material/deep_learning/mnet_segementation.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "mnet_segementation.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HYzKnHXzN0lB"
      },
      "source": [
        "# 폐 영역분할"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ROQ8VnQXGeU4"
      },
      "source": [
        "다음의 2019 대한의료인공지능학회 Summer School에서 진행한 AI hands-on의 자료에서 코드르 가져와서 수정함.\n",
        "\n",
        "https://github.com/mi2rl/ai_handson/blob/main/KoSAIM_Summer_School_2019_Handson_03_Segmentation.ipynb\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bMHwQjK9OhLf"
      },
      "source": [
        "## 폐 데이터 다운로드\n",
        "\n",
        "다음에서 다운받은 데이터\n",
        "\n",
        "https://www.kaggle.com/nikhilpandey360/lung-segmentation-from-chest-x-ray-dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EAKPT_j5GITc",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bbd7e81f-2577-48d0-9d10-10efe0ee49ce"
      },
      "source": [
        "!rm -rf Lung_Segmentation.zip\n",
        "!wget https://github.com/dhrim/2022_WISET/raw/main/material/deep_learning/Lung_Segmentation.zip"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2022-07-12 06:41:19--  https://github.com/dhrim/2022_WISET/raw/main/material/deep_learning/Lung_Segmentation.zip\n",
            "Resolving github.com (github.com)... 140.82.121.3\n",
            "Connecting to github.com (github.com)|140.82.121.3|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://raw.githubusercontent.com/dhrim/2022_WISET/main/material/deep_learning/Lung_Segmentation.zip [following]\n",
            "--2022-07-12 06:41:19--  https://raw.githubusercontent.com/dhrim/2022_WISET/main/material/deep_learning/Lung_Segmentation.zip\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 37648324 (36M) [application/zip]\n",
            "Saving to: ‘Lung_Segmentation.zip’\n",
            "\n",
            "Lung_Segmentation.z 100%[===================>]  35.90M  --.-KB/s    in 0.1s    \n",
            "\n",
            "2022-07-12 06:41:21 (312 MB/s) - ‘Lung_Segmentation.zip’ saved [37648324/37648324]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N8TLRtBfGsKj",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "71da3d5c-82b5-4d30-d0e8-0bdea3ae1fb7"
      },
      "source": [
        "!rm -rf Lung_Segmentation\n",
        "!unzip Lung_Segmentation.zip"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  Lung_Segmentation.zip\n",
            "   creating: Lung_Segmentation/\n",
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            "  inflating: Lung_Segmentation/image/CHNCXR_0279_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0280_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0281_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0282_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0283_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0284_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0285_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0286_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0287_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0288_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0289_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0290_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0291_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0292_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0293_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0294_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0295_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0296_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0297_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0298_0.png  \n",
            " extracting: Lung_Segmentation/image/CHNCXR_0299_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0300_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0301_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0302_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0303_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0304_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0305_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0306_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0307_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0308_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0309_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0310_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0311_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0312_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0313_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0314_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0315_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0316_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0317_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0318_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0319_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0320_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0321_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0322_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0323_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0324_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0325_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0326_0.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0327_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0328_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0329_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0330_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0331_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0332_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0333_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0334_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0335_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0337_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0338_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0339_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0340_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0361_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0362_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0363_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0364_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0365_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0366_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0367_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0368_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0369_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0370_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0371_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0372_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0373_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0374_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0375_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0376_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0377_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0378_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0379_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0380_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0381_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0382_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0383_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0384_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0385_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0386_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0387_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0388_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0389_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0390_1.png  \n",
            " extracting: Lung_Segmentation/image/CHNCXR_0391_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0392_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0393_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0394_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0395_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0396_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0397_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0398_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0399_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0400_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0401_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0402_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0403_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0404_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0405_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0406_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0407_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0408_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0409_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0410_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0411_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0412_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0413_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0414_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0415_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0416_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0417_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0418_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0419_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0420_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0421_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0422_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0423_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0424_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0425_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0426_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0427_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0428_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0429_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0430_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0431_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0432_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0433_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0434_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0435_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0436_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0437_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0438_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0439_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0440_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0441_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0442_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0443_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0444_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0445_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0446_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0447_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0448_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0449_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0450_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0451_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0452_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0453_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0454_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0455_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0456_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0457_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0458_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0459_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0460_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0461_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0462_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0463_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0464_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0465_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0466_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0467_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0468_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0469_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0470_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0471_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0472_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0473_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0474_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0475_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0476_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0477_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0478_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0479_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0480_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0501_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0503_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0504_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0506_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0507_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0508_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0509_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0510_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0511_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0512_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0513_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0514_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0515_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0516_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0517_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0518_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0519_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0520_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0521_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0522_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0523_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0524_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0525_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0526_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0527_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0528_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0529_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0530_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0531_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0532_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0533_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0534_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0535_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0536_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0537_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0538_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0539_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0540_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0541_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0542_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0543_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0544_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0545_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0546_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0547_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0548_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0549_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0550_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0551_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0552_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0553_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0554_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0555_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0556_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0557_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0558_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0559_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0566_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0567_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0568_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0569_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0570_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0571_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0572_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0573_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0574_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0575_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0576_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0577_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0578_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0579_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0580_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0581_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0582_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0583_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0584_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0585_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0586_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0587_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0588_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0589_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0590_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0591_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0592_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0593_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0594_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0595_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0596_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0597_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0598_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0599_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0600_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0601_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0602_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0603_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0604_1.png  \n",
            "  inflating: Lung_Segmentation/image/CHNCXR_0605_1.png  \n",
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            "  inflating: Lung_Segmentation/label/CHNCXR_0274_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0275_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0276_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0277_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0278_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0279_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0280_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0281_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0282_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0283_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0284_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0285_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0286_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0287_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0288_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0289_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0290_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0291_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0292_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0293_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0294_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0295_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0296_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0297_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0298_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0299_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0300_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0301_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0302_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0303_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0304_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0305_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0306_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0307_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0308_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0309_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0310_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0311_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0312_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0313_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0314_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0315_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0316_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0317_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0318_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0319_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0320_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0321_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0322_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0323_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0324_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0325_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0326_0.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0327_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0328_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0329_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0330_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0331_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0332_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0333_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0334_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0335_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0337_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0338_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0339_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0340_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0361_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0362_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0363_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0364_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0365_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0366_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0367_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0368_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0369_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0370_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0371_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0372_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0373_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0374_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0375_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0376_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0377_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0378_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0379_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0380_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0381_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0382_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0383_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0384_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0385_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0386_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0387_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0388_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0389_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0390_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0391_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0392_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0393_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0394_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0395_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0396_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0397_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0398_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0399_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0400_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0401_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0402_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0403_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0404_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0405_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0406_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0407_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0408_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0409_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0410_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0411_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0412_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0413_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0414_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0415_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0416_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0417_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0418_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0419_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0420_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0421_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0422_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0423_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0424_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0425_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0426_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0427_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0428_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0429_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0430_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0431_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0432_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0433_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0434_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0435_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0436_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0437_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0438_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0439_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0440_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0441_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0442_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0443_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0444_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0445_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0446_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0447_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0448_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0449_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0450_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0451_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0452_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0453_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0454_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0455_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0456_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0457_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0458_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0459_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0460_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0461_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0462_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0463_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0464_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0465_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0466_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0467_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0468_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0469_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0470_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0471_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0472_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0473_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0474_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0475_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0476_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0477_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0478_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0479_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0480_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0501_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0503_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0504_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0506_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0507_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0508_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0509_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0510_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0511_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0512_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0513_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0514_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0515_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0516_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0517_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0518_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0519_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0520_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0521_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0522_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0523_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0524_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0525_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0526_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0527_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0528_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0529_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0530_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0531_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0532_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0533_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0534_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0535_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0536_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0537_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0538_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0539_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0540_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0541_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0542_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0543_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0544_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0545_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0546_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0547_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0548_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0549_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0550_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0551_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0552_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0553_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0554_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0555_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0556_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0557_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0558_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0559_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0566_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0567_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0568_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0569_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0570_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0571_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0572_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0573_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0574_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0575_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0576_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0577_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0578_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0579_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0580_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0581_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0582_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0583_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0584_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0585_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0586_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0587_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0588_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0589_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0590_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0591_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0592_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0593_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0594_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0595_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0596_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0597_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0598_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0599_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0600_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0601_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0602_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0603_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0604_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0605_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0606_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0607_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0608_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0609_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0610_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0611_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0612_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0613_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0614_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0615_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0616_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0617_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0618_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0619_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0620_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0621_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0622_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0623_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0624_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0625_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0626_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0627_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0628_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0629_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0630_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0631_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0632_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0633_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0634_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0635_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0636_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0637_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0638_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0639_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0640_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0641_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0642_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0643_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0644_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0645_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0646_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0647_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0648_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0649_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0650_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0651_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0652_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0653_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0654_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0655_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0656_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0657_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0658_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0659_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0660_1.png  \n",
            "  inflating: Lung_Segmentation/label/CHNCXR_0661_1.png  \n",
            " extracting: Lung_Segmentation/label/CHNCXR_0662_1.png  \n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AoxCIJscPmAC"
      },
      "source": [
        "## 풀린 데이터 파일 구조\n",
        "\n",
        "```\n",
        "Lung_segmentaiton/\n",
        "  image/\n",
        "    CHNCXR_0001_0.png\n",
        "    CHNCXR_0002_0.png\n",
        "    ...\n",
        "  label/\n",
        "    CHNCXR_0001_0.png\n",
        "    CHNCXR_0002_0.png\n",
        "    ...\n",
        "```"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZN8aC7EMQpDL"
      },
      "source": [
        "## 파일 보기"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IaPaC-FnQKU6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 529
        },
        "outputId": "cd5a2992-5bf1-454c-d27a-551e39be444b"
      },
      "source": [
        "from IPython.display import Image, display\n",
        "\n",
        "display(Image('./Lung_Segmentation/image/CHNCXR_0001_0.png'))\n",
        "display(Image('./Lung_Segmentation/label/CHNCXR_0001_0.png'))\n"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Image object>"
            ],
            "image/png": 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KvgjDRi0M8OA328nk4tWgORSGWrH3wAAk5p31osAUVSe2JPEvyUQAfZC36VX5cp2V2DfGuN1uXcfoug5Mv91ut9st4hhF5gNDQzvlbTzyeDyGrRljZNFiQtEDkzyqHxsY8Kc+SZIitYgs8uqPe/1RDKSfO8eNsAIYHeND1JKFgnfIUvzrv/5rruRVCOGb3/wmAcN2u+UG7HJh74YQdrsd8XHbtsfHx3d3d1dXV9///vdTOfSiWQ3C29zS7Kd/+qefPXtGjTAV6C7h6limsyRQ7t+mZ+QJwdNq89/iHF7Ye8hqOHT7XOfXXK8BeiI3bLMTOBZinhl/itUEVVv7uTh1AFww0WqnUqWtPlCVXXfKmAW1dUG2SlE4+V6S+iQx8jxfLBbwOpum2W63dV3f3d1h1zebjeUgz/PJZAI1FYQAzmnb9uHhwSHNarWaTqekVvokA0he69WrV33fQ8hBeTKRYdBt0Mh+v4e1xmUJslkQ+yL/F0KbQx1XEjMRhPi9s8+gvkxVP8tMURTANqwJN4DPxFFTh0a1DPMczGDj0Ap0G9EliLq/v394eLi7u3v58uXV1RXZaoSTV6ZiiFOi8ezs7PLy0kml7J3ilI39I4ORvuFRfBx+5Bz/ZDJZ6AXixxD6jk1EcQTMM4D1iWLZDNPXkForMOafq9neY8mMHHgidqIUrY38OirXikaSIkgvQoyRQI03GDsRUdiPGyn1fQ/FHxa+wQ+6jQSAHGyVEVAeH2XuVA7rxLLORL5A4ZHmoijI83BjpHpwLzwUVGfDRaSzV8oV/EPszoNYrC36IEbQV6H6o1WaN/ClfIuZKbYgtv32Y8YqQbnvQr0ZCECuUvfBwQEbhPkbjUbz+fzJkyfL5fLg4ABmUSfqaKGKpC8VT09Pr6+vnUl412w/wjbv/iZ1CD8K1OE1Go2Wy+VsNkP0LaN+fodlSCrrOJlMnA/F8FOiYkVy1bNIHGG8ASFBRXvfrb1EkJ9xjGHHEtTnYUIOq8kF5/P5wcGBFYwcueM27tx3ZZ4M11mv16AaxAJNMyJnDRF0x44ABmRuv99jktHwIMBtnTHm4c7RCjQcR4cOt2LdsY/gGeJskvoO63FoDugd0gB+vHe5mII8tU1+IeKGU3YOqHpxEwq9MhH3Qwjj8dgr6WJWr/yS01MIA6rCsozH48VicXZ2tlwuiTQwFn3fs0pvEmWAJ2cPwtulgJDY+1Ti3w2If/RXVVVnZ2eLxWI6nULFwbRjocnbWLKd9Yelg1UGI02n00IdWBZ9Puj4IaqjAjlDgHLlGaMIITaBmZKJvD8INhgWe4+RG8Luvu+5grPaBvE8S6bycwjBmVAYL45HjWe4h+FwSMHVsWBd1w8PD0gzYIz3W22ccu2VisGfjEaj9XpdqKLXq8QLAOtU5udnB0JOMds8ZwmLuFDdw/dfiGFhC+1XIZZRIRZ0IRq5fUWuhAcabiCA2nDDuaLwSg1JbDpy7/8CAdhcLObR0dF8Pi/LcrVa2Xy/cS/2AH7I8F9nPP36EcH9o1eM8fj4+OjoaDqdzmYzZAs7jRmzzGHtsNBExhTGUQ/LfQjBuQiWLFNV2BJvM8z+pZ+1mWcXMxFjbOltsLl/rPtisTg5OQEqgDSs2CHBV2VZ4h/ahD1v/4sokwJaLpdf+MIXKPRAiJjNZqTCeGGG1+t1J+4afDKng3hAw4BGnYrIHOkpCEWWvCiGXK8kJs8bkxYf1MyFLQOtkJCsnFN3Loi0G99o22GTYTMU5HgzVXAxE13XzWaz+XwOvwuYYKnFg2EF+iQr6HQFRhNvAC4FF8GqgHG92Wy8a0WqDdk7ycrwTmLnv1KJ//Z1dHR0cHCARqYQ0+XxtBqFSqDKb260KNIAF6oZroBn9qKD7PkWtp+FcHRVqKPFwM8hL2LBw6axQd/3gHX+u1qtZrPZarVar9f0c4CtScg4T0X05h6AUgz4tm3fe++9q6sr4FlZlhcXFySsuAjwgKJPI450VFm6F/nRRpe6LMrGG0qRo0xGyvN8tVo5G+iQ11UqRyBBUJ4lYiOurq64K+8FRQxKB0FJLRAIadOgojI3Awxj0//qr/7KyAJh+Ou//muc55MnT1A81rxpGjb68PAQXaVIkqYNCB39pFa5pmmgijguKori8PDw9PT0+9///hv/eXZ2RsORQXz2diUrvFPq+p++5vP56enp4eEh3C8bYChfIQTsZVVVuAW8P/lQloxINxMZPaiZK8hH8+r7Hkxi2eXKIQRTGygxGjghTNYZ5yuIsB0hQBSDpcg2B5l8aD/d2xSXLqEZI8GDweDg4MB0a+6Brvwsy6B5FmIWNeomIcdqtABocXoRrTZ2pcuH3Iifzrvp0Dyq3Jsuix0dEDmItEd8wpNOJpO+79FYzE2nJknuweVz1hmhxBA8kqhf/MVf/Nu//dt/+Id/cDD9sz/7s9Pp1J7E2S2+BZuCzNhOGdSRH+e2WZ9cKUSXIGzvSK+dnJyMx+Obm5vsZ37mZ0iDZirgBaU4wjtR7/9UAXBhtvpFMmTBMLGuawJW4w3+FJKcgB29PXih+pfFpVQjrCkr/k1Q4/92u4X9ZsMfkg5uZJeL53mOq/WOcgO0sVIHDcJOPGwn4mFaB3VAAhwKIYDs+75n22g5v7m5gc2W5znpTvx1rx6AqMpX13X4/a7raKU1izMouGxV/ivVos5KkhJZr9cuCLbqWQmiVzgObNSTjt+mXxFbgG02QHJCzIpqOG7NB8Qad/3qr/7q9773vS9/+csOJv/+7/+eMnlQ7ohFRp9BjDxOCAEqoaOvh4eHRp03XnDuCqRKw939/f3d3Z1vcrvd3t/fFyn4yZNe41TWsyTP86O/zs/PJ5PJZDKpxJ7HwuVJfZfCTaawia1Ng55C9AeH/KQjghidQU4Ac4X2G3CjchjRINAZ1B6aqbcDdm4nvmeuDEYQPkSmASTYp6DiYqX2qC4hkDtfSUWWi9zf35PT6DX3gbuiPZIWYaQWDQyyRMvlkly+9eHh4YG9xyQDI20s1+u1KXq4FKdWEWgEAjOB5UaL8qS1zblL6jPz+Zyk7XQ6vb+/56/cAzdmMwSIXywWJiCxZVS+ENO+7589e/ZP//RP//iP/8g6E7amZBPX3RoxN9FJvoJ/wVr2PI70vAsuethwZFnG6Jc3jIFeDPI+aTn7/wXzkOHhWxG+SkTZXCxlQJvfU6pfzumgVoyATB2oQUEwqxPk9bKEu5aLbcJvSISzdtaBNqn2h6SE56AzV3cBexzVC8tfnWJCRJBIa4vLn4eHhxR0AFoAViwx3o/HYS4Tfe5FMvKEW1qv171IH9CkcSBp8tRrhX4eHh5yfYSVxWG5mqah/zAI8T7KATpIs1SQecO7Op3q+KFXTpm+XiATQtyoTRSLhnPLsuyf//mfQZK5Zka4+MCnWBn6HGyqnNhgAauqeu+992KMt7e31P4MnOwc+AhhGCws9ogQK8/zNwndVNC7t6k7/9PXl770pcPDQ1i+fcIYCUKBSGemkVKVhrqU4hQ42EXy8B7sdBTB3Ztti8LFTdLis6vVitiIGMOgH2mg74nFcqo+JOxRm5+2beGlBdUTAACpsOZqGs5V0jLYI06g252WFyK5rut2u910OsUEQGFwPB2SRj4SR4zTYbmIRmIyAwdDXumFgTg+Pr69vQW6cKsxoQfnSkV4zQHDzm+mqffFYkGDDnvnGkLXdQA2F16wzUGNv6hKajVcPCZqz7IM4gNq1qkS3CspzFLAelgul4eHh1mWwaGKMc5ms8PDw/1+T1oC/0CtvRHB++HhYTab4Yc3m81kMuHO/1+TW69Opf+19J+dnb333numcNoYZ0pT9H0/m81MlyeySaXHt2X0H5LgKapaaYeQJfSSIJvqTPb9/T3hP1tiPMDVzP7gN8SjfLtdincChilze0AUWCxEBJ+Ai+dO2BgiSJ6r0jwcl5+rqrq7u8MXc2/T6fTq6grvF9UiTFLIkQzSM5lMnL3pRKznbhm+sl6vgVtBHGMaTeq6BrAtFovVatWJq4OOUTRwKOiUJZm0oJA0JGyxk5MTMJLF1BELquIUEwQQfzYFw13Xkb0IITDGhvjHLWMOrGOMr1+/ZmG5f+SKK8xmM5yMfddmsxkOhxcXF9fX19wPCRWSdTHGN6WHLmml+V9If4zxF37hF+bzucmrBOCVWkJbdYsDiiw9CJZj0KgWEyfR+LdQtZKvc5iPsLpEau+GpXR5KKoa4ESesYc3A3XiPk2IsOYQEDcJo4t1pwUEagYqV2gSAbeXoljgwWq1MhQkDn7x4sVsNnvx4kWWZWdnZyEEyNKdGhG5GZrC6rrGu3In5PiiujdN73FC06kCFiSKbcXTIUy2yoCf1LjYRpgHcXt7yzpj6YyzM7E8gooGdhGZKmiz2SyoaJCrM8ZP6lRm0zQQpZCETPUBbnK321FFXa1WACQWwcEMoIOo5vDwsOu6p0+fnp6efuc73+FJTepumib7mZ/5mY8//pgpkD880nXMlL5nOp3+/M//PKNdooqpDvssuAQcmZLNeFtbZWSa1sGoTCUft2mPIjO6emJxr9VB53pWlmWkih8eHipNhUhRdZeQdtJwM4VVrjLO53P7K2fTWrFtDw8P2QZaTGx7TCzL8xyPB0HDuo3Lvr299TBNpJMWsNlsRlK4VfcZUfJ4PCZmwLrbjg6Hw9vb2+FwOJlMbm5usqS4gdihDPDqHAvd39+DyqLSkaynsQdBOdlb0sRou9UGXppBRKbymS3FYDC4vr7OldyjHofDxPLCG++Uhev14tvBWtaEoYYLufOGTdnv95eXlyh2URREU1zBrizP808++YQv3Ww2yPybOkCjcUg/RPqdOwshLBaLp0+f/uRP/uSP//iPTyaT5XJpV2CHaHGnNaQUf9BWmUWh/MFCYxK4E9t4