp5fx4IpfEtCjLUnk+zRwfR7786olpUVLK3O16Pr7Z89Htnm7X4V0k9pE+epN9ajG2RTH5T0ozJSk1maS9VM9cK2OaGefEzgu7oWOZHUsqiFO6Tlph2oC4SOx75q+/Ii9WdcwA6opUOJ2Fp3NluDXwxgu4fsef/PM/ZXn/wPTN1xSE3WFnZbZPiZ/8+V/xJ//yj3k4PqN54Wbn6DycvvoRdx//gJv4BY9T5nEa+PHjHW9ufs5vv535F3/6mvdfLTyfFarjdM7sDo7drmOaForP7G565JQZ5wWx1ZplTEgt9Lcd+xg4PU2tjLexmVaU28iSxnk0OY8B5FrXpIExmdCygfqq2zTfCiCY/6VqRcXh/HfcmRjQWloCJNg907p5WYlYyfSqpb0X1oRMRTcZUkoJFyLnc/NSqVZtbJqWNjbUgK1q0hfEPgPGJs41kfO87ZGGXU8XIz7oxqrdNdBp6HtyKVQV8pzoOwOgpnlqe2ohF0WWDBW6LjLXxLLMxM5zd3/HPE3kJdmeFUjLwodxInY7vLfnHLvAoRtYloVlmpnHMyln+m6gojw/H5siwdhwPkRKVfphwDkhROHp6cmA3rkwDD373Y6usznBeeF8njnsb4xJERzDYNK7nCvOeXb7PU48p9MZMH8lRdntdziFZUl47+iCZzodmZOxfI7HEykt+GCegqVUSq3E0KFqDLIQOmKMxC6Qc6brI9M0kVKiK8Wq/mlLbjkhpUQIkZvDDefxBLowzzN975iXmVoNOBiGgeBdAwgtnuj7jmmeUTIs0Pc9v/mbv4M4ZZ7POKecRdj5PeP5REqZXCqffvIxy5L5oA9mXs3IMpu/jHMGsGtpjFrgdDy1cdjkfGVhqsp+6Cm5tA1z82Sj0g17xvHEkHr2uxv2u4GU7FpKNfnkdSXq7+IRnO3JsgRKAXCM00zXR7pdT55mum7H8+OJ2EWKFJxUOiMbkpZCIRkgkBNOHSEYA8z7gGilaMI54yJXgrGHUiFU6KIjSaYLtRVyqdQ80sWdGYSrgWAhBArCVBZ2XWfMNswXNOJR2fNcEyUXnJoP0ZIKTj3OQcZTF+uHu97W3dANLDUj4oguMLieIXrO80wqCXEFFWGcrO1CBU3s93vOz5PZwRSswqmzang+ekKMBDzZZcq00Ic9mWzJsCzMTzM+Ou5fv0HGSClnXIjm9TgmfFF0mpmXhFTlZn/D+DQzTU/QO27fHnBOuNlHYrjl+XTmZ199zb737Pcdu35nTKRsLKZXb27RWtl3PTF4qjR/OFUk2D7UBYfrIeTI+dmqWCZGKpkh3RDPM6IL3nuC61ExeV5tz3xJ2WJwqQSvqBaWtKD+wNO7n/HhwzecxyeWAt4NbRw5ppxIU6KXROcjU850XX8p0CGeEhUXW7V7J4ir5HIGd4uvga56nsdnxvGZGATV3OIQ37LBBaqRW5w6k3hiJvpURUtlIlEx718tsLgJIRHd7lcbR7/qgLsGbmQDG+oWxK7yGsNPGnizBhNcZXC2Ek1X4c4WmK1eP1fgFHL1dwtUtuDx8t6N5iKyMZuuQSJZfZwaqLRVlGMFey7ttuMiX7gEy7pd+5pNv4AO2rKeF7bRNegEupXFBTZ0/yLhubRhDc6kBYXaAtwNDGlsE9uYyQYoWB6xXJ6J2OB3rCyRFsS7xlgobVOzGXlam7Ss12agQrkCEzeWxfYAVm5JA26qbkyirYT8Biy1C9WX51iL0aheBH2itTFVgt2jFmy/uon86e9/xHNOPH1Y+D/8/vd5+2qHyoRet0VX+NDCzdXXCW0eVluz9Oofrv6WDfRqokMDxGptfdACWKsU8+uCPNmx0m6r83hWnyer7uXFpBDruNiUSTRYRDwXHzTXqtwZvdT7NWgEEbdhT5tPx7rBdoJT64PaMrobOIyBJr4BTwJb9RQnK3OwAStOrp4rV8ATm3+GkepWOVx5ARwZULuCpu012QRl23+FNXxv89AGMsn1mba5gQ3Uade/tq+BASvQeanOR+uX9VteeOvTYnufiasMYLL5doXPV8+rNvbbPbO3um0e28SUDbV5wevcKvUBlMucfQWUrW1a520zNl/ZU7qNL2vH2v6VJWYuTHV73s1HTFZmlbu6bQaci3iMcXWp0rlKr6VVEbz+LutfDXi6vLKB6F789R01dtvVHP1dPmrFvLVke1Tt2Rt7pLa5z8aBb3OYlbhV8TjtKDWb34BzuGrAhmiA2jUQrjaAwJOkw4kBNgEhU1hN/S0/6gi1NGBayLWgEgw08IpWb5lxAdGKB9xaVVIjUiH6HT4ERD2dD4gv5Jxa+fcOUTXjaRFCMHZc0YSVYi48Hc9oCdx0kc5PPD0/MOfMX//wbxEV+kHQkphKoZ4LsTpycoxz4nQaefdu5PHxA/1wx8OHM8fnBRcit13P5/e3fHI3tDLgHZ1v66YmSq6UYuxEbcymnBKarU9VMfbXcZpJaQGEEPd0EshlwpUreaQzObP3ESRQz2ee3n+Jho+seky1AG5xjg9PM5/eBdaKnQjc3r/lsy8+58t5YnfYEZyw9x2/949+m//tz/6MH//wwO2wp47v+Kd/+DF/8R88yzzy9KM/5/73XvMgB06L8tPTns+fd3zv/gOffx9+47c6/td/P+Ospg7TlNjtG/h0TkjJ7HcRHMzHhbZlZZwLWRf2h4Hdbc/0aBtXdS0xKBXU2CBoy4aH2vzrHTht0ti1d69zhZqE1wnaChIgZasqVb7jQSusa1HLEKtuOyrFmDTailes++d1PVUn4AJSKxKsYlhOmdTGyrruKCujxNbpLkbGsZq/FhOlLKRk62EtlWE4cHtzYzIpXcg5k5dM7CLOebq+w2VzZluozMtozGQfDMZ3nrQk5mluHkw2nQ9dQJwwnkdyynaVaqx97wMxOHLNbeo3qWvOlRhsXU8Lrc0mPHdic5b33nxzaBYSeUHVius4H6Ekui6QUuasJ1xwbS6x9WW321FqRjWR84J5DEYgU4vyPJ3x3hlAHiwxNU8zihBCpAtCFx3zvNCLp+/7Bpwr8zyRUsX5jpzNxsA5jw+urd0m/SslU8aJGCNzLlYUwIGIJxclhMg0z6SUzM8G86DSpGgtxGCVm/sus9vvOR7P0BjGIibZQwXxjlITIh0/+9mPORz29INVkvSxJ6eMODP8P48jHx4fuL295/PvfcFXX3/F6iMbQiLnwJIWjnncWHrOG+gpyuZRJmJSvJvDjq4PLEs2JkaLUfp+sIIezvp21x0YnG+VgxX9zgtmO5OpS2wLcMKXQqgRh62vyzQZgyz2xjZhoVLJWpDgmCeTQTsxEDqlijhPbSxz58wz8DSOxlxWT9SIaCZg3kvzlOi0ox8GkhTmMrG0ddkVz3w+Eg/3ZK0kncFVavN0pflfehFu9zvG85FFhZIFVwrBTah45lwRbzYtEgJFE8FVQnT0cSDuDlRXSCTmMtEFbwVOFketSh8CvlNEK7kuVBfQYGyhKS1My8iSE+qtbbVawQARx6EfiC0I0OCZ68RBZigLUQSSELs9OEXzzO5mT1Hh66ev2fd3xjbsPG8//xQfA+fHD+xc5eZuIHXw6u6O1Ftsd3M4UGNEUbyP9L0j5WqJT+cp1bQ3rhsI4inLTBRhPp+pcybNmWmcqDISh2DVRPOC1gmPEMMAoozzI7XMID21RLRA1xuolctMqYUlw89/9kOWMjHnmVwi2dncDBM5V8bjQkHJUSjVJHiikFXxnSXHYnBNFWAM86gOXNeL66kAAQAASURBVGTRynh85nl8JNeC846Sl5Y87pBSUVLDDTqqesaaqa43W4waEQ34NldlV401yg4tAeHv2ePplwFPBuqsAMklCw3r+9YoQq7jsO19a1C7lr2Xq/hmy4a31y5gyhWgcfVZ1QvbaT3P+h3rBmaVj0nb1Jhtcgs83EuvISeXjd16ze5yOZeg6ipA1KqsUhLZJC26bSSMIm6fV2kQmOhWmckCrQaXXAVgVbVVp7swIErbwNj3NlBgy+av7VzZEvUCDrYLcSI43+RQbgVqMANLZ8lWV0GKBTurV5LWNdiXLRCsa9Cz3fdrKV5rjK6B8xrK/5JjlQQ1QGCN2AXQVnHNS+L7H+35P/2Tz/j6y2d+87MDwa3l252Z67YsadX1PrOBgroFbAZMwIVZpt96T13/n5cb2o191n7/a3esfYwGSqBQVsnRCiRf+t/Wz0UuQcD6W61NPlGp1QAhLeZhgVwDehcm0vV4rpsRYSVcMWCcczgsqF0lpU6s4p7BZbbJVbcCvmvfgq3yXTPsd6JQLZus7fpo7XGNLbWBzHLlsNQyzdIqpq3S0I2R1OYbrWroqbZA/gXi/O3+LtvLxqrSy/vW/vRtwOrlbGb/6jpGeAHe0IAnMxS3azIw7SLltblBXjatgV+XptoIsetoWrmra7AxqY3pJDSdXgMT7T2bhPPFFVzBfJYhgLW97d0r+CdrFmYFqNozWYGny9x8tR60mf4iJ3z5HvfiWejVosZ3/rDHdRmZa9VAxYwnVSzj5VpFrKp+W2NUQ6v4dHqxZlWw6iYqJJRQzeg7FUXFXo9aWuBva0IBCubxBIUiUFqO04tSxNbCViPevAFknXS9SQbE2u+dmVeqRLrmITCWRC2Xvu5dR/CdySRVyHWh6MI8JuakRD3zx7/v+fmHr/jrv4y8+fgjvvnqPSh88vkrap1wzpFT5fFx4nzKTEvh4cOJx8eF83miGzwlFYoIQxC+9+bAp6/3HDoLkiUIUWyeM8l7scRNVUrKxhqjQLGsYXAwRJMHUiz7r6WieUJZ6PqIC4HgAuKFGMwjy7mIk8RXP/kbPvqtt5SSzA9NlaodT6eF09Jz13dIG2uhG/j8d3+fgOfQeQYC0XuiBP78Jz8hB8/5+Zn98Dm/8cUb+n3PfFampwdul3fs4oE5Vx7Onq8ebzh/+shtN/HH//KOv/1Z5vh+svFelfG80Pcdu8PA+TxxzjPDYSCK+Z+s7LqcKs/PC4fDwM3bPc9PmbpkcIpXq84Gq8dcoJBYK9VJy/Vb4sNes/xaxWeTHRbfGJyt8EL9rtdhb0dVpZApTa5Tt0m+mY3X2vZagMhVklHISyYrnM8j5/OJnDLn43kDc0qxYElRcsrc3ByswlQdm8WEsaly8lvCzAfPOI7k6ojB7unt3Z2ZxYrj+fkZEaHrOjPVnU0+FEQ4n0cEY6a6YH56aUkgWIU0ceb9VQqv7m4Zx5G0FNCM845cC7kYsyEEoe8dOS+kCWLoORwOIIVpPBNjbOBuIYTQjOhhWSYO+wPOe0QicCaEYD5FRak5NZZkBjxLWtjte5Y5EWPHsmSenx+NleQjTiAGT6mZGATvA8ucydnkdiFahafdsCeE2EzDI8/PT4QmMXIuEveREBzLPNMPPafT2KruCTFYcGoAg7YkYOVwGAw8coGilWk8czod2e13CEoIYUuNBO9RbzJC7zwpFVvvVU1amEt7vrZ/fXr8wOn4hFIpVahVmJeZEGzdrovy5ZfvOJ0St3e35FKIfcetwH4oHM8z/niy8dbQ4BV4CsHsFUKICELwkVwrUY3Fk5YFBcZp5u52z/6w5/7VnT0vddQ5GdykTcL9HT4kDpBmtCSkyf1jiDg8S1GqjziX6VyFPKMukqsZ19cyM9czwxCpiwHszq9Am/kvLap4FToXEAkEcTj11KxU6ViqgpbNGiZ2kWUOVCdkb3tT3wVyntmj1LJQvKUbO7E086KJwkJ0SvCORYLt4aSQdaZUCN68BIOApjNx6AghgKsMu4HgB4pzaF7oh47zMnJezng1n0inFSeV3bDn9DzR9T0ShTAEplJIS2acMyqOvus5Ps1oUXrp0WLfcXuzR7xwmke+ef9At7NkTkeHK0JeZmI/MKXK62GHc44fzws3r+85nY6IFEK/4/h4Yn4eeVrnUYXX93uWpVLSTBj2hMG13K0DtyCuFeJaFPFKLgXEo6VSU+b5OHKcH01e5iP9LlJzT10WxnJqrEolFzF2Yp5JJRvz3pW27Y2UTAPwe0odSZqYU0ZVSNkqYkpITOmM5oorPdNpIZEou0AIypxO+MFTQiQeOiSYAkJ9Ba8U9YgGY9OmkXk5s5SZVZ9UNVNKs1BQMFMgpWJ7Gak2pisJddlwDm1J/oadOHWoD1T51TbSvzLwdAFfLun4SzBx/dqFqcMaeKyA0Bo0XX1WrtCm64DUrfIaGkNJ1t+1NmwNu7RvpVUIbCaVG8OJNUhb7ZNbiNLAns0L6kW72zU72b7zclsvPi8XgGcF47iqqrVW8oILAmKbqLrdJ1rQzoXApLL51axMnRbBb0DJKmu7SIPWO9be1zYXF2bVGvC1a3ItqJSKE2fSiO3et6tU87q5Bm9qvbRDqxgNrz3mun5TM0a/PlQvbb4+Nksr1mtr99JdQLsVixJ19Op4FXbs30SGoFhdpTVb2LLQl8e0ffdmDN5AB23P+AIirWATl83feqKtn/0aRKj/sWMdFxu7wcaCWmkwaOH6tXxJsQBy+30LQlWM/ePUKipyBUADzWtGt/u6/uoS/Bv4izg82mR1rnk6FbwIPrwEnRx+Y61skrqVSdXOukpiRSyLrmpeYV5o/mXWgrQ+4BX4Rlc4i0oDhFed4QaKrTPXJThoKT/wagCAr5cN1Pp+XUGYS8Blj8M+IxurrrRreznHbuOq2h1UaYzAbWK+eL1Z1sxtbRNo4Jle2s4KYrs2/tp59Iqduv65mhcvYNTKcsX6ykblgtWrpTZAb2OHrl+z9kHnmonwxbPLKL+udbfG5HJriqBJjGXjRdrnr4I3twFVV2wuMd+yS5B36YwiKztqvd7v8KEApTFHV2YsXJ6drT0ZM/8WbCOqCK4GfAyMeW7dsSU9wCjwilVTcQ5fKyLOZE/qqGI+cNu5XEBzxqFUJ6xFB8X0nHi1YgNBjDWnAo6IFRIoBF8pQQlBONzc4t2elIXoQ0tqzOZzLwXvPH3XEbsObUC1ZRQrY5rsGmrlcBjxz5mf/fCnZJ35/m99j7xMhF5Jc+Dx/ZHHxxMlC2nOnCaTt83LjOrOvEicp+8C97vIR/cD+12gdx7nI0HY/CtKVoJ6xKkxv1rwplgwGKSxLatlRqGQam0M40K/G3DeJELRe4jGcA/egct4gW9++AM+/Z1/SSoV3GqgXRinia8eOu4+s6DNU6nO8+qz36CrDj68JzQmySevXnF3d0d5c8e8LPzVD7/k668Sb+/2/OTxgQ9PR948vef+49/km3PhPDl++nzL+3PPx4cjn3+h/Ol/9Rv82f/7L8nFvl+zspQF5z33r/c8fRg5n2YON4G96zgeF6umJIrmwvi00N3C3X3P82OmLrbRlkvntZmkMVLw3jbE1e5pWfdZjWlcnTN6f/NKsu6/zq/f/aNWNYAY39hPGVjnct+m3ia3U/Nes0p3jlKVc0qcp5HH5ydEYUrJkoUpIS4QItSSiSGSl8Q4nxGgpMV8jZyxjvJimeouBmJ0dN5RigWCJatVjvPC7d0tx+cjjw/PxNiZQbV3aKkG1AAheAOqajXpnCrLUlolLcc8zYxx4e7+NWlJPD09krOZFd/ub0hLYtgNVF1Y1JNrRUrlPI6spp3LtFCLGhC0zPjQEgxUnDPT/pKbDNgF9vs9KS2kZdlYwK/u74hdR6kzIQaWlJnnZWMYV82ggXnOpNPSmJa2lgx9R2cbCLQoS1pYmPFemMQRYjCWBYWUTvTsGMcZdYWd9AjCPGdqzeb76j3zZJUiba6rjNOEArc3Nzin9ENHjAG00A17zuczJVfOp4XbmxtyqZxPz3gfiTEiIvgYDKTL2aSHudBHZegHKpXTceJ4GhHnzay9uramwod3HxjHkefjI33nKTlTcmZeEqUay8eksHWTSJZscuO+6xAxM/txPONiT6lNY+3M6qOWTGgeVqVUlMUqeVEolXbu7/YRojLsbjidzvR9pBQP2da+tMx0e0eInuVkQApgTJ9WzGmIgZoywVuVtFKhc1aRUbxDcqYsM0spuAJBvMnyosnoc8045xn2PaqV5+lELcY+HnykSEJRXHSEKNRVat98hdAFVzI1z0Cm1kJwBuh476wqejWgpXPBpGKxoxusX/VDhwseT0BqIaVCF3r2fs+UCilngkQ6FykUUlaKVLpdtPmlVMbHE+CZzxnfKbubyHCIHN+PCMZ+9GHko/09uWbGcQb13O7uSNExTskqVqrSH3rmOkOu3B5u2cWetx/dM6ZnDrsbhsOetCT2t/cGkDhPHSfifuDm1R0uV+o4k11FO8B30ACfRCKnCS0zNWViPKDVc55H3j+/Q/yCMtIF8AzUpOazpw3Ecs3ioGaTUjrBPAkLWpRcI0jPbtiRciLnCZWCFofUQE4dKoH5nHn/dGYXejSdKTmjwZMkEYeAC5GwN0/X0NHAyoATY3Gp91RxpOVsJBZAXMTpgiMRnaMUMbUUZl5u9BlbFwKelBJVtAFhJhf2OKLr6PCoZGY1u4FfaRz9qgPuJXhjrzknW7CDrlI2WEGZa38T2PbGLcBY33t5w4VVpZuJ7spWsuCggUqrxGILorZGsgJBK2AFF8mOtMBJxDXavwFKrtGqLJ6yoORSc0o3aZ/92oKe1e/FqPe6sWBWs3J7v7XFe0DXYPJyv1DdgiHvzfFpDQLXrH8tKwAiL4CRClRpGe8WSGwUiSsWjmXMLoDOdmRt2RbdwIWVAbSiX7V9r13nBSzYgJkm0ZMW8JS1fe1OF7HrvGajrAa4dp5VMnOFPF2+hhcBYqt+pu0+jqcTZPC63/zNVYqxWvTCYjIGFFffucrn1q9YZVgrQLg2YgVS4EUnXp/d+ox/XYGohpdsFc3whnCvbKAGlqwVH1cw0cb8yupZb/xqMFybvK6xbNbnD9uYaV/9IsZ3m2SXBu7Y2HGNErz+48QZS9Fd93EBvw4KMwhfJX6i1h8usE0zTseCbrf1A5tvjNLfxv31MGXtApsocbuSdU4Eky44L9RSDVDH7pWxj9aLXtmA1h7Dlwx0upbZQss+bHOGg+b9cfluWobhwnJyCHh/eT6yAkIXRqgBiWsbSgMp1ke/Zj5e9gNZDdi5zOOr/JUGAK03fgMgmgmwKWquIee2iKwsGufMsHPtV00O3CB8Nr8mcXjfKrthn9+8BJr0S7b3r6DT1fqyzl1NRijXff3X4mjjbWWDiq1lUlvPFOvXNKm0+WXYQutch3cVqbmBzZlcPaW0Pu18k+ABUnAaqWIAljYPOFcqeE8QQSXgJOEw9lJog3qp4Al4KSzOIbU2sbQS1MZFUSG6yE23g2o+KSEGQr+jlNmwz5Y8CMHTxx2dj41dl0kpM08jecloTa0XB46PH/jBX52QqPzBH/4BP/rx3/D1l1/xw79+R8mJt69eQS+8Oz+TU2Z3CLza9xSgj57TyUx9P319TxyMYeXUEdRZ271HFfpgBsFFDdTevKxyRvqCZKUUq8qzrqUx9sQoFNkTopkM+2KUYvGeplIypgWF09dfWjZzVlR9A50LKp4PT4n5E2XnzGybqlQX6V6/5vj+K6gLZEd8dUstldM3jzhxnJPwJ3/0j/joNvHVj77iuMA0Lex9JbrItBS+eo78/OE1v/txYh9G/uhPXvGTH37BD/7D3xhD1DYlnJ5HnA68eXvDu28eOT3PHG53HG4Dp6eK1oSoGnPjZJ5ct692jM8L85yhWlU61Upt871IaUmytla3Hu/V+lBxnixCAIKq+VCKIgULsEr6LzcU/zMPcZZsKapWeRJFyQZaVqiauLhrXv5ZloWwO+Caf8vQ9ZzPYzPJHjifpuaxWHn9+jW7fcc4ngk+kDSzG3YsOZlEL5tflg+RYejwHmLvierJydbi2A0s85kP5w9mOv3q3trU9q1zSjisn/dd5O72liUtnMczIXr2+1uOxxOlJoahA4T337zndD6iFD75+FOcE3JJgCfnmarmi9RFxzD0+ODou0jKi5VMnwvDsGMaT+xvDux2PU9PjzinpDQxjsZsHIZoZt+953jMHI9HVOHx2UBqJ46UMqVYVThpUoiu60C03R8rvnOz3yGijOcTy2TslsN+b23rTdL4dHxmmmdijLy9u2c6TRRVYtwTopWgf/XqFsUxzzM5JZaU+fyL32CaZsbzCdVKqQUwj67oA7tXr3n3/h1diCwyU0vlzeu3jNNEyYVxNICeUuw5DAO+gvMeyM1PyuaUx+cPiPN0XcebYWCZF/vu09m8rZxn6K0i1tPjB24O+w3s995bws4JofOUbH1k3RiJax60amy9ECJa1Vhd4onBm5Sw7Tu884zjRMqZZejZ+w5Zk/Pf8f10mReq83Qh4opFh8N+R+wDx/MRzSAEaloQCSzLhO+iyYC9o3N7XDAQH+8ZU2FRSHOmLwOBgRg75nIiDj01m1Q0+AgexjGBS7hkvmhTXhANOG22GcX83JZ5Nl9fZyw8cFQRQrR5t+a2poslpHKpZCuhB7LgnNB7z83ugGpi2JspeAzB9mvVQJaSM6705gnWvJtSqYS2r0tlJvaOXGZCL5R6huqAHu8CNSWOD4+IdBSntj8vlXSemAaHRKHqQqHQdzv2ux05P+C9Z+gjPnbEuWfKyhd3rxhuDrx5+5qff/NTbu96ht5Tb3a41NGJ+R3fHCKH3Z5+8CznkZwWlroYs+fgDCw/T2iujPmMkpBc2KlQivJ8eqKWE46EkKhZbe4uViUyRHOTNHC+ktKMK6s1SKGoo+aKVmMIM+xZcmFKFe8qrhYzFF9M5phSIR0zoQ9IzfRdz2G/J3ZCDNUM2aUjSEXSjEjFU/BeQe15VSrjbAC/1GrzoFdwlpD3EsnLYhYoRBa130koZJlMSps7QvBm9+DNZN+YuBWpgpeIuYX9p49fGXjym9Liwob59pZ9A3fWuIKX4FALkSzYWD+zRaGrNxIvQCsLP9bAZw3BVmCLb337eqyg1QV0WoNZceClErw0XfUKOl38m0Bxa2CrFYpuixOscpHW6g3F0G9d30VWdHXxG1Bh6/daarx9v7uANihWzaYFWZu8sJ1xBQJWps7KbtrOvYFMF6+ia9ypxS3b+QqtHLyltTcWiRergKbXShvaPfNNHoAZyLqiZNUNfFoZS8bq0BYkr228AIPaTr4CWibda2yV7SstvKzNx+rTz3eEaqy1ugXnax+x/2/enFfXLheAUa/MzNd7uD7Pq7Poiz72i8evk9RuG6+yOf1coKDVy0wNgnTVZFDawA9dzaalsYCkGZO3saZgbBNnVelKy1Bvz0XlMtYFkwRoAwBwBu462ORuLSvonLCKsBpWwQqYrD4+1AYwXSGza9jirsaYXcra8RvDUI1UKtL6usMqnlU2cEO2TnMBzWyMXuYIlQI4all97lZwzhnzZ2Mkre27OrZ+fjVIt3lx/bM6NF/ka3V7JA2Ya2WmbTMoGwBT62VeuEBtrR26MkrXz16e0dpXYIXc2H42WXEDLGQdK43dJKs/08q6Ws8jl/HY5kJxYjIJLvdZXJPgAeA2aecajq3g5zrLWkvaOdw6418OFZsf19avJdhZr3ubl77bY7nKOq8XQEy6vbI42/xV1QxCbbprpsQ4hu4WadK3ppc1Bklt8mTBZNS14FwgimMpxSj8znFrTHNmrGxz0IBJW0ZiY1fZWPMUKsV5qMWyfIDUjMeAlixKh9DFgX4vBk65gT4OTNkCQm1SDi91W1sdllE7TyPjOEIx2DGhUBeGm8xHH92zHM989fXP+Ys//yt++MNvEI18fH/L/rAj1co5mUeTU5hzpYpyd3/DZ598xFc/+YqbLrZ2O7LY2LPqf0ZOj2KsL1GHOocvCrqgsSdlY2G52BiceEoWNAQilswpjaIuLlObxF+qs+dbKl5hfnjPfHwCN7SxirFQnOM8J94/Jr73ym1ZdYCwH+gON5TjybwynPJHf/JP+H/9q3/Fx5//Bk/HZ4YhcPfxDU/HEXd7h2plN0CYPOjMlIQffH3DH/3GI7d94s2rZ/7Zn37Bj//qp0zjRKbgVJCSOT3a/P3203s+fP3I89PIzb7ncPA8nxLSxmZWKKeFujj2twPqFuZTQbSx52iSM7VZQFFydc3LbyHRvDbUWHdLY+ra1qxSikE3qyT6u3wY2FK2AgmrvLANQETMV2hd20otKI6u35G1Ms0Tp+eT9ati62xKo439RkWfZzO5FaltX9v2X1WbD5OtJbtdzycfv+XV6wPTfDbpnAilJNKczROo3/H0fGSanug6M8j23rMfBnxwLEvisNszTomUTPZ1Po+M08Td7W0zWn6C2HFze0s3RHKemaYT3jtOpxNd1+O85/n4TMqF/X5H1YFcMilNhBCJYcfT05mSCze3B+bpTFpGpmVkGifevHnD4WYgp2aqPk2I2PW+enXP4XDL08MTz0eT7ZlPlOP29pb9vifnhZvbA8fnZ9JScM6x3+9Iy0JOC7thYL/fA2aOLiJ8eP+eOSWG3c6kiKXw8y+/5v7mlhA8z89H+tpTtTCnmfM4Imq+d6fzCA0Aq1UZhqH1EGWZE+fxzM3hhi727ZnZ+vnzr35GSolhGLi/f8U0TeSUzEx8mkjes9/tCT6wGwbevX/HspzZ7/fc7PeM08R4nMm5Enxn1fVqxTnH6XwmrJXvooFHWiuxi+SyMOyi2R5IBOweoUrXRZbFQNCUFrsX1a4LKVbBc2d+feM4mVwzGKgVSqBKYS00891egeH8NONlh1JZymz+RZqRbOtpXgqDH9Ci1JgIg4BmQhcQ10FZcDrhPSiRJQmhNwahppmFgIseqUItGcRYypFKFwK7vZDUsxQ4P09EP1BSomgxKXIAR6BOQllsLa9UgvdICEgMjGUiu4KLwpwShcicjPncu0iQQr8L+KoEV3Axsj/0JsvLqVVVreSaSGHGRU/sva391YoXFF9xvcNVS9bUAnFn0rxSjP0cvCclbcVNhNDvCERefzSgaeb4/MjbL97w0dvPqD/7hqfHR/a9zQlVI8Owo6TmfxaE3esb+tsDp2VCdSGi1OcTIWU6H+hjh+sDfoiEPgCVuS6kZTTZa3aE6hmXkeP4geAdzmeW8QTq7R6pUlwiy0zUQggDJXmcmvxXMbP4ognNmZRKU10o5GokVrGY18Jvx8M0IlJx4imzzRW5KONYWBaMRdY7XBSidNzvB276geAitS7IYMxzFVOEOAkEgU6EbghWZXNJ9ENEnCXIcynGQlzqBhx3sUdKx1gF0QxistxSK4qBYbHfYVs7YZoSwSl9iIhEihbE/Wqcxf8dHk/u2/v5dlwAoRd/6yVkWoGKtYz2CgRtgW/7kEnfVinQChy1mkMr+4QLQCTXH74+RK6YUmyMHZPyWEl07xRx+qLdJhnUS5uvArUVTHMrg8FQp0swu2qJZGWBXYCQjRlyfYc2OZC9ZLdXt05pkrY1OFxxk8ZyUANbcsvKrDH3yt55eedXcEq5xkj0Csiq1aQBdX2WLdBbKci+8oLxsD3EJqWQFgvVFdxZA+EWoNd2j8wA91tLy3rruOAG5nXQNqNX6GLm4hrTO08ULghZNSnR5Vov4kJtm1pjtqzfpVsAvAFPeg0kXQXa32I4XYMOv07A04q6rdUa1ye1QiU2Aprmv72iDUSsLfBcX4O1QljzfVKrauREqa4gVTGvHd36wgo+XUy1Hau0zEsz9EQ3Y36nglQz37WNyVX9MVFUc+v7V4OgPQ+HVYipDVCtWtk8g9Amz7qAcSKrJ1KTZTX9Z8U1lLyBdc1H4RLsq/lHNR+klk9qTCcD4rQKQjBmVwustsuQNhav+51v/UocL/3FFNqctQn3ZGUGWRvXuecyai4/m7RuGxVoVaRxhi5JBLeRrC7T6+W+rh1gy3jC5TvXL3Kr1K3J2NxlLrS5jQYwaZPprX1PcD6wSeWkPZfG2lplkJvBAb8IMm3tkTYXtvm/rte+odmX+e8yX3+3D6eyNdOeYFuTVRrb08AgkQbRqd/+7rpAKs/UZmAvrICTx/uO4AKl2gZmEMc5LyhKT6VXwWnBqyPWTMGRWwfptvWxMFeHWf/XVrTAwLIIrQS0fTcqVBH8PpDziX0YOPQ37LuO8/lkc7c4AmaKXMuEyIFSHc/niafT0cyExdsXEMF/zO//yf+dePfMX//F/8L/+K//DV//9EROjqfxyKvbHTd3t3zz/pFclOIM9DgMkVmMDv98PPLqZiBQzRNBrOpMxaPSU+ZEFyKRJvFs/VCiUeZzWZAQjCrvbZQH3xhjKnSpMmshieA1g/O21pXMkgtgbIJIJE8Tz9/8jMMnv4VUqzqTKuSl0LvKw9PIp/dD21etYHKk//gTjuOP6VDm8ZnPv/hNPv7oUx6/ec/DdOa/+9d/yW9/+oYcer73ek8tC91uzy55xklJtfLzp46vnwY+v8/05czv/OMzf/ynX/A//NlfodWZrt5Vqi98eHjilAde3wwcz4nHp4nbu4G7uz1Pz2e0ZPsMnmXOFKcc7naIWzifsu1vKhRpXoHULcGUVTf2Yy6F4qwSb6qgpVxtzwSk9a3v+FGzb35gTc7d1kkr0lKa8bXdL2PrXua7D4/vGMeRPg5oFbxMpDIBSgiOGDoQNg+y25sdT0/GDphSRhvA4L2jehh2PefzER8rtWaGvseHwPk8UmvhdBrRKsTYcXM4kIv5Bpmh+MS8JFJKPHx44vb2jnlaSMUMrxV4ejoBlY8++oSh3/P4+MjDhwfEKbc3N2iF3f4GlAZg3VDbvO2co/c9MQZqqcTY8fpVx+vXr3n/4R25ZIIPDL3JX9JiEtzbmzumOZFSoZZCjJHT6cSH9z+z/WWt5Dxyd3cHSptvFkBJaSEIvLq/YZomnj68tyINCs7DPE+bn1g/dHzxve9xPp+Zmpwv+o5SHdM40+8C3//NLzgfR3KBKU3sBuHu9pZht7NCBAjjvLAsiWVO0NbL42lkno35mbKBzfvDDd57+i6yGyK1Kk9PD8xzsjm92r6pqPLlVz/DecfdzS19tzMPnvOZd+8eTJYXBpxUSi6Udt21Vvq+I+dMyjMpzez3B0IMoBUflL4PhODJ6bLP9s4zTws+BPq+s742zQxDh1JaUglKKQRn/lN935OWxO39Pd6bUbuuFgrfcfC46yPLfMaFzhjDNRN9xWeh1ELX7SAklmB+WD4FvDhczAietBS6uOf5+YH+JoCvpGUmuA7XRYpUk46lhX3sgYILoMtIWSAMZh59PCl5cQz3EXSm6xxpXlVHVjVtSZVuZ3vnnBMOA4uCurZPUNR5eyZVIRpjJ7qBWB0hKpnCLhow7AZHyDNpfkRR/K1DcqIwY4UfslVb7TxzmphPE73v6UNPt7vDucy5WrGKlRU/ppndrmPX7SnHE/dvDmiupMfRTP6puJrZDYGndz9Hb+746OPvcZ6Vp+czh13Pp59+xMPTAx+eHrn/6GPG88zd4Y7BDzw/HqEWXOc5HHqGfbTCCNX2pNEFfH+DqDem07EynkaTPPoFrTO6ZPAHWMx/a9ADwTtyPlKzsuQZzVOj5zpqKpRU8WLWGS44G2vOk7UaqaUEtCkN8rQgpaAls6TEebbCJaoVH5VuCPQxEl3P0B/ovDdTd7eAZEJQ1BUyAef2OIn44NDoSF6Y05lcYM89Xh2pKlSHKx1eBrQa0KlqVTxdS+47ZzGdaMCrEruIpyPlyfZ0Q0CdYy5jS/g7yH/PjCdFLGhfmUcr9sAltHkJDF02yVtw8QJ72eAdC3pWIGb7c/FEUWnORVenWM3H/+7jEkxdQhTjVmwsrKpbkKWscMklwFqz/E39gWMtVd4CRlmZFRdK9Pp+u8QVBFqDPZCrdtdv7ZMMJLmKn5tP0hZ66sUvJ9cGPJXWgno5x/qfC25zkZ6Bna+oaxkNY/5cMv+yBZcrwJAaC+XyBdcSyvacttfbHZTtybYNVOOAbTd8vRalrB5CeuWx1CCqtVesoT3QAnmrtGNffbmfm6k419etLeBpwFd73xYOr5vXrfetbdft56tHsPWvK/zg1+RofQLBN0mSPZ8mx9rYLa3v17I9g9rAH4NWlJXLCG38Oxujlj0LVm48Nynp1tHd1VjaPtyAJ0z61oLmlbnjkaYYkw18ah9rDh/VsCDXJJNrLN42iOsYVa1tHro8NF0BlBXHEDZpn3eNTQeoa5LWusJGejVYq0lgtDEG2wTgmnSiwSlbD750n/a9TfuvaDMtXwFnuK4Yuc2lugrz1ttnANc2BwsXf65tDrjI+0xj3qSHKwi1de+6zefaQI6NlcgqQl395KoBTEhj0Kxz28pykra5aIBea+3Kc9wKSqxTTgOSVj8vbedYPZ/WcSkALbuzzthr+66Pa5aa0hirVwxPu46X/fi7f7Rn19iGVnrd5n7nXANgLbtY1QxrQfFElMKcrPqRXW+g1D1F96gcqDhKY9xKK/LgEKIo0TtKNaZLh+cUQJMScQYMeZMpB2+ySnGeXpVRheCETq0aXibgdCG4zOAFHwe6XnA+4uOAd8beqCVb5s45KolcTbY2pYWH4xNLSgjm8VBxkAt+/98Q+j/CuX9LnuH9N2frI7UQNHLz6o79bU/9MlnmzgWen47c3R246RxlHqkL+BjJAlmFUECdGWwWWSBlPOa5IgGcD22d96g4fOfwCdQF1LsNjMdhQFZezLZTnBX0oFBzQkqBbPc+OoiS8LXy8OXPuP/stympQAhtnptJtfL+oXJ6u+P+rkfbZ6tU+rtblqEnnyZSEf7nf/9v+bf/7t/xu7//j/mNzz7lX/9//zv+P89HXt/dUcUT4sDNzWtua+H4NJJn4SE7/uKrPX/4xYSochu/4Y//6T1/8Rd3fPXVA671PbIlh84fnpnOHW/f7BHf8XAcudlF+l3H09NEyRMqHUKGo7CUhVf3t8TccTydyNWj1aQpDlBp8l8RXIIsGc/K8AOK3bttDtBia8+vAfAU4w6nlaK5rU3Bsui1gFQC0ebe6i97o+aFd3O753g6MZ4XlrkyL4kYrOKiEwP0rfJbwLlKiJH94RXeeWKcGaeFop6SPWvVUmkyVy+RUippyaQlg5iUZZlNyjonM6zOxcp6p6WQ0sJ+v6fvPfOSGfZ77ht4kYvtA2pNfP31NwiON69f8/nnn/H49ECtMC8ZFxyffvIx799/sEpwLhK9p+REyolSTcqXi3m9pJLx3hGimZ33PvLR2zumaaQXISUzLBcqXW8FFQ6HPSEYaAJwHk9UNdbS69e3jOPEstj9H/Z75mnm+PzE0Pfs97ekVFiWCaBV7DPW1ofHhZwK47Qw9DvGnJjmkT46avV8/dU3ZloeujanOT58eMA/PbaKfh7nrAKfcwHvtPluibGLXGCaZ7wPaIU5TzgvWGVhR4xC1/fEGHl4eCQl87ja7/eU5gc3zTOWhIGbww0gzNNixAAnxBhN+iuKyfMcIoEYAvM847yZxu92AyKJED05LW3PAcPQkfKCc45xHDnsD/S9Mci6VpghN4nd/d09qpUQA7kmumgSTKuAqs1P87u9Gsd9ZJozlIk4dBQVgj/gZqWLQuh7Hh/eEwcPWSjZ4pSqE3nK6BIhe1KJdDqgtRCCVY9zUZBckDzjvJJKBgJDDEzzRC2OsDioDq+V6MCnlrCo5lFWSyaEyFKtgmJHQEOg4s2rtxQ656g+UJzj/tUran1CZMJFYzmLVuIhoDITOqHvIZDQMZPzjHhBQluv6kBexCR3LlCWYgUzQsS5HZoFCrz96C0Px/cM7gZxnnnOZrytEGLP7v6G8zJRy5lUJ2Sv6LlyfHoglj2D70huwLuBoCBSwFdqVe4Pr3j88MjzwwfevHrDsPNE/wZXhF3f40VQqvnZWbqcXBfEVfphh1aPVtd8lwqarFBSbZVnq/Q4jSypsswjIjb+q1vIslA9dk8w4NfVQMGjzhPFQU2WqPM7qI6ccpMrKIFkpI1k4H+ptiYoym53gw+WKPCSmy1QRqKniuB8K8ikxuL3DrwoXfT46Ekuo1pMRiiOXBZTdDCbsYpGgngU81WsouYdW53tc0oG1pDGKp7H0KMJqi5kKWQS1MWknuJfpMn/Y8evDDx9K/6+NEjXOGMNkFrAchXEXv9s/zW9qaxR/1pl62rSWYEoe8cv/vTLG3gBElZw6QIEtQ33KiVbA+3Gcqb5xvh2YbVRtnxr/wZe6cqWaCKP5l2yWqlsDIotENJfuHebQkd/yWvoVv61VuzvzUdqfQ1yxQz5GoiyPhG9ltZcbgsXIMWAm1rZ3sfWvFW61ACc9myuz8H2fZcgU/Qim3sRrF4Fvy8BHjYAzV6ySjWrnG6D8WS9y9cg3SVQvnTyDQ5gdfS5/Eq3m6tXbbz8dQmoW4TwgvWk1x/g6tq3U323F8qXx4aIWt+/eh7rc1vxFFgf+wp+WIWs1WtsfUrrpLTeM3GCVxst3lv1HCfVuD7uytAf3ejVBkYZwroZ/Ttt7J5VgtWAjauHJ81jyLro+vStXQYDldZdVoaOgpTt+ld/q1XZtUoIaW1UzPepYH45FwCFLRu9gkZ2syrFnELNUFmwrIYTtBjDsjUd60PuZf/ShrGwAl3WghVEsrHU/sg1yNvkacClNOiVEPol3sblbGxTNu08/6nuvAFYXPGsrny/VnmhOJNnrhK+a+GxWydlGgBEA69XQ/TGcpBtjmksLGT7xz7/koX7i+xD3a5xLSxgYKternsdD78uh6yjrj3dVinVSqobc6JKMJJtw/Od64jO3tP4eCh7nP8ezgfmtLOy3ghBHLUUOucpta1xWmxDJYWkCa0RofkOqUAxmV0Vq9bVuwCNph8VXFWyFmMziFXKwRVCjJR8NI8ZDyrKlGZjurRDVchaKTrzfHwyHxf1+CDUBFSPht+if/Vf8/OHM8Q9hT0x7omhUnKGuHDYDey7zjZnrpJqQVGen498/NnHVFUWCtlhlYVyIQjG0kJs/CNUzah4rJKkbdlElCoZbcwkUaUU81eLYr5bokAXbY3LylIzusz23BZbDLtOiW4x/4xcePjqh/x2/hO0iIHfzeMOhbJUnh8f+OzmNXOpLMm+vywjJZ3J2cympzlzeHXP4fUr4tDzO7/zj/irP/8rhv0t3g/E3Z7iPP3Qsd8PzUS88sP3t3x5fOa+V/ow8f3PM7/7j1/x0y8fbHbNpc2fVs9wnBLfvDtyf39DCIEPDycOt3sOh46n58xSZwSH08rzOVMFXt3sULfn+TSzLIJopWhFXNt/6aXCaKLiizFyLcngtvlZbVhQ/XebLQFAYPO+q61v2VoWWuKs7WpEjQHsIxIjqpUpnehDpPSOnCcOh0OThNo8GYOVVw/Bcx6PxNDj9wNPT0+EvmfnOpzfMXSZooU3b+95+/aW25sd43imlAXVwmG/x/kICsOgjNNkc3pvFewQ2O8Har2zqrTOsTu45m/iGPY31ArLPOPoKcMOEA43NzgPIbpmx+goNXM8Hbm/v2MaF1zoGtBiTIGcU1MYKDe3twie3NhbfjDQzLL0ivPC/uYGfx45nY4sKRPUALgeYUmJWiulQFomA7B8b+bezhKxp/PIbjDDXwTO5zPDsAc8tajJdXNCS2G33xE765OH/S2lKMEJt3cDznecxpEYHbELlAI0wC7XTDdYVUvvI103bIkmtDDnmZvDDfO8tEIh0p7FjhhNdlcrHE9HSzhUYx4RhBitelUpGRHXZHATThyn80jw5vninVDmhXFaELEqef3QEYIVLUg5g8LpdKLvI7UWljlb4ReRVnDJKnZ57yilsN/vmZeFoe8IPiA4Sm6JuWZYHbxvlfGU4+lIH3cWcznzuO38rx6S/kMcSz6CDOTFpN+HvqcmR8VzHhNdqdTZ0QUzdpYYKMsZlsLge0ZNhAi9BryrDH1EXaZKskSqAsUsDM5zwjePm9JH0mLzhq+VQGaIEVdKq3SZyRS6DpIkBE9KR7TuqKUYacJpM+XXrZgVmnCS6HvBzLctYeWHhKij8x27ric6YUmBrhvMCHuaLR4uynxckOCMnZgSzilaHX0YzBSgVJbzhK/CMleqWoVIkR6K0sdA10X6sKPMhbjbkVxiuH+NLDPlrOxvdoRXVlhg6CNP48nWuH7HkhdubjuCz9zslDDA7f0teVroXPP+3JLOypJHlvKMl0wtQOkQsbWvGzqGXWReTBKYqyNrY2vXhcSCqPknFa1MKeG0JzoHXpGiuCSI95TiiG4HeNCKLJ6oEak9S8kkZvO0zJ7SgKfc2J5DN5jpuC64oVJLwaO4HmooFmOgiItoifji2TVWVBcC2RVKSXhn5uAuOtRlMoJIomsG8RSl6tx8YX0rdKR0LtBAApAObfv7V69ueP8hcZpmNFiUEaNHUk9NFRfdLx033z7+i4zybwcEVga47YqpjYVxkUfZZ2D1ZkFtI7Imrdf46O+SOW1sli0AuwAYq6fJFjRXGhtmDcW0ZRbXIKidkxU/ahn79uomI7oKXq4K9a0QDGBZ6nK9qa4vPwdN8qY0xoZlrg14kS27vbKU1jZdGD7tnNquV9cgvN2Hq5u7eeJs7ZRmKAzXUrUrahO0Z7R+2ar8uLSkXev2kWvAcT3v2ho7z8reWKVvWmUDqlTZLElWsGM783+E7bb6ga2B+v+/h74IhC4g369RuNqONWiHzR+Jl9dTroJ1GqCjzaxfmyziQsdcT3H17F+czwAE1zCh62Gyll5HbEEULj5iJpE1XzPzLWJjJhng2b5BGlhRLmas6zOvmgxUrhdYcWtrm1MMI3GYRbW2zX5rpE0wWOU/4dKXfAMyGmuo2rxkrKrWCm1jUtQYTdWhXpFm9iys88jKCpINHK/lIkc1tlJr/wqItrlKdAVRLsPtRX+8TID2XU3itL68eoy4dV5Yb69ewMBfkK5cAbjWjxqwtM6VK1DkfPO0WmV2YgCJrJU02UAqXc/bPIfWZ+pWNkOj3qtc7tsKboE0ZhRtgbzqfutNWAHRBlRurMn1zq3MK777h0no1LJldcXo1qpy0srUGyAk7mqlcp5xfkZrMUo5HSqvmYviwy3muGTmoE4bXV4iqQarF1ozDiFIwYvHN+8O83jz+GZ6jxrQ69cxJ0KpSnSCL4KXQlCTURcR+q5D1RNDh7gRVSWVBsg20FarQ1xgnCZO42ljVjkXyLVQ6mteffH/4Jsxcjx+Ra2Bjz7/LX7283cMMTOEJ778JjOOZzyVLkZu9wceTxNzqtTgeHh45Pb2jsfjV9zsD2Yau1SiMw/DQgFVuhCoXhvgISYnFMtoO63I6mO4LoHVfvBOIJinncsOJEGZyCkjzXNHNaFpYqkL81Q5jwvyox/w43/73+J8z7C/I+z2DP2eGgKx73nPjp+OPdNpRkXpfESWbPKHUuhix5c//gk3hz1vPv6Y09MDNS0sS+bpdOZVN3D76kBkoe/uOdwMTMtIzvA4HfgPPx747H6k7wKH/czv/5OO/+nf73j3zTOCSaqrM0Nkp8IxZ9Kxcn/YsasDH05nDvvA4fWBeh45lRHfElUPtZCXwuvbe94OkcfxzKnMZvasgkpt+z1pSQSoGLhaMG+nda/WhBtk+VXzrf9wR86TSeG0tnnXJK+FBuJWEC2Yk5WiIQIwziPPjyem80yZrRgN2vw6svkdWnWryliLVYoLPcs8UlJiPI827oqyzAVEqSmRpomnspgReC6IQNcFJFfzQRNHWRIumrn/kpYml+q2Pdy2NKtSlsQyLgbCBI8EM6c+nc5meBwc/RDQar6gJZv8r2Zj+5RilbFKKVuQnLUSQsA7z7SMdLGj63ecTifmcSJET62Jrh84PT2wpMyu71qwWVsi1RO8J2umj47Ewn7f03VWDW6eFqY0kUtmmWdQY/n0fWeyv74np0JOcD4viFRUZ2oxQ/wPDx/wzrHbDRyPE8pI6CPLMnMeTyZvcx7vPSlb4IjCPM0gAeeE/a5nXiZKUZ6ej+3emheN90LsolVzrJVh6BE5YGMgsCyJrjPAR8nNh6VSloL3BnCZB41V5/QeonqCenxYmVeJ0+kZ782EfL8b2n7IANAuRmI34ScDmwz0NIlfCIFlWRgGAyb62KGqOLFqW0ilZvN66jqryFZyJu48XRhIU8LFjuFw8w8wKn/1Y5oSOCF2PUogjRnvoNCzZMhpxLuA5mBFM7xDO4cukTICpVKXGU9gOk2E3qpA5prb9naHiLBkq7wm4kg1I10g10zVicELgWq1ZnyzpFiwPhXseyVEEgZgeW0ggk0ubWce0epIZSFEZ1L8nEAHKp5QC33s6fudrWsu4LtgrKnsmXMl68K0zKSiRPEQPC50hGhSL8FbkYkK83GGPuDiwDKekOrwXSBl5cO7JwNPKdy/vmEuM84LoVXarlJ49eaeaVn48P49n3/v+2SJHAq42PGcT7gboY8OF2ZCdOwPAzV2eNzGPUhlYcon0jJyPH8g+tLYswMh7AhhxzRn5vloCZwyWcXaIuSccU7w6tFic1bQHXvXk3K12MUrUjOxOmJ0nJaZUkKLcS2xgmTWGOY4JublyL7rQYNJ0h30nefVYWf7oKpkyWgA7zuLBzRZ4ksrqShO9vR+R5Se0Dl8J+ZhlyteHCH0FlNUbUXVrIiCJfgttqi6IOpsy6IgjWUOuYVYGS+Bd+++akbyFara/JQDVKHogq/lVxpHv7rUrgVV/1F124v364XptGaX27GW76QFUi0makGIWFZ3NU2lzdENjPh2Ur5uQe/lWD9ZV1mBghkAs53PtYZZvHT1Pa0JRqaQDRBp0W9jGqwtMytMfxXAoFyoAEqTA4gt+m0AbCbgdW3c1fWwSsasEbVavaaXoMxFsrJ9egVurhgpBlZdBVtXX/ULNn7X4NVmWPtSovdtkAy9gHrbp1uAp1fv31ga2+XK1voNYLr6Q9vQKLRKc8LV6bZzXl68BqTWy7kGQy4Xv31uBeXaA9+ArfXzW5D9S677+hb8PQBb/6WOVQrmxCHiL/KE9hC2/qQreLMyz8QmWypIaQw3LsDB9f1fR4aYHMo33EFW83K0sZpskKzBs+PSZwys8Q2kWIGyBli41nva/GLMvAb8yNrXVjizXgb19mBftpMGoq0eaxeodA13DHxqRmigAa6AqI1FuI1py2JrA0NMMuhwtYIrjXklrJOECEg1udxq1rlWyTQQpt3rNr5Xq721uzqnW3vXYH+joXKB3C4i4suIvSD4sJXtXkEwtwL1vPjc5TscQmjnkDY3OjM49CYFWMGjKtrYTBjA1M5h4Mh2VnvOTlr/XC3l/Utkbf2+DSlbP+et38p1X2x9uVUZdK6xyK4WkfXO/VqMYr30Gd2QJ8WpsfgEhbLKOq0/qwRQZUmJtv3By2uK7Kl1IsYbak64Nv6duI0T5b2BQEWbGbso5txRyBIIXOYCJ0InMKHkagU8cEItTWrhrBqZw/wLpdg6UYhtQ2UMkFplVW5Sq7EVyJXzlNtGyeF8pabKopHd7f+F5P6Ah4efwJxJS+KTL77Hf7W/4au//Z95fbDA6puvviH948+JwRG9VQByUkhV2PuAiLIbBkSEKVVowZOsctnowAeTPmHJpqpq3lq0PUwbbeosa2mb/bZeiwMyWhdIM6JqbA3nKbWQy2xVZWolVdh3A/HpA1/+D39GHAb6w55PfuP7fPY7f0AEdgT6vCM97KnnZBv83UAIgRaPcDofeXh4oHQdP/nbHxG8ID6SauXm7o7Hhwdu+8Qnw5mHp4Gb3Y5pOHOeMyqVv/jqDX/0G2fe7Gc6V/jd3478wT9/zX//757t2UkhDubL2QVnDGwWZge33CBj4FifuXnt+Pz5locs8GrBeUE8OCo1Hrkv9+zPbzkPR47lqYHUFd+YjyUXVJr82StllZKWNl+4ShD3Iqn3XT1U26wmviV5bH1akxd4QWvGokpjBpUlIUCQQOd7ko4EZ2PSeCXGKI3BE4NAElzs6LsOH2DoOh4en0mpkqkUp+yGnrv9juAcaVlYLQocMJ1nRBfLgAOxC+x2A6gyjRUfo8lpgFLNJDh4T/SeWgq1LLbvzYXc1sPgPcPQo6gxFQSGfqAGBTWpRwiOLjpyrqAmxyqlGOBbigX9QJXMeZ7RUpr/o+2NT49nui6yiz2VarIj78g1k1O1anDFTLFj8OSSmR8ncrF77bxjGA5oqeRsc9GyJJY008VIaCBV33UsaSYtBsDs9oOBZ6XgvWcslX7X21peK7thR8nSTMuNleR8QNWqXU5TYs6JnAraqrOO44QgDLuwVcXVWpmmmdgFVBNd78i5UMrC7e2eZbH7Os9mQmDG5dUkbWKM12HY8b0vPqHrIo+PRx4entntdvjGWBnHkePxRFoyS1rou455SQy+QxG8821rYbOMc+aZaXs1Z6BYv6PkhPce74OtV80wv4sDw9BTq+2FvHdW3dF1SOyQ8N1mPDnfmaRNDACvNbNzHtGF/Y0ZprtSiN6TVCklIcGkl06ErgyoLrZHUshZyU7xvoNqCVMfWjyiQimVKAGK0IVKrjNm+gTBNwuaWunMiJeaPU46Sg6UHFCC7adcxTtvVZerEoOjaAEKIUST6Aaxc0WP7yIOA5vRasWCvFJTRqsSohlUl2o+aloKyzziolKqoMUkmUGVvFRwnlKF/f0NqGd8OrHfC4eu4zwujMeRu/se7zM6TfRdAKlkl5He093d8fTlB4LbA4EQOu7fvoYYWMoRXMB5SLkg80zpDCiJnRne5yyMqTLPEy4nNAm5GigkLpBzhvxs4PP8TCeCSKWWhKvGdHYIopGMxfLLUhh2HarFJMBihbigoCUgEphLRp1VCXbVPGdTySyqOAoBRWSBoIQ4IE7YdYEgFVwmOkGlR9XYSGjBu4jzHVbXpyJSiVHRrrJEJQFCsM/WghYhE60PqODoqNpMe8FUW66YLYFEUrEYyhQljqSZJA7U4XVNDEZqAa8Br95kd05Rib/SOPrPHuV/Vyj+qwFTDWlaf+RbAX4Dn9hevw4I20buV9hkKK3kcdNprawppP3cYiHRlUXRwiBpbVhBnlbydwWj6gr7NMPsy0WvrdStytwa95Yr9hIbyHIJf6/bXAEtF+Bpq2a0BdDuKii8YiG131/YFysA87J9L8KsFdVb363Xvxd+8UmvgTasYrc2RwKGvq9Ms7oCSNsffXHm9bsr2kC1FtSubV7BtPYJ+TYDY/v2l/1hvTfX1/wL5uq0wKHdtxU8u+BS1wFsC6xXMECv7uSvwWb3ctg1bqCAs8qBgt2v9WmWahNPWQFDMfmcda8mOROx7PUl3dm+QTY/NZNJXQL9lX3k4PJZFKl6eb+F1BfQQI1dcN116yZHaC852cBabRTURtm5YsY1AEau++FqOG7j2jawDYaQxjICqMVKkBYswwkNpHFrN6U1t8njjIZrfcNAPmP7uAYurZ5FtQGBoS0gNtHbmLH7LFquRuE1TOONUdWq9K3XsY4FkQvwfzWibHNyNQh1nft+YZhv0MXLASU06UNsoNDKVHLbNW7G6o2lZMyQFTBqvWQDrK5mp+1cjZnn7V6tEs31Gi7g8uW+/LJ1Z3u/c/ZcRYwGzjofKC+a9V0/dOPCNa8660NWlj40sDe3pdO1ta+xBsioCMV3eLllGt/jXUclsKRGm5eVmCYmoRGrUuewYhxQiCokgXljzNHMyvUinXe6JZK8WDtso9FAzTZOUvVUPF20TF/OlsV9cU4E1YIPQsgGrlW1CjzV/y5z+Ge8/+YdaRpJy4QTz+Fwh+KZnl8xhzO/5T3/4Qcj37x/5PbQETsBZ2tV8I5lzlQdtzV/iBGvcDpNlM6AVKedrVPSJLQNLahqJfiq+FbAoA2maqBglSYmlULQgugCZEIIOAJFCyVWJAeWKigZyFg96kLsHLu+I4jw0WHgex/fg55xJeNc5XYX8Ycbq76VJyrZfFlCz9/+6AfMOfPq47dmSAw8Pz/hHbx++5rOeU6P7/jyr/8d3Pwx+/3HHPZ7CiMpJd5P9/z1VyP/5PN3lDry+rbyf/zTW57jPc/zGTTiY6toKLWNMQ/qCJq5m27ZfROptyf2tzPd0x0cFsJbA+HRbBnWPNH1jphuuHnjKGEkxsv+B9W2RzYwQ3CbFCzlSqkGSs5L/i80EP/zD0vKrftACwJ1Y6+u/HShqiPjUOctWEmZUqqB+8CamrbkaoAKXgLa5LZWiSwx7HpGZkKIpDxTUas4Rmd90AU6ZwUGajVD7uk8oipkQxIRKYz1zOonGEOrVKW1+flkY6l6C67HcaSqsaViFw1Aqplc2lqo5keXG7NJ1Nv7cmIaZ3yI7Pc7yLYPiTEgEfqhgXTOkZaEamNpSGXY71imRC2V0AU8JtOrpTYpHaDgvcl6Ul6YRgOmhj4wDAPBR/NiagmTlAz4ysmSUD5YckbVQK1uv2cYemLs8M5AunmaGZoEcpwnYj9sMv3D7Y4YI7VmUs08Ph4JoVCKcnPYN5l9YZonXr26pxRdiQXtegpd1wEW9E+nGVS4ub2h1oJhQK1CrwsUV6kpMS8T9/e3qMKrVwfevn2DKpyOE7VAycZ+ePvZW46nZ4L3rfrchHNWQt17IS3J1pgKlYr3ZoAfgmNZZg6Hg0kJyahWnFNyUYLvQBzTsjBOZ7zXzYtsSdk8uVQI2ZHmX82c+B/q2LvIrBV1ggeityqAc5pJOnHY3zA9TPT+Bkom1QXhIkkkwDwnbnc7gjpjBhJY0gIsxGD7yr7b8/jhhPcRH4RUbd3oxNPHPaWaIXuQiOpE6I2gkNVTVIjikGkkaiFpbftJA6F8COYNXAoShC6YF2MpglfwnZBDW49zxrvAnGnzlUNrJlRtXomOpWYqzQNWLp6jnY/kJTPpguaFuWTu4x1DvOf9eWQczwy7W6usWxO5LIzTiDjF1WrsPc3E/cDt/R3vvnpiv7vl+XimLDOxJIahI4eBzEzVhVVmOi8LwReTs5FQHykCqcV71XeoN+apb9JxrYVcFqoXEhVNC1oSztn4hkoJC0XNb9DFAjT/QTE5akVYUOaS0DCABigVXRKZkVIzU8lksTn0sN/ReUuiODNpIoZg+wlZjE2YPcIeR7KErFr1Ou8DuGrekjvMcLwIToJJbp0YPlyas7UTsto51utBLE7JmiwxpaufdiA1w/WSPUO3Z5qPzGWy6w3m22l11VJjPjtww981dF4c3w14Wa8i+SugoP3y8raVHXUNCrzQ/Fw+sXnxXL3aoIUNfCq2d7RM6obrXJgXCq1krzbQyRbhbYPdgvjNPWkNQNvJXngvqX3fy2v8xYintu9cvZwsI3ZhX6wZMsW9YHutv7UKFxfK+YVJ8ov36JfctW/91kCuX/q+Fa3Y7qxs7d/uw3oPuYBP29GiYd0khNffvzLN5OWb1xb8khNdM5R+4bu21/6uc7y86l/6+jVj6tcJa7o6LvjQ+rzc1ROyXyoGyJXGvFk7dtUCWSE4fCvBbpKoFYBik8XV9gBWpyXDF5TVAd83GGGFJV5yTtr5NoHoFcCgbWytfU/tOlbQuEr7lHPNFKwBPFcm/y+gz6YB3CRejS21veeKKqgte1lqZS1jL6s5VPt9vpLOllo2yZw4hxehqkey+V/ZGG5zlKuIhAZkrYGcGCDn1yp/jf2j32IrNSZZXYP0FbarbD5JSGOQbOPiGmm66sxqQGRzINy+w55hmwuaDE8MMWOV2m1+b2KLohmgtjauAKBc7g/u5ey8Alhu+x5v0UIrJW2PXK9b2079y+e37ZKugEhRbfP7OsNfJxy++8f6jI2JaODGCs+ANmasNIYXgKDFkcngs41fIplnUnmPj5+wLIkpJbJGvKzTQzFGDwWVzpiRpVCoRCkErUTnKT6bp4HafL20ailBm2x2BQ0aI8Mq6tmgSkuh4BhToo8DOUdymoy+3dgXuIrU0nxMklXVqiZty7yl9v81X37ITMcvQStzWnj70Sd4qXz48kf83u86/sP/OtIPPb/z/bdMp4nhduDmpuf5tDSGlXI6n7jvb6lLxd11FFGO04hDSBLwfU/E6mMWmrShtg1r6zpVm5dEexYSCjjfpihBNVM0k4sBBLbON7P4Vm1MfTULOqfgIYZWNSYvlJp5evyan/38hxzuDpAW3NORPJ8Y9rc4N+C87Qm0Zva7PT/62U95enpmwfOP7u95dbjhfP+GH+Yf8qMf/g2//fk9/7f/62/y4Zuf89/+m3/F+OZP6PefmaRHM1p2/M3DLU/TxL2M9D7zvVfKb7694a/eF5xv/bFk63cNWK+lsSL8mVvtyR8OlNeJ8AnI+wPunKi3RxBHQMiy4N5U4viaoXwf3X8gyTtQsam8ZYq98+CbJ6CzjJwPtq44B737NRjHLSGRywUNUa3mndTWXVWTo0rw9LsBFauoVmpt7ByroLUm4kQ8qSbyOBNz3O6ZyWEz52mxcuvUZtidyTUzpxkVTLZXIC2ZUjJVlWG3Z5kXQuzMO6xkcjZD7mHoiaFjaRXVckoszhgzaTHgoB86jqcj8zIb0CDC8XRmvzugtVJKYRoXYtdxOAyUnEmp0g8Dx+ORZZ7w3taQUxoREQ6HA0rleHymFKXvd9ze3pg3SrZqiCpq7cSTc8F5S4bshh4tyv3rV4jAu2++NuDZwS4GDg14WtJCrsUM0vOMqtL1Ee8i4Jnn0SrNhQ4XhDmNnMYjIRhrc55nAJaU7LNdT2rMoaieaZztGYrj9vYWcY4P7z9wGsvGEAorA7TOxGD7BcXYV85BzpndrmcYDgQfG0BmPIeqpVXSFLzvuL/tGecjabHKd+fTzNdfvSPnyvk0UXLhfDqTshkRd0NEAe89wzDYuK7KNJ7JxSqBrommrfKsE0IMzPNCDD2lVvreI2Jyy/1uxzja+UuppFzoOzMjLjVT1ADZnBbG/KtJdf6hDkGJrkPcwDjOJn0sI0imyMLzU6IkAZlxXZMAp4yrgZQh9IEqEe8ceU44FwjirUqrC8QwmK9Y59jFDucdc3om7Dw5VwYGBnpSH6l5IeeKxEAXA6pqftAVgoOsiaQLogFa8qhv/aligGB2SioFkrFr+hDxvTJLoXgIWdECNS8gZhUz5YQvYiwuVxAtdF1P7wbz9PIQvVWMmxKkUlnSmVQmTg/v6IcePyg5eZas3L6543x+ps4zcTdQnDJPE0E8sXbsZMCnzBCE0EVyHukikM6EJMRBybGQFCRHokS0JqY8tXjQ5tkuCDoE0ryYgiMIJVfzLqsQfaC6HUUDS5roakfwl6Q24nGh4lGCRGouqC62RxXzwK0ZoPmZiRCJqCTmfKakc4tAPNI5YueMVb0WevCO0DzcFk1UFoITonfNmrYzCWW2MdO7gPSC7h0lBFgEV80v17lCdWoFyLIBPa4IGhJWssKM/TvnCNUTwo5cEzUrroJ62ycXBY/nze0NX6cz6kFzZVkWxDlCcNQ2ZgfxxPr37vG0ogn6rX36twKYa8zi7/r56pSr/MdQ/TXQubx/O3sr56TyMvjwvxCJvPy9bfrMu8a3WLViezvLF2+xkVGNW7BtSY8mC1gve4t1Nzhl80tRpQVNzZegAV/ryV8yido1/cIca0HUKslb71GF1UO2ASZ1e/813UJXxEXWoH67yQCbL0/dbvILOOfFPfyFn1+87wp8umr79de9gDN0ZSRdPlC372/Bt1wBRqpX57iCDrdLvW6TvnjNMnHWnm8DTb/sc7/4/7/Ipruc+xdu2q/fsbFg1r8v/V/aA6jVzIQvgNsFNLJMfiXUxmxbDbob0CCY9EKdoKVVpYMm65MNeV9fFWnjfpWKbaDUChu1zXlVWjTcSEGNjVUVdS3GtS9vnmfmEbX6ltlXrL5m7dortnm3CaIRkdSA27WDNvZHSoVSoBRt7EXXAKF1HBgtujaQxiSiTfJUKsU136RaWGVvxXi+zUjdfFKkmYn6xh7yGGPMiUmMpLG6QHEbsNaA7GqSprUy34qpSAt+BaAY3LjOexeGIcbOELsnbpUCIpaJsadsf5zp9xFp4JZrEj1rM26tRtdAId/6zdqOtQ+ufk/r85C1TzjzvpEGOrX3uVXtuI759snraWg9l4plpn+h728MulWQ9i0A7Lt8aAM5G0X6sq5Yv1YPKpbdRIWKoxShUIhiMsS6LGT9Gk9CqictM1oyBavQ06kSS2UBzjW3+7R60gi+JtSZMWpByC07abKLYH3eFZRAriYFlQrdRrPzOEorFT4zTkLVHiFT8rxJJRVnGXtTILCkwpKxYLp0EP4pp/yFVYmqpVWJCuz6Pc8fviHWBz7/6Gf8P//6gTevPuHmJjCNmXGcONwM7I8LIUY+fDhStFDHhIgFmaVUxmnmZn8A15GK0fJzruAi1XsL7Mng4gY2qTjEeWq1IIs2R2g17xwtBlznICzjRFkqVlPBQKnqiplPhw7Xd/SdgOaWIXOkpfLu63ccHx/Y3+1gGslM9Gmm391yd/uW2HdMxzOpjDw+nfny3Xv+6Hvf59XHnxM088nH9xz6jpAWfvd3PuFf/OOJ0ydHXPeb/NkP90xhoI9nYu6ZqXw13vLX75/5F1/0TGnCy5nffD3w/vSGcxotieAKeLtuVJCIselEocuIS5SHO8JnM9zu0MfAfjggvbEj+mAAHDtHNwd0/IxhuEMby05jNR8aApprS+B5IKHBJCBoJrnvvsdTrZVca6teZBtA8zZL5FzaelooJVNQTg+PIGaMnVJmPI/klCxl5BSVTEoFJ97GZ7CAv+TMNGbm2ZNLYUmpMYByk0N1iMD5fLTlL1dyTnRdoOt6Ss4sy2LMQrXX724OAORcSHXh5u6GnArLPFNzZp5nk0eKsCwzfd/Z9TXJmrGrhdB16JIQZxWepvFsZcTPJpXrO/NVUmjm2KUxGSrjOJlpujfp2MOHB6Z55vb2lhAcIQbOp5GSM4qQl4WKrdvn04k8n/HRExCGLraS7cL7b57IeQFx7G52dH3H7hCJMdD3BkqVooTouXVmAyChMgxdq96neO8N6J0TX3/9jpQSIQzshxu8hw8fHjifT7x+/ZrgI89PT1aMBGPExBiZpsnmqP2Ow2FH7GyueX4+s98f6LqO0/HMeZxws93TnBNdHwleiLGj2w2MYyLlmWWZSEtGamf7l3zi+HwiZ/OfLFoQzLT5wVf2+57YGeBUSktkqzLsduz9jvH4ocVUZobsfGCZM30/kLP1sRg8y5Lt3ki0cu0CwXnSnNBhIGfFO7H+NnSUpZCWTE7zP8i4/FUPodCpFc+o3uN6oaQZrQu5JHoPoR+Y84jXDjpH7HpkDIQpcX4846MjTwveCSlnUsl0YbB1NlXqnCkCnRMoSqkRnx1d8AzeE51ZOEzZQEgnFd/5Fn9WgrNk4MICsSK5IkkJzhOiIy2KU2dsqTQThh6VQEAw37JK9A3IksicbD3z2fYRvnNo7BgXRWrhNg6kxYDI4/GEc54alIVKNxz47De/4N2HD3x4947np5nHhyOHm4G3H33Ch8cRvNLvBvKpMJ0KH332Mc+cKLlSKeQp8fz118gyc3i1p1ar3JYZGXPh0O2RAIHe5F/i0byAVmpxVDGwZplPlJoo6YSQoHg0VzrX0XnPnCcyBox2IRDN4BEnmYoxEzVVfBTEFxvzDkSMFYkGPJ35pwUlTTNlSZymM8qMd8YOjKGn+Ej//+Puv74lx7L0TvC3jwBgZle4CI/MSFW62ENVZA/XzJo1q/tl/u95m8Xu6Zpmk1Uku1hkVcoQrq40gzhiz8M+MLPr7pkVJZqMbGR63HvNYAAMwDk4+zuf2ESCV8axUL2zc1sVfKK6xSYiMvTOWaKdWm2iHnwMuGim4eIDOSmhavPNVUpRYtxZuIovjRBS0Sy44E3qiUOcTSw6rUCgOAOU5mx1hFcFKdzevzGmm0SSZLq4PZI5EgXU4wW8/wf2eDIq/ertwtmAfwU23JPZYznVd8ff1+G91WpPAR1EKMcodTPuNFp+yyhrsrTaCiMaYPEU3DoHx6wodHJaYfWOsFX0+LHSPuJFyet3qxDawWnL4i4fMbNORVuDofgkcHF+rGfvnUyEz8/myZPp9HnHE8yjURfOXVus5pbTvlYGx3H/p58Aq7n0+XU6kY7OCrEPB3OKDS7P1lkLufZlnpyHI0tBQM++mZmGrvK6VUjTACJZr8n5xT1u/glTrK6DN1bg7QRZcNzG31BYniXffczwoiWX/daUp795aQ14lY4ewRywS7BKzVasqWnxdC3Uq83s48MR3HDijDXY/mfsoFVCtzJ0mom40qStgjuydwwMWKWsbu0UZAVRaZeliVzP7wsBbca+cizE5WhKDdiNXU+sQQOyrB9RQKpAULRUoJrpaalUXY0YlVoyywIUyFVIxeS6RmuXY3sqWpvhs83St6NpKFPzXWvy2XJMrTMwyomlyzhnxorRe5u68uv5bc1aBLyc0PPzTrldx9U7/tQsm6zSWV+2NuuTFFGP21AaY+XYR5o0UxFYE73WcywNiGqaNT0Dn4xR1LZ/9gXWl46ypLPjEFkljPa9YQWl9el3bEd2vBXqiSH3Se2cnO6betYP/lYtGlEm7FmbaLbOZvjp1uQ180awgYZJXUUMENUUUTcSnCAZslYOaY+qxfLWdZJG47EobmFqdt3UQai4UHHNp0W14sTbwEWt/Sy54KJjpnkROfM/ULXZUdGKeJOl3B0SqTjMKDO3CGOgVlwN+GpSKkN7ARzV/ZiD/DPe34zkxweWkvH9luefP2eZJ96++xk/efUzev+W8XHmm2nk1TPP9jKy3ydCKby83vL11w9WVPkdD2li1+2oaSZ2W653O8iFw+FA31+xTCM1O2Kv9ALVOwPbnfWJ+IDWTKYifSA483BRFIqxBsZcmdPMkiqazTTZBZNGBQ8bIqhn6EKDlZUu9my6AbcbGA8HNjeB2/09GhzX19fM1eM3M/10QF1kKFt81/H+8YE//7f/hnB5wY9/7ye8/voXRKl8/uozXCeEAP/0T17i61v6rvAHX9zxnx+UL5ee4Cfi5Za8H3lIPf/u5wP/3asrhnrg8fFALDdc6Q95tvlXhNjjULIoIhmpgiV5Bpwz0GLZFQ4Xtzx+8zXPvv9jxnDHEJ9zdfUMGrCOZsCj1XN4eCTnkavLV3T9gKuNPYZJv8z+0jUg3WQvooX4CRbzd21JJR+Hgaeu65zxW0/9VDE/paKFlJaWcGUsvVQqiPmwmWeqo+t6uugNr4+RlG3dkmdKXkw2VrIVyEOkqmO72VJKRnsFOgQDPudpIkbPOE2owGFaeH/7YKa6wUyz8/I1DsdmGOj6jlorMXY4J/RDx2F/YMkJ1HF1dUXfe/ohctgfmGfb1ma7AQohwve+/xkpZQ77sbG+CvvDni5GNtsNh8MjIQRSnlCUEALXz54RD/b9MjP7w2KSQzW2YQyBOS3kmun7yMXljrpYkptSSCnjfc+cKy72iFi7jM6TloX7xz2qdzjn6LqOlCwpqlJx3oCTcZxZloyIgX4mBzVZ0jQmDo8jOR24vLrg+9//gmVZeHh85PmLlzzsD8zLxLDZIUDOC7vdQFpm7u4XhmFjZupdJKWlTfCZ5M+JM1Zc3+M8LMvEvH+k3D+AevpuQymOzWZLF3qWtNBFT4wdtQreQS4L3hsra3vRMQwGUN3fv6UfBna7S5aWAFhyousiBpQppRST0SnMU2K327AsI6UW+i7gnePly8/Y7Z7z+puvuLt9z2ZwXFxt2Q5blsXAymW/xxPoXYf/1LP7O7TU4ujjAOLodx2P8z1TmthuN1x2lzzcPXB5saEXJc1CypBEISdcs01Y5opqZnflwVekBhtrZvPJ6zcbuljwHvKycLXpmKeZkgq1E2bdM86FGDvmeSKIM2A3eLoYccU6l9jvSClwOVxQZALvKdg9QxvfbeOGqT5QnJK9oGrju1osWTWEnr7v0DTa8E2VVJVUMmNaqFSmfGDcT2x2G9xOqFOh0JHSxMwDl13H1csrpnJAp4UoIHlE6gOb6Hh884Yonm4YEKlc7Z6DbHi4fyBsCnHjuXt8oO+2bDdbpmXiMB7Az9SwocsDKoPV5zUzLzMikGqmUhGnLPPEYb6zZLd8oPNi46HF+D85OGAmaKULVqsXhCoe5wdECk4nNFthZMzQAWqAAt6bp5s4LKBgmVjmhTRmouvoeiVEJQZvScJZEWe2HX3nUTybPpKmA6qF4ByOSKmW2NlHpdTm3tR10HXE3jwpdVELCXAJXLHxVBCWoogbCJLNLFzAxQ6Px4vZX8w48C2SJguoQ2XGuQ6KhUCot3ulw8zHffDGDC2KCwOdj1SpIIllOXyrdvStgSd3nBnXE9Kxzjgf33tanH/q9/M1Tp+1P2qLil7j0eXDjTxZVmBh/fuImrR3PwE4nBdZn1iOMM4Rvzor7I7AyK87nnMI6ryge1IPfvCBlRPhWDn752Kg9ZBXDyddD+AI/MlH29eV/bDKSvRkCH9OZDoezZP3PvZK+fRz4OmLT8CtFSg4O/9Pv78e5XjaQKx1/0+Aqid7Wn1ZTmDWad9nx6JHzPF0Do6ftiL4YzBLz7Z58sc6N8c/rX1+NL+NS/Nh0TMwpx7n69s6q3xnLfTPC/+T59YJ6GttrRUCa09wul/dCt0Yo2rdQ8OV8HIEp87TIOV4s2oDIj5o3yvIqhhzSW2b5s9wAjKRRixWzGiPxpJqXg1SFfVCSQ1gq0ZJz83YEbW59VyFw2xJXqpKzmqmmK2T8kFbvHBt/juFYxtwq3m6sbFysWLLJFMOrXIctHpfbOaysSoUT+8iIud3uj3gViaQcvJYOhZmx3agT/+t8oxmBnrqZM9PPpiU0P44momvjCTO/nbrPdJAKHGoc2fbl7Puc2Uvtd7rrJ2uINRpO6fnwmrWrscNnbV5kaOH38nsfv2o3SMi0owZlYI2gEYa1vbdHug+WVwxz6Z2/OKMWq1YSpKrxjhyGCvPiZK1GNsw99j1WBDAqcO5C2odKHVPEQM+nUSoFS+lecYUpG1/TVLtS2aUSidQfLAwOxEzytSKR8hZ2QSHFoVSGzBVjKVRK1IzY60m31BHXpQ0L9SqzZMlUHVGm59Jza5NAF0z89/z/nHD7f4dZTlQZuXli1cMQ8+br35B9K95/uxrDrcLvcDdODPvKz/48RVdb0lfcVv53mcDUgtv9wc6Hylk7vaFLsPglCqVIB14z34ZGXDEEMEvqESyVIJm8J6srrEEbYbZyGlyDK/IpXJIow3MukgcOqL3CMUAvbmgKVHnwl4X8pzYdAOLTozxkdAP4AOPemN96i7y5S/e8uzVO64+u2Z7dcWw/QznA53CX/zlX6Ex8r3Pryhl5v3br1jGxPzwnujgRz9+zj/+o0JNd/R9x+fXI3/4/C337z6nxAGqst3uID3yy3cXvBkP/OQ6MmehyMxnu9fczwcu+muSBgZpj4s2pqntISCyZQiVXdgRsmP//j27iyum21uW0PHs2Uuqs/vMqU26hRB5uFP2t+/h+hnDsENcQFpmY6lNUNwKbwA08PGU3XdvqSUbE4zAyoI3maZ9p1ql+TcJXT+gXWCaZ5zzqCaMA6Bm1pvT0U8l5UIqI1kXdpc7SjIGVWkyRYclHeWcUSyJa+g7uhjMDJhMSgnB/FZidDgfeP7yGbd3t4xTJiVhGidqNBPfWisqBoL5aqy0XAp5bgBFM4dXFR73j9zeL2au7Y1V1feRvu/YHw4cDiPLMtPFjufPrxmnA9OY2fQDQzcYANlkZh5HjJHDfs+7cSL4nsurK8bpYNYYVc1vKniWNDMvyaTupZCXBYr5CmVtHllS8V1H0Wypf2PiML0DHF2IbLcD87KQsrG0XPA4HD54YojUKI31kBtr0hNCR7m9Z5knghe6vmMcJ9JSCMHz7NkVVS1lU7Vw2D/inbRJLFNR1KSk5cDFpTGiutg1IDERghCCcDiYJDEG31hEHddXW1IuTOPIbjfYuKdmnl1v+Ozzz9huLpjGxO3dO/aHGUfi4nLDdrvl9uaWx8PINM0m58TkgtMhEboNSzIfHRFH8N4SrjBlyOPjnmHTo1ooKgybK66evWKZE+Iqwy7SBWEazRw/+Ih3W9KyZxpHXN/ktN/hpbhIkUBZEpoXllooYhK0lApd35NJZK342JtlRSlQKzF6dhfX3D/eUzSDdki1Z5+oGbj7VdJVqgVPaKXkpgSQjBYlL60G9BXnLaVQZJ2sr4gvdBH6GPAosYuUkklF0Kz0bdIyhMCSZ/puRyl2vaMbzEqCiiPRhx51hUnN7yvlzJgTKUOMW+b5QJkrohFVk/dJCCgQ4oacZ96/+YboAxHBbzZsQk8pjzw+3uP8wG7X0XUbwJNqgeC5eHHFYZnoJLDZDixi/lkSbY7CxTU9r7O0+CWTkuKKUpvvG2KqgzKPpDyiLiPe4SVQ6mRhFdGTl4rmSgC2mA/o4gtVPLkKpZrXEuIJvrNE1VqpOVEoSBiQUgir52ZRNAEIm4sNEaGLBRl6xAk1W2qfZwM4QqfM80wpleCMnVSyR6oQXKawJ7tA7DeUGvD9Bte3pDqxcW6p2QS54gnqrB+UCRcqUQZqtkCVuhRCNDajd47g1EzmGyM+J8MLqpuQ0BPF2b1ajM1FTbiQkWhjo9rSER3m+UT9dpDSt2c8naNATcq1eo/87ZcPC/fGgDh7fZ0V+ps2f+4F9eG67ghLrP/9mwADPYJNx080+ZGymv/+wxUqR7BGFZNLrAbOH3+PwrFmtNeOcdknQGkFj74dLPJ0LWmFB/pEyPcbgL+nm1r3Wj+x/hHSOGF6RxDtCFJ8JIX7xHY+ksAdYT7OII+PDvr8nd/8NU6g0/9ZFzvfzTPoyE57eu6NdcLpYooCGSHaLBurXHX1FVo/b9urDQhw4kwa24CFFadZWURPQAnRth27Wo6V0ecawLSCCxxBAwNZagM7rf+oKvh17E5t7CqHOivGjRTXGDXaZIXZwO7aAKdcLQ2yFN/avTIlZT93lKTGcsCRihjDyQVYlCCWwFa14OAs0Q/MALyl/tRqrKcVSEXsWJ099GIQaiygFkubqz3U7DsGxJ/AZcOaTq1gvcgnXyZY/alWWfM5dnPep2mLf3dipoHuCTBlezdwRyzFxkk7liatWz2v5OQBcexJ5Qgvckq0e/o9TAu8/jtvw2f35hN07KwPXY/yrH/+sB2Xs/u81trW/yjf8zu7WDMxpmhtxv3GMvMmVaKY50RjztTqQaMZjotAnXHVZLBFAi6+pCZFSkGqkpwSUbJX8wXwzgp8BXM2MDxVgjGmXPQG0lYlCBQpJBydRPOFV2M5FTHgyQtIA1mphbwkxmKehInEUibMrlOostg2KmiTfIjrWfRHvJu+x9vbR6b9I4dxZAg7thcbxvGRx7uv+MmrN/TuDu+V//7/9j3+3/+fRFoKv/jVO159fsXFpkd0xl8oL/SCHCqv392z226Z5oKWiXjRoU4Jmnn9+ht6F3l+fYFPEz5syWSc2qyoJYQWxC3E0gOF6lf2Z7UBmRa0JggB1/cGRKfEMk3IkmEGgie6wNBd4DtP30dCjMSuI8ZItx0YdgPDtqd486EYD3fs72d8LDzePxiQjudP/6f/iR/90T9iSgI184d/+Ecc7h/4L//x3zGEyP/4P/4unz+bqGPG49n1md/7/Iaf7W/Yl884zInddkM5TCxzz1+/dvzOqwuQW6QErnYLN/u/Ji0vkC6YByCcDdpO/XsVj4+OFz/4CeXLnzEtiYur59zc3FAqXL94cTasCsTQ8ez5Z9zfvOPx7i2lJHa7ZyDmC9bmK9DGDlr9+cpvg8cTBoKvCY7rc6/WZD9phq0IWjNpzjw+PjJPE5WCD54yZ5OQlWLPDudMPhY8TjyP+xmTerbnbpuhN8JY+59Uis5My4iI+TN674wNo8oyL+y2G3wQPv/8JdOysN+P3N5USla224GcDVRCHEvOdD5Ysl63oZTCOM9M08x2M9gMvxhbJOVCcJF5MalW120Yhi05mdn4fr9nmidSSuSipLlQ7/dsN5Yml7Py8HBoAE3BuUBKifEw4ZyjlEquCVczuVb6bqBzcPHsGZVqYFAXWHJmP004EbbRUTVw/zgTgif2ym57TXBmyi4ixGhsH5M9LnSxO5q+u2bLYaEsjpQOQKEfhC4GhsHi0XO2pLOUEvvDAxeX12beXGZLtVNh63u860DteqfFwghU4e7uzhhlIZJSbpO3J7WC94Flqez3D/S9ma/3cSD0sL3o2W07NtuAuMo4RWq9YLvd4nwg+o5pszCnbF5Rwbwq5zmZXHJO7bFrE3K1tpqBivMW715LIXYB7wK7i2tUAvePdyxZEQl0wwbvOw6HmS5WPvvsc7qu5+3r1xaO0H03bId/3ZLmmc5FlpKZpoUqShc6fFJLJgsdpQjiImGzIS8LQdp9US0FzkWIdATpqeqQ1laXkhHNDL2Q5oUgW5zzTGVms7OE1ZwyWgN97Ag1slRHddWsGhBjmgaPC8VAjDyT64QLEIIzby3ncc0qQ6ugOeOKAVGRQEZREmRlf/uAOM/iLF2vNG/hUhSpnj5ewLKgZSIkY9H4zo41qsNXz35ceFge6YcNl88/Y3ux4/E+I2Uhrsz6mhkuLpjvH7i/v+Hy2SW7IRJ9JMZICJF+0xE3gSH0yKxE71DX0huZTN3kFA3GstQqLHlGc6KUCeeVaakmIlAhpZGiAe83BK2IGvtRi8NrRgR8dHZdqk2oZhy1VJxkPBY4sOQDQgQ6aqqUMhPNT5++D2ylA3WkWhAvVH1kiAEkkoApV5w3tmXwvolOHKkoMQTwlSpWU3Qh4kJP9YYKlKIgnura868065IiFn5YC9VZAmjVakzsCsFFKAIkolgyapYZFzKq5pFl+XgY3hOVtGQzM3dW6yiVrAs5RaKLxK6nlm8XDvCtW/kJBFp9QPh2oASfwGpa0fv0/fPh/6ky+hT4pGdAx8rw+dShHFlTx23/zcZXp63JJz7/LZe/MxZ3Kq5hBWMAlSdHvnJUTh9d4YOPL8onQZdfA6ysn1znHFaexEeH+emDB56e4XI8olbscQYW6fnZ/fuUfvLk9/N7xTVTK9WnX/lDVtXpjeN/fsM+/s+wtDvmCHxwOkFi7EZX5ZSm+NG/Bg1IAw9aoVFrWTdhg1nkmJJlTbohurUewabzdr4CI6JKldN9uA6YxclTFHP9VeBoVX40XOUo2TPDcAOQajMAlwae5OrJRSnqyAXGLByKR6t55CT1oJC0ss/KMlucbHQmE81ko62qEEXwzZTPU402Ls3nRhSLWa1NRmBSitrYWCaTrYRgqSTOBYJvs/t6Lg87azV6dgJQA4zOgZf15xFM/RjcPcOgGkgmZ/8MBDJ5nhUYtETENdkQGhvWmb/N0XB8vTeOwFNLUjwDvKSxlZxbGU4NnDqCVE+P8xxYPrbg0237Ucs9MhzX+7gBrWvyIOvEwm8J9GQDK5qlU5O+sZrdB0OF8EgzF9ba4WSL4wE0oc4MxrUqpaWqLPOdnZ9W7GYt7fkqOC1UAlWtqDAJaWTWAj6jzpnXmwOplYBFTLuq+CCMxQCr2EBTFaF5I+OBZVlshhM1qUxJlgaJ4jFfA1VnM5zOUXjJw/T7vHufmO8fqYcRUU+/7ah14e3r11z0b3l19Q4RYx/8zo9gmUacOsbbig8j/qWwHSLiElcC2801KNzeT6RsbcTNwhACzgs6gdsGZs0wZYufFiF6McldzTgNOM0t7chjrlcmm0XNzFlLwQUzk3XFfBFcvyUODUzxDimFPphUz3ln8cxRUcnkOjKnBZaBbnvN9rKj75/ZrKuH+fGekmb+4i9+Rv/sOb/68kv++A//iF/98r+wG5/jCTx7/oqXn/X83//VNT7/DILJBUUSXzy/4w9u3/HmcMlBPM7B9XbLY1L+7OcD/+x3Zzbbnoe9GR+/vP6GL9/+lOef/xOqmkTart1xJGPJOs1QzgfHy+99n3fffE3SyvXzZ9y8+RrxcHn9AvFyZE35IDz/7AXzwSSGkzwyXGxbP2p7CI0iu4Ifq7T5u7xYn8/RM63WaiARbeaZDA1YLkVY1CRNtRZSNoN9VA1IUpN1uOpAzZi620QkWAKZ1tq274xli/ULluzW0XVmnmsBOdanxuiY5pmcM3c3yxHYKhScg80msswmESklIxJIOROCMM+Feba+JHgDpWPsLLksF/qup5RC10V8iOSkTGNCnFBKoY/2WikFNOCdp2Rj64QQuLq+Yn9w7PejpcgdwTtYlhmHMCc7R+vzvdTMbtPTeWGaD/hg3jUhRIYQjM+ZK/vHRwCCCjUlihTuZwv9WHKi74cmT3MGvmNyc5RWGFt7XcYFS5xybJ+ZdEhVmedk18hZ36BVub6+MumKD2w3O6Y5MY4Ty7TYdQrmm5lzIeeWiiaKc0KaM1otoazUjFMhdoGcF0sZlJYIiT4BzaZ5YtgOXFxsOeyNgbXZbKma8UHZXkRK3cBjNuPvUkllxodgk4HOBN5KYxr7NcmWowRTnEI00AqEq6vn7DZbVBem6Z7Hw8h22FKq8ni4x/lIGAJlzsd67ru61FIZpxEXPKHzpLwQqQRxxl7DUVPBRZNL16p48UiUJiOdUAd97PAMlvfhMjXtccFZoppX/KYnzRMyeKpk+utn5Fk53D/goyPG3nxEg5Kj4L0llYUWUlNzIoeeVB0xbiky03fSgKdAyo2ZGBx1MqNqY69XxFs4STH6INSM+MKSKiUVSs3sxxGtnssXz3Gdo8uBixiYVSiN6VtTwePp4o6UrQ+qWqglE3wPgpmiJyil8KNXn+NrJY97FqdswwAugDgkCtlXBidcbDcEMqUuzKWQE9Sy4EO2UNXS4bXDI3gySzlASeaVWNXkd7WitbRQh2oSeUnM1RPcDuKWcd7DmKlzxquiDrJzhBCo1ULHpDZ5uYOis/lAScV1nNovQq29+aFWM/4OwQBywdHH3uqturCQ7JyLb5LLSEoHeh/wbmAYtvgwYFyrioipOOjMJ1HV+iGq9empWAiFeBuPiGshRs4sGBCr22oVcik4V8jF7tmqzdIXIddCkUSMAcSTckVdxdVEJxBDDwjflrD4t4SXzTfpU13Db2Y+feDrofrxdhSOaUqsRW0rN45shyYdawXqr9/d+mZtk8LSiiortn/Tcbb//y2+26e2craRs5rmKAX5FPCzThJyDsTo8S3D/NbzuLolPV3vaMZ7Bqycsx7ODuQTx6DHzawm6Z8EnuSsCD5joXy06MpVOQd5Tser6zlqO3lyjY+rP937R9/lE9fqbO2PWDzflsn04fVeAdfffibU0bHIBm36FJRoNBeCuXY1WdKp5F9d0qwd1Xa/Cq629qwrY+lkEW7KKmMcrSCXSc60gVfnQIo25sYKFqwgYQNNqrbtyel2XWWDnEy30UpTiQFGiy3FBlFmjdHe9x4kkirsi5Cq5zF53s6BokLGkaRDsOKsaGHRhZILocXpFk3G0RHoXWMnFg9q1FekEl1FNeGbs5lald+kODb77ZwAFV/N6Fmk4IP5lphflDu2pFOv4BHnW/+wAkErOHfGRPvwvj22HyuPdb0zRFpC3UrtbrK3Bjq5BkAZW2lN8GqfWdlOLVJb1s+xpt9I67+eAsUra4e1t3cnrtvxEv6mpd2D2ra/+oSdy3ZV7T5eB/yn83gCv38bFruUrbheEUOV1hQr7tiF28Cl4BBZUE3t7imUBiY6OsblnmV+i/KKavQB1BWqeotCl0x1kZTb1alKVvs5uEKpemRnILQ27ShSTYbaFoejVsiqZswq2W69lI2yXtSKqwbKoh5E8eJIFYI4kA2Pyw/56vaCx9s70iGzTAvD9RVxu+HLr35Jnb/hd374JUO8tZh2HMiEyxmhI8bA4VD41fzA9z6/YLsNdF3CR+XH37tg13e8fn/gMC3kuZDU0YeeTa9sNhse7+7QwXOfFny19u6DJ6RkKVdeiQ5yVDN7rolO/Kkdho4YPb33iITm01YtyhqH1wK5UqWSOUAGzQFmY1LG2LFxW7puQ/CBi2FD3VTmMuNjRNXxn/7TX/HLt/f83j/+Y371+h0PD++5fv4c1+2QlOg75f/5/3jJ9569hTwTYjAGmiq7/p4//t7X/Oz9NffzC+Zl5nLbkTYb3k+v+M9vKv/0lUmeSirsdiPPpl9wuP+cYffCQHKRJiUzoNStk4zeWNrDsOGz733BuzdfUYvn2fPn3N68RnBcPX95bPceh3ew3V3jQm9sLlfp+w3irb0fwyrWEJjvPu7UWIC0QBo93huWQgfW0pxJwKoj58UkcM5T8kwtJpcr1YDgnBIiQkpWNF5eD6SSidGb9EQ9S5ktkbWxbYPz7bluwIqqcDjM1FoaCAbORZY6knNhSQVxwQrkliwJ4H20/kfMcDw6Y12pQj8MuLQ0BpJJSVSVeTFgZJomRJUYoj07hw3zshBjwAfPOFqSXewCNVdyLuwPB8ZxRKsyDBtKTUxjYRwPOHUsqVp0vDjzulIz/+07MxuumtFs0l3nLfa985GilcvtpTGoloJKBp9YkrAUe57Wau6r4zgRQgDV5pkUmBczAvYh4L0jYF5eORkDNcRA10VKhlpsbDMvM/12wzwaQOgc9L3Hh4FpWhoDzbfC2FLmfPB0naMUYzoYQ4bjdY3RTM6d2H6qU6Z5pmRjKzmvPD488vCwZzPseNzvyaVwe/feADIs4auqWLpWNpA3uIB4ZUmzhVGojRtqY+4NfY+IMM+WfLYsGe8j4zjx8HDHbndJWmB/2DOO9wSv7LZb+s0AIhzGmcOYCeqMyfsdXrqdN9N1b7JZDLJgLkpJhd5VYvNMFO+gDyZdVw8poWSqerP8dIoj48n44PDOkWrmcdyz69fnx4asyjJOuBLp6aEaOz6TcRtBKThxFvRQK7kkXJOE7nY7Qt9YuNQ2jlvtLQy8VtcRQiT7RNYF64oCzkeSG5GacTlSiwFFdTEZfnFQykLKByqVhyVTpBDCKrtzxqwJEHolpQPLNLLdbHExsuTMqJUYhMLE5trzolzw+FDZ+I4u9hQnZFHUK5qVsiRSnpjGkaVOFK+owLQckDnRxZ4+7ohuaDWKIyvmO6nVDNTrQmkJ1d5Xak1Up83xxiFDx3B1yf3NjCRACp5iASBFqGwodbbQjOoIftvMxTPBm/xWXSWLsz4cwIcWGORRtmQS4guhLIS8mJWAaySkKkgtxJgsmMR7NO4ooWN2Hl+zYYRBrNZxgqrx1NR7qgeRZsdQiwFj1caO4l17fo5m4Nm84qzvF2pp4HKNNnFWxbxza4Zg/YBWab7Odi9Vp/S9jeFL/nbj6f+GvMa12D1jqUgroP4WywqSnNCZ02vrPI60KvVs/v3vffTAxwXdOTCiH65zdoDH1dejaebhKyPkE4f3Icvp07//ZmDEnRV9Kk/XNUnSuomPoaIPDuZU+MATb571M/Z1Gq/gHxiwOZ23p0bBq+fPp5htx0L0H+hYPgS1fluWFQqsWo4+4jSABFbmjTF3hNrkYCsYWhFtWl6OqJV18EewQFaYfP2rAQEnMHn1IzoypFw7hmaXrCsmqdbJIasE1voLS1lTtLai90yeJWuqV7UHkmKD/FxhLkrOFdco4pIdVXpm9dyXwF3tuC2BtyWwaDsO39HHyNbZOakkaqxmDq6JKScEZQiOZkdI1sKcF7xmyIsVlKp4MsGdvHBYcXBpRuaCmXMXMwhMbZBcqtiD0q2W/Dbr4KQlyx17TWGN6D5hwyf4+Cm7Z12heTSInDGmzv/ZBVpT6lYm05pip2uq3Woy3kApkOO2Vl+nY6DBWW9xBJPPwKlf30I/2TE+/UWfrnYs7D4Jo5+D/L8FSzPJXycYjkFxcrrfRaAWT632TBF3QNdWIsZAzBV83CHJgS7mO4AQxQz6qx5b01FOr7XVIShDMVCh5EJxwWTggt0LYlKirAERR9AFIVPWWXInBixVgWTRvbVmlpwsEl1pEb7roNERgyfxgje33+Pdu4n5MLEs4PqO4fKSPM3cv3vDD7//K57t3qI6G5urJC4uF3ZbIc2ePnQ8TDNjqcxL4otXl7y8cvgg7K7AdwMuem5uDkxzZT/OdCGwzInYZWqBpVTSfk9JlY1zbPuIE2GzXQghNs+6ii8BfJPA4AgCXYxE5wgIeJsdRyqCgWw+O6qItfcGpHgXccOGzXbg4vKKZy9f8Ozigt1uQ+g6UlXG8sD9Yc/b12/5xfs7Ll695O3bt/zzf/kv+Xd/+q959f1XiHoGgR//eMc//aNMqI+It9lRXdP3BH7w8oE/fvWGn76L3KUtmyGw20RqveaXt5Xfv34NrqPkPVIe+cEXG376i/9Mmv6E0JtcQGsDvcUCWUxWqOQVqPY9l89eMT4+EEPP7uIZh4f3IMJm9wx1QtaVJaqoc/TbHct4YJlu2VxcIq5DpXn6abbJlG8Z5fzfcqniqGtgRzPkP6Xluva8Mu8RnDGiRHxjwFjC2uOjJX9VVUqtR2A/5co0zdaHOprk3QzI+96kbbWCSKDvBuZ54v7ulmVRysr080KMNite1Byl+qFDJDAvyrJkUAOKwVLdQnR41xOCJRvmbKbdy5wJwTHNC1oNPNlsBoIPHBqAVGqlCMgyE7qA894S+GqhNIBIiz0o94+jfV8c+8NouRYhcn1xTZpnfKmEnBuQl4FC9JGSCxS1cXaFlbm7zAvznIgx4hws88I0TsTOk5MBBM4FYyGXwjIvxK7DO0epBS0wpgnnHcE7tBTEmxSpakZqoDQ5nA/WZ5dSSCXjY8c4zjgRUk0GYAfBx54+DiiwzDNLXuj7DnFCSouBQt6bmXs2g+lMYpln5lqbb42NVQBiMF+oaZrJZaEfHEvK7LbmhVVy4XCYGDYdOZdjYEKIVhouSyF2SkoLVAg+Aq5J9x0heFLOdH1slpFCaEmB+8d7tGYe7m9Y5pFNH3CYLHGeDghK6DqWRazt/sZn/3djiUPPeD/hi40jfY3NuiFSRyEM1n6KVnSxZ5/xfgUpM513JpPSQlkejAFXhRB7BLU4e/UQzY8pLRkpHem+tKAPwXWBpObv1JXS2ME9gc4SWjUdWefOOWpZWPJC5wO10EJbnMn8ENQrxRmQ3WlHpXlDisN3kZQEXzxaC05MInZ51TFOC9P9iGrBiTAtmX63BXFoLYTYITWz20T6AaapsNttcEFZ5pm46y3QJy9sOkcuj+yudxAiXlutoAtotnZEZJ8KNVeWaQJfKGmhukpeDmiZ6WPk4uKS4J8zzwt1HtGlwqKUYjWHugLSpI9asVRZe06Jr2bqTmEzXJPrRJaCeGN++WZpgBNUCiVXXLC+zVUHVXDqKUvFO+vPqijeKZoLngBEUi54lwiGaiNSzAbBOxYvBC+oLIh0hLjFdRtCN6AUtNokP1UwZ6oCOEoLO9Ky4KqYh5r31Fqsr/QeF22CotZsSd4IvhpoRXVAj1Ia89jZvhC6ECgu2+RgMcxiVczghXkxrzmRf+BUu7/P8lG5IOt/PhaHSZsE/1ttv33oicT/iOF8CNicH9OJO/AJqOI4H/5r58XlKUz2t+80T0d3LMDQ4wl4Ou+vv2EHcrbWWmDpR+/T9rO6yny4BdGPz9W3gVQ+LunkWPAf69tPHPF6zvV4P/z65fzIzs+VnL/5m06RfowTnm/7bDWefqP1Dv314N5vCxNKWWVeaqltbdB6kridQFxRPcrWTndUA5+s1ETVpGBW1B5x13b/uuN2WMFf5LgPFXDON1CpnPUDp4G4omuSeEu3VFQENRVzO57VjDq0Y8onNmCtVC1meKpCqY4lV0sLag/m6gMTA3t2fFkHblwg9WLSmFrpfeCq69lEh+JIwViUUZSlJupiyRm7zmRPU5rRrpLmGU0HggpLyVCcacclsXVY5C2lAXH2bVb5IpgBeaqQm4dOLUqNq2rFDJnFuafA+5MrtV4M14qcwodtbM0cPPZ9qphuyrWBi+1j9XZ6wnBaf5cTCHUErVq/eAShxI6j3QGnG+XIvDoBlR/2qeu3+tTv632k9YPGXU9AM3pi7Qlykqpx9tpx+W4DyIpJ3tbJFG1FfsVSYFfpic3Nd6yyOxHMx0ltMJFU8O4CamlJOyYhAQOUoqzMppbaJh5VT6XSteICTQTxzM1zyvybWl/otNHctYHWrvUlxeJ5azVZXzVJjbpKzrNF/1YFMblfroJzFfE77h9/wrt3nunxkXnOaOjZXewIwfHNz75hM9zwxctbohtRrZQGdm8G5fMvBn7+U09azHB5TpllqXxTKr5ecv28w0ll24N7Gdl1O75+N3F7X3g4HECFdHNLF4TDpNTZcXO/p/OO7z2/ZEmV/hG2m56LTaHrB0KsxM7up+CcAdbqyEuhiqX6iQQkNG8d1yNig2ttLIcudmz7jt3zlwxD4PLCUrH6zoNUMiaJ3t/f8/7hwGOqzFUZcqLOC+5yy4/+4Pf4+V/+J7phy09+8Dn/3R91eH2DC5FA11IoBSFQVRjCzB/84DXP/tLz5vH7jEPguuuJseP9YcOb+x072eHcnpLvKfkN/+j3Lvl3f/EVofuRFffSAPBqbbA0UH31BlUEHzZsrwLLeEBEuLy45v7+DcE7us1lu4fNh48qiPcM2x3j9Mjj/Xt2F89woTuOM7SxdL/ri3kvVfTsOWfLOoZrEwci5JyNoRQ8Xbch58jNzS3Bm3l/Lh/kc4owzQlQumhy0Komd8sp4707prMty0KaJ6ZpomZjKlcU5x3jPNm+m7qg6wqoeRvlXIihI5dETiYBDJHm0zQgLpD3e+ZpZlkS+8MKOnU4Z3LAYbOh1MK4PzTDbo83+jBpyW29jhiFlBNVsj0vRRj6LfM8k5aFfjPgnePh4RFQLi4uSPeP9L15UQYnJmMRYXzcW0G8gpniSdW24ZxnnEZjHgXHUgqpGEvaRWMClGJPr3meKSFQa8W1CeOUEtoFO9+1UnMx2amrdKHHEmWbhFBAvGPYbLh7f0vFTH4lVXJOOBfwPpjxc1ro+74x3AohBjOMLxb5DmKgGia5DGLyrpIXSz1c2XVV6bpAP/QMQ0SBYbNDVbl/uCPlhZ3fsMzm4WKsmUpOUHJmcZWaoe921JyBe0pZTArdGNM5Z2IMLMsEEljySK4LYCmAOS8E7cEJaS7IVo4MLS3GtItdRGr6P7YB/j2XUhOVmQ1KVIeGHt9FBE9U8D6hUcxyQNV8kTQjXghdb2x5ChIU1znwsEyFRSt9DEQnoJ3tLNokhBfzDkplgaAMbkM+jFxse1I1GXrN9ryYa6KWYOO/DJoWxsc7e647iGoys+CF0jucCpIrmaWN0X2T17d6QZSMo+BIJaGpUKtj2AxMh0pNBs4K4H0lZ4W6mF3GNOPLQrgwUG3oBkK3YZoXasn0ww6LY+yIWEACPuEGR14WNGWTDOpIdgsiA1JMopk1IXmhloUqCZGZqguhC3z+g58g4QWvX79hvvmSlBZ0MWlqlkJ1lbpMaFpwwUPoQMwkO7EQ60KtW5wGajJZ80yx1DwqMNslcgHBUYsQQzD1QTVQmmCgj0oBXeyc4Jr/V8ATyGWiUCkKgR7vIsEXqlOCDzaJKMEmxJynqiUdKhmqQ2tYh9ttMt98vrTYGEyoRO8ojY1p62YD+n1n9YdCKUop4LUzYN9FVIwJZi4Y69jd4bSYJFwVvMkPtXbkYsxLkX9gj6f1Cfek0D++8MFKnGqLdf2zOfn28wQ9nNcftCJ4Rb/l+N7pk+fI1PrwtrLwVMTZoZwdnLTid7UTaTNqqyDkBAGt27aHem0spGMa+IfyL7f+7ZoZs7SBxXGNp+fnnCmzDtLO3jfp0Vo6rwX4Knc52y+r9EuO/1uP+zfHhX8scVTgUx8R+eDy8mvWPd4PcpRa2SrFQKWVNaOn/buzbZR23ddTcyTAcLq+Kzj38a7lA+TrtM5TeaENTE8vreKlM6aOSJN6teP5YHvrq8f1z/bzWwM+KUdqvzbWTW1gUG2afWmx6IjHqxX3dU1oQpGqIBZjbdtafX7aDpr5pN0P9XRnVrtfj2dKOYLFZg1+Avm02OC8Nl8nu1ZNTlT54Lo5e4CpyQjNS8yor1oqRa2vqTimAuNkiL4PgaI9o99xEy65p0fFsROaxMAGvKENhCcVlqDm4SDKnBJTqIw5sw2OjsKUPUgiN9Pt6nujxM8zohOuFnq0PfzNx0ZUzd8EzmRpJrcoVclFyVXwFcSrddpyOonWn1WbzV0vmF0FcCZ1slVWitupz1plwdZPy9mGW38tK/flDHhi7Y+b5G71btJzIGcFoTgWm2eX/ePlA9agfGI95dSmV38ohA/khO0eazKW1ehe2nPj+Kxp98+pLf8WlK1aUHGoFLTJJKUZZTopFPXUIqh3UAMmtkvWnkNLYWzXS7WQljdom+2TWlAxwKg4qDnhCTj1JM1UJ/jmv0Qzy+6c3U9VW2qjKhmaDNUkV4tUVCM9NqRVCt41PwLEJERlZkkTqa407mxzxLLQh51J7N58zvubB+ZpoZTAdttzeXnB7dt3PNx9zR/+3luut3f27BRwmilAcIXra0f1lcM80cUNQz9wGGemIvz0q3u27xy/95NrHJU+KPLM830x1sHb93u2246u75gPCZHMy1ev6PoLHu7vmBdls9nRbTfMJL7+xRt2fcf2IrIbOrbbgc4HlvnAXB0BxQXzuAl+MGmRCMElQujxwdEPAXWR7dARHDz77JJSK0udeXf7FduLS8JmxzwlHg97/uzP/hO3s/Lm3WsOj295cf2KECt//Zf/if7ZZ1y8eAXTPb/7Y+FP/sVA2f8S576PC9Huq6o4Z8VBKhMvt2/5Ry9n/v0vAunqisk7Yuc5lIFf3j/nd3YX4O/AdYSauNq85QefXfDNw2dsd5c281qtjVVf8XkFoxXEglI0eEQdnTiYhGU+0Pcb3r39kpcvf0h3cdVSQmlN0zzvhu0FpUTGx1uGzQVhc8nqH2cJW9/tpSyz9UvSnsVn761MmaIYQ0xscsY7a685TZZQ1nxSVlDB+2gAX0n03YUxghvgnnKGYgykkq3HE1fJKeEksOkvkMEAlVxtvXlJBqw4b8/BeaIUYzf1XUvOdMpus8MFpWrCOWG/H0EyKS2NXaAEH3Gda95NmXmcGosSNrue4CPjuFAKdHHgYdxjfUpubVnp+4hq5XA4NDaV3RRLNv+SqkrOmcNoke9OOmqd6WJkGSdEjUE4zQvX11ccxpEpF15cXzGNE1OaqaUyzxMChBi4urwkV/NmWqefSykMg8Wmq/ekeWFZ1uIs4pxjnmdiiHjvKCmTtFj0OpnQxTY+NtlprUqIHd47cjNc9z6gNIYR63jAExory61pt2rsM2kjoxACwzBQqnmHCZklLcd6aGXA5gQh2v1yeXnFMk/UPNN1NlFxc3NLToVlKW28nREX6ELfxmuOLnbkbGb4pRQriqtdg1Iy2ZXm+1SZl0oMwdIcNXKxuWCa5yOLa9tvqDq2/fmjL+t3ddmPE92mo3OevkRyWRngldAFpjQTnY2HczErhFyMGXPyphO6CHNdKFKQaM/UaUmA0PcD83yg8w7nQbBt+F5MekbGuYDLnr725tvTRSQ4qnq0BLyLbMLAEAKHcWIYOpt4qqClgcxUSkpEF8zlRhxLNS+mJS8UWVBVYuwJw5Z5LpQ2rnfOcXG5xaMMcSB0HVNZeP/+nRnrSyF2HoqSDwuxH4jDDif2vLvY9AxuC14Iux0uL1ArWkeKFlKtOMJx/KYqzdjdgy5oeaBqZk5q4RVdpFTYbj/jh7/zh/jhFe8fHhmnye5VpxQqS0mUacGBebNWpaZE320QjVBg6KOxGjWR00QhUbRQasIJBhxWB3THmrRUxbsKUvHRfPskmF9WzY3NJDTQxvq2GCMaPJoqUnsgojLTxeZ76iB0A34Y0AxScmO3RavHKFQSvlact0l9IaLBWT+cFzyhTRpDEIAC2eFctOeQKqqDTWQLLDo2aV4xn76CTXZ6QUMFTWgxqacP2oJhBO8HcsqfIPB8evn2qXY8LUmOf+sHpcrK1lFpYA84XcGiUwnijgjW2T5Uj4WKrBFoDTA6xXA33wDWnWsDSE6Fx9HMeN0ODUQ5A8OkgUknL6xTKp6Tk0zveDysddnTcsitM8AY4W010vy12M/ZV3anwzz7wIdFkHmTlA8+bMd2KgTX91T1zN+mpaMoH9Z1pxXaeV7P2YfmxPLB9/31mNb5G2cn+gggnf44He96N5yuka3bPqqncvX87Ghb6elZOn6V4ysnX6f1U2fJh8cCdPWbWr//02M4QU1nhsa/tYscGYValVrqWefTztOqc2vrgzTrp7Wgxwa1VFyx2WyjVRSTsDUkSav5OtEwgcrp4hhNuzGYquK9gUq0mUEzTLboaHXeZhwxeVoFAk3+g0dxti+a70cJpOwpKTXTZWz2TpU5eR5G4d2jcKiCHzrYbli6Cx66DSFGrpxnAMZceZBEqcqXc8WlNphqFOVU4f1cGKtjrso4KlfB8zY5+hro1DOESNDKqOYF4asgqdBrBmnafgdempeDgyIC6o8AW1IhYBKfWBQNNovtG+BS9bxPbUwYJ+ZlhRUmSvPZwe7mI8R3BJVgBYSt7zUWmbSobuFMNnf+v6c0t1PX5Swl46znPLsFPwVAKWuE+NqvPWlp7aG99sVHz5ynGzltrYFOnINObXGY8Ov8Dv9tWVQLtXqj9q8zKFo45cFaG63ZrntwGVftfjKD0ArJzIVzyeRlRjRQayQLVB9wYlIVcVBcQbTQqydVG6wu2RF8xldPksLkGougWt+h3lwvQJhrBucZS2V17nKAUxuYpZwt5alJSbVaQY6ugygBfc5Xb37I128OjIcDaVG6fmDY7UjTxO3XX/Ps6j0/+vwGryNFxIA4FKojyAVf/fKe0H+BTAnBmFYhCOM00oeO1/eJ/LP3fP/lM64vA14yl1cdIfZE5/jy3R0SApttz9BteXP7nugDV5cbvMDd4Y63v/w524sLogs8zAuzKr98d08XHLvQseQZ5zu2ITIMPbGbCP2CD8Z2iH6g321xnePlcMHV80scZl77cLgjYayFx/s9h2++4e7+gd3VM37+059D11M08M//6T/mz/9//wt/9m//lH/yL/4Jr7/8in/1ox8xvvuKH/7gGf/D//CSH7+65U0KzHNh6C5ZzazLkd0qSBn5nVcTz2TLePghm6E3D6Is/MU3gfhSedn3OH9JCAfStOcnX9zz+vYXlPKPjOmo1YzXceaP1/p7r47W1VEUJHTEy4Butty8e83l5QtKmSizJ8YBj5CCM3C+QnXR0tOq4zA90Imj6zd4lKT5v0Wz/Fst6vxx/LJ6La59WVEz7a5A7HtyKkxzMuNcBzlX5iWTM5SsLDnhvMP7cCrY9RT2sIzG4ilLNll6Yzj3XUfRhBRjqpRsYwFLqyp0XXdc13thWRKqmWWBGDdmco2QU4ElgZTGqhnwXk2mVqUdF1xdXXJ7+4iNApR5mkjZwKrslWVJluAYIs9fXKFaGacD3omlgAHBecYycXX5jMf9gzFnssnxQjCzdOccWirXlztK7eiCI7VEtof9SOh67h4PpJIYtlvevH8HakDMOI1cbLcE78g1sx/3UB1dt2HOmZTMcH2eJ7qu4/r6CifQdY7NZgAxsGi76833LlsR6lYzYhyx71iWTFoyDw8PvHh+xWGeQCuxOwWDpJQRcQzDgBPHfr+n63uqZmJnANeqmjf/L7ufxnFshuLhOOlSa6GUGed2HPYFaQbBlgbp6PsN07xv13whhsD+8cA8J7z3XF4ODINjM3icBIrOBO/Nq0armd6nSoy+gXCOWgxwFBFqMca39zTzYsd2uyUlA09Kmem6Ht1C56PdT9/hxefIlGb6y4G4UToXGB9nxAtuo/TbLV1xRD+QgpLqyCKPqMLVxUtUA+N4x5wOxC7YpHsubGJFdoH9PtH7C4Qtgyi4GbxSs6MkUDcTdoB6lpRxudIHh3eWHite8CEQolLdzDhN9NsLJHiIPdJtUHWWyugC0UW7X4snV0WK4krFFyGpJye1dFuZ2FzAbrfj8W5PrSac7mPk+mqDuoCrPe/f3ZOWyuY68PzzF6RJqKNj05k5fe8dQ9cDjqhdG7ksOJ+ZpluKOBYs6EfztGbpUlKAYvJT72ZcXcg1mfm466B4dpsrXn32Q168ek5igFzxyZIWZ4xdNPSOkoVcAs5FqhrAWoHoPf3Qs+muGTZX3O3fAxm1CAI84KUzNuOsgKfkSvUJ6khwgmqij4Heb3EuIrIhu55cHxFXcLJAtUlyJwPkTBCjijipqHeoT0io9GFgGHqbGAzmIaZ0qOuoMlOYqTrjgnlHTQelk57oaR6IvtkfBCpC0kJ0EVccpTqqdghKTcYAmOQAQwuRWSqqNjmkxXwo8zISnUMYUGfP8aDV0v5cJpeZ5mj1Ny5/P6ndWpyfcKUTALTWr2KeB6fy5Ax2+GjUfwIJ1pl4pwYgGJiyFhK64gQcHUXOtrVG7DrRJ68flSAoTkxKdA7anACpxkI4B6vcCSY5buv4nQC1NJcjmvRr9II2y7UO8vQjr6UPzwasUhh58sbqX4PqmamyvfkELPok6PThPk6Dzr9pcbREFs5MyPUEydgr554/f9Py69Z6+rphfvrxe3r2SwNIdGXLnQ7oDEhaATU5Hvdvwgk/OqojkPXbu6wMraptYFJrAygU8TZ77Bp1kzM2lPkrSKPhWhvz1cw8V+uE4E1kIxRqWeE+LGGnwHq2V98Z28cKr2Zjc6hh+WA07Lq2STE/3oo0OZWjoKg4SvUUPKUI8wLTWMjJfKAs5QvGVLkbC28PmTdTxO0Cm64jbDYM3cB1iESFJSmHAnNxHIryZc485sL3+o7vR2ECvp6FL2fHQGUbArcp27G5wG2q+FK4Do7BVRYJEHqMIKJ0eSKu2iQxc0BxJjn0zhkl2ntWb6yiq7hKWA2/tSo4RbXF6B7lpxzZhSdnI+vIVBwrI8wfO+hVbCesXll2/c4ZTqeOcJXVrel1R7ByRRi1MeLcWd977LdP/cWT+/H4n1NPtLZR1ltmbcfrHaUfb+e8Fa8AlRw/Y2/Xs9/1b+ocv2OLEFjN6VfWkj13s4XPaLWku0ZsU3UG5PhCxbf51oJ6pdYHcllINYCY+emYHKHzBAdztjMVYm2+CIGgNDBB7LklkPCotKQoaR5kKlTN1m6rI4rJQ4I241saJVwXPDaTXrKad0A27rJ0Sohb3t79iC+/jjw+3pFyoarQ9T2hC9y+fkMq9/yLP7pl4w+Yb4PNBFotJmg94JzycH/AB0uVmsdEzQubfsPDYcQR0cXx+u3EmBwvnm3ppHDRCz/8fEvfOV7fPDJq5jBV5qWQ3EwOJhXe9JHLi55+s+Vq94yvvvmSu/0dl5uBlGAEfNywJJtnfnicmZaZYejYBOi9A32k3ltRdvv+BvfTn/Ls2TPCJvIXf/Vz9nPi6nLDL371Fd9/9WN2F1v+889+idBxf7jj2fMNX70P/OSP/4Cv/+f/L/dvXnO/X/jzf/8f+dEXL/gX/+L3+cGLSudhux24P9xz+ewaV7yl8GBpNhRL0Np1C7/72Rv+w/6eoX/FYf9IRRgPG76OPVevlC5s0OhY9MCg73l57fnpN1c8f/V9gqh53KkltFUJiBZcLbhqMuOApYFWBVzk6sVLHu/eU/EwPhBwZtreBjvmYeHQmgj9hg7l8f49FxdXDMMO91vgLm69VwuMqOeWB+tzT1iKMt7vqa4Zd9eCVsc0p9YGnJngeneUd1l/4PAxtmS6pSWZAaosh0wpinOBq6srQqh0Q2QalUQli1BSotSCj56h7ynZjKZjjBZZXgv7/QGAzWbHMAScBOY0GuNo/4h4oe9awpHzzHPi62/eYZMghZQMLAshEIOj7xzbZzuGfsOSDuwPj5RayckMyWmpcF0YqDUzzSMpGzPk4uKCvoscDgc++97nXF5csH98NCPxlHicMk68hVlReX79jLvHA0EjeUnEaIXXPBv7a1oKXYTNZovOS/N4FDaxxwdPTskS/HxgHmdqTcTOMS8TYAV67AJlydTV60TMf6XrOjbbHd5nVCameTZw8bBnt91SSyXlbGCdSPN2imyGgRgic5qQ5smTl2xeUakwDANVlSWZhLOLA6oOlYXYOfp+yzL37LY9j4eRGIQY4bC/R7UwDBsO48iXX36Fd+Y71fWREEMzNHcWlCBmSnxxueXdu/smHTTASWjSoBCPQFjOhc51bIaNvaaZlAr3Dw9cXl1xOEygnn6I5JYWjFMo323wuLM0DZgSOYP0EWKktmdoEDOBN9+vjPdC5zeM48L9/obnz17SqbcJw6Bs+x1eHLU8MudsUs+5UPcJ+oEaMz5UttGuwVL2dEWhHyi+ECSA98zYefddYJCK8zaeBM8QN2Qxz9JCxXlHR4eUQugdZTLw+ZAmwi7iek/dQ1e3+CJMhwl1mX4bOTw8MI6jje+8Zxh6DsuBYXNBTcr11Qs2uw2FRzrp2FxtmWNGymL352bTvF2zTS4nUJ0InbKkTPGOgmdZRtBCpoHiNVJKT+cC3hmYZF5jSsqPxBjpa+HlxcBlP/B2n3i4f0cpEzSxYOcEmSd6F8EPZusuQsVqE3WQUqHvLhk2n7HvKqm8RWuPdxOqqU3WR9KcCUEJaqqORZTJKT5ES4D0xvRTHchU83FzSwNmbPpc0ZaIXfBhwUtAJaI+ItERux7FPKJwSiYjks9Srrd03QUlT9QqbDqAZP5uEphFSa7QudZGnZ2v6u07qypS7NmPV3A2MSelN1CumX0q0r63kDWCM8/KVGeq9ywLaPXUFnT0bZa/F/C0BhKdhF6n3R49XfgAwGnFjuOEzcgHKM5KDVv/ton186LiWE49BbKeHJzQxCZtUYw95VqJ1QolWeeLT+XXqV7SRnXVI4BzOg45fpcVuDiCLrKW2x+eMDl63tgn9ewIz6GbVqC1N0/ZU3bIyOlzp/3K0xNwlKSczfh/Qg5W110+OYbzo/mwWNQnJuXHr3YEHNsgsRlonstsVjBxZWA9UcId2UlP3ztPsvs0lHVesdrZOGdK2atnXlDtWO08SgPxWvG8elCocl7If7zblU31icP5ji+CUfpTqcdZzlrMS8iYC9V4RE6bTUeTSZp/8ZENsUZoZWfrenE4paXmgEppwFa7arXNwHGSwxrbsJqtkKztuVpQqNZju6u1zZiLkr3aAEzNrDPXQMLSlHCBUoUxB8YaGZdErtays8I0Z24PmXdj5e1UGcvC5888P46e512k4LidC3+xL/zVqGwlslflp6KU4PiFFv4vNbD1MAelFIcXYduZ4SpBedl57lzgMBduyZRcGEthh/I8dkQvzKNnUcdWBFw2jTpWYPQeOm/UbZGAPVyb7A6PYgywlVgpK+OMBqSogVHKmRR3ZRDJ6s1k/hCnPnZlNa1+TGvf/bSdu2Pi3dpHtffdqU+2xn3esM8FlCdw+2OPpTVg4bj70ybknG243hO/rsg878PWQAEwlp7dgyv4ry2p6OSL991eKooGA1TscSbQ4nRNax8pUs1HABCXKU7NkytXcEp1ZpKZl1sonkBs6sxCRFqKojHuzNzT+sXSJLPOFYo6hErQSqcLixN09RxD6RS8VqoowUW0BFxry1oz4jy1mNzOuwjqLC0LkwGhNkjaH77Pz375nPv7PWXO1JxxoWN7MTA/PnB/c8MPPn/PD1/eUjWZXxG0wtzifpdy4IufbPjLny2oKI/znZnfqrCkzNXFBTllRirXnfD+dmGaCp8969l0lW7T8yoMdL3ny28eeH1zi4rH9Y6dbAgC+zkjrqPOC5dfOMZxYHyEF5c73u0fudvf88UX30eZOBwOuE3kYrMhl0oqjoura+7vHsA5dEyMWhiXkTc3e/phQAuEiyvmmwOPk/k4ffPXP+fLb77hT/6vf8IPPntJWWZ+9pd/yU9+9AXjfgQ2XFxv+Md/8k+43Gz4659/wz/5R9e8uBq4fP6S+e035LTQhQGpJn8rVEpeWJaJadnzj36ivP75e1L6fXwcWKY9iYGv7p7x46uv6EPBV4+6jmnc8/wi8au3l1A/b2xJ64f86kzXjIvXxB0rQBwmCjVJx7PrF9zd3jCnhZITu+sXeBlQVqaUsWBRZbPp8e4FDw93LNMD79+9/W/XOL/tUlfWsE2Zrl5PqqWNO8zbI4aAOrh5vDWD4TUdsU0CmP/SOrBWoNJ1PbVkDrnSdR339/f0sWdaHpmWGVWh7zaUVOi6wDSOR6mUqzarXYOByPv9HqCl0tn1itF8mkIwP0XnhBAEmj+ZSfkc45hQLSxpxrmOGLo2cRQbM8mYTLkUHscDYYS933N5ccHFdsd+nHA4vI90/crKsuS7lBa6fsN2uzX53f6B7TDgpHJ785YgQnCO1GRb+3FiSYmrqwvevX9PSoUudIAQnKXTBW/ji67rCMEzzrNJ7BTGeaHkzGY7cHl5yeEwgkoDv8CJ5+rZFfNkvlhUzzIvoMJ2s6WUjA+etCwcxncglmjmxPPN67f4EBinxDwvjS3eJGcSSDnz+O49lxcXlOaD5HCUZCbmsfOWWleMtRFjRLwjp0QIEKOjCw5qNCmQF4YhIqI4b4yllAwQUoWkSxs3VLpo4RBOPFU9ywzZZVBvkelq/pS1FGKM5GRMuS521Gp+YpZiaImKUi39LoZILZaU6HRks93S9z0Pd/c4V6wI/g4vy2JSWIaBXIGl1bIO2CsSHbXP1DARQkU1UxNstOPyMhIoDGHLsh2oLlO1kOYJ33lcEGJwSBJkE6ETCwFKhUF6fDRLieAV3zlydGgJJoVzETykuY3v04KPHQRFKPhaScuCc0oXtqBmhp/rjAjksrBoRpyjkvF9YZCOHITx8YHtZgOqjI/3QOXq6oIuBG7e3HJYEhf9DtLEqxeX3D1WEsru4pqaGgjae0LowaU2QbS0MYXNCofqyTWY74oomuuxDpTGqHSuZ6kP1PqIc5WUARxdEGraU4Kyu7jEuY754Zb7m7cUGUnMhlVk80Z1UqlMaO0QaUxJn0k6EsIFz188J15+wdubvc3FykJ1Nm6ZlwWPo3ohsyeKxxEI+EaQ8WYX0Dt8dHgGGCcUj3cdECxcAqulqkRE/FGu7ELExR0So5FLhBbAYBMCUhyS7cSYV2JvTMFijPalJopomwSviM+WKJ49NnFZzJaoVrIuaF3wMZKrN/P5XHClUGurFMSheETFAGjMj3fB/ERLAcTjvODV23juWyx/b3PxJ0DNGbi0lhfr41XO1uf4nr1yDih8BCB9oiBwZwyqdR/nRdIT4GotKo5gUG3rrgXR+vnzv4/8Ajv2c2zjEyANrQHp8fX64ZewbcvxaNpra/F9vrlT9aVnb9T2Cdca4xquvpoNH1kAH5RRT2R3n6itjppM4eg7YLs9B8J+83Iuczwd929ePvq6f+M+nkJz64ePrx39Wz7B29Kn7Cy7H9qR69l9A9/q2M+P/x86Le//yMU6cmMupVoopYFJ1UzCrQxocq8K0F5XWrqcnSPnFSnHU4hQEak47/Fe6RpIWGvThGsziS1YhykmnW32mOjRwkwxl5jSALJmYk4lt+QiyeY9tcZATyWwkMFHvDcmjxKodCQyU6qUqqSq7OfKm7HwdlT2WcgxslQzIk1VeZMq/2YPfz55XhMsatzBJAMuKjd55mFK/JGL7IJDi9FkB+/ZoJb6JZVNB14CD0vlf58W7krms+D4fSIvQ8dmAw/7TKyrX1Y2E2WUmmekA+dC83Kwk6zN4M8MUi39SgB/DsooVsC31DPUZnoF82YQwDy32rV0p37TyXkf+rRNnH7/EHRqT0bFQEs1tosdjms961M06Wk7aUeuoNQjgMbxtXPZ9NOeZWU0nd/bYKDMEYBbza7bZ9fzuYJOp3196H313VwEj2hm7b8agc7eE29ArRiQXtXo4SisP+xNG+h5rXhns7LOJ1DzLigZJNr59E5wVDp1LECRQCXTiyBqINNWDIDKQgOsPc4pSCEEj6RCdgWppfn62YOmSm6+MxO1mqeT+ZBYSoxyzf/ypxO3t18iYdtAQ2E7bEglcf/+Fonf8Hs/eY80SZ8xWIsxAItNDC3jzL/855fcv++JLvCff7HwzfsDfQw87vc4lGdX17y9e48ysKTCkjN393u+9/KK6yul7zyvnjuGKOyGwM3DRFJh6CIlZWoqbHpPCI6337xhXha6XQcRXj27Zj8t7Hozob25+4ogwsVVJJfKYVooN4WL3QWo8s3tHUHh2dU1+3nizd07nj2/YpcTNQS8BF6+/AzvzWPhVz//GcNmw6a3GPab20diF9hcRX4y/ITPri758z/737i8HNgfvs9q8jp0gcfDyIvrzen+10pKhXmuzGnis0vlX/3gHf/24YG4e0aaD2Tx3B+uudlf8WJ3Q1EPGnAqaNlz2f+Sefxd4u5Fu9aZpIK2gtKL/bNuonny1TY5WcGHjstnL9k/vOf+5hvKMtFvLui2F0joSC15ce0pQvBsL665//rnfPWzv/yv2Br/rouBtjZrbSwna53O/DJqRrwBIq7JrYSFeZqZ02zm1sUYhCKOmitVSgtqU5ZlYRh65nnm+fPnLNPC0A8Ijoey4L1nt9uap1pWclJECuM4WvsRm6ippZKLyW53uwtQWBbzHXLOEbvIvIyMk62TsyJEEAMQu97x+KitcNR2/cVS74oZanvnKaVaoqkPPD4cqBWy1gamwDQvDMNALoXlwTxnaq2WouQcwXsQuLm5xaml14UQiF3HZnMB0lEf75sBuYEzio15DocJgL4z+WvVjI8wbHd4P9qETxXSsiB4Hh8PpDRbXHy1ZOD9IfPwuGcYBmKMLaTBfJB86JnmzDTPKBnn1zGomYPnUo7BF8NgJug+mIdTKQYKCY6bmzsuLgaci3jnSakwHiYDCbSeTc5yvG+8s4j03GwN+m5LyoVpSuYj13e2j/GAFhuLhWCM9XFMzNOE80JKM947hqGn7yzd0PzFSpN36vGapJTw3hLvKHqcHAreE2Ns1zHjsz2Q9ocDcis8eyFsdx1elfrdJjzhvLDb7BBxLGWm6EzvO7z3NgHnHcELvVc2QyQXx2FqpvIkk1VJR9dFknoD8Gol5ErwEHpPkkqIkeg9pECMSucq6pR6sPGtpZoteIGgBe88uWZyMrZvcUBf0WgTTp10ZE1mJO2KjRuD5zDvCYIxtw6zMS1LonOOh3liKTCWjM9KLQlxjhgcUTp0MunW9npL3G6QNHHz+BUlJ64uL9mFyFKgBJNrepfNFLwVrrXWFjIUGNtARZbmCywWZiJq3pQuKLU84JiBStVIUbMB8VpwonRdz+7ymuB67m9uWfb3uFIQteTAVMC7inMFJeF9tPGOmEWAODN83z17zuc/+h2+/MUvKKoEPDoHcgNUvS+EYFYHeRlROpwLbMVRy0SZIfuezeYaXx1DFw3ApVhl4yNSDcfw6hAfqQToeny/JcQN0hK0pWQ6MOsM19hMbmvfqVQCCwFPVlD1KFvQBvKLeUZVLaRakBDwLuOIxq6q5tNrktyFoJHgOkoSXGPXI0qVilMliqOKPW+cd6h0JtNrY7/QEhW/zfL3Yzyd/Xv6tx5fPIE5p7/Pf/5m5OFUDJyKor9DcSDn2+EMCNOPjv0I8QhHBtRv3DQrE2dlcvya41wnp9pnrFhb96xnHzs9RI5MK1ae1keb/CQIs37mtDl7x/2GL6OibUh0AnA+9e2t2P3UWWjrqx7ZGL/x7ClHqdu3Qp44A8nWTTytYRtY8fEdYoU3rRD/4HN/l6WdH12/w8qq+I4v62W1pLdMKtqK8FMyUFVpCDzUIpYGV1bQsjEAm25RKDhvMjjnLSHDKyQx1lTJhSMfUEHq2uraQwb7bPHGmqJ5v6zFY2U12a8We6prBV0tyrRkxpI41JnqHUM0XyWTdnQkTWSpFF1YcuZ+Srx5zNxMHum3xM2WKo63s3KjlV9kx58vjm+8p8RIGSI1gAZBpSBL5WGZ+evlwAbPXa3MwTFWiE55rIU6J6JPdB3c58zXZWHUwpwFdUpSxxADOQ7sa0sZoRBqQbQSg2tmskqpBalNSuvNNLo0X6Unfc0ZoG3SlSblQI/tGgWRVaZ18tiz7VhPpzSfiaabrnry0zuC209upgYWnWM2K/hU9Wh0fi4tPn6UFaQ+doS0g3yyD233Do3ifs58etJrHPssED3vw1obrR/7Qhmb1Z3O5XdddienQACbQDFZ2noeRWxAmVQMHBYz85aWMlnVA9ngQwHnLN3G+HMW276CVrY0ANPuDIpAkA5XE8kJXS103pFV8VJA2tMwOCR4qhiY5dW8m5KYv5hTpYgnZYW0gDhKXa+Zw8eB//XPPH/xHxcuNo/EbQHv6TdX9EPP/uGRef+W3/+DBy5399Rm2o2uCYYVLz0ihaIb6gL/+J8NUAYmhZuHmZQqpThQTy7weEgEOZBV6YeB/Vj4xdePHMbKy2c9FxeR3VXHj7vI5X3Hm/d7ptn8SQCmvBC0EuOW+TATriKHuVDSTN977u9vefnyBV+8fEXxDi+Z6yuTJB0OjygwdJGLLiDFzvyL59fsLge0KMO254c/+gHlMPEf/v2f8vzF55aCJdBLII8HSk7c3d9zdXXNdjPwo9//Mf/hz/8tt+9u6MJL3t4UUgl4mbh6ds0337xht72kbwNLrQY8TfNCKUq/Ff7l797y5r98za37jE2/I6WRUQe+urnmD79/oI+OlBNKRKRwdfHAV+9/yUPxBB+t+FVrk6U9o7tgnnYizhKcMVn3qpQrVQmxR5fCId3w/qv/zHD9gs+++F2SmD9Ibv3GGuUtmo7JjN/txYAAM1pslhEqNrFz9qxUNTZJ8J7U2CNd1zFPVnx4X459d22ppzlVugjjNDH0PYfDwaTvYqbUpRRiF0gpkZaEqhB9R66ZLnYNzLaJqa7rINlxOBEDMBrAUKtNZtSiOB+g9R9OnBWR08iS7BnifWDoe3Q12W59S6k2geSccn11dWS852JP/dwYRVVNbjYvC6gj52ym1NsNOSfSvODFgRM0izF5qoHYt7e3VFX6LnCYDDRT1SNgAkoMnsM4Mt9OxC7SDwM+LFQVC/9wSoiBtJhEsOs6Xrx4wThNTONkDKzOPLZSKmgeKWWB6HABYmyR9mryK3Gh9ePmxeOcwzljGVV1+PYIPBqOd57Y+WaqnozVJM6i0Z3Q+WiTeKWa95YIzsM0zagWNhshZUsKXBqrqhRBayXEQN/3Jj9uiZ/ihBjNX6wZaiDiSCkTQkdtMkcDEddz2e7XWvDBH5+jro1jfLMNmJeZzWD+YUO/pYZCLYXD4QHnxeTW322LJ/romy0CiERqnVl0ARfxoVBCJriAczY5GoIn+EwqCec94jo0CN6DeM+UA0EdTmdq8zRyg8lS99OjyfWcs2e4F8KwsedWsUkkF1rfKUKoQsQj3tIZg0J0nlwqEoxlF4yTg/c2wVwaQ34Yeja1Yxor81w4LAdE4fLqklQKu8uBtCh+2eBcJM12F1xc79hd7Bi2A7ePghMhdIHOO2paKDXj/Wym2CrH4CKRRPDW14OB3JIVZzNYENvkRHXU4ll0glIYvKMSWVJEqyXn1griOvrhkk03IFK5u31NzaMFZ1RP9A7vlKImVRYHqdqYyax3EuIqXcx0HWy3nUkmq8NLZKGiwR3BWE2FGASqXevVyEA8zWw/oD6QKWgDDX3bV62YB55z9BLwLlBjT+0t5bZScBpwBComp5Tm7Wn1meCc4rTgW1XsxPrmiFktmA+uI6sDV5DOGFiazboEMACTADrhnU02BR9RD1RFXMCREVcQdRQ1dUrwJn8vySYTq/dIFbyz1Mdvs3x7c3E9A5bq2recioAn/ktrJQSnQb2u4Mr6GTl7/+lyLnVat/lrj2v1HjkvRHS1WlorolPx5HQFlZ4CK+semm0rRxrz2TGfmFwffKj9IXLiH30KSxE4eTrJqtP8ACkRbAZyPX7BBu5tf+dEpCptshJF1R1PM/IhCPUUDlP4IE3vwy/0m+Cg9Wro+UuYRO1UDgqtAFzPsxi7SI+MiBPwJOcHyxnkJWfXXjh++fW/p1L47F45u0YfgkEfnmYaYn4CDz86BW1dOd6+a0G7frNVpvRbsbSatRYl5zYbVtf2sYJCrjGgLM48F9ckcw20KzYwLQ088h68h+Ad3lsh68SYebQO1u4/14Al7CfWCXtRfDBQpEUo2PqurkN0am2AyhEgswdIyo5DStwnm0vYDMKzrTB05uUS48BcKlkqU808JLhflKkKfRzodleoi3wzKQ8VXovjxgVSjBaP3Dm0B/HWBr1W5nzg/cMBqUKNkVkGflU96gsqmaXMeCmEUCnMJK+wVA418zNdmGPPy7jhs+2GfBAOBZtpdQlBiYOlUCy5kKpCSVS1eFPrM7CbsFacNPiuOrR5y2kbEJY1WXNFXI+dhx79b6yPadfeYk04QfIGEJxmwVfJGkfQ0datiPrWD61gtzMD6dUibJW0qnHqVmXrEVQ6a/+i+rRvOgJIZyDS6ah5uuLZxp6AYfaj4S/2e2u3zplE7FPPoe/asl4DA9jturZmBtSjzMxmveuJ3QbQ2ivBnVh01WFsRJNgztWxEWXwlTuMWRdRygootQunbZ9m5F1t0CPO7kWtdOKR2PO4mDm509LaLa0PqJTi2W06Xnz2nHH+KwOpteBD5FdfDfxv/2ui1A1LLeg8IbHn4qqnpML+9j0vrt/xxee3OMWkH6xBIQ51Hc5d8e7O8dc/8/z8Fz1ffZ2Yxkdu7iaWmnHi2PSWtadUri+vycXAC0HouwAVbu9H9uPI9XXHi2dbNp3n1cvIdnfF7c3C+/sD46wsaWboO7peCE16Ap6cCt6ZFPiXv/oKXGC32xBFeNjv8V3PNM3kDHno2HWBh4c9728Tn3UvCd5xv39A3gs3r9/w4vkVDw97rp7BsLnkm7dv6LcXdDFyHR3Xz57xxfdeoU75q7/+Kd3FNa+6yB/+8Y94d/fI49TR75ToOzb9wP7+nnC9A63UtLDkkSVPtOw5Li9u+ZMffM2//urH9P0zwjTguku+fnjJId/zvU1CJseyeApCH0d28Wf84o2gXLAs6WgcjwghBPOt8c5MTBtTuba4+WKzOWgp7PcJL4WhJt7/6i+p4siys8G02p3tKJAfGG++/s4nYsE54O8bI7PA6UlnvyuIixStxkyaF2vTrX2VnBCqgTDi0CqIdHhnKUu+eT+F4Ch5ad5Me6oWtjvzgMpJKOU08RejASK5mj+Pa+zTUgpLSjYkFaHr2j6CmT+Ums3zsyouVHyEXg1wFOeoWdFqJuBmLm3eT+sIyntvHlbFnmfzbJ6TIXh8dEhV8pJMxtfS/KLzLNOenLNJz0oG53DesSwJaiZSDHivFcWzGQZKXhnElaH3eG8TurU6fNiA84i443lRb3VI10fWR8e0zLx9886uWEtR3AwmH0zLYuzNWlnSgl8cFkdV8bJWIELwgbTk4xg/58YMCo6Hx/3R2D0EA/6DDzxOE4JjM2wMXHeCd+bvFYIFPZixt/W1xjwyaVjKiZwyPgST2bmAccNPkxaqio+B4CM5NcjJOTrX0Q/R7rultnGDPQ9qY1eVanL1znekbOMYERv7uTNWVgxGpa1VzQsrm/yv70yOuWimpO825SlKQKtNlDgXrOAWCOLwbmG78VAyXjxk82D01Z6JXdig4umi4GTBd+CzJwXIU0KLMZmCKOqVRWdc6Ki+I9dq7HgsvMMR6cThS8LqP5Osi3OkavLZ4CJRAjF4ht6jRQnOEyTSdQNLKXiJdAIuJ3qBGnq0D+T8SC4z+/GRzaYDWZjyA5eXV2jy5HEhxAiuMi0T1cPmYsCLGARTlWlZ8LHQu8WYXtpS0sTGlr46vCi1LGaSrZ0Bs878XlMuaBJccbiyeopaPVCz1QsxBqKzSaa+G+g3W3JduLt7S9YJdW3MiQcpFNRYpY2F6ySDFlwF7wK+Ymw1r0Qs+S6lhErCB4Fqk0muelCTlTkvZkuCo8hArkpHT2CLjwOFGcU886QWAgaQg0dCpIsDIfYsrlKcRYkdg8e8ZyrmveSkb8xiNdaRmKIBBRcq1IIjgHPUuqz4nbVzB17MQ1BFKZJsbF5WhUgDr3AW6FAzHpviKW6hOjHiQA1ma0LzGHXgg4FdJa3BMn/z8q2BpxWwOYIYR8TgNLq3GmP1EbHlJM9Yh6vtdTlCNGeD/rPtnQFKTz70wd/rZ8/lfFbArMd3DjvJUTonDVfihIPYvtqA5jQLfqpaPpT0tQ+djl3OzsOvhW3OX1/BC568dkKQWrElzYx1/UriLA1BT+DZemqOLKqGunzoW2VXQVoyEpzQmRWAWI19191/UN6t6TdPQB1bea09j/KPVljq+Xr69FqfYKp2/HoyJX5SDB6By9POnx7CrwfSTiWpPjkRTyWWH33syd/r6T7dgecrffcHvMDJIF+wRLIjmgni3PGi28NhRdbleA21mhAuY55QZU3BcOCkImIDYSeKd74Z5zVehpx4cFpzY4lVA56cNqmZyQ5EMGqtawOcCqU4SpGj9C836ux+yTymQiqVLgVUAi/DQOeFPgQeXeBQErfJcTsLU3Go97joCLHDhcB7CfyH4rj3njF4qvfgHRpAvA3M0jjDfoalUosipUBxzFqhd4j10lRvPjx1a4l7VI/UBFMmp8wb4Fca+N5mwzIldvGCUj2Ph0znoBjix5LNVNw1Hy7r6LUN6A1gEDlLqtMKarPbrXxpAJUYq+DoYaZt4EibsVSOs++tM1z9Q0yVVZE2407bl6zteP2hiq5m4ypWiCitnTbDa5q3STOsVz3r2Q1Jse2f9TknkL0VHdoAM1o/pGtn0+AXsf4DXX2czhdrvM7+c/zdu0/06d/RZZUH6noNW8fmqDYT5kDzOvWzNCBKzx4Txm50jdGWVVjoKHQUPLl58jhWgNDav6/SUhYNdB59wGkmYwNHk0u1BJVWkHTe46SStRIxFpxoPTErc+FHLyJ/+Ac/5vDmX6PF5J6HZcv//KeF9+/AdRlCRyFxMexAhP3jHcG95wc/eMcQx+M4ZJ1AmPWCn//yirfvdvzydeH168rhQRgfJyteJTLESAzg8DhVM/qNnuvnn3N38xYQhr5jnMwjbpkKWWe+/uaeF8+3/OD7l1zuIrvQc30ZuLmfuLmFKSvvb96x6QaWlK149MYi9j6Q1TMeHg2k7yPTuDA/zlxue7bDwPsbY2jsusjV1TVeC/c3D8zjwuVmx8vPPuPNu7fc3dyy273nxbPn5Dlx2B949tkznr+8tijuwwN+9zmHww2Pd2948dlLfvK7L/ne85+D3lthqnB1ecGbt++IEbroSGlkXkbmNIEoXexwfuGPv7jhP739OYflmq7bMHWJ/XjNL99f8U9//wEpgSlloCO4yg8/f+Tt3Wt+9uXIMifmxSLpLR7cBsbruKRiaT3OdeY50dp3KcbiwRWeBeWLF68g3XP7/i1T6TgUA9xFKrrcUfNC3+/+K7fIv/3i2wC+qOIwVqCFtaxs38o6pZaLmUijinfGUvHOip9lmVsQqPX7ZiZsiZUhSAN6EsPQcf/wQEqFzdDTd0A1ICnlxaRu1SY/cplRAqUoXRcbqKWkJTUjaTOc7vuOEAPKzLRPR/BKU24+gG3Cotr3yQWWlGw8pwbQhBCs3xVHXgx8W0puJuZQq6cnmjRrHUugiHf4xtJ0GHARvCflgg8d201Am+RDFTrfE3zEe5N1dl3HNI7klCFXJDieX18h0fOw3zMvtn8nQikZ5y2Naxg6gjdj3f3jvo2RhS4EcrIkq+iFVNvUtTjmeUFLQgSGfkNVmJZEDJ19jmxM7mqm+QZAZ7w3H62UEtM0txQ6e7bNy4xzDu89tZjhe/Bm6r3M5qcU+x5VbclxzgBOJ2jFvGKCyfhzBlB8jOiyoOIIfQ9kS9RzBgxu+ojzGNsudMwpnWovAcSZD6/z5DS3iUR/JBBUmzkkF0/sIrHrKCUxbHpAiSGy6XZQlmbU/t1dtBpbz0dHyge8d3Y9O89u6AjS/EZV0AwlL8akCR5RY90F36NUogO8PbfCpieHQBpHG8t5pR8iIZjE0rH6wBmrOeIJmg0yEGPHVa0kb2NRoUXEiBC9b88hAfGkqtQ5kUuBLGSUKc/kkhiXjIRIP3TomFjSIxdXO/aHB0pNDJsNqSZcb8ymMc2kKVHF4UKgG7aQM7VMOKlEJ0Cg6ETVwpJnvAREIgsjqpUAyLLgoqCSKLKQa8ZptHEFFVyhlgVp45FIR9GMlibP90oIHS5EHh9mDnejFSqENtmlFCfNKxW8DHYcFEQzWkDVWFk90FGQulC0IMEm0r0WRA1Ms/ijQhWH+GrEj+qo4hFXccGDC2w2W1IDIQuOUidUGwAYHdo5aohUvzHPSymoMwm2tomZUguII8hq6FNav1+Nky6epNUASQ9IQXUBgU4aEcBZX+4d4CpVq/k6OmdgkjrEZVQzVHA4arLRvkZBJSMMOO0tyNTZ+NOpNAZ7Jbv8xATpNy1/b4+nv+8iv+aPJwbiH4AKJ1bLhwjBp7f9dyorFE5G4nqOprRjeHKw7ThPq3ybfX5qPSuY2qP8DNQ64i7uxL55cg6OQNPHwNjHx3IOAurZD1nrkw/W5QRIrduUM8QO/aR/1N95OeFp/82Wo4SOky/NJ32c2q3x2+DxRJut8j7Qh2gmebW2QZQNlqqCOvM2KNW8GbQKSR1LtodZEGVByS0lTat5vCSFeTGvItcM7rw4+xdM++6wGVptMglb99SeipoZogsKzujBYCBXrYGcPVNWlgopQ6qVXJS5FJZ6MC+BvkN6Q4Kqeu5S5fWUuU+V1JLYnJXrPKrjr4vn6y6y+K7JkQScIsH6ILdf4M1EKoDs6J/v8IPAUpiLUn0PLEjKdENH2CbmHhAz/WNxROlx3pNy4pvpwOsY+fx6y/Otp4w9d/s9ZJiXglfPXNQKtFwbkGLnuSYb9Kx9w8mRrgGHK97U7l8HSFWj77oTVqPYQw2wgQ7CuUjW+hzraGxgfKS52v1y1O22nqGcg/Q0gMkh1Y5NGyiFCCqrN10DPY9gOa0fcyvCbvtrMqC1J7JfVgbNWV/ZXref7thn0STLXs6szNsvLUPt79ae/msvR+93QUuTi6i2SQQD+3I1sNfmTRRnticgZtuPhsZC68hux4NeMJcNS4XghQNCpw7fWHUKVBEKq3eEIEXpfWPWsQpnV3AUlpwJQO/h4Jp0fWVWVpPDBV95edXz5c/+C8+7SlWL/P0P/7vnr3+amVNo/UrhwkUu1DONe+bphh/84I5nFwtRmjzQQ3Ed83zFn/4bx3/8q8CyON7fL9RkdPR5mnlYRoIEvDguLwaUyj5nnBZc1/HFi2vev3tLFMdSMjhIc8GLMs+V2/1E1Y6URy63js8utlztHNuLjlcvL3l8mHl3d0dRz34ujMuEF9jRNZnJjhp63rx75GrXs9luOdzdcJhhu92yGTrSWHmYDuxevjSKO46Hw8j8zdeIg4jiXeTVixfc39+xGRzPn2/40Y++x/u374Ceh8cZWd5zMTjqTUF94LAs7PqFw2Fm10eCGIix3fbc3Nzw7NkVqRTSUki5Ii4wdAY0bOIjf/DiNa+/vCXFHTH06PUL/vLLt/y/GNhtEvus5GxSzasLz+99MfJv/90NN/eWlufE0zkhBJslNhlwm5iQcAQV7L5tPmFVwDnei/Dy5SV9fs/3P9vwzeuRpSiZjfl8hB0Sr8jhu9+OFT0C8947jHVizoTawFkVQUul5Ar0OOcIrpLKjPOeECNuXtqEjOK9NrCn4MPp2SDqeXwYzXfNO2IMbLdbarbEuyWNJoVMahKJ1m+Xaj5fpVSTkQR/BEMEmOeFZVk4jAdSzvT9YMbazjyUnHOM49hkYZaIVOrJi8i5Nu4oGVEYhq7dawOqyjQt1GqAsEmWhMM4IgLXV5c4L9Sa6LrYEq8qpaQmPTXApmrCe0+M3tACBRWLrgqxsW2ieU6leSaNGRR6H3kYD00GJ6RlIiVhiD3zOJFzwTshdpb0p6W05DcLcQjOMwwdS17IixkSB2+MguA9FxtPDJFxVB6nGeeEvu9Zmu9R6H1jmJm0MqV0TBSuRQmpya7E5HVDb/eHEwPgcgvzCKGDvgGQ2cYPznm8C21smxBxzIvSt1AREdBa6HpL+8t5YlkWtCYUAyt9VUtHlEDWYiCds344pRkwJpieJS7mrHTB2bGkRN93rTU09nMbFwTnmL/jc7glmi/aNvRtYsfAv+g39NsLSsmoVqpEVDNxCHin5CLUbKBRXia6LqJFkCzECi4qBM9UI9M0UlggZGqdiQi4aD6KweOqQBGKM4N5iUpeij37EXoX8KJsu87kXaGy1HwESuclM00TQ2dM+hll8e0eC5DyPQBh8GzCjiU9Mk+PXF5dIAjjckDLnufPPuPhdjFvMoFlWohxA+Jbslu2MJcGxBUF8RGtgaKQXDGpnfY45ylVkLBybTNejFGXSjZfKod5S0qFsFhQiRfKmgYdQZxSUmWeMsGZNDdUJQqkmgkKSEBkQDVQNRGCtzAkV5pUTgjV2+dIIMlStrWRV4IJ3Obmp+WqoERUHcEFqss4hYBj229IpSMEYVwAyUZDUmcMxC6SxCFO6V1HbcBTUSXVSpTmndlqpFJncNU8xUqxcXYtaDVPzWqMFIIPxpzTgqpDqwH3Idikh68daERqJdWJrBVxFa0JwVPUajuHg9IjEm2SSJMFTlWPEAnSmQpGzXOuZP9rWs7T5e/t8fStlmM9YidFWo0iDa15AhAdwZsT8OTOASA+BHn+BvDp74wHnAAXjv9Ox3lu2r2++LcFnlal+YdfQTmxftoT014V7OY/MhTqky09wWuO9eOnT8ATw/QPVj/v+9f8vE9iQess+t/yHP8mM+4naXJ/2+UIDsrZS09fe7LfD5hTK4D09PjWa//rrujTe+M7vzTgqet6vDS/BmnAEw2VEBv0V22gRxWWWileSQFSEYoGkuoxnSar9YF0gnkxFFIuHFKmVCVGYYjC4E3TvKYCHluXWj+aqmmJ/VRBCk6KyTK8ASy5CKU6Ks5SHrTgS0WTMpfKfl64nxaC31gqTlfphwvCrFxeCC5kHg6VQ0qklPhphb8OnkI8mnKLruV0RR4L+qbgc8/wbGAZhLoTRBZkHglLYZ4CstlRy55NeuDH28hyUana8c4JD48jft8SY3Li/ZR5fbHFifCTGLn0A4ehZ94P3B0mur6wqOKCJ2iLqG9MEi0VXDV2iTkzgluNvO2cFqy416pmSKnNf6PKETDSNRlTjT4v7tyZrVGgm3+K3Qcrk7XJiasYMPj/J+9Pn27JsvM+7Lf2kJnnnHe6U83V1QMAYgZNgpRIUxGyZIciGApH+KP/SIcjFPIH2yFTlCgIFAGSmNiNbvRU853e+ZyTmXtY/rB2nve9t6q7C4DFLsgZcevWPUOeHHfu9axncEKVBiiKeZcYmGMyiTsPouYHhTukdcBhCGlLK8Rce6Hec4VadHuHAdPA7sOzQA9ra+t9Tfa8DGpGETv4jRnx86vRg3/ZS1W1Q6OFxqOxrjICYl5LVf0hkRKM7bYEKoiLUK1DpRIJ4S2m/JBtHYje7qWxPW+8V5JmPB6HMMjdk9ahZBpTUYWO1spY0hSxGGSazKVqxakVGUFAtfCd9495/GjN9374H/gnv2nGu589j/zRn4zcbAMum+yuzpWbsscXZbMeOD674r23buijTZRCrKg+4U/+bMXn5z3f/15C6cF3TNuXDF3PMATK5HB4eu/ZbvcomUenpxz5iATh5cUFu+2Wk80R0zxBrc0rTDhZrdmXmVUMvP/emzy7vOL62TW3lyPHZ5GHZ5H1oBwNnkcPTtiPkZcXExe3Oy63Ezs1xtPu4hLvheNjK1py2rEeOnIujLu9SR9CJJaOp08/5e1HD3FeePBgQxc8ed6R5sr77zyhCzPf+sZD1sfvg++5utnx8acvePCwsjp5yMX5Jdf5gpOTM9ZHPb/27TPeOv2Q84tLQvcI5pkHx57V0HFxcc7V1RXBCVPKlKKE4IhO6J0juB3fevuaH1++4NN8wlw3hFm5vH6DP/nhx/wXv7lhP8/kWZnrgMPxwTvK7/5W5S9+OFDS2gAnr3ikAdkCeGgyV1crSRtA6bVNopUuOrpuzdWYyduRX3kv8sHbR3zy4oKpjCTpSWp+KvLV5ry/1EUOs75q/nvicL4DOlwqUApJC3PJqDo262NKn6l5pO4L69WAVmGaKy6DBltX1wU2R2tWfU+Int1+NO/FENme79EKx8fHrFZrHAObBpiO+5n9NpFyoqjJ5sSZj49IMRaBcyDmzeScNXTECevNCfv9jhg7To5PmSYDZuZ5dwCcpnlqsjFLtIshUFVNJoiZgzsczi0snWReR0HYeCHXRE4jDx+dUlJlnEa7j/tArbk9/hwhrMkp4X1H3weG1akBANWS/KZpotSRqpmuX+GkIzhA2jN1t2PKiZITQ+wJXUeIgFNCNFPv3e3OJOVV2G93dDGYRBFlnux4B+/JtdLFyOr4mCXsQtWe2d4ZyCcus+4jFWcpn05JqoyjMX66ddfCMMwsvfcWgiLOjpH5QklLu4uUmgnBocWkhynZvC74SJJM7MznplYhz7WZ0dvzPUTP4KwxFvsOKY59zkzTbEBKMTsEMziudJ0xyEzq6XHOBD168J9pczu1AtmSEH27DiypF4Rxntms1gTvUc10fXcwsP+6Ln6ozKVwO04EH8yywTmCRurswA10QelDpuqM7x1dGEhJmObEEDp0VqSBJt45qAWpEyF43NGKrEJKwir09CIEEYiBfSns0o7QeaabZIbVVelrwXtnAH62NMIQPS72aPBo55nngiYQlwmdUJKambYzz97gK4VszMc6E/qI8za/H2+vCN7jfWAsI6NLpHlPOX9Gmtt80wnzVEjTTIzmO+XUIW5GyxZXR6SxgFQGSinUWfEamNVmYBFBskP82iSvdULIBMk2x3MeJQCFQmpy7Wry0uIQr0iANGV20xYh4ZhwviAakGLzpELF+0pJe5xTsmSUAq4yS2ESITtP6Hp6H5rSolIcuNhRtaCT0EnzT/M9SgderLkpgpaZs9WKd998j/ObiRf5E3ytzLOipCajHaB0NjuOUCRb+1ft/gwiFpaAGe8XLdTiqQgpO7z0+GDSShBc8XjtsMRh06YUPFmFQCTgQTNOKkE9kp0x3rKnjzbPn2ezPwFjsop0CJ6qjqoGqgYJZvUgAaQ3hleZbGp9PyDo5yx/Y+DJJvz36TT3kIylqJB74jQxwMTMXDGDYjiY19oX6t16WDT8Nrm9X/e358UrQNUrxX9Dfu7eeu29L9mbpYCxry7Az10Hf9mWA0jW9AvWfVDu7UUDdfSwrT8Ls7jbW72316+BR6pUUaOwLQBUveM52Lfrvb344nLP8cn2QzmElr6OT70uPFlSNw6fe+XDDaigPXAOb9l2OpqHQ7U3FhPuV0Gne8ftFdDpZ4M5ixHl6/u8+Ii8/s3FF+YVQGlBO9rJvb9tr4JTX74Nd4biX/8u693SgFzn8T6i1fxZDte3M8q0c+2825wWVBnUvB9yrqQqJDW5m6qnqDGSsjbnJhVKDkxz5WrM7FJlKgVqAV+JvhK8w4yPjWnhhTZhcYiacWDKrZvprQDBFwRh1UWOQ08MHalmUq7EuXCblOohUSnOcbzueXC65vjBCUfHa54/f8G17ri9ueXFzSVy+pCfDjOTrIyZc6isC1J3yFVGLhzfHtbweMVnIeBPAnnIPPSw3+5ZBSFl5fmt4tcPGMfI8+0zfuu4stl0/IlsmK9uKX/6fTZdx4nAo1DoVx7dPOQiR2rKZIGPX0486jOrbsLHjtUGMzf1Nm5apLjc0XUWwEQXEE/JLU2maLHiuWCTG2dsFQs5d4fxq7axztX7I1ClCojYeXXNQNyJGdMvwKQpsuxh7ppZMCy+YZayJloNfGqD9SGKwWFpRlUbGGZdY60VvLsbWxposvxXVZtX2atjhUOaXHR5Ue75/H0R4F8kvRbt/ndnKQp23n07pMYcqTgqyeQSPiHLCC9ixpQNsEICRYUpVdJY2W4dY7EjYBR2bQW8gXylVKIapXqv2LPIgcej6shlpA8zUSuz66l4NBUDNDEwQYGAEtSuyz4U/t5vvMsPPnnGW+uBdddxcbvmL7438/mzYs85H+j7yDwmKEKKiTnOPH605WyV6bFro1s/4V/+jz3/5o89q6OeVCGPe4aV8O5bb3Fzu+PZy0tOj1ecSsf55Ut855gLjEVBMjpJk509Z/ARxNgJ6h0+zzx6fMpHn36GCpxf3/Dy8oJYHTUnJglspxF1E++crtmsOtZHjmG14kmKbLeJ623i4nIkOeFyt+dhFFzs2e4SKsrp0epAnb8dzwn9itOjU65vtohUhi6y6gN99Bw/OubRm2cMXSBK4Nnllpv5ltXqlPXxA168PCfe3PDb//A/4ePv/RnpdmKQwjq+5I1HoPWMP/jvf8z5OPJ/+ed/j3WoHJ2ecPnyJc57pryn6ERHOHTz1SuPNi/5tSfnnD97n2FYUzWxfvCEP/3ogn/2W3uO15H9fqbMCvSseuX3fzuSJ8dtOmHOM6l5Vzi1+OVSxVgTusOLsXconlyTARHZkcrMuM3kUimS+d6nP+bNozWn6zVX2z05BVJ1pFoNWP2aL6k2theVWmYrwGzGbvuIkUdvt7fMWdlPyRgVvWOcJ6YpcXF5wzRmFDOYBmWeM/v9RAiO+Xpi6FfkXLi6vmGazHdIHOz3O5P/4JjTDAqxd8xZzYPJw2roEQlM0wS4u+eyWLJdzhnEmDom+SrmNRRDS5oz5mMt1rSa0sxqcNxOt/R9bxK/nOm7gRoMoNmPZpSvoqw2g6XfpcxmfUTO9oxPKZNrpeaRKRnAsSRYr1crcqmozihwc3Nj8j7AyQ3Oe7uetxnv90TX4cRYTQL4EHElQxBW/cA8z4w3MzjoevNRylPCzLIdMXqG9QqqMvQdwTu6GPACF1eXzPNMqAbi7+d0SLDrYm+Fnz2SWfU9vu9hP1LG0ZgMYAbwaUZEOD05BoTtbk+aZ1LKdLFnnjPHR0dstxPjlIhdYBg6FCHNhWkeyWRWw0DXC148tzsDk8wbzxMWMDAnSi6Mt1u6ONg+dpE6zgZIdT2DNy8wH3qmaeb8wlhT2gzjvbe4dcUAMWO/Gfs2VyWIQ7xjnie8800q6sglsdlsmhT36055UtYbZ35zxRggqg4nA/OYiH1EohJCa+pmrFFUIKjD10ggkvIIHSSvuBDQ6lFXCS0NL/poYTOa27O8EsgMPjPnkWHtCQTqHOi6juxAnSc4mws51+SLdKRtNoalCFKyfQ/PPGdyyUx5ZDfeUItN5wYfcSpMtzeA0HcngJLmEU0JxoIS2NeEhI5cYTfv0ZKJvkNqRkkmOzOeNNXPNmXUnpIFUWd/sHAPHBRGvHTU3FG04jQTyLgAM56afLMU6CnFm2RMrNkVnaPrBhyx+dPa+CiyQh3NO3C2hpwoEhPUuc1RHaoeVxx5KtY0J5GdZxJj9piVQ6KISWeJAZEV3eBNeqkJaY3rPjic82xONjx5+13mcMnTi6eAw6sBvyUJPmLHwGubiaslfsdwZ3HiA2VKqE53jT9VVA1U0gpZHYFwWKd30nzgHPiAakC1w6lDJZHKHsHS6aooHoUkVCKe2GxRjAFbSNY8xDxBnXpjKEZQqeQyE6V9r2ZjlX6F5W8ptZPD5PcL79yn/7B46dzz1JGW1KbLZ5fXD6u++yz3E+Ma7ez130HvtkME0Vc9meSwtV+yrV/cePsdaGCZvey4/7v2m4fNOmwjB0bXl6/81d9dwLM7D5XXAKSlAJN73Bq5IwXo/ZXpa4UW9iD/Argk5np/f2nuOlgxeveF1xPsTHy1/KRSub+j7Qi3balLoaiLhcurx35hvXyV5b608T4wJG2H/lZSt6/4Xfnb/s7XZnFmfuhNbtbsf2wS562badphEyFp1eYvkQlBidWugVI5+O6oVpCmx7YhlGn2rPeO60kZs0IteM2IFkotzUvI4XCEAJ33DM6RtNDk52bSqaDZGBQuKEGElYehU1QCuZpZ6FE2yU3sA5sh8uBk4GzT8yaF47XwvfmWl8/Pef7ynE9lRXz0Bml1jJBRNyMMSFQ2IeF2O7YXiaPNGf+Ht455ETs+yhVW8HitPNAZP2c6nzk5Hcg1oV0krDv21TO+vODb/QP+cfRMAb5bJo4vR1La896DYzYvX/LN9You9Xz4+TWxOK6yQ1LhQT/x8Ciw8Y7BO7roTbZYraNDxboSrgEzakKnXAu1GJV2SR4SQOodMC3i8Z52kxpoZFhOA2DRZqmUW0fMHaQhpZrpo/1uIyDV5TrxINYV08Y8EFdtYHF2TZkh6bLJy5jfNOjeU5bGxAEEW8Bi85ui2nijbUKPk8N1a2DYYkwqr46XtOtTaUBY+5S2LWjMvr82dfM/8mKbVxAJBjjVRWaXkeoQIt51OD9Z2ohyd8zw7Vi14ynC7D1jmgk5UgigCSfC7KxoDI2cIWSKzBQJlm4izSNAIVZP1dlSnajMODo8sxZyK4obIR3UpAXvPFpzM09876Mr3vx2wIcjXlyc8t3vfYyWYGyqAGmaqbMS+wGRwunJyDtvjbiQwEO3eshf/uARf/InO/K45+V+ZHN6gmg0XxqFWgtH6zXXN1e40DOsNmiuSPDstyNope8iq/WGl7tzSogcrdbN/yywWQ1cbbes12tuxj0vLy6JIpxtNiQqWWE3GYj6g5trVithPQTOHqzpe8/DPvDwwZq3n2yY9jMvLztu50qaRoYuMM6Z65stXddRciZKYBUEdORk0/Po4YbToxXrobNisO/xLvLxpy/xm4c8fVnBCburZ3znt3+D997/Z/zx//yH5Jz5z/+rf86Pvv99zs4GTo6OyTVyfrHl05cjb7/7kJef7XFPEkEcIXRsdzM5W+MgCIhPVJ0RXeFkz7sPP+P4/F2u+QZr2TCr5/LyEZ/fbHj/OBMuzSdkN01EF3nn0QnvPXrBdz/6kOId+zITvDK45l0hiX1RtrrjuHNQAjVHYuwo2ZOojGUiaYZgWPezecfV8y3vnJ2x9jDvJyRXLqdM5e8C5cmjWlphlNqTEgNBPKg2X7TgiH2kOs84JlLKpFKY5oKqkEtGm5zMB0fsevrOZG7eOXa7vYEYYqlszgubox4fhBg6bnd7VOzXc7WCR1UpGbImvK/WiPLmDeR9ZJ7nBjxYYSUN3J/mme3tDQA+GPjkvbd0Qt81eWUlho6+GwwcqcWAylK5urnGOyFXS24zRjSEGJiSeRpdXN7SdcEYcH1PyQnUmWE4yhaT5fVxYNzvmbMyDCucmL+UzVgEcYEQIj5E5r0V5H3nKdk8UY6OV9RSmevM0WYAcex3E3nKDENPyplxnltKYG3jrFJUubq5xqnS9T1ME9RCjB3ORZSe3X5mv90b26EPrFfRxnEtdF1gTo5dmQ8eW845xnHP+cWFlQBOiMGzXq0BzzRlbm5uTE6DAbfjWFrDoDD0a3IuDYjbE1pSXt/1VC0HFpKTSBcct7stWTP73WjN7ZaCuxu37KeREEyau1qLJSu6YEmFGHNmYR5rVWNC19oYWc0zsjUxQwishxW5NZ1CNF+u/bht6Y5f32WaJvo+gk5EicZIWUVm3bOJK7wkfKmQI15PwClzSVSqeYoqFHY4r+A6azigSI3Nn9HhdWK19qQ6oSkj6pjLjpTNp1Axj1/nspnWJ8FHA/EdmM9bF0CEoXPge2r1lFTJSdE5sV71THkkUZjFIbpCihKCESxuX96is/LgyRHVwz7vSXXGWC6R4Aa8twZjcI5SZoa1I4aRpCOVisOS2bR5v+Zkk5JAbeE4gSkZe96TKbJH3QyyxrmWtFoMrM9q0jCvFe9aTeKCsYREEW9AuPMRcqXWQiXjAwTXUdOEuoyLQp0T877Q+WispQI4j3jIatKzxTNUnFIlowS8E8Z0aZYhvgGuVY3xgwUwedfjJRB6h18Jsg4MR0cM62PmOpOK2NxXrKnc956pzqCJgEd8AKJtM5ixuA9EH8h5pIiZq2uxgIk5K4gwl9J0EUpHxUmyZrB3aM2QBXErao6QE5WJ4rKpFSJoUqiezndGpimTKRiCww89Vzc3Nq5XUzjMpaKSGXwx1rvryXXGua/GWPzKwNPBd+hLXl3i1X/etw8gy+FvMYCogTbAa9K7xRJc7wyy5d7nls/8rN8VW8OX4eevejfd36lWqjRgS9pg6hqotZiTLx9YgLJXQTY7HoeXfuYG2r4d8Bi5O1L3yx/VBaRrhsGIzeEbznZ/7YvYzk7HfQBqOW73z8CrRZbDohrbGn7mNoNpTpe1OvQOqFqO57IGbd5P7VwsxqFflMR9ye/9wiLwPuD15Z/9Mlnd/a/a2dYvvv+zfvE+W+reur7m9eori3lqeJwzDxVtoKfcM4e2Kp/GYhEM+YHqPa6aGaDF/3J3DguNCu5aF0xJuXAyJHYpMZbMXD1zckyTMqVMzSbJMZ8oB94RRImqBIHowHs53B8GpZgBoMfA5egdq+DZdFDEoa7HxZ5+ZeDT8WbA+0L0oLsjnn4MMt4idWK+uUDXR1AGKAZuhaPMIz8x75V92KAPVnw+BD4qhbyCTa98Z8g81pFPdIcT5VEvfPst4Q8/34PvWbFHPjznO6Hnf//BG3zoHP/dyYbnVyMvt8r+2Q0nKvzqPzjm7//Gt/n06VMuL895fPYNXn74GfH2BSsyG81sxNGLsYy893gneGeeHg5gSQxT8+Yo1fTcVCzZToXqhOhAQjCfpyLg28iq7d5s+HbRlo6GxZuHJu0VbYw1LWgph7FkiVzGeZCAUvEY22VhvC5eT0t+0wIcCc66MzhoyTfqXLv+lvu6rb+Yt4TKwkwEqdY5M+fH5SsLUG8g1KLOWxoRNEBuKfiqirE6gF/wEPsaLNJkDZb4aI8Cyxd04qhzT/AOaeCgNZ/aAVhctRry5/0GPzxm1nYH1mKyCfHMxSjf4fCsqwiFrKHF99qIX4HkhaCYtE6arNIVpJpUVJppctHWuHGF46Mj/vzPfsqurnBsye4b/Os/+gtemK+3PVNyZjtmkzPUjPPKNz4oPDxRLEZauLg94//1/77BuSM8jj7Cfpzx4gm9sSYenZ7y4vqWh/0TNpsVlxeX1GxkfcTROUvm247m63J0dErsA8+fPifVSh97xjTRiedoc8rJ8Sn72yuOj46YysTtbqJkZeiVqVbOr2amac1Hn3/Kug88erDhdNPjRYnB8eTsCHe9J3lj/eynkaO44tF6oAZhc9JzctKz6Qf6TlGM1t6vN5xfbpn3mRfnV9Rxz1vrRzx+8oCHTx7zrffe4/s/+gHj7S3/5//6v+bZ5TX/7f/jv+E3f+N3cPGIDz+rXDwX/vUf/IRvf/NNfuc33uC73/1zVkfvM7gJNDImmxjjBaISxVGrklJBvPJgfc43T55x/uIJsztCV5DnB/ybH77gvd9/yNBd4tgxzXtupZIR/vHvf8BPL/6ITk55dNRxmyam3Z4ixl51tSDTyH6C4/iI/jRSdEJTpUqiaGI/ZUoyILSOmVsVxotL3lqvOImRIynMXaF0X3/JbB1HA/edSVBrA8LNZNruFbQSu2jG9tPIEphgkrI702bnhRibPFkrVTPOdZRiz4Jaa/MTumVztOLhozM268h+u2OaJ6ZJTUblTZpTqnXQnfd0MbIfd4QQ2N7umWcbn/shAiYJOz46ptaKk4w0oMGeUb7NWw12Dt7YFTEG5jRRivn8VK3M4471ek3sO8pYcBKo1XyfVDI576kVgvXJ0Kpszk7RWri9ucV78w4KIZJz5ub2llIK3nvmlOk6b55OpTI1zyitlVxSezZU9iUbkGWULpO2Ha0PUrMxz4gLSA34EDgdBsY5Mc8GuM8p0WESJ+cWM1/7Xe8dOoOI52i1YrPqjUUaPE4gRk8qhTxnnCqb1YpULAXQu8BqvabvB7a3t1CFNMPcZkJFR2IwBlGIPbHzBkyow/sOi0oHrUL0HaXaOuc5WdPPe77xjTd5/71v8f3v/xUl50NBrVScC3RhRQgmLzIgylFSYRgife/Y71t94iylyztTsVh5p2Ze3/wpg1fSbNLElD21mvn7ECNOxEJrytf7Hu67AbLJy50vSIAQMuILLlT6aHMsQVHXMaowF3BUYqeIKyTNjNOOFSu8+JbkW1C8eSYKTHWi+kzwnhg35JypexsvXLZ7A6f43ppOXeeRWiglQCe4VUC7SA4eR8EH8JgUU1wk+0hlIsTAZt2Zuf7tllSMYeyjpxvW+K7DBXCM1OoY1TFrpa+Bje/IWikihCAG0vjKmAv4gCsOTYUogT6a35Tlnk1UZ9dp5zubZYQETlEyyGhpmjXhWhJm8MaY07mScka92XsHVZwa06aSbe6QDNDOXhE3kmVPqWa+rcUx9APeOfKYCH1PZU/wk42DYQM5I1pZhUAUUA9JCjUUBrfB12g+W7FrLFGHq4UYQrPrGEAswdGJY1itWa025HRLCR4p4HxFZaJkwYcOlWj3SUl03tOJgPO4KMzVnodOgwGV0VOdhzLitfk6OcXFigsgRQjOft9raIzEHdUVigrVZVRLa7g65qKmgkFw1Ty7ihrpIGeFOSFk5lxwYQAxC5BCodTZ5qJ+QMrCcPvFy1cGnqrUQ8TffQbNwtj5ecsByJBXGUK0jouDRrO9+46VHg2CkqW+bclF3AFW97vXd5CW/e3usX3uWFV3LCp3+PYd38e1AVPEbiTX3j9s9jKoLoWRHH78bn/l/iHR9gC+678fPqd3HiR3WMydie4SYS0N3XAIKtUMNaveW50dR7nHjrr7jddQksPnXz1pokrLRH9l27+4KEsR03iLGPmiFYTAIo/54s/qKydZfuZvcO/cfHFLlpJ04dYcXpeftbblDb3ztlou5AbgNRLHKwyuJWftlSNykNh5OPz/351lEbA6TOssInfhlCJNCtsGD12uP9p1HpoXkEO03ROuXUnBcjS894co5r4qQ0ysW2JGroUxe3a9shsL+1TY52QyoaqM2Y540No88yo1K1WzjRWNupvx7OvEOMN63XO8igzBgfeI97jO4Xoz9RRxVpT6yoNNz3sP1jxZC+fPrkiffoovHj0GWR3D0YrgYT8LOz9QHx2zWwf+53nH1A34znHSVdRNvO9m/l40c/Sf5mve79Y8dzsuryO/JcrvHg98MCYezoXTX3+fzdGaP/qTj7jZKeOYePf9B5ydniFkjk87hrjm3SfHnL+z4ukf3fJtP7PSW3wa0NGhrVvsncnalvQgu2cX9pjJ67R6S4VaUN/WrbHurPkKGBhT2y0pGJxsTCk7wzbm1Fpx3gpEiztsd94igatWRKkUxDVgSgtSW8IRGFzv7yKYbZhp15XzNlFV87oQdRbxuoyxLcXJmqWLWSLQroVl3BdprCpVo/rI4onXrvu7oc80+tZ+NQ+r+vWe7C5LgQZ0K4shMSrG9NCKhh4viaotrlyKyRdFyfcaAiKKk8I8XqHaAYHQnjVKwre4euda/G4FqIRqyYLVW6EcqlKoZBGTwLiMd8GieEshrgf2u9JizO3cvP3WMQV4canoukC/4g//5Jx/96fnVKIlqjTD0FoF1zsmX/mVtwrffMc8WHzseHl7xP/0BzPnL6GLtwzrIy63W1axJwTBObi5uiZtr+m7Nf3xMddXF6SUWA0982ieYYnC9fYWFFzw7Hzi1AeOjzbcbCeTJGfhweMn7PdXZC2cnJ0wTROXl9eoBkLwzKki3nNy9JA6J9CO/ez48OktgVtWfU/vBPGRccr0a88bD0843vRWyK0CJ48ecjIMJJkI3nN5u0fDgLjIbttxdb1jyplHb73P6WZNKRMPHjzk0eO3SPOOJw8fsL3d8dmzz/jzP/0e15c3HJ2e8vlnn/Lf/3cTHS8J8ZT3PniMr+c8eHjCZ58W3nwSSLOQ82yeFa4j+sG8PxyUnBACfRj59qPP+OjqHT6cVmipSHfGj89nfvDJyDdON/S3t8z7QqqJkDzHT+A/+8fv8d/+P/+KMB5xLbDdW9HQd57dlJEiOB/Y1okxTUxlT8lCkEjNEJ1DXabrhW6ITA6kKrcy46Nj1UfeAGr8evvDgPl4INGS22iJY01yrqqUYmmmBfOEGWcDA8QZU0RbsIRz1tzJ2QDNZb44zclMrr3Nebe7vbGI/Am1KPOUSHNGizUCY78ydoAqWu/kT9M8MvQDItB1PTHaHMiu9ZkQPNvt1jyaFp8uZ8C1E484KLUQgmMYVqxXa3b7LTnNgDDurcDp+0iIvsn6CqenRy11LTNNmb5fEUPPfjdxeXnJnDPXt7eEEFj1PTEGpD3Prre39F1PF2ML8pgZZ0v28y6ycp6c1Uzb1UCinCtpzCavSTPeTQzD0IrQgIuBKPZsylrZ70Y6F0yiEgJUZZom5mkkeo/rOxZT7d12iw+B9WpDSYqWmVITOVdK9sRoY0dJ2YD6otRcKJoAayCVUpnGa0LwDVyreGceV7FaE8AH32SDgdr8cFIarQmlEEPHOM6E0Bhx3q41S9db8fnnz7m6vCLngtRiDUlVUtq3a7LQDx2r1QCYJLPvAzE69vtiZuPOW4qeiIFP3uYnsYvteVPJxSSTuYxA4fGjJ+x2E1eXVzx++BAXhPF2+iXdmV9tSaPivOBDxWlhCAN98PjoiEFQTVamBrv+cZHgPdKea2b+vAIKpXiG0CGaKHVEQqILA7XrGVNnQIAWAxGYzYheAlI9RSviE+IE1/eUavMk9SO1E6pLTGWmzEKsShwiLghZHX2/QUJgdB7oGbdb0rxl3l8TO8/QD7iux/nKvhR6WRN8xxJgEnsDgoMHT2XOiUwm1ULUSAQkFzPdribbq7PiasXFSnUJ8VBrQiTiGktIc0dRY3GLQqjJZNlVCBFqHY3R5CxBsmZjCQXnG2SHNUjLhEhBRSl4O7YeHMGmrmlGO4/vhFRn1GmT3Do8HWUEmR1dXBHdmlJuUZkpzlE1EHSwhm8t+CUEIztj5Xr7HMVZnzZljvoNx8cPGFNmn5/TuUi3CubVKhZAIM5TKnTBQSiM7NEcqEVsLBLPfkog1fwWFFOnFGu+Fy12TaRKkI7gmp+rmJTPOUelUJyxukQFV8HR7ndPIwxkAw0PSYkF8kTv1ZqOC63R2fUfneBIiPdQFNGvBil9dcaT3IdO/mad4YUhdFgnC8CkTQm6sJzuvGAPgM+9n/1ZJKJXuVLLo/hnb8vdVjT0QV5//Q40c8vvutfel7sjcp/49PrvygJSvf7al8Avy7E2UEeXUCbqfeCv/cidz9B9SPBu+TL88UvhJPnidit8AViRe+8dXlE97Iu+8u5rJ/srLl/16lqYCxyAyHYaDwDY/c/99bbh5189y1rvVbZ/F5YDuLlw7e5vuzcgsXGmBUuzekWuakiTxXxWd2AD2ss2OfOH7zfIIQRC6SyRTSvrIqxzZVoVpjwzpZlxLkypMGczDtdSyRSKOnLN5DKTtaJVCC5RZW/0WODh6RH+wRq3tknVEGCI4IMQtFCLRUHvpx3TeIvTLSuXGdIe/fwTTsbEzYM96fgU9sfkccP5ySPqozW6DtApL7M9zKIPbNzMQzdyEvZ8Q7ZcpBFNI79WVry53/Lj88ivbzZ85903OFlHri5eEvqeN86O+dVvvUXVgb7fEFaBOHRMxZNqQFYnlO2WGHtYnXJUznm3h5L33F7OJA/SeYI7xgdnwIoaCOQwFbZXk01Uw5+oqs0EsFKqw/lm9S2YcfeiI1dFpR6AJ7Rp4qk2IVZBNCO1snjR3B8YjPHqmozN2Fe0pJ3DSJwbkH4ATswMU3xjHnmH8wWqb9dVC8x2bRyqBihpS+BbaLDa2KDLfW+fKQ0U1juA2TWT17qAVza5tpTQr6ZL/+Uvgi7pUNLOgVSkClVtAoZskayNEStYs0cPwI/DPAFyuSFMn7OSxzg6MpZoacFgBZrEsuJwauCta2OGNRicgY1tGHFiQKZTZZaASwU/K6JiDFlNnK2Uhycdz59fshsdR1G4uU784b/+A8a9wzlACx6h4FBfwXtWfeXXf60yDDBPPS9eHPHvv+v59OmazVnP9uo5dZ44OjoC9dzeXqKyZ1gfcbZZc/niGbqF1eaI46MTpnFPTsYGGSfBuQ60UFJhP90iWuiiYzMM7PYjpw8esT4aePb0p0wlU45PcKqs+sEMd1u0+XCyYSzQR8dqLa1htmK721G043o3mg8XkJxyu92xihEXg5EGneN2rzy7Sbzx1gN+9PFzjk47js7WkCoP3vmAy2dPOTs9xneRQM+UC+cvPmPVGZNj6AK32z3vfetb7MrEn/ybP+Lk4SmVEx6cPOTq8hP+lz8OvPVkxenphquLGzREMzrWNaoO82dbt7Q5mldcgTDy5ORzvnH2Mc+fnXDjIlU7btOGf/fjgTd+K3K8Coxzk+DEQs4jv/7Bm/z5+5/xk09G+n6DxoF9HZlrMc+O4pgozHlvl3k2tl515tMRxJmcKSt0nhiVkhI388wkMw9Cz8YFVvPX3B8GGsum3Hv+2n1ctVoClFZEjT2iNZPmGfFC7AI5Jfa7qc3L7Pnrmy+OeI/zAYdjvV7x/OVL0mwgjXOe4CPjbmK/M3ZPrgZY5JxI80TOxqrVakDDPKeWqmcNzRAiKSfmuZBzxofAatXRxUjVyjROjPOML5XYdeY7M09M80RVWA0Dzosxi7Uaq6kzY90QfPOsckxTIm8nOw4i1JwZJdMFx4OzU6Z5Zk6JECKlVvY3161RZsWVojjvKHVh5QpjA5ZKVbrYIc4zjpMVVZg8UEQJYaDvB1JK5FLNA6v5DoaoDbjxVCBES2Ybpz2qlnQnooQaEOmJoUmegifnwjTOB0Pw4D3iDNzLNVsDWhwuOFaxJ9ZgbLfZzG9MtpbJ2fyEUjYTeOdMUmTpg0LeJ7w30B0KKU2Ic+QqLaXPkXJCRPDes99PfP/7PySXTPBmHuy9PVhDCHhMiuedp2ghuK4x2yxQph8Gwm4yaVNjQS9Ny9oMr2mG4+KMpzvn2X6rKPvdnuA9JSfmeTSzZPf1voc3ZxucU6bdNargOqGaqo00Vta+b2bpts9eK9RkLHUVRKPBGz7isxHFe+ks3Y2MBMeomU3fk+cKzkylRdUY3i5QXSHVjKtiARxacBUkVyTYPRuiAaU5JbrQkWvBR8+wcsRYSYvxuXTs9jtEKut1Tz+s6EJPmkYsEEaZyfgY8A4o2VQKOlNq15qGhVKzgTelEGpBqwWT4KyBnNs9Uqqj4KF5MxEreZ6IRJx2JE24IER1RBfRAqU65rniqxJEKSWDZqpvRauriFdrnJQRcYXeg9ldm6wvNFKGKBa4Uwvgbb7rQNXjZA3JQbLPmQ9ZpNZoze+qdBKIQNGCFiWGaJOfTlBRvLdayHvfbJIUHx2PHj8GH3j+9DMkAdE8vQrmuVu0bSPR/JSaB1yeZ8Ca8oWEeX05IoGSrZHsxOyHvBr24USITvCuUOpEIVM0ULWzmgBADRjzmgmaqdlS/5xzTKUSJNq2i1hypXg6sbFtUgUf8EUIKI4KJZu00q2+0n30t/R4+tsvdyCK3Iu4vg+YNFBhYS/J/S/eLV/0X/rrbIMc1vEFv6rWeb9jXS1gk4EO9/2mnPsi4HWXqnYHUh0WvdvLV1RcDTgpLJlQ96CldqHVBelyLESlL983kS/I/RZSwL1fXCxTvvC5LzJ6xIrZXwjM/K+/fDnA9+rf8LeHhv634etEO2BNZFTvCnM5mD8vIEQ7vw1pNX7cq7JWcQ1caveFLAbTzrXPNnBLnDH1FmZUdPTZ6Mld8Wyqdfxyqsw5M6dKLRbJPs0wyszNlLneV67HAtWMZtM0E1HmaUbKzHi8wg/KA4msY8GTcEWoY+I6zXz48pyXn37GxflLYp45EZB5z/HtC4Zp4vnVhnR6Bu9+AG+/ST0Skwz1DhkUpj05e65y4ri/5SHnvKm3vHf5gvnjT/nWZUe6iry7+gYae2p01OxIRZlut1Q/8d57D7jeKrl41puBzarHO+VsteJyf8nlttKHnuujh3z/6ZY3z8xMMsw79ueZ5Cq+98DRHfBctPV67th8C+A054UJ2WSRauwVrZUqronFDbxZgJjDn8YCUkOhoFGaHU12x0KSkwY+trGq+XNRzaActevjLpSusaQkgK8UtaJb1LUUFLtO7OFrE/XDNjQGlxPBTMHNkNw1gJ5sEyVLw7OibgG6DuvRaoVfrW29oJp/ySPZV1scajHzB+G1HuTLWgM+RFIt5rmBM/+nBuSICrXaMU3qm9nrnk4mFDPptCRLaV1rS0KsB5pVNX8UhUmtSaRioQC1gUsDmak6inr2c8Hd7sjZAKlHa+Vbb59weXnDswsDlUVH/v2/+Uue/fQc13XNFNPGHCdCdlDTzG/9Ss8H78Dz84HPnsJPftzx9EXHNmfET5wcHbGd9lxfJkLfMawHcoKr2xvA0a+PCJ1jKkIp1mUNsZC0EmJkEwfG3cTQdRQpnF9ccLxZ4cQi06kT47Tj+PSM9PKcMmW288x6vUJJdL6jBEdNhc36AV305PlTptGKr9UqUtLM0fqYlHbc5sw4VS5vM1ufWfUdMQju5gYhsr+d2Y7CsHpImhN5ntjvEx9885scHw/sry7w/SNurq75jV/7Fi+fvuDiesv73/wWly/P+fH3f4TrAm+8/RbnHz5jGI54751vUPLMT374EZ8+u2S1gYdngRg7Nj/u2axNGhm7zKqvZA10w0OqS0Q/0uGoNRBkyzcffMxPL97gNr+JipCK56OLFR+dd7y1NobFlBL7/ch2N7JZnfIPf/c7/PTFn6DTRPQzLgqTWOqW64RZJspcqamQM2h1JDODw6kjaEdCmYtJD3zz9Uhkzksia8cbX3HS+8tcVJVa82F8MsCpjae6xM3YeNr3ET8Zm7AUpTYWaymlFYViSViLIbNC33eUlBmGgdvtBU4ifR8Z+mByk2LFS6kZrUIpxmBRMIas3eqWQhejFXkCc5qopVKaFKrOmVoq+/1o2yD+MI8ep5FxGvHe4X2klMI47UmN7bQwTKfZfJUGXRn4gyUellrsGbDIBwHf/ANXnYGkqVS2+5F5num6ziR0DdBKqdo+GX3L5uXiEakWGV8N+HOyhFFoe/5VA+LShA8G9EGbGik4dcxzIsZInWcQKzYRRxWYSiZvd9TcVApSzYgde/blaiBjjB4EQozmr1WysdnsgYoXT6mZkjMK5hGl5ttUirGhcoauC6RkjTXvFRFvZvUKwQdAjGmeLdZ+VpMROm+FsTgLjKk1oz4cgKPl/Hh/l0TnqwGctRrTo9TCMAz03YzWyY5pbRJwd9dwKqVSikn2Ywy2HbVaI4s9J6cbjk+PGIYBqme/+3oznmI0AMPVwmrocM7mUBUH4ghhMD80w+8RTXiXUEnMJIL3lpI49WieqNNE6Tyxs+Qw5yOuevNGqltKyJSa8d7T+Z4pKzl45qKsYtfsESaKFryCw1uDNkT6MDBvbawR3xvAnQtT3VGd4JsEbr1eE3I2mZ2LSGhsyjLRhUAus4FfHqCxxb1QZKIUh7gOJ3URwEBrMFYBFZPFEQq5CFICTjso+VA/KhmVmbAeGFNBXcIwFrv+anDmG1YDwUWyZpPxt9qcJkvLaWScdiSlAc+KoxBaI1Md1CpUNTaZiDW2PB5Rj1MHtbDf3zLnPT4IEgTVzhqWJZmUjRl1M+oiRaD3sdl8OIKLBLdiPRwRnYc8EVdwvNlQS+VosyJNuwbmKj54PDYHxZmyzOPwauMZzaQ+aSJLBiyd2rtmzC5QJRGcw1VvDUFnqdaupuY95UDNeL2WEWNreUQ7Y5NVmJt0DrWmdtXRmIt0aB0QbQE10RmYWhSvJnNGfAMQwIWvNpP+awFPS/m96Le//DN6+OCSOLFgJIflHphzf3H3/pZXPtsYNe0J8DpAcv9zh3/cf+NL/rWwedxCHVsKE+TwO62yYkm5u5Pp2XeW/Trsn1TuDNRbR+u+j9HBo2opFu4AjfuSMYRDmtySuWSAlB2D1vO/U605aY2zL0robD+/CJwsm3X3XhPYLMjXa587rE8PO/szEZ1DQhyvAlSvb8bfFND5grn44cK0Q+x4bdMWfxf5m5uD3/+eFXwLHPh3aWlXZS1NbnR3Pb4OTto15l5973BfL/evHAAo1yZ4TpovlLBoIbmDAYybY5EqDi8RqSYLiDHTtQmMV0wuNsF2V3ix9ezryIv9yO2o7KZEHW8ZUDPOLhPD7YrcJR7mQPGREzcRqqBz4Wp/w/c/fspPf/gRV09fMN7sWImiwRmDKt/y4mZv6XHlTfImw1lBQoFOoAO6gru+ZPCJR5sr3hyf8e6nn/Pwx1f0lwk3T1zcKtUHxrdB6oZcOkIt3Jyfo74iq4HaPeB2nglDQOmYp5nry6dc3V6xPjrj9OSI3/ndI17+ReBi/Ii3/A3eKatxh3/+jNr3lLOAuN5GmjZRFKRJ56RNGpppLGZKrlrJxcCackji5MD6QRYZXG2eUe36biCOquKanE/UJIbO3fFVTdZcLSEEKwAWY+ulkFKsmLBrKNlvudweViaz8w1YEYEWrUebXQENZBKPk9oMKMVSTxfgbBl3udvu2thbti/Z/ujdZ0rN6FekCP8yF2MXWbfQ/PgCi8cXsgLXU/MCIjsrpmiyOYTsFHOn8Hgmgs90snRTlSqRohnUEaWBdvdotnaO7TpAvIF23sIAvCq+JR5WrdRccC5DFR50id/71TPmAj/46TlTVYIUuPyE69sXhKEzCUZyRhH3Hi2FXConbzh+6/ee8G//4nO+9wPHfuu4uk5450ha8cERhoGQMxOFGK1rXqWQp4n+yUDXdzDdUsYd4gOrYYOPgcubC65vblgN5qUydJHL60tciGQVYvNS293uuLneIwE2RxvOTs5IWtjtdgjCfp4RlG5wBImoeKa5sOoHHEroHS93Nzw8GVgf98j1FhccfReZ5gkvHdtxT657NkPmbLVif3PNqt9ws32Bd46zx2ecnp3yox9+l+35Jd98621OHz5gverJp0dcXBR+/KMf8c1vfpNvfPABf/i//CH/5Nu/Qvd+x3d+5Tt84+03eXH+DImR3U1im+DiKtNHh3dmWO1iZNUFvK8cHXmO1xNnJx3ro45HJx1vPOo5PukInePB6obPtsckCUylclk83/38mKP3I8iIiOHal9c3rIZT3n/7Db71/hv8+Q9ukF3i6HgFPrMjUcQZUFBsvKmi4DxVXIuvV4KrVCopBwSPixA7j1RhKjNbzTxP4y/z9vxqS/N0qrXe86trs8YmQ16SQ30MxBiRbIBTrcI4TsxTohTzZdyrNRJCCOaHFmDoV0jzKkKVs7NT81QqGa3m6XR0dML11ZZSF5lZsRQ6lRYoYXlGOZcm6ctAC39wVghO04QIDMMxzjlytddrrY3dA0vq2bifUC0s/o8IbayB29tbhqEnl0IMkc16xTSNxuypBR87YtcZMFXMJNzMyh2r1cBqtQHg+voW3+R0u90ImHF1q0ttv6oxy8wSQEg5vTK3s3mMM4DAm5+Wb7LGquCDJ+UEKF3X0Xc9KaX2zLSiTSQZA6kY0BS8sY1KqVQtBjA4mxs7AQnGLCy1mNTYeRxWXKZcKDk1wMyeZzH4Q1NYxBtwpAkRe645F8mzFd5VHZlqrIqSUM3mlWgWMPhgcsNSjF21pL2qKrVUM/8OJgVSLe3Z0xLbqMTYsd+Pbf35MMl3zrfr4E6KqSpMk8lKa6r0/UCpQlXHNCeoxcC5r/GyH2/QlAkt/tmwAfOllOiZyTgySZWOzgzYAxRNJl2vO1ZdpKCUYDYSOSRciAiBqSS864h+xagj3impJkQLPniigFdPHo1mVRpwHRtzXAVqnfCh4FxFSyF0K4LryHkkLewpBKcVJz0uOLREMhPCDNpkYMykssfVnlohS7VrCqAoKglNjhB6QEllppeuJfcFzASiIFJw1kpEvSLRUSXgskeqBVjNTMa4i2rBWT6Q1SHVwGewAAUjYRljsNKmh64iPuA0UlOhusAsGXGV0PxgETFnTOcp6hqQ59ECoSU0+xBwUdjNN0y6I64doVMLt1BrilQ1GWktQo1giX2VqhFcj+9WdP2GYbVCa0HLRCdQQyANG1brDU5v0CkZUCjGMgpwCCnwbUqenVKa9QRekWrnzrVmPt4jNeGCs0AIF5B2v6koqRrG0tw9rexSS7TW5nFZxYGL5g8rNscMYnWc+bZFS/ymkpmxrwVcC+upYpYOwWVjNd73S/o5y19vtq0L2PFlAM/P/Er7nL7y8TtD7ntQiS4R13LPONuKpIXmf8d8+nm/vYBfX45QHUChtnV3uIUcEClt27YAUXcAWj2AGIduv9xtjrRtvfO1evVIcFgvC8Wqbe/dttw9B5cjsBxF82m5h+1xOBTyRWDnZy/6C/7/q67oDi5bAKsDc0vv7Yu+um1fJR3uqybIyWuH9YCLLf9zOJfSrq//rSTT/Q2XA3h0/7q1AgtZ7kujoeoBWW0H1NmExEmbVLYJhV2lr4FXC+Cky0TFOBoZAwLa9OQAbHnxBiCQiSbwQToslcPNzHiK91zcJs4vC5dT5HwcGfMOVWXYZ7ZMvJxtnH77iScMgVXw9AqrlHj6+XM+/vAZaVJiXLGOHX0XSMXTEXh8dsp2FXjOiFtNSBSbfElHNyROpnO+JRO/PV/x7R/8iDd+csFqGvBuoHpl5Sfi5RU/uBx59K1v8PYHb1JKwQ2R6w9/AicrNo8juyuYp4Rzhf64axO/yvPrLY8fP+Ts4RH+2zO3P7xkO16wijbmuN2O/PmnSL/CbR6AhKXRYN3q2lhPKs2rw8CkUq3T66VSnEmzVOrSnGqeSK1LVRsgUzncXMvdUjCAx5XmSQKE5tHkRFqmVAObdAGgK1qbrbguvlN27ahg8sza/EE0UD3gXPO/u7uepAFPtYGdWhYHNmkY+H2Zr4EfSwe2FvOdsqIvoTWBlHbtCzTa9dd9MWjP5I/7XWAcPX3foaGw2znSOHJ6HOnWGQtcscmewU/WUY3+CNyEL0qUSvTVQCY8Ew4njuKxRoaoea1hM6GOSqrS/OFsAurVvN1KS5vxaoWXEKiaeRAL//nvvcX6KPD/+befcj06Yq5ErpCL52TN1ObNNs+ZpJVYoBNP2u/55rd+m3/zx5f8+38/E4bHhCDsti85e7BmFQdEPOeXlxydPOTxScf29paLywsePXjEN977ACfwyUcfM4TKkyePydlxdXlBzomh9wwPT3FSubwZGXOh6zds1o6b62u6EIhRWR0dsbu6JZfKcHSE9IGT9REvnj+j71ZQYZ4y4zTTxVvWwymb/sgKMe/YT5XHbzymlkytER96ap6Jq54SHMSBkgqTRo7UIcz0zuE2a9zUkbJw9fQp35c/44233+T8s6e88eQhf/lnf8qHtfD2O2/w4vKG7Thxu5948vbb/LP/7J/w8OER83rg0ZMHfH7xnI9++iHb7RYIFINwgUiunoSjjoVprDiE81tHHzpCy30XgY3fs+lvGYYrdnrJBT9hOH2fTnu208yPnp7yzvEZD+IltRRCXJNK5eb2kkcPIv/ot3+VP/nBv2W3r4gmclRuU2aaHePekjqDePa5UfylUJNS1ONDJRdlEwtSK8VXUrRWpWZjnkwu/RLvzq+25DJj1IAmQ7KyqEmcpfncZczc2QqA/X6LC8YWcRJYkkkVkx8aEB9RFbb7HdM4M2UraEpr5tC8Q3MuTFMmpe1hvC9F74AvlQbOFHbTbM1ZFyhF8X5JIFPzFxFFnElkp3lsTQsOQIPtU2VztGG/3aLqD2lnS9Oi7zs26xW5TPR9wIlnnCaT7nhLatNqxuB91xNiZJ7mBgSZ92OthWlKpHmm7wZiDORiDKqUEuM8GfBWC13X472Zbk9pMkloNSCl6/oGtITDPNE12czCiOpixPUD0zw1MMni170LHB+dGPMzBs4vXzL0HSEYqzAlS+yrRckuE51tnzGdGsPYOTuG2bzyOh/IKdt3csJ5T2wsF4CSK7EbDtvvnEnoajE2mW+skNo8+owpVag1UUpkGDor5Nu8LaeMhR0vc2RtoKMxdVbr3hhyydZVD3NJObD2cimEhf3eJH1dF411XQvDqiPnjObM7XZLaV6MwcODk0fgv973cHXmreRdRLw947xUoo8M654ila4zabRUNbBpTs0vz7yLcpqZq6N6oXcQXKTvNqTsKPs9Mdj3VAtSIEgkYyx1a8w4XPSkNFHSTNBC0UwSaxaH6hGdCF7xPtBHCxIqyYDEnGw+P0RhYkuqE0lvwc+4EAzc0IzWGa0zkiquNHDCm+ecl4BWZ/I79qgfbdwqmVA7HIGMkFWMRSWB2PLQsypZM0glCOYj63tCDWhjO5qBtoNScRlcHKgKuWSci1SxBmoh4xwEDBh2oSf2vT2wcjLvaA2UYsmcQRSRnaXIpmJBPBoQp6AJcZ4pbSkUfB+RzuNKxeWMBIUCuQqxW5FqwQWhSDEWWxyIfUfswMVCqoVcsIRgHH2MdN2avO1RMS83QcnVzNhrtcZ8ruCckktGsofq6MRRvYH6pSpTTQdQWMVTq5hvYkskDyIk8WRDl0EdPmO+vks6nVZTO0jGuUrnOiieqt5AOp2JoRhAX2ZSmfEaiBJJRrjFBWuE4rKxsNJXm0d/dY+n1qVYQI8D9PRzACCL0aT5By2oQLuBtTGXDmBWW9/dR+zf2jgzi5mELnXwq+DBl+NMX9y2ZTJuIIS20qUhS9oMaSvg7nmE3NuwQy3eXnJLAX/4mEnhDlvw8/Cxe5+7/zOvvLo8OHQRPf3sffvrLV8GMn1V4EkOF4E2gGE5vVb/NvS9fhn49P870Of1I6BwACz1/t/6JR/+/8tlMddX7srYewCv8yx26odvLISHRkuXWg/3xAG4eO3v++l/i3TLuh8NFKiLwfQiTxWMDGsmjN6BaDkYW8fBMRQ4Fo+PM0rl+TTzfD/i54LbK0c5oU4Jtzdsbwam9ZpVt+K9tWO9ClysE7ubcz789CnR9bz9KHK6CQzrwLhXM1J9cMQ2Am4G2eGjN6JMgeBnfv0k86vXn/L2v/sr3v/8hnUZCNJRxVGdJZy8EeHD0jEMJxyfPGY9ePZXn/L0u9fc3Fyxvk1sU8StH/HgbMM+2gSy7wbefuttHp0+4kefXfJvP97yn56ccPM0Qp3pvOJrIly8RNcriD3aH98deL3jF5oxUpO0qT0haq1Up0ixFJK7Ae0we7Ru+73TefeWtU20GohUazGDcxErPMTM6hcw6oDn0L6jNonSeifV8N4ebgs/W71HpG8XTbjbvnbtHcbHdk2hBi55rMuOW/a9xTfrXbKTRTpnqAnIOGasddMkf3XxePp6A9I2vgoUZXsbuLjqGdaelApjmvnggxM2sTDnaxCbbCgVvFJrIsoDYvcO+/mvcOJMn+8ynTfmVyZTimPKmY0DgqI29yOYhTmTmBxOWzdNsJCC0oDC3AqcDsGT+M///jf4nd98i//bv/xLPj9PFGDlFb15js5bEgWRwOAtMcskJUpwwntvv0dJx5x/esWj1TG+KzhkjljmAAEAAElEQVQ8p8dn7CoEUY42J+SjR9zeXlpS0GpDNwTG/YSME31YmyRBMs+endPFHidK1znzUckzq8HkBhcvzjl54w2GVY8TxzhmixhnRxcHTs7WqBaeP3vJkzffYBjWIB1ZJ8IQOT4Z6KLn05/+tHnbOIahZ1gPJBU8kTkHHjw6JU/X5ALOB8o0shtHVken7DWwv33K487Rux1vv/OYi/MtuXg2m2M+/+hDtrsbvv/dH9B1R/z0k8/47ONPKKFjc7yhHzqqzByfnbDbZVKe+Ff/6n/i+OyUd998h5/8+CfstxP9sCYUSPMW73pCF1AXqdPUOswdiWJgiA/MVdln4cI5gnMoI6l+RHn+HFkdcbQ6ZcsJP3nxkPXjT9C6A7fC9z27VIi7Sx4dn/DW2RH/7pPnpHHkqFc68dzMSpSB0Fc2Rz2boqQ0mRmqCqk6IsLtPkGniCplNt8PFxxBQgMJfpl351dbRGKDghc2poFMhum32V9VfBdsDF0aNzmTcybEiLidsUEBpLH2m0yq6yIhCGmX2F7eoOroO8887wFhGFbk7Kl1pKilRxqTBpw3uVwptYEvrjFqKog34MmbTCzGSEqJNCe7Z7OFPnjvjZ3T0swQYR4nmz8scTBamed8ACxKyZSaTLLnLHUqBN9AsYzmSsnCdt4h4thsjhiCMAwdpRT2c2EcR8QZ42g37gjRZGjDytLefLD9CMEf5vvzXNrzSIhxOABsJStx5dnvd7YPXcfp6UljhRVKLnTBgIdcE85bY+Pm9gaH47Y1YMdUWHmzEmgn38y2UUpqMTautBSp1pARZ8Voym2eZddEFztC89MquR7m1SVbVL3JGh2lzZn6wUzWS83GtKqlgUA902Qm/GY4bnGwXdcBUzv3PSXXJuG082oyTZu72euWprha9+Qyc3VxY683SXfKlmZYqzFoDdiL9tzxxtZxzmRDORlw54PDNFZf32XwgTxNBBEkK1KNMZIxXyfvC0fHA2lvBVFtwI2Bwx25ClMxf6NOelx2SBBKEpw6Ou9xDsY0kwFXKyrNL8sJNVVEZ0LIZrniHPPegTPPMVHwMhDrCi8RYmaumYge0spciKQ0M86VOs14EgMTUxqR4kGEadxT60R0CSkZKUMDeavJYtXY5qWFzvQhkAnUKsx01pxyGXEJwaPFM1VLZKY1Flwwxs+UK6E7NucHEbLalCxGa0iJK2iYDPhwDvXRGqDN80mqEqowTZmiQhc7jlZrxiki2SSCzgkdPSIVR6LUzCSZOHTkoqgEfHSId+ZXVpToA85HBI+rxjCNwZuBthOiCDF0ECKxO6aLPV1Xia7gpJDLzG6cOFJFXMVHGzergAaTLM6aoUDMJp2sKmgxKx2n1pQQZxYBVQWV3kjvLuCkEoI2FUGgNMZUCib9zQhIxNISTfkQ/EDOlYAc5Ii4QFSh1MioFRcCuWaMgJzMq0sC3imRYJiHdygBIykUCkJU3/wJf/Hy1wOeaEDCa2iKFRv3ECS5//lFYkFzlqd1eu6xihpisIAGhwJqef9uta/8/fo2fOl2vwamHDCrQ7zZ3TpVbDu9VTevrfNOZmfgUwOcXFOqtF+y/7+Djw6H6r7k7rDiex39e/sgDV0z0KQlL91779X9l1cwuPvgzs8Fve7t+ytV3SsvvLqNyzrl3rHRBVwAFr8RG3Bffa8egKf7a37txH5hw37+ttx94rXP6/3jufyjfmF18oVz/OXLovb54ibdA1i+5kXr/WURQMH9Y2BSpOpaLr3YSbRTem9Gv8hnF5ndMqFcTuUiI1WalLTdzQdgsoHRaPv+EsApOAlt/ZaAUapRibNURi/k0EH0hKEQNol5uyNkYecjnfE8kbRDdjdsbwcena056npczuTdC3bnF9xc3XJ27Ol7oeuV4AXXeR4+ecjNo4fspYOpoCWR2qSU4hnFU/eZf/rRp/zOT24ZJCAxtPErk0uj0HvHG48fsH7nCb6LjLst3/3j73Kzy5w8eZe4GVjLwM2YqdOMrjvmeUYplJTYrAbef+MRn7w7cnsxEXLA1UJ2M2uf8VrILz5Hzx5AGFCJzTBw8XqyY1sORrXYedQFSK/UJmETBJMYg2CTISseFrmWthu3jeNqYklxckjXs7+lmYLqoq5E7zGWlkmytpxIWdbbgCutUCVCtUmPSeLubSPeZAzLAHu31sN4JyrNOLwas0SLTZZb0QaFWiYcGeczQrFEGDGJ4tcddALIKs0c3iOhp0rPzU1mczzx3kPP4weONCdSBvNya5OAClWEYfUI/IAfM04q1TsIQtJKafe5iDA4TMpIYGq0bamWaOhUqFIRekIFp2YwLosZuRdCdXhG/su//01+/3c+4P/+P36X//DRRNZIx0yXL5EyErrIbsx0cyZhvjJCxblCyeb18vmHH8G8Z6MO0oyKI/pALIrmhJtuOTo65nraU1xPvzmj5Amp14h0iIPjsEElcnt7yZRzk9rBzfUtJU8MRwPSOYZHT5ic8PSTjxiC5/jkIcgZw9Dx7OVzLm4uGYae/fYWTQnfrzg+7nnzzROePztHQ8f5zTW1Fh6dPGAqI2eP3wQt7PaJh2++ybOba1YPH/L5959xfHaKD47t9RWuCi+evuSdd96gdCu2uSK7Ld/49ju88/Z7PLu45Hd/97f5l//iX9DFFTrvWJ095BsnT6il8lc//ZxuveaP/uCPOT3e8NnTj9jfzvzef/q/43d+97e53k189uwpoe+ZrvZ0zlhrFMc47VnFjRmlDivGcWScEloK9Gb+Lc4mwFmVOpn58+wikYnjCGU74R18/HLD4+EJZ8NLanpBjA/JecV+Epzb8lu/esZ3f3LBWC2CegjC47Vj0pnaFWadcQJusLjuKSeczIBjJULVwtykIvu9EnzBB4dK/aJJ5ddwURVy0RZbrwdDcRvHrEBXjFW4OTriZrcHRwMitIULKClPVpQ14L6UTBc7uthRdM847cmpEHwgzZkQOmqF6+st+/1I1xhApS7tICglM3Q9Mdi4sS+jZY04mPcJ781cOqXEfr+nix3znMyIvGScM0+WLkYEYZqnxmi+8w5EIESPDw4nloIbY2QcC/NkDYI0V1ufN5meIGhW+r5DGmvn6voW76xLJT7a9K4Fm8QY2e/3OOebfM/KnHG/B4X1Zk3wxiAz0Ma3c1FwLqAq7LZ71puNpc7lxMXFFSmlJptb2FCdFbSxw3