{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "id": "58e787ca-562f-458d-8c62-e86b6fb1580a",
      "metadata": {
        "id": "58e787ca-562f-458d-8c62-e86b6fb1580a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "04ef3efa-30a9-4178-a620-8e17d23b4b81"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/content/drive/MyDrive/Colab Notebooks/is_lab2/lab02_lib.py:444: SyntaxWarning: invalid escape sequence '\\X'\n",
            "  hatch='/', label='Площадь |Xd| за исключением |Xt| (|Xd\\Xt|)')\n",
            "/content/drive/MyDrive/Colab Notebooks/is_lab2/lab02_lib.py:452: SyntaxWarning: invalid escape sequence '\\X'\n",
            "  facecolor='none', label='Площадь |Xt| за исключением |Xd| (|Xt\\Xd|)')\n"
          ]
        }
      ],
      "source": [
        "# импорт модулей\n",
        "import os\n",
        "os.chdir('/content/drive/MyDrive/Colab Notebooks/is_lab2')\n",
        "\n",
        "import numpy as np\n",
        "import lab02_lib as lib"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Задание 2"
      ],
      "metadata": {
        "id": "rqdVflKXo6Bo"
      },
      "id": "rqdVflKXo6Bo"
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 1) Изучить описание своего набора реальных данных, что он из себя представляет"
      ],
      "metadata": {
        "id": "rSvJtTReo928"
      },
      "id": "rSvJtTReo928"
    },
    {
      "cell_type": "markdown",
      "source": [
        "Бригада 6 => набор данных Cardio. Это реальный набор данных, который состоит из измерений частоты сердечных сокращений плода и\n",
        "сокращений матки на кардиотокограммах, классифицированных экспертами\n",
        "акушерами. Исходный набор данных предназначен для классификации. В нем\n",
        "представлено 3 класса: «норма», «подозрение» и «патология». Для обнаружения\n",
        "аномалий класс «норма» принимается за норму, класс «патология» принимается за\n",
        "аномалии, а класс «подозрение» был отброшен.\n",
        "\n",
        "| Количество<br>признаков | Количество<br>примеров | Количество<br>нормальных примеров | Количество<br>аномальных примеров |\n",
        "|-------------------------:|-----------------------:|----------------------------------:|-----------------------------------:|\n",
        "| 21                       | 1764                   | 1655                               | 109                                |\n"
      ],
      "metadata": {
        "id": "gf-0gJ7jqTdk"
      },
      "id": "gf-0gJ7jqTdk"
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 2) Загрузить многомерную обучающую выборку реальных данных Cardio.txt."
      ],
      "metadata": {
        "id": "N2Egw1pho-F_"
      },
      "id": "N2Egw1pho-F_"
    },
    {
      "cell_type": "code",
      "source": [
        "# загрузка обчуающей выборки\n",
        "train = np.loadtxt('data/cardio_train.txt', dtype=float)"
      ],
      "metadata": {
        "id": "G8QTxAFapASY"
      },
      "id": "G8QTxAFapASY",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 3) Вывести полученные данные и их размерность в консоли."
      ],
      "metadata": {
        "id": "zj2WXPNco-Tz"
      },
      "id": "zj2WXPNco-Tz"
    },
    {
      "cell_type": "code",
      "source": [
        "print('train:\\n', train)\n",
        "print('train.shape:', np.shape(train))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "W6hTlfk6pAo9",
        "outputId": "6494b55a-d7f6-400c-8cfb-cf1b2aff34cf"
      },
      "id": "W6hTlfk6pAo9",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "train:\n",
            " [[ 0.00491231  0.69319077 -0.20364049 ...  0.23149795 -0.28978574\n",
            "  -0.49329397]\n",
            " [ 0.11072935 -0.07990259 -0.20364049 ...  0.09356344 -0.25638541\n",
            "  -0.49329397]\n",
            " [ 0.21654639 -0.27244466 -0.20364049 ...  0.02459619 -0.25638541\n",
            "   1.1400175 ]\n",
            " ...\n",
            " [ 0.85144861 -0.91998844 -0.20364049 ...  0.57633422 -0.65718941\n",
            "   1.1400175 ]\n",
            " [ 0.85144861 -0.91998844 -0.20364049 ...  0.57633422 -0.62378908\n",
            "  -0.49329397]\n",
            " [ 1.0630827  -0.51148142 -0.16958144 ...  0.57633422 -0.65718941\n",
            "  -0.49329397]]\n",
            "train.shape: (1654, 21)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 4) Создать и обучить автокодировщик с подходящей для данных архитектурой. Выбрать необходимое количество эпох обучения."
      ],
      "metadata": {
        "id": "0T11A0x4o-gr"
      },
      "id": "0T11A0x4o-gr"
    },
    {
      "cell_type": "code",
      "source": [
        "# **kwargs\n",
        "# verbose_every_n_epochs - отображать прогресс каждые N эпох (по умолчанию - 1000)\n",
        "# early_stopping_delta - дельта для ранней остановки (по умолчанию - 0.01)\n",
        "# early_stopping_value = значение для ранней остановки (по умолчанию -  0.0001)\n",
        "\n",
        "from time import time\n",
        "\n",
        "patience = 4000\n",
        "start = time()\n",
        "ae3_v1_trained, IRE3_v1, IREth3_v1 = lib.create_fit_save_ae(train,'out/AE3_V1.h5','out/AE3_v1_ire_th.txt',\n",
        "100000, False, patience, early_stopping_delta = 0.001)\n",
        "print(\"Время на обучение: \", time() - start)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rPwtBtdRPztp",
        "outputId": "a89c34e5-38fd-4d77-c9b8-a73ba7cff7d1"
      },
      "id": "rPwtBtdRPztp",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Задать архитектуру автокодировщиков или использовать архитектуру по умолчанию? (1/2): 1\n",
            "Задайте количество скрытых слоёв (нечетное число) : 7\n",
            "Задайте архитектуру скрытых слоёв автокодировщика, например, в виде 3 1 3 : 46 26 14 10 14 26 46\n",
            "\n",
            "Epoch 1000/100000\n",
            " - loss: 0.0574\n",
            "\n",
            "Epoch 2000/100000\n",
            " - loss: 0.0360\n",
            "\n",
            "Epoch 3000/100000\n",
            " - loss: 0.0261\n",
            "\n",
            "Epoch 4000/100000\n",
            " - loss: 0.0217\n",
            "\n",
            "Epoch 5000/100000\n",
            " - loss: 0.0204\n",
            "\n",
            "Epoch 6000/100000\n",
            " - loss: 0.0185\n",
            "\n",
            "Epoch 7000/100000\n",
            " - loss: 0.0189\n",
            "\n",
            "Epoch 8000/100000\n",
            " - loss: 0.0176\n",
            "\n",
            "Epoch 9000/100000\n",
            " - loss: 0.0165\n",
            "\n",
            "Epoch 10000/100000\n",
            " - loss: 0.0159\n",
            "\n",
            "Epoch 11000/100000\n",
            " - loss: 0.0158\n",
            "\n",
            "Epoch 12000/100000\n",
            " - loss: 0.0150\n",
            "\n",
            "Epoch 13000/100000\n",
            " - loss: 0.0147\n",
            "\n",
            "Epoch 14000/100000\n",
            " - loss: 0.0146\n",
            "\n",
            "Epoch 15000/100000\n",
            " - loss: 0.0142\n",
            "\n",
            "Epoch 16000/100000\n",
            " - loss: 0.0138\n",
            "\n",
            "Epoch 17000/100000\n",
            " - loss: 0.0138\n",
            "\n",
            "Epoch 18000/100000\n",
            " - loss: 0.0140\n",
            "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:absl:You are saving your model as an HDF5 file via `model.save()` or `keras.saving.save_model(model)`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')` or `keras.saving.save_model(model, 'my_model.keras')`. \n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n",
            "Время на обучение:  765.1605446338654\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 5) Зафиксировать ошибку MSE, на которой обучение завершилось. Построить график ошибки реконструкции обучающей выборки. Зафиксировать порог ошибки реконструкции – порог обнаружения аномалий."
      ],
      "metadata": {
        "id": "8ALjaY8lo-sa"
      },
      "id": "8ALjaY8lo-sa"
    },
    {
      "cell_type": "markdown",
      "source": [
        "Скрытых слоев 7, нейроны: 46->26->14->10->14->26->48\n",
        "\n",
        "Ошибка MSE_AE3_v1 = 0.0126"
      ],
      "metadata": {
        "id": "b4sk_fhYY6Qb"
      },
      "id": "b4sk_fhYY6Qb"
    },
    {
      "cell_type": "code",
      "source": [
        "# Построение графика ошибки реконструкции\n",
        "lib.ire_plot('training', IRE3_v1, IREth3_v1, 'AE3_v1')"
      ],
      "metadata": {
        "id": "a4sR3SSDpBPU",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 724
        },
        "outputId": "8f487b44-e128-4e72-b3ff-e400431401f3"
      },
      "id": "a4sR3SSDpBPU",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x800 with 1 Axes>"
            ],
            "image/png": 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YxlfQ0quqcvpVr9wl7aSUtPICsMfxDABm4HzcHkFLs5RTHS0MEgHFRBm0JNMShilJ0BIIDZmWQPnieAYAmIru4WYppzZDOX0WU5VT3ZcIWqKiBJrK+6yzzlKXLl0CL1dVVaXXX389SFEQFtNPSgQtgfLF8QwAMBWZlmYppzYDmZbwijEtUUECBS3Hjx/v+HqmW7jTcqlUiu7jJknaSSlp5QVgj+MZAMzA+bg9Mi0RFYKW8OqHiZEjwZiWMIzvoGWKylueTP9eybQEyhfHMwDAVOWQaVlOQctyajOU02dBaUydmv93lJmWQMx8BS1b+TWofJl+0SRoCZQvjmcAgKm4kTdLObUZuLcurXKoO19/nf833cNRxpiIB/nK9aTU2ip99JHU2Bh3SWCSpUulzz+PuxTIKNfzDwAgGVpa0u1Fq67gSesenkpJH3+cP2EHmZZmImgZvXKq+62tpc20LKdjDYlE0BL5TD8p+c20/O1vpb33lk48MfwyIZnWrJF23FHaZRfp0UfjLg0k888/AFApKvV8/ItfpNuLgwa1fy1pmZZ//rO0557SgQeW5/dZTp+JoCW8mDUrfR+TK8zjgTEtYRiClshn+knJb9DyrrvS/7/8crjlQXK98II0e3b68ZlnxlsWpJl+/gEAlLfMj5hPPtn+taRlWl5xRfr/jz+W5s9PPy6nbLNyajOU02dB9BYvjnb9ZFrCML7GtLz22mvDLoeuvPLK0NeJCsBJFH4tXBh3CcAYtQCApEhapiWSg0xLeGFVX+gejjLmK2h59dVXqyrkX+oIWhrCKohg0q+yBDkQliVL4i4BOJ4BwEycj9sjaGmWcqqjBC1LK+l1h6AlKoyvoKUkpUKsvGEHQBEAQUtUiqVL4y4BGDMHAMzE+bi9pHUPt2JSmz6ocqqj5fRZEL2og5a0z2EYX0HLN998M+xywBRJCwqaXj6YKzfTslu3+MpRyZJ2vgEAVC4yLc1STm0GMi3hRakzLYGY+QpaHnzwwWGXA6YwvQFgevmQHLmZluusE1sxKhq/5AIA3Jg5U3X19fGWgUxLs5RTm4GgZfTKve7TPRxlzHf3cJQp0zOfTC8fkiM303LttWMrRkXjeAYAFPPBB6rdbz8dudZaSh16qNSnTzzlIPvILOXUZiinz2KqctrHUQe5CVrCMNVxFwCGSVoQwfTywVxkWsaPTEsAQDEnnaSq1lbVrlmj6htuiK8cBC0RFTIt4QUT8aDCELSEM9NOUkkLqsJcuZmW3bvHV45KxvEMAGYy6Xycc72uWrUqvnIkuXt45vss9y6ySUXQMnrlVPeZiAcVhqAl8pl+UiLIgbCsWNH2uJwaMklCowgAUEyprtHFrkFkWpqlnNoMBC1LK+l1h0xLVBiClsiXtKCg6eVDMtBYjEfSzjcAgPJVLChJ0DJcjY3SPfdIw4f7e385tRnK6bMgegQtUWGYiAf5TA8imF4+JEdu5gZBy3iQaQkAMEWxoGSSu4dn2jwm9Sz5xz+kSy9NPx4/XvrRj7y9v5zaDLRD4QWzh6PCkGmJfKYHBU0vH9ybPVtasybuUqRVUmNxwYL8rvFx4ngGADOZdD4uVVnItCytTMBSkh57zPv7TaqjQVVSOzQuJgXsg4q6vlAfYRiClshHEAGlMGKEtMkm0nbbpbsHxaESMy0/+UTaaCNp002lRYviLg2ZlgBgKlPPx1EGHoplFyU509LE7zP3uzSxfKVU6Z8f3tA9HBWGoCXymX5SIqhaHo47Ln3BnT5deu65eMpQiUHLk06SmpqkpUulv/wl7tJwPAMAzFHsRj3JmZaZz2LSdTZo0NKkzxJUpbRDEY6og5a0z2EYgpbIZ/pJKozymfaZKl1cmQuVGLScMaPt8apV8ZUjg0xLAIApCtsjBC2jFTRr1qTPElSltEMRjiiDllGPlwn4QNASzkw/SRG0TL4OHeLZbm5jOck3Il7k3pDFtd9zmf4jCQBUKpPOx3GNaVmO3cNN+l5zVXp7vpw+SxIkfX9HGVgkaAkDEbREPtODCGRalp+11opnu5WYaZkrrv2ei0xLAIAHqTjHtEzyNcrEoCXdw9tUYju01JiIxx2CljAQQUvkM/2kRNCy/JiQaVmJjUUyLQEAaFMYtCxsGyS5rWDi9ZWgZZsk1y2UHt3DUWEIWiJf0oIIppcPxRG0jAeZlgCAhKmK8jpRbEzLJLcVyjHTspwk7f4L8SJoiQpD0BL5TL9ohlEe0z5TpTMh4y/JNyJ+mbDfTT/fAEClMul8XKpuncW6hye5rWB60NIPkz5LUOWU1YvolTpoCcSMoCXymR5EoHt4+amO6TSUe8GvxMahCUFLMi0BAMWYMhFPObQVTL3OVnp7nqAlvCDTEhWGoCXyFTspzZ0rnXCCdPHFZpzAKr2RA/9y68FHH6V/8f/lL5M9O6gXJgQtTf+RBAAqlaHn41gn4klyIMnETMvcH60rvT1P0BJelHr28J//XJo/P5z1Az4QtISzwhPXuedKw4dLf/+79OKL8Zen0hs55SCu78Nquw89JN1zT+nLEgcTx7QEACAuBC1Li4l42vAjbmklff/GcS4699zSbxP4AUFLOCs8qb/0Utvjiy6S1qwJtv7ly9OBoqlT/ZWn0hs55cCkoKUkvf12acsRFxOCljTSAQCmKOxpUU5DmJgYtMxV6e15Mi3hRRxjWg4fHs76AR8IWiKflyDC999L110XbHvnnpvukrvzzu1/4Xaj0hs55SCu78OuQVhTU9pyxKVUExs4KacbQgAoJyadj+Ma07Lw7yQHkkwMWprQDjEFQcvomVT3g2IiHlQYgpbI5zXz6YYbgm3vqafS/69Zk866LIZMy/JjWqZlXBMDlZoJxwFBSyAcbq6fgBemno9LOaZlOQWSTA9aVnp7np4n8IKgJSpMhdydwzXTT1QELREWgpZxl4BGOhCGc8+V1l5buuWWuEuCclKJ52MyLUsrN2jpZ9+a9FmCKqcAuanKqb6UeiIeIGYVcncO1wgiIGqm1LFKD1qagExLILj7708fO3/4Q9wlQTmpxPNxsTEtkxxIMj1o6YdJnyWocqprSZD0uhNl/Uj6vkFZ4u4c+UwJKNkpx0zLVEq6/HLpjDOkRYviLk30Ghvz/zYtaFkpY1qacByYfr4BgEpViedjuofHpxza80GU00z1pkp6fZkxQ/r5z6W//IXu4ag4tXEXAIYxPYhQjkHL4cOlm25q+/uxx2IrSkkUzjhv2kQ8lZJpacJxQKYlAJipEs/HBC1LizEt29AeQjGnny69/bb0r39J55zT/nWClihjFXJ3jrJVDo2csWPbHj/+eHzlKJWGhvy/Tcu0JGgZXxlMKBOQJEkOosBslXg+Lha0TPI+KcegZTkppwC5qZJex95+u+3xhAntXydoiTJWIXfncKvK9CBCOWZaVprCTMu4VFr3cBNvvkwsE5AkhUEWICyVeD4u50zLDJO+VzIt25RjXTNNOdWXpqb2zxG0RBkjaIl8BC0RNTIt42HKfncqgwllApKEoCWiUonn48KJeJg9PFpJmIinVD+0hzWmZUODWd8xohFl0BIwUJnencO3pAURyiFoGbTRljSMaRkPU/Z7LjItgWAIWiIqJgXoSnVtKDyeCFqWjont+T/8QereXbrttmi3I4XTHnrjDalXL+mQQ8z9nuNUTvvEKmgZlnLaTygbZXp3Dt/iPFG52XYY5eNkHC9TMv4qrXu4KfvdqQwmlAlIEoKWiIqp5+Mof+gt5+7hJgYtTe8efsst6eDQ738f7XakcOraYYdJ9fXSW29Jr78eTrnKlUnHgR90D0eFIWiJfHEGEfwELU1s5MBZYcbfu+9Kp5wivfZaacuRlO7hN94onX22tHBhsPWYMpZoLjItgWAIWiIqXs7HLS3SH/8oXXihtGpVdGWKGkHL0jI5aFnqc2tY3cMzli4N9v6Me+6RBg2SZswIZ31xMqnuB0XQEhWmNu4CwDCmBy3jek+UTCtP1Aoz/q6+Ov3/M8+YUd9MClqOGiX97/+mH9fUSPfd539dZFoC5YegJaLi5Xw8dKh0883px+usI113XSRFilzhmJYELaNl8uzhK1eWdnsm/oj73/9K55+ffjxrFtmbJiFoiQpj0N05jBR3EGnKlPRFMnMxJ8iRfIU3BXFJQvfw//yn7fH99wdbV2Fww4Rjx8RGOpAkBC0RFS/n43//u+3x44/HW5YgimVaplLS+PHSBx+UpjxhMj1o6UeUn6W+Prp1WzExQD5hQtvjN96IrxxhManuB0XQEhWGoCXymZRpuWCBtMMO0uGHS089Zb1MOWRaVhpTbrKTMBHP4sVtj9deO9i6TAxa8iMEEIwp51OUHy/nY5Mz5rwoFrT88ktpr72kH/84eYFLE4OWuUxrz69YEd26rYTdPTwMJg4rFISpdd8PJuJBhTHo7hxGMGkinvvvb7ton3aau/f42U7cKm32cFNuspPQPXzJkrbH66wTbF0mZjWaWCYgSUy4sTVVayv7Jwgv5+Pc62bU5/FSTsTj1F7JdJtNChODliaPaUmmZbLHpy13ZFqiwhh0dw4jmJRpadUwJdMy+UwJWtoxqXt4mEFLMi2B8mP6+TQuc+dK22wjbbddfsY63PObaRl1sKWUk684HV9Ju16ZWF6Tg5alzrQ06Ufc1lbp0EPTE2uVExOPAb8IWqLCELREPpOClm6WMa2Rg+JMuMl2qgMmZVrm3mz37BlsXSYGLU1qpANJZML51ES//a307bfS119LQ4bEXZpkMql7eKl6pBSbiCfJyLT0ptSZlmF3Dw+yb4YPl958M9j2TWfSceCH1bWfoCXKmEF35zCC6UHLJG0H1ky4CXAqQ1IyLRsapMsvl665xt0+DTtA2NIiXXllenZzv2PrkGkJBEPQ0tp//9v2+Jtv4itHkpkUtDRlIp5cSb1emVRuk8dCreTu4fPnx7ftKJlWx8JW7p8PFa027gLAMCaNaelmGdN+mUVxJtxkJzHTsjBoeeut0k03pR9vtpk0eLDzusLe7/fdJ113Xfpx797pzCavyLQEgjHhfIry5CVoUsrgUynHtDThR9awmJ5p6Qfdw+FFue9TMi1Rxgy6O4cRTM+0LMegZblNxDNvnjRmjH1j34Sb7KQELRsa2h536JD/2sMPtz1+7rni6wq7e/hjj7U9HjbM3zrItASCMeF8ivLkdyKeJAf6yjnT0vSgpWnt+aRnWgbZN3Hcl0yfLr3/vln1s1LxHcBABt2dw0imBS3jeg/caWqS9thDOuQQ6Y47rJcx4SbbqQ6Y1D08V9AAX9i/4jc2tj1eay1/6yCzAAjGhPOpiTiXBFeJQUvGtCwtk4OWpc60DHtMy7D5bee5sXixtP320n77Sc8/H912TKr7fhRLqiDTEmWMoCXykWmJIN5+W5o9O/34d7+zXsaEm+wk1gGnMrv5VTzsTMswgpZkWgLBmHA+NVHuuaTcejOUCmNamhc4CsLEoGUu09rzSc+0DMLqnNmpU3Tbu/deafXq9OOTTopuO0lXLKmCoCXKGEFL5DNpTEuriyZBDrMVZilYcbrJLtX36dQYNPUmJWjdNzFoSaYlEAxBy+IIWvpjUtCyVAqPp3I6vkwMWpqcaRl30DLoZwt73xQOURQmJmJ1h6AlKhhBS+QzKdPSzY2GaY2cSuemge+0TKkChk51wNT6EbRcYTeIc8fbJNMSiEc5BVVgFr/dw8tpIh4TfmQNi+lBS9OsWlXa7ZnUPdyqG3LHjqXdXtRMOg7cMiFoSZsDMUlk0PLtt9/W8ccfrw033FBVVVUaPnx40feMGTNGe+yxhzp06KCtt95aQ4cOjbyciWRS0NLvMqVYB6wRtIxO4b7x2tiPMtPS7y/wZFoCwXADgaj4zbQ0tbeCG3QPLy2TMy1L/d1H1T3888+lCy+Uxo1z/x6r9mU5BC1Nqvt+lGrMfaf91NRUmjIABRIZtFy5cqV23XVX3XXXXa6W/+6773TsscfqkEMO0cSJE3XxxRfr7LPP1quvvhpxSRPI9MwnxrQ0WzkELU25SSkW0CuH7uGmn28A0xG0tMa5JLhK7B7uZSKepH1OgpbelEvQcs89pbvukvbdN9h6ouweXqqMW5Pqvh+1tc6vlyLTkqAlYlKk9pvp6KOP1tFHH+16+XvvvVdbbLGFbr31VknS9ttvr7Fjx+pvf/ub+vXrF1Uxk8n0TMu43gN3go5pWapGYhJuRAr3ZdCJeMLet4xpCcSPoGVxJndBNVklBi3JtIyPae35Uu+nqO6/cttqblmdM6OcPTyO7uFJZEL3cIKWiEkig5Zevf/++zr88MPznuvXr58uvvhi2/c0NDSoIWfMtuXLl0uSmpqa1FSGB2zmM7W0tKim8Pmcz1vn8F4/ctfX1NiYt61qi7JUNTXlVdqWlha1Fmzfqoy5CrcTt+rW1vb7PKGqGhvzvh+rz1Ld2Ci7y25TQ4PjL4mZ9QXeR42NtvWkpbm5XZ2KxerVeWVsbWlRS065aiVlmpWtra15r1mpamjIP3YCfs7axsbs9ltqa32ty83xnFSh1VXAQeFx7bW+lWs9rW1tbTs/SkXPj0jLveY0Nzcr5XK/1ait61YqlVJzyPu78HoX1XWiuqkpr33SXNCmyZVqbQ39c4Yt7/tsalKqqUk1LS153eziPPZrq6ravteCNo4bVvcJYalpbva1n/yeU63qntvjL8Pq+M27z3K5vqqWlnb1Psr6Xqr7oNy6n5KMP34L1dbUyOknuMwx7pZtXXW4R2patUrq1s31NgAnXo71ighazp07VxtssEHecxtssIGWL1+u1atXq1OnTu3ec+ONN+qaa65p9/yoUaPUuXPnyMoat6lff60dcv5++623VP/tt9m/f2rxnpEjR/reXu763hozRiunTMn+vc2UKXllGTlypNb9/HMdkPPc99On67OC7VuVMVfhduK2w7ffapucv4Psz7ht9PHH2jPnb6vPsvUXX2hHm/ePeuUVNVscj4VGjx7tr4A/qK2v17E2r3391VeaYsB3ULtyZV4ZZ0yfrok55Tp85Up1+eHxvPnz9WGRMm84frz2yvl78pdf6psgx27OjzrTZs