{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "b0f256f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "from torchvision import transforms, datasets\n",
    "from torch.utils.data import DataLoader\n",
    "from sklearn.metrics import confusion_matrix\n",
    "\n",
    "\n",
    "plt.style.use('fivethirtyeight')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "ebe77bdb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "1.5%"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz to MNIST\\MNIST\\raw\\train-images-idx3-ubyte.gz\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100.0%\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Extracting MNIST\\MNIST\\raw\\train-images-idx3-ubyte.gz to MNIST\\MNIST\\raw\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "102.8%"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz\n",
      "Downloading http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz to MNIST\\MNIST\\raw\\train-labels-idx1-ubyte.gz\n",
      "Extracting MNIST\\MNIST\\raw\\train-labels-idx1-ubyte.gz to MNIST\\MNIST\\raw\n",
      "\n",
      "Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz\n",
      "Downloading http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz to MNIST\\MNIST\\raw\\t10k-images-idx3-ubyte.gz\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n",
      "100.0%\n",
      "22.5%"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Extracting MNIST\\MNIST\\raw\\t10k-images-idx3-ubyte.gz to MNIST\\MNIST\\raw\n",
      "\n",
      "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz\n",
      "Downloading http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz to MNIST\\MNIST\\raw\\t10k-labels-idx1-ubyte.gz\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "112.7%\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Extracting MNIST\\MNIST\\raw\\t10k-labels-idx1-ubyte.gz to MNIST\\MNIST\\raw\n",
      "\n"
     ]
    }
   ],
   "source": [
    "## Loading the data\n",
    "\n",
    "ROOT_DIR = 'MNIST'\n",
    "\n",
    "train_data = datasets.MNIST(\n",
    "    root = ROOT_DIR,\n",
    "    train = True,\n",
    "    transform = transforms.ToTensor(),\n",
    "    target_transform = None,\n",
    "    download = True   \n",
    "\n",
    ")\n",
    "\n",
    "test_data = datasets.MNIST(\n",
    "    root = ROOT_DIR,\n",
    "    train = False,\n",
    "    transform = transforms.ToTensor(),\n",
    "    target_transform = None,\n",
    "    download = True   \n",
    "\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "5cc5eff6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.uint8"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.data.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "eb299919",
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     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "train_data.data[0]"
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  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "abbfdcea",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
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LlmDs2LEICgqCo6MjRo0ahcjISGYwgxnMYEYJZJRWDjOYwQxmMIMqCqWEhISckg7R09OTa7/+/fujdu3a8PHxEdZ17NgRnTp1wuTJk4ulL8xgBjOYwYzSz2EGM5jBjG8hIzExsVj6UFrq1atX1l0o1J07d8q6CzIUZgYqMzMT9+7dg4uLi9R6FxcXhIWFMYMZzGAGM4o5o7RymMEMZjCDGYqprMvzWML3lcRiMSQSCYyMjKTWGxoaIi4ujhnMYAYzmFHMGaWVwwxmMIMZzKCKRK4L6d6/fx///PMPGjdujDp16uDhw4fYtGkTMjIy4O7uDldX15LuJxERERERUZkrdAB1+vRpDB48GDo6OkhLS8OuXbswduxYODg4IDs7G/3798fBgwfRpk2br+qIgYEBRCIR3r59K7U+Pj4exsbGX9U2M5jBDGYwo+xymMEMZjCDGYpJUUvkFF2hJXwrV67Ejz/+iOfPn2PTpk0YNWoUPD09ERQUhD///BOTJk3Cr7/++tUdUVNTg729PUJCQqTWh4SEwNHR8avbZwYzmMEMZpRNDjOYwQxmMIMqkkJnoB4+fAg/Pz8AQJ8+fTBmzBj07NlT2N6/f38EBgYWS2eGDx+OadOmoV69enBycsKePXsQGxsLDw+PYmmfGcxgBjOYUTY5zGAGM5jBDKoo5DoGSllZWfivhoaG1GnJdXR0kJSUVCyd6dq1K8RiMXx9fREbG4tatWohICAAFhYWxdI+M5jBDGYwo2xymMEMZjCDGYqHJXxFU+h1oFxcXLBw4UK0a9cOQO4JJWrVqgUVldyx19WrVzFmzJjPnqNd3utAERERERGVV+XtOlDloSxREU8fX+gM1PDhw5GZmSn8XbduXantp0+fRosWLYq/Z0RERERERAqm0Bmo4sAZKCIiIiKq6MrbDJSTk1NZd6FQt27dKusuyFCYC+kSEREREREpOg6giIiIiIiI5CTXWfiIiIiIiKhi4Vn4ioYzUERERERERHLiAIqIiIiIiEhOHEARERERERHJicdAERERERF9g3gMVNFwBoqIiIiIiEhOHEARERERERHJiSV8RERERETfIJbwFQ1noIiIiIiIiOTEARQREREREZGcWMJHRERERPQNYglf0XAGioiIiIiISE4cQBEREREREcmJJXxERERERN8glvAVjcLNQAUGBsLV1RUODg5wc3PDjRs3mMEMZjCDGSWYUVo5zGAGM5jBDKoIFGoAdeLECSxZsgRjx45FUFAQHB0dMWrUKERGRjKDGcxgBjNKIKO0cpjBDGYwgxlUUSglJCTklHSInp6eXPv1798ftWvXho+Pj7CuY8eO6NSpEyZPnlwsfWEGM5jBDGaUfg4zmMEMZnwLGYmJicXSh9LStGnTsu5CoUJDQ8u6CzKKPAP14cOH4uwHMjMzce/ePbi4uEitd3FxQVhYGDOYwQxmMKOYM0orhxnMYAYzmEEVSZEHUObm5ggPDy+2jojFYkgkEhgZGUmtNzQ0RFxcHDOYwQxmMKOYM0orhxnMYAYzmEEVSaFn4Zs2bVq+6yUSCVatWgV9fX0AwIoVK4q1Y0RERERERIqm0AHU5s2b8d1338kcx5STk4MnT55AS0urWE6BaGBgAJFIhLdv30qtj4+Ph7Gx8Ve3zwxmMIMZzCibHGYwgxnMYIZi4mnMi6bQEr45c+YgKSkJ06dPx7Fjx4RFJBJh06ZNOHbsGI4ePfrVHVFTU4O9vT1CQkKk1oeEhMDR0fGr22cGM5jBDGaUTQ4zmMEMZjCDKpJCZ6C8vLzQsmVLjB49Gn369MHs2bOhrFwyZz8fPnw4pk2bhnr16sHJyQl79uxBbGwsPDw8mMEMZjCDGSWQUVo5zGAGM5jBDKooCh1AAYCzszMuXLiAn376Ce3atcOWLVtKpDNdu3aFWCyGr68vYmNjUatWLQQEBMDCwoIZzGAGM5hRAhmllcMMZjCDGcxQPCzhK5ovvg7Ujh07sGjRIrx79w4hISGws7Mr9DbyXgeKiIiIiKi8Km/XgWrevHlZd6FQn5ZTKgK5ZqA+NmzYMLi4uOD69eswNzcviT4REREREREppC8eQAFAzZo1UbNmzeLuCxERERERlRKW8BVNyZwNgoiIiIiIqALiAIqIiIiIiEhORSrhIyIiIiKi8o0lfEXDGSgiIiIiIiI5cQBFREREREQkJ5bwERERERF9g1jCVzScgSIiIiIiIpITB1BERERERERyYgkfEdFHJBJJiWckJiaWeEZFsmHDhhLPSEtLK/GM8PDwEs/YuHFjiWdMmTKlxDP27NlT4hkaGholnjF9+vQSz5g3b16JZxCRNA6giIiIiIi+QTwGqmhYwkdERERERCQnDqCIiIiIiIjkxBI+IiIiIqJvEEv4ioYzUERERERERHLiAIqIiIiIiEhOLOEjIiIiIvoGsYSvaDgDRUREREREJCeFm4EKDAzE1q1bERcXB1tbW8ycORONGjViBjOYwQyFyti9ezf++OMPvHnzBgBQs2ZNjB07Fq1bty5ym2FhYdi9ezcePnyIt2/fYvbs2ejWrZuwPS0tDb6+vrh48SISExNhamqK3r17Y+DAgRU6o1q1amjWrBnMzMxQqVIlHDlyBP/++y8AQFlZGW3btkXNmjVhYGCAjIwMvHjxAmfPnkVSUpJUO+bm5nB1dYWlpSVycnIQGxuLvXv3Ij09HdWrV0fLli1hYWEBPT097N+/Hzdv3hRu26FDBzg4OEBfXx8SiQRv3rzB6dOn8erVK6kMS0tLdOrUCdWqVQMAREdHY8eOHUhLS0PdunXRq1cv2NjYwNDQEOvWrcP58+eF2x4+fDjf+//XX38hICAAADBx4kS4urpKbQ8PDy/wgq2BgYG4dOkSXr9+DVVVVdStWxejRo1C9erVpfZ7/fo1Nm/ejFu3biErKwvVqlXDrFmzYGVllW+7dnZ26NatG6pXr47KlSvDz88Pf//9t9Q+pqam8PDwgL29PVRUVBAZGYmNGzciMjJS2MfGxgYDBgyAra0tcnJy8Pr1a6xatQrTp0+Hm5sbateujYyMDISGhmLGjBm4d++ecNvt27fD09NTKjM0NBTNmjUT/j5//jzatGkjtc/evXsxcOBATJkyBb1794atrS0yMjJw/fp1zJ07F/fv38/3Pq9fvx4jR47EjBkzsHbtWgC5z82CLpA8c+ZMYZ/mzZsLz9+goCCp56+rq6vM8zc4OFh4/urp6eGnn37KN+PMmTP5ri9IRXjvrUgZVH4p1AzUiRMnsGTJEowdOxZBQUFwdHTEqFGjpN5smcEMZjBDETJMTEzg5eWFAwcOYP/+/WjSpAkmTpxY4JcpeaSnp6NGjRr4+eefoa6uLrN93bp1CAkJwbx587B3714MGzYMvr6++Ouvvyp0hpqaGuLi4nDq1Cl8+PBBapuqqirMzMxw6dIlbN68Gfv27YOenh4GDx4sVZpiYWGBIUOG4MWLF9i6dSs2b96Mq1evIjs7W8iIiYnB0aNHkZmZKdOHuLg4HDlyBGvXroWvry/EYjFGjBgBHR0dYZ+qVavihx9+wLNnz7Bp0yasX78ef//9NyQSCQBAQ0MDr169wtatW5GRkSGTMXz4cKll8eLFAIArV65I7Xf79m2p/Xx8fPJ93PL27dWrFzZs2IDVq1dDJBJh8uTJUoPLqKgoTJw4Eaampli9ejW2bduGESNGQFNTs8B2NTQ0EBERgZ07d+Z7X4yNjTF//nzExcVh8eLF8Pb2xv79+/H+/XthHxsbG0yfPh3379/H3LlzMWvWLBw/fhxZWVlo06YNNm3ahObNm8PV1RVZWVkIDg6GgYGBVM6ZM2dgamoqLF27dpXpy7Zt26T2GTNmDACgVatW8Pf3R9u2bdGlSxdIJBIcP35cJgMA+vTpg0aNGsm8h0RERMDa2lpqmTRpErKzs3Ho0CEAuc+t2NhYnDx5Mt/nr6mpKS5duoSAgADs3bsXlSpVwpAhQ4Tnb1JSElauXCm1HD9+HDk5OQUO9vJTUd57K0qGolBSUlL4RREp1ABq+/bt6NOnDwYMGAAbGxvMmTMHxsbG2LNnDzOYwQxmKFRGu3bt0KpVK1hZWcHa2ho//fQTtLS0cPv27SK32bx5c4wbNw6urq5QVpZ9e/7vv//QuXNnNGzYEGZmZujatSvs7e2lfpWviBlPnjzBuXPn8ODBA+Tk5Ehty8jIwK5du3D//n3Ex8cjMjISx44dg7GxMYyNjYX9OnbsiH/++QeXL19GXFwc3r17h4cPHwpf/sPDw3Hq1CncvXtXJgPIHYg8ffoU7969Q2xsLI4dOwYNDQ2YmZkJ+3Tv3h1Xr17F+fPnERMTg7dv3+LevXtCxq1btxAYGCg1cPtYQkKC1NK4cWO8efNG5nHJysqS2i8lJaWg/xX45Zdf0KVLF1SvXh01atTAzJkzkZiYiLt37wr7bNmyBY0aNcL48eNRq1YtmJubo2nTpqhSpUqB7d6+fRv79u3D9evX8328BgwYgP/++w+BgYF48eIFYmNjcfv2bbx7907YZ+jQoThz5gyOHDmCiIgIREdH459//kF6ejo6d+6M3377Dffu3cPdu3cxdOhQGBsbw8XFRSonIyMDMTExwiIWi2X6kpaWJrVP3uCxZ8+e+P3333H//n3cu3cPI0aMgLGxsdQMFpA7g7Ry5Up4enrKDICys7Ol2o6JiUGvXr1w7tw5vHz5EoB8z9979+4V+PzNyclBamqq1GJnZ4dnz54hISGhwP9Hn6oo770VJYPKN4UZQGVmZuLevXsyb44uLi4ICwtjBjOYwQyFyfiURCLBiRMnkJaWBkdHxxLJAIB69erh8uXLiImJAQDcuXMHjx8/RtOmTZnxkbxZr/T0dACAlpYWqlatipSUFHh6emLy5Mnw9PSUKWOTl0gkQuPGjfH+/XtERUUBALS1tWFlZYXk5GSMHTsWs2fPxpgxY2BjY1OkDA0NDbRo0SLfEq06dergt99+w8aNGzF+/Hjo6enJ3W5aWhqys7Ohq6sLIHcAcPXqVVhbW2PatGno3bs3xo4di3PnzhWp30DuL9pOTk6IiIiAt7c3/Pz8sGjRIqn/v5UqVUKtWrWQkJCAefPmwdfXF3PnzoW9vX2+berq6kIkEskMkFq0aIGYmBiEh4cjICBAatCcx8PDA3Fxcbh79y5++eUXqVnD/DI+HpSIRCLs2LEDy5Ytk2t22draGm3btsW2bdsK3bcgnz5/P6Wvr48aNWpIlZgWpqK891aUDCr/vvgYqISEBOzevRvPnj2DiYkJBg4cCEtLy6/uiFgshkQigZGRkdR6Q0NDhISEfHX7zGAGM5hRXBl5Hj16hIEDByIzMxNaWlpYv349atWqVawZH/Py8sLy5cvRu3dviEQiYV2LFi2Y8f8pKyujY8eOCA8PR3JyMgAIJVmtW7dGcHAwoqOjUbduXQwePBibN28WBnKFsbOzw8CBA6Gqqork5GRs2bJFmP2pXLkyAKB9+/b466+/EBkZCQcHB4wYMQIbNmwQBlryatmyJVRUVKSOkQJyjy8LDQ1FTEwMqlSpgkGDBmHhwoWYPHkysrKyCm13/fr1qFmzJurWrQsg9zM9PT0dgYGBGD58OEaPHo1bt25h8eLF0NTUlJmNkUelSpWgqamJXr164cCBA9i7dy/s7e0xYcIEvH//Hrdv3xZmt/r27Yvdu3fjxYsXaNq0KaZPn45Zs2bJtPnrr78iLCwMV69eFdadPHkShw4dwvPnz2FtbQ0fHx+cO3cODRs2FMowd+/ejZcvXyIyMhL29vZYunQp6tWrh06dOslkrFy5Erdv30ZoaKiwbs6cOXj79i02b94s130fPnw44uLicPTo0S96zPLk9/z9lJOTE1JTU7+oXLiivPdWlAxFoqglcoqu0AGUnZ0dQkJCULlyZbx48QKdOnVCdnY27OzscOzYMaxfvx7BwcEl+qWBiEgRWVtb49ChQ0hJScGpU6cwY8YM7NixA7a2tiWSt3//fvz3339YsWIFzMzMEBYWhg0bNsDMzKxIX3QrWoaSkhL69OkDdXV17N27V2o9kFtCl1diGR0dDWtrazRs2BAnTpyQq/2nT59i3bp10NLSQuPGjTF48GBs2rQJycnJQsb169dx48YNAEBkZCRq1KiBJk2aICgo6IvuS4cOHXD9+nWZE2FcvnxZ+PerV6/w9OlTBAQEoFGjRlJf/POzceNG3L17F+vWrRMGrnmlhM2bN8eAAQMA5J4QJTw8HEFBQUX6/5H3WNy8eVN4bF++fInq1aujY8eOuH37trDPuXPncPHiRWGfunXron379li+fLnQ3qpVq9CiRQu0aNFCqvRx3759wr/v3r2Lmzdv4uXLl+jWrZtwQo6PBz53797Fs2fPcP36dTg6OuLBgwfCtuXLlwvHW+VltGzZEkOHDkWTJk3kut8ikQhDhw5FYGCgXIPZTykpKcHNzQ0aGhpSz99P92nQoAH+/ffffMtAiah0FFrCFxMTIxwAu2jRItja2uL27ds4evQobt++jWbNmgkHun4NAwMDiEQivH37Vmp9fHx8vlPyzGAGM5hRVhl51NTUYGVlBXt7e3h5ecHOzg47duwo1ow879+/h6+vLyZMmICWLVuiZs2a6N+/P9q3b4/du3d/8xlKSkro27cvTExM8Pvvv0uVP+XNEsXFxUndJi4u7ovK3z58+ID4+Hi8fv0aBw8ehEQigbOzMwAIswWfzmbFxsZCX1//i+6LtbU1bG1t5TrDmlgsRnx8vNSxWPnZuHEjzp07h9WrV8Pc3FxYr6enB5FIBGtra6n9rays5J6Z+1RycjKysrKEM1TmiYyMFH7VzyuTi4iIkNonIiIChoaGwt+rV6/GwIED4erqiufPn382NyoqChEREZ/9AePGjRvIysqS2mfFihXo378/OnfujBcvXgjrW7VqBVNTUzx//hzJyclITk6GlZUVfHx88OTJE5m2u3XrBjMzM2zfvv2z/czPx8/fnTt3Fli+V7t2bejq6uLWrVtf1H5Fee+tKBlU/n3RMVA3btzA1KlToa2tDSC3Rnvq1KnCr21fQ01NDfb29jLToyEhIcV2TAEzmMEMZpSknJycfM/gVhwkEgmysrJkTsqgrKyc70H831KGsrIy+vXrhypVqmDnzp1ITU2V2p6QkICkpCSpL+ZAbknOlxyE/yklJSWoqOQWcojFYiQmJsp8wTIyMsr3xAaf07FjR0RHRwunuv4cXV1dVK5c+bMZ69evx9mzZ7F69Wrh9Op5VFVVYWdnh9evX0utj4iIgKmp6Rf1O49EIsGzZ89kBnWmpqbCl9K8E3l8PJgDADMzM2GftWvXCoMnecrVDA0NYWFh8dlySQcHB6ioqAj7rFy5Ev3790eXLl3w6NEjqX0DAgLg7OyMJk2aCEtkZCTWr1+PLl26yLQ9fPhw/P333/kOrj4n7/lrYmKCHTt2yDx/P+bk5IQXL15InYxDHhXlvbeiZCiSsj7DXnk9C59cx0DldT4zM1Pmw8HY2FhmlF5Uw4cPx7Rp01CvXj04OTlhz549iI2NhYeHR7G0zwxmMIMZxWX16tVo1aoVzMzMkJqaimPHjuH69evw9fUtcptpaWnCL/LZ2dmIjo7Go0ePUKlSJZiamsLR0RG+vr7Q0tKCqakpwsLC8Ndff+F///tfhc5QVVUVjjFSUlKCnp4eTExMkJ6ejuTkZPTr1w/m5ubYu3cvcnJyhB/5MjIyhFKqq1evonXr1oiJiUF0dDTs7e1hYWEhnDpdTU1NGGApKSlBX18fZmZmSEtLw/v379G6dWs8ePAASUlJ0NHRQbNmzaCnp4c7d+4I/fz777/RoUMHREdHC8dAVatWDX/++SeA3B8d8wYlysrKMDY2hrW1NVJSUoTPUTU1NbRq1Srfkj8NDQ24u7sjNDQU7969Q5UqVTB06FAkJiYWWL63du1anDlzBosWLYKurq7wxVtTU1M4TbmHhwcWLFgABwcHODk5ISwsDOfOncOiRYsK/H+srq4u3BclJSUYGhrCysoKKSkpiI+Px7FjxzBp0iSEh4fj3r17qFu3Lpo1a4bVq1cLbRw7dgz9+vXDq1evhGOgatasid9++w0bNmzA0KFD0bt3b4jFYpiYmADInU1MTU2FtrY25s+fj4MHDyIqKgrW1tZYunQpYmNjhfK9GjVqYPDgwThx4gTevn2LunXrYtWqVbh16xauXLmCjRs3YtCgQRgwYAASEhJkMuLi4mRmLT98+ICYmBg8fvxYan3VqlXRoUMHjBw5UuaxKuz5279/f5ibm2PPnj0FPn+B3GPLbGxsvrgcNE9Fee+tKBlUviklJCR89ic/AwMD1KpVCyKRCC9fvsSmTZvQq1cvYfuVK1cwatSoz16L4EtKJPIuXBYbG4tatWphxowZQolEcWEGM5jBjILklSwXZubMmbh27Rrevn0LXV1d1KpVCyNGjJDrRAiJiYn5rr916xYmTJggs75r166YM2cO4uPj4evri2vXriEpKQmmpqbo2bMnBg0aJPevdOUx4+jRoxg2bJjM+tu3b+PixYv48ccf8+3HxxfcBXKP83F2doampibi4uJw7tw5oSzM1NQUo0ePlmnj5s2bCAoKgoeHB6pWrQotLS1hgHj+/HmZmZvWrVujWbNm0NLSQkxMDE6dOiXMSKioqOR7zaZz585h/fr1AABXV1eMHz8eo0aNkplVUlNTw/Tp01GjRg1oaWlBLBbj7t272L17N+Lj4wHklup9rG3btvk+NsOGDZO6CO3JkycRGBiI2NhYWFpaYtCgQWjXrl2+t50yZQrq1KmDOXPmyGy7ePEi/P39AeSWwPXq1QuGhoaIjo7GkSNHpE4CAQA9evRAhw4doKOjgzdv3mDfvn3CfcrP/PnzsWDBAmhoaAjX59HX10dUVBTOnz+POXPmCIN3S0tL7Nq1C9999x10dHTw+vVrHD9+HAsWLIBYLC5wxtPHx6fAQxMePnwIPz8/4UK6eWbPno1x48ahRo0aUtfFmj59OqysrGQu+AvkPn8vXLhQ4EVyP77gLgC0adMGjRs3xqpVq6Tep+bNm5fv7fOjyO+9FSWjoPd3RVXQ61yRnD17tqy7IKPQAdSyZcuk/nZ2dpZ6sOfMmYPIyEhs3bq1wDa+ZABFRFSW5B1AfY3y9gFb1jZs2FDiGWlpaSWe8TUXWZbXpwOokjBlypQSzyiN6+1oaGiUeMb06dNLPONLBlBU8srb+zsHUEVTaAlfYS/+z03xExERERGRYlLUY4wUncJcSJeIiIiIiEjRcQBFREREREQkJ7nOwkdERERERBULS/iKhjNQREREREREcuIAioiIiIiISE4cQBERERERfYOUlJQUfvnU6tWr0bZtW1StWhU2NjZwd3eXuR5tTk4Oli5dCjs7O5iamqJbt2548OCB1D4JCQkYPXo0qlWrhmrVqmH06NFISEiQ63HjAIqIiIiIiMqFy5cv44cffsCpU6fw559/QkVFBb1795a6+Pivv/6KjRs3Yvny5Th37hyMjY3Rp08fJCcnC/uMHDkSd+7cwYEDB3DgwAHcuXMHY8aMkasPPIkEERERERGVC4cOHZL629/fH9WqVUNoaCi6dOmCnJwc+Pr64qeffkKvXr0AAL6+vrC1tcWBAwcwfPhwhIeHIzg4GCdPnkTjxo0BAGvWrEGXLl3w+PFj2NrafrYPHEARlbFXr16VeEZmZmaJZ4SEhJR4xuXLl0s8Q97p+69x8ODBEs8gxWNpaVniGZMmTSrxjMOHD5d4hq6uboln1K9fv8QzWrduXeIZRF+jIpyFLyUlBdnZ2dDX1wcAvHz5EjExMXB1dRX20dTURPPmzXHt2jUMHz4c169fh46ODpo0aSLs07RpU2hra+PatWuFDqBYwkdEREREROXS9OnT4eDgIMwkxcTEAACMjY2l9jM2NkZsbCwAIDY2FoaGhlIDSCUlJRgZGQn7fA5noIiIiIiIqNyZOXMmQkNDcfLkSYhEolLL5QCKiIiIiOgbVJ5L+GbMmIFDhw7h6NGjsLa2FtabmJgAAOLi4lC1alVhfVxcHKpUqQIAqFKlCuLj45GTkyM8Bjk5OXj79q2wz+ewhI+IiIiIiMoNb29vHDx4EH/++Sdq1aoltc3KygomJiY4f/68sO79+/e4evWqcMxT48aNkZKSguvXrwv7XL9+HampqVLHRRWEM1BERERERFQuTJkyBfv27cOuXbugr68vHPOkra0NHR0dKCkpYdy4cVi9ejVsbW1Rs2ZNrFy5Etra2ujXrx8AoHbt2mjfvj1+/vlnrF27FgDw888/o1OnToWeQALgAIqIiIiIiMqJLVu2AIBwivI83t7emDFjBgDgxx9/RHp6OqZOnYqEhAQ0bNgQhw4dkjrD55YtWzBt2jT07dsXANClSxesWLFCrj5wAEVERERE9A0qj8dAyXO5ESUlJcyYMUMYUOVHX18fAQEBReoDj4EiIiIiIiKSk8INoAIDA+Hq6goHBwe4ubnhxo0bzGDGN5dx5MgRjB49Gr169UKvXr0wadIkXLt2Tdiek5ODnTt3wt3dHd26dcPkyZPx4sWLL8o4duwYJkyYgH79+qFfv36YPHmy1MGUAPDmzRv4+PhgwIABcHNzw6RJk774wr8qKipo1KgR3NzcMGjQIHTu3BmGhob57tu0aVN8//33qFu3boHt2draYsKECVi+fDkCAgLQrFkzqe2enp4ICAiQWqZPn15ge5MmTUJAQACcnJyEdXXq1MG0adPg5+eHP/74Q+ZimH/88Ue+yw8//CC1X//+/eHn54ddu3Zh3rx5UhdS9fb2RmhoKMRiMaKjo3HkyBHY29tL3X7btm2QSCRSy5UrV6T28ff3x6NHj5CSkoLo6GgcPnwYdnZ2zFDAjPHjx+PPP//E3bt3cevWLWzdulXq4GcVFRVMnz4dJ0+exIMHD/DPP/9g3bp1MDc3l8rYu3cvXr58KbWsX78eQO5z19vbG/7+/jhw4ADatGkjddsDBw7ku4wcORIAIBKJMGTIEKxatQq7du3C5s2b8eOPP8LIyEhoozQeKy8vL1y4cAERERF49uwZ9u3bhzp16qAga9euRVJSEiZOnCisMzAwwC+//IIbN24gJiYG9+/fx+rVq1G5cmVhn/r162Pp0qU4dOgQLl26hC5duki1a2BggJkzZ+Lw4cM4c+YMVq5cKXNB5HXr1uHSpUtSy/z58wvsKwAkJiZi+/btmDx5MiZMmID58+fj0aNH+e67a9cujBkzBqdPn/5sm/Iob5+FFT2Dyi+FGkCdOHECS5YswdixYxEUFARHR0eMGjUKkZGRzGDGN5VhbGyMkSNHYtOmTdi4cSMaNGiAefPm4dmzZwCAffv24cCBA/jf//6HDRs2QF9fH97e3khLS5M7w9DQEMOHD8e6devw66+/ol69evDx8cHz588BANHR0ZgyZQpMTU2xZMkSbNy4EUOHDoWmpuYX3ZfmzZvD3NwcV65cwdGjRxEVFYUOHTrItFOtWjUYGRkVeh/U1dXx5s0b7Nu3D5mZmfnuc//+fUyZMkVY1q1bl+9+HTp0QE5Ojsx6DQ0NvH79Gtu3b0dGRobM9lGjRkkty5YtAwCEhIQI+/Tq1Qvdu3fH9u3bMWPGDCQlJWH27NnQ0NAAALRp0wZ+fn5o0aIF2rdvj6ysLJw+fRoGBgZSWcHBwTA3NxeW7t27S22/efMmRowYAXt7e3Tp0gVKSko4ffo0VFRUmKFgGU2bNsXvv/8ONzc3DBw4EFlZWQgMDISenh4AQFNTE9999x02bNiAbt26YeTIkTAzM8POnTtlrm/yxx9/oFGjRsIyc+ZMAIU/d0eOHCm1LF26FMD/PXfV1dVRvXp1HDx4ENOmTcPy5cthZGSEWbNmQVk59ytDaTxWLVu2xObNm9GhQwd0794dWVlZ+PPPP2UygNzXWsOGDWXeb01NTWFmZoY5c+agWbNmGDVqFFxcXLBt2zZhH01NTTx//hzr1q3D+/fvZdpesmQJLC0tMXPmTIwYMQLR0dFYs2aN8DrOc/z4ceEHr169euGXX36RaStPWlqacJzF//73PyxYsADu7u5Sx2Z8/Bi9ePEC+vr6BbYnr/L4WViRMxSFkpKSwi+KSCkhIUH220Mxy/twKEz//v1Ru3Zt+Pj4COs6duyITp06YfLkycXSF2YwQ9Ey5J3RcXNzw4gRI9CtWzd4eHigZ8+eGDx4MAAgIyMD/fv3x+jRo2W+pAAocKDxKXd3d3h6egoHUiopKWHq1Kly3fbjwUMekUiEgQMH4uLFi3j9+rWwvlu3bnjz5g1u374NIPfMOV26dMGZM2fQrl07PHz4EPfv35dp7/Lly1J/r1u3Dnv27MHVq1eFdZ6entDR0cGGDRs+218rKyuMGzcOixcvxqpVq+Dn54dbt27J1Fbv3LkTW7duxcWLFwtsa8yYMahTpw5++uknYZ2/vz9OnjyJw4cPAwBUVVWxZcsW/P777xg3bpxMG9ra2hCLxXBzc8OxY8cA5P6Kb2RkhJ49e372vnzMwcEBt2/fRp06dWR+0WZG2WZ8+uOAlpYW7t69i1GjRuHs2bP53t7W1hbBwcHo2LEjwsPDAeTOQD169Ahz586V2d/Z2Vn49++//46tW7fiwoULBfZv7NixqFOnDn788ccC97G0tMTatWvh5eWFV69eCc/pPCXxWL1580YmIyIiAgMHDsTJkyeF9VWrVsWZM2fQs2dPHDx4EAEBAcJsXH46duyIP/74A1WrVkWNGjWktp06dQpr167FX3/9JbS9e/dueHp64unTpwByv2weOXIEAQEBwn1dt24dnj17JpzJ62OLFi2SWXf48GE8fvwY06ZN++zjER8fjxUrVuCnn37C+vXr0aZNG3Ts2FFmv09nGQui6J+FFSUjMTGxWPpQWrp27VrWXSjUiRMnyroLMhRmBiozMxP37t2Di4uL1HoXFxeEhYUxgxnfbIZEIsH58+eRnp4Oe3t7REdH4927d2jUqJGwj7q6OhwcHPIddMibcfHiRbx//x516tRBdnY2rl+/jqpVq2LOnDkYOHAgfvrpJ/z9999f1K6SkhKUlZUhkUhk8vIuVKekpISWLVvizp07xfbBk3fK0kWLFmHo0KEyv+yqq6tj5MiR2LVrF5KTk78qS11dHc2bN5f6AlylShUYGBjgzp07wroPHz7gwYMHqF27dr7t6OrqQiQSQSwWS613cXFBVFQUHjx4AH9/fxgbGxfYFy0tLXh6euLly5f5lnQyQ7EydHR0IBKJPvu819HRASD7paxHjx4ICwvDmTNnMGvWLGhraxfYRkE0NDTg4uJS4OAtT95scUpKSr7bS/Ox+vgHDpFIhG3btuGXX34psPwtv75mZGTINVuvqqoKQPoHqJycHGRmZqJevXpS+7Zr1w5Hjx7Fzp07MX78+M/O1P/777+wtrZGQEAApkyZgkWLFuH8+fNSs+ESiQRbtmxB165dYWZmJtd9+5yK8FlYkTKo/Ct0ABUSEoLHjx8Lf2/ZsgVNmzaFpaUlmjVrJjUV/jXEYjEkEolUnTWQW2YUFxfHDGZ8cxnPnz9Hjx490LVrV/z666+YP38+qlevjnfv3gGATCmLgYGBsE1eL168QN++fdG7d29s3LgRs2bNgrW1NRISEpCeno4//vgDTk5O8PHxQevWrfHLL7/IHCf1OVlZWYiNjYWDgwM0NTWhpKSE6tWrw8jISPiCUb9+fWRkZMj9Bagw9+7dw/bt27FmzRrs378f1tbW8PLygorK/510dMiQIbh37x7u3r371XktWrSAioqK1K/8eeU2n85mJSYmFjgjv3btWoSFhUnNpp06dQqenp7o0KEDpk6dCmdnZwQHB0NNTU3qtmPHjkViYiKSk5PRuXNndOjQId9ZR2YoVsa8efNw79493Lp1S2YbkPsFfvbs2Thz5gyio6OF9UeOHMGPP/4IDw8PrFu3Dl26dIGfn1++bXxOfs/dT6moqGDYsGH4559/Cnx/KY3Havny5fj333+l3n9mzpyJ+Ph4bN26Va77q6enh9mzZ2PHjh0yP+rk5+XLl4iOjsbo0aOhq6sLFRUVDBo0CCYmJlLHcZ45cwaLFi3Cjz/+iB07dqB169ZSMxefiouLw8WLF2FsbIxJkybB1dUVhw8flvr/cPToUejo6Mgcf1lU5fmzsCJmKJKyLs8rryV8hZ7GfPLkyVi+fDlsbW2xefNmLFiwAGPGjEGtWrXw+PFjzJ8/HxKJBKNGjSqN/hJ9MywtLeHn54fU1FRcunQJK1aswMqVK4s1w8LCAuvXr0dqaiquXLmCNWvWYOnSpcKMTdOmTdGnTx8AgI2NDR4/foxjx46hcePGcmdcvnwZzZs3R//+/ZGdnY13797hxYsXqFy5MkxMTFCzZk0cPXq02O7TP//8I/z7zZs3ePnyJZYtWwYHBweEhYUJPwAtXry4WPLatWuHGzdufNVM1sqVK+Hi4oJWrVohOztbWL9v3z7h33fv3sXNmzfx/PlzdOvWTaqMavfu3QgODoaZmRkmT56Mffv2oWXLlkhPT2eGAmV8bM6cOXB2dkbfvn2lMvKIRCKsXbsWlSpVkjk5yZ49e4R/h4eH49WrV/jzzz/x3XffybTzOe3bt8c///yDpKSkfLcrKytj0qRJ0NbWFo7z+1RpPFZLlixBs2bN0KlTJyGjRYsWGDx4sMwsQUG0tbWxb98+REZGYs6cOXLdRiKRYNasWZg+fTpOnDiBrKws3Lx5E1evXpX6Uvfx+9ezZ88QGRmJgIAAqROEfCwnJwdWVlbCe2u1atUQGxuLCxcuoG3btggPD8fVq1cxe/ZsufpJRKWv0AHU8+fPYW1tDSD3WIAVK1Zg0KBBwvbvvvsOixcv/uoBlIGBAUQiEd6+fSu1Pj4+/rPT/sxgRkXNUFVVhYWFBQCgVq1aCA8Px6FDh4TXn1gsFsrg8v7++OxS8mbkneHL1tYWjx49QlBQECZMmACRSIRq1apJ7V+1atUvLuNLSUkRDgxXVVVFeno6WrVqhZSUFJiamkJTUxP9+/cX9ldWVoaTkxPq1KmDgwcPflFWfhITE6UeKzs7O5iZmckcJzF69Gg8e/ZMOBhfHlZWVqhZs6bUF1rg/2ae9PX1ER8fL6zX09OTKcVatWoV3N3d0a5dO+EEHgWJiopCREQEatasKbU+KSkJSUlJePLkCUJDQxEfH4++ffti165dzFCgjLwZhjlz5qBnz57w8PCQOjYwj0gkwvr161G7dm14eHgUes2TO3fuICsrC9bW1oiJifnsvnmsra1Rs2ZN7N69O9/tysrK+Pnnn1GtWjXMmzcv3/K9knys8gZZS5cuRd++fdGtWzep0r6WLVvC1NRUqkJGRUUFCxcuxPjx46XO2KetrY0DBw4AAAYMGJDvyTUK8ujRI4wYMQLa2tpQVVVFQkIC/P398fDhwwJv8/DhQ2RlZcmcrS+Pnp6eTFmemZkZzp07J2QmJiZKHSOVnZ2NQ4cO4ezZs1i+fLnc/c9Tnj8LK2IGlX+FlvDp6OgI0/bR0dFwcHCQ2l6/fn1ERER8dUfU1NRgb28vcyB6SEgIHB0dv7p9ZjCjPGcAub9afvjwAaampqhcuTJu3rwpbMvMzMTdu3c/e/rvL8lQVVWFra2tzGv7zZs3UoO2L5GVlYX09HSoqanB3Nwcr1+/Rnh4OI4ePYpjx44JS1paGh48eIAzZ8581X3Jo6OjA319fWHgEhQUhIULF2LRokXCAuSe3vlLS5Lbt2+PmJgY/Pfff1LrY2NjIRaLpY6TUFVVhZ2dnXAiAABYs2YNPDw80L59e6n1BTE0NISFhYVUOden8koe1NXVmaGAGfPmzUPPnj0xcOBA4cQEH1NRUcHGjRthZ2eHgQMHylUyZGdnBxUVFcTGxha6b5685+7Hx+nlEYlE8PLyEgZP+Q3gSuOxWr58Ofr164fu3btLDZQAYPPmzWjWrBlcXFyEJTIyEhs3bkSPHj2E/XR0dHDo0CGIRCL069cPqamphfY1P6mpqUhISIClpSVq164tc0Kbj9WoUQMqKipSP558zMbGRmagGxMTI5QFtm7dGnPmzMHs2bOFRV9fH+3bt8fPP/9cpP5XlM/CipKhSMq6PK/ClvB16NABAQEB2LRpE1q2bImgoCCpQdShQ4dgY2NTLJ0ZPnw4pk2bhnr16sHJyQl79uxBbGwsPDw8iqV9ZjCjvGRs2bIFTZo0gbGxMdLT03Hu3Dn8+++/8PHxgZKSEvr06YM9e/agatWqsLS0xO7du6GhoQFXV1e5M7Zv3w5nZ2ch48KFC/jvv/+E65f069cPy5Ytg729PerXr487d+7g77///uKykrwZrqSkJOjq6qJhw4ZITEzEkydPkJOTI3Pq4OzsbKSnpxdYVqSuri78CqisrIzKlSvD0tISaWlpSE1NRY8ePXDr1i0kJibC0NAQffr0QXJysnDwb0JCQr5fCN+9eyf84qiurg5TU1MAuR8uRkZGsLKyQkpKivClSE1NDS1btsSRI0fy7eeJEyfQp08fvHnzBlFRUXBzc8P79++FL17r16/HkCFD4ObmBrFYDBMTEwC5M3apqanQ1tbGvHnzcOjQIURFRcHa2hqLFy9GbGys8Ou8jY0N3NzccPbsWcTFxcHS0hLe3t7IyMjAsWPHmKFgGcuWLUOfPn0wevRoJCYmCs/j1NRUpKWlQSQSYdOmTahfvz5++OEH5OTkCPskJSUhIyMD1apVQ+/evXH+/HmIxWLY2tpi9uzZuHv3Lm7cuAEXFxfhuausrAwjIyNYW1sjJSVFeH5/7rmrrKyMyZMnw8bGRijbyzumLy0tDZmZmaXyWOXNbg0aNAgJCQnCDzepqalITU3F27dvZWYIPnz4gJiYGDx58gRA7uApKCgIurq6GDRoELS0tKClpQUAwgkvNDU1hZl+ZWVloaw4KSkJsbGxaNOmDRITExEdHQ0bGxtMmjQJly5dEkqFzc3N0bFjR1y9ehWJiYmwtrbGhAkT8OjRI/z333/o16+fzGPcvn17LF++HCdOnECjRo3w+vVrnDt3Dr179wYAVKpUCZUqVZK6jUgkQqVKlYT/t0VRHj8LK3IGlW+FDqDmz5+PTp06oUuXLmjYsCE2bdqEkJAQ4RioGzduIDAwsFg607VrV4jFYvj6+iI2Nha1atVCQECA8ObGDGZ8Kxnv3r3DsmXLIBaLoa2tjerVq2Px4sXCKYrd3d2RmZmJDRs2IDk5GXZ2dli2bJnw5UAeYrEYK1euFDKsra2xYMECNGzYEADQrFkz/O9//8Mff/yBgIAAmJubw8vL64uOfwJyZ16cnJygpaWFjIwMvHr1CmFhYflef0keVlZWmDJlivB33nVXQkJCEBgYCAsLCzRt2hRaWlpITExEeHg4AgICvqhsx8bGRupCmO7u7nB3d8eFCxewadMmALnXt1JXVy/wAPwjR45ATU0NP/zwA7S1tfHkyRMsXrxYGDCOHz8eQO61cj62YMECLFy4EBKJBA4ODhg6dCj09fURFRWFCxcuwMPDQyinysjIQJs2beDl5QV9fX3ExMTg0qVLcHFxQUxMDDMULOP7778HAJmSzzVr1mDt2rUwMzNDp06dAOReV+hjkydPxoEDB/Dhwwe4uLhgxIgR0NLSQlRUFM6dO4e1a9ciOzsbNjY2WLBggXA7Dw8PeHh44Pz589i4cSOA3LOJaWho4Pz58/iUoaGh8Br/9FpGGzZswIULF0rlsco7LCDvVOF5li5dKly7qjANGjQQ7sunZ0/r2rUrkpOTUbt2baly3h9++AE//PAD/vrrLyxZsgSGhob43//+h8qVKyM+Ph4nT57Ejh07hP2zsrLQsGFD9OvXD5qamoiNjcXVq1exffv2fI9tA3LLJ8ePH4+goCAcP34clStXRq9eveQ+HXlRlcfPwoqcQeWbXNeBSkxMxK+//ooTJ07gxYsXyM7OhomJCZo2bYrx48cXOqUp73WgiL5F8l4H6mvIex2or5HfdaCK2+fKZopLYcebFIfiOLaLyp+CjokpTh9fB6qkfHodqJJQlNOyf6n69euXeEZ+14EqbiU98KIvU96uA/VxyauiKs4TTRWXQmeggNwB0Ny5c/O9aB8REREREdG3QmEupEtERERERKToOIAiIiIiIiKSk1wlfEREREREVLEo6mnCFR1noIiIiIiIiOTEARQREREREZGcWMJHRERERPQNYglf0XAGioiIiIiISE4cQBEREREREcmJJXxEnxEWFlbiGe3atSvxjPJ2ZXSi0qasXPK/J/r4+JR4hra2dolnDBo0qMQzzM3NSzzDwMCgxDNq165d4hlEX4MlfEXDGSgiIiIiIiI5cQBFREREREQkJ5bwERERERF9g1jCVzScgSIiIiIiIpITB1BERERERERyYgkfEREREdE3iCV8RcMZKCIiIiIiIjlxAEVERERERCQnhRtABQYGwtXVFQ4ODnBzc8ONGzeYwQyFzQgKCoKHhwe2bdsmrEtISMCmTZswbtw4fP/991i6dCmioqIKbOOnn35CcHAwXr58iUePHmH37t2oU6eO1D4zZ85EaGgoXr9+jWfPnuHw4cNo3Lix1D5VqlSBr68vHjx4gIiICPz999/o168fAMDb2xuhoaEQi8WIjo7GkSNHYG9vL3X7bdu2QSKRSC1XrlyR2sff3x+PHj1CSkoKoqOjcfjwYdjZ2ZVaRkW6L8xQrIxp06bh6tWriI+PR2RkJA4fPiyTsXXrVnz48EFquXz5stQ+I0eOxJkzZxAXF4cPHz7AysoKn6OiooJGjRqhT58+GDhwIDp16gRDQ0Nhe/369dGzZ08MHDgQAwYMQPv27WFsbPzZNj+WnZ2N06dPY8WKFZgzZw5WrFiB06dPQyKRAAAkEgn++usv/Prrr5g7dy6WLFmCvXv3IiEhQaEyAODw4cMYNmyY1DJp0iSpfaKjo7Fu3TqMGzcOo0aNwty5cxEZGSl3xvHjxzFx4kS4u7vD3d0dU6dOxT///CNsF4vFWLt2LTw9PdGvXz/Mmzfvi9r/nPL8WcgM+tYo1ADqxIkTWLJkCcaOHYugoCA4Ojpi1KhRxfbmxAxmFGfG48ePcfbsWVSrVk1Yl5OTg1WrViE6OhqTJ0/GsmXLYGRkhMWLF+P9+/f5ttOiRQts27YNnTt3Rq9evZCVlYVDhw5BX19fKmvatGlo0aIFunbtilevXmH//v1SX6R8fX1Rq1YtDBkyBC4uLti3bx/8/PzQrFkztGnTBn5+fmjRogXat2+PrKwsnD59GgYGBlJ9CQ4Ohrm5ubB0795davvNmzcxYsQI2Nvbo0uXLlBSUsLp06ehoqJSKhkAKsx9YYZiZbRu3Rp+fn5o1aoVOnbsiKysLJw8eTLfDEtLS2Hp0aOH1HYtLS2cOXMGixYtgjyaNWsGc3NzhISE4NixY4iKikL79u2hqakJAEhKSsL169dx9OhRnDp1CikpKXB1dYWGhoZc7V+8eBGhoaHo0aMHvLy80L17d1y9ehUXLlwAAHz48AGRkZFo27YtJk6ciKFDhyIxMRHbt28XBkCKkJHHzMwMv/76q7D4+PgI2+Li4uDj4wNjY2N4e3tj8eLF6Nu3L9TV1eVu39DQEJ6enlizZg1Wr16NevXqYcmSJXj+/DlycnKwZMkSREZGYubMmVi7di2qVKmCOXPmFPj+Lq/y/FnIjPJNSUlJ4RdFpJSQkJBT0iF6enpy7de/f3/Url1b6g2xY8eO6NSpEyZPnlwsfWEGM74kIywsLN/1aWlpmD59OsaMGYMDBw6gatWqGDFiBCIjI+Hl5YXly5cLvzxnZ2dj7Nix8PDwgKurq0xb7dq1k/pbW1sbL168wJAhQ3Dq1Kl883V1dfHy5Uv069cP586dAwC8evUK06dPx+7du4X9/v33X2zevBmLFy+WyRCLxXBzc8OxY8cA5P6Cb2RkhJ49e372MfmYg4MDbt++jTp16uDRo0elnlGR7gszyjbjyZMnMhnx8fHo27cvjh8/DiB3BsrQ0BC9e/cutO2GDRsiNDQUNWvWxMuXL4U+fkwkEsHDwwMXL15ERESEsL5r166IjIzE7du3ZdpVVVWFh4cHgoOD853Z1tbWlvr7t99+g5aWFgYMGCCs++OPP5CWlgZPT898+x4TE4O1a9fixx9/hKmpaaH3tSQyzM3NZdYdPnwY//zzD5YsWZJvm76+vlBSUsLYsWML7TMAmcFxQQYNGoTvv/8eDg4OGDduHH799VdUr14dQO77+7BhwzB06FB07NhR5ra1a9eWK0PRPwuZIX9GYmJisfShtPTt27esu1CogwcPlnUXZCjMDFRmZibu3bsHFxcXqfUuLi4FfollBjPKKiMgIABNmjSRKfHJysoCkPslJ4+ysjJUVFTw8OFDudrW0dGBSCQqsLxFVVUVw4YNQ1JSEv777z9h/bVr19C7d28YGBhASUkJXbp0gaGhofAr8Md0dXUhEokgFoul1ru4uCAqKgoPHjyAv7//Z0uFtLS04OnpiZcvX+LFixdlklGR7gszFDPj09ehi4sL3rx5g3v37sHPz++Lyuk+paSkBGVlZZlZGIlEkm+7ysrKsLW1RWZmpsx9L4i1tTWePXuG2NhYALkDl2fPnn32i31GRgYACLNgipCRJy4uDj/++CMmT56MTZs2CZnZ2dm4ffs2zM3NsXLlSvzvf//D/Pnzce3atS9q/2MSiQR///033r9/Dzs7O3z48AGA7Pu7qqoq7t+/X+Sc8vxZyAz6VhU6gHJ3d8e+ffuEN7uSIhaLIZFIYGRkJLXe0NAQcXFxzGCGwmScPXsWMTExcHd3l9lmbm4OIyMj7N27FykpKcjKysKRI0fw7t07uev9ly5dijt37kjV3QO5v369evUKUVFRGDt2LNzc3KTuw4gRI5CTk4OnT58iOjoa/v7+GDVqFO7evSuTsXbtWoSFheHq1avCulOnTsHT0xMdOnTA1KlT4ezsjODgYKipqUndduzYsUhMTERycjI6d+6MDh06IDMzs0wyKtJ9YYZiZaxevRq3b9+WyRg+fDg6deqEadOmwdnZGadPn5bJkFdWVhZiY2Ph4OAATU1NKCkpoXr16jAyMpIaWFhYWMDDwwODBg1CnTp1EBwcLHfJWOvWreHo6Ii1a9di1qxZWLt2LZycnNCsWbMC+3TixAnUqVNH7uqR0sgAgBo1amDkyJGYPHkyRowYgcTERPj4+CAlJQVJSUl4//49jh49iu+++w5Tp05F06ZN4efnl+9M3ue8ePECAwYMQN++feHr64sZM2bA2toalpaWMDY2xu+//47k5GR8+PABBw8exNu3b+Ue0OanvH4WMqNiKOvyvPJawlfodaBOnz6NM2fOwNvbG+7u7hg2bBjq1q1bGn0jUjiRkZHYu3cvFixYIByT8zEVFRV4eXnB398fI0eOhLKyMhwcHNCgQQPk5BReLevj44MmTZqga9euyM7Oltp2+fJltG7dGoaGhvj++++xbds2dOrUCTExMQByTzRRuXJl9O7dG/Hx8ejWrRt8fX3RrVs3hISECO2sXLkSLi4uaNWqlVTGvn37hH/fvXsXN2/exPPnz9GtWzccPnxY2LZ7924EBwfDzMwMkydPxr59+9CyZUukp6eXakZFui/MKPuMj38k/OWXX+Di4oI2bdpIZfzxxx9SGbdu3cLTp0/RtWtXBAUFoSiuXLmC5s2bo1+/fsjOzsa7d+/w4sULqRNJxMTE4Pjx41BXV4etrS1atWqFkydPyrwe8nPnzh2EhYXB3d0dJiYmiIyMxLFjx2BgYABnZ2epfSUSCf744w+kp6dj6NChct+H0sgAck+o8TEbGxtMmTIFly9fRpMmTQAATk5O6Ny5MwDAysoKz58/R3BwMBo0aCB3joWFBdauXYu0tDRcuXIFa9euxZIlS2BlZYUZM2Zg/fr1GDx4MJSVlVG/fn00bNhQrvd3Iqo45LqQ7oULF3D69Gns2rULmzdvhpOTE4YNG4a+fftCS0urWDpiYGAAkUiEt2/fSq2Pj4//qhIJZjCjODMePXqE5ORkTJkyRViXnZ2Nhw8fIjg4GDt27ECNGjWwfPlypKWlISsrC5UqVcKsWbNgY2Pz2bYXL16MPn36oFevXsIxEx9LS0vD8+fP8fz5c9y4cQP//PMPhg4dipUrV8La2hpjxoxBy5Ytce/ePQDAvXv30LRpU4wePVoYQK1atQru7u5o164dnj9//tn+REVFISIiAjVr1pRan5SUhKSkJDx58gShoaHCcSK7du0qtYyKdF+YoRgZeccOrly5EgMGDECHDh2KnPElUlJShBNZqKqqIj09HS1btkRycrKwT1ZWFpKTk5GcnIy3b9+iV69eqFmzplQJb0H++usvtGzZUhh8mJqaIiEhARcuXJAa3EgkEuzduxcxMTEYNWqUzLFUZZ2RHw0NDVhYWCA6Olooufz02Clzc3OEhoZ+UbuqqqpCOzVr1sSTJ09w5MgRTJo0CTVr1sSvv/6K1NRUZGVlQU9PD1OmTPmq50B5/CxkBn3r5DoGyszMDFOmTMHt27dx4MABWFhYYPLkybCzs8PPP//8xdPj+VFTU4O9vb3UL+UAEBISAkdHx69unxnMKI4MZ2dn/PLLL1i+fLmw1KhRA82aNcPy5culZqW0tLRQqVIlREVF4dmzZ2jYsGGB7S5duhRubm7o3bs3Hj9+LFdflJWVhdKhvHKfT2etsrOzoayc+zJfs2YNPDw80L59e4SHhxfavqGhofDlpCB50+t5Z7kqjYyKdF+YoVgZq1evhru7Ozp27FhsGfLKyspCeno61NTUYG5uLnVSifz6LRKJ5Go3MzNTpgRGWVlZasZEIpFgz549iI6OxsiRI6Grq/tFfS+NjIJyo6KioK+vDxUVFVSvXl3m/0V0dLRMKdaXys7OFo5/yqOtrQ09PT1ERkbiyZMnwgxYUZTHz0JmVBxlXZ5XYUv4PuXq6gpXV1e8ffsWgYGB+P3337Fjxw68e/fuqzszfPhwTJs2DfXq1YOTkxP27NmD2NhYeHh4fHXbzGBGcWRoa2vL/Gqqrq4OHR0dVK1aFQAQGhoKXV1dGBkZ4fXr1/jtt9/g7OwsU36SZ8WKFXB3d8eQIUOQkJCAKlWqAABSU1ORmpoKXV1dTJw4EadOnRK+DIwcORLm5uZC2dDjx4/x9OlT/PLLL5g7dy7evXuHbt26oU2bNhg8eDDWr1+PIUOGwM3NDWKxGCYmJgByf/1OTU2FtrY25s2bh0OHDiEqKgrW1tZYvHgxYmNjhfInGxsbuLm54ezZs4iLi4OlpSW8vb2RkZGBY8eOlUoGgApzX5ihWBnr1q3D4MGD0bdv3wIz5s6di8OHDyMqKgpWVlZCxsfleyYmJjA1NYWtrS0AoE6dOtDX18erV6/yff2bmZlBSUkJSUlJ0NXVhZOTExITE/HkyROoqqrC3t4eERERSEtLg4aGBmrXrg0tLa0CT6ryqTp16uDixYuoXLmyUF53+fJl4YugRCLB7t27ERERge+//x5KSkrC7JeGhobUCRPKMgMA9uzZA0dHRxgaGiIpKQlHjhxBRkYGWrRoASD37IUbN25ErVq1ULduXTx48ADXrl2TuVbU5+zYsQONGjWCkZER0tPTcfHiRdy9exdz584FkFtKXalSJVSpUgUvXrzAli1b0KRJk6/+Yl3ePguZQd+6Lx5A5TEyMsKPP/6IH3/8EZcuXSqWznTt2hVisRi+vr6IjY1FrVq1EBAQAAsLi2JpnxnMKKmMj4nFYuzcuROJiYkwMDBAy5YtP3ua0JEjRwIAjhw5IrU+b4YrKysLdnZ2GDx4MCpXrox3794hLCwM3bt3F878lJWVBXd3d8ybNw+7d++GtrY2nj9/jv/97384deoU9uzZAyD3GjYfW7BgARYuXAiJRAIHBwcMHToU+vr6iIqKwoULF+Dh4YGUlBQAuWfNatOmDby8vKCvr4+YmBhcunQJLi4uiImJwfjx40s8A0Cp5DDj28sYN24cAODMmTNSGQsXLsSiRYsgkUjw3XffYciQIULGxYsXMXDgQCEDAEaPHi182QaAo0ePAgB++OEH5EdNTQ2Ojo7Q0tJCRkYGXr16hdu3byMnJwfZ2dnQ09ODjY0N1NXVkZGRgfj4eJw+fVruk9L07NkTp0+fxpEjR5CSkgJdXV04OzsLl1RISkoS3kc2bNggddt+/fp9dua8NDMACO/jycnJ0NXVRc2aNTF37lxhhqlhw4YYPnw4jh49isDAQJiYmGDUqFFfdPyTWCzG6tWrIRaLoa2tDWtra8ybNw9OTk7C9m3btiEhIQEGBgZo27ZtvicU+lIV5bOQGfStKPQ6UPXq1cOFCxdQuXLlIod8yVl2iBRJaZyy9NPrQJWE8nZdCqLSllfqWpI+vQ5USfja44oURX7XgSpu8l4H6mvIex0oqjjK2+ftx9dvU1Qfn8BHURQ6A3Xnzp3S6AcREREREZHCU5gL6RIRERERESm6Ih8DRURERERE5ZeinuVO0XEGioiIiIiISE4cQBEREREREcmJJXxERERERN8glvAVDWegiIiIiIiI5MQBFBERERERkZw4gCIiIiIiIpITj4Ei+gwrK6sSzzA0NCzxjPJ2ZXT6ek2aNCmVHH19/RLPOH/+fIlnqKmplXjG0KFDSzyDiOhL8BioouEMFBERERERkZw4gCIiIiIiIpITS/iIiIiIiL5BLOErGs5AERERERERyYkDKCIiIiIiIjmxhI+IiIiI6BvEEr6i4QwUERERERGRnDiAIiIiIiIikpPCDaACAwPh6uoKBwcHuLm54caNG8xghkJlhIWFYerUqejRoweaNWuG48ePS21PS0vDqlWr0LNnT7Ru3Rru7u7Ys2dPge2NGTMGBw8eRFhYGK5duwZ/f3/Y2tpK7dOxY0ds27YN165dw+PHj9G4cWOZdqpVq4aNGzfi2rVrCAsLw6+//ipcpNfb2xuhoaEQi8WIjo7GkSNHYG9vL3X7bdu2QSKRSC1XrlyR2sff3x+PHj1CSkoKoqOjcfjwYdjZ2ZVaRkW6L6WR0aBBAyxfvhxHjhxBSEgIunbtKnVbAwMDzJo1C0eOHMG5c+ewevVqWFpaSu1TuXJlzJ07F0ePHsW5c+ewY8cOdOzYUdj+3XffYe7cudi5cydOnDiB9u3bS91eQ0MDY8eOxc6dO3H48GEEBASgd+/ewnYdHR2MHTsW/v7+OHz4MHbs2IEJEyZAV1dX2GfKlCm4fPkyYmJi8OrVKxw4cAB169ZFQdavX4/09HT89NNPwrpq1aohPT093+Xnn3+Gl5cXzp8/j9evX+Pp06fYu3cv6tSpU2DG2rVrkZiYiIkTJ0qt9/T0xNGjR/Hy5UskJiaiWrVqBbbxOeXtfZEZzGBG+aSkpKTwiyJSqAHUiRMnsGTJEowdOxZBQUFwdHTEqFGjEBkZyQxmKExGeno6atSogZ9//hnq6uoy29etW4eQkBDMmzcPe/fuxbBhw+Dr64u//vor3/aaNGmC3bt3Y8CAARg6dCiysrKwY8cO6OnpCftoamri1q1bWLJkSb5taGpqYvv27VBSUsLQoUPh7u4OVVVV+Pv7Q0lJCW3atIGfnx9atGiB9u3bIysrC6dPn4aBgYFUO8HBwTA3NxeW7t27S22/efMmRowYAXt7e3Tp0gVKSko4ffo0VFRUSiUDQIW5LyWdIRKJoKmpiWfPnmHt2rV4//69zPNm+fLlqFq1KqZPnw5PT09ER0dj3bp10NDQEPaZO3curKys4O3tjSFDhuDkyZOYO3cuGjRoACB3gPTy5Uv4+/vnmzFq1Cg4Oztj5cqVGDNmDPbu3Yvhw4fD1dUVAGBoaAhDQ0Ns27YN48ePxy+//ILvvvsO3t7eQhutWrWCv78/2rZtiy5dukAikeD48eMyjxUA9OnTB40aNZJ5fUdERMDa2lpqmTRpErKzs3Ho0CG0aNECW7ZsQceOHdGjRw9kZWXhyJEj+Wb06tULDRs2zPc9RFNTE+fPn8eyZctktsmrPL4vMoMZzKBviVJCQkJOSYd8/EXwc/r374/atWvDx8dHWNexY0d06tQJkydPLpa+MIMZX5Lx7t27z253dXXF5MmT0a1bN2Hd4MGD0aZNG4waNUpYN27cONjY2GDKlCkybTRp0kTqby0tLdy6dQvjx4/HuXPnpLYZGBjg+vXrGDx4MK5fvy6sb9GiBbZu3QpnZ2ckJSUByP1l/+bNmxg+fDh27dol1Y62tjbEYjHc3Nxw7NgxALmzHUZGRujZs+dn7/PHHBwccPv2bdSpUwePHj0q9YyKdF+KO8PDwwOvXr0S1gcHB2P16tU4ceIEAKBq1arYt28fvv/+ezx58gRA7i+Rx44dg5+fH44ePSrcbs2aNVIzrYcOHcL+/fuxZ88e6OvrC+sPHjwIX19fBAcHC+s2bdqEK1euIDAwUFi3fPlyvHjxAr6+vvneh0aNGmH+/Pno378/0tPTcf78eZnHKiYmBgMGDBDuD5A7y3T+/Hl07doVR44cgZ+fH9auXVvgY3Xs2DHk5OSgR48eUFNTk8l4/fo1Bg0ahJMnTwrrq1atitOnT6NXr144cOAANm/ejPXr18u07ejoiAsXLsDBwUH4/5CYmFhgXz6m6O+LzGAGMwom7+tcUQwZMqSsu1CoT7/DKAKFmYHKzMzEvXv34OLiIrXexcUFYWFhzGCGwmZ8ql69ekK5EQDcuXMHjx8/RtOmTeW6vba2NkQi0Re9CaupqSEnJwcZGRnCuszMTGRnZ6Nhw4Yy++vq6kIkEkEsFkutd3FxQVRUFB48eAB/f38YGxsXmKmlpQVPT0+8fPkSL168KJOMinRfijsjKiqqwP0AQFVVFUDu8yRPTk4OMjMzUa9ePWHdnTt34OrqikqVKkFJSQktW7aEvr6+3OUs9+/fR5MmTWBkZAQAqFOnDmrUqIGbN29+9n58+PBB6vn8sbzHKiEhQVgnEomwY8cOLFu2DOHh4YX2y9raGm3btsW2bdvy3a6jo5NvxtatW7Fy5cp8B/PFoaK8LzKDGcwoH8q6PK/ClvBlZ2dj5cqV8PDwwPbt2wHkjgQbNmwIR0dHzJ07V+oDuKjEYjEkEonwIZvH0NAQcXFxX90+M5hRUhmf8vLygq2tLXr37o0WLVpg/PjxGD9+PFq0aCHX7WfPno379+9/0Rv17du3kZaWBm9vb2hqakJTUxPe3t5QUVFBlSpVZPZfu3YtwsLCcPXqVWHdqVOn4OnpiQ4dOmDq1KlwdnZGcHCwzC/zY8eORWJiIpKTk9G5c2d06NAh3/eA0sioSPeluDM+fPiQ7+OV5+XLl4iOjsaYMWOgq6sLFRUVDBkyBCYmJlKvl9mzZyMnJwcnT57ExYsXMW/ePMybNw+PHz/+bPt5/Pz88Pz5c+zcuRN//vknli9fju3bt0vNoH5MW1sbQ4cOxcmTJ5GdnZ3vPitXrsTt27cRGhoqrJszZw7evn2LzZs3y9Wv4cOHIy4uTphp+9Ty5ctx584dqX7OnDkT8fHx2Lp1q1wZRVFR3heZwQxmUEVW6HWglixZgi1btqBLly5YtWoVIiMjsWXLFkyYMAHKysrYtGkT1NTUMHv27NLoL5HC279/P/777z+sWLECZmZmCAsLw4YNG2BmZoZmzZp99rYzZsxAw4YNMXDgwAK/PObn3bt3mDRpEhYsWIDBgwcjOzsbx44dw927d2XaWblyJVxcXNCqVSupbfv27RP+fffuXdy8eRPPnz9Ht27dcPjwYWHb7t27ERwcDDMzM0yePBn79u1Dy5YtkZ6eXqoZFem+lESGl5dXgTM4ACCRSDBjxgzMmDEDp06dQlZWFm7cuIGQkBCpX/zGjBkDfX19TJw4EYmJiWjVqhXmzJmD8ePHC6V/n9OjRw/UqVMH8+fPR2xsLL777jv88MMPiImJkZmF0tDQwLx58xAfH1/gzNDy5cvRvHlzuLq6Co9Vy5YtMXToUJly2IKIRCIMHToUgYGByMrKktm+ePFiNG3aFJ07dxYyWrRogUGDBsn9QwgREVVchQ6g9u/fDz8/P3Tu3BkPHz5E8+bN4efnhwEDBgAAbG1tMXfu3K8eQBkYGEAkEuHt27dS6+Pj4z9bssIMZpR1xsfev38PX19fLF68GC1btgQA1KxZE48fP8bu3bs/O4CaOXMmunXrhqFDh+L169dfnH358mW0a9cOBgYGyMrKQnJyMkJCQqTaWrVqFdzd3dGuXTs8f/78s+1FRUUhIiICNWvWlFqflJSEpKQkPHnyBKGhoYiPj0ffvn2FGuXSyKhI96WkMtq2bSt17E5+wsPD4enpCW1tbaiqqiIhIQGbN2/Gw4cPAQAWFhbo37+/1HFST548Qf369dGvX79CT5SgpqYGT09PLF26VJjJefHiBWxsbODm5iY1gNLQ0MDChQsBAPPnz893Bm3FihXo168fOnfuLFUG2apVK5iamko9fioqKvDx8cH//vc/mcerW7duMDMzE6oqPrZkyRL07dsX3bt3l8po0aIFTE1NpUr3VFRUsGDBAowbN+6zZwX8EhXlfZEZzGAGVWSFlvDFxMQIp9a1s7ODSCSCg4ODsL1+/frCsR5fQ01NDfb29ggJCZFaHxISAkdHx69unxnMKKmMj0kkEmRlZUFZWfqlpaysjJycgs/XMnv2bHTv3h3ff/89nj179lV9EIvFSE5ORtOmTWFoaIizZ88CANasWQMPDw+0b99ermNEDA0NYWFhgejo6AL3yatPzjsbYWlkVKT7UpIZecc4ySM1NRUJCQmwtLSEnZ0dLl26BABCPz+dxczOzpZ5judHJBJBVVVV5vYSiUTq9pqamli0aBGUlZUxb968fM/mt3LlSvTv3x9dunSROf4oICAAzs7OaNKkibBERkZi/fr16NKli0xbw4cPx99//y0zg7Zs2TL069cPPXr0kClR3LJlC5o3b44WLVoIS2RkJDZt2vRFJ/koTEV5X2QGM5hRPpT18U3l9RioQmegTExM8ODBA1StWhWPHz+GRCJBeHi4cH2Mhw8fytSJFtXw4cMxbdo01KtXD05OTtizZw9iY2Ph4eFRLO0zgxnFkZGWloaIiAgAuV8ko6Oj8ejRI1SqVAmmpqZwdHSEr68vtLS0YGpqirCwMPz111/43//+l2978+bNQ+/evTFu3DgkJiYKr6e0tDSkpaUByD2Tpbm5uXBtHCsrKyQnJyMuLk74laxv3754+vQp3r17hwYNGmD27NnYvn07nj9/jvXr12PIkCFwc3ODWCyGiYkJACAlJQWpqanQ1tbGvHnzcOjQIURFRcHa2hqLFy9GbGysUCqWN2tw9uxZxMXFwdLSEt7e3sjIyMCxY8dKJQNAhbkvJZ1x5coVaGpqCtd1UlZWhomJCWxtbZGUlISYmBi0bdsWiYmJiI6Oho2NDX766Sf8/fffwmzRy5cv8fr1a0yZMgXr169HUlISWrVqBWdnZ+E04xoaGjA3NweQ+0FsbGyMGjVqCM/PO3fuwNPTE+np6YiNjYWDgwPatWsnlOhpamrCx8cHWlpaWLRoETQ0NITTqCcnJyMrKwtr1qzBoEGDMGDAACQkJMg8VnFxcTLHJnz48AExMTEyA6GqVauiQ4cOGDlypNT6lStXwt3dHYMHD0ZCQoJw7GBqaipSU1Px9u1bmV+k8zI+HohVqVIFJiYmsLGxAQDUrl0benp6wnuGPMrj+yIzmMEM+pYUehpzHx8fbNu2DZ07d8alS5fg7u6OvXv3YtKkSVBWVsbatWvRs2fPAq9PA8h/GnMg98JlW7duRWxsLGrVqoUZM2bA2dlZ/nvEDGYUY0Z+pzG/desWJkyYILO+a9eumDNnDuLj4+Hr64tr164hKSkJpqam6NmzJwYNGpTvLymVK1fON3vdunXC6ZHd3NywfPnyz+4zZcoUuLm5QU9PD2/evMGePXuEEqWCDvhfsGABFi5cCA0NDRw+fBgNGjSAvr4+oqKicOHCBcydO1f44mdpaQl/f384OTlBX18fMTExuHTpEnx8fBAeHg6JRFLiGQBKJaciZOjr68PR0REbN26UyTh+/DgWL16M/v37Y9CgQahcuTLi4+Px119/Yfv27VLHBVlaWmLcuHGoX78+NDU1ERERgb179wrXNWvZsmW+z80zZ85gzZo1MDAwgKenJxwdHaGrq4vY2FicOnUKhw4dApB72vX8bg/kXmz4v//+kzpV+cd8fHywePHifLc9fPgw39OYz549G+PGjUONGjWkjhH79Pi6PEuXLi2wVPHOnTsypzGfPn06ZsyYIbPvuHHjCjxte34U+X2RGcxgRsHK22nMv//++7LuQqF27txZ1l2QUegAKjs7G2vWrMH169fRrFkz/PTTTzh48CDmzZuHtLQ0dO7cGb/88gu0tbULbONLBlBEiqSw60AVB3kPfP8aX1sWSOVPaTyvAEhdB6qkfHodqJLw6ZkNS0J5+2JFRF+uvL3Ohw0bVtZdKNSOHTvKugsyCi3hU1ZWlrloWN++fdG3b98S6xQREREREZEiUpgL6RIRERERESm6QmegiIiIiIio4lHUs9wpOs5AERERERERyYkDKCIiIiIiIjmxhI+IiIiI6BvEEr6i4QwUERERERGRnDiAIiIiIiIikhNL+IiIiIiIvkEs4SsaDqCIPqNy5colnvHLL7+UeMaxY8dKPMPR0bHEMyZNmlTiGaWhQYMGJZ5x5syZEs8AAG1t7RLPuHfvXoln/PrrryWeQUREFQNL+IiIiIiIiOTEARQREREREZGcWMJHRERERPQN4jFQRcMZKCIiIiIiIjlxAEVERERERCQnlvAREREREX2DWMJXNJyBIiIiIiIikhMHUERERERERHJSuBK+wMBAbN26FXFxcbC1tcXMmTPRqFEjZjDjm8rIzs7GmTNnEBYWhuTkZOjq6sLR0RHt27eHSCQCAOTk5CA4OBjXrl1Deno6qlWrhl69esHU1DTfNm1tbdGpUydYWVnBwMAA27ZtQ0hIiLB9+PDhcHFxkbrN06dPsXTpUql11atXR58+fVCjRg0AQEREBDZs2AAAMDMzg6OjI4yNjaGjo4OzZ8/i4cOHUrd3dnaGvb091NXVERMTg7///hvv3r0DAJibm6NPnz759v/kyZMAAG9vb/Tp0we1a9dGRkYGrl27hpkzZ0pdbHXbtm0YNmyY1O1DQ0Ol7p+/vz/atm0Lc3NzpKSk4OrVq5gxYwYePnxY4hl5j3fbtm1hZWWFDx8+4L///sOGDRvw9OlTqTZHjx4NNzc36Orq4u7du1i+fDmePXsmbD969CjMzc2lbvPbb7/l+xgCwM2bN/H777/jwYMHiIuLw/z589GzZ09h+9mzZ3Hw4EE8fPgQCQkJCAgIKLbXSkm9Dg8ePIjAwEB06dIFo0aNAgDs3r0bV69exdu3b6GiooIaNWpg4MCBsLOzy7cNW1tbdOzYEdWqVYOBgQG2b9+Oq1evCts9PT3RvHlzqds8e/YMy5Yty7e9SZMm4bvvvoOfnx9u3br1xfepvL1nMYMZzCifWMJXNAo1A3XixAksWbIEY8eORVBQEBwdHTFq1ChERkYygxnfVMaFCxdw9epV9OzZE5MnT0bPnj1x9epVnD9/Xtjn4sWL+Pvvv9GrVy9MnDgR2tra2LJlCzIyMvJtU0NDA2/evMHevXsL3Of+/fvw8vISlnXr1kltr169On7++WeEh4djyZIlWLRoEU6fPg2JRAIAUFNTw7t373D58mV8+PBBpn1HR0c0aNAAf//9N/bv34/09HT07NkTqqqqAIDo6Ghs375darl58yYyMzPx6tUrAECbNm3g5+eHFi1aoH379sjKysLp06dhYGAglRUcHAxzc3Nh6d69u9T2mzdvYsSIEbC3t0eXLl2gpKSE06dPQ0VFpVQyGjZsiP3792PEiBEYO3YsJBIJNm3ahEqVKgm3HzZsGIYMGYIVK1bg+++/h1gsxqZNm6ClpSWVExAQgI4dOwrLli1b8v3/CwDp6emwsbHB1KlToaGhke/2+vXrw8vLq8A2iqKkXofh4eE4c+YMrKyspNZbWFhg1KhRWLNmDRYvXowqVapg0aJFSEhIyLcddXV1vHnzBvv27UNmZma++9y/fx9TpkwRlk9fH3k6dOiAnJycIt+n8viexQxmMIO+JQo1gNq+fTv69OmDAQMGwMbGBnPmzIGxsTH27NnDDGZ8UxkvX75EnTp1ULduXVSuXBl169ZFnTp18Pr1awC5s0+XL19G27Zt4eDgAFNTU7i7uyMjIwNhYWH5tvnff//h8OHDuHnzZoFf7j58+ICkpCRhSU1Nldru7u6O8+fP4/jx44iMjERMTAxu3bqF9PR0od+hoaEysyh56tevj1u3buHZs2d49+4dgoODoaqqilq1agHInXlLS0uTWmxsbPD48WNhQNalSxf89ttvuHfvHu7evYvvv/8exsbGMrNnGRkZiImJERaxWCy1PSAgAJcvX8bLly8RFhaGOXPmwMLCAjVq1CjxDAsLC/zvf//D0aNH8fTpUzx58gRz5syBgYEB6tevL9x+0KBB+O2333Du3Dk8ffoU8+bNg5aWFjp37iyVk5aWhvj4eGHJ+/+RnxYtWmDixIlo3759vr88du/eHWPGjJG5r1+rJF6HqampWLt2LSZMmAAdHR2pba1bt0a9evVgamqKatWqYfjw4UhPT8fz58/zbevu3bsICgrCrVu3kJ2dne8+WVlZUq+PtLQ0mX2srKzQrl27z84CFqY8vmcxgxnMoG+JwgygMjMzce/ePZkPbRcXlwK/EDKDGRU1w9raGk+fPkVsbCwAICYmBk+fPhXKj969e4fk5GTY2toKt1FVVUWNGjXw8uXLIt6T3DKm1atXw8fHB99//z10dXWFbbq6uqhZsyYSEhLg7e2N1atXY9q0aQWWRH2qUqVK0NbWFgaBACCRSBAZGVlg2aG5uTn09fWlSuc+paurC5FIJDN4cXFxQVRUFB48eAB/f38YGxsX2IaWlhY8PT3x8uVLvHjxosQz8vsVU1tbGyKRCMnJyQByZ1CMjIwQGhoq7JM3QP54kAUAQ4YMwdmzZ7F7926MGDECKiqKVZ1dUq9DX19fNGvWDA4ODp/d78OHDzh9+jS0tLRQvXr1IufVrFkTK1euxKJFizB06FCp1weQO4s1cuRI7Nq1S/j/+KXK63sWM5jBjPJJSUlJ4RdFJNcAKjo6GosXL0aPHj3QuHFjNG3aFO7u7ti5c6dQuvO1xGIxJBIJjIyMpNYbGhoiLi6OGcz4pjLatGkDJycnrF69GjNmzMDq1avRsGFDNGvWDACEL2ef/uquo6NT5C9ud+/exdatW7Fq1Srs378f1atXx5QpU4Qv43mDg169euHy5ctYs2YNHj9+jJ9//hmWlpaFtp9Xdvbpr/bp6ekyJWl57O3tERcX99nHce3atQgLC5M6XuXUqVPw9PREhw4dMHXqVDg7OyM4OBhqampStx07diwSExORnJyMzp07o0OHDvmWbxV3Rn7ljVOmTMHDhw9x584dALnPHwDC8WF54uPjhW0AsHfvXsyaNQtjxozBH3/8gcGDBwvHWSmKkniNnDlzBtHR0Rg0aFCB+9y4cQODBg2Ch4cHjh07hnnz5kFfX79Ieffu3cP27duxZs0a7N+/H9bW1vDy8pIarA4ZMkSYtSyq8vqexQxmMIO+JYX+TBkWFoZevXqhRo0a0NTUxNOnT9GvXz98+PABc+bMQWBgIA4cOCDzSxwRFd2///6LW7duwcPDAyYmJoiKisKff/4JAwMDNG7cuEQy//nnH+Hfb968wYsXL7B8+XLUq1cPt27dEn4FunjxIq5cuQIAeP36Nezs7NCmTZvPzhIVhbq6OmrUqCFk5WflypVwcXFBq1atpMqu9u3bJ/z77t27uHnzJp4/f45u3brh8OHDwrbdu3cjODgYZmZmmDx5Mvbt24eWLVtKlcCVRMb//vc/vH//Xtjn559/RoMGDfDDDz8UWD5WkMDAQOHfT548QWpqKpYtWyZTflmRvHnzBoGBgVi8ePFnZ9u+++47rFq1CklJSQgODsbKlSuxdOlSVK5c+YszP319vHz5EsuWLYODgwPCwsLQtGlTWFpaYvHixUW6T0REVH4UOoCaMWMGxo8fj+nTpwPI/dKwefNmBAcHIyEhAT169ICPjw+WL1/+VR0xMDCASCTC27dvpdbHx8d/tiyGGcyoiBknTpxAq1at0KBBAwC5Z7cTi8W4cOECGjduLPxgkZKSInVig5SUlGL7MSMxMRFisRhVqlQR/gaAqKgoqf0iIyPl+kKaN/OkpaWFlJQUYb2mpma+x5LY2dkhJycHjx49yre9VatWwd3dHe3atSvwuJY8UVFRiIiIQM2aNaXW5x3L8uTJE4SGhiI+Ph59+/bFrl27SjTD1dUVJ06cAAB4eXmhU6dOGDNmDN68eSPcLj4+HgBQuXJlREdHC+sNDQ2Fbfn577//AADKyspfPBgrKcX9GgkPD0dSUhJ+/PFHYV12djbu37+PU6dOYc+ePVBVVYWGhgbMzMxgZmaG2rVrY8KECQgODsaAAQO++j59+vqws7ODmZkZ1q9fL7Xf6NGj8ezZM6xYsUKudsvrexYzmMGM8klRS+QUXaElfP/++y88PDyEv/v3749///0XsbGx0NfXx8KFC/Hnn39+dUfU1NRgb28vdVplAAgJCYGjo+NXt88MZpSnjA8fPkBZWfrlqaysLJz8oXLlytDV1cXjx4+lbvP8+XOZs5EVlY6ODgwMDISB09u3byEWi2FiYiK1n4mJyWe/0OfJOylF1apVhXUikQjm5uZSA4Q8devWxZMnT/ItqVuzZg08PDzQvn17hIeHF5ptaGgICwuLfHPy5NVaq6url3hGXpnflClThMHTp8devXnzBm/fvkWTJk2EdWpqamjQoAH+/fffAjNq164NAF91FrjiVtyvkSZNmmDNmjVYtWqVsNjY2KBFixZYtWpVgbNS2dnZyMrKKtJ9+JSOjg709fWF10dQUBAWLlyIRYsWCQsAHDhwANu2bZO73fL6nsUMZjCDviWFzkAZGRkhMjIS1tbWAHIPZs/KyhJ+5a5Ro4bMgdVFNXz4cEybNg316tWDk5MT9uzZg9jYWKkBHDOY8S1k1KlTB+fPn4eBgQFMTEwQGRmJS5cuwcnJCUDuF/EWLVrg3LlzqFKlCoyMjHD27FmoqakV+Aavrq4u/FqupKSEypUro2rVqkhNTUVqaip69uyJmzdvIjExEUZGRnBzc0NSUpLUNWxOnTqFnj17IiIiAq9fv0ajRo1Qo0YN7N69G8bGxlBVVYWenp6wv46ODoyMjPD+/XukpKTg33//RcOGDSEWi5GQkIBGjRrhw4cPMrNMZmZmqFy5stRp2/OsX78eQ4YMgZubm9SALiUlBampqdDW1sa8efNw6NAhREVFwdraGosXL0ZsbKxQWmdjYwM3NzecPXsWcXFxsLS0hLe3NzIyMnDs2LESz7h06RK8vb3RtWtXTJkyBcnJycJxTWlpaUIJYd5JIV68eIFXr17hhx9+QHp6unBNLAcHBzg4OODGjRtISUmBvb09vLy8cOHCBTg7O+f7PEhLS5M6m2N0dDTCw8NRqVIlmJmZITExEdHR0cKxdK9fv4auri4MDQ1ljgn4EsX5GtHW1oa2trbUOg0NDejo6MDKygppaWkICgpCo0aNYGBggKSkJPz111+Ij4+XuZZTHnV1deHXZWVlZVSuXBmWlpZIS0tDamoqevTogVu3biExMRGGhobo06cPkpOThYPKExIS8j1F+rt372R+yS5MeXzPYgYzmEHfkkIHUN26dYOXlxfmz58PdXV1/PLLL3BxcYGmpiYA4PHjxzAzMyuWznTt2hVisRi+vr6IjY1FrVq1EBAQAAsLi2JpnxnMKC8ZvXr1wqlTpxAUFISUlBRUqlQJjRs3Rrt27YR9WrdujQ8fPiAoKAjp6emoWrUqRo4cKcygfMra2hpTp04V/u7duzd69+6NK1euYNeuXbCwsECzZs2gpaWFxMREPHz4EH5+flLXjAoODoaKigoGDBgAHR0dREZG4tdff0VERASMjY1hbGwsdSHcJk2aoEmTJnjw4AHOnTuHsLAwqKiooFWrVsKFdP/880+ZkyrUrVsX7969y3c2Z/z48UJfPrZgwQIsXLgQEokEDg4OGDp0KPT19REVFYULFy7Aw8NDKB3MyMhAmzZt4OXlBX19fcTExODSpUtwcXFBTExMiWdoamoKZWR+fn5SGf7+/ggICAAA7NixA+rq6pg+fbpwId0JEyYIJY8fPnxAx44dMXr0aKiqqiI6OhqHDx/Gzp07cfr06XyfB/fv38fo0aOFv/38/ODn54cePXpgwYIFuHjxIubPny9sz5tJGT16NMaOHZtvm/IojddhHpFIhFevXuHs2bPChahr1qwJHx8f4cfAT1lZWWHKlCnC37169UKvXr0QEhKCwMBAWFhYoGnTpsLrIzw8HAEBAQVeU+1rlMf3LGYwgxnlE0v4ikYpISHhs3UeKSkpmDhxIo4ePQqJRILGjRvD399f+BA6d+4ckpKS0Lt37wLb+PgXaSKSFhQUVOIZx44dK/GM0ihtmDRpUolnlIa8Y9tK0t9//13iGQBkZoJKQnGfoCQ/v/76a4ln5A2MiajiyivrLS++5oex0vLpD42KoNAZKB0dHWzfvh3v379HVlaWzGmTXV1dS6xzREREREREikTuqy1qaGiUZD+IiIiIiIgUnmJdrp6IiIiIiEoFj4EqmkJPY05ERERERES5OIAiIiIiIiKSE0v4iIiIiIi+QSzhKxrOQBEREREREcmJAygiIiIiIiI5sYSPiIiIiOgbxBK+ouEAiqiM9e7du8QzSuOC17q6uiWe8e+//5Z4xtatW0s8Y/LkySWeoa2tXeIZpcXe3r7EMwICAko8g4iIKgaW8BEREREREcmJM1BERERERN8glvAVDWegiIiIiIiI5MQBFBERERERkZxYwkdERERE9A1iCV/RcAaKiIiIiIhIThxAERERERERyYkDKCIiIiIiIjkp3AAqMDAQrq6ucHBwgJubG27cuMEMZjCjBDJu3boFLy8vdO3aFc7Ozjh69GiB+y5ZsgTOzs74/fffi5yX559//sG4cePQqlUr2NnZ4dChQ190e1tbW0yYMAHLly9HQEAAmjVrJrXd09MTAQEBUsv06dMLbG/SpEkICAiAk5OTsM7b2xuhoaEQi8WIjo7GkSNHZC7mum3bNkgkEqnlypUrUvv4+/vj0aNHSElJQXR0NA4fPgw7O7sC+6KiogInJyf06tULAwYMQIcOHVC5cmWpfRwcHNC7d28MGDAA7dq1g56eXqGPmTzK2/OXGcxgBjPKe4YiUFJSUvhFEck9gEpNTcWOHTswfvx49OvXD/369cP48eOxc+dOpKamFktnTpw4gSVLlmDs2LEICgqCo6MjRo0ahcjIyGJpnxnMYMb/SU9Ph42NDSZPngx1dfUC9zt79izu3bsHY2PjonZdSlpaGmxtbTFz5kxoaGh88e3V1dXx5s0b7Nu3D5mZmfnuc//+fUyZMkVY1q1bl+9+HTp0QE5Ojsz6Nm3awM/PDy1atED79u2RlZWF06dPw8DAQGq/4OBgmJubC0v37t2ltt+8eRMjRoyAvb09unTpAiUlJZw+fbrAD4QmTZrAzMwMV69exYkTJxAdHQ1XV1doamoCAOrUqQM7OzvcvHkTp06dwvv379G2bVuoqHzd+YDK4/OXGcxgBjPKcwaVb3INoB4+fIhGjRph9uzZiI+Ph6mpKUxNTREfH4/Zs2fD2dkZDx8+/OrObN++HX369MGAAQNgY2ODOXPmwNjYGHv27PnqtpnBDGZIc3FxwYQJE9CuXTsoK+f/VhAVFYVVq1bBx8fnq7+k52ndujW8vLzQuXPnAnM/5+7duwgKCsKtW7eQnZ2d7z5ZWVlISkoSlrS0NJl9rKys0K5dO/z2228y27p06YLffvsN9+7dw927d/H999/D2NgYLi4uUvtlZGQgJiZGWMRisdT2gIAAXL58GS9fvkRYWBjmzJkDCwsL6OjoyGSKRCJUrVoVt2/fRmxsLFJSUvDff/8hJSUFtra2AAA7Ozvcv38fr1+/RmJiIkJDQ6Gqqgpra2s5H738lcfnLzOYwQxmlOcMKt/k+vYyZcoUNG3aFI8fP8a+ffuwYcMGbNiwAfv27cOjR4/QtGlTTJky5as6kpmZiXv37sl8QXFxcUFYWNhXtc0MZjDjy2VlZWHWrFkYMWIEqlevXiIZJaVmzZpYuXIlFi1ahKFDh0JXV1dqu7q6OkaOHIldu3YhOTm50PZ0dXUhEolkBkguLi6IiorCgwcP4O/v/9lZOi0tLXh6euLly5f5ztorKSlBWVlZZlCYlZUFY2NjaGtrQ1NTE1FRUcI2iUSC2NhYGBkZFXofClJRnr/MYAYzmFFeMhRJWZfnVegSvps3b8Lb2zvfchsNDQ1MmTIFN2/e/KqOiMViSCQSmS8ChoaGiIuL+6q2mcEMZny5gIAA6Ovro1+/fiXSfkm5d+8etm/fjjVr1mD//v2wtraGl5eX1AzakCFDhNkleaxduxZhYWG4evWqsO7UqVPw9PREhw4dMHXqVDg7OyM4OBhqampStx07diwSExORnJyMzp07o0OHDvnOnGVlZSEuLg729vbQ1NSEkpISrK2tYWRkBE1NTaGM7/3791K3e//+vbCtKCrK85cZzGAGM8pLBpV/ctXk6Ovr48mTJwUe/Pz06VPo6+sXZ7+IqAzdvHkTx44dQ2BgYFl35Yv9888/wr/fvHmDly9fYtmyZXBwcEBYWBiaNm0KS0tLLF68WK72Vq5cCRcXF7Rq1Upq4LNv3z7h33fv3sXNmzfx/PlzdOvWDYcPHxa27d69G8HBwTAzM8PkyZOFmXuJRCKTdfXqVTRp0gR9+vRBdnY2xGIxXr58KXMiCSIiIio7cg2gvv/+e4wfPx6PHz9G27ZthTKVuLg4nD9/HmvXrsX48eO/qiMGBgYQiUR4+/at1Pr4+PhiO3idGcxghnxu3ryJt2/fokuXLsI6iUSCDRs2YO/evTh+/HixZ5aUxMREiMViVKlSBUDucURmZmZYv3691H6jR4/Gs2fPsHXrVmHdqlWr4O7ujnbt2uH58+efzYmKikJERARq1qwptT7vOKwnT54gNDQU8fHxSE9Px4sXL2TaSElJwdmzZyESiaCqqor379/DxcUFKSkpSE9PB5A76//xMV0aGhrCtqKoKM9fZjCDGcwoLxmKRFFL5BSdXCV8M2bMgJeXF/z9/dG2bVs4ODjAwcEBbdu2hb+/P7y8vODt7f1VHVFTU4O9vT1CQkKk1oeEhMDR0fGr2mYGM5jxZfr164fdu3dj165dwmJsbIyBAwdi48aNxZ5XknR0dKCvr4/ExEQAQFBQEBYuXIhFixYJCwAcOHAA27ZtE263Zs0aeHh4oH379ggPDy80x9DQEBYWFoiOji5wn7x6bpFI9Nm2JBIJ3r9/D1VVVZiZmSEiIgKpqalIT0+HqampsJ+ysjKqVKki80H/JSrK85cZzGAGM8pLBpV/cp9W66effsJPP/2EFy9eIDY2FgBQpUqVrz7708eGDx+OadOmoV69enBycsKePXsQGxsLDw8PZjCDGcWckZaWhtevXwMAsrOzER0djfDwcOjp6cHU1FSmbExFRQWGhoZf/ZpPTU3Fq1evhNy8kzDo6enB3Ny80Nurq6sLvwIqKyujcuXKsLS0RFpaGlJTU9GjRw/cunULiYmJMDQ0RJ8+fZCcnCwc/JuQkICEhASZdt+9eycMRNavX48hQ4bAzc0NYrEYJiYmAHJniFJTU6GtrY158+bh0KFDiIqKgrW1NRYvXozY2FihfM/GxgZubm44e/Ys4uLiYGlpCW9vb2RkZODNmzf53jczMzMAubNWurq6cHR0RFJSEp49ewYg94yo9vb2SEpKQnJyMr777jt8+PAh39msL1Een7/MYAYzmFGeM6h8++LzEltbW8t8gYqIiMDSpUu/+pfprl27QiwWw9fXF7GxsahVqxYCAgJgYWHxVe0ygxnMkPXgwQOMHTtW+DvvorPdunXD/Pnzi6nXsu7evYthw4YJf69fvx7r169H7969sWzZskJvb2VlJXXWz169eqFXr14ICQlBYGAgLCws0LRpU2hpaSExMRHh4eEICAhARkaG3H3MK0kODg6WWr9gwQIsXLgQEokEDg4OGDp0KPT19REVFYULFy7Aw8MDKSkpAHJPcd6mTRt4eXlBX18fMTExuHTpElxcXDB79ux8c1VVVVG/fn1oaWkhMzMTr1+/xr///itcq+rBgwdQUVGBs7Mz1NTU8PbtW5w/fx5ZWVly37f8lMfnLzOYwQxmlOcMRcESvqJRSkhIkL2K5Bf677//0Lp1a7x79y7f7Xp6el8bQURfISkpqcQzPj1VeEkYM2ZMiWd8fAxUSfn9999LPGPQoEElnkFERNLyysXLi59//rmsu1CoNWvWlHUXZMg1A1XYhcMiIiKKpTNERERERESKTK4B1Pjx46GlpVXgNF9+1zQhIiIiIiLFxRK+opFrAGVmZoZly5ahZ8+e+W6/c+cO2rRpU5z9IiIiIiIiUjhynca8fv36uHPnToHblZSUhIOciYiIiIiIKiq5ZqAmTpyI1NTUArfXqFEDR48eLbZOERERERERKSK5BlDNmzf/7HZtbW20aNGiWDpEREREREQlj8dAFY1cJXxERERERETEARQREREREZHc5CrhIyIiIiKiioUlfEXDGSgiIiIiIiI5cQaK6BtQqVKlsu5CsdDT0yvrLhSLLVu2lHiGh4dHiWcAgLIyf4cjIqJvCwdQRERERETfIJbwFQ1/OiQiIiIiIpITB1BERERERERyYgkfEREREdE3iCV8RcMZKCIiIiIiIjlxAEVERERERCQnlvAREREREX2DWMJXNJyBIiIiIiIiklOxDKBiY2OxfPny4mgKgYGBcHV1hYODA9zc3HDjxo1iaZcZzGBGxcioXr06PD09MXv2bPzyyy9o1KiR1PZOnTph6tSpWLx4MRYsWIDRo0fDyspKah9DQ0MMGzYM8+bNw6JFizBkyBDo6OgI2729vREaGgqxWIzo6GgcOXIE9vb2Um1s27YNEolEarly5YrUPv7+/nj06BFSUlIQHR2Nw4cPw87ODgBQr149+Pj44I8//sC5c+fQqVMnqdsaGBhg2rRp+OOPP3DixAksW7YMFhYWUvuoqqpi4sSJOHz4MI4fPw4fHx8YGRnJ/VgCQEBAAPr3749GjRqhefPmGDduHB49evRFbchL0Z9bzGAGM5hRmhlUfhXLAComJqZYBlAnTpzAkiVLMHbsWAQFBcHR0RGjRo1CZGRkMfSSGcxgRkXIUFdXFwY1mZmZMtvj4uJw+PBhrFq1Cps2bcK7d+8wcuRIYYCkqqqKUaNGAcgd4GzcuBEikQjDhw8XShnatGkDPz8/tGjRAu3bt0dWVhZOnz4NAwMDqazg4GCYm5sLS/fu3aW237x5E/+PvTuPqzH9/zj+yqm0KKUsxWBkT3ZjRpaG7IRsMZYwSMZ3ZhiMGQYhMZGdbGPGYBgjxjIk2xjLmCGyZzdpVac90fL7w8P9c6btUFHN5/l4nMdD13Xf1/s6Oae6znXd1z1y5EhsbW3p2rUrOjo6+Pv7o1KpMDQ05N69e6xYsYInT55keR4eHh5UqVKFb775hrFjxxIREYG3tzcGBgbKMePHj6dNmzbMnTuXzz77DCMjIzw9PSlVSvsf7efOnWPQoEFs3bqVTZs2oVKpGDVqFLGxsVq3oY3i8NqSDMmQDMl4UxmieNOJjY3NzOugf3+q+m937tzhs88+IyYmJtv6smXLatWZ/v37U6dOHebOnauUderUic6dOzNp0iSt2pAMyZCMkpsxefJkja/nzp3L7t27c/1ksHTp0sydO5d169YRHBxM7dq1GTVqFLNmzSIlJQUAAwMDZs+ezfr16xk3blyWNoyNjVGr1Tg7O7Nv3z7g+QyUpaUlTk5OWj93Ozs7Ll68yPDhw/nnn3+U8v3797Ns2TIOHToEQJUqVfjhhx/4+OOPuXv3LvB8nfrOnTvZsGEDBw4cwNjYmF27drFw4UKOHDkCQPny5dm2bRtffvklXl5eWvfrZUlJSbz33nusWLGCDz/8MM/jtR2sFfXXlmRIhmRIRkFkxMXFFUgf3pQvv/zybXchT9n9Pjt16hTLly/n0qVLhIWFsXLlSj766COlfty4cWzbtk3jnObNmxMQEKB8nZqayvTp0/nll1948uQJbdu2ZdGiRVlWe2RHq998PXr0oGfPnvTo0SPbx6effqpNM7l6+vQpV69exd7eXqPc3t6ewMDAfLcvGZIhGf+NjJepVCref/99UlJSlE8OVSoVAM+ePVOOe/bsGZmZmVSvXj3bdkxMTFCpVKjV6iz9DgsL4/r16/j6+lK+fPkc+2JkZISrqysPHjwgPDw8137r6ell6WNmZibPnj2jQYMGANSuXRs9PT2NwWNUVBQPHz7MstzwVSQlJZGRkYGpqelrt/FvJeW1JRmSIRmSIYqGpKQk6tevj5eXF4aGhtke4+DgwM2bN5XHzz//rFE/bdo09u7dq3wwmZCQwMCBA0lPT88zX6sBlIWFBWvWrOHOnTvZPn799VdtmsmVWq0mPT09y/p9CwsLoqKi8t2+ZEiGZPw3MgDq1avH3Llz8fT0pE2bNqxbt47ExEQAHj58SGpqKj169EBPTw89PT169OiBSqXKcdCwZMkSAgMDOXPmjFJ26NAhXF1d6dixI5MnT6ZFixYEBASgr6+vca6bmxtxcXEkJCTQpUsXOnbsqDEwys7Dhw+JiIhg1KhRmJiYoKuri4uLCxUqVMDCwgJ4fo1Uenp6lk871Wo15cqVe+Xv2Qvz58+nXr16NG7c+LXb+LeS8tqSDMmQDMkQRUOnTp345ptv6NWrV44rIUqXLk3FihWVx8vL8OPi4ti8eTMeHh58+OGHNG7cGF9fX65evcrx48fzzNdqG/NGjRpx//79HH8pm5mZkZmZ50pAIYR4I27fvo2Pjw/Gxsa0bNmSIUOGsGLFChISEkhKSuLHH3/E2dmZDz74gMzMTC5evEhISEi2P8e8vb2xt7enbdu2ZGRkKOXbt29X/n3lyhXOnz/PvXv36N69O35+fkrd1q1bCQgIwMrKikmTJrF9+3a++uorUlNTc+x/eno633zzDZMnT2bPnj2kp6dz/vx5/vzzzwL6DmXPy8uL8+fPs2XLFmWmTgghRMlVkrcxP3PmDDVr1qRs2bLY29szY8YMZaXIxYsXefbsGe3bt1eOr1KlCnXq1OHPP/+kQ4cOubat1QDK1dWV5OTkHOvfeecdVq5cqU1TOTI3N0elUvH48WON8ujo6FyXxUiGZEiGZPzbs2fPiI6OJjo6mocPHzJlyhRatmyprH0ODg7Gy8sLIyMjMjIyePLkCd988w0XL17UaGfRokUMHDiQDh06cO/evVwzw8LCCAkJoWbNmhrl8fHxxMfHc/v2bc6ePUt0dDRt27bl8OHDubZ369YtxowZg7GxMbq6usTFxbFy5Upu3rwJPP+UVKVSUbZsWY1ZKHNzc4KCgrT9Vinmz5/PgQMH+P7773nnnXde+fzclJTXlmRIhmRIhigeHB0d6dmzJ9WqVePhw4fMnTsXJycnjh8/TunSpYmMjESlUimrOl4oX748kZGRebav1RK+nj17MnDgwBzrzczMGDx4sDZN5UhfXx9bW1tOnz6tUX769GmaNGmSr7YlQzIk47+TkZ1SpUplO6OSnJzMkydPsLGxwdjYmGvXril1Pj4+uLi44OjoqAxacmNhYUHlypVzvb5JR0cHHR0d5RonbSQlJREXF0flypWpXbu28r0LDg7m2bNnNGvWTDnW0tKSqlWrcvXqVa3bB/D09OTAgQNs2rSJGjVqvNK52igpry3JkAzJkAxRPPTt25du3bopu+Du3LmTW7duKZs15ZdWM1B5CQkJYf78+fmehRoxYgRTpkyhYcOGNG3alG3bthEZGYmLi0tBdFMyJEMySkCGvr6+sjZdR0cHMzMzrK2tSU5OJiUlBQcHB65du0ZCQgLGxsa0atWKsmXLaszKNG/enKioKBITE6lWrRpOTk6cPHlSWd++fPlyhgwZgrOzM2q1mooVKwKQmJhIUlISxsbGzJw5k127dhEWFkb16tWZN28ekZGRyvI9GxsbnJ2dOXLkCFFRUVSpUoWpU6eSmprKmTNnMDAwUHb60dHRoUKFCtjY2JCQkEBkZCTt2rUjLi6OiIgI3n33XT755BNOnTqlbBqRlJTEb7/9xtixY4mNjSU+Pp5x48Zx9+5dLly4oPX/h4eHB7/++isrVqzA1NRU+R4YGRlhbGysdTt5KQ6vLcmQDMmQjDeVUVSU5CV8L7OyssLa2lrZ2bZChQqkp6cTHR2tcb1bVFQUH3zwQZ7tFcgASq1Ws23btnwPoLp164ZarWb16tVERkZSu3Zt1q5dq9V2gpIhGZLx38ioUqWKxlbjnTt3pnPnzvz999/s2rWLSpUq0aJFC4yNjUlKSiIkJIRVq1YRFhamnFO+fHm6deuGoaEharWao0eP8vvvvyv17u7uABrbnQLMnj0bDw8P0tPTsbOzY+jQoZiZmREWFsbx48dxcXFRNqtITU3FwcGBiRMnYmZmRkREBCdPnsTe3p5KlSrRqFEjfHx8lLZHjBjBiBEjOHjwIAsXLqRcuXKMGzcOc3NzYmJi8Pf3Z/PmzRr9WblyJenp6cyYMYPSpUsTGBiIl5eXxrVaeXmxzeuIESM0ysePH88nn3yidTt5KQ6vLcmQDMmQjDeVId6s6OhowsLClA9EGzdujJ6eHseOHaN///4APHr0iJs3b9KyZcs829PqPlD/3kf9317MQOX3PlBCCJGbf98HqjAsXry40DPatWtX6Bn/HvwVlle5aa8QQpR0xe0+UF999dXb7kKePD09s5QlJiYqs0mdO3fms88+o2vXrpibm2Nubo6XlxdOTk5UrFiRhw8f4uHhwaNHj/jzzz8xMTEBYOLEiRw8eJBVq1Zhbm7O119/TWxsLCdOnMhzIyWtZqDc3d0xMjLKcZrvVT7tFEIIIYQQQrx9xXUJX2BgID179lS+nj9/PvPnz2fQoEEsXryYa9eu8dNPPxEXF0fFihVp06YN3333nTJ4enGOSqVixIgRyo1016xZo9UutFoNoKysrJSRXHaCgoJwcHDQpikhhBBCCCGEeG1t2rQhNjY2x/pdu3bl2Ubp0qX59ttv+fbbb185X6u1F40aNcp1W1wdHR25D5QQQgghhBCixNNqBmrChAkkJSXlWF+jRg327t1bYJ0SQgghhBBCFK7iuoTvbdNqANWqVatc642NjWndunWBdEgIIYQQQgghiirZPkkIIYQQQgghtFQg94ESQgghhBBCFC+yhO/1yAyUEEIIIYQQQmhJBlBCCCGEEEIIoSVZwieEKDZmzZpV6Bnnz58v9IwTJ04UekZAQEChZwB06tTpjeQIIYQQRYUMoIQQQgghhPgPkmugXo8s4RNCCCGEEEIILckASgghhBBCCCG0JEv4hBBCCCGE+A+SJXyvR2aghBBCCCGEEEJLMoASQgghhBBCCC3JEj4hhBBCCCH+g2QJ3+uRGSghhBBCCCGE0FKRG0Bt2bKF9u3bY2dnh7OzM3///bdkSIZkSEauzp8/z2effUbnzp1p2rQpv/76q0b9kSNHcHd3p3379jRt2jTPvIYNGzJ37lx27NjB0aNH6dy5s0a9ubk5U6ZMYceOHRw4cAAvLy8qV66scYyenh4TJkzAz8+P/fv3M3fuXCwtLZX6qVOncvbsWdRqNeHh4ezZswdbW1uNNjZu3Eh6errG49SpUxrH+Pr6EhwcTGJiIuHh4fj5+VG3bt1sn9fMmTOZMGFClsfq1auVY37//XdmzpzJ559/zsKFC7l9+3au36tXURxfW5IhGZIhGYWVIYovrQdQGRkZXL9+nbCwsCx1T548Ydu2bfnuzIEDB/D09MTNzY3du3fTpEkTRo8eTWhoaL7blgzJkIySm5GSkoKNjQ2TJ0/GwMAg2/pGjRoxceJErdozNDTk3r17rFixgidPnmSp9/DwoEqVKnzzzTeMHTuWiIgIvL29NbLHjx9PmzZtmDt3Lp999hlGRkZ4enpSqtTzH7sODg6sWbOG1q1b4+joSFpaGv7+/pibm2tkBQQEYG1trTx69OihUX/+/HlGjhyJra0tXbt2RUdHB39//2yXZXzxxRfMmzdPeUyZMgUdHR2aNm2qtPXLL7/QqVMnpk6dyrvvvsvq1auJiYnR6vuWm+L62pIMyZAMySiMjKJCR0enyD+KIp3Y2NjMvA4KCQmhf//+3LhxAx0dHbp27crKlSsxMzMDIDIykrp16+b4S7Zs2bJadaZ///7UqVOHuXPnKmWdOnWic+fOTJo0Sas2JEMyJKPkZiQlJeXZvr29PVOnTsXJySlLnVqtpkOHDqxdu5bmzZtne37Pnj01vt6/fz/Lli3j0KFDAFSpUoUffviBjz/+mLt37wLPfwHt3LmTDRs2cODAAYyNjdm1axcLFy7kyJEjAJQvX55t27bx5ZdfsmjRoiy5xsbGqNVqnJ2d2bdvH/B8BsrS0jLb55ITOzs7Ll68yB9//EFycnKuxx46dIgjR44wd+5c9PX18fb2xtramsGDByvHeHh40Lhx4xz70KlTJ636VdRfW5IhGZIhGQWRERcXVyB9eFNmz579truQp5kzZ77tLmSh1QzU7NmzMTMz4+zZsxw6dIjHjx/TrVs3Hj9+XGAdefr0KVevXsXe3l6j3N7ensDAQMmQDMmQjCJBT08PgGfPnillmZmZPHv2jAYNGgBQu3Zt9PT0NJZ8REVF8fDhwyzL9F4wMTFBpVKhVqs1yu3t7QkLC+P69ev4+vpSvnz5HPtmZGSEq6srDx48ICUlJdfnkZmZyZkzZ2jevDn6+vqkpaXxzz//UK9ePY3j6taty71793JtKy8l5bUlGZIhGZIhBGg5gDp58iSenp7UqVOHFi1asG/fPmrXrk337t2JiooqkI6o1WrS09M1rhEAsLCwkAzJkAzJKDIePnxIREQEo0aNwsTEBF1dXVxcXKhQoQIWFhbA82uk0tPTs3wSqVarKVeuXLbtLlmyhMDAQM6cOaOUHTp0CFdXVzp27MjkyZNp0aIFAQEB6Ovra5zr5uZGXFwcCQkJdOnShY4dO5KZmfvighs3bhAdHU2rVq2A57N7GRkZmJiYaBxnYmJCfHy8dt+cHJSU15ZkSIZkSEZJ87aX5xXXJXxaDaASEhIwNTVVvtbT02PDhg3UrVuX7t27Ex4eXmgdFEKIoiQ9PZ1vvvkGa2tr9uzZw2+//Ubjxo35888/ycjIeK02vb29sbe3p3///hptbN++nb1793LlyhX27dtH9+7dqVOnDt27d9c4f+vWrTRr1gwHBwdu3brF9u3blWutcnL69GmqVq1KlSpVXqvPQgghxH+VVveBql69OleuXMHGxkYpU6lUbNy4EVdXVwYNGpTvjpibm6NSqbIsC4yOjs51yYpkSIZkSMabduvWLcaMGYOxsTG6urrExcWxcuVKbt68CTz/BFOlUlG2bFmNWShzc3OCgoI02lq0aBEDBw6kQ4cOeS6VCwsLIyQkhJo1a2qUx8fHEx8fz+3btzl79izR0dHcvXs3201/4PmHYpcvX6Z///5KmbGxMaVKlSIhISHLsS