kDDnMuBO/ouxWqyjTPxM6zXg8crdfUXJinqTHGDTyb5gkVYZ6NnZXngg+R4CMxBHLz5pLaGOIO+q5jmlJj/y7b3h2SfEWM2aDFWEfee2ozXHdt3rUwknJjxy1A1zTNjdVuqXSlFFIuDCtrDOWcGmC3SCst9U7VQEfzF7fGT07KLNUS+ZIFn4iISav3W252I/Hmhs1mzcnJQ77uzOM8JsiegicGh+sEQkQcqGYzv95d0dU1RSO5CKhDMImozRMFyAQXqdkzuwKh0okQPLgYqQRgasmQgeAjcy1IJ3QaKUmouVKrpzhPwkAevLPwhuzoKmSxeyqXjAuBuRaUTNWtJdKmJqXVipRqhtRacTlBtXtJnBXuwSlSHCU7nAqBRMmFlJRerFFRqwCdMSfzhMhEFyIlm0cgvoBmXJ7xFWIXSWmH+BEhmJUngeIcwXfGrNIdhZ0BUOoPZA9Xse0IZkyOBrMdqMXsenwg+jV1zqgWMrP5VEnXWIDJrKRaOk0QcBq43WbSWFj1K1ZxxVRNdqZ1opBwboW4jsH1uH4gDGuTRwZj9zk8FSED07RFa0ZaKmAfLH3Z04P27LdbnHfEEHBUnEZKNi83Kak1XaMx3V2li4B4ava4CjmNoJaGJwGqU4oIGbu/AxYEUGtG2tgWPZBz6/l2zI3lHGKkC4oFBSkhrCi5UnImODXWVZmZFUJcQQZXAk4iFFMR+O6r3UdfGXiqVfBODgZM2gChxVVIqlpB64KVCs0Pwprl2mpZ1woSvefjtDz2OJTDIosczjyOjFl0vwf+xeULzKulcKKBAvfAlVdLlzs3+OWzBfANbKjYg7713lGxfXNO8aIotk9uKZjRV8Gypf2v97b9/gYsv3tAxHQhLHB/jxd21lIcii7x6Noo0zTfj+Un6r2fev2/98V7B8FKO5d6bx1ffrTvQEHXJhWudUWUUq1AKk3us1B279b38+DD+8uiNf85n5bl3L72oXv/1gaCel2AsFZsqx6u3btyWLmL0TLvGEWpbjH/lDtwbTm+y2tf/7oVsOvRNaaCgSalFaZ6B3S6gEqjw6tSpTZDZ7l3DoVlMBDxB+HGcnUsV9EdDmrXWdVFUtCo2I32uMAfS0JNykrSylThNivXCcaijKVynSrbrIze88bRhjcerHkSHbsxcbmfufj4gngtHB33pLOZ8eITPv/pX3J9foGrlegdUirjbmKXBekHjt5+wOebiN4U9NkeeRDQtztcishl4swn/ovLZ/yjH71gVSoSPXmeSPbIZ0zCbVLG7AihIw4rci6cnqz5jd//B7z8/Cecf3LOfLXDh0wfPNxeUjeB8WbLxx99xqefvUCz44N33+Of/sb7/PiPb7iapfnvqKV1hIpeXqLPnyLDCfTHRkHWdhTbRNAhjSnZxtFSKGIspVoK6hxLAo02jyiTUhpV11yB7EwaONnOjVi+mXcO7yxJLXjfziN2btVRWvrNkna3MKq0bafXdvnU0gzpazODVZtRLOtyNr5SG/RfFcsCWQZUM9eVWtBSm3RipuhsD816J7OrJUOwfzspmK2k+zvBlAAQTDqRJVPdSIjKw0eZo9OJXgZCwLr0OJtNNd+rKoLKMSG+w378IZFsR/DwjLa0PF8zWqLJeJxDJWDObNYZUydInjBiu/mKJHEEMalQL5lVNW+Bf/Rb7/H3fv0N/ps//D7/4eORnIFaGcqWuHtOKYnMxGbdM+12JFWcL5ScmW/35FJ4cX3LMAx0AXrnGbxwvIr4wbMOSheEbZnIVztOY4Xec/38hxQCw+YI9Z79uOPR0Ybt9paTzTG30w1jTcRk19zDzZr91Q71AT8EBr+iH9ZMKTFdXOKdsNoETtY9L85vwHlC1yEh0K023O533NxcUiVw8fQpXTdgMuXC8fGKvnNcX23RYuyji6ef8vbZMbmLfPLyJU/OHqJJeHD0kNspIVW5uNlyeaO8/+Yjzp894zd/523G3SV/9K//FSKes4ePeHT2kOQqDx4+5tOPn7EZVpx2K9bvvs1HP/w+4Hjvg2/zxoPH/PRHP6Y64WSz4fj4mM+fnmPCWY8fjhjTNTfX15wcH9H3xpSwCa8Z1Yf2IF3g2Zyh5ASuMGlHnD1u1SPzNTe3R/zk/CG/+8Yjhv4lnj2lOObcETJ88MYpv/btU/7isyumCq7MHPsOmR03+8LOF6gOrZnZm7NEFsF7JYsS6Qhe0ZXQxWJmr77gpBJj/KXdm191qZoPMjObEYUGqtssrJRs3W4RpnlGRY3F5OH65pqcCk4iXb9MMJu/jMA4TeSyJ0S1rryGFmfv2e+zjfFiceqlZHIxmZ5qakCKgUpAA2YqfW+mxAyC845pmokhUL1SSjVTaJpnVQOX9vs9tZpRt3OOrhvwPpjEqti8wjlrbnjvKbkwDCvmeaZWGPq++YWYHKekQnVmxGspesp6s0FEGKeRm+st4oTN0cZ+Qyvr9fpgzj1NZrAt2PGoVRhTsmcT9ryM0TOsArV6sni225mbmx0xdgQveB9Zr1ds1iu2uz15NoN2xFGryXjGed+evZHb7dbS/5o87vZmh1aTIqGKbyBdTsnYTt7hfcAH8+zrhkgplSmPgGs+UiYfd85TSyXlRNf1xBiA0EzEy4GltpiEh2DFLLgGGNVDA2qRPt7c3OB9sICuLphZtY/2mG3zvnE0DzWtSoyxrbcyz4laLVEvFwMKrTFvjDkRT9dH1qs1Wi1982izsWvTR/rVmmHoWR89pJavt9di1wkaBpwPhF6IsRD8Hp8qwa8b2DjhuxW3+x37nBk6T3SeIIEaOsa8xceZfdohVfBqSWZFg0XS+0BKM+suUkVI1awqXC0E3xGKw01zayBXsitknREqXj2SC+PtJWme6FcblJkaOqKLTZY34V0hz3vqnPBDT5mK1fB5tvlSdTg3MBerK4OrBAUpQHVUF5lqRyqZKpkp2dwQIOdMFEfQyBCOqXu7r6vvKHlPVCHqilqEKTVwekp0IUAxGTGSCMn8hVDBBZOYuurpqs39Kh4XWnCROPoO8rylXx+x7jp2RUnYd0QcJYALFc0zksGXggYBFyw4xQVcDkiKzHPm6GxF368p6hEfDbBxFfW9+WZ1K8T1hC4aMOM9zq0ozjGXmZxmprRH0w5chFxxapAi3kOthKEDrZSgpCWdEPM7c87CH8R7gqwQUToNKEJyxih0VFzQA8tfVEjaGFNOcHUmiknznPPt2iomdWzsVb+2MWSaR2rK9C4i1ViXwWekc0h2RA3MaAufKbghQBFM8Sx4L6BfjbH41YGnVpRKXRAgach2qx8auLLUAyKWdKOLfK1VoBbNJwcJT1NJHOr2CkjTD955LL2C1ABfAjT9vOVngQKH1+8gMENgWppSa8w75U5y9NoqTG4gB0Drvoplef/VX3n9hQbK3PsNVZPwHcyf72+qLoCYFYNVOUhkDrK3+8fp9W1oYI688glb8fI7d+/pF47zK4CYLseKw5+y4EA/45jfX/e9vf/yD7+27V9Y9NUPLNLOw36IfIHVdP9YvnJcX3mlXeM/Z0e+eEX+XVjkAFwag6VQscmZdQzF/HjEQIVXKIjLGuRuPSLmQbHc9BZ5D4t/hWKU+9Kkdq4KtTQQehk8kMM9tDAFtWqLdYb9lDjfzVxuM3MpjFPidj9xM47MFcIm8u03NnxwHLnYV/7y6ZaPL2aYM3m8Zvvigqcf/ykff/RT0naPq0qaRm53WzYumIzjaM24joyhAaUvd/Csh2GF7gPH28I/vfmIf/7sP3A0Jgi0hB8l47itjv0etrmyTwZkj9vMn/7gY/7x73+Hx++8zfXTD9lf3TKXwsmDB6w8lMsXTEPHultxuj5iTsq/+qPvc/rgCe+8+Zg33nuPD793wu32c6pLNoHwmd4rPH9OPXuD6nrTu1cllUqqFu62SAiW8cjuz9oScJrBoLZI28aYogoO33wfTLrinFHAVWmpF7Wlq9k14rzHi2eJrnbSzn1VSqPpK83DpL2vauwEYxw1rGm551o3dgGGq1HnGnuuGdMvt6UqlWQPP2wCnUumlJmax4N/B+1ZYmaPHDxrDhD6VzRE/GUvqgVFiKKcnBS8L/QxExCCP8ZJoOZFwqJtsDfKQhyeoBSm6Yq+Aip4Dz4Yg02zTeAKhagCxTx2PB4VobYHh3gxjzDnzPjSOVIDLnsprH3iV3/rA37nN9/mX/zBd/mL58K+BJyDXiZW40v6umWnM65kxnFiPyldH8jjyHY/GUCoCupJu/HQjfeidDfCST9ztg6cDI7gN3S9xwswTfTeU0JknEdqKByvjri9eMFcMqU/IXQnkCZKTcxacH6Nhsw0JlZdz1gm3nnjTW63N1xeXzK4wLNnF+S6J2ll3TnOhmOSU45ON3z446fkrEgZeXByyuX1FY8fPeHi+pwVK3b7Z5ycnTGPnv3uirffeMiL5y95990P+N6f/Sl5mJnKTJCOGKELA6fHZ4hm4skZ+2nk008/4vLihk8+ecrm7AGXF+d88/03+OTDj+i6js+ff87xyUM+f/YJm03H29/4Jr2LfOc73yEOgW/+yq/zyWcfc/7sc+YxERR6H6gY42FYr7i5HLm+vOHoxBFCJMaAuEpBmldQxQEhBOrg2e8EzTv2zfy1K5V+syHENZ+fD7x//IQ3HlRCmJjyLdO+oHrEyXDMb3xwxmfTJROFUBx+X3kYHV0ObLpAbWlgqWCFapOmuFVFislOxHuOaiZ4pe+NJyHl6y3TARqzxo7Z0oQBOYAKiyy9amXKiTknas04H6xAKcXm0M7YtblYgRJ8aDI7uN2es72ZKFkYhnVLmwUQ8pyZ54QLJrvyzpLw5jRbE65I2w5Yr9aknJr5+NzMZpV5SsZObOP00PekbIysA3AVzBjdDL2VeZ5xToixs068D3gfGPqOUispW7LbOI7cbmcUZTU06bU4QvRs93vGlPDSjLpLYU6z+R4VM/vv+86OZ62EGNjvR8bRmFsxdjgvTOOuseMaEKPmbTXNO0Lw9lxzSsnmJdVvjlmte5yrXFydmxQvDAyrgVIy+93IdrfHOeiamXkpmfV6ZfueMqLQhciwWiNioNw8ZWIciF5IpTF027W+3e4RFxEXKKXivD9IIMEMjjsX8d4dwKNh6JnnmcXIu5TCamVJjzEGxsnkliF0eO8OwJhJEKPNn6U1W4tSikkpzSAcrH6rLUXQMY5jk1oakDVNY7MqsfXEYKATKszzRPCOWhzr9VGT7FecNKPuqozbHXXO/zFvx7/+osJcCjEGilO8ViR4Ft+2XCsER6YQOscQHcEXqAYsQGXoOvMUkox3Hd73uApFm+FzynQovhNGPPNsjUMz1xfGVFqRb3M6qYWuyR9DiKCZKOYe17mASE+QALX5sHqPasTFxLqHcbrFi1B8NVNuzHvOfNI6u1VkolQoVZAakOpsrhDsWvchUEWa9FPwIeBrZ+BvgUCgjIUQHXhPEfOFrGoNgy6s0BxwdUKdEp2j6DWl+crW4kGisfUKeISpCqmAlIILhWk+J083bE7fZ4gbonQoM+IDwXmkjpY4qQGRSgyRmpXsPcELUQuxJnyZSLtL5Owhw3oNEtGaUJQYOuL6lLDqUOdIEzjMl8/jLe1NrLGpKOM8Mqc9625lAFLvqc5881LKbLoN5MRcKjhPUponqvlH+VXEVfOJmueZLBnnPTUKqWaCM4mniBICaE4ErBHt1CSRIsYsQ0OTWhqrvZTczNIDPnjGDL531JJxvTT/LYe4FeDJcyauB1xUVCekOPBCZbJG0UEB84uXrww8lfvmH40UItXmtejCcr6bwNcGULzu7bSU9sqdn8jy4iK7WXyXpAELckCulg9+2RZ+GQTwBaiHZjj1hW++IqUSzLNCQesiQqEZkL22QrnbpuUQyKurYgF1fm55I+0Gw7yvamOGyeHbr22oOmqVVhAeFDF2rGQBoH7x8os/9TOO62uAk/VRbGt/tnDli68uIOWXLvdfvocBvXLdfMlRXdg35asc9y/dPv2S177k03+3UCegAU4Yr6823516uKYM5NWD5FK4A4S+5O8GnL6uIhUwhorS2GANRK3Np0ztXhIxaZVzd+wacGixSUlOhSkndvPMfs6UajT1Mm2p+1uYMrVM9NFxdnzC6amwWa/4xpOMxMCjWLh88Rk//PEn/PTpjOI56sFrsYSIWvAuU6VwdXvDHNegHsEhKcDzgJscv3tS+L/uPuPJzQ3iElU8OVdyErY1cF4rU1LGXNilQt3NvPXoMbdzYK6DdSFmyKkQnSNm86XCw3h5TfWeNCU+e3HOb/3Df8RbTx4QfeDoyUM4fsz22fdwMiGhIDnjQiJcnyMXz6nDMTmuSMVYYjY5WMbQ5U7xh3usYl2R5ZwI7iDVQxzR3Z33QLuXlgeQeLRmi6J19rrDtSQNzwI4gqBiqSql2ERy8SFRCtTaQEtbjw8e58MhAceuoIWHKa80HrQaAw9tY125u6JrVXKeKWmkltk6zGoU96KmqXfa2FoLQKa8ki76dV7sKBRLo6kWbKHOgKOh9+y3L5r/0gLQGavHxxP88JDtzU9xmsjiwWUrBF3B1WIJW+JM+69KcXb92LVkyUPBYYb4CLOCYh03FTPFLbXy3tsnvP/umv/hf/i3/OSlw8vAEUqYt/TjOXE6xyKOC1mVfUpodY0hkQ10EmdPEqngojGzxMzoU4WX24nz3UQX4SgknpysGKJj8BEfgDxxjIOi5PmSdee4lWN8v6HkmXXfo2oGt4pytBkYNoGUjYk3FyuG1n1HlIgT4dnzGx4/fMRqHSnNi+fy5XOi9wxdx9AFnjx6TNKZo7NTduPIsD5murllGhMh9pRpZH18xO3umqcf/cgkAgLBgY9wtb0h8Yijo2M+/vCv2JweU+vE7fU1T954k37YMKxX/Ogv/5Lvf/dH/PjjD9mPe9567z1qrfzar/8qF+eXfPLxx/yf/sv/imm85Qc//jHvpMRxH3k6zmxvb+ijBwLeFzsXPuBCR06Z7W7HZnNEHFYUTW0QrzhpJqilIhLw/UCOAvuJ3W5PSRU8PDk5oRtOeHp5zK+9X+mHl7hpzzRNjHvz7nrzYc9vvBP4+DqRqmN95MnXhYc14I5X7GTPlCpjEvaTUkpgKgZEiq8Use5uF6BzjuCNEVDk6y3TARtrhGJjsxaUhS1elj6e+ZyUgvOO4CN9bwbg/bDCucxuN7YGkoUyaJMKi0BKiZygVEfojKWzWgVLNMPSmHww5D3NM9t5NJ8WLO0O9cTQoWpyL5NVF4Z+RcqJlBJdF5pMy9H3XUtru/PuizGS8tyaEK1JERYlnGtspormzMV+JOfUQCrbF+dtpJvTjPfBfIiE5kMECPRxYBonkyeFYMfr0LCopFyo1RG7aHKeeWrrnFBg1Q9UVXKuCP5gsO7FUeqM883q1StznsjXifWmB1zzXFHS7pa+X8AfRy6JaRyh6/A+ULJJnLwEvDPPqt1ual5GioqyH3eW3gi2zZi/zZwrkKgVQujIeULVWGalmC+WiJBSZhgGagUz8K6t8WCA5e1tQXCEKKgawFSrklI+/AGhZEv688GRkrGYLEgmEEOPtdhca0oa06m2kJGFwbb4/Qj+MDcvtSIV4nJviiUJzuNE1UqIjmnacXx0xDo45nH6j3Eb/o2X2A/4XvEeem9yUec9VQpFTIpOAuc8odLANQNiSnVoLebB5dYIBuoRjINcSsZ7NZDDT3fEB5cwP0pL/RCUVCYQm7dlWigBhTnPRN+DBlyOsC+IHwm9sbSkNZxVCijUVInSIdEx62TecRIROoJ3aDZ1QPDGFBRXLeAASHXERU9oElhRQRsAVtJk5tsCsXfksYXBaEXVW0iMQAwdXipBIgnsvnHmEyaiSN0byBG6RsSw+bndUwWNNk/IOrObI7fTjodBGE6OqM8iIqPNO6tDJOEbGzTUNZoyc56hVnpvhu6IoD6xn2+MObk5JvY9OY843zNsTnBxTc1NKaTGDDJPpJFaZ7qVjTnOB+ZZ2aaZqAVVhw89PnREJ/TDiloS3aZDsiUhulzJ2aTKVSpVCjhnYQuhUlMb64OjUsg1QPZ0nUcjFFKbz1pi3eKlKr6H4pGMBRs4wWvGIWbLUSDE0AD92lLtHELAyZoalYkbQtA2b9/gg1JrJhdPKY2I4L7aXPqrezxhciTzDGkaSyd39QGLlvu+swcH2dxi5bRslj1y7wEqzubKB89EbcXK4XsGSX0JbmSf/4Xbf/8fr366Hl5a/GYUp2Y+6lspLQKuSRcasnNYs6WRN+aGLkbo9+ql9v+/GACpdgw4NP8PwNIB0bIZ+f2mfyscDQySg8/WfR7ZvV1vIMOyHz8r4e11MOieKxcHe+qlcIODqfgi97tjX716DO5tiIGKHHgHXwIkvfr9xVvs1T2Tw/4cttloDIdjab4o3P1SAzm/dN8P3l96Byq+sj13v3cnsfu7UbgeYLVWhH8BxG06vOU4LvK6u+u7QXoHbdIdQLV8X9sNWil3Hk/NPE21peAITWpnE+CDL5qoGay2S71qZs6JaZqYxpmUMtN+ZN7ewPaasM+kq8jFzcjurHJ6PPDO4543HgrBCat0xaefX/Dv/uqGTy+hH1Y8WAUqli6yTzOilfHyFn15gQtral6BmuQOJxydrfjdyx/xG5//ACk2+UtqRpvb5DhPykUx4UpOmV0u6HbH4CP/yT/4NjfXW3xU3vmV7/DZjz9if3nFLIpfbxj6AV/MMPb0eMPN9S3j7pLv/uRjfvfXfoXVZoNuHrGdhc4lnNqkxIfJuvvPP6eevEk6spSJuVRKMZBgkVlp82CSw6VqKXfGJLLPFVXT8PvGPGpSOifaMpeW7xqd2rfrwWRq7XpwHpFgE69qTCVpBuQ21LSRVQRtTCfnpJlH+iY9WP7cl7RaYaZC83AqJt0LDawUM0Ct1eQUOU/UnECTye9acketjQsqxqTL7d52ck/4/dUR6l/KsoyWpTUmnAPvKg5PP0T2F+cmvRZjFotCcR2xf4s535LzywOFu6ogUlh1E53f43KPEJhVqM4RtSJY184S6kxKHT04zBvG/LkE0UIgEeuWmB1/9q//iM8+u6bUDl/Nl2wlBV8yWieSFlJqXiZOKE5IqTAnk5k4B7gm08B8fdy9GPeqFYqQS2bPjn2pPDzeEPzIZhUYouPIQdeu+6yZ2A1cb8+hKv54jTrHyekpNc1sx5FUZoZuBeKYxxHKRHR2bQ7Bc3pywvpozTRu0erZTTYZfnh8jHdwcnrMzdUl0XvGceTh2SnjPNOteh4+ecJnn3zKw0dvIL6y2+3IBR4+fgx5DzjefOtdqjhcVKIfGPoV43akePj82VNOzk7Z3l4zXt/Q9x37nHFAGicolZ/++KeExlQ9PTnj3Xff5M//9DMrpl1lt92RU+Ly/NoMpucZF+w+9M7MhadSzb9n3CPe4buuybDMFFbVUzMHMKELPTlV0rinRmXej4zXF5xuVky7DT/+dOb3fvWUrpso1ZPnxHZ/Q/QDbx0d8dHzkT2Ci+BWHr8HP09sBqF6IVkTGBcVyYVpsiJDRShZTPbgHNMk5Fqp+euvmV3Sve57oNr800CX2tgjVM88ZnLS5h2UgcXLx4CD6mJr4EDsvDHUsvmglDKzXgd8EOY0UUoysGRurCnFAHhvUmNtsewiUGqiVmWa5gZmGbMBtLEPaxtDFobpAoTcCe5VK3NLZwsxoCUbyLasozbAXyHGHlUDnhELF3HON/aUgSkGeHVoreRsM+KqxpSyY2PyQMGS5hBMutf8s5xzhOZf6X1kmm1fzd8JWBjMueAaRuLEgy6WD5XziyvznhIzK1+tIjmb3Kkux4SA+GjyPe/pg6ePkZIzzgtOYgPFKnOaCaEDseIvNXnc4k9oYJaddzvmzoIXfLgDrxRUHeUgszMLA0QtuatwACjB4Vwww29oiXocjMRLseZBKckYSzEaEFBTmzNak3A/7i3BSpTaKMQhxtY8sGJOFtsPEWNFh85SxVrK3TSOjSVlDOWhD3gPpcz/q9+Df5sl+trAl+YP6gM48whLWRr7OCClMngh9iuQ5n1FIQTl0BIX86YTybgGxiSM5djHiLgecgIS4ivOd42VDhI9c5oZNVNF6Kr5LllarTdjajGzZ++FWiek2VrUOlkDUCteu/aMdUTioSktUigyU5wjuoi6DhFHYF7aTfSuR7pIzjMO8BLR7A3MLNWS+QLkKIwASQysczavlOoIrjemX+3Mu1IS3hnO4HOACplMdrOxpIhk1wC4ABIqlRlUmXPl5voWtLI6Okbp8BoQzRRGpJ9RIBdQeqqrlC5ZKjMrAh3qHVkLt7stCmw2x/iwQpkQV0hSEE1oika6cdmSBYmIr+AglYwUawiOeWTMe/PFdI7oO2KJ+JwN/AuVYtGAuFaXuurRuZjETUCcULPg1IOreBELNcIxkYGMFqGkcJgXUmz+La6jlAmpE746pEQDE81PwUqAYA3gXgf289jGaY/H2K+Q6WJAJZjRfejoujVJEzlPFJWW7GjX6ldZ/hpSO9cQkZaAsdT4biks2iTetfK+FQsOwyiX+lzb3MCKCYNPrKhon6/c848y87Bmy2Oxi9iHlfsyMDtUcmBq2G9VXQyp7u3HL9jPsmynwH2zbINbGhhUbT/tiVQOTXkBlvQ9K9/kAGRYyfB6ZfMqqLEYsRsgdAc+/ayG/CJtq9jfB8nK/VXLF7+8GH7D4nJ0tyzH9A4+vDti0j6/AE5oA76qbeOyLar3naLur9fgy2Xz7iRWd3S6O5eq+xQ7Ox+i9767bMtr+3a4IvRu/XdSz2Vb2t58Kej280EkOVwX92FU4Weytr5Oy3K/LQykBTDWdp7tAm6vt+vR6EmHondJIQNtthR6uFYP/u0N9DDA2S4OA5UbU6YloS0A1sKcWu4buwrMn2eeZ+ZxZN6N7MaJ/XbH9vqGcntNut7zUis/OVrzZNXj/Amr1QYfO6LAfld4dpF5el5w0nH64BhiZD9ldvvMfj8Tj1f0seO4Fna+cu0K9TLB5x3u6BG/113xf3z65wzjDeoytVrRPhblYnI8TcquOGMdFmVfKrK7JE8jm/UjohP2+z1DP7Db3nJzcUWPMkTP9uWe3dU13fEJc6mM2z3T7a75ODi6wcP6lL3CKidQK8JDybiUkPNz0uMrUndEwpGzkotNxoEmg2znBA737NIp09qKHlVjLnmPEyE05qkT17DXBkQ6D0ScaAOOrLslYhp5WYxBpbL4QjjvWotBmqm5jZH2fY/3Eee9dQ5dQCS2z9ylJ9rDIdv9XhcL9ZZ4IgZQljKT82Rx5cVAOmNWmUsRvkOroyBI9ZQMQR1B3d1D6euOPLXxs1ahFm++C67SdyeAkqoVB7V1A1T1/0vdn3/LkmX3fdhnnyEiM+/w7htqruoRYAMECNAwF0lJlNeiZMu/+R/1r1pLtrxoWRJJkBJAUpiIqRvdXXO98Q6ZGRHnnL39wz6R9xYAitWULRZi9ev36g6ZkTGc2Pu7vwOSNm7UP32J9KI+iKEEAsZmu7DbHLldzsBgRvoUrBGsx9prL0dFGXQFiJ3fGtXYUEnLS5a7T/myJBSlvT5QqzJNC9th4OLijBCFJkopleNU3Pw4ZSRCXeYui0zengqElNyrrHUHuBMzD0i4/KQaN8uMzJnzsx3BhOs3N+xz5tE4stsOZDOYb3mMUAOU6ZbFEnnYcBQ3ck7BmJeJUivDkAjWiHgTfHecuwzZp/w5R3YysttdMg6BKI2vvnrB9c1rdpsd8/yKt996wlJnLCSW6g3ho8eXvHrzmtoq2+0ZWeCLV9eknBi3I++8+x6fffoJ77//AfMycxnca+nN9Qtev37BRx98yD//Z/8CJPD5868A4c2rGx5dXfPRex8w5sz17TVPri758z//Y64ePWFfF4LCsijPX7xiacrlkAmxp1NZJAb3EaplYSmNafJGYisQsrMxAoEhggZnWrfW5QAxkPKIqke4X9/cUsvPefejD/jpJ1vefjbw7qNrclgoyQHHEBNPLt4ihT3zoTBPRhJlI0K4WTg/DNRgHMynwFFAgpGSyzx1Les0oFVoLVAsn9iV3+bNgYCVoe6Ag9oqSXZgvSmIRKo5SD5NhVIXpmnx6XrVBzW4M35CCGhTVI3jcaK15gwi7gdkrTVqlyMKgRjFWRimp1S0EAI5j24YXsHlaMVZB324GqIDMqrqRuV58Hr7lHhbe6MtNK1ICz1VrtFaLzF6GMUKnMUYT4nToddSKaUOOs0nhk+KySV5x4laW09r81TDpfsggXQp+EAUKGVGxNO4rDObWjNC6EwncduQgCFEf8b2Y3ryKBUA97RyoG3heHS2YE4ZxMEbU/eiWqbSDc45AUIx+BinGdRmLIsSoxCir+uh9zjuhWikFFmW4vWSObiR8+rN6E/BYRjcs6U1hm6SbgYxDB14aqx+TmbBDb419BmjDylIPgTyUs2lrCmtfj1Lfy9luzunNWdJqRk5DgQTSqunIbmq21uIGZHc62XrrD7racUOvLoHbAfFVJiPC3VZE2a/ndt44bLOGDoAlJI/p9LgTGOF3JM/Uw6E7EbPFJxBZIGqnj5mIv6cWVyOJjH4awUfPmhTMJeWWhVCV7iIOqCgMZDq4syUlbEXhRSSr5EpQozdJ7NQzf3jRJRmEGKmtOZzYQndy2h0mVhzzyhJrScuOhARc3brhWaMaaBqI3b/NbFIMCUPAWRkSAMxVVpaaFmQJSLFB4c5JoigwdyO0hJBEiEDoZLUwSldPXRV/T7pFg2tOZOMVn39kARzZXpzTTC4vLwiEsnNECm0WGgm1JZ8KBcLNTrjOTEQwoCEXQcJ4XCstDYzbiISxSV5tkALtCoENeYykZMxEGhNWJJRckNioNbINjWszCzlxsHcOECvht23riHJ0EXR6kO+SHJ8wXCArypKJZrQtPdpBtswAJG53hFz8fPdkqdDRr+vVHw9CJahLDR1QLn2e5Per8cxkyRR50pLidIK1vOJnW3uTLWc/DWRREwDhOTDoZARGjH1EKBvsH1zqV1/MLKSPvo/uzIDVoAI7ycN8+K/T8fvAYF782FZAavT9zr41F3rV0Bn7ZcU1/KvcImDFytQ8nUIZd3Nh/8+gV9/6bPdYzTmsCMGKh576OgXK7gVZY065L4xOr3K2jzf78u95TL8lVMiX/+PFVZZPaXcV2v91H6A1nQ4fSCpWb/mRcaKJ/zlo/Eftt2/yqkL5CSvMzuBTqr938hJuvW/1sbJCay7PyFyYi2tX/j679jpy/f78u/a5xXLWI/5N3+c/Ycfq2/7djqcdi+as44lOdPoHlSiSwFcHuVy03ACqHqEfWfNrT5aonZKKRM4gU8roJQkYNJBJ8GlNPQkMx7cUH3q21qlTDPz4Y7jzYGbw8T+7sDtzR3H6xsOr95wfXfkj3Lk0RgYQ+XZM9js3LS8dZ+QFEYuzjecX12yO0vcHio//3zPXdwRnr7Ph+9d8sKg3R2ZLkcm8c+S7chvffz7fO/Ln0ErmFRUAkuD28V4OUdeNWO26J5GahxaRQ+3HI9Hj18dI8tk/Kv/7l8w7wvLXFgOB66PB67fXLOo8OSd95Czc0waH3/yFf/Zf3nONkVqDFw8PufLMHCcXOaiVkEXCIUh3tKu31Aun7HI4Ibszf+4FMLXx9W024L1Q+z3XLMTpuTAUw9JiMHBJ+lApJt/u4+ENwbr+hzwsZNPT+hgk3TgKcYetyrSgQrFQjxdEyE62BS7xE5Oi0JfLV3rjJuDe3qaT14No6CNPp2uWC3QFtAZa1OXhuWTia3F7OATgWKB0vwApODn072u/v99B/5v29boh5WhlZKQiJxtrpina/crEWcanmTq7UA9/My9E8ABFP8WIQqbUdntFvLdQtNEFkAbK0s5Bl87RXsEcvNnYDIvSHZyIB+eM13/jHK84Y4N73/nHc42A3/644/RUknnI2kInuhUF5bWXPoYgBB7SpKvOSEmiN7IDjlhTaktcgrVEBDxievpuVeN2/2tG/Bebggxw5N3+Ozla87qxGWENETGmImqDK0xBmd/LMcDVSsmA3e3t0yLkhJcnW05lAVkBrpkpDePMQrDkIgUXry64fJ8y2E/IWSqVd5++oxp3tPUU38+//nP2AyZT37+ZwybM9579x20KmU6sM2JOAx8+fknvPXsXYzEF19+wZgybz19i0+//BQhcXN94LvfHTi7vGR6+YqlNB5fPWY53HA47nn/vfd48fwrHj17xu3NLb/92/8T/9X/+f+KLcrHP/8Zl+cXnF/sOExHCJ6IFAQ0RD+fQ2SjG5d5LRUtC3VObPIZm20iGNTiwIbgU3ozg2ikGL0ZN2NaKlEWrl/fsABf3P6AR48qWX/MoAUNCbPCsyfv8NHTK17ePqdIowbl1ipDijAtSBLGBKVPNFK/ZiUGT9bry4Sax5EPckJivtWbgwpyqp+8AfdrX7V/XxxgDzkRuwG0X/uBNeBE1b1dDBgGl3s5wOCAUKutm05DKT3JtCdCmRnDZoAVrOnXdtOGVF/fY0gQ9fS8cMbNKo2H0gECUzfvDkG6n1NzfzkiKWcHfLqfk5kyzZOnw6WevtZZiTlHr7DNwd1S6kla15pfa+41Vck5dYAsMA5nhNjZUSIsZUHVAZ1xyDRtqLqfSi1LB1UcuKm1+fHuMqcQAtvtFtXYzbMT8zy7fLEnv8XoQNzKlFJt1ArLMtOaA1bj5hF5GNC6dG8VQ4J/viCRlByA2IyZGAK1TdRWnBVY9ZT266yj1M9BIEbrnkxGSgOlzCcTca93jVrnfmwjZaknMBPckPxhU+S+Ws6Oc2mTA23D4IDRymRbJZDafA1Y/UCXpa8B1mWa9GsMOfkoul+YXzOCUaqDZM4Ay86YasKYRsq00Mq3G3jKeUs1I0UjRoMUfFDnixPZ4MyCD1kiqPj9lNNq/xFYluhMnc48rOa2BDmlzvT1+wU9uiRehdoiQfOJsa0kgkRGKmILFoSV4qHBCHmgSuvgjBFycuJGEE9ZE6FqJWYcjBZ8YCcBIVKteyHhXpJZIIp7rqUASPeooxCCIZKJIZNKcJZq6BLMHAlB0Vq6p6BL5mpwpq0FJx4EdQuMFjwAhj4YtdSQYuTgptp+TdkpNEpsXXd8HT3evqFNe67OtmzGCMuCsnTzdl9PNqmBHDECTQdUI0X9Gk5hdL+r2X3Yxu0GCQPHqSCi1GlGgrJNzT3gqqBpoJSFuig2NnZhYCgZKUd2Q6Rd3xCfKZadtV1FWXQCrQziHqlLda80sYY1I0SvfdvS8ZMoNBQtjWSREhuSKyn38B0WJFeEASyTolB7qI7DMwMSe9AMK8gohBTIaSCoQFRny6UutzMfXPgg2T3/qnnacUC9nwsDc2hoFdCEyDeDlH4Bj6c1Wt1OwV+9Lzh5Phm9EGwPaoDez644yD1rZTUdX8EsOf3MWmAH3G+ms3z7b/lrhhOoYPdAi51+0L/ev3YPU524Gn1f/yozx7V+nYlh1mOm++doLhMK3LOT7mud/rDoJ+q0X/3Ehwefj3V/WfdXOojXzcLF3zv05jCwSun8x1XN2UXmFMl7fydoZsQV/JL1c/5VqM1BxFXSEr6OzHVAaCW/rKfIvy1ddtFNjM3/ruqA00Nwz1Zgib8KQkn/1F+zzXoIOp1+7sF/r7KdB9+9Fx3yNUaHPTiuDsbdXx+6HoEVWFxfbcU91ous77U9/P8+vbmXa8rp639TNpczrZCcA0khrJKjgJzcl1dvJr+mzUdy0E1QORkY9/tAhNXpa9XEWgcqehDF+o4Pju6KMN//W9aGsjXasrDs77h+dcOX1xPLNFOmA8txoh2OLHcLn8TMvx0GLpMwxEgChhywtqAo282WUTKPr7Y8OhO2KfDiTaXkCw7DhjhmLg4zN8+vuUo77s4vKe8+5qO3X/Frv/+HpPnWWTVds3moyusJXi2J26YUcR8hNeNQKrqf2d/OpODxsJtx5Ef/6X/KsMv83j/9bW7v7ji8uebnn33KzVz44OUr3v/ou5y/+x77EPnjP/kpu90lH77/hMcX5xA23B0rxAJSSFRmKcjdDfbyOcvj95iyMFWXujYTgvi5yWFdNwxrup4d/2+j03FdEhdESCEQ6dNQgk/lOvPJAaDAyoJci2PXbVi/761fD33hD6mf365XPwllV/NynCUqjl2FoH1NWtcCj99F3XNCdf0cSuxeTx5DWzFbiLqAFi/ewojEhMWREEeUgVgjDTdfr7WAVKZasfTv48J+CzaxfvwhhUjMRghbdmdX3H721SmJ1c38Y6ezF5TaWUQ+3EjR2WMR4WxTOd9UbxBNSQRm6wxiO0HOPnUVpUQITdnIQmqFePsxh9efMU/XiAi3N8InP/2S73/vO1xdZq73gfHy3EHP7guytIoS2G4yrYVu4qtITITo8rokEavqXg4ivZI1tMvtQ2eGBEkwgNbCsc6UeWJ3ccZZUVrMTCEw7ra8vH7FECceDVsGenKjFJ4NkYPBYapsLs759Pk106Jcy8Q0HTg7v+BiM1KWhbu7O7bnI/NUmOcDIEhM3FwfQY3LR+dcnJ+DGdN85NGjt2jzzKtXr9icb7i5O/Lm1RvOtjtMa5epwv5wh341c3174NXrO8627qHx4sUXfPHF52xyZjtErl++4ocffsj+zRtMA0/ff4f5TWBaZv70T/+M5faOucz8w//kH/Lf/D//H3z6xXMOd7cgwieffcxxv2dIyVO+ppnzsw27s42zNIhECQwpEk1pVZmPEzENjKlP6ZuvLwRIIbi8KCdqqV6XzI3SCi1GDnc3VIVXzxuv3/4Nnm5G2t2/wexIkMQmKj967wm/9xdfUJtLUMwicxSWVDizxOM0kGOjhEY0o3S2n/tXO7AxDAMpgsnC9uzbn2oXY6SuIKtXQKwDwxDEo8yxXjdWapkcbNf+h1WqtwI8wQM7VjCrU6oEYRzGziyIlLIw17kzT5Ta/X1i8lpArZ5qm7v9nuRTC78Xk3v7iLgkU9VTkk7MZhFKsZN0y3Bwxc3TlRiNaZ5OJujgnla1zt48j/4MElNKc/leSqn7DzkzdhiEnEdicCmrdgPrUiuizRkQQTg/3/nvSGSeJ6Z5Qpt1sMZ9BHPObLeRWhqlqqc0dmbQ8TihWpnn2P2lUgehYvdX6g2iuJHzkJNLA6NSFkEkcnt7x8X5hgDstuOpwG2qLMuxDwYim3HDUhaQyHazYVDYHybmxQ3dQ+jG8uEeWHQ/LSOoYRZYlrmzDHoPERzQa81IKZyYxSKxM8f6c05WaxS/hlpTcgr9+vJrMcaMGQzDyPF4ZOn7JSLkGGlqXXLZmJfJZXraoPbGGSNEIZtLHN0Y32WiYs4YCYKnorbKoR4p9dsNPI1pyyiRYEdCMjS6bYO0Qk4LgzkbSgmojigRGRywjBZoc3WWU6CzjQLV8EGOKsGMnBqkA2oFLUqT5r6W0vx5FyOlQTPtzEEhRJDmXj0SAK1sQvL82ep1X9qOWGwszQ3o1SpBjUyiWiPREAuoRCRkIo1NqkBhkEyQRDUh0DzMQ8TN700JMiK2Iccuo7WKRdAwuxQwbzEZ0OrXsUmhiBLF680claDes5YgFCsMqZtV1+ydQVAkFq8/Q6TJqpiIaAhUCVwfb9jfveTy8hGXl1fcvP4Ka83Z/CZgBQ0GmsBGpHUz/aCYLG7oL4n98Zr9/o6LR+8Q8xnHY6TVQqMwDsJSDm6SDmhcgIwulc1G2JBZqLRgoAP7m4U6V2ISLCRmdW/aKI2gW1qXC5V2ZNGKxOTrrUXUYJsCJkawClYxSSw2MZUZMciS2CCYupSwaScBhdDBRqB/DdSBrRDQPlC2plRVLDWCClKGU2q1UqkUSqsMljs71TArlCouFY2VKEoQl/F9k+0XA546wBQVRyqtN/HqdGgQp4mdhsdrU06Xbtg9kCKr71Nn+pgRJLASL/zR7MCWRzmvr+PJeq2DC15AcirIeYDQrQDIujny50u0GfdNGL3T7Y13/wlOjXf3npHgUcLh1KJ3cEvuAbh7SdJ6BFYPKOOeUdI/00MZm4WOLt7LzVZJmJgXIiewrO+umtDUJSzaj4V20Cn27v3+8z88EvdSuxMcYOv73f/cQ7DI39Pfz9Qp4k3tBDpVfXC+11fpLyUreiVyAiTkxIa5B53ka2/6l1Ch9fx97dP0q2QFgtbGt8vG1nNsyPqlDtJp/ym5B59O77Uej3sAcm3Sv34cw2l/7eGH/VZv/Xx3uqRPrnlwwh6c8ZMsr6HS9cU9mcxWFo098GuQDj7111qTTlbTUcSp+PTJ2JqCdhJ72vr3evyVWhYO+wMvX13z+RdveP5mImAkWWilQm3I0jg+f86Po3CWjAxuGn6xoRwPLK0gg/sEXU/Kvhp3e+WlZW4YuT1W/vVXdwzzxNkw8t7dgf3bT7h7vPCP5DN+eHjDUo5kPNmrtsrdAq+XxJtaOahSgz8gaq1UBZ1n9vsDEIgIm92Wp8+e8PrpI86uznj+k5/x/IvP+enzL3kzVV7tF15e3/KdsvDkox/y9NGGMUdMhd3lBeRzT8trC0EKgYLpkVAWws0L5ts77rYjc/eaCil5qskDzzdr7o3iDLZ+rQZxCUsQ8iqxM+vnrk+j+z1wApVVnakW79d2kxXA9qmTtnvgPcbeXHWTzXURDn0SuH7NnwLtHvQ1AW0YBWsT1iq1uYeEtg6qr6h18N+P5iBJCKMXEGmDxYEQt8Q4oC2hIYC1U9qiS1eqR/h+2+/hfo8MKmhwP4TtuAMxmk5AgZY7S8l9Yvwe077WNUQTaEZCISikYIyjm4A2c8NKh2WCr/VAxK+d2q+Bs2DYcmT/5mccjl/x6Czy/rvf4Tgru7Mdd9evmfYHhs3ARcwEjSzlSJ0rizasFJK6H0RdFqxWEPcCgdAlkm5KqzFSFVLSPuRxjwhp0U2KAbSe/P+KCre3e+6Of8puHPhbv/Qjihqye8Tr22sKwqgLj8ZETO4DNRB5NAwsAcKzHS/2E7UJ47hjmZUXxz20wlQiz8ZEXTxZ83w38u5771COC7osvLp5xXfffZc/+clPaBK5ejpwfrZjXhYkJMp8ICDscmJSeHN34Ob2iGnjkVxwM01c7h7z8uWXBEukYeStiyu0Fspx4cXzL/nhD/4Wph6l/uKzj3n25IzjzcTFs0co8Kc//gs++PADhuGCf/nP/wf+zm/8HXYX5zyWt/mjP/gDcsoc7iYOdzeAsb28YGk4uFAjQQeiJGpq1HlhWQ4cDtaZib7Ip+7J1rTRSmPIoxuB74+MW2g7KNWfsa9evuJi81v8d//9H/Jbv/b3GdLvouw5HN/w0Xtv8eE7Z/zBz25YZshDB1wyHFslTsLT80w72zLVmXBesBo5ThCip//t8obWjrQwUez4v/st+YtuDvaLk+hP65ydpHd0tpOJkbKnvqmZ+4zcaZdpbjCrHaRNDHmDEGi19SEnXFyes9lkSp2pZaH1dE+1Rq3O2JnnmUFGUorktKFp9deQhODG1SszSdV9h0yXDvK4DAw8FU87qxZzQGazSczLwmazY1lmVBspDSeGTgjBJWr4s+UwHcgpYeLgHPSU0tp6ipobZmPuOdVa7XMqQbVxdnbO8XhkmidSztDBjiARlRkJ5pK06sboZsY0TcxzwYcgfa006BmJqNIBIOmJgYFaneHhwQCBcRhYyoFaK5txy1IU08Y0HwhSOB4FWdnAAlpcdtescTgeXGY77JjmmWmZmabZ18LQvZBmZbXv8MS63qNo6/srpJS79NX3fZndT8o/pwNJOfeOpXtFrSwRB6lKlyxmpEveV5DLj/Whs5+8XUzJGcqGnx9DGMdtT8E7OgitRghuTu6m6K2zefyctC6Dbx3AnKcjKebTOv5t3aK5pyIWQM33mUJKwnbMSIV5mRk3G0xdYtpMwRLWhGSKjDA3T5GMEghxc7ov5mVie+7s9armgIDiBuRmPmxTY9EFRIkpoLaFCFnw4Z4ENmnD+eUVc4W2FHIGEaVUg7ZBzHkrY1BnQBnIMBIlUIqxiRsWXEJZTckyEtIWwWhlBqlYFFIaieqG3yEoRapLvGKAlLwOIRLETcPHMSMUSnPpfhQlWmRMI7XMnj6HEmR7UhfV7iUWtBA4EmKmWaCVQszOykniTKvjdMfN8Za33n6Hs7NnvH7xcV9iBdWKSsIsg7l3lZpjEqjLoFur7NsRnRsf3b7m0eP3ODs7R9WZVcvinnaDZBRYlsq+NYZBGEQIc2S+XjARUh6ppfBqs2deDlxuK0mdmF8nRaQx1cbddEQSNKsgDgYGPBCgakUskDVBMVIcqGIsVrAoWHNvN19+kzOKpYIYMQyIDZSqjl20QtPuo0chSiQSne2UAs0SQT31zoIPL5IlNxqPAaILLksr3XfTB2QpVlR82KnfkHX8jYGnau6/FO8H5n4jniCAk0XrKVltJSGJOpEoyjpJ94fsynjoRALXXgb/+ZNZt0ARI5r/vje4vQh98EdlbaphzchaxWsn9QbdL+lBf2H9w3zN7cjc/s3RGEMaJITF1DXp1Qgd3JLgSVIxrASQFdLwzY3LfG98WHi/n/I1KGVt1exEJFkZBSfGka1SNtdSN6/T/G+nSXkEIh2gWhHOv+6EnoCG9SysHCFOxcuKn62fqKnrTEszajOKespQa6tXzPpyq7Ggg0uhN6frO50+rd2fl69969+xv+tkkPWcPTgupz8PIKkTC2kFpTolav3/9Wesx8X/Zezl3gvr37U9AC7/Rmz9pAaBEBELBFZvBvVkK2v9hPdUCRxkakGRVd9g/jUDp2R2vbv2kyDW/bO6PEo7Ahx64SOr6TguyVoRq7VFNlW0VLRW5nni5es7Xj5/w/5QGcZE2rj5tUsEF+xQefWF8W+DkVDEFvTtS6Qtbs4ZfKp5c3vkbq4cZ+G2ZlpUtFW+OsCFwvvbxvH1F7y4veOsBH51+zHbm2uoR5oJLcBSjGMZ2S/GXW0crLlVZHQ5TquKhIpUA3PzbDPl4uqMx+++zVyV/TTz/OY1d/NCzC7p+firL7mtyneJ/Bfj/4lHVyOKki63HDY7pqqMNCaphNiwWtnQCMcbDnd33LGjEVECySCm9HWUtoPKD69oh5VWabCRgqe1yLqSG/2aoC80DigR/MEI/R5RdR+lh0jzal7f/SoQP0YrUhugXzfOtArBpzpK69eXF0TWFp80tUZt7m+iRjcFlxNTK3R2VYzRCachQ8xIGglpQ5RMiCOlgdYZK9WbHHkgF/+Wb1F8OmV1Q8iCWWW323GYXnmiDpnWz42Jdkmk9bVPEBJNGmKdcp8gaGOTCiFUSjgylsBdiJwjiDY0RII6uF8DJBGy3bDff8bFrvL4nY9IeWAYNpxdnPH6+g03t9e8vNlDGDgfNn0SriymHFfHaPGmrim+r2FgDTQMMaLN142Mkke/l6wZQ3SGbxXQJkgo90C3xN5cC2026jzzr//V77F99IhM4KMffMjTZ0948+ULvnrzijgXLtKGPEZ2omwCvH9xxpPdGfup8sX+jtupUMtCVaWp8eLTl4ybwPlmw9m44fr6ho++90M++9mf89477/LJV58gAS62I7evX3IcEhaM/fGONO744sVrWk5kCWyHDYdQIWW2cSRH91QJkokYx2nharflWGb2R+Hl9YG/fXbG1TtvcfvZHYENU4mEuGEpgc35I57Vxu/+zu/w/R/+MiG8w2evXvFUjOXujhQHDLg9XPP8qxe8GwJXy4xKJIbENg/MFJ+ENw8PMFNKmdjuLhiGROsDlyiwVKNpJQ8JC8K2jFirtGpISGzGxFdffMX/+//1T/j13/xHfPbyc37pg7/Psvwe0zKz1cY/+tXf5JMv/zlHEyQJOQopGTlAmDwO/CxtKUOmRiGKsGwLm7xhk5VhKDBkplk5zt+4nP2Ptt1n/kofgK3/7c9a6cfcgP3+yPX+0IeMPt0ZhrGHLLh/R4yBEI0Y6B5Hbo49joFxjKQcmSYHXWKIpBjdnDoEdmcbwOvlMhcHSHsSHUDOuRt3Bzxx1BktqyfVdrv1JMrOPmqtOck1NKbZGVTLspxkaqWUvs+xN9pG6dK4lAI5exy5D1e7tLUPBKZpYZ4XUkrstm4cbGbU5mug9SHYOA6UUrvJujFuMtvdiJlxd3tAVTgc9ogYu90ZF+fn1Fo5HCeOx0OXLWZMHQALnWl0PBTuh8YJT5Vu3O1vKWVyRpE0NzOnEuNAlG5c7m0kOWa2Y8JEOez33B0OMAdynknZgawUnSUN1tlJXhuF4IDesriscbMZqa0yBGd4DYPLAsEBSz++tbPiusdSc089/wywyic3m80JjINV2nnPXIixA4TaPLGw1JPBu7OlE91WkjXMY1VMrIDlsiyc7XasYOsyzSytkZP7Sa0g2S/Qkv5H2SITEgrb85FSoTUhMDhgsxQCCUsDTQJxcMld7HW3BGGxigUh2o6gUFpgqV4fKaBkSnOfpiCF2IwgQ8/BNKoKViCJJ7hanTzkpXX50wBVIovB7uyMgUC5vvbDKkZsgSRbTITJitcDQNRMVn9WGS4xzxLQGBENTKWQ8oCEjKURCzAMRivNE9qGgbvjDU0USZtu5D/1piyhVnHbsMkTSYOgFp3xlpzpvJWBWWt/wjSolVAS5zI4w4mChcWZRCJEjw0EE5IarS5UC7x58QVvvf0DNmePqOxQXTBZaDZhEZJGogpIpeHys7LA3fFI5UihEnPjxYuf89FHP+Tp4yfstmccZ7fuMHPQjOay7xASoThruMXIsiyMm0TRwlIDr17ecPf6DVeP3mFIgToXXr3awzyRhgM1B2Y9dM6LMKbEGCBMMyYNs8SxREINLmsPXgvR3ODe1JgXGFOg1eIKNDNCXUjJiQatVgKNNCbmpTHPM1qM7WbrdhTVB7lroIGyUMwYwuiy6x5IkNOATg1tlSB6ChQL0WtsCd/MZ/GbA0/qCSgrCWQFiRx1t55WhPclct/z+FCiRz/31/BUKz/I6veDNy62gk4O6qzgh4lL7jqeRQydOMFD4UZ/nMsKOjnI5dtDYOAebOH03QeCrhWrWOUeD8EU6ewjjNBcwypdhoStcIuekvBO7yjSQZh7oOWhMfoKqsB67O5BmpUk5ItSZzdp6ClyDgj2vgDwHKKVPSSnI/SXD4OdHjJrQwr4Z3sA+H3tLFqgmbA0p/LVDkA1vTcV99eQ+4++si3Ww9gb2b/G73w96P+Obzz49l8nGzx9Sdav9J53ZYet7Lr7xntlKa3fP3mPyddfm4ef5+vf+ffu77dtk5O3kxtUGopY6CXwCt55XLU/HBOIM57QHnHezTuta+cc2/S7MOAXZT+0p7vKfX/6Fa2Kxnb6fcd2/fsq7uejVsAqWhf2xyO3d0eWqSBmDCkyDgnRRBLp64DRpgMvvnjOj4fI2RiIVjgfhRCFq8sN1/vGzbRwPBZui3G0SjtEtMwcESrKn3xxJKIsw44P3ygfPH5DqLMDKwZIpJbIYa7cHCtTE2pKNCrWHLRr1RBpJxBWQkBb483nr/jt//a32V1ccj0duV4qTz74AR/84Jeo056Pf/pjbqcDr1694rNPXzBsPuZXf+UHbLYjtnnMvlQGJggN0RmrjaMJ6VjZ3x7Y2y2SBmIekRg7i8mZqNHuz8lpWTOXuokmX5NX6aSq+wD1SfyJfykKVKD5P6N19pNLEIPJPZDuXGtgDVkAC9GZrl2muTJP3U/ETuzOIN7gq1a0VVop1Oo+JE2V1lOK1EJ/0AeSSR9wJ5dyi2ASQCISB0LeIDJiZGrrRq5hIXaansja/H27t1CgBiFEj+ttbIkhcXf3ov9A5ZSoSl/DTTCFgKddBQsoglTp16mDgFmaxx9TyJpo4lPzHNxcnAADcJYLhxefcHYxcHl2ye31LY/ShuN85Hb/hhw3fPdXfsSb56+Q5UBbKmLOdKqqTsUngRjLXKlUCIExD1TMTVJFyFmozQEm93RSsEhtEGIgWPWBhkITCNmB9HuPAUGiT9rvbvcEjEc3t9zsb8kIV2+9w83hls+vJ+Jh4vEgbIeBhJCBizGThkc0AoflyPW+cnO4Y5mMeW6EVAnzRFgqN68/4/HVJR//9GMuLi+ZysxhvmGMwrDbcbfMbGNmHEaCHXl29SFaKo+fPiWPL/j0ixfOABkSt6/viBIYxwwYh1J4/M573sTXI4fDnvffex/yG7773gc8f/2KDy4uIHqa1nvvvsvv/e6/4vzynI/efY+/+OINx8OCtkQTsNqgNMpizKUxtcIYgjMxYiZKos3NTfpVKKaggYWJLDuIwSe95ufVJ6UQgjEMkf3Nnv2trwXx0Y7Ls5GffPYZGoU3L5/z9rP/hOl6z/mjT3n55prvvPNd/tZ3LvnJqz1DGBkDVPHi1YbI3b6SbyY2T3ZYK0xSaFHZZIFo7OdXpJJBAiEN/3vejv9Bm0lDbQ1ccC+1NSS2qT+P74eBIObeS4Z2L6PZvTRVOjPIGDeBIQeUQKlu7L3Z7lhKYV6KNxaGs2nAWRi1kkTYbrdMc0FrJYnXlSEmHOwQYvTQClM39DVqr/uNaTqeSiD3P4oOIkdvjFSNZZkZx5FSSmfZaP/ZxLLMBAmcXZyz223c3L42aqm0VhnH0Y+ZCUPekNMG8LS1aT5SmxthT9NEKUsfHvrwJ/SQitYqx4PLwFZ20DgOJxbR/rB3kKZVLi4u3MekeniRM4xgs9kihD74cF+o1pScM60qObtfVtPSvawCtVRiHjhOEzE4c2wpBzbjBjogdfnoEbUUllpPvlye7OcMqWVZyNklh6oztXbTc/Hm9jgdO/vIQb+cB2IMbDYbSin9Tw+UCM5cWOWRMa5SwnwCBkU8PXGe55Npu0g4eTztdjumaWWvZb8+UvZjbQ2zI4YHXOQ8kFL3bez9hmpjGDZM07HL9BwIHdPQE7QM7FseEJAaYa2J00giEc2BF6vN2WVDoNmR2o5EyUQ2FK3oKMxSGDQSJTNhVBIVJUhDcMm7S5qLEx5sh9FIAgS/F5VMsozUI8aMMJHZICHSglMoQmjsb19C2pDzQKtGaELqHbOKQg6eBCoRC9pTFQWVAVO/tzQE8jA6u1JTV7s0tpsdb739Ls+/ekEtx94/jISgpCG7+qa07sksFBwYShL7dQg5CDlFLEIcAlKEUKCY2yvE4IbsrcyQMy1G5gJtdgDF0yNj3ycHQpI0Xn31MfajPbuLDSEnlsl6n5GppSJJ+1qbqeYA3PVSWRYY8kApBzatsb95zjK95smTx5xdPKVW4+r8gsP+mlqPoPjxCQaz1zealXEjLK1RzdeASQs30y2HZU/IESJM2ihlYUsHrkJg2h9YVDmMg9fbZWETheE6sh2usFZA9i5YiYGYkrPRhkgVWGZwSfQIFigxIHUBWaAZuT9bNsNICwkZIjlF6jwRBfKQCdGNw6dSUFsoKCZbjEQrxqxHl/3FwXtCA63u8VVj8yL1m9xG3/R+OyWWdfaSNytgoU9iWfvwcJIvmdnJA8kn23YCeUR7mgXSpTzSmRKKSUBETwaSAX8PDZ1x5Tb8HdnjlLLkYQ+rd0lveL8GNMBDSMa/0UGdk8SnA0An8MhRE1WhSegNjvj0PwQeSupUFIn3zKGvbadGTE4N+9ekdvKXAJT+ArqaPiGd7eQU4HuPJzmZrK6je+nHXbmX2nztINBNajtDJXRgr7/zg/3wE6wmFPN4Y5fVCbXZCYDSB/trp/9bAQc9nRPFTky2+wP01wM7f2WT9dw9+DgdYLqPX5fTm9v9T/CXk/usv97XcKMHOCD92j1BiX8ZYOrH7W8Y7tQ3OU1WATf5BVYadlvNYwk00X5feoSsiaDtATPOgLUppBuQ2goBW2dZdL+oB2i09KlYP32sbElWmZYqaPVGa56YZgdyhhjZDIltToSaHFQJDmYEVerxyMtXd3zx/I63xoHh8YiIF2rTsnBcGoe5cqyNheYxoFawWtFWeH17A3Uinz1iLgnajG0d1UfNtdWzMi2BUvq0Sr0B8iXBPQzE3ExUCNQ6EzHO33nKj/7zf8Af/ot/ws1hT9iecfHW25w9fcbhBnaXVxxubnn15gVLmzExihrjkDm7eoevbMN+niBWYvTjk81I08KbV3teLxseXcI4jAwxsImBIQixH1vroPSaaGhmxODeXqtvnZizzcToC63T8z1dZJXP9fPbwxfAGaFN6dI8VtcS6OdfuoGkaYPq5okaQKMQox9fseZroFpnSTnwVK3RpJ78xcJqjs1qUh/RkHrSknuKNOmLoWRyHEgxIzHTNNNipdZwP9GVe97Xt33rwdWMuy1QifECwkjRCUlOl0fdYDSuz5OeJPg1NqoFNy/uC3GMkRRASYSojF1mnHpqYI34xDIIMr9giJVnTz5iOR7I44baZs4fPeH27obrmzfclT1D3FEZiaIsVSlFMFyiBdaNt2fQgopHSQeCM4kjD9JsGjE5I66ae0IQne0UkxFloJXZC1hdhzvuDREDzOrPhNqUn/3FJwybxNtPn6GXcPX4Ke0yMh3uePnyU3YtYscDl9vNqegOIbDLGy4vB6b5nDc3M2/ublmWhX2tnG/P+PTnX3B2eYGMG957713G4TW1KXfTLXlIcJiZjoXt0y3vvfs+WpQUR7748ivKPPPd998ljwO77ZaXNwd22w2Pzy54tb/m/OySGCNn2x3lCK9ev+ZHv/Ir/PF//d/ws1IZtyPT8ZrzR5e8efOaX/uN3+D21ff4N7/7B9jfFc7Pr7h+uXffHBLzcmTZF68fJBDDxtO2RE/GtYFEis5krfOMmfnEe1nYnEVf8xukIRHFqDWgLSBpxiQ62LE/kFJgs81kgaeXT3jnrbc4lIFXd9/BxpHd+BnT8RW/+b2P+Pj176PNmKqvpwpsNyOygZvjgk5KC4LGBQtwNzdm8zXrME8UIA+b/xi35S+49SdeT4r0R0tvzB94booZOUa2G+Nmf0dM0YGHnPwZ3E113YopIBKdZRMMwdONxmH09MhaPb0t+M+udYuiTNPBWaB9ONG6jNNM3dia1WbC67aUVkCnESQCHg5AH/KFEB086azneza6nVg1x6P7o60FgWrjeDiwlDVJT8jDQG3tBJy05pLOPAxM8xEEdrttl/FpB0h8oUspU4t7ES2Le6mlFMkxU4ux1AkJdN8kZ1w8unzEcTpye3cHhJMUMYj7D4XgjJa5zAw5A4FhSH4eJJIG6cehklL3ZFKIIXkNLL4/2llgZakMFmkN0pC9zsSIObkMXCtuCu71zThuTswyNe1BIIEhjxjaB0niUqH9/oH0jm4y73Jmbd5TaJfoiLikEWCe5z509s+fkhusr/5XzpByhcOyTA5W1eZNuMVT4mAIkRwTOSW0S3tU3YR+ngtlKX1/EylFYvCUNB/8frufw2YRgjEthRATORpDCAxp454/c0VbQNX9dVJw83HU+6UhbSjqxv9qM0bx+6gFb6bV2dytuQQ9x4Tk2iXlkWiBLBGThGqCuHUJdDOyJEIzNAmWjLtaMI3kOBLUiQUhZEJKNK1o9mS8Za5YMKJEAi6p1jaBKVqFGJyZGcz79HE7stlueXR5xTwv3OwrSzmQx0TVRoogFk/sWDUlxkIMzYeE5kzZECGNEQsBQiVIZQxG0oTjCAWyJ18WKWhQJMVuRD5i6tdNbQ0JDtzVpXF9c8P+7sjl5RNSPqMd3xCle0c6x4lihSDCopXDtFCKdrCoIKpUEtdvjry+fs324pzHz56Qe1rcn1+/Rq35cKV1/7IslFLYRA/ZWpoyt8ZGIgwb9sc91aqzvS0wTzOIupLEjPlQWKZCE0VFfOg6HyjJW6dpAW1Gq5WcIESv23MYGcYBNfdQldxTp4EoikSFpFhRdvkcipK0YKERiSgJbKFV935Kg9FiRaQAM2pKxWiavLYszVlYktgMmVaM0hoxdhPzb2jR9gsAT3JqDleJQhOX2q3+LhFY/ZC0/7ffMD0+m55Kt7IBcEwlcsKR4AQWSQcVVraPETvopUFoXSefRLqEz00ZQzeqDX2A/1fBCr7+QOTB36tLN126tyIUXXoi9J5YFUv9awbEQOiyIe+xbUXI+v/6RL8zilYXqRPs5HdnfxT/1YVX1z8dbGoWuscSJ8NPwy/4JD2FSOw+XYwH/3fCnvpRXr2yTsic8LUfN6W24DHtTVgq/d/OtqqrN9Xphe+PubDCHJwAul9kW6Vydvrv+6+t31+N6P/SL/Zz+tcxnvwV7z8fD86znb538tJ68Fv37/lX9/FvwvbwDNnXEUY695q10PHruHmyowbQisToIMF6b/brOjwoFmwFEeBBwfqADdOldG4U3O8Nk94fr8W40nSh1Jnb5cBUqqfUjJmL3ehJEXNEYoeHg1+/tS68ub7mJ58lcmocyxlRG1++OvLiemI/N45HZVajRpy6qwatEtpCYIE6ozfPSWHEnhlL6EGy4h4a85KY5sBUAkUDNbnn2eqDUVojDY04RCRC6lGj08sDf/jbv8vd9TXXy5G7aaF+8gmvX73mMN9hc0Fr4a0P3+PJkzOmpbGUym6z4eq977LoGXGGFAtDbog1jg3y3Li+mXhTZ2LMDMOMbAaCZTdufLDurAhEXZMu+uLnsEtnm6l77Tho2IHpIPcJpSa0XjgohomvfYanCgXxIYFPUHsap3pCYW2VZVmw1sg59CJOHBIT9xNY96vWxtKny50ci8TYp8UOiEtIPp0PEQsela14KpAJ7vMUkgMoKaEaCQl09mQg64MNWykH3/YtRcQGxnFL0VvOt+e06v4bkXXdr3AClm19jNLwqGeTHU0TqV07NidCGjKyarRjQ9tEjiMW3MvPMAaZkXZkYOLRs2eUaU9KiW1LGI3D8UhOmYuzc/ZFCcmwWvw5of68juaW5ohxnBcHnMUNSjEv0v06dcNkCUqSSDGQ6CbH0fFM955pMzkmau2VRZe9Bgm0BlXdryYEv64tBObS+PTTL3jx6gXnuw1nl084P99x/uSKMWz585/8KS9v9jx+dIkFY8wj2zGBVC53I9th4PHVljf7Pfv9xHFemGvjev+SFJUvX3zJ+e4cDnvGNDDEgXceJ5bjkSePnzAvdxynxvl4xstXr7h6fMn5+RnXtwde7I+89/YzlqmQzzZsKYRx4Pr6NYe7Pee7xO3tHUOObNVoS6VuthyOyuZiw+VF4vNPPuFHf/uX+PnHP2Z/e8vLVzeMMaHiHpXT8cg0H9lsImMOBG1YCLTa06hWtqI5ODaMSqsVNTgeZ0iBcbvFE7rMgWUgDRt2FwmzxN3r17RSmKbC3WFmt9vx5z/5CeNmw+Vu5Cc//zlze4uLTWYzvuA7b1/w9u7H/OTl5ElHpWExYqEwiMAQeFkLDRi2QtBK0ULSQNbIcYGZRpq//R5P3vi3bpfoa7J1uvE9+7r/LEoMwpATS6l9yOrPldYaMTnY0iosZhz2M7e3d4CRsxuKt+byOOsDTLPVt6kPD+kMi6Y9FdNZKhKc6aLWcA+5pbNOHaw5gT2yJhF3f6SVKdubbWcTtdOQ03/PF/qcc2c3xu4lpN3nTbpHUCCmjPpBc9UDzmJclqVL93w/xnFkWWZqVfeRCevI0RvdshRSZ2+BEVM4HWtV426/p7ZCkIwQ3Hg9egcTYuggW2M77k6MseP+QIhCrUqpym43YBhlqZTFvRNTzJSqPtgWcdDMHDwKrfWkQKOWxdfqvt6m/rzKKbGUcupXVvDJ8OPn0hjtyX+rf1ZGe0pXCM4GyXlg7qCIb91epIOBtVZW6d16PlutKzRIzoNfC1g3mHfvKJHAkP0aVA0M2cFfLzmE1JkZnnLrjD1Du0S0p6a22j0LA/YL5E//x9iGdEbOPohdqp6u9ZwjEgYO7UgTaDaCKBqhdFAg6EAyl42ZZnISQlgQVcrsdVGMAbSrDfrwQ8yvVdGANe/JJFSGnBDdeJiIGE2j3yuYeyPKSA4jgic5+iPeD7r0gSHV2ZfWbSFSCERpaBCqKNIKKSQHOk+Ap9/D8/SSmBY0Fic4NGOIyXtbExAHuPz8Dz0p2SAGEgNQEDEiofuCClgg4ebaVaBqQaOcbANCjlT1RLWlgLWZKBMigaoRCYl9Wbi5fcPl4+/w6PIZ5Xgg2IzaBClwLAdqM5apohppU4JaySk42x8DCdzdHfnk55/yw19+xrtvX3IzGC+evyJE9zdOeSDJhkEyi84sNCQatRSSDAjJPaD2B/Y3t7R5gTCwO78k5REpyjTNZLMuZSvUNtPu9myGkZgCVQuLLixVybIhhZGlGVonAg1tB4blwgew7dhB5kIaV9n7TNw4QFNbZhM3hAhTuSHHhKWRZm5hgcykmrwWjLhNiSi5VUox0IVgSjXIY0B1ZmkLhqJtZJSRVr9ZP/yNgSdnrPR/9z+CnRhQSbxZJ6wgk3lKUf8FE/qDo0vtZOWTyNdAKG9u6NNZ/xAr60lxWvLJbyo4UByDkMXlIq4xd/ALVrxDvsbIOXkFncCJjsKa+u+d/JHg/he9ESsIzVMKwYSgEBLdY6SbO0YQ9USH1ez763/8dU/eIvZ1f6UVsFk/v7FGRzvbaU2Vaw+kbph/bu0krKZwioxbJW8PcYb1/8L9cQn9mN/DRj29rimlCksVShVqCxQ1GuE0KTtJPOShW1Q/vl87p7/Y9hDoWR++pz3u6NHqX70CRSf88IQoPgAcH8BkJ1+qtTtbj7g+BJruD9jp/R8cx79JwNP9ncvpuugi2P59v8vATimWIoLSIz51fTh0OSYduFxBTHPQCDNWeDXYvffbwxXETvJQ61Oue0+y9XZtZtxOyn5R0hDZ7Qa2m4EcHOhxr4t7r7AkRl2O7N9c82I7kKtCrby8mbg7uqHh0mBWY2mZ2invoV+bljPMR1hm8tygRE+yCxGRRGnGoRj7kpmKJ15q8UVZOmrS1Eghkode3FclpECSyFsffUg6K8gQuXs1E7aFrDPzPLEbz5hD5IuX16ga4zh0KYHw0fc/5H/afofl9Z8T6i2pzYTg8faUyrQU3lhF48QwBLZjhBR9UQ6xAzF+jFXdOyKKNw8trMxHn3xaqJ3h5aBhUHFp3erOD5g22mrQjTdDrU+0Q3CfikwkpgDmMoZlKRyXmeM0oa2w20R2Y+7rR0EpRPAiRyJLdQ8ZMS+aYkhegHUmj4PqnsCoOE2/mhtkx/7gEXN/BRP3holRGJJxjH5dO2POE/3uuaff3i1ERTSRu2+LxMhxeolZc/o6SjTpnmpeqKn4GqUaPb0kDk6dlpsOOAa248B2gJvYIEQGgdC0Pwka46BchkabD4zjOcfp4Ak0m8Td7Ss24xZKYdbK5eVTpjqj0+z+XK1hrTFEIaWBpnCcps6lCx7zHJOnqgWvEbSt93P3cWsN0UxQHFxM/VqzgDZhkIwRKLg/nbV6uhbRztkTA+msOFHmubKUPa/fHNlsRs4uBoZ4ZCFymJXbr96wScLFbkfZRM7OcpfVBy62IxcXW8pceXM38WY/cZwWhihc3+ypCxz3e9JmJGtkWRy4udvfst3tOLx+ztPzK64ePSaPmWmavdEHzrYXwMR4cUk6HNGibMaRcThju40cjkfm/XLygnnz4iVDHjkefs5H3/uIaVE+/vhjPvjguxzvZsJmC10GpcuCWuOwzOTRU7ekGZJbf4Z2r7ToDChJkSEmaoBWfd0oc+lMBT+DrVb/HYwhCrYZaOPIcTowTUeGactmMIjK8TjzF3/xU0qtPHv7A776+DOW93+Nw/GP+D/80nf4/PWfoHmg1g5nqVLx0xbigEijmJIMxBJHizTpXmVGl6l9uzf/ZD7FX70VvbJtvb6IzkiUzqA1JYZ8koOtabTDkB0AafVBWlihlJnNZuR4PDCOI7UqtTRPQuvg47ImkLU1XGSVU+NYtYQODERXIQSlFGcOuTF1QoKbepu5RCym2EGe1llb7SThah14at1AWWQd4nqT1qqDTOfdb0mE/nmae1PFSFyzTRDMIiLuOxSC+0W5+bUyju795MybVeJvlHnpHkiRcRzYbLKn+3X5mkjw/Y3yAIQJXm83A9GetFe6J1UkJtxkvym1Lt2oHIRITtkZUc26NYin/KUsJyn5mKMf4+AgbyyNaSoIxlKWDgg5kOCDLSOtSV+4MbfOtb+er/e1tp7Cl7pMUk/ML1WXQar6cCYip/rVj8EDxlrfYkousTQP9YB739mVFQUOUqxm7MsyA4GyuAworMqUGKH0gb0ou82G3TiSbO12vv21dDblfNgQx8hhP9PmSiIgIfpgSzMp+b0a8kCz4uAJjdCUFDfEZiCeIBdkBAoq1ZPVuoIlCaQwULqXmElxpkkUVBdSdFN8F4UOWIgs5gPdZpGgG4QRMbc4iFFAFMGT8IKpS/ODm8V7siMkA8sunR2C/17Eh3hBO+GhNfbHO47LhIRIVmfANO7Po5l6orLMxFAIMSCk7oncWfjmLOdIJobIoguSjdiMpo0iUCT3ILJGbLH36uLwZF/PkNpDbQZEA8t+4tWXn/Psre/w7Nnb7G+umacb2jKjNA6HxnQErRFtA1YGYlvIBmqNvB2IKXCcZ7784kveevoV2zyyF+Xu9hYzaGQeP3qbbRg5vnnDKMmVD+pM0DyMDviLEENimSeoMzFtubp0Se9xnpAWQJUyHfvgF0CIoZ+TEsGG3oc0JBQkuOVHLco4bLkrggZjEMGWhmihVO9PaqmwKGRY1Ou8jVbm/Z4sGycXBCMM0a9RdXmvRVx+HY0SF5ANVT3YKBCwArZEih5pOlMtEbZX3ziV8hdItesPS7lvT8XuWUys/20AzaelBKL4BFJwOq+ugJQ6W0rFD1DoyISYuA8a6rGHEgjqci8R7T5EHdxqDjqlEGjBvUKiWo83PYnsvEE2B1a0m7hZn6yKOmDlEacd2OnazdXusaMRJ/CiAFUDzWLHNhSVykbcTM7ZT574FjsDS7ifDK2fc2UdAb1RMgesTtCNR9paW5lW9wbfqxv/CkjRUeaiK6DS0T65Nye/ry7WmbjHsiKGBQcVAgGhupRG3VOjVKX0RnCuRlFnPXTx3Hr2/VibdmDxAarFOn1iPaL3CM6/B5B6SJS6/6ecwDSPCbcTi26lqt/vU0e9pPVp0oPjcQLH+mKpTiXtfbf/xMoAWzEbe8ibWt/zb8ZDEwCjP6zg/jh2gABvwLV5oRq7CbChYIHahNjFWxLujZ2B7n+miCqmq/S1v75VxKLfu8GnqWsqi/+y3ZvPm0+EjUopjf1RmCtsU2I7DozZY+Jjl8E0NYIpKQan+GqlTUdur/dErVgr7I+V2pwh00VfaAz0p65fH+Yyo3YMaKtYa1gdaEkRixiNucBhaRwWmFtwuRgeRUrsFGnzu2jYJD9u3dfikz/5MY8fXbDZfYft7pJFXzFsBs4vt9ztbwnjyNXVE66vDxymyA9/8IHLJ0Lkw+894uzDX+XVz/4ZQYyjVl/rYsRqY2rGnTXKbWEYZs5y5CJnhgQW02rBheGSI2eTeAHRJKBr4IP4uiLqa10wLzpaBzEQD12YS2OpPskm+LFfga0Y3TPKUQTcH6tVljJzmCaO0wHVikgih0IpStUFs0oMmSF6wpYRTlJOF/v5PV27HLCpewCFZuQUUQ0cNbLURrLg00QLhNzIXf4YpZGkuQytg4HQvuZJ+G3egrhZrkgjECh1Ypr3oJ5id3LkUn9Wai/41xVxMUNbI4aERkgY2IZxSJyNlciIiflz2RQxZZOOnCcj6cK8HHl69YTjMrFMB+Imo7Uio1FqYb8/sNmeM4SGLo25FpKF/qzwYrZZYy73iT4xuXQL82uraSMFZ1Jovwaio6R0ezk/WU1R87jwmBx8TCHTmjezRiRa6uxjX3tiAGvB/et60doU5nnisExd6u/3cTFYinK8veNsHphKI+fCbhwZaWQS23Fkt3vGk1Y53B2pTfnq5SsOdwdyDOzv7nj85G0M42Z/gHDH+fk52WB/PGIp0iRSy+wSJ228ud3z/nvv8uXLz7k422AhMsRMziPvffCMjz/+GcfjkV/+9d/g+vbAF199wjtvvcPrr16yv7nBYuD17R1xGNgMGz8Hm0waBg7TgVJmqilbiZgEmuDGrE37M9CZ07F7yVRcUtJa80a8GXWpWAsQAladzq/SGMSlmSFH2tSo88RuWah19EK6VJALPvzwe7z7zgfcvp7Jm/d4efNT3np0xftXW77YKxadBaJaXcIrQimgttAMxuDhLs3EG58hITgL9Nu+aR/e+GOzYX2f72dd5l/vg0Nfd/vfuAQrpUhKiTxkanHAZFlmlmUBAtvtmUuktNFa6Qlw3fMOOlDh9aUDtA5yifgwUyT2v30I5d5ByUNGOojUHwcux4reRrjBuHIyGl8HESn5enICLfzDtuqeMqU0ttuenhRCB3JW03IwU4Yhn8A16WmsK6tmNUEXkZN59sr+aU27pOz++JZaYGrdj0k4Hp0xse6zSwojIUTKAmWpwJoGJ/339FQ96iqx19AliKB1HcCt/P9Gju59JCIuXTGwtoAZMSZiiASpzsbCzcJTSh1Ii52B5euoX0telKYUaM1/3+LqoeMDJTeF78zzsJCip5aZOWgs4senNenAVjidSzsVvb75sXQQapUzr4blKbu80Y9P7MMOpVUo4mBmLYnSJZBnZxuuLlz6Q+2TQ/H9/DZvZ+cDIQlD2CBhgI2SNhA3gTpXhkGZ20KWCk2pos7CjREs0RZB5yMympuQa+pql9xVKhWloKFRDSJbEolqRmF2udmpn0xuS2OQolDwezvE7ExfDQ5w0XvmngwWRIF036ul2KvibsPQBIKnrqXkzPQQXXZLVE88izgQ1gJJI0b2600aiHoPztrDVkKoHlpBhObBMVESoftkOVs7+XO+FmytaMLgIJUWsIyogiWm6gzQhCC2xVCGkKiWaDXw8qvnLPs9T5895fbuls8+nXn55gihscwGcSSQobnMv1rx/TLD8oxZJVvk+nbPn//Zn3F5fsHLNzdcv3kBrZIs8Xi8IqHsW2HWhYUG1timRIvu4udAdWJpjdaMnIyrRxdcPrpiOuyZpwmdjdYitRlBk4fwtBGheaqmbPogsWFaSGFg3OxY7OjJu6VRmhJDIkehFIU2IxjaCiFFgkUmnTGF1/s9oQhDVEKoLG3h2VtXbIcdh+mGeTrQqJSpkFImp0ZO69DAiEGQWDnsj8SxclzuEHEyijB+o/voF0i183jjFbyRQCdZ3zfmQdYHqHf2ZgbRJQ3auqQjdhPFtZ0w6/KM/nf3iAKjNb9hFOvGyH4jrUbdQYSgRhElBe91kggxckrBW2Vtse+3v3bnHdkJS/C/VU6Ic22rFn61+naQzP1IzI1PzcEgRWgiIK7Ndx8nvZceYqcFVXqTE05MD04MD/9+94jhHrwxOsupWadOS/cdcqnfani+PibWFMHaX/iU5Gf352vFBBBnkakFp9xDL8AjtQXm2pgbTDWw1C616zu9Hh9WlpN1qWN/jsTQAZq1++H+c36TTeweHloZCfe07o74PKBS3T8n74GpFRn6GjC0noT+7wdeyH1qaqwsNPpE8HQ99+tmzQpcf0YfsKS+vZucgLc1EfEegmygPqmorfaJg0++nWbeDcnNgOjeTyG41EpO9uR+3Kw/bLtm3f1DWgcP4gmgOnlznZDstXGutDIxLYW7Q6U2hZicBtybyBBCT5zxe9Jp3+ZTvFq5ub5hOoReoAZCGNlsRmIMSHWPKYt+v6o2mhg59GYKo7ZCaYVScT29ZJbiDKbWAmaJVtuJ9YcFqlRac6lCHofOzPEp5NMPvsdGCz/7+e+zNGdmzHMhBBhz4KsvPuf8/AlXz97l9W0jijDmTAyBp49G3v+1X+ezf3ZJKtWPaYQBZ6ysTeJ+hs+vG2M6ssmZFM3TUQANLllaqp/b1qW9KsGtBcTXYm3W5W0diOwmrGJKVWM24bCYTzas+nQvhX4+euNpXkyFLneoVsAKoc4kLb4OW+uvYbRSMW3UkNBsjObFfVy9muJANVjKQml9EqzCvirBGmdDRFLguCSm2hgEShVS6xOnPBDS4KEPZohVMsoY6fa+f0NgY4Xz7QWqSg4Za8fuK9IXXAv9+av3y31H1cRwE2NrJFmoKh57HM6IsTHmBQtbIo1KQCXy9CIzojAdmWdlPx24279iPtxiJqTNlmG3g5QQMd5+622/nurc46DFU6p6nVCrcVwWl5kQiMH9PVozFlVCB5QN0GrYAFKVOGQHHPuzzgMRevOpXbaCD4Rc1t/XOQHV6qk/+ICsNJcMOytYUGoHOQzMG3Ft92mbijA1o+wbrd1xudtxUQe2S6JmZbvBAajHVyytsh0jy1SYp0Jryv76FY8ePeJieIeb4y1P33mX61e3FMNTgjBiHqjzzJPHzyhL45NPPuV2uiY/fYaoMh0WQlae7Ge2Y+Q435E3kdtPXvP02bu0UlCD16/fgJhLFgmE3ci4Gdw0dppY5pn9/uCpZp3lQfcKEnXT8KqFssyMNjIEIcTUm+h2StmS4qwnrLMiJSLJG828iYx1IC0j01S4vbkh58BZOEfEePHiJbUKP/vp57x6+Yrl+x+w1L/Fzc3Mf/73/kv+5z/6I/74i08cfmkOMluILK2iVTENTGLkqAzRsEEYJVEtcpi+/Xex13IOIt2zpQOB4LHrANITzcTvhxisM5sqIQbGTebq0SWqxtEW9vs9x8NMWRQzN40OCbRVxpz8fjA6oNTcf6b7+kRxJk4txe/pOCISkKAMY6K1BbXq3l9dFqbNn5khpQcDv7V+vl9NN5sNJlBK7eCZnKRc3pD5a+52W1KKXN/cespVdl++IEqthVVe56yk5WSinfOAqbIZN8xMaLPOsskn4GO73bEsvQnTQi0Vs8BSGnQmIjijaBgGXFaWKaUwTfOpLlRrRHP5YYyps78g5UTswKyaM5RVnSE4zYWcIjm7Z60EN/N1NoOARGpV0uCATCs+jAsxMIREa4Wc48ljSbt0cQWgfNATuoxu6YAQGM3vG+PE2vJroLk5tbp00NPkHAwdBmfPzd3TLQSvrfy9/b3MhFrbyZT8fpDulaWag2ZzcQZaiJGmStRAyv761iopJx5dXLLb7DguR9S6h1Gvl77Nm4yDW6sMI2PoNDw5eJJxFlpVGk7nb4tLKccgPvyIA6Wps0uiP5DFHPjwQFZF8ojWSrWDgyk4yBFMyHFEgl+LrYdyEAZovnaICDlsQAYHH5uzJUUFsYQ0r5MS2b2rzUkgTTyEx3lEihbthpK9b7XOjU7uv5iRPqiuxCFCSRgBFSXLOsQuWH9+YpBIWHG/RhMnkqBCrA7yWi2IeSpn1YoMgQw+VGu+j96TCaqJafHhtHtsbXvarboayYRXr57z1Vc/49m7P+QH3/0Bb168ceCzVlqLWGhsh00PLVMsKTH7sDyMwn6ayPmCZVZ+/tPPSfKcuRYa5gyw1njzxceM24z1+laCUWVhCs70XPYLppUyV5Zpy2Hac7W74my35d33P+TF9Z7l7pYsYMGN0kMUcga0sBkTh8X9GKUmsEQOiSFEaDNZZpIFBjMkBDYpcXV2xovp9SnorVVf160pbZ5ItG5DAI3agbzG8eAS4HFzwf7FV9Q2s5SFgLPp06hUCwxxIEYljt5v6dy4myslzLyZCufbR9/oPvqFzMUdAPCVOGh3kZB+/Tu2iQMg96yWoJ0t1UGJFHwxWvXrCesHTkgoOTiFUyWjZen0znXqwwkwWOV3HYYgBHUWQBCyQlQh0uiyTZdVrPqgvp9Cf2Cas4VW8+5m1uOT/Qek687dxM8pRcXsPtVNQAlEnLG0UqYx96kQM5/ORXN2lazvfi9fwbj/cF/bOrDTJxgrWibmAJPYPePMz43cK+zUFdMn8/F7JIUQOhsr3DORXIbQG/nm0fFTM45FONbIUiOlNQceZQViHmA4JzCIB5/THkyb/n+/nXT6qyeTnb5xAuJWud4JYOSvP9LAvTF+L5/c+DOejr89eN2H+/A3Z3NAoamjPYI3bmqewlBqZWnaA8686Iihg7kABGLsjZ1yP6EyBxN8KnZ/DcQOjoTgcefhBAo+OGaGg07rl61SSuHuOLM/zE6B3zh1PIaIYYTkNO8YImVpoLV7GgRaK+wPyl4clIki5DEwjF60BRU2eUTSwHxc0CDk7cg2GHJeORxnlrbnsMzMyagasVBZmkuFmjZqcYaGBtfHW4+ZbpY4f/SEdz94mzFHFoVFjKfffY/HVvidf/nfcpxmLq+uuLp6TJkLKUItRwTlR7/yQ37+yV/wb/7gD/mtv/O3STkwpsiP/t4P+J//79/n+NkfoMXlvaNExnHDO1dbjjry2QFeHQyTRgxH93cikDaNJolFhdIfNCk6s7SJUgOIdQYTRgxKaNUnQeIgXVOYGxxqYr8YwsIgha06wGhJiGFDCkMfIHSWilX3B6OSYyMOAhFSMnzir52GHWmS0CaYBk/Y6uZO0tPoWpnRHrcbWNP6ItZ8+qfVU3w0RDLO5GKGtA8u28pbDkvjOM/kWhg67XspekpJ/VZvkjg7v+Tlq88JcUOt15i5NMVWIJd+O51m7W4ivz7HihYWvXO/p5gQImoz46ZCrFhNbENhtw28tYtM+8YSAnlM7IYdMW0Yd8LzL77E4ktarZQK51dXvPPhB3z1+RfUvTPraMrShBASMblvis6tJ0C63GOpSpRGFgeUU/Z9kmDM5pHs2owYvUi2FiizMuaMJe1MCp+PJnWjUoudeZGc0aDV2AwDKtUbLskuq6+K1AYxeraQI7FeMARf50SCD1pCZKmBF29uuTlGLrZbHp25n8tmOPjksSmXm4gMA6/1gKnw+uaax48fsd1d8Ocf/wXfmSeu3rrii8++4DsffheVRsyZUpSLi0s+/vlnXF495p3L9zne3nJ5eQlkLA988uVnbIbiu1eFV3fXPM2Jw91tZ9I4WBtjJI8ji1bGOGAi1GnheDhwPEzU5kXDkAcH1xRchhHJIVBNPLZdhbwb3PsjCVjBrDHPEzGdkUJAbOn1Gv66BDbbHWfFWJbXHI5HxruBzXZLygKSePrsMbsh8M47b7PNAz9/rnzy6Zb/23/1Iz66eslPn39CC4HSffPMGqGnoTWrqAnzIlRxNvY0TTQxlvrtv4mFgCeAORC0dgjrYE3xGkPpAwBZQ3l8EBtCpFW4vbkDEea5sCyVWpSyVMbdhs1ug7iBC60Gl7LFVRLmnk7b7YZpOjBNc09623awxleQlCLTdETEfc5cvuuykVbdn21IiVLmExhlGqjVG7CUErW5v4thnvIWXSHg/kD3K9XhcDyxaPLgYJLPoVz66ZP22KVyobNmYJknBJg7LX4YMq0p03Hy+jbF7gNF9wdckCjEzhhrXToWow/VlmVh6KBVreWUqufSO2fyiHgQz4kxXBshJE+7w02jQ3TJmaoizUGcJkoyZcj5BPjUUl2WnzLLUkkxUtXDXtwjMXRQy7r8zY3TXVbovk2rF9ZJBjn6cM4N5dupZ1ildNrcbFwIvc51xl3O+QRqOZvJJYfDMLAsywmIWg3HQ/BqUEQYcmZeFq//1OWe2pyhEWTo4QVCWaYTY8IVHAFCpkntvqD3zOZv66YqnG23pCj+fGlKkI0bYZOooRClQfJRR7IIHfAsESSPYIlI68E9UCy5D6K4lFZFgEQME2Kl96egNvSwqILGQEWJydieR453C0ETkR21GCE04i6CJBAHR1NYyRHZR9BBCFp68IrXDg0lJk+8NElukJ8yWp1B7v2+9LoNYhKKFq/zZMBkgLYQwhHJUIKgi4Mm2+0IrVB1IeBgFUtxlrUtZKvUqOhZcPCuNcQqSXx4vKjRLHN3O3FYCnFYyOdbTDYoiYXKIpUyHzjMb/jsix/z1rvvM0RjPh5cCoqvwbYoFWdVxhTYpB6S0BRpW9At0xwJaaTNlRntsjnpCYOVeblmMsAiY9qwCYG5GSF3r0oxJAlLnZimI4fDgasnfm8/enLFs/fe5dXNV4y7wI7M69fXaKnun2oz9RCRGpyZRSBLQppQl0ZjYanFvWoNtsM5weDm5pZm0KxjFnHHbrtF2kypFWl+PWpwo3niBsO4WxaOVbm8fMTcErUJEkdq7bK91gjbgcuUON9tePL0kp9/+jGvX99gQYlbN5Yv5fCN7qNfgPG0gjzema9yKk+GghTuZWOeUOMv3voDxtk/3mAEa46kmV9+Y3DZQwww5ogSKM1PqKlS6cl3cs8Cgk52OaENSghu6BdjIDUYxOU3KXjCjbu9W6ce+qs4uOBYbzOh4iG3Dj6Zy0ysT5R7MW9djkfz5KlCZxWpoPmeSmyAJJ8UeBhebwY6dXplKsHqi3SCcFiZNd0ci9MLIr0ZkxPg5ABgZ3U9OGdr+t0qyXvAq+qm8A4KJaMbx1UiUM2R+9oiUw0camCqXZuOdNP2e9CO03lZp9tdVriyhh6+dQfOTtu/x/zpHtRZX//+3/79h8epf+71fe3BYbO/9N/rl772+v4O2gvB1bwc7kGnv7p/D4C9b/22gq0r88nAfDpVrHUvr0ZTfLGxe2t+P8TdeLT5PRhXU2aj+zc4vVjx6XnCacFrmqFfsF3S2SWvvkDfL0PSKdfFjLupMs1zL9S9wVyvN0/iiuTQqbI9PUWi8zBraTRbCHXo3hYZUMYhMkhiskA99KlrykhMxGikITMFOBTYt8ZcjdzLs2kx5gK1dq05RlsKxRyEMgXyhkdvfchbzx4z9ulmypFmwusvv+QPf/d3mJbC7mzLj/7Oj7i7ecHnP5vYnu2YyxErB57/+R/xX3/2U47/+P/CP/jH/4iLR5f80g+fcPb9v8vrn/wTCAsxKJXMeHHFR+9cIW3D9KJy96bx5Z0SZMEk8H4ztheFEAeUzkgKnUFpsBhQA0sArKBavGmxSgqJMWYIkaIw18C+FubaGENlzIWofVVUQSwTDII626RZQSiE2AcCQwZLrhMP1Y+f4LTwlCg1UJuDFnnoJqchEEk0qZ4kopUUhTFGxiiUVdIhwphcElyauUwb3NdoPnKUiA3K8dhYlomqBYuwVOUwF86Gb/8NnOIGNVjK7AVf2fcpZfDnCa0z/JwlItCDV5XQXDblIKI5s08M1Zmold1g5FCIEnn09BGvvvycu+szynHfG+Ee1S6BpnB5cckuDZAiqsJ7735IzpmzccNNve3sJPHi0qc+tKXRrNJQgiTmVn19CYPX6SYU9aJ5EyNW/NmgzchxwKJLWgIeN51DoEUHfptUYm5dKuZGqVoVE682ZysMY+oyPkADZKhkKOtjVgky0mgeCx1zT6aiPzQSaZOY5srheMvt3YFnlxdcnmf208Lu7IxWIDbj8nzLbrdjs4ncXr/h2dtvc3X5iOvbIy+++Iy5wtwqt7dveHR1wf52T6RRysz3f/nXePHiS47TxNPHT7i9uUFS7AO8gdvnz3nre78GizLtF8yEkNznSkSw4IySFCN1ccPkVitzmSltBW2FVd7SzEGFIXtaZwyR2hotOFMqDgN5cIZGqUrOo/+eepylVnV53cqKD5DHRMoDWgvH6cj+MHF+fk7abnh0+Yg/+qM/5Pvf+wF/8L/8G9774AO+ennB5692vPX0N3nriz/nk9evvA6rwWVgRE/pEQ+4qBGEhEpyFqc12vLtv4c9vdPXzNbNKNdaQ/pws60G3DijLElkyInp6HK6WitTl14ty0KrDTW3l9juBppWZ/U2vzdSWr1ZvDp0Fox7AXlamSetiazDVR+cTtMMCG0IXc5WiDExDMMJKnPmi7G0AiESog81V2+nocuugJMXk8vj0mlItTJ4YoydqWOn31dVNpstS62daePeiXaSERZCB+TMlHmZUA0nf6ucIykNHA53vj/D4BLFWjwNi9T3q1Jr5exsx+Gw76+31pjWpX/a96EHZ4iczJzNGrUVmjqjOIbEMIykKOw22UH2pbCU6kbS3Us2bEYOhz3zUkAyYO7f1SWHJysEnD3joE84SfDWc7eCeSE4QFnK3I+rs7ShdAaT0mMoTpK91Sfr60bj9zVvKQvDMNCaA1GrmbZLIQPzsnSZJyfQCnEWRq2Fw8FfO4bAxfmZ124xugdOZ8qvZvB/JUH6W7aFGF3Cr26ivQIx2oRRApaCJ313k/2mBaS4UXtVwjbTiGhLpJiQ5EblbRJaFaAiEWIcEBoW1O/fxWit2w7kClGQxVeMWqvX82Gk1kBMgZiNEGq/pCIhuc+hBDfgLq1gDOisrvJIax+7ppMFQtmCQQpGd/Mk2OBhQ5Iwm/2Z1FPEMolajSgbB4xtcoArep8RwoCQ0TqgsmCpYcEoLN1mJnp6Z1CO3T8uVqBmCnCsM8fjzM3djOF1ubSEkSkycKiVV7d36FwYo/Dppy94++2PqXPgzesXzMuEBccTYk4suOm/1NklhCpYHWmvjZx3lCoce3iQMSPJSBYItbLJI7Mnp7hNjQqDRHIaiMGltMNw7v5HbeZwnLm5veFtLRSMlCPf+fAdxvyrmE2EFrndHzmWxb10zYO7YroksnVEIFbUCgocqrK0DFMiakNrY+xguOTIOIzUEsjxzFVkBLBCqbHbEiibMTNszjCLtDazubikeFwt42YEhcPxlmE0D/IZRgJGXWa+/OwzjncTu+2OqgWqkoYNbflmLJNvDjxpB36CgzDaAZGAA03NurQt+AM0AckcmMLcG6qZF8djXHXhwhhgFNd6t14MldaYilPGQ4jUYtRObwoGrLI1VqTFfKHrHj1BhSiBHJTUhBwdqQwCmXZiPj3omzuTwQE2N+wWqhrV7l3uRQL3nk9yarjrbP1B4v43jUrD2OCtfu5eG6YBSzggEyDEDqF1HGWN01VdwS33dNLmPk9NxacE1kWOQk+WWRduTmbqLqcyqnmj8DUpWD8XQ4Dcf0/NPZ2KeTrCXANT8SniXIVFcbqv2cnM97TZPfuM4FMqx4G6KYc8YB1xb0x9Ovj/nmvVYcXVn6kjSLYe05WhJP1zPGQmhQcA1AqM3oN6Zqtv1wP8kj5d6CCXdn+j0748AKq+9oj8dj8vT9t6z7Qq3Zy+0Mw9JeZmvfFvThk2ZxAZze+p7o1iQcmITw/ED5x1pl81PRWv9GLYLNIwkus4XWJ6QrQErEczG+6tZEatcDd5co37s3TReG8CQwgMOZNTolQ/n6ouzQgSGBKUSqdxx35OfcocCZSlOusrJpTArDCJ8WjcMW7PKLd7rmdhHirW6amtdZNiK9CTiVZWJCZMCpth4J3v/JDt+Qj93k9D5FAWfvef/g/86e//IcvxSADqdMMmwHc+ep9mic+/fMPrrz7j7/0ff533v/sumwQ/++O/4Ie/+kOene340T/8Df4///0Zg76hBsHGLenp21y+/ZQPWmKKR/Zl4S9eHfjZ9cLNXHhzHHjr0ZGLbWK33fbCXWkGVSISHEA0MZpOfZrtzMcQRnbDhu0wgmQ/p03IYoxS2UZzX61g3fx7lcB6IoZSSVKRKJ6Es7KT1FDzqOohD4gll9DggKOosenNh4pA6rKsmqgoeYBt9vN2XHqCCjCGBGOmqHvtJTGqNo5FsXaLTgtLaVgrWDBf16pS1KfJ3/bt/PLKTZ5VwCaaVi8AvazogIqcJLHS48UBLKin2ODMtFbBbAI5kEQ5HzOX+UjLG85S4TAEoDgNvxnjJvG6FvR4ZCvGIQsXTx9x/foVTZTtxY6mC2k7oDGe/PTSmFAzjtPE8XD0AvzECDCGNLjsfL0Gi8f8TgIWMhFn95XJ47vXKCRJLp3XBHqshCGgFjHx4Ukr4H1XJGWY6U2cOFleax/RBPPXMp/uKgqlYjVSRyN1GQJijDETg1BTQi0ztcoXtwde3AlXj864UkPGkYtx9MQ4EZ5sr7AcibFxsQnYsnD16C3G6cjzTz8BhOs3b1jmwouvXhME/tW/+JcYynKovPz8NZfbDbvzDRoyNmZevrrlV/6z98njptcfzdmN4mlGIbpQVi1go8saSinMh5mq3Ug0JG8GRDHLmHr0thkneUXVRg4BKwWN8T7i3YymgRwzcRip2mhzJYaR1K0VgrisqKZEXYyyzKhuuX7zin/ze/+Kj77zA+amDLszCIG/83d/HRHh9njBLvwqt1/9DiU5Cy0DrYJ0X701zbQBIWhHbrph17d8swConYZ3K8OptfsEMa9LPCs0CuQhkrKDis52aag2qgTmyRlPK6iUU2Azjiw9Pa211kGNzrDqD94QAvO8nACe1dtolXMFAldXV8zLwmpmHbqvovVBrDYHW9ww2Gu91TDduiny8XjPZlrNue9BDT8mK7Omlop0CeI4jmy3W1prTNNEbY2Li0tUlf3hzj2u8nDqIxw8MrabHbU1T7aTyDRNHI8HzNpJHlZLdQnUmIkhdaZXQtU4HPanGlMk3fsqyT3Dp5QGFvpQycGnlH1QUrWw3W4IkjoIXjlMBQgue0/OPEk5U2ZnmDeUYRipVYjJl2yXBNXOcPL0PqBLFB04GseRUtzQ3MxT7PxYGEHcE+s027aAmRu1q7b+uUJPmvPXWIG+WgsiwVlj0aWFm43v39nZjmWp6wjeGXnJ28h5nvs59IFlQPrv93S9boKvunB3uGM7bH04gL9v+Jb7OwEMY8NYvHbUbpkSGxaNwsSd3THXyYMvUGI0qlVsGDugU1FTCGdMqsTuBeUATcXaQrRIYkeURNU7SlGMhKRAFR8uCULI/Z41JaYtrWVCcqJFMiFbRkJgGO5TBUOI1O7xlohAdM+mELG2RUkEq35uY8QopKgsLFQCgbEPBCNowlbze9xjTMLkKX5hh8QdJoVtNlItnqBnGSNSgRYK3hQYqWbQRmkLi+E1u7rXXNXIvizs9zOHY8FCYIgj2gKlDMxVOR7fUNqRWmZiTMwt8eXLA7/7u39EmWG/n9zDaL7rQJpSmWgyo9UIOpKGEYlKFscPRCuqd+QcMap7kYYNGiP7qmgNnI8jcSNUlGmeoCoyG2NOlOJ9TB53gK9FKQ2Mmytu918Q9cCzRztu75TPPvucOhcHNUOiIoS0dd878yR7TUrIm05kcXwjBD9fh+OekgbOhkRMrkgIcYtqoDSvs6L4ehWpiCXOto/Z7DYc9q84ezTSUkHLwnZ032xtRjzbcLe/ZpkPbLaFA5WbtkB2i5ZUByRuHFNZqlv3foPtF5Laubv8qXUHOmDR2UMtQMQlNW7c6Q2Ogw3+u1orKQwkElOpSA7EIBxKI6SALI2KUJp40SeJaoV5ZU6ZO/+vXIwVaNHOuAlC96KynlpkpAA5CikKA4Ek3aCt+wtDN9W04AwhdWPwTmo6/XudVK2EUOkUyG5F5Z/POljU/60GGs3lPOt7hfvQKU9cctGTmQNYTlk2b3ar/6lVqNVRcX9dp0VrB508Ut7ZLF7MrHTWnvb04IIQcfmUrYCY2Ykx1UwoNVCaesxiC9QW3UhdfSLRumfAWjmsrJYY1hBvp1SYdHnECjqdtFT/2x4w1jVzuoJOtkpMnAJKL2oeyuWkg3G6sn16wbfiZ/0lO9jk79FYmVPagaqV9SQPfr6/7rdcmw5+PBQ/bouuKTMukWhqLM0jYmvtckv8XlolrNH8Hh48yAQxj2QO3chTze8h1e6dIKDBo1JNzKcKFtwzqcvT/Mx4kIDTvwu1LByXmek4+0SU9R52oKQ2Nx6M2YvHeQk9Wc2p7Sn6q0YJnVXlkb2lVmppJAK7GFlwM/XYDC3mpsM97eVYhecLvN9g202o5jZTGphmrAWn0VtwmWID08j5xYf8ym/+BkMvxvz6g8Ob5/z2P/+n7I8LKUa2Zzt22w1ZA5uLRzx/M8GXb7ibJiQF8tkl7//tD0m24frVK3KEX/+t7/I/PvoB86vP2MXE+dvfRy/exrY7LuKGD0gsyx3H0vjyrvKTm8pXxwPfvRO+8zjz7LyxGV32ZLo2Nw7oVWmYTrS2YObpcmN2ttHYI5OH4JNbN3KEMbgReDVPX/LP66zRqi4H2A6BMSQkKskyiyhLde37INXXC4vUAAVlQVx21Z8pQZwxli2jOlNjYjcspGTsi8/htHXHNYlcbDaENFAF5mXi7nhHORaOLFg4MoRESuIP4eAeX2O8f558m7dsiflwJIUNEu4Q8RS7ZnoixfogQ2i4L5eCr9vd39CsUXWhNfGnvzZE4cXryCiZu+PEbTty8+Il51ePwCKH5cD5mEjdN0JloJVr9ocDIY388t/6Jba7Da9f7T3hdohMeyMMmRwiTQv1VFw7QGCtIBapCiE2kq3DJNDuUYII5OwAd3Aqd6iNHAOmUBal1AWRzFB9wFRjPq37qDeKzo6JXotYAFWq9glulw6jggX3p1ifD1UVC0KtgZQ9uSuEwJaApQGJjXmZqQYv38y8uT2wC8L7V5X33nnMsB04H2ETI9vLkQ///m9xy8jv//Gf8ub2lpu7wqKNTU4ESdzdHbncbqhzQc0Yc+DsYsvY49FrnViWSN1FdL7jbn9gu73wmiAYRkNqI9gC45YhulfNUme0uNyjVpf77M42IAGtRoqN0gRdFjD3+YBCq5CG0WPmcRlOWSpFlUGMGowcAyH61DXl4NHoqB/bEBnTwHJ35Pb6hmGTGMcd2+0F+7tX7DaJP/mjP+FX//aP+PCHv0ydZv7k3/6ct977u/z6Dy7513/yO8z759QonQkTIKvHPUtnrokPGrRqZ9d/yzeJmCwOzOrDmmKVPnW2Ux/YltIc4KkuK+2OoSzFwSdt3WpAld1u48/D+QjcM79jdNZYrZ0VTOB4rCzLdNqtlfHiPk7OTvYSr5tqy5om58CGqTe8ZkYgkrPLpFNMqHkqnHshOWhVS+2hJf56pqvJ+epfVPu92U6+QytIVWtFQuRuf0fOibOzHaVUDofpBJqNw4jgBvalG6qHDrTl7AXLcZr65zBCSH0Y4lXeKsmLkW4A7iBOKQ6KDbuRGBPTPHE47Dkc9wSEYUjkIbEZvSGcpolWG3mTem8hXfLuz5yyLCxq7CS6P1T3J6tNqabMS+1DA1jNu8GlcsBJtvaQEebAkRdcrdYuXe+J06fUxHCS0aWUUG2UslCrV+zuFagdvHIwDzgBFrU2Sqkc++dLyYGr1pQQnOnh7+9Jga3bNKwDYpFASh4UMQwbzs52RBLH5eBhNMFZrCKrjuPbubW5MYWJLD7JzDm7bKwKiy2kMLA/7EmDoFFoQVlw/6ukkWxOvJAEU3VmXG0OFORsNGnO0m7FQepwhuJopIl6emQTHzql4gx/i2ARUe2z2YCEjAYhrvKc6PKvGJ39MsSMaO/TrXQvn0htEffua50oEphLoZmhIqTYfXylv4caMUJtLjW1FD29T9wGoVn0YW8WqlVfr5LXdJKEWSvaXAoIBZFCxlmDFgIaM/MCN/vC3d2hkxyEKoEhBRZTDoc75