covid19_classification_focal_loss.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "g564yNs_aT8W",
    "outputId": "7509f811-529e-4431-8fec-954b5c7394ee"
   },
   "outputs": [],
   "source": [
    "from google.colab import drive\n",
    "drive.mount(\"./gdrive\")\n",
    "!unzip \"./gdrive/My Drive/Copy of A_05_Part_02_Dataset.zip\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "zZFdZMyyaW5E"
   },
   "outputs": [],
   "source": [
    "import torch\n",
    "import pandas as pd\n",
    "import torch.nn as nn\n",
    "import torch.optim as optim\n",
    "from torch.optim import lr_scheduler\n",
    "from torch.autograd import Variable\n",
    "import numpy as np\n",
    "import torchvision\n",
    "from torchvision import datasets, models, transforms\n",
    "import matplotlib.pyplot as plt\n",
    "import time\n",
    "import os\n",
    "import copy\n",
    "from tqdm import tqdm\n",
    "from sklearn.metrics import confusion_matrix, f1_score, precision_score, recall_score\n",
    "from sklearn.metrics import multilabel_confusion_matrix\n",
    "from mlxtend.plotting import plot_confusion_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "p-_3qxUGcRRq"
   },
   "outputs": [],
   "source": [
    "data_dir = r\"/content/A_05_Part_02_Dataset\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 51
    },
    "colab_type": "code",
    "id": "_w1UdZ2npYJ2",
    "outputId": "71d1eec2-1a0c-4cdc-d9fe-3fb6ca11e404"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Classes: \n",
      "['covid-19', 'normal', 'pneumonia']\n"
     ]
    }
   ],
   "source": [
    "#Define transforms for the training data and testing data\n",
    "train_transforms = transforms.Compose([transforms.RandomRotation(30),\n",
    "                                       transforms.Resize((224,224)),\n",
    "                                       transforms.RandomHorizontalFlip(),\n",
    "                                       transforms.ToTensor(),\n",
    "                                       transforms.Normalize([0.485, 0.456, 0.406],\n",
    "                                                            [0.229, 0.224, 0.225])])\n",
    "\n",
    "valid_transforms = transforms.Compose([\n",
    "                                      transforms.Resize((224,224)),\n",
    "                                      transforms.ToTensor(),\n",
    "                                      transforms.Normalize([0.485, 0.456, 0.406],\n",
    "                                                           [0.229, 0.224, 0.225])])\n",
    "test_transforms = transforms.Compose([\n",
    "                                      transforms.Resize((224, 224)),\n",
    "                                      transforms.ToTensor(),\n",
    "                                      transforms.Normalize([0.485, 0.456, 0.406],\n",
    "                                                           [0.229, 0.224, 0.225])])\n",
    "\n",
    "#pass transform here-in\n",
    "train_data = datasets.ImageFolder(data_dir + '/Train', transform=train_transforms)\n",
    "valid_data = datasets.ImageFolder(data_dir + '/Validation', transform=valid_transforms)\n",
    "test_data = datasets.ImageFolder(data_dir + '/testing', transform=test_transforms)\n",
    "\n",
    "\n",
    "#data loaders\n",
    "trainloader = torch.utils.data.DataLoader(train_data, batch_size=32, shuffle=True, num_workers=4)\n",
    "validloader = torch.utils.data.DataLoader(valid_data, batch_size=32, shuffle=True, num_workers=4)\n",
    "testloader = torch.utils.data.DataLoader(test_data)\n",
    "\n",
    "print(\"Classes: \")\n",
    "class_names = train_data.classes\n",
    "print(class_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "KO07QsMSpgTy"
   },
   "outputs": [],
   "source": [
    "def encoder(a, num_classes):\n",
    "  labels= torch.nn.functional.one_hot(a, num_classes)\n",
    "  for i in range(labels[:,0].shape[0]):\n",
    "    if(labels[:,0][i]==1):\n",
    "      labels[:,2][i]=1\n",
    "  return labels.float()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "ykof74sAjM_K"
   },
   "outputs": [],
   "source": [
    "def corona(model, trainloader, validloader, Epochs, name):\n",
    "    device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "    model.to(device)\n",
    "    model.train()\n",
    "    history = []\n",
    "    for epoch in range(Epochs):  # loop over the dataset multiple times\n",
    "        total_train = 0\n",
    "        train_loss = 0.0\n",
    "        valid_loss = 0.0\n",
    "        running_loss = 0.0\n",
    "        correct = 0\n",
    "        total = 0\n",
    "        vcorrect = 0\n",
    "        predicted = []\n",
    "        train_acc = 0\n",
    "        valid_acc = 0\n",
    "        vtotal = 0\n",
    "        # pbar = tqdm()\n",
    "        for i, data in enumerate(trainloader):\n",
    "            inputs, labels = data\n",
    "            hot_labels = encoder(labels, 3)\n",
    "            inputs, hot_labels = inputs.to(device), hot_labels.to(device)\n",
    "            optimizer.zero_grad()\n",
    "            outputs = model(inputs) \n",
    "            loss = criterion(outputs, hot_labels)   #----> compute loss\n",
    "            loss.backward()                     #----> backward pass\n",
    "            optimizer.step()                   #----> weights update\n",
    "            outputs[outputs >= 0.5] = 1\n",
    "            outputs[outputs < 0.5] = 0\n",
    "            correct += (outputs == hot_labels).sum().item()\n",
    "            total += hot_labels.size(0)\n",
    "            running_loss += loss.item()\n",
    "            \n",
    "        for i, data in enumerate(validloader):\n",
    "            inputs, labels = data\n",
    "            hot_labels = encoder(labels, 3)\n",
    "            inputs, hot_labels = inputs.to(device), hot_labels.to(device)\n",
    "            outputs = model(inputs) \n",
    "            loss = criterion(outputs, hot_labels)\n",
    "            valid_loss += loss.item()\n",
    "            outputs[outputs >= 0.5] = 1\n",
    "            outputs[outputs < 0.5] = 0\n",
    "            vcorrect += (outputs == hot_labels).sum().item()\n",
    "            vtotal += hot_labels.size(0)\n",
    "\n",
    "        train_loss = running_loss / len(trainloader)\n",
    "        valid_loss = valid_loss / len(validloader)\n",
    "        train_acc = correct / total\n",
    "        valid_acc = vcorrect / vtotal\n",
    "\n",
    "        history.append([train_loss, valid_loss, train_acc, valid_acc])\n",
    "        print('Epoch #', epoch, '\\t\\tTraining loss: ', train_loss, '\\t Validation loss: ', valid_loss)\n",
    "        print('\\t\\tTraining Accuracy: ', (100 * train_acc)/3, '\\t Validation Accuracy: ', (100 * valid_acc/3))\n",
    "    history = pd.DataFrame(history, columns=['train_loss', 'valid_loss', 'train_acc', 'valid_acc'])\n",
    "    torch.save(model.state_dict(), './gdrive/My Drive/' + name)\n",
    "    return model, history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 169
    },
    "colab_type": "code",
    "id": "NuPTX-fRXH2i",
    "outputId": "2ed7dbad-9650-4afc-9322-ac03dfc8eca0"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAACGcAAADFCAYAAADzVg1ZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nOzdeZwcZZ348c+3r+nuue87mUzuE0IC4SaAoiLIIR6sF6CsqLvqrqyuiive666uuroePy9EvFAEFEFu5A4ESAjkTmaSmcx9T3dP38/vj6ohPZ2emZ7MjIHJ9/165ZWZqa6q53nq+VY9VfX084gxBqWUUkoppZRSSimllFJKKaWUUkopNTscxzoBSimllFJKKaWUUkoppZRSSimllFJzmXbOUEoppZRSSimllFJKKaWUUkoppZSaRdo5QymllFJKKaWUUkoppZRSSimllFJqFmnnDKWUUkoppZRSSimllFJKKaWUUkqpWaSdM5RSSimllFJKKaWUUkoppZRSSimlZpF2zlBKKaWUUkoppZRSSimllFJKKaWUmkWTds4QESMiQRH5yt8jQTPJTvuiY52O2SIiN4nIl491OmaLiGwUkdZjnY7XAhF5WUQ2Hut0HCsa6wpARM4SkV3HOh3HiohcJSKPH+t0zCaN9dc2va5nT6/rczvWZ4qI/FBEPnes03GsiMgjIvKBY52O2aLXdTXqeI/1mSIi94jI+451Ol7rjvc2ykwRkYCINB7rdBwLItJgn/9dxzots2Wut1Fmioi8S0TuO9bpOFZE5EYRueVYp+PVTkTm2edM57FOy7Ggz1Gyd7y3Ueb6vdVcf2Y6U4739yMz5WjbKCKyxL5mJSZrC2Y7csYJxpjP2htvEJHmqSbqWLOD96osP/vIa+1Ebl+oH8nys1eJyE2zm6KZJyLNItKQ5WfN7Kbm1cUYs9IY80g2n822bDTWX52Oh1g/WsaYx4wxS7P57FTKxr5hvnE6aTsWNNbHfFZj/VVIr+vj0+v6YXM91qfDGHOdMeZL2Xx2KmUzldh8tdDr+pjPaazPMRrrM8MY8yZjzC+y+ay2UcanbZSZYYzJM8bsn+xzUymbqdw/vJrM9fPW8dBGOVrGmF8ZYy7I5rNTKZuptCleLY6HWD9axpiD9jkzMdln9TnKEZ/VNso45nobZa7fWx0PsX609P3IzDjaNooxZrcxJg94bLL1XjXTmsgc7jE9SuZ4D8/j4Riq6Tse6slcj3U1M+Z6LMz1/MHcj/Xj4Riq6dN6orIhllfNvedsmOuxMNfzp5RSKrO5fv4/HtooambM9VhQM0PricrG8VBP5vozU6Wma9qNT7u33vUi8qKIDIrI70TEm7L8WhHZKyJ9IvInEalJWWZE5CMisgfYY/d4ahWRT4pIl4i0i8ilInKhiOy2t/GZlPVPEZGnRGTA/uz3RMQz3Tyl5e9GEblVRG4WkWGxhkdan7J8ud27bMBe9paUZTeJyA9E5G4RCQLn2uX1b3Z5BUXkpyJSKdYQm8Mi8oCIFKds4/ci0mGX7aMisnKG89dgH4f3ichBEekRkc+mLM8RkW+LSJv979sikmMvGz1enxKRDuDndnn9XkRusfOzTayhXD5tH9MWEbkgZftXi8gO+7P7ReSDM5k/ex+PiMjXROQZERkSkTtFpCTL/DtE5N9FZJ+I9Np1YXTdjZI2rJh9fF9n/zzVsqixY6TPjplrU5ZNVg9T9zsrcSEa63Ml1v9RrFhuF5Hrp5D/GhG5TUS6RaRJRD6alv8vp/w+JjaOoizeYu9/wC7z5WnbylgPM+x3NHaHRWS7iFw2A+U4Wnc/kVJ3r05ZXmiXYbeIHBCRG8R+0CNWb9QnRORbItIL3GiX3fftsgjYy6vEOtf2i8hOEVk7m3nKkEeN9bkR63pd1+v6ZOV4PMT6H+x8DYvI8yJywhTyf5GIbLHT+KSIrEnL/6KU31+5Dh5FWWQTk+Ndc1L3Wywid4l1/em3f66bgXK8SUT+T0T+YpfjJhFZmLL8dBF51i7DZ0Xk9JRlj4jIV0TkCSAENNpl92ER2WNv70sistAu4yE7Ljyzmae0/Ol1XWNdY/3wPn4oIvfb5fg3EZmfVhbXiRW7A2KdFyRl+TViXf/7ReTe0XUlw/QFkjLcf1ocDYjVdjjd/nuLXR7vS1l3sph8XES+YaejSUTeNM5+F4rIQ2K1BXpE5FciUjQD5ahtlJlro3xarPNiv4j8XNLu+SaIlxy7DhwUkU67XvvsZVdJ2nRRkhLnMvVz+GT3DRNdP1P3+2YRecGuMy0yQ99KlAni1q5vN9hx1GUf70J72Whdfb+IHAQekqnH6qzkKS1/x0sb5TNinS+aReRdU8j/MrHO6X0isktE3p6W/w+k/D4mNqZSFvbnJ2tLjFcP0/f7Hbu+DInIcyJy1gyU42TXhsnOh38Q69w6BFxll92X7bIIiMifRaRUrOvIkF3XGmYzTxnyaETko3Zc9ojIf0v218ZCsZ5htIvIITtvzpT835Ly2THX9KMoi8li8ktinWeGReQ+ESkbZ79Xyww/cxB9jqJtlOzLsVnm/r3V8fDMVN+PTK8ctY0yE9dzY8yE/wADLJpgeTPwDFADlAA7gOvsZecBPcBJQA7wXeDRtG3fb6/nAzYCceA/ADdwLdAN/BrIB1YCI8ACe/11wKmAC2iw9/3xbNOezT/gRiAMXAg4ga8BT9vL3MBe4DOAx87vMLDUXn4TMAicgdURxmuX19NAJVALdAHPA2vt5Q8Bn0/Z/zV23nOAbwNbUpbdBHx5mvlrsMvpx/YxOAGIAMvt5V+001sBlANPAl+yl40er6/b6fOllNcb7ONyM9AEfDblmDal7P/NwEJAgHOwbopOStl+63TyZ2/nEeAQsArIBW4Dbsky/x+z819n5/FHwG/GS599fF+XVneyLYtHge/b9eBErLp/3mT1MMN+J4yLaZRjMxrrcyHWf4MVB6vtMk+vr5ny7wCes4+XB2gE9gNvyJQ+0mJjKmUBLAGCwOvtcv+kXfaeLOph+n7fZn/OAbzD3m71NMtxI1bd/aKdvguxzlvF9vKbgTvtY9kA7Abeby+7yl73n7Hqss8uux6sOj5aFk3Ae+3j8GXg4WzyZG//cY11jXX0uq7XdY310TKOAVfYabrePl7uLPK/FiuWN9jH533253MypY+U2D2KssgmJse75qTutxR4K+C39/N74I4ZqCc3Ab3AKfbx+hXwW3tZCdAPvMdedqX9e2lKrB608+yy82CwrpMF9t8jwINYbYtCYDvwvmzyZG//A9PM32RlrNd1jfXjKdaHgbPtuvCd1Ppnl8VdQBEwz87rG+1ll2C1n5bbx/oG4El7WYO9ritT7HI4jq7mcIwcBP7PTscFdrrysozJmH0snMCHgDZAMux3Edb9Ro59PB4Fvj0D5fgI2kaZqTbKS0A9Vtw+wZGxN168fAv4k71ePvBn4GvjnVdJiXOmcA4nu/uGjNfPDPvdiHV/7gDWAJ3ApTNQjhPF7TV2+huBPOCPwC/T6urNWPXYx9Rjddw8keG8MI3z1vHQRvkfu4zPwWonTFrH7OPWYh8vF9b1rgdYkSl9pMXGFMsim7bEePUwfb/vtsvWBXwC6AC80yzHq5j42jDZ+TAGXIpVl3122e3FuucdLYvdwOs4fP79eTZ5srd/ywzF+sNY9X6enZ4PZJn/27GuN7lYbZRngA9mSh9psTuVsiC7mNyH9UxwtJz/c5z9jvvMYRplOLoPfY6ibZTJyrGZuX9vdTw8M9X3I9Mrx41oG2XCNkp6PjJ+JouCnjCo7Yrw7pTf/wv4of3zT4H/SlmWh9UgaEjZ9nlpB3UEcNq/59uf2ZDymecY5yYF+Dhw+yyckB5I+X0FMGL/fJZ9EBwpy38D3JhSCW/OUF7vSvn9NuAHKb//M+M8XLEriQEKMwX8Ueavwd5mXcrfngHeaf+8D7gwZdkbgOaU4xVNrYR2ed2f8vvFQCDDMS0aJz13AB9L2f5MNT7+M+0YRrFOsJPlfwdwfsqyarsOuzKljyMbH1mVBdZDhwSQn/L5rwE3TVYP0/c7WVxMoxyb0VifC7G+LO0Y/jSL/G8ADqZt79Mcvskakz4yNz6yKgvgc8CtKcscWDcPG7Ooh2P2m6EMtgCXTLMcR+tu6gPmLqzGsRPr3LIiZdkHgUfsn6/KUI43AT9OK4sdKb+vBgayyRMz+xJHY/3w8tdqrOt1PXP+9bo+dh9zPdZTH9Q4gHbgrCzy/wPsh20py3cB52RKH0e+sM26LJg8JjNec9L3myH/JwL9M1BPbgJ+kvL7hcBO++f3AM+kff4p4KqUWP1i2nIDnJFWFp9K+f2bjPOCND1PzNyLD72uH16msX58x3rqi+M8rOtYfUpZnJmy/Fbg3+2f78HuIJFyDELAfLLrnLEnLUYMUJnyt147n9nE5N6UZX57W1Xp+82Q/0uBF2agHB9B2ygz1Ua5LuX3C4F9k8UL1kutILAwZdlp2C99yK5zRlbncLK7b8h4/Uzfb4b8fxv41gyU40Rx+yDw4ZRlS1Pq22hdbUxZfhVZxupkeWJmO2fM9TZKHMhNO4afyyL/7wAeS9vejzj80mdM+sj84iOrsiC7tsR49XDMfjOUQT9wwjTL8SrGuTaQ3fnw0bTtPQJ8Nq0s7kn5/WJSXiZOlCdmtnPGG1N+/zDwYBb5r8R6qeVLWX4lhzuhjUkfmTtnZFUWZBeTN6Tl4a+Z9psh/688c5hGGY7uQ5+jZM6/tlHG7mOu31sdD89M9f3I9MpxI9pGmbCNkp6PTP8czIyOlJ9DdibB6pFzYHSBMSaA1VivTfl8S9q2eo0xCfvnEfv/zpTlI6PbF2sIpLvsoW6GgK8CZdPJyDjS8+cVayitGqDFGJNMWX6AifMHR+ZnvPw5ReQ/7WFnhrCCDv4+ecx4DO2fa1J+7zbGhNO2lZ6fngzHdDSPbxKRp+1hZQawAnU28pd6HA5g9ThL3c94+Z8P3G4PazOA1RhJYDVgs5FtWdQAfcaY4bR0ptal8erhGLMcFxrrh71WYz09FlLjebz8zwdqRuPAjoXPkH0cQJZlwZF1KWmneaJYyCMDEXmvHB6megCrd/hMlGmvMSaeIQ1lWOeW9HPmjNQTmNU8pdNYP+y1Gut6XT9Mr+vjm+ux/koa7bhuZeLrXmo9+UTada8+bd2JZF0WTB6T411zxhARv4j8SKzhyYewvnFUJDMzz2u25xOY2XPmbOYplV7XbRrrx32sp5ZjAOgj+3L8TkoZ9mG9JE+tRxNJLzOMMZnKMZuYfCWNxpiQ/WOmcqwUkd+KNYT7EHALM1c3tY0yMya6bx0vXsqxXjw+l1KOf7X/nq2p3LdOdt+Q7X3rBhF5WKwhsgeB6/g7t/Xsn12MrW/p5/9sY3W285RqrrdR+o0xwZTfJ3uGk3o+2ZB2fXsX1gv5bB3tM5xMbYlsY+F6saZ2GLTTXMjM1Jvxrg3ZnA+n29abrTyly+pZX1r+52Ndo9pT6smPsEaHyNZR1ZOUdB5NPZnNZw76HOUwbaOMb67fWx0Pz0z1/cj0aRtlmuU4U50zxtOGVdgAiEgu1tAfh1I+Y6ax/R8AO4HFxpgCrGCQiVeZUW1AvdjzuNnmMXP5+wesIUJfh3WwG+y//73zOD/l93n230Yddf7EmpvtNuAbWL3ti4C7mZ381af8PA+rh1RPFuu1AG8yxhSl/PMaYw5hfSPDP/pB+yZsKjf9qdqAEhHJT0vnoXE+P5FjERca66+dWE+PhbbxPpiiBevbRqlxkG+MudBePiYWmNrFNF16XRI7zVOKBbHmuf4x8E9YwyQWYQ2NO5v1pgfr3JJ+zpyRenKM8pROY/21E+vj0eu6XtezMVdi/ZV6Ysd1Hdlf976SVk/8xpjf2MtDzNJ1j+yvzek+gfWt1w12mZ5t/30260p62mFmz5nHIk+p9Lpu0Vg/bK7Hemo55mENkZttOX4wrRx9xpgnsa6tMDPlmE1MZuurWHV7tV2O72bm6qa2UWbG0dy39mA9kF2ZUoaFxpjRh6zp5TjdmJ7sviFbv8aaiqXeGFMI/JC/c1sPK+1xxj7cns75/1jkKdVcaaMU29fmUVN5hvO3tPNJnjHmQ/by2XyGk6ktMSmx5m7/JPB2rGmKirCGx5/ttuxk58PptPX+nnk62md9EaAspZ4UGGNW2stnrZ6kpHOq9eTv+cwhlT5H0TZKNubKvdV45tIzU30/Mn3aRplmOc5254zfAFeLyIn2hearwCZjTPMMbT8fGAICIrIMa960SYlIg4gYEWmY5v43YT2w+aSIuEVkI9bQTL+d5nZH5WM1knqxKuRXs11RRB4RkRtnIA2/AW4QkXIRKcOaU+mWGdguWHMz5WDN5RMXkTdhzVM5KRG5SkSap7Cvd4vIChHxY80T94eUXokT+SHwFftEhl0Ol9jLdmP1nHuziLix5tbNmUKaXmGMacGar+5rIuIVkTXA+zm6ss46LkTkRhF55Cj2kU5jfXr+nrH+ObG+5bESa26v32WxzjPAsIh8SkR8dk/WVSJysr18C3ChiJTYD7g+PoX0pLsVeLOInG/H1SewyubJKW4nF6tB2A0gIldj9QzNSESaReSqo0qxzT6n3Ip1zsi3zxv/ysydM6eUp1Qa61mbS7E+Hr2u63U9G3Ml1teJyOVifcvh41jx93QW6/0YuE6sb32KiOTa9WL0IdEW4B/s6+EbsebXPFozFZP5WC+kBkSkBPj8eB8UkY0iMp2HJqPuBpaIyD+IiEtE3oE17OddM7BtmEKe0ul1PWsa6xrrqS4UkTNFxAN8CWu6mEzffkv3Q+DT9v0FIlIoIm8DMMZ0Yz38erddjtdgzak+ZTMck/lYQ2oPikgt8G/jfVDbKBOazTbKR0Skzq7nnyWL+1b7W4U/Br4lIhX2fmtF5A32R7YCK+1znhdr6OqjNZP3DflY3xQOi8gpWC8nMhKRm0TkpqPYR7rfAP8iIgvE6oz1VeB3ZuyIJNORdZ5SaRsloy+IiEesFwMXAb/PYp27sPL/Hrt+ukXkZBFZbi/fAlwu1rOhRVjngKM1U22JfKwOQt2AS0T+A2s++YzsdsLGo0uyZYbPh5lMKU+pjiLW/01EikWkHvgY2Z0z24H7gG+KSIGIOERkoYiMtne2AGeLyDwRKcQavv9ozVRMTumZg+hzlHTaRslA762yNpeemer7kQy0jTKuo76eT2RWO2cYYx7Amh/nNqx5XxcC75zBXVyP1cAfxroByyaIwOpldICj63X3CmNMFOsE9CasXobfB95rjNk5ne2muJnD6dxOdg+YRtUDT8xAGr4MbAZeBLYBz9t/mzZjDVH1UayTTT/WsfxTlqtPNX+/xJrrqAPw2vvNxnfsNN0nIsNYx2ADgDFmEGsOvJ9gHaMg1hC6R+tKrB6BbcDtWPMsPXAU25lKXMxIPdFYn7a/Z6z/DdiLNcfsN4wx9022gt1QvwhrHtUmrDL4CVYvVrDiayvWcGP3kf3xybSvXVjfXPuuvZ+LgYvtYzCV7WzHmmPsKaxv/6xmnHIS6wF0KVMr9/H8M9a5YD/wONY3hn42A9udUp4y0FjPwhyL9fHodV2v65OaQ7F+J9Z8lv1Y8xxfboyJTbaSMWYzcC3wPXvdvVjzTY76GNa5YnT4xTuyTE8mMxWT3wZ8WOeup7GGcR9PPVO/qT+CMaYXq33wCawHKJ8ELjLGZPPtq2xMJU+v0Ov6lNKgsa6xnurXWC8Y+4B1WG3ySRljbge+DvxWrCGIX8JqS426FqvzQy+wcoppSjdTMfkF4CSsbzz9BfjjBJ/VNsr4ZrON8muse8v9wD6yj5dPYcXy03Z9fABrhAOMMbuxXkY9AOzBqkNHZYbvGz4MfNE+7v+B1ZYez0zdE/wMq64+inWPH8aKr5kylTyl0jbKWB1Y16c24FfAddnUMfu+7AKsa3qbvZ2vc/iF6beAKFb74xf2to/KDLYl7sUqx91YbYAwmYfHx+6AMIx1PZ2umTofZpJ1njKYaqzfCTyH9VLrL8BPs1zvvVidA7Zj1bU/ANUAxpj7sc7rL9rbPurOTTMVk0fxzEGfo4ylbZTM9N4qC3Psmam+H0mjbZQJTed6Pi4xZuIOySISxuqV87/GmM9Nd4evBiJyA9ZcYD861mmZDSJSB9xqjDn9WKdltojIfcDHjDE7svjsI8AtxpifzHrCXmNEZAtwvt1InnM01sd8tgGr4eCewW/DzAkicibwEWPMlcc6LbNFY/21Ta/rR3z2EfS6npHG+pjP3ggsMsZk9XLxeCIiPwF+b4y591inZTbodf21T2N9Zkwl1u1v57YaY26Y9YS9xmgbZWZM5bxlfwv4AzP4gnROsB+abwXWZNMB7bVI2yhjPrsR63xSN+sJe40RkXdjTV80nZEcXrWmGutijTaz2Bizd9YT9xqiz1GO+OwjaBslI723em3T9yMzQ9soM0NEFgPPYnV8/LAx5qZxPztZ5wylXuu08aGUNj6UUnOHXtdVNvSFrVLHB431maGdM2aGtlFmhnbOUEpffKjsaecMlQ1toyil70dmirZRZsasTmuilFJKKaWUUkoppZRSSimllFJKKXW805EzlFJKKaWUUkoppZRSSimllFJKKaVmkY6coZRSSimllFJKKaWUUkoppZRSSik1i1zHOgFKKaWUUkoppV6d7Hmsj3ZtYLLVHYAfGAESaX/PBUc+JMNA39EnIytCTmEDK046naZdO0gkhRXrz+JQSwut27dCrBsIAulT0+bY6R79uxNXwWKSsSjJkf1TSsGChYv57Kf/HY/HPebvQQMugV37uvjBD35PcHAQ4gEwUXD6EVcuuDysWr+e9RtORpJD/O1Pv6Bp93aSycQ4e/t7ygFxgMkBIvY/JxA7JqlxOF2UVDYQCgQIDXVkvZ44PFQsPR/ERffB/Xj8Baw7sZYn7r8NZm1EUhdH1rlXH68/j8Wr1rLh/LewZ28vT95/L7FQF0TbmPwckCqbc8aRXO4cyuadTHfLHhLxCJCEZMD6P0sVtYu54u1vo766jHv/eg/PbX6G4aHBKadllDFGjnplpZRSSimllFJzlnbOUEoppZRSSik1cyQHXLUQiwFDWJ0Xwox9ySxALlAChLA6PgDiB3cVDpeXZLgPkl1AAZAPDM9Sgp0gtTj8y2lYdxkmdxEH9u1l3spz6AtsAk83DlcBmGEwUUSiJGIBMCWQ7ARx4SnfgCQC1C9ZT83itTxz1/cIj4xu38FknRHE4eCfPvpxrrnmakQOv9M1QNJAFCCRpHb5GXz/p39haGAQjMHp8eD2ePDn5nLZO67gxLWLWLvIyZeuv5o7b7+D73///9i+beux7aThKsFdspxk3AHRKIloNySjEN/P0byIP1oOh5NFy9dQveBEtm/dRGi4cwprO8mrOYU3vONjxBMJ/vqXuwkODrB246V0NL3Evj07Zzax7gLEtwATikN8F6/GDhpOl4eGJSs47+JLeMulb8FbuZy+AQfOB55hb1uM3qYthNvaye4Yi3XeMABxJKcSE8m+Y0fjstWc8dZPsOWFHQz29xKNRAn1txIb2kuwp5lkUiAZxzrXZNZ1aA83/+wnXHDp+/nqd39BTryfe/5yF3+68w62bXuRkVAwq7QopZRSSimllFIT0c4ZSimllFJKKaWmScBZhMNfSzJwCBxlIBEwLqwXon6sDhoBrI4KRUAeMGj/cwAucC/GW7uCgvIKAq3PEu7sI4kPTA0k9zPRy1UAp8uN1+sjPBIikZjshbYDXMU4cmowkk8kIXS2t+N0unAnh2netY2cXB+OnDgSC2HiYVz51SxZdz5l5ZU8//hDDDXdjbjy2fD6Kzhp/Rqq6xu5/+77iITdWKNqRHB58impWUZX86ZxU7J4yXLedeXbx3TMsEsVh4AXwOXgQ1dsYOmCWh5+vo1AKIrTkcDt8bJgfg3nn16Lw+2gMkfweku47tqrefsVl/P7P9zO//3fd9n+0ovHpJOGOAsoqF2KQwwuga62DhLd2/h7dcxwOBwsWbacS955LV2hfH79v58mEuqaZC3BqqdJXAVLKJ2/lhUnb+SUU08iGAzQ0tJCf18fAyMuPvDhj3HD9f+cRX2bnHiKceQ1UtywDqfHT2/TXuKd7Ux95Bi7Q5A4yMkrJxqKYBIDWB2lsh9NYvyEFrL09Cu59hP/yuoTFjA8DPv2B3G7PTgcDvILCukKGqAMSC1rJ2NHyLH4KlaRX7OekYEukskkiVA/4UgX2Y6usvb01xMYMVx0+WXs2L6TQ62trFx1Gfn5fpr27GHf7r1sf/x+EsMvYp2DjsgQUEpg2MPfnt5L+V92c95Za7jmY9dz9Qc/QtPuHfz5T3/irrv+xJ5dO4lGI1MtMaWUUkoppZRSCtDOGUoppZRSSimlpq0YZAnJ8DCYACR6wFMDkdHpQDyAFxzVVocNAzACkguOcutvbi/OolrK6uooLimhvPwCml8uwDgKCPUOwogTotuY6OXyietO5R3vfBdf+9IN9Pf1pC11AG7AgMONI2cRxuvDhFswsRbMiJfWnTVUNSykr62dvJJuhrr2kex7+pV9RkdaaN48RO5Z76asuobkyFpiCQe9rQcINNZSuGoNsWSCgoWnMtzkJRnaRzIZoaK6kq7mzGkWh4PrPvRhKspKMy/HmjUjjiEYNZx+Qi31DVU8+kIXfq+husTJiQsrKfUJCQSPvQ4ilJYU8cFrr+KKKy7ld7f+ke/873fYu/NljJmBF/STsjs4OHy43G76dj1GIp7AW7GCEWcOJp75Rf3M7V5oWLCId73/w6zY8CY27+hj187NxKUSayySIJle/ou7GKd3AfFgEw6nsOrst3HxFZcQi8UpLBByc4tZs2YNgUCAYDDAuo2XcPIpt/D0U09MM8FunEXrKKhbSsOiRcTjMUYGBhjqLYX4INmVlQMoBWcFDn8huVV1FFfNo6+1lcDB54AwJFqZfscYD3v2dfGrX93FxrZzWH3CUrxeJ0NDIySTSYYGB0k63EAVEAcJg+TZYTTA2HJ34cyppnL+Epi/BGMMrXt3Ewn0Y8K7Jk1JXn4B73nPO9je6WXd6jqWNOTT2rmMcMSB35+DPzeP4rIq3O4c2hxSvikAACAASURBVPYvZLjvAJFgH/FwyD4/hRFPOZ7S9bjzCjn19W9k6bIl4PGzsztBS6vB71rE2vPfxVmvv5TgQCePPHQf9/31bg407ycef/WNaqKUUkoppZRS6tXLeeONNx7rNCillFJKKaWUehX6whe+cGN2n/SCFIC3DGJxSPaB8YEZAXxYL2SHwYyOlNFr/e50Q9Ei3BULyCmrpbSujoqKSmpqqvH6cgkbDy5vLjEDCYcX4gOQGH96gfZDLTz2+A5CYYMxDsRTDVICyUGsN8N+iua/ntXnXslQ/0Ei3ZsgNgjJMJgAwcE+Yo4iYpF++lpeZGSoHRMfGLOPaGiAQzs3Eezdx5INlxMKOmjZ8igvbd5CQfVCYvEEBhgaGsBbWI1JuskpqGCgfXvGNC9Zupz/+eY3yMvLzbjcYI05svlQgrufaKcv6qQo30F9XSFPbtrDH353P568EpbMK8bnFGuGiJT1RQS/z8f6dWs59S1vJyIVHNy/i3BwcPLDKj7yq04gHh7CJDONYuDgyBf9+UAtOCvAUYE7r4KFq9fStXcTRtwUzV9BdHiIZHgQayQFYeLRHCTt1xyKSyvx+72MjGQeSaWiupaLrriaC975L3SEyxmM+HC6PJSUltIfgv7OCIgPEiFSOwq4ckqpXnMpJfNXMdjeAaYY4ytlIBhl+8t7aO/oZe3aRgryi6muqSEai5F0+jhr3SL+8ufbSSSm09kkiYm7KKpfTn5BPgd372Lw0B4gB+JhrA5OYJV3epkL7rwFeItPwOQtwlU+j/zaBRSUVZGXX0B3ZycGDyL5IMOQGGF6HBh3NSPROL68PBwOD/v2NvPko48xMDhIc9N+MDHiQzuAEcTXALmN4C4CVzEkXWByACc55SdQWLuK2uoqyisrcbrddPX1I24fsYG9TDbSx4bTzuDfPvkxViyvYHmpmxXz86ltLGN5YwkHDgXo7Rtk7boVnHXeaUSTXg4daGJksIUkIK5SiuafQt0JF7BgxWrqFjRyymknc8IJ8+nsDLJly36qairYtbedb/739/jZtz/D5ueep6a+kXdc+W4ueOObKCoqpre3l2AwgDGHj8uNN974hWkWslJKKaWUUkqpOUg7ZyillFJKKaWUyii7zhmCNW2J2C9c/WCGwSSxJuQY4vBUAkkgjjUKQAJMEKJDuP3VFFfVUlFZidvtJhqNAmCMQRxCLBYnEgrhSBhMtH3C1CRws/CMd1O1+Az8lUvw+vMI9uwBEkhOBd6ShUTDw/Qd3IaJjZ0uIhkLEndWEB7shXgEkwxCMr0zSBKIkogF6Wtronrl2YzEXETigq+4mPzCQvbv3MHArkeJDr6EN6+QU846h71bHzuy5MTBpz/7H7zuvHOOmNLEyj8MJWF/X5IXdw8SiUY52NLD/pYQHp+HHG8xhaU19AeidAehvtqPz2VtZ/Q1sRzeGUUFPpacdArPbe3i4M6nmGwEBYenmNMv+1fql5xOd3svODz4ShYSDwcAF+7SU3B5CgAHJhHC6qwhQBScbqRgHu6Saiqqquja+zRiQixcez6BYJRIfwAY4XDnCA+4ysBZAkljbQPBWXgCDlchJhElv2IZBfM2ctppZ9LXtZ+hwf4x6c0tKGHtaa+nom4pzz61ied3DFJe20AoFOLZTZsoKSmhvKqKEE4S3hKSjjJIujExwFnG/PVvo3HlWiLhMN7SOhz+IiIG4okEpWVlFBYWEwolWL60ErfXR25uHtGYg5NPXsGBnVvYs3vykR4mlIzjLmjAON0MdnYQ7doPvhKrKMgBSu3/Y1gx5ARykZwyyF1GbnEdVQsaWbB0CeUV5TQsaMAYw3AwCL48cgqKcDjdxIcPTi+dOCFWiLewhMFAkKQxDA0O8dyjfyO/pISh/h6Gmx7ExDustMZ7INwOJoS7sJKC+espmbeagpqV5JTNp3fffpqee4ZQMERhZSWDA4PkFZUSGeokEZ5oShfh4//yCc4+41TynIIToS8h+F1CoRcc+fksWFDBru17+NUPfsTmh++nZ++9JCOdEOuHeDfRQCs+n59la8+ivKKCkzesZCQUYM+eNkKhIPXzKtm1s4kXHnuUobb99HXvZcvmJ7nnrjt5/vkXqJ+3kHf8w3s47/wL8Pl89PT0MjIS4sbPf147ZyillFJKKaWUOoJOa6KUUkoppZRSahrcwJA1SkYMcBRjvTjuxXqZHMaenCPz6oleIm1PEPB4qKqqwOvNIRQK4cnJsUY66Otn2DeM0+8nPlJiTYVixhs9QzDxJH0HW3jnRz6K1+fhb/f8leDwMC4JUVi7ikMv3sPAnmYyfyM/gTEJfBVLCbfvAROeMOexUDtDHTtZvP5U9u/bR3dvLyUVFXj9uSCFkOwk2LOTbc88nnH92vmNvPmyKzhidAhbEuiPQ1NXgpaDXfzml7+hr6ODpatWsf3lRtasXUVfbx8NDZWIy8NA0FCcYxV1GMiRw90lAHIR+jt7eWnLXpAiMBO9+HYj3jrE4eRD//pBet95Ee0dPSQcOfz829+hc/sTSGKQM976z3Q272L7Iz+A5AhWh4sRiA8iIx58uYsY7u8hHh7EmVNEQWEhrhwPSBeY1M4VCTAxHDk1JGMGCAGCP7+UqsYTKS0rYcHyNTxx3z1UlJcSi48dpcKbV0FecSXbNj/GSKAfcOI1VQwPD1NWVkbTS1vpb2nindd+iI72dhAH0Xw/Pft7CYeawLho2fYkrdvuAROkoHwh9UtOZ96yEzFAJBwmLy8fcXhoaRuhuNhBIBClp7uNnqWFfPT6T/Ho3x4hMDw0YZ2ZkBlmYO+TDPctJxGL48jNxxAFXwkmFoX4ITAdWB2c7BrizKek8TyiSSeDXV0UVlfj9Xrx+f3U19eTTCSY39BAX28f/X194K3G4S0hGe49ykRanbEcLgfG6UAEgoEApWVlSDLJoaYmwl37SYZ7sGqfi9EOTcQ6iHV1EQy103De1dQvWMTWLVsoblxIoKeQrr5+cru6aVy4kN7eHgprVtHVv2fclBQVl/DGN16AU+SVs4vPae0tgbCi0vCzWzfxzes/wkDHdqxz1diYTsZCtL50D3kFpVxx7aeor/ez9YV+9u7ey/IVCwiHw7S2tBI2TnDXQqwPiJFIxGhvbeLWX/+U2269mdr6Bt548Vu54YsX8fBDDxxl2SqllFJKKaWUmuu0c4ZSSimllFJKqaM0Oq2FsX/ugWQE61YzZv99tLNGZJxtuJDcGoLde9h2314WnnYRxZWVRCMRioqKiOVFGRz04s3NIxCOQLgeIjszbEeAUvAuIZgU9u7ZS3dLM1vuvQ3xFrLotHPJyzEcGOmw05NpEznkFRZTWLmAHpeLaH8O4d5DE+Q/Sc+ee1my6gQWNDYy0D+AMYb8/HwQF6PdIoaDCbt8UvYrwvlXXMOhaAkLAZd55eMYYxgcMfSFEgxEk4SCIbq7eunv6qT3wB6e3LWJzfmlHHjDZaxZdxKhUJjlDXXUFznAQGfYkHBBpVtIGkM4Zr26znEJOJxULVvN0PAgyZ4nsDpTZOCuZOGGi1iyfBlL5+UQK63h/23bz45dTQQSHryljVQvX8XOp+6ge/+TkBwdyeFwHpORFvL8bvy5eRicFNeuIC8vl+DBpyCZoXNAoo9kcAhn3mow5SSC/YwEDNGRCKvXnQJOF509/fzih/djEi1jVg0HugkHulL+4icWjNHb08O6deuob1xIZ2cnHe3trDv5ZPq72tjx9O+JBdutgk92Ew90MNqJqDfYTu+BzfQePJdL3v/vFBSX0tfXh9vtxuvLI8frpqKyhJ6ebu697zned/Eq3nrF2/jFz386QX2ZjAsTGSTe04qnfinR7gCMdOMoWYwZ2AfmEGM7ORlIBOnddQ/uwgbKF51Kwhh6e/vwDA9TXFxMUXEJILhcLtweN21NIZwFi0mG+5hs5JSxvCDluIpryS+dTySSINTdisMk6M7NxeFwEI+G6Ws/hDu/BmfZWST6WyExBPSR2qEkFmhi+8O34vG8l6XLlxEKhnA4HERjUXq6u8kvyMfn92GiQbp2+u3pZ4506mmns7CxAbBDRyAXa6ARpzH84ZFd/NdnbmCgY5ud13jG7WCSNG19gETsozgcDpqb2xkZCdG4aAGtLT0EAgHqFi3iQLCHUOtLR6yeiMc41NJMS3sXv/3lT0kmMk0BpJRSSimllFJKWU+HlFJKKaWUUkqpKXIAlUAB1gv5ADAIdGB1xIhgvfh3Me5LUQCSmMgQJtpDPNjKvs2PM9Dbi9fnIxaP4/V6ycvLx+Vy4vR5IW8eiHfsJsSDw7cAHCU43EJBRQX9/X309fQi/lLEnYvb5WDnk7/NME1JChOjvKKMcy94PfNXriEnzzdpKSTjI2x7+JcsW7IIf66fRDxBZCQMiRFe6bhiEjicY78bUVxeT/3y1zMYivDMoSjb2sMkjSFp4OWuBN+/cy9f/P5DfP7rt/Hdb9/C7Tf/mJ7td2ICuzCxILFgLzteeI5tW7dywqpq8nMdOO2pUfLdUOQAp4GOkOGmB1r53h17+clfm+kajHLN+6+gevFq8CwDCjPkSnAXNLB42TJOXHsC4nTyiz8+w/Nbd3LoUBt1jQtYd+EVuFxuelt3EI8EQXJeWRcARz7+qvUsWLocwYDJo6hqKX1dnUSD6Z0MUsUhtp+6VevJrVhEfKCJA5sf466bfkFPdzdOt5tkcgRj0jvYpG1PXJBfQl9fH4fa2lh/xlkMdezhoTt+RTQSobtlJ7FgR8q68SO3YcIc2vlXfvOt6+npaGPt2jXk5fkJBkIMDcXJyXGzePFCYkkXv3tgP++57l8or6waJ1/ZcAG5IG4cDidOvx9wWnUpOl6ZDUGyl1j/C/RtfxSJRikqKsTt9tDZ0UleXi5FxcW4XC7isRgkDRLPBcdkdVs4PO6K0xppxd9Afv0JFNXMJ9yznVj3JoYOvkhHaytuj4eVp51JzdLlLD3xJNxuNyQPAu0c2TErSXR4J1sf+iWBrhZOWreWU08/lXXr1nHCiSdSXl5uTUFTMx9PYUPm1ImDt771rbhdY+NKAI8x7Gkd4uvfvJnelu3jlNtYsWiEA00t3HPXC2x/eSdLli3F5XLR3dWD08TwueIUVNbhzF1Ipu85ebw+covrCAz1ExgamHR/SimllFJKKaWOTzpyhlJKKaWUUkqpKXIBPiAfaGHsy8841stYj/1/nv3zOCM0kITYAXsLLuIDT7PvqT48Z15BfeMiQqEgLpcTn99PNBol5MkFRxkkWu31BYe3jGSkDZJRksPtBLurMQ0NJMRBEjfFVdUkhpsJ9e2bJF9xBjqbKCwqoqammq7mWgYPTNa5BAZ7DjDYdYDKqiqi0SixWBjoYfSldCIaABk7dUlx/Tpe3t5MWWUNu/dEMIkYjZctxuWGwSiMRBL09vTy1EMPMdR5kHjfJkiOTpnhREwDTqewZ9tL9HT2c8HKfARrN7kue5oHA14nLGgo55nnW3nhiZdIJBIsWdLIW9/5Du7xemnesY34wG5MuAlrtBPA4aewfjlOlwuPx0FTUx/9g1Fqampwu1ycefZZhEIjOE48gQeShv2bbsHpCBMZSVo7RXC4K1h+2sWctfFctjz3PLvq1rL65A04XS6e8/iJjYw//UciMkjnjr9Ss+YKDg53Ex+BzkNt7Nu1m+jwMJgQVseBTFPTjDKYWJRQMERXZycnnXQS85asobW5lRdfeAEceUAR0D/BNqzt9Le9wG+++xXyC7/I2eduYOeOTuJ9cTCFJBIwf/58mpuaGUjW8d73Xc03/+s/mdqoFNj5KbLrSZjESBBPQRkj/e0k+/ZY0wZNKEks2Err9qcpKC2hbn4D4UiEvj5r6ppoLAbiwJXrZ6RbsDpWNU2Y78N58IAJIyZAjtdL34HtJEMHgRjJaIC8/HxycnJYt349zU1NBIYDFFXW09E3HyL7scaySBcl0vciT99xkOHhEP/4r59AEOrq6zHJJH19fQSGA5QvWMeh/l2Q1hmnvKKS173ufCRlSpNRg6E4X/rvm3np4f8HyYmm7hklFNadjDe3gE1PbSYUCNDQUM+mx57mzzd/nY79m0nGwhhxI64C8DUiJoGJdoBxkluxkuJCF2tXLuUOZwnJxNFOGaOUUkoppZRSaq7TkTOUUkoppZRSSmVh9Jv0LvufA+gmc6eLMKMv6a0X/kVkd/sZB8LEBl9m16YHGRwcwOfzkeP14vP5cTgcEB6BhIdXRmjAkBxpg2QY62W9kIyG6OzsJBQIgsNBw9LFHNrxNyZ+mW8pKq1h2bIG5jXUk5OTm0WaLQMDQ5SWlhKNRYlFR0cNsUSCg5i0N8gHd+1k1/bt7NrZREdHD0sbK0gmE7y4u48nnniZZzc9Q2tzM4logGQ8iDVhg5vR6VES4SaC3ftZsmoltWU+65sXY/t/EDKGB14c4uHHdtLd1U1ZWR4exwgP/vV+9u/eyXv/8T2ccsGFLDnnSoqXXILDW2mt6HAz2N3D4MAAra1dbNnZR25eHn6/nzdeeD5Ll87H5XQyMDCE2+Phi9+7mVPOv5Kc/AagAKd3HktPv5wL33Ih9fOqKCopYc0ZG3njxeeQjI0Qj2WepiJVeOgQjng/9WvPA28RSY+HoeFha6HAxMcyB3IWIIwQ7NhFy75d9Pb2svFNl1JaXcW2x+7GU1SOq3Ax2dbLYOeT/PJ/Pkdby0FWrKzAmASdnV20tLTQ3d2D3+/nhR1dXPbu61jQ2JjFNjOkmX4w+yH6IrGuZ5FkDFdhhd1HImeS9QH6SQ49z57H/0RgcBC/3084HMblcuH1esnPz6O4pBRPWTk4K9K26Xrlf0dOLZ6ilfby/FeWefMrCPc2M9j8MIgbiGFinQy1vkxPdzdebw61tbVU1VSz7qyNePLqgbRRbtKYpOHg3n1se/ElSssKaGioYvHSOhYtXsCCxgWsWr8Rf+GRo5Gcfc5G6mqrgdQzgTUl0B8f3s1dv/sFiUg2HTPAmVPJyedeQjwWo629nZM2rOeZxx/lp19+Py0vP0BsZIBEPEwyNkxi5BCEm5i/5mzecM3/sPqCj1Gx/BxOvugj+MsXsXTjP1K59HVZ7VcppZRSSiml1PFHO2copZRSSimllJqEPbUBYHWgSGJ9G36iUQfCWB0zYoAfa6QNmeDzqQyR4X6a9+/HAF6vF4/HDSKIzw8OJ5lvZ51gwkS6txIdCWIAp8tNrt9HaCibb7M7MDgoKvZSVFTAUE/H5KsAkKD3wGZrP8EgIyNBMIdH24hGhki+Un6WePAg3e2HaG5uZtHCOk5bXsjPb3uaz33rT9x51+M8du+9bL3vdgb3byM58DwkO7DK0gF4wLuAUM9OXn7iAUgmEOSIl9TtwwkcbjclJUXU1Fbw5gtP4Ss3vJ1Pf+qd1FYVsWheIR+6+iLOOucM3nzlNZx75ecorF4FiSQ4nBSXlJCbm0syCclEgvp59Sxb1sjISJQ9O17iwdtupuXlTcTDI6w46Uxyy1fjKaxGHLDspJNZvaaRNauLWL1mOe+48iJOPamcHK8TJJtHEUl6mp5gzfp1eKuqIScHIw6cPt8E1ciBuApxFqyCWAeJzocZbrqb7Q/+kDtu/hmBQIA1604mFvfgcbkRTylWvcxGjJ6mTfzgGz/A4whx0tpKnE4Hfb297N61i46ODto7umnqc3PdRz5qdSTKmmDF0+hUOEmIdRLp2oG/oh5HXjVIGVYHnckkiAx2snXTU8SiUUwySSwWA2MwxhCLRUkM9UK8E6uzz6g44ARnOXkLzqZ48bkUzDsXb9UZ4GzAWXASxfMXE2x7AQjZ9TsJZpDwYCsej4doNEZpWSm5fj9utxunczT+xztgBhgi2PEsj993Dy0HW5k330nDPAeLlxSyaEkDCxYtYcGqs8as5XA4ufzyy3E6na+M75EExMChvgi/uvVeggMHsix7FwtOegtrTz2TZDLJwoWNOJ0u/nzzz4gMd42T7AT9LS9yyhlncOp55+Nwunjh+a388d7nMR4PA8OTdz5SSimllFJKKXV80mlNlFJKKaWUUkpNwnB4ag8fUA0cnGSdBIdfOBcDdVidObqZfMqHJET20b37BbqrqymvqCTgC1BYWEg0FCLqKoKow94HWC9/jf17AhPtJtTfCTmFOP0+3Dk52XUIEDfldQtxu5yUlJSy/JSNbGrdTDJ6aNJVW3c9gUuuZWBggOBgX0rawESHMubZk5PDvHn1nLSinAIv9MX8FBQWUlZRQWBokD0mRqS/AxOOQ/QQmCDWcXDgL66nYfVZ1M+vo6o0b+yGDezpifGD3z7Hti0vcbC5mcraWp55uoQ1q5awdEktl1/5ZmpKnCwthDeur2JoJMFI5Gy+5trLLT/9NTl5+fh8PsBBJBJBRDjhxEaGhwPcdefd/O22HxLr3wMmxBc+sZ2Fp7+H/OpFhEaGyPW5qauvpajIQ4kPEokEVVWl9A0n6R8IZpyKIpOBrib6Ow9SVVdPS9N+DAZxCJjURxmC+OaBs4yi2gYal61l1+bHCAxte+UYJKO9dOx6mGefrOENF1+CXP42+gcGyM09i613P4eJBbNIDUCEHU/8im/e6OdL3/oUp26oJhKJ0N7ezq6dOyksLOSpHDfvetPbWX3LzWx94bkstukEyQOTPs1LlMTwbhLhpRQ3LKdvtwOTMBBvZuJRQxJAK6FDT9G0s5YTNpzGSGgEcTgQESKRKInwMJjWtO3kgbMKd+VKXP5iqmuq2du8mXDPQZB8ihoWk+NyEAuNjkYxfLhUhg9x6EATweA66upqiUajjITDrDr7Il581E2k6zGszlqZOEiMRAgM9tN2qJu9u/M4a0MpuX4waypxOjwM91zMzk13kIhZ26ipreOcc87CGLtjhlhdlqLxBN/98W08cdt/YqI9WZQ9eHJLef1l/4Df72Ph4oVcevmZ3HH7o4SH2hh/OqMkg+1b+OW3Pscl7/935i1ooLCgkLLyMk495TJ++b3s9q2UUkoppZRS6vijnTOUUkoppZRSSmXJDzIP3H6INmfx+SSvdNKQcjBOYBCIZLHuCJGevezbsYPiklKKiosIBIZxOpyQjDJm5AzxgEndZoyR/g7cFQXkFBaS73OSjGf3bXan20UsDlXV5SxetozN7ri1u0lEwgHCw/24nC7Cfb2MffF95Eteh6eIJStWseGUVSyvdvLC7l4euO9vvPDAg7hz84iG+ogO7cMk4yA54CiDhBMkjtubh8RiLFm5kvdccSYr6vOQlMEJkhjufvB57vvz7Qz1DxIcDnBo73Ziw93c6/RRuWAZr7/0Ui697Exq83MoyXVTmufGAPVl1kgSYm9wYGCAYCBIVVUJKxfn8rObX2DXy9uJB+KMdtpJRLvY9/TvKW08lYXrXkdhUTELFzVSXeYg3wPeHGukk0g0xoE9O0hGh9OLIzOTIDjYTU3dfJp37iQwNITTmToCiQ9PQQN4K3C4C1m45nR6m14k0PYkVsegwyVCtIW23S8SibyBN1x4Pk89+RzhUAU7n1hBuGeYzNPzHCkR7uLB33+Poop5fPpzV7FhwzwCwwGa9+/nua1b6evtpaw4hw9/9Hr+6R/fRyw2XuVxAgU4C5cijgjx/h12mlPrTZT4YDPFjW/A4GR4oIpYlwMieycrOBIjrTQ9+xCVdfOorqtjYMAa5cbhEEQcGCRtX8WIpxpvQTG19fWYkT4C3S2AC0deOfULG+nraAdnLiRGsOLa7hQVHyTY38VIKIQ/N4eFi+opLS3D43FzqGkPbd1PTdAfKwH0E+5vYu/O7dTUVtE/DJXFgqPaSTJZSiJ+Ng/VLaO9aQsA5553PgXl5RwYMYgTqj2CE8Mv79zE97/xFaKh7knK57DC8gaWLFtMOBJn7eoaaqq9LF+xguWnnMa2h1+eYM0EB7c/QHDwGk477VT8uXnE43G6e0OsXbcq6/0rpZRSSimllDq+6LQmSimllFJKKaUmUADu5Ti8S3EWnQy5tWBiU1jfAyTAIeAtB+cioIKxUyqMRwiHR+ju7sLpcOJ2uxGHAyTJmA4PJv0FuCEeOEQsEiY3P5/gUC8mmUWaTYLoSJDBgTgejwu3x4PHV5pdNg2EQiH83hzMSHrnjCP5iutZumI565cW0DeY4PGXB8krLMFXmE+gYz/h3jaS4V6IdkHkACTagAhufx1v+dA3ueqTn2f9yas4e201jrRpI5IGWpt3s/Oh73LouZsY2H07IwcfID7cSzSWoKOtjQfvu58tW5s5GDSvpPSVrSSHCR3aQUdbG329vSQSCRoXVFPkd1FeXkyoYzsmth/M4U4WyfgIfV1dDA8Okuv3UVjoI5qEg0PgzytgcDBJa8sg7XueZfwRCY4s1Gigi4XLluLMz2N4eJiR7g5IBgAHucV15FcsIdrfi9slBAe7aN7yhzHpOixBNNBGy4EDlJR4WbiogbKKCv4/e/cdJMl53nn++6bP8r66qr2Z6fGDcbAECIAASJAi6CRQoriUWZ6kiFspVicdQ4qTLnal1e5KulgGZXa1cpS0EiVS5MqRlGhBGMJjMBjvu6e9q6ru8ibN/VE9GNfTM+SRcRGL9xOBGMR0mjffzJyIrvdXz3PPEz+CYiVuczzro3LX+PLnPs1f/eVT9KU1du4eYdeePbTrNY4+9VX+8s8/R6R/L2974IEN9hZADMQgKBmEEcatTtINLF3/zLi0iudp16ps2bWT7NAwerAfCF1/0A3OYeM6PmdPn+mO2fepVqs4nc56pRD32l00CxGI0HY9isvLrMwvAXFEeJTU+D527t6NpQlwy1ftu564UBJEk1niiQShkE4+b5BIhBkeHmbnwbuxew6BsK4a2/VjbbF84Wme+rs/54XnX2Rmrorh+mR1QU9WsHVbD7vveQ8Aqqbxvg9+kKNzHV46VUd43X9JJhYq/PZ//ydq1eot5uYKRTV59If+d7K5FPvu6OHgFgtVgW3bBzjw54yF/AAAIABJREFU4PtRzdim+3tOlbNvvMT2naMMDuWIRsPUai1a7dt9viVJkiRJkiRJkqS3Glk5Q5IkSZIkSZIkSbqJMGpsJ3ZskGAySdNxqBYKeMUifud2GlN4dBdwLQiEIBJF+En8YhSaF4AaUGfjIIMH3iytxQsUVnoJhkIYholuGqCFoaNxwyLx1drLuI0ahm6sV+wQG293DQshVOJxnWAQ0ukMPWP3caEws0Hbieu5FBcmiEaHwL/VArEgkRtjfHyAwaTK8UWffF+G/QcPIoTg4vlzNKoVCtPnaRYv4rc9cKsgFLbe+Tg7997BgYPjbM2qJCxxTdUMH8D3iUVjIJKo4ThuZRKognMOv1Ejt+tDjI2Pc+zoGfbtyrBrZ4xrF80buOXDTJ3eSyyRYHR0mH074uA4PP+1L1OcfOraSiWKyeCdT1KpNEmmUni+R/+AQTAgyOITORhjct5hftHHtm1Kt5idq83PzPNAJELAMKhMn4PGJFAnmtnCT/3qH7NadfnKl/+Z3v5+po89he/cvEVJq3iClZlzRKMK73h4jGMnEuR7e5l47UtMvjHPrQI1V6svvMyf/OYnyGV/n3vecTfnz/YxsvcOjn/9c1x87o/59f9rko999GO8+MILNOrrYxI2aP3gBlF0ELqCr9v4nstNn02/geu0sGybweFhdEVh+qiLU3puk/H6QAWcaTrVIqulEql0mosXLtIsr0Jn8cZ9nTLCa6MaOmtra0TMIEq8n9ToKENjYwQCQdYWZ4Aw0KEbsBGAAoqC6/ksLS5Sr4/R22uSySqEIxngUVrNJi/8Q4XO6uvcEApZfy+1QC92rB/fh8XlNvO9MB6DqCGIJ1QOvv1xvvU/P0V/X54d++7myILHHVttei3w8fnyc2eYOfEs3GY7E4B4fg8jOw4SiSiMDatoQuD40Ol4rCzO4zm3qvDjszI/QTqtUq1qJFNRdN3AW5YftUmSJEmSJEmSJEkbk78xSpIkSZIkSZIkSRtSYlsJ9u8im8vT19/HxMQEkWiMxcYs7dvrEgK4YITREykCiTj4PnUEnSUHFAXcNXDP013wvZ7AazsUllcwTJN4PI4dCFI2AvgNk03bo3h1/FoBXddRxCaL39eoU1q4QDrjYWoaHadDtVoG/+YL/le78Ma3uOeDn0BoAn/TL8+rpHuH2DWWpFJzeP6VGSYvLXDm9Bkq5QquD41GGyOao1lpg9JAOHE+9jMf457HHqPWCXL2zDwHe/Mo4rpf63148dQCv/MffxXfXcVrifVLX29j0Z5m4Y1/YnzbONt3bKNcEbg+qNcXNPBbTLz6GTrtMju2/zzpmMZXnj7L81/9R3zvxnmvlVdZvfAcmZhOeGSAsK2g+JDRBamIoDds8LRTxzdSdIt43l4QotVuomkahluD+utAE4Ade3dz4N4DzExXqDdaCAHHvv4Xmx5LqAb77ryLfE+AeFAg1DTnzgZ5/KO/yOcrJZYvPntbY+ryWFs4xn/5v/8df7DzL7j33lEmJvYwdfooq2dPcfKlL/Dp9hKBUGQ9nGGBMgxmDtUOMLJjO4WVAmhQXNzkYfFbrMxcpG90G6FQiP6REdYWZymuRsBf3WR8PnhlVi+e5HQszf2PPkoylcTv1GnPtDZo1aMACqZp4boOVjSKnU4zNDZGX38f7WaD0soiWAPQboNXAUxQIuAsUl05j1DeCfiYJoRsga6C7yXodDp4vg0iC/4a3RYyKsLM43dWwHNxGlWqS9MsLSxw9MgpMuk76AsFiWgC04Dd+3eRH9nLIw8dpOhEGexVGY5025m8fn6F//r//Cb1+ee5vfdcgNA49NhH2btvhHRKxRICAVgGuG6b2fOv47u3/keuXqtj6B1MU0fTDHxfgKHecj9JkiRJkiRJkiTprUm2NZEkSZIkSZIkSZI2FOvJke8foCfXg6br+D5omorvCW5sT3AzTVTLJtWbp79/gL7+fgZ27sAeGAM7CmYPiH42/vXUBa+O026xvLTM2toauqEjDBsI3uK8LjSXyGTSrC3PcHuLtgrxTI6graFpAnwP0wyBEr2t611dmSMcslG1zVu2KHqAPQf2M5Q2+fobZeYXVmk2W7iOi2HoWKaF57mUF+bRTItQMkF+6wh3P/IQvQNZLMvgnjuyZCMbLwKbgQDD+95PuPce/NYi3UCDv34NJq3qDM998bM0m2vs2RFFucmlee0yM0f+jqnzZ1ip+Zw7fYF66eJGG7Jy7lu47TpCMdm7ZzuZiEG10a2TYAiICMhY4NTXuHIvbv2RhFO9iNdp4zYW6C7qd/c1DDh+9AJTl6bo7eslkYjRqhc3PZbvNnjh6Wd57UiBatsnEhIMD5kMDA0R79sDfKeL6j7zF57jk//+U+RiCvfdu5uB8d0IIwv4nHn9GQpL8yAMhDWMkRolNjrGwJ49DGzdRiidJmAa4Nnc/PnycCsXKC4v0m63MQyDrfvvJDH+OEJL33qIzhqLUxMszC8wOjZGKJ7GzBzc4Fp1UDScVotINIodDNE3Oko6k6G3rw8zYJPduq8byvBqCG2k+154LYSWx7LCjIwMkcmY6JogbUPegN2jFh/40GMcePQJcnveTWj0B9AiO0CEEHoPQu8HdLTQIPe890ne+/73kUimOX26xOGJDo4LuiIwzBCHHvpBHnzne5ktthlOggkUKy0+8Sv/nTOHn+HW77gCRh96+l5ivXdy38OP0NtrkIsJwqLbHsVSfGrVGrPnXr3N40XRFdA0UFUQQqFcvp1/ayRJkiRJkiRJkqS3IhnOkCRJkiRJkiRJkjYkgFqtSqPRYHFhEddxaHc6CD0KGLd5FBcPD9u2CUfCpFJpenv76BvbQiCfR8/2IOJbQAwBFtcuUrvQWaQ9fZ5mscDa6ip+NyHSbRFxi8CEcEtEQiFKxQa3VThSWITjOcI6RAKCPXu3MrLnTrTMvUDolrsrRop4Ko0VHdx0bKFEL489dIBL81XqbZ90OsXAwAADgwNkslkGh4dIplL0bRljy947ePeP/CSHHv0AkViQxZUaqtphJKOjiBvP4QGxkM7Ijj0M7LgLNTgGinnVTw3QtuBicuLoaUJeB3WD47x5PLfDiy+8ytR0hTPHjuB3NgpACPxWEYHC3rvu4v0PjtFjQDp01YcOAgazIe5/74fRA5krf4m16Zy26g0mL17Ec6+tXmLoguGRPNmeHoZHBunJRLutXzbjd5g+/TxTk8vUm6Dr0JNVyWSC7Lv3EeJDbwclsD6u2wwf+S2e+9Kf8Jd/8UXu3p/hnvvvItizi2vCD2oeq/8Avbv2sGvvHRw4eBDHdQiHw9iBCIjMpudzKhe5dPxVVldLtFttUuk02w7eh5XZRzdSYLPx89kC/xKdldc5e/QwyWSSdDqDnRoGLXvtpkJgxmI0lubRVA3DNBgZHSWZTNLbm2dwcIBsTwahRTDS9yE0ExEYAi1PeOht9G47RKvZpl53aTT87ogE9BmC9z6ylZ/46R/njrc9gCp0jPg4CA3fWUCoGogI+A65TIrlpSU0TaNRb7C06jFZ8rFMUBXoGdzKfNUgGhakDEHH8/mzLx3n2WcP42NucP3XXCBgYUSHsSIpfuz//A888fg42fVghiW6TZamV3xOnZigXJi/1Z0HIBwOEQ5qaBoEApDLqcSj8qM2SZIkSZIkSZIkaWPyN0ZJkiRJkiRJkiRpQ6ZloWka9Xod0zSwbAtd07Gise/gKD54Dp2Og6oohMIhotEI/YMDDI6Mku3vx0r1IBLbwN4PYgCIcU2YolOnXVihNDVFu9lEEQrdcMjmC+i+3wF8MkNjt9wWAKEiBNiiu/g7OBCgt7+PcCq9vru66XECAY/xsTTZkd0gAjfdLjt0B1uHEjzz0jm+/dzLPPfMs7zx+hEmLl7kwvnzuI5D//Aw+cEhXE1DCMHI6BAXppo89+wRooZH0hIbjsQBXjx6iS//zWfJD40QiKQRShJEcn38FfQAHHjHe8jm+phYaN2yQIBt23z1a4f5xj9+AXz3+kmj+9FCE98tcO7wN8ikTNq+wHGuzJgAfCFIZnpQ1Mtz4wI39Ne4hu+7rJaKNFuNa/5eUWBsLEE+nyWRCBGM6Chm5iZHuWJ1+kW+9vd/w8WJCnMLPo4n2LIlxoc+/Dg//xu/S27r/d0N1Sy3+5GJ0yrw337j/+B//OkXePydB9h3/zsReuKqLXTcZgs8n0g0QiQSoVGvo+s68WwPWtBk8zYvHjg12q0WuqFjmiamaZLduh8lepDuu9Jm42fTg84Cc0e+zonDr9HX30csmUaLjl17faKDpni4q0eYP/l1dF0jGo2Sy+XQdI1INIweiBAe2YsQCsI00Q2VaO8AViiCZdvU6nUKK3WiJly+w5qAgbCgvy9MvreXoR07MQJhhGqD6+M1lxBmCjue48Vnn+bFb7+A67gsLCzw/Ldf5/mXZ6nUXMIRgef5nL5YJJcwUPF5Y6rJMy+ewanOgVPZ/CaJEJjDtFfeIBUP8b533sGWmEpO7YZIdKDd8VlY8mm1OnhKthsa2ZRHNKxh6yqqCgiBYQj0282tSZIkSZIkSZIkSW85t/HVIUmSJEmSJEmSJOmtqNFoENYNdF1HVTVCoRDNZpNQJEL5trP+PjgVFCHQNI1gMEgwGCTS7gCgzAtURWFFVWjWI3j1BH6tBI1F8KeACviL4ATpLDdZ9QFdA6GDr7L5oraC57YYG0vxba4PFVzPRo9spW9kBFMTWIAdUOjvzyOE2q2o4FbZLMnQqq6RCgq27NzLxEuDeO1TN24vDLbtu48jR87y+//xP2Cm+wnE0mR7skSjUWamprj42qs0Vov4qkogmUZVVF566ikOvv3tjI308cDOOPpNepEYwKFtvRx46CHOvP4a7UYH1Yrh1DwQafBX6JSnKU6dZf+PPUkoHniz4clGhKIRjiV49ZmvUVk8tuEcdyMh3XYt4XiahgcxAUHt2uMqukL/QI5YfgeLZ6bohjM2u3/g+y2atRKqcK75+4CAgC4IhQ10HZKpGNHsFpZWT256TN9rc+GNbzI383Gi0TC2gHBKQVFNLGsr977rR/i7C6/iddbW91DXx7m5xto0//XXf4F6vcU73vUOjnzzb6nMLwMCvA7tapXl5SVCU2EsyyISjVIsFInEYkQzWQoVC2ix8fPl0y6eYPZMmmwuh+d5hMJhevK9NBt3sXiijl+9/KxpXL4fVwj8Tokjz36LaDpDb18vK7ODlIuvgl9f30anWSvhO4u0C6ssL8wwvm074UiEeCxMvV5lcWmRUDiEW3BJjN+L7/lEUyk8x6FWrZJMJrBMn7wJqrhy7y1ge6/OzJ07GRjsZ3Zqhkvn72K5VObsG6/jdFoEI2Ey/cOMbBljcXERgMLKCk/NzOA4B9i9Z4BINEiz2SYRUJhYbPCnn32O5//pD/Eqr2x6z0GAEoT2FJoV4OH3/TBDvRE6oltv5PI4wypomovjuHi+Df7mzyYY6HYcVQhUrTv9wRA0N88bSZIkSZIkSZIkSW9hMpwhSZIkSZIkSZIkbch1HBqNBqZl0um0sWwbVVVxIgnQ+6Fzjlstrnf5qJqKbdsEgkEi0Siu4+C6DqqiUi6vEQqHWVtdo9lqUq9Waa+mcQphaJ0ClqBdAfK0lxyIxEE1bnlqRY8RjkVJpzUQ6k0XW9XgKHZ2P8O79pFKJbGV7oJtwIBWq4Vp2RiRbbRLZaCx4TEAXBEgGjbZc8dunu/bTXliCvxrW22oRpAtO3bwqd/8JIWJo5jtFmY4Tr1Wp9lo0Kg3aAOuU0foERTDZHbiIpGgTbFQ4MB77iAXN7lZJxIhIBIO0tObp7i8wuzJVdzaDNAE4aJGd6JZgtVam764w0BK3fhAb06iRa3exqvXuTE4oKCoOp7rgpYkO/44P/9L/5a2r1Js+GRtEFcNNGrAIw9uo17/9/zV74eYP/UvOK01NuV1WF2ZxWlfe24PEC6YpsD3oTcfIT88ytKZzSqkKKAYFGaOceHMKXbv7cVQIagKgjbULZWHH3+Mw8+8k4nDf8OVB0zhdp7zdn2RT//WL/DYj/4SWw88xGtfehV8D9WKoyYSmLaNEIJ6rYZlmmha9yOZaHYbhUuz4JzmxmDF5Quu0K6u0Wo2URUV3dbpyfWgKALfc1k6oeHXLwJ1umGSq+erDazSWZvl8Avf5u4HHyaZ66NyMYrfvhzO8PExQOtDT2RwPIVyuYyiKCRTFmrJYfuOHTz/lS9jBFL4bof68jRmIEAml2fP3r1EIhF6+yJ4190CIWAwpPDBBzKcXMowNT2AblrMP/MMIGgXplntZGgdOUwwGuP+B+5i9+4BPK/J5OQqxWKDZ54+jet45LJRdMXjP/+3v+bPPvlrNCvT69cq3ryOG/ngdgMffTvezQfffYj+oEDhqqougKIIUkmNWCyC6hVwbnYv1imhYZL5ITQBnku3esb69UqSJEmSJEmSJEnSRmQ4Q5IkSZIkSZIkSdpQu92mWuuGC8KRCJquY1kWSiaLldlKc/Yit7NoLcwwILBsm2gkQigUQtM0VFXF97uLqaFQCMMwWF1dxbIsKoZJXTfpzLWhc4ZuKGISvBVYS4ESYfNWJTp2fISRsWG29iioqonrdDYYnM3IwScIp/vI9mQZHe1DV7ptDvT1OVBME8c3QUuBM33z+Wqs0FwrsW/vKDvuupdXFl/HrZ29ZptIspdiqcnZYy8CTTorF2iujUI0hh0Iks3ncF0HkUqxtrJCIBRkbNt2DNPkjr1beGh/36arvz4QtRVW5qZYXlkh3LefylwEt3YJvDUUf5XdD3yMLePjKEqAlHqrhi86qqpTrzdACIQSJDV4kNzQFoSwiPcMUJo9wfEXvoSmVDlzqU5L7dBsdHjHvgA95pUjmQhSUYVsT5YtBx9l5dLxW4czgLVCAad5bSim4UEgCHYL6nUfVdPZf2gPR76ibtB65TIPfBenVeWzf/hHpLI5hp7cRVSFviB0OoKdu7L8wI/+JH90/jma5akr+92Eoocwgmk8T6BqBm67zNf++rfY+8jPEEwMUSvMopoRdDuAbdm4rsv8/DyZbJZwOESr2SLVN8ilySHcuQvr57r+fALwcNp1lhYXyeXzhAMRNE1jYHCQcDjCadtm5ngMt3QE/MIGI+1A5wzFU2scMzRyY9uYsdJ02vNv/lzTDTp6P3Z2O8FQmFq1BoBhQi4foK+vj11334dl28zNzBBLpBCqRmO1SDyRwDBVLFvgX/dECUARENME6ZhPu2MwOJTj6BtR/HYZ3ynQLk7z9vf8Gu9/8gNsHY+SzQha7TCZbIpazWdyosgLTx1l+5Yd/NFf/At/9qlfoW9kK6M7f4h0bgArFGV6cpZjLz3F/PmX8G9oc+IjVJv99z7MXdvTqOLGtkAWEA/AhQvn6DgFoHnT+w5gWBb79mzB1gXtFlg21Ko+9fot+gRJkiRJkiRJkiRJb1kynCFJkiRJkiRJkiRtqNVoYDgOruvS6bRxHQfDMAhHLEKxJM3ZKFBgs1YfAH5rBTwX27a7AY1oFNMyMU0Dx3FYW1ujXW9hBwLdQEiliud5uJ0OGGnoFIAi0AHWuq0Y3AG6TTxu0kNAhEkP7mB4IE/AX8YXJlC9YTPF7CcQy5DJZkin04wOJdBFt1aCpoJlmXQ6HTzPAW+DcMdVnFaD145e4MM/sp1Dd9/J2Veeonj+PFcvtsczg0xPTbPzzvt52yOPkM+liCQyREMGkzMlXnzlFJeOvs7qwll8B5bqFTTdQNV1fupfvZ1EQL1FmAJsXXDv3bt4/dUjVOanCfXtwO3005g/SadlUC4W2bp1jFgyDEDd9VEAQ73xTqqagmVbTM2fomf0XvY9+CHe++QHOLQvi9PxqdQ8ysVVzp38MVqVIhPnzhOJxRjsj96QMRACQjoEgxYjo6Mcz26jUTrFLQM+noMQ7jVja7V9XOETCghWVz2WlzwOvu1O/iaxnXrhjZsfy+/ew+WLz/DSt1/iw0/swDZVAsBIFKZ0wYeefBunT36Cb33+9+isnWGj51vRwvTueAd3PfpDDIxswXFcDMOgVq3wjX/8LCde/gZ2bIxaYQnVtOl02vi+x8z0DKFwCMu2icfjNFstkukM8XQPK/OJ9TYjpesHDah49RaFxSWKhQKJRALPc1EUhZ5cD4uLCxRyQ9TaFfxqiSvVJK6e2zY4M0wf/hLt2hJmIE6nvF4VxOvQrpWgXcVzHDRNw/M8SsUiTieHZgkSiTg7d+2iUChQLBZZbTbZtmULtUqVVDpFMmmRi0BwgwdUAJqAkYAg1guxYD+N+v00KmVOPl/lnoffznt/8D2Mj8foSQliBtS1buUVzxMkU3HSmTSHDx/j83/2J3zw47/Mr/ziT5JLBvEVqHmwUvd49sWP8oXP/D2vfO0zVOZf40olEoX8+MPcef/bMdQbgxmC7jsfNQT5fAYzNkKjMc9mDLXNnvE8ng+e7zM/79Judei0ZThDkiRJkiRJkiRJ2pgMZ0iSJEmSJEmSJEkbEwJ81qtbCDqOg+G6RMIRIukeVqwhaK7RDU3cnN9axmk1MQwD27YJBoOYlomu67TbbUqlEsuui+M43TYYAjRVxXccaF0OVHhcWSTvAPOAzUaBCwDFyjAwvo2BfBK3DqHsXsozT3HtQruOCA0QSyQYHBykf6CPVFRHWV+6NeguuqYzWYqTp3HKxU2vUwsMMF1SiNmC3buG6RvfR/HiU+Bdrg4hGNl5Fz/1v72f7eM/wWBEIyAEHqDSbSxR+fDdvPSxR/jzP/0cX/niV3HsJFYwxF137+WB/QPcqs5Fd5FZcGhnH+m+QSw7RK1eJ5ocJjOwlcLcHOdfepGTe3fy0Se20vZ8vnR4lbn5MrlMmLnVa1s5eL5CqVhi7K4P8OGPPsnd9/QQDyokdEFkPcQiRnsQh3oAn6XVFtM1lcGsIKnduAge1ASHdifwvF0889URls5a4NXZjOO7KIZ6TTamUnFZq3ropqBSbrK2VmXXrkFGdt3D8aeP023tcXOKZjI1Pcf8UpWtkQhCCBIKiJCgFTT4yI99gKXFAse+/hm85gxQu7wn0Z5dPPSDP8uHfuS9jA4nsSy1W5RDgVLZJ9OT5Z+/+C9MnT8DqtktPdHusDY3R0dVsWyLwsoKuqa9WU1j647dFE+/gde6ePN7awaIpZK4bjdwEQqFEELQbnfI9vRQKBTA3Ub17AXwynSDCZebdkD3iXbBX2DxzBcx49tBBNZb72j4nTo4KzRLBRqNXnx81tbWWFtr0Gx6BENhhKKytLTE8uIi/QMDNBsNMj1ZggGLoO2T0ATKzVruAKaAHg3slMJdd41Qrb2Thx67nyfed5CeuEbCEN2qNQJCCthBUAWUywLXdTl/boZf/S+/yw89uJ1kQH2zikxIhXREpf/hfvaO/Wu+fM8+Pv8Xf8L5Vz+P16kRy+3k45/4NT78zjFC+s0mGEIG7N23g713P8aLf/cSN20zA4RjPWwZSNJ0oF7rcOrkJQQ+xpvPiiRJkiRJkiRJkiRdS4YzJEmSJEmSJEmSpA0pfgvHdWg2mwhFwTD07jfgdY3B0VGWpieoXjjBrcIZCA/D1KnVaiiKgmEaBIMGwYABPqyWVqlUKjiOg653t6tVK/jtNvgC1DC4K9cdtE43sHH14vMVdiLP8OgIubSN20kSCiqUb9hOgw5EIhHy+TzZbJzoVV/7bzrdyhmpdIrlVIKlxVt9I75Dpdam3vQYGYgxtGWck8/04lS64QxFD7Pn0D3cty9NVBcExJVv7EM3VBE1VR47OMhD+36RU7/wY3zrlUlePrnEE4/tJ22rm3U0uUYsEcLUNZxgCF/VaDQahMIh9t17L1OnTlFamidjeZSagmefP8nKSgnTNDl66tq2LX7HoVFeY3znTqrVNqtrELAFhuguoF/fwCIbs8jEundko0X6gABF+NTrDqn8ABetJE5983BGq17Ec69dJFcUwfyiQy6nUq83mJtdYMeOKPc/chfHn/mjWxVzQSgK0XiCN06XODAUIawDAqI+1ITgwYM5Wj/3k/x93wDnjx2mNHuadmOZh9/7fj7y4x/jjl395MMqthBvnsoH1iKgPjCK6z7Kc98yWT79DZyWh2a2qC1M40d7KOsGnusihCCf7wUgm88TGd7J6rn5jXMlwsZM9hCORGm1mpSKJYaGh+h0uu9eJpOh3W5zuFBYvylXv5M6CA2ECajd6iF+hVbpFJAEqiAaaDq0WaSzcp7CfIpUKk25XKFSbqPEDIQQvHHkCPl8nh944gleeeklAsEgI2PDbN8RZrhHoS2u1OzYcN7pvrVNX5CIGxw8OEwmG2I4rZBQwBBX3gddgPChZUE0KohEQjz5kcd54uFdRNdDXOKq4yoCorrg3pEABz/+Nn70PXv49P94iGefeZZo/wEee/s4/WFl07ZAHReaLY9kfgjVTOK2FjfeUAkyuPN+euIWKwKKpRpTl6bo6Ynz7Df+BX715256DkmSJEmSJEmSJOmtS4YzJEmSJEmSJEmSpA155Qs0rUGavkI7kSASDiNE9xvsmWyWTN8Q1Zmt0DoNtDY5UJvi3BTl8q71AIZGIHD5h0H6Bvq5dOkS9VqNVquN0+nguS6RZBI9l0K3Q3itEisXXsRrLtL9NrtPdwFa58bWJirBWI5cvodISOHSxCrltQ7d+hRXr3w7hOMRNE1namqKUFhH9yJAd8FdMyGdDiOAvfc9ykkVFs6+1F2w9ZtcW80DOtVJ3nj6H1n7mXeSTwXI9mSxonmqlZMAmKEso9uG6QABrl1Y5ur/FwJDE+wdy7JrJMMbk1UycbNbVeR2aSoLE6fJje0i4EdwXRdN00kkkzz8s/+GfEohoCvMVl3W1iq88PRTNNcWKZz98jWH8fHRVIVGo8H5cxcYGMww1BvgxpoY6+O/IbBxrboDF+c6FAurLE5PdVvX3EJrdQmv3bjm7woLExSX1zCtDJVKhYsV6ulJAAAgAElEQVQXLzIzm+PgvXdiRrbQWju96TEVK4EdCKBqIearEI51x64ICAMhS/DDD/WydfQjnJ14L6dPT5LNhPmhx0fpDyroV92Ly//nA0lFsL9Pw3jnNvDbvPpFlVplDa+xit9ehXqQZkHQqVbx/e7eqVQS1/PYcfAgL88dxinPckO6RIkRTmRotZr4vs/s7Cx9A/2omoZQFAJATy5HKBajrAfx3TXQo6iBfkLZccxgFEUz8DyP4qXzOIWT6y1UWnQratRRFAdoQ+csa2c9ZgJBkqkky8urRGO9VCsVfN8n39vL0uIiC/Pz9Pb3s2XLEMGAgqZ0kxnKLZ4BRUBWgBZX6YlEsAXElG6FjMvz6dMNaRii2w5FVcGyDYJhjYIr0LTufbre5ffH1GB7X5T//Msfo/TzH6XQ9BiIaCjiZk9ulyHA7Tig6CjBQdzW0o33AhAK7NnbbYmjugJVFdTrdfyWz6nXX9jkDJIkSZIkSZIkSdJbmQxnSJIkSZIkSZIkSRvy22v4i8eBOG3DpN1p43k+juNgGAb9I6OU1+5h5UQVOhN0FzGvXshUEUYPmp3EddcXXT0PVQXTFOgGaBo0W3ESiQRnz5xhdbVEMBAgkUgC0G63CEci2PYYvpVk5fjT+K1T6+cx6bY2uT6cITDtINFoGFWF149eoukGQMTBv7oCh0ejusC3vvj3pAaGqddrvPvuLD22CUBMEwzkYkQiEXTD4N0f+WmmL72LqfNnaFQKeO06rVqBtaXzNNcu4XstLhz5Ki+/cpTHf+AeYrEwVjRLdaYbCgmEUySSCcxbrV5fPYOKYN9weP2qbl8oECYajaNpGuFolO07dqAqCoqqsmM8zUN7QiDg4lyDiXPnmH7ty3jtBXDL186kplMoFMmUy/T29tLp+HgdsG/WGmIzPqy2obTW4fjx4xRmzuF3CrfczWlXwL/2Hk+ePcbLT32Bux/7cRoNh0qlwqXJZfbtH2Tr3R/g2Fc/tR4+2Jgdy9A/0E9PLkrZ7T5BBlcFZgREVMGdQwahaIJcLsxITqc/KDaoGLK+D91CLwEE2YTC9h1DBCyfam0JtzoNOFAP4zdWcawgzXCYiq7RbrdQFJXBoSEm+nczf2ICqFx39G6oyHVdLMsCfBbm5xkaHsbzPJxOh2AgQP/AAJWVBwgEDIKxLMFIFNsO4Ps+zWaDQqGAnRukaUfolErQKII/C94S7fLk+rk6+O0CS+dOMdvby+RElt7eHGtrawwMDiKEoNlsMjI2xsFDB9E0k1YLOj6EbuMhvbxJUnQLeiCu/fs355Ju9CoowDJBEYJ63SegdsNNtzyPABVB0lZJ2uoN59hoXJYKY0Nxzo4MkRzYw+LaWXx39cZtfY+hfAJVgIKP03EIBAKcP/Yc1fKN20uSJEmSJEmSJEkSyHCGJEmSJEmSJEmStJnOJWCZzorFajJBOBzGsi08zyOZSpLK5ynNbcctBaFTBOZAaCj2IFZ6K5nBHYxsHSeZSjE+Pk4kGsU0wQ6AaXTDB7GYzvDIMOVymVarRalU4tLkJIvzC0RjMYLBEMlUknK5TDHUg9uaoNvWpA0kgFWuD4VouommaagCfM3CMj2q/tr6z7urwmZkFMWv0CycI7F7D48+ehf5uPFm14MYsH9LjHP33cnMzCI9PT3s3rMLIR6jWmsRsG2E4jAzNc/E6aO89tTfMnniRZ5/9QyPP343mq6jaVdSDIIOuuYTUr+zW/CdFMy4zHVcaqUlWm2P1ME7qVWr7DtwB4ahkO+xiamCiuPzxslZTr/8L3iNs3QrgVzLd31KF4/S3radWDxOJKITMq+0nvjOLgQyAXh4p02cfQznDP7mj1vMn/7Khue+er/rl9V9z+Of//r3GNrxINVqi/LaGhfOX2J8fJR7HnyAE0//JV7zZuEMld6+Qfbs3YuiKDQdKLrQo157GiG6IYCRuCAfM8go3Q9RbrXArwpIa4JkVENVBTTPg+8CPviT4CtQD1Gb1uk08ljhELquE4lEGD/4NhYmz+HXDtOtEHNZh06nQyAQwDANnE6HudlZstksmq5jGAYAO3buxDQtyuUylm0RsAM4jkOz1cRxHILBIIqi0AoEqUdj1BcDeFUFGit4zeUrp9NUOvVVZi9eJJFMMjQ8jKppKL7PiePHyWSzDAwO4TgujtPGsg1cD+zbfLYFt36uLwc0TCBoC2xbEAsKkqI7x7f7Wtzudr4PTQTpXIB9+3eyvPReXtBcZl7/PL57fVhGIZcJoiBwXZ9iqUwwaPHst796m2eTJEmSJEmSJEmS3opkOEOSJEmSJEmSJEnaRBto41dPszYdJhqNYds2rWaLaDSKruto0TgYFu7iGegUCffdQ37H20hlMvT195PL5UimUqRSKaIxm2hUIRjshjN0AxQVtm7Ns7iwyOLiIvF4nE67Qzqdoaenh3xvHoTA6TjMnz9PrTQI3jTQAcW6cV1fKGiWDXjoKkSTCURrHoRLNLuDXXe9i7EdOwkGw4TCFsPD/ezfM0IqGyK4/lvy5TxAPqxwYN8gqXScUMgmndFJxQQ6UG+DbYPn5Wh39rPw0x/kr/7wc0zNrdGoO3TabTqtGpeDI5XCJean59D2xm/aFuR7QkDQ0glnBqjWmtiBAO12m3BY48AdMVSlO2WzRYdXXjhMcepVbhqOcMr4bo2luTmy2STJpEEHQZvuovl3xIdCzePbr1/k9/7Tf+DYay9Qq3qsL9V3N7ih9QzQcTfqLMH85GmOPPs/SQzfz4WTJ6iUimzbvoVDd23jM2GLanPjYejBPLvvfRe6oaMoAtMAV3RnQOG6xXwBiW63jjdHeTvCArZmVUxTBf/qkEVt/c8qfrlBqzqLnx6hbNlMTV1i69ZxstsOsvD6OfBKV3bzXJx6HVVVwfdpNps0my1OnDjBwUOHum1rPA/TNBkaHub06VMAOK6DpqkE1QC2Za1X0GhSqVSoWBaGblA8t7Z+5Vc9A24BlCjFiZNMJpNMjYwAUCp2x2ToOkIRrK6uEo6EWF0N0hMQXM5mXJ6v7wVLQEiDYEgQMrutR74fb48HVAFVgWDAYnBwkPKdD1Gau0B17pmrttRQzK3YVgAfKFVcJi/O0qktMX3uje/DyCRJkiRJkiRJkqT/VchwhiRJkiRJkiRJknRr/grOyjEK8xnCkTDVWpVUJk0mm6VYLFKrVFhdniCY2cYdD32Q3v4BEokEiUSCSDRKONwNQsRiCvG4IBoETYCjg2UInI6Opqv4vs/g4CAjIyOEwmFs20bTNHRdJZ/Ps1oqcnj+MH6jCVoCLZzHKU1cN1aPVqNOo9FdnV+cmcHzXN72vn/LT/zcv2HH7gESIQVLhZgKthBvRgOurwihCEEkLDh4RxTVh0RYYCsQXv+5s76PA4zEImz/9Z/g689O0Gz71GsN3HaLy8mCVn2VI68dp/2unVjfTVuQ27lNgOdDqe0TzebpDUfI5XMEAkHwDYTXnW8Pn1NTFU4dfhavtbLJEZugaqiajuu6KAq4XjdQ851y8Dl2qcgnfvaXmT35D3RDGCpggT0I7Tnwuq1U/M5VVRxoA50br9X3efaLn+aHf+E+dMXj4pHnObJ7N//644+xbfddvPrN82yU6oj37iKby9NutdF1iAQEQQXKfve+Xl2V4fo/b8fl9iZRHYybfuriA6vgrdFerdNuDdKoN1grr7HrwAEKZ75Gp7rGm4EJv47XqdNsNqlWqwQCAcBneWmZ+bk5MusVNFzXZWBwACFgZXkF3dCxbbtbLaPVotlooBsGwVCIcLjGPLAWjeLWxLVT5behPYXXqbNwvofp8XF832f60hT53jzWos3xY0fJZLIkk3FCgTSq2m3GEv0O5up25lKh+55GQxBWvj/BjMvnsoBa1WdpcZXSaonFxUVEuA+UEHjV9S0VgrkxAuE4Td/n9MU1Jicmqcy8SKtZ2+QMkiRJkiRJkiRJ0ludDGdIkiRJkiRJkiRJt8EDd57KzGkKyRShcJh6rUYul6Neq3H+1Cl0M8idjz/J7gOHiMViBIPB9TYoJqGQTjQKkYggGoKg6H4j3gFWNQiHYWSkj0qlRr43TzIVIxSy8VyBDwQCgmIhzOiWLZzp2UV1oogaGiHa109hVXR7ErypQ2VljqXFAuWmR7Va5Zc/+WmeeGwvg2mdthCYgC260YDLwYyNaMCWVDfAYXRnAW19dVhw5ZdqAwgg0AIaP/zIGAsll8XFJeqlhWuO3mg6NBwI69/7RebLwYz5Dji6xv5D+0kmM+RyPTQaTTxfYW7Z544haDpw9MQlpk88y6YtRfDQgoJQMsHSUgFNHSCuizfn4Dsd4KsvnWLx4st0Zz4KhEAJQ8dHiexE7SwRGzhEceI53MbU+n6Nm45xaXaCEy9+iXRvP/Mnn+LIK69w/sH9vP3xd/PaU5/F968PdQjMYJxms4mqqnieR8cVTKwK2i70RyCv8//55gi6z7d+y+P40FqkMncRw7QprKwwNjZGauAA8yeX6bbsAWjRqa+wtLiIWA9aBIMhVkslXn7pJR5/97u7FVJaLRRFYev4OLquoygKuq7j+T5Op0PTttGrVVqtFrqm02o1Ka3EqMyLDV6CBvjzNBbPc+nCRTRdY61QIBQJUy6fplwus3vPHnK5NIoqKDVBMcFRv/cfNhlAwADz+1Q1w6cbFQoC+3OCtBUlFx9lZWGKcy9WgBDduhoAbaJhCAQt5is+L7xwmoX5WaZf+8b3YWSSJEmSJEmSJEnS/0pkOEOSJEmSJEmSJEm6TR28yimWJ3sIBINvVsbI5fMszM3T99Dj3PPAQ2SyWWzbwrINbEvDtLqhjFAYYgGIqt1F1gDQFt1FUT0s2Lc/QyQaIpezCYcVOh2oVASOA6bp02rqDA8PMzS+k1PFJQI9wyCcDcbpUSvOsrCwSLXh8uSH7me4J0hCvXFl95aVEQTErwpjKNdtf/V+Pt3FXV8RrNU6zExO0q5cvHIo1SYYjqJ+F1UnbpcHVOs+i3NtotEY58+eI5NJE4uFcVyXCxeKxI0gg0mTl5/+CvXSuVse0++0aLda1Gt1XMfH4Dtr8XFZy4UjR8/j49CthFEGKuDNgycY6HmY3/zk71J0A/zB7/wxR7/+R/juVdUjNh4dr3z9r9n29p8CZ5mpI0/zrW8e4J3vup9Yfjel2cM37LGyvMKpU6cIh8Ok02GmZxSiNoykBIn/Xz4l6eAWjlEOpbAsi2KpRN/2A8xPTkD9NboRJp9O6QxrfggtEqNVr2NZFkIIPM9jaWmJkdFRPM+j2WyiaRqmZQEQCATQNA3XdWm1WpiWRbVSoVgsYpomqVSKqqLg3zDNPtCB1iWWpiaw4klqzQZrxSLFuVmMcJhLk5OUSnupVYKMxCHxfWrYowuwlBsr23wveUDTh6Ai2JI02XpPHw/u/Qifv38Hf/g7f8DRb38Gz2kA0K6tYmiC4+dXee5bz1JZmaS0cHHzE0iSJEmSJEmSJElveTKcIUmSJEmSJEmSJN0+f5XW/GFm7RDRaJRwJILv+2RyPdxz770MDg0SjgSwLAgEQNMgGBSEQhDUISq6wQyTbu0Ek24VDQ3YmhL0RIOYuqANlBvd/VstUBSBYSrohk4828OWe99BKBSmUrxEYYPl4E7lEjOTkxRLLR7eHkYBxHexanz9Lpsd4nJgwQWWSxWmTr4ATvHNn4fT29hzxziB71NLkzfHpkPY8vHbRY4fe4NotNva5PzpU5x89VW2/cZP8saS4OWv/nm3fcUtjuo2OpQX51BVlXrD/64X3wMa/NLHH+YD9/8Z1UqFasNjpVhiaWmFcnGe7bv3cWj/NgIhi9mlf0Wt4XDh5X/Ab05setxycY7zr/4DeA06q8d56Ztf5d63HWLn257guc8dg2uqZwicShFN8bhvf5b7dujohqDUgqAFxveobYbn+UxNzVKt3mabC3eJ5uIZClYAO2DTPzCAmeylVT9Jt1kI4BXwSydQtN2M7NxFKBYlm81iGAbVapV2q4Wqafieh+s69PX1MTc7+2ZVGVVVCQaDaJoGvk+j0aBSruD73qbVY6BMZXmSZsdD1zTmJyapTp9EC4YprRSIRiKEQo/Tk4wTC37vP2i6HIqyv8fHvf4chuj+1/GhAYSFIBXQ+OkPHODx+z/Fv/utPfztH/8W9dVZaqVLNFsO33zmBGdffhZdWcJzb2y9I0mSJEmSJEmSJElXk+EMSZIkSZIkSZIk6TvjzFCbPMxkKEwmm8WyLELBIJlMBsMwsCyIRgW2DZbdXfQOKhChG8zQuLIArtCtNhEUgBAkzO432Bs+KDbYJtQb0GqDZQls2ybf20v/wAB4HV7++gtsVFnB7ywxdfJFZhefxNkewvxukhnfBd/3ma54fOvbx1g6//Q1Y3PqUyyf+ib1ezLY8eh3lxa5BQ3osWBCEQgtxMMP38fff/q3WVspUK/q5LbuIhgM8tuf/BOKc2dv54rAr1ItLqKul/z4bqoX+IBAsHvnIHt2Dl5p9+H7+N0/1reBhRaEIyGsWAbFiOE2b3384vQbdOe6zfzJb/Dtpx9i36G7eP4LGp7z/7J339F1XOe997975szpFb0DBAiSICn2JkqirGLJsuUiyy2249wkjhMljmy/suO77ntz3xsnufFNcWIncu+WZMuS1Ysl0ZQoUSJFsZMgQZAA0TtwcHqbmf3+cQCxCOxU7rr2/qwFFuDMnj17zsFawP6d5zm5aR6uWsQHP/NXfO7P3sOSKg8agp58sY6H6wrcDiklI6Oj/OCHP+Xb3/omgwO9F3ikDemjpEdLGHW5KC0ro6qmmt7+2chEcXLeinpar76OquoaMpksoVAIwzDw+X2MjY1RU1uLJgTZbI6SklKCwSCJZLEdh+F0IoRA0zRcbjdul5NcfJCpY1uwzdw55mZixnswLQ+EgmRHj4GvCt0fIFxWTiqdJpFMkSpEzlnj5HLNVmx5u8yObQgwTvmkhqCxzMc//82fs/6adfz9l/6S0f6jvLq/h1e2vExm8jAZe+JtnJmiKIqiKIqiKIry2+LtrAipKIqiKIqiKIqi/FayIH+cyeP76T5+HJfLRduSJTidTqS0MQxwu8Hnh5AHIhqUCPDPbHqKMz60Uz50igGDgIBqAeU6lPsh7IdwWLD0qhpWLGtl/NjLPP3dz3N858NvVgY4nc1Ix/M899TzxDMWtpwJAMiTQYArRQIpG4biFvv7U/z91x7iJ1/7a6zc6Ru26dgIf/flz3LjjTfzw5/cz3Qsjpxz7pdOCAhpgk2tHm64upWGphY+86W/JlSziFDLEhraFjCayPLK809w7nYhp0qSzRQYGhpCSPvNe3ihJJCfOVsBiFFs1FHM4wg0IdA1gUMTIATxAgRDfpwOB3Zu8gLPcvJa7Gwf2555BE334XT73vx8sKKVP/kfP+BTn7mT5ioPmhBIoMoJC/yXt/kvpWRsfJKv/evX2bRpE//jv//XiwhmzA6SQkbfID7YTe+JHirrm9CM2fkLdP8i6pffRGl5BblcnmAoSCgcIhwJ4w8EsG2Jy+XC5XYjbZt0Ol1c+3yeXC6HZZpIKdGQDB7bw7Zf/SN7n/kX4sMHOe8rojAOmRiZyTFkdhgNG+Hy4PF5KS0tI5POY5o2BYqvL0ue5WV5kYrBHcl0LM6Bg4cZGh6lUDCv+OvmVGd+f5qdh+nUWbp6Ddd94C8AB/v3HaNr38vI/DjSTL5t81EURVEURVEURVF+e6jKGYqiKIqiKIqiKMolyGEnDtPTXkV1TQ2VVVUAmJaFbYPDAM9MG5PAKe9Ev5DN79nHOEUxrKFLiUuzGBo6ykPf/xFP//IXRMeHON+Gsl2Y5qkf/y0NtWEWL13EqrYGPD4vXi9Uu8QVLVwRNWHzgRQvPP8Kz933bSZPbJ97TrbFwf27+dNP/yHf+tZqPve5z/H+995OwO9HXKEJCQFeTXDTkgBttT7iZjWRki/zzW89zNqV83ll2xtMDBy4iBHz2HaORCKBQ7PQOFnl4kIZM8dkbXCfo3WICWRsQTAYANtCFtIXcZaTo0x0beXg3k2Ey+oYSU6A7qF57Yepa2pF0wVJBDrgFuC+yGs5lZSSeDzOL3/1GP/2r//KkfaDSHkZ9SPsGPbEq4xpBULBTXiC9aQmJ8BZT3j+dTg9PhLxBGXlZZSUlKDrOh6vFyEEbo+b8ZnqGW6Ph2Qyid/vRxMQjyfI5zIMtO9h1+b76O14A+uc1TLOlIXCFGiVgAt7uptcehi9vo7S8jIikQi5gkaGYvuRzhgEXVDuAuOUtwVd6DpLKUlncxw8eITHHn+MJ594gmOdRwgEAmy85lruvPNObrrxRmqqK9E07Yq9ds7FtOFwZwzDX024fgPH2veTGN5FsQmKoiiKoiiKoiiKopyfCmcoiqIoiqIoiqIol0ZGyQzupqujiXnNzTQ1NWFbNrZdDAg4NfBeZDDj9PElhVyendt38r3vfZ/nnn2K+PTURQ2RmjrBj779Xfx1K/nQRz9Cc3MjtVVObmrz4nWIK9Ymwa2Dx+sgHk+Qs2e3+88eHrEsk907X+eP/uBTrFqzhr+8+27ee/vtBK9QSEMI0BHUhYutSCLXNtN+eD0fvH0Vn/30XUgzdRGjmcjsJLqmkTWLG/D+i5nLzEdaFgM3XjF3GU/J7IpJzAK4DAMuMeggzXF2vnA/+kzlCc3ThDdSQy6bweEoVvKIAy4usU2LlCRTaR5//Cm+8fV/Yc+ePViWdUlzfQs7QWF0K93b+0DMVs5wk0kkyWYzlJWXEQwG8Xi92JaFruvYloXL6SSdTjMyPExdfT25XA6n08DrCbH31WfZ+9LPGe7eh20Vznn6s1wx2AnIOkEEwJ5EEiKTTuP1eNA0jYkJi0yZjumAvjGbQERjNClpKdPQKFbOOecZpKRgmhzr6uHpp5/h0Ucf4cC+PaRTJ6tSTE3meOqJx3jmqSeoqq7lHTfcyIc/fCcbr76astIShBBvS1BjdshMJoMtJY3Lrufoa48jrfgVP5eiKIqiKIqiKIry20uFMxRFURRFURRFUZRLZw4ydvwA3V1tVFZWUldfh2VJLEugSdBnNjUvqg2GlMTiSX79/At897vf47VtW8llL/3d6Zl0inKPl3QqzRs799BbUcqalmV4HRe3iXtqJ4Uz93+dAgSSQr5AZipBseaHed4xTdNk544d/Jddu1i9Zg13z4Q0rlQljdkhyv0O/utnbqDj+CDd7TsuehxpptF1nUTcQtin3NiL4DnlkFOPPjXCYgP5AoyPT+Px+kA4LrkHTXLkAMLVCuhgC5yGgc9nYMykhYxzHj03KSXZXI7Nv3mRf/zHf2bHa69gmpcSdjjfiUyy0eNg1FF8LnnxRSIEQyH8fj+6riMAp8uFEALDMJCA2+3GcBoEggHSQzFefvph9m97hL6OXdj2+Z+P5zYOMgPOFsgnEIYHE4gnEmQyWVJJDyMxncoyWFyrMVmAqbhgOA9hJ5xs0HLKZUqJbdsMDI3w/Au/4Ve/epgd218lFj13CMu2bYYG+3ngvp/w4M/vp76xiVtuuZU77/wga9esJhwKXtmQhoR4StLXN0IumyWdiJMaP3zlxlcURVEURVEURVF+J6hwhqIoiqIoiqIoinIZCmTG9jDcs4qjJSWYlkUguJB8zsC+yLoUUkqGhsd4+FeP8KMf/Yj2g3sxzcvdUAYzncIwHHQePcrYQD9/9eU/xHMJ5RIkkhMpSakhCLlOr7ohBAR8ApfLQHfYWBeZKLDOCGl87u67uf322/FfoZCGQxNU+AR/+9CTJKYGL/p4aaXIpNNo5LCFB1sWK05czNSEKIYvJKdXq5BAmmIVC4BsTjI5OUWhkEWQudRsBsgMMjsIzgaklSWTTuFyO9GEwAOEuLg2G/l8gZe2buNrX/sntr70IrncxbQFuRQSCuNAELwlxcoito0QAsuysaXEAQgh0HQdpMTldpOKT/ObR7/H9l//hOGedqR9hSp6YAKJYgUNDKRpIS2byYkJMpkMqbSXaMJJPCKo84Jmgq1DwS7e21PX2rYlk1NTvLztNR5+6CFeenELoyPDl9QSxrJMerqP891vH+dHP/we8+cv4LZ3v4c77riDFcuvwuf1XPZryAIGJwsMDQ4zMT7OZN9hVTVDURRFURRFURRFuWgqnKEoiqIoiqIoiqJcHnuKoY6dNLS2kUgkSCZzpFIGWRNsg3PugM++c77zWDc/u+9+HnjgPvp6TlzSJu3Z5DNJcrk801NTbLj+WjasqCHs0i66pYkAUkmJxycJOTUkYNmSQiGPJiVLSgp84v0rMPhjNj9kExvcRTGOcOFM0+T1HTv41K5drFmzhs997nO85z3vufyQhpS8dniER+7/AciL36yXVowTB17kyL5qrEQFUvezvrWUqnCxioPTMN4Masw1TymLIQwBbz4f8hRXR5OQoriBbwHptE00Ok10Ooa87FxKFFfpMgResrkC2WwBhEQiiuGS8123lFiWxc5du/mXf/k3nn36STKZi2kJc7mygBuhCdKpNJlMBsuy0DRBPpfDoeuYpolhGCRjE3S88Tz7XvkV0dHuS24Jc242mMXKMIY3QH1TI7lcjng8zrzmOhCQsQEH+BxQ6QcnEASQkngiyRu79/LoI4/y618/Q29PN9YVCGDNKuTzHDl8iCOHD/HNe/+dJUuX8t73vp/33n47i9sW4nI5L+l1ZEtIpYvfq5xOJ9n4AJdc0kVRFEVRFEVRFEX5naXCGYqiKIqiKIqiKMolEUKAEEjbJjF+iOOHdxNwQ7fLJp8spZDUSHvAe44xRsYm+NGPf8pTTzzG5MTY2zJPh9OFz2XT176L5PQIS5pd3HxVGfp5jsvmLIaGBjDNPNF4lsG+E1h2gdHJJBNDvUhpMZ3MMzrYhy1NYoksyfgU2VyBdCrFxQYzTmWaJjt27GDXrl2sXbuWu+/+HCtWLEcI8ebHqWxbcq7N4umczb9+/TNt5PoAACAASURBVGEmBw9d2oSsBN077+crux9EaA4Mp5NgMERFeQkeb5D6+mpC4XLmNdTg9QVobm7E5wtSV1uFrgls4PiUpCwgCBvFUMT0zNAuYMKEGgekbTh2NEd/1yHGew+Dnb20+b7JJj++F1f5WhJTg7Tv2Y1TNDNeKWhwnV7BY671m4rG+Oa99/L444+SSCQucy7nI+acA8SQyRPk3QZTI4KgR5BLBjAMJx6PG5/Px77Dr3Ho1UeZHu87vf/OFSeBDKCh6wWsbJRU1OLQngRhXwHNDHAiC9MaGAgsAboQnJhO8OhjT/DUU4/T2XGEfP7trjoC2Uya3W/sZPcbO/nnf/rfrFy1hg/ecQc33HA9bpdzzmOE0OYMhuUk9BxPk02MkYqOk57ueZtnryiKoiiKoiiKovw2EvJt/aFdURRFURRFURRF+b+VEOKsPzAKIfjc5z5P3YI1/Pcvf5lsYhihedAdoAkboQk07czN77cyTZNcwYmm29iFt6cigdBd/P5f/L8k03l+88TPySZGcGhn2wg/yZZQKNiAjWXm+c/++Vl3OPC4vQTDIerr6lnU1kZzcwutrfOpq60hW5Dsbu/n2Wefo333NrKp0bNuzEsgm81hW1euSsG5FFttOE7bBLdlsbXJXHUL3qyqAZg2mKaFZRYuqcrHmZy+clZe/yE+8dFbyOHjyPFhurp6iE/HEUA2lyM6Pk56OoqVTSNzSYQdx1u5gOq6Mk4c2EJ8api3s1JCaXk112y6gScf+cVZqsYIEBpCaAhNm6lSIt6sVmLmc2/r/M42H03XERRvqkPXZ173OsIxDyNcxbL1V3PDO9YQ0sZ56uGH2LP7DWLRibfhtXTG61kLgZ0GCqd/XQg8Hg/aHNUzhOZgxbqbKCkL07F/B8NDA9jWyeefaYNlWdi2jW3mzzkbKS+/5ouiKIqiKIqiKIry20eFMxRFURRFURRFUZQ5nSuc0Tx/IZu3vMihKQ9f+et/4vCrj5JNTmKbFtgJik0rLpCjhpXv+mPm1+R46fH7GB8dugKzP8npq+LOu77K/MWrONx+mF8/8G0y8RFkbgBpJs95bFnzJt73ybtIj+xi55an6OvpwryCbRg0Tcft8VBSUkJVdQ21dfXU1NRRVV2D1x8C4UDXneAMIVwRbrt1FVlTMBa36e5L8sufP8LWh76FlY2CNcLJzejfdQ7QI7hLWmlYupE//vNP86F3tRI3BYYEh2XSOxbjyLEoHcdG6e3tpbenl3hsmvGBAXQBK67eyDtuuoGWRg8HXnqQR+/7If093Ve05c4sIQRuj5dM+j+zZcrbRcddejXVbeu4+oabWLFyBTdeU0VTyGKwb4CXt27l8cefYMe2bSRjE5dd6UMIHc0ZwcpNzHzGgad8Lfl0FivVAWRBD4LUwJ7mXCEWITRqWtbyybu+DNlhXn3hcfbu2kEqGb+oOalwhqIoiqIoiqIoijIXFc5QFEVRFEVRFEVR5nS2cIamaXzt3+7lA5/8E57YMUGhkKGz4xhH9h9kz+afkEmayMIIdmHqwk6kBVl88938wWc+wYIawRP3f4vHf/EAU5Pjl38RRh3hhuX4A0FWbrqdYKSE7uPHi2+iN+N0bv8lEwMHYa4Nd+Fn7fu+yCf+5C5WrCijwjlN5+uv8+gjj/DC888xMjyEbV9YZQchBOUV1VRUVlJdW0dZeTVen59wpJSgz02+YDExMc7gwAADA32MjgwRm54il80hhQ/Nv5iGqzbypf92F/19g+zYtp9b33c7+/Yd4JknnqCQTpEdOoyd7gESwJkBEgE4KbZaMUH3grMUjz9MZuIISJP/3MoLbyOjBmdkCXVtK2lbtpzWBfNZv7aZ9W0llPk1ckCJKDbnsC3JseE8QzGTA4fH6OvrIxFPUV5extrVLbS1hKgq0wlrMDU8yi8efJjvfPteuo53Iu3LDGkInVBlG1YhQyY+iFXIczmtcIp04PKrjVwW4aR65adoWbqatsVtNM1rYvmKekpLNDxOcOiSaNxk83PtbNv8GPu2PcnU4BGkmbmk0wVKGjBNk0x8CHAiXE20rn838xYuZe8rm3E68mjE6e/YBdKFtCdnnu9nmb6rjg13/hWtC1tpaazATg3RffBlXv3NU/R2H8O6gOozKpyhKIqiKIqiKIqizMXxf3oCiqIoiqIoiqIoyv9dlixZwic/8RHGEaQTo/z0Z48zNjxKcmA3uYkONCOIq3ojhVgPZqyDtwYFziC8jAwOcd8PH2LdtRvZ8IEvcscnP83Pvvl1nnj4F+Qy565ucdZhHR4qltzCunfcQk1NDQ2NNYTDYcKhEMPDwyxYsJ73fvAOHvvJt9n5wi+QVhIQoPkQjgAOfxP1rUuorQ1SERFUeUpY9J53cftttzI8MsqWl7by4IMPsuO1bUxNTnKucIPL7WHTTe8hlUowPDxA+6FDTEcnKeTzmGYBOWfIwwuuZiLz11JW20hlVTW25uTlzdt444XnmNc6n3A4TMO8eUwO9TA8kAKyFDfoTRyuEJGaxQRLyhkaSWHlNIIBSTIvyGV1/GWVWJkEmjGNNEeRdu6S1vlsnG4fC5etobujnVR84vwHXAG600/1qvdT19zGorY2Fi5qZdOaGq5qcOCf6aniBYQED2DqguV1LiojTurKGzjaH+bQoUGEphMO6bh1mzKhYyCoranins//BZ/4+Ef5+S8e5Dvf/ibHjh699EoaUpJLRSmpX4c70oLbbRAdPEgq2s/czyUx83Gu8/0fDmYASBe5ZIpISQSHYeBwOMjlBPGEJCbB5YLxcRtfqJLmq25gaFonnXOQGdl5Saernb+CY3s3IxwhJE04SpoJVjVw/TvfyaoN68llE/R09RGdSGMW0lhaG/mJHSCzc46nGSV4vF58/iCWFuBAd5YsC6lsnsIVbqK/q51kdOicAQ9FURRFURRFURRFmYsKZyiKoiiKoiiKoigXTNN1PvvZu3H4InQcjvPyK/sZGx1n4vhRiHUAAqtgYSVHCNcuI1aYopCe5GS7DcmZG8+aw0d5bR3hsnJA4/HHt7KorYk177uH9kE3h7f+DKzYRc+1rnUdG9/9AVpaWli6pJ51i/0YOixoWc7IeCtdXaO4fR4+/Vd/Q/WCVQz1D2OZJqMTUQyXi2AozIarV7Fonosmj8AtAAS6Lqirreb3P/5Rfu8jH6LrRC+/fPwJHn3kEY7s30su89bWFNlMmocf+N55ZqxT3Hh3AG4QBpgDxI6PYUYXUlLyIVKJDBU1NbgjZVimhWmaxAcPM7z3V0grfcpYDmoXv5vfu+uvKCkrpa+3F7fbzdjYFC/+ZguZZJKqmmqqqqp4/ckBCuk82cTIRa/xmYSmU17TxK0f/AjrbnwvpijjP/7bH9HVvu2yx74QdW2bWLZhE/Oa6li/eiHrF5XQWKKha4LZUgY6MPsfCVhSEnHD9vZJfvbAZo4eOcr4QB9uc4q1N76HL3/xY2xsCSCkoICgqqKcL9z9F3zi4x/juz99gO/cey+DPccusj2HABxkE1GmRntwBUrJRyfxhetJTQ/NvERsTn+tOGdmn5n5vDjj6/ocx7zdNMCg2MZo5rx6GcmcTXRqipqaWizLIpuxSSYsnC7w+x2MDCexLAuHw4HP5SQ71XNJZw+ESgiESgCNcPONxCYLlDfNw+VyIQQcaT/Myy+9TDo6SXa0C0QeR8CPr3wZ6cljSCvG6WEXDVe4OOddO3ZQVlFBwTTZveU5osceBwoI3cmbTyBFURRFURRFURRFuQgqnKEoiqIoiqIoiqJcsJWr1vKhD3+YE1E4dHQcoTkoLSsjE6vGcm+gdl4zpu4iOjZAScQJhWVMdO0HmQfNXdzAloCMUdxk9mOEmpmaioIQSCSaprFl86uMdh9hpONVsArnmdVbaZqD9e/8GEuWLqW5uZrrrnJR4xFIARXNXhJNHo7WBhkcSbOwOcg1qz9B30CW0ajJ4fYenC6DxsYyrl9RSl0QjDn2YoUQOAwHrQta+KN7Ps8Nn/wztv1mDz/6t//Fsd3PMtcmuRAaTYvWsXLZAl76zfNMTYwBEt0ZQnM3YhWySKEh090gE2CBbUFiOMpQRx1wJ+npcWI9W5gYvYVkJsPAoefOCGYASHr3P8Wvvp2gbeMdjEwmkVLyjuvX8XsfuZVUXnLDxjbSmQIbr1nJa09+i82PfP+i13mWNxBi6ZpNbLz1Y9TOX00gXEY6nWXzM88y0NNxyeNejJKKar78d1+hZdECqsrc1AcdhGeqZcy5lS5Bl5Jdx6b4zgNbyJpOjh9qZ7T7OKmJHmLJYZ4bHmbJ8sWsaroGXYeUhLAo3vtIWRkf/bO/pHbVB/mPf/gKB7b+Eit/vhCRBo5qkAKscSBHIdmLlc9RSHYSP60agwD8FIMPeeDMyiazLUxmq2l4Kb6mrkxFB6G78Za2AZBLRtFdBm4DMoko+UyheC24gNTMPEzAAQ4fnnCYqckpxsZGaW5pIp3OYjgNLEtjbCxHPJ4klUwSjUYZGRkBeWlVWxYuW8fYYC/h+e8kaQUJVTtZd/UGVq9exHR0kuHhUbw+H/lUAn/1agq6gWalCJXXkIlPIS1zZu6zLWVcuD0BomMjHNn2NLWL1+EKlREbODDzGJDWla0woyiKoiiKoiiKovzuUOEMRVEURVEURVEU5YIYhsEXv/RFbF+QwTEwDCcNjY14PF4WLlxIa2sjR3Zv46Unfkx6qov4sTPaBlhQ3NB1AhEgDA4fRqiaaG8nU4dPEGu7kXB5JVP9xxk78hTYF18xA6CstoW1172L+QvrmVenUekRzOzTI4GxaRgYhsmohcdns7ZVp3mhj65pyfz5y5iasknE03T2pMhUellQ7sCpF7f4TYrjaDPn0oCAEGiam5wsIzpxZlCiSHc4WbPpvSQzQcbiQaK5JozyxZTW1rBqwyb8wVKGezvZ9vBXeMtGvLQYbH+BHdu2geFD8zex5/UdTHa/hpUdm+NsEuwEx/Y8xcTYACtuuYuenj5qaiu5/cZ5RJwQcoAtIbGxHvf0SjY/cnFrLDSdyrpWbvrAR1l7w53UNLYwMpJheHgEf0jgdrsRdoFc9hLbflykD3z8D1i/YSWGJvC7QEdgi5P36UymlLx4KM7PfvU6v37yRTQpmb94MVMnDpFIHgB0XKGrGByNkixI0nlwA8IjQIJEUuqBZUtrWHvzxzh6ZJD0wG94a4jiJKe/Gs1VQXbqIMVfyRhYuSxWrp+3hiokkDjHFVucfnUpzt3y5CIIHVe4hXDrjfj8AZyaRTqZoqqqmpaFrYz1dbP35V8z3ncCaQcohkLSoLtxV7RQW19PMBgin88zORnFtmWxzYlDZ3RkjJHhYfr7+xkeGsIsZMG+hACWrlO3YD0HHtmCjHgQBqy6eh1XLVtKvlCg82gXXp+X8opyyktLsDKTHNl2H7nUCJmhM4NTDqAEHCW4QhUMdryBmRxBIhk+dhg7O3AFFlVRFEVRFEVRFEX5XafCGYqiKIqiKIqiKMoF2bBhIzfefCvbjxaIpwXpdA6v18uq1VdRURHmJ//2VV598uvYVv4co9hAFhgF6nBEWvD4PaR6O5FWlHh0iun+DrJjO2Yed2nWXP8+FrbV0zqvGMyY/eHXlDBgwmQehEPH6XJSXqaTswW6Q1Lphc6jKbbvPEE8FqequpKBST/GiioWRnizCsNsJYbZsIcHsAqSzs5jZPRK0KvBGuHkZrlg3qKNVMzbyK5Hn0WgEyhvwldaTnlphFTGorE5wku/eBJpZeZeOTNJ19F2AuFK7ILFxFAv+VjvOda5aHqwHZ+e57bb343EzUAUHKWCiAMcGpQ4YcG8RjRNx7atC1hdB57SZtbf8gmWrb+JsooynL4yjh4dI51OI4TA7XEyODBGV/8Y7vLlZEe2csWCA3PwBkppXnYbu/eM4gtGqKpxYVVDlQa+OR4vpWQoabN5exf7tr9M/MRL5LMpAkaS1be8j+1P9hEb2o9mR1nY2ozbIcgDAYqhjOGEzY6jk8STOZYtr2F+awM+Xxlp0QByEJg7oCOFg1z0GEjnzGN0oJTTQxgaF7ZWcuZxGsVnopOTFSAujx5Ygqd2PcFwmEAgiGE4WLKyjuGBAfYeOEwkEmHTR/6Mga7jHD9yhEQiicfjJFJRQUEYmKZJIhEnUhLB5/MxMjLK1FSUQCBAf18fsekY09PTFAoF0rEE0vLOXM/cz/25zGuez7wFyzHNV/B5fbQsaKWmtoax8QkS8QS6w4HX68Xj8TDatYeDL30XM3e2sIsJxNB9S/AGAoy1H8HwusnlbeK9u0Be+LwURVEURVEURVEU5WxUOENRFEVRFEVRFEU5L6fLzRfu+RKHBrIc7pympCRMPp+nujJAa5OXe7/2DV59+jvnCWacygYtQbCsnOTwEWS+H1f5SpyGk+mJI1xOMMPl8XH7Rz/M4iYNQxOk8hB2FrewM4DugEBAEItpVJb5WFQKZtbiRy90cqRnGq8/RKFQoKuzkycfeIA1mzbS1vpx5keKFRMSNoS02auQWBJ0ASUuKC8vp2nJMvoEJE7sAHuY4oa55ERnBxOJME6nC83w0NAyD6c/yKHXtrP2pjIe+8H/Yqxvx1mvy+EuJ1xWTXllFV6/FzwhCoYPWUidcz2kNOk6uIPPfP6PiE47QIBlnF53obGxHqfLRTYzd6jgNMKP7l/GWExw+HAndcks7YeOUVpWiuFwMB2LkUwm6TvRw9CR7eSn9mEEWykkh8BOUfxVhMXJGZwZJpiNv1x4yGDBmtuI5UNoMROH92QrE2PO9YDpjMUPfrmTH//HDxjveB7MYmWErl2/YHJsFOlbiK/GB1aSttZSnDo4TYHHkHSM5/neL97g2V8+SDI2yqf+8m6CJTW0rVtPNJ7AjEYgexhInnFmnUIiOvN5NyejPU6KIQ1BMUoy28bkfATFtiLmzN/emX9fbjjDhWUG0RxO5s1rxuf3kUwmaV3QyspVq9i9azcH9u1neGiYBQsXcNtVy8nncySTSY53dDB6YAe5ynk0L1lCdXUNtm2TSadxOp1MTU1RKBTQHToOh4NYLEa2YINvCeQzYA2CPcJMmZ3T+ANBUskEUharXrzjlvfxxq6j+MoqWb12DelUisnJaWprG7DM4vFer5exgV72/+an5whmzLLwlZeQmhrAyo4Rmn8jqegkmHkgCMSYq1WRoiiKoiiKoiiKolwoFc5QFEVRFEVRFEVRzuumm29h/XU38A8/fp3ahhbi8SQNDaXUVer8z89/kT0vPQDyzLYM52GnSE/2kZs6isM3D0/lUuI9HWBnufDqAW+1dMVqli5t4/iATUm5Tnnw5NcsAV4JOQOqKgStIcFkzOTJVwZ46OEtdB07zu3vfy/V1TUEQiGaFy/G5/ORyZhInGiAe6ZsRtySHB01OXBkkpY6P/V1PjZdv5hCIcfBSISDUhDrOQz2CRAZAhXzufnDH2PN2jakabFy2Tye2XIY3emmoqKE10/sOuc1aw6D+QsXUtfQwIGl15DOm4zGGylMTZxnrSSDx1/DYcepqa6kNAwhvRgomVVTVUkwGLqwcIbMYOdipGJRksEgHe3tOF0uDh7YTzgcxuv1MTri4MCr24j37sEZriDUsJGAHqe0ej57tu9CZk5gZ7opbnbPhhROzldzuLDNAnNt0p/J6QnRsuIWCoUCUkqEAE0rVgWZ65ceNrCjO8Mbe7uIxyaLvV3ePLXJdO82hFFP202/x4oVbayeH8YlBCEDMhY8sbmdxx5+gv7927Cyw3z97zLc8N4Ps+Haa8kWCnQePMh0twaZIxQ39GcZp1yvNfO3TjFUkWG2zUmxPcmFmGnFQYximCl5Qet1PpqvFr2iHrfXAwIqq6qo1jRisQR19XXU1dcRDIWITU8DMDU1yejICMlEgmgsBv4yDK8Xp1G83mw2i9A0DMMgNj1NMpkkk8kQCAQIhUIkysuJ6zpmOo0VD0AuDIVO4GSrE28gwsYbbmXzU79ESonX56dtzU0c29rDTR/4ADteeYXqhgYikcibxzidTiorynj6B3+NmZu4gCsXOA0n6ckJ0CLEhvuxs/0Uq5rM3jdQAQ1FURRFURRFURTlUqlwhqIoiqIoiqIoinJOXq+Xe+75Ai/s6mf/gU7qmxZQGvHSUqfxD1/9Mfu2PX3xwQwAPUx28ihCEwQb1+HQJDI7wMmWEB6KFQQuZsNZcNXG93K0B8orNAwDXLNFCShugxsCsk6oNkArSB7d0sVzT79I5+ubmRod4uH+VwiXN9B41Y2UV1fz0Q9tYm2LgV4cHpeAjCXZeiTB1m2dHG7vwO/38Y4b1nPd+kqcty7H4/UTDofZ8qhNetSHyxXl//n7r/KOa5axuMGPBPpTsHzlQuY1N7D5sZ9j5uPnvDIrn8DtMliypIbrb72N3p5eUmNDRKfaOVsbjVnJ6BDH9h/gtg+8E90hCIqTW80AvlCIqupqxkaHL2CNc6RH9zKpO8EsEK6qIZlM0Xf8OF2ZJBKBsPLkp4bAIXCULiM10kc8eRh3sJZgbQu5SYt0ZoCzVYiwzRwXugkeqVtOpqARi8dxu90UKkowDCeuM64Riu1MknnJ9p0d7Nv8EPmh34B9assKz8zjkpiFPHf94btoiLhm6nxItndOs3nLLhJjvdjChbtyPbULl/HGa9vZcO0qPvzR29nR0MDuHaUMdkYojL4IcrYKjEYxfOEAEZj5vLv4f8opBjQGLuC6DYqhDtfMsZ6ZjwIXXnFDp1hl463CNQvQIxWUlpXhcrlwu904DQMpJdGpGMlEklQySU1NDd3HjrHj+aeJDR9D03W84SrKapuorGugtKwMTdPJZbMgJfFYjIMHDtDd2Ynb6WLB0iWsXLWKQCBAPB5noL+fKdPCtirAssHuYbbNSXXzSnp6B96smrFm3QbK6hfikCd44amn0Z1OvD4flmWRyWaR0mblqjYe++n3mezffQFrCgg3UrhITewHaxorOcncQRknCC9IVUlDURRFURRFURRFuTgqnKEoiqIoiqIoiqKc0ztvfTfVzVdxz2fvxRsqZV5DCS3lBf72f/5vNj/4LezC5CWMaoBtobl91K54P/lUlLH2XyGtU1sPZEFUzGyCXlibE1+wlMalN+PzeXC7QRPFQMZs+w6DYuUEnwC/lDz8Wjff+Md/Z6hjP56ABztxiFg8TWyog4HODhqWX8eH3r8Ov1aCEMXtbClhvABjk2mSiTjJZBLLtOjuHiXs03nX2go87uUsXdpMaWmIbS9tIzPVza3XzGN1c4AcMJ4BqUNTUwket+TR7/dzvkohHn+EtsUNrG7zMT29nGAwxHDXYaLHrfPuEdtWnldffpWPf/SdFERxHU4NLtiGQUV1LezbcwGrrCFcJfhqW/CWlROdjGK4XeRTKfITozgDfnzhEB5PE8GyDeRsjcl4BrNQSeehYxj+ILmME6gAJpj73l7oprdO2i7h2LFjJFMpcrkcNXWVuAwf/jPCGRLIWXDfsx38+FvfZ6TzRd4aaskDPmoX38g1mzbQWuNDCIEmwbLg6Rf2sPuFR5gefA0hBLbmJJfJsHTNGtxOnRvW19NYW0pjYxWvb6/ljUd3kU9lOVkdxAEEZsIZgeIpDR94wpDoBHlmnGQuLhDl4K4tjpudAOEAe4LTK3Wc43ijutjKRRZO+4rQnDS0riRtu6mvb6C0tBSn04nP60V3OBgfH8e2bQKBADt37mTfy1vJDh4FuwvIk592ER8JYRifpGX+fMrKy5icmMDv95POZCgtLSVWUUk6k2ZoaIjFS5dyw003IW2bRDJBMh7DzGbQZIH45Ci9x/bSeWArfZ37MHPxmcooGjfc8j5+9s3v8NILbyBDJdTX1BCLxWjQNAr5PKvXLGK49wivPfNDkBcS7jJwl6/AGwgxaYaBOGevYGLiCC/A5ZZkk1E0aVNIJ0HaM9+rCmc5TlEURVEURVEURfldp8IZiqIoiqIoiqIoylkFgiHu/vw93PuDZ+g93M7H//wuljQbfP0/nuKJn/8AO3cpwQwNT8Ua8qkE4ZpmdMNg8vhLZwQzoLiZPQ3OOigMgMydd+QFy6+hvLoRh6HhcAgMvVgjYNZszYCwhK6xHL98ejfCYeAvCRPr3wZydrNew8rlSSXzxOM5ZotvzIY7ylyCTVdXUlZWwqK2pYQjbnxeQTKZwTQlG+fpFBpDvHvFLQz9/jW88MKv8WrFsIhHgtcF8TyURARBLOKJ81+br6SBisogfhcsbQuRSldx8/vu4PjezWQmzheqkLTveh0tV8Dvdb7lqwU0KmobzjuHIjeyIEhEo5RXVRMuK0UIQaiyiqzXSyE1SCHRg7NiGXlb4ACal69iYriaaE8XZqy7mHQQ1cWkC4MXeN65rys5OcGA4wRDHW/gf89HCIe8BN3FmhRwSkBDQsdIji2vHSGby4Ew5siAWAgty63vuZav3vNuyrz6mwd3R02yBQeLrrmNkb4F1DfOI5O38Xi91NXXsXxpI0srDdoqQ6xvW8fhGxbwme3for9rnJMnKgGHo/gk0jwgc7iqG7DzMQrxqXNc52y4wwsEQQ+DvwSEKLZl0RyQTV5gpiVXfD3NUTkjULKAivpWsrk8NbU1pFIppiYncbvduBwOLNOkrLyc7uNdnDh8kPzUUbD7KFa4kIDEtuvJpNJIKXG5XGi6TnR6mp7ubpLJJL3tO9HyUZxt13HowAGWXHUVTU1NBIJBRnWdZCKOEAKHbRBp8bAw2EouOcXA4c1M9L1BRVU13UMZtjx+P9I1H/I5zGyGqkULiYTDLFveguHI8u2//RK5RN/5l0O4iTS/k/olVxMf7p6ppHJmq51T2ZDtp/nqP2V8bIRIKEBfVzeF5CRmogs7N3AhN0FRFEVRFEVRFEX5HaTCGYqiKIqiKIqiKMpZffDOD5F3lHD/D35C64Z3cv3Vi3h9+yEe/em3sHNjlzCigbfyahyReTSubGLt1VfzO1QcxgAAIABJREFU3MMPYqYn5n64zIE5hHC3IPO9IEFzGNj5aQDcHi/ZTDFQITSdhavfRSqVwbL8BIIGbqPYhuT0GYApJQf6cpSWlKLnR4kPvgz2qW1FEmBnyMYaEVbutAoMQkA8B72DFj09UWxb0t01RGlpgJraUnJCUKGBRxcEHA40V4iKiggxs5hFEALCGlju4nvsxbSJ/WZtj7MRVDS0EfY5CSBoKYfh+lKcho7LKcmc52iA8clpRqeyLPIVwxnyzT/AklDd3HIBowDCh/A3oBlONE3DMgtk0mnqmxrp3ruNxMDrZPGj5dxgJrHzSSI1DZTUtCJr64gN92En+0H6AB/FuibnrhpydhKZ7ibTfZhg1WJqGxopLXMRdAr0Mypn2EA0Dw7dgbQKvDWcULwHC1bdxB/+ye9R6nUgxExEKA/3P/w6T933PTLxfoRmcGTkMLZeglkQ7H3+ccJek6u/8G6mhUB36pQGPRiOU6NBEfBWI7CQ2Qy4Azi8FXhDEaY7ds7M8MxAgAD8QDmIPHhq0HwVaIYTPRDEymYxzVDxuAsrLkOxHcpsNQ+Dk5UeDJquuhmPz09ldZCRkREikQiGYWDbFkIISkpKSCSTbN/2CqPt2yF/mNPbDlkIexRDN6msrMTr9eJxF2My09PTHD+4j1T/HrDSJCcHGDxUwfTkHVR85GMEAl4CAT+5XB6Xy0VtXTWZTA7LlIyMjhIMe3llYDdrr7mJvbt2I7UQGE5IJKisrKK8vJx5zbW0zIvwjX/+IRMDnedfCuHGWbmJeSs2cfU117L9pQI9mgNs/ZyHmZkRjr3+MJ6KlRxtf4OF19yM32hg37Yp7ML0hd4IRVEURVEURVEU5XeMCmcoiqIoiqIoiqIocwqHI/zpXX/ON37+CuUty/jgnbdR6ilwzx/8JeNdr3LhrSdmCdyheay48YOYlmTZyuWUlVdgm2ngHJUj7Cxl9c1Eat7FiUP7KK2tZvrEa2Tjw0RKqxkZ7EZKiT9ciStcT9fxLiIlXjzOED5dvFk54833wkuYTJns2d/Nlsce5MTux2DOeINJdnIfPv309gYScBqSeCJFb+8AnR0dHN6zh+TkBAtXrUJ+4VOEV4UJ6KK4/a2DboBmCKaBEOAQUEqxqUZKQiYW5dzv1pf0HNjCq68dZOP8q9E1QUmJTl+fJFhSyfTQuY4tik100d7Zz6K6xSAEppR0TdmY2QzxnEVeFCtgSHmucdy4ypdT1roMKQS2bVPf0EA6k8GyLDTDj7NsHfmpA9jTu4tVHTCJdncSPbEV3duAp3Y92aEcViYLWhAKOqeHM85/LaeuC/khEAaR+uWUlpVSEtYJnpF1kRJSpuRAey8vPvEwE0d+DfLUSi3FGIfucPGnn/88KxsCCHHy4IFonrGJNJm8TXTgCHZhimIowQBXK0aokaHBCWxL4jIEEQPcQXDpFB+DAY4KnJES8rEY+F0Irw9/VTX5XBb04Ew1C3n6nEQ9OGrA4UIPhHAEg7j9AcrKyzAcBpOTk6Q8HgqpJIXp87e3KXJSbN9ic2oLDoe7ikVrrsXw+PB6vViWhWEYeL1eXC43htPAF/DT3t5OPl8AzQUEKLZSOXli3eUjXFKB1+cDwOV2MzY2xuTwMLmpfrCiQAqZmyI12suRlx0suWopt3/gXdTUljAxXorX66Ch0c/QUJItm3dhGAbBUBCn00XL0o1sfv5eCNWj+0LIRIJgSQlLli7mmjU1bH3lAK8+8wDSPrNlzVtpnmqaV17D4qVL8ft9lFTWofkasOPx86ylpBA/wbp3f5qjvhDvuPU2brltNff9eB1bHv3RhdwERVEURVEURVEU5XeQCmcoiqIoiqIoiqIoc/rwRz+Ov6KFpNXBn33+Lj504zz+4RuPMXiim4sPZoArOJ9b/+D/wxIay5YvZ+nSFsYnYlTUzWPiqAPkW9ssFEmSo3upblmOlexntH0XgfJFOF1Bhgd7ZlpjgK+sle4T/ViWxVXLF4JdbG2hcbKCgqC4JR3PWmx9/gW69++h+KjsKdfkAWyEsPjQf/kCt16/klNrMNhS0tmf4IEfPUJv7xAdO58jFU3jjjSQLZhsfeUQrVWrWVnnBQEhHUJIDh3PEyiT6D5BUBR/IDcATUhMyz3zv/xZ1y8V7ePggWNMZ9YT9uksqNLILoiw5pZPMdjVjpXpP+f65wvw2q6jfPDGxSRtOJGQPPLMER76/r8TGz9OpGYJQputKjFLzKygBQg0Zw01i1Yw2buLXDJHpmYp4XAIj9eLYRgs3XAtrz/5S7DzFDf+A0C8uOoyh5U6TmFUJ1S7gqmujpniFU6K/5hd/4t/boGG0AzcbichT7E2xKlMKdmyf5pnn9nB5Il9IM+obqBXgSjQtGgBd9yyAa8m3rzjyYLk3u/8iqcfeIh0Ko0wAlCYrfRSgPxxqpuuo6SqFmlDSBRb53h00MRs5YsQ3tpWPGUVpL1eHE4noUgEXyDA+EAPWYd9Wv0JEAhnI67aDWhOF7rhxOVxF9vHhML4A34cDgcSieE0SDocFEZ9kNfhjJHeKk9xhqcHYuoWXUtZVTVen5dodJqS0lK8Hg/lFRWkUilcBSe2ZXG88xixwT7I9QBnVokQNK++nRUbrsXj8WDbNrquMzkxwcjRQxSie4FTw04u0lNRXvz18yxbuRqf34/H46NpnkEqZTIdtVi1egXJZIbY6HEWtC1lZCxNNl0ArwvbNJnXtojrrr+O69bVk42O8B9/+1Wmel/nnM8jvRQsE2+kkXktLTS3tJDJZDBcLoI1dUznhiE7yVytX2bZVp6q8lKEw4vT5WZyIssX/vx2IvrQedZfURRFURRFURRF+V2lwhmKoiiKoiiKoijKnK7ZuJ7+qOQDd9zMu9aWMzWd4rWXXkJa0UsYTaOsro3Fy5djWRZlZSVkMgVe37ad3v1bQJ49lACQiQ2RnBzAFWghMxHH6S9n+XXvY9ezPyc2vBWAaMLBzhd+zdKN1+Fw6DhmqmaIt4wm6eufYmjgBMhJivUrTt3ILbZ8KK1ZwD33/Omb7S2YeVQ0bfOzB3fy9P0/Ix8/gsyPAhq2y8LKrSYeS9I5kGV5nffNZiWWZTM6kiSagBrfqasCmu4gUlXOifNsqntCtSxfswbDqeEF3LpgcZPB4iXzeVI/c3P/raSVZmhoGNOGaE6y92Ccx+//KR2v3oe00kz2tyPlGe1FhAdHYAnOcASXy6CqcSmmZRPvbwctjLdaIiUEAgF8fj+aEBhOLzlCwBgw/pa1z8c6SEgXgcYlJEdGkGkfyBSXRVq4DEF1dYRSN2intDSRwHhGcqBzHNO0cASqyWd6OdnaAxwuBxWt7+RLf/NZ6spOVs2QUnLg+BgPffffiQ69wZytRyTYuRwLFzThcgiM075ooLlq8FUtpnHZCtLpDAgNl9tF47xm+g6/xnTHU9iF2eoTBggXmrscd9lV1LYuwOV24/F4irdDCDweD1JKgsEgbrcHwzD+f/buNEiO877z/PfJu7Luq++7cZ8kCALExVPUQVKHaVGyrcv2SGvP2h6NZ+xZ7e6MZzdmHesXa+/GrMc7EY5dz85YtnWZY4kSJYoUKfOUSOIGiKsB9H13V3XdVZn57IvqBrqBBkjKoh1ePZ+IBtBVXU8++WRWR6CfX///VAoFeNvWOMtECmSR5aY6gEAzwux94DHCkQhIiRsKkUylkFKSz+fxPI94Isbw8FWuXL5MPT+5/J69uSWNDHxsx8E0DaSUGIaB67oIWVznOtfA8liqVLl48QIHDt6D78HkJDTqgnQmhu9L6o1mVZAj7/sw333mVXAyCE0jpAkeePRR9t09yMYW+I3/9UnGL5zh1gGVZlUWoTlIGWLjHQ/Q39+PbVtYlklHRwem0bwGb0dKEyF0Nm3ehGk52I5BS1uYnRuT7+w6KIqiKIqiKIqiKD9zVDhDURRFURRFURRFWVddQjgV47GtAq9Y5ff/t69y5qW/Yv0WILdjYMR2073zflzXobevG9uCq8MznHzzx5TmznDjBu/NJDMjb9G27QEmz+ts2PswbizOx7/wef7s918i8DVq87MIFkkkEkSjDrbRbB+yZhQpGZ2v8h//8zOMHfsmNFb/lrsGSBAmQtPYtOdh2luSCLF2kHxNUqp4JPu3M312HurzzfXKnePM80+yYcsWejsiayp2gETTJJl4s6qDL0EXzX8HgE6Ft6t4UC+XmJuZZ7YiSZsCISBqCu7Z20s808tccYLrtUHW4Zc5d/SH5MtfAGHy6os/5uyLX0b6zfYPteL0DS8QIBvI2mV0fyuZ7iO0dPcxNjpKqPMIlcmr5K9e5Lxl0d3TTWdnJ8lEgtqjH+Gl/zpOZX4SpLF8XmsDDY3COOFsP9H2TpYuj4Ccuc2ZrzSmuc36CJPOnn62bUyQ1G+O49SkwDCM5Qsil9dIgN5Kons3W+95gC984XE+frgHfdX1bviSbzz9JlZmK0yeXg413Dg3l6V8ka0DcSx9bVMWLZQl0t9KKJrE8338wCccDtM30I8bCrEwMYrUY4jAIJTdQrx9M7Fkhli6hWg8TjKValbIkJJoNIpt2ziOQ8gNUavWuHz5MrquMzV8BeQSCB3k7e4jAVbrcheh8vI6BLQN7mVw204ikSjz83OkMxk8z0PXdUzTxHEcQFCrNWhpyZK/GOAjuR7OsEFzAQ/TSWLoOkEgAUmpWGTordM0Cue5KdhCANUrWMF+ZCAJuzqVKjgOgIYMoF7zmJqYpFgs0tnTyeilJ8FMQ26c7R94nP37d7G33+TVN4Z44ekvgz90w72igQihh7tAhMFfwkoMYpoOew4e4uDh3diWRbHYYGx0DL80C5Wz3K5qBoDQXZLZDF19fbR3ZGhrdZEajOd+ksoviqIoiqIoiqIoys8CFc5QFEVRFEVRFEVR1lUFdrRrhKTP//j/PMtTX/0GQePGzenbWW6xoMXZevAx3vfBD7JzVzczM3UuD03x/W8+yaXX/uIdV00IhRNs2bGDXC5HqVyhNjrKjge3oGkage9D/RzS7EYGAfG4ias3G2asVqgG/MnXjnLsxDmEmYbaHM0KAhIQaGaabfd+it6Nm3nik4+RdvWb5lEqe5w/+hKzZ59BVlbCHTaE+hChDBPjE0TMtQGJIJDk80XqNcmClCyUYGNaENIEOgH5pQbNtiaNGw+3zAQ7gx+AS7MyBEBEwO6BNHcceoxnrx4F4YJcuOUaXr08zEtHr7L3jgFOvPI9GuXJW3ylgxHdghHJUlsYp5yrEgQB504cZ2lhhvr8efAKaGaSdCZLW1sb5VKJkOuyZeduTPtf8Mp3/jO5K8+xbnsJucjSyMtkt/8ctVQvtbkR1m/pImi2Rilxu3CGGW7n0L372NFuYtxQNcOTMDxd5czpc5w7c5Z6pUhz493Bjrex+Z6HeOgDh3jkYC8R83o7Eynh1NAMX/naM5TmR0HW1jlyCMwBYi2tdMYNVl69MoYeSlMvaGRiUUIhl2g0RjQWpbOzEyklH/zMF6mWy1SKBTBMyuUKITdEIpFA0zQcxyGTyWBaFoZhEA6HMQyDRCJOsVjC8zxs22boYoLk9kdoLI5RHD0JQZHmO3hlTeXyrGyEbiCFAzJBM2hV4s7DHyAejxMEDQzdoFIuYzsOruuiaRqmaVIulanVaky8dQq/cB4orFqHOgQmTnqQLXfso6W1lWg0ipSScrnMUm4B6a8X6rJAtLI0v0C9XsOyBbYjsGyoViX5pRJBIDFMEz8IeOqbT9Mo50DMEGnbyaEH7+fA9gSXL43zpX/5b1gce2PVfaIjjBSR1t20DOwEyyWVThMKhRCaTnt7GweP7GHzZpeGJxgbhUw2S+vAVhauPHuL632dbvj092eJpqJkMg7ZtCCly5UuS4qiKIqiKIqiKIpyExXOUBRFURRFURRFUdYV1iBpSL77xgRPfucVKsUaEAPmWHfD/SYBmpmif+8THHzgQTZt6aa9w6RU8qlUqlw5f5JqfvgdzyediTMwOMDo6BixWJxYLEJL0ll+1gd8NDOMG4ng2BqGYE31imZ7Cwg0l96BAaaHOvCKF7m2cS0MdMNh+97DPP6Jh7l3RxRT3FyFwfN9ZoaP4ZeHV23gCjTDZMuB+7jjrruYq2jXtsMBgiDgrTNneeppm/GxWeKpNh55eCv39BiYhkaqvRs0G4JbhTN8QvE2BnqTdMXEteoMHlD2JQ0pQHi3DWYAlIpFnnn5HBsH2hk5f4Kbr6OgGf+QRNs2sGHPIaqlEsVikdauLhaO/pjKyPMQCCBEUBljbnqK6elpTNMkkUg0wwSGweToYY6P/gipt0BQh8bIquNYBA3B/Pgo2f6tTOUvIRu3uhc8bh1aAdDp2X4/jzy4jbi+to2NlHC5JHnz9CxvnTlLfm4WYaWQIotmGVjxTnbu2spnPnonWRvWXm7Ja6fGKJfLeNUSy01oltdsZd0qJPr6uevgAdpSYW68XTTTJJXN0tHZSch1iYQjJFJJMuk0Dc9DBgG24yClpFatMj8/j2EYzSoZjkPYdYknE2hCQwixXMnCQAhBJBqhu6eHhuehGwam5VAXYZArgaKVaxkBFgELtB7sdB/VhRCUZoF5oEQmkyGdjvPmG8ex7GYow3VdwuEwQRAQjTlcvHieoUuXMNww2D3QWIBgqnkkM4sZ28jg3vvo6ukhnohj2za1ep3C0hLxdCtCd5DejQGNBsKO0TKwBc/z0TSPaMxiKR+wlK+xlC+RTJqYpo4MAoaOfQdkFbQ2dh56iPfduw3dr/EH/9fTzE7niab7adQLeFo7RrSDbM8Gtu6+i0wmQxAEbNq8mWKxSDqdYvvWLNsHQ9iOYKECMtAJfB+d4G2qjzRFUoP0DbbT8BxMU6NWBDssSMZv/p6hKIqiKIqiKIqiKKDCGYqiKIqiKIqiKMotmMDEkseXn3yFydOvEBTOAHluH8wwlp9vbm7Gew5w72NPsG3nDuJxBylB13xmpqeplXLvYjYCNxIlkYjQ29eL4zj093eRSa6ttqCZDrF4DMvWuKnmhQQpAqbGRnnz239OaeYUCB9wQNbJbniQZMsAu3b3sXtrlJgp1u70L4uGLbo276cuE0yc/jYES0CdoHCJxfERuns6ScbMNa9p1Co8/Wf/M9/9vwsEWHTvegzX/R22tW7G0nXScQOC8i3P3ooPcud9H6Gjs33NlHQg5gj6Bvp52Y7jVeeb50ON9a6Tt3SVH3znae66awea20WztsjqNbTA2AhSUvENioUCsUSC8clJUrUa1fmLECwCCWCeoDpDZWkbl4eG2LZ9O5quYRgGqXSauw/dz/TFo0xcukTzblo5lr78dw5v4U1kRyvx7r3kLs8BJbp7eikWSywurISAbl+tRXe7+MDP/Tw7OiNr0hUSyHuSU5fqDA9P4nkNQpEI2fZ2ZK0XKyhw8H0f5Au/dIQNCf2m9jV1H65OlUkm4oxdzS3PeSVyc715SXtblk//4gdJRtZecwDDMGhLtZPJZkmn04QjEaLRKNVqFV3XCcdihNwQbshFN3RAEgQ+miZwHItUKoRlaQjRbMmj6QLDgFoVSiWJYeiEHAfD0CnlFqlVyohIB7JkQLDy/qov3w8eumuS7OpiQdOpVUrL11Jg2ybTUzOUyxVAXGtnYpommi4wTcgt5gmFQrT0DpIbu0BQXwkCmdiZnaS6tvDwYx9j67atJJMu1ZpPEDQYHxunUi4hgxsro2jL94KJ44aJRCKEQhr1GhSWQCIQQlCpNANQiUQcgiogiLTt5Mj77mXPhjCzRY9/8uuP8/FPfxghfY4fH2Upt8SVq1fQdJuDBw/S0dWCofvYdohS2UcGPncNhOgICWpAzQDLlkxNTTJ8/jTrV3FZK9XeS1c2wkzBwbah0gBdgi1U6QxFURRFURRFURRlfSqcoSiKoiiKoiiKoqxrNOfxx185ytN//RT1udPA7aoyrGxWX68qIMwkqc7NdHZ2kk6HaWvTcWyoVmu88NQ3mB96DghuM+Yqmku6ezeWbZPNZjFNk127+5keHVozBzsco7OznWRYEF71jJSwVJc8/+NJ3nj9KIGTQETvwAo5eJVJ/MIIkUQ7//2/+1ccOdBF1hY462UzJMws1sjPF1kqlNFjm/Dzk4AGVpzZ6RkuXzpPx6PdiFWvlkEDr3y9csTwm1/h+98c5Bc/8Du0R3WKs5dvsxY68fZdPPj+h9nSn2J1XQQTaLU0fu1XHuFHL3yYcy/9vzQrTWis3wakzJXj3+Trf7WRtr7NjJ90Qa7aiNZMRKID0AgaHnNz8804gqZRr1ZpFAMgC8w2FwOTxuxxFua2MzU1RSaToaOjnUg0QigUYvzBx1kqfwMjkqU82059fgw0B/wiwjCQIk4uX6Kle4DC9Cb80ikymRY2bWnluWeeusV6rF2btg2HeOzhuwgba6ukAJR8qNfBsR0isRip1lY2b97EfffdyfsP9dCTcJqvE+KmihvjizXi6XY2b9/B2JkXaYZeKsujR8BIIXSLZMcg92yJY9wQDAmASCxGcqD/Wjgjm82wuLBILBYjFosRDrtYtkkopGPbzeCFaYITAkNv/jsUEgQB+L5A18EwIPBhYREiEYdSsZ27999DfssWZmdmmJ+bY2F8jPL8OI3iLHgN8HxAopsubiRCyQ1RIwDCgIVuwNjYBLlcDsuyCDkOpmmi6zohVycI6oTDYU6fOs3o1SsEgba8FiDsfnzfxq9VMUwT29YJRyAa0xHCJhwJE0ulMZwkXnl1CyMBpJDSZCm3SCqVJAh0ikUIZEC1WkHTmsEUy7LJZNPNAI0Wp3fn3Ty0v590COIhk3A8xdAEhBzJ8GiRvoFuPvsrD/D661cYGV2gfzDLnt0JLB3yRTADSZvbzPI4QMqCwV6N/oEuTCdEMzSiLV/F9d6XNpFQiLaERa4msGxB2gVDk8zM3r4diqIoiqIoiqIoivKzS4UzFEVRFEVRFEVRlHW9cnySkdlJ8pNXgaVVz1yvGnDdSkWBZiDAcFLs+/Dv8PCHH6e7p5P+fouWmKAeSLItUXr6urjy2jvfxNQNnbvuuYt6zW9ucrckSKWTvPHyNEGwsnkaom1gBxs3dZFwwVgVrgiAt2Ylvh5nx+7d5GZnKC2coJabgqCAEB4RV6erPUHPckuUWzUnqFQbVOoBpYmjyHqh2dpEz+J2bGPzHXuIJVJIeWOLjBtWyy9y5pUnOTf8y7RuTbM4X7rl12pOB5n+nbR1JIjHV6o2NAlACkFHyiGabF9+xLvtWjZKE5x+9ZtsO/Jp0Ky1GY7AQ5YKaPE0BAGJZALDMIlEItSWcnjlMlAFPQt+DSjQKE/h2hrJZIpINEK2JYTvAzLCnrv340vB/Pw8bx1r0KjryOIYBGWE1Q+BwCsugjZAov9O5s+McvzYG2RbWm97DtfO38xw5+GH2LspvXbBZbNWRK4iGbo0yvzCHFu39HHvwQ9yYEc3HSkTVxOIW1xnieQHrw/j+XD11I/wS0WgDZhcPn+b7M4P4QXQP9hLyhHXDr8STyoCdihEJBIhHos1QyuRMLZtEwrZOCETfbkShuMIHAcsq/kRDoFrNsM3uoC6bI7ZkGCKZkDDygriMcnoiIFtWUQiEaqVCuFwhFQ6w9JSPwtzc81WLvVBdMMi29mL67rNgI9waF58l5HhCYKQztTEJAODg7jhMJZtY1oGiYRgZLjI6MgIi/NzUK1hJNrxDQH1BTYd+hia6fDgw/ez565B2tstnFAzEzI54VGv1ynmFwkaNSDESqgDfBA14n1b2LhlK6VyGc+TSCnwGgG6pqPZGmFXIwgMolEXCWh2kr3793Dn5iQFIYgCuge+B5moYPvmVk6enWAg1c6WRzfy4olZrowtMbsQI5MQDKQgjkAX17+TxQTM+AFnT5wkN/K3NNvoOMvPrvN9yuxg+74HidgGSEHgQ8SGvA/oN1dQURRFURRFURRFURRQ4QxFURRFURRFURTlFi6ev8DVC9ME5RlY0yRkZft5JRSxssVp02wHIOjY8j4e+flfYNfuLtJJg94UuBqMlWFiokJpaaVlxerX35putdDdk+DqSJ14Is7GTe0sLlaZnrpezUOzs2y9cy/d3QlcfW0lhAaSQr3G0NAFXn3heabOvAj1SRA+ltPKgQ9/kk9+4bfZ1RfF4NbBDIDWdIQjDx9m5OyL1HMl8CvgT6HVchy69wgHD+1CGLcboSk3eYYXXniNQ1sew4l3cHOLEUBYtG6+nzv33o2uGdT8m8cVgJCSSLINYUSRXv5tjz0/fgZdBOjmcpBi9WhCYBo69Vyehakp2np6CIfDOKaJFgkRFOpg74TaVfDzEMS4cuo4VjjJwGA/vg/hsCASCZHJbqDeqHH65BnEnXuYm5pg7GQJKdsItXTihiN4jTqaruOmMpQyW6nOvszM9NTbngNAKNnPox/YTyqsr6maUQZmJeim4NC+dj76QCe9aYewCfpyiuJ2V8gPoOqbeI0qQkiCWg5wQHSBHAdfJx4Os+fIvXziI/sImdq1Y0ugIGGiBqYTJhaLEYlGSKVcnJBBNBYFwDCa7UIcB0Kh5UCGBSENbNF8N5miWb9BLk82WH6bBICrQ86A2ZlZRsdGMXQdJxTCNEwM0yAajZJKpSh3dlEoFHDDLr19fRQLBUY0DRJpyAXgR8jnlpgfPkW9UkETAsdxcGyTSEQjFpMUCjWyra30l8vYTojhc2/h+Q5mdJBGtc7Bgwf5uZ8/RDqtEbYFvoRKfaUNiwHSJ/DhehJo+fuJ1HFDDolUEt/zEMstQSTNNi6BDHBCJlKGKZWKyCDADTnce2Q3dVsjSjPA0uMKMoPNdYtviGAY7ZQ9QacjeGxPlkvdHkUdojZE4FowY+U+0CUsFTzGR8YI6itBqeot75JQxOTwvfuQGgRSUq1AEAjyPnSkbmqopCiKoiiKoiiKoiiACmcoiqIoiqIoiqIotxCJhth14B7mLoeZHilEXlMFAAAgAElEQVRRKUyCXK/Ev6S52eoitCStm+7iocc/x+GDnWQyBi2WIKU1tznzGszOLDJ68SzXAxm3D2aARarvAKFIknpjglQqRq0mOH3qMsVCcfnlgnBmI9t3biedMm9qaTI8W+fP/8tz/OhHR/E9j3jnBoqLKVr6t/Brv/k5PvvRu2iJWjjG7SteICCTNLAdFye9BWm2ACWCagWirczNzZJJQsRc1eJCSqq1+k1DBV6Zb3/ly/z6p95PS2fHuusQyuxg/0Mf5kOP3odtO5jG9Rolq8XDJnfcvYdXnuqhtnDqbdYTqqUFigtjWE6USvXGJwsEjRiyssj8+bdolCsc+dAHyWQyDB19iby/BfwGyASIIsgchcnj6OJBDN3A8yRuWKBrglBIY9fuQUzDJJfL02g0GN6+g1KphOc1K3wEgcQPfCbGxwl3bqOauwCN6ZsX/qb10Ui29HL4zm60G1ZEA6IC2sKCgcEw1vIQbx+ZaVqqSVq7ephdHGLjnUe48OZx/Mok6FmEkUbokO3s4jO/+BD3bwmzeuSChIkqTEyDYTq0tafZvqMLwzCRUiClJByGcARCNoQsCOng0qwrsRLIWHeuqx40gYYGUnr09/dhGCa2beN5Hn4QUK1W8RoNDMOgWq3i+z7xeJzRkREwLUQ0igw8yF1hbm6O8UvnGdy+G9d1cRwHy9KJxQW+L4lGk8SiUTzPY3ZiAq9UQtMg2dFJ36aNPPaRI2SzGnGnWcmiAchAYNsmiUSCeLoNq3U/9elXIZgHdHA2IwyX+ekpZCBJZ9LLgRVJrVYll8th2zaacLAdm7HLbyFlQPvAFnQngeZBeLlIhRAQWV6bbNRg384kkeV1sjTBthaTPM34k3WL+yAeNdCCYrMSzjU33nPNdieBF9CedBASPA9sQ1L2YGS8ivDWayekKIqiKIqiKIqiKCqcoSiKoiiKoiiKotzC55+4h8c/+SkKlQYvvHmVHzzzPG+++H1GL/yISn6a65UzoPkb8Qt0bn2U3/2Df8+Bu7oYbDMIECQBbXk3NO1Aa0uYeNsmpi+9cMNG6C0InyPvuwfTdHBdFyEMTp24RKlYQl7bPLVp6dtOT18Hcae5Cbuynb/owfHROoE02LR5M+PhMONDHumObv6nf/dFHj08QFIXtw9lLJMSpgsBA/0d1GfOo9kJjGQv6ZZWQo7N4kKO+akCTmf62ms83+db33563fFGhoZ48eQkxdw0zS3t1eftkN1wkPaODmJRg95OjbS9/sayocHS4jz1wo2hhludSMDk8FnsSIpKbtXjug4C/NISQiwhqzWWhmFpbo7NW7YQ695M3YxTnR4D00QWLwN1rFgbjusyMTFBOpOivSOJGwYhBH2GSyy2mdHRIjNTMwRBwOLiIvNz81SrFarVCrnFRbxKBdMNYya30piZZeX+siyLO/bfz5uvPo/vXV8jYbbRtXk3mah507XTBMS5Xu/lnYYyYPka531mZwuYlokbjWGnO6iWo9jRBD1bd2DoBgfvO8SBjS5ho3nvSJrvgpKEyTnJ5ESVrvYUd+0dwLIFvi+IhCEeEZg62HozYGHRDGTYND9/J/OVNH+gE0jYd89Wdt2xjVKpQRBArdqgUm1QrVRZWlrC9zyq1Sq1eh3TMLAdBzfsUq/XqCzNgywyOTxEaeYsmYcewQ2HMS0T2xHEolAuC+r15li5XB4zFKJ3x06yrS0cOHyA9z18B1sGbeKGwF0+lzqQCyTlch0hBL5XI0CiuZ0ExUWggfCWSAzejW47LOYWSadjza/1oVwqs7CwQDQaQWgJvGqDSydfAnTSXduoV6tENPCW27ysXi8DyHA9ZCWW/4jfbkFFM+jR2t6Gm9pE4BcIvBqNSgEZ3JBeMrrA6cGQFSoNKBU9LF2jUBUs5ur84Pkf8lu//vm3uYKKoiiKoiiKoijKzyIVzlAURVEURVEURVHWFTE1WsMGLa5B7/u38PiDWxie+1VOnR3h+We+yw+/8yQjF07iN6pohkW2Zzuf/eK/5kP399ETBhDXNk5XghKGBrFYiIc++glmrh4nN/oSb1c5Q2gWB+7aSLUcYBgGl4euMDMzg+/7XD37Y4LAAz1Oe+8A6XSEqHl9s9yTkpkqGCYYhsGp115mduwKfYMb+J3f+2d86Egf8RtaoLyd3GKZgBCZjXuYm5ymOj9LqK+PO/bsYcPGQbrbY2vGu3J1hJf+9oV1x2rUyrw1tMDI+ddvPm+zhdaOHhKJKJs6DNpiotnuYZ3f/Hd06GqNXTvvd2Jh6jKG27X2waCCFjEI6g2ELsGrQr3Ia99/hkDXybS20vB9rHCE0sRZvGIVRIJaSefU668RjcXYum0LMmhWhTAFtNqCpClYWnLRRAsSiWGaZDIZyuUyjUaDk0ePMXFpCCsawYp3ERQ78cujzTVqNDh99NU1wQxEiLZt7+e+9z2Ma1s3ndvKI+/mul4nuTS2yMT4PJZl0NndxaFHP8qJo0dxIxF23XEHrW2t7LtjgLi1NtRTlTBTkFy9UuT5b3+DRmmccFjguoKwA6bevD6OaFb20Gj+YMak+e93OueV91PEFGzu0SnWoVyzKZcl5bJFrQaNhqRaTVMuVVlaKlCrVVmYX8A0TaLRKJVymUotB1TJj53EsiHbuQkAXdexbXBCkM8HlEoVMpkMe+7aw+TEJJZtcfDQPdy9r5e+To2sIYiI6+eg0XyvRyIWqXSK6cun8WbegsAHrRtEGen5lKfG2Hz4AcLhMJGoSbUKCws1pqdmOHf2LJu3bkHTNHLzk4xcOI5mxOjduIOu7hQXcoK2GLSbN6yNaIZy/OUPY9Wa3U46pPF7/+Zz7D90N68fG0b6AVcunuHCj75JbvIU0m+GNIxoB9n+bQz0dhJIqNbq+Dgs5jwq+Wl++INn3sEVVBRFURRFURRFUX4WqXCGoiiKoiiKoiiKcltCgIkgaUKyzWFX20Y+dv9GLv3mr/LdHxznzTfOEsu0c9f+XRzc102HKzCWf3t+JZixohyAbtik0mk27nuMNyZPI73F2xxdp2XwYQa27eDiSIWhS0M0GnUmJyaYHrvM8NFvA6AZEdItrYRdk9hKuQQpubJQ40//8jWOnbhIsVBi8solsimXf/Ivvsgjh3pJauLahvLbkRJqUlKTJtnWFno2bGJqdAqhm0xeusjefXdz36FBNrcZ105aSslT336a+fm5dcf0G0WmJ2dZWpi4cdWJt29hcMtWuns7CDkaNZqtL0oBRLS166ohePjenfxJSwuzYzPv6HwK8xMkbgxnSB8aYwhnJ5qo4dfGgDKNnMbU2BjZ9nYKs3PYkTB+aQ5EEvR2qJ3HL8RIJBJYlk212vyBQ1iDuIBIDOY7dCrZKK1tYWZm2hkdGadQKKBpGpF7I7jRKI16jeGLFxGdByhemgdZRkpJuVRYM00z0sLdD3yA/fu3YVtrr+BPFshYtQSA5YYxrSXqjTrFYomt27aCgJnpaUzT5P57d3BwUwhdiGthmIaEmYbk0lWPUyfO8tw3/gOPPvFRWlIQvX5LoNNsXxLi5vfHu517WDSDR0UDlkKQtwRCaxZA8TyBZZmEwyaxeJj5uTzlUhlN07BtBy0IoDoFBODN4aS3Y9huM5hhGUQizdshn4dYLEqj0aBYLBKPxzlwaC/79nfQltFo1ZvBjBvnrhmCVNqivb2FRLaTMU0iAx2CBczsHuxEG41qnUa9wYYNG4jHQ9SqkkbdZ6mwxPzCApomEEJw+o2XKSzOEM7sZtO27SwVBYYFrWGulxu5YR31mx++JQE4QrAlYTH4c7sZOrKV4VmPpeoHWMp/jhOvH+Xl7z3J2df+hnruJIO9D9KWjbIowWvUEcJifLzKiVe+w+L87Lu8ioqiKIqiKIqiKMrPChXOUBRFURRFURRFUd6RlfYAOoKoDnd2Rdj22UNM/cIh6h5ELEgZAptmg471NkcDKXBCBm3t7dz30EOc+v6fUF26dThD6A4PfPSTCCfOubde5fixo7iuy7kfvUBx/DVYDnZopksynSIW1rEEICVX52r8/h8/zdf+7MtoooHfENi2yYOf+Dy7trWRsJrtL97NhvhMBX78xiV0w6SlLUO4tRVd14iEQriuS1vSIKJdH7FSrfH1r321mexYbz28EtPjI9TKubVPCJOOwe0kUyka9YDZKrSYzcCLLpvhjDVfLmB7T5z+bQdZKmvohkM1P4wMakjfg6DM2jY04NVyVIvzN8+pNoMIl9FDrfi5ISAHjQYzV4bItLcTTqUozM4izS40s4WgMARBlVimDSEECwuLtBYjBJ5GSL9e7aMrKxjPga5reI0QU5Mm6XSCkBumXEpgOw4T4+NUa3VyC/OUJjYjSydumnc8kSbdu5F9+/ewd2MIS/u7xjFuWEsEG3pczlxyOPfWGKMjI8TicbLZFkzTZOeujdy7PUzGXNvOZAmYWICrV2Z57QdPMjtympj7MVKGwBHNDIFOs6qEuHasv8s8m8e2AWO5LYrhNoMZlRBUK1CvCyoVCAIN0zRxw2GCIEAIqC3Ng389SCA1l1KpBEhMSyMeFeRzEt+XlEplZqanKZWKPPzB+9i+LUlXiyC1XAHkxnMRgJDgeVAqVWnp2Uiibz/5ifME5UUaCyNE2jfQ3t+OYVlksxkSyRAzUz4SyeTEJEiJaRqA5NhL30JKSefGPUg0dF2QTUky9q1X8N2uraD5PrKEYGvWZlPWphJAIEI8criLsc9+kD//0yP8p//999BlHdfSWPSaAaxLF+fpaHV5/qlbv9cVRVEURVEURVEURYUzFEVRFEVRFEVRlHdtJahhI+iyQVrNjWchwJdQkxC+9oXLG9gS6gIyKSiXI3iNDjo23cPlN4ZvcRQdTdO4/9AmxscWOH7sBBMjIwi/TnHs1TUby7oZIpGIEQsLNCRTuTr/8Wtv8uJ3nqYy/iYYMdxsP+2bd9HS3kZ7wsDk3bUzAfA8nx+/8hqpli5GLw2TTiVp7+pmYMMgbjjC6EyDrWn92n+2T546zfFjb956QL/G5OgwnnfjAptgRpicmCDsupxLu1R7wyTjgvgt/icfdQz+6e9+iZdev4ym6czPzjI3O8Ps1CTzY5eYHXodWRsBlg8W1CkvjNw8kPSRxYvoyfvRLI2gDrBAefYyi3NbCUcjuGGXccCbPQ3UwOgBPUq5VKZWq6LrECwHBixohnpM0FLgSYEhBO6dHWRbbPJFmJ1tEI1GEEKQz+eRMmCxZTP18SlkfQqQRBMtbNixl3DIRbNjHNjTRWeYNW1FfioEWFLiOA6RaIRSqYwTCrFz1w6i0QgbNyZxjbXtTISEQkMyNFTglRdf5OSLX0VKH2s5vHBj45Wf1pRXV+OILAdAbAfyJhSMZkBDSigVA4QQaJqG1/ColMvUFsaB2rWx6nWPYrFIo+Eh8DE1jbn5gLnZJUKuQ7Yly517trF1S4yebLNqh7tOMGPlcx2o1zwKhQJzU1PUPElm8wGWxtLU8iVqlSotrS10dnUhNIllCvxAQ9N0yuUypmniOBaV4gKXz7wCQpBs7yYScZFSx/Cb5/seXH4QzR+YRfTmJ1ET2tostn7pV2iJmbz42iVguX2LadIolFmaPMmF08d/yrNRFEVRFEVRFEVR/v9EhTMURVEURVEURVGUn9jKJmywaodUu+H5FUtArgFogpYWnaFLDXYf/gjj516gVpxeZ+Q2Wjr7uXt7H3/94gQz4xNUSyVqE8fAX9smxHBihFwHa7nFwVe+d5IXXnyDYrEExDDj3Ww9cISunh7C4RCO3Zyl5J1v7kokL75+hVNnLvL+3o1EUmkuXhnGjUaxbRvXdbHM64EPKSXf+OsnqZRLtxm1wdTECMGNvRmCChde+ismL51k/uD7aWuLsnugn6wlsMX689aE4EOH+9iwvQ/fC1gqBkxPl5idzXH+3EWO/XgnV06+SrUwSyN/AYIcQfUWLRhqsxiUINZBZe4MAH5lnFqpSLXRID85gTBM8G205HaEEaVabRCLx4jHY9i2RqUu8KxmQAOaG/m2AdMBdLdrpDsdAPJJSCZMQqE09XodXdNwbJv83Bw5/268uXN45Yu0dg0wOXqZqeHzHHjfx9jR7aD91Lfmm8JhQcjxaWlJs+uOXc3AghBs3pKhPa7h3HDYKjA2F3Ds6Dle/t5XKc83A0cONwcz4N3dd+/EShUNSzRDUb4OWhgMHRoeGKZGw2tQr9ep1WsUc4t4xWFWVyURsoSh6wRBQCwm8AOoNwI2bY7jhjRMEUe3NSxTEAC2WFsFZPW5SUBoEIvqWJaJ8MqUh09Ry7UT7ejByUjaegewbJtsSwvhcAihQRDIZnCkWsWyLMLhEENnXic/N4EQGvFEshkKsyHpvgfBnHXWFVaOI4hagi/88hM4LWcRCKp1CHxoa43z3f/0VWrVyns7IUVRFEVRFEVRFOUfNRXOUBRFURRFURRFUf7OVgIZK60BIquekzR/P78QQN2DchkqVYgnIui2Syg1uE44Q+Kku/jCv/q3JNMp8vkLLE5OUp0bhsrQ8qgrBJrhYJomIR0qDckPXjxBqVDgjn172PfLH2T77p2k0wkcx0G3XWoe5IGYfOcbvBOLVb733DEOHD7Mwvw8Y+MTWKZJbnGRcqnE7of2sbnTvLYWi7k83/rm37zNqD5LUxfxbiqdIXEjNt0btzE3N8fw8CTWg32k9bXhl9WEgBZbEGsDgU5N6iz0xZnMx+npzdA/0MuZHTuYnJjg1CvPkx96GmTxFqMFlCaOEmndQWXuLCAhyJGfGqV1w1ZmRkaRuQXseDvxnj5KczMI06RWqyGERq0qEYhrV2l1hYeUAG+56sJKNCCICvwOjXqtDcdxcMNhQq7L0MVLjJw2mb9wiUunX7s2u3RMI2WL92xzPq4JNvQkGR1bIpVKMz01xeJCjmSoi61p/aZrUPElb52f54XvfZfZCz9k5cxWvy/W3rE/fStjWjTbnBiAbUHIAV2XlIol8rkchaUCS7OT4C+seX09P4wjKnR0ttLZauBL2LzRIBkGRxMIdBqA12iOLW5zHv7yRyAFkWgUy9ARok7IdbClT+uGLURiMZASAbR3tCwvkGBxbhZ8HysUwrZ1fvjDpwkCH003sW2bdCqCEOCs1zfpPSaA1rjDpz92J0KHhYLH3NwCXVmNH37vqb//CSmKoiiKoiiKoij/qKhwhqIoiqIoiqIoivJ3st4G7bXqEcsfdQklDzwPAtl83rZsHMehQYLmf09XBxQcNu0+wKeeuBdPA8/38aolKJ5ldSuGFbquEY3YJCzIVSSa7fLffvZ9fPqxPURDy80PVk9q1dHeSRUDCUzna7x15gLRWAzTDuHXa9SLBdxoFMexGegwaAtpIJpVM156+TWGLl14u+WjVppA4K95LJzZyoO/+D8wMjqOX60QsgKSlli3UsFqQjSrNQialQ1ijqDNge5UmE0bNrJrdzc/eu0ixaU8J4ZfQTYqcMOxVwTlKWSwBc0IEXhlQKMweZG2jdvIdHcxd3oW3DCLE2M0Ji+i1buoVCpcvXKVtvYYjhG6qbKFgDVVJzSa7TgMgJig2qaTy1kkEgkymQyFQoHJoRRYrVCfvPY6W4D+HgUzVqrB7O02yW2IcOpKiVQqRUdnlpaEiSVuCPRIyFclx14/zbmXv45szN803t8nbfnDl1BrgO8359toNKhUKuRyi1QWx7jxfRQEcOLYKe44cATz7k0IQ5C0mveTJq6HMQxz7Q+T1nv/6IAmQddBELB9/xF23b2f9u5e0tkMoBEEDU6feotINEI0aiGXvy8sLCwQTyawQy7Sr3Hi1eebx5ESP/CZmcmhaRrGYPzvfW0BhBC0hgRVYGq2xPjYGPnRISbGbtWeSVEURVEURVEURVGaVDhDURRFURRFURRFWdepU6dYXMyRSMQRP2GJgpVghiWhVpRMzYLvBywt1ZmYmCXkukRbBylN9UN9hGZQIIWw4rQObCYd0pisg2mYOGFBVebXOYpOLNtFV0ecsA5VS+Pf/vZH2NkZxtDWmffyQ+bNz9zWtp44/+H//CJ/89RxTp+9Snf/AKFolL6+PuKJJFcm6mxtMTAMQRBIvvrVr+A1Gm+/RpU5pOauesSkWqqwmMvx+V/7JXZvS7I9axNb1TLldsTqv5fDGp2mIJ2EbNShWu3jjR9lEXoE2bCAW7ViCKjnh7AirVRzV4AGfq1BpbCEITSMZBbbDVOYOo+m2bjZHmq1GhIPGXg0fCgDIdZu3q93DiEB7RqYrSBlhMmpMI1Gg7m5Odo3bMILHmT+7NeRfjNQUK3VqdUb2Jb5E9+btyMEuIbgsX1t3LND8uqQR7ECcp1DBUjOXs7z/W/8F2q5t2495k99lrc+zsqxGnUolyWVikTXdWq1GoszMwSFUdbW8gBhhGjp7ieTDhEISOsQo7kWOs2Plco4b3d8DUhoEI/Cho0JunsOE47YWGYzLBIEoGnQP5Dg1MkJPK+OYThUqlVm5uYxbQfHcRi+cJap0SvNcYWgXCrxykuv8sEPHMDR4z/FVXt3BJCrSc5fmGb4yiWmT/4VMgje9nWKoiiKoiiKoijKzzYVzlAURVEURVEURVHW9Yd/+Ec8+9wL/Mvf/Vd89MOPEHZD73ojXAAz+YAz43U29li0xyWnzuc4efoKExMT5HN5wmF3uQVGAwhAszCzOxnobSPi6DQqEsuykPU81xthrKKFaO8ZpLctgoGgxYK2rshPdTdcAI4u2N0VwfrYAZLpFi5cGmHDxg3EYlGEEEzNlJkquwxGYXxikuee/f47HL0Ogdc8ihYn0rGftoEt3Hv/IQ7ubWcwLgjfWK3hXc5diGZIIm0IOjvCpDJptFAbQfXq7We2NI6b3rj8WQOCSRauvEl2cB9+o0FldgzhF9j14Md55BOfpq+/m8ENEfrboMUQ19pfvN38AEwBaU1QzQp8X1KvZSmVNiOEoFatolXuY+bS80CD5559lp9/4hf451/8IvcePoD1HoU0NCHIuoLDG0z+9kKd6A2lSyRQ8ODZZ9/g6snvsrb6CwSBREr5nsztVgTN4JGUzRBErQblUp0gCCiVShSmroI/e/PrtBCRSIy+/hQxG7LazdVJbigYcls2MBARpFwTXZg0AhAa+AGUvWaLo2g0RKmUYXJijrbWLhbmF2g0GizOz5NtaeHNv/0LvEa9eTwpWVxcJNk2SCgcorF8jH8YktGZBq//6ASnj77G5NEX/8FmoiiKoiiKoiiKovzjcatWtYqiKIqiKIqiKMrPuCDwOXb0dX7ls5/iscce45vfeopypYqUb7ctu1a94fHMc2/wB3/8LM/87RCd7Rb3H+4lHLY4e/wYxVKJ5rZvvPm3aLBx126OHNiBpkE9EBSW8pQXrqw7vtA0UkmHTBgEEn05yPDT3g4XQFgX7O3Q+acfGeSJ929ByBpXrlzF8zxqtTrFarORy/e+/yzTU5NvN+QqARDCTN7Bwcd+iX/2pd/hw49tZyABYe0nD2bcOH8HSEU1enu7sKyA9VrErCYDj2phGoQJSJDzlObPgqFhWBaN/BybDn2Mwx/6KMlUCjccwrYEIUNgCJotQN7F/CwBLSZ0tQu6ehw2beploK8HozZOce4M0KxEUq1W+M63nuSjH3mUJ37hUzz3/ItUq7V3fW++o3kJSIXgyFaLhH3D+UgYmi7zzF//JX515qbXfvVr3+CP/v2fMHRlGM/3eQ+mty6dZuuXIIBKBQrFIpVKhcWFRSr5UaB+02uEbpFty9Le4pDWxLVghlj1sebrb/H4ClNAVECnDq0adBrNwEeLDi02JFzQdUF3Tww/CJibr3Lx4hACyeWTr2FoknNHn782ngx8Js48S0RfYN/m8Jr2OH+fJM2WMUdPjvDGq6+yMHqCerX0DzMZRVEURVEURVEU5R8VFc5QFEVRFEVRFEVRbqvRqPPDF57nE088wccef4If/PBF6vX6O9oIF8BgxuRLn9vLBw5tJJ/LceLEFR7aleG/+ZUH+fgnHycZjaJZcUR4EGF2I/Qkm7ZuYdumHhoIiuU6Z469SaN88+Y3gPTy/ODL/5rf+Nwv8Bd/9XUmp2cIguA92QhvVqEQJFyDD93dxf/ymw9yx9Z2FubnsSwDOySoNzy+9tWvIuW7aXMgAJt4WzcbNg1wz/4O+lM64Z9yxMQQYASSWt1DyOo7eo1fXQQZsLINH9QXWZgexYolSAzsZPMdd+OGQui6jm1pxKJg0QwI/CRcASlD4uhFTrz8JH/5R1/g1HN/Sjk3ftPXVsolvvVfv86HH/sQP/fxT/LMsy+8JyENIQRpS2Cuuh4SqEnJt79/nKFj32W9qi7nz53hd3/7tzhw4ACf/uyv8q1vf5dcfuk9CZGsmS/LASUBtZpHuVRicWGRmbER/MLVdV8j/TJ+aQLHq+Is18X4Se++1cGNlZYoBs3qLe5yaMMRYFsQcgSDg23MzCzx1unTjF48hWYIFqeHmZ9aHciSzFx5nb/4w9/gcx9+iD/8w/+DCxeH8Dz/PV/P6zNoViQZzdf5y7/4G6bOn6Q0ffbv5diKoiiKoiiKoijKP34qnKEoiqIoiqIoiqK8I/V6je9/9yk+8tgjfOrTn+HV116n4XlvuzEqhKAl7vDxI338d5+5i8cf2IwrYEubyac+c4jf+4Mv8fOf/3VCjomVvRMjPkA6HaM3a1INJG+9Ncmlky9DULnlMWqVAt//zt/w2U//IgfuOcBv/NY/54UfvkihWHrPNm6FEP8fe/cdXtlV3/v/vXY5/Rwd9S7NSNP7jMdtZuyxwQ3jjhshIYkT4pCQQMJNnhtCLjc395Lk9ySBJARCwiWQhGYwBmzcMO5jezy9q8yo9350+tll/f7YkqdJGo09Jr8frNfzyLJGZ6+9dtPzSOtzvl+qigJ84kNXsW5lLYFAkFQWjre1s/uN1y5yNG+OVr6AzzQJ+wURLn0FEClhOuMyPDhMIVtgcaNLwJ141+QAACAASURBVAFCM1/aZMdP4aSmKamsJhaLIYQgHA4SKxL4fd4fG/RFjn7uBNOpNE9951E+euct/P2nfo2etn1I6Sy4WS6b4ekf/5C77riNu+6+l2ee+Qm53MVXeVnIbNjh9FyhYzTPY9/4D6zM0LzbSSkZHR7kO9/8dz5wz53suHYn//MvPsuRYycoWNa7cn8WpPfhuuDYDul0hoGBfoZ728BNzLmNmx/l0S98gnuu38kf/fGnefGlVy9ZkESc8+HHC2oYOti2IBzxMdg/SsfBXex/7hHKa5roOPoqjn1+ZRfbKnBw/17++x99km3bruaDH/plfvCjHzMxMfXuhzQkTDiSR54+wptPfgNnqgW3MP3u7lNRFEVRFEVRFEX5uaHCGYqiKIqiKIqiKMpFyaTTfO+7j3DLLTfx8Ec/xtFjx3CchRfPZytOlIR0msv9aEJQJARrigWXr4/yp5/5MA/94R8ik8MU1y+hqaGUqB8GphxefP4NxrvfYDbAsBDXdeju6uCfv/iPvO+Wm9i583r+z1/+P95CeOHSL4QLAfGgwa3bl9Da2k4qmefRR3/AdGLqbYyWwcpnyeXyOAX5titPzGe20sOpniSd7a3Y2VEWc05PM0CrAMBOdGAGA9iFPNlsFsd10XWBP+DVj7jYuUspSWeyfO+xx7nl1tt46Fd+icN7XsN17IsaJ5fL8MzTT3DXXXdy11338Mwzz1zykMasgiv5wbMHOLH7SRZ7Hm2rwLHDB/lfn/k01+zYzt333Mc3v/M9hkfGcKW8JNVeXLzmL5kCZLMSTdcpFAoMDgwwNdTCXBU+3ppfIceJI/v53N98lltuvpFt23bwe3/w33jqJy8wNj6J68pLFtYIC4jqEAqBZUmOHmphpPcUjpMnGovSdfxCASfJ+Ngo33vk29x/7z1s276DT336M+w/eIR8fnGVfRZrtpVJBsnek9N89fP/QD5xFOQQF/cMKYqiKIqiKIqiKL/IVDhDURRFURRFURRFeVuS0wn+7Stf5vrrruP3P/FJWttO4bqLCFBIyWDSZTzrYiJp8gvWFml89Ndv5bIb76BpxQp2bF2B5cKre3t449nvYGeGL3p++XyOA/v38Gd/+t+5Zsd27rz7Hr7+H9+kv39wpu3JpVlUFULQWB6gkJlkbGycx77/vbc5Up78RBsD/YMcbssw7XiL9e90ll4rBonjOAxOZTi4/xjdx3cj7fGLHCmJHmsEEcLJTWLlUwQiEdLpNK7jABLXAV0uPpwhpSSTyfKjJ57ittvv5EMfvI/XXnkR27Yucm5ny+dzPPPMU9x1113cfffdPPPss2QvUUhDArbj8tSudr7y+c+RT53fbmUxElOTPPnETLWXbdv4w0/+MW+8uYds9p3Nc7a4h+NANjvT1iSTITU9hZ3sWfQ4hXyOE8eP8E9//3fc8f5buOqqq3n4dz7G4z9+muGRURzn7T1Ds9UzTCAGBE2IhL3KPKHyZeimj+nxYcYGTi56TNu2aG05xl999i+47tpruP2Ou/jav3+DgcFh71m/6FmeQ8KYI2mdknz9q49z8sATeBGYi2ldpCiKoiiKoiiKovyiEz+rvpyKoiiKoiiKoijK/78IIS7qF8aqmjo+8pHf5Dcfeoj6+jqEOL+phQQmsy5/+61DDPQP8uEHdrBjeQwdyLuSR18f5HjrML//wAZeO9zHH33s43QeegrpFi7JMWmaRk1NHTfefAsPPHA/V11xObFYdM65XgwpJbtap3n0ief5wqcexLbe3nyFWcrld3+KBz70AO+/sYYSn6BEA20R7U2klLiuS75gkUymGBkZobunl47OLk6ePMnJk+2c6uikr6+fTHIKLtAqZM75+WqQjgBnEAIbWbnjVpatWcuatWtZs2YF9Q1+6qoF9QYEF5izlJJsLsdzz7/I5z//eXa98hKF/PktLC4VfyDAzuuu4+Of+ATX79xJwO9/W9dcSig4ku/+tJU/+NgfMXbyaeDiqnssJBQKc9nlV/Dggx/k/be+j7raGjRdW3R7GK86Cgy7MDAJ/f0ufX0THDt6jKcf/Tp9e//9bV33MxmGQU1tAzuuuZbbb7+NHdu3UVVVga5pF3VOJV68od+GoQmLT//JVzn0xi5Sgwcor1tK35HH39E8NU2jrq6BW2+/jQcfeJCtWzYTCgUv+rpLoCAlr/cU2L2nn8//2R8w1PI4C8WmpJSXshuRoiiKoiiKoiiK8nNChTMURVEURVEURVGUOV1sOGNmG+rrG/jIw7/De667BiEEhqGj66drKRzpSfJ/v/Mqiakp7rznOtYtL8FvQLkOSUtyqDNDc5WfP//slzny8reBd7aYPB/T52flytXcdddd3HTjezAM4x2NN55y+JPP/DVHX3/iHYzio3rDXdx+731sv6oWU4cyH0QWKEWRyRZoP9lOa0srpzo66O3tZWR4kKnJSXK5HK57Kc+fDpQCo2DWE2vYxOqNm1i5ahUNDbVUVAaorBCUCZvgPCMIoTE6Ps4//OMXePnFFyjkc3O9iEvS4+Mc/kCAHddcx0c/+jA1VZUXvb0DnBhy+d6PXuenj/wTTqbrnU1ICITQ3zpcIcB1HIQQVFZXc/PN7+P+ez9AcXHRoofMA0M2TCZgeNimt2eI4aEhXn78KyQHDy96HJ/Ph+O4XssiIWZCDYLT2QaBrutUVdewbft27rzzDlYuazprDCkllmUzG2Q4929QLjAJDIxafOEfv09nyyHyiT50LU8u0bvouV5IIBBkw6ZNPPjgg1x5+daLDmj0ZeAnu7ppPd7Grsc+j1OYXPD1KpyhKIqiKIqiKIqizEWFMxRFURRFURRFUZQ5vd1wRjAUoqamjvUbNnL55Vu5bOtWotEYo+PTvPzq6zz54ydoPboPKR00baYqwBlVFmZ/TbXt04u67474zPgpDEPj/PXaMCJUjcyPgZMDXfc+LxAWsW37nbfOEBqapqEJcdZ5mY+UcuZc/VfQEJrANH2sXruRdRs28frrr9Db0XbO6wzARTMriVau4pb3X8+PnniV6YEOKHQDOc5sEVHVfAVjPYewrXenmoau62jaQp1eBf54E7gZ7MwEjn16Hq7Ea5VxCUIv8aXXcvl1d1FcXEyhUCAxNcXh3a8z3nkA7EGgsIi5AloUTbNx7RwgvadGnm5pg5SLD+noYaJFVfzpn/8FfWNZRiZT5G2bXE6g6QbBYBBN0wgEfCxtqqauJsqyUo24T0PX9beCDxLI5Cz6enuxrTyDownGhnrI5G26+wbp6R+ip3sAKzuN41hk02kcKwvy3XvuvbDYYkJYb/008v4rwXUlUkrkIiqPqHCGoiiKoiiKoiiKMhcVzlAURVEURVEURVHmtJhwhqYbhGPFrFm9isu3bmXjxs00r1hOeWUN41M59u3bx749e2lp66W/p5PR/sO4ziJafgg/yLe3MO/zBdi09Ur27d6F4Y/hug5WLjHzXR1vwdXFW4D1z+4QhAFoIDMzr4mgFW/BTY2Ak0WvXIMzegTsrrc1r4uncWZg4f+LTNPk8iuuYOfNd3H8aCvPPfU90smpc141U/ZDC1K79lZKKuvo7hwgNTmNr6SEwmgHwp7CyU2BMwpYNK2/nkjA5fCel37WhzRDo2jZ3TSu2czGtc30tOxi70s/IDM1hHQvTRDGHylj4y3/jWtvuJmVq1Zi2w59vb20tbZxaO9e+lsOkBluR7r94KQXGEmgRbay4877aarI8OKPvkF3x0mkvPh7J1y6kmVX3c/y1Ru47r3baF4aJxwKUFIEhVSe/hGLjGOQy9msWeonk03y6q7jlJWXc/2Vy6iMGERN5q1MIWdSIwVX8vi+KX768jGmJsbJ53MMDw4w1NvBeM9xUiOtOLlxvMYn/wXPgFlNpHY9QSOHnR4iOdGHnc+y2NCICmcoiqIoiqIoiqIoc1HhDEVRFEVRFEVRFGVO54UzhIbPHyJaXElRWR3R4ioCoQiunWdJhQ/btujr7WNsfIx8QZBxq0hNDmKn+ylffQOGP8bggW/OhB8usG/NJBSrID3VP9d3WWiRtLy8kv/9t//EJ3/3IRrW3cTEcC9DHYeBMIgYyDQwfMYWOlANgVqwh8AeBuJglEMgCqkjoBdBYClkDoBMXfjkvW0CtDBQBq4L9LyL+3r7/IEg27Zfyy//6m/SN27zxb/5M4b7T57zKg093ATSxcn0ADbetdMwwsspX3czuYLFdNurOOl2EBpggEyhm37ed99v8fR3v4htLSLMc8lpxJa8j9VX38xV267CZ5q0tRwnOdbDib3PMdZ7GCc3hetYb2t03Qiw7roPc81tD7Fs+TKqq0rw+UEIm+7uBCPDQ+zZvZfuk6dIJ8eZOPkimfF2vHN4NiNURfXGB7jxttt58P5rWBGe4j+/9V3+9Z+/TO+p44uumFFSu4E/+/uvUV5Rimn4Wbe8gomCJJ+H2iKNurgkKGA077VfeeNgH5/69Bfp7Ohh5aZNVFaWc+01W/mNO9dSERRnVaKZreCRzEtsCZbt0jZuMzwh6OgcIpezsW2b0ZFhktNJJsbH6Go5ymBXK8mhI7jZvjmP/d2hQXAD4aWXUdtQz7p1a0gnRhnpbWG05zjJ0Q5SU4M41hzteGaPV4UzFEVRFEVRFEVRlDm8s4a6iqIoiqIoiqIoys8t3fQTjpUSLa4mFCvH9IWwrQKZ5DjjQ930tO3FLmRBuuw5d9tgPQ1X3Ez1qis5uW8Xjau2MtDVfrpnyYVIB9MfxvSHsfKzVQMEIAgW1ZNNdM+7ad5yefKFQ9iuxvHXvz+zXQi0GIjwTI8CH95irwnEgCTkDgCzQYBxMGoQQkNSDMFasByQsZnvF/De1X+p3vCgga8cgg3gRCBngTuMFxx55+0zLpVgMMSNN97A7/7ex7lq+zYeeamXv/vTT5LoHwN8nD5/GsJXhevGkdnDnK5+IAGJnU5QmJ6gpG4J7lgjifQ4yFHAu9aOlWFyfIy167dwaP8bP+vDBPxIWyMQDDCdmCYQCBAtKqGyug4zVsvE6DAVcZOffvdz5KbmvxfnU7/mGrZcdx+1tbUUF0epqIR4XIBjEA2Xom8oZuc1S/jWt3dRKLjkrnkPB1/4MR0HHkW6ydMDCZ012+5j887bWLlqOfEik5KyCm588GEqN93DqYPP8Oy3v8yhA/tw7IWDJMs2buPqK9eysdbEAASCnBQkHbAK4M702Kn0w1jO5amXWhhNpBGGzlB/H9lslmQqzfYrl1C+NHJWOx5XwrERyXOv99LT248QkqMHj/Dgfddx445lHGrN47gOO66sZ2AwRSAoyRZuYXQ0xRu79vLaM48x0vYs2JMXfa4vXgAtVIqp62QyGSYmpgiGiihp2ExR7QbKS4t586mv0H3k6Z/BXBRFURRFURRFUZSfJyqcoSiKoiiKoiiKosyprHYVvkCI5MQQI32tWPkMLLJVgpMbZ6yrncveeysdh8JICZX1TQwerkBaF17MltJlavgkpxf1fcy2I6leupbOw71Id+655PN5Ok+ewnVcZtuTQAn4y9HDJbjJXmS+AnQDXB1kP3Duu+AdEBoymwB0EIGZsMQkkAdMEKUgE5x+R7+OFwSxWXxoQwetFLQa8JeB4Qdpg0+AEwAZxwss5M8Zc+HqIZdaLFbETe+7jd/4yMNcue0KhOGjPwNp2yBUWk0qcyWyMI10JtB8YTRMKppWkcumSSeCgIGdmcCe7gDXO9dTvV0U1y6huH45ib6umXDGabtfeJSr33sPur4Xx/lZVU2YFaHg6AQDAXRdJ15cTDgSIRqNYhgGJSUltBw8iGVdfHBGN4M0rHsvRfE44bCfSERSEoN8AYI+QXWpRBY0fJEwd91xNfsPDdLYWMF9D1zL//q9DCf2/Bjp5AFB49qd7Lztg0SiRVRWRqgtggAQDeo0NpRy9YYP8du/8QEeeewZvvy3n+PUsTfmfYZNw8R2vVCGLmYiTQJCGkjTuwNdKZnOu7SNuTQ1N3Pl1Vey54XnmWg7QnT95VSvX8/gqIW9FEzp3aECmHYk+1rH+dHjzzI2OoqhG4z0dPPpV17gr//hT9lx+XoMTVIbEzgrguQETOUFo1MVVFeVU1NXywuPF3PixS9z4ft+9k9dZ94zM1VZcLlwBY4AbrpAoq+XfD6PaZq4rkssFsPv8zE5MkB/+5sXGENRFEVRFEVRFEVRzqfCGYqiKIqiKIqiKMqchrsOvYOtNYQvhJTgLypmanKCiqpqhKYh5w0WeC0vvM9RwALNQvPXEClbSzweYmzwFNUNyxntfINkYmLOPeez0xx+5ZveOCIElHmBh9w0Tr4T3DGgHHz1kD8Ocp72BJYNjgW6CY4N1hCQnd0LiCLQloEz6H2NH+/X7CkW14LBBErAjYM0wHG9OWsCdH1mrBBe5QyBV5VC4oVA8M7Pu6woXsINN93CzpvvIVK1iuloDa0pH909KU62DxCORNi4bQd79wYwBEx276Uw3oJjp+k/sM8LAgiB0IOYsUaKmm6AfJrp/k6czDQTQ0MUV1agBWK42TCnK2+AXcgy2N9LfdNqutqPvOvHejYT27aZmkpQXVNDPp8nHApx6uRJJicnmU4kOLbneZzM4EWPXN6wmaLyBkZHRvGZPlwXYrFSimICzZIc65S4CMJhQTAS5crLwwSCUBqXfOYfP8f//efrSE5N4DN0dt5yK3VLlmDoGuGID1sKLFcynJBsrjMJ+AWdKQNf+WWEaq6D1nGwTnH+/SmobmiirtzEPOtfTwtISf9kga8+2UY6axMMhLh6+w7WbdjIYG8nJ9tOEYuFKdiCgguGBikgDHRPSMYnLOLxOIO9fYyM9VHX1ERlyTryWZvGIjA1zbv9AZ8EYUJJJVSVRVm7ZhtbVto8/OpXcOz5ni0N7+eGxHt2cjNHMFN5RysBNz9z7CnO/hmknfERAsOHlBKnUCAxOcX0+Bi9roNIJpD2GG7uZ1HBQ1EURVEURVEURfl5o8IZiqIoiqIoiqIoyqUnLQrT4+A6FCZa6R8/QW3DQwRKV5MZGMYLOZwd0PBFl1Cz5kaGerrIjXVR3byM7bc+AHqQsooKNm5axT/97ZeQhqC6rnHOcIamG2iajm3lgYD3ln+yICoBG9xpIAIiDtljwPQ8B6CDnQVMMIvBmuStRd5Z7hgIgRfMyHG6+sZiK1pYQAYIz5QYEGDo3mfLwvuVPYi3YJzkdPWMi6nM8fYY/jCr1m2mvmEZrSc7efKpP8AIr+b6B36N9950De0nTvHEYz9k85VXU1dfz8jICL1HXyA/9Aanq53MkCDtFIWJY9jJHmrX3EBp/fvoO3acqb5e9GCQUFU9qa5JkNOc2calq2UvV1x3J92njs1bKeXdkUW4FpOTE3Sc6qAmlyMSjZLP57Etm55TJ7En20BebOUMjWm3hFOnOlizdi2WZZHJZEklJZEw9CYgHBUUhaEiKklMpnn59QM8+/SLaKEKNl1xNaFYCe3H93LZ5VspK5Y01AXwB03yOYFPSLqnIRoUFPlhzJZ0dKd5/Icv0HLoEFjTnHd9ACEE69c1YvpAzgQkzvo+3lXZdWKKZNplZHiU9tZWyuJxmlauYMOWzRj+CKWlUZobIviEdxtH8boImYZA02BybAw3m+X6G29k3aZ1bN28hKXVBlKcrrLhAoaAIh3yCIoNiMUFHRGThbl4z5QOTIJRA8ElkB4GdwDcUTDqwSgFZxLsvpmfD7OBDhfQvNZH+TzYWZyMwVRiGHe6A2QB3NnKOT+7qjWKoiiKoiiKoijKzw8VzlAURVEURVEURVEuMQGiBFcP4bgujRuv59Se19A1jdLGlWQmJiDXjbfcmwBczGgDS7bcztK1W8hkHQyh8b4PfpTffegGJnOQdwTJRJqKunqGejpYsnw1bccOnLfn6oaV+MNxOo7uwQs2TAA5kNUzrwiBVgWyj/mDGeC1UZmpZFFIgXsKb1H2TO5MK47ozLFYeIu2sy0UClxYcmZfMSjkISW8ahOW7bU4sWMgk8AIcy2qvzt86HqAliN7Obrv1Zl/C4C7hF3Pv0DBslm9Zg1CuLz84+9zz6/9FsuWLePEc1+84BxdK0nv4R9SvfI9bHnf+zm6Zy/p5DSRsgrSI+XIdBdeYMVjFzIMDfRQWbuUod5T7+CYZqsiLLY9SgI72UfX0cPoUhKOhBkfG2NiYpKx4WEGDu/GLYy8jXlEyGd1bMsml8uRTKWoqCynuEQQCEA+L6iOS3yFAt/+4QlefGUfr3zvS2QmutDDTZw41k5uso+hlmfpfP3r/Ohfy7nn4c/wsT9+iLJKE01A54hDc6lGDo1kQdLWNoYrJcX1SxkZPwT2XOEMjabaYkxNzDFn767OupBxTMbHxzl29BjH39xNbrCbqhUrWbJ6PU0rV1GyopmaIg0hzq664bqSbDbPFdu2YVx7LRUVFUQiPo63jnPoSJrVKyvZsixMXRBMcXpL/8wHQLF+9phzy+A9e2Fws+jRMhwrDwXphansJFpsOeGazQgrRaq3Gzd7EuTYzFGGwbcEcCE/iTPlgp0E1wHhcLpyzc8yKKQoiqIoiqIoiqL8vFDhDEVRFEVRFEVRFOUSEkAx+Oopq6unuqaG6dFBkEkcK0d9czP9bSdw86dAzrb/CBCs2EzV0lUM9PczOT5FReNq+ocn+cq3d7NiWRXhaDHHT/SwYuVKXNdheXUJz/7gm2fvWWgM93fj2G1ACTA68x0JwgYRAFEFmjtTQWAhM4v4egRvwXe+FiIz77anDpjEC1v48QIbYywuDJAHEmD7wPSBYUAoDJoG2QykMiDPDYa8mwrkM+Pn/asRCBGIxRgeHqamro7m5ct5pa2N9kNv8p7b7+XZSBXZqY4LDy9dBltfJBovZ/uNN3HkyDFAogcj2OnZ831aT+t+mjfsYKi3g4urWCDwAjoCfM1gJ7wKCotqB+OC1Ul+oEC7FIxPTSFdF4FgvL0Fe6qdxYVvzhUF18UwDUzTxGeaFBUFKI4LTANWVkgGeib5n3/1n7z81HNkk20UkmMIIwhyksm+QwhAaAbS0bAsHy++fIh47S4+/pFr6EvoSKA6LhjNQdewxJUGVVVVnLAT4IzOOSt/IEBTQyVhMU8AQkLShu7uPo4fPcbEuFc1JlJTy0hvB6MjExw9cAA0wS1XV2HEfGdtHgsJli6tpr3Nor9/kI6WFqanE0jdoKa2lkzWJjVdzH1Xl+PT59i9gMCCyYzZjWZbJvnBzSDTY4hADOlm0P3rMYNFaMEI8ZISUuMStzANcoLToQsLcMF2vNIfuh+smQo6/kqEfyVyuh3k0Mz+AjPb5Vh88EdRFEVRFEVRFEX5RaXCGYqiKIqiKIqiKMolooMoAaMKhEV6cozhkRGEEcCI1GIXLIxQAENLUXjrneoAkunO3bwxcoxY7UqWbdyCbTu0trSg6zrZnEVlZQZ/wEe8OE5DYx1Vvh58Pj+FwunQQiBUwvrtt+E3XJCSvt5Ouo7vRrqBmQ4hJWj+StzJPYs8Fh/oJlhJFl54TQDFQMFrnyKC4E5wZnuOhc00kRDSC2cA6Jq3OGyaoJngXLhmwLtKSIqryqmsrMAUNsf27eaqa9/DyMgE0h9F4lLeuJGpvt0s6rilTdvuR/CZAa57z70c2L+fEekCofNealtZBrraMP0RrHxyEZMN4S3SR8BXDUJDi9cgcwlkYvKM+V2g+oHMgNuDNSYZTQ3juj7AhlQbMLyIeZxLA7I4EycYaRWsWb2KktJSqirDxALgk5LJ4Sx/97VXefmlN0kMtxAtL8XJT+Dk+3AsmEp3opmlRKo2YmUyWIUCJdW1vPby61x19UaWNsVorhRMSwj6wO8TxGJRpOswcfLNeUM+pqETi/gJcDrecFblCyk53llAEqC2thbLKpBMJhG5DMnJJCVl5QTjxYyOjnGkZYD11Y2ImQoYEsl0xmXPnkM89u3vMdLTQ36sG1kYJd6wlWvvupeysjJOdScYXV9KbdH56QzBQlUzZpuhgBeU8IHwg9RxU8NAEpw8mAbVa3YQicXoPPAimbF2cFJnbDtzz7ia99wVkmCPguwACmBnCDXeQMFvYo3nQZSDK8DtxbundISms+XKnYu7HRRFURRFURRFUZRfOCqcoSiKoiiKoiiKosxDgNBAnrnYrgEhNLOYUHEJuelhHDuLdAogQ14LDmscLEm6fwyfdi3xqJ/C+CGS4800lG/FSXVxdgWEHLi9FJIw1tZBXX0DV+28g9dfe42xsTE0TSOdTrNkyRJsO03r8Q6ia0soLS9nsL9vZgyDbDrLnuefQTMDhAIZdCOIdCXeYq2JUVyCKEzh2pMXOG4NqIRwpddaJBkBx2D+gIbrHQOO1x5B1uJVVVhMlQfD245xb1HY8nu7yaXAHwLHAfdiqkW8O4xwPT4TWl74IrnkKK6r0X7oTZZddi3H9+9l0+a13Hj3ffSfeJ7MROviBpUOJ3Y/xporrmPT5s107X0Nmwyn4wGnJcd7Ecb5wY3zCB9oK8DNIvyl6GU1OK7EzUzB9HEgzekqCX6867bA+ZV5yJ3EzXXgtZ+xefsVEiSQBHuKsZNDkL+TteuaWNdoEBUCn+Pyj4+8yE++/VVSfQfwByyEKMLJj81sr4EoxbUmsfN5dt7/ML3dXcTicSLhMCdPjpLLZtl4fQ0BAf0pi9HxFIX8NOOjY5jRGgqpduYKpWi+EK4ZRErvjAThrDTERBYmsgaxoghjY6N0nTiOa+VJ9u6CgkWibwLMyzAMg5GJFK6E2Q4pWRdODtiMj03hALGyMiYmB7B8laTzNrtfeYXk9DTvvfEGbMR5wZALm20z4vJW8EaOA3FwxoEU6HW4RpzRgT4GDx8il+icCWboaMEa3NwgSBu0CASi4Fog/WCN4oV9DHAc3HSS2tVbmZ5qJjk+gTV8GNwsXgWNIPGSEFdcffVFzV5RFEVRFEVRFEX5xaHCGYqiKIqiKIqiKMqczHAN67ffMV12xgAAIABJREFUzdFdP8B2dISvCH+kEl+knIbmldQ2NZFJJQmHghx+4yX6DjyCt7TrsTN9vPnsY2y/45eJN16NP1yGpusgzfl36uY58uK/UVLZyPoNG+jt6UVKieu6OK7D0cOneO6b/0bPlpXUNjSfEc6IAAWkHsPJdZDMSrwFUz8QAuEjWhwncWoACANTCx+8EUTEipG6BtkYOCYLL8pPA3FOtzbJ4oU8LlCd4a3FfhOYgMzEzPxcKFQABkgXbwF6sZU4Lg3NjCK1OOHiCsoar6R7//eQ1shb35849TR9oSBLVm8lHIuxYcNy9rz8AfY9+fe4dnpR+3AKUzz1tf/Bhz75ZZZtuZIjPzkI9lxhCRdppy48oL8abBMRr0IPBjFDIaRl4YxO4rW6iQNpECbIFN51WozZAM47IZltqaJpJs0rl1NfZ1AbFfiRfP/lFjpaT/B7v/U++vvXMpGSPPXov3FWeETmwGxGi1TgDwZZt2kTN9y0jb7eMayCxRWry9EFtIwW+NLXXubpJ55movXHxMoqadq4jdZMP4VE23kzC0cjBMJhcnhNZYLnzNoWMDo6wN43D9B58hSJng4CEQ0nOw4InHSURNdJQu/dxh3XL0M/I12hAYmpBNJ1SQ6eItF7FNw8GCW4wsVyJZ2dnXR3nULqdRd5Tmd3NNteaPY5mX328t7XEnCmSXXtg8IpTrekcXALCa9vCnGM4iXEGpaTS0yRGXYgPYz3bDsg4jiYpBIJfMEwMt8F1jBQgfezZojyhsuRgZKLPAZFURRFURRFURTlF4UKZyiKoiiKoiiKoihzilatZsv197D2yhs5eOgYgwODaNIlEolQv3w509PTNDUvIz0xxFjnbryF0LPZrktZeTnFNUvRdB+maSLFwoEFx0ry6g/+hds/8ufU1tYyOTlBLBYjFApTWVWFFgjR0z3MZRtXs/f1l2a2yoBWAfYYSAsvlGEDZUAc3R8hEAwyZfpZOOSggaiFUBW+SBjbsnFkas5jO1sOqMarrhCe2UeetypqXJCFF+wALziigfThhQkMIAqML2KcM51fgWJxdNACRKsuI5WG1TtupfvAk0hr9OyXySzD7S9Rv3ITLSc6uenaFfzJ//g4fzLaT+vuR8FdRJgCSI538+Q3v8ztD32S8aEeBg5+22spcrGED2QxGBKhu9jjo0gERiSKG69FOg4inwNTIhP78Bbd/2sEYnFqGuspighMAY4jeeH1Fn7/4Q/w3OvtfPRjd1LIF2iuK+If/u4vSScTeGGDJEKzaVi+mm3bN2LlLa7dGKenIYpRyLO+2mTYghf2DPPc08/Re+Bx3PRJkqOtTAz1UL7sBoaODOPYBe/WkF44xe/TCRgaUy5ENc4uXSElYxNZXnphH9lcnorqKlxnM7nJcdKjCYySSoqKS5keOsWS+gpq4v63WpoA2A7senUfLz77DImuPeCM4LUJ6cMeHKGgO1SsuIF83qF/MEfjspDX0mfRzgxjzP5s8eOFcSy8Z0hDpo7MHNg5ISsnBWiIcANFjeuJxovIFwqIQBhkBTIzAkhwh7BG9jA26CIC5chMAu8eSuE9o3l624/z2NgYX/o/H7+I+SuKoiiKoiiKoii/KFQ4Q1EURVEURVEURZnTpsu2cM3Va1jVVMzIxLWMjo9TXxJiLCn53hO7GR8b48T+XRx85gsUsnMFByTW9AjSdVm3ZTOlpWWMDA8hF6qcMaOQOsWhV57kjoc+wdjYKNlsFum6hCMR/PFyJge7qarfihACKSUQ9NZdndl55PHaEUTAFyNQUYlwXeR0C15li/nEELHVFDcvw/T5SSamyGBx4QoYLhhBsMOg+cCdxqtBoHHxFS9mGzuMe8eFD2+heeoix/LPfC5w4fmfSYCrk+h9FSNYTn9bGSMdrzBX0MPJ9jPasY/Lt1+L48J7NpXz4d/9GF+0AvTv/09wF1dBo/fEc0z0vZdf+q1f5yt/3c9U13Nc9HnTKsB2MYqLsaeGwF+K0HRKysoYB6xEglhlJcnOV5FyoXtA5/SfSxzefhuT+fljS4mXRAiZ3h1yqHuaJ779HRg/zt33341pwDf+47sUlVTywIc+wlf/+W9mt0SQY7LrKFs3VbGxLkrMhJqYTlD4sIHdx8b5/n9+l+HuUxihegrZDLgT5KanKCopY+cnPkdfzxD9HafoPf4MhcwIwWCMqZSBqUPpOd1jbAk9CZ2mZcvo7xsgOT3NiKZh2VnQdYIBnQc+8qu8/NNX2LKhiYB29vYakoHubkpKyyisuo7xzgM4uUlwC+AKkn3dDHR1cc211zI4bVBwwa9fzNk8txGKBpigB8ApAyMMzmyrnfmeA4mmQVFxnFA4gm3Z5FMp7NSpme97bY1kodt7dXoEqMS7V2xmn41sspdssvdiJq8oiqIoiqIoiqL8AtEu/BJFURRFURRFURTlF9HqdWtYv7aCy+p83Lwhzj07m2hYUkGoqJQVK1awpLGRwy98a55gBoDAFy1DNwyWLG2ivrGOaDSMeKulwEJsek48hbQyrN+wnomJCUZGRpBSEojGyBZcNH8xgWAIMBDBWnCGzxnD9D5MP9GyMqaGh8C5UAWMEIZPJ1pURCQaIRiOgBHi7MXfuWiIaBn4YyDTeO+oz+Et3L6dX71tvHfkp/AWgINA8dsYJz7zEcQ7HzoLHUsgWk68ZvPMfn2EKrcw0XsY5PxBif7Wl0hNjpIqCDQBv3bnZu79lV8iXn8laHG8cMnCpJPk8a9+lrrKAA/89ieIVF0xM9fFCoCjIQIBnOlWCJSAL4AZDBAKh/D5/ZQ1NuAjhZvru8BYJlCEt/geXeB1c11XE6/FzsJzDRY3EghoxDTIWJITI4KiupX861e/y73vfx933XYbK1evZt26tbS0Hp/ZTgf/SoRew/W3XM+KqgglpkAXgrDmfTaB7taTvPb0D0l1vkBhdC+440AAKcro6zqFZoT48G//Dvc//Htsu+/TlK2+m5KKGvqnTfLz5FCKS334fBqHDx5g76uvMtpyDDfRC/kesqPHGR4Y4fLt11AcDSPOub+CpuD++9/Ppisup27FevBVQmAFBNegl6wn1rCSvOPS1taCFNZFxIhMvFDEudfBBQrgK4JwLdjdXjsYr1TIPGP5cLUSBBCLxTA0cCdbodAzzzZ5vGc0gPc8hWf+X/2ZTVEURVEURVEURZmf+q1RURRFURRFURRFmVMul0Nq3hKkkJLXTqR49o0pJlPQuLSB4Z4OctP9C4wgkJhYhQJC0ygujrFi9QrWXXMvQg9ecP+F9BR7X3yW1WtWUFJcwsTEBKlkEtPvg1CEVF6joqoGzRdFMIXXwuBMJggTI+wtGGeTC1VLAAiCWU+0up5QKEQoFMLn853VomF+BkY4CpoNMoFXceHtthWZJYE8aCaIIFAFxC5i+zzeAnYpXkAjgreIPH/YRAgd6WqAgeavobh2GYXU0MJ7SQ0z2HmUaNSHI6EqrPEb913BR/77Z1l708eJr7ybcGnzvPuclZoa5ZFvPMFdd13N+3/1E/jiGy64zcys8Vqx2EirF1mYAsvBFw4TL68gHo/TuKSRJUuWkBjsAhFg/usi8M6ZD+9cn3tPnck7T6eFQV8KWgMLBVKM6Aouu/Y91FdGKNIlw2mHvoExrMw0Tk4yPTlJ27F9/M5DD/DBu9/Pay++CMKPHmrCCEa5fPsV/NWnH6ImKEB4s5g9Sy7g97uQacELB6VmPifA7mS6/Yc8+sX/TV/PALYtWbFqGUtWrSdrmWQtCAbOr1ciBIwNT7Bv70F6e3rIZ7O4hokRKsWILGHJlltZvno1lVWV6P5zym7gjZfNpOk4eYrx4UGczATYOTS/n1B5JdUr11FbX0dvTx8jAwMYi+poMvvnLDFzrs+MdARAq8RXXoXunzn2M7835z1lomMTCocxfSZCCNxMH8jZINlcqZUE3jMVAlGCF+RRf2ZTFEVRFEVRFEVR5qfamiiKoiiKoiiKoihzCoUM6mayAOkCpApBqqvDaLogHHbpbtkNMrvACC7CGcT0+YiEw1RVhWhqLuVk+3tpP/gS2dF9F5xDW0s7miZZ2txEf18fyWSSbCaD5vPT1z9O0/JVdHc+BYWpObY2QfPjLypCNzRkthvk2AJ7M9FCUSpqaykqKkIIgWVZjAYj2OmF2pNoQAmuBVhJvIVii9MBgHNrAZgsvOh/pjxowmuZIv1g+8DpwGtxciESb3G+BG9ROjMzF2dmzueHVbLTCbLJBIgV+EKlVFWU0G0vdI29/XS0H+fgoV6WVi8hqgvWVvn57V+6nGA4zJu7DxIw72S46wj7n/8O+elu5j6XNsd3/4QjB27nVz98E12dvbz5wyFkfvAC+/cBBe9eLEwCEcxYlKrmZuobGyktKSUYCtLe1oZkNjwzHwMCy0Av8lIJ6QTI2fN2/ny9iiQObwVpCOOd10q8xfvU2duKECuuvJlfe+gW1laaWJbLV7/1Ev/yL48wceIJZGHordfnszPBChGicuXNBOM1LG1eyl9/6kHqSsPnhYZcKTlwvJtHvvolHCvB3PegQz7VRTrRz9KVG1m/fCVLa8M89vU2fKbE0M++MhLIFCSHjg4TiUS91iY+HxN93dSvv4xAMMDGzZuprCqjUHCorDo/PORK6OkbJlZUxLI16xhsPU5hshc3nSbVk2Igl2b5ZVeyZt06NF+ctAVx/3nDnCMyc27D3jk6SxAtspR4ZSVjI6+ecw7mupdNMOqoWL6RqpoabNtGui7IC1VuyYJWD7KM2NL12KkuMiN7WFygSFEURVEURVEURflFpMIZiqIoiqIoiqIoypxKi3zEdTAFpIWgosoAAYYG/b0TjHS9ydyL1qflp4cpL4vSvLye6qoARTGN1WtWsvqqW9j/xMEF22WAxdTwIcZH+2heVk0mnWZgYIDU2DhWMklnexfXXb4ennl8nu11EBrBSBgrMQSZtgvM1yYYL6KispJoLIZVsMhkMpiRcuyxCmCIuSsueNUpnEwSXAdvkX6+4/J781p0OMP19hmLIUwDnBLkhIBCC5BexPZJr5pHuAZsC6y819pF+vHCBecsVhsmRBtBCsKVVVRVlixwLLMEQz29ZDMZIjOVHBCCxih86NaVNNUXk85r2M57qF66kZaDu0iM9jI52I6dHcMuTOPaXtuJqb7DfOEv/4Evfe2zfODeW2jb9wKTp55k/koXGt651N4KXWihCkqallNZVU11dTV19fWYpsHxvXuwU6k55++FLAToASINa8AXpJDJUugfhfxCbVD8eMGXvDcPJwVaMYhekO7M/GbvOYE/upzf/N1f4pp1pYQFPPpaN//+nz8mOTqKFqrHsTJntOAoIATEa5Zyx6/8NsFIEffdsoKty+NzBjN2HR/hV+7/VbqPv4oXXvDhBRjO5tpZWvbvZvv1O5jOSq7cWMNzJRVIBDkHchpEZ4eX0J8WlJSVUlubw3EcDMOrLJGaHGfthp2sXL0SIUxwJygKn185QgfKK0pZknE5fLiFsqYVjLQkcCwXmRsl2Z+nq6iMrVduZdXqUgoXyjYIPwgdXMML0MhzqlrocSI1dUg7j1tYKIgzO16MyJLLWLVpMxUVFSSmpjD8AYSvFJk9t1XSWWcSdAluEJ8hMWNxMiPz9IVRFEVRFEVRFEVRFFQ4Q1EURVEURVEURZlHcRGkXQhqkoBPUFEGeRsipmT3S71k0+e+Y/18vkCYuvoqqqtDRKMQ8ENpWdEFIh2n5SfbOX7wIL/+0Qfo7AgzNTmJVSiA6zLaP0jF3ZvRdR3HOa8ZAxBAhMJEiuIMHTuJ13ZgYt59iWA9Vc0rKSsvx+fzkc1ksSwbK5cHUQkyDUzPsaUNIuutp0uX8985P9veRAfK8d7pX2DuVgnnCoCmo4eCBGMxNKGRD0cojISQqaMgJy+wvQ3uAFpoCUakEseycFJJSAbBKgB9nBm+8AdDBOobyGRyhCoqKCop91qdyPmumADhZ80V17F5y3KCmnjriHUhWF5i0rSzhgkbhicdtm2+h4np2xkeSzI4PAGuS+uxk+z6yWOc2v8T7EKYof4B/uXrP+Xh37yNptUb2HfqaRYOiMizzmWovJnK6hoqKisoLimhpraGnq5upqaTSF8x2Dpnh3TCgIPwNVK5bifVS5rJ5fP0dXZgYS3cmEbMhDNkAbC8r/0SssN41/tMMVZtuY4H3ruaUg1OjhQ4cDLJuk2beHFkFCnq0GQINzkAQqKFwlQ1reCynXegGX4SU6Msq7vMCyScefQSOiYlz++fpLj5vYyO22SG9+LdY3PNOcrktI3p0+nuylIWtAgHA+RyDtmcTga8XIfwzqwvLCguCTK5d4psNktvxynGTrZTWldD+4kWCpaN3zR56N4rqJ+jY44u4NqrVrJ92zL+TUJVVTWdDY20HDxIIT2NrkkMQ2d4cIRsOkXEXLh1jxaowM2PgRYD99znOYgeayJWXsFkZwu4i3jGZAaZmyZWVERRURG27eC6LogL/8lM+H1gFDHW9jzC0PGu+YXCTIqiKIqiKIqiKMovKhXOUBRFURRFURRFUeYUkNDa57ClXscUEDchZ0JEwvBwEvTQBccIxyqwHT/ZrIvQNUwNSotDNK9YyxF/KU5uAm+hfJ7Ff+lwdP9BIoEHqKkpwrJsnNQ0WsBPNpNhKmmhzRnO0EEL4SsqwvT5sFzB3IvVM8EJESBSv4XaxkZKS0vRdR3TNInGoug+P7bPD/n5lukl6BlEKIxMGXiVNMTZ30cDikGv9ObhpFlcOGMSnASGYRCJRAgGg/iqq0mUlzPeGcYafgGvasN8dMBEZqaJ1TchdI1sOkpm3I87aoGd5MzASjgSZu3mTbS2tBMMhqhpbMYfLieXHJhzdDO8lFDVZsrrl5MvaCQtCJ3RkkII0BGUm1BeYYAEt8okuzxEZ7aSqaSktn45/kgZwdLltL7+JHZ+imTa4lj7CGvWNbPvx8xTOMOYOYfaWy/Q/XFKG9ZRU1tDeUUF69atJhqLcGDffpJjo5Adnzkntre9FgLfUrD6MYuqWL5+I+UVFRQKBUzToD2VINs7CHKuUA6IUDHSMqCQBq0C5Mz/i4hXQcMZ5a3rrAW58eZtVEV8jGXh1RNZMtkCXV1dGKaJJl10GcaSEfL5NFUrrqBx1XomxsZ55ekn+cxnfovyoH7enZVw4PigTVd3H0Vl1azbcTv7Hm/BKcwdRNJ9gm3v2YZAIxIJEfH7EEaYdCpPJmMykHKorzHQZ66fgWR4aJLjx46Sz+fxhcJUrVyFELBi9Wo6OjqpqimnuiGOQMzZ1GNiMst4TlLIF3j5qR9jFQpkElMIw6BmxWqWNjfj8/vZv7+Pnc1rvEfoHA6gmSGErxw3n5wJxJzzc0OUU1S7lGAwyFBmAoww6FWQ72HumyiMCDRQ2biU8ooKwuEwyWQSp1BA2nNf8zNJx0KEAiDiSLsX755U4QxFURRFURRFURRlbiqcoSiKoiiKoiiKoszJtiBZ8NoUaAKKgbSEEJBKZZCFqQuOYQbjZDI5TM2hwq+RcQXLmoNsueJynv7WBtIDz7NwqxGXzpZ9tB/rpqIsji4EbnoASSlS+DlyvBsp51p0DYC/iKKKSux8HteRoEXAPbfNg7etMEspqaqnOF5MrKgIQ9cxTJPi4mJqljXTa+Wxh9rnWN8VQAlQgm6Y2Oh4YYFzl6i9qhkiWorQHdzxExc8d2/NTzj4AgHi8TixWIxgKEQ0FsXQNYYyfdip7pmqHt75On+/Mfh/2bvvILvO887z3/ecc8/NOXXuBtCNDIIUE5iTRCqZVrJpybZs2XKYsWdr7FlrZmp3y7see2Zny96dGcl0lG1ZlixZlpVs2pQYRYpiAEAiEKmBBjrH2zenk97943YjdiMwqGqX76cKjXTPe97z3lDV/f7O82CiGzrpTAYrFmfZ76doWcjlCsgaq8EVgWBwcJBms41lWQxsyJLt6Wfy+BrhDGGS6NvJxnfdzXXXX4eueZgXF4u4eCVEZ0ZhYDAIEV2Aa9C8cTu6rpFIZzhz7DD5bILFxTLSTOMLdWPXL24tshrI0NF8caRbRXo24a7ryHT3093dvdKeJkBxucipkyeRPhMRSCNbNYSZINi1nVAySyKTQxce2a5ehkdGMP1+6rUak+PjWOVlkFE67V8ubkUjMMMJ7JqG55rgj0FzClwbRAz0FLgLZx9tBmPcc+duGi7sG7cYn1yg2WgwMDCI67qUiyVyue04VovS4gJ77nsP42OnmZme4gMffj+feHgPmrg0+iABx7YZO3aY40eOY5fPgFjvPWWgYbJnRze2pRGPQ8wQhGIJisUGhw+1CAVhV3eGiBBIKTk+WqFQaJJMpZiemiIQDOD6DGKRCD29XYydPMnPffweBlP+Nc/oSnhp/yjFmsfOnVv4l69Kludn8fn9eHQqzaTTafr6++kb6KHhdT5jLg6hAAQSm6iXXfRQF27txEVn8qGHe0jk8zRLBZzSOBgBLvv5oncR2XAr199+D/lcDiEEsViMRDrNpD+FZ02xfohKQ3h+hNCQ6HQ+IVtcfcsiRVEURVEURVEU5Z1GhTMURVEURVEURVGUNVkehCPa2S4Kfjp30jsuzEzN4DlXU/lBEgr5yad85HXBvITZBtRrLXq238q0vURj8bXLjlCbeZV/eewZfuZXP4Fjt3HtOSgtgzHE8ddew3UvTkwI0FLoySyZ7i4WT59GVmfBq3Ouxcj5NMzUZmLJFOlMmnA4jN/vx/U8dF0nkUxR7uqhWN2KrB0Ezg94SNBDCCOOEGJl/DUqgQgdol3401k0p06joF3F2gG44FXw6TqxWIxMNksoGCKXy5HJZMjm84wdOURl4iVkc/q8kMYqH+AgrSp4HuFwmHg8jtAEzXqdZqMKzSKwAEja7TatVptcLk+hUMDQJSM7b2Xy+D4u3KQW6MFB7v/Qz3Hvu29nx/Yc8ZAgol8aS1mLEBAVEPVDT4/GUCrBzTtvxa5dh2u3abRdnt97lL0vvQr+AajPXLSmHmB0nmpNEEqN0GrWyG++k76+PnL5PN09eRIJP6fHZrjp5psJh8PMDg4yc/IYzaV57MosWjxJ/9AQkUiE3bt3E43FsCyLWrVKtVqlVrqVyRNxrOVj0Dp20UVE8cU24lLDM1rQXABZpdMPpAm2xvkb9fkN2xkc7OHgjMfBI4sYhsGu67aTzmSIxWPMz80RCoXxPJfewSGEphFPxElnkvzCpz5AJuxbs2FOXIe4v8nh5/6eSM/1+KIRltvrBKe0GDtue4ThkUFOLkMiDuMTkmqtxfJyiVOjo9x4824W6hCJQtuFA8fmqVWrBAIB/IEAbq3Ohk2b2LlrJ7ZlMbJ5kJs3ZwmLtatmeBIyuTyl+ixbtnRx3V13c+i1g9TKJYRu0Gw22L9vH4lEnE2bovhMcd6xkoYDIZ+gJTWC8Q00quNId4FLQxcxwl0b8QeCzJ0+BV4LrMX1X4QEQYbxCY2enh5y+Ty2ba+sewKhRS9z7AojgC8ap11MgdUAGkDgyscpiqIoiqIoiqIo70gqnKEoiqIoiqIoiqKsKWRCNHpuC9QDTKDScCiVmyDcddpNnNNqVIhGDdKRTq2DnAH1GAwMdXHTntvI5TK8/O0idm183TGk1+CHT36Xj3zy48STSYQeQLanwUuwPDmH9C5uIxBABHpI9faRTqfxHIe21aY6DtI6wbn2JgYg8cWHGdx9F/0D/XR1dxONRjFNk2azQTgcJpPNUCgUqOaGsFsFcEY5tyoB8FqIYKSTOEDS2aC9cONY6ILY4CCReIbqwhyQBua44gKuzFMAgWCQdDrdqZ4RDGJZFvmuLsKRCPMDGygvTFMafxWnVcVrtwAB/h4wIwjDpG1ZtNtt0uk0UkrqtTrtUgmvlQZZAto0mg1eP3yYDZuGiUYjzC80ec/HfpYXnvgOrfL4ynw7v7z2Ip7d5Lbrc2STghCCNQpnrEusfDGBvoCgLyCYCwT4v/70B3zt8/8382MvI/UUwkjRiQY1LzraA+nh2iUaZUhv/3G6egfoHxhgeKSfvr4wQtPYff0G2q1NDAwOcnpsjMWdu5iZmqS0MEMi38vGjRuJxmL09HYTjoSRnqRUqlCt1Wi322imn9nTfmpjM+BWVs6dBEyS2QzFQIja7CxUanTCGCFAX6lIsvI6EEEGtt7Ct74/QS6XozvhkQiH0U2d8mKTwuIcJ19/nVxfH7F4HM/zGDt1irvvvp1f+Ni72NLlX6dhCNgSjp4q0qrO0TixD7/fYu0QkkEg3s2//cyniSQjJDyBRFKptigsLXH88Gu8+tJLbN66habVObxQ86g2PMKRCNft3k00GuXY0aNs2NBPu90mGgnzsfc/SE90jT4kF9DYsXMTubTJfQ/cQzgSZXlpidHRURr1OuFwhHbborhk4cvrrCbC2g4cmvHYOaAxOrXI8uwUoVSSyuTFgS4NLTRIqm+QZrOB1SwCl6vs4wMtRyDXz6Zdu+jt6yWZjNJsWjQaDYLBIP5UnkY1BN567U0kmmgQicewQlGk7Vtpf3O5SkCKoiiKoiiKoijKO5kKZyiKoiiKoiiKoihrWp5fJBOWuAgkUJMQAapNi8LsafAaVxhBJ9Gzg/7uAN0hcbalxUBI0Jf34bouG0a2Mrn5Lib2T7L+pqZk5vRhTo9OMDA0hBHKYrfPgHcK6fm5cBNaA7L403309PUSjkTwBwJE43GWenpYPLOR+sIo0imCSIM9QWLwFlLpDLl8nlwuRzQawXU9DMNHPp/HNE3qtRrlYpFKcgRZBJxpOiGMBEgdXzSMazl02hq0LrkCTQi6u7sJxdK4tkPFn4f2Iuu3TFgVQIR6CcZiJBIJUqkUmWyWcDiMlJJardYJZ8zO0WpvpVq5maXFRWbHTlFZWsJMZXClRyAYItfVRSAQREpIplKUS2VKySSNchqaS8ACnuMyMXaKRCpNV1cXlXKTj71/B9+85V60VX+HAAAgAElEQVReeuJxkEuAhT86yM3v+VkeeeQ9bEoJDCHww9WVzbiIAKSAuuXxl998lT//g89Sm/kBaDa6P4lTfo1Lf3yxGhIB6Unc0GaMUJpsNsvI5mH6+qIMDQikFNSbJuWyJJHsYuOmNJWyRb3RxjR1KuUG2WwSn6nT3e3H86DdhnpDx+/3E4/HyXXlQcAiHqVTL4M3B1oKfCmSyTSO5qO5XMQVrFTOaNEJAJ0LSIRSI6R7N1BcmOZffXgLyWDm7FI9uPtGfvKBYf75ib08/sJJZueKNNoWO3eO8GufeBcb0n6MNdqZrK6CJyCeDGGGuqhW2rSWj3BpMENgpm5k1/0f5o4bhmhIgemXnBytsH/vKCdee55j+55FD3ZTLpdBSEDQloKhoX7Gx2ewLYtQKMTg0BCNepWXXniae+/fw0jfDsQ6VTMAhAY+n6RatXl5/wylYplwOMzYqVNkczkMwyAciRBPJDgzUac6FCAU7XzmtAScnq2TyYaZnl3ACESwqqdBXhzIihDMDRNPJpiZmMAtnODy7y0XPZyid/v13LLnVjZu6iaR0Gk2gzQanbmk+wZpzvUim9U11nNl9aUkGAwiDANJHRXMUBRFURRFURRFUS5HhTMURVEURVEURVGUNb344ov8iiexdYFfQl2CX4Bt28ydOkbnW8qLN0lXmaBlKEyexGpUEcSAzna1CfSl/WzdNkytWmf7rQ9QnD1Bde41kNaao7Vrc7x+8BBDW67HH+3CLup02otc3MYjCME+Yt09dHV3k8lmMXSdgcFB2lu2cGZgkKmJ7RSXCzQX55GtCJFUD+FwhGwmQyIZIxg0sNouhqEjNA0hBJFIlHQ2g23bNH1+ZCUHtVMgEuBPYfgCuM3KynpcuikshCAYDBKNxcjk8xSiOex2HzALtNdZQz+IfkQoA0IQCoWJxeNksxnCkSCmKbCsJJlMmmQySaVSoVIuE4/HiURjLMzNUlwqUKtWMaKdahvpTBrTNNE1nUw2S6VSoV0u47aXwCuAXaMxcYCJVAbTZzIVCGC3tvBzv/o/cWbGZf71v0PoaW588Jf4o//+G2ztDqILwTrZgWvSciWxWJTeTSMcn3kSTfOj+6K4TbGyRhprbn6LNEJLE4lGyGaz9HRH6M4J4kankkfSgJ6owJI6bVen1vRTb0RxHGg2YzSbgmxGozcHdUtgOxLHiWJZA4iV585zXVxnM/XFReySD4QkMbyTZL6LUqOJp2ugB8FxOL+VSYfB9j3v430ffIA7b0iQDOpo5y2YT4eR3gQjn3yAn/3o3Tz5wjEOjC1y9/3XM5T2o19pcSXkc2mS6SiNlsQzU0hr5vwFAiCaSPArn3qY3lyEOSmZnG2z75UjmIaLvXyESmmZUM+9lEvls62ChCHQdJfFhQXq9Tq2beN5HvWGJBKN8JH330DWf/n5CcDQQNMMdENy6NAREokE0WgMz3Pp6e2lf2CARCKB6zmUHcjLzjtpyYXp2QJCrzE3X8Pwu1QX1qiy48uT6OlDCEFlfAxpCTpRsPUCGh7C0EnnsmzYMEBPr040IqjWJKViCNP0Y1WXka0lOp9zFz+nK1cmQdN1hC5AXimspiiKoiiKoiiKorzTqXCGoiiKoiiKoiiKsqajRw7TrtfxolE8CUstCAag3vZW7iO/3KasB14Rq3oCy7YvfKSA4Yyfjz68jVbL5eWNffT29fPMP/0D44efwqmOg2xeNFyNw6/8kFvuvp9wIkttwqSz8XrRHe0ihi/dQ66ri1w+TygUIplIEAqHO20YYjF6+/pYWlpieXGRRqtFMpUik83Q3ZMjnTbQdEENaNQblMtl2m0LiSQQCGKaJg3HBjMKRg84TQiE0MMRqNXpBAgu5TotZLuIz9dPPBEnlO+n3LKgtsT64QwJ6EjHRRMCv98kGouSSAZJJDTCYYHnCer1GIYhKBTCxGIxwpEI2XyexqaNLBcKLC4sUKvXMYxO6wmf4SMYCiKRlMtlqpUylWoeqtNABdk4yvzRGJZtM3HmNNu39fKx9+7gufc/xFfH9rL7znfzn//3X2JbT/DKwYFrkA7ofPJ9m6nUfob/euoFqgsnsSpjoEXAs+ls11+8Aa6DjGH4TWKr1UXSOr0RQRgwBat76DiArYHtE7SiICUY6CzVIBIQhAwIGlB3BOGIhmkaZHM5fKaJ67q02xZLmV5sz4dm6PQMDBIORzAMA8Pvx9ZNcC5tJxJMbuKu936EG3en2ZwSiDXWrNPiRZCKmHzsPbv4yMp8jXWbmZxjCOjNmWy9/ibGT3wZPdSNY3UqnHRoaOYAO268gx+/ZxgpBJWK5OiRIlNTM7z/tjxf9NqAi1UvUKtVcT2Ji+T0XJ1DB0aZnp6m1WoRCASIxaK0Wg22DXdx69Yc2mWqZrCyGo7r0WjUyecTDAz0UyqVicaiVCtVpJRY7c57YGQkjW6Is2vSssC2PZ5+8gALM9PUZ/eDvDhwYaBHe0mk0tTKZdq1xspZ1wqOdX4MJowIXZvexe7rr2d4JEMu2QnJgMBnCmrVCuWpQyufQ1FgeY2xTKT0gwTh1oHqFZ4pRVEURVEURVEU5Z1OhTMURVEURVEURVGUNU1PTzE9OU1s21bqDszMesS6BcdOztK2K6zVvuMsEQJZB6ET0iQ+zkU5BBDUBRtiUIsaaLfkCQZDDG7YyBOPX8fep/6RxvQPwCueN6Bk8ujzBEyNbG8f84cDa7dVMRJE0hm6e3rOhjLyXXmikQjtdptwOEw6naaru5tqpUKz2cQ0TVKpFH39SeLxThWIRl2i6TqG0fm22Wq38fv9JNMp7HaLemEZYnmwGggPfKaJFKLTDmKNDgjSc5kb/SEDW2/B7/fTPThIqzRLuybpfGu+1h3+NmgO4VyedCZDNBolnY6TSmtk0oJQoNMupdmWmGaUWDxEvdaip6eber1Os9mk2WxRrVSYmJjAcRyi0Siu4yKlJBqN0dXVRblcolnKYdcz4NUAC6e4j6VjNgVfkhdf2MqH3r2dO24dYXbx1/hPn/kpbt+avKD6w5slVr4EdYhGIwzf9jFO7f0ujdISUho4lSOgxcBrcWH1DB2ExB+Jkk5nSGeSRIM6McB30fR0OpVfzp2w84d0vPNXj5X6CHonhBQOBXBsj3a7xdDQELZtU16cp91s0LdtB9FEglA4RDAYJBAMYou1gjkaG3Y/wI03b6U3KfBdRdhCCIFGp8IMdF5O67YMoRPOGIkJHnnkIzz7+Is0SzMr7z+P1QDT5j3v56Mff4RIwGCyKTkz7XDk8FHsZpnXfvgalUqlcy6rRrvVwvMkbUfy8r5xTo6exLYdbMui3W7T1ZXH81x+41P3ETOu4nqA7t4s4YRE1yT5fA7HcYnFY1jtNqVSmbFTYzRbLXbt6iIbOnesbUGrZfP9f/4uPvs0nr1WACJMINGF6TcpFosI00a2plm7FYmDMHoZvOlhbnv3B9i5aysbBkwShsAAPBOiUR/9g4Ok+3cyvTwK3nrVN1yEGcaT3spar3U+RVEURVEURVEURTlHhTMURVEURVEURVGUNTXqdY4ePsxtW7YwuQiTkxW6gkGmJseozR+6wtERoI7VKDAxOYe8ecMFm7iSTlMSn4DNSYEzEqFYrLHzul0UlwsctyyshRdA1s4eU5g7TWlxip7+AQ5rwTU6XOiIQIpEJk13dzfJVIqu7jzJZJhwWCCln3glRL3exrZsbNuhVCrheZJkMkYuZxIKg2OD63pomkY4FKLVbCI0DQSYpkkinUE3TVqNJo4TQ5bLCEB6q5u0a1uaOoTbKhHL9JPJZJkJxmgbQ+AsAIuXXAsYaKZL39Ag23fsoLevj2QiQCIuSIUgJMAH2EFBpAeSCZ1aPUy5DNVqhFqthdW2aWcyxGIxyuUyrVaLcrmMWGlFks6kyZfyVMtllgvdUJ+mU8mjgay+hjR3cebkGKcmG/zEe3Zz+83b2NUffkuDGecTArYPd3HfA/fQPzDA/r17KYwdxql4K2GcCFA57wgb4fORyuVJZzN09yTpjnFBGGg9q1vp+srvGp0fkggBpQj0D/jxLxg0m00sy6a/v596rUa9bROOREml0/j9foLBIKFwmKrmp3Pmc5VQNDPBthvvJp8LEdfFlSf1Bgg6FTZuuX0nI7t2c/CZ10FW6bxB/IAgm/Dx0B0bma5KXni9xWv79vPtP/9f+dBPfJxv/+2Xzo7lWmWKS0u0mi7zRZfxySWmZ2bI5XJEYzFisTggGRrqYrgvwdX0s3E8WCrUqTddPE/Q3ZOlp6+HxYVFxs9MkkwlKSwVMAyD6ekqziY/BMCWUK5JisslZk6+SHPp9bVPYGSIZvMYPh+e1YLmSTpVQ8TK9bc5PzgRzvYztP0G4vE42VyUREAQE53n3tLAcx2QktzgZmYORZHe7DpXZqBH49i2A4EYCN+6bZkURVEURVEURVEUBVQ4Q1EURVEURVEURVmHlB77XtnLnoc/yviZBi+/+Cobuq6nXFxCuuu14oBOH4ki4OK5FosLBS6+/1+js83eBnwIhvIa5j3dTIxkCYeDxOJxjr4UZfnkY2dbnDjtKq+9/CK9/cNovugaN7Tr6P4wqVSaTCZDLpcjm42QzUE00jl3vW7gOAaWBY4DzUYCy4Z4XJBJC/wGlOvg2A7VarVTWcPvJxAIUKtW0XWdaCyKpmvouk693kDLZBCajnRd1m6lwMr865w5/Cx73v/LJJMJYt0DtF1Be+I5cP1AiE7bDhv0bvB00kO3sXP3bnr7+ojHY5h+gemDiICoOPdNfVSHUFRQCUE4DLWaRq0Wolz2aDYCOI4NQiCLxU6rl2QSy7axbZvevj6WC8uUglG8un7ejFtgnWR2bJSxqWUevD7O9VHzbQkYrNIR3Ls1ynDvTTz+QpJAQHAyl2X/Y9PI5iSXhjM0jEQP4XiMRDxOImYSN64uBLHWQ1abYTRagoAfhoZ0AoE0kxMGQggy2Rz57i58PpPh4WFqtRqhcBjTNEEaQHilekpnkz6cHmLL9i0MdOkrMYmrc61LLIBcyOCG2+9gbn6BpdGncFuLK/PpYqCni6GMzncP13jlxQN89bO/hV2boro0ztTkmXMDeVXKS/PYbYejS1UmxidpNZt0dXWhGwbzc3PMzjbYvmUPAePqZmk7UK06aEaAmZkZ6vUaAoHP9JHJZNB0Hcd20HWdpaUKi40UKb9O05MsLVtMT07SLE3jWGtVzTDQQt1kcnl8hkFl8hjSboIWBN+mTrWV1iTIAp1KPxrRdC+ZbJZsNk1fj5+U3olwAMQF4EmazSZzU1NIt85KPZU1Tt0PRhjDZxBMpKjO+cBV4QxFURRFURRFURRlfSqcoSiKoiiKoiiKoqzr1Vf306g7lMsNDr52kNv2bGVi0QbNXGkxsRYJdAIVaH6Sydilm80CwrKzKWoAKU3gSwiiIR/h0A5i8U6riOeKi1hLz9OpAuDx1D/8FT/1m39EKNFFrXnsokENArEk+a482VyWdCZMJgPZpCC2kilohQSOB64HngTP83XaXfg6AQcBtE1otVs0Gw1arRZSSkLBED7TxO96OI5NMBCk1WohkMSSSaQEHIvOHfvrV88Yf/1Zbn3o50imUuS7u3BaTeYm4qAnIZCGxrHO8pk9BBJZRDCOaZqEwyHSmTDRKMT8EKVTo2FlKfELSAEBHSJRqIcElTAEgxpS+hkc6qbdzlOtuFSqDu2WTblUolatEgwGSaaSBJNZ6qUEOOe3iylTLUwxdnqasrWBQPBtzWYgRCegMRCFX3xoEw/dsZHP/8MRijNnOHP0AAKBW5rm7BqLNCKYJRQKEY/HyKd19Dc5QRPYlgRHQB1BNuGnvy/H5FQaq91icXGBQCBAd08PExMThIJBpCfBbQMuQg8hHRuQ5HoH2LxlgKgJ2tu6cBDzQT6h40qd1Nb3Uzr5MnatQCCT5cMffT/ltuSHr4zyzb/+Q5bGX2H3ngd44Zl/Qsrz2nFIm0atCNLhlYNjLC4uks/nObBvL61mEw8NXcCmoQ+iX0WLFoC55RattoPbrFKtVllcWMDn87GwsICh62zfuZOt27Zx5vRp5ufmmSoMMpKU1GyYnS1x+sRRnNbyOqPHCGb6yeXzLJw5Tru4SP/OB8lu3EXDgkqpRGV5Ezht2uVZzECEd937IfoHBtiyrZ+hjMZqFxVBJzSWTgUYGBygb2iI+YMBvPXyFkYQKQThUBjXalFFX+eBiqIoiqIoiqIoitKhwhmKoiiKoiiKoijKukZPHKNeKjIzNc2ZI4eZX3gfxeXqSpWAK9N8Ycbnm9RsSdQ8t5UrACk6UQadTlDCkmC5Atcz6O7pZWBoiET/FhaW94PXaW8yc/ogc+NHSXf1UJsVnN+uACNEureffFcXmUyKeFwjnRKkzJU74oG26JzX08/V8tAAfaVFiCXB1AEk5UoF13HwPA/HdYhFYzQbDTzPw2f6SCQSSM/D8Plw7E4rhCupleaYOvYi22/7MXp6eqiVyyxlNmIEw9jVAp4VRI9vJtrdjxkM0Swu4/P5SKVSxGIa2ZQgqXfawVy8Me6jc51hIKZDIgZuRIAGLjotT6faMlhc8jM706makcvnqZTLbNy0iWazyanq6zTnZs4b1cNtL3F6bILZqks+YLy96YxVAjQEXWH4sQe3MTH+QSaPH8OfzFAr+zvVVLQYiB50TScWj5NMxYiFxdkqCG/wtPhE55cEgkBTE5gx8G3QqVZGiCcSlMsVEokoS0tBhKbRatTBLQENpOOw+rrMZrNEo2H8VxlkuFaSznun7UleGasxPrlAo7SE9CfIbruLpbETbNy5nTtvHGZ0psmhA8eYO/lDNF0H3WTi9ImLRvRolJdoOS5nphYAOH30dXq74nziUw/TP9BDMijYvSV91XOMhX3gNkBqaE6FjT0hUokQ/fdsZO8rhzl6aD9mIEo2nyeVTjExVcLamGauJDl1apyJo6+stLS5mAB/N5n+AeKJOK/PL7Hnx3+G6/fcgT8QwLYsPM+jWCwyPTXF3NwcmUyWG2+5lWg0QiYdIGZ02vusfpLYElq2xDRNsl1d+OP9NBfnVld65bwm4AOniq5pRKIRGpUl1dJEURRFURRFURRFuSIVzlAURVEURVEURVHWtbS4yPEjo7zwxBNU5k/jei7t5jLItTZLL+W2Cnz1zx7l5z9yOzv6oxdsUAs6lTNcOpUfAkDTAsuSTE7M49g2wUgCRBzohDM8t82hFx8nksxwbku1I5DoondwiFwuRzQWIBYTxFeCGasb9n464YzzrYY0VjfmYzqkkhG6urqwLYtqtYbP1yadThOLx5ibnaVcLiOEIJvL02w2OoNoOlzp7nkpOfzit7npvo/S29fH4sIi3Vu3EwwEmTr2Ohtu+hmi6RyLiwvouk44FiORTOLzCRIJCJusWRni/H8yAGMlpIG+WnME2hqEQwItI/FcHwF/Ck0TlKJR6vU6rVaLwmiK5tyFY3vtWSbHTjE6XmZHNoX5NqYzLo63mJpgIK5x003beXxgM8uFAgSGoXkYcMHQMcNhAoEA8USIsK9ToeLNzPD8Y0066y0kOH7Bxk0hItEBCoUW4ZCGz+ej1WzSKBbAXeLiFhi5fJqejEFUexMTugJbwpmSxxf/7gccPDaNEQjjj8fp2zTMpu07uGPPduKxADOjJaZPH8dtzpPtHWb69DGkd3GVF0m7XmC5ZmGYYQSSz/zHT/PgnSN0Rw38YiVkcg1rnIvq/OoHN4EAQ9uATz8XVPnY3cPMFxs8+sXv8dgzz/LQj32IRsPGcmF2qc3YyTEqc0e49JUBECSQ2UTfwAA+n4/bHnwfm7dsIZ1JE4mECQT8SM/DcRxmZ+c5euQo+a4cN9+yEb8p6MsJQhddhA14niQW83Pn3XdgGhpPfvMrWK0m0prDrs4h7RoQAtdZOU8Aq7bM+iU2FEVRFEVRFEVRFKVDhTMURVEURVEURVGUdVntFk8++QxHXvwm0gnheRbYy1yudccFpEO1ME6x3gIZvWBHV3DhN6VhIGKCEBqOY3Hi2DFmj7+2UpHgnNEDz7Dljp/thCHO21zWsenp6SGTTRMOa0TDEBYXtv8432q0Q5z3dw0ICUil/OzYsZVWy+b48eO0mk2EprFt+3b6+vtZXl5mdnqaYrGIrmtU3EqnJ8dVbFnPj7/O3PgRuoZ20d3TTTAUZHJiAjOZYWjLNkzTpNVqEg6HSSQSdHXl6OmNko5BDM62YVjPxTPQVn4ZKyEVERT4eqEc1/GZacxZP81Gk1azybF4jNmLB3RKnDn4NM//4D5u33oHvZFOtYG3gyeh4HbCEEmjE4zIBgVbNqS45Z47WZxb4NBrAWonJzuvC2+SgP8mEokEuVwIn/HWTWx1JB0ICDA1yKYEjgN+fxDXdXEdl+XlZVrL80DlkjHicZPhrIbB21NwZLWlzdaUxm/99E38fvkM3yuXCCXTZLJZcrkc9995HQgoFKtMHfkBQjiE4jkmjj635phWs8xCoYnP9PHv/s1HePi2QQIriZc3cg1CCML+tY8UArpSYf63X3+YzZsH+et/+AEPf/jHaDswMVlk7OhBnMbMmsdi5Ej0DtHT20v/wADxeJxUKkkqHSEa1fEHwFjJSg0Mhtmxs5t41GDLgEbCEATovCcuCDYJ2NmnMdKXYaqQIRD0Y7sS27ZpNpvUyiUmRw9QPPUyrhPDDATRdZ3K/Cmu+jNRURRFURRFURRFecdS4QxFURRFURRFURTlsp74x69TXjiFCG6lUmmwPL94Tcc7tkW5doW7ymVnEzxiSOr1FmMnxzj60tPYhf1A/YKHNsqzNGsFDF8Yp30uuGG3W7iuQyQcJBqFiL8TRtDgkooda/15lQnk0mDZQYrFAIHAdhYWijQaDUKhUOdO+XabeCKBafpZXFykUa+vVM5YuZjLcB2Lfc98jY/+q5vJ5nKYpkmj3sDQdAKBAJqmMTwyQm9fD3193WzZmmewXyNtCKLi0uu5kouramQEhEwIJARSguNEqFb9eN4g8Xh8jREklakX+eev/Q0337CBR+7qxbdSQWH1St+q4IEHzNRA6uCLQHxl7NtHIrxy01Z+/z8+ysC2O5ip9lKaKYG9wNKRx5nZcR2eJ2nZEmm+9eGR1diNrkMyKdANWJh3KZfLLM3N4dWm6TTpuVBX2CP5diUzVucmQCDYPJjmD//zL/EvPxzlv3zuOywXCmzevIltg1FaDux9aR+FyVeJJPuoLk8hPXfN8axGmXajxgcf2s2DO5IY4u0L46zO32dofOK91yOloOnzaNgeJ09OMH1iH8jWGkf58SVH6BkYoK+vj+7ublKpGOlMgFgMwhFBOAhBvfMZYAgdjQj+lYoyq9dz8WVFBERMgS3ByEqqWzKUSzfjeR5CaJSKRRZ37uLIgR0c2/8qQnRKojj1i8rNKIqiKIqiKIqiKMoaVDhDURRFURRFURRFuay50wdBeuh6mcX5Zcql5WsbwAhzcnwZ78Ye9Iu3QyXMtiW2hGIDZhYsaDW5++Y+bt78a0wv/Tzf+Ju/ZOLYS7hWGem2Qbosz55BakHgXDhDaAb+QJBQ2CQSgYDWaVNyLQSdu+dTfoGTA79fkE6HyXeFqJRd6nWHYrGIlBLHcdANnWg0SqGwhNAEEueqznPi1adYmh0nFIzSaDTQNI2e/j62bdtGb383uVyYVEonHYdUEMKaIMS1BzPWuj5NQITOYF6iEztYWjJYnq/RKC+sfaBsceqlL/J7/75I8g9+hy0bexG6n0TcR3qdqghvhAEMx8GRK3Oks5Ee0GHPdT088PCHObz3GRrLZ1b+148W2kAgHKFe16i1QZpv2XQ651+ZV0B0KntIP9RqklKxydzcHMXJM+AusFYo56tf+hvSiTQ//fGfpLe3G/E2phyEEJiGzgfv3EK71eZ3P/sd+vvSpEIah08XePpbX8azi/gC/ZRmX193HLtVot1ucN2Wtz+YcXbugKYJfvKh3fxwrMnsUpN9L71MZfa1tQ/Qc6QGNzM0tIHunm5y+SS5nI9kUhAJQcQHUdEJW+isXTVnrTms8gnI64J2r0Fj1xDtlgQ0HGeQmZl54okEuhlgubCM3WriWvU1RlQURVEURVEURVGUC6lwhqIoiqIoiqIoinJ5snOHvdteZHF2/irCGRoIHSFA90XI9G2j0bSR5/cQOY8uodSCbACGBn1EtiTRRRIJFC0Y3nkTJ0fPUCkt8+w/fpXRl79OeWEc6Vy4GS49cB2HYFAn4BedO+bfwOVqQBIQQfD7oOUKHFvgDwh8yzqlksDw+fD7/TQaDXRDx3M9pGUBzas6R7NWZN8zf88tD/0CnuvSajW59bZb2bJtE9msQTotSIUho3farKzW5Hgr9slXK15EkFiuzf7jB/jrP/krnnvsHygX5tc9TrpNjr/093z6lxrc8uBPc8999/Lee7pI+t98aOT8yYVXfheAlBLLcdi7dx9/9N8+x2P/9G0a9eq5x+vdJAe3Mbx5M+mUSTYk0N7iMMHqyzZMp7JH1YFmE6anlzhzaozm0hmgtuaxE+Nn+I///jf5oz/8H/zcL3yKT/7MJ9kw1I+maW/tJM+jCcGHH7iODUM96NE407MlPvOZ/8rpA4+hm2Ea1QU8b/0QkXRbLBdatC06ZWR+RARg6jDSH+TFfdOcfO0FpFVY45EGvsQIfRs20j/QTyabJN/lI5OCdKQTygiLc1N/Q61Y6AQ0eoMCd6uPaqvznFdrEqHlaTabbNm2jZnpaVqNBkLzXaFejqIoiqIoiqIoiqKocIaiKIqiKIqiKIpytdwaSzNncNrrBBC0IMHkZjbuvof7H7yHTX1R+nvz+CMZ+vvSa26aCwG5gCAXYGUXVZzdTBVAwoR79/Ry/e5eeuLw0EO38h9+XWPy+F6ELsA+N5bdmGf6zAlc9z1owo+Pc+0orsXqxmwc0AyoG+CY4HkC2+rc4W/6fMTicSzLotVqYez9zBwAACAASURBVNsW0rHobN9fncMv/iO77/4JKuUKGzZsYPfunaRSBtmsIBOGtOgEM1bn9FaRUlKuVPnuk8/w+T//PM99/2ma5wceLn80i+OvcuzIDQxvHsbT8zSkIHKVE7xSG5TVf5dS0rIsXnhxL48++lkef+yfqNXWCECIMj53AR0Lv99D19/IM37l+Uo6P0BxgFoDKhWHifEppk+eQLZngLVbhKxey/j4aX7nt3+bP/3jP+WRR36KX/nlX2Tz5s3o+tsT0tA1wQ3DGcYWWvzG//KHPPutR8FrEEkPUy2MX/5g6VIu13CsddJUbyOBIOCHsdklijOvs9b7SZi95DfvZtPwMH0DfeTzfpJJQfK898xb8SoQdKqlDJpQNaEUBp9PYLV9JFNJEskkIJifnULTnWt45yuKoiiKoiiKoijvVCqcoSiKoiiKoiiKolwlh4WZk0j34nCGhhEeYNudj/Dgwz/O/XdtZc+WBAnfuaCFx2U25Ff+Y607zzUBm6KCUgiSOrz3hhzWH/yffPlvH+f5b/0JpanZs4+Vbo2DT/0l+++9m8G+G+nO+d7U1ZpATHSqQliAG4KiD/wBP4bPwFypnlGr1fA8b+VCrv7++crSFKcOPU8wu5Ubb76JaMxPLC6IhSD1FgczpAQpPSanZ/n7r3+Dv/7CX3Hk8EEcx77ywRfxGnMUTu+jWLibqXlJ1ISwyVW1v7hSOENKSavV4umnv8//+NyjfP/ZJ2k2LtMywikyfeDrfP7/eI6Dz9zHTz7yUT5479105zNoQrwlbUSaKxMXgCWh2ZTMzlY5OTpKeeY0yNIVRjh7dczNTvHf/9vv86W/+QIf/tgj/NKnf5Hrd+/E0PW3rOWJpNN+5UTJ5fc+9y888Y3Pg9fADMbRNA3PvfxzLj2HUmGRtsO5siE/IhIoNCQnR2ewarPrPKiCqJ9EWNcRj0BXXpKOSFJCvGXBjPP5BfgAQwc7ApUQxGNRuru70YTg1JF9OK2rfQ0oiqIoiqIoiqIo72QqnKEoiqIoiqIoiqJcJcnC6VHkeR0RDH+C3ff9PA8+/DD333M9129MrLS5EBds1uuXDnaJNTdUpUS4LqJcYf/pcQ4cOsRzP3iRg8+9SHX+6CUPbzWanB6b4fjoFnpSSWK+N97WQNLZlI0AdQF+AwIB8FyPdrtTMUPTNDQhkFJ2kiS0r/ocUnq89v2v88Ff/n26e7rw+yEYgKDW2RBencebIaXEth0OHHqdL3zhr/nGN77O7PRkZ75vmEfx9F6mxk6xXLiHckbDMwVXUwPicqGMaq3O9554mkcf/Sw/eO77tNtXu5aSWmmep7/1FZ79ztf43d5+7r3/AT720Y9w+55byaSTb7iNyOoq1YC6Aw6SpaU2kxOznD5xHLc6wbU856uWlhb5sz/+HF/58hf5wAc+wK/9+r/h5pvehenzrRnSkLITcNK4uhBMS0peOjjL89/7Z9q1KQAyvSMsTh658sHSpVJawhXyR53NwAUWKx4njx5BOpW1p2cXmTz4Hb525F946m972X3zzdx33708cMdtbBnZRCwaAaFd1TpdyeoQGhAREPdBNQ71uh/byWJZFk5jEbxrDzkpiqIoiqIoiqIo7zwqnKEoiqIoiqIoiqJcNau1jC8Y6fxFmOy+/xf5nT/4be7aHCGidW5bf6N7olJKpJTUG01mZmd5/fWj7Nu3n337XuHY0aPMz83Sarc6O9XrELiUZw6zOJGinB8kkk4QiUTwGecqE1xthYLVR/mAAFD2IBCEeCJAOBymXqsRCATQdL2z+S8bdGpsXL3FySM0i1MEAj5MU2D6Oue6mjDL5UgpqVRqPPXMs3z+83/Bs888Sa269mb3GxrfrTJ29BAnTpyht2sjTtxA58rP/cX/35lnhW996zt87tE/5tX9r+DY17aG5/M8l+nJM3zpC5/nK1/6Av0DQ7z73Q/yoQ/9OHtuvYVkMo64KDh0pfmu1l8pNmF2zmXvy6OcHD3FwulR8IpveK4A1UqZr/ztl/n2t7/Nvfe9m1//17/KvffeTSAQuOB1agM1CckrzHu1asaZosfe/eMUzrwM0iEQiqNrYLcbVzErl0pxiXbL5c2/Eq9NS8LcQo1Th18BefnAg+fYLM6c4YlvneGJb32N/xQMMTC4gZtv2cO9997DnltvZmhwgHAoCNfwnK9F0PkBWlRAIipoJCTtdpDlQoja0uk3PrCiKIqiKIqiKIryjqLCGYqiKIqiKIqiKMpVc9sLmPHrAJ3ube/jI5/8JLcOd4IZ17L5KQGkxLJslgrLjJ48yf79r7J37yscPHCQqakJqpUKnude0/zs+hTf+9Jv8/TfmfxuOEIikaCnp4e+gSH6+/oY2bSRoY0byWVz5HNpEokEftPEMDqb0OsFNwzAsqFSASF0YrEYlmXRqNeRnodt22AV4BramgB4rsWxlx/j/R/7BIahYWjg5421ZlgNt0xOz/L1r3+DL37xCxw+dADHfjvu6m9TmDzG4sIic4t91Pp0/PrVz1hKyVKhyNe/8W3+7E/+kAOvvYrrXttzfSWu43Bm7CR//qcn+au//DOGNgzzngcf4iMf/hA33XgD8Vj0skGd1WfSAuoe2LZkYaHNsWMneOXJ79CceRK4mrDDlTXqNR77x2/y5Pf+mTvuuodf+dV/zXvfcz/RaAQhBJ7sBAMu96KQQFPCXFvy4qESLz3zXeqLxwHI929jfvLSSjPrjTQz+grf/97j2CNJQtEU2VQUXRMEwzFCAR8IgWH4MPQLK5K82dYstpRMTCywPHO1cz2n1Wxw4tjrnDj2Ol/+4l8QiUTZOLyFPbfdxr333sNN77qBvt4e/H7zDc8zJCBmQCUiKJU0DF2wPDv6hsZSFEVRFEVRFEVR3nnEmytlqiiKoiiKoiiKovz/lRDikm8YNd1Hsu9GGsVJbnroU/z0x++hJygRngues9YwCKETCAXx6RrNVgvbsiiWq7z88ivs37+fsVOjFJaWsN9ExYT1+Ew/CIHdbp39N13XMc0A4UiEXC5HV08fvT29bB4ZYXhkhEjIv/JIyeoWvQss2DAx5zI9VabVauE4DpZlMTk5yYnDh6lNvACyds1zDMfSfOoz/w89/WnSSZ28qRMyDKSUOI6D57ogvQvmsxbX83jqmef5+te+ysybbl1yZcLXxU0P/TR33HUru0aCZK+hhczx4yf5/F99geNHX8dzf7QtIUzTz6aRzXzgAx/kztv3oJ8NGGig6Suv487aOUATWLZgatpjerrA8aPHOPTCEzSXXuVawzhXyzB83PCud/HpT/8iPd3dIASabnbWSnprHiOBJRdmS5IfPn+M737lUazaGTTNoGvDdmZOHbymOWiajqYJDDNIMGCiCUE0kSYeCSA0g3S+h3Q8hCY08r0byKXCGGaQwcEhwkHflU+whpoDf/f4Eb79F7+Ha11rpReNTukegabreJ53tsqOpuuk0hm2bt3O7bffya23vAvTWH3exeoFdx4v1/4cg84aN4DFNiwVYGx0kq989n++pCKJlPJH2Q1GURRFURRFURRF+f8IFc5QFEVRFEVRFEVR1rRWOGPXbR/g3Y/8O6anZnnhmWf45E/cx2zJ4pnnXmbu6FO0iyeRZ4MEHYY/xV0f/Q1+4sP3kwzYnDj4Ei/98AccPHCA+blZLKv9ls891bWJ8tI08XQO3TBYnB5b41EGne33EBAFEUWEMgifia4JNFNHiAZ2dQavVQC3CchLt+Pl2S9vmBA+tOQt5Id3sm3HDnZfv5N4LMxzz72Eaei88NiXqBYm8Fozlz2XFD5CyUFMUadUmL1sC5g3T4DQMANhdF8Iq9XEF0xiVWeR8vJBm1AkjmZGqBUXkd5b9fyv7oevdc0rG/dcWJ3jXAUFAyOyldz229C9Fq3aIs3KEo2lU3jWudYl8sIvbxuhGfhCKaQWxvP8hLODbNx5C1NHfkhh7Kkrnl/+COa4njdbPeONzT0Koh8RzZDbNIzmuSycPoEeT2OGo3ieR19/H5FIFIlk4sQo9cICtm0hPYGGQ3p4K65jU184gVsdw2ksI+Xlq7msVgC69BpUOENRFEVRFEVRFEW5lGproiiKoiiKoiiKoly1O9/9XrZddwM9g5uIJrOku4IcHztAvmeYPfc8wIlXnuXAc4/hWCWE0PBHkwQT/VStIPtOWuzaOcKn/u1d/Iff+k2Wi0WOHz/Biy++xPPP/4CDB15j9v9l786DJDnP+85/37yz7qOr+pzunqtnBnPhIm4CoESQIqUlRYqWRFPXKiyZinV4N3ZlyRHrS16HbEv2hqy1LcmyddgSRd0iRfEQBBIEQeIgLmIw92Bmeqbvo7ruysrr3T+yei70TA8kynKY7ycCAXR1Zeabb2Z1BOr95fMszuNfU+XiLyuOI+I4orZc42rrCcGVRV+RAmsCwkWI2snrMo008uilMtliiWwuS+AHeF6X+vxF4tWTEM2TNLr45koNH2T44GPs2r2Hg4cO8ejDM+yeznL00E56gcGpV1+i2eghDR2C2ZvvSProRpaf+le/Suvis/zGf/4VFucvf5NHqwEOCA1hDVM59G6ibpPVc88SyAIxK9uGQjqtOlC/4dVkn8gkBPN2zRx8hDdPv0IUdgavmCRhjBiwwZiAcBVoDl5jUF1EAHlimQI9jenmsArT9C5dJF5fQ8ra2x7LX5XuVBna/0FqS6sE60t0NnzansAL5CD89D+uv5GHgJwpzPQE5V17iaRk9fJFYqdCKjvE+PQ0QRAwPD6OZVpkMmlGJ2dYX1uj2Uiq4LRbbXTLJJNKMTK1H8sQLM8ep3bpZbyNi8iw99//nBRFURRFURRFUZT/6ajKGYqiKIqiKIqiKMqWbqyc4bgpPvv0s5T3HSUjIJKSvhfx1POzHD85R2koSy5X5szJEzzz1NN49TWGd+5l5uAhKpUKhWKR8YkqH3i4SNZKIg45TRAjObnoc+7cPGvz5zn+ja/zlWeeZvHSWRprS/j9t7swqnO1QkKWKxUTRAj2bvBWgXXs4YcIpUm0+izIAEhD6m704Qky+QI7JnfQbreRUtJuNumsr+PNPQdRC76JC/ZCdzj6/n/A/iP3cfjIHUxMVLlzxuWll87yJ5/5Cq1Wh9kL83jdFtN79nDsi79Je/WNG/cCuKBXOfiu7+ff/sI/5LEDOU6fPs+v/vJ/5Pc++dusrixvOxbDckkVJmitLyOjNpshhpsPPotZeQRDrhG0LhCGNoRrwHbVMDTQXZA6xB7J3WCQXLe3+z2FRnmowkd/+Cf4pX/3L4nCJDyj2ZNglIk7x5P9azkwpgatS5bB7wyOpwEFsCcQtoEWrWOP3oW3NEfcPQvx/NsczzeDg156COn1MAvD+K06qXIFv36eoP7y38B4bsUFkR+0W+kBm+GqzTY8N6k+YVRwh6aIW+fpd/7ynydh5cjv/wjZVI61y5cRuRz9nodEUhkZ4eidd5Ev5MlkMjSbTaIoIptNqmnU63W6nQ6NRgO/71OpVui22zQ2NjAcB8syWV+8RK92js7yCbr1eeRN2jddS1XOUBRFURRFURRFUbaiKmcoiqIoiqIoiqIot2ViYpKjM7vI5DQiCWdWJPN1jVhL4wchqysN9u6ZYO6ixvr5r9NcOMnKWZOF1yc4/M7v55H3fCeuYxIBXzvr4aQt7h3VWAvg5TMt3nijxsnj85x+/iU6q5cpVPcyMfMAQkg69WXWFi7SrC0R+LcKa+igTwGdpAhDEAAVwEOzJEZ+N35fgOwQNk6S2f2dtLo7iNvngT54q8TdEjKXY3lpCdt2yOVztFstzGyWILMbEdUIW02Slih/ddIaY2GlSX5hgQcfupdq1ebpr53nz596lROnLrE6P0/c98hWq9xz/wMsnXmR9upxroYYLIQzg5YewS2P8dh7HueevTn8SBLnd/Avf+5f85Ef/jv83M/+HF/63B/idVs3HUvoezRX3xwstN/O4LtEvVU0K0aiJSEXvQDRCteHLOxr/lsAcVJdI94MSMDV+RQ3bLt1S5KrTPbc8RhtLxwEM8YADTO9k9Luw6yegrC1kAQI7DxWoULkVYjq5yFYIAnzFMBOI/0WWmE3/U6X2Lv5PP3184jqZ0FKIlsiu5fwtJiocfFvcExbcYARyO1B2A6yWyeTtth9eD/Hnv5d4tACOkCDq21nALLoqX3sfsf72LNrgo1Lr/D6s3/Ixurc2x5Bcewwjqaz8PqrRJk8otEEAYXhYXbv2cNQZYhcPo+h60gpkVLiui4AmqYhpURoGvWNOsdf/BprFy4gvSbujhmqU9OURqYwJ/dA/G6WLh4napxn+cIrhP3mN2H+FEVRFEVRFEVRlG8lKpyhKIqiKIqiKIqi3JbDR+/ESWd5Yw1CHTohuBnI5VLcc+8dzF04zz/78Q+zNN8l9Dog14m8iJWL83xp7jSmrnPw73+cdl/y5myX8RFJZ8Tl9Tf7rKx0yWYyjIyO8vzKJZoLp1mbPwmAZjikc1XShWFGS9PIWNLr1OjUl+l3N4ija9uMpCCy0Uq7ccpVum9+HUiDtJBaFqdYJA7KhM0eke8RtGpYlSN4nRpQBLuKnk6TSqfRNZ12o07Q9xgeGWV9bQ05Oo2/rJMEAOZ4S2UJod1+sAEAA2SFKAjJ5nIsLqzR7QYcO3aOXrdLsVikkM/QXj7H4tkn+bV//kf0WstcH14IsNKCXfc9QiaX5z2PHSbwAr4+F7B/1MKXGl8+7vHmUor88H68i6+CvFmwRG7bkuR6MUKAH+hoIg/RJRAZ3lL9QqRBZAdVMtpAH+Kt2sPoIKog68l70IFg8O8bQxuDLbI7mTp4P1995knQqojMXmQ/pN/XWD39KmFnGYQD2R1oWgt//s8hjkgqPEjAAU0idIHsnyLqeGj5PRCFIE3+8hU9/moMx0ZzJwiaC9jZIlN3P8z5r68Rtta52Vz896UDo2COIgyLVHUY05gglXKxC2MIaxIIEe4M+G8i+zUgA7qJXd5Pbsd+TMsCI8UjH/g4H/iB/41nP/tfefrTv87G6m1WKxEGQWCy8cZLSCMPfR/Z99DTGUqlMqVymUw2i6Hr1Ot16vU6YRCQy+fxfZ+l+XmWlxbx/BDLsmg328RSgh7SD3zmZ2fpdjpM7dqF62YY33MXun4veukwl1/+HLI/S3J/KoqiKIqiKIqiKMr2VDhDURRFURRFURRFuS2PvPNRmrrAzUEkIZcVGLFEyjyvvrzEf/q5n6E++1yyEK9PQ3z1Sfk4bPLqs08S/sQPcfFyxEtff5WdH7ybyxs2J0+vEgTJAufQ0BDTd3+A055Nv/YG0CQOPVq1S7Rql5KdCQ3DTGFYGQy7gN9duX6gokWsmfS7bUADYYJmI4MezbN/DnEIzhTW0DRGJkd+qEJTN+n3JX4QYZgWSMhkM7gpl8j3kTJGCEGuVGR1owb6MEQbwPXVFTTDBSRx0L3NWXXRnCyWY1OpVul0u8zPz1NbX8dNpXC0kBc++x9Znz8O8maVIyT92gn6G/dw170f4o7dQ3zpWJ3V1QYP7d7N519a5Y9+51Ocef53IVq/zXHdyjUVEIRF1LoIRpUoWgJ8kFscQ9YGrWB0kq8iTJJgy42hhxToJkQOSJ9k4VsD0iQVGG6cA0FxfIY//eRnCAwLYZcRMiK79wBxFNE+8yoYFbBM6L5B7K/w1lYtPogOmpMiMncj3CpRp50cy8xB6gFovwlRBJoB8eo1Y//rYhLHYJYmsNIucX+DTrdL1GuAGAORgrgO1LY4n2tpV36vW1XiOEKG34x7AKAA5MBOobkp8oUCQ0ND6LrO6sYGmV130zj7OmY6hzHyTroXXwMji8hW0csVdNui3++j6zoAkcjwxPf/Ax5+3w/zmU/8fzz3+f9Kv1u/9RAktOZfB2wIu4ioRGFyJyMz+ygODeG6Lp12m4VGg5XlFaIoQsqYuQvnmT/xNZors0R+G80dwkyX8TsdhF0kNbkbO+Xi93qEUYzneUgpGR0bw+t5mKkCevEOwpUoaZHD7X7eFUVRFEVRFEVRlG9lKpyhKIqiKIqiKIqibMu2He67714yQuBY0AMskmXfnNHnS09+ldbam8mbZQeizYX4zQoNMVHcx+93mWt4uK5Dq29y5vlLfP2rL7B8/hinX3uWMGoTWyNUdx+mWZ6ks3yK0OugizZx0AQRIYQgkhC213hraxEfNAdD9AiXT0LcgNwYYEBzPvk9GvTbCCBdKCVP1k/OsDx7HgHohoFlWQT9PmtLi1TGJwBBEAS4KRcptGQfWINzvLpIH4c97NwEYW8dGYXEUbTFGK/Vgu4xiul3sG/fPoIgII4iKtUh3jz+Db7wiX+B176NVg8yoj53jHfc/VPMLbd549QyH35ihss1n9/+/ac49fwXIdpmoRsQQsNwMkRBCELHyZaRsaDX7UMcYuV3oAnw1l4BBJg7INJBsyEyk9CADEmqXmwlujpf2gTgQ7yS7AsN9ErSfkQLQRog2yC9ZJ6Q3DjfumFh2QXaKR07rtMJBDKTx3IdTMOgm62CJYlXvwLyZu1wBGiS2PdBt0GzkM0zIM9D5II/hCgcRTZXk0CEyA4qe/x1sEi+qnGRIovf7hDXzmFnLELfR4oSsDAIiERcCWboLpnKAfrdJmHfRPobydwNroMwRsmP30Ozvki4UU+2FZnBe24yK5qOEPoNlWk2uYNj98A0yZRLpNwUuq7TqNfZuHQJv9dDL08QS4mTLSJ23kun0cDKZMmXipRKZQqFArZt0/c8alFyXQ0rz/3f8XeI3Um+9ulfImyd52ZVQjS7hNCsZKxGidz0YXbtP0C5PESv1yXwAzzPY2lxkW63i9dpsXTqRXqrbyDDGpv3Utyep9/WgAx64S7slEsQBJiOQ3kQ8gBBq9mi3/cI+n2KI2O0HAdvfRa6ZwZhLUVRFEVRFEVRFEW5ORXOUBRFURRFURRFUbY1MjbOvr27SYkk3rBZ+4AYnvrzl/ny7/0yUWf26gZyiesqLAB+d4mNepuF+VUuX7rMSy9n+ewf/wGnn/kEUW+Wq4vugvZciQc+9NPsO/yDnDl1nj27J1hdWmJtvYaUgq7XZ/bka3TnXyDqL149iFGAcIlw9fzgBRchfKRmATZoLmQqmMVRrFSGxuIc0vdAN+mvLRJ1ZjEyj5LN5SiXS6RSKSIpEQLSmTS27WCl04SGlVR3QE8mQdhJxRDNwu90yQ1NE4U92uuz23afiP0VVi+dIop8isUClUqKV577Mk/+1j+9vWDGQL+7wUglzVwN0q6GaUT8u994hhNvnCCMJEmgZJtqD0KgmQViAmTsIrVRorgLoouWGUakMvirx0hOSoJ/Hswqwh1HIpIqAsEGt9d2w8PIHyDsj4C3AHFnENQAZBP0AsgchBe4GkJwIOpc2YNmWDjFCnsn9nLyK08hSrswCkUsy8ZNuZR3TrF+6vO3CGYM9mMPk6pW6a6TVFaJekCYhDF6TWTQgriajJGYJEThkXwKrglJ/JWZJNVCGqBL7FyObrNI0F0kCEOEWENuVZkk6mPbNmMHPsTC3BK95TdwHA0zP0HY7XHwoSeY2r2Xz/7Gz9MeXBcnN0y/1UPGW98TxfGjGKbJyvkXbviNAFJgToBdgDjEtiyEECwsLOB1OjTrdWQQoOXzxF6H+vlvIPUctOsEnVWCfJ5UymVsfIxcLk+z2UTTNAA67TbtTgfDLWAV7iBszbJ1wEkQ+x2EFqCZNsIWaKbNwvwCGxsb2LaDHOyvXm/Q2Vhn9cRzRN1vsPXnIAmbSBkjowjTNAEwTINsLodpmHS7XRbnF7h87DVk8wIiO4xR2YNsl4hWXiCpZKIoiqIoiqIoiqIoW1PhDEVRFEVRFEVRFGVbR44epVjIIwCbZGlaSDi/3OZXf/mTtNdXb9hisHh/DcMp0mzFvPzcK5w9cYxet8O5F/6QqHf+uvdpVgE9N02tts5HP/owy6sP0mn2KBcMnnz6BN2uh2VZPPTouzj24hd5/o//xWCBOQVCANdWAwhAxOD3wcpBbgTNtIjCmNb5F6C/QXe+CkYWZIw7fAi/H5BKucRxjJtOI6Wktr5Ot9nEqdiM7dzJiq7TuughhAWZYTRzCC2SBI2LyP4sjaUTV89f6IxM3cHSxWNbT64wKY3vxjAMRsccvvCnX+Y3/vVP4b+NYAaAZub45O99heJQhR/92Dt54dgCX/rU73Dp7EvIMAAywK2f7pdxRL95CRAg0vRqi0klDM1Bdtv0m2tJeOGKGIIlBDsQ6Qpxqw4iNzj1bVo9xGuE9RcQ9hRSSqCXbBdFQH8QhLjalgM2f3eV7WY5dOfdHH/1ddJTezFsG9OyyGQzDA0NsXL8y8S9S9vMnImeLmK5aTw7Tdy4ACxydQE/hnA5GRNFoAXmGIikwgXB7DexksbV4InsnCf296HJJrqdx9RBBs2bbBezPvscG4tn2XH396LveD/ZbIYHHr6PkbLDyI4pzpyZIzCGQAyD7DC25x0sn2vQaaxtucf64kluHjoxIGxB6CPcKkEYsba8TGloiOmpKV5arxEbBnH9MjRfR0oP2AVCIw4kvU4bz+tjmiZCgKZp+L7P/Nw8nU6baHCdc8MTdOddiFtbjEGC7CKjLmMTu1lc6bJ+6RL5iQks2yaKQhr1Or7vE/a9QTDj9C3OCSAg7szSXCwwMrMf13WpVodJpVIEvk+73WZlfg7p9UD2kY0FhFvCHRqjtTEJQR/V4kRRFEVRFEVRFEW5Ge1vegCKoiiKoiiKoijK//geevgRdE27UgsjqYsgeeF0jVp9A7SIW1dK0CiO7CGXy1GdmOToQ4+zdOkifmOO6//X1ID0Icyhg8yfP81v//pn6XZDXj9+kcV1jyfefZC9e3cxNDTEjskdHDxyGE1sbt+DYOmafSVP+EsjDU4KfXgXuuNip9OIXg36F5NKDLIHvXXwWogoprpjkkw2i2Xb2LZNs9lkZWmJXqvFp5w6mQAAIABJREFU5TeO0Wk1qUzuYPL+d1E5+r+QGzuMHq4RNp5H9k+RhEM250Lj0Dt/gJm7v/2mM2O6JR56/F28485hvv7sM3zi3/8sfnu7QMGNdDLVA7S7HkNDWebml/iFn/m/efPFTxDUTiC7Z9kumHE9mbS8iHsgcjjloxDWIO6zZdWB/hKG7SCsChhDW7/nCoHQzcFhfGT/AlfamgBJ5QiLQVKDpDqJk2xp2tftqTwySaVaxQeqY+OUymXy+Tz5fB7TNOm1t1rUv5GGkc7TbzUJV5eJW2fZui1LY/B6BMFcshAvo22rctzquLo7zk2fm5Eewu9gFfeRGr+PVKYAmnPLPcb+GkvHP8XMnh0IXefTf/JnfPL3P4dt9PCDPvnxnejlI8AIApNSdfzm+wp7xOGN86ABaaAOsg/SRkYx7XaLxvIyy7MXuTx7CdlvI1fPQePsYH4ECB+EA1YFO5UilXKJoohYSirVKvl8ns3PTRiGrK+vs3HpDYhv3noFJLqh84EPfQRTjxC2jWmZaCL5SxXHkl6vx9LprxN13yAJv2xT0SVcIWrM01xZxbZt0pk0MpbUajXOHz9Od/YM+GuDljBLhBtvEobB4G/gILCjKIqiKIqiKIqiKFtQ4QxFURRFURRFURTllkzL5sH770cMFjzF4J+6J/nSV47Rmn0GoltVedAZ3/8Yd9z5DoaH05TKQxSKRTR9s83GtU+ym8T143TOfYrmm5/n+WeeJZ1xOHhoP6VyGUSOdz8yxfRkmV6vi+M413RPuXHRVQeRQbOz5CYmKI+N4aRt/KWXiTZeBLoQLUA4B9QhPUS32YYoRNM0NKERRRF+3yeTy1GoVBC2Q6FYolodZnh8HEM3aa+s0G/3if0AKIB5APQSIMgWhnniQ3+buYsXbzo7lfHdfOwj93P55DF+6Z/9NO3Fl3m7bTKM1Ch6qszYxCiHj87wz//hP+Xkc3+QVL14C5HMzVZfCWgOQh8Z/E7DyYwi3D0EoUTGHhgjSfuWG8TeCv7qeWS3kVSSwAKR2XKsmpmnuvc9CG0zoBENKk/kBscNSUIQmxc2vvLfMmxf8zrs3LuHpcUFstlc0hKmWqVSqTBUqbCxNEfYObfNzAkQNrqhg66DIUB6N3mvBNaAPBCA9JPqEdu1irn2WBigFbHyd7Pjro9S3nHkFtsHREETkGRSNuNTU+jZndsepd+a542v/An3P/AAwyMjtNoev/f7T1HIZ9g7s5cddxyluOtOYj3NxM6Z2xz75vh1koDDZoAmBssm9H3iKKLX81i7PEu8Pjv4XNUG5xeB3ADdRKRzOI6DZVl02h2iKKLVauE4DnEck06nabfazF24QH99jRvbI71lVELw6T/6PL2+g2Hb6JqO0ASO49Bs1Jk/d47+6imShky3w4BA0F5aoNlo0G63abfbrK2u0qxvQLAM8WmSChkTSFFE03TMwvhgTv6yYR1FURRFURRFURTlf3aqrYmiKIqiKIqiKIpyS9XhEfbtu34RV0rJC8cX+eJfPE3o37qlQ6owxt/9R7/I+584QMYWLCxMs7a2wVe/sAJyc+F9M1jRS560DwEEjfV5ZNzh0MEq5TysN2BPCY6OjTLbHua1lzr8ihA3Wd62wSqSHaqQyeVo1+t0Z48hvWU2wwcQgkwByxBVQC8RRhGNegOAxQtnWVteBc1ANw36jSaL8/O01xfR3CzNep1wYwkiH5GewR2aJsLAX/k6srvBniMP0PP6rF4+vfXkCIsnvvuj5FyT//3f/DqNlfO83WCGZuSpHvgOXMdlz64xPvfHn+LMi5/iZov+kwffzeShx3jxC5/Cr59I5nzzmLGPFBuAzdDEHr7v7/08v/4f/hPe+ivJdYq7W1eKkD7EQVKJhCEIV0FPQfjWqgdx0KCzfAwZB5sbAyGIFEgbWOb6oI0kWVg33hI2CUWeKBKkUi7DIyNomkYYhjiOw+y5MxDdLGixKYVIH8JMZWmv1yBqc+tFfJ/kvskklRKcYeh2SKqSxLw1ILQZLNCSdi+ag13aw8SRRwmay6y++cwW21zdNgojSKXIDo2wZ98+XnvKoV0Xt9gmsXTxdTrNDe574AFOvPEG8wsbTCw3SKfTLJ89i7d6iqCls+vRR7cY71b71gavb14z8+r7NB3Z6aJbFjoB/tJFkF2uD9jogAGxR7pSoThUwXVTOK7D8tISDA/jeR6XL11ibWUVoet0W63BcWzAw3TzBL23/q0Jg5jLl+qQnkYYBpqukU5n6Pf7LJ07TbB0EuKtW7dsSViQKWOVhwjDiMWFBdq1NVZOv0rs+cm9DoAHogXOTjRdY3TmMHPtLrJ/9vaPpSiKoiiKoiiKonxLUeEMRVEURVEURVEU5ZYOHjxCuVS47rVQwuvn1gmCKFlU5+btI8am9/LQI3vZPaTjB5JcLoXn+RiZIXAmwXuTmwUJNhYW6dYbTN9bJacJXAt0DXQBe/M6zbxA3PTBehMjU8VNpREIgvo6MtIRVhrpr5AsputgTUJcA6+OldMYn5xkbGKCOIpo1DcYTuUIw4Bet0u2WKS+vET92DOkRnaSm7qfjmkS92vIdocolcYtTOL7Asjwja8+ybGXThD2tloc1pg48AQf+p4P8HP/5rc4/dwnbjmPWxGaw/C+b2Nq/1EeevAIBw6M8e//yceJw+ZNt5FahtLwTtzCGGF3lvzYffRa6/itVWTsI/Q8dn4nXih45eXX0URE3K2DcCFukXyVIAf/iKv/Nl204iRa1CVcXYBwJVnoljeGHSTtjS3atoga6OMQ1klCANeGVCKS1ibXhzOq47tZ6/YoFIsUi0XiOCaOYxobG3TXz7FtVQvh4g5PUh0dJfADgtWAbdte0AOKEEuSm2+zeoY9GN/VY6aKe7DSVdrra9i5KkcffoKl1QaFYpHTx/4MGXVucZyYqHEZpzDJ/Q89yB0HD/DOD/4oT/3Wefz2wi1HGPYWOPHcZ/jgj/40G7UacSxZWVllbWUFr95ARjqdjQWkkUHTdOI4IglgWIDH1fo4kFzvG69hCkiDkQHTQlgmumXiz52DsAc0B9tsXi8J1jh6bgItinFTLpqusTA/z9zcHPsPHMCyLFYWFjjzwlewK+PEQgOnAr0A3VhmdN+3cfkbf4SUN4aXNBASkcljOzaZTIYg8Ll89jT95VcgvMztB54EkMYtFtl54A5iKVleWqQ5e5yo+cLg99fcg3IFOvN01xwmpqcZPngnyycbt3ksRVEURVEURVEU5VuNCmcoiqIoiqIoiqIot/TQQw9h6PqVnyXQ8iJeeObLLB/7Ywhv/VR6FOlkXUlKgGbC5GSWVrtJfW0N/DrJU/VbLaKnCSKbznqNipZ0nBB6ssy6GMG4fqtenRqQxSmO4LouQa9Db+V1smN7iD2TzvLC4D0RhLNg7sYpVLjnifcyvXcfQgiajQZC00DGtJfnEYaFNPLkK1VWF9N0l18jN3aYVGWCdrsGxPTXl+g3PIhMYIQ4qhF3a9wYKgBBfvwd/OQ//se89o2z/OnvfpKw//YWdYWW4dC3/wSH73+U4WqJH/ueO/n13/0itcVbP7m/cPpLlHfeTbo6xeGH3sV9D93LK6+cwO/1mD/+eZYuzyIQ9BqzXJ49h+v0aDOoYmCMQuxAfCmZOyySCgkxBEvIcAy3Mka7NoyM5hBmCRnUtgho3MiEOATZBooklSj6N5ywMaiskbyuGyaZwgiRY5DJZEhnMvj9Prqu89JTnyaofYNbL8pbiPReSiOjuK6L7di0w9o24yQ5vlZMqnj0O1y9dwOSr1k2gw4xh+9/lB//yX/CK6+dxRQB0zMH+fKXX8TC57VPb19hQThZSqNjHDy0h8NHRul2HuDFL+xjfZtwBsC515/DNMB1XXRDp+959Hs9ZNQFuYgMm0RBgJNK0203wRiCsAO4XK0Cslm15Fo2UASrCG4G4Tg4mTTewuUkkENE0vrk2ns+BhEh3Az54RH8fp9Ws8XpEyfp1da5lEoRhiFBt0vsBwTtFmP7DhAPV4m8/bQaa2wsLSPl1eBMNl8iCCO8Thf0HHoqTTqTQROCuVMnaV988W0GMwBK6Pk9jOzaTb5QIIpCGvUNNroNtv4bFUFwGRlPYZomlbExvPrY2zieoiiKoiiKoiiK8q1EhTMURVEURVEURVGUmzIMkwcffABxTXmKKJZ85tnzPPmHv4nfnt12H17gkJUhBqAJQbmgsba8TGv2qxCvctNKBULiFooUS3lMBs0kRPJuTd+uvoEORp5UsUQYBqytrIJewmu2SJd3QK2W7MSfRxh5ZNhlfN8+du07QCabJQxDGo0GrptCIKih012v0VpZgbCNdMeg2ae5MEtmYobOQh7Z90CkwcqC7kLYBT8gWai+fmHXzu3kY3/vH3HXwSl+8Ad+gv7GS7y9RWSDiSPv46F3fxfveeIe7pk0yDoaTz/5JFF/45ZbRn6TfEojf+gQK4sLFHMmH/ne99HthHxy+SVmX38SmAcN/E6b2sWvkbQU0SH2QHqD85Fc17pC9nFzGexMjn5xBr8WIP21t5z79TYrbwyCDbIF5i4ItjoHH0Qe5CoAppUiW6iSEjaapmE7DlJKup0OiwtL20+hPkp++iBjOyaQEmzb3masmwJwsxCFg3DR5mcj5mq7nOS1tbU1xkZTfOdD7+LzXznHZ59+mXwhT33uFJG/RXuYG0hvjnTaRYiIoSHBzP5pDtz9CM9eeJrtPgGd+nl6zcvkCzlcx0XXDdLZLBpNYmqA5NLZ13AzRTzPxxm5k97aHNKbG8yDz9U2JptMoArmCLhptGyGfLWCt7KCbF37Wba5LtQhhhF2BV0TmI5NfaPOxsYGnXYb3+uzOD9PZ6OefIYwiYIAEQUUhyo06hsEi0v46yvXnbPrupixhtfxwM7jZtJYpsXs2XN0Zy8MWupsVwXlWgaIAtmxafKFAlJKer0erfU16K/fYrs2Iu5iWRalUhlvrfo2jqkoiqIoiqIoiqJ8K7n5Q0aKoiiKoiiKoijKt7yhapWDB/df+VkCl2oRz7++lLS54GY9RQzQRzBSY0wcuI+cbSFEUmch7cLFc+fwGvPccvFUdkjbASPDFbTBcQRXQxrmTduZADhoqSKW4+J5HiDRC6PI7ASdnsAszaBnx3DGHmfyge9j5vEPM3PnveTyeVKpFKZpYts2uVyWXCFPcWwcUxfE7XXi5mlor4Jepbe2iIwj3NFpsEbQShNohSLoRhL+EA5JJYjUlZEJPcWD3/Xj/NhHH+e3Pvk5Lr/xBYi2X6i/ljDLPPzej/Dd33UX7z6YYrJkE2o6E9O7ufk12RSzfPEEjXqdUy+9zO/+zp+xd1eZiWGXbrdLUvGgD1i06uuDEEEhmfm4BjJZ2L/KBUxE/gi6YZMvFChM7UNk9sFmrEYfArJAjuQ5EZ23Ghw3CkFk3/pr6Q+OnUhl8+QKJQzTxHVdLMsik8lQX1ulXzvFW6uVXEMrYw4fpToxQaFYZKgyhGnoIG8nnDHQXwU3l5RzuUK/es6A7wd87YWL9PohTz9/FikFR48eoLUxz22FceIuaUfHNF0sC/J5QX31MrcTOoiCHt948TmmpoYZGRvFtMykAY3uXdl+7uwr9HohM/e8l/H970CSAWGTtDa5MZghgAJYY1CsoJdKlEZHSaczeO0WyO5gvz2SeyIHpJP50DOkxqYpjY4hEKQzaZAQdNrE9SU6ywvIKCRqzIG/jmzWWTh5nMWFBdrtNpptI908197bK0vz1FYuAy5aKk8uX6C+tkZ3/gKEc8Atgl9voQMORq5CeXQMy7aRUtJutekunYb4VpVKIkS4hm076Lq27adPURRFURRFURRF+dalKmcoiqIoiqIoiqIoN7X/wEEqQ+WrL0ho+ALdsDDcEskT8l7yO82BOMZIVTGyO4l8nTsff4J3vfdx8mkTgL6EIIJ+t50stos8yJu08xAWmpPDsQc/3vaoNdDL2JUdaJqgdXkWb+U4GGkwSgg3Bd1FpLeGtAowuZc7H36Y0dFRiqUSrWYTXddxHIeV5WUWL1xA+n2ioIFwC+iZo8RRRNw4jUxPInSD3Mgwoa6RLRZpnj9F3LoE+OCMJ71culerCFT3PMpP/N2PsrrR4UtfeR0Zv93lXJM993wXH/9f382DMxlMBL1I8ifPXOCFL36K21n0X1s4z9jwIbR0GsN1qTU8XnxtFj/wuRKBiSO8VoPkq4N1ri50uyTXfPPnLiAQoo/muMRxjOm4DB84Qu2Mj19fBl2HaBVocX1oYnMfGkl0RwOxBmRAXnvMTVfPrVgZw3JSpEUSzhAiCUO8/PTn8Jvnb3n+WnonYzN3MDk1xdjYGK1mi9jvQdTcdu7ABqElQY4oAmly5TNw5WuW5BwzmQyWW+DCUo9sfojdM8NMTRVYnN2+pQkAMiTobdBq+SwtSYTQcNM5NtumbGdxfoGJ8SKXZvOsLC/T7XSQ8dXtAq9JFGsURma4tFRH01aJ5RpbhxpSoI9AvoqZy1MolxgZGWFlfh7ZXSW5DzJgjieBFdlH2FlkdxFhlyiUSoyMjyOBTDqD67r0Om3WVt4gXJ4HIwOhD1ICBtIcRkpJp9NhZGqSht6ivtXlETnsXIE4jmjOXYTuGeDtVM0QwBB6aoKpux9neHQMkHiex/riHHHrTbarqCKDLp7Xw7Yt5Nuq1qEoiqIoiqIoiqJ8K1HhDEVRFEVRFEVRFOWmHnzwIUzj6v86SiSnz83xzBc+S3PxVa4uSoPQ01i5CYo7DjO69wiWofPw4+/inQ/uwh3sounD2oak3WqCjEFEXG1tcS0NvXCEsX33YmjaW5IZt44zWGi5Sex8gWajQT+WINPgR6BLhJQUdt9D3OsyNDLCrkNHEEKQSqdxHAdjcL6mYVAoFpk7eYrO8gXonwP3MFZ5jDjs0/dyyHAd17FJZfMYlkVz/jJBbZ6k6kAPodWwho/SX1iFPmhWkfd95Ed4+O5xfvG/fY3V88eum8PbkSrN8IMf/1Hu213EFAKk5PWLDX7xZ3+WuZNfvq19+P0mqXSaXLlMpTLC5ctd+v0QGScL48nCv4cwrMGV0QfVL3SIbqwiIEBzcAvDyQL8yCjnz55hYmqKqFVjdeM4WuwzfOAxVi88R+hdG8bRSK59TNIGQ4e4B84U9Ba4rjUGcO19UhmbwnFdUukslmWhGzonjp+g3uiSVK+4sfLD4HhahaHdd3HHoUPs27cPx3WJoggnlQGtCvE2lSlEBLoJ2BD4XH/97MHNGYGEUrnE0NAQtbYkl89TKORwXZ0wvs1CpppFu69Rq20QhpPYtsk73/+3+MYzf4TfmdtmY8ml40+TtiNy+SxxHCM0DXndV0GSOPRZmTvHxpuvEHdv1qbIBCqQHsYsFCiWygyPDBNFMbWlJcAFUQHdAcMGISE0kEYGffgolR07mNy5C8u2yGazmIZBz+sRR4O/AXIJggBwgFGI6khtCsM0sCw7CXTkM9TfejHAyKFZNvXVVeLmHNAgqfxyOyEJAVigl6kceIDpvTNomkY0aGvUXT4D8a1amiTioIXX6ZAvFHBs5zaOqyiKoiiKoiiKonwrUuEMRVEURVEURVEUZUu6bvDAAw8iRBKFkBIu1SN+5b98mte/9AXob1z3fiF0pMiyMXsM183xrg9+DxMTY+wbS11pS+IYEIQhXQ8QKRASYRjI4MZl1xjhN5iaHGd4KLPl+DaX9N+yBKsVsQpjuK5La20F2atDvAp44NXQnT3s2L2HOw4dolKpkMkmC9eVSgXLsoiiiGazief1yeZyTNxxgCXTp3HuBHTP0L24ilXdgcjvRdaXybguhXKJOApZanUHFUS6QA/Zu4itzeDrBhIY2/sgP/R97+LiUpM//C//mcb86yQBBXHNGd2ck9/FD/2fP8PHv/c+HD3ZZKkd8Yk/eZ5TL/4F2z3hf2U/qXxS9WBlhVQ6zbHX3+Dc2XMsLy1yZcFaK6CZKWKRBDasoSNEvSWi5rXhBQ3I4I48xPShdzA8MkIul0M3dPK5PMvnTpEEFgLy1Wlaq7O0rwtnWEAmuTaYQAdkAF4byJO0pthaoTKO7bjYtoNjW+iGZOHyJYLGOZLWGjcSYO2nMH0XR+9/iL17ZxifmCCOI1rNJrEUYLngbbeor6O5KeJWJhnrtddMswdTk4RKlpdXWFhYxnGG0DSBZZnYuoZBd5tjDMQhGwuzGLpOGILtwGPffidffdcP88Kf/QeQb40rXGt9cZ7luVn27N7N+TeHqK2uItCv/8zEAedf+czgXLaiAWWwR7Gro5Srw5SHyhQKRU6eOIGRzhAXh4g2BOgSK5tBEIGTJ1et0mm2qIyOUiqXyOVySAndbodOu0N7bR78ea6GcHrAEjCN9H1MwySXy2EYJtLJoZs2UXBtGMYEK4/X6RC1aoPgkHfNuG22vhdMQII2jrCHyY7vYd+RI1QqFXq9Hl6vRxRGxP61FWJuToZton4X27av/L1UFEVRFEVRFEVRlBupcIaiKIqiKIqiKIqypUKxzOFDd1z5OZSSr53YYH29jpCtwZKlCcQIPQWajpMxGN71BN/zt97P3sOH2TddYKqkI0SyxJnXoZoTpPMFrOIM/saryKC/5fEjr4dlQCln3nKc1y+FpjFKd1CojqAL6C1cQnhrCDsHRBRGpjj66IfZsecA2WwW27ZJpVKUh8qUSymCEPr9gCAIiKKQxYUFFubmMNwiGBMIywKrjN/cQE+VyO0+yPCOSQrFIstLS0SmmbQxiQeVIGSfuD2LaZkEfZcnPvj9jJRcfvKf/zcuHH8BrXKUuFOD7hxJsCIJdXBlbs3BzxK0DEcf/xg//qPvp+zoCCEIY8kv/Orn+LWf/3+J+jdpD7OFyugYwyPDjK+PI2PJhfPnOf7yS3TXa8m4sRCpEUzHIZQx6MP4G+cgXAThDFp5JNVBEB52vozneTQbDTzPY3JyklQqxfje/SycP0vcOcO5538PzaoAOldDJDFQG1zFHkKzkLEHrINwQW5VVcUAQiqjO8nnsrgpk1RK49zZi7zw9Bfxmxe22MYCrYSRn2LP0bs5dOQIO3dOUx7K02x0MQyDbqcD4a3DDsllqaDZKWJhQ9Tm+kCNDloGZAckmKZJu92h0y2g6zphGOFYkijYviXJ5rnGQYim6yChUhJUymk++AMf5Y3nPk1nvTuYy61DOVEcsTy3xqPvOcro2Ajzc3PobpG4f+28+rfIHwigCNoIVnWC6vgY1WqVcrlMv9+n3+sSdNoIwySzay+FoTKjY+OkMmlCPyCby3JpdpZ8Po/jOJimhRDg9bogY6L6RZL76NrxBKCZ6LqRVLIxTTKZNP1mj6MPvpfa0iwb60s0aytImQEsouVZCFYG+7i2asrWf1vABq2AOXYvlalp9szMsHdmBtOycLpdVoMAz/MGVUa2ugdvZGGYFoZhYJq3/nulKIqiKIqiKIqifOtS4QxFURRFURRFURRlSzP79jM6UgWSpclWCL1QZ3L3Hk6+MI2Ihgm6DYT0QLQxTMm+I/dy1zvfy8c/9gipnElagDlITwiSZfnQA82wGTn4CBsXcwSNU3jNy1y/yJ3CLkySypWJ/Bhh6W8ZnwCIJfLKuqmOkd7N8L47cdNpNE1j9Mi9SBkT9H2y+Tx33XsvM/v3k0qlcF0X27axbJNy2SGbFcSxoNOxQBYZHhlh/4EDdDsd+r0eLVsjDDW0yMeoTBPV10hn0oRhSBzHxHGMrgnCqAlskIQcJEFngXT1CDK1j+/+rsf4t7/0KZ76wtPEsYFoL0N/HdhsnbA5BymwRiFsQdzDcIeZPPQ+/v7/8SMcqDqIQSSl5UU8/9zLdGuvg2ze5pU1qU4dIp1x2blrF71ejzNff47muVcgrA3e00FoIbrpgpaHqAHRBuCiZe9EaBpRZx7CiyB9GrOv4fsQTU4yvXMnY2Nj9Pt9Jnfu4nh1B535NmH3Vehvhh/SQIdr25YIzcXJjuD3W0ReD/Q0RFstjEcITWd4fBfVYZtMRqBpISeOnyNER1iTyP5pksCCBfYu3OEZCkNjDE/v4o5Dh5ia2sH0ziKpFJhmimw2S6FSYdmtELeWbzl7umVjmCah7UBgQ2ANzsMB3QCRgSiZx1QqRavZRLAD17UQQsPUBKWpu+C1p0De2LblesIskKpMUS7nSWc0RhxwBTz24B6e/fCP8fnf/H+I/ZtXF5Fhi5eeeZIf+ti7OXJkJ5dmL5Md3kmt/grXt4y5WQDBAjGMNjRJaWKCkZERxicmGBoa4tKlS+zcvYdMJoObSuG4DpZlIYSg0WiQy+WwTItHHn2UbC6HZZo0Wy1azSZ+ELC+ukYUCCBHEkrarHjhgmWipdLoho5hGFSqVepRgxf/4nOUqyPsO/IoJ1/7Kq1GFvwmBLVkOxygPdjPVgGYwXnqFvmdD1Ce3s/0zp3ccccdFEsloigiCAK6vR69Vh3pLd5kXm68Tjnc7CCAYqlwhqIoiqIoiqIoirI1Fc5QFEVRFEVRFEVRtvTQI49gX7PQ2A2h2ezS63ZxMina8ychijFcg3sffz/v/vCPsGfPFHcdrDCe19FEshR6Y5F/nYBLb57D7/fp9vpErTmuX0g10FN7OfjYB6lUSpjG1m0CJHDyzJuE4eZT8kVyOw5j2Q6dTodyuYxdHmJ9dQUtjqmOjlIolchkMwwPV3GcpLVBPq+RzYJuCKIQPA8kkna7jWVZ3HvffQRBwBcvf4Pm3EtIMUIqtx+jUGBtfp5soYhl24RhmCzjCj+pnDBY1PV7dYYcjX33fAe+1+MPfuPX6C+dhWgZeWWGNhu0CCAFlMC/CEC6epTv+IH/i7/9vd/Gd947iqUn0QwpoeZpPPDEd7Ow2uLii79F2FvZ9rrqmQmm73gHluUwMjrKc195hrXZExCeBsIrsxt7K7j5BwkLu/A2joG0QMuBphH1liBcIPlaIU1+eJI9d93FyPg4e2dmKBSLxHGMlJLuH7xSAAAgAElEQVRcyqXd2yBpMdElqWywGQy4GgqQMiDoN8jkijS8RnKC6Lx1kV3DtHLs3reDiXEoOHDuksQwbCzHSSp7DFrF6JlDFPbcx45du9i3fz+VapVdu6aZ3lliZARMUxAEGqZlEgUB0m9tM3samrCwbBvPdiAy2KzkASmEZSPjLMRJmCjwfRbmFzh65yHKQ0PYtkXK0jl8cCfPfWq7FjQGMuzT77RYmF/m0KFxLARpBEfHLT76w/9/e/cdJMl53nn++6Yv77u6q9r39AwwwBgMvCdBT0gk5UCKMpQou3eSjhQVF7envQvyQqfb243d0+3KcKWjJEqUlgGKlESKFC1oQPgBBpjBeG96pn13eZfm/sjqsT2DgeHpNvh8Inq6pzor6803Mzui+/3V8zxCt6d49mufojq7B4L19hew9+V9WF6PHTelOHRoiiM3bmPl+HcIuucu2W59cVR0gOzICKNjY5TKZYrFIr7voylFabhMNBql1WrR7XTodDoEQUCv2yM7nMU0TVLpNOMT4xi6wfz8PAqo1WrEU0mW0kO4c/u5NChigq9I5LLk83k6nQ4ryyvUazU8z2X+7Cnmz54GkqANQm+Rtcor4XmwCCtneBcdl0EY3sigdI2hbQ8xvHErmUyWDRunGR0bw7IsWq0m1WqVTrtNdWZ3WCnmFSns9BjJdBrTNFFKu47nCCGEEEIIIYT4YSThDCGEEEIIIYQQ69q6eRNKKYIA6l2fbzx5nD/9489wbP9+eqsL4FYpTW3kVz72P/NzH3g7sZhFUgNLU+jqylDGGj/wqS0tUJ+fZ2B8E/PVF/C6F1d98FCGIpsvcP89G4nZVwlnBAHf++73CIIAsDGT0+RGp4jGYkwVpognEkQiEbrdLvl8nvLwMMlkAsexcGyDeDyslJHNKtJJ6HmEbU26imZTIxGPs2ia1Gs1DMMgWdxIo+7hNVfoViokxyaonTmM227iuR7tVgu/VgW/CQSY0QJep4bvtWmuzvDWd/wOn/qT/0xl5nuEs7O2eKwRBhYu+r9qQwD5iXv4sV/5N/zsT9zNPdNx9PM1M0KtQKG0gHYvQGnX8yu+Ip4aYPNNm2g0A77xT//Ic1/+E/zmWa4IQfSWwO2QHNpAT4vgVc5Abwa/8iIQQ+k2kewU7aZFPD9Bo9Gg3WrRajaJRqOkM2kKwQDb7rmXpTNHcL0BvNXnCf8UsXbcHc5HeAIXt71Cpd2v3uE3CRfUe5eOC59YIs6mTQVGYgozCFhcanHq5CkWjh0kaB8HpZEaexPlzfeQyuYoFotMTk0xMFDghhtzDBUVuaiiB9RiEAQeXq9L0Ft5hflzMKLDaIYJjg2ttfBSGAhQRhgCCNzwLPV6PY4ePcLs7C0MDRWxbR3L0hnKJyDQuFo7kpBJPD/GwMgopXKKTSOKaH+qoprirTsKvHTXXZxbXOXQ4wG9yp4rzyFQqSyxXGkzPGRx662TnJ25jWO7bqZy8pWCBwY4ZZITGyiWSiSSSRKJBLF4nMrqKpZt02q16PV6OI6DikSo1+sUCgWyuRyObeNEIgwNDZDOxHFdSCaT1Go1HMehVCoxd9CmfkkwRIFKoyeLFAeHiMXjLC4uEo1G6XQ6l46NLPgVoAVmHuUUCNot6C0AVWD1wj5JE15zbVITb2Lj9rvI5fMMj4wwtWGKWCzK2k8sXddpVFdoL+x5hfNz6XlyHCcMpvQuv16FEEIIIYQQQoiQhDOEEEIIIYQQQqxL9VMAbdfnb79xhC9+7TlOHTpEb3kJFQTc/s6f5bf+zW9z/+2jFA2FdVH7kmvJJ0yGhkuszJxg+oYH8Jc2M3f86Yu2MHDrNWZPn6KUMTCussdms8XzO58DNDBGyE/fQnFwkFgsRjQWI51OE4lEyOZyDA4OUBhIks5oRBxoNsOqCckkJKIQM8A3oe2Bm4R2S2ewNIRuGCwuLHDq5EnyY5N0lcHS6dP0NB3X8xi44RYKpWFct0e30yFoVwgXhRXKSOK3wgVitznHmRMHeeyLnyZc8LUJW3vU+1+v8VirpKESt3LnOz/Mg2+6ndun4ujq0mBGoKCcgQ1TJSK2Sa91PW1NckxNb2Xj1CDffGw3O7/2Kbq1o+tvGgRU5+fIT24iHclRPQ69lXYYKlARzPw20sOTzB54kjMH9pIdblAcKuEHAaZpEo/FIIDtt91GrV7n3JlTHPv+CYLeApdWNbi40sDFC/WVy+bmwjaFwTwTAynSwKkaHD+xjOd7qMBFmWmGNr+L6R0Pks5kyOZylPsVHwaH4oyXFYO2IkrYSKOdgmIxy8T0Rk6+MI5bfZn1W2IAdIkN5FGWBUoDZRBW94gSVgWBQNMgCJ+/PHccTY1w5PARSqUhdF1h24rR8Wmc3FbaS89f5XU0wGbrA49w/zt/lM2bR4iZXAg9KUhZiptvmkTxowwNFHjqn/+KxuxzEFwaDliaO8M3njrMr//krWwci7Bt+83s3fEgz556AoLm1V9flVGJUeLpDMlkikKhQC6fp9ftouk6yWSSbrdLr9slGo1iGAaapjFQLBKLxbBti/GJQXI5hyBQtFoBzYaF74etQ6KxGOg2qEh/zBEgCXae6OAgmWyWbreLUgqlNBLJxEV1VvLh2dOjmPkdpMqTmI5DfWWZ2qn90Fjun8O1qjTLQICd3cbQ9GayuRxj4+NMTo0zMJBG06DXg2ZTJ/B96kvzBK4fjocG1wxpaDlimQGUUjSbTeq1V6q+IoQQQgghhBDih5WEM4QQQgghhBBCXJUfBDy26xx/9ldfwrYdbtxxKycPHeSOO27mP3ziFxgZjOMo1W8icR0U+N0eHR+2v/Vh7n3gXg7sfBI9vopXP0m4kOqjGToDQyVOzLlsKQWXBDTWlu9PnZ7h+PGjQIpYeTsbt24jXygQiURIZzIMDhaJRmMkkwmyOZt0RpFMgGGGwRPLgmwCEgoM1V+O18OCCJ4XQBAwOjZMLB7jxIkTLC8tUVuYQzcNVBDQaDSYmJxgsFxmbnYO3/WgVyes9BDQrV4IPTTrFf7iDz5Bt1Nfm1nCYIbH2qL++QmiBZpJPGbw5rc/yNbpFLZ25fwqwAogmbDJ5PIoTVvLBFyVkRrjXe99mEa9y5Nf/xydlUPX3L5TWcbttEklk6z2WujpG/FWTqFFCrj1Rc6+uI/c9N20vSiDU9NsumETI6OjJJNJYvEImqbT6/VwPY+eF6A5JTy3clkoYL2F77WqEu11x7VhcpyhaBjcOFMJ6HU9HNth6MZbiNh3csudd5HN5YhFoyRTKYZKRQp5m2JRkbMVCRW+gh5A3ADT0jEsCz0xgVs9SFjRYx0qjmXHsRMJlm0LD0W4gJ8CzqIZBno8gdsICIDGyjmyZcXc7CzNZptMJoqt4PYdGymWS5y8ajgjvD6WF86SzycZKtjELwvnmJrips0ZUukEt90xRXlsjG//06OceelL+N3F89u5zRUee+w5fuZHdlCKKcYn8my/8152fXOcXm3fVV4/DloRM54gGouSz+cZHBzEtixq3S6nT56kXq+j6zpOJIJpmvi+TyqVQtc0CoU0o6MF0hmFZYftgpSCRDJCJpOlVqvTabcxE2nQ8uA1gAhoJTQnQzyZpNfr0mw26Ha7lMvD1BfXKmHEgCjoHZyRWxmanCadSaPrBo1MlsV4gtXTCXoLO8GrAgmgheYU2HDne9l22+2MjI5SHi4xMpLCcSAIFNVqgNtzabfbVBbmw9fA5NL783I6mEUSmSyg+u1dWtfYXgghhBBCCCHEDzMJZwghhBBCCCGEuKrZisejX9mF5/nYto1hGNx63z383u/+FJuGIih1XZGMCwI4drbGqd1Po0WypOIOndocuC7hQqiDkRglO76VRDrNaqVFEMQvSSYEgBfAzud3Ua9VwbmJ0c1bGCqVSCQSFAYGiMfjJFMpYtEI8YRBMqVI9atk2Bo4CpouxIGMCvfZ6++750AmoxGLRmk0NTqdOOMTEzz/3a/Snt0Peobs1EZyQ4NomoZSil6vh+f2+qGDKxMSntujVV9E6Q658k1sv+dtlEcGWZ47y96XXmDm8At0miv9Ebjg18kNpLlpU4FNWXXVeY5oim0TUfA7BN5VAgXn6ey4/yHe8s4H+NvPP83+p/6Oq1UE2H7LHZw8cYrVdpd2u42uPLxmnejwOM3qAfzO2bB0B3Xo1bj3rQ8zVB6mWCyi6zq+7+P2PCIRi2wuzZatW6lWq5S3vZmZ3RZedRdhPKLdP+aLq2iEbWrCr9df6I