DAY4_MNIST_DATA_pytorch.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "D7Knnk1YRVdR"
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "from torchvision import datasets\n",
    "import torchvision.transforms as transforms\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import torch.nn as nn\n",
    "import torch.nn.functional as F\n",
    "import torch.optim\n",
    "from torch.utils.data import random_split\n",
    "from torch.utils.data.sampler import SubsetRandomSampler\n",
    "from torch.optim.lr_scheduler import StepLR\n",
    "\n",
    "from sklearn.metrics import confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 252
    },
    "colab_type": "code",
    "id": "aNxnzUiMRofx",
    "outputId": "7d2a2d6c-a0ce-4d8a-d939-7fe2954e5542"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\prabh\\anaconda3\\envs\\boston_house_prices_prediction\\lib\\site-packages\\torchvision\\datasets\\mnist.py:498: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at  ..\\torch\\csrc\\utils\\tensor_numpy.cpp:180.)\n",
      "  return torch.from_numpy(parsed.astype(m[2], copy=False)).view(*s)\n"
     ]
    }
   ],
   "source": [
    "train_transform = [transforms.ToTensor(), transforms.Normalize((0.1307,), (0.3081,))]\n",
    "# valid_transform = [transforms.RandomCrop(28, padding=4),transforms.RandomHorizontalFlip(),\n",
    "#                   transforms.ToTensor(), transforms.Normalize((0.1307,), (0.3081,))]\n",
    "\n",
    "train_transform=transforms.Compose(train_transform)\n",
    "# valid_transform=transforms.Compose(valid_transform)\n",
    "\n",
    "num_workers = 0\n",
    "batch_size = 40\n",
    "train_data = datasets.MNIST(root='data', train= True, download=True, transform=train_transform)\n",
    "valid_data = datasets.MNIST(root='data', train= True, download=True, transform=train_transform)\n",
    "test_data = datasets.MNIST(root='data', train= False, download=True, transform=train_transform)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_train = len(train_data)\n",
    "data_idx = list(range(num_train))\n",
    "split_idx = int(num_train * 0.05)\n",
    "train_idx, valid_idx = data_idx[split_idx:], data_idx[:split_idx]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_sampler = SubsetRandomSampler(train_idx)\n",
    "valid_sampler = SubsetRandomSampler(valid_idx)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "7i_XM3daRpEH"
   },
   "outputs": [],
   "source": [
    "train_loader = torch.utils.data.DataLoader(train_data,\n",
    "                                           batch_size= batch_size,\n",
    "                                           sampler = train_sampler,\n",
    "                                           num_workers= num_workers)\n",
    "valid_loader = torch.utils.data.DataLoader(valid_data,\n",
    "                                           batch_size= batch_size,\n",
    "                                           sampler = valid_sampler,\n",
    "                                           num_workers= num_workers)\n",
    "\n",
    "test_loader = torch.utils.data.DataLoader(test_data, \n",
    "                                          batch_size = batch_size, \n",
    "                                          num_workers = num_workers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([40, 1, 28, 28])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataiter = iter(train_loader)\n",
    "img, lbl = dataiter.next()\n",
    "img.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying the validation data of a single batch\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-7-d643939dd0d1>:6: MatplotlibDeprecationWarning: Passing non-integers as three-element position specification is deprecated since 3.3 and will be removed two minor releases later.\n",
      "  ax = fig.add_subplot(2, 40/2, idx+1, xticks= [], yticks= [])\n"
     ]
    },
    {
     "data": {
      "image/png": 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ll16C2WxGpVJBMpnE22+/Da/Xi+XlZS4gzMHBwcHBwbEtkMlkMBgM6Onpwd69e9HZ2YmnnnoKUqkUarV6U8VsPp/H22+/jbGxsbbb761GJBJh9+7dGBoaQm9vL4xGI8xmM7RaLYAV4QN5BktLS7h69SrGxsZw584dsCyLSqXCnSmbTEsFhPl8PgYGBmC1WnHo0CEMDg6it7cXIpEI1WoV2WwWoVAIt27dQiKRwMTEBCqVCorFIvR6PTweDwwGA5XrCwQC8Hi8bW3YrVKpoNPpaADd6XTiqaeegl6vh0gkuuvr+Xw+DZgnEgnw+XyEQiFEo9EmXP2DwePxoNFoIJVK0dHRAa1WC6vVCpVKhUqlgmq1inw+j1wuh1qthnK5jFwuh3A4jFKphGQyyU04jxjS8JE0fWw0Gpx6tAmQhgV9fX3YtWsXOjs7sXv3bojFYrohkUqltDHnVuwK1Go1XC4XVCoVzGYzBgYG0NPTg0QigampKWSzWSwsLKBSqaBcLm/refZ+iEQiKJVKWCwWHDp0CHq9Hv39/VAqlXA4HBAKhZiYmMCNGzcwPT2NWCyGc+fOIRAIIJfLNfvytwRRnkulUphMJkilUggEAvD5fFgsFmi1WoTDYYTDYfo9qVQKPp8P1WoVpVJpW8+/DMNAqVRCIpGgu7ubbog1Gg08Hg/cbjckEgnkcjkEAgHEYjH93nK5jEAggOXlZTpG2wk+nw+JRAK3241vfvObcLvdNPAdDocRiUSo4vlJnie2Ap/PB4/HQ19fH/r6+qBUKqHRaDA/P4+zZ8+iXC6jVCqBYRiqQNdqtZBIJLDZbFAoFHC73VCpVPRnfvLJJ7hw4UIT74rjUcMwDFQqFaRSKR1vPB6PvhdSqRTVapUqr1iWRaFQwOzsLAqFAlKpVFsHIDg4OB4/YrEYYrEYnZ2dGBkZgVQqhUajQaPRQKVSQTgcxm9+85u22dd+WRQKBWQyGQ4ePIgDBw7AZrOhs7MTOp0OCoUCQqFw02Bwo9HA8vLyttoTMQwDhUIBnU4HHo+HQqGARCKBeDwOo9EIh8MBpVKJ7u5uSCQSZLNZLC0t4eOPP0Yul+MCw02kZQLCDMNAIBBg9+7dGBkZwZEjRzA4OEg3vIVCAbFYDLdu3cIbb7xBA8P1eh08Hg9OpxPPPfccDYzIZDIIhULweLxt7dWoVqvR3d2N3bt343d/93eh1WrhdDrB5/M3nIQEAgF27NiB3t5eGgS+fPlyWwSEBQIBdDod9Ho9Tpw4gY6ODoyOjsLpdCKTyaBQKCAYDCIUCiGfz9OJ5tq1a0gkEshkMtwG+BHD4/GoTYFIJEKtVuPUo02AYRia7Pn2t78Nt9uNwcHBu5pvrreKuNfvSaPRQKPR0K8rlUpIp9NYXFykjTvJOKtWq9tqU/OgSCQSGAwGDA8P44//+I+h1+uh1+tpwDSfz+O//bf/hpmZGXz88cfwer1tVx5GbJn0ej127doFvV4PsVgMoVCIPXv2oLu7G9euXcONGzfo98zMzCCbzSKfz2/7kjCSsNRoNDh69CgGBwfR1dUFq9UKtVoNtVoN4Isxt7rjdD6fp1ZYAkHLbMu2jFAohEKhQEdHB77zne/AbDZDp9OhXC4jmUwiEolQxfN2fgceBXw+H0KhELt378arr74Ku92Ozs5OvP/++7hz5w4ymQzK5TJ4PB5kMhm1p9FoNNi7dy9sNhuOHz8Oj8dD7Uj+1b/6V1xAeJvBMAy0Wi30ej0OHz6MXbt2gc/ng8/nQ6lUQqfT0cM4y7JYXl5GNBrFr3/9a+ph2U7rDwcHR/ORSCRQqVQ4cOAAfvSjH8FoNKKjowO1Wg2pVArXr1/Hp59++sQEhIko76mnnsIPfvADKBQKute7H8vLy3RPtJ32RSqVCgaDAYVCAcViET6fD5OTkxgaGoLdbodKpcLAwAAcDgfMZjMVy9TrddRqNa6CrEm0xMlDIBCgs7MTBoMBIyMjGB4ehslkglAoRD6fRz6fx8zMDG7cuIG5uTn4fD5ks1ksLy/TDW+pVMKVK1cQj8epb4vL5UJ3dzfC4XDbdnAUiUTg8Xg04CIUCiEQCGC1WmGxWNDd3Y3h4WG43W4YDAbI5XKqEtgMcuDo6ekBwzAIhUK4ffv2Y7yrB0MoFMJgMECtVlOPml27dsFisUCn00EkEkGhUEAkElGFFZloXS4X7HY7VZSnUilMTk5Slc2THMT6Mqz2xvR4PNBoNLBarfB6vXjvvfe2jUqYKN9IVrO/vx8ymQwAUKvVcPPmTTq/FIvFpl3n4OAguru7sX//frjdbqjValQqFeqxns/nsbS0hHq9vuXFVqVSQaVSQa/Xw2azQSAQQC6Xw2w2U193hUKBSCSC999/H8lk8iu+y9ZDJpNRFfDIyAj6+/uh1Wohk8mwvLyMYrGIqakpxGIxXLt2DT6fD8lkErVarW3mHmIDoNPpcOzYMVitVrjdbiiVShrwNpvNkEgkcDqdaza2BoMBUqkUkUgEt27dQi6XQyQS2VaBCLFYjIGBAWi1WvT29kKn02F0dBQOhwNGoxFKpRJisZg2v63VasjlcohGozTRnclkcOfOHcRiMYTDYRQKhbbaFBOVKmkkJxaLUalUkMlkMDY2hrm5OSSTSS4gvAVIMsnj8aCjowNSqRSVSgUCgQAWiwUmk4n2h7BYLJDL5XC5XJDL5fB4PFAqlchkMpiYmACwokJq114aG6lgFQoFVCoVfY9INVg8Hse1a9dQKpW2dTUCn8+Hw+GAWq2m6z15NrlcDrlcDplMBrOzsyiXy8hms5BIJDCZTJBIJHjhhReQyWRw/fp1xONxTE9Pc5ZFHE8kDMNAIpHQip2NkrGFQuGJCW5uBblcDpPJBKPRCJPJRK2vniQYhoHdbodGo8HQ0BAV4JC9D7BS9UWEapFIhNrIicViGqtYXFxENBpFKpVCpVJpqz3femq1GsbGxmjlidvtRigUQiKRQDAYRDgchs/nw+zsLPVXBkAtxl588UUsLS3h7NmzSKVSbXVG+rIIhUKIxWIoFAqYTCZaaV0ulxEMBrd0XnK5XLDZbDAYDLBYLCgUCkin0/TstZWf0RIBYZFIhP3796Ovrw/PPfcchoaGqNJ3cXERc3NzOHXqFH7xi18gl8shHo+vyaiwLItMJoPf/va3sNvtGBgYgNvtxo4dO8CyLM6fP9+WAWGGYSCVSiEUCqmUnpSA7969G0eOHMHQ0BAOHTpEFZpbmZiJonPv3r3YsWMHbt26hffee+8x3NHDQSZSp9OJ3/3d34Xb7YbNZoNcLqf3SyZhuVxOy5rlcjkajQbq9Tri8Thu3ryJubk5/PSnP0U0Gn3iVY1fBqlUCqVSidHRUbzwwgvo7OzE6Ogo3nvvPZw6dWpbBISJ+lmr1eLw4cPweDz40Y9+BIvFAgAolUr49//+3+P8+fOYmppqWkCYYRg8/fTTeP311+FyudDR0UETHul0GgsLC1haWsJHH32EQqGwpZIchmHg8Xio9YTVaoVQKIRQKIRSqYTL5UKlUsEzzzyDubk5XL58+YkMCKvVanR0dGDXrl341re+BZPJBIvFAoZhaNDvzTffhNfrxblz5xCLxdBoNNoqWEEsENxuN37wgx+gq6sLEolkjbXBasuS3t5e+vlcLofDhw9jZmYGv/jFLxAIBLZdqbJCocCLL76I7u5u7N27F2azGSqVak1DV7JO1et1FAoF+P1+XLhwAcFgEFevXkUymcTExAS1Xmmn9wNYWQ+sViu1yJDJZMjlckgkEvjkk08wPj6OSCSCWq3W7EttachBk1j/DA8PI51OIxaLQSgUoqurC2q1Gjt37oRWq6WWEkajEUKhEMDKwezMmTNYXFwEsLI/DgaDzbyth4ZhGJjNZphMJnz961/HgQMH4Ha74XK5AKzcW7FYRCKRwJUrVxCJRBCPx9v+cH0vhEIhdu7ciY6ODnz/+9/HyMgI0uk0Fc4Eg0HMzc3h1q1btGLLZDLhwIEDcDqd+O53v4tGo4H3338fPp8PP/3pT7mAMMcTyeqEk0ajgVwuv+tr2snW63GgUqngcrngdrtpNTKJx6z+2M4Qe9Pe3l6cOHECe/bsWVMFBqx4A3u9XgQCAZw/fx5GoxHf+c53oNPpIBAIUKvVcPv2bXi9XoRCIZRKpSbe0ZenUqngk08+gUAgwNTUFBwOB27duoX5+Xn6ThABzdGjR/Enf/InMBgM8Hg80Ol00Gq18Hq91GIum80+MfEZiUQCrVYLl8uFffv2YXl5me774vH4ls5LQ0NDOH78OHbv3o2DBw8iHA5jcnISFy9exOTkZOsHhIknoVarRU9PD3p6eqBWq8Hj8ZBMJpHL5XDnzh3cunULs7OzyGazm3pVLi8vI5lMgs/nY2JiAoVCAUtLS4jFYqhUKk24u4eHeCBLJBLs3r0ber0euVwO5XIZIpEIAoEAO3fuRG9vL6xWK0QiEW1CQ2wTyuXyXQdvPp8PgUCArq4uaLVa2um8t7cXx44dg9/vx9zcXBPvfAXiRyuVSmEwGGAwGKg3j8VioZ7BlUoFCwsLSKfTtFQum80im81CLpdDrVZTpY1IJILNZgMAHDp0CKFQCKdOnWrLREEzIb+brq4u9PX1YXBwkKp2iCr7q4T4K0okEkgkEtTrdXr4e1TjnDR8kslkMJlMsFqtGBkZgd1up55QAFCtVqk1SzMz5MS71Gw2U8V/JBLB/Pw80uk0AoEAYrEYfD4fVQ1vZcO2vLyMQqFArQ2USiVMJhNkMhkNQJDS1P7+fggEAiwuLjZVKf1VI5PJIJFIqHWN0+lET08POjo6YLFYIJVKkUqlUCgUMDk5iXA4jJmZGQQCARSLxbYKUhAbEqVSiaGhIVoJQJQ0qxsTEpU8mZeFQuGaBKVcLkd/fz8kEgmuXr26LRR8YrEYdrsdVqsV3d3d6OzshFarpd7Kqy0hUqkU0uk04vE4AoEAlpaWcP36daTTaQSDQeTz+bYNYvF4PKhUKvT29sLlckEgEKBcLmNiYgI+nw/xeLztFM/NgCTqDQYDHA4HVCoVeDweXY/sdjv27t0LuVwOt9sNuVwOhUIBPp+PYrGIRqOBQCCATCaDK1euwO/3AwAdn+0EwzBQq9WQy+UYGRlBZ2cn+vv7YTKZoFKp6BrMsiwtYbbb7Th8+DACgQA+++wzFAqFbWNTQ5SMfX190Ov1tAKBeDCOj49jfn4eS0tLWFpaol7uRBBRr9cxPj6OfD5PfT9J1Y/L5aLWLuVyudm3umXIPpDMw6sTcARSyVapVFCv1+m5ivS9IHs3stdZPUfl83nUajUEg8FtExAk5ySdTgeVSgWFQgGFQgGpVAqFQgEAa87XpPq2UqlgaWkJxWIR6XSaimnadWyt9tkeHh6G2WymFbbruXr1KoLB4JYCneSZtOtz2Qrrx86TBplD3G43+vv7YbVaaYUyABqH8Xq9+OyzzxCLxTA/P49yuUxts8i5NRqNIhgMbpsz02oBXqPRuMums1qtUkHEuXPn4HA4IBAIIBQKIZfLodPpYLPZ6JyznYQjG2E0GqHX62G329HR0QGz2Yze3l5UKhWqKid7nc0g+ySPx4Pe3l5YLBZIJBJqRVcoFLY8HzU1ICyRSDAyMgK3243nnnsOfX19UCgUYFkWc3NzmJqawsmTJ3Hy5Enk83mkUqlNb6xWq2FpaQmJRAK/+tWvoNfrMTk5iXg83nZBPz6fT73BfvjDH2J4eJgqhMvlMqrVKlVikQAdaRLh8/nwm9/8BpFIBFeuXFmzwROLxZDL5fjxj3+MPXv2wOFwQKfT4YUXXsDg4CDeeOMNms1pJnw+HwqFAmazGU8//TQ8Hg++853vQK/X003L/Pw84vE4/u7v/g43btyggZpIJIJoNAqNRgOz2YyDBw/iD//wDyGTybBjxw709PSgr68Ps7OzuH37dtu9G81GJBJBJBLh2Wefxfe+9z26OPL5fKpS+SrfH5FIRMsfLRYLVaGRwOWj+LdVKhV6enpgt9tx6NAh2Gw2nDhxgpbItyImkwl9fX2Ym5vD+Pg4Ll68iHfeeQe5XA6xWAzLy8vUYmerTE1NQSAQQK/Xw2KxoKenB8eOHYPL5cLTTz8NkUgErVYLlmXx8ssvY35+Hm+88QZVpm1HDAYDTCYTbSDh8XiwY8cOmlxLp9OYnJyEz+fDf//v/x3RaBTT09M0YNNO8Hg8Gjj41re+RYPeq5uVkqYYN27cwI0bNxCLxRCLxaiHmN1ux65du6BSqfDSSy/hzp07tOFIuwcI1Wo19bI/ceIEbDbbXQclcjj0er24ceMGxsfHcfnyZcTjcfh8PtpQhFhftRukisLhcODFF1+EzWaDSCRCOBzGr371K8zPz2N2dpZr6LoFpFIppFIpurq6sGfPHlitVgAryRRi1TMyMkITNcvLy8jn86hWqwiFQshkMnj77bfh8/lw+fJlhEIh+rPb7WAlEAjg8XhgtVrx+7//+zh06BBNAhNffPI+iUQi6HQ6DA8PQ6fTYXJyEqFQiDZL3g6qdHIm+IM/+AP09vZix44d0Gg0CIfD8Hq9+Lu/+zv89re/RbFYRLFYpJ7BBIZhMD4+jo6ODjgcDrjdbuzbtw8DAwMYGxuDSqW6651pdUjyxGAw4Bvf+AbMZvOav2cYBnq9HiqViibkDAYDDYSLRCIqkimVSvD5fPRdqVarWFxcRDKZxK9//WvMzMxsi0AfaQhG7K26urrQ1dVFG2ExDLNmHSLNTqPRKH75y18iEAjgxo0bSCaTqFarbbuG83g8qNVq6HQ6fO9738PIyAhtyLmen/zkJ7h06dJ951CWZekzedC9Nkd7QJLfarUaBw8exPHjx6HX69fYZqTTaXi9Xpw9exb/6T/9JxoIHhwcRD6fh0ajQaVSoaKR8fHxbVWh0Wg0MD8/D6/Xe9eetlqtolqt4vr16/D5fBgcHATLsrDZbNizZw8YhsHw8DDkcjkVEmxn+vr68PTTT2P37t04fvw4hEIhTfJ6vV6MjY3hrbfeQiaT2fD7GYaB0+mE0+nEkSNHcOLECbquEe9mUpW6FZoS3WAYhmYEurq6aEdGsViM5eVlmpWdnp6m2dmtZPobjQZqtRoikQjNZBaLxbbbEJLmPTabDWazGXq9HjKZDNVqlSr8NBoNzXzncjkqD19aWsLc3BwSiQSSySRVTZKmfYVCAYuLi7T5jcFggEqlgsVigVKpbOp9k+C20WhEX18fLBYLBgcHaVMekUhEfRdv3bqFcDiM+fl5mkkRiURIJpPIZDL0oL2wsIA7d+7AZDKhv78fQqEQKpUKGo0GarUaSqWy7ZR7W0Uul9MsuEgkov5yZMPyIJAMKOmcarfbqWl8MplEqVRCLpeD1+v9Sp+lRCKBUqmEx+PB4OAgstksYrEYgsEgUqnUA/3b5J0hB3GJRAKFQgGj0Yienh4YDAZ0dHTAYDDQJpXAvRuxNQOWZRGJRHDnzh3MzMxgcnISXq8XyWQSxWLxodWYJNubzWapGufOnTsol8vo7u6GUqmkilGHwwGGYWC1WlEsFmmjue0C8f3q6OigSSWn00kV0/V6HZlMBqFQCGNjY/D7/QiFQm3tDSYSiahXnFarhUqlWmMTsby8TBWgd+7cwfT0ND14y+VypFIpZDIZ1Go1yGQyqNVqxGIxaLVa2pGaWCi02/Mhyk2r1QqbzUatnVbbWDUaDeTzeRSLRczPz2N8fBxerxfRaBTZbHZbdFMm6lWtVguTyQStVgsej4dGo4FCoYBCocD5Bm8BUrqs1WphNpthtVrpfowcNIlfd7lcRjQaRbFYpKq9eDyObDaL2dlZhEIh+n61GzwejwbA+/v74fF4YDabIZfLUa/XaRNTMq+Uy2VoNBo4nU40Gg1oNBq6b1Qqlcjlcm3//hH/ZIfDAZfLBavVCoZhUCwWMTs7C7/fD7/fT9fczdZd4mmfSCSgVCrpHGaz2ZDP5zE+Pv6Y7+zBEAgEdC9LvMo7Ozuh1+vR1dUFg8FAD74kyUbWLYVCQff8BoOBqvFJQoucq0jQr16v0/MEeVbttkYBK3MHj8ejZ0iLxQKNRoPh4WF0dnbSCpfVYpvVY0UkEtEGloODg9Dr9Wg0GojFYpibm0MqlWrWrT0QfD4fMpmM9sEgCk+j0Ugb5SoUCtofZDUejwdHjhy5ryJ6eXkZsVgMpVIJiUSCepm3W/zhfvB4PAiFQroXXL3X8fl8CAQCbZeA3AokhmIymWAymWggmFTCEcGe3+/HzZs3MT8/j2KxSJObLpeLKjcjkQiSySSi0Si1r9xO3C8ASfpoxGIxzM7Ool6vY+fOnRAIBDQ2dT9lbDtD5iBSYUqqj8kej1S23E+ARiqpVtvUkcrNbDYLn89HK4W2QlMCwsSX0+l04pvf/CYGBweh1WohFArpxvbMmTN455136KFyqxu6arWKsbExuoC3Y1mLXC7HiRMn0NPTg4GBAdhstru8echkHI/H4fV6cfHiRfz0pz+liklSlrD+3oVCIU6ePIm5uTnodDp4PB4YDAbodDoYDIbHfq+rEYlEUCqV2Lt3L/WXcTqdVBWay+Xw8ccfw+fz4Z133sHCwgKKxSKq1So9NJHfdzabRTgcpoeHXbt20UFHNoVdXV2o1+uYm5tDPp9v6r0/ang8HpxOJywWC1wuF8xmM27evIlbt27RgN1W4fP58Hg8MBqN2LlzJ1wuFw4ePAi73Y7r16/jwoUL8Hq9tKnjV3kQ1el0cDgceOWVV/D9738fmUwG4XAYJ0+exPj4+AP5MJGFvaOjAx6PhwaZNRoN7HY7LWUh/21VWJbFyZMnsbS0BK/XS8uTCoXCl5r/iMook8nQZmDj4+MYGBiAVCqFw+HA4cOHIZfLcezYMaRSKczOzkKr1eL69euIRCKP+E6bA8MwMBgM0Gq1eO211/DSSy9BrVbTkm6GYZBMJjE5OYlbt27hL/7iL5BOp2m5VDseJAHQpkU9PT1wOp0wGo1UnddoNFAul/GLX/wCZ86cwdzcHAKBABqNBhqNBj2IEgWWWq1Gd3c3xGIx+vv7qcVToVDA1NRUW5XkkkCKVqvF3r170dHRsSZ4x7IsbR43PT2NhYUFvPnmm/j1r39NP9+O+5KN0Gg06OrqwuDgIAYHB+mhm6hX8/l8WyqfHzd8Pp/ajuzfvx979+6lhwGWZel7BQCRSATvvfce/H4/zpw5Q61IiF3L47Bu+qogPslWqxU/+tGPMDw8TMUApPrr0qVLuHr1KhKJBEKhEA4dOoQf//jHUKvVtHHaH/7hH2J+fh5+v58m/Nt1vBmNRvyTf/JP0NHRgSNHjkChUGB+fh6xWAw/+9nPcOHCBWpTdL97LBaLmJycRK1Ww4kTJ6DRaHDkyBF0dXXh2rVrLWEZtxkKhQJutxsWi4U2lz548CDUajU9PxIrAzIOiB0COTutr+BYXclhNBrpv0X2PrlcDu+//z5u3759l+q6HeDxeJDJZHjqqafg8Xhw9OhRam1E9i8kCAHcLXYQCoW0kaXH40G5XMb4+DiCwSD+w3/4D7hy5UozbuuBkclk6OzshEajQW9vLwwGA44cOQKj0YjOzk76LDbixIkTOHjw4H3HVqlUwvnz5xEMBnH27FksLi5icXGxbRt6boZYLF4TfCJ2fQsLC/j5z3++bW3jBAIBZDIZ9u/fj/7+fnR3d0On09E5JBaLYWlpCR988AF+9rOf0YRAX18ffvjDH8LpdMJsNqNWq+H8+fNYXFzE5cuX4fV623a9flhI8s3r9eKXv/wlduzYgSNHjkAmk6Gjo4M2c9+OMAwDh8MBp9OJZ599Fq+99hpEIhHtg/WgP8vlcmH37t2wWCzg8/lUyOXz+fD2228jn89v+f1qSkBYKBTCbDbDZrNBp9PRUmyWZRGNRhEKhRAOh5HJZFAqlR74QNGuGTmBQACVSgWj0QibzQabzQaZTLZGlUUO3ET55/f7MTExgfn5eaoaISVjG0GC5Ks3yOTwvtmC+LiQSCTQ6/UwmUwwm83U54plWdpMkKghYrEYUqnUPQ/WZEMXDAZhNptp2aparaZdZcVicdPv+1FBFA9E+drR0QGXy0W73RO1WjQa3fLBkTwji8UCu91OG7rIZDIUi0Ukk0ksLS0hEAggHA5/5ZYR5F0lTSDIodnj8WDnzp1b3ojweDyqcibPyOFw0KQBUbptRqVSQalUokGPZs85qVQKfr8f0WgU6XT6oVTgm0EOQsT/ioxD0hiBKKxrtRr0ej2MRuOaTGW7w+fzYTab4XA4qJpGKpVCLBYjl8vRZz85OYn5+XkkEglayt2O908UIGq1mirT1s+T1WoVpVKJeqAR25bNqNfrUCgU0Ol06O7uhlAohNFopOs76RlAVBatvEEWiUS0w/Z65XS1WkWtVkMymUQ2m8Xc3Bzm5uYQDofbKui9VcRiMS3LJqVqJOhNApSPKiDM5/OpcoR0hheJRGvey3q9TtXJuVwOtVqtpZu1EPWeXC5HR0cHVTwSJREAWhlGupYvLCxgZmYG4XCYqoHT6XRLj5mtQBItdrsdLpcLJpMJGo0G1WoVxWIRCwsL8Pl8mJ+fx8LCAlKpFKLRKBYXFzE9PU07bJPKhkKhALVaDYVC8UCHolaBHIpVKhVt2EhU0l6vF36/H4FAAIlE4r7VBjweDyKRCAqFggpAWtX+aiNIqXZ3dzcVOajV6jUetwDW9JMga45UKl3jdbrZcyJWLBqNhopQlpeX2+o5rYb4TisUCjidTnR3d8Nut8NsNkMmk0Eqla752tXPZfWfie+wUCiEWCyG0WjE8vJy2wRseDweFAoFDeD19PRAq9XCZrNRz//VZ+z1kP0tYbP3p1KpwOFwQCgUIhKJQCqV0vM46cOxHVCpVHA6ndBoNABW1qdUKoVYLIZAIIBIJLJt7pVAzpzEy9/pdEKhUIDH41HRRyQSwfT0NPx+P22wTb6HVBKGw2EUCgXq9072KE8iLMuiVqshm80il8uhWq1CIpFAJpNBLpe37by7ESTpplQqIZFI0NHRQS34iE0uqZaMx+PIZDKbqu3JOmUwGKBQKOBwOGCxWKj/eSaTQSKRoPGYB+mj0JQnrlar8dJLL6GzsxMWiwUymQwsy6JUKuE3v/kNzpw5g4mJCSSTySdKXaJSqXDixAm43W4888wztLHIakgg+M6dO5icnMSlS5fw0UcfoVAoUCX1/TaGxMSavECkE3GzyxbsdjueeeYZjIyM0PIKHo+HTCaDc+fOIRAI4OTJk/D7/YjH41sKeKXTady6dQssy+Kzzz6D0+nEgQMHqOenVCrdFgFh0ihCKpVSm4Mf/OAH2LNnDzUmf+qppxAKhXDy5En83d/9HfL5PBKJxKbvC7Eu0el0eP755zE0NITu7m6YzWaEQiHcvHkTn376Kd555x1ks1lqJP9VjlmSzCCJDeId/eKLL2JkZOSBAnAkcE4+SCMs0rhuM+r1Om3UNjk5iYmJiaaX5/r9foTDYZp5/SoCkWQBD4fD+O1vf4uhoSE8/fTT1NtRLBajr68PIpGIqkjI76ldIWWqL730Ep5++mn09fXRTsIsy+LOnTv44IMPMD09jdOnT6NYLCKTybS1ApSUlg4PD+N73/seTCbTGjuh5eVlRKNRxONxzM7OYmpq6r6b2kKhgJmZGQwNDeHll1+G1WqFTCbD8vIy7ty5g1gshpMnT1KFezQa/apv86ExGo14+eWXqd2VXq+nqthYLIZsNov333+fKsbn5+e3rReaXq/Hzp074Xa76eEok8kgmUwiFovRaqUvCwkIfe1rX4PFYkF/fz891K/u7J1MJpFOp3Ht2jWq1pqcnGzZOUgikeDll19GX18fjh49iq6uLlq6TYI0pApsenoan3zyCSKRCMbGxlAul6k3ebspF9dDDtwmkwmvvfYa+vv74XK5wOfzqRXam2++iXPnzqFYLFKbmXq9js8++wyBQIB6uqtUKtrccHh4GBKJBLdv397Uh69Vkcvl6O3tRX9/P0ZGRqDRaDAzM4NIJIK//Mu/xOTkJDKZzKaNtlcjk8ngcDjQ39+PH/zgB7BarbQ5czAYxMLCQsvOUaSEdmhoCP/iX/wLyOVyiMVipNNpfPzxx0gkElQJTp4FsaohCYGtwOPxoNFo8NJLL8FqtaK/v7+tm2YJhUJqCfHyyy/Ts8D6JNqDQCz9SNPvVockVXp7e/Gnf/qnMJlMUKvVEAqFNBB8r2DwgyASibB7927U63WMjo4in8/jr//6r3Hq1CkEg8GW3tM8CHv27MGPfvQjyOVyMAyDeDyOS5cuYWxsDKdPn6aJ/e2EUCiEx+Oh/WR2795N339SDfjee+/hjTfeoLaVer0e3d3d1KM7n8/jJz/5CcLhMC5duoRMJrPtKpMflNU2UNlsFiKRCAaDgTYA3Q7weDwqfD148CA6Ojqwb98+WqnA4/GouOzq1av427/9WySTSYRCIeRyuTXV3AzDQCwWQyaT4bvf/S6Gh4cxPDxMRXr1eh1XrlzBO++8g4mJCZRKpQfafzdNIUwUNqRBTalUQqFQQDgcht/v3xZNZx4UkUgEq9UKu91OPbLIYkWCYMQbeGFhAfPz81hcXEQwGHygAATJfq9WNbWC17JEIoHBYKC+pERtVCgUEAqFqDL4QdQwxPeHlIoBX3geEeVNqx4WH4TVZvfEIsLpdMJqtYLP54NhGOrpuNXMPvmZRqMRFosFVqsVGo0GcrkchUIBCwsLVB1YKpUeS0KhVquhWCxSZSZRQKjV6g39v+4F2Qyu75ZL3g1STrceEhALBAJIp9MP7dH7KCFJncdBtVpFPB5HPB5HLpejPlo8Hg9arXaNMos0+2tHSOMRtVoNm80Gu91OSwsLhQKKxSJCoRC8Xi8WFhYQCoW2xZpFlHpyuRx6vR5arXbNoYlUbJAN7VY605O+AWSON5vNUCqVtNpFqVRienoa5XK55RsbCYVC6HQ6aLVaiMViaidDbBKSySQCgQC8Xi9tyLNdEYvF0Ol09HBIyrXL5TJV7j3M+koqQYhlj1KppBZXNpsNXV1d0Gg0cDgca7wv1Wo1MpkM0uk0QqEQWJbF0tISqtXqlt7Txw2Px6PNF0mne7IWkT1fKpWC1+ulavNkMrnlhHi7QLyDVSoVrRATCoWo1+uIxWJYXFzE0tISTTKuvvdcLodAIED7CJAGbKSKaHUlUTtBPMrJXCkWi5FMJhEMBmnTvPtBgqlEZUwsNUggp1QqIRgMIhwOt+T4AL5IyioUCqhUKgiFQtpkfHFxEbFYDD6fjzZvqtfr9L8qlWpL+0Iy1xDP12bv574MREFGGsKSCkGtVrvp96zuT1Mqleh6LRQKqYcy8IUooB3OTSR4otFooNPpYLfbYTQa71KM3w9ytt7onSBnB/JB3jVik+V0OuFyuVAqlWiPk1Z/bvdDJpNBr9fTPSE5o+fzeeRyuW1rF6HX69dULgMr70Yul0M0GkU4HEYwGES5XKa/Z7IfisfjSKfT8Pl8iEQiT0TDtK1A9nYk1kX2kO0sqCGQ+AmpelKr1bQKjFSbCoVCWskeCoWwuLiIubk5ZLNZRCKRuxp3kjlGpVLB4XCgs7MTJpMJKpWK9giIRqPwer0P1EyO0JRdkkQioeoasViMer2O8fFxBAIBjI+PY35+vm2DCA8DOfxoNBo89dRTtMkeMSsnKpFsNou33noL58+fp5vjh2nIsz4gHAgEqN9aMyH+TqRbe61Wo80L3nrrLSwsLFB/oq3es81mw759+7Bjxw4cP34ccrmc+leOj49jcnKypUtKtwrxCXO73XjuuefgdDpp8wxS0kJ8fm/fvo1wOHxfJSnJePf29mJ4eBhdXV2oVqtIJBI4ffo03nzzTdo463FtciKRCFKpFD755BPw+Xzs2LEDR48epUGsB2F1IHj1cyCJKbKhXl+SnMlk8MYbb+DWrVuYm5tr+w3eg0I6T0skEly6dAlutxsHDhyAQqHAyMgIOjs7MTk5CbFYjNu3b2NpaanZl/xQSCQSvPLKK+jr68OhQ4fQ2dlJg3/Xr1/H2bNncePGDZw6dQqlUmnbBGhWl4cSRdHqA1S9XsfMzAxmZ2e33FRGr9fTrvaksQ2fzwfLsujq6oLT6QQALC0t0YRnq0JKUOVyOV1DiZcesQ25ePEixsbGtsXaci90Oh2GhoZgtVrB4/FQqVSQTqeRSCQQi8UQj8cfWCFMEnFKpZKW1T377LMwm83Ys2cPVCoVpFLpmsZQJCG5ukfAU089hc8++wxCoRChUAjj4+MtV8pKSv9IY0LgC8/gbDaLVCqFjz76CH/+539Oq8Da2Zd8M+RyOXbt2kUPTGazGcViEfl8HqdPn8bZs2exsLCwYbCOHLhnZmbw7rvvwuPx4Gtf+xpEIhG6u7vB4/EwNjaGRCLRpLt7OIxGI37nd34HLpcLOp0OxWIRV65cweTk5JbnXZ1Oh97eXrhcLjz//PMQCAS4dOkSisUiJiYmkMlkMDs7i0wmg1gsRj0IW+kwrtVq0dXVBZlMhsuXLyOZTOLcuXNIJBKYmZlBuVymVhEkcEfuIZ1Ob0kBKpFIaMC8t7cXnZ2dtOS/3VhtyfjjH/8YPT098Hg89/we0ghrcXERV65coU3XnE4nvvWtb9EAWLVaxfXr17GwsNDS3rhkDXE6nTh27BgGBgag0WhoMuRBIOq99UFhPp9PhUvrK03Jvunll1/G3r178fOf/xy//vWvkc1mqZ0AR+tDBGVqtRrPPvssent7qdc4qaq+du0aLl26hJs3byKbzdLzYDqdxu3btzE3N4dLly5RQV+r21g9TiwWC1577TUaJGUYBgsLC7Q/VDujUqnw+uuvw+VyYdeuXTAajTS5SyqbSaLo7Nmz+Id/+Af4/X7cuXOHCrzIWkYQCoUYHh6Gw+HAvn37sHv3bmqfRmJ4ly9fxmeffbalyqH1PPaAMDlsKpVK6h1MAnThcBjpdLrtX4QHhZTLKRQKGI1G6oNGsiWksVMsFoPX68Xk5CRV6D3Mv0XUX0Q1Qbxgmz1JkcmXbOAajQadPEn5KcuyVDW0enEmQXWSXSLNjAwGAzweD5xOJ/VNIx4t2Wx2W5RsEH84ogr2eDxwOBz074n6PhqNYmlp6b6ecySzrlAoYLFYaFmuRCJBOp1GOp3G0tISfD4f7eL9uCBdtMPhMGZnZ6HT6ZDL5ajlw2rWvx8CgQAMw1CfydVfRzK69Xqdqo/XN6IhPj+kk+z8/Py2eH8eFJL1zufzNHBeq9XAMAxUKhXtxGs2mzE7O9vsy90yRBVDygxJRrenp4f6BpMFmgQgiEKplQ7QjwJim7K6soJA1qNEInHfxC2Zl2UyGZxOJ2w2G93AkL8nHXdJhQOpGmpVSHMRcrhcrehMp9OIRqO0bHC7Q5rrKRQKGhQn6vlyufxAVQvkWYpEIqpOt9vtcDgcGBgYoB3hyXxDfM2Xl5eRzWZRLBapeken08FsNmNpaQkmkwnFYrHlyr9Js1LiUUkSJMSHOpPJIJVKIRgMYnZ2dlsnHoVCIe2boVAo6F4jn88jEokgEAggl8ttOM+SPR/ZJ6pUKjQaDao6Jl6P7QbxQjYYDBAKhTTAmUwmtyyYIWsZeQ71eh2hUAiZTIZ6WGazWVQqFQiFQsjlcqqSbRWIyrlarVKP0snJSaTTaSps2Iyt3AdZo8hzUiqVkMvlqFQq1HqinSABLKPRSL0q16ukSVKJBB5CoRB8Ph8WFhbg9Xqpao+MJWLpSJRsS0tLTT8v3gvyLuv1eng8HqrG28o8QOYYYr9GmnauDwiTPgsb9aIheycSACLVla00rh4UcjbfqKpyu0L2riqViq5PpMK2VCqhWCwiHA5jYWEByWRyzVxB7BDy+TxisVizbqGlEYlEtGkl2deR/g/tNu8CoI20pVIpnXu6urrQ398Po9EIuVwOkUhEkwm5XA7JZBJ+vx/T09NIJBIb7nNW+8GTZB/p3UEqpjKZDLWmSaVSD3UmfawBYYlEApPJBJfLBavVCqPRCKFQiEKhgJs3b+LmzZtP5MDR6XQ4cOAAzeSaTCYIhUI0Gg3qSfjuu+/izp07uHLlCvx+/0MpqEUiEWQyGQYHB3HgwAGYTCYAKyV3rdD0JhQK4cyZMxgZGcHQ0NCaQLlOp0Oj0YDFYoFYLEaxWES9XqcqV3IoTaVSSKVScDqd9Hnu37+fHgrC4TD+4R/+AT6fb8sqi1ZGKBTSg/P+/fvR19dHzf5JgPP999/H+fPnMTk5iampKWSz2bsmC7KZ4fF4UCqVePrpp2G32/HCCy/A7XZDLBYjFovhl7/8JS5cuIDx8fGHUn89KmZmZhCLxeD3+5HJZGAwGNDZ2bnGYoUklsiGjfgzknIKMpESK41QKIT5+Xk6mXd0dMDj8awpjSKHU9Lx/EmqZFhPKpXCu+++i+7ubhw+fBg6nQ7AysZxaGgIMpkMc3NzbRMUlsvlGB4ehtVqxTe+8Q3aPEKpVNIxRQJdU1NT+PTTT6lv+5NEo9HA0tISZmdn77tmyOVymM1mDA8P47vf/S5taLOeer2Oq1ev4vr1602vVLkfRAlvt9shFouporNer2NychJXr159YlRAKpWKqul4PB7y+Txu376NmZmZB54byYa3q6uLrj+k8sBkMtFql0Qigdu3byOZTNJ1nDRZe/nll3H8+HFYLBaaBN65cycA4NKlSy1zIBcKhXC73TCbzTAajbQUnmVZnD9/Hrdu3aKB4YmJiW0/xxgMBnz/+99HV1cXbVrl9XqxtLRErcIe9HdHEnxfxjO1mZDy/PWJ6QchlUrhxo0bmJqawpUrV6iiXq1W4/nnn6fWfXw+H2fOnIHP58PFixdbas0m1hZkbiWWVY9CKU8EMjabDd/+9rfhdruhUqlQKBTw4Ycfwuv1wuv1olartU1CRq1W48UXX0RnZyfsdvsaywdg5b2amZmB3+/HrVu36Ll7aWkJdrsdTz/9NKxWK/bt2weNRgOZTIZMJoO33noLfr8fp0+f3rJlSbPo6urCkSNH0N/fj69//eu0mdNWIFZHExMTmJycxJ07d3D58uW7xqBer8czzzwDm82G559/fkNLDplMBrFYjMHBQRw/fhyXL19GIBB4JPf4OGEYhgqNXC7XhkKB7YhKpcKxY8fg8XgwOjoKl8tFE2vnz5/H1NQUPvroI1y9evWJFAc9Ssh6R+w32u1sTezTyFpitVppzxly7iFCRuKEcOvWLYyNjcHv92N2dnbTRuQqlYp62x86dAhmsxkWiwUsyyIcDiOZTOLkyZM4deoU5ufnH3q/8FgDwgKBACqVCiqVCnK5nB4iiOIqGAw+UNbxfhNSu2yiiccIWbxJ6SDxJCQecnfu3KFdKh8UkgUXCATQarWwWCz036lUKtQIvpnPLJ/PY2lpCTabDbVajSqBxWIx1Go1WJZFR0cHpFIp7c5JAsJGoxFqtRqxWAzRaBQ9PT3YvXs3HA4H+vr6AKxkfPP5PGZmZrCwsND2xvfkwKPRaKi/kdlspgo7koXyer24evUqFhYWNgy2kPeCKDHUajW6urrgdrtht9thMBiQSqWQyWQwPT2Na9euIRaLNdVzjpjQKxQK2Gw2WK1WiMViqjwk2VmWZamaz2g0gmEYRKNRhEIh2oma/Cyv14vx8XEYjUb09/dDr9evOQQ0Gg3qk1UoFFrWc+9xUalU4Pf7IRaL1yzexEu4VCo9sK9zMxEIBHRBJw2KyAGasLy8jGq1Suflcrm8oe3IdoZlWRSLRWSz2U2DNKs99Yiys7u7GxqNZkMlP0m2LCwstPzGmnRa1+l0NFlE1EPkudTrdfB4vPs2eW13SLUX+Z3WajXE43FaYbEVyLsikUig1Wpht9uxY8cOOBwOjIyMQCQS0eRmMplELpfD4uIiwuEwJiYmEIvFqDVNZ2cn+vv7IZfLwbIsFSFoNJqWOsDy+XzqbUmCBmQvHAgEMDY2Rr+23awOHhSiwurp6UFnZydVI6ZSKUQiEWSz2fuuteQdIntG8rverMqhHSBqcXJIJN6wRKG3FSqVCt3nBoNBiMViukd0uVy0AkYkEtGmtK22Zq++h0cdhFxdDdTd3Q2n0wmhUEj3zaRxXztZtIjFYrjdbng8njWVoKQSjvhy+3w+3Lx5E+fPn0ehUEA2m4VGo4HT6YTT6UR3dzekUimEQiEqlQq1iZqbm0M8Hm/p85NKpUJPTw+6u7vh8Xju2nPci3K5jFwuh6WlJdy5cwc3btzAuXPn7lrHSfXk8vIySqUS7S8BfBGbILZGOp0ODocDMzMz1Aay3dBoNLBarVAqlU+EQpgI0jweD/Vq1Wg0tEIyEAhgamoKCwsLCIfDzb7ctofMT0Qh3C5zLomtkWo5q9WKvXv3Ums80gSO+AWTHkRzc3MYGxvDpUuXkM/nN60oJIpjMpd1dXVBr9dDLpcDWImbJRIJLC4uYnp6Gul0+qHv5bEGhJVKJXbt2oXe3l5ablmtVlEqlWijjK0GWUjgilhQrIYYMWez2bbIMhC/JrvdvuZearXamkzC9PT0Qx+WyYGLGMITFfLy8jKWlpZw7dq1pnt9xuNxXLt2DWq1GolEAmq1GkqlEp2dnfjjP/5jVKtVqFQq2mxutfk48WwijSVUKhW0Wi1kMhn1IybyfNKgpFXUQg8KKW8jyuDvf//7cDgccDqd9PBcKBRw5coVLCws4LPPPsPU1NSmiQStVouRkRFYrVacOHGCbl6I9+Ls7Czee+89zM7OYmpqCpFIpGU2g4FAAB999BHkcjlOnTpFN2SknBhYmSv4fD4sFgskEglVwxM7FpJYIAuR3W7HSy+9tKbpJbByMJmamoLP5+MaAgA0QJNKpdqyvGc9xWKRKg+vX7+OfD6P7u5u6p8HgB6Qjh49CoFAgPHxcXz22WcoFApfaiFuJ4iljFwup2WYJOhCAqAajQZGoxG7du3Ca6+9BpvNRpuwrW/gSGxogsEglpaWWn5s8fl8KBQKurYAX6yvL7/8Mnbs2IG3334b4+PjyGQy1Oe/XTa4X4ZKpYJQKIRIJLLlOYE06Dtw4ABeeOEFmEwmdHd302BGpVJBOBxGLBbDO++8g1AohKmpKdrYsFKp0M30lStXkE6nqZpCpVLhqaeeQrlcbqnGYiKRCP39/ejo6IDb7YbJZKJB0Bs3buD06dP0a7dzFYJMJoPNZoPb7YZAIKANXTOZDM6cOYNr167dV1FH7K26urpw4sQJus63u/VcIpHAyZMn0dPTg/7+fvrOCAQCeL3eB6pCkMvlsFqtcDgcePXVV2Gz2bB3717IZDIsLCwgnU7j1KlTuHXrFoLB4Fd4V60FmXe6u7sxNDQEnU6HWq2GZDKJixcvUvFDO0Bs0RQKBbq7u9dUbpCk66VLl+Dz+XD69GncuHEDqVQKuVwOnZ2d2LlzJ4aGhnDixAkolUp6vibnJ5/PR/2mW72pnFarxdDQ0F09QO5Ho9HAuXPncPHiRaoQ3qz8ularIRKJgM/n4+rVqzCZTHA4HJDL5XRvRLBYLNixYwcmJiYeyf09bhiGgc1mw44dO2Aymdo2ybZVpFIpzGYzOjo6cOTIEbhcLiiVSiwvL8Pv9yORSODq1au4cOECFwx+BJCK3kwmg/n5eczPz7e0Jc1q1Go1PB4P3G43XnzxRVgsFvT391OhBLGRWF5extjYGAKBAN59911cvnwZsVjsLquR1chkMpqoPHToEFwuF93fiEQisCyL+fl53Lx5E9PT07QR3cPyWHfIRAlLOggDoB5GpIHEvQ4Rq7NSJCBMFKSrVVrEu450mm1llQ45XOt0Omg0mjXdXInfl9frRSgU+tIm/qTLu0wmg1wupwEx4gmbzWYfxS09NKR0PxaLoVgs0qyKTqfD4cOH71qA7vU7Xf21xPezUqmgVCpR72CWZakqp10g2SiRSAS9Xg+n04nDhw/TpjQMw9Ax5fV6MTY2hoWFhU03tQzDQKFQoLOzE729vfjGN75BS59KpRJOnTq1ZgPZamQyGWQyGdolmgSliKKMZVm6qSWdTAuFAlXDr28SQUpM+/r6aPKBUK/XaSfZdkg0bYXVc+pmG7yN5k/yjImP1pcpa20ViJdeo9FAMBiEQqGgzc4IRPHR0dFBPd7JJn+7BW7utW6ShnPEc5lUGJAknVKphNlsRm9vL5555hnI5XLIZLIN53DSLCudTiOTybT82CIVFWQPQ+5JKBRiYGAAZrMZY2NjiEQidB4iKr9W3os8CogHO0m43Q/iIW2xWDA4OIjnnnsOUqmUqpCISjKRSGBpaQnnzp3D4uLiptVkfr8fyWQS/f39KJVKkMvlMJlMsFgsLXWAFQgEMJvNsNvt0Gq1kMvldAwEg0HMz883+xIfC0KhEAaDge59SdloqVTC3NwcTarcC9KA0GAwoLe3F1qtdk3wv13HW7FYxMzMDAQCAcrlMpRKJSwWC0qlEiQSyZYrEMgZw2w2w+Px4JlnnoHJZKLWHOPj41haWsLc3BxmZmba5iD+KJDJZOjs7KSNDOVyORKJBPL5PHw+X1uNQ6IgF4vFMBgM0Ov1a4KSLMvC7/fj9u3buH79Oq5duwaRSES/fu/evejt7UVPT89djfjIOTGVStEGfq0KOdMQhd5m58aNxs7y8jLm5+dx4cIFeL1e+Hy+Tf8dUl0okUiwuLiIUqlE1y2yNyKQsbt6XWs3yJ6O9AvYzpB1yWKxUOsVkUhEG8MFg0H4/X74/f4tCRi2SzX7o4aISYAVMUGxWEQikaDN91od0qfA6XSit7cXR44cgV6vh8FgoPYQqz3Jl5aWMDU1hTt37mBsbOyetkdkHrHZbHC5XLQXFuk3Qc4WpNojGo1+6erKx+4hbLfbYbVaqR9cJBJBKBSijVjWHwZJgMZsNsPlclGjeJ1Oh4GBAYjF4jUeYY1GA+VyGdVqFTdv3kQoFMLt27cRCASoErBV0Ol06O7uxuDgIHbu3EkVidVqFQsLC4hGo7h06RImJia+tCchn8+npuhEap7L5WhjqFZoEkCC+6TEnwT4HgQSkCCDhcCyLFQqFfr6+vAnf/IniEajuHjxImKxGK5du4ZkMtly3ZU3gpRgd3d34/vf/z6dLFiWxenTp6lis1gs4vLly/D7/Xcpv0nGSqVSwWq1Up+t1TYiwMqzJF1xW31yJqV/ZLNFFHmrO06TxkKkeyf5XSsUCigUCvT19WHPnj0YGRmBSqW6S81YKpVw7do1TE9Pt33DKKFQCKfTCYVCAbvdDpVKBbfbvcYHjajwg8Eg5ubmUC6XaRbX5/PRhaxcLuPatWsoFou0XLtdIUkirVYLo9FIs7Ck2WksFkM6nYZSqYTD4cDu3bupz+f7779PPR/bGRKAi0Qi8Hq9KBaLsFgsNMgikUjw3HPPYXh4GAMDA/D7/XTOJmusw+FAd3c3fbdWl3Gvplwu48KFC5ifn8fc3Bw9cLYyyWQSp06dgtPpxMjICA10MwxDO5l/+9vfxtNPP41wOExL36PRKBYWFjA5OYlardby9/lVQxrAHTt2DEePHkV3dzeUSiWAlTK4dDqN6elphMNhfPLJJ4jFYpiZmUEul9s0aUCazBWLxZYci0TFJ5fL0dnZiZ6eHojFYpTLZVy5cgWTk5NYWFho9mU+NlY3TiMNpmOxGILBIFUvbrRnJ8Evkpx7+umnMTg4SH36iKd3JBJBOBxuy7FWLBYxNzeHer2Ojz/+GBaLhQpqyuUyFhcXcePGDQQCAWQymQ0V0TqdDh0dHejs7MTLL78Mi8VCGw6fPXsW0WgUH374IfUwJONnu0OamBKvWeLHmEgkcOrUKSwsLLRdjxGSGFEoFGuac5O9LqnGiUajMBgMGB0dRXd3N7q6uqjF3mbWOlKpFLt374ZSqcTp06db1i7NZDLBarWiq6sLBoMBcrl8zf0Ui0X4fD6k02mMj4/f1QOBZVmcO3eO9ia5F6VSiVoG+P1+GAwGMAyDzs5Ouh8iyGQyGAwGdHR0YHh4mCY4W/28+aRBEiqdnZ34gz/4A9oIWSqVIp/PI5vN4je/+Q3u3LmDyclJFAqFTc/GAoEAEokEEokEOp1uU6V6o9FAOBymIrUn4Z0gNj0ulws7duyATCbD7OwsgsEgAoHAQ/UMeNx4PB4MDw+jq6sLR48ehV6vp9aVfD4f5XIZt27dQjKZhNfrRTqdxtjYGEKhEF3XNxNNKBQKuN1uuFwufOc734HNZqNWT8ViEZVKBSdPnsT8/Dxu3LhB44VflscaEBaJRDAYDHRwLC8vI5lMIhaLIZPJbBjdJqpWi8WC4eHhNV1D9+3bR6XT6xXC5XIZBoMBc3NztEvo+iBhsyEByr6+PnR2dkKtVkMoFKJYLNIM1MzMzJeyiiDw+Xya8VrdJZME/L6s+vhRQCZQsVhMveAeFBIMJP65q382UUZ/61vfQiqVglgshtfrxdzcHPXDbPXJmGTze3p68M1vfpMG8OLxOMbGxjA3N4fFxUXkcjnMz89vmEggalpS6tDX14f9+/fTICiBBFHvp9xvBcg9kUW3VqutmRNYlt30UCiRSKDRaDA4OIhXX30VJpNpTTk4oVKpYG5uDpOTk21fjkq6uhsMBuzatQtmsxl79+6lh0VgJSBcq9Vw+/ZtnDt3DrlcDvF4HKFQCH6/nx4cib8cADidzrYOCBNIh20yB+VyOaTTaczNzSEYDGLnzp3weDzo7u6ma9knn3xCqy7aGWKvk0qlEA6HwePxaMAGWHl39uzZg3q9Do1Gg0AgALVaDZlMhmq1ikqlArfbjYGBgfv+W/V6HRMTE7h9+zZCoVDL+wcDK/7lN2/eRC6XQ39/P02iEWWSQqHA008/DQC04QMJeItEIqom2qyBxJOCSqWC2WzG7t278dJLL0EqlUImk6FcLtPO3Ddv3sT8/DzeeecdZDIZWvWxGaQ6hlSJtdpYJAFhsVhMA3zEs3RmZgaXLl16okpQBQIB1Go19d8kQatUKoV8Pr+hSIEkX8jh3WKx4MCBA3C5XJBIJGsay6bT6XuWZLYyxH6FZVlcv34dHo8HL7/8MrRaLViWRTQapb0MiLpqPUqlEt3d3RgeHqbNtcRiMW3MODc3h48//hh+v/+JmouEQiFUKhUt5Sc9SsjcPj8/3/Qm2w8K8eImCrL1vQ1INU46nYZaraaVlwcPHqR2B4T174JIJEJ3dzf4fD4uX778+G7qAdFqtejs7ITNZttQ1EGsL8LhMN577727KidZlkUwGEQikbhvEqlarVKxzezsLLRaLQ4ePAi1Wr3mWQKg8xKxIeDxeAgEAttmzG2XQCYRFlmtVjz33HMwm810biBrycWLF3Hp0qV7JqaBlbVNKpVCpVLBbrdvGs8gVVWlUmlbVFpuBZFIBI1GA5PJhI6ODtTrddrbKR6Pt4Xgymw24+DBgxgYGMCLL764xl4S+MJicnFxERcuXEAoFKLJ2/vtTWUyGVwuF/r7+3H06FEYjUbq7Z/NZpHJZHD69GlcunSJVrQ8Cqu9xx4QNplMtJSlVqshkUggGo3eNfk6nU4YjUb09fWhp6cHFouFNhQjh09STkgUocViESzL0gBxX18ftacYGBjAxYsXcePGjZaZvDQaDXbv3g2PxwOpVEqVDbVaDdPT05ifn6cddr/swUYoFGLHjh0YGBiATqcD8IV5fquU6BLrENLldSsZIiK5JwfvxcVF+P1+2vSJoNVqMTAwQL2lGIahz14ikSAYDOKTTz6Bz+e7Z+amWZAyZY/Hg9dffx1dXV1rMtAikQhdXV0QCASYm5tDJBLZNIvvcDiwY8cOdHR0YP/+/bDZbFAqlWsSK8AXJdAqlQoXLlyA3+9HtVptycNVvV5fcyAic8JWEIvFUKlUMBqNtIvselUB8TVKp9Mt75+2ESTgrVQq6e97cHAQGo2GlkparVYoFAr6PURZ3dfXB6lUSi1XkskkRkdHkUqlMD4+DoVCQZN0W+3k3IoQb1jif2swGKgndyqVQigUwuXLl3Hr1i2Ew2HE43Ho9Xr09fWhUCjgmWeeQTgcxu3bt1syGLVViMIyGAzi5MmTtGSOqI5WB2ScTidtnLC6aYJarQZwd6kcWXeXl5eRSqUQj8exsLCAxcXFtkmypNNpnD17Fj6fjzZo7evrg0KhoNVK5L6VSiW1lzCZTHC73dizZw8SiQS18rlx4wbK5TIKhUJL7EseFPI+bPXaie0Rqcjo6emhSaRCoYC5uTl8+umnCIVCuHr1KpLJ5APb0kQiEVy/fh0dHR3Q6/UPfW+PGoZhIJVKqYXK6sbKmUwGiUQCZrOZNg2RyWRQKpXQarX0nVpcXMTJkyfbUvW6HrFYTM8EWxUAuN1u+jEwMACbzYbh4WHqeVqr1ZBOp2nTn7m5ubaZW9bDsixyuRwuXLiAqakphEIhuj5JJBIcPnwYIyMj8Pv9iMViCIfDiEQi9Iyza9cuvPrqq7BareDz+Uin01SJdfr0aXpAbcd558ugVqsxNDSErq4uKsSJxWJYWlrC7du34fV6W97Lfj31ep368ZM+Oust0Xbt2gWlUkmbujscDlgsljX7vo2oVCq0oVwrjyWhUEj9/Ymd1Wqy2SzOnj1LGzBtpBDO5/MPZYtBbPqEQiG1ICGQfZPD4cChQ4cgEAhw8+bNh7/RxwipwlapVLQCCvhCfOX3+/Hee+/B7/e3vKrzfqy2W1EoFHR9rlarSCaTtMkp2Y+sRigUUqsJoujs6+uDUqmE0+m8610k1Go1XLp0idq5+P3+tjtfPihGoxFHjhxBT08ParUaYrEYTp06haWlpbZJxMlkMtjtduh0ug2rKhiGoZY8IpGINrZXKpV07BCq1SqKxSLMZjMGBgZgsVgwOjoKs9kMjUZDYzPVahUTExMIBAKYn5+n1mnVavWRjL3HHhA2Go3Q6/VUUh2PxxGLxdZsbhmGgdPpxODgIJ599lkcO3YMMpkMKpVqjT8oKQskZaqxWAwsy9LNUm9vL/Vqi0QiyOfzuHXrVstYA2g0GuzatYsqEsmGuFqtYnZ2llpFPAorB5FIhKGhIYyOjrZsQJh0ayWWH/dTAwGg/owLCwuYnZ2l2bt4PL6mOYbL5cLzzz+Pzs5OOBwOaLVa7Nq1CyzLwuPxIBaLUW9C8o61Enw+HyKRCG63G9/85jeh0+nWqHlJQFgsFuNXv/rVPZv6OBwOHD9+HAMDA3juuefuaspInrlQKER/fz/MZjPMZjNkMlnLqewJJIj1MIjFYupB6HQ671IGF4tFjI+PY25uri0aamyERqPB4cOHYbVaMTo6SpUU9+oovroMvqenh36+UChgaWkJfr8fP//5z2lg0GKx0IXrfr7ErQiPx4NSqYRGo4HBYIDBYADwxUErGAzi8uXL+OSTT5BMJpFOp3Hs2DEcO3YM9Xodfr8fU1NTmJ2dbWulMJmHw+EwTp8+jXA4jBdeeOEuT20ej3eXEmarv+96vY5EIoFQKETfpWZbFm2VdDqNc+fOwWw205JsrVYLPp9PPwgKhQJyuRxGo5F+jmVZLC0t4fr167hz5w6WlpaQTqcfSeL3cfOw45vP56O3txdHjx5FV1cXZDIZisUi9U39xS9+gWg0itnZ2Ydab6LRKK5fvw4+n4/du3c/1DV+FZCGsEQNTZRjy8vLtAKju7sbNpsNer0eRqMRNpsNnZ2d9FlfuHAB586d2xYBYYFAsOZMsBVcLheOHDmCAwcO4Otf//pd72ClUkE0GqUB4fn5+ZYOYt0LEhC+ePEibV6lVqvx2muvobu7GwcPHoTNZsP8/DwikQhu3bpFzziNRgOjo6P4nd/5HdqckcxdCwsLOHfuHD0zPWmo1WoMDAygs7MTSqUS9Xod0WgUfr8f4+Pj9/SObVXq9ToymQxyuRw9E68PCA8PD6O7uxtarZba8wD3n8er1Sq8Xi+mp6dbeiyJRCIa7F5tJUnI5XI4d+4c5ubmEI/HH2kAs16vw+v1otFo4OjRo2v+jnilOhwOHDhwAIlEglaWtTrExlGlUkGtVtOAMNnjkoDwRkHSdkMsFtP1SKlU0uovsl+NRqNUzbseoVBI/WSJH/exY8eoNeNmlhG1Wg1msxmzs7O0n1O7+kxvFaPRiMOHD8NgMNC598yZMwgGg22zryEiqnsFhIVCIe23Qt6tjchms0gkErSPk81mw+7du6l4gPz8Wq2GyclJTE9PY25uDqFQ6JHe02MNCG8URCGDhEyYVqsVGo0GBw4cwL59+9DT0wOZTIbl5WVEo1Fks1nqL7b6sNBoNGi5KWnSMTw8DIvFQn8uKZ2KRCL37Vz8VULUiB6PBxaLBVqtli4O2WyWeqiFQqEv7dVEshREaUIUSyzLIpPJIBwOt1wmPBwO44MPPoDVasXw8PCajopEBU5MtcnCPjU1haWlJXi9XsTj8bvuKZfL4fbt27QLo06no4pJYqXxwgsvwOPx4Pz585ienm4pz2mNRgO32w2PxwOVSkUbyBGI8kipVMJut1MLjOXlZWg0GlrKLJfLMTQ0RJU19+rAS8pbV2eHq9Vqy/qHfVWUSiVMT0/D5/OhVCq1TELpXhCfaBKw6ujowOjoKPR6PfXEIplvUoUQiURQLBZpZpyU8pIAr1AopIkrYlVy/Phx8Hg8qhQVCoVrKjBa/TltBZZlqZ8uabwZjUYxOTkJl8uFQCAAHo+HPXv2QCaT4c6dO1QB2s6KiWq1img0CqVSSW1SOjo6IJPJthy82QiyzpGKjEAggEKh0DJz7VYpFovUE6xSqUCn00GhUEAsFkOr1UIqlUIqlVIVpMlkot+rUCjQ0dEBkUiEQqGAeDyO8fFxakvSLsHxBx3ffD4fO3fuhN1ux/DwMO0LQRRoV69exe3btxEMBrfcmG4j6vU6TSy3Eo1GA4VCAdlsFvF4HIlEgtp4PfPMMzCbzTAajVCr1ZDL5VAoFFCr1TQ5BawERPfs2YNwOIz5+fmWu8cHoV6vI5VKQafTYXl5mTZ/JfdsNBqRzWZRqVQgl8shkUjgdrsxNDQEq9W65mctLy9Tm4UPPviAlp+2YwJ3I0gTV5ZlcfXqVfj9fiwuLtLnRCzobDYb3bv29vZCKBQim81iYmICi4uLuHLlCsLhMN1LP0kYDAY69+zduxc2mw1CoRCVSoUGUyUSCRQKRVsm6IAvEtiZTIb6CQNfnBGIuORBIPNWPp9v6Wei1+vR29sLs9m8RphQq9WQzWaRSqWondCjfvcbjQbi8ThEIhFKpdKmQaJ2gmEYKpKwWCxwOp1QqVR3fV07nInuBbF26OnpwfPPP4/u7m5axR6PxxGPx3H27Fl4vV5qw0gU6GazGVqtFk6nEw6HgzYYM5lM0Ol0tLfNZvB4PGp3dPLkSdpfq5XHGbBS/bZr1y4aV2AYho6vSCRCm0WvTiCR5AJp1qdUKiGTydYETdulujIWi+HKlSsYGBigdjqrf89EpGcwGKBSqe6pfM5kMkgmk7TqSa1WQyqVUrEesWWMxWIYGxuD1+v9Suz1HmtAGLi31wyfz0d3dzc6Ozvx0ksv4fjx43RSJ+U8Xq8X58+fh8/nw/vvv78mm0AaApHA549+9CPs3r0bIyMjcLlcGBkZQTKZxNWrV5saENbpdBgeHsbg4CC1LGAYhg6kQCCAubk5GoD6MpAuiHK5HBqNBlqtlgZt4vE4FhcXaZCjVfD5fPjbv/1buN1ulEolqFQqKBQKsCyLWCyGarUKiUSCRqOBDz74AFNTUwgEAkgkEpu+X6lUChcvXgSPx8NHH30EnU6Hb3zjG+jo6MB3v/tduFwu/PCHP0Q+n8e/+3f/jvpZtkqQwmQyYd++fRgaGrpLHQyAHqR0Oh16enrA4/GoQqCnpwd2u502FdRqtdT8nHSqXu83BnyR4SKm+BaLBblcruXel6+aQqGA69evY2FhAblcri0WK+Kv6HQ68fLLL6OzsxMnTpyAXC5fU35SLpfh9XoRjUZx9epVBINBatfj8Xjgdrtp8x4SKCaVHqS5IZmjyTvUKmPmUdFoNKhyKJFIAABCoRBSqRRsNhvm5uZgNptx/PhxmM1mevAOhUJtHRAul8vUI+/KlStIJBLQ6/X0/blXMgnAmnmF/D/LslRt8fOf/5xWwbRjUIuojQQCAS5dugSJRAKlUkmrk0wmE4xGI7RaLUZHR9eoA9RqNdRqNW3mEw6H8dvf/hYLCwuIRCJtExAGHsw/UCAQ4MiRIzh06BBGR0fR09NDlcE3btzAf/kv/wXxeBzz8/NfKohXq9VQKBRazqd5eXkZmUwGUqkUwWAQWq0WJpMJcrkcr7322l1jBrjbkqNcLuPEiRPUz7wdxw6hVqshGo1CrVbTgLBGo8Hy8jJsNhtisRi8Xi8qlQr1PR0YGMDBgwehVCrXPCvixej1evE3f/M3CAQCSKfT22Y9IuXs+XweJ0+eBI/Hg06ng1wux+/93u/h+PHj6O3thdPppPZOJCGVTqdx5swZzM3N4cMPP0Q2m22pcfG4sNvtOHr0KEZGRnDixAlqdUQCP+l0GgqFAlqttm0CE+up1+uIx+PUo3015Cz4oBBLm1YfTxaLBXv27IHNZlszN5BEUTgc/sr8+5eXl6nCcaOAcDuON1IhaLVa4fF41lQKEkj5ezsn3RQKBVX2/qN/9I+gUqkgk8mQz+cxPz8Pn8+Ht99+G3NzczQQR2wABgYG0NfXh71792L//v00mbn6THQv+Hw+hoaG0N3djZ///OcQCARtUWGo1Wrx6quvwm63w263g8fjYWpqColEAteuXcPS0tJd1TkymQxmsxlutxs7duyg/ROIzQupFGv1ewcAv9+PDz/8EJVKBc8999xdSTaxWIzh4WEAwJEjR+75s4hCWKFQwGg03nW2KhQKtLLn7NmzCIVCSKfTj/R+gMccEC6Xy/D7/QBAy0+tVivq9Tp0Oh0SiQQGBwcxMjJCPa8CgQDC4TAWFhYwMTFBO01Ho9ENF2zSVI5hGPh8PkgkEhrYIErZ9SXyjxudTof+/n7qK7M6ixmJRBAKhWgnwS87yZJGA0RVKhaL0Wg0UKlU4Pf7MTY29ki6Ez5KiF8Pj8fDpUuXIJVKIZFIaNOHer1OvT19Ph8SiQRVbt6L1Q3n8vk89ZDq6upCPB6H2WyGVCrFjh07kMlkMDY2hqmpqQfyo/2q0Ov1GB4epgG69ZCAMACMjIzAZrNRDzFS1qDVaqHVamlGbrVygMAwDC1fLZVKGB8fRzQapdmp7aQOXu3zabVaoVar1yzi+XwegUAAMzMziEQiSCaTbbFQASsbHJvNhu7ubgwODsJisdAkAvndTk1NUR/gRCJBs9/pdBoqlQo+nw8mk4l6oNpsNuzcuRNyuRwGg4GWx7eb6uFhWT0HLC8vo1qtIpfLIRaLQSaTUTVFf38/+Hw+zp0718SrfXQUCgWMjY0hkUhAqVTCbDbD5XJRL8LN1tONAltESUJsKdpl87cZ5F5I8LFWq9GGqPF4nGb6i8UikskkdDodtd/RaDS02alWq0VPTw8tKyNrVCsfvoEV+4ypqSmaZCSNg/P5/BpPWIZhoFKpoFQq4XA46PtDfkYkEsHS0hLi8fgTEawiHahzuRz18tRoNHQeAVZUI9lsFiKRiKpFJBIJBAIBTZLfLynT6pTLZQQCASiVSlQqFbAsSy2cDh48CIvFglgshkKhAI1GA6VSiaGhISgUiruUV5VKhZ4XSEO6Zu/bvipWz6Esy2Jubo564bpcLjqvCIVCNBoNlMtl6nu/FSu27YZAIKD2JN3d3XSuInOURCJBR0cHxGIxtUEi/SLaDXKOVCgUXzohTazYiLVgq787mUwGi4uLkEgka2x2KpUKIpEITbZ+FQph0uPFbrdTARP590nAlFSzhsPhln6O69lqcLNdUSqVtGKbzJtkXzc1NQWfz0fnA5K47OjooBZ8fX196OzshFqthkgkomKbXC6HQqGAcDhMm3QLBAIYDAZIpdI1TbhX955oB0QiEZxOJ1wuF3Q6Ha1yJ3GURCJBbQ0ikQji8Tg8Hg/tZSUWi+nzJbGYdlqzS6USQqEQpqen8emnn0Kn08HlckEoFK75PZIYnEAg2HS/RvoYEZEeABqrymQyiEQimJ2dxcLCwldqL/dYA8K5XA7Xr19HJpOBx+OBQqHA0NAQzRjk83m8+OKLePHFF2nQ6/bt2/jggw8wNjaGc+fO0Yl1vSkzgWVZmgG8dOkSFhYWsHPnTuzatQsSiYR64DTTo8XpdOLFF1+E2Wxec2gqlUqYnJzE/Pw87Rz4ZSFl43q9npYhEkXO5cuX8dZbb7Wciq1UKiEQCCAYDGJ8fPwulRkA+vsjwdoH+V0Sr61Tp05BLpejVCrB4/HgBz/4AYaGhvDyyy/j0KFD+Iu/+Av4fD7UarWmq3DcbjdeeeUVKJXKDQPCfD6f+p46HI67lL7rP+51kKzValhaWkI4HMZ//I//ERMTEwiFQl+qhLcVIY2xSKfp9aqCRCKBkydPYmZmBtPT00ilUm2ziSOK8tHRUTz33HPUq5IsYqFQCD/5yU/g9XoxMzODTCZDx9H6d4UY44+MjOD111+Hw+HAwYMHIZFI7lsOtV2p1+tUiTM3N0crFvR6PY4fPw6dTodf/OIXzb7MR0I6ncY777wDhUKBhYUF2Gw2vPLKK/B4PHA6nbSB3FYha/d2qTYg6qnVvtkLCwtrDlEdHR20odzx48dhs9mgVqup8l4sFuOZZ56B3+/Hp59+Ch6PB6/X2/IB4cXFRXzwwQfo6+uD0WiEVCpFV1cXDeyRhml8Ph8OhwMmkwnDw8PYs2cPrVQKBAK4du0aLYVr9/LTrZDL5fCrX/2K2oUNDQ1h165dtFkyAASDQUxNTUGn08FkMkGpVFKfdpPJRJPm7Uwul8PNmzfp4bvRaEChUNAKv9XJ+NXNLDdqQJfL5WgSP5VKtZwV2lcB6S5+/vx5zMzMQC6XY+/evRCJRFQ0QVTp09PTbV+18rAQG4jOzk489dRTtMqOzM8qlQpPPfUUIpEIZmZmoFQq26rB0WrK5TKmp6dRr9exd+9eau/1MBDbqNWB1FY+AwSDQVy6dAlCoRCjo6P084VCARMTE5idnUUmk/lKKnDEYjEOHTqEwcFBqswmczkJBs7OzuLDDz+k6xxHa0DOS/39/VSsWKvVkEgk8PHHH8Pr9VJLPWAlGHr48GHs378f+/fvR19fH7U9LRaLyGQytAfC4uIiPvnkE2qhIJPJcODAAdhsNrz22msPpdhvBeRyOUZGRtDV1UU/19HRQeMyy8vLmJ+fRygUwtmzZ3H+/HkcOXIE3/jGN6DT6SCVSuH3+/Gb3/wGPp+P2oS1C6lUiibt0+k0urq68M1vfhMKhWKNUEogEMDpdNJm9Rudl4nokfxdo9GgNjd37tzB4uIiPv30U/j9fiSTya8sUflYA8LELyydTmN5eZkGG6RSKcxmM7LZLFQqFYRCIVWKkM6mpNRjqzAMA4vFAo/HA7lcTjdFwWCwaQoUmUxGJeGk1Gv1C1CpVBAOhxEOh790AJI0LyHNE9xu9xov5kQiQbvRtuLCRMpQv8prI55zgUAAjUYD4XAYFosFAoEAer0eFosFDocDyWQSsVjsK7uOrUAm2Htlhci7dD8F/OqsdaVSoUrHWq2GYrFIN0/RaBTBYJBmRlvxPfky6HQ6qFQqeDwedHZ2rulGTyoNSGbzq1AUfJUQw3u9Xr+m23KpVMLY2BiWlpawtLSEaDRK1Y2bsby8jHq9jnA4jFu3bqFcLmPHjh1gGOYu65InDdJkkYwNgUAAuVy+RunX7hCbh3K5TEvUr1+/jnA4DJ/Pt6Y5DVFiEa9Goi7f7OduJ+7lm51OpyESiTA9PQ2FQgGPx0OVkKREjKzXRIW/kRd+q0F8Tcn8IZVK4XK5UK1WYTKZaFWPQCCgdmAGgwECgQC5XA7FYhHz8/MYGxtDMBj80sFgsuGWyWQwGAx0E95qNBoNFItF8Hg8TExMoFQqIZ1Or/EKXlxchN/vR29v711NCdvBY3ArEPUqqVTJ5/PUp5x0bV/PRjY0JClDvP6bncB/3Oh0Ong8HtrcslqtIp/PU1U5CYYKBAJ4vd5t83yIuEEul6+peCPWPURRr9frodVqsWPHDtpjhlTDlctluteLRCLw+/2P5AzWLCqVChYXF7G8vIzr168jFApBKpWuSaJUKhW6p2VZFiaTCS6XiwptVlet+v1+2vS11ROU5JxE9mNkLeHz+bRCktiePYo9PUlQkSofi8VCPeFX/2xytkqlUvRMtd32P+0ImT9UKhWcTicMBgO1W0wkEkgkEojH40gmkzSRRjy41Wo19Ho9rZIjis5wOEyr2El1aSAQQKVSQb1epxU+Op2OJsVTqRRyuRzy+XxbJcRJlehqoR6h0WhAo9GAZVn09fWhVquhp6dnTeyLKGDbxYpxPWQfR5q7kYr21aI9oVCISCRCFcBCoRBGoxEajWZNle3qZ0eSEbFYDNevX0cgEEAymfzKKyofa0C4VCrB5/NBLBajXq/TgIJSqcTo6Cjsdjs9RNy4cQM3btzAJ598glOnTj3wQiQUCnHs2DEcPnwYbrebZk1PnTrVtOCezWZDX18fdu7cic7OTurF2Gg0UK1WkUqlcPXq1UdiGC0SiWC1WuFyufCP//E/RkdHBywWCyqVCq5evYqpqSn4/f62HISPEvI85HI5du3aBT6fj/7+ftjtdoyMjCAej+P69etNDwiXy2VEo1E0Gg1qbfBlKZVKdNK5ceMGMpkMtQ24du0abUzRqkmDLwPDMOjv78fQ0BBefPFFPP/883TDvFpVMz4+jqWlpbZT1RiNRuzbtw8Oh2PN4hSJRPDnf/7nmJ+f33LDHaKGJdULBw4cwN69e2GxWCCXy79Ug7HthkAggFqthlKpbHv13nrK5TLGxsbA5/Nx/fp16qG2OmhD1H3PP/88fv/3f59617diUO5xQg4Vs7Oz+OijjzA0NIRAIICuri58/etfh1gshlwuh8PhwB/+4R8iEAjQ0tJWpl6vU3srlmWh1Wpx7NgxuN1uXLt2DT6fD3fu3IFAIMBrr72GQ4cOwWw2g8/nY35+HrOzs3j77bfxzjvvPJIDOp/Ph1AohNVqpb0jWvHdIw1yS6US/v7v/x4CgQB8Pn/NnEESwN/5znewe/duAF9YOhFlaLuvy/V6HdlsFl6vF//5P/9nul91u93QarUbJhxJwIq8KySxvbi4iF/84heIx+NrfAu3MyQgtW/fPrzwwgsYHByEWCym3ssGgwG9vb1wOBz47ne/i/HxcVy7dm3bNJQjvRK6u7shk8kArKzBw8PDsNls1C7N5XLB6XTSADk5gFcqFQSDQQQCAbz11lsIBAI4e/YsFcu0I6Rhq0wmw9zcHLRaLTweD03csiyLaDRK73F5eRmvvPIK/uk//ad3Vc6SSkqv14tEItGWFhrAigJ8165dkEqlMJlM9Lz9Zfb1q3uskPP1zp07MTg4eFfjtXw+j3g8jtnZWVy5cqXlrTeeFEhw1+l04umnn6YVuNlsFtPT05icnMTk5CSCwSAVMZLm7RaLBW63m46rcrmMfD6P8+fP42/+5m/oHEzU4aT3ikAgwJ49e9DV1QWlUonl5WWMj4/D5/NhaWmJ7qXahdXXunptZhgGZrMZJpMJHR0d+PrXvw6BQLCmMoN4e0ej0baNRWUyGdy+fRsTExM4e/bsXcFdoVBIE5HEFuzFF1/E/v37IZPJNlSI5/N5TE1NYWJiAn/2Z39G7Tq/6mTBY1cIZzIZZDIZmi3h8XgQCoXQ6XRoNBqQSCQAvigrJV4sW30IpNGCRqOhL2Oj0UAqlaIS72Y1bFEoFLBarbSxG9n8syyLarWKSqWyJkv0sDAMA4lEQv1dDAYDNBoNVWMEg0HMz89vi3LdR0GtVkOpVEIwGMTc3BzsdjuAFdP0jo4OLC4uNtViBACSySTGx8eh0WgQi8U2DTbx+Xy4XC7aXXijryuVSigUCtQ3NhaLYXp6GtlsFktLS8hkMtSyZDsGg4EvVCQWiwUajYbOOwCoWoso6YmdQjvB4/HW+EST8pNYLEZ9gokf1v0gh07iH0sUEAKBYNNgC9k0mUwm2O12VCoVqkZvx0MFCdhtVKq8GqI4aMUg1KOgVqvRwB2Px4NIJFqTECAHrGq1SoNcwBebRtJEKhaLtbza6FFCSt+J0joej8Pn80Emk6FcLtNAJkkoFAqF+75rrQDxx7NYLMhms5DJZHTsd3R0QCgUUlUMmWtJ8w2imMpkMl9aCU3eNaIEdDqdMJlM9Pm24pxD1Hn32482Gg2qagNWxlAqlUI2m227dWkjWJal1XEAMD4+jlQqteZdITAMA6vVCovFQj9HxlMikaCq83Y6UD8sDMNAp9PRfgFWqxU8Hg+xWAx+vx+3b9+G3W6nQQdS9eZ0OiEQCGgflnaBnBUlEgkMBgP9s0wmQ3d39xovzp6eHphMJphMJmg0GphMJmi1WjrmisUirZKcnZ1FKBSCz+dDNBpFPp9vyfliq5DxxLIswuEwTY6Q58OyLBKJBLLZLK1mWv29AKhIKZfLIRwOt827Uq1WUSgUUC6XqZ8/j8eDQCCAUqmETqeD2+0GwzAoFAoPfU8kMOh0OqFUKtHT0wOz2Qy9Xk/9QldD1jpypnoS5qd2QCQS0UaLq5W+uVwOMzMz8Hq9a1SZqy30FAoF9YouFArw+/1YWlqi80k6nUYulwPDMBAIBJBKpejo6KCeu0qlknq8RyIR+Hw+Wr3eyu8Hn8+HRCKhKt96vY5IJEID4vV6ne5XxGIx+Hw+VCoVTZKsjqXIZDJ0dXVBJpOhUqmgUCigWCzSpsDtUJlLKrbq9fqG68bqtVahUEAkEtGq3fXxGXI+IP7LCwsLj2R/vFUe64mjUChgenoafD6fdtRTKpWQyWTo7+9HoVCgfkcymYzK8Xk83pbtAyQSCU6cOIHOzk7s378fXV1duHPnDvx+PyYnJ6k9QDNwuVx4+umn0dPTsyZoUKvVkE6nEY/HEYlEEIvFHnqhIod0i8WC119/HR6Ph/o1RyIR6olz5syZJ0ZFsRVqtRo++ugj3LhxA1qtFg6HA319fXC73Ugmk3j33Xeben2XLl3C1NQUDRxsFnBSq9X4N//m32Dv3r3Up2c9S0tLuHXrFu7cuYP33nsPmUyGmt6T8ncSCG71yfjL4Ha7MTo6CqvVuubzoVAIZ86cwe3bt3Hr1i26iWtnkskkPv30U0xPT9NDz1bnQRIM3b9/P370ox/BarWiu7v7rmAggc/n04DMSy+9BJvNhvn5efj9foRCISwuLj7q2/tK4fF4sFgs6O7uxszMTLMvpyUg42H9BkipVEIkEkGhUECn0931fqTTaXz44YdPfEIyHA7jvffeQyqVwokTJ2AwGOjzIvuidlDeLyws0NJK0g+ip6cHBoMB3/ve91AoFBAKhdBoNLBz505otVp6IEgkEvD5fMhkMl/6OtRqNRQKBY4dO4aDBw9icHAQe/bsQbFYxNLSEmKxWNsGT2UyGWw2Gw0yZDIZ2sW73dclQqlUoh6f4+Pj9NC0OrBCPBr/2T/7Z/jxj39MPx+JRHDmzBncunWrbQ6RjwI+n4/Dhw9jYGAAx48fx+7du3Hnzh1cvnwZZ8+exVtvvYUdO3bg1VdfhdvtxtGjR6FWq/H9738fPp8Pb7zxRss1lL4XUqkURqMRXV1d+Pa3vw2dTgebzUY/vzp5QBrG8Xg8umcGvrB4mpqawjvvvIPFxUV89tlnKBQKSKfTqNVqbR0MXk2tVsP8/Dx4PB7u3LlzV/VBo9HAkSNHMDIyArvdvmbMkF4Tc3NzuHLlCoLBYFucFzOZDObn59HT04NsNgupVEo9+sm78nu/93vwer34sz/7s4cKtBBlsNPpxB/90R/B4XBgeHiYNk1dbdFGCAaDuHHjBoLB4KO6VY5HgEajgdPphNVqhVwuR6PRQDabxdTUFP7yL/8S4XB4zf6EYRhoNBoYjUbYbDa4XC6Ew2EEAgG8+eabePvtt5FMJhGJROj5WSwWw2AwoKenB3/6p38Ku92Onp4eyGQy6jl8/vx5fPLJJ/D7/S2/dpEgbmdnJ8RiMXK5HN544w06V8TjcQwPD8NqtVLbwv3792Pv3r1r+mywLIvu7m78y3/5L5FIJHD58mXE43HcuHED8XgcN2/eRDKZbHtR2vLyMgKBADKZDI4cOYLR0VF0dHRsWDmZyWTg8/lw69Yt/NVf/RU9qz8uHmtAmHQszefztOSNqK5I6THDMKhWqxAKhVAoFJBKpRCLxfc0syeLvkqlgkajgdvtpiUyfD4fqVQKfr8f6XS6KaokkglQqVQwm81QqVR3vQgk4P2wvrlExUey53a7HQ6HA2azmTaXIJ6wsVjskRzCthMsyyKdTqPRaNBDBWnMsVo92ixIeelmpuQkC0k6m67uQkkWGDLu/H4/5ubm4PV6sbS0hEKhgGQy2fIL0aNCKBSu8YBar5DI5/NYWFhAKBRCsVhcc+gmm+p2WaBW+0Xn83kUi8U1nrf3+j6StNJoNNSPvaOjg5byksN6vV5HoVAAy7J0HheJRDSQShoFCIVCWtrbipBML2kiSdYh8gyI4vB+P2O1h912ZTO/XNIkjTQx3CgDTuah7f6M7kW1WqUNKYhynjxLEvhqB5U5uY9EIoFgMAiGYeBwOCAQCKh6USAQ0LlhdVUUKR8kB+it7n2ISoeUiwsEAthsNuqj6na7oVarqZJ2fn4e4XC4rd43hmGoAol4DRJ7MaIgIfuV7QBRNZIPoupbfYCUy+WQSCR3BeyKxSICgQCi0egTUYpNPLJlMhnsdjs6OjromSKdTtPS40gkQpsPGgwGiEQiyGQyGI1GZLPZtkg4rYZ4tSoUCmi1Wuh0OqjVanq+Wb1PI38m75FCoYBcLqderqQ6zu/3IxgMUkXpdnp3SOXpvRCLxTCbzWv6AAArz2+96r4d5hqiaiY2RsSjdbVK02q1ol6vw+PxAACtVib2GZtB1KRk3SJrjd1uh9Vq3XBvWK1WqeArEokgn89vm3esXC5TFWy7IpVKqac4aYBLfMVJNeXqd4Kci8gZh8w95XIZyWSSWj40Gg2IRCJoNBooFAq4XC54PB7aWJfH49H9STKZRDgcRjweR7lcbuLT2BrEA5k8s3q9jlgshmAwiMXFRSQSCahUKrqO8/l8el+FQoGqiJeXl2mcT6PRwOVyQalUIpvNQq1WI5VKQSaT0V4a7XquIvtViUQCrVYLo9FIkwEEMiesbvoeiUSQyWQeq5XGY7eMyGaziMfjtAsqkZLr9XosLy8jkUggGo1CKpWip6cHHR0dcDgctIR7PTwej6qJX331VTidTjz33HO0pCyRSOD06dP48MMPsbS09Dhvl6JWq6FSqdDb24u9e/eu8VAh9yCVSiGXyyGVSiGVSrcUtFmNWCyGWq1Gd3c3XnvtNTgcDhw8eBByuRwsyyIWi+Fv//Zvcfv2bczPz38Vt9nWsCyLTCZDG5zkcjlIJJK7Shabxf3KSIRCIfR6PQwGA0qlEuLxOLRaLRQKBS3zPnPmDFWJXr16FaVSiZadbpdNyv3g8Xiw2+3Q6/UYGhrC8PDwXeoRr9eLX/7yl0ilUncFg0mZDFmg2gGSRNhqgIkos6RSKWQyGY4dO4bvfOc7sFgs6OvrowF1lmVpU4BPPvkElUoFx48fh9lsppvm0dFRDA0N0VKgv/7rv8bNmzdb8n0jjSSkUikWFhZoKa5MJsOePXvQ09ODK1eu4Ny5c5uOGRLwbJcD1KPGYrFg165dsNlsm75vZNPdiu/A44JYuJAPok4B2qvZHhkHPp8P//AP/0BLt0l5ulKppKWCqxOrDMOgp6cHUqkU0WgU4+Pj1MroXpAKqM7OTqhUKgwMDMBkMmFkZAQejwdGoxF6vR4+nw8ffvghrl+/jl//+tdIp9NtcdgCvph/jx49imeffRYjIyP0AFkoFOj+OZFItEUZ94NCRBur743H42FoaAh9fX1wuVxrvj4YDOK9995rm7L2L4tIJML+/fvhcrnwjW98AyMjI8hms5iYmMDHH39M9y4kyB6Px2GxWNBoNCAUCmkwtR0saVYjFothMpmgUCjoXp00OxsbG7srMMUwDPR6PdRqNY4fP46jR48iHo9jZmYGFy5cwAcffIBCoUCT2e007z4qPB4Pjh49Cp1Ot2a9jsfj+OijjzA/P49EItE2+xlihbFz506k02kwDAO1Wk3/XiqV0jnEZrPRPiGJRAKzs7Mb9oohgZuuri4cPXoUMpmMBvp6enpo88L1sCyLxcVFRCIRnD9/HmfOnEEgEPjqbv4xMzU1hZMnT+L69etta/9lsVgwOjq6pqEiOQeS5OS95gUiACGJpkwmQ32qOzo6cPjwYdhsNuzfv582MAdWKjaTyST++q//GtPT0xgfH6fNy1sdsVgMi8UCk8kEPp9PbeCCwSC1IZyZmcHi4iI9QxFu3LiBd999F7lcDrFYDDabDc8++yx0Oh0GBgYgEAiwb98+VCoV+Hw+JBIJ/OxnP8PY2BhNTrUbQqEQu3btgtvtxoEDB7Bnz55NRYY+nw8///nP4ff7EYvFttTj51Hy2HcEpAFELBaDUqmkN0w2wSSr2Wg0qOqVlP8QFQnJ0pCyMuIX3NnZCZfLBa1WC5lMhmg0SsvhQ6HQY5Ver4Z0DyeBYbLAkEmnWq3SjCaAB1YGEc9gcgjr7u6GxWKBSqWCQCBAIpFAMpnEwsICfD5fy3cuJxBFAPHZ+6oDl+2kzFoPURSR3znwhW9luVxGqVSi3U9J+f6TClFdkSwn8IWaolgs0mz++qY9JCDM5/O37L/bTFaPF5J0Ih6fpOqCeMGufueJjQ95n9xuN3p6eqBWq2mCiSgfstkskskkfD4fyuUyRkZGqLJNKBRCqVTSn1coFKBQKJr1OO4LCXBXKhWUSiVq4s8wDO0Qq1KpIJFI6P2T9YmorZaXl+n3PokHTJIF30xJTdbt9UnRdoTH40EikVAVBADqf7aV7xWLxVRJT54FOZC0U5KOeHIuLS1BIpEgEAigVqtBo9EAWDlArJ9jyHplNBphMplgNptRKBTuW41DxpvdbodOp0NnZyfd87jdbqryIUpJ0rjuXhVmrQZRNRqNRvT09MBoNAJYm0TI5/NtE+B+UDaqPmBZFgqFAiaTia7Z5CCey+XoXr9dxszDQpSOZrMZLpcLVqsVRqMRqVQKsVgM4XAYwWCQJrLJMyIBG1Lufi///1aG7D2SySQEAgFKpRJtwLO+6pFhGHg8Htr4EgBV8pGP7WK58qCQ87RSqYRer6fWciTAVSwWEQwGEY1G26pkm9je5fN5ZLNZ2sCevO9kDy8Wi9HT00PXa9LTYKMGT8DKu9TZ2Yn+/n7aKFcsFkOj0dyl9Fvtw5xMJuH3+xEOhxGLxZoWg/gqIGOpne9JJBLRPT3whXiGVFtLJBK6n1vtYS6VSmlFO3mvSJyHjCmn04nu7m7YbDb09vbSfVC1WqUCx5mZGUxOTlLxUTusXwzD0Mqu1c3hVs8T9XqdrlWrvZLT6TRmZmaQyWSoYr6zsxPlchlmsxlSqZSeEZRKJer1+n371bQqxGec9A5zOBzQ6/V3VWMAX4hkCoUCreK/X8XCV0FTUsTpdBq//vWv4XK50NnZSUt6yMvD5/Nx9epVzMzMYG5ujjZd0Wq11A9Kp9NhcHAQJpMJ+/bto4cDgUCA6elppFIpfPbZZ1hYWMDY2Bji8XhTslgMw6CjowPDw8PweDw0qF2r1eD3+3Hx4kUUCgWkUikEg0GEQiFks9ktvwhCoRBisRj9/f34nd/5HXg8HuzduxdSqZTaRLz//vtYWFjAxMQEAoFA22yCbDYbXnnlFZTLZXz00UdIp9NrDN4fJXw+nzYGIAF1oqxtByQSCUZHR+HxeLBjxw56OE6n0xgbG4PX68XJkydx9uzZpjVVbAX4fD46OjowODhID9qE+fl5XL58GZcuXdrQN1gmk+HQoUOQSCQ4efIkIpHI47z0B4IEDzQaDViWhVarxdGjR+HxeGj29vbt2ygWi9Dr9bSbO8MwePbZZ6nKk3TptlgsazwsJyYmEIlEcOrUKcRiMYyNjdHEVHd3Nw4ePEibM7Isi5s3b+LGjRsYGxtr2jPZCqQsaXl5ec08QwJRHo8Ho6Oj8Pl8NAPudDqh1+vBMAxyuRxu376N6enptpk7HiWko7ler9/w7+VyOXbu3EkTE+2MWq3G0aNHodVqYbPZ0Gg08Oabb8Lr9d43AGmz2bB3717s2rUL3d3ddNMMgNpqtXrCaTW5XA7T09O0MavNZsPXv/51WK1W7Nmzhx6gV5ep6/V6qFQqvPbaaxgZGUGxWLxnQzBy8BIKhejq6oJKpaJNOvh8PhqNBs6cOYMrV65gdnYWExMT9KDVLgENALRhi81mQ19fH1W4+f1+fPjhhxgfH3/i5hbSsby/vx8GgwEAaBf3qakpxOPxtlExPiw8Hg9KpRJarRZPPfUU9X5lGAYTExM4d+4cpqamtm1TvXQ6jZs3b0IkEuH69esAvrB5ymazd53v+Hw+9u7di6eeeoqqyjOZDObm5qjH55OKw+GAzWaD2+2mzbSAlZLlZDKJubk5XLhwAfF4vG3Oi6tZXFzEu+++i97eXtowjNiqkITI6tL3arWKo0ePbnivJBAlk8mozz/xp14fDC4UCjQoXa1W8fbbb+PDDz9ENBptGwXoVtFoNOjq6kI8Hm+7YN1mkES91WrF1772NSqiqtfr0Gq1kEqlNO5E1iG5XA6dTodvfvOb2Lt3L7UiJE24iZAkl8vh1q1btEF8NBrF9PQ0IpFIW9rVbFZ1yuPx0NXVBavViueffx7PPfccRCIRcrkcvF4vzp49Sy35gsEgZmdnIRQKoVar1/y81V+Ty+Xabh5SKBR46aWX4HK5cOLECTgcDjgcjg2/lgTIiY1nsxrZNyUgXKlUqEIxkUhQfysy0YrFYppFIRkC4n9FDuYkcGez2TA6OkpVaJVKBZFIBEtLSxgfH4fX60U0Gm1qowCVSgWbzUYXJKIAyufzmJ+fRz6fRzKZRCwWox6f94MMRjLZmM1m9Pb2wm63w2AwgGEYZLNZOgjn5+eRSqXaKhgok8nQ09ODQqFAAwwMw6BWq60J3HzZiXS1IsfhcECj0UAqlaJWq6FcLrd0OQzJZkqlUlgsFtjtdmg0GsjlcmSzWZRKJQSDQeqXtlFJ1JMEKSEzm813qRhzuRztNE28CIllSL1ep9UIMpmMbqBbFVJevNrPymw2o1arwe12g2VZLC0tgc/n0+adwBcdukdGRu5awJaXl6lHG/GLIg0AfD4fBAIBvF4vhEIhBgYGYDQa6QIfj8cxNzeHeDze8hufRqOBSqVCxz6pSiGKGqPRiEQiQVUEarUaMpmMdtwlvmpP2oFztUpiMwUwed9SqVTblSyvRyQSweVywWKxoLOzE8vLyzh37hwNTq0+/BHlEFm31Wo1Ojs74XA4oFQq13RsLpVKbRfcqtfryOVytDlTPB5Hb28vKpUKOjo66O969bwpEAhocx61Wo1yuXzfxkWNRgMCgQAOh4MmFMheqlAoYHFxETdv3sTi4iLm5uYe2HqrmRAVtVQqpVYbarUaEokEjUaDrk/hcLitkgVfFrI/UyqVaxrlkoaFiUQCpVJpWwVbNmK94sjpdNJKn3g8jsXFxTWel2TNIl7u5NxBhA6tvg6vh3ixAthSMzyyPlssFlqZRAKe7axq/LKQ6gyy7yNVKgCoBRhRnKdSqbaca7LZLHw+H2QyGRKJBOr1OlV1EmUn2dvfryplo34/6yFn0mw2SwNZ5XIZXq8XExMTtKKsHVndT2Q1YrGY2hK2a0CY7PXJ7w8A7Wnl8XgglUqRyWRQr9dpdYrD4aA+sMDKnkYqlcLtdsNqtVILVLJurVbdkzP43Nwc7eXUbpU+JAlH4iKkQo7cr0gkgsFgoOdHm81GK5uSySSi0Sjdk+XzecTj8WbeziOHJJ0UCgU6OzvR1dVFA+Tr5xoiPCJVTsQvuVkVpk05kdXrdZp5/Ju/+Ru4XC6qbiUdtg8cOIC+vj7kcjnkcrk1Bypy8NRqtdQqoVwu4/z584hEInjzzTexsLCAaDSKYrHY9AFnMpnQ29tLg5pkU5ZMJjE5OUmDJaRx2FYgz2n37t04fvw4PB4P9u3bRwMTiUQCJ0+epKqSUChEN1PtgkAggFqthsvlwr/+1/8a1WqVdqcnKvCZmRnE4/GHNhwnh0udTodvfetb2LVrF3p7e8GyLG7duoUrV67g5s2bX8HdPRoUCgVGR0dht9tx4sQJOJ1OyGQypNNp/PKXv8TY2Bjm5uYQCoW23cT7MJCA5759+2A2m9f8XSQSweXLlxEIBNBoNGA2m/HUU0+hWq1iYmICtVoNn376KViWRSKRaNIdbA2/348PPvgA+/fvx+7duyGVSiESiaDX6/H6668jk8ng8OHDKJfL6OjooGUsDMPAZrOtKSMkkI7ci4uLOH36NLWhKZfLtLzl008/xcTEBAQCAQKBAJRKJcRiMS5evIhPPvmkLRISuVwOb731Fq5du4bf//3fR09PD1VwGgwGdHZ20jLc/v5+DA0NQaFQ3NVA7UmCNIB1OBzo6uqidgHrIYmJTCbT8kmV+yGVSjE0NESbLZIAZygUwvXr19d0FCcbYoVCAbVajR07duCVV16hyfDVjT9PnToFr9fb8nPMRpDmTrFYDG+//TY0Gg2mp6dhNBrR399P3wuGYWAymWiCzWg0Uu++zSgWixgbG0Mmk8Gnn36KYrFI93jE729+fh4LCwu0GWi7BL3IvKvRaLB79250d3djdHQUKpUK+Xwe0WgUPp8PPp/viVI3kuei0+kwNDSEXbt2Qa1Wo9FoYHJyEm+88QYWFhaeiGZyEokEO3fuhMPhgNvthk6nw9TUFMLhMM6ePYtLly5R2wRS2mw0GtHZ2QmTyYRqtYpwOIwPP/wQPp+vLf0Yt4pYLIZYLIZOp4PZbKYJ70gkgosXL7Zdk8lHjVgsptYJq4N9oVAIH374ISYmJqgqrx3HVTgcxrlz5zA2Nobz58+ju7sb3/72t2E0GtHR0fFIe8Pk83lcuHAB0WgU165dQzKZRCqVQrFYxNTUFLUea0dWN5VeL6AxGo3Ys2cPlpaW2jYgPD09TZPJZJ9vMBjgdDrx+uuvo1QqIZFIoNFoQCqVUiUr8TMHVva+YrGY2n2RRBRRAGcyGfj9fkSjUZw+fRqZTAbpdBqVSqUt5+BcLkd9o0ulEkQiERXTkX4R3/nOdzA8PAy5XI7JyUlcuXIFV69exY0bN9pyPnkQtFotjh8/DofDga997Wuw2Wwwm83UXg74ws5zYmICk5OTtK9TMPj/Z+8/g+NK7zRf8DnpvbfIhEl4AiAJ+iqyrKSSqlQlVct2jzTTo43u6Y3puBMxvbMz+2U3Yrfv7NzdiBvb0zNzx3RMj9pIGkkdarVUVSqn8sWiJ0iQ8DYBJNJ77/cD6n0rAQJ0RRKZwP8XgZBIAlnnHLznNX/zPOvcG2LfBIRrtRpv/b9+/TqCwSBvK2T6LG1tbbzleCfYC8iq4VZWVrC8vIwbN240lZM9azVpDLCwzBSrpmG6e/V6nctKALeaibGAuEqlgtFoRE9PD06fPg2r1cqfF9NQmp2dxfLyMhYWFlrycMk0aAwGA4aHhyEIAlwuF6LRKEQiEfx+P0KhEFKpFA/Q3K05BKvUYmZsDocDQ0NDOHLkCORyOWq1Gvx+P27cuAG/39+0k5hCoeAOpt3d3XA6nVxjcGJiAh999BGCwWDLJQMeFoIgwGQyweVy3aIXlsvluGQLS0b09/dz589EIoHV1dVd7Ta4W1KpFObn59HW1oZcLseDVQqFAgcOHECxWITBYEC5XObt19vRqGnKWp2WlpZw9epVnsBqnKu8Xi83PZLJZDCZTFCr1VhdXcXy8nJLPLtisYjp6WkkEgmEw2G4XC4eUGeGWWazmeuf2mw2Htxkz6sVq2o+D6yDR6fT3bLWNdLoFN/qAXSJRAKTyQSLxcI3fKwzp1qtbnoG0WgU4XAYJpMJNpsNfX196O/v527DbN0qFApYWFjA/Pz8HatlmxWmhTY7O8uficViQb1e54coALx6l821ALh0zU6fy1rrrl+/zhNSrCqLVWg1u0cCG/eN+u5isZh7YfT19eHgwYNwuVyQyWQol8uIRqOIRqOIx+N7yqn+TrBqeqvVCofDAYfDwatdo9EoTxC0asDlXhCLxVw7WK/XQ6lUIhwOY25uDsvLy/D5fHxcSKVSqFQqrmep0WhQKpWQTCYxNzfXMvuY+4VVqrG1hgUAM5kMb8ndL+/QdrBOXKbNyQJ66XQa8/PzXFqwVfcxmUwGmUwGIpEIc3NzCIVCOHnyJGq1GpxO5y1yD7ejMdi5VdecxTIWFhawurqKc+fOIRAI8ERlqyMIApfb2BpEV6lUfO1u1YAwMyrr6+tDNBrlexWtVovBwUFeDcviMlurpVkXKUvqsy/W0bO0tIRwOMwl9q5evcpNLFsV1oXPOk7lcjnv3mHeMcPDwzhy5Ai8Xi+CwSCmpqbw8ccft0SH6OdFoVBgcHAQHo8HPT09sFqtPPHGqFarqFQqCAQCmJycxM2bN3H+/HneHbhb7GrPZrlchs/nQzwex1/8xV/AYrHgyJEjcLlcGBwcRHt7O9Rq9S2BVKYZ5fV6kUgkMDs7i0gkgg8//BDhcBixWGwX7+pWotEoFhcXodPp0NPTw1v8BwcH8Qd/8AeIxWJc+4sZHUSjURQKBfh8Pq5nWq1WMTg4iI6ODgwMDKC/vx8ejwfd3d28FN3v9+Ps2bPwer14++23EYlEWrY9KhgM4u/+7u/Q2dnJdaM7OjrQ0dEBl8uFTCaDkZERrK2tIRwO84DdysoKb9lpbJtj5oRyuRwKhQJ9fX0wmUx46qmnNgm/s+DfzZs3MTk5eVftaY8aFmyz2+3o7OzkGpaxWAyvvPIKFhYWcPHiRQQCgZaSCXmYsMWc/f+tOJ1OnDlzhlesMXmXQqGASCTCJWxagUwmg9XVVVy9ehU/+clP0NXVheeee47L7igUCrhcLp753g5mvNKYvbxx4wYSiQQymcwtVVnM8KVer+ODDz7A+Pg4NwRYWFhAPp9viQNGtVrlsiF+vx9OpxMajQZqtRq9vb1QqVQYHh5GLBbDwMAApFIpD+ql02nMzMxgeXm5ZVsE7wc2r7KW5p3kIFhwa7c0/R8koVAI/+2//Te4XC58+9vfhtvths1mg8vlwpe+9CWcOHECwMZ7wSRI2NpjNpthMBi4FmEul4PP58PKygo++ugjLC0t3WKS1IqUy2UsLS3B7/cjEAhsMm9hTu1szNyJYrGIpaUlZLNZvj9ieyNmwtfsOnNqtRoHDhyAXC5HPB4HABw4cABmsxn9/f28opNJPwHA+Pg4fvzjH8Pv92N2drZl5tEHgUgkgtvtxsDAACwWCyQSCe8aZAUB+8XAUyaTobe3FwMDA9BoNKhWqxgbG8P777+PlZUVbrzHxtiJEyfQ29uLU6dO8c6DxcVFzM3N7WlDNZFIBIfDwZMIRqMR5XIZoVAI8Xgc2Wy2ZStfHwSCIMBqtaK3t5d7H7DW5Xg8zufrvTDHML+elZUV/M3f/A2MRiPvVBkZGbmrdWdrQJgFCWOxGD755BPEYjHMzc0hlUrB7/fz8bUXEIvFOHLkCJ566imuw80IBAKYnZ3F3Nxcyybk2Blmfn4er776Kux2O19rDh06xGMGwGfjYOvZkUnzra6uYm1tDevr61hcXOSd3/l8nst1FovFlp93mPxFMplEOByGRCLB888/v8mEu6OjA8ViERcvXsS5c+cwNTWF1dXVXe/WfxSoVCqMjo7yTkmZTLYpgVCtVnH58mXMzMzg4sWLuHTpEqLRKJLJ5K7PubsaEK7VaojH44jH4/D7/ZBKpYjFYujt7eVahCx4wWCuualUCouLi/D7/fjoo48QDodx9erVpgx+plIpBAIBXtnBKlPb2tpgNBqRTCbh8XiQTqexurqKbDYLr9eLdDrNg5osANPV1YXR0VEcO3YMx44d41VZLCsVj8dx4cIFLC8vY3x8vCmfx92SSCRw/vx5BAIBPPHEE5BKpejo6IBGo0FnZyeq1Sr0ej3W19e5th4AXg1dLBa5ro1UKuXmCUyfb2RkBG1tbfjCF74Al8vFszjxeBxerxcrKytYXV1tymfIWldYhZrJZOJaNBcuXMDY2BjW1taQSqV2+1KbBlYVwDK8Wxd2o9GIgYEBuN1uHDt2DOFwGOfOnQOwsei3ktFToVBAoVDA4uIiPvroIyQSCTzxxBO8KkQikcBoNO748yy4ydrff/nLX3INKKatvR3sYDE5Ofmwbu2hU6vV+HsTj8eRSCT4Bp+1uTPNMbVazY2yWNeH3+/nrtX7hUb9sNtp8rFkbjqdbpl3aSdSqRR++9vfwmazYXh4GAB4AMJkMkEQhFu0g4HPqozYn1mXk9/vx8rKCqampuD1enfnph4wLLkC4JauLalUCqlUyhO2d6JWqyGbzbb0uFEqlejr64NCoYDP5wMAnDx5Eu3t7ejr64PVauW6jGxPt7y8jDfffBP5fL4lW0w/DyKRiLfw6nQ6iMVi7m7P5uZWDUbcKxKJBA6HA263GwqFAtVqFUtLSxgbG+NVZwqFAgaDAX19fXjmmWfQ1taG3t5ezM/P4+bNm1hcXEQwGNzT40gQBBiNRm6Iq1arEYvFkEwmkclkuGbofkav1/NEN/BZ4DSbzSIQCCAej++J94qtv5FIBB988AFUKhXm5+e5oTQzBrsdWwPCTBZpZWUFP/vZzxCLxVAoFB6In02zIRKJ0NXVhSNHjtwSPI/H45idnW3qDto7wbofg8EgxsbG4HA4UCqV0NXVhcHBQUil0h01pNn/MukHr9eL69evY2pqCufPn+eJ673wHjXSWOCQTCZhsVhw+PBh3g3Gzo7ZbBZzc3O8MrgVu9TvB4VCAY/HA4/Hs+l8CIB3jy4sLODs2bNcRqNZaBpXF5Z1m5mZQTgcxvr6Ot5++20oFIpNbYSsQpi1cWezWayurnIduWajXq9znRrW/saCUqxsvFgsIpPJoFwu86ClSCRCsViEyWTiGp21Wo07uJdKJSwsLPB2hVgsxvXzzp07h1gs1pTP415grac+nw8//elPYTKZMDAwAJPJhMOHD/NWuN7eXtjtduTzeQwNDeGpp57iRn0sSCGTybgOqFarhUKhgNvt5g6hgiDA6/UimUzijTfewI0bNzAzM8PbUZsF5rKuVqu5bs+hQ4eg0+l4VpK1aeyHbNzdIhaL4Xa7YbFY4HA4uOs9W8CAjQrhxx9/nEuGxGIxXL58GT6fD/l8viUX9lQqhampKSQSCVSrVVgsFhw8eBBKpXLbTVy9Xuc6lWwRZ8kWtgloxedwP5RKJXzyySfw+/1QKpW8uprJR9TrdS4VkclkuFkE04XfTwHhO8HalZmOmtfrbcpE2/2QzWbx9ttv48aNG1haWoLdbofFYoFGo+EBYrYGAZ9VCbB1f3V1FYFAAG+99RZ8Pt+eqAy+G9gB+m7bd9nhrZVgrft2ux2PP/447HY7Tp48CaVSyZNOXV1d0Ol03MU8n88jlUrh6tWruHbtGq5cucILAvYLgiBAq9VCo9FgcHAQR48e5UGcSCSCqakpXgCw12EGWGzPZ7PZ+N5FoVBAo9FgaGiIV5d7PB60t7ejp6cH+XweH374IWZnZ/Hxxx8jHA63/LngTojFYoyOjuLEiRO8qpHJXE1OTu4LA8LbwbozXC4X945g5wYmr7DXZGnYmstMtmOxGDeauxPbVQgzeSKmBbsXg8HAxv0mEgn4/X64XC6oVCqEw2GEw2GcP38er776KtbX11s6SQsAyWQSs7OzWFtbg9frhV6vx4ULF27rc8F+3yw+EwqF+LkpHo/zmM1eJRaL4Re/+AW6urrwne98Bw6HA8ViEaVSCZcuXYLX68W1a9cQDof3hHzK3cLmB/bFCjXz+TwmJycRCATw/vvvY3x8vOn2ME0VEK5Wq9w44+rVq7t9SQ+MxcVFLC4uwmg0orOzk2vGbYdCoYBCoeCanj09Pdt+H2tRYCwsLHDJjJs3b+6Jw0OtVkM+n0c+n8evfvUryOVy9Pb2ch3CgYEBeDwemM1mXmmUy+WQy+V4NaNYLIZcLodMJoNer+eB4a16Lux5rq6u4v3338fHH3+MSqXSdAudSCSCXC6HSqWCxWKB0+nE4OAgZDIZzp49y/Xh9ks27m4Ri8XcmdtqtUKn092S+bVarbBarchms3xRv379OsLhcMsGQpmWGqs8tNvtePnll3c0/arVavj4448xMTGBbDaLXC6HcrncVEmRR0WpVMLly5cxPz+P48ePw+PxcJ37rbCWf6/Xi4WFhT1dgXU/lEolRCIRrK6u4vz58/D5fHtmk5jL5fDRRx9BoVAgEAjA4XDw9v/Dhw/z4E3j4YIltSORCA8kv/7664jFYvtm7LRigPdekUql0Ol06O7uxre//W20tbVhaGgICoVix4QccyJ/55138JOf/GTXdeV2A5FIBK1Wy30