uPsthTbkaJKI3B7XCjHLwkEllpQgUULm2FLsOheh50mEiSSY8aCEQyGlJhtobM2CKIEE7Q42GMIwxgBo1VDI1ioPqDv5BClUZKzzaalcvvmlnqcubzaUqvy2edfQKu8fPGSLz//HK1CCp7YaQFqSGzDGgKjbC/OUQkMEsjzhEQjpYE6+3Dg8vIxoVaO0zWFwsXVBds8cry9Yxgy9c69QZ9ePKO2wHD+iKXOnrzZlMPhlrRJ1NS4uX1NKMowZgcsY0XLxNkus7fmaZfq4OQwnCHAfFyoS/1fvX/W7RsDT6ZeuEpnm6y+PSuUoEBUl5wgRu4M0daM0jXYwfz7UtoD0+rGFJ2ZE9SQDBYCBRhxX4hjrRQJIEYy64kqvh8OkmtPZjJnPJkDRNKlZFHcA2qMgW2nRgZxQ1KJcmINKS6tU+3Furm3Sem+T9I/dxZHRa2zY2jC0uPmw8oo0QcJeUlo0dn9TSH3oy4dGGtBTgv0Chg1hdocMKrFaB14qhWXAHYYwZVHvhiEleZqXnQ0NWqTznryxlAM95o6oYeeRnY+CGMSSoMlNEpqtJDQm8ZdaTSNp0Kpygr++AEJ/TwEcy0u/Vh2vpE/gLrpOF2Cx4n08tcUi1/70v3U/vS9Dhj5P+X+3dYH3dd+9H6ydmI29ev1AXZ2AuB0BZIefF9Or7MCUfbg+w+8t/4GbAYUbQ7CaHNwWDkBnaUzKtTC6VhEdY+mgBEToK5zbiiIeuOrK+BnlNbFigGSBtTcxNavDf/ZziZ1pmCMiLmpt/Z90tqopRddQXpqnRfFIm5sHkIgD4lxHLyprD75FcSbySAEhdIK82Ic9okYM2mM5OCGjaEZdlwQMtKNPJelUErjk73wS9vghWMwijUWWxzI1Egw84a1eXoLccuHv/KbfP9H753WRxDqcuB/+e3/kZ/95MeENJDHDWePrgjDBtHIxdUTLq4OpPQld/uZjz9/ycWzd/ijP/y3vP/hh7z17F328x3ffTvzzg8+4sXzhNTE9bHw4ovn/ODpFU/fPuPy0QUfNWHWwPmbxp9dT9zs9/z85UJsjdjg6iIzbjKLwbwah0aD2MgsiFZyDOwGl65tYuXRmNiNyhAqRmSxgDWPSa7q8imie+sY3bheAhYSktzYO4ivhXPdsy8LMDHEmQWfkhQbgJHtOJC7LwghEvNATmNP2DoQayTHRFGXydV+fTWUIUa2ux1pGCmtUdvi5orTkYphMbDZ7BjihpwjQ8pscuNsk1il1N/mbbd5xBfPv/LitB5PKuz1GeAq9HtmpzeIydmNqC/B2mg2IZIR23CYzri9g7lekoYd7XBLC5k4nDMdC3kw5nlit7tAQmJzeclUKvPzI2av+c73f8DjqyveXL/BVCkNhhRdIhQzMWhPieyx76lhxe//YIY0T6dpXsMBEROoLGzjSMKl3+5JGLHkn7W0BgJpyFhxFuXSj0PsjauJIuqJi6Juot+sIU3xwAN6klan3hdzKddS3QBVG9aaf5bhjNqMJIEhWW8OM8MQ0ShQBE2FEiM/fv6G5/s9bz8558Onl7x1vuH4/DUhwuMnj/nH/+DX+NM/ueDPPv6C59dHgprvgwwYtbPFAgVBSyNGI0RncZV5wjY77l6+QHrTqQhaG6KeUIVFUltYJCDiyYN1WiiLe3ecpUTEyMOIBAffCYJadTaigqnXXpHKmggrUUhpcLaNwRiDnwcgZDcAp7lRtap7eNaeZlZK5e6moJfK9d0BZcv3zs55590P2NfAo/MrbDtxdnGJLoU4Ja7kGUc9YswYE0UEbZHQGjn4oNMEavRzmfTbff+Cm7027al1Jj1y27CQsOafJ+DAMSe5jnWJWKLNXbbTgwTWARHiRvAC5C7HKqVQzZx9U1c7h7X+Ff6/1P3pr2RXluWJ/fYZ7r1m9mYf6U4yIhgRDGZkZGZl5aCauqurVV2oFgQ1BOiP1MeGAKEbkFSCGuoaVFU5T5HB4Ez67G+y4d57hq0P+5i5R0otsYACknkRDHfS3Z/bM7vDOWuv9VvOLQ7xKnOcWLNS1YqKY7PdUoptBp2Lh7XlfhjnvEPE+EYgB5FC1JOzHpw07bZ0ECDetON5hsUCWiQ/58qiXzZRJJFSwjlhuViSSraojGZEBmMFBWNC7QWaoe+puh9SWHzODtss3r1zTM4G0E5pRtVio+LcYZ1XdCKlia5bWpFPSeScuC0bRBx9H1guB+ZZSJMxLcuYSLNF3WK0Bkrvot1rq2sDmGjtchIRhN007VfHpGLrMW2T8H0j9d4pZkUbbbXcXN3jNNP1HYBFH9vexP4Ras32HFWPc4EYA9M0Hz5vE4JsI5JS+pX1yv6z7Pu+uezygfcJViZgjjYTtXJJTaxTuj6gMqAbi/jVXIidxSm7LtL3juWqY7lcoFlJow37RTxCsZj/d/ioCIPv8KWtFmqhqIk5rnqCRvphgYYCPpCKgpuhZMPSiDe2bh2JzmLRBGumE+dwIVK9oiSyCN4bEwq14atDUG+RNKWtQVGKny3imkB8R22NsZZQUiuA8AFctOZul9HgLHpXMpoS1MkGw77dK4riiuC8cf68VLzYMGb/mREGlJnoZwoTopHo7PnivdBJh6+gGplaaYc1KSaDn2uE0pzLIqRskVlqIenM9faG7UYo2ZujC0c3LCl5Mh7avGPOlaIBVwNBPaoTBUsKWS4joWQbiDrYFW2oH0HoWfSR6MNh35NKRXygFkfng61dRMk14bXgSkOMxwFij/eeabcmVWNSuSTge4oz17BohjGxvVkzrq8hzQQfePrihvXlS1ypaBGicyz6AYKJiJtczWmcM4u+42RxRFIlRkc8XpDmHVoF6QaOjo8R9RSZSHWJhkz1Si4z47gjhohrIFMfIsvjFXPJpHlHUnh9uaHrFshs+/y5jEiu5DLhgtqaZ67stkpVT5kzw6rjaGlNemYW4lAI9v/v+PbCk0lG6N7tUw2cDUJpPhe7BqRdoCZ0ZGBuu3QvQsXqlX27qeYCc9mrWIWpmMAzi9kYp1zYVsudVmfxM6cecTMqnoQitFY7KdRqJ25Wy9uiFV/NZr9oDKh1UkoQhuJM7XPgsaBqFbvp1wJzm5IWVTLGLgk+ceeo4qrncldRDbhqQLbjpXBxbNO37c5R6t79YZPd3CJKdU/Sd0pA33wIB4eSNQLlVhleVEhVmIrBgffxMvFqF3FxlOoNGFYNGFy0Ump7/dXUV6TiCAQpRCcNLu7pYmV5JIw7ofrA6SmAIyePOuFqm9m0Fj/VNz+itoAx08T+hCsHoUkA9A1cvKUBwDUBswl+KjYhNYHnjZNN2YtobTN1EIdshmP/6a1IHG82XXvRaO9IUji40OxWLY1F9EapUsQEENUG8dPD36Dor6C29o4pi2F+26vou3Hkai1SZrlt/6g5n3I1i+WeDQbW2GiQTIupOudIDoub0bhRrQSgVHNN4YxJUFSNv6FiDQq0/Lu6Fi213YPz1vpizxxbtOb29b2nCU+tyU4gdtFs6zGyGAYAtqOSs02E98LkXuDcQ3HjbscgBviMmP1bU4Eo5FHZ5sk4DFX5cgNXx4IExbsWQ2z3QSfNMZdrMwlEhsVDfvuf/Becnq2aIKDUPPHJz/+Q//H/9N+TMBZLCB1d11OqMMSB5fEZdx4WTi+esdlsef7qhsevXyJ5w9fffM6j9z7ghx/8mPunx/z4137I/Jd38X3hk5cjv3z9hO3yiN8/PWexPOP8vOPDuOLO2czJ61u+fAk3641dsyHifUcQj4pQKVRJRF9Y+swqJLxTlhH6TumcsuwdZ4uOYRhwGDyxJAOPlrbRVfEGA/cdwUW865r9Xqy5q+sRHE4TZZqoVC7ixHmYeF2E23nE+47lsKDvFmzGRJ2V897RxQ6vFvcMWkyIKLCdM5ojC99TnCfjWPUdy36BxA5JMwHonFJdRUtGs7mGBheI0jN0tjBbDbBV3dtnv7PHdtqxm3aELqGusUVEUW/PY8SuN0RtEaJKnYVc5FAi4V0gaEFxbLcnvLq+y9dPR8ZtpbjMtB05WnZoqIS4xHkDys5zIs07pnkkp8xyseDkzhnf//An1jxVbRaUppndeiQQrLq7JOZpIo3JXLDJ3EVOXHseFdDQ4OhqMW1AklCaS1KCs+p1LW0dsJ9qmSW8kHFaELHIJqVxK7D4eJDc7OZii+Bg7o3c3K+iQtU2cXW0RWd7QnhjeeRakKLMKvgYMU+BIy47wqJDslBdJsbAxgXWuy3rJ1e8eHXF4zun3D9ZcX56xPzqCn95w0/un3P/3hmfPXnJ19+8Zr2bKWK8FYeSa6bOJorNDkJ0hNABge36hl988iW1KkH2MQyQ2ZwpiGOI0TZ+ZcLVRJpGcq0E5+l9xxAW9KEJrs3lKYQDd8U7T3XNTaTKXAudszhicK3yuRZwVgVf2lSn1mpic5nNPRoNrFyBNFXmKbHdJn704Y+pOJ6/eMY//OhHSC28ePqcRd8jonzvgx8z5pF1eUKWzG42p5o4e+cLb4ZK++eY6rdezv6tHVph7wtXDB6+j9vtgQWKCbPmrNbmy82t4c6T2+8VsZWPuVeV2EVi11vJgmbmySDg3nUWG3MV1dIgz29YpMBbAtQbp8vfGOEd3Et7B7OINVKlpC3C9aZ5zZxGxgNKs7XDdV3XXFdWOGBD1UqI5jq0xrs37itjUClzmghdpKNjnlMDogf6fmjRMzsPtrstIcQG2ja3076VLaWMyHRwdRnDybEb58PwPISAl44uRlI28avrOpwzp1IumbG1VdZaDryjvSvJNb6s1sI822RtThNOrOho3xAcG9+otuhbjAZiV4yPhXMtilxYLJZ4b0M/e39ri6/5wwq4lHyIUWljdgoWk5uaG2IcJ3OBOX/4TGXP7BSLO9p7Y6gP5wy2vndTHa1O6JqrDYWSams+NC5VCGLNhxKoCt5nSi5t0Aw5J4Yh4hp3KoSIeGHntu3e4Q5D5O/y0UVzgEQXcFVaqqe0wXsll9laDH1oKRltAkdEux4DnUY0Z7rOkWjlIPukEI4+gJLa8C3Z9V8FxARIY/l1aPHUabQvKYEgwQbEbp/8qYcIuzrXBr/WZuqCNwaqt2dmBcQVvJjzDJ1RTeAjpSEP9gUFtbYce/VIjSDWWmhylbdyGHVEzCUtumelds2d3fbZBUQrUTGotkLKkUpkKpmr7YbbTWAekzW9iQ3FpzThZUarY5oqSR0ERxYhT4Ws1d6TljRKUzEjivf2Xkpobc3WuDj4BV2AuZoZpmhmnCqigZqUYTARqUztXlFsWB+cAccFj8cbg8sFEEjZSlmkFupuRhF2U+Z6fcP9uuP8/IQu9i0ZUumHrmEwbE9DGyYFH4iD52i5oB86ZNqxW99QOmvx26x3xH7BjCE0onMsVidEbHC/G2e0wM3tmtj3pJxYTxuK27u+Mz5ALULX90hOxJTpxcpdxlrxCFEVwZOq6RfemSC9vrmCGqzd2BXi8J9ZeNqjTKAZV4AogqhlWAOtWtc3/hOeWWGsStI9ZNg2sc0IanE45NDcgSqp2OKwj5kTJ9zgodgiOnlIgEfpWvQuOVCJHPvMO4vI51thlyuiCYpr7OrKSVf5wanjpBM+fjrz9dQx4vEu26JLOoIk4j5L7TwJQWpu7gYPOnNxOvP7v6Z0Ivzpx8p6WxE3cXIcuHfacbKcEKd88VXldlep2pE0MnQzvVM63UOdmzwS7MYsbv/+anOOGOeJ0iaSonix2lHx4HxkDkK/iMhuYruFMQVcESRUnINOPOrMJo/Mxm4oFvOLAlEKQYTlwrOZZp6+Coyz0i8qfZcZYkZcoOsDvlYmrZTGaTmINSKHZr19/FAOYtPB1nSYxOwjNDZXab9v/31L62FqAtNeRGJ/7ukbx5IJS/soXRM725/b/3wfgzxE89QEq9raGfaOnjcLMH3jOjsIS2/Erb8JF/9fAo5/Vw97q5WstbU22oK9FKXkylSUqUXGrNXO3jORYoteUXM11IortkgIe0i+0fXb1y44Krm06FpRm1bXN6/E4e1z2L9/4luDjUUCpjkzzeag60KgD54YjN2jmNvJtXYa+s4Er1KsEaI5Fn2jAnvvDzHPeRoNNL6IRN+TRZk1o7vCdsQ2w2JdfE+3lac7ISyUTlrk1imlMQm07q9VoAYefv83+PXf/5nBFhXmeeSrX/4Z/9P/5b/n1XrN2d173G4nhrrAiwP1rE5OGRbHnNwR7j16xF//yV/w+tU1uzHzD37vQ55fXvHZp3/Nq6srfuOjH/Pgg0fc/r3f5/b5L7h6VfnmOvHnX1zz6PE1P3h8zNFqxTCsOD/ecWflebyKPLnsEU3cPeo4X3n6YO5RbaJedJlVTCxDxnnjhATv8QR819P1HT72KELR2dq/bIduTWRhYOiWDN2CGHucN/ZGiAGCtQeqmntDtXAUZy66RHTVJscZ+tixWi5R9WzSRKiF86MlWuHVNDFPt0i5RhmpeYLq6buBoV8yoUQnHPXBYoOlUEvFi2MVOqaYuZkTJU+c9B6pgSBLglN8UKJXJO+vkO/usRm3pDLhmaG12ZkZzxyf+wez0tpWszT3TBNiXMGhRISder560nG9duTSkTSRUsU1d4uTiuts4TSsjhgWp0y7NU++/pKLuw9IufLDn/46/WrJ5ubSJrCqpGmyEY4LFCp5SpTUIvfO20LTGfi4HByk6cAkQex7cd5clnWfY2dvALFvcs8Q9I0bV9XhxaG5mCMxelxVqrNYifNik0wn1OIwrpxNm0syzgi1NmeVQ3wFdUi2+EBNGVFzjqVSLMZbC/SeIUYWw75taqbvB+ZkDo3LXebyq9ccdZc8vHPOwztH3D854vXlayaEj773gHcuTvjiySu+evKKcc7U4qjiiEVAK5lK0Y5V9PRdx3p9w08f3KP/68+hYswGSsMhwD66VKRBkGslzQkQAx73g8HltbbIVznAlIv1UR9iVKlmHBazz9UGd6rVygSo9Ajq7EErYg2eNPdW5zMlBHaixtGIGUoijRs+++RTxof3efe993nx/CmDwO1mw3YcOTk64vrmFe+9/z2ux694uf6cOUFxcnBrF5s+4agE8eTDVOu7fYg0m5bYNLZCG9YKUNt7/xYqQE0McOoMRkyGau/BHgmgKMF7go+gFnG0+JInN2j2YU2lpcHF32zw93ydWi06LwIkbSwhDiDrnBPeuXYN6YHZAzR30pvn+RveUMWHcFgThiZ2ihMkG/sIFVJqqQNna4xSSuM42aQ+RGMwDYNnTjM5zzi3d+CpbZKxCF+2GAJ7cLo0NMQ8z63Br/+Vdd8hfidWQhJitDWMs0FwySa+hNaShxpzNak16e6Fsn7o6brAPE/knExca2LcrK45eSs5Z0L0uMa0NYi4iUC1HILCAIdmuv17uP/3ECKlWvtv3/fNndVatxVoLX2lZqQE9rD6vTClasKUvRd76Ls7uNf2IuO+8W8cd+2e3BwpaumOnNo5VOoBeh6L4P3cIpo0Z1zjP4qnFpjGRB+NwyWCOTfku89pkyKErrPnkm8uv9reD1W8WN29FnMtBjLiOnBtTZ0SJXgbpuBwgJeKC4aLieLxag2jON+GqIpKafHLDopt20styF5U1q6xR5IJA9HuL947YtQmehqHWV0Tmqvxf70ENCyodUaqMeSkKjlPECvowgqFGrNZtZj7ifaZ0kMJBG8tz0Va2UwbMOU6m9hEM0TobPcxtV+X4EizGVRmrezylvU4crNOUDqiOvJ2QqgUt2PGEX0A55ESCc6xb6KdU0VcRLzdR7xzaOdJOb1hsalFd9WZ0SCV2dhEzhiuDkEkUJlQyVTnTTBmQIsyF8NyOEl0MSMYO0kI5Nl41dWZa9SHjkGMVVmc5/XtFWPecnR8wcN33mVzewvTDd1qQXaOWsVSGXiWQ6D3Hu87KpXtZo2rmZpnkjenYGo2x86Z+/F40ROcMk47xlSYvSBdByJWEOcjuzlTZWv3csS+vnPMyUTTcZNbjDSYkaXYXtHVROg9rvMMwwInwpwTSU0Ecygni6NvdR39Jzie9v/XNv2idMDgHZMUFirs2LsoYFRhFpiq1RE7zEVh3A5rdfPaIGkiB8UYF+jEMfhA9JjlvdXPUk0sqFSy9ESUyEykcq+D7y1gLo5b15G3mZ3aBd0H5f2TQNd5NBQeXPR89iIzF2Wh7aHrMsUXVIVlnzlbKDe7yi44tpMt0iKFVe+4e2fD8TBTypIXlwW/OOby9cTz5xPTceX4RLn7zoLx62vGnS2mRbSpxIqoQwg4yTgpjZ31lvgh1TZ2zoOvhBzpfSUcw1Q8c+p4uS68vincPYMP3+kZb2eevbKH73Kp3H3oKZuJq2vbiJ2celaryO16ZM5Q5oBDCX5kMQy8XAu3GbbZUa8hRuX+uSM46PrIhatwM7Orpn7bJ0eb5tAaA9vn2z5n2X+u7o0N2O3twLZVenNSHU6sXxV0KntBCXvg/4rwtBeO7N/38TeaaFL0zZ/fCwS1iUq1PfT3i7w3qqoe2Ahtbdv+85vIXvtt7e//7i92f+VQA/vOyezTRa3pJOXKlLUxjMw19GbiasDn/Ts/kY3P5AR963O396NaZLXYIlrEHq7aoq02WbfInTS4ocViKxWrJ07zxDjOlGyTU6s/3jMCLHqjajEZ7z2us03f3KJ21uJii1Dn2iLXeZsu50KeZ1xMDL4H78godZpRge5o4Pj0nNfTltv1yOcbuBMgO2Eudp6r2ES6FKGWCiWicsqv/9N/wZ337phDYLfhi1/8EX/6//pXvHp1Q3d8wbBYsLq5Zcg0MGnP6vSMsDwixML9x+/y87/8Ba8vb3n28prze+/w3g9+xH/8kz/lk6fPOX/yjIt7A5++2nHn6JifPLrHZ3/2jL/4/BWL4884WZ7ww++dEMKArCLni8idRcc7JwvmNHKxqJwshBiF4I3j4qXgvcWigjO7v0qHuBXUHh96qnhrilMTKgUh9gPRZQqZ6AcW3ZI+LhAfrUii2uY8eFNHSq2UPOJ0TWDLXJWbEthMHuc6jjqDad5MiXGaWHmQKmxT5vNXt+h4RS8bprKBtONiecRiCBTvgcyqL4RQ2aaZKds57BAWcaDUxJgqUgo1j5Q5Ir2583Iyzs7hpvIdPrbr2dw+kppE5tqVBHsykfeQsqNkY6u5ds91bTBErXRd4PU28uo6kKjklK1xkEBXF/h+SWXLzatX9F1HXAzW3BIDfRlYLFacnt3j0fs/4Ormyqb04pjmhISA9B3UxK5k8jzZsLY5JC2iFszaPicrFKHSQvrWnOnMfazOhli+DTpsumgit/N2H9HGGClFkZrRap7EIB6PgIesAVcyPjpyMcew3RMMEFtbjCGII7Xz29GEGWzxb06VSsSm97hAobDZCjVX6vGCo2HgeDhi11VKypSSmBuD69V25Gb3iieXVzy6OOG9OxdUJ+T+Nd97/A6ny8jd82Ou1pnPfvkVde86KhZZ88FxvFrhc4Lq+eVf/KUJE8VC9+JNkCuYZd85hzYWXh6T3U8TLILxWDKFlJMN/PAULFK4F5iqFhP6UsE5adwWxfd9E62UmgvFB4Prpsqei5OzNU+6EAniKN2OvNmx3W2RSBMPEk+fPuPxe49Yrk74i198yo9+9H1evnzByfEJU564d/cBjy9/Qlwcc7n+AzSnJti0z0ytkdeoVE0s/I4fB5c0jdfUCk6q7t0he++4fVdWFNA25jhC8IRo/Lxa9LBucd7hAgdWjz0HcxOYTEwo1YTcg2NGlVzy4f4MHBxBtLW5/U+QJsIgoLXYwCF2zNNsG5j9xLC5ZlwTNmspIErsAmlO+BDxPpDyzJzmFiOLiARKycalK6UJYYXNdkakRYsqhOjxLpgrYTfjXLJooQjTlPChTX3EnlUmTsUW3bMGSN+A5CZKaRPS7P6TkznCvPe2aVUbMomzXws+YMUbrlEjWrwVZdwVpsm4P7akNHeSvRb7PMwVZRD/kgqh69BaSLlaTHovJIZwaJtTVaZ5pqTZXrN31p5XCqoO74dWY24b7b3LyDmHqAk6te5dUa7xoQzTYU4ne8/ebrYz0Q7eiFUJp3uhqhxE0VI4uMuMJVgJQeg6zzTWNrwUutDZr6eCBG88J9fTDwvyvGXfVvwdNzwRdEKccYRMWLOBjyV5ikW8vJDFritXHbUat8ej1AgSbI0s4qk12gDFNeSLVhze3KdizymXK96sHRQ8c7vne+dwPloxhhqv0mEcVBUFKeZsbZGT6IxrWQQombB3Y6kwIWRtYrNWG1qVDt2f50VbRF0IAdAR5xUJK6QGrP2rIqpoVtR5EgXNE6nOWNWMHuDoZrww91Quwq5Wbjcz2zQy6Y5x2gER781FJn4v7LUCMQ1UOosAu4zqRJAAUZEozDkjBKgBpOIHW+P7JnxKtRY+7+x+Nos3NhZKVnNYxQ5ExURBdWjsKQKjWnQ2Bm/OX0ZchFJCi/AXYm/3JO8CCxepZJIqL1695urqNQ8enPLuu4/58uuvSV6NdS3GUT1eHRFw5kmZJ2pSbqeRcVzTBYd0ninPKIF+eYQPkUEs3miRZqGmDCmz7Ac0LhEXGEtFfUffdUiZcTUTQ0chUHVCdUa90B+vcFNHGkc6ceSUmaZEonDU9cSuYzmsQMG7TOdMNC2lgPTf7jr6thfcfhbs2lRVFChKFzxdFBYZxpyYSmsiKnZTV1EqdqOt0E50eyAU3mxaDVruiVXpY+G0cwTnUFdxYrXLpbWLuZpJAU698ujIWiI6n/F94cfRkbIynvRsy0zsjGF00gtfvM4sl5GLbuRO7MApx0eBLjp8mUlpppaOh+eRwcNChM8uZ6RC1UARx+0msx6VZV94537m5Wvh0y/WvL4VqkaORod7uePR/cQP3j1iewW7TSY6taYcMfaR85lYC12zUntsGi3iWpwJxFWctxapZZcZ7nVcpRV/8leZz19nYvCsN46ffzny4GzJ+Z2Cm0fu3qvcfXdiXAtnd5Y4UU5OKkO/Y5wzc1rw7MvCduMIHbi+MF4HttmxLYVSA+TI3Bby6zlzPASOoodayPt2FJWDiLTnaYnYQ9oh+xbtgxvK7wWn/QO/xfFKEzn4/xCA9hNcWmtgEzdED2fkfr9YlDeTwoO7SVqcay8cSRMu34riNZHq7bN8v5Hbf+23f/ktfXD/Mv8OHdJEObNhqmprbty7xuzhtY8tWpNju9kfrGk2Nc3V5CPXgPJ2DVcKBkGtWmziUQoTkHnjhAvYJN5g+1jdZ3Na1JKY59GuRbXFmIi59PoAMQpWSOVs0eo9qoUuBrrY4IhwAKQrlqt3Ygt3myommGYWseJjYIqeaZ6Qkonac+/8DJm3fLNd8yQrL2viXAtTs5l7zP2Uq7m6SgosHv0WP/3nvw9OWd9u+eIXf8ov/uRfs7z3mHAJD9zELInjuxN5qow3t9QqhG7B6ckZF+eOzS5zdH6H8fo1L1+85vWrNR/98Mcs/tEp+sd/xdVu5v79BZvs+OgH32dx54zv3yS+/LNv+OzJDa/XO34iwrIL5v4IwtI7jpc9OS1YhpFVDzYsMo6Aam8gWVdBikUtit3LnO+pLjBlparxIQShb22CXgqZjBdzREnoUDypZHJNZAkMpjiwm2Z222tyumbOO6ZZcNITSodoxKswjTvG3cigIwsiUx4pdeYsbNGFoiWym5Sr9chRN9DFjmxjaY79ll2BabazsfMtDhQDPnuWnScWoZSJlAbbZBSYUyUl2cMCv9PHXJQQCqoZxLWaXyg4xBWLqZVMyZGa97HhFil2A6jDx2NeXVa+/EbZjEopG5w6KIW5zOT1SLfMRHF0yxX9cMSr60vmkoldz92L+/hFz3/1z/8FU9oSvLN2uVKpAsfHxwY/nV+RdolcK0Pf2UZmUqo3hkIqFe87cp7QWiAJKr5xl5TO9/Zr4szBINbksmdY1aJEC7A0d2vF5Yw2B3HNhVw9QarxLrzHa2kL8mgtf86aD6dScdrhXQJRktri1ksh1WLuzJKpHpIWWzC3Tb/oTEK4vMpMfsfDhw85Pl3RRWF50/Py+oZtGi3y6OD1duZm/ZznL3dcnC9YXd/w8ulLfvrj93nv4Qnnt4n33vkdfvnV5zx7fsNuNxKcJ4iwXt8gtVLE8+zltQlipTSQLNAmvE48uZromOeRaTczTcadVOfINbOIA14ipdY2CLSHm7Y1SMn2bPC+tdSi1JzZ1cKwWOE6Ewp2zd1OUVvjiMW4qzg6D733LIcFmwJTmnG7kcWiY9xsWJ3fZ9kviD7wu//gvyDvrvitv/fbPH36hHmXCU45O7ng/Q8+4ovPvuBWn5KyJ7ezvtI2voAUkPB3IWqXm9t07wBo0XDasARvKw8nSN2vUSq1WAw0xIhLyYwh0iJvQIiBrgs4B+NoNhTnnEW/1DhRFCuDcG7vptLGN9IDeLrk5hBq7XTeOxbDYNFqzAFVMbbSMAzo33CoVK2Yac7+uzVvCnMyoaSoUqfR4mEuokXIMuO9sjpakFNirBlp8OxSs60Tm4t5muYmnEXQQskz1UEIkRiDOSqKuUFNYDI3lveeEJZMDQ4u8qbRLQTjD+WcLAKGY7FYsF7fHISiUgp97w8td4VKF7v2td+8h85bbK6UYo7NWq05r8KcTSTruo6SEz4EfPTGokxWKIDYQG3v1IoxkrNFeHc1G+cSKDmbOCV7F5SxsEpJh8HrniMG5rTbu5j2UcPUygZEmjsu1+ZosrXh3gVpAmhsMchyEC3fPqSdb3vY+9AFds4xz62kYGGcTh9CM2TtxW2xHzEG4Xe92U6cMo83VHHAANrb8JZMpljBjRSIxYD5FcRZwyFiQkXA8Ciuj4xVER/pqsG3xYPD25rcZYvOqeCrp1TXYn4mbpirb4+aCbZHIpijKYiVdbmIwKFoiz1DyykRJWsh5ZkqFp10rkARijOuU5WZUncWy8Scwko2c4TLOG+CJASoJt14NbRBcTOVmYqYWLZ/Ic6bY3CeyOPMlOBmN7MbTUidMch3CyygzrA0LnmCRIP3h55avP2aJGsqrmKiVqmQK1qtKEuD0IWBTnqojhocTixCL76Z9yu4JtJ3QSjM4CM+DNQaSbOtZUSU5RDo/MBqOKLWCZXZhpi14KJDgqDBo2Wi5hkWHSEscC6yXWeef/mcO6v7vHPvnIvzu7x4WYi95/TshD723L+4YLq+Yb2+ZT0mdmnHlGYkeOIiIMUx10IlIASii3hJlJrYpoCK2Osg0HcBkR7xCzoHYYjGFcs9sVS60JER/Ebt3MkJ369QN4Nz9N4xjTugw8lAhyfWnjoKc7FBkMaAH5b0R0tbS36L41s/qX1ztrTb2GFGmWpmUYUodmOhGgDYNvf2/9oeru08AjVukbTWKddy5SoOT+YoFu5FYXCOKQjdcUeulae7xFTNK+OlcDYY2+ibdSEDV2nm1849qz7hemWJEL3nevZ8fTVzs8k8PBIeHm3ZbQrSHfFsLLy4zfzkfsd7Jx2b3cTS7SgOlkE5Wp7yxesdT25s0dxFqLslz25uuHO352rj+fT5SHIOFwq7TaUjMMiG798Tvv/RQEqBOQlPv95QthGvDl+LQUXF4kgxOLxUm1B4Tw1CX5RUlcwIS+H1ZuKX3yifP3cUBi76jmmsfPl65hfPL/neReC3v7fk3p0NMShXU2Ecr3n0qGM5WGNNrBBlxSru0B66led6W3l56ZmSJ9XCXCq1BG5mYarCXIWrXeKd48j5IOxyeeNKUnu2GZ9DCW+1CcYWW3jbDbWHJDreuLwOj5omEu055Ptz5eBE0DeCkd0+W6tgVYrKIQ6q9c3P7UezhO5pCdqEpzeW9v2reDNxanjst7SwJrzs9Zc3UuxbL/C7f+wXnLU1FGY1J2KtdsMwMbBVsjffk9s7Ddpnp61Zcl/5bKUDUEsmaUKNwEHRSmq8KCl6cL+FJkbirfqVNvkVKpon8rwzLkzJli1volIfIHpIXog+mE3be0QDISh9H61doypoJeWCFg7fn3PmqpJSGPxM1IwXx+AdWdRE1ttrxpOOo+MlfT9wpTO/2GU+6ltzUoHomqhZhaSQq+PD/9V/wTvfP+XJk2/4+pOf8/zLj7n7+EMuHr/Pv/53X/Ljn/0a62nHmCrPnzxnO01MqRBiz+nxMTfryjfdyNn9R3z1+iUvX73i48+/5rd+82fcO7vLP/ud3+YvvviG8fJLPvyNdzl/vKRbLvh7Hz7k51++5OXlmj//4iU/efcRp4sFofO4rqf3QtcLOYk5SXtw0Vyk9k9uhRDlsOA0JKs9kWu1aueUCsEb/DDGSBcMHC4lIRKNBYBxM1IpzNOusecKc4abzY6SXrOMr/BhpOQBysCcCrlcIpIhdpQ00fmE0vP0amK5WPHwSLgahWnuGIvy1VXhYqF0cUBdYLNJPKkTV7sRx8jF8pggLT5WR5AGuoxvHAcqgmqHr57enbDd59a+w4fzM8GnNil17CVi5/bg8EpKgTyBmgeE6k+Ro9/CdY9Zryt5ytx9/Ig/+qv/ieWww/nIejMybnd0i2MmJq6urtntJhZ9pMw76rillMjy6ITLq9f8y3/+f8B5hdk2W0WVzbgBJxwvljx+9A7/8796Rhlns6rjjEMVvPGd2vV+sMG2ibwIUAXNatN956AKEs2pVSmt4KNFRX3FFWto9DjKflGtxgAKIQJ2nqsTREwU3Y86ajWoqfoWAZdA8BYN1GL3hNomwhIiOo3GaezM6VhrwSPMVfELZT1PfPXsBSebgdPzUy7u3+f4/JQXr57zShzzmMlUpgLPb3bc7EaOVh1n2y3zOLEcFnz/+++wDBO/+cFD/M8+5D/+yS+4enVDSsI2JbwTuigEvPGf2tWqjZMZnLnAJil0nX02c+PqdH1HGCI+BnKtbFNi8JhTpm0ailr7mBbIu4T2AmRc9Eh7hm62W4YSTaByhUWOEEyMN8HBhNz9s0F9sEbASZnnwnqckW5iWGxYLZZ89vknHJ+fM774hs+ePuXo6JTH7z5mtx25Xs+8+4Nz/unv/tf8n//v/0ekM85lEIzj6RSPAdX3fMjv9CG0GGOLgbV1hxOhFD08O2nlNlKNnNJ1EapQtFFNmxNGm8soeG+RutZ0BrCHhhs7yFzD+xdRaqHWZE7BhkDQfc0xHEQZ58LBBZPzm8ainDPjOB1ex8EpcxjZ7d01JkxqbS65Yo13IkKInnnO2PM/s16vD197nucW87IFV6lT+4yricMp0Xc9IXR458jF4muasc1YZxzHeU7t69t7MQwLnHOM40iMjmE4agKdZ70ubDc7rB2vtva3SsomFi66BcvlklIK282mfYa1RQCHw3tUqr0DMXbNRWTIDw0WTc8Nep5LZt5mQJiTsZictzrB/TptnmdAmab85vNs0btaE1Ur85jImbY+zsTWJniIPrZho4lC9vlbzG4vnFmU0iDlyh6GIXunTOxJaaLvB0oxwWuakjnfBNQpJWeGwdYG3ttQOjTOnPeOlCcWy4D35q5Lc4E6mSs9KDnVFnX6dhvXv61jmwqxC4RgsSzRgrja3IMC6m1VXOw6MK6Qvf8IVpSSlLyb8FGInbTGVyFKwNyKVqQBgquVKPWN+EITHrXgoyclZ24XhSr7RmHjKeFgW6EILILgXNubiaNKasPBQrFIgn3ebs9hFooYskaKOZPn6uhixIm1QebiiRVEMtUpaKBWu7dQJpzPiLPWOHGB6AJFYa6BpMLtVNjdjJRqg0mnrkXeHF3v0ZpI82R7ABlMSFZBuuYZzROJZHsK7SiTJ6w6UpkIvthgK5lbuc5CrFY4NuUJ15lrMcRo1/tkw/ggsIwdGhy7rIR4QhgGar2mpIngFOcd9x7coe8G5s1oBTt5DX5L1kyplvSp4iFWZjcRquLcEsIRz59f8fj+c955/H0++t677DY3nB0v+N67j9FS2F5dcvn8ObtxJhVlnCaKg9Av6brIwhkaZZcUTYWht3Num3ckn+kWSxbhCN3N1DkTO8diNSBeScyoE2LoCCWyXK1Idba1ZK6UOqJ5pg8dfQjUknA5cXx6aiB6jAfZx4EhBtbjln654ujOfVZHR0T3n1l46rwQnbfFrFaSQlJlVwsrdez7Vxdi+cdNVVvemRKA7F0m+537wdlCq7sHfCVJYGwWw+AqZws4wpGrbWhej3YhLYOwCp6no+N5iogom0urcnz/zoqr6w04z+00s65C8AP3Tj0f3q0cH/e4uOL1zvGH30xcl4Bq4uYW7t8RhghHq4FFUPorGJaO/OktLgQen8Fmc8LnTzPdZeSzy8zWWT38kDKrIfGDh47vv9Pz4GFlebJDsrC+iZzd9bCr6GbLIjiWHfS9EoaM6zO4PbfDXGGdWCNfDYnMgtuPA998kdD5iKoTV9eZIrBVRyqR+Xnh+w8r7/iEiHJydspiAf3qFhdmmAu9BHabHYuQGe4OFLfi668y69mZ/V6VqWRKg77n5sfaqjDOM4/vLLhem4W7NAcSh/2DEJ25U1wTn/aNgdYMJocHn1TYo8DdgfpkTqP/r0c7ZQ6/2iJxhT3PqTXdtfibwaWb0NRi7yp719NbAOq3Fqv61gP/beGp/s0Fre5lqr9rh71qs86LsbraghHnDPbnwO0NT+xz4SaQKlbj2gVrNIM3125DHbe/xZbTZlIzbgGYI0IEilOCJcRxOKqYI1JqIaeJWubDprRoBSIuOEJwdNETUoPMmi2wNXgEQg70XQQVnCuHyF9t/KlaLHIQPGhJBln1Bs47XQzUoEgp3Gw2XJwu6BdLxkl4OnvO3JZzrdb214a8WSEh7PxdfvrP/hG319d89su/4vb5U773wUec33+P3fqS65dX3H94n8W84/b1K24ubw5VyMMwMAwDq+OMxDV3Hz7i67/+U25ub/n8qy/5/JvPefz4Pe6cn/Mz/4h/+8Vf8t67FxaPcz3fv3+XH71zxr/5yy/54z//JR8+OOe9e6f0w8IeFF04VNWDR7wjet8ekDSejzkIc92/V2/chQYFNyEjVViow2PAYVdteiq+Q12g4A9sNYe1qk2T2abXmw2Dv+bO4hKY+Hp2rCfP9XZkrFtO2FBTIOmaR0dC5IL5drDNvVsyjQ6vA0t/Tu8LIZ4xEZlSxRXP5S2spx3Hi4mb9Y5OTqnVsucUx+12ZJaJPgqrhcEwN0WJocP7vuFhvtsCsvPFGExKa5ltNngSKlCSULJAEGMyoNC9S4m/ySb11KVycdbDeMPXT77kZLFitXRWjuEgdJ7dtOZ8OOPk9Jh53NL1jrvnZxRvLTnvvPMejx4/4tWzp3QidM5Rp0ydd3TdgtOzO6Aj4+aWIBAbf0RLc3G0Tba5aipeGixZzM3kg8UEaotK4qV9hqChDWm8My5dtZlfEavp3scru8ZzUhJFHcEJWSrF2YK+ZovWKYqvjj5GXMnN4eMJQcjORmU2+bcW29y4aLmaC1miNUZVKqFCzZWrumZMI3PKvPPuA47PjlgtO957BFfXV1xe3/D8xQtKDWxSZnOz5nrn2c3K/eNCnj7nZIj84MMfQ93wD//+r3F5dcsf/9lfM06VGI8prZmwgpmNUoU2DVdnEFDnHbkU0jQza2Em03lBIphxzJhYFWUsE0GW7fOxeJFzFWWmlmDtSsWEZwkeKZWSM1UrEgJJlKCekUoI3pzNqtS24V52S8rtiPrArGKDxiLc3Gx48foVfR/49//u3/Pf/ot/SQlLrq5vmKaZTz79lJ/82k+ZpzV37j7gvYcf8fFXfw4Lf4DQVzUXLNQ30/zv8FGb2FTbuXWYYx2i/9UcgG1UW9XusV3fMW1H0jzjXSBGiy43YxHeB4Z+gBbvKi2OQ4baYnoVE2Gcswp4i4vlQ7QKgNYQZ84WcxTP80wp5eD22a98ct47e9rQqlUlawOMp5RalMsGP76BrZ2POLHWRFV7JltcTei6DtAG3Y4t+meDkmlMLS4mDXw9UYsSvEHVc55ZLheAY7vdsNttAROgReTQlOe9t0KEBmzfr4v6fjBxekqUYuDlUjO5ZJwEbm93bDazidQOVose7wPjOLLbbdlzlELX0/exNcE1/EAF19zZU5o5Xi7ZjZM10ynMIbaoXRuOVGWeTeyxgdAeLB7eAqcbj7LvI95lQnSk1PhspRoKoJqI3A9dixpC3xu0fd866L39vTmXJkLuQe9vGg+rmsOm63pEAl2M5DwhlLb+l4NTzkR/z2KxYJ5NvETNidf5zGLVUbUwpx2iJhrWfc3xd53Tpt4aIr2hEkouaLZYbPDBriuEjDGQ0IA6bxgkMomRGBf0p8e4LlJJtjeiIsUilrMqST0eW5cUEkVms+V4hehwDEiGoUU19206pVaqCsF5PNlEmW7AhdAYiQ5qoIrlzQS1aHZr1CwkfGixOiC4zhpDxTNpaucVOJeNrxcX9pGpWqlBMfahhb7NnlKzIW8EQG34NWXHblfZVs92yjjtiLVQWrQ1FCxOVxUmiL7Du4E9ijPVCSXh1eHUEYfB4nNdj0seTcZz01ohmKM0SWKIoJuNwcHj0qKMohBqE/UchUIUx0nnieIhF7QWJqdMTul8S3ds17hS6SSQvGfE2gND7Gzd4Tu63hGjp+9XdMMSHxxJM89fP+Peg7t8791znPyEMk30RXnx8hWXl6+43W3YTZOVPjlLGXiMpZZLJpVi8UfZsd0K/WJJF0/otHKsSzoCtygjwmoYCDVR00wferQbbL8VPVOtiPSEXph1BwslzkpXKgXjQi2P77AYFmxLwkVrnQ7RU4Gz4R0WqxVnZxcctVKfb3N8a+GppGTxDDHBIPrApNoI54GswhAjS6/sSmVXxepB2QsMb7tL2gNX7YblsZM8V5hVeLqFIxXuD0IXEqXOCD0XwbNcRFQSx7EimhlTwleL7U30fHFj/JCVOyJJ5Zv1jLiZd08S7545gox8+cLzzW3hMo2sRRhJfHoLX9wI9zaZ90+WSN7x0/dO+fr5mscPK//ggw5xA25w/Ie/vuEXV4FZJ7xCEYfXSB8DP3gc+Z2fJlZdZpcqL7/u2N4kdruE08iP33fEMuMS+CDIUHHDDMMMXaH6YpEXAR8DMdrEK0yR97hLxvPNC8eT14Vd2qFAN5+Qpo6NTPzJxxvefRA57iY+/uI18wgfReH8JCNxRpaFsIPVkedyC7/88oZna2EsgbF0TCky50LeW601oxRUHBenS477hBZhTragaaS6luunVW7qPqnV4nUtydLEC6WaxbEBcWuDP7a1B+iBMGTPIvbxujbJg8NiqbZN8D5Kt4/Zqb7hN9XD+Xc4E9+cg4cz9I0Qunc57R+Bbz8LVd/6TW9ezbe9jP5Wj7dfpcHVzTOhYuIc0hRt/+Y9ssbH/ftlXJTQoIoOoIFCtakxbr8Zbk2U5p4y8XnfyqIonbdq8n3cVpzFffK8JbU2lZwyFo9zOB/wMRrjwTfXVfuepLELum6gVkF1bFOmwKSpTZRsmqvYdG47rsnOEdWcM8fLAV+E9W7DPE50d05YrRa8HDess+eTbeB7rjI4e69EIAlss+fsN/4xH/zWY7765GMunz/no49+xt0H71Dzjs//9E+5efqEmj0nqxUnDy7onj6n6zpWi56jfqDOMzknNuPExb17xC6yvb3h9ZPn7K5viI+Vebvjy4//iqtnT+m6QIyexbDgeFjw+x++z19+8pSbly/48vkrXq/X9EOgi3Z79/sJN4W5RVbbasc+94qxnQgotgiUak2h4gIiShFHLhbZ2E0TIQqhxR1FHOICiIkGQ+zRCNO8w2ll1Xnmzlo+19ozV1hnMbaSgzvLzFF/RZbESb/he+czrzaZPD6i6wInq3vU0wXTJnFHFvzGD844Peq42Rq3Ah9wybNyll2/GtcsnNCHgblUrsfEy/UWnW9YLTynyzN8Khx7Z04CJ2jmO38ZB2eATW0iv4rxU0Sc2c4p4GtrjLNNz83uC55/83+jzgPazXx6q1y+tGl9N5xye3PLNG0RFwg5c3xyROgipSSevXyO1gtEPIHAsFjx3/53/x3r9YY+9qQ0olpYX6+hCierI84vjvmr//DX+GDny+3tBhc8UylE1wETroISbNI9NTaQzrZpmROO1qSj7V4iFaLHY20y6lrEt0KaMj2OKdKahMxhZU4LczZpVWKAObVmjebu8OLIJASl7Fs2M8Z78o6UMwXbwIkXCBFyohahhEgQb+J2ngCHU0U1Uktho2uefV14cP8uy9WSLgaG4R5HZ+ecnR5ze7Ph9fXaNhnjlm+eXXN9tebxwwt2MXL7x3/GBz/5AQ/undBdLPhn/+Vv8c3Laz755VOmJGy3imaowVwkNYOTiK+CYjXujkhpw4XY9XSdwzsbAUotCLPxNb2B3YuaK0JLtQ2Id4R93KZa7KdUa3z1MeJrsc8jWLxOxFHmRPDNQesD4Ihe6YJjHs0hMM8TS10QnOOzX37BPG/4+7/3j/mPf/zvGASurm746KMfkuaJ9x69z4sXX/Ef//IvefDwh7jY84tnf0qNCVfs+VW8w3d6WG9+pw/dD7Kay+gwhH1r4bEfBrVIHoLBcbU2sciEIXEOEYusHh0f45xjGidjeGlu4oKBxc31ibkli1pzbN410chh0OfSQOStbc1Fc/uoxaJci3GWWux5L95i9Q1MbQ4CT3DeYmMK+MbGbANH5wyAXlrz3T7Cc3J60piNrpWLjOx2uyZc2bDHNSgybajhcBavy+YKELeP4sUmkNAENaXr+oMDqWR7boQWGds346WUiTGCZHNtNLeOb81ffg/Wbk1Au91oz8ZayMUidd4H8lzI2Ya/YGvRvfNqGHq6rmM7T+ymLRUbooXgDsKPtd1FlssVq9WK7XZDra3QRCs5zWgJlGob4BBAsesqxkj03QFCriqEEMg5tffE2qhMSIzM83Rwle33Y2CiojmgCikVRCzeuD8/8lwOYlTfd/a+tfWhtAZVafuAnDOxRRhVHOOcGXrPMPTk2UQbs7LqIc75XT2CW+LI9hyQxsoSixyFhqSYc0VdsHKWGkGEiRn1Jm3skxguBHRSXNXGULNhsMMc2rmYGFcK4AecBFKtSCjEmohOyWVDjUKpQioevLQo3pY+2rUWRHGU5hiCPRi+VDM44Gyg5SzrSNHK0O33ZIWCR1wk1mrDL6qln7xSagIdcGrgfJGEC4qjwzHZHjJ4NEQyynZOXO92XN9smJKaS95Xag7k6kEyPhQ0qZWAFCU4pRsCuSppMtOL1VxVepy5wyQjXph2t6RsZgYfoetsf581IQGmogZkJxCkw1VhnLdk2uwreJb9kilvmfOWVA0ePpZEbeUoPinXz15zcnLCnEf8YkHyztYdCIWCC57VMNiQ2kVCGFjFiFNh2fWs1xu++fpT7t15yMPTFVc3ylffPOH58xekcUsmMWtCNeK7BVOZ6GtBNDKjVN9ZuZI3vpjGjkXfUeZMF3q8LeqNpzdZ++xyuUB8IPtAxjPWSqdKFzqWi44YHNkt6WNk6TvSnBjnLZ5KFyKDVlZHC5bDku04mu4RIv3Q03cdve8YN9O3u46+7QVXa8eMIq4SHXQoyyCE4FgXZcrKxeBYRlNrBbWs54HH0zY6ut/CtspH4CQqqHBVBEpiLsLn1UStuyKM2fF6zCy9J3rheDVw5hKf3Cg3RRnFaPuOxFodN7XnNs1sUmFXIycdLBaRi2Xldix8/rrnj57CtQZmUQrWrOEUntwGnq+FZQgcDSOTVm63wqOzwMsdfP7FzCc3jnXukeoN1OYzkBlL5dl14avnHk3Cp5+PrFNkmwAR3jnxPLi/4eHjGdeBkpEwIYuExhG6YlNHZ6wGqR3MnvFV5OuvVzz5dOTkdMl7jwO5KHfOVgQPf/DxzHZ0JBVebJUnzxNTXvKLzzPPrgvXY+V3vtdz790JXQlhdjAqus4NQLggZdglYUxWqVuaVVAJZrkELm8mHnaJdy+WXF+XN9bwJir5xsyQ9rB/E/ds8s7+QbwHyTbPS60mIFmCoqBekeIPDiQTnrC4hjYHU1Pv9xIVWpB9BEzblLz9baLN9sge3gfwBm9+gJK3/+54U+uqv/p/TbWHfdjvOx5J/5VjL/uheqhgFnlj8wcOixBs/WvvUGMz0Wo0RS0uZ20lFsVzTg/xH8Xg2W3XB22KYf9Y1rs4a0pQJ2idLMZRM7nurII9Z1KL1YoLhNDR951FvJwtkrKKCd4+Ep05tGotKB2q4GvBa3tN7aQRhVITJSt1twXx9MFqX2NwDH1g3O4oqXB6fMLV1RXraWQsIL3jnUGgFFKBLMLc3eO/+d/8S3wembcTP/vZb/Pw3Uc4rdw+fcYnf/pXlPUNedxydHLC0dERxIHQDSyGgSE41peXbC7XTPOWBxcnPHjwgK8/uSGNG24vX/Pq2Vfcrjf88ud/QSg7cBGntpjougU/fPce379/yh9//BX/9s8/4e6dE/63v/9jzk8vbCOuGcXqmmecNe7Udt1VOyeCmMBXFVLNePVEbxt8rUKodpWUXEiuEGNA9jW7Yg84cQFXK4ZujURRSklEb4yfy23i+TYzayW6yOmR4M7gzkII+gSnNxwNWyZxXN1manYsj085P7mAeMSur6yWiTsoU9lRSXQhMo5wenzH7itljfcbQnNrTdmilkeLgdd15GZOvN6tWWyv6aKQysQ0b1BZ8V33MArGzlEq4pQoDpU9W8LEf++ErMY3gsJxd8um+5yRu8x5ZJ4qLnScrJZ89c2XDD5wdHLCNE7k9ZY0JY4WK+Z55OzklNXJCUUd880tv/cv/yG653bURJ0z65tbUp45ObvgnXcfsb654fXVNQ7H8ihwrEIInpv1jnFXqEQkmkvNBUgTBquuYk4ahCqWD/CNA0KBiKOGSsmFuT1PXXC43pESaFaCd6gPBrQt2hyRhShCmfTgrJWyR02UxqN0rdJbkRoaL9CYO33vbKNeLbbveo9mi7PtocFSTZDNVPoIJVeywu1uxL96zUkqDMOCGEy8efjoPu89EsZ5YrO1aOOryxu26w2//PolT2Lk/smKr178MXfufsbf+53f5GTZcy8oP/iv/wE//6tf8NVXL9ntErt5pBarbynJUdUT+oxUGKcZamDeJfAF6QbE23XrfMC37HOqwYSEPFNSZs7ZnFPFMddMFwIxOntOtGHjbrsjRE/G4bPxikIINpRorCdXa2P7AdGT/cxul9HJ048TTjynZ+fE2EOZ+eyLr/jwhz/gBx98QE4zz5+/pOt+wb/7N/9PfuPv/y6vXr3m3tkpW17y4vYL22hoazjVQk3f7et3f+zFE5H9OsWaBL04wFw2NlSzZ2WIHd2iYy5KjsqckrlRxWI83tuKxQdH1/ekOTWwdmt9xWD8ut/E1pY/UEGrNdMFP5i71c2IC3hn50mIxvKyBiurjrfzx1xVwXsTMmoC8ZSsBG/nU07GBfQ+GPNRGrwaEyyAFllNXF6+put6i8k3US6E2CrGXRv47QH4JqDR+EOxDwdXVkr1EOUrJTMMfXPzZEo2F5ZqJcRgIppWum44OHsAFsslACnlBvjOuFZx34UOa39L5JLpukgfexbOM43zwTEsez4l3opElrG5xJVUTGSP/WCrzFra91jMndXA5qWYYziliRDMfVarXYe1mGuzlIzqTPQO7xf2uuepuaN8i72ZCDVNI3t3mYgjBCHG3lhELWJnjrKKqolgXdeTkrXEjmOiarLCFu+IrjXUzTMpWwth33fmkPee2Dt8EFIyfqBXR66VUE266PsjyCMwARXeJD2/u0c0xIKoce2qVgq2PvaAVItiVW/iqLQNg1QIKsSwoGRzmQVRc4qLknWmOBPsbdAqbVhr11PhjQstZIfH45w1lRaxocHQEDfOm/hXULxUc2SJQ2trFwxWnkHpTL7JE85bq6vB6BsnKheii1SZjQ8VnHE8BcQpjkwoCVFzeBEEqjWiiWDCjg8kXynVM42Z7TZxu71mKhO5BpwEBi/keUZp7LFS8KpQrBRINDHOG9R1IN5a7WXvqjeHXZkznQ/MuRKHAU3FAPbNZei8IMW3JMVMF5Rlr+RcqBhfLXpHSYmwWDKLNyHJB1JS5rkSvCcKeBVc8GxLpUpE58pukxhY0cVAkgShEoNDfA+usxhhst3RZrejFuHjjz/n5fNr+uGMl5sdV9sNkwNZDGgBzTN3jo/YTokxgAux7eCURbfkaHEKs7HiiJ09j7u9C63Q1cSR76zwxTn65QIfPBIClcC0mwje0S8NFj5uPYK5mIfFipyVZUlW7OQd8zRxsuzRMuHdQJFA7HtCv2SxOKLb45a+xfHtHU80Fws2QRStdG16cpVHchVOS3dwJDixB9ve7/Q3lwQqDi+Z46jcXXp2CW625cDg2WXh2UapxZgQV8nxdDRFNW4Kd5eey52SZj3QyRWYVHm+TaBKJlARugrPN4nX28p5P3CTCjeq7Goj2csbiLUV6FTwHdOknA8LxlH5g88z32wrL9bKJtsJEGumClRXKSKsi/DlK+V6O+PUM41LkNCsq8rzW+XLV54794U4FDZTR6TSu4o7EerKbtg0N4peAxvH9vqUP/jXga9fB6Sf6fzEenS83ik/eLwgxgR4VCNoz+tL5fKVUHaRlV/w9JsN3/jA3bvKLsHmRWQ5FB7dERa9sPnY8c3a24KTGdHaeA7BIlSqeBV2I1xfT7x7FJGumitKTKKprb3MgHDNLyNvPnV7njRBSo1NUtWbImxjbdM71PLmew6T/ak9QFYOTXUHZ9Pe8bSHcgomdupbf7Hu/U3yK7+2t0Hba91PH+GNRPMGML4/5HAReP4uHm++1+ZEa1dmboLRATLbxENa64tgCx3BGcC2Ndc4J8RW91xF3gAt1QhQIkopzbVmW2bQSsAmO6i1TFWn5DIxpYntNLKbJ1KpzU1nkTrXFkshWGRHixIkEIKjj4KXeiDF7+3++ylyra06HPuca8lUmRjqki46usEzj4mUZ7yrbHc7Hlycc31ywpOnW+asXA49F0cr4nrDJo2kcMSH//B/zc9+70M262s++OjXuH/vgj44yjxyfXVJmhzHxx27q6ecng8cdyYa9X3PyckRJ0cD8/qaOK7pdeKkE96/d5enn3xCLoVp3vLk68/45Scf8+rlcz585xFd19vENkYkRO7evctHH7zDH//yCd98/ZKPv3zOkx/eZdW1BUgZqZrB+QPPouyFu1IIqrhoZ0fRZAtRB+oqPmJcHnVItgbQfujoFz0uCqnAXNUmddUaSJLOLLvA0PXkYkLuoj9iLtCXnm2uaM0cN+dWYsGnN8pm5ziJgVoW+PyI8+P36ZfnxhsomeICw9HKFrVzJMiE7zr6bmCIwkyh7AIhFNJoouO95TFHXQIZee/uwLPbG15t1+RXX5HLa46iY7e7xi0X33XdiSzuIBRr2zjaCe1aM2xpm0lj3nmcXWcuMI+wPArosTJNhbMzx2bTsehXtuAXZbFYMuaZy8tXrE5WxMERhxU6ZX76W7/OD3/8IdebGdqCb9rtuH51RewG7j24z/Fyyad/9dekeaKPDo3CvLMoV8FTxCalCmQ1PlK/6EiTOY5UDG5bwQYJ0vhvTlBX0JIJAkJ44xapARXju9Rq7qQgoN4ELF+tYjl2wjwLwQk1KDiDZ1O9rSlcsEUq1roXxNF5T9HCtNuZa1CNJ+j9m2eDF0FiQLwjq9nfFeNskCu7XUZYM00jfexx0ZO6wLLr6WPPcL7k7OSM87Mbrl/f8Pz1Fdt55MtXa86Gjqy3/Nt/8x/52U9+wOXz15xfrvnRo8f84OEjfvnsG7767CmbzUhWyFrpRHGuw8WAbnYGXZVE9D2CQV29mHCWFChqUTkqrmZzojRRw3lHpjaOYmVipoozd1Qt6JipLpCHaCyikuwcVY9gUecazM/uGy9n3E226RwGYog8efacH334Q3KeKdOOMlV2Ycuzknj07rscHa3ouyVHRxdsr2548Ogh/+Tkn/Kv/sP/QCrXkBMqQiDipP4vXjvflcPWD4YCADmYnfbrIvOnvvW7GwMtV3t65ryPRwXjJUEbAgi7nQ1MUipNkND27LSFrcUoAayxLISItbbZuil4j6ezKGfNiItM00wIFm+z9jNzC9qP+2GVa79u8cGUDXDtnCMEi5wZE0daNM8iqmKLtSaCeEpJ5rp563yxOJhFkELwbU+h1Jrb3y2HNrYQog1KFHK2xrw3UXshdsGYhsUYR2+c8ntGlVWhl1KYpglVZ9gI73BOUW3A82JcJtSbKFPTYT0krtq146I5mKA1X1nT4L5RMNVCFzu8RMZxtPcMT0qVlGf63purOs/44BpkvOC9RZRV3j5nGssJc3CJszXacrG0GJtWaA6ofTRSFVKyxsAQOnJzgZlTy1xeOafWUBltIDUnik44cTgXrd1MOAgizrkG0bb1ukgkxoGURoL3DWCerKk0OHa7iZpANNo5+d2/fBGXSBlUDOkggVaWBFE6nAYKUzMQKNQW6fQOqcFa0rw5aKtXalBUvTUjB7V9RcU+JxHUNR5ltsZHX+y5rgrV923vVPEyE9ScekpHlY6inuj3bqBgLXRSEG/PrqQVp22Yr9XWfMGEmlKKsdNqMBeUVFBP9ZEixtbrxFzIrhpqp0o5rBspSqU5a1Jl3iWuLydu88ykioSIq1BLakUoYntwCYiEVkqg7XuN4LQVH83NnRTIVajOioqchOauVFZnK+o8M15t0WzXnOJxxaOpENwS2ns/5glxGd8EdXLH7eUav+rplz0VxWli2UXI2URc5xDvYK6E6Jhy4mix4Hg4Aqdsxltjqo3K0VG0+3ep7OpIFwIOT1ys0Fr54usrxvIaDYF79+5AKRwdHbG9vUZS5ni1YJtmFsMJwTk7Byio89x7cM+wIwVqDGQBVSsdC+JYLMyJ6EJgGneE2BGXC4auR6qDleK9a2B5QZZLPCZmD9E3J50nxoBqZREcx4ue25u5PSuUhVOOVj3Hx8f4knm5uf5W19G3Fp6yvHF82HNSqXNmEVvNq1e886RSyaXZazH3yd9c0AsQFc4C3O2EMw9pNLfKwaeijtvkGBwcd9aWtW5TenBclYK0mNceaGhRKs9YBCeeTiBXZTM6vsnwJwg/uBN4NY9M1Yz4ihweoFX30xbHFuGz2xkXl1ztKp9dK7fJXDb2Go0ZsXeEgJI0cJs6xpKJToh4U7klImTGXHn2ouP5ySlFMl8/jyyHJfcfZu7+9JZ+9QyCNRbJxpOeCnUjLJbC6rgyvvLcrnuohYLj1W7m8xdbxqpUIkErZ93A1QhXNxPHg+On9wr9onCx8oyvBz59Uri8CZyfCe/eLfR9xbkbhu6EdSpklSY22WTKhGdh4TL3VsKj80DfzdRi+dpid4uDOCNqDhjcviDbRJ9S94st19wtoMVTm1petFqEoVoTXVZt0HAT4YratNX+XaiVgwjV4s2HeNxejKJF7VSxi9JezOFHadMK40OZgCZNNKkodX/eHsSot7/Ad3yX+v/j0Ld+sl+MmHX+rYVwsz7vhTnX+CzeSxOerH3RO0dwJmDpvlmjJmtYUkCLuaHARCZn71xwemjKq1qoOTOnHdtx4nZXuJ2EzWwLGe+DLXbgAEc0/oQp/d5DDGKQ2Rrtc2+16TUXNATmlNq5Utlb5kpN5DLbJFJMhAHh4njJXGBY9JyfHnF51TGOmde7wnIOvHvvIWEzcXzve/zmP/sHjOkVKj2hMyt65ztSUVbn9/id/+ofszjvydOaJ9885+xkxcPjJbeYC2fRdwwlsOkyR2GmT2vuH0Ue3Tvh7tkxy+WSL7/6ho9/+RmaRtyD+yxiJHYDBKuhjsOKn3zwmDsXn/D10yv+8pMn/D8ulixj5uHFqb3HUnEuEGNnMalaKVOlMlnen3a9UBGpxGgPHPG+tWxWnFO66BkWS/tMtOJFGJ01fpYKu+2MY8K7Yry+KdFHT5VIiEtWyyP6XHl5eUXKHvE9X617fvkCnj4LPFwWPnr4gIuzd+m7I6YsxFRArA67G1YgjtoqdsVHnFP6EJlc4MvnVyxnW9AG3bE4WXK5S8zFcz5Ulp2j7LacDeB9YRGEV9fC7u9ATOfV5SniZoaYiV3Ge9sA2SZMG8MuUEsAOvCJzdbz7JsF2zkSVpXVynG13oEqR+cdm9vJJtCpEO4sma9eovNMSicG662Ve/fu8nv/6B9R8OamShlP5fr6BlXh/OKc04sLnnz1FTdXNxS7YVizYBfZbWZqsedsqkp0HhXFV1DnEWfAZBHfbjuN+6IzjkhVi45J4+AUMs4LgUCeK0QTmr00aH7FFv7FNn3qPEkUFzKlenxw4OweIe35b7d9oY/BWC8BiwKXxjcplZJa3YKI8VoawyWXQsBipqUmvI+NaydoUNJszVw5JcR3uBDJK2WZOzSA84GT8wuWiwXLkwXbzY7X11esNzsuX71mm45Zdt9w9/QUV4TX33xNP0R+8vAe58uBr75+xZOXV+ymmRi9TV3ThNdMrUrno7WWeYvDloKJNO0Z33mFxuSQxhqx2Iu9L1MyR52oTV1r+/5lTkSZcdUGkHuyh0Wi7JkegzcRw1e82PMhzzPzNDEPHUPoyNNEPww8uPeQT7/4nF/7tV9neztRyw0vnz0hHi358Mff47O//ks224ky9nzv4qds3S+43D4nA1X2oO7v9lGx4cieNVn3a8+qBzGz7h3j1UZDIPZ+TdNbIksgpXIAcKd5tjhWqaSUm6tFmvvHxKG9Q28PxDY3T1vVaG7rJlvd7hvh9vwmc28Ye03bRnsv2Oz/sa+jh3Yz5/ybWFeMtsmpmVoTqg4nEYv3W947BHdwN9VaG9jc40SbA8dg1dbMZ46SPaNpD+KWA/YhUGthmszVb8LNjGolxnCAbe9dVSac7RvsEub+sfhYLU0IcELJ1nwZgrVrgTk6AZx4tDGytJo4Yy2GVtwBEEKH88bIFIQ5TSCt5bvsf4+3pryq7TXUxtOq7AHksh/s+30jXSbnFpNvn/c0T8zzRIhdE+TsM9qLdQdcRfu5xegUaQKuMaq0xS3dYQxrDL7MPJf2d7357OmicW6C0PcdfZ/YbneH89Z5c8vUUhl3s8WutWEZRN5anH43D/GJLvZIEVxuBRdB0L0blELwgeA81hKcqQ5UHLVGY/FJpbhKJUPA7p/VoRScNyd71dwaSgPeReOjNsHQxBOh1oDHI1JaC5wJOMUFawqulhBywcoHzM1m13WphYBRcNVBDuZCK1khWezOnJQRqfZ5l2q4HSe+JR0AgYSjOnOCgRBiQANMqbLZTWx3E/NUydkc9cEHpNrAI4uY08vb+VyrJV6KZCRYDFihxTcrrhZ6SwZb6qVoc5oJUr1xJb0jO2/DLPXE0CEIVYo906qnFM/l9WRuRvHWgLcvEhGL3Dtvny8BJFe0JEpJxljzFvGrakUXJ0cLeu/ZzTti70kJOuk4Wh4x5cR2GtueqRLwzKm2uLQn5cxqGLh7dmYW8FJwrqNbHLGZEkdHJ3THZ8yjtfctFtY4eLI6wlVz2UmMJvqVieAxfMbQ21pEK5JnxDkWITAEd3gN1kCL7c28Yzks2e22NswJHlftx2zZUDbjRCpWOCTO4QfH2WLAzVtur24oc/pW19G3j9pZnYwt1KptytU5FuoZqMZpUtjkypit0bCK2CJFfxUZLWrA4t6bNatUA3ZWS8+aHKTKrMJtBVeVqSi5OkStvjmp8Vl8W+wUtYWpU7uBeeAoVm4TpCpMBT5fO3aq3EzmtBGB7CxD794ST1Qh5cJT8aTXifUENzkYULdBUZQ920nxVcA13gCCVFPD24tB8HTicJq5vhb+9OewHT3rXUeMwstnkR/pzPurDn8+mlMoKU4dea6Eow2P3lvw8y8y69ph+C6rntzM0RoFqoHfEbjdFuZc6F3hvXszd969pQ+wvTzh2auOm6nnZkrMU+beidKTuX/ecT0mNqOnEClUO2Fr4LiD948mfnhWePdMCH4iLG2hnmalNOdSbZlymntM1JaypbabslpbSq7FHBdFzTEhDRRe7OZVVQ7w8goH0Sk3AcuiEO0f3rDD9j/+yjSx/Zj3E3L2omiL4O1Fp+aYk7qP3+2FMth7gN/YgPdiqhwmZn+3Dm2WU2MzaW2L4fZws3MWaJssaZXNzTSGc0JoU7Xo962FtlCWEM1qW22aUkvCKRRprRxKa5iq5gwo9kDJeWK327HZJtYjbCdPoSNGpQvhsMD24hvs3BbHohXvarMuh/aQtMWSy8W4JCiSm72/3R/Mrp4Zxw3XN9dozZQGxgvesZszUypcXFzw5MUrct4wjoknr27pVic8ePyYxx/8mBhmrl+94N6D98gpsxtnaqmIFs7uXBCD8Pmnv4SgjLc3bMTx7r0Trk46OgpDF6gzrPoC4zWvv3xNHwr/+//dP+D9D37MbrfhL//q5zx9+ozvPTg3O7539vD2wVxMCD965x6/8+PHPH9+zReff80fHy/58cMjzo4Hhi7iJeJix9Av6LselzO5ZqROOE04zczFFkriYIie6INxU5yz6WY1oKaTaMOFUgih46hb4oYlu7mwbZy1aS6stzMpz5wdLcD7xmCJSG3vc1ySOKKTyvsnnjhlHp8uee+d9yGsTAwRc605Mnnecp0mm5qOl5yfnjDXwMtnL9DjHn96lyk58m7JvNni65b3zh9yemzVuVfjFbe3GUkzZ8OC1ckpoV8wXO4Yv100/W/1+Dd/9j6VkWVMHC+3nJ3sOFqNHC8TQ6zgJruXlQGRE2rd8eJS+PqJksqI75THD4XjZeDZrbU65TkToj2vnl++oo8eoSf0C0rJXF2+4Hd+97c5uXuP11fXjNNIqYXpds24GxmOl1zcvcM8Tjx/9ox5npnmzDgnqg/GFhNlKgmluSrEIrRajfDmvSO3SOehDUhsnaHa6ueLjTEkgI0yLIqXfMaLt2m5a/dwcVCVUm3x6IKjCEjbrLraBgziCCoU8XTBFqhdZ5FedQYEDnjoF4xpxhVwzQ3s232ytNcsotRc6XtzaZUCqLkLESFlmyCrVijJnq9dRmLE+Y4hepDK8fGSs+Mjjo6X7NZbXl9fcnO75Y8+/pKLo0se3Tnng3fv4Dysn7zgbPCcvHfBOw/u8MXXL1jvdpRSmcZETYWxJJzv25DAmqacc8auqEIXm9vBOeZcmeaEB3KpBD+gqeKisVtqLtSc0OCQIuRq12WZZnM6S7TNU4spFCqhFDSlJgia2B8VpBSkVGrN5Gni6TfPeP/77/LZV19Ta2GxWvDZx18TQ8dv/frP+NM//A8UMRFxHGc6WXB85xH410yaKQhd+O6LxzTn769oZHsIkqiBLsU4WmDnrKqw3U5sdztci3rZ+K3F7NraJufUomv6K+sSEeMjmcBgf2Y/qDVhq7mbTfGxpQGN29gg7nvRxQSrQKn7wqA3QhQiBxYROMT5BrOxvytnu6ZQGp9KKSWbi7Y1ptX2/DYYeAYVfIikvGO72Vr0KDpiCDhvg0ttvKjQNlkmstjrMhfU3hFk/3jvSCkRfMSYV3shzjhLJRdzBzaHdNf1lOI44BUc1Drjgj9MMZ0LlFwbYN0EtBiiXUfBBOycK9utcfG63obRIhC7wDxZ1MkWztJEPgNb1bIXKF0DitvmOJeM1kJojjcEY3HhGnJgz21ypDQfXFn7z8s536KJxYpX2iDQ3ofUfp/a16pNYHTNpdbYb+ZWC6Q0E4KlFUq1tuAuOIahs7KGkgnB22tF6aIjRiGPBk639622Sf5396iugJ/xWsl1xkvFEcD15JrofIeIR1uDaknmOK1OwTvjGVVL9jh6govm9KVCVLTMBG8MvlorQsQJaFSyJivgcBmvQsQhWOlFUbtmg0SCWCzzaDngg6Le4UKPDwMqvhXKlHYeFWpwlNz2TQ3z4lRas15GpOADBPW0GS1445wHjDkkUe3yqBFxwpwq693EzWbHbhqpOLwLkGck6xu3tnj7WsGEvGywQqge7zu8BDKZorkFqJSuN0HIa8QlZ4786u2cJLEbt0zrDC60AZE9o1OdqM7urTXPSFAbOmdzbCmeLJk+OGqdmXcV13uLmGPxOicDeONMhxiZJ9MPSk3M1aLIGj3e9UiVxsRL+DjQd5E+OFbDEo9Hc2G5OMGnkePjJRcnJ6Ttlt1ciccLuuWAD0KMHcPyCK1QcmKIER86iyY3k4B4aXsri1Xv5mymmtJcsmKOQ1+gTpnZC1tVq5soLcEiymrRQ83sUsa7QBAr8lguF0zzyGaztf2NswRKDB15nslzZrvbMaX/3MKTarsv7B0ujoqQqjB4YYknV+W6KusMuXGT2lb/LaeUneAzymWqzCgrr4zirJoYe1Z5KhnhJgtjdWyLGJEfh2hGqkO0UN3+ESztb4F9i14RSK5SVBFmNiXy9W2rimx/T33LwSLsLaKCU09KystZScVcVdV5qkZ8g+o52U+pHFKbQwQhq6eKUqSSZSY3aHOQzC4p31xb8wyqpBx5deN48HRENytqXymj4k4V+VGmmyK6yfifm+NAdEJFzPKurr2/heoy6jw3ufJuP/PwXLmzKCzvrFm8d2UMhLpgkzsqPbsUeH2dOV3ueHBvyYsnibnApN4W0w0M2DvlvRPhN+8rj1eZZbSFu3qbBOeozCUwvfWgrtpAeTVS1BaoSb1xIMQYBT4E1EMpSspyEHrsz2LOJ/ZuKciqJJRcbfpWdD8n4yAI7Sc65tbSX2mj2yMLtVm1UVoz1H45Im++zv57sNOi/TnYS1f2H+ycs0Xet72K/raPvWfLFrnSuEhCsc2gc22ha9//voFqPw10zh3cTtJ4MvvJh7N1EfuYhnhBioFBD40n0j5PTOzKpSDVOA9jGtltR9ZjZZscRQOrRU/oHMfLjiEE27gdxDDoY2AsrbljD8JWAyLOMVC0UkrCV2vkMiCpicy2mVVKSlxdXzNPO4YQWoUyeJd5ebXmvXfu0w8LLq9vqFrZjiNfP3vN0ek9lidH5GnH7TpSynM2t7aJj13k/HTJnZMVL56/5nY9cv/BCdP1xM///Bd8791TfuOj93n4zoXZh9NEL5l884rPPnvOxdkx/+Sf/xapwhe//IynT7/huBMe3znGR9uoR2eZf4MlC3fOz/mHv/4Bf/hX3/Dl02e8eH7Jn3zykg8enfDe/XNUOnwYiN2CGAPgSd1EVMFlYc4T4zwxV1h2A31c4ENPpUOINsUa9sHMynbast6OhB4edpGliwQHXQiU4pizkjIc9UsW/YJRKykpm23mZr3FaWExrJj8MedROe09dxbC/dMTzo5P2STHqInYO66mCeaZzfqWzZTxOrGotxz1mVkKL549xd043l9GfvTwlFeXkafb5xyddnTHF5xkZbVYMqdTOgnoZqZjSTd8nxpOyOWv37gZv8PHJy/P26QyMbgdizCxDLecLW84Pp54cF9ZnTl6fxcvp2w3lzy/hFk7Otfz4smG+2eORe9ZdgYTXh55fI14UZ69vuT8/AiHQ9PE2ckJR48u+Omv/zpzyoxpJu1mUhp58fQZfuhbc2rP5598zrgZKVVY9JFQBrZV2W7WdF1H0dkmin5//1WyVLoYmRV8qJRsTggDqFuzTnXBHBNhvzk2d0EuNvwxlhOoa24AcUSUXGxBLS32YbemFkes1RappeJ8IPrAcrEgRgcSECpebNimDrOmO+Oq1CkfOIMOmyRLbyJYzhZhja5BdkMrPXDemjyDOROcBOpUmam4UglBmasJ+H2MuBg4PjriaLHi6OiEq6tLnr9+zZPrHS+udzy/es27D8754YMHeOkJZcuDYeDBR+/z9Dbx80++Zl22THNiR2XhbWFqpWSZWowxgmtOCxeYUqFmoJorp6g1fGqtFs2LbwAsNSdQW/AXbBAYa/taWiHN+BhBKzkZZE2zve9aEvNUmaaJOSUkBy5fX/Lq8pI7Dx7w/g8+QLTw4MEjLl+9YDcmTs/u8Ed/8AeIei5+/YTt7SXvPPwex2ePce6Km/wc3/Xkafe3cl3+px0NVLlfvWhrIWurkDYNs03gIQImlGIioYTuwCiUtjFMacRNakJuleY6sutE3hITQrC4lnOOWvcbhL3jSZo7XA/Pe2tXgz1Mm4YmABMqxFk7naq2OEsDmCOU0nhS7ZAWA/Mu0mQ2qpr7ae+uUt0zi2jOJ4N7i4M+DiRmCPae+OARHNM0mRMIc8GbYzc0R1RtsTgQMQevOaGULvZYdK6SckJcpet6wwfE4cCkdG7Prcw27LIJDKoVJwHnA/M8AQXnXRO1yqG1LQRLacwpIeqs4r0Wc5ZQcM2lmXNhP+Dsut7OgVrwag1+4HD+DZjdt5ZR703sEWcuOPautFqsla+0gW7TlfaiXq16EC2dOOOJaUsrsBcpy8HBZpxMYwvth/aucahUbZ1nMT3bG4aiJBIxRJbLJdO0xXlP8D0lmzMzeDm0lBleoxwE1+/qEVxPYcZqTG04Ty14sYFgDJa2mDWT1Yarrq3RvFOQinohamNkqRXsqKtEcQ1FIUhrFnUUVBpzqwJ4XOzwNZuhQxPONZPAnicWgjnOFh5coGJsJonBDApVcM2Bl50958w8UBBROtci2dXi4zU2jYiALwBK9XvXYyEGKK4ZDKpnt81sdjPjVJkSaA1Q7LniqiCus3W8E+wJkvAeCpMZO0oAjUgOOIFQBSW2IVTXrneHEAjOWthx3hxKKNM4IzhcV80wU+x8x5tTJwbwzgbttXqCRLxzJGfWESeVLniKBqr6xjXswPd0MRC84kJhrjMZR9d1TDWRHXSLJbEbEN9zFCJHi4GuHKFdhw9C55Rl3+PUIxJaNDUdig7OL+6wnE2YTC7ZPrsIQ4hEcQS/sn2OC1SBaTKrTggdaZpwrqeIkMQcdIMTnFRitLKt4hw1BHw3IKlCzrhm9HAi3N5s7FxyJqo7VSRnXAzWDpwmOh+akaSy2+1wqiyHFbFb8O1kp/8E4Un36jsG1xK1NPoU7IG5UGWXCjcFdupNjHlr097kGfsPIiR1lCzMFSQWhhg4cspcYGZv6xQoNj3MOIImKpY59dhieW6BLkP3CCqO3H5ex0oSQB2zRFsotQVv8WbNk9IsyG3gJEjLvELRfHBiobWtuypl/xuk0hBueLXvzuYNtr3ec2aqE5J3eIHewYOjzIPzjMsLPn05E7uBi2EJs4lndQsswL8DISqbz+CXHyduxhVJjJMjxVHFquk9jlgLRxGOBsevf3TE45MRtonFakJ8guK5vIbtCBIS6zETRRhzx6sJPn2x42bumRWURFCDww+hcNJFLhawChnNlVy9tf1UoRRPqq65mvZRuSYGVsi1MhcxS5/CNFWDpFUTAFMupFlx0WzOuhdyxKzGuXL4egX7eda3XE/YQ6seTDw2LfqbLqRf5RLsz0O7ib7NkzqIl7ST6nD+2uJMWiSj7oWo7/Ze9VePX7ke62ER6XxtDVLaBEdBijZujLz17tgXMe4E7AU8q4huv/r2z9vPfBOf1DlKsUrj1JpxalHG2aYjm6lwvancZqDrOFoJxwjHQ2DZGplUm722uZ5w0AVH3ypTtSpd5xmy5cRLcGhxVO8pfr+otdfu1ezk825NnTy6XNEvFow54b1wfXPLwwf3uP/gghcvn7GvC95u1nz95BsefPOIs4sVwzBw/foZV69eQexR35PmibM7Z/zg0Sl3v/8eR72Br//H/+E/8MmfO373N95n8d5DyrymFIManzjhydevWC48lIlxt+PJ188om4kPf+1dvv/wAaujU1tAB0+MHqu0EXTo+Oj79/jdH7/L0xcvef78JZ98dcrzy4e8e/+cEDp8WKLSWyxOzH0oLb+ftDBWSPSEeIfYnyEy4Fwg+EiIHeI88zwxbW/ZzjMlC0eLvi22bVEbuoCXI5zAcuFYOI8fLP4477bsdmtudpnHZysWqxVDPGYzJYqr9F1hLpnr9Q1EA6/O7f5Ri5CrWfglZ0Qd4/qSTdmw297wcuyIX7/gwfe/h797jz4MhOAYR2E9j9zuNhxJ5bw/oT/+kGElxOV95tE3Jo28uUC+q8c84rDp96Y6ttLzqgSePT/Cc83J6paLi8qv/fYHCB2ffnzD9W6J9+ZKcd2KL7+64eKhLSLQwtFJx3hd8CFy93zFsFohEnj59DnDMvJP/sv/htPzM568umROMyknXj97RnGOo+MV53fvsr664fnzF8xVmbUy7W5wKmw3O87PTFyVArvZBI0CaGwtUS3y7pxHpVCw0Wt1bfq/V7S1vHGdehtA5XlGXbA6XMDMqg22Cvasckp1gZCBOtN5W7AFcfjoceJZrQZcF8g1E0itMapFdrxF79FICUppkTswl6xzihaBjInyVUEcfQgQLZocY7CIiVokWLENV85KkNwYeJ4oSvaBkjIei9wsjxaELjAcnXD1+hU36zVfvtrw4mrk+bNbfvTePd57cIelzLh8zf3Fgovf+TEff/Ylf/jHv6BmwfVYhT22sUeKbc69OSWCeHKyRboP3oYztZh7xHuLH5Tc2GGKBm2bZ0E1EXpH9YGpzHhx1iVY5iZEgZaZOifqPDI3FpyfZ5al0ouym0ZOzo5Iace03XD6wQ/4+JefouK4f/eUf/9v/2dOT0/54MNfA3F88+VTfuvv/YzN+oqL1Q9J21urKe/i38JF+Z94qLOho3AQloL35MbgoYmkBUCEnDNpNsi1OGWcZ/bNsCAtftWeyc6ElNLa6VyLoVmEzB0mv2/4SPC2a9tEiswQOvuzapGc3Nh+YHGy/UPUOd9EpvkgBmltzZON3RQ7c8PkkpveXNnD1WnPoHm2eGo4DH5qe/0WDwJlmk3ESMna6+ZpbqwoE9TSnFksBlKaKLlQW9zOXFV2fyjZnFY5K6lO7O/3rsH2hT2HKDPPU4OiK3neURpk1zeX1DAsmCdzRsXYQXOc5dxG7Qp9PxCCN+GoiUP7aKUIFuNtf3/s+gPyQKtxsiw6Vw6vcR+JA0zkcRzilrUqOY+NI+XaudFaKtXYWZqb4NnWbLVw2JDXCrGzOCK5tPPL4b0Vz9Tm3HIS8bFF+5JFDYvaWnKerQ2xp6d2gpmVC4tFj0ilFCUnQ+VMU0VdY3q19aTQGFHf4SO6gHfZREAC8ziRa8FVh++CNZp5j6vQ7912zpiZXvwhnROdb9FwKGouFaPmROoMKpXkdtTG1PIFOtmjaELb7GiL0AoeE1uDF2uV8xl8smIAv2hrcMwZU5tRq8pX8QABAABJREFUwnk8makkJAihxravqWgWXDZHU21VfA5wQe05INpMHw1uPRfmubDewtV2wnWRxfGSmme0KOIKNBeNisHZVYQG+cJ7u/+IOmp1+BAoVZlroYiQxf49Ok/OlV6tsMCFyrAKtsavDicrRBUNdg8wwUpQlxA19A0KQ9eRakK0MyZiCARX8apEhaPFkbXuiac6IUYT24dhgfd2HTnXEYowDD2hC8TYs1wcs1wtWa5WHA09ERh3OxPZPEgD/Dg/4F2k5BGRSPDBimO6iOs6fFE6PzDrjFZPJOJrNQeSD0gIZKVx66w8Yaq5IU086qxcBufRsNciQJ1n6JcsYk+oM5or2tibwXnWU2I5LOiiN1ccSp4TiMVJL47POFotcT4wJXNFDq4jSE8UZeG/XSvlfwJc3I59w5g5aCuSzZGC88w1M9LMIE1B31uLzZtTDwq7E9/EncpYDFCMKJFKbm0eaCtE1j1w2zWZoIkLzTXUHHjsvSvKGwj1/qh29Vh5stji75BNhsM0by9LuNZKUb1Dk/lCmgTF/oGl1SynNFHEFg02ydpvYzzuwCPKGiFUHr078uFHO8rrzDELXmxGXl5uOFsHOgnEh0AHtRMYFzz55TlPX3rm2pnMVs26LCoN4m4n2/GiYyob/uiTNV8uCxdd5acXPYtbT5kXfPOJsh17tk7YpcKdVc+fP4FfvMi8mJak9n478ThJnHm4s7ST8ZtrT7e0yuhZQSWSi03iRKFSSGrSeHaFqoFeKlW9iYxoO2/s5CnJMc0GtpwRvELMFam091kp2KZ63n8wbZpns6IG3Wu28j0kDyeUw8Km2cDbUl/a+VjfklLsXNpPXOTw+YpIM6G/5dbjjUuutrPlV0Dmf0cOJ/vv295nH+wBmFsltjbBjWbNt+t3f+zfz7evH4PNUmsDLe4XX8XqWqlIrVAyJY3keWaaE2OFzaTsJlgnWE8wzcpcbaF1tuwZYmARHIvehCdjBSjBW7t5KEIfTXzK9U1Ut/NCCR7tovGjnBB9gIOtHLxTSrVJXm2VzHZeJS6Ol6CV7W7N/QfnfPnlCWm6hJLwTrm+es2f/NGfQBnZXd1nOQwWJ1ueUSVwe7lhnr/H0RC5uHhIn6/ZuA1elU8++YrzVSS4BUW/YX2zYbx5webqNXdOBn7wwT1WUXj67Irnz19xtlpx/85dhtUJw3KFc7GxEgx8qu26XZ10/N7PLvj3f33GV89e8OlXL/m//uETTo6P+NH7K5xEVDtzrkw7fNnhm7uk847VYsXK3WGxuEfsjoEO8baYCS04nhjNDeE8/bLj/PQc13VtcwJHRytcCJYtr4UyZjQENE9U4Px4wUkUjnrwvidVe9/7ECkamMeZUjOr3rhSne9YnvWUIkzTClxgO83U8ZL15isqwvuPHxLC/5u6P2uyJbvyO7Hfntz9TDHdIecEEkABqAJQE60mkl2yJq3V6uaT1JJaVOtb6U2mbyCZTGZ6kKlNTZOaItkkQLKKVYXCmEAi82bmnWI8g/uelh7W9hM3gSINaLKrkp557caNOHEG9+17r/1f/2GBuI6UdH73JrDbjsTpimHtWPU9dr+l847qTojpgNteMm2FmkeExXEN+LweQRJTi7uvVtfSikNcj+Se8W7Dp7sDy9dWbK8+4dMPR4rLWDKDDxgJPH8urE+EnCs5VYYl7ALEbaRGoVsYfM3sDrf89ju/yZe+8hWurm+1wJ4y0+HANB5Yn11wfnrG2XrF+9/9HjFFrnc79Q9zgUMcGVYLDuOBGitTighBmYeiC6K1TtmHLURbjMpzaq2aUAoYiRgJr8zP6u1onSaopSpIrljfnB6rUd8ImlxJKqEa8NLumyb18J7gPcEHBb0a48NqCBilzE0Koatg8Qw9VGsZ2RNrRQr4Uo6gpW9IuFSrbCYqyRdCfzSDRKTHW8GZgsmCZPXWKVXAC9I22HRGNzSiqWZn5x0X6wWHOPHi8ortduTp3R0v/uLHPL2642tffIPzkzXEHfH6it/+8jnnJ9/kn/zz74OD0KknX2rS8iIV4yGVrEwwMrkkrWMqSBH6lXrqtLcOxqlMGjWxV6+Lxlpo8po8FWyv3jbqFeWOfliIUAwUKcScySlBhf12y7e+8et8+uRDPr28ZXN2xslqxSefPufRwzf44P3v8OOPPuQfPn7AX/7F9/j6179F1/f89INbHr32LofrH7DLl/jF5z/wI2VtmIjVRgkiv1A+1OPfzQQ4F3JrEqUUEeOP7CTQNSyl1BLMaOlnM3NJ62z1T1E/RefQtLpcjxv/2bw7RtHXkNQ8oFpDwXtlOrdi21nbPI5Ax7U0yRqNAaXO07PXmW6Kw1GKV0pWubi1WKMMIKmZlPXnXdBk2pwUqKpFUyNLEWrKysCFI4hVaiGl+T2Xe9+j1IzAMYgpSFYzdtrjai2UCq4GcpplepXlcqVsqqy+Lqal8Cq7QB9bip4rmlWA8yqBn2Ki7ztC6Ki1MgwLRHpEDNOkzKZpmui6HmOcMiamSaWGJYOoVGq1Wh2ZV8bOnl7u3kPLGWW7tc86e/ioVE49v1CCOCJz2t+8h+IoSZyBy1pmjyda0rHRfVPz/VJgMhFE2VjK0prZVrapCUwD7iLOVUIIdF0gpkm/j/qUpeTxQZP89PPRGqGf76NzllI9zvSIMbjeIp2lSgAipujc6I3HDHrvGdHz7DAMIaiiBEc1Bl+bLQ0KIBQS4tD7z0wYyYTQ46pT+R1Jk/Na/U5wOi/nijcJHwyIhdJ8G62ls6ghtejYs2qUSs0tRABwLfFNnM4RIoJxjpIzzg5421FLwriE9ZZQIJdCMYWYEs+e33LYF1J2FCMc9jvGwy1OArRETWMtOEMyufk0qjVGwDYG4RJrCtJXKrEF5Ona7MVi6VSa2msqnxRNa150C0z1HG4jfQj4TplYMRZtstoJMRErsOkXxFSoOIzt6BYLTHaa5GkMXoST1ZpwsmJpNe22lELoHEPXsVqsEFOZyoEheLztMKbHuoDzgc1yTR8g18RytWa9WHO4u2NK49HftpaKDYHgO2LpqVnnuCiV1Dz5XABjDV0Rum5QFqWBLOBSRXIk9IEuqPS8SsQU9bEN3kMD37Nz4Je4WukFNqsVm+WKdJiItbDoLKEbmk8vTCljquAox7TU4WSF9x0G6FiR40FDPQ5RUwEXntt4UEZcWP9S99Gv4PFk1UDYzIpwBSCsaIGXZsPE1smZd+PSAAcA37yXnEhz1tcnG6shT7l5A8yGxpYjDDTTP9v2V6pQNcCRo7zqlT+A3pTaYvnM55CmmZ/BhKa6OT7HrJeHli/SEtisoUn9zP2D0SfQd9nMqRsYUWmsadM6WEatN50k3CLSXUw4H5HrzOZLmckeyJcV+/6GGipuSLgUuPnkhD/5R5Gr7ZpcrKb7UNEUt/tJrSA8u95Tq+GTy45A4WIprDbC+tEJ0DP5NR/FSMwdQwg8vas8HQtXB0ciY8hY8XiprLvAO2ee0xA5JNHFR4Ragxau84TZul9qb1sw4rgehV2yPFo69cqQwiEqK8ob1bXnAlUMpqX47YvgqqhxnLVsk7CNlZSdygW8x6HxwxX0xY8wZLvm7Tvt/0bK0euh3ppG/T2QBqTqb87XX9k65viT2jqQMv85AlRtXN+/4n9ER4tdd7bRqk0b2+CF42cqWa+rgSa3s0efpYqmOSlwjG4Sc9bORi042wAtFIiqRWV1KU5M0579IbKbCncJbqNlNwljUYDWFuhxrJaBcPSRMnRBi95StTDyQQ0Og3N0wdB5g0mV3ES6zlmCdyTnCV2gK2pWL1WfozaxrWv3e5FKnEb9noU0JKjC82dPOT99h7def8zu9o4J7SISJ66efcKffGfL7vJ13n7rMXSe/uw1KBXv14zTxNNtpO8tA3B5+ZLX3jjjyUc/Je0P7G9eIHUi7u948zxQV0t2eSIfDnzwk+/zF99/iuSRr/3aWzw8P6XzQe975ykNqDfUdh0rwQlf/+KGP/rm2/zfr7fc3Vzx/PkVz68Lv/aFgDHCOI5cX19S4iVnm4qYDLWwch2rxRl+8Q74M5zrMRhSitRSyFIoZSLHiWAdr188Qmyg9wumYig103eexaIHa7F+oV4zkjEmUlNkcJZh6HGLHlMLcaw8u3nOPk2crZYEHzg7f0RJlZwMt7cHNqee0NJNnO8oRjg5PyXve7rNmtVmxX4UBTAs+K7DmMBQbvHyCQcOrE7eZRfPqbfPGR69zu7lM8b0nDLesDp5R2PM/yO4ifNs4klBalDPLGPV37APCJ7erHn+9BIrhtXZI/a7AzWO3E2Rsn/GcnHGdPAY69jdXuJdYrN03CYtUKy3nJ1u+Obm1/lf/lf/G7I0oUkqxGni5uUlm7MTur7j4YMLnnz4EXe3d8RxhJQZp8RqswECJu1Zb1bEMRFv2ia1atJTidI2HIYuaItGaktL87qBphS03VqbbDqB6ZAsFIlYq+acii85fGjyuJY24axtKT8TjgD0hK6j79VfZE7By1IwtbLoOowUTXsDjBWcUYm/9SrRXXaBGA0UlaAZUd9B6xvLwXcKslUI8+bcVILvG9tBfTJKLWqSgYIEpskbEup7NVXD4LWLboqyo6z1DEvHW+u1bjxq5vrlS376yQtu9z/lS2+c85X33qNME9d3mXcfn/P6P/gj/sW//gFXdyMSOkxVT5VDLHQEuoUoi4Ss3Wm5Z8iIMcd1f0KbO0lE50yjLDkpWidlqZSkkhsvE773usmtuuEyTkGvEtVIfrKJ/eHAMPYshgX/+l//Bf/Zf/7HiH3Cw5MNXbfga1/5Cnd31/xX//B/zdOnz+i6QImGm+0Vr7/1gC4ELs7f5vfP/rd894f/jD//0Xf+um/JX/mYe2J6zJXEPYg0T0TzupuKtsn60CGoZCvn3JghWuXUXDG9YRiWFF/JuTCNo5rI2xmIKmp0jY7TKrG9DXeUpeV87/0zs2usVaBFmiReKA2omD+D+hmpP1ODeIyl5KgJiaYQgnqRxDgqi+jI3FF7C2stOWWyOthSi0qVjhL9BvjknBr4oylRvtUl69Wag50Yx6kZHKtJcsminqGlKGPXaDrqLDdEqtoFWK++hTlzGA9a50zaVJ49baxVlp8xnq5bqOy2Ti2lTtOjcsnEqFLWlIQ43TYDc4/KEH1rbRqcC/R9/wqASAPA9STWWtjvI/0wEGPEejkqHtU8PmOqMp66blAPRmigYTMuNlCLwfUCpt5Lfdvr5JJQxtsMTtHkhLNnXmNlNQ+tVhVTa27bKh0vBsgp4bwCCFJtu5YVSBgjBG+UIWUFaiVNE4vQNWmdaa/xGb3B5/LohyW5eQIVEZzv8G6gRGGKEyKC7x3V6bpkTEtpzbVtBvWemv1wjXV0RgMbiiSokWIS1tWmyA1UHMVYjFepuMsJb0IjRmjgTpGIqQlfHUaaN6doc8dUlcA60Ga8LUx1ohgdvwu7QLxVdqUYKBZjC2KjMoUYQMAEB7ZiXWi2HIUYI88ud1xtNV0NKepF1ZLXSpPuFSzVW1Ldq5LI9erBaMAklWgaK1gfVb1SerVUIROsp1PlNs526ktmwHZdY3lCbzuWS01azmWPtZ5uGNS/ioBlQYejDwNjPDBKwruBziwI4uh8x3q9YbXoObk4Q5oaoB/6BkRvWC1XpHFkOoyM6YD3Td5rHLlUbZJboZZCN/T0XU+/WFKzUJ0Hb1pZowqvodMEUSkqVb7bj0z7g6bMOauhPDUhZWSME3MAS7ABJ5WuVtbDgJQKxWF9wFahpoSzHhscvuvwLrCwjnXf0beQh1XXs9lUDikqeaYUUhrpO4+05Eu8J1bDFDO77V6bl75DJDDFSC3KHPNkSk4cIv/hPZ6oVQcb98tjpCVTzZPQsfd3zycRoLSH9MbSY7AiJKElTKmZdMTgzPx92xhGjYFiZgCgvbJpoMXPvcVXzRTnibH95H6xnwXKn/3NX3wuhAHtFO7IFLEqF/sM54mm0dTiwc0MkCM40Z7ZqJn6w0XliyfAVeaT78Jp17E4M5x+eSTlFTd/Vnj+w0i/8VxcVMqTBd//S8eTny3YpTUZq5OTcPQnOl4eEWIxZOuwOCKOKWb++Q8rZvWI8W7Ldz+qXMYOkyxjSdxMlkkCWRpLpBqKbakWtRAkct5bFsbwcEisQyHVAVsLKVdNkxEQa3FW5RTFeOJoeXqwRDEsvA7ine5v2QQ1xDueN6sU6H0Eaz1SC84Kk3i2pTKJUlNrqiCKznfOY4sua6XhkjruGlDySkFHAysKhoB2yOwMRprG35F6NMCfYcwW6sbs/VQxx2JpTsCbh9h/BHtWPUQLUess3qkW3xoFDO2rn76COKubPdHO6/GYQeAmb7SC+oJUpflLFpypOCk4EShZQac8kdOO/X7H4SDcRriehEmcxtNWIRjP4NWAr3NOOzNYjJWmc2/3uBG8Mzjb4huMoXMeJ4XiHblYbFGpSgiOlB19aIaoRumzST2Lj3OV0uA1aaTWif1ege/DdqJ+4R0enp3x4uyUZ89fUNKkj7WV6+uRv/z+NYf9FWfnJyzvbvHGExaPKOGUxdk5t6GysHdsr6/Zb+94fLpi5SLbq49Yrnp8l/iXP3jCpx9ec/L6I86MkLJwe7Xn9dMFb7/xkMX6DO8XGOvVm6oVg9bqZq9IpiCcnGz4n//+23zvoxf82Q8/5skn17z/s0u+/oXXOTlxvP/RJZ1c8+C8Y3dI7OrIMgh+CHi7JnRn4BfNTFRB4ClHap6o8UCKe7yzrPozqh24GQvOFqyBVCLT3YgPHcuVRnNj1ecnkNVI3Ti87Vl5y37KZMk8PllxcrYC4wjdkjRFxlg4e7Cg7z37/cTt9hLvAycXp7jgqOs15MC+FA5ZQQ9TJ1IWdtNzevMBNn+AtxtuLjew+4gHpwG/Soy3FjEbtmXN4ZPn5P0dDB38wirw+ToO/QUijlSrdkpdG88IC1NZLwLnJ4GbT/+coe+wBJa9pz+74OZuy9nJQ3784SdMP37J17/+RaZ0SdxX1mc9e1MwnePDn37I3arjf/W/+284PXvAJ08/YRwPCIXd3Q1+EVgsV5w/eEBJE+//8EcqfVXDBK5fvuR5GnHdgsWwZD9GxhjZjxM4R+csUwXjLKFXY99clQWSjUFcBznplfAd0opZYzyIR7Ca7lMLk1isOJCMSGEaDSYEQrAqDTMZWz1iA84K3mihanCUaqlotxWTwKsnXO+a/M9CLQURjYw22SFBi/il73ST2fwRfLtfizVI0Q29s5Br4TAlzF3i1GqSlcoiHOrW2hg6bWPtrKM6A86TJOOKUKIC+kKTPRvBB0ghsOkG/MMHpGb0/8HLA3eH7/PlL73BRz/9GV/88hd54/yCP/q93+DDJ5f8+MOn7KIyk3xoQD+WYDumXJhiY487ZSCnccRgyNUgzpHapt8abXvlrOCA6zxmSgiWXCvk2PyqFppISFV2j/Ft66qdnJIrKWZ6n+n6gavnlzw67Xj/u98lh443X3uDH//oR7z+5hs8e/6Uy0+f8V//H/5rXj59wkc/+4g33n6bn/7kA4IJ+PQmq/DFv4nb8lc6DBNz29MC1czm2PdrrDXmPpsGcM14WVlDPaVEvCuMKR+BjBQre9lr6qwLhOAacATGzCxk31Kt9P4pNTUJV2lelTOg5DBNmqNyt/uUOhF7ZOF0QT2RYoxHc25lVSjI4WmNEhqXvKVEAupHJEWTHo2yb4zopmxO41MfIgXNnGu+TpVjHeCssqJevLhqiXbQ94smG8yoVMzr5rt1F7uuu0/acxoTXlIGNLWuC/p+p3igVmUw6bVRCWNiIifTIsaFcdrrZwFyypSiXm6lGanXatu1Uw/c2oI1AEre47xtn3k+18oQEqltcyY4b/B+rs2qWgy4rgFRY/s8+nnBEEKg1pkZlen72URco+fBHsGnUirWybGu08dYtS2g4L0lJt3nafCItMpaZZCGlopXUa2zEawDKRq2RNXAkilOKlOyFpw2Accp4uorRhfG3NuxfE6PrltirSenrNO265rtx0QYOpz3uEEZiSULiKPaQnaT7q28A+egWoK4ZvdScAi+iIL54hGTtNFvdJ8sVlmFnWj4jXMO650SAIz6E1mTMbaqb1qwysC3ckzEcx5tNFqPq5r05kTBrEIGyZAVrEpSqHmic81WxxSwGeOK3qd4Yq5cXyVub4oyEXPCeCjkBoZYqJXi1HymWgEbNBGwKpvOWQ2yEpTBr+QPRxcWIJkIWvM6o4lw4hqL1mtoQdX7O/Q9q4sVsSbGndCFBcPqjCSqbPAI6+WS/XjgrEJYdhAsQzewtAND17PebAidpe8D0yESS2W5WOh5sj1Dv+B2SpSYWfVrsAZxKntdL9T6J1iH90NTQiUMyvzreteahOqna6mUNOKso6SJcigQI10pFAsmO2LJSIWUVEJrrMMER5J7VVWVStd7EIu1nrXvSVVrE+8tQx+wYlh0gUenF0yHEd+F1ogoBL8gV8MhTawW53SrwLjfQtbgoGXwbMcdOSbGaWTcR2pVrMZIoRjH9e2OaTeyGzNT+uVYi7+8x5O2ZV7hgwBm9rrRwxqODCAlKjU2kMxo6xw7WY8+PbaBTEWk0eubVEpagl4DheoRPDLcwzqvvJfPUJbnTbR55av7n3AEqI4Ilb6OmcEFMCazwNBZw8FBwSHxXmM9ox3z+bi3Udd/HT/48ecWb9Wb4vbKsr/p2fnIF75QCXfCzfM90yFw/sizPLWUu46ffrDmX35feHoYiBLIcwHXPLTuu2R66DmaWqdSSFJ4/3ng9tuOLjluDw5bNDJ3rBYN1JzBvIFFGClkdtXjPQyt87zoDIM1GhltW2qJnaVoTXcsmkJ4aJ2mQ5qYqiG0c2gtLLxBxOsCLJWCkCrEYhoTBQ7G0mEwos8sRuiMwdZCrKImbEa9vI4An8zFmmlgwgyV6JXPVYhFwDk1woajaPMzfKUZSTLmyPZBaN2Denz8zLQ7wpr/kSBPM4hmncG1Ys8ZtfcrLXHOGKEWcwR3q5hmyqvGvUrft8yMsDJfu4x6K+SC5ISpyiKQEik5MsWRw3Rgt4/sxsxNdByK3tlgCday7GEzdCz7gHPaDYrFNGlGJJVMSpUYFcyyDVSMpRkIWwXUtOt6n2ronMVbQ2gSW5qvkViLqcpwsujnpepm7yBj6xjCs6cv+MpX3uPBw3Pu7m41JUIqIpq6c3Ob+elPP+bNw8TZ6cRiWDAkjyxfcvfygtSdMZo9t7fX/OyDJ9R04Icf3HG1vSOWyjRGxmSIpXBxAJY9tcU3v/fmY9arM6wfqL7FO1OgmpZwk6gUpjRRpND1S77whdf5o9/5Gu8/uebTTz/hn/+bUxZdz8XFisenlcevdezznlIzUnUhwXQ4hJOV4I3Ox5LVMLW3AUNlX/a83N+wCJ5+sWY7TXxyu+e1sw0XywWHceJ6d8Pp+gTnezpvSHnP4XBN54SFWyJieX59yaH3rBdrzjcrFsMAuWCsYTokLZI6y+HmDpOi3nMlMazXjPuJfLfHB5UCjONEbxP7ccTLgSlHbu+2TDc/YWVuef0rXyMdNlhuSBPUu0RYPSBNS9gm0v5D0vgxDKevzNefz6OIoFahmSbQomvG+m+/9YDzVeb2048Y3JJpu6eUPWKEPgWkGg4psvSV9foB1zcjFcf11US36Oi9wyRhvej5tW99k7/9d/+YlzdXxDhxuLsjp0SaIpvFkuVizcOHD/mTb3+bnCp321tePPuUvl9w8eghvbPspwObZc/TJ58itdJ1TgGU4sg1sQquSbQTPZaIQUylSkaaIbBIxJiA2njPLpEtSUu1/hgE4zT9p0hFSlHwgxZL3hl6GxiCZzRVAdrc1iwrDMGpzAFIVSVwIuDEIi6oSXgSimSoLQ46WHxyxKzGr8UKLnTkFBEywWkH1IgyfmNKTKnHBwiqQNL+VzM3F1tAHFkqpmr331sPxpJKwbUIeIdGqfdOoFR208h42PP86pKcMg/Pzrk5CN/+kx9y0i349pM/4/V3H/KNr3+Zr7/3Go8envMX73/IzdWeyRaN2m6rmjNNsjHPq+KUMWYKvg+4WpAKRnQTmvHklmmk/HStN0pbkCWrLMSaihXD7jCyPeyJDVAYRP00SsnKTqmFf/rP/jm/8a2vslys6frAarPkt373t3j/B