omEj15jwFzIxxe1nSI3zOP66SgNCgpozsqR/Kk96qO2aKCBkqiREkSMaTZVbLBbAPDTEElyJrDoajW5vb6PqNTyRZ6tgye7u7ojMXIs15qYY4rQGZbgYI8k7xy1ITBp1sK+lGBwALW4JbTc6z8UfCW9zE5yjw4S78ML0DSQP9QM3AkG32y02mDcziKDTfCHcI+kXfNH9/f12uyUWx2D36q4mAkGUB+rhHmgIMRuB/XYOIMsyyhR0h1pgWEw8aghhMpngnws1DMbz83MUoE2mDv1ABajrerFYHB8fv//++1/+8pe//OUvM7gCY5ZriFou4gBLk6tEn4mQ4x9KDVrzz1nSL+viVC4ySRQnls0z/vFjF+K0cakQAlZnMBgsl0tQSiV6qd+Tq+bAG1xi45ag8ueiUoLZFosFtjDLsu12C5KhS6sVaQfcTAQclMGgoEv+AadHO3yuNhob9bOzMwey7D20TctuJr4TvIm2bbGjeHJ3IzjN5edFDUzzzlQPcdEwS7jT/Pf4+Hg6nWLagirB6ZUxvXBVJpNJqfbrpmlWqxUjJ5ATRAVYiC2gT9K5EO+12TGlZhSkQoJRSMfIEU2dnJysVitDcReAMY7AKot0lmVvak/dDyW3nZ+fuzH39PQUwnohSmAqrwhr0zTQ34F0ho+sC72OtQY4sqNDzQSvRG1tNKUsU13D4IePsxkGXfa8pXpeUVocC04GtmYQDO3VqFGrUySIxcnFGddTiNvcqw6KHDO3MChBgT0mV2h0G2M8OTkB5Nzf3xO8Ip2ZUjFm9a3Xaz4L1MHDELzaJOearxbFmwpqCXd1FlHG9DKqlvAAI4UoNOoOxWnTTmXGHtYa57ZYLJDIu7s7E1QxDQ8PD6Roy7JcLBY8FB646zryXXXSY4AXAuLzqVKNFg4JUE4KAjDGUy89HA4fHh7sH9DV7XbL/NYQwmazef/99+2u8ZCXl5dt2/JE5+fnr169ippXUORvZ8HT12g0Oj4+nkwmRVEcHx9jiojW7VwQaBK3vUaDEIxjh9g2Y+tWI7/LsqQfAhJL8/akA9f/WAiEydmJLmnByVUZaJLhwLwMsUDhjHF1iimIoBY0LiGqoFZpPgo2vVuGcwAAIABJREFUOKjmRajDk7q8D+Jcr9ckjpztCZoUa71FkrAX7O7BwQGCDmNxtVoBZIEZbkDj6/h3uVwi/Sw1s9NQ70JEYiR+MpnA881EsXT2KdfQOypiIRmChFyenZ0VGnfnVBg67LgWk08l20nk7XZ7dXVF+Y/Qq9AcHm4A/OaNc8YmU96JhK/bKXkRO+E0omiedM+RS2B9KLnc399zn4hWXdd2znmekxfqRZgt+rdHLvJaLBZQGMhJmcSC/euUkmfF0UgYaYgvG4DQY55dEWTnYKfVdU2dyJl1CjfpQDznLqJyQZnaPgo16fI2qlG2YU7CYhvQscvLSxxur/Qr5tDxfasSMvfZink2m82KokAcWcrhcIhFz/N8uVySfOT2wDzj8djJbydqEK+qqsbj8cPDA1QRnE+u2gWZ7Nls1mlmP49M9vrh4YHWHzMg9jo0wCVP0n8cohGTORfr9Zo7iRr1ZSiIgWBssLGTUwXYUQwT0Yg9M6xVNI3Zj1GztO7v71er1dHREflHrB6f8o6TScNNtW2L5LA1UXVGIgQcFDX7MhmaEkRKTxPT7l6gfdTKHJKxSG8M08/93M99+9vf9oB2o73Dw0NyC8RzpXrhME5gABbd5MdM/FsyHqhK13VO2x0dHbF2Iw2H4rH5uA0Yy8S8bNTDdt1q4Nw5eYxCI6D7hJLOkvEbAnGccqvGUMejWRLzsevEcDBJkE6nuchzG1SUGkPUq6bupAr+xI8QVOHudS7B8+fPCZS/+MUvrlYrPDjZsPfff7/RLAO+l3yr3S+igO/NVLohC77b7cBmrRoYGpFk6bfm0aDosDjOcPTKvvc6NSNq8CMLS3OJ4YfZO4VqbVxkt9uRn+i6DgIVxB6+EXc9n89NZ3Ks7OSVI0YsCLmHWi04uB0vLJpzd3eXaW6Nf+B+WnFsg4IcFPvNOBdE//DwELkntOImwM25eAGsBUVNY4ZOQ/SdtXWRy+t4fn5OzEdc2DTNbDY7OzujGJSJwoGIHBwcHB0dvffee/69M1RelFbdfXyvn7Ou69vbW/wVH/zxH//x6+trdi4TkS6qhl+qAu1UTyZuEhW9TBz3VucF8XMuwgzbgLPCnjWiXlJTazReoVfjlZ0+xowSJr0EjIgz3sWTtOo+AQih9gaHzqKMx+Pb21sG/qQ8BYw3MMa4nBsmtK002o3EDhiGaKfQoGwWDTCDwPH+oIjZXFcEkUXruu7y8jIqB+0iD37MPs39cZhIlquu69lshqqjYB7hMdBIFUJhh0YhSXqys2XS6d8lTZhIQvZTP/VTr1+/XiwWENcQ3JHOSglKDhYqerOdLoViIXA6rNRP/dRPcXO4oV4cxqj+t16sbooXh4eHrCm+3uaK2tNAh6MAPGw/nPzCHpibZUxJXMtWIRmff/55THi/LE2fcA3so0lt8aXmmfUqLRcJqbjVrMVWneAOwYkFK3XJsM0Etbamq9Xq1atXdPz4oACe6/z8HCEoxBbpus5eohf9hj8hx3gbZn3f3t62GscSVRTDZpHArdRXjVFzkrQVrcihJ3KG4cQ5wM0EWLOkfv/9/f3Z2RmPAJTlzRivTgPniqLgbcSK7B190lH5cYSKbUIrUt1gi29uboxNHCgbwvn2WD1cawqAm6bJfu/3fu/58+cQEnMdC1dquBqiE8SkZ90/+OADgBc856DpIG0yFgptPjs7Y0ug1HpxjQWd022TeVUYCVw5CoYOFKpzsa+9iri9iLhlclRRpSkax8fHHB23Xq/X6/X9/X2XjDxoVfpFkrIsOz4+Bte1Sb9sWZZ0vZRqUHYwUKpeBuUO8+FVLkSey7KMcT3WKOYX3NzcpLOUqQwsl8vhcMjcB8P0LMtub28b8WeQeJsMfgA0kl24uLjY65ABP2mM8ejoaLFYQIwBpaD/Q40ldMBqz8/tEb8aX/XKXTbirqFmBnghBMSdyRR2Yk3THB0dlSqQ98m0AdgNeTJT0cm3Xo0KgE9SqywLIufSRxqiIPqoE9AfQ1NVFbFW/OVf/uXNZrPXqDBvMNAfqWVHi6JYLpfvv/8+Q8YdOJLzztRwCMeLgS0gNpw4T96ITYCS8Cli9izLyL4Z4rPuNiGZ0vZlMm0vJiUqFKxLSOqLxYJER6F5EMyhANCbJ9eLhQJZv1APqx/TO73ZbO7u7l6/fn1zc3N5eXl1dXVzc7PZbDyKh23A6ZH95E8UB4wMHW1zzycnJxyR1Pc9mlaoywSBJrnhzC88nzzpqgMO3dzcTCYTE8JYSadB5/P50dERWWxkqEhq7X1CVXIKodJYMaJJE28G6j4j82t0wUrWGsjFtNPlctlpnk3TNNRkokqZrDPpBOJplh02ANkIx1EsCF/aJ7OnYjJ+2EYtT1ptHXyHtw8NiL/0S7+0Xq+d4iW/cXh4SBqrUH8xuY6TkxNDVb8Zm4HE7Pf7yWQynU7JbfcaNkhC02E7/oF7BWSbKgc6BLNapAx/C1HTgDGVJhz2OrvFRqgsS/IPXA241avOFWME8i0WC78/qqEuaAQD5qAoiuvr688++wwi/t3dHSAbD47KAbTu7u7ItGRJqioXTcCvXKwk14lKHQ1EWj3GOBwOh5qnUmheC8YlxbKtSKNZlr1+/ZoKPyKSa0ADVyPGY1u9GiGZqgnm3quxkBwiu0ySh7WtElJtr7xqlrQNsSN+6rqur6+vY4wnJydOwg41TT5oyGSm8RakK6Ly9L34FL2ajTzHJUsKdn7YUk0zjricTXIMuU8O9ivsHbgzn5WbRvrAYhw0PsX66tCwaZoPPvgANTWw22w2pPPoehnqOCAz1A1+GE3ldDWhGCl2G6cocsheo72tM1ENUyRY6aYl44tdRJJKFSCrZOCK0wsIFqYFtErOB5kmX0EEQkrBfDsWGoNaqA8Qnc/UWNeKRu8YtBWbKIRweXnpE/XovgVscBskmol6sf2O/sEAm82G7BMEekoBBu7EGEAXWBvkQJEkS/Ne50Oi3jFGlJNeNm8Ny+j+NeQhU/0BQ2v/YBVdr9fkar/85S9XVQUBxAlK8pjsNcLQqdRj1SqKghgsdVmAXjh5ju78WRhB3EmXsMXyhNcUf+VXfuX29hanBu5EOqkAYDyqqiIXtFgsKO+PNNSOVTg7Ozs9PV2tVqvViqdyftOYio5vF0cQ2fl83qi9y7ntNFfA+lLD6jUbjFVoxNRvNNqa/WYgjI0BfVhcx4nFPqFLtBocS7hJYDMej6+vr1+/fu2ABNvjdBMqmovRiePKEsZoSGapR/EfAYdBTRdt215eXiIQmFiC16jWNnMEcXFgIR+LzW+QdTdSYsV5WDpUgvKMIZkwGZODjLJk0glQbbvdkskBTKb1H65WJcy2TowJDFMjigRexXpoHJJlGcRhBxhYzKAzY9wLhVizMg5no0Yy4sYHOtcHk+1osNckLKfjWcbU+qASBQO0yPxwOcyM+3EoPRQ6e+L4+NgoqlXPhNMO1opMBLigrNl+v8eHoIJFUXz++edEk/a2UQx40ILnhJILiyJIk6pr25bz01l6Bk/4aVsNu0XoDYRaHY/HI5Qirlgr8jy/uLioqooKxsuXLwlUUAO+a6eZm0dHRzDdc7VH5kkPFAYYBW40qMfuO9e5v2iXbcFOR5R6qqGpO73SyqwwXw1QJrHGjlCfwu7YlE4mE4p3Jg4wLR04SkBM0iKqmHV0dMQiwzjiJmkwSHFLq5mNbFMvjkyveXKdDkciSbrZbM7Ozubz+Xq93u12s9kMfhQ3Sb8veYI+4RPY9ZEgMtsFq9ppVHOVtK2xxaYGOWcddUxb/LVf+zU8C2YPBejUJ06jfiEWIdIDB6bSKCswievSrCkfpxqPKBMt5MnYXnwZ5ZhObRZ4T5AMGgzLNyi9lf5LF1LQQASW4ODg4MWLF1dXV61IJpn6E6z6QXMLKx2dwgoUOt3IWdcYI9NYSdU7DqvU7Yk20irFfboekmsQ9EDtYL3Sl7kGnPB1WCbMbS4Gx2KxYAsZQdfoKICo+V+o00BzzrBt2C+okbR9kGXiN2BX96By871OriaKcM5gu93CKsfzVDoaea9m1EwlLQcV2dsjjW34cw2d3muKG0ekzefzSh1CXULf6ETor8SqQsbwpWhjrxJHoWPfQTsoDx9H3Cudem8/02kUSPz1X/91FA6o56wCil6KvpYnfeI4B7aqFVsd8QJBEU/34k4TWhQJy4+FA3a7zF6WJYmjVkU7FsUODpcaNV+S7acI0us4nbZtX7x4AUaCbUucig/BD7hQFTWhibtlci0S6UAfG8wjcEusPpUmCwT3Np/Ps6RDvNZh18gHZEk7IpaU2NdWk9VmJhRqUCYnXTtg5U7QHEJzXBOLQMTi9feMf7aGV6EjAMknkj/t+x4FYIOI3DDSXDm+PWjadteErio5RpaLD0Qat2IQm0UxCbCAZVlCKwpicUa1MQ10eE/UlIpeKWbvXauOK6ICc5yCqh9dwo31ndd1HX/jN36DxYrqFaoSNiIOBQfNoqMDeDFKktfX15vNhmxgrlHmuWihhegJTsyxIgNNtDTI68R2KjQ9JY1u7YL4FwGCdECADgUKed1rZqBLbD5+AoPBswQdDcQPrknjSQmhGg2UbZoGc0VD6nw+ByQgGUw96tVlW4qvRnCfi/INzgS5ciwSsYSpmoRemO1KjEgYdcCPUudvk3oybZP4DXK1U4F3d3cMwwJLEJh1XUfAwNbc3NzsNdUCn0zA4CASKIWHt+Fz+OTGfHeiOTzt9CpEHHZOJdOg75EOWSKBHlX0QP9dY+m6zpai0JDdUpMHtjoYyspj55Mn47u5sqvg3Fj8yle+Ak2g1IQSG+wumQ1Yqvei0wwmbpH7I9Kt1PfJOmKkew1pczSciRbaq+vFa9qqvO+KQa6+rfTbC43dJGHFjjqQsvHAZGbK4rNkO01IdZwAE8Y9RLjR6+vrQqc8OB0Mq5Yec56IbC/b46o7YCbToEUe3yE7RV/iq9FoBEaHOrVYLABRVuAsGVLkKN8wF/Vwso6gCDWgXsGXFgm/Y6BBwvf398+ePbP0u+xQahaYBRfxMniwNGPFrC25eu46tcWkOQZExcYY8DkYDFar1c3NjSGWW/KD+jAzcWEopUeNwHA8HTTtBlHMxT91d5jjLvykYwPWJH7lK1/Z64i1QjMkfEXiDCQjVx9apXO48oQgVGheF0pG9QrR6URv2qvn2ianV6U9qjnLEI16QtDgp0wdkjaNhZjMuO/ubRIVSeugNHMIAUuGTpI5aduWJCP6RhDigi6OyMGl6xJ8lr3HkKAJpSjBBruFykyZyEUOcH39m5sb8qdRvbAGit6IQmRvBhMRVvLV+/0eHMgmXl5eNjoTIC215nk+Go3Ozs4AdZ999hmsCiSSmKdRs5uTVJ3G2rXJcSHEFV0y2rZV/TGqoSdTectZeRsva3Uj2lyMcb1es604OiuPjb1RcZ+cA2uM4ASD01aYcvucoFHYPqTMf42/+Zu/CakDT4QhD6pGBRH9kMhW00GAZYXmL0S9zL60kQYk4BCHGt+QJnbScmBIjlwGkZMdd04dmIHE9H0PcaAXt9uJMJtPEAVw1rawVfvvYDCAL4AUwl3Be4A0djrUGg0famhHL05bptrCdrslu0IJPEv6oYtkwq6NJXOmHDGTccLLF+ocKnX8RJ7nzJl69eoVWnFzc+MB69aBVudS2mRwnxwvRxH6s88+M8xzwhopIUeH33DJAgMUxYzCCBbuJ5ShiWp7Sp80aDZoGg5l4v07cuC/bgYiD2EBZbmwJkUy18OOy2YOl1hp/ghm2r40avaHBYAtjr/1W7/FM7PrvQ5JZ40qMWq4OQc0QZy7XnVNLBwe0IKI5bCS9Jru1Os42zR8iRplPhgMjo6O0JO+70nvQIzh6xaLxc3NDcvUaopjVGol13Ale0+b0l7jO5m6cXl5iSFfrVYXFxccbY1YO7vHNZ1AQG5oEjo6OrJ99ROhKsC/TnTiQkd7RBFvQgjQNNDtQjRpV7Lbtl0ul71eeXK8F3cI1MR9UYfOxIby3mFHlstllmV3d3effvqpiagQMFuxBhynEUUAZTFzrm+QHLdiR3Wo2cbHhHs80IljDgIdGDgGBRlWatCh4lFpsqWxCu+nbFdq2GMmSnOhKWl+cHAK7tHOJFPeuVPXBy40/vZv/zahGBtj4D5Qt0RQSzLPGdWsacScxgk24RYI7EebzK0nIqmT9laenMc7OzuzBWV9iS9XqxUDxGHg2EXyqahJE0FjVPg9QCImrRUkBLuug3uz2WxevHhB6jaq1AKgL3TqDO6i18Tcuq5Jej579gyOPhy1pmnwpc7H96rOgNzQLh6ZOBgRpNOF5x1ouBUeGHdnvSJZic5QUbE19cY3TQOblbIxXQcvX76ERuEXqDrT7NSoKhWFZHbK0GixWBSqKDmmIt+K5OSikToS7TQ1zG6wVx3T2d4+YU/1InLiq3ux9EEKUYyYTvMmYnLUZ0xOrAKjOmlm22pmB7dqFYq/9Vu/tVqt8mTcSFQRxKA8DS9MM+b9jtMfKVmfjMpwgEF6tNC4SQSUeHo6nc7ncw7BdEBTiVPNEdNXV1evX79u1bbSi0WYrnulHsgsKQd6D8AexLikIF+9egVsA4yBl1xehRbv/PfFxQWDTPYa7OEHdIhCJoBN2uk4PYMu+5NaHYzYIe4cDoLloNNJe33fU+LtNPnHqthrvghO5urqyn3VMHA/++yzm5ubmDQ/9Gp56URhQIxQWseXjpdIN+12u/Pz81qM4D45Ysc5R6dlyN7aS8SkyGg3VYrs6WoMorVarc7Pz0lJNRpWkmmWNVfAtlaiTDc6MtA1Dd5mW8zWg/BNMuDG4u/+7u/SgpmpiyqoQtlpxADxbqNhRla7TrltCj0YV2wYxi9TZy02L1NZZK/zfFLFI4tiZwLWrMQ93m63kByDyPe5Dug1AjHKzFWF8Ui2QqxazEOe51dXV/TN7MVx75O5+8S+VVV9/PHH19fXXdfhE1JwFcTtYwWgMRo6j3RcMVVwlvH6+jpT2ziJETYYK2BaLlkpiNlef4ssoB8/2ajXIqoHnM5jRIRIl8Q/JTAuAp40scoYErpOrgGJvHgPihdCODk5qTUABlmnbT9Pqku56gNRZKdOJ6HkyWk0KSLIkmmNxJmdKp4OuHsRTKLSTdZS5IoEhkMRMsi2QSEEgngsFzdQOPQsxZ61Ta10FHiu8hPWbqBjPNK0tC1ujJE+V1LvZAxYPrxb0Iw3E92c1Ynit1GrQuIRAupZbcJqyjXVudXICQcnDrYIg3LRYr2UzoGgXXaIRFpIOW21yPrr168bjUrOlYZ3JgqjXpbl8fEx5OehhhdUajQpy3K1Wt3f349Go6EmH3phHS2w5pmIG4X6kHplPzA6IHV21Amc1Wp1enqaa5Lpq1evKDmRqwXJkO3FkEFQgz49m83gelj0kTDSMkQCqMqnn356fHwMnKPUcHBwMJ/PyV+Rw3GqoDfpUnPke81HwvAb4ufqauj7/uLi4vz8PISAADi2LNWhbxuf+oRcY0nZMsgd7LsDFV4oAG4n/v7v/z5fk2lcj2+x1RjkQmlvMjn0yAflQ4Ooeb1IxSneYMUrDTuxsnqCJEHYQCe8n5ycQNgCT9d1DQQcqDXMpBH+9cMbcFuUAVSPAjJDfKofHlLAPZOwIikERzBNdOz3+6urK9xu3/cHOkKYUTFN09zc3EBsNFTgbmOMGF2TfACBLDip9KgWszRQs8XJlJR0WEUdhuxcVVXz+Rx2N3L54sULTr5yPQQnFjVIjz9BRjRzCdedJUeEEHriPaJS1ThMMnJO0Dnh88g2Ow42BnMgZOlPwTMbPZ/Pe1V1eo3SeJQDcABti+MnteexBXEMEDWd6Y14owB7HYAcxBwqNL7cwQqPkdbIjIWCqr8uMYAKMGkAj6g0bZE0LkSV1vm6J0+etG3LzEdP8+KpGk20c2jeix9hrMxj45SzJI3t9WVH1+s1Ip7iRUqSPl+2E18/qnfON9x13cuXL7klmMaYRp6l0QQKLk5BnQzbxcUF229gFsUaSCMuylhRNUTQPKLgxmsn2Sxk/MwxFp999hm43KjDVrMX+6gQLQoXMRwOX7x4UYpsx8a1qp27/6bRuZTsBWNdqAFnKvwhGGkA1unAi6ChlMi0v6jTOBajA0qcmB6sM99iK27Yxn8dKhDZo0VGmJkSQUVRcMOOEOLv/M7v4LUtB51aYK3upegobo+0XXGUnCllmyvpa8OM34BsSE6N7EqrQ93yPKdXo65rcHCbFBeD6lNpkciQ0SF4J5KpNSSqS8hxkglCOD2khODp5cuXJMKdj3IPQKvZ9tj+kDQPXF5e5nk+0gE+5H88SLlXssJjYAC4tbqZbM+4VehoDhDH4zEz0NEfzopj3RrxHLuuo5WWddtp3CIC5zqxE52Njudok7OHSXr6DBvTsXgNNc4xU9LZu0ZvEMPzSvFcavH1W01oJDPRisXUq3uJp2g1yo4oyymBmAw+M8xmuzt1INU6AqLW1Gu+dK8BCGmoZnfEzgLg44cffogH4CvLpKEGB12I1F6oWk5LUaNRVrn6azMVd3tlmkEgTvDBuMzVvAMaphM/E7MXD+PIGJXgVaj0WyfjbmxRoib5DDWaF7SHuWKliICROcpey+Xy9evXq9WKFaR+ToIyDZp7tS+DXs7Pz53xAFC5Q9pBsIfVYOz5OnbrvffeYx3g/AAmPcqB76V6hS30lDh2mtip0DEqJHM9JNAzOh31lmK5NxpsYx9uTbi5uaFxggdBM4Ec9q5UdQyrclEndrvdyclJ0AmwrqVkOpY9EwMHj2pYYi+BF0W4M6UWy7IcDockmu0wecZ0PpfLSq3Yu0hdnvRRcQPkiEgTe35w/IM/+APQdkiqsEXSC1aqE8Ly12rcQBrB9H1vlix336hnvE+qoZkGWiDlbCeqBUx6eHiggYsHI3p2OdZexWGJnTXWC11K+YNRk9PJoNOy07YtNH24/uZNoNiZTkjn0faaXkF7K0au1cBQUA16ztG/dV3TeIWIV+onZmUoqONOQVDGhHgPcAXjRwk2HDu1ohIhaqB5iA+j0ej29pbQNujwemdmex3t4cx9VVX0xQ+Hw6urq6AWKiwx4ntyctKpiwgjYpzjvotcZ/BQFnRkCELrxMaxT2a1M1E4O/U2GKn26p6z7TC0tgPpNf/GWN8AZJeMGMqSHrF0DRlqzxvi//k//4fooUz6hREpRxhZklEZDodWULtFP0DUkUeO4YIO0OTNeZ7TIk10lYlxxEnO9/f3Nzc3hCydxluj7o1ON3Esa9tPfJO611zjV6OqlQTThubz+fx73/sexpIX6ocGEg6Sm4KZfHx8zJXBTkVRIGdZlpHsYlw9+J7U+EjnGcYY+VOpLhaXYzGQjfqqeEz0HI9XaEhHykgrNRetaRrYoAC8/X5PSQfFY1jB7e0tR4a9fPmS0B/RYXzl3d3dcDgkIeE9AiGgqJZm/E+l81gNCgxL9vv9+fk5fX+OgqIqCcaEGBpTZvh4rwETuYhnVDPMnXFU3b491Gyv7l6eGi8E3LLQpt/i5T08PHzTS/TVr36VlSqScn2fZOhylb0gEjmicoDLd3eqw2HeHIAaTfVqVG/blgAXW0J6pG3bi4sLRyNBpNm9GoUzpVm7pBZIXjVXkqvUIGXSc4VYgRxC6tD21atXeEAEywGZpdANXCcnJzwgCWYYZjhMl3jZe4PyJ0+e0EwIe3E0Gr148QLtck8Mnmo4HM5mM3ygcTN3hdkuNZzGW8g6m5qO3qI/NK+QiuWCjmGK5DDgTrPfnGfjbul946sHajIMmuLqv7aaolmKpxTfboRnTnWmFuFGjQGZSGmluAyFyClR08WLhIATlERKb55lr9VG4jXxn3Y6EtwqYU1oEoJTWZbMa9ntdvEP/uAP3AORqmCurovs7Q7XShNarCoDHStLas94K4gYyBUqTZtBVhD6Qifk+YwC7DFhBvY4JIM++SV+07kRpMQuyNgUXAQFgHEJWZZ98sknNiSINYnaIH4VO/Hee++h8FjrMmmAcu0vyzKDeEdjXdfRFoOT5AiWkBzl0DQN4/fIYGKTgFU4DUJz1hnyLBtR6rjpkIyDdpEhxnh4eLjb7VADntolUhpWrWPsPYaPpFCt45ORj6hZD0Gtc855ZDoks9IYjkLz1nkEB06j5LQlX6pTecvppkwUTkfYSPxAJwM49shFMohKsRh62D0aKdXqy+1Vqs+TxOt+v6coFr/2ta/Zm/sLKjVhZaJ8FjomKNNM8yyh6xjABWWE2uR4nDIZiWqN5FLkoW9vb7FVripwQY60z5LYH1RQae5nq+G1Qcy5LKFhMieQjifu8/PPP29FAEYr8BhoAldwYyeJ8Fyhc1VV9NrP5/OQDDpu29bZd9bw9evX1KqwOoS/7uokRscDpPSyPM9pjd3rCF4Aug0HaSsjOrp87NzAeBh1OtoslK3GSXTqM9xut0DNrutcb3FXJ1wpQ1bkhq+mDghVBDkG7hr08le2j4yixTpP2nbtASw23rtcTDhmjuR5ziq1qkpVGqPSqrLmTJHlsxGL2/cflSo0kCa1EL/2ta9R6OZhcjWkovFRbVOsoHXdqmbl7rqO9B+qbB9qDGeMjqXHflDzoi7rUMmACmBmCo2zsUHHimHe/Clkq9fg+bu7Ox4N0Qf2NE1DQc0hO9VQqKAEsqzv3d2dT9UejUYkakEaL1++JJ2K89ztdmRs0Kv9fg+87vuejk1HWZYtqygpHUAzq0Flmh3i28E82M6gg+hIv7Rti/S7uGMBcicki+MOAbAcH4yaQ2hrjRo8PDycnJw4JWiRdcLR/Q9dUn5BE+C8GN4Yd0VlFPukOoaG2Iq7GcCNO+QnDZz65BDrOpmWBVIyiIiqX2VqobYmmP3xRgi/+tWvkkJO45JeQ9E6dVJyDiaRGb8Zj8deIJ58n0xvBAWBW3oRZQ0GWo1ty/P8k0/DIse8AAAgAElEQVQ+CcnZ9J1Y4Mh3VG0FhSzFuUi1xQghKjcKkweycZZlL1++5LJknBoNRHCR/+7u7smTJ5a/RscdsLJHR0eMFr24uLi9vQWtOSIEsWBcx+Pxzc2NQ3/23lzlTnUfR+fkWx0jknBs1C3NBJqg3jqwZauOs93bJ7ajZo3mXe+T0Un39/f4rhACRoHpZo5bctXvao1V7PuegqD78bkU4CfPc58a1qqa1qvlFwPK3SIPZdJN3iaDMR0lOkvjVDtw2okQh92motU6VMq4wBlP2+U8OfmlE7HNnu2Na/r617/ulFCWVJdy8d6iqDVIlUseQDrCjk5Mil6keWMyBLdLiBy5ak/ESQS+QQnWVlMb7MIyhfwsN/in0zko3DZLgMGgf8BnkDx79gyb2mq2T67SCRaRUihmNYjrNhwOQerr9fri4uLq6qrUkUGNhj4AfnpV+O2aGLJtujJUGR7KUyLzPKfDGAPvucpkdSaTSVQlGPW253TW2KyKkHScQUzAiSFemPnlcknzIWpDDbtXHTOo/A+tLU3aXFxcbLdb2idQV1p5bBzt6nNF8FmSR7HYdaLExYRP4f3NkrIuzzLUYOYmmXk8SPo/Q3L4ZBS/wzin1DAIOwRfvE/yqiGE+PWvfx3LERTWOLpqk057ylWtZjz1CV22Tgbzp+mjoMbkUieQ+rFLsaOZC9SpSaLWIT9Rs3h7HXzgRGeuvscsGa8b1Q3DoDgMeZ7nz58/z1RNy5XRJ+rtdbjDbrcj5q50cj3DT3e73atXry4vL7GIs9mMzBLv5G7hmaGQy+WSfCibvVwuOcC5VU99rtQhqWReQaHhwcGBpxMgYR5/gOE3GwqHCRsUVaQUnSt0zkVU9pgtINOrV6+8WUGt4jwIWRHbPoQMe0dHATqD/4TUUOlI8CJpkcGgsLm9iEworXFUm7SDW14dEOeq82Q6IrtNGE2ZIuatzrrLRbgyWutF2LZPCOJ6dQnr8Q3I//3f/32nQew0DSd402AwWC6XYIZK48h3GpOWKSz217tCQazNoljL7f37vsdOB7VQpP/atVmDs6SIZvzjh+x1QFNQEv3TTz/tNLu31ekjQTkldoil32ukGcK03++vr69plCMTRXaF0Bak1CbnPvlsZ04yfbQ+A52dg9zDUAhJ0ymcVmADVQj3vmGSSx1l12nE/iA5NzfLMlqFouZwudhHlyY5H5APV3BtkZskdWNaOKnGRl227EJd11dXVwcHB2dnZ43aDxBf8DD+vBLHu9J0KZvInebRG+t24qtlSXttrvFYqTwYnjgMq3WgfJF06oSk+cYSYjEukrn2Frn4J3/yJwRq/vpc1H/bg+PjY054D+q+Yc+I7bKkOzaq8JGpDGEqS53MEMZNM5TX990rjeUHttPMlVVoRUeLSSdRL8ZBmpV6/vw5wWj/9uDLuq5x6LlOky9Vq87zfDKZvHjx4vPPP7+6umILax1azN3ChscQLpdLUn6F6tw0jkRVYTn43pn1kMzdH+rYqEZn8lE+a9VX1eoA8JgQ5rCddB5nmuCEDxxoXoiPhHLqYrlcYrkWiwXpUS5OjsGAPssyJJgrOA/rnEemUd5UBnAFpU4gJ39Qq9GHO7QQ98kMdMfN3uhGB3hhtofJ0aAG6+BMJsHsNV2r1tHzJNO9vLyiqBOW7TbppnpjkT/88MNG016Nk+wmWNMnT554Zjde2JdzBpebc53CYNoOl6tRQueOeZhU+jN10zth6uJDphEp1t1Oc08t91EE448++oh8IiJei0BLv4gTQXVdQ5EfjUaz2eyzzz67uLjw/YN82radz+fkqQqxqU9PT8/OzgjiDw8P8zzn7Dru0+clDnSiPf8yIwiAa5oNe4PhLzSIBQ/mUVylzoBA+qtkwBMqSkLCgRBUhbZtX758GUJgkh+fhazBCCqMt6kZ8CkytdJj4zqxxwFdyAm24OjoyMg71zGyDE1CHx5NLCxU0krlz69OFFdXIZCKNhniyV05KcJtB6VVnDgCcKaorNDY01wMF0td/PrXv87qeJ9icsJwlmXn5+fD4RAFqNWVx3UdDhaquVKFscFgP2ytg5qAcfeewoBYdMo4eTmMFLuEQ1toNIBdSpZljIBlFZgMRzXXNAHyGxSe7GcprxDVffzxxxwVym2U6jM2NXW9Xn/xi19kxD6Wz3DF6QU/DsDGPq0RGZMjU13ltY9mYzj50CSCQjRETJKTLX5qdBjjh3luNVwVDT84OCCZ4xCLS+FbptPpYrEodbJqyqLhtdeMdTBJUO4FlA9nG/cSdPwZzzvQvErME3h9kMwZyJLqWJ/0+jicsChnyfHSTnkhh5WOswBisAsjTYqOPgNGh2RCozJcR20KoyurvncFYzadTvF6rQZQOp2Mbd5sNiOdN+EEheE7S2+VyJWtB5zgwkY697dXsaxPgvf042hal9QRcZeotfM8QQQkEjtIGw+818wMPn50dPTxxx+/evXKN0Zms0vOTcKw/ezP/izL+vDw8Pr167Isj4+Pg3IXTBfmqTnw1AxwQkDKiCGEo6OjRmQyIuZaTFXmmfqUpKBYrRTvAKRu3+jUipfaUTVtkK7yRiWgOb/5+voa616WpQ9pbJqGujvXpErIRvNDp8Yml1AoGnzwwQe1OuuN35A2EnfEe7VOqM6SQd+Z8vG5ZqU565UpIO6VzicY68XrRsyapAOB9+PPGxGlotiQpFUGmsP3xpL+4R/+YS3+t8Wi1YhWWuxgUxm6kKwoxGXPE7IeJtM2GzvaqXUdKcQSkKt2kstxDPuNPRhqEpi9aq/kWq70X9d1i8UiUxDMERUgFhJB+/0eIMsj7DQzdTqd3t3dffbZZ97OQmMXjDr4up/4iZ9g5ikNA8hKVVWXl5dFUSyXS5h83DaL3muaeZ9kAzt19CK+sI7t3IFDrC0oH7DkSLRR61ZI0ogsiyMcNsi5Tgf3kIpRpK1OOO77frfbkfJCddlceIrUqgktgk7s63R+kZvs8jxnVJ6PguSezSPEZhsLWWlTo2bYaTkJb/No8mQ2c68yMDIz0FkE3HajqRy0p2eqmjnk6JNJ4F3XxT/6oz9yW6DlgF05OztjcBpWHz9gJmOWVBMMdvska8ktlmLR9JqFhk/sdayiS7lc0yWeImGN50qAOhbkeyGNIQHcPzOcqYxiqziho9b4crZnOBx+9NFHTANwcIw3a8U5OTg44FQVoi6m5TjRZD7wZrOBM0dYjwFjzkqdHONDfbTRmAMyJMY/NhPb7Rboj+ggf3XSYGloavwQRJRg5etkcAMS7NMHQwgkM/gTNS8qxAMdREAeOaVgdV2HzuBVWvHA4b365ikeG/FWGq+G4W915lejgXB9MkCtSoZHmczbKTPJB0MIq9XKBsUQnwcHWjuBtt1u6W3iJtMctK38G2D5R3/0R+6TdwxQFMXp6Snkqtvb2xBCmijsk2pXUCKsFIfRECgo3YEDZe24G+4y1SWkyujQWX+DOTtNfwTjx1HbmSpBtIbYpx0fH3PumnOXi8Xi7u7u+fPnjp9qzSXnxjCER0dHtBTj6E3agSdMvEVQcXl5ydmvfhBKVKhZI2ZiJ1ZMpomRTuSb3UmO1cznkU6CCuLh8RSsJBdEsbHf3kS+yCOuiGIPDw+h7nEyqRP2Nk+AJfZuMpngGRwXBY3/78S06ROmA7RczE2rhjXMNkuXJRkhTJUzLnky8CImTGT7eR6Qgb6sRpH0GOQiUPSq3Ddqu8FdDwaDR46oTM9o/PDDD8k5tCpdhRCWy+VyuSTh2qgdLu2YdnhqUx1CoJ4CtA3q0Kk06CtTn4qr9L7vVs3BQQOHbWZyZc3C2xlcnG8UZ5D/Mh2aluK+70nbdyo/N01zcnLyrW99iwn07CjDk9kwMoNoft/3ZM2RZjBVVVVPnz6lUIDck+JcLBavX79GJUAa7p90spxd578+AXagU9Ks5NDRcLbAjEKDGaH78m+u41NzJftSxsHt7e3V1VXf91CS9vv9ixcvqGff3NzUdf2FL3yBtA8fYb94HKv3brebz+dlWZJOQDMtfC7IkPO1YJAJHCbHhpNjtbXulT/Ev/VKtcekwFokU6adMkoVwLC+Scg/xhF9whAx3X0wGJhJYMM3HA7jH//xH9sD8MXHx8eE9jc3N74Jf4f1MmosnDE6EVKmQZO470KVWqNYh9qNGkHQEAolg6S9vRA3sNfgqpAM2HAdoNLhqpSrcLI8ba2huVzwo48+Ai+R++tUgwSXn5+fc0I1wIAYjhTZ8fEx5+JsNhsGCuFqKLVeXFwAt1arFdYFLDTUdLd06cDHdDzmIsGTrUpFBCGLGpGCkhM18WhBvMNW42pCCCB4Y2WL1PX1tQ883+12TLfHm4FI8WaFChpk83g/f+LnNEUBqHOVoNTYQ96Jkhca5eCQPYX1KYqz/y9ENosaKMjvnTHPxKoyuA9JgbVTWjJTCa9XwtRjle0i+r5/EwN4b5bL5eHhYaNDOV0rMTIOGnJk+G7sHpJOcDAuC+QkhpcAH0JYGdXVFpQ4y8SbsL/LEn6e+Vg8tun4g8Hg+voa21kUhYuyMcb5fP769WsGKpIhoUSNcHP/p6encAfcfHx6egqo++CDDzabzSeffPLixYsongKDOwvxsQDuq9VqPp8zb4uvXq1WRCOgW4xuVFehzUGZtPCBJ/caCmT8yjb1ybCQoMYAKM2sTxr7GhYzBTVXKhnLBbMD7mee50AjS6TZMoiyWxdQCTbLI7HQ4So5CPTh4eH09NSJE9eLHL5HjYGx5U4T31HjCbmNRi+uA94Oaup3dqFXGTjXcEUvSCrMvdLoMcb44Ycf7jVY9Pj4mKQ4yAHMg1+OOoi3TNqyDIEcmfVihqGRDPRznNCqXIW/RnTsxQY66od7zZQsM/jJRH4itu66ziEdGwnhp0+6xqqqmkwmn3766YMOWnSQzfbjZyhjgZVDCBwMtV6vz8/Pt9vtd7/73VevXvmaeZ4zqtF1U7wf/2WMHDUjBwO9jnz0wIiiKIjOc43yxQrsNIQdl92pJpgrS2iD58VnyIfRc6+Wo0JFmOvra658dHTk2WluaiFvsd/vmXDKs7PCzKTAm7VtSz80t8ri929PKCt12nauGZ00Idged8lMQgcGfqJG5FDkp1WTO5tbq6u9UN3TMpO93VnGesZkUgkSlScEvs6zFP7wD/8QbPf++++Tj8eNZmosMH5tNFED8a3Ul2CFztXwmqsou9PhhA7quTmUL9dhcpnaI3ORkdJouH17MrOdHV/tWGq1WrE92+12qIG44/GYbE+eHLTR6YTTqNNlIM9E9U0/PDxQJHr27Bmp9LZtyc1VVQXprWma1WpFxNwkI46RVFp8WEbm5IVkNH4mKnihGSeNeiR6TUDCyxG92fU3GgpkCoBzo50qsntNwsvUUMrUD0BdCMEzaTJNqqQ/hhWjUYaSSK5T+pAtfp7NZgTxRGvGPzauvbrd2d/j4+NcMywKUdDS3cwSTmufjMu1heU2gnLrbTKkw3kRx4G2EZbMTOd0uIRMvPcG14BVnj59WhQFp03xnK4nszeph0WTSK61Kl4EheE+DmyvgQ6NGkM7MbG4OQc0mVIBfgb/KTWixnx9UijNVLQGB7P93NtwOGToQ1Rlo1ONhtDz6dOn3CdMTGzMaDRaLBaffvrpf/zHf9B1xRKR0DCvjut3XUcdsNUYC+M3wHrXdZ9++mmuc+lApc6B2PgZ5Xc6koglSu09e0lC1uuTqwgDBG1VJbCUYPKDaibYr04NN50mT/bidPHO169fE94cHh5iMgmIqQYgQIvFwrNYLLu+Kys2gNDo3HLZaYy+a8/G5a1y/P3b1OVMrDM71dTRcZ8WjFIHvuRqas/zHHO20zj0g4OD+M1vfpPo5/b2tq5rih2G8oX6D+2eMo1tcqRfaQjucDgk7Ks1ggEH5zCANCImvFfR13Gq1y5t8jDI9trl4iDlmgLA7RHvGxnneX5xccFvsDSUSOifevLkSUgSuJhPeuQmk8m3vvUtQiUE3WdTZypIHR8f0wfjHglDZyaLUH3LlcOmSgC6qDTzp01qOr3mPyMZIcl/928T63EgQ41XSpeCJzVGxXhdXFyEEDhOwZGbM62gc9qGougtoBdiegq9RUIgMxWv07zbSvP5fJ8hGbFj2WjU2J0acquNs/UhGeVAaJGrUzckQWYjEmGf1Eb3yYznXvVjuxHrnoVqMBgU8E8oAKFqQx3fUqn7JkvYqiGpdlU6FpcnjDrMtdIsDQQUSfJNwycpRGrA5RGgmNEQkvYIuwtHBVjigYZLU8DKlFmi9vHpp5/iEyjHthojQ6CPbkOQ5mZwXC9fvnz9+jVoByIDmR+yftfX13TJXFxcgDEGg8F0OoUnM5lMXr165bvFs93f3x8fH2c6jiWK3E+WjBjOrsBgI9NsiEIn+Nr19ToD1HR8IjyW2pmQXEUbU5UQR2OJGONwOOSkXssHmX6KnoVmAf3bv/3bdDr94he/CHSk2kh5h8CJTomQjODEtLGwu91uvV7TcsTsrfS7HIx2mm851Ow9Y+xeiU6Hs636j/2YUS2jhab5olGdWInItkuT4ILtdhv/8i//ktywQY7Nie19lwwGyzVjnjuYzWaz2QwrstWxpGSUSS/EZOBMppOKc/XgtSro2LT3bzeM2jP0moOH5zF7JOiAnVwT4zabzeXlpfegbVvuCkB1cnJCRsXZJBIyo9HoO9/5juc3UiSmrFMm40DyPP/ggw+ePn36hS98YbFYDDSFhcLqbrfjLAnby9PTU+j4KCrombb6mJyI401KQ+1SXRlRlDvvUanDrFrxglgin19UluWbqQcxcllc/0Anf45GI474ZjW2On0+V3GTiBM9JCd+dHRUauIVqVhMQ6m5KThMbwoPQtxf1zXzbrlyXdcATjQZxS7E47f4GtyTQXqUFg9KkbE1XXIcpYXWgUdI5oc6+xJCiN/4xjc4bcoL3Ws6aZZw9DL1dmHJMADwv6+urjgpdatDr3L1dhkL5uIDN+ICRPWY2lvZ5YWEI5lmh4IGKqVJofF4TOWrFTmCOWd0WhrhtOoO4d4wG5Qdnjx58vz5c0hEBEK9+EhQKiAbLxYL2h1PTk44Ftb+lHKp2fypwvDUaBFQE51xR2jUq9C5cUG8LuOBFNzzBpKSdu6FJsBhBVnGzWbDVHcWYTqdUrHCVLmmRpLHVg9+BA4TOh03MJvN2OWnT596lFOZnPxJfplEHNsHvgKZDJJzv6mpRc0G7VTw6TSA0EmOFPy0SR+Z0wCFGNSOvFnMvSbcZIqkTWYzkHmTdPmzP/szUuYxqULbJ1o0zdYgHiKeuLy8XK1WNqW5CLch6W33f+lztTsuNSa61TTTWn2YeXIa9qOQLhdZirsnXqREwnNeXl5m4nvVOoUpxrhYLDBy7BAYum3b09PTf//3fydbQvwDox1HjAnhjCbEDsr3Xgd0O+vH4tZ1zcRFbAwZdGgIPp/Qx59YTzKFp2DxXKkMe79Sc0jruuYo1VrUdpuDgQZfuu0Lkw8z7Pr6mlPouq5bLBYe8A8sofTBUEcwd1TljniGjCdSSGKDsYq2TQO183tOsE0vf0XA3MIS1C7C0yFCLvgYe1v698kRYJmSV5noDAhbWokbaHRnljDWcH3Gh2987J/+6Z/udQRvI9ZDENPI3+T4GqtwcXFxd3eX8mwzkXP8TYVYXKXa4UvxqPH+zpbYRfSqdrUqZJaiGKVRQa3BafzS+SgMHvF36umWy6XrephkBL2qqv/8z/90fyP3jDRwONJyuWSUXa/xxbe3t3S424fQ1EZ8T5Mx3sADXIMavWez2dnZGX7Pbcd4g9TIOawvkklmrCR6uNcBR/wpqFcLAog5sIxuxpxzfCo8IgAPOlloegpABQYo6zmdTl3TKNXjgRPDvbi/wmKaBtbeylIMS7AlEkVWzRbQ2AZtaZJxWmkeM7UXXdJW1id8z6Cce5k0DBpVOoA2IC+cYGlUPSlFKWnfmXgRQqBWutf5e2YXF5pYzw9uyOiVQo3qlPetYMOCWIf2FWDfOjkR3petNXOu1Wh1AsSyLJ89e7ZPJmxSeEK8bm9vM+XOWNPZbPa9732PiJkv5RA+Hp/Q1iVGTBeFWEJAm4ZKL8phLBFiXWo0ncM4KmWZpmJtNhuwRNBU8S6p8KOlNFpkGkHncVTefid87DkrNeVR9MjFtphMJijwUCc5YFBOT0/7vl+v10xGYu/Ksry5uaG8jUoArtBD3vDpp58WRXF+fg5RotToA7s+Aw96pnvRbzwnJkuOQDa8MdIzlMo0rs/C0+jYh5gQJb1fjpgzVd9ajRrhfmxQmqYpHPQEcTANpLKk5oqG3NzchLenuBj1Gs3vdfRNyugICTuoF8OJnxtV/o2jHDZUyVA0Hs9ZMNoLiSgODg6eP3/unECa5e1ExLe1IBf57W9/2zGPI1EGqs3nc08+y7Ls9vZ2MBgAlPH7mVrXC811xIkxzv/6+hqsUojOPdQ4YeMlY8VSp+1i56bTKRXrTvwogEqtJqRctHgMBxtZ6wxCbIENEMtOQrPU6T6OuzKdRJbn+e3t7XK5PD8/J19XakIoNBP3PyDfEIfcRMHsPYt4jHEwGADxjbm7roN/xXZnOt8lT+pfhit+hEeQ3QEq1rDW8dI2+W3C5mzVYWz7bsTRi3/xJiv4jW98w4Yz9VZONeBEsPrIXJuc7BJV0Ml0aHilQ+lSQBU1lrpT815M6H5+Ev9b6UilTuyjTucmZGoGtxV5/vw5S9z3PZmoqHNHak2S4s1I+bNnz7ANIATg/n6/Pzk5IcsJp63VIG8uwmUnk8l8Pj8+Pi40kOPo6AiWMowD6wP2G+kHOXDYtSGlldmP02t4qAE9OhOTEVHYdSTe9rIXqZswhq0datZnGlCBiLBEXdeZNM94DuIxN9fiPwke0P+dZtQ5m+QUE/MhfeeGqb36QDJFktbwIGpj9nbavlPWMYjl5ppSqVNknJ4BGrkbs0/m2DaafNEmE7VCQpTouu4NVbNNzr8glGGr0FSUlYN1U3RVJNXvqIk9/Nf5ChvmUiTsOhlN4yg5qqjZqVrsyM9RYCYWnendw+Hw1atXvTKkzpefnJxwUEqmMCvP8+Vy+a1vfQtnQv6OMHqz2QCIOav9/Px8Op1y1lBRFDc3N+RPaF/Msuzq6uru7o74G9PQ9z3QwpLK4RR+ZO8xY9NzNcIjYYid4yKMtNGq/WGnnumYHIubJwf0gpRo/qIEtl6vUUveeXh4yNcxCLHQNDXiNBI+2+12MpmQToUfUencvqurK8LZXJk0pBzdu7i4WC6X4/E4HSnpmyT8yMT2I1SgcyNXxi8k9W/LqLMmfTIT1+CeBjQzxwyY7eI6ZV3b5GjaqMNb27YtrHCGVkOdYejMUdM09Hx0OvQBp2HPGJNpSkaxWCCrhytfZN+IdWr1udltpSYh1zyI1LVVOgUEI22ez1bnnyL96EmvJokY4/e//31y3h7hz6K/9957fkw0kHFX5EYHgwHET46SR25WqxWDa8yswjATUA6HQ0DFw8MDRKBM2fFcL0Ba27bg6b3GL/OALgkPdLilMwq4VmOGoD4V9J+rcQ4IDTEmPw8Gg7u7O5g5NJFi6UngYA5QgFb9cVTK9jo9hCgiKMXsg2QwMZPJhGNmnjx5wtr2StGk8MmqbhzvENaiiH/bJ2dE8IAuegQRQzJxz1z8qpNZtJYZzCVq32qQ1Juy2je+8Q0zQPhicx/Al9SzMvVo50rXpIDE8YqRXK6I22qNU66TLrBSfVheBYdBDl98HYs+peu2bafT6cuXL6FvgMvp/WWVibRCCGQzPv744y7pQsRjLhYLt8yRxqFYg52oqoqJGNvt9lvf+tbr16/ZeCiouUpyfd+7JurYN6o/g4DEBTWqK4a/jkS7ZCKqgW8mgg33QyQalT7PNeARBpTlgBQwwIAaXJeUGpumIe+Z5/lms3nvvfdIdLL1UPyxUJ3qvuQDaEekBh81hqgXgc91g7ZtN5sNg2FysejruibnlquKWooLbBOZiSZo6ezVN9KKDZmCFAukLUuvVhvErxOJ0NtRi0FoeauqKv7FX/wFII+NrHR6GTYJKlWuToUUl1vujWoyDfHMkr6ZTp00rQYe8cDl27OFbf+6pGvEnrERxQXXydVGoxEMXvLuuebp9prhOhwOp9Ppt7/9beK2rusA9yATzhU1cNputxxMXdc158iPRqP1es24FEhy+/2eOHU2m+ElSGvgMymvAilpd2ToCEYUWYcr5fgnS45/y0Vtwj8UyVgoQLatvqslvci52D++otLUIJ4F3JUCJ7oij4+PsT5bnRvSKU8VkkxijPHm5oZw//Dw8Pr6Ok/oJ3wLT92rZ5VMgMnSw+EQmlOZdIw0anIICZutSw5X7ZMOMt+8DYQhdJOc0GGRc5BpLSrenrFlc9O2bfzzP//zWodhjXSoNd4Kum+etFb0CamoSObxFprVkymVOdA43z4pi3TJ4aq+XS9HltAuck2FcHYvV3so68LBzjAazBhFzmoNiooxfve73yUMJbtPEQPQD5LZaYILHyFridrUdX13d4cx+9KXvgSLrlATICD49vb27OwMqsVwOKRARqGAJ0JFXRfn7DBTU0iz+JHtA4GtFnRDRBYTkXUmulULUZZkHg0Ur66uos4ZocdgNBpxcgJKxdZ//vnnnZrTDTPwA+wXj8wUMOb+VhqSiZyR4TD/Yq9zeUsdpd5qSEKhEYVt0lFY6xiYNBfSiSLl4NVWtdDoButMoSmaRhNGJbzat4/t4s3xL/7iL7go3T1gHiodMWHS+XJG1S5k8Kco3oXNidfOj4qlTBO0mVqEa7GU7MtSqGdcQQu8XTw7wTudH+z7nm0gI0laluCP+P709BR8zJ0Yx2MbPvnkk8vLSwZ9Hhwc3N3dYcBQDM5RXK1WXJMoiNGzXGEymXiMAAUHdAaUTP0rJAfbOCVQqlMsJmXOXlMwvJNZP7gAACAASURBVBfOF3cJR8D5QctlnkwgJLoFyRTiG4OFhsPhwcHBy5cvCaWCar3cD/rJYX6Njqjoug7PGZQw7JWmRNYLNR5RfLRXRANLjY/Okhptp2SlpSWqKd5falRjrJ8CxTyJjENCH8rEcrVLwQvBBGnbNn7zm9/0PFQoInVdMz8+JllIW+ugIYchmVniHfL3pcGrX9b4SsedW9H9Xb3OI+pU5bH098oScnH4PzhubBVLM5vNPvroI2MG4OlgMPBJhgS7fi7bvBcvXlxeXmICSp0yVOkY3TQFcXJywpkafd/TOgMu4g0IFqrlo4jzPD8+Pq40nKcX6yRXQadXT1OXdLXmScWwFGc2f/ts5kbt4aWI0MYJnQiS3keUM2iQW13XUJic3mnb9vLyElPFycGl2qYbMXmM5UzRi8l4kkaDGbH39ueVeoaQvCZpgX8U2fNia1y1sIAZ5UelRzOl+e0QuoRT6ISPPQaKwTe+QRqYfHjRHP6c6WzXUrQwO6ZMU/gKVbAzVeaDEjWNujQMijp1Y+DEXdgrNF6c61Qiczs952DIj2EQNdRI1FJ87Pl8/tFHH0G67EXQQChPT0+pErSaHFjoLM79fv+f//mfYH1mAtze3sYYPRFoPB4fHh5C5Q0hAHBxNUQaWHrarv8vX2fSG0eWXf83RGRSFEWKpOaqLrfLA3rhhg0b/gpeGbDhXaMnD/gD3vlj2t40DK+MHlzVVZopcRAHkZkR7/0XP51TN6V250KQqGRmxIv37nDuuefev3+fmgmPin1AOOc79THIUkbhYRsk8V0vAu15Vim9SXdsGebV2hJzzCaJjr17947uFkcI3tYeaXMrjHP94osv2Fu//e1vmYUziMjQpbfVJaoFF9jHmIOKAQU/IC/PAh/Xahj0Rqd26Vzf6ZD3bg5NID4GXgSH6F1VNh+JxWaHXZdaxBx65+u//du/IQ2yWq143oMGQsZApUpLvqp3Mbo/JwBNjXAl1AHYK74rH25OhQ9ul/RDFh5SpWyaN6Wu7fucqRfV9r/++mt7oSy543v37gHbs8loAQNQ2t7e/tWvfsXkCBCkWTQkYuUsCU7YMsaj+Ja7d+8eHh6S+WEv+XyO1s7ODoojOzs7gIP+EPh89iqDXrOEBz/KAu0k7X7HMF53sVhQZx1FNfdhSCmhlFFVTqGlcxgG+HzedlV9c2jfwqKjsgYRg7B+odl4WUwEsDWwOMf9xuBt1xl443R2Cg2K3mAOhGZxPx3V2OpFi+k4sAexthII0jkoNeUwVqyo0Wwg4p/n+ezsDIMBg8AnxpmEjVN0NDE0wi1UQf4xE+fZfGSV/c61lCqi4zYM7H1vj8l6oXhDSIr+0bNnz3A+NgZETYQis+oMbH3+99e//nXv/erqypMsSGQBFjH5RAusz87ODrT47e1tP2OcD86Nmj/ZCCcThUBadmyGZxG8ewA6bSmLuBJmzHOu4tN1tJ1ULrW2M44RuDOLpJhSIjbrmreHBcE0WAVotVoRJnG17OBvvvlma2sLNSH7ENIGIzn379+nUaaUQsZl+8WncUKIf+zhvcWb6Pv8og1u3Bgp9IWWMPCrS+WhCSGtAh5LmDzri4+BZf3Xf/3Xd+/esRxNZYgUdEccUS2lQN8DZm+Iqm4KmqZA7LG9z8IEuobeZJX9Bml1zFKP8xmzt1qIkp2ErxNxcjP0/hG42wxTh3r//j36lTlnhJ2Xy+XXX389z/Pp6enOzg6BPnHRLDoAOe7l5SXw/ziOf/qnf0rcTAaMH7i6ujo+Pi4asru/v8+3Ex6gRZ4FlA3DQLDESi40/ZN1jue8KMvM6oXvIgtkzY9wKGzjN2ks0izlr0G6Q2QyozjDzr9JLTjYOeezs7P379/DC2QNQZxdPTg8PKSGze0YNwdJA0W1f8DqOYbBV4AQOjZ2dGAQ3AEzfzHGOKvLItZP+Ek0rEkNAPwdDou3kz+Hr67//M//zHhxrOlCnVZ+PCnQlWYV1ewKDG/NYcqd/dpK4jZcNObBJ8GoVhX0Gx1x1tx5L5b5FDwb87FWqxXKbRxjXnT3onTiAKCUAqDx/PnzxWLBEF9c0DzPqGUNom37rh8/fvzgwQNyXGMUFErneb64uMhqGaXgQHGAXX7nzp3Dw0PP5SZQYUGMh9inDSr0RHNYAmeW+7IZS5pqlQQR4nmMn2ZJihPRbWkqR0ROcez0Q0/TdHR0xLM4PT2lLEgY6Q4sxiOY79l758AsFgs6CiDYOlifNB+Ii+FoOfbj5DQVhh3eDOqqS8Iq4qYvQaDX+a6DcEcfXF7V0BZnoU4hPhwA8sIuJK4EuQ7HUl097LY6DoHGIE06q+LYg4JNE3rlTNfHKf5wEH/OPmetdoJBvFFjIGDh7F22lxF9wp7t7W2sfpLKUq11d3cXjYaTk5OzszNSWygMQHt8LwPcT05OmAgEyEN1uariwzV48xkJwY6ShjJGpbV27969pr6QouSVqxo0WgFP5UVbrVY1lHiaoP0quJkHwSlyh0AL3EFMQ60VaItnB22Ty2PFspq5pmn66quv7ty5Q4MbRBI8IVCS6dAppaOjI2optmvu6GWX94CNNg145SKpEs6B1Jk20cKuUpcDfdv4FIoAdgXe9K6Wsm8dU5g62kUmdR5c/+Vf/oUUwdxxB5rGtm1vYvzkP+dA3cnqK4iJy6BOnyyVvx6AC//p3GjcHKrHizvHQSVNAeu9v379ehgG3ByrQJLnXYg1pXsDMtyrV68GUV9tHb3tZomMP3z4cH9/n8CGkSrU0Wyb8W+m7DNJEoDFc/hAmdipu7u7WEonlEk6ag4g7UhZtFHiA1uaq7fWIIVBJRdbqByKPjxQ3kmdzsYSQwhthD1t6ptjxYVGeHDBLCx6iax2U3lhb2+P9xOROi7wAbPTdgB8fX1NeyTPyLlvDwmxQxrnSKP0Bf1On7FZIoVcgN2FLbKXxcfmuwDec4KxRo4y/eldAxpwuH6DS3dNYjstNHnZ46QwHNOFmKS5Tl1gFqbFCAwrUjXjiTtxaw7J4jiOR0dHUJXsLre3t7kd8BaHW7XW3/72t2jWZvVbOVnHHpyensIOYpQQPtBNrkmZ4jAMhFVffPFFFl2RzUHzFDUmtsWs+Z5bmp2Y1J1Nh65tjaGeLIKXjRFwHtmew62suTJ5UyOWz3wfBjPGiRstaJHzTyTgebLDMKCPhJQ0uTsdBVkNrrVWDvAwDNfX11dXVwiqGvDhvngbhqNK+qGoxwNvRjblPZ2VKvgMe8c79h4lTur9aSab91IXQphUHqUaM4tX2/Uax7H+v//3/7BqtvdZmGMXm4279X8l4ffeqTy/WRUAl4f9Tt9SVbUlC+3yLu+hVjeICWcbUAK7mFLL69evVxJ44/2QsfgiOGEciZcvXzIzj8ePu7cXogt+nucvv/wSOLxKbXOhiZS0DTS1Co3jSBxMZ6DtJTsVeDGpVrW7uwsBwckVzCL7T6thjyIzjmIHeZc78hlCKdfPy2kSb1iEweiQBVcSwyqC/5hm0MWBBaK5uroCAySsp9vTauxgYqMauB1YQw5nVff29iaJkzbx9fEVllkgCTaVcNDg1FFyvE1QvQ2E96R9XRbhpylddrjuX+cn2Aino11tDx98OL8wiaI9q2xGJue4pQXiXgpTrL19+V9Yvjb8a6m7JKkbcAOmaDt/cJ6QlQcnNQngZAgrnf0cHR2xV0jfe2AO1loB9bFkX3/9NQ6BX7y4uDg9PQVYtC78F198MWm2Uq0Vc263w3ZJKZEn8CdOH7FopEVfv3597949wEGX84CYvPVbaF9sQrdaYLB4T/TAhCuhqOJ79MoQaXi3dUmmzRrzA0xMRLSlmUUu/nDOoQmi3nPr1q1vvvkGMHQOrGyYMvbw0zQRRLXWmETGQAma9WYxfLJyKui6kUHjxDcpIfYmtnJEE5bv/3I6mqTzs9JQohxq51nVJF5duFATxfqDqY1HhyVz1SAmH/EAjEHLbiVVJlugWWxyP60sENC7n+PYlPvH9zhnz2o49imH97u9vY3ksnH3qsmtTTU7tvvu7u5vfvObWZ3N5+fnZo+ycLBcAO+GYQAU4rQ4o2CX2DWDPi0WC+YD3Lp1i3waY3F6eopt9nQg1wRmFTK7CLo2QqaNFNUZcadGWrz4Pjk1TIAbxxFOlB8ZG3RWWYPedgKSJrbsSrrcxO4EMxS253l+/PgxMEATlbqKFgrqxcYdx5HxycSl7969u3v3bld1H5uCpbhz5w6PDIwoiffqNKBpfm6XPkMR7817w1nBLN1FPN5aHHsbC1Z4rbaKlabXNSkQO+KoP/vZz9w/bucyBEn0LKAmFmU4VVWlSgdhpijxhkHdlSVwp2qod+QAYKVNdivv5NOoW/lb3r59u1qtQO55YBRWjZSxLV69esW9EIai/7VerxGmba3t7e1hnCbxGUexrIgK6BQjGHjx4gXdYaenp7RZUWba29tjWbIKKWxirADDxZLKC4Rk7P51aHDJKoXO4np4TUoYJtKChE6Xaixel7CEkgUmLKmUOU0TY3ImDZaDzGyr5yhge3v79PT0zZs3k8Z6EyJiCIjyzZxntYn4pzBMyR4e4NXRCKAq+4rqZFJW2oJAdIwveuiTjC5iDtRX5zM50AeTNG27tLIdydsQf/jSf/mXf3EswfucoHCOHY3MAeLk4GKDe6jqxW1qiuVCQyI4sqNUJ4pQoypWXPT7TXhClooG4fLJyQkleihrcxgV4WDp9evXCIEAgLAzBgkEgH5+9tlnWYPizIMidXPF5/r6+s2bN69evWJqvPNaisHezZCcgXfIyOFR8r+D5lKtJXVYwyz4Iqqc87Ms/Lepf9pGztGmU7qkSURrNVfwnpubG0ekoFgkNqzG27dvObTs0bOzs6ZZg9hmRACoANDVgJp81/Q3TC/fhZ2iYxh4AGSpS5rSns3JiRl1KeCbToW7ADH74RxY303IZBejYRi+EzcZpJllQ1yC2iy/NQdp8fqP//iPju26FOd4VNGrpkDjmUSlbGEqTAkEDFCwrBazLODIR3zW/IselF+H0E+cBZmlQBThcGLMGKeFEo5TauLdFy9eeDPN84z3oE0spfTZZ59Bar+6uoIlz/O40WRFUNGc89OnT4+Ojs7Pzy176ncuFosnT54cHh4SU7H1Cf8Aguj9deHP53lLQ5Mw3o4Weuh1tPdPob+0ij1hkzmK7uYUqAsbtdG9DsNPs4asEMMQmSTphpOa0/RIyNfVe7C/v399fX3//n3M0Hq9xq1xy0tNeSJAjekfXdRjGChRRIAdpJbumH6SKo9R0Vm9EJyZHugts/gXSRW3EkiZMT3gnyyRE85JDWWttfrzn//cbdTe3zbJ9gmOakrozzDQFv1RdBpd+g5NPZp2ak06eDHN8De6z5X4x1t8pVcN7S8sEAH3r3/9awe1+GWIPaRrjx49IuA5Pz8vGuIABRBoYpqms7OzZ8+eeXYYY+KXmv7AX5jLvdKoJR/jWuvnn3/O6QIvNyZIGRgkJAmKLmJiOxV2NFzELklC0rCFN0EvPm32c8c1nDTwD48Ey50sha3Pacw58wYmB1cx0mh8I6o5OzuD0ldrpbA9iajiWcJ8HVavqSwF3u/4hMiiKaXGSrZAbqviWfbNcpUj4SQgyFYjSTQyciidJ6zUJpHErvOruqjMzVxrjI89LJuShYs72MFoD8zYSTMv/FQmtUEZjnRMxj/t96uo8IOIFXzgQkohNh7AC0SxeFvbA5bpf/7nf3yceu9XV1d0x5dS7ty5s7+/DzOCWo+f2aNHj4D/p2miNYTV397evn//PpvYFH+eEI6+CATLoTRDdEvrzCjCJjaP2moWs7AIr6gifq2DdrEfVVY/ELtkS7PPeHDe9EXAq0+I+3XW6rnhh0WMg67uFqJzRuuhKW+/RwNQER8b3UUiQEZOgSiklDz0MkYKL1++XEg6hVBkUPdPCpVaXt4bXBgbbxAJYA5yq03yGXPgt+GC7G8dDjkSNkxiNaeUUv2nf/onD742yBBdMPYspmhN9fZZUn5VFbEqQR7bexLfFggb8SuaYF0f3KS20a5uGJtMSJ21ViaqsxFLKbdu3To9PWWAF7ndtUbcNYlhLZfL09NTUmeDsFlztp8/f35ycmK62MHBAT3gPFrAE0N7LmYNQbucKz88PEwpHR8f32jyKR2xpRRiBof1U+ikcxqQVctchgnPTg98KgbxQQjtaigGd2F0jokxYYYreBwgmK7YzBK1hxDOnDU0VADKYMIZwCD739/fJwotpdBOiNOY1NSG30NBY7FYgFjEWmoWmjSp2lVVA87iFkyq8ZXAG+2hGTKrDGLbMUkJnc+JmZIxxmS6549//GMKqyuNEHRwaQu0kPaLcaFZnQ22PcNmx76DnCaNF5+xQTzEJhnDpvJ1EneI71pIcYTP54HR2+FEcGdn5927dxBxSdS8+lgIIlHs4iAaFkx9YO/Xr18TUPEeXEHv3b2zRQQNPpNaD5I7NrR7e3uHh4ecB0efPHhcP5dRVbNLYgd6Tbz7q9pKcsBAsZE2H7xttVpthVHEObDhi+oMeOwkXhr2mOzz+vqaDmasBruZDVBCucMDsYGMMbRc9u3bt9E8pmSWVejkqIDOZQnpAZc55OsS9E0B1SlhoGoWm2NQ33B0AmbLO1duoWBicsBKjWwUg11gtd+oP/vZz8iNbIONEDs9tYFpglGrpNLta1Joi6kCuYvmhsfgJ0lAvAeOXtarqSJWlMUTCwG0z/PM1Rq4PD09RbARWwhJjjCGx0wYxl5hSspCHZWUeyDD+lBdXl7e3Nyg2llrpcZ5eHhI0kzIt729fXBwANAJayAJiSIDprawXq8Zng6WmjYHYWSpjiblc5PEAbyPc9BEcqI/hH4Mb4JZ1U07Cs6Vg9ikWiRQzKQ+LHb8MAyvXr1arVbMT6hqbzg7O+MGT05OCCQWi8Xe3h5cUUJB0ptJAhMpJQd7VVOPOIcoDFDxJTmkWlKC1o6DhTm0v3GivEXzZgHRP+yapJbCa5omguccSuZFY9TqT3/6U8MRSYIOKTCfHQ7FYzCrp7OKisQl2mnMouZhz/xzH3Rfx6BGB2e6Vk/hS+3xW2vE9OQVYHMnJydZ6oW4C06Ie7HtWPAG7vd98eLFIC5k7x0LTZDN0nCP6/XaOtillL29vbt37969e5dtsbW1xUQMq4DYL/PtRF/s8lmttzz+opJ5Vaun79r3nkPnuBcQnGpQN4wDmy4+r4NjJ4isM60IVgiF9mNf8fDhQ4MwYDgE0B9hl65vMPclawjNOI4IQ3ANmHlz1ChNppQYQt7EjR1UvXZA4UArrokRMP/dXs6moSn5dtDhyALwwAa6hHaI+uMf/9jZw1oDhWLtIIlRxE8Iu41mJqXzjuPtprkTFjR6q64SsreFvY3xkC5V+IXaW91g6tju3bt3R0dHwzAAcXLblIo5wysNNvQ/oVUi+UbjNgyWUsrbt29nCSI8ePCAg4T3ADMh+SYzph0MiCOWNUaxLLOUvqmSWmrSZ6ArEeR4D2EUmuFgr6StzxAm6To4zCpcOnokUTEDmUwGKqv7v3LOLBTrj1oMu5xlOT09xdyAAVxdXb1584bREPZUXQQe5+IEVLavtkpJdZ7WGmNKFpJJHdWjYwM6CwAl7k3ixjoN8IotJBHrjM4Hg4DZnsE7bdAER9an/vznP6fqkQMjfwiqkd7r3t+GnMZxXGhuwKzuCt9kDyXeHNovehjDYW+QRUC3l8jq7psl5soYvy6u35s3bwYNCAEbxTQ6oyIz42nBx7y8vGRUBKEzyigrNZv7sL1+/frOnTtA/nzF7u7uvXv36AC+rZdb8tnrSwnbczEAph47gHFxPlM3Ib9oxlKgi0fbX9V7gMXx2TDCw9LNgV/I+ylrVElOcBlcOVkv/s1xM5+Azc45n5ycwK3qvZ+enkIZgvC3kC48y8v1Q65m82Euh2Fw/ZirZRx1FYbmZDcp2bNbcLLuOGoMg0V8SHpQRplDNwyGn5/T+tskhM761J///OfXGtTz4UdhqrDTL+PTjsKT2AopzPXOKnbkUEGzgXc0NasQ5kAoq7bXBRT2MKSM615L9Pji4uLFixdJUDT/Rb0TmzRq/iQtKWB/33zzDfOAB81R8/Pz2EakspC55EnjQO7fv//o0SNsNr2zODRSXsKnlaSkYdTwHqASvK3JdjZspKTYEd+gEYgiMlUK2K5XuAfKzbBJo/K5wjydn5/zRYjbIXJMCE4j2Lt374gCsgScWRMCPEp7gF0LSSbv7+/fvXsXz1Cl+cMh4RxySPAwJfQYVmG+oKucoialqSJFUfsZBzMp5E5DEH9eazSgX0Y/o+2O5eHoV+vPf/5zN3l4lRdBKGoK9AxnIdEJLsNwv6S6mP1O2uxvWmvcSwyZuuoAVZUEL1wWm9/9Fq21ly9fJvVhTWJx4ltWktkqIlpRijo9PZ2miZKfV4ejMoXq4DiOb9++bWpR2Nra+vLLL4F9nM4iiuhkZhDBCWNDFFdKAfWrtbKT7O6HYVhJ1C0HCqADS3Z/EnE3B2HdtQQG7TZz4If56U4aad41mKNr7hD7GAZUSgkcDICcyTF4sIVmV9o/IJDhDAGg2f52sVhQW+SjmCmfpVbE01lq4NUgVYsaxNQc+GWJ7vjRzKFDwKmwk0wb/rVmXjgfwIFPmi3ZwvBt78APOQCB/hiUNhyIV0GZ9qpFQgmO/oegnjKE2n4OVWEfsFHjDJrKBfhQl8y6xgQ5+JvDkIujoyPsGdF5Ur5rMzNLYZyfvHjx4vj4mFqHH1VTQxM8XuRxuGVcwfb29r179x4+fIgZPj09JZjhnJMo29vyX6b6EG0TUO3v7zc1ndGP70fIs3GHeAsTHIyHsleIH9ycMGiM3BCUBLx77ARaYJitJJ3g3Ax7TDqEKzNBPwmiRe7XxUc+BISNg8EGxc0yJ8b4FeYASw+q1lU5sT11OtRC4ahtdgU5NXICYK+YRa6pAQcrqg454LGpnSSU5MB7nuf605/+lBqHfagz7qx+HO9dL3TVwBmn/CnANfgEO40kYCSe8i7Wu0HlJIoLD9VdXXw+3/X8+XMHHrMUiXvvPI9SCsxb9t+jR49QoDfizg4GrSddcwPD+/fvz8/PmXbx5MmTg4MD3CCLww7me7lldjw+gYdN48iofhGKAHTBd2naOcq3CTS64sNvr7KUcHkOHK8m5Y55kytmvMXBcVHX3yDmeVXb00qyIs7isN+DtMG3t7etocK942adImJ9sVMMR2tq4+bkz0GtjDSa33IkTGkZuvggwpiDwBQ6PbzjY8zM+thkeFVngb9NEJAhHMxcVkGWS60/+clP8MiTGlOy4FJub1ZpbVax2qtv8GGxOVJ7Dmy7ogKna7pJjUv26VlDX1JQvMghpS4aT7bWDHoeDPOOfEqJX1Ese//+/cuXL8/Pz3Hr1PCZG/f69WserXULSaDHcdzb2/ve977n/nps/2q1unPnjqts9Exi+FNKFxcXFxcXTM3ghJB0Mnt4Emfd4WwOqICDGQddjmj9LCJ2wapy9hwu5sCBGVSOtC1caDBjaw3mUsQKyXCw0+gsoQdMtgCjFjy0a2IN/BEbbJAA/pcBm9zLVphbwSQBfr0L2EjCzaIvnVXs8y43KuC0Jxp1MEDvWCzRLCkNAgSyHeIF68Swma+vr+uPfvSjWWJDC+lIFklx+BkkMXzKJ93xTP/1qXAmYH9iNKOJPTGoJ2gIDNsiGBiTOYoNyrZj6KfT8d47KS8aZlkCYKWU3d3d4+NjKL5GhGa1H1CapWWWh4Qq+ueff+5BGDzUs7Mzzg9O5tGjRzg3DvzTp08ZxAttjqqq47rLy8v79+9Tc3BU5qDfqZG9dhXTxLs5Oska2Ob2qH46Pv94CSfBDqDZskvJOGMyzGOz1SQKKqVAOGfTAwEv1DHsmprD+h6qn1ZTJem0cZw1AY3SG+vgIJ4T6Hh7CjJ4PXD3e4AB5jDQqEudP6mivFaDh3NREkj2FQZ0UO28/uQnP/EMwKRmmaYXbojQwgeDfWYAtEpLy1iQQ5osmrQPkg22kYqsKoEDJHwCxsYJzcnJSQ85bhOwxUI7DEAbFPwBSUAXtkDuz8/P2ZSAG9fX148fP2YqXgpipq9evULlAadE8cscdzrxuZf79++fnZ0RSmW1Ljx58sR9lYY7i/RmmuQCRolWNKkWTyJ1LjRqzbCGjYtd61rzdbB8a43gJSCcNXxkoZ76JKgA3YCuzpWYNIPqjIHFOIiEwj4DHuWHiGTZP2CMCfwGVcEM+7gT2sdgqfk3iDX1MDjDGyPCoymMEXLMY0+I//QZWGmwjROAtUhro6h4vff64x//mACgqdJWAzlxLc3xQTXCJu4+1iKlRCTgC3J1xhYLp7MWm4gzY4r2Qs2TDoKx7jZst2/fpgPLgmemZ2f1K2NHF4vFV199lTWMA3YXlglLyWdSfj8/P3/y5MmDBw9evXpl80NfH/ES1waAw5KxOVhKgJTbt29bUs4GfpRwYhYlqaju44zZmU8O9XlXlKKH9PGwQ8MeJbFQS2AHedP7V0xcBf10iEWCUVXV4Ys4vVdXV1R5ES8hClqtVhxpRmU6zDB2udYEUnA5EGRiodVqxZo7XHEwUyTNb5e10tBsx4H+i72Kd4s9Q9qkP+UgMIOX46kxCLQFflr90Y9+RB3AUbt3OXfCJZoLOakxqqqqvJBs2GJztGMWhF+E2fmasgSCSuBEVJWHnd/knMmfwO/X6zVqBWtJJ6zU002GypQHIA4mANAMABXEPufi4mJ/f592Fni/pMgXFxfMAOYMQxJer9cwvWZpVlbxNzkMz58/57iyP9CR5UBSC2OJJo0mdwBJWWrUDGpbtSZ6c1apdZomp1XGfHKYZx7LPVlsM37LX5RC/yHxob0uuYoba8ZNrs4oHemufqlBfTCcZGwQ70xi73BhRI+cqx40YFwJsaGpgQIYs6CkPN6bCcbD9QAAIABJREFUPmKaOYwYW4sOw/Xb8BcpIuecvX+y6k71H/7hHziXLbx84GbJbzTl1MfHx9wq2UzsH+cMJHUUkKBUlZN74P0VER+il/ChBF1dSxaOags3T8sS3pYdxg+fP3+eJAzapA3Krl0sFsB5ZBH7+/tE8zxRql0I3bx7947hLkD+QJ/L5XJ/f//OnTt0lrmqlXO+vr6m0R7NLKwaqB+uw7Ia2JG9vT0Hb/6QpNzdgaLje6OBMd+Nr67+yYWkN6rg4Fnos7lPSZQWxoZzZsxdXwflFaAt4FFOxdbW1sHBAc2i6MbZcRUBmsSHZM/YMqKde/fuWccph5FQDmz4ocXkfHS5kpUGJsQ0oKiYwOPOUkaqap1xL+ioiUxJBOmbMGMhpfQBBm1Bbo4vs1C419HwKH6NjBmH4n0/qsfHCYoDuxKGHTShe0lSTbyT/0U2IqnSTBdLa8183SRmS+99f3//22+/5dshmQCeksgmZXhkpd///vdhdLqVMQmQGSVrRXxPlAzn+Y//+I9ZU+sKYi+R5eJUDKLBgcAatCnSDTcPoomb3TZHzeaAMiex1W3eatAf8HsAi9mmSTheF94/q9eRJKGGmVmUxhyIk4aS+OacUYPLOZ+eni41XRj4v9a6u7vbWiNjhvTKzyHUwLr13pjn+erq6tGjR7N66jnhQAtJ+QwR9bQpsMnm9g7OYZSqL74LrDdO43AfYOZG0/7YvTR8OtZYr9f17/7u79hJRHu9dzgh4N9rSezyqI6OjghhDQv0ML3VsYGdFAbGz69orpuTDU6hUdRRIwRnFZhubm6gZFVp0rOlcJHb29sMBCB2B5CZJeJ3fn7Ox+acP/vsM0LAs7MzWhPR5yBagPLO59MjT7oGAEpSSGDj0unx8bHnVfIhcOOauoI+GJhavZ+SYOyqTvkkenOMPIsE2IzlRw/g48H716EXntVOKvhjTW4058u2k8Uv0uGCFNhF8sWlrNdrclYKGoRAHIYe5DO4tlu3bjmSHNUTjIHDVJ+dnZFOrKR75QNsRBVLmsTec2C8lkhHUVnD1oHfpbbt0DGaA9vfWcyilBIWyvl3/fu//3tsagmwqymfNkvEXlS/a2h6WGjuTd7kPiQVMsYgR+zKF4/BRDGbwy6OpD+Ehl2+fRKF3dnhs2fPuGGicHYDR3dWwe9P/uRPeFqg4GxTojis787OzvHxMc2Qb9++hSrX1UA4aJQQVtwpVGuNzq/FYgH+zaSw3juUScpA4zjikfjSFEbYslx4P4LGtVT+ogcYQsdMUkmxizrvtXIwYHtpINshxELdiVQqXHjhudDbtdJ0DzLXra0t5mMTStEIzw6h7ZOx2OYdOhSJWdMwDG/evIFBOKlfivUnwyHoNQw4hwpuV2X6ozSyaFi3I59ZwjOzuiV7IIYkySVN04SUHRuy/u3f/u2sSVtdwCILyp7zmn777bdmGnO5uDm21yAJoCp6XJJ0Y1Nx7SO0ZwyURse+oyYyEfMA0ToSwKQRRD579gxowo15DvJcnD88PHz16tXW1tbu7i7gIKbo6OgIy/fu3btXr169fv06qaVmFFGstXb37l1+14AStMejoyOPoUfyCe40/2QSHiILWaC1o8SkcqHXpKjsOIVGvEk1XUdHKeTHo0YslzBGzgs1hz6BJrw4OpYeeibZuziKpUYJkjsR0IN7spN2d3eRHlpqwP0wDChsl1IuLi5oCfDDcvKahcIdHBwYFMqBe4etaaF8FC+yafxhFgDFajt1aZIK596nwAjKYeg1a0saSQZf/+Zv/gbXP2m4rH+fcCLnvFqtjo+Pu8Syq7Su+Ls9csT1YoSDGfCl8Kg4OV0NEHZwFrXFOdzc3FCCaKJ8kk49ffp01qARGuSbVKCzmoAd4nMvBEg8nt3d3YuLi8vLS2bo7u3t4W2maaLThU6/27dvc2BSSvbvlEixi3fv3gU4Isa9desW45gIz2zbsoqmJSi+ZGFuKTS+VMGmZZMxbhPoPM+f442ShC9l5dbeN5gqjllTKa0E3i4fTu5o906to6kUxYOYpun9+/f0dhEfppTu3r3LyQH0JEj21i+b4Cbwmk/FoJFcoyaWU6YcNR4uZkfOXzml3JTbPr16XKpvbZZCurkV5+fnHxC9v/7rv4a8bkzXRpqkgZCaplsMJDkfd458n4/pKIVdB/o5TFadVQD3408q9PrkFBGnncKy++cwVPnp06cuUJQw7oYlsLgNOSLE5q6iGxnO8fExdKCLi4ukAiSsd2wD0045BmtNGN/a2qJZvpRCOMS0CJz7PM/37t3z9a8kk4/hsDguRsRbcBA1ct7kApA2lICSxRQwh+mfY5jG5cdnQ4jFWair2/6nasRJVR0TezdoHp7BVrraOdLv3r0DU2adScYmMeFIkLY03XmQDFvR0KS1xhTYOvj8L4MOwLzJvsniONl+ZTGi2RuD6LecCkeAN9L9dwZchMTM83x2dnbr1q36gx/8gG3H/TvYAHkkcXz69Kl3/1JjOdj9JfQXO8A1NdIPo4nlNorjai/h51pUH+nqhABIJXlaqxHs+PjYgIMLhzSFEbFYHhAHgrQJu4Ge4KQxlTS8g/kYpGNnw7AAChyGATkdFvfdu3fwSVEVBzklBiPGtV0308tuky3SBHf6iTrGsCUzDtY0LqWGsc1ZEileK/6ZBaz58MxiFn5ka3ooNbDUrJt7l6NJgkYOy/Dy8vLJkyfX19fAqS7JYTtG8b15ZNM0wZuyvXOCS3+901nXVYhM7CT5lRR0qKLDdMKwlsxCko4G2937k/08h96AaZouLi7qX/3VX/F0B3UJsegc1pubG4atF5EWCf1ZbqzauDkBwQd00JgZk8tr6ADyzrD/ddjq8KnWisWdRQeAdNAFCrHL1+s1DVy+SZqSVqsVNXYYzjwkWxegPVup9XoNY5ktdXFxsbOzE/FB8grvVFpJuEJ8KfPIYvjrvUUENavvvqhl1AGM6x5JaesQyOSGPrz1bQJjHDWrWGYbz+6ZVFPHxZGZGAOwZ+YMO2YYNdKdnzA3dnt7e3d3l/gB9TtnEVzeoKZC/DBZBMvL+eQzQUudIuMYjSA1le26ampF0529CElVESM8WUmz61ddCg+rMBbJ0VTv/fT0tP7lX/7lN998w6U7TORJr1arZ8+eVdULbclSGF5rwNvJAPfZpRc0hDE4o4b1ZQkidFUuI9zBIo4a/mO/eXl5CSRKISypjEJ0zpqyfPg+boeHR1BEXPHu3TtMFJ/Te7++vt7d3a0i2YPcQ41m8zEyg+LAo0ePlssl4VOWRuqdO3f29vZ2dnbu3r1LZYp7JxWJNqIH6NrPzPHMLLzcbiE+WtwLS9RD00wMfrp6X2aJ7mNlupi8BOgx+/Krq6+fHUzLKPMNtre3Ly4uFosF5T+wXeMlbESKa6ALjky6qn7DMJDgsU/AKgYVQIsy+3gjDutd4og/LKGxqwdKCCmvuag9IARFTXaENr33+hd/8RdnZ2fPnz9/8OBBDROv3r9/f3R0dHp6uiUdU/xUV2dG0gQoA3ODJprMocnVjyGGQwaAexCK6wLRJw0r4E7sxJkJ4CM+S/iEzYQ5d/eqowijB4RS9D1xwOh1bK1R+jWmnkXDgi+NOBQO4cmTJ+4xOD8/B1oltnGyi3Ug7vfNEgn46WaVdZwIOfhxuaposqKjl1EN+A7fcfQGB2d1kHWVw5wp5VBDJfCrIrPgpjBPrmHlnHd3d7mLWQo3bDLroyRxMbh4jj2eYRbdiHPC/olmizslSuSRkVtmtcL4jtYi+Tl1NibGkzKHKguxnNTl55xh0qtJJbuUcn19XX/4wx9CefecQFYNcBBSu0HPLIXHLF5XCbBGUXruHyZlYy0M9uBq3DQzqEN8Dj0Gfie4RO/9+fPnXNtKGpS41/V6fXl5ySGxKNBanXtUfLMG5sABBuO7c+cOhR6oELMkfSjosFhYvocPHxIdpZQYxrq/v08UZLt+584dNgc1AYLGW7ducTAIrLPaO3uYDewc1G9w4O5AKIvROQdkvasU4Df3QBAqmxKufLJjUVhVQ1Cr74KVUkpkNU3DHEgulxouj0MDTgEI8tM0hGqXnjT/HH/imDAHaIiQIebivh62Ygmz5Owwc2gS6oJHJ3E6fWamQD12dNA1YeD8/Lz+2Z/9GUqD33zzDcp+KaXnz5+/ePGCp+jNzaX7GNhvklbauY8iuGN9I2zn2GshNSh7pSJiiTcH5o1tja43+xiz0dU3iHuhLctZIM/v4uICtIG1nucZzB73XWu9e/cuOj8OfjhUfMj+/v7e3t5nn31GFzyd49w7RgGSKRViIjqwIA6GrUMOLVQ2z86Dm+pis0RRnSrEgMQbwq4jfVIe8kf50/j7WqzpJoVqIkDvfue7s9tElAe2UD7Dbyyl7MCCQy+jXMMtN5FMcTJWDQNKKptjjniDJcyyRkI1lXW9Vi30OWT1CdnscpZKwPF9zU0ic/gfgM15nqHx1h/+8IfukWXnnZycPH361GQHrnuQpmlWUy/kFrtRvt7kqqK2t3gMjI4Zs7ORWIR2MJs9jukwDC9evMgCHMAi4tKwvxeLBf0rrB1aZeac0ZLHFGj4atgDbxE2BLjQ1tbW4eHh48ePHz58SBJ/fX3ND/f29ggAyP94bPv7+4RJwzAcHBxEVNcm0M97Chz9rl4+h7Y5MI17aIDye5w15TDOsAhgdUhZpKtjpMXl7SYC5iBi6UeRjL+OjZJUteSyzQpjPQntkghjLAtoBOFDC4PVRmnXRUdXawW0mEWAmwPdNYdXk3AG12m/N0lMwFdrB7UKkwE49o5TeNU///M/d1j84sWL1hqRDzcwiNJkLlfEsKM7M+3HAY9XPwdNG5s98ukpyMv5sQHFOLR9+/bt+/fv3d7WRJE1MjOIE2bXXEphjFITQ30QolqEJzDQCn4H3YDHx8eLxeLu3buff/45Sm9ZsePh4SHMn947z3i1WvFDQilAUmop+EmHiEsJMnfReAb1diQxCCepJ8ziAqXAKJlVHPCzj4FBkzoQu8Teo2rAYQrsIBaE7LaKj8A1m1Hi72W31U2VdmeDJEjQ2ggCTcId9CqBxkPs6pweSwoTG4fcw/SNmMLWzVb1Ir2PpurQJLJDCnwHnwcWx4S3rMLwhgfA3lxeXv76179GCob4xynRoB4Af719gk9FVgOEffcYxvf1UCsYJIXJajqlS6FVgF8BjHcseKMBJIQc7lAhgWmtUc2N9nKaJprfZ7GGXLfCDxIS0HLw5MmTx48ft9boJiNbwnscHByAfA/D8Nlnn3HG5nk+OjoCnHW+blSb3TYIfZ83tbx7oDSyIK7Vz2ounSX6UERQZ5fbY8Dk9aXOKrf7nNskedltTQe1eplWkEJDPQcVg8Iri30Uo9ze+9u3bz1Wh8DBz92fNk2TxSrZ903AFLaDJrIeqhw9sKOd4GZRjAiPvQ5Nr7Xa0yLcWTX3kTjCie7JyUn9wQ9+gBrUu3fvXr58CbRC1mLE03iZsUv+4nzA3zQGYZWqJhuOfg+cFtuYErhAXJypphiGV69eTZKOAreaNYzVYSVLA0ZJnEqEQ358dna2XC5JpltrjNHuEqNMKeEBvve97x0eHsYh5u/evfPikjwQO+EqmSgBogqyjlaUbbbt7iJoa1cRlb1cPdAVU+iljmFPDANWQYcwC9ueVPvsoi3y+XbC0SL6K+xMMK5s0HEczQdL6m4pIkf4dNVarRq9Wq3Q3rJErr+IapfRQruLJs6sz1IXQ9GormH0lWa8Rp8wqKWmBwnopLoHP7ThuNH4HzsH7vr6+rp++eWXZ2dnJycn3377LddxcnLy+PHjUbpFbPQpCJjBjuTSB5V7SiipzFI2t8+1//Jt8ziHIIrkLCLGf7TwkhVNon07nSBFe//+/enpKRvXMwxn1eAM3a5Wq88++wwwjlIXWiCLxeKLL75AwLmIdcP8Z1Yc3fOLiwv0Mc/Pz8HNWPfeO2m0A+WielBSH2MEMbP69AyVOMqncSSF7r5RrcNJ2Lltcw6VnbIp41fFZeSHRI+OrEpAGppAJJ/SIuHYrHZ7uoVyEMHNSrt9rjCrWeVnrm1vbw+OYAnsxiK1WjsE7xPXFuLRbYFZ0yR/m8V19fPCjMYM2IHWFITPon+Ypuns7Kw+fPjw9evX9JQMGsKcUtrb2+MSuzp33fTUVMTlzPFz1pE8zL6sa5yg87YWqvRVsgj4I86JO4OWyyXb2kV1jI2XjxWhrZHFguczS9WZs2ERDlQKmYByfX29s7Pz6NEj8M2FpgaVUnZ3dynuPnz48OrqCk8I4PPmzRtEUFgr8j/wQV6Aobgjs/F46l63FmQO4lHvSnv4uUPnmMg6IOZlF9GCKGwJcsqziDHe/f5eltHeAI6tHYubJDEcW1tbOOcslG9UlxntL03UCWBTDOLu7i7QgitINogkb0kVVQfr1OyblBK7sEu7LBzUqBEW/G8ONeAsERATgdZBMQ4H3qQk8PLly7pcLp8+fZrUpcHanZ+f379/38+1hckOWcoiLfQ09t4xnw5eyQTsDfyMa1DRyiKQDhqVjCPmWpfL5dXVFUbd574JwSAiOjs7W0mNzLGW75BDwjXs7e1tbW3RIuPWFtN9r6+vyWjJAkEz0H8lsmK7vH792lmXC/u9dzQ0bRE49oS2wCZZaukRtx6kquTE15veEbBPyEf5gMPLrJ5Jhyu8bB1tF22kkno/spqzCDNG0ViMe4KF2F9l1Teg3ybxO6qQbo4K0Ta7BZLVSip9zoyzknWcD4iqG+s4oial+zbZwTavXjdXPJOqorYyBrU5OZNaSggufvGLX3zHTxpUhGP5FosFPW+OurpkQLuGzTvX4cZW0pSMTyg6rx4AH0cLRWS4SWotk/rH379/D8AMtXMtUYDlcvnq1Su0G4oKfkAH0NE4fnSooBU3DIPn1TWxNSfx6ed5Pjw8PDg4aK0R+oNysNBXV1cvX76Exdl7hzQBcre/v4+XIE4wI5UHQ0HNMlslVDzaZvMXa1UEfMU8qgsyty3MAfL35m6a2Olf8co48pklvjRIVdfQmcNXPLBxoVIK2qYUB4wkAuI58uEDGTXi+mAPqItNpPOiJGUkZ7r8lyMuX4BhZYc6DpvtVfxYZ5VTvFF9+CcRC0BKzs/Pf/Ob33wIB3MArTn0X3/9NX0eLBMAn9lmGAC2TlKy7/A9h+KL3bGd1DiOlt5Oog9xM2zfIjABFie/MmnORSnl5cuXtpcryauYfuxzDyDjnka+Yla10hVlrpkgx4+chT45OWGKzKy+CFZ5d3eXzUTKwWHjlltowqBeEYmGrGT0hNFg29A48Y3ewMmig9UUiJ+jaLa2jvbGa/W71FCg8G/5NFYN3pw0oZArh3TougeLQJ9GVn9CKWVnZ+fx48ckwaw2uQdL6p+b5AssMaiam4RgjiLh+QYncUN4cLPYrFW6ok09epxSbqFLhb9tsi25r+zGaMKAJEzGwBkBmXvnCE78nBwA2Ja4CT2mQSQAg1T8m8bPON9KYYJDCUrZuEVIDV4gWMoAL+M40tRr8+nIh7SPpGVvb48BtytND+C/WAjA4Hme4S+8evWKyOr09JSyIIUCfB0Bleug4zhCmWZQABsadI8nZEbQECYaecMVKSV6LzYpENt8zoFG1TanDKagVJk36Q8+NrM0UZJ6kkognHdJs6xDp1UOA6iztBHsi7AsPNOiFsQqzpWr+wRC1hK2eR7USwlfMKs6xJ+xR8zhn49r1eR2Y7U9gFo98CZsbbN6i30YIBNMGp778uXL09PTCm/Jbnel4e+EAciBOHKwja+18tRbmN9EkOD1KgIrcmAvVfUcsqcHkZ9j+JvF3cV0zSoQHh8f81tgBdzMzc0N4j+YHCd2KaUHDx6w4cBDjSrUWs/Ozti4VDzsXq+vr1er1cnJyTRNFxcX1sPjAOD0Ha5gQvb394mIRvVSkgpjHUbpx8Soj7vIYVxkFaWZh8eziImjvV8PXHEbNs4Sf9qfN9UNepAMmsSMykoWV0HFZAo8vCzeF6Gz0wy2/pbGJTkS84mK5xADwUlwNHh9fQ3C5kBu1ExEbnxLeqPYwWgdFkFjmFvDI/XQa15KWasdxbYmqSY4i/v9n//5nznnD2JgPJIiuIp/Xl1dgZx0jZSZpmkpsWKf6VKKwd0ismFXkdKMf1syB7iucdiRjePoij2wI28ehuH169eOdz0LFYyiSH6sSv0YBhsB20LaqE4fecO9e/e4TRJf9j338uzZM4OnPNqFGmTt8VHLunv37vb29uHhIc8YIiQrwHnI4rcNYp75DIybasE9DJzlK5IUpP0r9uZFrxakhHyiHCk1EZVtkmyM5gBVJ1Wgm1BRGx0/nSrW6qTmrJyzETY6ZuZ5tn9YaUYOXzRqzpXBDCf0SYXUhUT+eCJNoFkOQqLsk/V6vZSkbhMK5KSCdm2cmxECoxcs0cXFxX//93+P4/hBgy0pkfJb+QlCwabLeuGMbWWplw1qiufALaQEaBScFMTkXmcLfqJJ5At+8u7du6bODzgapZQbzQirKtlkQUM2GB5ty2XjRlgICwdxL+4cpVDCeeM6c86MoKya9cvd0SNGikzl6+DgYBgGKmicB3ZJ9HLme7E+3tO2Uv5JV0PwHGjAszgzJeid5MAs4m1jEGPkJ1XEKhNPbHSdhPQwTyCeW6cBrAmIfswYCQ7ZxESnQKKEDCZQkUB7wZdS5L25uXEq5R2I+eMkGLmfA9k7ifjgE+sIwtE7sUAOmmLOE7L4lKenp1999dUwDDVCqg6kkl6MQMTA28azibckmunFGkWVY0WIJuMq26cPgfiQQuMfvUW87eLigrV4/vw5x4xMzraN6KhKtOv6+hqsc2dnh9+d55nKAHKFrCMEdLKlWWOGqSRQNKDfktMFMAfPwiE1V/Lo0aPPP/+cHY8NK6GrfZCKSYzm/XiaoIx1kLAdA5FpUiOvs3Zea818b4JB2I4rCcE6KMphWugUlBUdZc2BeYZjX6vBelY71RA6wrIyDXt+J+JEROx+aotZpBguIEb80zQBoBGTILGKSWUnOJBOoRCeVOtokhONEY7PT5cGoQGutRpIsCYcxfPz85cvXz579qyU8mHUQgqQsz0AF7S7u2tRX4wTjfBca5bGb1UDVA/6dd7fhnGcETrK5HkMw7C3t+fnREzSWmOKNcycKK3KXbkIsL29TR3+3r17dvejtLEIS4bQhbOS4gtTge3itzSroonTC6iXJDUH0vfgwYPPP/+c+ISqQlPjSxJcYxowOT0BtzOoFiq1tho+P7yMJvnYj2qI+chURWuSxFpjtaHoVJGOVmoOrIHCOUizGkdhbBQXGiN7PyBf4TzPAJeUxsCaT05OPrq8pq4Xe7Yubhi7K4kX2DXs1cdmCjyOElqBvVDmUDXV/uIGJvctpXiQ/Wq1+uqrr96+fbtYLL4b1JoFPkQPcHV1de/ePYJXq3rg3G37k+YrZiXsozqazZ/DgCW1Pzs2iNbFf0kpUYR6/fo1GyVJUcPWq4gAjA7PNE2ENzlnNHEpA3uD8ryPj4+HYaC2AMPUz4nEYJ5n9C8sEEKnQREPD8j/D/7gDzj5HOCFdGQxMM40knRkB7WkjOIROEdyfcD5ehHyPUpGoCilbmqRaQKUVtJa4+UgKu6ALlkof6mP06zKANAN2wgDXNUTwxVaQZmLN5DvSh8oGT3cC82jJ09batIj9qUEiqj3vR1mXEAOKm48BTh/Ci0BTexgDnOtlecbLU7SsGSsycuXL//93//9w+J/5JrtYvyagjYWvw8834Wn+kzXMLiqh5a8lZr8q3rqisZIOfpcSiaoSD6RsXa8c6224Dt37iTFP3fv3sXq8/BKKWz6pol9hPuUja+vry8vLw8PD5voMa01j0Lh6bryBaiPwBvBFVHQw4cPHz9+/Id/+IdVAkSziDeU4Rygd2koZVV8YXoVKTpVCdWPYcZ4zhl6BduOzCpLvpOdlDeLQY7sm1CRJMa1f8IF2GyZfWBnYnftWCCpF9Fn4M6dOwsptYzSRSyaFjdN0/HxMefBqFqSEFgTl+Hy8nIIPW7sYEbvLKSQNQeChk1q0auqZ9C7iEObwwC/T6O1JIBnHZQHPqRMQ+imG0Ih2geAJNiyUDyGhdpl/OJBehOPmwNjvMRD0Lep6neuQSgPq4YhcbXlWqOqZ7XI7OzsuEeenYR5hqhDBQfNStJWbmocR9pZuKNJgmEOPVHwmzVTnmBvuVwStsLW2t3dteDPR/Z+oQFbSV28IOIpjDUHPM1CJB191cB85Ie8swhV5FVV8nSEyWsM0uRNsuBNQErTCAU+4UYjTvhdO//4v9wg8U8N/Yp2wk3QJA/R4dkg+vc4jlQ2sf1JPOokYoLNP89uCHToGiaArIIe+qSWEicVXXxYB0s9CGV3jQqm2s3FvH79+n//938/nK5Bair+xBTqwSkl2PPuNmLfENswGq2EfrGUEniIsT9nxms1Z/EaVB3rajFJwraR9p+mKVZncQLv37+HhQuuP44jdrpqNgQxLv98/fo1EQhdYK01QiDgTo++aq0dHBwg9TFNE8KGWfNm9vf3rW579+7dBw8e4D14JGjILRYLen+LqtqWxvCJ9ZKygeJDYgdMUnJ211KT7HYS/ugYxtYEF23MjbWdVZ53ImFOQRFTlSM0a1RjPGYG9e0EqlSYigjkkxgQltCqKmUU4