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{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Volume Dataset Analysis\n",
    "\n",
    "In this exercise you will be analyzing a DICOM dataset. This dataset is not as conveniently organized on the filesystem as some of the datasets we have seen in this lesson so far. Rather, this dataset looks like something that you are likely to get as a raw dump from a clinical data archive.  \n",
    "\n",
    "Your task is to use the skills you have acquired in this lesson to go through this dataset and answer (or provide your best quess to) the following questions:\n",
    "\n",
    "1. What imaging modality was used to produce this dataset?\n",
    "2. Data from how many patients does the dataset include?\n",
    "3. How many studies are in the dataset?\n",
    "4. What are the oldest and the most recent studies in the dataset?\n",
    "5. How many series are in the dataset?\n",
    "\n",
    "In addition, do the following tasks:\n",
    "\n",
    "6. List voxel dimensions of all 3D volumes (i.e. series) that the dataset contains as WxHxD\n",
    "7. The dataset contains two outliers. Can you find them? There is more than one way to find them. Type up why do you think these volumes are outliers and what approach you used.\n",
    "\n",
    "Lastly, I understand that you are not a radiologist quite yet, but as a *stretch goal*, do the following: \n",
    "\n",
    "* Load a few series into 3D slicer and tell what is the anatomy imaged in our dataset\n",
    "\n",
    "You can assume that this dataset is consistent with DICOM information model, i.e. all instances within series share common attributes of the series and all instances within study share common study attributes. In other words, you can expect that something like Series Description will be the same for all instances belonging to the same series and you can read this value from any one file of the series. You can also expect that all the slices in same series have equal resolution and are evenly spaced."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pydicom\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import os\n",
    "import shutil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let's use the same code as in the walkthrough to load data\n",
    "\n",
    "path = r\"data\"\n",
    "dirs = np.array([[(os.path.join(dp, f), pydicom.dcmread(os.path.join(dp, f), stop_before_pixels = True)) for f in files]\n",
    "                   for dp,_,files in os.walk(path) if len(files) != 0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How many directories?\n",
    "\n",