/WJB/r6jN+vPbO+Xvat9/6Wo/JgtZVwMl6EyZov5y//V4/yq2eHlpfr8xt1YIFCzSuzM4rUcltP0369FNNd7nfdp05U5v/8LilqSn0dsxxOUGNmTNmtGv3hWWnb77RVjl/f/LRR3nXqFwrVqzQm4bXq9zv8/3339fi5cu1+4wZ2jTn+ZEjRsSWjXzYqlXq+sNjN+2YQrtOn56td1K47ecfzZ6tjQOs2+s5dYvPP9cuOX+Pe+89LVq2zNM6cr/viRMmaFbXrnnPuf0Mm37+uXYveG7Z0qV6K6L6vuWUKdo55++o7oP2nDNHG/3wONXamrj7rSObmuR0h/Tu2LFaOn++5/UW1tUuc+bocJtl33j1Va3p1cvzNgArqzxMeFYRQUs/hgwZoksuuST79/Lly7XJJpvoyCOPVPfu3WMsWTSampo0evRobb311nnPH3TggdIOO9i8K+2YY45R9eWXq/q559Ry991KHXGErzIcfNBB0jZt4bvqSZPabaeqS5e85zbdZBNtfMwxgbYTt+q33877+xiPn8ckVYsX5/1t9VmqP//c9v1HHn641KOH7euZenrEEUeorq5YTq2DJUtsX9pmq620lYfvoPrCC1U9erRaHnpIqf33b79AS4tqTjxRVd9+q+bnnnNf9xYtyvtzk4031oY55arN+fFkgw02KFpvqurr8/7efrvttG1IdW3z//kfbepjXVW5M5BL2nyLLXytx0Ru6mr1vfeq+uab1XLFFUqddVaJS4hyUFXQrc7r9SO0c6phanPaCuutt16ir6tx2XmnnbSjy/1W/fLL2cc1VVWh7+/qnHq+sY92n+vtjBqV9/ceu+1mu2y3bt0SVa/2/fGPlTrwQNU891ze88ccfXRs3XNru3bNPt7Ax3Fa8+9/5/0d5vdR89hjvtbt95xa/d13eX//eJ99lDroINfvL7Tbbrtp14Iyu/0MVQsXtnuuR5cukdX36m++yfs7qu3kfqdVEZynolbbtWu7e4Nc+++3n1J72/3M0p5tXf36a9v3HHrggdIWW7jeBuAk05PZjYoIWvbu3Vvz5s3Le27evHnq3r27ZZalJHXo0EEdLAYdrqurK6uGfaGagl9b62prpSKft27pUum22yRJtcce63tMjXbbKugmXFdX1248j5qqKtV4/D7cfKaSKvhMia5fhfXH63dTU+Pquwl8HDp0QfdUp774Qrr//vQqDz3UevyrYcOkH37NrTvjDOnjjz0XV5Kqq6pUnVuunOOsuro6/zUrBd9NTXW152PHTk2nTv7WVXCj5Od4Np1jXf3tbyVJteeeK51zTglLhbIR8Jyb+75EX3sK5eyXdudOuOLpGpHTjqlKpcKvSwXXu1JdJ2odMhCrqqoSdczUZtpXVu38Us1KXCj3OJW8H6chnf+iWLfnc2rB9mqrqwPdq9Ra3Ou4Lo9FfahqbY2uvvstp1c5+7gqyu1EpchxavWdu9GurjrcI9Wl3+B5G4AVTz/sRFgOY+y77756/fXX854bPXq09g06k1o58hNwXLkymm1bNRaZPdxsSZk9PKyJeGbPLv6+qVPbHn/yift1e5mIx42wZw/P5XeA9sKxTDg2AW+YiKc4JuLxx835uLVVuv126b77vL3PVF5mcE7a57SbiCfOyYaCHpvMHm4vyL6x+l6ivNZwjnanEibiGTdOuuwyKWdoukCeeUa65hrJQ0YfzJTITMv6+npNzQkEfPfdd5o4caJ69uypTTfdVEOGDNGsWbP06KOPSpJ+/etf684779Rll12mX/ziF3rjjTf0zDPPaMSIEXF9BHMlbfZwmCVo0LJUdcBpO17KsGZN8WX8NjyLBS29NvKinKnb76+uBC2BYAhaWss9l3BD7I+b8/ETT0i/+13+c1EHe6L8PsMOHJnELmhpynXXtCSEUu+XUtS9VMr/8RPltaZUwxOYUtf9qoSgZSah7Nlngwcuv/xSOuWU9OO5c6V77gm2PsQqkZmW48eP1+67767dd08PE3zJJZdo991315VXXilJmjNnjr7//vvs8ltssYVGjBih0aNHa9ddd9Wtt96qBx54QP369Yul/Ebz05gJqwHpZltkWpotKZmWTnXASxlWrw62LSeFDYOgQUcTgxthZ5P69d//8issksnE49oEXOeDc7MPrW4Ck7zvybQsrSRlWkb9fZcimOx2nVZBRDIt4+fQbVuS+++3tTXd86uwDe5mPaU6XxSM8erLa6+1Pb733uDrQ6wSmWnZt29fpRwOqKFDh1q+Z8KECRGWqkwQtEQQ5RC0DDvT0m998xLQc3MMRtkADyswG8ex+fTT0oABUu/e0rRpksVYxpEopwwexIegJaLit/2X5DYWmZallVt/TGvPW+2nJGX5Wu2blhZ3WY2l7h5OpqU7YWVannuu9MADqjnxROmMM7ytp5yGZECiJDLTEoYpZdAyrvfAnaQELcPKniiY/drztpwUC+gFzbQkaJk2YED6/7lzpeefL912GxtLty2UL4KWiIpJQctSXRsKr9cmDGcTFtODlqYFLEqdkVqKgHmQdUb5+ePItEza8SuFN2HWAw9Ikqqfe8769XIJWibxO4YtgpbIZ/qYlmRami0pQcuwuj7EOaZlLjcNviiDll4/Y329dNhh0m9+E12Z/LDrKhMFgpYIA0HL4uh66I9JQcti2wxL4fFkWiAtCLqHtzn3XGm33aTPPrNfptRZt6X4XtxeL0qdaVkqcbcxg4piTEurelYuQUuUlUR2D0eE6B6OIMohaOmlfkQ5pmVhAC3ovjGpe/g110hvvBF8PUlG0BJhKIcbySgwEU9wbs7HVt06Sz32X5i8ZFomjYmZlrlK1Z4fO1a6//7042OPlWbMcLfuqPdTKcbQDNKOjPJYiKPtn8TrQgRBy1qr+5i4gpbldL5F6Mi0RD4/F+moZitzc0EhaGkWN5lq5RS0jDLTMuyu0yZ1D3///XDW89hj0p13Rj+bYRQIWiIMNPKtcZ0PrpQ/WpuyHS/ZdYsXSzfcIL3+erRlCovd92lKpmWp2vO5MxLPnGm/XKkzLU3qHl7qTMs46mASrxERBC3rVq3y9oYkZVom8TuGLTItkc/0oGUY2+IkFh03FxzTg5Zhdw8vxUQ8bpgUtPQzY2Gh116TBg1q+/vCC72VIW4ELREGgpbFJTGjxgRuroXlNoGGl8DRvHnS//1f+vHChdK660ZXrjCZlGkZR9DS7TAwpe5Gb1L38LDfW4wJbf8kiCLTcuVKb+shaImYkGmJfGGNhxHVtukebrYwuofPnSstWRJemey2Yyfs7uG52/Jyg1csaOm1HofZ9Sho1/XJk62f91KmBx9se/znP3vbvp1SBjfcTOIEFEPQElExKdOyVPxmuzmNjWgKE7uHxxG0nDbN3XJxZ1oG/V6s3m9qpiXXMXdKlWlpSvfwFSucs6FRUQhaIp9JmZYmvSdK5dToD9o9fMIEaZNNpI03lubMCa9chaLoHt6hg/UyuY1EL9911N3DgygMuHkp2y23SMuXW7/m9zOadky7QaYlwsDNHqLid0zLqEXZZvIbqEpCO64cJ+Lx6rXXpOuuc7dsqfdTKYKkpk7EQ6alO2HNHp7Dc9Ayyu+qcN2bby5ttpn01lv+1pf07xt5CFoin+lBS5N+IUZ7QTMtBw1KBz5XrZIuvzy8chWKont4p07Ft+Wlge4lm7HUs4cHCaj+4Q/2r3lZTxJuEp0QtEQYohz2IcmSPuGCCci0LK8fBUzMtMxViiSEY491v2wpJsZx2l6cY1paKbdMS1PqvRfFylxu3cMXL04/5+W4zZXE7xi2CFrCmZsDvthF8JtvpAMPlH796+AnQrqHm83NhChOjZPcIOCjj0rHHSdZXVCDCuuCnNs9vGPH4usLkmn5wgvSAQdIX3/dfr1uhNkAj6oxT6Ylkuj226Uf/Uh6883Sb5ugpTX2Q3CVGLQsPJ7izEIMm4lBy9xM3VK0571cd8txTMsgmcOlzLCLStKvCxEELY3uHp4RxX0gEoegJfJF0Wg4+WRp7FjpvvukUaNKu+2w3gN3ggYtC40YIV1/vf/y2AlrTMvcIKtd0DKsMS0l6d13pZ/9rP3zpc60jOqmJ+5My1LegBO0LA+NjdLvfid98ol06KGl3z5By+LKLbBWKiZ1DzdxIp6kMb17uGnt+XIc09LU7uGlyrRM+vWx3IOW5XS+RegIWiKfn2BEsZPMhAltj7/6yv223SxjWiOn0gUd09LK2LH+yuIkiu7hbjItgwYtJWnSJOdt2IkyaFnKybjCfF+cmIinPMQdfC7nzLAgknhOMI2pmZalvGkOEuQxjYmZlrlMa8+X45iWQTMto9rfXLfciaJ7eDkHLU05tyEUBC2Rz6QxLa0umuUYtExCY9etsDMtoxLFRDxuMi2DdA8PKsxf8cs107KU4g52IRxxX0/ItERUTMq0zFVO2XWlZHqmpR9e64KXiUxKHdyN4nvxu0677yWqukKmpTsRlL/OpDEtTbg/hLEIWsJZGJmWfkUVlDDtohXlLNmllhtos2sclqqBPGuW/QWwlJmWYXYPt1Pq7uGMaRkcQcvyEHfdI2hZXNJ/4IgLmZaVEbQ05ZwRRjmKrWOttdyvqxy6h4c9sZTX9zc1ubvHKafjLE4+6kyV1XdKpiUMRNAS+eLMXKzE7uHPPJOecKZc5Aba7IKWTo0eq/f4uSm6915p442lQw6x/r6jyLTs0KH4+rwELYtlWnqtx4xpGc867RC0LA9xX08IWlpjPwRHpmXwzDSTmBi0DHsinmLrqKvzv+6kdQ+3CloGrc9egpYtLdJuu6Xb4s89V3zZUkj6dSGC7uFVUd4jeUXQEg4IWiJfFGNa+t22m2WSHrQ85ZS4SxAuN5mWTo2TsG6Azjsv/f8770jTp7d/PYqJeNx0p/FyYxN2pmWYjQHTxrRMIsa0LA9x11mClsUlIaBkIjfn9Tj2bSlnMS6n7oqmdw8vRXve5EzLsL+XuDMtX39d+vLLdBlOOsl52ah67xTKXW8Sr5URBC09v4fu4YgJQUs4i3NMS5PeE7YJE6S+feMuhbXXXpMOOMBfBmgUQcugN0W5gcWMsLqH52bL2a0z93m3n2XoUOnCC92Xw41yy7SMYvul0toqDR4cdykQhrjrHhPxWIv7eykHhmZaWmYGhaWcu4dnmJRpmctrOebPl5591ts6gmRaRr2fTMq0tPusXoJKVm1vO1zH3CHT0htTzm0IRW3cBYBhyLQsjYMOkurr4y6FtSOOSP//7rvSoEHe3pubHVhrc3rxGrQM+n1ZdbMO64Kcmy3nppHn9gbvrLOKL+N1vzARjzn+/e+4S4CwxH1zRaYlolKJY1qWU/DE7jpdLpmWF1zgfXtegpZJH9OytdV/fbbbtpd94OUHjcL1Njd7mzTJraRfH0uVaRlWYodXST7fInJkWiKfn2CEl5Nk0GCRqb8Qe2VqwDIoU7qH54oqaPnhh9Ls2cXflxvILcUN3jffSNddJz3xRP62mYjHHF98EXcJwtHcLA0bJo0eHXdJ4hN3I5ugZXErVkj33Sd9+mncJUmWSgxahp2ZFie3Qcs4yx4kaPnCC+2fK7aOwu7hToGxUgd3TeoeHkampZf2fOF6vQyPVEkiOFaNyrSkezgckGmJfH5ORnGOZ5fUTMtylRsgtGuwlLp7uFXQ0qnOuqnPixdL++yT/5xdvXKzT8L005+2BcXq6qSf/zz9uNy6hyd5Ip511y3NdqL28MPSOeekH3/6qbTLLvGWJw4ELc33+uvpf5K0apXUqVO85UmKUva0KaZUY9H5DfIk4Wa73IKWfq7XhUFLux5BUvyZlknvHu7l+7HKtIxC0q+PJmRa0j0cMSHTEvmizrR0uogVrsdq2XLpHl6ugnYPj6I7SBSZlu+84/59uduPasKc3PXmZvH997/26w0zaBn3RDy571u2LJoG76JF4Z07uncPZz1xyx139d574ytHnOIOWlbCGHx+2B2rX31V2nIkmZvzXRzBOhMzLU087pLWPTyM93od09KkTMuwz+WtrfFOxOPluyXT0p0ogpZe10PQEjEhaIl8UQctvayHoGXymDgRTxRBS6tMHTfdw91kWoZ50c7d15WQafnOO1Lv3tL22+dPkhTUP/8prbeedPzx4ayvXBrkQWd+LQdxByvItLRmtx+8jGlX6dzUpTjOZSYGLU3MtExC9/Bcpci0LDz+vWRaRr2fwt5e3JmWQca0tGq3h8GUuu5XBEHLKqs6QfdwGIigJfL5aczEmWXlZ9tJv2iZLIru4UF5DVq6qVMdO7pfp9fu4UHHHMqV+1kqYUzLww9Pz1g5dar0yCPhlElKd4FOpaQRI6QFC4Kvz2udhLkIWiYLQUv3yLR0//niPg9YSVqmZRhBS69jWjoFLctxTMukBC3pHm6NTEtvkv59Iw9BS+QLM3Px22+ln/zE/fr9ZHWSaRktr/vKzaQzJgYtb7jB/jUrVkFLu4ut14l4/NwEutnXYTYGTM20zM2uXLbM+/aj+n4KWWWBmnjTi+Li/t7cBi3vuEM65pjymQTKryiGIClXJmVaxjWmZSV0Dy+nMS29dg9fvFg69tj8oXTs1lVJ3cNLPaYl3cPdKfdMSxPPozAGQUs4C5JpedJJ0r//He62wmhEELR0z+u+amhoe2z33Xgd0zLqiXguvFA67bS2v9185sJf653e5zXTMsgv4U7HR5Tdw00a0zIJrIKWSfsMEt3Dpfgb2W6O61mzpIsukv7zH+mII0pTLiRfkEzLKM8HJgYtTezWWIlBy2Ks2m4jR1oP/RL3RDwmdg/3sg+YiCd8UZTfzb1E1GXIMPE8CmMQtES+Yo0ZN79sZga6nzAh2LZNek+l8tpImzev7bGfX2r9/HJeTLFMy6qq/O26+cxeLvJex+YJctEuLEOpxrQcMyb9A4XVvlu8OD3L9KxZ3tcbRFTHeRjZwOXSPZygpXlBy9zyZI698ePbnpszpzTlilsYN92Vzs2+sgsuRHnzWcqb5krItDSle7hXVtdir5mWGVOnFl9X2O2Tl16SXnvNfv1RdA8Pmmn50kvSffdJjz4q1dc7r6NYW2nNGumxx6TPPyfT0q1SdQ+Paxt0D4cDh8E8UJHCGNNyl12k5cuDb9vNMgQto+XlAtLcnD/en59Myzi6h1dV5W/XTz10el9u48tNgzHMoGXudxDmr/iF65oyJT0UxPPPSyeckP/aaadJr7wi/c//pJfr2DHdWLWShKBl0MxfqTwzLStV3MEKpx8jBgyQRo8ubXlMQdAyuCCZli0tzuMFelVV1VaeKL9DMi3jU4pMSy9j2kaZafnyy9JPf5p+PHGitOuupekeHjTT8tJL2x6//750zz326yjWnr/5Zumqq9Jtwn798l8j09JaGEHLgmXoHo6kINMS+cIIAjY0SN99Z72sUyOjVN3D4Z6X/TtvXv73Y0r3cKvGT9BMSy8X+dygqZsbG791ur7e+Vf1KDMtMy68sP1zr7yS/j+TgR3WjWyxepG0oGXSz2VJvxnwK+7vzem49hKwXLnSrO9wzZpoblzj/r6SJMiYlknNtCzniXjsFJY9qmPPStwT8TiJ8n7jlFPaHt99t/X6TZyIJ9e993ovU66rrkr/v2ZNuot+LjItrYURtPTbm8zL+/3KHWIsDCa1aRAYQUvk89M93OoE5ufGnu7h5vGyr+bOdffeUmdaFgsQVVd7bzj77R4eVablM89I66yTHlA+V6nGtMwIGtCrlDEt6R5ePuIOVoRwXPf69FPVbrSRtM8+8X8eKf0Dx0YbSVtu6W9CLScmfL6kCJJpedtt0ZWFoKU/bjItv/pK2nBDaautwj/2rJR6TEsvP5pGmWm5enXb4/XWS/8fdgZsFN3DvW7frcI2EZmW1jLlt7tX8pNpacqYlgsXSkceGe46k/59Iw9BS+Tzc9G0WsauMeHlROjmV1Qm4omWl/1bOFaan0xLq+88aCCsWFfccuke3tzcPrPKafbwKIKWbt6XaaAHXW8UmZZu6loYNy50Dy8fcQcrQgha7n/VVapatUr66KP0ZD1xO+OM9HicM2ZIN9wQ7rqTeJzFJUim5RVXhFuWXKUMWlZa9/DTTpOWLJG+/1666aZoyyeVPtPSi1J1o1933fT/Sege7kWxdXToYP+a17Hg3Ur6+T9Tfi/DHBRycy8QR9Dy//4vmvWibBC0RJ52v7j4TTUPI9PSTYOETMtoBQla+sm0jKLh7yZoWaqJeMLsHu712Awz09JvY7qpybmhmoRMyzC2VS5By1xxlX/iROlnP5Oeeiqe7ZsWtAxaHj/jUYdtypS2x/Pn+1uHXX2M+/tKkiBByyiZGLQ0sV65DVrmln3y5LbHuWOUR6XUmZZevqeoMi2tuuNbPZ/0TEur/fXII9JJJ0lffJHO5o1y++Uos1/8JAbZLWNK0HL2bPvX/P5ATj0qK0zEA2d+Aol2y3ndlhtkWkbLy74qvLn0k2kZRcPfa9DSb6A+zu7hbtYV5nr9HkNNTeE1huLK8osqaGniTW8xJnQP32ef9P584YV08NLLmGVhiPt7C/PHCCmaITq8yj1n+h0Dl6BlcEG6h0fJxKBluWRa5o4p17FjNOWy27ZXfjItvWwvjJ5dVgp/4M90FTdpTMswFG5r2TJp8OD047fekvbaS/ryS+v3RnWMl8v9X4hBS2O6h0fR9iiX7xuSyLREobACh1FlQDo1tjI3rmFspxItXSo9/XT+c14aOIXdOZKSaVldnczu4V6Dq6XoHl4skNjYGE1jyMv38e670pgx3n9d9rJMMYxpGZ7c4zvsQdzdiDsIVo5By9xzptducKmU9Prr7QMDGXF/X0liUqZlblmiPNf4zVw2sV75CVrmfp9OvSLCEuR7tTpXhRm09BvwmztXG44dm54c0UomszIjE7R024Z2K+7u4YXbWrSo7fHChdYTb4a5/XIURv02tXu4U31gKCKITEsU8tP92moZuwuj002un23lbueWW9yNicHF0Nppp7Wfwc9LQ9ztr9Jeg5ZBbwasAhm560xq93A3Sj17eDGlzLS0Wtf48dIBB6Qfjx0r7b+/9+3TPdxccezDuIMV5R609Jpp+cor0jHH2L8e9/eVJGRaVkbQ0q7spQha5jKte7ifexRJtUccob2mTFHr3LnSY4+1X6DwmFm1Kv1/Ybsg6d3Di63DqSxkWlqLoHt4WWdaoqxQQ5DPqZFjNzCy1QnM7mLk9Ktq0OxMt4P4Jv2iFZXCgKUUTVcap4aKVdZG0AG5o+ge7iVQ77WLdpg3gaWePbyYpibnmwar78pveaye+/3v2x7/5jftX/cbsPaqXLqHR8FvHZAIWkrBy2PCjUPuZ/CaaXnmme7XDWdBMi032sjdNvwc76UMWrq9HpdL9/BcpmdaRtU9vKUlXa/9dA9PpVT1w5i81Y8/br/+XJlMy8If2OPsHh5FpqWX/RnVeTrp939hBC1NzbR0anuU+5iWra3RTT5VRgxoncIoVo2ZxkbpRz+S+vRxnwnnpgHXv3/xbRcrH2NaRivIoOVhdQ8P2v0sitnDvQyJkPt8a6u3X5/32ivYLIFRzR7uJpPaSrHu4a+9Zj/GkddtWcntltWpU/vX/X73XtE93Nqzz0prry2deqq/9xO0LI9My1x+x7S0E/f3lSRBMi3dfG+nniqts076uA+7XH75DVqaWK+CZlqWekzLUmRaOm2jtTU9c/o220ibbSbNmNH+9WLcBB4K27SZoGXYmZZW3cPjnojH7etJbA+VQrGgpZd1/MCYTEun7uHlbNUqaaedpE02yZ+EEO0Y1jpF7KxORo89Jk2YkD8eSbH3FLtYffml9O9/ey9L2NmZcBZF93CnRl1cQcsou4d7bTTmLr/rrsGCCCZmWhZ772mn+Vt3Iavt5AYtrbJI6B7uTdjjDJ18cvoG7sknpZkzvb+foGXwfWDa2FFeg5bFyh/395UkbvaV3fW52HVu9uz0cb5qVfq498LE7uFkWvoT5Lv0k2np9H2uWSNdc4303XfWMxmHFbSMs3t4nJmWXl6ne7i1UmVauilD2Cp1Ip7bbpMmT5bmzZMGDoy7NEYjaIl8Vo0Zu2Blhp9My+XLi2/bjSSckHJNniydckrw9aRS0lVXSb/9rbRyZfD12Ql7/J+WlrYGmpVSBS1zP1d1dTjdw8MKWua+Xlg2N9uzW1dhOe69V/rf//V3sxVl0HLy5HDKUyxoaZVFQtDSP7/lHzo0PaPotGn5z2eyT7zIreOzZkm/+IV0333+yuVnm3Go9EzLW26RfvUrafHi9N9BghbIFyTTsth1xakdUEyU32E5jWlZyMSgpZty2Ak703LNmvbXoVwDB6bHwnbiZrgDu+7hSQxaesnIC7N7+PTp0llnSQ895LxcuckNWk6YIJ1/fn7PFB9tWGMyLSs1aJn7A4nbnmYViol4kM/qIlOsi4hV47RYg9VvFmXSu4dfcYX03HPB1/P009K116Yfd+wo3Xxz8HVa8bKv3Hw3xQKsVgFKP0HLurq2X7ytJuIJ2j3cy0W+8HkvQcuammCZT06ZlpJ0443SFlukb/q98HsMFeseLrnvDh+0e7jVea1UY1paZWMk4aa3UNDu4bNnp288JOnTT/Nf87O+3H04aJD0xhvSww9LfftK227rfX1etxmHcg9aOp0PPv1U+sMf0o8XLpReeKH4+uL+vpLETV2yuz4Xu27HkenvRjkFLd22SezKXorummF3Dy+2jmJBS6fzzfz50oEHOq8jzKBl0DpViu7hzc32+yzKTMsTT5Q+/jj9o+eRR0obb+y8vNv1mi43aLnbbtJdd0l//7s0bFj+627WYfd3sfVEda6LYkzLJPDa06+CGdY6hXFSKeux33J5ybTMHJxhBS2Tlp05dWo46xkxou1xkF8ap0yR3nnH/vsKMqal1Xvr653XEVamZW4jKoru4V7GtAzSPTxo0NLNJEDFbvS/+056/fX8crkd07JwOTeZln7G8Fy1Kl2Pi8kNYJNpGVzQoGXu+XDixPzX/DTect/zxhttjzMB0VWrpJdflpYt875uN9uMQ9gT8Zh2c+B0Pvj887bHw4e7W1/c31eSBAla+vnh2i0Tg5bl2D28FNekIEFLqyBHkEzr1auDjSEu+QtaZrKOC39gT0KmpdPnjTJo+fHHbY+//dZ52XJi1T3cazss6I/zcWRalvNEPGGPDV/GCFoin9UB4yfT0u6kGKQrgZWkZVr66fJoJYwby7lz04P/HnSQ9Mwz1suE3T08CUFL07qH213IvR4ffo7J5cvT42oefng6Y83LtqX2n7XY7OGS/0zLgw7K/9uqjLnHn9+gZRhBj3IMWoYtaNAyV6YennOOdPzx0s9+5r9cbrdZKmFnWppWD526h/fp0/45uof756cN5rd7uGn1LMPvjwAm1iu3QUu7spfiM4Wdaelle4WKZVq6YdJEPFZBy7AzLa16MmUECVp6qXteMoJNPe+4VSxo6WUdmbd7ScIo9loQldo9nKClawQtkS9p3cOTlmmZ2z01LH4/z623tjWe7GbrDbt7+IoV7teXEVbQMrc8uWUtDAyGPRFPnN3DW1raPo/ddp2+42efbfvOzj7b3XsKt58rzO7hxVhtp1j3cDd1LapMSxNver0I+7watHt4rkw9fOKJ9P+5WZhBxf29hR20jPvzFHIKWno9t0rmfT6TVUKmZbFMtErOtCx10NKrUncPd8P07uFWzwXhFLQsVs+cjhkv9YKgZfvXnSQx09KvJFzvCVq6RtAS+awuMmut5fwexrR0L8jg87lK1YWv1JmWVtz8cl0ot+HZ0JDuOrzBBtJPf9r+12fTMi3D7B4+fry00UbSYYfZ70enzxsky1Nqf0MbZvfwYvvFaju5NwVWQctzz23fTdnNer2y+i6S2FiJsrEVRaZlFOJuFIcdtDQt+OJ0Q1pY1hkziq8v7u/LZF5/FE6l4sm0DOtcc/HF0jrrSE891fac38w0E+tVEoKWbsphx0/bqNjs4XF2Dy9FpuWvfy2tt540alTx97oRVaZlVEHLINsxQRhByyRmWvq9DzLxvFyIoKVrTMSDfFaNmWIHvZ+gpdtte32Pn+2Ukp9MwziFHbQsVaZlbnZOY2Nb1+GXXpLefrt993CvE/FEOaal29nD3Zg7N/9/K07fsV2Wk9sxLa26hxfbv8VmCw6L3cyoxx0nzZxp/76oMi0rsbHi9JkJWroT9piWcX8eLwqvDU7HbUaSPl+peW2DOe1L04OWq1enJ7CQ0rNCDxiQflyJQUs/Q8eEJXcbXvdh2JmWq1cHn3zI9NnDJWnxYqlfv3ACU16Cll6STugebs0qaGn1uhNTMy2dvsdyDlp6vf+sYGRaIp+foOWrr7Z/rtIzLcePT8/I/N57bc81NTlf4P2K8vN4WbebQJ6fTEs/QUunX67mz28ftPQ6EY/bTEur54p9njC7h7vh9B0XBhDfeqv4e3IVflY33cOLZXZn+Mm0zGU37MWsWcHW6wZBy+Ki6B4ehbgbxeXePdyuPLffLl1ySf5zbq4Vpn0+k3gNWjodV6YHLVeutH6+UruHr1gh/e53+c+Xunt4GEFLL9srtGaNv/ZmLpPGtAzSFdzttnPLPHZs+r7nk0/atu+0TjItvYsg09JTzzG32/CD7uEogkxL5LM6GRVrjA0b1v65YicKrydJu2VMzbTca6/0/w880LY9PwE7O2Gc5NysI0imZeb9uQ2KUmVaOgUhW1qcg5Zhdg/3czwVdg8P2kW7GC9By75908u73bafTMuwxrQsxm1wtFBU3cOT0LgqFGW3FoKW7vgJWqZS9ud/04IvVvv3tdfaB1gkgpZhK1aXnPZ3lPUorExLK36DlibWKy+Zlldemf4hoPD5qOWWJYzu4UGyg+vr3SUWtLbat8v8ZFo2N6ffV9guCLr/3SSdOL3Xjdz9deCB6f8z9z2F6yg8X8QRtAzjHjJOUXQPJ2iJhCDTEs78XvSKjQtnty2nv62YmmlpxW3Q0ms2ZpSfJ4ygZa44Mi0Ly9DcnP9cYRdsv/XO7XOl7B7uhtPntWsM2r2nsKxWY1oGmT28pUUaM0Zatiz4fvF73DB7eBur46alJZ2Ru2RJ8fdH0T3866+lzz/Pf56gZb6wuuWVglV5/vMf62Wbm4MFLSqd154sXn6AK7YtL8I4V9qNL15OmZaFnDItCwOWkvmZln6CHE51Z9o0d5NlOrVJ/QQtJevM36i6h7t9rxteuod7CcqW6jxtUrtrwYJ0tqqbgGGQ2cOLZcAWY1LQcvFi6emnpcmTrV9PwvU+imBtmWJPIZ9VY8ZPY+zyy71tx27bfpYxlduA3VlnFV+mVOnkXvavm++rVJmWTg3hYpmWYXYPDxq0jLt7uF3Q0m1DwE/3cKcxLa+8UjrkEOmAA4qvJ6rgBd3D21jVzeuvT2fk7rtvsAajn/3x9dfStttKu+yS/3wlBi2d9l9cGXJ+eNm/ZFoG47V95WWoEy+vFRNV0NLtNdyKifXKS/dwK6ZPxGN1sx+kXfD11+6SBpy6gBO0bGOVMOD0up/tF1tPkPWWUmOjtOuu6WzVu+6yX66cMy29dvNvaZH22Sc9HvEOO0iTJrVfxsTzciG6h7tG0BL5rBozURz0cQYtg3RHCcJtwO7JJ6MthxdJzbR0CloWZuNkLhiZ/03rHh5n0NLuM8XVPfyGG9L/T5okLVzovJ5i5wq/x34Y5wyrOmBqY9qtTPmvvjr9/5Qp0vff+1+fn+vOkCHuj7mwrmtxN4rtJuJxKpfTOTXuz1PI6vu0OycStAzG6zmyWIDH6VoX5HsI4zu0ChIFOU+YWK+8dA+3YnqmpddgS7FtfP21u0xLp6ClnzEtJev6GMakaqUc07LYOrxkWgZNmHC7rCntrjFjpDlz0o9/8xv75cIIWrrJtAy7F4wbTvc6Vq/Nny9Nndr2d+4cEhmmfL9OCFq6RtAS+fwEWaLadtTdw3/3O2nDDaURI7yvw48wx7TMZUr38Kgm4vETOPeaaSm1/WofZtAy6d3DrcpauP+cWHUPL/Zet2NNFptlPHc7Cxakf8XOFWempduhBExXrLFcrNtL2A1juxvGSgpaZvap36AlmZaVy2sbzG5cyIyo6lkY52C3QSK35TTtuJHc76c4My2DBC397PMwMi1N7R5+7bXt32+3T7t3d15XFJmWhfsmrO7hQc4Hm20mnXxy/MGtsCahSnKmpVN70erzFh4zVnUxCdd7gpauEbREvkrJtFy0KD2Gz9y50nHHeV+HH366RttJ0kQ8uexm7CzGa7Zl7naLZVpmLpSZ/eHmM7sJ0Not57V7eJwT8Vjtd6dx4wrrVOFnddM93O1EPF66klx6aftxDuPMtPSTIWKiYueQIGP1+Lnu2G3PLvgehrgbxX6CllFlwEWBoGV8ggYto6pnUXUPDxK0NLFeJaF7eJCeT356LDi9Pneuuzaqqd3Dr7qq/fvtvsO113ZeV9CgpdW2C/eb07FVqu7hc+ZIzz4rvf66+3VEIcgPDKXOtDSlezhBy4pD0BL54gxaXnJJ/gD7bk6kfjMt7QZhj1KUmZbjx0u//a306afhrzvIsoXP+enqLWUbO1UffqidHnhA+uIL92WxyrTMfc6ue/icOelg14svOq/f63OmdQ/3mpHlJlvS7v1u3lssgzKj2H7J3Y7VxGB+z2thnA/dBr2TxE+mpRM/QUUvQUsyLd2tr9TcXOPpHh6NsDMt7erSSy+1n/3dbnIlK6XMtEzyRDzl3j3czz4vto2gQUs33cOtym11fxC0njt1D486aFk44aVkRvdwO7NnB19HKRTrHu5lHXZ/2z3n5rUgvLYXC+/jrYZ2SML1nqClay7vDlExrE5mpWqMzZsnHXOMtHSp1KOH/266UbzHC7v9FWbQsvAkt9de6f9HjJC++Sa87YSdaeklaLnddtJ//5t+/ENjp/aAA7SVpNQ776TriZuyuB3TsrB7+JlnSqNHS7femh47Zb31rNfv9JzV/vMyeYFT9/C4Mi3dzACeYTWmZbH3us209PL5rX7BNS3TMgmNq0LFfuEPcu3w8167Y8VqSAOClvnLZ8T9ebxM1lDIzdAVcX8+k3kNWhb78dfqGJ4/X/rpT9s/f8wx0vLlUrduzut0Uy433GZaVsKYlqlU+twZ97kg7kxLyV3QMmj38CjGtLRrk9qtw81x5kYmaFm4nTVriicthNU9PIyu5En50bhY0NJHpqUx3cO9jmlJpmXFIdMS+aK+mf7yy3Rw0mmdM2favxZWpmWUFyi7RovfLMNick/c334b7rqDNhysshzdys24K3hf1bJlzu8tlmlpFbQs7B4+enTbMl99Zb9+p+es9knuzdLy5dLHH+e/1+3s4aUIWlp9X07dw62WzRVm93AvNyemBS3LMdPSSrHzh9e6V4xT0LJwfeXaPdzrRDxR7Re/Cq+fxbrD5SLTMphSZFp++aX98m6znci0dKeUmZYtLdK4ce4msrEqk9ftZbbpVRhByyi6hy9Y0P65MHo6RT12d2b9hZ+poaH9tguHyDJhIh43ZSkFr93DQ5w93JhMS6/rLTxWybQsewQt4SzsTMv77pO22io9pqSdzEnGzYk092+3qeVRdXnP8DIZRBj8rtfNiTLO7uG5E7J4mfxF8jampZ/Zw4OMaZnJuG1pkXbbTdpzT+nOO63f4zSmZVh12E+mpd17io1pGXT28FxBMy3jnIjHayPRVMXOIaXOtHTqHh4kg89J3I3ioJmWXrrslUJhtgRjWsYniqClU8DH7XdjYtDSxHrlJdPSipfPdNFF0r77Sscf7/49hdsOI2gZNNO6FJmWVuU+//z2z/lt8+Y+Z/d5i11fowhannaa9XuDbL/Yekq5jlKwClpave5mHT8wJtPS63oLs+XJtCx7BC2Rz6oxE/ZBv3KldNtt9q87BS3tlpXcj4WXSkWX9SjZN8rD3I+lOsnF2T08N3jV3OztvcUyLXOfywQ6Mv+7+cxuL/JWz2V+bR4/Xvruu/Tj3/42v3y5ZbP7rk0MWhZ7v5v3BhkHMVexHzS8Nsq9vs/LOsNab5xM6B7uFLSslEzLzPfg9Plyj8vCYzTujDEvM8wWImgZTCkyLZ2+o1IGLa26hweZsCsJ9SrKoOVdd6X/f+01/+3GMLqHe9melbDHtAxyXQza08np/i1ILwir9RR+pjVrim8jrO7hZFp6W4/fexwv2/DDqVx+u4cnoV0d1j1PBWBPIV8pgpaS/eDNkrdMy++/l7beOt1QMjVo6SbzxVRhjKmTy8t+L+we7lRnnLbrtXu4m+6IQbqHZzItC9e5//7SfvtJixe3PefUPbwUQUu7m06/XebcdA+3e/3ii90tV/j6iy9K77/f/nW/GTRBG0GmNpr9KNZYXrNG6tdP+tGPrIf9KGX3cDIt2zgFLeP+PAQtw/Pxx+mxoc8+293ybrsNZ/gZ09Ip4OP1xj0Iuoe3aW21Pnf6PVaKDd9jpxSZlmHUHS/dw60+k9u64qWsdvsirEzL886THn20/XJOmZZBsl6j6h7upywmiaB7eJXXH9HjCFpaoXt4xSFoiXxhZ8vYcVqnl6CllJ545ogj3ActpWiDlnaNljD3Y6lOckEbDkHGtCzMtHTT7caqLG67hxdOxON2/XbbsXsuE7Qs7LL83nvp4Npll7U9F/eYlkG7h/vJtLTaZ999J/39787vK5TZTv/+zq8XU1ieoI0gu+0m4RfhQsXOQ3fcIY0aJX3yifSrX3lbt5/97CXTshyClk7nHL/dw+MOvri56WdMS3cOOUSaMkV68EHpww+LL1+KTEs/3cO9lssNtxPxJDnTspTdw3M5Df9UyLTu4W546R5utT239x9Rdg/3mmnZtat0xhn2yxWuL2impZegWRhZmUlpfxULWroRVRs2KK+ZlnQPrzgELZGvVJmWbroFeD0xWo1bZ6XUmZaZhlUSTp6FgnZPCat7uNdMy9ztes20bG1NBxDdrj/Da/dwuyB77j5KevdwP7OHZ15ftUr6y1+kxx/Pzz4tXM6vuLqHJ73RbMeq/J9/3vZ47Fhv6wsz07K1Nbpu0HGe151u2p3Kdccd0j/+EW0Gql9BgstuJgmL+/OVUu7EF24nucmVhKDle+9J//d/0owZ6Uywm292NxkMmZZtws609Bu0NKF7uBteMi2DDDkQNGgZZqZlse26GdPSSxmc3mvXuyCIuK8LpeweHjTTMqp95fV7JNOy4nhITUNFsGrkmJ5pmWFq93A3mS9eJWVMyyDdwwszLcPqHl54Y5vJzsrs0+bmdFdtu/VZ/W33nJdMSyulmIjHbUZW7nNuGxd+Zg/PlOf229M3o1I6wFIoaEM1ru7hfjMfTFSssZx7nrc6Z4XdPdzuWLEaE7dcMy3dBC0ffDD9f7du0gEH5L8Wd/DFzfEWJNMy6T8ORMlrRmPY3cO9Bi1bWtqu1TfckL+NzLXDTm7ZM5P+BQlamnj+jivT0upHRjulzrSMOmjpZmKzJI5pWezH87DHtPTyY3oYmZYmHr9WwghauvmsSeweTqZl2SPTEs6iyrSMImhpSqalXfeQoA2QXEkJWgbJtCw2puVnn7m7ybHKtMx9rrB7uFUGhpvB1d0GLT/+OP2/myB7Kca0tLN0qfTVV+2fd5MtmWGVNeU2aHnFFW3PPfVU++WC3pyQaRmcl6ClV2FmWjY3t1+fn8wzK0nMtMy4447yy7QsJu7PZ7Kwu4dbfR9O73EbYMn8bZdRed11zuWS8ttpmR9Iy717uN3zqVTlZFqWunt4nJmWTt3D/WZa3n+/9XajGtNy+nRp4cL819y0x4ut10tZSsHt9q2CllavNzRIkya5u1fxeq9tavdwMi3LHkFLOIuje3jUmR5xZVp6+VylyHZxc6IM2hgofC7MMS133VX65S+Ll6VYpmVh93ArhfXF7UXe6rk33pCef97d/o+re/iKFdKWW0oPP9z+tSBjWroJWmZe79q17TmrQHLQoKRpmZZJD1paCdIFLcxMy6am9nVxn33SN0RBJTloWVNTfkFLuof7F3bQ0qp+OmVnes20tDv/uLm25rbTMj8gBglaxp2hbCUJ3cP9bs/vdbTU3cOtyul0/7HVVm2PTewe/qtfSQ891H67frqHO73e2iqNGydtsYW02WbS/Pltr7nJZvUq7uuC13FOnTItUynp4IOlnXeWbrrJfh2Zt3vtHm5K0JJMy4pD0BL5rBobSeke7uWXKqdGR1BhjGkZJNMyzAtKnJmWbrqHDx1q/d7c7ba25mfhFhvT0m7GbLv1Z7jNtJSks85y9z3FNXv4vfdKS5ZYL++le7jV2ENugwpdurQ9l+lSb7WcX34zLaPabhKDlrmsvtti145S/XjV1GS9vnPOCb5u04KWXjL7a2rMm4gnyPHmpuxJuIkxRRRBS6f32H1/boNvGV6Dlpn2QblnWpZT93C/56kwrrNRZlp27972OM7u4U7WXjt/G1I03cNPPjn9/6pV+cM/uEkicFqv17KUgtfsW6eJeBYskD74IP14yJD26zC1e7jX9bqZiCcJ7WqClq4RtESeqqlT858YNEi6+urwNxR30NJvpuX//m86w2/cOPtlwugeHuTGMcyLbxiNplylmoinsCGcG7QsNnu43eQzdut3es5u/61e7T6o4HUsQK+s1uV0Y+llIh63mZa33Za/jCR17tz23PLl7d/jdUwmr69nhD3oexQ3EaYo3FfFxrQMO2hp92OUVaallJ7ZPCjTgpZ2N5FWqquTmWnJ7OHRcBPMOv98abfd0sOz+BnT0unaYvf9FWYGFavjdhnXdtvKLO/mB0s7cQf7rSQh09Jv93C3Ae5CYRz/UY5pmTtsUJTdw6dOTWfivfOO9etO2849vqLsHp6bXZl7XxWke7jT9uIUVtAylfKeRZuE7uFWkj4Rz003STvtJL3+etwlSQwm4kFWXX29qvx26/DK6aSaec3riTHqoOX330s33ph+vO++9uULYyKeIA3g5mb343sWE/QXzMLP7OVz5TberLqHuy1La2t6XZn3F45paTURT6Ewu4dL6a7XbvZtdbX1DVjUQUunuuplTEurgIjVe7fcsv22c7uHL13a/j1BZ7+Mq3t4OWVaFt7oeu22Vax7mFd253W7TMswmBq0dPmjSFVUs6r75eZHAoKW0Sh2Mzt+vHTPPenHP/2p9KMfOa/Pa/dwl0HLonXca6ZlZvlyy7QsVKpMS6vrtZ2wMy1N6x7uNdPSb9DS7lrgtE8nTZIOOshd2zX3mHITtAyaadnaaj3urBSse7ipmZZhdg/32MOlysu9S7HXgvD6HbjJtIz7e7XT0CBdfnn68RdfxFuWBCHTElldwpqYwA2nE0nm5O31ROpl7KFMw9sLtwHdUoxp6dQoD/Om05Tu4UEzLQsDoF67h7tpJHkJ/m2xRbBMyzAvxF4bIFdfLU2YYP1aYVndjk+X+/1YdQ+3CliXqnt4YSZCVJmWSQxa5rIadiNIYPnuu72fy7xmWhYrgxtJDlqamGkZpHs4QUt7bup5sWDWzJltj6dNC797uN33Z/fDkd136SbTMvdc4bS+pAUtp0+Xrr/eehKOqIKWVpmbboWdafnJJ9bPP/+89Pe/20/e5IXTecZNm8fp/VZBy9Wr02V/8UX793ntHl5MGJmWQbuH5ypswzst60fcx2+QTMtcTzzhvRdSEoKWVp+38L4gSZmWXpJwkEWmJbK6zJlTuo05naD9Bi3dnpyGDZPeesvdsrncNIQl+19aS5Vp6fa9brIRggYtw+oebjempZ3cchd2D7cb09JLF7Gg3cPXW8/dhT+uoKVT2T76KP3PDbcBEaugZW6mpZWg+8DN++vrpRNPzH+OTMs2hb/wFwYNc79/r/X444+lRx9Nj//qlp9My8Lzg1flFrQ0LdPSa9CyFN1Dy1Wxm9nCfVeqoGUUmZa523LqDZO0iXiOOEL6+mvpiiukzz/Pf82pe7gVt8dKkGO2UCrl7vuz298nnJB+Lbe9PmlS++t4EE6Zlm7Op24zLTP78aabpGuuST/+/PN0l9JCXruHF+N0Hs39fkoVtFxrrbbH5ZhpGVb38I8+kl57zXkdpmZauq1zGYX32knKtGQcS1/ItERWndUMvVFxM5ZZVN3D/QQsJfdBy1J0D/cy03UQYYypkysJmZZ+u4evXu2+8V7YRd2O3ezhcQYtvXAa4zBXbtAos+3cTEsrXn9Ntnq92DoKx/h1s91igt4g5lq1Spo1K1h5gigWtAwyEY8kXXedt/L4ybQMer40LWjp5XpjNRFP3I38ws/07bfu30umZbgK91XhBCvFJjQ0OWiZW3anY8bvMCJx+frrtsdeMi2DtDPCnBilcJvTplnXMzdDTGU8+6z78rjhVO/dtAG9dg/PBCyldMaoFdMyLdesKV4PnPZD4XsLkxiclnViatDSazvEaSKev/3N+b1uM63dvj8sXr+DwuOwWNDSpEBhEpMUDEDQElk1pUxXjiLTMsgv3W7HF3Qj7jEtTeoeXvicl7IVNlKCjGnplGlZOKalm+7hdvWlXz/75Q49tO2x2xm4a2qs612YDSynbC2vChsFbrO4rLILcifisRJG0PKUU5yXiWISpLAyLVevlrbZRtp0U+nVV4OVya9iY1oGHXfUK6egpV1Zgp4vTQtaesm0rKkxL9OysNyvvir985/u3kvQMphiN7OFQUs/mZalGNMyzO7hbsV93FgpVffwIBOjOJXlwQfTQ+nsvbe3tmRhubt1c18eN7x0Dw97TEu7uh0kaGn1eQq3bTemZWY5P5mWXnrOhTWmpdvtlZrXTMtche2whQs9rcOYTEsvmbdSsruHE7T0haAlsowLWloJo3u41/Jk+O0ebvdLZNDyBH1vKbqHB8m0zG28OWVaFtuuVaal1a9vTt+v227Or78urVhhvVxh5miQ7uFh3iCFGbQstm4vQcsgv9K70dpaPAMjiizUsMa0fPRRafbs9PqOOipYmcIQRaalV2Raeg9aLl+e/1zcjXyrz3TOOfl/MxFPNIoFswrH9S42DnpcY1qG2T3cLRPrldugZWtruJmWQdqNue89++z0/xMnSp9+mr9cnEHLoJmWTuep3Hai1XvthjIJ0j3cauIkr5mWVkNHBB0mIJdT9/BKyrQs1j1cKh60tDufFnvO7v1h8RooLbzXtpokNO7v1Y6p5TIcY1oiq8ZL99ugnA5Yu0zLww6T3njD3zqLaW7OD5xY8Ztp6WdMy2LLmtg93M2FL4oxLa3GpHPKtCzWPdyKl+4ohQHTjMKgZZDu4WF+x2Guq9CFF+b/7SVoWaxcQbP4/H7uqDItvZ6/nDKWSqVY9/BiXXOCZssWsusq7xS0rORMy+pqVc2bV3ydpRRk+wQtg/EatCw2Dnrm+5g5Uxo0KJ0153TecjsjdNiZlpUetAya/R9l9/AMN7Ny260jzqCl10xLq6FyckWRablokdSrV/v32nHTPXz16uL3VE4Kt89EPGlWQctChftnwABpyZL0JD29erk7/pOYaSml7xM7dbJ+n0ndw+OubwlF0BJZxmVaFp6knAKWxdZZjJubHbqHOwuSaVlb2/41t0HLlpbiQUs3Y1o6fb9eftnNfS33ceHnCZJpGXXQMoxGidUsnnZ1c4MN2h67zUwOGvDyG/QzJdPSBFF3Dw9rnzh1Dw96LBWuN5UqXePYaUxLt70HCgNPcTem3WyfTMvSKNY9vJhMHTznHOnNN9P/nLjtHl6sTeV3TEtT2l1hcRuMDJppGSTzrZDbMnsZ07LYUDNeOZ1n3GSdmtY93Oq4DiNoWWwyRSeF5c5dfxQT8cTd/gprIh4rTz+d/v+Pf0wPuVCwvyzfbVrQ0uo1qx8PCoOWpo5pSTvEF7qHI6va9KBlMUFOpG4uGG7XH3fQMsyAVtDsUKeGRy6rRmVhZqJd/SwWdGtokL75pu3vpqZoMy0zr02enJ71MSPMTMswb5DCDFrmlnXJkvav55a7a1dp//2lG26QNtyw/baL1eOgQUs3E49F0XXe1Eazk/p66a67pHfftV/GKtMyyOzhbng5J5cq09KqTLNmSbfdZj2xUxAhdA+vmju3+DpLKWjgqFidqNSbBTfHitdMy2Iy3+V//uNuea9jWtrVlcy5prFReuAB6zF/K6F7uJtzk9PzfruHf/SRdMcd1t2Oi23bbptu25JO6wiLl0zLv/61fQ+AIEHLKLqHWx3XTucLN7OHr1oVbvfwTB1bulS69VbnZb2sNyPu4zfM7uF2Ro3KX0eGXcC7WBnC5jVoaXVPaDc8m2lMLZfhyLREVq3p3cOj5OaC4bY8dt1YwhzT0qksJmVauu0e3rVr+7HVCrMj7eqn164iheOeFE7EY/eeXG4urv37S1991fa83zEtrX5ZT0KmZffu7Z/LrZt77tmWeeMn66UUQUurfRO0sZHETMsrrpBuvz39eP58ab312i9jFbSMekxLL0HLqDIt3QQGjj02PSbbtde6u5F3K4Tu4SoMWsbdmKZ7eHyKBS39ZlpWV7vb72GNaZm5Zv7jH9Kll6Yff/GFtMMObctUwkQ8Vlnguf8XPl/Ib6blzJnSRRdJH3yQ7pLqxG9ZvAQtwz7mvUzE89BD0qRJ6X1ht0yuYmNa2mVa2l0L/AYtC3mdiCfsMS0z+/w3v5Fefjn/tTC+37ivC1FmWmZkMhBNzbR0O+xWhlXQ0usQRXExub1vMDItkVXSTMtiQcvVq703kIMI82anFJmWTusKs/Ec9BdMt93Dc9P5M3IH3naaiMdP0NJr93Av28js/9yApdS+e7jLTKhEZVrmKpZ5a9cIdjumZSm6h1tlVESVaRl3o9lJJmApSe+80/a4WPfwoN9RWN3H4860zEwisWxZsG0VCiPTcsKE4ussJbqHF7dokf310M6CBc4ZYlLxAJLdOdPu+8jUpY4di5dPCm/28Ex5MgFLqX3wrBLGtHQbtFywwPr9fjMtM4YNK/7eKDIt3U4A6KRDB/vXvGRaStKHH+b/7XSeCntMSzc/zlqdS5zOBW67h4d5PGWyVR9/vP2yZFq6e2/mPiuJmZZW27SKWXz/fX5djPt7tWNquQxH0BJZJR3T0snixdLmm0uPPVa6bYaZaRl30NLtxa8Us4fbjUNUuO3a2vY3Nm7HtAwraBlW93C7785PpmUpJuIpdiPrhVW3oVy5+ya34eumEey0LivF6q7fTMtKH9PSqct32N3Dw+rqG3emZVSCBi2fe05V8+fnPxd3Y5pMS2fvvJMeTmPrrb2Ny/vrX0vbb28/zIoVtz0lcn9gzJX5Lq1+lLQSdtDS7bYqPWh5/fXWs7oHDVr64fb6GHWmpdN4jE5tJjf7olRjWq5ZI/3lL21/P/qotO227soTxpiWQa6Fhe+9/377e0IyLd29N3OPVZhp6ebeze1rQeSW62c/s39Nsh9ia7/9pH33tb5GmJRpGXd9SyiClsgq6ezhTm66Kd0FsZTCvNmxG1MjiZmWQYOWue9vbW1bJjeAJ6UbaoW/bOc23ryMaRlF0NLLQPN2AclKm4jHqu7YBbGsgp1BMy3DCFqWMtMyKUFLuxs207uHx5lpGRWniXjc7NtiPyzEgaCls6OPTl8LZ85M38h78c030pNP2r9eLNPS7tjv0cP6+agyLTOKdQ+3k0pZZ+OU20Q8boOWdvz2LvLCb/dwp+B7GEFLp8l7vHQP97qM3+7hVsu+917+3717Wx+rbtqAxXrGhD2mpdV7Bw2yXrYcMi3DnD3cTqZOu9lfcQcte/a0f01yPud89JE0cWL795nUxo67viUUQUtkGZNpWV9f+m36ybS8++78v7/9VjrqqPSv1rmiGNPSxO7hxboY5O7j2oLhdK0yLf2OaVnsYlAYtMw0wLx0Dy+2/4sFLd1OxBNH0HLqVOnmm4Ovt1hApPBzZf52ewMZNGgZcffwqnff1f7/93+qeughd+VKSiPGLvBsFbQMK1My6PujyrRcsyY90UKuuIOWQcfni7Mezp8vDRjg//1ufgxKynFmJ/fHlhUrvL/faoK0jGLdBu1uFNdaS/rkE+nGG9PjtmbE3T3c7jm783qQ4JuJ9apUQcsg51C/3cOd7hNaWqTPPpMOPzx9fvbz3RT+sF64fj+vuVkmzEzLwmVXr7aeyMdrpqWbiXiCdg+3yvy1E8axF3dAK8bu4VUmdA8fP156/vm2vwvHxPfyo4WUbptJ+WWN+zvOZeL1IgEIWiLLmEzLKGy2mfPrfjI0Lrggv+H0s59Zz1LpJ9MySEAmrtnDi2VaOgUta2ryMy2rqqLNtLTqMhBm93Cr13MDkF66h1s1UsPs0l14o3/iieGs12vQMvM5M2UxYfbwABPx1B5yiHp98YVqf/3r/M+d9ExLL0HLYoKOWeklaBlFpuV117V/zpSgpd/PFWfG2AUXBHu/m7GCK/1mwelmz2+mZW2ttPvu0uWXp7uuZ4TVPdwum9lLpmXuucruvB7kumpipqVdu6UcMi2dAvatrdIhh0ivvy5ddll6nDuvCtuoTmXJ5aYeBBnT0svs4YX3dD16hBO0LEX3cC9DX1R6pmXAiXg8i6KNs++++X9bZQTnbrfYOcfqvtukNnbc9S2hCFoiy5hMyygU6y5k1YiYM0e69950NyzJ+oSX+2tgZrKFQknuHv7KK+6XLRa0tJtJW2qfaVlVld+4am62b+iZ1j28tdX+V+9MQzjoRDx+Mmyc5Jbls8/8r6fYmJZO48tkjtGwuofPnSvdc4/9606N4sy6w+oenrstt2N2mcopsODUkPQzpmWu2bPT5+PZs9ue89I9fOxY69eC/Mjz6KPtnwsaiPWi3DItn33W3XJ2ZWxu9n/tXLAgXb+mTXNXhqQKMqal3fGde63OfWxSpmWuKDItM2XKtBszE4eE5b//TQ8H4GUyr3LKtCxczinTsrU1fyLP3GuGW05By6RkWhYe6wccYP3+IEFLux/JgnYPd/OjcmEZgiwbdxDJ7X1MkKBlJjHEzQ8Fxe5xwlb4+bt1a79MbpmKXccy9cfUoKVJZUkQgpbIKutMSz9By+OPl847TzrmmPTfVidqL5PZlCpoGWam5ZNPptP23Sh24cv9Ja3YmJZWmZZuu3cWuxgUZhb6mT28WNDYrq5kbujcZlraBS2XLy/+Xi/CrDMZfjMt3XYPL/b6yy9L559v/3qxbFkpmqBluWZa+slU8nJOPOqo/POxl/evWmU//l+QH3kyP2jlKmX35KBjWlqJ++bNjSiClqeckq5f++wTrGymc2rnBcm0zChl0NLuu/YTtAyaaZmpV8cck65HRx/tf12FmpulnXeWzj3X+ZpWKAlBS7fb9No9PJefa6vf7uFBJ+IJc0zL3Pp83XXpY9Mq0zKKMS2Ddg/30sYN45oV93XP64z3foKWmXUWfFZjJuLJVdg9XMovd7GgZeb8YGrQMu76llAELZFVTaZlvo8/Tv//+efp/4tlEtpJ8piWknTrre6Wc8qsa2lpG2NEsu4enttYs8q0dBu09DqmZRTdw+0am5nPtHCh++7h5Rq0LDwmvWZaRtkdL7Nuq6wWPw2f3KyBch3TsrXVez3ykpWYOQ/nZrSH0QgNu+7HHbQMmmkZZzdXtzdfUQQt33wz/b/XSQCdxog0kd/u4U6ZiHaZlpljq9SZln67hwc5F2TKkpkAInO+CsP8+W1lGzbM/fvKeSKe3N4mhbPX2w0n4IWfoOXSpfFlWhbbbubzhJ1pafcjWdCg5dtvu1/WzfebSqW/H7tlo2gDe+EmaGl13+JF5twfNNOyFME/q+7hQYOWUnyByxUrpO++Sz9essTM4UQSgKAlsugeXkSxIEyx95nWPdztRc/tck4XvsLsDquJeHK/o9yu1JK3oKXXMS0z2w1z9vBi3cNnz3aXMVFTY113kxq0tAt45f7tNtMyyiBfS0u6O96vf93+tUrPtMw9FrxkWvrpHl6KAKDfuu+3m3+YjdVy6x5e7Dqd4RS0LOWYlldemZ7l9KKLwlunF0FuXK043cw61duou4cXfmfF2lR+JuIJK9MyCk5dlZ3YfWcmZVq67R7ulGlZ2JXUa6CiMPuwqir/XLTvvtKIEc5lfOQRqVcv6+z7Qk77q1jQ0suYlrkygd1SjWnZ3OxtKIpCXsYhdVNPf/rT9PfzzTfWr8cdRCqsE16Clm6vA5nvoxwyLYudqzM/apgQtPzsM6lPH2nLLdPf1brrhjd3QIUhaIm0VEq1dA93ZnWyMzFoGXYAKkjQMlPO3CxLybp7eG5jqjDTMszu4XaZll66h/sJWhZ+ptwxPu3U1Vnvfy/jWrkR1sQ+YYxpmdm3Qce0DKKlRfrFL6xfc9PoKSy7m0zLpAQt/Y5pafeeIMLYZ35vVuwy7JIetExypqWb+hfmeSMzEdMdd4S3Ti/81H8v7Ty3Ex8U6x7udiIet0E2P5mWuaIIWkZ5/rYLVBUq3B9JzLR0+kEiV26mZWHQ0mv38MJMzcIfi1Mp6X/+x379kjR4sPtzp9tMSy/nqmLLes20dOJm9nDJ27iUQRT7fufNk/797+Dd+qMUJNPSa9AyCZmWVkFLL2Na2mVaxvGj7Asv5B8LqZT0xRelL0cZIGiJtHIOWEreg5Zuu4J7ydA0rXu42wtPkKDlhAnSccdJd96Z/7xV0LKwkeg30zKK7uGFjXI/Y1oWZo+60a1bsrqHF3YnLBTmmJZRNj6am6UZM9xtN5VKz5p7wgltXUsLx9sqbLC4Wa9fH30kHXus9Pjj4ayvkFPQ0utnCNr4jTPTsvCHmIykdw+PM9MyaNDSTTvGzedLyg8IfvjNtHQKTOUG1QrHoi58zonL7uFVM2emx3e0+yzFMi3txvAzNdPSbX0sFvgwcUxLt93DC7cRZqZlYXu0cCzx1lbrYLxfQbqH+x1eJvMZ/Y5pmcvNRDxS6YKWxT570C77pVCKoOVrr6XHbl6wwH69Ts+5eS0sQce0jDLTcvz4dBvbaiJGK0uXelt/Obc/AvLZ5wBlJ+zZiE1TLGhZeIFwOwGHm/EqbQY/liRtt126G2qhIN0mTQpa/u536f9zu9ZI1mNa5jamCoOWTpmWXn9VjyvTMndMS7e6dClNpmVYQcvcz11sOIWgs4dHPaZlYfZFRuF3P2mSdNNN6cezZ0sffNA+aFnK2cP33jv9/8iR0sCB3utcMU6BBa/fSdDu4XFmWtoFyOLOtPST2V9snaXitnu43T4OK2hZGKTwu62olbJ7uJ+gZeY9QYNfVt/3/ffbB0Ximognqmwtt/svrkzLUkzEE2XQ0k2mZZhBy0yW/lprtT8eiwUt/f7oGbR7uNeJeCRzMi3dXFfiDlq66R5ux8t14Jln2sZWzLw96UHLrl3bt7kzf7v9UcSLvfZK/z9ypDRggP29QobX+zU37Y8KRaYlJElV334bdxGiVeykXnjBKMyiaW11Dlo6Zb5Z3UTusou0337SLbdYvydIllljo/TSS9K4cf7XkSto9ouVwn1Z2D28sJEY9piWucu4GdPSyzYee8y663dh9/BiOnZM75ekZloGDVrGPaal3UD8hd997hhWH36Yfr3wRyA3mZZeG1Nulo+iIZ57Y1/4fTttz8+YlsV+FIoz09Jv0DLMemtV9vHjpeef9zSeWKrYsA6lYkqmpZtlFi0qvoyJ/M4e7rZ7eNeubY8zN45uz0PNzdL776e7cuZ+B3bH1CuvWD/vt3t40Il4ogpkuz0mrcYVzOU1CzuO7uF233XhZwuze7hVpmVhYC637RbkHPnvf7eNq7jXXu3PeVFnWkY1EY/JQUs315Wnn26bfDVXfb30xBPtAn2h+//2zjtciiJ928/MnMQ55JyTCAiCCCoiIgZWEXPOGHFNaw4f7iq6urI/dXVNa9g1rWnXuG7ACGICUVAUxSzBACggSDxp+vuj6Jnqmqrqqg4TDu99Xec6Mz0dqrurKzz9BvH6LV6cu05YS0uX77/3fC1J0ZJvc/g+x0VlaRn1+MZknGUrWhZaQC9iSLQkGF9+WegSxIute/imTd7vYvIWcTtb0fKNN4C332ZB/GWEEWwef5wFnR41CtCJ0fmwtFQhe7uscw+PMqal48gTwkSViOfOO4Fdd81dbuse7g7ESykRj42lZdjs4cUiWlZXe79//nlhLS154hj88PdFFC1190T2fPmds9tOqCbFUdSBoNcoqHt4lPdE9ozceScL8v7II8a7SfN1vRQGzHGLlibXYPVq/3WKERtLS9PEB7ygw2d9dSdrps/pp5+yl7kHHww89ZS8HDyq/jSIe3gUMS2LTbRUiXdRi5b5SMSTT0vLZDLXPZwfrwRpI92XmQcfnF12wAHypJT8cUXicA+PS7QUx0FxEdXLy9GjgWXLvMsvuww48UTmwRJn3yjW7zFj9IJ+ECt7F9n8wcYiMR+ipcx6UWVpWVOTu26+soeb1D0SLSODREsCAJD46qvslzvvzHachx9emAJFja1oKU5IGxr0lpa6RknWqbvlUZUrjGj57LPZz3fcEWwfPPkQLUX3cPHNdpQxLcXjB3EPDzJIsnUPd98e5tPSkhfXeCorzfYTxj28mLKHNzSYu4eL5fjuu9zBOp+0Je6Yljz5Fi2jdg/3Ey2jGICWsqWlTmQRQ3JoSNskf1C1EVEQNnu4+LLRZlvbdXSWlvX10SU3ixqbjL5BLC3DiJavv579fPLJ8nLwqF4syeoRf0/icg9XvcgIS9Tu4abtdKmIlqJoIbbNpoKeSxzu4el0rrXescfqRcs43MNlz4YsPJiuHzNNxJOvEBpR9bm1tcADD3iX3XMP+79yZTZmeRyIVqmbNukFtzCWljIx2WYslQ/RMplkor7quEFFy6jH2SZtge18rZDeLkUOiZYEACDBW1rusw/rXL/6ir31bgr4iUV+oqXK0tJEtJTFtPRzSY5KsNFNArdWS0vx+CaWlrpjmF4fW/fwfIuW//sf0L69/Pd8iJbFlj1cNSH2GwStX587CbjkEpbBUra+SxQDQb9Ja1BUVko2lpYyTEVLsb0IG7eRp6lZWgagkRfodeU79ligTRvmLhcHcYQiEYkqrIJKtPz+e6BnT6B37+wzX0zYuIdHZWkZVORRlUt2XB5ZPfrDH4ABA1jfGZdoubVaWubDPVyVPbxZs1zhb/Ro73e/+pePRDzptLcfO/hgoE8fe9EyDkvLBx4A/vY377IoLC3z9eLG79xt+gvdiy+bFz42fPghi48oogtzEEa0lGFjaZkPUS2ZZAY4HTvKjyvGtBSJMxEPj0lbQJaWkUGiJQEga2npJJNA375A9+7ANtuYixXFTlhLSzEOoovbuOhit8gm2O7AIQ5LS55SEi3FwVRcMS0B7+QirHu4qRCZTJpbEgFZl6d8JeI58ED1gM20HdgaY1qK5Vy/Xv4m+09/km+v2m8QxONGdY1kyTXE/cdhadnQIBcT3ONs7ZaWEYmWHvdwVfl++onF/aqrY+5ycZAP0TIqS0uVe/hvfgMsX86Scl12mV3Z8kHc7uF8LDJbS0vVsW1f0qnq0aJFTKCJK3t4KYiWNvciH5aWpscUz8Udq1RX28esF7FNxBOkPjc2ep+9bbZh/2VJKXXHMb0+IrqYlgAwaZL3u2kiHp31br5ES5OQUKboPAniEi0nTpQvNzWWiEK0tBH38mVpWVHhDbWl6o9klpbufYxbtDRp+0i0jAwSLQkAQPrII/HdmDFwJkzwduCiWPHII8CVV6o7vjvvBDp3jq+gQYnCPVw2WHC30w1iZKJlMVhaRu0ebjOQk7mHi2XlB3NRi5b88f1c9f2OYSpEJpN218h9e5iPmJZ+g8uqKrP9+Fla8suKPXu4qWgpnue6dXLR0r1ncVpaioOjqK4Rfy2CuocHiWkJyF1tZdbrQSllS0vTSeFFFwEXX6z8OS1atcuIa8LGE9Y9PKptw1ha8nGkv/3WrEz5JA7Rkq8/5eXM+g2QW1qefjpwxRX+5eSPrYq5roqZp6tHdXXxJeKJyz3ctG8olGgZpaWl6pjnnOP1YHDvlUmccL/7apKIJ2xMy8ZG73Vy51ky0dLtK6O0tNRlD3fhj6ezvDO1tPzpJ32ZoiJKS0veAOX++72/xfV8f/SRfHmxWlrmQ7SUGZOoLC1loqVqbh61sQOJlnmFREsCAJC+7DLMu+QSNPLxEIFc0fKEE5ibDe8CxLPnnsCtt8ZSxlBEkYhHZ2lpIlrmK6YlT1OxtLRxDze5NjJLS9210sVIsrG0tOkwdZaW+U7Ek0/3cFNLy7hFy6AxLVWWln375m4fddbmuERL8QWCS9zu4QB79sT2wi1DKVha+lnmhsG07P37M0vfLl2kPzupFPOyAAobTymOvkYkKtGSj1Or2r+NZX2+sBGf+eugq2tiH+iOD2WWlrfcoqyHHvh7rBItVf2grh717BmPe3gxJOLxCw9SjJaWNmLJNdfkHrOszL/dCOIersseHlS05J8995iiaMknAYoypqXOPdyFD2chHqdPH28ZxeMWUmiJ0rvBfRm1YgVwxhne30xiJgdBJbxHEZbKlGIVLWVWvYC/e7jblhfa0rKuzl7sppiWSopwREUUFeLEXUyWIWIbty9f+E0ennzS6xZgG9NS18gEiWkZ1ZvDfFpaRhnT0l3mErWlJX+v3TqusqwDcgNwB7G0TCSCWVrKrn/Ugye/jjcqS0td9nD3PH/4AXjxRf8JYJwde5hEPOvXyye/rgitEryL2dKSfxafeIJl9l2zxs49XFaPTe6hzDLKxMLdlLgtLeN8028qsrjPmqJOp/lJeiEnn7q+pq4OeP55YMmS4nAPN8loL+sb1qwBnnkm+hAfPO+9B7zxhvw33QTK1NJSFB3FSbdOtEwm5ZNMHSrRUnUPdPUomYwne7jM0jKqCXJU7uGqZWGPm49EPADw6KPZz+55xGVp6RfTcsMG9hybWhOKoqXO0lKM780T1NLSzz0cUD9nnTsDp5yS/S4TLQsptEQpWn75Jbuv77+f+5s77v7pJ+Dpp+UJjIKgmjPn09Ky2NzDXWR1DfAXLd1nXgzdlu+YlkH6ebK0VEKiJaFHZWGly9pYiqLl//7HXOhcTLOHh3UP31otLcXzE7OHu8v49aMULXlLOLeO66wJV6zwXvOg7uE2nZFOtIwa20G9Cr+Ylibu4QCw//7RuvzYEiam5bp1+smiKh5qHKJlVNeIn1ht3gwcfTRw3HF27uEyTOPPlnJMSz/rpzCYlt2tZwrR0uEnynGGL/BD15ZOnQoceigwcmQ4N72oLC1Vkzw/0fLII9nfccf5H8MPWd/w8cfALrsAY8fKt9G98DIVLU86ybueytJy3brcdiGZVHvqqNgSc90Yv5e1+UrEE1X7G1S0lI2Nis09XETXzvDtl3tuosAow+95dsMZuIjxx8WYlo2NwHnnsed4/Hj9vvltTEVLnXFInO7hvGjJ34eXXvJuZ5o9PF9EOVb86CN2Xw85JPc319jhoIOAo44Czj3XfL86wlpaNkX3cBeVaOkX09Kds8cV550/jg6VR4YOEi2VkGhJ6FEJOU8+KV9eqpaWAHDffdnPUVpaiqIlX5a4Y1rqOrOoLS3DdAYy9/A4LS1tRcuGBm8Ms3zEtHQt8/KBX8drYs0AqIVdGTrR0vZYplx7rdl6YbOH60RLlaVlMbuHy67Fiy/mxsCKwz1cjAUGlIalpePIYyHz3xsbw52DqWjpPluKOp3m21/V9ciHJY2ur3FdQ1esYNlWgxKVpaVJZmZZmzZ9Ovv/wgv+xwjC5Mn633UCk6loKbNM4+FFSVe45Ne1FS1VSY9U+I17ZNcgjkQ8cYmWqv2axLSMw9IyTLxbG0tLvt5FZWlZUQFcdZV3mczSUhRPHnqIfX7/fbMxZ1QxLcO6h+vGWWvWyI+jG6vpEvHkiziS38naAveFz5w57P8jj9jvV4Zqzry1iJa651MVQomfw8n6k/p6dr8K7R4+a5b9Pkm0VEKiJaFHJeTstRebtIoUq6WlbaMeZ0xLvsOP29LSJui+inzEGZNl1haTQ0QZ05Lv8NzBo8od2GXZMvkxTOt7UPfwfHRgcYiWfucaVrS0vS7NmgGXX26+7zDu4bLrKbMOVMXrCUo+3MN5wibiMRWHxHYsykQ8cVha1tezrJfdugEffOD93S37Tz+xWJN9+3pjidkQkXu4kaVlPtoh076mGC0tZR4VxTgWCmpppxMtVe7hAGuTwlpa2oZD8RMtVe7hYd2cxXoZl2hpEpoACBbTslOnbL01LX+YWJ42omVQS0vZfW3blrXNX37J2mkeWfZwXSIek3bYJqZlnO7hujaJPw9T0bKpWVrq2LQpnvNUja+2Bvfwv/8daNlS/bvK0pIf63bokLtdQ4M8tny+3cOnTbPfZyFDLRQ5JFoSenTWZzvumLuslC0teaLMHi5OsFVuFrJtVEQxmCykaDlxove7TOzmv0dtacnHOdFZWlZXZz/zomU+3MPdjjxK1ysVfpM102fazz2cJ9+WlmPGmJ9Hfb16XZPs4UEsLW0HU7L1xfg9cYuWokgdh3u4zDIqykQ8cVhaPvww8O67LBbuAQd4f3ev2VVXsUzTS5YAv/lNsDLYWlrqYlr6CRVbk2gZRNiUTd4LkYgnjNWRLvSFjaVl69bZzz//nGt9aita2t5v3TVIp+Uvc0vJPVxVziiyh++9d/aFqWn7GuZ5tLHw4uudTfZwWdvlOMCwYSwxky6uJMCuWSKhjvtrcv5B3cNNRV1T93Bdm6RKslfsomUclpYyNm2KJ9mWqnxbQyKek0/Wv5RSvdjnk7CpREtZzNF8u4erMsPrIEtLJSRaEnp01meySX2xWlqGFS2jsLSUuYfHbWmp62CjbrxNO7Lhw4HLLvMuC2NpqXsbqcLUPbx79+znKERLm2veuTP7H8b6w5RStLS0rb+JhPlAr7ZWvX+/mJZ+7uFRxbTUxdh1ieoZN4m5lE7nzz282C0t+bZCdG11y754cXbZggXByhCRe7jH0pKvuw8+yDKofvddftoh0+czjDtqXJaWGzcCl1zChGiXYswebjMZDWpp2bZt9vPq1fkXLf1eIssmyVGIlnFZWor35Ztv2HPpuii7mMS09KvbJlbXIlFaWj7+OHDqqcDXX+euy89H3PMIammp6odl+xQNDoKKlkHcw00t4EwzpOvmZ0FEy8WLgdNPz62L+SRflpYbN+bW9bAipuOoE/rk09Ky1GJa8paW7dvnbldfnx9LS79xUZA+hURLJYYzUWKrRWdpKRuQJxLmAkc+Ed0//GgqMS1tMoWqMJ14me7vllu8FozuMfJpaWkqWnbrBnzxBfu8fHl2eT7cw90MrfmwtPQ7RhyipSp7eFwkk3aWXKr6FpelZRSCn/gsxBnTEvBadgaxtDS1ehNFqigtLaMQLTt1yrp4m1p98Mkf3AD/tti6hyueY4e3tHTv4aJFwGmnsc9ffQXcdVewMtpg81IhKFFZWorr3HAD69t44hYtg9R/G0tLnWjJv4QT+0BRtHTrlPviqJCiZTotf95KydLyuOOAhQuB++9noZp69WLLVda/LiaWlkFEyzCWliLuMzR/fu5vQS0t/URLP0tLd13VdTEJX6CytNQJpm5cZJ5icA/nv3/6Kfvzo6Ym1xMkKvJpaSnW9bVrgY4dg+9zw4Zgc5u43cN1FJtoWUj3cL/xY5DxZT5eEJcoRfgamCgqdKJlqVha7rMPcMwxdtuIgxBV9nAT0dJdxyampWx/9fUsi9/Klfm1tDRt5E33V1mZ28mKg0QgeCIek3LwkxZdTEte7M63pWU+RctStLS0RWbNq0InWornJX7PV0xL3UsU2ffPPmMB5IMM2lT3n3+O/ETLMDEtxWdgyRJgxoxoRNko3MOrqrKf/a6vezz+xU1Q0dLW0nLwYOnP6bKy7Dm458Vbf77+ut112rSJxXISY6yaltOPqN3D/ayngdznR1znr3/N3abUREvduqJoyT/P4pivXbvs51WrcsVN/nnxo74+2pch6XR0lpa8+Oo4+RMtFy6UfxbXC5KIJ2pLy4YG4JVXvC99xTLJ0ImWvPhqMt+QnTN/bibu4fyxonAPN41pGZVoGZd7uCldu9pvY0q+LC1l7uG2fZxbnhkzgKeeUj8XQPFaWkbtpadDlYjHz9IyX+7hfu1pkPlb0PHgVgCJloQeW9GyGGNavvqqfZlMLS1NYlqKlpZBY1pOmQKMHw/svrv5ID4KS0vTibHp/mQTlnxbWvLoLC35gZZKtDQdMNjGtHRFy2JwDy/GmJa22FpamrqHh7G0jFq0VFlaLlnCBKtdd81mL7ZBdf/5AVkQ9/CgMS1/9Sv2Muovf7E7nuqNfBD4yQtvNRlEtLRNNOJia2m5777Sn51UKnsObln84uPpOPtsFsvz4IPNtwHMn0/xnsnajquvBvbYI3d5ENGSf35mzJDvR3bf427TVLH6dERpaamCFy1593B3G5tJdhCBOohoKROIdPTpw85t2LDsfvOViIeHF8KiiGkZtaXljTeydmeXXfwtHv1whTf+vMrK/Pfhd1xZjNa4RUvTmJam49soLC1LVbTMl6Xlxo2595qPrWjKAw+w8cvRRwOHHaZer5CWlsXoHs4f1xUtq6vlc8picQ8PMr6UlZsAQKIl4YcupqXKPbzYREvAfjIUZUxLcZ2gMS2nTmX/P/8c+OEH9fF4orC01E1W+Wti2hnILC1lVnC8iFhbayZaOo5dp5RMZgeNKvdwF5VoaXMsm8GTK2roOj3dSwUbtgZLS/d4Jm2Brr75CRwqdx+/mJZRuIer3AOnTMl+PvZYu+MAZtfMxj3cvQamlpaqGIb33GN2PJf+/eX7D0JYS0tb93BZ22Y6IHbr2f77S9uMdCqVPQe3LGFEy4cfZv/feMN8GyD45ItP/OIi62cAu+fG5ZprssuOPlq9H5G427Qgk/E4REtxO949fNUquZeJKXGIlir3cJtYqW5iFl7gy5elJY9OtJSJHn5l2mWXaC0tf/tb9v/bb+VuxFGIln7ltHUPF19wRiVaBolpGbV7uO4ZDJI93BTbEF02+NUhkzo2bpz/OlFZWs6Zk/388cfq9Uw9V0z7zY4d5Ql0gfhiWoYVCf3cw1u2BFq0AAYN8m7X2FgciXiCWFqqYpwSJFoSPjQF93DAPiupLIaabrKjawjPPdc76YkipmUUWVbDWFrW1zOLz969mYhqs7+qKvkgSKw3vMuiynqNL9/xx7PYcjaWZHz9ltX1mpqsCxgvWvL32/Re2Ma0dNF1erxFSxi2BtHSxsonTEzLjRvzkz3cxtIyrBu1qUWkySB74UIWg23sWLMBXdhYczz9+uUui8PSUlfHxowBJk+2s85cvJiVfZddvFZiQbKHv/12zs9OKgXHfUmyebPcjTRoHbK5d0HbAFnZKirk+5M9N35utbLfTK5HISwt/bARLXXZw1Vue4Da0jLI2DCIFXIQS8tddgFee838GGJ/UihLS/6+mFha+tWZ006LL6alzAgiiGjJt3upVPyWln4xLU1iNdpYWsbhHm4iWsZpaRmnaBmFe/iTT/qvE5Voadpvh/Ui4+nXD3j/fXU84ThEy7feYh5jRx4ZvOx+omWrVqx+vvEG8MILrB13+fnn3P2RpWVJQ6IloacpuIcD9iKf2DGpLC1N3MMB4Npr7WJa+g0sTRte3Rtw033IynL//Wzyu3QpcNRRbJnpALeiwky0BNgbNECdkRlg92DBAuCJJ4CffmKuiabwg2jZgDqZzLpp87Fnglpamk4y+Rgtukm/zMIoCFG5h4cRLfORiMf0OGFEy/p6+aQ46uzhNjEt+eVB2mdT0dKkDTj8cGZ188YbZhlHZTEtgyITLfNtaQkAf/xjbjIyHaecwjIGz50L/OlP2eW27uGAdPKYLivziqiy+m96ncS2xCY+U9A2QBarU9bPAMEsLfn9qKyEi8U93I9isbQ0feEWtaWlKnu4bXInt07wApP4sjvflpYm4rtuX7165VqPmmB67cIKBq7wFrWlZdjs4SYig01MS517eBDRkhdCddbEqv4kCtGyUyf7bXTI2mQVfvWjXz+gTRv/Y8rcw4OIlqb9dtCYlj165O5r331Z36+a08fhHj5mDEtQ+MwzwLvvmm0jInsO0+msNaIrwrZrx8Kn8eOqNWty9xe1aOnXB5NoGSkkWhJ6bLOHNxVLS5loGdTS0mXxYvY/aExLHtOGMC738G+/zX52EzaYdgYyqz1VkpTmzdn/9evV5W1okL9RM4Evs6yu86Llhg3ZjjJO0fLEE4GZM7Pfdfc6qs4tKktLm5iW4v3Ol6WlyXHCiJaA3i0lTtFSZWmpiqMZ5lgiflY8338PfPhh1jIbMBvwl5qlZTptdi9NnykA+OCD7OdFi7KfbS0txc9bcJJJ7zncdltw0XL1au93m4yxQUXLAQPYBIlHFdomiKWlbIIcxNIy6gmTSXxOk21M1tWJljpLy+efzz7nfHtnGjogX+7htoiipeylTRgL902bgN/9jr2kiDKmpa5M7v2JS7SUrWfzTLhCn2hp6Ydt7FeVpWWUomVQ9/AgMS15S1JdWVWWliJB2mmbl3Q8vXoBJ50E7Lyzdzl/TmEtLU3PR2ZpuWQJcOml8kRsKqKwtNSJlq+8krsvt+6q+sW43MNdZAKiCbJ+hh9fi5ajfL24/vrc/ZF7eElDoiWhR3Sb4Ekk5NZSpSxaum/gxY4pTPZwXVmCWlqadnpxuYfLJtym+xPfYrvLZPXGFS117uH19cEnu/w+VaJl587Z7661ZZBO29Q9/JFHvJZDunsdVXDzONzD/a5RKbmH33tv9rPJxFQWnN3PPTzOmJb5srT0a7d41x1TbGPN6WjZMndZISwtAXvLLhlBLC1loqVoaTl5MnMl4wkqWubD0jKVAi680LtMNXYxES3jsrT0O44thbS01LmHV1ZmvSSAbAxu/noMGsSSUfiRr0Q8PCb9nShaAv4Wuzb86U/AH/7ABJFnn1Wvp3MPt41p6Z53XO7hsna8UIl4/CwTQ1pafjNhAhp/85vsgrhjWuragrCiZRRjNb5/sWHYMODvfwcOOsi7nL9uYV/UmJ7PqlW5df2aa9izeuaZuX2mirgtLQcMACZO9C5zz1FliBS3aGnzkpZHJlry42tRtPSrF/l0DzcJxyGDLC2VlLRoedddd6F3796oqqrCyJEj8a7G/Pihhx5CIpHw/FXJMk4RXvwmEeIEuFgtLU3ZtAl45x2vJSEAfPWV3rLJZnDKN3JBLS1NO724LC3DiJZlZWaJeIDsxGfzZrVwsXlzcMGLvxeyzpzPqgtkyzBvXnaZTfZw3TWvqQGefjp3uepet2rF4qWqsBEA/CxVm0JMS9kkU4UoWuosIk0tLWXu4fnKHq4SSsMcS7aO33pBxMco3cN1IT5s4YUPm/iULlGIlkEsLSXtQlps54BcSzjTY61a5f2eD0vLVCq3/a6oALbbLnddm7AKsnKFES2jihPqEkQUy4d7OMBCGogEsTzlnjOnbVs06pJDuujOceZM/0mhydxAltjNVGAy4Y47sp//8Q/1erYxLeMQLU3bsrCipcrS0q+cUVtaisf77rvc3YtzIVP3cDGmpakQrrsG/DOjq/umiXiCtNNB59vuNRSvUyEsLefMyX0px6OzHl+/nv3e2KjuS88/3/s9TPZwsa11r2MQ9/DRo9W/mRJ0zih7sc/XYdewRXcc22MC7Jk2EaF146KgY0t+/vDjj8CsWdFbiJYoJSta/vOf/8TFF1+MKVOm4P3338cOO+yA/fbbDz/++KNym5YtW2LZsmWZvyVLluSxxE0UsWEsdUvLe+4BRo0C3nvPu/z665l7o0gQS0t+YKASUPz2ZzqJj8vSUmbFEsbSUiV28x2SSvDYtCn4ZNdPtJQNPP/zn9z6YUIyqb5GDz/MhMMjjtCXkeenn/RxeFQxZ2XI3Cj89iXDxj28mC0txezhure3svOUuT3nIxGPSUzLINc5KkvLIETpHq6zlrfFFVMqK4OJz4USLWWWljLRUvxezO7hKtFy/PjcdU2srkwsLYO4h0fpPhx0exvRkt8/f938LC0B4PbbmcUPT5CxITeGSZ99Nv73+ONoPO88/Ta6c/zPf6TJqDyIoqwM2UuwKEVLXmjStRW6mJYyIUJXZwphaWmDTLQMamlpI1q618FdJl7D667L3b34Ij6Ie7gspmVY93Cd66mppSVgP47QhRrT4bYZskSdLvmytKyrY8leVOgEs3HjWPLByy9X99vbbQdcdVX2u6mlpQyZQREQzNJy6lTgyy/V65oguzYm/Rd/Hu5148cUNTXe9WVzU10oExkrVwL9+wMjRrD+QofuHIKKlq4ou3kzsP32TDS+775g+2pilKxoecstt2DSpEk49dRTMWjQINxzzz2orq7GAw88oNwmkUigc+fOmb9OUQcGbqrsvjv7f+SRub/JGsagZuBxYjoZuvtu9W833ZS7LKxoqSpXVHEy4krEI7vH7jXwG5yoREtdTEsdYURL/txUiXhE0fLgg4MdS1fGZFLtzii717vtxtbXWZ3YiJZ+2DzTKkskv7KoBo7uxDeRYC44QbF1D+fLbyta6tzDCxHTMqx7eFSWlkEQJ3tBefRRs2tmiitaVlfbJQVwEdtm0+349Uz7ge23z36WWVqWlWWzh7uIljGmAploaWnjHh70xUUqldsWVlSw5AO9enmXL1yYW5/8LNRkkx6Tui4+a8VuaalblxemKiv9RUsAOOww73fb+5tOe4/brBkLZaALW6Qrjynl5f7tZNzu4fw4SufOzl+fsJaWcce0DGtp6SL2Z37lDCJaXnll9vujj2aXi8dX4GtpqRIt+UQ8Nu7hUcS0NLW0dMtpg4mFtAyVpWWUoqXNuJgX70RU4+TGRmalCQC33KLut6uqvM99lJaWfqKl7holEt77F5VoaTJ+EZ8hwDumEMctsuPwYbRMyn7nndk295BD9OvGaWn57rvMOAWwSzDbhClCdcmfuro6zJs3D5MnT84sSyaTGDduHGbPnq3cbv369ejVqxfS6TSGDx+OG264AYNlWScB1NbWopbriH/ZMgmtr69HfVRWH0WEe07Sc3vqKSRmzoTzq1/lNDJlqRT45rK+oQFIp+EzpMwr9fX1SDQ2hq/sbuPB0Vhbi3R9PZL19TCVApz6ejS417GxUXqtGuvrkRaudZBr6tTWZo8lkGpoMHprkW5oQKOwj2Qi4Tnf+vp6lDkOEgCc6mokNIPYescB6us959O4pSMR95mqqfEtY3rjRqRD3F+3zidSqZx9NKTTSHDlaqitzVnHAWAy5GlIp5VlbGhshKO4T2UNDZn9pw8/HOkjjoCz555AfT0SiYRyn47wbAJsIJ0IMJFqTCaN63d9bS2QSvk+E42O46njKcjfojUecwyc0aPhtGqF5OuvG5dDJA32XJUlk773K71xI8A9Hw3IdpaNDQ2ecifr6nLK5Kxbl3OMdH09Guvrkairy+wrnUxmjiF75nUkGxpyn5e6Os81bKirg1Nfj1RjY2a5k0go2wQVZVueAx1OOg2nvj7yN6ENdXVIbN4c+L4DQMO//w1n332R+N//cp4X9764JKdORfKee9B4441wjjlGuc+yjRtZe9esGRzHyZx3fV0dko2NvuVNb9rkuVb1v/yiTFZQlkhk24B0OlPelMH1Tu+5Jxo7dMj23ZI+x0kmka6o8JQ5XV7urUtC26caByV/+smzn4a1a5Vtm0gZzNpSkcZEAo7QfjckEnASCeDVV5GYOxfJZ55B8umngfXr0fDaa3D23ju7cm2t55o01NZ6ypx0nMw5OY6Dhvr6nP7T2dL/ecoltHHiceo3b/adzCfefRepE0+Es9tuaHzoIW+/KWkzUlxdVFFfVyed6Cbq6z3X0EmnM21Fcv36zDWor6jwtKPpxsacMQIAJPr18+4vlfK0Pal0WlvW+o0bkVi/Ptv2bhFf0qmU9vlyyx10HOqUlwNlZUho6q3bjqYSicw5pIX2t762NrCVeFlZWeb6Ops3K5+LxvXrM3UgITyjYnnSjY1oFOogTzqVYn3klvaGv//asmrKx9OwYUNOW1AmeW5UNDY0IF1bi7IJE7J1b0uCQ109chobc8dCW57jTDm4sVEaQGOvXsCcOUisWZMZb7l1Xra/HJJJpLlxcuOCBUhxbv71iQRQX48UNwYAgPp0Onscx0HD5s2+zzwA7XjLqajInGvZL78oy873hfyYob6hIXfux/VJJjRIxtcmpBMJNG7p5/jzc8rLM8f3GzvxYy4Z7rNs0l44muvXkEjI+7q6Os++04p+uyGVQoKrMw2bN3v3x+0n7TiZeyXOb+vr63PmaI3uccvKpPWkbMcdkd5+ezS++CJQXe0ZwzQ0NsLhxg2yOaEMT5/a0JB7bTZsUF5zd3zB33e3X06sXZvtE6qqvPMI4XkCgHSXLkhuCeFQX1enbZMT772HsmuvzS5wnJyxjm6s4GHjxkB9UPqXX9hcoazMaMxV6ticV0mKlitXrkRjY2OOpWSnTp3w2WefSbcZMGAAHnjgAQwdOhRr167FzTffjN122w2ffPIJunfvnrP+1KlTcS1fcbfw8ssvozpoFrQS4BVZ1jGAuYq99VbO4gmCQPnyq6+ibONG7BdP8QIxbdo0tP30Uwi5ReEkEkiEDMr7+cKF+HLaNGzzySfY3n91Rl0dpk2bBgCoWLsW+0tWWfrNN/hoyzouPu97pKQ3bswcS2SnH35AN4N9rFq+HLOEffT5/HMM5b5PmzYNv9qwAdUAah0Huug10156CZVr14J33Pvks89QsXYtBgr7HLJqFfr6le/bb/Hp7NnYw+BcpOXZcm7tP/oIQuQWvD9/Ptp/+22mDG+/+SbGCuts2rQJJi3CBx9+iJ0Vv83/6CN837q19LcDa2sznfaSjRvxUU1Nxj29zWefKc+7wXFyxQkEEwUWL12KbQzXfeF//4NTVob+n38OSUS5DEuWLsUCrl6N/vlntJes9/Hy5Vi8aROwaRO2+ewz8+dM4LsffsAH06ZhguJFAc+yRYvQbNUqtN3y/f0FC+CmkPns00/xFVfufgsXQnz1lZC4YH27ZAnmT5uGLvPmZfa1dt06uA7+ny5ciK8Vz6qMwV9/DT4X9rRp0zD822/Rg1s2d84crGhsxK7Ll8PtLddv3owZFscBgL3XrUMLv5Xq6vDj99+js996lrw7ezbaf/45+gfcvrZFC7yYTgMvvojOc+dipPD790uW4H3uehwyZQoAoOykk/B8C/VZ7//LL6gAsCGdxurvv0fPLcvffOMNdPniC23dB4DvFy3y3KtXn38edWJQ+S1M4CZU3373HeZvKe+Yn37K1FEV37RsiU+480tt2oQDhXXSZWX46ocfPGVeuWwZOnLf5737rufaqfqV7ebM8dyr+bNm4XtDS+19Nm6EgW19Dt8sXYrv3n0Xe3HL3p0/Hz+5wlyzZujRrRuGb/nt8yeewFechVrV6tWeMcu777yDn7jfhy5dij5bPqcbGzFt2jTsumIF+BFoo+TF2dJvv/X042Xr1+MA7veXX3wRDT7eBAcedRQS9fVILF6MN4cN8/Q/3y5ahA+F+7Drjz/Cz4do2n//K7UkbPPFF57+JJFOZ+7zjl98kanjb8ydi93r6+Ha7Hz/3XeeZyizv5UrPfvbVFuLV7j1dlu1Ch005Xz5P/9BlzlzMvft00WLgAED8PW333rGCiKbN27Ey9OmBRozAcCmujpUOI5XAEwmkeRe+P2yfj1mTpuG3VavzpzDD99+C3428fprr2HDF18EKsOetbVwWwPdOHXxp5/i4y3XtLPwjC7//nvwqfp++OEHfC0Zw7isWbcOb06bhr02bkRLAI3cWFXHQYai5ftz5mCZUO8OthiDf7tkCX68+mrs8umnmWXfLV+ORGOjpy0Vadi0KbfPdxzPuR3EiZbLfvoJc/nz3uISvPemTWgBoHHzZt/JczqVwtdLlmTqaeqCCzy/v/r666hr3Ro7LFuG3tzy1996C6Nra9EMrB6/+/rrnvv1zTffYKHknvT/7DNln7O+tjbT5/ffYQdst3ChdL2fli3DO1vW4+cHr82ciU0dvE/qgYDVi8TZ77+fMwcz4bvly/HBtGk5c46NdXVwHYO/+fpr6TVx6TB/PnbTHMN9lk3ai9pVq5Tzm48++QTfSsqRrK0Fn0Zo9Y8/Sse67y9ciOrlyzNj3PfnzsUy7qVW1U8/ZfqpZStWZOpoq6++wp7cfqZNm4ah336b6bMA4KtFi/DZtGkY9N132FZy7MT69Ui88w4+vvRSLDrwQAz+5pvM+HLWO+9g09dfZ469fNkyvGfQLvDXc9Zbb+HnlSs9v6vmv+45AMB2ixdnxhNzZs3CyvXr0WXWrOx4fOlSz3h8xxUrMv2Uy/JUKtMOvvn661j3zTfKMu9/4onKsgAA0mnPeX08fz6WKK5FxZo1yvPTsWrJEsyaNg1tP/nE88y88J//sFA+TYyNFt44JSlaBmHUqFEYNWpU5vtuu+2G7bbbDvfeey+uk8QjmTx5Mi6++OLM919++QU9evTAvvvui5ayDKQlTn19PV555RX86le/Qrmf6w1HWWWlx1R73/32K7rMVxMmTEBCFvuvoiJ0XLEB/fph2wkTkBTEcqdDByQklpkAG4BOmDCBfRFd6bbQs1s3dHfXCUGSP5ZA6uGHjfbRrk2bnH0khcDjEyZMQNmWGGiVPgG3Jxx4ILBihWfZ4CFDcixZJ0yYgORbbwE+nWO76mrsxj3btrjnlpCIhsN32gkJzjVr9K675qzTrKZGaoUrsuPw4crfhu24I3ZQ3Cd+otSzb19PvUh07CjbBMCWZ1NwK0ukUoFcFnpvYypZAvuPHw9UVCA5d652vV59+qAHdy6pP/9Zut7gPfbAoC3rJXWuOT5079EDXSZMQFlFhW/22C5t2njexg7faafM54H9+6M/V+7kJ58YHb9Hly7oOmGCpz61apuVnLYbOBADLJ755PTpnu8TJkxAynVj28JOO+4IZ8IEpLikDs1btlS2CSrKDF7UJdJpdAwafkDDLjvthITM3d6QioqK7DMueaPbrXNndHavh2CFPGHCBOCjj5B85BGkTziBZTLdQtmW56imfXtU98hOmcfsvjuSinbdc9z23mnLuD33BLp0ka5bxvXJPbp3R9ct5U1Jxi4iffr1Qy/+fktiTDqpFPoN9MpA7YVxzgju3AGo+xUh0/Gw/v2VbZuIST2T0bdfP/TmLScB7LL77nDGZqf7icZG4LbbAACD3nwTA3v0QPqyy9gLWSHx3i4jRsDZLytjJl98Mfs5kWDP2p13erZJSdwle/bu7e3HhXif++6zD9CunfbcUlydHb2td7rZs3t3dBOubUoX4mYLE8aPl7pYJyRlmbD//kAigdQjj2SW7TF+PLNG2fJcduvSJfsM8ey8M/D//l/ma7OaGk+9UbX5LvvuuSeS3DUbuOOOWAygrxgrU6CKe+aD0KxVK9b+c8J1oqzM497bcks7mrr99syyroKwM3bMGGCgTl5Vk7r+emDxYt/1+nTqhJ5b2qkyQRjrLJSna+fO6CwZw7i0bt+ejeV+9ztWhmTS/zo2NHjGKDqGDx4MR9ifjeFAz5oa9LrlFs+y7r16+fbnZZJnMyGMjRPcOl26dZOed9mWNjFlUGYnmUTfbWXyEGPchAlA69ZI/u9/nuVj9947M5auqqzMGXP27d0bvSVlS/LJIQWat26dPZ+xY9HYvDlQU5Pz/HXg1kv9/e+Z5XvtvTfQwysLJ8vKrKyIR+25p/G6PN179kSXCRNy5hzVLVuyJCUA+vbpI70mLgmfl2YtW7Uybi8qNec8dPhwDJHtR5gTt1W8DB0+ahQS3Bh3+JAh3udl6dLMxy5dumTL/MEHnv1MmDAByZdf9izr178/+k6YgOS77wLPPac8h8Ft2mC7CROQnDEjs2y33XaD0zMrBXbu1Mm6fd1t5Eg4YkIfWZ4I7hwAIOm61QMYudNOcMaNQ4IbXw0cMcIzHk89/7xnP05VFToPGMAS7ALY84UX0Hj//cp+t1yiX3jOVZg/DdluOwxWXYsffpAv96FdZSXTLYQ+ev9BgwCLuVip8IvF+L4kRcv27dsjlUphhSB8rFixAp07m9l5lJeXY8cdd8RXX30l/b2yshKVktgP5eXlVqJeqWF9fsJgoLyiIniWuJgoLy+XD9AjEC1TAFJiUPpnn0WieXMWT0tXJkDpGpZKp9l+Q5JobFTfT0OBIZlOIynuQ7jH5eXlmVghCV2sm1SK1RHhvFOS+Izl5eWAwvrQU77Nm5EMIZZkro9kwlxWUeGpO2UylzrD45RVVAA9e3oGHqrjeOAmBKnKSm+90EzyZQO1RMDrlLJ4u1eeSuUmalDs03MuimOUdeyYvTYhnolkWRmrxwbXIFlXl73uqZRHNEolk95ymz5HjsOOz51nkrtHqUQi1DPPP4MuZYkEu2bc8kQqZd+HGU4skwEHaTrKEongsYHAJqeZ822ba5eYbGzMtm9Cf1BeXs4Ss9XXI3Xbbdnr4DiZiXKiupq9DHC3KSszihuaFF2O3Hvlt10ymS2vG+OpslLZl6UqKrz1SjKucVIppISJVFKIPye2feVisgoXYVxWtnmz+XMbMMZjqqICKcFisay62ntcrn9JfPMNUtdfj1RtLXDjjTn3q0yMMcz9nqlPglAjawUy4wMXcbyki2UsoUxYN9OmeAri3x5l2uicA+T2GeVunHJOwCtv1cpznCSQWw6AifCtWmUSk9m2PeVbQsm4pLYkXUj5jDET6XSocXpCEtMyIX5PJtkx+PZcaCeV19kEw8Qlydpadu0PPjhnkiyWJ5lIIKkZnyXLyz19lNF1tIg3XJZOm1+PsrKcdj/5r3/lrJY0eAmZUPQf5YpnM3MdZGUCczf2wxHHCeKxa2qkccnLuXixCcfJaXdz2hQXzXOfqKzMnmvr1tmkHoJo6ekLuf2Vy8anljEtg76QytwL4XngBR3fsZNPWTPPsgEJjVFOWbNm/olgwK6zdPvmzT3nWSaOCbj2OZlKZe+VcEzZnDdVXs6ukc99SPXpkzOnLRPqaTKRkD8fGnLOxQfZHDmzD26sk2rZUju+SXTu7JkLJadNQ/LuuwGJJ62URMJbN4R+P+U4kczVeZIbNrDrK7Rb5YsXB34JVszY9NUlmYinoqICI0aMwHTO0iSdTmP69Okea0odjY2NWLBgAbooLBsIQ2SJeIrRfFnWoQfNZsfjNip8Q6ZKKiNDtV5UWXjT6WDZBnlkAz5Zud396SZNbt2IMhHPxo3RXC9V9nBdoH0bkkn1G05TMVFs3HWNvew5DJrowmY700QVpol4+DeiYSz53P2bnAufPVxMHKXLsKsjH9nDVUH7wybiMS2b5s15YNLpcC+X+LLvtVc2sZwLf81kk1GZZYWQHCSSRDxB4hW525SVAS+9JF9HlUWUI51KsTh+PH7JalRvx5ct8363ScQTtH2VZQ83mWTfdBPwySfA8uX6coj3t6Ehm1hBh182Z9vzlWUj/+UXZmlj036o2mbZPtx1xeQHJhlZEwmA93Kx7X/q6rzPmitWFiIRjyjo5jN7uA73vsheGMkSeejK5Jc9fNky4Ouvvcts2mabhGqm559KBcseLsI/46o+0l1u8qz5zYV02cPd6y/L9h42EY+O+npgwYLMS4YMcWcPv+oqlgW6myRglXsc8TpphKQc/O5X0HGxiC4RD4+qr6+slGfLdrHJHq5KxOP3XLm/i8cyHeNs2gTMm2c2TjZpD2SJeHhvEb9EPK1b514r3nBk8WKpIYn0+EBuXYsjEY9bP/i+DwCWLAm2vyZESYqWAHDxxRfjr3/9Kx5++GF8+umnOPvss7FhwwaceuqpAICJEyd6EvX8/ve/x8svv4xvvvkG77//Pk488UQsWbIEZ5xxRqFOoWkgPtCJROmIlkGz2fHIhAgb0TJo9nAbVBOjMNnDZdu6y3SdqapTVw3wNDHlMmzaFI1oqXpDypdLNjgyFdKSSWD4cOC3vw2+D/H66eqw7FoHFf1stguaPVx1jKhFS9Ps4bxoyT/PJtnDZciyh+v264fsuKrssWL7ZEscWcFNaWyMTrRMJIA33vAO/oRA90bwlj1RiZZB2nx3m7IyZtkvExJlfbSAI0s64ida7rijvF6IoqXEHV1J0HomEy3FtlE1Ltl+e0B0mRXLId7fE0/MPS+d4OcSNnu4eO9qa4EddmD9ioFbuLJcLrpzcM83kWDioWnbxd8H27FhXZ33WdOJls88A/Tr5y1zULYk4vGgeo4KLVpu2pTNNisiq1+6OqcTLX/4Aejdm13jLa6WAHIn1jrENs+03ugoK/Nvc02eM/4++omWBqRVlujivmT1zK1b6bQ8A7wM3TmaipazZwNDhwKDBvn3uVGKlgceyFy9Z83K/c29TrqXCPnMHh5kP6ZCV2Wl97x0994ve7h4vdzvfsY67jggiGjpOMAeewA77QSIoWuiFC35F2g1Nd71xeeppia3rrr7WbiQuVv36QNwcXK1+7Ppw4MmznH3yfd9f/wj8OtfB9tfE6Ik3cMB4JhjjsFPP/2Eq6++GsuXL8ewYcPw4osvZpLzLF261OMG8fPPP2PSpElYvnw52rRpgxEjRmDWrFkYNGhQoU6haSB7m0OiZXjRMipLS3dfMgHLdHIt62B1QmYQS0vVAG9LbB8tUYmWqo5f1mmG2b/YyQLm9UW8j716MWFXNmmJ0tLSHbSY1JmoLS15l94wg0t3W1PR0i1/Mundxs96SkUhLC2jEi1DJiwLRTptNzH2I5EA+HiNQnZnD6rJBT+YrK4uvGjpTkplbYuhpWXOANuvfIsXs4H+YC4NVX19bnxfG9EyjKWl2J+L323qvc7SMp0G/vnPYPsJa2kptl2zZmXjcZ57LnDOOXZttIiJpaVb33VtIg9/H8R74FfWjRtzrZrXrYMjG7s1a6a2ELRFFuJBJVry16FQoqVoKewiEz10ZXLPUXYdp0zJigzHHpuNtxnG0lJ3/03nESaWlqaWkbLPqnV8cPzmQm690YmWUVla2s51fvgB4JOmyMZMNmOxoUP1YlmzZrnW2y4qcZcXYsOKllFZWqqOI95DVV9fVRXM0tLEEtb9HqdouXYt4May35LQMIOsrzMR9WwtLUWBvqYm9/q4+7nqquw9O/10vWjukg9LS7d8fN+nyV+wNVGylpYAcN5552HJkiWora3FnDlzMHJkNm/ezJkz8dBDD2W+33rrrZl1ly9fjv/973/YcccdC1DqJob4QMvcaoqVON3DTa+BqrNUiQ9BUDWctmKL37IwoqXqmplknY1TtBTLFdY9HJCfZxj38A8+ACZNUh8vyHFk+zLdViZa2gyqRPgQAflyDxctLXUDtjCWln5WvDpsLC3DuoeXgqXlNtswV9+//x044ojsctkAm3+OdJaWomuz7A14VJaWgwcDZ53lvx2/f949HDCzuJBZWpqIlib9wJbECB7y4R5eVubvHm5T78X6btJmFMLSMqiYb/M8y0RLwNzSUhPT05f1683dw/mXxYVyDxfv58EHB6/TNu7honWzqjwyEYxHZ2nJt3m8aGBTB21ES9MJv4mlpQkm4Q4s2hBf0dJFrFd8PZaJzOk0ezE0ahQwblz2vkThHq4ijHv4brsBL76or89um6Lrv2RzTRe/5z1flpaqZ8vGPTyIpaUM8f7kw9JSh+wemFhayq4H3/74WVpWV+e2Ue5++HNSJT0T652pAO33mw6ZaFlkuUIKRUmLlkQRILPiMBGa8o2sgY9iIp4vS8sw7uJxuIfLrh1vmaZC5aKrumYmdWnjxuDXZ/z47Gch02amXH6ipY17OBDOAlI2+NxmG+Ckk3KXy65dWEtLE9x6wNcvE1d1Vdn49cK8EVfVvREjcte1ES1LIaal6pimlIKl5YknMre2k07yWlKGES1FK0FXyOOFuKhESwC4996cTNYA/MOI8MkTxHVlk2KBdCoFZ/hwfflM6vknn+QusxEtw7iH58vSUoWJaBnW0lI8RtCwCTr3PhGVaHnkkdl19tlHfSydpaUfgmjpuBNuVd/Gi21h2iwT93DZSzCx/f32W4DLum6FqWi5ebOdaGkT0xLwD4kTV0xLU9fKVCqasXyxiJZ8EhSVe/iFFzIX/enTWVxeXZndfdrCi1thRMszz2QJufwsLVXHUVlaRukeXuqWlrLjqtqrIKKleLwgIQoK6R6uevnMWy+KHiKy4wN2lpZ8G2YjjJNoqaQI1SWipOAb+7Ky0oppKZsc2hJWtDS1tAwaGwNQdyS2iXh++onFzRozxt/Scs4cgLN8zqBy0Q1jaQn4Zo9U8te/Zj+3bcvO7+yzveUyGcya4J5zGEtL1fUwsbCyOY5sO9NtZTEty8py67CJaPmf/+i3sUFlaSm7Tps3Z691nJaW+YppyS8vtZiWN91kNmBTnVeUouXmzUy0ES0t+X2EES0BdYIbGaKlJcCug86yVmFp6ey5J9C1azahh8o6QbevF17IXcf0hdIXX3hdEm2QhRcxjWkpI4hoabIfU1dP0/3Z1BWT48rqrjhRdEXLa69l96u6Wh9ri78Ptue7bp08pqVM0BNFyzBtVlSJeADg88+Dl8GExsbo3MPdcxStm5JJdbtmI1raxLQ0HfPGYWmp2p9FG9IoJlXh4RMyivWqZUt/9/A338x+//DD7HIVQUJh8eUKI1q6IpmJaKlzDydLSzvRMmginjCWlraipa17eEMDG5c8+GB2mZ97eHU18PPP8rLwoqVqnGIS03LlSuCuu4BFi1gohHPPZfeS32dlpblVuns/xXEmQaIlERK+QeEn+cWGrFMyaUD23ps1IDNnyn8Pmz3c1NIyjGipaoxtLS1PPz0rIl1zjXp/iQSwyy5A377AN99411Gdr+qamQ7cVYHodTz7LNC9u3fZWWflipb5cA/X1Zfy8uz95+M7+m0fdfbwMO7hQSwtX3wR2G8//TY26ARzkdra7CAhatFSZfUYhXu4KqxEWPfwQlpazptntp5N3XBfrjU22rmHu32GGNOSF4/CipY2L2D4RDwufqIlkBOfNu2+cLzxRmaxKiuHiXv4jBn+66jYYw+z9WTIzjGMpaUuEY8KE2+OsJaWJuOAfMS0BFjYjocf9j8W34ebJhVxEd3D3TbZxD08TF8ts7RUiZa6mJZhsLHgtxEtdfuVWbU1NOjHYXG5h9uIllG8VDOJ0WrRhjSKVnMuV14JHHpo9rusXvmJlrL2PWpLSz8rMdNroXvR4GLiHp4PS8uePfWZpP0IK1r6WVry+ImIYRPxiMcyMd7QlTcqS8snnvD+bmJpuX69vCy8R47J8QG5peUFFwCPP+7d5oILvNfSRrQkS0sl5B5OhEMmWkb11ipKgpZJ97YUUFta2roMi4iNfxzu4aYDve+/Z7HKeKu3L77IXU+MaakL3i1LxBPG0lLslFRUVrLB03bbsYyFfhRDTMtXXmEd1sCBWUHBZPtCWVp+8QW7H34uyeL+TMTEKCwtZXVPJF/Zw6N2D1dZdoVNxFNIS0tT+PMysQpwJ3K6RDwyS0sgnpiWLkFES13cQIOXF47MmkWcvJhMOtasUZfRjxUrzNaTITvHMDEt43IPDxvT0mSSZ7JPW9Gyvj57H0XLFj94scL2fH/5xfvSwiamZZgxk00iHl1MS349W0yvVTqtTnYV1NKSP9eNG4HPPvOuF5V7eBQvw6IykojYPbyxsjLbrvKI4p3OSk7lHs7X7bhES/5ehUnE44pkqvUTiew1KXRMy2eesW/fTI4jLlc9MzaWln7HLUQiHl2bGzSmpSjinn++93fxftm4h5uMa8XrKN6TDRu8giWQNerhr4eN6EiipRISLYlwiO7hxUrQgWM6HUy0lCUksClXEEtLv7hnIqYDxo0bgR49vMtknam7P5OEJ1G7h5uKlvvsw+7NggVmA7koY1oGdQ8fO5ZZUnz8sbrMsu0LFdNy9GgmCvMdbhBLyyhFV37/Jseprc0+N6KlpYW1VFpWdwoR07KULS1N4e+RST1x66TO0lJsV9w6HVdMS8BOtFS5h/MYPHuZybWuvTURLd36xk/Mo7Q+UxG3paWJgKRzrQ6zXx4/gWjzZrPrbZuIR5et1Q++z7KtCxde6PXWsHEPP/10u2PxROkeHrdo2dionvzLYuKZJOLhz3X33Vl/Lk7MXeKytDSlSN3DG1QGD+IYbtWq3HWitrQM4h7uJ1raWlqq4PtP2T7dZfmwtNxpJzbWvuIK/fpt2siXm1paqvr4ior4YlrmIxFP3JaW55yTOyYT3aZl7uHiSx2ZBxIgn2eLy8Rrfeedudu4ZRLdw01xy0Xu4TmQaEmEQ2ZpWYzIOt2LLvLfbvVq/UBF5R4+apRZIxVlTEtVoxY2EQ+Q27nIAku710BnaekiE6xMhTcZpqJlIgG0amWX3d0mKL0O93oHcdv2K7Ope3g+LC0B4LvvgDfeyH43EVCDipaie4jLttvKtzWxtASywpRYNy0sLdOyt+aFsLQMK1puLZaWYjsnhp1wRSPRPTyIaKkasNskronI0jLtJ1omEmYxqdx18i1aysodpaVlUAv7qC0t/UTLtWvDiZYqS0u+TtqKlkEsh1TYuIf/4x92++YxScRjKloGJQrR0tbSUtYOiFaWQHSWllEQVSIeE/dwG0vLqir5uEwUEPkEIK1aecuiEi1lLz519aWQ2cP95kF8exLUPTyspSV/Li1asPBWOvr0kS83FS1l7URlJTv/IDEtZcdVja/799fX42KOaSlra/xe0urcw8V6sXp17rMSJCGh20/x52fz4oAsLZWQaEmEg29QijGWpYvYGd53HzBliv92fqKlytKybVvg9deBnXe2K5e4XxeTwbCtaBlmoCfus7bWzj1cJKxoedttZuvZWhqKbuth3MNFS1SesCEVTAeVYWJa2sIPRoNYWpqWX3Xtpk/3flddfz/RMkRMy7QsnlshYlqGdQ/Pt6VlkDLabmMiWoqJTorBPdzdP+8mqLO0NHEPl1lYifswsZRw1+EnqmHaTFNMXgQVwtIy6piWfgLRL79EL1o2NuqztfphGqPNZD9u/ZSJMHwYj7AiVpSWlkEx3VfcoqUfNpaWNol4TInD0jKKmJYqS0udaNmhg/c4svslCplxuYfz2IiW4nITS0vdcUzcw8NaWorHPfTQ3NiJPK64bHock3bevU78eU6ZAtxwQ/Z7mEQ87n47d2Zz06uvBnbYIXe7Yra0FHn22dxlYSwt167NvW5u+7Z8OYu7ffjh/mWWWVrauocvWQL8/e/Btm/CkGhJhKNU3cMnTTILwhtUtARY9mxdVk1ZuVyCWFqqGrWw7uEyTERLW/dw2fqmdUoV08nvuH5EGdMyjKWlH6aDyqDiqE2cVheTZCDiMXhMLS1l59mxY25IA7F+6o4DqN3DbURLWd2JK3u4GOuKP2apWVoG6Uv4e7TbbtnPfNIDHpOYliaipWhRY3ofVeuZuofz99RWtBSegbQu3q67PJ/u4QMH2q2/3Xb+6xTC0tJvP3FYWsYR0zKMpWVU/Sdfx/3cw8OKWDaWln6JeArpHh5FIh4ZxRbTMor+KeKYlkr3cLHujh2b/XzUUey/e31lMS3z5R7OYyNaipaVfpaWvGip8xgK4x7u97vsBdexxwL9+snXb95cvtzU0lKGe53E8/ztb7PzG5VoaZKIhz/H0aOBa68FxozJ3a6YY1qKDBqUu0xmaWkjWortWV0dO99zzwXefBP44AP/Mrt9pJiIx5TGxtwQBSRaAiDRkghLKbuHmwwmf/45uGgJ+L/hVAk3pWZp6TbsQPBEPGEsLU2xFQejjGmpEy3DWlqauofnI6alCz8gMbG0NBETTZ9jWd22FS3533WilG5AmkzCEZ/puGJaqlzJdMc0Jd+WlkHKyN+jk09mL6YOOQT485/l64extOTXq6gIZmmpQuYeLqvjpqKlQWgGI0tLWR90113e5VG5hzc0eMNL6Jg8mYVjAVjSsjFjgEceyV0vbktLk/2I3199Fbj11twwBCridg9XrZsP93DXykwFt62jqtNhX/65mCTikcVIjtKq2CYRj6peyPahu/duOxOXpWWpxLSMyj3cJKbl+ecDRx/NRLKrr2bLoo5pGdbSUoapaJkPS8uoEvGYUlPj3yebLOdxhVBVjHUgnKWlqRFDsbmH69oimRAoEy1VLt5imVaulB+nttabiNaPsDEtGxqAf/5Tvs+tnCJWmYiSgG9g+UaxstLuDWyx0qWLvtFUxbR0sX3D6b41jjKmZRyWlrJseKL7rY1oqZpw+A22+vUDvvrKv7zi8U0xiWlpSpyiZVBLy5Ytc4UZ1f7jFi2DDrJky3R129Q9nP9dN0DU1AnHFb35iUZcMS1l7YZscBZkYl9qlpbJJAsBosNEtBSzYbsTdDFWkTigD9O2mlpayjLIAoEsLX0T8agsLV96ibkwnXYa+x6VaFlfz8TH3/0OuP56/bq8+9y4cexPRtyWlkGyh7sixddfywP6i5RiTEtT9/BOnbyusiL8tn4xLU0pL5ePrZpKIh5bS0tT0bLYYloWYSIeY/fw6upcgcImpqVJSIQ43MNV9VqsOzaWljYxLaN0D1e1G6pzrK6Wv8gL4x7eogX7L3v2ZGPHoIl4eGTnXUru4TJBXOYe3qGDt29RxbRUJdCtrbUbA4cVLWWQpSUAsrQkwsI3evxnE9frfBJk4FhezjImxmlpKeJ2WPlIxBNGiFixwvudb9TzmYhHFVtGRRyWlqYUg3u4uKxbN/P9hxEt43QPtxUt/Y4rEtY9XAyUH1dMS5krmeqNsi35trQMIlrGEdNy0SLvd3eCzm9TXp5bP8K0rUFEy5AxLX0T8SST6jrkCm+A3D08SN1zr2+UcbJt6kdjI7uP33zDyhJXTEuXu+5Sl4PHTyCqrQ0mWjY0AEuXqs8hTPZw0/6zogI48kizffq5h5uiGp9FnYinvh749lu7ssUR0/LHH6O3tCy0e3hUlpYRJ+Ixdg+XwQuRfsJzGPfwv/7VvyxA/mJa6jyGisnSslkztbi4aJHVi+0MOkvL+npg8eLit7S0FS1NwnrpnjlTS8tnnpGPScQyqV6a2YqWbp0P6h4uIw5r6RKEREsiHHyDwjdq7lujYsGmU0okgO+/Z3977plf0VKVCTAO9/AwA7333/d+N41pGXUiHtt6VqwxLeNwDzcR+Lp3N9u/TrR8+23gsstyl/MddlSipel5ylzBbRPx8L8HFC0dvv7EHdNSZ2nJrxukDpeapaUJbtvMXzNxUv3pp97vMvfwqEVL0+zhqjilASwsMu62tjEtAbn7L580Jah7uKScobARQNNp4OabgW22YWOAuGJa+iG+rPQTiEwFVr5+Og6zau3VC/jLX3LXFRPxxJk9/Mknge++8xc6orK0VIk5MkvLoDEtARa+oGdP4IEHzMsWh6XlvHnAJ5+o9+Vev1JKxJPPmJY29UtM4uhiIlrmyz38jDOAH36QxzaUlYdHdS3Ec/YTa/jfbSwtbWJaBrW0VKESLS+7DOjbl7n784S1tJwwgWUs/8MfsstsRUvTeYdMtBTXjSqmJZ/VW9U22lpaykTLMWPYfN5FJVqqLC03b7Zrq9wyB03EIyPsHLGJQKIlEQ6VaFkslpb9+7P/Ng3OoEFA167ZGEu6RjOIe/jJJ6v3Z2NpKQaDzmciHhHTmJYupu7hfoNn23qWj5iWEybI9+XWkWKytNxlF7P96xLxdOkCtG+fu9zPPdzvTXAY93DZb2FiWuoGbD4xLY0tLaMQLU1iWgaZ4G0tlpbipFolWvq5hxeTpaVBaIa0n1ihEy1lFgx8vQ9i+VcMlpaXX84+z5oFLFvmv00YS0sVohhlIlraXu/Fi4F33mGfn3tOvm4+3MPdF2Pduvn361G6h6uWi8+CuG/Zy1nZM/Lpp0wsBIDTTzcvm01MS5VoKbveMmHaxVS0DOoeLo5jo+hXwobjcInYPVy5vokhg59oKTtGUPfwLl38hdSoRMvx43PX5+ctuuOI++XbobgsLf3cw1U884xXzLeJaSl79j78kP3nwwjwZdt55+znSZPYf10iHt0y2VwzkTB7PmxjWvKxnPlkevwcytbScsAA7++9erHP7dtn63kQS0sb3GsYlXt4mzbBt21ikGhJhEPlHl4slpavvsr+2zQ6ohgYxtJS7ID+/Gd1Ygh+/S++AP7xj+xyWUciDuzz6R4uUl9vFtPSJapEPH6Tm7599cf1Q5wImQw+7r9fvlxl6RekXCbbmxxn3DgWAsFk/7qBXbt2ucvDxrSMwj08CtFSFGzDWFo2NAAXXig/dhTu4SYxLYM898ViadmiBZt077RT7m9BLS35GGF+MZZkomXUlpa33w4sX+6/nsrSMoDFslEiHlXbJ3PT4y0tTdpM1Uu6KEVLm3199JH3uy7WoovsnrvP5MSJwAEHqC05VNiKlg0N9qKln6VcIbKHy/oTnqjcw1VijSwRj4loKbv2QV9I2lhauvUimQSOO85+Hy5B3MNtLC39LG2DkE4XpXu4cn0b93CZaKmygAuTPdxGpBbLKKJz437kkdz2gxdzdO7hYhm7ds1+zndMS5WlJc8332Q/21hamtYxvmxt2rCXa3fcAfzpT2xZnO7hqutp6x7OW1q2bs3E2VtuAR5+OLtcdz1k5zR4MPDvfzOr11dfZfsV96USLR96SH6cxx5Tl0GG229H5R7+/PPBt21ikGhJhCOf7uG21jfl5UCPHuyzjWgpNi5hREuxM73gAm8jKsIfix98yjoDUaTMp3u4SF1dbkzLvffOXU9lhRnUPdxvAnXMMbnHsUF08fEb/Oy2m9zqEIg3pqXpW1SZoHHccdnsu7r977+/+jfZJJN/5uIWLfm3tEAwVw7d77pn2iampRhDKl8xLUvN0lJ1T/bfHzj7bHn/EsbKyh1cFoNoCQDXXqv+zb0XccS0VF13XUxL/joGdQ9XhUOJ0j3cZl9i5nIT0VJGYyNze3vkEWDaNODcc+22z4d7uF8iNlG0rKnx3z+PTrRUtStt2+r3KZsAiu20CTpLy6hES9tkjLp9yeDdw2tqgF//2vubiC4LbdhEPH4ZbuN4+eXGnw2LiXu4rWgpu4427uFi0h1Z2dx7rKsvftadftb9Nh4uqjAKABsbX3yx93c/S8t8iJZRxbTk+fLL7OewlpYyxDKPGgWcd55a/AzjHh5XTEtetGzRAhg6FLjoIu8cKsiLy4MOAm68Edh9d+9yndeTDp11ugy3PY7K0nLw4ODbNjFItCTCoQoMHId7uG18SL5sNqKlOKgI4x5u0ij+7W/Mcuh//8vtsG67jWXHlllamoqW770H/Pa37I+PRRnlAFLmHn7ttcCBB8rXz5doqcr4aYqte7joRsGT7+zhJsvcsvhN9hIJZgG2777Ajjvm/iabZPJ11kS0FJ9vG/dw0a1RZ2kpDqxs3cPvuMP4OcqxtHTdMF34Z9bWBWVrtLR0B35RCP9hREt+PZl7eNjERy+84P0uq/f8MWxFS2F/vtnDdefk9pe8m6ate3ixWVqKSVNM3MNlpNOs/3WxFT8XLPB+92sjHn2UxagzKZfL2rX+60YV09I0QZqfpWXLlrlJ+PLtHi7zKJHVddU5/+c/wJVXAu++K/89SEzLykpvOdesyV2fd55D7M0AAHWXSURBVMkUsbW0nDEDuPfe7He/uG3FbGlp8gLRtn7JroeNaAn4u4e7v+vaBr+5k/iSRlceF1NLS7/tTGNaivvlk0iGdQ+3va/V1fGJlkEsLWWYWFrKlrltWNSipewe8G2R6OHoEscYwCRBpcpIwwR3/BKVpWXQF19NEBItiXCokkp06RL9sWytN/0GviqitLQ04fTT2cRmwoTcY114IXuDZiJaqhrFSy4BbriB/f3qV9mMbXHHtGzenA3M+Yygqo5WNeHwG2z5vdn3m3j4ESSmZbGIlqaWlibHr65mMV5fegl49tncY/s9aybnbPLcqUTLAQOA007LLtOJlqIwZStaNjYCI0ZkJ/K2MS15eAHAxs0OsItpGVa0LJaYlu4k0EQE90MmWppkZ+bXd/cTtaWlG4dJBz9B0LmHG8ST9c0eLqtbLrybPV8eG0tLldheKEvLqEinw0049tvP+92vfs6ZY7bffIqWQSadfpaWiQSw7bbeZVGLlkEsLWXPiGzZhx8CBx8MTJ3KPFJkQmKQmJYVFf7XQGdV556T3z1LJIDPPwf22ce73G88Fodo2dgYzUu1GNzDHZloaRPTEshtG8Vr5v6uaxv82iDxBYCuPC5BRUtxX/w1snEPd3MOAPFZWqq8ppo18z/Pr77Kfg6biEeGrWiZD0tL25iWvKVlsYmWgwZl42PaGhREbWkZNvN4E4JESyIcKkvL3/3OvyO0oXNn4NRTzdcvK/NaX+2xRzYpj18Mvzjdw/2QdVgrV8onflVV3mOZTNpXrwZee419jiumpUksy6gsLW1FyzgsLU33Xwzu4SpLS52Y3KULi8nmIj4fJqKlicgkDqxtz8kvfqW7THwBkEwCp5zCPsvqkyre6uzZ7L+NpaW4H14A8HPR+uknb+zFVau8v5tmDy8FS0tVm/vzz+rfm5J7uIloGaWlpV9MS1ndcnGvI2+NGDamJb+fqIhyX6Y0NgYXLWV1yHbyZLJvP9GysTH7ohPIj2hp8sI5CtHSJnu46rny86yR1f/PPst+3rABWLLEbDsZ6XS2XlRUhKvnpol4AOCee3KX2YiWK1ZEJ1oWQyKeigpgr71YkW64gS2TPSs2MS2B3LZRrGPu77qXnn5C6S236H+3FS3dEAWyxFO6l9U2lpY2oXWCWlr+7W/sfsm82vyekc8/z9Yjk/FA1JaWQcfT+XQPd1/W6ETgQomWFRXZuuk3LhSJWrQMkpiyiUKiJREOlaVl27bMxWrMmGiO8/XX5rGUPvwQWLrUG6cvlWLB9Rcv9saKlCE2LroGI2rRUtVAqywteetTfmKh43//C1Y2HbylpdgRyo6TL/dwlXWEKaK7d5jYOLrs4YW2tJSx3XZsMvXVV95Bm/h8JJP+ljEm2cNNwjLoztNkUAXkPkupFIs798UXuTEn3d9lxx03Dvj4Y7uYliL8ddVNOh57jL24GTOGvZ3u2xeYP184mCamZVOxtHTdZW1ibKmI0z08rGipsjrgMbW0NEnE4xfT0s/S8pxzsvGj3f2HiWmpKCcAeQZaEwplaWkb1sZF1ufbWmOrCBPTMox7uIiqXcmXaKm6N2VlueUWnw33d79jyqwLxWdCJhybxrQEsvXCxNJSh01MSz7RiIufe7hb737zG9af+Y0bTIhKtAxradm8OfDyy8BXXyF96aVsmUzEtXUPz4doedppbI711lv+ZXPRiZZ3360eT4nbmca01Hk0xWVpOXAg8N13wPffe5ebiJYzZ2Zj6pu8gHDriunYwW+8I9a9KBPxmIiWBx8M/PGP2e86S0vdeCdKwc69BiYxLSsrs3Md23436kQ8YeeHTQgSLYlw8A+9+GC1aOGNOxKG6mrzNy6tW8vd0ysrzSxYooxpyWe5NbEUVR1LZoXVrJm3sdfFKuKZNs0bf4znxBOzn0eONNsfIHcP1yGz+IvD0tIkrosOx7GPaalit93Y/zgsLXWDPd16OkvLZBLo3j13kio+H4kEW2Y78PCztLRxD/f7DdC7h7vuhipLS9X9OeMMO0tLEVP38BNPZMeZNYtZMYiDaHf/qnhXhba0tI1xrHruL7iA/Td1w9RRzJaWJhZ1cSTiCeoefvfduccME9PSRTbQ58VRG0rNPVxWF20tPlQUo3s4/wzJxKwrrvB+L7Slpfus+I13RPF58+bcZ0l2D2zaM/f+hBUtbSwtv/46d5mppeWdd9qVS0dUMS0vvzz72e1nRHTXtnlzdt222Sa7THY94nIP140fTNqgvn3V3nE2lpauwLXttmYvF00tLfmy7buvmcjs4lc/dPe1QweWnZvHxD0cAJ56yjzGtdu2d+5s9vz5tTviC4Sw7uE8Ju7h++zjjX+vEy11od+KwdLSFtl40q9tJIwgm1MiHGE6A1tM9xW2kYvSPbxDB2D6dBazks/qqELV+fKTBhfR0tJUtFy6FJg0SX6sSy8Fdt6Zib7vvGMeI4tvnIO6h5u6L/D4dQTicWzfWJmIln77HzUK+P3vs0J6HJaWpm9RbWJaqsokcw8HgLffBo46ir1hFzE5ZxN3FtNyytollXs4f09lliIqK2CAiYcdO8p/wxbRUny7yxMkpqWYJMRl331zl0UR0zKKCWF1tb9FF49q0O668cus0EwtzV38RMuamtx9PvQQiz0ct2ipE6fmzGFx8Pr2zS6zjWkpuodHEdOSJ2xMSxeZ2G1ihSqj2N3DHcd7X2R1YNasaMpVjKIlj2hp2b8/CznEE6elJW8pzC/jMbW0FO9jTU1umxpWtHSfHzERjy2mlpaA3NLSNqZlFEQV0/KYY1h7n0wChx4qX0dXl2XCSxTu4WJfJ57re++xvv+jj7LL7ryTZZJ2MbX2Vq1nMz60dcX2s7R016+oYCF5pk9nL4v5Zyjf2cMrKswtABsb7UTLZs1Ygqs99tCvbytahnUPd/+rDF6A3Bepfl5q7pxV16fnS7Rs356FYnMpLw//wpEfP8aRnHgrhCwtiXCo3MNdojRrVjVefEBm3XqmRJ2IZ++9mZVA69b+x1ZN3mQT8qoqO9GSf1t4//3yTKZVVcD55zPxyebNEG8ZZPpWjsdwwuGIVja2omUclpa64wHs3o8bpy9DHJaWJst0dVtVJlWc0KFDmTgrI+5EPOJvNol4+Lore7OqsgIG2KBGNyD2i2nJ11+/mJYuqjbi449zl7muc2EsLaMQLW3fMssmBMcdl92P7BpEIVrywrEqHMnRR8fvHq4TLT//nMUlvv/+7LIQlpYOX7+DiJaq9iyKmJYyy5+g7tbF7h4uWtfKhPmo4J/pfGYPF+G9OfhwPqJo+bvf5U5s4xQtEwl/S0t3W79jivdV1p7KXugEEfhUMS3PO89sXGzjHi72V/yLChVRuXLzbLttsH0OGeL9nkwyMey009T9ve78ZP1FHO7hYr347DPglVey3zt3Bs4917uOqcCmKpuNpaXfvfAb9+nGqLvuCvz2t0CnTtG6h9u2GyZ13cVUtOzXL/t5zBh2nmEwsbQMIlqKv/GIoqVu7tTQkB1v5Vu0lL3M79rVu255eXBLS5loaZtImJBCoiURDp17OBCvpeWee7Lsmldd5V2eT9HSzz3cFlXnxmdZc5FZWj7+OItFKA7IAO+bV8CbOMGFL3scoqXO0tJE4BbvTdwxLR3Hu4/vvtOvb2PdGKZcQY4rW09Xt1Vl0gnBqoFcVO7hunOSvdWVnYM4CeCFKpmlpU60rKz0PvvCefq6hyeT2To9Zw7w6KP+rsE24lxjo39MLD+isrS0QVZf+H3EZWnJiwe6uHqFtLSUYRvTki8vfx2CxLSUWQjbWlqq9i2zTigrA+66i/Vzzzzjv2++TPnGRrQUvSmicgWXYWNp+eabzLrJJUpLy9//nr3Q22cf4Prrs8v79PGuJ2uXRRfyIKKlalJqIloGtbSUETampYvKPbyy0iwmvKl7uKz9FRNDyuAznYehvJx5BB1/PHDYYXZ91Mkns7BNTz9tf1xdzE6Z8JJM5o5rbEVLsW30e5khK6Opl4ONpaXqXttaNYrlNR2j2riHR21pKYt5q6KhQd2/7bADq4snnAAccEDuMXREEdNS1v5FJVryIWIA7zV4/31vSJlCuYfz9UJsH8vKwruH8306WVpGArmHE+HQxb0A4hUt3SzYDz7oXV5slpY2hBEt169n1kjHHcfcQ37zG+/6nTsDl10G3HST+vh82W0mJ7zQYnL+QUVLccAXt6WlOHl5+GH9MUyeAdlkJA73cJmYYOMebnqt+G2jFC1t3cP9AoWrBlpRipbl5Z77m06l5G91XZJJdkz3+TnpJBa+4cor5ccD7NysGxtzJ4m2gloUrndRCB38oFI2cZOF0NAhEy158aB9e/W2+RYt/dqHMDEt+esQxNJSVh+jimkps7RMpVjin3PO8d8vT5B+ediw3IRXNti4h4uWa8UiWvJtkYkwJeLnUstbibmIHhV+CV6A3BeMJuj2G5d7uIyw7uEuKtGyosIsRIeppaXMS6ey0r+damw09yjQ0b8/8O672e827e1DDwU/rm682bmzfHl1tbcO2Ma0FPs6v+snq9OmbUk+REtxO1liR34fqvajkJaWlZXm80ydpWXXrizHgIywoqWJe7isruhE8WRSH46BP0+VpeWaNczCnu/zi8E9XLwWZGlZlJClJREOP/fwKEVLVePll+XRFptEPPkSLWVWRLqYlrIOr6bGP1tjoSwtdcIQj9iJxBHT8k9/Yv933BHo3duuPpkM7mSDzjjcwwcO9F8viKWlbj3VoNfEajLKRDw693CRMKJlRYX3mRXOIcfSUlYfxTrs5xZkI1qm07mWm6XqHu4nWkZhaemKBzU1ekGDnwSWlUUvWpok4uEJkz2cv9Y60VIVfkQmuPi5h9fXe0VmW9EyCEG2C2sdkU6bt+2FEi1tMqPavnwAgl13cRvV5NF9ATt0aK7LqAmqZ5xvt/llPKaJeIpBtDS1tDQVLWXPq/jyRkZjo/3LJRli+aJ2OVeh6scqK72ZknXb2Ma0FK+1n2jpPiuuFXqHDsBBB/kfU1e2YnEPV62XD0vL225j/7ffHhg82M49XHX8Sy5Rbxe1aCm7jrL6HKV7uMz7acaM3DpdDIl44hAtydIycki0JMJRSPdwl6hFy0K6h6smbzJLS11MS1mZq6v1Lo9APKIlj+o305iWtu7hQSwtL7oIWLCAJT2QuYnZHE92TNmgPWr38H//20woLCZLy3zFtBQxES1V10KMaSmKtslkNsmJztLSBltLS1EAs50MBxHgxPtdKu7hrnjQqpV+cukOSt2JuqloefjhZmWzFaz46yU+N37Pnol7eG2t3CIOkAsuvHu4GMfu55/Zy6CuXVk8NiA/omWQflmVTdeUdNr8+RHFiDhjWvJlsqlrQURL08m9DpllH8Am/R99xJIGJhLRiZaJRGlaWgLy58O1tPTDVLRUHdfvWkRlaSmeY75ES9k1PP545h0hWge7iOPosNnD/V4yuHX68MNZ/OMvvzR/bgudiAfIrffFYml5/vksbvi773pfyvmhsrQ8+2wWFkNFoS0t44ppKbOqLEZLy7Iy/xcM55/PXPxF3GvojkkTiWB9J5EDiZZEdMQtWqoaL3F5U3QPl1m5NGvGYqG4XHNN9rPKvdLP0pK/hzaNrC57uGkiHhPhTuzIVQNF1X5NjpFIsLepbidmcz9NnoHhw/3XsUXcXnWfVW+xbQalumMXi3u4bn0RfhKgCpxv4x7Ob7p2bfYay7IuJhL2oqVNrDOZaJkPS0ux7bDN+CyrL/x1kgk6EyfaHUMX07JVK/3k0p14u+uYipZDh5qVLe6YlraWljpUoqUqntW11wI//MC2c128xX5v0iT2v3lztVhkS5A2Nqx1hGkSBqBwMS3jFi1/9avsZzFBiA7e/X/0aPk6iQSL3+2221GKlqJgLdYFU9HSxGo6qpiWq1erM1ZHGdNShom3TDpd2qKlbHzQowfQsaN6G/5+iNZnKnSipcyAgYev0/372714icI9PKylpdh39urlv598xbQcPDhbB0znmaqYlmPG6LeLOqalrLxRi5b8earGALJnKIhoeeqp6m389iWbt4v10MTSskcPoFu33OVuv++KltXVhYmp3QQh0ZIIR9js4QMGmB+rUJaWus6j0DEtR48G/v534IYbgAsvzP6mslSKy9Ly5pvl+zDFVLQU992hAzB2rHr9RMI7EAsyuA1bn8Tz6tKFWXPq1gl7DFV8KRNBQ7WuybHjTsRjKkzaxLTkJ5WyQVy7dur7k0hoRct2n33mPQ+xDMmk/3MWRrwIE9PyoYdYcPj337c/rjgI1cWHlCGrL/y1FSdyd98N7L+/3TFE0bKxMdvO+omWrsDk1llT0dLvzb17zDCWlmES8Zi2wzyyF2qiJcoOO7DMrw8+CHz9dXb5kiXsv3g/b7wxW05RLArTHtv2TVG4h5uKllG6hz/xRO6yY47xlivIcYKIlgMGsKQnv/89G6eY8n//x17E/vOfzDLXhKgS8QDA3nvrvxejpeWqVcyCWTwvU9EyjKWlGCZDRlzu4VHEXTZB1lf7HZvfxjQpF1+nxBd0KqtjF9uXoDym5QOiEy115e3enQmvfvvJd0xLG1Qvrrp00W8X1kI935aW99wDXHpp9rvK0lL2MkbnHi67Drvumg3jZYOtpaWfaKmrN3wInJqa/LVRTRwSLYlwhHUPnzzZ/FiqfRXS0jJf2cNVMS0Blrxj8mTvhCKopWVQ0ZInRvdw6Xkde6z+eLxQEMTlzq8+BUlGdeih/uvYIBsImgh8UVhamoiWJgJk2Ozhfu7hKvzcw9u2Ve9n82bvMysM+lcOHqy2OHPL5zfJCDPJCxrTsr6evcmeNg3YfXf/9cV7JU6QoxAtVc/xYYcBZ51lL7aJoiXvdu/nHh7U0tJvEOz+nk9LS3GiGoU7L+8eDgALFwJz5jDruZUrs8vdPoufyFx2GdC6dfa7aCkUpn+33TafoqX4nAd1D7/hBtYnjh+fXTZggDfGMV8/bY4T1MXtiCOAq66yu57NmwNTpgBHH22+TZSWliNGeJeNG+f9bhrT0sTScs2a3GVBRctkEujXz7s86piWMrZW93Ab0dJUuNBZWvrVizCipc3zE1ciHp4zzzTbT1hLyyDjb9MwPUFFS7++yu858gtvAahFeLHM7rYq0fLLL5m7u3h82T2SjW1sLS2nTgXatFFv47evqGJa6u5RXV123l5TY56Qj9BCoiURjrDZw3fayfxYpol4wgpAtol4Zs8GXnopmuPbxrRUoUpkEZelJU8Q93DTRDymHS9fFn5SHsR6JQ7RUrw/YS0tTQeCNjEtg5QpSktL0zKJAyrALqZlGEvLzZu9A2LhHBaedJJetDSJaWkbq5EnqHu4bSIYv1iztqKl7JmTuXOLy23gt/vmG6+1U8uW4dzDVRNLv4Gr+3uUlpayZ49fJ+qXfu4+ZMfdvJlNcFzceiJmHeWJUrS07ZubNw/XNuuSMIiIz5xfHbjiCmbBuuOO3uVuHeLrWl2depJvU9dMhK9CYivYqPpJNz7mAw8wy8WpU4O7h5tc359/zl0WRLRcvZr933Zb7/KKCrNJvnsuQZMnFcrSspDu4Taipek95a+jbT0II1r6lYUnH5aWupckUVpaBmnjw4iWp5zi72Xo9+LAL0yAykCBR3XtN2wAfvwx+92dN6pEy+eey92Hyj1c1h7aJuIJmiBHDNXkJ1r6jdd0bf9PP2Xbuupq5i1wzjnANtsAb71lXXSCEcErdWKrJkz28GHD5PEgVJhaWoYVgGxEy7Vrgd128y7Lp3u4ClUiHhtLy6BigE601A2ATN7um2bA4/erEjtM8bufxSBamg4ETQYyLqb1WAy+LcNPOAH8s0j6LQsqWorusRUV3oFV27bqa7F5s/cacufp9OmDnwcO9CYwEYUJE0vLQoiWtvHUqqq8k1FR3PB7WSIiqy/8Mv45DmoZyN/3Cy/0hplo1Ur/TMblHu7+bisaR+UeLu5LpLqa9UWuqKN6pmTZl11Wrcp+duuJrg0ppKVlZSX7s8mw3b07O86SJXaWlraiZb9+wPz5TPDi+/U4RctiTyZgK9io1nfr4KmnqmOnuc9NFDEt+WfCJYho6fahMtHSb+wHZM+JYlrKCSJa8s+Mab/KX0fbMWtQQceWoKKljaWl7iWJTSIe2zKZIAvpIKOhwVtHnnwSOOoo/+38nkHbcaGpezjA+vhly9jndu1yxzni9Xzjjdx9qNzDo7C0DGq1KJZHF9PSxD1cN544/nivezgA3HWXeVkJKWRpSYQjjHv4TjuxCcmQIWbHMo1pGZawlifFKlrW1LBtdOXTWeCYEkSASyZZfE436LaqcVeJsbqyFKOlpbjPqN3D47a0vPpq9n/4cK8rp0roDuIeLsM2EQ+PauD64IPe7+JAztTSUhTe3WvB3wsx/p9JTMswlil1df6i5ebNbB1+ua1oKdY30SrJVkywiWkZtP3fYw/vd3eQDvi7h7t1ydY93M/iVGVp6Ve38+Ue3qWLmQupytJSROYe7hdqIIybVZCYh7YiAC/Y2oiWrjDa0MD+/Poqt1zi/SPR0hzZve3UCTj4YP9to7S03LjRK4yn08GEODeWqWgMUFHh/+KoZUvgjDPY56AxLck9PBc+BqUuYQ8Pfx2DvEAMw4EHer+rrq2qjthaNerKqxMtC5GIh0cW0kGGaF1s2geFtbQUsTH4WLkyOx7i3dhVouUPP+TuQyZabt4sF+ELJVqGdQ/XxQB/993sdSp2D4USgkRLIhxh3MNbtmTbzJ4NPP88C9DvNxGyWR4Uk0lfFBZqMlSdq61oqUrEA+gtKKMQLcXzt7G0/PBDYO7c3Pgouu393MOLMaZl3O7hUcS01NXjKVOAd94B3nzTP6ZlIlE40dLvuk6ZkmspbSNabtqUHfiI1mXu+fADMtENMG5Ly82b9Yl4/u//2PNTVcVi3rmiatiJkmgdZ2u17SdaRuEePmKE10Vr+fLsZ79EPOKxTUXLli31E9c43MN9nj1HvNZ+oqXJeqaipVtvdCK02C6EES2DWFraigB8bD+b7OG1tWyi2KsXcyX7/nv/sgHq6yU+LyrRMh8xLfOFbCxwxRXArFny9cV7+6tfAZ9+aiZUm8a0NMV17QaCWVl27ZqNlS2KACai5VdfZV82xWlpubUl4pkzJ/t5zz3NjqOLaelHWNHymWfMPCNUz0jY7OE8uvbGxtIyjpiWptb3bjxfF9M+SJZglhe/4rS03GGH7MtuE9FS5iovvsR49FHmBu4aPPDYuocXi2hpei9N+82oQzs0QUi0JMIRRrR0B1Y1NezNdt++5u4APGEsLUXBQnYcv/hqfttHgWwQq2vgdG/VTMtumrFTJGgiHoCJBSNGqNdrqqJloS0tTfYp7mfkyNzOWCVayvYlCjMmAxHTRDwyZAPb7bfPXSbWJ79EPLylJX893eeMH5DxE1N3m7hFS52l5f/7f9nPX37JMkAC9hMlsU0Rr2EUouUuu2Q/X3ZZ9rNNog4R3so/iGhp6x6eSukHwnEk4pFdS74/sQmHYipamob7cNtjXUzLKEVL23a2oiKYpaV7nHTaXFDZvBm45BJmtfL99yxkgQ4/S0s+W/jFF2+9lpaVlcCoUWbrjxhhnuDB1NLSFN5FPIhoOXx49rMoWlZW+ruHd+iQ/RyXaAmE68/4Y/GYWloGSd7BIxtrHnaYfhtesPJ7pl0KKVpWVAD77GO2ngxbgVBnZVfMlpamLFzo/R5UtNxuO29ysDhFSx6+z+f7NR6Zq7wY0xJgdZmPae1ia2kZNqYlkCtaytzDTWJamtQdU0tLWaK6004z23YrgWJaEuHwcw/XPdCytys1NepYIaYxLW345z+BW24Bbr1VvT+VaKl60xaHaCnDxj38tdey5dI1xHzZW7UC/vtfYPp07/XxI2ginqD4vY2N2z08SIiEuGNaqu5xVJaWKlSxK2X7Eq2Hw1pa+q0vq4cyYUpmackHJefhRUshe6prweaEtbQMY5niJ1qKXH45cw369a/tjsO7wAHRi5b//Kf3Jcrll7P72aEDsO++dvvm4a89b9nWrh2wYoX/9lFnD8+XpSXvoikOqE0tLXX3VDZhkcG7RPPb8pSapWVQ9/DaWu+Ezm+i7V4HVYy48eOBO+5gz/Oll3pDrrj7dpymL1rq6rO4vo1YF7VoOXQoi0U5aRJL2GAL/zyKY2sTS0ueuLKHA/ZurTJ0iXgGDWJ9Qtu2uVZdb74Z7rhiv/bnP/sLfOeeyzwYtt9eLZ6L8NfR9kV7FNZaJiKLqi+zFQhlQo1JOaJMxJOvORsQXLRs3twr7kXhHm5SVzp3zn6WWVo6jnzOLrqH6yi0e7ho3AIEs7Rs2VJudWoqWrZo4Z1rHHcccPPNZttuJZClJRGOKCwteYIMisNYWnbvzkRLnmK0tJRh4x7Ou6XYlP2AA9j1scn+GzSmpQmywYdN9vBiScQTdUxLcXuVdaNsPRVB7qONaCm+KTZ5exrGPVw2sJUNfviBXEUFa5NMLS35+umeMz9gEUXLOGJaplLZSeumTfaJeG68kbny2CCeVxgxAMh9PkRrymbNgGuuYRPCMPDXXhQtTQbGtqJlVRUwbpx6f7xoaROnzTamJS9aivVPd6/4CYyfezgvRKqebZlo6WdpGSbRhKqdVT2DQWJahnEPt+kH3HKpXlglEsB557HnRIxl7dZPWyuuUhQtdRNn8d7aiNpRi5YAE60vvzyYuMY/N0Hcw1X7MsXU0jIK0VJnadm7N3vJvv/+3nVuvx0YPDjcccX6f/75/tu0bcv61IkTzY8TxtIyikQ8Js95UPdwm5impu7hhbC07N7dfhsguGhZUxPOPdx27uTiJ1qq4lTaiJaFcg/nx+7ivNg0piVPhw7ehI4uJtcZyL0Ot94a3jq8iUGiJRGOMNnDVZaWtkQd01Lcn18mW5E4XQ14bBPxuOhESz/3bRN0k7Sw+5cNiHTXobw8vGhp4x6uc1/midvSUrfsiSdY5yqLLcMTt6WlOOgKa2lpeu15/CwtXddw1bXgs3Mnk96679Yb3YAskfAmMuL362JbZ6urs4P9zZtz47mZuKv+979mx1Ehiw9kQ9TJ1VTw5eSDybdrF497eGUlcMMNucs7dmSxxIKGsojS0lLXB9u4h/Pl79hR/gwFES3jsLR88kmWjVskqKUl70ZnKlquWcOC95uimlCprg9//RsbgZkzgfffNz8eUPyipWwsELelZRzjvRdftN+GL7vM0lLmHn7aaeyFtBsWRLYvm+Pny9JSfI5l3i5iWYLGPuYRn624xvr8fm1DBURhaWkisgR1D//mG/NymFpazp6t328clpbPPgv06GHmSs9TKEtLmUW9SV3h2w2ZaKnyjCwlS8tUSp6QMEgiHlmdNX2RIFodR/ECoolBoiURjqgtLU07KZ6oJ7iyAMgiqgFQPt0MdB2O7pqYuoebLJchdo789VOVK4xoqZtIVVTEH9OSP6egA5I4REsZySRw7LHM9fXaa/XbR2lpKdtX1KKl7Df+OZXVMdkx+QG72x7proV7HirRUjcgSyblFjC8daStpUVFRbZtWLIkd0JqIlqaDGb79zffvhRES97Ssm3beBLxVFYyy4UFC7zLly8HDj88N+OzKTpLS1m911la6uqrTSIevq1VxdRzy6GLaSkO3OOIabnttsAXX7C42uKx+OOLv6uOESSmpejx4UcY0fK//wX22gvYdVe7Y4a59vmg1C0tXW67zX4bvr0ytbS85BLmjiiGA4nT0tJN9hYGnXu4ajwQhWiZL4ME/jiFcA832UdQS0te5JK9KOLRje3FezF8uLpuxWFpufPObHz1r3/l/nbIIertwlha8qKWjScGoLaG9INPqmgjWpqGiwD877MqBIotNqJl0EQ8snMxbXtkL5sIDyRaEuEodfdwF3eQ2KULMGaM97diFS3jsLSMQrQUO8ebb87WjYceCrd/WxeHior4Y1o+8gj7n0gwNyAR2eAibvdwFaoBfVQxLWV1K1+WlrLf/vnPbBl+//vc32Xl5e+X2x7p3qa67tuplNQ93NGJQImEXswB7C0tKiv1z0RUouVJJ2WTN4jXVhbT8u9/Z591MaxcCi1axukeDrCg+m7m8quuym6vEi39JlU6S0vZtlz9cuISLfnyqyy9iiWmpSu4iC9NRfdwkxcIfDxPG/dwW1TXwUS0fOyxYMfMl2gTlLAxLW1ES/fZz+eYT4fO0rKyUh7mRCU0xilaivGPg6BzD3fvRxyWlvmCL3u+E/EAZpaWQWNaXnpp9vM//qFf18/zjq9va9eqPUTiimmZSMjbDJ13jemxxP02b84SJ7rX3e/aAcAf/8j+9+4dPDRCUNHS1NJy9Gj/dkPcT9Bn2dbS0m+sIeoVjiOvs6btqfjckaVlDpSIhwhHENdYF1v3cNW+onAPP+88YMcd2UTSJJtqMYiWttnDXeIWLcUYettuC3z2GVvOZ+vlMb2HtqJlFO7hfue+667ARx+x+7HNNrm/y0TLQlpaRr1PnjCJeEw6dtvs4XvsAXzwAWtrevbM/V32LPAxJFWWlm3bZkXXNWuyZYvK0pJP8hXG0lIGX8bycvkzYTJpad6cXdtFi9iAmA83IBMDTjyRWVb07OkfDypfoqXsPFOp+LKHu4PQVAp4+23WbuyxR+7vQHBLS5O2lG+TxHsVhWiZTOaKlvzkxyXf7uF+yfzESYjoHm7SfwR1D7dFNaFRLS92wTEKwlpaFiIRz8svh0sm5uJnaenG9+afS1XZ40zEw78cCopOtIzTPTxfFDJ7uOk+glpaDhkCfPwxaxtV8wEXP9FSHHOpjh1n9nBZndeVO4ylZefObC61ciWw007++7j0UjY/2X774PNkP9FSlngGMBMtr7ySCbF+8J4bpmEoVPtxCRLTslkzr0FBu3Zm7uFRiKwEALK0JMISJnu4bHLUq5d9GaKY4CaTzMKyY8fc32QNR1g3ZxWnnWa+ru5YuoFDvt3DAeZKqhug6PbPZVxMn3FGdvlZZ/lvmw9LS4Cd27bbyn8zES3D1hubmJam20cZ01JW5444wqxsfuu45VRtP2yYV0zeeefs5z59ctfnRUuVpaVrJSeWgx9Au+XSiUCA3gIN8J+07LKLN7O2n2jJZw5WiTCm975bN2D33XMHd+LxGxvZNRw1im3DM3Ro7n4LYWnp0qZNbgIvFe6LN1tLS4ANePfay9u+BHUP11la+iEKtzpvB15gt3EPLy/X13Ode3iUiXh0lpaA3NKSn7QtW+Z/jEKLliaWlkEpduEzbEzLQriH9+8PjBwZbh98eYDcZ9itE2KbpjrfoDEtTerHd9/Z71t2LJ58uYfni1IQLVXtjInb8uDB/oIl4N/Wm7ZHcWYPlz1DcYmWABvrmQiW7rHGjrVLwiXC93+8B4GLzj3c71z3319vlSoeF4jO08LEPVzsT8QXr23bepNEnnGGuXv4oEG5y1RzSCIDiZZEOMK4h8saq8suAyZNAnbbLfe3OC0tdeTT0vKmm6IxCddNlOK2tAwiDOr2/49/MIHyH/+Ac8QRWHD66Wi84IKs64OOuGJajh8PnH468MYb/tvnw9LS1MrZRrSM0tKyUyfvssMOA447zn7/UZTzqadYDK+nnpIP5mSipXh9r7oqdztV9nDdoKyxMbylZbNm3me6okJvKbl6NUvAoWsjTDKW89ddHEiKx9cdSzbAz9cbZtnkzL0fJoPjPfdk//lrMXEis0CV4de288ecNAm46y7/MgD6mJZ+2Lgk8fv260f4fqC8XF7PXauFYrG0FOtiRUX2HpsiTtZsRQcZsjaERMtcbC0tiyERTyoVjdCke3GhEi1VdSVO9/DVq+32e+WVwMCBucfiyVciHgCYO9d87BcUvuy2Y9Yo5g9xuofb4FefgoiWe+4JPP10sP3IyJdo6ffyOy54oc6tF7y1oc493K/PMe3LCyFalpXlhjISv7drx+Yx113HLEYvvtjcPfy//2XzkNtvZ/PbJ54Auna1P6etDHIPJ8IxeDDw5Zfss+wtQY8e6m1ljXD37sB99wFLl+ZaXeYrEY9IPkXLtm2BO+9kE9YwBBUto8geHkS01A0aevYE7r6bfa6vxzcHHYSBEyYgZZooI47s4bvs4k1koyMfMS1NB1025x+kTLJrlUx63UoBYOrUYMKUbUxLGb165San4eFjbarcw/v1Y29KFy7MLhNjWm45P0c3gG1o0Is5gL+lVnW1tw30s7QEgBEj9MKkiWjJ12vxXtq4HIeJARQW2XVyLQLF9mXUKJallGf8ePZftIz5+efc/ZpYb/ID8pdfZn8mVhVRWlqaCij5immZj0Q8OvfwCRPsjxFGdJDRokVukokwMS2DIrbjxYZtTEuTUEAqorK0NMlSa4KubXH3b/oCIE73cBsmTgT+8Adg2jTvcp2lpcrzIirRcsQI4G9/i2ZfKkrB0jKoe3iUBEnged99uXPVMPVWrGeioYRIWEvLfMMLdTLR0g2PJGLiHh5EtIzK08LE0lK0rJRZWiaTwO9+l11m6h7ep0/uPOQvf9GXnyBLSyIkd93FMmput51cxDn5ZBZoV4ZuImszeGxKlpa6fdugEzqCTPrCxLQ0IS4LDtE9PKqYlmHvUdSWluXlwPnnswHG44+r11MJylFZWsq2qa/PneyqBsV/+ANrF1TZU6MQLf0wcQ+vrs4dwKjcw3WWlg0N8kGOraUlX0fFOHwqdM+CmCTJD/H6VFUBL73EXK2PPZb1DyoKKVrKLErc+yU+4+JguWXL7Jtxk7pXWem/nqw8L73kPxEMYWmZk4gnKtGSr1+q7MUNDdk/1X7zlYgHkLuHd+vGYl5XVwMPPmh2nKhFS9kzkm9Ly+23Bw49NNw+4kYVo1aFqbu0jKhEyzgsLUVUlpaqcUyQkAamlpam9O8P3Hor+yxe40JaWuYD/jra3otSFy3/9Cc2BjTxpBKfd5WVp8wDhicKa2mXqip9OxJUtGzTxr5cBjTccw8aqqrQyCdI4uH7E/d6b9yYvc8rVsi3i0u0jNLS0q0XKtFStKwUx/yyNkXmHm46nqUYlr6QaEmEo2tXZmn5ySfyQPtlZcBbbzFhU0Q3iJA9vFuDpSUQzfkEtbRUEbelZVyIbz2DuOrJ7r9Nx5kP93CACX2rV2fdrmX7tBEto7KaWLvWXLS88kr25vb88+W/2ybiCYv7YiWIaGmSiKehQV5uXjg1ES35OmZiaQl4xRRxAmIiWuqud1UVSy7x00/M7UWHbJCXL2sN2XVyBSK/WIqyAPU6TCwEZKLLmjX+LndhLC3Fa2BqyWCTiEcV0xJgL7nyFdMyiKUlANxxB7N0POUU/2Ns2uTtM6IQLWX1wjYRT9j2/M03iydTtgpbS0uxby9EIh6dpeWoUeYilG5cZ+seHuTFc5Si5SefsIQjbpvhJ1o25UQ8tu1HoWNahnUPv/hi1uddcYX/umJ7raq3fqJlFC8eXPxES9NjiW1RmLiUGpzTTsP/HnsM6Rtu8F/Zvd6Ok+3fVXGeTWJamj6TcbuHyxLxlJXlPgcyjUMkTCIeEi19KfIRCFESJJP+gxVxUDZ2rP8+TYn7QZcNZItdtNx992xSoZtv9v4Wt2gZZMAbltNPly+vqACmTMmW309AkWEjWsuQCTDi9YxqMuj3LNgIylFNQA44AGjd2rtMFzNJdw75sLR89FH2v7wcuPxy+b5lriOtW8sHx7pM1O6gSUxK9N572c8moiV/XL+Yli68W48Yt8/W0lJWJsCsbeaTJLmIrrBxIZucuQNz8Z7pBrAmdc9kIii7b2vX+k8Eo4xpGcTSUiYqiJaWKovjTZv07uGFtLTkj2V6XTdsiN7S0ibBTFBLS9GqRKQURB9b0VJ8boNYWsYZ07K6Orjl8znnsP/DhmXPy/RZGjDAvz7Ijh/VOKZrV+91Ffcrnutjj2U//+EP7H8pJ+Lhz1fV/x98sHx5FKJloWNamj6HYnu9ebN8vO0nWpqEw9HB7zMuS0vVS78oMC0TXy9cF3GVaNmihX/baNqX88fNZ0xLEZM2kUTLWCHRksgP4kP73HP69YMMHuMin9nDgWgGV5WVwLx5wAsvABdc4P0tbvfwQlha3nEH8O9/5y4vL2cxDD/6iFmK7Lef/b7DuoebWI3FYSVYDJaWjzzChGKZ+3AQ8iFaHnwwMHMmMH8+i7EL5F6LRCJXtNx2W7mlZSoltzQHshOSBx9kAbld/ve/7Gc/97CqqlxLNZPry7v1tGgBvPhi9nvYQbzN/ZVNvmQxIeNAZ2np5x5erJaWPCZxsEwT8eiEA/GlhCymparf2by5eBLxqCwtbdi4MT+iparOBX2h6ud+GOa65wvbRDziNSw2S0vTUB98eVxuvpmNiV55JbvMZGLuLlclE1MRpaWlzItBPBbP2LHArFlsnOfGK2wqlpYy0XLyZODJJ4H//Cc3HFCh3cOjTMTjh9he/+EPrC+68Ubvcplo2bt3dtnMmeHKwdfHZs3srLtV5MnS0oNr6KKC74fatGGJY1WipVt+3fma9im8WBhV/+8nWgZty8g9PFZItCTyA//QjhnjP0C2iTtSTDEtoxi0mTRwfp0LwASX8eNz9xe1paXoMlcI0bJZM+Cgg3KtedwObvBgZn0a9P6osnGq2GGH7Oc+fez3Hxdxx7QUOfHE7D3hBzxBJxA6cTWqCVMiwSZBgwbpjyu+dVWJlu5vMvr3Z/9btAB+8xuW4Adg2b1d/Cwty8tzEwCZTDqWL/fugy9jWEtLm4lT9+5A587eZbxoGWfGYp1oKYY06NbN+z0OS0vZgNfE0pJv49evz34WxUQZpqKlrl+SiQynnpr9ftBB6mc+n6Kln6UlnziwvDy4aMmLxUuW2O9DxC9zLD+eCuoe7ldX8hVnNgy2oqX4vNmMJd36HIVrqeqeVVWZWb3x5XFxx0Tt28vXKS/Xt1tiIkw/ohQtxf2I17hTp9z1R40ChgxR76OUREv+WePjW7vstRerMwcemH2x6hJFUqcwouWZZ4Y/viniS7lly4BffmGu5byxgEy0vOqq7DKTsB868hHTMh+ipWjgIibSFdvLyy/3jiNdrrsu+zkK0dLELdsEm5iWMtzxOQAMHy5fJ4ylZZxj3SYCiZZEfuAbYJO4gjYxLYtJtAwSwFxE7KzEAdoJJ4R7Mxi1aCm6n0dxDYISZaZZHrEO+F3D555jSagefDCbrENHvjqruLOHA8D06Sz5yttve5fPmsXibT7/fPDzlW1nOqkLg+y4MktLlRuSTLT861+9b/uB7MuI2tpsO+nXXpaV5R7X5JrwlpaiQBP2xYPNPamuZlmyeX7+Gfjvf4Hjj2cW43EhK6c7MN9+e5YMYK+9WEIIV2B2yZel5VtveYVIGXz7xLv9mwTvN3UPF9u8777LfhYFjlSKxac97zyWWfP449VtZl2dPqaleN3C9Pd+lpbHHMPKvO++wFNPBWsDN25kL2ZdPvnEfh88NTW5or7IG2+wa/zss8G9QHSiZUVFaUyoZGWUCf5HHQU8/XS4uhXE0lLltaN65nSWlqK7qImozI+H/MYwts+ZbfbwwYPN1xXv68kn+29TypaW/Mt3Wf3lBSy/MCZBMOm/xbH1tdeykASue34+0HkSrFyZ/Swbl516KivzmWeyl+th4OtnVKKluJ5tuIYgXHYZcOGFQM+ewNFHe71vAHm9WLWK/R8+nMWiv+QS4P/9v+zvNonQVPD3mc9cbotNTEsZ7dsDDzwAnHQS6z/8yupiep5Bci5sZZTAq1OiSWCbwdnG0rKY3MOjsDIUG7jp09kE2sWNuReUIEKebsLSrh3rpEyy/cWNOAmJaqAqxmjz22+fPsBDD5nvPw5LSxv3cNPtTdh7b/YnMmyYPrO5CbLr5A7S45xUm4qWppaWu+wCnHFG7j75N9kbN7KBqt9LANHSMpkMZmkZhYWGi83EqVkzZiFz+OFMdAGYleMBB7C/ONFZWgLMYsNNCPC3v3nX4ycRcca0NIkRzPdHvJWqgaWl06aNd4Kneski9nmLFmU/9+3rfZGWSjHrwDvuyC5T9Tt1dd621S+mZRj8LC2rq71lllFeni3v+ed7wzoA7HwmTABU2Vht6dfPf6K7/fbeuH4ywoiWpST4iMgmgo8/Lh/DBXEPlz37HTqwJGQi/fsDn37qXZZM6i0tVe1G584s8Z6LyT3i1wn7sv+ww7xhnsrK7BKo/fa37MXZRRf5r8vfw113NbMg94uDWcz4WZbxoqV4XoVyD7/66vDHtUXmmeDy5ZfsOQTkomUiEV2Z+frZrFk8lpb58MYqL2cvaG+9Vf67Tszu3ZslAxWJwtKSr49xiJamlpabNzORm/ciEQnjHk6ipS9kaUnkB75BCGppqdv3mWeyTvTBB+3LFqQsOquRsIgDv0GD2ACxWTP/WKAmxJGIp1jiXUXpSsgT50QayJ8Vi039LMZMsbLr5A5o4iyviWg5bJja0lK00hNdjV14wcx10TZxD+fbDFPR8sMPs591cdWCYDNxctujv/yFubr16MEsIPKBLhGPiNhuxmFpqZuE6bC1tHz2WXasI4/MFdQPPhgYPZqdHx/aQhx4822JGALDJg5wXZ23zOJzFWVbq2ojbNqO115jZdxtN3UyjIEDo/MA6dw5d19BrJnCxLQslv7dhCuv9H6XvST3E69N0FlaqsI53HRT7rJEIlhMS9H61mRizD+DYcccYrl07uGyJFzV1bllrqlhcdhFeBdp076llN3D/URL3so2DkvLMO7h+URXhvvvzwpc/PMYx1ib7wurqvTPoqkwVYwiu258onqRoLMQNX0mebFUFi7BlLCipckL5DCWloX0UiwRinBWSjRJ+AbYxNLSdsB/770slknY2CSmZYlTtBQbxkSCTTJ//hk49NDw+2/KomWxuIfbkq9EPKpON66YllGjEy3jLK+szRKvZfPm5paWqhiX/IDHTYZj4h7OH9dUtHz++ezn8vJon2GbCY173zp1AhYvBr75JjckRlz4WVryiJOIfLmHm2BraXnYYcxK66mncn9LpVjSsh9/ZFZNsmOIiKKlTZ9ZW+u1GBPdXvNhaWnTdoweza7NW2+pr0kiEV22V5nbrSjMmWBraTlwYPazX3iCYkIUdGVtdxShhoKIlp07y0P7qOqRLqalGHPX1j08LGK5dO7hsnZIlrBk1SoWh12E72tNRblSdg/3Ey35GLemyZVsKBXRUve8PvAAi/kJ+GcPDwvfxvi5h4cR3QqNbnyiEjR1/WCYrOVB4I+XTtvHtIxbtCRLS19ItCTyg21MSxv3cJe4hDPZfuMcAKmEz6gGCVFmDz/6aPa/GAYwQHzu4WIQ7KjvfxwDKZn7cb6zh0eNLqZlnKJlmzZZYeacc9j/X/0qe40efpj9Vw2OxWD5KtGSH/jZWFqKx1VZcur2YdsuHHGE9/tZZ7H//fr5Wwwefjj7v8su3uWpVH4tDGSD8LhEy6Du4SaoLC11bpS6NjuRYPWBn4yJ5z91Kvvfti1L+KEqj4vOPdyNi+Xuz2S7IETVprkxHnX7C5M4Ya+9sp8vvDAaq01b0XLChOznKDKgFwq37CecwP4PGKBe16btce+JjWipS7ojQ2Vp2alTbttp6x4etr+UxQNV7VMmwslES9W14YUe0+vXVEXLXXbxXuc4+ssgMS0LgV+7OGMG80KJW7TkkYmW7lipS5dcrxsVbdqwsCsAS9JYDOjqhWrcFEUCoThES9OYlm44tvJy4PTT/Y9B7uGxUoT2x0STJE738LiRDRrjnFjHnX07KkvLJ57ITmyKYQADeAe0yWR0A5SXX/YKTaXgHt6lC3MBPvjgbAbbfMS0jJNCWVomkyzZxaxZ2bf3vXsDs2ezuFzuMs7i0eHbMLEeuoNREZmlpZ/LiJiIJ5ViMUVTKXN3EzeTbEWFvo5MmsTOtV+/XHHp5puZ2DJ6tP+9eOABlgxjn33MyhcXsoG2SnDNh6WlqXt4ixbAunXqsrmYJOLRocvqfcklrE3cfvtcFzAb9/Bx47Ln3ayZeTbzIJhYStig61+CWlpecQVwzTXAu++yCdq4cXKXWVtsRcsDDgBuuSX8cQuNK1recw8T18eOVa9rM+5015U9+6rYjrYvZWQxLe+7j7WbM2Z4l9u6h4dFHAPZipbV1eblIfdw1lf97W+58cLjOC+TfRaDoYLJ+P6XX/IrWspiWv7hDyw55U47md+vZJJZZc+enR1fFpoglpZRiJb8Mx/GhTqIe/ixx7K+sXv3XOt2GbJrRO7hkVGEpjREk8TWPVw2+OHdlYYPD18mU2SDpDgHQHxWxT32iH7/QcQd2WD+2GOzk9ViGMAA3ntlExTej379vN9LwdISAIYO9YYUUD17xShQyiiUaAmwQcvRR3sHZ7vswibC7rFV7uEAMHJk9jPflvEEjWkpDspbtfIezw+3Pvs9x+XlTAQfNCj3t5oadn1MrDxbtWLthxsov1DILJ+CWFqaPL9RWlry7oGAt64dc0z28557mu1PBV/3xDavvJxZkMgs12zcw4GsQC+b4ET5gihqN+c4LC1/8xtWV/bYA9hvP9a25MPSki9vixbA7rtnv2+3Xfjj5xPexXjHHdn/5s3Zs6HLxJ4PS0ubY8gsLY8+mr30CpJoJk7RsqxMXcdUlpY77JD9rhvr8i8btlZLy86dWZ/ZsaN3eRznFdVLuLiR1TfRknH16tyY31HDH7NTp9xnsWVLFj+6d2+7/fbokTvmLCS6cqjGTVGESYkiTivgvS91ddl6oRMtUyn2Ao9vq3Qkk7njONM2v5Q9GvIEiZZEfrDNHi6jf3/gz39mFjpPPx1JsYzIt2g5dChw441sgB02U7gM1YBaR6nEtOQtfqIULUWitoaNU3AzuTey4xfjWz9d9vBiQPdG/6GHmID8l7+oMzRH4R7u3ktxcuO3D8C/rhRjyICwiANxU0tLXuTJd0xLMbEFf19uvRU4/njguuu8bsZB0Fla6rBxD+eJW7TkrVOjIA7RUhbPNYrnzm8fnTuz8cYhhwCvv86u+/PPMyufu+8Of/x88sADwHHHAddfD4waZb5dEEtL2VggnWYxT2Xb2Fpaim2Cex+DxNnmn6WwYw7xeKmUesylEi2HDWPJifzGukFEy1K2tJQlL3HFd5FCJWwphjG/7HkVM1ivWhW/peXddzML2KOOAs49N/4Y+IUiCvfwiRPZi/7//S+a49rAj+34F5imMS1NEa8FxbSMDHIPJ/KDbUxLFRdcwP7ySb5FSwC47LL49h1EjPLr6Nu3D1aWqNFlqouSqAW9QouWMhGtGDtQXUxLvg76BbKPi379gM8/Z59F8WHgQOC55/TbB0nE065dbiIeIFgGb78JYalY5NpQU+NNXmNqaWkrWprcD1OLCtHSkp+UdekCPPaY2X78CCpa2riH88isMorZ0lJ334NamMiuM28d2KtXsP2aWFqOG5eN/Qgwq2pVhvRipksX4PHH7bezad9cYYKPIeuSTrMwGdOmeWOD6oQ9GTJLS5VoafJ8RilwydzDVX2V2F4B2bbu0kv9j0WWlmqr+UKdVzGIlrI2bfBg4He/Yy8sAGZpyRvKxCFa7r23121/3jzv78VwraIgikQ8v/oVcOKJdsflvXfCWG7yYzv+BWaUocTc46xcmf1u+ozy55avZJQlRhM0myCKkqhEy0KQSMSX4KUQBLn+fg36AQcwV9lmzYBXXjHb5+TJ7NpedZV9eVTEKVbNnMkmEEOGAPvuG99xosZkwHTttbluvcX4nOrcw08+mbktt2gBvPhifsvl8uSTrA727Yt0kJcr/KBqxgzg/ff192HHHVlSG5klQRyiZVO0tBRFSlNLS36AmW9Ly+bNWUzh8nImivTsabadLbpEPDps3cNdZNaJUca3zoel5fPPs/9RxPJyOessFj+0RQvgmWeC7cPGPZzwx72e/AsPF1eYFNuWVMquPstiWrrtU76tuQ44wPtdHFckk7l9VSoFHHaYfAJuYz3Fv5QLmj28UBaJQRDHsQMGAKecIl83rvv+u9+xfu3KK+W/N2vGXnCkUsC998ZTBj9kbVqnTt6+edUqYOlS9rlFi+is9nSIz2ZTES2DuIeL/UqQa3HCCWzeVVOT7V+DwJfxl1+yn937dcYZrE7dfnvwYwC518m07Tn9dPast2gB/Pe/4crQRCmhVpwoaaJwDy8kVVXet73FlCjIFlHgMHEX95vwJJPAO+8w6zBV5yVyww1sQCR7Cx+UOEXLsWPZ2zNZdsBixmSQ0KYNsHgxEz+WLWPLSk20rKgAFixgQfsLFQNo6FDghx+YQBUkDANf7r/+lf2peOwx5gKZSMhjNpGlpRliXVG1X+LkkE9yUwj38GOPZa67pu1tEIJaWsrqvkk7JLOiiLLOxZ2I55FHspaJUYqAzZoBn37Kyh+0bRPLeuGFLNyOSxSxx0odGytIdwwgEy3d+i8TLW0oL8/dxn0ewopyts/V3/7mTUQhPs+JhHds36oV8O23bHx3zTW5+wsqHgV1Dy+lvkvsuxcuVI/B43qReN11LCmYbnz+6KMswVWUY3gbZOdeUeFte5ctyyai3Hbb/NQDcg/PIvYrQUTL8nJg/nyWmC7MeIfvOy+/PPvZrUd//SsLrxO2Pgd1D6+sBD75JFw/38RpgmYTRFFim4in2BAHEeLkp08f9p9PglCsiMlC3ADDo0ertxEHB4cdlrtOImHfoUQ92InbLbimJjrB8qCD2H9VfMOoMB0klJV570cxxrTUuYcDrJ4WurOvrg5eR2yenzZtstdDzB4O2E0Kt+aYluI1F+NFuoiiAP/dRAwzEZFNhWY3DEbz5vFOwnSJeHTI2g6T7WVJUjp2zLbrp51mXoZ8ID4PfEIGm77IFcCnTFGvk0qFa9vEeiK6mccpfjcVJk5k/5s3z07Gzzordz23PRbvlyqmpbtfkXXrsi8Rxf0FcQ+3jfN96qnsf8uWuSGAxOc5kch9ydGihTyRVFlZcCEnqHt4KZFIZBPpHXSQ/lyqq7MJ7fjQDlFgMj4vlGAJsBcvPPvsw/7zQtncudnncdtt81KsnGexlIwcdOj6CFXfJPbpQa1Ok8nwfZRq+48+yn6Ooj4HFS2B8P18E4csLYn8wD+0xWjB5YcoAIiT1JkzgVdf9WZqLlZE0fLFF1nspQMPVG8jDpoeeCCesoWlULEMg/Dww8C//pUdaMWFzSCh2F8uFHsinrDYDFb4NjVf7uGlZK1iijjAVA1adaKAzNpKxGSybXp98+XKG6WlpcnAXTapTKXYxPOtt1i28mJCFGdHjMh+tplgvf468MEHLMNsXIgJY8Q61BSfbVv8RL0772TJrcaMyQoRffsCb77JLJ+//967H5mlpawP696deaosWeJ98b16NbNWdOHDQASx5uLPz+R+33Yb8zAZPTr3+ZeNK1TthVjWMC66QS0tS42nnwZeesk/pqzr5fTGGyxUzNZE//7s2fvwQ1b/3fkX37Y98YR3/XzQVERKEd38StXfiX16Ia1OVWXk409GQVD3cMIXupJEfuAf2mK04PJDFAA2b85+TqXYYLLYrEBUiEk7Onf2L/u++wIvv8w+X3450Lp1bMULRSmJlm3aZC0Z4oTPOjl2rH7dYo89q3MPbwrYCB384C+qRDx+k8lStl5RIQ4wVZNd3bmvXu1/HNP70bq1PLkHT75ceYOKlrI+3uTlicoSpl8/9lds8JPj3r29k1WbZ3nIEPYXJ+KLVnIHz8VPtGzRQh5bcPfdWeZg191eZ2mpYuRI9vfkk9m4pcOGsbZ55kz2/aST1PuKY2LcogWLFS1D9jzzLzr5/ilK0TJoTMtSo3t3FuPOhL592d/WyO67sz+ejh3l6w4eHH95gK1TtFS9cI8ipmVUqMq4//7RHieMpSWhhURLIj8EeWifew646654M2mbonMPLzVTbn5CaTrQPf98FlNr8+ZoE+dETSmJlvli9Gh2zz780D/AdLG/XCDRMgs/+Atraenedz5Oo4xSt16RwV9z3YBal3k6KktLgFmxT50KvPeeep18WVoGTcQT1D08X+57ALOMW7kSuOSS4Pvo3Zu1re+9x2K78ZiOC3r0CH58G0RLy1IbtxQ7srZRbM9NnqF77mHiaffuLPnNnnuyvruqyjsWLnTcPNnxVOEkRAExTN3bGtzDiXD07cvir/KhFRKJ/Fmibo2ipWrsKraLhZxXqMp4ww3xHodEy8gg0ZLID0HeAh96aPG4W4sCwKZN2c/5yEYXJXxsot69zbYpL2eB2Isdissl5/e/N1uPH2yViqVlqT1/OoK6h/fqBXz9NfvsPt9BsrP6WV81xYkgX+d1E2KdYMu7lA8d6o2R5GIqIh92GPv7wx9YBlcZpege7ld32rbNr/XfqacyD4KwqNpW074oTpdwHlG0pL4ylzAvwExCl6RS/i9+2rf3Zohv3hx4/PHc9cTnMQ73cB1+lpZxuYeb3qOm+IKNMCORACZMAO6/P7vsq6/yJx41VXdg3fjItD8R+6F8IhtfT5rELNrjPE5TrQ8FoAnOQIiipNQfWjHZB+8eXmqiyeTJQKdOrJN57LFClyZaSu1eFBvkHl5Y3AQrJvAD8CefZAOlrl2zlmM218WdbPqJYU1xIsi35bprNmYMG9yWlQHPP+/97fLLmdhQU8PuxaRJudubWgiZrF+K7uF+dOpkv40tzz3HzmPECGDcuHiP5TeJq6xkLxuuvjrecriIk8WddmLuyKkU8I9/5KcMxchTT7FrMHIksPPOwfcjEy3F9lKViCcIo0cD3bqxz4MH58/11UWWPdw0piWfhdwWsrQkTDj77GwdPfDA/LrPN1VLSx26F+4vvsiuyYAB8cfw1yHrk8O0RSrE8GlkaRkZJa4kESVDqT+0/GS2pqa0LS3btGEB32tr7USSUqApCViFgETLwmLzPPKTxuHDgR9+YG2Ru9zmuriCxtZoaWkqWiaTLCHM2rW516lDB2DpUmZhWFMD3HcfE5CvvdZs3zJ06xe7pWUQ0VKVtT1KDj0UWLGCTSrirst+VtM//MDOOV9jIzGmZTIJzJrFQhvkqz4VI0ceyepEmzbhXsqY1CdVIp4gNG8OfPMN8MUXwHbb5V8o8UvEo4tpGSYMBFlaEiaMGMGe6+XLmViWT7Y20TKR0D+X++0H/PQTa7OKLRFPHKKl2J+WutFWEdEEZyBEUVLqDy3/dre6mlkruvzxj/kvT1gqK5ueYAl4Bydnnlm4cpQqxS5aNvXs4TYvQESLk1atvBPJIKLl1ihemIqWAJuMqITdZs28g2I+0y9QmpaWQWNaytzD/VBlbY+atm3zI77rLC3vuIOVI58TuEMOyX52XdqTya3zmRdp1y58nTARyVIpds/dZ3vChHDHrKgAtt/eXCQJ6x7Ox3/dbbfc31XthXhtbUVLPpbnHnuYbdMUX7ARdrRuDQwcmH8Be2sTLU1e+LRpU3jjpYqK3HahQ4fojyOOzwp93k2IEleSiJKh1EVLXsCprmYDp2efZRYlBx9cuHIRXqqqWND6t98Gjj++0KUpPYpdtGzqMS1tBtd+lmk218WdbPqJYevWme+zVIgr1Ie4L1vRkiwtSxvR0rJLF+DRR4HvvgOOOy7/5enWDXjzTeDLL6lvjANTS8tEgo1RXn2VJYPKJ37Z0f249lr2YnjYsNykbYmEeUxLW9FyyhS2zbBh5i9syNKSKBSlPt+1JQ5rxThIJNjLRH4cK7pyR4E4PtvaROwY2cqeLKJglPqbhg0bsp9raljjd9hhhSsPoWboUPZH2EPZw0sHP8s08bpsuy0TLGS48dD8xDCTLNmlxrhxwOuvs88HHBDdfkXRyrae6kROXRbPKDnwQODBB9nn0aP16+6+O/DWW+zzoEH2x8qXpWW+SKXYPXTdspNJYO+9C1um3Xdnf0T0mIiW7joDBuTfZTUKamrk8XqB3JiWOvfwfv2iO64KEi2JQrG1iVSlZK1fXe0VLeMYS+UzoeBWBomWRH4oddFy48bsZ5sMvwRRSpRi9vCmGObABD8RTPz9+eeBc88FXnvNu/ycc7JuirLBZ1lZti40RdHy4ouB+fPZZ1W27iCEtbRUiSB//Wv+XB9vuglYuZJZVf361/p1H3uMCQsDBgTLyt3ULC0BJra4ouXWNpHd2lA9k6+9xtqVk0/Ob3n8iEPUM03E07179MeW8de/Ag89BFx/fX6ORxBAeIvmUqOUREsxbEsc84dSuh4lBomWRH7Il2VIXPCWliRaEk2VUnMPLy9vepaWyaRZTEC/Sacomm23HTBjhne7c88F7rwz+13WTnfoACxbxj43RdGyuhp4+uno9ytef9t6yrta8pxxRrDyBKFdO+Df/zZbt2dP4KWXgh+rqVlaAqxurV7NPpNo2bRRtcd77pm1QC40vAVQ587R759vs3hDBVHQzdcLijPOyG97SRBAsJjOpUJ5ee7YpH//wpQlCKJoGYc2QaJlbFCkYiI/HH000KcPG7hPm1bo0tjDW1rqAuwTRClT7KKlOPlp1arpuYFFFQ/JRCQTrf969gRGjvQu4wOVuwIM4Y/4csvW0lIlWjZVmmK/yp8TiZZNm1JI/HL11SyGW2Uli68aNaaWlk2tzyYInqYsWr70kvd5btfOmyir2BFdt+MQLcV4v0RkkKUlkR8qKoDPPmOT3jje8MYNiZbE1kCxi5biZKfULbhllJVls3mHIYhomUgwqyDeSoYf5DVFS8u4iMvSsqliK+qWAvxYoRRELSI4pXB/O3QAvv2WhSyI2hpIjGnJjyW2traM2LopxnjwUbHXXsD33zO36nXrWB9XSnNiMWlQHJ5apR4Or4gpgV6WaDJUVJSmYAkA//d/2c/nn1+4chBEnJBoWXiiGvCYiEAVFbnLysqAgw/OlmXKlOxvU6dGU7atgbAxLffbL3fZuecGL0+x0xQH+ry1bVO2viGAI4/Mfr7uusKVw4/mzeNzX1S5h//4YzzHI4hiZNtts5+PPbZw5YiLTp3Y+KZjx9ISLIH8ZTrv2ZP9D5KUkFBClpYEYcLxxzPrpzZt/LOoEkSpUmrZw5uiaBmVe7iJCKQS0u6/nyUw2HNPYKedgGefZQlZTjghmrJtDYQVLbt3B159FVi4kMWM+uwz4LTToitfsdEURUt+Qrd5c+HKQcTPwIHACy8AixYBp55a6NLkH52lJYmWxNZETQ3wzjvA229vnW1BMZMv0XLGDBYr/aij8nO8rQQSLQnChLIyCuhNNH1KLXt4UxQtDzwQePjh8PsxSWwis7QEgPbtgUsvzX4/7LDw5dnaEGNaBnFD2mcf9gfILS+bElGJ9cUEn3Bk+fLClYPID+PHF7oEhWWffYBHHmGfd9klu5y3Njr88PyWiSAKwciRufHBicKTL2/PbbYBrrgiP8faiiD3cIIgCIJB7uGF509/ygpVYaipAW68ERg+HJg5U75OKcRhK1XCWlo2dc47z/tdJaCXMrvumv1cjO0pQUTJLbcA48YBRxwBXHBBdvnEiUys3Gsv4N57C1c+giC2bprinGErgmYsBEEQBKN1a/nnYkEU2Vq2LEw54qRdO+YWHIVwedllwLx5wNix8t8pi2t8iO7OJBB7Oess73feKrGpcMABhS4BQeSH6mpmof/KK8wtkm//KiqAZ55hLpPt2xeujARBbN0U47yGMIZG0QRBEATjiiuYEJhMsolHsSG6PIvWbE2Ju+5S/xZV/D8S0oh8cvfd7P8OOzCX0WeeYd979GiaIQgGDGDWZQBw5ZWFLQtBRM1LL7EXXx06AKefXujSEARB6NltNxZ/GAD+9rfCloWwpgkGESIIgiAC0bYtsHQpsG4dSwRSbCSTzM22tpZ9X7q0sOWJkwEDgLfeAnbfPfe3qFyNydKSyCdnncXcR3v2ZHXv8MOBb75h2Uibovt8IsGSs3z9NbDddoUuDUFEy777AosXs3FDqWURJghi66OsDPjgA+C774B+/QpdGsISMrMgCIIgsrRqVZyCpcsDD2Q/H3dc4cqRD1T34frro9k/WVrGS4cO7H/btoUtRzHRr583fmWfPrlJi5oSlZXMqpReEBBNkZ49zZK+EQRBFANVVSRYlihkaUkQBEGUDscdB6xfD9TVNf2YcaIb+COPAKtWAeecE83+SUiJlzffBB5/HDj22EKXhCAIgiAIgiBKEhItCYIgiNIhkQDOPLPQpcgPYnKSE0+Mdv8kWsbLgAHAtdcWuhQEQRAEQRAEUbKQbxhBEARBFCMtWjDRa+BAlpU1asg9nCAIgiAIgiCIIoZmLARBEARRrFx9NfDppyyBSdQ0xeQnBEEQBEEQBEE0GUi0JAiCIIithSefZP87dACOOaawZSEIgiAIgiAIgtBAMS0JgiAIYmvhqKOAhQuBrl2BZs0KXRqCIAiCIAiCIAglJFoSBEEQxNbEdtsVugQEQRAEQRAEQRC+kHs4QRAEQRAEQRAEQRAEQRBFBYmWBEEQBEEQBEEQBEEQBEEUFSRaEgRBEARBEARBEARBEARRVJBoSRAEQRAEQRAEQRAEQRBEUUGiJUEQBEEQBEEQBEEQBEEQRQWJlgRBEARBEARBEARBEARBFBUkWhIEQRAEQRAEQRAEQRAEUVSQaEkQBEEQBEEQBEEQBEEQRFFBoiVBEARBEARBEARBEARBEEUFiZYEQRAEQRAEQRAEQRAEQRQVJFoSBEEQBEEQBEEQBEEQBFFUkGhJEARBEARBEARBEARBEERRQaIlQRAEQRAEQRAEQRAEQRBFBYmWBEEQBEEQBEEQBEEQBEEUFSRaEgRBEARBEARBEARBEARRVJBoSRAEQRAEQRAEQRAEQRBEUUGiJUEQBEEQBEEQBEEQBEEQRQWJlgRBEARBEARBEARBEARBFBUkWhIEQRAEQRAEQRAEQRAEUVSUtGh51113oXfv3qiqqsLIkSPx7rvvatd/6qmnMHDgQFRVVWHIkCGYNm1ankpKEARBEARBEARBEARBEIQpJSta/vOf/8TFF1+MKVOm4P3338cOO+yA/fbbDz/++KN0/VmzZuG4447D6aefjg8++ACHHnooDj30UHz88cd5LjlBEARBEARBEARBEARBEDpKVrS85ZZbMGnSJJx66qkYNGgQ7rnnHlRXV+OBBx6Qrn/bbbdh/PjxuOyyy7Dddtvhuuuuw/Dhw3HnnXfmueQEQRAEQRAEQRAEQRAEQegoK3QBglBXV4d58+Zh8uTJmWXJZBLjxo3D7NmzpdvMnj0bF198sWfZfvvth3/961/S9Wtra1FbW5v5vnbtWgDA6tWrUV9fH/IMio/6+nps3LgRq1atQnl5eaGLQxBSqJ4SpQLVVaIUoHpKlApUV4lSgOopUSpQXSUKzbp16wAAjuP4rluSouXKlSvR2NiITp06eZZ36tQJn332mXSb5cuXS9dfvny5dP2pU6fi2muvzVnep0+fgKUmCIIgCIIgCIIgCIIgCGLdunVo1aqVdp2SFC3zweTJkz2Wmel0GqtXr0a7du2QSCQKWLJ4+OWXX9CjRw98++23aNmyZaGLQxBSqJ4SpQLVVaIUoHpKlApUV4lSgOopUSpQXSUKjeM4WLduHbp27eq7bkmKlu3bt0cqlcKKFSs8y1esWIHOnTtLt+ncubPV+pWVlaisrPQsa926dfBClwgtW7akhosoeqieEqUC1VWiFKB6SpQKVFeJUoDqKVEqUF0lComfhaVLSSbiqaiowIgRIzB9+vTMsnQ6jenTp2PUqFHSbUaNGuVZHwBeeeUV5foEQRAEQRAEQRAEQRAEQRSGkrS0BICLL74YJ598MnbaaSfssssu+POf/4wNGzbg1FNPBQBMnDgR3bp1w9SpUwEAF1xwAcaOHYs//elPOOCAA/CPf/wDc+fOxX333VfI0yAIgiAIgiAIgiAIgiAIQqBkRctjjjkGP/30E66++mosX74cw4YNw4svvphJtrN06VIkk1lD0t122w2PP/44fve73+HKK6/Etttui3/961/YfvvtC3UKRUVlZSWmTJmS4xJPEMUE1VOiVKC6SpQCVE+JUoHqKlEKUD0lSgWqq0QpkXBMcowTBEEQBEEQBEEQBEEQBEHkiZKMaUkQBEEQBEEQBEEQBEEQRNOFREuCIAiCIAiCIAiCIAiCIIoKEi0JgiAIgiAIgiAIgiAIgigqSLQkCIIgCIIgCIIgCIIgCKKoINGSwF133YXevXujqqoKI0eOxLvvvlvoIhFbEVOnTsXOO++MFi1aoGPHjjj00EPx+eefe9bZc889kUgkPH9nnXWWZ52lS5figAMOQHV1NTp27IjLLrsMDQ0N+TwVoolzzTXX5NTDgQMHZn7fvHkzzj33XLRr1w7NmzfHEUccgRUrVnj2QfWUiJvevXvn1NNEIoFzzz0XALWnROF44403cNBBB6Fr165IJBL417/+5fndcRxcffXV6NKlC5o1a4Zx48bhyy+/9KyzevVqnHDCCWjZsiVat26N008/HevXr/es89FHH2HMmDGoqqpCjx49cOONN8Z9akQTQldP6+vrccUVV2DIkCGoqalB165dMXHiRPzwww+efcja4T/+8Y+edaieEmHxa1NPOeWUnHo4fvx4zzrUphKlAImWWzn//Oc/cfHFF2PKlCl4//33scMOO2C//fbDjz/+WOiiEVsJr7/+Os4991y88847eOWVV1BfX499990XGzZs8Kw3adIkLFu2LPPHd5iNjY044IADUFdXh1mzZuHhhx/GQw89hKuvvjrfp0M0cQYPHuyph2+99Vbmt4suugj/+c9/8NRTT+H111/HDz/8gMMPPzzzO9VTIh+89957njr6yiuvAACOOuqozDrUnhKFYMOGDdhhhx1w1113SX+/8cYbcfvtt+Oee+7BnDlzUFNTg/322w+bN2/OrHPCCSfgk08+wSuvvIL//ve/eOONN3DmmWdmfv/ll1+w7777olevXpg3bx5uuukmXHPNNbjvvvtiPz+iaaCrpxs3bsT777+Pq666Cu+//z6effZZfP755zj44INz1v3973/vaWd/85vfZH6jekpEgV+bCgDjx4/31MMnnnjC8zu1qURJ4BBbNbvssotz7rnnZr43NjY6Xbt2daZOnVrAUhFbMz/++KMDwHn99dczy8aOHetccMEFym2mTZvmJJNJZ/ny5Zlld999t9OyZUuntrY2zuISWxFTpkxxdthhB+lva9asccrLy52nnnoqs+zTTz91ADizZ892HIfqKVEYLrjgAmebbbZx0um04zjUnhLFAQDnueeey3xPp9NO586dnZtuuimzbM2aNU5lZaXzxBNPOI7jOAsXLnQAOO+9915mnRdeeMFJJBLO999/7ziO4/zlL39x2rRp46mrV1xxhTNgwICYz4hoioj1VMa7777rAHCWLFmSWdarVy/n1ltvVW5D9ZSIGlldPfnkk51DDjlEuQ21qUSpQJaWWzF1dXWYN28exo0bl1mWTCYxbtw4zJ49u4AlI7Zm1q5dCwBo27atZ/ljjz2G9u3bY/vtt8fkyZOxcePGzG+zZ8/GkCFD0KlTp8yy/fbbD7/88gs++eST/BSc2Cr48ssv0bVrV/Tt2xcnnHACli5dCgCYN28e6uvrPe3pwIED0bNnz0x7SvWUyDd1dXV49NFHcdpppyGRSGSWU3tKFBuLFi3C8uXLPW1oq1atMHLkSE8b2rp1a+y0006ZdcaNG4dkMok5c+Zk1tljjz1QUVGRWWe//fbD559/jp9//jlPZ0NsTaxduxaJRAKtW7f2LP/jH/+Idu3aYccdd8RNN93kCbFB9ZTIFzNnzkTHjh0xYMAAnH322Vi1alXmN2pTiVKhrNAFIArHypUr0djY6JmYAECnTp3w2WefFahUxNZMOp3GhRdeiNGjR2P77bfPLD/++OPRq1cvdO3aFR999BGuuOIKfP7553j22WcBAMuXL5fWY/c3goiCkSNH4qGHHsKAAQOwbNkyXHvttRgzZgw+/vhjLF++HBUVFTmTlk6dOmXqINVTIt/861//wpo1a3DKKadkllF7ShQjbt2S1T2+De3YsaPn97KyMrRt29azTp8+fXL24f7Wpk2bWMpPbJ1s3rwZV1xxBY477ji0bNkys/z888/H8OHD0bZtW8yaNQuTJ0/GsmXLcMsttwCgekrkh/Hjx+Pwww9Hnz598PXXX+PKK6/E/vvvj9mzZyOVSlGbSpQMJFoSBFE0nHvuufj44489cQIBeGKrDBkyBF26dME+++yDr7/+Gttss02+i0lspey///6Zz0OHDsXIkSPRq1cvPPnkk2jWrFkBS0YQcu6//37sv//+6Nq1a2YZtacEQRDhqa+vx9FHHw3HcXD33Xd7frv44oszn4cOHYqKigr8+te/xtSpU1FZWZnvohJbKccee2zm85AhQzB06FBss802mDlzJvbZZ58Clowg7CD38K2Y9u3bI5VK5WS3XbFiBTp37lygUhFbK+eddx7++9//4rXXXkP37t21644cORIA8NVXXwEAOnfuLK3H7m8EEQetW7dG//798dVXX6Fz586oq6vDmjVrPOvw7SnVUyKfLFmyBK+++irOOOMM7XrUnhLFgFu3dGPSzp075ySKbGhowOrVq6mdJfKKK1guWbIEr7zyisfKUsbIkSPR0NCAxYsXA6B6ShSGvn37on379p7+ntpUohQg0XIrpqKiAiNGjMD06dMzy9LpNKZPn45Ro0YVsGTE1oTjODjvvPPw3HPPYcaMGTkuCDLmz58PAOjSpQsAYNSoUViwYIGn43UHkYMGDYql3ASxfv16fP311+jSpQtGjBiB8vJyT3v6+eefY+nSpZn2lOopkU8efPBBdOzYEQcccIB2PWpPiWKgT58+6Ny5s6cN/eWXXzBnzhxPG7pmzRrMmzcvs86MGTOQTqcz4vuoUaPwxhtvoL6+PrPOK6+8ggEDBpAbIxEJrmD55Zdf4tVXX0W7du18t5k/fz6SyWTGFZfqKVEIvvvuO6xatcrT31ObSpQEhc4ERBSWf/zjH05lZaXz0EMPOQsXLnTOPPNMp3Xr1p6soQQRJ2effbbTqlUrZ+bMmc6yZcsyfxs3bnQcx3G++uor5/e//70zd+5cZ9GiRc7zzz/v9O3b19ljjz0y+2hoaHC23357Z99993Xmz5/vvPjii06HDh2cyZMnF+q0iCbIJZdc4sycOdNZtGiR8/bbbzvjxo1z2rdv7/z444+O4zjOWWed5fTs2dOZMWOGM3fuXGfUqFHOqFGjMttTPSXyRWNjo9OzZ0/niiuu8Cyn9pQoJOvWrXM++OAD54MPPnAAOLfccovzwQcfZLIu//GPf3Rat27tPP/8885HH33kHHLIIU6fPn2cTZs2ZfYxfvx4Z8cdd3TmzJnjvPXWW862227rHHfccZnf16xZ43Tq1Mk56aSTnI8//tj5xz/+4VRXVzv33ntv3s+XKE109bSurs45+OCDne7duzvz58/3jFvd7MqzZs1ybr31Vmf+/PnO119/7Tz66KNOhw4dnIkTJ2aOQfWUiAJdXV23bp1z6aWXOrNnz3YWLVrkvPrqq87w4cOdbbfd1tm8eXNmH9SmEqUAiZaEc8cddzg9e/Z0KioqnF122cV55513Cl0kYisCgPTvwQcfdBzHcZYuXersscceTtu2bZ3KykqnX79+zmWXXeasXbvWs5/Fixc7+++/v9OsWTOnffv2ziWXXOLU19cX4IyIpsoxxxzjdOnSxamoqHC6devmHHPMMc5XX32V+X3Tpk3OOeec47Rp08aprq52DjvsMGfZsmWefVA9JfLBSy+95ABwPv/8c89yak+JQvLaa69J+/uTTz7ZcRzHSafTzlVXXeV06tTJqaysdPbZZ5+cOrxq1SrnuOOOc5o3b+60bNnSOfXUU51169Z51vnwww+d3Xff3amsrHS6devm/PGPf8zXKRJNAF09XbRokXLc+tprrzmO4zjz5s1zRo4c6bRq1cqpqqpytttuO+eGG27wCEWOQ/WUCI+urm7cuNHZd999nQ4dOjjl5eVOr169nEmTJuUYJlGbSpQCCcdxnDwYdBIEQRAEQRAEQRAEQRAEQRhBMS0JgiAIgiAIgiAIgiAIgigqSLQkCIIgCIIgCIIgCIIgCKKoINGSIAiCIAiCIAiCIAiCIIiigkRLgiAIgiAIgiAIgiAIgiCKChItCYIgCIIgCIIgCIIgCIIoKki0JAiCIAiCIAiCIAiCIAiiqCDRkiAIgiAIgiAIgiAIgiCIooJES4IgCIIgCIIgCIIgCIIgigoSLQmCIAiCIAiiBOnduzcSiQROOeWUQheFIAiCIAgicki0JAiCIAiCsOTXv/41EokEEokEZsyYYbXtyy+/nNn2ggsuiKmEBEEQBEEQBFHakGhJEARBEARhycSJEzOfH330UattH3nkEel+CsXMmTMzIurMmTMLXRyCIAiCIAiCAECiJUEQBEEQhDWjR4/GNttsAwB45plnsGnTJqPtNmzYgOeeew4AMHjwYIwYMSK2MhIEQRAEQRBEKUOiJUEQBEEQRABOOukkAMAvv/yC559/3mibZ599Fhs2bPBsTxAEQRAEQRBELiRaEgRBEARBBOCkk05CIpEAYO4i7rqGJ5NJnHjiibGVjSAIgiAIgiBKHRItCYIgCIIgAtC3b1+MHj0aAPDSSy/hxx9/1K7/ww8/YPr06QCAvffeG926dctZ51//+heOOuoo9OzZE1VVVWjdujV22mknXHvttfj555+NyjVt2jSceOKJ6Nu3L2pqalBVVYU+ffrgiCOOwEMPPYSNGzcCABYvXoxEIoG99tors+1ee+2ViW/p/j300EM5x6irq8Nf/vIX7LXXXujQoQMqKirQuXNnTJgwAY8++ijS6bSyfKeccgoSiQR69+4NAFi2bBmuuOIKDB48GC1atLCOrSmLyfnkk09in332QYcOHdCsWTMMGDAAl19+OVavXq3cz5577olEIoE999xTe7xrrrkmczwZ7m/XXHMNAOC1117DoYceiq5du6JZs2bYbrvtcN1112Usbl2mTZuGCRMmZNYbNGgQpk6dirq6OuNr8d577+G4445Djx49UFVVhR49euDUU0/FZ599ZrT9V199hYsuughDhgxBq1at0KxZM/Tt2xennHIK5s6dq9xOvAfpdBoPPPAA9tprL3Tq1AnJZJIynBMEQRAEYY9DEARBEARBBOK+++5zADgAnNtuu0277k033ZRZ9+9//7vnt9WrVzt777135nfZX8eOHZ3Zs2cr979y5Upnn3320e4DgPPggw86juM4ixYt8l2XX99l0aJFzsCBA7Xb7L777s6qVauk5Tz55JMdAE6vXr2c2bNnO+3bt8/Z/rXXXvO99i6vvfZaZrvp06c7J554orJc/fr1c5YtWybdz9ixYx0AztixY7XHmzJlSmZ/MtzfpkyZ4kydOtVJJBLSsuy2227O+vXrnXQ67Zx//vnKMo8fP95paGiQHqtXr14OAOfkk0927r//fqesrEy6j8rKSufJJ5/UntdNN93klJeXK8uRSCScq666Srotfw9eeOEFZ9y4cTnbn3zyydrjEwRBEARBiJClJUEQBEEQRECOPvpoVFVVAfBmBZfh/t68eXMcfvjhmeW1tbUYN24cZsyYgVQqhZNOOglPPPEE3nnnHbz55pv4wx/+gHbt2uHHH3/EhAkTsGTJkpx9b9y4EXvttVfGknPEiBG499578fbbb2Pu3Ll47rnncNFFF6Fr166Zbbp164YFCxbggQceyCx74IEHsGDBAs/foYcemvl9/fr12GeffTKWe4ceeij+/e9/Y+7cuXjqqacwduxYAMBbb72Fgw46CI2NjcrrsX79ehxxxBHYvHkzfvvb32LmzJl49913cf/996NLly7aa6niqquuwqOPPopDDz0Uzz77LObNm4dp06bhgAMOAJC1JMwHL7zwAiZPnoxdd90Vjz/+OObOnYsXX3wR+++/PwBg1qxZmDp1Km699Vbcfvvt2H///fHMM89g3rx5eP7557HrrrsCAF588UX89a9/1R5r/vz5OOuss9CxY0fccccdmDNnDl5//XVcccUVqKysRG1tLU444QSlteRNN92Eyy67DPX19Rg6dCjuvvtuvPrqq5g7dy4ee+wxjBo1Co7j4LrrrsPtt9+uLcsVV1yBV199FQcffLDnHrjnTRAEQRAEYUyhVVOCIAiCIIhS5uijj85Yk3322WfSdT788MPMOhMnTvT8duWVVzoAnNatWztz586Vbr948WKnS5cuDgDn+OOPz/n9oosuyuz/3HPPddLptHQ/tbW1zvLlyz3LeCs5PwvHSy+9NLPu7373u5zf0+m0c8IJJ2TW+ctf/pKzjmtpCcBp3ry5M3/+fO0x/eDLD8C5/vrrpeXad999HQBOWVmZ8+OPP+asE7WlJQDniCOOyLGSbGhocHbddVcHgNOiRQunqqrKufDCC3P2s2HDhowl5dChQ6XHcn/HFstVmRXpjBkzMhaYO++8c87vn3zyScbCcsqUKdK609jYmLFgbd68ubN69WrP7+I9kNUNgiAIgiAIW8jSkiAIgiAIIgQTJ07MfFZZW/LL+fXXr1+Pu+66CwBw3XXXYcSIEdLte/XqhauuugoA8NRTT3niIa5Zswb33nsvAGZhedtttynjLVZUVKBTp04mp5VDbW0t/va3vwEABg8enInZyJNIJPCXv/wF7dq1AwDceeed2n1efvnl2GGHHQKVR8aIESNw5ZVXSst18cUXAwAaGhowe/bsyI6porq6Gvfddx9SqZRneSqVwplnngkAWLduHTp06IAbb7xRuv3JJ58MAPjoo4+wdu1a7fH+9Kc/oXPnzjnL99prL0yaNAkAi3kpWlv+6U9/Qn19PXbaaSdMmTJFWneSySTuuOMOVFZWYv369Xj66aeV5ejfv7+0bhAEQRAEQdhCoiVBEARBEEQI9ttvv4wQ+Nhjj8FxHM/v6XQajz/+OACge/funsQ3r7/+ekaMOvLII7XH2WOPPQAA9fX1mDdvXmb5jBkzMsl1zj///ByRLCrmzZuHNWvWAGDJdFTHadmyJY4++mgAwMKFC7Fs2TLlPk844YRIy3j88ccrBVteEP7mm28iPa6MX/3qV2jbtq30N16oPfzww1FeXu673qJFi5THatOmDQ455BDl76eddlrm86uvvur57T//+Q8A4IgjjlBeOwBo3bo1hgwZAgBa0feYY46JrQ4SBEEQBLF1QaIlQRAEQRBECMrKynD88ccDYBm533rrLc/v06dPxw8//ACAiXTJZHb4xVu9denSJSdzN/+3/fbbZ9Zdvnx55vMHH3yQ+TxmzJhoT47j448/znweOXKkdl3+d347nubNm6Nv377RFG4LAwcOVP7GC4jr1q2L9Lgy+vfvr/ytdevW1uvpyrzjjjuirKxM+fuwYcNQUVEBAFiwYEFm+ZIlS/DTTz8BACZPnqytf4lEIlNf+fonMnToUOVvBEEQBEEQNpBoSRAEQRAEERKdi7jKNRwAfvzxx0DHcy0rAWDlypWZz0ET2JiwevXqzOeOHTtq1+XdlPnteHhBLiqqq6uVv/FisS5BUL7LEkWZ/e5HWVlZRrTl70cU9U+kTZs2gfZJEARBEAQhon4lSxAEQRAEQRgxbNgwDBkyBAsWLMBTTz2Vif+3YcMGPPvsswCYe/KgQYM82/FC1Pvvv690Exbp3r17dIUPgM6N2BRyIY6OoPeDr39XX301jjrqKKPtampqlL/RfSUIgiAIIipItCQIgiAIgoiAiRMn4rLLLsOaNWvwn//8B0ceeSSee+65TNIc0coSQCZhDQB06NAhkBjZvn37zOdly5ahT58+AUrvD+9evWLFCq1bM+8+rIrrWGy4Vo3pdFq7Hp8EqVhYsWKF9veGhoaMhSV/P/j6V15e7glBQBAEQRAEUWjIPZwgCIIgCCICTjjhhIyV2aOPPgog6xpeXl6O4447LmebHXfcMfP57bffDnTc4cOHZz6/8cYb1tubWunxgtacOXO067777rvS7YqZFi1aAAB+/vln7XpffPFFPopjxfz589HQ0KD8/cMPP0RdXR0A7/3o27cvWrVqBSB4/SMIgiAIgogLEi0JgiAIgiAioEuXLhg3bhwAYNq0afj4448xffp0AMD48ePRoUOHnG3GjRuXiWl4++2352QeN2GvvfbKuOvecccd1vEaq6qqMp9ra2uV640YMSITh/Lhhx9WWiSuW7cOTz75JABg0KBBscbZjBLXQvWLL75QJr1ZuXIlXnnllXwWy4jVq1dnsoDLeOCBBzKf3ToKMFfuCRMmAABefvllfPrpp/EVkiAIgiAIwhISLQmCIAiCICLCdQGvr6/HsccemxEQZa7hAEtGc9555wEAZs2ahYsuukjrnrxixQr87W9/y9nHr3/9awDAvHnzcOGFFyrFz/r6+pzkK7yo+PXXXyuPXVlZiTPOOAMAywh+3XXX5azjOA7OO++8THIg99xKgbFjxwIA6urqcMcdd+T8Xl9fjzPOOAObNm3Kd9GMuPjii6Vu4q+//jruu+8+AEx43nnnnT2/T548GalUCul0GkceeSS+++475TEaGxvx2GOPadchCIIgCIKICoppSRAEQRAEERGHHXYYWrRogXXr1uGTTz4BwLIpH3TQQcptfv/73+P111/HnDlzcNttt2HmzJmYNGkShg0bhpqaGvz888/45JNP8Oqrr+KFF17AkCFDMuKhy3XXXYdXXnkFCxYswJ133onZs2fj17/+NYYMGYKKigp89913ePPNN/HEE0/g+uuvxymnnJLZtmfPnujevTu+++473HzzzejevTsGDBiQcXXv1KlTxnX66quvxrPPPotvvvkG11xzDRYsWIBTTz0VXbp0waJFi3DnnXdi5syZAIBRo0bhzDPPjPDqxssBBxyAXr16YcmSJbjqqquwcuVKHH744aiqqsInn3yC22+/HR988AF23XVXvPPOO4UurocddtgBCxcuxIgRIzB58mTssssuqK2txbRp03DrrbeioaEBZWVluOuuu3K2HTJkCG6++WZcdNFFWLhwIbbffnuceeaZ2HvvvdGpUyds3rwZixcvxuzZs/H0009j2bJlWLBgQcGTQREEQRAE0fQh0ZIgCIIgCCIimjVrhiOPPBIPPvhgZtnRRx+NyspK5TaVlZV45ZVXcMopp+DZZ5/Fhx9+qLVQbNmyZc6y6upqzJgxA0cccQTeeOMNzJs3z0owvPLKK3HOOedg0aJFOOSQQzy/PfjggxmRs0WLFpg+fTr2339/fPbZZ3jmmWfwzDPP5Oxv9OjR+Pe//11SmaQrKirw6KOPYvz48diwYQNuvfVW3HrrrZnfU6kU/vznP2P16tVFJ1oOGzYM5513Hs4++2xp3amoqMDDDz+MkSNHSre/8MILUVNTgwsvvBBr167FTTfdhJtuukm6bkVFhSekAEEQBEEQRFyQezhBEARBEESEnHzyyZ7vKtdwnhYtWuCZZ57Bm2++iTPOOAMDBgxAixYtUFZWhrZt22LnnXfGueeei2nTpiljKrZv3x6vv/46nn32WRx55JHo3r07KisrUVVVhb59++Koo47CY489Jk0IdPbZZ+OZZ57Bvvvui44dO6KsTP1eu3fv3vjwww9x5513YuzYsWjXrh3Ky8vRqVMnjB8/Ho888gjeeOONkskazrP77rtj3rx5OOmkk9C1a1eUl5ejS5cuGTH4/PPPL3QRlZxxxhl48803cfTRR6Nr166oqKhAt27dMHHiRHzwwQc49thjtdtPmjQJ33zzDa699lqMHj0a7du3R1lZGWpqatC/f38cccQRuOeee/D999+jX79+eTorgiAIgiC2ZhJOkIjvBEEQBEEQBEEQBEEQBEEQMUGWlgRBEARBEARBEARBEARBFBUkWhIEQRAEQRAEQRAEQRAEUVSQaEkQBEEQBEEQBEEQBEEQRFFBoiVBEARBEARBEARBEARBEEUFiZYEQRAEQRAEQRAEQRAEQRQVJFoSBEEQBEEQBEEQBEEQBFFUkGhJEARBEARBEARBEARBEERRQaIlQRAEQRAEQRAEQRAEQRBFBYmWBEEQBEEQBEEQBEEQBEEUFSRaEgRBEARBEARBEARBEARRVJBoSRAEQRAEQRAEQRAEQRBEUUGiJUEQBEEQBEEQBEEQBEEQRQWJlgRBEARBEARBEARBEARBFBUkWhIEQRAEQRAEQRAEQRAEUVT8f1D+3iUehuAcAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 6) Сделать вывод о пригодности обученного автокодировщика для качественного обнаружения аномалий. Если порог ошибки реконструкции слишком велик, то подобрать подходящие параметры автокодировщика и повторить шаги (4) – (6)."