e6w1ti+Sd0O7AGiJoyLExJrp9ZQRJrUcGy/18V08NXG4BkTk1RXXkn1kMgFY3p0dPT1119zqr+juPkYOCLi42qte3t72FSvO+wa27xRcnFZZPqummUO6b89QFFBZ9YUjDkQhF69esUNA+Y06ZaiTk7E4sfpsq7dFzUBVG44WkWjspj+wjE2c6GUcnl56RZKLm8YhocPH0Lo5TZhy/GAQfq2t7dRCLy8vORALq05rBzOxLIaJoX5kc/qWC8SyIjRvHcwGJTDxQgUS3gIAAAgAElEQVQiO1aZRN70LzZVQyfJFFS9skBYHoe5HklTakoAMIyoJM1vnlTDToEZ4GxktVoR6vidOWf4gjyXLp1gHsSWRszfaKRalmzRrIlyN5rBk5TiT4EI45gtJgk25TYHRBAIvb169SqpQF4dDtbQ/OYDcHNzs7e3B10+KWfnngFGsmDNUdNQFqHflDDXXrhuQuArzULlrhaLxdu3b5PaGmyhU0oko4QrTDgdhuHevXtLaXaDYx4cHFCQGiTcC2GhBql3B7IcD9Yd2gVH5fHjx48fP97a2iIYqLUeHBzAKeI1iPVwdnZ2enrK6eJhkwcPQXvQ6Ttbtqm/JIX4tYRm9iKljBT4z/7FFHrYU0rgYw4PJtFpSpATdchkqzGLwml77Pf7kuxI0ydR8TAMhI4+qAQYjkYGlTjZJNgsqkDGdtwmlQJBcLlcriSdW8PYuEk8l4UET+umtqnRZPsWe1oHUfx5fn4Ov+tD+Bph0I/+9At83SBAzpnCEEU7bGEW5mMTZSRuFtFqoSayrmQ352yYBazADFA2DVrnWUQoHC46KCTEgDYkUln5Q5Wy+Zs3b+hX2traQtahSr6BY0ZaCQNiuVzev3//yy+/3N/f78odx3E8ODgYVaKeRYOlU9nYgp0h2aEpIXYpWeF7DVLyVaVrYyNJ2W0MZnj5ufoZTaEXZFJX8VqaUA5d5lA/KhLH9CPg026kO8+3FHE2OVR22vGxNqGFK43PamGq4jzPVuTumqZK9kgjawp5IMEkn0N7nRPfJqLboGJ5TAYwBysNU+yalufUpQV1ia6BV//1X/9l3kS1842mqAUkNKUE3lKlDcrTLRprw1YzW9jprD1sDrMhFpLD72putKulAYDN3dTvPEtXlIsEqMGB0jnAc2WV4fBgYy4vL5lxRCOvy1XYJxC69XqNdO7u7u69e/c+//zzx48fYxeBRDkS3I67IIBZ2SiD1AVHUTD4FhBY79pPY8IWcD3ilmhlZ/UJ2Tc2dfe3MG/Tp8ghchfp/0bTPvn8WVx8I3j+Xx/Lplqpf84lFc0a8pbNEg6bRW71NQ8i1fNQHH0tJBfLKk2qSbPI/LrDwlsaTJYDB8TX1iUi6G2dQnUvaVxkDnUPIGw+/PT09D/+4z8WasP/wL+Phr8FQI2XpdS4KxChSH5mI15dXZFB+tgVkVUmjdbjug1T0muLsaHP0KEtH75cLlGl5DpRnLy5uTk8PKy1UpY6OTmhw98b10xdElbsH3QgygKc2L29PQClw8NDHjOH2UxG0594rqenpxwAbyk0FTE5WxryA/iN8hRO35XOIQzbtF2I0ZHjw0mdXEUsaD+mWZT3HDI3PHkWvOi0B5y+hq58FtMdcM5DcpCUi2EV8RhAApkGZ8l7jiUileqqwm5tbZ2enu7t7fE5JuHy6Od5pg+JLesz0DeL3EmVLztSdqMT66ISU1VfEdHvpGkptjW8baVBgD7bH4Cntlml/ygEwjf5mrJwSb6JjpCmNjYbvC6SSRYo1APYmiXrjmEYg0J3k6A2eGUJ3YDgPwBNQP5XV1eceD4WKThkDBGD4I5WqxXa0dh7nha8CfYum4NYzue8i5mTwgxTokG4Aw72piAKHeG8HiY++bk2kcNt75t4svx9JRnTHkpXg+SomsDNMZCrXdC11ZylhNxFs3Myxvc6CvVhYx2a2r65KmDEEiYUzdKis9XnYwdN6iYW5Qwsl0tTvLqaRemcNDoETsoa3rp1682bN/ALWXwDJ5M4HXGrcHSvNQrbpsR7BuEM57oOqj88rBLGuHuPpt/1yoIvWPHbt2870rL/GsSB6SqyYL0wAC008mAMeDwQciDfYzwIIVj9+/fvv3jxgutEh4yNAnaBFcGiVNF6Ly4uzs7OCFqw7ox0JpXPGkuI+I9xtEGEdcBH6l9NbDmjn/v7+9eaCA0EGSOEIvL6qF7+UbN1J6m+cfv+uyHjCBS20K07aGZRC0UDmxib9hQmyPNcuC8jmMAg1nCH7OQtRViIHwCryWGYZBK6ZbOVVKDEHJydnbE9WCjY4yS1+BDudEvzplglZg4spVc5qEwEiGduaRZWMWmMyzoIbdgMcdeWPfXq8Re8DSCpHUi1+fcW/51nAL3IQQT3xWKBGjgd0GzWRZj3hmEwCEjIFNMpqiSYKBS3uWdbr1kTR9YaPhVrq2/fvm1h3LGXprUGWLS/v5/UCA9UD+ZDGoOKm++0qashibxJD5SBBe85/BIA0ST+/RDoDHwCp4LdicxMDPEN0tmD2/Z7O9pTD2Hib5eay6Tmr0GdomUT/Yx+n5DG9gjTa9s5bxL12Nm4SptJvnEIY+tNL8OxrMPL8bpTBTvVWaI4jgVQqgRrdgrO3RGIOhXugamAJV0F0fOsWgdHF8voNMNu8OLi4ttvvz06OrId/673rAdo+dMcoKiGnwITC8jPsWALXRfD5hh0NroHM87zDLqKnWYzGcdwsEFIh52wc8g5Hx8fN82E6upU5uavr6+dtnKKRvHMgCCYz4OXn9TnkTXqdK3BcqPYoDB4HenO0hQyopcFqnIXWbQRP+OqVhU7Yi/sFCgxXq5Zo2Liz30wsKk+JHMoEsdcguupqqfyXVx/VZnWaTSh5qzJnG4xKUHEzjCiz9I4jmxcg86WcxuGgVnzPvnsY9IAltSbDda0A60mfRDGViS1CuKdDLbGrZXD6C0WrWnkgs3BLJKOOcWs/HfTfG3++yYfzmfD7FzKn8MwsDuriDFcAZ+A+/M/ObLgmzbV/OXOnTuosrHE7OmVpio0YVsPHjzgPFByIkzqkkEnQjg4OAC/dxc8sv2Eod795AZeHYucsnBbGjJQAx0F6JNfMcSJr3CCPgTV7yJRYZJy34gXxz7Wniemtkldb0k0YF6j+ORlkwdh1+Hgai1ucw+a0gZJZmn58xRYPX6C7TBs0lRV8EHqykOSZhm5vGOuP5Eh/8veYJOspXXl82+cEBrpJHJKDjRYH8h1UCuytTUI5i6CWbCvreSkYvxK4ya8Cb+7mhJUZdInrwcPHvCwkfxm6HlSC8tqteJIeK/MmovK5mAR+YQm6j8m6vbt23ATDDlH3n9WeeH09BRjAwjAUmLFcQsWMoK3Q7E2idHta45xS5a6PJ6HQ8u3GPlZSx+BbcTDtmOx77btL0L9urL2GoqmWQxwu44c5AiyUqa62d+YAtm9BAEy/72HloNZJOrVakV5zo/jRsPkHAv5YmbhnrPoxFk9jez+qmqMU3+/rUl6bVAxftKcSWuQTBrP6m221pAH7gXauU9IFyBJ0wxImqPKvKnM5c3jT57EoPZeoj59fHz8y1/+EgiHJz5EG5M/qQB85AcI91lH2NVzaKcwttpEYrFv8WbysjKnkb1FYN1VtWYYiU3F1dXV1dUVkeKo9h2bopwz9h7LTWkii6hHK5afAcE9BiOHck9W8gomiyVbSqi1f9KZ3kJzhiuJTfWKUYzAIZB7a2hT9CaYgwonOVINPOoibnNW428JWG1XQ2AJJaop8IS9ibOaY/gKWxa2IGd70GwRikqELr5NOys7EIcMFNGRUVpq0B2Jr5MNgiUgSCAjR0QIZ/DrzjBtuXwLpJTmz/EQHX73MBx2FnPE+UYTwsZHPX/+PKZkH5p6bfU/iv79sglcLpfu6reTGgKN1EEtRq4H9ktTyTMprMTUUVKFq5TUOIcoIguXc+YYeMd4+RjSaKG4pcZddg00d8o4SwHTHtzISdFE8qrWTQfWPtVcnqEGPpOva6I8ZLU+JxWGKTyRYMQowqlt7x1dAkMlKQgnegtWtR+tQzeJDUGXMAwrY6sfg6uiIdhd7Boubwjqs8TZDnJaGGLQxP10UDcFvg0mHDyHXMsDJLmp7e3ts7Oz1hoESiAg9qiVIwAeSPkcCJ2dnTGcOKkcVjVPmltIoYyNH4gBUgqZfZOKsFvV5nmuDhzTJ/C/z19KaW9v7+DgII4QdLzocB+L6xNVQutaDTzThTrZU0o7OztscTxAkSQq5xvhNzu7tSQxnDvCV2MdQQzwpAT9VRzDeZNg01QfcSDBBnKE4IiTW3NAwu4fgrhaC0NusopQpie5wMS+7IIZDEA1VTyM86zDqGf7emfevrASFDc+si+TRu264jZJeCKpKTltjh7y9/K7Nv9DYDTZUcTI28FJU/OK17aGjhY2ZazcHx0dubfBkZ6TMXK8pvFKTITAuk1q/J3ENWqquuacifqcTBa1CnGcpmk6Pj7+1a9+BRL4wfblwMT61PD7SFhUmr3OhlhIJN1wbNPIloUmZayDoncWv8r6h1jWa42OIr68vr6+uLg4OTkZxCyH959EQYEsdf/+faJM+tG4Hs43m34cR0pmHAa8RJYe46RJZElhq3kZWTP8EJqe1MzJmweRYWqtqKa5ujxLOzaHGn5X62AJ0ldVQjcliJH4tyapgMXN5Cif5wUElwPBZNgUHs2igjoiXaphdSXl5PV6jfzZEKb1QEd32kANhFvAH5IxTwKpHWHeBDnOWuvOzo7NU1dtsYjydHZ2hnDiUpILnHbW02oorbWTkxPza2LwmUIUyveyUJaumcUtd3TtZnnKAsXpV9qEQT99Oany4Al/GW8AG2GtbbZt9m40l4aPuqW5Y2xErzK/y5Hl0tHbQH6e00IaQO8vy+fNPUidgbyiSBsnhdEbjmghOxT17xvMdn48S+SD5zrPsxuaiHycaSTplywk6lTF5RrHcWdnh4YKVsnPpoYXn+NshJuyaffBqGE64jLIebjCzzU0UTK78EcMPDVR1mSSbkVUOiLU9ApAHfchIfiGrEVABYrPh/DIwOjYKq01fmsOff28iPVvbm6gb43q1R7H8eTkhNvh89m74NHeqGvNfn3//v1KM6SdWTmg6EEkz/FPCuWaWtU1EwOm33kAbt26hQQIMQCUPaIO7F/WBLgsJNil36RuyapyNKeZkiQFXUJhTsLV1RUxKAtHBXeW5Oo8z48fP6a2RfzqfkiMExGnwTtHIPY5WSRNth2PPIYTRfh3Vrt6l86e/84KGIWIcafZATaNtvoxXEmCNReaN1pUBGjqLzOYVoVQmVXmkMZBHR/Cw77WQJ3Y3kVgSZqbhRSVoC87ScbPeAtWKWl290oqovzFGKDL86O6JbtK3Xwg5vlGMmdOMAZ1vRi+dFQ2S85omibSTugVhEMxaHcS3wOCvwoSbzeaD/Ds2bOnT586Xh3HsUYnkELQ/9FrGIY/+qM/YsDBqN5Wdh6bj7pdV0t1koKQI90SJNFv377Nnl6tVkdHR010g5ubm/PzcwIk7D0VELv+3vv9+/cB9Tl1NDeabZZzNtPOIInd6xh0WZYagu3d76DWRj2a21HThKwcMUtsuQbUsod5Z06QWJYUpOsdF+WQZfYgbJoF3ZSABTkr7UE/tKiVNgscZN3Yr3mzUTipsjZqLtOsIldRESqJ0kJQTiWbSHJnZwd8GclAfyyoA5AldRjIEd4A0zTReL3QPBgst8sF1q3xEXWvVVL/fhNiO6ssmDeHDnLy1xKJKOJ+c7ApA6MzYgP9HR36o93/0UmotaKB0zXybdSLB0+gUkObAptyUlUoq0RKJWEScRIonWcA29l4C6i/g7/WGkOqyUP4Cx2SXaU6J3kOMyht9jB/BRvmUtog+qcpD7P4qjnMTnRqHo2u2d1DEGsYJYcYg5ykTKMKdOoCTFOYXrFW146fKN9oe5lUGU1hiHSXuGeT1pCTMZZuEjchqy+MHcBz4VLxyTYNS2neEI/hb7ECTpFtd0bJaWGP2H+7u7uLxYK5gzYW6/X69u3byNVMQdWLr0jC4mcRBGcxwxk2k0JXZNL8RQeBzuz95zAMBH6ct6+++uro6MgpRynlu+aM9H/HPxxHxuWSt9HpM2lszBBGY5QwQb4G6oRpum66HYbh5OQE/0tXIYebxwYwXKTzOAzDo0ePaujCQdbTIUHabGuOrtZx+SzGFUZrlmhPUXNd0XDLLuzfW7YEblYJTQ4OtQcp6DvG867tounHDNXbOq6zYxU2q31XDs0xs3TV59AyYZvlTRADOSeUmPNZwxPGcaQ4VVS0djliUMueT2+WpGESrOccIwe6QQnKUaUUBtE6lUopEXNS0PAZHjQtwTJySTPmqoDUWeKWyG+t1+tRQz2SGO8rKek7Ix/Uu3N2dvb111+z5SJ4U3/PvvertXZwcLC7uwsJlF24kJhj1Sh551IG6XwM8P4Q0fxEMflXV1cw+EC1IOEQTRqSYwIFD2yUNHRT7amrs76IOTiogOVNNqgs5e2ODHoLuvJVjZ2jVPN5w1Iiz0m9F3HjYiynME2ab2F9jbI38Q5K+Y6BktyZuglT8pe1hAGdVERTVQK4mUKc4PTDaEmWglORcGUXSutt1AJDpgU0iSvxIffPWyDkuEAebVaR7tV6vd7d3d3d3U1SicPZUnrLYcIFDxTIkcvb2dlZi24zSfTBVOpJ9OyVxlWxzew9VlJNHsfxzZs3v/3tb1E/GCRyuqEoFl+fWiZoNn5aJQi2WHMzi1xpZ90l9JWVHGPgc85UANbr9du3bycNNnMwSiEM+P/Ro0fenSjVdYmvsIhr9aey9CzrHPQAB/UqOEBMAtEckdcgjjCIEoOykE14FfezqL47qGRbpefjRXPakzd1PB2VZk2Y7QJGHaskBeKuqdv848GyCrGTKAmT+FQ5NI83FemcrXmhkqrLHi3VxBoYJNDCXdg9OlvzteXA3LajcM5W1QQHWR2EmudF6kxi4O1Bfuiz7XxpUMeIcwCfpZUE9poaEpKawuzGYdqfnZ394he/8Mk3UPmdDNbvPAnxDOTQ1GJrNAQ2tp9KDQ11YMb8nSBqLaHGUsq7d++Q78PoUkpzm8HNzc2jR49SSqRWhE+GOHzqFpo3aMWe1pq9PNdZRW5zh1QMx4tgIh+JrqEmPvPx6fbQe0Hw1tWQamTDDzWp8j0GCUTbdb4rptFNJS0vuw1HFaCUlHy3UOiZpCSQwmxJTmmVtt9Cmk5JgsysJKhOU2PnIE07b2UWpCuhjxuG4GSUOm+VjpALGq6lYFAePXq0v78f0UmS11LK69evs3on2N/Yfv8zS5q3iEtSpQjEvXNCuGD4mkWlAI76pL62nPNGEhxv6dPDcHh4iKZ+VrrJgm5pCFwRsJiDXG6S2s+kQnrSSCWmOzKSaCUx6yLAm9/d3d3F7XhSgWGKIgqaf2USxW8W3TepLchmw5usaFbAIGEYQyI4ENtgewzbbxaEaI1HEpe+iaZC2pBUFvDv+iA5gB5E4/EdOXpJQTzYB8PXb4PnbZQlLREveB1mN/mJ2yfk0NxcVL93rMjZm4KMV9WwiKShXYan8qbEyyAN9CFMNBrVOgwDlBGrrLzLSkS27BMHbP7qFBp/HQV1FcvNwOtBOHqe5zdv3vzyl7/kM5MoqyUaMz/p33kA7N+b9DoddXkzNcGOk4gi5GSc1/39/UlkrOvra2rAWKakpA2PNs8zUg7UBWH1OLIcVW11xGXXRM2yi1ibggjKUrNck5JXnsRKLUtNrKlRcpwl9KDEGIYw1IWVHMZ7dSVkRaKOOQxG7xqO5HNr81nEWfJ92RB04UWTGBPklGvJxsyhIjZpEtYk0e8SJLFmzXJ0G1PTVCK6wxaSKDSo7fiQO8VU+RFTDB7E33SK7KTWOjqLIPLF19Va9/f3Hz9+zIdDTCpSsZ3V7xFHfboXt6uTbtbU1Bryafd/rUOTnU+mreGHlbdPj9u9fUIL7ZKZzlJQsu9eqyfQQNUQkCY/Sz9R4hBXDW2ZZjVnolRF2JMlQ+t2sCwAxOGKbQA+PW0KHzhpqwHwdiLufLFKodGWjA1XxRP2RXqJ/CC7SjDeqfAFgCNsUMfQGx3jSeNFRa+FhjAUaSbfSOJvLQ5PDgp8vl/vXfzDEBqRu8Z+dWVQduYtjCfiq1n2UeoeTpB4P0Mo5iDXtZBIwhSagbhN7ggMqguydKMcUpMgsOyl6+vrV69esbuuNWjMPjPGlpMK3uQVXtgcSnt8CNbWoEhWFf8D4JA+oUJ86gGauJxxqw2SxFpr9ttaY1l5GM4ptzRAkxV5+/YtjSnDMEBz4AFjCQANyJm2ND3Tds6G3O4MrzdooHcRm2D4hDbszW2rUAR9Am0NoZethKFavp0k+kBRrc0RcN8kHtrbcAyK1ImdXJbNGnMK4jZOKprYRDXo9kTExkEX5YseKMdj0OtcBtU6lpQQf9LIQDMU2U+GxTgGGCAedFYxrod0yBCN5bidudYg3OK0ysdgsVigvGsJLc4S+rCENE31kC4eRHR9Wc1Yg6ox9thFs8xyqKDZJ7TWiqPbsilN0z/BRl3M6+okYuf58DgjyarpcHybkE1fIiomWchgE7+NatSdO3eQYTMgwIZmZW16vfUj+uZElrudgrhID0objvIxaa6gGSPqofvEu43jzaF1TuxCQVVF2W+2+ZykU1lVKm4aflgEojts9Ym1s/bzboJTq3S2o1XKqnY7OPYerbUu9CqC5vh1HxKO7qhJRIRJDgWbOJiENDEKXWq4RlWR0dmw44hZZXi47iWoZLMTdnd39/f3cfiTpkNEb8nVdvF2vc6+8iQgNanaHVeAB8c/7bt67x9nZt7uJaBDPgDeFsRzswQ94+92cVOrdD6yBBS8P8A9oayZwzNpDg/VBiuEuTlrJZEzPpYo3N+ORTHbbAidbj3kfCkI/fXeOWM1oLRd3VV8TtV066SQsapIZFfjdyY11s1qkfHXDdLLyKoYkH1m0UN4tEuJEPsbbUHtqewKbPzS5rhV3uwePWy//+4YOqmnEdKrj80Y1FaqMFy+dyFlAy7PleBIP7GRSmEknFH8FJjkY5jBjrug1gTnZ71ev3jxogYwdCGpmHXor8dGrDQMk2TA6ZmPRJM4bhZ7ggUscTfE7f47PUBc61ksfAPGWeG4zZV3A5jXpDYrtFn4FTIB3Pc4jqj3IOxjyt0QpKQnzTlLIhfYRRSRT4tw7hpaH7s6bp3/DWphwZYQP7RQ7LQpahJLq2HYaAqIflEng1cAuMzGzz7TC2VgFA/mjRUzDYdGCw0hndTzNQcOjJ8RBnghiVxjO35/xJomiXgu9TLjEl/hC3Aa0JV6cv4niZX7oU/q8uEbBxHak4pxAD6YHhv4pEhvHMf9/X107ZtGNTdBpU2wUlfVxR2bvLLwtEFK6N7uvXdIGTkA2fM8b5j5uOk/PQDGFqro6VnwX7zzppejNBsh6rjMZsKcc9aTGAfWL2kancLWN9jiUqsjE58Eqgrx4qO9yarMLzRncwhc/KYJF0k8CFtl76dFaPIcNqV/Jwlf+xsHYXZJwMgoiuggXM+5pgEor14P+smOx+J9lfJdI0cLKX6T8pKtuMnek8Z+NTHeikof5GBpE+HFozqPYqduSfadp+YSoRfZ8P+ocQQw3tignkoI6u9UO4lPztI9ePCAigRUSJC6HnCIFEYN8C3OZCbJvxWlefM8007IAbCf5E4/jnN+z8vQkp1vVpGlhZfRniLQoPcObxt3QbI7z/NyuQQL4kns7e3t7Oyg2MMdOk6w3XWtIJZ1iecGNSt5l3CFtqze1oPQbqcrgxRvehg320PxPy7cQg0PXl9vxEFdrTEh8T7mehyi8M8Pj0H/rOpBq2qoHyRzbYswBhEkPwsueFQL8hCK1l3oe9MgZHJNY26OQLCahqcdtnVJvrL/aqCj1oD926uXALk2EdGSBisa7e290+1FGGlDMAzDo0eP7MZxAnOoJ9pyOb8ydRxwyUbBfuP09PTZs2dmSfk6NxLf+MqfoEBrcdYNDhapm7BpjNVUicpjmBFOHMfx9u3bjP3CWtuNtNYguqH4aW/roH+tzibHYClMFx1EM+Q6eWxx49pEEcXyFONdO6R2Yh1PUQrFhCyGpvFWLwJubVLt07bZeDFRAbVJ9gQggSvl7iNpm8XdyEpIAROMpqdsKqc7EfLNThJrYkaOhWEcwBjg5kZ4TH7WXijjP1kEOO+nKXBOHVuOQYCIS/VZso7BSmNNfCB77w8fPrTtmCV05U/LwjZ8MPxqosSupXxDvTKGW8mt0un/IIF++kNSJRwNH801dUlTebPaIbLoUBL4QPTs4+V24XSHh4dJBMCioS8pMIu8OkZ8MV0llOFs1JuKpqZ/+mD3kDkYuMhBecFPNIurUwJF2YY5hiIlwD45MDcxTnxUDwCu0zXHkFVQPe2IXWBFUjGRAwMAMgaSc1Otw1vfy2U7HeOlScKxjoZt4JL6g0d1SPseY3i20GRE/28WG8WrtA7CRLYdzj0cHTlwclzO9r116xZ1YnKk4+NjvEdTn7EjRqcZRGW+C3YRZwyP5wVJAW4uJdSSovH49EikIDbkwCNrSJ6dIKCY8ceuYcsGniImuFgs3r179/Dhw0ePHpmRYiMdnUwWp3oKugCO/1wpdMLgMMNnLAfttGFTwcY3mINCTtw0/K/3t0EGr5Wtl0OpJH9SRC5wbOCfTFI4jI+gqlYYr8FBYA46PEWCXD1IEAxBud8PN+71UZp5hKMO4YzU2WBPkqnyw61iIsXU1t81qPJldM6omlNw+/xZWhUpJWK8IloN+k455+9///vs3Wmajo+PF5rAAN06K/AzTJQCLsI6EHszItF+Pi7pd8KgSYl8DIo+Ogk+c37qSYSnJhFmxwDO1lEoGIbh4uKCipXjxd77F198ARY5z/OdO3eKMAc+irXzV6eADLILuzBQbyxfvGEWr86wSWluQavQrnzULEAOYd7EN7tmZBgT7GHSejwDNNnAgqRVqAbmOc8e5GpL06Xy5jSXvDl6p0sKparsMEmGrSilSeoyqcJqwS0IukgAiLvWIlo3KU2wDitNAo9exXFLCtrXtr5FTZWz6Ld4tibozKZw1CQ/O9KmLs11UAPBpPIGyHNZE945WqMGvEY6EPc1a7zsJFFaf74PQAqzMTfs/ae2/9NAyBs3KfCK/t382LUmFDi72tnZoQ/IloAxE3QyRX4AACAASURBVKCfLfBsbRia5CfseW0k2iZTI1p3Z7q2/UkworfprNZbB7WDyr2+QbvvSRr5SfGY97o3a7TWtoXsvIWGyRaVZrMok1l4olnKboefRXuu4olwotw2laSRYQNh71FEb3Ey7XQrXu2kmYK2MnaMzkpHTQbhPUWpVApTcNiXNYChLZTqujh/PjNlc/wei48T4GGZozGO45MnTyY1MLDlSN/9pc4nx8CXZif48PfeLy4uOCexxDYDg/bNEtjveeEQ/fjtTAlMqzqyiwYZzPPM/Ag81zqIOnGg7969y/ylJHG8WZ3EPRBmYt1tJZXwHDrWk2oxOYSYMRw3JJw3pRYcyXAj3ohJudckPbY5qJKUIP7lzeRdy2VjkLhxWLgtzDF3vtuV4RE30iFk3kQX+WcQhzzJu/qanYn6n0mh1CwI3MM+bNezkntaUg03NwEMTAd1hO1Mxk7PQDssCW/xWeopdpUwQZIqZc4NeGQ2cCtpVE5SyMT07O3tEcGjwM6K3b171xbKRo314WBz7xDsVqsVY4yT6ra2Gt8VFP36PQeABeIRLiWjx4deXl56tpfDxCpqsTerRWZyzpS+l9KGX0vswI/QW8172uFWDtUTTIW3sqMaY4JZAZ/Ns9fOMZJ/0RlOFSW7CNcfJeXykd/IauX27v+Obr455sTbq4vTwoIY87EDLJol7m3nfWP35ezIa+JvTIEw4qx90KxVn3mKo12pp8PLnZ0dOldMW5hU7xtFR0/qW8+Cm5rYgUk+qigZLYHrancUVU+qSMHu6DDCwbAMfgiVyJ8/S2rE/raFGUprCS1P0/TixQsnvt7ztdbvIstoFX6PB3D4bncWN6vTkSn0zhrocAjLd1Or9+7kwLQAUTmb5OeEp6TCNhs5pHct8NL8Bu/1FBy014It6JjBd1rDvAnvsCZBRccnPfDViNAIOvNmrNkCXNjVt8HKtFAhjum+jYtDNUd0PUAZKXihGigSjqOKqkXA0BDLZ0HmXsmUErxDSjFUJGf1VftMsph8u+1ID8JEKXQPk8vGEGhS16hrnbO6kA0xT9N069YtGl85JMvlkuQQAsEUxh+NIsm3gK/Y0NTQDOAn4rX6YCDSZqDve/idBwBnzdVPaurjYPDDotabJhDGIQq9i6zCer0+ODhArHwt4d8qXtTNzc2ozqkSBjiPgRnvHyYpSgyqE/mJejdkdb5mUYYioNEDVui4rmyy+W0m7DccwDj25QqtVOdA01npFPrri4h3bVPppAqAokrYe7cqzLCpyZwUt8TKnS/VuYqfPXfkdnXuFC0mDgP9RlybDdCNhu0lAWsxynLY81HsMGlglB3UJAmWtXqCIyRQNeELPD1rcivPlKawq6urSQTbFMo+WcnYQtNYjAow0NvSd172EpRmhrwJk5WQKX/6AhyImZajav+lq3nHmaid8qT65Z07dxgVaCzZcUsX9NtFIMPWwomtockrCwDtKgm55cKf5uM3uAlatTM+hMPmR+hn72fsW+jCf3w8qtSSDXE6hPDxczpoenoOHX1JjBpbEz58sTnZLj68Lk7YOih/lKDUMoui4ousYUYy8BSLz5uZEO5aR9XwmEHNTzVUvryqvoUY2PDPKrWYteYup0CaIFZ0x4Jt6Ed581Iqjsb6uGYT0R1KzYK/PQCThw7OPqr7/KNUkG2wWq02FIbZBP3/zomtsEXmZKtT1YvtO08hs+yqOBgbZsTGKD05jJALny3Mx4zhlh1uDrDaJCV452E25wuJ33tdRvVJcpL53ikQFqoUjaKJzSoFVJFV7OWm0ChIzcVUiB4qRzwMJxW+BadJcIw5D2Y6+IJLSHCrquxJ9DLf4BDash3C8YtVdNdJE5NmAYWmY/lz7EN4c0QvvP72MMbHYvxsCNLBXnQCRSAejynuFlKIIRSwfeCxID7qDg0WkiHjCfpUcLPuSRoDZ7kEDOMDDPrR1v+/QiC6v223HDRzjqmx85OuCN6KA3ZqeOFJxP0k2Itj7QEtSYkdffSjpJfYND6ilm2yU6vSne2CzFNATtbqGa/CkRw6O/z4yCjY8yQlJ747ftfXZnqwv8WH30ECi2ARF1upIYzKtB9eS1rYfegRjMphJIcdXVEmRryaNss7g5QPHZhlgWMxzpnUoT9JWbqF6pvvaJTeh++uhukhrTWeTrypvNmeYSdQhB131cuLoDyXIKqqvyXgzilEXE7tkuQzMM1nZ2felilkuR0qhG1SfP3OA5ACjOoL6ho9WVR5jfaDSe6zysA0OiINFKdXuBXYPTcxzpnELOpS/4oV71F9gz69EeqyWxgk7e8oy7Y23q/RtLi9HEnbRjRBbwQPk7Ro+OqlpHkH1WVnVYirutpHdUv5ClNgFmEFbAXjuS0BtDDuNGhaXjxvzvH8TKdAqTI7wNaHa7DTM1zRpGhkJzCpRumfOFiq4sD2oB3EcRpCu6mfkS2p458qzQ5qPiml7e1tmJE91D27wKsmfDmHUZxEFtfX19fX12/evOmhM9jp2XfrHg1A+r1AECBmDAy4fyJpciYfD170YtLzBtmTzefZrlUFBG9x9kTML3soHw56eXemIKifQz4Tl7iEnLiHFjZbei9cUsjkENPX4HOVpeVtP9DF3svK4UrghI7qiO+bAUaSTHFTC69vvIq6568uYrw5tvbOK0EvcRmGK3f199gZQjDOKoMYPEiB4ZtU5Rw0+jcaXUxSEiji7WubOEtitQY2NVvflLtZHF7f0RQaHXNQ8ipqwHDw5mBvENmkaVAD4NVqtWKmRkrp8vLy7du3rrJNYux9WF7vCS9Z+r9DoKQSus8MdTiS9DlIolN755xYhpY3WIvPMbrhDqPOLZTEHd/74PrQ8jmDSvRxc3sTt9A8kJTXZgXKRYAAL7tRH6Q59H0nhZiuhMwitPj8xACdZ2MJYdvXHhRsHJkYp49pelci2CSaiwFaSdN3CI1mKRC8bWVL6A6lQuRwzsqEPIJo0fiE9+/fn5+fR+dsfsoUaPeuEpZQNS8hC7LhJ/2toWbMTTmX6yGOtT3y2YsUKe9v4Ee82eXlpam1KWj6J5U1ban5+2q1+q4foIfc9/dEQSyHwwkOJR0VvuF1EOvsvV9cXPhXxnFEGohXlZQFu3wV1I64BiP6RQpqSXQdB10uPkQrm8XI+Oi0+DqNctiJ51BFtlnqAXTvIQhJgXVj2CQ+oajWbfNm2+OozEvaN9FYH0jvSMczRYl4FtkkKfq3Icuhb52fIDrvI+14zFBEPD/kbNisSb0m3rLxwfFah9GLfu6smzO3ptH2PZQgfUSxcf+/vbNZsuOotnBmVp1uq1sKyYQiYAqMCd6AZ+HdeBdGOIKZJwwAB9jmRxLqbvfPqcxksLQ+rTot2b725N6IWwOHZJ1Tpypz595rr/0HlK8mjmf0BVOMbHHKk97l+vpa9xkRHtXzHJxJWn0hXWxKm49c4/KtEOj169eQSsOxRqCbtq2b7tVKqZWpREGBGLidxew4W3VwYxK8K/TliNYA5zEwa3HpRo2JQDVczHSpl30Tv2pQWAL7ntxk7sfxtigJhwbQ85cwRPA2yAeP1M1s4h70yMfGKsrVwUOVqLH9xdn52J8RvbQ4Krot3vAMH6a4sUoxIBFhQgC1O5eG7caF0DFIVaVPAp/WKKZBiPnFJaptahTTDfcKoFO38EWL9KrEdTI4hEpKNDOW5Nze3qoQDMGu+/aY740+RzbV3uNLX6Ysv9bK9F+24eD0bnTbcNLLcP8ZLY0GpxUnxFKOuERsSwSIzhVUUjGvinZp0QAD7chXln0TT44WCvJEPnQf7X1KFdGl1W1FJNAADNliJFs/BAF1gqdRujMy5NhjqV59BZe0xRhWjgdKfUSAksBQd8fcNXJAaA8hQcfbwShhz4uTfDfnoXTzPARiezR90PNjcIprPIoDONjn1dWhaJbU98fo8444dVdmc4dic1eilwzBwevr67/97W81MuSq0f87y5kS/50esC6kn0OvN9TIJ7GcI0aITg+ce/r0qerfsAAoLZQHBjGVKxExjMwwMT/t72oLE45X95zK8EeJWP3Jaa9BiaRIockAHm3Pd6E+NlfupsDho7egenrkCZeYbM4HEqVMozt94CEG9bFKxRYVEwcrspjrLFHxvDqu3CJBbTiBObd7RurYjO6/+q4oPiidGQPR5EArBn/yRnl/nR82VCBe/qF0n5Dz5pZvW5RwcCpkMeRR6Ifkncug4QFr6VZHRd95ZtNXqqtvMQJXV1f3njSKTz2iVdOMlhu1VjXILsHXFk97pdkBvtHmLqegz+7kMxQSGLpE4QHApkeWBDKBouXAICsc+7nPeEEbVSd7oT5RJOwcQs+Rrsay3bMhmq9iZMzTln2Xu2JMr3WWGC2Rt8cZ5r1y5blAXMDrHk2wAVfNMeYTbg2zia6pwTGwKfqr8ljxjLFgWpO6L1LF566O9FfzS2gE3UQxrFrr5eWljDkU9hot41tr2F7e8f7+Xp1n4abYqdXFxO/jpnniZzjEj6/Xr1+LrUdj0VVGb0uTx2LriYXRZigMRJOw6srDE71eg984Ho9M/splGnatJNAt4ikj2nZjZFF102mViBRwHxWAKDfTEUv0WTlGjQU3L27/iLjj4XB0BfCKvRcq5vgueAmatUQeOCNY8jDkyUGR6YZabUkMv1X33H+x30LI5bAvXhnOfazO1ZtzKgW4e1iqnmqLBhaptvJcKdNB69Pd4ZCtqUah06QN0FE4c9t3vBpmO9BHUrX39/d//etfMVnF9EkJ0ry1iKrUYIHKx7HQ9fX10f1uJS6r+71xdlONVbNsEgVSIOec6gSGiJ/4Ricgj6ABz4xa2pzno7XgX3lmeOviNGl8lRoUcKJzZOjgJmoo6RpdtKaHFPFb4k8ksnQ9qi5lVIuOEg2xqbTW/7y9vdXkBBXy0deSPJTNqdH6ue5k4BG9jzjzS6S1tv3oefZohNvWnGNSw0WRkk7Rac5uWtdVk6by2GBdjx7Wi3O/RJQTLdnMkoGZ9VvIkpJD9YsaTZSQMhEvTqBW+6uvvtLDsOkcsHerwTufiP6JWTi5tHk9yjsAEluUngA2OAyF8ZRuMHHm2aBrxPYWxyCVSYG64v410sGnI/xkeubyTfOGKPu+D+QtUd7KxTHAOqcPyjNUM6eouuoi6azCTpg03cyjRehHtwK2SskNV3tBNcrFrIHWUoJrRDNR+dMpaNVAjq1h3XKn0Na6Vucg1OjaoM9wc/5VNAZN4JB47slxLWZTNudcHDxjRu5p7/36+hqQyQqMKBI8OvufXdDqwZXpDs0ZoItzlnp2hsPKI9zV4Oxj0l9K0VCj7mpa+IoWjMqIIn+dbM7rq1evkIliQNw8XGxxuJRj0x7xMMjfiPzvsq9MIPWKh8nzgJSnh5efr7UKPJQgyJEtbLd+VCLLEoOzcW9alONwAtOrbuZkyp5UbS40Bc6VSHYY0QQAAZ1OQNKLMNJhROINe8TPZandnJPyS+BcGufN5ZTTFMWMQLWeLTMjIZGKrfFZjGni3HIMhuksoNfJvw4X+BMrSBsog6nJA5tr+rB+zakrpZT3RARXYsr5cVf45cuXZBEKzWuhKelHFHQTxbmUEHF0V/R1P+8WZxGxO0FTxMJ4yJP9TiicD9/Cc92iYwW/xU4Mt5JdnInUIkd6dRC+mHTjW9UtGfVXwYbFKXdAc456i76zooCWiIcoflzN05cYesdxquENIyvVbvfmWXcz2qO3CKKhApEB5Bj7wNmr+8zwEt7kiJyl5hY1SYitEaprZqLTcjYHFkk75X/SLBU6REO+pH0k6JTDd3PWsqJffPHF119/XSKfItdKh/B9OCbt/nde//73v5OsTBiqKjuwYPd8dmpSr66u5pyauCj9tDrGOfcVKjMSmKQhlMfC/mHQAUJAw6PbCsAcd5Px/PQ0Xbi64hbOBOjSwkcqBl3FFhztVVzsX2uV7BKW5ruLuwDlYSilqColk/lWNy0t9kzorZQ6XicNy8YDJ2PDYeDmvCZvxEkj5RilTrx/cRNc8R+J3zZ3X5vmzfCXlJnDv/I6eVaHc5nArti0u7s7dQcS13l+fn51dcWtWhBflLnoVLTW7u7uVEO8uoqVDyPkDw8P74vo0JcnKvZjZ+AnP/mJBkUyH/LMA6cOh4OymmkcgCI5Pz+/ublB92ArztwuE7WaeQ2Aorqn/NLH4K2AlVoUXTVYmu7EFdQVWqBFq36k6gQ7Yn+B45yQEQNyeEdO0XDEgAme+rq8W4qDdX8eaXXoDQRM5X61N8IT8hiIGiuTCzVN5+P8bBH5Ri61nmvE/vhAlnAMe1+Ifm5Q3YdlWEZ0Vo2klelKUZ7/wSPmV3cgpjTq6E5hzZlmote0jFdXV7///e/ZIOhs9Ow7R5RP5OE4ORIfvBR6EBY8embOEomExc7xGEMzfWUNWAsiNVomfQC2eEZuzwhyHSEujpzr58CRi9N31yhLr5GBUwPEY0wx98UGbUbaSY1iqMWVpjViJiP6hclxx8nTtpG/3aJ/+vF4VNOkzRkH09Nljm5ECfZtDs9hfKDDkbka8woGDZD9o/hOwBVhJPjcE12jL3aHEbrL9A6eNyEhYeapQgHVNADnkD1FxJOoQMvwYAdXLQP5JEviyqpB/OLIhp5f7JmOBzzE0VXsunN3Iu0wi70raa+PSOX2aEoA1+Zy8uJukhiy1XlvKGk9EOBBLmOLMpQRs4xaMBXFfYPrft5Bj9SrtG4lQC0nJ5UiOhKnXNeyT1ArAWnY7M2JkHmuknYsnlk73coFBNX2MzvQmlhwjqhSu6QgFGDpQduvUWW6OKCOIzhcFTndlJOcAlTGNNDlSOtRxz5sV8KdHeYzOL0Q3MWBbUFcUbrY2LRFD+7wnFoG/vqEsTi4B2gzg6cXhz2rnla2xrTj6kmHMya7TbsQCQt5jJ18J5zlD/UjXsHbt2+7uwYc3bFZlLBkXT+Dx7ZGpgrGlF8c0ShX/EN1bEsLt7mAeDiaJjW8OLeMht1wLEfPSgCq4nj1CPjzbMPp1jjK1Q5uPh7ylCt7krhSw7/kqPPwuvPBc63BY3rf6rldi+N6+DMClskxtAhpt8hRLQ6Kt6jDWqNMPoW7Ri5NifaaNaZRbO5Cp88odwtvRyuGZUiBRr/IncUdP0Sbe2mN1QMLk/UazihDi2k1jq6Vw9vWo6p2Xh2IU+jLvq8hCuUDNcFlHxv+mBF49eqVEsTBxC1S9jCX3Ym1aKmjS3hSmosrDca+OLo4endw3y9OjogaLUR3+R/r0vYdbICAxY7sMHeOMtMibK5faSZ/HnwdoylYGmLkZrghK7uF3q1RJNTdsgYtXoIkYWpONd7TqdYjKZ22RLb2sqdodXHbaecYNYlS5GyXGJlaHIkHYKB3pjH9tJPG8VtcpVRKUbAiX79E7wYeEvwJDBljaCxAdzax0sb0bAI/+tg333yzxJCKPPzFuaivXr1q+2mzeiSa/r5bw1Tw/LmGD/AxC8Bpq5ETLyzbzHY/DklcX1/r66Ag1EaeZkCt/gAcn1GQNSImAm9w4uusnhahH03YwxnD7IIr9P8VUqFnGyeWQ8VXuvMoiTRtDpfimQznZbQYwHqik9LLrLUyfzIXYfNksXwpjEBuGXaPUzGdnzN9IVJ8EV0g13yJVCJkY3VXrMPhgIwOdwvXx4Bz053LGPkB/Eg8xkKxsBDQ2HARUOohIMUKwKZQUUjh4eHhyy+/LDEtjqPLj75b87IvX0Bt8GRwHY/PgBhPtLhs9IOHvGuHNPRPCls6ko5Ly7Lc3d3RBaCaLAIoH1xmuUZeIQ+zOCeiuPXndGCS7dzcBKFFf/PFscl13z8UX1A4B2KhGKFhN8AnxHdkKAQJENDUI4mwq3NdEFbEl5WHRybHhqWu+/CqVPsaiaslrEEJihArxy/yhMh6icRVbN2IDkhHNxyY7rgoWq+7SSNW7sxd1MluKtHWgZtjBNDf1eVNnMl1XekZNezcV9ck6p8Uei/GaV9//XUNODPNqfBe7zwrVqSED/A9LxJUCN0Pz4vd9k14gHrbtn366afF+kkiPqPYdDFxDkYs1srYGZZ4OqUETZAqk1ed5i45J2WfAaF/bY7FYutba/f39/JER/A8LJr+oH/lXYh/8fzNhT76odWNFpU4QH54if7mnMwT69fNFOlWgEbOJxLAVe10simcqP6hrLglhl6WgADd2XXTNKL2Qr2vxQ5lFqBOeybVlUCDW/SB5IYlQpYAxVqrOBVFS3hO8i9FGODKi/8R1gB4Y9Mwd4XhAPpL3ZcFtyCtykc8AQGeavIBQHzmyXndTT+3bXv9+jU2URc+4nTvlx6TgLGAa+Sr8OY82+acmR4dyzgDNca/pkOcuytNfyJz02QUh2dzBvlwDnrbtwbTtuG65dko0ewR47PQnS/6bDYzYCwy8GlEnSSOdY0BCDz5B01Bfrc+4r6bGbkl2C3kPheWIwGGZNGap9k297IGUOXO6nkkJKlEimOF/E9uvsYQE/3PRMvdEYA55+3tbYoxUTO92sHViADdNveokZfJd04rkZfaBDWXsbfWxASDgFtrAjmMbRJmePbs2TT9pxPy9u3b6lAA+iP9igSOKf0os2JQsUbjKkSzOXKJDjt6onUeSL4453x4eKD8Qrci2Y7/IvQS34PnBvCZg2uaWbQ8Hi2SUppZGjTr9BC+/HqLoK8uPox7B0Thz3kHHIbhluIzaOgaUYIS1qAYnGA2kemxj/ThnvKES+Scs3cjZufwCmioEzJacrJ5XpP4vcUNoJr7bfbeNWvizZs3KLjhYBGqE9NXVBLJYtUIl/Lz5eM18m/evOGHZZ6UzablEzRUj8vuGalg+ubGSfIZxhiq8+f4orlZ6xJzZ6ej7ggiy82uDJP9wKEZ5DRfWRyC0XPy/8t+lEg1By+pOkarZzQiTA65FRIIyl9aBFsYhkC6GJoJrdwcq0Y9rZ4Q1SOHTy7gEmkXMyBHC7d7BP/G+c/Po24B6y1i0nD5I3xK/ZXeH9g0jivAbBpc6JFw0JvLIYZbZhDAyh3H5ihrQ2GoWqvyMvX61AdPk5B5UDenwLzXevnm6JWUeBb08QGYjurrOSTxmzuYTjNNaxTC6ZPK8UhUA5TnRAlNZkCxRGM2TNjmCwnrUQBV7QPgHmzO3972efPNY05qdExRO+WnT5+qMRO/rkgFvzWcwt0iSi1fH3dlCaq+mhPU3Uopqv3Ti8AFtUjQYCN4bN6ix5jKsfdZ2TV0J3KfVqI63Q2AJCYXnd2i4jT3VLK+RBXHp59+yqEa+zylxZl5x+gKXGM8RzWBrjP/5MkT4Rm9F7CzRFqHvitXqrV2f38vGkat4HBBa4zMSdWwbduuEwTrVffu82PR51IooHimkKpkEFlZruKKh2+++aaaCemeRpGKiiUrDhjPQLREAYsD47D+JdLUplvvzz2RhdKCCkSVohSb5103Z57iHrCgh5hNxpPzFgrJLQ5dK4AgTaHDgFoiqoDZmVHcU90S7+hODTi+xChKsED8FQHiX0vwOYjO0dV8mMrhanfURMKB1cMB1hikqfdClJ8+fcpXtmhXuEVGbY1uViCxEd0xumkucYwtOspwqGDbh5Pht21THaKeRzKJRpjBnmNMtMU79x+FxF/zMHzwAGh3FZlrzpORHVyWRU/Dal5fXzfn9A6z+Ivn7Wgt1GoBmeimgdkt7MYIXqh4Yo/eOSuMeXikPFtaYE/WaMk2HIxrran/SnNDT2X+zSj9XpwmifnW9igoDj9WHQGsEb4tMZsMs6D7EzrEvz97NOAVuIjzgzVjrfiMkFIJKNKjq9d02HgETc4bsVDDmUgc+4ObAV9eXmoLoIMO7tUDksGxbs6OwYBIaqUmijubN1eT0XEwDRdtjqSIE9io5o597ya7kMZuMq3l1zi+CQ2/3QJITws9c7KlIdQRcbp5GLZbETSIP1l/KU7BBh39GmW+7Mri6mb0x7SvOewxgzt5/+JJozWmg2FSE2o3R0M3dzjrnoUhd1YHdZqIFI6vDjiMaFCeSGBzBWoyKiPmu+jrBzcty7AGOjh5j9ysEoNSyj72DD5EAo4eS1Oin8BxX0TaYoRz8pgzsHWiXKmJBEurB4Ynyu0ODZVSFEIttiQ0U8k/r86vPnrWfLHhItdGX8H6AUAy3Ls4pq5TUfaRuBU1j8Tz1xrUUPsQDcrJ03JsztQlHNudSqB69hrFzsOtg7sHaxeDrtXpTcMli2xnsVup2priKSCHaCne3SKqOxStpRSIpzaNOAs2Gp2Bj95cqq9HJZSDL7Xus2skQET6ipEhhmuJgmYRBiDGJVpe64Z4QdqC6vkdOpza7BbJBS0mN+pRM8OshO7XUiQWH07LGeE+zvAP0x9geaeb3WNO00Q3J8CVfeueFvlLiZZvb2/RQQQl+SF+Qm8t9SrWcQQxOIM1wf0lmoQwT7I5SsCbEWRZ2Tu+H7MDJISeeXohoIWfV6cg/X+Ve5fgp2s4nWj6EmFdVOkJWtvcnpJXbfsenUCsHsFFXEZSuMAVepgSMTI2croJWdnXy4K4inUz5v7MA7qbHQZscbXDyioNE3+aRq7zj2md0e+f1xdlzO7WIK9YRjFsW7RFSmjKt3owBHxxRqYWItv26bcAOcSD7UjHCemaEQkBGfIVDAvqA7lnlYAxWsaDZ8PhxszIfFkiPYS7AW71ImvdRzdKOEz55ZOzkQfg5ubmZz/7WXV5RNtHaoYzQEWSHo9HJXt1d0JXlsiM+BSIeXEiCgKESiDy0J3hjRFYnK9P1zH8Da1OC16Cn0stwv0h5hPFTXORnKsTDcRpnO6TnOpf1rlE0x59nUEKc075D8Pl1CdqVV8njqG/diecozg2T889uL8I+5LuKdz0wU2HcAaaG9tov2o0EarmzXBGF4eiVte4pE1grRLEYnsxDhx18I+IoIeHB9XxpRIUfEorwfqMPfGKTUOY9aYPNMetwfbMbsRx0QAADyxJREFU4LDqR3xfrhPlAY2gU3iMopDe+8lkqGmOZZjZKKYC9dqbRz5BWXAmR/jBR3fnYxFTywruH9w0ASDO2o1wxyGwi8FVMeN0oimUfQ3AAGEfXdKlF7n3mMc15nizVjPyqHlgLAzIih4c0z4x