    "len(dirs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That's to be expected - we could've seen this from looking at file system. So, everything is lumped into one directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "864"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "instances = dirs[0]\n",
    "len(instances)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have 864 instances. Now let's calculate series:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "32"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series_uids = np.unique([inst[1].SeriesInstanceUID for inst in instances])\n",
    "len(series_uids)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have 32 series - that is our **answer to Question 5**  \n",
    "\n",
    "Now let's calculate studies:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "studies_uids = np.unique([inst[1].StudyInstanceUID for inst in instances])\n",
    "len(studies_uids)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have 10 studies - that is our **answer to Question 3**  \n",
    "\n",
    "How many patients? Let's print out all patientID tags to see if we could rely on these."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', '123456', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'OPA135179', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-003', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-004', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-005', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009', 'PGBM-009']\n"
     ]
    }
   ],
   "source": [
    "patient_ids = [inst[1].PatientID for inst in instances]\n",
    "print(patient_ids)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks like PatientID is set for all instances and it's different. Without having more data about how these images were collected we can most likely rely on Patient ID in distinguishing between different patients."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of patients: 6, patient IDs: ['123456' 'OPA135179' 'PGBM-003' 'PGBM-004' 'PGBM-005' 'PGBM-009']\n"
     ]
    }
   ],
   "source": [
    "patients_ids_uq = np.unique(patient_ids)\n",
    "print(f\"Number of patients: {len(patients_ids_uq)}, patient IDs: {patients_ids_uq}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have our **answer to Question 2** - there are 6 patients  \n",
    "\n",
    "Note that by looking at these patient IDs we see something odd in naming patterns. But let's pin that thought for now.\n",
    "\n",
    "Let's see what imaging modalities do we have?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create hash of all modalities for individual series\n",
    "\n",
    "series_uids_modality_map = {uid: s[1].Modality for uid in series_uids for s in instances if s[1].SeriesInstanceUID == uid }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'1.2.826.0.1.3680043.2.1125.1.45859137663006505718300393375464286': 'CT',\n",
       " '1.3.12.2.1107.5.2.33.37105.2015011616025092819028166.0.0.0': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.105521800202421035670670758706': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.108708982094690934070899838243': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.111299569371716382165219422799': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.131971402732874033229609248302': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.137802635701410656176169562528': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.148342356080268980546237840587': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.149455479236394071679725178532': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.158869091666854803918782490935': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.165843183220097757648432257390': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.167613564536106399232524912048': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.170099978014836890431312652906': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.201921745402287812448748810010': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.211130119213590294311880514408': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.214279913601315478068344395213': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.223133215495128411564518210326': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.231116285499203734317125269666': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.249332750522009823872986282200': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.250698293053013179878447218670': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.276770677201759689184680286476': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.283146136537679072065477030736': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.285581607999649001090869568979': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.290881399408626464415134513575': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.292260123189044684287428848596': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.293816446347585254079913156086': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.295423364175091911131452091831': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.338954569012020140657951382116': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.728364200801418237396977783812': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.732954519300668202085572772042': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.874630167789792163807785802052': 