3/B1e2er3z119lt7/j4ySe8/9MP+KM338RZx3KxYNgM/Jsf/o3clr/iob4sc/PqWL+1tUpNtUGNiwuYJqkqs6cORzmU9+pXVIrWRYtFf5SPafKaAjfq+6S1q0jWtKgmKZu/P5uYq6cSr3yvoqwoewR05kCVGCdqFULQdankZlBttaa3zZBfRFOrZvPUObHYO3ufhFay7g+aHQdonaJmzVonxDg1wEq7fbWpLERqk4LDbIit9cM9qGeMYbFYALDfp3Yu2vmeNRxCYy4pKzB4j3OenCeUsWRb4nJjZxmOX6vXTsUHq4EJKbZaxJEbMGTmPZHoa5WWVjf3wr1XRkPOKmUrReVytv1OCJ2eoyajnHcbMY5tDAT1h0oauCLtHOl1okkl74Ni9D3UxpJSwKyWpmxoAU3q31mwNij4b0qT8/l2DRK+gVizIbyatus4DEGtSHQsKvAc44SUSh+6ZsWgdeeRevU5Pkp1YNfYTrClKAOIQnWhnSNtclCTejO5vnFYe6pVXzFdx5xKXI16EmLAuh6Ti44X1LrAFgX71fBZ8NbijabRGQMl6XzijGC9p/MLBQ+tI1NbEI3FBe11YC3VWLrqGssq6l6sFsQWrLdQ1EbFoJ5L3liMKbjQ9uDFsD9EXrzcc30ZFWTKFUwz4q4VUwtUj7EDKWuj2IoldGvitMVKpPOV4ByJjmyF4h2l9LgK3nSawIfF+44qlWG1hFqZ9gfCMNA7x2ro6ULXAJiehfU8evA6XehYbU4QsYipLBb6uGkckQLd0OFsZTl0mAIGj+96xBY6r2ltqRhKjEquqZmSJkKwbM7W7b5QpKz3nuVyiQi6bksiOMiS2N9eKYDt9YZM04iIpskVa4njnYK3JWFE6EDN2Nv+vYrgbUdvDViD6xeUpIypEBxYcF4YcCysY9H1dMMZ+/GAkcgi9Bx2ERkzB7MHDLe7HTYoAGytMhFLHhmnxD45xnGHmSYuzh9SJXPzyXMOd3ekVBizSmY7r3L63lvifs/hkLnbF/Zj/HfcPffHLw08NZvCRh6StkgAM8jCce185R96uNZJyVU0blBqM4O2n2GNGFHmwZxE09ie+irm/olnMElefaFX5qv77x/5K6884OcQub+i42QMdAjLYSDVQizCWFWcY2dggnuzdDM/D/PkOX9XASARIWbh6R3EKKz7wOsnlVXfEeQad2c5HQr2awmzisSp49lHp/zoZysuD5aJSjWpyRB14vossDVfIwdFz6EXofOWiuPJteesd5wsCvu9sJ9ZRFJxUqnGsPDC1x4Kt/vC+3eBzhpydtwcEg9WlnEy7Au4EKFa1di2RVBT6BwvJ8+LyTJm1ZPvksfgGZzlxGtKUaxOixIsSeA2F1I2eKOL+qEYoliwCjRNWYsKaz3B6JiJtcGR5p7ldn9lFUhTRwQFs5LKrhFpZqegyYAzc0maGa3IcayIqI9UbUbixz8NvJhH0X8soJMe+umcMXTOHj0b9N4WrOiYtt5ixFObYby0e/J4DzZQZ6bMq6+D0rtjrpRUNfWmZFIcGQ8H9uOe/RjZxcIhFsYkZKOspkUwLENgM3RslgN9N2CdVZlPKaSpMObClApTzEy5UopuQg00DzXtEFYRNTiVqhIaCy54TCoah1qLRsW2tBxjmked4RjLXGolxYQP6gj86fPnvPeV9zg5uWC9udaEr/FArY2qD1zfjRzic17fH3jtwQXW99ibp9z2C35y/YQ7d8ePf/Q+zy5ftMUvtg6nsPSGNI7EYrm+2/Lpx9eYlPnSuxdcnG+aSWmPsV1LO9Jo+ipQaiaVkSlF7aS4ns36gv/0dwL/5nvP+Bd/8qf88IMPiGXi7//Br/HFNy4Yp4lcJqrkFlXtmFKPNR12jCzEIwUKld51aowoltjmwqEz3O3vuNtFToJwPixY9ZaaDJSElIm4vyS7jjGOGCoxJ0xy9N3AOE3Eww6xARsC1ze3TDeXuEXPJI7VuqPgiNsIi8zJqerGu1BIOVBMwbmO1XpD73fYmri+SXz/e9/n4VkHbiBud5w8XGHcKUO/oLv4TQwd8e6Wmg7YaWQxOOT1h9jdzf2c+jk+fNUOGcZignDejww2sjlZMPR7PvrJB4TDjrP1wNZadrst1sJ+P9L1C3a3L/FW06h2+8hqveDJB8+wnaPvO3wuvPHm6/zD/+Z/z5QTUid++Bd/zqcffshis8L5BVIzjx6d8+z5Jc+fXuJ8YLfbcXNzh+9GTs8fYb3n7tMXLNwpRQreWFaLgXFMHJL6MuTcWAjG4Y0hkVoUMEgISFaJn/UVyTp36xpbjjIQaxxGCoilmjYjS0XjrAs4izUd3rV5AYt1mWqyFsESCHgOtW1ErUfqBMYQizSzV4PxBlMrxlZcKeA9IQSsV7l/lYqrgjMerCFmBbWtsRRbCbXg0M4t0NJELU4U9MZ1TKmwdFYBe9Qbb5ZTSVVmcLZCHxxCoY6J/faWy6sbDttITJmar3h0tmQX4cnlp1ysTok/e8rNzZYvf/lt3nrzTf7WN3+NJx+/5GdPX7CfsnZea8IVwZomQRaHbSmBqRRkjOq9ITQzeO04WylUU5Ep4akE56k56ZwoRgFED0UsuSRyTCrTE2WHpJQ5xAxdJiStQ/ZJeH75jPWq4+5uy9e++mv84HvfJ9klrz1+jf/hv//vee/L7/FHf/fvcvXiOU+efMJvfOOrvPv2u/wD97/4m7kxf6WjHlv7cwKY+lmWVjIavfba8QI0xSyXxkqqcgQxZtMLfTrdiDpvMUUrIGcdxhqsGGzzhZobNAYaG0hBAXOspYT7xLPW3Gt/7lk5M+vIAIUYp/Z9f2wUC3J8Put0I2VR2Z9Y3TBpnV8aM6c1f+3cjFLgKpfYvnZ4HzjW//aeeWXtzKRSmw5jaZ5UKoWZQbHZtBxQKWljsPdd31hDCpogQvCdNujc7OOq8jfXpIXeBVKeWkIs7T2quX2V3M6RUMqEpvze72EMNBaW+iE5q2bK0jbt3nms8Rozb1WObBByVvNx9etC2Udyn2Bo3fw3DQDS86/XsTQJbdBQl1rbv51aBxw/g1UgoalRRO7nn1pF598GnJm2v8G0AIbGPq9VK+RKxtigcr2icu2+63FWGVVN7Qi1GVdYufcX/Zweirepib5tlg4iFtN1uAY8iUwYBy4YBdsquOop1QIJ4zqkWmxVtXVyjXGEQ2qgZqMG1jW3GtURbK/yu9Cue8nUXCnk5pk1sl6d0PuTBnYmfEDZVdbjbMAb9TbLVIzTMAk1NweTLcZ5sCqR9gg29HiULanAMaRRuLnZ8fx6z+0+q8WKFU3Ny4KvlVI6DSOwHqsLNcYqmNo7TY2cxFJLxvpK32ny6yEXfAiYbHEScF1PMBnXGUy3woQ1ccyEwTIsPJthwWCDJtIOHTZ0CI7T9YrBWowPhL5Tlp01xJRYdCvAEEticB2D78gtVbJKxZnAOKnPqKC+iEWEnCZyyQTv6HrHPiUkgmSh845gLX0XyFWYRt17jHkkU8ni6SSAGMqUsN43vpJlykJwXtOKG3sY2x3neWcsp+sltvnRWt9DEVa9pw+WcdyRptSIEh273YHbm1viNFFLYbFYYaqC37sp8ujRY/a7HfFuj6GSc0SM5ebmDkkVvCaelmnE1Mxmc8r28gXX13fkJrsd00SqQug6rAgeS0ywLYLp+l/qPvrlgSdrj8j7nMzwqkDNMDOUXjleAaQUSGq/15hRFhCj4rVZ/azGzdod0d+TX9gQKHvqs6AD3E/s96yle8Dp1Yfe759ns2r5OQRBzd92CUaBXJ0WrkYBi/byDTS758zMeNP8ltU7RtQ7yEA0MElmXSsyJlh4xoMjbJf0qxvEjEgpOFepwwlPp8K+Nt23KC2+Nm8nMW2Bb50pgM47Uq4KFrRFcgb2sOBDoLZIelMShoKIxi2+3Y9861T4WQh8uK9sE3y6s7y5sPhaicky2Z6+jszAjFQaOGFJ1XKXDC8PzfjNdsToMFIZTNXY9mqYEHJV9skohm0GqiFjmGplyiilMkCqliSVLAbjrG6Gq/rxHM95+/wGLbBK65jlCqkIWaBIizIVIctnAcnZKFzHmlJ9dYzPIFX7T5RxIPAZb7HPeQjHLx4NdFoE1wpcXXgs0ii1zVwer134VhQw30ttkNd2U+c20pHaOidCrpVaMnma2B9G9vuJ3WFiNyWmVIhJ2QU2wBAs6y5wsuhZLwb6XlPSqjGkXJlK5VAKY6nkWslV/cF0I6pvSf0W9PVlNl5s3UxjBTLNo8phnYW5sAaMqXi0QKeq6bKUpJ3Toh3Y27tbrm52nF1ccHp5yXZ3yzSNGmts7XE0jYeJJ58WDmPmcSqcZSHGyPPDjmch8/4HH7EfD0zjxBgnTIXl4OhWHY/OF1RjuT1YTgbHxXrBeljj7KCmyDagEgju5ZGm1YdFu0nOdnRhwzBs+NI7Hf/J73yZ7//4J9xub3DmAh8S42FPZzogQ810YSC4NV3/ANNv2B0KJWtnbp8i/jBxtb1ByoSpI1O2XO6FdY0camGDp+80rcU5yzoEOl8R2RPTiHc9Elbsxjt653FdT7dYQz6Q23WLpVKHoDJmF5lKROgo3uP8HaerT6nZQVni/UDXr+m0hsIulpRSWJ4kuq5nf31FvLvmwZmwXn+JPHV0ncOajnh74PD0KXn/HBk/ZfnOF6ir18lyebyfP8/HYjjoOizaUV3YGwafcDVwePGSQCQwEg+CMZ7FcqPdt67j9u4Obwx9UAN3JNIvHDYErq4mloMwDIVQM9N0YFgu+fY/+cf8D//4nxHEsTnfsD5/yPJkye2LE374g59gjWW/3+KdcPHgFGcDffAcSuLk/BEpJe3S18p+d2DMzehXDGKcSgNQ0FhMi1ZqqUzqRe2RrGa7Os2qjAexCjY1EZcxFuOs6tuqOW5Mg3U4a8gUeuMwVhmMxpoj8zUn3ZDVqib6hYAtNJ2T+g8a0dShmjXaGN8MQGnpPlg1AW+MlWq1HrJGa5qcM/vxwLrb4K1yFo2ZpcJArXgjmjCZBZsLzik7RdNAHVl0Xh7jxJQL427i+sUdu8OkBbLvOMTCp1e3lFw5xIkx3bGcOmKq7Kf3+fT5Ne+8/RrvvfsmFw9O+OiTS16+vCbvD9Qkev6dggCWDEGUGVPrsblQWqKanxkzog4aVlCgqWSyQBc0m02xfGWHxJTJSdfjIppY69s1V28bw2634+LiBAOcnZ6ScuYbv/W3mHKhxsQYYbc/8OY7Cy6fJb7261/j9PSUq+cvGfP0135P/qqH1k1y//Wx7mxwTZNRaG1sVcpphXIEGXT+V/l6bt02285fY62Yeza8iPIFnVfz4hlUSs0YXI3F7c/Vx0LXBVJKjT1lj6DIvI7q154QvAY6CC1NbU6k00TImpQVRNWfKxikIGautYEe93X7zLwCGjhiGziSP1PXO+ebAXYLWahyXO9FdN1VaaJvjbLaPKJaCqA1yvKDI4MLQzPFbimARs/FLDcUCfqeUE9DUJN1MzcxS2mNobZp9EpvtNZ8dm8iysYsRWtSlfzJcVzElI81BUbrWlWX5ONzlBLbudAGYpFMLY25gmkgoW3Am0WkARTxVUaCtP1K1bRCmqSu1VSlKOPCGEtJRe99UwnBEmM6Sn9rTUc2F4CxTTpoRBl5WSjFHpsHi2GBMYWhD6TG7tG3Y5tH1+f3UGyv4AwKIOlMSfWtqQsYOvXgBIx1eCcgCVdBUP8lIwFyxQmI7/TciCo7XGs2qE+pHAFC6wPFJK1zRdlFubGVKro3mmrRMevBhYCYgPE9xXqq8QSrTYUsOn5DVflqEZXSWtRH01hdn6xOUhSEfaxcXe14/nLP3Zi0AWZ0zbXWkF1szUyVfjk8VhowZyrGTtSywxiVx83KEqlCAGLWFDbfd3R09D7gvBIU+pNThn7DbjdS88TJauDs5IzS2MD90NGFHieOZTAEZ8GrbNZ6iziLkLFVx3ZwHZ0PeNtBqOQa8d4zBM82HcgpEkthtViqyqIWqhVyLFQsCct02COlwGJgNwqFXtMoi/pYTrnghw4jjmwcJSaM8yp1dx5DZTKaKhvCwGLR45sv02E/kW8iwXuWCw2+OYx70jhCNVzu9hjJlDhRC4SwRLyQSIzjlpoioVtQxqzWOHEk5j1VRox1pJh48uEH5BTxXWC3PbDfjbgWWgRQU2K1WnBzfc3uoP5f0tYd9RvVBkqwhuoK4j9jyvLvPH4Fqd1MDZ6/MTNHXmUfwWeoR+0orcj7uQcyW2RbY+iNQcSSpG3tj6DVL36U2erus4f5hUd+9jG6spj5S3TBOX4QjuC9UuHE8XwsZKOmcMbqAili75/NfMYCvT3JPWima4yaYYtVDwhjYeGFRfAckmP/qeNkb1lvlvRrQ3i4hwFuxspdqTiTCdWSMNg6g04zn6exflCPDCMZa4QRtFDJtZ2XTJosVwlyyTOnBzBU0xGIbFwmRsvlQcGYkiwHC4OBRRVCUPp0LU3sMYNOjW1Sa6a3joUFU/U8ZzH01TBgGlVQmV+5GrII+1o5FLAmk0rgUA0OoaNiqmCq0FmF22oVcmmA1z3m8Mp1lrZIckxoq1jEaBqaM68Yax6HgNyzntrvtR5R0223MdWArhlA1Wvbrvov4qKf28OgRVJnLUNwx65lqZokaUWLMWPcEXzyM3XW0GirOnGLAWusyl2qoVqHWE91gi1WGYI5k2MhxUKMVTd9oneMd4bFEDhZ9pwNC1aLnq7vEOuZCqRa2cfMlBNj647PXd/SDObnoirXTMoqgsylNmYgx2utD7NNiucR0cQoGv3ct0SLWguTUfZeLoVcs4KRJvOzJ5/yW9/8dS4uHnB7d8M4TsTxoPHHzQvLGIg58+zlLdfbkfXTaxaLnwGGRWe5vrlVen1tOm8Py8GyGizvvbnh7dcv+PFT4Y1HJ5xt1kCgiJ5XATUGNhakFQWNpRVM12QBHd71+ODx3Zrf/8Y7/NN/9Tr/9E+v2W1HPvp0S9zvGbxwiBEjidfOz3jzjXd53HUsO8/13Z5ctuwPkatxRGrhw48/ZLXoePjoAVEM0zSx7g7YWth2ngfrEzabtRo3L9cccmIaI0PnOT1ZkCfPOEUOe0vejvgKm9Dj+o6uX9CvTjDecnt9Rdw9Q0rBLxakAje3keBusPuOxBVh1VOmiDFblg/egP4R5folZ+uO9957zPaZgc2KiwdnbB7/OmY4x/UDcRfJSb2K/GbNyAVpTEySuHlxyfB4+Td1W/7Sx4P1R+RUNARAKs5nEhXJlaW9ICxPiAhpzBwOO/UKMIah9yz7QL9YQ8mMhz2roWdYrvnqe6eM44GSEmM+MB1G/m//1/8Lf/v3f5//9v/5/yanjLGW62nP+nbHa68/Yrw7MLYo3Rcff0hwlmANi82GHBPPP37CyeqEKAkXAmncwtzwaJIUjEqExKDy6RpbI6UFeJjGmkF93I7saAAyiEVaYdwIyMqadboyWKvSPqxQi7AriW5wBOfxRrv61RQmqRRn6EwrqozFtY1srRnbIuIxhmCsUuSb7Mw6hxdNKsOjaTW2+ZSIAgTWGAVYc9b7t9r7QBPjoGg4gAPIymgmQyoF49Tzwzr1TqFk0pTJMTPGRMayWi6xfmKMiSKGmJOC764jWeFuLMR0w+k0MMbMdrfj8uqGt996jd/6+tt88vSE55+84KNnz9ndalFtqvZjpd5L0psrhTYCU9aWjfOUoqyMJJq+NjNOjYlICNhqyDURp0TMR7cnbVaVSp8KVipT2eGNQ0pmv7tDxHN6cs5ffPe7fPkL75DHid1+5Au/9kV+9pP3uby65mvf+Dp5PLDf7vjBDz/im7/9tb/uW/JXP0T9dbSmmP1ymixt3vjnuVCu2AakBK9gSa2W4FUiZ1pjU6XuGhzhnbsHke67o+SsDNvgXQMwNKRmbp4c/Vab7KtWZftgrHpBGdeYNVo9KdsoHTfF0BhMjWGkQNBcNbV7BpW9mGMzTxqgNbOj1L/tuCkVHXnaHNV1fn4dDSCagaPGsLYGb/0R3DLGKpu5vV6panwrCN6px01uiVIhqPdTltzmJgXsYQaN2jzQZEzeCfWY3ivqu9gCWdRAXbDGUaqyfdSXrra9tiW1ROeZb16b91WtRZPJ2lFKk7jaZh3QmqFV1FNLE0J1zqutQT1ff/27NeCMbe//lZ2a5cgGmRvJORcEZX8UqcpEqw0Ap9U4dfbfamBYey/W6vUjN7aVKENKE5AdKWrKoKXiXKHmGUSZ+5mOOVf6c3tYsLSEQDFYNygrxmvogq0qwUoN8HS1zZ1OlPmEyi9jgSwZ7wPOeGXsScH6jDUJIeOrIYh6dtHua1OU6adNOyipIDXROYOtVQFR6zQl3lV6b5RRZw2+Ab/GeqQaBWNswVvABHw1uGqpJpOtxbgWDJRheyg8vdzz8nJLjEmZzM4jseLpKGbCu9gyn0yz69AE2s4Pyhp2HUYyuVpCS63sg46hoQ+sThwuLOiHNYthwIlhMazIxuN7z3pYaN09RRZ9z+rklH2M6lVkYDUs6awjGJUau95TKcQGbgfbUjWniLdOE3ZroVIwtpLTRKyJkiMpFw5JayyL4J2l8x6DYYwFQYilMHQdoe/xnSoDnFfwvWJwZsAZh8fSdQsinpojXiqu+TARM2bwWKt7Ii+QbnYcdiPb2z2FHaUWet9zc3fLeJgwVmWB3hrKVFgMPU6E7fU1SSKHaUeKCSNbEB0jL2+uOcQ9jy7OeOvha8RD5JMPP1E5pg2vgL4ZMRXnA89ebPFXe1JV8seUivoNGvUoK1k9yxKFzlQCWeP4fonjlwaeNL2qGQh+5idzElibgI+MIPMKtagykznbEsVMDTKo34xWYi19oz12ZmT8FShT+775q39oXmWjyP0rmgaKiKjvmREUTpmho/uvkoEouhgYOy+A95/XIlipWDPHiMK9v9XMQqpgUqMvOham8nAovP74wMXKMN1Zbm4qdpVZnXXwekROl+yeD3z4dIkTy9ceGJ5tO55Mka5RXJv1apusKx6LN4XODayGzH6vC2xvhEdDJdXEdRrYZUs0Vbu7rZSsFAYDp51jG4WX20Iuhg7HRZe4WGY2Q6H3greFkjyHYlust6L8qS2EvTU8XMA+BfI+No8Ci7PQ2cpW1MdGqKSiC5hUYRIhVvUScEbPq1SloPcNtJSq6Q3zFf0s+DQXLnpW5tRCbzRGVDcBjZHXwELkHsC8B7AEI66BFboa2nbNj6NIzOwIcD82DXzOGzXA/Z1qDWouXg1VdCmciwdngnYZVXSHRw30EIU6pQrVSdvcNLNPVKceqJhaGavD+YCzBWcTzjo6H5qvhLAGrLcslwPLYdDJO3iqsdqtnwqHVEglqWF1mkgpqVdF1qJYPdkUcS8i1ELzDCukOqcu1hkhPhbIsy8YWRQ4a8yDYJpIoCWOkJRtOXcbL19ecXenuufr6xu2t3ekcdINgOhJtY1JIQLTOBFjxN/egrH0nWO56Nn0DtMH9lNFquGNh2e898aGL735iIenGx49DkwRxDh612nSZ1FpikqT1PtlBp3mdB+Nr1ZgueSEdfD4bMkffuNNvveTn/Hs2Uu+/Z3CYb+l5JEQHJuzgdceP+SLv7bhzcMtJ8uJkiIvnz7h+tkz+tPHDKcXXB8KMgx0KVBzZJwiRhzBeg438J2//JST04mL8zVXu4nL28S4u+HBUPmtX99Qw4pnV5U9E9kYViYTzhy9dTg3INZSpwPORN0gGYN1nmHdk8oFN/sF4fkTVu/2xJiQ8RrXRZ25uyUp35KrMCw2hEfCar1mOH2MdStNP+wH4vWOsBjwb72NhI707JJxfM7V86dcv/iYRw9e/xu6K3/54/R8pxL1CiToVgYzKAArz2HcT+A8NlgGMdztd1Tr2F9dcnp2SiqZuNuzWHiltBdh6ANhWJOniI+OPGV+8qMf8+xnn3J1tdXNXOiIeWS3HzkcJlbLNd2qO3pTKDU8sR8nNus16/UKIwrCxFi4u9uT2iSifnGC2EIU0zq+RmUiiSOIJGKPm3KNy7HajGD2YdR53FjbknSVXSNGO4mlGkQ01suJblrlUJDgMSGo6SoK5Gq0skrxVKpnjmurZHRjVirJ9GRbdMNhnV4LMVirviqmCsYDqFzHtORW7zv64JGSicapHAr1i5JcEGtRF3UAR7WBatGOsTEKUlQhppGUlFFsnbBYLfA+MJSJ7d0thyljnCenBMUgpmCwFDHc7TK7eM3dfiKOwuWLa9567TlffPdtylngwaOv8Kd//kNevNxSrcXgcUU9FqlWM4SNaQmQs2TJYp3XdKLZm2deX1HGhAu9np+YdZPZ1upacpu/UJa3BEQKcTzwzjtv4rBcXFzgOsc4Rd5+/XW+851/yfLiFKmG25stXei5u7rhu3/x51w8fos0Hv76bsb/kce9ZYR+bc0ctKKM9mNDC2U3HcPrRB+X4gy+cJRJHZulKc0PppaqIAAc659GU6YUlZY0bwtoMuNZNm+MpqXBLH3TNV4ETThNM3CkG3CVwfljDTaDEPf/pkk4tPacU/QUeLqvwpRl1NhXrR6ZmYGlVE3Xa79Ta2mmsgCG0EzD1fBeE3iRmQl1/55yTo0xVHSjb/3RcsAYg/MKWoECWsri0rpH5WT3pvo0oFAb1kZVTc61z+IbAJUVBGvvxXvfnl+awfc98DaPjVlKqe+rNdGKHCfHOW2w6zqOaXC17V/aOVFWmRzHyKubtlkJ4lrNknOiFGl/l/vGalUfKmk1VNOiHNlhmu52v9dx93hhA+s1/MJZR/AGKNAYOiVHZZ9UMLj2/LNB+uf3EGfJMVOmEWcM3nhM6JRJBK1nIs2HqYKtGJzO8agvlrOBgP7TmaBrpWRSjQrKGRAneAxBLN4HMhbJFdsSndKUdEykkc4VOhPwRqhSCK5TEMNZDdqwgnPNoN823yTjMAjOZnLJmmZYLa4YSjW4GpiqME2Z6+2Ol9stL293xKTvy2GxVd+Xdx3S2Hja3HYYm7F6K+AXvdaL3Zqu07XF2iXOdiwXAethc7Kk7zsO+5FhsabvB6b9xLIbNBG1vcd+0cNiiQsd1geVyJWKN+CtmvAHO9B1nsWqI6aReHlLKrGFaEHf9eQ4EpNQxZJFfURLsZSsKcEYi3eOUjRIYNkPrLoBqZUxRMaS6UQB6+WiZ9F7Pb9mYL/fU3LBViBWgnV0xoCH/ZS52+6Ih5ExFfrFgt3NDYsh0HUd3nlePrtlNyUFBk3h9vaGRT8w7nfs7rYMXY8tmbuYiCWxjwFXKvvbW0qt3O0T+5ioJSIlcxgj0RhizayX53z84QsOd3fEJBTnmUrBmqpzRVY2MxUyjoQnlUnbII3tOSeHSgZjK9iCM0JvhMP0y63Bv3yqXQOVZpndz7NNfl5mJ8hnFtn2zc/8FrQF0TSWPa8wFNrDDZ+ZM1/5/gxq/Vt2/PLzv6VHheNEeQQt5vdkOH4Og9KF1VNJ/zhhDthri3Zp78QcQac5o8Eiio7Q46pj5YUvrgu/+2bltbcmal+Jd5YHJ47FmSG8c4f74kR1nqfvB569dDzuAt84EcL+ltviOBirvlfSFj1lxvPYBsQJN0aIU6aTwONQ+c1HI19/S7jcWf5/Pys8OXgSDtsgF4NhYROPfeTtC93kuueGDjgPwhc3hi8/gpM+01mhZsM4WSRpUW0a8tIZRWqjBPLB8mKCWCBIVoBLFHW3yRCqFjoZQ2eEpREmI41+r/1QEf1sg/XHTouAblAbyHVUxog7Fgo002s1pp/bPvfDwbgmCD0+4by1keN4Na0Am6n/82LyGSo69+Pk3zr+PpeHHDvxzuj5nP0k3Mw0oHVIjFO1ibVtHBsKLYK8qieFEfBBEAdSLLn5mjhr8Xhc8VA8ne04GZRRUASs97phWi3wXcA4Ry5CiprUsxszY1KddZVEzpHcEh5qtUcgyZq5KNT5wzdfiipQ2j3JvDk0dka9AS346/FKQrAgUhrTy+JsbLISS8xCilueP3vKF999h35YsF5vmA47TeVpo8g5q/4K1ajnjDH4oIWmt4bN4Hn70ZoHa0MlM8bCw5MTvv7eW5ysTskp8trpmqvbRKqWzaJnETw1Jaa6U1q9CzjfqV8eRVMyQtfMPg2YSso7ajJYB7/9tcf87g8e8Z3vfsLh7orbm2tWJ4GvfOMP+NJ7XwPrcOsNu+K4u95Txjvi4YYpX7G7cXT9AmN79qNw+4PvIfEFj95+i+HRu3S+Y7zJPN/ecSV7Ptwl7sbC5UfPKJefEOSaw+GO87e/xrPrK07OTzlddtzejDx5saNfLOn6JbvrPUPe8+DBCuyGPCbiIZKnW8z2Y5YnCxZvvgurN9l++BH750/Y2i3TNGJOC7unL4hPf4Bze8IQsJ1Brj/BLC7AnHNIleI9UjPlMBF3I7u7D/HsKONLctnNQ+VzfZy+Zll5Ry1J5ZcmkCnE0fD0ZsduvGY3OjabcyDjgyMVwYXAfj+psWWtxOyZ+sKyS/guzCZpOIcy57Bsb7cqWRkL05RwgxazbndgHBNh37E+X2OxGOu5vX4JBm5fXlHLxPnZA+K0p0phFNHiFgtFAwis8cxSfWUvZGVY2KCMixJ1pSqKRilkUXFtnZ4vWG0264gh54gmeOk6UCpESc38WDd+KUXtTFpNq4tZqfrFqc+ElUKuzVzc6iYsBEvKubE11fQfA1m0wz1v5r21yqTM4Jyh2EoVw6n3eJ1MkQJZCt5ZpiIElM1YpGJMVeZlm5Ot05mlFiHFpGBNM4CuxmB6j7GG1XJJNwSubu4ou0jNlZwqxlv6oeMkDFjgkPe8uN6RY+HBWU8Xer72G2eYFy856wp/97e/yr/63od8+OlzcCohdBSSqOk7Vj0vcOrxqGuoMhesd1gnSNa6R9nHFeMr3lhSSnq9C0gt+DC0tT0TU+TUrfn4058xJstr7wgf//QvG/Ol8J1vf4f/2R//Pd54/XX+0f/rv+W//Af/JX3X80/+u/+OL3/tNzh5+AbD6oTvff8Hf/035a94KEOFz9g2aP07V6GtQVKOlteApRRp667eB9aqXM62wBprdYOviY1NGqnaOm2OttdTL6nGTGrrp6Y3Nlleq7lKUTmXsmUMtUlRnHVHvxHvNeVOwZPS3oc5eimpxEw/onOm+RrN3lHo+GjvISUFlqx1TC2hDoSueYZUye01TPN6AsQ2sO0eWJobMApszQwjGkCjvlb3qXYKaldRVtEM1Nw/3iiwh+E+/W8+V62IbF5KzqlJeRWoxbSkO3PcQ4D6Ts0gIXCUDyrApbVIlYIVGihVXvn9e0AM9DmmadSAGDezQjVpbjaUN8aQUmpjRDBijq9pZ48r40hZyFHU16YxkJBZfmmOr3dstvLK/otXWHJFm/TIDKTZpvqwrUEhem31giorpzV45+v9b9u3fV4Oy4IsI1hDNywpoubMwYiuXdYjNlFzxHmL9R4jlpqV8YTV+9gawxA04S1n9b9Vw3gIRiWi3llM9cSqXjxljJQpkvNB95kFrMvYYHAh4LoOHxZ0fqDzyljqgoegMm1nLN7oHGRmqxarHlT4qkFfpmCLjpuruwMvr+7Yj3vGPKrHru8UsBWLLQtc0IaStwYjGckoqNWB6QJ22GBtIFh4cP6A1WqDdw6Pyu2sd9hg6PuALYXeD0DAmwEbAiFoXR3CoM0Xl3BBf7cWoXedsu9sQSSSsmWxGbC26DxV1HNR73nBGk1axgq7ww5rBt3dW+h6BX/EQJ8ifb/Edx4rQt+k+8YFlrYHC+VQmPY7sBmTo7K7hgWjVPa7kdu7kZwSjx5fYGrPtB/J1WGGDbtt5Ha747zrOUwHUh4Zup593CkQJok0TvhgqFF4fvmcMY7sbnekCTAeHwboAuJVMdYbZSzebvccUmxS58r2UOhO1yy9xdnA88trxnFUlrYVqnFYYxhrxQXbAlMS1kWqKaTGWsySCNZzdnbOy+stIpUpZbwXerGYIvhf0nvml5fa8Wq3kXuJXUP75V6ndtyMz5N9w5aOFPS2GwRMWwyVYVJqaVImmXGge1Do59/P/D7+HROVfWV6BI6Ahb4XwTckv3zm6XVy9Qb64JiSJvAJVn1jhCNrZqEtDqbYFiEzQ1m2IcAGjCPYwsNF5mtvJd56uMOYicNOWAXwZ4YDOxiF+NMVt/sFP/5uz3QDr72248EX9vz225XxT9Z872YBZMWbq8fbxNo73l0HJnNgv08ckmPtK1+5GPm9r0Qebg6sb05469rwfLcnEvC1UI3HW8dpB6+ve2IqPLvLHEqH2MxJbznzmROTscmQxVPEcCiOfRKoHd4pxX6fFYNLYnm2z9xEw1QEEUe1mlJ4l2HKYIwnYdinTLWqJ3ezwaaglGJjKa17M7PMZvbaLPmcL7umgpjjGDNC6+zdd9z0Z8pMe3W8SFvxpCXWgb7XWmdPrVeG3jxuX0mzmwuU+leho5/Dw7zylZnBS5pUpYC2Y+aUIxR4U1oB4NQbaWYDiDKNMGCdUfG7KQy6JaGrlk56elvIyUL25BRVyhFUVhe6DvGOVEEoRAop5WbsJxS0gymvINEKDraky5ZAoGNDiy9rVI5aLRjnkKxFnTH1lfnI3ncCmxQzOEtJCUOG4HC+I6VMrZroUWrh8vIZrz9+zGZ9ymX3jGExEK2h5KRFu7MEZxTg7DS2ukjFW0vnHKtFz+uPTnnntQVnmwXeWzarE1xdIFVNIHNWnw5vNd3PijCOW41UdkNr8up7n1o0s+kC1mlxYajklMi5UErm4cWG/+KPvsprb73L+Rtf4qMff8Di8Tmbh1+gjyNl2jJNew5xJE8HvLOsF6c8evwGt3nJy7utRtKHnlgiHF7i5Q287whDR7yZOGyfs+wCxXquXl7y/MnPCPGWk/OOD17ccFU/YBjW7G/uKFPFI+Rpx8snHzAZz+HOE/YvORwqtvOE5SnTrsDVx3D4Kf78t1lcvMdk1yxOzrEYDs9/RE2WcvsC5wr9eo3zHtN3cP4mUgwY9WDw3jPGTJkiYyzc7i+x3rBaXFD9wPLk2RHE/Dwfjx8NPD5ZsN0fwGYeXbzB9bMFf/btn+L7E+TuktUwcH31AivQr9acnS25vbnm5csbdaOIDnwixcjeOBarBeuuZ6YkG7FYH7g47+k7z4u7PVe3ew5TZhkMh5IYukxxsG5SzOAt680aiYWU9vT9khQTL55fqv/IpIWz970aT9dClkjwHaa4JsFVf7mUcpOdWAW3bUAzYCo4uZeP2NpMvnplyKYKNiBiMV4leKFrwRC1kLLQd10jI6k566EWrHOUWCjAwVaVHaB+TSUp00hMMwGvo2J0TtnSXQi4AlMpJFED/ppGHL2azwZLFwal9Iuh5KwUf6mIV2+MEhMlVIzT+kKqaPcxVAXnTG2gu5CNxQ09ZdxSqqMLS5wHHzzdYkHol/Qvr7i+u0HsArIw+J7FasFmsyTVc26ub9ht79g+vWaMkfW/drz31lsscWQT+Tu/82V+/OEJf/bDn0JJFKeSamMcpoU2ON8jpuIdiGhMdq4FSpMKFu2EGtu8AEtiHCf1x/Bal5VaSJJY+g5bC0ii9wvefOcLBCd845vfZFisCAa+8bVv8NOf/Jg//KM/5sEPfsphElbrJR89+ZTbQ+ThW2/yyZMfqxfG5/x41WCaV2oaA0erAC1LFTy1VVk6aYqND2Iaw1eBSu8dNLn8NCUQ9U+amStIxZkWxNHouNZZStV7S6Vmcy0jSJ2wzrb32WQjDVgwUjGdsnrDDDoBIg3MsBXEKatCBJGihvuGo4m4MbzCGJqZTzTfKJW3Ag0EU2ApZ2VPKGilAE7OytRQ9lNtwJVvZuSNXeT8cb6wsyRQWrcWOT7PPeim59paf2Q65ZzUg6mqhFUEQte1zr9uaHVN1ppRk36VPTCbrs/SQP3a0fdquG0tTU3hyDlhjEr4jFU2lAJdQhc6BMhp3mNpqIiSIUUN/qso8FuLNnBFJV+mvTe99PXorwUauhInHVsi99YL92P1MyMXaExr2r5Lt3D3r9EALvWfnecybWiqF5BKlrxz6kvZGOtaW85sMcfn+XAm0C063RtodCQ1TZRcMbbQh4AJQdNRjcExaLOAhO8sVSZmovBsEGuMbt51HxQwqLQ2SSam3Jg4mWlq9XAzpBeg61UyZkKHHXqc8/hgCV1AfMV6h3cd3g70vsM2hmEhkU1GxOGdphmmVBljZjyMvLi+5fo2sdsKNXs6v8R5x36f8c7TL1esFmdMU8T3Hfs0MtYdg3d0LhBCR78+ZbE+m7FFlkPP6dmpygNzxorROc07ut5DinT9gNApGKeSFYz3rBYrpMKyZO7urjAOxBkKmSKFErWmEWuQDGGw6ilYDOOUyKI1uimVvuuYpkixsFo5OoIyeSs40SaSLRnSSBoraYrsq7AcFooNDJZSMzcv7ri725H1ImJs5WRzwm6X2G0TKXu63vHy8ga3vcN1gVIMb731LuebNd/7y++yWsBht+P2dmLcjcScKDVx2O1Ih4gthtPVhsvDjl3JTLHg7IBzjgGoh8yw7lmsl9xeX3F9dUOpwrDqsAZ2cc9iMyCuslwu2O1vmPId0VRtfFSPqbpPEadzWRKdf7wkHJlcKvsxq/dttXSTR8qIM4GSDuSijaSF70jj/pe6j35p4Gl2C5qPea89R27aI+gy8ybuDyOzkllmflAzEFdDtHkilCoUc3Qv+oU/8srf8Iug0y8wrF45ZpKLKs2hk0rvLFGbvQBHvyZMA0WRo4eLdiU5qvs8wqnvmKxnjCOv9gAQixHbkNTKIkTeOM289eiO7myHuIHVXp3+WU4s14Z98fzJP7J8/KLnw1vD2WrP174Fj765xa8XPHmxY4w9V9HwIioVcB22vLewPAqJGxGGWsgW3lxF3j23yOh5ng3Prh13O6VQ4iA06tZghIWB21H44d6wzb1681gIPtN3lZfbzG5vKFiSMXwyVa4PmbUR1gtIJXMXLbUqZfl5KtzlonQ846kODgLTpG2+QuWQK7uUMUHtz6WYRpe0+KrjYjKCtE7c3K2xrUgT7ruFR4C1FXHHSR2OBRNoIXyk0pl74EpEx4Q0GrN6Axjt7DZOscgMhM5Foz5WaD5Hn+kFfX6P+R64v23m7yjPsIq0rn5LHdEolvZ5lZpdS+P/HZE+0wA8wRE0vt0GgrE4UwlOi7mSJ6R0VONwoceFgPVWzfdzIRfBUfBG9doFIZX7czoHqisrCWoz7p5SwphKrobeoSCSt8Sq8czGa8eilkI5Utm10zqnwaicwOK8pr64kvE10ze98j5Vpqmw391ydXPJ6dkF6805BuH66jn7rXYVrXN0g2Pw6hsl1ZCaQeciBNZ9oLeWlDxj6lmHJYYTslTuDjumacI3I+zBe0C43d5STWa98vjFORal+1apmFLoO0+nnF6sVf+akmuj+Gc8A7/3rW/xla/1/PTOcLpa8nx7QMbL5kPhGa9uWS56LtYrOhLrjeXsjXP2cc10e2AswqZbcvLoTWI/MiwWSBYWq1Pqa2e45z9F4iX9EJDtNVYOnD8ceOe9L2EWr3H1yU+I3YecPHxD03EMWNczlUD+2fvsdwp6bdaek9MVi7OO6e6G8eUnfPEbv03/9u9y2EdMPrA8f0y/OCFsVuz3VwQifuMZzl4jnD5gLFBzpDpPqgUniSwLisBUM9tpx3TzgpOVxQ+v0ZXKyeniaDb/eT48I4P3uJOOy/0Nd7uPePZkzfVLjeFdbk5Zb7RAG2Nl3N6xv7vhbrtnihnvHcHDerFUqUboyLVwdzgwNBAlYqjJYPzAyekZZ+cP+fTyBc9fXKm3UE0Y5zi1BophWC25ur1q/kWVYb3idjtyuvScnj1gt99xeqImn7c7vV9zLeSdULxhORhooI1uYrQLb5xS/0tW2di8EVdvnIqYoBu+khRktB4Y0VV8QAQOsdKvB7pYSCZRxwreapJUi4DPKWM7hy0FX6D0PUjFGt2g2oZ6e+eouTI1TyNpKQdJClIN3lpMZ6F0pAxUh0kqsXWI+kSWotIyD3af8M5B0Dk4xcrSeawriG0G3PFAygrCI+C7AQMUMzT2SQMMcsU5z7Ac6LpHrE4WvHj+gu0hQWkM1VJZrRdsTtdM+4kXT59xebvnn/yz7/Hhm8/45tfe482LE8J4y9e/8JDNZsWfffd9Lscdlh5E03tygUPOOKsypFg4dtNjiVCVLWyNSh9SqQz9gDQ/LylCNoaAaEpErepfknUV/fTJ+7z7+u/yp//yX1Iw/O7v/R4pj/zJd77Db/6tP+SP//gP+LM//VNifJff+zt/TDGWL3/5i/zln/05/+Zffftv4rb8lQ4ljNnjxn0WmqkVkVBn5AmjTg0oA7nvA74KKWnwibimfz8yRpyCBlW907CzN6M2We4nt4qYpOASmeDtsaFTDVSrkqq5zzYDC0Ya825MFCv6eoQWY67rqJZL0liQaipcmoG4IMrKco7wioeRMmMcOUtL7ARTcvOEUkAuBK/vqbGDDoc9CoKoV4wCPNpgKCXhvPqPAM27SZswNHmdIM3cuzZJ4Pw+WqJ2mYG7rDHo6P1VqHjXaS3RAlSMbfUP2tw0QNfptZnleDP7KOeCGu7recil0PeajqfvV+WVnQ8NVFPgJpeiVgVdf9zjiHQAjVlmEfWE0HW/gXHOGmpuvpBUfHCE4BlHbYq7JsUMnSenjGT1sDVGmq8cM6kLbf7e+zHZGTiEBmpq/WOgeeuZdt4MziujwllDiqPWZIb2m35+gcaeS/9e99f/1EdoaYouBHBW57WW4GmqbtwDgbGlhCqekRGn3XmtrgVbHdiOjHqROWk0idboGKcJTEfJEzkdKLkQU9S01E7Zx1Yqxjtc6MAOiA/4zmtTcLHAOWEYFlg8XRi0kVErWLVEN7WFa4gmN+7FcDsabu8qY+lwXY+w4/TkAWKU7ec3hUXfc/H6a2zOzrm+3tIvFtzsb4l5pA+OvuvxNrBarBRsrpXebZhiosSMoY0vDAFtDLmqAT8xZ3wXsL0hZ6tJqWRKPpBjZhkGgrXEXCjGYoMHb4mj4I3Dh8A+R+y2IIuie8gyUSRR0AS2/W7L7e2WbtmzCBY3rKAU4pSYbke9JiEguxEpMB5GXAVrdxymCRsC3ndMh4lULLkKmEDoHdN2wnuHWS+oh6LeXhZKGVn1HVcvr9i+tHS+oxxu2V5NPH/2KU8/vcR1S0LfN0Wtoyb1kCwciNaRjMX2grdeZfylsNmcME17Pv7kBSI9lYFSJnKplBKxrtJ1ULuOKpbr/aT7bSNUyXhr1CezMZhthdAtSDkzjVntnKpBZS00r+WCD448TYSm8JBUiDUzpV/u/v0VgKfGCXkF3PmFQn1mIUHbsH72MKAu+bMXCs0csVFJMTKrej6zjX/1ef69tvcNxLCoPGwTHDexkKqCYrZBawU0yn3KLdlM0eVitCPlQQ2JccRpemWBbh2lBlh0NnCG8NhmHneZoVTiVUXCnhyXTHlBJz1hOnD9iWO6fIO7G8NFt+c3vrzjzc1I3R+oPbz3uPAgW/70yYqbInRGeO+s8Du/4VjaW64+ckwT7Evg1x4LISc+fTpy+rDy4vbA831PT8eZsWz6zHUSvGQ64HovLJxls+ox44E6wipnlrZANdjgqMZxt4OfXBf2teON3uOrRWps3SHLvlYijtSSgXsHvakYKahlgJDEsC+GsRr6aluEsxwXJteADpkXPHN/3WfAaTZXnAeKdgjvwaDjGDn6E8w/ue80Clrz1vk5W/FxXFgb2DL/ex7T9kgfvn891e/PqNbn/bhH6qRWck3qjaBie0zVFCWqUWmjqK7XmBk6PpalerwiFwCLt4Fq1fTYVo0dNtXSVQu1p4rF+q4tPGo6alDWmvT33guIkGordowWUYpaNMmNqFnoIUd6ZzFo50YIeu+KJVKUlQVUYzGtm6odUI7UcjU11fdvoSU5WQwqCTJWE1x2U+L66gUXFw85P39IiiN96ClDolQhBN+MnD3BeigwxUoq2gmzvmc7FQ4vD3RbeHTikdOI95kXN3sud3uWQ+BsZXE2cZUzN9Me54XXi3bzxRRM6SnNdDK4QMwT45Tx3rAMHVKVvj1NhcNo2bLktgS2+2swhgvXsd1f8s57X+bF85dMyXNxtuHR2QlW9pw/OsN6D2XiZOjIKTHGOzaLjtX611g/fIy1cNjucdWxOHuAs5VFKDx8MDD4B7zx6CGnF4/Y7mD36Q+QYeLi4ozOW2wIdKEj9Evys6fUm49YnjzADSdMY4YXT9mszunf/W2unmdOuk9xLJBxS788IVeHtQNdrRibmA49Up5AP+K6c+LzJ4TlBn/6Jqku2d9smYrq3kUiUkZKMSQphP6MxfptivX8FSva5+ro+8CUI+LU/HE/el68zIwJpnTLer3m408/oesWnAwD25dbYhXWywXnJ56zzVqN58WS0qRrre+VDVYy3vfUoitgiYlEYdgY3nnjMSeLnk8+ueTZds/SOrwBKYU4Zna7O+5u9gz9wOvrNbfXH2LKGSlbpulAihOrxQJbK946ctVUnlozMVlC7ymoVDZ0HoqQIxx9I6xF6oSxavarHXJDrQnnB6pNKM1G2R81Z6pTtohsK1uihhKYjK0qUZRS6ZxpjahCErA+0EvCVqcm7cbRGQWm90VYuAa+V6FznmwTNWs66OwVYGylekMg0DnTPm/G+QC2UpNBPHhxlCrgdMNlrCdZx2LQaOWpZoJR2YKIwQUP3uMxRDPgvcp3bXCUDEIhGEu3XLMaFuQxYdgTJ934xzThDpZuPXB60nOyfpPt3Z6Xz1/wkycveHm345tffotfe/dNVmx5Y+N54+/+Jt/+ix/x0SfXRISxFLwPdOW+SOsMUA2xjsq+aAu3EYfzKvctOeMNWKMNKf0asAoSQ0dxHavFkrzf8cHHn7A6OVPjdTfwu7/3B4xTZXtzySCZn73/IZXAdH7gh9/7N3znH3f8nb/39/mdP/yDv4nb8lc6TJOEzR5HMNtNKNta6wyB0uQwooCNxylDpoERtmSs1ZhsAErR+9lpo8xUZTiZxlq2di7PZyOeeT2nyekVRpidP+daaO5Uab2kvj2lNCmobfemQN+rx1ItiUrWGmvucLVgAAVfIgqw2MYyUmZPLgmYrRUqc2orxlKlkHMmNEm5tfXoNzIDTillUkrMBuf6t5qEC0LoXGN2eVKaVJL/CvsH0Bqn1ZXOWZzvsdaQUiTGqQFbysC2Rzp8bQ0sTYPMSdfhEEKrKWdvKj1/3luV0DYpmjbAwPez/6QQU2zvtSHLCCmn4+o0q0ystZRSCCE0D8zczqmCm7OXV60RcIwHBd1KBiQTp8a08Zau70i2UIo5AmjzuT963Da/rGP6II1QYGleV3U+kYDgvNPPaw3e6aY1hF5Tv2pVya3TdERrLELSOfxzfHjrNdDDNnmrMYTQ67pSC9YGsvEaSlOr1pWmBdigKaAZwYpDEsowVt2BOu5aDVXKsd2jYojTDikTQwia8O0twYnW110HYYH4gRCWLNYnBN9YT159x4IxWNr4MCrhpFllWHHUCrYx2P1iCQePdxNuKfSrMwbft8TowmpY40OP6zxVhOVywHeO064nTer+JOLoQ896WKv3oQNrKyZowFAXHMVUiroVkg4TrmRSHUkJQi8U51RaR6SaSskRZ9Tgu1sukVJZuE7nzZKIAYaupyTh6uWWPN5RR0PJwmGa2l7CYCrEMWFtx34XcbKjLmEaIzFlKto8W3Ubrm5uMdZBv2CcRtarBcN6CabjbHPBpx9+ROcSwWhIQyqJQ5xUBZOgTImaJu464ePnH3N6foqphp/88MfkLGwPE/lJZh8jd1Nm2SvU7o1vSZeOsaryw3uhI2PwBLEEr95ULy4/0fTJFsDVuYGucwiFKWd6d880HNOeRCZKJDhDcIFgPdUbTHXUWMhOKDLhrc6jsRRMMUi0VCxTFV7ELaELuCC6jGCZcsUQCTb/u2+g+T76ZW+4KrNpJMfNpvm5n796zGvWvXOMaSi56ObRziwRe6/y+bknPaa/8O8JOL1yeCN4sSycI6ALO81EOcz+CqK0dl2M7bGjAbWxt5Q9dBsjU8kNsmrMGFGkW4xlcIWvrCvvnQtfeFgZlpCTwwS4vFvyZz82nG4S3/zihnjtQTpW3Zb3vlz46u8bhnPwj09hXXnrwnL6vcj3/h8dj8fA+SbxW//Jiq/+/W/iw0se/n+/y/CvoRt6loPw4TNh9djx+HXHs0OHexF5PXjeXHSsN/CX1xoXfxpgcA5nCqYcuLAZ0zvOO8sCQ0C7UFGEznbkqkV7bw02OUR6epPJRriqhTFBrR7jrUoKiiLNkQAiZAwJQ5nptXOxZdVPSaV0xyUWXqH+1oY1VWnSO9PS/JhLqM88/K8cN69KUF9NsRPTYr1pkahaKX32OVolNi/86vel1xz5DzVC/yc85PiB0URCndBjnihzseY5ptTYxj5TO9vavJRmY9H7c0FLncKUJltscaxB1EeqqFTPiGCswzqHUEEMViwkQLKapvSCqWpCmYou3MXoAmWM1bTGKtQaOcSJ/RTphg7nNdrZukb/b4OlNE8qY6Am02R3mnZTs8GILqDOWFxQw0VkLvj1eQYgFaFzlZxGaskshwFnPYvlQqm+NbNZLLg4DawGNenLqSU+pUI/dGCEF1vVby+7SpCOwTqcK7y4vuVq2rOLniqVlCa2Y+LZdiQMlptDz8XtHRenJ6wWA9YNnJyc4gNc7yde3o7UnOmCZ0qWlCCVSucXYJKaO4eOzcljduNPeO0ksFkEwqPHnK+WXJyv8VS87VlvTtUDg8JX3jrn09s9h6LMz7C+wLgVNV0rky1O9P0CZzwmFx5dnPL44oxhWOFth423nA6WzaZnGaAbAi4scP0GSsIuesJtpQtCt36dcrhhPDxVzy23wYWs5unek0uH9TqexquXmDziFxtyLJQXT0i7D1g9/BJ+WOuCGDx5G9lvP2QSy7QfCfXAyckJw+oc41dgDhjv2yTy+b6HjYVdiip5qZ6Pf1S5fREYhgXXu2dML58xJSFJZeULwQacreQ2o45xpCue0RhqyuptUkRjzY2QStaI4aAmvuM4MiVl4TlneHS2ZF9UxpkyrFe6sTrZnHJ68hBrLGl/4MH5A2LSzvd6ueRgDYlMFoV5VLKu6WZTTZjiCMHpxqWZe2MrJptjKEShIC0R06CbbGUitxnbt7VCtKNci1AdFCfUKSqj1XttNJQKklSibR0+K2hVnGGfIn0JRCAZldmQBBdUEuiC1cfWpExJA/hmRJozJUNvLC6oL1XMEestZIMVx9CMUrPRjbBkXcuct4h31GCRRsOOtap3Q/CY4DWiO4N3c/yFMp9NgM3pKX/4t/+QN998HVMj/6f/4/+Zw1hI055SRnKj06dpIlWP945+teGh8zwZJz65vGV/mLjbT3zjC29zftLjY+b3v/oOr52c8Bc/fcL1dmQqI9b3jdlQsdUcgziKFEpRn5vBWuIUGVzQ+HCnEmjbQhwE1HsjW8Q4ppSZUqHEiZvbG9564zW2V5d8+5/+f5h+81v8xte/yHe//2d85Ytf5T/7L/5zfvzB+8Qaefz4XfaHLcvVwA/+8i/+hu7MX/4wTRb36iHNAuKzFgFG2Ql6lVtMu2k+W810W0QT6WqlmNnXCIxTuwLTZOdzBaOMnvnZ7mv0ubFmrMVIxeF182SrNqBMbWl0M2ClDTsN7yiYKMRpwjqDa6AHoj5HznlyqXAskczxz+wBBJUQFEg2Rpm+zqlMTL2PwhHsAAWrZlP12YtJTbtVNqj+cWp2XUW942otzaDcI2JJsXl4NvmfyuMsXTeDRKklXkkDqbIyhC0Uydjq2t6gNbZKxmA1Dt35xrJSExEzp1xTVHXQPkeK6stkrSXV8RUmiAI0IkLXdWrk3xqgs5m4SCUlZS7NoJN6RSlA2Q8DOVdy3qq3DdJ8wprk0RoF6UVZndZa+l4lTjlpbXYEkpjPuz3aqrxqY3Hvc9FCIKy28I6ut01ya4/rqzYKjcw7w1f+/neoVj4Ph3ULnE3H6+5bKnIpE85o/Wms4NYBBPVUK4lZQJFp904RgtFxXqtTrLlEMIUsmVQOWDqKaC7gnH4XgvqImgrGB8R3EDzLZcdi6Amdw3pLcC0tNoJbBExLd80xI5K1/sZjfI8PgYTFFcti4VltKjkNWKmUlPG+o1olB6xXGzo/ULJQk6bppRQRDP1irdLarFYdOWu6Wy2Rw36rAPWqpyBk9ddnigdi3CFYpmlCckBqwi1QjzhRKxZpIO1iWIAVQpkI1nDYHvCpULcHIiO3twcO+8g07tl3liqOkmB/OFCksFlscHZNN6wYU+bF3cjVYcvF+Qm+E+62O0L2LLo19SRwdf0C5w1FIlXgbH3GbjsxhMq0v+XqxSWZyJgitRqmlJFaSGNUH04HuRwYa+JuulJD/SJU448+sMWqVNK7AVO0XsFDtpZu0ePx1Do2k/5A7wJ5vyfud2QMZuioJUMtVDPiMOrDnCzVKyus5AlbE75UKl7nemuxeE3aloqlEirHTbLgKKV5ggUNElEW5Z5hCKScSVlTD4mw6E9YhP/AqXbzCqUMEOEoRm8z4qvm4j/PULKAM6J0dNSAc15c50lH2q3w80jBLNOzRgcioFGSP/ca+kWbDJk9f+7ZHXN6nsfSWcNgG1XxleeZ5YJGhEIzMZb7PYlpRYAaE8NB6pEaraZ82ilQ8KOw8IU3zwzvnGUGl5hiRoInm54P74SfXju+2G2428OLbeVqd8NyAZulRupGU5EyYu/ADQPJCT2Zb17A669NfOELA10olLxke2c4WxVO3ij8+CeVj65gddpz+SKz3Xk6W1gsAtc5sTskjEDnOhZW2HRCzIYqnpOhY7/bMVXD5V4lh6k4JnE8G+GAvq/rUhmLPXadUoXbLEShmdDDKApZTAhRLLVkqi0k46hW0/BmkEf77ArktOVagaFXFj/TDLpmBhrycxK3n2PKvfoPmY2oXynFZkNhberpmKoyb3SaoE6gNnBMpJnctm7e/LszgPW5P1qRIKLdwJgih7jnkCfUacDjim7kOqdSCVNbR9TOrET0vBstgHQuaCJVqbrItgQYo7nk4EzrVIpOimj3wVml/gqFWgTvhC60p5HKkBSAEmnQrnNYo/T9XWMaWqCzc3fV0nkt3EsbN6nqhjqX+2JWJCsN2ijgGKzXFBCjhWStVaWyzkAteDxmmvBeu4i73Y6L84ecrE/I047VwlDKyGbVc7oKrBeBGAv7Q8EYYdH3hKARtyWr0XI2lilO3O49sWau93sqiSzCXTyQJbM/QIxqivjh/sAnzvHg4sAbZyc82JwRwpJiEjf7yLPLPZe3I7UK69Wa5XqghjVPX1wxbW9xvuP04k0ePVxx9vgc5ytuGKBGTk4esBo68u4O328IXY/sd3Te89pra/oh8PR25Gqb2G8zlC2mRhY+E5xnsB5KwVHpFgul7uaRGG9x5Y53vzgwnJ7B6gIbeqXkG8EHiz+7oHO/QZGITXusKfj1QwgLHXvlp0g2hNNv4bqF3qNlIiwc1m+o0uPMNW6o2PWbjHvoH16AXTBZyzZtSfGKKgO+bgl1j3VLnO8a07EgZQS/+Ru5JX+VwzrRQiB54t5x84kw3u3pNmc423MynLI9HBgPe67iREqZWDPWGfrQ0QO1Wrx1lGLxDoyHzqrkNRch50JOSU19vYdcyVOhek83DLx2Xnj68obdVNiIIVjHNo10qwXWWm6u93irhXXfe2X1GMNulxtTorR4Uj33psysA6MsKJR5YVG2ZbWzKatB1L0WrH/F5y1hTSt21PSkdeaVui+lIK2LbsU2cDGjRbfFVAW1nRWkZqgOnMVLxaPJQFESvnqmWrENWCmqg9K1Xhr7wApeDJ33OA9VNP3VWzXR9hhcrfjBko2QaqKzQRnYDjZnJ3z1q19if3fH+z/8EVOK2ObhlMVQk4BzGCmAB6/+eg9ff42/9/f+Hr/z29/i6uoFD08WbFYLduNEioZsHbVqZ1uKJdnmC2MNvltw+uABYy5c7Sf+zY8+4up6zze+/DbvPDrF5T1vnA30v/EFfvCTj3l2vWXMcoyids7qfVQ1ITjlRDFqmG5MwKCG9cE7ldrkjBiP2NlwWqPEU0m89c477O5eUKqhGs/65ILdIfLx02vOTx/wlz/4Ec+vD3zrG1/nRz/6IQ8fPuJv/8HfJo97Xjz5gN/67d/8670h/0ccs4k4Ro4b+Ln2rXUOTbHKSrAeqqYAz2x6WhvUNVmYwSprzzhNNKsGvEqsjDEUKa904xqgJfMGf14n7z0yxdynVtu2OcFYaksHntUJRjjWZ8pSlmOTVu+JqobyUuHIsrDN/6n5LRpaEynjgz1+Rt8MsjUF755fbRuLaWZKqSyuHk2/+35orKrcHjcn+1kg03X98b2qwrOxvpoRey2isihRbyfrjBolm9mfaZbz1cZccyABqFSjwQbOOpyzpEPCNR8sDTyQBpw3o/JilAXSEvico4FlrnmqGXKuxBjbfNYCUZrv03zeQwi8mmAnUokxq6daqsdk39JSM501zVR9LpabN1XVYAPvTDOmb9f7FdDSzaz3z2z05AiGWaymYLbxPY+xeR/m3GxOr+PUmTnoR+mP90Ysn9/D9TouS80thCeot6bT+c85jzOGKIVsGnvfZHJJOp5paaXBgRRK1cgMjG/7mqQyKCOIpOaT5TAevAtY56hYqlXA3tvA4HuGbknX9fTeE5yGThjryLYiVsGrVMwxBc4AxnkEp5YaGCQWfDFs+oHS9dScSKZgnLKTvbGQKrlElb92QkaQaKE6ggu6X6wa6GHJmnpqHFI1TCTmTI0ZKWqXUUvGukrOhXEcqTFRcqU3Hf0wgNWghWl7oDOWO3kBRjjEPaHr2G4PSLHc3u2pWA77PSmlNs9aMB5nPIdUMK7g+hWPLh4Tp4nD4Ur3OM5x2E/0nWOcJs5WG/Z3l+wPO65ePiflzGF/x3Ob2SxXxH3m6Ucf8cmnl6RYyBTGXI/2OlCIsyQtOwqWMauMrTMeJ5CrkIzWZkGETejoKkgp7ToHajNQV6axZ9H36jd1e0MdIyIG0yn7u3NB0+dqwVi1F3GizbhS256qQE7otWjG/mIL2Irk1FJU1cvRiBztOopAcJXHZ6fEw4FSLIODFDO2WFw2gNP1Pvxyyp9fGniy5kjAnOcbZtMca2YTu/sOyr3nkzTdq+o5tWDTE2IaLj53XGbmk4I8uhg69AQGwLcN6B5DkqYAtzOuXjWFq72+LsxtMywz8GTxIvSilL+xKkhiTEOh26SpTI+Z+TADZ9rtOQJgUjX5y0AuRaVipvlEGfBkrAif3hrqZFj2C/ouYHzhunh+8MKwzYG7HPjhxwdKWpFtoaTExx9adtvAarlgvclUCxjPy08C8eBZDoU+WfL3rrn+9F9ws+v5yZ8bfO7xe/j+p4HrLZiPhMDAzWjJyXKJsJ8qNlscwqk37LJSQlOB3hZus7DLlo9KI6IY12QphsupMBYhS+XZZOms0PqYZIGpagFVrByTeZRKZNU4Ukwz4laDYSXnzQaDM5hj2rVoCYoyZ4aZo7n7/dpktCA6/uuzyYrzoaDR/dfH773yCF3MtSjLGO0uty5dPTqUyXExntlRx/f981Srz+XR7jRRU8yYJnbTnn2eEDF429F5aROIwTjbpI9aPL563p0xDQh2ukjW2jq0c2S2UjPFtiRBp6wpLXTqLF5Fl8QMJIwpOCtKKw2VPog+XzUE55RVYy2HSRcuBDZ9M+G2FrGWENqGcwaba8EWgViRqqCUdVq0qyRP1PvAqQF4FVHKba2kVlBVo36kXXBkKtv9nm6RMCFQiuCsYeg61oNn1Qc6H6jFKNXZquS2C5auM8SUSUUNzacYeXlTmSRTJNOrboVSK0MXWPees2FgjJHL3YFdSiwTHCYh90KeBHGVxXBC3wm5ZvbjHusipw/WFGcQJ0xxxBZDP02kwxWbcAC/RLIlTxOdX1DTAe8i3lRCVe+K6eZT3NBzdv4Gk+u42V2yu7mmHCo9BbrE8PA1LB1G9qwXnuVmSTpESt5j2RLCnvWDDf7BW8TpTP37RDDTFmsnwrCkO3+dw+0V9fZDus4T1q9jrcHWA8iBtPsZLgyIewBmhZFIN2jyUtzv8KFy+t5XKRd/xLPvf8D47BkhOIY64sOGYfGYnCPWRUJ4QNreYsYbTD1Qphvq/iXSPeCzLZPP39HbyiEtuH0+EPeBYipTvCTfvKTGxHBxzm6MlKRpI7UUYq74CqVM7FPmdCEMIajxaXCts63rrPV6L2MLrrEiXKddV+8Dq82S2+nA2WbF9fXI/5+6P2uyZcnuO7HfWu4eEXvncMY71VwoFAYSBESQBMlWt7XYatOD1CYzqaXW19CbPpbeW5OJTbKbxiYpkOAAoKqAqrp1pzNm5p4ifFh6WB4789wqkgWqBVxEWd1zTubesWPH4L78v/5DWUaG0f06bJlhjEzTQMuFKSohKWWu7A4H1kRvtTUpti9UayMvi5vOqqBByZXe+XcAA/E0N3Rd/OqZ2UGfP6xKl3xEZ2rgmDfV3LTWMlhxADz6ojVKXyj1VNXYmVaFSqMSJZKCQotQ8HHFap9n3By7qc87mxQJAebszC6VCNKoxT0UaskEicyyUBZjTIMD7iaEMDCXI9//8An/h//mf0ueF/7h3//v+O//4T+mWWNUlx82nImZUpcWjwPPv/Yhf++/+M/53d/961yMW7abDWMsPHnvES9vbtDkhrIqvpimL56TeYrhYrCZLrm8PIAq+1L4w89e8Obujt/81od89xvv83i64Li74Xvf/oCLR1f86c9esuRKU6WJ+z+a+EJnVFhqO0vJasnYuMHUQX1zGikBN1FufSZOUXn7+hVPnz3izc2Om1cvef+D51w+umC/e8vTJxd89OGHHHPh5u7E7/3Nv83t7RvevPmCoBM3t3u+/+uP/kKeyz/LZvi8uQZorFWIGpiYe6n0yc19z6SzTAAzT001R31EjHC2p3BPpXMxHfw9SnCwtidHdnMBQLufGmdg6txUZn221k39ue3MHTqmoCK9Puv7cUyHXLx1mIbVU8b7VqGn3vqx9uZxdABLeqMxBCXFDlyi983gEHzn1sEa7VqK0AtCkS6Xb/6MaqIVvFm5AhtrIdiZJjG6RG71wlqT8BzEcc9Seg0agkvGanVPyVYLrQ3e/FJx8Nv7VJjlboZOZ2Wt4I12eZyDZb7QadR2L7f042vU4uy1Vvz7uSfUag0g1Lr6IrX+e2+sluKyxFpbtwsIHfharzpnLyvroJM0SOqsGK8DhWorgAir15aut0T/U3oTcyUE+Gc0NxcXOpDY2WT9NWMafFFbVwbd2rW17rX51d4kQFQ8lc38uUAqRHO2XlD3DM7+QCju1bVUozSIMZHixgFTW12PQwdJG2EFgEOhlkIhMw6RNI6ojJSiYA4UxRiZhsDlZsN2vCDGiRAjK64IkRgMy0JpQm0D1QK1eEJqMWctDpN6cvKcaZaIaUCleLgH7iOGGJom9yjMMyIZpJBLJed+f+d8bvgQfY7UZoxRGeLE3e7IaZ7J+URdFqz6+iJF0OjXfrbCbnfDNRekcQMV8qlx3BV2S2F3s1DLggUhjiMSlDSMhG2k5YUwZA5lgcFT8dqyEEPg6nrL6XSg1YXnz7a8+HTHcnxNU6Pu4e3RQxUOxwPH12+xWtjnI4dT9oZczkiDqAcUZWlvus+kA0uLGYFG9NmQlALBApFEaY25ZXKBmBJBjKTOAFRVyv7INEZSU2pQWkjOZOqg9+Yi0Kyy3+04HU9Y9Qa+RKPaQmrKoBOtFKRlCAtWG6Y9Czg3tHYPvxRIePCRVPMwBvX7tFrFJCHm6pbcwFoh1EyKC6ldMi9HpFaWwx3BjFEnsgT3yZSZFv8nltrp2hLxW4w1XQruF/Cr/Gj9ob/FJ8BibiLWBIqufRufE1xi1f+kg0d6PxF+2TR8VeyBy25+fr1gjjf1onIFo6xLtGbzRWUTIfdOQmAFqToRtE8WKu7ToOLU5zP5Y52B8fcndRmfg08VsUa1wMujcMyBdIKAG5reZHg1C5XI568Ld1G57A9fbZEXN7A/Bi7SlikUFlEOx8RhjuyyUWnYFxs+fZupsXIzV97sJ3JT8pvGm1NgqcL+DQTpoJAlWm5UDKoQCOTSeI3R1KeWJP77gwWCGa+y+Ujr6mOyeUx9s0gpoNLOIOTKHlqhB+jFlN2DPo3eTelsNwxHzNfCp1dNhnS/iPsJzV/wJfSo34vna95/0c5dl3tQ8+fSD8/Hdf/ZK4sJbHX77N9pvTNXcMx6MfHgZ38ZpHb0O9adQiklMy8Lp7JgzfXgQSNWM4SExC6P7V9NkXNaCmJI8IJW6PJHcU5go/W0Sl+MqKob4Zp/rj+LrXs7FHJZvCNkda1oETVShFp9co5RiapYa5zmwtt9pTTh2eXIk4uhLwaFFCIpOE28GW5aa42ijRp8clDtaTf9YU6ijDEwBPefKbW5/Ag7yz+ncXQTwQpLnrnZ3TGNiQ++9hGffPwTnmxHNlMgxhEvcptLZGQgiDANsBmEPCq7Y+Y4N25PM7BgWrm+SIxJORQ3/Ht+ueXJxQXLInz68oY3dwtXk/KdJ5dsponjUphmuLi8oFmiyEILJ3Ko7IYr9rLhetzwjV95xt31R5z2O64ebXn8ZEvIjWOu3L38kfvDnAb0MvD42VPGqydoGNFyou5/TNkfSd94whgKafmM4+1rSvBoba4eQ1kIMTHqwpNLYXNRObWevLSNLKcNcRhIzFBfUnjsfgQ0YjmSmhGHhOme5fQzhC0yR6gLGkeYntHaC443PyBsT4TNtwmDMmzfZ78rlN1n2HKgXXwP4wrZXDK/+oR69wVadujVR6S4ZdAAegUMlPoaO91gZXCT9cMdXLcvjStfvU2Bu1fwg98/uvQ9bRmnCwd968KbLz6nEtnnTMmFQQObFGgGhcbpkLFWGTQxDgGf/gOqidifGW+iGFGNmCIheWpcKxVDePr8Oa+/eEHQmWXOTMn9zN68eQ0pYsXIeablxlxPhLhhWeo68Hih3edh7SbDzQql+2OYGcGEJl6U+rqvYV2CQ29crJNCCBExOctszDgbG4P1OOvZDawRrOPn0sEPxKHvQOzejL2xQMNsIdZeSCtd3uOyPMvdKNZcqB8sOKs7VGp1H4kmjdp8gW8qhJYJMQL+Gukx9ygcTyfubl8xTBPPnz/jf/9f/++Iw8g/+cf/mGBKPs0ENbQ5CBii8ju/9zf5W3/n9/j+r/wK4zAQVIgtMG4GfvOv/SYf/+nPOKVAWzo71RysqGZY8YZCUGXYRC4vN1CNo2aOeeGz3czuD3/CF29u+bVvfQO2iSDwV77/ba4vNvzgJ59wt58JEqhNKUWx7ElFAtRG93KBsbqUeWkeW7/OH6HLympppBjY744sH3+GhcBmGpmXzO72lhBH/s0PfkQKgc8/+5z9+99gEyM/+sEP+clPfsxv/uZveWe2/HJF71/ktjLj1xLoLOe3zhLu4IpvzVkuIr0ZKmemf+gy8IoDOmvK2lqLqa6SKDnXLCsjKXR/ombVm8ld8uaHsjKMtR9Tr5Me1AG93+v/XIdN8fv5XragbtXYqVHBKYDU/p1MGhrWdFkHkz0VsSfFhXj2LIoxeOOXzhyien3YzT9EQZoyzyf/HNEOPq37c9Zgax6g4qDSvWfRWl+651KHQle2lBtnna+Pp/fJmQGmnZnl1yS4Zxv1zEgSWSVqegah5AySST/fYD1ddzU3Vw20UmmtdA8pOe9nTeJzg3T/LEF7ol69b4T276b9kkj/jv2G6xfNAR8N7jVVq18futF7O9fEnGuhNZGwV9bnNLt1XXhmOqmPBdq98UJwz6h+gh+8tt8x8m7q9FdxE5mQJtB60qpV9zQTo7SEEMi1QqloNLR79QwpoT2oqpo4sFvDA381Q6JhTWiMEIUiFQkHCIkwTFCEYJlWK2mYGKYtm01imkZimohxQjRgzWvpOVfyUqA0kAGJI1iitMD+dCCXyjBuCFxwmm9d8if9Xu+SXsPraA0D43bDvN9DXWhZKNZYTpWaoVhll4+ehjZuWKKQWyUKTDrQirF7c0uuPi/k5gxoaepps0EwixyPM6eTy1M3G+F4OJKLUVrk7eFI1MqgwrCJZFO2w0S62HDxdOLt65e0vGdIge3lBc3gxZsXzM0wEe72d9y9XXi0FW7fnjwwpXvYEpSlzJRSub3ZYwSWlt1TtbOFIKFhAjOKLcytMCZnjUkAa4sn8pp0hife/KWRxFDLqATSkNiOG077ilUPLkrb0ZO0S6GKkabIZkzUspDzwuGwh9I64N7czL43ccTMwWZrDNK5gwrRhKU1jlZJIVIIpCGi2SW+NGe5SwWtQrVGCRn33FVqdcZnVK8fXr19S26CNCNVY0yBFJwlKp3gc1yWX+o5+qWBJ4O+6OyA0vr3jlrbasjUJ7AV9V45vA8X+X3peR/NuT7UrJRSOi5hHXF3uVPp9ebas1nfKPCOt4+zVNbJth/WeQB1RgvI+ZhWWd7a5BH1zqxPENoX1t3sEfpk3T8Ip6gOwZNaYj83zYRM4KYqdw3InXZJpDQhN1BZOGSl2oa5FsZO359r46ZoN7JWwL2TZrtHkT+eBUhEG2jNIxCL+WK/NC/s98Vpxn6OV8bOyhCrvjBvDgr2KZwsillBgROrdLCbVZp3q+qKNp37Y/dpcm09LetvWqd2Iz2+sff52lrLyIOEul419YntfMXWpsg7AssHNw4PgMwVuFoZa30/9gveara6lsn5T5OH/kUPPrVXYLbeYL/4ML7S21oueLGT3XSyFSgFLHg6uQhJlaSBJO7HJBYIuKeBdBrw+VKId/QRXywisT8fbigphF54uGSm1UCrGdSNP1vLlDJTm3uBVXNQb6V9D8H13UHcA2x/bHz+5sRnd0dUhfeuEtcXE4e59sNRT9JrlVMpSPXCfBoUDUopoY9XRrKAhkQUYUhCCurypKIsxViNx1OMhJSoBqEUjBPYzKNH7/H8+df5/PPP2A6RIeK0ZfPEsBgSdL+M1bu6tcZcjdu5gjSiKtsxonGgtsYxGylXilXGpE5vRiiL8uzRyEePNtzkSJWJMlxxyIkZYbGB1oSyP7F9OhLGxzx5/xvEsEXbF7Typ2wHYXz0lMh7cPeWuzcfIyEgQYjDBYFA0pGGUo4vEe5o9UR+/c+Q447h+BmTRZSJoJdchMKl/IzBBjbxhiebyRNJYkAuIiVuOcZCno/U129AFjRNwOAAffCkFbUDkTtarLT8irI7ITog6Zvo+BF1AZsPVBb09COiZdJ7HxGn79J4hdXK8WaPbH7G5noiyjeR05WzdPXSz3M+IfGaZa7QChJ78tbFSLp86p5+X/En+fYucbebOO2Km11eQltm4vaacZuhLJSycDEOXF5fIjEgCKVAqZlDNlrL5PnE7rhwOAJEQhy42AZPTurgbrFGk0rU5t07EU77A5ebDZ/MJ39u8UVdiso0DtwdZh5dbrgTZzlh4saiaaLOR8Dti8Wd/Wl1ZTBBWU5dCuusYtEAy0IMwmK9VljH6y5RQV2CYLNXFHQ2hazzM40QGrWuK2UHm6w1mgpzqy5/Mw8VaNX8OcV9GpXA0gSpns5Ua/NxK/cwgegSv2ahBxVUcjP3ilT8vqVSs6Fj9PE2+/PcunF0UMNqZQiBVy9esCxHVK+4fPqc/81/9b/myZNr/vE/+h/J5RXbaUueF6arR/yd//nf4e/+Z/8pTx9fn+UrAYEYqE34W3/r9/iH/+3/25Pt+hwYAigZs0hRRav7gakqFxcXSIuk05G0BA5L5eZw4N/89HNe7Y9888PnaBDe3N7y3e98i6tHl/zRD3/Kze0BwT9zrpklO6DQWpcwmWEtI1FcdaJdjrUCg91oecmeZlR3MzoKb1+9YNpsekpj40//5E/51V/7Pm9vjty+ecV7T6758Ju/wrIs7OfCZ598xk9++n/l//h/+q//fB/K/4jt3pzZb/61rl5RyLX9Zqx+PitqoOfaw83ZBdq9PElEfQFHl+1ZB4Cs9LqlJ99h0IGTM5uKtcTxfamuoNWKDaz+anauzU3MwSvRM8ixerh5zV8pS1c4RPec0VXi0eWzpbiMMEZhaZUQvdHp/kirv1JjNddY2ToSXGbnz7t/nxVwcbVE8eNr5jVruU97A/e4NHPWwX3j0PfjbCQHnKTLdK1WZ3azsnwU6+d4PSbfrx+rqnYpqbMrc86+KI8BM5cir95RDmbRr/Nai6ozwIMDAS6nW83UfdwpxX2rzLpO4HzMsK6sPD6hq1K6fci6rUsYv60cfle80d7RSZfRipMG1OjXZX139+GR9Xj9T28gNJcS6soI8/u6lEIQT7/zZsHK+nm3mftV3VwB4FJhrGC2OMMopD4O9nVvcB9RoiEDhGrYvD6P+PPRg3UMQJXaAsUWnxM1UM0tUIJMBHvk82k7kEJhs33M9dP3u6dXw0SZi1HmGVplbo3j7LJ5NUhRSMOCSXW5W/D7L4RIXSoxTRSbHTBRJ1hUDFEPgglEtBlimUYmFyUTONVOQBHleJoxywxLIx6D+xXVQquFpcA897GpOveyNEhpRHRD00AKgbbsmSZBLbLbHZjzjMSEjgmd/HkMoj2kIGOT1/N1WVj2e+5u3lKb8cWbHae5cLt7w9Iqs7k3W2ozp3/9r2llZKnVAzC6n3PuIG7UyDK70kJCJIDP013+iESQgdBBasqJEFZsICBq5NooprS6gJXu52SEUdBJSZNy9/ZEEGF7tSGMgSWfvOmelGoLt2/3zLMDwoF1HGgk6fNqLmiAnE/MLdMAjZHYHHii+di8mK/1U4BBjWJ9bMTHBZXo5u0hUqVCT8MMGogqBBJJhJorYRggJnJd2PQ1S27FpbN59FClX2L7M6XawQoOWJfX9ewvkwcspBU06NOhdVDgvLZfuzZeAK4th5VQtQ5k1qna64C+mqyJQe6xnuun+e7ukfn1Zw4udNSdB7CFCI3Qaacr6GJn1F1wppAPzH1yOcNW/lrvHjYwZ3Mo5tHL1mhNaJqYm9MuvWsgqAyeENFAa2AJPlHPeTXJjr1j2KCsCScBrcoiQhVzynNzFo6auqcqRhZltYwr3bRMGq7XxNldK2BnneKrneppzYuKKlBEPX6eHpUqxb2XVJHm+lS11tPl3FKgE8u+dPYdLGzSf2bdP+fn5hU5o4ZrUXRPbLrf15fcnO7fegaPHr6yvYtEwgNB3ro5oPHlnbpq+cGt3O/l++923ym6h3G+6tPllzYxL0a7IZ1aQzQ680d9ATrE5IUibgwbVsZAa0RwKmjvXJ0LNxOo4pp0cfP41ewyCIgKRRrZ3IBPpNDMwafcCkvN1OrJH2eJbrj3dppz47O7hT99e+DQFj68iDzeJsbRPVCK20h4obQW1OalfAoOrLXUn+vmOusUB2IIjEkJAqegnErlVDJavIgIGhg0UM1NmC1ACAvH45GPf3ok5wbNGOJAb30wDIkYBpeD1UrOjWNuHOaF/dyY3RcUkmASKE0orXEqkHeFT9/c8Wjr4J/IwvPHF3zzGx+y/ZXfIB8bL7644eVSyLcvSJtrdrd7LJ+4io109zHD05F6U0AGjrsjy3wkl0uqRez0Bjv8K549+Yh9EaaLxwzbxyzLz7A3bwnxgpp3pKsPkDZS5o+JEnn+0Xe4mg3ViRQntuMdj7YzYwgMesc4bFBNjNG90DQlSl6Y90eKbQiXjyFdgCoFIYSJ6rFX6HhJuHxKO3zh4HrYoGnE4gVL+xDqa3RpML8hlzvC8gJ5OpNCxYJRjzdgENMl8eKSNk4wn7xQMUH1CsKIbLeEzTO0vGJIM/r4I4an19T25XHkq7f94F9uyPM1w1XlWHfMWVga5MMOq5nTfGKUgRSTe6n0sTRF93x4PDSWAqREVlhORw5z4bC/o5WBNA6MKTIMg8vOc2Uoe+J2gw4TSSt5LkSJnJbMdpkZHj2iSqTu7gg0jseF/f4Ws0DOC6VWUlICg3sjNcPMi1LrHY8UA6KRJRdCHNhGodVCHsy7sKpQW5dzuYTEO31Cy+KLpOoyBVZpb1TKqWAUT8GygBLR2gFocf+180I7+GI7qHiyp8TOUuhjW4Vh8MVeE2PUgMZA1O7PUyrFMonYU6AyIfVCMSaCicsep0rCzclj9DEVgykOHO6O/PEf/pCPPvoGrVbef/4Bf++/+C/59d/4K/zRH/8Rp2NjKZnf+eu/yfsffMDl5pEzsjtw0UTQqJSc+d73vsfl40d89ubAw6So1H1tcvO5rqG0pmgYmC6EMETinGB3RAyW2fjk5R13p4X3Hm84HA68evmG3/6d3+av/Ma3efHyDX/yJy/JofXQEOspatXngVY91c9FX2gQanGQQGKfT0KgZZ9Fy9wYh8qT959jBI43e/Y3b9Fp4Mnjx5R5zydvbnjvw69x/eiCf/P7f8TN20t+92/+bd58/vmf+zP5Z92s18pnMIm1drZzzbEyP9Zm4UNA5dzQs7XJ2wGhB++ngwlylrSKAy24vQU0T7LqgJHVdmbCyBmIeQej4Fw9v/PDFXRZ/7mCQ6EfiPbn0aB5uusK0lTz2tTEJex5Kay1X0qpM298jbEsi4NEXaa2glfQLTD6+YphOteZIhHEgRlslfN15rVIl391g39rPXTEj1nVWdGYUWo+g2CGohqJKZKXjFE7Q8kZWh6U44vXIY1nIMVafz5LpXUJnQao1aPH3S9t9YeKtO715BI55XA8OvDV/JysMtZz43ytT+1dhyR5+F/toQ7SLSxYvb3u3+OeXdIbvd4El/M944QATem8bjsHyTy4LdZq2Re09/5WZ+Yc/V63d6ppf+eDdd1XdQvRgTlr941Jb5anfn8YsVZyXag9eTGoIMWIoigDuVs+YIEQE4XO1JSB1pRiswPHGrEwQgiEdMEwXrHokRgLF4+u2V48AgvM84n5NHM6HSitIZoQHVjaQq6VKUQXgTXhlE9Uq259EZTSbgktEdPUVRAnbzbrgBUQUwaEvOzZHSv744FGJYQRk0hjZBgC283A7c8+9e9cXV6LRk45UltgLkITZ2OJFWLYuO+UwKPrax49uSYozHcHbj9/SQwO9qg2rB1pNnO6e8PpeERzpeYTEiN3j59wdfGELz5/weFwx7I4G7zOntAYIrQuI8ulYCGwy8YmwmCGlUKVyKkWRN2niqURug1PLcVN3INQFZZiXGwGUm1ILh5UEvud3IH8oI0pJBaUw3IAjFOpDHHAirLsM2/2M+CKzKyNshxIKTKMif3hwLIrqAWEoZuFHx3QHgZqU69bFBor4xGqKafi96QYtN6YiwyYVQaE0AotGsUqWfzpnrSAeKqotsCpZEQd4CMXGt4v0yC0o2NB0zhhDY55Zs4FMVebPLn65bxSf3nG08MRoa8x15nOB4/zyNOHqXsgAfrCX9bB5h7Ztr5vx4L7vxvnQdU/y+PW+5V9B0QInH/8YBBbj+seijrrlc/Su9Vfyge7irDaKrbzhO3gmNIlR7LCaR1qMNfYB6DVRjG3hzMCrcdUunwIvB8pYNm7Ch25RRpilUamSKCKa0ODQRKPjW8SQNx3guaU2qYFMZcfVBrVemJP7zoB3UqrnDs1FaGK0nBJlK7dI5MONPnsUIl+7SwSzFwrKg7oCHJmINn5Aq7XdNX7uy/OPfvJX3jfVXpwH33pqrHuW9b9d5hS3nnng/vyF/zwQYHmu9Sfe6+d3/wuuNXs4XsfHteXGGMPdviXDXjyCdMZH4o/Q87ai4zq0pkg0sFX9QVER9yBHsPa4ThpXeaQydXPRJToTJbo9HEVO/sDWF0wGhX3NapWyC2z1Mpca7/evaDtgFGIA1Yrr+4yH7/Zc3tcuB4THz6eILhfxlpEl+ajQ6mtH4/2Iry618sZghYGjHFcgbbon60wLJlhjjyUL3gBrR5rHSKbQTndfcaPfvhjltOJ8vT9syeEtUbJRi7GUhqHxanPOWdMhHEYSEkpxRiGyDQmQkje+S2NfV7I9RZ0wnTLN7/3Eb/25OsMaaKGRB2Mebz0CTbBsYJeXXFxGXj+7Fe4iAGtB5LtqRYI00Qj8sWnn5BCZcifMOrnbJ59D1lGYnRdd1sOLMeXaNz6OYsDafg6zRoxPebx5tvuh7S8RWxmkxLPrp8RpSCWCOEKdCAMbp7qixjvaqarD7GL95HSaIdX7uM2KcfqNPRxfEoSpcnk4/lwiYUG9YalRqgjKd9BrWja0MJ7SN0yTEbtUgGPKrzFxvdoEtAo2DhiugEtkBeGBoyPCIMRtgPt4uvY8FOYl3ce96/i9uZzodmpJ7MWhmHLzb5RjntkKR6fXY0alCuBYRwJwa9BkEgImaSRkzWkFcY0cZGM/Slzc5pJduJ4KkwXE2McuZ62BDGW+cQYApoGqsGz997jzc2eT1/esD8tfPOD5zy9fsRxWHh7e8d8MiQsbIZEHCYEL3Ly4vOcYYQUaaXRqrq3CzAGl5AV3Lh1rtz7QqIg5V6qtS4+rfbuvBv/h+RgB6WBCkEruTQgIupNmahKFI9ujxrPC/1WDEke7a2hy8ibIUQsdDC8KUO8r38SkWqVE4FRGnP0hJgyr7LhSDVDWyFEddlhdH8ta8GL3RQZhshun/nDP/5D/sv/1d/jcDszPZ549PgJwxD55jc+4HZ/JGpgmDa9sWSYusQ5nCdjXzwP08jXv/MdfvDDj91fySqlKLM2hugLRh3dGFk1oa1HbavAqM5uboqESj5l9ouRXx/54LFLv/7h3/8HfPc73+TXv/9Xub684vf/1R+QbOBNrm5oLIlkEE0JEggpdSZ5H5vNWR9NF2oZIFdPLpTGbn9g+eQzvvGdiW9/7xvc3b3Pe8+f8MWnn/I7v/03+ZNPfsrFxZbtOPDtD77F6/0NL1+/5Hh8+xfwVP7ZtlbdqFpFvYnRpW1I6x1t7uVq4mCL4SwZb+65jJvOFKnWzveidqlAWxnbq6fimoknhlfinmrm0q+GrlT//vkPsaV/199tBSmkJ9TS1wDnQryeX7cmoUFXDnQQyY3p/TlLMXpKai7UUn1OEjfTTilSiu/PGT9e964MgJw9oMBwk+7Q/a1q8fOgGnqtL/cMIl19yEoHShVrQi2e3mQVYroHZQxPhJPOCNUA47jpYEk8M4HGYaDUzJC6CXkHd0r1ObEUB32c7dKvV2n9ulWWWtzYvFOkVQPTMFFyIdflDDo9gJt4d+Jar/27Nay1dZHUG+bnsaL1Bq5fy9rMwQMpnRPQAXjzukl7QqV/UmUN//ESSfr5Lrijr0sXXU3ijCgfs1bTdzuzpFzaCML4ix6br8wWJCHq6hVTodVEw1PONUasQWjB7+u0sucCtORpjC0hJl7vdbansCDqzY3t+JS7fKTVE5KElAaGtGUcroi6QeNI0EazyNu3R6bNllwDx7lyWirDsGG7vfY5qFZvLFSjKQ9AVE+ANiu0shASlNzIx5mlLIQ4omMk7zPWFjKN/f6OWmE3NzQlVCqtnagGG00c3h558WqHDgNtilyNAxfbK4aLSI0Dp9xYToW2HCmHO0TclKPkzOn2M77/9Ss2KfGzt0d++uozcq3MXVI6n47kauxP1es/M5fhRmFuwtX1M+ZW2c0LVguxA6sxDs7abMYg/ixV8TLRBI4tU7JLckMcQZMHW9UFl+AXWnAAapg2MAzcvL6lHA9so6BafP2De7dGVV9p5trZoN3MICYsGnkpVC2kcSAQONqCqTJsNkxpILfC2+OBPBekg2ajdD8uXCLsCZXuD1eq4wGIoDExWCVhLnF02jitVobR1/65GMUchDZVKIHWGaeNSLMAdFmzijO6TShtcYlymxgGT8tsZeE0K7kqVgcSinRJ6S+z/dLA01kLiTMX1v7w2lFZAQQVN5zsw52/3uqZEWUPECKTLok7o9/qE+8DQGCVt62wxxn0ErzL08fXd6R29+9+FxTD/SSCBKL1MFRbLdTEXd3pvhLUvmD2T1/3IKzJdve9hvVTVmNs+oK1idH6wK40p0WvZuiSYTXbJkC7uL+h6LpfcwPKLK6jVAsOwEijSulm6D2mvpueYjD0iFkztzrDjNUYnjMIcA8SyQpEURGrlM6ECjgVNHYGioiCKc0epMqdOxmdHC7v1E0PAJ6VJv4QEPL/N2nnH6wT5lpHnwHPFYj80vZuvuEKZD68Yg/e/uX32s/zqH4Rs0rOB3M/rTdZP6sf718m5ImGSO26/kAIA1FHUmeHBLmnRp+NKLvpJn1Qd+VKc8lNnc9FkchASJGg6XwNtMOaZg2tnmRVa/EY1rVw7gVI5yv4BBIGp7qqcnPM/PjVgc93JzYJvv14y/VmoIgnYpTmA8NSHfmfcyWX2ruZnIt47Tem4IX6EITNGAiqzsbI0tWeCriZZ26CUQgxMKWBYRxJIVDlQG0LuRVimtyYvBWf8FujlMZc1tQXIUngejPw/MklrQWOp0Iclc04EoIwDEoaGvG48PgR1HlPGy/42jf/KiYDr159wub9j1zPv7zkePOW490LrAWu3/8ajy+vmULk8tl3uHh6TW0Trz77GcvNp2xiIqtw2n2OXsDFr/w31PSc8sXHSDuwLJ9Cu3Wg8PS5g+2bp6BvoWR0eUkIT9FpS4sLZGM7XhPDIwY9IFb6g6/YcEk9zpTjQs6JuHkfmZ5QmGjHVxxffIKZUKZbJExsrp9i2w2hXRFGJchCSoObRNsdqXmHOS/d4FECrSpCpMmIBR8Xg+2pyw3ES9pcqPkFRBji4GwXMnZ8AWRaGKnDU+yYaW8+wcbHX3n0eM6GLXuXiZ1carqNyj572lMTyPUEEtkfjbvTyZNkFYJMTEkICWKMiPWCtMHlBBdjpDRjX2Z2twt7yRymhUeXW7abiViBUUmDm3V/95vv8wc//Cl3x4WPP/2CD957xsXlyN1+TxoSh8MRSYknT694++Y1h9PCGsWOQLPsBbmag9hSUatcyEQLidpOnQXobBkLDZPBn99WXRKAITFiuRDHSC6dXVyls47c9HcIhWpCrRVNilC7lD702Glf9KbBxy2tnnKXW6WpEaV4UlH1hKAQPWHOmrM3gzRoXujTfXNUIkU7W7rCYo1NigwpEGMk18oYB2KCGJUQI2kc+PGPfkg57rndn9hcbtjEgSFNyLRF0gVLWVACpQoyehHtc7gnzGH+2Ybw/e9/m7////i/o2FLLd5EEFWvuRrUktGoZ/9OxZsNOngn/niqWMsQ3dw0l4XPXu8pufH+xcAPfvCn5FL4nb/6G/zdv/Eb/PEff86r3U9ptftlBaEuRrhSpk0iAceloikyhN68kA6CRIWyICrUJRC3I7u3R/745kf86U9/wgfPnnM43fE3fu8/5XTY8z/8g/8X3/z6t/ned7/Bh/F9Fhn4q9/7lb+4h/OX3lxSVGqF4I0OLzEdtFHoNWF/be/YKmui2UPm0X0H8Oybea654Qw6GN22oRdl/oZ7xoysFbb1+lDPH3FO3jsXOPLOfqU3Vf3ffjDurfTgMPtBnr2B+vEu8+yyDu1+QOqeMmIdENPV+FuIMfS0ukprQggRs0ZKI1A4nU6IFEKPB3fz8Hg+L6s/U84+t8QYyLn2ZDq6JYS5OXOgN0wUs9wXFEJKyjRtHPwpq2zPzqBTKZW8NDccXlwGI+rfPeeCoAxDAjywZ73GtS6kQYgpsMwLUtWDAHDAeCZ7SuHDc9ivhUAPPXh38hK6pBl5UKP2e6TvY5Uku8rEA4BqrR0c9a6krxL6Cqmn7a1m4u2+cPM7z3DJIGtjM3SrEvff0/6sr+sFFxwoQSKov+er7vFkUjFznz6xghJ8TSvNTZ8leMPVElW7XxODj28yOENX/X5WM3KdfT3W3FCeFIm6RTcjEhutmqfUNUWiMIwbkEbNC7kU4iZTwkIN1RUmtXJ388YTWhXUIiX7sYl6bVpy4bhrWPdZsnZgWRrzfKCUyuXlFeM4s98fKUUoKsxzdj82UZJ5bb/URkiJm+OJaRq5ev89f09ILCGRzNN0rzaXhDSynGY+/emPudvt2J92lFzJy8wrndlapeaZL372ki/eHDmUwrSZiKK0XFiA4+zeommIzCfcz8iMMcJ2bMy6IC1wd9ijQTFmalOq+DpCpaKhoWLsloWGEKaRKUYGSTQCd7cHWi4EKaCFqMlVQ2UhBNgMiiwHEsltxGPgeKpIG2nWsOhNdet+XjElmkaqNEwq4xCxOfPqzS1xMzCmkbEJ+e6O05K7VDPec1uAWtVBTXPQ26TRBKoEX1a3SrAjgwasRDQkJBjTNGDVo1JKaSxN2I4TkguhFFpx7GOpYDLQqjAAQwjk2ro8uVIFhmFiCBNpjNy+eekNAIsujQ4uBY7RvUJ/me3PxHhyvELQRu+e9M7Lg4ly/WOV1/07D+NL48uZ2vvg5+t+zxKxh/vXe5BhZVg93G8nkv7c53sHwl/RcFSy9feXTlVdVUNRVnPldwf2h/DJ/eTdoTc7873OR+xd2v6T5h4HhYpY7jsYCBYQa2ioVHHEtJ47EwFh6kWjm4kFAtLUwTr8oWoiDm6dQb7O6uoFgWIdDb53EKj9PEtPGnM+WWe3SD074/skKL3Tdo8D3f+5Ku3vz2fov1wnmi9fiS+fT5N7ryh58PLOKv+F25fxKN+P33j2QDPefiFo9bCY+vLr7OdfJw8+w+55e1/1yXLdVpBOtaHB0NALraZOrdRVXiq9dPBFYWvuE9DOVGi/l5p4gkyrmVYXavP48SCRIKmDuPX+/7VQy0zJM3M+ka3SqmGdVp9C5xNapakvDAORZSn87E3hT95WTJSPrhJPrxIa3ZMpPwBVS6fGBQ0+yNMTVXpbuLbay3jrf0ZEElggV5hroRGRUJCqSPPPlBhJKbAZx06jb2yGxDSMrl/PldzccPHQ41wFN1gs1UgxoEmJcSCEsb+3MoyBGAdSUL720cT+eEfRD/nw+RV5njktxlyEw7JwyIFUMsfauNnfsey7NGmzYXt1yZNnH5IPt7x99RqphVgXdn/6r6i2YXMBj59+gO1/Sr75nJwXNlKQ0x4GIaQtGr/uaZL5xygHdLjE2gmphfr6E2S3wx5/E6aJIV6huvj1YwHJWB2pObDYlpID8+7IUkDGiVAbYgdaPnBaMrt9ptqJaRjZHmcurx+x3Wy4SEKMRhoKsFDmT4l5xuYNpSgqhlhB2g2pXiF6gUXDiOh8g5TPyPuFsih12ROlUZcdpCssjuTtE1rItMNr8mnPcTH2u9eE4ZejCP9Fbs8fP+f1i88QjdRmHI+3vsAvnrIZVJGUWGrj1DIq0tNBG2KNm1YQNYZh4nJIPXpZzqP+YHChAzdD5XZ/5Lg/cTjOPH58SbgSxqAUgXrYETYbL4iBAszziWGaGC82jPOJy+mK/Vw53tywHE7dNLV34lo3zY0uS63ZpQDDJqLTwHaTCDmQlzUOfIEQiFUwMu2BYZ91Dxf3PnAJTTPzglEMQuxdPV/oaKuQBpopsSkLHk/urCkPF5iiGxQX3Mx7CY2NqnchVTACS83e0xchV+vzaGRu7o/oUmZf1KI+HgVNLKVQmzGkAQ3mwFNnaUzThp/9yU/46Y8/4Vu/+mu0UrA0OENo9nj3KY0+Nmuh9OPxJpj2ho8XNKUYv/4bv8FmM3E8+djnwSc+V7nXs5GrMqkvwJsttFppFjBtXG233NaF1rxjOiQl54WXtwfysnD9aMuf/PQT3tzu+L2/8Vf5rd/4FUIY+dFPPmO3z7AsyJA4HWeiJjaX1yzHHUlTZ+AlZ8yYYPNCzdkTklrlg/ef8t4HX+f2cMOvhsgxF/7e3/1PePP2louLJ/zs48/49MVLqi18/OMfs716xum3/uqf5+P4/9MWuhzZt7WLdW/8fDYHP7/D/x7UGe8Pa46zx9CZsXTvm7NKz+4Bo1UWT8cgHtZFHQh8UCudQSmr94CBSDeUfsj19n+fzavX73WuBu8BCv+6fgDWwWURJQ1eb2tn1Kwg28qYitHnav++SsmNZZkdQFUPRxEVSnaAamXcunwu9H35WFGrJ/xZBdVECKGDWhkIjOPgjCURhmHwIBU8GVLEjbJXQC6ESC0VEWWaJm9W5UKIkVozKso4TN3/6d7Xbhwnas0eRrBkwLi6vMZMubm5ZVl6HWH9nHNv+H6+lg9WOfcgm0uSH66/HHO0Dkbd0wbWa7my3+jnv/PDzuz4dX3WzobscgYyZcWyzrfRPZi5sgrcsPr+Rc764ywBdV/QgFngq7xZXvpsmd2nC7onTiNoRmndHisBAyEMIBELASQQtGJEYhrdo2xOFCucjns0KTq4WfiyOzKEiE2xX+XeILAFU8gtYzVzPBmnuTf5TgsHDmANlUocIi0ry9FrBDNjbp5eV1FEIg3l6vIJFWPOvo67OUTSbIhsOCzFP08iKURCUMYhMqWB42lhmQvSKstxx7Nnz6i7Pe2wZz4tnF7fMm5GTpvEB8+fcTGO3N18zhcvPudwWs6seB3gf/iDHxCqMehIk4E4JI6ledNTgKSkFGnVmJcKmlCBujSWwxGtMC/Nme4XF5TlSCszSRNRhaYFusrJmqfOigpRK9YqmUqeG9KakzxUGIfYfc0yS6+xNtLrhNwoKrRDYSBQRSBECh5MlJL7RqomjnNhvLgmXQj5NLMshc31Y8YhspwOvN3d+dwsgVRBQqMGoUlh173gEgsR6enxQg3Jn8dyIpphtcIQEZRAQMVYamZAsMVlnnGIlLzQDjNBrOMm3YuxCUlAyZSWyc2jG4Y4sB1GQnTJ75vjHgykej1X64KGSIyRpS3sjvMv9Rz90sDTuq1TiHa2iw9uv3jhrQ8noXcF4+et92fWodP9h/oHeQ11v2j88tZ8rEJM0F9wCLqCA31eD9YnNlbYqTOc+jC7slE7bnFm87R1gPYj7Fpo37/KWsrddxPkrLWW88UN9Ajhla5qoX+u/zyoU/NFhUEanfTm7+9AQKE5G8kiBYidMlzNuwoenWvcw1X5vKhYz3ZbwSC5N5V05lXz11mPWlzPe1svsoNcDl908Moe+GYhD+RxKyBzP8GxnrvzVKhnJtEqGbjHDx74Kn0J8Ht3+3l20hnuMx4Udv+ud8N67zWEd8u8B/er/Dy4tDL1/rJtIo0gC1F9EWp0gEe7EXFt5FahpyY0LR35614J0nDGQIYOOC1lYa4VY3BzOR3QmMBap/dmWsmwnKjzzDFXTrlReocr9CjfqNC6B0iVStBIWyovbmZ+8HJmaZHvvHfJd5+NDKFxWAqhVXcqUekgkpuEbzeBy+weIs0KuQi5eqyoT+CFpbqprUkGMQ5LYXeqgHcGQhBaSeRiDEm4nC4Yx8RmnKidEn+1HdgdC6/e7Pja8+f+nDacjtrcM2aI7ns0JKU0odXIsBkIGrm8SFxcbHn+3hN+/a/9FT754Q85lErUyr68Il5NnI5Hbl7fgRSOX7xlVwJ3P31JLY1nTxKPnz7m0QffZDM9AgKvf/RHpPkV14MRTy8RYLr8iOtH73F3/AnLaaG+fc3t/An57Y+5/ug3ID0FTiQKNlwwDteMV9/EyoKlxzQLlN0bNO8I2yegI2Y3lHJkHECDd/YaCSOx5B3H454mjRAW6gKqJ6cxhw1ZlcPuxP7uyOs3b3j25Iqvf/AMriKack8f3IN9Qa07anmK1mviaMTYCJIJ88HZbMMVTR+BvqHpG5b5lnpUTBMtj9RyZD5+wnjxFLv8VXJLLPVz2mHHUgO1WAfJv9rbze4NWpW0jchdIUlkVxYKlUebLXE0VCbmChoVK10SYEKuAmoEc5+UKo3ZGkN0CYBYJZrSYuNxGtiOA/v9kd3hwKsXN8yHmQ8/eMa4magIN7e3XG0nHm82SGxM08B4ecGnr16jolxOF9zNN7w53jl4pAkNAat9ktUEGCqBVh1sMDwCOKahP8eFPCxYXpyZbNI7iV6kyai0pYAGrLMTBHzcaj5blVpIKVBKJcVEE5fgJjEqRihACp7qJ0YthSxK1MEZRFKdC9zWxboDWZ7Q1PrayhmRpd7PKbkZovVcV1wMEykq8+y/p0ExpRZo0eWEaRhZTgf+0T/6B/zmX/st3t7uaQLjmKgr+7m0Xru4MXGpzWXCCtq60aoVlhmePnvO0yeP+fiTtwRbgYjgXXuie5XgzK0WWmfxRmeT1cowDlxKIhwH5rKgVIY0cFwyr+eF05sj719uuam3/JN/+i/43d/+Lb794TXffP8p//qHH/Pq1Q0L3nAIw8g0JubqYSgCWG3EwT0ACY18WFhawarwkx9/zOeffsHmasswXLDfveT3/8l/z+Pn3+bp80u++yvfoVThw29+l3GcOO1PPHr66C/mwfwzbB0a6KR+LzDtYS1hD8EgOQM1mM8l1RpRlNKTHLWDOKp6bsJCBwbafbNp3R+96tUv2Vu61Cr6IXUjzhVgaG3dv533/e7v2/nvX/62zdaq8f494GyZ+xafH3vJpSeh9SZmLe551L2EPFnaXFbdQSurnujkjfDo3lXqaXmluDdUiO4JtybTrXI1Pw+eSueNIuv/No7Hky+KNbgpea5nMGU1ZPcuf0Qkuo+lBswWVN0PrraMNa+rRVpncfWQAtYGuKfYleIMg/l4e2YdnWHJLhVcGfoqa1ncJcjr9baHfkvyLrgoD1vxa6EtiLRzeecSyNV+wxfYjlG28z5XBttqhL5e9/v7wz3eZF0X9vO8Xng7N/dbX2+l+/vGvPb/Km+tVhRny1Q87bwVT+usGISCEUATppPf99kJBiaVWozW3NNJNRJDophRA0ybyDRN1AI6QNSBSia3hRChnA7kwwk0Mh8caLLY13K50YqxtBV8DoTZr/QxG8fDQgwj26tnpFiZD0eKwGa7Zbi+oh0Lsblh/1IqSmSTEiOV4zIDmdYawQKnPNNkhmrcfvHK63jgdHPgcDoyHxdqLqwhADFW/nQaeP7+R7y5fctc3DeohuYq4GZoCagONCK1EzIMZTaj1IVoMGggiN9DpafSl1Z4c3PLzd2J0yK0YFALQVzSWVigOpisYQWbDCRRUJoK1MqSC4ecGYIQm1EywOqdp0gzarfJCQin3LAYiCHRstvZlOqBSdUgN2U7DEQNPEoD5EKZPXlVglGYsbzQrNDUxxJvZHkKsa3AoBlqMOcTEtX9oVGiJmorUBtDCEgFKW41ECSTTcinSmswjpE0BXanI8sacibSWWDrqBCcdUegaDuPOVETQeF0uCM3n03EQKMwbhLL3LqvL0gQ5uX/T8DTw201lX444Tzo4fDvG0J+rs5fMQ7ugYN18Fwn6wcv9UHqPJH+4k9qK31mPdYOKq1ePdKN