1+qiana3R64EOpulWJym3oM4Lw7qo7MXx4MF/zjhI7J381pcfydjCJGPEmSvdf7Zd/b0BLR0p/5fXl7qz4i7foj4vdZwdWN0tAZaRq9Pn0Y2UVL33nqi8tFk5ePIh+vo5Pjm/DAsmniATNjQbRmBIVyowy0RZ5TNfFTu2M0913BtdX81igGOF0/jwcof3DtAn8T8DRN/6NFhcoP6Hj7JeUtTK2mjVF8Ow4NnpILEDp4NdXQnDwS9hF+7uOyr7IeQlwADbErbs42LJ9cDHla37CxBCA4Tzai26QG9nMnz8/Pb21uy8aBuip20zUm+R/cBQUEkFp1Rd9rc0+rMc9zYnRYT0+q+iTcksh6JvQB2sl+iTVf3PDxBy2VvGVjzzqDsPBlln0v4nQcApX50ZVpSeBh6nYdpfzo9vOpoSAuOb4uCyR6TGiATi9OhpunzzYF09U7jIdlFeSxgJwRiOiuhBlmJ2KERSMzklRlAXczcn6i9dV01fREpPLhDBMcAb+Qhuu8fXAY5Y2IcIsLbYV645wxXZEYSBK4k8EBPK/+eJP7N0YYtYoslVOHw6Ibq+PeJxtSdsV0Yn2q+q9gnTtVOzhhreBYDFDlRlNElEEBfwJbybGgWXj9dvqLmuMVGgD/zA9/nQnUJsZHgUSJMM+dEqRwOh9vbW43/bq1pSiHcvyyyVCnHFCFLgmwaeMxIdCsxnGeG10tUa3P3bQgowAPpsqkjU6xJkRcmAQWRArmZusanbx6Oy4qDcDCD27bpVpsHr2spRBCj8EDM1RXViXAA6KAUUpKKNfQxRpHjezzEyIxuAg04UWxMEvpPQ5F13yilOS+tRHyDwzAiC2N1gqN4ZKU2IEW689GdgOHrDjFegNqDsU946b2rAXOzD8aa4/kAK5ZleT86ZX4/zPP4qg6vnlhwvYmC6jO4J8muUuf1Gqtbciv6XT0EangI7mZ2vwZRCFAezl1DSaMC15jzPKKDC08Cn4iDdX5+nkOEtAHd5djVvj5eh0QTpTg9MVt7o+eBFAcnoLm762tLKQrj592gsPit1TWo0CmLa8b1rTUaAaUI8tceXEKx7lucNYBzD9rWIpzFGEKdBNIfADCPoYS2SfeR+cWTqZF4dmLfoHGJ9Ms2QvoB6LeYVzAdcaKFTG79jBHLSOOgOW5asf/pNR3N1h0ocBHXNiIXr9pTXJblH//4x5zzxYsXWhSScFqkFfD0uIlIPx8mdJ/YcTo6xvEooZOwxXPfQJeDdHDNoc5hd6lRAg8iRCNSIaoplObEYEWO12jwNpw6Xp3JTJ66LsmHMC5bnuHzLeowy77LC7ae3Vkc5CaLQY+ROTwA68d/nk5eAM0O55DWqCdG6w2npp+83dHtLpGB6ZwUAf3FM2QXh31mpDEr40b84RYRtDznHADtIEi77mkPtuld7kIJpPsDpH9Zlp///OcvXryYc0IXNBPtKpVopufX6F6mNX3y5Mnl5SW1VxqmVB0D0pqe7TuJo2DQshL03jtDr8reDxOD1qKtdAvin10p+1RhbO7m0o3N3Xn5QCowCYG6gIFcAZbrPkFQuIhxLJI54QHJBNBuBMM93aiCvVxixhFHCBhW9w0d2H72TusGyBl73w/Zqh/xKXtwbtNNuEBWJfAPkDXdtlznFqPesST6vEpbsE7ruipkJraQ1YMt7L2/efPm73//u/5/sSlm30dUVuwqwn7ARf2X7DIh8RlVS1u0IjzzQIDe+93d3VdffSXTpi/iE8+oSU173R7RMhKX7jRxZfAXA4MZ+aGbMw1nhJ+6L4GxtFczYm14xpxADgOu6ojErOEsJg7DCBZ/uMXi0Q0XiP/36KPWPQxPk5JRxnVfaQmwnk5qqntqfDg5ir8ePJi5lHJ+fq7sPdikNUqTp8dN6wlLtI0p5iuRn2VZSH2vJjBa1DaNiCYheM2hm6RoU7sBBOqj2r3FXXJThU17icVAn1PNK+jX3yGwH3NpsR48zojstxm+FyPUielQKlBKUQNxkkNqrff39zripBwCVFBFa2ScjwgVH2NMQY3hU+JVst1+qrfh4gz2cotU9cWZzAe3VNhcgJfhMP2cPDAdxcQ/uhuBcwUQ5U4snh/KOsDhLNHki6G5EAaJ6VH8NZrVDTsJDw8PohzEF2k1WmtqO16jJVFy2XnM9Adp3Gaaa3WZQTf7XKNTkB41Uw85e8DL4tSSFplqJUrDlECJm1GcJzfc4mFzbm+J6hncepBhIuphBrbW+mMPAFz4iLA55ls7QRXFzc2NHl3f2mIGlnRMdeSl2kNFj86oBSn7ZGluqBXfogS+RLhNv1XCC5xu2FSDswI4dbN4qXeln0pEAKsTBzg/imbggWz7ciRCY5xPPFpQUybq8Y7MUeTQTgccwdz8KyLIUV+jNAypZdH0wBnEhczpjnWUqNtcoqUxi5bWia9zqyUauZ1gyxFO6uLqqOb04R7t3KrDyVI9ixMQq5n0E0SDAi37WjzU4o89AGoPKgnW1ffNz4pdRvLsMaYlOjscXOOjzWYpi3nALVrNHN1ilt1Ngp9ku81Z42kKWBdgKwo4Yw48NqYcqyLMKmNCxgRKdFkWqXaef85JK/mUvOlM4+ZCKt0cchO1ooIvSaGWetilG/sRZui5o1um5XHVK4C7DlGnr2uagJcegXwTRBkRSkPE0RfNeaDpRrMCJRINi22FniRxfDcdohAntIHEY4s5x3VfzITg9ehGU8IW8eEl4pvruu7Glf2A6+XLly9evFhj6hhoskRv6yVGWcGa0++pOOEEqyqzcILnMDKLW5LAEkIdNM+QKlEwANHZI4wPzGWf6qN8RlYQSVqcTzYiTME99ZwSrNW1qjV8PmS6hltZwrDkIcEGVmfyob95KiSgRYPy6fDCsu/qwy5Ut4lHUqfdLQ45EBHcdWInS5Dm1V1PMIxsmT6Qb90cLhj7HjPFU+5SI2RBhW519KAQ9ILynImjSWX85S9/YTF5BqABz/BjD8BPf/pTVbhLmR18IZcK8aBZ0x3E9MsZwAEa0eO7eLLfNAu0uNgqZQg5qOYcAGO5wenz9OjuX/akXguOnBRzdGF1aKyaKZ9B7RfXH+K2Dvup0zzSdDAIp7/FBBr0peIJm7MbEsPUmNvHSyXekGTruLJWmNAU3AwhI/rDvUamu+GyyMPMge6gjx3dhTJlXffsQWHz7qzM6gpy3CGoFEhStFJx+r1QgBCHfl2iD6F8PB7//Oc/txiGACkyTyKSP/IAqEdkd/46VgwtWCMhFAe/9y4oLBJJfX3zbGzRLTn9XU5Ci5DKMToWFp9vaH6sdncCVoJjctHYMzmj/GuL5mSIvr7O/+H4Jb6splDkSHAace967/J2EF9CbFD1PCcgmOcZ4eHoY6TH5JHu5l5YrsU5f5svDM6I8r3uUaczikhnEL6sVXVzVbabsqFie7i47o9tmpH7NGK0Y/HMxbJHOGTXDWc0amH1/+UTilmWQXj+/DlyUh5Ruu/t+Q+T+2qH7/nz5xcXF8pvowOeSLeDa2dFX5CfU527sjpHunuIlWJ4+mtmOw27cd1dWNgGogrgDXxodov9QA+hEqq5FHQzklpK0TCbhA1sVXWK78HliCi25rLPbds++eQTCtwEah8eHhTxLa5mbGY5uJYoFgHKt2gRwJnBb54RbFqcd827j2g0gjeCycJeARoBS3gOhxhUfObZR9WBs1RJ2JzmOgrgovJccLqGu3yiaNCJuSPaCCl7ISLVwTSXK7Emmtmu+z958uTq6mqL1rkpwIuTGr/vAWiuemlBlTx79uzly5fPnj3TWKQnT55cXFxcXFxo9uO6rpeXl2dnZ7SPPDs7U2ZEi9aWOhjyt4QKqrNBFBlhj2utFxcXM1LT5BJVT0VnZFOCltWtU4Cni7t3ySKt7ium9+qR3DIjtwLBmo5XqEMlEIjeXglppvORhlNQVI2lRpljDPWxkQKDoIQeyUYyYLx88XS9pn2SElT39NgRQFqeMd6Rfx1mKmFjEWV5d8NBDL0IK5b5syPi68ujEQTAv+ZCjjw5LfI9Rd2OGBavL56fn799+1akMyoM70XHTPsOEADvoArfAYSLiwsASXnUPkD7t8YcwtRwv/rVr375y19Khz19+lTHTpd+79mzZ9DMkl3JKMZBRmNG9s79/T2UPC7KCV6swX4skXaGhVncO6l+iCEprtbDJ6n2HGhUofdVzpzEUR2+ihFa8fjUvL/WRzmJWoEzd0QFKNZ9kwLZOoXhkHu0VCKf6q4tJZzLFtlj3FlzGmGiOAzIAaLPH5bIKSgxNwmxk41ClQDw0pMZ0UG6OI+whb+e7pAukR/V/VjlDWq4nagz/A2Zi2mmX9Nj1XhcUY63b9+21v71r39pcz///PMvvvgCIhvFve0Hk9Zf/OIX3W2teqRMSBrgpw8es1wN+Hrvv/nNb16+fKk45bquz58/lwBJvckDVv+f1V2aCUmuHpZa7Txo1ZQ0Ws1CYJFz/7bIjavR9BzdiYAm20AIQjw0iKg/onFq8EI1itaLg7jp1SnhD8+yuqCsR/JMCRzfgq6prlWoZlFqpCuemF95VseYM8IJmZGhDdqZHhJxdnZG+yZes4bTkicK9bG6LDiBXzPNUCLfERwyw+XtTos4WVIJ9DSaB3/qW5eXl9u2XV1dNXcionpT4KdEH4bj8ahmand3dwog6lTc3NyMMT7//PM//elPCcZytcGK353x/7/wOkSH1JPr6NqxD15//OMfe0TBSjQjKaX8+te//pbvaq1LNE1hs0dMNNG1RLgKAy1lqfPZPcSlRlFsi0bt1WwM2X6JamYEATiK+VJYg+FkG4zkifA9eGZ9ieOHZePxOCrcuUXu3YwZMKj/7mxzDO/mgVH5APAz45GLv7k6gqxERUuZfaT4qc6Dguvdw5G+/PLLP/zhDyPS9UAQWPVSyv/JA/D/14+/vkWJlO/SI7/97W8hmpB4Kfvf/e533/LFf/7zn8Cq4fK6ZnJMOKI7kFqimY2wMTnSQkFkXpVS/vOf/4jQu7m5ESK6urr67LPPcE7wo0o0J/3kk0/+C/c5xb9fajTQAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Image object>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GVdJ49RtQtry"
      },
      "source": [
        "## 데이터 로딩"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5ME_l5d-GuRE"
      },
      "source": [
        "import numpy as np\n",
        "import os\n",
        "\n",
        "from skimage.io import imread\n",
        "from skimage.transform import resize\n",
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "IMG_WIDTH = 256\n",
        "IMG_HEIGHT = 256\n",
        "IMG_CHANNELS = 3\n",
        "\n",
        "data_path = \"Lung_Segmentation\"\n",
        "\n",
        "files = os.listdir(os.path.join(data_path, 'image'))\n",
        "# files = ['CHNCXR_0402_1.png', 'CHNCXR_0461_1.png', 'CHNCXR_0422_1.png', ... ]    \n",
        "\n",
        "\n",
        "raw_x = []\n",
        "raw_y = []\n",
        "for file_name in files:\n",
        "    # file_name = \"CHNCXR_0402_1\"\n",
        "\n",
        "    # input_file = \"./Lung_Segmentation/image/CHNCXR_0402_1.png\"\n",
        "    input_file = os.path.join(data_path, 'image', file_name)\n",
        "    # output_file = \"./Lung_Segmentation/label/CHNCXR_0402_1.png\"\n",
        "    output_file = os.path.join(data_path, 'label', file_name)\n",
        "    \n",
        "    image = imread(input_file)[:,:,:IMG_CHANNELS]\n",
        "    # image.shape = (256, 256, 3)\n",
        "\n",
        "    label = imread(output_file)\n",
        "    # label.shape = (256, 256)\n",
        "\n",
        "    label = np.expand_dims(label, axis=-1)\n",
        "    # label.shape = (256, 256, 1)\n",
        "\n",
        "    raw_x.append(image)\n",
        "    raw_y.append(label)\n",
        "\n",
        "raw_x = np.array(raw_x)\n",
        "raw_y = np.array(raw_y)"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qhp-Lt0OWcxT"
      },
      "source": [
        "## 원시 데이터 보기"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MXnw8NwqTJd8",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a7f72977-15fa-4052-a8fd-f779ccc2cfaf"
      },
      "source": [
        "print(raw_x[0])\n",
        "print(raw_y[0])"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[[ 70  70  70]\n",
            "  [ 44  44  44]\n",
            "  [ 41  41  41]\n",
            "  ...\n",
            "  [ 46  46  46]\n",
            "  [ 46  46  46]\n",
            "  [ 45  45  45]]\n",
            "\n",
            " [[ 65  65  65]\n",
            "  [ 40  40  40]\n",
            "  [ 32  32  32]\n",
            "  ...\n",
            "  [ 31  31  31]\n",
            "  [ 34  34  34]\n",
            "  [ 36  36  36]]\n",
            "\n",
            " [[ 58  58  58]\n",
            "  [ 35  35  35]\n",
            "  [ 27  27  27]\n",
            "  ...\n",
            "  [ 24  24  24]\n",
            "  [ 23  23  23]\n",
            "  [ 28  28  28]]\n",
            "\n",
            " ...\n",
            "\n",
            " [[ 56  56  56]\n",
            "  [ 37  37  37]\n",
            "  [ 32  32  32]\n",
            "  ...\n",
            "  [ 23  23  23]\n",
            "  [ 24  24  24]\n",
            "  [ 26  26  26]]\n",
            "\n",
            " [[ 48  48  48]\n",
            "  [ 39  39  39]\n",
            "  [ 31  31  31]\n",
            "  ...\n",
            "  [ 23  23  23]\n",
            "  [255 255 255]\n",
            "  [247 247 247]]\n",
            "\n",
            " [[ 56  56  56]\n",
            "  [ 42  42  42]\n",
            "  [ 30  30  30]\n",
            "  ...\n",
            "  [ 24  24  24]\n",
            "  [181 181 181]\n",
            "  [249 249 249]]]\n",
            "[[[0]\n",
            "  [0]\n",
            "  [0]\n",
            "  ...\n",
            "  [0]\n",
            "  [0]\n",
            "  [0]]\n",
            "\n",
            " [[0]\n",
            "  [0]\n",
            "  [0]\n",
            "  ...\n",
            "  [0]\n",
            "  [0]\n",
            "  [0]]\n",
            "\n",
            " [[0]\n",
            "  [0]\n",
            "  [0]\n",
            "  ...\n",
            "  [0]\n",
            "  [0]\n",
            "  [0]]\n",
            "\n",
            " ...\n",
            "\n",
            " [[0]\n",
            "  [0]\n",
            "  [0]\n",
            "  ...\n",
            "  [0]\n",
            "  [0]\n",
            "  [0]]\n",
            "\n",
            " [[0]\n",
            "  [0]\n",
            "  [0]\n",
            "  ...\n",
            "  [0]\n",
            "  [0]\n",
            "  [0]]\n",
            "\n",
            " [[0]\n",
            "  [0]\n",
            "  [0]\n",
            "  ...\n",
            "  [0]\n",
            "  [0]\n",
            "  [0]]]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uf0F31eBQ2S0"
      },
      "source": [
        "## 데이터 정규화"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-WA09ov8G19W"
      },
      "source": [
        "x = raw_x.astype('float32') / 255.\n",
        "y = raw_y.astype('float32')"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "f9aAVB3HRMHB"
      },
      "source": [
        "## 데이터 나누기"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wBiEDjFBG8Lj"
      },
      "source": [
        "split_index = int(x.shape[0]*0.8)\n",
        "train_x, test_x = x[:split_index], x[split_index:]\n",
        "train_y, test_y = y[:split_index], y[split_index:]"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YAlIG-SDHGCk",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0d844c56-a303-4b5c-fcdb-2d8ad7f45a2e"
      },
      "source": [
        "print(train_x.shape)\n",
        "print(train_y.shape)\n",
        "print(test_x.shape)\n",
        "print(test_y.shape)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(452, 256, 256, 3)\n",
            "(452, 256, 256, 1)\n",
            "(114, 256, 256, 3)\n",
            "(114, 256, 256, 1)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FcqjqeYpHL-7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "44f754a2-982c-402d-c27f-7c2e5504ca20"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "def plotTrainData(x, y, set_type):\n",
        "    print(set_type)  \n",
        "    for i in range(3):\n",
        "        ix = np.random.randint(0, len(x))\n",
        "        plt.subplot(1,2,1)\n",
        "        plt.imshow(x[ix])\n",
        "        \n",
        "        plt.subplot(1,2,2)\n",
        "        plt.imshow(np.squeeze(y[ix]), 'gray') # np.squeeze()는 (256,26,1)을 (256,256)으로 변환\n",
        "        plt.show()\n",
        "        \n",
        "plotTrainData(train_x, train_y, 'train')\n",
        "plotTrainData(test_x, test_y, 'test')"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "train\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "test\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ],
            "image/png": 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N7HMwGIR5dQVVujAL5zAajQINV61WE7r3mZ2Zzc3N6fnPf75uvvnms+ax78+uuOIK1et1ra6untdxrr32Wv3ar/3anuZRrrvuOt1222162ctepje84Q2JYOJitqkB90OHDiV6stRqtQCSLPPL5XIABsAM82IVB3lev7S0FEDbKyV7vZ62trYSfL7/DU0Crwtv3u12A1h5FaWkkDxNywT5zdiRX0LjwLUD8AA0wNftdhMFVb1eL9EszJ2ZJN1zzz1qtVrK5/MqFotqNptqtVoJ6agnMF3bjnmSmfn26BgJ5sLCghYWFjQ3NxccLg6O1Q5z6gVbUCcAOVQNK4Y0wLi0EaeGAqjX6+nYsWOan5/X8ePH9cQnPjE4z5md3qIo0gtf+ELdcsste+4QDx06pBe84AV65StfeV7Hed3rXqcf+ZEf2aNR7Vg+n9e///f/XkeOHNFb3/pW3X77xd9VYirAneIdqkGLxWKIDHu9Xog6y+VyAFmnZGgPIO2AkWu7PUpEvri0tKRutxs03BQ3STuRIUlOQIbIv9FohJJ6AAsHREMtKBMagOEgvDeMj4mx9nq9EHXOzc2FMfE+l1O6woVxEwVzPawcNjc3T9LIA+YuOSyVSmGl4NfW7XbDqsa18HNzc6GhmUfQrm4BoLlHdLhst9uJlZTnSnx+3HE66Lgy6tChQxqPx7r22mv1ta99Tddff31Ysczs9PaIRzxC73znO3XttddesJXOQx7yEJVKJW1ubp7T+5/85Cfr8Y9//B6Pasey2axe+MIX6hd/8Rd1ww036Otf//oFO9d+2FSAeyaTCQnFzc3NAOSZTEbFYjGUxMMFe88Ql9MB9i6L9CgV8CQ6X1hY0PLycojkScZJSlBBKDvW1ta0srKi4XAYwI7zkDSFfnBenUgTVU69Xg8qDwdAImmP+l0Zw3E9iQzV4tfa7/e1trYWHne7XfX7/RA1syLo9/tqt9uJWgGXV1Jk5SsZz4NAmdHWId28zaWj0nbEv7GxESpuocJ8BcHrvbjKZZ0O1iiFcrmcqtWqfvCDH+iOO+7QE5/4RNXrdb373e/WT//0T+/DJ/jitVKppB/90R/V+973Pl1zzTUX9FzPeMYz9MpXvlLf/e53z/q90EWlUukCjCxp11xzjT7ykY/oQx/6kF71qledszOatE0NuD/oQQ8KmnW6CLq8ybXNGxsboZJTUmh7m81mA0cMWNB6IF0RiWyQ/i6oTehACDjl83m1Wi3dc889ajabiWZZACfHgoMminWtONEzoAqX7/y/N+na2toKVa+DwSB8qJvNZkgc4/hc84/eG/qHx0TycNmuTGHuiPI9oeqtF6Co3MH2er2EtBOw9l70nU5HnU4n9IPBAbBqcDUU58LxSckWDzgZis5oQby1taU777xTP/zDP6xer6fNzU09/vGPT9B1M0taoVDQH/zBH+hZz3pWuAcX0qIo0s///M+fE7g/8YlP1M/8zM9cgFHtbtdcc41e8pKX6MiRI3r729+uT33qU/t27r2yqQH3AwcOBCBD78yXm8dElgCRUy9QK4CaL+OLxWJChZJWCPF+OHYvWvJKU5xPt9sNQO0Vq4yrVCqF6J5xuJIGvp8EJO0LnHJiDDgG5Ickk6GvhsNhoHWIwhlrq9UKnPbW1laoMPUOlJwHB0PP+lqtpnK5HMYF6LL6wSgwQmdOziSKIm1tbYUxpPsBASZcq7S9KQqdOGmW5nPtSqj0ymc8HuvHf/zHE+fO5XKB1ppZ0q6//nr93u/9nq6++up9SzhHUaRf+7Vf0wc/+EEdO3bsrN77pCc9SbVa7QKNbHeLokjPfOYz9ZSnPEXPetaz9Cd/8if7ev7ztakA9yiKdPDgwQDYS0tL2tzcVKPRSNAqfKEBBKJrpxUkJaLz0WgUokaW8UgOvREWxwLsyuVyiAj5UOE4aDngsinveQ7Pj5TPOX/AleifaJlroIjIS/Wz2WxItvJaeHtAdbdqXs8pkPx1B8n1UiBGRS0rHm98xiqHc9B2GFqIeSQHsrW1FR6nWxP4vDn3v7i4GKJyz48gd/T38XnwpCuvcZrKE8Yzk5aXl/V7v/d7espTnqIDBw7s+/kf/ehH66d/+qf14Q9/eN/Pfa62sLCgt73tbfroRz+qG2+8cU/knPthUwHu0g49ICkU8xw+fDgkMOGNHYDplZ6uToWOAORc0QKN0Gq1QmEOig+SlVSdEvESOS4vLweQTW9BRxLVi6lYWTi4eBUnoBRFUVDfoEJx2gXFiVd/Ei27RBT9+2Aw0MrKilqtVnCYJD89+se58ZuVh7TjNBwsx+NxSCxLCooeXtdoNDQYDDQ/P696vS5JIcHMKgYe31dY4/H2rldeQEYSmvYF/X4/UUHMXKdXYdw75+xntm3Ly8v60Ic+pL/39/7epIdy0dnBgwf19Kc/XR/4wAf08Y9/fNLDOSObGnAn+uSLD1BDWQCyJCqhEXK5XCiWAWw7nU44Hsk979KIdbtdjUajQEPQ9AstNxtMOMVDtEpi1NsBOHBTXcqeosgJAVgSsCQ6SaiiJImiSO12O0TGSB4ZhzfsAnS3trbCKqXT6SRaKjBX0DjpilDaKXB9XhjkKw+nmYbDoTqdjo4ePRoas5VKJXW73dC7h9wBtBnJUXIIzJm3eEBpBDXH88wR1J07z8FgEObaE9E4kQe6XX755XrPe94zFcD+Yz/2Y/rIRz5y0d2XarWq97znPfrxH/9xff/735/0cE5rUwHurk93MPEvL3JHgAJwglIoFApaWFhQr9dTrVYLUjuPDh2sXAaIUygWi4GK8aIkL2pI9x/nONBE0s7uSgBgu90+STmzsLAQgI3j0o8cJU6lUkk4BJKRcRwnlCzOy/f7fW1sbARwBZRxZPDROCUiZugNrgVenOvyoq9WqxXoHoDX+7lkMhk1m00tLCyELQbJD3A/cVhcA0lhVhGsQphnd8qu3kErzwqCey3ttIue0TLbHPt111036WFIkm688UbdcsstFw294bawsKCXvvSletGLXjT1HUenAtylncKj3aJEKAyAdm5uLgAfP667JkKlta0XvXivdDjver2uarWqra0traysqNvthnJ5aApe79WgnA8w8mKldJKSDzLXx7ldQkik6oocX82gIEK/7rwztA29YXK5XOhrznXwGgduqBDmBqUMEXSr1QoaeY+MnQrCcfF62u6iCoJeYaXihVb0/cnlconXQ6vhWKCgPMrv9/uBZuMeORXjq50Hsj3lKU8JDb1mdv723Oc+V7fddps++MEPTnoo92tTAe5RFGlpaSlEozxHNOuNsACRdAdJvuwAE0lPqjqdSycSpEwezh1gh5OH4iiXy0FFIik0vQI4AGLoFVesAMpebQook8QFkFyRwmoCvpkIGqUKcka4aKJ6rgW6yblpj8BZ/ZC7YNcnwBmFC05I2lEtcc2SEs7UwbTZbAbHU6lUVK1WA4/uKx4cJY9dmknSmsjb+/ZQUJZuJOdO1VdZD1S7+uqr9d73vjfkQGZ2/hZFkW655RZ985vfnOpCp6kAd2kbDCjeoRkWS3XXbhPhEj16TxFeC1hQaIPaw4GOwhcaTB07diwAmrQDDJlMRu12W41GI1RP+qYe3rfcAdyrONHPc+wo2qnIBdx5j/dygSuHo3Ypo//fKQrnsHFujIsxEPV7N8zhcKijR48Gh+OtdnFQ8PHFYlGlUilR1Zvu4dLv99VoNMLxyZ1wXN7DeInCcXw4AV/FuYPmM+FKKRwLjsxbFTwQrVwu6+Uvf3noizQttry8rH/0j/6R3vGOd5zxe9797nfrN37jN7S0tHThBnYWds011+h5z3ue/sW/+BdTuzo8L3CPouj7klqSRpKGcRw/JoqiJUnvl3S1pO9LekYcx+tncjy+iCzvAWg2W+50OiGKA7BdwUHDqE6nE1QbkoIcEpCiIAeJ49133x0Kp3g9/D5UCU4E7tobeZGQJVononZaBh26N8iCXnL+HECiSIvn6IfuRUBEw/l8PrQDZkz8prCp0+mE15KczGazoQ+997cnwscx0XQNfTwy1Xq9nughMxgMwnNc58bGhiQFpwjn771kJAXKRVJYhdFLiNUJoI9Td918unOkr57Oxfb6sz0Je+pTn6obb7xx0sM4yQqFwllXw37729+eupqFG2+8Ud/61rf0ute9btJD2dX2InK/Lo5j31vrZZJui+P4liiKXnbi8UtPdxBfoks7HDGADnA7sAI40o6SBZUFUZ0nXj0CJEFLcy1pZ9nPuQEM6AGoGgf2OI61sbGh++67L/DWFOJ4ZE3REcoU5+mpQGVcnhxktYLk0vMQrjln7nK5XGjEhQP0+eQYrVYr0aLAcwrkMIjMnRohqo+iSM1mM6iGHHRZhXD+ZrOpQqGg5eVlzc3NBaVQuh7B8xs4Fdo9+7VKOzp3B3F3+IzXtfHnYHvy2Z6EPeIRj9Dv/u7vTnoYl7RlMhk9+9nP1vvf/37dc889kx7OSXYhaJnrJT3xxN/vlPTnOoMvQJo3lRTAiogU3htQ9GpOHrdaLQ2Hw8QGGRwLpQwKETh1QAHH4OX5mUwmNArzZKePFUAhYQi9UKlUNBgMgpzR9yT1Y+Cwut1uKGBCvcO1EdVyTtflkwtwx7e+vh6AlNej0YfiYgzQPDga1+2TvMXpAqauSllfX1cul9PS0lKglLgfzA0KHmgdVkCuZqJKGGNOiOChvjwpzvx7oted4h7bOX2299tyuZz++T//53rwgx886aHsaqPRSGtra5Mexp7Yox71KP39v//39Za3vGXSQznJzhfcY0l/Gm1vSPDmOI5vlXRZHMe4sXslXXYmB/LCH/72XisADk3FSCx6Ic3a2ppardZJpe6usCB6JuLGSD76RiBw7Wx5x3Fdj41CxXX0OB2AFn3+xsZGeA2l/eQWOPfGxkaiL47zx94tkbyBr1yIUinZR0sOrSIp0E2eXCXK9tfR0ZJ7wjwzfkCc8TiVtri4GF5Lz57NzU2trq7qyJEjkhT08D4Oly56AhgHgzNKF6ZJSqxAeHyeAL9nn+39tgc/+MH6jd/4jUkP45R27Ngx/af/9J/O6j2j0Uh/8id/MpU00ytf+Uq9613vSrTlmAY7X3B/XBzHd0VRdEjSp6Io+qb/M47jODrFTjRRFN0o6UZJoQCJilNXZXgU71wrEbT3R6HKk/d6tDsejwMVE0WRNjY2Ah1TLpeDzA99Nbse+bH8vESSuVxO9Xo9UXjFCgPAlxQaaQFaTvOUy2UtLi5qNBppfX09bC1IEzMoGyJVxuMNtnAgzWYzUUEqJROyOEt4ceaQFQt8N4lbl0tmMpmwivLksVeWkrsgn+E9eHCWKJRc5+z3nR9WQ2jw3alyTByoP+Ze+eriHGxPPtuTsFe/+tVTXZnr8uQztdFopLe//e264YYbdOjQoQs0snOzK6+8Um984xt10003TZX2/bw6BsVxfNeJ38clfVjS35V0LIqiKyTpxO9dNyeM4/jWOI4fE8fxY1CNcNMdnFw77o95juh+fX09QTmkN32QlOiVggacCB2AaDab2tjYCBQH54MTBrzZ2o7Nu+ngSHLXKRreQ5dLIndAjtyCb1VHN0tWAs5Pn5i/wDXDT9O2GDDMZrOhl06lUgn0EKDO+6BrXFXE896zZjAYBGd24MABVavVxGqC4/Z6PW1sbIT+Mg7GbPRBcjRNxXF/pB2JqcsbuW53Pu7wnE7zY03qs31OJz8Pq1QqOnz48H6f9qxsZWXlnO7L5z//eT372c+eOkoH7v3hD3/4pIeSsHMG9yiKKlEU1fhb0s9J+rqk/y7p2Sde9mxJ/+1Mj+kRm5tXYXqkCd/uSc7dtmUDCEhsUvhClMrS//jx41pfXw/Ax2/GwHZ7tCnAEQGM/D0YDNRut9VutwPAc06vEqXMnp9yuaxKpRLGSXTuFIRXeRJBpyNw14ynN+x2wPPX0brYG4KRBAa4caSAdaVS0fLyshYXFxM8OM610WiEzpessFzSSi92QJofTybzmSD/ko7ufaco/xxJOucKyAvx2d4ve9KTnnTOG1rvl73mNa85Z/ngJz7xCf3Kr/yK1tenS6SUyWT0qle9KiEHnrSdDy1zmaQPnwDQOUnvieP4E1EUfVHSB6Io+pQkvbEAACAASURBVHVJd0h6xpkczOVr/Dg14+AO2GSz2UDFAGwsRz2iQ9PNc1AKfMDYGBpg8fP6Vn+MywuJGDvAJO0U+1DxKUmdTifRaRFA4jGbSBPlOw3BeaAoqFr1qJaELY4wm82q2WwG5wXdBPAC0pTuQ8WwGuBDChAvLCwEnTp0EK+luAwnxvhoQzAajbS8vBzGQb8ZaYfbd0ljOoonB8L1unMjQe7yUlYb56Fz39PP9n5ZFEV69KMfPelhnNbOgyqTJP3P//k/9cxnPlN/9Ed/NFUUzXXXXacnPelJ+tM//dNJD0XSeYB7HMd/LemRuzy/Kulnz+F4iSZY8NkepXtEBwAhjfMkqrSzLPdOiAAa58tkttviAkB86HgNACTtfCCRAZIERYdNZCopgKhXn/I6yutpPuYqFSJlpxu8xF/SSf3McSKoiIjioTxWVlbCHNFKgPfl8/nAEQKKACKUFMff3NxUq9UKm3jQ/gGnwHVls9mgQOK+dTod5fN5HTx4MKFPl5S4X3wG0ioa5t9VQzg/xoiaCgmnc85nm1Td68/2ftnc3Jye85znTHoY92t/+Zd/qc9+9rPnfZxPfvKTuvHGG/WRj3xkD0a1N1YoFPSSl7xEt9122/lKcPfEpqZClS+8AzxRopf087wDJ0b0J+2obvx1Dhhw7SzviIA5n68ciDZxFlAqo9H2rlFUfvqqQ0o2vHLFTj6fV71eD211oygKHSTRuTMWrg/qhuO5dJTrQeoJmFerVQ0GA919992Jvi5pWaVz9HD2jB8nweYXo9FIq6urarfbyufzOnDgQFAg4dDq9Xrg67l3vV5PrVZLBw4cSOxaRYdKB3HXtXsiGyAH/L0XPglZVi8X69Zo52MXQ+/6tbU13XfffXtyrP/1v/6XPv3pT+sJT3jCnhxvL+yHf/iHp+YeTA1BlP5g8qXmiwtnztLe+df0xtauaXeAxzHwHpJ7ACnVsGwS7VpwVgnNZlOtVkuNRiORaIVS8cgeR+W0kV8TMkqackGRsAMRr/MGWbvx0US8rGaYJ6dNUAM5T81cMB++KQZzDGg7PeXtgZvNpo4fP56IlofDoSqViubn5xNNyEgas8Lw9gqSErQLEk/uoc8fx2Nems1mcLisjrxP/wPFnv/85099MnUvbW1tTV/60pcmPYyEVSoV/diP/dikhyFpisDdOW1A20vlAQKiQ0mJCNmjVyJ1Px7gJ207DnZ5AlDguaFuOCcKmkajodXV1aDIIXEKJeI8uYNwms92VQnOgd4zrVYrgLhTJDQqQ4boyWJAGOdIQnNzczPkI2gt4GoWd2o4JXeiXrbPa4mmfYVAm+HV1VWtr6+HewfYU5SFw9nY2AjX403icBa+enNNe/q6ue+sEOhlg+Pd3NxUrVZTvV6fmkjqQhuJ/mm1OI73vFT/1ltvTdSrTNoOHDigpz3taZMehqQpomUw/yISAZOY5AvuKhZJiejcaRoAnmgWIF9dXQ2cMpGtg1c2m9XW1lZQvHgkC+XhUSrKEp6narTVagWgwlmlaQYifaiJtbW1IDEkOeqgivwT55CWIrK6IDEJeHsRFpEv1+85DWkn1+CyS4DfC5cAZJwD/D2UE7RaqVQKvW3ov764uBjOz7wxNu6zpESvfKe5cC6uc2cOGEun09HCwsIDBtyn3eI41ne+8509PeYdd9wxdX3h07TupGxqwN05ZJfEoRYhWiRK47GUjPpdseI0DQnD9fX1RNTom0iQJPV2v0TC0AiM0ZO93ET4Yk+yViqVoK7pdrsBxLa2thLSQloTo9rx7eK4fhwc18zKwWkKL1RyfT+bdhPdEY1D8czPz4dma+VyWY1GI2yb59G9K2UwV9l4afnCwkLIn9Tr9cCDQ0ORgGUMHnV6ARag73kZaadASlLC6fB+CrvOV51xMVi1Wp0aOuCBbjfddJPe+MY36ujRoxMdx1SBOxQM+4cCgnDKyPgkJaJGV9KkZYlQLq7cIAqlNH44HIZGX/R09zG5kwHEGAPAv7m5qWq1GgCd47oeH9kj5/dOiE5LjEajkFh1VQlJTYqRADyu1+WJrimHcqEqloQuxlyVSqWw4ojj7dYBrExwYt4HngIlV+5wvY1GQ5KCBDKKotBlE1qMqNp70PB/jsmP3+9MZrvfjwM552U+eY8Xfl3KdvDgQf2Df/APJj2M+7X77rsvrHwvZaMX0qRtasAd3XetVkvwuZ6MLJVKJ/HsyP7SnHuaw5cUiorgyeGLiWrpIwPAAr5EhV6AhPTQNeE0xfJKVnjh8XgcIlmknFEU6dChQ0F9Im1Hu94JkYgdWgXzyNYVLzgUomEHd3rgZLNZbWxsBEfKNZIg9dUIDknaoUgAexK/6RUT897pdFQoFEJrhSiKQr8b3lur1RLyTqfefMs/d5Jo6QFzf09arfRAAPaLxd7xjnfoBz/4wZ4ek7zcNFkmk9Ev//Iv6z/8h/8w2XFM9OwnLIoizc/Pa35+Pmx1t7q6qk6nExKYm5ubgRYgUgXI2MQB/tjlflAcURQFBQpdFDOZ7TYA3W43JEtxJowLcEg7kTjebiNcr9d16NAhLS0tBYoEuoHoNptN7irkCc9Op5PYu5Rt56SdIikcAhQTvL0XGnE9nlz1vADXynwwPqJ75+ZxCpJC4hgQ9WR2tVrV0tJSAPt0IRnnRm5Kl0vmicQu8lP/PHhFajrRzmoufZ+9CI37NG1f/Jntrb34xS/WgQMHJj2MhEVRNBXyzKmI3AG81dXVRESK8UXt9XohevcGYelkJ8/xw/vhqDlHPp9Xo9EIyb50awMAFMchKezc5CBGtI+mm9WBJ4E5Jhw/UTjACrjDUTMv0k5TLVYLROIc32kVQBB5KAAu7exFy5h9jom0Nzc3A9DjCDmH90pHyUNBFj3kOQ+rGqdu6KlPDoTr4H55pO3Oxu8zc+eO1+k4/ufzN7NL19i5bGYn21SA+3g81rFjxxISxt1oFnThcNsAt/dfSSfWvFkYS32Sl0gcMfhZAJFImaZf7gD4v7RTou/gQ+SZdhSSwr6oHnGzhyncP86BzaU5HgAGoHP9hUIhSDhxZIwtk8mEnai8GZhr46Vt2sqpnEwmk9hj1q/HaTFXHEF1+aoAh9RoNHTgwIFwn50PpzMox8RBuGPkOvhfuv2Cr2q8CnZml6YR1M1sd5sKcPdIGBB0CsABpdlsBurBi1+kpOJG0knJz2KxGPql09bXoz/OC7hks9kQGXhnSu9JQ8LRGyHhZEi4klylORg8NedzWoZjFQqFIANN0z30N3eVjtMVaSfliWhWFVwz5ywUCmq322FMyDmjKAo9anA4FAh5tTBqI1ZQXKODdLfbDW0IeD2bpOCkXAkFODvV4glofrvU03n4B4JKBnvsYx871Rr3zc3NPS84eshDHqJ/9s/+2Z4ec6/syJEjuuqqqyaqmJkKcJd0EhB4tOsgL21HmPV6PVADvJ6EooObR3SSAr1AdSrn9uMTQQOmfkyPDON4u3856hKPFr0IiM6MyPJ4TMMtol/eSzUnO0Y5B+1cOg7IVSVexs+1z81t7xlLL3WnROI41vz8fEgw00oB3j9Nt9A3J5fLaX5+PlAt7oDn5uZUr9fV6/USlBYAv7W1FY7P/KeT3+nK1HSk7/fTqS+nZTjnAyGp+k/+yT+Z6pXKxsbGnveBgaqcRnvkIx+phz/84TNwl3bUL7vJG6Ud7pglvkfMnjhz5+BfbI9Ijx8/HqJrBxRWAyTnvD0w0W6v1wuqGwpmSJpyLErgK5VKYgwkdumE6J0t6bNCXgFnAOUCQHoLX3d6nsSE6+50OglqyWkLVjvOi1cqlUDNEJF78pbonfxHJrPdn71SqWhhYSGRB2FHJlYvPCdtf9HZ3Jt7Kyk4Une2fp1QYs7D+/MO7J4cntmladMK7NNiUwXukhLFQi6D86QgEST0jCs1PBnpkWS/3w+7G3lkTyQPBSMpJCOhCKCDiGzhhqFq4Lg5B31mKFSan5+XtO0Y3HH4/qrw8Ch6uC6O4xWcALJfM44mjuPQGXE02u7T3u12E5toOwVGTxlfpXjrAylZDAVFFUU7VbVspL20tBS28OOewKX7/RuNRmo2mzp48GDiXknJSlUHcq4LJ++rvDTn7sA/zVTFzM7PXvva1056CFNtUwPufDn5O03FSEnAJvKmFN+jV2iH3fTT3W438