'MR',\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.951760044234185587156102946949': 'MR'}"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "series_uids_modality_map"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Interesting. So most of the data is MR and one series is CT. Let's visualize a few slices from that CT and a few random MR series:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "# First, load the pixel data - remember that we didn't load it for the sake of speed\n",
    "\n",
    "slices_ct = [pydicom.dcmread(inst[0]) for inst in instances \\\n",
    "             if inst[1].SeriesInstanceUID == \"1.2.826.0.1.3680043.2.1125.1.45859137663006505718300393375464286\"]\n",
    "\n",
    "slices_mr1 = [pydicom.dcmread(inst[0]) for inst in instances \\\n",
    "             if inst[1].SeriesInstanceUID == list(series_uids_modality_map.items())[4][0]]\n",
    "\n",
    "slices_mr2 = [pydicom.dcmread(inst[0]) for inst in instances \\\n",
    "             if inst[1].SeriesInstanceUID == list(series_uids_modality_map.items())[9][0]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1b47fa09dc8>"
      ]
     },
     "execution_count": 93,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(slices_ct[10].pixel_array, cmap=\"gray\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1b40551ba88>"
      ]
     },
     "execution_count": 95,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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HPe8kaHIUc9Jj0cjpcdqZZgxenJnnRt1j46wm9LIxChuSsME2Tr4tO5K/Talog35e449Go0gmk0gkEggGgzIOEqImkn6/j06ng1arJcFItvf2+XyIRqNIJBIIh8NoNptSkCWZTCIcDqNWq6HdbiMSiQxJy8FgIB6MbreLQCCAWq2GVqsFn8+HVquFVCqFUCgkKgX7ti1UPTbGUITDYfF8uK4r7zgYDNDv99FoNERlYR821fI4wWGqlaOYCPvQ5/T9XnUqzWePEgxeaEd/Q9v7Hce8/skiBlvTk2L7wCeZDJtqAZxMqrNxUZofX/82/9YS0ybVeG00GsXk5CTC4fBQoRQaYTVBUMoSXQSDQbRaLbRaraHn+f1+xGIxxONxsR2EQiEJVEomk9ja2kKtVpPx9no9dDoddDodIexQKCSoJRwOCxNgVma5XEa73QYA8WQEg0F0Op2HpKOOo0gmkzIe2jV4PxGL3+8XBFGv1x+aU6/vOErF09/IhmbM5vX99FjM735SgWDep593kupPHxVTAM4wYziO4EdxWNsCOYkeZ/ZrEqFtbKP6tCENfa0JpxlLwHgA4EhdMN+f1m2tOhBpRKNRdDodtNttgeihUAihUEjQRzabRTweR6/Xw97eHlzXRalUQqVSQTQaRSAQEOJnLIPruiLN2+02EokE6vU6arUaEokEfD4fJicnEQgE0G630el0hLgBCIPx+Xzw+/2Ix+OIRqMIhUIAMKS2sM4k/+/3+wiFQgiHw3BdF/F4HI1GA5VKZWg+ze9Ehmp+Hy9VgCqPFwow79X/e0l+8xpzzdiYzHGMxQvZmNeftp1ZxgDYJfBxTetc+piXJPDi5qMm2RyPrQKwHos5BvMccOhCnJycRCwWG+rLNNpRzydUJ2IgwQEQdUOjBcJxSmSfz4dms4nBYIBAICDl2jhGwnXGMAAQZuE4DtrtNlKpFBKJBPb391EsFmU88XgcjuMgEAgICmi1WqIecPw0dDL5Sn