CovidNet_ensemble_final.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Covid.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/rohankrgupta/Lung-X-Ray-Classification-Deep-Learning/blob/master/CovidNet_ensemble_final.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mUrURh-gft7U"
      },
      "source": [
        "%matplotlib inline\n",
        "\n",
        "import matplotlib\n",
        "import os\n",
        "import random\n",
        "import pandas as pd\n",
        "import imageio\n",
        "\n",
        "import cv2\n",
        "import shutil\n",
        "\n",
        "from scipy.stats.mstats import linregress\n",
        "from tensorflow.keras.preprocessing.image import img_to_array\n",
        "from random import uniform\n",
        "from sklearn.preprocessing import LabelBinarizer\n",
        "from keras.models import Sequential\n",
        "from keras.layers import Convolution2D, Dense, Flatten, MaxPooling2D, Dropout\n",
        "from keras.layers import BatchNormalization\n",
        "from keras.utils import normalize\n",
        "import pickle\n",
        "\n",
        "#dependencies\n",
        "import numpy as np\n",
        "import tensorflow as tf\n",
        "from tensorflow import keras\n",
        "from tensorflow.keras import layers\n",
        "from tensorflow.keras import Model\n",
        "\n",
        "\n",
        "from tensorflow.keras.optimizers import Adam\n",
        "from tensorflow.keras.applications.efficientnet import EfficientNetB0\n",
        "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
        "\n",
        "matplotlib.use('Agg')\n",
        "\n",
        "%matplotlib inline\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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",
              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 89
        },
        "id": "peqQTA1om5jo",
        "outputId": "f3fbc2c7-9441-4233-ef5a-bdb5cf1e8db6"
      },
      "source": [
        "from google.colab import files\n",
        "\n",
        "uploaded = files.upload()\n",
        "\n",
        "for fn in uploaded.keys():\n",
        "  print('User uploaded file \"{name}\" with length {length} bytes'.format(\n",
        "      name=fn, length=len(uploaded[fn])))"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-6147ec0c-24c5-4e83-9329-86264c9799c9\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-6147ec0c-24c5-4e83-9329-86264c9799c9\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving Database.zip to Database.zip\n",
            "User uploaded file \"Database.zip\" with length 349581599 bytes\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": "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",
              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 89
        },
        "id": "wRqXjYMZw3Wc",
        "outputId": "4fe879ca-a276-4667-ac8a-8cc626894846"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-4e82f1c5-81e3-480b-83a7-f63f01b9a7ad\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-4e82f1c5-81e3-480b-83a7-f63f01b9a7ad\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Saving test.zip to test.zip\n",
            "User uploaded file \"test.zip\" with length 59913358 bytes\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mUwnY-L1nYnW"
      },
      "source": [
        "import os\n",
        "import zipfile\n",
        "\n",
        "local_zip = '/content/Database.zip'\n",
        "zip_ref = zipfile.ZipFile(local_zip, 'r')\n",
        "\n",
        "zip_ref.extractall('/content')\n",
        "zip_ref.close()\n",
        "\n",
        "base_dir = '/content/Database'"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bJWjvUonw4PW"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7QlOPIjKnlZk"
      },
      "source": [
        "# Model\n",
        "class CovidNet:\n",
        "  @staticmethod\n",
        "  def build_model1(inputs):\n",
        "    # Base Model\n",
        "    base_model1 = EfficientNetB0(\n",
        "    weights = 'imagenet',\n",
        "    input_shape = (224, 224, 3),\n",
        "    include_top = False,\n",
        "    drop_connect_rate=0.3,\n",
        "    #pooling = max,\n",
        "    input_tensor = inputs\n",
        "    )\n",
        "    # Set train to false\n",
        "    base_model1.trainable = True\n",
        "    \n",
        "    #Get the last Layer\n",
        "    last_layer1 = base_model1.get_layer('block7a_se_squeeze')\n",
        "    last_output1 = last_layer1.output\n",
        "    \n",
        "    # Flatten the output layer to 1 dimension\n",
        "    x1 = layers.Flatten()(last_output1)\n",
        "    x1 = layers.Dense(1024, activation='relu', name = 'denselayer1')(x1)\n",
        "    x1 = layers.Dense(3, activation='softmax', name = \"model1_output\")(x1)\n",
        "    \n",
        "    return x1\n",
        "\n",
        "  @staticmethod\n",
        "  def build_model2(inputs):\n",
        "    # Base Model\n",
        "    base_model2 = EfficientNetB0(\n",
        "    weights = 'imagenet',\n",
        "    input_shape = (224, 224, 3),\n",
        "    include_top = False,\n",
        "    drop_connect_rate=0.3,\n",
        "    #pooling = max,\n",
        "    input_tensor = inputs\n",
        "    )\n",
        "\n",
        "    # Set train to false\n",
        "    base_model2.trainable = True\n",
        "    \n",
        "    for layer in base_model2.layers:\n",
        "      layer._name = 'new' + str(layer._name)\n",
        "\n",
        "    #Get the last Layer\n",
        "    last_layer2 = base_model2.get_layer('newblock7a_se_squeeze')\n",
        "    last_output2 = last_layer2.output\n",
        "    \n",
        "    # Flatten the output layer to 1 dimension\n",
        "    x2 = layers.Flatten()(last_output2)\n",
        "    x2 = layers.Dense(1024, activation='relu', name = 'denselayer2')(x2)\n",
        "    x2 = layers.Dense(3, activation='softmax', name = \"model2_output\")(x2)\n",
        "   \n",
        "    return x2  \n",
        "\n",
        "  @staticmethod\n",
        "  def build():\n",
        "    \n",
        "    inputShape = (224, 224, 3)\n",
        "    inputs = tf.keras.Input(shape = inputShape)\n",
        "    \n",
        "    model1 = CovidNet.build_model1(inputs)\n",
        "    model2 = CovidNet.build_model2(inputs)\n",
        "\n",
        "    model = Model(\n",
        "        inputs = inputs,\n",
        "        outputs = (model1+model2)/2,\n",
        "        name='covidnet'\n",
        "    )\n",
        "\n",
        "    #return the constructed arhitecture\n",
        "    return model\n",
        "    "
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z5VcgEZHqiBL",
        "outputId": "5ae8e61d-1f75-4b34-dfe2-e6ddde0efe40"
      },
      "source": [
        "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
        "\n",
        "trainAug = ImageDataGenerator(\n",
        "    horizontal_flip=True)\n",
        "\n",
        "testAug = ImageDataGenerator()\n",
        "\n",
        "mean = np.array([0.485, 0.456, 0.406], dtype= \"float32\")\n",
        "std = np.array([0.229, 0.224, 0.225], dtype= \"float32\")\n",
        "\n",
        "trainAug.mean = mean\n",
        "testAug.mean = mean\n",
        "trainAug.std = std\n",
        "testAug.std = std\n",
        "\n",
        "train_generator = trainAug.flow_from_directory(\n",
        "    '/content/Database/train',\n",
        "    target_size=(224, 224),\n",
        "    batch_size=20,\n",
        "    class_mode='categorical')\n",
        "\n",
        "validation_generator = testAug.flow_from_directory(\n",
        "    '/content/Database/test',\n",