9/gPY6SsprSzIkQzIkQwjQcgbK0dGR77//Pku5SqXiu+++o1GjRnkuF8mLvr4+tra2nD59WqP89OnTNGnSJF9tS4ZkSMZ/J+NNSkpKIi4ujsqVK1O7dm3leQUHB/Ps2TOaNWumHGtpaUnVqlW5evWqUubj44OLiwuOjo7K4Cs3FhYWVK5cOddZ/xdLHnKbgfrzzz/R1dXV2EhDV1eXd955hxs3bmgce+PGDd599908+5abkvLakgzJkAzJEAK0nIGaMWNGjrs56erqsnnzZh49epTvzowYMYIpU6bQsGFDmjZtyrZt24iMjMTFxSXfbUuGZEhGyc1ITk7mn3/+AZ5vjhAeHs7NmzcxNTXFysqKuLg4wsPDldmVf/75BxMTEywsLLKscwcwMDBQ7uuko6NDhQoVsLGxISEhgcjISNq1a0dcXBwRERG8++67fPLJJ5w6dUrZNCIpKYnffvuNsWPHEhsbS3x8POPGjePu3btcuHABgOXLlzNkyBCcnZ1Rq9VUrFgRgMTERJKSkjA2NmbmzJns2rWLsLAwqlevzrx584iMjMTPzw8AGxsbnJ2dOXLkCFFRUVSpUoWpU6eSmpqa41r9zMxMTp8+TdOmTSldurRG3YcffsjmzZupVq0aNWrU4I8//iAuLo7WrVu/9v/NC8X1tSUZkiEZklEYGUVFUb3GqKjTagClq6ub6xKOsLAwFixYwMqVK/PVmW7duqFWq1m9ejWRkZHUrl2btWvXZrlBpWRIhmRIxsuuXbvGmDFjlK/XrFnDmjVr6NmzJ7Nnz+bEiRPMmjVLqZ8zZw4AY8aMwc3NLUt7derUwcfHR/l6xIgRjBgxgoMHD7Jw4ULKlSvHuHHjMDc3JyYmBn9/fzZv3qzRxsqVK0lPT2fGjBmULl2awMBAvLy8lGuc3N3dgef3eXrZ7Nmz8fDwID09HTs7O4YOHYqZmRlhYWEcP34cFxcXEhMTAUhNTcXBwYGJEydiZmZGREQEJ0+exN7eniVLlmT7vbp16xZRUVEMGzYsS12zZs1ISkri0KFDxMfHY2Vlxbhx43Lc+OJVFNfXlmRIhmRIRmFkiOJNq/tA5eXy5cu0a9cu3/eBEkKI3GhzH6j8+vd9oArDiRMnCj3jt99+K/QM0P4+UEII8V9Q3O4D9eIDxaJsxowZb7sLWWg1A7Vt27Zc60NCQgqkM0IIIYQQQog3Q5bwvR6tBlDu7u4YGRnl+E1+3a17hRBCCCGEEKI40WoAZWVlhZeXF05OTtnWBwUF4eDgUJD9EkIIIYQQQogiR6ttzBs1apTl3iUv09HRyfc25kIIIYQQQog358WtL4ryoyjSagZqwoQJuV68XaNGDfbu3VtgnRJCCCGEEEKIokirAVSrVq1yrTc2Ni6Q+4QIIYQQQgghRFGm1QBKCCGEEEIIUbIU1SVyRZ1W10AJIYQQQgghhJABlBBCCCGEEEJoTZbwCSGKDWNj40LPWLduXaFnNG3atNAzRo8eXegZAB9++GGhZzRv3rzQM8aPH1/oGbJURghR1MjPpdcjM1BCCCGEEEIIoSUZQAkhhBBCCCGElmQAJYQQQgghhBBakmughBBCCCGE+A+Sa6Bej8xACSGEEEIIIYSWZAAlhBBCCCGEEFqSJXxCCCGEEEL8B8kSvtcjM1BCCCGEEEIIoaUiN4DasmUL7du3x87ODmdnZ/7++2/JkAzJkIy3mrF3717c3d3p27cvffv2ZeLEiZw7d06pX7x4Md26ddN4fP7557m2OXHiRI4dO8Y///zDnTt3+Omnn6hXr16Oxy9ZsoS4uDgmTJigUe7q6srevXt58OABcXFxVK1aValzd3fn119/5cqVK1y4cIENGzZQu3ZtpV5XV5cvv/ySgwcPcv36df766y+WLVuGtbW1RsZPP/3EgwcPNB7Lly8HoHbt2nz66af4+PiwadMmWrdunaXvFStW5JNPPmHVqlX4+voya9YsrKysNPoxZMgQli9fjq+vL59++inm5uZKvbW1Nd27d8fV1ZVPPvmEunXrZsl47733GDFiBG5ubvTp04dy5cpp1JuZmdGtWzdGjRrFmDFj6Nevn8b3Sht//fUX48aNo23bttStW5ddu3a90vmvori9RyRDMiRD/JdoPYB6/Pgxx44d4/HjxwBERkbi7e3NvHnzuHbtWoF05sCBA3h6euLm5sbu3btp0qQJo0ePJjQ0tEDalwzJkAzJeB2WlpaMGDGC5cuXs3TpUho1asScOXO4d++eckzjxo358ccflYeHh0eubbZu3Zr169fTqVMnevbsSVpaGnv27NEYOLzQq1cvmjVrlm3/DQ0NOXbsGF5eXlnq3n//fTZv3oyzszODBg0iLS2NLVu2ULZsWeXcBg0asGLFCrp3787HH3+MlZUVP/zwAyqVSqOtHTt20Lx5c+Xx1VdfAWBgYEBISAhbtmwhNTU12+/d119/zePHj1mwYAHTp09n165dGscOHjyYZs2asWbNGjw9PTE0NOTzzz9Xlpbo6ekRHR3NyZMnefbsWZaMpk2b0rhxY37//Xd27NhBcnIyvXr1Qk9PTzmmR48eqFQqdu/ezfbt2wkLC6N79+6Ymppm+/+TneTkZGrVqsVXX32FgYGB1ue9quL4HpEMyZCM4klHR6fIP4oirQZQ586do2nTpjg7O9OsWTMCAwNxdHRk27Zt7Ny5k/bt2xMYGJjvznz33Xf06dOHAQMGYGNjw4wZMyhfvjzbtm3Ld9uSIRmSIRmvm/HBBx/QokULrK2tqVKlCsOHD8fQ0JDr168rx+jp6VGuXDnlYWJikmubzs7ObNmyhevXr3Pt2jXGjh2LpaUlLVu21DjunXfewcvLi1GjRmU7eFi9ejWLFy/m7NmzWeqGDRvGzz//THBwMDdv3uTzzz/HwsKC5s2bA5CQkMCQIUPYt28fd+/e5dKlS3z11VfUqlWLmjVrarSVkpJCVFSU8khISAAgKCiIX375hb///pvMzMwsfejbty9Xr15VZrGioqIICgoiJiYGeD6Ia9u2LTt27ODq1as8ePCAtWvXUqVKFWxtbQF48OABZ8+e5c6dO9lmNGrUiPPnz3Pnzh1iYmIICAhAT09PmW0zMDDAzMyMCxcuEB0dTVxcHKdPn0ZHR4fy5cvn+v/0snbt2jFx4kS6dOlCqVKFt4CjOL5HJEMyJEP8l2j1G2DevHn07t2bhw8f8sUXXzBkyBAcHBw4f/48gYGB9O3bF29v73x15OnTp1y9ehV7e3uNcnt7+wIZnEmGZEiGZBRERnp6OidOnODJkycaS+6uXbvGoEGD+Pjjj1m6dCmxsbGv1G6ZMmVQqVQa56lUKjZs2IC3tzfBwcH57vuLjLi4uFyPAbIc07NnTwIDAzl8+DBff/01xsbGeebp6OjQuHFjQkNDmTRpEsuWLeObb77hvffeU46pXr06urq6XLlyRSmLiYkhLCwsyyAuO6amphgbG/PPP/8oZenp6YSGhirLBJ88eUJMTAx16tRBT08PHR0dbG1tefbsGWFhYXlmvEkl4T0iGZIhGaKk02oAdenSJcaPH4+JiQlubm6EhYUxfPhwpX706NH5flGp1WrS09OxtLTUKLewsCAqKipfbUuGZEiGZOQ34969ezg7O9OrVy9WrFjB9OnTeffddwFo1qwZkyZNwtPTk9GjRxMcHMy0adOynTHKyYIFCwgKCtK4tuqrr74iOjqaDRs2vHa/XzZz5kyuXr3KhQsXsq3X09Nj+vTpHD58mPDwcKV8z549fPrpp7i4uLBs2TK6du3KmjVr8swzNTXF0NCQHj16cOXKFby9vfnzzz8ZO3YsjRo1AqBs2bKkp6crM1ovxMXFKUsNc2NkZAQ8X173suTkZKXuxXOwsLBgzJgxjBs3jvfee4+9e/dmOe9tK87vEcmQDMkoft728rziuoRPq23Mnz17pqz31tPTw8jICAsLC6Xe0tJSWY4hhBAlUZUqVVixYgVJSUn88ccfLF68GC8vL6pXr067du2U4959911q1qyJq6sr586dy/IpZnbmzZvH+++/T5cuXcjIyACeXyM1ePDgbDdleB0zZsygRYsW9O3bV8l4mUqlYsmSJZiamjJq1CiNupeXrdy8eZOHDx/y66+/0qBBg1wzX/ziu3DhAocOHQLg4cOHVK9enQ4dOnDp0qX8Pi2ttWvXjidPnvDLL7+Qnp5O/fr16dq1Kzt27CApKemN9UMIIUTxp9UMVOXKlXnw4IHy9YYNG6hYsaLydURERJYdj16Vubk5KpVK2aTihejo6Fdaoy4ZkiEZklEYGXp6elhbW1OrVi1GjBhBjRo12L17d7bHWlhYYGlpqdUFx56envTr14+ePXty//59pbx169ZUqlSJ4OBgoqOjiY6Oplq1asyePfuVN+6ZMWMGTk5ODBo0SGOp2wsqlYrly5dTt25dBg8enOfyw6CgINLS0qhevXquxyUkJJCWlpbl+xAWFqZ8CBcXF4dKpcpyzVjZsmVzXWr4wosZpJdnm158/aKuSpUqvPvuuxw6dIjw8HCioqI4ceIEz549y3Xnw7ehOL9HJEMyJEP8V2g1gOrVqxcRERHK1507d8bQ0FD5+rfffqNp06b56oi+vj62tracPn1ao/z06dM0adIkX21LhmRIhmQUZAZARkZGjkv04uLiiI6OzvODJS8vL2XwdOvWLY269evX06pVK1q3bq08QkNDWbVqFU5OTlr3c+bMmcrg6c6dO1nqdXV1WblyJXXr1mXQoEFaLVGpW7cuurq6REZG5npceno69+7d09iyHKBSpUrKHyf3798nLS1N2TACnv8BY2Vlxe3bt/PsS3x8PElJSbzzzjtKmUqlwtraWrm+SVf3+WKLf29AkZmZWeSWh5SU94hkSIZkFA9ve3leiV7C9/XXX+da/+mnnyq/oPJjxIgRTJkyhYYNG9K0aVO2bdtGZGQkLi4u+W5bMiRDMiTjdTO+++47WrRoQfny5UlOTub48eNcvnyZWbNmkZKSwpYtW7C3t6dcuXJERESwadMmypYtywcffJBjm97e3gwcOJCPPvqI2NhYKlSoAEBSUhJJSUk8fvw4yyegz549IyIiQmNgUaFCBSpWrIiNjQ0AderUoWzZssTHx/PFF1/Qp08fxowZQ1xcnPLpaVJSEsnJyahUKlatWkWjRo0YNWoUmZmZyjHx8fGkpqZStWpVevfuzbFjx1Cr1dSqVYvp06dz5coV/v77bzp16qSsSNDR0aFcuXJUrVqVxMREYmJi+O2333B3d+fmzZtcv36devXq8d577yn3kUpJSeH3339nwIABxMfHk5iYyKBBgwgJCeHq1avA89m/F9dD6ejoYGJigqWlJU+ePCExMZFLly7RrFkz1Go1sbGxNG/enGfPnikbb4SHh/PkyRMcHR05d+6csoTP1NRUY9YvL0lJSTx8+BB4PoAOCwvj+vXrlC1bNsu9s/KjOL5HJEMyJEP8l+R/1MPzT1vnz5/PypUr89VOt27dUKvVrF69msjISGrXrs3atWupXLlyQXRTMiRDMiTjtdpTq9V8++23qNVqjI2Neffdd/Hw8KBZs2akpqZy//59jhw5QlJSEubm5jRq1Ihp06ZlWVb2stGjRwPPb9L7svnz52d7T6ecjBw5kmnTpilf79y5E4BJkyYxbNgwgCxb7/r4+LBkyRKsrKzo3LkzAPv379c4ZtKkSezcuZNnz55hb2/PyJEjMTIyIiwsjKNHj7JkyRIyMjJ49913+fLLL5XznJ2dcXZ25o8//mD9+vVcuHCBTZs20aNHDz766CMiIiJYt26dxvVPW7duJSMjA3d3d/T09Lh+/Trr1q1TZowqVKhAnz59lONbtmxJy5YtuX79OkeOHOHChQvo6urSrl07SpcuTUREBHv27FFmCJ88ecLevXt5//336dOnD6VKlSImJoYDBw680kXhV65c0dhAafny5SxfvpzevXu/0v9ZXorje0QyJEMyxH+JTmxsbNabaryiy5cv065duxw3ktBmJyUhhCgKslvmVtDyu+RZG2ZmZoWeAfDhhx8WesaL+1YVpvHjxxd6RlFdiiKEKDjaXLtZlCxatOhtdyFPkyZNettdyEKrGai8bhwWEhJSIJ0RQgghhBBCiKJMqwGUu7s7RkZGOX56lt2WuEIIIYQQQghR0mg1gLKyssLLyyvHnZ+CgoJwcHAoyH4JIYQQQgghRJGj1TbmjRo1IigoKMd6HR2dLNvDCiGEEEIIIYqut71FeYnexnzChAm53qm9Ro0aWXaSEkIIIYQQQoiSRqsBVKtWrXKtNzY2pnXr1gXSISGEEEIIIYQoqgrkPlBCCCGEEEKI4qWoLpEr6rS6BkoIIYQQQgghhAyghBBCCCGEEEJrsoRPCCFeYmNjU+gZmzZtKvSMESNGFHoGwObNm0tERm4bJRWUYcOGFXqGlZVVoWcIIUoOWcL3emQGSgghhBBCCCG0JAMoIYQQQgghhNCSLOETQgghhBDiP0iW8L0emYESQgghhBBCCC3JAEoIIYQQQgghtCRL+IQQQgghhPgPkiV8r0dmoIQQQgghhBBCSzKAEkIIIYQQQggtFbkB1JYtW2jfvj12dnY4Ozvz999/S4ZkSIZklPiMjIwM/P39WbBgAdOnT2fBggUcOnSI9PR05ZgrV66wYcMG5syZw5dffsmdO3dybfPzzz/n6NGjPHz4kNu3b/PTTz9Rr169HI/38fEhNjaWTz75RKNcX1+fhQsXcufOHR49esS2bduwtrYGYOrUqZw9exa1Wk14eDh79uzB1tZW4/yNGzeSnp6u8Th16pTGMb6+vgQHB5OYmEh4eDh+fn7UrVv3jWVUqVIFZ2dn3N3dmTp1Kg0aNNA4t3bt2gwYMIAJEyYwdepU3nnnnSzfPzMzM/r06cOECRP47LPP6NWrF0ZGRjl+v7ds2cLYsWPp1q0bvXr1Ytq0ady9e1fjmPnz5+Pg4KDxGDduXI5tvori9h6RDMkoaRmi+MrXAKpBgwZ5/gJ/FQcOHMDT0xM3Nzd2795NkyZNGD16NKGhoZIhGZIhGSU648SJE5w5c4aePXsyceJEevbsyZkzZzh+/LhyzNOnT6lWrRrdu3fXqs3WrVuzYcMGOnfujJOTE2lpaezevRszM7Msxzo5OdGsWbNs+z9//nx69uzJqFGj6NatGyYmJmzfvp1SpUrh4ODAmjVraN26NY6OjqSlpeHv74+5ublGGwEBAVhbWyuPHj16aNSfP3+ekSNHYmtrS9euXdHR0cHf3x9dXd03kqGvr8/jx485cuQIz549y/I90NPT49GjRxw9ejTb77Wenh4DBgwAYNu2bfz444+UKlWKvn37Zns8wMWLF+nduzcrVqzAx8cHlUrFpEmTiI+P1ziuWbNm/PLLL8pjwYIFObapreL4HpEMyShJGUWFjo5OkX8URTqxsbGZeR20YsWKbMtnzpzJ+PHjqVChAkCWTy1fKFu2rFad6d+/P3Xq1GHu3LlKWadOnejcuTOTJk3Sqg3JkAzJkIyinuHn55elbNOmTRgZGSl/hAPs2LGD5ORkXF1dNY5NSkpizpw5jB49Ghsbm2wzRowYkaXM2NiYhw8f8tFHH3Hw4EGl/J133uHQoUP07t2bnTt3snbtWuXnvqmpKbdv32b8+PH8/PPPAFSuXJnLly/Tr18/9uzZkyVDrVbj7OzMvn37gOezQ5aWljg5OeX6fXmZnZ0dFy9epF69egQHBxd6xsvf488//5zDhw9z5cqVLOcYGhryv//9j61bt/LPP/8o5dWrV2fAgAEsXbqU1NRU4PnM3Weffcb27dt58OABw4YNy7U/ycnJ9OjRg7lz59KqVSvg+eA1Li4OLy8vrZ6TlZWVVscV9feIZEhGcc2Ii4srkD68KcuXL3/bXcjThAkT3nYXstBqBmrGjBmsXr2atWvXajwyMjKUX7br1q3LV0eePn3K1atXsbe31yi3t7cnMDAwX21LhmRIhmQU9Yzq1atz584dIiMjAYiIiODOnTvUqVMn3/19oUyZMqhUKmJjY5UylUrF+vXr8fb2zjJQAWjcuDH6+voaMy+PHj3i5s2btGzZMsvxJiYmqFQq1Gq1Rrm9vT1hYWFcv34dX19fypcvn2M/jYyMcHV15cGDB9y/f/+tZLwqlUpFZmamxpLL9PR0MjMzqVKlilZtpKSkkJGRQZkyZTTKL1++TO/evRkyZAjffvttluf9qorre0QyJKOkZIjiT6sB1PDhw7GwsOCXX34hKChIeahUKnbt2kVQUBCXLl3KV0fUajXp6elYWlpqlFtYWBAVFZWvtiVDMiRDMop6Rrt27WjatCk+Pj589dVX+Pj40LRpUz744IOC6DIAXl5eBAUFce7cOaVs2rRpxMTEsHHjxmzPqVChAmlpaURHR2uUR0VFKasPXrZkyRICAwM5c+aMUnbo0CFcXV3p2LEjkydPpkWLFgQEBKCvr69xrpubG3FxcSQkJNClSxc6duzI06dP30rGqwoNDeXZs2c4ODigp6eHnp4eH374IaVKlcoyIMrJ8uXLqVmzpsb1Xe+99x5fffUVixcvxt3dnRs3bvD555/nq8/F9T0iGZJRUjKKkre9PK+4LuHT6j5QS5YsYc+ePfTu3ZvJkydnWU4ihBAif4KCgrhw4QIuLi5UrFiR0NBQ9u7dS7ly5WjRokW+2583bx7vv/8+Xbp0ISMjA3h+jdTgwYNp06ZNvtsH8Pb2xt7enrZt2yoZANu3b1f+feXKFc6fP8+9e/fo3r27xnLGrVu3EhAQgJWVFZMmTWL79u20adOGlJSUQs/Ir5SUFHbv3k2nTp1o2rQpmZmZXLt2jfDwcDIz81wpz8qVK7l8+TLLly9HpVIp5R06dFD+XaNGDWrXrs3AgQM5e/Ysbdu2zXe/hRBCvDqtb6Tbq1cv5SK6w4cPF/iaSXNzc1QqFY8fP9Yoj46OznUZhmRIhmRIRknIOHDgAG3atKFRo0YAVKpUCbVazfHjx/M9gPL09MTZ2ZmePXvy4MEDpbx169ZUqlSJmzdvKmW6urrMnj2bcePGYWtrS2RkJLq6ulhYWGjMQpUvX15jBmjRokUMHDiQDh06cO/evVz7ExYWRkhICDVr1tQoj4+PJz4+ntu3b3P27Fmio6Pp27cvP/74Y6FnFIT79++zdu1aDA0NycjIIDU1lfHjx2ssmczOihUrOHr0KD4+PsruhjmxtLSkfPnyhISEvHY/i+t7RDIko6RkiOLvlXbhq1q1KgcOHKBu3bq0bt1aq0/VtKWvr4+trS2nT5/WKD99+jRNmjSRDMmQDMko0RnPnj2jVCnNH8mlSpXK989ZLy8v+vbti5OTE7du3dKoW79+Pfb29rRp00Z5hIaGsmrVKnr16gU83ynu6dOnfPjhh8p51tbW1KlThz///BN4vv25i4sLjo6OGoOxnFhYWFC5cmXCw8NzPObF0o3SpUu/sYyCkpKSQmpqKlWrVsXY2Jjbt2/neOzy5cs5cuQIPj4+VKtWLc+2Y2Njefz4MRYWFq/dv+L6HpEMySgpGUXJ216eV6KX8L1MpVIxY8YMHBwcOHXqVIGOxkeMGMGUKVNo2LAhTZs2Zdu2bURGRuLi4iIZkiEZklGiM+rWrcvx48cpV64cFSpUIDQ0lD/++EPjF3ZycjKxsbHKkrbo6GgMDQ0xMTHBxMQkS5vffvstAwcOZMiQIcTGxirXLCUlJZGUlMTjx4+zfMqalpZGRESE8kd/fHw8mzdvZvbs2URFRaFWq5k3bx5Xr17l+PHjLF++nCFDhuDs7IxaraZixYoAJCYmkpSUhLGxMTNnzmTXrl2EhYVRvXp15s2bR2RkpLK0zsbGBmdnZ44cOUJUVBRVqlRh6tSppKamsm/fvjeS8cUXXyjbouvo6GBqakqFChVISUkhISEBAwMDTE1NlcGWubk5qampyvcSnu/qFx0dTXJyMtbW1jg6OvLXX38RExOT7f/5kiVL8Pf3Z+7cuZQpU0aZ4TM0NMTIyIjk5GQ2bdpEu3btKFeuHOHh4axbtw4zM7N8Lzssju8RyZCMkpQhirdXHkC98OLTSoCQkBDmz5/PypUr89WZbt26oVarWb16NZGRkdSuXZu1a9dSuXLlfLUrGZIhGZJR1DN69eqFv78/u3fvJjExEVNTU1q0aKFxDcy1a9fYuXOn8vWuXbuA59fJdOzYMUubo0ePBuDXX3/VKPfy8tJ6W2x4vtFEeno63333HQYGBvz++++4ubmRkZGBu7s78PweTC+bPXs2Hh4epKenY2dnx9ChQzEzMyMsLIzjx4/j4uJCYmIiAKmpqTg4ODBx4kTMzMyIiIjg5MmT2NvbExER8UYyKlWqxODBg5W2X/yOu3z5MgcOHKBmzZoa99/q2rUrAH/88Ydyw95y5crRtm1bDA0NiYuL48yZM/z11185fl93794NwMSJEzXKhw8fzogRI1CpVNy7dw9/f38SExOxsLCgcePGzJo1K9cb9GqjOL5HJEMySlKGKN60ug9UXi5fvky7du1y/JRN2/tACSHEf0F294EqaNndB6owJCQkvJGcwubp6VnoGXndB6ogaHsfKCFE4Shu94FatWrV2+5Cnl58iFaUaDUDtW3btlzr83MxqxBCCCGEEEIUF1oNoNzd3TEyMsrxQq6Xt5IVQgghhBBCiJJKqwGUlZUVXl5eODk5ZVsfFBSEg4NDQfZLCCGEEEIIUYiK6i53RZ1W25g3atSIoKCgHOt1dHQKdEtzIYQQQgghhCiKtJqBmjBhgrJNa3Zq1KjB3r17C6xTQgghhBBCCFEUaTWAatWqVa71xsbGtG7dukA6JIQQQgghhBBF1WvfB0oIIYQQQghRfMk1UK9Hq2ughBBCCCGEEELIAEoIIYQQQgghtCZL+IQQ4g3r06dPoWfUrFmz0DMAJk2aVOgZR44cKfSMr776qtAzHjx4UOgZX3/9daFnVK5cudAzhBBvhizhez0yAyWEEEIIIYQQWpIBlBBCCCGEEEJoSZbwCSGEEEII8R8kS/hej8xACSGEEEIIIYSWZAAlhBBCCCGEEFqSJXxCCCGEEEL8B8kSvtcjM1BCCCGEEEIIoSUZQAkhhBBCCCGElorcAGrLli20b98eOzs7nJ2d+fvvvyVDMiRDMiSjEDJ27dpFv379WL9+vVK2YsUK+vXrp/GYNm1ajm3Y2dkxe/Zstm7dir+/Px07dtSoNzAwwN3dnS1btrB37142bNiAs7Nzlnbq1KmDl5cXe/bsYffu3fj4+GBqagrA1KlTOXv2LGq1mvDwcPbs2YOtra3G+Rs3biQ9PV3jcerUKY1jfH19CQ4OJjExkfDwcPz8/Khbt+4by4DnNzh2c3PD09OTVatW8f7772ucP3ToUFatWqXxmDx5ssYxurq6DBgwgIULF+Lj44ObmxtmZmbZ/v9s3bqVcePG0aNHD/r06cNXX33FvXv3NI5p3759to+lS5dm2+arKO7vEcmQjMLMKAp0dHSK/KMoeq0B1LNnz9i3bx/Lli1j+/btJCUlFUhnDhw4gKenJ25ubuzevZsmTZowevRoQkNDC6R9yZAMyZAMyXguODiYgIAAqlWrlqWuYcOGrFu3Tnl89dVXObZjYGDA/fv3Wb16NU+ePMlS7+bmRsuWLVm4cCEff/wx27ZtY+TIkXTo0EE5pm7dusyfP59Lly7x6aefMn78eHbu3ElaWhoADg4OrFmzhtatW+Po6EhaWhr+/v6Ym5trZAUEBGBtba08evTooVF//vx5Ro4cia2tLV27dkVHRwd/f390dXXfSAZA6dKlCQ0N5eeff+bp06fZfk+vX7/Ol19+qTxWrlypUd+vXz8aN27Mxo0bWbx4MQYGBowbNy7bPzQuXryIk5MTy5cvZ9GiRahUKr744gvi4+OVY3bu3KnxmDdvnvJ9z4/i/h6RDMkozAxRvOnExsZm5nVQp06d2LFjB2ZmZjx+/BgnJydu3bqFtbU1YWFhVKhQAX9/f6ytrbM9v2zZslp1pn///tSpU4e5c+dqZHfu3JlJkyZp+ZQkQzIkQzIk4/LlyznWJSUlMWXKFMaNG8eOHTuoWrUqH3/8MfB8Bio+Pj7XQdPLXu7Hnj17WLFiBYcPH1bK1q5dy8mTJ9m8ebNS5u3tzb1795SBgY+PD5cuXWLTpk3ZZhw5ckTja2NjY9RqNc7Ozuzbtw94PjtkaWmJk5OTVv2G57NnFy9epF69egQHBxd6xocffqhRt3jxYnbs2MHZs2eVsqFDh1KmTBlWr16dbXsGBgYsXLiQzZs389dffwFgbm7OnDlzWLlyZbazey9LSUmhZ8+eeHh40KpVq2yP8fb2JigoiB9++CHb+sqVK+ea8UJRf49IhmQURkZcXFyB9OFNeXkFQlH14vdTUaLVDNRff/3Fs2fPAJgzZw6lSpXi8uXLXLp0ievXr2NtbY2np2e+OvL06VOuXr2Kvb29Rrm9vT2BgYH5alsyJEMyJEMy/p+vry/vv/8+DRo0yLb+xo0bjBw5kgkTJrB69ep8/UFw5coV3n//fcqXLw9A/fr1sbGxUZbDmJmZYWtrS0xMjDKgWLRoEY0bN86xTRMTE1QqFWq1WqPc3t6esLAwrl+/jq+vr5KZHSMjI1xdXXnw4AH3799/Kxk5sbGxYcGCBcycOZPBgwdTpkwZpa5q1aro6upy/fp1pezFssMaNWrk2XZycjIZGRmYmJhkW5+SksKxY8fo3r271v3NTnF/j0iGZBRmhij+XnkJ36lTp5gxYwaVKlUCwMLCghkzZvD777/nqyNqtZr09HQsLS01yi0sLIiKispX25IhGZIhGZLx3OHDhwkPD2fQoEHZ1jdu3JgJEyYwc+ZMhg8fzu3bt5k1a5byIdqrWrVqFXfv3mXLli0cOHAAb29v1q9fz59//gmg/C4ZNmwYhw4dYtq0aVy5coX58+fnOCBYsmQJgYGBnDlzRik7dOgQrq6udOzYkcmTJ9OiRQsCAgLQ19fXONfNzY24uDgSEhLo0qULHTt2zHYp3ZvIyM61a9f4/vvvWbp0Kbt27aJ69ep89tlnyhJAU1NT0tPTSUxM1DgvISFBuWYsNytWrKBmzZrUr18/2/ojR46QlpZG586dtepvTorze0QyJKOwM4qSt319U3G9Bkrr+0C9eAJxcXFUrVpVo65atWpEREQUbM+EEEIUqEePHrFt2zbmzJmj/EH+b61bt1b+Xa1aNWrUqMG4ceM4f/58lg0PtNGrVy/q16/PN998Q0REBHZ2dowZM4aIiAj+/vtvSpV6/jne/v37OXToEAB37tyhUaNGdO/eneXLl2u05+3tjb29PW3btiUjI0Mp3759u/LvK1eucP78ee7du0f37t3x8/NT6rZu3UpAQABWVlZMmjSJ7du306ZNG1JSUgo9Qxvnz59X/h0aGsrDhw+ZO3cuDRo04OLFi1q1kZNVq1Zx5coVli5dikqlyvaY/fv306pVqxw3pRBCCPEKA6gxY8agr6/Ps2fPePDgAfXq1VPqIiIitL7OKSfm5uaoVCoeP36sUR4dHZ3rEgnJkAzJkAzJ0E5wcDDx8fF8/vnnSllGRgbXr1/H39+fLVu2oKenp3FOuXLlsLCwICws7JXz9PX1GTlyJHPnzlWu87l37x42Njb069ePv//+m5iYGAAePnyoce7Dhw+pUKGCRtmiRYsYOHAgHTp0yLKT3L+FhYUREhJCzZo1Ncrj4+OJj4/n9u3bnD17lujoaPr27cuPP/5Y6BmvIy4uDrVarfyfx8fHo1KpKFOmjMYslImJCbdv386xnZUrV3Ls2DEWL16c4/XKt2/f5ubNm4waNeq1+vqy4voekQzJeBMZovjTagnfoEGDqFSpEuXKlaNbt24an9QB/Prrr9jZ2eWrI/r6+tja2nL69GmN8tOnT9OkSZN8tS0ZkiEZkiEZ8N5777F48WK8vb2Vh42NDfb29nh7e2c7KxUfH09MTEyW3ei0oauri56ensYsDjwftL2YeQoPD+fx48dUqVJF45jKlSsTGRmpfO3j44OLiwuOjo7cvHkzz2wLCwsqV65MeHh4jse8WB5SunTpN5bxqoyNjTEzM1N2zXv48CFpaWkaW6ObmZlRqVIl7t69m20bK1as4OjRoyxatCjLCpKX7du3DysrK5o1a/ZafX1ZcX2PSIZkvImMouRtL88r0Uv4Vq1alWv9l19+meNygFcxYsQIpkyZQsOGDWnatCnbtm0jMjISFxeXfLctGZIhGZLxX88wNjbG2NhYo6x06dKUKVOGqlWrkpKSwo4dO3j//fcxNzcnMjKSrVu3YmpqSsuWLbNt08DAQJnR0NHRoUKFCtSoUYOEhASioqK4dOkSo0aNIiUlhcjISOzs7HB0dNTY+ennn39m2LBh3L17lzt37tC2bVvq1aun7NK3fPlyhgwZgrOzM2q1mooVKwKQmJhIUlISxsbGzJw5k127dhEWFkb16tWZN28ekZGRytI6GxsbnJ2dOXLkCFFRUVSpUoWpU6eSmprKvn373khG7969KV26tPIpdqlSpTA3N6dKlSokJSWRnJxM9+7dCQwMJC4uDgsLC3r16kVCQoKyfO/JkyecPn2aPn36kJCQQFJSEv369ePRo0fcuHEjy//P0qVLOXz4MB4eHpiYmCgzfoaGhhgaGirHPXnyhCNHjjBw4MAC+4OlOL5HJEMy3lSGKN60XsKXG7Vazfz587Pcq+JVdevWDbVazerVq4mMjKR27dqsXbtW6y1TJUMyJEMyJOP1lSpViocPH3LixAmSk5MxMzOjQYMGTJw4UeOP7ZfVrl0bb29v5evhw4czfPhw/P398fb2xtPTk5EjR/Lll19iYmJCZGQk33//PXv27FHO8fPzQ09Pj7Fjx2Jqasr9+/f5+uuvlRkVd3d34Pk9mF42e/ZsPDw8SE9Px87OjqFDh2JmZkZYWBjHjx/HxcVFWeaWmpqKg4MDEydOxMzMjIiICE6ePIm9vT0RERFvJAOe76L38hLKnj170rNnT86cOcNPP/2EtbU1LVu2xNDQkLi4OIKDg9mwYQOpqanKOTt37iQjI4NRo0ahr6/PzZs3+f7778nMzHpXkhff5y+++EKjfNiwYbi6uipfHzt2jJSUFLp06ZLt//PrKCnvEcmQjML+2SuKH63uA5WXy5cv065dO+WTrX/L7/VRQgghXk1u94EqSAV135Xc/Ps+UMXV2LFjCz3j66+/LvQM+SNSiJwVt/tAfffdd2+7C3kaMWLE2+5CFlrNQG3bti3X+pCQkALpjBBCCCGEEEIUZVoNoNzd3TEyMspxXfS/LxAWQgghhBBCiJJIqwGUlZUVXl5eODk5ZVsfFBSEg4NDQfZLCCGEEEIIUYiK6i53RZ1W25g3atSIoKCgHOt1dHSyvXhVCCGEEEIIIUoSrWagJkyYQFJSUo71NWrUYO/evQXWKSGEEEIIIYQoirQaQLVq1SrXemNjY1q3bl0gHRJCCCGEEEIUPlnC93q0WsInhBBCCCGEEEIGUEIIIYQQQgihNa2W8AkhhBBCCCFKFlnC93pkACWEECWQnZ3dG8nZsWNHoWe8iU2K3sSd7n19fQs949atW4Wecfjw4ULPEEKIokyW8AkhhBBCCCGElmQAJYQQQgghhBBakiV8QgghhBBC/AfJNVCvR2aghBBCCCGEEEJLMoASQgghhBBCCC3JEj4hhBBCCCH+g2QJ3+uRGSghhBBCCCGE0JIMoIQQQgghhBBCS0VuALVlyxbat2+PnZ0dzs7O/P3335IhGZIhGZJRiBkFnRMYGMgXX3xBjx49aNmyJfv27ctyzMOHD5k6dSodOnSgbdu2DBs2jHv37mmdoaurS/PmzenTpw+DBg2ic+fOWFhYKPWNGjXCycmJQYMGMWDAABwdHSlfvnyO7U2dOpUzZ84QExNDWFgYu3fvxtbWVuOYDRs2kJaWpvE4deqUUm9ubs6SJUu4cuUKCQkJ3Lt3jxUrVlCuXDkl4+zZs6jVasLDw9mzZ0+WjI0bN5Kenq7xeDkDnt+QNzg4mMTERMLDw/Hz86Nu3brA8xsoe3h4sG3bNg4fPkynTp00zjUwMGD8+PFs3bqVffv2sXHjRpydnZX6ihUrcvjw4Wwf/fv31+a/RkNJeY9IhmQU1s/et01HR6fIP4oirQZQt27dIjQ0VPn68OHDDBgwgFatWjFw4EACAgIKpDMHDhzA09MTNzc3du/eTZMmTRg9erRGtmRIhmRIhmQUXEZh5CQnJ1OjRg0+//xzSpcunaU+NDSU0aNHY21tzcqVK9m2bRtjx47FyMhI64wPPvgAa2trTp8+zb59+wgLC8PR0RFDQ0MA4uPjOXfuHHv37uXQoUMkJibSvn17DAwMsm2vXbt2rFmzhjZt2tCxY0fS0tI4dOgQ5ubmGscFBARQuXJl5dGjRw+lztramsqVK/Pll1/SuHFjhg8fTps2bdiyZQsADg4OrFmzhtatW+Po6EhaWhr+/v7ZZlhbWyuPlzMAzp8/z8iRI7G1taVr167o6Ojg7++Prq4uhoaG3L9/n1WrVvHkyZMsz9PNzY2WLVuyYMECRo0axdatWxk1ahSOjo4AREVFMWDAAI3H0qVLycjI4OTJk1r//0DJeY9IhmQU1s9eUXzpxMbGZuZ1kIODA9OnT8fR0RE/Pz9Gjx5Nnz59qF27Nrdv38bPzw9fX1/69OmT7flly5bVqjP9+/enTp06zJ07Vynr1KkTnTt3ZtKkSVo+JcmQDMmQDMl4UzmxsbG51js4OCizUS/MmDEDHR0dPDw8tOrf3r17Nb5WqVS4uLhw4sQJQkJClPJu3boRGhrKxYsXs7Shp6eHi4sLAQEBhIWFZakfMWKExtfGxsbExMTQt29fZQZtw4YNWFpa0qtXL636DdC1a1f27NmDhYUF8fHxWTLUajXOzs5KxsaNG7G0tMTJyUnrDDs7Oy5evEi9evWoUqWKUv7rr7+yYsUK/P39