9vMr1+vy82B76T3+9HKBSSgjKVSkUMpPob2Obfi4BPgjK8znsRsfkdTypgzPNaNbQxl1FjO20704zBBtHYTP3Sxgz0uUeBk/q3rT+z2ZKizIWum+mCi0ajyGaziEQiQjyUkKbxUY+Xko05DK7rCsGQAeg5ILH1ej1hCGQClUoF5XJZUqx5Ph6Po16vo9lsSlQkUQQAkfb9fl+8EL1eD91uVyR8IpGQPAoSCNUIohnNjMzv4bqHrk/aP6jiuK6LZDKJWCyGRqOBcrk89L1tDMBEaSbjGPWtbWqL2WzP4zc3mRK/iVfzYhT6/5MwpdO0M80Y+NK2SjpmSi6bl4Q/DhaO0hfNRaMJnlD9uOfo8/pjBoNBqXlAog0EApiZmRGCaTabQxKRBET9ndKZyVD8odWeREj9PJfLiRTf29tDvV6X+ASiB7odw+GwSHXmS1CloLfAcRxUKhUxYkajUflG0WhUvhFVA74LPRysHanfj3NFoySjKweDAVqtljCJVquFQCAgHpR6vS5Cw5aWbkphvQ7MNWB+KzYGW3nFxng1L3XCXBvmGEcVsNUl9nU/j9vONGOw6YFstg+rz3lJfq/rzb+9YKYNWdg+ttdv3ScJKRQKSR+pVArpdFqiC2noo15OhMFGZKCJiRKWhr1QKIRGo4FutyuLmgTa6XSkbmMikQAA8VYQUVCvN9+dzwiHw0KkADA5OYmZmRk0Gg0Ah25LqgXsg54UMgieI9PT6EZ7OajapFIp9Pv9oeCqWCwGx3HEZUrmQNVKf0syKtu3P4nqauZenFRA6fOjbA62dWhDQVrF4Ld9FNXbq51ZxnAcQXtxRvPj6snU93lJCy84aUohL5hpjtX2LPYViUSkr0QigXw+L8QKQCQsC6+SSZAQ+EMiIsHQHRkOh6VeYzQaxdjYGFKpFH75y1/i5s2bAI5yJWjwLJVKwkDIHFi9iQyKqgJdmmNjY6JqhEIhqQnJeIlGoyHh1M1mU9QBvqOeaxIyGYa+hu/Lc8FgENlsFq1WC+12W5BFtVpFqVQaKvhiegy0wNGQ3gbfNTEeR7D6G5v9jZLkJ1mTmmHYrrWpUadtZ5YxeBGo+QHMCbERoU2PM681+yQR6EVjRtqRIPXH0H156YhaGieTSYyPj0sUYrfbFfVAL2DWRKAUZfwA4wto/R8MBuh2u0Ol3wn9yWjIJEhQsVgMsVgMrVZL1JF0Oo1UKjU0ZhIq+6RBkeoCEQQjIxuNBtLpNOLxuDA04FB96vf7UvSF6EFXiHJdV9yeAAQBUC2i+kTjazAYxMHBgZSm6/f7ghy0Dcb8TiaTsIVm24SQDXHaok71NxiFNkcJOlsftjaqMtajtjPLGGwMwGvivCbLdtzGQI6bfJuk0IvBfBYXmIaw7IMLPxgMYnp6GplMRuwBlLjAEUynWsCaCFq1MC3degzaUKhVil6vh6mpKcTjcWxsbGB7e1uMm/v7+6hUKgiFQkgkEhgMBjg4OJDAJkrtwWAg6g8JE4DER/R6PUSjUeTzeczPzw8FTpFYw+GwBGWRAbRaLZkzvcjJ8LRKwd9kCplMZigqc25uDsViEcViUeZNf2vzu2q1gteMcnPq+X6UY/pbHae2Hodk9Xr1QimnbccyBsdx/gOA3wGw67ru0w+O5QD8XwAWAKwA+D3XdYvO4aj/FwBfAdAA8K9d1/35aQc3ChLZ9DrbOa8wXPNjm7/ND2x+BP0sPVbte9cSFoB4Ha5evYpMJoN2u41MJiOJTM1mU4ilXq/LgjZ1Zs1EGPRDSUqY7ziHLsVCoSCeCr/fj2g0ing8jkwmg0gkIkFN1NdTqRQuXLiASCSCYrEIAGK4BI52qWLgUb/fR71eR6fTES8KAExNTWF5eVnGmkgkJDiq2+2i3W4LEQMQ+wTfUaM0VqPWKI2NjM/v92N+fl6QTL/fx/T0NIrFIjY2NnBwcDAUD2KuB64TM8/AC+Lr9WUy5FHCyiRsPlv3fRxhezEAMuqPgjGcJO36fwfwz41jfwzgB67rLgP4wYP/AeC3ASw/+PkWgH9/2oF5SXAbl9XXazior7PVMjhOEhDC66Z1Yj7LhKbm39T/fT4frl69iunpaQwGA6RSKYyPjwvDIEOo1+tDNgTTtcd3YZ4EFyj1dhrzCM1JsKlUCrlcDqlUCpOTk3jiiSfEPclQ5LGxMfj9flFV6Jqk9Z8tHo/D7/ej0+lIoRdtBMzn85ibm8PY2JjMYywWQyQSkTnlOLXblePm3DGak2MhOiGzJFOMRCKSHDY5OYmFhQUkk0nE43E88cQTmJiYEKZlW1v6O9rWjqm2aobgJdm9BJfXuvVSPc31pI/pv0epJI/ajmUMruv+HYAD4/DXAHz3wd/fBfAv1PH/6B62/wog4zjO9GkGZuPaNk5oRv6xmS4em56niViHG5sf3Ww2js3+TIlDG0A8HsfTTz8txVCWlpYwMzMjNgHq34TtlMh8FxoD9fux8TqGNlOiU4WIx+NIJpNIpVIIh8NIJpOYnp7GzMwMYrEYarUaisWinCdxEh3UajVUKhWEw+GhsTLegUxjMBigWCzCdV2xT4TDYczOzmJqakq8BlQB9Ni9ILMOrybzCgaDUhCGiKrdbou9ZmxsDFevXsUnP/lJMXouLS1henpa7DdeTTMDvR5szYYezTXB3+b76Xv09