9Bxk6uh9T+QQgNYZPL1b4CBQl9oB1ejpN/7/tbgLfV9N/HXJuhdVZ4dFYBB1/FUKhIyKEcx9ZSKVQdcJ22NNq8ChGqUYtbOavHRvQCaRu5G5f78VBKrm721oN2jvhbI48BM6m6tKZ7Cs57Qzvc6Qn60A3r2w8nzm3ymaHlzjleJ7/vc9VOQ2pH5xz0o74bzfhzfI+a9fuswrKPjl1/4cGPVlGvIvBEF/HqxaX/fOuztF/Z19/jtA1a/mZiAVIdPzjh3oM6F0g+VQKhIqUkr3mGiuVQeQSsDBHKueorWUhSUDIrRxvTuaL3rLTF1ObuLXjeh2s3s6iQZi9zhx+Yf5vamQJVNz5uXtwr/9fOblAb7x5Jrf/uYVTx8NHJcF3bnGPMRGDJGo6cycGkKl5cBhObmpbwxsEVYDueM8M5eFpRRnKrXCqbqX3MU0cpUiuQwcTgs3R4/OjaqMMbIZBpYsjFH51gdPePH2xO1+wSxyvU1sk4NVp+49sb28otbM9Rh4/uSK9y4TGkcO84ZHjy7YjMLTRwMX15mLKRDqwDBVLi7e5zjPvL79nHl34L2vfcj11XvE2x0/fv0pS14Ij75DSI+obaAUQS1wPWwZyTz54GuMm4GbV58AhXL7MZSZcXqKHl+yf/szclnYtoVSTwR2BLsjyJ5x8w10fEQNGYkGT68gfgohoNE7XzUPtOUOuQBJA80itTXqcqTkA9Iy1IVSM1I21DBiTZG4dclTapSSOe0OBIzLoTLpxCYJDAXsBtEDqjNhMEQSw2jEYcH0RM6fYcsbUtuQNk+wTWLRW2yeKUsgbN7H0gQ60soNlm+R02e0eWAue4pVX7jkA+kvAYp8ujuQjzNJTqSYqNi5I5Vqo82Zt/WOnM0NxcXZDkOIBAmu2w+RjQaGUZHg1yvX7I2QWgky0tTYbCJjVMZJefH2jpvbI2aveO/pYxarfP7iFbHBMo6M6nLYi2kiKrzcZ/Z3L8lWIUS0ZR8/mmJqiCmhCc0W1thvteJpsLVSy4JKIowJrQtK9HsouCkx9OZEaX388iQe6w0Mf0k9z+OFvsAx90mUzt6tuB+WtgpFqdo8Hh2j1hmJXmS21ijiXk+xywNpUKqn0xE87j5oeLCo0N7RN3JrHMtMmTM0COK0eRFvR5XmShMJjRAD/+IP/hW3b1570tCysBlGogaWsriPlzWkuV9N6Ca+qnKuh8ygtMwwbfnu93+dP/nJPyKGgIVGbCDFPT9qcBaUS5sUNEJszjoQMFGmsCEkZWobasmYVXRZkGNkLjM/eXvLk+1ASom72z2DKo8vJ/7Gb3+fH338Gf/mTz7GF+vKOCTanTMfQhBSTzBr4oulLIXDspDCQNxuKXNGwkDYbsiv4M0u8/iDEcJIWfYsFQ67t2y2I29fveQf/YP/Dv4v/+c//wfzz7Q1RN3YwIGZ1dDU8GpToAMxD1nVK5agHXDQMwik7vPUr/u7KXVdGkVvMPVOsTOmSq+htZNS7iX1otKNsf1Dz3XQuTDz362eUqFr2b3J47Ya6++seTrkw1rQzmhaXyesX9DAqpHrcv7sWrN/f/UYej8+T5RrTfu4Ykj0ABPD5aeqDtjQz+PqGensHveXqg0HkGtvDTeotRGjYJY7S8oAJQb1BD9dWUfW5X5GKUtXFQga8LHZPLynSO3nVs8Al/WOdl6Wcz2CKVaEasa9C21/po0H53W9FzoYZPd3iH/HlRG1mkb4OLPKIb3Ybufr6ed/vQArE3xdFFkH9OgMt3W7B5z8d+v1tXOKn/tIlX4PxjNYJnhjm9W+o6cRIg4kshptf0W31pTcChIjEgdvnJoDtrUWlrogoaKxhzrVhpWM9XCMnP2aLtkbqyAsdaFZpi5CLupzUV5oWsitcJpnyIXT7pacGyobT4arhVwLkgIaE0akVvcy2kxTX3OCjNXXpE14/PQDtpuRF69ecHN7izbYxAEZI7ev31Lm2f2qUqRIIYpy2t9S8oyYcThkTktGakaqccqZ6XJLi4HDzQ0pBAYR0uhs6GaNpcK8n3n9k485nGZ/XjtoGVSJCK1kWm4sVmgqVAELEYlKqKHb4DgrL7ZGlATmDMTPP3/BYS4sUmlaETxhNqQIFtCm5Aq5BU65MEYlpcBuzkhoTBhl8cbW3GDSwNjZkKVAtQ4uxkbSgBRDq4FVIoG5Fu7vWyENyjRGLoaJlhf3bpv3vUFVHewVD1MyEwd5AuTqgJy0iCyBlv0zWrcpObZKEve9ldpotRBFyDWjweM7asUBt9qQGhg1siwnpLnVD1WIw8gYtY+pjdIqJgU1pVRBw+AN3dbVGz2ISjUitYA1am0cToXaGkEbuQ2EEjl5VPJ/cPuzmYvLefQ4AxDSpJvC4YNHByh87FsHRH4ODXgX2LYzsPHgJ/jg2bsbff+YOXPIVqPvPmGeIQ1/3xnb7wNiMPUYwg48NQwTPROBdZ39zhovB2EaK3rv3c2A9K6MH6SokRQmPGFO+w6bQsEYBLbiAE82Z3kMITAFmPoEiSpWK5toqFTG2LiaKqrZEdnoDK3dXFlKoJZACsqoQmEhhsSIQHMPnWpQCcxVOTVPsJkrzFWoaDdPhxacbt+aURBW0/HWutRK8NdzDxo17v9s3MNI9/5WHXb4EohzvoYPzi7nd9+zxNz36/4OWCuSXwQo9TmZ86325e3fsZhs9nDfD4Gud1//LrjUfy0PmFH/3g//am7vyAYfHHYzo7ZCDIFiLslcPZ1Kq+SSWf2SnNZfqSUz54Ule7yqBpfQ0BasenFrbYY2+4KyZU6lUgwII2EY3DMp+QK4lYagtGBEZj57+4J/9bMdf/xq4enVht/65mO+8+EVcUrMy4KGkdKZiBdDZFBP7nBpUWauPqioKhfjyDaNWGscltmjVCVD87S8pXkq08WY+PqzS7Zp5OZu58yKMDKNA5fTRLDGxTSSY2ST4Plm4I9+/JK3h8rbuxNPrgYebbfEDkdvNhOX15fkWvj+t7/Gd7/xDDv9iLdz5CcfD3z49SeeCBfesql/wmaauLj824RpQ5wGluMnlD/6YzbTY77+9ffYXkx8+PQZ+dVP+eTTP+a9S2c+Hl58gl084joZ73/tKWH3Y67kjicffMRVOnF3e8vh7ccMCGn7jEAkpceYNvJ8YG4nkuyJ4ciYJsJwjehAVYNciXFD3Tyj4elDSKXpQAtbSjugnVreSsVqJmikppFWXEITEWQQwDXoIRaGzeQ+X6occ+P1LrPZJtI2EMaFMTmdXKwyTQnSBWkQRHeIzrR8pOYXDK2QwjVMF36PxoimR0jYEOIGGS7RWqjlFW3+KWRxfwYL5FxYyonpgXzrq7rFNDDPM6VA1A1zPvhzWHtDRJQgCWJD0TMzt3YGrWqiNe+wHU7t3J0nKDEGN4GOExK9A7fQuNARCNzEE3eHPeXz185OOWYWEXR35LFesJ3UE2eaolo5HhYnNQUlhIFSPCVNQiBKoKr7Ivlg3xBzqUttzpCJKTKOgd0uIyEgsi5UjGZKk4y0DiYFnzTWwJB1EdQEknkCUaN5il7QvsT3RVnqBse5FFBhEum+Tu6z0JrHKmfMTV0lnKsSBGqrPrbV6kBmcbNz0eZ+H3iaXTawYgxRkR6Hrtal5U3QZh6tPG34/NPP+Wf/9J/xe//Jf0peFjbjhpAGrCzuu9AaeamMmwkJHaRY50kRN6Csnpz37e9+05OOhsFBi77ol9WkMChajWYe9Z7b4h1NPJGqoe59VQWG5HL9MSOcmGdjf1z44ubkiyMRvvXRBwQRLrcT337vET/96SfscmVZFqZhcuNS3IdKNVDVuBxGlpw5nBaWZUHHwOl4oOVGu7nlw6ePATjNC/vja55Y4rvf/TZ3+z3z6cgQRrDKab/wVd+8hO0VaDfg9voynKWS955K1k2YHXhpdXUQxeXjrbH6abqcrP+23c/x0r704XjqbOvm1g6A/vxx6upF+mBcvPd7PH/oGaAA9/NRW6vCXnd3+T5N738ucq4GBenhQfeL0RV087/346irbM5lJbXes33AG8iluJlzM8GaokEInf0EkPMCBGcysjKfYa31NShKZDXfPh/v2mzsHf8QnLVkzc5rgbCaZSPMy4KoEkIiOEWDGJTSF4ut+iK1LP49au3yuzM7TTi76K6Nc1mv0+rz1O8P8Ta4L886UCS9pmb19fLv4PfS/cUWuV9DrfIV6df8HsBat3drZvBrdA/ESb8efq6cUbeuzx7cgsi5USvi53uVbDZqHx++ulsLnlYYcNVKbdXTz1pjWSp5yVQriM6EuAVT8nIEK94QqMo4XHCaPSgjSOC0dK/T2DjkE/Opcion9xNMAyU3DvsjyzxTNbpPEe7nky0QTLkYt0zbLSX7/dSGgWnaMs8nRlxRU08z8+1bnkzXfO3JxM1nP+Nuv6BLZRwvuPniNfMxE1S5up7YhA25ZF6/+Jx5XrAGu0OhiTIET4WuMVGbkkTRlJx5Q6OV7IBH0L6W9AaJNSF0SU71AYZq2RUE1e+VGN2zs1nxukWcIbn4xE0wI0VzX8WcWcjkWqk0WoEhBqwYy+xjh4rXQxGlNCUvlVp27h1phoREIkE1P6ZYQbLf28XZzsUKSCGZEvAAElQROzGkwrLMpDjy+OKS68sNh8MJO85uQSILHowiRHNDm9wfl5obF+MWoXEyqBWU2pt1IFJcNqvGXNwsXhUozcHkmHy9EyOUQK6RhQKhMYizsgMNyZUxXCBDoIlRtSHF/XnbiomY24VMaUPJ3vgv2QkBQZQsjVpdIXPMFaqrlYZYyBqYaya2/4nNxeHddfbZUFutp6etQM+DocnWSfXBz9ax3u4nnvP77BeACw8Bpf4etfucMhXpVNz1wHxQFiDYvZBuENzZvgmiSpFGNS9Og8iDgtUn2Ngn6dIEzCPkRxUGVfepsIY12KgwRSV1/5sW7GygV0vlOimPog/yS3Um02USNrowavUEDoQYjMuLzLA5MVwVLq4zep1h67RLwcizUZeA5EBYBE6VGqqzPZYGx4FwgrYorYyc5oGbOXK3CIdsHC1QTByEasLSXG6xtMaCkmsHnNTd71tf1Fezs+zQ6EyvFXyyFYzyFxjnOezdi7l2UPC+XjUoBqUUpph6LO46nb5zt73zL7/M9/eEf9aDD7Ofv4lWUHR978/dYf8B4OjLS1JbEbL1pj4Xil/1zdaqFeuFZRCD6AVJQF0hrEoQ7al2uAa6OmshWehdVDfTza2Se5pWIGNWaC3TdPWFyBjFi0sRYhq4GLdoGolDYuqymladzt5qoWrldDjxgy92/OEXB1II/Pr7E19/vmFzuSUNIykVcgsdcRe2yRd5p7myn2fmnDksM6clE5K68d0wUnKh2oI1YUiBFrzTpg2uBuX51cTXnz8i58DhUHh6teXbF5d87f2nWDH2NzdMQ+RQKtsE1hYeXY683e9ZsneL3bQ8cLUZeO/xJc+eP2UYAt/91S2PL93s+1KecXq78PjpJY8++gZDvWFzUXny9e9xtK+xHI/U/Z6oxvMnjxiuPuLJs+eMF98gpkdskvDyp1cMl9fczcbHX/yUEAqPLx7xjY++jpy21HwHQbh+9AFxekKMkVoawhU6PKbYSNu9Jt+9QYZKGCBcTsTpAyxcu19Ga764bmvkr0sPrHmB0HSkWIUyIlwAAyEG4rilmBBkwE4HEJ+4Q4ikCNMQKC1CioRxIotwZGRuA7nCUiGqyz+GIaISMDViSqgMGEJIRsTNyOEtajsGHYjpOegVlUvUIgklROnm8o1kjTj4ANQiDNN0XuB9tTdPUNkmP+dLPnnB2rTPTS61XuMqgznA4Ga7DamF1M3GMS8Ia8M9ospCkMAQFqJFLi4vSTFyd3fDZhuYNiPpbeTm7R0XITFcXzGNCaExqJDiyHFeuLs70KyRxsQ8n9BSfQLDMHNmVaFCN9+ke4i0FjyivDgzSkVJSSEkcp7BuhFwSFirPgYHA/Po81Yq7WzKqUgwrJYebud+CE4e7ua40pkd1rrnUqQRXN5D8OaECUGCg0hNvCPYvENfa2FZ8PEKjyf2DAFFzKPam3iHU6N/ntE/g8ogSimFISVkbYWZMzcPJ+Of/vPf53f+5t9CQwJxuW4dfNGzlOLyRBFnIMoqyfIQEb/egZvbPe+9/5w09HqkGtmqM180ItUbDC4RqpgE32fNXWYEzbopuay+LI3tMJDCSF0CkwpvjzO75cQPfvqCN7d79vs93//6MzYJvv/RI/7gx6+pc2GIIyrWzQUAxRtrVih15niYKUvm8aNHjGHgyftP2M9HDrsTjx9v+exPP6EtR+6OC59/9ppPf/YzUpz43b/+19lsttze/HI0/7/ITbs3arP6bk1D6zJUfcAmua8xzrXpg3cgjbVbe/ZWMq+YV4DIsZW1QvNwGDBU0n2j2Br3JggP6uAHn++f8eVvsxqSAz299B688N9LZ87Ta+J2fifvfJ93wIlfAD6c09OMDsDdV4pg1IoXlOKNcJXOVqzlzNa+r+9XsCSxeleF0IFbcwP3Zt1wQu4bptK9kBxYcdGNPxOGimGtgipD3PSEUTeHxhxkD8HHsyo9fbQft1+7dk78Ew3n77qykvoBnCVv92yk9frft4Md7In9+rf7e+V8VZ0J16w6S7S/38GpVUa3Am5fWtA9uHKrDBOsM6LsDEKZhZV34PW6OPNtPZ/n9ERx4/LVkqR9xetoEyGXQi2e3pdbppm5508umAWwxPF4YBgjRqQWX7zX3gjNh5njvPg6M42UIoQwclgap7lwc3d045QobK5GdBi4Oyg5bRFVhhC52CTUAqkYS5lRiVxvNshGuLm55fDmlquvTQiN29dvkGIcdntezUfuPpvYTImXn3zO292RF2/eUAxOx4IU43KYsDHw8vMjb+92HA/lbEViKqQUUCoxCHFQ0EytJwKVMi/kprRSKGUhjImQ3E/Sr7EnOq6+yd5MajQUicoYldpmmkExZ/RK84CtikCA1Nf8NS80KWTcr00qTGEgNAiaOOaKhESIQtDmabcrE7KcGMYJgp9HF380LM9UKSyaaQhBk8vhpRIFSq3EMKApdnai4wtx3LKZNmwGT4VrVdgfD0yjkctMXipSBbFE00YxwwioVGj+DCSJiDaaZSQ4eF37ojhY9eqh1w0SIIWEFf9eKUTPKKsNzYVYu+elufIrRqGJE1mKNeZcCDkTO25RzIibSMBtAoJGAs2JAwiYeqgPlZwXD0MKAQ2BGCIVoQbFHhj7/Pu2P6PU7n6g8+Gm857k/qdhbWqonjskX0YCBM6eTApnimjg3lDxfrBdgQc7T4TB7IyEGj6An8GtB+CTyv3EoX3GiHi6lEPynhQxiKK2Tm5dr6yNpRrZPEVpG2CjkHCNtfYUjggkq0QxahBma6gIA8ImRp5PgStdiOpmh48G4dFojLEQxyM6eGRjmCrh6kB4XtDnhl5X7HGFxwJDn86z0E7AwbA3wGs8pric4PVCe3sNxwkORjsZ0eRs3hxRtBi77B4KSxPmWjlZY8aYzcjmXbeKs7NWoMjle11saA42rdffyyjvILdzidP/fy6GfEJ6YGnIfs589uYt++OBj54/5dn143NH9hfxm87+UazAj++pddSc9Rr/O+7ad5M9Ht6J/+GJ7l76uX4duwe4+n31VZ8wffOnZO0oIkaInk6gRPdh0UDQyBATKcRu1rvQWsaaUaz1xVWhNk+Oq827kc18spm7AW8vrXwsCA7wbtOGMFwQhy06RI/fbG6uWfRIPh4oOfODL3b860+OlCr8xnsbvvvc/ZUIkRgHVEe2S0UuPR7arLIsmaUn/9TWyC2z1EKQyL5Usi5QG0vzyWe7GRGUy+AGhBdj4MmjC957+gwsURbleKw8f/we3/joA/K8cNxMqApvbneMofJ2N7MZAlYLuVTGYWQTlTEZjy6Ur3/0lOfvfUCsM5fDnu0HW6b3BqZyx2G3peRPSO0D2vySXYjkbOR6IJ92UO6wABdXz9l+8D2G6Yo0PiXVynvPP+LRdkMLiWMzxosBa8bz54/YXFyhl0847veUsjBuHhNyJphy2r2kMhAS5JOwtD3S9kxSGeOE2hUmFz4ZLSdqqR2gcNNBegiBSaJRaXlhrs0XNJqoYfQiIgiatsicqXbwyVMiohENEDQSg7HZXiEWWWojM7CfhYvDiWHMJDWGuCVFRap5xHCHRz2BcHbtvShahNAGvHtdUB0hXWMSqWUm6hELjZQmLAhVjZohDsJ4cfGXAng6nU7sDjuuri6wbNRSya37FTXjJA6AnLIveHyOgtq6xCpGxkEZbQJRptElUsTAsngBVEtj3ETKsrDOxFGFYUjUauzv7ojqUu15yQwxsdTMkjOSIrllal5QCWgaKMsRrac+J3cmQQOzSkfAAKUpLG3hVBY2NTNYYBoGxnHDaTn1EHh1mr66F4I1wVhlLiAxdCWJdWAmoEGwHm+tNKR1QkhnbYoo0tznRYKcF8+1ugzN1JkRgyjz3IjB3Leoez5VPP3OHcKhzcWbYhrdM8HWRpTfX9YqVowWA1TIZkRrJNPuhaUoid//5/+Czz/9Kd/+le+T88I4jCSNlBCZrVHKAmsXebxnYBt+LxBgKZkPP/oaz55c8/rNntqEghLUD1dxKVELCaUirXqh31Ps3ENC0RShsyk8PRJiili86AEnB44x0Grh7WHhkxcv+d7XrrgM8L3HwtXF1/lHf/gpZo2xR1yHGDAaagqtsZxOlFJIMTIm96x6/fJTWqvs90d+66/9Jm8+fcXt61dUVT768H2mlLjdnTgsC9OTJ5w+ffnn/Uj+mbfa/Nyv6TiNNaGxs1FsrWa9Ll4DUvwWX8GhezkW0g3v21pz9Wav3P/DWukAQDuX8J5Q3HFGe8hu6V5KcC66Vn+lMyjVAY+VmRVj6Ol71iV2fYnZOjtW12Ph/F3ONX6vn/QMttz7RZ0D/B781/2GHtRe/sMO0HTwqPnYaNqIMRJSopTcAeOKSGZlS6kqKd3LBZecqbX1tN/YJXIFqPeCD3FZLYRuyG006QnQGr0pExJQOGU3P18XkJ4c5+fDzgCjfxVFzt9pZcb1xVQ/N+ayuT6Wvss+c2jAT15PWgOkt4hVwj0QaetvfKG71s9oB40kODjVRZrGPfBHB+7vwcG1rq7nsXP9mYhLadf71QSqle7921O4+5rOVvjpK24ufnh7y/5wImhEQiYzU4shpfsKxkSeYXccmOpAUJfBoY1cKlETpQjVErUZ+6UwDCNpe80pZ27zjnmzznMGQUlXl8ipIHlhjMqgIFpd+VMbSztyvN1xa5knT644vn3F6y9ec7p5gwG3d0cM2GVnLb3d7d32olQ3gxbh1AxtjUmEuQmfvTi511mu5ObAZLN8lrCagTT32qwsnEomaXAgrqqviZqh80LMlTgpc55Z6oxU93YMksAE0RGsOQhSizOScAKEqlLxe9RtgO3MLqzSWBRMA9ECiYZa43hcuLi6Zrsd+xjlcty6yhJD4DA3mE+EGIkoqJGjUaQ5a99AgtBsRoN4Cm4FVMmWGQQPCtNEmhJRIjUL+7kwz5VTy2Q7Mkpy6VxVjEKVudvaCC27dM9llT5uqQia/JiXUphrb7qKEcSN0JtIT++sUJ3Zfjo1JLgPpHbmoIo4I6/74C5LJuvCMI6E1hg1kCzQLHJsQMvUsgCNJNqfaa/XMMdz0pDwVEaIGpzJGqITj8x9CH+Z7c/GeDJ7Z3F/Dz755sOJy9GseYJUCOpouKyvuX//OkX5DaVnMOqhn9Pqp3Q/GSumtZtvezJIAKf6rfsVj052HNTnvIJ3NjNGssYgkKS64viMiLj+ukpfRAOE1IfHRhAINGIQ0lm07P27ESGqujRNGqlVnqWB92LjcTI2SRgTbIdKGmaYFnRYkCHDWOBRxZ4WeFbhkcBGYKPIpFjy7ooFQcTNQ20G9pHTQahvFP3igrp7TCmVusBpidydlLtZOSzCsQq3JbDPwrHBvlWyKU0D2ejyO6GYO+fn2o0M/YQC6gvKfuFXGZ1PeS5lqL2cOANPX+IKrfdKacYnL1/zky9eULrHSNDA9eaiDyoPbpCH28O5Tu7ny//g9oAh9e6bVqHl+h1/8fZub9IP4HyUK+j01Vfq+NZBp0rDxEhDImpELAIBU09vizG5uTcFW9aKxb9ks0KzTKvFTf4647A1Yc4nFO/8qLjfmcbo1HNTNE2M4xVxuCCmAQ1Aq6gcOeSZnAs/+OyG//FHL3ixa3zt8Ya/8rUrHl1uOJVIWIQxBYYYGVOi1YFcKqdj5nSaybUxDImrzSMuxsjrcMthbuRqiBtCUUNle7Hl8TYwxsSpNsYUub7csNlMPH30iJKN6+2ElRmp3sFrEpguLkijkraJ5bjjR198Rgg9XSoEHl9t+eDCuLgUvvOrv8Y3fvU7jHKF7Y5Y+xHH28rAYyRsefZBpE6NXH7My5/8W4YP/jPmekkLmTiNKI1BIdiBWI7YETguWL4lTpek7TMWCUic+CBekm8+5Xp8xBg35Npc4ji/QscrYpqIasR6JKUIHLjcKHI1IlSmQUhxoOqG0gQ7Hfp4o51R0ZDqHi+mzlQsdqLVStkXDx67mGDjtGoJBrbQ6sn9XMYNxIkmyT1xIgwIzQL5WAh1JueZ3eHEhR64mAp1EiROGBCaocFHmrNviG5ArtFhS4yR1gItL1iNDIPClLCYUDKCECSiuiGOI5MKJVVCrgzbiSbvyhC+itt2mxC75rB7S0oT1fUfiCh5gSonrDVKMXKpEAKrMezJBJqb54e7I6UsbIaJ7WZD2AwETZ6MIpV5OVLmGRPYTCOIsNvNzKfMxbRhmiJREpWZQSMaBQ3CkhesZSiNpWXuywuD5oaVTbJrvL1HBhKcqWQ+n5+Whd2cCTGxGYRhCB7jXHxhI9EX72ZQNaMWCBYoVtHaoXURrHcHjUALhrZK7Yvks1GU0xqYS0Nj8ASY5sBLCgHxGDgS6jT/EEAqE5ESlVazF6NWCeYpbUcpNELvCgY6b8Jb/CgNow4uJx70HkZozZCGF28p8Ob1W/4/v/8HfOtbv8px2ZOSL4SDBGKphDT6Yq71dak4H642T9RSGUjpkrRtXF1vuHu7Z+Up+6I+oy0SkjrrG7+GVPc9CyF28+pCY8ak+9bE4Atr80X7dhqoBrL3OmrcJI555t/+6HOG7zzhva3yoZ74z3/r6/zzf/s5UxrJ1f3ykinVlBCEnDPVMs8ePWIYB7YXl+xuGxqLh05U41vf+jp/9Id/zNxTs2pZONzuONzu+Pb3v8fv/u7v/Lk+j/9xmwd4gEvMMAc1aCP+vBSPmTc66+ShgQGcCw1xyQOtcxHU7SfojU/BGXeYEMVN9a3v72FCNXBvMm+Gae0/Vlrzj/ckKP9cFe0MKfOkt+bA8ZrCJ7Iyk3zuQDLSQQ//9u5JhYGY/ntbf2587UBHa/7KMyPIOphrvc6UtRL147EKtXkirxSv01tzX5yhNUJMjMPYQwJcKmMNTNVT3ToY4kl01j1OQpeHhXPjc2Urar9oeamIGbUumLmHl3s7cWYw3X+/e9aSM4DupYPgz1M7A48dwO7F78p8egg+eeCNC47B/XXkDBrGs4yt78FDjoBG6fdDT6wjnI9BxIMbqpV3mGgPSQXnhLtz5U//osbDr9TOzLuGqjMtVwDU69L1On51t8PNAjYiw0DOhWP2NNm2QM5+fy1NqXWi5UCKRiM7QJxGclWCBNJ4SSuF4+mGakpaBkIcCEMmMBOtMWBQKm05MUTjtDu5YbSdKLVhVakS2c8zUhtvX7zl820iL5ndcWY3exBBbYXFKkXd6H5eKhS30DBVToc9pARN/N+WKaVRltrHokCrjWIzwzZ0Bq9L1nIxcnGwcq7L2WTazChmqDQsKLktLi2fDe1BI1hP9lRvcqhGjA21LeRWSIMRU2du+mIcBycblUyLzvAdYgQT0pioLTPGiCT3X5vnE7UcSF2ZlU9KM+0pfpWJgKjLIGcEm0aYb9FaCbohF4jSFVSasACteT25HSfCOLHYgjUjpYRZ5JQXcp6R6nXBZozk5UCrnvkegoNCaRwpeSYvmRCd8eVZXvHeq7k5oBODezAWqwSD1JsUlUJVmFshyUgwoYpSEEZ3DkdwVYfUyEUamIYBS5VycnmjNaHlSkUo1YhaqCadDu9r+5gizYRaFdWR1iq5uX9WAAjuG2m/ZErPLw08nUPHzowUX/lLp0z6XOXxzdYax1Pm5rDn8XbkyeWW1YLbgSIjCt5d64l0Kt0fCUECrN2dNRdunVSktY7FOzxVzx0eR0RXO8BKI/eJRLjvHrilhJ0VCRH3wKhAbq0vcpSAMIhPPBjM/UtOApdmhAZDlyRF8aPNRu9sCFI9hnk/VybtFLpQyTWgS8IK6BCJE1gu1JNRvijYRUUfFxgN08g898G+QbkTll3kuIP5IMz7xGEOzFlYDgmKF/YnhKUKcy3MLZCbuoGyuE721Izc6MVLNxdnvcDeIe89iw44fLm7cT8RrkBTQ99h/dj9y89bxZHeu1z47M0bDstMQ3hxcyTFV3znA2U7jawf/XPbeb1wv+OHL1uZWF/+XEMeTPj3k++9mf39f7/cb/HlgtzPpxguU1nf/IBu/pdkW9Mbp2HtNvrzXCvUbi6qop65jSEhEGqhhnBmPbVmZwmmaECs0NpCWRpNB5baF3mpFzwhImEkDdfE6ZIQJzdApmJSETtx3B/4Fz95xf/zX/6Ez94cud5E/trXt3z7g5EZ5e1pIUvgcrPx4rVHP7fiKRgxJSTBk8trnl1taHnPFy8nfvZiz84qz64fc3mxpeUTmyg8vR6x2njxZsc0KNePJiqBu8Mdn7+64TgvBLwojzGyPxyZxsR2kxgT/OTtGz55dWDOwhiFJ9uRZ9dbnlxEnj9/xPvfeMTF9idUe4Jd/S6hPqPsfkDNC6dFOeQj2yujLRPz1X/FoX2Dkbfo8QvGyydMl88IcfT41+MrYrnBypGcBavP3MdIIcwLE5GhFTh8ypyE0wK7uxuW3RuG64l4/QSGZ2j6grmD9TaOXH3wDcZpRMcL7NSYjyfyKXNoBzTAOG0QTYQO1Jd6ouUMYegTqGJZOO0LwgllRgJYzVjZM8ZMVV/UmghNBYmJtAmwzLSlYsuRfNgjCse5cbQT8wXYoy2EbZdgl5XIClVJaUKG54hcu6eRuEtd4UgII0qlyoxKIYVAlK3L9NIlxta/vyxYKIQ0dluUr3bRi4xoMubDEQ2VuVaWktmXhak3xk/ZwZzajGU+9maB0aLLzFttjKOQ0uDnOh/Q/Z4YlcjA/rRjOWbCNDIm5epiyzQFyuJsmO20IUSvB9K0JWggBhjGgdefv6IUwxgQKUgzQhypJfvCojWkDBA8hcc08dBQuUmltEpdKm3rBdQ4RkKIUKt7QBjQlForqhFqpsTOnrLZG0Ua3cNIFYkVasPX6N3LydrZw8jLJk+9EYnOprLqxptdBlO6iWWIvthfFk+rajRXLvnyjpor0kI3pRBKzQBukqqeaBdjdcBcgV44m3lKWejEwRSUGEf+5R/8W/7e/3JPCh5yMI0TISoaIZkb06YYzqBEWP1S7ERblOV0Yn97y4cffMgnf/KFs/+qj/eTGS14Sl5ghiF5faVexJfqnn7uv+gZTjSw6t4SlUwVYYjKxaNLQnSp5OOnTxiS8smnn3D8w5/xv/jtb/LkSki58Lvff4/P39xAGJAEGiNjcDBsd1j48Po9xqDMx5kYDozDSG6R3d0db199zrfee8pm/G2+2B8oktjd7djf3JE48rOLLxg3V3/uj+SfdeuVc19gu+/OykDxxfwKDj54k/S4eTNal4mtwS++z75y74uMXvDiAq4OEvDAB/W883f/dLXBfZMYM0z9/e8ItTT0arz1ftT629ABJ3BGzoqKrmsEOSfKWa+/RVzC2j/uS9u9P5DICsLw4LXrwkp7C7qPDxrO6gVfuzubU9XlItbMGRDZPZZC6NI0CkEU1sZ1zc5GGVw2vLKq5nl2o13xhDJZu7FCXyjSF5ld/ua64P49zgjcO9tq3n3PzF+//4rcrFqCfr/IugK69+hyUPCejaQoSDsnV60fvIKEq2eeinTGWa925d1j8eO7Z6Sdr448WAt09HsFxGz9EubNcr99m3u7iYMvIcTz2NVau1dIfIW3u30kxcRxzpyWPWbKNG0pBV4vmbkWxrQFjT3sKVCrm+Q/vhwpe2/qjBtvBIkt1FIZ9Rkwchkuub5I3N694c3bG8qpsL2+gGHg9vUNLAub6MyUWgPoSCUSpJIULHcCQYicmvv4DDRKa8y2MJcGNREMQjA0CCX7ny37s2A1kzFaEmfBUqlUwqDdq9UgDDQG5tlY8kIKlSQg0a9orgUJXapejKU2kEQpMMXOflOD2JDRDdstwHYjhJCwqkwjxFCoc/YxKCRUk9uDqKsuZKmE6tK1uTqbWIgcbu4IKpS2eEqeFAKRYgPEgCQllMaIMTTDNFBRllydra2GmocQWCmIZ8+jogzThovNRCuN5bQn18b24ord7Q2iynZ7DVlpIbFfCjFmTBaQQLGItOZMdArWjDgE941rjVK1j7Uuwb8ek1shVE8aTxJpVqgFhuBWRwse1BSskhh8vU/w7yEwDInltGOp1ZsG3Sh+ycXxF9TDGYDtsOW43JKtQK0kUZpmtwhozsoeBoPuy0dSTGAuGWLsGM5/ePulgac1UpWOxPmQ93D8XHF0H3Rfvn7NF2/f0p495mozojGcJXHnxb154aXSJyHtc+KDTg/wQGblN3UinGVZlW5ypl1+19+6mKvWpX9GEiX4waEijAKjRpfOYb7gxo0Xg7qLvpmRO8RguEF3SIGiyoJrTrU5sDHX0h8uJXYd6qEan9RGaoZWnwg0GB1ZA0sgSqWwtIVmEEMgaKFJdhp/7jryZtACpUDpiTzFlGruR7G0ABIQhAyYW4p5V7x1Ja24dHAxP28rXmLWk056MfQOgHSva3vnT+vFjV+fbkwuvSNznlvfnV0NB/fu9nvmZXbwAI+5PywzS6tszpXZg4/7Bdu5g7aiodj5Z/UXvu8eKHrnnrrnHoO9w4H6BZ/Zu4LrDh6AWH95gCcvMobokxVUp4xWR21rceZaAaIoopE0DD4olnI2Am2aEImEHDBOHrWqhSQ9ncqMXCMtDJ6qFUYkTmgYEB1wqpOftFoLd3d3/MufvOS//Vc/49XNjq9dJ77/0SW/9uEFKQ283mduj9kTYzqbUczN7YIJ22HCQkA0cv34EZvrDXZQtrcHxk3h2eUF3/vwGZsRWruimTCXI3eHIxqU/WlmN+9oEim18epu7wa9S2I097ISM5aS+fjlLcfdHV+8estxqagZ21T54Eniekhsts/YPH5KObzk1Zsfs/BNLp9ckNIbyvKay+ePSadb6meFn/3xnuNpQ0kC+cfk0BiHkeHiKePFMxIKYaK1iVr3WNzjD27EWnEJ3OktNt9h+RWVC043t8xloRRnX5T5Dj2NWLyipUvorKGYGnG6Qjbvw/AE0hGtn5DnW+9QVvNurWSCNEIStDWMSpTAEAe0zrCVXsSfqMcdpjPUTCszPgWaGzs314C3LofSNqPHW1JzOZblDCreTZmVdjRk8OFSiLTi/FdVRWMiDFcg3ZC+3fUI35GYhKix3+0F4oYqV4RYMUZaDb6AlkgaAzEO5PKX4AFOkdEGVK54c3vrRYR5E2Uui6fDWPO44t5xhN5ZrwNBRtgIz59f8Ozykjd3e+5uDy6BGhIQuNZrlpDR6PNxFAgKJCWGSGviHczjiViNoBDiQAPe7u8o1VkbKgNVZ6QUaBWT5vNdK4gMQHBPFq2IRYSIFe+JN3O/jBwSgYFNSMyxdm+I6gXP6g0loM3cXLO695FZcTZGqEhrRE0+xFdDQkOaG9mKBSw2lMhSKtIW0nTRWdI9d0yELD5h5lpI0cvwVjO5lu5o4MyyXDNpSCxz6Uaq2Sue5l3xlCoEcwmQr+gptTizNCgaIjo49X47bPj4Rx/zwx/+kO985zsY5sCXRoa4IVI5ZR+TrAoWQx9NXUu4sLC9uuB0uuX5B19jab8PQQjiMsWmio7Bj08MK43SPZdEI+RGK76cT61iKgxhICmUzkQxFTIDoTUuH11RamPYbJhS4NmHH/H205/x9//lp/znv/M1nlwGPrwu/M3vPeWf/ekN+wI1Z9Jmw1wdgLmZd7STMU4j108f0wxuv3hJa42Xr3a8+PwFu/2J66fPeLy54snTJ4SysLu9I42B3/grv/Hn/ED+x2zuj6fRFxra0439IWvn+kJXFkmvuc923Pc0JIB3WChwD2xZ/9+a9LaylFZ8vUNVwMpU6u9fH61uumrmiy6X0D2of+5bkw/+s1b39Qw2SAdDPEegg22ysm26ibasR7OOV5wlbX5MXZ73EJSRB2XieangwMz5vBhdvgKiqbMuFWuNmisl1+7j4s+i0ZDF5YHSm5U1O9/dGRlujrzMmZgiy5IJQRnG2NcLa5vy3iT9oU/Wu2ynBx5cdv99HwJt/p71ajowpOdFUv+dWQeS/O9B1JlZyBkkWoHH+3P5oI7vNbgfg3aZ5Wr03u+NdV8PfnZ/TVbQbAWgwoOa3I+9dYKCpxu654wIzqgI3iBw+4aHx/bV3HZLpB0KTQqm0QHhxdheXRHmO7bDQAlAPWImnIpCw+VUy47NNvHi5Rvm48LN/o5iMyEIr9QIOrDb7Tke77g77JlzprbA3dFNuskFbYU8G0UiWSGoMahzWZdaOdydaMWcVRkip/nITHAGTQjU3GjlSIvO4JuXwnYcXZqfBsSUVmZMIU4DoTSkzIhVjjkjzUGSbnBI6hKwIB6QZaW5n+R8hKiIJqYQacDeKktUJAVSUharaFTmCosMIJW0ScQxcNjtWY4z2SoqSiMgTQm1kfOBqo1cMqGCSmVWD+7CBK3OanL/8YUYFVqikGgkKEJeZmKKiLjNQ4lQ2okxRGrz12sQr12sj2XmJuoX24iR2WfXd0X11N0SHdi5Co3vfetDPvviU754c0u6vGSaRm4Pe5p2S5icHYw3T7Yzi6iZs6urs5KlebBOLY5lDCEg1ceCpVRyzii4bD0IQSqSMoOMtFxcWhgCx8NCFGOK/kwKXmfIssNypmkADZTsx1Kt0VpmHJzFnU8Nirn/lixgngBYmzehmiYoSlsK+5vDL/Uc/dLAU20ONijrJGXnqeeMpXeQJzdYlsJpyRzmTK4wBiPKitF349Ne9KwjcxOXsz3MPxM8ltRf0ieV/msvEAXE2Ua5F+FGZx6Jh3cGW72dxDXf4gW1dkTeCWu+r4JRaqYW+qTfAbV+CPsCcy1rBkmHrVbDPF8YhebdiTW8GRFP+2ni7BLxbqsQeufUaWwmSiQSe9cLcUNIcc6tI8rdTSmYUs1j6IdewBw7Ehxa76IC1fxhEFWKOSDn3IA+LTT/Fo11YnwoS3vnX/eb3E+s/t5uKSbvdkl+EfBkwN1uR2mGt4s9IeQ0L5RS71/3Cz52JV7ZPbZ1LkJW0OgB7vXuIT84hnfe987x/cJvewbizt/N7l/5MBr4K7/1WkBUiUkIUcHUjX0LWF5BRCjii5QQlQEHe6yDERbTWVgZxbuNjYIUcf8K1EFISX6PS8Ik4rC6o/Bi0Iobkb9+e8s/+9Gn/N/+4Me8vr3hr32Q+K0PH3N5vSWMgd3i9+7VGLlURUpzmn5tHvMq4h4ow8R4sWV7fc2wGZlL41hfcPXokl/98EOmIXG37IlANKXkwOFU2e933J0OHEvm8mLL48sNz68ueXtTaL2IOxyOvN0deLV/wZu7OyKBYMbVFHg8Np5964r/2W9f8Z1fq7Sc2Dz9gLS8Yvf2Cafx21jcI/NPKTPEOJFCpdklmV+nhMjy4g+hZXj/b7B9/B6bZAwBP2ftFos7ml1g6X2QW6zMqAm1QF5OkBdseEQbLpjvXnDcvaLoQK2Z0/4ThrvPiBcf9Wen0sriRs6ADO7NJzgjpFp1/bYqtVXEZhQHD9IwIFRUKmKVOEZibJRcmecjx72bFYqCxoEwTL0Z4Q2JdnxLnk+I9IlWdlyEBVJFyWwnYRoCYxjQAnbKSFKELcLo91RUCJ5GYqucqk5AwWRBQyPpJYZ7TlWdaJ1NoH18d+AJpNn9g/EVf45//OM/YRq2tFaJakxpcHCQ6r481cdiVUWqQlTiENiME9P0mCFs0EF49niiLgcUYzNEtttLri42pCFRj5WlnJjzibnObsxuobMFDImBOAh3i/tpucw0sFQ4HTMpuv/P4W6GqJ0RaW5c3fy5tVr6WODUc1mbAOpzRrOGtgIl/3+p+/NfSbIsvxP7nLuYmbu/NZaMXKuy1l7YXHo0Q4IDAQKo3wVBI4wgSH/fQBCknyQMIHGAkUAOJZFDtcjmdHV1V9eea2REvM3dzewuRz+ca+4ekVns7GZPMduAqnzxnrttbn7vud/zXSBEuhDx04TgKTmb/KMTqhRcBueVmi2xynyeqvULxVGyGGtDFReN1VCKsQC8F2MmOJMmFXXEWsE7Uq10fUS1ElSZMuBNclCLkmmAj1bEFagmT65UYlwi7jlIkfCK5rawq5DJ+GKMry4IUjGGRRGQQHWJu/sH/uhf/2vef+8DHHvS3ON9h+hicFvxwbfZ3B8aR2ALZS8WO/+dDz9kteq5nxLOCUUtiMGY2qDqjSqvjdklgvhArXsCoUVZWzy4+V6BI5gU10UiQj8EJHacP3rMRd/z6sUL+q7no48+4p/+97/if/4Pv8N1V/jdd3vuxoH/4eOtdZiLcNGtWPWBXUrkqfLofMX9zS1K5Oz8mlQmfAg8fed3eHTe8ed/8ReItRx5eX8DKrz64jk/+aP//rf9lfwrbwI475qMURFd4m/qoREHVnMsUigDe4w54r1D1ZvdwgGosfeIWgd8AQFo713iy1nAG6F5Qp02GNv5iUlZqqqxH1phaAASWMty0Tw4VBrYgBzYTkewZLliO0erFMw5CA5OUAcAxl7H4d/HGlBZpHuLB9Sy52WusRp9SXhsNXsLATp4CbGAs77VcCZTNiyvtCaGrT8WMwXzuDTmV13GL4R5tgaKLRGWBZ2BN+3DOHhlLcdf2E5y8LZbzvsrAERVjsDb4l/qXgPjFlDr9Xr4ACci6JHJ20DA42Ga7E1oQJl9ju2lb5xPM6Y/SOs4vredu4FVNn4s1yzOsXDlhIDgj68Xi4mnNgba8lnyzd5kfUbZjlZ31AkXHLt5ZFU3BArzdkeNlf1+S5oLgd5CafYP3G87uthz8+KelTfjbz94sng+fnGDlkTeT6ScSDqTRAlhDeKbP72agbnzhH5Fnmervd3MPFmyW/WQU4IZ0JnkknkUBvPmUVFqsLXhnBSvET9VPNlIFcWe4UAmakab119VhdQATqnWwPEm7abJSJ0P1DQDQugG8wKKAcQTRVnVSt/3+IVBX9VSacXwhRAdKe/opUfHPWk7UouxgiSuLE3XCzkVVBxeepwD5wuSd9CcIBMefE/RgidDUbQ6cpP152nGCwzBI9WsI1IBRMg1UasQgqO0ZDl1jqGPdB5ElLvbe3uqu4GApbul0SRrY0l8cfOctLtj3o0MvsM5T+w6Xu3uyFS8itW+3qEecrZU2ZIU3wUDcvNswviUEZQg5iGmQPQ2dwuBUjKVwpxnCIFYM1WLgUs4SBWvi4Ta0YkauaDNBcGZjFi9oKWY11c30LpQIIHQgOcy7yma0OCYWv2MBkRtPRl9oMxfj7X4tYGnl7cPDEPHZjUQfJtMlj8qLNWjRxmzdV1LVW4ftjxsH+jjpUnTOMBHLL5NqlYwi9SD7ntB4QWLGZYDtXiRdql1UZz9XKoc/mavsglUxSRVCUuqqE3al+qRsVVEyXIgLJuWUUGy9ZmcQHDOzLqrMrGMuI35w6JTbh2cauactXVYjoO5Hq7PhnBngJM6+yhOig0rAAqOAqXg1DE4z8pFOoV1sNjqSsEVxyyOXIxtsvaBmUoq1ZJ1QgAszjVjTK2TkuMAnB0klCcfaz359+lPjqPe/KDvPnUA500pm/1QgFTMaO/kw6JUKCrteF/mHenJfk7BoaWsUI7FzvG1J9DXwaT+jf0sbZs3962v36HTn+vJfr/pHZrXtgb2OueJfW/pRggle7QN2B6jlzpvg28QxWlg8hFXqgFWLpA1mbeTgJCpdUTEE1zEOzMBrxJxvrPnvCrROaL3JnMqiTRPfP7FDf/8J7/i//Onf8Ht7R1/8FbPf/7hIz54dMVtVm7nmYRwsbngvG9x3Fqp1eLVve+IPtB1A3234uzskrOzC/qh5yErq7NzLoPHRcdHL19w+/DA9XrDxWpF8D0ex3Z8IOXE0PWs+kj0wlwzdw9bPGuG0NKemOliZV8SeU68e3XGxUp470nkh7//+/zgD97j0VNB7xx9yAzhwkDn7S2u7CFEJMPtZw+cPR6I60gfN5RxhUvPmO8+J4wfs97+kvVqRuIfkuO30PHn1LsfMd9t4PIfgAeXRsI0I3FAgkeJsD6jyEC+/cxMxH1ENZHvn5PV487uCX1H8ZCTt7Gwzgz6kjDO1HnPtN9SSybVputOswFPruJ8wPcb63ChdJ2n2ziEjDhjOM11T05KXK2Jw4a+H3DOkxKk/d66LLvn4DxdXOG7gh9goBI8rNeBs/OB9WpD8L7VEhFLRusQ73Ah4MMK8cacqSVQGBBVss5UWbwu2rigJhtVOrJmM9utlVInNOWDVPObvn347gekqjgXuL9/gU6TmW+KEvBIVCRFut58StbrM/o+0ndr3nn3u9w9vEJWPeVhy247U4oyrAaeXJ+jzuE9RNexCR1p7plSYpwmRL0RIGoheodXoY8ds07kUhnEkafZCpqSTd4eBM0JkYy2BYftZGE6LvOFJUvRTG5VEzknUp7xHvoYGYbIKvdMKUOwRbWBRx6corUgzkBIEYd6ZSpKcA6V2phbnpSTYUDBPBNRm9fzIuPXwlwSIhER8zvwTf7hnSIUm1PV6hG8WpPHBUqqdNG8FcQbCEBtPlHB6POuWkFYcqVEW5gG71ozzx+S8nwMSBBCKvy7P/r/8Y/+4T/iydMnxLBnvfE474jDgOssuAEBp7UtMh0+dui4xbtISpXYeYZ1x91saULeqTHNMvhg1xqCEF0bE4BCR3QF5krojD29BKoMXeTi7Jz1ZuD68RMeX1/z9L2nvPX0qS2SysQf/9Ef8z/88Y955/0P+PyTX/HP/u2v+Effv+b988gfvLvhZjfz8+cT2auZ1RaTWAYRbm63dFPk7GzFw8MLdlPm6dXEpjvn9maL957PP/mYD95/j9/54Q/55JPPTeLUfbONiQFbZDtj+JsTvjSTfBqLv9Wx2ny/DgCASVL10C08VR3YgnBhOS2gwAGEcNYQlarGPASWyu4AGDSg1ImCbwlk7XjaalsUAycoTbVgsr8mzDoBhBbZVQA5YdPX2oBY2iJ4uSntfbJc0cLUWYZld3jd4hclh2MaE8cAqaUx2ACaU2qUartZy+/rIUkbqQfmDyf3x+5dU84iSG2SRbUULrNYEMQtFbQcDnVobMpSYZ/KJysL4LRMOwf52ykAyAmws9TY7Q6/zgarDViyz0ya0bd5PNlZucP9bSfYJJWngk1pSZ9KpVaHkwXUrnbfD0Cnvd5jz9XRpqMBpLiT5wUzydbFI0ygOgMFqwKZQzLj8r5v8HZ1MfB8vGXabnFacDFwv92ZX9NuZNztSVK42Y6oegaZjbThHGmbEDL9+SVIQNNEzpnpYcekav44tZK1oF4gBKoIxdk9ywSIShe9La4mpbrK3hX7nKqFvZS5oiVSKtakk2req14BT1YDerzXZlnRnoI6A+HgyVryZPO5Vks5C8aW8Z0wp6m1nj3RGXlDQ6AS8N43C5s23wfzihWdkbxDpSOrgJpkvdAbA7EWxjLj145aKlpmVAvig6W/+Wr3IoIUEDXpeCkKYkCeqsXP1Opw3lnaZM6U7EihsyAF7+hCZ0CfVqrzxvoBOjxRPPNcCb6jj0qI9ninqX2WvoO+4+rqkt3LF6Q8UdRAcacz2Ude7hIyVXyn9F1EnZIzJIFKISjMAloDqp5ao82DFaC00CyzDBBv51yxdDtVAwKLqskIq2EJU8qIcaaIrhKIqArVm3ev1szu4Z5hc0ZJM7REXsGh80Qvhbl5hPZdz4AjJ8wrO8/gIIs1IU1GacSFrJVQKpWZLv4NA0/PX75iPfSEt57gXTyhgi60zGXsqWx3O7a7EVVhTspunHlUihW2mOTMOtU2XBdswPWyeDcJuSoP88Q4z1Z8xkDvLV5RZfHz0QNjx+AKMer9AbSy/Wfk4Iw/FWNQGbn/dJozuqf5UNl7Gt+IKPZzVetQVQltf7bPwwSiZvCo4qjaaOx6LAQW8/Rl/lBRaptUjXBdyVqtOys2gDuKxT1Wx97BLJmIGfOdScFRmZ1jX01HG1SQKGRRpqoklUPnMysUcSa/W05FjoDNAh6ekqmPIbvL318Hd/TkepbPYfmpnsysC0W7ABJiK5TaxCdCKspuSuRaG2vm9bXg6bT7JVBKj7/X187i9Pr0y299Y7H5+jGOvzswudvlNJi0/f2rWVLfzK0VDj4S4oDH22JdHKquJRNIS7YzK1zBJqlUzXOl85EQgqVDlZmiUETwIvgQWhfCIT4SfY/iTZ/srJR1jUJ6v93z01+/4F/8+a/54199REh3/M7jwB+8e8Hj6zPisMLvE0mFuFrx9PE1mxB42I3MKaFUhnXH2bpHqpCrgDdz/9I6by5GLq6ukZK4ubtlmrYMQdGaeHFf2HRr+tjT9x2TVmLsQYVS4exsw/c+PGfaJcTvmOeeZ2/1fNhdsTlPfPGqcDGsWcVL3rt+h+/9zne5fvpDQrfHr18Q/Q4fH7MOl/gzxYVC3ieSz/gcCC4wDMLu9gbyTFit8DWx6T9nPZzh1m9R+kfU6qjTDdOrz9jdZKJ/TFg9hZRRt4XQ4WMEVyB2ljYXYfYTU9oyz5OB4M4haaLGgFYh+xVaC9M4Mu0/sc5UKxt9Sy2hZsTNeHYEJ8Sux8UzYzrViUgiSMH5THCKy4kSIRMIIdDHjr7zLQXFkX3GScWxRaojqENCYDjrqb1FfK83PeuzM/rVyhI7o7HkigIS8M4StsyrzxI5aulJpaOoozCTNJPTCGUH+QbB4cMlQrDOndozUPNMrjM5TxziWL/BW5oncin44JmnmeACVxePuHryroUBREfKjlonNsPAs6fXFK188fyW0CtdqqQ0kvcPzNPE0HU8ur6gi5GCmNH0ZIyfIhMShd6tyEWAghRjKVIsgCDPghZM8lqMkl4qaM2IVNRZyMiyCNRq4/HiJ+uco+Y2CyzyLTXp/D5l+iGAtGcXrIPqvDUqLKjL5L+tmLQReQGk7Jgm0wQtdnwRMfCyzYmqlc4HihZw3lJZBLwzgKZUW0CHIJQ6WZe3VOa2qEOUWgTngs3dh7lBEPXNG0XRDOocIVgxXCiMdWJVe1QtPVSdN/aWVpyz7+EXz1/w81/+gmfvvsPu4R4fvfmbVSX4cMTwLOLXZNBtHE854aKn6zu6PtD51sXEZJPOmbzS2F9Gt/eYLUGKHZ0L1N0WHMSu5+r6mmfvvM3jJ0959913efbWY9555xmb1RoXHNv9yKefP+fTjz7j808/IaeRGBxPnz1je/eCH300sn7P89bjNb/7QeXl9iV0HrSSSuGs70klk0vG+Y7VENAaGcfEdjfhu8DuQXj+6XMkCK9e3BC8J6XMuuu53W5/69/Jv872mmTsgCUcay5OemGLF8/hNdqkS63oF1UDSxbwRJeGrjbmUKtTWrKdNFZcw6IauLW8g8P7zAjSngttnfZFTaDqD/s1g+gFGJEDo0oW4+oG8hiQtrBs3Gt12OvysoXVo80PikMtL+5NAGZ502JwbQxeA3HshO07ajOb3Y9W8Z+WgwfKlZ4wqJbjYoC2GmjiDj5ES9P5FIxZQMNjpPiRbXXEvF6XotXXnolTltPr71lefwT4Dkc4CcYw7E5MWrXcV9d8m07q3WOa3ulCcal2dcE/7VqkNMBxOW89XJfJJo8OVLYtLCd7nVRv8rrGxrP9LpBYuwvVmg6vn883b5uef8r+9gW7ccY7h5ts3Lx92LHd7kk5UQSmFPDOkb2CBx+h79qXzgl340RNGZcTohVcMUa42BptHie63oMoPioxWopZmpXtdmQYBmoz7s/VpFGOQikJxRnbxzs8xTyXS8ZhvkBead+lhNJsMxADE5wzO5e0fLc9pSaGoUNcIRWleohhhSuO6CLkZCEUAqEzDyOKIs48EKd9RvOMSKXUjDLixGRuDvMGFLU1RKmF0inDKpKnxqZqzZUggaTpuJ9i86vhWyaXdyKEmokl4dQ1YFZwQcEV5lpYryMlG5sqp4oGd2hW9tLRSY+TRIyR4DM5j4xzsfoBpR8i4jNnvWdXizVW59QY3RbiULQSg7VwBKuLcjG2q2CWPM71lKx0zoIgxDlUMiXbNTrxZpegDleqpdph2EQW80isqdD1nQUazArJg2bEjfheqbE31RWB2kItaq4wFZPuOWGWaqm/IcA0k9OMU5glEHyPk0AOgvhKHwU0E4qzECEBrYWUJ6jQD5uv9T362sDTfjaU7WqaWXXRCkkBxEotVzkM3gUO/hLOBe52M5+/uuP9R1eE4A7DFhiFe9lXVQNytQp3+5FfffGcm92eoYs8Olvz7uNrVsGTFuYGNmi5BpjUtiAxA3NZ+gzmAdFAJBOqWWHpxOR20phKBio5ltQPESPnehTXKLsqlpFUaltEy2LU1zo7rSA9FAzLRK+N6FuPQIWKUQadmhmiARrV+q8NhFMNB4CuNujGUanmDk4Q4eVceSjm99Q5x7469lSSOnIVK6rVvgJVX2cxLeduk8FJQcRSZNjPcqhMDohjA6ka+HJC87e/OzPFP/wbcq3s0sxccuvciRVKCnPKfPHyhuvNis265ziJL0c4qdFYukBHkGw5hrKATa+DYm8wmf/S7RQjPF2OLs/p3yqmU9uWW+B8wMeueaUdQU5vo7wVEdU01KkqD1NhO2VblAV3qMxKhSlDqg5xHSJqAFCudM4hEqmlMKeZrvkD1TTx/O6eP/rJZ/w/fvRrPn51x3ubwvcfDzxeR67P11TpSerwsefq6pKr6wseX5xR8ozOiVoroQ+cnw90zjFNM+P93hYtMzA6pjIgCM/eeps87Qg60bsZJfPqbmbSgafPnjDUxLdXa3bjljzt6XuHOOiHNY+uL9neveLlyzte3X/Gt75zxvvv3PH+B8JPftLzyYvKo2ff4rx/zPmjtxDXoXGNf3xGKBnRHnE9YX1B6F7it6/oaibGJ2YomG+Ir74g1koYAv3Zewzn38Kfv8u8eUyRNewfqOkC5B361YQrt8S0RmSAah0km7BoE99I9MLq4gzZPqB5D+tH1HiBSCBXcOqQGMl1JI33kGdKF/AhEnyHhKEVqjNe94Swx3sIfo3zDi8RnxKUCVImxIyLwSKFV445BAidsTfVGKshiC2aV2vWdU3NxdLuOk+/7lEC0Xm62NEPQwO5BsR39n2uE84pMYL4Nso3s+y5KtMcmAtICCb1nhx13BNCJUqk9BZwITUZ6FRmSkktbpYGPH2zt7vtlpIK63XPatjgu4Hv/f7f5f0f/l0TwIhSsiOUkQ/fe8K4fYWK8pOffMKP//jfoNPOpDjtGbm8OOPRk0d48Wx3O3bTnryd2M07ajBpRcQzZ2MTRG/BE2WaiKvIpu9woeNss2bOxr5VtY6emesKxoEu0CQq0iZWs3Esje3b8melw6miOTFVR1KlUz0wMP2BlQG0Aq5kGoBic1jVYyqYqpln1lKO0ezq0CKW8lWbIbGz+b4oZuDpjf21GOLTxsegrWmjjfcaWk2RW7KYVmpWXACnHqTipRoYB0gnzZA/IN4TnO2/CAiZDjNvpTUCQugp+8If/5t/w+/8zg/ouh4/TmxcBLVGXUWpJZsHj5jErzQ2qHOO0HfEruPy+pIvvrjHhY7S6qMgkeqtSqrVzq0LkeAs1W99cc6T8+9y9fiSZ8+e8uztd3nrnbe5urikX3WWhqbmFycKMUTW0fPxT3/Kz37xK2qqhNgTQ+Ty+hnjPPPnz+/4vU75/rMVn70ceJ6jdcsxefdmszaPCyrjlJiTst3v2c+ZVzefo9UbE9d7A+sodH2g7yO1zL/17+RffdMTwMmSZJc0saq1GXX7Q31zrEDUFg7iGpvlWBEeSpEW1rMstpaCSNEFR2qyqEOPEeek+UnB0lQ8gg667Lb9rQEJJ+DLYooNnDB2FrBpOS/7lSyAVHtuj4DVcTOg5VSK1vYjC9BxskOOlaFzQilH0GaBNA4sHcfRBH0BjPSU+d+AcD1CKMtY1b69X6ohnXOHpjs0rFuaXy3LdRxr1TaUHO/X4X4un+Hpz8f7d7zmL2/OOY6G37J8yCzSSjuv5qF0uGcn56BvfIYnBfPSHD5+Gsu16gHYWwC9w6elSytd2z6MTd+ethMQzXGEnVqNr43B9g3ePv7Fx9TegXpKtgbCXDNzLuafVCo+huZ9ZAx/CQKhMZkE0n5HTjTFgUOcUpkpZULCQFYIqzWI4AvoNJNLpZTEXGbmkihFmHXCF9++qwuM2UgdDtTVJvlWQuyotZJVUB8s0AfoOzEbhGoqH6cmAY7B4TFG8Rwcuwqdj0RfycxtlepIKeOrGZVryZSayXlGC60hGikp4YrJ9MVFpKpRKmoDlILVAkVAnXmsrofIGAPTDEUj4iMpZRvHAiQSuET0Ea+BnDIAQkVrwXsliyW1OQeRyuCBIGidGlNam9uLxxVTeoQYGfqeaaqgM3NO7KfcFFJmF2RNrMzL5y+JYWCc5lbnLg1RUwR4qSZ4mwupFFbOk8Xm5iAwuI6xmlVILQUfCqGvVGcem50LyKyMqZqyy2nz7gRtqZBVIzWbAbh6+yI6teZsRklzarVERHC4zhhKhAjqoBRKnVFXUFmhIRKKeULNWinOoUHwRHCKk9ysFSq0YChjUNu17+avNwd/fY+nUihuIV7akO5OjKcXdL1Ui3LWBvbkUnl1v2O32xGc573Hj4iY71IVKO2/qi31rFHItjXzYrfjbjdyLY5SYC6Fzplptw+enmYAqtLgpNemKxbNMgqGrRoQ5JzSCwdjcdwCpjQJn1Y6ALGHVhbWknNUNYNss+1tE7vSwCErJOWgFQcaPbfSKJMnUInR+2m2gXIwTOcANMEy7Gsz0ZUaAdiKQq5Ep9yoFW2NgIXUYtTNahN7afdgMf82wNCdTBi6zK1t4XA4wcOmh3P7ir/xZsdj+e3rQNZ+Tnz02XNu7h5QXZgV2gqjyn6/Z54Tq1V/pAV/xYR7CgYd2E2Hguf0fb9pMfn6PuvJ6w4+UidFyyn993Sq/Nu52fPonSPQFoCuttS5zFQcc6qoJkat7FLidp+ppXLWR2aFmk0qOc6VfVacBIZ+g2hlu89MU+ZMAhvvKGXmYbcHEvux8usH5V/+5BN++tOPuB8zP3h3zX/6wRmbaDHQm7NLNusLYojEGHj34pphbZPwfp45l8BZLfQkuk6oubDLI7fzjqkUVjJRnaJuw/X5GednG4iQxjUfPdzQUZmAq2fPePz+uzzc7+jPnvKOT8zbV4RY2E93Bl67ifWZcH9XCUxcPVpT6mfs7jvOh/fYrx3D6pLh7EPED9SHlxQR3OMn+F3FhUt0dQ3+nFk7wnCNdJf4/gkwobc/I7rMxbrDr67o+hWsnlqa4Jzw6TN03AEbuvPv05+D1kTwHo1nZOdAM1STAJMqQSrSnREvf5caX1DlM7y7IPlzap2p82gL0+mBMm2pecJi7SMuROsgOctCo0yQ73BhR/CBLiR8mPF01qXLGV8yvqh1r1ykX3e4WahEvLPx1ZPpvMDgCNeP2LqReXdHFzr6wdP3jldjInQD56uNpc/5FfieulD8pTCXiV9//kCIwqPrFZtQybky5sB2EmOzzlBqYR4TdUwEl6j+lhAiIawtmj03OVcp1CrUrGg4jNjf2K3vBlxsC1UfePLed3jnh38H7eLBryt2wtXqEX/n7/wev/r1xwxDx9tvfxcvlR//6z/Ch8I2eWIwQGL7sGO/33G33TPu93TimJkpSagZS3VUk+DMzoh1D/vMkGbOho5updQaWyfTUSnWParAiQzGQCfBxWDPK5b45rxQa2NbUlH1VmSJMBdlVcxXbN33zKWQFn/F1mkTwDVAzIl5KBlNvcliqoFD2TWZzyHCvLY5UKx49q4VcwBWlOZW8ImvRBFyNqcjdSand86WVMbiVAiBpCbts+5WY/1Wu05xAZxrXo4Q2yLcE03ihHnoiYecC14MjP2LP/1zfvoXP+VbH34XlTucj3QhmG+kAxVvzTcRWwyDGb06kyDPIfDOO+/xsz//BAmOgFrh5wrOB4MHvWez3vDOO2/xnW9/i3ffe8ajt55xtrlkWHWs12fEGA2o0MXfxbUgD2OLBe+5+eIzfvTv/pTtwx4RZRBjS7nqkGHNy7Hw55/d8ve+2/MH377mTz7z/OrFLSImO5xzZjslvHN03YAPgWFY452jTHugo2oh+I7twx1x6Cgl89lnn5K+ZtH7H3drrIelVjkkiJk8agFFlpHoNKZexOrPA3Bir2ig0RHVMJeGI+hkcvjjon8Z6WqrXRd24GkVd1Q0YM1UkQPodMowPx0yTwjuVkcuVhOI+bq1MUDE4bQu1XfzSSoHQOvYAF0ACtp7F5DlWAEuVdqSrGZj1XFZY7VaPYBpx99Zbb8AUMd7rAdQbrm/Tk9kgQ1sM6eqivPGCjnw92XxPmkAixnMAY2iuXhVgc2hQpOdLQD38tm2szx8DoYsnCYU2uvKyWd2Up06O7bdb2/2B6iB7S1ZcPFfep1ttRihLJJGt6B2nN4YOVzx8m+HasEdACVrocthfw2Va+wsxTU27LIDu75Sv9nA0yQenTP7NDVgUci1kGsmxAEtnlIaW6jpalSFki0NrnpH1wkiZhqttaK5ULXixXx2BJvDcikIkZLNJmUvhSqVrDN5P6MVhgBBlFwmUqmgnjor0UdCjKQ6oZIRgqXIO8EHCDGi2cC+6iujzEipBGeM5FJzY80ayDTmRMETpDU4ipJLoeZK50BKbexgtYGlGBBUKYRoLK8KzGrfnCiuqZbseHNN1FIJrme/3+Fdjx82lJQo1SF1xmlGNOJrh/OJImYdU7PVHl0De0pNaN+R2v59A85RAwPnVAjeqhXvhUKm9x3DEEEL++mekmdyTeSqTGrPakTI4tjPmeA9+4cJUYdXLKFbFHJpwV0G6OdSuL9/ACoeqzdTETKOuaXC1zI1tlqlZCUVRbMg0bd3FbRgtYxvKq9SCVgKXqmB4kAieG/JchljZdcq9M7hccR+QKQwzjtr9Yn5RVYcSSGKNZKkVLTOqOuZ04iixGjqGO+txsIlSp5w3mS4TsRkj5Sv/uK8sX39VDtaZ0yNrtb714v0ZfDX6ppszAa8qpWUK6qOXz5/yebsjMe9UfsypnMsS8dAXUtrUyZVsvMktaJtO868mEeqrPjkizuGs54nmzMGXGO4WEGkYmPYgrovDkYiFlBo2kelw5lfjNgQKmo63KoWtKBiaOgETI3uNoh1RBKZ7KxPa7rvpWNwCoIccHwbdAUWHf1xWrPfmxnYgm+82VlZaKsGgIna/pLAbRWat1lbnMGolr63+DgdlfzWjUDAqRw6YCrH1xzPfznLE8+s5RL4srjMPvsvL9xE6wHEqsBc4WEsPOxnoEV4Fm1aeyV4MePNlq7xGtwjp/4EJ/fv2F95/YSW4q39X9XjBLjc3wPgpMdP5XCEA5B1IpHEqOOu7beqHowR/3ZsJ4WiCirVDAsVainGSKvK3d7SoVKeeJj35CKsY4cCUymkmimlsM+FUiv94Fl1kZIrebtnypV1FVwufPpqy7/82XN+eVfYJ3j1aoume55F4f1nZ/xPfvctfv+9pxbUI44+2qIqS0fXDVxenIMLTHMmhMD11QapM3m8ZZ7vyPPINO+Z0sTtfubVtOcyw3efXjFIII0T827kFy9nRnfO4yvPeYXV5ozt7o7buy37Pfzgw3cZvJDKK54+e0yplXksjPPA7/2D73Dz6Se8/PiG9LCilgtWF1d864MV43aHcxtivcGPP0WkEIYPkP01ujlH3CU+j8j0Csl7wtmmGbhHSn1MtwAdD+sAAH0uSURBVMrEQWDzFPGBUCb87V9Qtz9DS8H1z/DdE7pwifqAc6sGHA9IhVQmckoWrQuoJNT1hPU16s/JdQ1lRouSc8aJkupMzbMl9YQeHxxxfcawWtOJNK+ABCUTZKILmT46+lDxoUXE1wxiiX6SA2iPkxVdP+CcRdZDAk3UrHgfGYaB0J3x+asNu7TnvfMIHrqV0okgodKde7wOOOmo4nEutPSbQNEdn97e8Ovntzx9dM53n51zvdmwnTLbUZmmyZ7nMqJpQksieqU83JHGwvXlUzQYozVXm7BrMYDBD6dw9jdzG7pI7DfmGUDh+vEZZbxl3mVEKyKFWuDR4x/y1tOnhPU1m6Fj7ZXvf/s9/rtvvc9Hv/yEf/dv/zWfP3zG7pPPKLVQSyW2blxVb7TwmkDEZJoYuyarNr8WWyjlXNEpsd8nnj56xO/8AH78Z79gnmZwxi22dW1AqzM5XAyQ22JOHV2IpLk1jpZOfZN8lVopWugE+hhMzot9Sq5iqULR6PgOA8UWy2VjaYgxpbxDE0YuEUfVgluikb0/MG6iMyYNzuBSbb4NUis+BJIL1JraGizipTb6fcH3VrTFzmjxc6i4GlCFKJWu+Q95NUmDE9cWFoWgmeDNqFmLImkyz8rO4Vzk5cs7/vRP/owPf/B75JSZp8QqdohrjNV4bMA58eRSyGrgcYyR0K/47nc/5I/+9b9jrqBVqS05+Or6nA8//JDvfe/7fPitD3j65JrN5oyu6wldh3fmFVObx6a4Ju9a9oEgzrysZM78+Mc/4vMXt9Zdd4rLGXB0MRqw2PV8dO+4/mLkw2dnvD0KP/9kT81KXDszSVUDTsZxotTMNM68+9Y1ZZ7R2D4jVVIRnly+hdaZX//yF8Tw9Wj+/3E3z9JqXCRy9ugvmtBqbAJdwBQOTB1LNhNye16dGizjGoOI9irADP1bZ1FabXhgJDUgyrV61mqY49jn3GL/bUCM1hMk5k12DSeAky5IFgcVwcHMQpZq2AAK21d7poTj67DFa63LPuUE7zCG25KYt4Bc7mDWvfyiXWRj4i0yQHdottZDr9lu0PHa5Y3/ggFvVvOZFcdilF6q4NQUC7asLhyoJ8qBMaXLZw0NiKvHNcFyn90JqOOsTq319fOSBlJpY6kv6XKHxag9FdAUG66BfuLEpLgsahMBLfYZnag2jveyPXtOjwy1amPV8pkePVUbYIc9w+Y3tST7LeBT+1zb6K0nqzN7Ao5MtDdN1r9p2zQmKpmpmk1K9AJS7TNwNu5KsSutpVCcNxVN6G0czZXiad5KtuKwtPhgCcI5E8RTqxEw9jXjNKBeSSWhOqEUSrEUvFoyKhkwvySHefB456EIiiesPBRP0A4fTIrvs3nqzWPGRW9eSLWymya0VqK3tXutFqaBeNRbo8GJEtCWgma+P6KBnCp9FwgBxpzQkuhCs0lwESVanojKYdxZwPS5VpP1aiVVuL/f0ftI9KZTgtnmx+rx1RGdBXOVbAEBQjKJPyZJc76nJCXUgq/N86wYszo6Y3qGNs45qXgSeSzMKuScWHcCNUFrXDnxUCE3sLxopYsBLZa0i1jq7RL0MqVCJVFqxZdqgF0QSlWECCo8zBO9M7V5zjNTSdQsmO9lYMTY00EUqZb+JyItUCQ0gosl5wbp6HxHLXNj0KkFjDgBMiF0BBGm/Y7ojLGd1Izgi3PmU1kVzQUplnpLUxrgszHXZsVLZ4FDOROW+UUFJwZsxy5+re/R1waeloFvHEdyzjy5sgUh2gbNtil6SOewCaMizhNj5Ha75eMXn3P27rsEgaT1YOotgKoVZ2Oa+PT5Sx4e9qBC6DrSnLnZ7Vj1Ay/vt4w3X5CePuW960eEhuiZP9Jr4/lhUtHGdQ0ixrhqfzK1l6PKIkMz0KZrwNmklVwzRayTXtEDu8jMGpe+wXLANiyfjJ9vytBeu1vtmKfgxqlH0aGQaODM4S/1eG0L0ALmcVX1RJp2QmXWdrylBNCT13750379x+U9ds5fBp7eBJ1Oj4uYhvv+/p79uD9MqDknWGjVonQx4kM4FBX65u7kzTM9BaBOgLM3XqKwVDcs9dFrb/+q953sT5ednABUSqNqfsMXq1/ejLI7zjMTmTlDmp0tJFPhxYNyt1XQjGjBiTGdhmBd/XmczPNMlaDQecfgPb518jsX0RhxUrh52PL//fNf89/++efc7+DSVZ6uO37w/jnvXAXi+Yrf/9417z+6MNS+Bl7dbdkV5awfCN1AFc80FfZTZVYhVhh8NVZOLaTphjrNbB923G5n1DkuVxuGINQ88zDuGXcT64tHfPetM+7uP2Xab5nnW9brJ2xWgYe7e+ZUuDw7o+bKenCEkHkxfww+0F2tuM6e/W3P6q1H7PZ7plpxzjMMgtY7vN8Q/SUxQh3P0Hpu5VXJuHFHvrvFu4z3n1O0I9eC5onYd4CiPqIihPwZjD9H5ltwAecLeAhScb5CvyZLpJaAr5m5mAa9VEelMteKRIePFYkr4uqSur9F0j2kB6PeltK+9xbhHoeBMFwQho2xSeY9mufG5lCchxgVHyshtDHDG/igQEkBJ2vErRAXcKLUsgdJFlMvnt5f4MMG6InDOW7aM2nlX/3Jx/y9Hzzh2ePI7Zj4Nz9/ztsX11ytVtztMp+8euDv/+ADRJUY4FtvrYm9Ge/uppngPB9/OjJmz+3NK754eQOu8uRyw/l6IMTAxUb47PkN+31lsznn85c3vPvWNX3ftYXM154G/6NucbXhyePHzHlmteo42wjj7UcmL1PzXvDV8+T6PyPEgctLxzpGNrFyfbbifPNP+K/+q/8jfR8IMXL/MIPkRd9OcVCZcc0HsVaI0QrQUtWKKA9D15n8PDi8eHb7PWfnG7734bf49PPnfPFiNB+BZZEtIMEkBVpbh17FvNlyhlYY4n0zEgWhkvNE1kjKwRYrYmbgCSE4SHNB8Bg2WckVFOs82lxplP6slmCXaz3Ooa41NoLgWzd4kcooUKUaqyiYpEtQvBOSc7hQiWJgD07xMeBVmFXoUUprqDjnDqAdtDAQr0RasewUjyK+sT+KosUWqbW2ZonrcD7yi5/9nJImXOgsOUjOWOAGaQ03bbQM16j7qo6hX3PjHG+/8w4/+MF3IASePnnC02ePeOft93n3W++wOb+kH1YMsacLwRaXQpOCGLDmcC35y+ZawRgti++l1srLLz7jxz/6M3KuJnvKlk5YxFkfNDpwHtef8+OPvuB8VXj78pI07UjquLvZ43thnvctDFA4P18j4nh5d8/6YsMgkdXmgk9+/UvUBVarjtUQuXx0hgur396X8a+5VeqBVbcANVZfLNCRa3+qHNgnYmO7gRptoX/QYZ0YEn1lNfJ6HXawhjiYPbdm2kEv5tp5Nqin2oLUJF02BpjEbKnJlss4Kdjaj4usT7+qRBKwFLnFkmI51dMX18PzhupBBldZADXf/rewbwyBtntloJxyvDZtYIgxgeAoUavLCb1+iu3aFs+phX1ma5UGqEhp65/GqHztEkwfYiBTON6ww4ta47SxoBYgwqBCY07ZfV/OZVlXWM1sDDH3+vGWe48pCpYjLWCVyZCXiv3N62336cCAOv7tmCa4jAl6/CwAFsBJDh8kh3RDtYAmtDbgYvHhak+8O4KO3/Rtm4slqQlWRznFdRHNQs6FZTWbKvQtuAEx8M9FmxfSVPARvCi+95QMZYaSK5pmvAQmFaZa8G4iekcuHktkLXhs/pam+KEqvrNGvqs9uYoZfJfGgA1iBtA1UafEfjZARNRYNiRT6rgQLKk1JyhKbb5wWow1FF3FObVQFiC6QOc6SnVk1BgbVJxWui6g0lFKJM8J5z19twJR5jKhpdj+mhdkhwWWOK+klEiT1RoxCOITVZSs3ppPXklJqcUZE8g3/6OaLO0urlAcnUYCgtMJUwYYA895h3OeLgakKqUqeapkcZTgIWRiZ2bcMcR2TyAEx1wrcxE6OvKYcXWmetjVSi4FFSXNs9UavhAaW2oSm/uqZHwo5JKpLjQPZqGEgE4KJeNDxXnQdm+kMauHHNBitYI4yFrJ3lKgBzEm8wTkZHhFVUsB9nGkDz01ZUqe8D4YgIRhMLNTgleCWkphDZ7sAkEcEWf9kWzqteoynQ/U7CmCMfCxoa0fBnJjuv1l29euuJ0LeB+Y50TKmVrPwMtxwjoAH4J4bzK6ckyaUBFSrbx82PJiv+NsWGHDl/D6vKPMRRnnRE4FH4J13mLgxd0t0zRztxvZzSO5fkYXI29fXh1HyQakiC4dBTGkFFrK2nESQuy8sthAMadElcXDxqGlMtZstDQ17ypEmlmXdW0rsLgunuIYpxjJUsAd9OaHcz2cyfK2k9+338kRP3sNdznp+JzcvUPTaZnCTv96yhdawBTDPk8OfjL5m377CLYcTu8rsZavKnn0sDvVyjzPzHNi0ZWfUny9c3R938xYX5e/0X7z5QPL6+f7lYDYb96+5NMkrx/itUjiwxUdJ3L9ChDuG79VZT9NfH67J1VlSo5azKBvHme+uDdW2qqDi8Fz1kWLHUXYz4VZLX7UixJ8bQa3gSl7Ui1sVgOXQ2Q73fCzL77gs5uX/GdPHN9e9zg6urMzvv3dtzhfO4a159mjFWerjl0eeHG/524sXK3OGM7PqHie3+25n/aUrOQirDpPCTu83tK5LdR7RBKDV4YA6+hZi+Pl/cjjR49wPaxc5MnVBa/ub5mTpbOt+guuLt9mMzzw5PFbdH7F7v45w2qF73vub36Eul8y9E+4fXHPmb+h85Ht/o4n7z1mu33CbhdwfY9Wj579AX74NkH34DoUReZ7tIzomHE54tY9mnfo+HmT6hRcGFE6it4TqgUe1OGK2p/hXNPmS2kJHzZx1LihumZInCp5nplyoTCZWGKEbhRisOh6k9zad8VTwZn3QnQ2/IvzaIgUPxCcIlXwaQSUlJU+t++pN28oX3tUHSJKyTOFAUoH6rFEnB1zukddYZ4TPvREf2FJh9oTVud0aebl/Sv+0d/9Ds/vbwkPmRdjx2oQaqjcTXt++vwOipCmW8TPOJmY9vf86C9e8Hvff8KzJz15hJtxZtyPPL7oubutPH18wS4LO/W8/PSe7/UraoGb23u248zNbubRdEGMfVsLLG6B3+xts9owzxOXj65ZDZHOO+acoAVSRAlIzZytI2W6px+u2KfMq20hSuHHf/LH3N3fUH1g6AZSl0iTmt+pMx+YiCBdpCaTl7lmti/O2EHOK9Er2o69m2dyruYP9rBl3I+UVJHQtQnHnhNxAdWWlCgOHUcrfnGoj8tU3eKNA+N+ol/3TJMZqAYJxOCZKMRajBXbezoRahIK+9YIqGaq6m1cQ2wB2odgjL/DPF3Na0kVH6xZhFpssVBxruJdpXcDLkrzKxPi0BOKwweh1EDOljyr1TrNriYKxpDKqvTirUGl9v2JIRho5xwhBLoQ8Z1JdwSPi3Jo5GmthFhZ9R2ff/6cVy++4N3332c3TfTTxJlfQc4k5wkhWpdTzbesiz1oIoQVj58+42qz4r/83/2vAU/oe1IunG/OOL+6RMXTxw4vFoiyxKqYh4tawEE1mcKy+FRVqBZfrdia4+WLz8k5E7uID0KebDyqEto1KW5O+LjiXtZ8+sXIH/7eE7wv5JTZTnsuwxVPrx5zc3fPPE/c3mW0WD0wv9jy9rMVq77j2dtvMY8TadpT2tz1/NOf/da/k3/VTZc0t7IstFs1pnpIJVQ8i7arFKU6A1CEbNYMFRYKulIbICONpXLKUj+afS8ww/F3S+0kTTYJxug51mQLE1/c0atoqc+WsJjl54NMsLFwaAmTQDPx1wO7xgApY8O0M10q6lYrWrVqz9qp19HxfknL1VvAE+Fwy0ycJ8c9v+ZrpScSu8PmTn4+BaAaUIU2NqFZZijmw1Z18WNrPkmLF5YuErbGapEGLh0sPQ622xwWC3IifTs571MPqeUenBqQi+jr64BDN53mF7f4S6UGgbX7p2rzhguH/ZnESw/PxLJPe3+wdx8CFJbjLeflDh63tRZ8kyAu923Zl5PFx6oermExnT+Ce9/cbVcUzeCodAszr5iELVFxweNjT0meEiCXhEfRVBBX6XsDItCKamGcRwvdUSFlgeK4H2dmlLB27VmLQKELYinRBfqut+cuVap6YyU5h4ZKScV8hrxHdWYclXGujCnjcwEJxH7FNNvcX1pDIeWMpkwvBjinUgkdlGpj9qwzUR01CzF0gJBUmZgMKFHlYZqIrhBjpJYVee7RmnA+M5dC8QXxM6R9k2yZB1bnTX0xz5nORYIPjVthEsSSA7kxGxNKIhKip2KendIJuWayeFAPD0dfY995fHAQjdkTom+MrYoX3yRiqdUflb7r6fqOWuB+b0l/Xpx5zKKklMk+ISGgVC6Cpyv2bM8ZfO3NEzoneu9RgUkcU2nKKsl2PmIg2HY3GanfW/RaAWJLfZzninilOiU2joaGZi5Ox/Wqo+bK7u6B6DzJNW+2JIh6giirPrCfHhjH2ViuFcAsC9RVC5WpiSAR33kmPKl6iB3URK/g1Vmd4Czdlj4yT4A4vK+sho77m5Ga3W/45ry+/RVavY0UWRb6qj1oR9CioduA7wLOu+Y7odRSmOaZqrAbE8/v7un6lV2Atg6dKqUkxMOkM+rUYgSBcZyJTnnYzmy3E+NovlD348xHL15wvlqx6YevYLLYZpYTStbK3DxPG+OPIvYgz1WbJtQGwLEWQ1mX/WkT7Yn5T4gIydkAtBz06I20TCqHNxvqzXHCWP6yGDueNny03c1Dx6jd3mV5VJbXfQmpkgOgdmQyyeEVp7fl0NHidD+v3zwrDr5iQfZm8oSe7P2UYSXLsQzgK0vH6ITae9wnDEOPP0TXf/mc33yk9YTazRuvbbs8FDlfZzo7bUjVr9rvct56nOzl5Hff9E2Boo6X94VfPy+kpKRS6JyaP9NuZjdaQZglULuWIIlnLsIuJ/Yl04uyceCdWd3PbbEYw0C3cQxilOr3rhPxe8p1Z8e4mQMXj9/n2++/zTqClxEYudknphzIVXhydc35+oJ+1TPuE2dd4KzfcP8wkopyuVH2tzdsxxf4M484WA9nfOedDeuXDzjxbIa1DerdwHpzQRln9vstuSYu1xeI85yfP8OHFZqswHZBePzWIx52L3lIM935Y2KduX81Etgj+TnTq8qnLy8Y/bt00ZMeXhH6DeBxNSFcWOInFi/rEEpKTPOOmkcYFVkJ1Y1UXVlKmMuIL8Z4LJ7EQO0eITLh/IQ410zZHUlNjiPBIm6nacd+d8/27ob7/cSklkMYuxU+jAxRcL6iIeLiI2LXoeMDLtvzW3LCtUWBNpNtFY/ESNABrQGZOtBCLUb/VfWIj7glUFsjVTvUdVZQ60RJI/O8RV0hZaMeFzXKdnEBdZaOh5+5WlfuRyyJbsy89fSS9DBzN4J3M6J7HvaVIDPr3hHdzLOryjzd8K9+dMuz63f55aef8Z/84HtM88Tbbz9lWHWUsVJd5OrpGfdj4eLsjIdt4sWrLY+vLrl/2NPFAe+lyQn4xmNP+3HH9aMryBPPrh9ROs/DOOK8x4vHOfBV+MUvf8Hd3Q1/9w//MalGbm9HxpL505/9nPv7B0LwhM4TYwvUUAvaIBd8jExLkABCaiaVzlnDxYtagVetI1iyBXWE2HG73ZNKRdSzxGSYl1BgkbuUpOCzARvB4eisYM7J2EjOoVKNst2aV3mulnqoBa9G7c9ZWYeAUBhdxtWA7wquNsmaM+85YzolpmKRI0WU4CzhLTUjVS/OZAmN9eQwZvTQB54+esyTd58Susjtq3tSmrnb7dvCrtHrcyK4nrmMgHlvlCkxl9QWamrWA94Ruw4ydJ2lSAYcLgZi6PHOfKMqSp4VJ0ofTaZ287DnZz//KR988G3UB/I8otFAK7B0GgFcMaMDKwhtkdP7nl0YkL6BEsFzfrZi6HuEgMPSAaVJEc0dHZbiznuHuNIM4Y+MMSfR/LNKQZj4sz/9M169vGty9Iw4R0Ihj2RZoSixARqr1Rm/eL7j9z4sfPjkEb/45BN8NzDOmYe7kdALF+crztZrYtfz6vYLci7Ukri535oMsxYckeu33sZNO56sLn/bX8m/8larEJrXV60zB0aMNjaKzdIskjb7nUm83AEMPDLNDO9plhInCIXVkou30bHGFMC7YLVVNSmNYVBiiUytEhWwc3qDZX5k3FgnvtSjp5Ed49jwrY2lVA8pb6cIilvIWwdWT8NCWJg7B8aRPdnt+Mu1LjVYOTKRZPFPskWbtHS7BWcT5w5JeQuI9npK3uug09KJ1HZccbSkLGdJvQgQcGLsEwDV1O5gaSBQabtq3kYqmPdPA4FkYTg29mJjDcnBB2x5Jk6BKPty1lqO9+SgMnHWaKK2xEKTAVYzY7NQpbavg79Yu9kV+ywWqeVpQqFWGpi0fEhtnMoLw0FA7ecFnKQxO5XXCQqnQJn5e3FQQXzTpXaDr9zPBe8g19LaBUps36miMI6JLpixtTpFgmMI0cDmOlFqopYG4HRr0jyyTzPTnMjzTCqZucw8vriCGtAaCKIEEkomTxUvPeIC+3GLiqWCqleUTNd3+AIpT0zTlvt5RkJvzG7XoURcKgQyVPM+nusedWZrg4KEjjD0wIjKnkkf6N0ZezxVAmP2QIaNx7uOPO1QZ4whFYdqxKniYwZnLKiiiewKhUzsPCF0VLUaGWzNVVEkgCvFEmAdpGwAjTR5d5LSkhozzhdKs8TxIRJwaKpmbt45XABcRHwHEhCvOF/QKZFGxQWrU6oIWgvRQ1Bl3j2gY2ZIlYxHvZCqEoOy6RzFVSYUqoPimKfJJNIOkETvI2kOZI0EH+lRKHsItbFKhd4JUR1RPLNzzOKpoSI1sZ8SnmggZlY6rzhJiPMGHIZCDI6+H3i5u2dPYCpilgaVFu7k6IaerDPTPJqNnDOPLVE7TlAPyVLIffBkKl31BGcgGLXFnWkh4ChzpkRvRvnBMVeFbM2+uYrFN36N7WsDTzZYe3KuLUGiUoI240I50L2nWrm9vyelzCFG2Rn6LgumLx51i95Ym5618vzVS/pVx+32gW494Lc7liwG57zR6haqqFoRe7edud9P9D6+Pm+c/FjVwBqHMmNmWg4DQrIauJRVqM43oMWK3yrHVIfXQ48MhKqnaNHJcXX5XTsLaf/UrxhUl77Xl5RzyxVo8x3U42usu/NGp+P07E4BqzeOtfgoHntHXwHKnLCcvgynyBv/tVe+eWXL+5ZeBgIxRuuelVMDMqOUHyJhW9dE3wS3fsN2FGr+hr8fEKKvtbvfcIwv//uUMfa3aau1cv+QePEyU6uAF3ys5Dlx+zBSK/RdoBbYz1byjjKDGG3XFaXWwlStOJai4OB8s+J8tTYvqFqJV5Gz8xUfvHXFnB549XDPM7/h+tF7bM6v6AM43bHbv0TVBsqwOqfrN8Q44GqmTjP90LObHtCaiM78Vi6GFTe7FbWecfX4O8QQiCpcXe5QhTl5tqMw3uyRM0Uo3N0+Z0wz3eVjVsM5Q7/GR4dTB7VJanTGdfcQRvb7CzS9x90XP2J9Icxp5v3ff8T6/u9ztztnvv0Vu+c/JWyuQdZsVle4zbcsMaRkYEfSSNZIYU+uGaYJ8UKuK4rrTGeuCYej5mLmxdLj/QUiN4gUW7I6j4aOUgWtmfxwQ8mZeU5M05bt/QtevHrgPlssa78+J8TAunOcrQf6y0fQn1H9GnER5hmdJnwQXB7xdUco0GlHZEWgIAHoPchgxsfFozlDnEF7A6M0k7ECvjpHzTOUEdWZUkdynqg4lE1LA1sWFIEQV2QVbnYdwQ+gI5ermZXLTDnz4sWeb78VuNtW/uSXX/D999esfKDrA289ueDR1cDHzxOi3hhymw0Tnk47tOu56IXtlLi6uuJnP/05zx4/4fOXn0EpbELgl599gVTl8fWGkmYzh/6Gf5XXQ8fNFy/YSuXJtdBdbeg6jCYtZnod1POLn/8RfzYp9w8vuHzyFtvdRC2VtL2z4A+B2EWGzjNWx1wgVQBP5x0Ek9dJtfnROTEWvSoqjqyZWiulwKbvePvpIy6vzvn48+fUKjhvSUZeFHRs/w6HBnktViC7KJAaS6nztpB2ail1GbrQGj1aGCSi0YzHpQKaKWlvpvHRfJo6DVRnkcqWWKP42mZg7yDbuaG2BggNsHE4ilM6Z4tC7x0V5d333uO//N/8Fzx58oh+05Fbh/jmfs92nElVmJM11aZcTYJQMmnO6H7PnGb2+73R40uli0IXbf/BGbtI1WKTazV5XBfDgbnSdZGuCzhXyAUunrzFlEZWmwtc7NmXzFB7gltaROaGod5TpskMSH1ABbpuBc6jav4gQQL9sAKtlgAsJn8Bk81Zqoo7WvQgh7lWabVKWwh7FeYxEUMEUYJ3jGMiFUHJFtGdEp5AlSatCZGd6/nkTrlamzcXWYmdY7gaqKVScmFOiblUag3kVCjF/EVdWBkrL3Zcrns+efk55hr6zd7sO5EwwGnxQGqSpbqwlUrz1DIGkhOl0EJiwL5P5XTB71mEZSLamErKwnGX5ku0mOkv3qvVicmi6xG4ceihaSnU9r6FieIwTq6ds5LtMWGR7y1Hs0Rj1Xpo4C0JcMu2+GTaZsd3rUFcF6QIjlKlQ3FfD4CYeUUd5WeLZNpgl3w855PjLqypN393rKX1AHgtncg29BlAomr+ZdlkR/aNa5+Fa+I+Xc7RPpfFVPsIJtUjIKTZDIplAWvs87TTy22lsdyPBlcp0BjHxy0c5GsmaW7XggFkS9LekgC+HGpZy4QY6foVsesQHyxMqtQmE1Z8CPgYoFamcWQa95Sc2vNEA7nMA+8oyVs+w+N9XwgLrrH4lqXA0SP2mw08lbSzRFAf2xhotgNJHHOFtBAznCfEYHUzjlwULZlaDSAxQ2xlzCOpJPAwbAIlVnyq1AdlnrI1ewBPomRLjZNs9aJ3YkCnK8TeUxdAWGGaM2W7JThr0Ggf8G5Ak+KkIjpR5plSHOKFMWc6H61RUyDlirdvMqJi8vpqsnUJQp4SEqHWTFRPnUGltmS3QnGOEBRa0h3iGHPCieDxeN9ZWq4W83xE0TIhnSfV2tzsHC6Y4bfWRMD8ZSkdFEtwFWxOzgLJCS7NaK6EMKBSCVWI4hGplDriU6bWCXWOhENKJXqhlpncggV8ASm2tonqqFJBM4N3qDPQq5ZCL4WKpWlW7w3AoiLBwthytX07b8yoXiGIp6iS2uK6VnDa0buOogUnmS46cLmBvlBSw1tQnBRidAQVasoQK+qhW3dQhHnONPoJ3ivew7iojFqypdaKdw6JPV4CplQIlKJQZjosqS4VY8OVmkma8E1lEVpfSsuMMffgfrtDM0gLjfnLtq8vtROHE8+cRmIXDulzLa/mMHiP88Tdw/2B/gtmxOXVHaKMBWcFKiAqZJRxztw9bJluX/Gw21usd3v8xjTTuQ5XHalk6z5UATEj1Idx5mqjJ2bhp9sRXinApObgLmLMpbywtpRGo21WeGKeTwusUZdGDqa3rPVo23043oGpo5z6LXCYyN64qXIEgGo9YfS0uWHpEsProJPNF4u55+vbIo87mUdfuxOnavZFZvdleuu/B3haUKTXL+Mr54t68gKtBlgsZtwHejawJHWUXGwC841xdJiwvupE/vLttev6D+mknIKKHD/Lv22g0/LcpKkw7S1FxvWWVFG0kOaEC8GcExRqFiY1HXbXd3QEem8sgVArWgOKpwuRdRcJjW6NVPrVQPQbyhB5dVfZ1MDZ+RNW60tWg8Wmj2Mg5YFcZ6qbDcCQzDTdM+/uudvuKPdrvGR6N3N/85K8igzaEbsnrM+esTq/NFoxhevBrP/mVDjfZ7YJos/odE/HSL+5ZD1csFlfsN6cUX1kdf0uWmbuPv8TPvr1j5jTHWerFX0MxOjxqtx8lvngh9+mWzm6Uendlpxe4nRLzREflFhvEZ1BFo8y00sn15HxZLzd9zJD3+E6CF6Qukd7T0orqg6YxNcMeYuIGQd7Qb1JMcb9njkZO7QUZc4T0/TA/f1LPrsvZBxdd89q6LnY9DgeIeceLwPVeySM5Gkm12bxWWfgnpB3hKx0/soMwxmRLuBkoGYzbixpi/cDEqyRsJynYj49tW6pecuct6S0Zc4juAFpFG6RjA+J7cMD5Ewujl99vuWH376ilgdWj3ZElxj6zAdP4LJLDMGxXgfOzgZmErkk7u/35AzvPn5C318w5p6+H+hL4NX9S55ennN5fs5VLvjgef/dd/Decb4eGC42dBHefnTOulPquCNNe5MgfsO37fjAvN/zkPZ88qqwApyHrqUH2nPnSBVyWvMv/tUvWa9gTInBn3E2fEhJiYiH1ZppvwXd4w7dcmFKyRhA4qyrpbRuvzMzYwdSAyis1yvefvKIJ0+uWlc8oZqRoDg84qxIVAHxBVRay0ep6qEUxJl/kFPrxhECQSEPmUqkO/g1YabSVUmuQhDQaDbLuRKpOO/M50kwA+9lLizWrcfb6lGgBW0IrgpJauvmG+ujYH52t3ev+OLlc9brnrlmnO/Mz0Mds0LRBBTUFfrBA5G8rwRxqO8ZpOdKzkEtnnroB/qhIzpvfoZAFzyb80vAk1Pm/OwMcQ7vxUJZpBK84H1gPxXG/ZbbF18QnjiGi6sGNkhbBFkN0XtPiYFptyNLwPmAD0LvesZppOSJWUaGsaNbRZNTsnj9LM+RtMWhLLBIs7FpxtbOt+fBISEwy8Dv/r2/z1/84iN+8bOPGHOFksy/K3vUJ/CCOm/Fjle6zQWf3408ubpgs/6C2+3EdhxZ0xG8sJ8yLgYuztaICLvxgZIzedyRcuXxo6d0g+eTX/yM4eyKi+u3/mN8Lf9Km/mQeI6BNEuNt7QfOabNiR7m7EVstzC4DbhYuognMTB6KjVriaAH1o4dp5SWvNieHd8+kmM1YzW9d54Fp1jAlGNTVY+F0In8a/m1wIEJJbgGai7HXGwWFsCrMY8WltdB8nfo7LLI7xZw61hQH9cep9up15DhqItk7LRxuuz7+Hs9rFta/WlwTTu23Rcn3ppCakCeKdssJUt8Y28d5IULaHW8V7YVkIro6w1We89yDo5DmtxrL1p+8Id/nB5HdAF73BFAW8ZX5MCCW3ZWVc0w2GGMCqJdV5MfQaXUmd39ljynNvdbbL02oK4efMCO93+p8U0ZUxpj7/XrOAKWr38m39TNB89F6JlVqeIt2l6xOcp7uuAJbiAEb1J1zDNJ60ihWNJcymhRpjJxP+2ZMwyhZ/AgWpmmhOKQuRBDsDCBmg7SydhHVBQfDDA01p0yppmUWgIaBn5l09EDwRrNxl9hTiB4SslkpxRZfBTtOYjiEE240JNTpcwKOoI4nAv0vTcwfD+Si0PocRQ676g4slgzKAZj+RXBpNo50floHqdqqXJZoVRlWK8p1ZFypXqH1ECZqgFXTtGaGWJrvhIsEdC3gAR1uNhZsyXCatOR5orQk4saIOoK5EKqCb82O4ySKhQL4gjBiBFpyiZfxEGn5DITncdLJJcG8lfF9B6erNV8nKu2pHaHes9qBVozys4eHkksSZ1UoTprOs1OcbESVXFV8VoNVHOZOSfDQZqxWKqKkqgKvQ8MMVJzMpmeKOsYIED0ihfIaQ+txpKijUCT8BINKA9mpVBrxVeBXK2e7wK1epS2bnBCkUwCS6ht68NqaDbkQnCO6P+GPZ5CEIoa0t8PVqRZP36Jz7QI4Jv7B6Y5H2muhuiYnluE4IT1amidAUhV2U2Jz1++4O5+z5TN+CyTCM7TdcayupkfzLyLVliKHjqbpVh2gl8GU3kDfOGI/efjfAVij84COZ16IEldkhra5MXJmPkGqnMAaJZBV4+vVY4D65v2eXK6L+GQNPc6nnT0FVqG5dP/vbnpG395/R6w2FFRl6n9NebUm2+SL7O0ml79jV/+hnNZrt/+GmNn3c6y6LuXwqqSq/Ly7o6L8zPOzzeHVKLDySinEN/X2l6/9i+f4Veec3tuvuwXpQew6cTp6eAn+U2fMJdNtTKOmf2YiDGab4sq0QlDdO370UCJAhkbULZj5VYyg69cDJYslLNQxWJbp5KYZzjvBmJw7HMml0xQiKHn/HyDhg3SBfo+UuaZMVf2RUhFCW6Plj1l/8B22rO9v2O3U5y/4K1H58SoRM2M9xNjHXj85H3Wl48QH8h5phYbW3wfWV/2dNuRbs6MD79md/sxkkFqj18rXejpQ6TkiYdPXuHkFePnP+blx7/k/Krj4uqW4D5ne7difVbYF+Hl58Jut0H9OeHccV4e0fdCZQ3S0fWD1cOlUlJq6SUFdWosqBippSNNt8CM0zui60hUmM+wdbglx9Q04upMiCPxzJtkBiWrkGsktecwtyWheCG4BHliTp79fmLceurU0/cBd5noe4ttL8UbXTZNuCDgLOWj95nB7emkyTC0EHyPUyXrgy1I60hJr5AyodVj3gPeKMQAeTbmVqlUPCljZ+kzY9lR4x3iC3d3N6yD4+p8YOhXRC8MK08fHE5nujMoXaWkmXXnOT/fkJ0jV88QPb/3rTU+nIG/oNQV7z+7ANfxuF9xcX5G361xoUPVkmDeevSIPG55cnlm7CYKV+uINvBOS+bLg+A3b9NsxpU+KEVmkEKt2RjDzhFaMVyLSWD22wkfHSknpu09K/eY97/1AeN+Yk4TL148Z24Rvk4VnPn5GNAk5KoEaYCMeBDrqXoR1ps1b7/9hOuLc0IX8WKFW/DRuvhLUpa3RYgXT22pLCioF1xudBpvCywt1vapXnDVUzuLkfad1R7NpNG6eWKymXqYGRuYVEGdHKj53gVKqNRUDJzzxrhyamOheKPKWyPK2mg6V0L0fP75c/7v//X/jf/8f/oP+cHv/T776Z7QDYQQ6KM3lrQIWYulL+KgKzBXpgqosbxdSzbap8yUZjbDimmeiCGStUMfdqzW56zOL4mbNVLFZAYVoBCDNzaUZnKe2Y8P3N68JMaAW60a280K8ZIS8zQS8BTvyXlJwDPO0rofzFBVK+NuB+GMwQcWJokCOGmvb+wnXbjpNpfnlEEsZdQHk+oN6zUffOf7/C/+i/8V/69/9i/4l//yX/HAlmkqVIHojW3lWnpbKubTc5+UawLzuLcxrSiFzsIs1KNVGMeRs82K/TAwtUABnOfm4RV3H99Chnfe63C8/C1/I//q2wJAaCvyllrP2D40vEMWss2RIQIL0QgwryFpMffW5DXqiIrD9B7GNRcaMNIoOwsYYgDKEeAxyVM91D2LdK9BO5igiEPRqk0O5+TN2s9qNmmeaLCwnU7/vgATnAAgrfo+sJuOgFA98YgCPYJIxzbscncP4NqBldUA1KWCri0hcEl8OwBKi2UCC/jjXgNulnpU28+LR+kicT35gA/NVTvGKeCkr1+nGH1zmXqOPlgLYKUsht26sM9oTDi1he8R6DncgsN9ttcv+9cGwNVWwzd2nNh3PKXC3V1G5RZZQqMoyPIcuUDOBnCa2q5y9J+S43Pqls9rWU3V9pyePFMt5v3LmwEI3+TN+x6hR6VQRMEFOmfGA85Z86OKNdlR0GTO4aWOBrDMidy+h3me0WnG0Vlaesp4028TJaIFCBZq4SQi6pHoWK1WUI0FKX4g58I47QxESjYXlZKIncPXQkrGlqrqCC7Y32uAkjGravCxM4VvtrEkdIVMYtaeVANSC84bW4paLckMxRfzZfKuI1dj2BhgHagtMcsHSNUMwr2Yr1Ap1qTq/GBMS9dTSsS8xErzIFugcyONeIRBHIVKlkx2xtosKkBAssMRzWerETm0zqQl6l4L1RVjbU8mP1U19ZUTIYgnJzMuD85Y0MFVnBrvrKonVyg00+9qQRHOQW2kiVIVivlgLhLVWi0JUUQpBMCsKmopEMDEbAnVYpLYnJsMO9nN8x6Cnb/OmYKjFPvcnn/xAiEgWfBaca5YPeaFcc6MWii1mHWA8wRAXLQk81qhZGNCkxl8h5ZoGYK12tqkhR5oqWhoY0pVtCVki3iyCIVs+NPX/B59beAppemAcIdg9DwrE12bi4TduOflyztyqs0bRtsEYaCOOCUEiMHhMDnVwzTx2fNXvLi5Jadm8NU6IBVjS5W5kub5AJYUlnHcpDdgxyq0zt9h9NXDRL2AIxnXcBNpZ95kc2/AOYdy9mRWtV29Dh191XJFTt74OkzR9tn2sRidHqZFeR20Wo6x7Ou0J2/M1JNB+gCYfFXn/suD/AHvUsEt730DZDK/KP+l977ZgTl0oXgd4Kkn99K6bK/TnpdTW+Jz73Y7vri7Y7VZNXrkyYmyEAj/0kv7ymv9Sj5Dm8jrceb/SoCKVnC/5uV0mHC/+UyJZWulLsEr6w5CgOCt6B2C4/EqcrfPaMm44HGNIuudpU9JEDZdpPeO3TjykD0X6xUXmxUpTUzTSA0B80CojNki7VNSNqsV1XX0wxrvPalm+n4g9B15fmCeXzDmEUSRsufVFy9Q7bi6WCE103cr+stH7HOlX12zvrg2o+JsXQwthSKC0uF9T5GRPkIJFeksvW19+ZSLt99mOLvElS3bX/9btje3DFdf0PlbLjbK1bPK5dsfI3Nmnt9n9eRb+GvPPI2oe8Kc1nTDwPppZH05omMhlUJYPzJKbTZWjvmZeRNTeNNQV1FymZBS0ZLQMqClhyq4mKgVap4p846gIyoPuCKI7i1VTAfw5zhM9++84Cv055dc7F7yMI7oXtgn8z/Zj4nt/Sviwysknpmvze6B/HCHlBntBB8y65Vnc2YsjOicJVK5gPc9FSHI2goOZrTsoE5UBsRfoLVYBLALVs86AyPx51QR5ilRHUzTzP34BVpf2US+7tAaqMWxHY0Bm/0GpwHqFqeC+A71nkxEMb+aXAVjumzQOiDiCU5wrlKdo+96W+g4DADLmaLZCkPNgFGYl7FXxcal/yBG5G9p894W/84Fbl9MnJ/3xFjxtkJr3hpGXa95Iu0ro7fV67Sf+Pju5/zO3/uAq+sNf/xHf8zD7a2l7BTzYvJt8VUcuNJcZfzRELZWT6rK+XrFe9/6gIvzDTGaWSdqrKEYTE6Vx2xyHsDhjczQurSluObnRLMLqeA9WsphLnJV2nfaurClpX5VPSynwUFQoYilqHkEiximeZdVtNrxoZgEvdrM74Aq2ozTlYB5FXlvC+xaLdXvl7/4mN3uv+XTz57z/R/+LuvLK1QcoYuWMOc9zjtKTnhRnPc4H+lUyHlCRM0jyS+AgFLV4YPHxQ7f9bhorLCihZyVIZqsRUuhpGpFpouIs/s5a6aMI3e3D3jnCcHjnUn1xDlSKVAyKSdwjr40RlyrNkJoZqmlME0TwzoY9X5Z9Au4ZoDskFbBC0W0LZYdc1pitwPOA6rEGPn2hx9ydXbG1eWGf/bP/t988smn5nWi3ioZLc1bx2quu0n4aOdAPFoSIs4M5asZ7madEalM+wB47h7uETzXl2dk4OL8nJwSwVW2d7e/3S/kX2PTBfwQhZOmrdIkZoeaWU4KxlbBNsBgKQkXoMKJa6DRKSNITjqYzceOBUhZ6rRTr81jg3CRhBmAcgSKGnn/pI51r73XMGVlSWlzzhKokNpWAAvYY8+ZuOWYgi0xy+FYy4keTbaB5kW3MI8WAMXe8+UhvF0hywteT2s71m3y2t/ekObBESR0zhbnupzjopEwAM6e7zdBJwOXDiFLh9NZ7sVyPvL6fWwgl3PLEk1fu9YDk+m4l4ZvncBxbyginFv8DN3hvkvz37Jb0lZBzTvqwBjFYttPz582DsMCQC3P0/F+2n/tuiq055Rl9LbfHzq3DvAnB/hmbr0bKASij6gWxHmEgupMVU+alcxsjQ4n+JpJc6K4SvGQam3jaGA3F2pxdF0HIuSUqSXhNBOGHh8jEj3iCp3YmI33eBxpTjxMEyAG5uRsQIhUcNXwhOqhmJxNMdmeU1MGidq8L6HSOQc5GbzsrMmTamEUtedDTAZfc8WFBpjmgqu1sV6Dzasq5unZe0urE2PIulwPLD71keoDjgK5UudCFFNOOAKqQifSJH6VOSeKE6ookjNzaQLU9vzVHAi+o3PBJH8SyTqT04yUSlaFGMgVpAioN2k7C3tXUWfm8N5DmQtSoWrGqyIl2fzmIKkyN9and9LGu2q1Qy4kCrNXYvTGeKwFqRUXm8TZOZyEJmBUajE5cPSOko1Uk7MSa2efUWgAbp2hqRychNZIMNJOqZXqIEhhiB4XAqlCKoUsmZlsY2i1sbKKo6hZFninh4YDah5Xi+yzSCVLMc9Ltc9ZS6CIp4onRIeTSirm4W0WDI48f73v0dcGnixSuOKb94B7zYOnDX2LSSAcMR+WzkSbXlqRtESzbh+23N7e2pdOK8F7vPdmWqdmXmd+EvWAlqsc3KGa0WmLB9e/zPHnuPj+D9p+0+D471m8fGU6HMsg/GWwywoNOZ7qV0yqX5LIfSVwcuzInB5HT94DDXT6quvSr7qjf/nkoGjz/bIOyO39A3d395Ra33zhYatVW0fqK6qIv+x4fwMT1jd7yvub2ZwTLs873n7UUzK2GPSm++2D0kmhqDL4Si2ZeRJCXDGsHV3nOOsHvnjY84ubQugHnm7WdL1n3t+zvb/HOeU6rtlNM3fjFnLG+w0X8YxuOKOPPWmeebUdmXLGiWMdPLvdlvuHB87OIzFNPFn1nF0+4/HTt+n6wDTOuOGC89ixWp9TqrO4YFG6EFHvid4TBer9HXm7Zf30Ceofs5PIZr3i/GxNtwHViVq3xPOelVvRr2F1MTLWLfM48uKXN0h6Sv/WdwmX38K5jvL8Zzy82KPcEVcd7uwdupWjDlt8KdCfI85T00hOW0qdrUjQaN0STFNe4xniFVxjjBUPSYlutoS4caTmkcJEcSPqMrE+oK6j1mCLSulxMRLwqOvROnM23vI4K91euNuNbMeZKc/cP3xB96IjSkKCZ7z/jPnuhQEKDIRQWa8rq01HcD2SI44I4qkampRmRnVCdMI5MzYv1SHM1KLkvDOAADNArxLtfy6An8jaI75jPXgoGckzZZ5xREpYsZ+N1jv7AS+BwWfTuFPM6NiH1p0KKEIpHVojOCEERUIBEkFW4NuCps64kpA8EeqEuozrXANGaQv1ypxPosS/4VvJE9E59vs9D5/YaP7ksTB0xgryKKkW9rNSS7Uo4JZamSfPRx8/59ef/FOuLi/4i5/+0kw9W2OhqMU5OxSnARUz2Pbe5BwBwfWR1eaMtx5dcHV9yaofiH3ENf8JdSBURG3RUtTMaJeEWdHGoCmKawl3JWUWqZA2ZsTSuPHVTk8xUKVywt5gkbobGLV4XNmrFUo9vFZqK75QLLbeUY26RcmKF8WsYK0J4Z0zQLUKeMftzZZ/8c//FT/5i1/w9/7T/4Tvfv+HTPNMUGt3enGoZKtZxBMaixQ1JpGBUeZROfRmIu69w0dH7FfG+gsmG5ynLSV7Nu7C7mku5ocZHVDo48DUn1FzZp5n9vOEi5YgJa0GirFjriPeBVz01GreSMGHQ93ggyAhml+NVgYfzVxdBVdA3TFXdlnEmizLUte0mt9LKdn2Q24GxsrVk8f8z/7JP+Gddz/gn/43/w0//+mv2O2TAaQVdMkPEdgVQfaW3JdKYU6VVewsMjsXOvFshoFxHOliz/WZY7OOZkbfbUw+5Gce7l8yDFe/te/iX3crrZ46QjaNSbaYZjd2k3mh2pfhUL8ti3Y1PyQ9FnYNBDi5sa3BuniIiTqO3kgNJKhwkJEdQB73Ws13kl922FrbtP3jpNFYj1I5ME/IuJjl51aJLufXADJhAVFOPJCW73dbYzhZ9LOnx28/LSAHVr/a6TfQ6uSkl8bymwDVm+bpy/nr6cO/LGiwxab31rJO1Qz3nTRwXo/KjiPzaqnxS1uoLklvDq31sI6y76UBOQdmEpyAiUc9xsI8FFfbQ+EPoNPypT1liOE4sM8W4GlZBQgeL4vnqsfVJiEWPa7j9CjzPKzlxB3+XtVqAvPYOj3O4kfVvL68MxZjG4cXfHQBQ83e5JtdhVcUnIVF0Jijc7WFd8WYwzVVOiq5lPY3oK2DKsY0U2ayzhQVap4J0eM87NOMWzmkU/NpdtVSO6nUeaakTBSPlsA4zQy94HxGKEYCqQYQCUKpniIWDJHIJNRYRk5wYsmr6oxpQ26yaucpMhhM5Yzd5J0nO0GLmN+fFijFmE2+w0lPmQKOTGIyiwgFyUqhEpwl8hURqotmt1McQqTWxqf0ID6znUdEnDUT1cKQwFHSREkF9YFywNSD1YEmeAOdqcWAN4KYN1J1SM10oYHbxb7Dbh2YMuRFZuSEUs2qo/PGRrK3mKyx1ErND3S0BNrqCGEgpUrK5TUPG4mBkpQglgCexDe2l7F4yYpXoShUnQndhnlS5lKbj5oBWlozFCU0iWytHVMyhngMwWSeACXjuyaNb/5zKjZuRrcAzDBNZpMi3qTeOc1EvCXWFfMhs1EmN9l9xEmEmojt4lxo3twukvLM3N7jQkv8/Jq19NcGnqzTBSE6uq6ZRJ9MAYbceWIMTLNpEJdB0KiulhhzttnYYFsVqtG29RCneTowtgm56OEw2rqeh8EVTFKQZlIpLYlnMS78H3cxsQyQB4Dob2hbpvylqPjKPR8YSl/17q/e51f+7g2e7pvcnWNT5S+fDN68B8t8rZhk4/Zhx+3DtqWKLJ/1l98RQ3PFb138v+p2KrH8m/5s/rZv5gfiON+subrYsN+PjaFv36E5TYQgbEJHdGrSVucZhsjZ2cCYMmPZ89HNxE9ewHefdEzJcz8Z6Hx+1lMl8Wr7wMevtgTnOPfCfpfZnjuuzntLhPQwDA59UKZpJueROs7ofibJA72L/OC7v0u3vkBDh2MmTQmGc7r1BpEeLZmpJNOhO2UY1ngydfdgn/+6Z3Y9mZ55cmyuHjhb/Rn5vmO3fYZsPJvre3wfceHb9Bcjb70zsN0OhNXb6DSzUyHtJ2qZ2b5K7O4ycbiDcolvTJvar6nFU51Qa6bkLWX/gpL3WDz6GlxEJVJ9R+XK/l0LRSfryOSZKWXyPONqgZpBi5n+YhHpzkcyjlos4cN3Pd5FXKdIPaeeP6PUgO8eiKHgfeZhp+Tpnun+V0x+T3aONO8odWwpWj1D71kNShchBE91gTJ7VGOTRgWjTdeMMOPx1BqplhiBVrvuqhMQKLIBWRks4AJx2CChAz/gUiGXiZTbIlXBx4hzgTmDSkfwjkCP6gxFkSCIN3+CUotNGwRjqmBMDimLrMRSAMmBWjI1zZASUhMiSghClb6tqwzMyO078bdhlJjmEaGSE3jp+PSjLZSB998ZyLvKVAqqnen4xRpFJVdS6vn8+Z6PP77l+997wosXd4zTiJdoT1htqR3LavikO1+TMcK61cDV9RXnmw3DqkcEutXaYoGnwlRhP+6Zp9kMSEVwPuIFk90X83Soan4OsQsUFD0ot43WXbzQOfAYkCKlkqYZiZYcJc7o/DkD6phTxkj4pXXuAITsTE7nEFKT8eEsg9a1OcgZzx1VJU2V0GRjqg14Ues4igp5qvzq5x9zf7dlf7/je3/wd6gES2HFmXFniE1GYUVacIFcEpbDYAutnIol60jXzFutbqqlNCaSkKeJvdsScEzzRL8eQD3eB7xX1rEjC3RdtHMstRXNwjyNpLmQcyJ0AzjrYsZoXk9UMzauVVn1HXKSxrSYjJtnjRzGn8Mi1BlrwauiMZgno1ZqXhpaSs4zKQn9asM/+MM/5O13nvLRx5/xf/2//Ne8+vxzxikhxaSSSSvZDLm4urrkfhpxBFZ9YJ5Hcjaj7PvdSO8jq+j57P4WrSug0K2Ei6vHnA0D43RnseDf8C3Ighgt9fNRdocYSOFwlgyFt040Nh8suILVNY7m0HnYtxNpwTJHdMWAFneY5wVMrVA5HndBAA7bAW1hkYqedCqP501uqXiuNUsXWZixBaUtuA0oC+3dR7ai6umhjBG1NJcFDoSq13uVcmT8HLbT62hHkeNflopwuRcGkrzOVl9AruO2rCQXAKzdU7H3+hComto+5QDOejHT4+Xoh7VMY0q4k5Q3dQY+HeWOgvlGHe0vlnM8LdWXa5PFk+fkNiyvX6SEy2dXTwJ9FlbS8hnJ4r2kbaw+eFrBwTzORDrtmasg5eQzkHaN2kDQ43F0SVbEGsvOmdl5rS18CnfEGpd9f4O3okLVGVRxFZNpeSG39EZPoJNC70xuV0UbY8bYteSApAQ6E2qmjxGl+V9GyDlQnSUydz6Q9iM1F0a1Y9UCsxi7SYONzbUWUp6pYvNZrYoER2I2aXMzji6uoprAQYyeMs3UnKkSrFHUwgdqtu+M7xew27Ac18IIlsRIH1xjFAlRpbGHoTAi1UNpkjsFiQ4nSp5HalUCNt8VD6lMgGflOpxM6NL0xJqroORq41+q1ZqLBaIP+Cgoo/lgqeVW9b4z0/Aw2HmQQZs3dDTfJFKPloATR6nKrBnRYvJ86aiumORfFArEAh1CcWYF4GMA8QYQqcdpz8oVQilUjDTjo2eeIFdjhFuqpoAEswhCoFamlNirZ+8cq+AJeUbSfGD412xzpKoQVM3MXA2owxtTMIaBWhNp3uF8IJmlJn3XkSqM84wP1cA0EbvGCpoLIsZUMwa3omJeYp5goQcCTgqOiidbINvcahptoU/O0lLn+jfs8bSg56vVQN/1LH4AyyAOLfo4l8PDehj8TzAE57zRzlsknAh455qUQ14DJhY66dLlOejTZcH9LcfkYb9lzjN91wpHjl2iN7dTZkwb0mmz5tdbfLxGbz25yN8AcPxlCP6bDKVT0AlZ/n4czQ9yr1YcvvbGk72iyzl9+fhLasnhrdpIzsLrr/8ysvWbr+O161zYZ3buuaqBFnM6iU2lGbHZ7OecoEVJOX1t9tJvet2/76xfB6ak+SOc7u/L+zxYTR2ey+M+Fo+DvwnG1f/Y2/J5xNjR9x2UxG47MuWJmiuaC6vB4519J2MYOF9vePT4iohQyx7nKt+69Lx9fWbASp5Ikxnd9bXj85c3bNPMxfkVZ2vPw27Hxy9nGGaurz25eOZiaRWuPrBeGdPmyTvf5uJypOs3iHiSBhh6ilSmnOn7zHT/grF4qt5Qty8Iw5rNOuD7FevNY9J+QjaB1HJAMiBDJaYfc/fxPY9Xma52tmh9KJTygs36fe4/+ojtCHr2dxnOLondT3D6C+5/+inbm5H9raNKh8SAi32bnCslYKaMLoJUtDxQ5htKekGe9/h4Tp0vzSjRRbwb2vdsQ/GOKltyviNPO8o0keZE8BavWlGij4QakbQnT5ZGFTsFb4tbiR3eOTqtUB63LqgjBksq3HQjZS74uiftX1LDAF7oNhf0w4r16ozVhcP1I+I9RLtvJJtUtCpaJipbCvfAA9V15AQJj/diE7uaTEpFqN5R3RkSwkE8oa51QmUiFzMGLqV5hISZgqeP0c5bHFVNgic4RAuuFkrtSJNQCpQiOK+ETqiFFkFvrKzgFK2Rkot5bS3pT2qMGpMuhDZ/zXis2NDF3+YbvE27wuACfWdMmpw9zz/dE6pn1Xvu9yPg6KNHgvkP+C7wxWc7PvrlK1yIPGxveHn7gOJIdW7jseC8Se18E2WBjQGbfmB9tmZzdc7QdXTBk4BNN7C6XDPd3rM5v+D280+Zx5lpYVOUYoTyCjUu7AolqKCdM8p3SVYYa4bswKl5QUlBpOKx+SEnS6rDeRwmL/XepFtFnRVP0aE5oxjYVO0CcMuQ7m3xLU1K5wQW+Y+TRJX+YCI6l0rf+bbWFHKFVDMOz/3tA//d//Ofc3Nzxx/+43+MH7wFoTTmmJOKVod6O7BX80tRzfiuo5SKc5YYNKeE8zN7N9KFnpwyrvcQI+N+Z+fmIM+F6hJ93xF9pQbHfs7MuxsqF6xCD4OjqCXHVqKBwblQxWTKIQScVErOiFTG/USetnTdGavNmlIyuEIVIXiPkG2cdI2do00WIzQWjVCdMKdMrcamMrDAkefKnPf03vP2u+/hg+N//7/9X/Ljn/yS/9P/4f+MCyZpFA10FUiFR1fX/PLjz1GEh7GgGkAqUyoMU+biasXZxQUxhnZvPPf7LdPzPU8ePSF4x8ubF7+Fb+F/2LaYVS9em0Cr5+rSMG/PpRxKyqLSQKKldjIO7WnNsTTZBDnAUUfD73KoTxdZxVLrLcl69vw2bxpoDeBjHa8NHWguaFZ9S4MoVBFCq4Xs3F0zw1WSHcM1I2w9bTI3cMLcajCHEGnXfuB9HS5QeBNweuPeHurdJmGUBYh5vTb9UpP0S3Wynvxv8VyyoKOlD14XcGj5INs+lhCGRc5mQJwzMPHgodWkQu19i0m8c9586w7MMQ4sqKMcr53hAYhabswRSJPGPl5eJwuQd7juIziuKifgVYPADumHy60/en1xmB9OASJ/uIfHZ9eu332JoJAPIJ/Jb098sMgscstv6pbzlhoqMfZE56hpJjqxRplabShdZM47gihdUIpmkjYfPsnUlNg+3NOvIzFGG+uceQFJgXWIuKJMZUSdKQ+62uRiPoJkOm/+gtM04VRIs1LdDJjcSqIQakJytnrJCa7ammsulvFexBi6KpbqLFooOkPzGrKlWse03bIeBkIfKM7Sl4fQsRjP1ZSJqpb4Fwu1Jryz8AwfHCl5dnPFe0UkM8QKNRF8wSGMJVHDwN1+S4zR5HwV6mysYykmyfMOYh8trCyap2tKiSrGClNRxDtyNpBKfGPV1XIAVpMX8spsIboMZMdcFBVLHFVNFJnx645p3hNqJVaHpzOvVi+oOKLv0DQRq1KCR/pASSOuCKkklMLDDENYMaAksfOj84zVpI/iitU244wPK3o8fqpIgeAs0CQpEDxzUQYn5jmFolItW8BBlAHVYN5qroAPrZlaYc5QK70TfBEcnlQdORhLKddkw7ILyGAgtHNrG3zqTNDZasXScBWFrIVJC04tebgPHVUzJRtb+etsXxt4qtUMxjfrAR/8m2QZRIQQPJv1mimZ8eQ8m1G4CHRdRy4zr1695OpsxdX6fCn7WtfOOj8LXfzAKBIDtJaJ4c15R2k0uDaoVzkOZX+d7ThZ6+kvf/PrfsN7j6ye1nniy1j+V7sxvelkdFIwnBynyuk1nlYxxynkN8Fvb8Ir2t6mp/9m6Ya0s/prACvLO6qamWgpJ2esJ1O76uHfNzc3PL66pLs4/ysfz875rwCWnd7BrwCdDnRl/TJAuGzLc/q3AniqwpLWmFUoxfPibkSprIMVv69uM6uVLTgfGtL+4lXBa+GdwRG95+oqsk/Cn32yo2jg6kzZb28YnMXsXl8/4XLVs7t/yc3NS87jE65XnjJtqVW4e/WKl/f3vP3WFWeXG2pdE/sL+nMlbgakzLz64lPqMDBOW7oQiH7Fehip93/C+OKW2Xni4NH8A/zjb1H7K/J8S8p7dLwlZ+jWHokjb334S+4+fZ+bVzsunyZ8uoX8COSKKs/pVjPVDQR9het+Qi1fMN4N1H1gutki9PSbc9ywRuKa0G3wvkNDxGxXBUqiOAdhhQ7X+Dg0IKfiJCCxJ5dIKBHimiqeMgE8QB1xMtN3Vgh6Lzjf47qBimOaO3Kp5lUTPd5HXDcQ+jPEB7zrcLWgeUZ8YH22ZrULjDvPuN+Rc8Z5R+g7uvNrfLcixo5htaFbV3y/Q/yMk2QdDi8tElgp6QHNN4ibEW+6dBFPdAPoCvPt6Uk6gusgnuPCFbEOZjdUsunNU6YKVHoqM+LMeL0oSC2WmpdnslQOKRwSLHFJlHEu5NlRs5HKoxSCKOINU3Di8N5qoaI2OXsnSDDmjKXueJzvUfH///beplmy7DrPe9ba+5zMvLequhsACfEjSEFNwAYJMGxaQQ8cdtgRmtkDWxH+CQ79I0d4KP8DR3jggeeOUGiioAhRFiVSENlAA/1RH/dm5jl777U8WPuczHurq1FNdYMN+rwBVHXdm3m+z95rv+td76LV6EiinTCQX4H3dxwHbKqcamW/36EZznPjrz94ybNnN+xvMpTM2Qyfh+ioYjOvnp9JKYLLn374nNIKOe3wni1NaWCpvmhEadx42HF7c8u7T2+jnr+vHVMS3v3WO9wcDrz66JNQM6vwwU8/5H6qLG2+ZQivCBkio51aozkUjY52GYuyLgVTC58zC3l9Isia0ks8ck7MFmRH8lj45KpUsXheB8fmWN4loLgFwVSMcMHoiaUcizxNsdCttWGiqA+oN9IQC1Yzw2osoptWJA1kFSoGNbpV/um/+BP2z57w/R/+MMpClSDiU7dC9Wgj7RIqooRCCWNQMSU70H1wJCVKnVERJmmM44HiTibMSqfTiWKFfb1hL/Dk9hlTmZmOUySN+tyak3JuBgbjkDmeCq1NQbjJAR0SOcW1ffZOxuaZuZw431VKzhx2e8Zh3+d8WzvY+RzLwehK1cu8WosOPCn1GKyBt/7eOdac4+nI8XiP1cpPP/wJaoX9uOd4PMMYtgsuift5Jg8D777zjJcvX0VnohydgVKPS37+/BUfP3/OMO6Y5xOaBp49ueXd2wNVK8e7e26f3vwtvZlvD/NYL4jqw5hjSbD2RX6UZll0jl7ij+7bFLGkkxeVTo9TzIMW6vKbZa0VSpv4ESy00Sp3McJ7THoC8BI9+5rgtO7HFPd3USDF39HgR5Os5yML4WNQzeIZR/s5dWrN2krWXndvll6mtqhnkEhW+1XCcvl79SnSi1rJffEp66wWMR5pT9TGfnt6Wi4ur5cN0BsjXUfnqxQ0jl/1ouC0R3GkxZsSZNpyH6SrHeiJ+ouP1MVfavFHCi9hOiEY05KuBNpSwpeSY11dEIRv+Kgt21lUTXFKyxriQqjF71K/v90Dz5djl5VMU+mNHbz1rniK9GWji0EfGcIUvLKSdetzuDyJMZ66tzXZERxhEJgxq7drjupridYKTuLUJkwHmglybuQcXkzWjEpGWmIgSq2mJszmJC3sBKo7GsEQzYSkoSDGnGSJcn+OsrSUI1khkVxLIqQslNmwJtwcDkzJmUqhaiRwhiQMOTwVkyvVwm901FCvNJNo4FDvoTSShG1OZY73tDWUigyJ0hTVxGF/wNWZrISlwjAgu1DxaIG9hy/rTo3ZFGyHy0DaZ+bWqG7kWfAUFgfeCvM0MamR8kizKBVPQ7fSsQEjU90RjyThkIdQa7kwJmee7zmX+/AuIuEJXC3sLnQk50wxC8W2A5LIu8SYK8lmvDXEGknDb89qmLFHTGT47CT2vWzPwzYgjYBQTPDZGEQYx4wZlGpoC7XjMO6oAtZmXCrSYnxsCdxLxD2i7MYbXpRCGnIopaZzN+iOZiRVE2mXcS8cFAbTaMAyRGyBw053IMKxTahC8QQ1kTyF72lz8qDgBdx7fJ3xpDTCu0vHHQkjpwmKYG2E3njCrIAPKJm5lq6mS+QEQ4Ydzu2443Sy7hH3dorFt1c8EbLNmMj8wQARyZMw1nzn3XeZa2Oa52DzJb7XWryUp3Pl7u6Od/a3ka0fQua3YCU/3NdJaMkQPEbPHYQx6TL5eCxUvjCWue+zvupv/McDUuq6K8aCbuzfa/bf7jCWj16otke0x5Iae8MhLcHGZYJ59LFlTv6MY1ryWcvnHwuQP++YL5u/HL05nKeZaS6xiEgxibZm6+S+PlNAmQvTdMb9yVuRSP8xy8Vlcl6Nw3ko0V4Ip4vw6yEBd5FDO78KxJNoNDH40Z/9mBev7phOE6/uJ8ZBebLLTPNENeX29oC1yl998oq7mjkz8vR2xx/+xjvcJmG2xvO7mZ98MnF7e8PtWHnx4iVPbkb2w0AaPuJfqHO6P2Kt8s13X/DBTz4GSex3wvl45Pmx8M57TxhzFJyczrF4fPqtdxikcnr1Ar25RcSgnhF3ht2IMFGnQp3ukFSQdGQY/z2oUFsPfM4vafUT0g3o7glJjkwv/zV1mhifJPAJhnt016Lm2TMuR9Q+pdnPqCdjfrXndPeSZolxvycNLzGNbNIw7slpRFMvC8WwNtFaA2u0+Yy3CdIHkPYgIyqNaT7haEjsEWo70+ZXtHIKM20V3KLUWDWheQzfCHese3WkvGPc35B3hyC3NGGtYNMryumuK04rtZ2ZpokyT9QSmbA0nhluTkgaSSkyFeNojHlGZY48cROsKVZjMVvrhLU7RGZI3XRUZlxOCDmys15Cfq4Zyfe4/Az3SE5UM6pFpzu3RplOtHlCehY39WuqGmNDlqiNR6I8TnIEFtMUHdci6x4Zp2GI7h1DioyeaE/UxG1Y1aECYSmhCpKjFr2bP7ZW+KuffcQffvN3esn31xeOsdsN7HNDs1CmWAyM4w0ff3xkPDoiQ7Scb+GXYdU5nWem5ugk5JRJKZOzBBGqSkIZCM+sXRIOt3sOhz3jMERHlpZ6+93EuBvxaeb5y3v2Nzd869t/j7/48b/jR3/6Z5xPp1jkpkwrRhoSVipWYrXdAG0JEQsvFAZyVuqcQhknUTpvjdXUtNLIHoQUKpG8MPBMbw0M51NFcs+wpwie21xRTdQW5p/evV/cjKyhYGrNGXIochMaHhYSC/25RTnJMAy9LMVY8jvmxvF45MXzO8ykmyhnWq1kC6VHlKyESihJ0NOtkwl4eJ2IgxXHxpn97paMUjwaMuScmE/nIG7nSkpCmyd8f4sMe3Z5R0sVsUqthdPpxJBDdWL1zLlNOEt7g0QpYXR6s9/xH/7i3/DXP/5zvMA0VxAh34w8uXnCmHddyQgM0Y3wsNvjKtSpcC4TqGNz5dXdq5Dyn07IOFDmSinh33Y8n7i7f8XpfubnH39EORWevzhxf+pxYVVMKurK1CopJ54c9rx68QnVMoM4zYRWnLvzS26e3PDs6TN2ux0fPw9lVq2NDz76mLzbsR9zvPRfcxiOpnj+1wU+EAtzxa8irmYxnykCvnjqLE1xrBMF/dsahsHSH1KDeMZYFHdBiLp4BAKaWXcuttBRF3JCZO3Ydim67B5RKRpQNG+ReEgg0rg28l5U9eK6qnaW8xRJq9F0sCTpigCKhaD07nyLOfW1l9RCOvlynCt5ExPAsj4R0SgtBRZ6RUiX47hsscfEXRO+HK8IKmltgCC6fC5INyGt6h3Ew0drYfDF6W2QWMpkFrLrgodk2uW4L89FhJVL44jr9YX0znrQqcyr67tcq4tyKq7To33L4psXhKCrRfcy7x0MLWLfZX0mvlyr5bgFJ18RWotKuT+z12sP8a746h0OBcZR+MZ7z3j29IakhLL0a/4KV+/zjyeK9LJGN+a5Me7H8EVqlVaMWUKpGqXegrgwV4umDPuRPAYBUFuFuUGbyYNgRamloDpAUdwzlRPmZ3zufeTTQGkgtZOGdONqBUlGnb0TyglrM0Yhj4mUlWaFpGCqIAM9V0F4Kw2klJgN8jjQ5hpdy3xGCaKjtVDOmp0RNGKD5Ey1QU6kGcSM01SoGBmFZrTSsOwkBkhjnLtqeFm1uROk4TWUh4RrL8DVhJNiv2WmTaX7m8Ua0gCvUXY6HgRVp2JBBvWxS1WoXsgtvAaLJ1pSGg1rE5oNlx2tCZPFuzLmRMqGW2EuTmpBtg69mUjNjowD53MFE0YdyC7MNYQh1RtVwUsB635TOpB8QE2RIhzGA8cyow00RSc5lRzjtgjCjEhl6P6LjUbz8BQbdQwiKoe3XCWUVUmWpIKAhC8qmpjSifDDivg+VFLAydnvhPk04yakHKpzc6dpjio1bUztRNYdgwy0Nvf9CnOD2ZX05MB5mt7qPXpr4sklDEu9eVd4Wb8wFx4kA7e7gZfjwKtXd7gbqbOC8xxsJSjFPFoQ92ujolf15oG1pM4WMuB1gicUOVG2t7Yw7fPU9YB5Dbva1kOy4DGbcz3YLmPooxK117bx+rbstZ//IhivWYQvA/6Dn1328VByLeuXYn66TDaXsr8LuSRvvBZXu/kMeucB73X165Us6i2LzI3T8b4vSoyl1FxkkeNa9xvokn6RR5mwN6OHKa8f2yor/9yvr+fh/TuLCn3Z+iVT9HCvttbesWaXfgV4J1QS7//e7/EP//i/ivsf0QWgrz1DDvz2d66e+MWg0p0R4ck34Ld/h/4gLExmKAnC5O4h4bkEfxUhvfOUb75rCEFOmMBuiE9VN4or3L4XahgHTwcEqA2QW9rgSP71OEpxikhsRMICz/bfQuRbNPeY8PlNOIAfnGk5IgfOcgnyxPp5/x4Mhrwn3H5jeU+EKM3qZKo484OwNUPO4SWMdMlqz2Bf4kF2t++GJ8ZVNvCSxfb+MApLKcT6ti6Etlzk78viIiLghO7eZbd/l7GTzd4zsTFGXrGpV+S6yWWkWu7e9eeSQLLrY43rFIxtqB+C3FmC6n6ia9b0QuQu+1iyurELu3o4esebXroQCe/LHHMjy4Lgogygj03RCVTX+6PrIfeRdDVWBVz70uPyVH73N9/nh3/4n5PSW0+Hfys4zSeqjNTaGCRRWw110jjy4sU9r376MtoLtxRlG9JLgTWCSm2Qk5A1zCnHFH5ZQ87cDAO7XWaXEnm/CxKH6IpTaaiMtHPBSuXdZzfsn7xLs8qf//u/5P/5Z/+Mjz59Qai2oxOdWYM5DFaXRaB0or95eKTgxlwflgE1s764BsmAOyWiYnxp550Ea05zZ9BIOhlh3OxzC/KK8JQUN2YkTFebIK2GCqs/kc2M1hqeB8JXLdG9PIM4ahXLOYw3JUxB3Z13v/kNfuc7v0tKfZHqofipzUMBqUOUFtB9kHq7YZyuOlq0zU45zWCJJ7c3qIxM0xHVTK3hiSUaCr3JzpzLzFTOaErMreITjLuGzOHXsZTGmUcANe6f0KxitWA+4Bg/+tM/5f/6P/5PWh04A3nIKM4w5HjnNUgc6d12xmHA3SilcC4VT8KYBJ97228zPAWBZ+7sJFFVaV6ZzxOeMk9ubzgdJ2qbkb44HoYRQ3GbsTowjAlN0pvJCENW3nl3z8d30RL6xf0r2qv7KLeUSt5lhnHHaZrw3Y6PP/z538Jb+cWweJytqpwlXu1+Y8gyz1gf7+jXS9bBc22icxXLyloa1Vt6I5gH8aGrwmfZficq+nhrHiVOIqyqFlhiNFlJUmfx9Yn7lzqH00xI66jqQdL08XqxIoDLsS7/6RbE7FKSFafXj00W5eA6K7GUeq1xy5qY7vHbcr30UtYWqqa2kjraX+7lPFZyBnq3wYU4Sg+2LesFXzwNIdRU/ViW+SgWBXG0rtHJuZenLcRP+GI9PPawGLFo5kEYVeOxYF4b7nSoLj5QXc21ElDduHq94P2Z6NfhYdI0iCLtHjFu7erQr+ZMLmWBl9gj/vFY7b9ebwezth7n4gfsvgQ1vWGFKk9vD/z23/s1nhx2uGTqW62R/vZwbGd2ukelolZQgcSeuWXOp1CA7Qi/vFqjQcog0R3abWQmIbuRdm5QI3HQugegupNFyMOADGOoeKxhU4g2ECB5f0eh1lCSJxVGU6JRiGGiFCk0jF1W8BSqYiyadDjkYYgOs1Ww0hiHHe4NTTEnIsJun7gvE00VzZmdWjRqqQZ5xHCsTLgKjYHJjKEKyebw8rIofcs6xHpAw0JCNUeiFaIDXZuR1jhoplXrq4iZ0TOuBtmi8cR8TykzSZV9UgbZY25Er2IlyZ5sOYicMUhoScJONDryNUO94ZKZW7yPuxTUVCvGPEfSbNgJpVRKs0i4zIXkCbyQJIdKKhunNnGcZsLjqcW76OGhmCXGMhGivNIFb6zxwmxGO0W3W3dB8lKpJeAa5t7e0Nogh9raKJATw7BHHEoxkip2LKQsDDvpimvrDQ8ypomp1BiiPJO9QisIA6TozOvNaa2SPNG8UmXqPrSRoAjBwoQkJY1CVuf2cEu1uRMqGbIzGaDD6y/NZ+ALRdptaX3pTsiqe3ZeCPbRQqbfagnvHF9ekgZEtrEhnKdwTc84Q069c04gBuHWjei4+jmrcurBQsqjBeI8V+yGNTB0Ovl0NTmv3S+4fD1wqYe+BMG+/kboE7v2lXD//ZuJkcvk/QD+uf9cv/ua28gqG2Y9Tr/ax2uUkftFzXO1tUfU3rqt6xp34TLF+fV3rn742VPDZYV9/R0RGMfMkBO1xuB3wRKAXQKjyyLyTfu5/vajXV9t9frnq2z76nfLvXvgwXVZsbIk0PqHuCydL39fS8R/FZBS4gc/+AO+973vrYct67N0fbeXexg/k6t7+2ZcvotE9jWIA4hgcc2ponQvCEndf6Dfk/UxXDRzFyJktaXomTOI0hpY/C9C3u1LUPrgKX58jMs5h5JiNTe+OnfpQdtSsuouD7fzQI0XzhqLbwJ94RBk0sXjIGLDIPouh2frmLKMNouf53JfxB89j/jaKWzZ7hIrXtoYL9drGVEu78BVSMkarK7XPG7EQoQ9yDj79Qb0waWNoXM54n7OSwb3+sotY+xygMstluWuhJnzcr0vTRYePXuPbu+FFmTd5+JLcl0q8fjLy3M+DMOlscHXFIf9gBUYcmaqjayZhHB3dx8BmyQSvd2uRWmcRr9ckguWorvQkAdEhfeePGV3uCHlzJiU1OdsI8aKPI5oCvPUrGGgP+bMk6dPONaJH/3Zv+Lf/vl/4O40UUtPIGDRalmiY5ymWEiqKOaNZnOQzXVAktBaI/UsU7MSz4YkJOVuYppo5wJDJiUJFxARLCtijhElnPNUkRTkk/YOPHOt/XlrvdQliE5prAbA7kbyeH9bJ+BVUu90GD4aiJIyQca4MOwS3/vB7/Nbv/2b8Z5YZICXp87aZQyJ2EixFqol6e93dF6skUnd7cni1BLnKYvBsEQpT05CygNmylzPHE+vSGkXwWxtnMtE9sp+GLpZeCJLptQJ6+WFIg4aWei//53v8eTpe3z0fOrvu6IpUfvitwFpiLbdzRovjmdEBHXDLK9+kFljTp/UEFPcoutNdaFJiiD+AC6J6uFhMpeIDZsKNCHnPSk5rTZuxj374cBcZo6nM6rC1HaQMvNUaM242R3YDQOvjoW5Vg7DyKADp5cv+cZ77/3S38kvDI8kqWgoeuJnMRZa986Ci9VEZ41Z1EiyZmSvh+NLnHedeAzZ2vUYH3PU6k/E0kUYpJt/iyzjvvffO9rVVovHKiuBEMRKNBDoxIZHplz7XBxbucQQF5LFr/xcl3Nb/KZYv7UmSJfJzBd/ol7SKxcS6VohvzRDgh67y2W+ungMXSmCiDHP+lpFJREeRMKabHFYu8z1rmyqlzklPrvMa/nB/bh0E4wxeVFpydV6I8jFOO4l4R7/X+KZ6zXFst20fveinGK9jqs6zC8VBpdrJX2sifORfhzef3/tt/sYawLpMem0KOXsKoLsyql43vuz58o0NV6+PHJ+b+bJbk/OGqXTX2NoA0sNz0HYYpBwsinTXMhJ0GyoOq06aEJyjrmJBEWRZng1ztN9KO6HITqNqYYKCeU0TUjXq5o4Oo5BKNDCmFo81EvJEWnhbSmOKRxPM+bGoJXaiUC1gWFIYDUSM1OfGz1DjTkzSShycMVq5XR/h6iS0w5RwXwK9bo7dZ7jeMmUZqHCMiVJw7ygZAYZwKFaC/VWi3NxncmSERLVokHQYBknI0nCIgFwapRo1Hg2d+KIWFQb+IB7qHskxbye00itTs4Z8UqSAXeNrnO1MuQoKzQSA5mMkszxphSvaEqRlEpOVqfNJTxSW0WjXp3q3pXWQdYrTnYoXjnjjBrl9lmFgYzUhuz3Yf8gig6ZqUT5IRodZyXleDc9mg2Yh2raJBqvaQsPPhfQJAzZ8RbWF2FNANkVb0AKj1QhlGQpF2q7ByJ5JRINLswLQ+5jTxbAkJT7SiZTazQ6Gd3I1mgicNhDUtpUaCWR00CzxiTnIJrPzl7fjlJ6e8VTH2Bqbdwdz+yGxG4cu5krnM5n7u9PjDe362S2TFbzXLq/T8hDVXUlJfIwkIcl4F8Y/viX2eMB9boj2mWSuSiEBLsaJ43LwmL9c1n4/aLz5eI7tNTHi18W5/ZaGuDtrt/DfbyOpcK/75JLhuvRpx/97FLPfdnu4y4TvwxcznNZdEqfaPukw2XZZ9aX/+KX6/2IZPvi++/77liuyzXBdD3Z//8JokKSzOGNyo7ru8PVW7Vu4Qvu8YqMevSTv8nWLlt4eJxXb+ln7MUf/ESu/nx9u8t/fdanvsjRfpGzfHw+b/7861fz8/f8Nnu/Jtw+f3tX78/65+WIHt6RX7zXN4SzyEoayoPPfXbC4ILrcfPN5/IafdV/fl3W/fVFHg8UnOl4z9waeUiMQ6ZMZw6Hkf1+x3Q+cZxLBCGddELC90glShvPtSINnv7WM379177JXCrTeULqHMq91lDNHA57TMGbBZUo8NHHH/P+997n//3n/5x//a/+HWWOTjKxr+jwIrViooiGzD1MjxVVC4NVb4i3mOf7/Laok12iJXzrSqkkIVtf5lvtJXOtRnmWuNM64duaoUlpGOIWMn9NIRmvNcgRkcjo4mF+LN0bpzZU4/qQpCfUImu4KDg0RVb577//Pt//gz8I5dK6zg/FnarQqmEIYg2rnXzvi4Uxp66Y0OhyhJNSxETDsAOpkAdEnLnOnE9HrBTqHD5Gn/z8Z5yniftSef/993n/e9/HenfJ0kon8pdSKqVME6QBaY2UMufzzHfe/wd8+9u/zqef/mV04ROJgLVn3VW6+b/1DlwpdW5cu9CxIdWonkgJcm/nXqSrbYQ4xwaCxsKgVcxqdLQEZG6Mg5M0Y5ZxdTKJcT9ywLH7ypJcy+KcmkFOTKVEgkgTx6mQ88DTpzfcH+/Ju6/3ohWW0V67Ifcl6bLkaNzD1yk+fCEtFtNvt4WcgnWM9MtcvahJogwvnltb1bqhBFwkLGH0DKARFouE5w7L75dvRRmdr0RWJ4e7ckq6Tw8SyeXwQQ+CVQnfE+eaBAkiZInt3ZdEo6xk2RJ5RDc8Y1HvxhieOnFT+/B2NVes64MlPJfLVCXxPAbxsly/vi7pyiztRcAxPFx8uMIj6jpe7eWJ67Vf4o+FAuwkDD0Bx+U4H8yq1+uZNXa9kG8sZB8CV8mmOI70cBpen4ogL/oCbE24P1Y9Sb9e6+y9fm4hkrgkntYrtZyrr/dyjWEWghK4dMOLf6++Tn3hJ0A14dXdzIsXZ57sn3A4wNecd2Jw4TRVNA2M+QYmaE1xq4xL1zcRqiZsyChG1kYtZ6ZiNIs5I+8E0hBdTiWTVMO4WpW5FZo2RhloxahuqOYoPauVhHEYg+BKNhPqyOiYpu7oXMLUuzYsJRJjGEtb2BUkd7wUmiuzpR51BamF5uhS2gnqKo1WTgwaJX3NHNMRTMgGA4laJxoTguKaEEbMo/ux9zLDnIO4Kq0TXhnG7u011UpOe6rsyUmQ7l9U3IPAtEYhTL1dMuaVpJmG0NQvr0VaOIaMUkkKc62AkbMTvouGSwmlUPdrlKzd35FIZrVQ71YLMnmnI97Cv8ip0VCnCllydJizTiQLkHbMZlRv7LIiGmSPkhhItJnwMEwShHILXmGUMHfPOnBscUKDgXoog5unuAc+RRMVN7LGCFxrC1WSlU46Ld6yBfUTg59x3YWH1dIEyKEyk6SEgioFMWUthTLchEFhtMaojknMG+dSojtha3RBLSQjp2hGwwNvvDfjCyiewlTw1d2RaZrYj5l3nz4j7Ufcjbv7Ix998oJ3zCnl0pls6dKw+JbkFPKzUgqjRPvf1mWezVmltwuuWfyF0HqMZsZUamQ7V40S64B/jRj6Hi9cr87yKqu/fGqNA/pE8OBzEIqL11ZDfxNS4yGZtHiU+HLgb/vtdQ7rx/ULFlSXrNfrJM2jNMr6nw/P7vH2fZ1DH2as3nAa65wk5JzDV+Nzj/jyxSVIeB1vJpd+YQnfMqGuH1vu+eV3v6rk1RqIffZvH/3ry1qI/82pq8/bVuAqoPmcvXyR/X75x/i2n3+7733ep77Ynh8Tdq9f28tPPous/3wy6m2wxNeX25ge/PaztvLmLf/NnoEv7zn/auHR4YPbw4GhFKwv9I/HwmE38M333uFnnxiOcuwd6+YWi8so8UykXcVKpSL81YcfMk8nnj57ws3+BkmKSWaWlzhKmQtk4Xh/z81ux8tP7/n440/5l3/yI+apUjrBgkcZmedeLtOCTDKPwCmUy1HGIt7zuG4gFq3dZ8M1/KmW6cq60a3YomowmoVyKhF+GV6DDMritFjJsPi8mBClLkRM0GooGUjSM7UR9Ll7dKCTFJnW7s2knTAL5XZiGAamcuL9/+Q/5b/+R/+IZ+8+XRdigtFaKDFEI+ssvWvjUkJj3nCXbmrfQCPQzWOKtbY1xCvT3XN+/vwVH37wY37+wU/46ScfM08z5Wyc7yfu7+5wh1OZmKYzf/RHf8z9+UwaBlLv3IdGi+icM2Xu3juaQJRhFOb5yH/xx/+QH/3JvwmFlFjovfqc1qyRpOvUPTy5vAfkBr3coJfW4QwiUR6hQaalBF4rrQqDKKYR9EtbDIwTVmtkYEfDLbwrBh3Iw4ifztFS2xrnuSJecY3jKi7sEJ7e7nn+8gV3J4JMbILdnX/p7+QXRVyxpeNXV8n4pbTN1lhjid26KmlV2gvWiYnV12glBx4mVRdSRNb4dFHlhILAllLnTva7A+3inbRuR7tKpWdgIw5uF4JpCZJ7ybhILFzifJd43FYSJBbKlySkqIQ/lyzm5nqJNxdiWjpxshBkAJKC6LqiQ2IovyiZlt/1inbgoe9pXEjpxxnjki7f6x5aAl0pISzVGyyEi8T4sCz2QjmU4ve9vCnUX8uCYiETrw3Ml7Jb1nuZCCX3Oq9eliVX+e5+3wjiV6St2xS6ok4qQu2KtnR1zJ2cXLsl+rqOuU7wr5fI4z1bEruXboHeO5Iv8XG6kE++EFeXFZlLjK6Lam+eK89f3PHs6TNSzuRr5cDXEvHM2WyhTpUUCplkaDJ2+x1zbdRWYg5zj+5ktWA+xhxgM3mELANuA95y3BkvQf84KAPJEk6N6yuOoFE265VaCjscaTNOo+lIUyG1Fmra5ng1RCvJlZyU5o3SKtIqqPXxtJLSQO3lqUqo/iqNQmMYMjIZqXsjmlk0qCSRqsV7qzB303xMST6EKqoZyRWpRrNzdKvNvSi3xbMXRtsjTiZLok4TQoFhoHqQZWGn4ZyrkzWRu3+aiFKJ/Q5JkQTVQ1FYazQNsQlSNtJYqHXGMSw5phVPOxzIbkhtJIK08WYMvbPj2RzRTCKFr5QYogPmoSK2JohmRI3c1+vmHubsQyJlQYqDQbHwlFUPX8WmQQBJjek57nEh42DC3lM0UymJaglP0dXXDVrvcni7j0RebTNkR0wRHRlSQtorVIyd7qiSY1xLYOpBpLWG5DEMzVsNH+7qjGmg2RlpI9TwX62pYjkaH4lalP+ZoNJIyVF1Rh0Z5EtWPEFMdOepMM+FWgee3FTCYNY5nSfOpTGez1cE0UI6CLvdnlqMZpW7u3tejIn9u+8xnSfO84yIXGUYLionuRrs3oRWGy9evOSbz56Rxs85JSFKVN5ioWHIZR0lizfU1bVY//6s43ozsfXaIb2lwuezPiGf8fvrvz9zSS4Xg+xl8n+8rS98IJ8DkWjxnHNmEVA+5sGuuD5STgzD2z2WV8VBb3EcrxNFj3/2YGuvEW3XGZ43b3/DNb7Ka/KFn9y32NaCX+a9fPt9fblH9bbX7/raPP7sF6OFPvdT8vbffcst/p3DiDFNJ5IO7Pcj1Y3zVHhyuGE3Zk6nifvTmazK7e0Np2lmKg23ID1UjPv7GaQy7kbqeeaDn36EfvQJt/uRwzgy7m9pdk9rwjxFRrCWwm7MQTxo5a8/+Gs++MlPKM3Dg8Isyu41SlctRfcVuvQ7lrLdS86I4IxeWtNSNAPRtGSecPMoLbsmyXt9VxNoEoHLkBTHSA4quXe1cZIoTaLk3xFMnTxGq3J0Sc/0TKlBGi2MgWlRbmO2LuOtQdplMOO73/0u/+P//D9x+84z7o7HyJbi3WDcMGu00qkDDyPnMLKPDCgGaRwQTXgLY/vnL17w0fwBH/3sI+4++YSXL57z8csTL1+8ZDqdmeqEOwx5Bx4y/v1uj5txd3+PJ12YOkQjaVTLCRclyRhG5xg57VBNDLuB8/nID/6zP+Sb3/6/+dlPP0TyQGsNXUtlwti1SQIS2jvumQYh564UK5g1cs5UC+8flRw+oLo0DgB6qdbewx+qloYmAe1dwVp4U6k22A1haN+/W0ol5fA8GXNmPh15550dWKVUYRhG5mq8mzNuZ16+fDtj079NmNe4j6K4BZmxlEFGZ+ZLfNarobpa3FayakmAAVcBX7e1WIdrWb/34GedBBGB1Mu0QjV0nUTo5KuGoW+YLUYQfImU4FI+1uOormrp9FYsWPo7J8DKf60k2MUjySUWL9r9gFpbSs2EcMwRQDFZlDixsbT4CPWL4Vhcz/4T6+bil/K6y0UL7uhSdhcEeSiF+idW0ulSHun92VYwe2DFsXo1LgQXy7EuHlDSCSLpRuT9WDrZtIxL8T8hPGIWVdwlkl/UUKJ6ERiIcinJizsY5H0QFkEWLfHuchz9mvV7eB0HPzQijx+aLarg5VpAKJTtUQyt/RkNcsHdCb/j1M+yIZ0Ir+68PJ14cbxndxgYHu/3awbPiXZqZKMrb0K9khTmNmO10eaejDjNVB04u2MyktPISCNrotSKNyV5L5UsQUY1K2iCUqG2c3QR7l7JLuH7F9KnmKFaMTTnMIz2SrFG7URmk1AEJynMEF1jEcwjUYA09qOGL1AzqggyF9TCqyiR0TYCRvbCmJQmiWqdkFKhzjNjTrQW3diqR9mYSCXbTLZhnf/dhFFGssLynCcXbscgSev5hFtBB6cZtBLPqSGYdoVkTiQEbQSZ6r0zrMc5NKvkcaDWOTrssaeJ46KoDJg3LFUKhZ1nTITWguzRrNTSKAUkhVH7PiXUhZw1nnU3WjtRxdmnASXGBu2yK8lRmhaG6I2cMuU4gSkmiknpflsxrlRzcMU1Q+ulczJHIifvu+IzklO1VrI42slbz5m8v2WaK+tw0pQhh8DHLCF+QIGBrmL2ATAG7/OCKXMplNbIqqhEDKUpEnNVhZIH2O1BnMMwkDDMvHtxFZJAmWfKPKP6JSueFMg5k3OObkk1TMrcozY96hbheDzj6yAZg9EwDAxDZjqfsBoS4FILC22zSFjpShJd/BhYJJo8nIyvFhlLrfJcCs2W+uT1tw8m1C8M6Tkk5yrDccWSPPrsil/EEl1/7osoZj5vH2+pjHqNOLlS73x56KHLEjj45T7j/uiUFx8MetCwmGG++djXspj/SLXR42vh/Wdvo5JaPvcmFd6GXxbenuT9u4wvk4b7fLLpy/j8Izz4ypd7Jn+XUN1QM07lzHgYeHU8g8O3nu1ptfHpy3uaO6dzZTcIbo0hwWwCtZvSCuRhJOcwnTyfQzn1XJWsQh5ecXOTo6WzCs+ePeW73/8+dy+f8+lHn/JH/+WvI7sb/uU//bdEdyxIeYi1k8UieqdjZMd3hlmYSYcyNVY7Tng/qeRexjOSU3zGrUVU4oms0juqOLOEt1MizMSbO3hjZEQGY1BH0565lr4IJwzMm0Mv/RvSiIuF54MmXJykjvoARDtqaiPl6PbnotG+2go//OEf8L/8k3/C4ekzXrx8jtXC8XSmWaXUyCRr954xa9Q6oxiqoYZqc+XVRx9yf7znL//ix0xTIXelzvk84XO/PhReHWemYkQDF0MUarXIZHpmP0AzmOfoaljK3BVaO5JG95sgoGY0pyDmNBYarTi3T59xev4J//0//h/43//X/w0h05qtflBZWvg7EUavh0wnHeMYTYxwNonOl1EylvqxVtwESQlVJWuYpLbqTK1wnI3dYKQUi2a3KElovcvkmEZaC+UAkjhPM/M8sTs4T26fMvfF/iEPnM4nxjSyGwZu90EOfv3RE3CuQdBImIAr3dz5KvvlK4kRJJJ0dcol9IlrjreuBloSe0HqWM/WRxS71EUoKpcOaSwkDkscuKh8Fg8igChRfTwmOw8TmavHohAEr7V1PxeCyq/Iksu8kdKwbv8idlqIjsWg29FEqJx0+aC8RmilkA9EjCZhLL74ptGJqajCSOASfXA8rpF0T8YrwRWs6p4gZFTCCSqLhj/cot6SThgtaxDvaqu1+6CCLJ36lvu6kOtXO1yPFfC0KpAWP6lLvL4QRv0YO3GmkoJ0WlVyxH0V4j3tjQ0uJNxixs56vdd73G9WcIq6Ek4xoC9lkf7gntHPP56q1q/fUgIat/lwOHD77B0ER72EQojWn9evMZIx7kZaAsbMPg2kWih15jRN1OIMkhFVSks0MpI1VCxtZm4n0j6H/xOQBsPFqDW6OpufMa9B0lnC5oqmjNuEyUQ1Q0057HaIVEL1N0TTL00IhorTvJITjNafB6LkLelAEaV1Y+2cEvM84a0xY9FlWGDcj+TJ6VVvoMrsSvHwV/QMVmfGvdL6vr02WtTXLiMNqCFZsAa7YWTp2+kKBadVY9RQ5pErT4YdtRlza7gsTqnKQZSbIUqtR3HGnCmtRqMG3wNO8zPucxiJu6LqyFiYrXAqiWwHkjQyEzbfc9gLljJHK5CE4oWm0AaltDkasKginrtyORTbmoxdTmQGqoSCiCS4CUYi7ZQynaIJdL7BXEk5UVphqoKTGVPqKrKYQ600kmR0GMk6oF5xMj6kMH/XRDEQMqU4xRxJMLWC6MC5OuOQ2O0GUqqYV8wzVroSWWcYEu4juCFeIlEgUKi4O2PexfhKQ3Jm0ByeZRoEX54KrZ7QrNh0DusBFUp1IDNb43w+vdVr9PYeT2bhqaAxmJpfOjFYM1qLTg/m4Vlw9U3cjVrrOpElDZawlUYrJfwc1k8/LKm7TH50JvV1UiLqGy1c6B8rpt72BN985p18WmqhL5Oly+OffDHoJbUCv4D8eRxSPQgDFmKnT3zLBx4vya9L6FafALkyH//SysaWySjKLWprWGtvIIouhKKKYq2FaSgPjX6v1VnLdr78MHMpsXtMSH02EfWrVmb3dwtXEfqXsq0Nb8Z2fb4OaDn3hLyRxj1+Cvn4qRR2OnBz+4Tbp+/y6njk7v7EeLghiYe0vvUG7qOyGzMphepm93SP5sg4WqnMtaFNOBxu0CFzczhAavzW7/42v/m736GMf8bLV0cOT59xPs+9WXFIr7FYwCRN+KB4svCw0Ggu4dXxFkqIPGamc2TLvIYHoKiRU8YHx+fwy8iiWDL2Q+4LLGcYFPWMaUNcmcQZiAWkJCENinujkUjmDEmYWyWTaNKghoJCe2fG2lpkjWXEzdmNY2TqJVRc4y7x3/23/w2/8RvfplU4vXpFnWemaSINwmE/Yq9mWjHO04laT/zkpx/y/MOPefHJp7x8+YK7uyO1zJgotRg5DbFA1TAhTuxI3SBWhz2HbJQ6h7uNON3iJ8xtESQrp1OhzOFzJEmje15t4QO026Gu0bilRSdWmyuDKuOTW44q/P4Pfp9vfvvX+OTFXZQ8qEQmuytIkkcX0moNw5ktlAspe3Q6k+heJSqxAFCPLj0WC9WcBfHGbjfwciqgmazhE1JqtHBPw0hqjfNUEVHGXRjA1tZozZA0MOQRa43TXHApPHv6lGEcOTy5xeYzH3/6HBwOT77ezQEgVGEiehX7LQRDdwO6mtIupE6UVyyNenwpsTJHtHuPdCJKWGLmq9K0kKb0ZN1VG4Y1BLzuAvdwXlXV3iHx4hm0YCFbFoLo2rJB3MOoe1HndI+QIDcSePilxCVIKKkrYpZyzGuCJY7RWo2SFO3PXVdsIRHPrrlhDVIvPGL7msHTut1obNKj407iLaVjD6vwFh1Vv5bQVWkR+yXRWBf0br9x/ZZrHRf44v9ky5aQpcX5Vbe9UKvZlUVKP7C+naVcerknawJ+3dflpqylkPHpZam/HsNCC1zuIp3YvNiUgHUet680OqFkrXfRi48gD5d6scZYebHlhjxOTDnTNOEv79bSI2mVp4cd+WuueCo6cnOTqXVCilHnwtzCR0g80yYn70bM5jBtVhiTM3hjamfuyz159zREG9OJnBVrQqu6+hWh/e446JCwBOqV3EIRuRv3ZLyX73l/14SUcvf4K+yyRxONWtGcGfM+inwT7LJynButv3c0wAzR6IiXh5FxHDke79iNB6o7xRNuMQ5lT+xSjjI9hGaNQSBnqK3gGkbXZouXcyiVTB3pne2sNYwaZVtAs5m0S3hy5uMcXnQ5LoJWR004Hu9I4x5JmWphhl1rwSxUnJoHUmo0BtJw6IqiM+6V2SpVKvuUSOdKqnSDeKfVmPsUmK2yO4xhKt75+eBwBdWxi4uNPZkyRYfXopVxlOgAXaAcz2SC3C51wkUxDS8mM0UNsg8MKbod2j6RPOKbkzfSuGc0oU0lytk00jxzmyjVUN2Rk/Ty8+hod7t/ilthP2bmeeY8F1LeQYPdOOIpca4T5pWdZg43T7BWcDF2g3JzOJBFuD8e0TwgTTmfT9ydjpAHkimKUjKcBbILJGeuHl1NPRqLvKXFE+Lb6nnDhg0bNmzYsGHDhg0bNmzYsGHDV4CvN728YcOGDRs2bNiwYcOGDRs2bNiw4VcWG/G0YcOGDRs2bNiwYcOGDRs2bNiw4SvBRjxt2LBhw4YNGzZs2LBhw4YNGzZs+EqwEU8bNmzYsGHDhg0bNmzYsGHDhg0bvhJsxNOGDRs2bNiwYcOGDRs2bNiwYcOGrwQb8bRhw4YNGzZs2LBhw4YNGzZs2LDhK8FGPG3YsGHDhg0bNmzYsGHDhg0bNmz4SrARTxs2bNiwYcOGDRs2bNiwYcOGDRu+EmzE04YNGzZs2LBhw4YNGzZs2LBhw4avBP8fxw4QzGmWnj8AAAAASUVORK5CYII=\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def normalize_image(arr: Union[np.ndarray, torch.Tensor]) -> np.ndarray:\n",
    "    mean = np.array([0.485, 0.456, 0.406])\n",
    "    std = np.array([0.229, 0.224, 0.225])\n",
    "    if isinstance(arr, torch.Tensor):\n",
    "        arr_copy = arr.clone().cpu().numpy()\n",
    "    else:\n",
    "        arr_copy = arr.copy()\n",
    "\n",
    "    arr_copy = quantus.normalise_func.denormalise(arr_copy, mean=mean, std=std)\n",
    "    arr_copy  = np.moveaxis(arr_copy, 0, -1)\n",
    "    arr_copy = (arr_copy * 255.).astype(np.uint8)\n",
    "    return arr_copy\n",
    "\n",
    "# Plot some inputs!\n",
    "nr_images = 5\n",
    "fig, axes = plt.subplots(nrows=1, ncols=nr_images, figsize=(nr_images*3, int(nr_images*2/3)))\n",
    "for i in range(nr_images):\n",
    "    axes[i].imshow(normalize_image(x_batch[i]), vmin=0.0, vmax=1.0, cmap=\"gray\")\n",
    "    axes[i].title.set_text(f\"ImageNet class - {y_batch[i].item()}\")\n",
    "    axes[i].axis(\"off\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "vmccxpA0n6MY"
   },
   "source": [
    "### 1.2 Load a pre-trained model\n",
    "\n",
    "In this example we load a pre-trained ResNet-18 model but it goes without saying that any model works."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 464,
     "status": "ok",
     "timestamp": 1665166038760,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "s5jVhWiPPnlW",
    "outputId": "4651ea83-d8c2-4283-e9c8-0c8f714fe650"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/artemsereda/anaconda3/envs/quantus/lib/python3.9/site-packages/torchvision/models/_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
      "  warnings.warn(\n",
      "/Users/artemsereda/anaconda3/envs/quantus/lib/python3.9/site-packages/torchvision/models/_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=ResNet18_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet18_Weights.DEFAULT` to get the most up-to-date weights.\n",
      "  warnings.warn(msg)\n"
     ]
    }
   ],
   "source": [
    "# Load pre-trained ResNet18 model.\n",
    "model = torchvision.models.resnet18(pretrained=True)\n",
    "model = model.to(device)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "4vY9mZQanaxr"
   },
   "source": [
    "### 1.3 Generate attribution-based explanations\n",
    "\n",
    "There exist multiple ways to generate explanations for neural network models e.g., using `captum` or `innvestigate` libraries. In this example, we rely on the `quantus.explain` functionality (a simple wrapper around `captum`) however use whatever approach or library you'd like to create your explanations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "id": "gNxAtc2Co1pL"
   },
   "outputs": [],
   "source": [
    "# Generate Integrated Gradients attributions of the first batch of the test set.\n",
    "a_batch = quantus.explain(model, x_batch, y_batch, method=\"IntegratedGradients\")\n",
    "\n",
    "# Save x_batch and y_batch as numpy arrays that will be used to call metric instances.\n",
    "x_batch, s_batch, y_batch = x_batch.cpu().numpy(), s_batch.cpu().numpy(), y_batch.cpu().numpy()\n",
    "\n",
    "# Make sure s_batch is of correct shape.\n",
    "s_batch = s_batch.reshape(len(x_batch), 1, 224, 224)\n",
    "\n",
    "# Quick assert.\n",
    "assert [isinstance(obj, np.ndarray) for obj in [x_batch, y_batch, s_batch, a_batch]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "iRDwzUUp8bR2"
   },
   "source": [
    "Visulise attributions given model and pairs of input-output."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 267
    },
    "executionInfo": {
     "elapsed": 1636,
     "status": "ok",
     "timestamp": 1665165561587,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "MSLdchJUNpHn",
    "outputId": "65236e20-3c40-4516-b655-5d76283268da"
   },
   "outputs": [
    {
     "data": {
      "text/plain": "<Figure size 800x500 with 3 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "index = random.randint(0, len(x_batch)-1)\n",
    "\n",
    "# Plot examplary explanations!\n",
    "fig, axes = plt.subplots(nrows=1, ncols=2, figsize=(8, 5))\n",
    "axes[0].imshow(normalize_image(x_batch[index]), vmin=0.0, vmax=1.0)\n",
    "axes[0].title.set_text(f\"ImageNet class {y_batch[index].item()}\")\n",
    "exp = axes[1].imshow(a_batch[index].reshape(224, 224), cmap=\"seismic\")\n",
    "fig.colorbar(exp, fraction=0.03, pad=0.05); \n",
    "axes[0].axis(\"off\"); axes[1].axis(\"off\"); plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "tuBkEBv3mihR"
   },
   "source": [
    "## 2) Evaluation using `Quantus`\n",
    "\n",
    "As a preliminary step to evaluating the explanations using all the available metrics in the library, we will first view what categories and metrics we have available."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 9,
     "status": "ok",
     "timestamp": 1663672365951,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "m2ERMGxymqn8",
    "outputId": "738d30cc-6add-4e1e-e8bf-ea37f3de56a1"
   },
   "outputs": [
    {
     "data": {
      "text/plain": "['Faithfulness',\n 'Robustness',\n 'Localisation',\n 'Complexity',\n 'Randomisation',\n 'Axiomatic']"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's view what metrics categories are available.\n",
    "quantus.helpers.constants.available_categories()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 772,
     "status": "ok",
     "timestamp": 1663672366718,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "ZScHT03wl00s",
    "outputId": "76171728-47ab-45dc-a170-9d837b2e6a5d"
   },
   "outputs": [
    {
     "data": {
      "text/plain": "{'Faithfulness': ['Faithfulness Correlation',\n  'Faithfulness Estimate',\n  'Pixel-Flipping',\n  'Region Segmentation',\n  'Monotonicity-Arya',\n  'Monotonicity-Nguyen',\n  'Selectivity',\n  'SensitivityN',\n  'IROF',\n  'ROAD',\n  'Infidelity',\n  'Sufficiency'],\n 'Robustness': ['Continuity Test',\n  'Local Lipschitz Estimate',\n  'Max-Sensitivity',\n  'Avg-Sensitivity',\n  'Consistency',\n  'Relative Input Stability',\n  'Relative Output Stability',\n  'Relative Representation Stability'],\n 'Localisation': ['Pointing Game',\n  'Top-K Intersection',\n  'Relevance Mass Accuracy',\n  'Relevance Rank Accuracy',\n  'Attribution Localisation ',\n  'AUC',\n  'Focus'],\n 'Complexity': ['Sparseness', 'Complexity', 'Effective Complexity'],\n 'Randomisation': ['Model Parameter Randomisation', 'Random Logit'],\n 'Axiomatic': ['Completeness', 'NonSensitivity', 'InputInvariance']}"
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# In each category, let's view the available metrics.\n",
    "quantus.helpers.constants.available_metrics()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "aBJnm6Uf47Ng"
   },
   "source": [
    "### 2.1 Faithfulness metrics \n",
    "\n",
    "Score explanations using the following faithfulness metrics:\n",
    "\n",
    "* Faithfulness Correlation (Bhatt et al., 2020)\n",
    "* Faithfulness Estimate (Alvarez-Melis et al., 2018, 2019)\n",
    "* Pixel-Flipping (Bach et al., 2015)\n",
    "* Region Segmentation (Samek et al., 2015)\n",
    "* Monotonicity-Arya (Arya et al., 2019)\n",
    "* Monotonicity-Nguyen (Nguyen et al., 2019)\n",
    "* Selectivity (Montavan et al., 2018)\n",
    "* SensitivityN (Ancona et al., 2018)\n",
    "* IROF (Rieger et al., 2020)\n",
    "* Infidelity (Yeh et al., 2019)\n",
    "* ROAD  (Rong, Leehmann et al., 2022)\n",
    "* Sufficiency (Dasgupta et al., 2022)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 20389,
     "status": "ok",
     "timestamp": 1663605635056,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "4mEx1Ogbtjpk",
    "outputId": "614126f7-cbc2-46a8-f68a-6fde070443da"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Faithfulness Correlation metric is likely to be sensitive to the choice of baseline value 'perturb_baseline', size of subset |S| 'subset_size' and the number of runs (for each input and explanation pair) 'nr_runs'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Bhatt, Umang, Adrian Weller, and José MF Moura. 'Evaluating and aggregating feature-based model explanations.' arXiv preprint arXiv:2005.00631 (2020).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[-0.03852115130120209,\n",
       " 0.05681358501733275,\n",
       " -0.023240354085029294,\n",
       " -0.007335645392576588,\n",
       " 0.07114167908973591,\n",
       " 0.10796982893359308,\n",
       " -0.13866391825714072,\n",
       " -0.023036546248715033,\n",
       " 0.01251575207587471,\n",
       " 0.05595064896365906,\n",
       " 0.00884666287591645,\n",
       " 0.009519672411087364,\n",
       " 0.22290830979836326,\n",
       " -0.1186819643123575,\n",
       " -0.09198627498464948,\n",
       " -0.025075883597024583,\n",
       " -0.04287550840012317,\n",
       " -0.2242524663613466,\n",
       " -0.20020833827481757,\n",
       " -0.006196208583163412]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return faithfulness correlation scores in an one-liner - by calling the metric instance.\n",
    "quantus.FaithfulnessCorrelation(\n",
    "    nr_runs=100,  \n",
    "    subset_size=224,  \n",
    "    perturb_baseline=\"black\",\n",
    "    perturb_func=quantus.perturb_func.baseline_replacement_by_indices,\n",
    "    similarity_func=quantus.similarity_func.correlation_pearson,  \n",
    "    abs=False,  \n",
    "    return_aggregate=False,\n",
    ")(model=model, \n",
    "   x_batch=x_batch, \n",
    "   y_batch=y_batch,\n",
    "   a_batch=a_batch,\n",
    "   device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 38323,
     "status": "ok",
     "timestamp": 1663605673366,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "vqNSdIRndI3i",
    "outputId": "8a9e163b-6766-4e16-de23-6d241168b54f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Faithfulness Estimate metric is likely to be sensitive to the choice of baseline value 'perturb_baseline' and similarity function 'similarity_func'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Alvarez-Melis, David, and Tommi S. Jaakkola. 'Towards robust interpretability with self-explaining neural networks.' arXiv preprint arXiv:1806.07538 (2018).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[-0.15454811443663005,\n",
       " -0.30933664258003946,\n",
       " -0.15927610181143093,\n",
       " -0.6879649617539156,\n",
       " 0.08609686619002017,\n",
       " -0.20238983957329543,\n",
       " -0.3439131733828681,\n",
       " -0.3528094861960702,\n",
       " -0.07530687223381272,\n",
       " -0.3005613698366527,\n",
       " -0.5438176985228981,\n",
       " -0.09018626782454381,\n",
       " -0.0684177220189427,\n",
       " -0.03195967660623574,\n",
       " -0.3405809252387466,\n",
       " -0.42783366828762304,\n",
       " -0.36181560432334536,\n",
       " -0.5092673365063154,\n",
       " -0.023251215571104628,\n",
       " -0.0019366275390666939]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return faithfulness estimate scores in an one-liner - by calling the metric instance.\n",
    "quantus.FaithfulnessEstimate(\n",
    "    perturb_func=quantus.perturb_func.baseline_replacement_by_indices,\n",
    "    similarity_func=quantus.similarity_func.correlation_pearson,\n",
    "    features_in_step=224,  \n",
    "    perturb_baseline=\"black\",\n",
    ")(model=model, \n",
    "   x_batch=x_batch, \n",
    "   y_batch=y_batch,\n",
    "   a_batch=a_batch,\n",
    "   device=device,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 41135,
     "status": "ok",
     "timestamp": 1663605577188,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "g_6bztd0NOc9",
    "outputId": "22d52542-ca50-4e4c-a72c-09156feec381"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Monotonicity metric is likely to be sensitive to the choice of baseline value 'perturb_baseline', also, the monotonicity constraint between your given model and explanation method should be assessed. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Arya, Vijay, et al. 'One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques.' arXiv preprint arXiv:1909.03012 (2019).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return monotonicity scores in an one-liner - by calling the metric instance.\n",
    "quantus.Monotonicity(\n",
    "    features_in_step=224,\n",
    "    perturb_baseline=\"black\",\n",
    "    perturb_func=quantus.perturb_func.baseline_replacement_by_indices,\n",
    ")(model=model, \n",
    "   x_batch=x_batch, \n",
    "   y_batch=y_batch,\n",
    "   a_batch=a_batch,\n",
    "   device=device,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 37497,
     "status": "ok",
     "timestamp": 1663605614681,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "qs6Rufw6wahw",
    "outputId": "fd749b03-0366-48ff-85cf-eefa964fbb77"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Monotonicity Correlation metric is likely to be sensitive to the choice of baseline value 'perturb_baseline', threshold value 'eps' and number of samples to iterate over 'nr_samples'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Nguyen, An-phi, and María Rodríguez Martínez. 'On quantitative aspects of model interpretability.' arXiv preprint arXiv:2007.07584 (2020).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.5411764705882353,\n",
       " 0.85,\n",
       " -0.01764705882352941,\n",
       " -0.4264705882352941,\n",
       " -0.10588235294117648,\n",
       " 0.1411764705882353,\n",
       " 0.7764705882352941,\n",
       " 0.8558823529411764,\n",
       " 0.42352941176470593,\n",
       " 0.9205882352941176,\n",
       " -0.1264705882352941,\n",
       " 0.03529411764705882,\n",
       " -0.4764705882352941,\n",
       " 0.4911764705882353,\n",
       " 0.3941176470588235,\n",
       " 0.23823529411764705,\n",
       " 0.6235294117647059,\n",
       " -0.27058823529411763,\n",
       " 0.3852941176470588,\n",
       " -0.6588235294117648]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return monotonicity scores in an one-liner - by calling the metric instance.\n",
    "quantus.MonotonicityCorrelation(\n",
    "    nr_samples=10,\n",
    "    features_in_step=3136,\n",
    "    perturb_baseline=\"uniform\",\n",
    "    perturb_func=quantus.perturb_func.baseline_replacement_by_indices,\n",
    "    similarity_func=quantus.similarity_func.correlation_spearman,\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=a_batch,\n",
    "   device=device,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 510
    },
    "executionInfo": {
     "elapsed": 36933,
     "status": "ok",
     "timestamp": 1663606468228,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "JuQAmE4br5FO",
    "outputId": "f88d553c-a0ae-40ee-f8cf-4b7623f42ce4"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Pixel Flipping metric is likely to be sensitive to the choice of baseline value 'perturb_baseline'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Bach, Sebastian, et al. 'On pixel-wise explanations for non-linear classifier decisions by layer - wise relevance propagation.' PloS one 10.7 (2015) e0130140.\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create the pixel-flipping experiment.\n",
    "pixel_flipping = quantus.PixelFlipping(\n",
    "    features_in_step=224,\n",
    "    perturb_baseline=\"black\",\n",
    "    perturb_func=quantus.perturb_func.baseline_replacement_by_indices,\n",
    ")\n",
    "    \n",
    "# Call the metric instance to produce scores.\n",
    "scores = pixel_flipping(model=model,\n",
    "                        x_batch=x_batch,\n",
    "                        y_batch=y_batch,\n",
    "                        a_batch=a_batch,\n",
    "                        device=device,)\n",
    "\n",
    "# Plot example!\n",
    "pixel_flipping.plot(y_batch=y_batch, scores=scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 4,
     "status": "ok",
     "timestamp": 1665163410992,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "nyPKHv476C1Z",
    "outputId": "b137bb35-ffc3-431f-fb0a-13eb8041dc67"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "   -2.040754168319836e-06]]}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Create the region perturbation experiment.\n",
    "region_perturb = quantus.RegionPerturbation(\n",
    "    patch_size=14,\n",
    "    regions_evaluation=10,\n",
    "    perturb_baseline=\"uniform\",  \n",
    "    normalise=True,\n",
    ")\n",
    "    \n",
    "# Call the metric instance to produce scores.\n",
    "results = {method: region_perturb(model=model, \n",
    "                                  x_batch=x_batch,\n",
    "                                  y_batch=y_batch,\n",
    "                                  a_batch=None,\n",
    "                                  device=device,\n",
    "                                  explain_func=quantus.explain, \n",
    "                                  explain_func_kwargs={\"method\": method}) for method in [\"Saliency\", \"IntegratedGradients\"]}\n",
    "\n",
    "# Plot example!\n",
    "#region_perturb.plot(results=results) \n",
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "id": "8DfswMlbSVir"
   },
   "outputs": [],
   "source": [
    "# Create the selectivity experiment.\n",
    "selectivity = quantus.Selectivity(\n",
    "    patch_size=56,\n",
    "    perturb_baseline=\"black\",  \n",
    ")\n",
    "    \n",
    "# Call the metric instance to produce scores.\n",
    "results = {method: selectivity(model=model, \n",
    "                               x_batch=x_batch,\n",
    "                               y_batch=y_batch,\n",
    "                               a_batch=None,\n",
    "                               device=device,\n",
    "                               explain_func=quantus.explain, \n",
    "                               explain_func_kwargs={\"method\": method}) for method in [\"Saliency\", \"IntegratedGradients\"]}\n",
    "\n",
    "# Plot example!\n",
    "selectivity.plot(results=results)\n",
    "results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 405
    },
    "executionInfo": {
     "elapsed": 1455,
     "status": "ok",
     "timestamp": 1663674388771,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "mZ_XsZoMlfwS",
    "outputId": "1063c3db-48ea-4efa-a486-357979bf7a2e"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:matplotlib.legend:No handles with labels found to put in legend.\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create the sensitivity-n experiment.\n",
    "sensitivity_n = quantus.SensitivityN(\n",
    "    features_in_step=224,\n",
    "    n_max_percentage=0.8,\n",
    "    similarity_func=quantus.similarity_func.correlation_pearson,\n",
    "    perturb_func=quantus.perturb_func.baseline_replacement_by_indices,\n",
    "    perturb_baseline=\"uniform\",  \n",
    "    return_aggregate=False,\n",
    ")\n",
    "# Call the metric instance to produce scores.\n",
    "results = sensitivity_n(model=model, \n",
    "                        x_batch=x_batch,\n",
    "                        y_batch=y_batch,\n",
    "                        a_batch=None,\n",
    "                        device=device,\n",
    "                        explain_func=quantus.explain, \n",
    "                        explain_func_kwargs={\"method\": \"IntegratedGradients\"})\n",
    "                        \n",
    "\n",
    "# Plot example!\n",
    "sensitivity_n.plot(results=results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 23551,
     "status": "ok",
     "timestamp": 1663674419557,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "6_nIBdxxH5BM",
    "outputId": "65dde49a-0034-41e8-8f7f-459c381dc676"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The IROF metric is likely to be sensitive to the choice of baseline value 'perturb_baseline' and the method to segment the image 'segmentation_method' (including all its associated hyperparameters), also, IROF only works with image data. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Rieger, Laura, and Lars Kai Hansen. 'Irof: a low resource evaluation metric for explanation methods.' arXiv preprint arXiv:2003.08747 (2020).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/dist-packages/captum/_utils/gradient.py:59: UserWarning: Input Tensor 0 did not already require gradients, required_grads has been set automatically.\n",
      "  \"required_grads has been set automatically.\" % index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The IROF metric is likely to be sensitive to the choice of baseline value 'perturb_baseline' and the method to segment the image 'segmentation_method' (including all its associated hyperparameters), also, IROF only works with image data. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Rieger, Laura, and Lars Kai Hansen. 'Irof: a low resource evaluation metric for explanation methods.' arXiv preprint arXiv:2003.08747 (2020).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'Saliency': [-2450.2173034978723,\n",
       "  -16.374110163577612,\n",
       "  -28.863229005189176,\n",
       "  3.4739964811507207,\n",
       "  -11461.351480565618,\n",
       "  -4.350771566117068,\n",
       "  -129.88071852734805,\n",
       "  -2097.1381447828126,\n",
       "  -35.36820374450471,\n",
       "  -156.78475600201338,\n",
       "  -454.90247938336296,\n",
       "  -399.9201570419748,\n",