      ],
      "metadata": {
        "id": "DGBM9xNFo-4k"
      },
      "id": "DGBM9xNFo-4k"
    },
    {
      "cell_type": "code",
      "source": [
        "# **kwargs\n",
        "# verbose_every_n_epochs - отображать прогресс каждые N эпох (по умолчанию - 1000)\n",
        "# early_stopping_delta - дельта для ранней остановки (по умолчанию - 0.01)\n",
        "# early_stopping_value = значение для ранней остановки (по умолчанию -  0.0001)\n",
        "\n",
        "from time import time\n",
        "\n",
        "patience = 4000\n",
        "start = time()\n",
        "ae3_v2_trained, IRE3_v2, IREth3_v2 = lib.create_fit_save_ae(train,'out/AE3_V2.h5','out/AE3_v2_ire_th.txt',\n",
        "100000, False, patience, early_stopping_delta = 0.001)\n",
        "print(\"Время на обучение: \", time() - start)"
      ],
      "metadata": {
        "id": "ZvM1VbKEgalO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d5e2632a-b541-47ec-dcc4-434aacfecaf5"
      },
      "id": "ZvM1VbKEgalO",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Задать архитектуру автокодировщиков или использовать архитектуру по умолчанию? (1/2): 1\n",
            "Задайте количество скрытых слоёв (нечетное число) : 11\n",
            "Задайте архитектуру скрытых слоёв автокодировщика, например, в виде 3 1 3 : 48 36 28 22 16 10 16 22 28 36 48\n",
            "\n",
            "Epoch 1000/100000\n",
            " - loss: 0.0554\n",
            "\n",
            "Epoch 2000/100000\n",
            " - loss: 0.0276\n",
            "\n",
            "Epoch 3000/100000\n",
            " - loss: 0.0217\n",
            "\n",
            "Epoch 4000/100000\n",
            " - loss: 0.0195\n",
            "\n",
            "Epoch 5000/100000\n",
            " - loss: 0.0179\n",
            "\n",
            "Epoch 6000/100000\n",
            " - loss: 0.0166\n",
            "\n",
            "Epoch 7000/100000\n",
            " - loss: 0.0157\n",
            "\n",
            "Epoch 8000/100000\n",
            " - loss: 0.0151\n",
            "\n",
            "Epoch 9000/100000\n",
            " - loss: 0.0144\n",
            "\n",
            "Epoch 10000/100000\n",
            " - loss: 0.0139\n",
            "\n",
            "Epoch 11000/100000\n",
            " - loss: 0.0135\n",
            "\n",
            "Epoch 12000/100000\n",
            " - loss: 0.0131\n",
            "\n",
            "Epoch 13000/100000\n",
            " - loss: 0.0131\n",
            "\n",
            "Epoch 14000/100000\n",
            " - loss: 0.0128\n",
            "\n",
            "Epoch 15000/100000\n",
            " - loss: 0.0117\n",
            "\n",
            "Epoch 16000/100000\n",
            " - loss: 0.0119\n",
            "\n",
            "Epoch 17000/100000\n",
            " - loss: 0.0108\n",
            "\n",
            "Epoch 18000/100000\n",
            " - loss: 0.0103\n",
            "\n",
            "Epoch 19000/100000\n",
            " - loss: 0.0100\n",
            "\n",
            "Epoch 20000/100000\n",
            " - loss: 0.0100\n",
            "\n",
            "Epoch 21000/100000\n",
            " - loss: 0.0094\n",
            "\n",
            "Epoch 22000/100000\n",
            " - loss: 0.0090\n",
            "\n",
            "Epoch 23000/100000\n",
            " - loss: 0.0090\n",
            "\n",
            "Epoch 24000/100000\n",
            " - loss: 0.0098\n",
            "\u001b[1m52/52\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:absl:You are saving your model as an HDF5 file via `model.save()` or `keras.saving.save_model(model)`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')` or `keras.saving.save_model(model, 'my_model.keras')`. \n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n",
            "Время на обучение:  1065.6178832054138\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Скрытых слоев 7, нейроны: 48->36->28->22->16->12->16->22->28->36->48\n",
        "\n",
        "Ошибка MSE_AE3_v1 = 0.0098"
      ],
      "metadata": {
        "id": "9BrPUb_8fX5R"
      },
      "id": "9BrPUb_8fX5R"
    },
    {
      "cell_type": "code",
      "source": [
        "# Построение графика ошибки реконструкции\n",
        "lib.ire_plot('training', IRE3_v2, IREth3_v2, 'AE3_v2')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 724
        },
        "id": "kh1eMtvpf6F-",
        "outputId": "f4226ec6-4667-4280-ef13-f87c28dc13f6"
      },
      "id": "kh1eMtvpf6F-",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 7) Изучить и загрузить тестовую выборку Cardio.txt."
      ],
      "metadata": {
        "id": "vJvW1mOtpgFO"
      },
      "id": "vJvW1mOtpgFO"
    },
    {
      "cell_type": "code",
      "source": [
        "#загрузка тестовой выборки\n",
        "test = np.loadtxt('data/cardio_test.txt', dtype=float)\n",
        "print('\\n test:\\n', test)\n",
        "print('test.shape:', np.shape(test))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GrXQ5YymtD2u",
        "outputId": "47e6519f-3133-4eb0-c955-64df75880f72"
      },
      "id": "GrXQ5YymtD2u",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            " test:\n",
            " [[ 0.21654639 -0.65465178 -0.20364049 ... -2.0444214   4.987467\n",
            "  -0.49329397]\n",
            " [ 0.21654639 -0.5653379  -0.20364049 ... -2.1133887   6.490482\n",
            "  -0.49329397]\n",
            " [-0.3125388  -0.91998844  6.9653692  ... -1.1478471   3.9186563\n",
            "  -0.49329397]\n",
            " ...\n",
            " [-0.41835583 -0.91998844 -0.16463485 ... -1.4926834   0.24461959\n",
            "  -0.49329397]\n",
            " [-0.41835583 -0.91998844 -0.15093411 ... -1.4237162   0.14441859\n",
            "  -0.49329397]\n",
            " [-0.41835583 -0.91998844 -0.20364049 ... -1.2857816   3.5846529\n",
            "  -0.49329397]]\n",
            "test.shape: (109, 21)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 8) Подать тестовую выборку на вход обученного автокодировщика для обнаружения аномалий. Вывести график ошибки реконструкции элементов тестовой выборки относительно порога."
      ],
      "metadata": {
        "id": "6iqO4Yxbpgob"
      },
      "id": "6iqO4Yxbpgob"
    },
    {
      "cell_type": "code",
      "source": [
        "# тестирование АE3\n",
        "predicted_labels3_v1, ire3_v1 = lib.predict_ae(ae3_v1_trained, test, IREth3_v1)"
      ],
      "metadata": {
        "id": "Vxj1fTAikDuU",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "595470a6-9824-43d6-90af-89d584c971e3"
      },
      "id": "Vxj1fTAikDuU",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m4/4\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 8ms/step \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Построение графика ошибки реконструкции\n",
        "lib.ire_plot('test', ire3_v1, IREth3_v1, 'AE3_v1')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 727
        },
        "id": "21DdnIKYtmtM",
        "outputId": "2de5d71c-bd32-4899-c902-7af454334fd1"
      },
      "id": "21DdnIKYtmtM",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# тестирование АE3\n",
        "predicted_labels3_v2, ire3_v2 = lib.predict_ae(ae3_v2_trained, test, IREth3_v2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ql1JMAM6sf7Z",
        "outputId": "28a32237-a652-410a-d768-4088d74ac238"
      },
      "id": "Ql1JMAM6sf7Z",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m4/4\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 6ms/step \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Построение графика ошибки реконструкции\n",
        "lib.ire_plot('test', ire3_v2, IREth3_v2, 'AE3_v2')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 727
        },
        "id": "jczBRWjTt35R",
        "outputId": "d63185b5-9904-4e31-c77e-afc23b63f7dd"
      },
      "id": "jczBRWjTt35R",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# тестирование АE2\n",
        "lib.anomaly_detection_ae(predicted_labels3_v1, IRE3_v1, IREth3_v1)"
      ],
      "metadata": {
        "id": "2kF1XknIpg48",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4a05ee5a-54d0-4995-b7b7-8190fa974b23"
      },
      "id": "2kF1XknIpg48",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "i         Labels    IRE       IREth     \n",
            "0         [1.]      0.59      1.75      \n",
            "1         [1.]      0.61      1.75      \n",
            "2         [1.]      0.69      1.75      \n",
            "3         [1.]      0.71      1.75      \n",
            "4         [1.]      1.57      1.75      \n",
            "5         [1.]      0.6       1.75      \n",
            "6         [1.]      0.68      1.75      \n",
            "7         [1.]      0.66      1.75      \n",
            "8         [1.]      0.7       1.75      \n",
            "9         [1.]      0.62      1.75      \n",
            "10        [1.]      0.51      1.75      \n",
            "11        [1.]      0.82      1.75      \n",
            "12        [1.]      0.75      1.75      \n",
            "13        [1.]      0.63      1.75      \n",
            "14        [1.]      0.59      1.75      \n",
            "15        [1.]      1.13      1.75      \n",
            "16        [1.]      0.66      1.75      \n",
            "17        [1.]      1.12      1.75      \n",
            "18        [1.]      0.57      1.75      \n",
            "19        [1.]      0.78      1.75      \n",
            "20        [1.]      0.57      1.75      \n",
            "21        [1.]      0.29      1.75      \n",
            "22        [1.]      0.48      1.75      \n",
            "23        [1.]      0.99      1.75      \n",
            "24        [1.]      0.66      1.75      \n",
            "25        [1.]      0.86      1.75      \n",
            "26        [1.]      0.59      1.75      \n",
            "27        [1.]      0.77      1.75      \n",
            "28        [1.]      0.69      1.75      \n",
            "29        [0.]      0.45      1.75      \n",
            "30        [1.]      0.4       1.75      \n",
            "31        [1.]      0.87      1.75      \n",
            "32        [1.]      0.54      1.75      \n",
            "33        [1.]      0.29      1.75      \n",
            "34        [1.]      0.93      1.75      \n",
            "35        [1.]      0.3       1.75      \n",
            "36        [1.]      0.17      1.75      \n",
            "37        [1.]      0.74      1.75      \n",
            "38        [0.]      0.28      1.75      \n",
            "39        [0.]      0.34      1.75      \n",
            "40        [0.]      0.35      1.75      \n",
            "41        [0.]      0.5       1.75      \n",
            "42        [1.]      0.82      1.75      \n",
            "43        [1.]      0.36      1.75      \n",
            "44        [1.]      1.12      1.75      \n",
            "45        [1.]      0.34      1.75      \n",
            "46        [1.]      0.34      1.75      \n",
            "47        [1.]      0.75      1.75      \n",
            "48        [1.]      0.56      1.75      \n",
            "49        [1.]      0.37      1.75      \n",
            "50        [1.]      0.3       1.75      \n",
            "51        [1.]      0.3       1.75      \n",
            "52        [1.]      0.65      1.75      \n",
            "53        [1.]      0.5       1.75      \n",
            "54        [0.]      0.21      1.75      \n",
            "55        [1.]      1.06      1.75      \n",
            "56        [1.]      0.4       1.75      \n",
            "57        [1.]      0.6       1.75      \n",
            "58        [1.]      0.6       1.75      \n",
            "59        [1.]      0.67      1.75      \n",
            "60        [1.]      0.55      1.75      \n",
            "61        [0.]      0.24      1.75      \n",
            "62        [0.]      0.64      1.75      \n",
            "63        [0.]      1.75      1.75      \n",
            "64        [0.]      0.89      1.75      \n",
            "65        [0.]      0.38      1.75      \n",
            "66        [1.]      0.56      1.75      \n",
            "67        [1.]      0.73      1.75      \n",
            "68        [1.]      0.49      1.75      \n",
            "69        [1.]      0.47      1.75      \n",
            "70        [1.]      0.26      1.75      \n",
            "71        [1.]      0.51      1.75      \n",
            "72        [1.]      0.83      1.75      \n",
            "73        [1.]      0.71      1.75      \n",
            "74        [0.]      0.4       1.75      \n",
            "75        [0.]      1.28      1.75      \n",
            "76        [1.]      0.42      1.75      \n",
            "77        [1.]      1.34      1.75      \n",
            "78        [1.]      0.55      1.75      \n",
            "79        [1.]      0.92      1.75      \n",
            "80        [1.]      0.65      1.75      \n",
            "81        [1.]      0.82      1.75      \n",
            "82        [1.]      1.23      1.75      \n",
            "83        [1.]      0.4       1.75      \n",
            "84        [1.]      0.49      1.75      \n",
            "85        [1.]      0.47      1.75      \n",
            "86        [1.]      0.45      1.75      \n",
            "87        [1.]      0.69      1.75      \n",
            "88        [1.]      0.58      1.75      \n",
            "89        [1.]      0.76      1.75      \n",
            "90        [1.]      0.57      1.75      \n",
            "91        [1.]      0.33      1.75      \n",
            "92        [1.]      0.57      1.75      \n",
            "93        [1.]      0.48      1.75      \n",
            "94        [1.]      0.31      1.75      \n",
            "95        [1.]      0.42      1.75      \n",
            "96        [1.]      0.43      1.75      \n",
            "97        [1.]      0.51      1.75      \n",
            "98        [1.]      0.46      1.75      \n",
            "99        [1.]      0.43      1.75      \n",
            "100       [1.]      0.54      1.75      \n",
            "101       [1.]      0.63      1.75      \n",
            "102       [1.]      0.47      1.75      \n",
            "103       [1.]      0.51      1.75      \n",
            "104       [1.]      0.49      1.75      \n",
            "105       [1.]      0.25      1.75      \n",
            "106       [1.]      0.16      1.75      \n",
            "107       [1.]      0.2       1.75      \n",
            "108       [1.]      0.7       1.75      \n",
            "Обнаружено  96.0  аномалий\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Для AE3_v1 точность составляет 88%"
      ],
      "metadata": {
        "id": "LXHt7-gxuJIy"
      },
      "id": "LXHt7-gxuJIy"
    },
    {
      "cell_type": "code",
      "source": [
        "# тестирование АE2\n",
        "lib.anomaly_detection_ae(predicted_labels3_v2, IRE3_v2, IREth3_v2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5ow1D88nsrir",
        "outputId": "cc278276-2b8e-4ae0-b723-81718aed5542"
      },
      "id": "5ow1D88nsrir",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "i         Labels    IRE       IREth     \n",
            "0         [1.]      0.69      1.6       \n",
            "1         [1.]      0.81      1.6       \n",
            "2         [1.]      0.51      1.6       \n",
            "3         [1.]      0.62      1.6       \n",
            "4         [1.]      1.6       1.6       \n",
            "5         [1.]      0.34      1.6       \n",
            "6         [1.]      0.51      1.6       \n",
            "7         [1.]      0.49      1.6       \n",
            "8         [1.]      0.5       1.6       \n",
            "9         [1.]      0.45      1.6       \n",
            "10        [1.]      0.4       1.6       \n",
            "11        [1.]      0.3       1.6       \n",
            "12        [1.]      0.7       1.6       \n",
            "13        [1.]      0.54      1.6       \n",
            "14        [1.]      0.59      1.6       \n",
            "15        [1.]      0.64      1.6       \n",
            "16        [1.]      0.4       1.6       \n",
            "17        [1.]      0.73      1.6       \n",
            "18        [1.]      0.86      1.6       \n",
            "19        [1.]      0.45      1.6       \n",
            "20        [1.]      0.71      1.6       \n",
            "21        [1.]      0.33      1.6       \n",
            "22        [1.]      0.49      1.6       \n",
            "23        [1.]      0.83      1.6       \n",
            "24        [1.]      0.65      1.6       \n",
            "25        [1.]      0.92      1.6       \n",
            "26        [1.]      0.41      1.6       \n",
            "27        [1.]      0.48      1.6       \n",
            "28        [1.]      0.51      1.6       \n",
            "29        [0.]      0.42      1.6       \n",
            "30        [1.]      0.35      1.6       \n",
            "31        [1.]      0.4       1.6       \n",
            "32        [1.]      0.42      1.6       \n",
            "33        [1.]      0.29      1.6       \n",
            "34        [1.]      0.48      1.6       \n",
            "35        [1.]      0.28      1.6       \n",
            "36        [1.]      0.14      1.6       \n",
            "37        [1.]      0.55      1.6       \n",
            "38        [0.]      0.26      1.6       \n",
            "39        [0.]      0.32      1.6       \n",
            "40        [0.]      0.23      1.6       \n",
            "41        [0.]      0.43      1.6       \n",
            "42        [1.]      0.46      1.6       \n",
            "43        [1.]      0.26      1.6       \n",
            "44        [1.]      0.92      1.6       \n",
            "45        [1.]      0.34      1.6       \n",
            "46        [1.]      0.34      1.6       \n",
            "47        [1.]      0.69      1.6       \n",
            "48        [0.]      0.49      1.6       \n",
            "49        [1.]      0.44      1.6       \n",
            "50        [1.]      0.31      1.6       \n",
            "51        [1.]      0.54      1.6       \n",
            "52        [1.]      0.66      1.6       \n",
            "53        [1.]      0.45      1.6       \n",
            "54        [0.]      0.26      1.6       \n",
            "55        [1.]      0.44      1.6       \n",
            "56        [1.]      0.45      1.6       \n",
            "57        [1.]      0.48      1.6       \n",
            "58        [1.]      0.68      1.6       \n",
            "59        [1.]      0.75      1.6       \n",
            "60        [1.]      0.5       1.6       \n",
            "61        [0.]      0.34      1.6       \n",
            "62        [1.]      0.33      1.6       \n",
            "63        [1.]      0.54      1.6       \n",
            "64        [1.]      0.57      1.6       \n",
            "65        [1.]      0.36      1.6       \n",
            "66        [1.]      0.48      1.6       \n",
            "67        [1.]      0.66      1.6       \n",
            "68        [1.]      0.36      1.6       \n",
            "69        [1.]      0.53      1.6       \n",
            "70        [1.]      0.25      1.6       \n",
            "71        [1.]      0.58      1.6       \n",
            "72        [1.]      0.47      1.6       \n",
            "73        [1.]      0.45      1.6       \n",
            "74        [1.]      0.46      1.6       \n",
            "75        [1.]      1.04      1.6       \n",
            "76        [1.]      0.25      1.6       \n",
            "77        [1.]      0.99      1.6       \n",
            "78        [1.]      0.37      1.6       \n",
            "79        [1.]      0.52      1.6       \n",
            "80        [1.]      0.39      1.6       \n",
            "81        [1.]      0.52      1.6       \n",
            "82        [1.]      0.59      1.6       \n",
            "83        [1.]      0.38      1.6       \n",
            "84        [1.]      0.44      1.6       \n",
            "85        [1.]      0.45      1.6       \n",
            "86        [1.]      0.41      1.6       \n",
            "87        [1.]      0.55      1.6       \n",
            "88        [1.]      0.61      1.6       \n",
            "89        [1.]      0.75      1.6       \n",
            "90        [1.]      0.4       1.6       \n",
            "91        [1.]      0.23      1.6       \n",
            "92        [1.]      0.36      1.6       \n",
            "93        [1.]      0.39      1.6       \n",
            "94        [1.]      0.22      1.6       \n",
            "95        [1.]      0.43      1.6       \n",
            "96        [1.]      0.44      1.6       \n",
            "97        [1.]      0.43      1.6       \n",
            "98        [1.]      0.41      1.6       \n",
            "99        [1.]      0.54      1.6       \n",
            "100       [1.]      0.48      1.6       \n",
            "101       [1.]      0.45      1.6       \n",
            "102       [1.]      0.34      1.6       \n",
            "103       [1.]      0.4       1.6       \n",
            "104       [1.]      0.46      1.6       \n",
            "105       [1.]      0.33      1.6       \n",
            "106       [1.]      0.19      1.6       \n",
            "107       [1.]      0.21      1.6       \n",
            "108       [1.]      0.62      1.6       \n",
            "Обнаружено  101.0  аномалий\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Для AE3_v2 точность составляет 92%"
      ],
      "metadata": {
        "id": "LDsC5WyeuRHS"
      },
      "id": "LDsC5WyeuRHS"
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 9) Если результаты обнаружения аномалий не удовлетворительные (обнаружено менее 70% аномалий), то подобрать подходящие параметры автокодировщика и повторить шаги (4) – (9)."
      ],
      "metadata": {
        "id": "fPPbYwnQpqS3"
      },
      "id": "fPPbYwnQpqS3"
    },
    {
      "cell_type": "markdown",
      "source": [
        "Результаты обнаружения аномалий удовлетворены."
      ],
      "metadata": {
        "id": "IVmw2aeduXml"
      },
      "id": "IVmw2aeduXml"
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 10) Параметры наилучшего автокодировщика и результаты обнаружения аномалий занести в таблицу:\n",
        "Табл. 2 Результаты задания №2"
      ],
      "metadata": {
        "id": "u3cAX_IgpvWU"
      },
      "id": "u3cAX_IgpvWU"
    },
    {
      "cell_type": "markdown",
      "source": [
        "| Dataset name | Количество<br>скрытых слоев | Количество<br>нейронов в скрытых слоях | Количество<br>эпох обучения | Ошибка<br>MSE_stop | Порог ошибки<br>реконструкции | % обнаруженных<br>аномалий |\n",
        "|:-------------|:-----------------------------|:----------------------------------------|:-----------------------------|:-------------------|:-------------------------------|:---------------------------|\n",
        "| Cardio       | 11                             | 48, 36, 28, 22, 16, 10, 16, 22, 28, 36, 48              | 100000                      | 0.0098              | 1.6                           | 92%                      |\n"
      ],
      "metadata": {
        "id": "tryfJdjTvgU8"
      },
      "id": "tryfJdjTvgU8"
    },
    {
      "cell_type": "markdown",
      "source": [
        "### 11) Сделать выводы о требованиях к:\n",
        "- данным для обучения,\n",
        "- архитектуре автокодировщика,  \n",
        "- количеству эпох обучения,\n",
        "- ошибке MSE_stop, приемлемой для останова обучения,\n",
        "- ошибке реконструкции обучающей выборки (порогу обнаружения\n",
        "аномалий)\n",
        "\n",
        "для качественного обнаружения аномалий в случае, когда размерность\n",
        "пространства признаков высока."
      ],
      "metadata": {
        "id": "eE7IYyGJp0Vv"
      },
      "id": "eE7IYyGJp0Vv"
    },
    {
      "cell_type": "markdown",
      "source": [
        "1) Данные для обучения должны быть без аномалий, чтобы автокодировщик смог рассчитать верное пороговое значение\n",
        "2) Архитектура автокодировщика должна постепенно сужатся к бутылочному горлышку,а затем постепенно возвращатся к исходным выходным размерам, кол-во скрытых слоев 7-11.\n",
        "3) В рамках данного набора данных оптимальное кол-во эпох 100000 с patience 4000 эпох\n",
        "4) Оптимальная ошибка MSE-stop в районе 0.001, желательно не меньше для предотвращения переобучения\n",
        "5) Значение порога не больше 1.6"
      ],
      "metadata": {
        "id": "67p7AeSWwVXE"
      },
      "id": "67p7AeSWwVXE"
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.12.3"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 5
}