FER_CNN.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "FER-CNN.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "Vp6zC3l7OT9h"
      },
      "source": [
        "from __future__ import print_function\n",
        "import tensorflow.compat.v1 as tf\n",
        "tf.disable_v2_behavior()\n",
        "\n",
        "import keras\n",
        "from tensorflow.keras.utils import to_categorical\n",
        "\n",
        "from keras.models import Sequential\n",
        "from keras.layers import Conv2D, MaxPooling2D, AveragePooling2D, BatchNormalization\n",
        "from keras.layers import Dense, Activation, Dropout, Flatten\n",
        "\n",
        "from keras.preprocessing import image\n",
        "from keras.preprocessing.image import ImageDataGenerator\n",
        "\n",
        "from sklearn.metrics import classification_report, confusion_matrix\n",
        "\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "o3D1vfbaURHr"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n8qhLqgAOZ10"
      },
      "source": [
        "config = tf.compat.v1.ConfigProto( device_count = {'GPU': 0 , 'CPU': 56} ) #max: 1 gpu, 56 cpu\n",
        "sess = tf.Session(config=config) \n",
        "keras.backend.set_session(sess)"
      ],
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TVHVfOpZOhEe"
      },
      "source": [
        "num_classes = 7 #angry, disgust, fear, happy, sad, surprise, neutral\n",
        "batch_size = 256\n",
        "epochs = 8"
      ],
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QO-XKU5NZarP",
        "outputId": "144cc8ec-2417-45d3-9c19-ba62f6c3f250"
      },
      "source": [
        "#/content/gdrive/My Drive/DL Project/fer2013.csv\n",
        "from google.colab import drive\n",
        "drive.mount(\"/content/gdrive\")"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/gdrive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dTovMpxVcXTb"
      },
      "source": [
        "with open(\"/content/gdrive/My Drive/DL Project/fer2013.csv\") as f:\n",
        "\tcontent = f.readlines()"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "toQzFXYUgZ9d",
        "outputId": "3e8c4d7c-a557-4a00-e8e5-a5ef01996031"
      },
      "source": [
        "lines = np.array(content)\n",
        "\n",
        "num_of_instances = lines.size\n",
        "print(\"number of instances: \",num_of_instances)\n",
        "\n",
        "x_train, y_train, x_test, y_test = [], [], [], []"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "number of instances:  35888\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9UyjBpV7gaGm"
      },
      "source": [
        "for i in range(1,num_of_instances):\n",
        "  try:\n",
        "    emotion, img, usage = lines[i].split(\",\")\n",
        "\n",
        "    val = img.split(\" \")\n",
        "    pixels = np.array(val, 'float32')\n",
        "\n",
        "    emotion = to_categorical(emotion, num_classes)\n",
        "\n",
        "    if 'Training' in usage:\n",
        "      y_train.append(emotion)\n",
        "      x_train.append(pixels)\n",
        "    elif 'PublicTest' in usage:\n",
        "      y_test.append(emotion)\n",
        "      x_test.append(pixels)\n",
        "  except:\n",
        "    print(\"\", end=\"\")"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fbUaS6UEgh5V",
        "outputId": "db517772-50b9-4280-ba4a-b25dcc9a9c31"
      },
      "source": [
        "x_train = np.array(x_train, 'float32')\n",
        "y_train = np.array(y_train, 'float32')\n",
        "x_test = np.array(x_test, 'float32')\n",
        "y_test = np.array(y_test, 'float32')\n",
        "\n",
        "x_train /= 255 #normalize inputs between [0, 1]\n",
        "x_test /= 255\n",
        "\n",
        "x_train = x_train.reshape(x_train.shape[0], 48, 48, 1)\n",
        "x_train = x_train.astype('float32')\n",
        "x_test = x_test.reshape(x_test.shape[0], 48, 48, 1)\n",
        "x_test = x_test.astype('float32')\n",
        "\n",
        "print(x_train.shape[0], 'train samples')\n",
        "print(x_test.shape[0], 'test samples')"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "28709 train samples\n",
            "3589 test samples\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "v18A43qpAgaq",
        "outputId": "684f8517-cf64-4c04-e991-7d1471adcbcc"
      },
      "source": [
        "cnn4 = Sequential()\n",
        "cnn4.add(Conv2D(32, kernel_size=(3, 3), activation='relu', input_shape=(48,48,1)))\n",
        "cnn4.add(BatchNormalization())\n",
        "\n",
        "cnn4.add(Conv2D(32, kernel_size=(3, 3), activation='relu'))\n",
        "cnn4.add(BatchNormalization())\n",
        "cnn4.add(MaxPooling2D(pool_size=(2, 2)))\n",
        "cnn4.add(Dropout(0.25))\n",
        "\n",
        "cnn4.add(Conv2D(64, kernel_size=(3, 3), activation='relu'))\n",
        "cnn4.add(BatchNormalization())\n",
        "cnn4.add(Dropout(0.25))\n",
        "\n",
        "cnn4.add(Conv2D(128, kernel_size=(3, 3), activation='relu'))\n",
        "cnn4.add(BatchNormalization())\n",
        "cnn4.add(MaxPooling2D(pool_size=(2, 2)))\n",
        "cnn4.add(Dropout(0.25))\n",
        "\n",
        "cnn4.add(Flatten())\n",
        "\n",
        "cnn4.add(Dense(128, activation='relu'))\n",
        "cnn4.add(BatchNormalization())\n",
        "cnn4.add(Dropout(0.5))\n",
        "\n",
        "cnn4.add(Dense(128, activation='relu'))\n",
        "cnn4.add(BatchNormalization())\n",
        "cnn4.add(Dropout(0.5))\n",
        "\n",
        "cnn4.add(Dense(7, activation='softmax'))"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "WARNING:tensorflow:From /usr/local/lib/python3.7/dist-packages/keras/layers/normalization/batch_normalization.py:532: _colocate_with (from tensorflow.python.framework.ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Colocations handled automatically by placer.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xsMAab4DAhgt",
        "outputId": "6646b437-e916-4d0c-d9a4-88ec7aa78e45"
      },
      "source": [
        "cnn4.compile(loss='categorical_crossentropy',\n",
        "             optimizer='adam',\n",
        "             metrics=['accuracy'])\n",
        "history = cnn4.fit(x_train,\n",
        "         y_train,\n",
        "         batch_size=120,\n",
        "         epochs=30,\n",
        "         validation_data=(x_test, y_test)\n",
        "         )"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "metadata": {
            "tags": null
          },
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Train on 28709 samples, validate on 3589 samples\n",
            "Epoch 1/30\n",
            "28709/28709 [==============================] - ETA: 0s - loss: 2.1059 - acc: 0.2817"
          ]
        },
        {
          "metadata": {
            "tags": null
          },
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/keras/engine/training_v1.py:2057: UserWarning: `Model.state_updates` will be removed in a future version. This property should not be used in TensorFlow 2.0, as `updates` are applied automatically.\n",
            "  updates = self.state_updates\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "28709/28709 [==============================] - 354s 12ms/sample - loss: 2.1059 - acc: 0.2817 - val_loss: 2.2257 - val_acc: 0.2407\n",
            "Epoch 2/30\n",
            "28709/28709 [==============================] - 351s 12ms/sample - loss: 1.6013 - acc: 0.3915 - val_loss: 1.6155 - val_acc: 0.3608\n",
            "Epoch 3/30\n",
            "28709/28709 [==============================] - 348s 12ms/sample - loss: 1.4382 - acc: 0.4477 - val_loss: 1.4604 - val_acc: 0.4461\n",
            "Epoch 4/30\n",
            "28709/28709 [==============================] - 351s 12ms/sample - loss: 1.3542 - acc: 0.4814 - val_loss: 1.2912 - val_acc: 0.5057\n",
            "Epoch 5/30\n",
            "28709/28709 [==============================] - 353s 12ms/sample - loss: 1.3000 - acc: 0.5063 - val_loss: 1.2880 - val_acc: 0.5077\n",
            "Epoch 6/30\n",
            "28709/28709 [==============================] - 356s 12ms/sample - loss: 1.2594 - acc: 0.5231 - val_loss: 1.2902 - val_acc: 0.5043\n",
            "Epoch 7/30\n",
            "28709/28709 [==============================] - 354s 12ms/sample - loss: 1.2199 - acc: 0.5406 - val_loss: 1.2457 - val_acc: 0.5238\n",
            "Epoch 8/30\n",
            "28709/28709 [==============================] - 352s 12ms/sample - loss: 1.1879 - acc: 0.5526 - val_loss: 1.2021 - val_acc: 0.5444\n",
            "Epoch 9/30\n",
            "28709/28709 [==============================] - 353s 12ms/sample - loss: 1.1516 - acc: 0.5711 - val_loss: 1.5195 - val_acc: 0.4767\n",
            "Epoch 10/30\n",
            "28709/28709 [==============================] - 355s 12ms/sample - loss: 1.1298 - acc: 0.5791 - val_loss: 1.2396 - val_acc: 0.5369\n",
            "Epoch 11/30\n",
            "28709/28709 [==============================] - 354s 12ms/sample - loss: 1.1068 - acc: 0.5842 - val_loss: 1.1973 - val_acc: 0.5517\n",
            "Epoch 12/30\n",
            "28709/28709 [==============================] - 351s 12ms/sample - loss: 1.0799 - acc: 0.5940 - val_loss: 1.1786 - val_acc: 0.5628\n",
            "Epoch 13/30\n",
            "28709/28709 [==============================] - 350s 12ms/sample - loss: 1.0519 - acc: 0.6083 - val_loss: 1.1469 - val_acc: 0.5770\n",
            "Epoch 14/30\n",
            "28709/28709 [==============================] - 348s 12ms/sample - loss: 1.0287 - acc: 0.6171 - val_loss: 1.1580 - val_acc: 0.5670\n",
            "Epoch 15/30\n",
            "28709/28709 [==============================] - 350s 12ms/sample - loss: 1.0030 - acc: 0.6253 - val_loss: 1.1109 - val_acc: 0.5943\n",
            "Epoch 16/30\n",
            "28709/28709 [==============================] - 347s 12ms/sample - loss: 0.9946 - acc: 0.6330 - val_loss: 1.1040 - val_acc: 0.5890\n",
            "Epoch 17/30\n",
            "28709/28709 [==============================] - 345s 12ms/sample - loss: 0.9518 - acc: 0.6490 - val_loss: 1.1296 - val_acc: 0.5851\n",
            "Epoch 18/30\n",
            "28709/28709 [==============================] - 346s 12ms/sample - loss: 0.9306 - acc: 0.6576 - val_loss: 1.1427 - val_acc: 0.5762\n",
            "Epoch 19/30\n",
            "28709/28709 [==============================] - 349s 12ms/sample - loss: 0.9288 - acc: 0.6564 - val_loss: 1.1396 - val_acc: 0.5857\n",
            "Epoch 20/30\n",
            "28709/28709 [==============================] - 347s 12ms/sample - loss: 0.8861 - acc: 0.6722 - val_loss: 1.1276 - val_acc: 0.5924\n",
            "Epoch 21/30\n",
            "28709/28709 [==============================] - 346s 12ms/sample - loss: 0.8711 - acc: 0.6770 - val_loss: 1.1545 - val_acc: 0.5913\n",
            "Epoch 22/30\n",
            "28709/28709 [==============================] - 346s 12ms/sample - loss: 0.8471 - acc: 0.6856 - val_loss: 1.1177 - val_acc: 0.5885\n",
            "Epoch 23/30\n",
            "28709/28709 [==============================] - 347s 12ms/sample - loss: 0.8211 - acc: 0.6961 - val_loss: 1.1217 - val_acc: 0.6052\n",
            "Epoch 24/30\n",
            "28709/28709 [==============================] - 348s 12ms/sample - loss: 0.8033 - acc: 0.7035 - val_loss: 1.1450 - val_acc: 0.6018\n",
            "Epoch 25/30\n",
            "28709/28709 [==============================] - 350s 12ms/sample - loss: 0.7836 - acc: 0.7128 - val_loss: 1.1317 - val_acc: 0.6021\n",
            "Epoch 26/30\n",
            "28709/28709 [==============================] - 350s 12ms/sample - loss: 0.7661 - acc: 0.7206 - val_loss: 1.1477 - val_acc: 0.6024\n",
            "Epoch 27/30\n",
            "28709/28709 [==============================] - 348s 12ms/sample - loss: 0.7507 - acc: 0.7235 - val_loss: 1.1819 - val_acc: 0.5938\n",
            "Epoch 28/30\n",
            "28709/28709 [==============================] - 347s 12ms/sample - loss: 0.7367 - acc: 0.7311 - val_loss: 1.1379 - val_acc: 0.6052\n",
            "Epoch 29/30\n",
            "28709/28709 [==============================] - 348s 12ms/sample - loss: 0.7040 - acc: 0.7438 - val_loss: 1.1665 - val_acc: 0.6052\n",
            "Epoch 30/30\n",
            "28709/28709 [==============================] - 350s 12ms/sample - loss: 0.7003 - acc: 0.7445 - val_loss: 1.1765 - val_acc: 0.6052\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CfIbbSeYfxaW",
        "outputId": "f35c2ce1-3ce7-4792-f72d-710980b667fb"
      },
      "source": [
        "train_score = cnn4.evaluate(x_train, y_train, verbose=0)\n",
        "print('Train loss:', train_score[0])\n",
        "print('Train accuracy:', 100*train_score[1])\n",
        " \n",
        "test_score = cnn4.evaluate(x_test, y_test, verbose=0)\n",
        "print('Test loss:', test_score[0])\n",
        "print('Test accuracy:', 100*test_score[1])"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Train loss: 0.428030126731329\n",
            "Train accuracy: 85.49235463142395\n",
            "Test loss: 1.1765036651370053\n",
            "Test accuracy: 60.51825284957886\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OG48clX2EQf7"
      },
      "source": [
        "predictions1 = cnn4.predict(x_test)\n",
        "\n",
        "pred_list1 = []; actual_list1 = []\n",
        " \n",
        "for i in predictions1:\n",
        "\tpred_list1.append(np.argmax(i))\n",
        " \n",
        "for i in y_test:\n",
        "\tactual_list1.append(np.argmax(i))\n",
        " \n",
        "conf_matrix = confusion_matrix(actual_list1, pred_list1)\n",
        "fig, ax = plt.subplots(figsize=(7.5, 7.5))\n",
        "ax.matshow(conf_matrix, cmap=plt.cm.Blues, alpha=0.3)\n",
        "for i in range(conf_matrix.shape[0]):\n",
        "    for j in range(conf_matrix.shape[1]):\n",
        "        ax.text(x=j, y=i,s=conf_matrix[i, j], va='center', ha='center', size='xx-large')\n",
        " \n",
        "plt.xlabel('Predictions', fontsize=18)\n",
        "plt.ylabel('Actuals', fontsize=18)\n",
        "plt.title('Confusion Matrix', fontsize=18)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545
        },
        "id": "nz-zJcY3do-M",
        "outputId": "0100eae4-fbd5-4478-9e3b-12617f18ec3f"
      },
      "source": [
        "accuracy = history.history['acc']\n",
        "val_accuracy = history.history['val_acc']\n",
        "loss = history.history['loss']\n",
        "val_loss = history.history['val_loss']\n",
        "epochs = range(len(accuracy))\n",
        "\n",
        "plt.plot(epochs, accuracy, 'bo', label='Training accuracy')\n",
        "plt.plot(epochs, val_accuracy, 'b', label='Validation accuracy')\n",
        "plt.title('Training and validation accuracy')\n",
        "plt.legend()\n",
        "plt.figure()\n",
        "\n",
        "plt.plot(epochs, loss, 'bo', label='Training loss')\n",
        "plt.plot(epochs, val_loss, 'b', label='Validation loss')\n",
        "plt.title('Training and validation loss')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(cnn4.summary())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aeKMPUWPOUkf",
        "outputId": "bfb89b99-6663-4b5c-fc17-5a544b6d1b4b"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " conv2d (Conv2D)             (None, 46, 46, 32)        320       \n",
            "                                                                 \n",
            " batch_normalization (BatchN  (None, 46, 46, 32)       128       \n",
            " ormalization)                                                   \n",
            "                                                                 \n",
            " conv2d_1 (Conv2D)           (None, 44, 44, 32)        9248      \n",
            "                                                                 \n",
            " batch_normalization_1 (Batc  (None, 44, 44, 32)       128       \n",
            " hNormalization)                                                 \n",
            "                                                                 \n",
            " max_pooling2d (MaxPooling2D  (None, 22, 22, 32)       0         \n",
            " )                                                               \n",
            "                                                                 \n",
            " dropout (Dropout)           (None, 22, 22, 32)        0         \n",
            "                                                                 \n",
            " conv2d_2 (Conv2D)           (None, 20, 20, 64)        18496     \n",
            "                                                                 \n",
            " batch_normalization_2 (Batc  (None, 20, 20, 64)       256       \n",
            " hNormalization)                                                 \n",
            "                                                                 \n",
            " dropout_1 (Dropout)         (None, 20, 20, 64)        0         \n",
            "                                                                 \n",
            " conv2d_3 (Conv2D)           (None, 18, 18, 128)       73856     \n",
            "                                                                 \n",
            " batch_normalization_3 (Batc  (None, 18, 18, 128)      512       \n",
            " hNormalization)                                                 \n",
            "                                                                 \n",
            " max_pooling2d_1 (MaxPooling  (None, 9, 9, 128)        0         \n",
            " 2D)                                                             \n",
            "                                                                 \n",
            " dropout_2 (Dropout)         (None, 9, 9, 128)         0         \n",
            "                                                                 \n",
            " flatten (Flatten)           (None, 10368)             0         \n",
            "                                                                 \n",
            " dense (Dense)               (None, 128)               1327232   \n",
            "                                                                 \n",
            " batch_normalization_4 (Batc  (None, 128)              512       \n",
            " hNormalization)                                                 \n",
            "                                                                 \n",
            " dropout_3 (Dropout)         (None, 128)               0         \n",
            "                                                                 \n",
            " dense_1 (Dense)             (None, 128)               16512     \n",
            "                                                                 \n",
            " batch_normalization_5 (Batc  (None, 128)              512       \n",
            " hNormalization)                                                 \n",
            "                                                                 \n",
            " dropout_4 (Dropout)         (None, 128)               0         \n",
            "                                                                 \n",
            " dense_2 (Dense)             (None, 7)                 903       \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 1,448,615\n",
            "Trainable params: 1,447,591\n",
            "Non-trainable params: 1,024\n",
            "_________________________________________________________________\n",
            "None\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "ZyoOgJeoplFM",
        "outputId": "fe398107-38dc-4872-ba51-1525c3c4c69d"
      },
      "source": [
        "from keras.utils.vis_utils import plot_model\n",
        "\n",
        "plot_model(cnn4, to_file='model_plot.png', show_shapes=True, show_layer_names=True)"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.core.display.Image object>"
            ],
            "image/png": 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Jx/HVV1+1ycvPVVVVAPDIF67ryWQy7N+/HyNGjMBrr72GTZs26WwvLi4GANjZ2TXY197eHqWlpXrFV//4buXKlQ3mHXNycmr2cc6ePYuMjAxER0c/tN7du3exadMmLF++HM888wwAwN3dHfHx8XBwcMCWLVuwbds2k2+3JWxtbQH8d0yYAo5PXRyfpjU+janDJ3+TJ082dghkZPVr+nIs6Kctkr/6/1D1Wdpu+PDhWLx4MbZu3Yq1a9fC1dVVu83e3h4AGv0QLS4uhouLi17x1b98HhMTg/DwcL32/a19+/bh1KlTsLBo+LBk/fr1WL9+Pb755htUVFSgtrYWvXr10qmjUqng6OiIzMzMDtFuS1RXVwP475gwBRyfHJ/1THF8GlOHf+xLRMbTvXt3SCQSvedHW7t2Lfr374+LFy/qlA8aNAh2dnYNXna/cOECqqurMXToUL3a6d27N2QyGS5duqTXfr+3f//+Bivl5OXlAXjwOEsIAV9fX+2H/927d3X2Ly0tRWFhoXZqC1NvtyXqx0CPHj3ava3m4vjk+KxniuPTmJj8EVGLyeVyeHh44NatW3rtV/94zdLSskF5REQEUlNTkZCQgJKSEmRkZGD+/PlwcnJCaGio3u3MmjULBw8eRFxcHEpKSlBbW4tbt25pP4hCQkLQo0ePNlm+y93dHYGBgYiPj8eZM2dQWVmJnJwcbdyzZ8/W1u0M7f5W/Rjw8fFp0+O2BsenLo5P0xqfxsTkj4haJSgoCJmZmaisrNSW/f3vf4eXlxeysrLg5+eHt956q8F+w4YNw+LFixuUv/vuu9iwYQOioqLQtWtXjBw5Em5ubkhLS4NCoQDwYB61+nc9Bw8ejBs3biA+Ph4REREAgNGjR+PatWsAHjzeXrRoETZt2oQuXbrAyckJ4eHhKCoqAvDgcVBubi6OHj3a6r6QSCRITk5GSEgIZs+eDQcHB3h7eyM7OxspKSkICAjQ1jX1ds+fP48RI0agV69euHDhAr7//ns4OTnhqaeewpkzZxrU/+abb+Ds7IzBgwe3+nzaEsfnf3F8mt74NBrDLCPX9jrB2nrURri2r/5aunaqs7Nzg/Jr164JKysrceDAgbYKz6Bqa2tFQECA2LdvH9ttofz8fCGTycTWrVsbbFu4cKHB1vbl+GS7jTGF8WliuLYvETVfZWUlTp48iWvXrmlfoPby8kJUVBSioqJQVlZm5Aj1U1tbiyNHjqC0tBQhISFst4XWrFmDIUOGICwsDMCDVTDu3LmDs2fP4vr1623WzqNwfLLdxpjK+DQlTP6acP78eQwYMAAWFhaQSCTo0aMH1q1bZ+ywdKSkpMDDw0M7d1vPnj0xY8YMY4dFnVhhYSFGjx6Nvn374rXXXtOWL1++HJMmTUJISIjeL9cbU1paGlJSUnDixIlmzwXHdnVFR0fj0qVLOH78OKytrQEAR48ehbOzMwICAvDpp5+2STvNwfHJdn/PlManKZEI0TEXuktKSsKUKVPafZ2+0aNH4+TJkygqKtJ+zd/UeHl5IT8/XzsHlbmZNGkSgP9O+UKP1l6/P59//jlOnz6NjRs3tulxyTQdPXoUly9fxpIlSxp8OaI1OD6pLXS08WlAybzz14FUVlbC39/f2GFQIwxxbTrC9X/hhRf4wWpGXn75ZSxfvrxNP1jbE8eneelo49OQmPx1IPv27UNubq6xw6BGGOLa8PoTEVFbYPKnp7i4OCgUCsjlchw9ehRjxoyBSqWCi4sLDh48qK23bds2yGQydO/eHfPmzYOTkxNkMhn8/f111n8MCwuDVCpFz549tWULFiyAQqGARCJBfn4+ACA8PBwRERHIysqCRCKBl5dXi+L/17/+BW9vb6jVashkMvj4+ODkyZMAgDlz5mjfH/T09NROcDpr1izI5XKo1Wp8/PHHAB68mLt69Wq4urrC1tYWgwcP1i61t3nzZsjlciiVSuTm5iIiIgLOzs64cuVKi2JuD0IIREdHY8CAAbCxsYGDgwPGjRuns55ma66Noa7/Z599BpVKhfXr17drfxERUSditC8at5Khvmo9atQoAUAUFRVpyyIjIwUAcerUKXH//n2Rm5srAgIChEKhENXV1dp6oaGhQqFQiMuXL4uqqiqRmZkp/Pz8hFKpFNnZ2dp606dPFz169NBpd8uWLQKAyMvL05ZNnDhReHp6NojR09NTqNXqZp1PcnKyWLNmjSgsLBQFBQVi2LBhOl9znzhxorC0tBS3b9/W2W/atGni448/1v777bffFjY2NuLw4cOiqKhIrFixQlhYWIhvvvlGp48WLlwotm/fLiZMmCD+85//NCtGfbVkqpfVq1cLqVQqDhw4IIqLi0V6erp48sknRdeuXcW9e/e09VpzbQxx/Y8dOyaUSqWIiorS6/w7wVQF1IlxfJIp6wTjk1O9tIa/vz9UKhW6deuGkJAQlJeXIzs7W6eOlZWV9u6St7c34uLiUFpaiv379xsl5uDgYLz77rtwcHCAo6MjXnrpJRQUFGiX5Jk/fz5qa2t14ispKcE333yDF198EcCDhbHj4uIwfvx4TJw4Efb29li5ciWsra0bnNfGjRvx5ptvIiUlBf379zfciT5EZWUloqOjMWHCBMyYMQNqtRo+Pj7YvXs38vPzsWfPnjZrq72vf1BQEEpKSrBq1ao2OR4REXV+TP7aiFQqBQBoNJqH1vP19YVcLtd5vGhM9V99r1/4/JlnnkHfvn3x4Ycfar/JdOjQIYSEhGhfmr1y5QoqKiowaNAg7XFsbW3Rs2dPkzmvh8nMzERZWRl8fX11yv38/CCVSnUey7Y1U7v+RERkfpj8GYGNjY32Tpuhffrpp3j66afRrVs32NjYYMmSJTrbJRIJ5s2bhxs3buDUqVMAgL/85S86ay+Wl5cDAFauXKl9R1AikeDnn39GRUWF4U6mheqnxLGzs2uwzd7eHqWlpe3avjGvPxEREZM/A9NoNCguLoaLi4tB2jtz5ox2jcns7GyMHz8ePXv2xIULF3D//n1s2rSpwT4zZ86ETCbD3r17ceXKFahUKvTp00e7vVu3bgCAmJgYCCF0fr766iuDnFdr1M/X2FiS197XxtDXn4iI6PesjB2AuUlLS4MQAsOGDdOWWVlZPfJxcUv9+9//1i42npGRAY1GgzfeeAMeHh4AHtzp+z0HBwdMmTIFhw4dglKpxNy5c3W29+7dGzKZDJcuXWqXmNvboEGDYGdnh2+//Van/MKFC6iursbQoUO1ZW19bQx9/YmIiH6Pd/7aWV1dHYqKilBTU4P09HSEh4fD1dUVM2fO1Nbx8vJCYWEhjhw5Ao1Gg7y8PPz8888NjuXo6Ig7d+7g5s2bKC0tfWjCoNFo8MsvvyAtLU2b/Lm6ugIAvvjiC1RVVeHatWtNvt82f/58/Prrrzh27BjGjh2rs00mk2HWrFk4ePAg4uLiUFJSgtraWty6dQt3797Vt4sMTiaTISIiAqmpqUhISEBJSQkyMjIwf/58ODk5ITQ0VFu3tdemva//iRMnONULERHpx4hfNW6V9v6q9fnz58XAgQOFhYWFACB69uwp1q9fL3bu3CnkcrkAIB577DGRlZUl9uzZI1QqlQAg+vTpI65evSqEeDDVh7W1tXB2dhZWVlZCpVKJcePGiaysLJ22CgoKRGBgoJDJZMLd3V289dZb4p133hEAhJeXl3ZakO+++0706dNH2NraihEjRohdu3YJT09PAeChP6mpqdq2li5dKhwdHYW9vb2YNGmS2LFjhwAgPD09daYfEUKIJ554QixfvrzR/vn111/F0qVLhaurq7CyshLdunUTEydOFJmZmWLTpk3C1tZWABC9e/cWBw4caMtL00BLpnqpq6sTW7ZsEY899piwtrYWDg4OYvz48eLKlSs69Vp6be7du9fu1//evXvi+PHjQqlUinXr1ul1/p1gqgLqxDg+yZR1gvGZxLV929G8efOQnJyMgoICY4fSIkFBQdixYwfc3d2NHcpDmeravqZ8/TvC7w+ZL45PMmWdYHxybd/2Vj+FSkfw28fI6enpkMlkJp/4mbqOdP2JiMg88AsfpLV06VLMnz8fQgjMmjULBw4cMHZIRERE1MZ456+drFixAvv378f9+/fh7u6Ow4cPGzukR5LL5ejfvz+ee+45rFmzBt7e3sYOqcPqiNefiIjMA5O/drJhwwb8+uuvEELgp59+QnBwsLFDeqR169ahtrYW2dnZDb7hS/rpiNefiIjMA5M/IiIiIjPC5I+IiIjIjDD5IyIiIjIjTP6IiIiIzEiHn+olKSnJ2CGQkd26dQsAx4I+vvrqKwDsMzJNHJ9kyurHZ0fW4Vf4ICIiIjK0Dpo+AUByh03+iIhaqhMsz0RE1FJc3o2IiIjInDD5IyIiIjIjTP6IiIiIzAiTPyIiIiIzwuSPiIiIyIww+SMiIiIyI0z+iIiIiMwIkz8iIiIiM8Lkj4iIiMiMMPkjIiIiMiNM/oiIiIjMCJM/IiIiIjPC5I+IiIjIjDD5IyIiIjIjTP6IiIiIzAiTPyIiIiIzwuSPiIiIyIww+SMiIiIyI0z+iIiIiMwIkz8iIiIiM8Lkj4iIiMiMMPkjIiIiMiNM/oiIiIjMCJM/IiIiIjPC5I+IiIjIjDD5IyIiIjIjTP6IiIiIzAiTPyIiIiIzwuSPiIiIyIww+SMiIiIyI0z+iIiIiMwIkz8iIiIiM8Lkj4iIiMiMWBk7ACKi9nTr1i38+c9/Rm1trbasqKgISqUSTz/9tE7dfv364YMPPjBwhEREhsXkj4g6NRcXF/z888/IyspqsO2f//ynzr//+Mc/GiosIiKj4WNfIur0Xn31VVhbWz+yXkhIiAGiISIyLiZ/RNTpTZ8+HTU1NQ+tM3DgQHh7exsoIiIi42HyR0SdnqenJwYPHgyJRNLodmtra/z5z382cFRERMbB5I+IzMKrr74KS0vLRrfV1NRg0qRJBo6IiMg4mPwRkVmYOnUq6urqGpRbWFhg2LBhcHNzM3xQRERGwOSPiMyCk5MTnnrqKVhY6P63Z2FhgVdffdVIURERGR6TPyIyG6+88kqDMiEEJkyYYIRoiIiMg8kfEZmN4OBgnff+LC0t8dxzz6F79+5GjIqIyLCY/BGR2XBwcMDzzz+vTQCFEJgxY4aRoyIiMiwmf0RkVmbMmKH94oe1tTXGjRtn5IiIiAyLyR8RmZWXXnoJNjY2AICxY8fCzs7OyBERERkWkz8iMisKhUJ7t4+PfInIHEmEEMLYQXQETa0MQERERMYXHByM5ORkY4fRESRbGTuCjiQ8PBzDhw83dhidVkxMDABg0aJFRo6k4/jqq68QGxuLxMREY4fSodTW1iIxMRHTpk0zdigdCscbmar6zw9qHiZ/ehg+fDgmT55s7DA6rfq/2NjH+omNjWWftcD48eMhk8mMHUaHw/FGpoh3/PTDd/6IyCwx8SMic8Xkj4iIiMiMMPkjIiIiMiNM/oiIiIjMCJM/IiIiIjPC5I8QFRUFb29vqFQq2NjYwMvLC0uWLEFZWdlD95szZw6USiUkEgkuXbpkoGgf7fjx41Cr1fjkk0+MHQoREZHJYfJHOH36NN58803cvHkT+fn52LBhA2JjYzFp0qSH7rd3717Ex8cbKMrm47zlRERETWPyR7Czs0NoaCgcHR2hVCoxefJkjB8/Hp999hlycnKMHZ7egoKCcP/+fYwdO9bYoaCyshL+/v7GDoOIiEiLkzwTjh071qCsa9euAICKioqH7stl7x5u3759yM3NNXYYREREWrzzZ2AHDhyAr68vZDIZFAoF3NzcsHbtWgAPHldGR0djwIABsLGxgYODA8aNG4cff/xRu39cXBwUCgXkcjmOHj2KMWPGQKVSwcXFBQcPHtTWGzBgACQSCSwsLDB06FBtErdkyRKo1WrIZDJ89NFHTcZ5+/Zt2Nrawt3dXVsmhMCWLVvQr18/2NjYQK1W45133mnjHmqds2fPwtXVFRKJBDt27ADQ/D7btgVqqGoAACAASURBVG0bZDIZunfvjnnz5sHJyQkymQz+/v64cOGCtl5YWBikUil69uypLVuwYAEUCgUkEgny8/MBPFgOMCIiAllZWZBIJPDy8gIAfPbZZ1CpVFi/fr0huoSIiEgHkz8Dio2Nxauvvorg4GDcuXMHt27dwooVK3DlyhUAwJo1a7B8+XJERkYiNzcXZ86cQU5ODgICAvDLL78AAN544w0sWrQIlZWVUCqVSExMRFZWFjw8PDB37lxoNBoAwA8//AA3Nzf07t0bX3/9NeRyOQBg8+bNmD17NjZu3IiZM2c2GmdFRQVOnz6NuXPnQiqVastXrVqFpUuXIjQ0FL/88gvu3buHZcuWtWOP6W/EiBE4d+6cTllz+ywsLAwzZ85ERUUFFi5ciJs3b+K7775DTU0Nnn/+ee0j8G3btjVY3mrnzp147733dMpiY2MxduxYeHp6QgiB69evA3iwriwA1NXVtUsfEBERPQyTPwPRaDR47733EBgYiGXLlsHR0REODg6YPXs2/Pz8UFlZiejoaEyYMAEzZsyAWq2Gj48Pdu/ejfz8fOzZs6fBMf39/aFSqdCtWzeEhISgvLwc2dnZAABLS0ssXLgQ2dnZSE1N1e5TUVGBlJQUvPbaa03GumHDBjg5OWHdunXassrKSsTExOC5557D4sWLYW9vD1tbWzg6OrZhL7W/h/VZPSsrK+3dV29vb8TFxaG0tBT79+9vkxiCgoJQUlKCVatWtcnxiIiI9MHkz0DS09NRXFyMUaNG6ZTXJ2mZmZkoKyuDr6+vznY/Pz9IpVKdx46Nqb9DV38XC3gwFYtarUZsbKy2LCEhAePGjYNKpWr0OKmpqUhKSsLJkyehVCq15devX0dFRQWeffbZ5p1wB9BYnzXG19cXcrlc5/E7ERFRR8Xkz0BKSkoAAPb29o1uLy4uBvDgm7e/Z29vj9LSUr3btLOzw+uvv45z587h66+/BgDs2rULYWFhjdY/dOgQNm7ciLS0NLi5uelsu3XrFgCgW7duesfRGdjY2CAvL8/YYRAREbUakz8D6dWrFwBovwzwe/VJYWNJXnFxMVxcXFrUblhYGKytrRETE4MzZ86gd+/e8PT0bFBv+/btSEhIwOnTp7Wx/pZMJgMA/Prrry2KoyPTaDStugZERESmhMmfgbi5ucHR0RGff/55o9sHDRoEOzs7fPvttzrlFy5cQHV1NYYOHdqidl1cXDB58mQcPnwYq1atQnh4uM52IQSWLl2KjIwMHDlypNE7j/XxWVhY4J///GeL4ujI0tLSIITAsGHDtGVWVlaPfFxMRERkipj8GYiNjQ1WrFiBM2fOICwsDLdv30ZdXR1KS0tx+fJlyGQyREREIDU1FQkJCSgpKUFGRgbmz58PJycnhIaGtrjtiIgI1NTUoKioCM8884zOtsuXL2Pz5s2Ij4+HtbU1JBKJzs/WrVsBPHjcO3HiRBw+fBj79u1DSUkJ0tPTG/0iSkdXV1eHoqIi1NTUID09HeHh4XB1ddX5drSXlxcKCwtx5MgRaDQa5OXl4eeff25wLEdHR9y5cwc3b95EaWkpNBoNTpw4waleiIjIaJj8GVBERAR27NiBtLQ0eHl5QaFQYOTIkUhLSwMAvPvuu9iwYQOioqLQtWtXjBw5Em5ubkhLS4NCoQDwYM66mJgYAMDgwYNx48YNxMfHIyIiAgAwevRoXLt2TafdJ554AoGBgVi4cGGDmPRZCu3DDz/ErFmzsHTpUjg7O2PBggUICAgAAIwdOxbp6el690lb27FjB/z8/AAAS5cuxcsvv6x3n1VVVcHHxwe2trYICAhA37598Y9//AM2NjbaOm+88QYCAwMxdepU9OvXD2vXroWtrS0AYPjw4dppYebPn4/u3bvD29sbL774IgoLCw3SD0RERE2RCC6E2iwSiQSJiYkN5nejtlO/lnBycrLRYpg3bx6Sk5NRUFBgtBj0kZSUhClTpnA9YzIIjjcyVabw+dGBJPPOH9Hv1E/CTERE1Bkx+SMyY1988QWWL1+OlJQUeHh4aN/1fOWVVxrUfeGFF6BUKmFpaYmBAwfiu+++M0LELVdVVYX+/ftj5cqVDbb97W9/g5+fH5RKJfr06YNZs2bh3r17HbLduro6xMTEwN/fv8G2jz/+GJs2bTLaHzgcbw9oNBps2LABXl5ekEqlsLe3x6BBg3Dz5s0O0+6mTZvQv39/2NraQqFQoH///li1apV2WrN6UVFR8Pb2hkqlgo2NDby8vLBkyRKUlZVp6xh7XJolQc0CQCQmJho7jE4tODhYBAcHG6395cuXC6lUKgAINzc3kZycbLRYmisxMVG09Nd49erVYuzYsaKkpERb5unpKbp06SIAiGPHjjXY58SJE+Lll19ucbzGtHjxYgFAREZG6pQfOnRIABCbNm0SxcXF4uLFi8LDw0MMGTJEaDSaDtXu1atXxVNPPSUAiMcff7zROrGxsWLkyJGiqKhI7+NzvDVfU9ddCCHGjx8v+vXrJ86fPy80Go24c+eOeOmll0RGRkaHaTcoKEhs3bpV5ObmitLSUpGUlCSsra3F888/r1Nv5MiRYufOnaKgoECUlJSIxMREYW1tLUaPHq1TrzXjUgjjf350MElM/pqJyV/74y+v/lr6Yfz++++Lvn37isrKSp1yT09P8de//lVYWFgIZ2dnUVxcrLO9o34Yf/nll+KFF15o9EMxMDBQ9OrVS9TV1WnLduzYIQCIs2fPdph2L126JCZMmCASEhLEkCFDmkz+hBAiLCxMDB8+XO8kk+OteR523Q8ePCgkEolIT0/v0O2OHz++wfWcNGmSACDu3LmjLQsKChI1NTU69SZPniwAiOzsbJ3ylo5LIfj5oackPvYlMjPXr1/HqlWr8N5772kn7/4tf39/hIeH4/bt23j77beNEGHbqqysxDvvvKOzzOFv5eTkwMnJCRKJRFvWu3dvAGh0+h5Tbffxxx9HSkoKpk+frvPN9MasWbMGly5dajK2tsTxpmvXrl148skn4ePj06HbTU1NbXA9nZ2dAUDnke6xY8dgaWmpU69r164AHqw1/1uGHJfmjskfkZnZtm0bhBB46aWXmqyzbt069O3bF3v37sUXX3zx0OMJIRAdHY0BAwbAxsYGDg4OGDdunM5ayHFxcVAoFJDL5Th69CjGjBkDlUoFFxcXHDx4UOd4tbW1WL16NVxdXWFra4vBgwcjMTGxxecbGRmJBQsWNLk0oYeHB3Jzc3XK6t+78/Dw6HDtNoeDgwNGjhyJ2NjYdv/mLsfbf1VXV+P8+fMYMmRIi49vau3+1rVr12Bvb48+ffo8tN7t27dha2sLd3d3nXJDjktzx+SPyMx8+umn6NevH+RyeZN1bG1t8dFHH8HCwgJz585FeXl5k3XXrFmD5cuXIzIyErm5uThz5gxycnIQEBCAX375BcCDeREXLVqEyspKKJVKJCYmIisrCx4eHpg7d67OainLli3D5s2bERMTg7t372Ls2LGYNm1ag9VvmuPLL79EVlYWpk2b1mSdFStW4N69e9i+fTtKS0uRmZmJ2NhYjBo1SmdVl47Qrj6eeOIJ3L59G99//327tsPx9l937txBdXU1/v3vfyMwMBBOTk6QyWQYMGAAdu7c2eKEx1jtAg++RHL79m3s2LEDX3zxBbZv3w6pVNpk/YqKCpw+fRpz585ttJ6hxqXZM94j544FfOev3fGdDf3p+w5WWVmZkEgkYuzYsY1u9/T0FD/99JP23xEREQKAePPNN4UQDd/BqqioEHZ2diIkJETnOF9//bUAIKKiorRlkZGRAoDOe0I7d+4UAMT169eFEEJUVlYKuVyuc7yKigphY2Mj3njjjWafZ/1+vr6+4tatW0IIIfLy8pp8EX7lypUCgPbHxcVF5OTk6NWesdv9rT/84Q8PfedPCCE+/PBDAUD85S9/afZxOd6a1pzrnpGRIQCI559/Xnz55ZeioKBAFBcXi2XLlgkAIiEhQa82jdluvR49eggAokuXLuJ///d/RXV19UPrR0ZGir59++p88ee3WjIuheDnh56SrAyTYnYOX331lbFD6NRu3boF4MFEstQ8+o7J3NxcCCEeehfmt9atW4djx45h586dmDJlSoPtmZmZKCsrg6+vr065n58fpFIpLly48NDj1//lX38n5sqVK6ioqMCgQYO0dWxtbdGzZ0+dx3rNsWLFCrz++uva95CaEhkZib179+LUqVP4wx/+gNzcXCxbtgzDhw/HuXPntO/hmXq7+qofA/V3y9oDx5uu+ncxBw4cqDMVz3vvvYddu3Zhz549mD59eodot15OTg6Ki4tx8eJFLF++HHv27MHp06fRvXv3BnVTU1ORlJSEzz//HEqlstHjGWJcEsDkTw+xsbF8EdUAGvtPn9pGVVUVADzyCwH1ZDIZ9u/fjxEjRuC1117Dpk2bdLYXFxcDAOzs7Brsa29vj9LSUr3iq3/ct3LlygbzlDk5OTX7OGfPnkVGRgaio6MfWu/u3bvYtGkTli9frl332t3dHfHx8XBwcMCWLVuwbds2k2+3JeqXI6wfE+2B401X/THz8/N1yqVSKfr06YOsrKxmt2nMdn/L2toa3bp1wwsvvAB3d3f07dsXGzZsaPBZeejQIURHRyMtLQ29evVq8niGGJfEd/70kpiYCCEEf9rpJzg4GMHBwUaPoyP96Ptiev1/rPpMpjp8+HAsXrwY165dw9q1a3W22dvbA0CjH7rFxcVwcXHRK776l9VjYmIanKs+dzn37duHU6dOwcLCQjuRcP2x169fD4lEgm+//RbXrl1DbW1tgw8jlUoFR0dHZGZm6hW/sdptierqagD/HRPtgeNN97rb2dnhsccew+XLlxsco6amBmq1Wq/4jdVuU7y8vGBpadlg/G7fvh0JCQk4ffr0QxM/wDDjkpj8EZmV7t27QyKR4P79+3rtt3btWvTv3x8XL17UKR80aBDs7OwavBx/4cIFVFdXY+jQoXq107t3b8hkMly6dEmv/X5v//79DT7M8/LyADx43CqEgK+vrzZZuHv3rs7+paWlKCws1PvRq7HabYn6MdCjR492a4PjTfe6Aw+ebFy8eBE3btzQ7l9RUYGff/5Z72lYjNVuQUFBo18uqf+jpn78CiGwdOlSZGRk4MiRI43esf09Q4xLYvJHZFbkcjk8PDy071c2V/3juN/P1yWTyRAREYHU1FQkJCSgpKQEGRkZmD9/PpycnBAaGqp3O7NmzcLBgwcRFxeHkpIS1NbW4tatW9pEKSQkBD169GiT5b7c3d0RGBiI+Ph4nDlzBpWVlcjJydHGPXv2bG3dztDub9WPgbaeb+63ON4aWrx4Mfr06YOZM2ciOzsbBQUFWLp0KSorK7Fs2TJtPVNuV6FQ4PPPP8fp06dRUlICjUaDixcv4s9//jMUCgUWL14MALh8+TI2b96M+Ph4WFtba+9O1v9s3bq1wbENMS6JyR+R2QkKCkJmZiYqKyu1ZX//+9/h5eWFrKws+Pn54a233mqw37Bhw7T/qf/Wu+++iw0bNiAqKgpdu3bFyJEj4ebmhrS0NCgUCgAP5l2LiYkBAAwePBg3btxAfHw8IiIiAACjR4/GtWvXADx4t3bRokXYtGkTunTpAicnJ4SHh6OoqAjAg8dCubm5OHr0aKv7QiKRIDk5GSEhIZg9ezYcHBzg7e2N7OxspKSkICAgQFvX1Ns9f/48RowYgV69euHChQv4/vvv4eTkhKeeegpnzpxpUP+bb76Bs7MzBg8e3OrzeRiON10ODg7417/+BRcXFwwZMgTOzs74+uuv8emnn+rMw2fK7cpkMjz11FOYM2cOnJ2doVQqMWnSJLi5ueH8+fPaL9AIof8UMoYal2ZPULOAU720O35VX38tWW7r2rVrwsrKShw4cKCdompftbW1IiAgQOzbt4/ttlB+fr6QyWRi69ateu3H8cZ221NLx6UQ/PzQE5d3IzI3Xl5eiIqKQlRUlM4yTB1BbW0tjhw5gtLSUoSEhLDdFlqzZg2GDBmCsLCwNjtmUzje2G5zGXJcmjsmf0RmaPny5Zg0aRJCQkL0fhnfmNLS0pCSkoITJ040e+44tqsrOjoaly5dwvHjx2Ftbd0mx3wUjje2+yjGGJfmjMlfO7ty5QreeustDBw4EEqlElZWVlCr1ejbty+CgoJMYuLoqKgoeHt7Q6VSwcbGBl5eXliyZInOX+kpKSnw8PBo8MKuVCpF9+7d8fTTT2PLli3a92TI9K1fvx5hYWF4//33jR1Ksz377LP461//ip49e7LdFjh69Ch+/fVXpKWlwcHBoU2O2Vwcb2y3KcYcl+aKyV872rdvH3x8fJCeno7o6Gjk5OSgvLwcFy9exNq1a1FcXIyMjAxjh4nTp0/jzTffxM2bN5Gfn6+doHPSpEnaOhMnTsSNGzfg6ekJtVoNIQTq6uqQm5uLpKQkuLu7Y+nSpRg4cGCL1sQk43jhhRewceNGY4dBBvLyyy9j+fLlDb5Faygcb9QYY49Lc8QVPtrJ+fPnERoaipEjR+LkyZOwsvpvV3t4eMDDwwP29vbab5wZk52dHUJDQ7W/eJMnT0ZKSgqSkpKQk5PT5JxjEokE9vb2ePrpp/H0008jKCgIU6ZMQVBQEK5evdpmE4caUmVlJZ599lmcO3euQ7dBRETUFN75ayfr1q1DbW0t3n//fZ3E77dGjRqFN99808CRNXTs2LEGf3F17doVwINJQJsrODgYM2fORG5uLnbv3t2mMRrKvn37kJub2+HbICIiagqTv3ZQXV2NU6dOoUuXLvh//+//NXs/IQSio6MxYMAA2NjYwMHBAePGjdNZYDwuLg4KhQJyuRxHjx7FmDFjoFKp4OLigoMHD2rrDRgwABKJBBYWFhg6dKg2iVuyZAnUajVkMhk++uijJmO5ffs2bG1t4e7urte5z5w5EwBw4sQJvfZrqeb0WVhYGKRSqc57LAsWLIBCoYBEItGudxkeHo6IiAhkZWVBIpHAy8sL27Ztg0wmQ/fu3TFv3jw4OTlBJpPB399fZxH51rQBAJ999hlUKhXWr1/frv1FRETEef6aCXrM83f16lUBQAwbNkyvNlavXi2kUqk4cOCAKC4uFunp6eLJJ58UXbt2Fffu3dPWi4yMFADEqVOnxP3790Vubq4ICAgQCoVCVFdXCyGEqKmpEW5ubsLV1VXU1NTotLNo0SIRExPTZBzl5eVCqVSKsLCwBts8PT2FWq1uct+SkhIBQPTu3VuvcxeiZfM0NbfPpk+fLnr06KGz75YtWwQAkZeXpy2bOHGi8PT01KkXGhoqFAqFuHz5sqiqqhKZmZnCz89PKJVKkZ2d3SZtHDt2TCiVShEVFaXX+bdk3jWiluJ4I1PFef70wnn+2kNJSQkANGsdw3qVlZWIjo7GhAkTMGPGDKjVavj4+GD37t3Iz8/Hnj17Guzj7+8PlUqFbt26ISQkBOXl5cjOzgYAWFpaYuHChcjOzkZqaqp2n4qKCqSkpOC1115rMpYNGzbAyckJ69ata3b89ZRKJSQSSaMLr7e1lvRZS1lZWWnvLnp7eyMuLg6lpaXYv39/mxw/KCgIJSUlWLVqVZscj4iIqClM/tpBfdKnz/tymZmZKCsr0y7CXc/Pzw9SqVTnEWNjpFIpAECj0WjL5syZA7VajdjYWG1ZQkICxo0bB5VK1ehxUlNTkZSUhJMnT0KpVDY7/nrl5eUQQjR5/LbU2j5rDV9fX8jlcp3Hy0RERB0Bk7924ObmBplMhqtXrzZ7n+LiYgCN3y20t7dv0Z00Ozs7vP766zh37hy+/vprAMCuXbuanD390KFD2LhxI9LS0uDm5qZ3ewC059y/f/8W7a+P9ugzfdjY2CAvL69d2yAiImprTP7agY2NDUaNGoX8/Hx8+eWXTdYrLCzEnDlzADxIVgA0mrAUFxfDxcWlRbGEhYXB2toaMTExOHPmDHr37g1PT88G9bZv346EhAScPn0avXr1alFbwIMvLgDAmDFjWnyM5mqvPmsOjUbT7m0QERG1ByZ/7WTNmjWwsbHB4sWLUVlZ2WidH374QTsNzKBBg2BnZ9dgguQLFy6guroaQ4cObVEcLi4umDx5Mg4fPoxVq1YhPDxcZ7sQAkuXLkVGRgaOHDmi13uKv3fv3j3ExMTAxcXloe8UthV9+szKykrnkXhrpaWlQQiBYcOGtVsbRERE7YHJXzsZMmQI/vrXv+KHH35AQEAAjh8/jvv370Oj0eCnn35CfHw8Zs+erV3DUCaTISIiAqmpqUhISEBJSQkyMjIwf/58ODk5ITQ0tMWxREREoKamBkVFRXjmmWd0tl2+fBmbN29GfHw8rK2tGyzftnXr1gbHE0KgrKwMdXV1EEIgLy8PiYmJeOqpp2BpaYkjR44Y5J0/ffrMy8sLhYWFOHLkCDQaDfLy8vDzzz83OKajoyPu3LmDmzdvorS0VJvM1dXVoaioCDU1NUhPT0d4eDhcXV21U9u0to0TJ05wqhciIjIIJn/taOLEifjxxx8RGBiIZcuWwcXFBba2tnjyySexa9cujBw5ElOnTtXWf/fdd7FhwwZERUWha9euGDlyJNzc3JCWlgaFQgHgwTx/MTExAIDBgwfjxo0biI+PR0REBABg9OjRDVYNeeKJJxAYGIiFCxc2iFEI0axz+eSTT/D444/j7t27qKqqglqthqWlJSwtLdG3b19ER0dj5syZyMzMbPFdypZoTp8BwBtvvIHAwEBMnToV/fr1w9q1a2FrawsAGD58OHJycgAA8+fPR/fu3eHt7Y0XX3wRhYWFAICqqir4+PjA1tYWAQEB6Nu3L/7xj3/AxsamzdogIiIyBIlo7qe/mZNIJEhMTMTkyZONHUqnVb+WcHJyspEj0TVv3jwkJyejoKDA2KE0kJSUhClTpjQ7iSdqDY43MlWm+vlhopJ554+oGWpra40dAhERUZtg8kdERERkRpj8ET3EihUrsH//fty/fx/u7u44fPiwsUMiIiJqFStjB0BkyjZs2IANGzYYOwwiIqI2wzt/RERERGaEyR8RERGRGWHyR0RERGRGmPwRERERmRF+4UMPMTExnECyHZ0/fx7AfyfrpEe7desWAPYZGQbHG5mq8+fP66y1Tg/HFT6aif/ZEXUe9+7dw8WLFzFmzBhjh0JEbWT48OFYvHixscPoCJKZ/BGR2eEyZURkxri8GxEREZE5YfJHREREZEaY/BERERGZESZ/RERERGaEyR8RERGRGWHyR0RERGRGmPwRERERmREmf0RERERmhMkfERERkRlh8kdERERkRpj8EREREZkRJn9EREREZoTJHxEREZEZYfJHREREZEaY/BERERGZESZ/RERERGaEyR8RERGRGWHyR0RERGRGmPwRERERmREmf0RERERmhMkfERERkRlh8kdERERkRpj8EREREZkRJn9EREREZoTJHxEREZEZYfJHREREZEaY/BERERGZESZ/RERERGaEyR8RERGRGWHyR0RERGRGmPwRERERmREmf0RERERmxMrYARARtSeNRoOysjKdsvLycgBAUVGRTrlEIoG9vb3BYiMiMgYmf0TUqRUWFsLZ2Rm1tbUNtjk6Our8OzAwEKdPnzZUaERERsHHvkTUqfXo0QN//OMfYWHx8P/uJBIJpk6daqCoiIiMh8kfEXV6r7zyyiPrWFpaYsKECQaIhojIuJj8EVGnN3HiRFhZNf2Wi6WlJUaPHo0uXboYMCoiIuNg8kdEnZ5KpcKYMWOaTACFEJgxY4aBoyIiMg4mf0RkFmbMmNHolz4AQCqV4k9/+pOBIyIiMg4mf0RkFv70pz9BLpc3KLe2tsb48eOhUCiMEBURkeEx+SMisyCTyTBhwgRYW1vrlGs0GkyfPt1IURERGR6TPyIyG9OmTYNGo9EpU6lUeP75540UERGR4TH5IyKz8dxzz+lM7GxtbY2pU6dCKpUaMSoiIsNi8kdEZsPKygpTp07VPvrVaDSYNm2akaMiIjIsJn9EZFamTp2qffTbo0cPjBgxwsgREREZFpM/IjIr/v7+cHZ2BgC8+uqrj1z2jYios2l6yvs2kpSU1N5NEBHpxc/PD7dv30aXLl34fxQRmZTevXtj+PDh7dqGRAgh2rUBiaQ9D09ERETUaQQHByM5Obk9m0hu9zt/AJCYmIjJkycboimidpGUlIQpU6agnf9W6nQkEonJ/v4fPnwYwcHBxg6DjIC/z2SqJk2aZJB2+LILEZklJn5EZK6Y/BERERGZESZ/RERERGaEyR8RERGRGWHyR0RERGRGmPwRERERmRGTSv78/PxgaWmJIUOGGLztWbNmQSaTQSKRoKqqyuDtm6KtW7eie/fukEgk2L17t7b8+PHjUKvV+OSTT9q1fUO1Y0id8ZyIiKhjMank75tvvkFgYKBR2t6/fz/efvtto7Rtqt5++22cO3euQbmh5sbqjHNwdcZzIiKijsUgkzzrqy1WBamsrMSzzz7baPJCrRMUFIT79++36TEbu17t0Y6xmdI58XeEiMg8mdSdv3rW1tatPsa+ffuQm5vbon25JJ3hteZ6Ucuwz4mIzJNJJn/Xr19H//79oVAoYGtri4CAAJw9e1anzr/+9S94e3tDrVZDJpPBx8cHJ0+eBACEh4cjIiICWVlZkEgk8PLy0u534MAB+Pr6QiaTQaFQwM3NDWvXrtVut7CwwKeffooxY8ZArVbDyckJH374od7nEBcXB4VCAblcjqNHj2LMmDFQqVRwcXHBwYMHdeoKIRAdHY0BAwbAxsYGDg4OGDduHH788Udtnc2bN0Mul0OpVCI3NxcRERFwdnbG/PnzoVAoYGFhgaFDh6JHjx6wtraGQqHAk08+iYCAAPTu3RsymQz29vZYsmRJs/uxMWfPnoWrqyskEgl27NgB4MH1kkgkjf783//9X4uuV2PtNLevIuCXOwAAIABJREFU9Ol7Q2rsnJob67Zt2yCTydC9e3fMmzcPTk5OkMlk8Pf3x4ULF7T1wsLCIJVK0bNnT23ZggULoFAoIJFIkJ+fD6Dp35HPPvsMKpUK69evN0SXEBGRMYh2BkAkJiY2u/6zzz4rPDw8xE8//SQ0Go344YcfxB/+8Achk8nE1atXtfWSk5PFmjVrRGFhoSgoKBDDhg0TXbp00W6fOHGi8PT01Dl2TEyMACDef/99UVBQIAoLC8UHH3wgpk+fLoQQIjIyUgAQp06dEsXFxaKwsFC8+OKLwsbGRpSXl+t97r893v3790Vubq4ICAgQCoVCVFdXa+utXr1aSKVSceDAAVFcXCzS09PFk08+Kbp27Sru3bvX4HgLFy4U27dvFxMmTBD/+c9/xLvvvisAiAsXLojy8nKRn58vRo8eLQCITz/9VOTl5Yny8nIRFhYmAIhLly41ux+vXbsmAIhdu3Zpy3JycgQAsX37dm2dZcuWafvo7t27wsHBQfj7+4va2toWX6/ft9OSvnpU3zdXYmKiaItfl8bOqbmxhoaGCoVCIS5fviyqqqpEZmam8PPzE0qlUmRnZ2vrTZ8+XfTo0UOn3S1btggAIi8vT1vWWJ8fO3ZMKJVKERUV1epzFUL/338iQ2ir32eithYcHCyCg4Pbu5kkk7zzp1Qq4ebmBisrKwwcOBDx8fGoqqrCnj17tHWCg4Px7rvvwsHBAY6OjnjppZdQUFCAvLy8Ro+p0Wjw3nvvITAwEMuWLYOjoyMcHBwwe/Zs+Pn56dT19/eHWq2Gg4MDQkJC8Ouvv+Knn35q8fn4+/tDpVKhW7duCAkJQXl5ObKzswE8eO8qOjoaEyZMwIwZM6BWq+Hj44Pdu3cjPz9f55zrbdy4EW+++SZSUlLQv39/bbm3tzfkcjm6dOmCqVOnAgBcXV3RtWtXyOVyzJgxAwB07pLp24+N8fLywvvvvw+5XA4AeOONN1BZWYkPP/wQFhYWbdZOS/rqYX1vapoTq5WVlfaup7e3N+Li4lBaWor9+/e3SQxBQUEoKSnBqlWr2uR4RERkekzyCx+/5+PjA7VajfT09Cbr1L8nWFtb2+j29PR0FBcXY9SoUTrllpaWWLhw4SOPq9Fo9A27UVKpVOd4mZmZKCsrg6+vr049Pz8/SKVSnUd6LWmnpqZGW9acc3lUPz5KUlIS/v73v2PTpk3o169fm7bT2r76fd+bsubG6uvrC7lcrpPQExERPUyHSP7+P3v3HhZVtf8P/D3cZmCAAUQUQURARRTzxjeliDiVaTyamhe8VHYx1BJR8q6paOTtAY73NKPvTzsKKOHJS3rMOGYl5UmD8FRIKooVN2GQSwywfn/4ZXIcUGa4zMC8X8/DH+699l6fvfba8HFf1gLuJgv3/iE8duwYNm3ahKysLCiVyof+kVQqlQAABweHVo1TVyUlJQAAW1tbrXUODg4oKytr1fp1bccHKSoqwty5cxEQEICoqKgWr8fQbWWspFKpTndQiYjItBnlY9/71dTUoLi4GB4eHgCA3NxcjBs3Dl27dkV6ejpKS0uxYcOGB+6jW7duAKB+4d1Y1CejDSUuJSUlcHd3b7W69WnHB5k3bx5KSkqQkJAAc3PzFq/HkG1lrFQqlckeOxER6addJH9ffPEF6urqMHjwYABAZmYmVCoV5syZAy8vL/XMHA/i6ekJJycnnDp1qi1CbrL+/fvD1tYWFy5c0Fienp6O6upqDBkypNXq1qcdG3Ps2DF8/PHHWLlyJfr166devnDhwharx5BtZazS0tIghMCwYcPUyywsLNrFo20iIjIMo0z+qqurUVpaipqaGnz//feIiIhAjx49MGPGDABQ3wE8ffo0qqqqkJ2drfW+l5OTE27duoVr166hrKwMZmZmWLZsGc6ePYuIiAjk5eWhrq4OZWVluHz5clsfoppMJkNUVBRSUlKwf/9+KJVKZGZmYvbs2XB1dUV4eHir1d2UdmwKpVKJWbNmYeDAgViyZAkAoKqqChcuXMClS5f0Ol8NJS+GbCtjUVdXh9u3b6OmpgYZGRmIjIyEh4eH+toA7n6AU1xcjNTUVKhUKhQUFOD69eta+2qozU+cOMGhXoiIOrrW/p4YOg71kJCQIEJCQoSLi4uwsLAQnTp1ElOmTBHXr1/XKLd48WLh5OQkHBwcxMSJE8W2bdsEAOHt7S1yc3PF999/L3r06CGsra3F448/rh4GZNu2bcLf31/IZDIhk8nEoEGDxPbt28WGDRuEtbW1ACB69eolcnJyxP79+4Wjo6MAINzd3cWPP/7Y5OPYvn27sLGx0djf7t27hb29vQAgevTooR66pq6uTmzatEn06tVLWFpaCkdHRzFu3Djx888/q/d3b3zdu3cX+/btE0IIER8fr67H09NTfPnll2L9+vVCoVAIAKJLly7i448/FgcPHhRdunQRAISjo6M4cODAQ9sxMjJSvY1cLhfjx48XW7duFV27dhUAhI2NjRgzZozYvHmzANDgz3PPPafX+VqxYoVWPU1tK13avqlaYmiIhtpOl1jDw8OFpaWlcHNzExYWFsLe3l6MHTtW5OTkaNRTVFQkQkJChEwmEz179hRz584VCxcuFACEj4+PeliYhq6R48ePCzs7O7Fu3bpmHWs9Xa9/orbAoV7IWLXVUC8SIVp3slGJRILExERMmjSpNashalVJSUmYPHmyQefmnTVrFpKTk1FUVGSwGHTF65+MkTFcz0QNmThxIgAgOTm5NatJNsrHvkTUMH2H4CEiIqrH5E8HP/30U6PTmN37ExYWZuhQidq906dPY+nSpTh8+DC8vLzU19eLL76oVXbEiBGws7ODubk5+vXrh++//94AEeuvqqoKvr6+WLFihdY6lUqFmJgY+Pj4wMrKCg4ODujfvz+uXbvWburdsGEDfH19YW1tDblcDl9fX6xcuVI9BFe96Oho+Pn5wd7eHlKpFD4+Pli0aBHu3LmjLvPPf/4TGzZsMOh/hNg372LfNL6+2WSt/WAZfOeHOgBDvyO0dOlSYWVlpX63Mzk52WCx6ELf6/+dd94Ro0ePFkqlUr3M29tbdOrUSQAQR48e1drmxIkT4vnnn29WvIayYMECAUAsX75ca924ceNEnz59xPnz54VKpRK3bt0SY8aMEZmZme2m3tDQULF582aRn58vysrKRFJSkrC0tBTPPPOMRrng4GCxfft2UVRUJJRKpUhMTBSWlpZi5MiRGuXi4+NFcHCwuH37ts6xCNG865l98y/smy3fN9vqnT8mf0RNYOjkr73S5/p/7733RO/evUVlZaXGcm9vb/Hxxx8LMzMz4ebmJkpKSjTWt9c/sF999ZUYMWJEg3/oDhw4ICQSicjIyGjX9Y4bN07rfE6cOFEAELdu3VIvCw0NFTU1NRrlJk2aJABozF8thBARERFi+PDhQqVS6RyPvtcz++Zf2Ddbp2+a9Ny+RGSarly5gpUrV2LNmjWQyWRa6wMDAxEZGYm8vDy8/fbbBoiwZVVWVmLhwoWIj49vcP3OnTsxePBg+Pv7t+t6U1JStM6nm5sbAGg8Njt69KjGAPEA4OzsDACoqKjQWL569WpcunSp0WNoaeybmtg3jadv6oPJHxEZjS1btkAIgTFjxjRaZt26dejduzc++OADnD59+oH7E0IgNjYWffv2hVQqhaOjI8aOHasxF/KOHTsgl8thY2ODI0eOYNSoUbC3t4e7uzsOHDigsb/a2lq888478PDwgLW1NQYMGIDExES9j3f58uV488030blzZ6111dXVOH/+PAYOHKj3/o2t3ntlZ2fDwcEBPXr0eGC5vLw8WFtbo2fPnhrLHR0dERwcjPj4+Db5apd98y/sm3cZS9/UB5M/IjIax44dQ58+fWBjY9NoGWtra3z00UcwMzPDzJkzUV5e3mjZ1atXY+nSpVi+fDny8/Nx9uxZ3LhxA0FBQfjjjz8AAHPmzMH8+fNRWVkJOzs7JCYmIicnB15eXpg5c6bGgONLlizBxo0bERcXh99++w2jR4/G1KlTtWadaYqvvvoKOTk5mDp1aoPrb926herqavznP/9BSEgIXF1dIZPJ0LdvX2zfvl3vPyqGqhe4+6J+Xl4etm3bhtOnT2Pr1q2wsrJqtHxFRQXOnDmDmTNnNlhu0KBByMvLww8//KB3TE3FvvkX9k3j6pt6ae0Hy+A7f9QB8J0//ehy/d+5c0dIJBIxevToBtd7e3uLq1evqv8dFRUlAIi33npLCKH9XlVFRYWwtbUVYWFhGvv59ttvBQARHR2tXrZ8+XIBQOPdn+3btwsA4sqVK0IIISorK4WNjY3G/ioqKoRUKhVz5sxp0jHeu93QoUPFzZs3hRBCFBQUaL3flJmZKQCIZ555Rnz11VeiqKhIlJSUiCVLlggAYv/+/TrVach669UPGt+pUyfx97//XVRXVz+w/PLly0Xv3r01Pq6414cffigAiP/3//6fTnHoej2zb7Jv3q+1+mZbvfNn0RYJZlxcXGsPWEjUqm7evAngrwE4qeXl5+dDCPHAOyv3WrduHY4ePYrt27dj8uTJWuuzsrJw584dDB06VGN5QEAArKysHjqVYf3/5uvvrvz888+oqKhA//791WWsra3RtWtXjUd1TbFs2TK88cYb6neLGiKVSgEA/fr1Q2BgoHr5mjVrsHPnTuzevRvTpk1rF/XWu3HjBkpKSnDx4kUsXboUu3fvxpkzZ+Di4qJVNiUlBUlJSTh16hTs7Owa3F99X6m/U9Za2Dc1sW8aT9/UFx/7EpFRqKqqAvDXL/iHkclkSEhIgEQiwauvvorKykqN9SUlJQAAW1tbrW0dHBxQVlamU3z1j/BWrFihMa7n9evXtV74fpBz584hMzMTr7/++gPLubq6AgAKCws1lltZWaFHjx7IycnRKX5D1XsvS0tLdO7cGSNGjMDBgweRlZWFmJgYrXIHDx7E+vXrkZaWBk9Pz0b3Z21tDeCvvtNa2Dc1sW8aT9/UV5vc+Zs/fz6nd6J2rX46KN7B1o1EImly2fpflroMkDp8+HAsWLAAmzdvxtq1a+Hh4aFe5+DgAAAN/iEtKSmBu7t7k+sBoH4BPS4uDpGRkTpte6+9e/fi888/h5mZ9v+93333Xbz77rv47rvvMHToUPTq1QuXL1/WKldTUwOFQtEu6m2Mj48PzM3NkZWVpbF869atOHnyJM6cOdNgcnSv6upqAH/1ndbCvsm+CRhn39QX7/wRkVFwcXGBRCJBaWmpTtutXbsWvr6+uHjxosby/v37w9bWVuuF9/T0dFRXV2PIkCE61dO9e3fIZDJcunRJp+3ul5CQACGExk9BQQGAu186CiHUjwMnT56Mixcv4tdff1VvX1FRgevXr+s81IWh6i0qKmrwBf7s7GzU1taie/fuAO5+/bp48WJkZmYiNTX1oX9cAaj7SpcuXXSKSVfsm+ybxto39cXkj4iMgo2NDby8vNTvVzZV/SO2+8fgkslkiIqKQkpKCvbv3w+lUonMzEzMnj0brq6uCA8P17meV155BQcOHMCOHTugVCpRW1uLmzdv4rfffgMAhIWFoUuXLi02hdeCBQvQo0cPzJgxA7m5uSgqKsLixYtRWVmJJUuWqMsZc71yuRynTp3CmTNnoFQqoVKpcPHiRbz88suQy+VYsGABAODy5cvYuHEj9uzZA0tLS61pMzdv3qy17/q+0tJjzd2PfVMb+6Zx9E19MfkjIqMRGhqKrKwsjXekPvnkE/j4+CAnJwcBAQGYO3eu1nbDhg1T/6K+16pVqxATE4Po6Gg4OzsjODgYnp6eSEtLg1wuB3B3LLW4uDgAwIABA/Drr79iz549iIqKAgCMHDkS2dnZAID4+HjMnz8fGzZsQKdOneDq6orIyEjcvn0bwN1HPfn5+Thy5EiLtIejoyO+/PJLuLu7Y+DAgXBzc8O3336LY8eOaYx1Zsz1ymQyPPbYY3j99dfh5uYGOzs7TJw4EZ6enjh//rz6IwWhxzAd3333Hdzc3DBgwADdD1JH7Jua2DcfrC37pl5a+3ticKgX6gA41It+dL3+s7OzhYWFhdi3b18rRtV6amtrRVBQkNi7dy/rbWWFhYVCJpOJzZs367ytPtcz+ybrbarm9E1O70ZEJsfHxwfR0dGIjo7WmFqpPaitrUVqairKysoQFhbGelvZ6tWrMXDgQERERLRJfeybrLep2rpv6sMok7/Dhw/Dy8tL67m6hYUFnJ2d8fTTTyMlJaXV43jllVcgk8kgkUge+Ln2/fG++OKLWmVGjBgBOzs7mJubo1+/fi32/kNr2bx5s/ol5127dqmXHz9+HAqFAp9++mmr1t9W9ZDxWbp0KSZOnIiwsDCdX7A3pLS0NBw+fBgnTpxo8nhwrFc/sbGxuHTpEo4fPw5LS8s2q5d9k/U+jKH6ps5a+94imvHY19vbWygUCvW/i4uLxenTp4Wvr68AIA4ePNhSYTaqodHVG+Pt7S06deokAIijR49qrb9/lHdjl52dLQCInTt3qpcdPXpU2Nvbi3/+85+tWndb1dNUfOyrn+Zc/ydPnhSLFy9u4YiovUtNTRUxMTGipqZG730093pm36SGtETf5GPfBjg6OuKpp57C3//+dwB3x17TRWVlpcao4K1hy5YtMDMzQ3h4eLv6n2FThYaGorS0FKNHj26xfTZ0XlqjnvauLfpvW9TRVCNGjMD69esNHQYZmeeffx5Lly7V+oK2LbFvUkOMoW82VbtK/urVj6pdP0p6U+3duxf5+fl61dnUwWoDAwMRGRmJvLw8vP3223rVZWqac15MSVu0E88FEVHH1y6Tv4yMDABAcHCwxvIvv/wSfn5+UCgUkMlk8Pf3x8mTJwEAkZGRiIqKQk5ODiQSCXx8fNTb7du3D0OHDoVMJoNcLoenpyfWrl2rXm9mZoZjx45h1KhRUCgUcHV1xYcffthofOvWrUPv3r3xwQcf4PTp0w88FiEEYmNj0bdvX0ilUjg6OmLs2LEa8zFu3LgRNjY2sLOzQ35+PqKiouDm5obZs2dDLpfDzMwMQ4YMQZcuXWBpaQm5XI7BgwcjKChIPfing4MDFi1a1OT2asi5c+fg4eEBiUSCbdu2AQCuXLmi9W5m/c+//vUvvc5LQ/U0ta127NgBuVwOGxsbHDlyBKNGjYK9vT3c3d1x4MCBB56LltaUeCMiImBlZYWuXbuql7355puQy+WQSCTqaYwaaqctW7ZAJpPBxcUFs2bNgqurK2QyGQIDAzXmBm1OHQDw2Wefwd7eHu+++26rthcREbWR1n6wjBZ856+iokKcOHFC9OjRQ4wYMULcuXNHo3xycrJYvXq1KC4uFkVFRWLYsGGiU6dO6vUvvPCC8Pb21tgmLi5OABDvvfeeKCoqEsXFxeL9998X06ZNE0L89c7f559/LkpKSkRxcbF47rnnhFQqFeXl5VrxXr16VQghxNdffy3MzMyEp6enOs6G3vl75513hJWVldi3b58oKSkRGRkZYvDgwcLZ2Vn8/vvv6nL1ccybN09s3bpVjB8/Xvz3v/8Vq1atEgBEenq6KC8vF4WFhWLkyJECgDh27JgoKCgQ5eXlIiIiQgAQly5danJ7NfTO340bNwQAsXXrVnWZJUuWqNvit99+E46OjiIwMFDU1tbqfV7ur0eftvr8889FaWmpyM/PF0FBQUIul4vq6mqhD33eEWpqvNOmTRNdunTR2HbTpk0CgCgoKFAva6idwsPDhVwuF5cvXxZVVVUiKytLBAQECDs7O5Gbm9sidRw9elTY2dmJ6OhonY5fCA71RMaJ7/CSseI7f/+ntLRUfSfJxsZGfSdn2rRpWl/STJgwAatWrYKjoyOcnJwwZswYFBUVqaeJuZ9KpcKaNWsQEhKCJUuWwMnJCY6OjnjttdcQEBCgUTYwMBAKhQKOjo4ICwvDn3/+iatXrzYa9/DhwzF//nxcu3ZNY9Txe1VWViI2Nhbjx4/H9OnToVAo4O/vj127dqGwsBC7d+/W2mb9+vV46623cPjwYfj6+qqX+/n5wcbGBp06dcKUKVMAAB4eHnB2doaNjQ2mT58OABp3nXRtr4b4+PjgvffeU39RNWfOHFRWVuLDDz9Uz9PYEvXo01aBgYGwt7dH586dERYWhvLycuTm5ja5zubQJ159WVhYqO8u+vn5YceOHSgrK0NCQkKL7D80NBRKpRIrV65skf0REZFhGX3yp1Ao1HP9qVQq3Lx5E/Pnz0dERAQGDBigfmTVkPrksLHJuDMyMlBSUoJnn31WY7m5uTnmzZv30P2qVKoHxr5u3Tr06dMH27dvx7lz57TWZ2Vl4c6dO+o5C+sFBATAyspK49GdLqysrADcnehal5gf1l4Pk5SUhE8++QRr1qxBnz59WrSe5rZVfZs87Jy1lNY6t00xdOhQ2NjYaCT6RERE9Yw++buXhYUF3Nzc8Morr2Dz5s34+eef8d5776nXHzt2DE8++SQ6d+4MqVSq9Y7b/ZRKJQDAwcGhVeKtn9dRIpHg1Vdf1ZgWCPjrg5WGJol2cHBAWVlZq8RVT9f2epCioiLMnTsXAQEB6qmHWrIeQ7eVrgwdr1Qq1enOKhERmY52lfzdq36y5MuXLwMAcnNzMW7cOHTt2hXp6ekoLS3Fhg0bHriPbt26AcAD7x421/Dhw7FgwQJkZ2drfEQC/JV0NpQIlJSUwN3dvdXi0qe9HmTevHkoKSnRmsS8peoxZFvpw5DxqlQqo2wTIiIyDu02+fvPf/4DAOrHi5mZmVCpVJgzZw68vLzUM3M8iKenJ5ycnHDq1KlWjXXt2rXw9fXFxYsXNZb3798ftra2uHDhgsby9PR0VFdXY8iQIa0Wkz7t1Zhjx47h448/xsqVK9GvXz/18oULF7ZYPYZsK33oEq+FhUWLPo5OS0uDEALDhg1rtTqIiKj9ahfJX2VlJerq6iCEwK1bt5CQkIAVK1bA2dkZ8+fPB3D34wYAOH36NKqqqpCdna31XpWTkxNu3bqFa9euoaysDGZmZli2bBnOnj2LiIgI5OXloa6uDmVlZeo7ii2h/vHv/QM/ymQyREVFISUlBfv374dSqURmZiZmz54NV1dXhIeHt1gM92tKezWFUqnErFmzMHDgQPWHLVVVVbhw4QIuXbqk13lpKEkxZFvpQ5d4fXx8UFxcjNTUVKhUKhQUFOD69eta+2ysnerq6nD79m3U1NQgIyMDkZGR8PDwwIwZM1qkjhMnTnCoFyKijqS1vyeGHkM9pKSkCG9vbwFA60cqlYpevXqJOXPmaAxlIYQQixcvFk5OTsLBwUFMnDhRbNu2TQAQ3t7eIjc3V3z//feiR48ewtraWjz++OPq4Ta2bdsm/P39hUwmEzKZTAwaNEhs375dbNiwQVhbWwsAolevXiInJ0fs379fODo6CgDC3d1d/PjjjxrxOjs7i7feeqvB41q4cKHWUC91dXVi06ZNolevXsLS0lI4OjqKcePGiZ9//lld5t44unfvLvbt2yeEECI+Pl7Y2NgIAMLT01N8+eWXYv369UKhUAgAokuXLuLjjz8WBw8eFF26dBEAhKOjozhw4MBD2ysyMlK9jVwuF+PHjxdbt24VXbt2FQCEjY2NGDNmjNi8eXOD5wmAeO655/Q6LytWrNCqp6lttX37dnWb1J+z3bt3C3t7ewFA9OjRQ/zyyy869Uch9BsaoinxCiFEUVGRCAkJETKZTPTs2VPMnTtXLFy4UAAQPj4+6n7eUP8NDw8XlpaWws3NTVhYWAh7e3sxduxYkZOT02J1HD9+XNjZ2Yl169bp3G76XP9ErY1DvZCxaquhXiRCCNGayaVEIkFiYiImTZrUmtUQtaqkpCRMnjwZrXy56GzWrFlITk5GUVGRoUNpEK9/MkbGej0TTZw4EQCQnJzcmtUkt4vHvkTUOH2H5iEiItPE5I+IiIjIhDD5I2qnli1bhoSEBJSWlqJnz544dOiQoUMiIqJ2wMLQARCRfmJiYhATE2PoMIiIqJ3hnT8iIiIiE8Lkj4iIiMiEMPkjIiIiMiFM/oiIiIhMCJM/IiIiIhPSJjN8EBEREdHDTZgwodVn+Gj1oV4SExNbuwoiIp188803iI+P5+8nIjI63bt3b/U6Wv3OHxGRseHcrkRkwji3LxEREZEpYfJHREREZEKY/BERERGZECZ/RERERCaEyR8RERGRCWHyR0RERGRCmPwRERERmRAmf0REREQmhMkfERERkQlh8kdERERkQpj8EREREZkQJn9EREREJoTJHxEREZEJYfJHREREZEKY/BERERGZECZ/RERERCaEyR8RERGRCWHyR0RERGRCmPwRERERmRAmf0REREQmhMkfERERkQlh8kdERERkQpj8EREREZkQJn9EREREJoTJHxEREZEJYfJHREREZEKY/BERERGZECZ/RERERCaEyR8RERGRCWHyR0RERGRCmPwRERERmRAmf0REREQmxMLQARARtaaCggJ88sknGssuXLgAANi9e7fGcjs7O0yZMqXNYiMiMgSJEEIYOggiotby559/wsXFBXfu3IG5uTkAoP7XnkQiUZdTqVR4+eWX8dFHHxkiTCKitpLMx75E1KFJpVJMmDABFhYWUKlUUKlUqKmpQU1NjfrfKpUKADB16lQDR0tE1PqY/BFRhzd16lRUV1c/sIyDgwP+9re/tVFERESGw+SPiDq8kJAQdO7cudH1lpaWmD59Oiws+Bo0EXV8TP6IqMMzMzPDtGnTYGlp2eB6lUrFDz2IyGQw+SMikzBlyhT1u33369atG4YPH97GERERGQaTPyIyCf/zP/+DHj16aC23srLCyy+/rPHlLxFRR8bkj4hMxosvvqj16Le6upqPfInIpDD5IyKTMW3aNK1Hvz4+PvD39zdQREREbY/JHxGZDF9fX/j5+akf8VpaWuKVV14xcFRERG2LyR99x0dEAAAgAElEQVQRmZSXXnpJPdNHTU0NH/kSkclh8kdEJmXKlCmora0FAAwePBg9e/Y0cERERG2LyR8RmRQPDw88+uijAICXX37ZwNEQEbU9kx7OPjY2Ft98842hwyCiNvbnn39CIpHg1KlTOHv2rKHDIaI2tmDBApMe29Ok7/x98803OH/+vKHDoP9z/vx5ng8d3bx5E4cOHTJ0GO2Ou7s7unTpAplMZuhQOixez2SsDh06hBs3bhg6DIMy6Tt/ADBs2DAkJycbOgwCMHHiRADg+dBBUlISJk+ezDbTw5UrV+Dj42PoMDosXs9krDigu4nf+SMi08XEj4hMFZM/IiIiIhPC5I+IiIjIhDD5IyIiIjIhTP6IiIiITAiTvw4iOjoafn5+sLe3h1QqhY+PDxYtWoQ7d+48cLvXX38ddnZ2kEgkuHTpkt7119XVIS4uDoGBgXrvo6UcP34cCoUCn376qaFDISIiMjpM/jqIM2fO4K233sK1a9dQWFiImJgYxMfHq4dbaMwHH3yAPXv2NKvu7OxsPPHEE1iwYAEqKiqata+WIIQwdAhERERGy+TH+esobG1tER4erp6wftKkSTh8+DCSkpJw48YNdO/evVXq/eGHHxAdHY3Zs2ejvLzcKBKv0NBQlJaWGjoMAEBlZSWeeuopfP3114YOhYiICADv/HUYR48eVSd+9ZydnQHgoXfjmjPg5SOPPILDhw9j2rRpkEqleu+no9q7dy/y8/MNHQYREZEakz897Nu3D0OHDoVMJoNcLoenpyfWrl0L4O4jx9jYWPTt2xdSqRSOjo4YO3YsfvrpJ/X2O3bsgFwuh42NDY4cOYJRo0bB3t4e7u7uOHDggLpc3759IZFIYGZmhiFDhqiTuEWLFkGhUEAmk+Gjjz5qNM68vDxYW1ujZ8+e6mVCCGzatAl9+vSBVCqFQqHAwoULW7iFDOfcuXPw8PCARCLBtm3bADS9vbds2QKZTAYXFxfMmjULrq6ukMlkCAwMRHp6urpcREQErKys0LVrV/WyN998E3K5HBKJBIWFhQCAyMhIREVFIScnBxKJRD2o8GeffQZ7e3u8++67bdEkREREGpj86Sg+Ph4vvfQSJkyYgFu3buHmzZtYtmwZfv75ZwDA6tWrsXTpUixfvhz5+fk4e/Ysbty4gaCgIPzxxx8AgDlz5mD+/PmorKyEnZ0dEhMTkZOTAy8vL8ycORMqlQoA8OOPP8LT0xPdu3fHt99+CxsbGwDAxo0b8dprr2H9+vWYMWNGg3FWVFTgzJkzmDlzJqysrNTLV65cicWLFyM8PBx//PEHfv/9dyxZsqQVW6xtPf7441qPWJva3hEREZgxYwYqKiowb948XLt2Dd9//z1qamrwzDPPqOeC3LJlCyZNmqRRx/bt27FmzRqNZfHx8Rg9ejS8vb0hhMCVK1cAALW1tQDufiRDRETU1pj86UClUmHNmjUICQnBkiVL4OTkBEdHR7z22msICAhAZWUlYmNjMX78eEyfPh0KhQL+/v7YtWsXCgsLsXv3bq19BgYGwt7eHp07d0ZYWBjKy8uRm5sLADA3N8e8efOQm5uLlJQU9TYVFRU4fPgwXn311UZjjYmJgaurK9atW6deVllZibi4ODz99NNYsGABHBwcYG1tDScnpxZsJeP2oPauZ2Fhob5z6+fnhx07dqCsrAwJCQktEkNoaCiUSiVWrlzZIvsjIiLSBZM/HWRkZKCkpATPPvusxvL6JC0rKwt37tzB0KFDNdYHBATAyspK49FhQ+rv0NXfiQLuDsWiUCgQHx+vXrZ//36MHTsW9vb2De4nJSUFSUlJOHnyJOzs7NTLr1y5goqKCjz11FNNO+AOrqH2bsjQoUNhY2Oj8eieiIiovWLypwOlUgkAcHBwaHB9SUkJgLtf3t7PwcEBZWVlOtdpa2uLN954A19//TW+/fZbAMDOnTsRERHRYPmDBw9i/fr1SEtLg6enp8a6mzdvAgA6d+6scxymTiqVoqCgwNBhEBERNRuTPx1069YNANQv9N+vPilsKMkrKSmBu7u7XvVGRETA0tIScXFxOHv2LLp37w5vb2+tclu3bsX+/ftx5swZdaz3kslkAIA///xTrzhMlUqlatb5IyIiMiZM/nTg6ekJJycnnDp1qsH1/fv3h62tLS5cuKCxPD09HdXV1RgyZIhe9bq7u2PSpEk4dOgQVq5cicjISI31QggsXrwYmZmZSE1NbfDOY318ZmZm+Pe//61XHKYqLS0NQggMGzZMvczCwuKhj4uJiIiMEZM/HUilUixbtgxnz55FREQE8vLyUFdXh7KyMly+fBkymQxRUVFISUnB/v37oVQqkZmZidmzZ8PV1RXh4eF61x0VFYWamhrcvn0bf/vb3zTWXb58GRs3bsSePXtgaWkJiUSi8bN582YAdx/3vvDCCzh06BD27t0LpVKJjIyMBj9EMWV1dXW4ffs2ampqkJGRgcjISHh4eGh8We3j44Pi4mKkpqZCpVKhoKAA169f19qXk5MTbt26hWvXrqGsrAwqlQonTpzgUC9ERGQwTP50FBUVhW3btiEtLQ0+Pj6Qy+UIDg5GWloaAGDVqlWIiYlBdHQ0nJ2dERwcDE9PT6SlpUEulwO4O+5cXFwcAGDAgAH49ddfsWfPHkRFRQEARo4ciezsbI16Bw0ahJCQEMybN08rJl1m1fjwww/xyiuvYPHixXBzc8Obb76JoKAgAMDo0aORkZGhU3ucP38ejz/+OLp164b09HT88MMPcHV1xWOPPYazZ8/qtK+WsG3bNgQEBAAAFi9ejOeff17n9q6qqoK/vz+sra0RFBSE3r1744svvtAYxHrOnDkICQnBlClT0KdPH6xduxbW1tYAgOHDh6uHhZk9ezZcXFzg5+eH5557DsXFxW3SDkRERI2RCGOYj8tA6ue9TU5ONnAkBBjH+Zg1axaSk5NRVFRksBh0kZSUhMmTJxvFtHpE9zKG65moIRKJBImJiVrjtZqQZN75I7pP/SDMREREHRGTP9Lw008/ab0z2NBPWFiYoUMlIiIiPTD5Iw2+vr4QQjz05+DBg4YOtcUtW7YMCQkJKC0tRc+ePXHo0CFDh9TqTp8+jaVLl+Lw4cPw8vJSJ/cvvviiVtkRI0bAzs4O5ubm6NevH77//nsDRKy/qqoq+Pr6YsWKFVrrVCoVYmJi4OPjAysrKzg4OKB///64du1au6l3w4YN8PX1hbW1NeRyOXx9fbFy5Ur1+KT1oqOj4efnB3t7e0ilUvj4+GDRokW4c+eOusw///lPbNiwwaB3wdk39S9nbPV2tL7ZIQgTNmHCBDFhwgRDh0H/h+dDd4mJiULfy/idd94Ro0ePFkqlUr3M29tbdOrUSQAQR48e1drmxIkT4vnnn9c7XkNasGCBACCWL1+utW7cuHGiT58+4vz580KlUolbt26JMWPGiMzMzHZTb2hoqNi8ebPIz88XZWVlIikpSVhaWopnnnlGo1xwcLDYvn27KCoqEkqlUiQmJgpLS0sxcuRIjXLx8fEiODhY3L59W+dYhGje9cy+2bxyxlavsfVNACIxMVGvbTuIJN75IzJB69evx8GDB5GUlKQxBSAAbNmyBWZmZggPD0dpaamBImxZX3/9NX788ccG1x08eBCpqalITk7Go48+CgsLC7i6uuLIkSPo379/u6nXysoKb775Jjp37gxbW1tMnDgRY8eOxb/+9S/89ttv6nK2trYIDw+Hk5MT7OzsMGnSJIwbNw6fffaZ+it1AJg3bx4eeeQRPPfcc6ipqdH94PXEvtm8csZYb0fpmx0Jkz8iE3PlyhWsXLkSa9asUc/6cq/AwEBERkYiLy8Pb7/9tgEibFmVlZVYuHChxvzY99q5cycGDx4Mf3//dl1vSkqK1vl0c3MDAI3HZkePHoW5ublGOWdnZwBARUWFxvLVq1fj0qVLjR5DS2PfbF45Y623I/TNjobJH5GJ2bJlC4QQGDNmTKNl1q1bh969e+ODDz7A6dOnH7g/IQRiY2PRt29fSKVSODo6YuzYsfjpp5/UZXbs2AG5XA4bGxscOXIEo0aNgr29Pdzd3XHgwAGN/dXW1uKdd96Bh4cHrK2tMWDAACQmJup9vMuXL1ffdbhfdXU1zp8/j4EDB+q9f2Or917Z2dlwcHBAjx49HlguLy8P1tbW6Nmzp8ZyR0dHBAcHIz4+vk2GE2LfbF45Y6/3Xu2tb3Y0TP6ITMyxY8fQp08f2NjYNFrG2toaH330EczMzDBz5kyUl5c3Wnb16tVYunQpli9fjvz8fJw9exY3btxAUFAQ/vjjDwB3B8WeP38+KisrYWdnh8TEROTk5MDLywszZ87UmCpvyZIl2LhxI+Li4vDbb79h9OjRmDp1qta0iU3x1VdfIScnB1OnTm1w/a1bt1BdXY3//Oc/CAkJgaurK2QyGfr27Yvt27fr/UfFUPUCdz8iycvLw7Zt23D69Gls3boVVlZWjZavqKjAmTNnMHPmzAbLDRo0CHl5efjhhx/0jqmp2Df1L2fs9QLtu292NEz+iExIeXk5rl69Cm9v74eWHT58OObPn49r165hyZIlDZaprKxEbGwsxo8fj+nTp0OhUMDf3x+7du1CYWFhg1MHBgYGwt7eHp07d0ZYWBjKy8uRm5sL4O5XhTt27MC4cePwwgsvwMHBAStWrIClpSUSEhJ0OtbKykpERkZix44djZapf+TUuXNnvPvuu8jKysIff/yBsWPH4q233sI//vEPneo0ZL31unfvDnd3d6xevRobN27E5MmTH1g+JiYGrq6uWLduXYPre/XqBQDIzMzUO6amYN/Uv5yx11uvvfbNjsjkk79Dhw41aVw7/rT+z6FDh3g+dPx52C/P++Xn50MI8cA7K/dat24d+vTpg+3bt+PcuXNa67OysnDnzh0MHTpUY3lAQACsrKyQnp7+wP3X/2++/u7Kzz//jIqKCo0PHqytrdG1a1eNR3VNsWzZMrzxxhvqd4saUj9lX79+/RAYGAgnJycoFAqsWbMGCoVCr3mvDVVvvRs3biA/Px//+Mc/8L//+78YNGgQ8vPzGyybkpKCpKQknDx5Uuvjinr1faX+TllrYd/Uv5yx11uvvfbNjsjC0AEY2rBhwzB//nxDh0GAev5dno+m++abb3R64bmqqgoANOYpfhCZTIaEhAQ8/vjjePXVV7FhwwaN9SUlJQDufqV3PwcHB5SVlTU5NgDqR3grVqzQGlPM1dW1yfs5d+4cMjMzERsb+8By9fssLCzUWG5lZYUePXogJyenyXUast57WVpaonPnzhgxYgR69uyJ3r17IyYmRqufHDx4ELGxsUhLS0O3bt0a3V/9nNX1fae1sG/qV87Y671Xe+2bHZKhBpkxBhxXzrjwfOhO13H+rl69KgCIadOmNbje29tbXL16VWv522+/LQCIQYMGaYyl9t133wkAYtOmTVrbWFlZialTp6r/vXz5cgFAVFZWqpft2bNHABD//e9/hRBC/PLLLwKAiIuLa/IxNWTGjBkCwAN/vvvuOyGEEL169RKDBw/W2oefn5/w8/NrF/U2pq6uTpibm4unn35aY/mWLVtEaGioKCsre+g+kpOTBQCxefNmnerW9Xpm39TsI7r0JWOutzGG7JvgOH8c54/IlLi4uEAikeg8RtratWvh6+uLixcvaizv378/bG1ttV54T09PR3V1NYYMGaJTPd27d4dMJsOlS5d02u5+CQkJWrPSFBQUALj7BaMQQv04cPLkybh48SJ+/fVX9fYVFRW4fv26zsOwGKreoqKiBl/Mz87ORm1tLbp37w7g7tevixcvRmZmJlJTUxu8K3a/+r7SpUsXnWLSFfumZh/RpS8Zc70doW92REz+iEyIjY0NvLy8cPPmTZ22q3/Edv8YXDKZDFFRUUhJScH+/fuhVCqRmZmJ2bNnw9XVFeHh4TrX88orr+DAgQPYsWMHlEolamtrcfPmTfVgsGFhYejSpUuLTeG1YMEC9OjRAzNmzEBubi6KioqwePFiVFZWanxMYMz1yuVynDp1CmfOnIFSqYRKpcLFixfx8ssvQy6XY8GCBQCAy5cvY+PGjdizZw8sLS213iHdvHmz1r7r+0pLj4N4P/ZN/RlzvR2hb3ZETP6ITExoaCiysrJQWVmpXvbJJ5/Ax8cHOTk5CAgIwNy5c7W2GzZsmPoX9b1WrVqFmJgYREdHw9nZGcHBwfD09ERaWhrkcjmAu2Op1b/TOWDAAPz666/Ys2cPoqKiAAAjR45EdnY2ACA+Ph7z58/Hhg0b0KlTJ7i6uiIyMhK3b98GcHeMvPz8fBw5cqRF2sPR0RFffvkl3N3dMXDgQLi5ueHbb7/FsWPHNMbhM+Z6ZTIZHnvsMbz++utwc3ODnZ0dJk6cCE9PT5w/f179kYLQYwiZ7777Dm5ubhgwYIDuB6kj9k39GHO9HaVvdjit/WDZmPEdM+PC86E7feb2zc7OFhYWFmLfvn2tFFXrqq2tFUFBQWLv3r2st5UVFhYKmUym8ztVQuh3PbNvst6mak7fBN/54zt/RKbGx8cH0dHRiI6O1phaqT2ora1FamoqysrKEBYWxnpb2erVqzFw4EBERES0SX3sm6y3qdq6b3Y0TP5a0M8//4y5c+eiX79+sLOzg4WFBRQKBXr37o3Q0FB88803hg4R0dHR8PPzg729PaRSKXx8fLBo0SKNX7SHDx+Gl5eX1jsXVlZWcHFxwZNPPolNmzapH3VQ+7N06VJMnDgRYWFhOr9gb0hpaWk4fPgwTpw40eTx4FivfmJjY3Hp0iUcP34clpaWbVYv+ybrfRhD9c0OxdD3Hg2pJR8zfvDBB8LS0lI88cQT4rPPPhO3b98WVVVVIicnRxw8eFAEBgaK999/v0Xqao7g4GCxfft2UVRUJJRKpUhMTBSWlpZi5MiRWmW9vb2FQqEQQtz9LP/27dviiy++EDNmzBASiUS4urq2yCf/9fjYV3f6PPa918mTJ8XixYtbMCLqCFJTU0VMTIyoqanRex/NvZ7ZN6khLdE3wce+SSY/yHNLOH/+PMLDwxEcHIyTJ0/CwuKvZvXy8oKXlxccHBzULw0bkq2tLcLDw9Vfxk2aNAmHDx9GUlISbty4of7s/n4SiQQODg548skn8eSTTyI0NBSTJ09GaGgofvnlFygUirY8jFZTWVmJp556Cl9//XW7rqOpRowYgREjRhg6DDIyzz//PJ5//nmDxsC+SQ0xhr7ZEfCxbwtYt24damtr8d5772kkfvd69tln8dZbb7VxZNqOHj2qNSSCs7MzgLtjjDXVhAkTMGPGDOTn52PXrl0tGqMh7d27t9HphtpTHURERI1h8tdM1dXV+Pzzz9GpUyf8z//8T5O3E0IgNjYWffv2hVQqhaOjI8aOHasxR+SOHTsgl8thY2ODI0eOYNSoUbC3t4e7uzsOHDigLte3b19IJBKYmZlhyJAh6iRu0aJFUCgUkMlk+OijjxqNJS8vD9bW1ujZs6dOxz5jxgwAwIkTJ3TariU1pR0jIiJgZWWFrl27qpe9+eabkMvlkEgk6im2IiMjERUVhZycHEgkEvj4+GDLli2QyWRwcXHBrFmz4OrqCplMhsDAQI25QZtTBwB89tlnsLe3x7vvvtuq7UVERMR3/pr5jln9lD/Dhg3Tabt33nlHWFlZiX379omSkhKRkZEhBg8eLJydncXvv/+uLlc/7dDnn38uSktLRX5+vggKChJyuVxUV1cLIYSoqakRnp6ewsPDQ+s9iPnz5z9wOqLy8nJhZ2cnIiIitNbd+85fQ5RKpQAgunfvrtOxN0af89HUdpw2bZro0qWLxrabNm0SAERBQYF62QsvvCC8vb01yoWHhwu5XC4uX74sqqqqRFZWlggICBB2dnYiNze3Reo4evSosLOzE9HR0Todf3Pf+SNqLXyHl4wV+M4fh3ppLqVSCaDhycMbU1lZidjYWIwfPx7Tp0+HQqGAv78/du3ahcLCQuzevVtrm8DAQNjb26Nz584ICwtDeXk5cnNzAQDm5uaYN28ecnNzkZKSot6moqIChw8fxquvvtpoLDExMXB1dcW6deuaHH89Ozs7SCQSnSdIbyn6tKO+LCws1HcX/fz8sGPHDpSVlSEhIaFF9h8aGgqlUomVK1e2yP6IiIgaw+SvmeqTPl3el8vKysKdO3e05kcMCAiAlZWVxuPEhlhZWQEAVCqVetnrr78OhUKB+Ph49bL9+/dj7NixsLe3b3A/KSkpSEpKwsmTJ2FnZ9fk+OuVl5dDCNHo/ltbc9uxOYYOHQobGxuNx8tERETtAZO/ZvL09IRMJsMvv/zS5G1KSkoANHy30MHBQa87aba2tnjjjTfw9ddf49tvvwUA7Ny5s9EBMA8ePIj169cjLS0Nnp6eOtcHQH3Mvr6+em3fXK3RjrqQSqXqCc+JiIjaCyZ/zSSVSvHss8+isLAQX331VaPliouL8frrrwO4m5gAaDA5KSkpgbu7u16xREREwNLSEnFxcTh79iy6d+8Ob29vrXJbt27F/v37cebMGXTr1k2vuoC7HykAwKhRo/TeR3O0Vjs2hUqlavU6iIiIWgOTvxawevVqSKVSLFiwQGNC8nv9+OOP6mFg+vfvD1tbW1y4cEGjTHp6OqqrqzFkyBC94nB3d8ekSZNw6NAhrFy5EpGRkRrrhRBYvHgxMjMzkZqaqtN7ivf7/fffERcXB3d39we+U9iadGlHCwsLjcfkzZWWlgYhBIYNG9ZqdRAREbUGJn8tYODAgfj444/x448/IigoCMePH0dpaSlUKhWuXr2KPXv24LXXXlNPQyOTyRAVFYWUlBTs378fSqUSmZmZmD17NlxdXREeHq53LFFRUaipqcHt27fxt7/9TWPd5cuXsXHjRuzZsweWlpZa07dt3rxZa39CCNy5cwd1dXUQQqCgoACJiYl47LHHYG5ujtTUVIO986dLO/r4+KC4uBipqalQqVQoKCjA9evXtfbp5OSEW7du4dq1aygrK1Mnc3V1dbh9+zZqamqQkZGByMhIeHh4qIe7aW4dJ06c4FAvRETUJpj8tZAXXngBP/30E0JCQrBkyRK4u7vD2toagwcPxs6dOxEcHIwpU6aoy69atQoxMTGIjo6Gs7MzgoOD4enpibS0NMjlcgB3x/mLi4sDAAwYMAC//vor9uzZg6ioKADAyJEjtWYNGTRoEEJCQjBv3jytGIUQTTqWTz/9FI888gh+++03VFVVQaFQwNzcHObm5ujduzdiY2MxY8YMZGVl6X2XsqU0pR0BYM6cOQgJCcGUKVPQp08frF27FtbW1gCA4cOH48aNGwCA2bNnw8XFBX5+fnjuuedQXFwMAKiqqoK/vz+sra0RFBSE3r1744svvoBUKm2xOoiIiNqCRDQ1I+iAJk6cCABITk42cCQEGO/5mDVrFpKTk1FUVGToULQkJSVh8uTJTU7sidqKsV7PRBKJBImJiZg0aZKhQzGUZN75I2qC2tpaQ4dARETUIpj8EREREZkQJn9ED7Bs2TIkJCSgtLQUPXv2xKFDhwwdEhERUbNYGDoAImMWExODmJgYQ4dBRETUYnjnj4iIiMiEMPkjIiIiMiFM/oiIiIhMCJM/IiIiIhNi8h983Lx5E0lJSYYOg3D3XADg+dDBN998A4BtRsaH1zOR8TL5GT44dAcREZFpMfUZPkw6+SMi08Rp8YjIhHF6NyIiIiJTwuSPiIiIyIQw+SMiIiIyIUz+iIiIiEwIkz8iIiIiE8Lkj4iIiMiEMPkjIiIiMiFM/oiIiIhMCJM/IiIiIhPC5I+IiIjIhDD5IyIiIjIhTP6IiIiITAiTPyIiIiITwuSPiIiIyIQw+SMiIiIyIUz+iIiIiEwIkz8iIiIiE8Lkj4iIiMiEMPkjIiIiMiFM/oiIiIhMCJM/IiIiIhPC5I+IiIjIhDD5IyIiIjIhTP6IiIiITAiTPyIiIiITwuSPiIiIyIQw+SMiIiIyIUz+iIiIiEwIkz8iIiIiE8Lkj4iIiMiEMPkjIiIiMiFM/oiIiIhMCJM/IiIiIhNiYegAiIha082bN/Hyyy+jtrZWvez27duws7PDk08+qVG2T58+eP/999s4QiKitsXkj4g6NHd3d1y/fh05OTla6/79739r/PuJJ55oq7CIiAyGj32JqMN76aWXYGlp+dByYWFhbRANEZFhMfkjog5v2rRpqKmpeWCZfv36wc/Pr40iIiIyHCZ/RNTheXt7Y8CAAZBIJA2ut7S0xMsvv9zGURERGQaTPyIyCS+99BLMzc0bXFdTU4OJEye2cURERIbB5I+ITMKUKVNQV1entdzMzAzDhg2Dp6dn2wdFRGQATP6IyCS4urriscceg5mZ5q89MzMzvPTSSwaKioio7TH5IyKT8eKLL2otE0Jg/PjxBoiGiMgwmPwRkcmYMGGCxnt/5ubmePrpp+Hi4mLAqIiI2haTPyIyGY6OjnjmmWfUCaAQAtOnTzdwVEREbYvJHxGZlOnTp6s//LC0tMTYsWMNHBERUdti8kdEJmXMmDGQSqUAgNGjR8PW1tbAERERtS0mf0RkUuRyufpuHx/5EpEpkgghhF4bNjJSPhERERG1rgkTJiA5OVmfTZMtmlNxZGQkhg8f3pxdEHUo33zzDeLj45GYmGjoUNqVyZMnt+nvk9raWiQmJmLq1KltUh+1T7yeyVjFxcU1a/tm3flLTEzEpEmTmhUAUUeSlJSEyZMnQ8/LymQZ4vdJVVUVZDJZm9VH7Q+vZzJW9dNR6nvnj+/8EZFJYuJHRKaKyR8RERGRCWHyR0RERGRCmPwRERERmRAmf0REREQmpE2Sv4CAAJibm2PgwIFtUZ2GV155BTKZDBKJBFVVVW1evzHavHkzXFxcIJFIsGvXLvXy48ePQ6FQ4NNPP23V+tuqHl3U1dUhLi4OgYGBhg4FgHG2Ed/UMLcAACAASURBVBERdQxtkvx99913CAkJaYuqtCQkJODtt982SN3G6u2338bXX3+ttbythjMwtmETsrOz8cQTT2DBggWoqKgwdDgAjK+NiIio42jWIM+6aolZQSorK/HUU081mLxQ84SGhqK0tLRF99nQ+WqNevT1ww8/IDo6GrNnz0Z5ebnRJF3G1Ea85oiIOpY2fefP0tKy2fvYu3cv8vPz9dqWU9K1veacr7bwyCOP4PDhw5g2bRqkUqmhwzFKxn4OiYhIN22a/F25cgW+vr6Qy+WwtrZGUFAQzp07p1Hmyy+/hJ+fHxQKBWQyGfz9/XHy5EkAd6eTi4qKQk5ODiQSCXx8fNTb7du3D0OHDoVMJoNcLoenpyfWrl2rXm9mZoZjx45h1KhRUCgUcHV1xYcffqjzMezYsQNyuRw2NjY4cuQIRo0aBXt7e7i7u+PAgQMaZYUQiI2NRd++fSGVSuHo6IixY8fip59+UpfZuHEjbGxsYGdnh/z8fERFRcHNzQ2zZ8+GXC6HmZkZhgwZgi5dusDS0hJyuRyDBw9GUFAQunfvDplMBgcHByxatKjJ7diQc+fOwcPDAxKJBNu2bQNw93xJJJIGf/71r3/pdb4aqqepbaVL27dnDbVRU499y5YtkMlkcHFxwaxZs+Dq6gqZTIbAwECkp6ery0VERMDKygpdu3ZVL3vzzTchl8shkUhQWFgIoPFr7rPPPoO9vT3efffdtmgSIiJqSUJPAERiYmKTyz/11FPCy8tLXL16VahUKvHjjz+KRx99VMhkMvHLL7+oyyUnJ4vVq1eL4uJiUVRUJIYNGyY6deqkXv/CCy8Ib29vjX3HxcUJAOK9994TRUVFori4WLz//vti2rRpQgghli9fLgCIzz//XJSUlIji4mLx3HPPCalUKsrLy3U+9nv3V1paKvLz80VQUJCQy+WiurpaXe6dd94RVlZWYt++faKkpERkZGSIwYMHC2dnZ/H7779r7W/evHli69atYvz48eK///2vWLVqlQAg0tPTRXl5uSgsLBQjR44UAMSxY8dEQUGBKC8vFxEREQKAuHTpUpPbMTs7WwAQO3fuVC+7ceOGACC2bt2qLrNkyRJ1G/3222/C0dFRBAYGitraWr3P1/316NNWD2t7fTz66KPikUceadY+EhMTRTMuK7WG2qipxx4eHi7kcrm4fPmyqKqqEllZWSIgIEDY2dmJ3Nxcdblp06aJLl26aNS7adMmAUAUFBSolzV0Do8ePSrs7OxEdHR0s49VCN1/nxC1hZa6nola2oQJE8SECRP03TypTe/82dnZwdPTExYWFujXrx/27NmDqqoq7N69W11mwoQJWLVqFRwdHeHk5IQxY8agqKgIBQUFDe5TpVJhzZo1CAkJwZIlS+Dk5ARHR0e89tprCAgI0CgbGBgIhUIBR0dHhIWF4c8//8TVq1f1Pp7AwEDY29ujc+fOCAsLQ3l5OXJzcwHcfU8qNjYW48ePx/Tp06FQKODv749du3ahsLBQ45jrrV+/Hm+99RYOHz4MX19f9XI/Pz/Y2NigU6dOmDJlCgDAw8MDzs7OsLGxwfTp0wFA4y6Zru3YEB8fH7z33nuwsbEBAMyZMweVlZX48MMPYWZm1mL16NNWD2r7jq4px25hYaG+i+rn54cdO3agrKwMCQkJLRJDaGgolEolVq5c2SL7IyKittOmH3zcz9/fHwqFAhkZGY2WqX9PsLa2tsH1GRkZKCkpwbPPPqux3NzcHPPmzXvoflUqla5hN8jKykpjf1lZWbhz5w6GDh2qUS4gIABWVlYaj+D0qaempka9rCnH8rB2fJikpCR88skn2LBhA/r06dOi9TS3re5ve1PS1GMfOnQobGxsNP6DQEREpsmgyR9wN1m49w/XsWPHsGnTJmRlZUGpVD70j5pSqQQAODg4tGqcuiopKQEA2Nraaq1zcHBAWVlZq9avazs+SFFREebOnYuAgABERUW1eD2GbitTIZVKdbojS0REHZNBZ/ioqalBcXExPDw8AAC5ubkYN24cunbtivT0dJSWlmLDhg0P3Ee3bt0AQP2CurGoT0YbSlxKSkrg7u7eanXr044PMm/ePJSUlCAhIQHm5uYtXo8h28pUqFQqtiUREQEwcPL3xRdfoK6uDoMHDwYAZGZmQqVSYc6cOfDy8lLPzPEgnp6ecHJywqlTp9oi5Cbr378/bG1tceHCBY3l6enpqK6uxpAhQ1qtbn3asTHHjh3Dxx9/jJUrV6Jfv37q5QsXLmyxegzZVqYiLS0NQggMGzZMvczCwsIkH5UTEZm6Nk3+qqurUVpaipqaGnz//feIiIhAjx49MGPGDABQ3wE8ffo0qqqqkJ2drfW+l5OTE27duoVr166hrKwMZmZmWLZsGc6ePYuIiAjk5eWhrq4OZWVluHz5clsengaZTIaoqCikpKRg//79UCqVyMzMxOzZs+Hq6orw8PBWq7sp7dgUSqUSs2bNwsCBA7FkyRIAQFVVFS5cuIBLly7pdb4aSjYM2VYdVV1dHW7fvo2amhpkZGQgMjISHh4e6msNuPtBT3FxMVJTU6FSqVBQUIDr169r7auhc3jixAkO9UJE1F7p+50wdByaISEhQYSEhAgXFxdhYWEhOnXqJKZMmSKuX7+uUW7x4sXCyclJODg4iIkTJ4pt/5+9O4+Lqt7/B/4aYGAWZtgFAkEEN1K/5XK/Svo1W/xqpimK4tI362aouaCmaS4ZKbmFJkJ+XaK+2kMBNey6lJnXa6s3U9PwZkSLWwYiOxgjvn9/+GOuIyjMsMzAvJ6PB3945nPO530+5zP45pzP+XzWrxcAEhoaKufPn5cTJ05IcHCwqNVq6dOnj3EakPXr10uXLl1EpVKJSqWSBx98UJKSkmTFihWiVqsFgLRr106ys7Nl27Zt4uHhIQAkMDBQvv/++zqfR1JSkmg0GpPjbdy4UfR6vQCQ4OBg49Q1N2/elFWrVkm7du1EqVSKh4eHDB8+XM6dO2c83u3xtW7dWrZu3SoiImvXrjXW06ZNG/nss89k+fLl4ubmJgDE19dX3n//fdmxY4f4+voKAPHw8JDt27fX2o6xsbHGfbRarURGRkpiYqL4+fkJANFoNDJ06FBZvXq1AKjx54knnrDoei1cuLBaPXVtK3Pavq6++uoreeihh8Tf3994bn5+fhIRESH/+Mc/zDqWSMNMDVHTtTDn3GNiYkSpVEpAQIA4OTmJXq+XYcOGSXZ2tkk9eXl50r9/f1GpVBISEiLTpk2TOXPmCAAJCwszTgtT03du//79otPpZOnSpfU61yrm/j4hagqc6oVsVX2nelGIWLaelUKhQGpqKkaNGmXJ7kQtUlpaGkaPHm3VZeImTZqE9PR05OXlWS0Gc/H3CdkiW/g+E9UkKioKAJCenm7J7ulWHfNHRI3D0il9iIio5WPyh1uTI99tGbPbf6Kjo60dKtWC19L+HDp0CPPnz8euXbvQtm1b4zV++umnq5UdMGAAdDodHB0dcf/99+PEiRNWiNhy169fR8eOHbFw4cIGKWdr9a5YsQIdO3aEWq2GVqtFx44dsWjRIuOUXlXi4uIQHh4OvV4PFxcXhIWFYe7cuSgpKTGW+fDDD7FixQqr/iHEvml5OVurt6X1zSYb80dkD6w9Rmj+/Pni7OxsHCuanp5utVjMYenvk8WLF8uQIUOkqKjIuC00NFS8vLwEgOzdu7faPgcOHJCnnnqqXvFay6xZswSALFiwoEHK2Vq9gwcPltWrV0tOTo4UFxdLWlqaKJVKefzxx03K9evXT5KSkiQvL0+KiookNTVVlEqlDBw40KTc2rVrpV+/fpKfn29RPPX5PrNv1q+crdVra32zWS3vRkSNKz4+Hn/++SdEBL/88gtGjhxp7ZAazfLly7Fjxw6kpaVBp9OZfLZu3To4ODggJiYGhYWFVoqwYX355Zf4/vvvG6ycLdbr7OyMF198ET4+PnB1dUVUVBSGDRuGTz75BL///ruxnKurK2JiYuDp6QmdTodRo0Zh+PDh+Oijj3DhwgVjuRkzZuA//uM/8MQTT5isitTY2DfrV84W620pfbMKkz8ianZ++uknLFq0CK+99hpUKlW1zyMiIhAbG4tLly7hpZdeskKEDau8vBxz5szB2rVrG6Scrda7e/fuatczICAAAEwem+3du9dkwnkA8Pb2BgCUlZWZbF+yZAlOnTrVYG1SG/bN+pWz1XpbQt+8HZM/Imp21q1bBxHB0KFD71pm6dKlaN++PTZv3oxDhw7d83gigoSEBHTq1AkuLi7w8PDAsGHDTNZCTk5OhlarhUajwZ49ezBo0CDo9XoEBgZi+/btJserrKzE4sWLERQUBLVaja5duyI1NdXi812wYIHxrkNDlLP1em+XlZUFd3d3BAcH37PcpUuXoFarERISYrLdw8MD/fr1w9q1a5vkrV32zfqVs/V6b9fc+ubtmPwRUbOzb98+dOjQARqN5q5l1Go13n33XTg4OGDixIkoLS29a9klS5Zg/vz5WLBgAXJycnD06FFcuHABffv2xR9//AEAmDJlCmbOnIny8nLodDqkpqYiOzsbbdu2xcSJE00mMJ83bx5WrlyJNWvW4Pfff8eQIUMwduzYaqvY1MUXX3yB7OxsjB07tkHK2Xq9wK3lCC9duoT169fj0KFDSExMhLOz813Ll5WV4fDhw5g4cWKN5R588EFcunQJ3333XYPFeDfsm5aXs/V6gebdN2/H5I+ImpXS0lL88ssvCA0NrbVs7969MXPmTPz666/GVWruVF5ejoSEBERGRmL8+PFwc3NDly5dsGHDBly9ehUbN26stk9ERAT0ej18fHwQHR2N0tJSnD9/HsCttwqTk5MxfPhwjBgxAu7u7li4cCGUSiVSUlLMOtfy8nLExsYiOTm5QcrZer1VWrdujcDAQCxZsgQrV67E6NGj71k+Pj4e/v7+WLp0aY2ft2vXDsCtpS8bE/um5eVsvd4qzbVv3smpPjt/9dVXDRUHUYtQ9Z1IS0uzciQtV05ODkTknndWbrd06VLs3bsXSUlJNf6izszMRElJCXr06GGyvWfPnnB2dq51acSqv+ar7q6cO3cOZWVl6Ny5s7GMWq2Gn5+fyaO6unjllVfwwgsvGMcW1becrddb5cKFCygoKMDJkycxf/58bNy4EYcPH0arVq2qld29ezfS0tJw8ODBai9XVKnqK1V3yhoL+6bl5Wy93irNtW/eqV7J39q1a60yUJHI1tX21yBZ7vr16wAAFxeXOpVXqVRISUlBnz598Nxzz2HFihUmnxcUFAC49Zbendzd3VFcXGxWfFWP8BYuXFhtTjF/f/86H+fzzz/HmTNnkJCQ0CDlbL3e2ymVSvj4+GDAgAEICQlB+/btER8fX+3/mx07diAhIQFHjhzBfffdd9fjqdVqAP/uO42FfdOycrZe7+2aa9+8U70e+6ampkJE+MMf/vz/n6qB09aOo7n9mKPql6U5E6T27t0bs2bNQlZWFl5//XWTz9zd3QGgxv9ICwoKEBgYaFZ8VQPL16xZU+08zXlasmXLFnz66adwcHAwTg5cdexly5ZBoVDg+PHjdS5n6/XeTVhYGBwdHZGZmWmyPTExEdu2bcPhw4fv+Z8rAFRUVAD4d99pLOyb7JuAbfbNO3HMHxE1K61atYJCoTB7jrTXX38dHTt2xMmTJ022d+7cGa6urtX+Mzh27BgqKirQvXt3s+pp3bo1VCoVTp06ZdZ+d0pJSan2H3Rubi6AW28wigh69OhR53K2Xm9eXl6NA/OzsrJQWVmJ1q1bA7j1h9XLL7+MM2fOICMjo8a7Yneq6iu+vr51jscS7Jvsm7baN+/E5I+ImhWNRoO2bdvi4sWLZu1X9Yjtzjm4VCoVZs+ejd27d2Pbtm0oKirCmTNnMHnyZPj7+yMmJsbsep599lls374dycnJKCoqQmVlJS5evGicDDY6Ohq+vr5NvoSXLder1Wpx8OBBHD58GEVFRTAYDDh58iSeeeYZaLVazJo1CwBw9uxZrFy5Eps2bYJSqay2dOPq1aurHbuqr3Tp0qVxTvD/Y9+0nC3X2xL65p2Y/BFRszN48GBkZmaivLzcuO2DDz5AWFgYsrOz0bNnT0ybNq3afr169TL+or7dq6++ivj4eMTFxcHb2xv9+vVDmzZtcOTIEWi1WgC35lJbs2YNAKBr1674+eefsWnTJsyePRsAMHDgQGRlZQG4NR565syZWLFiBby8vODv74/Y2Fjk5+cDuPWoJycnB3v27GnYhqmFLderUqnw0EMP4fnnn0dAQAB0Oh2ioqLQpk0bfP3118aXFMwdJgAA33zzDQICAtC1a1eLz6Gu2DctY8v1tpS+aUIsBK7tS1SNtdf2ba7M/X2SlZUlTk5OsnXr1kaMqvFUVlZK3759ZcuWLay3kV29elVUKpWsXr3a7H0t+T6zb7LeuqpP3+TavkRkd8LCwhAXF4e4uDiTpZWag8rKSmRkZKC4uBjR0dGst5EtWbIEDzzwAKZPn94k9bFvst66auq+eTsmf0TULM2fPx9RUVGIjo42e4C9NR05cgS7du3CgQMH6jwfHOu1TEJCAk6dOoX9+/dDqVQ2Wb3sm6y3Ntbqm0aW3jNEIz723blzp4SEhAgAkx9HR0fx8vKSRx99VHbt2tUodd9uwoQJ4uLiIgCkvLy8zvGOHz++WpnHH39cXF1dxcHBQcLDw+Xbb79tzNDrbdWqVeLj4yMA5O233zZu37dvn+j1evnwww8btf6mqqeh8bGvZerz++Tjjz+Wl19+uYEjouYuIyND4uPj5caNGxYfo77fZ/ZNqklD9M0W+dh3xIgR+PnnnxEaGgo3NzeTV7VTU1Nx6dIljBgxol6LUddFSkoKXnrpJbPi9fLywrZt27Bv3z6TMgcPHkR6ejqGDBmCzMxMdOvWrbHCbhAvvfQSvvzyy2rbxYIBrZZoqnqo+RswYACWL19u7TDIxjz11FOYP39+tTdomxL7JtXEFvqmTSZ/d+Ph4YFHH30Ub731FgDzl9AqLy9HREREY4RmtG7dOjg4OCAmJqZZ3e6vq8GDB6OwsBBDhgxpsGPWdF0aox570RT9vCnqICKixtGskr8qbdq0AfDvpW/qasuWLcjJybGoToVCUadyERERiI2NxaVLl+p015Dqd12ouqZoT14zIqLmq1kmf6dPnwYA9OvXz2T7Z599hvDwcLi5uUGlUqFLly74+OOPAQCxsbGYPXs2srOzoVAoEBYWZtxv69at6NGjB1QqFbRaLdq0aWOyzI6DgwP27duHQYMGwc3NDf7+/njnnXfuGt/SpUvRvn17bN68GYcOHbrnuYgIEhIS0KlTJ7i4uMDDwwPDhg0zWWR75cqV0Gg00Ol0yMnJwezZsxEQEIDJkydDq9XCwcEB3bt3h6+vL5RKJbRaLbp164a+ffsaZ3R3d3fH3Llz69xeNfn8888RFBQEhUKB9evXAwB++umnahNZVv188sknFl2Xmuqpa1slJydDq9VCo9Fgz549GDRoEPR6PQIDA7F9+/Z7Xgtrqct5TZ8+Hc7OzvDz8zNue/HFF6HVaqFQKHD16lUANbfnunXroFKp0KpVK0yaNAn+/v5QqVSIiIgwWRi+PnUAwEcffQS9Xo9ly5Y1ansREVE9WTpaEE0wz19oaKi4ubkZ/11WViYHDhyQ4OBgGTBggJSUlJiUT09PlyVLlsi1a9ckLy9PevXqJV5eXsbPR4wYIaGhoSb7rFmzRgDIG2+8IXl5eXLt2jX53//9Xxk3bpyIiCxYsEAAyKeffioFBQVy7do1eeKJJ8TFxUVKS0urxfvLL7+IiMiXX34pDg4O0qZNG2OcBw4ckKeeespkn8WLF4uzs7Ns3bpVCgoK5PTp09KtWzfx9vaWK1euGMtVxTFjxgxJTEyUyMhI+de//iWvvvqqAJBjx45JaWmpXL16VQYOHCgAZN++fZKbmyulpaUyffp0ASCnTp2qc3tlZWVVe+HjwoULAkASExONZebNm2dsi99//108PDwkIiJCKisrLb4ud9ZjSVt9+umnUlhYKDk5OdK3b1/RarVSUVEhjcmSAeJ1Pa9x48aJr6+vyb6rVq0SAJKbm2vcVlN7xsTEiFarlbNnz8r169clMzNTevbsKTqdTs6fP98gdezdu1d0Op3ExcWZdf4inDeUbBNf4CJb1SJf+LhdYWGh8U6SRqMx3skZN25ctdejR44ciVdffRUeHh7w9PTE0KFDkZeXZ1zT704GgwGvvfYa+vfvj3nz5sHT0xMeHh7461//ip49e5qUjYiIgJubGzw8PBAdHY0///wTv/zyy13j7t27N2bOnIlff/0V8+bNq7FMeXk5EhISEBkZifHjx8PNzQ1dunTBhg0bcPXqVWzcuLHaPsuXL8fUqVOxa9cudOzY0bg9PDwcGo0GXl5eGDNmDAAgKCgI3t7e0Gg0GD9+PACY3E0yt71qEhYWhjfeeMP4mvyUKVNQXl6Od955Bw4ODg1WjyVtFRERAb1eDx8fH0RHR6O0tBTnz5+vc51NwZLzspSTk5Px7mJ4eDiSk5NRXFyMlJSUBjn+4MGDUVRUhEWLFjXI8YiIqHHYfPJ3+9u+BoMBFy9exMyZMzF9+nR07drV+CiqJlXJYWVlZY2fnz59GgUFBfjv//5vk+2Ojo6YMWNGrcc1GAz3jH3p0qXo0KEDkpKS8Pnnn1f7PDMzEyUlJdUWmO7ZsyecnZ1NHsmZw9nZGQBw48YNs2Kurb1qk5aWhg8++ACvvfYaOnTo0KD11LetqtqktmvW1BqrD9RFjx49oNFoTP4gICKils/mk7/bOTk5ISAgAM8++yxWr16Nc+fO4Y033jB+vm/fPjz88MPw8fGBi4tLtTFudyoqKgIAuLu7N0q8VYt1KxQKPPfccyZrPQL/fmHF1dW12r7u7u4oLi5ulLiqmNte95KXl4dp06ahZ8+exvUkG7Iea7dVY7H2ebm4uJh1B5aIiJq/ZpX83a5Lly4AgLNnzwIAzp8/j+HDh8PPzw/Hjh1DYWEhVqxYcc9j3HfffQBwz7uH9dW7d2/MmjULWVlZJi+RAP9OOmv6D76goACBgYGNFpcl7XUvM2bMQEFBAVJSUkzmLmqoeqzZVo3JmudlMBiaddsREZFlmm3y9+233wKA8fHimTNnYDAYMGXKFLRt2xYqlarW6VnatGkDT09PHDx4sFFjff3119GxY0ecPHnSZHvnzp3h6uqK48ePm2w/duwYKioq0L1790aLyZL2upt9+/bh/fffx6JFi3D//fcbt8+ZM6fB6rFmWzUmc87LycmpQR9bHzlyBCKCXr16NVodRERke5pF8ldeXo6bN29CRHD58mWkpKRg4cKF8Pb2xsyZMwHcerkBAA4dOoTr168jKyur2ngpT09PXL58Gb/++iuKi4vh4OCAV155BUePHsX06dNx6dIl3Lx5E8XFxcY7ig2h6vHvnbN5q1QqzJ49G7t378a2bdtQVFSEM2fOYPLkyfD390dMTEyDxXCnurRXXRQVFWHSpEl44IEHjC+2XL9+HcePH8epU6csui41JR/WbKvGZM55hYWF4dq1a8jIyIDBYEBubi5+++23ase8W3vevHkT+fn5uHHjBk6fPo3Y2FgEBQVhwoQJDVLHgQMHONULEVFzYOl7wmjEqRl2794toaGh1db2BSAuLi7Srl07mTJliskUFSIiL7/8snh6eoq7u7tERUXJ+vXrBYCEhobK+fPn5cSJExIcHCxqtVr69OljnEZj/fr10qVLF1GpVKJSqeTBBx+UpKQkWbFihajVagEg7dq1k+zsbNm2bZt4eHgIAAkMDJTvv//eJF5vb2+ZOnVqjec1Z86calO93Lx5U1atWiXt2rUTpVIpHh4eMnz4cDl37pyxzO1xtG7dWrZu3SoiImvXrhWNRiMApE2bNvLZZ5/J8uXLxc3NTQCIr6+vvP/++7Jjxw7x9fUVAOLh4SHbt2+vtb1iY2ON+2i1WomMjJTExETx8/MTAKLRaGTo0KGyevXqGq8TAHniiScsui4LFy6sVk9d2yopKcnYJlXXbOPGjaLX6wWABAcHy48//lif7nlPlkwNUZfzEhHJy8uT/v37i0qlkpCQEJk2bZrMmTNHAEhYWJjx+1BTP4+JiRGlUikBAQHi5OQker1ehg0bJtnZ2Q1Wx/79+0Wn08nSpUvNbrfG/H1CZClO9UK2qr5TvShELFtEVaFQIDU1FaNGjbJkd6IWKS0tDaNHj7a5tYknTZqE9PR05OXlWTuUGvH3CdkiW/0+E0VFRQEA0tPTLdk9vVk89iWi+rN0Ch8iImpZmPwRERER2REmf0Qt3CuvvIKUlBQUFhYiJCQEO3futHZIRERkRU7WDoCIGld8fDzi4+OtHQYREdkI3vkjIiIisiNM/oiIiIjsCJM/IiIiIjvC5I+IiIjIjtTrhY81a9ZYOsEgUYt08eJFAP+egJPqjr9PyNbw+0y26uuvvzZZl91cFq/wwS8DETVXV65cwcmTJzFo0CBrh0JEZJHevXtj1qxZluyabnHyR0TUXHHZLiKyY1zejYiIiMieMPkjIiIisiNM/oiIiIjsCJM/IiIiIjvC5I+IiIjIjjD5IyIiIrIjTP6IiIiI7AiTPyIiIiI7wuSPiIiIyI4w+SMiIiKyI0z+iIiIiOwIkz8iIiIiO8Lkj4iIiMiOMPkjIiIisiNM/oiIiIjsCJM/IiIiIjvC5I+IiIjIjjD5IyIiIrIjTP6IiIiI7AiTPyIiIiI7wuSPiIiIyI4w+SMiIiKyI0z+iIiIiOwIkz8iIiIiO8Lkj4iIiMiOMPkjIiIisiNM/oiIiIjsCJM/IiIiIjvC5I+IiIjIjjD5IyIiIrIjTP6IiIiI7AiTPyIiIiI74mTtAIiIGpPBYEBJSYnJttLSUgBAfn6+yXaFQgF3pC5o0AAAIABJREFUd/cmi42IyBqY/BFRi3bt2jUEBASgsrKy2meenp4m/+7fvz8OHz7cVKEREVkFH/sSUYvm6+uL//qv/4KDw71/3SkUCowZM6aJoiIish4mf0TU4j399NO1lnF0dERkZGQTRENEZF1M/oioxRsxYgScnO4+ysXR0REDBw6El5dXE0ZFRGQdTP6IqMXT6/UYNGjQXRNAEcH48eObOCoiIutg8kdEdmH8+PE1vvQBAM7OznjyySebOCIiIutg8kdEduHJJ5+ERqOptl2pVGL48OHQarVWiIqIqOkx+SMiu6BSqRAZGQmlUmmy3WAwYNy4cVaKioio6TH5IyK7MXbsWBgMBpNter0ejz/+uJUiIiJqekz+iMhuPPbYYyYTOyuVSowZMwbOzs5WjIqIqGkx+SMiu+Hk5IQxY8YYH/0aDAaMHTvWylERETUtJn9EZFfGjBljfPTr6+uLPn36WDkiIqKmxeSPiOxKREQEAgICAAD/8z//U+uyb0RELc3dp7y3ERcvXsSXX35p7TCIqAXp2bMnLl26BC8vL6SlpVk7HCJqQUaNGmXtEGqlEBGxdhD3kpaWhtGjR1s7DCIiIqJa2XhaBQDpNn/nr0ozaEyyYQqFAqmpqc3iLzJbERUVBQBIT0+3ciSNY+fOnRg5cqS1wyAL8PtMtqg53aziYBcisktM/IjIXjH5IyIiIrIjTP6IiIiI7AiTPyIiIiI7wuSPiIiIyI4w+SMiIiKyI0z+7NDq1avRqlUrKBQKbNiwwbh9//79cHNzw9/+9rdGqzsuLg7h4eHQ6/VwcXFBWFgY5s6di5KSknvu9/zzz0On00GhUODUqVONFl9tmqKNiIiIGhOTPzv00ksv1bhqSlPMpXj48GFMnToVv/76K65evYr4+HisXbvWOKfc3WzevBmbNm1q9Phqw/kmiYiouWs2kzxT4xs8eDAKCwsbtQ5XV1fExMTA0dERwK1lcHbt2oW0tDRcuHABrVu3btT666sp2qiuysvL8eijj3L5QyIiMgvv/FGjERGkp6dj48aNxm179+41Jn5VvL29AQBlZWX3PJ5CoWj4IJuxLVu2ICcnx9phEBFRM9Pikr+1a9dCq9XCwcEB3bt3h6+vL5RKJbRaLbp164a+ffuidevWUKlUcHd3x9y5c032/+yzzxAeHg43NzeoVCp06dIFH3/8MQDg3XffhaurKxQKBTw8PJCRkYHjx48jODgYjo6OGDt2rFmxrlu3DiqVCq1atcKkSZPg7+8PlUqFiIgIHDt2zKSsiCAhIQGdOnWCi4sLPDw8MGzYMPzwww8WlbvT559/jqCgICgUCqxfvx4AkJycDK1WC41Ggz179mDQoEHQ6/UIDAzE9u3bTfavrKxEfHw8OnToALVaDW9vb4SEhCA+Pr7WJZguXboEtVqNkJAQk/NYtWoVOnToABcXF7i5uWHOnDm1tmljqk8b1fVaT58+Hc7OzvDz8zNue/HFF6HVaqFQKHD16lUAQGxsLGbPno3s7GwoFAqEhYUBAD766CPo9XosW7asKZqEiIiaI7FxqampYm6Yr776qgCQY8eOSWlpqVy9elUGDhwoAGTfvn2Sm5srpaWlMn36dAEgp06dMu6bnp4uS5YskWvXrkleXp706tVLvLy8jJ+fPXtWNBqNPPPMM8Zt8+fPl82bN1t0fjExMaLVauXs2bNy/fp1yczMlJ49e4pOp5Pz588byy1evFicnZ1l69atUlBQIKdPn5Zu3bqJt7e3XLlyxexyWVlZAkDefvtt47YLFy4IAElMTDRuW7BggQCQTz/9VAoLCyUnJ0f69u0rWq1WKioqjOWWLVsmjo6OsmfPHikrK5Nvv/1WfH195eGHH77n+ZeWlopOp5Pp06ebbF+wYIEoFAp58803JT8/X8rKyiQpKUkAyMmTJ81uZwCSmppq9n53qk8b1fVajxs3Tnx9fU3qXbVqlQCQ3Nxc47YRI0ZIaGioSbm9e/eKTqeTuLi4ep/ryJEjZeTIkfU+DlFDa6jvM1FDsiRfsZK0Fnfn73bh4eHQaDTw8vLCmDFjAABBQUHw9vaGRqPB+PHjAcDkrtjIkSPx6quvwsPDA56enhg6dCjy8vKQm5sLAOjUqRPWrFmD9957D++//z62b9+OP//8E3/9618tjtPJycl4py48PBzJyckoLi5GSkoKgFtjuxISEhAZGYnx48fDzc0NXbp0wYYNG3D16lXjY9W6lrNEREQE9Ho9fHx8EB0djdLSUpw/f974eUZGBrp3746hQ4dCrVajW7dueOqpp3D06FFUVFTc9bjx8fHw9/fH0qVLjdvKy8uxZs0aPPbYY5g1axbc3d2hVqvh6elpcfxNobY2Amq/1vU1ePBgFBUVYdGiRQ1yPCIianns5oUPZ2dnAMCNGzeM25RKJQDAYDDcdb+qMpWVlcZtL7zwAj755BNMmjQJjz32GHbu3Nmgsfbo0QMajcaYlGZmZqKkpAQ9evQwKdezZ084OzsbHxvWtVx9VbXl7e12/fp1qFQqk3KVlZVQKpXVxvhV2b17N9LS0nDw4EHodDrj9p9++gllZWV49NFHGyRea6ipjWpy57UmIiJqbC36zp8l9u3bh4cffhg+Pj5wcXGpNiawyrJly1BSUtJoA+5dXFyMdxsLCgoA3HpT9k7u7u4oLi42q1xjeOKJJ/Dtt99iz549KC8vx/Hjx5GRkYEnn3yyxuRvx44dWL58OY4cOYI2bdqYfHbx4kUAgI+PT6PFa0tuv9ZERESNjcnfbc6fP4/hw4fDz88Px44dQ2FhIVasWFGtnMFgwIwZM5CQkICvvvrK5JFlQzAYDCgoKEBgYCCAW4kbgBqTN0vKNYYlS5bgkUcewYQJE6DX6xEZGYlRo0bVODdfYmIitm3bhsOHD+O+++6r9nnVHcQ///yz0eK1FXdeayIiosZmN4996+LMmTMwGAyYMmUK2rZtC6Dm6UWmTZuGiRMnIjIyEpcuXcLrr7+OAQMGoHfv3g0Sx5EjRyAi6NWrFwCgc+fOcHV1xfHjx03KHTt2DBUVFejevbtZ5RpDZmYmsrOzkZubCyenmruViGDevHnIz89HRkbGXct17twZDg4O+Mc//oHJkyc3Wsy24M5rDdwaF1jb42IiIiJL8c7fbYKCggAAhw4dwvXr15GVlVVtnFxSUhICAgIQGRkJ4NYLC+Hh4Rg3bhyKioosqvfmzZvIz8/HjRs3cPr0acTGxiIoKAgTJkwAcOtO2OzZs7F7925s27YNRUVFOHPmDCZPngx/f3/ExMSYVa4xTJ06FUFBQfdcpu3s2bNYuXIlNm3aBKVSCYVCYfKzevVqALce944YMQI7d+7Eli1bUFRUhNOnT9frhRVbUdu1BoCwsDBcu3YNGRkZMBgMyM3NxW+//VbtWJ6enrh8+TJ+/fVXFBcXw2Aw4MCBA5zqhYiI7s3KrxvXytxXp9euXSsajUYASJs2beSzzz6T5cuXi5ubmwAQX19fef/992XHjh3i6+srAMTDw0O2b98uIiIvv/yyeHp6iru7u0RFRcn69esFgISGhsoDDzwgCoVCPD095csvvxQRkZkzZ4qDg4MAEDc3Nzl+/LhZ5xcTEyNKpVICAgLEyclJ9Hq9DBs2TLKzs03K3bx5U1atWiXt2rUTpVIpHh4eMnz4cDl37pzZ5d58803juWu1WomMjJTExETx8/MTAKLRaGTo0KGSlJRkbMt27dpJdna2bNy4UfR6vQCQ4OBg+fHHH0VE5PDhw+Ll5SUAjD9KpVI6deoku3btEhGRM2fOmHx+58+qVauMMRYXF8vzzz8vXl5e4urqKn369JHFixcLAAkMDJTvvvvOrHZGA0wNUd82quu1zsvLk/79+4tKpZKQkBCZNm2azJkzRwBIWFiYcVqYEydOSHBwsKjVaunTp49cuXJF9u/fLzqdTpYuXVqvcxXhVC9kuxri+0zU0JrTVC8KEdterDQtLQ2jR49usWuqTpo0Cenp6cjLy7N2KPWSnJyMrKwsrFmzxritoqIC8+bNQ3JyMvLz86FWq60Wn0KhQGpqaq0TTjem5natq9ZbTk9Pt3IkRKZs4ftMdKdmlK+kc8yfDbh9Gpnm6MqVK5g+fTpOnTplst3Z2RlBQUEwGAwwGAxWTf5sRXO/1kRE1PxxzF8D++GHH6qNZavpJzo62tqhNhi1Wg2lUoktW7bgjz/+gMFgwOXLl7F582YsXrwY0dHR0Ov11g6TmtihQ4cwf/587Nq1C23btjX2/aeffrpa2QEDBkCn08HR0RH3338/Tpw4YYWILXf9+nV07NgRCxcubJBytlbvihUr0LFjR6jVami1WnTs2BGLFi2qNs45Li4O4eHh0Ov1cHFxQVhYGObOnWsyFvjDDz/EihUrrPaHUEvul3Vpf3PK2Xq9LalfNjnrPnauXTN6hm62+fPni7Ozs3F8Ynp6urVDstjRo0flscceE71eL46OjuLm5iYRERGSlJQkBoPB2uFZfYxQc7zW9Rnzt3jxYhkyZIgUFRUZt4WGhhrHhe7du7faPgcOHJCnnnrK4nitadasWQJAFixY0CDlbK3ewYMHy+rVqyUnJ0eKi4slLS1NlEqlPP744ybl+vXrJ0lJSZKXlydFRUWSmpoqSqVSBg4caFJu7dq10q9fP8nPz7coHku/zy29X9a1/etaztbrtbV+2YzylTSbj7IZNSbZMGsnf82RpcnfG2+8Ie3bt5fy8nKT7aGhofL++++Lg4ODBAQESEFBgcnnzek/2dt98cUXMmDAgFqTq7qWs8V6hw8fXu16RkVFCQC5fPmycdvgwYPlxo0bJuVGjRolAEzWrxYRmT59uvTu3duiPw4t+T7bQ7+sa/ubc51suV5b65fNKF9p2Wv7ElHT+umnn7Bo0SK89tpr1Zb7A26tfxwbG4tLly7hpZdeskKEDau8vBxz5szB2rVrG6Scrda7e/fuatczICAAAEwene3du7faij7e3t4AgLKyMpPtS5YswalTpxqsTe7FXvplXdvfnOtky/U2935pTUz+iKjBrFu3DiKCoUOH3rXM0qVL0b59e2zevBmHDh265/FEBAkJCejUqRNcXFzg4eGBYcOGmayFnJycDK1WC41Ggz179mDQoEHQ6/UIDAzE9u3bTY5XWVmJxYsXIygoCGq1Gl27dkVqaqrF57tgwQK8+OKLtS5FWNdytl7v7bKysuDu7o7g4OB7lrt06RLUajVCQkJMtnt4eKBfv35Yu3Zto78daW/98nZ3a39Ly9l6vc2pX1oTkz8iajD79u1Dhw4doNFo7lpGrVbj3XffhYODAyZOnIjS0tK7ll2yZAnmz5+PBQsWICcnB0ePHsWFCxfQt29f/PHHHwCAKVOmYObMmSgvL4dOp0Nqaiqys7PRtm1bTJw40WS1lHnz5mHlypVYs2YNfv/9dwwZMgRjx46ttipOXXzxxRfIzs7G2LFjG6ScrdcL3FqO8NKlS1i/fj0OHTqExMREODs737V8WVkZDh8+jIkTJ9ZY7sEHH8SlS5fw3XffNViMNbGnfnm72trf3HK2Wm9z7ZdWZc2HznXRjJ6hkw0Dx/yZzdwxfyUlJaJQKGTIkCE1fh4aGiq//PKL8d+zZ88WADJ16lQRqT62qqysTFxdXSU6OtrkOP/85z8FgMTFxRm3LViwQACYjP9JSkoSAPLTTz+JiEh5ebloNBqT45WVlYmLi4tMmTKlzudZtV+PHj3k4sWLIiKSm5tb45i6upaz9XqrVE0O7+XlJW+99ZZUVFTcs/yCBQukffv2Ji9Y3O6dd94RAPJ///d/ZsVhzvfZnvrlnWprf3PL2Wq9ttIvm1G+ktZs5vmrmnCWyFJr1qzhhMVm+Prrr03WHK5NTk4OROSed1dut3TpUuzduxdJSUkYPXp0tc8zMzNRUlKCHj16mGzv2bMnnJ2dqy29eKeqv+ir7rCcO3cOZWVl6Ny5s7GMWq2Gn5+fyeO6unjllVfwwgsvGMcX1becrddb5cKFCygoKMDJkycxf/58bNy4EYcPH0arVq2qld29ezfS0tJw8OBB6HS6Go9X1Veq7pY1Bnvql7erS/ubU86W622O/dLa+NiXiBrE9evXAQAuLi51Kq9SqZCSkgKFQoHnnnsO5eXlJp8XFBQAAFxdXavt6+7ujuLiYrPiq3qMt3DhQpM5N3/77TezBpt//vnnOHPmDJ5//vkGKWfr9d5OqVTCx8cHAwYMwI4dO5CZmYn4+Phq5Xbs2IHly5fjyJEjaNOmzV2PVzXxe1XfaQz20i9vV9f2r2s5W6+3OfZLa2s2d/54x4bqQ6FQYObMmVwOygzm3m2v+oVpziSpvXv3xqxZs7B69Wq8/vrrCAoKMn7m7u4OADX+Z1pQUIDAwECz4qt66WHNmjWIjY01a9/bbdmyBZ9++ikcHKr/7bxs2TIsW7YM33zzTZ3L3XkHydbqvZuwsDA4OjoiMzPTZHtiYiI+/vhjHD58uMYE6XYVFRUA0Kir/9hLv6xS1/Y35zrZcr13ai790tp454+IGkSrVq2gUChQWFho1n6vv/46OnbsiJMnT5ps79y5M1xdXasNej927BgqKirQvXt3s+pp3bo1VCpVtWUIzZWSkgIRMfnJzc0FcOvtWhFBjx496lzO1uvNy8ur8aWRrKwsVFZWonXr1gBuvQH78ssv48yZM8jIyKjTf+xVfcXX17fO8ZjLXvplXdvfkutki/U2935pbUz+iKhBaDQatG3bFhcvXjRrv6rHbHfOw6VSqTB79mzs3r0b27ZtQ1FREc6cOYPJkyfD398fMTExZtfz7LPPYvv27UhOTkZRUREqKytx8eJF/P777wCA6Oho+Pr6NvkyXrZcr1arxcGDB3H48GEUFRXBYDDg5MmTeOaZZ6DVajFr1iwAwNmzZ7Fy5Ups2rQJSqWy2pKWq1evrnbsqr7SpUuXxjlB2E+/rGv7m3OdbLne5t4vrY3JHxE1mMGDByMzM9NknNQHH3yAsLAwZGdno2fPnpg2bVq1/Xr16mX8ZX27V199FfHx8YiLi4O3tzf69euHNm3a4MiRI9BqtQBuzae2Zs0aAEDXrl3x888/Y9OmTZg9ezYAYODAgcjKygIArF27FjNnzsSKFSvg5eUFf39/xMbGIj8/H8Ctxz05OTnYs2dPwzZMLWy5XpVKhYceegjPP/88AgICoNPpEBUVhTZt2uDrr782vqggFsyJ9s033yAgIABdu3a1+Bzqwh76ZV3b35zrZMv1toR+aVWN/T5xfTWjV6fJhoFTvZjNkuXdsrKyxMnJSbZu3dpIUTWuyspK6du3r2zZsoX1NrKrV6+KSqWS1atXm72vud9n9kvWW1f16ZfNKF/h8m5E1HDCwsIQFxeHuLg4k+WVmoPKykpkZGSguLgY0dHRrLeRLVmyBA888ACmT5/e6HWxX7LeumrKfmlNLTL527VrF9q2bWt8pr9o0aJ7lk9ISIBCoYCDgwM6duyIo0ePNlosCoUCSqUSAQEBGDduHP71r381WF13Wr16tXGw84YNG4zb9+/fDzc3N/ztb39rtLrj4uIQHh4OvV4PFxcXhIWFYe7cuSa/eGtqG4VCAWdnZ7Rq1QoPP/wwVq1aZXz0Qc3D/PnzERUVhejoaLMH2VvTkSNHsGvXLhw4cKDOc8KxXsskJCTg1KlT2L9/P5RKZZPUyX7JemtjjX5pNda+91ib+txGDQ0NFQDi5+d31xm/b9y4IcHBwQJAHn300fqEWmssbm5uInJrxvkPP/xQgoKCxNXVVX744YdGqzcrK0sAyNtvv23ctnfvXtHr9fLhhx82Wr39+vWTpKQkycvLk6KiIklNTRWlUikDBw6sVvb2trl586bk5+fL3//+d5kwYYIoFArx9/eXb775pl7xgI99zWbJY9/bffzxx/Lyyy83YETUEmRkZEh8fLzcuHHD4mPU5/vMfkk1aYh+yce+NqR79+64cuUKMjIyavx8165dDT4Lfm20Wi2GDBmCt956CyUlJUhMTGzS+gcPHozCwkIMGTKk0epwdXVFTEwMPD09odPpMGrUKAwfPhwfffQRLly4cNf9FAoF3N3d8fDDDyMlJQVpaWn4448/jDE3V+Xl5YiIiGj2dZhjwIABWL58ubXDIBvz1FNPYf78+dXeom0q7JdUE2v3y6bW4pO/KVOmAADefvvtGj9PSEgwvn3V1P7yl78AAL7//nur1N9QRATp6enYuHGjcdvevXurfYm8vb0BwKxZ60eOHIkJEyYgJyfH5NF1c7Nlyxbk5OQ0+zqIiKj5a/HJ3yOPPIJOnTrh73//O86dO2fy2RdffIGysjIMGDCgxn0/++wzhIeHw83NDSqVCl26dMHHH38MAHj33Xfh6uoKhUIBDw8PZGRk4Pjx4wgODoajo2ONk0/e6caNGwBMlx0SESQkJKBTp05wcXGBh4cHhg0bVm2Nx7qWu9Pnn3+OoKAgKBQKrF+/HsCtKQm0Wi00Gg327NmDQYMGQa/XIzAwENu3bzfZv7KyEvHx8ejQoQPUajW8vb0REhKC+Pj4WlfPuHTpEtRqNUJCQmptm9tNmDABAHDgwAGz9quPurTv9OnT4ezsDD8/P+O2F198EVqtFgqFAlevXgUAxMbGYvbs2cjOzoZCoUBYWBjWrVsHlUqFVq1aYdKkSfD394dKpUJERITJ2qD1qQMAPvroI+j1eixbtqxR24uIiJoR6z52rl19x/z98ssv8tZbbwkAiY2NNfl8+PDhkpKSIsXFxTWO+UtPT5clS5bItWvXJC8vT3r16iVeXl7Gz8+ePSsajUaeeeYZ47b58+fL5s2ba4ylalxbla1btwoAmTNnjnHb4sWLxdnZWbZu3SoFBQVy+vRp6datm3h7e8uVK1fMLlfTmL8LFy4IAElMTDRuW7BggQCQTz/9VAoLCyUnJ0f69u0rWq3WZLzksmXLxNHRUfbs2SNlZWXy7bffiq+vrzz88MN3vQ4iIqWlpaLT6WT69Ol1apvbFRUVCQBp3br1Peu4F5g5Rqiu7Ttu3Djx9fU12XfVqlUCQHJzc43bRowYIaGhoSblYmJiRKvVytmzZ+X69euSmZkpPXv2FJ1OJ+fPn2+QOvbu3Ss6nU7i4uLqfO5V6jvmj6ixmPt9JmoKHPNnY6pm/H7vvfeMk3z+/PPP+Oabb+55h27kyJF49dVX4eHhAU9PTwwdOhR5eXnGpZI6deqENWvW4L333sP777+P7du3488//8Rf//rXe8ZTWlqKXbt24aWXXkKrVq0wY8YMALfGbCUkJCAyMhLjx4+Hm5sbunTpgg0bNuDq1avGx6p1LWeJiIgI6PV6+Pj4IDo6GqWlpTh//rzx84yMDHTv3h1Dhw6FWq1Gt27d8NRTT+Ho0aPG9RBrEh8fD39/fyxdutTsmHQ6HRQKhdkLpluqMdv3Tk5OTsa7i+Hh4UhOTkZxcTFSUlIa5PiDBw9GUVFRrW+8ExGR/bCL5M/NzQ1jx45Ffn4+duzYAeDWItpTpkyBs7NznY9T9er37QuEv/DCCxg5ciQmTZqEtLQ0rFy58q77FxYWQqFQwM3NDTNmzMATTzyBf/7zn8YXTjIzM1FSUlJt3c2ePXvC2dnZ+DiwruXqq6ptDAaDcdv169erzZheWVkJpVJ514Gyu3fvRlpaGj7++GPodDqz4ygtLYWIQK/Xm72vJZqqfWvSo0cPaDSaWh/fExERWcoukj/g3y9+bNiwAQUFBUhPT8ekSZPuuc++ffvw8MMPw8fHBy4uLpg7d26N5ZYtW4aSkpJaB9u7ublBRHDjxg1cvHgR77zzDoKDg42fFxQUAECNC0+7u7sb73zVtVxjeOKJJ/Dtt99iz549KC8vx/Hjx5GRkYEnn3yyxuRvx44dWL58OY4cOYI2bdpYVOePP/4IAOjYsWN9Qq8za7YvcGsMaNXdZSIiooZmN8nfAw88gF69euGf//wnYmJiEBUVBQ8Pj7uWP3/+PIYPHw4/Pz8cO3YMhYWFWLFiRbVyBoMBM2bMQEJCAr766iuLHmtWcXd3B4Aak4uCggIEBgaaVa4xLFmyBI888ggmTJgAvV6PyMhIjBo1Cps2bapWNjExEdu2bcPhw4dx3333WVznRx99BAAYNGiQxccwhzXb12AwNHodRERk35ysHUBTmjJlCr7++mvs3LnTuKD23Zw5cwYGgwFTpkxB27ZtAdyag+5O06ZNw8SJExEZGYlLly7h9ddfx4ABA9C7d2+z4+vcuTNcXV1x/Phxk+3Hjh1DRUUFunfvbla5xpCZmYns7Gzk5ubCyanm7iMimDdvHvLz85GRkXHXcnVx5coVrFmzBoGBgXjuuecsPo45zGlfJycnk8fi9XXkyBGICHr16tVodRARkX2zmzt/ADBq1Ch4e3tj+PDhxoTuboKCggAAhw4dwvXr15GVlVVtrFdSUhICAgIQGRkJ4NZLDeHh4Rg3bhyKiorMjk+lUmH27NnYvXs3tm3bhqKiIpw5cwaTJ0+Gv78/YmJizCrXGKZOnYqgoKB7ro959uxZrFy5Eps2bYJSqay2fNvq1aur7SMiKCkpwc2bNyEiyM3NRWpqKh566CE4OjoiIyOjycb8mdO+YWFhuHbtGjIyMmAwGJCbm4vffvut2jE9PT1x+fJl/PrrryguLjYmczdv3kR+fj5u3LiB06dPIzY2FkFBQcbpbepbx4EDBzjVCxERmbLiq8Z1Ysmr07t37zYu7ebt7S1Tp041fjZ37lz58ssvjf9euHCh+Pn5CQBxcHCQ8PBw+eyzz0RE5OWXXxZPT09xd3eXqKgoWb9+vQCQ0NBQeeCBB0ShUIinp6fxeDNnzhQHBwcBIG5ubnL8+HH54osvpH379gJAAIi/v79ERUXdNfabN2/KqlWrpF27dqJUKsXDw0OGDx8u586dM7vcm2++Kb6+vgJAtFqtREZGSmJiovF8NRrL4lFxAAAgAElEQVSNDB06VJKSkkSj0QgAadeunWRnZ8vGjRtFr9cLAAkODpYff/xRREQOHz4sXl5exvMBIEqlUjp16iS7du0SEZEzZ86YfH7nz6pVq0RE5MMPP5SuXbuKRqMRZ2dnY9spFApxd3eXv/zlLxIXFyd5eXlmXf+awMypIep6HfLy8qR///6iUqkkJCREpk2bJnPmzBEAEhYWZpyy5cSJExIcHCxqtVr69OkjV65ckZiYGFEqlRIQECBOTk6i1+tl2LBhkp2d3WB17N+/X3Q6nSxdutTsNuNUL2SrzP0+EzWF5jTVi0Lkjlc3bUxaWhpGjx5d7Q1Tso7k5GRkZWVhzZo1xm0VFRWYN28ekpOTkZ+fD7VabcUIa6ZQKJCamlrrRNRNadKkSUhPT0deXp61Q6lRVFQUACA9Pd3KkRCZssXvM1EzylfS7WrMH9XPlStXMH36dJw6dcpku7OzM4KCgmAwGGAwGGwy+bNVt08bRERE1BTsaswf1Y9arYZSqcSWLVvwxx9/wGAw4PLly9i8eTMWL16M6OjoJhuXR0RERJZh8kd15ubmhoMHD+L7779H+/btoVarER4ejpSUFCxfvhzvvfeetUNsNl555RWkpKSgsLAQISEh2Llzp7VDIiIiO8HHvmSWvn374pNPPrF2GM1efHw84uPjrR0GERHZId75IyIiIrIjTP6IiIiI7AiTPyIiIiI7wuSPiIiIyI4w+SMiIiKyI81mhQ8iIiIiW2fjaRXQHFb4iIiIQGpqqrXDIKIW5KuvvsLatWv5u4WI7JLN3/kjImpozWgNTiKihpbOMX9EREREdoTJHxEREZEdYfJHREREZEeY/BERERHZESZ/RERERHaEyR8RERGRHWHyR0RERGRHmPwRERER2REmf0RERER2hMkfERERkR1h8kdERERkR5j8EREREdkRJn9EREREdoTJHxEREZEdYfJHREREZEeY/BERERHZESZ/RERERHaEyR8RERGRHWHyR0RERGRHmPwRERER2REmf0RERER2hMkfERERkR1h8kdERERkR5j8EREREdkRJn9EREREdoTJHxEREZEdYfJHREREZEeY/BERERHZESZ/RERERHaEyR8RERGRHWHyR0RERGRHmPwRERER2REnawdARNSYcnNz8cEHH5hsO378OABg48aNJtt1Oh3GjBnTZLEREVmDQkTE2kEQETWWP//8E61atUJJSQkcHR0BAFW/9hQKhbGcwWDAM888g3fffdcaYRIRNZV0PvYlohbNxcUFI0eOhJOTEwwGAwwGA27cuIEbN24Y/20wGAAAY8eOtXK0RESNj8kfEbV4Y8eORUVFxT3LuLu745FHHmmiiIiIrIfJHxG1eP3794ePj89dP1cqlRg/fjycnDgMmohaPiZ/RNTiOTg4YNy4cVAqlTV+bjAY+KIHEdkNJn9EZBfGjBljHNt3p/vuuw+9e/du4oiIiKyDyR8R2YW//OUvCA4Orrbd2dkZzzzzjMmbv0RELRmTPyKyG08//XS1R78VFRV85EtEdoXJHxHZjXHjxlV79BsWFoYuXbpYKSIioqbH5I+I7EbHjh0RHh5ufMSrVCrx7LPPWjkqIqKmxeSPiOzK//zP/xhX+rhx4wYf+RKR3WHyR0R2ZcyYMaisrAQAdOvWDSEhIVaOiIioaTH5IyK7EhQUhP/8z/8EADzzzDNWjoaIqOlxOvu7iIqKsnYIRNRI/vzzTygUChw8eBBHjx61djhE1Ah69+6NWbNmWTsMm8Q7f3exc+dOXLx40dphtDgXL17Ezp07rR1Gs8P+2LACAwPh6+sLlUpl7VCaNX6fyVZ9/fXX+Oqrr6wdhs1SiIhYOwhbpFAokJqailGjRlk7lBYlLS0No0ePBrudedgfG95PP/2EsLAwa4fRrPH7TLaq6uldenq6lSOxSem880dEdomJHxHZKyZ/RERERHaEyR8RERGRHWHyR0RERGRHmPwRERER2REmf43s+eefh06ng0KhwKlTp6wdTouxf/9+uLm54W9/+5u1QyEiImpWmPw1ss2bN2PTpk3WDqPF4dQSRERElmHyR2YpLy9HRESEtcPA4MGDUVhYiCFDhlg7FJtpEyIiorpg8tcEFAqFtUNoMFu2bEFOTo61w7ApbBMiImpOmPw1MBHBqlWr0KFDB7i4uMDNzQ1z5swxKbNy5UpoNBrodDrk5ORg9uzZCAgIwLlz5yAiSEhIQKdOneDi4gIPDw8MGzYMP/zwg3H/devWQaVSoVWrVpg0aRL8/f2hUqkQERGBY8eOVYuntuNNnz4dzs7O8PPzM2578cUXodVqoVAocPXqVQBAbGwsZs+ejezsbCgUCqtNkvv5558jKCgICoUC69evBwAkJydDq9VCo9Fgz549GDRoEPR6PQIDA7F9+3bjvnVtu/q2yUcffQS9Xo9ly5Y1RZMQERHVnVCNAEhqaqrZ+y1YsEAUCoW8+eabkp+fL2VlZZKUlCQA5OTJkyblAMiMGTMkMTFRIiMj5V//+pcsXrxYnJ2dZevWrVJQUCCnT5+Wbt26ibe3t1y5csW4f0xMjGi1Wjl79qxcv35dMjMzpWfPnqLT6eT8+fPGcnU93rhx48TX19fkXFatWiUAJDc317htxIgREhoaana7VElNTZWG6HYXLlwQAJKYmGjcVtWmn376qRQWFkpOTo707dtXtFqtVFRUGMvVte3q0yZ79+4VnU4ncXFx9T5XEcv7I1FjaqjvM1FDGzlypIwcOdLaYdiqNN75a0Dl5eVYs2YNHnvsMcyaNQvu7u5Qq9Xw9PS86z7Lly/H1KlTsWvXLgQHByMhIQGRkZEYP3483Nzc0KVLF2zYsAFXr17Fxo0bTfZ1cnIy3tELDw9HcnIyiouLkZKSYozHnOO1FBEREdDr9fDx8UF0dDRKS0tx/vx5kzK1tV19DR48GEVFRVi0aFGDHI+IiKihMPlrQD/99BPKysrw6KOPWrR/ZmYmSkpK0KNHD5PtPXv2hLOzc7VHunfq0aMHNBqN8ZFufY/XEjg7OwMADAbDPcvd2XZEREQtFZO/BnTx4kUAgI+Pj0X7FxQUAABcXV2rfebu7o7i4uJaj+Hi4oLc3NwGO549ub3tiIiIWiomfw1IpVIBAP7880+L9nd3dweAGpOygoICBAYG3nN/g8FgUq6+x7Mnd7YdERFRS8XkrwF17twZDg4O+Mc//mHx/q6urjh+/LjJ9mPHjqGiogLdu3e/5/5HjhyBiKBXr15mH8/JyanWR6Mt2Z1tB7BNiIioZWLy14B8fHwwYsQI7Ny5E1u2bEFRURFOnz5d5xcrVCoVZs+ejd27d2Pbtm0oKirCmTNnMHnyZPj7+yMmJsak/M2bN5Gfn48bN27g9OnTiI2NRVBQECZMmGD28cLCwnDt2jVkZGTAYDAgNzcXv/32W7UYPT09cfnyZfz6668oLi5utslRbW0H1K9NDhw4wKleiIjINln7fWNbBQun1iguLpbnn39evLy8xNXVVfr06SOLFy8WABIYGCjfffedrFixQtRqtQCQ1q1by9atW43737x5U1atWiXt2rUTpVIpHh4eMnz4cDl37pxJPTExMaJUKiUgIECcnJxEr9fLsGHDJDs726RcXY+Xl5cn/fv3F5VKJSEhITJt2jSZM2eOAJCwsDDjFCgnTpyQ4OBgUavV0qdPH5PpYuqiIaaGSExMFD8/PwEgGo1Ghg4dKklJSaLRaASAtGvXTrKzs2Xjxo2i1+sFgAQHB8uPP/4oInVvu/q0yf79+0Wn08nSpUvrda5VLO2PRI2JU72QreJUL/eUphDhIqk1USgUSE1NxahRo6wdSo0mTZqE9PR05OXlWTsUs6SlpWH06NFWXZu3ObadrfdHsk+28H0mqklUVBQAID093cqR2KR0PvZtxiorK60dQrPFtiMiInvF5I+IiIjIjjD5a4ZeeeUVpKSkoLCwECEhIdi5c6e1Q2o27LHtDh06hPnz52PXrl1o27YtFAoFFAoFnn766WplBwwYAJ1OB0dHR9x///04ceKEFSKuu7i4OISHh0Ov18PFxQVhYWGYO3cuSkpKLCpn6/WuWLECHTt2hFqthlarRceOHbFo0SIUFRWZXe+HH36IFStWWPUuOPsm+6at9s0Wz7pjDm0XOMC+UXCAuGUs7Y+LFy+WIUOGyP9j777DorzS/oF/B5hhhmEogigBFYTY9bWxPyVhiZuN0bAaO7ZkTTFqYhAlsVdUYruAV2NZjSH7ataAZTWrMeZNXNZNLCnqgpgYxa5RitJhaffvD19mM1JkBpgZme/nuvjD85znuc+c5wzcPuWcvLw8fVlAQIB4eHgIADl48GC1fQ4fPiwvvvhig9prLqGhobJx40bJzs6WvLw8SUxMFKVSKYMGDTKpnrXHDQsLk3Xr1klGRobk5+dLUlKSKJVKee6550yKGx8fL6GhoXL//n2T2tOQ7zPHpnH1rD2utY1NvvBRpyT+Fa4Fk7+mweTPNKaMx/fee086dOggxcXFBuUBAQHy8ccfi52dnfj4+EhOTo7B9sfpD2xYWJiUl5cblI0ZM0YA6N/GNqaetccdPnx4tfM5evRoASC3b982KW5ERIT0799fysrKjG6Pqd9njk2OzfrEbcjYZPJXpyTe9iVqhi5duoRFixZh2bJl+pVnfi04OBiRkZG4desW3nnnHQu0sHEcPHgQ9vb2BmWenp4AgKKiIqPrWXvcffv2VTufPj4+AGBw28yYuEuXLsXZs2cRHx9vdHtMwbHJsWmtY9OWMPkjaobWr18PEcHQoUNrrbNixQp06NABH3zwAb788ss6jyciiI2NRefOneHo6Ah3d3cMGzYMP/30k77Opk2boNVq4eTkhAMHDmDw4MFwcXGBr68vdu3aZXC8iooKLF68GG3btoVGo0GPHj2QmJjYsA/9f27dugWNRgN/f/9GqWftcS9evAg3Nze0a9fOpLju7u4IDQ1FfHy8WaZs4djk2KxvXHOPTZtiyeuO1gy87dskeNvXNMaOx/bt20uXLl1q3BYQECBXrlwREZHjx4+LnZ2d+Pn5SUFBgYjUfGtt8eLFolKpZMeOHZKTkyMpKSnSu3dv8fT0NJjoe8GCBQJAvvrqK8nNzZWMjAwJCQkRrVYrpaWl+nrvvPOOODo6yp49e+T+/fsyf/58sbOzk++++67en7EmhYWFotPpJCIiolHqWWvc0tJSuXnzpmzYsEEcHR0NJoo3Je68efMEgJw5c8aodpjyfebY5Ng0Jq6pY5O3fevEZ/5qw+SvaTD5M40x47GgoEAUCoUMGTKkxu2//gMrIhIVFSUAZPr06SJS/Q9sUVGRODs7y9ixYw2O8+233woAiY6O1pdV/YH99bM/GzduFABy6dIlEREpLi4WJycng+MVFRWJo6OjvPnmm/X6jLVZsGCBdOjQweAlgobUs9a4rVq1EgDi4eEh//3f/22QvJgS98MPPxQA8j//8z9GtcPY7zPHJsemsXFNHZtM/urEZ/7qEh4erp96gD+N8xMeHg4AFm/H4/ZjjIyMDIgInJyc6lV/xYoV6NixIzZu3Iivv/662va0tDQUFBSgb9++BuVBQUFQqVQ4depUncdXqVQAoF8H+sKFCygqKkK3bt30dTQaDVq3bm1wq85Y+/btQ1JSEo4cOQKdTtfgetYc98aNG8jIyMBf/vIX/PnPf0avXr2QkZFhctyqsXL37t0GtetRODY5No2Na66xaWscLN0AaxYZGYn+/ftbuhnNyokTJxAfH99oz9DYiqqkuT5KSkoAAI6OjvWqr1arkZCQgKeffhqvvvoqVq9ebbA9JycHAODs7FxtXzc3N+Tn59e7bQBQWFgIAFi4cCEWLlxosM3b29uoY1X55JNPEBsbi+TkZDzxxBMNrmftcZVKJVq2bImBAwfC398fHTp0QExMTLUH4+sbV6PRAPjP2GkqHJscm8bGNdfYtDVM/urQv39/rqXaBOLj49mvRjIm+av6ZWnMBKn9+/fHrFmzsG7dOixfvhxt27bVb3NzcwOAGv+Q5uTkwNfXt95xAKBly5YAgLi4OERGRhq1b002bNiAI0eO4OjRozUmAcbWs/a4DwsMDIS9vT3S0tJMjltaWgrgP2OnqXBsNqyetcd92OM0Nm0Nb/sSNTNeXl5QKBTIzc01ar/ly5ejU6dOOHPmjEF5t27d4OzsjO+//96g/NSpUygtLUWfPn2MitOmTRuo1WqcPXvWqP0eJiKYM2cOUlNTsX///lr/iNS3nrXHzc7Oxvjx46uVX7x4ERUVFWjTpo3JcavGSqtWrRrUxkfh2DStnrXHbQ5j0+ZY5llD6we+8NEk+MKHaYwdjwEBAdKzZ89at/36ofpfO3HihNjb21d7o3LJkiWiVCplx44dkpubKykpKdKrVy/x9vbWv4kpUvND9du2bRMA8uOPP+rLpk2bJiqVSjZu3Ci5ublSXl4uN27c0E8GGx4eLl5eXvLDDz/U+hnPnTsnAGr9Wbt2rVH1rD1ucXGxeHh46N9WLS0tldOnT0u/fv1Eq9VKamqq0XGrLF26VADI2bNna41fE1O+zxybHJvmGJt84aNOfOGDqDkKCwtDWloaiouL9WV//etfERgYiPT0dAQFBeHtt9+utl+/fv0wa9asauVLlixBTEwMoqOj4enpidDQUPj5+SE5ORlarRbAg7nU4uLiAAA9evTA5cuXsW3bNkRFRQEABg0ahIsXLwJ4cOt/5syZWL16NTw8PODt7Y3IyEjcv38fwINbPRkZGThw4ECtn1HqOe9XfetZe1y1Wo2nnnoKr7/+Onx8fKDT6TB69Gj4+fnh5MmT+pcUjIlb5bvvvoOPjw969Ohh9L7G4tg0vp61x20uY9OmWCrttHbglb8mwSt/pjF2PF68eFEcHBweOceWtaqoqJCQkBDZvn074zaxrKwsUavVsm7dOqP3NeX7zLHJuPXVkLHJK3914pU/ouYoMDAQ0dHRiI6ONlha6XFQUVGB/fv3Iz8/H2PHjmXcJrZ06VL07NkTERERZonHscm49WXusWlLmPw1gr1796J9+/bV5mZTqVTw8vLCM888g7Vr1+pvGxCZw7x58zB69GiMHTvW6AfsLSk5ORl79+7F4cOH6z0fHOOaJjY2FmfPnsVnn30GpVJptrgcm4z7KJYam7ZCIcIF82qiUCiQmJho1JQkgYGByMrKQk5ODkQEubm5OHv2LP785z/jz3/+M1q3bo1PP/202oSktiQpKQnh4eFcp9FIpozHKl988QWOHj2KVatWNUHL6HF14MABnD9/HrNnz4a9vb1Jx2jo95ljk2rSGGNz9OjRAIDdu3c3ZtOai9288tdEFAoF3Nzc8MwzzyAhIQFJSUm4e/cuwsLCHqv/6damuLgYwcHBlm6GSczRdmvqn4EDB/KPK1Xz4osvYt68eSb/cW0MHJtUE2sYm80dkz8zGTVqFCZNmoSMjAxs2bLF0s1psO3bt9e6ZI+1M0fbH+f+ISKi5o3JnxlNmjQJAHD48GEAwJo1a+Dk5ASdToeMjAxERUXBx8cHFy5cgIggNjYWnTt3hqOjI9zd3TFs2DCD9SXXr18PtVoNLy8vTJ06Fd7e3lCr1QgODq62pmV9jhcREQGVSoXWrVvry9566y1otVooFApkZWUBeLDsXVRUFNLT06FQKBAYGNhUXWaWtte3HxvaP59//jlcXFywcuXKJu0vIiKiOlnuTWPrBhOmegkICBBXV9dat+fl5QkAadOmjb6sauLRGTNmyIYNG2TEiBHy448/yuLFi0WlUsmOHTskJydHUlJSpHfv3uLp6Sl37tzR7z9lyhTRarVy/vx5KSkpkbS0NAkKChKdTifXr1/X16vv8SZMmCCtWrUyaPfatWsFgGRmZurLRo4cKQEBAUb1j4hpU0OYo+317ceGxDh48KDodDqJjo426vOLcOohsk6cuomsFad6qROnejEnnU4HhUJR4zqUq1atwvTp07F37160a9cOsbGxGDFiBCZOnAhXV1d0794dW7ZsQVZWFrZu3Wqwr4ODg/6qWJcuXbBp0ybk5+cjISEBwIPnz4w5njUxZ9sf1Y8NFRYWhry8PCxatKhRjkdERGQKJn9mVFhYCBGBi4tLnfXS0tJQUFBQ7a3goKAgqFSqard0H9a3b184OTnpb4s29HiWZMm2P9yPREREzQGTPzP6+eefAQCdOnWqs15OTg4A1LjotZubW41XDh/m6OiIzMzMRjuepVi67b/uRyIiouaAyZ8Zff755wCAwYMH11nPzc0NAGpMbHJycuDr61vn/mVlZQb1Gno8S7Jk2x/uRyIiouaAyZ+Z3LlzB3FxcfD19cWrr75aZ91u3brB2dkZ33//vUH5qVOnUFpaij59+tS5f3JyMkQE/fr1M/p4Dg4OKCsrM+ajNSlLtv3hfmyKGERERObG5K+RiQgKCgpQWVkJEUFmZiYSExPx1FNPwd7eHvv373/kM39qtRpRUVHYt28fdu7ciby8PKSmpmLatGnw9vbGlClTDOpXVlbi/v37KC8vR0pKCiIjI9G2bVv91DLGHC8wMBD37t3D/v37UVZWhszMTFy7dq1aG1u0aIHbt2/j6tWryM/Pb7KEyJxtf1Q/NjTG4cOHOdULERFZnkVfNrZiMGJqjU8//VR69OghTk5OolKpxM7OTgCIQqEQNzc3+c1vfiPR0dGSnZ1tsN/q1atFo9Hop3/ZsWOHfltlZaWsXbtWnnzySVEqleLu7i7Dhw+XCxcuGBxjypQpolQqxcfHRxwcHMTFxUWGDRsm6enpBvXqe7zs7GwZMGCAqNVq8ff3l7ffflveffddASCBgYH6aU9Onz4t7dq1E41GI08//bTBlCt1MWVqCHO0vb792JAYn332meh0OlmxYoVRn1+EU72QdeJUL2StONVLnZK4tm8tGrKWqjlNnToVu3fvRnZ2tqWbUi/Wuravtffj4zIeybZY6/eZiGv71olr+zYHFRUVlm5Cs8B+JCIiW8Dkj4iIiMiGMPl7jM2fPx8JCQnIzc2Fv78/9uzZY+kmPZbYj0REZEscLN0AMl1MTAxiYmIs3YzHHvuRiIhsCa/8EREREdkQJn9ERERENoTJHxEREZENYfJHREREZEP4wkcdTpw4YekmNDtVfZqUlGThljx+OB7J2vD7TNbq5s2b8PX1tXQzrBZX+KiFQqGwdBOIiIjIRKNGjeIKHzXbzSt/tWBOTNR8cVkyIrJlfOaPiIiIyIYw+SMiIiKyIUz+iIiIiGwIkz8iIiIiG8Lkj4iIiMiGMPkjIiIisiFM/oiIiIhsCJM/IiIiIhvC5I+IiIjIhjD5IyIiIrIhTP6IiIiIbAiTPyIiIiIbwuSPiIiIyIYw+SMiIiKyIUz+iIiIiGwIkz8iIiIiG8Lkj4iIiMiGMPkjIiIisiFM/oiIiIhsCJM/IiIiIhvC5I+IiIjIhjD5IyIiIrIhTP6IiIiIbAiTPyIiIiIbwuSPiIiIyIYw+SMiIiKyIUz+iIiIiGwIkz8iIiIiG8Lkj4iIiMiGMPkjIiIisiFM/oiIiIhsCJM/IiIiIhvC5I+IiIjIhjhYugFERE3p5s2b+OMf/4iKigp92f3796HT6fDMM88Y1O3YsSP+9Kc/mbmFRETmxeSPiJo1X19fXLt2Denp6dW2/eMf/zD4929/+1tzNYuIyGJ425eImr2XX34ZSqXykfXGjh1rhtYQEVkWkz8iavYmTJiA8vLyOut07doVXbp0MVOLiIgsh8kfETV7AQEB6NGjBxQKRY3blUol/vjHP5q5VURElsHkj4hswssvvwx7e/sat5WXl2P06NFmbhERkWUw+SMimzBu3DhUVlZWK7ezs0O/fv3g5+dn/kYREVkAkz8isgne3t546qmnYGdn+GvPzs4OL7/8soVaRURkfkz+iMhmvPTSS9XKRAQjRoywQGuIiCyDyR8R2YxRo0YZPPdnb2+P3//+9/Dy8rJgq4iIzIvJHxHZDHd3dzz33HP6BFBEMHHiRAu3iojIvJj8EZFNmThxov7FD6VSiWHDhlm4RURE5sXkj4hsytChQ+Ho6AgAGDJkCJydnS3cIiIi82LyR0Q2RavV6q/28ZYvEdkihYiIpRthKaNHj8aePXss3QwiIiIyo8TERIwZM8bSzbCU3Q6WboGl9evXDzNnzrR0MwhAXFwcAPB8GOHEiROIj49HYmKipZvyWKmoqEBiYiLGjx9v6aY0W/w+k7UKDw+3dBMszuaTP19fX1vO/q3K7t27AYDnw0jx8fHsMxMMHz4carXa0s1otvh9JmvF5I/P/BGRjWLiR0S2iskfERERkQ1h8kdERERkQ5j8EREREdkQJn9ERERENoTJXzMRHR2NLl26wMXFBY6OjggMDMTs2bNRUFBQ536vv/46dDodFAoFzp49a7a4Temzzz6Dq6sr/va3v1msDURERNaKyV8zcfToUUyfPh1Xr15FVlYWYmJiEB8fj9GjR9e53wcffIBt27aZPW5TsuF5y4mIiB6JyV8z4ezsjClTpqBFixbQ6XQYM2YMhg8fjs8//xw3btxodnHrEhYWhtzcXAwZMsQi8X+tuLgYwcHBlm4GERGRns1P8txcHDx4sFqZp6cnAKCoqKjOfRUKhUXi2oLt27cjIyPD0s0gIiLS45U/E+zYsQN9+/aFWq2GVquFn58fli9fDuDBLcfY2Fh07twZjo6OcHd3x7Bhw/DTTz/p99+0aRO0Wi2cnJxw4MABDB48GC4uLvD19cWuXbv09Tp37gyFQgE7Ozv06dNHn0zNnj0brq6uUKvV+Oijj2pt561bt6DRaODv768vExGsXbsWHTt2hKOjI1xdXfHuu+82av/UFNdcvv76a7Rt2xYKhQLvv/8+gPr39/r166FWq+Hl5YWpU6fC29sbarUawcHBOHXqlL5eREQEVCoVWrdurS9763YbXSAAACAASURBVK23oNVqoVAokJWVBQCIjIxEVFQU0tPToVAoEBgYCAD4/PPP4eLigpUrV5qjS4iIiAww+TNSfHw8Xn75ZYwaNQq3b9/GzZs3MX/+fFy4cAEAsHTpUsybNw8LFixARkYGjh07hhs3biAkJAR3794FALz55puYOXMmiouLodPpkJiYiPT0dLRv3x6TJ09GWVkZAODcuXPw8/NDmzZt8O2338LJyQkAsGbNGrz22mtYtWoVJk2aVGM7i4qKcPToUUyePBkqlUpfvmjRIsyZMwdTpkzB3bt3cefOHcydO7fR+qe2uOby9NNP4/jx4wZl9e3viIgITJo0CUVFRZgxYwauXr2K06dPo7y8HM8995z+Nvb69eurLVm1ceNGLFu2zKAsPj4eQ4YMQUBAAEQEly5dAvBgXVkAqKysbJI+ICIiqguTPyOUlZVh2bJlGDBgAObOnYsWLVrA3d0dr732GoKCglBcXIzY2FiMGDECEydOhKurK7p3744tW7YgKysLW7durXbM4OBguLi4oGXLlhg7diwKCwtx/fp1AIC9vT1mzJiB69evY9++ffp9ioqKsHfvXrz66qu1tjUmJgbe3t5YsWKFvqy4uBhxcXH4/e9/j1mzZsHNzQ0ajQYtWrRotD6qKa41qau/qzg4OOiv3Hbp0gWbNm1Cfn4+EhISGqUNYWFhyMvLw6JFixrleERERMZg8meElJQU5OTk4Pnnnzcor0rS0tLSUFBQgL59+xpsDwoKgkqlMrh1WJOqK2VVV6KAB1OxuLq6Ij4+Xl+2c+dODBs2DC4uLjUeZ9++fUhKSsKRI0eg0+n05ZcuXUJRURGeffbZ+n1gI9UW11rV1N816du3L5ycnAxu3RMRET2umPwZIS8vDwDg5uZW4/acnBwAD96AfZibmxvy8/ONjuns7Iw33ngDx48fx7fffgsA2Lx5MyIiImqs/8knn2DVqlVITk6Gn5+fwbabN28CAFq2bGl0Ox6lrrjNgaOjIzIzMy3dDCIiogZj8meEJ554AgD0D/Q/rCoprCnJy8nJga+vr0lxIyIioFQqERcXh2PHjqFNmzYICAioVm/Dhg3YuXMnjh49qm/rr6nVagDAv//9b5PaUZtHxX3clZWVNej8ERERWRMmf0bw8/NDixYt8MUXX9S4vVu3bnB2dsb3339vUH7q1CmUlpaiT58+JsX19fXFmDFjsGfPHixatAiRkZEG20UEc+bMQWpqKvbv31/jlceq9tnZ2eEf//iHSe14WH3jPu6Sk5MhIujXr5++zMHB4ZG3i4mIiKwRkz8jODo6Yv78+Th27BgiIiJw69YtVFZWIj8/H+fPn4darUZUVBT27duHnTt3Ii8vD6mpqZg2bRq8vb0xZcoUk2NHRUWhvLwc9+/fx+9+9zuDbefPn8eaNWuwbds2KJVKKBQKg59169YBeHC7d+TIkdizZw+2b9+OvLw8pKSk1PgiSn3UN+7jprKyEvfv30d5eTlSUlIQGRmJtm3bGrxZHRgYiHv37mH//v0oKytDZmYmrl27Vu1YLVq0wO3bt3H16lXk5+ejrKwMhw8f5lQvRERkMUz+jBQVFYX3338fycnJCAwMhFarRWhoKJKTkwEAS5YsQUxMDKKjo+Hp6YnQ0FD4+fkhOTkZWq0WwIN55+Li4gAAPXr0wOXLl7Ft2zZERUUBAAYNGoSLFy8axO3VqxcGDBiAGTNmVGuTMcuZffjhh3jllVcwZ84c+Pj44K233kJISAgAYMiQIUhJSan3saxxGbX3338fQUFBAIA5c+bgxRdfNLq/S0pK0L17d2g0GoSEhKBDhw74+9//DkdHR32dN998EwMGDMC4cePQsWNHLF++HBqNBgDQv39//bQw06ZNg5eXF7p06YIXXngB9+7dM0s/EBER1UYh1vgX3Eyq1p/dvXu3hVtCgHWcj6lTp2L37t3Izs62WBuMkZSUhPDwcKtMxMm2WcP3magmCoUCiYmJ1eZrtSG7eeWP6CFVkzATERE1R0z+yMBPP/1U7dm9mn7Gjh1r6aZSI/jyyy8xb9487N27F+3bt9ef35deeqla3YEDB0Kn08He3h5du3bF6dOnLdDi+ouOjkaXLl3g4uICR0dHBAYGYvbs2SgoKDCpnrXHXb16NTp16gSNRgOtVotOnTph0aJF+imqjIn76aefYvXq1Rb9jxDH5gNff/01nnrqKTg5OcHb2xtz5swxecYGS8UFHsyaEBMTg8DAQKhUKri5uaFbt264evVqrfuUlJSgU6dOWLhwob7MGsZmsyA2bNSoUTJq1ChLN4P+j6XPx7x580SlUgkA8fPzk927d1usLfWVmJgopn6NFy9eLEOGDJG8vDx9WUBAgHh4eAgAOXjwYLV9Dh8+LC+++KLJ7TWn0NBQ2bhxo2RnZ0teXp4kJiaKUqmUQYMGmVTP2uOGhYXJunXrJCMjQ/Lz8yUpKUmUSqU899xzJsWNj4+X0NBQuX//vkntacj3mWPzgXPnzolGo5FFixZJQUGBHD9+XDw9PeWVV155rOKKiAwfPlw6duwoJ0+elLKyMrl9+7YMHTpUUlNTa91n1qxZAkAWLFhgUN7QsQlAEhMTTdq3mUhi8sfkz2rwfBjP1OTvvffekw4dOkhxcbFBeUBAgHz88cdiZ2cnPj4+kpOTY7D9cfoDGxYWJuXl5QZlY8aMEQBy/fp1o+tZe9zhw4dXO5+jR48WAHL79m2T4kZEREj//v2lrKzM6PaY+n3m2PzPOQgPDxd/f3+prKzUl61du1YUCoX8+OOPj03cXbt2iUKhkJSUlHrv880338jAgQNrTP5EGjY2mfxJEm/7EtmYS5cuYdGiRVi2bJl+4u9fCw4ORmRkJG7duoV33nnHAi1sHAcPHoS9vb1BmaenJ4AH62MbW8/a4+7bt6/a+fTx8QEAg9t6xsRdunQpzp49a7C8ZFPi2PzPOSgvL8ehQ4cQGhoKhUKhrzd48GCICA4cOPDYxN28eTN69+6N7t2716t+cXEx3n333TrHnbnHZnPD5I/Ixqxfvx4igqFDh9ZaZ8WKFejQoQM++OADfPnll3UeT0QQGxuLzp07w9HREe7u7hg2bJjBWsibNm2CVquFk5MTDhw4gMGDB8PFxQW+vr7YtWuXwfEqKiqwePFitG3bFhqNBj169EBiYmLDPvT/uXXrFjQaDfz9/RulnrXHvXjxItzc3NCuXTuT4rq7uyM0NBTx8fFmeaOcY/M/5+Dy5csoKChA27ZtDepVre5kzLRcloxbWlqKkydPomfPnvXeZ8GCBXjrrbfqXIrU3GOzuWHyR2RjDh06hI4dO8LJyanWOhqNBh999BHs7OwwefJkFBYW1lp36dKlmDdvHhYsWICMjAwcO3YMN27cQEhICO7evQvgwbyIM2fORHFxMXQ6HRITE5Geno727dtj8uTJBqulzJ07F2vWrEFcXBx++eUXDBkyBOPHj6+2co6xioqKcPToUUyePBkqlarB9aw1bllZGW7duoX3338fX375JTZs2NCguL169cKtW7fwr3/9y+Q21RfH5n/OwZ07dwAAOp3OoK5arYZGo9G339rj3r59G6Wlpfjhhx8wYMAAeHt7Q61Wo3Pnzti4cWO1xO2bb75Beno6xo8f/8hjm3NsNjdM/ohsSGFhIa5cuVLj2tAP69+/P2bOnImrV69i7ty5NdYpLi5GbGwsRowYgYkTJ8LV1RXdu3fHli1bkJWVVePqMcHBwXBxcUHLli0xduxYFBYW4vr16wAevN23adMmDB8+HCNHjoSbmxsWLlwIpVKJhISEBn32mJgYeHt7Y8WKFY1Sz1rjtmnTBr6+vli6dCnWrFmD8PDwBsV98sknAQCpqakNatejcGwanoOqN2sfvk0LAEqlEsXFxQ2Kaa64VY8ctGzZEitXrkRaWhru3r2LYcOGYfr06fjLX/6ir1tcXIzIyEhs2rSpXsc219hsjhws3QBLu3nzJpKSkizdDMKDcwGA58MIJ06cMKp+RkYGRKTOKyu/tmLFChw8eBAbN26sMYlIS0tDQUEB+vbta1AeFBQElUqFU6dO1Xn8qqsNVVdXLly4gKKiInTr1k1fR6PRoHXr1ga36oy1b98+JCUl4Ysvvqh2RcOUetYc98aNG8jJycGZM2cwb948bN26FUePHoWXl5dJcavGSmNcaaoLx6bhOah65rG8vLzaPqWlpfoVhaw9btXKSF27dkVwcLC+fNmyZdi8eTO2bt2KCRMmAADmz5+PN954Q/+s6qOYa2w2Rzaf/J08efKR/zMm8+L5aDolJSUAYLBUXV3UajUSEhLw9NNP49VXX8Xq1asNtufk5AAAnJ2dq+3r5uaG/Px8o9pXdQtv4cKFBnN7AYC3t7dRx6ryySefIDY2FsnJyXjiiScaXM/a4yqVSrRs2RIDBw6Ev78/OnTogJiYmGoPxtc3btUf+6qx01Q4Ng3PQevWrQGg2jyNRUVFKCkpMTmmueNW1c/KyjIoV6lUaNeuHdLT0wE8mFcwNTUVsbGx9T62ucZmc2Tzt31HjRoFEeGPFfyMGjWK58PIH2MfNq/6ZWnMBKn9+/fHrFmzcPHiRSxfvtxgm5ubGwDU+Ic0JycHvr6+RrWv6gHvuLi4ap/V2KucALBhwwbs3LkTR48erTPBqW89a4/7sMDAQNjb2yMtLc3kuKWlpQDQ4CtNj8Kxacjf3x86nQ7Xrl0zKL906RKAB+uUm8LccZ2dnfHkk0/i/Pnz1baVl5fD1dUVALB9+3Z89dVXsLOz00/oXdXnK1euhEKhqPZspbnGZnNk88kfkS3x8vKCQqFAbm6uUfstX74cnTp1wpkzZwzKu3XrBmdn52q/lE+dOoXS0lL06dPHqDht2rSBWq3G2bNnjdrvYSKCOXPmIDU1Ffv376/x6o8x9aw9bnZ2do0PyF+8eBEVFRVo06aNyXGrxkqrVq0a1MZH4dg05ODggBdeeAHHjh1DZWWlvvzw4cNQKBR1vhFtTXGBB3dzzpw5g8uXL+vLioqKcO3aNf30LwkJCdWS6szMTAAP3v4VkWq38M01NpslsWGcVNi68HwYz5RJngMCAqRnz561brty5UqN206cOCH29vbVJtJdsmSJKJVK2bFjh+Tm5kpKSor06tVLvL29paCgQF9vwYIFAsBg8t5t27YJAIOJY6dNmyYqlUo2btwoubm5Ul5eLjdu3NBPVBweHi5eXl7yww8/1PoZz507JwBq/Vm7dq1R9aw9bnFxsXh4eMhXX30lubm5UlpaKqdPn5Z+/fqJVqvVr6JgTNwqS5cuFQBy9uzZWuPXxJTvM8em4Tk4d+6cqNVqWbhwoX6lDQ8Pj2orbVhzXBGRe/fuiZ+fn4SEhMi1a9ckKytLpk+fLnZ2dnLmzJla98vMzKx1kmcR08cmOMkzJ3kmsjVhYWFIS0szeGvvr3/9KwIDA5Geno6goCC8/fbb1fbr168fZs2aVa18yZIliImJQXR0NDw9PREaGgo/Pz8kJydDq9UCeDCXWlxcHIAHt40uX76Mbdu2ISoqCgAwaNAgXLx4EQAQHx+PmTNnYvXq1fDw8IC3tzciIyNx//59AA9u9WRkZNQ52axI/eb9qm89a4+rVqvx1FNP4fXXX4ePjw90Oh1Gjx4NPz8/nDx5Uv+SgjFxq3z33Xfw8fEx+TajMTg2DXXt2hVHjhzBF198AQ8PD4wcORKvvvoqNm/ebFDPmuMCD+bk++c//wlfX1/07NkTPj4++Pbbb3Ho0CGj5v97mDnHZrNjwczT4nilybrwfBjPlCt/Fy9eFAcHB9mxY0cTtappVVRUSEhIiGzfvp1xm1hWVpao1WpZt26d0fua8n3m2GTc+mrI2ASv/PHKH5GtCQwMRHR0NKKjow2W/XocVFRUYP/+/cjPz8fYsWMZt4ktXboUPXv2REREhFnicWwybn2Ze2w2N0z+iGzQvHnzMHr0aIwdO9boB+wtKTk5GXv37sXhw4frPR8c45omNjYWZ8+exWeffQalUmm2uBybjPsolhqbzQmTv0Z04cIFvP322+jatSt0Oh0cHBzg6uqKDh06ICwszKTpABpbdHQ0unTpAhcXFzg6OiIwMBCzZ882+F/23r170b59e/3r9lU/KpUKXl5eeOaZZ7B27Vr9cy70eFq5ciUiIiLw3nvvWbop9fbss8/i448/1s9FxrhN48CBA/j3v/+N5ORkuLu7mzU2wLHJuLWz9NhsLpj8NZLt27eje/fuSElJQWxsLG7cuIHCwkKcOXMGy5cvR05OjlUsQXP06FFMnz4dV69eRVZWln7y19GjR+vrjBw5EpcvX0ZAQABcXV0hIqisrERGRgaSkpLg7++POXPmoGvXrg1e05Isa+DAgVi1apWlm0FW5sUXX8S8efNqXOLLXDg2qSbWMDabA5tf4aMxnDx5ElOmTEFoaCiOHDkCB4f/dGv79u3Rvn17uLm56d8YsyRnZ2dMmTJF/8UZM2YM9u7di6SkJNy4cUM/H9jDFAoF3Nzc8Mwzz+CZZ55BWFgYwsPDERYWhp9//lk/Uefjrri4GM8++yyOHz/+WMcgIiKqDa/8NYIVK1agoqIC7733nkHi92vPP/88pk+fbuaWVXfw4MFq/2Py9PQE8GDSzfoaNWoUJk2ahIyMDGzZsqVR22hJ27dvR0ZGxmMfg4iIqDZM/hqotLQUX331FTw8PPCb3/ym3vuJCGJjY9G5c2c4OjrC3d0dw4YNM1ggfNOmTdBqtXBycsKBAwcwePBguLi4wNfXF7t27dLX69y5MxQKBezs7NCnTx99Ejd79my4urpCrVbjo48+qrUtt27dgkajgb+/v1GffdKkSQAezPxuKfXpx4iICKhUKoNnU9566y1otVooFAr9mpORkZGIiopCeno6FAoFAgMDsX79eqjVanh5eWHq1Knw9vaGWq1GcHCwwcLwDYkBAJ9//jlcXFywcuXKJu0vIiIizvPXwHnlfv75ZwEg/fr1M2q/xYsXi0qlkh07dkhOTo6kpKRI7969xdPTU+7cuaOvVzXzfNXM/RkZGRISEiJarVZKS0tFRKS8vFz8/Pykbdu2Ul5ebhBn5syZEhcXV2s7CgsLRafTSURERLVtAQEB4urqWuu+eXl5AkDatGlj1GevjSnno779OGHCBGnVqpXBvmvXrhUAkpmZqS8bOXKkBAQEGNSbMmWKaLVaOX/+vJSUlEhaWpoEBQWJTqeT69evN0qMgwcPik6nk+joaKM+vynz/BGZA+ftJGsFzvPHef4aKi8vDwCMWpuzuLgYsbGxGDFiBCZOnAhXV1d0794dW7ZsQVZWFrZu3Vptn+DgYLi4uKBly5YYO3YsCgsLcf36dQCAvb09ZsyYgevXr2Pfvn36fYqKirB37168+uqrtbYlJiYG3t7eWLFiRb3bX0Wn00GhUNS4cLo5mNKPpnJwcNBfXezSpQs2bdqE/Px8JCQkNMrxw8LCkJeXh0WLFjXK8YiIiGrD5K+BqpI+Y56XS0tLQ0FBQbVFqoOCgqBSqQxuJ9ZEpVIBAMrKyvRlr7/+OlxdXREfH68v27lzJ4YNGwYXF5caj7Nv3z4kJSXhyJEj0Ol09W5/lcLCQohIrcdvag3tx4bo27cvnJycDG4vExERPQ6Y/DWQn58f1Go1fv7553rvk5OTA6Dmq4Vubm4mXUlzdnbGG2+8gePHj+Pbb78FAGzevLnW2c8/+eQTrFq1CsnJyfDz8zM6HgD9Z+7UqZNJ+zdUU/SjMRwdHZGZmdmkMYiIiBobk78GcnR0xPPPP4+srCx88803tda7d+8eXn/9dQAPEhMANSYnOTk58PX1NaktERERUCqViIuLw7Fjx9CmTRsEBARUq7dhwwbs3LkTR48exRNPPGFSLODBSwoAMHjwYJOP0RBN1Y/1UVZW1uQxiIiImgKTv0awdOlSODo6YtasWSguLq6xzrlz5/TTwHTr1g3Ozs7VJkg+deoUSktL0adPH5Pa4evrizFjxmDPnj1YtGgRIiMjDbaLCObMmYPU1FTs37/fqOcUH3bnzh3ExcXB19e3zmcKm5Ix/ejg4GBwm7yhkpOTISLo169fk8UgIiJqCkz+GkHPnj3x8ccf49y5cwgJCcFnn32G3NxclJWV4cqVK9i2bRtee+01/RqEarUaUVFR2LdvH3bu3Im8vDykpqZi2rRp8Pb2xpQpU0xuS1RUFMrLy3H//n387ne/M9h2/vx5rFmzBtu2bYNSqay2fNu6deuqHU9EUFBQgMrKSogIMjMzkZiYiKeeegr29vbYv3+/xZ75M6YfAwMDce/ePezfvx9lZWXIzMzEtWvXqh2zRYsWuH37Nq5evYr8/Hx9MldZWYn79++jvLwcKSkpiIyMRNu2bfXT3TQ0xuHDhznVCxERmQWTv0YycuRI/PTTTxgwYADmzp0LX19faDQa9O7dG5s3b0ZoaCjGjRunr79kyRLExMQgOjoanp6eCA0NhZ+fH5KTk6HVagE8mOcvLi4OANCjRw9cvnwZ27ZtQ1RUFABg0KBB1VYN6dWrFwYMGIAZM2ZUa6OI1Ouz/O1vf8N//dd/4ZdffkFJSQlcXV1hb28Pe3t7dOjQAbGxsZg0aRLS0tJMvkrZWOrTjwDw5ptvYsCAARg3bhw6duyI5cuXQ6PRAAD69++PGzduAACmTZsGLy8vdOnSBS+88ALu3bsHACgpKUH37t2h0WgQEhKCDh064O9//zscHR0bLQYREZE5KKS+GUEzVLWe7e7duy3cEgKs93xMnToVu3fvRnZ2tqWbUk1SUhLCw8PrndgTmYu1fp+JFAoFEhMTMWbMGEs3xVJ288ofUT1UVFRYuglERESNgskfERERkQ1h8kdUh/nz5yMhIQG5ubnw9/fHnj17LN0kIiKiBnGwdAOIrFlMTAxiYmIs3QwiIqJGwyt/RERERDaEyR8RERGRDWHyR0RERGRDmPwRERER2RCbf+Hj5MmT+slIybJOnjwJADwfRrh58yYA9hlZH36fiayXTa/wERsbixMnTli6GURkZnfu3MGZM2cwePBgSzeFiCxg1qxZ6N+/v6WbYSm7bTr5IyLbxGXxiMiGcXk3IiIiIlvC5I+IiIjIhjD5IyIiIrIhTP6IiIiIbAiTPyIiIiIbwuSPiIiIyIYw+SMiIiKyIUz+iIiIiGwIkz8iIiIiG8Lkj4iIiMiGMPkjIiIisiFM/oiIiIhsCJM/IiIiIhvC5I+IiIjIhjD5IyIiIrIhTP6IiIiIbAiTPyIiIiIbwuSPiIiIyIYw+SMiIiKyIUz+iIiIiGwIkz8iIiIiG8Lkj4iIiMiGMPkjIiIisiFM/oiIiIhsCJM/IiIiIhvC5I+IiIjIhjD5IyIiIrIhTP6IiIiIbAiTPyIiIiIbwuSPiIiIyIYw+SMiIiKyIUz+iIiIiGyIg6UbQETUlMrKylBQUGBQVlhYCAC4f/++QblCoYCbm5vZ2kZEZAlM/oioWbt37x58fHxQUVFRbVuLFi0M/j1gwAAcPXrUXE0jIrII3vYlomatVatW+O1vfws7u7p/3SkUCowbN85MrSIishwmf0TU7L300kuPrGNvb48RI0aYoTVERJbF5I+Imr2RI0fCwaH2p1zs7e0xaNAgeHh4mLFVRESWweSPiJo9FxcXDB48uNYEUEQwceJEM7eKiMgymPwRkU2YOHFijS99AIBKpcIf/vAHM7eIiMgymPwRkU34wx/+ACcnp2rlSqUSw4cPh1artUCriIjMj8kfEdkEtVqNESNGQKlUGpSXlZVhwoQJFmoVEZH5MfkjIpsxfvx4lJWVGZS5uLjgueees1CLiIjMj8kfEdmM3//+9wYTOyuVSowbNw4qlcqCrSIiMi8mf0RkMxwcHDBu3Dj9rd+ysjKMHz/ewq0iIjIvJn9EZFPGjRunv/XbqlUrPP300xZuERGReTH5IyKbEhwcDB8fHwDAyy+//Mhl34iImpvap7x/hKSkpMZsBxGR2QQFBeHWrVvw8PDg7zIieiy1adMG/fv3N2lfhYiISTsqFCYFJCIiIqKGGTVqFHbv3m3KrrtNvvIHAImJiRgzZkxDDkHUrCQlJSE8PBwm/p/KZikUCrP/PtmzZw9GjRpltnj0+OH3mazV6NGjG7Q/H3YhIpvExI+IbBWTPyIiIiIbwuSPiIiIyIYw+SMiIiKyIUz+iIiIiGwIkz8iIiIiG2KW5C8oKAj29vbo2bOnOcIZeOWVV6BWq6FQKFBSUmL2+NZo3bp18PLygkKhwJYtW/Tln332GVxdXfG3v/2tSeObK059REdHo0uXLnBxcYGjoyMCAwMxe/ZsFBQUWLRd1tRHRETUvJgl+fvuu+8wYMAAc4SqJiEhAe+8845FYlurd955B8ePH69Wbq65rKxpzqyjR49i+vTpuHr1KrKyshATE4P4+PgGz6HUUNbUR0RE1Lw0aJJnYzXGqiDFxcV49tlna0xeqGHCwsKQm5vbqMes6Xw1RRxTOTs7Y8qUKbC3twcAjBkzBnv37kVSUhJu3LiBNm3aWKRd1tRH/M4RETUvZk3+lEplg4+xfft2ZGRkmLQvl6Qzv4acL3M4ePBgtTJPT08AQFFRkbmbY5Ws/RwSEZFxzPrCx6VLl9CpUydotVpoNBqEhITg66+/Nqjzz3/+E126dIGrqyvUajW6d++OI0eOAAAiIyMRFRWF9PR0KBQKBAYG6vfbsWMH+vbtC7VaDa1WCz8/Pyxfvly/3c7ODocOHcLgwYPh6uoKb29vfPjhh0Z/hk2bNkGr1cLJyQkHDhzA4MGD4eLiAl9fX+zatcugroggNjYWnTt3hqOjI9zd3TFs2DD89NNP+jpr1qyBk5MTdDodMjIyEBUVBR8fH0ybNg1arRZ2dnbo06cPWrVqBaVSCa1Wi969eyMkJARt2rSBWq2Gm5sbZs+eXe9+rMnXX3+Ntm3bQqFQ4P333wfwBMPzJgAAIABJREFU4HwpFIoaf/73f//XpPNVU5z69pUxfd8Qt27dgkajgb+/f6Md0xg19VF9P/v69euhVqvh5eWFqVOnwtvbG2q1GsHBwTh16pS+XkREBFQqFVq3bq0ve+utt6DVaqFQKJCVlQWg9u/c559/DhcXF6xcudIcXUJERI1JTARAEhMT613/2Weflfbt28uVK1ekrKxMzp07J//v//0/UavV8vPPP+vr7d69W5YuXSr37t2T7Oxs6devn3h4eOi3jxw5UgICAgyOHRcXJwDkvffek+zsbLl375786U9/kgkTJoiIyIIFCwSAfPXVV5KTkyP37t2TF154QRwdHaWwsNDoz/7r4+Xm5kpGRoaEhISIVquV0tJSfb3FixeLSqWSHTt2SE5OjqSkpEjv3r3F09NT7ty5U+14M2bMkA0bNsiIESPkxx9/lCVLlggAOXXqlBQWFkpWVpYMGjRIAMihQ4ckMzNTCgsLJSIiQgDI2bNn692PFy9eFACyefNmfdmNGzcEgGzYsEFfZ+7cufo++uWXX8Td3V2Cg4OloqLC5PP1cBxT+upRfW+qwsJC0el0EhERYdL+iYmJ0oCvlV5NfVTfzz5lyhTRarVy/vx5KSkpkbS0NAkKChKdTifXr1/X15swYYK0atXKIO7atWsFgGRmZurLajqHBw8eFJ1OJ9HR0Q3+rCLG/z4hMofG+j4TNbZRo0bJqFGjTN09yaxX/nQ6Hfz8/ODg4ICuXbti27ZtKCkpwdatW/V1Ro0ahSVLlsDd3R0tWrTA0KFDkZ2djczMzBqPWVZWhmXLlmHAgAGYO3cuWrRoAXd3d7z22msICgoyqBscHAxXV1e4u7tj7Nix+Pe//40rV66Y/HmCg4Ph4uKCli1bYuzYsSgsLMT169cBPHhOKjY2FiNGjMDEiRPh6uqK7t27Y8uWLcjKyjL4zFVWrVqF6dOnY+/evejUqZO+vEuXLnBycoKHhwfGjRsHAGjbti08PT3h5OSEiRMnAoDBVTJj+7EmgYGBeO+99+Dk5AQAePPNN1FcXIwPP/wQdnZ2jRbHlL6qq+8bIiYmBt7e3lixYkWDj9VU6vPZHRwc9FdRu3Tpgk2bNiE/Px8JCQmN0oawsDDk5eVh0aJFjXI8IiIyH7M+8/ew7t27w9XVFSkpKbXWqXpOsKKiosbtKSkpyMnJwfPPP29Qbm9vjxkzZjzyuGVlZcY2u0YqlcrgeGlpaSgoKEDfvn0N6gUFBUGlUhncgjMlTnl5ub6sPp/lUf34KElJSfjrX/+K1atXo2PHjo0ap6F99XDfm2rfvn1ISkrCF198AZ1O16BjmUt9P3vfvn3h5ORk8B8EIiKyTRZN/oAHycKv/3AdOnQIa9euRVpaGvLy8h75Ry0vLw8A4Obm1qTtNFZOTg6AB2+TPszNzQ35+flNGt/YfqxLdnY23n77bQQFBSEqKqrR41i6rwDgk08+QWxsLJKTk/HEE080eTxLcHR0NOqKLBERNU8WXeGjvLwc9+7dQ9u2bQEA169fx/Dhw9G6dWucOnUKubm5WL16dZ3HqPpDXfWAurWoSkZrSlxycnLg6+vbZLFN6ce6zJgxAzk5OUhISNBPidKYcSzZVwCwYcMG7Ny5E0ePHm22iV9ZWZlZ+pKIiKyfRZO/v//976isrETv3r0BAKmpqSgrK8Obb76J9u3b61fmqIufnx9atGiBL774whxNrrdu3brB2dkZ33//vUH5qVOnUFpaij59+jRZbFP6sTaHDh3Cxx9/jEWLFqFr16768nfffbfR4liqr0QEc+bMQWpqKvbv31/jlcfmIjk5GSKCfv366cscHBwa7bEHIiJ6fJg1+SstLUVubi7Ky8tx+vRpREREoF27dpg0aRIA6K8AfvnllygpKcHFixerPe/VokUL3L59G1evXkV+fj7s7Owwf/58HDt2DBEREbh16xYqKyuRn5+P8+fPm/PjGVCr1YiKisK+ffuwc+dO5OXlITU1FdOmTYO3tzemTJnSZLHr04/1kZeXh6lTp6Jnz56YO3cuAKCkpATff/89zp49a9L5qinZsFRfnT9/HmvWrMG2bdugVCqrTWezbt26JolrDpWVlbh//z7Ky8uRkpKCyMhItG3bVv9dAx680HPv3j3s378fZWVlyMzMxLVr16odq6ZzePjwYU71QkT0uDL1PWEYOTVDQkKCDBgwQLy8vMTBwUE8PDxk3Lhxcu3aNYN6c+bMkRYtWoibm5uMHj1a3n//fQEgAQEBcv36dTl9+rS0a9dONBqNPP300/ppQN5//33p3r27qNVqUavV0qtXL9m4caOsXr1aNBqNAJAnn3xS0tPTZefOneLu7i4AxNfXV86dO1fvz7Fx40ZxcnIyON7WrVvFxcVFAEi7du30U9dUVlbK2rVr5cknnxSlUinu7u4yfPhwuXDhgv54v25fmzZtZMeOHSIiEh8fr4/j5+cn//znP2XVqlXi6uoqAKRVq1by8ccfyyeffCKtWrUSAOLu7i67du16ZD9GRkbq99FqtTJixAjZsGGDtG7dWgCIk5OTDB06VNatWycAavx54YUXTDpfCxcurBanvn1lTN/XR2pqaq2fD4CsXbu23seq0hhTQ9R0Loz57FOmTBGlUik+Pj7i4OAgLi4uMmzYMElPTzeIk52dLQMGDBC1Wi3+/v7y9ttvy7vvvisAJDAwUD8tTE3fuc8++0x0Op2sWLGiQZ+1irG/T4jMgVO9kLVq6FQvChHTFhFVKBRITEzEmDFjTNmdqFlKSkpCeHi4RdfmnTp1Knbv3o3s7GyLtcFY/H1C1sgavs9ENalaf3737t2m7L7bos/8EVHTMHVKHyIiav6Y/OHB5Mi1LWP265+xY8dauqn0CDyXtufLL7/EvHnzsHfvXrRv315/jl966aVqdQcOHAidTgd7e3t07doVp0+ftkCL6y86OhpdunSBi4sLHB0dERgYiNmzZ6OgoKBa3a+//hpPPfUUnJyc4O3tjTlz5uDf//73YxUXePBmekxMDAIDA6FSqeDm5oZu3brh6tWrte5TUlKCTp06YeHChfqyTz/9FKtXr7bof4Q4Nh/g2LS+sWm2Z/6IbIGlnxGaN2+eqFQq/bOiu3fvtlhbjGHq75PFixfLkCFDJC8vT18WEBAgHh4eAkAOHjxYbZ/Dhw/Liy++2KD2mktoaKhs3LhRsrOzJS8vTxITE0WpVMqgQYMM6p07d040Go0sWrRICgoK5Pjx4+Lp6SmvvPLKYxVXRGT48OHSsWNHOXnypJSVlcnt27dl6NChkpqaWus+s2bNEgCyYMECg/L4+HgJDQ2V+/fvm9SWhnyfOTYf4NhsmrHZ0Gf+mPwRNSJLJ3+PK1N+n7z33nvSoUMHKS4uNigPCAiQjz/+WOzs7MTHx0dycnIMtj9Of2DDwsKkvLzcoGzMmDECwGCd5vDwcPH395fKykp92dq1a0WhUMiPP/742MTdtWuXKBQKSUlJqfc+33zzjQwcOLDGP7AiIhEREdK/f38pKyszuj2mfp85Njk2RZp2bD5Wa/sSETWGS5cuYdGiRVi2bBnUanW17cHBwYiMjMStW7fwzjvvWKCFjePgwYMGE6sDgKenJwCgqKgIwIPJ8g8dOoTQ0FCDeTYHDx4MEcGBAwcem7ibN29G79690b1793rVLy4uxrvvvov4+Pha6yxduhRnz56ts05j4tjk2ASsc2z+GpM/InrsrF+/HiKCoUOH1lpnxYoV6NChAz744AN8+eWXdR5PRBAbG4vOnTvD0dER7u7uGDZsmMFayJs2bYJWq4WTkxMOHDiAwYMHw8XFBb6+vti1a5fB8SoqKrB48WK0bdsWGo0GPXr0QGJiYsM+9P+5desWNBoN/P39AQCXL19GQUGBft7NKgEBAQBQ59rp1hS3tLQUJ0+eRM+ePeu9z4IFC/DWW2+hZcuWtdZxd3dHaGgo4uPjzfLWLscmxyZgnWPz15j8EdFj59ChQ+jYsSOcnJxqraPRaPDRRx/Bzs4OkydPRmFhYa11ly5dinnz5mHBggXIyMjAsWPHcOPGDYSEhODu3bsAgDfffBMzZ85EcXExdDodEhMTkZ6ejvbt22Py5MkGE5jPnTsXa9asQVxcHH755RcMGTIE48ePr7aKjbGKiopw9OhRTJ48GSqVCgBw584dAIBOpzOoq1arodFo9O239ri3b99GaWkpfvjhBwwYMADe3t5Qq9Xo3LkzNm7cWO2P4zfffIP09HSMHz/+kcfu1asXbt26hX/9619GtckUHJscm9Y6Nn+NyR8RPVYKCwtx5coV/f/i69K/f3/MnDkTV69e1a9S87Di4mLExsZixIgRmDhxIlxdXdG9e3ds2bIFWVlZ2Lp1a7V9goOD4eLigpYtW2Ls2LEoLCzE9evXATx4u2/Tpk0YPnw4Ro4cCTc3NyxcuBBKpRIJCQkN+uwxMTHw9vbGihUr9GVVby8+fCsMAJRKJYqLixsU01xxq97WbNmyJVauXIm0tDTcvXsXw4YNw/Tp0/GXv/xFX7e4uBiRkZHYtGlTvY795JNPAniw9GVT4tjk2LTWsfkwh4bsHBcXZ+oEg0TN0s2bNwH8ZwJOanwZGRkQkTqvrPzaihUrcPDgQWzcuBHh4eHVtqelpaGgoAB9+/Y1KA8KCoJKpXrk0ohVVxuqrq5cuHABRUVF6Natm76ORqNB69atDW7VGWvfvn1ISkrCF198YXBFo+q5svLy8mr7lJaWQqPRmBzTnHEdHR0BAF27dkVwcLC+fNmyZdi8eTO2bt2KCRMmAADmz5+PN954Az4+PvU6dtVYaYwrTXXh2OTYtNax+TBe+SOix0pJSQmA//xCfhS1Wo2EhAQoFAq8+uqr1f7Xn5OTAwBwdnautq+bmxvy8/ONal/VLbyFCxcazC157do1/QPpxvrkk0+watUqJCcnw8/Pz2Bb69atATxYi/vXioqKUFJSAm9vb5NimjtuVf2srCyDcpVKhXbt2iE9PR3Ag7nbUlNT8frrr9f72FV/7KvGTlPh2PQz2Max+WjmGpsPa9CVv5kzZ3I5JqJfqVoOilfEjfPrN/IepeqXpTETpPbv3x+zZs3CunXrsHz5coMHwd3c3ACgxj+kOTk58PX1rXccAPoHvOPi4hAZGWnUvjXZsGEDjhw5gqNHj9aYBPj7+0On0+HatWsG5ZcuXQIA9OjR47GI6+zsjCeffBLnz5+vtq28vByurq4AgO3bt+Orr76CnV31axcrV67EypUr8d133xlcLSstLQWABl9pehSOTUMcm/9h6bH5MF75I6LHipeXFxQKBXJzc43ab/ny5ejUqRPOnDljUN6tWzc4OztXe+D91KlTKC0tRZ8+fYyK06ZNG6jVapw9e9ao/R4mIpgzZw5SU1Oxf//+Gv/IAYCDgwNeeOEFHDt2DJWVlfryw4cPQ6FQ1PnWqTXFBYDw8HCcOXMGly9f1pcVFRXh2rVr+ik2EhISICIGP5mZmQAevGEpItVuk1aNlVatWhndJmNwbBri2LSesVmNqTMEgpM8E1XDSZ5NY+zvk4CAAOnZs2et265cuVLjthMnToi9vX21iXSXLFkiSqVSduzYIbm5uZKSkiK9evUSb29vKSgo0NdbsGCBADCYvHfbtm0CwGDi2GnTpolKpZKNGzdKbm6ulJeXy40bN+T27dsi8mACWi8vL/nhhx9q/Yznzp0TALX+rF271qCuWq2WhQsX6lcz8PDwqLaagTXHFRG5d++e+Pn5SUhIiFy7dk2ysrJk+vTpYmdnJ2fOnKl1v8zMzFon0hURWbp0qQCQs2fP1hn/YaZ8nzk2OTZ/ranGJid5JiKbExb2/9m797CoyrV/4N9BZhgOM4CCSiCIYJ7LVNqK+pq7Xsu8NDxTWpm7QtMIZZuahxSVVNzATwPdHjbtS0vBQ9r2kO70MjPNdqVBWGqU4iHjoJwxTvfvD19mO3KQGWAGWN/Pdc0frnnWeu71rGcxt+vwPCOQmppq9IzUxx9/DH9/f6SlpSEgIABvvvlmlfX69++P2bNnV1n+7rvvIjIyEhEREXBzc8OQIUPQsWNHHD9+HI6OjgDujqUWExMD4O5to19++QWbNm1CeHg4AOCZZ57BpUuXAACxsbGYNWsWVq1ahTZt2sDDwwNhYWG4ffs2gLu3ejIyMmodbFZMGPerR48eOHz4MI4cOYI2bdpg7NixmDp1KtavX29UrinXC9wd9+yLL76Al5cXevfuDU9PT3z99dc4cOCASWOs3e8///kPPD09zb7NaAr2TWPsm7WzZN80Ym7aCF75I6qCV/7MY+rfk0uXLomtra1s3bq1EaNqPOXl5TJ48GDZsmUL621kWVlZotVqZc2aNSava875zL7JeuuqPn2TV/6ISHH8/f0RERGBiIgIwxhczUV5eTn27t2L/Px8BAcHs95GtmTJEvTu3RuhoaEWqY99k/XWlaX75r2aZPK3e/dudOrUyehVdJVKBVtbW7i5ueGpp57Cnj17Gj2OV155BVqtFiqVqtbXsO+P98UXX6xSZtiwYdDpdGjVqhV69OiB7777rjFDr7c1a9YYHl7esGGDYfnBgwfh7OyMf/3rX41av6XqoeZr/vz5GD9+PIKDg01+wN6ajh8/jt27d+PQoUN1Hg+O9ZonOjoa586dw8GDB6FWqy1WL/sm630Qa/VNA3OvGcICt339/PzE2dnZ8O9bt27JZ599Jl27dhUAsmPHjkatX6T6h2hr4ufnJ23atBEAsn///irfHzp0qMrDvE3ZpUuXBICsX7/esGz//v2i1+vlk08+adS6LVVPQ+NtX/PU5+/J4cOHZe7cuQ0cETV3e/fulcjISCkrKzN7G/U9n9k3qToN0TcVddvX1dUVTz75JP7f//t/AO6OqWaK4uJio9G5G8PatWthY2ODkJCQZvU/vroaMWIEcnNzMXLkyAbbZnXHpTHqUQpL9HNL1FFXw4YNw8qVK60dBjUxzz33HObPn1/tFF+Wwr5J1WkKfbNZJX+VKkfzrhz9vK62bNmCjIwMs+qs6yC0gYGBCAsLw/Xr1/HXv/7VrLqUpj7HhaqyRHvymBERNV/NMvlLTk4GAAwZMsRo+RdffIHu3bvD2dkZWq0WvXr1wuHDhwEAYWFhCA8PR1paGlQqFfz9/Q3rbd26Ff369YNWq4WjoyM6duyIZcuWGb63sbHBgQMHMHz4cDg7O8PDwwP/+Mc/aoxv+fLlePjhh7F582Z89tlnte6LiCA6OhrdunWDnZ0dXF1dERQUZDTP4urVq+Hg4ACdToeMjAyEh4fD09MT06dPh6OjI2xsbNC3b1+0a9cOarUajo6O6NOnDwYPHmwY1NPFxQVvv/12ndurOidPnoS3tzdUKhXef/99AHdHTL//2czKz7///W+zjkt19dS1reLj4+Ho6AgHBwfs27cPw4cPh16vh5eXF7Zv317rsbCWuuxXaGgoNBqNYdoiAJgxYwYcHR2hUqkM0w5V155r166FVqtF27ZtMW3aNHh4eECr1SIwMNBobtD61AEAn376KfR6PVasWNGo7UVERPVk7g1jWOGZv6KiIjl06JD4+PjIsGHDjAa4FBHZuXOnLFmyRG7duiXZ2dnSv39/adOmjeH7sWPHip+fn9E6MTExAkDee+89yc7Ollu3bsnf//53mTRpkoj895m/o0ePSk5Ojty6dUueffZZsbOzk8LCwirxVg7geerUKbGxsZGOHTsa4qzumb/FixeLRqORrVu3Sk5OjiQnJ0ufPn3Ezc1Nbt68aShXGcdbb70l69atkzFjxsiPP/4o7777rgCQM2fOSGFhoWRlZckzzzwjAOTAgQOSmZkphYWFEhoaWmUgyQe1V3XP/F29elUAyLp16wxl5s2bZ2iL3377TVxdXSUwMFDKy8vNPi7312NOWx09elRyc3MlIyNDBg8eLI6OjlJSUiKNyZxnhOq6X5MmTZJ27doZrRsVFSUAJDMz07CsuvYMCQkRR0dHOX/+vNy5c0dSU1MlICBAdDqdpKenN0gd+/fvF51OJxERESbtvwiHjqKmic/wUlPV4p/5y83NNVxJcnBwMFzJmTRpUpU3ZMaNG4d3330Xrq6uaN26NUaNGoXs7GzD9Cr3Ky0txdKlSzF06FDMmzcPrVu3hqurK/7yl78gICDAqGxgYCCcnZ3h6uqK4OBg/PHHH/j1119rjHvAgAGYNWsWLl++jHnz5lVbpri4GNHR0RgzZgwmT54MZ2dn9OrVCxs2bEBWVhY2btxYZZ2VK1di5syZ2L17N7p27WpY3r17dzg4OKBNmzZ4/vnnAQDe3t5wc3ODg4MDJk+eDABGV5NMba/q+Pv747333jO8KfXGG2+guLgY//jHPwzzGzZEPea0VWBgIPR6Pdzd3REcHIzCwkKkp6fXuU5LMGe/zGVra2u4uti9e3fEx8cjPz8fCQkJDbL9ESNGIC8vD4sWLWqQ7RERUeNo8smfs7OzYY680tJSXLt2DbNmzUJoaCgeeeQRw62o6lQmhzVNsp2cnIycnBw8/fTTRstbtWqFt95664HbLS0trTX25cuXo0uXLoiLi8PJkyerfJ+amoqCgoIqc/0FBARAo9EY3ZIzhUajAXB3wmlTYn5Qez1IUlISPv74YyxduhRdunRp0Hrq21aVbfKgY2ZpjdUH6qJfv35wcHAw+g8BERG1fE0++buXra0tPD098corr2DNmjW4cOEC3nvvPcP3Bw4cwBNPPAF3d3fY2dlVecbtfnl5eQAAFxeXRolXq9UiISEBKpUKU6dONZruB/jvCyvVTU7t4uKC/Pz8RomrkqntVZvs7Gy8+eabCAgIMEwp1JD1WLutGou198vOzs6kK7BERNT8Navk7169evUCAJw/fx4AkJ6ejtGjR6N9+/Y4c+YMcnNzsWrVqlq38dBDDwFArVcP62vAgAGYPXs2Ll26ZPQSCfDfpLO6H/icnBx4eXk1WlzmtFdt3nrrLeTk5CAhIcHo9fWGqseabdWYrLlfpaWlzbrtiIjIPM02+fv2228BwHB7MSUlBaWlpXjjjTfQqVMnw8wctenYsSNat26NI0eONGqsy5YtQ9euXXH27Fmj5T179oSTkxO++eYbo+VnzpxBSUkJ+vbt22gxmdNeNTlw4AA+/PBDLFq0CD169DAsnzNnToPVY822akym7JetrW2D3rY+fvw4RAT9+/dvtDqIiKjpaRbJX3FxMSoqKiAiuHHjBhISErBw4UK4ublh1qxZAO6+3AAAn332Ge7cuYNLly5VeV6qdevWuHHjBi5fvoz8/HzY2NjgnXfewYkTJxAaGorr16+joqIC+fn5hiuKDaHy9u/9AzpqtVqEh4djz5492LZtG/Ly8pCSkoLp06fDw8MDISEhDRbD/erSXnWRl5eHadOmoXfv3oYXW+7cuYNvvvkG586dM+u4VJd8WLOtGpMp++Xv749bt25h7969KC0tRWZmJq5cuVJlmzW1Z0VFBW7fvo2ysjIkJycjLCwM3t7emDJlSoPUcejQIQ71QkTUHJj7njAacWiGPXv2iJ+fnwCo8rGzs5POnTvLG2+8YTREhYjI3LlzpXXr1uLi4iLjx4+X999/XwCIn5+fpKeny3fffSc+Pj5ib28vgwYNMgyj8f7770uvXr1Eq9WKVquVxx57TOLi4mTVqlVib28vAKRz586SlpYm27ZtE1dXVwEgXl5e8sMPPxjF6+bmJjNnzqx2v+bMmVNlqJeKigqJioqSzp07i1qtFldXVxk9erRcuHDBUObeODp06CBbt24VEZHY2FhxcHAQANKxY0f54osvZOXKleLs7CwApF27dvLhhx/Kjh07pF27dgJAXF1dZfv27Q9sr7CwMMM6jo6OMmbMGFm3bp20b99eAIiDg4OMGjVK1qxZU+1xAiDPPvusWcdl4cKFVeqpa1vFxcUZ2qTymG3cuFH0er0AEB8fH7l48WJ9umetzBkaoi77JSKSnZ0tQ4cOFa1WK76+vvLmm2/KnDlzBID4+/sbzofq+nlISIio1Wrx9PQUW1tb0ev1EhQUJGlpaQ1Wx8GDB0Wn08ny5ctNbrfG/HtCZC4O9UJNVX2HelGJiJiTNKpUKiQmJmLChAnmrE7UIiUlJWHixIkw87RqNNOmTcPOnTuRnZ1t7VCqxb8n1BQ11fOZaPz48QCAnTt3mrP6zmZx25eI6s/cIXyIiKhlYfJHREREpCBM/ohauHfeeQcJCQnIzc2Fr68vdu3aZe2QiIjIimytHQARNa7IyEhERkZaOwwiImoieOWPiIiISEGY/BEREREpCJM/IiIiIgVh8kdERESkIEz+iIiIiBSkXjN8EBEREZHljRs3zuwZPswe6iUxMdHcVYmIrOr06dOIjY3l3zEiarY6dOhg9rpmX/kjImquOGcrESkY5/YlIiIiUhImf0REREQKwuSPiIiISEGY/BEREREpCJM/IiIiIgVh8kdERESkIEz+iIiIiBSEyR8RERGRgjD5IyIiIlIQJn9ERERECsLkj4iIiEhBmPwRERERKQiTPyIiIiIFYfJHREREpCBM/oiIiIgUhMkfERERkYIw+SMiIiJSECZ/RERERArC5I+IiIhIQZj8ERERESkIkz8iIiIiBWHyR0RERKQgTP6IiIiIFITJHxEREZGCMPkjIiIiUhAmf0REREQKwuSPiIiISEGY/BEREREpCJM/IiIiIgVh8kdERESkIEz+iIiIiBSEyR8RERGRgthaOwAiosaUmZmJjz/+2GjZN998AwDYuHGj0XKdTofnn3/eYrEREVmDSkTE2kEQETWWP/74A23btkVBQQFatWoFAKj8s6dSqQzlSktL8fLLL+ODDz6wRphERJayk7d9iahFs7Ozw7hx42Bra4vS0lKUlpairKwMZWVlhn+XlpYCAF544QUrR0tE1PiY/BFRi/fCCy+gpKSk1jIuLi7485/V44zFAAAgAElEQVT/bKGIiIish8kfEbV4Q4cOhbu7e43fq9VqTJ48Gba2fAyaiFo+Jn9E1OLZ2Nhg0qRJUKvV1X5fWlrKFz2ISDGY/BGRIjz//POGZ/vu99BDD2HAgAEWjoiIyDqY/BGRIjz++OPw8fGpslyj0eDll182evOXiKglY/JHRIrx4osvVrn1W1JSwlu+RKQoTP6ISDEmTZpU5davv78/evXqZaWIiIgsj8kfESlG165d0b17d8MtXrVajVdeecXKURERWRaTPyJSlJdeeskw00dZWRlv+RKR4jD5IyJFef7551FeXg4A6NOnD3x9fa0cERGRZTH5IyJF8fb2xp/+9CcAwMsvv2zlaIiILE+xw9mPHz/e2iEQkZX88ccfUKlUOHLkCE6cOGHtcIjICgYMGIDZs2dbOwyrUOyVv127duHatWvWDoPuc+3aNezatcvaYTQ77M+m8fLyQrt27aDVaq0dSovG85maqq+++gqnT5+2dhhWoxIRsXYQ1qBSqZCYmIgJEyZYOxS6R1JSEiZOnAiFdkuzsT+b7ueff4a/v7+1w2jReD5TU1V592/nzp1WjsQqdir2yh8RKRsTPyJSKiZ/RERERArC5I+IiIhIQZj8ERERESkIkz8iIiIiBWHyZ6ZXX30VOp0OKpUK586ds3Y4TUJFRQViYmIQGBho7VBw8OBBODs741//+pe1QyEiImpSmPyZafPmzdi0aZO1w2gyLl26hP/5n//B7NmzUVRUZO1wOLQEERFRDZj8EQCguLjY7Ct233//PebNm4fp06ejd+/eDRyZeUaMGIHc3FyMHDnS2qHUq22JiIgaGpO/elCpVNYOocFs2bIFGRkZZq376KOPYvfu3Zg0aRLs7OwaOLLmrz5tS0RE1NCY/NWRiCAqKgpdunSBnZ0dnJ2dMWfOHKMyq1evhoODA3Q6HTIyMhAeHg5PT09cuHABIoLo6Gh069YNdnZ2cHV1RVBQEH766SfD+mvXroVWq0Xbtm0xbdo0eHh4QKvVIjAwEGfOnKkSz4O2FxoaCo1Gg/bt2xuWzZgxA46OjlCpVMjKygIAhIWFITw8HGlpaVCpVM1+8NuTJ0/C29sbKpUK77//PgAgPj4ejo6OcHBwwL59+zB8+HDo9Xp4eXlh+/bthnXregzq27affvop9Ho9VqxYYYkmISIi+i9RKACSmJhY5/ILFiwQlUolf/vb3+T27dtSVFQkcXFxAkDOnj1rVA6AvPXWW7Ju3ToZM2aM/Pjjj7J48WLRaDSydetWycnJkeTkZOnTp4+4ubnJzZs3DeuHhISIo6OjnD9/Xu7cuSOpqakSEBAgOp1O0tPTDeXqur1JkyZJu3btjPYlKipKAEhmZqZh2dixY8XPz8+kNqzOn/70J3n00UfNXj8xMVEaoltevXpVAMi6desMyyqPzdGjRyU3N1cyMjJk8ODB4ujoKCUlJYZydT0G9Wnb/fv3i06nk4iIiHrvq4jp/ZnIEhrqfCZqaOPGjZNx48ZZOwxrSeKVvzooLi5GTEwMnnrqKcyePRsuLi6wt7dH69ata1xn5cqVmDlzJnbv3g0fHx9ER0djzJgxmDx5MpydndGrVy9s2LABWVlZ2Lhxo9G6tra2hit63bt3R3x8PPLz85GQkGCIx5TtkbHAwEDo9Xq4u7sjODgYhYWFSE9PNyrzoGNQXyNGjEBeXh4WLVrUINsjIiKqKyZ/dfDzzz+jqKgITz75pFnrp6amoqCgAP369TNaHhAQAI1GU+WW7v369esHBwcHwy3d+m6P/kuj0QAASktLay13/zEgIiJqrpj81cG1a9cAAO7u7matn5OTAwBwcnKq8p2Liwvy8/MfuA07OztkZmY22PbIdPceAyIiouaKyV8daLVaAMAff/xh1vouLi4AUG1SlpOTAy8vr1rXLy0tNSpX3+2R6e4/BkRERM0Vk7866NmzJ2xsbPD555+bvb6TkxO++eYbo+VnzpxBSUkJ+vbtW+v6x48fh4igf//+Jm/P1tb2gbc06cHuPwYA25aIiJonJn914O7ujrFjx2LXrl3YsmUL8vLykJycXOcXK7RaLcLDw7Fnzx5s27YNeXl5SElJwfTp0+Hh4YGQkBCj8hUVFbh9+zbKysqQnJyMsLAweHt7Y8qUKSZvz9/fH7du3cLevXtRWlqKzMxMXLlypUqMrVu3xo0bN3D58mXk5+crPql50DEA6te2hw4d4lAvRERkHdZ+39haYOLQGPn5+fLqq69KmzZtxMnJSQYNGiSLFy8WAOLl5SXff/+9rFq1Suzt7QWAdOjQQbZu3WpYv6KiQqKioqRz586iVqvF1dVVRo8eLRcuXDCqJyQkRNRqtXh6eoqtra3o9XoJCgqStLQ0o3J13V52drYMHTpUtFqt+Pr6yptvvilz5swRAOLv728YuuS7774THx8fsbe3l0GDBhkNF/Mgp0+floEDB4qHh4cAEADSvn17CQwMlM8//7zO2xFpmKEh1q1bJ+3btxcA4uDgIKNGjZK4uDhxcHAQANK5c2dJS0uTjRs3il6vFwDi4+MjFy9eFJG6H4P6tO3BgwdFp9PJ8uXL67WvlUztz0SWwKFeqKlS+lAvKhFlToKqUqmQmJiICRMmWDsUI9OmTcPOnTuRnZ1t7VCsIikpCRMnTrTq3LzN8Rg01f5MytYUzmei6owfPx4AsHPnTitHYhU7edu3CSovL7d2CIrHY0BERC0Vkz+q4qeffoJKpXrgJzg42NqhEhERkYmY/DUh77zzDhISEpCbmwtfX1/s2rXLKnF07doVIvLAz44dO6wSX2NqKsfAkj777DPMnz8fu3fvRqdOnQzJ/Ysvvlil7LBhw6DT6dCqVSv06NED3333nRUirruIiAh0794der0ednZ28Pf3x9tvv42CgoIqZU+ePImBAwfCwcEBHh4emDt3rtnDO1mrXuDusESRkZHw9/eHRqOBi4sLevbsicuXL9e4zp07d9C1a1csXLjQsOyTTz7BqlWrrHoVnH3zLvbNptc3mz2rPGrYBIAPyDdJfEDcPOb258WLF8vIkSMlLy/PsMzPz0/atGkjAGT//v1V1jl06JA899xz9YrXUoYMGSJxcXGSnZ0teXl5kpiYKGq1Wp555hmjcj/88IPY29vLokWLpKCgQE6dOiVubm7yyiuvNKt6RURGjx4tXbp0ka+++kpKS0vlxo0bMmrUKElJSalxndmzZwsAWbBggdHy2NhYGTJkiNy+fdusWOpzPrNv3sW+2Th9U+kvfCj2V5bJX9PE5M885vTn9957Tx5++GEpLi42Wu7n5ycffvih2NjYiKenp+Tk5Bh935x+YEeMGCFlZWVGyyZMmCAADG9ji4hMnDhRfH19paKiwrAsKipKVCqV/Pjjj82m3u3bt4tKpZLk5OQ6r/Pll1/KsGHDqv2BFREJDQ2VAQMGSGlpqcnxmHs+s2+yb4o0bt9UevLH275ECvTzzz9j0aJFWLp0qWEGm3sFBgYiLCwM169fx1//+lcrRNgw9u/fj1atWhktc3NzAwAUFRUBAMrKynDgwAEMGTIEKpXKUG748OEQEezbt6/Z1Lt+/Xr06dMHvXr1qlP54uJizJkzB7GxsTWWWbJkCc6dO1drmYbEvsm+CTTNvtmSMPkjUqC1a9dCRDBq1KgayyxfvhwPP/wwNm/ejM8++6zW7YkIoqOj0a1bN9jZ2cHV1RVBQUH46aefDGXi4+Ph6OgIBwcH7Nu3D8OHD4der4eXlxe2b99utL3y8nIsXrwY3t7esLe3xyOPPILExMT67fT/uX79Ouzt7eHr6wsA+OWXX1BQUABvb2+jcn5+fgCA5OTkZlFvSUkJvvrqK/Tu3bvO6yxYsAAzZsyodd5yV1dXDBkyBLGxsRYZsoV9k30TaJp9syVh8kekQAcOHECXLl3g4OBQYxl7e3t88MEHsLGxwWuvvYbCwsIayy5ZsgTz58/HggULkJGRgRMnTuDq1asYPHgwfv/9dwDAG2+8gVmzZqG4uBg6nQ6JiYlIS0tDp06d8NprrxnNKjNv3jysXr0aMTEx+O233zBy5Ei88MILVaY0NFVRURGOHTuG1157DRqNBgBw8+ZNAIBOpzMqq9VqYW9vb4i/qdd748YNlJSU4Ntvv8XQoUPh4eEBrVaLbt26IS4ursqP45dffom0tDS88MILD9z2Y489huvXr+P77783KSZzsG+ybzbVvtmSMPkjUpjCwkL8+uuvhv/F12bAgAGYNWsWLl++jHnz5lVbpri4GNHR0RgzZgwmT54MZ2dn9OrVCxs2bEBWVla10yAGBgZCr9fD3d0dwcHBKCwsRHp6OoC7b/fFx8dj9OjRGDt2LFxcXLBw4UKo1WokJCTUa98jIyPh4eGB5cuXG5ZVvr14/60wAFCr1SguLq5XnZaqt/JtTXd3d6xYsQKpqan4/fffERQUhJkzZ+Kjjz4ylC0uLkZYWBji4+PrtO3OnTsDAFJSUkyKyVTsm+ybTbVvtjSKTv4mTpxYp/Hs+LHcZ+LEiQBg9Tia28cUGRkZEJFar6zca/ny5ejSpQvi4uJw8uTJKt+npqaioKAA/fr1M1oeEBAAjUaDM2fO1Lr9yqsNlVdXLly4gKKiIvTs2dNQxt7eHu3btze6VWeqPXv2ICkpCYcPHza6olH5XFlZWVmVdUpKSmBvb292nZas187ODgDQo0cPBAYGonXr1nB2dsbSpUvh7OxslOi88847eP311+Hp6VmnbVf2lYa40lQb9k32zabaN1saW2sHYE1hYWEYMGCAtcOge5w+fRqxsbEN9gyNUlQmzXVx584dAP/9g/wgWq0WCQkJGDRoEKZOnYpVq1YZfZ+TkwMAcHJyqrKui4sL8vPz6xwbAMMtvIULFxqN7QUAHh4eJm2r0o4dOxAdHY3jx4/joYceMvquffv2AIC8vDyj5UVFRbhz547ZdVq63sryWVlZRss1Gg18fHyQlpYG4O7YbSkpKYiOjq7ztit/7Cv7TmNh32TfbKp9s6VRdPI3YMAAzoXaBMXGxvK4mMiU5K/yj6UpA6QOGDAAs2fPxpo1a7Bs2TKjB8FdXFwAoNof0pycHHh5edW5HgCGB7xjYmIQFhZm0rrVWbduHQ4fPoxjx45VmwT4+vpCp9PhypUrRst//vlnAMAjjzzSLOp1cnJC586dcf78+SrflZWVwdnZGQCwZcsWHD16FDY2VW/8rFixAitWrMB//vMfo6tlJSUlAFDvK00Pwr5pjH3zv6zdN1saRd/2JVKitm3bQqVSITc316T1li1bhq5du+Ls2bNGy3v27AknJ6cqD7yfOXMGJSUl6Nu3r0n1dOjQAVqtFufOnTNpvfuJCObOnYuUlBTs3bu32h85ALC1tcWzzz6LEydOoKKiwrD80KFDUKlUtb512pTqBe7+J+Ds2bP45ZdfDMuKiopw5coVwxAbCQkJVWbryczMBHD3DUsRqXKbtLKvtGvXzuSYTMG+aYx9s+n0zRbHMuMJNj3gIM9NEgd5No+p/dnPz0969+5d43e//vprtd+dPn1aWrVqVWUg3XfffVfUarVs3bpVcnNzJTk5WR577DHx8PCQgoICQ7kFCxYIAKPBezdt2iQAjAaOnT59umg0GomLi5Pc3FwpKyuTq1evyo0bN0Tk7gC0bdu2lW+//bbGffzhhx8EQI2fqKgoo7JarVYWLlxomM2gTZs2VWYzaMr1iojcunVLOnbsKIMHD5YrV65IVlaWzJw5U2xsbOTs2bM1rpeZmVnjQLoiIkuWLBEAcu7cuVrrv5855zP7JvvmvRqrb3KQZyJSnBEjRiA1NdXorb2PP/4Y/v7+SEtLQ0BAAN58880q6/Xv3x+zZ8+usvzdd99FZGQkIiIi4ObmhiFDhqBjx444fvw4HB0dAdwdSy0mJgbA3dtGv/zyCzZt2oTw8HAAwDPPPINLly4BuHvrf9asWVi1ahXatGkDDw8PhIWF4fbt2wDu3urJyMiodbBZMWHcrx49euDw4cM4cuQI2rRpg7Fjx2Lq1KlYv369UbmmXC9wd9yzL774Al5eXujduzc8PT3x9ddf48CBAyaNsXa///znP/D09DT7NqMp2DeNsW/WzpJ9s0WxbvJpPeCVvyaJV/7MY2p/vnTpktja2srWrVsbMarGU15eLoMHD5YtW7aw3kaWlZUlWq1W1qxZY/K65pzP7Just67q0zd55Y+IFMff3x8RERGIiIgwjMHVXJSXl2Pv3r3Iz89HcHAw621kS5YsQe/evREaGmqR+tg3WW9dWbpvtiRM/hrA7t270alTpypjr2k0GrRt2xZPPPEEoqKiDLcFiJqC+fPnY/z48QgODjb5AXtrOn78OHbv3o1Dhw7VeTw41mue6OhonDt3DgcPHoRarbZYveybrPdBrNU3WwqViDInxFOpVEhMTGzQIUX8/f2RlZWFnJwciAhyc3Nx7tw5/POf/8Q///lPtG/fHp988kmVt5Xov5KSkjBx4kTO02ii+vTnI0eO4NixY1i5cmUjREbN1b59+3D+/Hm8/fbb1c70UBf1PZ/ZN6k6DdE3x48fDwDYuXNnQ4bWXOzklb9GolKp4OLigieeeAIJCQlISkrC77//jhEjRjSr/8nWpLi4GIGBgdYOo1FYYt+aUvsNGzaMP65UxXPPPYf58+eb/ePaENg3qTpNoW82d0z+LGTcuHGYMmUKMjIysGHDBmuHU29btmxBRkaGtcNoFJbYt5bcfkRE1LQx+bOgKVOmALg7UCYArF69Gg4ODtDpdMjIyEB4eDg8PT1x4cIFiAiio6PRrVs32NnZwdXVFUFBQUbzR65duxZarRZt27bFtGnT4OHhAa1Wi8DAwCpzVtZle6GhodBoNIapfQBgxowZcHR0hEqlMkzNExYWhvDwcKSlpUGlUsHf37+xmqxOGnvf6trO9W2/Tz/9FHq9HitWrGjU9iIiIoWz3pvG1oVGGOrFz89PnJ2da/w+Ly9PAEiHDh0MyyoHFn3rrbdk3bp1MmbMGPnxxx9l8eLFotFoZOvWrZKTkyPJycnSp08fcXNzk5s3bxrWDwkJEUdHRzl//rzcuXNHUlNTJSAgQHQ6naSnpxvK1XV7kyZNknbt2hnFHRUVJQAkMzPTsGzs2LHi5+dXr/aqjjlDQ1hi3+razvWpY//+/aLT6SQiIsKk/Rfh0EXUNHHoJmqqONQLWYxOp4NKpap2nsmVK1di5syZ2L17N3x8fBAdHY0xY8Zg8uTJcHZ2Rq9evbBhwwZkZWVh48aNRuva2toarnp1794d8fHxyM/PR0JCAoC7z5eZsr3mxJL79qB2rq8RI0YgLy8PixYtapDtERERVYfJnwUVFhZCRKDX62stl5qaioKCgipvBQcEBECj0VS5pXu/fv36wcHBwXDbs77ba8qsuW/3tzMREVFzwOTPgi5evAgA6Nq1a63lcnJyAKDaSbddXFyqvXJ4Pzs7O8OE2A2xvabK2vt2bzsTERE1B0z+LOjTTz8FAAwfPrzWci4uLgBQbeKSk5MDLy+vWtcvLS01Klff7TVl1ty3+9uZiIioOWDyZyE3b95ETEwMvLy8MHXq1FrL9uzZE05OTvjmm2+Mlp85cwYlJSXo27dvresfP34cIoL+/fubvD1bW1uUlpaasmtWZc19u7+dG6MOIiKihsbkr4GJCAoKClBRUQERQWZmJhITEzFw4EC0atUKe/fufeAzf1qtFuHh4dizZw+2bduGvLw8pKSkYPr06fDw8EBISIhR+YqKCty+fRtlZWVITk5GWFgYvL29DUPLmLI9f39/3Lp1C3v37kVpaSkyMzNx5cqVKjG2bt0aN27cwOXLl5Gfn2+1hMeS+/agdq5vHYcOHeJQL0RE1Pis+rKxFaEBh8b45JNP5JFHHhEHBwfRaDRiY2MjAESlUomLi4s8/vjjEhERIdnZ2UbrrVq1Suzt7Q3Dv2zdutXwXUVFhURFRUnnzp1FrVaLq6urjB49Wi5cuGC0jZCQEFGr1eLp6Sm2trai1+slKChI0tLSjMrVdXvZ2dkydOhQ0Wq14uvrK2+++abMmTNHAIi/v79hWJPvvvtOfHx8xN7eXgYNGmQ0pEp9mDM0hCX2ra7tXJ86Dh48KDqdTpYvX25yuzVkfyZqKBzqhZoqpQ/1wrl9G3BuX2uYNm0adu7ciezsbGuH0iCa6ty+Tb2dW0p/ppalqZ7PRJzbl5q98vJya4egCGxnIiJqCZj8ERERESkIk79m7J133kFCQgJyc3Ph6+uLXbt2WTukFontTERELYmttQMg80VGRiIyMtLaYbR4bGciImpJeOWPiIiISEGY/BEREREpCJM/IiIiIgVh8kdERESkIIp+4eP06dPWDoHuU3lMkpKSrBxJ88P+TE0Nz2dqqq5duwYvLy9rh2E1ip7hg4iIiJRp3Lhxip3hQ7FX/hSa8xIROO0YESkbn/kjIiIiUhAmf0REREQKwuSPiIiISEGY/BEREREpCJM/IiIiIgVh8kdERESkIEz+iIiIiBSEyR8RERGRgjD5IyIiIlIQJn9ERERECsLkj4iIiEhBmPwRERERKQiTPyIiIiIFYfJHREREpCBM/oiIiIgUhMkfERERkYIw+SMiIiJSECZ/RERERArC5I+IiIhIQZj8ERERESkIkz8iIiIiBWHyR0RERKQgTP6IiIiIFITJHxEREZGCMPkjIiIiUhAmf0REREQKwuSPiIiISEGY/BEREREpCJM/IiIiIgVh8kdERESkIEz+iIiIiBSEyR8RERGRgjD5IyIiIlIQW2sHQETUmK5du4aXX34Z5eXlhmW3b9+GTqfDE088YVS2S5cu+Pvf/27hCImILIvJHxG1aF5eXrhy5QrS0tKqfPf5558b/ft//ud/LBUWEZHV8LYvEbV4L730EtRq9QPLBQcHWyAaIiLrYvJHRC3epEmTUFZWVmuZHj16oHv37haKiIjIepj8EVGL5+fnh0ceeQQqlara79VqNV5++WULR0VEZB1M/ohIEV566SW0atWq2u/Kysowfvx4C0dERGQdTP6ISBGef/55VFRUVFluY2OD/v37o2PHjpYPiojICpj8EZEieHh4YODAgbCxMf6zZ2Njg5deeslKURERWR6TPyJSjBdffLHKMhHBmDFjrBANEZF1MPkjIsUYN26c0XN/rVq1wlNPPYW2bdtaMSoiIsti8kdEiuHq6or//d//NSSAIoLJkydbOSoiIsti8kdEijJ58mTDix9qtRpBQUFWjoiIyLKY/BGRoowaNQp2dnYAgJEjR8LJycnKERERWRaTPyJSFEdHR8PVPt7yJSIlUomIWDsIS0hKSsLEiROtHQYRERE1QQpJhwBgp621I7C0xMREa4dAAE6fPo3Y2FgeDxNNnDgRYWFhGDBggLVDadbKy8uRmJiIF154wdqhtAg8n6k5q+y/SqK45G/ChAnWDoH+T2xsLI+HiSZOnIgBAwaw3RrA6NGjodVqrR1Gi8HzmZozpSV/fOaPiBSJiR8RKRWTPyIiIiIFYfJHREREpCBM/oiIiIgUhMkfERERkYIw+WuGIiIi0L17d+j1etjZ2cHf3x9vv/02CgoKal3v1VdfhU6ng0qlwrlz50yud9WqVejatSvs7e3h6OiIrl27YtGiRcjLyzN3V+rt4MGDcHZ2xr/+9S+rxUBERNScMPlrho4dO4aZM2fi8uXLyMrKQmRkJGJjYzF+/Pha19u8eTM2bdpkdr1ffPEFXnvtNaSnp+P333/HsmXLsGrVKowbN87sbdaXggblJCIiahBM/pohJycnhISEoHXr1tDpdJgwYQJGjx6NTz/9FFevXm20ejUaDWbMmAF3d3c4OTlh/PjxCAoKwr///W/89ttvjVZvbUaMGIHc3FyMHDnSKvXfq7i4GIGBgdYOg4iIqFaKG+S5Jdi/f3+VZW5ubgCAoqKiWtdVqVRm17tnz54qyzw9PQHggbeclWDLli3IyMiwdhhERES14pW/B9i6dSv69esHrVYLR0dHdOzYEcuWLQNw95ZjdHQ0unXrBjs7O7i6uiIoKAg//fSTYf34+Hg4OjrCwcEB+/btw/Dhw6HX6+Hl5YXt27cbynXr1g0qlQo2Njbo27evIYl7++234ezsDK1Wiw8++KDGOK9fvw57e3v4+voalokIoqKi0KVLF9jZ2cHZ2Rlz5sxp0Pa5dOkSXFxc4OPj06DbrYuTJ0/C29sbKpUK77//PoC6t/fatWuh1WrRtm1bTJs2DR4eHtBqtQgMDMSZM2cM5UJDQ6HRaNC+fXvDshkzZsDR0REqlQpZWVkAgLCwMISHhyMtLQ0qlQr+/v4AgE8//RR6vR4rVqywRJMQERE9mChEYmKimLq7MTExAkDee+89yc7Ollu3bsnf//53mTRpkoiILF68WDQajWzdulVycnIkOTlZ+vTpI25ubnLz5k3DdhYsWCAA5OjRo5KbmysZGRkyePBgcXR0lJKSEhERKSsrk44dO4q3t7eUlZUZxTFr1iyJiYmpMc7CwkLR6XQSGhpqtHzBggWiUqnkb3/7m9y+fVuKiookLi5OAMjZs2dNaot7lZSUyLVr12TdunViZ2cnW7duNXkb5hyP6ly9elUAyLp16wzL6tLeIiIhISHi6Ogo58+flzt37khqaqoEBASITqeT9PR0Q7lJkyZJu3btjOqNiooSAJKZmWlYNnbsWPHz8zMqt3//ftHpdBIREVHvfRURASCJiYkNsi2ihtJQ5zORNSiw/ybxyl8NSktLsXTpUgwdOhTz5s1D69at4erqir/85S8ICAhAcXExoqOjMWbMGEyePBnOzs7o1asXNmzYgKysLGzcuLHKNgMDA6HX6+Hu7o7g4GAUFhYiPT0dANCqVSu89dZbSE9PN7q9WlRUhN27d2Pq1Kk1xhoZGQkPDw8sX77csKy4uBgxMTF46qmnMHv2bLi4uMDe3g11PfMAACAASURBVB6tW7eud9t06NABXl5eWLJkCVavXo2JEyfWe5uNobb2rmRra2u4ctu9e3fEx8cjPz8fCQkJDRLDiBEjkJeXh0WLFjXI9oiIiOqLyV8NkpOTkZOTg6efftpoeWWSlpqaioKCAvTr18/o+4CAAGg0GqNbh9XRaDQA7iaZlV599VU4OzsbTTC9bds2BAUFQa/XV7udPXv2ICkpCYcPH4ZOpzMs//nnn1FUVIQnn3yybjtsgqtXryIjIwMfffQR/vnPf+Kxxx5r8s+6Vdfe1enXrx8cHByMbt0TERG1JEz+alA5dp2Li0u13+fk5AC4++bt/VxcXJCfn29ynU5OTnj99ddx6tQpfP311wCA9evXIzQ0tNryO3bswMqVK3H8+HF07NjR6Ltr164BANzd3U2O40HUajXc3d0xbNgw7NixA6mpqYiMjGzweqzFzs4OmZmZ1g6DiIioUTD5q8FDDz0EAIYH+u9XmRRWl+Tl5OTAy8vLrHpDQ0OhVqsRExODEydOoEOHDvDz86tSbt26ddi2bRuOHTtmiPVeWq0WAPDHH3+YFUdd+fv7o1WrVkhNTW3UeiyltLS0XsePiIioqWPyV4OOHTuidevWOHLkSLXf9+zZE05OTvjmm2+Mlp85cwYlJSXo27evWfV6eXlhwoQJ2LVrFxYtWoSwsDCj70UEc+fORUpKCvbu3VvtlcfK+GxsbPD555+bFcf9srOz8cILL1RZfunSJZSXl6NDhw4NUo+1HT9+HCKC/v37G5bZ2to+8HYxERFRc8HkrwZ2dnZ45513cOLECYSGhuL69euoqKhAfn4+zp8/D61Wi/DwcOzZswfbtm1DXl4eUlJSMH36dHh4eCAkJMTsusPDw1FWVobbt2/jz3/+s9F358+fx+rVq7Fp0yao1WqoVCqjz5o1awDcvd07duxY7Nq1C1u2bEFeXh6Sk5OrfRGlLhwdHXHkyBEcO3YMeXl5KC0txdmzZ/Hyyy/D0dERs2fPNnt/ramiogK3b99GWVkZkpOTERYWBm9vb0yZMsVQxt/fH7du3cLevXtRWlqKzMxMXLlypcq2WrdujRs3buDy5cvIz89HaWkpDh06xKFeiIioabH2+8aWYu6r3O+//7706tVLtFqtaLVaeeyxxyQuLk5ERCoqKiQqKko6d+4sarVaXF1dZfTo0XLhwgXD+nFxceLg4CAApHPnzpKWliYbN24UvV4vAMTHx0cuXrxYpd6hQ4fK5s2bqyxPSUkRADV+oqKiDGXz8/Pl1VdflTZt2oiTk5MMGjRIFi9eLADEy8tLvv/+e5PaYtSoUeLr6ytOTk5iZ2cnfn5+EhwcLCkpKSZtR6RhXq1ft26dtG/fXgCIg4ODjBo1yqT2DgkJEbVaLZ6enmJrayt6vV6CgoIkLS3NqJ7s7GwZOnSoaLVa8fX1lTfffFPmzJkjAMTf398wLMx3330nPj4+Ym9vL4MGDZKbN2/KwYMHRafTyfLly+u1r5XAoV6oCVLgUBnUgiiw/yapRJQxOWpSUhImTpzIuWCbiKZwPKZNm4adO3ciOzvbajGYSqVSITExERMmTLB2KEQGTeF8JjKXAvvvTt72JUUrLy+3dghEREQWxeRPwX766acqzwxW9wkODrZ2qNQAPvvsM8yfPx+7d+9Gp06dDMf3xRdfrFJ22LBh0Ol0aNWqFXr06IHvvvvOChHXXUREBLp37w69Xg87Ozv4+/vj7bffrnbO6ZMnT2LgwIFwcHCAh4cH5s6da/Zb8daqF7j7ZnpkZCT8/f2h0Wjg4uKCnj174vLlyzWuc+fOHXTt2hULFy40LPvkk0+watUqq/5HqCX3zUoVFRWIiYlBYGBgjWU++ugjBAQEQKfTwcfHB6+88gpu3rzZIus15dx5UHxNoQ83O9a86WxJCryn36RZ+3jMnz9fNBqNAJCOHTvKzp07rRaLKWDmM3+LFy+WkSNHSl5enmGZn5+ftGnTRgDI/v37q6xz6NAhee655+oVr6UMGTJE4uLiJDs7W/Ly8iQxMVHUarU888wzRuV++OEHsbe3l0WLFklBQYGcOnVK3Nzc5JVXXmlW9YqIjB49Wrp06SJfffWVlJaWyo0bN2TUqFG1PoM7e/ZsASALFiwwWh4bGytDhgyR27dvmxVLfc7nlt43RUQuXrwoAwcOFADy6KOPVltmx44dAkBWrVolOTk5cvbsWenUqZP07t1bSktLW1y9dT136hpfffqwtX+PrCBJMXurwIPbpPF4mMec5O+9996Thx9+WIqLi42W+/n5yYcffig2Njbi6ekpOTk5Rt83px/YESNGVJkTe8KECQLAaJ7miRMniq+vr1RUVBiWRUVFiUqlkh9//LHZ1Lt9+3ZRqVSSnJxc53W+/PJLGTZsWLXJn4hIaGioDBgwwKwffHPPZyX0zXPnzsmYMWNk27Zt0rt37xqToaFDh8pDDz1k1Efef/99ASAnT55scfXW9dwxJT5z+7ACf484ty9RS/bzzz9j0aJFWLp0qWHg73sFBgYiLCwM169fx1//+lcrRNgw9u/fj1atWhktc3NzA3B3fmwAKCsrw4EDBzBkyBCoVCpDueHDh0NEsG/fvmZT7/r169GnTx/06tWrTuWLi4sxZ84co6kj77dkyRKcO3eu1jINSSl989FHH8Xu3bsxadIk2NnZ1Vju6tWr8PDwMOojleOnVje0VHOvty7njqnxWboPN2dM/ohasLVr10JEMGrUqBrLLF++HA8//DA2b96Mzz77rNbtiQiio6PRrVs32NnZwdXVFUFBQUZzIcfHx8PR0REODg7Yt28fhg8fDr1eDy8vL2zfvt1oe+Xl5Vi8eDG8vb1hb2+PRx55BImJifXb6f9z/fp12Nvbw9fXFwDwyy+/oKCgAN7e3kblKmfQSU5Obhb1lpSU4KuvvkLv3r3rvM6CBQswY8aMWqd7dHV1xZAhQxAbG2uRtx6V3Der06lTpypzpFc+19apU6cWV2917j93TI3P0n24OWPyR9SCHThwAF26dIGDg0ONZezt7fHBBx/AxsYGr732GgoLC2ssu2TJEsyfPx8LFixARkYGTpw4gatXr2Lw4MH4/fffAQBvvPEGZs2aheLiYuh0OiQmJiItLQ2dOnXCa6+9ZjRbyrx587B69WrExMTgt99+w8iRI/HCCy9UmTnHVEVFRTh27Bhee+01aDQaAP/9wdDpdEZltVot7O3tDfE39Xpv3LiBkpISfPvttxg6dCg8PDyg1WrRrVs3xMXFVfnR+/LLL5GWllbtDD33e+yxx3D9+nV8//33JsVkDqX2zZq88847uHnzJtatW4f8/HykpqYiNjYWTz/9tNGMQy2l3vtVd+6YE58l+3BzxuSPqIUqLCzEr7/+Wu3c0PcbMGAAZs2ahcuXL2PevHnVlikuLkZ0dDTGjBmDyZMnw9nZGb169cKGDRuQlZVV7ewxgYGB0Ov1cHd3R3BwMAoLC5Geng7g7pun8fHxGD16NMaOHQsXFxcsXLgQarUaCQkJ9dr3yMhIeHh4YPny5YZllW/W3n+rCQDUajWKi4vrVael6q18G9Ld3R0rVqxAamoqfv/9dwQFBWHmzJn46KOPDGWLi4sRFhaG+Pj4Om27c+fOAICUlBSTYjKVkvtmTYYMGYK5c+ciNDQUer0ePXv2RH5+PjZv3two9Vm73vtVd+6YE5+l+nBzZ2vtACwtKSnJ2iEQgNOnTwPg8WhMGRkZEJFar6zca/ny5di/fz/i4uIwceLEKt+npqaioKAA/fr1M1oeEBAAjUaDM2fO1Lr9yv/NV15duXDhAoqKitCzZ09DGXt7e7Rv397oVp2p9uzZg6SkJBw5csToalvlc2VlZWVV1ikpKYG9vb3ZdVqy3srnqHr06GE0jMbSpUuxfv16bNy4EZMmTQJw96rJ66+/Dk9Pzzptu7KvNMRV0NootW/WZsGCBdi8eTOOHj2KP/3pT8jIyMC8efMwYMAAnDp1qtHmT7dWvfeq6dwxJz5L9eHmTnHJX3V/OMh6eDwaz507dwCg1oeu76XVapGQkIBBgwZh6tSpWLVqldH3OTk5AAAnJ6cq67q4uCA/P9+k+Cpv4S1cuNBo3DkA8PDwMGlblXbs2IHo6GgcP34cDz30kNF37du3BwDk5eUZLS8qKsKdO3fMrtPS9VaWz8rKMlqu0Wjg4+ODtLQ0AHfHFUxJSUF0dHSdt12ZiFb2ncaixL5Zm99++w2rVq3C/PnzDfO5+/r6YtOmTXB1dUVUVBTWrl3bYuq9V23njjnxWaoPN3eKu+0rIvw0gU/lg9PWjqO5fUxR+UfQlIFPBwwYgNmzZ+PSpUtYtmyZ0XcuLi4AUO0PaU5ODry8vEyKr/Llg5iYmCr7WXll2BTr1q3Dtm3bcOzYsSo/IsDdHw2dTlflDcGff/4ZAPDII4+YXKc16nVyckLnzp1x/vz5Kt+VlZXB2dkZALBlyxYcPXoUNjY2hkGTK9t8xYoVUKlUVZ5fKykpAYB6XwV9EKX1zQe5dOkSysvLq/QfvV6P1q1bIzU1tcHrtGa9lR507pgTn6X6cHOnuOSPSCnatm0LlUqF3Nxck9ZbtmwZunbtirNnzxot79mzJ5ycnKokDGfOnEFJSQn69u1rUj0dOnSAVqvFuXPnTFrvfiKCuXPnIiUlBXv37q326g8A2Nra4tlnn8WJEydQUVFhWH7o0CGoVKpa3zptSvUCd6+Ynz17Fr/88othWVFREa5cuWIY/iUhIaFK4pKZmQng7q00Ealym7Syr7Rr187kmEyhlL5ZV5XJ6W+//Wa0PD8/H7du3Wq0W6/Wqreu54458VmqDzd3TP6IWigHBwd06tQJ165dM2m9ylts97+goNVqER4ejj179mDbtm3Iy8tDSkoKpk+fDg8PD4SEhJhczyuvvILt27cjPj4eeXl5KC8vx7Vr1wx/7IODg9GuXbtap/A6f/48Vq9ejU2bNkGtVleZnnDNmjWGsosWLcLvv/+Od999F4WFhTh9+jSioqIwZcoUdOnSxVCuKdcLALNnz4aPjw+mTJmC9PR0ZGdnY+7cuSguLq7xpYi6qOwrdR0/0FxK6Zt15evri6FDh2LTpk04ceIEiouLcfXqVUPcf/nLXwxlW0K9dT13TImvkqX6cLMnCqHAEbybNB4P88DEGT5CQ0NFrVZLUVGRYdmePXvEz89PAIibm5vMnDmz2nXnzJlTZRaFiooKiYqKks6dO4tarRZXV1cZPXq0XLhwwVAmLi5OHBwcBIB07txZ0tLSZOPGjaLX6wWA+Pj4yMWLF0VE5I8//pC5c+eKt7e32Nrairu7u4wdO1ZSU1NF5O4UZgBk8eLFNe5jSkqKAKjxExUVZVT+888/l8cff1zs7OzEw8ND5syZI3fu3DEq05TrrXT16lV5/vnnxdXVVezs7OTxxx+XQ4cO1bpOZmZmjTN8iNyddcHT09NoNoW6MOd8VkLfFBE5ffq0DBw4UDw8PAx9o3379hIYGCiff/65oVxWVpaEhYWJv7+/2NnZiZOTkwwcOFA+/vhjo+21hHpNOXfqGl8lc/qwAn+POL0bWQePh3lMTf4uXboktra2snXr1kaMqvGUl5fL4MGDZcuWLay3kWVlZYlWq5U1a9aYvK455zP7JuttaOb2YQX+HnF6N6KWzN/fHxEREYiIiDCMD9dclJeXY+/evcjPz0dwcDDrbWRLlixB7969ERoaapH62DdZb0OzdB9uzpj8EbVw8+fPx/jx4xEcHGzyA/bWdPz4cezevRuHDh2q83hwrNc80dHROHfuHA4ePAi1Wm2xetk3WW9DsVYfbrasfe3RUhr6su5PP/0kM2fOlO7du4uTk5O0atVK9Hq9dO7cWZ599lk5depUg9VlrqVLl0q3bt1Ep9OJRqMRPz8/mTNnjuTn5xvK7Nq1S3x9fas8c6FWq8Xd3V2GDBkiq1evllu3bjVobAq8zN4gYOJt33sdPnxY5s6d28ARUXO3d+9eiYyMlLKyMrO3Ud/zmX2T6qO+fViBv0e87WuOLVu2oFevXkhOTkZ0dDSuXr2KwsJCnD17FsuWLUNOTk6TmFrm2LFjmDlzJi5fvoysrCxERkYiNjYW48ePN5QZO3YsfvnlF/j5+cHZ2RkigoqKCmRkZCApKQm+vr6YO3cuevTo0WhzWpJlDBs2DCtXrrR2GNTEPPfcc5g/f361089ZCvsm1UdT6MPNjeJm+Kivr776CiEhIRgyZAgOHz4MW9v/NmGnTp3QqVMnuLi44NKlS1aM8i4nJyeEhIQYTogJEyZg9+7dSEpKwtWrV2scw0mlUsHFxQVPPPEEnnjiCYwYMQITJ07EiBEjcPHiRcMgss1dcXExnnzySZw6dapZ10FERGQKXvkz0fLly1FeXo733nvPKPG719NPP42ZM2daOLKq9u/fX+V/Qm5ubgDuDghbV+PGjcOUKVOQkZGBDRs2NGiM1rRlyxZkZGQ0+zqIiIhMweTPBCUlJTh69CjatGmDxx9/vM7riQiio6PRrVs32NnZwdXVFUFBQUYThMfHx8PR0REODg7Yt28fhg8fDr1eDy8vL2zfvt1Qrlu3blCpVLCxsUHfvn0NSdzbb78NZ2dnaLVafPDBBzXGcv36ddjb28PX19ekfZ8yZQqAu7MSWEtd2jE0NBQajcYwnyoAzJgxA46OjlCpVIb5UMPCwhAeHo60tDSoVCr4+/tj7dq10Gq1aNu2LaZNmwYPDw9otVoEBgYaTQxfnzoA4NNPP4Ver8eKFSsatb2IiIiqZeWHDi2mIR7ovHjxogCQ/v37m7Te4sWLRaPRyNatWyUnJ0eSk5OlT58+4ubmJjdv3jSUW7BggQCQo0ePSm5urmRkZMjgwYPF0dFRSkpKRESkrKxMOnbsKN7e3lUebp01a5bExMTUGEdhYaHodDoJDQ2t8p2fn584OzvXuG5eXp4AkA4dOpi07zUx53jUtR0nTZok7dq1M1o3KipKAEhmZqZh2dixY8XPz8+oXEhIiDg6Osr58+flzp07kpqaKgEBAaLT6SQ9Pb1B6ti/f7/odDqJiIgwaf9F6vfCB1FjUeAD89SCKLD/8oUPU+Tl5QFAjfMQVqe4uBjR0dEYM2YMJk+eDGdnZ/Tq1QsbNmxAVlYWNm7cWGWdwMBA6PV6uLu7Izg4GIWFhUhPTwcAtGrVCm+99RbS09OxZ88ewzpFRUXYvXs3pk6dWmMskZGR8PDwwPLly+scfyWdTgeVSlXtxOmWYE47msvW1tZwdbF79+6Ij49Hfn4+EhISGmT7I0aMQF5eHhYtWtQg2yMiIjIFkz8TVCZ9pjwvl5qaioKCgioTqAcEBECj0RjdTqyORqMBAJSWlhqWvfrqq3B2dkZsbKxh2bZt2xAUFAS9Xl/tdvbs2YOkpCQcPnwYOp2uzvFXKiwshIjUuP3GVt92rI9+/frBwcHB6PYyERFRc8XkzwQdO3aEVqvFxYsX67xOTk4OgOqvFrq4uJh1Jc3JyQmvv/46Tp06ha+//hoAsH79+hpHNf//7N17XNRV/j/w1wDDDDMwMIgCgiAXb6RlKptifo1qTTPNu3hp021b1ApJNDWvqZmKC66KtV6yVl0V1LC8ZKtm6ua6Wboibqau5SUNBLmjDPD+/dGPWUdQmYFhgHk9H4/5w/M58znvz5nDzNvP53zOZ8uWLVi0aBEOHTqEli1bmt0eAOMxt23b1qL315Q1+tEcKpUKmZmZVm2DiIioLjD5M4NKpcJzzz2Hmzdv4h//+Md962VnZ+MPf/gDgF8TEwBVJic5OTnw9/e3KJaYmBgolUokJibi8OHDaNGiBUJCQirVW7FiBTZu3IiDBw+iefPmFrUF/HqTAgD06dPH4n3UhLX6sToMBoPV2yAiIqorTP7MNHfuXKhUKkyaNAnFxcVV1jlz5oxxGZj27dvD1dW10gLJx48fR0lJCTp37mxRHP7+/hg2bBi2bduGWbNmITY21mS7iGDq1KlIS0tDamqqWfMU73Xjxg0kJibC39//gXMKrcmcfnRycjK5TF5Thw4dgoiga9euVmuDiIiorjD5M1PHjh2xadMmnDlzBj169MCePXuQm5sLg8GAS5cuYc2aNXjllVeMzxZUq9WIi4vDjh07sHHjRuTl5SEtLQ3jx4+Hr68voqOjLY4lLi4OpaWluHXrFp5++mmTbWfPnsWSJUuwZs0aKJVKKBQKk9fSpUsr7U9EUFBQgPLycogIMjMzsXXrVnTv3h2Ojo5ITU212Zw/c/oxNDQU2dnZSE1NhcFgQGZmJn766adK+/T09MTPP/+MH3/8Efn5+cZkrry8HLdu3UJpaSlOnz6N2NhYBAQEGJe7qWkbe/fu5VIvRERkM0z+LDB48GB8//33iIyMxLRp0+Dv7w8XFxd06tQJ77//Pnr27IkRI0YY68+ZMwcLFy7EvHnz4OXlhZ49e6Jly5Y4dOgQtFotgF/X+UtMTAQAPProo/jvf/+LNWvWIC4uDgDQu3fvSk8NefzxxxEZGYmJEydWilFEqnUsn332GR577DFcv34dt2/fhru7OxwdHeHo6IjWrVsjISEBY8aMQXp6usVnKWtLdfoRACZMmIDIyEiMGDECbdq0wfz58+Hi4gIA6NatG65cuQIAGD9+PJo1a4awsDA8//zzyM7OBgDcvn0bHTp0gIuLC3r06IHWrVvjyy+/hEqlqrU2iIiIbEUh1c0SGrjk5GQMHz682kkRWVd9/TzGjRuHlJQUZGVl2TqUKikUCmzduhXDhg2zdShERvX175moOuxw/KbwzB/RPcrKymwdAhERkdUw+SMiIiKyI0z+iP6/t99+G+vXr0dubi6CgoKwbds2W4dERERU65xsHQBRfbFw4UIsXLjQ1mEQERFZFc/8EREREdkRJn9EREREdoTJHxEREZEdYfJHREREZEfs7oaPoUOH2joEAnD16lUA/DwskZiYiJSUFFuHQWTEv2dqyCrGrz2xmyd8HDt2DAkJCbYOg4jqgRs3buDkyZPo06ePrUMhonrCjv5TnWI3yR8RUQU7fJwTEVEFPt6NiIiIyJ4w+SMiIiKyI0z+iIiIiOwIkz8iIiIiO8Lkj4iIiMiOMPkjIiIisiNM/oiIiIjsCJM/IiIiIjvC5I+IiIjIjjD5IyIiIrIjTP6IiIiI7AiTPyIiIiI7wuSPiIiIyI4w+SMiIiKyI0z+iIiIiOwIkz8iIiIiO8Lkj4iIiMiOMPkjIiIisiNM/oiIiIjsCJM/IiIiIjvC5I+IiIjIjjD5IyIiIrIjTP6IiIiI7AiTPyIiIiI7wuSPiIiIyI4w+SMiIiKyI0z+iIiIiOwIkz8iIiIiO8Lkj4iIiMiOMPkjIiIisiNM/oiIiIjsCJM/IiIiIjviZOsAiIisyWAwoKCgwKSssLAQAHDr1i2TcoVCAQ8PjzqLjYjIFpj8EVGjlp2dDT8/P5SVlVXa5unpafLvyMhIHDx4sK5CIyKyCV72JaJGzdvbG//3f/8HB4cHf90pFAqMGDGijqIiIrIdJn9E1Oi99NJLD63j6OiIQYMG1UE0RES2xeSPiBq9wYMHw8np/rNcHB0d0bt3bzRp0qQOoyIisg0mf0TU6Ol0OvTp0+e+CaCIYPTo0XUcFRGRbTD5IyK7MHr06Cpv+gAAZ2dnvPDCC3UcERGRbTD5IyK78MILL0Cj0VQqVyqVGDhwILRarQ2iIiKqe0z+iMguqNVqDBo0CEql0qTcYDBg1KhRNoqKiKjuMfkjIrsxcuRIGAwGkzKdToff/va3NoqIiKjuMfkjIrvx7LPPmizsrFQqMWLECDg7O9swKiKiusXkj4jshpOTE0aMGGG89GswGDBy5EgbR0VEVLeY/BGRXRkxYoTx0q+3tzeefPJJG0dERFS3mPwRkV2JiIiAn58fAOB3v/vdQx/7RkTU2FRa8fTq1av4+uuvbRELEVGdCA8Px7Vr19CkSRMkJyfbOhwiIqsZNmxYpTKFiMjdBcnJyRg+fHidBUVERERE1nFPmgcAKfd92GUVlYns2tChQwEAKSkpNo6k4aj4z2R9/D7Ztm0bhgwZYuswqB6rz+OX6GEedDKPk12IyC4x8SMie8Xkj4iIiMiOMPkjIiIisiNM/oiIiIjsCJM/IiIiIjvC5I+IiIjIjtQ4+QsPD4ejoyM6duxYG/GYZezYsVCr1VAoFLh9+3adt18fLV26FM2aNYNCocAHH3xgLN+zZw/c3d3x2WefWbX9umqnOhYvXoy2bdvCxcUFWq0Wbdu2xaxZs5CXl2fTuOpTHxERkf2pcfL3zTffIDIysjZiMdv69esxefJkm7RdX02ePLnKJ7TU1TpV9Wk9rCNHjuDVV1/F5cuX8csvv2D+/PlYvHixzZf4qE99RERE9ue+izybS6FQ1HgfxcXFeOaZZ/h4OSvo27cvcnNza3WfVX1e1mjHUs7OznjttdegVqsB/LpIc0pKClJSUnD9+nX4+vraJK761Ef8myMisj+1lvwplcoa72PdunXIyMiw6L21kXySeWryedWFHTt2VCrz8/MDABQUFNR1OPVSff8MiYio9tXaDR8XLlxA27ZtodVq4eLigh49euDo0aMmdY4cOYKwsDC4u7tDrVajQ4cO2LdvHwAgNjYWcXFxuHjxIhQKBUJDQ43v27BhA7p06QK1Wg2tVouWLVti/vz5/zsIBwfs3r0bffr0gbu7O3x9ffHhhx+afQyrVq2CVquFRqPBzp070adPH+h0Ovj7+2Pz5s0mdUUECQkJaNeuHVQqFfR6PQYMGIDvv//eWGfJkiXQaDRwc3NDRkYG4uLi4Ofnh/Hjx0Or1cLBwQGdO3eGt7c3lEoltFotOnXqhB49eqBFixZQq9Xw8PDAW2+9Ve1+rMrRo0cREBAAhUKBlStXAvj181IoFFW+/v73v1v0eVXVTnX7ypy+r4nz58/Dw8MDgYGBtbZPa/86ZAAAIABJREFUc1TVR9U99uXLl0OtVqNZs2YYN24cfH19oVarERERgePHjxvrxcTEwNnZGT4+Psay1157DVqtFgqFAjdv3gRw/7+5zz//HDqdDu+++25ddAkREdU1ucfWrVuliuIHeuaZZyQ4OFguXbokBoNBzpw5I0888YSo1Wr54YcfjPVSUlJk7ty5kp2dLVlZWdK1a1dp0qSJcfvgwYMlJCTEZN+JiYkCQN577z3JysqS7Oxs+ctf/iKjRo0SEZEZM2YIADlw4IDk5ORIdna2PP/886JSqaSwsNCs47h3f7m5uZKRkSE9evQQrVYrJSUlxnqzZ88WZ2dn2bBhg+Tk5Mjp06elU6dO4uXlJTdu3Ki0v4kTJ8qKFStk0KBB8p///EfmzJkjAOT48eNSWFgoN2/elN69ewsA2b17t2RmZkphYaHExMQIADl16lS1+/H8+fMCQN5//31j2ZUrVwSArFixwlhn2rRpxj66fv266PV6iYiIkLKyMos/r3vbsaSvHtb35iopKZGrV6/KihUrRKVSyYYNGyzaz5AhQ2TIkCEWx1Ghqj6q7rFHR0eLVquVs2fPyu3btyU9PV3Cw8PFzc1NLl++bKw3atQo8fb2Nmk3Pj5eAEhmZqaxrKrPcNeuXeLm5ibz5s2r8bFa8n1CVF9w/FJD9oDxm1xrZ/7c3NzQsmVLODk54ZFHHsGaNWtw+/ZtrF692lhnyJAhmDNnDvR6PTw9PdG/f39kZWUhMzOzyn0aDAa88847iIyMxLRp0+Dp6Qm9Xo9XXnkF4eHhJnUjIiLg7u4OvV6PqKgo3LlzB5cuXbL4eCIiIqDT6dC0aVNERUWhsLAQly9fBvDrPKmEhAQMGjQIo0ePhru7Ozp06IAPPvgAN2/eNDnmCosWLcLrr7+O7du3o23btsbysLAwaDQaNGnSBCNGjAAABAQEwMvLCxqNBqNHjwYAk7Nk5vZjVUJDQ/Hee+9Bo9EAACZMmIDi4mJ8+OGHcHBwqLV2LOmrB/W9JVq0aAF/f3/MnTsXS5Ysue+DruuD6hy7k5OT8SxqWFgYVq1ahfz8fKxfv75WYujbty/y8vIwa9asWtkfERHVL1Zb569Dhw5wd3fH6dOn71unYp5gWVlZldtPnz6NnJwcPPfccybljo6OmDhx4kP3azAYzA27Ss7Ozib7S09PR0FBAbp06WJSLzw8HM7OziaX4Cxpp7S01FhWnWN5WD8+THJyMj755BO88847aNOmTa22U9O+urfvLXHlyhVkZGTgb3/7Gz7++GM8/vjjDWKeW3WPvUuXLtBoNCb/QSAiIrqfWrvhoypKpdLkh2v37t2Ij49Heno68vLyHvqjVrEem4eHhzXDNFtOTg4AwNXVtdI2Dw8P5OfnW7V9c/vxQbKysvDGG28gPDwccXFxtd6OrfsK+HUcNm3aFL169UJQUBBat26NhQsXYtmyZVZvu66oVCqzzsgSEZH9stqZv9LSUmRnZyMgIAAAcPnyZQwcOBA+Pj44fvw4cnNzsXjx4gfuo3nz5gBgnKBeX1Qko1UlLjk5OfD397da25b044NMnDgROTk5WL9+PRwdHWu9HVv2VVVCQ0Ph6OiI9PT0Om3XmgwGg036koiIGiarJX9ffvklysvL0alTJwBAWloaDAYDJkyYgODgYOOTOR6kZcuW8PT0xBdffGGtMC3Svn17uLq64sSJEyblx48fR0lJCTp37my1ti3px/vZvXs3Nm3ahFmzZuGRRx4xlk+ZMqXW2rFVX2VlZWHkyJGVys+fP4+ysjK0aNHCKu3awqFDhyAi6Nq1q7HMycmp1qY9EBFR41JryV9JSQlyc3NRWlqK7777DjExMQgMDMSYMWMAwHgGcP/+/bh9+zbOnz9fab6Xp6cnfv75Z/z444/Iz8+Hg4MD3n77bRw+fBgxMTG4du0aysvLkZ+fj7Nnz9ZW6GZTq9WIi4vDjh07sHHjRuTl5SEtLQ3jx4+Hr68voqOjrdZ2dfqxOvLy8jBu3Dh07NgR06ZNAwDcvn0bJ06cwKlTpyz6vKpKNmzVV1qtFl988QUOHjxovGR98uRJvPzyy9BqtZg0aZJV2q0L5eXluHXrFkpLS3H69GnExsYiICDA+LcG/HqGMzs7G6mpqTAYDMjMzMRPP/1UaV9VfYZ79+7lUi9ERI2ZGbcG39f69eslMjJSmjVrJk5OTtKkSRMZMWKE/PTTTyb1pk6dKp6enuLh4SFDhw6VlStXCgAJCQmRy5cvy3fffSeBgYHi4uIiTz75pHEZkJUrV0qHDh1ErVaLWq2Wxx9/XJKSkmTx4sXi4uIiAKRVq1Zy8eJF2bhxo+j1egEg/v7+cubMmWofR1JSkmg0GpP9rV69WnQ6nQCQwMBA49I15eXlEh8fL61atRKlUil6vV4GDhwo586dM+7v7vhatGhhXGJk2bJlxnZatmwpR44ckUWLFom7u7sAEG9vb9m0aZNs2bJFvL29BYDo9XrZvHnzQ/sxNjbW+B6tViuDBg2SFStWiI+PjwAQjUYj/fv3l6VLlwqAKl/PP/+8RZ/XzJkzK7VT3b4yp++rq3///hIUFCSurq6iUqkkJCREoqKiJC0tzaz9VKiNpV6q+izMOfbo6GhRKpXi5+cnTk5OotPpZMCAAXLx4kWTdrKysiQyMlLUarUEBQXJG2+8IVOmTBEAEhoaalwWpqq/uT179oibm5ssWLCgRscqwqUyqGHj+KWG7EFLvShETB80mpycjOHDh/P5o0T3GDp0KAAgJSXFZjGMGzcOKSkpyMrKslkM5uD3CTVkHL/UkD1g/KZYbc4fEVmHpUv6EBERAVa84aO++P777+/7GLO7X1FRUbYOlR6Cn6X92b9/P6ZPn47t27cjODjY+Bm/9NJLler26tULbm5ucHR0xCOPPILvvvvOBhGbr7y8HImJiYiIiLhvnb/97W8IDw+Hm5sbAgMDMXbsWNy4caNRtjtv3jyEhYVBp9NBpVIhNDQUb731VpXP435YfJ9++ikWL15ss/8wcfz+iuO3Ho5fM64RE9m12nq8m6WmT58uzs7OxrmiKSkpNoulumryfTJ79mzp16+f5OXlGctCQkKkSZMmAkB27dpV6T179+6VF1980eJ469oPP/wg3bt3FwDy2GOPVVlny5YtAkAWL14sOTk5cvLkSQkODpaOHTuKwWBodO327NlTkpKSJCsrS/Ly8mTr1q2iVCqld+/eFsW3bNky6dmzp9y6dcvseDl+H6w+jyOO3wfP+WPyR1RNtk7+GiJLv0/ee+89ad26tRQXF5uUh4SEyKZNm8TBwUH8/PwkJyfHZHtD+vE8deqUDBo0SDZu3CgdO3a8749JZGSkNG/eXMrLy41lFTdfHT16tNG127dvXyktLTUpGzZsmAAweX61OfHFxMRIt27dzP7R5/i9v/o+jjh+6+jZvkREteHChQuYNWsW3nnnHajV6krbIyIiEBsbi2vXrmHy5Mk2iLB2PPbYY9i+fTtGjRoFlUp133pXrlyBr6+vyTqbFetUVrV8T0Nvd9euXSYLzgOAl5cXAKCoqMii+ObOnYtTp07VyVN9OH5NcfzWz/HL5I+I6pXly5dDRNC/f//71lmwYAFat26NtWvXYv/+/Q/cn4ggISEB7dq1g0qlgl6vx4ABA0yehbxq1SpotVpoNBrs3LkTffr0gU6ng7+/PzZv3myyv7KyMsyePRsBAQFwcXHBo48+iq1bt9bsoB8gODi40rOoK+YFBQcHN7p2q3Lt2jW4uLggKCjIovj0ej169uyJZcuWWf3OXY5fUxy/9XT8mnGakMiu8bKv+Sz5PgkODpawsLAqt4WEhMilS5dEROTrr78WBwcHadmypRQUFIhI1ZfNZs+eLc7OzrJhwwbJycmR06dPS6dOncTLy8u4lqiIyIwZMwSAHDhwQHJzcyUjI0N69OghWq1WSkpKjPUmT54sKpVKtm3bJrdu3ZK3335bHBwc5JtvvjHrOO/2xBNP3Pcy0qFDh0SpVMry5cslLy9Pzpw5I+3atZPnnnvO4vbqc7v3KiwsFDc3N4mJialRfNOnTxcAcvLkyWrHyfFbPfVxHHH8cs4fUa1g8mc+c79PCgoKRKFQSL9+/arcfvePp4hIXFycAJDXX39dRCr/eBYVFYmrq6tERUWZ7Odf//qXAJB58+YZyyp+PO+ep5WUlCQA5MKFCyIiUlxcLBqNxmR/RUVFolKpZMKECdU+zns97Mdk5syZJgux+/v7y5UrVyxur763e7cZM2ZI69atTW6csCS+Dz/8UADIX//612rHyfFbPfV1HHH83j/5c7rfGcGKBW2J6Ff//Oc/AfBvwxxXr141q35GRgZEBBqNplr1FyxYgF27diEpKQnDhw+vtD09PR0FBQXo0qWLSXl4eDicnZ0f+mhEZ2dnADA+uvDcuXMoKipC+/btjXVcXFzg4+NjchmuNs2YMQNr167FgQMH8MQTTyAjIwPTpk1Dt27d8PXXX1vtOdW2avduO3bsQHJyMr744gu4ubnVKL6KMfXLL79YLV6O38o4fuvn+OWcPyKqN27fvg0AD5xQfTe1Wo3169dDoVDg97//PYqLi0225+TkAABcXV0rvdfDwwP5+flmxVdYWAgAmDlzpsnakj/99JPJZO7acv36dSxevBh//OMf8fTTT0Or1SIoKAhr1qzBzz//jPj4+Fpv05bt3m3Lli1YtGgRDh06hJYtW9Y4PhcXFwD/G2PWwPFriuO3/o7f+575s+UjrIjqo/rweLeGpuLxQtVV8QVnzqKm3bp1w6RJk7B06VLMnz8fAQEBxm0eHh4AUOWPZE5ODvz9/avdDgA0bdoUAJCYmIjY2Fiz3muJ8+fPo6ysDM2bNzcp1+l08PT0RHp6eqNqt8KKFSuwb98+HDx4sMrEx5L4SkpKAPxvjFkDx68pjt/6O3555o+I6o1mzZpBoVAgNzfXrPfNnz8fbdu2xcmTJ03K27dvD1dXV5w4ccKk/Pjx4ygpKUHnzp3NaqdFixZQq9U4deqUWe+zVMWP+/Xr103K8/PzkZ2dbbVLV7ZqV0QwdepUpKWlITU1tcofTkvjqxhT3t7etRz1/3D8muL4rb/jl8kfEdUbGo0GwcHBZs8VrLh8du/6Wmq1GnFxcdixYwc2btyIvLw8pKWlYfz48fD19UV0dLTZ7YwdOxabN2/GqlWrkJeXh7KyMly9etX4RR4VFQVvb+9aeTxXUFAQIiMjsWbNGhw+fBjFxcW4cuWKMe5XXnnFWLcxtHv27FksWbIEa9asgVKprPToxqVLl5odX4WKMdWhQ4cax3k/HL+mOH7r8fg14+4QIrvGu33NZ8n3SUxMjCiVSikqKjKW7dixQ0JCQgSAeHl5Ge+OvNeUKVMqLZVRXl4u8fHx0qpVK1EqlaLX62XgwIFy7tw5Y52kpCTRaDQCQFq1aiUXL16U1atXi06nEwASGBgoP/zwg4iI3LlzR6ZOnSoBAQHi5OQkTZs2lcGDB0t6erqIiAwcOFAAyOzZsx94nMeOHZPu3buLr6+v8W4/Hx8fiYiIkK+++spY7+bNmxIbGyuhoaGiUqnE1dVVunfvLp988onJ/hpDu2lpaSZ3P977io+PNzu+Cn379hU/Pz+TJyo8DMfv/dXncWSrdhvQ+OVSL0TVxeTPfJZ8n5w/f16cnJxkw4YNVorKusrKyqRHjx6ybt06tltP3Lx5U9RqtSxdutSs93H8st36wArjl493I6L6JTQ0FPPmzcO8efNQUFBg63DMUlZWhtTUVOTn5yMqKort1hNz585Fx44dERMTY/W2OH7Zbm2zxvit8+Rv+/btCA4OrnQt3MnJCV5eXnj22WexY8cOq8cxduxYqNVqKBSKB946fW+8L730UqU6vXr1gpubGxwdHfHII4/UytwBa1q6dKlxYvIHH3xgLN+zZw/c3d3x2WefWbX9umqHGq7p06dj6NChiIqKMnvyvC0dOnQI27dvx969e6u91hvbta6EhAScOnUKe/bsgVKprJM2OX7Zbm2x2vg14zRhrQoJCRF3d3fjv7Ozs2X//v3Stm1bASBbtmyxegxVrYh+PyEhIdKkSRMBILt27aq0varH8tRn58+fFwDy/vvvG8t27dolOp1OPv30U6u2XVft1DZe9jVfTb9P9u3bJ1OnTq3FiMiepKamysKFC6W0tNSi93P8ki1ZcfzWn8u+er0ezzzzDP785z8D+HV9MHMUFxcjIiLCGqEZLV++HA4ODoiOjm5Q/5urrr59+yI3Nxf9+vWrtX1W9blYox17URfjvC7aqK5evXph0aJFtg6DGqgXX3wR06dPr3QXbV3h+KWasOb4rTfJX4WKlbArVjavrnXr1iEjI8OiNhUKRbXqRUREIDY2FteuXcPkyZMtasve1ORzocrqoj/5mRERNW71Lvk7ffo0AKBnz54m5UeOHEFYWBjc3d2hVqvRoUMH7Nu3DwAQGxuLuLg4XLx4EQqFAqGhocb3bdiwAV26dIFarYZWq0XLli0xf/5843YHBwfs3r0bffr0gbu7O3x9ffHhhx/eN74FCxagdevWWLt2Lfbv3//AYxERJCQkoF27dlCpVNDr9RgwYIDJMxSXLFkCjUYDNzc3ZGRkIC4uDn5+fhg/fjy0Wi0cHBzQuXNneHt7Q6lUQqvVolOnTujRo4dxwU4PDw+89dZb1e6vqhw9ehQBAQFQKBRYuXIlAODChQuV5mZWvP7+979b9LlU1U51+2rVqlXQarXQaDTYuXMn+vTpA51OB39/f2zevPmBn4WtVOe4YmJi4OzsDB8fH2PZa6+9Bq1WC4VCgZs3bwKouj+XL18OtVqNZs2aYdy4cfD19YVarUZERITJcz9r0gYAfP7559DpdHj33Xet2l9ERFQHzLhGXKvunfNXVFQke/fulcDAQOnVq5cUFBSY1E9JSZG5c+dKdna2ZGVlSdeuXaVJkybG7YMHD5aQkBCT9yQmJgoAee+99yQrK0uys7PlL3/5i4waNUpE/jfn78CBA5KTkyPZ2dny/PPPi0qlksLCwkrxXrp0SUREvv76a3FwcJCWLVsa46xqzt/s2bPF2dlZNmzYIDk5OXL69Gnp1KmTeHl5yY0bN4z1KuKYOHGirFixQgYNGiT/+c9/ZM6cOQJAjh8/LoWFhXLz5k3p3bu3AJDdu3dLZmamFBYWSkxMjACQU6dOVbu/qprzd+XKFQEgK1asMNaZNm2asS+uX78uer1eIiIipKyszOLP5d52LOmrAwcOSG5urmRkZEiPHj1Eq9VKSUmJWJMlc/6qe1yjRo0Sb29vk/fGx8cLAMnMzDSWVdWf0dHRotVq5ezZs3L79m1JT0+X8PBwcXNzk8uXL9dKG7t27RI3NzeZN2+eWcfPpaOoIeP4pYas3s75y83NNZ5J0mg0xjM5o0aNqnRXy5AhQzBnzhzo9Xp4enqif//+yMrKQmZmZpX7NhgMeOeddxAZGYlp06bB09MTer0er7zyCsLDw03qRkREwN3dHXq9HlFRUbhz5w4uXbp037i7deuGN998Ez/++COmTZtWZZ3i4mIkJCRg0KBBGD16NNzd3dGhQwd88MEHuHnzJlavXl3pPYsWLcLrr7+O7du3o23btsbysLAwaDQaNGnSBCNGjAAABAQEwMvLCxqNBqNHjwYAk7NJ5vZXVUJDQ/Hee+8Z74KaMGECiouL8eGHH8LBwaHW2rGkryIiIqDT6dC0aVNERUWhsLAQly9frnabdcGS47KUk5OT8exiWFgYVq1ahfz8fKxfv75W9t+3b1/k5eVh1qxZtbI/IiKyHZsmf+7u7hARiAgMBgOuXr2KN998EzExMXj00UeNl6KqUpEc3u8B2qdPn0ZOTg6ee+45k3JHR0dMnDjxofs1GAwPjH3BggVo06YNkpKScPTo0Urb09PTUVBQgC5dupiUh4eHw9nZ2eSSnDmcnZ0BAKWlpWbF/LD+epjk5GR88skneOedd9CmTZtabaemfVXRJw/7zOqatcZAdXTp0gUajcbkPwRERERAPZrz5+TkBD8/P4wdOxZLly7FuXPn8N577xm37969G0899RSaNm0KlUpVaY7bvfLy8gAAHh4eVom34lmMCoUCv//971FcXGyyveKGlaoe7Ozh4YH8/HyrxFXB3P56kKysLLzxxhsIDw9HXFxcrbdj676yFlsfl0qlMusMLBER2Yd6k/zdreLBxWfPngUAXL58GQMHDoSPjw+OHz+O3NxcLF68+IH7aN68OQA88OxhTXXr1g2TJk3C+fPnTW4iAf6XdFb1A5+TkwN/f3+rxWVJfz3IxIkTkZOTU+nB47XVji37yppseVwGg6FB9x0REVlPvUz+vv32WwAwXl5MS0uDwWDAhAkTEBwcbHwyx4O0bNkSnp6e+OKLL6wa6/z589G2bVucPHnSpLx9+/ZwdXXFiRMnTMqPHz+OkpISdO7c2WoxWdJf97N7925s2rQJs2bNwiOPPGIsnzJlSq21Y8u+siZzjsvJyalWL1sfOnQIIoKuXbtarQ0iImqYbJ78FRcXo7y8HCKCn3/+GevXr8fMmTPh5eWFN998E8CvNzcAwP79+3H79m2cP3++0nwpT09P/Pzzz/jxxx+Rn58PBwcHvP322zh8+DBiYmJw7do1lJeXIz8/33hGsTZUXP69dxFGtVqNuLg47NixAxs3bkReXh7S0tIwfvx4+Pr6Ijo6utZiuFd1+qs68vLyMG7cOHTs2NF4Y8vt27dx4sQJnDp1yqLPparkw5Z9ZU3mHFdoaCiys7ORmpoKg8GAzMxM/PTTT5X2eb/+LC8vx61bt1BaWorTp08jNjYWAQEBGDNmTK20sXfvXi71QkTUWJhxa3Ct2LFjh4SEhAiASi+VSiWtWrWSCRMmmCxRISIydepU8fT0FA8PDxk6dKisXLlSAEhISIhcvnxZvvvuOwkMDBQXFxd58sknjctorFy5Ujp06CBqtVrUarU8/vjjkpSUJIsXLxYXFxcBIK1atZKLFy/Kxo0bRa/XCwDx9/eXM2fOmMTr5eUlr7/+epXHNWXKlEpLvZSXl0t8fLy0atVKlEql6PV6GThwoJw7d85Y5+44WrRoIRs2bBARkWXLlolGoxEA0rJlSzly5IgsWrRI3N3dBYB4e3vLpk2bZMuWLeLt7S0ARK/Xy+bNmx/aX7Gxscb3aLVaGTRokKxYsUJ8fHwEgGg0Gunfv78sXbq0ys8JgDz//PMWfS4zZ86s1E51+yopKcnYJxWf2erVq0Wn0wkACQwMlB9++KEmw/OBLFnqpTrHJSKSlZUlkZGRolarJSgoSN544w2ZMmWKAJDQ0FDj30NV4zw6OlqUSqX4+fmJk5OT6HQ6GTBggFy8eLHW2tizZ4+4ubnJggULzDp+LpVBDRnHLzVkD1rqRSEicncymJycjOHDh+OeYiK7N3ToUABASkqKjSMxNW7cOKSkpCArK8vWoVTC7xNqyDh+qSF7wPhNsfllXyKqOUuX8CEiIvvD5I+IiIjIjjD5I2rA3n77baxfvx65ubkICgrCtm3bbB0SERHVc062DoCILLdw4UIsXLjQ1mEQEVEDwjN/RERERHaEyR8RERGRHWHyR0RERGRHmPwRERER2REmf0RERER25L53+yoUirqMg6jB4N+G+dhn1JBx/FJjUyn5i4iIwNatW20RCxFRnTh27BiWLVvG7zoiskuVnu1LRNTY8ZmtRGTH+GxfIiIiInvC5I+IiIjIjjD5IyIiIrIjTP6IiIiI7AiTPyIiIiI7wuSPiIiIyI4w+SMiIiKyI0z+iIiIiOwIkz8iIiIiO8Lkj4iIiMiOMPkjIiIisiNM/oiIiIjsCJM/IiIiIjvC5I+IiIjIjjD5IyIiIrIjTP6IiIiI7AiTPyIiIiI7wuSPiIiIyI4w+SMiIiKyI0z+iIiIiOwIkz8iIiIiO8Lkj4iIiMiOMPkjIiIisiNM/oiIiIjsCJM/IiIiIjvC5I+IiIjIjjD5IyIiIrIjTP6IiIiI7AiTPyIiIiI7wuSPiIiIyI4w+SMiIiKyI0z+iIiIiOyIk60DICKypszMTHzyyScmZSdOnAAArF692qTczc0NI0aMqLPYiIhsQSEiYusgiIis5c6dO2jWrBkKCgrg6OgIAKj42lMoFMZ6BoMBL7/8Mj766CNbhElEVFdSeNmXiBo1lUqFIUOGwMnJCQaDAQaDAaWlpSgtLTX+22AwAABGjhxp42iJiKyPyR8RNXojR45ESUnJA+t4eHjg6aefrqOIiIhsh8kfETV6kZGRaNq06X23K5VKjB49Gk5OnAZNRI0fkz8iavQcHBwwatQoKJXKKrcbDAbe6EFEdoPJHxHZhREjRhjn9t2refPm6NatWx1HRERkG0z+iMgu/OY3v0FgYGClcmdnZ7z88ssmd/4SETVmTP6IyG689NJLlS79lpSU8JIvEdkVJn9EZDdGjRpV6dJvaGgoOnToYKOIiIjqHpM/IrIbbdu2RVhYmPESr1KpxNixY20cFRFR3WLyR0R25Xe/+53xSR+lpaW85EtEdofJHxHZlREjRqCsrAwA0KlTJwQFBdk4IiKiusXkj4jsSkBAAJ544gkAwMsvv2zjaIiI6p5Nl7NPSEjAsWPHbBkCEdmhO3fuQKFQ4IsvvsDhw4dtHQ4R2ZlJkybZdG1Rm575O3bsGP75z3/aMgQiE1evXsW2bdtsHUaDs23bNly9etXWYVSbv78/vL29oVarbR0K1QMNbfxSw7Zt2zZcuXLFpjHY/EGWXbt2RUpKiq3DIAIAJCcnY/jw4RyTZlIoFHjzzTcxbNgwW4dSbRcuXEBoaKitw6B6oCGOX2q46sOC8pzzR0R2iYkfEdkrJn9EREREdoTJHxEREZEdYfJHREREZEeY/BERERHZESZ/jczSpUvRrFkzKBQKfPDBB8byPXv2wN3dHZ999pnV2p43bx6xqOymAAAgAElEQVTCwsKg0+mgUqkQGhqKt956CwUFBQ983x/+8Ae4ublBoVDg1KlTFrdfXl6OxMREREREWLyP2lIX/U1ERGQJJn+NzOTJk/H1119XKhcRq7d98OBBvP766/jxxx9x8+ZNLFy4EMuWLcPQoUMf+L61a9dizZo1NWr7/Pnz+L//+z9MmjQJRUVFNdpXbaiL/iYiIrKEzdf5o7rRt29f5ObmWrUNV1dXREdHw9HREQAwbNgwbN++HcnJybhy5QpatGhhlXb//e9/Y968eRg/fjwKCwvrReJVF/1dXcXFxXjmmWeq/E8BERHZH575I4uICFJSUrB69Wpj2a5du4yJXwUvLy8AeOjZuJosevnYY49h+/btGDVqFFQqlcX7aazWrVuHjIwMW4dBRET1RINK/pYtWwatVgsHBwd07twZ3t7eUCqV0Gq16NSpE3r06IEWLVpArVbDw8MDb731lsn7jxw5grCwMLi7u0OtVqNDhw7Yt28fAOCjjz6Cq6srFAoF9Ho9UlNTceLECQQGBsLR0REjR440K9bly5dDrVajWbNmGDduHHx9faFWqxEREYHjx4+b1BURJCQkoF27dlCpVNDr9RgwYAC+//57i+rd6+jRowgICIBCocDKlSsBAKtWrYJWq4VGo8HOnTvRp08f6HQ6+Pv7Y/PmzSbvLysrw8KFC9GmTRu4uLjAy8sLQUFBWLhw4UNXxL927RpcXFwQFBRkchzx8fFo06YNVCoV3N3dMWXKlIf2aUNRk/6u7riJiYmBs7MzfHx8jGWvvfYatFotFAoFbt68CQCIjY1FXFwcLl68CIVCYVzY+PPPP4dOp8O7775bF11CRET1idjQkCFDZMiQIWa9Z86cOQJAjh8/LoWFhXLz5k3p3bu3AJDdu3dLZmamFBYWSkxMjACQU6dOGd+bkpIic+fOlezsbMnKypKuXbtKkyZNjNvPnj0rGo1GXn75ZWPZ9OnTZe3atRYdX3R0tGi1Wjl79qzcvn1b0tPTJTw8XNzc3OTy5cvGerNnzxZnZ2fZsGGD5OTkyOnTp6VTp07i5eUlN27cMLve+fPnBYC8//77xrIrV64IAFmxYoWxbMaMGQJADhw4ILm5uZKRkSE9evQQrVYrJSUlxnrvvvuuODo6ys6dO6WoqEi+/fZb8fb2lqeeeuqBx19YWChubm4SExNjUj5jxgxRKBTypz/9SW7duiVFRUWSlJQkAOTkyZPmd/RdnnjiCXnssccsfv/WrVulNv4satLf1R03o0aNEm9vb5N24+PjBYBkZmYaywYPHiwhISEm9Xbt2iVubm4yb968Gh+riAgA2bp1a63si6iucfxSXaoH4y25QZ35u1tYWBg0Gg2aNGmCESNGAAACAgLg5eUFjUaD0aNHA4DJWbEhQ4Zgzpw50Ov18PT0RP/+/ZGVlYXMzEwAQLt27ZCYmIiPP/4YmzZtwubNm3Hnzh288sorFsfp5ORkPFMXFhaGVatWIT8/H+vXrwfw63yshIQEDBo0CKNHj4a7uzs6dOiADz74ADdv3jReVq1uPUtERERAp9OhadOmiIqKQmFhIS5fvmzcnpqais6dO6N///5wcXFBp06d8OKLL+Lw4cMoKSm5734XLlwIX19fLFiwwFhWXFyMxMREPPvss5g0aRI8PDzg4uICT09Pi+NvaB7W38DDx01N9e3bF3l5eZg1a1at7I+IiBqORnHDh7OzMwCgtLTUWKZUKgEABoPhvu+rqFNWVmYs++Mf/4i///3vGDduHJ599lls27atVmPt0qULNBqNMSlNT09HQUEBunTpYlIvPDwczs7Oxkt91a1XUxV9eXe/3b59G2q12qReWVkZlEplpTl+FXbs2IHk5GR88cUXcHNzM5ZfuHABRUVFeOaZZ2ol3oauqv6uyr3jhoiIyFIN9syfJXbv3o2nnnoKTZs2hUqlqjQnsMK7776LgoICq02SV6lUxrONOTk5AH69U/ZeHh4eyM/PN6ueNTz//PP49ttvsXPnThQXF+PEiRNITU3FCy+8UGXyt2XLFixatAiHDh1Cy5YtTbZdvXoVANC0aVOrxdtY3T1uiIiILGU3yd/ly5cxcOBA+Pj44Pjx48jNzcXixYsr1TMYDJg4cSISEhJw7Ngxk0uWtcFgMCAnJwf+/v4Afk3cAFSZvFlSzxrmzp2Lp59+GmPGjIFOp8OgQYMwbNiwKtfmW7FiBTZu3IiDBw+iefPmlbZXnEG8c+eO1eJtjO4dN0RERJZqFJd9qyMtLQ0GgwETJkxAcHAwgKqXF3njjTfw6quvYtCgQbh27Rrmz5+PXr16oVu3brUSx6FDhyAi6Nq1KwCgffv2cHV1xYkTJ0zqHT9+HCUlJejcubNZ9awhPT0dFy9eRGZmJpycqh4yIoJp06bh1q1bSE1NvW+99u3bw8HBAV999RXGjx9vtZgbm3vHDfDrvMCHXS4mIiK6l92c+QsICAAA7N+/H7dv38b58+crzZNLSkqCn58fBg0aBODXGxbCwsIwatQo5OXlWdRueXk5bt26hdLSUpw+fRqxsbEICAjAmDFjAPx6JiwuLg47duzAxo0bkZeXh7S0NIwfPx6+vr6Ijo42q541vP766wgICHjgY9rOnj2LJUuWYM2aNVAqlVAoFCavpUuXAvj1cu/gwYOxbds2rFu3Dnl5eTh9+nSNblhpjB42bgAgNDQU2dnZSE1NhcFgQGZmJn766adK+/L09MTPP/+MH3/8Efn5+TAYDNi7dy+XeiEisle2vNfY3KVeli1bJhqNRgBIy5Yt5ciRI7Jo0SJxd3cXAOLt7S2bNm2SLVu2iLe3twAQvV4vmzdvFhGRqVOniqenp3h4eMjQoUNl5cqVAkBCQkKkY8eOolAoxNPTU77++msREXnzzTfFwcFBAIi7u7ucOHHCrOOLjo4WpVIpfn5+4uTkJDqdTgYMGCAXL140qVdeXi7x8fHSqlUrUSqVotfrZeDAgXLu3Dmz6/3pT38yHrtWq5VBgwbJihUrxMfHRwCIRqOR/v37S1JSkrEvW7VqJRcvXpTVq1eLTqcTABIYGCg//PCDiIgcPHhQmjRpIgCML6VSKe3atZPt27eLiEhaWprJ9ntf8fHxxhjz8/PlD3/4gzRp0kRcXV3lySeflNmzZwsA8ff3l3//+99m9fOxY8eke/fu4uvra2zPx8dHIiIi5KuvvjJrX7Wx1EtN+7u64yYrK0siIyNFrVZLUFCQvPHGGzJlyhQBIKGhocZlYb777jsJDAwUFxcXefLJJ+XGjRuyZ88ecXNzkwULFtToWCvA9ksXEFmM45fqUj0Yb8mK/x+ITVQ88zUlJcVWIVjVuHHjkJKSgqysLFuHUiOrVq3C+fPnkZiYaCwrKSnBtGnTsGrVKty6dQsuLi42jLD2JCcnY/jw4TZ9RFxDHDcKhQJbt2596KLfRPURxy/VpXow3lLsZs6frdy9jExDdOPGDcTExODUqVMm5c7OzggICIDBYIDBYGg0yV990dDHDRER1V92M+evNnz//feV5rJV9YqKirJ1qLXGxcUFSqUS69atwy+//AKDwYCff/4Za9euxezZsxEVFQWdTlerbdpjPxMREdUVJn9maNu2LUTkoa8tW7bg7bffxvr165Gbm4ugoKBaXyy6rri7u+OLL77AmTNn0Lp1a7i4uCAsLAzr16/HokWL8PHHH9d6m+b0c2PTWMaNOfbv34/p06dj+/btCA4ONib3L730UqW6vXr1gpubGxwdHfHII4/gu+++s0HE5isvL0diYiIiIiLuW+dvf/sbwsPD4ebmhsDAQIwdOxY3btxolO3OmzcPYWFh0Ol0UKlUCA0NxVtvvVXlTWUPi+/TTz/F4sWLbXa2vDGPX4PBgNmzZyM4OBjOzs7w8/PD5MmTUVxcXC/2V8GexlutqdMphvew5Nm+RNZUW8/2tTewcALz7NmzpV+/fpKXl2csCwkJMd5gtGvXrkrv2bt3r7z44os1ircu/fDDD9K9e3cBcN/nTm/ZskUAyOLFiyUnJ0dOnjwpwcHB0rFjRzEYDI2u3Z49e0pSUpJkZWVJXl6ebN26VZRKpfTu3dui+JYtWyY9e/aUW7duWRQzx2/VJkyYIGq1WjZv3ix5eXny5Zdfik6nk5EjR9aL/YnY13irRclM/ojuwuTPMpZ8mb333nvSunVrKS4uNikPCQmRTZs2iYODg/j5+UlOTo7J9ob043nq1CkZNGiQbNy4UTp27HjfH6fIyEhp3ry5lJeXG8sqViM4evRoo2u3b9++UlpaalI2bNgwAWC8S93c+GJiYqRbt24WJa0cv5VdvHhRHBwc5I9//KNJ+cyZMwWAnD171qb7E7Gv8VbLknnZl4jq3IULFzBr1iy88847lZ4bDQARERGIjY3FtWvXMHnyZBtEWDsee+wxbN++HaNGjYJKpbpvvStXrsDX19dk4fkWLVoAQJVrNzb0dnft2lXp0ZBeXl4AgKKiIovimzt3Lk6dOoVly5aZHbe57GH8fvPNNygvL8cTTzxhUt67d28AwL59+2y6P8B+xps1MPkjojq3fPlyiAj69+9/3zoLFixA69atsXbtWuzfv/+B+xMRJCQkoF27dlCpVNDr9RgwYAC+//57Y51Vq1ZBq9VCo9Fg586d6NOnD3Q6Hfz9/bF582aT/ZWVlWH27NkICAiAi4sLHn30UWzdurVmB/0AwcHBlZ4lXjHPqOKJRI2p3apcu3YNLi4uCAoKsig+vV6Pnj17YtmyZVZfqskexq+Dw6/pwb0rObRq1QoA8J///Mem+6uphjTerIHJHxHVud27d6NNmzbQaDT3rePi4oKPPvoIDg4OePXVV1FYWHjfunPnzsX06dMxY8YMZGRk4PDhw7hy5Qp69OiBX375BQAwYcIEvPnmmyguLoabmxu2bt2KixcvIjg4GK+++qrJo/KmTZuGJUuWIDExEdevX0e/fv0wcuTISo9XrC1vv/02bty4gRUrViA/Px/p6elYtmwZnnvuOZNH+jWWdu9VVFSEgwcP4tVXX4Wzs7PF8T3++OO4du0a/v3vf1s1XnsYv23btgVQOSlr0qQJACAzM7Pa+7LG/mqioY03q7DlRWfO+aP6hnP+LAMz5rAUFBSIQqGQfv36Vbk9JCRELl26ZPx3XFycAJDXX39dRCrPmSoqKhJXV1eJiooy2c+//vUvASDz5s0zls2YMUMAmMzTSkpKEgBy4cIFEREpLi4WjUZjsr+ioiJRqVQyYcKEah1jVZ544on7zkkS+d/cp4qXv7+/XLlyxeL26nu7d5sxY4a0bt3a5MYJS+L78MMPBYD89a9/NStWjt+q9e7dWzw9PeXAgQNSXFws169fl+TkZFEoFPLCCy+YtS9r7O9ujXW8WYnt5/xt27atWmu68cVXXbyGDx8OADaPo6G9zJGRkQEReeBZk7stWLAAbdq0QVJSEo4ePVppe3p6OgoKCtClSxeT8vDwcDg7O1d6hve9Kv7nX3Hm5Ny5cygqKkL79u2NdVxcXODj42NyGa42zZgxA6tXr8aBAwdQUFCA//73v4iIiEC3bt1w5coVq7Rpy3bvtmPHDiQnJ2Pfvn1wc3OrUXwVY6ribJk12NP43bJlC4YOHYrf/e538PT0RPfu3fHJJ59ARIxn7Gy5P0s0tPFmLTZ/wkfXrl3x5ptv2joMIgDAsWPHsGzZMqvO72qMKpLm6rh9+zYAPHCC9t3UajXWr1+PJ598Er///e+xePFik+05OTkAAFdX10rv9fDwQH5+frVjA2C8PDdz5kzMnDnTZJuvr69Z+6qO69evY/HixZg+fTqefvppAEBQUBDWrFkDvV6P+Ph4LF++vNG0e7ctW7YgISEBhw4dQvPmzWscX8V8sooxZg32NH7d3d3xwQcfmJRdv34dmzdvrvR52WJ/5mqI481abJ78+fv783mKVK8sW7aMY9JM5iR/FV+Y5iyS2q1bN0yaNAlLly7F/PnzERAQYNzm4eEBAFX+SObk5MDf37/a7QBA06ZNAQCJiYmIjY01672WOH/+PMrKyir9GOl0Onh6eiI9Pb1RtVthxYoV2LdvHw4ePFhl4mNJfCUlJQAq31RQm+x9/H7zzTcAgMjIyHq5v/tpqOPNWmx+2ZeI7EuzZs2gUCiQm5tr1vvmz5+Ptm3b4uTJkybl7du3h6ura6XJ7MePH0dJSQk6d+5sVjstWrSAWq2u9Dxra6n4cb9+/bpJeX5+PrKzs41LTTSWdkUEU6dORVpaGlJTU6v8IbY0voox5e3tXctR/4+9j981a9YgKCgIPXv2rJf7u1dDH2/WwuSPiOqURqNBcHAwrl69atb7Ki6f3btel1qtRlxcHHbs2IGNGzciLy8PaWlpGD9+PHx9fREdHW12O2PHjsXmzZuxatUq5OXloaysDFevXjX+MERFRcHb27tWHs8VFBSEyMhIrFmzBocPH0ZxcTGuXLlijPuVV14x1m0M7Z49exZLlizBmjVroFQqK80fXbp0qdnxVagYUx06dKhxnPdjT+P3N7/5DX766SeUlpbixx9/xOTJk7F//36sW7fO5C5ZW+2vOhr6eLMaW95uwrt9qb7h3b6WgZl3r8XExIhSqZSioiJj2Y4dOyQkJEQAiJeXl/HuyHtNmTKl0hMSysvLJT4+Xlq1aiVKpVL0er0MHDhQzp07Z6yTlJQkGo1GAEirVq3k4sWLsnr1atHpdAJAAgMD5YcffhARkTt37sjUqVMlICBAnJycpGnTpjJ48GBJT08XEZGBAwcKAJk9e/YDj/PYsWPSvXt38fX1Nd496OPjIxEREfLVV18Z6928eVNiY2MlNDRUVCqVuLq6Svfu3eWTTz4x2V9jaDctLc3kbsp7X/Hx8WbHV6Fv377i5+dn8oSG6uD4rdpvf/tb8fDwECcnJ9Hr9dK3b1/55ptvKtWz1f7sZbxZAR/vRnQ3Jn+WMffL7Pz58+Lk5CQbNmywYlTWU1ZWJj169JB169ax3Xri5s2bolarZenSpWa/l+O3ce/PGupyvFmB7Zd6ISL7Exoainnz5mHevHkoKCiwdThmKSsrQ2pqKvLz8xEVFcV264m5c+eiY8eOiImJsXpbHL8NZ3/WUpfjzRoabfK3fft2BAcHG6/rz5o164H1ExISoFAo4ODggLZt2+Lw4cNWi0WhUECpVMLPzw+jRo2y6mNtli5dapygfPct9nv27IG7uzs+++wzq7U9b948hIWFQafTQaVSITQ0FG+99ZbJl2VVfaNQKODs7IxmzZrhqaeeQnx8PG7dumW1OMk2pk+fjqFDhyIqKsrsyfO2dOjQIWzfvh179+6t9lpvbNe6EhIScOrUKezZswdKpbJO2uT4bRj7swZbjLdaZ8vzjnVx2bdiDoaPj4+UlJRUWae0tFQCAwMFgDzzzDNWjcXd3V1Efl0l/tNPP5WAgABxdXWV77//3mrtnj9/XgDI+++/byzbtWuX6HQ6+fTTT63Wbs+ePSUpKUmysrIkLy9Ptm7dKkqlUnr37l2p7t19U15eLrdu3ZIvv/xSxowZIwqFQnx9faucG1LbeNnXMqjBZYx9+/bJ1KlTazkishepqamycOFCKS0ttXgfHL9UXbYeb7XEPi77du7cGTdu3EBqamqV27dv3w4/P786jUmr1aJfv37485//jIKCAqxYsaJO2+/bty9yc3PRr18/q7Xh6uqK6OhoeHp6ws3NDcOGDcPAgQPx+eefP/DpAQqFAh4eHnjqqaewfv16JCcn45dffjHG3NgVFxcjIiKiwbdRXb169cKiRYtsHQY1UC+++CKmT59e6S7ausLxa19sPd5qi10kfxMmTAAAvP/++1VuT0hIQFxcXF2GZPSb3/wGAHDmzBmbtF9bRAQpKSlYvXq1sWzXrl2V/kC8vLwA/Ppg7eoaMmQIxowZg4yMjEqrwzdG69atQ0ZGRoNvg4iI6ie7SP6efvpptGvXDl9++SXOnTtnsu0f//gHioqK0KtXryrfe+TIEYSFhcHd3R1qtRodOnTAvn37AAAfffQRXF1doVAooNfrkZqaihMnTiAwMBCOjo4YOXLkQ2MrLS0FYPqoIBFBQkIC2rVrB5VKBb1ejwEDBlR6LmN1693r6NGjCAgIgEKhwMqVKwEAq1atglarhUajwc6dO9GnTx/odDr4+/tj8+bNJu8vKyvDwoUL0aZNG7i4uMDLywtBQUFYuHDhQ5+Mce3aNbi4uCAoKOihfXO3MWPGAAD27t1r1vvqQnU+h5iYGDg7O8PHx8dY9tprr0Gr1UKhUODmzZsAgNjYWMTFxeHixYtQKBQIDQ3F8uXLoVar0axZM4wbNw6+vr5Qq9WIiIgwee5nTdoAgM8//xw6nQ7vvvuuVfuLiIhszJYXnetqzt+lS5fkz3/+swCQ2NhYk+0DBw6U9evXS35+fpVz/lJSUmTu3LmSnZ0tWVlZ0rVrV2nSpIlx+9mzZ0Wj0cjLL79sLJs+fbqsXbu2ylgq5rVV2LBhgwCQKVOmGMtmz54tzs7OsmHDBsnJyZHTp09Lp06dxMvLS27cuGF2varm/F25ckUAyIoVK4xlM2bMEABy4MAByc3NlYyMDOnRo4dotVqT+ZLvvvuuODo6ys6dO6WoqEi+/fZb8fb2lqeeeuq+n4OISGFhobi5uUlMTEy1+uZueXl5AkBatGjxwDZqypI5f9X9HEaNGiXe3t4m742PjxcAkpmZaSwbPHiwhISEmNSLjo4WrVYrZ8+eldu3b0t6erqEh4eLm5ubXL58uVba2LVrl7i5ucm8efPMOn6RejGHhchiHL9Ul+rBeLOPOX8A8PLLL0Or1eLjjz9GcXExAOC///0vvvnmmweeoRsyZAjmzJkDvV4PT09P9O/fH1lZWcjMzAQAtGvXDomJifj444+xadMmbN68GXfu3KlyNfC7FRYWYvv27Zg8eTKaNWuGiRMn4v+xd+9xUZb5//hfAzMwHGY4JAqBEAdNSc0tTcVcs7LVSBMUxUOl7ZpmRpoHNA+ZmZuHwIcK60dz3f3mrgLKYmtqrZm5bebmqiuL5YEWFU8gioCgDPD+/eGP2UYQGQ5zD9yv5+PBH15z3df9nvt+B+/uw3UBd57FSkhIQHR0NMaNGwcPDw907doV69atw9WrV823VevbryEiIiJgNBrh4+OD2NhY3Lx5E+fOnTN/npGRgccffxxDhw6Fi4sLHnvsMbz44os4cOCAea3D2ixduhR+fn5YsmSJ1TEZDAZoNBqrFzlvbs15Hu6m1WrNVxfDw8ORnJyM4uJibNq0qUnGj4yMRFFR0X3fjCciopZNNcWfh4cHxowZg+vXr2Pr1q0A7ix8PWXKFItlZe6n+rXuny/q/dprr2HEiBGYPHkyUlNTsXz58ntuf+PGDWg0Gnh4eOCtt97C888/j3/+85/mF06ysrJQUlKCHj16WGzXs2dPODk5mW/z1bdfY1UfG5PJZG67desW7vzPy/9UVlZCp9Pd8yHY9PR0pKam4vPPP4fBYLA6jps3b0JEYDQard62OdnqPNSmR48ecHV1ve9tfiIiop9TTfEH/O/Fj3Xr1qGwsBBpaWmYPHlyndt89tlneOqpp+Dj4wNnZ2fMnj271n4ffPABSkpK7vsQvYeHB0QEFRUVyM3Nxe9//3sEBQWZPy8sLASAWhef9vT0NF/5qm+/5vD888/jX//6F3bs2IGysjIcPnwYGRkZeOGFF2ot/rZu3YoPP/wQ+/fvx0MPPdSgfZ46dQoA0KlTp8aE3uSUPA/AnWdFq69CExER1Yeqir/u3bujd+/e+Oc//4lJkyYhJiYGXl5e9+x/7tw5REVFwdfXF4cOHcKNGzewbNmyGv1MJhPeeustJCQk4ODBgw26rVnN09MTAGotGgoLCxEQEGBVv+awaNEiPP300xg/fjyMRiOio6MxcuRIbNiwoUbfNWvWYPPmzdi3bx8efPDBBu9zz549AIDBgwc3eIzmoOR5MJlMzb4PIiJqfbRKB2BrU6ZMwXfffYdt27bh9OnTdfbNzMyEyWTClClTEBISAuDOHHR3e/PNNzFx4kRER0fjwoULeP/99/Hcc8+hT58+VsfXpUsXuLu74/Dhwxbthw4dQnl5OR5//HGr+jWHrKwsZGdnIz8/H1pt7SkkIpgzZw6uX7+OjIyMe/arj8uXLyMxMREBAQF49dVXGzxOc7DmPGi1Wovb5421f/9+iAh69+7dbPsgIqLWR1VX/gBg5MiRaNOmDaKioswF3b0EBgYCAPbu3Ytbt27h9OnTNZ7hSkpKgr+/P6KjowHceakhPDwcY8eORVFRkdXx6fV6zJgxA+np6di8eTOKioqQmZmJ119/HX5+fpg0aZJV/ZrD1KlTERgYWOealidOnMDy5cuxYcMG6HS6Gsu3rVy5ssY2IoKSkhJUVVVBRJCfn4+UlBT07dsXjo6OyMjIsLtn/qw5D2FhYbh27RoyMjJgMpmQn5+Ps2fP1hjT29sbFy9eRE5ODoqLi83FXFVVFa5fv46KigocP34c06ZNQ2BgoHkanMbuY/fu3ZzqhYhIDRR81bhZp3pJT083L+3Wpk0bmTp1qvmz2bNny7fffmv+9/z588XX11cAiIODg4SHh8vf//53ERGJj48Xb29v8fT0lJiYGFm7dq0AkNDQUOnevbtoNBrx9vY2jzd9+nRxcHAQAOLh4SGHDx+Wf/zjH9KxY0cBIADEz89PYmJi7hl7VVWVrFixQjp06CA6nU68vLwkKipKTp48aXW/jz76SNq1aycAxM3NTaKjo2XNmjXm7+vq6ipDhw6VpKQkcXV1FQDSoUMHyc7OlvXr14vRaBQAEhQUJKdOnRIRkX379skDDzxg/j4ARKfTSefOnWX79u0iIpKZmWnx+d0/K1asEBGRTz/9VLp16yaurq7i5ORkPnYajUY8PT3liSeekMWLF0tBQUFj0qHeGjLVS33PV/nJAnMAACAASURBVEFBgQwYMED0er0EBwfLm2++KbNmzRIAEhYWZp6y5ciRIxIUFCQuLi7y5JNPyuXLl2XSpEmi0+nE399ftFqtGI1GGTZsmGRnZzfZPnbt2iUGg0GWLFli9XGD8lMXEDUY85dsyQ7yLVXz/weiiJiYGABAWlqaUiFQAyQnJ+P06dNITEw0t5WXl2POnDlITk7G9evX4eLiomCEDZeamopRo0bVeJtZaZMnT0ZaWhoKCgqUDqVWGo0GKSkp953km8geMX/Jluwg39JU98wfNc7ly5cRFxeHY8eOWbQ7OTkhMDAQJpMJJpOpxRZ/9uzn0wsRERE1lOqe+aPGcXFxgU6nw8aNG3HlyhWYTCZcvHgRH3/8MRYuXIjY2Fi7ey6PiIiI/ofFH1nFw8MDX3zxBf7zn/+gY8eOcHFxQXh4ODZt2oQPP/wQf/zjH5UOsdV55513sGnTJty4cQPBwcHYtm2b0iEREVELxtu+ZLV+/frhb3/7m9JhqMbSpUuxdOlSpcMgIqJWglf+iIiIiFSExR8RERGRirD4IyIiIlIRFn9EREREKqL4Cx+5ublITU1VOgwiAMDBgwcBgDnZANXHjqglYv6Smii+wgenrSAiIiI1UXqFD0WLPyIiJdjrMn5ERDaQxmf+iIiIiFSExR8RERGRirD4IyIiIlIRFn9EREREKsLij4iIiEhFWPwRERERqQiLPyIiIiIVYfFHREREpCIs/oiIiIhUhMUfERERkYqw+CMiIiJSERZ/RERERCrC4o+IiIhIRVj8EREREakIiz8iIiIiFWHxR0RERKQiLP6IiIiIVITFHxEREZGKsPgjIiIiUhEWf0REREQqwuKPiIiISEVY/BERERGpCIs/IiIiIhVh8UdERESkIiz+iIiIiFSExR8RERGRirD4IyIiIlIRFn9EREREKsLij4iIiEhFWPwRERERqQiLPyIiIiIVYfFHREREpCIs/oiIiIhURKt0AEREzSk3NxevvPIKKisrzW3Xr1+HwWDAU089ZdH34Ycfxv/93//ZOEIiItti8UdErVpAQADOnj2L7OzsGp99/fXXFv/+5S9/aauwiIgUw9u+RNTqvfzyy9DpdPftFxsba4NoiIiUxeKPiFq9sWPHoqKios4+jzzyCMLDw20UERGRclj8EVGrFxoaim7dukGj0dT6uU6nwyuvvGLjqIiIlMHij4hU4eWXX4ajo2Otn1VUVCAmJsbGERERKYPFHxGpwujRo1FVVVWj3cHBAb1798ZDDz1k+6CIiBTA4o+IVMHPzw99+/aFg4Plrz0HBwe8/PLLCkVFRGR7LP6ISDVeeumlGm0igujoaAWiISJSBos/IlKNESNGWDz35+joiGeffRZt27ZVMCoiItti8UdEquHl5YWBAweaC0ARwbhx4xSOiojItlj8EZGqjBs3zvzih06nw7BhwxSOiIjItlj8EZGqDB06FM7OzgCAIUOGwN3dXeGIiIhsi8UfEamKm5ub+Wofb/kSkRppRESUDsKepaamYtSoUUqHQURERPXAsua+0rRKR9BSpKSkKB0C3SUxMREAMH36dIUjaTkOHjyIVatWqT6fKysrkZKSgjFjxigdSqvGfCNbqs43uj8Wf/U0cuRIpUOgu6SlpQHgubHWqlWreMwAREVFQa/XKx1Gq8d8I1ti8Vc/fOaPiFSJhR8RqRWLPyIiIiIVYfFHREREpCIs/oiIiIhUhMUfERERkYqw+LOB3/zmNzAYDNBoNDh27JjS4Shq8eLFCA8Ph9FohLOzM8LCwjB79myUlJQoFtOuXbvg4eGBv/71r4rFQEREZCss/mzg448/xoYNG5QOwy7s27cPU6dORU5ODq5evYqlS5di1apViImJUSwmTghKRERqwuKPrFZWVoaIiIgGbevu7o5JkybB29sbBoMBI0eORFRUFPbs2YPz5883caT1ExkZiRs3bmDIkCGK7P/nGnNsiYiI6oOTPNuIRqNROoQms3HjRuTl5TVo2507d9Zoa9OmDQCgtLS0UXG1Bo05tkRERPXBK3/NQESwYsUKPPzww3B2doaHhwdmzZpl0Wf58uVwdXWFwWBAXl4eZsyYAX9/f5w8eRIigoSEBHTu3BnOzs7w8vLCsGHD8OOPP5q3X716NfR6Pdq2bYvJkyfDz88Per0eEREROHToUI147jdeXFwcnJyc4Ovra25744034ObmBo1Gg6tXrwIApk2bhhkzZiA7OxsajQZhYWGNPl4XLlyAi4sLgoODGz2Wtb755hsEBgZCo9Fg7dq1AIDk5GS4ubnB1dUVO3bswODBg2E0GhEQEIAtW7aYt63vOWjssd2zZw+MRiM++OADWxwSIiJq7YTqlJKSItYepnnz5olGo5GPPvpIrl+/LqWlpZKUlCQA5OjRoxb9AMhbb70la9askejoaPnhhx9k4cKF4uTkJJ988okUFhbK8ePH5bHHHpM2bdrI5cuXzdtPmjRJ3Nzc5MSJE3Lr1i3JysqSnj17isFgkHPnzpn71Xe8sWPHSrt27Sy+y4oVKwSA5Ofnm9uGDx8uoaGhVh2Te7l586YYDAaJi4uzetsRI0bIiBEjGh3D+fPnBYCsWbPG3FZ9br788ku5ceOG5OXlSb9+/cTNzU3Ky8vN/ep7DhpzbHfu3CkGg0EWL17c6O/akHwmaijmG9kS863eUnnlr4mVlZUhMTERzz77LN5++214enrCxcUF3t7e99zmww8/xNSpU7F9+3YEBQUhISEB0dHRGDduHDw8PNC1a1esW7cOV69exfr16y221Wq15it64eHhSE5ORnFxMTZt2mSOx5rxbG3p0qXw8/PDkiVLFI3jXiIiImA0GuHj44PY2FjcvHkT586ds+hzv3PQWJGRkSgqKsKCBQuaZDwiIlI3PvPXxM6cOYPS0lI888wzDdo+KysLJSUl6NGjh0V7z5494eTkVOOW7t169OgBV1dX8y3dxo7XnNLT05GamoovvvgCBoNBsTjqy8nJCQBgMpnq7Hf3OSAiIrInLP6aWG5uLgDAx8enQdsXFhYCuPNW7N08PT1RXFx83zGcnZ2Rn5/fZOM1h61btyIhIQH79+/Hgw8+qEgMzenn54CIiMiesPhrYnq9HgBw+/btBm3v6ekJALUWZYWFhQgICKhze5PJZNGvseM1hzVr1uDzzz/Hvn37ai1KW7q7zwEREZE94TN/TaxLly5wcHDA119/3eDt3d3dcfjwYYv2Q4cOoby8HI8//nid2+/fvx8igt69e1s9nlarve8tzcYQEcTHxyMzMxMZGRmtsvADap4DoPmPLRERUX2x+GtiPj4+GD58OLZt24aNGzeiqKgIx48fr/eLFXq9HjNmzEB6ejo2b96MoqIiZGZm4vXXX4efnx8mTZpk0b+qqgrXr19HRUUFjh8/jmnTpiEwMBDjx4+3erywsDBcu3YNGRkZMJlMyM/Px9mzZ2vE6O3tjYsXLyInJwfFxcX1LmpOnDiB5cuXY8OGDdDpdNBoNBY/K1eurNc49uZ+5wBo3LHdvXs3p3ohIqImw+KvGfz+97/HhAkTEB8fD39/f7zxxhvo168fAGDIkCE4fvw4li9fjoSEBABAx44dsXnzZvP27777LpYuXYrFixejTZs26N+/Px566CHs378fbm5uFvu6desWunbtChcXF/Tr1w8dO3bEV199BWdnZ6vHmzJlCgYMGIDRo0fj4Ycfxvvvvw8XFxcAQJ8+fcwrcLz++uto27YtwsPD8fzzz+PatWv1Oi5ih8uorV27Fj179gQAxMfH48UXX0RycjISExMBAN26dcNPP/2EDRs2YMaMGQCAQYMG4fTp0+Yx6nMOmvvYEhER1ZdG7PEvsh1JTU3FqFGj7LJwmTx5MtLS0lBQUKB0KIqoXg84LS1NsRha2jmw53ym1of5RrbEfKu3NF75a+EqKyuVDkH1eA6IiKglYfFHjfLjjz/WeHavtp/Y2FilQ6UmsHfvXsydOxfbt29HSEiI+fy+9NJLNfo+99xzMBgMcHR0xCOPPIIjR44oEHH9mUwmLFy4ECEhIXBycoK/vz9mzpyJsrIyuxivWlVVFRITExEREVHr54sXL0Z4eDiMRiOcnZ0RFhaG2bNno6SkpEbfP//5z+jZsycMBgOCgoIwYcIEXL582fz5p59+imXLlin2PzjMN+XGq6amfFMVpdYWaSnsdbmYuXPnipOTkwCQhx56SNLS0pQOyeaaanm3hmqJ56Ax+bxw4UIZMmSIFBUVmdtCQ0PlgQceEACyc+fOGtvs3r1bXnzxxQbHa0tTpkwRvV4vW7ZskaKiIvnqq6/EaDTKmDFj7GI8EZFTp05J3759BYA8+uijtfbp37+/JCUlSUFBgRQVFUlKSorodDoZNGiQRb+tW7cKAFm2bJkUFhbK0aNHJSQkRLp37y4mk8ncb9WqVdK/f3+5fv261fEy3+6N+WZf+aYyqTxK98Fksl9KF38tUUPz+be//a107NhRysrKLNpDQ0PlT3/6kzg4OIi/v78UFhZafN5S/hhnZ2eLg4ODvPbaaxbt8+fPFwBy4sQJRccTETl27JhER0fL5s2bpXv37vf8YxwZGSkVFRUWbSNHjhQAFutNDxgwQB588EGpqqoyt61du1YAyDfffGOxfVxcnPTp08fij3R9MN9qx3y7w17yTYW4ti8R1e3MmTNYsGAB3nvvPfMk5j8XERGBadOm4cKFC5g5c6YCETbe999/j6qqKvTq1cuifdCgQQCAzz//XNHxAODRRx/F9u3bMXbsWIs3ye+2c+dOODo6WrS1adMGAFBaWmpuO3/+PPz8/KDRaMxt7du3B4Aa0xAtWrQIx44dw6pVq6yO21rMN+abLfNNrVj8EVGdVq9eDRHB0KFD79lnyZIl6NixIz7++GPs3bu3zvFEBAkJCejcuTOcnZ3h5eWFYcOGWayFnJycDDc3N7i6umLHjh0YPHgwjEYjAgICsGXLFovxKisrsXDhQgQGBsLFxQXdunVDSkqKVd/RweHOr8Lq6XeqdejQAQDwww8/KDpeY124cAEuLi4IDg42t4WEhCAvL8+iX/XzVyEhIRbtXl5e6N+/P1atWtXsb1Iy35hvtsw3tWLxR0R1+uyzz/Dwww/D1dX1nn1cXFzwhz/8AQ4ODpg4cSJu3rx5z76LFi3C3LlzMW/ePOTl5eHAgQM4f/48+vXrhytXrgC4My/i9OnTUVZWBoPBgJSUFGRnZyMkJAQTJ060mFh8zpw5WL58ORITE3Hp0iUMGTIEY8aMqbGqTV06deoEoOYfyQceeAAArF6nuanHa4zS0lLs27cPEydOhJOTk7n9nXfeweXLl7FmzRoUFxcjKysLq1atwq9+9SuL1Wmq/eIXv8CFCxfw73//u1njZb4x3wDb5ZtqKXnTuSXgMwT2i8/8Wc/afC4pKRGNRiNDhgyp9fPQ0FD573//a/73jBkzBIBMnTpVRGo+g1VaWiru7u4SGxtrMc4///lPASCLFy82t82bN08AWDz3lZSUJADkzJkzIiJSVlYmrq6uFuOVlpaKs7OzTJkypd7fU0Rk0KBB4u3tLV9++aWUlZXJpUuXJDU1VTQajbzwwgtWjdUc4/1cr1697vkM1t3mzZsnHTt2tHhxolr1M2HVPwEBAXL+/Plax/n9738vAOT//b//V+84mW/3xnxTPt9ULFVr21Kz5UpNTVU6BLpLbm4uAJ4baxw8eNCq/nl5eRCROq/C/NySJUuwc+dOJCUlYdSoUTU+z8rKQklJCXr06GHR3rNnTzg5OeHQoUN1jl99JaH6SszJkydRWlqKLl26mPu4uLjA19fX4rZefWzduhXx8fF4+eWXce3aNfj5+aFXr14QEfMVFCXHa4j09HSkpqbiiy++gMFgsPhs3rx5+Pjjj/Hll1+iV69eyMvLw5w5c9CnTx98++235uexqlXnQPXVsubAfGO+VbNFvqkZi796qu0XC9kHnpvmc+vWLQCo84Hvn9Pr9di0aROefPJJvPrqq1i2bJnF54WFhQAAd3f3Gtt6enqiuLjYqviqb/fNnz8f8+fPt/jMz8/PqrE8PDywbt06i7ZLly5hy5YtePDBB60aqznGs9bWrVuRkJCA/fv319jfpUuXsGzZMsydOxdPP/00ACA4OBgbNmyAl5cXVqxYgdWrV1tsU/08WXVONAfmG/Otmi3yTc34zF89iQh/7OxnxIgRGDFihOJxtKQfax9Mr/4FbM2kq3369MHbb7+N06dP4/3337f4zNPTEwBq/aNbWFiIgIAAq+Lz8fEBACQmJtb4rtZe5azN999/DwAYMGBAo8dqjvHuZc2aNdi8eTP27dtX6x/+06dPo7KyssZnRqMR3t7eyMrKqrFNeXk5gJovFTQl5hvzrZot8k3NWPwR0T21bdsWGo0GN27csGq7999/H506dcLRo0ct2rt06QJ3d/caD8cfOnQI5eXlePzxx63aT/v27aHX63Hs2DGrtquvDRs2IDg4GP3797fL8e4mIoiPj0dmZiYyMjJqveIFwFz0XLp0yaK9uLgY165dq3ELDoA5B9q1a9fEUf8P8435Vs0W+aZmLP6I6J5cXV0REhJifr6yvqpvx909/5der8eMGTOQnp6OzZs3o6ioCJmZmXj99dfh5+eHSZMmWb2fCRMmYMuWLUhOTkZRUREqKyuRm5tr/kMTGxuLdu3a3Xe5ryeeeAJnz55FRUUFcnJyMHPmTOzduxcbN260eGtRqfHq48SJE1i+fDk2bNgAnU5XY5nFlStXArhzy23AgAHYsGEDDhw4gLKyMpw/f958/H/961/XGLs6B7p27droOO+F+cZ8q2aLfFM1oTrx7SH7xbd9rdeQfI6LixOdTielpaXmtvT0dAkNDRUA0qZNG/PblnebNWtWjRUXqqqqZMWKFdKhQwfR6XTi5eUlUVFRcvLkSXOfpKQkcXV1FQDSoUMHyc7OlvXr14vRaBQAEhQUJKdOnRIRkdu3b0t8fLwEBgaKVqsVHx8fGT58uGRlZYmISFRUlACQhQsX1vk9Bw4cKJ6enqLVasXLy0siIyPl+++/r9FPqfEOHjwoffv2FT8/P/Pbkr6+vhIRESFff/21iIhkZmZavE1598+KFSvM4129elWmTZsmYWFh4uzsLO7u7tK3b1/5y1/+Uuv+IyMjxd/f32KFhvthvt0b880+8k2luLzb/TCZ7BeLP+s1JJ9Pnz4tWq1WPvnkk2aKqnlVVlZKv379ZOPGjaoYrzlcvXpV9Hq9rFy50qrtmG+tf7zmYMt8Uyku70ZEdQsLC8PixYuxePFilJSUKB2OVSorK5GRkYHi4mLExsa2+vGay6JFi9C9e3fExcU1+76Yby1nvOZiy3xTKxZ/RHRfc+fORUxMDGJjY61+GF9J+/fvx/bt27F79+56zx3XksdrDgkJCTh27Bh27doFnU5nk30y31rGeM1BiXxTI42IcOG8OqSmpmLUqFFoqsO0fft2zJo1C//9738t2nU6HTw9PREeHo7IyEj85je/gZeXV5Pss7WKiYkBAKSlpSkcScvR2Hz+4osvsG/fPnz44YdNHBnZox07duDEiROYPXt2jZcp6oP5RtZQOt9UJI1X/mxs+PDh+OmnnxAaGgoPDw+ICKqqqpCXl4fU1FQEBwcjPj4ejzzyiFVrRRLZwnPPPcc/xCry4osvYu7cuQ36Q9wUmG/qonS+qQmLPzug0Wjg6emJp556Cps2bUJqaiquXLmCyMjIFnXL417KysoQERGhdBjNwhbfrTUfPyIisj0Wf3ZoxIgRGD9+PPLy8mos19MSbdy4EXl5eUqH0Sxs8d1a8/EjIiLbY/Fnp8aPHw8A2L17NwBg+fLlcHV1hcFgQF5eHmbMmAF/f3+cPHkSIoKEhAR07twZzs7O8PLywrBhwywWGl+9ejX0ej3atm2LyZMnw8/PD3q9HhERETUWN6/PeHFxcXBycoKvr6+57Y033oCbmxs0Gg2uXr0KAJg2bRpmzJiB7OxsaDQahIWFNdchq5fm/m71Pc6NPX579uyB0WjEBx980KzHi4iIWiGlJplpKZpr3qDQ0FDx8PC45+dFRUUCQNq3b29umzdvngCQt956S9asWSPR0dHyww8/yMKFC8XJyUk++eQTKSwslOPHj8tjjz0mbdq0kcuXL5u3nzRpkri5ucmJEyfk1q1bkpWVJT179hSDwSDnzp0z96vveGPHjpV27dpZxL1ixQoBIPn5+ea24cOHS2hoaKOOV20aMs+fLb5bfY9zY/axc+dOMRgMsnjxYqu+P+fBIltivpEtMd/qjfP82SuDwQCNRlPrguQffvghpk6diu3btyMoKAgJCQmIjo7GuHHj4OHhga5du2LdunW4evUq1q9fb7GtVqs1X/UKDw9HcnIyiouLsWnTJgB3ni+zZryWxJbf7X7HubEiIyNRVFSEBQsWNMl4RESkHiz+7NTNmzchIjAajXX2y8rKQklJCXr06GHR3rNnTzg5OdW4pXu3Hj16wNXV1Xzbs7Hj2TMlv9vdx5mIiEgpLP7s1KlTpwAAnTp1qrNfYWEhAMDd3b3GZ56enrVeObybs7Mz8vPzm2w8e6X0d/v5cSYiIlIKiz87tWfPHgDA4MGD6+zn6ekJALUWLoWFhQgICKhze5PJZNGvsePZMyW/293HmYiISCks/uzQ5cuXkZiYiICAALz66qt19u3SpQvc3d1rTAh96NAhlJeX4/HHH69z+/3790NE0Lt3b6vH02q1MJlM1nw1RSn53e4+zs2xDyIiovpg8acgEUFJSQmqqqogIsjPz0dKSgr69u0LR0dHZGRk3PeZP71ejxkzZiA9PR2bN29GUVERMjMz8frrr8PPzw+TJk2y6F9VVYXr16+joqICx48fx7Rp0xAYGGieWsaa8cLCwnDt2jVkZGTAZDIhPz8fZ8+erRGjt7c3Ll68iJycHBQXFytW8Njyu93vODd2H7t37+ZUL0RE1DCKvmzcAjT1q+OffvqpdOvWTVxdXcXJyUkcHBwEgGg0GvH09JQnnnhCFi9eLAUFBRbbLVu2TFxcXMzTv3zyySfmz6qqqmTFihXSoUMH0el04uXlJVFRUXLy5EmLMSZNmiQ6nU78/f1Fq9WK0WiUYcOGSXZ2tkW/+o5XUFAgAwYMEL1eL8HBwfLmm2/KrFmzBICEhYWZpzU5cuSIBAUFiYuLizz55JMWU6o0RkOmerHFd6vvcW7MPnbt2iUGg0GWLFli1ffnVAhkS8w3siXmW72lakS4AnJdWtNC0ZMnT0ZaWhoKCgqUDqVJxMTEAADS0tIUjsSSPR/n1pTPZP+Yb2RLzLd6S+NtX5WprKxUOgRV4HEmIiJ7xeKPiIiISEVY/KnEO++8g02bNuHGjRsIDg7Gtm3blA6pVeJxJiIie6dVOgCyjaVLl2Lp0qVKh9Hq8TgTEZG945U/IiIiIhVh8UdERESkIiz+iIiIiFSExR8RERGRivCFj3qqnlCY7Md3330HgOfGGrm5uQB4zMg2mG9kS9X5RvfHFT7u4+DBg0hISFA6DCJqQpcvX8bRo0cxePBgpUMhoiZmb6s+2aE0Fn9EpDpcBoqIVIzLuxERERGpCYs/IiIiIhVh8UdERESkIiz+iIiIiFSExR8RERGRirD4IyIiIlIRFn9EREREKsLij4iIiEhFWPwRERERqQiLPyIiIiIVYfFHREREpCIs/oiIiIhUhMUfERERkYqw+CMiIiJSERZ/RERERCrC4o+IiIhIRVj8EREREakIiz8iIiIiFWHxR0RERKQiLP6IiIiIVITFHxEREZGKsPgjIiIiUhEWf0REREQqwuKPiIiISEVY/BERERGpCIs/IiIiIhVh8UdERESkIiz+iIiIiFSExR8RERGRirD4IyIiIlIRFn9EREREKsLij4iIiEhFtEoHQETUnEwmE0pKSizabt68CQC4fv26RbtGo4Gnp6fNYiMiUgKLPyJq1a5duwZ/f39UVlbW+Mzb29vi3wMGDMC+fftsFRoRkSJ425eIWrV27drhl7/8JRwc6v51p9FoMHr0aBtFRUSkHBZ/RNTqvfTSS/ft4+joiOjoaBtEQ0SkLBZ/RNTqDR8+HFrtvZ9ycXR0xKBBg/DAAw/YMCoiImWw+COiVs9oNGLw4MH3LABFBOPGjbNxVEREymDxR0SqMG7cuFpf+gAAJycnvPDCCzaOiIhIGSz+iEgVXnjhBbi6utZo1+l0iIqKgpubmwJRERHZHos/IlIFvV6P6Oho6HQ6i3aTyYSxY8cqFBURke2x+CMi1RgzZgxMJpNFm9FoxMCBAxWKiIjI9lj8EZFqPPvssxYTO+t0OowePRpOTk4KRkVEZFss/ohINbRaLUaPHm2+9WsymTBmzBiFoyIisi0Wf0SkKqNHjzbf+m3Xrh2efPJJhSMiIrItFn9EpCoRERHw9/cHALz88sv3XfaNiKi1ufeU92QTubm5+Pbbb5UOg0hVevbsiQsXLuCBBx5Aamqq0uEQqcrIkSOVDkH1NCIiSgehZqmpqRg1apTSYRAREdkEyw7FpfHKn53gfwz3FxMTAwBIS0tTOJKWo/p/LphfNW3btg0jRoxQOoxWhflGdeHFDvvBh12ISJVY+BGRWrH4IyIiIlIRFn9EREREKsLij4iIiEhFWPwRERERqQiLPyIiIiIVYfHXCty+fRtvvfUWfH194erqimeffRZt27aFRqPBunXrlA7P7uzatQseHh7461//qnQoRERENsd5/lqBjz76CHv27MGPP/6I1NRUeHt7o3v37ujQoYPSodklzkFGRERqxit/rUBGRgZ69OgBT09PvPbaaw2ev6ysrAwRERH3bWvpIiMjcePGDQwZMkTpUFrl8SUiIvvG4q8VyM3NhU6na/Q4GzduRF5e3n3bqOnw+BIRka2x+GvB/va3vyEsLAyXLl3CH//4R2g0Gri7VS4xqQAAIABJREFUu9+z/9///neEh4fDw8MDer0eXbt2xeeffw4AmDZtGmbMmIHs7GxoNBqEhYXV2gYAlZWVWLhwIQIDA+Hi4oJu3bohJSUFAJCcnAw3Nze4urpix44dGDx4MIxGIwICArBly5bmPyj38c033yAwMBAajQZr164FUP+YV69eDb1ej7Zt22Ly5Mnw8/ODXq9HREQEDh06ZO4XFxcHJycn+Pr6mtveeOMNuLm5QaPR4OrVqwBqP+YAsGfPHhiNRnzwwQe2OCRERKQyLP5asIEDB+LMmTNo164dXnnlFYgISkpK7tn/ypUrGDVqFHJycnDx4kW4u7tj7NixAIBVq1ZhyJAhCA0NhYjgzJkztbYBwJw5c7B8+XIkJibi0qVLGDJkCMaMGYPDhw9jypQpmD59OsrKymAwGJCSkoLs7GyEhIRg4sSJMJlMNjk29/Lkk0/i22+/tWirb8xxcXEYP348SktL8dZbbyEnJwdHjhxBRUUFBg4ciPPnzwO4UySOHDnSYh9JSUl47733LNrudXwrKysBAFVVVc1yDIiISN1Y/KnIiBEj8O6778LLywve3t4YOnQoCgoKkJ+fX+8xbt26heTkZERFRWH48OHw9PTE/PnzodPpsGnTJou+ERERMBqN8PHxQWxsLG7evIlz58419ddqUvWJWavVonPnznB2dkZ4eDiSk5NRXFxc4/s3VGRkJIqKirBgwYImGY+IiOjnWPypWPVzgtVXmurj5MmTKC0tRZcuXcxtLi4u8PX1xY8//njP7ZycnABA8St/1qhvzD169ICrq2ud35+IiMhesPhTkc8++wxPPfUUfHx84OzsjNmzZ1s9xs2bNwEA8+fPh0ajMf+cPXsWpaWlTR1yi+Hs7GzVFVQiIiKlsPhTiXPnziEqKgq+vr44dOgQbty4gWXLllk9jo+PDwAgMTERImLxc/DgwaYOu0UwmUwoLCxEQECA0qEQERHdFyd5VonMzEyYTCZMmTIFISEhAACNRmP1OO3bt4der8exY8eaOsQWa//+/RAR9O7d29ym1Wpb1C1uIiJSD175U4nAwEAAwN69e3Hr1i2cPn3aYnoSAPD29sbFixeRk5OD4uJimEymGm2Ojo6YMGECtmzZguTkZBQVFaGyshK5ubm4dOmSEl/N5qqqqnD9+nVUVFTg+PHjmDZtGgIDAzF+/Hhzn7CwMFy7dg0ZGRkwmUzIz8/H2bNna4xV2zHfvXs3p3ohIqLmI6SolJQUaehpyMnJkV/84hcCQLRarTz22GOybds2+eijj6Rdu3YCQNzc3CQ6OlpEROLj48Xb21s8PT0lJiZG1q5dKwAkNDRUzp07J0eOHJGgoCBxcXGRJ598Ui5fvlxr2+3btyU+Pl4CAwNFq9WKj4+PDB8+XLKysiQpKUlcXV0FgHTo0EGys7Nl/fr1YjQaBYAEBQXJqVOnGvR9R4wYISNGjGjQttXWrFkjvr6+AkBcXV1l6NChVsU8adIk0el04u/vL1qtVoxGowwbNkyys7Mt9lNQUCADBgwQvV4vwcHB8uabb8qsWbMEgISFhcm5c+dERGo9vrt27RKDwSBLlixp1HcVaVx+EVmL+UZ1YX7YjVSNCBc6VVJqaipGjRrF9WbrISYmBgCQlpamWAyTJ09GWloaCgoKFIvBGswvsiXmG9WF+WE30njbl8hK1kyNQ0REZG9Y/BHRPe3duxdz587F9u3bERISYp7a56WXXqrR97nnnoPBYICjoyMeeeQRHDlyRIGI689kMmHhwoUICQmBk5MT/P39MXPmTJSVldnFeNWqqqqQmJiIiIiIWj9fvHgxwsPDYTQa4ezsjLCwMMyePbvW1X7+/Oc/o2fPnjAYDAgKCsKECRNw+fJl8+effvopli1bptj/4LTmfKt2v/MJ3FmGsm/fvnB1dYWfnx/i4+Nx+/Ztiz7Lli1Dp06d4OLiAjc3N3Tq1AkLFixAUVFRjfFMJhOWLl2KsLAwODk5wdPTE126dEFOTo5FP3vPD2pCSt50Jj4DYY2meOavMebOnStOTk4CQB566CFJS0tTLJb6akx+LVy4UIYMGSJFRUXmttDQUHnggQcEgOzcubPGNrt375YXX3yxwfHa0pQpU0Sv18uWLVukqKhIvvrqKzEajTJmzBi7GE9E5NSpU9K3b18BII8++mitffr37y9JSUlSUFAgRUVFkpKSIjqdTgYNGmTRb+vWrQJAli1bJoWFhXL06FEJCQmR7t27i8lkMvdbtWqV9O/fX65fv251vMy3utXnfP7nP/8RFxcXWbBggZSUlMi3334rbdq0kQkTJlj0i4yMlJUrV0peXp4UFxdLamqq6HQ6GThwYI0xo6Ki5OGHH5bvvvtOTCaTXLx4UYYOHSqZmZnmPvaeH9SkUnkWFMb/GOpP6eKvJWpofv32t7+Vjh07SllZmUV7aGio/OlPfxIHBwfx9/eXwsJCi89byh/j7OxscXBwkNdee82iff78+QJATpw4oeh4IiLHjh2T6Oho2bx5s3Tv3v2exUJkZKRUVFRYtI0cOVIAmF8sEhEZMGCAPPjgg1JVVWVuq37p65tvvrHYPi4uTvr06WPxR78+mG/3Vt/zOWrUKAkODrY4TytWrBCNRiM//PCDuS0qKqrG8YqJiREAcvHiRXPbli1bRKPRyPHjx+uMz57zg5pcKm/7EpGFM2fOYMGCBXjvvfeg1+trfB4REYFp06bhwoULmDlzpgIRNt7333+Pqqoq9OrVy6J90KBBAIDPP/9c0fEA4NFHH8X27dsxduxYODs737Pfzp074ejoaNHWpk0bALBYdef8+fPw8/OzmN+zffv2AFBjGqJFixbh2LFjWLVqldVxW0sN+QbU73xWVFTgs88+Q//+/S3O0+DBgyEi2LFjh7ktPT29xvHy9/cHAItb/r/73e/w2GOPoWvXrnXGZ6/5Qc2DxR8RWVi9ejVEBEOHDr1nnyVLlqBjx474+OOPsXfv3jrHExEkJCSgc+fOcHZ2hpeXF4YNG2axFnJycjLc3Nzg6uqKHTt2YPDgwTAajQgICMCWLVssxqusrMTChQsRGBgIFxcXdOvWDSkpKVZ9RweHO7/6XFxcLNo7dOgAAPjhhx8UHa+xLly4ABcXFwQHB5vbQkJCkJeXZ9Gv+nmu6onfq3l5eaF///5YtWpVs7+ZqYZ8q6+ffvoJJSUl5nlZq4WGhgIAjh8/Xuf2p0+fhqenJ4KCggAA5eXl+O6779C9e/f77tte84OaB4s/IrLw2Wef4eGHH4arq+s9+7i4uOAPf/gDHBwcMHHiRPOaz7VZtGgR5s6di3nz5iEvLw8HDhzA+fPn0a9fP1y5cgUAMGXKFEyfPh1lZWUwGAxISUlBdnY2QkJCMHHiRIvVUubMmYPly5cjMTERly5dwpAhQzBmzBgcPny43t+xU6dOAGoWZQ888AAAWL1Oc1OP1xilpaXYt28fJk6cCCcnJ3P7O++8g8uXL2PNmjUoLi5GVlYWVq1ahV/96lcWq9NU+8UvfoELFy7g3//+d7PGq4Z8q6/qYstgMFi06/V6uLi4mOP/OZPJhAsXLmDt2rXYu3cv1qxZYz7vFy9eRHl5Of71r39hwIAB8PPzg16vR+fOnZGUlGRRuNlrflDzYPFHRGY3b97Ef//7X/OVhrr06dMH06dPR05ODubMmVNrn7KyMiQkJCA6Ohrjxo2Dh4cHunbtinXr1uHq1atYv359jW0iIiJgNBrh4+OD2NhY3Lx5E+fOnQMA3Lp1C8nJyYiKisLw4cPh6emJ+fPnQ6fTYdOmTfX+nl27dsWgQYOQlJSEffv24datW7h8+TLS09Oh0WisXpqvqcdrjKVLl8LPzw9LliyxaO/fvz/i4+MRFxcHo9GILl26oLi4GB9//HGt41RftczMzGy2WNWSb/VV/Ubv3bfxAUCn09X65nj79u0REBCARYsWYfny5Rg1apT5s+rbvz4+Pvjggw+QlZWFK1euYNiwYZg6dSr+/Oc/m/vaY35Q8+HavnaiegJjurfvvvsOAI+VNXJzc63qn5eXBxGp8yrMzy1ZsgQ7d+5EUlKSxR+dallZWSgpKUGPHj0s2nv27AknJ6caSwzerfoKRnXxdPLkSZSWlqJLly7mPi4uLvD19bW4rVcfW7duRXx8PF5++WVcu3YNfn5+6NWrF0TEfMVOyfEaIj09Hampqfjiiy9qXD2aN28ePv74Y3z55Zfo1asX8vLyMGfOHPTp0wfffvut+fmuatU5UNvVpqaipnyrj+pn+CoqKmp8Vl5eXuOxAuDOs3qFhYU4evQo5s6di/Xr12Pfvn1o27at+dnCRx55xGJqmffeew+/+93vsH79eowdOxaAfeYHNR9e+SMis1u3bgFAnS8Y/Jxer8emTZug0Wjw6quv1rgyUVhYCABwd3evsa2npyeKi4utiq/6dt/8+fPNc8BpNBqcPXvW4uWG+vDw8MC6deuQm5uL0tJSZGdn46OPPgIAPPjgg1aN1RzjWWvr1q348MMPsX//fjz00EMWn126dAnLli3Da6+9hqeffhpubm4IDg7Ghg0bcPHiRaxYsaLGeNWFRnVONAc15Vt9+Pr6AkCNufpKS0tx69Yt+Pn51dhGp9PBx8cHzz33HLZu3YqsrCwsXboUAMz9r169arGNk5MTgoKCkJ2dDcB+84OaD6/82QkllyxrKexhebeWpno5pfqq/oVuzSSuffr0wdtvv42VK1fi/ffft3hY3dPTEwBq/aNbWFiIgICAeu8HuHP7CgASExMxbdo0q7atj++//x4AMGDAALsc717WrFmDzz//HPv27au18Dl9+jQqKytrFKFGoxHe3t7IysqqsU15eTmAmi+xNCW159vdgoODYTAYarxde+bMGQBAt27d6tw+LCwMjo6O5vPp7u6ODh064MSJEzX6VlRUwMPDA4D95gc1H175IyKztm3bQqPR4MaNG1Zt9/7776NTp044evSoRXuXLl3g7u5e4+H4Q4cOoby8HI8//rhV+2nfvj30ej2OHTtm1Xb1tWHDBgQHB6N///52Od7dRATx8fHIzMxERkZGrYUfAHPRc+nSJYv24uJiXLt2rcYtPQDmHGjXrl0TR/0/as+3u2m1Wjz//PM4cOAAqqqqzO27d++GRqMxvxFdUFCAMWPG1Ni+uoj7+fkcNWoUjh49ip9++sncVlpairNnz5qnf7HX/KDmw+KPiMxcXV0REhJi9bOC1bfj7n5QXa/XY8aMGUhPT8fmzZtRVFSEzMxMvP766/Dz88OkSZOs3s+ECROwZcsWJCcno6ioCJWVlcjNzTX/4YqNjUW7du3uu9zXE088gbNnz6KiogI5OTmYOXMm9u7di40bN1q8JavUePVx4sQJLF++HBs2bIBOp7O4NanRaLBy5UoAd64oDRgwABs2bMCBAwdQVlaG8+fPm4//r3/96xpjV+fA/eaHaww15Vt9LViwAFeuXMG7776Lmzdv4uDBg1ixYgXGjx+Phx9+GADg5uaGL774Avv27UNRURFMJhOOHj2KV155BW5ubnj77bfN47399tsICgrC+PHjce7cORQUFCA+Ph5lZWXmF2fsNT+oGSkytzSZccbz+uMKH9ZrSH7FxcWJTqeT0tJSc1t6erqEhoYKAGnTpo1MnTq11m1nzZpVY8WFqqoqWbFihXTo0EF0Op14eXlJVFSUnDx50twnKSlJXF1dBYB06NBBsrOzZf369WI0GgWABAUFyalTp0RE5Pbt2xIfHy+BgYGi1WrFx8dHhg8fLllZWSJyZ+UDALJw4cI6v+fAgQPF09NTtFqteHl5SWRkpHz//fc1+ik13sGDB6Vv377i5+cnAASA+Pr6SkREhHz99dciIpKZmWn+rLafFStWmMe7evWqTJs2TcLCwsTZ2Vnc3d2lb9++8pe//KXW/UdGRoq/v7/Fig/3w3y7t/qcz2pff/21PPHEE+Ls7Cx+fn4ya9YsuXXrlkWfoUOHSnBwsLi7u4uzs7OEhoZKbGysxZJt1c6fPy+jR48WLy8vcXZ2lieeeEJ2795t0cde84OaBZd3Uxr/Y6g/Fn/Wa0h+nT59WrRarXzyySfNFFXzqqyslH79+snGjRtVMV5zuHr1quj1elm5cqVV2zHf1MGW+UHNgsu7EZGlsLAwLF68GIsXL7ZYJqolqKysREZGBoqLixEbG9vqx2suixYtQvfu3REXF9fs+2K+tTy2zA9qHiz+Wpjt27cjJCSkxrM9P/+pnuZh5cqV5geq161bp2zg1KLMnTsXMTExiI2NtfphfCXt378f27dvx+7du+s9d1xLHq85JCQk4NixY9i1axd0Op1N9sl8azmUyA9qeiz+Wpjhw4fjp59+QmhoKDw8PCAiEBFUVFSgtLQUV65cMf8SmjlzJr799luFI6aW6oMPPkBcXBx++9vfKh1KvT3zzDP405/+ZJ4vrbWP19R27NiB27dvY//+/fDy8rLpvplv9k/J/KCmxeKvlXB0dISLiwvatm2Ljh07NmqssrIyi9ng79WmRrY4DvZ0rJ977jl8+OGHSodBNvLiiy9i7ty5tS4vZgvMN/umdH5Q02Hx1wplZGQ0avuNGzciLy/vvm1qZIvjwGNNRETNicWfCv39739HeHg4PDw8oNfr0bVrV3z++ecAgGnTpmHGjBnIzs6GRqNBWFhYrW3AnYedFy5ciMDAQLi4uKBbt25ISUkBACQnJ8PNzQ2urq7YsWMHBg8eDKPRiICAAGzZssVm31VEkJCQgM6dO8PZ2RleXl4YNmyYxbqccXFxcHJysrh188Ybb8DNzQ0ajca8NFJtx2H16tXQ6/Vo27YtJk+eDD8/P+j1ekRERFisI9qYfQDAnj17YDQa8cEHHzTr8SIiotaPxV8rsm/fPvOkrnW5cuUKRo0ahZycHFy8eBHu7u7mxb1XrVqFIUOGIDQ0FCKCM2fO1NoGAHPmzMHy5cuRmJiIS5cuYciQIRgzZgwOHz6MKVOmYPr06SgrK4PBYEBKSgqys7MREhKCiRMnmhdOb26LFi3C3LlzMW/ePOTl5eHAgQM4f/48+vXrZ16QfPXq1Rg5cqTFdklJSXjvvfcs2mo7DnFxcRg/fjxKS0vx1ltvIScnB0eOHEFFRQUGDhyI8+fPN3ofwP+Wv/r5rP9EREQNweKvBbtx44bFW77PPPNMvbYbMWIE3n33XXh5ecHb2xtDhw5FQUEB8vPz673vW7duITk5GVFRURg+fDg8PT0xf/586HQ6bNq0yaJvREQEjEYjfHx8EBsbi5s3b+LcuXNWfdeGKCsrQ0JCAqKjozFu3Dh4eHiga9euWLduHa5evYr169c32b60Wq356mJ4eDiSk5NRXFxc41g0VGRkJIqKirBgwYImGY+IiNSLxV8L9vO3fUUEX331VYPGqX5d35rF1U+ePInS0lJ06dLF3Obi4gJfX1+LW6p3q17myhZX/rKyslBSUoIePXpYtPfs2RNOTk4Wt2WbWo8ePeDq6lrnsSAiIlICi79W5KmnnsLMmTPv2++zzz7DU089BR8fHzg7O2P27NlW7+vmzZsAgPnz51tcfTx79ixKS0utHq85FBYWAkCti917enqiuLi4Wffv7Oxs1dVUIiIiW2DxpzLnzp1DVFQUfH19cejQIdy4cQPLli2zehwfHx8AQGJiosXVRxHBwYMHmzrsBvH09ASAWou8wsJCBAQENNu+TSZTs++DiIioIbRKB0C2lZmZCZPJhClTpiAkJAQAoNForB6nffv20Ov1OHbsWFOH2GS6dOkCd3d3HD582KL90KFDKC8vx+OPP25u02q1TXorev/+/RAR9O7du9n2QURE1BC88qcygYGBAIC9e/fi1q1bOH36dI1n37y9vXHx4kXk5OSguLgYJpOpRpujoyMmTJiALVu2IDk5GUVFRaisrERubi4uXbqkxFerQa/XY8aMGUhPT8fmzZtRVFSEzMxMvP766/Dz88OkSZPMfcPCwnDt2jVkZGTAZDIhPz8fZ8+erTFmbccGuPMW7vXr11FRUYHjx49j2rRpCAwMxPjx45tkH7t37+ZUL0RE1DSEFJWSkiLWnIZ//OMf0rFjRwEgAMTX11eeeeaZWvt+9NFH0q5dOwEgbm5uEh0dLSIi8fHx4u3tLZ6enhITEyNr164VABIaGirnzp2TI0eOSFBQkLi4uMiTTz4ply9frrXt9u3bEh8fL4GBgaLVasXHx0eGDx8uWVlZkpSUJK6urgJAOnToINnZ2bJ+/XoxGo0CQIKCguTUqVNWHasRI0bIiBEjrNqmqqpKVqxYIR06dBCdTideXl4SFRUlJ0+etOhXUFAgAwYMEL1eL8HBwfLmm2/KrFmzBICEhYXJuXPnRERqPQ6TJk0SnU4n/v7+otVqxWg0yrBhwyQ7O7vJ9rFr1y4xGAyyZMkSq76/tflF1BjMN6oL88NupGpERJQpOwkAUlNTMWrUKPA03F9MTAwAIC0tTeFILE2ePBlpaWkoKChQOpQamF9kS8w3qgvzw26k8bYvUROwZpocIiIiJbH4IyIiIlIRFn9EjfDOO+9g06ZNuHHjBoKDg7Ft2zalQyIiIqoTp3ohaoSlS5di6dKlSodBRERUb7zyR0RERKQiLP6IiIiIVITFHxEREZGKsPgjIiIiUhEWf0REREQqwrd97YRGo1E6hBaDx8p6PGZkS8w3IvvG4k9hERERSElJUToMIlU5ePAgVq1axf/2iEiVuLYvEakO1xglIhXj2r5EREREasLij4iIiEhFWPwRERERqQiLPyIiIiIVYfFHREREpCIs/oiIiIhUhMUfERERkYqw+CMiIiJSERZ/RERERCrC4o+IiIhIRVj8EREREakIiz8iIiIiFWHxR0RERKQiLP6IiIiIVITFHxEREZGKsPgjIiIiUhEWf0REREQqwuKPiIiISEVY/BERERGpCIs/IiIiIhVh8UdERESkIiz+iIiIiFSExR8RERGRirD4IyIiIlIRFn9EREREKsLij4iIiEhFWPwRERERqQiLPyIiIiIVYfFHREREpCIs/oiIiIhUhMUfERERkYqw+CMiIiJSEa3SARARNaf8/Hz85S9/sWg7fPgwAGD9+vUW7QaDAaNHj7ZZbEREStCIiCgdBBFRc7l9+zbatm2LkpISODo6AgCqf+1pNBpzP5PJhFdeeQV/+MMflAiTiMhW0njbl4haNWdnZ4wYMQJarRYmkwkmkwkVFRWoqKgw/9tkMgEAxowZo3C0RETNj8UfEbV6Y8aMQXl5eZ19PD098fTTT9soIiIi5bD4I6JWb8CAAfDx8bnn5zqdDuPGjYNWy8egiaj1Y/FHRK2eg4MDxo4dC51OV+vnJpOJL3oQkWqw+CMiVRg9erT52b67Pfjgg+jTp4+NIyIiUgaLPyJShSeeeAJBQUE12p2cnPDKK69YvPlLRNSasfgjItV46aWXatz6LS8v5y1fIlIVFn9EpBpjx46tces3LCwMXbt2VSgiIiLbY/FHRKrRqVMnhIeHm2/x6nQ6TJgwQeGoiIhsi8UfEanKyy+/bF7po6Kigrd8iUh1WPwRkaqMHj0alZWVAIDHHnsMwcHBCkdERGRbLP6ISFUCAwPRq1cvAMArr7yicDRERLbH6exbsYSEBBw8eFDpMIjszu3bt6HRaPDFF1/gwIEDSodDZHfefvttzn3ZivHKXyt28OBBfPfdd0qHYVdyc3Oxbds2pcNocbZt24bc3Fylw2gyAQEBaNeuHfR6vdKhtAqtLT/Ubtu2bTh//rzSYVAz4pW/Vq53795IS0tTOgy7kZqailGjRvGYWEmj0WD69OkYOXKk0qE0mTNnziAsLEzpMFqF1pgfasYJz1s/XvkjIlVi4UdEasXij4iIiEhFWPwRERERqQiLPyIiIiIVYfFHREREpCIs/qhefvOb38BgMECj0eDYsWNKh6O4Xbt2/X/s3XtcVHX+P/DXAAPDDAwMgoAgyC2vmJm0irrm2s1cTUAT01qt9adZIUaG98y8hPhFviqs6yV2H2oGpOnmpVr1a+VD18e26mJYXijFa9zkDnJ7//5omW0aRAaBAeb1fDzmDz/nc87nfT6fA7w958znAycnJ3z66afmDoWIiMgkTP6oSbZu3YotW7aYO4x2Q0TMHQIREVGzcJ4/omYYM2YMioqKzB0GAKCiogKjRo3CiRMnzB0KERF1ALzzR03GiT/bp23btiEnJ8fcYRARUQfB5I8aJCKIj49Hz549YWdnBycnJ8ybN8+oXm1tLZYuXQofHx/Y29ujf//+SE1NBQAkJydDo9FArVZj3759GD16NLRaLby9vbFr1y6D43z55Zd47LHHoFarodVqERwcjOLi4vu2YQ7Hjx+Hj48PFAoFNm7cCKDp57p+/XqoVCp07doVs2bNgqenJ1QqFUJDQ3Hq1Cl9vaioKNja2sLDw0Nf9tprr0Gj0UChUCAvLw8AEB0djZiYGGRlZUGhUOgnLv7ss8+g1WqxcuXKtugSIiLqQJj8UYOWLFmC2NhYzJw5Ez/99BNu376N+fPnG9WbP38+1qxZg3Xr1uHWrVsYO3YsXnjhBXzzzTeYPXs25s6di4qKCjg6OiI1NRVZWVnw9/fHjBkzUF1dDQAoKyvDuHHjMGHCBBQUFODSpUt46KGHUFVVdd82zGHYsGFGj1ibeq5RUVGYNm0aysvLMWfOHFy5cgWnT59GTU0NnnzySf16muvXrzdaKispKQnvvvuuQVliYiLGjh2LgIAAiAguX74M4OeEGQDq6upapQ+IiKjjYvJHRioqKrBu3To88cQTePPNN+Hs7Ax7e3u4uLgY1KusrERycjLCwsIQEREBZ2dnLF68GEqlEikpKQZ1Q0NDodVq4ebmhsjISJSVlSE7OxsAcOXKFRQXF6Nv375QqVRwd3fH7t274erqalIb7UVj51rPxsYGvXv3hp2dHfr06YPnF3RmAAAgAElEQVTk5GSUlJS02DmNGTMGxcXFWLJkSYscj4iIOg8mf2Tk8uXLKC8vx6hRoxqtd+HCBZSXl6Nfv376Mnt7e3h4eOD777+/5362trYAoL8b5u/vj65du2Lq1KlYtmwZrly58sBttBe/Ptd7GTRoENRqdYc4JyIi6tiY/JGR69evAwDc3NwarVdWVgYAWLx4MRQKhf5z9epVlJeXN7k9e3t7HD16FMOGDcPKlSvh7++PyMhIVFRUtFgbHYGdnR1yc3PNHQYREXVyTP7IiEqlAgDcvXu30Xr1yeG6desgIgafkydPmtRm37598emnn+LmzZuIjY1Famoq1q5d26JttGfV1dUoLCyEt7e3uUMhIqJOjskfGenXrx+srKzw5ZdfNlqve/fuUKlUD7zix82bN3H+/HkAPyeUq1evxsCBA3H+/PkWa6O9O3bsGEQEgwcP1pfZ2Njc93ExERGRqZj8kRE3NzdERETg448/xrZt21BcXIyMjAxs3rzZoJ5KpcL06dOxa9cuJCcno7i4GLW1tbh+/Tpu3brV5PZu3ryJWbNm4fvvv0dVVRXOnDmDq1evYvDgwS3WRntTV1eHO3fuoKamBhkZGYiOjoaPjw+mTZumrxMYGIiCggLs3bsX1dXVyM3NxdWrV42O5eLigps3b+LKlSsoKSlBdXU1Dh06xKleiIioYUKd1oQJE2TChAnN2rekpET++Mc/SpcuXcTBwUGGDRsmS5cuFQDi7e0t//73v0VE5O7duxIbGys+Pj5iY2Mjbm5uEhERIZmZmZKUlCRqtVoASFBQkGRlZcnmzZtFq9UKAPH19ZWLFy/KlStXJDQ0VHQ6nVhbW0u3bt1k0aJFUlNTc982TJWamioPetlv2LBBPDw8BICo1WoZN25ck89VRGTmzJmiVCrFy8tLbGxsRKvVyvjx4yUrK8ugnfz8fBk5cqSoVCrx8/OTN954Q+bNmycAJDAwULKzs0VE5PTp0+Lr6yv29vYybNgwuX37thw8eFAcHR1lxYoVD3Su9QBIampqixyLOh9eH50Lx7PTS1OIcJHSzmrixIkAgPT0dDNH0n6kpaVh0qRJZl2bd9asWUhPT0d+fr7ZYjCVQqFAamqq0dyDRACvj86G49nppfOxL5EZ1E/CTERE1NaY/BERERFZECZ/RG1o4cKFSElJQVFREfz8/PDxxx+bO6RWd/jwYSxYsAC7d++Gv7+/fq7GF1980ajuU089BUdHR1hbW6Nv3744ffq0GSI2XV1dHdatW4fQ0NB71jl+/DiGDh0KtVoNT09PxMbGGk2nFBcXh169esHe3h4ajQa9evXCkiVL9Otc/1J1dTVWrVqFwMBA2NrawtnZGf369TOYJB0APvzwQ4SEhMDR0RG+vr6YPn06bt++rd/+t7/9DXFxcWa7G83rA1i+fDn69OkDrVYLOzs7BAYG4u2330ZpaalR3fY+ntRBmPmlQ2pFD/KFj86qJb7wYYnQzBfAly5dKmPHjpXi4mJ9WUBAgHTp0kUAyP79+432OXTokDz33HMPFG9bunjxogwdOlQAyMMPP9xgnW+//Vbs7e1lyZIlUlpaKidOnBBXV1eZPn26Qb0xY8bI2rVrJScnR0pKSiQtLU2USqU8+eSTRscMCwuTnj17yj/+8Q+prq6Wmzdvyrhx4+TcuXP6Oh999JEAkLi4OCksLJQzZ86Iv7+/DBgwQKqrq/X1EhMTZcSIEXLnzp1m9QGvj3tryvUxYsQISUpKkvz8fCkuLpbU1FRRKpXyzDPPGNRr7+NJHUYa/wp2Ykz+jDH5a57m/DFYvXq1PPTQQ1JRUWFQHhAQIDt37hQrKyvx8vKSwsJCg+0d6Y/72bNnJTw8XHbs2CEDBgy45x/3SZMmiZ+fn9TV1enL4uPjRaFQyHfffacvCwsLM+qviRMnCgC5efOmvmzXrl2iUCgkIyOj0fhGjhwp3bp1M2h348aNAkCOHz9uUDcqKkqGDBlikEQ0Fa+PhjX1+hgzZox+doN6zz//vADQf6tfpH2PJ3UoaXzsS0Qt7vLly1iyZAneffdd/YoxvxQaGoro6GjcuHEDb731lhkibBkPP/wwdu/ejSlTpsDOzq7BOjU1NThw4ABGjBgBhUKhLx89ejREBPv27dOX7dmzx6i/vLy8AMDgEeCf/vQnDBw4EMHBwY3Gd+3aNXh6ehq02717dwAwmjNy2bJlOHv2LBITExs9Zkvg9WFo//79sLa2NihzdXUFAINlLNvreFLHw+SPiFrc+vXrISIYN27cPeusWLECDz30ELZu3YrDhw83ejwRQUJCAnr37g07OzvodDqMHz8e33//vb5OcnIyNBoN1Go19u3bh9GjR0Or1cLb2xu7du0yOF5tbS2WLl0KHx8f2Nvbo3///khNTX2wk76HH374AaWlpfDx8TEoDwgIAABkZGQ0uv+lS5fg7OwMX19fAEBVVRX+8Y9/YMCAAfdt29/fHzk5OQZl9e+H+fv7G5TrdDqMGDECiYmJrT4VEq+P+7tx4wbs7e3h5+enL2uv40kdD5M/ImpxBw4cQM+ePaFWq+9Zx97eHn/5y19gZWWFGTNmoKys7J51ly1bhgULFmDRokXIycnBV199hWvXrmH48OH46aefAACzZ8/G3LlzUVFRAUdHR6SmpiIrKwv+/v6YMWOGwVJ58+fPx5o1a7Bu3TrcunULY8eOxQsvvIBvvvmm5TrhP+r/ODs6OhqUq1Qq2Nvb6+P/perqaty4cQMbN27E4cOHsWHDBtja2gL4eUWcqqoq/Otf/8LIkSPh6ekJlUqF3r17IykpyeAP/cKFC3H79m1s2LABJSUlyMzMRGJiIp5++mmDpQTrPfLII7hx4wb+/e9/t2QXGOH10bjy8nIcPXoUM2bM0I870H7HkzoeJn9E1KLKysrw448/6u9sNWbIkCGYO3curly5gvnz5zdYp6KiAgkJCQgPD8fUqVPh5OSE4OBgbNq0CXl5eUbLDgI/PzbUarVwc3NDZGQkysrKkJ2dDQCorKxEcnIywsLCEBERAWdnZyxevBhKpRIpKSkPdvINqP9G768f6wGAUqlERUWFUXn37t3h7e2NZcuWYc2aNZg0aZJ+W/3jXzc3N6xcuRKZmZn46aefMH78eLz++uv48MMP9XVHjBiB2NhYREVFQavVol+/figpKcHWrVsbjDUoKAgAcO7cueaf8H3w+ri/VatWwdPTEytWrDAob4/jSR0Tk79O7uOPP9ZPncCPQv9H1NxxdLSPKXJyciAijd7V+aUVK1agZ8+eSEpKwvHjx422Z2ZmorS0FIMGDTIoDwkJga2tLU6dOtXo8evvnNTf2blw4QLKy8vRr18/fR17e3t4eHgYPCZsKfXvtNXU1Bhtq6qqgr29vVH5tWvXkJOTgw8//BB//etf8cgjj+gf99W/O9a3b1+EhobCxcUFTk5OePfdd+Hk5GSQ7CxatAibN2/GkSNHUFpaih9++AGhoaEYMmQIrl27ZtRu/Zg1dDeypfD6aNyePXuQlpaGzz//3OhucXscT+qYbMwdALWuwYMHY+7cueYOo904efIkEhMT2/z9nY7ul3ee7qeyshIAGn3B/ZdUKhVSUlIwbNgwvPzyy4iLizPYXlhYCABwcHAw2tfZ2RklJSVNjg2A/vHh4sWLsXjxYoNtnp6eJh2rKTw8PADAaK6+8vJyVFZWNtimUqmEm5sbnnrqKfj5+eGhhx7CqlWrkJiYqK+fl5dnsI+trS18fX2RlZUFALh16xbi4uKwYMEC/O53vwMA+Pn5YcuWLdDpdIiPj8f69esNjlGfiNaPYWvg9XFvH330ERISEnDs2DF069bNYFt7HU/qmJj8dXLe3t5cn/FXEhMT2ScmMiX5q/+DY8oks0OGDMGbb76JtWvX4r333jP4coSzszMANPhHvLCwEN7e3k1uB/j5cSkArFu3DtHR0Sbt2xx+fn5wdHQ0+jbm5cuXAQD9+/dvdP/AwEBYW1sjMzMTwM9JTlBQEM6fP29Ut6amBk5OTgB+/qJIbW2tURKh1Wrh4uKiP94vVVVVAUCDdyNbCq+Phm3YsAGff/45jh492mAi217HkzomPvYlohbVtWtXKBQKFBUVmbTfe++9h169euHMmTMG5f369YODg4PRy/anTp1CVVUVHn30UZPa6d69O1QqFc6ePWvSfs1lY2ODZ599Fl999RXq6ur05YcOHYJCodB/4zU/Px8vvPCC0f71f/Trp/QAfk7Gz5w5gx9++EFfVl5ejqtXr+qnf6lPem7dumVwvJKSEhQUFBgcr179mLm7uzf3dO+L14chEUFsbCzOnTuHvXv3Npj4Ae13PKljYvJHRC1KrVbD398f169fN2m/+sd7v/5ihEqlQkxMDPbs2YMdO3aguLgY586dw6uvvgpPT0/MnDnT5HamT5+OXbt2ITk5GcXFxaitrcX169f1f1gjIyPh7u7eYsuHLVmyBD/99BPeeecdlJWV4eTJk4iPj8e0adPQs2dPAIBGo8EXX3yBo0ePori4GNXV1Thz5gz+8Ic/QKPR4M0339Qf780334Svry+mTZuG7Oxs5OfnIzY2FhUVFfovRvj5+WHkyJHYsmULvvrqK1RUVODatWv6/nrllVeM4qwfs/vNH/ggeH0YOn/+PNasWYMtW7ZAqVQavW+7du1aAO13PKmDMtPs0tQGuMKHMa7w0Twwccb/qKgoUSqVUl5eri/bs2ePBAQECABxdXWV119/vcF9582bZ7SCQ11dncTHx0tQUJAolUrR6XQSFhYmFy5c0NdJSkoStVotACQoKEiysrJk8+bNotVqBYD4+vrKxYsXRUTk7t27EhsbKz4+PmJjYyNubm4SEREhmZmZIvLzShsAZOnSpY2e58mTJ2Xo0KHi6ekpAASAeHh4SGhoqHz55ZcGdb/88kt57LHHxM7OTjw9PWXevHlSWVlpUGfcuHHi5+cnDg4OYmdnJwEBARIZGWmwZFu9a9euyeTJk0Wn04mdnZ089thjcujQIYM6eXl5Eh0dLYGBgWJnZycODg4ydOhQ+eSTTxo8nzFjxoiXl5fBChJNweujYU25Ps6dO6ff1tAnPj5ef7z2Op7U4XB5t86MyZ8xJn/NY+ofg0uXLomNjY1s3769FaNqPbW1tTJ8+HDZtm2buUNpM3l5eaJSqWTt2rUm78vro/1py/GkDofLuxFRywsMDMTy5cuxfPlyg2XJOoLa2lrs3bsXJSUliIyMNHc4bWbZsmUYMGAAoqKiWr0tXh+try3HkzoeJn+kt3v3bvj7+xu9c2Jra4uuXbvi8ccfR3x8PO7cuWPuUKkDWLBgASZOnIjIyEiTX+43p2PHjmH37t04dOhQk+ei6+gSEhJw9uxZHDx4EEqlsk3a5PXReswxntSxMPkjvYiICPzwww8ICAiAk5MTRAR1dXXIyclBWloa/Pz8EBsbi759+7bZMkfUsa1cuRJRUVFYvXq1uUNpslGjRmHnzp36+fk6u3379uHu3bs4duwYdDpdm7bN66PlmXM8qeNg8keNUigUcHZ2xuOPP46UlBSkpaXhp59+wpgxYzrU/9bbk4qKCoSGhnb4Nprqqaeewvvvv2/uMOgennvuOSxYsKDB5efaAq+PlmXu8aSOgckfmWTChAmYNm0acnJysGnTJnOH0yFt27ZNv1RXR26DiIg6JiZ/ZLJp06YB+HmS2nq1tbVYunQpfHx8YG9vj/79++uXUEtOToZGo4Farca+ffswevRoaLVaeHt7Y9euXQbH/vLLL/HYY49BrVZDq9UiODhYvyxWY220JhFBQkICevfuDTs7O+h0OowfP95gnc+oqCjY2toaPAp67bXXoNFooFAo9EtxRUdHIyYmBllZWVAoFAgMDMT69euhUqnQtWtXzJo1C56enlCpVAgNDTVYl/RB2gCAzz77DFqtFitXrmzV/iIionbO3N83ptbT3KleAgICxMnJ6Z7bi4uLBYB0795dX/bWW2+JnZ2dfPzxx3Lnzh1ZuHChWFlZyT//+U8REVm0aJEAkCNHjkhRUZHk5OTI8OHDRaPRSFVVlYiIlJaWilarlbi4OKmoqJDbt29LeHi45ObmNqmNpmjOVC9Lly4VW1tb2b59uxQWFkpGRoYMHDhQXF1d5fbt2/p6U6ZMEXd3d4N94+PjBYD+HEREIiIiJCAgwKDezJkzRaPRyPnz56WyslIyMzMlJCREHB0dJTs7u0Xa2L9/vzg6Osry5ctNOn8RTv1AjeP10blwPDs9TvVCpnN0dIRCodCvpVlZWYnk5GSEhYUhIiICzs7OWLx4MZRKJVJSUgz2DQ0NhVarhZubGyIjI1FWVobs7GwAwJUrV1BcXIy+fftCpVLB3d0du3fvhqurq0lttKSKigokJCQgPDwcU6dOhZOTE4KDg7Fp0ybk5eVh8+bNLdaWjY2N/u5inz59kJycjJKSkhY7vzFjxqC4uBhLlixpkeMREVHHxOSPTFZWVgYRgVarBQBcuHAB5eXl6Nevn76Ovb09PDw8DB6N/pqtrS0AoLq6GgDg7++Prl27YurUqVi2bBmuXLmir9vcNh5UZmYmSktLMWjQIIPykJAQ2NraGjyWbWmDBg2CWq1u1fMjIiLLw+SPTHbx4kUAQK9evQD8nAwCwOLFiw3mB7x69SrKy8ubfFx7e3scPXoUw4YNw8qVK+Hv74/IyEhUVFS0WBumKiwsBIAGF1t3dnbW3/1sLXZ2dsjNzW3VNoiIyLIw+SOTffbZZwCA0aNHAwDc3NwAAOvWrYOIGHxOnjxp0rH79u2LTz/9FDdv3kRsbCxSU1Oxdu3aFm3DFM7OzgDQYJJXWFgIb2/vVmu7urq61dsgIiLLw+SPTHL79m2sW7cO3t7eePnllwEA3bt3h0qlwtmzZx/o2Ddv3sT58+cB/JxQrl69GgMHDsT58+dbrA1T9evXDw4ODkaTWp86dQpVVVV49NFH9WU2Njb6R9gt4dixYxARDB48uNXaICIiy8PkjxokIigtLUVdXR1EBLm5uUhNTcXQoUNhbW2NvXv36t/5U6lUmD59Onbt2oXk5GQUFxejtrYW169fx61bt5rc5s2bNzFr1ix8//33qKqqwpkzZ3D16lUMHjy4xdowlUqlQkxMDPbs2YMdO3aguLgY586dw6uvvgpPT0/MnDlTXzcwMBAFBQXYu3cvqqurkZubi6tXrxod08XFBTdv3sSVK1dQUlKiT+bq6upw584d1NTUICMjA9HR0fDx8dFPrfOgbRw6dIhTvRAREad66cxMnerlb3/7m/Tv31/UarXY2tqKlZWVABCFQiHOzs7y2GOPyfLlyyU/P99o37t370psbKz4+PiIjY2NuLm5SUREhGRmZkpSUpKo1WoBIEFBQZKVlSWbN28WrVYrAMTX11cuXrwoV65ckdDQUNHpdGJtbS3dunWTRYsWSU1NzX3baKrmTPVSV1cn8fHxEhQUJEqlUnQ6nYSFhcmFCxcM6uXn58vIkSNFpVKJn5+fvPHGGzJv3jwBIIGBgfopW06fPi2+vr5ib28vw4YNk9u3b8vMmTNFqVSKl5eX2NjYiFarlfHjx0tWVlaLtXHw4EFxdHSUFStWmHT+Ipz6gRrH66Nz4Xh2emkKERGzZZ7UqiZOnAgASE9PN3Mk7UdaWhomTZqE9nbZz5o1C+np6cjPzzd3KA1SKBRITU3F888/b+5QqB3i9dG5cDw7vXQ+9iVqJ2pra80dAhERWQAmf0REREQWhMkfkZktXLgQKSkpKCoqgp+fHz7++GNzh0RERJ2YjbkDILJ0q1atwqpVq8wdBhERWQje+SMiIiKyIEz+iIiIiCwIkz8iIiIiC8Lkj4iIiMiC8Asfndz169eRlpZm7jDajZMnTwIA+6QZ6vuOqCG8Pog6Dq7w0YlNnDiR04YQEZHJuMJHp5bO5I+ILE57XeaPiKgNcHk3IiIiIkvC5I+IiIjIgjD5IyIiIrIgTP6IiIiILAiTPyIiIiILwuSPiIiIyIIw+SMiIiKyIEz+iIiIiCwIkz8iIiIiC8Lkj4iIiMiCMPkjIiIisiBM/oiIiIgsCJM/IiIiIgvC5I+IiIjIgjD5IyIiIrIgTP6IiIiILAiTPyIiIiILwuSPiIiIyIIw+SMiIiKyIEz+iIiIiCwIkz8iIiIiC8Lkj4iIiMiCMPkjIiIisiBM/oiIiIgsCJM/IiIiIgvC5I+IiIjIgjD5IyIiIrIgTP6IiIiILAiTPyIiIiILwuSPiIiIyIIw+SMiIiKyIEz+iIiIiCwIkz8iIiIiC2Jj7gCIiFrT9evX8Yc//AG1tbX6sjt37sDR0RGPP/64Qd2ePXviz3/+cxtHSETUtpj8EVGn5u3tjatXryIrK8to25dffmnw79/+9rdtFRYRkdnwsS8RdXovvfQSlErlfetFRka2QTRERObF5I+IOr0pU6agpqam0Tp9+/ZFnz592igiIiLzYfJHRJ1eQEAA+vfvD4VC0eB2pVKJP/zhD20cFRGReTD5IyKL8NJLL8Ha2rrBbTU1NZg4cWIbR0REZB5M/ojIIkyePBl1dXVG5VZWVhg8eDB69OjR9kEREZkBkz8isgienp4YOnQorKwMf+1ZWVnhpZdeMlNURERtj8kfEVmMF1980ahMRBAeHm6GaIiIzIPJHxFZjAkTJhi892dtbY0nnngCXbt2NWNURERti8kfEVkMnU6HJ598Up8AigimTp1q5qiIiNoWkz8isihTp07Vf/FDqVRi/PjxZo6IiKhtMfkjIosybtw42NnZAQDGjh0LBwcHM0dERNS2mPwRkUXRaDT6u3185EtElkghImLuIMwpLS0NkyZNMncYRERE1AYsPO0BgHQbc0fQXqSmppo7BKJ2Zd26dQCAuXPnmjmSlldbW4vU1FS88MILLXrckydPIjExkb9POgmOZ+dSP54EMPn7j+eff97cIRC1K+np6QA6789GWFgYVCpVix83MTGx0/aZJeJ4di5M/n7Gd/6IyCK1RuJHRNQRMPkjIiIisiBM/oiIiIgsCJM/IiIiIgvC5I+IiIjIgjD5M1FISAisra0xYMCANm97+vTpUKlUUCgUqKysbPP226O1a9eia9euUCgU2LRpk7784MGDcHJywqefftqq7bdVO81RWVmJXr16YfHixWaNoz33ERGRJWLyZ6J//vOfGDlypFnaTklJwVtvvWWWtturt956CydOnDAqb6tJPNvzZKGLFi3ChQsXzB1Gu+4jIiJLxHn+mkmhUDzwMSoqKjBq1KgGkxd6MGPGjEFRUVGLHrOh8WqNdlrCiRMn8O2335o7DADtq4/4M0dExDt/zaZUKh/4GNu2bUNOTk6z9m2J5JNM8yDj1ZYqKiowb948TmbagI4yhkRErYnJXzNdvnwZvXr1gkajgb29PYYPH47jx48b1Pn666/Rp08fODk5QaVSITg4GJ9//jkAIDo6GjExMcjKyoJCoUBgYKB+v+3bt2PQoEFQqVTQaDTo0aMH3nvvPf12KysrHDhwAKNHj4aTkxM8PT3xwQcfmHwOycnJ0Gg0UKvV2LdvH0aPHg2tVgtvb2/s2rXLoK6IICEhAb1794adnR10Oh3Gjx+P77//Xl9nzZo1UKvVcHR0RE5ODmJiYuDl5YVXX30VGo0GVlZWePTRR+Hu7g6lUgmNRoOBAwdi+PDh6N69O1QqFZydnfH22283uR8bcvz4cfj4+EChUGDjxo0Afh4vhULR4Ofvf/97s8aroXaa2lem9L2pFi1ahNdeew1ubm4PdJyW0FAfNfXc169fD5VKha5du2LWrFnw9PSESqVCaGgoTp06pa8XFRUFW1tbeHh46Mtee+01aDQaKBQK5OXlAbj3z9xnn30GrVaLlStXtkWXEBGZn1i41NRUMbUbRo0aJf7+/vLjjz9KdXW1fPvtt/Kb3/xGVCqVXLx4UV8vPT1dli1bJgUFBZKfny+DBw+WLl266LdHRERIQECAwbHXrVsnAGT16tWSn58vBQUF8uc//1mmTJkiIiKLFi0SAHLkyBEpLCyUgoICefbZZ8XOzk7KyspMPv9fHq+oqEhycnJk+PDhotFopKqqSl9v6dKlYmtrK9u3b5fCwkLJyMiQgQMHiqurq9y+fdvoeHPmzJENGzZIeHi4fPfdd/LOO+8IADl16pSUlZVJXl6ePPPMMwJADhw4ILm5uVJWViZRUVECQM6ePdvkfrx06ZIAkD/96U/6smvXrgkA2bBhg77O/Pnz9X1069Yt0el0EhoaKrW1tc0er1+305y+ul/fm+L48eMybtw4ERHJzc0VALJo0aJmHWvChAkyYcKEZu37Sw31UVPPfebMmaLRaOT8+fNSWVkpmZmZEhISIo6OjpKdna2vN2XKFHF3dzdoNz4+XgBIbm6uvqyhMdy/f784OjrK8uXLH/hcm/P7hNovjmfnwvHUS+Odv2ZydHREjx49