4YGpZSdIBGJ0DTdfIDBe598EE67Q62bWMaBqZlYds2tm0RjSnyCUW6v2fV/9ztQa3aJvB9LMOnc0UblTUKLbkRMxoGFiKRCHWlgVUCIw7dCrphYCcSNOaCMFpSX6bbrFKr1VhdWWHTpjyODpmowm23+iNYP1FjJ0e57cF3MTExyEA8vGYvpgGZmMIdNFmtGNxy6w4Wl1aorNSoHP0nCC4EW44eOcq+EyvcdUOOsSGNjTdMkC7fyMKB/VxarWRt5zYqnSc/VGJwcIjScJlsLsfc3BynT51idXUV27axbBvP8wgCyGQyaLpOKp3ghhsLZDKKiKNQGrQ70O2GPVl0XSOfzzM/N0erVuuf6wKQgFgaLZEkXyigaRqappHN5bAdm9PLCwQoYAA0A6N4MwPjkwyVhsjmcpimied6FIsDrAwPs3hmA8unD+I2oddcZPLOd7DjrnuYmpqiWCwwPBInl1NouqLdhlrVp9vtUqvV+uNqAbX15+f8JRHFGZgikUpRrVbodtosHH/h6tsLIYQQQgghhPihJuEMIYQQQgghhBDrCoCn9i1w4sRpZg48z+FGm8LoBn7tt36Tnu7goV71L5UecOjkHNX5GXxtmS//+XME3QXwa4ACPUtqfBtb7rqHdCZDKmWgLgtmhEGKgCeeeIIgCLBzZSanp7Ftm+LgIPl8HsuyiEYdUmmDVEqRSkEmBhEFtoKUDTUT0ipsSgHhYndHhc0VshlFwtKZWQioVkw2bNjAw498iL3Pb+Tw0VOYToRkMoXr9vrVIcL2DhfCBleKpCf4qX/1cR55/zu4bTpP2tHwfZhZbvH8niN85tOf5vGvPEq9UkHpMW689QG2j0YwL6uYcDGlIGLrxOPx8D9XXUeOoCe38JPvfx8nz1X4xhf+nObqmauep9JwmdWVRVa7PbqdLt3aOQxLp7V8EtwltOQ20uVpNMshnRsgk8sRi0XxPI9Oux0GIhyDZFLDrEfYdMMm6vU6h/bvZ9aJ4dUsCGr9WdfhfCBiLZzhEoYWrrEwDnSBdFpj29ZBbtueRjNNzs32WF1tsTC/im4YRKIRTFNhmuBoYZWU8/OpwDEgX0gSiUbp1s4BRn8u1+I6wfmNTSdBJl/AdV10XUdFYgRaEjQDVnw0XSeWiNPSNDzA7bVp1xbw/Wk0XScdD6/Bjm0wNH0HM4efhqB+5YGhEc3fiOVEmJur0NtYIDBAu+hCUICtg6aDE4FMNsnIyAib73iAvX6L6vFvQtABXJYWl3nypZPccUOW4aRiaCjFwOhGFg5a/W0upZwE+ckNDI+OMDI6wsDAACvLy9RrdRzHIRKJEI/HKQwMYBgGjuNgmiZOJML0xhFSKUUmqbBVeM9rCmoGKHw8z6fb6eD2etBaAd8HEuAMYaTz5IbLDA+PUK/XsR2HhfkFKisrzB5+CgIHjAIksySKZQaKRcrDwwwUi0SjUTSlaLXbNOp1Gps3Yxjv5fThQ+z89tfYtPUWRkZGKJeHKA9HGBwE21YEAXguuF6A67p0u93+GTcJgyPXCD0ZMaKFAUzTpNvtsnTuKLWl49e8ZoUQQgghhBBC/PCScIYQQgghhBBCiHWdW27zzLNfZNc/f5La/H4iyRHu/uAvkM8nScXCwEDAdbYz6W9bcwNOzqxiZsaY3HoLx174Nu2lRQIi4UZelerJF1kYG+f+B+9hw4Y0fv8V1pbJu0Cr1eHZZ58GpZi4YRPDIyOk0+mwnUYsSixu4ziKTEaRTkEmEgYxHNX/RVhBQg/HvnYcGuH3dMAwoOWFFTqyOQPDjLPtlu1MTm/g5PETHDp4kIWFRSIRpx9K8MPqH3533WPXDJs3/eRH+Y3f/AC3DJroqDB0osFUIcrUQ1t4+L5/x0uH/gcOnJklUCZ3bJ9mIKpxteIka+M2g4BOswL+ehUfwq10J8OWB3+EW7ZO8Ynf/xSndn+NawUfvv2tr+P2egRqBLfbIR6JEivkWZp5GYihKQsv0GgsrTB1w82cPnUa23aIxWJEY1EGB9M4EQ3LgmhUI5lKhJUNel16y2cg8Pqvv/Z57Wjc/pkw+49daCmhDAeC4JIKIRFgS17h5R2qOLR80M2AoVKKkdE8CwsNTNMhkVDEYoqIduWx2roimXDYunUrpx94H/Nnb0MpjVZ9BbdTozH3Et1aGGTxWzXS6RSrq6vEkilc36fZbILbJfDq+K6HYRgo1X+hwKfbmMeyLJLJBImIhg7Yhk4mm7vGOfBZPf0MLz37FDfcuImTC1AeuRAkWju1aR16CVg1FKOjNkePZOm5LrqdRTNs/F4HsDm390Ue+/oTfODd2xhM6GSTJtnCIGg2rFNxxYkPMD45Sbk8TKEwQLvdplqt4fs+0ViMjdkslm0TiUT6lUlsisUs6YxOedgkGQ+DGY4K7yFXh1gUkimdWDxCt9vF9318dFBhCxstlSZVLDI5ORm2KTF0Go0GpmWy59lvUZvdB/YUxAeI5vOUhsuUS2WGR0YYHh4mnU4CAY1mm3qtxupqBcdx6HW7vO0DH2Lbjh0MDw9RKkcYGlQko6Ar6PhhwAUgCAK63S7KiBAGhtarbLJ2Q6bQ7Q0MFAfxg4BOp8vSyRcIvKtVXhFCCCGEEEII8cNOwhlCCCGEEEIIIdb12S98k33PP0a3sYwVTbPtgYcZnyzityt4vSQ+OuusdV9dAKcrPb75xa/Smd9DpzaGrtnkpt/M4oGv9RfsO/Sqs5x8+SVc92Fs89IF6UYAlQCWZmY4fvQISinGJyYYGhoinU5jOzaJpE0ioYhGw4oZ6SgkCBeKzcuGpC76vNZMY9kDvZ8XyGYViQQkEgaJRJLl5Ri2ZaM0DdiPbTtEolFct9dfCF//Xfa2E+XN73grmYyJuqwSRhi+UMRtnXtuHmVy0yhnGjCR4qrBjEumVWmkU1EuREvWKj5AGF9ok8wV+Y1f/ymeeeEIz331MwRu7Zr7bDVb/X2s4DerqEia/GCRpdMH0GIFvJ5L5ch30G0buI+x8TGGR4bJ5XL4vo9SCk0D04REXFGvaRQKBVLZHPlNd7M649Bb3UMYzlivrYcOxAhbS4THYthpLCdJY+nQ+a2MftjGB1oBaBqkEopmGyzLYHQkxcJigOOELW1i68ynDyRTGlPTw7zv/R+k1+2yslqhWq3SabdZmp9l93c+y9yRvWAkwpYppokf+BimiWFZ+G4Tz2/h9cJWIrp+4c7QvRqJRIJcPkEurs6f06XTx/rVOa5yXntLLJ/Zh2HoNNse/mV/wlGEx6Pr0DUDltyAfCFPLpdjxvCJb7wb00kxvfV+2o0GZ2bm+fJ3j/BLD28kFTewHQeFWjceEk1kGRwaJJFMAAH1ep14Ik4sFiWdTuN5Hq1WC03TSSaTpNJxcjmHUgmijiJqgEM/YqPC+0k3wLIhm02xtLhCo9FAj2dRnR6B51IYm6A8OsL4xEQYquj1wnYwy0u053cT+B4qWcbJ5RmZmGByaoqx8TFGRoYplXIkUxqaBs2mQ7MZJ5VOsbS4THFokOHhMhOTRXI5nWIe0nY4vkCBp6DXhV43oNVsUlldpduY789EgysDNP0TqBXRkwPE4nHarRa11Xkq516+6vkUQgghhBBCCCEknCGEEEIIIYQQYl27n/giyfwo2970c9z3tnfx0x98E1MZg6QWLrgqgKBf9+A6QgRuEPDUzjMcfvFJ/O4CR5/+LIGn0ayUUEYZPWrhVg+BphMvlnl+517u2jrE9PYiawuiLRcW2/Dii7upVldRSmNgYIBsLkciESWRMEkkIJlUOBGI2WE84eJgxrWGqgEZHQI9jAW4QGCBYSiUCvA8Hc9NMD4+DkCn3Q6rbyhF4HYI63qss18trM6QNtS1Ay1rbVbcsP3F9VQlabZdFubOET4zDtQ5X3FCOWjOMG/98V/ilq2j/Oqvf5pO9ch17LVfS8SIoGmK2tIK1WNPEQQRgnYXgjmUbqE5aU4eP86W7dsZHhmh2+3QqrWo1ToYZhTbAtMC27EYKg2RzefZft8DvPC4S8VXuNV9XBpoUYTL5t3+MVyoqtFrzOG2Fi+fLghHSlaBFkA8DbM9qLQg5kCspFip9VuacOWcmhqMFRXZZISRkTGCQLG05DI/V6dSqVGtjDEyOs5XvvB5Oq4XBjJMk06rRafVwrIsOtUGBC6B38P3fCLxLO36IoHvo9wGmUyaeNzA1vtVYDSNwclJ+M56VRn6YQClUVk6RbVSpZQdWP8POAFUvYDTc3D0aIOlhWWmpqcYHfsVbrv9JgZSoJsRur7OuXML1Jtdmh2feFTHNAKCdVqagBaGFFZWmJ6eZnl5mfJwmY0bJ0ilLRxH4XngeT6u6+N5ilxOJx6HbFwR0cN7TimwCK/KBmE1Gk0pNE0nGo1imib5UolaPE5AQLaQp1QqMzg0RK1Ww3VdOu02jaUTdCsnwhY0ySSjExNMTU2FLUqGhxkqZRkc0kgkFEqDTge6HYNcLkkuF2F64xDlsk0iDpmIIqWF95ZOvwmRD64b4HouzWaTeq2G357pf3e9u3XtnAUYhkGn3aFaq7J66iW8dnW9sySEEEIIIYQQQgASzhBCCCGEEEIIcRX3vvtDvOcXfodtm0vcNGJTiOrnf4lc6QU8vb9CdXWFrZuKTBUcLE1dM6RhKLjzxiw/8aEPcfzwbjqdNmfPnKXdbNFYdel0NBJT78at1Vg8eYKXDYOX99/EO7cVQUEQwGIzoOfBE49/n8D30QydTCaDY5skEybprCIRD9+hb5sQ7S/E2v0xXCvs0O8yQkKFy+MWYTij1y+p4ScVrhvQ7ZgEZAE4dPAgpmkSBAEELmEliHWO3dDYPG6R0V85cBHVYTx9WQuLqwgCmFuqcuSlpwjDDD6QY60iRWzgRjbd+15+8efewxM7T3Bg5zeuWa3hoj339+UTSSZwO206zRy64WBaMZRm4mGgqS6ReIxkKonn9lAKYjEH0wzIZKDnQjIBY2WNs2cNBgcHOVarsnr8KfzuMuEyfheUjmbnMVLT+M1VfL+H36qAv8yFwEtA4LtXHfH5djVA1wg4ttDlyYNzzM8tcM89G5nKxdHWmf2UgrgB3bhiMKZoBFDIGeTzaVZWktRqA5TKJQzbZuezzxJxImhKw+310HQdAvCbc0CA32syVBzCzL+LZ79yDM/v0mutEnEMsmkNu38D+T7kypMYkTJuew5l5bDjRZzkECroMjE9xR0P3s/Y9E0MDRepdRVNH+LalUGopQZUKz2mxiK0mhF27jyFUoqIvZV33pLGVIpuAP6WYVa6gA2d+UrY2sZvXzmRKkJr6RC9bgfX85icmmTzTSPkcgbplCJq99sBKZ1WT0cnQDfB1BQxBaYKz2rAhT86mf2gkWGAZSmSySSZbBalqX61myTpdIbxiXEsy8Lt9eh0OrRbTWozO8OqOkqnPDLM5NQUwyMjlIfLjIwUGB7WKWQVMSN8DT8CXqDo+tDsWAQBxCMQ1yEN2OrSUA+Ec9rrebiui+/7BIHbv+6udrdqoDpEMhmqtSorS4vUz73EtVoFCSGEEEIIIYQQEs4QQgghhBBCCLGu2++9l/e/fYpSLKz2sLYo7AdwZN7jxf1z/MPn/h6/2+LnP/wI73/LNAMJ86oBDaUU20ZTfPL3P0zDDaj1Ak4utJmZbzI7V2PP8y/wnS9/iRXdQjcjVBYXqdab+Kw16wg4u+QTdXq88Mwz5/c7UIwxORVF1xXxOFgWOFa4kB0jrMOguL4qFBe3OXEIl1o7CrwAEhHwM+EWmm7huUlM0yQSidDr9Qg6Na4WztA1KCUU2isMQgExLfy4eB6DANp+gK6BqcL0iAecaQQ8+dIM9eXT/S1dsIoop0xQPcv4zffzoZ99D6WhAv/xj/+B5uLB65iF868K7jydyll6tdPg1ogN3wC+hubW8f0u7foyiWiEyuoqS0tLFAp5kpkkmuaj6WCaiqQFlhZQLCapVkqsLi+j22kCv40RS2Gl78KwEyTyJVw0qqurKKB1eh9+fZHrWfC+eFoDwuvF8zROnVrkpV27SabibJ/YeMVfQdRFH4YKgzzpAFoRRbYEi2md1arG0pJFENxIrVrFdhz0hXlQCsM0IfDxW7MARCMO8UScl77+z3huGCrptusor41jhKEFAE1Bz/WwB25jcqzM6KatDI+OkkjE2LalxF23lojETHquQg8C5itwfAW25K489qEYlDabLLTge0/UGRwaopDPUy7GMVR4zUUUBCiiDsx1Pf7g//pL9j3zT+vMpAlBFys5ge1EMA2DickSxaJBLqNImeExrLWS8XRwUTQIH48SBh6si/bo98+JYYBtg20rdEMjkUximRa6rpMvFMgX8uQLBarVKq1Wi06nQ3XhGJ2VE+G5UorBwSGGhoYYGR1hdGyI4RGDck6R0cNj1ABfhaEqVwPXCO8TgzB0tXb61+qTqH7lH9eFdruD7/uYptkPWq1dTetRaE4WJx6nsrpKffYoQWvhKtsKIYQQQgghhBAhCWcIIYQQQgghhFjXDUUYjl1ZDUMBO0o6G98zyZ3j7+OZnQc4dvAAL04M8PZt+WvuUymFrYOlKzIWDMdi9MajdPw8lbdM8PSP3Me//1/+T07MNdm0/WYsJ0nPBcOCmgtnZxtko0scPXwhZJBKWuSzCqWDroOhg92vmBHl1f3ie/ki/1o1Db3/bnvHAcdRWFaAaZkMj4zQqNfRNZ3Ab3O1xZSDynYAABVZSURBVFz1KsZx+XwHATS9gO8f6VIsmkwkodmFc42AF1+e52tffYJexwMVC18+qKKcTdBu88Cb7+CRt0/z6DcP8/x3/5HAq7+K2QDw8VEEukbQNajP7EWPFvBaS2hWioEbHqJVq/HMU0+zslLhne96Cz3X5czpc0RjwwwMWLgBaDpkMybRqIkPbHnLI5imQYBGrVanWlnFD8B3XQzLxnEc1OhmGmcUQfUFrtYu5vwcXfb/uFIM5wymxgcpZBzu2F4mba771HDOL/ps9lvgxAAnFlZ66LmQziSZmJigVq+HgQ5NwzAM3PoC9FYASGVzlEbH2KUu1D3x3A7t6jz1pn/htTRFcbDAB3/xA3z4F96Bsh2CQKMYVyRiClspDMLrWUdRsqG7Tu5HKUgbYVinY/qkklHSmRvJ55KM5HV0Lr2mW17A158+x2OP7SLww8jTpTyUWWR06wNs2LiRsfExkgmLSFQRMSGuwnlZC7T4hM0/zCAMM1nqykYga01A1u4f2wbLNIhEImRzWUAxMDBALpdD0zSajQadTodOu8XC4cfPV0tRSpHP5xkZHaU8PEi5bDKcVxT7wYyLWUCgLgRD1ubh8myUB7R7YTjD93w6nQ6KAPxrXW8KGMDJj9PzPOqLiwTLB7laMEsIIYQQQgghhFgj4QwhhBBCCCGEEOty9CuDAhA+ZihFOmrw0F2beOjOjeHC+qvYt+r/oxMuPts6JKOQvLVI6j/+Gz72W/+WXC5LNps5/zb3xWbA4mKFueoeapWV8/sxDIWm9xd9+wvrTn8R+eJ3yr9aa++u17iwwBsE4fFrGliWQSwWo1qt0ut2CHrrtIjoq9fr/Ne/eZRf/vDPk8tmUNfq/3KZANi/AM2ux649DQ5EdNodlye+/xK7ntvJ3u9/MWzDYGWgswC9kwSdIXJT23j/w7ezsNrlC5/7Equnn3nF11rv1X2vjmaYeN4yQeDg1qqkxh8gVZwimcvx4EMP0et2SaUSmJbJ4sIKkYhDECgqFchEIBNTlHIB7uYhAiw2bNhAvdGg1WyyurrK8tIStVqN+fl5LMui1WqCbqBigwS1QQhO82paRhjATTnY9LYhNDWEroGGelXVU3QFcaBhQMRRWJZGMpWi1Wrh+34Y5DBNGov7zlda0M0YtVqNSKJA5dyFfc6eOsDiSo+6b5PRFZ1uwJ13bufNNzoUExYeF4JAnrq0pY0iDB9EtGtcxwoKtuLn3jFGtatI2JDr9+/wA+j40ALOtsCIJhjfchvzx5/Gqx+6bEc2qbH7uemWHUxvnKZUTjNQVKSjYbuYCBe1Aul/HQWi15hYjX44IgDPD+/XSMQglUpRHh6m3W6Tz+eZmJyg3e7QbDZpt9ssnt5PfeHwhUNUiqFSidHREsPDDuWConBRMOPyIVwexlhviGvhjW4XWq0W9XqdTrtFGLTQ+5/XfhKsscApY6UHqK+u4i2dAU+qZgghhBBCCCGEeGUSzhBCCCGEEEII8ZqFIQuFftmC8mvbD6RQ3LMpyy/+6iP8xZ8+Su+td6Nr4fv7Z5a6NBot9j7xBL7vnX9iPAG6EQYy4v3WBQ5hSOP8vl/HuLSL9xGAYa61aFD03B6dTod2owFu9ar76bTb/O7/9DH+5q8/zUc++jF+8ifeRzIRe8WQRgDUfSgm4YZ8BAKHWsNl3/EFTu9/kb3f/jztld39UWZYq/eRymd46OF3sHFigD9+9AWe++qnCdxXWzUj5Ncr2LEIHiYEPRLlu9l0+5sARTQaw/c8xifG2LSpTICGYeTpdrtYlsbAAMTs8HwU4gpN1/DdLCdsm/n5BQgCnEiETCbD4uIirufR6XRwWhEWFuYJUGAPQ3sVuPr8XjGLCgwUxuv8q4dOP/BjgmFoWJaF63n0ej2i8Thu9Qyd5QtVXOqrc+z87ndpVJcv2c/Jwy8xP1+h7sbJ6JCMKN52S4KcGVamuXiY6w35WlfJ+e8pRSGiKEQuPO4D8z6crgAatFrQ7QaUR0aw4wWal4UzlJlkastWtm7dyvBIgYEBRSqpSGgX7q1rBR6Cix5f+9oAkgpsAzQb2g5YtobnuViWRa/XY6A4QDqT4eCBg9TrdRr1Kmf3f+t81Yz+4ZHPRZmYdBgegCETYlcJZlzPvK193zLCCiVKKbrdHueOH8DvXtyi6OJghg4U0FNDuJ5Pa3YGWse4sgKJEEIIIYQQQghxpcurTQohhBBCCCGEEP9yFMQ1xXvfthWtfYKje55FATU/YGa2wcryEnt2PnXJUywTEka/DQXhO/nfiGDGRUPCoL9Eq9aqdUAQBHiuh+e6tKor4NeuuR/f93l5z4v82q/+Iu9697v5wt//A41miyC4dkWImAbDUUXcVMQtjcG0xUO3lPjrP/pN/vX/8QnSQxNAD7wqYa0HDdwaP/HOW9l1ZJXPfuqTNJf2v+bjD7wmSs8AFnpkIzve/D5i8QTLy8voukar1ULTdDxP4XuKeNxk48Y4YyM6MaffZkaFC/RDEcX0uE55OMmG6TGmpjcwNDREvlBgeGSErVu3Mj09zcjoCKVSiWS+AF6Pf4n3lqwFcwzC820YCqUpfM/D83wMTVE9+SQEFxbmW02XSq1Gp7lyyb6Wzh3j3MwM3X7WwNYVOevKlkGvd7wXf6w9ltdgMhm2a5k50+W5Z/fTabfBvbLSS9Cb4/Djf8rB579CLFIjl4GMEV5V1qsYw8Vfa4QVN1IqDFQMZSCVDKMjmqYRj8fpdDqcOXWa5aUlKpUK547upr5w5JJ9u70un/zEh/nUv/0fObnrBbROB4Lgdd3jugJLA8sCy7IwDJ3W6tlrPQNUHAyb1soyQfUQIFUzhBBCCCGEEEJcHwlnCCGEEEIIIYRY1/HjJ5mdW6Dnuq8YIHijrFXQyCcsbr7tLpbP7MVXcK4Bx47OsX/Pbk4dOXDJc7xeFzsIiBBgcaGCxxu17q0Iwx4mF4IZmga1WgfLMul0OvQaVaBzXfvzXJennnicn/7AB/jR9/wYX/3Gt+l0uuvOsSJcQF5bxO8FAcdqHssu5GMmv/Pht/Px//QZhm54C6gaUAfabN8ywcYNZf7vP/xbjj7/91yoAvAaeHVMJ4tm2sSHNmJGIpimSXl4mGQqxcDAAPF4HD/QCIBoVJFMQacHjQ60fdCDcHHfVhA3FemkIh4zyGbTFItF8vk8AwMDlMplBgcHKRQK5PN57IhD2JCj+drH/xoFXJg1rd/KRlOKIAioLC1y9qXv0qleupDv9jzas8foNi6tnFFbPsen//1v8+ijj7HYcF93qOB6rV0/WQNG41AqapRKBSYmxxi98VZQV0YuqounePQ/f4yPvf8hvvSXf0GwsorTrx7xWtsDrX3YCtIGlAYgk0kQiUSIxmIsLy3T7fWoVqvUKqucu6xqxpqFsyf4mz/6D7znLW/i3Q+/h//nLz/D2XNz+L7/mn5GWYCjQTQKuq7RbDYJIkMoM3uVZ/igwGs28BYOgj/Dq2m3I4QQQgghhBDih5v+8Y9//F96DEIIIYQQQggh/n/orW9768f/9m8/y7e+9S2OnzhJr+fiRCLYjo2maa/YkuP18IGZmsWR/cd59488wM5DTb7xjaf4/lcepTq7m7UFUd/3eeGpZ3nx+RdZXl7FMgxikSiWGTZgeKOG6AEu4KowdOB5cO5sHcPQ2L37ZQ6/8H3c5glezUKt73ucOH6Uz3/+79j10ksMj4xRGhpE09RV57YVwLd21Wi2XcZyJqamkRnIc6KS5viRg/TqpzCsOP/647/Ht549yef+5H/Fbc29zqP3iRY2Y9smTmqQWDqPYeg4kQilcplisYhhGgSBhuMYDAwoej3o9UDTwQvCyiaGCps/6IBrQc9bazui4QcaruvSarXwfR9d02i12pybmaExOwf+MtA9P6LNmzfzyCOP/ECvwTUVoNIMmJ1zmZtbYv++vez+7ufpLD7LpaEXHfQUfmsOgtXL9hLQWDnNM48/RZDbxh3bxrC0N7ZyxtWsvUREQTGlMTmR5Zaby2zZtp3ZVY3VlTqdxgKXXrsBKwtzPPaVL/P1r38D24kzOTGObVuva841IFDQUVCpG8wvVKlVq5imiVKK06dOcfbIThaOfI9r3Utur8vJ40f5py/9I5/73Oc5euwkqXSWQj6HYejXNca11ittoOnB7GyH/fsP0vUD2l3oVY8T/iS6mAF6GToVcA9z8TV5sY9//OOfuK4JEUIIIYQQQgjxQ+X/+7qgQgghhBBCCCH+m+D2esycOcnMmZN87atfwTBN8vkCm2+6mbvvuZd77r6bLTfdRLFYwDSNN2yhPHyHveKmLZs4dmiG1ZrP44/vYc/zO1k9uQuCSxdMjx/cy/GDe/ncX32KaDTO6Ng4t952O/fdfz933H4bUxNjJOIxlLp66OF6aIRLtT03rGRhOxbdTpPlpSWC7ipXLuRen3aryT/+/Rf41je/yft+/Kf47Y/+FltvvmndAIwORCIWR2Y6DA9CygpoK510JkNs4EYasy8wuvEuunqWv/pPv0WneuI1H+8FLm53gUj+BpxUnmq1QiIRJ18okEql6Ha7pI0UlqmTz4NhQqsVtjMxdYjb/coThNVHNCCig2mCritMM6DbM2nUDWKxGACNeh2AeCrFYjyHvxIlrAoSarbazC8skkgksC0TTQsLg76RYY21lhxxwFKwslxjz+7dPPXlz1KfeYIrq5H4+O1Z0OLgrx8saCwf5pP/+0fJpv6QX3rfnaQjOufjE+qNq/ZyhSDADwK8Zgt/cZEzx05weu9e0uYCumrBVapO+L7H7l07+bVf/hCf/OSdfOQjH+E9D7+LeDz6mudaA/xAYTsOhmHg+z6madJqtaisLjN78NsQXF+ll8D3OXXyGH/8h3/AX/z5n3HrbXfwwQ/+DA8//C6GS4PXvOcvPmLdgHjCZmxsjFq1RuDfwsnlA7i1Y5c9KwJeF4LjhLEOIYQQQgghhBDi+kk4QwghhBBCCCHEdXF7PWbPnWX23Fke++bX0Q2DXK7ADTfeyN13380999zD1i1bGBwcwLZe3zvsdWA4azNULnD0zDLPPfM8Zw88C+781Z8UBDQbNQ7s28OBfXv4m7/+C6LRGCNjE+zYcRv3338/d9x2K1NTEyQTry6sERAuKq9t7fmQTJocPNCg2Wig3oCF2nqtymc+/Sm+/KW/55FHfpr//jd+g803bkTXLnQkdRTcucnmpZM6RxZ8zpxuMDd7lpdffIFmvYbSbEZuuJU//Hf/G4snnuKNarnQWjlBZHAbdjSKUhrZXI50KgWE1UtQEItrpNIKXQddA9OAvBVWzHC5qD2MgqgOlhWGOLpdhW3r5AspKqsGrUadVqNCbfksfnMWTV/Bv2x+v/XNb7Jjxw6Kg0OUyiOMjY2xccMGJqemKJVLFAs50uk0jm2j6+GZe62XowZoJliWggBqK8usH8QJQI9h5jbQm5+96v5WZl7k93/3E9Q6v8/b37KDgTwMRhTx1za8S0cQhONwXZdqrc7Zs2c5eOgoe/fuYc/ulzlw8ADnzp6hWqngur3r3q/nuex85gl+4eee5Y677+OjH/0o73rHW4lGnFd9nytAaRCLGWSzWVaWlzEMg8pqhaXTe2hXzryq/a1pNRt8/3vf5onHv8vvlYd5+OEf5YMf/Gluv+0WopHIFeNca7ViAY6pyOUijI6NUq/XUZpitbyDpQMnuPRcmxDMAI3XNEYhhBBCCCGEED/cJJwhhBBCCCGEEOI18VyX+blzzM+d43vfeQxd18lkc2zcdAN33HEn9913H9u3baU0NIjj2K9uEVdB3NG5/c4befqFIxzZu5vWwi7CZf7rFAQ0G3UO7tvDwX17+K+f+Usi0Sgjo+Ps2LGD+++7j1tvv43pqSlSyUS/UsX6u9IIqz+YgG1DpwOaprEwP0erXifwmtc/rlewsrzMf/nkH/H5z/8dH/rFX+a/+1e/wvjoyPlKGkOOIrfJ4uCiy57dNfbtO8qux79G4/S3Iejx1Nc+S7d+ijcqmAHgtlZoVVYYLJcJggClNAzTxHVdbNsm8D0iEY1eFwITLBPiVjhnNcIF8HgQoHyfbs8jaDaozy1z5MQ8xw6e5szxY8yfO838mRPMnz1BdWWBbruO53auqJQC0O12ODtzhrMzZ9j1/HPnH9c0HdtxiMXjDBQGGBkdY3R0jMnJCTZMTTIyNkYhnyebSROLRtF1vR/SufqxO0DMgmQqQiQaIQi8a8yth+a/8sJ9qzbPsZOLvHRgle3bMhQir/iUKwRBQBAEtDsdlpZWOHnqFPv27mPPyy+zb+/LHDt2jIWFOVrNZhigeQO4bo8nH/82zz3zJPfe/wAf+chHeNtbHiLyKu/vIABdh1QqiaZpOI5DrbrCyomn1z3fr0YQ+Jw9c4o/+y9/xF9/+s/ZfsutfOCDH+RHf+RhxkbKaJp+/nwrwsCTbUAkoshk0hQKBSqVCpnSFMtHogReL+zFQqf/CtXXNT4hhBBCCCGEED+8VHCV0pVCCCGEEEIIIX64KaVe1y+MmqaTSqfZsGEjd99zN1tu3oz2KhZw6x5Uuj7/+OXn2fX4t/Drh1/PcNblRKKUyiNs234LD95/D4l4bN3tPKBLuDxb70G9DrWaz/69hzi8/wBzhx/H666+4eMDKA0P8zM/8/PcsHHq/GNtH04udnjs8X2cO3uWc4dewG+e5sK7/N/o3/U1zMwWBsamsCyLkZFRzH51lEgkQiIZI5+PoykwDHAiEIuE4QyATrPDucNHOHn8OLNzcyzMnWVlZZV2q4nb6/0AxnslpRSWZRONxclkMpSHhxkdm2B6egMjpeJVn+cBCz04NeOyZ/dBXn7+SapnnmX96hkGKBOC1rUHo0WZ2P5uhicmuPvOaaayOsarrOyxuLTKCy/s4tChA5w5c5rK6irdbueVn/gGsmybB9/0Fn78x96LZV7f+39cYMWHpQrMnmtx5sxZbNviyL5dHHn+S687nLEepRSF4iDveOe7eeDeu9G0C5PtAasBLFVh9lyH+fkFZmdnmZ+d49z+76CcPF5jBrwWYczolavkBEHwA+tQI4QQQgghhBDiv10SzhBCCCGEEEIIIYQQQgghhBBCCCGE+AHSXnkTIYQQQgghhBBCCCGEEEIIIYQQQgjxWkk4QwghhBBCCCGEEEIIIYQQQgghhBDiB0jCGUIIIYQQQgghhBBCCCGEEEIIIYQQP0ASzhBCCCGEEEIIIYQQQgghhBBCCCGE+AGScIYQQgghhBBCCCGEEEIIIYQQQgghxA+QhDOEEEIIIYQQQgghhBBCCCGEEEIIIX6A/l8u1jgMfICFywAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "def imshow(inp, title=None):\n",
    "    inp = inp.numpy().transpose((1, 2, 0))\n",
    "    plt.axis('off')\n",
    "    plt.imshow(inp)\n",
    "    if title is not None:\n",
    "        plt.title(title)\n",
    "    plt.pause(0.001)\n",
    "\n",
    "def show_databatch(inputs, classes):\n",
    "    out = torchvision.utils.make_grid(inputs)\n",
    "    imshow(out, title=[class_names[x] for x in classes])\n",
    "\n",
    "# Get a batch of training data\n",
    "inputs, classes = next(iter(trainloader))\n",
    "show_databatch(inputs, classes)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "Ck-fy2nVLhSY"
   },
   "source": [
    "# Task1 starts here"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "TDjBw0HKQLiw"
   },
   "source": [
    "# Working for VGG here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 83,
     "referenced_widgets": [
      "a2ebc1b09972407b979ef1114f88cba6",
      "08c280e65cbb4819aa73f4e9b542c397",
      "2d706c6ff466458bbc4677066970658d",
      "e92a0f08e6d44acf8b1a3c5f9fd6d8f8",
      "07a68bd404dc42c885125399b7729715",
      "c49c88b32cb94bbbb485f8054e17cf87",
      "a80d50ebc74542838ba454e9d05be0ba",
      "eb1acb46667e45978af77403e7d45680"
     ]
    },
    "colab_type": "code",
    "id": "kIyMvDMe0nyP",
    "outputId": "6a3fd2c0-5f67-447c-afe8-68e07ecd3201"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading: \"https://download.pytorch.org/models/vgg16-397923af.pth\" to /root/.cache/torch/checkpoints/vgg16-397923af.pth\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "a2ebc1b09972407b979ef1114f88cba6",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=553433881), HTML(value='')))"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "vgg16 = models.vgg16(pretrained=True).to(device)\n",
    "vgg16.classifier = nn.Sequential(\n",
    "               nn.Linear(25088, 770),\n",
    "               nn.ReLU(inplace=True),\n",
    "               nn.Linear(770, 3)).to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 697
    },
    "colab_type": "code",
    "id": "ywlCdYDJ1AHB",
    "outputId": "1e94d449-3f0c-4988-eab7-e763a88e4beb"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch # 0 \t\tTraining loss:  0.26106827404618876 \t Validation loss:  0.185352947935462\n",
      "\t\tTraining Accuracy:  89.12903225806451 \t Validation Accuracy:  92.83439490445859\n",
      "Epoch # 1 \t\tTraining loss:  0.1650070145764609 \t Validation loss:  0.1887102885171771\n",
      "\t\tTraining Accuracy:  93.66129032258065 \t Validation Accuracy:  92.88747346072188\n",
      "Epoch # 2 \t\tTraining loss:  0.1516976814486624 \t Validation loss:  0.14988368451595308\n",
      "\t\tTraining Accuracy:  94.34408602150539 \t Validation Accuracy:  94.26751592356688\n",
      "Epoch # 3 \t\tTraining loss:  0.1355941454236655 \t Validation loss:  0.16312287487089633\n",
      "\t\tTraining Accuracy:  95.05913978494623 \t Validation Accuracy:  94.21443736730362\n",
      "Epoch # 4 \t\tTraining loss:  0.12724155793446548 \t Validation loss:  0.13259730506688355\n",
      "\t\tTraining Accuracy:  95.13978494623655 \t Validation Accuracy:  94.4267515923567\n",
      "Epoch # 5 \t\tTraining loss:  0.12495369176121102 \t Validation loss:  0.1362723920494318\n",
      "\t\tTraining Accuracy:  95.23655913978494 \t Validation Accuracy:  94.79830148619958\n",
      "Epoch # 6 \t\tTraining loss:  0.11223812389773191 \t Validation loss:  0.11508005503565073\n",
      "\t\tTraining Accuracy:  95.77956989247313 \t Validation Accuracy:  95.64755838641189\n",
      "Epoch # 7 \t\tTraining loss:  0.10586633057016687 \t Validation loss:  0.1251739552244544\n",
      "\t\tTraining Accuracy:  95.91935483870968 \t Validation Accuracy:  95.32908704883226\n",
      "Epoch # 8 \t\tTraining loss:  0.10440726030963599 \t Validation loss:  0.14362744418904186\n",
      "\t\tTraining Accuracy:  96.1236559139785 \t Validation Accuracy:  95.01061571125267\n",
      "Epoch # 9 \t\tTraining loss:  0.09869115830389495 \t Validation loss:  0.12194491475820542\n",
      "\t\tTraining Accuracy:  96.48387096774194 \t Validation Accuracy:  95.75371549893843\n",
      "Epoch # 10 \t\tTraining loss:  0.09106989031100703 \t Validation loss:  0.12373729608952999\n",
      "\t\tTraining Accuracy:  96.68817204301075 \t Validation Accuracy:  96.01910828025478\n",
      "Epoch # 11 \t\tTraining loss:  0.09632423350145829 \t Validation loss:  0.10890215933322907\n",
      "\t\tTraining Accuracy:  96.32258064516128 \t Validation Accuracy:  96.01910828025478\n",
      "Epoch # 12 \t\tTraining loss:  0.08451354637809251 \t Validation loss:  0.1230417531915009\n",
      "\t\tTraining Accuracy:  96.89247311827957 \t Validation Accuracy:  95.38216560509552\n",
      "Epoch # 13 \t\tTraining loss:  0.07773246306724385 \t Validation loss:  0.1247622387483716\n",
      "\t\tTraining Accuracy:  97.06989247311827 \t Validation Accuracy:  96.33757961783441\n",
      "Epoch # 14 \t\tTraining loss:  0.07576175823270045 \t Validation loss:  0.1620323561015539\n",
      "\t\tTraining Accuracy:  97.06989247311827 \t Validation Accuracy:  94.85138004246285\n",
      "Epoch # 15 \t\tTraining loss:  0.0754859793172746 \t Validation loss:  0.11810846077278256\n",
      "\t\tTraining Accuracy:  97.17741935483872 \t Validation Accuracy:  96.12526539278133\n",
      "Epoch # 16 \t\tTraining loss:  0.06899019471398488 \t Validation loss:  0.1086373302154243\n",
      "\t\tTraining Accuracy:  97.4731182795699 \t Validation Accuracy:  96.656050955414\n",
      "Epoch # 17 \t\tTraining loss:  0.06159660354623878 \t Validation loss:  0.12570814623031765\n",
      "\t\tTraining Accuracy:  97.76881720430107 \t Validation Accuracy:  96.81528662420381\n",
      "Epoch # 18 \t\tTraining loss:  0.059118865470680376 \t Validation loss:  0.10590068614110351\n",
      "\t\tTraining Accuracy:  97.8763440860215 \t Validation Accuracy:  96.39065817409767\n",
      "Epoch # 19 \t\tTraining loss:  0.05934179310696488 \t Validation loss:  0.1119940219912678\n",
      "\t\tTraining Accuracy:  97.75806451612902 \t Validation Accuracy:  95.9660297239915\n"
     ]
    }
   ],
   "source": [
    "for param in vgg16.features.parameters():\n",
    "    param.requires_grad = True\n",
    "criterion = nn.BCEWithLogitsLoss()\n",
    "optimizer = optim.SGD(vgg16.parameters(), lr=0.001, momentum=0.9)\n",
    "model, history = corona(vgg16, trainloader, validloader, Epochs = 20, name = '/vgg16_BCE.pth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 808
    },
    "colab_type": "code",
    "id": "SKpI_DTwq4Im",
    "outputId": "bc4e45d5-29e8-4bd1-ec8c-10bea60785fe"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Training and Validation Accuracy')"
      ]
     },
     "execution_count": 10,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6))\n",
    "for c in ['train_loss', 'valid_loss']:\n",
    "    plt.plot(\n",
    "        history[c], label=c)\n",
    "plt.legend()\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Average Negative Log Likelihood')\n",
    "plt.title('Training and Validation Losses')\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "for c in ['train_acc', 'valid_acc']:\n",
    "    plt.plot(\n",
    "        100 * history[c], label=c)\n",
    "plt.legend()\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Average Accuracy')\n",
    "plt.title('Training and Validation Accuracy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 989
    },
    "colab_type": "code",
    "id": "Uh-OK-sVYLxN",
    "outputId": "1d57db9a-086b-4016-89cd-096b0ae261ae"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/mlxtend/plotting/plot_confusion_matrix.py:59: RuntimeWarning: invalid value encountered in true_divide\n",
      "  normed_conf_mat = conf_mat.astype('float') / total_samples\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/metrics/_classification.py:1515: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  average, \"true nor predicted\", 'F-score is', len(true_sum)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1: 0.6666666666666666\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "device = torch.device(\"cuda\")\n",
    "vgg16.to(device)\n",
    "\n",
    "pr =[]\n",
    "tl =[]\n",
    "\n",
    "with torch.no_grad():\n",
    "    for i, (inputs, classes) in enumerate(trainloader):\n",
    "        inputs = inputs.to(device)\n",
    "        classes = encoder(classes, 3)\n",
    "        classes = classes.to(device)\n",
    "        outputs = vgg16(inputs)\n",
    "        outputs[outputs >= 0.5] = 1\n",
    "        outputs[outputs < 0.5] = 0\n",
    "        for i in classes.tolist():\n",
    "            tl.append(i)\n",
    "        for j in outputs.tolist():\n",
    "            pr.append(j)\n",
    "\n",
    "    pr = np.argmax(pr, axis=1)\n",
    "    tl = np.argmax(tl, axis=1)\n",
    "\n",
    "cm = multilabel_confusion_matrix(np.array(tl),np.array(pr))\n",
    "labels=['Covid-19', 'Normal', 'Pneumonia']\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[0], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('vgg16 Training CF with BCE Loss (Matrix 0)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[1], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('vgg16 Training CF with BCE Loss (Matrix 1)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[2], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('vgg16 Training CF with BCE Loss (Matrix 2)')\n",
    "print('F1: {}'.format(f1_score(classes.data.cpu().numpy(), outputs.data.cpu().numpy(), average='macro')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 901
    },
    "colab_type": "code",
    "id": "UxPdtAlsX_wD",
    "outputId": "4409bb3a-137b-49f9-ef7f-e0f97c95664e"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1: 0.6286799620132953\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "device = torch.device(\"cuda\")\n",
    "vgg16.to(device)\n",
    "pr =[]\n",
    "tl =[]\n",
    "with torch.no_grad():\n",
    "    for i, (inputs, classes) in enumerate(validloader):\n",
    "        inputs = inputs.to(device)\n",
    "        classes = encoder(classes, 3)\n",
    "        classes = classes.to(device)\n",
    "        outputs = vgg16(inputs)\n",
    "        outputs[outputs >= 0.5] = 1\n",
    "        outputs[outputs < 0.5] = 0\n",
    "        for i in classes.tolist():\n",
    "            tl.append(i)\n",
    "        for j in outputs.tolist():\n",
    "            pr.append(j)\n",
    "\n",
    "    pr = np.argmax(pr, axis=1)\n",
    "    tl = np.argmax(tl, axis=1)\n",
    "\n",
    "cm = multilabel_confusion_matrix(np.array(tl),np.array(pr))\n",
    "\n",
    "labels=['Covid-19', 'Normal', 'Pneumonia']\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[0], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('vgg16 Training CF with BCE Loss (Matrix 0)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[1], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('vgg16 Training CF with BCE Loss (Matrix 1)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[2], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('vgg16 Training CF with BCE Loss (Matrix 2)')\n",
    "print('F1: {}'.format(f1_score(classes.data.cpu().numpy(), outputs.data.cpu().numpy(), average='macro')))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "HT5dfGKWRxIA"
   },
   "source": [
    "# Working on Resnet here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 83,
     "referenced_widgets": [
      "5b93576c6c2e48e59db4091d4b0e07de",
      "1cdb15b6773d4ad2bd955aac3c796e01",
      "8e8bfcc788a542978df651dc6d9cc54a",
      "55954b3e354c481eb62d56ed4010ec74",
      "3c0c31d73b824db2ac72cad00596508a",
      "7c4efd6c4df642ada5036db412e1ea27",
      "a92a4200bd8c47cc97c8079a379816dc",
      "a462a2e3f90047dfa6b0d9cff35eeb2b"
     ]
    },
    "colab_type": "code",
    "id": "C31abXwBLfcY",
    "outputId": "b0986451-d1f1-4fce-9d6a-e62fb9598e3f"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading: \"https://download.pytorch.org/models/resnet18-5c106cde.pth\" to /root/.cache/torch/checkpoints/resnet18-5c106cde.pth\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "5b93576c6c2e48e59db4091d4b0e07de",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=46827520), HTML(value='')))"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "resnet = models.resnet18(pretrained=True).to(device)\n",
    "resnet.fc = nn.Sequential(\n",
    "               nn.Linear(512, 770),\n",
    "               nn.ReLU(inplace=True),\n",
    "               nn.Linear(770, 3)).to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 697
    },
    "colab_type": "code",
    "id": "ujUbs38JROis",
    "outputId": "38399be8-9ba4-424b-9768-66ff31ffd2bd"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch # 0 \t\tTraining loss:  0.36141679674079735 \t Validation loss:  0.26451341696083547\n",
      "\t\tTraining Accuracy:  83.31182795698925 \t Validation Accuracy:  90.12738853503186\n",
      "Epoch # 1 \t\tTraining loss:  0.21469911449041562 \t Validation loss:  0.21567235998809337\n",
      "\t\tTraining Accuracy:  91.75806451612904 \t Validation Accuracy:  92.19745222929936\n",
      "Epoch # 2 \t\tTraining loss:  0.18679734676615478 \t Validation loss:  0.1936913788318634\n",
      "\t\tTraining Accuracy:  92.83333333333333 \t Validation Accuracy:  92.67515923566879\n",
      "Epoch # 3 \t\tTraining loss:  0.174964719711198 \t Validation loss:  0.18093329686671494\n",
      "\t\tTraining Accuracy:  93.23118279569893 \t Validation Accuracy:  93.09978768577496\n",
      "Epoch # 4 \t\tTraining loss:  0.15662231110036373 \t Validation loss:  0.165464698523283\n",
      "\t\tTraining Accuracy:  93.8763440860215 \t Validation Accuracy:  93.73673036093419\n",
      "Epoch # 5 \t\tTraining loss:  0.14990339428186417 \t Validation loss:  0.16116290539503098\n",
      "\t\tTraining Accuracy:  93.98387096774194 \t Validation Accuracy:  93.73673036093419\n",
      "Epoch # 6 \t\tTraining loss:  0.1384340904499452 \t Validation loss:  0.16013952158391476\n",
      "\t\tTraining Accuracy:  94.53763440860216 \t Validation Accuracy:  93.84288747346072\n",
      "Epoch # 7 \t\tTraining loss:  0.13657623555357615 \t Validation loss:  0.14671537429094314\n",
      "\t\tTraining Accuracy:  94.55376344086021 \t Validation Accuracy:  93.94904458598727\n",
      "Epoch # 8 \t\tTraining loss:  0.12805706625516267 \t Validation loss:  0.15058080423623324\n",
      "\t\tTraining Accuracy:  94.89784946236558 \t Validation Accuracy:  93.84288747346072\n",