yGtu7o9Eo5ubmEA6H92QQZisikQgymQxKpRIWiwVWqxVSqRSVSgVyuRwajQaHDx/mXwcPHuR7m6mpKVy4cAHT09O4ePHivpAPE4vFGB4exjPPPMOTCEzfdWFhYd9IjNwOnU4Hh8PBOxGYwTnTPN2LAXMWoGFBmOXl5d29oBagXq9z3X6TyQRgIxA4Pz+Pq1ev4t133+VeAK0MM/0l7p54PI7XXnsNHR0deOKJJ6DVanll8Llz5zA2Noapqal9GYtglcAsfhSNRhGLxfDhhx9icnISN27caMr5p2kCwvuBhYUFvP7665u0TB8U0WiUV121+uS8E5VKBZFIBIVCAW+99RbGxsbQ0dEBg8HAW7l1Oh20Wi1vr2PBd4lEwlsamC7s/Pw8b4tPp9O4ceMGAoEAvF5v02Z8WWtXJpPB8vIystksfvjDH0IsFuPixYsIBoO0sN0lrJWbkclkkEgk4PV6cfHiRSwsLCAcDu+Jd4pVR0SjUZw/f/4Wx2BGrVbj+qWlUolLI+xH6vU6stksarUaXn/9dczNzfHq4K1kMhmEQiGsrq7uy+A5C1jNzc3h3LlzcDqd6OrqQqlU4u10r7/+OgKBADfs2yvPiXU3FYtFeL1exGIxhMNhqNVqTExMwGQy7VghzGSiYrEYEolEyyaeiM3I5XKo1Wp+WOrq6kJXVxeXQWs0oCmXyyiXy7h+/Tr8fj8PCN+4cWPfVjOytn+Hw8EN1JiWI9vTtbop5d3CWtRZYpd1xSmVSjz99NNwOBx8/xuNRvHJJ58gmUzyBNylS5e4Jv5eRiKRoKurCzabDW63m3eBAeD7/FQq1ZT7+t2mWCzyZCQ9H4JRrVZx7do1FAoFlMtlCIKAmZkZXL16Faurq7wCkth/1Go1ZDIZ+P1+/PSnP4XNZkOxWESxWMS1a9fg8/n2TXFDI5FIBD/5yU9gNpv5nj8ejyOXy2FychLBYLBpuwApIPwImZycxNTU1EP57P2wiFerVQSDQQSDQSwuLkIQBNjtdmi1WgwPD6OzsxNDQ0MYHBxEW1sb3G73JkkA4LOAaiqVwrlz5+Dz+XD58mWEw2EsLS0hkUg09bNkOqVM72tubg6XL18GsBGUacxKEfdGMpnkZnx/8zd/g2QyCb/fvyc2PMwNOZfLIRgM3tYVuJnH/6OEaWGl02n87Gc/u6ef22+wyoAbN27AaDTi5MmT6OzsRD6fRyAQwPj4OH74wx8iHo8jlUrtuTmqUqmgUqlgdnaW/929OG/vxzGzl1EqlbDZbBgdHcUPfvADmEwmuFwu7lTeqEPIzPHefvttnD9/npvksg6N/YhYLOaSWEajEWq1mv8bk826G93pvQDTbMxkMpibm4NIJILT6YROp8NLL72EF198kScRJicnMTk5iaWlJdy8eXNP7WHuhEQiwcGDB9HT0wOPxwOTycSTBslkEl6vlxs5EpvJ5XIIhUL7MoBD7Ey1WsW5c+dw48YNLk9z7do1fPzxx1hdXd3zSSZiZ5hsSiqVwn/9r/9107/t5/1sMBjEf/pP/2nbf2v250IB4UdMsw+IVoFV1+RyOdRqNXi9XmSzWSQSCSwtLcFoNPJ2sa0/x7SJr169ilgsxjNZreAAyq6PaWk3GhexbG2z38Nu0HjwZppPEokEIpEIkUgEkUgE09PTuHTpEhYWFpBIJJDL5fbss9yr9/WwoOd1Z+r1Onw+H8bGxpBIJBAIBLjD8uLiIjdJ3Q/BCYDGzH6GaWYz93KNRgODwcANTYHP9jCFQmFTVQ3Tm6PD9uakSi6XQ6lUwtraGmZmZhAMBnfxyh49hUIB169fRzAYRDgc3iT7FI1GkUql4PP54PP5EA6H+TjaL/Mt8Nk7BWyMnUgkwk29k8kk+WoA3GSNedDYbDYoFAqYTCYYDAZotVoUCoV9IS9C3J56vc67E27cuIFarYbp6WneVUsQAO11t9Kqz4MCwkRLk0wmkUqlEA6HuZN7o6P77WDBU7ZhbpWXmG162XXvldbrh0mtVkMikYBEIuFBYYVCAZlMhuXlZVy+fBkfffQRXnnlFa6Z2yrjgSB2GzYnzczMYG5ubpMsEvs3CnAR+4VcLod8Po9gMIgLFy7c1X6ksf2W1p5bSSQSiMfjuHHjBj744AMkk8l99ZwymQxeffXVHSXnGmVIGr/2E0y7kbG8vIzZ2VlMT08jGAzuu+exHfV6HYuLizh//jy0Wi0GBgag1WrR3t6OWCwGs9mMTCaDYrG4r5IJxPawzsLXX38db7755r7Q/ieI/QgFhImWZz9ufIl7g1WTJxIJXLp0CaVSCTKZDBKJBLOzs9yMby87BhPEw4Z1KhDEfmdr4pa4e2q1GqLRKMRiMc6ePcsrXtPpNGZnZ3lH136D5tadYUn/SCSCTCaDfD4Pv9+Pubk5RKNR2tM1UC6XN3UhiMViKJVKaLVa2Gw2iMVihMPhXb5KopkgOUKC2NtQQJggiD1PrVZDOBxGNBrFn//5n3ODGkEQUKlU+GZnPxr4EARBEESzUC6XMTExgampKZw7d26TER/r4CGIRqrVKpaWlpBKpbC+vo6enh5cunQJr732Gvx+/25fXlPBDE1ZUkUul8NgMKCtrQ0jIyPwer1YXl6mACBBEMQ+gQLCBEHsC1j14n416iEIgiCIVoCStMS9UK/Xkc/nkUqlMD09DYVCgeXlZcTjcdIO3kI6nUYoFML09DSsVivC4TB8Ph8CgQDC4TCSySR1NhAEQewjKCBMEARBEARBEARBtBy1Wg2xWAyJRAL/4T/8B8jlcmSz2X1lZHo31Ot1zM3NYWlpCRcuXMB//I//kZtUV6tVlEolSsQQBEHsMyggTBAEQRAEQRAEQbQkzPAqkUjs9qU0NeVymesIEwRBEMS9BoQjALwP40KajM57/P798lyAe3s29Fx2Zr88G3ouO0Pv0vbQmNkeei47Q+/S9tCY2R56LjtD79L20JjZHnouO0Pv0vbQmNkeei47Q+/S9tCY2R56Ljuz7bMRyHmVIAiCIAiCIAiCIAiCIAhifyDa7QsgCIIgCIIgCIIgCIIgCIIgHg0UECYIgiAIgiAIgiAIgiAIgtgnUECYIAiCIAiCIAiCIAiCIAhin0ABYYIgCIIgCIIgCIIgCIIgiH0CBYQJgiAIgiAIgiAIgiAIgiD2CRQQJgiCIAiCIAiCIAiCIAiC2CdQQJggCIIgCIIgCIIgCIIgCGKfQAFhgiAIgiAIgiAIgiAIgiCIfQIFhAmCIAiCIAiCIAiCIAiCIPYJFBAmCIIgCIIgCIIgCIIgCILYJ1BAmCAIgiAIgiAIgiAIgiAIYp9AAWGCIAiCIAiCIAiCIAiCIIh9AgWECYIgCIIgCIIgCIIgCIIg9gkUECYIgiAIgiAIgiAIgiAIgtgnUECYIAiCIAiCIAiCIAiCIAhin0ABYYIgCIIgCIIgCIIgCIIgiH0CBYQJgiAIgiAIgiAIgiAIgiD2CRQQJgiCIAiCIAiCIAiCIAiC2CdQQJggCIIgCIIgCIIgCIIgCGKfQAFhgiAIgiAIgiAIgiAIgiCIfQIFhAmCIAiCIAiCIAiCIAiCIPYJFBAmCIIgCIIgCIIgCIIgCILYJ1BAmCAIgiAIgiAIgiAIgiAIYp9AAWGCIAiCIAiCIAiCIAiCIIh9AgWECYIgCIIgCIIgCIIgCIIg9gkUECYIgiAIgiAIgiAIgiAIgtgnUECYIAiCIAiCIAiCIAiCIAhin0ABYYIgCIIgCIIgCIIgCIIgiH0CBYQJgiAIgiAIgiAIgiAIgiD2CRQQJgiCIAiCIAiCIAiCIAiC2CdQQJggCIIgCIIgCIIgCIIgCGKfQAFhgiAIgiAIgiAIgiAIgiCIfQIFhAmCIAiCIAiCIAiCIAiCIPYJFBAmCIIgCIIgCIIgCIIgCILYJ1BAmCAIgiAIgiAIgiAIgiAIYp9AAWGCIAiCIAiCIAiCIAiCIIh9AgWECYIgCIIgCIIgCIIgCIIg9gkUECYIgiAIgiAIgiAIgiAIgtgnUECYIAiCIAiCIAiCIAiCIAhin0ABYYIgCIIgCIIgCIIgCIIgiH0CBYQJgiAIgiAIgiAIgiAIgiD2CRQQJgiCIAiCIAiCIAiCIAiC2CdQQJggCIIgCIIgCIIgCIIgCGKf0LQBYUEQTIIg/FIQhKwgCF5BEL6329fUDAiC8CNBEPyCIKQEQZgVBOEPd/uamgUaM7dHEIQ+QRAKgiD8aLevZbcRBEEuCMJffjpO0oIgXBME4YXdvq5mQBCEzJavqiAI/3G3r6sZEAThgCAI7wqCkBQEYV4QhG/s9jU1EzTH3Aqt2dsjCML7n44VNs/M7PY1NQM0XnaG5t9bofV6Z+jZ7IwgCF2CIPxGEIS4IAgBQRD+kyAIkt2+rmZAEITfEwRh6tOz5IIgCE/u9jU1C7THuxVal7aH5pjtadbx0rQBYQD/B4ASADuA7wP4L4IgDO/uJTUF/xuArnq9rgPwdQD/VhCEY7t8Tc0CjZnb838AuLTbF9EkSACsAngagB7A/x3AzwVB6NrNi2oG6vW6hn0BcADIA/i7Xb6sXefTjcyvALwKwATgjwD8SBCE/l29sOaC5phboTV7Z/6XhvlmYLcvpkmg8bINNP9uD63XO0PP5rb8ZwAhAE4Ao9jYC//xbl5QMyAIwnMA/r8A/k8AtACeArC4qxfVXNAerwFal24LzTFbaObx0pQBYUEQ1AC+BeD/Ua/XM/V6/WMAvwbwT3b3ynafer0+Ua/Xi+yPn3717OIlNQU0Zm6PIAi/ByAB4J1dvpSmoF6vZ+v1+v+zXq8v1+v1Wr1efxXAEoB9f/DewrewsaB/tNsX0gQMAmgD8Gf1er1ar9ffBXAWNMcAoDlmJ2jNJu4FGi87QvPvnaH1emfo2WzGA+Dn9Xq9UK/XAwDeAEAFNMD/C8Cf1uv185+eDXz1et232xfVDNAeb1toXdoZmmNupWnHS1MGhAH0A6jU6/XZhr+7DhpIAABBEP6zIAg5ANMA/AB+s8uX1AzQmNkBQRB0AP4UwP9lt6+lWREEwY6NMTSx29fSZPxTAH9Tr9fru30hTYoAYGS3L2K3oTnm9tCavSP/myAIEUEQzgqC8MxuX0yzQOPlrqH5dzO0Xu8MPZvN/HsAvycIgkoQBBeAF7ARsNm3CIIgBnAcgPXTVu61T9vclbt9bbsN7fHuCVqXNvj3oDnmbmiK8dKsAWENgNSWv0tio31j31Ov1/8YG8/iSQB/D6B4+5/YF9CY2Zn/FcBf1uv1td2+kGZEEAQpgB8D+Ot6vT6929fTLAiC0ImNFp+/3u1raRJmsFFh9K8FQZAKgvBlbDwf1e5eVlNAc8xtoDV7W/5vALoBuAD8BYBXBEGgSljQeNkBmn9vA63XO0PPZls+xEbBTArAGoDLAP5hNy+oCbADkAL4Njbm3lEAR7AhKbffoT3e9tC6tDM0x9xK046XZg0IZwDotvydDkB6F66lKfm01PxjAG4A/3y3r6cJoDGzDYIgjAL4EoA/2+VLaUoEQRAB+FtsaE//L7t8Oc3GPwHwcb1eX9rtC2kG6vV6GcDvAHgRQADAvwLwc2xsdPYtNMfcHbRmb6Zer1+o1+vper1erNfrf42Ntrmv7vZ1NQs0XjZD8+8dofV6Z+jZNPDpvvcNbCSb1AAsAIzY0M7dz+Q//d//WK/X/fV6PQLg/4d9vi7RHm9naF3aHppjtqeZx0uzuv3NApAIgtBXr9fnPv27w6B27u2QgPTlABozO/EMgC4AK4IgABuV1GJBEIbq9frRXbyuXUfYeCB/iY2qgK9+OlETn/H7AP4/u30RzUS9Xh/HRjYXACAIwiegqqNnQHPMvUBr9vbUsdE6R2yGxsun0Px7W2i93hl6NpsxAegA8J8+1SsvCoLwQwD/FsC/2dUr20Xq9XpcEIQ1bKxF/K9363qaiGdAe7wdoXVpW2iO2YFmHS9NWSFcr9ez2Mgq/KkgCGpBEM4AeBkblXz7FkEQbIIg/J4gCBpBEMSCIHwFwD8CCbzTmNmZv8DGYXL006//CuA1AF/ZvUtqGv4LgAMAvlav1/N3+ub9hCAIp7HRyk2O3A0IgnBIEATFp5pY/1dsuOf+1S5f1m5Dc8wO0Jq9PYIgGARB+Mqn75JEEITvY8PNfV/ry9F4uT00/24Prdc7Q8/mVj6tfF0C8M8/nX8N2NBYHt/VC2sOfgjgX3w6FxsB/AmAV3f5mnYb2uPdBlqXboXmmJ1p1vHSlAHhT/ljAEpsaG38TwD/vF6v7/dqzzo2WgfXAMQB/O8A/mW9Xv/1rl5V80BjZgv1ej1Xr9cD7Asb0hqFer0e3u1r200+1ZT7P2NjcxMQBCHz6df3d/fKmoZ/CuDv6/X6vpZc2YZ/gg2TpxCALwJ47tPs976F5pjbQmv29kixUSkSBhAB8C8A/M4WU9j9CI2X20Pz7/bQer0z9Gy255sAnsfGHDwPoIyN4Od+538FcAkbXadTAMYA/L939Yp2Gdrj3RFal7aH5pjtacrxIpDhKkEQBEEQBEEQBEEQBEEQxP6gmSuECYIgCIIgCIIgCIIgCIIgiAcIBYQJgiAIgiAIgiAIgiAIgiD2CRQQJgiCIAiCIAiCIAiCIAiC2CdQQJggCIIgCIIgCIIgCIIgCGKfQAFhgiAIgiAIgiAIgiAIgiCIfYLkXr5ZEIT6w7qQZqNerwt3+7376bkAiNTrdevdfCM9l53ZT8+G3qUdoXdpe+hd2gF6l3aE3qXtoXdpB+hd2hF6l7aH3qUdoHdpR+hd2h56l3aA3qUdoXdpe+hd2gF6l3Zk2zFDFcLEveLd7QtoUui5EPcKjZntoedC3Cs0ZraHngtxr9CY2R56LsS9QmNme+i5EPcKjZntoedC3CvbjhkKCBMEQRAEQRAEQRAEQRAEQewTKCBMEARBEARBEARBEARBEASxT7gnDWGCIIhWRBAEiMViCIIAkeizPFi9XketVkOtVkO9Xke9vp9khAiCIAiCIAiCIAiC2I9QQJggiD2LWCyGwWCARqPB008/DZfLhba2NhgMBqRSKWSzWYyNjWFsbAzxeBzBYHC3L5kgCIIgCIIgCIIgCOKhQgHhJkcQhE3/yyoYqZJxZ7Y+s0aoCnR/IQgC1Go1zGYzTpw4geHhYQwNDcFutyMUCiEej0MkEiEQCKBSqSAUCtH4IAiCIAiCIFqO7c4+giDsuLelPe+9s9MzboTO6wRBtAoUEG5CJBIJ7HY7NBoNhoaGYLFY4HK5oNPpMDc3h/X1dXi9XqysrKBQKCCXy+32Je86crkcMpkMQ0NDOHDgAH9mjFKphHQ6jVAohPfffx/JZBLRaBSVSmUXr5p42CgUCgwPD6OjowPDw8Po7e2FVqsFAGg0GkilUjzxxBOw2+346KOPEI/HUSgUkM1md/nKCYIgCIIgCOL2SKVS6PV6qFQqdHR0QKFQANg4T3o8Hmi1WiSTSeTzeSSTyU173FQqhVgsxs9IFMDcHkEQoNfr0d/fD5lMBrVaDalUCqPRCIVCgY6ODmg0GgAbQeDZ2Vn4/X7MzMxgaWkJlUoF1Wp1l++CIAjiVigg3ISIxWJYrVbYbDY8++yz6OnpwejoKJxOJ9577z1cv34d58+fRyKRAAAKCAOQyWRQqVQYGhrCiy++iN7eXhw6dIhnbHO5HAKBAGZnZ7G4uIi1tTUkk0kKCO9xZDIZent70dfXB4/HA7fbDWBjs6ZUKqFUKjE6OoqhoSHkcjn89re/hSAIyOVytCkmCIIgCIIgmhqJRAK9Xg+z2YyjR49CrVYD2CiWefLJJ2Gz2eDz+ZBIJODz+RCJRPjPBgIBLC8vw+/3IxwO0973Nuh0OgwPD0Oj0cBkMkGpVKKjowN6vR6nTp2C2WwGANRqNbzzzju4ceMGSqUSfD4fAFBAmCCIpqRpA8JKpRIymQwOhwN2ux1OpxPd3d0AwE2harXatj8rEolQKpXw9ttvY3l5GblcDqVS6ZFd+/0iCAIkEgmMRiNeeOEFeDweDA8Pw2w286xjZ2cnZDIZrFYrDh48iPX1dSwsLCAWi/GK4XQ6vS8WdEEQoNPpoFKpcPLkSQwODuLQoUMYGBiARCLBwsICNBoNrFYrJBIJDAYDPB4Pfvd3fxfr6+t49913EQwGsbKyQkH1PQb7fbe1teHYsWPo6+uDXC5HJpNBIBBAOp1Ge3s7LBYLxGIxZDIZtFotHA4HRCIRotHobt8CQew7BEGAx+OBzWaD0+mEzWbD1NQUxsbGUC6XUSgUdvsS7wmpVAqxWIxKpbIvk48ikQgqlQpqtRpPPfUU2traIJfLIRaLkU6nkc1mUS6XUSqVeLcTq2DL5/OIRqN8nycWi2E0GiEIAhKJBMrlMoCN5F65XEalUuEGoa0Eex4SiQQikQg6nQ5KpRJ6vR56vR4ymQwKhQI6nQ4OhwPpdBpLS0vIZDLw+XzI5XIIh8P8eewVJBIJpFIp+vr6YLVaodPpoNFokMlkkMvlkMlkkEwmkU6nEQgEUK1W9+U7RuxvdDod2tra4HK58PTTT8NoNKKzsxNyuRzAxnvU2dkJjUYDmUyGQqEAl8u16cyTSqUQj8eRSqUQDAb5+bFSqSCZTKJQKGBlZQXZbBbr6+vI5XIoFAr75n0TBAF2ux0HDhxAV1cXvvKVr0CtVkOpVEIikUCn00GhUEAikfBYQ61Wg9vthkwmw+rqKlZWVhCJRMinhGhJWHxqqzE7QyQSwWQyQSaTIZlMolQq4emnn8bhw4cBbLwPiUQCoVAIxWJxU4dCNpvF7OwsCoUCisXivohfNSNNHRDW6XQYGhrC4cOHceLECXz5y1+GSCS6RU93K4IgIJvNIplMIpVKoVqttkxAWCaTwWQy4Wtf+xoOHz4MmUzGX756vQ6PxwOPx4Njx46hWCxiamoKly5dwtzcHAqFAlKpFDKZzL54oQRBgNFohNlsxpe//GU8//zzMBgMMBgM8Hq9mJiYQFtbG8xmMw8Q6vV6dHZ2IhgMolAo8GA6BYT3FlKpFDabDe3t7Th58iT6+/uRSqWQTqcxPT2N9fV1yGQyHhAWi8XQarVwOp0olUq31VsjCOLhIAgC+vv7cfDgQRw/fhwHDx7Ez3/+cywuLiKTybRkQFgulyOfz++bw3MjIpEIWq0WNpsN3//+93Hy5ElotVoolUqsra0hHA4jnU4jk8kgkUggHA4jFovB6/UiGo1iamqKV1TJ5XJ0d3dDLBZjaWmJHyjq9Tqy2SwKhQLK5XJLBYQFQYBCoeBBX6lUCrfbDbPZjK6uLnR0dECr1cJgMKC9vR1Hjx6Fz+fD22+/Db/fj3PnziEWiyGZTO6pgDDbCyuVShw9ehRDQ0Po6uqCzWZDMBhEKBRCIBCA1+vF2toaEokESqXSvnzHiP2NXq/HwYMHMTIygn/2z/4ZTyJtp3FrtVq3/QyWSKtWq5vmkXw+j9XVVUSjUXz00UcIBoO4dOkSwuHwvklysgBYW1sbvvSlL6G3txcvvfQSl+So1+v8+TUmrQVBQHt7Ozo7OzE7O4u5uTlUq1UKCBMtiUgkglQq5f+7dX5pTDx5vV6k02l861vfwg9+8AN+lp6fn8f4+DhSqdSmToRAIIBIJIJ4PI5yuUxV9LtEUwWERSIRuru7+WbY4XCgu7sb3d3daG9vhyAI/OtOwRqxWIyenh5Eo1FcuXIF6XT6Ed3F54dlYlg2ZjtYVaPdbsfIyAgUCgWi0ShCoRDP3maz2T0d1BKLxfB4POjr60N7ezu0Wi1KpRLW19cxPj6Od955BzabDaurq7xSWKlUwmq1Qi6X4/jx47Db7Twzlcvl9sQGh40ZsVgMQRBQrVY/1yFZIpHg9OnTcLlciMVivDIpFAqhXC435UFUJpOhvb0dHR0dkMvlqNVq8Pl8CIfDuHLlCpaXl2E2m6HT6aDX66HT6dDe3o5nnnkG165dw/z8PAqFQssFoIhHg91uh91uv+W9KhQKiEajKJfLe37+fdCIxWJIpVJ0dXXhyJEj6OzshMFggMlkgsVigSAISCaTj/yZsutiVZsajQbt7e2o1Wr8cGc2m3nyttHUVKPRQKFQYH19HT6fjx8Ys9ksotHonh8f9XodlUqFV/CytYI9GwDQarUoFAqwWq1wOBzIZrPo7u5GNpvF6Ogof8ckEgmsVitEIhEikQiy2Symp6cRjUaRSCRQKBQQi8WQSqV27X53gu3ppFIpryZzuVxQq9Ww2+1QqVTQarWQSqVQqVRQKBTQarXQarUwGo2w2+28Olqr1WJwcBAOhwNqtRqBQADRaBTBYBC5XG5PHKakUikOHjwIp9OJY8eOob+/n6/XbC/X3t6Onp4ezM3NoVwuIxqN8qALQewnRCIRRCLRHc+Nt/t5drbeitVqhUqlwokTJ5BMJuFwOJBIJDA9PY1wOIzV1VXEYrEHdStNg8VigcVi4dIQrAOVdRGWSiWkUilks1ksLCwgk8nwQiMAfK6Wy+W4cuUKfD5fU65NjwqxWIyBgQGYTCa0tbXBaDSiVquhXq9jfHwcFy9e3O1LJLZBEASIxWK43W489thjvFhza5WwSCSCzWbjsahCoYD+/v5N36PX6+HxeFAoFNDW1sb3v+3t7SiXywgEAnj33XeRSCT2/N64GWmqgLBYLMbx48dx6NAhHD9+HP39/XxT3FgVfKeBUq/XIRKJcPToURgMBgSDQSwvLz+CO/j8sEWZLew7wf69s7MTHR0dcLlcEAQBCwsLCIfD/IC0FwKc28GyVEePHsWZM2cwNDQEs9mM5eVleL1evPfee/iLv/gL2Gw2HDhwAA6HgweAT58+DbVajRdeeAHRaBTnz59HJpOB3+/fE8+LZbRlMhnEYjEKhcLnCgjL5XJ873vfwxe+8AXcvHkTKysreP/993H+/Hne8ttsKJVKDA0Nobu7G0qlEuVyGdPT05ifn8cbb7yBqakpGI1GaLVa9Pb2QqfTYXBwEJ2dnTCbzfjggw9420srVZwRjwaPx4PHHnvslrUoFArh+vXrSKfTe3r+fRiwoOvBgwfx3HPP8cCY0+mE2+3mSZ1HvVGUSqXQarUwm80YHBxER0cHvvSlL6FcLuPSpUuo1Wo4fPgwdDodr6AAPjOgUavVuHTpEq5cucLNe9gheq9veuv1OkqlEorFIvL5PAqFAg/YGY1GGI3GTXu6nVzZ2Z8b94GFQgE//OEPce3aNUSjUaTTaVSr1aY8dItEIigUCqjVanR3d8NiseCLX/wiHA4H+vr6YDAYYDQaoVKpkEgkkMlkkE6nkU6n4XA40NXVxfeGBoMBjz/+OCqVCh5//HF4vV6Mj4/zgPteCIjK5XI8++yzOHz4ME6dOoWOjo5NwarGcXL9+nUAG9VHy8vLe+L+CeJuYft9JjsjFovv6zMaP4chl8uh0WhQr9fR39+PWq3Gg6Bvvvkm5ubm8MYbb+zJgHBHRweOHj0Kt9uN/v5+tLe348SJExCJRLwrZWVlBYFAAH//93+PtbU1XLt2DfF4HMDGM3W5XDCZTAiFQvvexFwikeCJJ57A6OgonnzySQwMDHCZn3//7/89Ll26tOf3Q60IKz4cHh7Gn/zJn8BsNsPpdG4bn9ravS8Wizf9Ti0WC9fYbvz7fD6PQ4cOYWFhATdu3NiVwg+iCQLCLPvgdDqh1+sxODjIA3gajQYSiWTTJNqoL8cWIdZu193dDZVKBeAzPZNCoQCLxQKDwYB8Po9isbgr93m3VKtV5HI5XLlyBZlMBu3t7VCpVAgEAkilUrw1hUkjqNVqaLVaqFQqeDweyOVypFIprK+v84PFXgtoCYLA79vhcMDtdnMDhXA4jImJCayvr6NSqSCTyXDNK7FYDLPZjGq1CrPZjNHRUYjFYhw4cAAA8PHHH2/StWlFWJZOpVKhvb0dOp0OS0tLCAaDyGaz9yWNIQgCpFIpD87I5XJMTExwPbJmhG1uK5UK5ufnIZPJMDExgaWlJUSjUZRKJcTjcfj9ftjtdgAbi5dcLodKpYLBYEClUtmTG10G06xkXyqVClKplM+TGo0GarUacrl8U6CLIZVKYTAY+NhoPLCz72VtvIuLi1hdXW3aivJGxGIxDAbDpopPVm3vcDhgNBoxMjKCoaEhAJs3NslkEgaDAYlEAgsLC8hms5s0syhYsT0ikQgOh4NvGBUKBUqlEteRDYVCSKVSD32TKAgCOjs70dbWBqVSydv51Wo19Ho9Ojo6YLVa4XK5UKlUeLKto6MDarUaYrF403vCgtoej4ev7ZlMhjuOp1Ip+Hy+PTsu2NohCAKCwSCWlpagUqmg0WgQDAaRSCRgNBphMBj497N3pVwu83Vbr9ejXq/zJB3b20xPT2NlZQXpdBr5fB75fH53b3gH5HI5l686ffo0TCYTnE4nNBoNv1e/349qtYpIJIJkMsmDwjabDYuLi/yzdDoduru7IZVK+d5XLpdDLpdvq+3XSrC9HdP/d7vd0Gg0fC1nmqapVAp6vR4WiwVGoxFDQ0MwGAwolUqIRqNYWFhAPp/nSYL9RGNwj2lPS6VSqNVqvkZLJBKYTCbI5XK+dsfjceRyOSwvLyMUCu3yXdw9UqkU7e3tUCqVkEqlkEgkkMvlkEgkKBaLm86P6XQa8Xh8U4t/q0vsFQoFBAIBaDQaXLp0CUajERaLBXK5HFqtlncmbK3+rdfrfI5hqFSqbav/Grtz2XjxeDyQyWSYnZ1FNBrlgeJWhY0du90Og8GAgwcP8lhEZ2cnTCYTTziurKwgFothfHwc4XAYi4uLiEajt3SZMj+fbDaLSqXS9HORIAhQqVSQy+UYHByETqeD3+9HMpn8XN03rMtKp9PBbDbzswYbU/eTxHiUMG1/mUwGo9EIhUIBo9HIva4kEglSqRRSqRTvAGN7f1YF3aqwhH2tVkOpVEK1Wt1UsFiv13lnUuO91ut1hEIhJJPJWz6TzdEajQYul4ufufR6/aYuu72KxWLh44lJz7AOD6lUimq1yiXQ2J43Fos99ITSrgeExWIxVCoVHnvsMfT09ODFF1/EwYMH+aDI5/ObJiG/348bN27A7/fj8uXLADYqTZxOJ/7wD/9wU0CYVfv19/dzB9Vm1u9hL1w4HMZf/uVfwuFw4Fvf+hY6OjrwxhtvYHZ2FsViEaVSCaOjozh8+DA6OjowMDAAnU6HJ598Evl8Ho899hhu3LiB69ev8+qcVp6QtsKCnlarFUNDQxgdHeUyIjMzM3jttdd4pUgikUAqlYIgCLh48SLUajXef/99dHZ24t/8m3+DtrY2vPTSSzh9+jTW1tawtra227f3uZBKpRgcHER7ezu+/OUvo6+vD7/61a/wySef8Orp+6ExSyiRSHDz5k189NFHTRsQBjY2N7lcDm+//TZyuRzeeecd+Hw+pNNplEolrK2t4ebNm2hrawMAriWs1+vhdrsBYM8Ga1gAuPHw1NHRAZ1Oh/X1dUQiEfT29vLq6e205/R6PY4cOcITMzKZbNPnA0AikUA2m8V//+//HT/72c+QTqeRSCQe1W3eFzKZDAMDA9Dr9dwUTKVSQSaT4Utf+hLvPDEYDLfMq6yNMBqN4pNPPkEgEMAHH3yAUChE5pW3QSKRYHR0FAMDA+jq6oJSqYTP50MwGMTMzAxu3ryJcrn8UNcxVh317LPP4sUXX4TdbkdbWxufF2QyGVQqFa/EAoCDBw/yn926iW08RFssFpw4cYJvrCcnJ9HW1oaZmRn88pe/3JNzDLDxDJRKJeRyOcbHxxGNRmGz2eBwODA+Po6xsTEcO3YMR44c4c8vGo1iaWkJyWQSXq8XKpUKIyMjqNfrmJiYQCwW41XBMzMzm6Q3mjX5rdPpMDo6ir6+PvzhH/4h9Ho91tbWeJVZIpHA2NgY/H4/1tbWuK9BPp+HwWDgUhkAcODAAfzBH/wBrFYrurq6oFaroVKpoFQqWz4gzAIyTqcTBw8exOjoKD8w5XI5ZLNZTE5OYmpqCiMjIzh9+jScTidefvll5PN5fP3rX8f8/Dz+83/+z1hfX8fs7GzTJgkeBmwOY3MUM8JiySypVAoA0Gg0eOyxx7gciVgsxtjYGNbW1vBXf/VXm/Qdmx21Wo0vfOELvBqTycKpVCoeqGTMzMzg2rVr3MgymUxifn6+peffRCKBa9euYXV1FfF4HFarFU888QQ/+7IuW/a7Bz7TDPb5fJifnwewMVc7nU6MjIzwYoGtsIChUqnEmTNnUCwWEYlEUK1WMTU1tSlx1UqwRJRKpcKTTz6JI0eOoK+vD/39/dDpdDCZTKhUKsjn81hcXMQvfvELrKys4N1330U6nUalUkG9Xr9lHMViMcTj8bvqbG4GmCyT3W7Hn/zJn2BwcBBvvvkmJiYmcO7cufsKCDM9eJVKBbvdDrfbDZVK1TLPBNg4V3d0dMBkMuHYsWNwOBy8epx1gU1NTWFqagqhUAirq6uYm5vDhx9+iFKp1PRFMLeDjetCoYBEIgGlUrnp91apVBAOh5HL5XhHLdMj//DDD3kHTyNarRZWqxU9PT14+eWXoVKp4HA4kMlkIJfL71oathVhPilDQ0OwWq2bfIxY4UmhUEAoFEIikcDExASi0SguX7780KVvdzUgLJFI4HA4YDAY0Nvbi76+PhiNRkilUv4Sra6uYnV1lf9MIBDAxMQEIpEIVldXIRaLUSqVIJVKN0XPG00pFAoFFApF02ehgM8csyORCCqVCm7evIlwOIyFhQX4fD6USiWUSiVotVqIRCJummez2dDX1weFQgGDwcAzw3sx0yISiWAwGGCz2XhVVi6X4zpygUAAmUwGAG5ZpAVBQCQSgUqlQjwe55qQIpEIFosFJpMJ2Wy26SvJGSy7KpPJ4HA4oNPpMDIyArfbjba2NhgMBmg0Gp6RvdfPViqV0Gq1XH6CHTSafVwVi0W+QWYH60Qiwc2dWLUZq5xuhLkGazSapr/Pe0UkEvEq6MHBQW7wxPTI1Wo13G43kskkXC4X2tvbecVWI2wDbbVaebV+4/hqXNBlMhk0Gg0312ommDwPc4hWq9X8HTKZTDwgLJfLuS610WiEWq3eFABvbJFif+7q6oJGo0E8HkcoFEKhUEAkEtnTUhImk4kfnliFL2uh3A5WeaHRaNDV1YXe3l7o9Xpesba8vMw1mR/moV0QBJhMJmg0Grjdbh5cMBgMm/QZ2WaVsbUlbutnMra28jIn+HQ6DaVSeYuZT6vD3iu1Ws31X9kzjcVimJ6e5kY7bL/HSCQSWFtbQyaTQSAQgEKhQKVSQa1Ww/z8PNLpNO+AYpVXzU61WkUmk0E0GuVB7rm5OSSTSayvryOdTmN5eRnhcBiRSASpVArFYhHFYvEWbU+r1YpYLAa5XH6LlEYrr1es+rCvrw8dHR28S4O9G8vLy/ygPTs7C7PZjHK5fMt7yboMstlsS+z57wc2JliiknXyKBQK3pWgVqthNpu50Y/T6eTPQ6lUwmazQafTQavVQiwW804pg8EApVLZ9CZ9bC+j0+nQ2dmJzs5OqNVqSKVS6PV6yOVyAOBrO9u3smrzUqmEdDoNq9XK77NSqSAej/NAZysU01SrVRSLRaTTaZ5kYtXzarUaFouFG1YyWDAuHA5jenqat+4HAgEUCgXeEcbmcLlcDrvdzvc8jZ0frNuh8ZzeaohEIpjNZv6+dHd3w+l0QqfTQSKRIJ/PIxwOY35+Hl6vF4uLiwgGg1wabCdaJejJOgY0Gg2Gh4fhdDrR1tYGi8UCj8cDAFheXsba2hqPQdwN7Gza09PDE+wGg2HT2tVMz6dRbtFoNEImk0Gv10OpVOLAgQMwGAwYGBiA2Wzm3YIajQZKpRIWiwUdHR3QaDT8zF0oFJBOp/l7FY/HWy75xIoYyuUy7x5t/J2xOF08HkcsFuNdc6xAb7t5gRXTmM1mnsRnz76V9zDbIQgCdDod5HI5ryo/ePAgBgcHeWERO2MolUpoNBqUSiWo1Wqk02kIgsAl0VhXcz6ffyjvza4GhNVqNZ544gl4PB585zvfQU9PD68GiMfjSCQSePXVV/Haa6/xn2H6e0wvTS6Xw+l08krYRlgFHMuQNh7gm5VarYZisYjl5WWIRCLMzs5yAXsWyAKAhYUFnrU6cOAAzpw5w1t42EGWbYD2WqZFIpGgv78fg4ODMBqNADakIkKhEKanpzExMbFjpRALFFarVczOzqJer2N0dBQ2mw0jIyNIp9OYmprC+vr6o7yl+4a5uJvNZvzu7/4uurq6cObMGb65r1arvCWXvVt3i1gsRltbG2w2G1/E2Wey9pBmrchKJBJ45ZVX+NhnWpaNLS2rq6vIZDJ4/PHHN/2sVqtFZ2cnisViy1dcbUUqlaKtrQ0ulwv/8l/+S/T09MBoNEIul3NZBPaMWPs7+9oKOzCwhbwR9oxZ+5nRaITJZGqqRAu7fo1Gg46ODuj1evT398PhcOCb3/wm18lq3KSwauqdxgXL8iqVSh4YPX36NMLhMP78z/8cExMTWFlZaUqd0wfBkSNH8MwzzyCZTCIUCmFxcRHnzp3bcRMslUoxPDwMl8uFF154AUeOHOFmY1NTU3jttdcwOTm5ae17GIhEIr5JO3PmDA4fPnyLnuKD3Kg6HA48++yzUCqVePXVVyEWi1vysLATrNOira0NP/jBD9Dd3Q2xWIxarYaLFy/itddew7lz5zA5OYm33noLWq2W/yw7RLH1hQV+GlsTWYC4VZ5XJpPBxMQEfD4fN0y5evUqEokEb8Msl8v8ntiaxRKXjZUharUaMzMzKBaLGBwc3MW7enCwBILJZML3v/99DA8Pw+PxQCKR8MD/3//93+M3v/kNIpEIIpEIpFIpnn/+eX6Al0gkUCqVyOVy6O/vh1QqxcTEBC8O2Euw9vauri5YrVYMDAzA5XLB6XRyw9OOjg4+h203l7GgH1vLmDmzx+OBzWZDPB7ftt23WZBKpbDb7fB4PHjuuefQ39+PTCbDDSyr1Sq0Wi1qtRo/A546dYrvcVjVG5OQADZa/N977z34fD689dZb8Pv9D70z5fNSrVa5Pns8HodIJMLZs2dhMpmQz+d5lxfrngXAAzxjY2P427/9W2QyGcTjcRiNRng8Hj5m1Go1BgcH0dbWhu985zubOsXYfrG3txe1Wg1ra2sYHx/fjUfwuWBBy0OHDmFoaAjPPfccjh49yosBWPHZ2bNn8Zd/+ZdIJBIIh8M8qbAX0Gq1ePzxx9He3o5vfOMbfC5RqVR47rnnUCwWkUwm+Tn7biRlmGSNyWTC7//+72N4eBiHDh2CzWZr2kQdu2aHw4EnnngCNpsNx48fh8lkQl9fHy8EYWtO4/zpdrvhcDj42TibzSIcDmNpaQmvvvoqfD4fPvjgg5brEmTGwCwpolarN537s9ks3n77bczOzmJsbAzRaJT/205JRbPZjO7ubmg0moe+t99tpFIpDhw4AKfTiSeeeALd3d3o7++Hy+W6JQDe+GcWZ2EyuaOjo1hbW8OPf/xjLC8vP5R1aVcCwmzjZzKZ4PF44PF4YDKZoFaruW7c+vo6VlZWsLy8vCk4l8lkNmkJyuVy/llbRa5ZoKLVsg7sBQSw44LDsjWs+qwxwNC4+Wul+74TrOpbo9HA4XDA5XLx1hM2+abT6TtWWrGNYCgUglarRaVSgUQi4a2ZS0tLj+iOPj8sq6TT6eByuXhbi0aj4a2nrPXgXuUdWNUI02hmEi6lUolXUTdrBUmtVrvjwsvuI5fLoVgsbqp+3k4zdy8gkUhgNpths9n4wZFJIwC3zhfbLTg7fc92xk+N+lPNoqXFdPKYiZlOp0NfXx90Oh16enq4u7TBYOCHnq3cbl5lVftKpZLfN9PcK5VKXGeOHVyb4Zl8XlhAxmKxoKuri2t85vP5bZ+VWCzmlcHd3d1cm7dRLzSVSiEUCj0SjUdBEGCz2fhe5GEnj6VSKTQaDfR6PaxWK6rVKpLJZMsEOO+EQqHAwMAA2tvb4XK5YLPZUCgUUCwWEY/Hsbq6ikgkwit8G+dqtrep1+s8oc26OJo9OLMTbGMPbCQiWXUe07i93T2xLiemA6vVaqHX63kFUi6X43pzzZqgvRMsgWA0GnkbpUwmQ71eRzweRzgcht/v53uZTCazKbnYWCHN9CpboZPpbmEdBqwTR61WQ6FQYHBwkLfeOp1OWK1W/vwag3d3886w58YCYc3+7FgSQSwWo1qtcp3FbDbLK+wZer2e73PYWsXGF+t+02g00Gq16O7u5pWBsVgMtVqtafe5jMaiB2AjqSYWi7G+vg6VSsUTaewszM7GrDsqlUpxIydWbd+Y1NPr9bfMLY3/TdZ512qIxWIee+jo6EBXVxdMJhNUKhXK5TLv6pqdnYXX60UgEEAul0Mul2vJdWgrzJydFcF0dnbC4XDAbDZzTXq2F7qfIC7r3rDZbGhra4Nard6kPRuPx/lXM6BUKnlsoaenBzabDe3t7TAYDPyZZDIZFAoFvrdlHitsLy+RSHhHLutgZwlx1mn5eY3edwO2TysWi5uunQXRlUoll5W407vB9nFsj8e8AUKhUMvu8RiNc6vZbIZGo0Fvby/a2trQ2dkJt9sNs9nMiyDutPdj61V7ezv3RotEIshkMg88IbUrAWGj0Yivf/3r6OzsxO/8zu9wcw22SU4kEvif//N/4u233+bVAIytQQWz2Yzvfve78Hg8vFp0P5FOp+H1ehGJRFr6JbobJBIJz8J94QtfwLFjx7jZzPLyMi5dugSfz3dXn5XNZvHee+9hfn4ehw8fhl6vR09PDwBgaWmpZbSwZDIZ3G43Ojs7cerUKfT29kIqlaJQKOAf/uEfcOHCBUxMTMDr9d7z5KFUKvGVr3wFBw8e5NXnMzMz8Hq9vIq6lQMYzMwnHA5jfX0der0eJpNpty/roaLVavHYY4/B4/HA7XbDaDQ+1Gx9oVDgFX/pdLopKoS7u7vxxS9+kRsXWSwWHDp0iJszsSrf7Vx07xUmiaBQKPD9738fsVgMf/VXf4Xr16/ztndmltTKsEDE8ePH8cwzz/C///Wvf41XXnnllvtjWn3t7e343ve+h+7ubt7mywJcq6uruHnz5iOp8BOJRDhx4gR+53d+55HMAUyWpqOjA88++yxvQd0rshEdHR34d//u36G7u5u3xPl8PmQyGUxNTeHjjz/mcldbzX5ZAqmRre7VrQaTAROJRLy66l4PhTabDaOjozh06BCef/55iMVi+Hw+eL1e+Hw+hEKhlq1YU6vVOHr0KDweD7q6uuBwOCAWi1Eul3H27FlcvXoVV65c4cZ7+wlWrKDT6XDmzBnYbDbe2TMwMACr1QqZTMYDEFvlae6WUqmEQqHAq7paIWDBxsj09DQikQg+/vhjrK2tYXZ2dlMVIwuSN5ojj4yM8AAxM3tkyeBwOIzx8XEUi0U+b7UauVwOZ8+exdLSEo4ePQqLxcK7ZtkYGRkZwcsvv4zz58/zjrmlpSU+37Lq8+2CNCwIPz09zZ97K8G8IZ5++ml0d3fja1/7GoaGhqBUKgFsdCMHg0H89re/xU9/+lNEo1FEIpGmKWx4ELAO6/7+fnznO99Be3s7D3wyOSy2d2eJuLtdY5hPiV6vR3d3NwYGBnjhCavQ/+CDD/D2229jfHy8KZ6p2+3GN77xDXR3d+PLX/4yl0thZl+lUgkXL15EIBDgyTO32w2r1cqlCa1WK9xuNyQSCTegMxgMWFhYwPr6Onw+H6anp1uuUjifz2N9fR06nW7T70qpVOKZZ55BT08Pn4dZN+5OsCSERqOBQqFAOp3Gq6++isXFRZ6Ea4bxcK8wWU2VSrUpNnn06FFe8CKTyXi39Z1gRZASiQSnTp1CLBbDxYsXIZFI+LN+kDzSgLBYLIZCoeAGB52dnbBarTxrwhyWfT4fVlZWsLq6yisSd4JVGz/swEazwloNWz2rcjeIxWJeQWI2m/lBs1KpIJFIbKsHuxPVahXRaBQKhYIfzJj0gkKhgEgkamr9J5aVYxl8ps3Eqoby+TwCgQDXJbyXDS3Lemo0Gm7wolQqIQgC0uk0QqHQXVViNzusbY5VWbGN4H6AZTG3zpmsO4G1qzS2ZrMDAINVebKxuF1FUTqd5i3Pu11RzhZrk8mEzs5OGI1GrmvqdrtvqQq93bvPgpbs+1i18VZ5DVaNwzSalUolOjs7eas464hp5YAwk62xWq1croiNme0qbZkEgMvlQmdnJ5elATaeZTQaRTQaRTgcRjabfSRBLqaJzTbwjWO5sdKdvRPFYpG/E43t/gwmK8ICNcxNuNFoDtgIjLvdbhQKBWi1WpTL5ZbQrbwdbJ/ncrngdru5LwKr/GUHTPZ73c6MZyut/DyAz+7xfrSiG4NWHR0dfK0vl8sIhUIIBoObDF1aEbaWMK29xiqyaDQKn8+HZDLZ8nuO+4F1XpjNZnR1dfFOBqPRCLfbvW0CixlUs3mLtfwC2GSUytaqer2OYrHIO79aodqczSv5fB5ra2u8OIZ1l4bDYf69rGqYVcTmcjmutcwkiljFsVKphFKp5FXSzV4pvRPMVFsmkyEYDCIUCsFms0Gr1fL7MhgM6OjowOLiIvR6PTfbY+NDp9PxZMTWjjlWGZxIJBAKhe767NUMNM43jTIprKspkUggEAhwD6O1tbWWrYLeDjbWmWeC2+2GzWbbdP4FPqviDYfDSCaTd60rzroszWYzLBYL9xBhsKQvM5BtlBnYTVQqFdra2uBwOHiXCotBsTmUxadYoK5SqSCbzW7qNmUVs6wYxGKxIJPJwO12o1arYXFx8aHpwD4sSqUSotEo4vE4stks77JglbDFYpHPmyKR6LbrB1uXCoUCAoEAUqkUlpaWsLKywtetVqFRd5r5HhiNRlgsFvT09PAzjtFovK3c4E6fDYB3sFQqFdjtdkQikYfSyf5IA8IGgwFHjx5Fd3c3vvrVr8LpdEKv1/N/L5VK+MUvfoF33nkHXq8XqVSq6TclxKODVZX19/fD6XRCKpUilUohl8vh5s2b+OCDD+46Y1IqleD1elEoFBCNRpHP59HW1gatVguHwwG1Wo1isdi0FTcGgwGHDx9GZ2cn/tE/+kdwOp2w2WyoVqtYWVlBKBTC5OQkJicn77kqU6FQYHh4GG63GwMDA/B4PFCr1ajX61haWsLly5cRCAQe0p09OliwM5FIYH19nZtc7mXS6TQ++eQT+P1+fOUrX9n2e/x+PyKRCMLhME8msE0/090GAKfTiW9+85uw2+0YHBzcpFEHbBxIzp07h8uXL+PcuXPw+/27uqFmRisHDx7E008/Da1Wy+UB7rUa+Nq1a7hw4QL/c0dHB06ePAmVSgWj0XjLIZJVCqvVavzgBz9AOp3Gz3/+c5w/fx5zc3NYXl5+ELf4yGEVaSMjI3jsscfQ398PpVLJzZ8WFhY2reFMSsNut+MrX/kK+vv7YbFYIAgCD4b++Mc/xuuvv46VlRVkMpld3wM0Jo5Y4vHChQtIp9OIRqPIZDKYmZnhSTexWMwNm3p7e+FyuTA6OorDhw/z6iyGw+HA17/+dczPz2NxcRFra2u4efNmSx2uG5FKpfyg3ZhUrVQqWF5exuLiIl9vW2nTv5u0tbVhaGgIR48exXe/+10ud+Pz+fDLX/6SVwhnMpmWrZ5lhR1ms3lTMLhSqWBxcRFXr1594NUwrYLFYsH3vvc9dHZ24vjx49wPgrVjb0cqldqkc7q+vo7z589DLBZzWbGnn36an79qtRqvYFteXuam1s1MqVTilfF+vx9isZgnmraa17JzAju8Ly8v4/r161CpVLDZbBgeHsZzzz0HmUzGZQrX19cRjUaboqvpfqhWqzzY8rOf/QwXLlzAN7/5TRw+fJgnKlkrs1qtRqlU4gbmDocDTz31FJxOJ86cOcPNjxi1Wo3vE2/evImrV6/esyTdbsGCwV/60pfQ0dGB3/md30FPTw83c7p8+TKmpqYwPj6OGzduIBgM8qrFvYJKpYLVasWBAwfwx3/8x9xErjEYDGx0trz++us4f/48xsbGEA6H77jGMBlDq9XKKyS3nquYZJrX68WlS5ea5h3T6/XcU0gikSCdTuP8+fPI5/PQ6XQoFAr4+7//e0xNTfHiD3Z+YPvXwcFBHD16FMPDw/jqV7/KTT87Ozvxgx/8AIuLi1hYWODdGK0yrgKBAN566y2sr6/j4MGDcDqdGBgYgFwu5+bjJpMJWq2WF07sRLFY5AV8KysryGazmJiYQC6Xa2rd+u2QyWTQarXo6urCd77zHdhsNgwODkKj0cBisUAul0OpVD4QCSuFQoGnn34aPT09WFpauuuO+LvlkQWEmYOw0+mEy+WC3W6H2WyGSCTimq6pVAperxezs7PIZrO3nXgadTpY5VerZnLvF5aFY63Oe/n+2b2yilVWbcUqBBKJBCKRyF23YdTrdeTzeS4bUKlUeIWfUqmEVCptymqURs0nt9uNjo4OdHd3w2KxQCQSoVgscgmEeDx+X61uTOvIaDRCq9VCpVLx9qFMJnNPz7nZYZWMze6o/aCoVCqIRCJQq9UIh8O3yOzU63UEAgH+FQwGkUwmEYvF4Pf7MTk5CWDjAF8sFpHJZLhsS2NbN6sIXF9fx9LSEnfs3g3Yxk2n03HTHavVCrVafUvly9bWdFYpxVqY2Dhh98WqrFUqFUqlEtcl3JoFZvOXVCpFe3s7KpUKXC4XzGZzS7pzswojpmXJ2uRY10Y+n4ff79+kJ8aeAZtbHA4HHA4HNwxj1aPLy8uYnJzkuoePAmZYlkgkAGBT0LZQKCCbzSKTySAQCMDv92N+fp5rnqVSqU3SFoIgcN1F9i6w3zmrzGHIZDLYbDZks1m4XC6USqUHIlWyW0ilUm5iyqpE8vk8crkcTzLlcrmWOQTtFqxLRy6Xw2q1oqOjg+sxSyQSFAoFJJNJrKysYG1tDYVCoWWDweydYMZfbPwzCYNUKoVEInFP60ertpxuB0tUM6OnxpZdlqwql8ubtKij0SjW19d5kILJKMhkMr7Pbdzv1Ot1HkRurN5vZlhVM9uH3I6tskys2421LTNdzEqlglAohEAggGw225Janwy2X6nX61hZWeEdBfF4HAaDAVKpFCqVildFdnd3c71hVgxit9vR3t7OAxrsM1m1IAuWtopJLptrFAoF3G43uru74Xa7Ybfb+VgKBAJYWFjA/Pw85ufnkcvlmvIs+Hlg1YwOhwN9fX2bNIMZrBPK7/djYWEB8Xj8rp4Dq2ZkHQ3d3d2bui9ZZWg2m0UymWyKACCLJzF5B9Y10CgZo9frUSgUsLa2hrW1tVu6B9gcIxKJoNFooNPpkMlkoFKpoFaroVKp0NHRgVKpBLVa3bQxhp1gsYVwOIxIJMI9UgRBgEqlQrFY5L4gbO7ciUqlwgPiiUSCnxe260xp7LJslLth5zK2T3hU632jLBPrKDGbzXzOdDqdm6RnGmH7ksYO3MZ1iSV5WWxzu/+2zWZDvV7nfgLMxPBB8EhOHqydtr29Hc8//zzcbjd0Oh1flNPpNF577TXMz89jbGyMG23cDqVSiba2NvT29qKnpwdtbW0P3QimmZDL5VAoFOjp6cHo6CiGhob2pAkW8FnGUa/Xo7e3F/39/bxilW1imSPy/R6KRCIRz4AbjUZent9sWW+bzYZDhw6hp6cH3/zmN2GxWHj2lclD/PCHP8TExMR96yCzFnCDwQClUgm5XM4rTYLBIJaXl1tmA3g3KJVKbiyx1ymXywgGg0ilUvjX//pf31LVC4C3SLENMsvms4MX09zt6+vDkSNHYLFYNi1+1WoV4+PjWF9fxwcffICzZ8/u6ngxm83Q6/X46le/iq997WvcNGNr+87WDV65XMbk5CRisRg3q7l06RKmp6f5z5nNZrS1tW0yNdquOpjRGBx1Op04cOBAy2nvseSuQqHA888/j6GhITz22GMYGhriG2mv14u33noLS0tLqNVqvD3R5XLhO9/5Djo6OtDR0QG1Wg2RSIRyuYwPP/wQc3NzmJycvKs9wIOkUqng7/7u73D16lV85StfwWOPPcYTCTMzMzh37hwCgQAmJiaQzWYRi8X4nNjYjg1s/I4jkQiSySREIhESiQTcbjcOHDgAnU4HmUx2yxgxGo146aWXsLCwgOvXrzfFIel+aG9vxx/90R+hq6sLBoMB2WwW7777LtbW1vDmm29ieXm5JRMgj4JGGR+xWIxnnnkGTz/9NDo6Orj+IvPYmJ6exuLiIiYnJ1u6ipEdwm02G55++ml4PB7odDquC+v3++Hz+e5pPqhWq8hkMk3RXfAgYF1MTG+eJc8aTdTGx8extLTED5hra2uYm5vjQeJisYhUKoX29nZ88YtfRHt7+6bzUrVaxczMDK5du7YvKrGVSiWMRiMOHDiAf/pP/ymcTidkMhn8fj/+6q/+ine35PP5lk20MCqVCubm5uDz+aBQKHDx4kW88MILOHHiBA+wDA4O8rbvTCbDk7wymYwnzVly75NPPsH6+jrOnTuH1dVVXiTQCshkMjidTrjdbjz//PPo7++HzWZDrVaDz+dDJBLB+++/jzfffJPHJlr9978ddrsdL7zwAvr6+nhxRKN8XKVS4TrcXq8XsVjsrs/CZrMZL7/8Mjo7O3HixAnYbDZ+zmCSSe+//z6uX7+O8fHxh3J/9woLYLvdbq61zYKUb7zxBq/EZFXN5XJ5R3NtJl/DJGu6u7vx/PPP8yC81WqF0+lEMpmEz+e7pZuhWWEyH+l0GlNTUygWizh06BD/3cpkMhw/fhwqlQrvvfceFhcXd9Siz+VyWF1d5c+QJTa3mtUJgsB1hk+dOoWenh709vaio6MD8XgckUgEly5dwj/8wz/wwr6HTWdnJ/r7+2G32+HxeGAwGNDe3g6j0YjBwUFeoLkVJn/FdNoDgQCWlpY2dYf29vbimWeegclkQnd39y1BYbFYzDvZh4eHkUwm4fV6H5jkyiMLCDN91s7OTtjtdr4ZyeVySKVSmJ6exs2bNxGJRO4qa8JMWfR6Pc/y7tWAKPDZy8H0WdRqNdRqNWw2Gzo7O3nbLbDZlGUvVEmwQ4NKpeKtS8xZmI2ffD7/ubJtrCKnUfexGccTaz1hIv1Mc4+54fp8PkxMTODmzZv3XeXRGPBhenNMPoNldVv1ALodLBvXjL/vBw3b1Ofz+U2SB3cLe1ZOp5O7mje2ErJq60AggMXFRayursLv9z/AO7h3mMB/d3c3jh07xpNpW2EtyqxqnOlbsa9UKoULFy7g6tWraG9vR0dHB2q1Gs9cszm6kZ26NthGZ2swvRVg84NWq0Vvby8OHz6M7u5uOBwOVKtVFItFxONxbnYKfLYHsFqtXI5Go9FALBbzgKrX68XMzAyi0egjr5yo1+tYXFxEJBJBT08Penp6eHDO6/Xixo0bWF1dxdjY2LYHxMZAHksKsOqFTCbDjdPYhnXruiyTydDR0YFisdjSiW2NRoPh4WG4XC7IZDK+8WcVV6urq3tq7XhQsAoYsVjMXcu7urpw/Phx2O12dHZ2IplMYn19HcFgELOzs1hdXUUsFmtJwysG0xNXq9VwuVy8sKNSqSAajcLv9yOTydwyH9xO27VWq3Ez070QEGYBbqbDz+YUtudLJBKYnZ3le75KpYKVlRXMzMzwz2BdLFarFVqtFjqdjgeA2GGcPe+90v21E2yvzzwERkdHodPpuBfJ1NQU5ubmkEql9kTXGCucyWazmJ+fR7FYxIkTJ3g1I4BbJCG2rk+NHZVerxeLi4uYmJjA6uoq4vH4o7yd+6axQ8lut/OkNNv3Md3glZWVe5Lw2m4uatZ5h+3fDQYDuru74XK5+DmPwfYt4XAYPp+Pn6/v9l1QKBTo7u5GV1fXLecDJr21srKCmzdvbtL53k0kEgnUajUvgGJdONlsFqurq1hZWeFeH8zjYafYSi6XQy6Xg06nw8LCAlQqFarVKl/jFQoFj9+0mu8VSy6Gw2HodDrk83loNBpeMdvW1oZ8Ps9Ns1kV8FZuZ6TN9tDsXKXX66FSqdDd3Y1Dhw5hZGQE/f39XOM7GAzyc8TDhJ3vTCYTurq60NnZieHhYRiNRnR1dfGixUb9bfbFgtXxeByJRAJer5d3Qk5NTfH/RqFQwKFDh3in6VZYVya7DrPZjGAw+MDu8aEGhJmcwfDwML7xjW+gs7OT65FKJBLkcjmMj49jbW0NY2NjmJubu+vKGIlEApVKxUvzWaXRXkQkEsHj8XD9S1ZFodPpeKuuXq+HWCzmmrjMsXwvtM6p1WocP34cHo8HTqcTWq0W0WgU2WwWH374IWZmZh6KwHYzwQTcPR4Pvv71r8PhcHDzpvn5eYRCIfzoRz/C0tISvF7v5xJmVygUOHDgAHp7e6FWq1GtVhEMBnkbYjgcbomWwruF6S3X63W0t7fv9uU0LWq1GlarFaOjo/i93/u9TZl/YKOl6ObNmwgEAvi7v/s73Lx5c9erAQVBQH9/P06ePImBgQFuerAdsVgM7733HsLhMObn55FOp7nzNmuBYovvmTNn8Lu/+7vQarVcWsVqtd6iE9X4Djb+f0EQ0NHRAZlMhk8++eQh3f2DhR2k1Wo1XnjhBXR3d+PZZ59Fb2/vJv29sbExXLp0CXNzcwDATZBefvlltLW14ejRo1yjPZFI4IMPPsDq6ireffddLC8vb3KHf1SwQ3M+n8err77KXa9ZtS87EGx30JPJZOjq6oJOp8PIyAjMZjNMJhNUKhUsFgs37tkPXUwsUa/VarkcWDQaRSgUQiaT4WZ8xAYsMaRUKnHixAleDczkoNrb2xEKhfDBBx8gEAjg5s2bCIVCuHHjBk80tDJqtRp9fX3o7e2FwWDg+3hWoTYxMXFL9QtrwWUJpa37/mw2i2vXrsHr9e6J4GYikcBvfvMbWK1WJBIJGAwGzMzMIB6Pw+/38y65ZDLJ22i3apBbrVY8/vjj6O3txfDwMNc2ZJXYwWAQ169fx8TERMsE+O4HFow5cuQIfvd3fxculwsOhwPRaBQ//elPeQdDOp3eE8FgBus+0Gg00Ov1KJVKiEQi3ATpTqTTabzzzjvw+Xx47bXXsLKygkgk8shMXz8vMpmMmwf//u//Pjo6OmC1WlGr1RAIBJBIJPDKK69gbGxsU4DmdrBCJSaT1Kh9zqSRGmVcmoHe3l6cOnUKQ0NDOHPmDLRa7abff6lUwvz8PMLhMH784x/zs3UsFrtjkp4l93Q6HTdmaww0VyoVXLp0CV6vFx988AEuX77MJbp2m3w+j1AoxDtwtFot5HI5X2sUCgVSqRSXlrkdLOjrdDq5z08ry4BthZ2T5ubmoNfr0d7ejtOnT0On0+H48ePo6+tDrVZDb28vrl69irm5OW5UvhON8qfd3d0wGAw4deoUbDYbnE4nr+BmHYjLy8sYHx/H5cuXuU/Sw56v29vb4XQ68eUvfxlf/epXoVar+fypUqk2FQUxWQgmKffaa69haWkJoVAI6XQaiUSCF9elUimIxWJIpVLUajWeRGH7msZCz8YuMlbY9CCTCg91lLKLdjqdePLJJ2G1WmE2m/kNlMtl+Hw+LC0t8cqHu4VNxnK5HDKZbE8etFjmUSKRcB25EydO4MiRIzAYDNDr9VAqlZta3cvlMhKJBFKpVNMtRveLXC5HZ2cnP3TLZDJks1lEIhEsLCxgcnJyT29igc+c2y0WC4aHh7mxSDabRTgcxsrKCi5fvozFxcX70mhsbHmXyWRcq5llqjKZDOLxONLpNPL5fNNmwO+HTCaDYDAIl8u125fStAiCAKVSCYvFgvb2dl5VA3wW6KxUKlhdXeWLdbO0g1ksFt4ayDao282LuVwON27cwMrKCq5cucLn0VKptEmnSSwWw+Px4Omnn+Y6n1vZKRDcCOt0YJucZofNDWq1GsPDwxgZGeGmNKxybWVlBefOncPc3BxisRg0Gg3XITx9+jRsNhuX2GCbb7ZpZMmE3YJVFU5OTnIzPKbzdbtDL9P1stvtOHbsGFwuF1wuF/R6PU8WsOrhvQ6rHmfdNkwvkOkw7qUgy+elUX9cq9VicHAQIyMjOHXqFAYGBvj+LxgM8kQva+mfmZnZE89SKpXCarXyBArbx9dqNV6htrVVWaFQQKfTcS3crdV5zGyMaei2Ovl8nstn2O126HQ6XLlyBcFgEMFgEOl0+o6fodFoMDg4yDs52NpdKpXg9/u5FnUwGNzTFfxSqRQajQbt7e144oknoNPpoFKpsL6+jkuXLmF5eRnxeLwlgpz3QqPeJZPby2azdy2TViwWMTc3h/n5edy8eRPr6+sP+YofLKzS0OFw4MSJE7xDicmxhMNhTExM4NKlS3clb8a6dVknJUuwABsV/SxQzgJDzYLFYsGRI0fQ19eHrq6uW+SrKpUKwuEwVldXce3aNdy4cWPHtv+tsHgPq5Tc6s9RrVa5xAjrHmwWyuUy0uk0stks8vk8DwYzTVeZTMb3g3eCPQetVgubzbatyXQrk8/nsbi4iGw2i5s3byKXy2F0dBQGgwFutxsOhwNerxcSiQQ+nw9erxcAbvvsWGe2SqXiSbonnngCnZ2daG9vh1ar5QUFgUCAxzwmJiawtrbGpZQeJuz++vr6cPToUR74bewQaPw912o1pFIpBAIBnD17FtevX0c4HN7WMJolEer1Ok9AbPWzYbC/fxidzQ81IMwWIL1ez01WmBYR01i5ceMGb8+5X7Zr0238ZW33Pc0KMw1j5hHHjh2Dw+HgbuydnZ2w2WyQyWSQy+X8kMkc0Ofn5/GLX/wCKysriMfjj+RFeViwjKPVasWTTz7JA8KseoSV3M/OzjZNpvFh0dvbi6eeegqHDh3iLTg+nw9ra2v40Y9+hNXVVX542mnibUwwNCZQmLanRqNBV1cX7HY7jh49CofDAZVKBUEQYDQaIRKJcOLECdTrdUxPT99TW1Uzw7Si98IB+2HADEf6+vrw7LPPwu12b5JcYIm9SCSCN954AzMzM01zYBAEgWuZmc3m235vuVzm0hBf+MIXNt1jY6eFIAh48skneUCiESbXUywWEYlEUCgU4Pf7Ua/XucQLy+qyBV2lUkGn03HN5maDVQbr9Xq89NJL6OzsxBNPPAG32w2tVotSqYT33nsP165dw7Vr13D9+nUAG9ppQ0NDeOGFF+B0OtHd3Q1BEOD1ehGPx/H666/D7/fj6tWriEajTaNL3thZ0yi/tBMajYbr8fX09ECv10OtVvNN3oNwF252mCanw+GAWq3mJrdqtRpf+MIX0N/fj0QiAUEQkEgkmk6b/1EhFouhVquh1WrxxBNPwGq1btKEczgcsNvtm36GrU+FQgHFYhHlcrll93R3CwtYJZNJHtRl7bxPPvkknnrqKRw+fHjTHnivwtp0E4kEzp8/D5lMxisQ7/QeaTQa2Gw2DA0N4fTp05tMPAuFAuLxOM6fP88Dznu9gt/j8eDJJ5/EwYMHodPpEIvFeGfK5OQkIpHIngkGM2lBlUqF0dFROBwOPPnkk+ju7kZbWxvMZvO20lnbwQy9C4UCbDYbisViy5gPAoBer8eJEyfQ09MDu90OvV4PYKMI4OLFi5idncXCwgIvANgO5jUiFou5HuyJEydgMpkwMDDAu+VKpRI+/PBDLC8v4+bNm03lEWG323HmzBnuobGdDi6TnXE4HJtM12Ox2LbJJ/Y8TCYTBgcH0dfXB4/HA7vdvilIXiqVEAqFsLa21nQyR42yOePj43C5XDhy5Ahfl5VKJd/P3wkm6bO4uIg333wTIyMjGB4e3lQtvRfIZrO4fv06AoEAbDYb2tvbebHa8PAw39ccOXIEFy9exKVLl7gfDYMFgpmmNfNIMhgM6Orqglqt5obmH330EaanpxGLxZBIJBAMBrG2toZsNvtI9kNM3uSTTz7hCgfJZJJXSZvNZgwPD0MsFiOTySAcDuNHP/oRFhcXcfPmzdt6PXR0dGB0dBTHjx+HzWaDUqmEIAjI5XJYWVnh51i5XI5SqYRcLgefz8fnrAfFI6kQVqvVMJvNfMIsl8vIZrOIx+NYWlriTp4Pgttpi7UCrHSeObB/5StfQV9f3yYH9+0yAsViEbFYDIuLi/jNb37DqzlbuZKTBYQNBgMOHjzIdVoKhQJ8Ph/m5ubg9Xq54Ptepq2tjRvMqNVq5HI5RKNRLC8vc9OeO8lEsHYDloljGAwG9Pb2wmaz4cSJE7Barejt7eVVJLVajWt0DwwMoFqtIpFI7KmA8F4/CH0eTCYThoeHcezYMbz88stc4xL4THeXLc6XLl3CxMREUwXXbTYbBgYGANxeU51pPBUKBYyOjqKtrY27azciCALcbjdPqmytBmY6uqyNd2JiAvV6HRaLBVKplOtyN7b+sKqdZgwIsznDYDDg6aef5pt+1npaKpVw/fp1/OpXv4LP54PP54Pb7eb6wt/+9rehVCohk8mQSqUwPz+P5eVl/OY3v4HX60UikWiqSj7mAHy3KJVKnDx5EocPH+bOv8CtSei9HMRjB0Kj0cjnB9bFdeTIEbS3t+P9999HOBxGPp/ftwFhkUjEtVyZiVpXVxf0ej30ev2mAE2j4QoLBJfL5X2xTrG5sNHUi3UnHDx4EF/72tdgMBj23CF7O5gGIZN3uBeUSiWcTifXO2TPjI2pTCaDqakpjI2NIRqNNtW6/TBwOBw4deoU2tvboVQqkc1m8fHHH3Pd2L0gMcJgc43BYMCRI0fQ39+Pp556Ch6P57Y/t906JRaLYTQakc1mYTAYeFKvVQLCarUaAwMD3OxUrVZzo2Q2/u+kn61QKGA2m/n5qa2tDc8++yyXBmDV1uwsodfr4ff7myogbDabMTQ0dNtEGkuIM43tQqHAtX93Cgizc3p/fz/vGtvqLcJ0msPhcNOt/2zfnkwmsbi4CJFIhCNHjkChUKCrqwu1Wu2uPVeq1So3pLt8+TKkUumenFeLxSIWFhYQi8XQ1dWFeDyO9vZ2LpHW0dEBjUaDvr4+pFIp3jG6NSDMiv6Y2enw8DDXXWYm6KFQCO+//z7ef/99pNPpXUkosOT0xMQEgA0pp/X1dTidThw9ehRdXV3o7+8HAB4QfvfddzExMXFHc1KbzYZjx45hYGAAer2enzmLxSJWVlYgFot5x3apVEKhUEA4HMb6+voDXbMeakDY6XTi8ccf51HzSqXCW9zfeustrK6uYnFx8a70abYik8lgNpt55SKDLWb1ep3rd3i9Xni93qapQNoJVr1pMBjw4osvoq+vD8PDwzyY3tgel0wmkUwmsba2hoWFBSSTSfj9fl59lcvlWv4AqlQqecuAWq2GVCpFPp9HIpHAzMwMxsfH77syWCKRcH0aJr0hFoub7plJpVLIZDJYLBZ4PB4YjUZu2jQ5OcmTKY2V4CxpwNowWTWAUqnkmxqn08n/G0qlklcDu1wuqFQqyOVy7ladSCRw9uxZLuCeSCT2hRP1fsdsNsNsNmN0dBRnzpxBV1cXD2YCG9UV8/PziEQi+O1vfwufz4dQKNSyUjUmkwnf/e53USwWMTw8DI1Gs6O5ZGOyhFXwJRIJxGIxLmEzOTnJNwYikQjZbBZOpxMnTpyA0+nc1L46MjKCpaWlu2r/fdQolUoMDQ2ho6MDXV1dcDqdUCgUqFarmJqawvr6OiYnJ+Hz+aBUKnlFxMmTJ9Hf3w+FQgGRSMTb8qanp7G+vs47h9gBqtWSl8yxvLOzk1d+32/7FjO7cblcvJJvamoKyWSyJd4nZsKYyWSQTCa5lIpIJOKVVV/+8pfR39+PDz74AIuLizzwns/n+RrWTImBBwlLqNhsNl4xf/ToUZjNZhgMBm5k0wjrcHM6nXjqqacQj8dx8OBBLC4u4pVXXkE6nUYkEtmTAWImPcIMawBwh3abzQaTybStVA+xAUs29vT04Lvf/S46Ozuh1+shlUpRLBaRSqXwzjvvYG1tjcv7tEpw715gZ6bBwUH09/fj1KlTOHz4MGq1Gubm5jA5OYnr16/ftZl5K6BUKuHxeGAwGHD8+HFYrVacOHECdrt9x/b1TCbDdS3D4TCkUik/F7W1tUEul2NwcBBOpxNisRjBYBBXrlzB+vr6A3W5f9AwaQe9Xs+12VlChBmSM9PTrUEmiUTCzcb0ej26u7tx+vRprmfKPnOrDq9IJILFYuEdVGKxuGW8fCQSCTo7O2EwGKDT6ZDJZFAqlVAul+H3+xGNRnlCN5VKIRqNwmq1YnBwEDabjeuTNyY2q9UqwuEwL1ibn59v2lhMJBLBhx9+iFAohL6+Psjlchw6dAhOpxNra2tYWVnB9PT0XXldsbHXaDLGAuu5XA7ZbLal125mdlqtVnHu3DksLCzA7XajUCjA5XJBp9PBZDJBKpXizJkzAIDp6WkeJNdoNHA4HDh58iT3TmBa3OVyGWtra4jH4/jNb36Dubk53Lhxgxur7gas4I4lDlmCpFqtorOzEyaTiUvQ/Pa3v8XS0hL3W9rpbMNiNXa7HUeOHIHT6YRIJOIFnky2kM1ZbAyxZDnbNz8oHmpAmLWoeDweiEQilEolJJNJrKys4Ne//jVWVlawsrJyX8YYUqmUG7YwrToAtwg6BwIBeL1erKysNP2Gp9EF9cUXX8Thw4d3/N5kMgmv14tLly7h7bff5g6p+Xwe8Xi85Q7X26FQKNDe3g63280DwqlUapOr8v1miqRSKdra2rghn0qleiROlfeKVCqFSqWC2WxGV1cXJBIJSqUS4vE4pqam+OTUuLCwVnSbzQar1YqjR4+ir6+P6053dHSgv79/x0p69vfFYhHLy8tYW1vDT37yE4yNjcFoNEKtVjftBpB4cJjNZvT39+PQoUM4ffo0r35kGxymIbW8vIxXXnkFfr+/pbsSzGYzvvWtb/E/36naHvgsIMwOFouLi/jVr36FUCiEK1eu8EoIuVyOeDwOl8vFA0A2mw1qtRputxvDw8PI5/OYn59/uDd5HyiVShw4cIA7RzOtbVaxNj4+jqmpKfh8PoyMjODgwYN47LHH8Pzzz0On00Eul6NWq/EN1NTUFKLRKDdkYJU5t3Nubkbkcjna29vR1dUFrVb7uQLCYrGYm4Q+/vjjcDqdCIVCyGazLXGYrFaryOVyPLCgVCq5RjZLMD733HNIJpO8ooFVl7PkYj6f3zNBma3IZDLeqfC9730PbrcbOp3ujmYz9XodLpcLbW1tvJPlypUrmJychN/vRzweb+lD5U4wzXpmQC0IArRaLdra2rjmMLEzTHrO4/Hg29/+NjQaDVQqFWq1GjKZDCKRCN58803Mz89jcXGxaQM0nxcWGB8aGsJLL72EwcFBHDx4EMvLyzh79iwmJydx48aNbXUdWxWlUomBgQF0dnbiW9/6FtxuN29D3olsNgufz4dgMIjp6WmoVCreBm2326FQKDAwMIBarQaPx4NUKgWtVoupqSlks9mmPQ+w90Cn06G/v59LptRqNeTzeb5v267bUSKR8AKajo4OHD16FF//+tdhNBrR3t6+Y4UtCwiXSiUeEAZur6HaLEilUrS3t6OtrQ2jo6MQi8XcQyMSiSCZTCIejyMej2NtbQ3z8/Po6+vDl770JZ7g3/pcmB78+vo6lpaWsLi4uEt3d2fC4TA++ugjJBIJnD59Gm1tbTh48CAKhQLW1tbgcDgQCATuOiDMAn6CIPCuDBYQLhQKLXtWAsDNS5mfk06nw5EjR7ixMAsIm0wmVKtVOJ1OvP7665icnIRKpYLNZsPIyAi+973vwWq18oKjer2OfD7Pde1feeUVXL58ebdvl3fpsLglQywWczkV1j3929/+FgsLCzwgvBMsVmO32zE6OsplCJlWciqVQjKZhFKp5PNHY1LhQXe0PJSAsF6vh8FgQGdnJzo6OmCxWPhNsocZDoe5xu39wEwSOjs7t20bY4MqnU7zlodWePnYoTifzyObzfLN8FbxaKbhFIvFeNl4Op3eU/pyarUag4OD6OnpgUwm44L3LPB0O73cnWgMuj/++OPweDwwmUxc2zCbzSKVSu26pqxEIoFYLMaBAwdw6NAhjI6OQqFQ8A09W0y0Wi2eeuopVCoVvvlgVZydnZ1882K1Wnm1calUws2bN5FKpXilXm9vL9RqNSwWCz+klstlLC4uco1mZpbADqZ7BaPRyFvJCPAAzsDAAM6cOYPBwUFeASkIAsrlMnK5HILBIG7cuIHV1VXeQtgKc+yDIJVKIZPJIBAIYHl5GaFQCHNzcwiHw1hcXOSVnYxqtYpAIIByuYxkMtkSEiVifuY3CAAASQhJREFUsRhKpRI2mw1Hjx5Fd3c3b4tk65TRaERbWxu++tWv4vHHH4fL5YLT6eTvExszTHbCZDLhySefRDab5Vnurq4uRCIRfPLJJy0l/8MMmcRiMZaWlrjUU6Mcz73IVzF92ZGREV6FHQqFcOnSJQQCAcTj8aYNXLDur9XVVbz++utwuVx46qmneFWnVCrlumiPPfYYD3DWajVEIhHEYjEUCgVks1meOEin0/B6vSgWi49MJ+5hwfQJ19bWcP78eW4OJhKJEIvFkM/neTUWg+0BPB4PRkZGuNGNw+HAc889h4WFBXi93qYvdLgdrMqImQ5Wq1VugNXX18f1y4PBIEZHR9Hd3X3HlndiQ5Pw4MGD/JAplUohCAIKhQLvmFxbW0MgEGjp8XMnDAYDDAYDuru7MTg4CL1ej3g8juXlZVy4cAFLS0tNVwRyr0ilUqjVamg0Gu4x86UvfYkbQ2u12lsST8lkku9f/H4/1tfXuR6l3+/na7XT6YRcLofZbIbL5YJMJuPz+NDQEHQ6HdLpNDeJbcbAMDs/q9VqKJVKfr6+efMmVlZWeDKEGb9arVauC+p2u2G1WuFyuWCxWPj5a3V1FYVCAaurqyiXy7wj5sCBA9BqtXzNGx4eRiwWw+rqatP4atwOZhxcq9X4nCGTybgEhlwuh0ajgcVigdVq5c+HdaNuTYizQoCZmRneydzMMAm8SCSCs2fPwu12c+36/v5+mM1mJBIJPoeyfUtjIpt59HR0dODZZ5/FwMAA7z5me14me9DsZ4B7oVQq4cKFCzxg7vF4NmmVMzmIM2fOQKfTwe12o6OjAw6HA1qtFiKRCIVCAVNTU4hEIvjggw+wtraGUCi027d2W1QqFdxuN0wmE9LpNKLRKNbX12+7trJEQW9vL1cCUCgUPJaZTCZx7do11Go1Ph/JZDIUi0VcuHCBnzkfNA8lIMwqyw4cOICBgQGo1WoIgoBsNouZmRnMzc1hbW3tc7WdGwwGnDx5cpNweSP1eh2ZTIYfolqp8oRtkpPJJDel2WpgxKQTWECClZHvJXQ6HY4fP4729vZNEgbMMO9+siOshdVms+HFF19Ef38/7HY7BEFAJBLhm5rdHjPMNPDEiRP4/ve/zwMN2WwWuVyOa9Lo9Xo89thj0Gq1XBeNVUXY7XZotVoelGCmNHNzcxgbG8PCwgLOnj2Lrq4ufPe73+Xu040B4fHxcYyNjSESiaBSqfCD+l7CYrFgcHAQDoejpfXHHxRarRZGoxHHjh3jFRGNhmzlchmRSARerxeffPIJ1tbWbiuYvxeJxWJYWVnB2NgY3nvvPfh8Pty4cYO3928NXlUqFSwvLyMcDiMSiTzwVp+HgVQq5Qklpu/FqozY/dlsNgiCgJdeeglut3uTietW911mTPPyyy/zny+Xy1haWkIwGEQwGGypgDDTUMtkMpiYmOAJOhYQbrz/OwUzWRWJTqfD448/jnq9jueeew6ZTAZ/9md/hvPnz2NmZqZpA8Is0VEoFPDXf/3X6OzshFqtRmdnJ2+pVavVUKvV+OpXv7qpoysajSIajfKqB/ZuLS8v48033+Sf2+zvy+0oFovw+/0oFAr4zW9+w7t1AODmzZuIRCJYX1/fdGCWy+VQKBT42te+hj/8wz+E3W6HwWCAx+PBP/7H/xhXr17Fr3/966Y/ZN+OSqWCZDKJVCqFYrGISqXCq/pGR0fR0dEBj8eDRCLBdVAbEy7E9rBKdOY5war28vk8pqameOt2K82394ogCLDZbOjs7MTIyAiOHz+OeDyOQCCAqakpvPHGG5tMC1sVuVwOi8WC9vZ2vPDCC3C73Xjuuee4ifvWPW1jxeYnn3yC8+fPY2VlBbOzs6hUKqhUKrzd3ePxQK/Xo6urC0ajkc/jKpUKJ0+exMjICIrFIpRKJa5cudJ0AWGWjJZIJNBqtVw7OJ1O49y5c1wuBfhMnq+3txe9vb04deoUTp06BZPJBLvdjlgshqWlJSQSCaytrSEcDuOdd95BPp+HVqvlyQcms+F0OnHq1ClIJBK8//77LRMQ3mo0yM6DjfNuozTnTr5NLLiazWZx6dIl3Lx5kxtzNSu1Wg2lUgnr6+v49a9/jc7OTlitVrS3t+Po0aM8+eL1ermBdjQa3TSHyGQyaLVaDAwM4Nvf/jaXN6pUKpu6qO5X7rJZKRQKePPNNyGTybC+vo4DBw7gzJkzXLueFQEAGzHC7u5u6HQ6uFwuvj7F43F88MEHmJ+fx6uvvgqfz9f0RUYajQb9/f0wmUxIJBLw+/1YWFjYVEW8FYlEAqlUys/YPT09PE4KbJwv33//fRgMBvz+7/8+bDYbZDIZMpkM3nzzTYyNjT0UbfKHEhB2Op04duwYuru7oVKpeKapWCzC5/PxSqnPy3YTUa1W49Vbk5OTPNvQCrAJNJVK4b333sP8/DyvsrJYLFCr1fxQwLLBIyMjWF9f59UnhUIByWSypatpmGupVquFyWSCwWCARCJBPp9HIBDg2dn7gQUm2MTOsufVapW3DkWjUd4ms1s4nU643W50d3dvCuxKpVJotVrY7XYcPnwYIpGIZzGZcyxrvV1eXkalUkE+n0epVOKLkN/vx9LSEqLRKM9SqlQqrqNcrVaRSqUQDoe5oHuzmQA8SHK5HMLhMHQ6XUu/Nw8CQRAwMjKC0dFRHDx4cJPRERP5X1tbw29/+1t4vV7e1t6sme56vY65uTm8++67MJvNsFgsvGJELpdDp9NtkkhZX19HpVLh7f9M25ZVAbC5NhqNIhKJYGlpCaurq7zbZafxw9oIjUYjbDbbJodv5mjs9/u55FEzwKpD2HzJ1nGGSCSC0WiEWCyGRqPZtoWSHRhYu1y9XucyG4lEAvl8HqurqzxI3oowfT2lUgm32w0AXCqDJQhYIo3tWZjZT2PAeGswnbWs9vX1oVgsckOWWq3WtJtk1kUSDodx4cIFrKysoFwuw2g08vWlEXavIpGIV7mpVCooFAouoREKhXD+/HneEdXqgeHV1VXEYjF+wA4EAkin07cYjzRq1n300Ufo7e3luuZsH9De3g4ACIVCLRnYKpfLm4J02WwWPT09UCqVm5LTuVwOdrudV7sC4HMJGz8EuJnP4cOHN3Vn5vN5RCIRrK2t4fLly1hbW2vZ+fZukEqlXA/18OHDcDqdEASBd1zMzMzwLsNmWW/vF41Gg97eXm5qZLPZ+P6FrSnM1It5PszPz2N9fR3T09NYWVnhPj5btfxZpVo0GkVbWxvsdjv/fFaI1d3dzTs9VlZWUCwWm7Y4gGlw5nI5eL1eLC0toVgsQiaTweFwwGAw4NChQzh48CB6e3thNBqhUChQqVQQCoVw+fJlZLNZxGIxbkBWLBb5GZ0lL5m0GpOvbJb1OhqNYnJyEgaDAXa7HVKpFHK5/J4LYRr3KjvBKmLZ+YolRFuBSqXCK+jPnz+PpaUl5PN53inZ2dmJU6dOwe12Y2ZmhndJJpNJvjbL5XKUy+VN+xVWLNIs4+FBw2JYq6urqNfrvOuW6QMzA3uNRgOj0YhqtYqZmRluwh2JRHDt2jX4/X5kMpmWeE4SiYTvW2UyGWQyGRQKBRQKBT/zbIUlj1iVNOtSZ3vnQCDAuyo1Gg1P6tbrdWSz2YeWyHwoAeHh4WH83u/9HhcmZ5NGOp3G+Pg4VldXH1qbEhuMgUAAr7/+Oi5dutQyFY1sAvX7/fizP/szSKVSbgbR29sLm82GZ599FocOHYLFYkFnZyccDgd6e3sxNTWFt99+G+FwGJOTky19aGKSDlarlbdASSQSFItFTExMYHJy8r41z5irpVqt5qaErJXu2rVruHjxIpaWlnZ1sywIAg4ePIinn34ax48fh8fj4QdnthGzWq28pbLxkM3GfzqdxtmzZ7G0tIRAIIBYLAav14vV1VUeUGA6j5VKBRaLBSaTCWKxmOvkrK2tYXZ2FvPz8y0xMd8vkUgEU1NT0Gq1u30pu45YLMZLL72EP/qjP+ItdI0B01QqhevXr+Pf/tt/uykI2qyHqnq9jnfffRcLCws4ceIETp8+zStBzGbzpgr6dDqNjz/+GLlcDg6HgxvwMKfbZDKJt99+G1euXNm0sdupKrgRqVSKwcFBtLe3Y3BwkOvqA8Dhw4cxMjICn8+Hn//854/kudwNYrEYCoUCSqWSB4YZrOWpvb19UzBzO9ghLJVK8aRCNpvF+Pg4kskkgsEg14ZvRYrFIjcSNBgMSKfT6O/v5zqCLDm3uLjI2+Hb2tpw6NChTXN34xxbr9e5ZMdTTz2F4eFh3tZbLBabts2bJbQzmQz+5m/+BjqdDjMzM7DZbDygx2BrWnd3N3p7e6HT6WCxWABs3H+pVMJzzz3HNQe9Xi+uXbu2Kw7TD4pcLofx8fFNxQxMI3q7roJKpYIrV65gfn4eZ86cgcVi4QazZrMZR44cgdlsxscff9ySlcKFQoEHkV5//XX09PTAarVCrVajra0N9Xod3d3dqNfrfM5h1Go1lMvlTcY9+52TJ0/im9/8Jnp7e3nBAJNDY4HQn//853u+o0epVEKlUuHEiRN48cUX0dbWBmDD1OhHP/oR/H7/njFktFgsOHPmDHp7e/HMM89wPxQGO1dms1m89tpruHjxIubm5uDz+bim6XbzDzMD++Uvfwm73Q6NRoPu7m489dRTUCgUvIjk9OnTOHLkCOLxOK+4bdaxxczk4vE4xsbGcPPmTS5nNDw8jJ6eHrz88ss4c+YMn2+YnM/U1BT+9m//FrFYDD6fj5uiMqxWK3w+H9ra2vg5jel9Nst5fHV1Fa+99ho8Hg/3BbFarQ+lM7JWq/EkLjNwbJVzJJN4YlXhWq0WzzzzDNrb2/GNb3wDIyMjOHz4MCqVCl577TVcuHABN2/eRDKZ5LJOarUamUwGKpWqac9HD4NqtYrx8XFMTEwglUrB6/VCJBKhr68PTqeTd2QLgoClpSW8/fbbWF9fx7lz5xCPx7GysnJfcqC7hUKh4LIOGo2GdwskEgnE4/FbAreCIKCtrQ29vb04cuQIjh49yvcv4XAYn3zyCcLhMORyOfR6/SbPBGZa97DW74cSEGYVnqyiiB0AY7EYwuEw1yP9PDROYI2b63K5jMnJSSwsLCAYDN5iuNUKsAW8XC7zxVUmkyGdTuPQoUPctVAsFkOr1cLpdKJcLnNtm1AoxFsTWmUCboRVRzEtHqajDIBnW+91gmWHa51Oxw2SmBZWqVTalMVshrZcFjhhByEGC0Cxd4o9j0qlgng8jnw+j8XFRSQSCUxOTmJ9fR2xWIwHXBoNHPV6PZ+gNRoN1/tk2fBAILAndGFZC2p7ezvP8EqlUj4vDA0Nca014LO2oVabNz4PrL1Sr9dvcglmFQ5sTExOTmJ6ehrZbLZpg1JbYVrZ8/PzXIKHmTyx5AhzTL5+/ToKhQICgQAPCFcqFV5NHwqF7ssElVVA6nQ6yGSyTe90uVxGqVRqmkMDg1X1suoyuVwOmUwGsVgMuVzOD0yNLsoMlsVmbtRMc5rpjxcKBSwsLCCbzSKRSDwUg4RHRbVaRTAYRLVaxY0bNxAKhRAKhWAwGPjvdW1tDaurqzzJ4vP5kM1m+ZrEZIwa1zpg473UaDSo1+uw2WxwOp1cc7eZYWOH6Qoz+a7t5L0SiQSCwSBvzTQajXC73fx72aE1l8vd0YStFbjX9bRUKiGTyfBAhCAI8Hg8UKlU6O3thUQiwbVr17gMTasdPuv1OtfjZAYtWq32lopythbFYjFEo1H+nuh0un0v98Q0Tvv6+tDe3g6TyQSJRMLfw1gshhs3bmBpaYmv3a02Tu4W1jXndDq5MVqpVMLy8jIvFkomky2/r7XZbPB4PBgYGEBvby/a2tr4+gyAGxzl83mudzo7O8s7mth8cbvnwLqjUqkUZmdnUSwWMTg4yAPCrNNKEAS+dywWi03blcu6LFk3Ty6X43PN8PAwuru7YTabIQgC745ke5SJiQlEo1Gk02kUi0X+3NhnMs13kUi0yYhtfX29aZKYzJCd+ROZTCZ4PB4oFArodLodjfIA8OIQ1qFyJxrPkfl8vuXeN5YkYfEBn8+HUqmEy5cvw+/3cymsUqkElUrFpfYkEgkP2gWDQW6UBtybp0Qrw2I0sViMV/sCuKWArVQqwefzYX19HeFwmL9bzXYWuh1MLk0qlXITvVOnTqG9vR1erxe5XI6PfYVCAZlMhkOHDqG7uxttbW28Q51VpQeDQeTzeZjNZr6OC4LAv6dSqTy02MRD310LgoBMJoP5+XlMT09jZmYGsVjsgdzQdpIR2WwWf/3Xf41PPvmEZ+ZadeNTq9UQDAYhCAJWVlYglUoxMjKCQ4cO8XZD1oZ84MABPPvssxgbG0M8Hoff78fU1FTLBG0aYQE8ZqLyIDTj2Aagq6sL3//+97kIOMu4RCIRTE5O4urVq03xzFjwKZPJbKrAK5fLXIOItVowI7yLFy8iHA5jbm6Om3yxDd92bSoWiwVPPvkkBgcH4XQ6uf5wPp/H9evXuclEK8NMafR6Pb7//e9jZGQELpcLWq2Wt/Ow9g7Wws00xnK5XMvOHfeKRCLByZMnMTQ0hO7u7k3/xg4EFy9exH/5L/+l5SREgsEgwuEwlpeX8e677/IgZkdHBx5//HEkk0lcv36dy6RslYxgFa7VavW+5waxWAyHw7FJhxfY2HTG43FustpMMM3wYDCIsbExBAIB3i5qtVqhVCp5gH0r6+vruHr1KlZXVzE2NsYPoywY3FhZzeanZph374dCoYCJiQmIRCJcvnyZt5AxM5ZqtcoD3mzP0mj2eeTIEbjdbrz44ou8Tb6xJdNsNkOv1+Pw4cPIZDK4dOlS0weEgc9cqC9evMjb+rc7ELEgeXd3Nw4dOoTHHnsMP/jBDyCVSqFSqWA2mzE0NASFQoFz587twp3sLqzKfGVlBR9//DHXQzWbzXjxxRextLSEc+fOIZ/PI5VKtdRhipFOp/Hhhx9icXERzzzzDJ+fmYkl8JnL9+XLl/HRRx/xQ/jAwABsNtttgxl7GZFIhC984Qv44he/iJGREQwPD3MT6kKhgFgshsnJSfyP//E/uAnSXt7XSKVSfPGLX8Tjjz+OI0eOoLOzExcvXsSlS5fw8ccfc63cVn8GJ0+exL/4F/8CVqsVHo+HtyszisUixsfHsb6+jl/+8pdYWFjgOuV3K2PA9j7RaBS/+tWveGdquVyGx+OBwWCAXC7nBRcjIyOoVqvwer0P89bvG5FIBI1GA7vdjhdeeAHHjx/nBTHHjx+H2+3mHj7vv/8+3nzzTW4SlUgkuKZp47MTi8XcZ0OtVkMul/PA1vj4OD766KOmCQgvLS3B5/NBrVbjjTfegMPhwBNPPAGLxYLR0dHbnrVZMIvJON6JfD6Pq1evcpPlViafz+PKlSsQi8X4+OOPIZfLMTo6CqfTyU32urq6IBaLEQwGMTMzA2BD+jGXy+H48eP7roulXq/D5/MhlUrh2Wef3fZ7WOdKIBDAysoKL3ZsJdLpNGZnZ1Eqlbh32p/+6Z8ilUrhww8/3KQxzWRp+vr64HK5eGKFFfitr6/j+vXrMBqNOHnyJBwOBy+MYGen+y2KvBseSblFoVDgB97PW3nHBOKZRk9j5SjLRsTj8ZaRibgT7OVg2YG1tTVMTk7y7K5Go4FOp4NUKoVCoYDNZsPg4CCUSiV30G21F6zRkKjx98u0n+5Vs1QkEkGlUnF9NVZNIZFI+DNlC35j5ne3YJqToVAIy8vLPNggFouRz+cRj8eRTCZ5+zALNjCzPZbFvtOkwdoy2bOo1WpIJpPccGIvOFCzykxWDe12u/kGsNHVnEmJAJ9lcdlc8zAzcrsN04HVaDTo6uriQv+N5HI5BAIBBAIBhEIhJBKJXX9H7gW2gWfa2mxekcvlWF5e5lnZXC7H35tSqcT1fFll2v0swCKRiLcQORwO3k7YKDcRCAQwOzuLQCDwEO7+/mHPIZVK8SRTJBKBWq3mnRuNB1BgI5HF2sRmZmbg9/uxurqKZDKJSCTCq6Fb/TC+FbbhY6ZYhUKBz6ms44fNpWx+kUqlKJVK0Ol03OzJZDLB5XLxLgaWvJBIJLDb7ejr68PCwsKu3ee9ci+BfiY1wQJW7DnJZDJYrVZks1mYzWYUCgVkMpmWDHzeL2wOYp1jwMb40el00Ov1UKvVUCgUTRN4uFdYJWIymcTs7Cz3MdBoNPx7WGB8ZmYGi4uLsFqtEIvFe3I+uVtYUs5ms8HlcsFgMPA5uV6v8+e5vLyMVCp1X90trQSTirDZbHytZSa4CwsLXGu7lccLS6BptVoeYGDV9KySjBWNLC4uYnV1FT6fD+FwGJlM5r60J1lyTyaTYW1tjUv6Me8AkUgEvV4Pl8uF5eXlB3/T90mjtBdbg1lVs9vthlar5YFcvV4PmUzGnxWrKGcJ+2KxyIuV2PNm8mNdXV2w2+08ocs6oVn3U7Pou1erVeTzeS5JBQALCwuIx+Pcs2A7BEGAUqnkcoUWi2VT7KGxYpitVczzx+/3t/w5EvgsIcnGkN/vR61Wg06ng0ql4tX4bI3eT/uTnWBxqZ06u5hPCdsrt9K5kpHL5bC2tgaJRIJQKMT3ZBKJhM8x7P232WzcG0uj0aBYLCKdTiMSiXB/NalUCo1GA6vVCqPRCGAjhrq8vMyrrR9WQvOhBIQbL5SVjV+6dAlzc3Ofe2KUy+U8Q9UoS5FOp/HWW29heXm5adtVPi+1Wg2vvPIKPvzwQzz++OM4deoUDh06hDNnzvAKnJ6eHvyrf/WvMD4+jvHxca5h1MobIKb7lEwmuRbj3bYXs8W/o6MD3/72t+F2u3H48GFudphMJvHzn/8c4+PjmJuba5rA3+LiIiKRCCYmJvDrX/8aMpkMSqUSqVSKm+qlUik+ibK2S6ardzcTq81mw9NPP/3/b+/Mftu80jP+kBQp7psoLpKofbXlPXacTOI0GY9dZDATDNCiCFqgmAK9be962T+gVy3QAgXai8F0BminDdx0msZ2YsvxJi+KLFmyRIoU933fF3HrhXFOSFnyLonL+QEBYog2+H36vrO853mfBz09PfRe3L17Fw6HA3Nzc/B4PC2vECY+3P39/Th69CiOHTvWoMDbHuYEgJq5i0QiKBQK8Pl8eq/bDYFAgHPnzmFsbAw/+9nPcOjQoQZVFgC4XC5cvXoVq6urcDqdLXmKC+AZVYzX60UkEqGFz/oFCSkcv+m4KRKJcOLECRiNRnz66aeYmpqiRY58Po98Po/Lly/jP/7jPxAOh5tqnC6Xy0gmk8hms/iXf/kX8Pl8KBQKqNVq/M3f/A1OnDhBbSQIa2trWFhYwIMHD3DlyhVsbW2hWCzSAz0ATXWNbxuiCCZJ7YTta6JMJoN8Pg+PxwOTyQSZTIZ79+7BaDTil7/8JYxGY4PnLpfLxblz53DmzBn4fD7cvHlz369tv9ieYC6RSPDOO++gv78fJpMJdrsdCwsLLaGS3kv4fD40Gg1yuRy0Wi3i8ThSqVRLbr7JwUEoFMI//dM/QSQSoa+vr2EuIgVhn8+HYDCIkydPUtufToSoqEnA8LFjx+h4Qea6lZUV/P3f/z38fn/bF4O7urpgNBqh1Wpx9OhRHD9+HOl0Gl6vF/Pz8/jd737XFl1fYrEYCoWi4YC5fk2bzWaxsLAAl8uFX//613C5XIhGo29k/0bez2QyiWvXrsFsNkMmk0EsFlNV7OTkJGQyGcLhML755pumuM+kOJnNZuH3+wGACkI+/vhjKgghwbeZTAZXrlzBzZs3sb6+DrPZTC35uru7oVQqoVKpMDU1RUPeVSoVPvzwQ2g0GgwODoLH4+Hx48fUujKbzTbFvaiH2HrE43G43W4qiHmepQGxFTQajejr68Px48fxySefQC6X09BG4OnYQ7qU7969S8UE7QLZL5hMJlgsFnpoT9Z9pIZAalVEYNPMWSt7AZfLRV9fH0ZGRqDVanf8jFQqxcTEBLq7u+nestXwer348ssvMTg4iHw+D6PRiPPnz9Oug3phHjk8IzYiwWAQHo8H8/Pz+Oqrr6DT6XDkyBEMDw/j1KlTEAqF1JLuV7/6FTY3N2G1WvdsTNlThTD5wvXKhte9CFLwJMnKer0eQqEQPB4PlUoFhUIBfr+fGuW3K2SD7nK50Nvbi56eHsRiMQiFQjoxa7VaaLVaulkgyqxWhUzqRCG8PY37eXR3d0Oj0UCv11O/XBKSRP69ZkxAJd+FLGZIgZIscEulEj3pfV3ISRTxUiYFoEQiQdVazVIgf13qFZokvT6bzTZ48UgkkoaNJ1GklUoljI6OIpPJIBwONwREkCJXq0Ja52QyGQYHB+mkrVAoaGtTOp1GKpWi/qehUKjlvZXr3xdy4g/8EJJGWubqfZ9eBx6PB7FYDKVSCYPBgP7+fvT09DT4tJExLZFIwO/3N6WHLln8xmIx8Pl8SCQS2q1Q36Kdy+VoIKrNZoPH40E0Gt2z1qZmhdwbhULRoLbJZDJIp9NUrUT+I2MKKXR1dXXtGkIjkUhokE87Qjbe21viyAFdvfKR8RQSUkgsAlrdo7BcLiMcDoPP51PrnvqflctlJBIJpNPpXcOwOgGiTDQYDBgaGkJPTw9EIhHdaBIrMaI8isVibV8453K5UKvV0Ov11JedJLZHIhEkEom2UO0RezOZTEbtGkhBk9iduVwuOJ1OBAIBWgx+G+u2Wq1GO6nIIXq9P2ozjkGk+8DtdqNWq0GtVtO1TD3ksIB4xlarVap87e7uhkwmg06ng0ajwdjYGCQSCbRaLZRKJYxGI7VRyOfzCAaD1Du/Gccnsqd+FRs0Ul8g4qP+/n4UCoVnbCbIPjIWi9Fu1nZ477bzojoTyULqNKsI4Icu756eHgwPD+9qMSIQCKDT6ZDL5SAQCFoqTI5A9kek47RUKsFms0GhUNCAz+1jYj6fx9bWFtxuNzweD52jNRoNretJJBJwOBz6Hnk8Hng8njeu+zyPfbGM4PP59DTxdScLgUAAsViMU6dO4S//8i9hMBig1+vB5XKRSqXg9/sxPz/fdqdR2yEbpuXlZdjtdjgcDiSTSUxMTODcuXN0o67RaPCHf/iHsNvt+OqrrxCNRg/6q782xMeKhKu8ilpzaGgIn376KSYnJ3H69Gna7kw24KSl2ev1NpWColAooFgsIpPJ0EUWOYUkBytvOiiQjTZp5yiXy4hEIohEIrS9vhkXM68Cn8/HyMgIRkdHIZFIaAKq0+lEOBxGMpnERx99hA8//JD+ndHRUXz++edUEZFIJPD48WMaOhaLxWAymehCpxXvkVgsxscff0yV8xMTE5DJZODxeLRodfPmTVy5cgUWiwVLS0uvdBDTSpDASZlMhtnZWdRqNTx8+PC1fc+Ip9z7778PvV6PH//4x9DpdNTnsl5JQYIE4vF402/Y5XI5/uRP/gSTk5M4cuQIDUGr1WpYWlrC+vo65ubmcOPGjVe29WkHOBwO5HI5pFIp/viP/xjHjh0D8HT+unr1Kq5du0bDXrdDfBpJgFwn+qEWCgVEIhGqciXzE9lghkIhrKysYHNzs2WtERjPh6z1yuUyfD5fw2a63r6nk+HxeOjv74darcbnn3+O9957DzqdjoYCA09VS48ePcKDBw9gt9vbIhz4RQgEAnzwwQc4evQojEYjAGBpaQl3797F6upq21iLGI1GvPvuu1RZR+aKXC4Hh8OBzc1N/Nu//Rs8Hg8Vurzp755YBpAwOZFIRFXJ5Jkj/pc+n++Nr/FtQYrkm5ub+Id/+AfMzMzgb//2b3f0yiVhv0NDQzh27BgMBgPGxsboz4eHh/Huu+9CrVZjbGyMWiXweDxIpVJUKhWsra0hEAjg+vXr+P7771u+w7KefD6PQqGAfD4Pl8sFvV6PVCoFkUjU0GmZSqVw+/Zt6lccj8c7fszuNIgK9pNPPsGf/umfQqFQ7Pi53t5eXLx4ESaTCQsLC+ByuS13gEAKwiT3SSQS4dKlS1AqlThz5gyUSiW1fwOejkmLi4t0HZtKpaBUKtHX14fDhw/jJz/5CaRSKfh8PuLxOB48eACHw4FHjx7teZ1q3wrCcrmcqoteB4FAAIVCAZ1Oh/HxcWpmTzbV+XwesVgMsVispdWwL4IsiknLqd/vh8fjgVqtbjipFQgE0Gg0SKVSbZHMXc+LDhVIEioJPxoZGcHAwADkcjk94dza2qLqAaI2aaZJq947eq/Y7tNMfFZJ4a8dFs/kWSCLPeLPHI1G4ff7EYvFGhZttVqN+mRVq1X09PRQ7z21Wo1UKgWZTIZEIgGhUIh8Pt+gaqtXnTYzfD4fWq2WpnH39vbSnxGvNb/fD7PZTNXB7QgZK0lwl0ajQaVSeeUxk7xH9UFYQ0NDMBgM6OvrQ29vL23JI6qafD5Px55mXgBxuVwIhUIoFAoMDQ1hZGSEeseRgyuiDCYp7p0Il8uFXC6nyd3T09P0Z1arFevr60in0/RAMp/P04Uz8SUk3sG7KT7bYUzejXpf7foCBrGMIovndDrd1O/LXkEUR/WHBfXJ0+2ixq9Pd38ePB6PKiSBzkhwJyntCoWCzt9DQ0N0biHF9Gg0CqfTSRPLO+F96erqgkajgcFgoJ0W4XAYLpcLiUSiLd4N4AeFMNlP1x8w53I5pFIpBINBRCIRcDgc6qP8vKIwERKRjoPtkCwOkUiEnp4eqFQqdHd3N7TKJ5NJBINB2gnTLBBVs8PhoF6vxPe1vh5BRDdyuRw6nY7OyYTR0VFaezAajeDxeHS+ymazNBTK4/EgGAzSDql2gVwL6fbebZ9DPLsjkUjTr20ZewPJvejp6aGHczshEAig1WoRi8WgVCqRzWZbLv+rVqvRNVixWASPx0MsFoNcLodKpaIdCfU2lWazGWazme6fSDAuUQcLBAKqxCfKYOIOsJfsS6Wwv78fn332GXp7e/Gf//mfr6XuGBsbw8cff0xPf8lkVCqVaPpeLBZrSPRrZ8imiahmVCpVw+RDJvA3KcI3C/XBYENDQ8hkMvD5fDu2WJPN9ezsLN5//33MzMzQExeS+k4m7n/+53+mnizNVhA+COon8naZxMvlMtxuN3g8Hn1eyGKmUCjQ1jfyWTKeEON2MsCfPHkStVoNZ86coSeC+XweZrMZkUiEhq09fvwYJpPpIC/5hXR1dUEkEmFiYgLT09MNrXPk9NJkMuHatWtYXFxsKiuVtwmPx4NQKMTExAR++ctforu7G9FoFOFw+JmwtBfR3d1NgwvPnTuHgYEB/PjHP6aec3w+nx5GpVIp5HI53LlzB2azGRaLZY+u8M0hoYPnzp3D8PAwzp49C6PRCLFYjGKxiOvXr8NiseDGjRt4/PhxW228XwUyRxEf7vfffx/Dw8MNrXM//elPEQwG4XK5YDKZ8M0330Aul2N2dhYSiQS9vb3o7e3F5OQkNBrNjs9gOxe9iIUR8fcnhc98Pg+LxQKbzYZUKtURasedEAqF0Ov1UKvV4HK51HOXWPr4fL62tkvbjlarxcmTJ9HX19cRinoShCqTyXDu3DlMT09jZGQEQqGQrvGtVissFgvu3LmD3//+90gmk22/riWHumKxGH19fTAajfD7/djY2MCdO3dw69atPd9INwPkEKVWq1FFHlGyWq3W5xZaNBoNBgYG6GHm9nmmq6uLjs0zMzNQKpXQ6XSQSCQ0iHpxcRFXrlyB1+vd0+t8Hcjexmq14ne/+x1GRkbw6aefNgghiL/nsWPHMDY2RvcDBJIpQgrnpVIJ8XgcoVAIv/3tb+H1euHxeJBOp2G329v2vZPL5VAqlRgYGEB/fz/kcjnN2yD7a4fDAafT2VHzEeMpHA4HYrGY1lyeB1nTlMtlXLhwAQ6HA//zP//Tsh3tpC5HwpHn5uZ2tA1JJpPUlqZarWJmZgZ/8Rd/Aa1WS4WuqVQKNpsN//7v/w6Px4N4PL7n33/PQuXqW6nFYjHEYjEMBgOkUimy2ewLg4mIFx/w9AHTaDQYHR1Ff38/JBLJjqdzxJejVan3nNn+ABEFCJm0yOc5HA4KhcIz102UBO2wUCb3hZi0a7XaZ9oKyL0gKqv+/n4cOnQIY2Nj6O/vp63w5XIZuVwOiUQCZrMZGxsbSKfTbTt57wRRAdSfWhH/xmw2+8b+qc1EpVKhXrjkeSHvEEkJJu9TqVSi1x+Px2nngUgkglqtpl0KwFMrkq2tLfD5fPj9fnR3d0MsFsNmsx3Ytb4MPB4PEomEKhlJsbI+yCkcDsNiscDj8bR1cBM5xVYqlZidnYVAIMD6+jrK5TLkcjk9FKhWq1SJQ5Tz25U0EokEarUa/f39mJ6exsDAAMbHx2mAHIGo8NPpNHw+H014bkZIy75MJsPY2Bj1mVYqlbR10O12Y319HVartanSxfcbog4fHh7GzMwM9bEkY4tMJsPo6Ch8Ph80Gg0A4PHjx1Cr1dSuRafTQalUQi6X75r23c7UWxjVd64Q39hEItGygZZvAhmnSJgUOcCr9/zPZDLI5XIdtY4RCoXQaDSQyWTPFLDIGvptBIM2C8TjXi6XY2BgACMjI9TmifiBxmIx2Gw2bG5uwmKxtM21Pw+y7heLxZDJZJBIJLRTJRgMtmV3026/1/o1DZ/Px+DgIIRCIXK53HPXciT8Sa/XY3p6+pn9J4/Ho/PSxMQEtUgg6+t4PI5AIACv1/vaVlt7SbVaRbFYRCqVgsVioVZdKpWqwcaLw+FAqVTu6HlK9kik4FMsFhGLxRAIBLC8vAyn00n9mpvJfvBtIxAIIJVKIZVKqa8w6XwjnsQkh6bT5mrGU7q7u6mtzPMg3YcymQwGgwH5fJ52/LQq9YrhF3VLkhpET08PJicnIRKJwOPxqD0qmc9JIOZesycF4Wg0io2NDQwPDzekCw4NDeGv//qvYbPZcOnSJUSj0R0X+BwOB6OjoxgYGKADz9mzZ3Hx4kXI5XJ0dXXRMB63243f/OY3dDBuRUirSr3nCEmPBZ4u/BcWFuDxeDA5OYmBgQHq5aTVajE4OIiBgYGGl69SqSCTySCTybTcoFzvFUcWPqT94M/+7M8QCoUwPz+PYDBInx+VSkUHFdKmPTY2BqlUCh6PR1NVk8kkVlZW4HK54PP5GgqFncLU1BTee+89vPPOO1CpVABAw0fW1tbg8XjaRhVKFMKkuMvlcmE0GiESiTA7O4tqtYqhoSEUCgWsrKzg1q1bCAQCWFtbo4N6vQf66Ogo5HI5JiYmIJFIEA6Hkc/nEQ6H4Xa7m96/XKfT4c///M8xMjKC999/HxqNpkEhXKvVsLy8jC+//BKRSOQAv+neQxTCCoUCg4ODUCgU6O/vRz6fx5kzZ5BMJrG4uIhoNIre3l6IxWK4XC6EQiGcOHECx48fb0iPFQgEkEgkMBgMEAqFtN2QbK7ImLaxsQGHw4Hbt29jcXGxaQvCarUap0+fxvDwMD777DPo9XpaDL569SrsdjuuXr0Kk8nU1gcHL4IUakjh/NChQ5DJZADQcNACAEqlEpOTk9BqtTh8+DAEAgE9lCGhUM8LjWvnAg9RP5IgDlLQKxaLsNlssNvtHac44nA4GBkZwZEjR3D8+HFcvHgRMpmM+v3fvn0bDocD8XgcxWKx5dZ6b4JIJEJvb+8zh24kbK1UKsHj8bT8M0OUwUqlEj/72c8wODiIjz76CEajEXK5HLVaDSaTCS6XC9evX8fc3BwikUhbjxX1SKVS/PSnP8XIyAjGx8chl8vhcrmwvLzclsXgcrlMg0jrf8cSiQRTU1MwGo0YHBxEuVyGUqmkOTvPE0uRokx3dzekUukzBeF6sVKtVkMikcCTJ08QDAbx6NEjOBwOrK2tIRQKNW2HLrGLu3v3Lux2O6ampuh8vVvoVT0+nw+Li4vw+/14+PAhCoUCcrkcstksnjx5QovEpDDarnR3d0Mul0OhUEAul1MVaL1Fy5MnT5oul4exP/B4PMzMzGB0dBR9fX0H/XWamomJCUxNTeHYsWOQSCS0GB4Oh3H58mVsbGzs6zu0JwXhbDaLYDAIlUqFSqVCT+CUSiXOnj0LtVqNubk52sK9ffDkcDjQ6XQYGRmBWq2GUqnE9PQ0RkdH6SaBnPAFg0EsLCzsaiHQKnC5XIhEIoyPj0Or1WJqaooWakqlEvVGnpqawvT0NKRSKWQyGTQaDfr6+p7xQyJKtFZtryR+eKQoR9rcjxw5gkwmg2w2C6/XS6+PtFKOjIxgeHgYUqmUqjlJK1U8Hkc4HMbm5iY8Hg8ymUxLK8pfF41Gg6NHj9J2Q5JInUqlEIlE2ioEoFKpIJlM0uus1WpQKpVUcSUUCumBgd/vx9LSEhwOBx4+fNhwD7q6uiCRSHDixAn09vaCy+Wip6eHdiUQlUQzbz45HA5kMhnOnj2L0dFRWhgnEAVEIBCA2Ww+wG+6P5BNDmlVV6lUtIVwZmYG+XweAoEAXq8Xg4ODkMvlWF1dhcvlwgcffIDz588DwHPH13qFWrlcpm3eJAXc6XTu/YW+BhwOBxKJBBMTExgfH8f09DTUajUAIJ1Ow2q1YmVlBSaTqaOVwYSuri7q7djT09PgF0ao1WoQiUTUh7E+sOZlvIJ38tdtRYj6d3swKhmTiR1YvUKY5EO0y7z0IohIgMvlQqPRYHp6GpOTkxgfHwcAOl/b7Xa4XK6OUwcDTy1GiEINQIN4QKlUIplM7puyZi+p93A/fPgwJiYmMDw8DI1GQw8ZQ6EQNjY2sL6+jtXV1ZYfI14FgUCAyclJTE1NUb/GRCIBr9fbluGTlUoFxWKRduGSQC+iNHuRb+dObM8SIf/u9nmoWq0ilUpRWwCHw4HFxUWYzWbE4/Gm34MXi0W43W4UCgW4XC6IRCKMjo4CeP51A0AsFoPZbIbVasXly5epN3e1Wm3ZffbrQLzbu7u7G+xqiFo8kUggFAq1rEDvbVL/XnUKHA4HarUaRqPxmcNaxg8Q54Pp6WkYDAYIBALahZpKpWA2m+F0Ovf1gG1PCsLr6+vY2trCiRMnUCqVoNPpMD09DZFIRNuc/uqv/or6d9YvZMlGYGhoCDqdjkrPyUadFK9sNhu+/PJLuN1u2O32llZ6ksKEUCjEwMAAjEYjZmZmqMqIKGATiQS0Wi0UCkVDEI1YLKbqYFJEjUajuHXrFpxOZ8stiorFIqLRKFZXV/Gv//qvGBgYwLlz5yCXyyESidDd3Y0f/ehHNMmebLTJKTdJak+n08hms4hEInA4HPj666+pBJ+opzsRiUSCvr4+qg4ulUpIpVLUtDyfz7fN4oYcBuRyOTidTmi1WqhUKuh0OjpRr6ysYHV1FY8ePcL9+/dpaFH9opDYSZACmMPhgFAopAvCSCRCrSmaERKUNzg4CKPRiL6+vgZ/p0qlgvn5edhsNmxsbBzgN90/SqUSkskk7HY7Ll26hKGhIXz44Yd0/Ojq6sKxY8eoGpzP50Oj0SCdTmNgYOClFFikrTuVSuHKlStwu91YXV1FMBiE2+3eh6t8dUinxczMDC5evAiDwQCxWIxKpYJwOIxIJIKVlRUsLS01vSJ+PyChNclkEiaTCTKZDMPDw7SA/qb/NlEeff/997DZbFheXn4L3/pg4PF4OH78OAwGA6xWK/x+P7q6utDV1YWZmRn8wR/8AYaHh8HlcqmHezweh9PphMfjadkD3PpAOKFQSH+v9WtfotAjn5ucnMTk5CQOHTpEO8e2trbgcrnw+9//Hj6fD/Pz80gkEk1fiNlPent78fnnn2NzcxP/+I//2LL3hgROajQaXLhwAUajEWfPnoVer4dEIkG1WsXa2hoCgQAuX76MhYUFuFyutgkEflm6urqg1Wqh1+updYrJZMLy8nJbFqWcTify+TyUSiV+8pOf0EPGNyk8kYMFcugYDoextLREA8TIfqBcLmNjYwOJRAJWqxWxWAzBYBDJZLKpxRD11Hegkmsul8u4ffs2bDYbPB7PjsryeDwOh8OBRCJBLQvJfWmX/dLLQOwbt9tRptNprK2twWq1tuw8/TYRi8UNnv+dMiaTnJRQKNSyc+9e09vbC4VCgR/96Ef4xS9+Aa1WCx6Ph83NTXz33Xew2Wz47rvvkEgk9nVc3ZOCMEnZrFarGBwcRKlUwsTEBPh8Pnp7e6lHT6lU2nHxQtTEMpnsGT9dUrxyu924du0awuFwU7epvAxEDUI8cnt7e9Hf308VrsBTu42XoVqtolQqIZ1Ow2Qywe12t8xETSiXy0in0/B6vbh27RpGR0cxOTkJLpdLN02Tk5PP/TdIKnksFoPL5cLa2hquXr1KvQg7aQLfjlAohEqlglgsBgDqw53L5VAsFttuMieFhVAoBJ/PB5VKBYVCga2tLZRKJbjdbhrwtbm5uePEXavVUCwWaWDG5ubmfl/GGyEQCNDT0wONRgONRkNb5Mi1VioVmEwmLCwsIBgMHuA33T+In3goFMKDBw8Qj8dx6tQpSCQS6hO8fdw1GAwAGpW/wO6t/OS0NxgM4tq1a7TNcnsxqJkQCoUwGAwYHh7G8ePHoVKpIBAIqE0TaQt0OBysJRCNh05er5e+YyqV6o3VIbVajXpOP378GA8ePGhpRTaXy8XIyAhmZmZoqCcJXBwYGMDs7CzUajXtAisUCvRQNxqNtvyhP1G1kt8rWYeQIBaJRAKBQACBQIDDhw/jgw8+wPj4OI4fP04PJf1+P7799lv4/X7YbLa2m6/fFJlMhvfeew9arRa/+tWvDvrrvDYkLE2lUuHdd9/F8PAwJiYm6L6A2GGZzWYsLi7i/v37HVcMBp4eMikUCiiVStoV6fF44HA42nKdT4KfT5w4gWw2Cw6HQ+0FX3e+IYVg4gEbjUbx6NEjKhAha5WtrS08fPgQkUgEsVisZa3l6gvCwNN12traGh48eIDl5WWaBVL/LlUqFWrT0Y7P1ctCfE+3F4TJexcIBJp2bbuf8Pl8KJVKSKXStvKyfxG1Wg3ZbJZmPjAa4XA4UCgU6Ovrw/T0NE6fPk1/FgqFcOPGDbjdbjx58mTf65p7UhAmRUm3241bt24hk8lgdnaW2hzweDzIZDKasFcPmdBIKwJpjSGD98bGBubm5mC322nbf6sPPtVqlbYSf/nll9DpdPD7/dDr9Th27FhDC+p2KpUKyuUygsEgTCYTMpkMAoEAXC4X4vF4S4ew5PN52O12JJNJ/OY3v6FWBwqFghaGh4eHoVKp4PV66YaxVCrB6/XSE2yn04lQKEQXMJ0yML8sqVQKy8vLsFgsbTeAk4VfJpPB119/jcXFReqbS8aUzc1N+qy027MhFouh0WioDyyxPqhPBXa73YhGo1hcXMTDhw87piAMgPrhkUL44OAg9Ho9+vv7aYgTUe1t99WrhxTtyHhMnqN8Po8nT54gEAjQcYhssJr1WRMKhdDpdNBoNA0hX1tbW7BarXA6nYjH4ygUCi0/974tSFF4eXkZqVQKIpEI5XL5GesImUwGlUrVYImwE5VKBYFAAJlMBt9//z28Xi/u3LmDjY2Nlla9cblcGAwGTE9PQ6PR4KOPPgKfz4dAIMDU1BT0ej2EQiE4HA4ikQju3r2LjY0NhEKhlsxDIKhUKpw6dQpqtRrT09Pg8XgIBAL0sJ7D4aCvrw8KhQJCoRACgQB9fX3o7+9HIpHAf//3fyOVSsHv98PpdMJut9NOFkYjhUIBdrsdNput5cQQ9YjFYoyNjWF8fBwzMzPo7++n6vJ8Po9sNovHjx/j/v378Hg8TT2n7AU8Ho9aPanVaojFYszPz8PlcsHv9++4v2wnlpaW8Hd/93fQ6/XUj55Ym01OTtIw953WLYFAALFYDKlUiv5H/hwIBJBIJGCxWFAqlRrWM8RSLJfLtfTYs7W1RQ9WjUYj7RZVqVQ02JX4AxM6vRAslUohFotx8uRJnD9/HjMzMw1rmEKhAJ/Ph1AoxNaFeOpxr9Pp6Hovl8vR7tJWFjC+iGq1Co/Hg3w+/9LZItlslnqRt7vIhMPhYGJiAqdPn6aCo0wmg2QySR0PIpHIgYw1e1YQrlarCAQCePDgAQQCAaLRKGq1GiQSCZ3It7OTjx5RixKV3/r6Or744gvEYjH4fL62GKBrtRpKpRIikQiuXr0KhUKBUqmEkZERGI1G2nq60waS+El5PB589913iEQisFqtiMfjtK2lVSkUCnC73fD7/fB6vVAqlQgGg+jt7YXBYIBcLqcTeCAQgNVqpQmvq6uruH//Pi0Id9JC+VVJp9N48uQJXC5X2xWEgafvSC6Xw9zc3EF/lX1HJBKhr68Phw8fxh/90R/RjRMAmgzsdrvhcrnw+PHjlm5Hfx2Itczq6ipCoRAGBwfR19eHkydPQqPRUP/77Z0q29na2kIkEkGpVGpok8pkMlhZWYHP54PP52uJ8DViL6JUKiEQCKgSpFQqwel0wmKxsNP/Hdja2sL6+jpCoRCGh4chFosb5uxarQaDwUAVftsVNvWQgnAoFMKtW7ewvr4Oq9X6wtTiZofD4UCv12N8fBwnTpyASCSCQCAAn8+nQbmEeDyOu3fvwuFwIBqNNmzOWw2FQoF3332XBoIJhUK43W66+eFyuRgaGoJKpaL3hHiO37p1C1euXEEwGITVaqXdU+2w9t0LisUiHA5Hy69niMXe+Pg4JiYmaEB3tVqlFjVra2u4f/8+UqlUxz0PPB4PcrmcdpyKRCKsra1heXmZdqi2M0+ePMGTJ08wNjaG8+fPQygUQigUore3F2q1Gmq1mvqx11Or1RAOh6moyuv1IhAIwOFwIBAIYGNjo+3vXblcpocoExMTdJ9MisFyuZzaZTCeIpVKoVQqcezYMVy4cIEqXwlbW1sIBAKIRqOsIIyn62jSjcnlcqndUytbX70MtVoNfr8fsVgMyWTypf5OLpfD+vp6xxSER0dH8d5771HrwVwuh0AgAK/XC7fbfWDihz0pCBOIvcP6+jp+/etfQ6fT4ciRI9S7UiAQ0I0TUQ4TP7RQKIREIgG/349AIIBCoYBMJgO73Y5wOIxcLtd2RT6i2MvlclhbW4Pf70c+n6cK4Z0KwiR0LRAIYG1tDblcDpFIhBretwMkIA946vdKlOZCoRBms5kqhElBplQqIRgMIhgMtuVz8rYgNghkgxkMBtlE3iZwuVzweDwYDAZ8/PHHGB8fb0gxJYdt+XyeFvnS6fQBf+uDJZfLYXl5mRYTpFIpxsfHoVQqMT4+Do1GA6lUCqFQSAPh9Ho9hoaGYLfbcefOHWQyGUSjUTqZk+JEKpVqGc/yfD4Pn89HQxM5HA6SySSCwSDtJOj0Z2UniNp8a2sLN27cgMVieeYzxA6KvJ+E7XM7UWMnEgmsrq4iEAi0dEGUUK1WsbGxAYlEgoGBAWg0GroBLxQKND+AdG0sLS3Reb2VIcFDpVIJQqEQUqkUBoOhYY3G5/ORz+epAs/tdsPj8cBkMuHx48d0bGFdTk/xer24efMmjEYjjh8/TjuBvF4vHj58SMP2Wg2JRILe3l6MjIzgk08+wcDAQEP4a7lchs1mg9frpT6N7bLWfxVIQbheVd9pAU4AkEgksLy83GBJEwgEqEJ4+8EjKdgQ0VAikaChyOl0uiPGFtLBnEgkUKvVoFAoaBcK6Zhr98LUq0K634jV524Fq3Y/THhdqtUqisUiDTdvZ8j+8ubNm+BwOOjv78fg4CDUajX6+vro5zKZDFwuF/Ulb6f8ou1wOBwMDAxArVbTYFhi3ej3+zE/P4/19XVks9kDe0b2tCBMHv54PI6lpSX09/fj4sWLdHEjlUpx4cIF6PV6mlgZCAQQDoepj4/ZbMbGxgbS6TRVV7Xzy0T8XBcWFgAA33777Uv/3Xa9L9VqFdlslnoJAi/2ymrXe/E2IX5hJK08HA535MaiHSFJwMPDw/j5z38OjUYDmUzWED65tbWFbDYLq9WKlZWVjg8Iy2QyuHfvHgDQ1O7Z2VlotVqcP38eU1NT6Ovrg1qtxv379/Htt9/i9OnTuHDhAlZWVvBf//VfNMCy/mCl1cYiEsCoVquRy+VQqVRokXx+fh5Wq7XlC3R7QbVaRTQaRTQahcfj2fEzSqUSWq0WHA7nhQphn89HD3Zb7RnajUqlgpWVFcRiMczOzmJkZAR6vR56vZ565z558gT/+7//C5fLhXv37rV02z+BHGoXi0WIRCIoFIqGjAii2stkMtjY2IDD4cDdu3dx7949mtzeLs/A28LhcOD//u//cObMGRw5coR2aTgcDszNzcHv97fkwZVcLsfMzAyOHj2Kzz77DCqVinrEAk8Lwuvr6zQjpBWv8W3A4/GgVCpp11N3d3dHFoTJnEPgcDj46quvXvrvd+K4UiqVaA5IfVdcJ96Ll4WE79UXheshYX3k/xmNVCoVFAoFFAqFti16Eoht7OXLl3Hnzh189NFHOHfuHA4dOgSDwUDH6WQyiUePHsFisSAajba0LdiL4PF41AJqdnaW5mDVajW4XC5888038Hg8B9rts6cF4Xqq1Spd7BKFMPHDIq3/AoEAgUAAqVQKLpcLoVAIgUAA6XS6Y1URnXjNLwO7L69POp2G2+1GKpVCPp+Hw+FAOp1GPp9n97VN6OrqgkgkoioR4stJKBaLMJvN8Pv9sFqtLaum2itIt0YkEqFBKm63GyqVClKpFKurq7Db7eBwOCgUCrDZbA0+p638HhGVpsViwRdffAE+n49gMIhYLIZEItFxXpWvw273p1gsIpFIUBuS3SC5Au12r2u1GlXQE6UaCYTi8Xjo6uqi/v/t1HqayWSwvr6OaDSKrq6uZyzTiHVNoVCA1+tFOByGzWZDJpPpCEXR65BIJGA2m6lXd7lcRiKRgNfrpR7nrXjfxGIxjEYjdDod9a/ncDioVCpIJBKIx+Mwm81YW1tDKpU66K97YAgEAmi1WmqlUSgUEIvFaEdpp9KKz/xBwu7Xy1EsFsHlcrG+vo6rV69ienoap06dooXiUCjEQuXwQ+jey2SPtDOkAxkALBYLeDweHA4HzGYz3YvG43Gsr68jGAwim83S0MZ2hcfjgcfj0WeCHLCkUinqinCQ179vBWHg6S//9u3b9M8cDgdXrlyh/w/8MDiTDUP9qRODwXhzIpEIlpeXqVLJYrEgEomwgmAbIRAIqApNoVBAIpE0FIRzuRxu3LgBq9WK+fl5uN3utj2ZfV1I4B4ArK+vU9se4r1crVbx6NEjXLp0iRaQ22GuyuVycLlccLvdVDFN5uF2ucaDIpfLvXQrajve52q1Sp+tlZUVOiZt91quX/+1A7FYDHNzc+BwOPjiiy92/Vz9mrfTQ4xehM/ng9/vx927d/Hb3/4WQHuMUwqFAkeOHKF2esTmiQRhkbyQpaWlju7UEAqFmJqawvDwMICnhy5Op5NmiTAYjLdHJpNBJpPBtWvXsLi4SEOqy+UyMpkMNjc3sbq6imQy2bJj79tAIBBALpdDIpHQfIROJZfLIZfL4cGDB1hYWNjR+pSs9TrhEIEcFpCCMOnSDYVCsNlsBy7K29eCMPCsv0wnPAQMRjORSCSwubkJgUAAsVgMv9/PrCLaDBJulkwmEQgEUC6XIZFIUCqV4Pf7EQwGsbm5CafTiVwuxwoPu0Am5+fNU+04h5HCSjuHXxwUnbxZAtBWhd5XgYyx7TheHATtWjQndjJk00jG4UwmA7PZDKfTSQOjO/E9IhBFeDQaRTgcBpfLRS6XQ6lUartngsFoFgqFAlKpFKxWK65fv06tEEwmE7a2tjp6TAKeFoSlUinEYjENZa7v8Egmkx23BiACmk6mVqshFovRDrBYLAa32w2v1wu73Y5isXjgdZh9LwgzGIyDxeVywefz0ZM64vfDaB9yuRwKhQI2Nzdx//59jIyMQKfTIZPJ4JtvvoHD4cC1a9fg9/uZMpzBYDAYjCak3grj0qVLMJvN8Hg8HVdU2E6hUIDZbEYikYBKpQKfz0csFmsLz3EGo1nJZrPI5XL4+uuvce3aNQA/WKwxZf5Tyx+9Xg+NRgOJRILu7m4AoPsxp9PJxqgOpFKpwGKxwOfz4fDhw9Dr9bh+/Trm5ubg8XiQyWQO/DCFFYQZjA6D+FMy2ptqtYpkMgmLxYJsNguxWIxsNguTyUQDd4rFYsef3DIYDAaD0QyQ9utcLgehUAgul4tkMolQKAS/349EIsEO8PG0UB6PxwH84FGZyWQO+FsxGO0P6Vpg+8hnKZVKyGQy8Hg8uHfvHrWMcLvdCAQCiMfjHX+Y16lsbW2Bw+HA4XBgaWkJm5ubCAQCTVEMBgDOq3wJDodz8N94n6jVai8dV9tJ9wXA97Va7Z2X+SC7L7vTSfeGvUu7sufvUldXF8RiMXg8Hrq7u1Gr1ZDP5+lpfpMuTNi7tAvsXdoVNi/tDHuXdoG9S7vC3qWd2Zd3ic/n0zlbIBBQz/pKpYJ0Oo1yudx0waUH8S5xOBzqx0juUzabPfC2222wd2ln2Ly0C2xe2pWWeJe4XC66urrQ3d3dEB5Lxu9KpfK2w9PYu7QLzfYuEQ9lsViM7u5uFItFKsra5734js8MUwgzGAxGm0ISTBkMBoPBYDQ3pVIJyWTyoL9G01Pvcc9a1RkMRjNAOnC3traQTqcP+uswmgiSe0ACGpuNVy0IRwA49+KLNBlDr/j5TrkvwKvdG3ZfdqdT7g27L7vD3qWdYc/MzrD7sjvsXdoZ9szsDLsvu8PepZ1hz8zOsPuyO+xd2hn2zOwMuy+7w96lnWHPzM6w+7I7O96bV7KMYDAYDAaDwWAwGAwGg8FgMBgMRuvCPegvwGAwGAwGg8FgMBgMBoPBYDAYjP2BFYQZDAaDwWAwGAwGg8FgMBgMBqNDYAVhBoPBYDAYDAaDwWAwGAwGg8HoEFhBmMFgMBgMBoPBYDAYDAaDwWAwOgRWEGYwGAwGg8FgMBgMBoPBYDAYjA6BFYQZDAaDwWAwGAwGg8FgMBgMBqNDYAVhBoPBYDAYDAaDwWAwGAwGg8HoEFhBmMFgMBgMBoPBYDAYDAaDwWAwOgRWEGYwGAwGg8FgMBgMBoPBYDAYjA7h/wFRsVJgQQuFpQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1800x288 with 40 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print('Displaying the validation data of a single batch')\n",
    "images , labels = dataiter.next()\n",
    "images = images.numpy()\n",
    "fig = plt.figure(figsize= (25,4))\n",
    "for idx in np.arange(40):\n",
    "    ax = fig.add_subplot(2, 40/2, idx+1, xticks= [], yticks= [])\n",
    "    ax.imshow(np.squeeze(images[idx]),cmap = 'gray')\n",
    "    ax.set_title(str(labels[idx].item()))\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = {}\n",
    "dataiter = iter(valid_loader)\n",
    "for img,lbl in dataiter:\n",
    "    for i in lbl:\n",
    "        i = int(i)\n",
    "        if i == 0 and i not in a:\n",
    "            a[int(lbl[i])] = img[i]\n",
    "        elif i == 1 and i not in a:\n",
    "            a[int(lbl[i])] = img[i]\n",
    "        elif i == 2 and i not in a:\n",
    "            a[int(lbl[i])] = img[i]\n",
    "        elif i == 3 and i not in a:\n",
    "            a[int(lbl[i])] = img[i]\n",
    "        elif i == 4 and i not in a:\n",
    "            a[int(lbl[i])] = img[i]\n",
    "        elif i == 5 and i not in a:\n",
    "            a[int(lbl[i])] = img[i]\n",
    "        elif i == 6 and i not in a:\n",
    "            a[int(lbl[i])] = img[i]\n",
    "        elif i == 7 and i not in a:\n",
    "            a[int(lbl[i])] = img[i]\n",
    "        elif i == 8 and i not in a:\n",
    "            a[int(lbl[i])] = img[i]\n",
    "        elif i == 9 and i not in a:\n",
    "            a[int(lbl[i])] = img[i]\n",
    "    if len(a) == 11:\n",
    "            break; "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Displaying the validation data of a single batch\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x1152 with 60 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print('Displaying the validation data of a single batch')\n",
    "fig = plt.figure(figsize= (10,16))\n",
    "count=1 \n",
    "for digit in range(10):\n",
    "    plot_complete = False\n",
    "    for num_digit in range(6):\n",
    "        ax = fig.add_subplot(10, 6, count, xticks= [], yticks= [])\n",
    "        ax.imshow(np.squeeze(a[digit]),cmap = 'gray')\n",
    "        ax.set_title(str(digit))\n",
    "        count+=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 704
    },
    "colab_type": "code",
    "id": "Nhoh0o_-Rtka",
    "outputId": "d23b15f2-52d7-4003-ef2b-2888ac6313b7"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor(3)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x864 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "img = np.squeeze(images[2])\n",
    "print(labels[2])\n",
    "fig = plt.figure(figsize=(12,12))\n",
    "ax  = fig.add_subplot(111)\n",
    "ax.imshow(img, cmap='gray')\n",
    "width , height = img.shape\n",
    "thresh = img.max()/ 2.5\n",
    "for x in range(width):\n",
    "    for y in range (height):\n",
    "        val = round(img[x][y],2 ) if img[x][y] != 0 else 0\n",
    "        ax.annotate(str(val),xy = (y,x),\n",
    "                    horizontalalignment= 'center',\n",
    "                    verticalalignment = 'center',\n",
    "                    color = 'white' if img[x][y] < thresh else 'black'\n",
    "                   )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 101
    },
    "colab_type": "code",
    "id": "2YoAz8ccUV7O",
    "outputId": "f9ea46d8-82e1-40db-cc06-04e470c06b60"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method Module.parameters of Net(\n",
       "  (fc1): Linear(in_features=784, out_features=512, bias=True)\n",
       "  (fc2): Linear(in_features=512, out_features=10, bias=True)\n",
       "  (dropout): Dropout(p=0.2, inplace=False)\n",
       ")>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Declaring a neural network\n",
    "\n",
    "class Net(nn.Module):\n",
    "    def __init__(self):\n",
    "        super(Net, self).__init__()\n",
    "        self.fc1 = nn.Linear(28*28, 512)\n",
    "        self.fc2 = nn.Linear(512, 10)\n",
    "        self.dropout = nn.Dropout(0.2)\n",
    "    def forward(self, x):\n",
    "        x = F.relu(self.fc1(x.view(batch_size,28*28)))\n",
    "        x = self.dropout(x)\n",
    "        x = F.relu(self.fc2(x))\n",
    "        return x\n",
    "model = Net()\n",
    "model.parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "FInO8u6gUZ7s"
   },
   "outputs": [],
   "source": [
    "criterion = nn.CrossEntropyLoss()\n",
    "optimizer = torch.optim.SGD(model.parameters(), lr=0.001)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "def validate_training():\n",
    "    model.eval()\n",
    "    valid_loss = 0.0    \n",
    "    for data, target in valid_loader:\n",
    "        output = model(data)\n",
    "        loss = criterion(output, target)\n",
    "        valid_loss += loss.item() * data.size(0)\n",
    "    valid_loss = valid_loss / (len(valid_loader) * batch_size)\n",
    "    print(\"Epoch {} : Validation loss : {:.6f}\".format(epoch+1, valid_loss))\n",
    "    return valid_loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 353
    },
    "colab_type": "code",
    "collapsed": true,
    "id": "NzN1xDEIUbgR",
    "outputId": "420af5c8-e769-4d4b-8e2e-ac09463afbe1"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1 : Training loss : 1.339655\n",
      "Epoch 1 : Validation loss : 0.767042\n",
      "Epoch 2 : Training loss : 0.597849\n",
      "Epoch 2 : Validation loss : 0.493251\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<ipython-input-14-f54a5cfcf728>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n\u001b[0;32m      7\u001b[0m     \u001b[1;32mfor\u001b[0m \u001b[0mdata\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtarget\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mtrain_loader\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      8\u001b[0m         \u001b[0moptimizer\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mzero_grad\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 9\u001b[1;33m         \u001b[0moutput\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     10\u001b[0m         \u001b[0mloss\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcriterion\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moutput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtarget\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     11\u001b[0m         \u001b[0mloss\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbackward\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\envs\\boston_house_prices_prediction\\lib\\site-packages\\torch\\nn\\modules\\module.py\u001b[0m in \u001b[0;36m_call_impl\u001b[1;34m(self, *input, **kwargs)\u001b[0m\n\u001b[0;32m   1049\u001b[0m         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks\n\u001b[0;32m   1050\u001b[0m                 or _global_forward_hooks or _global_forward_pre_hooks):\n\u001b[1;32m-> 1051\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mforward_call\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1052\u001b[0m         \u001b[1;31m# Do not call functions when jit is used\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1053\u001b[0m         \u001b[0mfull_backward_hooks\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnon_full_backward_hooks\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m<ipython-input-11-f8ddccaaf9df>\u001b[0m in \u001b[0;36mforward\u001b[1;34m(self, x)\u001b[0m\n\u001b[0;32m     10\u001b[0m         \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mF\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrelu\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfc1\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mview\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mbatch_size\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m28\u001b[0m\u001b[1;33m*\u001b[0m\u001b[1;36m28\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     11\u001b[0m         \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdropout\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 12\u001b[1;33m         \u001b[0mx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mF\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mrelu\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfc2\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mx\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     13\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     14\u001b[0m \u001b[0mmodel\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mNet\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\envs\\boston_house_prices_prediction\\lib\\site-packages\\torch\\nn\\modules\\module.py\u001b[0m in \u001b[0;36m_call_impl\u001b[1;34m(self, *input, **kwargs)\u001b[0m\n\u001b[0;32m   1049\u001b[0m         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks\n\u001b[0;32m   1050\u001b[0m                 or _global_forward_hooks or _global_forward_pre_hooks):\n\u001b[1;32m-> 1051\u001b[1;33m             \u001b[1;32mreturn\u001b[0m \u001b[0mforward_call\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1052\u001b[0m         \u001b[1;31m# Do not call functions when jit is used\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1053\u001b[0m         \u001b[0mfull_backward_hooks\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnon_full_backward_hooks\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\envs\\boston_house_prices_prediction\\lib\\site-packages\\torch\\nn\\modules\\linear.py\u001b[0m in \u001b[0;36mforward\u001b[1;34m(self, input)\u001b[0m\n\u001b[0;32m     94\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     95\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mforward\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minput\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mTensor\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[0mTensor\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 96\u001b[1;33m         \u001b[1;32mreturn\u001b[0m \u001b[0mF\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlinear\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mweight\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mbias\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     97\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     98\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mextra_repr\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\anaconda3\\envs\\boston_house_prices_prediction\\lib\\site-packages\\torch\\nn\\functional.py\u001b[0m in \u001b[0;36mlinear\u001b[1;34m(input, weight, bias)\u001b[0m\n\u001b[0;32m   1845\u001b[0m     \u001b[1;32mif\u001b[0m \u001b[0mhas_torch_function_variadic\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1846\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mhandle_torch_function\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mlinear\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0minput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbias\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mbias\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1847\u001b[1;33m     \u001b[1;32mreturn\u001b[0m \u001b[0mtorch\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_C\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_nn\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlinear\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minput\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mweight\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mbias\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m   1848\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   1849\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "per_epoch_loss = []\n",