YGNjg759+2LLli2orKzE5s2b9XUmTJiAd955BzqdDi4uLhg3bhzy8/ORm5vb4DGrq6vx7rvvYuTIkZg/fz5cXFyg0+nwyiuvICQkxKBuaGgonJycoNPpEBkZibt37+LHH39s9vmEhoZCq9XCzc0NkZGRKCsrQ3Z2NoCfHyMmJCQgPDwcU6dOhZOTE4KDg7Fp0ybk5eUZnHO9999/H6+//jp2796NXr166cv79OkDtVqNLl26YPLkyQAAHx8fuLq6Qq1WY+rUqQBgcJfM1H5sSGBgIFavXg21Wg0AmD17NioqKvDBBx/AysqqxdppTl811vemqKioQHR0NJKTk03e11yacu42Njb6u6h9+vRBcnIySkpKkJKS0iIxjBkzBsXFxViyZEmLHI+IqL3jFz5aSHBwMJycnJCRkXHPOvXvCdbW1ja4PSMjA4WFhXj66acNyq2trTFnzpz7Hre6utrUsBtka2trcLzMzEyUlpZi0KBBBhh1Y70AACAASURBVPVCQkJga2tr8AiuOe3U1NToy5pyLvfrx/tJS0vDJ598gri4OPTs2bNF23nQvvp135ti4cKF+H//7//By8vL5H3bg6ae+6BBg6BWqw3+g0BERE3H5K8FKZVKgz9cBw4cQHx8PDIzM1FcXHzfP2rFxcUAAGdn51aN01SFhYUAAAcHB6Ntzs7OKCkpadX2Te3HxuTn5+ONN95ASEgIYmJiWrwdc/XV8ePHce7cOSQkJLTK8dsbOzs7k+7IEhHRf/GxbwupqalBQUEBfHx8AADZ2dkICwuDh4cHTp06haKiIsTFxTV6jG7dugGA/gX19qI+GW0ocSksLIS3t3ertd2cfmzMnDlzUFhYiJSUFFhbW7d4O+bqq23btuHIkSOwsrLSf5Gl/gsfK1euhEKhwDfffNMqbbe16urqVr/uiIg6MyZ/LeT//u//UFdXh4EDBwIAzp07h+rqasyePRv+/v76lTka06NHD7i4uOCLL75oi5CbrF+/fnBwcDBKHk6dOoWqqio8+uijrdZ2c/rxXg4cOICdO3diyZIl6Nu3r7583rx5LdaOufoqJSUFImLwqb8ztmjRIoiI0aPojurYsWMQEQwePFhfZmNj02KvPRARdXZM/pqpqqoKRUVFqKmpwenTpxEVFQVfX19MmzYNAPR3AA8fPozKykpcunTJ6H0vFxcX3Lx5E1euXEFJSQmsrKywcOFCfPXVV4iKisKNGzdQV1eHkpISnD9/vq1PUU+lUiEmJgZ79uzBjh07UFxcjHPnzuHVV1+Fp6cnZs6c2WptN6Ufm6K4uBizZs3CgAEDMH/+fAA/L3/2zTff4OzZs80ar4aSDXP2VWdVV1eHO3fuoKamBhkZGYiOjoaPj4/+Zw34+Qs9BQUF2Lt3L6qrq5Gbm4urV68aHauhMTx06BCneiEiy2LO7xq3B8356ndKSoqMHDlSunbtKjY2NtKlSxeZPHmyXL161aBebGysuLi4iLOzs0ycOFE2btwoACQgIECys7Pl9OnT4uvrK/b29jJs2DD9NCAbN26U4OBgUalUolKp5JFHHpGkpCSJi4sTe3t7ASBBQUGSlZUlO3bsEJ1OJwDE29tbvv322yafR1JSkqjVaoPjbd68WbRarQAQX19f/dQ1dXV1Eh8fL0FBQaJUKkWn00lYWJhcuHBBf7xfxte9e3fZvn27iIgkJibq2+nRo4d8/fXX8v7774uTk5MAEHd3d9m5c6d89NFH4u7uLgBEp9PJrl277tuP0dHR+n00Go2Eh4fLhg0bxMPDQwCIWq2WcePGydq1awVAg59nn322WeO1ePFio3aa2lem9H1ztYepXhoaC1POfebMmaJUKsXLy0tsbGxEq9XK+PHjJSsry6Cd/Px8GTlypKhUKvHz85M33nhD5s2bJwAkMDBQPy1MQz9zBw8eFEdHR1mxYsUDnasIp5LobDienQvHUy9NIWLZC2+mpaVh0qRJXH+U6FcmTpwIAEhPTzdbDLNmzUJ6ejry8/PNFoMp+Pukc+F4di4cT710PvYlonatuVP6EBFRw5j8dTLff//9PZcx++UnMjLS3KHSfXAsLc/hw4exYMEC7N69G/7+/voxfvHFF43qPvXUU3B0dIS1tTX69u2L06dPmyFi09XV1WHdunUIDQ1tcPvy5cvRp08faLVa2NnZITAwEG+//TZKS0uN6n744YcICQmBo6MjfH19MX36dNy+fVu//W9/+xvi4uLM9h8IjmfnGs9OxZwPndsDvgNA1LCWWt6tuRYsWCC2trb6d0XT09PNFktTPcjvk6VLl8rYsWOluLhYXxYQECBdunQRALJ//36jfQ4dOiTPPfdcs+NtaxcvXpShQ4cKAHn44YcbrDNixAhJSkqS/Px8KS4ultTUVFEqlfLMM88Y1Pvoo48EgMTFxUlhYaGcOXNG/P39ZcCAAVJdXa2vl5iYKCNGjJA7d+6YHC/Hs3GWNJ6dTJrF9wIvBqKGmTv564ia+/tk9erV8tBDD0lFRYVBeUBAgOzcuVOsrKzEy8tLCgsLDbZ3pGTh7NmzEh4eLjt27JABAwbcM1kYM2aM1NTUGJQ9//zzAsBgPeeRI0dKt27dpK6uTl9W/yWt48ePG+wfFRUlQ4YMMUgimoLjeW+WNJ6dENf2JSIyp8uXL2PJkiV49913oVKpjLaHhoYiOjoaN27cwFtvvWWGCFvGww8/jN27d2PKlCmws7O7Z739+/cbTMAOAK6urgCA8vJyfdm1a9fg6elpMB9n9+7dAcBomp9ly5bh7NmzSExMfODzuB+Op6GOPp6dFZM/IiIzWr9+PUQE48aNu2edFStW4KGHHsLWrVtx+PDhRo8nIkhISEDv3r1hZ2cHnU6H8ePHG6yFnJycDI1GA7VajX379mH06NHQarXw9vbGrl27DI5XW1uLpUuXwsfHB/b29ujfvz9SU1Mf7KRNdOPGDdjb28PPz09f5u/vj5ycHIN69e+H+fv7G5TrdDqMGDECiYmJrf5NT47n/XWk8eysmPwREZnRgQMH0LNnT6jV6nvWsbe3x1/+8hdYWVlhxowZKCsru2fdZcuWYcGCBVi0aBFycnLw1Vdf4dq1axg+fDh++uknAMDs2bMxd+5cVFRUwNHREampqcjKyoK/vz9mzJhhMIH5/PnzsWbNGqxbtw63bt3C2LFj8cILL7TZcoHl5eU4evQoZsyYAVtbW335woULcfv2bWzYsAElJSXIzMxEYmIinn76aYPVX+o98sgjuHHjBv7973+3arwcz8Z1tPHsrJj8ERGZSVlZGX788UcEBATct+6QIUMwd+5cXLlyRb9Kza9VVFQgISEB4eHhmDp1KpycnBAcHIxNmzYhLy8PmzdvNtonNDQUWq0Wbm5uiIyMRFlZGbKzswH8vApOcnIywsLCEBERAWdnZyxevBhKpRIpKSkPdvJNtGrVKnh6emLFihUG5SNGjEBsbCyioqKg1WrRr18/lJSUYOvWrQ0eJygoCMDPS0a2Fo7n/XWk8ezMbMwdQHuRlpZm7hCI2pXr168D4M+GKU6ePGlS/ZycHIhIo3eJfmnFihXYv38/kpKSMGnSJKPtmZmZKC0tNVrHOSQkBLa2tvddGrH+Tkz9naILFy6gvLwc/fr109ext7eHh4eHwWPH1rJnzx6kpaXhiy++gKOjo8G2RYsWYevWrThy5Ah+85vfICcnB/Pnz8eQIUNw4sQJ/fti9er7uP5uWWvgeDauo41nZ8bk7z8a+sEjIv5stKbKykoAaPSF+V9SqVRISUnBsGHD8PLLLyMuLs5ge2FhIQDAwcHBaF9nZ2eUlJSYFF/948jFixdj8eLFBts8PT1NOpapPvroIyQkJODYsWPo1q2bwbZbt24hLi4OCxYswO9+9zsAgJ+fH7Zs2QKdTof4+HisX7/eYB97e3sA/+3z1sDxvLeOOJ6dGR/7/oeI8MMPP7/4TJgwARMmTDB7HB3pY+qL8/V/wEyZtHbIkCF48803cenSJbz33nsG25ydnQGgwaSgsLAQ3t7eJsXn5uYGAFi3bp3RuZp6l9MUGzZswI4dO3D06FGjRAEALl26hNraWqNtWq0WLi4uyMzMNNqnqqoKwH/7vDVwPBvWUcezM2PyR0RkJl27doVCoUBRUZFJ+7333nvo1asXzpw5Y1Der18/ODg4GL28f+rUKVRVVeHRRx81qZ3u3btDpVLh7NmzJu3XXCKC2NhYnDt3Dnv37m3wjhcAfdJz69Ytg/KSkhIUFBQYPSIEoO9jd3f3Fo76vziehjr6eHZmTP6IiMxErVbD399f/35lU9U/Lvz1/GkqlQoxMTHYs2cPduzYgeLiYpw7dw6vvvoqPD09MXPmTJPbmT59Onbt2oXk5GQUFxejtrYW169f1/+hjoyMhLu7e4ssR3b+/HmsWbMGW7ZsgVKpNFrKcO3atQB+fiQ4cuRIbNmyBV999RUqKipw7do1/fm98sorRseu7+Pg4OAHjvNeOJ6GOvp4dmpi4TjjN1HDuMKH6Zrz+yQqKkqUSqWUl5fry/bs2SMBAQECQFxdXeX1119vcN958+YZrQhRV1cn8fHxEhQUJEqlUnQ6nYSFhcmFCxf0dZKSkkStVgsACQoKkqysLNm8ebNotVoBIL6+vnLx4kUREbl7967ExsaKj4+P2NjYiJubm0REREhmZqaIiISFhQkAWbp0aaPnefLkSRk6dKh4enoKAAEgHh4eEhoaKl9++aWIiJw7d06/raFPfHy8/nh5eXkSHR0tgYGBYmdnJw4ODjJ06FD55JNPGmx/zJgx4uXlZbCCxP1wPO/NUsazk+LybrwYiBrG5M90zfl9cunSJbGxsZHt27e3UlStq7a2VoYPHy7btm0zdyj3lJeXJyqVStauXWvSfhzP9qktx7OT4vJuRETmFBgYiOXLl2P58uUoLS01dzgmqa2txd69e1FSUoLIyEhzh3NPy5Ytw4ABAxAVFdXqbXE8W19bjmdnxeSPiMjMFixYgIkTJyIyMtLkLwuY07Fjx7B7924cOnSoyXPbtbWEhAScPXsWBw8ehFKpbJM2OZ6txxzj2Rkx+Wtlu3fvhr+/v9GLrjY2NnB1dcUTTzyBPXv2tHoc06dPh0qlgkKhaHRepF/H++KLLxrVeeqpp+Do6Ahra2v07du3RV4Mbk1r167Vfwtv06ZN+vKDBw/CyckJn376aau231btUMe2cuVKREVFYfXq1eYOpclGjRqFnTt3wsPDw9yhNGjfvn24e/cujh07Bp1O16ZtczxbnjnHs7Nh8tfKIiIi8MMPPyAgIABOTk76OZVyc3ORmpqKGzduICIiotUX1k5JScFbb71lUrxdunTBjh07cODAAYM6X3zxBdLT0zF27FhkZmZi4MCBrRV2i3jrrbdw4sQJo3KRtlkQvK3aoY7vqaeewvvvv2/uMDqN5557DgsWLDD6Fm1b4Xi2LHOPZ2fC5M9MdDodRo0ahf/93/8FYPoSWhUVFQgNDW2N0PTWr18PKysrzJw5s0M9umiqMWPGoKioCGPHjm2xYzY0Lq3RjqVoi+u8LdogImpPmPyZWY8ePQD8dxmfptq2bRtycnKa1aZCoWhSvdDQUERHR+PGjRtNumtIDzYuZKwt+pNjRkSWhsmfmWVkZAAARowYYVD+9ddfo0+fPnBycoJKpUJwcDA+//xzAEB0dDRiYmKQlZUFhUKBwMBA/X7bt2/HoEGDoFKpoNFo0KNHD4Mlg6ysrHDgwAGMHj0aTk5O8PT0xAcffHDP+FasWIGHHnoIW7duxeHDhxs9FxFBQkICevfuDTs7O+h0OowfP95gwfA1a9ZArVbD0dEROTk5iImJgZeXF1599VVoNBpYWVnh0Ucfhbu7O5RKJTQaDQYOHIjhw4frZ6d3dnbG22+/3eT+asjx48fh4+MDhUKBjRs3AgAuX75s9G5m/efvf/97s8aloXaa2lfJycnQaDRQq9XYt28fRo8eDa1WC29vb+zatavRsTCXppxXVFQUbG1tDd4reu2116DRaKBQKJCXlweg4f5cv349VCoVunbtilmzZsHT0xMqlQqhoaEGi9w/SBsA8Nlnn0Gr1WLlypWt2l9ERGZhxnlm2oW2mvcnICBAnJyc9P8uLy+XQ4cOia+vrzz11FNSWlpqUD89PV2WLVsmBQUFkp+fL4MHD5YuXbrot0dEREhAQIDBPuvWrRMAsnr1asnPz5eCggL585//LFOmTBERkUWLFgkAOXLkiBQWFkpBQYE8++yzYmdnJ2VlZUbx/vjjjyIicuLECbGyspIePXro4zx06JDRZKRLly4VW1tb2b59uxQWFkpGRoYMHDhQXF1d5fbt2/p69XHMmTNHNmzYIOHh4fLdd9/JO++8IwDk1KlTUlZWJnl5efLMM88IADlw4IDk5uZKWVmZREVFCQA5e/Zsk/vr0qVLAkD+9Kc/6cuuXbsmAGTDhg36OvPnz9f3xa1bt0Sn00loaKjU1tY2e1x+3U5z+urIkSNSVFQkOTk5Mnz4cNFoNFJVVSWtqTnz/DX1vKZMmSLu7u4G+8bHxwsAyc3N1Zc11J8zZ84UjUYj58+fl8rKSsnMzJSQkBBxdHSU7OzsFmlj//794ujoKMuXLzfp/DmPWOfC8excOJ56nOevLRUVFenvJKnVav2dnClTphh9ZX3ChAl45513oNPp4OLignHjxiE/Px+5ubkNHru6uhrvvvsuRo4cifnz58PFxQU6nQ6vvPIKQkJCDOqGhobCyckJOp0OkZGRuHv3Ln788cd7xj1kyBDMnTsXV65cwfz58xusU1FRgYSEBISHh2Pq1KlwcnJCcHAwNm3ahLy8PGzevNlon/fffx+vv/46du/ejV69eunL+/TpA7VajS5dumDy5MkAAB8fH7i6ukKtVmPq1KkAYHA3ydT+akhgYCBWr16tn+Jg9uzZqKiowAcffAArK6sWa6c5fRUaGgqtVgs3NzdERkairKwM2dnZTW6zLTTnvJrLxsZGf3exT58+SE5ORklJCVJSUlrk+GPGjEFxcTGWLFnSIscjImpPmPy1oV9+27e6uhrXr1/H3LlzERUVhf79++sfRTWkPjmsra1tcHtGRgYKCwvx9NNPG5RbW1tjzpw59z1udXV1o7GvWLECPXv2RFJSEo4fP260PTMzE6WlpRg0aJBBeUhICGxtbQ0eyZnC1tYWAFBTU2NSzPfrr/tJS0vDJ598gnfffRc9e/Zs0XYetK/q++R+Y9bWWusaaIpBgwZBrVYb/IeAiIgaxuTPTGxsbODl5YXp06dj7dq1uHDhgsF8UAcOHMDjjz8ONzc32NnZGb3j9mvFxcUAAGdn51aJt37hcYVCgZdffhkVFRUG2+u/sOLg4GC0r7OzM0pKSlolrnqm9ldj8vPz8cYbbyAkJAQxMTEt3o65+6q1mPu87OzsTLoDS0RkqZj8tQPBwcEAgPPnzwMAsrOzERYWBg8PD5w6dQpFRUWIi4tr9BjdunUDgEbvHj6oIUOG4M0338SlS5cMvkQC/DfpbOgPfGFhIby9vVstrub0V2PmzJmDwsJCpKSkGMwn1VLtmLOvWpM5z6u6urpD9x0RUVti8tcO/Otf/wIA/ePFc+fOobq6GrNnz4a/v79+ZY7G9OjRAy4uLvjiiy9aNdb33nsPvXr1wpkzZwzK+/XrBwcHB3zzzTcG5adOnUJVVRUeffTRVoupOf11LwcOHMDOnTuxZMkS9O3bV18+b968FmvHnH3Vmkw5LxsbmxZ9bH3s2DGICAYPHtxqbRARdRZM/tpYRUUF6urqICK4efMmUlJSsHjxYri6umLu3LkAfv5yAwAcPnwYlZWVuHTpktH7Ui4uLrh58yauXLmCkpISWFlZYeHChfjqq68QFRWFGzduoK6uDiUlJfo7ii2h/vHvr2dYV6lUiImJwZ49e7Bjxw4UFxfj3LlzePXVV+Hp6YmZM2e2WAy/1pT+aori4mLMmjULAwYM0H+xpbKyEt988w3Onj3brHFpKPkwZ1+1JlPOKzAwEAUFBdi7dy+qq6uRm5uLq1evGh3zXv1ZV1eHO3fuoKamBhkZGYiOjoaPjw+mTZvWIm0cOnSIU70QUedl3m8bm19rf/V7z549EhAQIACMPnZ2dhIUFCSzZ882mKJCRCQ2NlZcXFzE2dlZJk6cKBs3bhQAEhAQINnZ2XL69Gnx9fUVe3t7GTZsmH4ajY0bN0pwcLCoVCpRqVTyyCOPSFJSksTFxYm9vb0AkKCgIMnKypIdO3aITqcTAOLt7S3ffvutQbyurq7y+uuvN3he8+bNM5rqpa6uTuLj4yUoKEiUSqXodDoJCwuTCxcu6Ov8Mo7u3bvL9u3bRUQkMTFR1Gq1AJAePXrI119/Le+//744OTkJAHF3d5edO3fKRx99JO7u7gJAdDqd7Nq16779FR0drd9Ho9FIeHi4bNiwQTw8PASAqNVqGTdunKxdu7bBcQIgzz77bLPGZfHixUbtNLWvkpKS9H1SP2abN28WrVYrAMTX11cuXrz4IJdno5oz1UtTzktEJD8/X0aOHCkqlUr8/PzkjTfekHnz5gkACQwM1P88NHSdz5w5U5RKpXh5eYmNjY1otVoZP368ZGVltVgbBw8eFEdHR1mxYoVJ58+pJDoXjmfnwvHUS1OIWPbCo2lpaZg0aRLXXyX6lYkTJwIA0tPTzRyJoVmzZiE9PR35+fnmDsUIf590LhzPzoXjqZfOx75E1OE0dwofIiLiO39EREREFoXJHxF1GAsXLkRKSgqKiorg5+eHjz/+2NwhERF1ODbmDoCIqKlWrVqFVatWmTsMIqIOjXf+iIiIiCwIkz8iIiIiC8Lkj4iIiMiCMPkjIiIisiD8wsd/1E9oS0Q/+8c//gGAPxumuH79OgD2WWfB8exc6seTAItf4ePkyZNISEgwdxhE1IZu376NM2fOYPTo0eYOhYjaWHtbtcgM0i0++SMiy8NlnojIgnF5NyIiIiJLwuSPiIiIyIIw+SMiIiKyIEz+iIiIiCwIkz8iIiIiC8Lkj4iIiMiCMPkjIiIisiBM/oiIiIgsCJM/IiIiIgvC5I+IiIjIgjD5IyIiIrIgTP6IiIiILAiTPyIiIiILwuSPiIiIyIIw+SMiIiKyIEz+iIiIiCwIkz8iIiIiC8Lkj4iIiMiCMPkjIiIisiBM/oiIiIgsCJM/IiIiIgvC5I+IiIjIgjD5IyIiIrIgTP6IiIiILAiTPyIiIiILwuSPiIiIyIIw+SMiIiKyIEz+iIiIiCwIkz8iIiIiC8Lkj4iIiMiCMPkjIiIisiBM/oiIiIgsiI25AyAiak3V1dUoLS01KCsrKwMA3Llzx6BcoVDA2dm5zWIjIjIHJn9E1KkVFBTAy8sLtbW1RttcXFwM/j1y5EgcPXq0rUIjIjILPvYlok7N3d0dv/3tb2Fl1fivO4VCgcmTJ7dRVERE5sPkj4g6vRdffPG+daytrREeHt4G0RARmReTPyLq9CIiImBjc++3XKytrfHMM8+gS5cubRgVEZF5MPkjok5Pq9Vi9OjR90wARQRTp05t46iIiMyDyR8RWYSpU6c2+KUPALC1tcXvf//7No6IiMg8mPwRkUX4/e9/D7VabVSuVCoRFhYGjUZjhqiIiNoekz8isggqlQrh4eFQKpUG5dXV1ZgyZYqZoiIiantM/ojIYrzwwguorq42KNNqtXjyySfNFBERUdtj8kdEFuOJJ54wmNhZqVRi8uTJsLW1NWNURERti8kfEVkMGxsbTJ48Wf/ot7q6Gi+88IKZoyIialtM/ojIokyePFn/6Nfd3R3Dhg0zc0RERG2LyR8RWZTQ0FB4eXkBAF566aX7LvtGRNTZ3HvKe+oQrl+/jhMnTpg7DKIOJSQkBDdu3ECXLl2QlpZm7nCIOpTnn3/e3CHQA1KIiJg7CGq+tLQ0TJo0ydxhEBGRhWDa0OGl885fJ8EfxvZn4sSJAID09HQzR9Jx1P9npi2u548//hgTJkxo9XYsWVuOJ7U+3mzoPPiyCxFZJCZ+RGSpmPwRERERWRAmf0REREQWhMkfERERkQVh8kdERERkQZj8EREREVkQJn+EP/7xj3B0dIRCocDZs2fNHY5ZxcXFoVevXrC3t4dGo0GvXr2wZMkSFBcXmy2mgwcPwsnJCZ9++qnZYiAios6DyR9h69at2LJli7nDaBe+/vprzJgxA9nZ2fjpp5/w3nvvIS4uzqzTgnCONCIiaklM/qjTqaioQGhoaLP2tbW1xWuvvQY3Nzc4ODhg4sSJGD9+PP7+97/j1q1bLRxp04wZMwZFRUUYO3asWdr/pQfpWyIiah+4wgcBABQKhblDaDHbtm1DTk5Os/bds2ePUZmXlxcAoLS09IHi6gwepG+JiKh94J0/CyQiiI+PR8+ePWFnZwcnJyfMmzfPoM6aNWugVqvh6OiInJwcxMTEwMvLCxcuXICIICEhAb1794adnR10Oh3Gjx+P77//Xr//+vXroVKp0LVrV8yaNQuenp5QqVQIDQ3FqVOnjOK53/GioqJga2sLDw8Pfdlrr70GjUYDhUKBvLw8AEB0dDRiYmKQlZUFhUKBwMDAB+6vS5cuwdnZGb6+vg98LFMdP34cPj4+UCgU2LhxIwAgOTkZGo0GarUa+/btw+jRo6HVauHt7Y1du3bp923qGDxo33722WfQarVYuXJlW3QJERE9KKEOLTU1VUwdxkWLFolCoZD/+Z//kTt37kh5ebkkJSUJADlz5oxBPQAyZ84c2bBhg4SHh8t3330nS5cuFVtbW9m+fbsUFhZKRkaGDBw4UFxdXeX27dv6/WfOnCkajUbOnz8vlZWVkpmZKSEhIeLo6CjZ2dn6ek093pQpU8Td3d3gXOLj4wWA5Obm6ssiIiIkICDApD75taqqKrl+/bps2LBB7OzsZPv27SYfY8KECTJhwoQHikNE5Nq1awJANmzYoC+rH5sjR45IUVGR5OTkyPDhw0Wj0UhVVZW+XlPH4EH6dv/+/eLo6CjLly9/4HNtzvVM7RfHs3PheHYaabzzZ2EqKiqwbt06PPHEE3jzzTfh7OwMe3t7uLi43HOf999/H6+//jp2794NX19fJCQkIDw8HFOnToWTkxOCg4OxadMm5OXlYfPmzQb72tjY6O/o9enTB8nJySgpKUFKSoo+HlOO11a6d+8Ob29vLFu2DGvWrGm3i5mHhoZCq9XCzc0NkZGRKCsrQ3Z2tkGd+43BgxozZgyKi4uxZMmSFjkeERG1LiZ/Fuby5csoLy/HqFGjmrV/ZmYmSktLMWjQIIPykJAQ2NraGj3S/bVBgwZBrVbrH+k+6PFay7Vr15CTk4MPP/wQf/3rX/HII4+0+3fdbG1tAQDV1dWN1vv1GBARkWVh8mdhrl+/DgBwc3Nr1v6FhYUAAAcHB6Ntzs7OKCkpue8x7OzskPv/2bv3qKjK/X/g74EZO//V8AAAIABJREFUmBmYAVQUFEFuZQpqXkpRj1nnVB6XJqJJaqWVX7QLoWZ45ZjXEBewNPh6vBxaSzsKiGmZVt/yq55WHr+npSQHj5c4ede4KA435fb5/dGPOY2gMsAwzMz7tdb80d7P3s9nPx+BT3vveZ6iojY7nyWoVCp4e3vj2Wefxa5du5Cfn481a9ZYJRZL+G0OiIjIsbD4czBqtRoAcPfu3RYd7+npCQBNFmWlpaXw8/N74PE1NTUm7Vp7vvYQEhICZ2dn5OfnWzuUNnFvDoiIyLGw+HMwYWFhcHJywpEjR1p8vLu7O3744QeT7cePH0d1dTUGDRr0wOMPHz4MEcHQoUPNPp9SqXzoI83WKCkpwdSpUxttP3/+POrq6tCzZ0+L9d2e7s0BYPmxJSKijoPFn4Px9vZGVFQUdu/ejW3btsFgMODUqVPN/mKFWq3G/PnzsWfPHuzYsQMGgwF5eXmYM2cOfH19ERMTY9K+vr4et27dQm1tLU6dOoW4uDj4+/tjxowZZp8vJCQEN2/exN69e1FTU4OioiJcvHixUYydOnXCtWvXcOHCBZSVlTW7qHFzc8PXX3+NQ4cOwWAwoKamBidPnsSrr74KNzc3zJs3r1nn6WgelgOgdWN78OBBTvVCRGRLrP19Y2qdlnz1vqysTN544w3p3LmzuLu7y4gRIyQhIUEAiJ+fn/z444+SmJgoGo1GAEjPnj1Npjqpr6+XpKQkCQ0NFZVKJV5eXhIZGSlnz5416ScmJkZUKpX06NFDlEql6PV6mTBhghQUFJi0a+75SkpKZPTo0aJWqyUwMFDeeecdWbBggQCQkJAQ49QlJ06ckICAANFoNDJixAiT6WIeZvz48RIYGCju7u7i6uoqwcHBEh0dLXl5eWaNsUjbTPWyceNG8fHxEQCi1Wpl/PjxkpaWJlqtVgBIaGioFBQUyObNm0Wv1wsACQgIkHPnzolI83PQmrE9cOCA6HQ6WbVqVauuVYRTSdgb5tO+MJ92I0shwoVDbVlWVhamTJnSIdd/nT17NrKzs1FSUmLtUKxi8uTJAIDs7GyrxWBrOejI/57JfMynfWE+7UY2H/uSRdXV1Vk7BIfHHBAR0W+x+CO7dubMGSgUiod+oqOjrR0qtYFvvvkGixYtQk5ODoKCgoz5ffnllxu1ffbZZ6HT6eDs7Iy+ffvixIkTVojYfPX19UhJSUFEREST+1esWIE+ffpAr9fD1dUVISEheP/995tcm/qvf/0rhgwZAp1Oh4CAAMycORM3btww7v/ss8+QmJhotf+BYD7tK5/UgVjzoTO1Xkd9B2PRokXi4uIiAKRXr16SnZ1t7ZDaXVst79ZStpiD1vx7TkhIkHHjxonBYDBuCw4Ols6dOwsA2b9/f6NjDh48KC+88EKL421v586dk+HDhwsA6d+/f5NtRo0aJWlpaVJSUiIGg0EyMzNFpVLJ888/b9Ju165dAkASExOltLRUTp48KUFBQTJgwACpqakxtktNTZVRo0bJrVu3zI6X+XwwR8ondShZzKKN4w9jx2Xt4s8WtfTf89q1a+WRRx6Rqqoqk+3BwcHyySefiJOTk/To0UNKS0tN9ttSsZCbmysTJ06UHTt2yIABA+5bLIwdO1Zqa2tNtr344osCwGQ959GjR0v37t2lvr7euO2jjz4SAPLdd9+ZHB8bGyvDhg0zKSKag/m8P0fKJ3U4XNuXiGzbTz/9hGXLluGDDz4wTmL+WxEREYiLi8PVq1fx3nvvWSHCttG/f3/k5ORg2rRpcHV1vW+7/fv3w9nZ2WRbly5dAACVlZXGbZcvX4avry8UCoVxW8NclvdO87N8+XLk5uYiNTW11dfxMMynKVvPJ3VMLP6IyKZt2LABIoLx48fft82qVavwyCOPYOvWrfjmm28eeD4RQXJyMh577DG4urrCy8sLEyZMMFkLOT09HW5ubtBqtdi3bx/GjBkDvV4PPz8/7Ny50+R8dXV1SEhIgL+/PzQaDfr164fMzMzWXbSZrl69Co1Gg8DAQOO2oKCgRutVN7wfFhQUZLLdy8sLo0aNQmpqqsW/6cl8Ppwt5ZM6JhZ/RGTTvvjiCzz66KPQarX3baPRaPDxxx/DyckJs2bNQkVFxX3bLl++HIsWLcKSJUtQWFiIo0eP4vLlyxg5ciR++eUXAMCbb76JuXPnoqqqCjqdDpmZmSgoKEBQUBBmzZplMrH4woULsW7dOqSkpOD69esYN24cpk6d2mhVG0uprKzEoUOHMGvWLLi4uBi3L168GDdu3MDGjRtRVlaG/Px8pKam4rnnnjNZ/aXB448/jqtXr+LHH3+0aLzM54PZWj6pY2LxR0Q2q6KiAj///DOCg4Mf2nbYsGGYO3cuLly4gIULFzbZpqqqCsnJyZg4cSKmT58ODw8PhIeHY9OmTSguLm5yJZyIiAjo9Xp4e3sjOjoaFRUVuHTpEgDgzp07SE9PR2RkJKKiouDp6YmlS5dCpVIhIyOjdRffTGvWrIGvry9WrVplsn3UqFGIj49HbGws9Ho9wsLCUFZWhq1btzZ5ntDQUABAXl6exWJlPh/OlvJJHZfS2gFQ22iYUJg6jr///e8AmBtzXLlyxaz2hYWFEJEH3iX6rVWrVmH//v1IS0vDlClTGu3Pz89HeXk5Bg8ebLJ9yJAhcHFxwfHjxx94/oY7MQ13is6ePYvKykqEhYUZ22g0Gvj4+Jg8drSUPXv2ICsrC19//TV0Op3JviVLlmDr1q349ttv8eSTT6KwsBALFy7EsGHD8P333zday7phjBvullkC8/lgtpZP6rh454+IbNadO3cA4IEvzP+WWq1GRkYGFAoFXnvtNVRVVZnsLy0tBQC4u7s3OtbT0xNlZWVmxdfwOHLp0qUm80pevHjR5GV9S9i1axc+/PBDHD58GL169TLZd/36dSQmJuK//uu/8PTTT8PNzQ2BgYHYsmULrl27hqSkpEbn02g0AP4z5pbAfN6fLeaTOi7e+bMT1lxCjJrWEZZ3szUNy0c1V8MfMHMmrR02bBjmzZuH9evXY+XKlfD39zfu8/T0BIAmi4LS0lL4+fk1ux8A8Pb2BgCkpKQgLi7OrGNbY+PGjfjqq69w6NChJguf8+fPo66uDt27dzfZrtfr0alTJ+Tn5zc6prq6GsB/xtwSmM+m2Wo+qePinT8islldu3aFQqHA7du3zTpu5cqV6N27N06ePGmyPSwsDO7u7o1e3j9+/Diqq6sxaNAgs/rp2bMn1Go1cnNzzTqupUQE8fHxyMvLw969e5ssFAAYi57r16+bbC8rK8PNmzcbPSIEYBzjbt26tXHU/8F8mrL1fFLHxeKPiGyWVqtFUFCQ2e8KNjwuvHf+NLVajfnz52PPnj3YsWMHDAYD8vLyMGfOHPj6+iImJsbsfmbOnImdO3ciPT0dBoMBdXV1uHLlivEPdXR0NLp169Ymy5GdPn0a69atw5YtW6BSqRotY7h+/XoAQGBgIEaPHo0tW7bg6NGjqKqqwuXLl43X9/rrrzc6d8MYh4eHtzrO+2E+Tdl6PqkDs9b00tQ2OON6x8UVPszXkn/PsbGxolKppLKy0rhtz549EhwcLACkS5cu8vbbbzd57IIFCxqtCFFfXy9JSUkSGhoqKpVKvLy8JDIyUs6ePWtsk5aWJlqtVgBIaGioFBQUyObNm0Wv1wsACQgIkHPnzomIyN27dyU+Pl78/f1FqVSKt7e3REVFSX5+voiIREZGCgBJSEh44HUeO3ZMhg8fLr6+vgJAAIiPj49ERETIkSNHREQkLy/PuK+pT1JSkvF8xcXFEhcXJyEhIeLq6iru7u4yfPhw+fTTT5vsf+zYsdKjRw+TFSQehvm8P0fJJ3VIXN7N1vGHseNi8We+lvx7Pn/+vCiVStm+fbuForKsuro6GTlypGzbts3aodxXcXGxqNVqWb9+vVnHMZ8dU3vmkzokLu9GRLYtJCQEK1aswIoVK1BeXm7tcMxSV1eHvXv3oqysDNHR0dYO576WL1+OAQMGIDY21uJ9MZ+W1575pI6JxR+ZyMnJQVBQUKN3S1xcXNC1a1c89dRTSEpKwq1bt6wdKpHRokWLMHnyZERHR5v9ZQFrOnz4MHJycnDw4MFmz23X3pKTk5Gbm4sDBw5ApVK1S5/Mp+VYI5/U8bD4IxNRUVH497//jeDgYHh4eEBEUF9fj8LCQmRlZSEwMBDx8fHo27dvuy1nRNQcq1evRmxsLNauXWvtUJrtmWeewSeffAIfHx9rh9Kkffv24e7duzh8+DC8vLzatW/ms+1ZM5/UsbD4o4dSKBTw9PTEU089hYyMDGRlZeGXX37B2LFjber/yu+nqqoKERER1g7DItrj2jrS+D377LP48MMPrR2G3XjhhRewaNGiRt+ibS/MZ9uydj6p42DxR2abNGkSZsyYgcLCQmzatMna4bTatm3bUFhYaO0wLKI9rs2ex4+IyB6x+KMWmTFjBgDg4MGDAIB169ZBq9VCp9OhsLAQ8+fPR48ePXD27FmICJKTk/HYY4/B1dUVXl5emDBhgslamBs2bIBarUbXrl0xe/Zs+Pr6Qq1WIyIiotH6m805X2xsLFxcXEwev7z11ltwc3ODQqFAcXExACAuLg7z589HQUEBFAoFQkJCLDVkzWLpa2vuOLd2/L788kvo9XqsXr3aouNFREQtYN1vG1NrWeqr98HBweLh4XHf/QaDQQBIz549jduWLFkiAOTdd9+VjRs3ysSJE+Vf//qXJCQkiIuLi2zfvl1KS0vl1KlTMnDgQOnSpYvcuHHDeHxMTIy4ubnJ6dOn5c6dO5Kfny9DhgwRnU4nly5dMrZr7vmmTZsm3bp1M4k7KSlJAEhRUZFxW1RUlAQHB7dqvJrSkqle2uPamjvOrelj//79otPpZMWKFWZdP6eSsC/Mp31hPu0Gp3qhltHpdFAoFE2umfnhhx/i7bffRk5ODgICApCcnIyJEydi+vTp8PDwQHh4ODZt2oTi4mJs3rzZ5FilUmm869WnTx+kp6ejrKwMGRkZAH59v8yc89mS9ry2h41za40dOxYGgwHLli1rk/MREVHbYfFHLVJRUQERgV6vf2C7/Px8lJeXY/DgwSbbhwwZAhcXl0aPdO81ePBgaLVa42PP1p6vI7Pmtd07zkREZL9Y/FGLnDt3DgDQu3fvB7YrLS0FgCYXJPf09GzyzuG9XF1dUVRU1Gbn66isfW2/HWciIrJfLP6oRb788ksAwJgxYx7YztPTEwCaLFxKS0vh5+f3wONrampM2rX2fB2ZNa/t3nEmIiL7xeKPzHbjxg2kpKTAz88Pr7322gPbhoWFwd3dvdGE0MePH0d1dTUGDRr0wOMPHz4MEcHQoUPNPp9SqURNTY05l2ZV1ry2e8fZEn0QEVHHwOKP7ktEUF5ejvr6eogIioqKkJmZieHDh8PZ2Rl79+596Dt/arUa8+fPx549e7Bjxw4YDAbk5eVhzpw58PX1RUxMjEn7+vp63Lp1C7W1tTh16hTi4uLg7+9vnFrGnPOFhITg5s2b2Lt3L2pqalBUVISLFy82irFTp064du0aLly4gLKyMqsVPO15bQ8b59b2cfDgQU71QkTUUVn1y8bUam391fvPPvtM+vXrJ1qtVlxcXMTJyUkAiEKhEE9PT3niiSdkxYoVUlJSYnJcYmKiaDQa4/Qv27dvN+6rr6+XpKQkCQ0NFZVKJV5eXhIZGSlnz541OUdMTIyoVCrp0aOHKJVK0ev1MmHCBCkoKDBp19zzlZSUyOjRo0WtVktgYKC88847smDBAgEgISEhxmlNTpw4IQEBAaLRaGTEiBEmU6q0RkumemmPa2vuOLemjwMHDohOp5NVq1aZdf2cSsK+MJ/2hfm0G1kKERGrVZ7UallZWZgyZQrsIY2zZ89GdnY2SkpKrB1Km5g8eTIAIDs728qRmOrI42xP/56J+bQ3zKfdyOZjX+pQ6urqrB2CQ+A4ExE5LhZ/RERERA6ExR91CIsXL0ZGRgZu376NwMBA7N6929oh2SWOMxERKa0dABEArFmzBmvWrLF2GHaP40xERLzzR0RERORAWPwRERERORAWf0REREQOhMUfERERkQNh8UdERETkQPhtXzuhUCisHQLdB3NjPo6ZfWE+iToWFn82LiIiApmZmdYOg8imHDt2DKmpqfzZISKHxLV9icjhcI1SInJgXNuXiIiIyJGw+CMiIiJyICz+iIiIiBwIiz8iIiIiB8Lij4iIiMiBsPgjIiIiciAs/oiIiIgcCIs/IiIiIgfC4o+IiIjIgbD4IyIiInIgLP6IiIiIHAiLPyIiIiIHwuKPiIiIyIGw+CMiIiJyICz+iIiIiBwIiz8iIiIiB8Lij4iIiMiBsPgjIiIiciAs/oiIiIgcCIs/IiIiIgfC4o+IiIjIgbD4IyIiInIgLP6IiIiIHAiLPyIiIiIHwuKPiIiIyIGw+CMiIiJyICz+iIiIiBwIiz8iIiIiB8Lij4iIiMiBsPgjIiIiciAs/oiIiIgcCIs/IiIiIgeitHYARESWVFRUhE8//dRk2w8//AAA2Lx5s8l2nU6Hl156qd1iIyKyBoWIiLWDICKylLt376Jr164oLy+Hs7MzAKDh155CoTC2q6mpwauvvoqPP/7YGmESEbWXbD72JSK75urqikmTJkGpVKKmpgY1NTWora1FbW2t8b9ramoAAFOnTrVytERElsfij4js3tSpU1FdXf3ANp6ennj66afbKSIiIuth8UdEdm/06NHw9va+736VSoXp06dDqeRr0ERk/1j8EZHdc3JywrRp06BSqZrcX1NTwy96EJHDYPFHRA7hpZdeMr7bd6/u3btj2LBh7RwREZF1sPgjIofwxBNPICAgoNF2FxcXvPrqqybf/CUismcs/ojIYbz88suNHv1WV1fzkS8RORQWf0TkMKZNm9bo0W9ISAjCw8OtFBERUftj8UdEDqN3797o06eP8RGvSqXCzJkzrRwVEVH7YvFHRA7llVdeMa70UVtby0e+RORwWPwRkUN56aWXUFdXBwAYOHAgAgMDrRwREVH7YvFHRA7F398fTz75JADg1VdftXI0RETtj9PZO4Dk5GQcO3bM2mEQdRh3796FQqHA119/jaNHj1o7HKIOY968eZzz0gHwzp8DOHbsGP7+979bOwy7cuXKFezevdvaYdic3bt348qVK9YOA35+fujWrRvUarW1Q7FpHSWf1DZ2796Ny5cvWzsMage88+cghg4diuzsbGuHYTeysrIwZcoUjqmZFAoF5s6dixdffNHaoeCnn35CSEiItcOwaR0pn9R6nOjccfDOHxE5JBZ+ROSoWPwRERERORAWf0REREQOhMUfERERkQNh8UdERETkQFj8UbO88cYb0Ol0UCgUyM3NtXY4rVJfX4+UlBRERERYOxQcOHAAHh4e+Pzzz60dChEROQgWf9QsW7duxZYtW6wdRqudP38ev/vd7zBv3jxUVlZaOxyIiLVDICIiB8N5/shh/Pjjj1ixYgXmzJmDioqKDlF4jR07Frdv37Z2GACAqqoqPPPMM/j++++tHQoREVkQ7/xRs9n6BKD9+/dHTk4Opk2bBldXV2uH0+Fs27YNhYWF1g6DiIgsjMUfNUlEkJSUhEcffRSurq7w8PDAggULGrWrq6tDQkIC/P39odFo0K9fP2RmZgIA0tPT4ebmBq1Wi3379mHMmDHQ6/Xw8/PDzp07Tc5z5MgRPPHEE9BqtdDr9QgPD4fBYHhoH7bsu+++g7+/PxQKBT766CMAzR+zDRs2QK1Wo2vXrpg9ezZ8fX2hVqsRERGB48ePG9vFxsbCxcUFPj4+xm1vvfUW3NzcoFAoUFxcDACIi4vD/PnzUVBQAIVCYZwA+csvv4Rer8fq1avbY0iIiKgdsPijJi1btgzx8fGIiYnBL7/8ghs3bmDhwoWN2i1cuBDr1q1DSkoKrl+/jnHjxmHq1Kn44Ycf8Oabb2Lu3LmoqqqCTqdDZmYmCgoKEBQUhFmzZqGmpgYAUFFRgfHjx2PSpEm4efMmzp8/j0ceeQTV1dUP7cOWjRgxotEj1uaOWWxsLGbMmIHKykq8++67uHDhAk6cOIHa2lr84Q9/MK7PuWHDhkZLb6WlpeGDDz4w2Zaamopx48YhODgYIoKffvoJwK+FN/Drl2SIiMg+sPijRqqqqpCSkoLf//73mDdvHjw9PaHRaNCpUyeTdnfu3EF6ejoiIyMRFRUFT09PLF26FCqVChkZGSZtIyIioNfr4e3tjejoaFRUVODSpUsAgAsXLsBgMKBv375Qq9Xo1q0bcnJy0KVLF7P6sDcPGrMGSqUSjz32GFxdXdGnTx+kp6ejrKyszcZm7NixMBgMWLZsWZucj4iIrI/FHzXy008/obKyEs8888wD2509exaVlZUICwszbtNoNPDx8cGZM2fue5yLiwsAGO9iBQUFoWvXrpg+fTqWL1+OCxcutLoPe3PvmN3P4MGDodVqHWpsiIjIPCz+qJErV64AALy9vR/YrqKiAgCwdOlSKBQK4+fixYtmTaOi0Whw6NAhjBgxAqtXr0ZQUBCio6NRVVXVZn04EldXVxQVFVk7DCIi6qBY/FEjarUaAHD37t0HtmsoDlNSUiAiJp9jx46Z1Wffvn3x+eef49q1a4iPj0dmZibWr1/fpn04gpqaGpSWlsLPz8/aoRARUQfF4o8aCQsLg5OTE44cOfLAdj179oRarW71ih/Xrl3D6dOnAfxaUK5duxYDBw7E6dOn26wPR3H48GGICIYOHWrcplQqH/q4mIiIHAeLP2rE29sbUVFR2L17N7Zt2waDwYBTp05h8+bNJu3UajVmzpyJnTt3Ij09HQaDAXV1dbhy5QquX7/e7P6uXbuG2bNn48yZM6iursbJkydx8eJFDB06tM36sFf19fW4desWamtrcerUKcTFxcHf3x8zZswwtgkJCcHNmzexd+9e1NTUoKioCBcvXmx0rk6dOuHatWu4cOECysrKUFNTg4MHD3KqFyIieyNk9yZNmiSTJk0y65iysjJ54403pHPnzuLu7i4jRoyQhIQEASB+fn7y448/iojI3bt3JT4+Xvz9/UWpVIq3t7dERUVJfn6+pKWliVarFQASGhoqBQUFsnnzZtHr9QJAAgIC5Ny5c3LhwgWJiIgQLy8vcXZ2lu7du8uSJUuktrb2oX2Y49ixYzJ8+HDx9fUVAAJAfHx8JCIiQo4cOWLWuTIzM6W1Pz4bN24UHx8fASBarVbGjx/f7DETEYmJiRGVSiU9evQQpVIper1eJkyYIAUFBSb9lJSUyOjRo0WtVktgYKC88847smDBAgEgISEhcunSJREROXHihAQEBIhGo5ERI0bIjRs35MCBA6LT6WTVqlWtutYGACQzM7NNzkXWx3zaF+bTYWQpRDrAGldkUZMnTwYAZGdnWzkS+5GVlYUpU6ZYdYm42bNnIzs7GyUlJVaLwVwKhQKZmZmN5h4k28R82hfm02Fk87EvkQ1rmISZiIiouVj8kc06c+aMyfQv9/tER0dbO1QiIqIOg8Uf2azevXs3mv6lqc+uXbusHWqbW7x4MTIyMnD79m0EBgZi9+7d1g7J4r755hssWrQIOTk5CAoKMhb3L7/8cqO2zz77LHQ6HZydndG3b1+cOHHCChGbr76+HikpKYiIiGhy/4oVK9CnTx/o9Xq4uroiJCQE77//PsrLyxu1/etf/4ohQ4ZAp9MhICAAM2fOxI0bN4z7P/vsMyQmJlrt7jHzaV/5JBtjnXcNqT215Asf9GBt8YUPR4QWvlCekJAg48aNE4PBYNwWHBwsnTt3FgCyf//+RsccPHhQXnjhhVbF257OnTsnw4cPFwDSv3//JtuMGjVK0tLSpKSkRAwGg2RmZopKpZLnn3/epN2uXbsEgCQmJkppaamcPHlSgoKCZMCAAVJTU2Nsl5qaKqNGjZJbt261KGbm8/4cKZ9kc7J454+IOrQPP/wQu3btQlZWFnQ6ncm+DRs2wMnJCTExMbh9+7aVImy9H3/8EQsXLsScOXMwYMCA+7Zzd3dHTEwMOnXqBJ1OhxdffBGRkZH48ssvcfnyZWO7P//5z+jevTsWLFgADw8PDBgwAPPmzUNubi6OHz9ubPfuu++if//++OMf/4ja2lqLXmMD5vM/7CGfZJtY/BFRh/XTTz9h2bJl+OCDD4wrz/xWREQE4uLicPXqVbz33ntWiLBt9O/fHzk5OZg2bRpcXV3v227//v1wdnY22dalSxcAMFnu8PLly/D19YVCoTBu69mzJwA0muNx+fLlyM3NRWpqaquv42GYT1O2nk+yXSz+iKjD2rBhA0QE48ePv2+bVatW4ZFHHsHWrVvxzTffPPB8IoLk5GQ89thjcHV1hZeXFyZMmIAzZ84Y26Snp8PNzQ1arRb79u3DmDFjoNfr4efnh507d5qcr66uDgkJCfD394dGo0G/fv2QmZnZuos209WrV6HRaBAYGGjcFhQUhMLCQpN2De+HBQUFmWz38vLCqFGjkJqaavGpi5jPh7OlfJLtYvFHRB3WF198gUcffRRarfa+bTQaDT7++GM4OTlh1qxZqKiouG/b5cuXY9GiRViyZAkKCwtx9OhRXL58GSNHjsQvv/wCAHjzzTcxd+5cVFVVQafTITMzEwUFBQgKCsKsWbNMlspbuHAh1q1bh5SUFFy/fh3jxo3D1KlT8cMPP7TdIDxAZWUlDh06hFmzZsHFxcW4ffHixbhx4wY2btyIsrIy5OfnIzU1Fc8995zJ0n8NHn/8cVy9ehU//vijReNlPh/M1vJJtovFHxF1SBUVFfj5558RHBz80LbDhg3D3LlzceHCBSxcuLDJNlVVVUhOTsbEiRMxffp0eHh4IDw8HJs2bUJxcXGj5QuBXx9D6vV6eHt7Izo6GhUVFbh06RIA4M6dO0hPT0dkZCT6repWAAAgAElEQVSioqLg6emJpUuXQqVSISMjo3UX30xr1qyBr68vVq1aZbJ91KhRiI+PR2xsLPR6PcLCwlBWVoatW7c2eZ7Q0FAAQF5ensViZT4fzpbySbaNxZ+D2L17d7PmxOOneZ8pU6YAgNXjsLWPOQoLCyEiD7xL9FurVq3Co48+irS0NHz33XeN9ufn56O8vByDBw822T5kyBC4uLiYvDjflIY7MQ13is6ePYvKykqEhYUZ22g0Gvj4+Jg8drSUPXv2ICsrC1999VWjL04sWbIEmzdvxrfffovy8nL8+9//RkREBIYNG2byRYIGDWPccLfMEpjPB7O1fJJtU1o7AGofQ4cOxdy5c60dht04duwYUlNT2/19IFvXUDQ3x507dwDggS/M/5ZarUZGRgZGjBiB1157DYmJiSb7S0tLAfz6Dct7eXp6oqysrNmxATA+jly6dCmWLl1qss/X19esc5lr165dSE5OxuHDh9G9e3eTfdevX0diYiIWLVqEp59+GgAQGBiILVu2wMvLC0lJSdiwYYPJMRqNBsB/xtwSmM/7s8V8km1j8ecg/Pz8uF5jG0tNTeWYmsmc4q/hD5g5k9YOGzYM8+bNw/r167Fy5Ur4+/sb93l6egJAk0VBaWkp/Pz8mt0PAHh7ewMAUlJSEBcXZ9axrbFx40Z89dVXOHToUJOFz/nz51FXV9eoiNDr9ejUqRPy8/MbHVNdXQ3gP2NuCcxn02w1n2Tb+NiXiDqkrl27QqFQmD3f28qVK9G7d2+cPHnSZHtYWBjc3d0bvbx//PhxVFdXY9CgQWb107NnT6jVauTm5pp1XEuJCOLj45GXl4e9e/c2WSgAMBY9169fN9leVlaGmzdvGqcI+a2GMe7WrVsbR/0fzKcpW88n2TYWf0TUIWm1WgQFBeHKlStmHdfwuPDe+dPUajXmz5+PPXv2YMeOHTAYDMjLy8OcOXPg6+uLmJgYs/uZOXMmdu7cifT0dBgMBtTV1eHKlSvGP9TR0dHo1q1bmyxHdvr0aaxbtw5btmyBSqVq9D7l+vXrAfz6SHD06NHYsmULjh49iqqqKly+fNl4fa+//nqjczeMcXh4eKvjvB/m05St55NsnLXWFqH2w+Xd2h6Xd2sZmLl8VGxsrKhUKqmsrDRu27NnjwQHBwsA6dKli7z99ttNHrtgwYJGy4HV19dLUlKShIaGikqlEi8vL4mMjJSzZ88a26SlpYlWqxUAEhoaKgUFBbJ582bR6/UCQAICAuTcuXMiInL37l2Jj48Xf39/USqV4u3tLVFRUZKfny8iIpGRkQJAEhISHnidx44dk+HDh4uvr68AEADi4+MjERERcuTIERERycvLM+5r6pOUlGQ8X3FxscTFxUlISIi4urqKu7u7DB8+XD799NMm+x87dqz06NFD6uvrHxjnvZjPpjlKPslmZfGvlwNg8df2WPy1jLl/XM6fPy9KpVK2b99uwagsp66uTkaOHCnbtm2zdij3VVxcLGq1WtavX2/2scxnx9Oe+SSbxbV9iajjCgkJwYoVK7BixQqUl5dbOxyz1NXVYe/evSgrK0N0dLS1w7mv5cuXY8CAAYiNjbV4X8yn5bVnPsl2sfgjs+Xk5CAoKKjROyouLi7o2rUrnnrqKSQlJeHWrVvWDpXswKJFizB58mRER0eb/WUBazp8+DBycnJw8ODBZs9t196Sk5ORm5uLAwcOQKVStUufzKflWCOfZJtY/JHZoqKi8O9//xvBwcHw8PCAiKC+vh6FhYXIyspCYGAg4uPj0bdv33ZbFons2+rVqxEbG4u1a9daO5Rme+aZZ/DJJ5/Ax8fH2qE0ad++fbh79y4OHz4MLy+vdu2b+Wx71swn2R4Wf9QmFAoFPD098dRTTyEjIwNZWVn45ZdfMHbsWJv6v3tbUlVVhYiICJvvo7meffZZfPjhh9YOw2688MILWLRoUaNv0bYX5rNtWTufZFtY/JFFTJo0CTNmzEBhYSE2bdpk7XDs0rZt21BYWGjzfRARUfti8UcWM2PGDADAwYMHjdvq6uqQkJAAf39/aDQa9OvXz7hEWnp6Otzc3KDVarFv3z6MGTMGer0efn5+2Llzp8m5jxw5gieeeAJarRZ6vR7h4eEwGAwP7cOaRATJycl47LHH4OrqCi8vL0yYMMFk3dDY2Fi4uLiYPFp666234ObmBoVCgeLiYgBAXFwc5s+fj4KCAigUCoSEhGDDhg1Qq9Xo2rUrZs+eDV9fX6jVakRERJisc9qaPgDgyy+/hF6vx+rVqy06XkREZCHW/r4xWZ6lpnoJDg4WDw+P++43GAwCQHr27Gnc9t5774mrq6vs3r1bbt26JYsXLxYnJyf5xz/+ISIiS5YsEQDy7bffyu3bt6WwsFBGjhwpbm5uUl1dLSIi5eXlotfrJTExUaqqquTGjRsyceJEKSoqalYfbaElU70kJCSIi4uLbN++XUpLS+XUqVMycOBA6dKli9y4ccPYbtq0adKtWzeTY5OSkgSA8RpFRKKioiQ4ONikXUxMjLi5ucnp06flzp07kp+fL0OGDBGdTieXLl1qkz72798vOp1OVqxYYdb1i3AqCXvDfNoX5tNhcKoXshydTgeFQmFce/POnTtIT09HZGQkoqKi4OnpiaVLl0KlUiEjI8Pk2IiICOj1enh7eyM6OhoVFRW4dOkSAODChQswGAzo27cv1Go1unXrhpycHHTp0sWsPtpTVVUVkpOTMXHiREyfPh0eHh4IDw/Hpk2bUFxcjM2bN7dZX0ql0nh3sU+fPkhPT0dZWVmbXf/YsWNhMBiwbNmyNjkfERG1LxZ/ZDEVFRUQEej1egDA2bNnUVlZibCwMGMbjUYDHx8fk0ef93JxcQEA1NTUAACCgoLQtWtXTJ8+HcuXL8eFCxeMbVvah6Xl5+ejvLwcgwcPNtk+ZMgQuLi4mDyWbWuDBw+GVqu16vUTEVHHweKPLObcuXMAgN69ewP4tRgEgKVLl5rMD3jx4kVUVlY2+7wajQaHDh3CiBEjsHr1agQFBSE6OhpVVVVt1kdbKy0tBYAmF2/39PQ03h21FFdXVxQVFVm0DyIisg0s/shivvzySwDAmDFjAADe3t4AgJSUFIiIyefYsWNmnbtv3774/PPPce3aNcTHxyMzMxPr169v0z7akqenJwA0WeSVlpbCz8/PYn3X1NRYvA8iIrIdLP7IIm7cuIGUlBT4+fnhtddeAwD07NkTarUaubm5rTr3tWvXcPr0aQC/FpRr167FwIEDcfr06Tbro62FhYXB3d290aTXx48fR3V1NQYNGmTcplQqjY+428Lhw4chIhg6dKjF+iAiItvB4o9aRURQXl6O+vp6iAiKioqQmZmJ4cOHw9nZGXv37jW+86dWqzFz5kzs3LkT6enpMBgMqKurw5UrV3D9+vVm93nt2jXMnj0bZ86cQXV1NU6ePImLFy9i6NChbdZHW1Or1Zg/fz727NmDHTt2wGAwIC8vD3PmzIGvry9iYmKMbUNCQnDz5k3s3bsXNTU1KCoqwsWLFxuds1OnTrh27RouXLiAsrIyYzFXX1+PW7duoba2FqdOnUJcXBz8/f2NU++0to+DBw9yqhciIltmnW8ZU3tq66lePvvsM+nXr59otVpxcXERJycnASAKhUI8PT3liSeekBUrVkhJSUmjY+/evSvx8fHi7+8vSqVSvL29JSoqSvLz8yUtLU20Wq0AkNDQUCkoKJDNmzeLXq8XABIQECDnzp2TCxcuSEREhHh5eYmzs7N0795dlixZIrW1tQ/to620ZKqX+vp6SUpKktDQUFGpVOLl5SWRkZFy9uxZk3YlJSUyevRoUavVEhgYKO+8844sWLBAAEhISIhxypYTJ05IQECAaDQaGTFihNy4cUNiYmJEpVJJjx49RKlUil6vlwkTJkhBQUGb9XHgwAHR6XSyatUqs8cNnErCrjCf9oX5dBhZChERq1We1C4mT54MAMjOzrZyJPYjKysLU6ZMQUf78Zk9ezays7NRUlJi7VCapFAokJmZiRdffNHaoVAbYD7tC/PpMLL52JfIztTV1Vk7BCIi6sBY/BERERE5EBZ/RHZi8eLFyMjIwO3btxEYGIjdu3dbOyQiIuqAlNYOgIjaxpo1a7BmzRprh0FERB0c7/wRERERORAWf0REREQOhMUfERERkQNh8UdERETkQPiFDwdx5coVZGVlWTsMu3Hs2DEA4Ji2QMPYkX1gPolsD1f4cACTJ0/mtB9ERPRQXOHDIWSz+CMih9NRl+cjImoHXN6NiIiIyJGw+CMiIiJyICz+iIiIiBwIiz8iIiIiB8Lij4iIiMiBsPgjIiIiciAs/oiIiIgcCIs/IiIiIgfC4o+IiIjIgbD4IyIiInIgLP6IiIiIHAiLPyIiIiIHwuKPiIiIyIGw+CMiIiJyICz+iIiIiBwIiz8iIiIiB8Lij4iIiMiBsPgjIiIiciAs/oiIiIgcCIs/IiIiIgfC4o+IiIjIgbD4IyIiInIgLP6IiIiIHAiLPyIiIiIHwuKPiIiIyIGw+CMiIiJyICz+iIiIiBwIiz8iIiIiB8Lij4iIiMiBsPgjIiIiciAs/oiIiIgcCIs/IiIiIgfC4o+IiIjIgSitHQARkSVduXIFr776Kurq6ozbbt26BZ1Oh6eeesqk7aOPPoo///nP7RwhEVH7YvFHRHbNz88PFy9eREFBQaN9R44cMfnv3/3ud+0VFhGR1fCxLxHZvVdeeQUqleqh7aKjo9shGiIi62LxR0R2b9q0aaitrX1gm759+6JPnz7tFBERkfWw+CMiuxccHIx+/fpBoVA0uV+lUuHVV19t56iIiKyDxR8ROYRXXnkFzs7OTe6rra3F5MmT2zkiIiLrYPFHRA7hpZdeQn19faPtTk5OGDp0KHr16tX+QRERWQGLPyJyCL6+vhg+fDicnEx/7Tk5OeGVV16xUlRERO2PxR8ROYyXX3650TYRwcSJE60QDRGRdbD4IyKHMWnSJJP3/pydnfH73/8eXbt2tWJURETti8UfETkMLy8v/OEPfzAWgCKC6dOnWzkqIqL2xeKPiBzK9OnTjV/8UKlUmDBhgpUjIiJqXyz+iMihjB8/Hq6urgCAcePGwd3d3coRERG1LxZ/RORQ3NzcjHf7+MiXiByRQkTE2kFYU1ZWFqZMmWLtMIiIiKgdOHjZAwDZSmtH0FFkZmZaOwSiDiUlJQUAMHfuXCtH0vbq6uqQmZmJqVOntul5jx07htTUVP4+sRPMp31pyCcBLP7+vxdffNHaIRB1KNnZ2QDs92cjMjISarW6zc+bmppqt2PmiJhP+8Li71d854+IHJIlCj8iIlvA4o+IiIjIgbD4IyIiInIgLP6IiIiIHAiLPyIiIiIHwuLPTEOGDIGzszMGDBjQ7n3PnDkTarUaCoUCd+7caff+O6L169eja9euUCgU2LRpk3H7gQMH4OHhgc8//9yi/bdXP82xatUqKBSKRp+wsDCrxtWRxoiIiFj8me0f//gHRo8ebZW+MzIy8N5771ml747qvffew/fff99oe3tN4snJQh+OY0RE1LGw+GshhULR6nNUVVUhIiKiDaKhe40dOxa3b9/GuHHj2uycTeXLEv20xvbt2yEiJp9//vOfVo2pI40Rf+aIiFj8tZhKpWr1ObZt24bCwsIWHdsWxSeZpzX5oo6BOSQiYvHXYj/99BN69+4NNzc3aDQajBw5Et99951Jm7/97W/o06cPPDw8oFarER4ejq+++goAEBcXh/nz56OgoAAKhQIhISHG47Zv347BgwdDrVbDzc0NvXr1wsqVK437nZyc8MUXX2DMmDHw8PCAr68v/vKXv5h9Denp6XBzc4NWq8W+ffswZswY6PV6+Pn5YefOnSZtRQTJycl47LHH4OrqCi8vL0yYMAFnzpwxtlm3bh20Wi10Oh0KCwsxf/589OjRA3PmzIGbmxucnJwwaNAgdOvWDSqVCm5ubhg4cCBGjhyJnj17Qq1Ww9PTE++//36zx7Ep3333Hfz9/aFQKPDRRx8B+DVfTb0Pp1Ao8D//8z8tyldT/TR3rMwZe1vW1Bg199o3bNgAtVqNrl27Yvbs2fD19YVarUZERASOHz9ubBcbGwsXFxf4+PgYt7311ltwc3ODQqFAcXExgPv/zH355ZfQ6/VYvXp1ewwJEZH1iYPLzMwUc4fhmWeekaCgIPn555+lpqZG/vnPf8qTTz4parVazp07Z2yXnZ0ty5cvl5s3b0pJSYkMHTpUOnfubNwfFRUlwcHBJudOSUkRALJ27VopKSmRmzdvyp///GeZNm2aiIgsWbJEAMi3334rpaWlcvPmTfnjH/8orq6uUlFRYfb1//Z8t2/flsLCQhk5cqS4ublJdXW1sV1CQoK4uLjI9u3bpbS0VE6dOiUDBw6ULl26yI0bNxqd791335WNGzfKxIkT5V//+pf86U9/EgBy/PhxqaiokOLiYnn++ecFgHzxxRdSVFQkFRUVEhsbKwAkNze32eN4/vx5ASD//d//bdx2+fJlASAbN240tlm4cKFxjK5fvy5eXl4SEREhdXV1Lc7Xvf20ZKweNvbNtXLlSvHz8xNPT09RqVTSq1cveeGFF+T//u//zD6XiMikSZNk0qRJLTr2t5oao+Zee0xMjLi5ucnp06flzp07kp+fL0OGDBGdTieXLl0ytps2bZp069bNpN+kpCQBIEVFRcZtTeVw//79otPpZMWKFa2+1pb8PqGOi/m0L8ynURbv/LWQTqdDr169oFQq0bdvX2zZsgV37tzB5s2bjW0mTZqEP/3pT/Dy8kKnTp0wfvx4lJSUoKioqMlz1tTU4IMPPsDo0aOxcOFCdOrUCV5eXnj99dcxZMgQk7YRERHw8PCAl5cXoqOjcffuXfz8888tvp6IiAjo9Xp4e3sjOjoaFRUVuHTpEoBf35NKTk7GxIkTMX36dHh4eCA8PBybNm1CcXGxyTU3+PDDD/H2228jJycHvXv3Nm7v06cPtFotOnfujJdeegkA4O/vjy5dukCr1WL69OkAYHKXzNxxbEpISAjWrl0LrVYLAHjzzTdRVVWFv/zlL3BycmqzfloyVg8ae3O8+uqr+Oyzz3D58mWUl5dj586duHTpEkaNGoX8/Hyzz9cemnPtSqXSeBe1T58+SE9PR1lZGTIyMtokhrFjx8JgMGDZsmVtcj4ioo6OxV8bCQ8Ph4eHB06dOnXfNg3vCdbV1TW5/9SpUygtLcVzzz1nst3Z2RnvvvvuQ89bU1NjbthNcnFxMTlffn4+ysvLMXjwYJN2Q4YMgYuLi8kjuJb0U1tba9zWnGt52Dg+TFZWFj799FN88MEHePTRR9u0n9aO1b1jb46ePXvi8ccfh7u7O1xcXDB06FBkZGSgqqoKaWlpZp+vvTX32gcPHgytVmvyPwhERNR8SmsHYE9UKpXJH64vvvgCSUlJyM/Ph8FgeOgfNYPBAADw9PS0aJzmKi0tBQC4u7s32ufp6YmysjKL9m/uOD5ISUkJ3nnnHQwZMgTz589v836sPVb3Cg8Ph7OzM86dO9eu/Vqaq6urWXdkiYjoP3jnr43U1tbi5s2b8Pf3BwBcunQJkZGR8PHxwfHjx3H79m0kJiY+8Bzdu3cHAOML6h1FQzHaVOFSWloKPz8/i/XdknF8kHfffRelpaXIyMiAs7Nzm/djzbFqSn19Perr6+Hq6tqu/VpSTU2NVcaSiMhesPhrI//7v/+L+vp6DBw4EACQl5eHmpoavPnmmwgKCjKuzPEgvXr1QqdOnfD111+3R8jNFhYWBnd3d/zwww8m248fP47q6moMGjTIYn23ZBzv54svvsAnn3yCZcuWoW/fvsbtCxYsaLN+rDlW974uAPw6KbmIYNiwYRbrt70dPnwYIoKhQ4catymVyjZ77YGIyN6x+Guh6upq3L59G7W1tThx4gRiY2MREBCAGTNmAIDxDuA333yDO3fu4Pz5843e9+rUqROuXbuGCxcuoKysDE5OTli8eDGOHj2K2NhYXL16FfX19SgrK8Pp06fb+xKN1Go15s+fjz179mDHjh0wGAzIy8vDnDlz4Ovri5iYGIv13ZxxbA6DwYDZs2djwIABWLhwIQDgzp07+OGHH5Cbm9uifDVVbFhzrK5evYpdu3ahtLQUNTU1OHbsGN544w34+/tjzpw5FuvX0urr63Hr1i3U1tbi1KlTiIuLg7+/v/FnDfj1Cz03b97E3r17UVNTg6KiIly8eLHRuZrK4cGDBznVCxE5Fmt/39jaWvLV74yMDBk9erR07dpVlEqldO7cWV566SW5ePGiSbv4+Hjp1KmTeHp6yuTJk+Wjjz4SABIcHCyXLl2SEydOSEBAgGg0GhkxYoRxGpCPPvpIwsPDRa1Wi1qtlscff1zS0tIkMTFRNBqNAJDQ0FApKCiQHTt2iJeXlwAQPz8/+ec//9ns60hLSxOtVmtyvs2bN4terxcAEhAQYJy6pr6+XpKSkiQ0NFRUKpV4eXlJZGSknD171ni+38bXs2dP2b59u4iIpKamGvvp1auX/O1vf5MPP/xQPDw8BIB069ZNPvnkE9m1a5d069ZNAIiXl5fs3LnzoeMYFxdnPMbNzU0mTpwoGzduFB8fHwEgWq1Wxo8fL+vXrxcATX7++Mc/tihfS5cubdRPc8fKnLFvrvnz50twcLC4ubmJUqkUPz8/mTVrlly7ds2s8zRoi6lemsqFOdceExMjKpVKevToIUqlUvR6vUyYMEEKCgpM+ikpKZHRo0eLWq2WwMBAeeedd2TBggUCQEJCQozTwjT1M3fgwAHR6XSyatWqVl2rCKeSsDfMp31hPo2yFCKOvfBmVlYWpkyZwvVHie4xefJkAEB2drbVYpg9ezays7NRUlJitRjMwd8n9oX5tC/Mp1E2H/sSUYfW0il9iIioaSz+7MyZM2fuu4zZbz/R0dHWDpUegrl0PN988w0WLVqEnJwcBAUFGXP88ssvN2r77LPPQqfTwdnZGX379sWJEyesELH56uvrkZKSgoiIiCb3r1ixAn369IFer4erqytCQkLw/vvvo7y8vFHbv/71rxgyZAh0Oh0CAgIwc+ZM3Lhxw7j/s88+Q2JiotX+B4L5tK982hVrPnTuCPgOAFHT2mp5t5ZatGiRuLi4GN8Vzc7OtloszdWa3ycJCQkybtw4MRgMxm3BwcHSuXNnASD79+9vdMzBgwflhRdeaHG87e3cuXMyfPhwASD