       "  -92.66307640776316,\n",
       "  -4.130042044001463,\n",
       "  -102.80285010028393,\n",
       "  -825076.2370666246,\n",
       "  -3.325261169068547,\n",
       "  -100.30074095804162],\n",
       " 'IntegratedGradients': [-2974.3905808129384,\n",
       "  -14.957913740375133,\n",
       "  -31.597699001362372,\n",
       "  3.399904352201858,\n",
       "  -11461.002755258021,\n",
       "  -4.255324475896472,\n",
       "  -134.6151674311129,\n",
       "  -2035.673341709858,\n",
       "  -27.785719333962703,\n",
       "  -170.03504515459696,\n",
       "  -455.42920531676276,\n",
       "  -401.69614527525783,\n",
       "  -93.4874045457903,\n",
       "  -3.977154934199362,\n",
       "  -102.60959033992808,\n",
       "  -412540.1193502592,\n",
       "  -2.043219271533964,\n",
       "  -101.26936100151497]}"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return IFOF scores in an one-liner - by calling the metric instance.\n",
    "scores = {method: quantus.IROF(\n",
    "    segmentation_method=\"slic\",\n",
    "    perturb_baseline=\"mean\",\n",
    "    perturb_func=quantus.perturb_func.baseline_replacement_by_indices,\n",
    "    return_aggregate=False,\n",
    ")(model=model,\n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   device=device,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": method}) for method in [\"Saliency\", \"IntegratedGradients\"]}\n",
    "\n",
    "scores # felzenswalb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 500,
     "referenced_widgets": [
      "202e87c666e846398d64b89a9c16ff45",
      "7fca2ae1e0b344b3a52dded546f22f43",
      "8bb29876bedb4cc9b0d23134b1e46767",
      "2f651b4eb3d54f81875175de1b439006",
      "8f2f32097c5340d59b3e1a24403c5885",
      "a3f344f4af8e42ef8d0e1b301d0194db",
      "b65de9bef1614c8eb56145197835f42a",
      "e559028c13234ad9ae0d01a64e796d6c",
      "97e6119596884d0781885bcc70c5e481",
      "56a32edb2f594c77ad9c697edb1eb3fd",
      "4856cb2fe2c844ac814a15cddfeb758e"
     ]
    },
    "executionInfo": {
     "elapsed": 155614,
     "status": "ok",
     "timestamp": 1663607922246,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "-QMnCmWLRLXq",
    "outputId": "100d9b2a-afde-486e-8742-1a0579010a8d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Infidelity metric is likely to be sensitive to the choice of baseline value 'perturb_baseline', perturbation function 'perturb_func',number of perturbed samples 'n_perturb_samples', the loss function 'loss_func' aggregation boolean 'aggregate'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Chih-Kuan, Yeh, et al. 'On the (In)fidelity and Sensitivity of Explanations'arXiv:1901.09392 (2019).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "202e87c666e846398d64b89a9c16ff45",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Evaluating Infidelity:   0%|          | 0/19 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "[1796483.4443198796,\n",
       " 12416903.33174478,\n",
       " 14158807.670184037,\n",
       " 363631.479612375,\n",
       " 159359.25294499582,\n",
       " 1113157.2950333632,\n",
       " 9323674.929579282,\n",
       " 1388681.5510537962,\n",
       " 8303985.413801474,\n",
       " 1070049.3484908913,\n",
       " 907060.4465064537,\n",
       " 8370813.388146776,\n",
       " 3530213.983484649,\n",
       " 4468296.148278534,\n",
       " 16211488.48945864,\n",
       " 30363664.373251207,\n",
       " 3374637.8717216603,\n",
       " 58902321.66314578,\n",
       " 626065.2206585895]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return Infidelity scores in an one-liner - by calling the metric instance.\n",
    "quantus.Infidelity(\n",
    "    perturb_baseline=\"uniform\",\n",
    "    perturb_func=quantus.perturb_func.baseline_replacement_by_indices,\n",
    "    n_perturb_samples=5,\n",
    "    perturb_patch_sizes=[56], \n",
    "    display_progressbar=True,\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   device=device,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"IntegratedGradients\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 46377,
     "status": "ok",
     "timestamp": 1663666983084,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "ApTAezBCRN9L",
    "outputId": "61e5091d-d916-4622-bfee-f32e9308212f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The ROAD metric is likely to be sensitive to the choice of baseline value 'perturb_baseline', perturbation function 'perturb_func',percentage of pixels k removed per iteration 'percentage_in_step'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Rong, Leemann, et al. 'Evaluating Feature Attribution: An Information-Theoretic Perspective.' arXiv:2202.00449 (2022).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
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       "{1: 0.0,\n",
       " 3: 0.0,\n",
       " 5: 0.0,\n",
       " 7: 0.0,\n",
       " 9: 0.0,\n",
       " 11: 0.0,\n",
       " 13: 0.0,\n",
       " 15: 0.0,\n",
       " 17: 0.0,\n",
       " 19: 0.0,\n",
       " 21: 0.0,\n",
       " 23: 0.0,\n",
       " 25: 0.0,\n",
       " 27: 0.0,\n",
       " 29: 0.0,\n",
       " 31: 0.0,\n",
       " 33: 0.0,\n",
       " 35: 0.0,\n",
       " 37: 0.0,\n",
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       " 41: 0.0,\n",
       " 43: 0.0,\n",
       " 45: 0.0,\n",
       " 47: 0.0,\n",
       " 49: 0.0}"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return ROAD scores in an one-liner - by calling the metric instance.\n",
    "quantus.ROAD(\n",
    "    noise=0.01,\n",
    "    perturb_func=quantus.perturb_func.noisy_linear_imputation,\n",
    "    percentages=list(range(1, 50, 2)),\n",
    "    display_progressbar=False,\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=a_batch,\n",
    "   device=device,)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 4699,
     "status": "ok",
     "timestamp": 1663666877695,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "ogW_EVxh0L_v",
    "outputId": "dcf4c85d-8098-4378-c81a-faf54dbeb051"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Sufficiency metric is likely to be sensitive to the choice of distance threshold that determines if images share an attribute 'threshold', distance function 'distance_func'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Sanjoy Dasgupta, Nave Frost, and Michal Moshkovitz. 'Framework for Evaluating Faithfulness of Explanations.' arXiv preprint arXiv:2202.00734 (2022).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.0625,\n",
       " 0,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.058823529411764705,\n",
       " 0.0,\n",
       " 0,\n",
       " 0.1111111111111111,\n",
       " 0.06666666666666667,\n",
       " 0.0,\n",
       " 0.09090909090909091,\n",
       " 0.0,\n",
       " 0.0,\n",
       " 0.058823529411764705,\n",
       " 0.058823529411764705,\n",
       " 0,\n",
       " 0.0,\n",
       " 0.058823529411764705]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return Sufficiency scores in an one-liner - by calling the metric instance.\n",
    "quantus.Sufficiency(\n",
    "    threshold=0.6,\n",
    "    return_aggregate=False,\n",
    ")(model=model,\n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=a_batch,\n",
    "   device=device,)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "TP5M_pe7u-mV"
   },
   "source": [
    "### 2.2 Robustness metrics \n",
    "\n",
    "Score explanations using the following robustness metrics:\n",
    "\n",
    "* Local Lipschitz Estimate (Alvarez-Melis et al., 2018; 2019)\n",
    "* Max-Sensitivity (Yeh at el., 2019)\n",
    "* Avg-Sensitivity (Yeh at el., 2019)\n",
    "* Continuity (Montavan et al., 2017)\n",
    "* Input Independence Rate (Yang et al., 2019)\n",
    "* Consistency (Dasgupta et al., 2022)\n",
    "* [Relative Input Stability](https://arxiv.org/pdf/2203.06877.pdf) (Chirag Agarwal, et. al.)\n",
    "* [Relative Output Stability](https://arxiv.org/pdf/2203.06877.pdf) (Chirag Agarwal, et. al.)\n",
    "* [Relative Representation Stability](https://arxiv.org/pdf/2203.06877.pdf) (Chirag Agarwal, et. al.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 39036,
     "status": "ok",
     "timestamp": 1665161586094,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "K8VhMuX_PRII",
    "outputId": "96ee3641-4c76-4d9b-a3f9-3fd9ec80f835"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Local Lipschitz Estimate metric is likely to be sensitive to the choice of amount of noise added 'perturb_std', the number of samples iterated over 'nr_samples', the function to perturb the input 'perturb_func', the similarity metric 'similarity_func' as well as norm calculations on the numerator and denominator of the lipschitz equation i.e., 'norm_numerator' and 'norm_denominator'.  \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Alvarez-Melis, David, and Tommi S. Jaakkola. 'On the robustness of interpretability methods.' arXiv preprint arXiv:1806.08049 (2018). and Alvarez-Melis, David, and Tommi S. Jaakkola. 'Towards robust interpretability with self-explaining neural networks.' arXiv preprint arXiv:1806.07538 (2018).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[57.52864385277926,\n",
       " 38.43395822304614,\n",
       " 48.92632463386785,\n",
       " 52.40489011736009,\n",
       " 58.048339504677806,\n",
       " 55.3765551198521,\n",
       " 68.49756565151691,\n",
       " 47.63754124498776,\n",
       " 52.923116734879784,\n",
       " 40.284309498958436,\n",
       " 68.23067270175258,\n",
       " 79.5426162423288,\n",
       " 49.8548827037425,\n",
       " 46.968453472503185,\n",
       " 50.83593110524175,\n",
       " 58.43350321279524,\n",
       " 32.325763130076226,\n",
       " 52.06859743343769,\n",
       " 42.800074602238816,\n",
       " 34.26269973908186,\n",
       " 70.26931166247635]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return local lipschitzEstimate estimate scores in an one-liner - by calling the metric instance.\n",
    "quantus.LocalLipschitzEstimate(\n",
    "    nr_samples=10,\n",
    "    perturb_std=0.2,\n",
    "    perturb_mean=0.0,\n",
    "    norm_numerator=quantus.similarity_func.distance_euclidean,\n",
    "    norm_denominator=quantus.similarity_func.distance_euclidean,    \n",
    "    perturb_func=quantus.perturb_func.gaussian_noise,\n",
    "    similarity_func=quantus.similarity_func.lipschitz_constant,\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,    \n",
    "   device=device,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"Saliency\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 34683,
     "status": "ok",
     "timestamp": 1663607610739,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "auaz5x_0PQVu",
    "outputId": "1baa50f6-587a-4643-f479-1be19f08c487"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Max Sensitivity metric is likely to be sensitive to the choice of amount of noise added 'lower_bound' and 'upper_bound', the number of samples iterated over 'nr_samples', the function to perturb the input 'perturb_func', the similarity metric 'similarity_func' as well as norm calculations on the numerator and denominator of the sensitivity equation i.e., 'norm_numerator' and 'norm_denominator'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Yeh, Chih-Kuan, et al. 'On the (in) fidelity and sensitivity for explanations.' arXiv preprint arXiv:1901.09392 (2019).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.014146048,\n",
       " 0.011706328,\n",
       " 0.016862085,\n",
       " 0.016317796,\n",
       " 0.018953297,\n",
       " 0.015230152,\n",
       " 0.013311529,\n",
       " 0.012152915,\n",
       " 0.045168135,\n",
       " 0.010675438,\n",
       " 0.011723739,\n",
       " 0.009206712,\n",
       " 0.011673499,\n",
       " 0.026382558,\n",
       " 0.01727627,\n",
       " 0.020674637,\n",
       " 0.0151237175,\n",
       " 0.032591835,\n",
       " 0.008827085]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return max sensitivity scores in an one-liner - by calling the metric instance.\n",
    "quantus.MaxSensitivity(\n",
    "    nr_samples=10,\n",
    "    lower_bound=0.2,\n",
    "    norm_numerator=quantus.norm_func.fro_norm,\n",
    "    norm_denominator=quantus.norm_func.fro_norm,\n",
    "    perturb_func=quantus.perturb_func.uniform_noise,\n",
    "    similarity_func=quantus.similarity_func.difference,\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   device=device,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"Gradient\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 35139,
     "status": "ok",
     "timestamp": 1663607552054,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "EJ9wefWzYdc2",
    "outputId": "1ca5dcfc-768a-44f2-c191-a9164e6fc198"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Avg Sensitivity metric is likely to be sensitive to the choice of amount of noise added 'lower_bound' and 'upper_bound', the number of samples iterated over 'nr_samples', the function to perturb the input 'perturb_func', the similarity metric 'similarity_func' as well as norm calculations on the numerator and denominator of the sensitivity equation i.e., 'norm_numerator' and 'norm_denominator'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Yeh, Chih-Kuan, et al. 'On the (in) fidelity and sensitivity for explanations.' arXiv preprint arXiv:1901.09392 (2019).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.009212605655193329,\n",
       " 0.007392846047878265,\n",
       " 0.010924143716692924,\n",
       " 0.010722446255385876,\n",
       " 0.01237289048731327,\n",
       " 0.009490462020039558,\n",
       " 0.008615540340542793,\n",
       " 0.009117192588746548,\n",
       " 0.028994327411055565,\n",
       " 0.007189278490841389,\n",
       " 0.007913483306765556,\n",
       " 0.006138150580227375,\n",
       " 0.007428924553096294,\n",
       " 0.017067646607756615,\n",
       " 0.0115343127399683,\n",
       " 0.01353415660560131,\n",
       " 0.00984276831150055,\n",
       " 0.019707508385181427,\n",
       " 0.006467340048402548]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return avg sensitivity scores in an one-liner - by calling the metric instance.\n",
    "quantus.AvgSensitivity(\n",
    "    nr_samples=10,\n",
    "    lower_bound=0.2,\n",
    "    norm_numerator=quantus.norm_func.fro_norm,\n",
    "    norm_denominator=quantus.norm_func.fro_norm,\n",
    "    perturb_func=quantus.perturb_func.uniform_noise,\n",
    "    similarity_func=quantus.similarity_func.difference,\n",
    ")(model=model, \n",
    "  x_batch=x_batch,\n",
    "  y_batch=y_batch,\n",
    "  a_batch=None,\n",
    "  explain_func=quantus.explain, \n",
    "  explain_func_kwargs={\"method\": \"Saliency\"}, \n",
    "  device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 8709,
     "status": "ok",
     "timestamp": 1663607623754,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "yFsFfzrRJFph",
    "outputId": "15a244f6-a8b5-4550-f6fa-757cc6c8132c"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Continuity metric is likely to be sensitive to the choice of how many patches to split the input image to 'nr_patches', the number of steps to iterate over 'nr_steps', the value to replace the masking with 'perturb_baseline' and in what direction to translate the image 'perturb_func'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Montavon, Grégoire, Wojciech Samek, and Klaus-Robert Müller. 'Methods for interpreting and understanding deep neural networks.' Digital Signal Processing 73, 1-15 (2018.\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
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       " {0: [515.9972862848081,\n",
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       "   505.10933636897244],\n",
       "  1: [541.480411733035,\n",
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       "   329.5472632027231,\n",
       "   415.0623317747377,\n",
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       "  4: [],\n",
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       "  16: [2.059391736984253,\n",
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       "   2.654944658279419,\n",
       "   2.330371379852295,\n",
       "   2.4710769653320312]}]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return continuity scores in an one-liner - by calling the metric instance.\n",
    "continuity_test = quantus.Continuity(\n",
    "    patch_size=56,\n",
    "    nr_steps=10,\n",
    "    perturb_baseline=\"uniform\",\n",
    "    similarity_func=quantus.similarity_func.correlation_spearman,\n",
    ")\n",
    "scores = continuity_test(model=model, \n",
    "                         x_batch=x_batch,\n",
    "                         y_batch=y_batch,\n",
    "                         a_batch=None,\n",
    "                         explain_func=quantus.explain, \n",
    "                         explain_func_kwargs={\"method\": \"Saliency\"},\n",
    "                         device=device)\n",
    "scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 1686,
     "status": "ok",
     "timestamp": 1663666926240,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "mSfAjuq60L_x",
    "outputId": "0427b272-189a-45d2-869e-dcf8a566921d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Consistency metric is likely to be sensitive to the choice of Function for discretisation of the explanation space 'discretise_func' (return hash value ofan np.array used for comparison)..  \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Sanjoy Dasgupta, Nave Frost, and Michal Moshkovitz. 'Framework for Evaluating Faithfulness of Explanations.' arXiv preprint arXiv:2202.00734 (2022).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/artemsereda/anaconda3/envs/quantus/lib/python3.9/site-packages/captum/_utils/gradient.py:56: UserWarning: Input Tensor 0 did not already require gradients, required_grads has been set automatically.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": "[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return Consistency scores in an one-liner - by calling the metric instance.\n",
    "quantus.Consistency(\n",
    "    discretise_func=quantus.discretise_func.top_n_sign,\n",
    "    return_aggregate=False,\n",
    ")(model=model,\n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"Saliency\"}, \n",
    "   device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Relative Input Stability metric is likely to be sensitive to the choice of function used to generate perturbations 'perturb_func' and parameters passed to it 'perturb_func_kwargs'number of times perturbations are sampled 'nr_samples'.  \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Chirag Agarwal, et. al., 2022. \"Rethinking stability for attribution based explanations.\" https://arxiv.org/pdf/2203.06877.pdf.\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/artemsereda/anaconda3/envs/quantus/lib/python3.9/site-packages/captum/_utils/gradient.py:56: UserWarning: Input Tensor 0 did not already require gradients, required_grads has been set automatically.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": "[0.9370962955664959,\n 1.400342565815413,\n 0.8362847066070609,\n 0.9300563738327268,\n 0.34368543547441677,\n 1.80912062730827,\n 0.6125925506956547,\n 0.6466403537291399,\n 0.6713025894279046,\n 0.5676414947631669,\n 0.49859090807245027,\n 0.6546771069761413,\n 0.4099039934179301,\n 0.6446867059212764,\n 0.5638572657567565,\n 0.8077426449301647,\n 0.6668300363658602]"
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return Relative Input Stability scores in an one-liner - by calling the metric instance.\n",
    "quantus.RelativeInputStability(nr_samples=5)(\n",
    "    model=model,\n",
    "    x_batch=x_batch,\n",
    "    y_batch=y_batch,\n",
    "    explain_func=quantus.explain,\n",
    "    explain_func_kwargs={\"method\": \"Saliency\"},\n",
    "    device=device\n",
    ")"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Relative Output Stability metric is likely to be sensitive to the choice of function used to generate perturbations 'perturb_func' and parameters passed to it 'perturb_func_kwargs'number of times perturbations are sampled 'nr_samples'.  \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Chirag Agarwal, et. al., 2022. \"Rethinking stability for attribution based explanations.\" https://arxiv.org/pdf/2203.06877.pdf.\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/artemsereda/anaconda3/envs/quantus/lib/python3.9/site-packages/captum/_utils/gradient.py:56: UserWarning: Input Tensor 0 did not already require gradients, required_grads has been set automatically.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": "[49.901998793079876,\n 53.24123943072003,\n 39.92974167614703,\n 42.65079933016114,\n 38.65713318786283,\n 46.6123852928791,\n 59.79080469324747,\n 46.94594190010342,\n 51.627784929029886,\n 39.626800133853514,\n 56.78942750839559,\n 58.43638515076417,\n 39.36197897635456,\n 41.64708400693029,\n 36.29111286187993,\n 50.444240504745466,\n 45.176516758881334]"
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return Relative Output Stability scores in an one-liner - by calling the metric instance.\n",
    "quantus.RelativeOutputStability(nr_samples=5)(\n",
    "    model=model,\n",
    "    x_batch=x_batch,\n",
    "    y_batch=y_batch,\n",
    "    explain_func=quantus.explain,\n",
    "    explain_func_kwargs={\"method\": \"Saliency\"},\n",
    "    device=device\n",
    ")"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Relative Representation Stability metric is likely to be sensitive to the choice of function used to generate perturbations 'perturb_func' and parameters passed to it 'perturb_func_kwargs'number of times perturbations are sampled 'nr_samples'choice which internal representations to use 'layer_names', 'layer_indices'.  \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Chirag Agarwal, et. al., 2022. \"Rethinking stability for attribution based explanations.\" https://arxiv.org/pdf/2203.06877.pdf.\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/artemsereda/anaconda3/envs/quantus/lib/python3.9/site-packages/captum/_utils/gradient.py:56: UserWarning: Input Tensor 0 did not already require gradients, required_grads has been set automatically.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "text/plain": "[0.2919503263131499,\n 0.032576507420171985,\n 0.20695623932817356,\n 0.18923498415818468,\n 0.1035082179315342,\n 0.11028891911386982,\n 0.14181839842277552,\n 0.11389669029822373,\n 0.11882913572655851,\n 0.2256330430473133,\n 0.04239658104868257,\n 0.22176035349575418,\n 0.13256847929894863,\n 0.18340840013237372,\n 0.0030804017747872135,\n 0.07369939671423234,\n 0.0716779019528837]"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return Relative Representation Stability scores in an one-liner - by calling the metric instance.\n",
    "quantus.RelativeRepresentationStability(nr_samples=5, layer_names=[\"layer4.1.conv2\"])(\n",
    "    model=model,\n",
    "    x_batch=x_batch,\n",
    "    y_batch=y_batch,\n",
    "    explain_func=quantus.explain,\n",
    "    explain_func_kwargs={\"method\": \"Saliency\"},\n",
    "    device=device,\n",
    ")"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "eBh5Z5teZoM-"
   },
   "source": [
    "### 2.3 Localisation metrics\n",
    "\n",
    "* Pointing Game (Zhang et al., 2018)\n",
    "* Attribution Localisation (Kohlbrenner et al., 2020)\n",
    "* TKI (Theiner et al., 2021)\n",
    "* Relevance Rank Accuracy (Arras et al., 2021)\n",
    "* Relevance Mass Accuracy (Arras et al., 2021)\n",
    "* AUC (Arras et al., 2021)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 1737,
     "status": "ok",
     "timestamp": 1663605966398,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "F5GOtuP3n-f5",
    "outputId": "a4c9956c-5d6c-4cdf-dfcd-9090d1ac7fec"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Pointing Game metric is likely to be sensitive to the choice of ground truth mask i.e., the 's_batch' input as well as if the attributions are normalised 'normalise' (and 'normalise_func') and/ or taking absolute values of such 'abs'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Zhang, Jianming, Baral, Sarah Adel, Lin, Zhe, Brandt, Jonathan, Shen, Xiaohui, and Sclaroff, Stan. 'Top-Down Neural Attention by Excitation Backprop.' International Journal of Computer Vision, 126:1084-1102 (2018).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[False,\n",
       " True,\n",
       " True,\n",
       " False,\n",
       " True,\n",
       " True,\n",
       " False,\n",
       " True,\n",
       " False,\n",
       " True,\n",
       " True,\n",
       " False,\n",
       " False,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " False,\n",
       " False,\n",
       " True,\n",
       " True]"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return effective complexity scores in an one-liner - by calling the metric instance.\n",
    "quantus.PointingGame(\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   s_batch=s_batch,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"Saliency\"}, \n",
    "   device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 2205,
     "status": "ok",
     "timestamp": 1663605943567,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "B0IquZmioJlA",
    "outputId": "b2274228-a89c-4abf-8024-c951bc976388"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Attribution Localisation metric is likely to be sensitive to the choice of ground truth mask i.e., the 's_batch', if size of the ground truth mask is taking into account 'weighted' as well as if attributions are normalised 'normalise' (and 'normalise_func') and/ or taking the absolute values of such 'abs'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Kohlbrenner M., Bauer A., Nakajima S., Binder A., Wojciech S., Lapuschkin S. 'Towards Best Practice in Explaining Neural Network Decisions with LRP.arXiv preprint arXiv:1910.09840v2 (2020)..\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/dist-packages/captum/_utils/gradient.py:59: UserWarning: Input Tensor 0 did not already require gradients, required_grads has been set automatically.\n",
      "  \"required_grads has been set automatically.\" % index\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.5148162841796875,\n",
       " 0.8962053060531616,\n",
       " 0.5655674934387207,\n",
       " 0.09387124329805374,\n",
       " 0.4196097254753113,\n",
       " 0.9943642616271973,\n",
       " 0.5516382455825806,\n",
       " 0.38236069679260254,\n",
       " 0.26735198497772217,\n",
       " 0.7278314232826233,\n",
       " 0.6226062774658203,\n",
       " 0.09952004253864288,\n",
       " 0.001369201228953898,\n",
       " 0.6229471564292908,\n",
       " 0.9224637150764465,\n",
       " 0.5589882135391235,\n",
       " 0.29845502972602844,\n",
       " 0.23174387216567993,\n",
       " 0.7260722517967224,\n",
       " 0.11046291142702103]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return attribution localisation scores in an one-liner - by calling the metric instance.\n",
    "quantus.AttributionLocalisation(\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   s_batch=s_batch,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"Saliency\"},\n",
    "   device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 1116,
     "status": "ok",
     "timestamp": 1663605944680,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "jGYXsVeJoJ5N",
    "outputId": "ab25a758-345e-44f0-e759-88d8bc0c59d2"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Top K Intersection metric is likely to be sensitive to the choice of ground truth mask i.e., the 's_batch', the number of features to consider 'k', if size of the ground truth mask is taking into account 'concept_influence' as well as if attributions are normalised 'normalise' (and 'normalise_func') and/ or taking absolute values of such 'abs'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Theiner, Jonas, Müller-Budack Eric, and Ewerth, Ralph. 'Interpretable Semantic Photo Geolocalization.' arXiv preprint arXiv:2104.14995 (2021).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.386,\n",
       " 0.996,\n",
       " 0.706,\n",
       " 0.055,\n",
       " 0.547,\n",
       " 0.997,\n",
       " 0.5760000000000001,\n",
       " 0.725,\n",
       " 0.276,\n",
       " 0.96,\n",
       " 0.802,\n",
       " 0.107,\n",
       " 0.001,\n",
       " 0.904,\n",
       " 0.882,\n",
       " 0.605,\n",
       " 0.554,\n",
       " 0.28400000000000003,\n",
       " 0.913,\n",
       " 0.343]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return tki scores in an one-liner - by calling the metric instance.\n",
    "quantus.TopKIntersection(\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   s_batch=s_batch,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"Saliency\"}, \n",
    "   device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 1982,
     "status": "ok",
     "timestamp": 1663605896588,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "Aks45rDRoKjx",
    "outputId": "d1a83314-53f3-42ef-9b7b-0b31339f148f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Relevance Rank Accuracy metric is likely to be sensitive to the choice of ground truth mask i.e., the 's_batch' as well as if the attributions are normalised 'normalise' (and 'normalise_func') and/ or taking absolute values of such 'abs'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Arras, Leila, Osman, Ahmed, and Samek, Wojciech. 'Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI.' arXiv preprint, arXiv:2003.07258v2 (2021)..\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05,\n",
       " 3.985969387755102e-05]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return relevane rank accuracy scores in an one-liner - by calling the metric instance.\n",
    "quantus.RelevanceRankAccuracy(\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   s_batch=s_batch,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"Saliency\"}, \n",
    "   device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 1794,
     "status": "ok",
     "timestamp": 1663605891950,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "Npd9c-43oV73",
    "outputId": "3d1da3e2-c107-4aa9-c7d7-2d0e0bfef259"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Relevance Mass Accuracy metric is likely to be sensitive to the choice of ground truth mask i.e., the 's_batch' as well as if the attributions are normalised 'normalise' (and 'normalise_func') and/ or taking absolute values of such 'abs'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Arras, Leila, Osman, Ahmed, and Samek, Wojciech. 'Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI.' arXiv preprint, arXiv:2003.07258v2 (2021)..\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.5148163,\n",
       " 0.8962053,\n",
       " 0.5655675,\n",
       " 0.09387124,\n",
       " 0.41960973,\n",
       " 0.99436426,\n",
       " 0.55163825,\n",
       " 0.3823607,\n",
       " 0.26735198,\n",
       " 0.7278314,\n",
       " 0.6226063,\n",
       " 0.09952004,\n",
       " 0.0013692012,\n",
       " 0.62294716,\n",
       " 0.9224637,\n",
       " 0.5589882,\n",
       " 0.29845503,\n",
       " 0.23174387,\n",
       " 0.72607225,\n",
       " 0.11046291]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return relevane mass accuracy scores in an one-liner - by calling the metric instance.\n",
    "quantus.RelevanceMassAccuracy(\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   s_batch=s_batch,\n",
    "   explain_func=quantus.explain,\n",
    "   explain_func_kwargs={\"method\": \"Saliency\"},\n",
    "   device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 1819,
     "status": "ok",
     "timestamp": 1663605859543,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "tqFwigFj4ii4",
    "outputId": "e928d573-fd15-4331-8577-87f5976f32da"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The AUC metric is likely to be sensitive to the choice of ground truth mask i.e., the 's_batch' input as well as if absolute values 'abs' are taken of the attributions . \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Fawcett, Tom. 'An introduction to ROC analysis' Pattern Recognition Letters Vol 27, Issue 8, (2006).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.5496032156149311,\n",
       " 0.8378034883871343,\n",
       " 0.5978047258304584,\n",
       " 0.4810583667775295,\n",
       " 0.6088005205623628,\n",
       " 0.6562129605999191,\n",
       " 0.5851947499344192,\n",
       " 0.6883728302277395,\n",
       " 0.6215463549723745,\n",
       " 0.7019519834709333,\n",
       " 0.7085925234251864,\n",
       " 0.559065186133047,\n",
       " 0.4976049816381926,\n",
       " 0.610841403913073,\n",
       " 0.48205099899315945,\n",
       " 0.47184680236897103,\n",
       " 0.6842717134624884,\n",
       " 0.629719089623429,\n",
       " 0.7285726396094813,\n",
       " 0.8325527955872081]"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return relevane mass accuracy scores in an one-liner - by calling the metric instance.\n",
    "quantus.AUC(\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   s_batch=s_batch,\n",
    "   explain_func=quantus.explain, \n",
    "  explain_func_kwargs={\"method\": \"Saliency\"},\n",
    "  device=device)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "lxs_aaUqZ448"
   },
   "source": [
    "### 2.4 Randomisation metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 773
    },
    "executionInfo": {
     "elapsed": 32793,
     "status": "ok",
     "timestamp": 1663667111523,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "Fa6AajO1Z4c0",
    "outputId": "2369f5a7-5e1c-4ca1-dd54-6da02abb66cc"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Model Parameter Randomisation metric is likely to be sensitive to the choice of similarity metric 'similarity_func' and the order of the layer randomisation 'layer_order'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Adebayo, J., Gilmer, J., Muelly, M., Goodfellow, I., Hardt, M., and Kim, B. 'Sanity Checks for Saliency Maps.' arXiv preprint, arXiv:1810.073292v3 (2018).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/dist-packages/captum/_utils/gradient.py:59: UserWarning: Input Tensor 0 did not already require gradients, required_grads has been set automatically.\n",
      "  \"required_grads has been set automatically.\" % index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Model Parameter Randomisation metric is likely to be sensitive to the choice of similarity metric 'similarity_func' and the order of the layer randomisation 'layer_order'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Adebayo, J., Gilmer, J., Muelly, M., Goodfellow, I., Hardt, M., and Kim, B. 'Sanity Checks for Saliency Maps.' arXiv preprint, arXiv:1810.073292v3 (2018).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Return model parameter randomization scores in an one-liner - by calling the metric instance.\n",
    "results = {method: quantus.ModelParameterRandomisation(\n",
    "    layer_order=\"bottom_up\",\n",
    "    similarity_func=quantus.similarity_func.correlation_spearman,\n",
    "    normalise=True,\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": method}, \n",
    "   device=device) for method in [\"Saliency\", \"Gradient\"]}\n",
    "\n",
    "quantus.plot_model_parameter_randomisation_experiment(results=results, methods=[\"Saliency\", \"Gradient\"], similarity_metric=quantus.similarity_func.correlation_spearman.__name__.replace(\"_\", \"\").capitalize())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 2317,
     "status": "ok",
     "timestamp": 1663605829181,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "Ggc8M0VYPqXg",
    "outputId": "ebfd2804-89c4-49cb-db6b-7b666a61880b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Random Logit metric is likely to be sensitive to the choice of similarity metric 'similarity_func'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Sixt, Leon, Granz, Maximilian, and Landgraf, Tim. 'When Explanations Lie: Why Many Modified BP Attributions Fail.' arXiv preprint, arXiv:1912.09818v6 (2020).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.2785277241429084,\n",
       " 0.7636847907139436,\n",
       " 0.49716974138222436,\n",
       " 0.4627671439594901,\n",
       " 0.5571587781387842,\n",
       " 0.6519391260950801,\n",
       " 0.7168172416351766,\n",
       " 0.8194065053937403,\n",
       " 0.5382503839623709,\n",
       " 0.4246806424579798,\n",
       " 0.3732174574133432,\n",
       " 0.5226632786691975,\n",
       " 0.4919609282309529,\n",
       " 0.49361720569078354,\n",
       " 0.4881337121259406,\n",
       " 0.645903774913976,\n",
       " 0.3145225318147408,\n",
       " 0.40125093337452256,\n",
       " 0.4119223151408124,\n",
       " 0.455222863450516]"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return random logit scores in an one-liner - by calling the metric instance.\n",
    "quantus.RandomLogit(\n",
    "    num_classes=1000,\n",
    "    similarity_func=quantus.similarity_func.ssim,\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"Saliency\"}, \n",
    "   device=device)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "id": "JEKC4Jp5ZvDs"
   },
   "source": [
    "### 2.5 Complexity metrics\n",
    "\n",
    "Score explanations using the following complexity metrics:\n",
    "\n",
    "* Sparseness (Alvarez-Melis et al., 2018; 2019)\n",
    "* Complexity (Bhatt et al., 2020)\n",
    "* Effective complexity (Nguyen at el., 2020.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 1791,
     "status": "ok",
     "timestamp": 1665165573395,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "kX8KfQBsbNxX",
    "outputId": "4e6501d1-ec66-4edb-910f-d4007a608b38"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Sparseness metric is likely to be sensitive to the choice of normalising 'normalise' (and 'normalise_func') and if taking absolute values of attributions 'abs'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Chalasani, Prasad, et al. Concise explanations of neural networks using adversarial training.' International Conference on Machine Learning. PMLR, (2020).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/dist-packages/captum/_utils/gradient.py:59: UserWarning: Input Tensor 0 did not already require gradients, required_grads has been set automatically.\n",
      "  \"required_grads has been set automatically.\" % index\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[0.4038726505741572,\n",
       " 0.4417775710056374,\n",
       " 0.43847453487263954,\n",
       " 0.46608260004703106,\n",
       " 0.4141086790933253,\n",
       " 0.45284584706748965,\n",
       " 0.420271762129851,\n",
       " 0.43028661260632267,\n",
       " 0.41026565943758697,\n",
       " 0.39818799234766555,\n",
       " 0.4366796556762597,\n",
       " 0.4486218971247016,\n",
       " 0.43187905108771174,\n",
       " 0.49551300177253116,\n",
       " 0.4530533022476297,\n",
       " 0.4529068350009297,\n",
       " 0.39059322088333015,\n",
       " 0.41575436635169527]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return sparseness scores in an one-liner - by calling the metric instance.\n",
    "quantus.Sparseness(\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"Saliency\"}, \n",
    "   device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 1753,
     "status": "ok",
     "timestamp": 1665166146548,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "DJQ1odjiU7vQ",
    "outputId": "ee97a746-bd42-473b-84c9-da704a75f6de"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Complexity metric is likely to be sensitive to the choice of normalising 'normalise' (and 'normalise_func') and if taking absolute values of attributions 'abs'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Bhatt, Umang, Adrian Weller, and José MF Moura. 'Evaluating and aggregating feature-based model explanations.' arXiv preprint arXiv:2005.00631 (2020).\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/dist-packages/captum/_utils/gradient.py:59: UserWarning: Input Tensor 0 did not already require gradients, required_grads has been set automatically.\n",
      "  \"required_grads has been set automatically.\" % index\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[10.44070243488689,\n",
       " 10.420596971333223,\n",
       " 10.484279878887667,\n",
       " 10.56721230819776,\n",
       " 10.540531584268715,\n",
       " 10.536727456028371,\n",
       " 10.500922736444046,\n",
       " 10.51492837656417,\n",
       " 10.512601491344476,\n",
       " 10.557478675883386,\n",
       " 10.40113705597035,\n",
       " 10.486384748693812,\n",
       " 10.551167703984634,\n",
       " 10.520842420783698,\n",
       " 10.547990322449959,\n",
       " 10.467381022906697,\n",
       " 10.339475828236742]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return complexity scores in an one-liner - by calling the metric instance.\n",
    "quantus.Complexity(\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"Saliency\"},\n",
    "   device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 1707,
     "status": "ok",
     "timestamp": 1663605748068,
     "user": {
      "displayName": "Anna Hedström",
      "userId": "05540180366077551505"
     },
     "user_tz": -120
    },
    "id": "cgSG9akIbP_F",
    "outputId": "faccf6bf-3b86-411d-acda-67315fd72ebd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Effective Complexity metric is likely to be sensitive to the choice of normalising 'normalise' (and 'normalise_func') and if taking absolute values of attributions 'abs' and the choice of threshold 'eps'. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Nguyen, An-phi, and María Rodríguez Martínez. 'On quantitative aspects of model interpretability.' arXiv preprint arXiv:2007.07584 (2020)..\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[50176,\n",
       " 50176,\n",
       " 50176,\n",
       " 50176,\n",
       " 50176,\n",
       " 50176,\n",
       " 50176,\n",
       " 50176,\n",
       " 50176,\n",
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       " 50175,\n",
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       " 50176,\n",
       " 50176,\n",
       " 50176]"
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     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return effective complexity scores in an one-liner - by calling the metric instance.\n",
    "quantus.EffectiveComplexity(\n",
    "    eps=1e-5,\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"Saliency\"}, \n",
    "   device=device)"
   ]
  },
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   "source": [
    "### 2.6 Axiomatic metrics\n",
    "\n",
    "Score explanations using the following axiomatic metrics:\n",
    "\n",
    "* Completeness (Montavon et al., 2018)\n",
    "* Non-sensitivity (Nguyen at el., 2020)\n",
    "* Input Invariance (Kindermans et al., 2017)"
   ]
  },
  {
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   "execution_count": null,
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    "executionInfo": {
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    "id": "Kj_upy9sDutk",
    "outputId": "39cc0619-9324-4493-aaed-efff7f745326"
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "[False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False,\n",
       " False]"
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     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return completeness scores in an one-liner - by calling the metric instance.\n",
    "quantus.Completeness(\n",
    "    abs=False,\n",
    "    disable_warnings=True,\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=a_batch,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"Saliency\"}, \n",
    "   device=device)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "executionInfo": {
     "elapsed": 22232,
     "status": "ok",
     "timestamp": 1663605887578,
     "user": {
      "displayName": "Anna Hedström",
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    "id": "vGWvMb-ns5xZ",
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Warnings and information:\n",
      " (1) The Non Sensitivity metric is likely to be sensitive to the choice of baseline value 'perturb_baseline', the number of samples to iterate over 'n_samples' and the threshold value function for the feature to be considered having an insignificant contribution to the model. \n",
      " (2) If attributions are normalised or their absolute values are taken it may destroy or skew information in the explanation and as a result, affect the overall evaluation outcome.\n",
      " (3) Make sure to validate the choices for hyperparameters of the metric (by calling .get_params of the metric instance).\n",
      " (4) For further information, see original publication: Nguyen, An-phi, and María Rodríguez Martínez. 'On quantitative aspects of model interpretability.' arXiv preprint arXiv:2007.07584 (2020)..\n",
      " (5) To disable these warnings set 'disable_warnings' = True when initialising the metric.\n",
      "\u001B[0m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.7/dist-packages/captum/_utils/gradient.py:59: UserWarning: Input Tensor 0 did not already require gradients, required_grads has been set automatically.\n",
      "  \"required_grads has been set automatically.\" % index\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Return non-sensitivity scores in an one-liner - by calling the metric instance.\n",
    "quantus.NonSensitivity(\n",
    "    abs=True,\n",
    "    eps=1e-5,\n",
    "    n_samples=10, \n",
    "    perturb_baseline=\"black\",\n",
    "    perturb_func=quantus.perturb_func.baseline_replacement_by_indices,\n",
    "    features_in_step=6272,\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"Saliency\"}, \n",
    "   device=device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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    "executionInfo": {
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     "data": {
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       "[True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
       " True,\n",
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       " True,\n",
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    "# Return completeness scores in an one-liner - by calling the metric instance.\n",
    "quantus.InputInvariance(\n",
    "    abs=False,\n",
    "    disable_warnings=True,\n",
    ")(model=model, \n",
    "   x_batch=x_batch,\n",
    "   y_batch=y_batch,\n",
    "   a_batch=None,\n",
    "   explain_func=quantus.explain, \n",
    "   explain_func_kwargs={\"method\": \"Saliency\"}, \n",
    "   device=device)"
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