    "validation_error = []\n",
    "epochs = 20\n",
    "for epoch in range(epochs):\n",
    "    model.train()\n",
    "    train_loss = 0.0\n",
    "    for data, target in train_loader:\n",
    "        optimizer.zero_grad()\n",
    "        output = model(data)\n",
    "        loss = criterion(output, target)\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        train_loss += loss.item() * data.size(0)\n",
    "    train_loss = train_loss / len(train_loader.dataset)\n",
    "    print(\"Epoch {} : Training loss : {:.6f}\".format(epoch+1, train_loss))\n",
    "    per_epoch_loss.append(train_loss)\n",
    "    validation_error.append(validate_training())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor(4.9323, grad_fn=<NllLossBackward>)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "criterion(output , target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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5iQZBiHFpyXhcok1DSilH0SAIkZQk5OlYAqWUw2gQ9GFdQqrTTCilnEODoI+CoF+bhpRSjqJB0Ed+ZoAj9a20tHcmuipKKRUXGgR9dF9CerC2JcE1UUqp+NAg6CNfB5UppRxGg6CP/MzuG9Roh7FSyhk0CPqYkOHDlSR6CalSyjE0CPpwu5IYn+7T0cVKKcfQIAgjXy8hVUo5iAZBGAU6qEwp5SAaBGHkB/0cqmuhvbMr0VVRSqmYGzQIRCRJRM6KR2VGioKgny4Dh3QsgVLKAQYNAmNMF/DjONRlxNDpqJVSThJt09DLInKliEhMazNC9NypTC8hVUo5QLRBcBPwW6BNROpEpF5E6gbbSUQWi8huEdkjIneF2X6yiLwiIu+IyHsicukQ6x8TEzJ9gA4qU0o5gzuaQsaYtKEeWERcWE1KFwGlwEYRWWuM2RFS7J+Bp40xj4rIDGAdMGmo7zXckt0uTkpP1ktIlVKOEFUQAIjIEuA8++Wrxpg/DLLLAmCPMWavvf9qYCkQGgQGSLeXM4DyaOsTa/l6gxqllENE1TQkIg8CX8X6I74D+KqI/GCQ3fKBAyGvS+11oe4FPicipVhnA7dGeP8vicgmEdlUUVERTZVPWH4woJ3FSilHiLaP4FLgImPMY8aYx4DFwGXD8P7LgceNMQX2e/xaRPrVyRjzU2NMsTGmODc3dxjednAFQT8Ha5vp7DJxeT+llEqUoQwoywxZzoiifBkwMeR1gb0u1BeApwGMMX8BfEDOEOoUM/mZfto7DUfqdSyBUmpsizYIvg+8IyKPi8ivgM3AA4PssxGYIiKFIuIFrgXW9inzMXABgIichhUE8Wn7GUSB3pdAKeUQg3YW2001XcAngTPs1XcaYw4NtJ8xpkNEvgKsB1zAY8aY7SJyH7DJGLMW+EfgZyJyO1bH8QpjzIhoi+kOgtKjzRRPSmxdlFIqlgYNAmNMl4jcYYx5mv7/0Q+27zqsTuDQdXeHLO8Azh7KMY9bZweUvg0nfwqiGBeXl6mDypRSzhBt09BLIvINEZkoIlndj5jWbLi9+yT88hI49H5UxQNeN9kpXr1ySCk15kU7juAa+/nLIesMMHl4qxND0y4FccGONTBhdlS75Ad1Omql1NgX1eyjwF3GmMI+j9ETAgAp2VB4Hmx/FqLshigI6qAypdTYF+3so9+MQ11ir2gZVO+FQ+9FVTw/07pT2Qjpv1ZKqZhwTh8BwGl/azUPbX82quIFwQCtHV1UNrTFuGJKKZU40QbBNVj9AxuwxhBsBjbFqlIxE8iCyefD9jVRNQ/lZ3ZfQqr9BEqpsSuqIAjTPzD6+gi6FS2Do/vg4LuDFs3X+xIopRxgwCAQkTtClq/us+37sapUTE2/HJLcUTUP5evoYqWUAwx2RnBtyPI/9dm2eJjrEh+BLJi8MKqrh9J9HtJ9bh1LoJQa0wYLAomwHO716DHjM1CzHw5uHbRoQTCgTUNKqTFtsCAwEZbDvR49pl82pOYh7SxWSo1lgwXBnO57FAOz7eXu17PiUL/YCGTB5EVRNQ/pWAKl1Fg3YBAYY1zGmHRjTJoxxm0vd7/2xKuSMVG0DGo+hvItAxYrCPppbOuktrk9ThVTSqn4GsqNacaW6ZdCkscaUzCA0OmolVJqLHJuEPiDcOqiQQeXFQQDgAaBUmrscm4QgNU8VPsxlEVuHtLRxUqpsc7ZQTCtu3nomYhFMgMeUrwuvYRUKTVmOTsI/Jlw6t/Ajt9HbB4SEfsSUg0CpdTY5OwgALt56ACUbY5YpPsSUqWUGos0CKZdAi7vgIPLdHSxUmos0yDwZ8KpF1hXD3V1hS2SH/RT29xOfYuOJVBKjT0aBABFn4G60ojNQwU6HbVSagzTIIBBm4d6LiGt1iBQSo09GgQAvgz4xIWwY03Y5iG9QY1SaizTIOhWtAzqyqB0Y79NuanJJLuTNAiUUmOSBkG3qYvBlRy2eUhEyM/U6aiVUmNTTINARBaLyG4R2SMid0Uo81kR2SEi20Xkf2JZnwH50u3mod9HbB7SsQRKqbEoZkEgIi7gx8AlwAxguYjM6FNmCtYtMM82xhQBX4tVfaJStAzqy6H07X6bCnR0sVJqjIrlGcECYI8xZq8xpg1YDSztU+ZG4MfGmKMAxpgjMazP4KZFbh4qCAaoamyjua0zARVTSqnYiWUQ5AMHQl6X2utCTQWmisgbIvKWiCwOdyAR+ZKIbBKRTRUVFTGqLpCcBlMuCts81D2WYMfButi9v1JKJUCiO4vdwBRgIbAc+JmIZPYtZIz5qTGm2BhTnJubG9saFS2D+oNw4K+9Vp8/NZfsFC/f+8MOOrv0tpVKqbEjlkFQBkwMeV1grwtVCqw1xrQbY/YBH2AFQ+JM/TS4ff2ahzIDXu7+2xlsPVDDb97an6DKKaXU8ItlEGwEpohIoYh4gWuBtX3KrME6G0BEcrCaivbGsE6D69U81Ls/YMmcPM6bmsu/vLiLch1ToJQaI2IWBMaYDuArwHpgJ/C0MWa7iNwnIkvsYuuBKhHZAbwCfNMYUxWrOkWtaBk0HIKP3+q1WkR44DMz6TSGu3+/HTPALS6VUmq0iGkfgTFmnTFmqjHmVGPMA/a6u40xa+1lY4z5ujFmhjFmljFmdSzrE7UpdvPQjjX9Nk3MCvD1i6by0s7DvLjtUPzrppRSwyzRncUjU3IqTLk4bPMQwMqzCynKS+eetdupbdapqZVSo5sGQSRFy6DhMHz8l36b3K4kHrxiNpUNrTz04q4EVE4ppYaPBkEkUz8Nbn/EqalnFWSw8uxC/uevH7OxpDrOlVNKqeGjQRCJNwWmXgw71oZtHgL4+sVTyc/080/PvE9rh444VkqNThoEAylaBo1HYP+bYTcHvG7uXzaTPUcaePTVj+JcOaWUGh4aBAOZcjF4AgPe2H7RtHEsmZPHI698xJ4j9XGsnFJKDQ8NgoF4U6y+gp2Rm4cAvnP5DPxeF996ZhtdOv2EUmqU0SAYzIzPQGMF7H8jYpHctGS+fdlpvF1SzeqNByKWU0qpkUiDYDBRNA8BXH16AZ+cnMUPXtjJkbqWOFVOKaVOnAbBYLwB6zaWO9ZCZ0fEYiLCD66YTWtHF999bkccK6iUUidGgyAaRcugqRL2/3nAYoU5KXz1gik8//5BXtpxOE6VU0qpE6NBEI0pF4EnBbavGbTojedOZtpJaXzn99toaI18BqGUUiOFBkE0PH7rNpY7B24eAvC6k/j+FbM4VNfCw+t3x6mCSil1/DQIojX7Gmiqgme+CB2tAxY9/ZQgf//JU/jVX0p45+OjcaqgUkodHw2CaE39NFz0PevqoSeuhtaBB49989PTOCnNxz898z7tnV0DllVKqUTSIBiKs2+Dz/wESv4Mj18GDRURi6b5PNy3tIhdh+r52euJvemaUkoNRINgqOYuh797Cio/hMcuhup9EYteXDSexUXj+Y+XPqSksjGOlVRKqehpEByPKRfB59dC81H4xcVw8L2IRb+7tAivK4lvPfu+3tpSKTUiaRAcr4lnwMr14PLCLy+FfRvCFjsp3cedl0znzY+q+N2WsjhXUimlBqdBcCJyp8EX/ggZ+fCbKyOOM/i7BSdz+ilB7n9+B1sP1MS1ikopNRgNghOVkQ83vAB58+G3K2Djz/sVSUoSHrpyNsnuJJY98gb3rt1OfYve61gpNTJoEAyHQBb8/bPWnETP/yO88n3o0x/wiXGpvPT18/m8Pb7gon/fwPrthxJUYaWUOkaDYLh4A3DNb2De5+C1h+APt/e7h0Gaz8N3l87kmVvOIjPg4aZfb+bG/97EwdrmBFVaKaU0CIaXyw1L/gvO+Tps/iX89npo7z8l9byTgzx36zncdcl0Xv+wggv/7TV++cY+OvWmNkqpBNAgGG4icOE9sPhB2Pmc1YncXNOvmMeVxM3nn8qfbj+f0ydl8d3ndnDFI2+wvbw2/nVWSjmaBkGsfPIWuPIXcOCv1ijk+vD9AROzAvzqhjNYtXweZTXNLPmvN/j+up00tenMpUqp+IhpEIjIYhHZLSJ7ROSuAcpdKSJGRIpjWZ+4m3UVXPe0Nfr4FxdB1Udhi4kIS+bk8fLXF/LZ4gJ+umEvF/37Bl7ZdSTOFVZKOVHMgkBEXMCPgUuAGcByEZkRplwa8FXgr7GqS0Kd+jew4g/Q1miFwVuPWsthZAQ8/OCK2Tx906fwe13c8PhGvvw/WzhSr7e+VErFTizPCBYAe4wxe40xbcBqYGmYct8DHgLG7l+7/PnwhT9BzlR48S74YZF1iWljZdjiCwqzeP62c/j6RVP5047DXPBvr/HEX/fTpZ3JSqkYiGUQ5AMHQl6X2ut6iMh8YKIx5vmBDiQiXxKRTSKyqaIi8oyfI1r2qbDyRVj5Rzj5LOsS0x/OhOe/AUdL+hVPdru47YIpvPjVc5mZl8G3n93GVT95k3XvH6SlvbP/8ZVS6jhJrCZCE5GrgMXGmC/ar/8eONMY8xX7dRLwf8AKY0yJiLwKfMMYs2mg4xYXF5tNmwYsMjpU7IY3VsF7T4Hpsu6LfPZXYcLsfkWNMfxuSxn/un4Xh+taSfO5uXz2BK6YX0DxKUFEJAFfgFJqNBGRzcaYsP2wsQyCTwH3GmM+bb/+JwBjzA/s1xnAR0CDvct4oBpYMlAYjJkg6FZXDm89Apseh7Z6q0/h7K9B4XnWpaghOrsMb35UyTNbynhx2yGa2zuZmOVn2dx8ls0voDAnJSFfglJq5EtUELiBD4ALgDJgI/B3xpjtEcq/ipPOCPpqroFNj1mdyY1HIG+edYZw2hJIcvUr3tjawYvbDvHsO2W88VElxsC8kzO5Yn4Bl8+aQDDFG/+vQSk1YiUkCOw3vhT4EeACHjPGPCAi9wGbjDFr+5R9FScHQbf2Fnj3SXhzFVTvhWAhnHUrzP078PjD7nKwtpnfby3n2S1l7D5cj8clLJo2jivm57No+jiS3f2DRCnlLAkLglgY80HQrasTdv0B/vwjKN8CKbmw4CaYeYXV8RyGMYYdB+t4ZksZv99aTmVDKxl+j92fkM/8k7U/QSmn0iAYzYyBktetQPjoZWtd1qkw9dMw5WI45Wxw928G6ujs4s97Knn2nTLWbz9ES3sXJ2cFOGdKDgsmZbGgMIu8zPBnGEqpsUeDYKyo3gcf/hE+WA8lf4bOVvCmwuSFx4IhbXy/3epb2nlx2yHWvX+QTSVHqW+1pq/Iz/RzZmEWZxRawTA5J0XPGJQaozQIxqK2Rtj7Gny4Hj78E9TZt8GcMAemfNoKhrz5kNR7qEhnl2HnwTo2llTz9r5qNpZUU9nQBkBOqpczJmVxhn3GcNqEdFxJGgxKjQUaBGOdMXB4m3Wm8OEfoXSjNTYhkANTLrLOFE79G/BnhtnVsK+ykbf3VfO2HQ6lR637I6Qlu5l/SpAF9hnD7IIM7XhWapTSIHCapmrY85IVCnteguajkOSGiWdCQbF11jBhrnVFUlL/weXlNc09Zwxv76vmwyPWUA+vO4np49MoystgZn46M/MymDY+DZ9Hw0GpkU6DwMk6O6Bsk3W2sPcVOLwdOq2mIJLTYfxsyJtrh8McyP5Ev3EL1Y1tbCqpZtP+o2wrq2V7eR21zdY9l11JwpRxqRTlZVCUl87M/Axm5KWTmuyO8xeqlBqIBoE6pqMNKnbCwXehfKv1fHgbdNhz/nlSYPwsKxS6AyJnmnX3NZsxhtKjzWwvt0KhOxyO1Lf2lCnMSekJhqK8dIryMsjSQW5KJYwGgRpYZwdU7rZCoTsgDr0P7fZ02W4fnDTTmgdp3AwYdxrkngYp2b0Oc6Suhe3ldWwvr2VbWR3bymt7+hsA8jJ8TM5NpTAnhUk5KRTmBJiUncLErAAel94jSalY0iBQQ9fVad1I5+DWYwFx8D1oDbmVZkou5E63gyHkOZDVU6SmqY0d5VYo7CivY19lI/sqG6lrOXYHNleSMDHoZ1JOCpOyU3qCYnJOCnmZfr1ySalhoEGghocx1iR5FTvhyK6Q513Q1nCsXOpJ4QPCvmrJGMPRpvaeUCipbGRflfVcUtlIY9uxaba9riQmZvmtcMhO4ZTsACdnp3BKVoD8oF/PJJSKkgaBii1joLbUCoQjO0Oedx9rXgJImwBZk62rlbIm2c+F1rN9FmGMoaK+1QqIqkb2VTZZQWG/bu3o6jmcK0nIy/RxSlYKJ2cHOCUrwMlZAWs5O0U7rJUKoUGgEqOrC2oP9A6G6r1wdB80HO5d1pcREgyTeodEej4kJdHVZThS38r+qkY+rm7i4+om9lc1sb+6iY+rGjna1N7rkNkp3mMBkZ3CyVkB8jP95GX6GJ/h0zERylE0CNTI09YIR/dboVC9r/dzzcfQdawPAZcXMk+xgiE9335MgPQ8azltAvjSqWtp5+MqKxysoGi0gqKqiYO1zfS902dOqpe8TD8TMnxMyLACwnq2lsel+bR/Qo0ZAwWBnjurxPCmwEkzrEdfnR1QV9onIEqsR9kWaApzr2dvGunpecy0H6Tnwcl5UGQtt6VMoKzVT3ltC+U1zRysbeFgbTNlNS3srWjkjT1VNLR29DqkK0k4KS3ZCotMP3kZvp7gsMLCTzDg0fmZ1KinZwRq9GlvgfqDVsd1/UFrnqW68t6PhkPWNBuhXMmQdpJ1BpE2HlLHW8/26wZvDge7Milt8lJe18LBmhbKa5uPPde20NbR+5g+TxJ5IWcREzL85Gf6mZBph0WGH79Xm6BU4ukZgRpbPD6rmSirMHKZzg7rTm915XZQ2IFRf8gKiSM74aNXoLWuZ5dUYAowxe3rHRQTJ8CMkzCp46lzZ3G4M53S9nT2NydTXtdGeU0LZTXNvPZBBUfqW+n7v1Uw4OlpespN85GT6iU7xUt2ajI5qcnW69RkMv0ekrQpSiWABoEam1xuuw8hDwj7T5ClrdEKh/pD1tlFw2HruXvd4e2w52Voq0eADPsxFUCSrLEUKeMgfRzkjaMzkEudK0gVmRzqSudAWxp7m/3sbfBSerSZrQdqqW5s7ddfAVZTVDDgJSfVS05qMtmpXrJTkslJ85KTYr+2gyMnNVnneFLDRoNAOZs3xbrjW4S7vvVobbCCofEINNiPxiNWcDRUWM+VH+BqOEyws40g8InQ/ZPcVmjk5GBOzqEtOYsmT5C6pEyOSjqVXekc7kylvF3Y3+KhrKmdj6ubqGpo7TWuIlRqsrvnbOLY87GgyE7xkpNmrUv3ubUvQ0WkQaBUNJJTIfkTkPOJgcsZAy210GiHQ9/QaKxCGitIPrqP5MZKgm0NnBLuOK5kSMmB/Bw6/dm0eLNodGVSl5TOUdKo7EzlUEeA8rYUDjT72F/hZWNJF0eb2vo1TYE1MC871UtmwEum30NmwGMtBzw9rzP8XoIh6zP8Hj3rcAgNAqWGk4g1gtqfCTlTBi/f3gyNlVZwNFVZz31euxorSanaQ0pjBeM6miMfy5eBGZ9Fhy9IqyeTRlcG9d3B0ZXKkY4AR9oDHGlNprzOx47mZA62uGjrjHym4Pe4ekIhM+AhK8VLMOAlK+XYo/t1MMVLVsCrneOjkAaBUonk8UPmROsRjbYmaK627jnRVNV7uakaaarC01yNp6mK1NoPOampuvfo7j6MNwmSM+hMTqfdk06rO50mVxqNSanUk0KNCXC0M0BlZ4AjzckcqvWzrdlLabOHOhOgPcyfEL/HZQeD51hI9DxbZxxB+6wjaK/ze1zadJVAGgRKjSbegPXIKIh+n/YWOzCqoLkGWmrs51rEXna31OBursHfUktmy95j5brvXdFXsvXU5fbT4U2nzZ1GiyuVRkmlXgLUdgU42hGgstpHxWEfh9qS2dPmo84EqCNArUmhngAd9p8grzuJYMBzLCAC3p4mqtDwSPe5SfN5SPO5SfO5SU1249b5pk6YBoFSY53HB57uK6iGwBir6aqltld4hD6SWmrwttTibakltaWWnJZaaCk7VsaEdHSHuR1FuytAqzuNpqRUGiSVurYUalsCVFX6qWz3c7jdx+6uALWkUGcC1BOgAR8Nxk8D1hmJ3+Mi1Q6GNJ+HtORjIZHm85Dqc5Nuv073e0j3eUj3u0m3AyXd73H85IUaBEqp8ESOnYGkTxj6/sZYl+f2BEfNsWU7VDwtNXjsEBnXEzQH7BCpG/QvVId4aXUFaJEATW0BGtv8NBgfdcZPbaePo50+jnZ4KcNPA37qTYAG/DQYP/X2cwN+jCdAmt9rh4Sn58yjOzBCAyTNZ20PXTfa563SIFBKxYaIfbVVKmTkD33/rs7eIdJcY0133lpvP+pwtzbgbq0npbWe7O71bfXQWnWsnLQM+lYGobUjQHNTgMYmKyzqjI/aTh81nVawVOBnn/HRiBU2jRxbbnMFkOR0XP5UvL400gNe62wjNEzs8Ejr1bxlPad63QkdTKhBoJQamZJc1vTkITc6Oi6d7T3BQWvvIOleltZ6fPYjGLKe1mqMXVbaIne6W+8DNEBXg9AiPprskKg3Puq7rNCox0+ZHSb1xk8jPhrw04ifTk8qeFOR5FTEl47Ll44nkEaa39cTGsWTgpwx6QQ/jzBiGgQishj4D8AF/NwY82Cf7V8Hvgh0ABXASmPM/ljWSSnlMC7PCQVKz//pXZ1WU1dbgxUobfX2c+/XSW0NBFobCLTVk2Nv72qpp7O1HlorkNZ6ktobSOpq7/9mbfaj/tiqZpLtQPGzv/AauOG+4/o6BhKzIBARF/Bj4CKgFNgoImuNMTtCir0DFBtjmkTkFuBfgGtiVSellDpuSS7wpVuPoe5qP3rpaO0dKK31vZu+7GV/az2+1gaCLXXkf+K04fhK+onlGcECYI8xZi+AiKwGlgI9QWCMeSWk/FvA52JYH6WUGjncydYjJXvQooL1xzpWf7Bjec1UPnAg5HWpvS6SLwAvhNsgIl8SkU0isqmiomIYq6iUUmpEXDwrIp/DmiLyX8NtN8b81BhTbIwpzs3NjW/llFJqjItl01AZEDpuvsBe14uIXAh8GzjfGNMaw/oopZQKI5ZnBBuBKSJSKCJe4FpgbWgBEZkH/D9giTHmSAzropRSKoKYBYExpgP4CrAe2Ak8bYzZLiL3icgSu9i/Yt0Y6rcislVE1kY4nFJKqRiJ6TgCY8w6YF2fdXeHLF8Yy/dXSik1uBHRWayUUipxNAiUUsrhxIS7r90IJiIVwPFOQ5EDVA5jdYbbSK8fjPw6av1OjNbvxIzk+p1ijAl7/f2oC4ITISKbjDHFia5HJCO9fjDy66j1OzFavxMz0usXiTYNKaWUw2kQKKWUwzktCH6a6AoMYqTXD0Z+HbV+J0brd2JGev3CclQfgVJKqf6cdkaglFKqDw0CpZRyuDEZBCKyWER2i8geEbkrzPZkEXnK3v5XEZkUx7pNFJFXRGSHiGwXka+GKbNQRGrt+Ze2isjd4Y4VwzqWiMj79ntvCrNdRGSV/fm9JyLz41i3aSGfy1YRqRORr/UpE/fPT0QeE5EjIrItZF2WiPxJRD60n4MR9r3eLvOhiFwfx/r9q4jssr+Hz4pIZoR9B/x5iGH97hWRspDv46UR9h3w9z2G9XsqpG4lIrI1wr4x//xOmDFmTD2w7o/8ETAZ8ALvAjP6lPkH4Cf28rXAU3Gs3wRgvr2cBnwQpn4LgT8k8DMsAXIG2H4p1k2EBPgk8NcEfq8PYQ2USejnB5wHzAe2haz7F+Aue/ku4KEw+2UBe+3noL0cjFP9Lgbc9vJD4eoXzc9DDOt3L/CNKH4GBvx9j1X9+mz/N+DuRH1+J/oYi2cEPbfINMa0Ad23yAy1FPiVvfy/wAUiIsSBMeagMWaLvVyPNTPrQHduG4mWAv9tLG8BmSIyIQH1uAD4yBhzvCPNh40xZgNQ3Wd16M/Zr4DPhNn108CfjDHVxpijwJ+AxfGonzHmj8aaJRisW8UWDPf7RivC5xeNaH7fT9hA9bP/dnwWeHK43zdexmIQRHOLzJ4y9i9CLTD4jUOHmd0kNQ/4a5jNnxKRd0XkBREpim/NMMAfRWSziHwpzPah3oY0Vq4l8i9fIj+/bicZYw7ay4eAk8KUGSmf5Uoi3CqWwX8eYukrdtPVYxGa1kbC53cucNgY82GE7Yn8/KIyFoNgVBCRVOB3wNeMMXV9Nm/Bau6YA/wnsCbO1TvHGDMfuAT4soicF+f3H5RYNztaAvw2zOZEf379GKuNYEReqy0i3wY6gCciFEnUz8OjwKnAXOAgVvPLSLScgc8GRvzv01gMgmhukdlTRkTcQAZQFZfaWe/pwQqBJ4wxz/TdboypM8Y02MvrAI+I5MSrfsaYMvv5CPAs1ul3qKhuQxpjlwBbjDGH+25I9OcX4nB3k5n9HO4ufAn9LEVkBXA5cJ0dVv1E8fMQE8aYw8aYTmNMF/CzCO+b6M/PDVwBPBWpTKI+v6EYi0Ew6C0y7dfdV2dcBfxfpF+C4Wa3J/4C2GmM+fcIZcZ391mIyAKs71NcgkpEUkQkrXsZq0NxW59ia4HP21cPfRKoDWkCiZeI/4Ul8vPrI/Tn7Hrg92HKrAcuFpGg3fRxsb0u5kRkMXAH1q1imyKUiebnIVb1C+13WhbhfaP5fY+lC4FdxpjScBsT+fkNSaJ7q2PxwLqq5QOsqwm+ba+7D+sHHsCH1aSwB3gbmBzHup2D1UTwHrDVflwK3AzcbJf5CrAd6wqIt4Cz4li/yfb7vmvXofvzC62fAD+2P9/3geI4f39TsP6wZ4SsS+jnhxVKB4F2rHbqL2D1O70MfAi8BGTZZYuBn4fsu9L+WdwD3BDH+u3Bal/v/jnsvpIuD1g30M9DnOr3a/vn6z2sP+4T+tbPft3v9z0e9bPXP979cxdSNu6f34k+dIoJpZRyuLHYNKSUUmoINAiUUsrhNAiUUsrhNAiUUsrhNAiUUsrhNAiU6kNEOqX3DKfDNqOliEwKncFSqZHAnegKKDUCNRtj5ia6EkrFi54RKBUle175f7Hnln9bRD5hr58kIv9nT472soicbK8/yZ7n/137cZZ9KJeI/Eys+1H8UUT8CfuilEKDQKlw/H2ahq4J2VZrjJkF/BfwI3vdfwK/MsbMxpq4bZW9fhXwmrEmv5uPNbIUYArwY2NMEVADXBnTr0apQejIYqX6EJEGY0xqmPUlwN8YY/baEwceMsZki0gl1vQH7fb6g8aYHBGpAAqMMa0hx5iEdf+BKfbrOwGPMeb+OHxpSoWlZwRKDY2JsDwUrSHLnWhfnUowDQKlhuaakOe/2MtvYs16CXAd8Lq9/DJwC4CIuEQkI16VVGoo9D8Rpfrz97kR+YvGmO5LSIMi8h7Wf/XL7XW3Ar8UkW8CFcAN9vqvAj8VkS9g/ed/C9YMlkqNKNpHoFSU7D6CYmNMZaLrotRw0qYhpZRyOD0jUEoph9MzAqWUcjgNAqWUcjgNAqWUcjgNAqWUcjgNAqWUcrj/D4IFV6TTI3FtAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(np.arange(20), per_epoch_loss, label='Training Loss')\n",
    "plt.plot(np.arange(20), validation_error, label='Validation Loss')\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Error')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 50
    },
    "colab_type": "code",
    "id": "C_HIk7CCUc7-",
    "outputId": "b7bde8f2-502d-4c15-bc7e-8384cbc93a2b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test loss : 0.208873\n",
      "\n"
     ]
    }
   ],
   "source": [
    "test_loss = 0\n",
    "class_correct = list(0. for i in range(10))\n",
    "class_total = list(0. for i in range(10))\n",
    "\n",
    "model.eval()\n",
    "\n",
    "for data, target in test_loader:\n",
    "    output = model(data)\n",
    "    loss = criterion(output,target)\n",
    "    test_loss += loss.item()*data.size(0)\n",
    "    _, preds = torch.max(output, 1)\n",
    "    correct = np.squeeze(preds.eq(target.data.view_as(preds)))\n",
    "    for i in range(batch_size):\n",
    "        label = target.data[i]\n",
    "        class_correct[label] += correct[i].item()\n",
    "        class_total[label] += 1\n",
    "test_loss = test_loss/len(test_loader.dataset)\n",
    "print(\"Test loss : {:.6f}\\n\".format(test_loss))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 202
    },
    "colab_type": "code",
    "id": "gyN7jIYlU7cx",
    "outputId": "91b835e5-799d-4f9f-b6da-31ec51620274"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Test accuracy of     0 : 98% (966 / 980 )\n",
      "Test accuracy of     1 : 97% (1111 / 1135 )\n",
      "Test accuracy of     2 : 92% (953 / 1032 )\n",
      "Test accuracy of     3 : 91% (929 / 1010 )\n",
      "Test accuracy of     4 : 94% (932 / 982 )\n",
      "Test accuracy of     5 : 91% (812 / 892 )\n",
      "Test accuracy of     6 : 95% (919 / 958 )\n",
      "Test accuracy of     7 : 92% (956 / 1028 )\n",
      "Test accuracy of     8 : 91% (890 / 974 )\n",
      "Test accuracy of     9 : 92% (933 / 1009 )\n",
      "Total accuracy : 94% (9401 / 10000)\n"
     ]
    }
   ],
   "source": [
    "for i in range(10):\n",
    "    print('Test accuracy of %5s : %2d%% (%2d / %2d )' % ( str(i), 100. * class_correct[i] / class_total[i], \n",
    "          np.sum(class_correct[i]), np.sum(class_total[i])))\n",
    "print(\"Total accuracy : %2d%% (%2d / %2d)\" % (100. *np.sum(class_correct) / np.sum(class_total) , \n",
    "                                              np.sum(class_correct), np.sum(class_total)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataiter = iter(test_loader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 288
    },
    "colab_type": "code",
    "id": "Tn8CPGqIVAF_",
    "outputId": "99c7f4f5-bb7e-4a6d-b6a8-e447baca58fa"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-27-dc495100ef56>:8: MatplotlibDeprecationWarning: Passing non-integers as three-element position specification is deprecated since 3.3 and will be removed two minor releases later.\n",
      "  ax = fig.add_subplot(2, 20/2, idx+1, xticks = [], yticks = [])\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1800x288 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "images, labels = dataiter.next()\n",
    "output = model(images)\n",
    "_, preds = torch.max(output, 1)\n",
    "images = images.numpy()\n",
    "\n",
    "fig = plt.figure(figsize=(25,4))\n",
    "for idx in np.arange(20):\n",
    "    ax = fig.add_subplot(2, 20/2, idx+1, xticks = [], yticks = [])\n",
    "    ax.imshow(np.squeeze(images[idx]), cmap='gray')\n",
    "    ax.set_title(\"{} ({})\".format(str(preds[idx].item()), str(labels[idx].item())), \n",
    "                 color= (\"green\" if preds[idx] == labels[idx] else \"red\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "-Ec-4FgV9lR_"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "collapsed_sections": [],
   "include_colab_link": true,
   "name": "EMNIST DATA pytorch.ipynb",
   "provenance": [],
   "version": "0.3.2"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}