9+/dvss2oUaMkLS1NSkpKxGAwSGZmpqhUKnn++edN2u3atUsASGJiopSWlsrJkyclKChIBgwYIDU1NcZ2qampMmrUKLl165bZ8TKfD+ZI+bQzWQ4/CvzHQNQ0axd/tqilv0/Wrl0rjzzyiFRVVZlsDw4Olk8++UScnJykR48eUlpaarLfloqF3NxcmThxouzYsUMGDBhw32Jh7NixUltba7LtxRdfFAAm6zmPHj1aunfvLvX19cZtDV/S+u6770yOj42NlWHDhpkUEc3BfN6fI+XTDnFtXyIia/rpp5+wbNkyfPDBB1Cr1Y32R0REIC4uDlevXsV7771nhQjbRv/+/ZGTk4Np06Y9cNLx/fv3m0zADgBdunQBAFRWVhq3Xb58Gb6+vibzcfbs2RMAGk3zs3z5cuTm5iI1NbXV1/EwzKcpW8+nvWLxR0RkRRs2bICIYPz48fdts2rVKjzyyCPYunUrvvnmmweeT0SQnJyMxx57DK6urvDy8sKECRNM1kJOT0+Hm5sbtFot9u3bhzFjxkCv18PPzw87d+40OV9dXR0SEhLg7+8PjUaDfv36ITMzs3UXbaarV69Co9EgMDDQuC0oKAiFhYUm7RreDwsKCjLZ7uXlhVGjRiE1NdXi3/RkPh/OlvJpr1j8ERFZ0RdffIFHH30UWq32vm00Gg0+/vhjODk5YdasWaioqLhv2+XLl2PRokVYsmQJCgsLcfToUVy+fBkjR47EL7/8AgB48803MXfuXFRVVUGn0yEzMxMFBQUICgrCrFmzTCYwX7hwIdatW4eUlBRcv34d48aNw9SpUxutYmMplZWVOHToEGbNmgUXFxfj9sWLF+PGjRvYuHEjysrKkJ+fj9TUVDz33HMmq780ePzxx3H16lX8+OOPFo2X+XwwW8unvWLxR0RkJRUVFfj5558RHBz80LbDhg3D3LlzceHCBeMqNfeqqqpCcnIyJk6ciOnTp8PDwwPh4eHYtGkTiouLsXnz5kbHREREQK/Xw9vbG9HR0aioqMClS5cA/LoKTnp6OiIjIxEVFQVPT08sXboUKpUKGRkZrbv4ZlqzZg18fX2xatUqk+2jRo1CfHw8YmNjodfrERYWhrKyMmzdurXJ84SGhgL4dclIS2E+H86W8mnPlNYOoKPIysqydghEHcqVK1cA8GfDHMeOHTOrfWFhIUTkgXeJfmvVqlXYv38/0tLSMGXKlEb78/PzUV5ejsGDB5tsHzJkCFxcXB66NGLDnZiGO0Vnz55FZWUlwsLCjG00Gg18fHxMHjtayp49e5CVlYWvv/4aOp3OZN+SJUuwdetWfPvtt3jyySdRWFiIhQsXYtiwYfj++++N74s1aBjjhrtllsB8Ppit5dOesfj7/5r6wSMi/mxY0p07dwDggS/M/5ZarUZGRgZGjBiB1157DYmJiSb7S0tLAQDu7u6NjvX09ERZWZlZ8TU8jly6dCmWLl1qss/X19esc5lr165dSE5OxuHDh9G9e3eTfdevX0diYiIWLVqEp59+GgAQGBiILVu2wMvLC0lJSdiwYYPJMRqNBsB/xtwSmM/7s8V82jM+9v3/RIQffvj5zWfSpEmYNGmS1eOwpY+5L843/AEzZ9LaYcOGYd68eTh//jxWrlxpss/T0xMAmiwKSktL4efnZ1Z83t7eAICUlJRG12ruXU5zbNy4ETt27MChQ4caFQoAcExTpykAACAASURBVP78edTV1TXap9fr0alTJ+Tn5zc6prq6GsB/xtwSmM+m2Wo+7RmLPyIiK+natSsUCgVu375t1nErV65E7969cfLkSZPtYWFhcHd3b/Ty/vHjx1FdXY1BgwaZ1U/Pnj2hVquRm5tr1nEtJSKIj49HXl4e9u7d2+QdLwDGouf69esm28vKynDz5s1GjwgBGMe4W7dubRz1fzCfpmw9n/aMxR8RkZVotVoEBQUZ369srobHhffOn6ZWqzF//nzs2bMHO3bsgMFgQF5eHubMmQNfX1/ExMSY3c/MmTOxc+dOpKenw2AwoK6uDleuXDH+oY6Ojka3bt3aZDmy06dPY926ddiyZQtUKlWjpQzXr18P4NdHgqNHj8aWLVtw9OhRVFVV4fLly8bre/311xudu2GMw8PDWx3n/TCfpmw9n3ZNHBxn/CZqGlf4MF9Lfp/ExsaKSqWSyspK47Y9e/ZIcHCwAJAuXbrI22+/3eSxCxYsaLQiRH19vSQlJUloaKioVCrx8vKSyMhIOXv2rLFNWlqaaLVaASChoaFSUFAgmzdvFr1eLwAkICBAzp07JyIid+/elfj4ePH39xelUine3t4SFRUl+fn5IiISGRkpACQhIeGB13ns2DEZPny4+Pr6CgABID4+PhIRESFHjhwREZG8vDzjvqY+SUlJxvMVFxdLXFychISEiKurq7i7u8vw4cPl008/bbL/sWPHSo8ePUxWkHgY5vP+HCWfdorLu/EfA1HTWPyZryW/T86fPy9KpVK2b99uoagsq66uTkaOHCnbtm2zdij3VVxcLGq1WtavX2/Wccxnx9Se+bRTXN6NiMiaQkJCsGLFCqxYsQLl5eXWDscsdXV12Lt3L8rKyhAdHW3tcO5r+fLlGDBgAGJjYy3eF/Npee2ZT3vF4o+IyMoWLVqEyZMnIzo62uwvC1jT4cOHkZOTg4MHDzZ7brv2lpycjNzcXBw4cAAqlapd+mQ+Lcca+bRHLP4sLCcnB0FBQY1edFUqlejSpQt+//vf/7/27j0qyuvcH/h3EIZhYIaLICKIcvESFWONpDrqMTZtEmNNRDRiNG1Ma9FoECUG7zXGOx7geOFYL6FraaqAGk2MmpzEktQV6zo50UKxUUOCd8JFcbgpIzy/P/JjmhFUbjMvzHw/a80f2bPfvZ93bwiP72VvHDx40OpxTJ8+HRqNBiqV6qHrIt0f7yuvvNKgzjPPPAOdTodOnTqhf//+bfJgsDVt3LjR/Bbetm3bzOVHjx6Fp6cnPvzwQ6v2b6t+qGNbvXo14uLisHbtWqVDabKnn34a7733Hrp27ap0KI06fPgw7t69i+zsbHh7e9u0b85n21NyPu0Nkz8ri46OxnfffYewsDB4enqa11QqLi5GRkYGrl27hujoaKtvrJ2eno4333yzWfF27twZe/bswUcffWRR55NPPkFWVhbGjRuHvLw8DB482Fpht4k333wTX375ZYNyEdtsCG6rfqjje+aZZ7Bu3Tqlw7AbL774IhYtWtTgLVpb4Xy2LaXn054w+VOIt7c3nn76afzXf/0XgOZvoVVdXQ2DwWCN0Mw2bdoEJycnxMbGdqhbF001duxY3L59G+PGjWuzNhubF2v04yhs8XNuiz6IiNoTJn8K69mzJ4B/b+PTVLt27UJRUVGL+lSpVE2qZzAYEB8fj2vXrjXpqiG1bl6oIVuMJ+eMiBwNkz+F5eTkAABGjRplUf63v/0N/fr1g6enJzQaDSIiIvDxxx8DAOLj45GQkID8/HyoVCqEh4ebj9u9ezeGDBkCjUYDd3d39OzZ02LLICcnJ3z00UcYM2YMPD09ERAQgHffffeB8a1atQq9e/fGzp078emnnz70XEQEycnJeOyxx+Dq6gpvb2+MHz/eYsPwDRs2QKvVQqfToaioCAkJCQgMDMSsWbPg7u4OJycnPPHEE/D394eLiwvc3d0xePBgjBw50rw6vZeXF956660mj1djTp48ieDgYKhUKmzZsgUA8O233zZ4NrP+8z//8z8tmpfG+mnqWKWlpcHd3R1arRaHDx/GmDFjoNfrERQUhL179z50LpTSlPOKi4uDWq22eK5o9uzZcHd3h0qlQklJCYDGx3PTpk3QaDTo0qULZs6ciYCAAGg0GhgMBotN7lvTBwAcP34cer0eq1evtup4EREpQsF1ZtoFW637ExYWJp6enub/rqqqkmPHjkmPHj3kmWeekYqKCov6WVlZsmLFCrl586aUlpbK0KFDpXPnzubvo6OjJSwszOKYlJQUASBr166V0tJSuXnzpvzpT3+SqVOniojIkiVLBIB89tlnUlZWJjdv3pTnn39eXF1dpbKyskG833//vYiIfPnll+Lk5CQ9e/Y0x3ns2LEGi5EuX75c1Gq17N69W8rKyiQnJ0cGDx4svr6+UlhYaK5XH8fcuXNl8+bNMmHCBPnXv/4lf/zjHwWAnD59WiorK6WkpESee+45ASAfffSRFBcXS2VlpcTFxQkAOXv2bJPH6+LFiwJA/vu//9tcduXKFQEgmzdvNtdZuHCheSxu3Lgh3t7eYjAYpLa2tsXzcn8/LRmrzz77TG7fvi1FRUUycuRIcXd3l5qaGrGmlqzz19Tzmjp1qvj7+1scm5SUJACkuLjYXNbYeMbGxoq7u7ucO3dO7ty5I3l5eRIZGSk6nU4uX77cJn0cOXJEdDqdrFy5slnnz3XE7Avn075wPs24zp8t3b5923wlSavVmq/kTJ06tcEr6xMnTsQf//hHeHt7w8fHBy+88AJKS0tRXFzcaNsmkwlvv/02Ro8ejYULF8LHxwfe3t743e9+h8jISIu6BoMBnp6e8Pb2RkxMDO7evYvvv//+gXEPGzYM8+bNQ0FBARYuXNhonerqaiQnJ2PChAmYNm0aPD09ERERgW3btqGkpATbt29vcMy6deswZ84cHDhwAH379jWX9+vXD1qtFp07d8aUKVMAAMHBwfD19YVWq8W0adMAwOJqUnPHqzHh4eFYu3ateYmD119/HdXV1Xj33Xfh5OTUZv20ZKwMBgP0ej38/PwQExODyspKXL58ucl92kJLzqulnJ2dzVcX+/Xrh7S0NJSXlyM9Pb1N2h87diyMRiOWLVvWJu0REbUnTP5s6Kdv+5pMJly9ehXz5s1DXFwcBg4caL4V1Zj65LC2trbR73NyclBWVoZnn33WorxTp06YO3fuI9s1mUwPjX3VqlXo06cPtm7dipMnTzb4Pi8vDxUVFRgyZIhFeWRkJNRqtcUtueZQq9UAgHv37jUr5keN16NkZmbi/fffx9tvv40+ffq0aT+tHav6MXnUnNmatX4GmmLIkCHQarUW/yAgIqLGMflTiLOzMwIDAzF9+nRs3LgR58+ft1gP6qOPPsJTTz0FPz8/uLq6NnjG7X5GoxEA4OXlZZV46zceV6lUeO2111BdXW3xff0LKx4eHg2O9fLyQnl5uVXiqtfc8XqY0tJSvPHGG4iMjERCQkKb96P0WFmL0ufl6urarCuwRESOislfOxAREQEAOHfuHADg8uXLiIqKQteuXXH69Gncvn0b69evf2gb3bp1A4CHXj1srWHDhmH+/Pm4ePGixUskwL+Tzsb+wJeVlSEoKMhqcbVkvB5m7ty5KCsrQ3p6usV6Um3Vj5JjZU1KnpfJZOrQY0dEZEtM/tqB//u//wMA8+3F3NxcmEwmvP766wgNDTXvzPEwPXv2hI+PDz755BOrxvrOO++gb9++OHPmjEX5gAED4OHhga+++sqi/PTp06ipqcETTzxhtZhaMl4P8tFHH+G9997DsmXL0L9/f3P5ggUL2qwfJcfKmppzXs7Ozm162zo7OxsigqFDh1qtDyIie8Hkz8aqq6tRV1cHEcH169eRnp6OpUuXwtfXF/PmzQPw48sNAPDpp5/izp07uHjxYoPnpXx8fHD9+nUUFBSgvLwcTk5OWLx4Mb744gvExcXh2rVrqKurQ3l5ufmKYluov/17/wrrGo0GCQkJOHjwIPbs2QOj0Yjc3FzMmjULAQEBiI2NbbMY7teU8WoKo9GImTNnYtCgQeYXW+7cuYOvvvoKZ8+ebdG8NJZ8KDlW1tSc8woPD8fNmzdx6NAhmEwmFBcX49KlSw3afNB41tXV4datW7h37x5ycnIQHx+P4OBgvPrqq23Sx7Fjx7jUCxHZL2XfNlaetV/9PnjwoISFhQmABh9XV1fp1auXvP766xZLVIiIJCYmio+Pj3h5ecmkSZNky5YtAkDCwsLk8uXL8vXXX0uPHj3Ezc1NRowYYV5GY8uWLRIRESEajUY0Go387Gc/k61bt8r69evFzc1NAEivXr0kPz9f9uzZI97e3gJAgoKC5J///KdFvL6+vjJnzpxGz2vBggUNlnqpq6uTpKQk6dWrl7i4uIi3t7dERUXJ+fPnzXV+Gkf37t1l9+7dIiKSmpoqWq1WAEjPnj3lb3/7m6xbt048PT0FgPj7+8t7770n+/btE39/fwEg3t7esnfv3keOV3x8vPkYd3d3mTBhgmzevFm6du0qAESr1coLL7wgGzdubHSeAMjzzz/fonlZunRpg36aOlZbt241j0n9nG3fvl30er0AkB49esiFCxda8+P5UC1Z6qUp5yUiUlpaKqNHjxaNRiMhISHyxhtvyIIFCwSAhIeHm38fGvs5j42NFRcXFwkMDBRnZ2fR6/Uyfvx4yc/Pb7M+jh49KjqdTlatWtWs8+dSEvaF82lfOJ9mmSoRx954NDMzE5MnT+b+q0T3mTRpEgAgKytL4UgszZw5E1lZWSgtLVU6lAb4/xP7wvm0L5xPsyze9iWiDqelS/gQERGf+SMiIiJyKEz+iKjDWLx4MdLT03H79m2EhIRg//79SodERNThOCsdABFRU61ZswZr1qxROgwiog6NV/6IiIiIHAiTPyIiIiIHwuSPiIiIyIEw+SMiIiJyIHzh4/+rX9CWiH7097//HQB/N5rj6tWrADhm9oLzaV/q55MAh9/h49SpU0hOTlY6DCKyocLCQpw5cwZjxoxROhQisrH2tmuRArIcPvkjIsfDbZ6IyIFxezciIiIiR8Lkj4iIiMiBMPkjIiIiciBM/oiIiIgcCJM/IiIiIgfC5I+IiIjIgTD5IyIiInIgTP6IiIiIHAiTPyIiIiIHwuSPiIiIyIEw+SMiIiJyIEz+iIiIiBwIkz8iIiIiB8Lkj4iIiMiBMPkjIiIiciBM/oiIiIgcCJM/IiIiIgfC5I+IiIjIgTD5IyIiInIgTP6IiIiIHAiTPyIiIiIHwuSPiIiIyIEw+SMiIiJyIEz+iIiIiBwIkz8iIiIiB8Lkj4iIiMiBMPkjIiIiciBM/oiIiIgcCJM/IiIiIgfC5I+IiIjIgTD5IyIiInIgTP6IiIiIHIiz0gEQEVmTyWRCRUWFRVllZSUA4NatWxblKpUKXl5eNouNiEgJTP6IyK7dvHkTgYGBqK2tbfCdj4+PxX+PHj0aJ06csFVoRESK4G1fIrJr/v7++I//+A84OT38f3cqlQpTpkyxUVRERMph8kdEdu+VV155ZJ1OnTphwoQJNoiGiEhZTP6IyO5FR0fD2fnBT7l06tQJzz33HDp37mzDqIiIlMHkj4jsnl6vx5gxYx6YAIoIpk2bZuOoiIiUweSPiBzCtGnTGn3pAwDUajV+/etf2zgiIiJlMPkjIofw61//GlqttkG5i4sLoqKi4O7urkBURES2x+SPiByCRqPBhAkT4OLiYlFuMpkwdepUhaIiIrI9Jn9E5DBefvllmEwmizK9Xo9f/epXCkVERGR7TP6IyGH88pe/tFjY2cXFBVOmTIFarVYwKiIi22LyR0QOw9nZGVOmTDHf+jWZTHj55ZcVjoqIyLaY/BGRQ5kyZYr51q+/vz9GjBihcERERLbF5I+IHIrBYEBgYCAA4De/+c0jt30jIrI3D17ynjqEq1ev4ssvv1Q6DKIOJTIyEteuXUPnzp2RmZmpdDhEHcpLL72kdAjUSioREaWDoJbLzMzE5MmTlQ6DiIgcBNOGDi+LV/7sBH8Z259JkyYBALKyshSOpOOo/8eMLX6e9+/fj4kTJ1q9H0dmy/kk6+PFBvvBh12IyCEx8SMiR8Xkj4iIiMiBMPkjIiIiciBM/oiIiIgcCJM/IiIiIgfC5I+IiIjIgTD5I/z+97+HTqeDSqXC2bNnlQ6nXblz5w769u2LpUuXKhbD0aNH4enpiQ8//FCxGIiIyH4w+SPs3LkTO3bsUDqMdmnJkiU4f/68ojFwjTQiImpLTP7I7lRXV8NgMLS6nS+//BL//Oc/2yCi1hk7dixu376NcePGKR1Km40tEREph8kfAQBUKpXSIbSZXbt2oaioqFVtVFdXY8GCBUhNTW2jqOxDW4wtEREpi8mfAxIRJCUloU+fPnB1dYWnpycWLFhgUWfDhg3QarXQ6XQoKipCQkICAgMDcf78eYgIkpOT8dhjj8HV1RXe3t4YP348vvnmG/PxmzZtgkajQZcuXTBz5kwEBARAo9HAYDDg9OnTDeJ5VHtxcXFQq9Xo2rWruWz27Nlwd3eHSqVCSUkJACA+Ph4JCQnIz8+HSqVCeHh4i8ZoyZIlmD17Nvz8/Fp0fFs5efIkgoODoVKpsGXLFgBAWloa3N3dodVqcfjwYYwZMwZ6vR5BQUHYu3ev+dimzkFrx/b48ePQ6/VYvXq1LYaEiIhaS6hDy8jIkOZO45IlS0SlUsl//ud/yq1bt6Sqqkq2bt0qAOTMmTMW9QDI3LlzZfPmzTJhwgT517/+JcuXLxe1Wi27d++WsrIyycnJkcGDB4uvr68UFhaaj4+NjRV3d3c5d+6c3LlzR/Ly8iQyMlJ0Op1cvnzZXK+p7U2dOlX8/f0tziUpKUkASHFxsbksOjpawsLCmjUmP3Xy5El54YUXRESkuLhYAMiSJUua3c7EiRNl4sSJLY6j3pUrVwSAbN682VxWPzefffaZ3L59W4qKimTkyJHi7u4uNTU15npNnYPWjO2RI0dEp9PJypUrW32uLfl5pvaL82lfOJ92I5NX/hxMdXU1UlJS8Mtf/hLz58+Hl5cX3Nzc4OPj88Bj1q1bhzlz5uDAgQPo0aMHkpOTMWHCBEybNg2enp6IiIjAtm3bUFJSgu3bt1sc6+zsbL6i169fP6SlpaG8vBzp6enmeJrTnrVVV1cjPj4eaWlpNu23pQwGA/R6Pfz8/BATE4PKykpcvnzZos6j5qC1xo4dC6PRiGXLlrVJe0REZF1M/hzMt99+i6qqKjz99NMtOj4vLw8VFRUYMmSIRXlkZCTUanWDW7r3GzJkCLRarfmWbmvba2uLFy/GH/7wBwQGBtq037agVqsBACaT6aH17p8DIiJyLEz+HMzVq1cBoMXPspWVlQEAPDw8Gnzn5eWF8vLyR7bh6uqK4uLiNmuvrZw8eRK5ubn4/e9/b7M+lfLTOSAiIsfC5M/BaDQaAMDdu3dbdLyXlxcANJqUlZWVISgo6KHHm0wmi3qtba8t7dq1C5999hmcnJygUqmgUqnMSfLq1auhUqnw1Vdf2Swea7l/DoiIyLEw+XMwAwYMgJOTEz7//PMWH+/h4dEgCTp9+jRqamrwxBNPPPT47OxsiAiGDh3a7PacnZ0feUuzNdLT0yEiFp/6q2NLliyBiDS4Pd0R3T8HgPXHloiI2g8mfw7Gz88P0dHR2L9/P3bt2gWj0YicnJwmv1ih0WiQkJCAgwcPYs+ePTAajcjNzcWsWbMQEBCA2NhYi/p1dXW4desW7t27h5ycHMTHxyM4OBivvvpqs9sLDw/HzZs3cejQIZhMJhQXF+PSpUsNYvTx8cH169dRUFCA8vJyh09qHjUHQOvG9tixY1zqhYioA2Hy54DeffddTJ8+HYmJiQgMDMTs2bMxcuRIAMC4ceOQk5ODDRs2IDk5GQDQu3dv7Nmzx3z8H//4R6xZswYrV66Er68vRo0ahZ49eyI7Oxvu7u4Wfd25cwcRERFwc3PDyJEj0bt3b/z1r3+Fq6trs9t7/fXXMXr0aEyZMgV9+vTBO++8Azc3NwDAsGHDcOXKFQDArFmz0KVLF/Tr1w/PP/88bt68aZ2BtIEtW7YgMjISAJCYmIgXX3wRaWlpSElJAQAMHDgQ3333HXbs2IGEhAQAwHPPPYeLFy+a22jKHDji2BIROSqVCDcO7cgyMzMxefLkdrn/68yZM5GVlYXS0lKlQ1HEpEmTAABZWVmKxdDR5qA9/zxT83E+7Qvn025k8cofWVVtba3SITg8zgEREf0Ukz+ya9988435zd2HfWJiYpQOldrAp59+ikWLFuHAgQMIDQ01z+8rr7zSoO4zzzwDnU6HTp06oX///vj6668ViLj56urqkJKSAoPB0Oj3K1euRL9+/aDX6+Hq6orw8HC89dZbqKioaFD3L3/5CyIjI6HT6dCjRw9Mnz4dhYWF5u8/+OADrF+/XrF/QHA+7Ws+qR1RZGMRajPtdbudRYsWiVqtFgDSs2dPycrKUjokm2ur7d1aqiPOQWt+npcvXy7jxo0To9FoLgsLC5POnTsLADly5EiDY44dOyYvvvhii+O1tQsXLsjw4cMFgDz++OON1hk1apRs3bpVSktLxWg0SkZGhri4uMhzzz1nUW/fvn0CQNavXy9lZWVy5swZCQ0NlUGDBonJZDLXS01NlVGjRsmtW7eaHS/n8+EcaT6pXcnkLHZw/GVsv5RO/jqilv48r127Vnr37i3V1dUW5WFhYfLee++Jk5OTBAYGSllZmcX3HSlZOHv2rEyYMEH27NkjgwYNemCyMHbsWLl3755F2UsvvSQALPZzHj16tHTr1k3q6urMZVu2bBEAcvLkSYvj4+LiZNiwYRZJRFNwPh/MkeaT2h3u7UtEHdu3336LZcuW4e233zYvYv5TBoMB8fHxuHbtGt58800FImwbjz/+OA4cOICpU6davKl9vyNHjqBTp04WZb6+vgCAqqoqc9mVK1cQEBAAlUplLuvevTsANFjmZ8WKFTh79ixSU1NbfR6Pwvm01NHnk9onJn9E1KFt2rQJIoIXXnjhgXVWrVqF3r17Y+fOnfj0008f2p6IIDk5GY899hhcXV3h7e2N8ePHW+yFnJaWBnd3d2i1Whw+fBhjxoyBXq9HUFAQ9u7da9FebW0tli9fjuDgYLi5uWHgwIHIyMho3Uk307Vr1+Dm5oaQkBBzWWhoKIqKiizq1T8fFhoaalHu7e2NUaNGITU11epvenI+H60jzSe1T0z+iKhD++ijj9CnTx9otdoH1nFzc8Of//xnODk5YcaMGaisrHxg3RUrVmDRokVYsmQJioqK8MUXX+DKlSsYOXIkfvjhBwA/ros4b948VFdXQ6fTISMjA/n5+QgNDcWMGTMsFhZfuHAhNmzYgJSUFNy4cQPjxo3Dyy+/bLOtAquqqnDixAnMmDEDarXaXL548WIUFhZi8+bNKC8vR15eHlJTU/Hss89a7P5S72c/+xmuXbuGf/zjH1aNl/P5cB1tPql9YvJHRB1WZWUlvv/+e4SFhT2y7rBhwzBv3jwUFBRg4cKFjdaprq5GcnIyJkyYgGnTpsHT0xMRERHYtm0bSkpKGt0Jx2AwQK/Xw8/PDzExMaisrMTly5cB/LjAdlpaGqKiohAdHQ0vLy8sXboULi4uSE9Pb93JN9GaNWsQEBCAVatWWZSPGjUKiYmJiIuLg16vx4ABA1BeXo6dO3c22k6vXr0AALm5uVaLlfP5aB1pPqn9clY6AGob9QsKU/vx97//HQDnpjmuXr3arPpFRUUQkYdeJfqpVatW4ciRI9i6dSsmT57c4Pu8vDxUVFQ02MM5MjISarUap0+ffmj79Vdi6q8UnT9/HlVVVRgwYIC5jpubG7p27Wpx29FaDh48iMzMTHzyySfQ6XQW3y1ZsgQ7d+7EZ599hp///OcoKirCwoULMWzYMHz55Zfm58Xq1Y9x/dUya+B8PlxHm09qv3jlj4g6rDt37gDAQx+Y/ymNRoP09HSoVCq89tprqK6utvi+rKwMAODh4dHgWC8vL5SXlzcrvvrbkUuXLrVYV/LSpUsWD+tbw759+7Bu3TpkZ2ejZ8+eFt/duHED69evxx/+8Af84he/gLu7O0JCQrBjxw5cv34dSUlJDdqr3+6vfsytgfP5YB1xPqn94pU/O6HkFmLUuPawvVtHU799VFPV/wFrzqK1w4YNw/z587Fx40a88847CA4ONn/n5eUFAI0mBWVlZQgKCmpyPwDg5+cHAEhJSUF8fHyzjm2NzZs34+OPP8aJEycaTXwuXryI2tpadOvWzaJcr9fDx8cHeXl5DY6pqakB8O8xtwbOZ+M66nxS+8Urf0TUYXXp0gUqlQq3b99u1nHvvPMO+vbtizNnzliUDxgwAB4eHg0e3j99+jRqamrwxBNPNKuf7t27Q6PR4OzZs806rqVEBImJicjNzcWhQ4caTRQAmJOeGzduWJSXl5fj5s2bDW4RAjCPsb+/fxtH/W+cT0sdfT6p/WLyR0QdllarRWhoaLOfFay/XXj/+mkajQYJCQk4ePAg9uzZA6PRiNzcXMyaNQsBAQGIjY1tdj/Tp0/H3r17kZaWBqPRiNraWly9etX8hzomJgb+/v5tsh3ZuXPnsGHDBuzYsQMuLi4NtjHcuHEjACAkJASjR4/Gjh078MUXX6C6uhpXrlwxn9/vfve7Bm3Xj3FERESr43wQzqeljj6f1I4ptbw0tQ2uuN5+cYeP5mvJz3NcXJy4uLhIVVWVuezgwYMSFhYmAMTX11fmzJnT6LELFixosCNEXV2dJCUlSa9evcTFxUW8vb0lKipKzp8/b66zdetW0Wq1AkB69eol+fn5sn37dtHr9QJAevToIRcuXBARkbt370piYqIEBweLs7Oz+Pn5SXR0tOTl5YmISFRUlACQ5cuXP/Q8T506JcOHwsKtrwAAIABJREFUD5eAgAABIACka9euYjAY5PPPPxcRkdzcXPN3jX2SkpLM7ZWUlEh8fLyEh4eLq6ureHh4yPDhw+X9999vtP+xY8dKYGCgxQ4Sj8L5fDBHmU9ql7i9W0fHX8b2i8lf87Xk5/nixYvi7Owsu3fvtlJU1lVbWysjR46UXbt2KR3KA5WUlIhGo5GNGzc26zjOZ/tky/mkdonbuxFRxxYeHo6VK1di5cqVqKioUDqcZqmtrcWhQ4dQXl6OmJgYpcN5oBUrVmDQoEGIi4uzel+cT+uz5XxS+8TkjywcOHAAoaGhDZ4tUavV6NKlC5566ikkJSXh1q1bSodKZLZo0SJMmjQJMTExzX5ZQEnZ2dk4cOAAjh071uS17WwtOTkZZ8+exdGjR+Hi4mKTPjmf1qPEfFL7w+SPLERHR+O7775DWFgYPD09ISKoq6tDUVERMjMzERISgsTERPTv399m2xkRNcXq1asRFxeHtWvXKh1Kkz399NN477330LVrV6VDadThw4dx9+5dZGdnw9vb26Z9cz7bnpLzSe0Lkz96JJVKBS8vLzz11FNIT09HZmYmfvjhB4wdO7ZD/av8Qaqrq2EwGJQOwypscW7tafyeeeYZrFu3Tukw7MaLL76IRYsWNXiL1lY4n21L6fmk9oPJHzXbxIkT8eqrr6KoqAjbtm1TOpxW27VrF4qKipQOwypscW72PH5ERPaIyR+1yKuvvgoAOHbsGABgw4YN0Gq10Ol0KCoqQkJCAgIDA3H+/HmICJKTk/HYY4/B1dUV3t7eGD9+vMVemJs2bYJGo0GXLl0wc+ZMBAQEQKPRwGAwNNh/syntxcXFQa1WW9x+mT17Ntzd3aFSqVBSUgIAiI+PR0JCAvLz86FSqRAeHm6tIWsSa59bU8e5teN3/Phx6PV6rF692qrjRURELaDs28bUWtZ69T4sLEw8PT0f+L3RaBQA0r17d3PZkiVLBIDMnTtXNm/eLBMmTJB//etfsnz5clGr1bJ7924pKyuTnJwcGTx4sPj6+kphYaH5+NjYWHF3d5dz587JnTt3JC8vTyIjI0Wn08nly5fN9Zra3tSpU8Xf398i7qSkJAEgxcXF5rLo6GgJCwtr1Xg1piVLvdji3Jo6zq3p48iRI6LT6WTlypXNOn8uJWFfOJ/2hfNpN7jUC7WMTqeDSqVqdM/MdevWYc6cOThw4AB69OiB5ORkTJgwAdOmTYOnpyciIiKwbds2lJSUYPv27RbHOjs7m6969evXD2lpaSgvL0d6ejqAH58va057HYktz+1R49xaY8eOhdFoxLJly9qkPSIiajtM/qhFKisrISLQ6/UPrZeXl4eKigoMGTLEojwyMhJqtbrBLd37DRkyBFqt1nzbs7XttWdKntv940xERPaLyR+1yIULFwAAffv2fWi9srIyAGh0Q3IvL69Grxzez9XVFcXFxW3WXnul9Ln9dJyJiMh+MfmjFjl+/DgAYMyYMQ+t5+XlBQCNJi5lZWUICgp66PEmk8miXmvba8+UPLf7x5mIiOwXkz9qtsLCQqSkpCAoKAivvfbaQ+sOGDAAHh4eDRaEPn36NGpqavDEE0889Pjs7GyICIYOHdrs9pydnWEymZpzaopS8tzuH2dr9EFERO0Dkz96IBFBRUUF6urqICIoLi5GRkYGhg8fjk6dOuHQoUOPfOZPo9EgISEBBw8exJ49e2A0GpGbm4tZs2YhICAAsbGxFvXr6upw69Yt3Lt3Dzk5OYiPj0dwcLB5aZnmtBceHo6bN2/i0KFDMJlMKC4uxqVLlxrE6OPjg+vXr6OgoADl5eWKJTy2PLdHjXNr+zh27BiXeiEiaq8UfdmYWq2tX73/4IMPZODAgaLVakWtVouTk5MAEJVKJV5eXvLkk0/KypUrpbS01OK49evXi5ubm3n5l927d5u/q6urk6SkJOnVq5e4uLiIt7e3REVFyfnz5y3aiI2NFRcXFwkMDBRnZ2fR6/Uyfvx4yc/Pt6jX1PZKS0tl9OjRotFoJCQkRN544w1ZsGCBAJDw8HDzsiZff/219OjRQ9zc3GTEiBEWS6q0RkuWerHFuTV1nFvTx9GjR0Wn08mqVauadf5cSsK+cD7tC+fTbmSqREQUyzyp1TIzMzF58mTYwzTOnDkTWVlZKC0tVTqUNjFp0iQAQFZWlsKRWGrP42xPP8/E+bQ3nE+7kcXbvtSu1NbWKh2CQ+A4ExE5LiZ/RERERA6EyR+1C4sXL0Z6ejpu376NkJAQ7N+/X+mQ7BLHmYiInJUOgAgA1qxZgzVr1igdht3jOBMREa/8ERERETkQJn9EREREDoTJHxEREZEDYfJHRERE5ECY/BERERE5EL7taydUKpXSIdADcG6aj2NmXzifRO0Lk78OzmAwICMjQ+kwiDqUU6dOITU1lb87ROSQuLcvETkc7lFKRA6Me/sSERERORImf0REREQOhMkfERERkQNh8kdERETkQJj8ERERETkQJn9EREREDoTJHxEREZEDYfJHRERE5ECY/BERERE5ECZ/RERERA6EyR8RERGRA2HyR0RERORAmPwRERERORAmf0REREQOhMkfERERkQNh8kdERETkQJj8ERERETkQJn9EREREDoTJHxEREZEDYfJHRERE5ECY/BERERE5ECZ/RERERA6EyR8RERGRA2HyR0RERORAmPwRERERORAmf0REREQOhMkfERERkQNh8kdERETkQJj8ERERETkQJn9EREREDoTJHxEREZEDYfJHRERE5ECclQ6AiMiaiouL8f7771uUffXVVwCA7du3W5TrdDpMmTLFZrERESlBJSKidBBERNZy9+5ddOnSBRUVFejUqRMAoP5/eyqVylzPZDLht7/9Lf785z8rESYRka1k8bYvEdk1V1dXTJw4Ec7OzjCZTDCZTLh37x7u3btn/m+TyQQAePnllxWOlojI+pj8EZHde/nll1FTU/PQOl5eXvjFL35ho4iIiJTD5I+I7N7o0aPh5+f3wO9dXFwwbdo0ODvzMWgisn9M/ojI7jk5OWHq1KlwcXFp9HuTycQXPYjIYTD5IyKHMGXKFPOzfffr1q0bhg0bZuOIiIiUweSPiBzCk08+iR49ejQoV6vV+O1vf2vx5i8RkT1j8kdEDuOVV15pcOu3pqaGt3yJyKEw+SMihzF16tQGt37Dw8MRERGhUERERLbH5I+IHEbfvn3Rr18/8y1eFxcXTJ8+XeGoiIhsi8kfETmU3/zmN+adPu7du8dbvkTkcJj8EZFDmTJlCmprawEAgwcPRkhIiMIRERHZFpM/InIowcHB+PnPfw4A+O1vf6twNEREtsfl7MksOTkZp06dUjoMIqu7e/cuVCoVPvnkE3zxxRdKh0NkdfPnz+dalmTGK39kdurUKfz9739XOgy7cvXqVezfv1/pMDqc/fv34+rVq1ZrPygoCP7+/tBoNFbrg/7N2vNJD7d//35cuXJF6TCoHeGVP7IwdOhQZGVlKR2G3cjMzMTkyZM5ps2kUqkwb948vPTSS1br49tvv0V4eLjV2qd/s8V80oNxAXO6H6/8EZFDYuJHRI6KyR8RERGRA2HyR0RERORAmPwRERERORAmf0REREQOhMkftanf//730Ol0UKlUOHv2rNLhtMjKlSvRr18/6PV6uLq6Ijw8HG+99RYqKioUi+no0aPw9PTEhx9+qFgMRERkH5j8UZvauXMnduzYoXQYrXLixAnMmTMHBQUFKCkpwZo1a5CamopJkyYpFpOIKNY3ERHZFyZ/RPfx8PBAbGwsfHx8oNPp8NJLLyEqKgrHjx9XbKHUsWPH4vbt2xg3bpwi/f9UdXU1DAaD0mEQEVELcZFnanMdfUHRI0eONCjz9fUFAFRVVdk6nHZn165dKCoqUjoMIiJqIV75o1YRESQlJaFPnz5wdXWFp6cnFixY0KBebW0tli9fjuDgYLi5uWHgwIHIyMgAAKSlpcHd3R1arRaHDx/GmDFjoNfrERQUhL1791q08/nnn+PJJ5+EVquFXq9HREQEjEbjI/torWvXrsHNzQ0hISFt0l5znDx5EsHBwVCpVNiyZQuApo/Zpk2boNFo0KVLF8ycORMBAQHQaDQwGAw4ffq0uV5cXBzUajW6du1qLps9ezbc3d2hUqlQUlICAIiPj0dCQgLy8/OhUqnMCyUfP34cer0eq1evtsWQEBFRKzD5o1ZZtmwZEhMTERsbix9++AGFhYVYuHBhg3oLFy7Ehg0bkJKSghs3bmDcuHF4+eWX8dVXX+H111/HvHnzUF1dDZ1Oh4yMDOTn5yM0NBQzZsyAyWQCAFRWVuKFF17AxIkTcfPmTVy8eBG9e/dGTU3NI/tojaqqKpw4cQIzZsyAWq1uVVstMWLECHz55ZcWZU0ds7i4OLz66quoqqrC3LlzUVBQgK+//hr37t3Dr371K/Nt7E2bNjXYemvr1q14++23LcpSU1Mxbtw4hIWFQUTw7bffAvgx8QaAuro6q4wBERG1HSZ/1GLV1dVISUnBL3/5S8yfPx9eXl5wc3ODj4+PRb07d+4gLS0NUVFRiI6OhpeXF5YuXQoXFxekp6db1DUYDNDr9fDz80NMTAwqKytx+fJlAEBBQQGMRiP69+8PjUYDf39/HDhwAL6+vs3qo7nWrFmDgIAArFq1qlXtWMvDxqyes7MzHnvsMbi6uqJfv35IS0tDeXl5q8em3tixY2E0GrFs2bI2aY+IiKyHyR+12Lfffouqqio8/fTTD613/vx5VFVVYcCAAeYyNzc3dO3aFd98880Dj6u/ylZ/FSs0NBRdunTBtGnTsGLFChQUFLS6j0c5ePAgMjMz8fHHH0On07W4HVu5f8weZMiQIdBqta0aGyIi6piY/FGLXb16FQDg5+f30HqVlZUAgKVLl0KlUpk/ly5datYLFG5ubjhx4gRGjBiB1atXIzQ0FDExMaiurm6zPn5q3759WLduHbKzs9GzZ88WtdGeubq6ori4WOkwiIjIxpj8UYtpNBoAwN27dx9arz45TElJgYhYfE6dOtWsPvv3748PP/wQ169fR2JiIjIyMrBx48Y27QMANm/ejD179uDEiRPo1q1bs49v70wmE8rKyhAUFKR0KEREZGNM/qjFBgwYACcnJ3z++ecPrde9e3doNJpW7/hx/fp1nDt3DsCPCeXatWsxePBgnDt3rs36EBEkJiYiNzcXhw4dgoeHR6vaa6+ys7MhIhg6dKi5zNnZ+ZG3i4mIqONj8kct5ufnh+joaOzfvx+7du2C0WhETk4Otm/fblFPo9Fg+vTp2Lt3L9LS0mA0GlFbW4urV6/ixo0bTe7v+vXrmDlzJr755hvU1NTgzJkzuHTpEoYOHdpmfZw7dw4bNmzAjh074OLiYnELWaVSYePGjU1uqz2pq6vDrVu3cO/ePeTk5CA+Ph7BwcF49dVXzXXCw8Nx8+ZNHDp0CCaTCcXFxbh06VKDtnx8fHD9+nUUFBSgvLwcJpMJx44d41IvREQdBJM/apV3330X06dPR2JiIgIDAzF79myMHDkSADBu3Djk5OQA+HGJkHnz5mH9+vXo3LkzAgICEB8fj1u3biEtLQ0pKSkAgIEDB+K7777Djh07kJCQAAB47rnncPHiRfj5+aG2thYGgwFarRa//vWvMXPmTMyZM+eRfTRVe9xGbcuWLYiMjAQAJCYm4sUXX2zymNW7c+cOIiIi4ObmhpEjR6J3797461//CldXV3Od119/HaNHj8aUKVPQp08fvPPOO3BzcwMADBs2zLwszKxZs9ClSxf069cPzz//PG7evGmTcSAiorahkvb4144UUb93bVZWlsKR2I/MzExMnjxZ0aRy5syZyMrKQmlpqWIxNJdKpUJGRkaDtQepY+J8KovjT/fJ4pU/IgdQvwgzERERkz+ye998802DZ/ca+8TExCgdKhERkdUx+SO717dv3wbLvzT22bdvn9KhtrnFixcjPT0dt2/fRkhICPbv3690SFb36aefYtGiRThw4ABCQ0PNyf0rr7zSoO4zzzwDnU6HTp06oX///vj6668ViLj56urqkJKSAoPB0Oj3K1euRL9+/aDX6+Hq6orw8HC89dZbqKioaFD3L3/5CyIjI6HT6dCjRw9Mnz4dhYWF5u8/+OADrF+/XrGrx/Y8n0899dQD/zFav9KA0uNPdkqI/r+JEyfKxIkTlQ7DrmRkZAh/zZoPgGRkZDT7uOXLl8u4cePEaDSay8LCwqRz584CQI4cOdLgmGPHjsmLL77Yqnht6cKFCzJ8+HABII8//nijdUaNGiVbt26V0tJSMRqNkpGRIS4uLvLcc89Z1Nu3b58AkPXr10tZWZmcOXNGQkNDZdCgQWIymcz1UlNTZdSoUXLr1q0Wxcz5bNyoUaMEQKOfZ5991lxPqfEnu5XJK39EZBfWrVuHffv2ITMzs8FWfJs2bYKTkxNiY2Nx+/ZthSJsvX/84x9YuHAhZs2ahUGDBj2wnoeHB2JjY+Hj4wOdToeXXnoJUVFROH78uPmtbQD405/+hG7dumHBggXw9PTEoEGDMH/+fJw9exanT58215s7dy4ef/xxPP/887h3755Vz7GeI8ynRqOB0WhscBciNjYWb731lrmeEuNP9o3JHxF1eN9++y2WLVuGt99+27zzzE8ZDAbEx8fj2rVrePPNNxWIsG08/vjjOHDgAKZOnWqxTM/9jhw5gk6dOlmU+fr6AoDFdodXrlxBQEAAVCqVuax79+4A0GCNxxUrVuDs2bNITU1t9Xk8iqPM5/HjxxsktleuXME///lP/OIXv7Aot+X4k/1j8kdEHd6mTZsgInjhhRceWGfVqlXo3bs3du7ciU8//fSh7YkIkpOT8dhjj8HV1RXe3t4YP348vvnmG3OdtLQ0uLu7Q6vV4vDhwxgzZgz0ej2CgoKwd+9ei/Zqa2uxfPlyBAcHw83NDQMHDkRGRkbrTrqZrl27Bjc3N4SEhJjLQkNDUVRUZFGv/nm/0NBQi3Jvb2+MGjUKqampVl+6yJHnc926dZg7d26DcluOP9k/Jn9E1OF99NFH6NOnD7Ra7QPruLm54c9//jOcnJwwY8YMVFZWPrDuihUrsGjRIixZsgRFRUX44osvcOXKFYwcORI//PADgB8XxZ43bx6qq6uh0+mQkZGB/Px8hIaGYsaMGRZb5S1cuBAbNmxASkoKbty4gXHjxuHll1/GV1991XaD8BBVVVU4ceIEZsyYAbVabS5fvHgxCgsLsXnzZpSXlyMvLw+pqal49tlnLbb+q/ezn/0M165dwz/+8Q+rxuuo83nt2jVkZ2cjOjq60e9tNf5k/5j8EVGHVllZie+//x5hYWGPrDts2DDMmzcPBQUFWLhwYaN1qqurkZycjAkTJmDatGnw9PREREQEtm3bhpKSkgbbFwI/3obU6/Xw8/NDTEwMKisrcfnyZQA/7q6SlpaGqKgoREdHw8vLC0uXLoWLiwvS09Nbd/JNtGbNGgQEBGDVqlUW5aNGjUJiYiLi4uKg1+sxYMAAlJeXY+fOnY2206tXLwBAbm6u1WJ15Plct24d3njjDTg5Nf6n2RbjT46ByR9Z2L9/f5PWxOOnaZ/JkycDgOJxdLRPcxQVFUFEHnqV6KdWrVqFPn36YOvWrTh58mSD7/Py8lBRUYEhQ4ZYlEdGRkKtVlu8CNGY+itr9VeKzp8/j6qqKgwYMMBcx83NDV27drW47WgtBw8eRGZmJj7++OMGz5ctWbIE27dvx2effYaKigp89913MBgMFtv5/VT9GNdfLbMGR53P69ev44MPPrDYb/t+thh/cgzOSgdA7cvQoUMxb948pcOwG6dOnUJqaqrNn+/q6OqT5qa4c+cOADz0BYif0mg0SE9Px4gRI/Daa69h/fr1Ft+XlZUBgHmdtZ/y8vJCeXl5k2MDYL4duXTpUixdutTiu4CAgGa11Vz79u1DcnIysrOz0a1bN4vvbty4gfXr12PRokXmlwtCQkKwY8cOeHt7IykpCZs2bbI4pn6v5/oxtwZHnc/169djxowZjb7gUs8W40+OgckfWQgKCuL+j20sNTWVY9pMzUn+6v8gNmcR3GHDhmH+/PnYuHEj3nnnHQQHB5u/8/LyAoBGk4KysjIEBQU1uR8A8PPzAwCkpKQgPj6+Wce2xubNm/Hxxx/jxIkTjSY+Fy9eRG1tbYOkUK/Xw8fHB3l5eQ2OqampAfDvMbcGR5zPwsJC/OUvf8H58+cfWs8W40+Ogbd9iahD69KlC1QqVbPXe3vnnXfQt29fnDlzxqJ8wIAB8PDwaPDw/unTp1FTU4MnnniiWf10794dGo0GZ8+ebdZxLSUiSExMRG5uLg4dOtRo4gfAnPTcuHHDory8vBw3b940L/nyU/Vj7O/v38ZR/5sjzuf69esxbdo0+Pj4PLSeLcafHAOTPyLq0LRaLUJDQ3H16tVmHVd/u/D+9fA0Gg0SEhJw8OBB7NmzB0ajEbm5uZg1axYCAgIQGxvb7H6mT5+OvXv3Ii0tDUajEbW1tbh69ao58YqJiYG/v3+bbEd27tw5bNiwATt27ICLi0uD5yk3btwI4MdbvKNHj8aOHTvwxRdfoLq6GleuXDGf3+9+97sGbdePcURERKvjfBBHm88ffvgB7777bpMet7HF+JODUGRjEWqXuL1b2+P2bi2DZm5HFRcXJy4uLlJVVWUuO3jwoISFhQkA8fX1lTlz5jR67IIFCxpsB1ZXVydJSUnSq1cvcXFxEW9vb4mKipLz58+b62zdulW0Wq0AkF69ekl+fr5s375d9Hq9AJAePXrIhQsXRETk7t27kpiYKMHBweLs7Cx+fn4SHR0teXl5IiISFRUlAGT58uUPPc9Tp07J8OHDJSAgwLwNWNeuXcVgMMjnn38uIiK5ubkP3DIMgCQlJZnbKykpkfj4eAkPDxdXV1fx8PCQ4cOHy/vvv99o/2PHjpXAwECpq6t7aJz343w+2Pz582XatGlNGhdbjT/ZvUz+VSIzJn9tj8lfyzT3j9XFixfF2dlZdu/ebcWorKe2tlZGjhwpu3btUjqUByopKRGNRiMbN25s9rGcz9az5fiT3ePevkTU8YWHh2PlypVYuXIlKioqlA6nWWpra3Ho0CGUl5cjJiZG6XAeaMWKFRg0aBDi4uKs3hfnsyFbjj/ZPyZ/ZDUHDhxAaGhog2eO1Go1unTpgqeeegpJSUm4deuW0qGSHVi0aBEmTZqEmJiYZr8soKTs7GwcOHAAx44da/LadraWnJyMs2fP4ujRo3BxcbFJn5zPf1Ni/Mm+Mfkjq4mOjsZ3332HsLAweHp6QkRQV1eHoqIiZGZmIiQkBImJiejfv7/Ntrki+7Z69WrExcVh7dq1SofSZE8//TTee+89dO3aVelQGnX48GHcvXsX2dnZ8Pb2tmnfnE9lx5/sF5M/simVSgUvLy889dRTSE9PR2ZmJn744QeMHTu2Q/3rviOprq6GwWDo8H001TPPPIN169YpHYbdePHFF7Fo0aIGb9HaiqPPp9LjT/aJyR8pauLEiXj11VdRVFSEbdu2KR2OXdq1axeKioo6fB9ERNQ2mPyR4ur3sjx27Ji5rLa2FsuXL0dwcDDc3NwwcOBA8xZpaWlpcHd3h1arxeHDhzFmzBjo9XoEBQVh7969Fm1//vnnePLJJ6HVaqHX6xEREQGj0fjIPpQkIkhOTsZjjz0GV1dXeHt7Y/z48Rb7hsbFxUGtVlvcWpo9ezbc3d2hUqlQUlICAIiPj0dCQgLy8/OhUqkQHh6OTZs2QaPRoEuXLpg5cyYCAgKg0WhgMBgs9jltTR8AcPz4cej1eqxevdqq40VERM2k9PvG1H5Ya6mXsLAw8fT0fOD3RqNRAEj37t3NZW+++aa4urrK/v375datW7J48WJxcnKS//3f/xURkSVLlggA+eyzz+T27dtSVFQkI0eOFHd3d6mpqRERkYqKCtHr9bJ+/Xqprq6WwsJCmTBhghQXFzepj7bQkqVeli9fLmq1Wnbv3i1lZWWSk5MjgwcPFl9fXyksLDTXmzp1qvj7+1scm5SUJADM5ygiEh0dLWFhYRb1YmNjxd3dXc6dOyd37tyRvLw8iYyMFJ1OJ5cvX26TPo4cOSI6nU5WrlzZrPMX4dIU9obzqSyOP92HS72Q8nQ6HVQqlXnvzTt37iAtLQ1RUVGIjo6Gl5cXli5dChcXF6Snp1scazAYoNfr4efnh5iYGFRWVuLy5csAgIKCAhiNRvTv3x8ajQb+/v44cOAAfH19m9WHLVVXVyM5ORkTJkzAtGnT4OnpiYiICGzbtg0lJSXYvn17m/Xl7OxsvrrYr18/pKWloby8vM3Of+zYsTAajVi2bFmbtEdERG2DyR8prrKyEiICvV4PADh//jyqqqowYMAAcx03Nzd07drV4tbn/dRqNQDAZDIBAEJDQ9GlSxdMmzYNK1asQEFBgbluS/uwtry8PFRUVGDIkCEW5ZGRkVCr1Ra3ZdvakCFDoNVqFT1/IiKyPiZ/pLgLFy4AAPr27Qvgx2QQAJYuXWqxPuClS5dQVVXV5Hbd3Nxw4sQJjBgxAqtXr0ZoaChiYmJQXV3dZn20tbKyMgCAh4dHg++8vLzMV0etxdXVFcXFxVbtg4iIlMXkjxR3/PhxAMCYMWMAAH5+fgCAlJQUiIjF59SpU81qu3///vjwww9x/fp1JCYmIiMjAxs3bmzTPtqSl5cXADSa5JWVlSEoKMhqfZtMJqv3QUREymPyR4oqLCxESkoKgoKC8NprrwEAunfvDo1Gg7Nnz7aq7evXr+PcuXMAfkwo165di8GDB+PcuXNt1kdbGzBgADw8PBosen369GnU1NTgiSeeMJc5Ozubb3G3hezsbIgIhg4darU+iIhIeUz+yCZEBBUVFairq4OIoLi4GBkZGRg+fDg6deqEQ4cOmZ/502g0mD59OvYfJ98/AAACuElEQVTu3Yu0tDQYjUbU1tbi6tWruHHjRpP7vH79OmbOnIlvvvkGNTU1OHPmDC5duoShQ4e2WR9tTaPRICEhAQcPHsSePXtgNBqRm5uLWbNmISAgALGxsea64eHhuHnzJg4dOgSTyYTi4mJcunSpQZs+Pj64fv06CgoKUF5ebk7m6urqcOvWLdy7dw85OTmIj49HcHCweemd1vZx7NgxLvVCRNQeKfOWMbVHbb3UywcffCADBw4UrVYrarVanJycBICoVCrx8vKSJ598UlauXCmlpaUNjr17964kJiZKcHCwODs7i5+fn0RHR0teXp5s3bpVtFqtAJBevXpJfn6+bN++XfR6vQCQHj16yIULF6SgoEAMBoN4e3tLp06dpFu3brJkyRK5d+/eI/toKy1Z6qWurk6SkpKkV69e4uLiIt7e3hIVFSXnz5+3qFdaWiqjR48WjUYjISEh8sYbb8iCBQsEgISHh5uXbPn666+lR48e4ubmJiNGjJDCwkKJjY0VFxcXCQwMFGdnZ9Hr9TJ+/HjJz89vsz6OHj0qOp1OVq1a1exxA5emsCucT2Vx/Ok+mSoREcUyT2pXJk2aBADIyspSOBL7kZmZicmTJ6O9/ZrNnDkTWVlZKC0tVTqURqlUKmRkZOCll15SOhRqA5xPZXH86T5ZvO1L5KBqa2uVDoGIiBTA5I+IiIjIgTD5I3IwixcvRnp6Om7fvo2QkBDs379f6ZCIiMiGnJUOgIhsa82aNVizZo3SYRARkUJ45Y+IiIjIgTD5IyIiInIgTP6IiIiIHAiTPyIiIiIHwhc+yMLVq1eRmZmpdBh249SpUwDAMW2B+rEj+8D5JGo/uMMHmU2aNInLfhAR2SHu8EE/kcXkj4iIiMhxcHs3IiIiIkfC5I+IiIjIgTD5IyIiInIgTP6IiIiIHMj/A9GFDvWtlp5mAAAAAElFTkSuQmCC\n"
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from keras.models import model_from_json\n",
        "\n",
        "model_json = cnn4.to_json()\n",
        "with open(\"/content/gdrive/My Drive/DL Project/model.json\", \"w\") as json_file:\n",
        "    json_file.write(model_json)\n",
        "# serialize weights to HDF5\n",
        "cnn4.save_weights(\"/content/gdrive/My Drive/DL Project/model.h5\")\n",
        "print(\"Saved model to disk\")"
      ],
      "metadata": {
        "id": "qUxdogagUTkQ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f3182e03-d3cb-4425-b4c9-99f669d1580a"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saved model to disk\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# json_file = open('model.json', 'r')\n",
        "# loaded_model_json = json_file.read()\n",
        "# json_file.close()\n",
        "# loaded_model = model_from_json(loaded_model_json)\n",
        "# # load weights into new model\n",
        "# loaded_model.load_weights(\"model.h5\")\n",
        "# print(\"Loaded model from disk\")\n",
        "\n",
        "# loaded_model.compile(loss='binary_crossentropy', optimizer='rmsprop', metrics=['accuracy'])\n",
        "# score = loaded_model.evaluate(x_test, y_test, verbose=0)\n",
        "# print(\"%s: %.2f%%\" % (loaded_model.metrics_names[1], score[1]*100))"
      ],
      "metadata": {
        "id": "pQyRggF2_mH-"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "visualkeras.layered_view(cnn4,legend=True, draw_volume=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 299
        },
        "id": "0S2Jj-NikgK4",
        "outputId": "869cef22-70d4-4299-c8fc-0d6ff06d3132"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<PIL.Image.Image image mode=RGBA size=1054x282 at 0x7F48FCA50890>"
            ],
            "image/png": 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AAIAVCA9xLsnp0r/yTv/hTheX5OTFZDtiGh2enSnH13uVeMPfiA5xEB0aO+uss/TrX43Q559+qKF9K8PaBkkyxq9Js77Vt3uqdPPNP29mOaNlH8/S7m+26Nyu/SyYazR1/1Z9567UpSnhfewAAAAAViM8QF0SkvXywDN1zTezdURyhk7p1D2q82MeHZZvV6JFFzQkOrSf6GCM0f1//K3mff6RZr4w2qL9PkfpKQnq3S1dY8aMCXohzTE33aZ9W7Zr8vG/tma/f/2J0pwJSnMmaN++fWGtDwAAALAa13iAJCkvJUvP9B+hP25frJ3u8H/zG6p4jw4yRlmuKqJDGHPDiQ5zZn1o4X6fo+LyWk196nRlpCUGnTvmpts0e+o06/b715+opK5+v6cnJGrbtm1hrRMAAACwGkc84AcjMnvq7l7H67at8/Xe0WcrMyHwi1arEB2Mem2Yocwkrz56/pdRjQ7LZy1T4fa9UY8O075aqU2FRR06OjS33yMZHTonJCvJ6SI8AAAAwHY44gGHuDr3KJ2W2VN/+HaxvMYfsTlEB6NeK95STtkWzRgf3eiw8osK7du2J+rR4TN/lTbuKyQ6RCg6SFKSw6WtW7fK2OQuNQAAAIBEeEAA/91nqFxy6PFdKyOyfqLD99Fh3zrN+NeoqEaHR/6xQUV76jTpuHOjGh3uLdmorU6/EmJ8LY2OHB0kyeVwyO/3q6ioKKwZAAAAgJUIDzhMgsOpfw44TSsqC/XW/m8sXTfRIbbRYdHSYk067ryoR4eZ7jIlxPiuIR09Okj1t8gdOHCg8vPzw5oDAAAAWInwgIA6uZL08sBf6N/78rWoYq8l6yQ6xD46TBwSm+jguiG2+33b6vkdPjo0IDwAAADAbggPCOqI5Aw9N+Dnun/HMm2tqQhrXUQHokO4c9u838s36uD+HVGPDv986NGoRwdJGjBggDZu3BjWPAAAAMBKhAc0a1hGNz3Y50Tdvm2+Sj21bVoH0YHoEO7ctu/3t5XjKdHHlu330KKDDjj0xZz5UY8OEkc8AAAAwH4ID2jRxV0H6LwufXXX9oWq8/ta9ViiA9Eh3LlhRYd9azVjfHSjwyNPbVBinSsm0UH6MTxwZwsAAADYBeEBIflTrxPUNSFFf9v5RcgvaIgORIdw54YdHaJ8pMMjT23QoiXFevd4i/Z7K6ODJHXt2pU7WwAAAMBWCA8IidPh0JP9RmhzTbleLdzQ4vJEB6JDuHPba3SwbL+3ITpI9Xe2GDJkCKdbAAAAwDYIDwhZmitBL+Wdqbf3b9ZnZbuCLkd0IDqEO5fo0Lbo0IDwAAAAADshPKBVeiSl6cW8M/S3nSu0obr0sPcTHYgO4c4lOoQXHSTp2GOP5c4WAAAAsA3CA1rtuPSuevTIU3TntgUqrKv+4e1EB6JDuHOJDuFHB4kjHgAAAGAvhAe0yTldjtSVOYP0u20LVeP3Eh2IDmHPJTpYEx2kH8MDd7YAAACAHSTEegPQft3RY4i21x7QA98ulbN7tj4lOhAd2jiX6GBddJCk7t27/3Bni27duoW9PgAAACAchAe0mcPh0GNHnqLhJQt0sGSH5HRIV42zZuVllVLPLtLdLwR+vzFy1CRINTWSwyHPSw+GPdIYv+SukU48S9q/U+o5QEpq4UUl0SHsuUQHa6ODdOidLQgPAAAAiDXCA8LicDj0s049NOfnXeW6eqQl6/T9Z678W3ZJ91wYfCGvT453liuxurOSR5xnydzaxR/Ls3uLjBzSkmlS4U6pay+pz6D6P70HSulZPz6A6BD2XKKD9dGhQUN4OOussyxdLwAAANBahAeEJcnpUidXkhzZneTI623JOh3ZnaT0FKlf9+YX7N5ZjqIsubofaclcZ2YXOTI6y5x5af0bvB5p3w5p92Zp3SLp0zfrXxz3GST16K/coq9V991G3X33UC1dsz+84cZo3OtrVVXj03P3naTC0loVltYetlhtnVcvv7ld81bt19/6D9cXFfvCHat/7lypap9XT/Q7VUWeGhV5ag5bzu3z6qmKHVpyoEAJv7pW/u/Cu2OCMUa+hR9K3jrpygeIDhZHB4k7WwAAAMA+CA9AMAmJPx7tIEnGLxXvlXZvUcL6+aoo2aMBfTL1zNsbwptjJLfHp8KSavXOTdOYf64OumhZeZ3KKurUNy1LL+xZG95cSW6/T8XuavVIStND330RdLliX53K/B45s3vIv2R62HPl9UiVZVJSsjTr/6Q+R9Xv525HSE5X4McQHVplyJAhmjp1akTWDQAAALQG4QEIlcMp5faRcvvIe8RROnr+P7Xxg0stWXX+tlKdc+dMLX1zdLPLbdpxQL/94yotG3GdJXM3HSzRJV99qFlDzm92uS015bqweJ0y7gtyzY1W8u3bqcrXHpa56s/S7i31f9YvkipKpJ79fww+DdfZIDq0WuM7WzgcDkvWaYyRx+NRUlLg/RUpsZoLAAAAaxAeAMROZldpcFdp8PD6v9cclPZuqw8RDdfZyO6pAZ198leWq2ffTP1u3PKwx27ddUBFpTW66ux+evWDbQGXMcZo2YIy7dpfo4FpWbpv66Kw5+6qqVS1t07vHXN2RKODJHXr1k3VyS5dPeZuJaeEF0yk+v0x77PPdWy33vrZqcObXW7z7gKldMoKukxr5y5csEC3XHmJ/vrnP1uyTgAAAEQX4QGAfaRmSHkn1P+R6k/J2LxKtV/9RxefeYRyuqRaMmbRqkKdOTRXKclBTuuQVFZZp53FVTo7d4C6Jlk0t2yPEuTQhuoyjcjsYck6AzHG6Np771Z1WoImVX0nVYW5Qr9f+vRLaXexRt98SrNzp86er/xtO+Q8NvhyoTJ+v/zrFkvl+7WsTwvXfAEAAIBtER4A2FdCojT4VPnXTNHvrhiiwXldLFntpE+36tLRR+icn/VqdrnFi+fqliN/omMyuloyd8q+zTo/8wg9sGOpLs8ZqLt6HieXw2nJuhsYY3TNn+7Su7NmSP/+o5SVHt4K/X7pd89LKUlyduuiMWPGaPDgwYHn3vF7bdyxW4k3/o81dz2Z8LiUlCxHp2ytW7dO06ZN04UXNnO3GwAAANiStT/xAgCadUxaF0099lx9dXC/btoyV/sD3EWkrYwxeuCpcXp31gz5X/i9ddGh/KD07B1ypAc+ZaMhOrz38Uy5rvuLddGhuv5Wq86UVI0bN0533nmn9u8P8w4yAAAAiDrCAwBEWbfEVL0xaKSGZXTTbzbO1NID4d0WVap/8b8vK0kzly+OSHRQZlrQuZGMDg23Wh06dKiuv/563XnnnTLGhDUDAAAA0UV4AIAYcDmcuqfXT/RkvxF6YMdSPb93nXzG36Z1GWN0b9UGHeyUJNMBo0ODRx99VFu2bNHbb78d1hwAAABEF+EBAGJoRGaPsE69aIgOn5gS6aU/dNjoIEnJycmaMGGC7rvvPu3atSuseQAAAIgewgMAxFhbT71oHB38L93ToaNDg5/+9Kf64x//qJtvvll+f9uOEAEAAEB0ER4AwAZae+pFPEaHBvfff7+qq6v1wgsvhDUbAAAA0UF4AAAbCeXUi1hGhwcf+3tMo4MkJSQk6M0339TYsWO1adOmsLYBAAAAkUd4AACbae7Ui1hFBxkj43bq04VLYhodGgwaNEiPPPKIbrjhBnm93rC2BQAQf4wx2rx5M3OZy9wozU2I8LYAANqg4dSLYRnd9MCOpbo8Z6B+12OI7q/eFJPooGc/lUyiXNf/NebRocEdd9yhcf94Wl26dVdiYlJY2wQAiB/GGFVV18jU1WrQwDw5HI6gy/ndJTJyyOVyWTLX+Gq1a1+V+vZrfq63sFTGaeHcGrd2uyvVL6/5ubsqquRyWDf3oNsjU1GsQQP6s58bLdeR9nNubnfNWbRWSUnN/yxGeAAAG2s49WLM9sU6OblEBz11Ur/u0th3wl/5zkKp9IB03inSlMWBlzFGjuU75SgskyOnt3zTXw57rK90v+Sukq77nzZHB2OMrr7xZu3dXyRzxDGSgwP4AAAhMH5p50ap5qDOPf9CPfX3cYEXM0bP/uNhfblsnv791+FKTAzv+4zxG93x+DKt3l6mG665WPf9+bGgc5956BF9sWu+nhl0hhKd4c31+43GbF6gdVWluv6Ci3X/E2ODzn1g7BP6ZuESuS64Q3KF9zLR+P3yTntZKtqjcy+7Sk89/Negc9nPbWeH/XzBhRe3GB0kwgMA2F63xFQ9cuTJOr9kmZwjT5Qju5Ml6/Wt/EYadpSUnBh8oQPVUmGpEo85WY6MLGvmbs+XnC5p6vPSiSOlo4e16huvMUZX3XCTJk/9QCbvp1JCM9sPAEADv1/auqb+v517qFv37ho8ePBhixljdN8fbtFXy+fr43+NUnZmcphj/Tr/ntly1/l0y4V56tGrR9C59954q76cs0CTjjtXXRJTwp571fpP5Pb7dG23o9S7R8+gc6++/W7NWrRMCdc/ZMmRjd63Hpe8ddKJo9Stmbns5/Dm2mE/pySHtj7CAwC0A3mpnZXmcKn66pFy5PW2ZJ3+T5bL/GqodNqQ5hdc/k8ljzhPru5HWjK3bs1C+UdcXH+VoVVzpXnvSiecWf+nU5dmH9s4OvgHnEB0AACEpiE6eOukIwZLZYFvXd3wIm3uZ9P10fMjLXuRVlzu1tSnTterH2wLOvfeG2/VnA8+0sQh51j2YrjEU6sJR43ShP3fBJ179e13a/KMT627htNbj0tV359OuWpO0Lns5/Dm2nk/B0J4AABEn9MpDfqpNGioVLJXWj1PeuN/pL7HSkNHSX2Okpqco0h0AAC0SdPoEOQou0i/SOuSGfhw9Ei/GO6cEPh5RPzFcJD1sZ879n4OhvAAAIitrr2kX14jnf4bKX+Z9NmE+lMxThwpDR4uiegAAGgjokPQufH0Ypj9HNvoIBEeAAB2kZwqDR0pnXhW/YW/Vs+TFk2Vz+/TTb+9XV9++aXUK086WBbrLQUAtAdGUsG3kt8n9cirjw/euvr3eT0qLyt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\n"
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "T-E3ouHmOmvX"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}