lbK1a9fyxx9/8MMPPyhlixYtUmbLsuPl5QXAl19+CTz/EFUbJeU9IhmS8SoZcXFxBdKHN+XFBzxF2UcfffS2u5CFVjNQwcHB1KpVC4Dly5cze/Zs1q1bx+TJk/H19eXbb79l0aJF+erI06dPuXr1Kvb29hrl9vb2BAYG5qttyZAMyZAMyXi7OS9kZGTwxx9/8O677/Lpp5/SuXNnXF1dtf6jHJ4vOSlVqhTp6eka5enp6dku0ytVqhS1atXi6dOnqNVqrTJMTExQqVRZjre3tyc0NJRr166xZs2aXJcFvmgnNTWV5OTkV8oICwvj+vXr+Pr65pphZGSEq6srDx484P79+3k+r6tXr/L+++8rbdavXx8bGxv++uuvbI+vVKkSTZo0Yf/+/Xm2/bKS8h6RDMkojIyi5G0vzyvRS/j09PSUT84ePnxIu3btNOrbtm3L3bt389URtVpNeno6lpaWGuUWFhZERUXlq23JkAzJkAzJeLs5L+clJyezadMmWrZsyfLly+nUqRMzZ87kjz/+0KqNtLQ0IiMjsbOzw9DQEB0dHd59910sLS2VJXwAlStXxsXFhcGDB1OvXj0CAgKyXdaWHR8fHwIDAzlz5oxSdujQIVxdXenUqRNTpkyhRYsWHD58GH19/WzbKFu2LLNnz2b9+vVZBnsAS5YsyTGjY8eOTJ48mRYtWhAQEJAlw83Njbi4OBISEujSpQsdO3bk6dOneT6vlStXcvfuXbZu3cpvv/3GokWLWL9+PX/++We2x3fr1o24uDhOnz6dZ9svKynvEcmQjMLIEMWfVveBatu2LT///DN2dnY0btyYkydP0qBBA6X+999/x9rautA6KYQQomTIyMgAnv9eGTx4MAC1a9fm+vXr7Ny5k9atW2vVzqlTp2jVqhX9+vUjIyODmJgY7t+/r7GRREREBPv376d06dLUqlWLtm3bcvDgQVJSUnJt29vbG3t7e9q1a6f0F2DHjh3Kv69cucL58+e5e/cu3bp1Y/fu3RptGBsbs2fPHkJDQ5Wlb9lltG3bViNj+/btWTLu3btH9+7d8fPzU+q2bt1KQEAAVlZWTJo0ie3bt9OmTZs8v2+9e/emfv36zJgxg4iICBo2bMiYMWMIDw/PcpF8qVKl6NSpE/7+/tkOAIUQ4r9KqwHUzJkz6dKlC+Hh4bRq1Yp58+YRGBhInTp1uHXrFn5+fixZsiRfHTE3N0elUvH48WON8ujo6DyXSEiGZEiGZEhG0c55wczMDJVKxbvvvqtRXr169VdaxpeYmKhsnKCnp0dKSgpt2rQhISFBOSYtLY2EhAQSEhJ4/PgxvXr1ombNmly+fDnHdhctWqTs2pfXroBhYWGEhIQoS9xfMDY2Vq5pcnJyIjU1NUvGwIED6dChg9YZNWvW1CiPj48nPj6e27dvc/bsWaKjo+nbt2+uF7nr6+szcuRI5syZw9mzZwG4d+8eNjY29O/fP8sA6oMPPsDCwoLffvst1z5mp6S8RyRDMgojoygpqkvkijqtlvDVrFmTI0eOkJmZiY+PD0lJSfz88894eXlx7949Nm7cyKBBg/LVEX19fWxtbbMsEzh9+jRNmjTJV9uSIRmSIRmS8XZzXtDT06N+/fo8ePBAo/zhw4dUqlTpldtLS0sjJSUFfX19rK2tNTaV+DcdHR1UKlWO9YsXL2bgwIF07NiRmzdv5pltYWFB5cqVNTalKFOmDAcOHEClUtGjRw+SkpI0zvHx8cHFxQVHR8dXyggPD8/1eeno6GS74+HLXgw2X57xgufXjmX3R1S3bt24dOkSjx49yrOf/1ZS3iOSIRmFkSGKP61moACqVavGunXryMzMJCoqioyMDCwsLNDT0yuwzowYMYIpU6bQsGFDmjZtyrZt24iMjMTFxUUyJEMyJEMyCiGjMHKSk5OVgUxGRgbh4eEEBwdjampKpUqVGDp0KF999RWNGzemefPmnD9/nsOHD7Nw4UKtM6ysrNDR0SE+Ph4TExOaNm1KXFwct2/fRk9PD1tbW0JCQkhOTsbAwIA6depgZGSU40YLy5YtY8iQIfTt2xe1Wk3FihWB5zNdSUlJGBsbM3PmTHbt2kVYWBjVq1dn3rx5REZGKsv3ypQpw8GDBzExMaFv374YGxtjbGwMQExMDIsWLWLIkCE4Ozu/csaL5Xs2NjY4Oztz5MgRoqKiqFKlClOnTiU1NZV9+/bRrFkzKleuDDwfWFWoUAEbGxvi4+OJiori0qVLjBo1ipSUFCIjI2nYsCEdO3Zk3bp1Gt+P8uXL06xZs1f6P/m3kvIekQzJKKyfvaL40noA9cKLH8gvCwkJYf78+axcuTJfnenWrRtqtZrVq1cTGRlJ7dq1Wbt2rfLLoCBIhmRIhmRIRuHmXL9+HXd3d+XrdevWsW7dOrp3784333xDu3btmDZtGps2bcLHx4d33nmHmTNnan39Ezz/lLhJkyYYGRmRmprKw4cPuXjxIpmZmWRkZFC2bFlsbGwoXbo0qampREdH4+/vn+O26y/6++9lhB4eHnh4eJCenk6DBg0YMmQIZmZmhIWFcfz4cVxcXEhMTASgWbNmvP/++wDcuHFDo50OHTooGf++d+Ls2bOVDDs7O4YOHZpjRmpqKg4ODkycOBEzMzMiIiI4efIk9vb2REREULt2bY1dcYcPH87w4cPx9/fn22+/Zd68eYwaNYpp06ZhYmJCREQEmzZtYs+ePRp96tq1K0lJSa9876eXlZT3iGRIRmH97BXFl1b3gcrL5cuXadeuHTExMdnWa3sfKCGEEMVLXveBKgj/vg9UYfj3faAKQ2Zmvn/d5ql9+/aFnvEq16oJ8V9T3O4D9dNPP73tLuSpKM78aTUDtW3btlzrc1tzLoQQQgghhBAlhVYDKHd3d4yMjHLcqePfF6QKIYQQQgghREmk1QDKysoKLy8vnJycsq0PCgrCwcGhIPslhBBCCCGEKESyjfnr0Wob80aNGhEUFJRjvY6OzhtZ2y2EEEIIIYQQb5NWM1ATJkzIci+Ll9WoUeONXOQrhBBCCCGEEG+TVgOoVq1a5VpvbGz8StvPCiGEEEIIId4uWcL3erRawieEEEIIIYQQRcGpU6dwcXGhXr16mJmZsWXLFo36zMxM5s+fT926dalUqRLdu3fn+vXrGsfExsYyZswYqlatStWqVRkzZozWt+aQAZQQQgghhBCi2EhKSqJ+/fp4eXlhaGiYpX7p0qWsXLmSBQsWcPToUcqXL0+fPn1ISEhQjvn4448JCgpi586d7Ny5k6CgIMaOHatVvlZL+IQQQgghhBAlS3FdwtepUyc6deoEPL/d0ssyMzNZvXo1n332Gb169QJg9erV1KpVi507dzJixAhu3rxJQEAABw8e5L333gPAx8eHrl27cuvWLWrVqpVrvsxACSGEEEIIIUqEBw8eEBERQfv27ZUyQ0NDWrVqxZ9//gnAuXPnKFOmDC1btlSOef/99zE2NlaOyY3MQAkhhHhtZmZmhZ4xdOjQQs/4+OOPCz0jLS2t0DN+//33Qs84fvx4oWfIvSWFEK8rIiICgPLly2uUly9fnrCwMAAiIyOxsLDQmIHT0dHB0tKSyMjIPDNkACWEEEIIIcR/UHFdwve2yRI+IYQQQgghRIlQsWJFAKKiojTKo6KiqFChAgAVKlQgOjqazMxMpT4zM5PHjx8rx+RGBlBCCCGEEEKIEqFatWpUrFiRY8eOKWVPnjzhzJkzyjVP7733HomJiZw7d0455ty5cyQlJWlcF5UTWcInhBBCCCGEKDYSExO5e/cuABkZGYSEhBAUFIS5uTnvvPMO48aNY/HixdSqVYuaNWvi7e2NsbEx/fr1A6BOnTo4Ojry+eefs2TJEgA+//xzOnfunOcOfCADKCGEEEIIIf6Tius1UIGBgfTs2VP5ev78+cyfP59BgwaxevVqPv30U1JSUpg8eTKxsbE0a9aMXbt2YWJiopyzfv16pkyZQt++fQHo2rUrCxcu1CpfJzY2NjPvw/KnbNmyhR0hhBBCvLbSpUsXesab2IVPV7fwPxc9dOhQoWfILnyiuIqLi3vbXXglv/zyy9vuQp5eDHCKErkGSgghhBBCCCG0VOQGUFu2bKF9+/bY2dnh7OzM33//LRmSIRmSIRmFmPGmcopyxuTJkzl16hRRUVGEhISwa9cu6tevn+PxK1euJDU1lc8//1yjvEaNGuzYsYOQkBCioqLYsmWLsqPT1KlTOXv2LGq1mvDwcPbs2YOtra3G+Rs3biQ9PV3jcerUKY1jfH19CQ4OJjExkfDwcPz8/Khbt+4bex7ZiYuL47vvvmPSpEmMHz+eWbNmERwcnO2xP/74I2PHjsXf3z/H9l5FUX5dSYZkFHU6OjpF/lEUaTWAmjx5MmfOnCnsvnDgwAE8PT1xc3Nj9+7dNGnShNGjRxMaGioZkiEZkiEZhZDxpnKKeka7du3w9fWlXbt2dO7cmbS0NH777TfMzc2zHNunTx+aN2/Oo0ePNMqNjIzYv38/Ojo6dO7cGQcHB/T19dm1axc6Ojo4ODiwZs0aWrdujaOjI2lpafj7+2fJCAgIwNraWnn06NFDo/78+fOMHDkSW1tbunbtio6ODv7+/ujq6r6R5/FvycnJynUDn3zyCbNnz2bgwIEa1xq83Pf79+8X2A2Yi/rrSjIkQ5RMWl0DZW5ujo6ODjVr1mT48OEMGjSIcuXKaR2i7TVQ/fv3p06dOsydO1cp69SpE507d2bSpEla50mGZEiGZEhG0cop6hn/vgbK2NiYqKgo+vfvz/79+5XyqlWrcvz4cbp168aePXtYs2YNPj4+ADg6OrJ3716srKyIjY0FwNTUlIiICLp3755lxsXY2Bi1Wo2zszP79u0Dns9AWVpa4uTkpPXztrOz4+LFi9SrV0/Zlaown8fUqVM1Mvz8/Lh16xZTpkzJtZ/R0dEsXLiQzz77jOXLl+Pg4ECnTp2yPVbba6CK+utKMv57GcXtGqhdu3a97S7kydnZ+W13IQutl/Bt27aN999/Hy8vL+rXr8+oUaM4ceJEgXXk6dOnXL16FXt7e41ye3t7AgMDJUMyJEMyJKOAM95UTnHMMDExQaVSoVarlTKVSsUPP/yAl5cXN27cyHJO6dKlyczM5MmTJ0rZkydPyMjIoFWrVlplvOhzWFgY169fx9fXl/Lly+fYTyMjI1xdXXnw4AH3799/K8/j0qVLVK9enbVr1/LFF18wZ84cjh07pnGDyvT0dNavX0+3bt2wsrLK8fm8iuL4upIMyShq3vbyvBK9hA+gadOmLFu2jBs3buDl5cW9e/fo3bs3TZo0wcfHh4iIiHx1RK1Wk56ejqWlpUa5hYVFljsJS4ZkSIZkSEbBKCnPpaAzFi1axMWLFzl79qxS9s033xAdHc3atWuzPefPP/8kMTERLy8vjIyMMDIyYsGCBejq6mY7aFiyZAmBgYEaS+QPHTqEq6srHTt2ZPLkybRo0YKAgAD09fU1znVzcyMuLo6EhAS6dOlCx44defr06Vt5HlFRUZw4cYLy5cvzv//9j/bt2+Pn58fx48eVY/bu3UuZMmVo165dtpmvozi+riRDMkTJ8MqbSBgbG+Pq6srRo0c5ceIE7du3x8fHhwYNGhRG/4QQQog3auHChbRq1QoXFxcyMjIAaNu2LUOHDmXs2LE5nvf48WMGDx5M586diY6OJioqirJly3LhwgWlnRe8vb2xt7enf//+GnXbt29n7969XLlyhX379tG9e3fq1KlD9+7dNc7funUrzZo1w8HBgVu3brF9+3YMDQ3f+PMAyMzMpGrVqvTp04eqVatib2/Phx9+qAygbt68yZkzZxg2bFiOmUIIUZxodcOInKbPGjZsyKJFi5g7d26+11Cam5ujUql4/PixRnl0dHSuyxckQzIkQzIko2jnFKeMb7/9lv79+9O5c2fu3bunlLdt2xYrKysePHiglOnq6jJv3jw++eQTbGxsgOcbQNSrVw8LCwvS0tKIi4vjwYMHGm0tWrSIgQMH0qFDB43y7ISFhRESEkLNmjU1yuPj44mPj+f27ducPXuW6Oho+vbty08//VToz6N27doafSlbtmyWmSkrKyuOHj0KQHBwMHFxcRrXSGVkZLBr1y6OHDnCggULcv0e5KQ4va4kQzKKqqK6RK6o02oG6uV1zNkxNDTko48+yldH9PX1sbW15fTp0xrlp0+fpkmTJvlqWzIkQzIkQzLeXk5xyVi0aBEDBgygS5cu3Lx5U6PO19eXZs2a0aJFC+Xx6NEjli1bRteuXbO0FR0dTVxcHA4ODlSoUEHZJMLHxwcXFxccHR2zZGTHwsKCypUrEx4enuMxL64TeLERxpt4Hi+zsbHJsow/IiICCwsL4PkOhzNmzGD69OnKw8zMDEdHxyzbp7+K4vK6kgzJECWPVjNQ/77AtbCMGDGCKVOm0LBhQ5o2bcq2bduIjIzExcVFMiRDMiRDMgoh403lFPWMpUuXMnjwYPr3749araZixYoAJCYmkpSURFRUVJbrH549e0ZERITG/Y6GDRvGzZs3iYqKomXLlixatIhly5YRHBzM8uXLGTJkCM7OztlmGBsbM3PmTHbt2kVYWBjVq1dn3rx5REZG4ufnBzwfrDg7O3PkyBGioqKoUqUKU6dOJTU1lX379r2R5/Fvjo6OLFiwgAMHDtC8eXP++ecfjh49Su/evYHnO/iZmppqnKNSqTA1NaVSpUp5/t/kpqi/riRDMkTJpNUAKi8hISHMnz+flStX5qudbt26oVarWb16NZGRkdSuXZu1a9dSuXLlguimZEiGZEiGZLylnKKe4ebmBjzfxOFlc+bM0djKOC+1a9dmzpw5lCtXjgcPHrBgwQKWLl0KgLu7O/B8edzLZs+ejYeHB+np6djZ2TF06FDMzMwICwvj+PHjuLi4kJiYCEBqaioODg5MnDgRMzMzIiIiOHnyJPb29kRERLyR5/Fv1atXx93dnd27d7N//37KlStHr169tN6KPD+K+utKMiSjqJMlfK9Hq/tA5eXy5cu0a9eOmJiYbOu1vQ+UEEII8Tb8+z5QhSEtLa3QM3R1C+Rz0Vz9e3BWGN7E4EuIwlDc7gO1Z8+et92FPPXq1ettdyELrX7Sbtu2Ldf6kJCQAumMEEIIIYQQQhRlWg2g3N3dMTIyynGaL7ttTYUQQgghhBBFlyzhez1aDaCsrKzw8vLCyckp2/qgoCCZbhdCCCGEEEKUeFptY96oUSOCgoJyrNfR0clzq3MhhBBCCCGEKO60moGaMGECSUlJOdbXqFGDvXv3FlinhBBCCCGEEKIo0moA1apVq1zrjY2Nad26dYF0SAghhBBCCFH45Bqo16PVEj4hhBBCCCGEEDKAEkIIIYQQQgitFf4d94QQQgghhBBFjizhez0yAyWEEEIIIYQQWpIZKCGEKIFyu/VEQdq5c2ehZ/z111+FnpGWllboGW9C/fr1Cz2jbdu2hZ4hhBBFmQyghBBCCCGE+A+SJXyvR5bwCSGEEEIIIYSWZAAlhBBCCCGEEFqSJXxCCCGEEEL8B8kSvtcjM1BCCCGEEEIIoSUZQAkhhBBCCCGElmQJnxBCCCGEEP9BsoTv9cgMlBBCCCGEEEJoqcgNoLZs2UL79u2xs7PD2dmZv//+WzIkQzIkQzIKIcPPz4/+/fuzfv16jfLQ0FC+/fZbhg8fzkcffcSUKVMICQnJto1q1aoxePBgvvjiCzw8PGjcuLFGffv27ZkwYQLTp09n2rRpuLq68s4772gco1Kp6NatG1OnTmX69OkMHjwYU1NTpb5BgwbMnDmTzZs389tvv+Ho6KhxvoGBAePGjWPz5s3s3r2bdevW0bt3b41j/ve//7Fx40Z2797NTz/9xDfffKPRj6lTp3L27FnUajXh4eHs2bMHW1tbjTY2btxIenq6xuPUqVMax/j6+hIcHExiYiLh4eH4+flRt27dN5YxcuRIfvzxR06ePMnRo0dZsmQJNjY2Wf7fxo4di7+/P2fOnGHdunXUqFFDqWvWrBmBgYHZPv79vc/J2rVr6d+/P82bN6dVq1aMGzeO4OBgrc59VcX9fSgZ/90MUXxpPYDasWMHU6ZM4fDhwwAcPXqUPn360KtXryy/fF/XgQMH8PT0xM3Njd27d9OkSRNGjx5NaGhogbQvGZIhGZIhGc8FBwdz+PBhqlWrplEeERHB9OnTqVChAjNnzmTx4sW4uLhgYGCQbTv6+vpERkZy4MABnj59mqX+8ePH7N+/n5UrV7J+/XrUajVDhw7F2NhYOaZr167Ur1+fnTt3smHDBkqXLs1HH32kLC0xNDTk/v37+Pr68uTJkywZY8aMoUWLFnz77beMGTOGn376iZEjR9K+fXvlmFu3brFo0SLGjBnD119/jY6ODp6enqhUKgAcHBxYs2YNrVu3xtHRkbS0NPz9/TE3N9fICggIwNraWnn06NFDo/78+fOMHDkSW1tbunbtio6ODv7+/ujq6r6RjGbNmrFjxw5cXV0ZM2YM6enprFmzRmNA6urqytChQ1mwYAFDhgwhJiaGNWvWYGRkBMClS5dwdHTUeGzYsIGkpKQsg7mcnDt3jkGDBrF161Y2bdqESqVi1KhRxMbGanW+tor7+1Ay/rsZonjTiY2NzczroFWrVjF79myaN2/OlStXmD17NtOnT8fZ2RmVSsVPP/3E9OnTGT9+fLbnly1bVqvO9O/fnzp16jB37lylrFOnTnTu3JlJkyZp+ZQkQzIkQzIkIygoKMe6pKQkpk6dipubGz///DPvvPMOH3/8MQBLlixBR0eHTz/9VKs+7ty5U/n3119/zf79+7l48WKOx5cuXZqvv/6aH374gdu3b1O6dGmmTp3K7t27lT6bmpoyceJEfvzxR27fvs1ff/2lnL9r1y5WrVpFQECAUrZ69WpOnTrFjz/+qJQtXLiQe/fusXr16mz7Ub16dVavXs3HH3/Mo0eP8Pf316g3NjZGrVbj7OzMvn37gOezQ5aWljg5OWn1vQGws7Pj4sWL1KtXL8sMTGFk/Huga2hoyMmTJ5k4cSK///47AP7+/mzfvp0NGzYAz/9Pjhw5go+PD7/88ku2Gbt37+bvv/9m7ty5nD9/Xuu+vZCUlMR7773HihUr+PDDD/M8vlQp7T7fLervQ8n472XExcUVSB/elIMHD77tLuSpS5cub7sLWWj1E+q7775j2bJl7N+/X5mJmjVrFsuWLcPHxwdvb29++OGHfHXk6dOnXL16FXt7e41ye3t7AgMD89W2ZEiGZEiGZPw/X19f3n//fRo0aKBRnpGRwfnz56lSpQpz585l5MiRfPnll1rPOuRFpVLRvHlznjx5QlhYGADW1tbo6upy+/Zt5bj4+HgeP36cZalfTq5evUrLli2xtLQEoF69etSoUSPHP/RLly5Np06diIiIIDIyMttjTExMUKlUqNVqjXJ7e3vCwsK4fv06vr6+lC9fPsd+GRkZ4erqyoMHD7h///5byTA2NkalUhEfHw9A5cqVKV++PGfOnFGOSU1N5cKFCzRq1CjbjGbNmlGtWjV27dqVYz/ykpSUREZGhsZMWH4V9/ehZPx3M0Txp9UAKiQkhFatWgHQsmVLMjMzla8BWrduzT///JOvjqjVatLT05VfgC9YWFgQFRWVr7YlQzIkQzIk47mAgADCw8NxcXHJUhcXF8eTJ0/w8/OjUaNGzJgxA3t7e5YtW/Zasw4v1K5dm6+//poZM2bwwQcf8P3335OUlARAmTJlSE9PJzk5WeOcxMREypQpo1X7a9as4e7du2zevJm9e/eycOFCNm7cyLlz5zSO6969O7t27WL37t00b96cadOm8ezZs2zbXLJkCYGBgRoDjUOHDuHq6krHjh2ZPHkyLVq0ICAgAH19fY1z3dzciIuLIyEhgS5dutCxY8dslze+iYzJkydz48YNZXbvxespJiZG47jo6GgsLCyy/V707duXGzducO3atWzrtTF//nzq1auX5Rq5/CjO70PJ+G9niOJPq23My5Urx8OHD3nnnXd49OgRaWlphISEUL9+fQD++eefLGu4hRBCFC2PHj1i69atzJkzB13drD/+MzOfr+hu3rw5PXv2BODdd9/lzp07HDx4kGbNmr1W7ouldEZGRjRr1owBAwawbt06EhMTX//JvMTJyYn69esza9YsIiIisLOz4+OPPyYiIkJj4Hfs2DECAwMpV64cffv25euvv2bSpEmkpqZqtOft7Y29vT1t27YlIyNDKd++fbvy7ytXrnD+/Hnu3btH9+7d8fPzU+q2bt1KQEAAVlZWTJo0ie3bt9OmTRtSUlIKPeNlkyZNokmTJowYMUIj41WULVuW9u3bs2jRotc6H8DLy4vz58+zZcsW5ZozIUTRINuYvx6tBlDdunXjk08+YeDAgRw8eJDBgwczffp0MjIyKFWqFLNmzdJqTXNuzM3NUalUPH78WKM8Ojo61+ULkiEZkiEZkqGd4OBgEhISmDhxolKWkZHB9evXOXz4MD/++CMqlSrL0rkqVarkaxnfs2fPiImJISYmhpCQED799FOaNWvGiRMnSExMRKVSYWRkpDELVaZMGR48eJBn2/r6+ri6uuLp6cmff/4JwP3796lRowZ9+/bVGEAlJyeTnJxMaGgoN27c4Oeff8be3p6jR48qxyxatIiBAwfSoUMH7t27l2t2WFgYISEh1KxZU6M8Pj6e+Ph4bt++zdmzZ4mOjqZv377KNVqFmfFipmnSpEl07tyZMWPG8OjRI+W8F6+ncuXKER4erpRbWFgQHR2dJb9Hjx5kZGTw22+/5drPnMyfP58DBw7w/fffa70kU1vF9X0oGZIhij+tlvDNmjWLtm3b8uuvv9K0aVOWLFnC0KFDGTZsGAMHDqRcuXLMnDkzXx3R19fH1taW06dPa5SfPn2aJk2a5KttyZAMyZAMyYD33nuPRYsW8e233yoPGxsbWrVqxbfffouuri42NjYaf3DD823NC/IPBx0dHWUGLDQ0lLS0NI2ttk1NTbG0tNRqabiuri56enpZZlgyMjJy/WT1RZ2enp5S5uPjg4uLC46Ojty8eTPPbAsLCypXrqwxEMkuR0dHh9KlS7+xjMmTJ9OlSxfGjh2b5bqoR48eERUVxfvvv6+U6evr06RJEy5dupSl7T59+nD48OHXmi309PTkwIEDbNq0SWOb9IJSXN+HkiEZovjTagbK2NiYpUuXapRNmDCB0aNH8+zZM0xMTAqkMyNGjGDKlCk0bNiQpk2bsm3bNiIjI7Ndqy8ZkiEZkiEZr8bY2Fhj+3B4vqFCmTJlqFq1KgC9evVi8eLF1KtXjwYNGnD16lVOnz7N5MmTs21TX1+fcuXKAc//kDczM6NSpUqkpKTw5MkTWrduzc2bN0lISMDIyIiWLVtiamrKlStXgP/fwKBTp04kJSWRnJxM165diYiI4M6dO8Dz+zxZW1srGRUqVKBGjRokJCQQFRVFUFAQI0aMICUlhcjISOzs7OjQoQMbN24EwMrKitatWxMYGEhcXByWlpYMGDCAZ8+eKddJLV++nCFDhuDs7IxaraZixYrA82uxkpKSMDY2ZubMmezatYuwsDCqV6/OvHnziIyMVJbW2djY4OzszJEjR4iKiqJKlSpMnTqV1NRU9u3b90YyfHx86N69OxMnTiQ+Pl65rik5OVlZQrh161ZGjhzJ/fv3efDgAaNHjyYlJSXLLFPjxo2xsbFhzpw5r/xa8/Dw4Ndff2XFihWYmpoq144YGRlleQ3mR3F8H0qGZBQlsoTv9Wg1gMqJgYEBBgYGhISEMH/+fFauXJmvznTr1g21Ws3q1auJjIykdu3arF27lsqVK+erXcmQDMmQDMnQznvvvcfYsWPx8/Pju+++w8rKik8++STH65+sra0ZOXKk8nX79u1p3749gYGB7Nu3j/Lly9OkSRNlid6jR4/YuHEjERERyjm//fYbGRkZDBgwAF1dXe7du8cvv/yiXJNVq1YtFi5cqBw/dOhQhg4dyuHDh1m8eDFeXl64uroyZcoUTExMiIyMZPPmzfz666/A8yWEL26GaWxsTGxsLFeuXGHixInKDnju7u4AGtujA8yePRsPDw/S09Oxs7Nj6NChmJmZERYWxvHjx3FxcVFmZ1JTU3FwcGDixImYmZkRERHByZMnsbe3JyIi4o1kDBw4EHh+I9uXrVmzBl9fXwA2bdpE6dKl+fLLL5XB7Lhx47Js5OHs7Mzdu3eznZnKy7Zt24Dnf4i+bPz48XzyySev3F5OSsr7UDL+exmieNPqPlB5uXz5Mu3atcuyq88L2t4HSgghRMHI7T5QBenl+0AVlpfvA1VY/n0fqOKqYcOGhZ6Rnx0ZtaXtfaCEKGqK232gisPPvk6dOr3tLmSh1QzUi0+SchISElIgnRFCCCGEEEK8GbKE7/VoNYByd3fHyMgox2/y626PKoQQQgghhBDFiVYDKCsrK7y8vHBycsq2PigoCAcHh4LslxBCCCGEEEIUOVotMm7UqFGu6+l1dHSUi32FEEIIIYQQRd+L2yAU5UdRpNUM1IQJE0hKSsqxvkaNGuzdu7fAOiWEEEIIIYQQRZFWA6hWrVrlWm9sbEzr1q0LpENCCCGEEEIIUVTJPqFCCCGEEEIIoaV83UhXCCGEEEIIUTwV1WuMijqZgRJCCCGEEEIILckMlBBCvOTmzZuFnrF8+fJCz/Dz8yv0DIDw8PA3klMSqFSqQs+wsrIq9IxSpeSzVyHEf5sMoIQQQgghhPgPkiV8r0c+RhJCCCGEEEIILckASgghhBBCCCG0JEv4hBBCCCGE+A+SJXyvR2aghBBCCCGEEEJLMoASQgghhBBCCC3JEj4hhBBCCCH+g2QJ3+uRGSghhBBCCCGE0FKRG0Bt2bKF9u3bY2dnh7OzM3///bdkSIZkSMZbzdi/fz8TJkxg4MCBDBw4kMmTJ/PXX38p9Wq1miVLluDq6kq/fv2YOXMmoaGhubZpY2PD2LFjmTt3LitWrKBly5Y5Huvi4sKKFSvo0KGDRrmJiQnDhg3D09OTxYsX8+WXX9K8eXOl/pNPPmH//v3cuHGDoKAgNm3aRJ06dZR6XV1dvvrqKw4fPsytW7e4cOECK1aswNraWiOnWrVqrF+/nqCgIG7cuMGaNWuwtLQEYOrUqZw9exa1Wk14eDh79uzB1tZW4/yNGzeSnp6u8Th16pTGMb6+vgQHB5OYmEh4eDh+fn7UrVu3RGVMmTKF06dP8/jxYx49eoSfn1+WjPXr1/P06VONx8mTJzWO0dfXx8fHh9DQUNRqNbt27aJy5cpKfYMGDfjmm2/44YcfOHDgAI6OjhrnGxgY4Obmxg8//ICfnx9r166ld+/eSn2ZMmVwc3PD19cXPz8/vv/+e8aPH4+JiQmvqri91yVDMt5khii+tB5ApaSksHnzZsaPH0+/fv0YMGAAkydP5sSJEwXWmQMHDuDp6Ymbmxu7d++mSZMmjB49Os8/RCRDMiRDMgozw8LCAldXV3x8fFi8eDENGzbE09OTe/fukZmZiaenJ6GhoXz11VcsWbKEChUqMGPGDJ48eZJjm6VLlyY0NJSdO3fy9OnTHI9r3Lgx1apVIzY2NkvdsGHDqFSpEr6+vsybN49z584xbNgwbGxsAPjggw/4/vvv6dWrFwMGDCAtLY2ffvoJMzMzAAwNDbGzs2P58uV06dKFkSNHYm1tzZYtW1CpVMoxW7duRUdHhwEDBtC7d2/09PTYtGkTOjo6ODg4sGbNGlq3bo2joyNpaWn4+/tjbm6u0deAgACsra2VR48ePTTqz58/z8iRI7G1taVr167o6Ojg7++Prq5uiclo27Yta9asoV27dnTu3Jm0tDR+++23bDPeeecd5eHk5KRRv2jRIvr06cPQoUP58MMPMTExYffu3ZQq9fxXuoGBAQ8ePMDX1zfb1+Do0aNp0aIF3t7ejB07lp9++okRI0bQvn174Pnr3cLCgo0bN+Lu7s63335LgwYNmDp1apa2clMc3+uSIRlvKqOo0NHRKfKPokgnNjY2M6+D7t69S69evXjy5AmlS5fm0aNHdOrUiejoaAIDA+nZsyfr169HVzf7S6rKli2rVWf69+9PnTp1mDt3rlLWqVMnOnfuzKRJk7R8SpIhGZIhGa+fcfPmTa0yBg8ezLBhw7Czs2PcuHEsXbqUd999F4CMjAyGDx/O0KFD6dSpU5Zzly9frvH1okWL2LFjB3/++adGubm5OZMmTWL58uW4u7vz+++/c+TIEY3zfv75Z86ePauUeXh4cOLECT755JMsuUZGRty4cYNRo0Zx+PDhbJ9XrVq1OH78OB06dODGjRu0bduWLVu20KBBA+Li4oDnM1/Xrl1j8ODB/PzzzxrnGxsbo1arcXZ2Zt++fcDzmRtLS8ssA4Hc2NnZcfHiRerVq0dwcHCJyLhz506WjMePH9OvXz/2798PPJ+BsrCwoE+fPtm2Z2pqSmhoKKNHj2bbtm0AVKlShdu3b9OzZ08yMzV/pf/yyy+sXr2agIAApWzVqlWcOnWKLVu2KGULFizg/v37rF69Otvc5s2bM2vWLPr3788vv/yi1XMv6u91yZCMwsh48XOyuCjIiZDC0q5du7fdhSy0moGaOnUqjo6OBAcHc+XKFWbOnElGRgYBAQGcO3eOCxcu8O233+arI0+fPuXq1avY29trlNvb2xMYGJivtiVDMiRDMgoqIz09nd9//50nT55Qt25dnj17BoCenp5yTKlSpdDT0+PatWuvnVOqVClGjBjBwYMHiYiIyPaYO3fu0KRJE4yNjdHR0cHOzo4yZcpw48aNbI8vU6YMKpUq29msF14s03rxR0Dp0qXJzMwkNTVVOSY1NZWMjAxatGiR7fkqlQq1Wq1Rbm9vT1hYGNevX8fX15fy5cvn2AcjIyNcXV158OAB9+/f/09mhISEcPXqVVavXq2R0bRpU/T19TUGwCEhIdy4cYMPPvggx7687Nq1a7Rs2VJZhlmvXj1q1KjB+fPnc30uz54903gd5KYkvNclQzIKK0MUf1oNoE6dOsUnn3yiTKO5u7tz/PhxYmJisLGxYf78+conYa9LrVaTnp6u/EB/wcLCgqioqHy1LRmSIRmSkd+M+/fvM2DAAPr27cvq1auZNm0a1atXp0qVKpQvX57NmzeTkJDAs2fP+OWXX3j8+HGWP4xfRffu3UlKSuKPP/7I8ZiNGzcCz2cPXlyD9d133/Ho0aNsj/fw8ODKlSs5/qGsp6fHN998g7+/P2FhYcDzJWlJSUlMnz4dQ0NDDA0NmTFjBrq6ulSsWDFLG0uWLCEwMJAzZ84oZYcOHcLV1ZWOHTsyefJkWrRoQUBAAPr6+hrnurm5ERcXR0JCAl26dKFjx47ZLm8sKRmLFy/m4sWLGjOI/v7+jBw5ki5dujBlyhRatGiBv7+/klGpUiXS0tJ4/PixRlsRERHZ/n9kZ82aNdy7d48ffviBX3/9lQULFvDdd99x7ty5bI83NjZm6NChHDx4kIyMDK0yivN7XTIko7AzRPGn1TbmZcuWJSEhQfk6OTmZtLQ05RNXW1vbHD8hFUKIkqBy5cosWbKE5ORkTp06xZIlS/D09KRatWpMmzaN5cuX89FHH1GqVCkaNWpEs2bNsiyn0latWrVo2bIlXl5euR7Xo0cPjI2NWbZsGUlJSTRs2JBhw4axZMmSLMfOnDmTFi1a0KdPn2z/CFapVCxfvhxTU1NGjBihlMfExDB27Fjmz5/P8OHDycjIYM+ePQQFBWVpx9vbG3t7e9q2batRt337duXfLwZw9+7do3v37vj5+Sl1W7duJSAgACsrKyZNmsT27dtp06YNKSkpJSLj5UHUwoULadWqFR9++KFGxo4dOzQyLly4wO3bt+nWrRu7d++mIPTs2ZN69eoxa9YsIiMjadCgAaNGjSIiIiLL4NrAwICZM2cSHR2tDNiFECVHUb3GqKjTagDl4ODAtGnTWLRoEaVLl8bDwwM7Oztlqcc///yT6zIGbZibm6NSqbJ8qhYdHZ3vtiVDMiRDMvKboaenp+xOV7NmTW7fvs2ePXv43//+R82aNVm6dClJSUmkpaVRtmxZvvjiC2rWrPlaWbVq1cLU1JR58+YpZSqVil69euHg4MCMGTOwtLTEwcGB+fPnKzNOjx49wsbGhnbt2rFixQrl3FmzZuHk5ET//v15+PBhljyVSsWqVauoW7cu/fr1yzJz9vvvv2Nvb4+5uTnp6enEx8cTGBjIgwcPlGMWLVrEwIED6dChA/fu3cv1+YWFhRESEpLl+xMfH098fDy3b9/m7NmzREdH07dvX3788ccSkfFipca3337LgAED6NSp0ytnhIeHo6uri6WlpcZrvGLFill2BMyOvr4+rq6uzJ8/X5lxun//PjY2Njg7O2sMoAwMDPDw8ACev4ZeLFfVRnF+r0uGZBR2hij+tFrC5+HhQVpaGvb29rRo0YILFy5oXAQdExPDhAkT8tURfX19bG1tOX36tEb56dOnadKkSb7algzJkAzJKMgMeL5RxL//oDQ2NqZs2bKEhoZy+/btXLcmz83vv//O/Pnz8fLyUh6xsbEcO3ZM+dn7YknXv2eBMjMzNT5RnD17trIL3783MYDnW5mvXr2aevXq0b9//1yXqKjVauLj47G3t8fS0lK5DsfHxwcXFxccHR212oTDwsKCypUrEx4enuMxL3ZfKl26dInKeDFA69y582tlXLhwgadPn2psTV65cmXq1q2rsdwwJyqVCj09vSyvm/T0dGUXP3i+++KcOXMoVaoUM2fOzHVHyeyUlPe6ZEhGYWSI4k+rGajy5ctz+PBh7ty5Q2pqKrVr19bYca9Xr14F0pkRI0YwZcoUGjZsSNOmTdm2bRuRkZG4uLgUSPuSIRmSIRmv4/vvv6d58+ZYWlqSkpLCiRMnuHLlCt988w0Af/zxB6amplSoUIH79++zfv16WrZsmesvW319feXTTB0dHczNzalcuTLJycmo1WoSExM1jn8x8xMZGQk8n4mIjIxk4MCB+Pn5KUv46tSpw9q1awGYN28effv2ZdSoUcTFxSl5SUlJJCcno1Kp8PX1pVGjRri6upKZmakck5CQoPzR/GLw9fjxY5o1a4aHhwfr1q3jzp07LF++nCFDhuDs7IxarVauw0lMTCQpKQljY2NmzpzJrl27CAsLo3r16sybN4/IyEhl2duL2Y8jR44QFRVFlSpVmDp1Kqmpqezbt6/EZCxdupSPPvpImeXLLmPGjBn4+fkRHh5OtWrVmDt3LpGRkcryvfj4eL777js8PT2JjIwkJiaGhQsXcvnyZY4cOUL79u0xMDBQZkt1dHQoX748NWrUICEhgaioKIKCgnB1dSUlJYXIyEjs7Ozo0KGDskTP0NCQuXPnYmRkxJw5czAwMMDAwEB5XWirOL7XJUMy3lRGUSFL+F6PVgOoF17cW+TfQkJCmD9/PitXrsxXZ7p164ZarWb16tVERkZSu3Zt1q5dq3GDwPySDMmQDMl4VWq1msWLF6NWqzE2NqZ69erMnDmTpk2bKvUbN24kNjYWc3NzPvzwQwYOHJhrm9WqVePTTz9Vvu7Rowc9evTg7NmzynKy3GRkZLB69Wp69erF2LFjKV26NFFRUWzZsoUrV64A4OrqCmheVwPPZ0EWL16MlZUVXbp0AZ5vkPCyzz//XDnPxsaGadOmYWZmRkhICMuWLVMGae7u7gAa22TD85kvDw8P0tPTsbOzY+jQoZiZmREWFsbx48dxcXFRBompqak4ODgwceJEzMzMiIiI4OTJk9jb2xMREVFiMsaNGwc83yjiZXPmzGHOrivWiQAAc/dJREFUnDmkp6fToEEDhgwZomScOHGCwYMHawyoJ02aRFpaGlu2bMHQ0JBjx44xcuRIZVapVq1aLFiwQDl+6NChDB06lMOHD+Pj48OCBQtwdXVl8uTJmJiYEBkZyebNm9m7dy/wfIlqvXr1gOfbqr/sVe4FVRzf65IhGW8qQxRvWt0HKi+XL1+mXbt2xMTEZFuv7X2ghBDibdP2PlD58e/7QBWGlzc1KEy5LV8Tml7cnLgwvby0r7AcOHCg0DOEKK6K232gTp48+ba7kKc2bdq87S5kodUMVF5blIeEhBRIZ4QQQgghhBBvhizhez1aDaDc3d0xMjLK8Zus7X0hhBBCCCGEEKI402oAZWVlhZeXF05OTtnWBwUF4eDgUJD9EkIIIYQQQogiR6ttzBs1akRQUFCO9To6Oq99w0ghhBBCCCHEm/fiVgtF+VEUaTUDNWHCBJKSknKsr1GjhrJ7jxBCCCGEEEKUVFoNoFq1apVrvbGxMa1bty6QDgkhhBBCCCFEUfVK94ESQgghhBBClAxFdYlcUafVNVBCCCGEEEIIIWQAJYQQQgghhBBakyV8QogCER4eXugZW7duLfSMlStXFnrG/fv3Cz1DvJrmzZsXesbXX39d6Bk53W5ECCGyI0v4Xo/MQAkhhBBCCCGElmQAJYQQQgghhBBakgGUEEIIIYQQQmhJroESQgghhBDiP0iugXo9MgMlhBBCCCGEEFqSAZQQQgghhBBCaEmW8AkhhBBCCPEfJEv4Xo/MQAkhhBBCCCGElrQaQCUlJfH999/j7u5Ov3796NevH+7u7vzwww8kJSUVaIe2bNlC+/btsbOzw9nZmb///rtA25cMyZCMN5fx448/MmbMGLp27YqTkxNffvkld+/ezfF4b29v2rVrx08//ZTjMZUrV6ZXr16MGTOGiRMnUr9+fY36mjVr4uzsjJubGxMnTqRKlSq59rFPnz5MnDiRWrVqKWVubm74+flx8eJFzp07x9q1a6ldu7ZSr6ury5QpU9i/fz+XL1/mzJkz+Pj4YGVlpdG2i4sLW7ZsITAwkDt37lC5cmWlburUqZw9exa1Wk14eDh79uzB1tZW4/yNGzeSnp6u8Th16pTGMb6+vgQHB5OYmEh4eDh+fn7UrVtXMl4xY/jw4Xz33XccPXqUgwcP4u3tTY0aNfi3jz/+mH379nHixAlWrVrFu+++q1Hv6urK2rVrOX78OH/++WeW81/m6enJ5MmTszw2bNgAQEZGBgcPHsTT05Np06bh6enJwYMHSU9Pz7VdbRW3nyeSIRklLUMUX3kOoG7cuEHz5s2ZPn060dHRVKpUiUqVKhEdHc306dNp0aIFN27cKJDOHDhwAE9PT9zc3Ni9ezdNmjRh9OjRhIaGFkj7kiEZkvFmMy5evEjv3r1ZuXIlPj4+qFQqJk2aRHx8fJZjjx8/zvXr17G0tMy1TX19fR4/fsyxY8d49uxZlno9PT1CQ0M5ceJEnv1r1qwZmZmZWcpbtmzJjz/+yIABAxgyZAjp6en88MMPlC1bFgADAwNsbW1ZtWoVTk5OjB07FisrK7777jtUKpXSjoGBASdPnmTp0qVZMhwcHFizZg2tW7fG0dGRtLQ0/P39MTc31zguICAAa2tr5dGjRw+N+vPnzzNy5EhsbW3p2rUrOjo6+Pv7o6urKxmvkNG0aVN++eUXPv74Y8aPH096ejorVqzA1NRUOX/o0KEMHjyYRYsWMWLECNRqNcuXL8fIyEg5Rl9fn+PHj+f6IcAL//vf/5gxY4by+Oyzz9DR0aFRo0YAHDt2jNOnT9O7d28mT55Mr169OH36NEePHs2z7bwUx58nkiEZJSmjqNDR0Snyj6JIJzY2NutfDy/p0aMH5cuXZ/Xq1RgYGGjUPXnyBHd3dyIjI9m3b1+Obbz4oyMv/fv3p06dOsydO1cp69SpE507d2bSpElatSEZkiEZbycjPDw8z/aTk5Pp3r07c+fOxd7eXuPc8ePHs2jRIqZOnUqfPn1wcXHJcv7WrVs1vv7kk084evQo165dy3KsgYEB7u7u7Nixg5CQkCz1FStWxMnJiR9//JFx48axd+9ebt26xcqVK7Mca2RkxMWLF3Fzc8vxj9eaNWty6NAhunbtSnBwsEadnZ0du3fvpm3btjx69Ij79+9nOd/Y2Bi1Wo2zs7Py83Tjxo1YWlri5OSUbWZ27OzsuHjxIvXq1cvSD8nIOePlgRKAoaEhR44cYcqUKfzxxx8A7N+/n59//plNmzYBULp0aX777TeWL1+On5+fxvnt27dn/vz5tGzZUin7+uuvc+3PkSNHOH78ON988w16enps3LgRIyMjjffCTz/9RHJyMiNHjsy2DW2ff1H/eSIZklFcM+Li4gqkD2/KuXPn3nYX8vTee++97S5kkecM1Pnz55k6dWqWwRM8/wPliy++4Pz58/nuyNOnT7l69arGH1UA9vb2BAYG5rt9yZAMyXj7GSkpKWRkZGBiYqKUpaWl4eHhwdChQ6levXqB5ORFT0+Pbt26cfjwYVJSUvI83tjYGJVKlesvxjJlygBkO7umDRMTE1QqFWq1WqPc3t6esLAwrl+/jq+vL+XLl8+xDSMjI1xdXXnw4EG2gzTJ0D7DyMgIlUpFQkICANbW1lhaWmosy0tNTeXixYvY2dnlmKOtzMxMzp07R9OmTdHT0wOgevXq3Llzh8jISAAiIiK4ffu2suzwdZWUnyeSIRnFNUMUf3kOoMzMzLh9+3aO9Xfu3MHMzCzfHVGr1aSnp2dZvmNhYUFUVFS+25cMyZCMt5+xbNkyatasqXH9ynfffUfZsmXp3bt3gWRow9HRkfv372f7h3N2ZsyYwdWrV3P85amnp8dXX31FQECAVjNx2VmyZAmBgYGcOXNGKTt06BCurq507NiRyZMn06JFCwICAtDX19c4183Njbi4OBISEujSpQsdO3bk6dOnkpGPjIkTJ3Lz5k0uX74MPH8fAMTExGgcFxMTo9TlR3BwMDExMRozVh9++CFNmzbF29ubqVOn4u3tTfPmzWnVqlW+skrKzxPJkIzimlGUvO3lecV1CV+e25gPGzYMd3d3bt26xYcffqh8ohcVFcWxY8dYsmQJ7u7uhd5RIUTxtmLFCi5fvsyKFSuU64QCAwM5ePCgctH8m1CvXj3Kly/Pli1btDr+q6++onnz5gwcOJCMjIws9SqVikWLFmFiYsKYMWNeq0/e3t7Y29vTtm1bjYzt27cr/75y5Qrnz5/n3r17dO/eXWPJ2NatWwkICMDKyopJkyaxfft22rRpozG7Jhm5Z7zs008/pVGjRowZMybb//PCcO7cOd555x2sra2VskuXLnH+/HkGDx5MxYoVCQ0NZc+ePZQrV65ILmkRQoj/ijwHUNOmTcPQ0JA1a9bg4eGhjAQzMzOpWLEiEydO5NNPP813R8zNzVGpVDx+/FijPDo6OtdlGJIhGZJR9DNWrFjBkSNHWLJkicYfiBcvXiQ6OhpnZ2elLD09HV9fX3bu3MnOnTvzlZudqlWrYmFhwYQJEzTKu3fvTlhYmMY1UF9//TU9evTgo48+4p9//snSlkqlYsmSJdSpU4fBgwcTGxv7yv1ZtGgRAwcOpEOHDty7dy/XY8PCwggJCaFmzZoa5fHx8cTHx3P79m3Onj1LdHQ0ffv25ccff5QMLTNebIb02Wef0bFjR9zd3TUuGI+OjgagXLlyREREKOXlypVT6l5XYmIiV69epU+fPhrl+/bto127djRu3BgAKysr1Go1R48ezdcAqrj/PJEMySjuGaL402ob888++4wbN24onxYfPHiQwMBAbty4USCDJ3i+c5GtrS2nT5/WKD99+jRNmjSRDMmQjGKasWzZMo4cOYKPjw/VqlXTqOvduzcbN25k/fr1ysPS0pL+/fuzePHi187MzalTp/jhhx/YvHmz8gD4/fffOXjwoHLcjBkz6NmzJ0OGDMl263VdXV2WLVtG3bp1+eijj7L8stWGj48PLi4uODo6cvPmzTyPt7CwoHLlyrkuE3yx5KF06dKS8YoZEydOpFOnTowfP54HDx5oHBsaGsrjx481Bi76+vo0btxYWeb3uv766y90dXWVgdILz549o1QpzV/TpUqVynbnyFdRnH+eSIZklISMouRtL88rsUv4Xla9evVCvch7xIgRTJkyhYYNG9K0aVO2bdtGZGRktrtxSYZkSEbRz/Dx8cHf35958+ZhYmKifFJvaGiIkZER5ubmWbai1tXVpVy5clStWjXbNvX09JTrLnV0dDA1NaV8+fI8efKEhIQEDAwMMDExUf4oNjMzIzU1laSkJJKTk0lMTCQxMTFLuwkJCcomEbNmzaJ3796MGzeOuLg4ZS18cnIyycnJqFQqVqxYgZ2dHWPGjCEzM1M5JiEhgdTUVAAsLS0pX7688nOzVq1amJqaEhcXh4eHB0OGDMHZ2Rm1Wk3FihWB57MRSUlJGBsbM3PmTHbt2kVYWBjVq1dn3rx5REZGKkvSbGxscHZ25siRI0RFRVGlShWmTp1Kamoq+/btY/ny5ZKhZcayZcvo2rUrkydPJj4+nnLlygHPNz55sYTwp59+UjaeePjwISNHjiQ5OZlDhw4pr6OKFStiamqq3BPsxf3FstsJEv5/84hGjRopr9kX6tWrx7FjxyhXrhwVK1bk0aNH/P777zRr1izbtl5Fcfx5IhmSUZIyRPGm1QAqNjaWP//8EzMzM9577z2N0WBSUhIrVqxg6tSp+e5Mt27dUKvVrF69msjISGrXrs3atWs1bj4pGZIhGcUnY/fu3QB8/vnnGuWurq6MGDHitdqsWLEiAwYMUL5u1aoVrVq14urVqxw6dIgaNWrQpUsXpb5Tp04AnDlzRmPTgdwMHToUQFk69sLSpUtZtmwZlSpVomPHjgD8+uuvGsdMmTKFX375BYDBgwdrzNK/uNZr5MiRyrWjAQEBGufPnj0bDw8P0tPTsbOzY+jQoZiZmREW9n/t3XlczPnjB/BXSlSkFBWpkERyRDkSlnIV2lxZ1s26Nr4suRMSu6F1J0fsYlv3uXIsNgobWcvmKLeOqUw3uub3h4f5GVPNVFNNeT0fj3k8+Hw+8369P828PzPv+bw/708cLl++DHd3d3EH8P379+jRowdmz54NHR0dJCQkIDQ0FPb29khISGBGMTKGDBkCANiyZYtERmBgIHbs2AEA+OWXX1CjRg3MnTsXtWvXxv379+Hh4YGsrCzx9pMnT5a4/9TH99DUqVNRkJiYGCQlJWHEiBFS61xdXRESEoIjR44gIyMD2tra6NixIxwdHQssqzgq4/GEGcyoShlUucm8D1RUVBRcXV2RlJSE/Px8tGnTBnv37hX/OiwQCGBpaSk1M9Gn5L0PFBFVXiWdfa44Pr8PVFko6D5Qiibv7H9Ufjp06FDmGbLuA6UIxbkPFhEpXmW7D1RERERFV0Gm8jg+F5fMa6C8vb1ha2uLFy9eICoqCmZmZujbty9iYmLKo35ERERERFQGKvr6psp6DZTMDlRERAQWLVoELS0tGBoaIigoCK6urnBxcSny/lBERERERERVjcxroLKzs6V6f6tWrYJIJIKLiwsCAwPLrHJERERERETKRGYHytzcHJGRkbC0tJRY7uvri/z8fIwcObLMKkdERERERGVDWYfIKTuZQ/hcXFzEM0p9bs2aNRg2bFip70lBRERERERUGcjsQM2ePRuHDh0qdL2fnx+EQqFCK0VERERERKSMinUjXSIiIiIiqho4hK9kZJ6BIiIiIiIiog/YgSIiIiIiIpITh/ARVbCEhIQyz7h//36ZZ3z//fdlnvHgwYMyz6Di6dixY5lnzJ07t8wzBg0aVOYZ1arxN0siUi4cwlcyPJoTERERERHJiR0oIiIiIiIiOXEIHxERERHRF4hD+EqGZ6CIiIiIiIjkxA4UERERERGRnNiBIiIiIiIikhOvgSIiIiIi+gLxGqiS4RkoIiIiIiIiOZW6AyUQCLBmzRpF1AUAsG/fPvTs2RPW1tZwc3NDRESEwspmBjMqS8avv/6KyZMno2/fvhgwYADmz5+PJ0+eSGyzY8cOjBo1Cr1790b//v0xa9Ys/Pvvv8XKSU1NRVBQEObOnYvvv/8e3t7eePTokcQ2CQkJCAgIwOzZs+Hh4YFVq1YhLi5OqqyJEyciODgYN27cQGhoKDZv3gxzc3OJbRwdHbF9+3aEhobi/v37sLW1lSrH29sbf/zxB27duoXQ0FBs3LgRTZo0Ea/39PTE9evXIRQKER8fj+PHj8PKykqijF27diEvL0/ice3aNYltAgIC8OjRI2RkZCA+Ph5Hjx6FpaUlM4qZ0bZtW6xZswbHjx9HWFgY+vfvL/FcXV1dLFq0CMePH8eff/6JdevWwdjYWGKbunXrYunSpTh58iT+/PNP7NmzB71790Zh8vPzce7cOaxZswaLFy/GmjVrEBISgry8PPE29+7dw86dO7FixQrMnz8fMTExhZYnr+3bt2Po0KHo0KEDunTpgqlTp0q1F0WpbMcsZjCDGfQlKXUHKiEhQWEdqDNnzmDVqlWYMmUKjh07hnbt2mHSpEmIjY1VSPnMYEZlyYiMjISrqyu2bNkCf39/qKqqYvbs2UhLSxNvY2Jigv/9738ICgrC5s2bYWRkhLlz5+LNmzdyZWRlZeGnn34CAEyfPh1eXl4YPnw4ateuLd4mKSkJfn5+0NPTw6xZs7BkyRIMHDgQNWrUkCrPzs4OBw4cwMiRIzF+/Hjk5uZi586dqFOnjngbDQ0NREZG4scffyy0Xvfu3cOiRYswYMAATJ48GSoqKtixYwfU1D6MOO7Rowe2bduGrl27wtHREbm5uTh37hx0dXUlyrlw4QIaNGggfri4uEisv3XrFsaPHw8rKyv069cPKioqOHfuHNTU1JhRjAwNDQ08efIE/v7+ePfundTruWbNGjRq1Ajz58/H2LFjER8fjw0bNqBmzZribZYuXQpTU1N4enpi1KhROHv2LJYuXYq2bdtKlQcAV65cQXh4OAYMGIDZs2djwIABCA8Px+XLl8XbZGdnw9TUFM7OzgWWURI3b97EiBEjsH//fgQFBUFVVRUTJkxASkqKwjKAynnMYgYzmFE5qaioKP1DGamkpKSIitrg818iPxcTE4NZs2YV+aXt0y9QRRk6dCiaN2+OlStXipf17t0bffr0wZw5c+QqgxnMqGwZCQkJMsvPyspC//794ePjA3t7+wK3yczMRL9+/eDn5wc7OzuJdffv35fa/tixY3j8+DHmzp1baO7OnTuhoqKC8ePHy6zj999/L/F/TU1NXL9+HR4eHhJfbAFAR0cH165dw9ixY/H3338XWa6FhQWOHj0KZ2dnnD17Vmq9lpYWhEIh3NzccOrUKQAfzqro6+tj4MCBMuv9kbW1Ne7cuYMWLVpInVVgRuEZn3bGLly4gHXr1uHMmTMAgEaNGiE4OBijR49GdHQ0gA8f1qdOncK2bdtw8uRJ8fPWr1+P06dPi8s6cuQIDh48iAMHDki9R4OCgqCpqYlhw4aJl/3+++/IysrC2LFjJbbNzMzEihUrMGnSJDRt2rTQfRo0aJDc+/9p2XZ2dti0aRO++uormdtXqybfb5bKfsxiBjOYUbjU1FSF1KG8FHfkSkWwtrau6CpIkXk0d3FxwYABA+Di4lLgY+bMmQqpSHZ2Nu7fvy/15dDe3h6RkZHMYMYXnZGVlYX8/HyJs0OfysnJwYkTJ6ClpSU1bK4w//zzDxo3bowdO3Zg7ty58PHxweXLlyESffhNJT8/H//++y+MjIywceNGzJ07F6tXr5Z7GIOmpiZUVVUlzpoVl4aGBr7++mvExsbi9evXBW5Tu3ZtqKqqQigUSiy3t7dHXFwcoqKiEBAQgHr16hVZ17Fjx+L58+d49uwZM0qR8anq1asD+NBGPhKJRMjOzkbr1q3Fy+7evYuePXtCW1sbKioqcHBwgI6OTqHvNTMzM8TExEAgEAD48CNETEwMmjdvXmR9FC0zMxP5+fnQ1tZWWJlV5ZjFDGYwg6oymR0oPT09bNu2DTExMQU+Tpw4oZCKCIVC5OXlQV9fXyo/MTGRGcz4ojM2btyIZs2aSV2/EhYWhj59+sDR0REHDx7E2rVrUbduXbnKTEpKwpUrV6Cvrw8PDw989dVXOHbsGK5cuQIASE9Px/v373H27Fm0aNECHh4e6NChA3bv3i3XL1YLFixAVFQU7ty5U+z9dXd3x99//42IiAh07doVEyZMQE5OToHb+vv7IzIyEuHh4eJlISEhGDt2LJycnDB37lzY2triwoULUFdXl3julClTkJqaivT0dPTt2xdOTk4SX/aZUfyMTz1//hzx8fH47rvvULt2baipqWHUqFEwMDCQaC+LFy+GSCTC2bNnceXKFXh5ecHLywuPHz8usNzu3bvDxsYG69evx8KFC7F+/XrY2Nigc+fORdZH0Xx9fdGiRYtChxqWRFU5ZjGDGcyoHCp6eF5lHcIncxrzNm3a4NmzZ4V+KdPR0RH/Yk1Eirdp0ybcvXsXmzdvhqqqqsS6du3aYefOnUhNTcXJkyexbNkybNmyRerAXxCRSARTU1O4uroC+DDcSiAQ4MqVK+jRo4e4Xbdu3RqOjo7ibZ4/f47Lly8XeUp93rx5sLGxwbfffov8/Pxi7/OpU6cQFhaGevXqYdy4cVi3bh1GjRoltZ2fnx/s7e3RrVs3iZzg4GDxv+/du4dbt27h6dOncHZ2xtGjR8Xr9u/fjwsXLsDIyAhz5sxBcHAwHBwc8PbtW2bImVGUvLw8LFiwAAsWLEBISAhyc3MRERGBsLAwiQ/F7777Djo6Ovj++++RmpqKbt26YcmSJZg2bZp46N+n7t69i9u3b8Pd3R0GBgaIjY3FyZMnUbdu3QInJikLq1evxq1bt7Bv3z6pdklERFWbzA7U2LFjkZWVVej6Ro0aYfPmzaWuiK6uLlRVVZGUlCSxPDk5ucjhJMxgRlXO2LhxIy5evIiff/4ZDRo0kFqvoaEBY2NjGBsbw8rKCiNGjMDp06cxZswYmWXXqVMHhoaGEsuMjIxw6dIlAECtWrVQrVo1GBkZSW1T1DA+T09P9OvXD+PGjcOrV6/k2U0pGRkZyMjIwIsXL3D37l2EhYXByclJ4mzW2rVrMXz4cPTq1QtPnz4tsry4uDi8evVKanhjWloa0tLSEB0djevXryM5ORmDBw/Gr7/+ygw5Mwo7S/TRw4cPMXbsWGhpaaF69epISUlBYGAgHjx4AABo2LAhhg4dKnGdVHR0NNq0aYMhQ4Zg9erVUmWeOXMGDg4OaNOmDQDA0NAQQqEQly9fLpcOlK+vL86cOYM9e/agUaNGCi27sh+zmMEMZtCXQOYQvgEDBmD48OGFrtfR0cE333xT6oqoq6vDysoKYWFhEsvDwsLQrl27UpfPDGZUtoyff/4ZFy9ehL+/P0xNTeV6zsfrS+TRpEkTqQksEhISxGeb1dTUYGZmVuQ2n5s/fz769++P8ePHy/yiXhwqKioSQ8rWr18Pd3d3ODo64uHDhzKfr6enh4YNGyI+Pr7IDBUVFfEMg8yQP0MemZmZSElJgbGxMSwtLREaGgoA4jI+P1OZn59f6KQLOTk5UuuqVatWLqMhVq1ahTNnziAoKEhien1FqczHLGYwgxmVT0UPz6uyQ/jK07hx4zBv3jy0bt0aNjY2OHDgAAQCAdzd3ZnBjC8qY926dTh37hx8fHxQu3ZtJCcnA/hwxklTUxOZmZnYv38/7O3toaenh5SUFBw9ehSJiYno2bOnXBm9evXCTz/9hD/++APt27fHy5cvcenSJYnZyJycnLBjxw6Ym5ujefPmePToESIiIjBlyhSp8hYvXowBAwbAw8MDaWlp4mGEWVlZ4rPYderUgZGRkXgyDBMTE6SnpyMpKQlJSUkwMTGBk5MTwsPDIRQKYWBggIkTJyI7O1t8bdbGjRsxatQouLm5ibcBPpy1yszMhJaWFry8vHDkyBHExcXBzMwMPj4+EAgE4iFpTZs2hZubGy5evIjExEQYGxvD09MT79+/x6lTp5hRjIwWLVqI7+tUrVo1GBgYoFmzZkhLS0NCQgK++uorpKamIj4+Hk2bNsWsWbPw119/4ebNmwA+XCf18uVL/PDDD9i4cSPS0tLQrVs32NrawtPTs8D3rqWlJS5fvoy6deuifv36iI2NxdWrVyW+3GRlZSElJUU8jDE5ORkaGhqoXbt2oZOxyLJ8+XKcOHECmzZtgra2tvh6CE1NTWhpaZWozIJUxmMWM5jBDPqSyJzGHABSUlJw48YN6OjowM7OTqI3mJmZiU2bNhX6QQfIP4058OHGZTt37oRAIICFhQUWLFig8CEZzGCGMmUUNI15t27dCtx27NixGD9+PN69e4cVK1bgv//+Q1paGrS1tWFpaYlvv/0WLVu2lHpeQdOYAx+mLz1+/Lj4rFL37t3x1VdfSbTx8PBwnD17FkKhEPXr10efPn0K3K/COm6bN2/Gli1bAACurq7w8fEpdBtDQ0MsW7YMLVu2hLa2NpKSknDr1i1s27YNT58+xYMHDyRulvopb29vLF++HDVr1sTRo0fRtm1b6OjoIC4uDpcvX8bSpUvFQwqNjY0REBAAGxsb6OjoICEhAaGhoVi5ciUePnzIjGJkTJkypcBh3KdPn4aPjw+GDh2Kb775BnXr1kVycjL++OMP7N69G7m5ueJtjY2NMXXqVLRp0wYaGhp49eoVfvvtN/zxxx8AIDWN+fv373Hu3Dncv38fGRkZ0NbWRuvWrdGrVy/xzH8RERE4dOiQVL169eoFJycnqeXyTGPeokWLApdPnz4dM2bMkPl8eacxB5T7mMUMZjCjcJVtGvPCvh8ok88n0FIGMjtQUVFRcHV1RVJSEvLz89GmTRvs3bsXJiYmAACBQABLS0uF3AeK6Eskz32gSqs8DpCf3weqLHy8boaUR8eOHcs8o6h7lSlKSe4DVVzF6UARUeVU2TpQ//33X0VXQaaCfhiuaDKP5t7e3rC1tcWLFy8QFRUFMzMz9O3bFzExMeVRPyIiIiIiIqUhswMVERGBRYsWQUtLC4aGhggKCoKrqytcXFwKnF6WiIiIiIioqpI5iUR2drbUDBirVq2CSCSCi4sLAgMDy6xyREREREREykRmB8rc3ByRkZGwtLSUWO7r64v8/HyMHDmyzCpHRERERERlQ1mnCVd2Mofwubi44PDhwwWuW7NmDYYNG1Yu994gIiIiIiKqaDI7ULNnzy5wKtiP/Pz8IBQKFVopIiIiIiIiZaRUN9IlIiIiIqLywSF8JcObUhAREREREcmJHSgiIiIiIiI5cQgfVVpv3rwp84zvvvuuzDPu3LlT5hlPnjwp8wySX5cuXco8Y86cOWWeAQB9+vQp8wwNDY0yzyAi+hJxCF/J8AwUERERERGRnNiBIiIiIiIikhOH8BERERERfYE4hK9keAaKiIiIiIhITuxAERERERERyYlD+IiIiIiIvkAcwlcyPANFREREREQkJ3agiIiIiIiI5CRXByo/Px9RUVGIi4uTWvfu3TscOHBAYRXat28fevbsCWtra7i5uSEiIkJhZTOj6mdERkZi7ty5GDBgADp37ozTp09LrM/KysLatWsxcOBAdO/eHcOHD5f5/m3RogU8PT0REBCAgwcPokePHhLrDx48WOBjwoQJ4m3s7OywaNEi7Ny5EwcPHkTLli3F67777jscPnwYkZGRuHHjBgICAtCsWTOJjN69e2PXrl24ceMGHj9+DDs7O6l6mpiYYPPmzbhx4wYiIyPx888/Q09PDwDg6emJ69evQygUIj4+HsePH4eVlZXE83ft2oW8vDyJx7Vr1yS2CQgIwKNHj5CRkYH4+HgcPXoUlpaW5ZZRlfalTZs28PX1xZEjRxAaGop+/fpJPFdXVxcLFy7E0aNHcf78efj5+cHY2Fhimw0bNiA0NFTisWzZMhQmPz8fISEhWL16NRYtWoTVq1cjJCQEeXl54m1EIhHOnz+PlStXYtGiRQgICEB8fHyhZcorMzMTP/74I/r164eOHTti9OjRuHfvXqnL/VxlO2YxgxnM+HIzlIGKiorSP5SRzA7Uq1evYG9vjy5dusDKygojR45ESkqKeH1aWhqmT5+ukMqcOXMGq1atwpQpU3Ds2DG0a9cOkyZNQmxsrELKZ0bVz3j79i2aNGmC//3vf6hRo4bU+g0bNiAsLAxeXl747bffMGbMGGzduhV//PFHoWXWrFkTL168wO7du/H+/Xup9ZMmTZJ4+Pr6AgDCw8Mlynj48CH27Nkj9fyOHTti//79GDZsGL799lvk5uZiz549qFOnjngbDQ0N3L59G6tWrSqwjhoaGti9ezdUVFTw7bffYvjw4ahevToCAgKgoqKCHj16YNu2bejatSscHR2Rm5uLc+fOQVdXV6KcCxcuoEGDBuKHi4uLxPpbt25h/PjxsLKyQr9+/aCiooJz585BTU2tXDIAVIl9UVVVhYaGBp4+fYoNGzbg3bt3Uq/pqlWrYGxsjIULF2L8+PGIj4/H+vXrUbNmTYntTp8+jUGDBokfP/30k1RZH12+fBnh4eEYOHAg5syZg4EDByI8PByXLl0Sb3PlyhX89ddfGDRoEL7//ntoaWlhx44dBb73i8Pb2xvh4eFYvnw5Dh48iM6dO2PKlClISEgoVbmfqozHLGYwgxlfZgZVbiopKSmiojaYNGkSXr16BX9/f6SlpWHx4sVIT0/HiRMnoK+vD4FAAEtLS7x586bQMj79IliUoUOHonnz5li5cqV4We/evdGnTx/MmTNHzl1ixpeSUdR7DgB69uyJOXPmwNnZWbxs5MiR6NGjByZNmiReNnXqVDRt2hQ//PCDVBnfffedxP9/+eUX7Ny5E5cvXy4097vvvkPLli0xc+ZMqXW1a9fGrl274OXlhf/++w8AcOfOHYltNDU1cfv2bUybNg1//vmnxDpdXV3cvHkTI0eOxM2bN8XLu3btip07d8LW1hZpaWkAgFq1auHWrVsYN24cfv31V4lytLS0IBQK4ebmhlOnTgH4cEZFX18fAwcOLHTfPmdtbY07d+6gRYsWePToUblnVNZ9+eabb/Dy5Uvx8pCQEPj7+4s78o0aNcL+/fsxduxYxMTEAPjwK+Hx48exfft2cR02bNiAJ0+ewN/fXyqroPaze/duaGpqYvjw4eJlwcHByMrKwrhx4yASieDj44MuXbqgZ8+eAICcnBwsX74czs7O6NSpk1SZffr0kbnf7969g729Pfz8/PDVV1+Jl48YMQL29vaYMWNGkc/X0NCQmQEo/zGLGcxgRtXPSE1NVUgdykt0dHRFV0Emc3NzqWW+vr5Ys2aNxLL69euLP79FIhFWr16NPXv2ICUlBe3bt4efnx9atGihkDrJPAMVGhqKVatWoXnz5rC1tcWpU6dgYWEBZ2dnJCYmKqQSAJCdnY379+/D3t5eYrm9vT0iIyOZwQyFaN26Na5evSr+1fvu3bt4/PhxgV8MS6JmzZqwt7fHhQsXSlyGlpYWVFVVi3UQVldXh0gkkjhLkJ2djfz8fLRv315q+9q1a0NVVRVCoVBiub29PeLi4hAVFYWAgADUq1ev0ExNTU2MHTsWz58/x7Nnzyoko7Lui6whcdWrVwfw4TX8SCQSITs7G61bt5bYtlevXjh58iT27t2LadOmFdnZMDMzQ0xMDAQCAQAgISEBMTEx4mGFb968QXp6usQQ0urVq6NJkyZ4/vx5kXUuyschjp+fFa5Ro0alOp4wgxnMYAYpj2bNmuHhw4fiR1hYmHjdzz//jM2bN2PNmjX4888/Ua9ePXz99ddIT09XSLbMDlR6ejq0tbXF/69evTp27twJS0tLODs7K2RsPAAIhULk5eVBX19fYrmenp7COmrM+PIyPjd79mw0a9YMrq6u6Nq1K6ZNm4Zp06aha9euCim/a9euUFNTw5UrV0pcxuLFi/Hff/8V60B9584dZGVlwdPTExoaGtDQ0ICnpyfU1NRQv359qe39/f0RGRkpMcwwJCQEY8eOhZOTE+bOnQtbW1tcuHAB6urqEs+dMmUKUlNTkZ6ejr59+8LJyUnii355ZlTWfcnJySlwXz762MmaPHkyateuDTU1NXzzzTcwMDAQX9cGAOfPn8eKFSswc+ZM7NmzB927d5f4xfRzPXr0gI2NDdatW4cFCxZg3bp1aN++PTp37gwA4g+WWrVqSTyvVq1apfrQ0dLSQuvWrREYGIiEhATk5eXh9OnTuHv3LpKSkkpc7qeqyjGLGcxgRtXPUCYVfX1Taa6BUlNTg4GBgfjx8TUTiUTYunUrZs2ahUGDBqFly5bYunUrMjIycOjQIYX83WR2oMzMzKQu9FVVVcWuXbvQvHlzjBgxQiEVISoPBw8exL///osff/wRQUFBmDlzJjZt2iTxxbg0evXqhb///ls8jK64FixYgPbt22PGjBnIz8+X+3lv3ryBh4cHunfvjjt37uD27dvQ1tbGvXv3pMrx8/ODvb09hg4dKrEuODgYJ0+exL1793Dq1Ck4OzujefPmEkMgAWD//v1o3749evTogcePHyM4OFjqrEd5ZFTmfSno+rxP5eXlYdGiRWjYsCHOnDmD8+fPw8bGBuHh4RJ1OHnyJG7evIknT57g4sWLWLZsGezs7GBhYVFguf/88w9u374Nd3d3eHh4YPjw4QgPD5cYDlpWfHx8UK1aNfTp0wd2dnbYv38/+vbti2rVOBksEREV37Nnz2BpaYnWrVtj/Pjx4hEkz58/R0JCgngoOvBhKHiXLl1w48YNhWTLvJGuo6Mj9uzZg0GDBkksV1VVxe7duzF69OgCZ+crLl1dXaiqqkr9GpmcnFzksBhmMENe7969w9atW+Hj4wMHBwcAH8bVPn78GPv37xf/Cl9SZmZmMDc3L/GslAsXLoSzszO+/fZbietj5HX16lX06tULurq6yM3NRXp6OsLCwiTKWrt2LYYPH45evXrh6dOnRZYXFxeHV69eSY09TktLQ1paGqKjo3H9+nUkJydj8ODB4uusyiOjsu9Ljx49EBISUmR5jx49wvjx46GlpYXq1asjJSUFAQEBePDgQaHPefDgAXJzc6Vm6/vozJkz6NatG9q2bQsAMDIyglAoxOXLl2FnZ4fatWsDADIyMiQmzMjIyBCvK6lGjRph586dePv2LTIyMlCvXj3MmzcPDRs2LFW5H1WVYxYzmMGMqp9BpdehQwds2bIFzZo1Q1JSEn766Sf07t0b169fF1+m8fnrVa9ePYX0WQA5zkAtWbIEQUFBBa5TU1PDL7/8InURfEmoq6vDyspKYvwiAISFhaFdu3alLp8ZX2bGp/Ly8pCbmyv1i3e1atUgEhU5l4pcHB0dkZCQgLt37xb7uYsXL4aLiwtGjx6NJ0+elKoeQqEQ6enp6NSpE/T09HDx4kUAwPr16+Hu7g5HR0c8fPhQZjl6enpo2LBhkcN0P55e/3hGpTwyqsK+fLzGSR6ZmZlISUmBsbExmjdvjqtXrxa6bZMmTaCmpobk5OQC1+fk5BT5/q9bty5q166Nx48fSzzn6dOnMDU1lbvORdHQ0EC9evWQlpaGsLAwqdsClFRVOWYxgxnMqPoZyqSih+eVdAifk5MTvv76a7Rq1Qo9evRAcHAw8vPzsX///nL5u8k8A6WmpiZxDdTnVFVVYWJiopDKjBs3DvPmzUPr1q1hY2ODAwcOQCAQwN3dXSHlM6PqZ2RlZeHVq1cAPtzzJj4+Ho8ePYK2tjYMDQ3Rrl07bN26FZqamjA0NERkZCT++OOPImcBq1mzJgwNDQF8ONDo6+vDzMwMGRkZ4l+o1NXV4eDggOPHjxdYRq1ataCvrw9NTU0AgKGhIbKyspCSkgIvLy+4urpi6tSpSE1NFY/hzcrKQlZWFoAPM1k2aNBAfBbA1NQU6enpSExMFNdh8ODBiImJwZs3b9C2bVssXrwYu3fvxtOnT7Fx40aMGjUKbm5uEAqFMDAwAPDhzEJmZia0tLTg5eWFI0eOIC4uDmZmZvDx8YFAIMDRo0cBAE2bNoWbmxsuXryIxMREGBsbw