dhbAqMFH4/HKhQKoblYr9cLiULGBC2A+saleP1+PzgL+rQg5dzc3FS9XlepVArPebET74VD57HPC+N2EOV5SvIzme0Oic1mM/R1gddmPAB7r9dLJE5ZUXguw9UpOBSXjA4Gg7AbFlvsSTvtGWiNwBwhg/R77PeXOfDVA/RQ2gE4NcOY0pr3mV165tTezE62qQF3wA1jqQ1n7F9gSUH5wfOePIP6SBc0+ebXHtFVq9Vwvrm5OVUqFTWbTTWbzUThk3PA0ADefjjNZXc6nbB3KqBK9O40CddDBM6qhGgVcGQ148VMDtzQSB7NUxjGsbyb5HA4DFWv6NF9xcR5fL9VqCXmmMToeDwOfPp4PNbi4mJCyYKjdYVQt9sNyidPBEtKgLZH5K7U8c+OS179vLPIfWYPVJsacHd1hHTyNnkO0gCPSxKdh01r1D0qxuDXvfEWr2u320Fy59p1l2hKO31PMLhqHyMRMu9nr9XNzU31+30Vi8UAvtBEjKtYLAYwdccCl8w1MC5AGDqI6+Q9gCXtDVxXD0hHURQSud63Pi3nBKjTeQ2uTdpuPcB5uSacz3A4VLvdDlv0eQGSJ4xRwXhSNw3yPj/pcc0kkTOblD3+8Y/XJz7xiYkl9KcG3NMyRq9M9KjN1RQe6blSxI0vNrwvwMHmFx7NS9ub99IwjPN4CT7gyPjgtwEb+HZAEoqCAiDaK3S73dAxsVKpJDToyAyRFgLinghlzK7zJdoF/J3qAth7vV6ikyL8PWPJZrNaWFjQaDTS+vq6er1eoqCIilVf6bhayR3p8ePHdejQoUS75mq1ehL15M3MmGM35tyjeXfGOCBkn+QMXKVzKdvCwoIWFhYmPYx9t5tvvlnXXXfdpIdxSvvVX/1V/et//a8TK+39tKkAd5fBeRToqhnXNzsH7UvxdPRO1Od0hUfFgADFMSsrK4Fz5/jOpTuPDz+PmqVSqYTI18cKaDqwesm/6+h7vV5QxhAlA1CM1flml0lyvkKhEHq/A+JE8eQDKAbLZDJhgxJpJ3/gG45DJ+FUS6WSyuWytra21Ol0gsOhiIn5h+pZW1vT8vJygoIqlUphLrvdrg4ePJjg29OJVL/vaX4eKojrResvKWy8cqnb4x73OD32sY+d9DD23e68885JD2GqbSrA3ZUyaY7Uk6S7JVkBAC9ikXYKdAAMKiV9hyQiyvX1da2srASVDFEfm114tDwYDMIWc0TWFBw55eBc+NbWVigUajabCT7Ym5Lx2PcjTTsyN3cSXm3qzcDYLMRlYwCgO55WqxVoJFcZAfhE6T72SqUSWi8w5zgTb81w7NgxHT58OFT5smLgujz5yb3cTQLJ3ALyzWZTGxsbYQer9Mqm0WiEXbVmdunZ+vq6vvzlL+tRj3rUpIcylTY12SZXXkg7oO2RuRuPfUnuAJ+ma+BhoTsATjZ+TnPLbEuXXjnMzc1paWlJ8/PzYZchQNYLlahe9XJ/OiRSdVqpVMJGH+VyWbVaTbVaTaVSKewF6vkFrjc9J0S1NFDLZHY6RBLZ0p/9vvvu0/r6engeuSQVu2wjSOROf/utra3Awfvq6sCBAzpw4EDi/D7fvLbZbCZWIuVyOTgLVks4Ka6NuWecOIXRaKSNjQ0dP348MVbuN05hPB6r3W5f8rTMA9WOHTumd7zjHbNahlPYacE9iqK3RVF0PIqir9tzS1EUfSqKou+c+L144vkoiqLXR1H03SiKvhpF0aPPdCCAqkffqDngeR1YpJ1GUphz5+4cnB92AOl2u2q32wE0XO1CZA7fy2bQ5XI5JCMBEmgQCpfo7IicEv36YDAIW/K5pBPeHu4+vW1eess7aWd14U4PJwQPDs8PKPN6fw1zi0wTvb535PSukLyO6J0k6oEDB4IyyJPDXlDVarXCteCAmAOM+8bqyvMD/I9t/dgExfl6p+bSx57UZ3tmF87e/OY3T3xTjGm1M4nc3yHpyannXibptjiOHyrpthOPJekpkh564udGSW8604HwRe50OlpdXdXKyorW19eDJHF9fT3skelcrzen8i+5gyOJVKgOqizX19cTQEBkGcdxKPzJZDKhx7onUnEEcMcAOe1819bWdO+992ptbU0rKyuhSRlRs8v/4IwpDvLVCGDJ9bDy8CQn43eummg4n8+rVCqFvjaLi4uq1+thDgBxVgTFYjHkDzyHsLm5GXrOl0olVavVQLNw/3K5XJBA4tRwWNnsdo/+drudoGconOIaWFHxf0+kStsO/9ixY0Enz/1PS1TTz0/ysz2zC2e9Xk//9t/+20kPYyrttJx7HMefiaLo6tTT10t64om/3ynpzyW99MTzfxRvf5s+H0XRQhRFV8RxfM9pzqH77rsvtJwlImZTDde6A9BxHAflibeVZakPUADwNLQCrOgGCRj4sp6/6ZFCxOqyS/7PJh9EiA78HjVSVBRFkSqVSnAccOTIKBuNRuDwi8Viov8MkXk6OnUKwykgqmAdLEkk81428Dhw4ECgZwBxaBYoHsYBv83OSt4OIpvNql6vq9VqSdqRuDKudrsd6Cy/LzjXXC6XSIp6M7TxeHuDbXIjRPKAutcY+FaKk/xsz+zC24c//GE9+clP1q/8yq9MeihTZeeaUL3MPtT3SrrsxN9XSvIU9tETz530BYii6EZtR0AqFAq68847AyCTDIXu8CV+NpsNzarm5uZCj5LBYBAUG2n+3vXg9ENJKzFcboliBT6d42WzOxt/9Hq9EN1TmJRW7vAbHtw16xxLSqp+SGD2+/1QzeorEFYhgCHj974rAKevKDgvm19vbW1pY2NDcRyH7fVYdbB6YUMRd2zSjqzTK1vp8wOoHjx4MKywPOENhw81xbj4v9+TNA1HxXCaenMH4907d0tC7/dne2bbtri4qF/6pV/Se9/73j0/dqPR0HOf+1zNzc3pH/7Dfzg1dQ2IDprN5mTOf74HOBHJnHXGKo7jW+M4fkwcx4+Zm5sL/C6WrjAEGLa2trS+vq719fXAEZ84XgAHj2b9GACIFyhxLmlHXkeyFIABeOfm5tRut3XvvfdqfX09RLgY1APqGHY+KpfLuuKKK0LvlXK5HLTd3W439K3BAcC5O+fv14R5vxYfA44GaoXCKRK5DrjeRphWBET2ROto8VkVUXHb6/XCZicUTuGAkVk6tYPDIdGLk/JNTdzSfDn73/p1+65RUFzQQaxCzvXLvhef7XM68SVoxWJRj3zkIy/Y8RuNhn791389bM4+DXbkyBE973nPm9j5zxXcj0VRdIUknfh9/MTzd0k6Yq+76sRz92seeXqfFcDY5W1Yq9XS+vp6ooDIVROucPHkH5tWcA5pZzu7QqGg+fn5QCMA6FAHgDpRNcesVquBw0bpIm0rQur1umq1mur1ekimIov0hCngC4AD0r4RiKQE/cP4AU9oK8bFagcdPtw7rRQolpIUOllyvXR1XFpaCvcIvh+lC8njXq+njY2NhCKGaB8OP12zQOtgriEdZXsjND4fJHJ5vc+Br7xwQCRyzxLc9/SzPbP9s2azqRe+8IWJDXgmaazEJ2XnCu7/XdKzT/z9bEn/zZ5/1gllwU9JapwpJ9nr9dTr9bS5uRlK84nmPaLzqI1kK19+55LdKXg1KQoLp0fYmMLb0AKU4/E4JEXh7F3BMh6PA1gD3sgBt7a2VK1WVa1WE5QB78cR5PP50EzMeWJP8HoU66Dm9Iw7Ae/9jkNBxTM/P58o+4dHJwnL3AHa7XY7dMNEvcS5icL53Ww2w3aGOBGu1Z2RK4zSII8ixh2wOwMHfOfcPblLFH/vvfeerRRyzz/bM9tu8/yBD3zggp4jjmO9613v0k033aRut3tBz3Ux2Gk59yiK3qvtBNPBKIqOSvo3km6R9IEoin5d0h2SnnHi5R+T9FRJ35XUlfScMxkEX2YAjKU7Xo9I0MvYoR7W1tYCUEk7Ow0BAg7GAISDQCaTCby2t8Udj8dqtVpaWVlJ9EWnspNImePRxgBnQbVpHMdaXFxUsVgMKwRWJByrXC6HLpFEza7rTuvseZ4kMo+5Tv5H/iCKdhqpbW5uhu6P1Wo1FC/FcRwck4/N96ZlHFwzqwv4epLEjUYjUflK1M+94FqoKvVqVMCc8XshmDteEqgc34uc+P2DH/wg7Ag1qc/2hbYoivSkJz1p0sM4rW1uburrX//66V+4B/bHf/zH+pmf+Rn95m/+5r6cb1rtTNQyzzzFv352l9fGks6JZALYvMujR6fwuL68J7HZarV04MCBkxKTRLUOJg7IkoIiBxoBXhkuWdqmV0gUkmT1QhmOC5CiPuH8ADjJwFwup06nk2g34IoRAFraUd8AsB5Z8xieGxoDB+Pb4Dm9wzwVi8WwYnLdPqCNjLJSqajRaAQHzDgBV6J0qBReNx6PQ3sFr5DlfqCxp/8OoO33EaB2cHd+ntfSvoEV3MrKSqgkPpXt12f7Qlo2m9UNN9ww6WFMlcVxrN/5nd/RYx7zGD3mMQ/ctMdUVKhSSUgiDPrC+7DwQ3QHeERRpI2NjQRtAVD6sh0pHtQN4AZdQJTa7XZ13333BU6dalbAksgatYekkDylypTNrgFud05bW1vqdruB+0fjTiMxB2KqR5kPb1XANTjQeasCqBv/SRcY+Ty6EgfVDICKQ8LpEFFLCsVR0nbSjP8PBoPQHoAcBslT74VDYtWPhyPjPOkKRI/wvciKx61WS3fffXeiedjMJmtvf/vb97WS9M4779TTn/50ffvb3963c06bTQW4j0Yj3XXXXYHXpWQ/XZVKRO/gFZ/QaqNcYYnv/LuDC0BWKBRCXxWSsoPBIAAvEa1z2ChYnDZiT1KnBZAeOpWCnjyKoqDgYDwAUD6fV7VaDTQNShtpp0e9gzXOwJPJPO8Nz6C9UJBwXq6BpCsNvXhtr9cLSh5WLeVyWQsLC2F8OCPmldwFTcrg4T03QNJXUkIl5Ql0j+C97YE7NK6BH8Z+zz33nJHOfWb7Z1/+8pfPRZZ6XnbHHXfoPe95z76ec5psKsBd2s50//Vf/3VQRHjE7lF6OoHGa9Fse6SOATQADHSDtMMHd7tdNRoNbW1tJUBzOBwGdQg/lUpF8/PzIQplBeB8MqAFCOKAAFoSj3D7zjET/UKhQH94QtYdnjfekhQAkiQpiVJPzJLsJJfBCkKS6vW65ufnVSqVgs4d+orVSLVa1cLCQpAxMj4ifpwMTrPdbp+k/ZcUkrR+f/3aMe85w7ncEfB4ZWVFjUYjUaE8s8na2tqajh07NpFz33zzzRdEW38x2FSsWfnCNptNff/739cP/dAPBR4WDpjXwd2ylHd6gWRqWj2BIgRlBsVOROybm5sBbL3603l9NOMu88NBEGHS7Av6xTsVwt9Dy+RyOS0sLATH4v3NibxxUFA7zqczNhyW5ye4Nl4PKDrAM49OazQajURuAe09cwJ/TiKUdgPuQADcubm5kKvAofV6vaD997EB4unEKPPKfLtzd9oNgO92u7r77rtDotyd7cwmZ//3//5ffeYzn5nIufv9vl7/+tfrCU94gg4fPjyRMUzKpiZyh89eX1/X0aNHQ9dCmlh5ks4LVwA2pG+udXcw4zkiaZKi3W43aNddDeK6csBKUuCrkRWyCmCTjo2NjZDMS7f+9YIlnt/Y2AgNxcrlcgBVonXnuB0I05JAAM2jVW8s5v+Lou2eMhQfFQoFXXbZZSGxjD4cyoXxQMOUy+VAEUk7en7AOt2D3q/VOzxCz9AX31sscP/SBVxOZ3n0PhgMdOzYseCQuGb+ntnkbNKrp89//vN62tOeprvvvnui49hvm5pPPl/EXC6nlZUV3X333aExF0k2IkzXdXuike3dAFO++IACgAz1QS8XJITSTosBnA3A5SoWImsfC7LJfr8fOOxisRgKdjqdTuhBk8/n1e/3dddddwUQ9ejVOXAHdE8aOzXjgIfzIT/gxVGe0OS1yCKz2WyooKWvDfp9Vh733Xef2u12kFMCyDi/5eVl1Wq1ANKuS2f8ODPuDysUHJTTbq4KAsD57Un3fr8fGrVxfb5SmdnkLI5jvepVr5r0MPSFL3xBn/zkJyc9jH21qaBlpB3gAuTvuecelcvlsEsPCTOPIF0bDUBAzWBEtnDjnGc43N4Q2nXRnlglskRiSHUrAFmr1QKdA59PpA7okeylvH8wGKherydaIMB7A0Q4IKpHHRw9EnXttq9UcEJQVrxvNBoFnh3gxZlybnphsOkIwCntcPTMMysWKCPGBJ3G+7wnvaSQtGYrP9f0p2sQnJ7xIqfxeJxw9sPhUPfcc09iDjzan9lkbWVlZdJDkCS98IUv1JVXXqmf+7mfm/RQ9sWmJnIHyLDxeKzvfe97YTMGB3eA05fvkhK0jCtroD1I1M3NzYV+4J64ddqCCBYABHgKhYL6/b42NjYCmBPlpyWHOJZ+v69yuaxqtRrGi/rFN8JmLK7Bd54doOQHqsX5dmlHEumRPuOE/qnVaiHKLZVKobUAVAnHp8WAR9LD4VD33Xef7rvvvkR0zN9LS0tBReRj5XXdbjchwcSBcgzmx+fRo3mXtfb7/VBo5gohjjWjZSZrf/EXfzE14N5oNPSHf/iHocL6UrepidxdJUE02O/3dfTo0UQ3Rf9iuwTRv/hI96SkFpyfZrOZ2GnJ+Ws6GlKcRKRLBSmKF18xMP504RT9UEajkSqVSqBooGz4jfQRJyEpUbTlrYu9yAinBhg7581jjkUSk9dD23D9OEaAdXV1NfyvVqsFSomVC0njVqsVHBTvpUNnrVbTxsZGSCx7wlcdpgAAIABJREFUkVqz2dTS0lJipeFj9wjc8wpE836vjx07dtLx0xz9zCZjn/vc57S6ujrpYQT7H//jf+jLX/6yfvInf3LSQ7ngNjVhjVc++kYUKysruvfee8OXG9VFmqPli+wqC/52jpmNnZ1K8Ii9Wq2G81cqFdXr9dBTPd1SFtmmq1GcPwd06c/OTk30oKHPCxQMmnOnU5yK8WSyrzicVvH5SEf7zC3/Q9ZIEdb8/Lyq1aqWlpYCF4/Tos0yNQiMNY7j4PTShVGSVK1Wg6OCL8dxu/yT6+OzwG+P5HkOuoj2wc1mM3EP3GbUzORsPB5PVZdGaXvV+Pu///uBNryUbWrAHYDii+uJwXvuuSdw217g5CDigO7JRacqoigKCVTvuEhRU7VaDbtBkZz1vUWJwMvlcpATlkqlhDoD/TagiIOYn58PvL+kwK1Dh3jHSHjrVqsVVDwcU9pR8LDyYJ78/4A9184P4/TonYgXHh31jEfo0EjSNm/uhVrMOVW3vI77Q0LaVyG+wkoDsyt7fNySEqqp0Wiku+++W5nMduti5sgdtlNTM9tfW1lZ0ete97pJD+Mke9/73rdvfW4maVNBywDG6WQhvweDgb7//e8HGaNvpMH708cC/JybxzkAfBQ3wTVTxNPv9wO3vrq6GqgXgJAIH4oAcBmPxwl1Cjr2crkcVDQuc/TGW94HHTUP0bFz6/7j8kxJYSzeLtipGJLRriYhomc8bLrBqgKnhj7dj8MckTBmDOQsXIa6sLAQKCrGzFy4YoeIKt3h02WR/CAtdVqH6/XPxCTbrj6Q7Wtf+9q+thw4U4vjWF/5ylf06Edf2tvgTgW4eyLSG1shC4zjWKurq2o2myqVSiF6B7gBK2lHGy0pIbWLoihoz4nuUMPQHgAHA1cMfQPw5vP5AMy+u5GkBHUBQAJYo9Eo6PYZGzy7pFAQBDgBmOnWAoC+tAOi0k5jNczpHKpjUQBRDep93wFLHArJXZQzvIe+7LzGx0rSldoBj/SxcrkcqCx/v+cTuB6/l9wvd+ZUo/I/zLX9vG5Gy0zG/vAP/zB8X6bNfv/3f19Pf/rTwyr5UrSpoGXS/Dd/8z+A7s477wyRN/y7R+a8HhDw51FWALbI+djPFO6aQiT6vwBc3vlQUuihMj8/r6WlJS0tLWlhYSFIHT0j782wKBCiUhWKAx08TsY1/YAvXLvPjSeD031kKO2Xdnay4sc5R0AVqosNOarValDVSAqrD/a1ZVXC3PA8CVP2g6X18Wg0OmljbYqOXHXj0X36GqFz0Laj+PFmZPz452hm+2t/8zd/o69+9auTHsYp7Stf+Yre//73T3oYF9SmAtylHSD2JKl/YaMoCptzAJ4Ae1r66AUscNa+YTWSRvhvNs0oFouh1S+tBlwaSMRbrVa1uLioer2uQqGQAOjV1VWtr68rinZaJXQ6nVDkRI8VSYmoBsqo1WqF6JbEsdNITrPw2HXdTkt41apTXp7gxJG42oZIn3wBW+zhWODZpZ2Gahh/06RsbW0tUSEcx3Hoy4OxwvIOmt5yIs2dZzKZsAuXf06cvnLufWb7b3fccYe+8Y1vTHoY92uvfe1rT9oqc6/t2muvDSv0/bapAHe+jGnZIv/ji4++2iN2X8Jju1WnAmBEpkj3HPTZoxN1C0k6nAaRPmBHcg8QhAah5W+z2VS73Q5ROPw5ChLXcrts0a/dQdx13Lw/TWVAITFvzrHzegdO5oYx0rrYC63INQCyLvF06aqPgfeMRtsteF2yKimxJ6s7uTRnns6nsHrpdDqJXkB+fCirGbhPzl7/+tdPegintaNHj+otb3nLBT3HL//yL+vgwYMX9BynsqkAdwcGHks7xT5evbqyshK4a1fMeITqXDzgR4UmjgIwQ6JIcs7leOmiGUmJjpG5XC6oW4jU8/l8oA348WvBQaCUYXXh3L6vEtJVqZ6kdE13WgbpDsLnluvy6Jb3eiUvzo/rptLWE9ocF3oG8KWnjDswaC6ciaRA4+AocKIepTtAOzVDv31/nVN4XKtf+8z2xz772c9OrFHY2dhwONRf/dVfXbKfkakAd6cE0kDvOnLoFfqT+GudcnEA5P0oSXwvT5xCu90OzbxceUInx2w2q1qtFvhewMgjxF6vp+PHj6vb7Qa5pBcF+cbUjI2e6Z7kJRKG7nAH46X4DuYuA/VoGiDlGFxvOtqHM/ekbaVSCVWmODKqbVEE4Zigter1esJB+b0ZDoeJLQq9jQTOAOeyW5sFr1sYDodqNpvBubnSyj8vs406JmNf/OIXp6pw6f7sj//4j3X77bdPehgXxKYC3KWdjZ7T1ZeYc+nHjx8PCVWnVbzYRVIi6iaS92ZX+XxerVZLnU4nqFwALZwHrWuhGlghQO3Mzc2FzT04RhzHgWvGIaEw8Sh0N86d5C7tEtJRhVM16a34HBg5L/OCebWq0zQ4Hy8uYuPuYrEYjgcwIy9kNVQoFFSv13XgwIFELsD5c4CZZOzc3FyiS6fz5ekkezqxnKZe0hp5nOjM9tcajYbe9ra3TXoYZ2zdbld33XXXpIdxQWxqwJ3lOwANJeGRGYAGIJ9qMw8p2XiK5+DQiYwpVvIkI6ALdw6ge4RMRamPEW23tF345IncKIqCmoTrJCHpYO0rGFYaHjm73JFr9EiVa8CBuCNCAYO6xIutnKdOtwIolUpB4cIKAFkn19Xv98M1U7jlm5m7NBU1ENfuVE26UtUT48wZqx3PQ3gRGe/zxPOMd98/6/f7+t73vjfpYZyVvepVrzopmLwU7LTgHkXR26IoOh5F0dftuVdFUXRXFEVfPvHzVPvfy6Mo+m4URd+Koujnz2QQgCPgBSD4lxegy2S2+38D7t5RMc3ZutyOhCyghVyPCN35WbaSQ9cNdTAe7/QvATQ8cgW4c7mc5ufnw0qA3y5jdO06tAiJWADW6RpkjekqXcbuwEiiV1KoesVJ0ZKAClnPIXAuzu/OgethDtHlU0UrKdA24/E4VLr66oCxtVqtRBROMRTzl47eua8YCVoonrRT9/t/f1/a/fhsz2z67f/8n/+jD37wgxfk2JlMZmLFUmcSub9D0pN3ef7/i+P4USd+PiZJURQ9TNKvSvrRE+95YxRFp93I0iNN/y3tRHHOn0fRdmMrtNweufvrHSAosgEI2FTbfzi3AxOOBiqDzawlBW4a9Uur1VKr1Qr7pUI99Hq9sNogCmcj7Xq9HvTkKFWclgJIvQ2wF23xf9+aD4om3Y6X96QbkfnxvXgMsIVGWV5eTqhrMK9CbLVaAeRJzjpVxH30JKpz7O6ouB9pvT/z70lzv/e+IjiNvUMX+LM9s+k3KuAvRGI1k8noOc95zp4f94zOfboXxHH8GUln2v3neknvi+N4K47jv5H0XUl/90zeuBsV4coPgIvfa2trJ0WuHuGl6RnaBks7rYF57OBdLpcTfUoAP+eN0djDoY/H4yB7ZCxxvL1l3urqagCjSqUSNrTAIQBOgCn6eiJqIvY07cK1enLUOztmszutfJ0Dd5B1SojrRPHDtTFPRPvSTisDFD0klEl0Q6HQ2oHt+bgG2hXA3Xukndby2+cwvM7VONyTNJCz6rs/26/P9gPJfCe0i8l+93d/V41GY9LD2FM7H879piiKvnpiabt44rkrJd1przl64rnTmkdeHmGnKxe97zqcOx8ookmP2j0Zx7G73a7iOD5pl6JqtRo6QMZxrFKppKWlpZAgbbVaarfbYUNrWt7ywwoAmiabzYZjsiUfHDzSQqecoEkAeF+N+CrFeWzmhTnwiB6wZE5247R5vWv+oWZoRwylA1ff7XaD+sWVMOQwGBsrBBLPTnFR+JXP54OT8qidudytKA3pKNeU7jnjq5VztD39bD+Q7NWvfnXo0XQx2fr6um6++eZJD2NP7VzB/U2SrpH0KEn3SPqPZ3uAKIpujKLoL6Mo+ku+oL5sl5QAFSm5E1G/3w+6dPhwKbnJsvOvRJoUFaWTtVSRpVva0mIY50GRU7fb1crKilZWVgIHLG3z9TgEInH+diAkaUyC07fw8+jaJX78+IrGI1p/zq/PVxM4Je/N4yseKCHmBcomiqKQXM1mswkZp98Xd56uzCF/QfQONUN7BBwNCiAHaWnHsSNFdWrKczaenOYzdZa2p5/ts33vxW4XuuLzQlkcx0H6fKnYOQmB4zg+xt9RFL1F0kdPPLxL0hF76VUnntvtGLdKulWScrlczJc7nSiTkjvquKKl3W4ngJzXpoFB2tHBb2xsJMA2juNQhEQEXCqVNBwO1Wg0QrIQ9QwdDJFh5nK5EIXX63XVarWTkqEclw2o4e4x2gbHcZzoz+L0BIDlHSU98na6Ji1b9KVyOqlLiwWP2Eng4uBwaJlMRgcOHAjSTzYvh5ph/qWdzpouq6TAazweB8fd6XSCM/S8yonP1kmrMM7LCstXJmmJJ47ybGyvP9tRFF18HMXMLgk7p8g9iqIr7OHTJKE2+O+SfjWKokIURX9L0kMlfeFMjpmOIj0id4rmxPkDxyztAHp6ec574Wg7nc5JjmJ+fj4ocKh87fV6ajQaQfLnbWzTicl8Ph96zczPzyuO4/BeaQfkJIVmYevr62o2m+E1UBr0zoF+SecbGDOgld5xSVIi4Qq1QSTv88j/mefhcBiul3n2zpP8phEYlBb3jsSutz5AskikXiwWValUwrzgpH0F5UlW7qnTUO78fZXm995XKrs5+vuzC/HZntnMJmGnjdyjKHqvpCdKOhhF0VFJ/0bSE6MoepSkWNL3JT1XkuI4vj2Kog9I+oakoaTnxXF82koSX6o7T+q8cpp7RTHjFIO0E9mfGE8AjFwuF8AUIKjX64HLhr6Ioig0/mJZX6lUEioPOiXS9zyKtpuakWiNTyhiOAY0BRt0u/yQqHg3MIeu4TgO8syTUzK7OYP0KsXn2MGQufJKWK82JflMRSrHgmYin0CE74nner2uKIqCJLVQKITNUHCmHnk7QDNWxgWlxfx4nsELoXwOJvnZvtD27Gc/W5dffvmkhxHs8OHD4XN4sdnKyop6vV5o+Hex22nBPY7jZ+7y9Fvv5/WvlfTasx0IX1KPrF0S5/I9IsrNzc2QnEOZASAB1vDDvA4goDKSCJIonJ2a4N0Bb6dhKNJxwONvZIP0U+E45XI5IfcD4AFBCqCc//bI2FcuPjdcI397lA6N41JFnk+vcgBDj4jZ7xW6xpOlXAMAy3WyE5ODMvusetdHv16cc3pzc+YLZzMej9VoNE7Kl3i+xSWTqIZOBTT79dm+kHbkyJGwMpwGe8lLXqI/+IM/CM77YrL3v//9esUrXqGHP/zhkx7KntjUVKhKyR7uHrUBRN5GAAA7Vetfjkf0nZZLeqITp0JCJY7jQD0MBgM1m81wbLo/jkajwL9vbW2FiLXX6wV6BWdCm2BaEzjYeqTK805FpVckPmbkiR6ppqPW3fIVnDe9EuA5AFhSUMbwGufzJQWVjxd3AbLO+XNNUGnuAHyjlPR2ga6aGQ6HIWHHnPHD2Hyl4tc5s/2xYrF4ye9wdLHY1IC7g4L/lhS+8Okv8Hg81vr6eiKy88iTpXwulwsAMxwOQwdDHMXc3FxoHhbHcYiyvUHYeDwOkkZ03/yvVqupUChoa2tLzWYzrCxcI+8VsjiHtMpltwSozw/HIhqHH0/LBj0id8eXlkJ622Cv0AUcvbEXjsrljJ4sZUcbV9vgyNhAm4054jgOToFz+gpK2onW4dtJSnONvtLA0isRd2wz2x+r1Wr6pV/6pUkPY2aaInB3zljaUT/wJXXw8WiMYiaAbjcgS+vPnUOmaZW0o0oBtHEyNNVCBkjUiCSPTTo4HpJGgM77rDhYMlYsTXMAbFyf00v+4wlE5sDnKz2/7gBcdum8vzdOw6CmHKABY6gWVhTcJ8Y1GAxCLYArfXxzD79faQmoj5ccjXPv/rngmtKqo5ntj/3sz/7sVOUBJm2PfOQj9bCHPWzfzzs14L6beRLQQdWTZiRUvTISwwF4tE9UCucN8EPBwIHjLOAOs9lsOA+SxuFwqNXVVTUajZMSkAASyRmSqhzLVSKck6iUVgkkenEY6cZg3maALpWoWHAiPmfQHswNKwXmGWfk9E5aYspY03NMchnnSQ6D//M+5oFzkp/w6tq00of3E/1LSsylK3qc5konZWe2P/aIRzxCv/ALvzDpYUyNXX311Tpy5MjpX7jHNjXgvluCL/2lTHOxgO/m5maCy94tYiWCBqTRS3e7XXW73ZCQTYMdOy8BrN1uN1SobmxshHOTvES/7eX8HqkT1TMG78HuKwcA0jtQ8sNY0sDmuQWPYAuFQsIRoF/nOC4zhAphQ5NTzSXn8Og4TQGx4nGnx/i8TYI/7yu1tFST3ZfSMkhe77QUDmpGy0zG/vE//seTHsID3qbmk+86bI8YHVy8ApG/G42GNjc3g5zOl/NpegMpItRCs9kM4ExC1BUnNNNykOX8q6urIblHD3gcDQU73gmRyNSTgLuBEFWdXlnr3LpH8z5HXJf3Y/dNODx3AB1C219oKv7P2LgPzB9gDg0CT+5UE86HRK9fC46o2+0mKLi0pNET674a47fPWZrecWomTXvNbP/sR37kR/SYxzxm0sN4QNtUgLurY5x68MRZOkJzUPFiJo/mAJB+vx++/ABNs9kMvVH8+H4conE2rAY819fXT1JocBwHGW+QBcigsBkMBgklSj6fD85kt92MAG2Psj0B6ZEs8+dRM6/xuUlH+GkaRtJJzpIx4aC63W64L7QkhvZiFYODScs/cVan0uQ7zcL8pz8vTm25uor7MwP4ydgVV1yhhzzkIZMexgPapgLcAXUMIEgv0R3ApB2t9ebmZuDA06oZr3gEnPv9fugxAyAQETsFQgSM1p2WB1S6EvGisiHKhhtmPFBBUDHsyuQKE9eTp3dtAhBdfugRqzsB/5vHTnGllUgO8tJOsRAOifkCiEkK8/52u61ut3tSrxnaK9AdkutkrpvNZiJxnY7S/ToAdvZh5Tr4bHB9rkZytcyMc5+MvfjFLw6rw5ntv00FuEvJRlFpDtYjS1d38Nrjx48HB+C6bQCRnZXgvImmOY8nYSWFDo4cAy4evt2jRl7jtJBz097FEJChEMojTlfskIz0a3Wgd0rH/8c8+t84vTSv7s7PI3vvx+L7u3IsQF7a2ZyDqlHvKsk1wfe7hJFz0yLZcxY4Bx8nzmZtbS3c2/T8u+wxnTye2WTsb//tv62nPvWpp3/hFNm73vWuSQ9hz2xqPv2eRAWgfGm+W6UhX+Z2u61erxfAwSv2eK9LBmlD4E24AEt46iiKQoWmpKDX9rGgbXeQZis9ona03IANTcLYng5QQ1kDsPE/KA2nQ6STdyfCqeTz+URCmPd4zxgoE7+2dOTP+N1BQFGxWnH+nTEBzpJCxO/n4dwcC5qKeYCv9+ujRcFoNArz4eP1356PSFNbM7vw1uv19K53vSsUnH3qU5+a9JDOyj73uc9Negh7ZlMD7q7akJIcr//Pv9SeOPOEIK/bDQTiOA6Rpis1AMZSqRRAv1arhaQtEr50VOlSSoqc6BJZLBYDuNNThfNkMplQLFUoFMIuSHRq9LETzftqIz0XPm/kLUhucn7oIy8MAkx5DkVN2im4uidNeXhNAM3H5ufnE3mUYrEY9lkFyDmuX4OvIrwa1p0JlIxH5g7ijKvf718yfUKmydrttr72ta+Fx51OR694xSsCbXf77bfPHOoU2NSAO190j8AAMi+9dxUE4O/7cjpISUqAOJ0PPfGG5C+KItVqtfAckTTVlUSdnvxjNZDP57W0tBSAnKiebfQAe8ZBkjO9Q5HnAOI4DlvuAXIumfSCI3dyvDedjPZt8ZhbqCScDBQViep05E4REysNlDCuRmLVgaN0FVCpVAobekgKzmBxcTFBq/g4mU+vE+C9aUWVzwMrpTRtNbOzs3a7rc985jP6wAc+EJ47fvy4Pv7xj09wVDM7E5sacAf00glTfjuoOwCyRym9XKBe/P2Aai6XCxGgK0YymYxqtVrQqY9GI5VKpdCel/NRwORyxAMHDmhxcTFsz+d7h1JUBEjjCGiihcPxRCSvYVemtP4fUAXIvNpT2uklQ3TL9TCHzI/3cOl2u2HuMegPVhvOu1O1i8PACXe73eDEWq1WSEajViJR7JttsDrwTpvSTuEZY19bWwsO1q/fr9eDgHSF7szO3v7Lf/kvetOb3qTPfe5zicK1mV0cNlXg7qCU/qK66gEQ8siVJCkSO2lHJw2Qt9vthHMg4kQNQ7RaqVTU7/fVaDQSESyrhPF4rHq9roMHD4aNrlkBLCwsBI07RTxE5IAtnD6RMwDoWn9066gNiNg9GQqd4s7O58SdgXeY9JbDXhDlKx5oHcaCIsZpGXrv+P0ZDAYql8shAU0egfvmyXDuIYDutJMnWr02gWsYDocnceqen9kt2Tyz09tXv/pV3Xrrrfr0pz+t733vexdld8fzsUajof/9v/+3fuInfuKiL4CbGnCXkg2tXK+e1mlLO8lU6Iljx44F+WG6GMf5WVYIRJ0kFpFBkuhsNBqBogFQAZPDhw9reXlZUbTd8ZFmYpTfA5a83mWNcRwH2sKTgQ6+jBvpJk7Fr985b1fSpBOvHuF7ARjz4Dr4dHKSBCdzzP9oxrawsKBOp6NWq5XQ4TuV1u12Va1Ww3s5ju9ERVdIvzbPo7iDdsUNx3QKj3lN1y7M7NQ2Go107NgxvfrVr9aHPvQhraysTHpIE7Ovf/3resITnqCnPe1pesUrXqHDhw9raWlp0sM6J5sacPcvoUed/tgjRP/ionVPS/d4jastHPRGo1Hgm0lkIu2DqpB2VDX1el0PetCDVC6XE7shkYREFQIF4Tyy8+nebMsTm2kn4jp53pNONDuV5fI/p2A8CUkU78dwJ8FjrsOdaalU0sGDB7WxsRFaObC7UqvVCtp1NuUgeY0DRGnDnKF+kXYct1fepgu0nGP3RDDPkStIU1Uzeub+7Y1vfKNe+tKXPuCi9FPZ1taW3ve+9+kjH/mIarWaXvrSl+o5z3nORQfyUwHufFm9zN21y7uBlIO7ywMBS5QnTmM4r10qlbS1tRU4aXjwVqsVKlKhIIrFopaXl3Xo0KGgoKHwSNqhTABaj4RxROko20EcusPL9jmu94Mhmk8DM0Dp2+6lKQmnWxiP92Dnb64begsqyNsMM8fD4TC0ZYBuKpVKYeNyksSdTifhKH2MjL3b7Wp+fv4k5+vFaXxWnOZJJ2I9KPC/Z3ayjcdjveENb9C/+lf/agbsu1iv11Ov19OLX/xi3Xbbbfrt3/5t/eRP/uRFQ/VNBank0VtaEpkGRKctvGgljrd3L0db7ZTMcDgMm3MAYMgXScJ6pau0U7FarVZ11VVX6dChQ5qfnw9ghl7bE4Uexft1ENV7x0YHJAc7N4+mcQRpx+GKEk++ejTvTkLSSZE6Y2KFg2SRFYyDJHOFM0b7X6/Xtbi4qMXFRV155ZVBOYPzWl1dTdAnOCLGsxsfn1ZQOd3kK5jd9P44LebqUrUPf/jD50SjjEajELFT9zGzU9vHP/5xXXfddbr11lsT+DTNNhWRe1oV4sDnXKzTGrtFZI1GQ1Kyw6S0k4ADyLa2thLKDegD+qQQdS4vL+vgwYOq1+taWFhISPsAeB8PIMoY0Fh7IjB9vRzLwcr76zhoO4ixSkhX5frr4fI5n+vCPalK6wAHTzh+JJAux+T4+Xw+OAH63VcqlbCn6tGjR0+qBnZVDglbSUFiiZPxpmQ+Vzx2ysjrApzv91XUpWq33367Op2ODh48eFbve+Mb36h/+S//5UnV2TM7tfV6Pd10002K41i/+Zu/OenhnNamAtwd1Dzq5H9p7p0vfTqpRpSZTuzxfx4DeICBR/P8XHHFFVpeXla9XlelUgmJOqgT3w/Ux+WKDcaWzro73bGbegTgTStknI+GxuH/ACD0Da+nKMvfJ+1EuL4JCPOBM/DXAPCMmb+J4JvNppaXl8MqgMj8zjvvTNyXSqUSCqOYU096M4e+WoNm428fH2P2ZCufm9208w90g4p5+ctfPgP2c7DhcKgXvehF6na7uuGGG/TgBz940kM6pU3VJz9Nu0gnb8DgqgmP5rwIR9r5crsSw9sGAEqu6gAkAPZaraZqtRpK5J3m8AjbNfiMJ12a70k+76XuQI7jcHBMR69Ou3jugedde+60R6FQCMogKmRbrVboZ+8tiT1X4aAJReLKmbTk0zcMWVpa0hVXXBGuqdVqqdPpnJQ7SFel+rVwPd7WgNdKO2op/6z4nF/qNhqN9La3ve2MXztLnp6/dbtdvehFL9Iv/MIv6Dvf+c6kh3NKOy24R1F0JIqiP4ui6BtRFN0eRdHzTzy/FEXRp6Io+s6J34snno+iKHp9FEXfjaLoq1EUnXa3XP9SOqi7QiIM2CSQUrIRFtGnR8RQAp4wBFBJimYymQBuANL8/Lyq1WqIhAFcV8kwHl8RpKWHLolMOwbn0Z1CSXfEBGTTc4Cu3x1YOonoYMyxJQXduleucmzmj7n3nMJuyVz+h3OtVqvBKS4uLuqyyy4LY/LqVH6T1OY6/VrckTv4c+/JpfiKxB3TqSi8E3NzwT/bF9riONaXvvSlM3rtm970Jr3gBS+YFSTtkX3zm9/UDTfcMLUAfyaR+1DSi+I4fpikn5L0vCiKHibpZZJui+P4oZJuO/FYkp4i6aEnfm6U9KYzGYirITzixNIFK/x2WaFv1eYRnaTAf6cbU1HhGsex5ufntby8HHrEONhSWUrkLSW5c1eoOKWSBnr+n05m+m5JvI458DxEeqUQxzvtkdNzxpy6mocxo0tPz7m/3itpGZfnF5y3596wCuB6isWiDh8+rMOHD4cxUSXsTkdKrtLcydNZU9px6syhK6nSc+CO7RS2L5/tC20rKythD99T2Sc+8Qn91m/91kWTDLxY7Bvf+IaYLpQVAAAZrklEQVT+63/9r6cMICZppwX3OI7vieP4Syf+bkn6K0lXSrpe0jtPvOydkm448ff1kv4o3rbPS1qIouiK05wj/HagSUdrHpVhXszTaDQSfdRdbYFMD2UOQIVDqFQquvL/b+9qY+O60vLzxhPHk9iundZJ06SlIC1qS3+wVbVqxYoffAhUqVqQ+gN+sJVADRJUYlX+BLY/qJAqQCUoKJSq2yAt6sIqUiJti0il3S0VRaINJS1JP7ROuiAljTdpa9ffY9fjw4+5z5nnvr7jj93YdzxzHsma8Z2Ze885c+d53/O873nPwYMxI4bZLfysBlBVEtAFUj7dUTNnPNGrHKElCdgn9US99w/kJRGej8dV7uCMRWUttpkBTTUebDfbwXOSzDkO+poSK4AYmOY1enp6cODAAQwMDMQALWdRnohVkuMsTMsKs118zWdFqXHQwHKL+27T7+2twBtvvIGzZ8+2fH18fBxHjx5NUswm4amnnmrLLJoNae5mdieALwJ4E8D+EMJY9tKPAOzPnh8EcFk+diU7ttp5G42RLAd63kVBMyC/6IlkwI2tSSCaM29mcSk/SaCnpycSEYl99+7dsXwA30OCBJqbUvM8cSAl3XA1b539JVn6fUbVM1ZpgaTNG0glHdX+eX69vmaTUOvWGYmOkbZXz6EGirMNSl5qAPl9zczMxBkJZZ1Dhw7FAC+/Az82GtjVeIIfOx7z7VfHQMdkLWzWvV02xsfH8cgjj2y70rvbCfPz83j88cfxwgsvlN2UHNZN7mbWD+AUgK+FEKb0tdBg1w3NS8zssJm9ZWZvccqtOc36IwXym1QQJHgNmDI/Xeu5aK67arQk55GRkVj8y5Mb5QUNgqqsIv0pDKh6Uuf5NUdeFy7RsDEbRmcqXrf3W+gpAQPISS+UYphiSNJnkFVlF39etlmlMx0P9ktTQxkP6OnpiUXVBgcHsW/fvlhgTY2PT//UseD94ceZhlBlIZ8G62M2Le7FTbu3N/K5nwTvv/9+4fHXX38dr7322lY1o2uxtLSEJ554Aq+++mrZTYlYF7mb2U40bv5vhRBOZ4evcUqaPV7Pjn8E4Hb5+KHsWA4hhOdDCPeHEO6nVEJi4o9TA2yaDijnyBUJA4CJiYkoy2idmRBCrK9OAiDh33rrrejv7487MFWr1RUrN1Vq0RWl9PKzcYieO71IJWPV2b22ztd9EFVXaepzbp5B8qJBYFle3R5PDSXPozMHVrD0deS9N00jpzq8ZjixfT4GoWN5yy23YGhoKLaNbfLyE2cZKlHp9w6sJG6NMajBXA2bfW+v2YAbhOPHj6+QBV555RU89thjbakHdyLm5ubwzDPPYGJiInf87NmzePvtt7e8PevJljEAJwB8EEI4Ki+9BODR7PmjAL4jx7+aZRY8AGBSpritrhE9c80M8amPACJZ6w9Xp+1Xr17FwsICZmdno0SjgUdqwTt37kS9Xsf+/fsxODgYUwRJ1gwG0gvWPHM/5fdGwHvr+qjSjdfQOXPRGQLJjzMSGj32m+OhkhYJkXVegOaiKxIqCZ591hW2HO9WqZ5sL8dd4wc7djTru7Bvupq3Wq1iZGQEvb29sZ3Ly41KnEBzMZMaOUo8KscQOhbaNt4raqwK7rtNv7fLwsLCAg4fPoyPP/647KZ0Fc6cOYNjx47ljo2NjeH69estPrF5WI/n/gsAfgfAL5nZO9nfQwD+AsCvmtlFAL+S/Q8A/wrghwAuAfgGgD9Y6wKqqfN/IL+K0pOmBtDUCCwuLsYCVfQkuUEH9W1+vlqtYu/evbnSACQhJTrVwlX7JzlqwFf7QALkcz8L0IwP3ZGIfzyuXjyhbQDytWNUVgKa1R1VYlFNm5/h5uBFxK1tV/mJn9XNTJheqqmhNC59fX0YHBzEyMhIbpyo1+uMgAZlcnIy9tPLcnpf6Lj5GV1Z9/ZWYX5+Hh9++GH8/9ixY7h69WqJLepeHD9+HFeuXAHQuP/ee++9Utqx5grVEMJ/AGg1v/3lgvcHAH/44zTGp/gpCSlZZtfJySH04BYWFjA1NYWbbropbrNGzZYZMzzv8PBw1Jy1qiOAQj1bV23SA/cEo5/XdlOyAZq5+eyPBjPZDyVr6vJq0PT9XvvWttATJuGp/KNyCMcRQCzLQPBzmjOugU4vj4QQoqFU47Nr165oiIeHh2PpB0LlN55Hg6/ea1dDyraxTzqbaIWtvLc3G9euXcPJkyfx5JNPYmxsDCdOnGi77I1uwfj4OJ599lk8/fTTqNfreO6550ppR9usUFVtXf9X3doTuhIDf/i1Wg3j4+NRdy7Sgum99/f3R2+SgVYziwFGn5miJL5aFowGWikHaVkAbT8NB69Do6EGQT1goGkE1fgByBE4r+2zaPSaWm6B56Vx4KpcT7T0sr327hc4aRE1vsb3VyoVDAwMYHh4OEpRlUolGiIuytKAOaEyGZDf3Fu9+yKj0w0IIeDkyZNtu7CmGxBCwKlTp3Dx4sUVcuZWoi1qyxBKOoSSIZD/MasB4OeB5uYPlDVCCHGrN5LO4OBgDCYqKXlPVvV/esrq1ascoP+TRFVuIBmrtKTkDuSJm9ciOSqhcZx4Xl2QpJUbadhaGUP2jZKKvs6NSzTArQuGVI9nf3hd9ru3tzfmqHOmwzayxjuAuP+szjhCCLEOv86iaKQpKalx0vesprd3IkZHR/Hyyy/jyJEjXdXvdsTo6ChOnz6NSqWCsbFywjJtQ+7+h0oiIXnwx+5/wHyuJKs7A5FMarVa3KeTKY/04L2OrJq46ukAImnxc57YNUbgM2K0bzw/4VM9vfxBOYPPtc9FVSPVQ1cjqHKOShy60tOneJJg1SgByMlMmuXEsVX9Xmcd/NNcew0O62yBK151LNUb0n7omC8vL0cpq1vw4osv4ty5c7ldrhLKw/Hjx/Hwww+XJo+1DbkDeULnH/VyJVld5KQERSK7fv16jtw5uPRQqfd6z5OeJj1hXazD6+t19JgndpVRgJVL/PkZ9Yr1GD/PQGURyWsGD8ePWUBsp6YxKgnz/EqUGudQzbqvry83C+KY8v1a5AxoxjY4dmyT1+7Z3r6+vjhmDIYzIM6NU1Tv19mRynk65rpquFtQZvAuYSWuXLlSmt4OtBG5F+mmmvHgUyUpOfgfON/HejHUcPv7+zE3N4fh4eEVgVp+RjeE1kwWJWuVWADkSJD/U9ohASnZFnmdq8kIPKYVLHkOXSnLfvD9lDJ0D1IaL2+s2B+t1AggJ0NxSzvN7FG5BGgWJuvr68uljfIalUplxbZ4O3fuxJ49e+L6AU2BXF5ejsZd4wpe3iLUyKl8lJBQFsqUx9qG3IGVA6FkR89PvXfN/ND/zSwGU5kpoucmAVOWIZn77BFeR7V4DX4qIevMQomT1yPher29SAv3Bk7HgRKGxhS0vfycGg32Vw2YyhUkS61xr33wGTl6XjU6JPaBgYHYP511+OtSmtm9e3euOBhlOJK7GlBtA//nuNIIcoz8956Q0E1omzmrErNmcPB/PvfZNEVyRggBExMT0QOs1+uYnZ3F8vJyDOAxVY+EU2QoNMPG69CqL6uerN6ietnaFyU4rwmrpqyevZ6TujL74MsHaOkD3X2J5+CG1br3qc/SYdt4HqYkAlghw3BGwN2YvMbP9/haPCR2AHGhlm4ewmM6jn5cOCZqXP2YJSR0I9rCc+cP1nvfJEO/lF09WQ3YqSY9OTkZjQSJgqVomTeuAVWvdauWDeR1dpVkigKX2i96/0WBPd8HIJ9Bo7MI1dK1PT6XW8fJp2Xy/Lo4SyUdrmbVfun3o/1jETa+f8eOZpEw7Tev9fnnn6NSqcSVthrQpsEKIcRYCStBfvbZZ7n+KnwwWeUa5tQngk/oVrSF567kqoTnvV49zuc+aMnj9AJZeGphYSGSCA3A0tJSJCSf2aIld1Vn9zIKsHLHH6/l68xDPXB97r18ShoqtWiffYzCGwMgX75BM1F0ZqBlB7SqI1/XAmv8rFbVpMe/a9eumIXkv1PfPh+v8LtnccZUr9cxMzOzIh7hYxTem+efVvNMSOg2tI3nro+EZnToH4C4rZt6s/ojn52dxfz8fG6aT6+wWq3GwltaQ0YJS4O1QD5VUz1rJVrffg1kalCUfSvyjnktn82ihkkzT3ic5E2CplHTQLR61Go0KN3oLEmNgdfa9doMtmqtfPaPRsUbZt9vau3cW5XtpSTjx5SfM7M4U9B9Vfm6/p+Q0G1oC3IHsIJwSB70FH1GjP/RazpjCI16JNPT0xgYGIhGwC+I0ZRKALmAItvhvUJNyStqt2a0FHmv2i9g5RaD6s3r4qN6vR7TNPk5oJnRosStsQZ9L8+rGUdsBwOf+jkvFWkfeS2uVuUiJI0p8FHHUQPBzKAxa6RA0girMdbPsy9F0peuJvaE7u+VhIRuQNuQu+ZkAys3y/Z57aq1+iAa38+VqqwOWa/XMTk5GbM5VHaoVqs5r1K9Quaas11Afms4Pioh8736uuaYK+F44iI5cfGOzhJ0vDQO4AlPpSefmcPzaLqkbiOobdJZhK4K5bV1kw4lbZWZmObIdmtbdRUtZyQ0ANw6Tq/rZTo1+JpF1Wo2lZDQLWgbclfJhUSkP1T94Ra9X0mR0sonn3yCQ4cO5TxCTan0HqqXSnh+XRmpxKbaeivvsihYyuN6bf95ACtIXT1iX6VSx03Hq0ha4XvVWNAo6U5SWqSM8guNsLZRs4B0tuKlNL6ffTBrrH7lrEG/n8XFRUxMTBRmQ/nvQKFjwTTRFFRN6Ea0DbmTQIB8ASyVKvR/ZmCoPKE6+Y4dO/Dpp5+iVqvFhTv05qenpzE8PIyJiYnctJ4eInO+tQ18ncSnHr6SNlBcltbPMpSoVabRczLFUGu5qG7P5fV+VqBtZMljNTC+CqTPRDHLl0f2ho2FzDQQynNrH2hgOPNRHVz3YdVFSyrreMOl8hfHjPVvtB1+39qEhG5E29z5/LHqwpOirJAij5ePXp5ZWlqKee0LCwuo1WrxGNPl9PpAfl9UHi8qTOVnDSopqKeq8Ho7P19kwADEOvNaY17HQYOjXrLwufA87q/jZww63j63v16vxwwkXcXrA6R8rx5nBoyej2WA+d0AzRlZrVbDzMxMPOZnRXpun+mk41vk3SckdAPaityLnvs8cU3FUwLSjBAAMUin+e5KxLVaLXq+WjdFA3KeGNTL1kdvcIr64QlfA8BextAAMr3woiwbkrWOjcpT6sWzPa1I3cMHYdXIqWGjXq7n8nKXfjccYwaIff0ffm52dhazs7OFY6t90rRJvqb3gZ43IaGb0DayjAYBSRC6C5ESCuUb7jDkA5dA80fO7fbocYYQYoqkbiBByUM9UkoYRd6uD94pybOdfPRSi7aTz/U4/5SU+ajEpQFoNXjaf8oz1NBVgvGkrkFL9eA19sDAKM/J8zDt0s9ulLx9yQZuos01CPxOOUMoWn+gRk0NhRpIykbJY0/oZrQNuQN52QBoerVe2yUB84fNzxJKwFNTU5EsmOdOQ7J79+6cMfEykJKgr0qoOrMnHH2fHi8yBBow9NkwXsZQ759ZQCRcLQamRkDz8rU//vxKytouHVMAOS3fS2N8zhmEn12QjGmg+b1qwTAag+np6RXSk6ZP+u/aj32REU1I6Ca0jSyjREi08oaB5tRcf9hKlECDiMbHx+PiGC0lOzMzk/PSaURUvtG28VHJU+UiH/wtIlrfD98/TW3U9/E6fC+lkKL0QRo7PtLTNivew1WzbpQcta0qs2hqpcpdmt+v5/FjREPJgDXLEWh++9LSEsbHx3MzOf0udDbnpS++l5kyaYVqQreibcgdKK55rouOvAesOdVFREnJhh47PcQQQtxIW8mN5K4kqZq+asckUxKWT69U4lGi09d9YJXXK5oZeI9a5Q1vYJhWqO/Rc3iDo/XVtX/aR72OJ3ef9cLvQrNdzCwaGhoYriPgObkiVUsP63erlSG98fCzEz+uCQndhrYhdyUxJRP11FRfBpCTSoq8Tp6TUgy9Xc3I0CX6JBX18tVDV++4VX65XpcoklTWki+AfJVJtp/no/fL95HYfPlflTW0rV5GKkqHLDIMbD+hr2v7fTaRGh0WEGPsg+Os3xOlG8ZFirR8yjxskyd6H6hNSOgmrEnuZna7mf2bmb1vZu+Z2R9lx//MzD4ys3eyv4fkM39iZpfM7Adm9mvraYh6ocxfVxkCyHtpGvwrIsisHQihsVUbyZrL2nkd3elJiZvEwEclOJVuiiQK/q8BRW941ICp3qySCclbC2BRc2axrj179sRUSZI8iZ+rR/VabAfHyZNw0XM/Jp7MdUMQ9oPHdNbkN/uYnZ2NBpf13PkZDcCq0VXDVJT+qX3SgHOZ93ZCQhlYT0B1CcAfhxDOmdkAgP82s+9mr/1NCOEZfbOZ3QPgtwD8HIDbAHzPzH42hNDShfLenXqA6oXpD1rJnMTs5Rm+Pj09HX/0SjqUBai906goSfC6zDRRQtFHrfFCcvErS4tkEiUsHiM566IqLmjSHHNP6LpwhwFIesAkVB949PKRyileylGi9Kml/txqHL1RqNeb9fX1+2bf5ubmsLi4mCtNzLGkAdTv3LeP5/V1gMq4txMSysKa5B5CGAMwlj2fNrMPABxc5SNfAfDtEMICgP81s0sAvgTgP1e7jhKyD4xqQE+JUqUQha7WpPyi3qR68PPz8+jr60Nvb2/OCwcQV2iqrKGzBBmjeE0lOp1d6HnUs/eeKM/HDB8aNq7o9Dq3Giw1VlqmF2h6sV4u8m1WGUOvof32MygaAzWKfv0BZ0o9PT1x0RLJ2ae80tvnalhtt/7vvwMaRnUAVguobtW9nZBQBjakuZvZnQC+CODN7NDjZnbezP7BzIazYwcBXJaPXcHqP5j4A/c78JAQVNrwAbsiTVgNhaYX8nz8W1pawvT0dG6LN2ryQF6q8bVpfKBTN4/W17yhcuMZCdYHUjkmCwsLmJubQ61Wi9fX8yuhaVvn5+cxNzcXqy16Y+hnN0qCfkyLvHEgv/WhSlwcD5XT1LCSvHku5rvrLInjzzaqseLYsH1K5r6ta0kz8l3ciU24txMSysK689zNrB/AKQBfCyFMmdnfA/hzACF7/GsAv7uB8x0GcJj/X7hwoaUnDjSXmIcQ4sYQXs5R2YQERG9xdHQUfX19qFarqFarsXZKb28vhoaG0NPTE6UAXerf09ODwcFB3HbbbfHcd911FwYHB1GpVCJ5avCTkkjRJh5eBgHy2R8kJ+4dSlJWj7So7ICOGw2XD9D6Rz2/BkkB5DxpPb9KITob4Pv5uurxmqVUqVTi5uWa0qnG3deFYZ9VjuJn2VadPXkjVmRY3b24qfd2QkIZWBe5m9lONG7+b4UQTgNACOGavP4NAP+S/fsRgNvl44eyYzmEEJ4H8Hz2+eDJxYMeHtCoEzM1NbWepgMApqamcPny5bXf2AK7du3CwMAAgAbR7Nu3D729vVGnJ8H5EgFKKnrMG7AiWUbH48EHH8Qdd9yBHTt24N5778XevXsBNDe3UF0ewIrVvd54+Jox2i7Vzc0MN998M/bs2QMAsc9K4lqLh5KK1sDxgdgiSUY3XeExGgeVrXgNwhsW/k/DWmT4PLbi3m558YSETcSa5G6NX9UJAB+EEI7K8QOZZgkAvwng3ez5SwD+ycyOohF0+gKAsze01VsMLpEnWGd8q3D+/PlNv0ZRoBgA7r77bhw4cAAhBAwNDcUiZLrgC1gZqPXrA/R9Rdk1JPilpSVMTk5iZmYGw8PDcVbFc6rhYltVYtK2M6jaCuneTuhk2Fp6pJl9GcDrAC4AoNv0pwB+G8DPozF1/T8Av88fhJl9HY1p7BIaU90za1xjGsAPfuxebD/cAuCTshuxRWiHvv5UCGHEH0z39qagHb7vrUI79LXw3gbWQe5bATN7K4Rwf9nt2Cp0U3+7qa9F6Lb+d1N/272vbbNCNSEhISHhxiGRe0JCQkIHol3I/fmyG7DF6Kb+dlNfi9Bt/e+m/rZ1X9tCc09ISEhIuLFoF889ISEhIeEGonRyN7Nft0aFvUtmdqTs9twIZEvWr5vZu3Jsr5l918wuZo/D2XEzs7/N+n/ezO4rr+Ubh7WurNiR/d0IOu3eTvf1Nuuvr8mxlX8AegB8COBnAPQC+B8A95TZphvUr18EcB+Ad+XYXwE4kj0/AuAvs+cPATgDwAA8AODNstu/wb4eAHBf9nwAwCiAezq1vxsYl467t9N9vb3u67I99y8BuBRC+GEIYRHAt9GovLetEUL4dwDj7vBXAHwze/5NAL8hx/8xNPAGgCEzO7A1Lf3JEUIYCyGcy55PA2BlxY7s7wbQcfd2uq+3131dNrl3U5W9/aG5pP1HAPZnzztmDCxfWbHj+7sGuqWfHf89b9f7umxy70qExjyuo9KUzFVW1Nc6sb8JK9GJ3/N2vq/LJvd1VdnrEFzjNC17vJ4d3/ZjUFRZER3c33WiW/rZsd/zdr+vyyb3/wLwBTP7aTPrRWMLs5dKbtNm4SUAj2bPHwXwHTn+1Sza/gCASZn2tT1aVVZEh/Z3A+iWe7sjv+eOuK/LjuiiEWUeRSOz4Otlt+cG9emf0di+7XM0tLffA3AzgO8DuAjgewD2Zu81AH+X9f8CgPvLbv8G+/plNKam5wG8k/091Kn93eDYdNS9ne7r7XVfpxWqCQkJCR2IsmWZhISEhIRNQCL3hISEhA5EIveEhISEDkQi94SEhIQORCL3hISEhA5EIveEhISEDkQi94SEhIQORCL3hISEhA7E/wPCbXqSpt2V3gAAAABJRU5ErkJggg==\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rmbvBqVeWh18"
      },
      "source": [
        "## M-Net 모델 정의"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oLVmgCbuI2Vy"
      },
      "source": [
        "# from tensorflow.keras import Model\n",
        "# from tensorflow.keras.layers import Input, Conv2D, BatchNormalization, MaxPooling2D, Conv2DTranspose, concatenate\n",
        "# from tensorflow.keras import backend as keras\n",
        "# from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
        "# from tensorflow.keras.callbacks import ModelCheckpoint, LearningRateScheduler\n",
        "\n",
        "# def unet(input_size=(256,256,3)):\n",
        "#     inputs = Input(input_size)\n",
        "    \n",
        "#     conv1 = Conv2D(32, (3, 3), activation='relu', padding='same')(inputs)\n",
        "#     conv1 = BatchNormalization()(conv1)\n",
        "#     conv1 = Conv2D(32, (3, 3), activation='relu', padding='same')(conv1)\n",
        "#     conv1 = BatchNormalization()(conv1)\n",
        "#     pool1 = MaxPooling2D(pool_size=(2, 2))(conv1)\n",
        "\n",
        "#     conv2 = Conv2D(64, (3, 3), activation='relu', padding='same')(pool1)\n",
        "#     conv2 = BatchNormalization()(conv2)\n",
        "#     conv2 = Conv2D(64, (3, 3), activation='relu', padding='same')(conv2)\n",
        "#     conv2 = BatchNormalization()(conv2)\n",
        "#     pool2 = MaxPooling2D(pool_size=(2, 2))(conv2)\n",
        "\n",
        "#     conv3 = Conv2D(128, (3, 3), activation='relu', padding='same')(pool2)\n",
        "#     conv3 = BatchNormalization()(conv3)\n",
        "#     conv3 = Conv2D(128, (3, 3), activation='relu', padding='same')(conv3)\n",
        "#     conv3 = BatchNormalization()(conv3)\n",
        "#     pool3 = MaxPooling2D(pool_size=(2, 2))(conv3)\n",
        "\n",
        "#     conv4 = Conv2D(256, (3, 3), activation='relu', padding='same')(pool3)\n",
        "#     conv4 = BatchNormalization()(conv4)\n",
        "#     conv4 = Conv2D(256, (3, 3), activation='relu', padding='same')(conv4)\n",
        "#     conv4 = BatchNormalization()(conv4)\n",
        "#     pool4 = MaxPooling2D(pool_size=(2, 2))(conv4)\n",
        "\n",
        "#     conv5 = Conv2D(512, (3, 3), activation='relu', padding='same')(pool4)\n",
        "#     conv5 = BatchNormalization()(conv5)\n",
        "#     conv5 = Conv2D(512, (3, 3), activation='relu', padding='same')(conv5)\n",
        "#     conv5 = BatchNormalization()(conv5)\n",
        "    \n",
        "#     up = Conv2DTranspose(256, (2, 2), strides=(2, 2), padding='same')(conv5)\n",
        "#     up6 = concatenate([up, conv4], axis=3)\n",
        "#     conv6 = Conv2D(256, (3, 3), activation='relu', padding='same')(up6)\n",
        "#     conv6 = BatchNormalization()(conv6)\n",
        "#     conv6 = Conv2D(256, (3, 3), activation='relu', padding='same')(conv6)\n",
        "#     conv6 = BatchNormalization()(conv6)\n",
        "    \n",
        "#     up = Conv2DTranspose(128, (2, 2), strides=(2, 2), padding='same')(conv6)\n",
        "#     up7 = concatenate([up, conv3], axis=3)\n",
        "#     conv7 = Conv2D(128, (3, 3), activation='relu', padding='same')(up7)\n",
        "#     conv7 = BatchNormalization()(conv7)\n",
        "#     conv7 = Conv2D(128, (3, 3), activation='relu', padding='same')(conv7)\n",
        "#     conv7 = BatchNormalization()(conv7)\n",
        "    \n",
        "#     up = Conv2DTranspose(64, (2, 2), strides=(2, 2), padding='same')(conv7)\n",
        "#     up8 = concatenate([up, conv2], axis=3)\n",
        "#     conv8 = Conv2D(64, (3, 3), activation='relu', padding='same')(up8)\n",
        "#     conv8 = BatchNormalization()(conv8)\n",
        "#     conv8 = Conv2D(64, (3, 3), activation='relu', padding='same')(conv8)\n",
        "#     conv8 = BatchNormalization()(conv8)\n",
        "    \n",
        "#     up = Conv2DTranspose(32, (2, 2), strides=(2, 2), padding='same')(conv8)\n",
        "#     up9 = concatenate([up, conv1], axis=3)\n",
        "#     conv9 = Conv2D(32, (3, 3), activation='relu', padding='same')(up9)\n",
        "#     conv9 = BatchNormalization()(conv9)\n",
        "#     conv9 = Conv2D(32, (3, 3), activation='relu', padding='same')(conv9)\n",
        "#     conv9 = BatchNormalization()(conv9)\n",
        "\n",
        "#     conv10 = Conv2D(1, (1, 1), activation='sigmoid')(conv9)\n",
        "\n",
        "#     return Model(inputs=[inputs], outputs=[conv10])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mjhRLU5tcW09"
      },
      "source": [
        "copy from https://github.com/adigasu/FDPMNet/blob/master/test.py"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UT6fo6ZgcfxT"
      },
      "source": [
        "from tensorflow.keras import Model\n",
        "from tensorflow.keras.layers import Input, Conv2D, BatchNormalization, MaxPooling2D, Conv2DTranspose, concatenate\n",
        "from tensorflow.keras.layers import Activation, Dropout, UpSampling2D\n",
        "from tensorflow.keras import backend as keras\n",
        "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
        "from tensorflow.keras.callbacks import ModelCheckpoint, LearningRateScheduler\n",
        "\n",
        "\n",
        "def getFPDMNet(patchHeight, patchWidth, ipCh, outCh):\n",
        "\n",
        "    # Input\n",
        "    input1 = Input((patchHeight, patchWidth, ipCh))\n",
        "\n",
        "    # Encoder\n",
        "    conv1 = Conv2D(16, (3, 3), padding='same')(input1)\n",
        "    conv1 = BatchNormalization()(conv1)\n",
        "    conv1 = Activation('relu')(conv1)\n",
        "    conv1 = Dropout(0.2)(conv1)\n",
        "\n",
        "    conv1 = concatenate([input1, conv1], axis=-1)\n",
        "    conv1 = Conv2D(16, (3, 3), padding='same')(conv1)\n",
        "    conv1 = BatchNormalization()(conv1)\n",
        "    conv1 = Activation('relu')(conv1)\n",
        "    pool1 = MaxPooling2D(pool_size=(2, 2))(conv1)\n",
        "\n",
        "    #\n",
        "    input2 = MaxPooling2D(pool_size=(2, 2))(input1)\n",
        "    conv21 = concatenate([input2, pool1], axis=-1)\n",
        "\n",
        "    conv2 = Conv2D(32, (3, 3), padding='same')(conv21)\n",
        "    conv2 = BatchNormalization()(conv2)\n",
        "    conv2 = Activation('relu')(conv2)\n",
        "    conv2 = Dropout(0.2)(conv2)\n",
        "\n",
        "    conv2 = concatenate([conv21, conv2], axis=-1)\n",
        "    conv2 = Conv2D(32, (3, 3), padding='same')(conv2)\n",
        "    conv2 = BatchNormalization()(conv2)\n",
        "    conv2 = Activation('relu')(conv2)\n",
        "    pool2 = MaxPooling2D(pool_size=(2, 2))(conv2)\n",
        "\n",
        "    #\n",
        "    input3 = MaxPooling2D(pool_size=(2, 2))(input2)\n",
        "    conv31 = concatenate([input3, pool2], axis=-1)\n",
        "\n",
        "    conv3 = Conv2D(64, (3, 3), padding='same')(conv31)\n",
        "    conv3 = BatchNormalization()(conv3)\n",
        "    conv3 = Activation('relu')(conv3)\n",
        "    conv3 = Dropout(0.2)(conv3)\n",
        "    \n",
        "    conv3 = concatenate([conv31, conv3], axis=-1)\n",
        "    conv3 = Conv2D(64, (3, 3), padding='same')(conv3)\n",
        "    conv3 = BatchNormalization()(conv3)\n",
        "    conv3 = Activation('relu')(conv3)\n",
        "    pool3 = MaxPooling2D(pool_size=(2, 2))(conv3)\n",
        "\n",
        "    #\n",
        "    input4 = MaxPooling2D(pool_size=(2, 2))(input3)\n",
        "    conv41 = concatenate([input4, pool3], axis=-1)\n",
        "\n",
        "    conv4 = Conv2D(128, (3, 3), padding='same')(conv41)\n",
        "    conv4 = BatchNormalization()(conv4)\n",
        "    conv4 = Activation('relu')(conv4)\n",
        "    conv4 = Dropout(0.2)(conv4)\n",
        "    \n",
        "    conv4 = concatenate([conv41, conv4], axis=-1)\n",
        "    conv4 = Conv2D(128, (3, 3), padding='same')(conv4)\n",
        "    conv4 = BatchNormalization()(conv4)\n",
        "    conv4 = Activation('relu')(conv4)\n",
        "    conv4 = Dropout(0.2)(conv4)\n",
        "\n",
        "    conv4 = Conv2D(128, (3, 3), padding='same')(conv4)\n",
        "    conv4 = BatchNormalization()(conv4)\n",
        "    conv4 = Activation('relu')(conv4)\n",
        "\n",
        "    # Decoder\n",
        "    conv5 = UpSampling2D(size=(2, 2))(conv4)\n",
        "    conv51 = concatenate([conv3, conv5], axis=-1)\n",
        "\n",
        "    conv5 = Conv2D(64, (3, 3), padding='same')(conv51)\n",
        "    conv5 = BatchNormalization()(conv5)\n",
        "    conv5 = Activation('relu')(conv5)\n",
        "    conv5 = Dropout(0.2)(conv5)\n",
        "    \n",
        "    conv5 = concatenate([conv51, conv5], axis=-1)\n",
        "    conv5 = Conv2D(64, (3, 3), padding='same')(conv5)\n",
        "    conv5 = BatchNormalization()(conv5)\n",
        "    conv5 = Activation('relu')(conv5)\n",
        "\n",
        "    #\n",
        "    conv6 = UpSampling2D(size=(2, 2))(conv5)\n",
        "    conv61 = concatenate([conv2, conv6], axis=-1)\n",
        "\n",
        "    conv6 = Conv2D(32, (3, 3), padding='same')(conv61)\n",
        "    conv6 = BatchNormalization()(conv6)\n",
        "    conv6 = Activation('relu')(conv6)\n",
        "    conv6 = Dropout(0.2)(conv6)\n",
        "    \n",
        "    conv6 = concatenate([conv61, conv6], axis=-1)\n",
        "    conv6 = Conv2D(32, (3, 3), padding='same')(conv6)\n",
        "    conv6 = BatchNormalization()(conv6)\n",
        "    conv6 = Activation('relu')(conv6)\n",
        "\n",
        "    #\n",
        "    conv7 = UpSampling2D(size=(2, 2))(conv6)\n",
        "    conv71 = concatenate([conv1, conv7], axis=-1)\n",
        "\n",
        "    conv7 = Conv2D(16, (3, 3), padding='same')(conv71)\n",
        "    conv7 = BatchNormalization()(conv7)\n",
        "    conv7 = Activation('relu')(conv7)\n",
        "    conv7 = Dropout(0.2)(conv7)\n",
        "    \n",
        "    conv7 = concatenate([conv71, conv7], axis=-1)\n",
        "    conv7 = Conv2D(16, (3, 3), padding='same')(conv7)\n",
        "    conv7 = BatchNormalization()(conv7)\n",
        "    conv7 = Activation('relu')(conv7)\n",
        "\n",
        "    # Final\n",
        "    conv81 = UpSampling2D(size=(8, 8))(conv4)\n",
        "    conv82 = UpSampling2D(size=(4, 4))(conv5)\n",
        "    conv83 = UpSampling2D(size=(2, 2))(conv6)\n",
        "    conv8 = concatenate([conv81, conv82, conv83, conv7], axis=-1)\n",
        "    conv8 = Conv2D(outCh, (1, 1), activation='sigmoid')(conv8)\n",
        "\n",
        "    ############\n",
        "    model = Model(inputs=input1, outputs=conv8)\n",
        "\n",
        "    return model"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "raJk70zBWm7M"
      },
      "source": [
        "## 모델 컴파일과 학습"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gGlqId9BJkxm",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "29447c82-43c3-4c55-d163-dfeaa88cedf2"
      },
      "source": [
        "from tensorflow.keras import backend as K\n",
        "from tensorflow.keras.optimizers import SGD\n",
        "\n",
        "# 모델 생성\n",
        "# model = unet()\n",
        "model = getFPDMNet(256, 256, 3, 1)\n",
        "\n",
        "# 모델 컴파일\n",
        "# model.compile(loss=\"mse\", optimizer=\"SGD\", metrics=['accuracy'])\n",
        "\n",
        "lrate = 0.1\n",
        "decay_Rate = 1e-6\n",
        "def my_loss(y_true, y_pred):\n",
        "    l1_loss = K.mean(K.abs(y_pred - y_true))\n",
        "    return l1_loss \n",
        "\n",
        "sgd = SGD(lr=lrate, decay=decay_Rate, momentum=0.75, nesterov=True)\n",
        "model.compile(optimizer=sgd, loss=my_loss)\n",
        "\n",
        "# 학습\n",
        "hist = model.fit(train_x, train_y, validation_split=0.2, epochs=20, batch_size=8, verbose=1)\n"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/keras/optimizer_v2/gradient_descent.py:102: UserWarning: The `lr` argument is deprecated, use `learning_rate` instead.\n",
            "  super(SGD, self).__init__(name, **kwargs)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/20\n",
            "46/46 [==============================] - 18s 94ms/step - loss: 64.6409 - val_loss: 62.1932\n",
            "Epoch 2/20\n",
            "46/46 [==============================] - 3s 63ms/step - loss: 64.6007 - val_loss: 62.2740\n",
            "Epoch 3/20\n",
            "46/46 [==============================] - 3s 66ms/step - loss: 64.5909 - val_loss: 61.9760\n",
            "Epoch 4/20\n",
            "46/46 [==============================] - 3s 65ms/step - loss: 64.5861 - val_loss: 61.8101\n",
            "Epoch 5/20\n",
            "46/46 [==============================] - 3s 63ms/step - loss: 64.5830 - val_loss: 61.6795\n",
            "Epoch 6/20\n",
            "46/46 [==============================] - 3s 63ms/step - loss: 64.5810 - val_loss: 61.6738\n",
            "Epoch 7/20\n",
            "46/46 [==============================] - 3s 64ms/step - loss: 64.5796 - val_loss: 61.7157\n",
            "Epoch 8/20\n",
            "46/46 [==============================] - 3s 63ms/step - loss: 64.5786 - val_loss: 61.8136\n",
            "Epoch 9/20\n",
            "46/46 [==============================] - 3s 65ms/step - loss: 64.5787 - val_loss: 61.8163\n",
            "Epoch 10/20\n",
            "46/46 [==============================] - 3s 66ms/step - loss: 64.5773 - val_loss: 61.7196\n",
            "Epoch 11/20\n",
            "46/46 [==============================] - 3s 66ms/step - loss: 64.5775 - val_loss: 61.6617\n",
            "Epoch 12/20\n",
            "46/46 [==============================] - 3s 65ms/step - loss: 64.5767 - val_loss: 61.7085\n",
            "Epoch 13/20\n",
            "46/46 [==============================] - 3s 65ms/step - loss: 64.5762 - val_loss: 61.6128\n",
            "Epoch 14/20\n",
            "46/46 [==============================] - 3s 63ms/step - loss: 64.5767 - val_loss: 61.6437\n",
            "Epoch 15/20\n",
            "46/46 [==============================] - 3s 65ms/step - loss: 64.5756 - val_loss: 61.6113\n",
            "Epoch 16/20\n",
            "46/46 [==============================] - 3s 65ms/step - loss: 64.5759 - val_loss: 61.6145\n",
            "Epoch 17/20\n",
            "46/46 [==============================] - 3s 65ms/step - loss: 64.5755 - val_loss: 61.6313\n",
            "Epoch 18/20\n",
            "46/46 [==============================] - 3s 63ms/step - loss: 64.5749 - val_loss: 61.6357\n",
            "Epoch 19/20\n",
            "46/46 [==============================] - 3s 64ms/step - loss: 64.5749 - val_loss: 61.8654\n",
            "Epoch 20/20\n",
            "46/46 [==============================] - 3s 64ms/step - loss: 64.5751 - val_loss: 61.6154\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "pRvmJPY6UrSP"
      },
      "source": [
        "## 학습시 로스와 정확도 보기"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DrqmWivCUrSQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 265
        },
        "outputId": "52cbb0d9-3408-481f-ac7f-c904f22d3801"
      },
      "source": [
        "plt.plot(hist.history['loss'], 'y', label='train loss')\n",
        "plt.plot(hist.history['val_loss'], 'r', label='val loss')\n",
        "plt.show()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VPpiU7yhUrST"
      },
      "source": [
        "## 테스트 결과 보기"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kPiPkfxtWlfr"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "def plotPredictions(model, train_x, train_y, test_x, test_y):\n",
        "\n",
        "    ix = np.random.randint(0, len(train_x))\n",
        "\n",
        "    input_ = train_x[ix:ix+1]\n",
        "    mask_ = train_y[ix:ix+1]\n",
        "\n",
        "    preds_train = model.predict(input_)\n",
        "    preds_train_t = (preds_train > 0.5).astype(np.uint8)\n",
        "\n",
        "    plt.figure(figsize=(10,10))\n",
        "    plt.subplot(1,3,1)\n",
        "    plt.title(\"train_x\")\n",
        "    plt.axis('off')\n",
        "    plt.imshow(input_[0])\n",
        "    plt.subplot(1,3,2)\n",
        "    plt.title(\"train_y\")\n",
        "    plt.axis('off')\n",
        "    plt.imshow(mask_[0][:,:,0], 'gray')\n",
        "    plt.subplot(1,3,3)\n",
        "    ret = model.evaluate(input_, mask_)\n",
        "    plt.title(\"Prediction\")\n",
        "    plt.axis('off')\n",
        "    plt.imshow(preds_train_t[0][:,:,0], 'gray')\n",
        "    plt.show()\n",
        "\n",
        "    ix = np.random.randint(0, len(test_x))\n",
        "    input_ = test_x[ix:ix+1]\n",
        "    mask_ = test_y[ix:ix+1]\n",
        "    preds_test = model.predict(input_)\n",
        "    preds_test_t = (preds_test > 0.5).astype(np.uint8)\n",
        "    \n",
        "    plt.figure(figsize=(10,10))\n",
        "    plt.subplot(1,3,1)\n",
        "    plt.title(\"X_test\")\n",
        "    plt.axis('off')\n",
        "    plt.imshow(input_[0])\n",
        "    plt.subplot(1,3,2)\n",
        "    plt.title(\"test_y\")\n",
        "    plt.axis('off')\n",
        "    plt.imshow(mask_[0][:,:,0], 'gray')\n",
        "    plt.subplot(1,3,3)\n",
        "    ret = model.evaluate(input_, mask_)\n",
        "    plt.title(\"Prediction\")\n",
        "    plt.axis('off')\n",
        "    plt.imshow(preds_test_t[0][:,:,0], 'gray')\n",
        "    plt.show()"
      ],
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vl3OZ7I0UrSV",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        },
        "outputId": "3ffd63f4-5e25-4bdf-bbfb-0d110bcb5bb9"
      },
      "source": [
        "plotPredictions(model, train_x, train_y, test_x, test_y)"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1/1 [==============================] - 0s 23ms/step - loss: 83.2717\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1/1 [==============================] - 0s 24ms/step - loss: 47.5937\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BZdGFkq7loZs"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}