      "Epoch # 9 \t\tTraining loss:  0.1269631503034652 \t Validation loss:  0.13348827455192805\n",
      "\t\tTraining Accuracy:  94.98924731182795 \t Validation Accuracy:  94.69214437367303\n",
      "Epoch # 10 \t\tTraining loss:  0.11900025683925632 \t Validation loss:  0.13970060124993325\n",
      "\t\tTraining Accuracy:  95.48387096774195 \t Validation Accuracy:  94.32059447983015\n",
      "Epoch # 11 \t\tTraining loss:  0.11452468271492068 \t Validation loss:  0.14248632192611693\n",
      "\t\tTraining Accuracy:  95.60215053763442 \t Validation Accuracy:  94.5859872611465\n",
      "Epoch # 12 \t\tTraining loss:  0.10810171089797597 \t Validation loss:  0.1362210748717189\n",
      "\t\tTraining Accuracy:  95.85483870967742 \t Validation Accuracy:  94.85138004246285\n",
      "Epoch # 13 \t\tTraining loss:  0.10645252283777773 \t Validation loss:  0.1412705896422267\n",
      "\t\tTraining Accuracy:  95.89784946236558 \t Validation Accuracy:  94.90445859872612\n",
      "Epoch # 14 \t\tTraining loss:  0.10549140492089323 \t Validation loss:  0.13848644997924567\n",
      "\t\tTraining Accuracy:  95.96774193548386 \t Validation Accuracy:  94.7452229299363\n",
      "Epoch # 15 \t\tTraining loss:  0.09874172220678673 \t Validation loss:  0.13168136794120072\n",
      "\t\tTraining Accuracy:  96.30107526881721 \t Validation Accuracy:  95.06369426751593\n",
      "Epoch # 16 \t\tTraining loss:  0.0931088711739969 \t Validation loss:  0.1369083769619465\n",
      "\t\tTraining Accuracy:  96.50537634408602 \t Validation Accuracy:  95.32908704883226\n",
      "Epoch # 17 \t\tTraining loss:  0.08664611431760426 \t Validation loss:  0.14643979109823704\n",
      "\t\tTraining Accuracy:  96.59139784946238 \t Validation Accuracy:  95.11677282377919\n",
      "Epoch # 18 \t\tTraining loss:  0.08440732665974454 \t Validation loss:  0.1474618579261005\n",
      "\t\tTraining Accuracy:  96.61827956989248 \t Validation Accuracy:  94.63906581740976\n",
      "Epoch # 19 \t\tTraining loss:  0.08179846971977464 \t Validation loss:  0.14394621653482317\n",
      "\t\tTraining Accuracy:  96.89784946236558 \t Validation Accuracy:  95.38216560509552\n"
     ]
    }
   ],
   "source": [
    "for param in resnet.parameters():\n",
    "    param.requires_grad = True\n",
    "criterion = nn.BCEWithLogitsLoss()\n",
    "optimizer = optim.SGD(resnet.parameters(), lr=0.001, momentum=0.9)\n",
    "model, history = corona(resnet, trainloader, validloader, 20, '/res18_BCE.pth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 808
    },
    "colab_type": "code",
    "id": "TcTYRa6CRbef",
    "outputId": "6055d3c6-3577-4505-ce05-eb05a2a26a4e"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Training and Validation Accuracy')"
      ]
     },
     "execution_count": 10,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6))\n",
    "for c in ['train_loss', 'valid_loss']:\n",
    "    plt.plot(\n",
    "        history[c], label=c)\n",
    "plt.legend()\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Average Negative Log Likelihood')\n",
    "plt.title('Training and Validation Losses')\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "for c in ['train_acc', 'valid_acc']:\n",
    "    plt.plot(\n",
    "        100 * history[c], label=c)\n",
    "plt.legend()\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Average Accuracy')\n",
    "plt.title('Training and Validation Accuracy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 901
    },
    "colab_type": "code",
    "id": "DeUnxM4nPe2g",
    "outputId": "4895331b-3e03-48d1-d991-34c63805fd00"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1: 0.9642579642579642\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "device = torch.device(\"cuda\")\n",
    "resnet.to(device)\n",
    "\n",
    "pr =[]\n",
    "tl =[]\n",
    "\n",
    "with torch.no_grad():\n",
    "    for i, (inputs, classes) in enumerate(trainloader):\n",
    "        inputs = inputs.to(device)\n",
    "        classes = encoder(classes, 3)\n",
    "        classes = classes.to(device)\n",
    "        outputs = resnet(inputs)\n",
    "        outputs[outputs >= 0.5] = 1\n",
    "        outputs[outputs < 0.5] = 0\n",
    "        for i in classes.tolist():\n",
    "            tl.append(i)\n",
    "        for j in outputs.tolist():\n",
    "            pr.append(j)\n",
    "\n",
    "    pr = np.argmax(pr, axis=1)\n",
    "    tl = np.argmax(tl, axis=1)\n",
    "\n",
    "cm = multilabel_confusion_matrix(np.array(tl),np.array(pr))\n",
    "labels=['Covid-19', 'Normal', 'Pneumonia']\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[0], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('Renset-18 Training CF with BCE Loss (Matrix 0)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[1], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('Resnet-18 Training CF with BCE Loss (Matrix 1)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[2], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('Resnet-18 Training CF with BCE Loss (Matrix 2)')\n",
    "print('F1: {}'.format(f1_score(classes.data.cpu().numpy(), outputs.data.cpu().numpy(), average='macro')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 989
    },
    "colab_type": "code",
    "id": "hoVRpHF2Penu",
    "outputId": "09037338-2a8b-4587-d82c-f604deee535e"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/mlxtend/plotting/plot_confusion_matrix.py:59: RuntimeWarning: invalid value encountered in true_divide\n",
      "  normed_conf_mat = conf_mat.astype('float') / total_samples\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/metrics/_classification.py:1515: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  average, \"true nor predicted\", 'F-score is', len(true_sum)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1: 0.5643648763853367\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "device = torch.device(\"cuda\")\n",
    "resnet.to(device)\n",
    "pr =[]\n",
    "tl =[]\n",
    "\n",
    "with torch.no_grad():\n",
    "    for i, (inputs, classes) in enumerate(validloader):\n",
    "        inputs = inputs.to(device)\n",
    "        classes = encoder(classes, 3)\n",
    "        classes = classes.to(device)\n",
    "        outputs = resnet(inputs)\n",
    "        outputs[outputs >= 0.5] = 1\n",
    "        outputs[outputs < 0.5] = 0\n",
    "        for i in classes.tolist():\n",
    "            tl.append(i)\n",
    "        for j in outputs.tolist():\n",
    "            pr.append(j)\n",
    "\n",
    "    pr = np.argmax(pr, axis=1)\n",
    "    tl = np.argmax(tl, axis=1)\n",
    "\n",
    "cm = multilabel_confusion_matrix(np.array(tl),np.array(pr))\n",
    "labels=['Covid-19', 'Normal', 'Pneumonia']\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[0], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('Renset-18 Training CF with BCE Loss (Matrix 0)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[1], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('Resnet-18 Training CF with BCE Loss (Matrix 1)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[2], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('Resnet-18 Training CF with BCE Loss (Matrix 2)')\n",
    "print('F1: {}'.format(f1_score(classes.data.cpu().numpy(), outputs.data.cpu().numpy(), average='macro')))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "2Il4_ZWoLzXT"
   },
   "source": [
    "# Task2 Using Focal Loss"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "NskGu0PMLxyi"
   },
   "source": [
    "# VGG working here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "7QvhyvFNM7AH"
   },
   "outputs": [],
   "source": [
    "def focal_loss(targets,logits,eps,l):\n",
    "  ce_loss = torch.nn.functional.binary_cross_entropy_with_logits(logits, targets, reduction= 'none')\n",
    "  pt = torch.exp(-ce_loss)\n",
    "  loss = (eps * (1-pt)**l * ce_loss).mean()\n",
    "  return loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "DD5ZLmocMv2S"
   },
   "outputs": [],
   "source": [
    "def corona_with_focal(model, trainloader, validloader, Epochs, name):\n",
    "    device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "    model.to(device)\n",
    "    model.train()\n",
    "    history = []\n",
    "    for epoch in range(Epochs):  # loop over the dataset multiple times\n",
    "        total_train = 0\n",
    "        train_loss = 0.0\n",
    "        valid_loss = 0.0\n",
    "        running_loss = 0.0\n",
    "        correct = 0\n",
    "        total = 0\n",
    "        vcorrect = 0\n",
    "        predicted = []\n",
    "        train_acc = 0\n",
    "        valid_acc = 0\n",
    "        vtotal = 0\n",
    "        # pbar = tqdm()\n",
    "        for i, data in enumerate(trainloader):\n",
    "            inputs, labels = data\n",
    "            hot_labels = encoder(labels, 3)\n",
    "            inputs, hot_labels = inputs.to(device), hot_labels.to(device)\n",
    "            # zero the parameter gradients\n",
    "            optimizer.zero_grad()\n",
    "            outputs = model(inputs) \n",
    "            loss = focal_loss(hot_labels, outputs, 0.25, 2 )   #----> compute loss\n",
    "            loss.backward()                     #----> backward pass\n",
    "            optimizer.step()                   #----> weights update\n",
    "            outputs[outputs >= 0.5] = 1\n",
    "            outputs[outputs < 0.5] = 0\n",
    "            correct += (outputs == hot_labels).sum().item()\n",
    "            total += hot_labels.size(0)\n",
    "            running_loss += loss.item()\n",
    "\n",
    "        for i, data in enumerate(validloader):\n",
    "            inputs, labels = data\n",
    "            hot_labels = encoder(labels, 3)\n",
    "            inputs, hot_labels = inputs.to(device), hot_labels.to(device)\n",
    "            outputs = model(inputs) \n",
    "            loss = loss = focal_loss(hot_labels, outputs, 0.2, 2 )\n",
    "            valid_loss += loss.item()\n",
    "            outputs[outputs >= 0.5] = 1\n",
    "            outputs[outputs < 0.5] = 0\n",
    "            vcorrect += (outputs == hot_labels).sum().item()\n",
    "            vtotal += hot_labels.size(0)\n",
    "\n",
    "        train_loss = running_loss / len(trainloader)\n",
    "        valid_loss = valid_loss / len(validloader)\n",
    "        train_acc = correct / total\n",
    "        valid_acc = vcorrect / vtotal\n",
    "\n",
    "        history.append([train_loss, valid_loss, train_acc, valid_acc])\n",
    "        print('Epoch #', epoch, '\\t\\tTraining loss: ', train_loss, '\\t Validation loss: ', valid_loss)\n",
    "        print('\\t\\tTraining Accuracy: ', (100 * train_acc)/3, '\\t Validation Accuracy: ', (100 * valid_acc/3))\n",
    "    history = pd.DataFrame(history, columns=['train_loss', 'valid_loss', 'train_acc', 'valid_acc'])\n",
    "    torch.save(model.state_dict(), './gdrive/My Drive/' + name)\n",
    "    return model, history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 83,
     "referenced_widgets": [
      "3a576f983d3045668558cd90c9932bac",
      "30ba326aaf7d45fbaaa2b6ffcc4c533c",
      "499dd9a0a93e403f8a5faf7c2745e8a8",
      "7f71af1d633f47caa60a3ecc89059e9a",
      "69ca34e5c719451c8f580076adf018a4",
      "61c1a600f827424a87d056b959776229",
      "cb45bf5ccfb04a94bc2aa82db8b74c9c",
      "1b81b78fd2474b3d9c0153a8a2c8648c"
     ]
    },
    "colab_type": "code",
    "id": "tnxq_taCQuUA",
    "outputId": "df315b9d-588e-43a4-f164-069e76e39428"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading: \"https://download.pytorch.org/models/vgg16-397923af.pth\" to /root/.cache/torch/checkpoints/vgg16-397923af.pth\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "3a576f983d3045668558cd90c9932bac",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "HBox(children=(IntProgress(value=0, max=553433881), HTML(value='')))"
      ]
     },
     "metadata": {
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "vgg16 = models.vgg16(pretrained=True).to(device)\n",
    "vgg16.classifier = nn.Sequential(\n",
    "               nn.Linear(25088, 770),\n",
    "               nn.ReLU(inplace=True),\n",
    "               nn.Linear(770, 770),\n",
    "               nn.ReLU(inplace=True),\n",
    "               nn.Linear(770, 3)).to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 697
    },
    "colab_type": "code",
    "id": "pIVXJw-lMRfs",
    "outputId": "34b8c0ec-2867-4b36-8d4c-646f667afb33"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch # 0 \t\tTraining loss:  0.008089171531706204 \t Validation loss:  0.007087351038353518\n",
      "\t\tTraining Accuracy:  94.26881720430107 \t Validation Accuracy:  93.84288747346072\n",
      "Epoch # 1 \t\tTraining loss:  0.008069793276066325 \t Validation loss:  0.006988990237005055\n",
      "\t\tTraining Accuracy:  94.20430107526882 \t Validation Accuracy:  93.47133757961784\n",
      "Epoch # 2 \t\tTraining loss:  0.007919748719378384 \t Validation loss:  0.007284316438017413\n",
      "\t\tTraining Accuracy:  94.22580645161291 \t Validation Accuracy:  94.47983014861995\n",
      "Epoch # 3 \t\tTraining loss:  0.007773030222844831 \t Validation loss:  0.006761748506687581\n",
      "\t\tTraining Accuracy:  94.3494623655914 \t Validation Accuracy:  94.37367303609341\n",
      "Epoch # 4 \t\tTraining loss:  0.007630891913725736 \t Validation loss:  0.006785229744855315\n",
      "\t\tTraining Accuracy:  94.48387096774194 \t Validation Accuracy:  94.05520169851381\n",
      "Epoch # 5 \t\tTraining loss:  0.007575368190654698 \t Validation loss:  0.006606836523860693\n",
      "\t\tTraining Accuracy:  94.53225806451614 \t Validation Accuracy:  94.26751592356688\n",
      "Epoch # 6 \t\tTraining loss:  0.007187266004170992 \t Validation loss:  0.0065726540167815985\n",
      "\t\tTraining Accuracy:  94.81720430107528 \t Validation Accuracy:  94.69214437367303\n",
      "Epoch # 7 \t\tTraining loss:  0.007513767375956415 \t Validation loss:  0.006445791851729154\n",
      "\t\tTraining Accuracy:  94.6505376344086 \t Validation Accuracy:  94.16135881104036\n",
      "Epoch # 8 \t\tTraining loss:  0.007420746581364884 \t Validation loss:  0.006515342567581683\n",
      "\t\tTraining Accuracy:  94.73655913978496 \t Validation Accuracy:  94.4267515923567\n",
      "Epoch # 9 \t\tTraining loss:  0.007056309497727984 \t Validation loss:  0.006653705833014101\n",
      "\t\tTraining Accuracy:  94.84408602150536 \t Validation Accuracy:  94.05520169851381\n",
      "Epoch # 10 \t\tTraining loss:  0.006915585777587881 \t Validation loss:  0.006749093462713063\n",
      "\t\tTraining Accuracy:  95.0 \t Validation Accuracy:  94.21443736730362\n",
      "Epoch # 11 \t\tTraining loss:  0.006821534313146293 \t Validation loss:  0.00663052995223552\n",
      "\t\tTraining Accuracy:  95.06451612903226 \t Validation Accuracy:  95.06369426751593\n",
      "Epoch # 12 \t\tTraining loss:  0.007004726124560153 \t Validation loss:  0.006237517378758639\n",
      "\t\tTraining Accuracy:  94.9731182795699 \t Validation Accuracy:  95.06369426751593\n",
      "Epoch # 13 \t\tTraining loss:  0.006810687071302925 \t Validation loss:  0.006059375038603321\n",
      "\t\tTraining Accuracy:  95.18279569892474 \t Validation Accuracy:  95.06369426751593\n",
      "Epoch # 14 \t\tTraining loss:  0.006480663912802858 \t Validation loss:  0.006189244682900608\n",
      "\t\tTraining Accuracy:  95.41935483870968 \t Validation Accuracy:  94.7452229299363\n",
      "Epoch # 15 \t\tTraining loss:  0.006585863459082416 \t Validation loss:  0.0061159379780292514\n",
      "\t\tTraining Accuracy:  95.19354838709678 \t Validation Accuracy:  95.06369426751593\n",
      "Epoch # 16 \t\tTraining loss:  0.006238507407539783 \t Validation loss:  0.006652492610737681\n",
      "\t\tTraining Accuracy:  95.41935483870968 \t Validation Accuracy:  94.63906581740976\n",
      "Epoch # 17 \t\tTraining loss:  0.006153976416320915 \t Validation loss:  0.006921608524862677\n",
      "\t\tTraining Accuracy:  95.54301075268818 \t Validation Accuracy:  93.6836518046709\n",
      "Epoch # 18 \t\tTraining loss:  0.006110587440246294 \t Validation loss:  0.006236499838996679\n",
      "\t\tTraining Accuracy:  95.71505376344088 \t Validation Accuracy:  94.79830148619958\n",
      "Epoch # 19 \t\tTraining loss:  0.006215786694587429 \t Validation loss:  0.0065417987178079786\n",
      "\t\tTraining Accuracy:  95.47849462365592 \t Validation Accuracy:  95.01061571125267\n"
     ]
    }
   ],
   "source": [
    "for param in vgg16.parameters():\n",
    "    param.requires_grad = True\n",
    "optimizer = optim.SGD(vgg16.parameters(), lr=0.001, momentum=0.9)\n",
    "model, history = corona_with_focal(vgg16, trainloader, validloader, Epochs = 20, name = '/vgg16_Focal_Loss.pth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 808
    },
    "colab_type": "code",
    "id": "2voqhKzAMWTP",
    "outputId": "bc4b67cc-6e81-4742-b451-d8b97a2b6d36"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Training and Validation Accuracy')"
      ]
     },
     "execution_count": 19,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 6))\n",
    "for c in ['train_loss', 'valid_loss']:\n",
    "    plt.plot(\n",
    "        history[c], label=c)\n",
    "plt.legend()\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Average Negative Log Likelihood')\n",
    "plt.title('Training and Validation Losses')\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "for c in ['train_acc', 'valid_acc']:\n",
    "    plt.plot(\n",
    "        100 * history[c], label=c)\n",
    "plt.legend()\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Average Accuracy')\n",
    "plt.title('Training and Validation Accuracy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 901
    },
    "colab_type": "code",
    "id": "Fv9tylr3Q15l",
    "outputId": "e72e3007-9111-494e-ed7a-5369575fa5b3"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1: 1.0\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "device = torch.device(\"cuda\")\n",
    "vgg16.to(device)\n",
    "pr =[]\n",
    "tl =[]\n",
    "with torch.no_grad():\n",
    "    for i, (inputs, classes) in enumerate(trainloader):\n",
    "        inputs = inputs.to(device)\n",
    "        classes = encoder(classes, 3)\n",
    "        classes = classes.to(device)\n",
    "        outputs = vgg16(inputs)\n",
    "        outputs[outputs >= 0.5] = 1\n",
    "        outputs[outputs < 0.5] = 0\n",
    "        for i in classes.tolist():\n",
    "            tl.append(i)\n",
    "        for j in outputs.tolist():\n",
    "            pr.append(j)\n",
    "\n",
    "    pr = np.argmax(pr, axis=1)\n",
    "    tl = np.argmax(tl, axis=1)\n",
    "\n",
    "cm = multilabel_confusion_matrix(np.array(tl),np.array(pr))\n",
    "\n",
    "labels=['Covid-19', 'Normal', 'Pneumonia']\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[0], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('vgg16 Training CF with BCE Loss (Matrix 0)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[1], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('vgg16 Training CF with BCE Loss (Matrix 1)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[2], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('vgg16 Training CF with BCE Loss (Matrix 2)')\n",
    "print('F1: {}'.format(f1_score(classes.data.cpu().numpy(), outputs.data.cpu().numpy(), average='macro')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 989
    },
    "colab_type": "code",
    "id": "vOfqvCVPQ1yD",
    "outputId": "f423ceba-4d4e-4719-aadd-ad7b81406f96"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/mlxtend/plotting/plot_confusion_matrix.py:59: RuntimeWarning: invalid value encountered in true_divide\n",
      "  normed_conf_mat = conf_mat.astype('float') / total_samples\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/metrics/_classification.py:1515: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  average, \"true nor predicted\", 'F-score is', len(true_sum)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1: 0.6010256410256409\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "device = torch.device(\"cuda\")\n",
    "vgg16.to(device)\n",
    "pr =[]\n",
    "tl =[]\n",
    "with torch.no_grad():\n",
    "    for i, (inputs, classes) in enumerate(validloader):\n",
    "        inputs = inputs.to(device)\n",
    "        classes = encoder(classes, 3)\n",
    "        classes = classes.to(device)\n",
    "        outputs = vgg16(inputs)\n",
    "        outputs[outputs >= 0.5] = 1\n",
    "        outputs[outputs < 0.5] = 0\n",
    "        for i in classes.tolist():\n",
    "            tl.append(i)\n",
    "        for j in outputs.tolist():\n",
    "            pr.append(j)\n",
    "\n",
    "    pr = np.argmax(pr, axis=1)\n",
    "    tl = np.argmax(tl, axis=1)\n",
    "\n",
    "cm = multilabel_confusion_matrix(np.array(tl),np.array(pr))\n",
    "\n",
    "labels=['Covid-19', 'Normal', 'Pneumonia']\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[0], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('vgg16 Training CF with BCE Loss (Matrix 0)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[1], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('vgg16 Training CF with BCE Loss (Matrix 1)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[2], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('vgg16 Training CF with BCE Loss (Matrix 2)')\n",
    "print('F1: {}'.format(f1_score(classes.data.cpu().numpy(), outputs.data.cpu().numpy(), average='macro')))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "UGI3MPmVM_qI"
   },
   "source": [
    "# Resnet Start here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "pBBpTVSNNIez"
   },
   "outputs": [],
   "source": [
    "device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
    "device\n",
    "resnet = models.resnet18(pretrained=True).to(device)\n",
    "resnet.fc = nn.Sequential(\n",
    "               nn.Linear(512, 770),\n",
    "               nn.ReLU(inplace=True),\n",
    "               nn.Linear(770, 770),\n",
    "               nn.ReLU(inplace=True),\n",
    "               nn.Linear(770, 3)).to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 697
    },
    "colab_type": "code",
    "id": "JLhPgt3_NIQj",
    "outputId": "01665926-fd8d-404c-b78e-649fd2921bc5"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch # 0 \t\tTraining loss:  0.03410597476801 \t Validation loss:  0.024902501329779624\n",
      "\t\tTraining Accuracy:  65.5967741935484 \t Validation Accuracy:  65.18046709129511\n",
      "Epoch # 1 \t\tTraining loss:  0.028705528399609413 \t Validation loss:  0.02321017412468791\n",
      "\t\tTraining Accuracy:  65.75268817204301 \t Validation Accuracy:  65.44585987261146\n",
      "Epoch # 2 \t\tTraining loss:  0.026492132766882785 \t Validation loss:  0.02168683297932148\n",
      "\t\tTraining Accuracy:  68.12903225806453 \t Validation Accuracy:  67.72823779193207\n",
      "Epoch # 3 \t\tTraining loss:  0.024522353645375708 \t Validation loss:  0.02016274267807603\n",
      "\t\tTraining Accuracy:  72.51075268817205 \t Validation Accuracy:  71.60297239915074\n",
      "Epoch # 4 \t\tTraining loss:  0.022677082299571678 \t Validation loss:  0.018612697999924422\n",
      "\t\tTraining Accuracy:  75.66129032258065 \t Validation Accuracy:  76.32696390658174\n",
      "Epoch # 5 \t\tTraining loss:  0.020732970596243117 \t Validation loss:  0.01754886470735073\n",
      "\t\tTraining Accuracy:  77.98387096774194 \t Validation Accuracy:  77.91932059447983\n",
      "Epoch # 6 \t\tTraining loss:  0.019220014698035325 \t Validation loss:  0.016065345052629708\n",
      "\t\tTraining Accuracy:  80.75268817204301 \t Validation Accuracy:  81.42250530785562\n",
      "Epoch # 7 \t\tTraining loss:  0.018032546702426735 \t Validation loss:  0.01511834324337542\n",
      "\t\tTraining Accuracy:  84.04301075268818 \t Validation Accuracy:  83.86411889596603\n",
      "Epoch # 8 \t\tTraining loss:  0.017035069918624825 \t Validation loss:  0.01435578060336411\n",
      "\t\tTraining Accuracy:  85.96774193548389 \t Validation Accuracy:  85.61571125265392\n",
      "Epoch # 9 \t\tTraining loss:  0.016277939071590752 \t Validation loss:  0.013887819228693843\n",
      "\t\tTraining Accuracy:  87.29032258064517 \t Validation Accuracy:  87.31422505307854\n",
      "Epoch # 10 \t\tTraining loss:  0.015541624841904364 \t Validation loss:  0.013634121231734752\n",
      "\t\tTraining Accuracy:  88.13440860215053 \t Validation Accuracy:  87.15498938428874\n",
      "Epoch # 11 \t\tTraining loss:  0.015120563524554377 \t Validation loss:  0.013390300329774618\n",
      "\t\tTraining Accuracy:  88.91935483870968 \t Validation Accuracy:  88.16348195329086\n",
      "Epoch # 12 \t\tTraining loss:  0.014726598768677447 \t Validation loss:  0.012420699442736804\n",
      "\t\tTraining Accuracy:  89.4247311827957 \t Validation Accuracy:  88.1104033970276\n",
      "Epoch # 13 \t\tTraining loss:  0.01444053115832053 \t Validation loss:  0.012587292352691293\n",
      "\t\tTraining Accuracy:  89.5752688172043 \t Validation Accuracy:  88.21656050955414\n",
      "Epoch # 14 \t\tTraining loss:  0.013998727345378282 \t Validation loss:  0.012548012170009315\n",
      "\t\tTraining Accuracy:  90.05376344086022 \t Validation Accuracy:  88.74734607218683\n",
      "Epoch # 15 \t\tTraining loss:  0.013711432055042116 \t Validation loss:  0.012486210418865084\n",
      "\t\tTraining Accuracy:  90.41397849462366 \t Validation Accuracy:  89.06581740976645\n",
      "Epoch # 16 \t\tTraining loss:  0.013560696348989593 \t Validation loss:  0.012139338091947139\n",
      "\t\tTraining Accuracy:  90.82258064516128 \t Validation Accuracy:  89.33121019108279\n",
      "Epoch # 17 \t\tTraining loss:  0.013400919713828828 \t Validation loss:  0.011931602703407406\n",
      "\t\tTraining Accuracy:  90.61827956989248 \t Validation Accuracy:  89.33121019108279\n",
      "Epoch # 18 \t\tTraining loss:  0.013358736729979054 \t Validation loss:  0.012347312388010323\n",
      "\t\tTraining Accuracy:  90.75806451612902 \t Validation Accuracy:  89.17197452229298\n",
      "Epoch # 19 \t\tTraining loss:  0.012992877640386986 \t Validation loss:  0.011726145981810987\n",
      "\t\tTraining Accuracy:  90.99462365591398 \t Validation Accuracy:  90.07430997876857\n"
     ]
    }
   ],
   "source": [
    "for param in resnet.parameters():\n",
    "    param.requires_grad = True\n",
    "optimizer = optim.SGD(resnet.parameters(), lr=0.001, momentum=0.9)\n",
    "model, history = corona_with_focal(resnet, trainloader, validloader, 20, '/res18_Focal_Loss.pth')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 808
    },
    "colab_type": "code",
    "id": "dmiGBMKPNGRK",
    "outputId": "0ee1a983-d705-4e3b-a8e0-d61d6a7a174f"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Training and Validation Accuracy')"
      ]
     },
     "execution_count": 24,
     "metadata": {
      "tags": []
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "for c in ['train_loss', 'valid_loss']:\n",
    "    plt.plot(\n",
    "        history[c], label=c)\n",
    "plt.legend()\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Average Negative Log Likelihood')\n",
    "plt.title('Training and Validation Losses')\n",
    "\n",
    "plt.figure(figsize=(8, 6))\n",
    "for c in ['train_acc', 'valid_acc']:\n",
    "    plt.plot(\n",
    "        100 * history[c], label=c)\n",
    "plt.legend()\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('Average Accuracy')\n",
    "plt.title('Training and Validation Accuracy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 989
    },
    "colab_type": "code",
    "id": "_nXEKryNNulE",
    "outputId": "74cbdd1c-7d7b-48ed-cf60-6bc7b7e51994"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/mlxtend/plotting/plot_confusion_matrix.py:59: RuntimeWarning: invalid value encountered in true_divide\n",
      "  normed_conf_mat = conf_mat.astype('float') / total_samples\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/metrics/_classification.py:1515: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  average, \"true nor predicted\", 'F-score is', len(true_sum)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1: 0.5915032679738562\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "device = torch.device(\"cuda\")\n",
    "resnet.to(device)\n",