9PTE+/fv8epU6fKJQNAldiXsLAwaGhoiM++VKtWDQYGBjA3N0daWhoEAgF69OiB1NRUxMfHo2nTpvDw8EBoaCj+/vtvAECDBg3Qu3dvhIeHIzU1FWZmZpg+fToePXqEf//9F46OjlLvwxYtWuDSpUvQ1dWFgYEBYmNjERoaChsbG/H7u2vXrvjzzz9Rv3596Ovr4+LFi1BXVy/1F4ewsDDk5+ejcePGePHiBdavX4/GjRtLjW4ojcp4zGIGM5jxZWaQYtWqVQuWlpZ48uSJ+JYiiYmJaNSokXibxMTEAq8LLwmZHSgASElJwY0bN6CjowM7OzuJ3mBmZiY2bdoET0/PUlemf//+EAqF2Lp1KwQCASwsLLB9+3aFDfFgRtXPePDggcR9yXbs2IEdO3agf//+WLJkCVasWIGtW7fCy8sLaWlpMDQ0xOTJkzFkyJBCy2zSpAm8vb3F/x8+fDiGDx+Oy5cvY/PmzQCALl26oEaNGhL30/lUhw4dJOo1depUAMDvv/+OYcOGAfgwRfqnNmzYgI0bNwL4cG3Vp9N1frwf1KfbNG7cGHPmzEGdOnXw+vVrbN26Fbt37wYATJs2DQCkZgf09vbG8uXLkZeXB2tra3z77bfQ0dFBXFwcLl++DHd3d2RkZAAA3r9/jx49emD27NnQ0dFBQkICQkNDYW9vj4SEhHLJqCr7oqenh7Zt24pfOwCYMGECJkyYgD/++AOrVq2Cnp4eZsyYgbp16yI5ORlnz56VuI9Ybm4u2rdvjyFDhkBDQwMCgQDh4eHYvXt3odfPDRo0CCEhITh27BgyMjKgra0NOzs79OrVS7xN9+7dkZOTg2PHjuHt27do1KgRJk6cKPO6LVnS09OxceNGJCQkoE6dOujVqxdmzJhRrLNxslTGYxYzmMGMLzODFOvdu3d4/PgxHBwcYGpqCgMDA1y6dEn8A+G7d+/E9yJUBJn3gYqKioKrqyuSkpKQn5+PNm3aYO/eveKzToq8DxRRcci6D5QifH4fqLKgiCGwspR2WCApVpcuXco8Q1H3Q5FFnvtAlZa894EiIqpole0+ULKu71UGjRs3llq2ePFi9O3bF8bGxuJroMLCwnDt2jWYmJjA398f69atw6ZNm2Bubg4/Pz+EhYXh77//LvU1vYAc10B5e3vD1tYWL168QFRUFMzMzNC3b1/xzR2JiIiIiIjKS2xsLCZOnAhbW1t8++23UFdXx/nz58UneGbOnImpU6di7ty5+OqrrxAfH48jR44opPMEyDGELyIiAidPnoSWlha0tLQQFBSEhQsXwsXFBSdPnizy+igiIiIiIiJF2rVrV5HrVVRUsGDBAixYsKBM8mV2oLKzs6VmwFi1ahVEIhFcXFwQGBhYJhUjIiIiIqKyU9SNaqlwMjtQ5ubmiIyMhKWlpcRyX19f5OfnY+TIkWVWOSIiIiIiImUi8xooFxcXHD58uMB1a9aswbBhwxRyDx0iIiIiIiJlJ7MDNXv2bBw6dKjQ9X5+fhAKhQqtFBERERERla2KvkluSW+kW9FkdqCIiIiIiIjoA3agiIiIiIiI5MQOFBERERERkZxkzsJHVc+NGzfKPOOnn34q84ybN2+Wecbr16/LPIPkp6GhUeYZM2fOLPOMhQsXlnmGlpZWmWcQEVHlpqzXGCk7noEiIiIiIiKSEztQREREREREcuIQPiIiIiKiLxCH8JUMz0ARERERERHJiR0oIiIiIiIiOXEIHxERERHRF4hD+EqGZ6CIiIiIiIjkxA4UERERERGRnOTqQCUlJeHSpUtISkoCAAgEAvj5+cHHxwf//fefQiu0b98+9OzZE9bW1nBzc0NERIRCy2dGwY4cOYLRo0dLPL7//nvx+u3bt0ut9/b2LrLMFi1awNPTEwEBATh06BB69Oghsf7QoUMFPiZOnAgAUFVVxahRo7B27Vr8+uuvCAwMxMyZM6Gvrw8AmD59Ok6ePIn79+8jMjISu3btgoWFhbh8NTU1LFiwACEhIXjw4AEiIiKwYcMGNGjQQKqubdq0wb59+xAVFYX//vsPR44cga6uLjw9PXH9+nUIhULEx8fj+PHjsLKyknjurl27kJeXJ/G4du2axDYBAQF49OgRMjIyEB8fj6NHj8LS0hIAmFGMDACYM2cOrly5gtjYWDx79gy///47WrZsKfWafrRhwwZkZGTAw8Oj0G2OHDmCjIwMuLq6AgDMzMwwatQoeHp6wsfHB+3atZPY3tHREbNmzYKXlxcWL16M8ePHw8TERGIbV1dXzJ49G8uWLcPChQsxatQo1KtXr9A6AMCtW7cwa9Ys9OnTBzY2Njhx4oTE+osXL2LatGno2bMnbGxsFHpcqWzHLGYwgxnMqOwZykBFRUXpH8pIZgfq5s2bsLGxgZubG9q3b4/IyEg4OjriwIEDOHToEHr27InIyEiFVObMmTNYtWoVpkyZgmPHjqFdu3aYNGkSYmNjFVI+M4pmZGSEDRs2iB8+Pj4S662srCTWz5kzp8jyatasiZcvX2L37t14//691PqJEydKPHx9fQEAYWFhAIAaNWqgcePGOHz4MObNm4c1a9ZAX18fixYtQrVq1dCpUyfs3bsXX3/9Ndzd3ZGbm4v9+/ejTp06AAANDQ20atUKmzZtQv/+/TFhwgQ0aNAAv/zyC1RVVcX1aNu2LX799VeEh4dj0KBBcHZ2xvbt25Gbm4sePXpg27Zt6Nq1KxwdHZGbm4tz585BV1dXYl8uXLiABg0aiB8uLi4S62/duoXx48fDysoK/fr1g4qKCs6dOwc1NTVmFCMDABwcHBAYGAhHR0c4OzsjLy8PJ0+elMoBPnRi2rdvX2S78PDwQH5+vsQydXV1JCQk4NSpU8jOzpZ6TmJiIk6cOIENGzZg+/btEAqFGDNmDLS0tMTbvH79GocPH4a/vz+CgoIAAOPHj0e1aoUfdt++fYumTZti7ty5qFmzZoHr27Rpg9mzZxdaRklU1mMWM5jBDGZU1gyq3FRSUlJERW0waNAgmJqawsfHB0FBQdi2bRt69eqFDRs2APhwFiAlJQX79u0rtIyPX2hlGTp0KJo3b46VK1eKl/Xu3Rt9+vSR+WVdXswAbty4IbXsyJEj+Pvvv8WdmM9t374d6enpctf/p59+kvj/L7/8gp07d+Ly5cuFPmfKlClo0aIFZs6cWeg2xsbG8Pf3x+zZs3Ho0CGJdZqamrh//z4mTZqECxcuFPj8Zs2a4eLFi3BycsLDhw8BfNj38PBwqToDH74Ef0pLSwtCoRBubm44deoUgA9nVfT19TFw4MBC6/05a2tr3LlzBy1atMCjR4+YIWfGy5cvpdZraWkhNjYW7u7u+OOPP8TLGzVqhIsXL2LAgAE4cuQIAgICxMetj2xsbLB//344ODjg6dOnGDVqFExNTSW2Wbp0KU6ePFnkD0U1atTA0qVLsXv3bkRHRxe4jYGBATw8PLB+/XpMnjxZ5n7b29vD09OzwL+VUChEr169sH37dnTo0KHA53/amZNF2Y9ZzGAGM5hRWTJSU1MVUofy8vn3HGXUsGHDiq6CFJlnoP755x9Mnz4dtWvXxpQpUxAXF4cxY8aI10+aNEkhZ6Cys7Nx//592NvbSyy3t7dX2BkuZhQtMTERHh4emD17NjZv3gyBQCCx/vHjx5g+fTrmzp2LnTt3Ii0trcRZn6tZsybs7e1x8eLFIrfT0NAAAGRkZEitq1WrFlRVVYs8eNWqVQvA/x/g9PT00KFDBwgEAhw+fBi3b9/GoUOHpP62H9WuXRuqqqoQCoUSy+3t7REXF4eoqCgEBAQUOVRLU1MTY8eOxfPnz/Hs2TNmlCID+P/XPSUlRbxMVVUVu3fvxo8//ijuKBf0vF27duH7779HYmJioXWQRVVVFba2tnj37h3i4uIK3KZ69epo3749hEKh1N+jolXmYxYzmMEMZlTGDGVS0cPzquwQvpycHPFQkurVq0NTUxN6enri9fr6+njz5k2pKyIUCpGXlye+vuUjPT29Un25YYZ8mjZtikmTJuGHH37A+PHjkZqaihUrViA9PR0A0Lp1a0yePBnz58/HN998gydPnsDX1xc5OTml3h8A6Nq1K9TU1Io8Q6WmpoYxY8bg77//LvA9t2zZMty7dw+3bt0q8PnVq1fHkiVLcP78ecTHxwOA+LqV2bNnIzg4GN9++y1u3ryJX375BS1atJAqw9/fH5GRkQgPDxcvCwkJwdixY+Hk5IS5c+fC1tYWFy5cgLq6usRzp0yZgtTUVKSnp6Nv375wcnIqcHgYM+TPAD6c7fznn38kzqwuXrwYycnJ2LFjR4HPAYCff/4ZFy5cwPnz5wvdpijNmzfH0qVLsWzZMtjb22P37t3IzMyU2KZjx47ibSwsLMTXgCmTynrMYgYzmMGMyppBlZ/M+0A1bNgQz58/Fw9r2blzJwwMDMTrExISULdu3bKrIZWLNm3aSPzf3Nwcc+bMwdWrV9GvXz906tRJvK5Ro0YwMzPD7NmzcefOHdja2pY639HREX///XehZ7WqVasGDw8PaGlpYfXq1VLrlyxZAltbWwwePFjqehbgw1mCn3/+Gdra2hg/frxEucCHi0V///13AMD9+/fRuXNnjBo1SmIooJ+fH+zt7dGtWzeJjODgYPG/P3bgnj59CmdnZxw9elS8bv/+/bhw4QKMjIwwZ84cBAcHw8HBAW/fvmWGnBmf8/X1RefOneHk5CTOcXBwwMiRI9GlSxep7T9yd3eHtbV1gWXK68mTJ9i0aRO0tLTQoUMHuLu7IyAgQPyjAwDcuXMH0dHRqF27Nrp27YoRI0Zg+/btJc4kIiKiiifzDNSgQYOQkJAg/n+fPn3Ew6gA4I8//oCNjU2pK6KrqwtVVVXxTH8fJScny5y5ihmKz6hZsyaMjY0lXvvP66Crq1vo+uIwMzODubl5odctVatWDf/73/9gamoKb29vqeF7S5cuxaBBg+Du7o4XL15IPV9VVRWbNm2CpaUlRowYITHU6+MwxcePH0s85/HjxxKz9a1duxbu7u5wdHTE06dPi9yfuLg4vHr1Cubm5hLL09LSEB0djdDQUAwdOhQWFhYYPHgwM0qQAQCrV6/G0KFD4ezsLDG8z8HBAYaGhoiOjkZKSgpSUlJgamqKFStWiIfz9ejRA5aWlkhISBBvAwB79uzBpEmTiqzzRzk5OXjz5g1evnyJo0ePIi8vT+p6pPfv3yM5ORnPnj3DgQMHoK+vLzUzYUWrKscsZjCDGcyoLBlU+cnsQC1atAhDhw4tdP3MmTMRGBhY6oqoq6vDyspKPAPbR2FhYVJTCDOj7DOys7MRGxsLHR2dAtenp6dDKBQWur44HB0dkZCQgLt370qtU1VVxezZs2FiYgIvLy+Jzg/wYdjewIED4e7ujpiYGKnnq6mpYfPmzbC0tIS7u7vU6feXL18iPj4eTZo0kVjepEkT8YWV69evF3cICrue5lN6enpo2LCheJhgQT6O661RowYzipkBAD/++KO48/T55BWBgYHo1KkTunTpIn7ExsZi06ZN4hn/vL29pbYBgIULF0pNTiIvFRUVidkdC/NxNkFlUVWOWcxgBjOYUVkylElFX99UWa+BKvUnee3atRVRDwDAuHHjMG/ePLRu3Ro2NjY4cOAABAIB3N3dmVHGGQcOHEC7du2gp6eHtLQ0HDt2DO/fv0fXrl3x7t07HD16FB06dICOjg6SkpLw+++/Q1tbG+3bty+0zJo1a8LQ0BDAh7NI+vr6MDMzQ0ZGhviXHXV1dTg4OOD48eNSz69WrRrmzJmDpk2bioftfeywZWVlYcWKFXBzc8OkSZOQmpoq/mUoMzMTWVlZUFVVxdatW9GmTRuMHz8eIpFIvE1aWpp4avWAgAD873//w4MHD3Dv3j24uLigXbt2WLJkCTZu3IhRo0bBzc0NQqFQPHw1IyMDmZmZ0NLSgpeXF44cOYK4uDiYmZnBx8cHAoFAPCStadOmcHNzw8WLF5GYmAhjY2N4enri/fv3OHXqFDOKkQEA69atg7u7O0aMGAGhUIj69euLX/fMzEwkJiZKdZRzcnKQkJAgPtMYFxdX4IQPr1+/hpqaGtTV1cXXeqqoqEBHRwdGRkbIysrCu3fv4ODggAcPHiA9PR1aWlro1KkT6tSpg3///RcAULduXVhZWSEmJgaZmZmoU6cOunXrhry8PDx48AC9e/cusM1kZWWJZxoUiUSIj4/Hw4cPoa2tDSMjI6SmpiI+Pl48TPDly5eoXbs29PT0pMbrF0dlPGYxgxnMYEZlzqDKTa4OVEpKCm7cuAEdHR3Y2dlJ9AYzMzOxadMmeHp6lroy/fv3h1AoxNatWyEQCGBhYYHt27crdPpCZhTszZs32LJlC9LT06GtrY2mTZvCy8sL+vr6yM7OxsuXL3H16lVkZWVBR0cHLVq0wIwZMySGc36uadOmEjfbdXd3h7u7Oy5duoTNmzcD+DCrTc2aNXHp0iWp5+vp6cHOzg6A9LTomzZtEs8G+dtvv0msW79+PdavXw8jIyP06dMHwId7Onzq02nQd+7cCXV1dSxevBi6urp49OgRxowZg6ioKISEhACA1PBCb29vLF++HHl5ebC2tsa3334LHR0dxMXF4fLly3B3dxcPNXz//j169OiB2bNnQ0dHBwkJCQgNDYW9vT0SEhIwbdo0ZsiZoaGhIZ4C/PTp0xI5q1atwqpVq6AIDRs2FN/QGfhwltTR0RG3b9/GiRMnYGBggPbt20NTUxNZWVl4/fo1AgMDxUNa8/Ly0KRJE3Tt2hU1a9ZERkYGnj17hm3bthU4g+RH//33n8QU59u2bcO2bdswYMAAeHt748qVK1i2bJl4/YoVKwAAkydPxpQpU0q8v5XxmMUMZjCDGZU5gyo3mfeBioqKgqurK5KSkpCfn482bdpg79694tnLBAIBLC0ti5yJT977QFH5KOg+UIpW0D2VFO3mzZtlnlEZ7o/wJSmqw64oRd2HTFEWLlxY5hnFuQ8UEREpRmW7D1RRQ+iVxcfRTMpE5jVQ3t7esLW1xYsXLxAVFQUzMzP07du3wOtNiIiIiIiIqjKZHaiIiAgsWrQIWlpaMDQ0RFBQEFxdXeHi4oLo6OjyqCMREREREZFSkHkNVHZ2ttQMGKtWrYJIJIKLi4tCZuAjIiIiIqLypayz3Ck7mR0oc3NzREZGwtLSUmK5r68v8vPzMXLkyDKrHBERERERkTKROYTPxcUFhw8fLnDdmjVrMGzYMIhERc5DQUREREREVCXI7EB9Ot1zQfz8/CAUChVaKSIiIiIiKlsVfZPcynojXZkdKCIiIiIiIvqAHSgiIiIiIiI5yZxEgoiIiIiIqh5lHSKn7HgGioiIiIiISE48A/UFOnr0aJXIqCpatGhR5hkDBgwo8wxVVdUyz/jhhx/KPENHR6fMM4iIiKjyYgeKiIiIiOgLxCF8JcMhfERERERERHJiB4qIiIiIiEhO7EARERERERHJiddAERERERF9gXgNVMnwDBQREREREZGc2IEiIiIiIiKSU4k7UK1atUJMTIwi60JEREREROVERUVF6R/KSOY1UJs2bSpweVxcHPbs2YP69esDAGbMmKGQCu3btw87d+5EYmIimjVrhoULF6JDhw4KKZsZ/69x48ZwcHBAw4YNUadOHRw8eBC3bt0Sr3dycoK1tTV0dHSQl5eH169f49y5c3jx4oVEOcbGxujTpw9MTEwAAPHx8dizZw88PT3x9ddfo3nz5nj//j1u3LiBhQsX4v79++Ln7tq1C2PGjJEo7/r167C3txf/PyAgAF999RUaNGiAjIwMhIeHY8GCBXjw4EGVyZg4cSIcHR1hZmaG7Oxs3L17F/7+/oiOjhY/39HREUOHDkWLFi1Qt25djBs3Dn///bd4vba2NqZPn47OnTujQYMGSElJwZUrV7BhwwakpqYCAMzMzKRe89u3b0u85q1atZJ4zc+fPy/xmk+aNAlNmjSR2Nd//vkHv/32mzjD3t4eDRs2hLa2Ng4fPozIyEjxtr169UKrVq1Qp04d5OXlITY2FhcuXMDLly8BABoaGujZsyfMzc2ho6ODrKwsPHjwABcuXMDbt29RmMjISOzbtw8PHjxAYmIilixZAhcXF4ltXrx4gc2bNyMiIgI5OTkwMzODt7c3GjduXGi5sih7O1e2HGYwgxnMYAZVBTLPQC1ZsgRbt27F9u3bJR75+fk4dOgQtm/fjsDAQIVU5syZM1i1ahWmTJmCY8eOoV27dpg0aRJiY2MVUj4z/p+6ujoSEhJw8uRJZGdnS61PTEzE8ePH4e/vj61bt0IoFGL8+PGoVauWeJtGjRphwoQJePLkCbZs2YKNGzfir7/+Ql5eHnr06IFt27aha9eucHR0RG5uLs6dOwddXV2JnAsXLqBBgwbix+dfem/duoXx48fDysoK/fr1g4qKCs6dOwc1NbUqk2Fra4vffvsNo0aNwoQJE5CXl4cdO3ZAW1tb/HwNDQ3cuXMHP/30U4GvZ/369WFgYIB169bh66+/xvz589G+fXuJ7WvUqIGEhAScOnWq0Nf8xIkT8Pf3x7Zt2yAUCjFu3DiJ1xwAIiIi4OPjI34cPXpUvE5dXR0CgQCnT58uMCMpKQknT57Exo0bERgYCKFQiDFjxkBLSwsAULt2bWhrayMkJAQbN27EwYMHYWZmhuHDhxe43x9lZWWhSZMm+N///ocaNWpIrY+NjcWkSZPQoEEDbN68GQcOHMB3330HTU3NIsstSmVo58qUwwxmMIMZzKCqQiUlJUVU1AazZs3C7du3sXPnTjRr1ky8XF9fH1evXoWlpaXMkDp16shVmaFDh6J58+ZYuXKleFnv3r3Rp08fzJkzR64ymCE7Y/78+RL/9/b2xokTJyTOQH2uRo0a8Pb2xs6dO/H48WMAwNSpUxETE4Nz585Jbf/5F30tLS0IhUK4ubnh1KlTAD6cudHX18fAgQOL3tlPWFtb486dO2jRogUePXpUJTJUVVUl1mloaOD69evw8PDAlStXJNbp6Ojg6tWrUmegCuLg4IDNmzejc+fO6Nmzp8S6ZcuW4cSJExJnoD5Xo0YNLFu2DLt27RK/5pMmTUJCQgJOnDghtf3n+7FkyRKcOnVK4gxUQRlLlixBUFCQxBm3T1lYWGDUqFHw8fHB999/X2hZH/Xo0QM//PCDRCd2yZIlUFFRwfLly2U+X0dHR+Y2gPK3c2XLYQYzmMGMLyHj46iPykIoFFZ0FWT6/EdrZSDzDJS/vz/mzJkDV1dXBAUFlVlFsrOzcf/+fYlhTwBgb29f5BcwZpRNxqdUVVVhZ2eHd+/eIS4uDsCHjoSpqSnS09MxZcoULF68GN999x2aNm1aYBm1a9eGqqqqVEO1t7dHXFwcoqKiEBAQgHr16hVaD01NTYwdOxbPnz/Hs2fPqmyGlpYWVFVVkZaWVmgZ8qhVqxays7Px7t27Yj+3oNf8o9atW2Px4sWYNWsW+vXrB3V19RLVT1VVFR06dCgw41M1atRAXl4ecnJySpSTn5+Pq1evonHjxpg5cyb69OmDsWPH4vz58yUqD6ha7byq7AszmMEMZlSWDKr85JpEYtCgQfjjjz9w4MABjBw5Em/evFF4RYRCIfLy8qCvry+xXE9PD4mJicwo5wwAsLS0hLe3N1asWIGuXbtix44dyMjIAADUrVsXwIdrcyIiIrBr1y48e/YM48ePh5GRkVRZ/v7+iIyMRHh4uHhZSEgIxo4dCycnJ8ydOxe2tra4cOGC1BfyKVOmIDU1Fenp6ejbty+cnJwKHB5WVTLmz5+PqKgo/PPPP1Lr5FW7dm3MmDEDhw8fRl5entzPs7S0xLJly7B8+XLY29tj586d4tccAO7cuYPg4GAEBgbizz//RKtWrTBq1Khi1a158+ZYsmQJvLy8YG9vj927dyMzM7PAbWvWrIlevXohIiIC+fn5xcr5SCgUIisrC0FBQejYsSM2btyI3r17w8vLC1evXi1xmVWlnVeVfWEGM5jBjMqSQZWf3DfSNTExEY8J7dq1K0SiIkf+URUQExODDRs2QFNTE3Z2dhg5ciS2bNmC9PR08awoN2/eREREBIAP15k0adIEHTt2lCjHz88P9vb26Natm8SX4ODgYPG/7927h1u3buHp06dwdnaWuK5m//79uHDhAoyMjDBnzhwEBwfDwcFBYlKBypzxqblz58LGxgajR48ucYdBQ0MDmzZtgkAgwNq1a4v13JiYGGzcuBGampqwtbXFN998g61btyI9PR0AJIYNJiQk4M2bN5g+fToaNGiAhIQEuTKePHmCzZs3izPc3d0REBAg0VEDPlxPNWrUKKSnpyMkJKRY+/Gpj3/Hbt264ZtvvgHwYVhgVFQUDh06hK5du5a4bCIiospMWWe5U3bFmsZcVVUVS5YsQUBAAObOnVvkMKXi0tXVhaqqKpKSkiSWJycnKyyHGcWTk5OD5ORkvHz5Unwmw9bWFgDEX6g//9IsEAgkriFZu3Yt3N3d4ejoiKdPnxaZFxcXh1evXsHc3FxieVpaGqKjoxEaGoqhQ4fCwsICgwcPrnIZ8+bNQ//+/TFhwgS8evWqyIzCaGhoYOvWrQCAadOmFXiGqyifvuZHjhyReM0L8vr1a+Tl5UFPT69YGW/evMGrV69w9OhR5OXlSc1spK6ujtGjRwMAfvnlF+Tm5hZrPz6lo6MDVVVVqdn2zMzMEB8fX6Iyq1I7ryr7wgxmMIMZlSWDKr8S3QfKwcEB8+fPL9aXJlnU1dVhZWWFsLAwieVhYWFo164dM8o5oyAqKipQU/tw0lIoFCI1NVXqYKKvry++Pmj9+vXiTsfDhw9llq+np4eGDRsW+aX24z0BPs60VlUy5s+fL+48yeqgFUZTUxMBAQFQVVXF1KlTi5z2W14qKipSk0N8ysDAAKqqquIOdUlUq1ZN/L4CPry/x4wZAxUVFezdu7fYncDPVa9eHS1btsTz588llr948QKGhoYlKrMqtfOqsi/MYAYzmFFZMqjyk2sIX0pKCm7cuAEdHR3Y2dlJnO7LzMzEpk2b4OnpWerKjBs3DvPmzUPr1q1hY2ODAwcOQCAQwN3dvdRlM0OSurq6uAOsoqICHR0dGBkZISsrC+/evUP37t0RFRWFtLQ01KpVC507d0adOnVw9+5dcRl//fUXnJycEB8fj9jYWFhbW8PExAQnTpzAxo0bMWrUKLi5uUEoFMLAwAAAkJGRgczMTGhpacHLywtHjhxBXFwczMzM4OPjA4FAIB721rRpU7i5ueHixYtITEyEsbExPD098f79e5w6darKZKxduxYDBgyAh4cHUlNTxa9LVlaWuBOkra0NIyMj8dTmJiYmSEtLQ1JSEpKTk6GpqYnt27ejVq1a8PDwgIaGBjQ0NAD8/4xAsl7zbt264cGDB0hLS4OWlpb4Nf/3338BfLjurW3btnj48CEyMzNhYGCA/v374/Xr13j+/DmqVasGdXV18fVxHzMMDQ3x9u1bvHv3Dg4ODnjw4AHS09OhpaWFjh07QltbW5yhrq6OsWPHokaNGti/fz/U1dXF15IV1SHMysoSn7XLz89HfHw8Hj16BG1tbRgaGuLbb7/FwoUL0bZtW3To0AG3bt3C+fPn8eOPP8rVXgpSGdq5MuUwgxnMYAYzlA+H8JWMzGnMo6Ki4OrqiqSkJOTn56NNmzbYu3ev+MapAoEAlpaWRU4sIe805sD/37hMIBDAwsICCxYsKHIIUUl86Rnz589HkyZNMHnyZKl1t27dwrFjx+Du7o5GjRpBU1NT/OX00qVL4hueftS9e3d07twZmpqaSEhIQEhICKKjo7F69eoCs729vbF8+XLUrFkTR48eRdu2baGjo4O4uDhcvnwZS5cuFX8RNjY2RkBAAGxsbKCjo4OEhASEhoZi5cqVePjwYaGTI1SVjC1btmDLli0APkzk4uPjU+g2tra22L17d4HljBs3DoaGhmjcuHGhr/nx48cxfPhwqdf88uXL4te8Tp06GDZsGAwNDaGuro7U1FQ8ePAAFy9exNu3b8XD5CZMmCCVcfv2bZw8eRJDhw6FsbGxOOP169e4cuWK+G9V2PMBYOfOnRJDHj/fh2nTpkktd3Z2xtKlSwEAp06dQlBQEAQCARo1aoTRo0ejT58+Us+RdxpzQLnbuTLmMIMZzGBGVc+obNOYV4b6FqcfUV5kdqDc3d2hpqaGgIAApKenY/78+bh58yZOnjyJpk2bKrwDRWXv8/tAlYXCbvhK0lq0aFHmGQMGDCjzjKKG+inKDz/8UOYZxelAERERfaoydEg+VRnqq4z9CJnXQEVERGDRokXQ0tKCoaEhgoKC4OrqChcXl0JvfElERERERFQVybwGKjs7W2p85KpVqyASieDi4oLAwMAyqxwREREREZUNXgNVMjI7UObm5oiMjISlpaXEcl9fX+Tn52PkyJFlVjkiIiIiIiJlInMIn4uLCw4fPlzgujVr1mDYsGG8qS4REREREX0RZHagZs+ejUOHDhW63s/PT3zfHyIiIiIiqhw+3pdSmR/KqEQ30iUiIiIiIvoSsQNFREREREQkJ5mTSBARERERUdWjrEPklB3PQBEREREREclJJSUlpcyn0FPGOwgTERERESlSampqRVehWDIyMiq6CjLVqlWroqsghUP4iIiIiIi+QBzCVzIcwkdERERERCQndqCIiIiIiIjkxCF8RERERERfIA7hKxmegSIiIiIiIpITO1BERERERERyYgeKiIiIiIhITrwGioiIiIjoC8RroEqm2GegcnJycOrUKWzYsAHBwcHIzMxUaIX27duHnj17wtraGm5uboiIiFBo+cxgBjOYwYyKyWEGM5jBDGZQlZCSkiIq6mFnZyd69uyZKCUlRRQdHS1q2bKlqHr16iJTU1ORurq6yNjYWPTff/8VWYa8Tp8+LWrZsqUoODhYFB0dLVq+fLmobdu2otevX8tdBjOYwQxmMEP5cpjBDGYw40vIkPW9WtkecXFxSv+o6L9RQQ+VlJQUUVEdLF1dXTx69Aj16tXDzJkzcevWLRw6dAiGhoZITk7GiBEjYGFhgU2bNhVaRp06deTqzA0dOhTNmzfHypUrxct69+6NPn36YM6cOXJ2CZnBDGYwgxnKlsMMZjCDGV9CRmpqqkLqUF7evXtX0VWQqWbNmhVdBSnFGsJ37do1LFmyBIaGhgAAPT09LFmyBH/99VepK5KdnY379+/D3t5eYrm9vT0iIyNLXT4zmMEMZjCjYnKYwQxmMIMZVJXI1YH6eIFZamoqTExMJNaZmpoiISGh1BURCoXIy8uDvr6+xHI9PT0kJiaWunxmMIMZzGBGxeQwgxnMYAYzqCqRaxa+yZMnQ11dHTk5OXj+/DlatGghXpeQkCD3ED0iIiIiIlIOnIWvZGR2oEaMGCH+d//+/fH27VuJ9SdOnIC1tXWpK6KrqwtVVVUkJSVJLE9OTka9evVKXT4zmMEMZjCjYnKYwQxmMIMZVJXIHMK3ZcsWicfXX38tsX7+/PnYt29fqSuirq4OKysrhIWFSSwPCwtDu3btSl0+M5jBDGYwo2JymMEMZjCDGVSVlPpGulpaWoqoBwBg3LhxmDdvHlq3bg0bGxscOHAAAoEA7u7uzGAGM5jBjDLIKK8cZjCDGcxghvLhEL6SkasDlZKSghs3bkBHRwd2dnYSf+zMzExs2rQJnp6epa5M//79IRQKsXXrVggEAlhYWGD79u1o2LBhqctmBjOYwQxmVFwOM5jBDGYwg6oKmfeBioqKgqurK5KSkpCfn482bdpg79694tn4BAIBLC0t8ebNm0LL4CQTRERERFTVVbb7QGVnZ1d0FWRSV1ev6CpIkXkNlLe3N2xtbfHixQtERUXBzMwMffv2RUxMTHnUj4iIiIiIyoCKiorSP5SRzA5UREQEFi1aBC0tLRgaGiIoKAiurq5wcXFBdHR0edSRiIiIiIhIKci8Bio7O1uq97dq1SqIRCK4uLggMDCwzCpHRERERESkTGR2oMzNzREZGQlLS0uJ5b6+vsjPz8fIkSPLrHJERERERETKROYQPhcXFxw+fLjAdWvWrMGwYcMgEhU5DwURERERESmZir6+qbJeAyVzFj5F4Cx8RERERFTVVbZZ+HJzcyu6CjKpqZX6trUKJ/MMFBEREREREX2gfF06IiIiIiIqc8o6RE7Z8QwUERERERGRnNiBIiIiIiIikhOH8BERERERfYE4hK9keAaKiIiIiIhITuxAERERERERyYlD+IiIiIiIvkAcwlcyPANFREREREQkJ3agiIiIiIiI5MQhfEREREREXyAO4SsZnoEiIiIiIiKSk8wO1OPHjxEbGyv+//nz5zFs2DB06dIFw4cPx4ULFxRaoX379qFnz56wtraGm5sbIiIiFFo+M5jBDGYwo2JymMEMZjCDGVQlpKSkiIp6tG3bVnTo0CFRSkqKaPfu3SI1NTXR0KFDRYsWLRINHz5cpK6uLtq9e3eRZcjr9OnTopYtW4qCg4NF0dHRouXLl4vatm0rev36tdxlMIMZzGAGM5QvhxnMYAYzvoQMWd+rle2Rmpqq9I+K/hsV9JDZgdLU1BT9888/opSUFJGNjY3Ix8dHYv3PP/8satWqlUI6UEOGDBEtWrRIYpmTk5PIz8+v2G9+ZjCDGcxghvLkMIMZzGDGl5BR0V/s2YEqn4fMIXzVq1dHWloaAODFixfo3r27xPpu3brhyZMnpT4Tlp2djfv378Pe3l5iub29PSIjI0tdPjOYwQxmMKNicpjBDGYwgxlUlcjsQHXr1g0HDx4EALRt2xahoaES6//66y80aNCg1BURCoXIy8uDvr6+xHI9PT0kJiaWunxmMIMZzGBGxeQwgxnMYAYzqCqROY25l5cX+vbti/j4eHTp0gU+Pj6IjIxE8+bN8fjxYxw9ehT+/v7lUFUiIiIiIlKUyjCNuUgkqugqSJF5Bsrc3BwXL16ESCTC+vXrkZmZiYMHD2L16tV4+vQpdu3ahREjRpS6Irq6ulBVVUVSUpLE8uTkZNSrV6/U5TODGcxgBjMqJocZzGAGM5hBVYlc94EyNTVFYGAgXrx4gYcPHyIqKgqxsbEICQmBs7OzQiqirq4OKysrhIWFSSwPCwtDu3btmMEMZjCDGQrOKK8cZjCDGcxgBlUlMofwfUpFRQX169cvq7pg3LhxmDdvHlq3bg0bGxscOHAAAoEA7u7uzGAGM5jBjDLIKK8cZjCDGcxghvKpDEP4lJFcHaiUlBTcuHEDOjo6sLOzk/hjZ2ZmYtOmTfD09Cx1Zfr37w+hUIitW7dCIBDAwsIC27dvR8OGDUtdNjOYwQxmMKPicpjBDGYwgxlUVaikpKQUeWVWVFQUXF1dkZSUhPz8fLRp0wZ79+6FiYkJAEAgEMDS0hJv3rwptIw6deoottZEREREREomNTW1oqtQLKqqqhVdBZny8vIqugpSZF4D5e3tDVtbW7x48QJRUVEwMzND3759ERMTUx71IyIiIiKiMqCioqL0D2UkswMVERGBRYsWQUtLC4aGhggKCoKrqytcXFwQHR1dHnUkIiIiIiJSCjKvgcrOzpbq/a1atQoikQguLi4IDAwss8oREREREREpE5kdKHNzc0RGRsLS0lJiua+vL/Lz8zFy5MgyqxwREREREZUNZR0ip+xkDuFzcXHB4cOHC1y3Zs0aDBs2TCnvEExERERERKRoMmfhUwTOwkdEREREVV1lm4WvevXqFV0FmXJyciq6ClKKdSNdIiIiIiKqGjiEr2RkDuEjIiIiIiKiD9iBIiIiIiIikhM7UERERERERHLiNVBERERERF8gXgNVMjwDRUREREREJCd2oIiIiIiIiOTEIXxERERERF8gDuErGZ6BIiIiIiIikhM7UERERERERHLiED4iIiIioi8Qh/CVDM9AERERERERyUlmB2ru3LkIDw8vj7oAAPbt24eePXvC2toabm5uiIiIYAYzmMEMZpRhRnnlMIMZzGAGM6hKSElJERX1UFFREVWrVk1kYWEh8vHxET158qTI7Qt6yOv06dOili1bioKDg0XR0dGi5cuXi9q2bSt6/fq13GUwgxnMYAYzlC+HGcxgBjO+hIzifkeu6Ed2drbSPyr6b1TQQ64OVHBwsGj06NGi2rVri2rWrCkaPHiw6Pjx4wrvQA0ZMkS0aNEiiWVOTk4iPz+/Yr/5mcEMZjCDGcqTwwxmMIMZX0JGRX+xZweqfB5yXQNlY2ODDRs24MGDB1i9ejWePn0KV1dXtGvXDuvXr0dCQkKpz4RlZ2fj/v37sLe3l1hub2+PyMjIUpfPDGYwgxnMqJgcZjCDGcxgBlUlxZpEQktLC2PHjsWff/6JK1euoGfPnli/fj1atWpV6ooIhULk5eVBX19fYrmenh4SExNLXT4zmMEMZjCjYnKYwQxmMIMZyklFRUXpH8pIZgeqsIq3bt0aa9euxcOHD+Hv76/oehERERERESkdmR0okUhU5HoNDQ2MHDmy1BXR1dWFqqoqkpKSJJYnJyejXr16pS6fGcxgBjOYUTE5zGAGM5jBDKpKZHaghEJhubxh1NXVYWVlhbCwMInlYWFhaNeuHTOYwQxmMEPBGeWVwwxmMIMZzKCqRK2iK/CpcePGYd68eWjdujVsbGxw4MABCAQCuLu7M4MZzGAGM8ogo7xymMEMZjCDGcpHWa8xUnZydaBSUlJw48YN6OjowM7OTuKPnZmZiU2bNsHT07PUlenfvz+EQiG2bt0KgUAACwsLbN++HQ0bNix12cxgBjOYwYyKy2EGM5jBDGZQVaGSkpJS5EVOUVFRcHV1RVJSEvLz89GmTRvs3bsXJiYmAACBQABLS0u8efOm0DLq1Kmj2FoTERERESmZ1NTUiq5CsdSqVauiqyBTRkZGRVdBisxroLy9vWFra4sXL14gKioKZmZm6Nu3L2JiYsqjfkREREREVAYqeoryKjuNeUREBBYtWgQtLS0YGhoiKCgIrq6ucHFxQXR0dHnUkYiIiIiISCnIvAYqOztbqve3atUqiEQiuLi4IDAwsMwqR0REREREpExkdqDMzc0RGRkJS0tLieW+vr7Iz89XyD2giIiIiIiofCnrEDllJ3MIn4uLCw4fPlzgujVr1mDYsGEyb7ZLRERERERUFcichU8ROAsfEREREVV1lW0WPm1t7YqugkxpaWkFLt+xYwc2bNiAhIQEWFpawtfXF126dCmXOsk8A0VERERERFVPRc+wV9JZ+I4cOYL58+djzpw5+Ouvv2BnZ4ehQ4fi5cuX5fN34xkoIiIiIqLSq2xnoCrDd/SC/qa9evWClZUVNmzYIF5mY2ODQYMGwcvLq8zrxDNQRERERERUKWRnZ+POnTvo2bOnxPKePXvixo0b5VIHmbPwKUJl640TEREREVV1lfE7enJyMvLy8lCvXj2J5fXq1YNAICiXOvAMFBERERERkZzYgSIiIiIiokpBT08PqqqqSExMlFiemJiI+vXrl0sd2IEiIiIiIqJKQV1dHW3btsWlS5ckll+6dAkdO3YslzqUyzVQREREREREijB9+nR89913aN++PTp27Ihdu3YhPj4e48aNK5d8pTsDtWPHDrRu3RoGBgbo3r07wsLCFFb2tWvX4O7ujhYtWkBHRwf79u1TWNkfrVu3Dl999RUaNWqEpk2bYvjw4fjvv/8UmhEYGIguXbqgUaNGaNSoEZycnBASEqLQjM+tW7cOOjo6mDt3rsLK9PX1hY6OjsTDwsJCYeV/FB8fjylTpqBp06YwMDBAx44dcfXqVYWVb21tLbUfOjo6GDZsmMIy8vLysHLlSnHbaN26NVauXInc3FyFZQBAeno65s+fj1atWsHQ0BC9e/fG7du3S1WmrHYnEong6+sLS0tLGBoawtnZGVFRUQrNOHHiBNzc3NC0aVPo6OggNDRUofuRk5MDLy8vdOnSBQ0aNEDz5s0xceLEYt+PQtZ+rFy5Era2tmjQoAFMTU0xcODAYs84VJzj4KxZs6Cjo4ONGzcqNGPq1KlS7cXR0VHh+xEdHY1Ro0bBxMQERkZG6NatGx4+fKiwjILavY6ODn744QeFZWRkZGDu3Llo2bIlDA0N0aFDB2zevFnu8uXJEAgEmDp1KiwtLWFkZITBgwcjJiamWBnyfPaVtq3Lk1Hati4rQxFtXZ79KG1bL+53kZK0dXkyStvW5d2P0rR1eTIU0dZJsdzc3ODr64uffvoJDg4OuH79On7//XeYmJiUS75SdaDK+qZYmZmZaNmyJVavXg0NDQ2FlPm5q1evYsKECQgJCcGJEyegpqYGV1dXCIVChWU0aNAA3t7euHLlCi5duoRu3bph5MiRuHfvnsIyPvX3338jKCgIVlZWCi+7WbNmePjwofihyA4zAKSkpKBPnz4QiUT4/fffcePGDfz4449SM7eUxqVLlyT24cqVK1BRUYGrq6vCMvz9/bFjxw6sWbMGN2/exOrVqxEYGIh169YpLAMAPDw88Oeff2Lr1q0ICwvDV199BVdXV8TGxpa4TFnt7ueff8bmzZuxZs0a/Pnnn6hXrx6+/vprpKenKywjKysLdnZ28PHxKZP9yMrKwj///IMffvgBV65cwf79+/H69WsMGTKkWJ1cWfvRrFkz+Pn5ISwsDGfPnoWpqSmGDBlSrFmH5D0OHj9+HLdu3YKRkZHcZRcno0ePHhLt5uDBgwrNePbsGfr06QNTU1OcOHEC4eHhWLx4MbS0tBSW8Wn9Hz58iN9++w0AitX2ZWUsWrQI586dw7Zt23Djxg3MmTMH3t7e4qzSZohEIowcORJPnjzBvn378Ndff6FRo0YYNGgQMjMz5c6Q57OvtG1dnozStnVZGYpo6/LsR2nbenG+i5S0rcubUZq2Lk9Gadu6PBmKaOukeBMnTsS///4LgUCAK1euwN7evtyyy+VGuvIqz5tiNWzYED/++CNGjhyp0HI/l5GRARMTE+zbtw/9+vUrsxwzMzN4eXkp/NRlamoqunfvjg0bNmDNmjVo2bIlfvrpJ4WU7evrKz7YlZXly5fj2rVrZX6G7lN+fn7YsGEDHj58qLCO+vDhw6Grq4tt27aJl02ZMgVCoRDBwcEKyXj79i2MjY2xd+9eODs7i5d3794dTk5OWLx4cakzPm93IpEIlpaWmDRpkviXvLdv36JZs2ZYsWJFid7PRbXt5ORkNG3aFCdPnoSDg4PC9qMgDx48QKdOnXDt2rUS/fggT0ZaWhpMTExw+PBh9OrVS2EZL168QJ8+fXDs2DEMGTIEkydPxvfff1/s8gvLmDp1Kt68eaOw925BGRMnToSKigoCAwPLLONzHh4eCAsLQ0REhMIyOnfujAEDBmDhwoXiZf3794eVlVWJjsWfZ0RHR6NDhw4IDQ2FtbU1ACA/Px8WFhZYunQpRo8eXaJ9+fyzryzaelGfr4pq6/J8hpe2rcuTUdq2XliGItt6QRmKbusFZSi6rcvzepS2rVPlpzRnoJThplhlISMjA/n5+dDR0SmT8vPy8nD48GFkZmbCzs5O4eXPmjULgwYNQrdu3RReNvDhlyNLS0u0bt0a48ePx7NnzxRa/unTp9G+fXuMGzcO5ubm6Nq1K7Zv3w6RqGx+NxCJRPjll18wfPhwhZ7l7NSpE65evYpHjx4B+PCBHRoaCicnJ4Vl5ObmIi8vDzVr1pRYrqGhUWad3OfPnyMhIUGi3WtoaKBLly6Vut0DEP+qXlZtPzs7G3v27IG2trb4i68i5ObmYuLEifjhhx/QvHlzhZX7ufDwcJibm6N9+/bw8PCQmk2pNPLz83H27Fk0b94cgwcPRtOmTfHVV1/hyJEjCsv4XEZGBo4cOYIxY8YotNxOnTrh7NmzePXqFQDgxo0buHfvXom+RBfk/fv3ACDR7qtVq4YaNWqUqt1//tlXFm29rD9f5c0obVuXlaGItl5QhqLbemH7oci2/nlGWbR1Wa9HWbV1qlyUpgOlDDfFKgvz58+HtbW1wjs39+/fR8OGDVG/fn3873//w6+//qrwIXZ79uzBkydPFHLmoSAdOnTAli1bcOjQIWzYsAEJCQno3bs33rx5o7CMZ8+eYefOnTAzM8Phw4cxZcoUeHt7K+yXqs9dunQJz58/L/GvtoWZNWsWhg8fjo4dO0JfXx+dOnXCiBEjMHHiRIVl1K5dG3Z2dvDz80NsbCzy8vIQHByMmzdvIiEhQWE5n/pYblVr99nZ2Vi8eDH69u2Lhg0bKrTss2fPomHDhjAwMMCWLVtw9OhRhU7b6uvri7p162LChAkKK/Nzjo6O2LZtG44fP46VK1fi1q1bGDhwoPjLfGklJiYiIyNDfG3D0aNHMXjwYEyaNKnMzkYfOnQI2dnZGDFihELLXbNmDVq1aoVWrVpBX18fzs7OWLZsGfr27auQ8i0sLGBsbIzly5dDKBQiOzsb/v7+eP36dana/eeffWXR1svq87U4GYpo64VlKLKtF5Sh6LZeUIai2/rnGWXR1mW95mXV1qly4Sx8ZWjhwoW4fv06zp49C1VVVYWW3axZM4SGhiItLQ3Hjx/H1KlTcerUKbRs2VIh5T9+/BjLly/H2bNnUb16dYWU+bnPz5506NABbdu2xf79+zFjxgyFZOTn56Ndu3biIaBt2rTBkydPsGPHDkyePFkhGZ/as2cPbGxsFHpGAPhwfeBvv/2GHTt2wNLSEv/++y/mz58PExMThXbWAgICMH36dLRs2RKqqqpo06YNhgwZgjt37igso6rLzc3F5MmTkZqaigMHDii8fAcHB4SGhiI5ORl79uzB2LFjcf78eRgaGpa67NDQUOzfv79Ek2wUx+DBg8X/trKyQtu2bWFtbY2QkBAMHDiw1OXn5+cD+DDU7eOxpHXr1rhz5w4CAwPRp0+fUmd8bs+ePejfvz/09fUVWm5AQABu3ryJAwcOoFGjRggLC8OSJUtgYmJS7Ik3ClK9enX8+uuvmDFjBho3bgxVVVX06NEDTk5OJT5TX5affcqUoYi2XlSGotp6QRmKbuuF7Yci23pBGYpu6/K8r8qqrVPlojRnoJThpliKtGDBAhw+fBgnTpyAmZmZwstXV1dHkyZN0LZtW3h5ecHa2hpbtmxRWPk3b95EcnIyOnXqBD09Pejp6eHatWvYsWMH9PT0FPZL8adq1aoFS0tLPHnyRGFlGhgYSA1NsLCwEA+HUaTExEScOXOmTE7rL126FDNmzMDgwYNhZWUFd3d3TJ8+HevXr1doTuPGjXHmzBm8fv0a9+/fx59//omcnJwyeQ8DH14fAFWm3efm5mLChAm4f/8+jh8/jrp16yo8Q0tLC02aNIGtrS02bdqE6tWrY+/evQop++rVq4iPj0fz5s3F7f7ly5fw8vJS2I8zBTEyMkKDBg0U1vb19PSgpqZWbm3/7t27iIyMVHjbf/v2LZYvXw5vb2/069cPrVq1wuTJk+Hm5lbsmRGL0rZtW1y9ehXPnz/Hw4cPcfjwYbx586ZE7b6wzz5FtvWy/nyVJ0MRbV1WhiLaemEZimzrxXk9StrWC8tQZFuXZz/Kqq1T5aM0HShluCmWonh6eoobYVlMy12Q/Px8ZGdnK6w8Z2dnhIWFITQ0VPxo164dBg8ejNDQUKirqyss66N3797h8ePH4g9aRejUqROio6MllkVHR6NRo0YKy/ho//79qFGjhsQvboqSlZUl9WuYqqqq+Nc3RdPS0oKhoSFSUlJw8eJF9O/fv0xyTE1NYWBgINHu3717h/Dw8ErX7nNycjBu3Djcv38fJ0+eVOj7uCiKbPsTJ07EtWvXJNq9kZERpk2bhuPHjyskoyDJycmIi4tT2N9MXV0dNjY2ePz4scTysmr7e/bsgampKXr06KHQcnNycpCTk1Nubb9OnTrQ19dHTEwMIiMji93ui/rsU1RbL4/PV1kZimjrJdmP4rb1ojIU1daLux8laetFZSiqrcu7H2XV1qnyUaohfGV9U6yMjAzxrx75+fl49eoV7t69C11dXYV9qP7www8IDg7Gr7/+Ch0dHfG4by0tLdSqVUshGcuWLUPv3r3RsGFDZGRk4NChQ7h69Sp+//13hZQP/P89Dz6lqakJXV1dhf0S/XHcuLGxMZKSkvDTTz8hKytLoeOKp02bht69e8PPzw9ubm64e/cutm/fjiVLligsA/gwecTevXvh5uamsNf5U3379oW/vz9MTU1haWmJu3fvYvPmzXB3d1dozsWLF5Gfn49mzZrh6dOnWLJkCSwsLEo1W6Wsdjd16lSsW7cOzZo1g7m5Ofz8/KClpYUhQ4YoLEMoFOLly5dITU0FADx9+hR16tSBgYGB3B/kRWUYGRlhzJgxiIyMxIEDB6CioiJu+9ra2nJPKFJURp06dbBhwwb07dsXBgYGSE5ORmBgIGJjY4s1la6sv9Xn16ioqanBwMAAzZo1U0iGrq4uVq9ejYEDB8LAwAAvXrzA8uXLUa9ePbi4uChsPzw8PDBu3Dh06dIF3bp1Q2hoKI4cOVKs+//J85mRlZWFgwcPwsPDAyoqKnKXLW+Gvb09vL29oaWlhUaNGuHatWv47bff4O3trbCMY8eOoW7dujAxMcH9+/cxf/58ODs7S03qVBRZn30qKiqlbuvyfL6Wtq3LysjNzS11W5eVkZaWVuq2LiujXr16pW7rsjIyMjJK3dblec1L29bl/d5W2rZOVYtSTWMOfLiR7s8//4yEhAS0aNECq1atUti87qGhoRgwYIDU8hEjRmDr1q0KyShs1hZPT08sWLBAIRlTp05FaGgoBAIBtLW1YWVlBQ8PD4XNylQYZ2dnhU5jPn78eISFhSE5ORn6+vro0KEDFi1aBEtLS4WU/1FISAiWL1+O6OhoGBsbY9KkSfjuu+8UegD866+/MHDgQFy8eBHt27dXWLkfpaenw8fHB6dOnUJSUhIMDAwwePBgzJs3T2rWvNI4evQovL29ERsbC11dXQwcOBCLFy9GnTp1SlymrHYnEomwevVqBAUFISUlBe3bt4efn1+xOuqyMvbt24fp06dLrS9OuywqY/78+WjTpk2Bz9u8ebPcHdCiMtauXYtJkybh1q1bePPmDerWrYt27dphzpw56NChg1zly8oo6DhobW1d7KmNi8pYt24dRo4cibt37yI1NRUGBgZwcHDAokWLYGxsrND92LdvH9atW4fXr1+jSZMmmD17drE65vJk/Prrr5g5cybu3btXontmycpISEiAt7c3Ll26BKFQiEaNGmH06NGYMWOG3McwWRnbtm3Dxo0bIRAIYGBgAHd3d8ybN69YIw3k+ewrbVuXJ6O0bV1WxvPnz0vd1mVlZGVllbqtl+S7SHHbuqyMt2/flrqty7sfpWnr8maUtq1T1aJ0HSgiIiIiIiJlpTTXQBERERERESk7dqCIiIiIiIjkxA4UERERERGRnNiBIiIiIiIikhM7UERERERERHJiB4qIiIiIiEhO7EARERERERHJiR0oIiIiIiIiObEDRUREREREJKf/A7C1TzSr/TioAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1008x1008 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,14))\n",
    "sns.heatmap(train_data.data[0], annot=True,cmap=\"binary\", fmt='d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "dd248ab4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([28, 28])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.data[0].shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "fdae006e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array(0, dtype=uint8), array(255, dtype=uint8))"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.data[0].min().numpy(), train_data.data[0].max().numpy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8314ada1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([5, 0, 4,  ..., 5, 6, 8])"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.targets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "a295cf3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.targets.dtype"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "da991188",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([60000, 28, 28])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data.data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "c69785f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([10000, 28, 28])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data.data.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "2b48c133",
   "metadata": {},
   "outputs": [],
   "source": [
    "BATCH=128\n",
    "\n",
    "train_data_loader = DataLoader(dataset=train_data,\n",
    "                              batch_size=BATCH,\n",
    "                              shuffle=True)\n",
    "\n",
    "test_data_loader = DataLoader(dataset=test_data,\n",
    "                             batch_size=BATCH)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "ffb9f145",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "torch.Size([128, 1, 28, 28])\n",
      "torch.Size([128])\n"
     ]
    }
   ],
   "source": [
    "for x in test_data_loader:\n",
    "    print(x[0].shape)\n",
    "    print(x[1].shape)    \n",
    "    break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "3cc3df96",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'cuda'"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DEVICE = \"cuda\" if torch.cuda.is_available() else 'cpu'\n",
    "DEVICE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "93865465",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Lets define the model\n",
    "\n",
    "class NeuralNetwork(nn.Module):\n",
    "    def __init__(self, in_, out_):\n",
    "        super(NeuralNetwork, self).__init__()\n",
    "        self.layers = nn.Sequential(\n",
    "            nn.Linear(in_, 256),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(256, 128),\n",
    "            nn.ReLU(),\n",
    "            nn.Linear(128, out_)\n",
    "        )\n",
    "        \n",
    "    def forward(self, x):\n",
    "        return self.layers(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "1a06e8c5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "NeuralNetwork(\n",
       "  (layers): Sequential(\n",
       "    (0): Linear(in_features=784, out_features=256, bias=True)\n",
       "    (1): ReLU()\n",
       "    (2): Linear(in_features=256, out_features=128, bias=True)\n",
       "    (3): ReLU()\n",
       "    (4): Linear(in_features=128, out_features=10, bias=True)\n",
       "  )\n",
       ")"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = NeuralNetwork(784, 10)\n",
    "\n",
    "model.to(DEVICE)\n",
    "\n",
    "model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "23eeb8f9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<generator object Module.parameters at 0x0000012E6F8076C8>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.parameters()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "7a2f2d6c",
   "metadata": {},
   "outputs": [],
   "source": [
    "CE_loss = nn.CrossEntropyLoss()\n",
    "optimizer = torch.optim.Adam(model.parameters())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "aff8a574",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch: 1/10\n",
      "   Batch: 0, Loss: 2.2782 Accuracy 0.1562\n",
      "   Batch: 100, Loss: 0.4222 Accuracy 0.8828\n",
      "   Batch: 200, Loss: 0.3204 Accuracy 0.9062\n",
      "   Batch: 300, Loss: 0.2486 Accuracy 0.9375\n",
      "   Batch: 400, Loss: 0.0994 Accuracy 0.9609\n",
      "Epoch: 2/10\n",
      "   Batch: 0, Loss: 0.1223 Accuracy 0.9766\n",
      "   Batch: 100, Loss: 0.2410 Accuracy 0.9375\n",
      "   Batch: 200, Loss: 0.1310 Accuracy 0.9688\n",
      "   Batch: 300, Loss: 0.0857 Accuracy 0.9766\n",
      "   Batch: 400, Loss: 0.2689 Accuracy 0.9297\n",
      "Epoch: 3/10\n",
      "   Batch: 0, Loss: 0.1029 Accuracy 0.9609\n",
      "   Batch: 100, Loss: 0.0605 Accuracy 0.9922\n",
      "   Batch: 200, Loss: 0.0692 Accuracy 0.9688\n",
      "   Batch: 300, Loss: 0.1476 Accuracy 0.9375\n",
      "   Batch: 400, Loss: 0.0451 Accuracy 0.9844\n",
      "Epoch: 4/10\n",
      "   Batch: 0, Loss: 0.0210 Accuracy 1.0000\n",
      "   Batch: 100, Loss: 0.1263 Accuracy 0.9609\n",
      "   Batch: 200, Loss: 0.1378 Accuracy 0.9531\n",
      "   Batch: 300, Loss: 0.0634 Accuracy 0.9688\n",
      "   Batch: 400, Loss: 0.0503 Accuracy 0.9844\n",
      "Epoch: 5/10\n",
      "   Batch: 0, Loss: 0.0268 Accuracy 0.9844\n",
      "   Batch: 100, Loss: 0.0760 Accuracy 0.9844\n",
      "   Batch: 200, Loss: 0.0117 Accuracy 1.0000\n",
      "   Batch: 300, Loss: 0.0502 Accuracy 0.9766\n",
      "   Batch: 400, Loss: 0.0473 Accuracy 0.9844\n",
      "Epoch: 6/10\n",
      "   Batch: 0, Loss: 0.0262 Accuracy 0.9922\n",
      "   Batch: 100, Loss: 0.0283 Accuracy 0.9844\n",
      "   Batch: 200, Loss: 0.0182 Accuracy 1.0000\n",
      "   Batch: 300, Loss: 0.0399 Accuracy 0.9844\n",
      "   Batch: 400, Loss: 0.0199 Accuracy 0.9922\n",
      "Epoch: 7/10\n",
      "   Batch: 0, Loss: 0.0311 Accuracy 0.9922\n",
      "   Batch: 100, Loss: 0.0423 Accuracy 0.9844\n",
      "   Batch: 200, Loss: 0.0331 Accuracy 0.9844\n",
      "   Batch: 300, Loss: 0.0391 Accuracy 0.9922\n",
      "   Batch: 400, Loss: 0.0644 Accuracy 0.9766\n",
      "Epoch: 8/10\n",
      "   Batch: 0, Loss: 0.0017 Accuracy 1.0000\n",
      "   Batch: 100, Loss: 0.0111 Accuracy 1.0000\n",
      "   Batch: 200, Loss: 0.0039 Accuracy 1.0000\n",
      "   Batch: 300, Loss: 0.0253 Accuracy 0.9922\n",
      "   Batch: 400, Loss: 0.0436 Accuracy 0.9922\n",
      "Epoch: 9/10\n",
      "   Batch: 0, Loss: 0.0477 Accuracy 0.9688\n",
      "   Batch: 100, Loss: 0.0091 Accuracy 1.0000\n",
      "   Batch: 200, Loss: 0.0116 Accuracy 0.9922\n",
      "   Batch: 300, Loss: 0.0184 Accuracy 0.9922\n",
      "   Batch: 400, Loss: 0.0287 Accuracy 0.9844\n",
      "Epoch: 10/10\n",
      "   Batch: 0, Loss: 0.0038 Accuracy 1.0000\n",
      "   Batch: 100, Loss: 0.0092 Accuracy 1.0000\n",
      "   Batch: 200, Loss: 0.0074 Accuracy 1.0000\n",
      "   Batch: 300, Loss: 0.0030 Accuracy 1.0000\n",
      "   Batch: 400, Loss: 0.0103 Accuracy 1.0000\n"
     ]
    }
   ],
   "source": [
    "## Training loop\n",
    "EPOCHS = 10\n",
    "loss_ = list()\n",
    "acc_ = list()\n",
    "\n",
    "\n",
    "for epoch in range(EPOCHS):\n",
    "    print(f\"Epoch: {epoch + 1}/{EPOCHS}\")\n",
    "    for batch, data in enumerate(train_data_loader):\n",
    "        x = data[0].to(DEVICE)\n",
    "        y = data[1].to(DEVICE)\n",
    "        \n",
    "        optimizer.zero_grad()\n",
    "        \n",
    "        y_pred = model(x.reshape(-1, 784))\n",
    "        \n",
    "        loss = CE_loss(y_pred, y)\n",
    "        \n",
    "        loss_.append(loss.item())\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "        \n",
    "        accuracy = torch.mean((torch.argmax(y_pred, 1) == y).float()).item()\n",
    "        acc_.append(accuracy)\n",
    "        \n",
    "        if batch%100 == 0:\n",
    "            print(f\"   Batch: {batch}, Loss: {loss.item():.4f} Accuracy {accuracy:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "60cbb0a6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot the Train acc and loss\n",
    "# plt.figure(figsize=(14,14))\n",
    "pd.DataFrame(data={'loss': loss_, \"Accuracy\": acc_}).plot(figsize=(10,5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "814d35a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "# testing over the test data\n",
    "\n",
    "test_loss = 0\n",
    "test_acc = 0\n",
    "\n",
    "with torch.no_grad():\n",
    "    for batch, data in enumerate(test_data_loader):\n",
    "        x = data[0].to(DEVICE)\n",
    "        y = data[1].to(DEVICE)        \n",
    "        \n",
    "        y_pred = model(x.reshape(-1, 784))\n",
    "        loss = CE_loss(y_pred, y)\n",
    "        \n",
    "        test_loss += loss.item()\n",
    "        test_acc += torch.mean((torch.argmax(y_pred, 1) == y).float()).item()\n",
    "        batch+=1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "fd94065b",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test loss: 0.0729, test accuracy: 0.9812\n"
     ]
    }
   ],
   "source": [
    "print(f\"test loss: {test_loss/batch:.4f}, test accuracy: {test_acc/batch:.4f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "11e14c95",
   "metadata": {},
   "outputs": [],
   "source": [
    "pred = np.array([])\n",
    "target = np.array([])\n",
    "\n",
    "with torch.no_grad():\n",
    "    for batch, data in enumerate(test_data_loader):\n",
    "        x = data[0].to(DEVICE)\n",
    "        y = data[1].to(DEVICE)        \n",
    "        \n",
    "        y_pred = model(x.reshape(-1, 784))\n",
    "        loss = CE_loss(y_pred, y)\n",
    "        \n",
    "        pred = np.concatenate((pred, torch.argmax(y_pred, 1).cpu().numpy()))\n",
    "        target = np.concatenate((target, y.cpu().numpy()))        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "fe4ce1b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "cm = confusion_matrix(target, pred)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "2687cd22",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12, 10))\n",
    "sns.heatmap(cm, annot=True, fmt='d')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1633b9b7",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}