        "    target_size=(224, 224),\n",
        "    batch_size=20,\n",
        "    class_mode='categorical')"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Found 3526 images belonging to 3 classes.\n",
            "Found 360 images belonging to 3 classes.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7snPlUlNq0uP"
      },
      "source": [
        "callback = tf.keras.callbacks.EarlyStopping(\n",
        "    monitor=\"val_loss\",\n",
        "    min_delta=0,\n",
        "    patience=1,\n",
        "    verbose=0,\n",
        "    mode=\"auto\",\n",
        "    baseline=None,\n",
        "    restore_best_weights=False,\n",
        ")"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "U3CKyufDq646"
      },
      "source": [
        "EPOCHS = 30\n",
        "INIT_LR = 3e-5\n",
        "BS = 20\n",
        "\n",
        "model = CovidNet.build()\n",
        "opt = keras.optimizers.Adam(lr=INIT_LR, decay=INIT_LR / EPOCHS)\n",
        "\n",
        "model.compile(optimizer=opt, loss= 'categorical_crossentropy', metrics=['accuracy'])"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Td77npbk5AGT",
        "outputId": "5d6bcd2a-a746-4666-9af1-9f3e7386632d"
      },
      "source": [
        "print(\"[INFO] training w/ generator...\")\n",
        "\n",
        "H = model.fit(\n",
        "              train_generator,\n",
        "              epochs= 30,\n",
        "              validation_data=validation_generator, callbacks=[callback])"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[INFO] training w/ generator...\n",
            "Epoch 1/30\n",
            "177/177 [==============================] - 89s 425ms/step - loss: 0.6101 - accuracy: 0.8281 - val_loss: 0.4729 - val_accuracy: 0.7528\n",
            "Epoch 2/30\n",
            "177/177 [==============================] - 73s 412ms/step - loss: 0.1415 - accuracy: 0.9521 - val_loss: 0.1552 - val_accuracy: 0.9444\n",
            "Epoch 3/30\n",
            "177/177 [==============================] - 73s 411ms/step - loss: 0.0810 - accuracy: 0.9779 - val_loss: 0.1425 - val_accuracy: 0.9389\n",
            "Epoch 4/30\n",
            "177/177 [==============================] - 73s 411ms/step - loss: 0.0551 - accuracy: 0.9819 - val_loss: 0.0977 - val_accuracy: 0.9694\n",
            "Epoch 5/30\n",
            "177/177 [==============================] - 73s 412ms/step - loss: 0.0479 - accuracy: 0.9839 - val_loss: 0.0536 - val_accuracy: 0.9778\n",
            "Epoch 6/30\n",
            "177/177 [==============================] - 73s 413ms/step - loss: 0.0374 - accuracy: 0.9896 - val_loss: 0.0485 - val_accuracy: 0.9806\n",
            "Epoch 7/30\n",
            "177/177 [==============================] - 73s 412ms/step - loss: 0.0577 - accuracy: 0.9793 - val_loss: 0.0425 - val_accuracy: 0.9833\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 298
        },
        "id": "whsRTcpbXbfd",
        "outputId": "fdf48584-06f1-4ddd-8436-ba78158117ab"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "R22 = H.history['loss']\n",
        "R21 = H.history['val_loss']\n",
        "val_R21 = H.history['val_accuracy']\n",
        "val_R22 = H.history['accuracy']\n",
        "\n",
        "epochs = range(len(R22))\n",
        "\n",
        "plt.plot(epochs, R21, 'r', label='Val Loss')\n",
        "plt.plot(epochs, R22, 'b', label = 'Training Loss')\n",
        "plt.plot(epochs, val_R21, 'r', label='Validation Accuracy')\n",
        "plt.plot(epochs, val_R22, 'b', label='Train Accuracy')\n",
        "plt.title('Training and validation Metrics')\n",
        "plt.legend(loc=0)\n",
        "plt.figure()\n",
        "\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "k6jIYUYkbGP_"
      },
      "source": [
        ""
      ],
      "execution_count": 58,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "r9MOI0AEfkCu"
      },
      "source": [
        ""
      ],
      "execution_count": 65,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 752
        },
        "id": "6oGJ9SdIYa1u",
        "outputId": "8ec949f1-6096-419d-e439-a689bceb115a"
      },
      "source": [
        "from keras.preprocessing import image \n",
        "\n",
        "test_dir = '/content/Database/test/'\n",
        "\n",
        "class_names = ['covid', 'normal', 'viral']\n",
        "\n",
        "for labels in class_names:\n",
        "  images = [x for x in os.listdir(os.path.join(test_dir, labels))]\n",
        "  #print(images)\n",
        "  selected_image = random.sample(images, 1)\n",
        "  plt.figure(figsize=(8, 4))\n",
        "  plt.subplot(1, 1, 1, xticks=[], yticks=[])\n",
        "  for img in selected_image:\n",
        "    imag = cv2.imread(test_dir + labels + '/' + img)\n",
        "    imag = cv2.resize(imag, (224, 224))\n",
        "    x = image.img_to_array(imag)\n",
        "    preds = model.predict(np.expand_dims(x, axis=0))\n",
        "    preds = np.argmax(preds, axis=1)\n",
        "    plt.imshow(imag)\n",
        "    col = 'green'\n",
        "    if(class_names[preds[0]] != labels):\n",
        "      col = 'red'\n",
        "    plt.xlabel(f'{labels}')\n",
        "    plt.ylabel(f'{class_names[preds[0]]}', color=col)\n",
        "\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 91,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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UPJfTXVZ6IxmjgBzbMsG0gc9arVZBJTmUQREwssTMXJfHmPtbWI0kmGegOijE3trkpvts4Xb4EbFP19ibcnjxSESU8IT0G6Wt9/f3cXV1FWdnZzEcDossnJycxOnpaczn81gsFhERMRwOo9/vR0SUNOjJyUlBmJBWNzc3JUxjvI1cmG/kt6lIxIaduQI10V9DeBtksg1cd+h41pQWgmJFtFXjc66xgiHcznfbCxqCzGazJ7AGBUCIyXefnJxERNRiSgtJr9eL169fx8nJSbx9+zZubm4KgWSF429IOPK3eAoUxf3AGxsKZwIOhBNRX65q5eTc7A0Ynxyz4nEYC/pCexCs+/v7uLy8jG63W/L9LnawwHEPG1zmEaNq5OXfeCUjMfppOSAM4DobHhOD9Jn5RbnX63Xc3d2VJaV8D7cCzAbmkhE5PT2N4XAYERF3d3dxc3NTvDvzYtRkz+wcur2255j5IXygrXYc2dBlaP9LialdUQOTZyYzxxo5PUHMBCRkMjITi5L7x/FkxF4Zia2wzKRrHFcy6JeXl3F8fByDwSBub29LW/CM3W43Tk9PYzQaRbfbrcF7Jgjo5jg1Q3ArAzE03jMriz0ggoyScF/Hzc7Nu9LOaAUy5uHhITqdTpydnRVlxOC5HJXDEN5KzzgbtdAew2S8t8fE8N3Gj78hqkiPcfhezNlisSj9Qnlo6/HxcVxeXsarV69KnEytAx59tVrFzc1NXF9fF8RmzsPIJSMwh1TmiugXJG1O3Vo27BRATHZqX3nxSUQU75Q7F/G0PLMpDskpAgbt5OSkJrgmGzKxhSJst9tYLBal2AJLfXFxEaenp9Hr9UqFFQLXbrdLbvLFixcFXhrC4vXwOvxERCkusABaUQ0pHcu6/4bvfGfhwFihwI7rIvZlmRFRWGw+Y1yJc4+Pj+P8/DxarVbMZrM4PT2Nly9fljGwEeZvDBkMLh4aA4ZnnU6nMZ/PCzQ2seV0nivUMBJGE6RJ+XGIR/oHOcGAz2azmE6npe7cjuD29rbMFQVR7XY7FotF3N7exu3tbS0UcRYFI2ciMSt15kyqal8piDzZ89rI2bDRblDaaDSK73znO/Gnf/qnzbr35dX0yx9NcaM7mj/L32doFfHILi6Xy9p9HVv7/EwGWUg2m02Mx+PCYF5cXMTFxUWJoVix1Gq1SjqONBgKy+CakXTpH4iCsXDbbOAQVu5H5ZZLJk2wGfrjbTmHPKe9MiSaob7jORhfBOrk5KQon40JhJlRg3kJjF02GhhKV/XZ+KEoXkMNJKe9NiCTyaQoFchtMBhEv98vTsQ1ABhKUloPDw+FEGU3GBNTKD67r7Bgw6kljxcIDfSToTdtJxQlhQUCMvKyrNtT20h3Op349re/HT/4wQ/i13/91+MP/uAPGvXvWYkyVz8ZZrvg3bGBGdSIp6WZpBMyecSBZ+D5TXDOXnM2mxWreXZ2Fqenp7WwgfgWoWZyp9NpicGIw1BmM9EchsoR++IZM5oWsJzugtCJeJxY0AX99Vhn3sFj6QUy2+22xI0mfiBsxuNxURh7H7cXA2hmHsiPMkMYmhjFYzNPVFmBHjJBhhIBoTFUZE76/X6cnp7G+fl5nJ6eFnILo0cFI7DVHpZw5+HhId69e1dYbdDYYDCI8/PzEmaxdxsVXhgg2pvJQhtyxhbvDyeBXJLGNPrEeBMe/eAHP4jf+I3fqPEN+Xg2T529NA1G8L3qh2sQFvJ/Vmp/j2K7tJR78NswLrORQJ+IRyEcj8dFOS8uLmIwGNS8TsR+mSPtI86KeIzjvLgCq21IbXLIBR+uWwc+W4nMjuIR7+/vYzAYFC9E30h/OdZlzIySPKbE1TwfL7Jer4uB8v3on2N4sgsYs9lsVphiEA+lul5kg0Hlfl7Dzb0ydHVVGOPkdQMXFxfx+vXrUitNG/HmjAfGOuLRqJHDxluzHHU2m5US5w8++KDE4I7Zs8MwP2CnAkS3h8cQI3NGn8iwOalf/dVfjX6/H9Pp9KD+PaunRqGBSwy+PVcmyjh3uVyW9bwcFkQELUMX7sP9sxBHPMZQk8nkSTWPizzMThp2V1VVg6QYKLxgxH71lFlOcpukUlBQYtpMikXsQw4EzYQbbZtMJsWA3N/f17IFoA7GEMXLcNwko8MBIL9jV0P/XB652Wzi9vY2rq6uyn5nVVUVJp3cPwsZmF/mE2htlBWxL3kFXuP98cSk1FhG+vbt21IVdn5+HhcXF0WpMd7IIWsCJpNJjZmmT5TCLpfL6PV6hYsZjUblmfSDsXTajbkEhaEPyJjz4PTV8m65R9aNdJqOZyXKICzwWF6vy2GhoAMo9mAwKEvodrtdMQp4fcioqqoKJHKO16kzflqtx0IEGE6W0TGBP/3pT2O73RYijJwggkXBA2WI7LCJR3bOGag+mUxKXAm8pg+uMHOJ5Ha7jel0WmqEeQbj5Pw/VVMILlV8tAVBtSKDmhAmDOFgMCgGGSPnvLLvAxJAEKfTadzc3DzhCRB6e/LpdPokzwuiYBdU2oWHc6yKckZErUiF9NR0Oo3pdFrGmnz20dFRnJ6e1hhocxf0FSNFqLJer2M2m5UtkF+9elWg+XA4LM8ifMiFUshfxKPjwTMzN3ZUWUc8DhiNX8rSy1arVZQOQcNyG6ZkQqk0TDnq8XhciBwGwSkrBBCrl9lmzt3tdoXlbbfbBSLe3t6WHTKJd7wMFK8MIqACjhjUSxBRRpQZ5tXWHIXA42C1uUfE3rJbyYHGEFn0G0iO94eVp/9GQtwfIbKw0BZ7NLw/ymEPZMMynU7j7u6uKAkIJW9cMZ/PCxHlwh7mEYNAPQGKhjJDjs3n8yeKwD1MEK5WqxJeHR8flxw0hoGswPn5eS08sDy6PycnJ4WLOT09jcFgUBwQ4+BUlPkg2mmlxjHkPvC/PbcLnszZ5OPZPDXeucmLOQ6m8f5xqguiBiFzLtqrs7CsEVGex28TKxAjn376afzoRz8qAmZyClKMwwYK6I1A8xxIoJubm7i5uYm7u7tSsGCGdL1+XALpFVEILvAWpheI5dwslhoy6ejoqCAHvkPY8f4IQ0SUHDIKB5xHmI+OHksmW61WWQRBuxgLs7pVVRWOgdV2eEsbXrgQCi04GHf6ADoyN+D40uiEMUTpka1+v1+IT8o+gf6bzSYmk0mBwBhAFn9A5BlFAJsfHh7KKrBWq1XmF49t3sicQzY+LsX1GLh/9Il28PzVahUnJyc1+czHs3lqoJ2XqJnut3AwMZ4gx8hnZ2clLkUgUBDY14j9Yg/iM+DN2dlZ8aLX19cxmUzKb+7n9Bp9oDqMyTk7OyvKY4/e6/Xi7du38aMf/Sh+/vOfl61o8J42GIaa5gNMrhie0j6MCVVRhoUYN7xwkzHA6+bqO4wjO4VSHYe3cwkqv4H0EVEWw8zn8+JZXI6LJ0LJaVdVVWWnEpQW0skIw6SnY12eg2EFOXghDHyCjQS1CO12u/ayA+adNhHyYehox2KxKAYIZT06OorpdFpCTOoeGDOnWr0Qic/NfTgc8znog6sVDx3PCr8Ng5qsEgrM4Vw193AljZlG7sG9c/qJewHj3r59G5999ll588RkMimDkwmJTCRFRBl4LCcebrlcxvX1dXz66acFwuf6YA6MDfdx+OC4FfbfxgAhQQHxarQxb3ODEpMiAakQ8znF5vLJV69eFW9Fqmg0GjXGm/P5vJRRerUS5+DBraSOJSlMwfi5qGiz2RTFZIyaCDSPEbUGhEaLxaKWwZjNZiW/XFWP692R0bOzs1J4wqIP2m5SlvoGxpVnYWR4vouMIBX5nTmliHiCTBzuGZ36+0PHsxafQGplWt9Kyfl4cs61BUX4GZg8GFSZwdIiCL1eL+bzebx586bEVVVVlRjXBoR25BQYcdjR0VFJb7DB3Xg8jtvb27i5uSm7d5yenkZVVWWJH+30/Tn8XUTUarBzKsk8gbe/YSGCGWxCkogoe40hCBgjp89evnxZlBJvEfEIyfv9fi21YngNPAd18HN/fx93d3cxnU5r3oZ5IlQhhAARMOYeK57HfUzW4UnZoQQkxT0YYxhs8v2np6eFF8H47Hb7dObDw0MMh8PCX+Q2zGazMi7T6bRA4uFwGA8PD+W+8AOQuvb6zI8V2AjK7TdKyex60/GsGw8Oh8Oa5bbFs1d2TMT1jpXpAPk9lLPT6ZQNGIB6y+Uyzs/PC3Pufay73W6B3gy4SSqUB+NAkYer2Obzebx9+7asBJpOp7U8NzFpu90ugp0tK8rEeDCh9lSMk8fNxtEVUPZiZnMZX48NfXOKivaBEhh/iEOzsy6NxRAQo6M4FJ0wn+SJ2+12WYfs6jvawD3ZPdPG32iGEAC5gIcgrofUw2t6N5GIR3TllXM8//b2Ns7Pz+P4+DiWy2VBKCYsQUTz+bw8lzav1+t4/fp14VmAyob6zA9oJBNp7q9rF9AL9/vQ8SxKjcfq9Xoxm81qbCKCZ/IlT56LL7if2WGs8+npaanwQcCBpeSEIRdIRcxms4iIwuRm1hdBGw6HxZpSjXR1dRU3NzfFeuP1zVQzoUA62oGQuxIIhbWCY6i4vyfUSmYYDNyHCHRb6AOkEgI+GAxqUB+PaRgMQ4znxhh44QPtIF9LlRlwkqWpVVXFZDIpCttqtcr15HthtFer1RPCDOWgfRhp5svZCM6nAhC0gsKiMCgIf6OkhHHb7TYuLy/j5uamEGYgz+l0GmdnZ7U5Iq5+/fp1DAaDwiVgRGxEc2bD89zEvHsuM8LLx7N56ouLi7IQI5dOHgrys1fKnYmIMjB4UAgaBG00GsVisYgf//jHsVgsilBQLZTztrQX2A5zymBCiFxdXdVW7Di+QbCw/vSX1AWL682021pzPRbfOWun69ioz3tgISQICv1CUJwFALJDTEH0efWUC028iMREJ2OI8puRx0uaaANZ8B1e2GWjKLSJSuCsiaGqqsocQdbl7AfPn81m8e7du2LYgcaXl5fx+vXrWqqNZ7NvW6/XK8Z7MBiU+BsugBDEfNFut4u7u7vodrvx4sWLMqc4D8bQ6S0jkhyHe9ys7LTh0PFsnhoLzKBlYsyUf8R+UwVbrxwbAW+96IGBPjp6XC652Wzihz/8YWF5IyImk0kxMDzbRoZnn5ycxGg0KucRk9/e3sbd3V1hThE0DImr0QxLgUvtdrsgF7xSZm5dPmlWlX7iSSnoobiEa8l50y5yzbDasM1ONe52uyJ4zuej7IyBq/+AznghvDGMLc8irnSRCFC40+kUggyFa+I2TM5xT5bOOnRyzhuSik0NQIWOR6+vr2O1WpVacdoM6mFOe71eLBaL2saAVkj6aw+KYlPjwEYURplGW5ZHE6fmD3wgD7+UijIssOt3cwrHFgnFYjL5wdMg4Ey+JxyFHA6H8Vd/9Vdxd3dXzqPM0zGZEQFenyWWCHWn0ymCwYZ1tBVrPh6PSxxHZRrPtSVFEan4Ig0EyeISQYiVLOgIJEpCzNjv92v9QlkpawRiM14oK9d4QUrE022L8fAc9iZGYeTw+Zu8asReSUEZ3sTABBH9RAZADkdHR4UIM9GEcGeFplYAAg/DhGKT437z5k3c3t7GxcVFKUgCsrdarXj58mVBFGdnZ3F9fd1IdhouEwJMJpPaWnvOy9xKJsJAHB5jyytz95UTZaQTIvbLzgwlHC/TSENC3yez5u4cAgQRQdGHY1QglBlkryxCMEejUUTsoThvRnCVFN4H6IUnJI7cbDaFnGFycq4biI7iss4bC844RDxdF24ijTiWNAmsL/dBsSOilH6aOFsul4XMQTlYodRut2M2m5VVWhbGLHj2PIavXhtNbE5tNqgELoI+2pgTU3e73RiNRgVlZFlwKHB/f182NvDWP5Y/xghv/PDwEG/evInJZBKvXr2K0WhU5gyybDabFblAFmizSS0rOE6N2BolzArqeebIsJyxidinLAk9mo5nU2qEkP8dIztWNqPJbw+WO5rZcLwa+cyf/exnxbpH1As8sPBUWPmeLLlEmBaLRVxfX5fyVPLBriFH8egn1r/dbj/Z89lxIZ41IsruKXit6+vrWCwWRbksPNScE+si9MBX1glTT47CYHh4I0puE68rguiiygzl8nJAz6+hekTUcrEgNKHMs2YAACAASURBVBSI3K7TWGbUmVPGlMzD5eVlnJ2dlbSdvaSRSavVqi18obafMXd5q2seMpH4ySefxHQ6jW9+85ulPJlCE9J7RlBGF+ZA6Pd8Pi+LSTAy7m+G3JkERQfMKdBWO798PBv8tvJZoW1p3bCstMTJWCk8q+tkgVYs7vcOoHhJvHaGP1zvfbpZOH9zcxPj8bgoOUqQYyEEh0ULd3d3sV6vawtSMAgRdWXwpA0Gg0LOwLSOx+ManKZ0FCPitc4Itos4QDBUas3n83jx4kURaAumyUmU4MMPP3wUkM/rBbIi0i+KT2ywI/bLPoH/VNlhcEBlXizDpoAffvhhvHz5ssZI20NipIHb7FLiVX2gFwyhx94OBDRBXyeTSfz0pz+N169fR7fbLQU8GGD4C9ph+fXfjHNEFLIVNt/jbuNA3G1ZyzxQU0iUj2dVasfQfJahnA86YeW2AXDsBWNMxRhb05jlRQgyvDcs43oEiIIKLK49MtewdHAymcTV1VXJhSOki8UixuNxjEaj4j1zDGsrj6IigP1+v8BIKyDHarUquWCUG2Vbr9e1SiwUHKaZcAilJ43FWLbb7dobTTAgGFSQAcaCKjrPJ+MOqw0aQDEx1FVVlXQU5B/vq2KsCHNMTEFMrtePGwve3t7WCEHaYvnCODEuOWMAMgK9fPLJJ7HdbuP8/LzwEKTFfv7znz+RXWdUrHgsiIGQBF1iIE28cY1z07kvu92urCo8dDzrS+et0HTajaMzbjy/rcz2KoZR5HzJBR+KW5xKw4NUVVXWeNMOSByU2fCImGq9XpcCFuJhhNoQyUz52dlZbQUZ48CkQuLQThaPsCIIL2cPwzMi9oULwOtsxfEQk8mkKAZvosCQuAaeNJehookpSCzicfpkg4nRG4/HxYMy18TeQGviYhQbT+WwDC9Gnpk0IeiINpiRtgJbxpAlcujOWIB0NptNfPbZZ9Hr9eL73/9+6f/p6WmtNt9lqkYSoADzMdwXQ4qjsdybnzCqsCxnI5+PZ1NqDjfYyplhB530ulm8py0zE2XiBAU6lL9jAFzUgmf0AOW8JQcDTPEK62oNj+gjE8JySDz5aDQqK4fwRIZ/GBKEkriMFTl4WuJe0kk2KOYxCF9oO2koxgNCjBicxTIQMaSeHCs7DWcW3v0GqbAWHGMEUccbHEFItJ1201engbiOZ43H47i6uipGjZSaDSQ8hMMvzxFGFLR2enpaiEsM0Ha7jXfv3sXbt2/jO9/5Tgkf2CDBcbJlLcfOXkBiXbDhwgA4xrYRd/t9r6bjWeE3A5MVmu8jomZZsWKQM1hwhBNYgofF0uUXu/EsK52LJyL2Qu/4HSjpNBw5T5TJJYERUawuFtbVVig3wnh/f1+W/PFMlAWlMLnIM0iVIfCwsy5s8PhwPbEnyue8/Ha7Lcbp9PS0zAWGBM+FoqIk9rb0k7ZhmL0hI96VlKOhtQ0jigsisrFknMbjcbx7964w6EZgufLMRJnl0PLp+aJ/ZCWYz9VqFZ999lkh7mazWSkFvr6+PogujRI8PqznBo4zThFRuAeTbiaOd7td2bLK+9bl49kqyjygTYqcD8cYKDNw1ZCT8lAmxGkRx3SeQCadtkVEbTsitk/y6irg6tXVVUlp4OFcUUYY4BQZ7WQisMIsdBiPx2Vy8UTkSDPjT6zHmALjLy4uinJk+O/xRticTsOQ2dBhJHPMS5+4h9dhV1VVyoA9P2yhyxJRGzYgu8MbCEsyD4wtCG0+n8fV1VW8e/eurLKL2G9wb/lg3FAiyoLJHji1yVzSXtrMmgWMzsPDQ/z85z+P0WhU6sL7/X6RGXM42XNbHzDEjIlXqyEnRo4ZMUbsuZ+vXKkNqzPUzmQY57k4BRLMUMpliUxGxL7Chol1qaHTZlYW7k+t9G63K/CTQb29vS1xM5877cD/sNwII8aG/DjX4LW22/02RcSVJmMQLsgsp30QUi9HZWxchOH74KVps/eIY5EBY4/icRgt2FBQgYbxNWxHEYnvUUBII3sezytKiMFA4CeTSXz66ae1giKjMddQZ/ljDCKiGFWKZDByOA7aSUjT6/Xi/Py8GCBKTr/xjW9Et9sttd9wD46FOZpYbsfvrqXnnFwEBKrifozRL4Uoi6gH9bb+Vjp+OzUDNPNOJdyPXCST7iNDLMfQhuGwraSS2Ac8IkoZIYsPMpNuoXCIgQczGedYks9zbvTNmzcxm83igw8+KN6Ka1FcKxaQ2yuAEA4Uy6WEKPtisSjL/wgNjHBs0BAmDCxj58/txTEeFJh4Vw7npU0OYhBIB5IyOj8/L2nCd+/exaeffvpkbbqNHEjExKxTejzPRCsr5yg7ZRGQz8NonZ2dFeNwc3NTdjgB5Y1Go7i9va05FsaE+aPNVk76YAPJDjrmKLLyMpboRNPxrDF102GGlIGxF8YqMrB4OD6PiCc7RzhllVNg/h2xL9nkbQzeY2w2m8Xbt29r5a1WRgyMc60YGDxtxH5HU5Qi7w+NAjFGGITRaFTW+tqDZgKFccJi028MDnDf421h9Ziw4UIm1GzETHZ5pRHtQQlpB7lWlCHzKn4+IYU3N7i6uoqrq6u4u7sr7bU8ebWUY2/6aw6GccNpYIAZQ9aDs0Oo5xHlwhg+PDzE3d1dvHr1qjyf/dIcPtoI5vDTsXceu4go67zzoh2PNZzBoePZ4DcDz8FgeztdE2RYLBrtgTDkQBD4jnubcLF3YTAi9jlbNj1wWoadMKnucoxoCGmFNvLwMlAUzudbsMlXYtFbrcfCkdvb2xIakON2uouxwah5+2KIOHsuqu2w+jyHNcwILT+UNkbsEclqtSqb6uGhLLTO/dqY4WUs6IyVeRIvc72/v49PP/003r59WwwZimgW2LEmRs1xOHPVxLGAVBzaUF56f39f1uLbMKxWqzJmIBGvRaBOgPZkwpaxgXjDONLOiP2rm0n3UQHolX25buLQ8WyeGiWGJEGhYX+B0sBIJtzMpwmDbAEjoiY0eIgmyO17D4fDEscwYWzhyz0j9nE3XgkFsuFwzI/Fvb6+LpabiTOz7TjV8a8FxWu/KVN0ysveyDGc2VwTXRgzCCSHCvZaJt2MfPBUtNl5/IgoRBvhCkqNEtrLek4cBrAbKYtc6CNtyYrNGPoZjLF5Cc8VcpDXI+CEMKx4bu8iy6aDoDv+hmhjF1GPiefeDsgymY0PoVVVVWWREXpC6Gnk1nQ829LLy8vL2psqGTizn5zr2MNQ2TGyY3G+47eZXY58PsJJNY7jKyYyIp4oAXGp8+isfgIisbDCRsYxNZ+btLP3QqnslR8eHkrhRt60wau1HJ9F1NN6/E1OHtKMclj6yFwA63a7XW0TPVdjYZx9DbtnQjY6fnacydxi7Hu9XiEkDWG5L2MOIvDfTYjAbfN3jqctWyAu5IPPCP8++OCDEnJZAbm3awxARJY3z0H23vTVm0PYcFZVVZanQqgyf8jHoeNZlLrdbserV68KRMTLMSiGDk2xluNrYgxbOyslA0iM4zjbA8Q+3iZT7u7uyooecuRAKaCSPSPPppaaPK89L2jB5BbCBEuMV0PpERgE2rGo874o1mAwqIUhRi6Z7c9oh3O8BpxxBdYDKauqekImWfgdFhmB+HnMDwJuBMWe635hgUkiw3q33QpkxcWwGwpjTG34aDNzYH6Hce10OuXFBMTQcBBAaMsbiz6MSmzYbKBsaPxKJcYwh5IQifTF2Z+m49li6rdv3xbBN2Wf00wocJNS2zMgpNni2QNkD2ghd2E/se/19XWNjOAZrmdGUbfb/TpZQ0DnEfmbtJG9jicYQohJQgGcOssEExkBKstYq4sQWmhdTsnhajKIMCCkvU/EPtVC2zOLy1hR020P5fMQPCMQjCJGnrjaqS17eowhYQIVcFYQ5pT7G9Z7jJAFE4lWfM+PibSjo6N4+fJlQTHEuXAOGD8bBRsvG1QfRjAeO9pnxAHn8M1vfrOGOJqOZ1Hq9XodP/nJTyLiaVrLVHwTO83hOBXCx/FItvxOJfkcLDvrfPG4V1dXNVIIxclGw0SKN9TLtexWRp7pN3egVBF7xeBve4uIvWfKhou4lxVkvGrV45JJPgwkzzDZBfkSETWjYhII1ME1XjmXCyOsZDyPz51io3Ci3++XAhwMrT0b4+ulq3znkmHzFUZCjpkZc/Y2c6bA2QiTc8wlfMu3v/3tMjbz+TzOz89LfI5iNzkdGz176Qy5MfB2erQPMpeS0zz2Pp7NUzuGzPGtYwzDKAs6nadTfkOFCZOs2IaTxG5sWYNSw3Tvdo9ld7nu1nt6U8dM3BNR39aVZzkn6jjWaQjOA+q5/UBr+oC3NMEDLwFTzVY7VEGR5jCcg+mlT65gwztC/sDKc66LWTicv85LGlFcxhJlJoTwnl9+NvdiSyYM79HRUW3jSsIFZwJyPxgDx73MW1VVRSk4t9/v10IFZCmnHSeTSbx79y4+/PDDkjmJiFLuSXu9Dp52+L58xnj5uZZlF53YeRzy+j6edZWWLXVOKzTBFCaC/62kmWTgyBDG94HEYeBRKDY/QChpo0tJvUuHa6xpi/kBnmXm3Ww/u4rAiKOc7g/EEdVf3poYMhGFpD0UlSBUEIFwASi3918nnqb4hnHGsNGPnHNlXIwmnI/m7R9+6VxE1PZ0Q6FZpIISY/w6ncedVF0ayzi1Wvu3RfK9eQGPOX02mZeP7FhAV7z4EGPgObu5uYlWqxXf+ta3inFhvhw6WRab0Axy6/g5y7jl2+ERffnK4XfE04F059wJwzQfTfG3v8tMo2toeX5V7d/QwYAAYYFRTDyMMEv6/OaIbFXtYWDKHfPTxkyauZQQ1EB7XAtNTMyE8xxvbxsRRXm5NztZAj/5vN1ul/p1Uno2EginXyPbxFfQbis7xSp+57b7mMlMDCZtN7fit6BARlKGaSjK/LFGm3Ennx6xVxqjHnt55tHwG0MKEUdpKec/PDyUqrLLy8sawegQKq8zoH0eT/63zOQje+RDf+fjWctEDV/yYehqq5k7ayXhs6b4IyJqwmiYi/B0Op3ysm4UCE/IYgsW3Lsdznsi/MRSEfV11IZyzi1ni+7+oVgoIl6QPmaYhvDbYDkWbbfbZVECz1sul2UVlONofqNUOUY02nJ4hMEi5nVFGUqaF5oAa2mrqwkZZ7Zzms1mMR6PC0FGW1yg4RponsHuN4yb0RohDuNHX8wtZEOAIWL+1+vHbadev35d0qOWt8yKm5v5Ir3AWTV9Z+NqY9l0PGvxSdNvf28oR6PtISL28YctoeF5HgAruTfOx4LCKjrHyDbAFD44BkPggX4IhSfOE2Fixm11iSnejBDACylIIUEOmliyMjlMwcvYGLhwAybYJJmXUXrMgZrMS5OBddyP4SKLwPWGjbS33W7XFnWASHa7XUlv+RU5NlQ27k0EF0YT1GOPCF9AHG3Iztx6AwuTZKzjJoyoqsdtkq+urmr7w3uBjR1CDi8tr+6XkSvyxzgbsREyNqFbjmdV6ibcnwmBrMT5czppqJbvlUkOfiBNECAm2MQVpBlF/pzPhJK24BmZ4HOMZA9tmMokEOdCJhlaEz4A5fxMlIc220OZMHIqCsjKGLiKyujAKIf+mFm2INqjMUbEoYbyjKOZZsgyG2ITaiYBbeyrar+nGoYERXdYkHdwpc9m/w3jvcmD337JWOfwDnTGfdiNJssYGY+s3FknbPj8v+UII4ujYA5AfoeOZ1VqCwaHldKBfyYMDsGTpjglW0V7B7zbyclJWXkV8ShwLBrAe9AGW/P7+/uSm3ZMlPtWVfuXmO92uyI4fI7iEat5+xwmzxsw8FoclMb8Q2ZCMQqZTEOpILMYe7P0bofnDc/najILG+eCLF69ehXtdjuurq4K0Ycyeb4wbl6XDWpgXbPDKATaBosxpr9+AwnXW4lzOBQRJcQiJLq/vy/vmWajQcfSmdPYbh+rEXmXNwbZr/S1rGan5eq0rB8mcDOC5R5feUxt73tI8dyBDCXs5RxL2Mrlcw/F2sDliP27fbvdbnkpvL0AcNAxHt7B7TEB5vd1AZWZKDwbHoidNYg3d7tdQQLEn7xNMiKKYfHKKXuAJqPIWNJvV1nZW2elsQBD0nF/56aZQ34fHT1utI8xgJE3M84zndoyzEXBzNhvt9tSiQg7boUlTeddZVywwRi4zRhbvidEgaTEEN/f38eLFy9q7yJnjL1dMWlOnsN4ZVK46W9kxEjJis851iPL8y+FKMtKeKigIitstkpMBELJAByC9xF7djpiv8MJe0p1Op3ahnUYBOqcI/YVPXmta8S+UIXabDbzMwvtOnKXizruJC5kM4HFYlGUmBQYBA9kFDATeE6IgFfkPCu0hYFwAu9r4g4h4znb7bbEk4y5eY6q2ufaGcP1+vGtjxhMcwfEwCARDChjxjvK2JmVOcgbCTBX3kSDPercF77jWYbgnkfGB3TDK4kjHl95OxgMSjs5ZzAYlNTbfD4vry/muU1pqnzYQyPLdiZ2fBg05M6Gpul49pgaT3N1dRV/8Rd/EdvtY+E/kOl73/tefP/7368pc2ZnURQUK3ulQ0ggb83b7XbLHtHe0AACBSFgIE1e8cI0NtPzogoG2ROFgJntBnrvdrtStgpxlhELhgEhs7JyHV6OuBHF4b1d3Ifnm/xhL2oTMygMwoniRNSNtBlYl8Li2Vj5Zu/JeBuWEjpgxHgGxBvzkktmMTSQYpTPIjtAWyM2w3AX9GSegQNDMZ/P4+XLl2VBhUm/iMf6dW8kSRiVFTnH2Dme5hy3Myu9deJ9x1eym2hVVXF6ehq/+7u/Gz/+8Y/jj/7oj+LFixdxc3NTXgdqaJuFJ6L+FoSmjuVBxBt6ch8eHp5sUUT9M7AOxhlFg7HlLRYIa4ZLtqZ4iRwvYcUfHh5KAQjxusMGx4B4MMgrYk8Op9+I1fBkzoszboafKAdwORu5/AJ3x3LAZSsK8btfKIfCMTYgJwwMKMqvR6KvRllWwu12v/OLNyBkfJgXQieeg4FyoRCyhUJiZEAJrr9+8eJFGaeHh4dixBwfH4LblhPGr+kzK7bHOqNX+tJ0PLtSR+xj5xcvXsQf/uEfxm//9m/Hj3/84/jN3/zN+PM///P4zne+ExFPrZk7YQbciu7OmrUlh8vgbDaP29GQKqmqqggf3zN5tt6TyaTmnemPYyILmxXb8atjO5QLWGor7343Fb5MJpOy1ZMZZzwhzOzp6WmZfLeD+7ue29AURXDKywJLPz32Jg+5ljSRn2kDx1xS0wyaMsryIg1CD5CfIT39I/630eIZGKocBpptjojCbbhsd7lcxrt376LX68U3vvGNJwbSBCjyATy2h80KjF4wvvbQht0+mgpb8vGVbGdEo9frdfzwhz8sgs+Wq/nc3GgGsckK2iMyYI7D+IxCBhQTaI5yA6VJSxBfQdaY7CK3jSLlPKottwk7v6zecdFmsymFIU7HYGzcb3varNgIOffGUNgQ4qX4nnvgDQlxaKeVivF2f+1VUFxzFTZ0EVFSehgmxoXlhXh8OA6IMoyEPSPw2yiPdCIKTQwKy54NbWbGIU5RHuZxs9nE9fV1DIfD+OCDD2qrzMybEB4wBllGM4kbEU+MTNYDI1ejnEPHsy3osDWn4S9evIjf+73fi7/8y7+M0WgUf/zHfxy/9mu/VvOwnOsYzvf0pNhjMgCtVqswlBzz+by8UQEltmX1IgZeM0sekh/HdXgz0IOF1nEd52PNiVcdAyOECDmGwvtp0/8cNzot400Et9tteTdzt9st2yJFRClq4TDDnZFPnsOMZOg7fYQ4IgPgdkVEibEJc0AD/O73++VlhRFRQgnOfXh4qM2jPTHGlrmEd+AzVuphhDAkzBlGEUNoueKz9fpx7/Fu9/Gl8uZWeAmejR3X+l5GX9lY8n9WaIxl9vaHjmdNaXFsNpv45JNP4vd///djsVjEj370o1LG+Fu/9Vvx8uXLWtxgIeLIVi5DWguclQcIDfHC2xUc02FQWF7p3VkstLbK5C0haiL2xRSZxaRdkCiwp36h23q9rrHVXIcHR9kNaXmmoRr9RulBK2dnZ0VBUCrHr3gXV6Uxtja4eceViD3ctKASr/N8SkAZO95W4rx0xH5RCukiFIzUIYtAHO86pUQxCbGxORorhdfXsxiFvjbJE9eu1+t4+/ZtGVN7eyMe5tBxcZZbH1bkHEP7bxcAHTqe1VNjzRmA733ve1FVVfzgBz8oDf3www9rpFPuBP9zWNiyl47Yl2NSFon3iIhS3MB33tqH/bHwJmzsz6TBWhtWoqhs7G5CxqWcXhoYsX8FL+9CpgQR4XQ12WAwiFarVfpgMmi73ZbPc+4So9Rqtco2vBcXF2X1kll+lM612FkAc9znuclVXJ1Opxgs8weUv7ZarbKxHts1oVQZfuLVGP9DyrHb7QpEB9UwXhBfKAT9Mzk5HA5jt9uVUAv5AjVQPYYB//TTT8s2UzyLMC73AcOT5TkrvcMYf+a/6csvhShDSGlkv9+P7373u7V4wl6XhvN/tlT2XlmZDRu9lxUkB7nKiP2OogjwcrksO0lGRImlgd32sjl2og3D4bDsV433QDDMYtJevnOcjUcaDAZlgQRowPDQ44ZQ5bdEYEwj9nAPdIJw46UYK4SOucnQMKIOJR0v470JG4C3kGbEtF5Jl6vfzH9wjjdOMCIxU89zrdBZscwBYKRBPBiciD2xxsYNIB1kxl50vV7H7e1tjEajiIgiY6Axh4l2AjzfY5jH0+31wZhk0jEfz7pFMANuMsJwNCupPUQT9GCCfD+f00QKkf+M2MdGxKvz+Tyur68LmkCRXSiBtcYDRexTJfa8rkl2AQde0MKPR8j13wjYaDQq8BMjQd8szBFR9uzGKCE08/m8GAXy7DYw3KPJQxgJeNxyjG8BdD+qqipvBI2os9Cr1ar2zu9Op1Pb59xv4dztdmUTg1zTjqLZ89K3XBuQSSjON8KI2FfdQaqdnZ3FeDx+wvnQDpboAsPhB8x8N4WTGYnyGed4nphP597f56Ujnpn9ztCYQfUE8H3T+b5XZpgNxRwbE995V0mvzgI1XF9fx5s3b4qnspA6v+v0F8KZywsj9gKBsqDAPoe2W8DNZhILe+GD40YrGsyujSQHAsb3m82meDKeiWehvRgUno/i0WYElTbk1JDHbrVala13skC7VtuC2263y/ZAZBZgoxFm2srcoHxeIZUFPqMN2uP8eUQUvoF20T9eMuCtk5G17XYbt7e38erVq/K2FzsmtyHzQxhCzynta0KpnvecCcrHs3lqT4Qb4DjB1Uq+psmSZeLBkDGXhPK9q5hMkvC6m7wNjXc8xaMb7nAfw1wUOKK+uZ8NSW4v4+CwIGKvjFbyXKnmyY2Iwvw6nrORIyRgAwCE2GWpeEaTShZC4tLcBn8HugHhQBhF7D2nt4tmrq6uruL6+rp4OarLbm9vi6d3uGEykPDI6569LZVJP1ALiAWFtgzZIYAkut1unJycRL/fL2SdUdp4PI7ZbBYXFxdlnrvdbq3tRkEe24xG7fxszJ22czHNoePZPLWZS5Q7N8bwzkcT/DapY3hiuG4FQakzhNxuH1/rAhuLcniFFZPfarWelING1Bec5HgNAYqI2tsTM3oYDoe1FIiRBhAU9hZFNEnndBj8hT12jjuNWPgeg4PxY/wyI+0CmTw/NpbcE2IOYXR6qd/vl4zBYrGITz75JK6uruLi4qKkEiOiGFgUrN2ub7pg3oD2Y7BdF41TocINY0YIhrFjbDEODr2QneFwWHs/OH0jW8LYExJk499kFJvkvskA4ExY8PI+BvxZNx50eidDjkyQcZjd5rdjojw4vg8CRomhXx2KhWZbYEgNe5Z2ux0XFxcF2qLkEft1rLSFzwkBzA/k4hNenzKbzcoyTN8Xxh1IScEFKRzq1vEYwGGUGw/rmmjnZVn0wfMcVtBOQ2JiOObOe47ZQDDuPBdSKysW805NOOnF6XRaI9TYEqndbpe0lBfZQCpaZswE53DHeetWq1VeGICxq6rH7Z1g5T1+EfX12IzVaDSqMfsoGuw4MuhqOMuuZbvpcBhmUo3/TTgeOp61TDR76eypLdycnxU8Ew0oSo6nUVJ7E6w992LjeO7lggY2vTP0YSIzOWWh8aAb/nqHj+FwWApiyLPe3NxERD1k8LJDvCpKwH0Hg0FZFoji4SURHu5HZdbZ2VkcHx/X6sSBkCa+Iup7yRnqO2b3gQc0muAa5sExOyw38DniMW1HDA+6IzfMtaSSsifjf2cbbOxBdvTTTgI0dHt7W3YW9VxhLDDE3Kvf75eqOPo8n89r6xhyMVWG4DYUblPTOUZxjO0vRakdf9rDmcHNHfuy92yCKHmygM4wp7yNw2WWDJZXIwG3OfDaEVEbWLYOtkWlLY7jaTcxL567qqrive0RvOrKaR/HgZvNJgaDQfT7/fIidRszT77LWjECfpUO53qLJocxNmiG2kYkFjriPkpAMW7mH1Bc+o0xxvtlwtJFJF7uud1uy1jmUM9z5zjcY4OXd2kwbDb1ExgLx7QRUd7kwtiATpBn+uUae+TDB3NrmN6kC9zXzuLQ8awxdUTzulFD6wy3uSZ/5kFpOpdnmoQxRGPdMwdKQP05HhwFscX3WyGIp7zTJZPoMMHP8La5eJV2u11y0uSlnbZxnAtZ4v6v1+uyJhxvSVud7oEbQLjxQrSHZwLrbJysBO4jCm2lRrGJV4H/WVERSF4bu1gsSl0+RstpL/plyM89iV0zK24DYnLJsgJP4rHlPnd3d7HdPpY1D4fDIgtOC65WqxgOh2VceQUTBUWWB8tqVmpk2+FcZsORJa4/FJNzPHtMzUQ0MXZZqQ3x7MUPxeI+zwMDrKTzvFmDc4hNrAxO0djSA3UoSKF/7ieCRhv5jBQSwuP6bFt0b0Tg3Uo4UG5nC6qqKu1yagujRirGddSMkwkyCyr9zR7P3qapn4f5ywAAIABJREFUMCLPUVU9bs08Go2iqqry6qWqqkreHAOLUaM9jInnlz4xhhjFXIpquXAYUFX7hSpeBJILlRzeLRaL+NnPfhbn5+fx+vXrWpjEuDkNhxc1NLaBzyFk02EEQtuzvOQws+l4Vk+NYtNYKwOHldnCYSXlO9+DZ9giGsoxWZvNpuxD5uc5tVFV+5Va9iZYYAggkz9Mkicwoh5LegwwcLDseBV+nBfmegSP+BLB88IOKyLP9NjgiTBccAeEHWZqyVg0jb8LNqzgWZHMeLNA5f7+vigysN9ohnk1Y4wy8j/zSjjl3V5MRjF2GEfGycU/nGPUh1zQf867vb2N7XYb3/rWtwpiQ8EJb1DqXPSCcaJt9rS0i88ylxSxr4NwO/1ihkPHs3nqiCgDmeERDc+e2eSGLRv/Z6X3hHA4r4zH9hY6xLSQJ16gADlFGsoVYLSfz1yoQDvxAi5O4VkZPjtGQtms4HnpHwLk0MCkF+kyPCmFG0BQ5oP7eDsgOADPUWZrmRfnc30tOWp7FbcNOXAcjTHFA3c6nWLw4EPcBowTPIILZ7KR4HzOs9KbwzAqIWTJCGq9Xsenn35a3qWF/PI86umdosz8QzaSlnnPZf7NeZYBZ2Wajmf11C7+yLG1YwMrclbe/L2JsqxUVgQUhDQGVnQ0GtX+933xqsTfKL6rjjAUi8WieDs8fCbIXG/unDkkHoJtwsXj5G1pnQqi300wFVYWIsc5bI7tdlsMHemerKg2JoyXvSnzgFJhRFiDjhFzRZ7b68U01NuboPR8kMYzqWmjbCVuMpI22iizqwYdzliO7CweHh7ipz/9abx8+bK8K9yeHS9uFj57Y8bD984kq8NMozPG+u7urtQxHDqezVMjTMBWvGREfZN4e2T/79/2ylnh7fGtJFxLLA1plO/vXCwwvar2lUmZucXLRESJoeinjQQKBRNMHtYhCXDUtcW+FnY74lEYYNtRLDP5hnUIJ8qC4uIJfb7RB4bJYxixj6mbns31meiiDyiPYTfzMRwO4/T0NEajUXzyySdxfX39pNjGZCGxdUTUXqObnQRHDss8vkYmlknmkXZU1b4QhRCONKE3d8Rw8pJ4O54czthY5NCB73NISltd+nvo+EpSWq4Bxso69sxQ+n1kmO/v/x3f4XWYDCYVNpb4jomEgcXD2CPxfD/TrHEmcSzwu92utoEeoYGVB7gdsa/cQol4OySkE6jBMJf2GYL6WXhMFNtxKv8bcnpMs5ehv8yFMwIOVXwuhUAm45iLly9fltLPiH3pKikm4ufsmZbLZQlRQD25iszcAHMHJ2DuAKOcyVEIPIdzKOtkMik5bRsDb5JI/33wf4bch44ci9uove941i2CI/bKRjzED0JG4zmyUmdyjM/c4Wwg+NwlkbwNEg9GGyeTSdldlO8QRhNdEXWyzj+bzaZUb9kT2sIC66z8CDAe1dDXnu/o6CguLi5KldxkMqltOAAjyvX5ZfKMn1eaEe+6TYy5q8nsNQwF7R1t7GgLz+deDkV6vV4MBoMYjUZFKT744IO4urqKbrdbijtcgIKx435+j5XJTbysDZ7DHubHfXPYhIc26snPu7+/j9vb29r68CZZth4cOrKM5NjboRD/w74fOp59lVYWfmJJx4YRT+Pq3DnfN+LpPtQ5BkEpIIUi9qkPvOlkMilrqbkvEHW32xWP5wULZlBpB33inIh9ztyEDIaCFVOMw2w2K8rG+Xg4tvfpdDrxwQcfxGq1Kosg6J/TXRH7d4hhSIhn7ZF4Pn3w2NloMjd5DjxPjl0pZwWGcl+En7JN57AJkT788MNaWggIz26nxO1uKzJDDG0CrYmXsfHLntD9NANtA+XFO+zN7k0uPS6G+F4RlkOmTHy6PTk8tcE6dHwlSy9z410uaCiar+ewAttzm/E0HCYm3mwed9sgreKU19XVVVxdXZXzzLZ6cJ2r9cTwLAQJhY/YV6p5YlgQAKwcDoeF9AHWcS33JM8MUWR2nb2mvesloY4V3FVp/A1sRfA8jjaUNq72GHyXuQSPB6jA78Cmr0Bu3tlNueXLly9LIRCloey97VVYEVGrLHNo533IQF5ZmbKBy47AKMQood1uFzlqtVplH3jXjTsMtKHIMtuE5KwvHE3xd47B8/GsMbUbY6vlv1FqQzuucSqL83xkIVuv10XIGfzBYBA3Nzc10uT29rYs7PCAZhiXmUkEFWExW4yQmBGN2AuMlRTFns1mZQ8yhIZ4HYG7v78vigj0Bi241BMOAIWiHdzPGwpYoBlfC4pz/xlqWziB7J4/+mDY7jlH4ciMmBH3opLxeFyu80IJUnd+EZ23pjLCw3l4Po0QzatwPUgrx9QRUQsh4WXm83l5i4flNPMRHkP+tyHnt8e4SYHNhxw6nn2LYP/238SKVqpDUMjf2ZNE1MmrXHCBxzI5t1gs4rPPPqstMMhQx5NoowOMRKk5HDo4fYQywnq7aATGGLiJ16UfhtTOexsqO4aN2JM8CAIQm99Nyuaxy16lyUtwHeGFx85j4HsZzrOAZr1ex8nJSZydndXmh5Di4uKi7ABDzQDfM8fud847O9a34ckhno0QRoOQxcVILol1zTzrv9kCyXKaDWMeX4+r0UWWe6Pbpuq5fHwlMXX+LMcRWeH9N4OB0DUpvOGyJxZiCUjGe4VJTXAAzxxz5QFGiPAmJsa8dRP3cyzl5yFILrrw55vNfumiix9QSq/J9hgZ6Th2tWJ7p5Cci7UCGF5nNOQ+8nwjr2zY3DbQDdeCXoDV3l7Y5avtdrtWpsumEBgj2ua/PabMLc7EfVuv17V3h1sZveOqKxKzF2Zt+NnZWRlL8xNcl2Ntxi8fRolW6lzBd+h41t1EM4vKd00lpDmu4Fyzk/l7zskCDsyiDSjimzdvYjqd1mL5bEws0GY2beU9wAhpU0wcEWWHUtrDvZ1mc9HD0dFReR0q3sm1xnkcWZgBGwqDy17Z/E1O2O9i9ph5owHib8Y959Aj9vn9iPquNK5qM5xnzTpHJu3gJPhdVY8149PptCgW0DgrTYb5GGbm1vPnOfI88sO1Vh4WqGBgIupvg1mvH1/wd3p6WmP5DymgZS3Lr/vR5AQP6YGPZ42pDdHc8BxXNyl2hixWbA+Wz+G5TM58Pi8x5XK5jNvb2yeVZM5HI0z9fr94EAsAcJl+cQ+Xb+JlEI6IqHkQFIh9wPD4nIfHgDxy7tzMvFl89z0iajEm7OxwOCyxn70n1wAdm8YW4UWonWmg3fxmYwdXlrXb7UJI8sN6cCsVL/a7urqK6XRadkJx4RJjauORy13x9u6DOQb6hHHD8zpORS7oJ+ggoyfGa7lcxnK5LJsQYrS8kg+dME+TD3+WdYjxsjNqOp59lZaFvek8K7aVG8ufFdwGwrGS7xfxCNHm83lRzvF4/MSIcA8rA+kWw1lDS3uv3CbaTjFGjttQHCYHSJnjcbwVTO98Po/1el22o/UeWq6iM2Qn9jP0zjGl+2+2vsnLZSOc54Q+AVUnk0nc3d3VwoqI/YYDDjVAPCY5Yb4j6tvv2vDYUyP8EU89Hf30PKDUjCMGC0/vfjMOHkeHXTxjOp3Ghx9+WNqXjVFGg4xdll3PD33JmRcjpXw8a+13HtgmeJ2P7Nk5PADZO2fiACHDik8mk5hMJkUBGCTHbH4vFRPNBHN+JqbsedyuHP+TN7YB4bdXUOGpO53Ht0yADBwvsn8aAmqPwrgB1xkX58R5Nm1z+81iN8FVG2v6b+SEwaKYhjAie/yqqmovTaCWmnp1UpAOCbKHdZstb6CTTJYZDqPM1Mm7wISQJZNnJtQ4F9TGXHtftowos7wzxtmxNemBw1X6nZfn+vhKXpCXG+q/3/dj8sbWOd/bXhVBhYDabDalYowJQmGBMhcXF0WpyFdbYU1uIBzEeOYOsOwIF5DTlpbJxCvZ+nIeMRyv54mIJ9Dx9PQ0Tk9Py75f3kfM4YXZbxel+JkcHmuPqb2ViSKPv+eHzyKipO82m01ty6jlchm73X5f7+Pj4xgMBuX+zINz6xH7ijTm14qLkXOxCIbdChSxX1dtWYvYvzqpqvbbQjOOjA3tOj4+rr0sYrXav4TeDohxdMiTFT7LcNYVI8uI/Vtdm45nXXp5SFnf992h7w3jMvzyATRCOabTaczn83IfrC6TxqZ8uUghe10mJSJq3i3HnDlOxCt4+SdKRjycN+ojRzoajcqOpJ1Op6RNeJ5f4mfj4LZa4XK44rFD0PhNW5uKaOhnk3IDUV3n7hVqXorLubSdXTldD2By0ugiYu9xgeBWCHs+xtbf+U0lKD3PQDkxOjm3z4Fi8+ZWQiq3x3F6lmcfVvrs2DzGjO1XDr+zV23yrgyC/2863/dqyuX5erPeKDCWFy8L1OZ7BNiDnZU44ummD26/B9iwGuG0cFMdRhEJUDQiarAewglFu7y8jPPz8xpzv1wuYzKZ1BAEbUSotttt2SqpqqpSF845hBeZvLGy5P891jzDGx+4tNLzaONHhR0kY0SUN1qSseCecA+G0LTLmQTa5tViPDtzH03fMR5AaIzM5eVlKRLK94Lf4BoQAC+kz/yFx9if5ZDSz7Bckk5t0gGOZ3/pvIXEjc3f52s8AZ7A3NlM/hju7Ha7AktNgoxGoxgMBqWoAdjrNbYRewtPyaILUQyjPPCZdIIIi4hSTeaKKJjViKh5VyAo3oScrr0jNef0w9DTSuQiF4TCSIP7YbCckuOciP0mC4aTEHtsDcQ5eGHG36nFqnrc7si7t3pFHTErCu211hgQE14YgqxAeF17WRcUwWjTN3tGw308O6vFMkIkvsbQcy6yYDSSx7QJmfp/y3REFL4lI1Qfz6rUhxruz/LfTecZriBECLuvd6FBu90uGwv4fizuMAOdJ9QK6sUehtduq0krPrOhMKvLCwQQtgyBuQ+5W7weaa7BYFCDtK42M+GDx+YZLjeNiNpyzyakkuM+j0meX7yk2eWTk5PyVkvHui5AabX2FXoYVApkttttIdpMLjKfnMO9vNDDxJarvBw6YPRchOIQw0hmvV7HYrGIqqri/Py8tAUDyPzymd9O0qSYIIs8zjmszJ9H7LeUft8SzK+kTDQLh2FckwJHPIXwmXDIcM4xCQo/nU5LjGPWkHsS25rpJs2CsCBQEE18z4QaMdDmvLaX7XzcRhsXs8kIkuEjfSS3Tcxtoo7x8LiRYnIYAdT2Uks+99jmECTH3PbuZpgZp8FgECcnJ+UFBoyTi0y2220MBoNSJRfxuPXubrcrytvpdOLy8jLevXtXjIONgON1PDMKDFqgnw5RbGgIyTIixLAyDsTZbJCAYY7Y161jYCLqIQL/Z7SJrJuMNEr1ecgvxu/Q8V6lrj6u/klEHATvu492/27j5w3K6jQKHckN9rWc02S97LUZEKx3xF4AvWkgimRBhoAyW0qqxSkvtxGlM/THKzRBV3sI+uwVY2bZ8fqOzWinl34izEBbuAYrL96ePljwGTPD/RweOV6mXzXZaCB6uH/Eo3Ken5+XtBV98D7cIIThcFjawU4ttJ1NBi0DGFeXzxpt+N7eNglugfnyQhd7zogocSvoxmip1WrFy5cva+EQYQ1zlEOVph/LhGXfxjQ7NSPAQ8cXeer/4vPfvxMRH0bEf//5/38vIj5734WZ0EIBs4DQaMerPpoIhIj97pYWSP5GqbDa9/f3MRqNam+TMLzB+7EU0LEi7QXCun9ObUTs4zL6ZQ/GZDD5mYHmPATD3hc4yH19Lfetqj3hx/3sVRlH2oIwmlTLmYUmo2uhdNvzHAGDuTeK5XZvt9vyMgO2bcIAmGsgBidvfXZ2VpY9Wib427ljjztoB0VF+fkMJaUOYLfblao/e0/WEHzjG9+oEYSG4aBFe2AjtaaxZdz5nZHUbreLyWRSiqoOHe9V6t1Hu38aEVF9XP3D3Ue7f0Nf/ZPq4+qfve9aN4ZOOu7InWjKsTbBcb53iZ6/x5I7L+zliYalCJs3tvfe3vmniSVer9cl9rO3NSznpW+0EyNgFtYC6JevUWxCzhRIiIeiGgols2fhHhF1I5g9tZXeXpr2ZqV1X5q+R2FGo1FMp9NaH1FYG8yIR7KJcl7iWF6Fs90+5rFvb2/Lc/O7r0A9niNzLswvskYbKRhpt9vllTuWF8ae+3pLKQgxLyMF7tMmDqM6xiHrQUay+Tfzk3mdfHzZmHpQfVz9y7uPdv88IqL6uPqXImLwRRdZGZxqsWJbWTwIGc7xGV6GH0Mcntdu79+6UFWP77IyBPXg8DoaV+iY6ebeOTeKNzAMjKjnhc2Ss/c1Au14C9KHOJJrz87O4uzsLE5OTuLi4iLOz8+j3W6XTR3tMR0DZ+FFyICOXrdshMQ9HQM6rDAct8EFTXihCOM+HA7L6iuIMeJRw9ZutxsffPBBIS7ZNZO5i3jMY7M23jKQyzrNL/gdWi6ppSjG8kB5LwppSE5xiWPx2WxWyoo9H5kAtaPKKNDKbCie5d9OAl7o0PFllfo/iYj/vfq4+ucRUUXEdyLi9953ga1Rjo39+32xWfYC2ZpxOI7lfIyIN61z2qOqqpIusffOA4fByWFBhvoR+/QHngmh4H5MGp6BwhfSUpyP0v/Kr/xKXF5e1tJwXOvctvPCEVE8TRYUhMlvJmlSaMaXNmcIyXjxWZ5H34v42JmIrACr1Sru7u7i1atXcX5+Xrw0aMo12qTvQCOQUzDuEftiHuqzaQNelBJUIwVQEWPEs7k3lX3ZONzc3MTLly8Li9+E1ExC2qHlMMbjmTkQ5on8/l+7+GT30e6Pq4+rfzUi/tbnH/0/u4929++7hgZaqGr3THA2f3fIEtExQ0yu4Xvund/nBHwiXeJyUTw7lpfXk+YYyB6RtkOikL4yrN1sNqUdjilbrcdNDwkXPMGt1mPp6tnZWfHOCC+EjxchZMIuw3WEC8HPxBiHhS/H3BH790DnkMnGm37Tn16vF6enp4W0tCdjXujL9fV1vHr1qrSHsIV4mxe7v337thjgnE9HJjAMEfvN++mP034orxn45XJZikra7XZh5AnXPF7r9eNed7xiyF7ZY2fWO8t6k+zbKNgR4pia9Ibji9jvv7P7aPcn1cfV76Sv/pXq4yp2H+3+16brrLBNREvuAJ83xW2cl2MMP8fWzRVSZ2dnNWaZc29vb2svCmdSORdohtXGOiPUEXtBdjxr/iDHS45XTbzBloIoer1enJ+fx+XlZVkCajgHEsBjIWgsRMg5591u96TuG2/tlT9wHgiRvb8ZcHttz2GG4xiIXq9XdjDBIDnU8kKZ1WoV19fXtbQV4398fFyr7PJ2VMwVFXj2vhktMUZOrdEOngn5BSLA8HjVFf3jZYnT6bS8KMJzlXkHK36Oiz3WlnPrRlVV5QUVh44v8tR/OyL+JCL+nYbvdhHRqNQ08FBcnL93A7OS2+o3VTmZ/EHwiKP6/X7c3t7WIMzNzU3t1bRewOHn8T0xrBljCzdtsSVGqREIJi/DMOBev98vL1nvdrvlbYvOqRMXUzKJUUKZI/bbHTleNnx1FZnZWddAe6wtSE3hkJXT3EkTehqNRoVUJM+PByT/y4aDoBr6w97pt7e3sdls4vT0NNrtdu3Fh26XeQSn/Yi/MV5UlMFo++UArgeHCAXFZYXb7R73VGOf9mxUkRm3w8Sxc+HZuaHkyJszI4eOL2K/P/r8z/9w99HuMN3WcJgcK/eTB3eH3eg8YLX2yNM1PY8DQihir7gRUZYDYnm9xzcCaIXkvobUCFrEUyKJ783Eut8QSXhlGFe8RavVKos2HPMy6WZeEWZ2MvH4ILzAcI+FhS4Lkcc3e4cmXiOHJTwzIzBi0vF4XCvu2e12xXixqQLLJhlLSMG8YT9hi+eCceLAeJpURYmYY3LKbMfssMDpMMYbZcfgIhtUnZ2fn5f43zXadj7uQ9aPHBZlSE/J7y9i3+8fVh9XfxwR/3NE/MnuowMBr45DcbEb2RQH+7ctXL6nB8nfRzzGfsfHx/Hw8BCDwaDEr2x4h3Bkz+8BbbX2b37AcxFfVVVVdvfwtrK0gXOBvC6JpEYatEA8jZDmJZnEh0y+Cx6IRR1fetcTxsJVVS5oYdwyrM5j4bnIB8bbaR4bDJdwwgm4GGWxWMTFxUV0Op0Yj8fFqGF0l8tlKUA5OjqqvcTAFYHZQHvMmBfawnyi1GbuQRDMscuM8doY+u12W+Qr4jHHPhgMaiSfQ5isA5ZZtzOf43kgs/OLWE/9tyLi346I34+I/6b6uPrfIuJ/2n20+9Omk62Y+fMcL7jDVtgm6MeRSQd7WhQEq4oQj8fjsjAA68xvv2USqwuMteBnBaO+eTabFWGBRe33+2W9sxeNcF/az8vsgHYmbExQeVscFIKNHYCzCCWwPsNkxhqjhTG1keUcp038Oxu+7LU9r45lB4NBXFxclBgUItIv8PM+a47jSTuy8wvxPoiGMMK1CYyfQxGyIXh4OJIc7zp9SdgA0QdkzlxOxH7hDHUIoAGXpWa59phbznNI4fOywcrHl2W/5xHxjyPiH1cfVxcR8V9FxD+NiIO8ehPcyJ3hvNyBLzrc8Yh9YQX37PV6NYvOTpUMBkaA2Au2EygFY45lZMAzBIx4TPtcXFzU+ko7UDYXiDje41mQP/y24o/H47i6uir9QXkpQoEZJv3k1/7Qfw5zAva+hqjOUWd4nSE512M8M1S09yO0GI1GsVqt4t27d+U+wG6MmlEJhpdMAbuj+EV0ljXIM7y70YXz6PakjnMj9nEs9+90OqWKjVSixx6IDvIg5s/jyPOIiTP3cUgHsgEgL37o+NILOqqPq78dEf9+RPxbEfHPIuLfe9/5Tew3jcZzeMAPGYCD7Unehns61YVCkwLh+SirBdOL5l0BxWHrjVfx9fTFcQ9eKlfSISjdbjfOz88LaUb6ithzPB6XzfeqqioL9unnarWK6XRae8uiOYc8piaJONxHC7jHPwtbZsWbYnETQ3g/lINX1nAdz8A4QGKhnFVVlX3PuD/Gle+9+AL43Wq1yhZFrvGH9wBCG4XZ2OUXO3If0Fe73S4r51BqvxOc+6DITeiV8TyULfIctdvtsmz2rx1TVx9X/29E/N/x6K3/091Hu9kXXZNhRUTdutuic76tVVZ4fpuhtSJxD5MPx8fHZRMBP9uDhLISa8NKZqMB1AVe73a7UsSQ1zMjSHhBBIL3QiHMvV6vVJpROYannc1mJfW23W7L+mNiffpNPIsA8tI5KzBCH7FP80TU9zvPGQDPo8eYvzMqMQdgz2QPxeotFno45sYAep6YI8ImFApegbCGElP6As8BSkIZ2OHGqU/mnHszVpZRxhv5g53HCDl8ZI7JqXONV8VZ9hn7rCuEETaONlbvc3hf1lP/a7uPduMvee4XHkycLb1j6/dBEH/fZCCYBIRpMpnUoJDjTCYYgfKWRgh+t9st5A0T6Imsqn3hAigkIkr8xz2dEzbUhPCBkCFt5bwokJuCCHbpBIbDzmJoHM9acByLGrVwNHEeedwYO8NHr0zyOV6U4vTaYDCIFy9exG63i5ubmxpqQtnwcMynFcc7xgBfDdsZl6qqyjhvNptiUOEoGHv6B+LBMbhUGBnCKPotqhjWVqtVnuMwz/LHZ02LZyzr2eHRHq9aO3R8WaUeVR9X/21E/Juf//9/RMR/tPto99NDFzTBCB8Z0tlTHzqfQeHHnbeAoqQsJmCSbcGBUL63oZxTT07TuOjERoV2A70RTt6MiPLj9dlKllQJcb+VmKo3hypm2mkr0NGCn2NhIC0wEcX2uVzbxITbe2avjcEghPF4IOieP9hlnkd+mmdgHBh/FI7nQ5zh4VHybHhAN8Bk5sVw2PDb2/+6z5SfggbMvDPntAX47XlCXnPs7L46VPHYmTCE+ea1uoeOL6vU/ygi/oeI+Luf///3P//stw5dwIAZUpjha4qfm8i1pr+z0NoL4EUoTuA6JiTHLc6bk9elIAEFWywWNShrL81z8cYYAJ7TbrdLfG2DhIKz0MExH4JqYUWgebE5z0JJEQD2zIZYo32G5BF7gbGByOPDs20sLJTZEGQG15Cce/NsDN1utyt7fKPYEfsX0LPLKMpNLIyX3u12JXNg2WCMaSvxs2NbjCHPXS6Xtbx/RNTmnYPvqTNgpRcGf71eP1kwYu7A43cIpTp0oV/5+YeOL6vUr3Yf7f6R/v/D6uPqP37fBU3wOn+fhcfCmwWI8/L3dJLYBS/HLqJMGALhtASwqdPplBeIR0SxtsTXrgBqIr5M7kTU37aIEqIcCFxVVeXNjiaveE7ObWPV/R4px5W0yxsKgEiyQclhCG3z+Jp7wABweK4YX3s8P5+xR8FQdK7pdrsFylKwwRzw3m76yL1c+OFS3ywPRjBZmfmeQhj6gjf30k5icO6NgjImhsP0kZV+5m88bvxwryZ9yDLPXOCxDx1fVqmvqo+rvx8R/+Pn//+9iLg6dLItD//TQB9W2tyR93lrp178GSmQXq9XqwvmHAgOSBrW6xKv+vxcNJBhPt/ZK/l74BjnEgvhodmrG8MSsV9TzP8YEeJCIwMbAp5Feszf8TfeLJNkjvsyinJfs0ePqL8fPHsgI6c8jtyH2LTb7cann34a0+m0zBsKdn19XWJ29gVnPCGgHB8bQbgvGD3SThgDPs+1DxhDxgtiDKXlWuQCiM//Du8sP5ZZj4X5Dy+QyT9GwIeOL6vU/yAi/uuI+C/jseb7/4yI333fBU0PzWQAnbX3tSX1QGRl8rU+ByFCOLwCyx4Tj4d3t0CapMmssOG9+8NE2Ni0Wq0YDAbFY7pE02u2MTgudHABCZ7JxQvAULwRJJPTN3AD9NU8xCFF5JkoJOPaVF7qseE8z5MF1PdhjugX/Y6IwiNgZAl9IqK8Xwx5OT09LQrE9Rk6ewktbTLpiXHIhCvjY+LUeW8MpTMosOs8z6y5DYc9dh57j7llu0npDx1fVqmSFb6lAAAgAElEQVT/s4j4D3Yf7W4iIqqPq8t43OroHzSdbOjluIvG0sgmWNFk0WxxM6HAPRznuDjfMBnFGAwGNRjtMIF7ZavoVJdjP+d2PTmkqChXZZUSwmShZqKAmTk+bbVaJVeNlzaLikLj1fHsKDk5dce4hteGxKzgsrfIc5dDK89hE/ymz3xnr8izBoNBYf0ZY84hN0s7jWyqal8TD+tMcYbnjetIb5nDMEtvx+HxHQ6HJVRiDjJflOXX42q0c0i283ceW/4mnWrdycf/n5TWTXnAR7vr6uPqX3/fBYYIOb6yUmar1QTFbR35nQfCSgVxwbNpCznGXEDgUktb9Pz8nJpyO7kmW38WX3hHTa+aMmRDUDACxIHkae0tUFraALz2WmqMjWEpysH/jlcxmJzH3zle5vMskEZYjInHx7KR4efR0VGcnp6WjIX5AHML2+22Flptt9vymhuIQpBP5gIcD3M/8sr00TJrspRUI3Lk1Ju5B+8qY16G73lGdkx5jC1fVnA4ml/EFsGt6uPqInnq916bLXlWVH5n6+4OZUFqgul8h4BHRGFS7VHJj+aJo62+VyaF8Db5pW1uC5a/1WqVHU0iorxjmS1zp9NpuY4wICJKNVtEFKEFvmFIHJPjcXhFLV7ZQkE5pV+DYwvfRH7xY97CUN2xOnMAn5HZ9Byq2IM51IEJJy5FOTHMXvziRTHMKyjEMTceO2K/AaUNp1di0TcXH5HRiIjyPMaT7zOi8Vhg0KnRb4LfTZD7kLMzsfeLUup/GBH/V/Vx9b98/v/fjYj//H0XZOjb1OAmONLksXMnDcHxRkym4Z5zt5BI3he6qqpa3MNvJthFFXhp+mUmGdLEQkPM/PDwUGAxXtPFFI6rEA7nfF0JZi/d7/eLN7LXsFVHuPH4tI/v+J3roA8hpkNCGLHfj9phQ1Xtq7O4zoaWe0DgsewS4svw1/lcox0MHAaPcIdn4p1dHOMtfA+FTyiuD9r98PAQk8mk5MDtaXmmDQHhleWsSd6zXDfNQ+aVmo4vu6Djv/t899C/8/lHv7P7aPeXB8/f1V95eqgTh5S86e8mQ4AAOwdo68sksBwOwfUA+zyuR4FdncW19gQ82wLh93N561lbbrwQyo5XMBR2PGwEAEOOspi4AhYiHNk70Gend7IQ5Xg5e19XjTHXJszys3wfxpXxtjFh3o6Pj8tSzFarVXu/FkUzNmT24hBgeGgrKIptRtrywhw5PcWyThsx+rxaPb5tlJ1dcBLZILjAKXverAsczJG/YxwZU29XnY8vvaDjcyU+qMj5aLIkFg5/dghq5M+zspusshdBEPGoeDhbU663QjinyXkmtuxh3A/uwytjct8oIrEnY+IRTMO9VqtV8uZmob2BnhcXAN290oxxySx+zhOX+U1Cw/VGJrnP+Vr/7zEzymGsI6JmIOzFiRtpC3uV0X5YZ8YMksyogfE27Kb9wHvH5a77xtO6YIV5cf/4nDeUWvkZ+1xSbNSS/2+SLV9XVVXZYw5j1nR8Za/dccPc6OyFD0HArOQZfnMvC663+rEw8hyUy5OPYFuxc07Xk0z+mWupr6YfxOERUTyz40vHdCzlA03AjnNPE2EgAm+15OIYe2hQAOPgElGex2+HIZxvYqyJJzHBZmW2l7YBtaGxwWCsnb/mc+bKcpURlmUN1MLz8fBGVoRI2QNbCU0gck7u62KxqC3iYUxMiOa+Z0+ddaNJqdvtdnnlzy/EU/+LHp7MJkX2/7lj+To+53BMxKA7XmLPaMeUWTgcc3pXEq+9tqfjcDGJ47ucp0QheRaKTXutkIPBoFhgYmqexfMskMBJCB6zsnmjQY8xz7TQejzt2biHYWCeQ+Ypx9o2gB4DDhsRe0nHzCiQycNcKOI10owH5bqWKZ4FPxGx3+Pdc73b7Wovn88OwfejTZPJJM7Ozophtgwjj1mu3X/H8/nH9wOl/dKU2lbVDeP3objifZCb75rOa7VatT2nbHkhX9wGPs9EUm4bSuoJaPK6WH0z5UYFXOPPEED3AY+LQcDYILAosREDoQKfA8MdZ9uLcm97OXsZ7pu9VlYQz0MOT+yJeY7nEvhs5cmvloXoos3OX2M0CFNANiyqgckGjdmIYSAj6kUtTSjC12UZoq3U3LPm3bLblGXgb9qH7GSFzjK/Xq9jOBz+8pTaqaNDin1Icd8Hu5noJiuKIlESSvyEgiMg3luMSXde0TGmj2xUnJ7JkDnDd7wtyoegESchRBgAzqMUkvZ7MT/n8nf2kiATEy/ZQ/g6Gy+OjCr4LCupx4V721OipFzvnL+9KM9xaMF8muiKqMflyEZEFANo+OuQC6N/dHRUdjVl7vH8cAG0y3UBzD3jAnnFpgmeH4+nQyPafAjJul+cg+H4pcJvGtkUizV53iYv/T7PjHA5fjk+Pq697RKhxYsBpV05BmxGMPL7uCLqbLnTdYa4JupMluCZcpyNtzKjzb0xSH5BPX10zI+Xsofl+oi9cUVgvfzQMWXEvurK8NbQ0AraRJD5N22xHNjruTCDdkKUMUfO+3LYY5M+BPE4HLPR9mFkgnLbCAJzq6oqq924dw4fPN4UE4EUHefnMCCjIBvJQz/0vdVqlTeGNB3PptTZi/q3YabzhE1wvMkTWMns4VAUFnYYMgJh/RL5iPpifhdvMOlAOXsdC4sn2tDME45gYlic1sHCgy5AG3lLHJNOtJt7G2JH1LctgjjDqOT8q2FzTgV6vvBwNgCea5+fv8vzZShu1OC5yP87nTWbzcqmEBgHxpXiFM9Bk9dDZjDeRiuc70UgGP5s2Jh3hyar1ePLGQzjMxS3U/IYcK9DukBpLGii6XhWpc7/H4IZjuVyPOHrm5Q9Yj+4WLGIuofweueIfYWRD5d1uuABZbeHxIMA79vtdlnQj9dwH1heuN1uSwkr/aVthAPe4wpPQpuzV42or/c1JCTOdLjimmULma+1N83zlNGWDRrnZ7LMyMYxqeeIc5zWw2NjjHi3tJ/Haivmi7nz5goOhTwGGTVE7AlJ0Byx93w+L3uqkU7z+Fveq2q/nBPOJYd5NiweJxsHGzzrCWP5vjXVXwn7nQWE31nB/XmG5BFP44+s3Pk+EVEsLdY9Yq8g5HyBol5QQdtRLCaLBQdMCNDQOc1cCebvYGi95Q6fs90OyyftbTiXvnnCDastzPbuLhV9H+EVUX/3ts8xarAHtueyYjdBTvqL5/d1KLA5CNrjubTh8C6rVbXfTdWbMKBA/1975/LiWZbt9XV+kRmR8cxHZBU2TemF6kFDgw60B4Lg5baDO9CJKCqC4MSZOHLQIA4E/wB16EDlqvTlzrqvA6FtEMGJbWtJC5fuQXM7O6sqMiMf8Y7IeBwHWZ/z+5xv7F9U3aqOSDr8LQgi4vc7Z5+9116P71p77X0o+DGqcQjg8Tkc8rKnYbr5zw9h4MnJyVC26lNd0nlZga3wLZmuepvU29/fr/v379csunaldhzqz67qfEvxE6aYObRpeGrBdx2xF/2rptVveEr3F6GydcSb41lcAOJlkKoaTTaKC4wkuYVXsDHBu1IgwdFKFxcXw2HyWTlm6E3b5mFrt5b5lryHZkFY+NIysgnprbR85vsSnlfVCBI79mUN2zGpoXHf94PhtWF1qISRA205uUbfjHKWl5eHE04sq2kMjI44kPL+/fsjpJI8cn4mUSttJ3+Pjo7ejaduTXTrt5UzoV8Kbd4H2SPY4t29e7devXo1Wqf1hKCg/s4nSiQ8bRUO4HGyLBavw8S7ooox4VWccXYCjrOvWG8nZ+AYmTdqIvQeI8+hYGUW/6ram2kSDmasnUJpWOnvaZPPLLQ2ghk6oYDc43yA4TYhi59Jsqpq+jYSG+WLi4tLRxflMhjjX1paqsePH9fOzs6oksuKDVqyXHhnHltak/ctXUi98GfI58HB7AN9bwR+0/nsrJnXSprNgtgmQ01bbhTSLx0HfhqWOVal1hdFNQwFtrkv3gnm2MxWu6qGDDZCRTzoQhmKWFKQSdQRu3v9Oj2m14Orpl6bcRqqG0JPJtNlt+R3op9c8vPSnOcEyqVHPvO1Vmr3ib/TsIKifFpN3/dDeNV6FkpGf3Z3d4fDGGhrZWVlCIEIk+jXZDIZEAKfZ78wOn6VEifxIFOZ02ghHJxEhi8ey6/jOKMvTbbWtjq2QlbolhemnYSIhqAIpgXt8PBwUNSqqRfnmlwvJiY10a+MSfPsK5SCkycZN2vMuR6bS2CMj3jacSftew81z/Drfly3zLU+3+zo6Gjw6A59HH/DX89TwkPHqXhA3+82/JnnLtvzakHLAfheUJhlijH65Yi5A89zzbVsXwXRLCwsDEkxQ3V42nXTo4kdc6PwqaCsK9s4pX4wthZqTRRT1d5XYbp2+N2ChGmR8x4sX0u5DQ1RilbhvT0oXi6F1H1z3IPSI7BWaATCDCepYgHGStvLVk2TdBcXF8NGE5baEKDJZDKcAoLiOjEH6iBb7ti/alzgYIGmv+kpUmm5xrw3GvHYDVMz/DAMTzKs/7w40gY7lZ++XVxcDG8QxdDRxyw+4T4OsLBcMt/w3jUByMfq6urwkj9QGf3wMUkLCwujmgTLdSvkNJ+cKM0Vg6vi6aobjKkTEtk7t2IKqGUUbBCYBENOvCPK5J1OTK6XLapqZBS6rhudHuI4kc+BeljwqhoqivwMxotg0rc8ZdQhQ9W0Iop+ItDe4pewzv31RhYrS1UN+5atEGTs/XkmuHJ+UZI8d5v5mfV8xkriy0uFJhf+wEfu53+MI+WiGxsbtbu7O/AFI0yZsBUKpcX42jhzDUbWKwF8xrZQ+OekYiJC88H8yNCNMaehRYaQ65ahhG6k9rsVN1hZ85qWgqfQ+LeTTsQ8QF5PYMYhKBqKg8Jk4omJtwFgjbRqOhHHx8d1cHBQk8lkUBxDPYTKmVfaq6pRTI03tsHKPARKQXsIn9dinSnnO8biHAT8RBA9f5nRr5omFFEe38fnVu5WGEYbDhESWmK88HiZ7wCKr6ysDK+95aCEhYVp0Y8Px7DXdjzuebN8wjvm0glQv28rl+gYbybxWnLtsMbfOX+BjKTuJF3r1ktbJwuaFc1xdVLGU2kQWnDw7OxsON8LpiwuLo6K9vFKJLr4vO/70U4ovK2tI8k3V4UBn6kE4zqWS7wJg7ax3iRvDKFdt5xej/dRTSaT4Y0ePguc64yCiP+AhPYG6TWs2PbaGAh7o1TUDD8S/uZ3CYdpx3DV3syhGYpNfzjumaoyG8pUEmQRHuMAeIbr810fkKsBHPLoYibaZxxGaDwf2TRKxchmOGJ4bpR6FV17RZk7YmGzhcpB+P6MvRxPew0YpfOBgggiW9VohzJShJbncuSQz7RysUMek2ToSoE9AsH/nAJqhaENQ2WKJQxFvXHfp7f4GteTc6356dyE+W+4y2dWoIzTrYQYqqrxWzeqLp8njuLZAKDk9uJV4zr4qhpKOK00lhFXf/EcQqGLi+lGHrYruvyW5Bb9IRY/ODgYySJLURCfe792S9YdyrnqDfLfVlr+d4L3Kv636EZiakPCFLirBG8WDDcjMiHkhXmUB0ag9NzvrO3KysrIwpM9R1gQHJSYScMjA/dcyGLDlKEAnzNRTCACxr5c8w8hc5tsVYRvroSiPSA8hgRlox0bJ1dbVY2Xn8x3/3i+fZ1zBvAET+a2IIc7jBuCr+ZZPvfu3bvD2nPXTZcDq2o4v8wemaOkMACETwsLC7WxsTHw2/xyzO3kKLXo9NUoFANdNVV8r5xYV5IX/pw2W6Gk6dpPPmEgmZHNBFlLgd2W40OEyTFM37990Zozn/wYRlZNFRGPzuSmV/YpJigFFh1yQovJs6V2vXJVDctsDjk4NIGD7B0KuF47lY7vFhcXa319fYCDPgbJ8SFGzbxA6NLYUPlWdTmfYSOQCg6/4aWNIAIM350ctLLa0DBOPC1jd/v0zxVkVTW8U8ye3Lx3qa6TjcyZl0ANjb2aQpvID7mCVEpkIg0Z7fHbY89wwyEQ57C16FqUOoUg42I6mNelMs+C3Si+k0Oc32xFdOKFCfOyFwUHxD9MhmNtvIyTb3gTsqb09c6dO0P1F5/B/OXl5QGmr6+vD8q7tLQ0vHj+6dOnl+qTMUApSCyzcUoq//NDmSljcCUWfYMPXrZJ5Z01L84NOEGWSmzYaSUxgmJ+7969O1R15TMJQTDGNhhOALKcZI9aVUP9P1DaCs1hjpPJ2wITzz2yQQxOtt0GCNl0MZKVuWrsvROZOmkIOQxk3sz3TCiarjX7bY9s2N2KoxOGtWIo/08bFhIspaGyEwwoI0LuUzaqpowE6oEK3rx5MzrPyl780aNHwwsCnIUmKcVnhvaTyWRYH6X44ejoaNgAkOiCcXmtnParaugTAmNvZPicBtbPoV8YD0Pwltexga66/JbTVuiBMDqJ5tNAbXAJQ+gH/fSJNgg5z/EYuq4b3qpB9ZiXnqjNvnPnzpCvOD09rcPDw1GhCcqO0jGPGF+vHJClRzaQKfMHch7DoVCOIREsxiONnulalNqd84+FpeWxU+khf8f/FiisKd9lNjKXX2xpLXBeF0aA8MaggKWlpcGyr62tDQmuqumatZNVJGkcNvR9P5yOwXdLS0tD8T/9dUxp4XVhjYtkEAbiVxJr8Mi8s1IjWA5pICsgyua1csfuhsT00xDbc2vD3ffTM8hAGYzRsN2CjdfPUk5DV8ZCvIts0F+8rj9nrPCV33k0VVWN6rm9OwvDkYYx8wBWzNb/RiN85rHMomtNlNlbZPxsgbAHSHhoZfZgUvjsqVJg8GR4aMebKALbKhFI4NzOzs6wRLa8vFyPHj2qBw8ejE6OzHXiLALJjDNC0EpMVU035zOhvt7rolU1OsTQ/Lm4uBjQgAXPWVsgYcJvEI0NUc4Zc9OC2/baTjx6Fxz9zURdS+C5n3vsCZn77IfRoHnjmgN4zArFysrK6HpXh9FPPLTllv7hCBw+mO/uD/1z4s5jxsBaR5BTJ95adO3Zb3tjK3nGbobfCTkgJh9PYYU3tGHyYJrhPZlglk7YbOFCECA377i+c+dObW5u1ubm5pCEAnJX1eiIIBuwqvZ7ic0DlsBsZOgHCmmLDU/xSun5rOA2aIaDjvMykca9CBvLfAiVvfRVmVva9Zyg2Gmo8fKZA7G3spzYANljexwZ0ztJShIQKE/IAUICdp+dnQ2HWwDBT05ORrx38hZZyASeeTJLxnOMDlV8D215G2jStXvqjJ3zBwGfBcXNgKrx+VJmQCvuq5qufRKT0ieU5fDwcFjP5J7T09Nht87m5mY9fPiwNjY2BgH35onMgrb6zsQw4ShzVTvmsjH01lCEx0bDWfbMS2DcUBonGg2r/VwoYz4bj/R+mZikfSeHbDDwQiiYlclFPQnXLQu+jjF5rPb+7Hl3oZHja8aAnBDC8BySnXhIyoTTQTDn1EVYLlNOmUN76hasboWsnucWXZtS2yu1FNwxthXef1e1Yw0LI1AaQUGIyIijNEBkwzggN4SFZ5vk5ubmcJazPZbXjQ2vXYyAcADlEXYbFisJgpXeMrPSTmTZq/l5VZcrqTBE9goYvDSE/tswvDUvabSNKtLo2luRmbfB4V4SWSlDCeetLDzfHt/GKj1f103jaCuTt6raUJkHGCO2blo5cRhGKzZ85kGGi84dpIIbtme8nnSt2e/W0pWp9Vl+n7AurRRM9uR6DdRZS3uHo6OjIaPt0s6+72t9fb0eP35c6+vrQ2IMxbQiV02ZnF7UlteC77229uKGo1XTc9T8rFRwZ7et0Bn33r07fRFACyZbUZPPFjDGapiccwR/TRlr8xmGyNcTt/b9tFCIHIP56CQg7Z6cnAw14CxBJm8Mzb1fgM+A4WnEvCkIQ+cCJNp2zsLtpxLagCbPHSr4/r7vB4S4trZWs+jGdmnlAHyN78n7W+224CLW0O1PJpMBJvk7YmiUxGuQ9+/fr83NzVpbWxusNgKEIKJoaYXpM9cxCUYQCKYtsRFE1fgklFbyz/zx52lEEzY7i4pCWSBtIKtqFD8bRltA7QG9Xg1fiHczeYby4uUYq6EovGPFwi+Tb4Ua9IFKMuoKqBbjM8pBKUxJCOwCoNPT09Eps/DTuQF/T9+cTGs5twx9PKdGQRByl7F6i65VqRNqJAxvxRi24B5YxnemVrGCGWN4Smzl62HYw4cPh3XnfHF7VY0U0zFzWmImEWOSSlxVlybIa+Rc73tpt4VUWnCNcUH2AsBLz016bBtgQ/urDC1Q2ktuGBOUmDadGERxyTlwUASncVpObOCynaoa/Q8M9sEV9PHk5KT29/eH5T+WrFi6dChQNX0NEoYuD2Bwfbj7mvxyv81Po6ZEPpnQtCFo0bWXiVph00rNsjgebFo4MyShq2MwmMc5ydyLsjieWlxcrPv37w+vUF1YWLh0yoj7YGVLpXUI0FrKcns2NvZWeCZ7JBtJC3l6bMN4GwzaZu2bnWvJG/rrpJ6Rh+ePvpMrcP26K8lSiFM2WMtnmZC1f56N4rGt1QjDZbR4fb9KyQaR+u+qGurrgf/w/+zsrHZ3d4cEKgrssllgNk7C6C1lPueJ71pLmeZV6pC/c19adCNbL3MiLdAtxbY3TMYY4l3VJhPKBnqvQXu31cLCQr333nv16NGjgVHOyNsj89twOpWC74l9DIHtTRKuVdWlhJSVh78zAWVe2zOk4mem3l6I61wHbR4jTLlcl+EApZepUB6/Bd/35DIdiSg8Pz9OijLPyAXyxnZI1nTJmyA7bN5h2QpZAEmsrq4Oy5muX8DYMVegHTy9t79m/2x4c/5Sb5KsH6CMdwa/+X1VB7impSDO7ragiQW9BRkpJsh1UOqHl5aWhiUrzpiysmZ2umocRkAW3jQGTmRZ+Ayj3F7L0/I/Am3jYIWmrVZ8zDNsLO1pE1GlwfS82NiCZlB6BJtTWdJAua/c76w8hT6UcZJ5dlhmg2V475wHsbEJ485uLr9vzbXyzB/7sw8ODurw8LCOjo6GE1I8hzgHlrssDy46ST62dKAVSnquj4+Pa29vb+Tckm5kl9YscufT87CGmFbNCmAhsxeqmr7QzOWGhliLi4v1/vvv18OHDwdBTIORMazhd44Vb5jK6e8xEmSQU0kyo9xKZJncZ64n+efv7TUYk6+jH15GgqduM5V0Vm7BiUSHJ+llQTSMgTjXEBr0xFhyAwn8S1SX67vmP0uWvIoYA5C5HJ517969WllZqb29veEIIx+PBD/fvHkz7Pgz+po1bylzjMfJRMuew4t34qlnWaMkC0bLO7Q+5x4rvIWE9rwdDit4enpay8vLtbGxMSi0X25uJZllmDKssFLPYrYhe7Zjy24+WTBzWcbXtfjjJTba5jrXadN//keZgabc4zO0/Rz33d4/+cV4mCfXKKBUr1+/Hr1+yPEz1xlKe2XBYQ79cQ2D+el+kzvgf9fde/mOVyetr6/X7u7uKM523oSae89JlohCV+lIS6G53oawRTfy1kuTLX1CM19juir+yLU8x2q04yWXhYWFevDgQa2trQ3rz1668fO9BAT5GnsGkxWR/xE6L5/gCTMPYE+dsC2hsT2gDYsVz6EDfKAf7oONhhXTqCJhfnpKe3gbFb7LU1mBv8fHx4NCJ99pi7X77CtIImEuhi2TahgtkmcYKh+g6KOf+N6w/dWrV7W3tzfKNWAcPVf+sQy34msb2ZRzxpR17y269q2Xs5Q4BzRLwasur0dX1Uhgcp2YEkwEBoYtLy8P1hbI7QSSYXI+38JrJUoBS69kstdx/G7Bt/JYEFKZWmvOV/HQCgk/rOw5bq7P8KcVppgXLbhthSbmRHkZC8mfXJOnLfIgRlI2iMln+mrvjJxgyFuJP57HOJwQ4zon9vb394dNHoy5tekjeWL+5Zwl/E7FnxV3Q9cKvxPO5gAcL7aSNLPaTY/iGIYkDUkW4NPS0lKtra2NDma3l271MT1rxm1WcgsZfWv1ORGBw4j0/i0r78m0EXH2t4UgeA5CB8+zWs1xvftlPs9CC/yPQqC49ow8w+vZrjZjvE6OIis2Rsk7hw6WhSz8YSMHf9sIc10ulVbVSLEnk0ltbGwMbe3s7Az3gD7yXDMb/5SPz5PvRBvmS4uuXamhhJF85r/9fXa85YHSayI8xGg8f3l5eVjCAHK5BtsKkM/x5x6XDZa9aCbX+NsxbiqGx4MCWUGrLm+6MASzoUgj0RISK7W9dd9P11/zmeaJPUWGI4wfuGovWTU9Jsrv/XaxCvdV1VB/bVTjEs70eJntN+/wuj4ZBq/tstdMgHnpz15yYWFheLNHVdX+/v5goHJvdvYlkV0qbxp+rrUhTjRpuhFP3fIyHmgqa8YVCY/SW/lzLDzFENTJGk5lLXHV5VDBMaH7aQOS/XM86Zg0PT/X2iCZ0hj6s+ShvZK9Kt/zTP5OdGT+ZTs2zDYyLe+cBtJGhv+93uzjlGcJbCbWLi7G+9793JY8JDqyp3bbvsd7yI26SBwamVXVsGy6sLAwKDaG0zKb4dgXQaUtOc/6/xZdm1JjhR3HJaXipvKnx8t41Es0CRt9IADngzmmSq+SQmsvlxPv6+nbLBSSVrpqXAHntXjua43/89CDldTPMKzku9azXC1lypjfzzNPUEgbLf92KGSl9POYG/jSynUg2FmEw1i8/TMhL215y6V5hEExcvAct4xg13XDMVR9348OOjTv0rsmerpKwT3OqstvLkm6tuOMqMjh/1ZHEnZk6ZsHXnU5tV91Gc4ApxYWFoZTQWCof0OG0lbWFqNb6MLe19e3vEVrqcft+ZmJSPzMNC4JsY2Q3A97LLyWeZBGLLPimVxzn1pQ0/+7QATFaxkV5ymqarS0Rs0+GztcuZaowjUDNqZ9Pz3fzIgt4awdRdX4hYY5VhQbOXCZavLC8u55xBBkCEFf+E0+iJdTtOjaPPX5+Xltb2/X17/+9UHwvWZsz7dc1FcAABu6SURBVJhC6cEYbuT1LUttoVteXm5Cu5z8hMcJie2VTVYWx11pvFqeHWrlHdIbYKzy87wHakHQqsuxP1VQ9NvGjc9SIe1xzDsf5pDkcKTrumEZyYcjQCTXPB8JeZlbj9Xe0Yk5K1CuUzP/uXKQSbMMpZJP3MN2yFevXg2xtSvrjDA9d/DI88f36dBWVlaG8+1m0bUuae3v79fu7m5tbGyMFDRhVSq2B1F12WNXTfe0+vNU1oWFhRGUsqe2olsBZilvq79psa1MXqvlGryL+2kv2MpB5P82DDmxKXy2/PzvRA88a8X/aRSSN4kUPJ705hZqDAOFQW6vqoatkQsLC6PTVUEWGBlnrv0ct+8EWyqjy1Npw5448x3wLJ2H+88rkc7Pz0enz2YMbEPTMsa+xryuevuyislkUo8ePapZdK2e+uzsrLa2turx48eDVzA0spU1JE6PZKFLqMz1tsBkt1EsrvEzDM/M8FQaT4iZngKdltYKaGUwJMy2Ukjdv1lKZB6Zjy0U4/57g7+LLHwoYSILh0hpCBJKZjyLQtMmhT+gALwysJLQbX19/ZKxZn49Tryzi2qsnMw3CAXFb3nRlM2q8f4Dj8mHKcIbjibOEIP+WqFbqC6/o43z8/P64Q9/WB9//HF961vfqll0bYf59/3bpMHr16/r008/ra997WuDV/QmAK6vGr84DWoN3oypqiGGpi2scFbfJGSiD1nokfAWahkB94lrbOVbmVn+Nqzk+RZ0xmUha/XLUNKQ0c/GM6ahtHeC6H/mQTAE9uIZ+qCcmR9ID9734wMkeB7vz+q6rg4PDwfv5/lx9hpyAtRwnDH6dUStMCPRkEMxo5mcUxSZ5zImdlO10Kllgb6mbDr3Yf6trq7Wz372s/rFL35xSQaHPs385isQHeeEiU8++WTYArm/v1/vv//+JcgMpUfJ7xJqef3XDKYSKL2dPUh6+6Qsx8swIL1RGogWROd+/s7MOl4m4bjvSQOXbaeyQX5xYCqz4aWXY/K5hvKeB88PhRf28M5KO542Od/hyjOMs9+Q4tie+ea3jT7PSeh8lXylEaJd0IyhehpaFHhlZeVSfiYVuWWozYNM4PX921dLffDBB03HAl37+6kPDg5GxfGk/FubxJOZrewrk5re2gggPW0akLSKea0VirZ9f2axU8kzTs0x5r1pbPJZ6QktEF6qyxjMgufTPGZtCEhBR5DdN1dLpYeZhXQ8fy7O4TeejfG5dHcyeftGTx/wRzu+hv9p1/F7KnJmw1towjzITDXt+x4rZN/3Q1Uj40uD0pJTjJWNgWXy9PS0fv7zn9fW1lZ985vfbMpX1Q3spz4/Px/K6C4uLuob3/jGpclPa9X6gVrWzuvOPl/KxGcIvxNk2W4meCwQue7e8qD2Slchgeyb+dIyLmnM0mMZzjtD7U0JrWokG4CM5/P5reRNzl8aOf/vNWaun0ymGz2A4FZ+cjHAcL83zAgj5zGNcRoT86qFEM0nJ71aOZJ0RgsL073lLZ5nH1s5CvPq4uJigPQvX76sn/zkJzWLrtVT07nT09Pa39+vhYWF2tnZqePj40sxw6wE2FUKD3nyMtPI3/ZwVXXJ+qY3bCmhFcre0kpkobcRSUHyePg7hQ9hSK/fEq5M1DkmdF8QMpNjd9q2EfByFePxyoP531IOP68FvbNMlPjY6KOqhlyJY2rv3XYcT39a8uN+G/n5e8/F4uLi8Bpd7+jz2jJ9NjkksEGk3VZOiSU9tpeiyMfHx0Py8OzsrPb392sWXTv8ptMckH9wcFCvX78e4o5U6rzv8xTda5CGlamUFsj0Qsnw1rPSe+aSB4pkQTJMcyiRiSn6z98tg2WyQlsRUkiMaOzN+J3rtq0EEDxthQnOMDvGTmPHdcT0S0tLowINnuv3etNHYup8WYHHmPkHz6dDLiMxK1Xyx0bRcDs9Lu2kk+FzHwft5cWMxVOOCDNR6KOjo9rb2xte9HfVvv2qG9xPzeDOzs6GrOadO3dqZWVlFHMkpWD6c7KxLiCwkGS9bmY9HSJYqHM5x9bfn2USI6G6BadqHIO2YmAbBm+acJu04cMKoBRWPuO+HH/OT5Z52qu3EAb/k1lvPbfVPy8/wUfKij1/s6oQPR76mMraMryGtbTl9lqGMQ1a3gffWuv+LWfVis+dSPSONdbsqXdHls2HFl07/DYxQM5Z4vu1tbURdGlB0lSsqsvKZQVEwf2/27YSWwBaSyVcz/NzLdTPTTjaSpi1+mSBdDIoBWIWj1F0DFJrndlbVPk/M7SGkzYIjMuxLu25MsxKwjU53pxDtsn6hFcbxrzfz7CCGkW0ZMjPZB5t6LKPnntWUxKx0U4+nzyBk7etuNm8tSdnLoHjPhjR+7VbdCOe2kJA5vTs7KyOj49rd3e3+r6vjY2N4dD8FoPtHVJpWgJtI+H4nf9hVkKZhKF+tiFdemCu8z3+jfBYAHJi3V/3h+tmrd+bJy6SYMx+hYzhdh5pxMF5fge0hbfl5SeT6dFJ3JMe0DwFrTEGv+PKz7JyohyMz/LBvDsbnsiLdqx4NgZ59FPylc9blYjc30JzrflMKJ5zaZ4QV1vB88z6Ft0o/L5///7o5etADE5HXF9fr5WVlUtLLoYxyYC0bkBBJvoqOGXLb6NhReT7nAB7tkQLGBa+57mp4L7efciEj2F7IgN7i3yOvTtLUQi0+ddamoKvvtaGwgaR61rIA+NhIUexvczGfa72Mtpwe1bKNJ7pmc1Lw33D90Rh9t4OPzCQySuem6iBaxybp3dOz5ybVOAPiu4TUGfRtSu1vfTDhw8HgaCz/E1MdXJyUqurq8NbGjJmoS0stzf8Z3LEmVoYlMprZbL1zTG01g4tYLnunhlZfjJUqBqXATqbm9dXtavu7OFoj+s5edJGkWso3YVvLAlyGB/PdTztvxMd2MCmEUO53T9nlZlD5rbv+9EyF8/Be7Ghw4bGPPIYjQ7MI8bgeXXpqFcu0tN7PltJQuTOyMB5h1TalDs/y4oPDzLTbrr2dWpoaWlpOEeZiUkvC7RAuZeWloYfn8hoDwyUTsWlD7b0rdgKWGuhbwmI7/EYbZVpy5NrpUQ4zR/XWue9FmjG0PLW7ksiivSE9qJVNcByrrPQ2lsTI9rrtkIin9UF/zxW/l5eXh7O5U4FYY49zslkMiSNfCQRz/UpoDlvKTPMkxUqDZVl0wrkPARzkvObuRA+y7DNfPRn1gkMEstcyFQuS5pu7IhgLLXXJFsCm8kPlB34mFslq8aJHCYBa5ZnSzkuAtZ4Ut33tMTpdem3xwo8s4V2ZhTic7fFs69KkqWH4TPzzPc48eVxo6BGKRhInx1WNT5AgQSNkUsrZqRfGFPnPujL8vLy8K5n5illgrbfvHlTR0dHw9ssvRfaWWEnPROdmG8ZLrhePdfsq2rktVFsxut7jYo8r5Yhx8fpqe3suB75p1z2nS1ptSwfk0LHfa09mxliJlRN99syqVU1gqsMPK18xrx8zn7X9PAJwbuuG7xQywu34DL3mFAwK63jPt9jvvh7j7m16QBy/IciJ6TkeQiPDYQVBGjaCj3cN89tCx0xLiMbYD+1+sxHGi33cXd3d1gStYC71jsdyyxvbHnLaxiDwzPmK1FFnv1mY+yCkkRRGUdD5jNK3fd9ra2tjYxf0o2cUcaAeZ2os65p2fndskQWBjMQQeA3cUdV+4B+YOYsa2clykRY1eXTVlLZvDbu53o5yPfyt8dJ/zFcLdjtjHoLSqZXT9jpZBPeyV6Hc95YU04eOcGTkDARjQ3wZPJ2XZrncGiCPboTeFV1yaudn5/X4eFhraysDM/LxJqRX6JDvvN8m19Zr53JNe9683HHVZcPZjT/c76tzEaxRqn0GYPlQzVbdGNLWgji3t5ePX78eMSEWdbJ3i+VjElEuA1zWcLJNqvGR/c4G8p16X1b/akaFzKYwQhE1fjgPO71klOiAfPDEKvFpyzMsOBdXEzPActcAR7X93Kd3wWVoQFe3saFcZvfaQCtMFchIoyCTzNNZXS4YIV1vxySmWctGG4Dl0rtRFfOkZ/tZ/k55o8NYqIQ7uF3em76R0Xm48ePL81f0o1XlO3s7NTe3t6QNEs4YovYYnQmU8wkmHd+/nZTwMnJySUlSo+DEKeX8LU5Ee6bhZBxJkROgco43AIGYXBoI9dCEwVYeBEMDBjvDvPWVD+L8SwuLg4wHbIS+rkooZWH0MLXpEesmr5lIj0xPOu6rg4ODoa402ggs/xv3rwZyjH5zkbf1/pvK13y0OWv3qWF80iv7BWENMT87XsII0Af/pvrM7fx+vXrOjg4qAcPHjSNjenGlNrWdnt7ux49enQpwVXVLrr3d4aYttDE2YaFuVaYkAooOMuLtpTVQmqIVVWXsqT2LFzj4gHfb0U3D5zkypg5+2qvBix0oQcKYKXzfSgqHtt9NA8SzSDs5oXvSaTEvc5er6ysDEaY+JpKs5YxxVgdHBwMRjF5bOTCM/3bRiX7xzwT59ugtjw+ZNSIcvIshwIJrZFhYme+p47j008/rb7vhxNjrqIb9dQwfn9/v3Z2dmp1dXUkVBl3JDmmacUnhsc8EyZnjOdJd/uOkVJp7T3zGdk+bZGIy8IE7uW340Un0XI9mv5YOSCeYzgJz3waZhpQGwx2Qs3iP20ghAgq53gj0Pyk8nKfPSH8u3v37qgGHCTkHAz95ffx8XF13dttmUZGVkIv29EHX5cIibGmkbecMQdGlpYHrnNf4ZXRh/nn//l9fHxcH3/88TA39+7daxp4043t0mIQ9+7dq6qqly9f1qNHj2p5eXmodEpKj51kZlbVsF7NPXzHETnc4z7Z0+eyUOv5FhgbkIwjDX2tXHfv3h1iUAuJ73E79tS5NpkKjWcx9DRasQfjeX4/Fe2wHJgGykrjOm1+u7jE40uUA/9culo1riUnAebahb7vh/VphD6RStXUEGbiKefSTgJFymRm5l9srJwo9Fg9lza0/u3kJojKHpr9EU+ePKnd3d0hWQn8fmdbL03n529PPVlfX6+u62pvb6+ePXtWKysrw1FHnpgUWJhoy8hnTMb5+fkoBkrltFX2JNo4WAi4z8LmODFDBXv2/DuFOT+runzSC+3a+LQ8B+M11LYCGn4agdC/qstVYeQl0giml7AiYRDIDuez0isattN/e6Ou64bTQ9hDzfIbP3fu3BnQEPOT+RijEz/b4ZxDlr6fvpEDowKisBG0p24ZDn5yTTqVmv/5Ybvl06dPa3t7e7QL8cMPP6yVlZU6Ojqq73//+9WiG92lxVFGxL4vX76sBw8eDC/qxhrl8ogJxjkWsVeGnNk2BEXwmLiqy9vluD6F369hdZbVUI426Jf74T77Ont+JjrDjDQ87iseOpGGldlxIfkHrm9VQMEne3b66LG0KA/L9xyZT05+2WBzQODi4mJtbGwMmfy+74clUQxXqybB/M3wBZ55Xiw/fd+PlIj7EnG5TSfSeK6dDspKvIxHpt1U6IODg3ry5Eltb2+PdGEymdR3vvOdeu+99+rJkycz+X+j76cmAeLzpra3t2tlZWV09KsFy8JjL5bWEGFhW1ru/IFhPHdW9pDrYaQ9cMZrCcGrajQBuZTRInsLK08aKoTH1+MFWsmgNCCgGHiP9+Ge5IcNGwJnnnhuDH/x+CcnJwMfaI/+ZI7CcbWNOgq7uro6qjpjjJPJZHAIGAcX1/i55neiqMzSZziSMsPfJLIcnvi3FR5+pULzc3p6Oij006dP69mzZ6MQhb588skn9cEHH9S3v/3tpjxVvYPs95s3b+revXvDFsyDg4Pa3t4ePvPLvjPhQRueRHvjzDiySN+aJE+mLX0qqT1cerOqy7uE/Hcm4nwtQpFJK/cnldXewzC4FbJ4aSmP1TGUZ1wotlGCt1SmFzJf8Ebmr4W4ZaAS7fjzqukSl+dhMpkM536BmqzMGZakEtI//nafEvFlWARPac/hF5tS6Ic3otgbp+fGe3Nc0d7eXv3yl7+sra2tUQbdFWvf+9736qOPPqoPP/ywZtGNemogHa8jQYh2dnbq3r17w77ZhFD5w+e2sGY0kwhjEFCsqJcpILxkPiPRgCedyXZc2lLkNFAJyw09U+laPOS3PTVjs/LbuBCTun8oNQY2S0jteT0X/O2ElBXIPGEuMgfgtdZEJ2msaM/Gxhs3XKvdCoHS4LaUP1FYGnfmzMbMfXGY1Ep8cXxTfo6j29nZqSdPntTW1lZzHZ/2X758WR999FH99Kc/vSQb0I0uaVVNF+vpOMmH7e3t0VJIywNmDOWkkTOhMNwwrmpaMOF2UwEgK7GvscDn87LPbsPK2PIKvjcTaNkmfMxy2/Q85gGfWVGzdBMeZRteErKXdryKJ3K1k72VT//0nPmZmTGHjDh8vXnfqvW2kbDMfJE55DnZT76Hh1bqpIuLizo+Pq6jo6Nhzf3s7GzIC6Dsr169ql/96le1vb09MpCG7w4pnG1v0Y3CbyAEg/P5zlbsrutqbW3tklJ4IM6AGs4ZYl5VPmgIb6VIS93K9JqMGPg/vXtCXcfb6Y2dPOJ/C7q9QaKHRBo2aGncWl6N78wje8SE3jzTyS7ay/6QzLOHtifiPnvpFu9s2LOvLXmz3KSBzb46Z+C+zeIv3yW6SDnhfopl9vf36/j4uA4ODurFixf1/Pnz4aTQHENmy1vGN+nG4bdL39xRFPvZs2d1cXFRjx8/rgcPHgzxk++tGi9ToMx4gny9ir0ifzvz7XarxsUJ6WV9TYYEfG7hTlhpQUmYl14loWKGGamYhvQmx6ALC9Mjf7kPfhKuJFKgJttekefRPgrhsdsQOO422kq+0obnzkrp7yxXfJ5KlcYnr/8iEL2FtHJ+PX+erzT6ff82BH39+nU9ffq0tra26ujoaDTf5g9bTXNrauYcTDeq1FXTd/daSM3Eo6Oj2traurTP2XXLjmeIwx1X2QNfpZQWAl/jNV4/k78hP8fGxs8yLMzCBvelda//tsU2v3x/ekvzahZqsQCm18t67BRQj91GykKeAp3VYUYVNhIedypc8sa883ctA5pGPjPXRljZx8yh8Jy8ruUgLi6mR3c9e/astra2am9vb8h1UBbL2zINtU9OTobVBBuvWfROPPXJyUktLy+PsqOOac7Pz+v58+d1eno6FLE7O+6TLwwlLXwuUaTNlsdOwU4vAOVn6aE9xlmJl1kT4eWizAzzPf2fBZtTkVp9hQ+OYTGeIAA+57kXFxe1tLQ0asvJPa7L71IZHebggUAArUSh+QiaMhx3KJG8bs1d8iwRAG3Rv1QcG336mfE5htfLVK4Oe/78eX3yySf14sWL0ck+hFO8qufg4KAODg7q5ORkVAvu3EcriQrduKemsmx1dXVgnCcWBh8fH9f+/n7t7e3VyclJbW5u1vr6+qXlrKrxRoMUJBdaWODTO+fvtPQtqAVd5dHzOYalvh4PbKVGUBw/t4yLn52ecZb3MN+chEHBE5YzZvMw+Z789TVp3LpufKgAZGPs/ji0MJ88Fwm9E2352ZnjSP60QijaxKjQN6M9kl+c1HJwcFDPnz+v58+f14sXL4byTsqlaY/8xeLi4vDDAf5pqFxo1KIbzX4zcM6a6rrp2wQTEi4uLg7Jsp2dnWFSgNyzoJG9LiWFVsQUeEOqlgdMY+H2aCfHaUuecX1ORsJ3x59GMlXtN2TOguLpdf2sliK3jBXXuzYg4WvLWBh1pMKlRzY55ub/hLd+no2LkQzz73lNj54GLe91XsE/jMUQOb30yclJ7ezs1KtXr+r169f14sWLYSupva3btSemvyDPvb29Ie7mvneWKGsJPAM4Pj6+VNAPzFhdXa2HDx/WxsZGVb0Vjt3d3aEN4LXrgJlYnmsr7s8NrXKSaT9/p9dpCVrL6rtdryG3BDzLXomhPIGpCLPgfCoe/EolytjWnj7RS3riTEwln1J4+e0sfCuRxEaRNNhWANrPlYlUPH68jmwezbrX47Wz4O+sFPQOtdPT03r58mVtbW3Vzs7OsHxFn80jO6AW38/OzoYwNb3zjSs1HrUV20FYNU/cxcVFra+v1wcffFCbm5uXoOrZ2dnoDZqOuawYeBZgEt+ZeRYabz5I+GvyxGcbVxkI4JXH2zJ4jmsTLrY821WWO8MDjBtK5RjV17U2RdAWn1u4sr/ZZ/MtP0sy3y3sjnXtYXOsiVKy7TTCLchth2Diu6wCROGIgw8PD+v169e1v78/yB8vqcD75hzi5dEZl5m6JvzNmze1trY2JNdm0bUo9ebmZn33u99tMgfyMknVdJJXV1frwYMHzUome72lpaVLdb8Z22Edad9ewcJqK+znmVIYWwrWiiftlV1r7e9bfUiapdCt/rXQhXejJV9aAt4af2b7u258GGOO6SpqPbP1vxVxFiU6usr4plLPQj7mo9tz2ILikdnmfVc+/MBKa8TR4gUoljZdjUaN+fvvvz/M3Q9+8IMmP65FqV+9elU//vGPP/c6TxwDvQpW5L3+/SehWV7iiwjjddNX7Ucq9J+0rZYnvQ7etIxQS7GzL1d9/uvu3yyvDV1lFFrXflnyvbNWZ0zddTBmYWGhX1tb+7W3++ui/x+U+ssK/m+aUl/XvH0Zpb5p2t3d/Z993/+F/PxaPLUTW3Oa05xulr4Y1p3TnOb0G0NzpZ7TnG4ZzZV6TnO6ZTRX6jnN6ZbRXKnnNKdbRnOlntOcbhnNlXpOc7plNFfqOc3pltFcqec0p1tGc6We05xuGc2Vek5zumV0XYckbFfVH19T23Oa05ze0p9pfXgtu7TmNKc5vTuaw+85zemW0Vyp5zSnW0ZzpZ7TnG4ZzZV6Tk3quu6fdV33Vxqf/3bXdX/4Lvo0py9GN36Y/5x+M6jv+3/6rvswpy9Hc099S6nrur/Xdd3/6bruo67rfq/rut/quu5Hn332X7qu+9Nd193vuu6Pu66bfHbPatd1T7quu9t13b/tuu5vfPb573Zd90dd1/2kqv76Ox3YnD6X5kp9C6nrum9V1T+pqt/p+/7PVdU/qqp/VVX/ru/7P1tV/6Gq/mXf9ztV9b+r6i9/dutfrar/3Pf9qdq6V1X/uqr+WlX9+ar6Uzc2kDl9KZor9e2k36mqP+j7fruqqu/7l1X1F6vqP372/e9V1V/67O/fr6q/9dnff/uz/03frKpf9H3/8/5tUcO/v86Oz+mr01yp5/T9qvrdruse1VtP/KN33J85fUWaK/XtpB9V1d/sum6zquozhf3v9dYTV1X93ar6b1VVfd/vV9X/qKp/UVV/2Pd9vk7xj6rqt7qu+/Cz///ONfd9Tl+R5tnvW0h93//fruv+eVX9167rzqvqf1XVP6yqf9N13T+uqudV9fd1y+9X1R9U1W832jruuu4fVNV/6rrusN4ag/VrHsKcvgLNa7/nNKdbRnP4Pac53TKaK/Wc5nTLaK7Uc5rTLaO5Us9pTreM5ko9pzndMpor9ZzmdMtortRzmtMto/8HXITd58RLjDEAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 576x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dtn7p6LmhFiG"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}