    "\n",
    "pr =[]\n",
    "tl =[]\n",
    "\n",
    "with torch.no_grad():\n",
    "    for i, (inputs, classes) in enumerate(trainloader):\n",
    "        inputs = inputs.to(device)\n",
    "        classes = encoder(classes, 3)\n",
    "        classes = classes.to(device)\n",
    "        outputs = resnet(inputs)\n",
    "        outputs[outputs >= 0.5] = 1\n",
    "        outputs[outputs < 0.5] = 0\n",
    "        for i in classes.tolist():\n",
    "            tl.append(i)\n",
    "        for j in outputs.tolist():\n",
    "            pr.append(j)\n",
    "\n",
    "    pr = np.argmax(pr, axis=1)\n",
    "    tl = np.argmax(tl, axis=1)\n",
    "\n",
    "cm = multilabel_confusion_matrix(np.array(tl),np.array(pr))\n",
    "labels=['Covid-19', 'Normal', 'Pneumonia']\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[0], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('Renset-18 Training CF with BCE Loss (Matrix 0)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[1], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('Resnet-18 Training CF with BCE Loss (Matrix 1)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[2], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('Resnet-18 Training CF with BCE Loss (Matrix 2)')\n",
    "print('F1: {}'.format(f1_score(classes.data.cpu().numpy(), outputs.data.cpu().numpy(), average='macro')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 989
    },
    "colab_type": "code",
    "id": "TTVLmAz-NuaA",
    "outputId": "a5c23910-55cd-4e47-8cc3-70647de9ec6a"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/mlxtend/plotting/plot_confusion_matrix.py:59: RuntimeWarning: invalid value encountered in true_divide\n",
      "  normed_conf_mat = conf_mat.astype('float') / total_samples\n",
      "/usr/local/lib/python3.6/dist-packages/sklearn/metrics/_classification.py:1515: UndefinedMetricWarning: F-score is ill-defined and being set to 0.0 in labels with no true nor predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  average, \"true nor predicted\", 'F-score is', len(true_sum)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "F1: 0.5393939393939394\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAATQAAAEhCAYAAADxmly3AAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+j8jraAAAgAElEQVR4nO3dd5wV1fnH8c93d1mKUsVCUbGANKWDgJ2i2MAumliRaDSxJDFqjAm/YDRRE5PYgiViL9iNEcSCAQUERRSQiIrSpEnvuzy/P2YWLsve3bswy+ydfd685sWduWfOnLk797nnnJk5IzPDOeeSICfuAjjnXFQ8oDnnEsMDmnMuMTygOecSwwOacy4xPKA55xLDA9ouJGmapGOiTlvZSbpJ0kOlvH+RpLG7skyZknSMpLlxl6Mkkn4i6e6Ytv2ApN9WQL53SbpihzMws1InYDawDlgNfA88Cuxe1noVNQEXAWPLSJMPjAjLbsAxxd6vDjwALAR+AF4DmpSQz37hfhdNBqxJmT8yrs9hJz/DRsDDwAJgFfAFMATYLXy/+H4uj3DbzcL888rzNy3lmCyaGlfQZ3UMMLeU9w04OIa/YT4wp+i4TflcPymWriGwEZidYb7l+lvsYLlL+242Cvcrf0fyz7SGdoqZ7Q60BzoAN2a4XpzGAj8iCMLFXQ10Bw4DGgPLgH8UT2Rm35nZ7kVTuLhdyrL/FqWVlBf5HlQASQ2AD4GaQHczqw30AeoBB6UkTd3PejEUtSynpP5tzGx+3AXaxfoDX5jZvGLLa0lqmzJ/HvBNlBuWlLuTWaT9bprZAoIf2FN3JONyNTnN7HtgJEFgA0DS4ZI+kLRc0qepzaSwKfG1pFWSvpF0fsrysZLulLQsfK9fynp1JT0saYGkeZKGSsqV1IqgZtVd0mpJy9OUc6OZ3W1mY4HCEpIcAIw0s4Vmth54FmhTns8i3Idxkv4qaSnwe0kHSXpH0lJJSyQ9KaleyjqzJfUOX/9e0nOSHgs/n2mSOu9g2o6SPgnfe17Ss5KGpin6dQS1sh+Z2ezw85pjZleb2dRyfgbfSuoUvj5fkklqE85fKunllPI/Ea72fvj/8vBv2D0lvxKPh3KUp7qkuyXND6e7JVVPeb+/pCmSVkr6StIJ4fKLJc0IP7+vJf2kvNsuoSx1w7/X4vBzullSTvjewZLGSFoRHifPhssVHk+LwjJ+Viw4peoHjClh+ePAhSnzFwCPFSvbDeH+r5I0XdJp4fISv1+SHpV0v6Q3JK0Bjg2XDQ3f/7WkCQp/1CVdER6jNYoXLoPvJsB7wElp3itVuQKapKYEH+SscL4J8G9gKNAA+CXwgqQ9Je0G/B3oF9YCegBTUrLrBswkqBL/GXhYksL3HgUKgIMJaoR9gUFmNgO4HPhwJ2sODwM9JTWWVAs4H/jPDuTTDfga2Bu4FRBwG0GtrxWwL/D7UtY/FXiGoHb0KnBPedNKygdeIvjMGgBPA6eVkk9v4EUz21zajmVoDEGTDOBogs/iqJT5kr5wRe/XC/+GH4bzpR0PmfoNcDjBD247oCtwM4CkrgRf7F8RfIZHETR7ABYBJwN1gIuBv0rqWM5tF/cPoC5wIMFncUGYN8AfgFFAfaApW1sHfcNytQjXPRtYmib/Qwk+r+KeAM4NKwCtgd2BCcXSfAUcGW5jCPCEpEZlfL/OIzjGaxPUsFLdAWwAbpbUHPgjwQ/m+jRlL8sMgr9f+WXQ5p1N0EexiqDN+zbBwQjwa+DxYulHEvxC7AYsB84AapbQTp+VMl8rzHsfguCwIXUdYCDw7o608YG5bN9Or0sQHIwgcH4CNMggry39JWE5visj/QBS+jTCz7J3+Pr3wOiU91oD68qbluALMA9QyvtjgaFpyvQlcHkG+7ky/PstB/6eJt2lwKvh6xnAIOCZcP5boGNK+Z8IXzej5D60Eo+HMo7JovK9HC7/CjgxJd3xhH1HwD+Bv2Z4zLwMXB2+PoZy9qEBuQT9Vq1Tlv0EeC98/RgwDGhabL3jgP8RBOWcMsr4JXBCyvyWzxUYHe777QRBvjel9KERVDT6p/t+EfxYPlbCsqHFtv9DeBzcuKPfzXB5H+DrTPIoPmVaQxtgQS3rGKAlwa8owP7AWQqam8vDKuoRQCMzWwOcQxDxF0j6t6SWKXluaT+b2drw5e5hntXCdYry/CewV0kFk7RfWD1eLWl1hvtzL8GJgT0IAu+L7FgNbU6xsuwt6RkFzeSVBL+WDUteFdi2D2EtUEPp++LSpW0MzLPwSCipXMUsJeh4LUtHM6sXTj9Pk2YMcKSkRgRf4ucIar7NCH40pqRZryTpjod0BqSUb0C4rDFBIC3ybbgMgtryVyVlJKmfpPGSfgiPtxMp/e9WloYEx3DxsjQJX19PUJufGDbNLgEws3cIat73AoskDZNUJ802lhHUlkryGEFgGkjQBN2GpAvCpnfR96stZe9vaccUFnRfvEsQ2O4tI6+y1Cb4oSq38vahjSGIzHeGi+YQ1NDqpUy7mdntYfqRZtaH4Av0BfBgBpuZQ1BDa5iSZx0zK+rj2mZ4ECu5474s7YFHzewHM9tAUOXvKqm8B3HxoUr+GC471MzqEHR8lrfZVF4LgCbFmmf7lpJ+NHBaUX/OzjCzWQTB9WfA+2a2kiAwDSb4lS+pWVuRw7vMJ/hBLLJfuAyC4+qg4iuEfWwvEBzTe1vQzHqDnfu7LQE2lVCWeRD0RZvZZWbWmKDmdp+kg8P3/m5mnQhq4S0ImsglmRq+X5IXCPqgvjaz71LfkLQ/wffwKmCPcH8/Z+v+pvv7lPp3k3QSwYm2twmaoDujFfDpjqy4Iwf13UAfSe0IaiCnSDo+bLPXUHDdTtOwttI/7EvbQNBEKLPfxoKzHKOAuyTVkZSjoLP96DDJQqBp2HeUloIO4qJOyfywbEV/tI+AC8KO22rAT4H5ZraknJ9FcbUJ9nNF2L+Y7mCM0ocEnatXScqT1J+g7yidvxD0FQ0PD24kNZH0F0mH7cD2xxB8OYr6y94rNl/cYoLj4MAd2FZZnibox9kz/HG6heAYhaDf9GJJvcJjqknYYsgnqK0vBgoUnIzoW87tFh1fNVKOueeAWyXVDj/n64rKIumssD8agpqWAZsldZHULTwm1wDrSf+deYOgb247YevoOIIugOJ2C7e3OCzLxQQ1tCIZfb9ShZ/1Q+H2LiSICSeWkr607yYE+7UjLabyBzQzW0xQpb3FzOYQnD6+ieADmkPwJc4Jp+sIfiF/CAuZ6QVzFxAcaNMJ/uAj2NpMegeYBnwvqbQANJPgWqUmBP1669j6i/lLgoPly7DcJ1J6R3qmhgAdgRUEJ0tejCDPUpnZRuB0gv6s5QS1wtcJfkRKSv8DwQmaTcAESasIflVXEJ7sKacxBIH8/TTzxbe/lqBzeVzY5Dl8B7aZzlBgEkHt5TPg43AZZjaRsMOfYF/HAPub2Srg5wQBaBlB5/er5dzuNILjq2i6mKDWuobgRMlY4CngkTB9F4LPfnW4ravN7GuCH5oHw3J8S9A9kK628xrQUlLjkt40s0lmtl0T28ymA3cR/BAuJDi5MC4lSabfr1TDgFfM7A0zW0pwLD4kaY806dN+N8Pui9YE/Zjlpm27XlwSSJoAPGBm/4q7LK7iSBpMcOLhmrjLEhVJdwFfmdl9O7S+B7TsFzbHZxL03ZxPcC3RgWHz3bkqIyuubndlOoSgybQbQRPnTA9mriryGppzLjF8tA3nXGJ4QHPOJYYHNOdcYnhAc84lhgc051xieEBzziWGBzTnXGJ4QHPOJYYHNOdcYnhAc85VapKulvR5OBhmqTfie0BzzlVaCh4ScxnBGH/tgJOLBsMsiQc051xl1gqYYGZrzayAYBy709MlzqrRNvJq1bVqdfeOuxiuHFo3TjckvquMvv12NkuWLNmpYeNz6+xvVrAuo7S2bvE0gsFWiwwzs2Ep858TjPy7B8FAkCcSDOJZoqwKaNXq7s2Bl5T2pDdX2YwbUt7RrF2cenbrXHaiMljBOqofcnZGaddPuXe9maXdqJnNkPQngmH51xA8eCfd8zy9yemci5pAOZlNGTCzh82sk5kdRTA8+f/Spc2qGppzLgsIyMmNLjtpLzNbJGk/gv6ztM+h8IDmnIteuR96X6oXwj60TcCVZpb2mZ0e0JxzEVPGzclMmNmRmab1gOaci160NbSMeUBzzkVLRFpDKw8PaM65iMlraM65BInwLGd5eEBzzkUs2pMC5eEBzTkXLeFNTudcgngNzTmXDN7kdM4lhYBcPyngnEsK70NzziWDNzmdc0niNTTnXGJ4Dc05lwjyW5+cc0nitz4555LBTwo455LEm5zOuUTw8dCcc8nhTU7nXJL4SQHnXGJ4H5pzLhEUX5PTn5zunIte0cW1ZU0ZZaVrJU2T9LmkpyXVSJfWA5pzLnKSMpoyyKcJ8HOgs5m1BXKBc9Ol9yancy5SwQjckfah5QE1JW0CagHzS0vonHPRkVBOxgGtoaRJKfPDzGxY0YyZzZN0J/AdsA4YZWaj0mXmAc05F7ly1NCWmFnnUvKpD/QHDgCWA89L+pGZPVFSeu9Dc85FLqo+NKA38I2ZLTazTcCLQI90ib2G5pyLXIR9aN8Bh0uqRdDk7AVMSpfYa2jOuWipHFMZzGwCMAL4GPiMIGYNS5fea2jOuUiJjJuTGTGz3wG/yyStBzTnXORycvzmdOdcQkR8HVrGPKA556KVYf9YRfCA5pyLnNfQnHOJEPVJgfLwgOaci1w5bn2KlAc051y05E1O51yCeECrgpo1rMVd5x62Zb5p/Vrc8/YsHv/guxhL5UozZ84cBl18AYsWLUQSl1w6mKt+fnXcxap0PKBVQbOXrOWMe8YDkCN499dHM3r6ophL5UqTl5fH7X++iw4dO7Jq1Sp6dOtEr959aNW6ddxFqzTiPCng93JWEocftAdzfljLguXr4y6KK0WjRo3o0LEjALVr16Zly1bMnz8v5lJVQhHdy1leXkOrJPodtg9vTP0+7mK4cvh29mymTPmELl27xV2UykXx3frkNbRKoFquOLblnoz8bGHcRXEZWr16NQPPPoM77rqbOnXqxF2cSifC8dDKxWtolcARLRoyff5Klq7ZGHdRXAY2bdrEwLPP4JyB5zPgtNPjLk7lFNOtT7HW0CSdIGmmpFmSboizLHE60ZubWcPMuPyySzmkZSuuvva6uItTacVVQ4stoEnKBe4F+gGtgYGSqtypoprVculx8B6MnuZnN7PBB+PG8dSTjzPm3Xfo1qk93Tq1583/vBF3sSqVTINZ0pqcXYFZZvY1gKRnCB6GMD3GMu1y6zYV0vPW9+IuhstQzyOOYN0mi7sYlV5VvA6tCTAnZX4u4KeLnEsAv5czDUmDgcEA1ersFXNpnHOZqIoX1s4D9k2Zbxou24aZDTOzzmbWObdW3V1WOOfcDlIVPCkAfAQ0l3SApHzgXODVGMsTiep5OTw6qDM5gv4dGvPGtT1549qe9O/QuMT0d55zGC9cdTgvXHU4o355JC9cdTgAeTnij2e05aWfdefVq3sw6KgDgOCateGDupAbU5U+idatW0ef446msLCQJx4bTttWzWnbqjlPPDa8xPQ3/vpXtGvbki4dDuPsM09j+fLlALw9+i16dO1E5/aH0qNrJ957950t65x4fG+WLVu2S/YnbgKkzKaoxRbQzKwAuAoYCcwAnjOzaXGVJyqnd2rC6GmLqF0jjyuOO5CBD0zg3PsncMVxB1KnxvYt/F8+O5Uz7hnPGfeM561pC7ec7Ty+7d5UyxOn/eNDzr5vPGd3bUrjejXYVGiM/3opJxy6967etcQa/q9H6D/gdFasWMGtQ4fw/rgJ/PeDidw6dEiJQahX7z5MnvI5H30ylebNW3DHn24DYI89GjLi5deYNOUzHnxkOJdc9OMt65x3/o8Z9sB9u2yf4hXfWc5Yr0MzszfMrIWZHWRmt8ZZlqic1K4R78xYRM/mDflw1lJWrCtg5foCPpy1lCNaNCx13ePb7sO/w+vRDKiVn0dujqiel8umws2s2VAAwDvTF3Fyu0YVvStVxjNPP8kpp/bnrVEj6dWrDw0aNKB+/fr06tWHUSPf3C597z59ycsLfpy6djuceXPnAtC+QwcaNw5q4q3btGH9unVs2LABgJNOOZXnnn16F+1R/HJylNFUFkmHSJqSMq2UdE3a7Ua6F1VctVyxb4OazF++nr3qVOf7FVtvNF+4cgN71amedt1OzeqzdM0Gvlu6FoBRny9k7cYC3rvhaEZffxSPjp3NinVBQPty4WraNvX+xChs3LiR2d98zf7NmjF//jya7ru1W7dJ06Zl3nj+2KOPcPwJ/bZb/tKLL9C+Q0eqVw/+5vXr12fDhg0sXbo02h2ojDJsbmZSQTOzmWbW3szaA52AtcBL6dJX+rOc2aRerXxWri/YoXVPPGwf3vh0690Chzaty+bNcOztY6hTsxqPXdaFD2f9wNxl69hssKlwM7Xyc1m7sTCq4ldJS5YsoW69eju07p9uu5XcvDzOPe/8bZZPnzaNm2/6Na+/MWqb5XvuuRcL5s9njz322OHyZgNBRrWvHdAL+MrMvk2XwGtoEdqwqZDqecFHumjlBvapW2PLe3vXqc6ilRtKXC83R/RusxdvfrY1oJ3Ubh/GfrmEgs3GD2s28sl3y2nTZOtN0Pm5OWws2FxBe1J11KxZk/Xrg5p048ZNmDtn66WR8+bOpXHjJiWu9/jwR3nj36/z6GNPbtMXNHfuXM456zQeeuQxDjzooG3W2bB+PTVr1qyAvah8ylFDayhpUso0uJRszwVKbbd7QIvQyvUF5Ejk5+Uw7ssl9Di4IXVq5FGnRh49Dm7IuC+XlLhe94Ma8M3iNSxMCXgLlq+n24ENgOD2qHb71uWbxWsAqFuzGsvWbqJgs1+xvrPq169PYWEh69evp0/f4xk9ehTLli1j2bJljB49ij59j99unVEj3+Qvd/2ZES+9Sq1atbYsX758OaefehJ/uPV2evTsuc06Zsb3C79n/2bNKnqXKoVynBRYUnRZVjgNS5NfPnAq8Hxp2/WAFrEPZi2h4/71WLGugAfe+4pnf3o4z/70cO5/96stfWBDTmu9TW2rpLHQnp4wh1r5ubzy8x48+9NuvDR5Pv9buBqAbgc24P2Zi3fdTiVc7959+WDcWBo0aMCNN/2WI7p34YjuXbjpN7fQoEHwo3LF4EFMnjQJgGuvvopVq1Zx8gl96NapPT/76eUAPHDfPXz11SxuG/p/W+7zXLQoOGv98eTJdO12+JaTCYkWYR9ain7Ax2ZW6hhbMsueX/majVrYgZfcE3cxStWqcW0u6LE/N474vMK2cfd57fjryC/5NjyBUJlNHtI37iKU6ZOPP+Yff/srjwx/vMK28Ytrr+bkU07l2ON6Vdg2otCzW2cmT560Ux1gtRofYs0vy+wSlan/13uymXUuK114r/dIM/tXaem8hhaxGfNXMfGbH6io616r5Yp3pi/KimCWLTp07MjRxxxLYWHFnWBp06ZtpQ9mUYqyhiZpN6AP8GJZaatA/XfXe2ny/ArLe1Oh8eqUBRWWf1V14cWXVGj+lwy6rELzr2yivGjWzNYAGZ0a9oDmnItWBd3WlAkPaM65SAX3cvrwQc65hPAamnMuMSroToEyeUBzzkVL3uR0ziVE0XhocfCA5pyLWMWMdZYJD2jOuch5Dc05lwzykwLOuYTw69Ccc4niAc05lxjeh+acSwyvoTnnksFvTnfOJYXI7BF1FcEDmnMucjne5HTOJYU3OZ1ziSC/Od05lyQxdaF5QHPORS8rTwpIWgUUPQevaA8sfG1mVqfEFZ1ziSWCM51x2KmAZma1oyqIcy454mpyRvZcTklHSLo4fN1Q0gFR5e2cyyIKxkPLZMosO9WTNELSF5JmSOqeLm0kfWiSfgd0Bg4B/gXkA08APaPI3zmXXSI+yfk34E0zO1NSPlArXcKoTgqcBnQAPgYws/mSvDnqXBUkoruwVlJd4CjgIgAz2whsTJc+qibnRjMzwhME4aPbnXNVVE6OMpoycACwGPiXpE8kPVRafIkqoD0n6Z9APUmXAaOBByPK2zmXRaTMJ6ChpEkp0+Bi2eUBHYH7zawDsAa4Id22I2lymtmdkvoAK4EWwC1m9lYUeTvnsk85mpxLzKxzKe/PBeaa2YRwfgQVHdBCnwE1CZqdn0WYr3Muy0R1TsDMvpc0R9IhZjYT6AVMT5c+kianpEHAROB04ExgvKRLosjbOZd9orxsA/gZ8KSkqUB74I/pEkZVQ/sV0MHMlgJI2gP4AHgkovydc1kiOMsZXX5mNoXgsrAyRRXQlgKrUuZXhcucc1WNsnSAR0nXhS9nARMkvULQh9YfmLqTZXPOZalsHT6o6OLZr8KpyCs7ma9zLktF3eQsj529OX1IVAVxziVHttbQAJC0J3A90AaoUbTczI6LIn/nXHaJqYIW2Z0CTwJfENymMASYDXwUUd7OuSwiQW6OMpqiFlVA28PMHgY2mdkYM7sE8NqZc1VUxNehZSyqyzY2hf8vkHQSMB9oEFHezrksk+1PfRoaDvPxC+AfQB3g2ojyds5lEaHsfi6nmb0evlwBHBtFns65LKUsraFJ+gdbH5KyHTP7+c7kX1zrxnUYN6RvlFm6Cla/y1VxF8GVw4aZ30WST7ZetjEpklI45xJDQG42BjQzGx5VQZxzyZGVdwo451xJPKA55xIhGF47C5uczjlXkqx+0LCkFpLelvR5OH+YpJujyNs5l33K8ZCUSEV169ODwI2EdwyY2VTg3Ijyds5lEQF5UkZT1KJqctYys4nF2s0FEeXtnMsyWXlhbYolkg5i64OGzwQWRJS3cy6LSFl+6xNwJTAMaClpHvAN8KOI8nbOZZmsrqGZ2ddA7/AR7TlmtqqsdZxzyZXV16FJuqXYPABm9n9R5O+cyx6CSAdvlDSb4ElyhUBBaU9aj6rJuSbldQ3gZGBGRHk757KJKqSGdqyZLSkrUVRNzrtS5yXdCYyMIm/nXPZRTE8ViOo6tOJqAU0rKG/nXCVW9Bi7TKYMGTBK0mRJg0tLGFUf2mdsHRctF9gT8P4z56qocgSrhpJShyEbZmbDiqU5wszmSdoLeEvSF2b2fkmZRdWHdnLK6wJgoZn5hbXOVVHluDl9SWmd/ABmNi/8f5Gkl4CuQMUENEm5wEgza7mzeTnnsl/wGLuo8tp6KVj4ui+ltP52OqCZWaGkmZL2M7Noxu91zmW1CO8U2Bt4Kazx5QFPmdmb6RJH1eSsD0yTNJGUSzjM7NSI8nfOZYmikwJRCC/ab5dp+qgC2m8jysc5lwBZfesTcKKZ/Tp1gaQ/AWMiyt85lzVETpZfh9anhGX9IsrbOZdFRHwDPO7sczmvAH4KHChpaspbtYFxO5O3cy5LCfJiujt9Z5ucTwH/AW4DbkhZvsrMftjJvJ1zWaiohhaHnX0u5wpgBTAwmuI455Ig2wd4dM65LbKyhuacc8WJihv1oiwe0Jxz0ZI3OZ1zCRHcKeABzTmXEDF1oXlAc85Fz08KOOcSQuUZDy1SHtCcc5Hys5zOuUTxkwLOuWRQuYbgjpQHNOdcpLzJ6ZxLFK+hOecSw69Dc84lgoBcr6E555LCL6x1ziWEUJY/U8A557aI8pkCknIlfSLp9bLSekCL0Zw5czi+97F0OKw1Hdu14Z6//y3uIrkyXDnwGCY9fxOTR/yGq847Ju7iVErBZRvKaMrQ1cCMTBJ6QItRXl4et//5Lj6ZOp0xY8fzzwfuZcb06XEXy6XR+qBGXHx6D4788R10Pec2+h3VlgP3bRh3sSqfDGtnmdTQJDUFTgIeymTTHtBi1KhRIzp07AhA7dq1admyFfPnz4u5VC6dlgfsw0efz2bd+k0UFm7mv5NnMeC49nEXq1LKkTKaMnA3cD2wOaPt7kyhXXS+nT2bKVM+oUvXbnEXxaUx7av59OxwMA3q7kbNGtU44Yg2NN2nftzFqnSCAR4zm4CGkialTIO35COdDCwys8mZbtvPclYCq1evZuDZZ3DHXXdTp06duIvj0pj5zULuevQtXrvvStau38inM+dSWJhRxaHKKcdZziVm1jnNez2BUyWdCNQA6kh6wsx+lC4zD2gx27RpEwPPPoNzBp7PgNNOj7s4rgzDX/6Q4S9/CMCQq05h3sLlMZeocoriOjQzuxG4MchPxwC/LC2YgTc5Y2VmXH7ZpRzSshVXX3td3MVxGdiz/u4A7LtPffof145n/zMp5hJVTsrwX9RiraFJegQoaie3jbMscfhg3DieevJx2rY9lG6dgs7lIUP/yAn9Toy5ZC6dp+8cRIN6u7GpoJBrbn+OFavXxV2kSqeoDy1KZvYe8F5Z6eJucj4K3AM8FnM5YtHziCNYt8niLoYrh96X3h13ESq/zM9gRi7WJqeZvQ/8EGcZnHPRU4ZT1OKuoZUpPI07GGDf/faLuTTOubLE+VzOSn9SwMyGmVlnM+u8Z8M94y6Ocy4DcdXQKn1Ayzbr1q2jz3FHU1hYyBOPDadtq+a0bdWcJx4bXmL6F0Y8T8d2baiVn8PkSVvPmG3atIlBF19I5/aH0v7QVtzxp9sA2LhxI72PPYqCgoJdsj9VQY3q1Rj10NXk5IjzT+nGZ6/cwmev3ML5p5R8kfNhLZowZvgvGP/MDYx98no6t9kfgHP7dWbiszfy0XM38e6j13FoiyYAVMvL5a2HryE3twp93WKKaFXoE941hv/rEfoPOJ0VK1Zw69AhvD9uAv/9YCK3Dh3CsmXLtkvfpk1bnnnuRY448qhtlr8w4nk2bNzApCmf8cGEyTz04D/5dvZs8vPzOfa4Xjz/3LO7apcS78L+3Xnl7U+pu3tNfjO4H0f9+E6O/NEd/GZwP+rVrrld+luvGcCtw/7D4efezh/uf51brxkAwOz5S+k76G66nP1HbnvwTe69eSAAmwoKeXfCTM7q23GX7lecIrz1qXzbjTzHcpD0NPAhcIikuZIujbM8UXjm6Sc55dT+vDVqJL169aFBgwbUr1+fXr36MGrkm9ulb9mqFS0OOWS75ZJYu2YNBQUFrFu3jvz8fGqHd8xP5u8AAAqvSURBVBGccuoAnn36yQrfl6ri3BM789p7U+nToxVvj/+CZSvXsnzVOt4e/wV9e7beLr0Z1NmtBgB1d6/JgsUrABj/6TcsXxVcxjFx6jc02bvelnVee28q55zYZRfsTeVQJU8KmNnAOLcftY0bNzL7m6/Zv1kzXnxxBE333XfLe02aNi3Xjeenn3Emr7/2Cgfs24i1a9fy5zv/SoMGDQBo07Ytkyd9FHn5q6Jqebk0a9KQ7xb8wOm9OzB34dZa9LxFy2m8Z73t1vnVnSN47d4rue3a08jJEcdedNd2aS4a0IOR47aOnDJt1nw6talCJ7ViGrHWm5wRWrJkCXXrbf8F2BEfTZxIbk4uX383nxlffsPf7r6Lb77+GoDc3Fyq5eezatWqSLZVlTWsvzsrVq0t1zqDzzqS6+96keb9fsv1d77A/b87f5v3j+rcnAsHdOfmv72yZdnmzcamTYXsXqt6JOWuzILaVzx3CnhAi1DNmjVZv349AI0bN2HunDlb3ps3dy6NGzfJOK/nnnmKvsefQLVq1dhrr73o3r0nkydvPWmwccMGatSoEV3hq6h16zdSo3o1AOYvXk7TvbeOntFkr3rMX7z9vZrnn9yNl9+eAsALb32y5aQAQNvmjbn/lvM469ph/LBizTbr5VfLY/3GTRWxG5VLhOOhlZcHtAjVr1+fwsJC1q9fT5++xzN69CiWLVvGsmXLGD16FH36Hp9xXk3324/33n0HgDVr1jBx4ngOOaQlAEuXLmWPhg2pVq1ahexHVbJ81Tpyc3Konp/HWx/MoHf3ltSrXZN6tWvSu3tL3vpg+4FSFyxewZGdmgNwTNcWzPpuMRDc3/nMnZdx6W8fY9Z3i7ZZp0Hd3Vi6fDUFBVVjdI4q2YeWRL179+WDcWM5rldvbrzptxzRPegIvuk3t2zpA7ti8CAGDb6cTp0788rLL3HdNT9jyeLFnN7/JA5r157X3hjJ5VdcyeBBF9OxXRvMjB9feDGHHnYYAGPee5cT+p0U2z4mzejxM+jR4SDenTCT2x58k7FPXA/AH4e9ybKVQXP0vlvO46ERY/l4+ndc+YenuONXZ5KXl8OGDQVcNfRpAG4c3I8G9Xbj7hvPAaCgcDNHnP9nAI7u0pw3x06LYe/ioNgeNCyz7LmXsFOnzjZuQuUe3eCTjz/mH3/7K48Mf7zCtnHOWacz9Nbbad6iRYVtIyr1u1wVdxHK1L5lU352/nFc+tuKu6X4mTsHcfPfX92u5lbZbJj5HJvXLtqpaNT6sI721OtjMkrbYf86k0sZD63cvMkZsQ4dO3L0McdSWFhYIflv3LiRU08dkBXBLFtM+WIuYyb9j5yoh4gIVcvL5dX3plb6YBaVTJub3uTMEhdefEmF5Z2fn8/5P76gwvKvqh57ZXyF5b2poJCnXp9YYflXSv6gYedcUsT1oGEPaM65yMV0TsADmnMuYhV0jVkmPKA55yLnTU7nXCIIr6E55xIkpnjmAc05VwG8huacS4qoBm+UVAN4H6hOEK9GmNnv0qX3gOaci1yEFbQNwHFmtlpSNWCspP+YWYlXQntAc85FL6KIZsHN5qvD2WrhlPYGdL+X0zkXqagHeJSUK2kKsAh4y8wmpEvrAc05F63yDfDYUNKklGlw8ezMrNDM2gNNga6S2qbbtDc5nXORK0eLc0mmwweZ2XJJ7wInAJ+XlMZraM65iAUDPGYylZmTtKekeuHrmkAf4It06b2G5pyLXIR3CjQChkvKJaiAPWdmr6dL7AHNORepKAdvNLOpQIdM03tAc85Fz+8UcM4lhY+24ZxLDB9twzmXDIIKet5MmTygOecqgDc5nXMJ4AM8OucSxQd4dM4lhtfQnHOJkcltTRXBA5pzLnLe5HTOJULK0EC7nAc051zk/E4B51xyeA3NOZcU3ofmnEsIRfYYu/LygOaci1Scdwr4ENzOucTwGppzLnJ+2YZzLjH8sg3nXDL4hbXOuaTw4YOcc4niTU7nXGL4ZRvOucRQhlOZ+Uj7SnpX0nRJ0yRdXVp6r6E556IXXQ2tAPiFmX0sqTYwWdJbZja9pMQe0JxzkRJEduuTmS0AFoSvV0maATQBSgxoMrNINrwrSFoMfBt3OSpAQ2BJ3IVw5ZLUv9n+ZrbnzmQg6U2CzycTNYD1KfPDzGxYmnybAe8Dbc1sZYlpsimgJZWkSWbWOe5yuMz532zXkrQ7MAa41cxeTJfOTwo45yo1SdWAF4AnSwtm4AHNOVeJKXjaysPADDP7S1npPaBVDiX2GbhKzf9mu0ZP4MfAcZKmhNOJ6RJ7H5pzLjG8huacSwwPaM65xPCAFjNJJ0iaKWmWpBviLo8rnaRHJC2S9HncZXHb84AWI0m5wL1AP6A1MFBS63hL5crwKHBC3IVwJfOAFq+uwCwz+9rMNgLPAP1jLpMrhZm9D/wQdzlcyTygxasJMCdlfm64zDm3AzygOecSwwNavOYB+6bMNw2XOed2gAe0eH0ENJd0gKR84Fzg1ZjL5FzW8oAWIzMrAK4CRgIzgOfMbFq8pXKlkfQ08CFwiKS5ki6Nu0xuK7/1yTmXGF5Dc84lhgc051xieEBzziWGBzTnXGJ4QHPOJYYHNFciScdIej18fWppI4FIqifppzuwjd9L+mWmy4uleVTSmeXYVjMfISP5PKBVMeEIH+ViZq+a2e2lJKkHlDugORc1D2gJEdZAvpD0pKQZkkZIqhW+N1vSnyR9DJwlqa+kDyV9LOn58BFhRWOzfRGmOz0l74sk3RO+3lvSS5I+DacewO3AQeF473eE6X4l6SNJUyUNScnrN5L+J2kscEgG+3VZmM+nkl4o2qdQb0mTwvxODtPnSrojZds/2dnP1mUPD2jJcghwn5m1Alayba1pqZl1BEYDNwO9w/lJwHWSagAPAqcAnYB90mzj78AYM2sHdASmATcAX5lZezP7laS+QHOC4ZHaA50kHSWpE8HtXe2BE4EuGezTi2bWJdzeDCD1yvxm4TZOAh4I9+FSYIWZdQnzv0zSARlsxyVAXtwFcJGaY2bjwtdPAD8H7gznnw3/P5xgMMlxwRPCyCe4lacl8I2ZfQkg6QlgcAnbOA64AMDMCoEVkuoXS9M3nD4J53cnCHC1gZfMbG24jUzuW20raShBs3Z3gtvEijxnZpuBLyV9He5DX+CwlP61uuG2/5fBtlyW84CWLMXvY0udXxP+L+AtMxuYmlBS+wjLIeA2M/tnsW1cswN5PQoMMLNPJV0EHJPyXkn7K+BnZpYa+JDUbAe27bKMNzmTZT9J3cPX5wFjS0gzHugp6WAASbtJagF8ATSTdFCYbmAJ6wK8DVwRrpsrqS6wiqD2VWQkcElK31wTSXsB7wMDJNWUVJugeVuW2sCC8OnZ5xd77yxJOWGZDwRmhtu+IkyPpBaSdstgOy4BPKAly0zgSkkzgPrA/cUTmNli4CLgaUlTCZubZraeoIn57/CkwKI027gaOFbSZ8BkoLWZLSVown4u6Q4zGwU8BXwYphsB1Dazjwmavp8C/yEYPqksvwUmAOMIgm6q74CJYV6Xh/vwEDAd+Di8TOOfeEukyvDRNhIibFK9bmZtYy6Kc7HxGppzLjG8huacSwyvoTnnEsMDmnMuMTygOecSwwOacy4xPKA55xLj/wGHbwUkb2KSDgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light",
      "tags": []
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "device = torch.device(\"cuda\")\n",
    "resnet.to(device)\n",
    "\n",
    "pr =[]\n",
    "tl =[]\n",
    "\n",
    "with torch.no_grad():\n",
    "    for i, (inputs, classes) in enumerate(validloader):\n",
    "        inputs = inputs.to(device)\n",
    "        classes = encoder(classes, 3)\n",
    "        classes = classes.to(device)\n",
    "        outputs = resnet(inputs)\n",
    "        outputs[outputs >= 0.5] = 1\n",
    "        outputs[outputs < 0.5] = 0\n",
    "        for i in classes.tolist():\n",
    "            tl.append(i)\n",
    "        for j in outputs.tolist():\n",
    "            pr.append(j)\n",
    "\n",
    "    pr = np.argmax(pr, axis=1)\n",
    "    tl = np.argmax(tl, axis=1)\n",
    "\n",
    "cm = multilabel_confusion_matrix(np.array(tl),np.array(pr))\n",
    "labels=['Covid-19', 'Normal', 'Pneumonia']\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[0], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('Renset-18 Training CF with BCE Loss (Matrix 0)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[1], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('Resnet-18 Training CF with BCE Loss (Matrix 1)')\n",
    "\n",
    "fig, ax = plot_confusion_matrix(conf_mat=cm[2], show_absolute=True, show_normed=True, colorbar=True)\n",
    "plt.title('Resnet-18 Training CF with BCE Loss (Matrix 2)')\n",
    "print('F1: {}'.format(f1_score(classes.data.cpu().numpy(), outputs.data.cpu().numpy(), average='macro')))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "-FxFiK0Yg75G"
   },
   "source": [
    "# Testing best Model and making CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "0WGu_ahZjGEw"
   },
   "outputs": [],
   "source": [
    "covid =[]\n",
    "normal =[]\n",
    "pnemonia =[]\n",
    "with torch.no_grad():\n",
    "    for data in testloader:\n",
    "        images, labels = data\n",
    "        images, labels = images.to(device), labels.to(device)\n",
    "        outputs = torch.sigmoid(vgg16(images))\n",
    "        outputs[outputs >= 0.5] = 1\n",
    "        outputs[outputs< 0.5] =0\n",
    "        for i in outputs.tolist():\n",
    "            covid.append(i[0])\n",
    "            normal.append(i[1])\n",
    "            pnemonia.append(i[2])\n",
    "csvdf = pd.DataFrame(list(zip(test_data.imgs, covid,pnemonia,normal)))\n",
    "csvdf.to_csv(\"./gdrive/My Drive/test.csv\", index=False, header = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 0,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "vJA1hAf--suy"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "accelerator": "GPU",
  "colab": {
   "collapsed_sections": [],
   "name": "Covid19.ipynb",
   "provenance": []
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "07a68bd404dc42c885125399b7729715": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "ProgressStyleModel",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "ProgressStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "bar_color": null,
      "description_width": "initial"
     }
    },
    "08c280e65cbb4819aa73f4e9b542c397": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "1b81b78fd2474b3d9c0153a8a2c8648c": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "1cdb15b6773d4ad2bd955aac3c796e01": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "2d706c6ff466458bbc4677066970658d": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "IntProgressModel",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "IntProgressModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "ProgressView",
      "bar_style": "success",
      "description": "100%",
      "description_tooltip": null,
      "layout": "IPY_MODEL_c49c88b32cb94bbbb485f8054e17cf87",
      "max": 553433881,
      "min": 0,
      "orientation": "horizontal",
      "style": "IPY_MODEL_07a68bd404dc42c885125399b7729715",
      "value": 553433881
     }
    },
    "30ba326aaf7d45fbaaa2b6ffcc4c533c": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "3a576f983d3045668558cd90c9932bac": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "HBoxModel",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "HBoxModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "HBoxView",
      "box_style": "",
      "children": [
       "IPY_MODEL_499dd9a0a93e403f8a5faf7c2745e8a8",
       "IPY_MODEL_7f71af1d633f47caa60a3ecc89059e9a"
      ],
      "layout": "IPY_MODEL_30ba326aaf7d45fbaaa2b6ffcc4c533c"
     }
    },
    "3c0c31d73b824db2ac72cad00596508a": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "ProgressStyleModel",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "ProgressStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "bar_color": null,
      "description_width": "initial"
     }
    },
    "499dd9a0a93e403f8a5faf7c2745e8a8": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "IntProgressModel",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "IntProgressModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "ProgressView",
      "bar_style": "success",
      "description": "100%",
      "description_tooltip": null,
      "layout": "IPY_MODEL_61c1a600f827424a87d056b959776229",
      "max": 553433881,
      "min": 0,
      "orientation": "horizontal",
      "style": "IPY_MODEL_69ca34e5c719451c8f580076adf018a4",
      "value": 553433881
     }
    },
    "55954b3e354c481eb62d56ed4010ec74": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "HTMLModel",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "HTMLModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "HTMLView",
      "description": "",
      "description_tooltip": null,
      "layout": "IPY_MODEL_a462a2e3f90047dfa6b0d9cff35eeb2b",
      "placeholder": "​",
      "style": "IPY_MODEL_a92a4200bd8c47cc97c8079a379816dc",
      "value": " 44.7M/44.7M [39:56&lt;00:00, 19.5kB/s]"
     }
    },
    "5b93576c6c2e48e59db4091d4b0e07de": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "HBoxModel",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "HBoxModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "HBoxView",
      "box_style": "",
      "children": [
       "IPY_MODEL_8e8bfcc788a542978df651dc6d9cc54a",
       "IPY_MODEL_55954b3e354c481eb62d56ed4010ec74"
      ],
      "layout": "IPY_MODEL_1cdb15b6773d4ad2bd955aac3c796e01"
     }
    },
    "61c1a600f827424a87d056b959776229": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "69ca34e5c719451c8f580076adf018a4": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "ProgressStyleModel",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "ProgressStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "bar_color": null,
      "description_width": "initial"
     }
    },
    "7c4efd6c4df642ada5036db412e1ea27": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "7f71af1d633f47caa60a3ecc89059e9a": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "HTMLModel",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "HTMLModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "HTMLView",
      "description": "",
      "description_tooltip": null,
      "layout": "IPY_MODEL_1b81b78fd2474b3d9c0153a8a2c8648c",
      "placeholder": "​",
      "style": "IPY_MODEL_cb45bf5ccfb04a94bc2aa82db8b74c9c",
      "value": " 528M/528M [1:31:49&lt;00:00, 100kB/s]"
     }
    },
    "8e8bfcc788a542978df651dc6d9cc54a": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "IntProgressModel",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "IntProgressModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "ProgressView",
      "bar_style": "success",
      "description": "100%",
      "description_tooltip": null,
      "layout": "IPY_MODEL_7c4efd6c4df642ada5036db412e1ea27",
      "max": 46827520,
      "min": 0,
      "orientation": "horizontal",
      "style": "IPY_MODEL_3c0c31d73b824db2ac72cad00596508a",
      "value": 46827520
     }
    },
    "a2ebc1b09972407b979ef1114f88cba6": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "HBoxModel",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "HBoxModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "HBoxView",
      "box_style": "",
      "children": [
       "IPY_MODEL_2d706c6ff466458bbc4677066970658d",
       "IPY_MODEL_e92a0f08e6d44acf8b1a3c5f9fd6d8f8"
      ],
      "layout": "IPY_MODEL_08c280e65cbb4819aa73f4e9b542c397"
     }
    },
    "a462a2e3f90047dfa6b0d9cff35eeb2b": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "a80d50ebc74542838ba454e9d05be0ba": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "DescriptionStyleModel",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "DescriptionStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "description_width": ""
     }
    },
    "a92a4200bd8c47cc97c8079a379816dc": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "DescriptionStyleModel",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "DescriptionStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "description_width": ""
     }
    },
    "c49c88b32cb94bbbb485f8054e17cf87": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    },
    "cb45bf5ccfb04a94bc2aa82db8b74c9c": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "DescriptionStyleModel",
     "state": {
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "DescriptionStyleModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "StyleView",
      "description_width": ""
     }
    },
    "e92a0f08e6d44acf8b1a3c5f9fd6d8f8": {
     "model_module": "@jupyter-widgets/controls",
     "model_name": "HTMLModel",
     "state": {
      "_dom_classes": [],
      "_model_module": "@jupyter-widgets/controls",
      "_model_module_version": "1.5.0",
      "_model_name": "HTMLModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/controls",
      "_view_module_version": "1.5.0",
      "_view_name": "HTMLView",
      "description": "",
      "description_tooltip": null,
      "layout": "IPY_MODEL_eb1acb46667e45978af77403e7d45680",
      "placeholder": "​",
      "style": "IPY_MODEL_a80d50ebc74542838ba454e9d05be0ba",
      "value": " 528M/528M [00:08&lt;00:00, 68.3MB/s]"
     }
    },
    "eb1acb46667e45978af77403e7d45680": {
     "model_module": "@jupyter-widgets/base",
     "model_name": "LayoutModel",
     "state": {
      "_model_module": "@jupyter-widgets/base",
      "_model_module_version": "1.2.0",
      "_model_name": "LayoutModel",
      "_view_count": null,
      "_view_module": "@jupyter-widgets/base",
      "_view_module_version": "1.2.0",
      "_view_name": "LayoutView",
      "align_content": null,
      "align_items": null,
      "align_self": null,
      "border": null,
      "bottom": null,
      "display": null,
      "flex": null,
      "flex_flow": null,
      "grid_area": null,
      "grid_auto_columns": null,
      "grid_auto_flow": null,
      "grid_auto_rows": null,
      "grid_column": null,
      "grid_gap": null,
      "grid_row": null,
      "grid_template_areas": null,
      "grid_template_columns": null,
      "grid_template_rows": null,
      "height": null,
      "justify_content": null,
      "justify_items": null,
      "left": null,
      "margin": null,
      "max_height": null,
      "max_width": null,
      "min_height": null,
      "min_width": null,
      "object_fit": null,
      "object_position": null,
      "order": null,
      "overflow": null,
      "overflow_x": null,
      "overflow_y": null,
      "padding": null,
      "right": null,
      "top": null,
      "visibility": null,
      "width": null
     }
    }
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}