Sbatd3Da8mwTKFnopjTtNPaGKZc1916MJgtx3EmHxyfBbCmrlt/cGzL7MBxnG/hEFVYGwnqwTPk5bWxz5aYY2MA+j7btWpMD8Ex/aFsQSr645kwURPGZz/7WZGIV65cQTAYRKFQQCwWE5SgmclgMEA8Hhcjng4Q4nW0VxBKUyICEOYSiUTwxBNPYH5+XlSTeDyOfr+PWq2GXq+HRqMBn8+H8fFxmfNqtYpIJIJoNCqBS4y5IIJIJpOIRCLY2NgQdYQIIBgMIp1OD+n9jI/Q2aChUEhiJqgKET3oe/Xc830BSKwHoy79fj+y2SwAYGZmBp///OfxxhtvIBQK4dKlS4jFYtjc3ES5XB5iSrrQrW1t6TVk0/fNNaT7sKmo5prheVv/5rNMZGCqy/9QqsSjNBsrto7Sdd3vuK77vOu6z9vOm7qaCf81gxiFLDRUHBqocZ9NldB9mGMxpYH+iOTkmUwGly5dwm/8xm+g0+kIrCXB0lpPBhIOhwEcSlEGFjGZCIAY30yvhZYcDEqid0B7BXw+nxRRqdVqqNfrEvHYaDRkB2u/3z/kGiQhVqvVoXBqIoepqSmEQiHU63V5BomaP47jSKIV34cqQDwef2ieqWbwXUxmyNwP7cp0XVcCpjS6SCaTEg4+OzuLhYUFTE1NDQkeU+UkMzK/K9eeub5sa8GmYprX6qZRq9mPuf5NpmRDKo/TTosYdhzHmX6AFqYB7D44vg5gXl03B2DztIM7Tl+ySXyT058EwulnjeLW2gswKrPTdV3EYjEsLi7ipZdegt/vR7PZxOzsrEB0Gh8ZTARA3H/c2QmAEKnrukJQpuSkDYNExOMsxkLYzflpNBpwnMNiLHt7exLRSEZQrVaFaDudjmR5NhoNSbACIAgBgBg4GTBFAyORDOMxEomEBFJRLSETo0pCtEBmZxoj+Tc9JXpOer0etre3ZY/NtbU1pNNpTExMoFKpIBaLiTrXbDaF2ZnrgIzEtpZsvzVRm+vHXHPHrWuby1QLShvytaHVx2mnZQzfA/CHAP70we//oo7/O8dx/hOAzwIoU+V41GZ7YS4SE06Z0tML6pkcdxS3NfvW99jO6fsvXryIJ554Ai+99BLa7TZu3LiBTCaDe/fuYWtrC4PBQIyB1L1Zb4ChxrQ9aGREKcaFzAVJGE24H41GEQ6HkcvlMD4+jkQiIfC81WpJf4TUPp9PCsIGg0GR/OFwWNQCx3Gkf2ZO8tm1Wg2O42B8fBybm5vY3d1FqVTC7OwsWq2WBEL5fD7k83nxmtTrdQneoudBzzWZGZmfVj94HWs50BXLPS5+/OMfY3V1FbFYTIK+0uk0Op0OpqamsLi4iEAggO3tbaytrQkj5jyZQsYm9bXqp5mIzctgW0ej1roXajXXtOmutqHm07STuCv/TwBfBDDuOM46gP8JhwzhPzuO828BrAL4lw8u/z4OXZUf4tBd+W9OOzBbfIAXwXtxR3NyKJm9jDM2jmw2G0rRz0qn01heXsZzzz0Hv9+PlZUViQdg6HG1WhXXHWsvUJ+njj4YDCQUWZdYo6pApkHJTmKhrh4MBhGPxwWqVyoVNBoNWbTValU2piUBEoaHQiE0m020Wi2B+YTu9DzQ8Nfv9yXWIZFISBg0mYsO5mIEZiqVQr1el8AoZnnSIKnfjfNECa7fjzEUHD8zT+v1Ou7fvy8xGlxLTEmvVqvIZrO4du2aMLzNzU1xM5tIQa8PU3DYomG9Qq010Y5aZzZmYgo3m0rthXhP045lDK7r/iuPU//Mcq0L4NuPNaKjvh5CAye9x/zb/CBmM9EH72cz7R2masHj2WwWTz31FL70pS8hk8nghz/8oRjpCoWCLMKdnR10Oh1ks1lkMhlx+aXT6aHUZz6j2WwCwJCBjTCdKgSlKhlHLpfDxMSEVGzmM3w+HyqVCprNpoyJ/RQKBfT7fczMzMDn80lqtQ7NppE0k8mITk9EQvcpDZapVEqInoiBrk0aLml/oFcDgKgTGh1pFYmFaWwZqKxFWS6Xsby8jHw+j/fee0/QWTKZxMbGBn71q1/hxRdfxOc//3mJmqRR1Esl5XG9RvR1XmjTdJ+bTME85mUv8FqbZjOD607TznTkI/AwtzVVCy8VwiR2k7PaPrzJTEyu66Vj+nw+LC0t4atf/SpeeOEFlEolvPvuuygUCkin01LhaHt7G51OBxcvXpTAInoGEomE6NtcvHQXlkoltFot0dsBCGEyilAnWkUiEVy4cEG8DDTG+f1+iQa8e/cuNjY2ZHwsm8Z4CeBQcjMqkwyBng3GOnS7XUxPT6PX62Fra0vqSRSLRUEXrusOMad0Oi22DCILqhT8tvRQkAEyyUsbLP1+v2SKxuNxuK6LSqWC9fV1pNNpvPbaa7h27Rr+7M/+DDdv3kSn08Ef/MEf4MKFC3jzzTdx48YNfPnLX8anPvUpdDod3Lt3D7u7uw/Vz9TrzX25vNsAACAASURBVLY+NAIYpbaeRLjZGIf5DJM+bCjhccOjz/S+EjbOqv824ZqeJJsOp3VCE36ZFmHep20awLA6wntTqRRee+01vPbaa8jlcrhx4wbu37+PfD6PhYUFLC0tod1uY2dnBxMTE/j617+O3/zN38TY2Jjs9kQdnYlAuVxOCF7HNhAhEFYzNoA2i3g8jnw+j2QyKe/Agqzlclm8CYVCQfTqUqmEWq0mRkymgPOdaTClIRQ4stprNYdqCZnRwcEBHMcRVYDoIB6PS52GRCIhKILfg8ZIhofz/fQ7+v1+pNNpxGIxZDIZTE1NIRAI4ODgAHt7e2i32/jVr36F27dv48tf/jIWFhZw//59vPfeexgMBlhaWkK1WsWNGzcQi8XwxS9+EfPz86KamEKGiEyvLZNI2bShV6MKzVhsgXK25iWobEJMr8mP3cbwj9VMnck0+pmMQTcvI4+NC5uTa3J/cl5TQvDDxmIxvPzyy/ja174m3odarYZGo4FnnnkG4XBYFmQmk8GnPvUpPPfcc1hcXMTm5ibu3r0rknF8fFwqKRERMBQZAGKxGJrNprjidOATy6RNTU1JtCGTlarVqmRIttttFItFHBwcyP6ToVAI8Xhc6j0ymjCVSonnhMRI+wejGEulEprNJhKJBCYmJoQhAMDOzo7YPhg4RW9JrVbD2NiYIBBmgjKcmbYWqkI8TwYRCAQwPj6OZDIp2+Pdv39fjKljY2O4efMm3nvvPQnNjsVi2Nrawic/+Uk888wzuHHjBq5fv46pqSm89NJL6Pf7WFtbE6appa4tJkEzCs04tKS2ud3N9WzLyTDXsl6vWpiNWsuPo06cScZADqpDYzUX94oHNxmBzTrsxZlHNTOwiX71dDqNb3/723jttdcAAKurq3jjjTewu7uLz3zmM3jqqafw9ttv45e//CXq9ToWFxdRr9fxJ3/yJ6jVatjf35faCiROJhfF43Fsbm5ic3NT3kVHNOpkJhr0MpmMSPvBYIBqtSoZjJR6yWQSt27dkjoGNC42m01xW66trUnpdnpKaB/hd9nY2JAsT9pBqMdvbGxgb28Pe3t7GBsbEyMjA6uAw5DqarUqUZEkau60DRwaC2OxmLwrmUI8HsfFixcxPj6OXq8nMRm9Xg/1el1UL4aav/XWW5LL8eabb6LX6+Eb3/gGvvCFL+CHP/whfv7zn+PKlSv46le/iu3tbfzVX/2V7Jmhw7ZNwaGJ3gyQMteaXkOAt0fDtp5tzzPXu/bYnXad63YmGQPwsGFP/zYlOI972QT0/RoimzqZhn+6D/1sRiD2ej383u/9Hl599VVxNW5vb2NjYwOXLl3CCy+8gJ2dHdy7dw+VSgWtVgt3797Fzs4O9vb2MDk5iWw2i1KphA8//BChUAhXrlxBJBJBpVLB2NgYstksJicnsbq6KtGJVCuo0rDeAisdMUrS5/Ph4OBArP3tdlvcju12W+werVZLmAfdpuyPlZip3vC9yRwODg4kiIqWfUpax3FE8qZSKVFHGD/A/S1qtRoCgQCmpqZktyvHOQyGYhwG1RCGdY+Pj2N8fFx2xqKhcn19Hffv30coFMLc3JwYIxkvwe90//597O3t4fnnn8fu7i5WVlZw/fp1PPPMM3j11Vexvr6On/70p4KgbJLcXIte68W2Dr3sFLb+vZ6t7zGRxCg0fdJ2ZhkDMGz11boZz/F/m12B93ipEjZDpc24A0BgOHAUYPPFL34R3/zmN0XC//SnP8VPfvIT5PN5fOMb38DCwgK+//3vY3d3Fzs7O+j1etjd3YXrHhZlqVarKJfLCAQC2Nvbw/Xr15HP53H58mWxG8zNzWF2dhZLS0sisQFIPAJ1/kKhANd15Vi320WhUBApToL0+/3Y3NzExsYGYrEYksmk5BkkEglks1lxY7Ly8/j4OPb392UHKtc9rL/AKEyGbdP9mMvlJPdidXUVU1NTyOfzcBwHtVpN7A9k/KlUSpDM3NycfHN6SpiVyf/5/ff29sT46bouNjY2cPPmTaRSKWSz2aFYj+XlZWxubsqc7O/vIxAIYG5uDr/927+Nv//7v8dbb72FiYkJvPDCC/ijP/ojjI+P4y/+4i+G7AM26G5TT7X01vdpqW+uQVuz2Qt0FWvdp03VeRwGcWYZg0motrgGToqGcWy23AjdvOwNNgMkS5Bx0T7zzDP4/d//fZGepVIJd+7cQT6fx5e//GVMTk6K246GP0L5bDaLmZkZgdcHBweoVCrY3t7Gz372M0QiESwtLaHRaIgeTolPt6XrulIMpdvtiu2BxkR6OxjhSENfv9/H9vY2tra2JHqRzGV9fR2bm5tigKSRUxt1mbZNg+NgMBAbhU6jDofDUgiGTJHRjoyKdBxHEAkJn+OhTYGqFQ2CtC0wuIqMoVKp4Be/+AVarRamp6fl+9Ot6bouxsbGEIlEcPv2bSmf1+/3kcvl8LnPfQ4/+tGP8O677+LZZ59FPp/Hq6++itdff13qOdhQAQnfRKOmS9OMWjSFkbnezHOmKmuuZRtKeFwD5JlmDMBoayww/DHYtJVXGwptxH+crUIzJtd1kcvl8JWvfAWf/vSnZSfoW7duoV6v4wtf+AKee+452QSW1YtrtRrGx8dFmhGBhMNh5PN5BAKHuzrdvHlT9nC4dOkSSqUSfD6fVFmORCJS+q3dbqNSqaBarUooNA2LLIhSq9VEvWDdx/39fdmjMhKJyPg6nY4EA6VSKXl32hcc56iKM3VqGifL5TKAo0KynU4HtVoNzWYTsVgMu7u7cJzD4jSVSkUQA/MyIpGIpKIzjoBBWzpOg+iMRtlyuYxWq4X33nsP77//PnK5nGzIy2s4dqouS0tLskM3x5vP57G8vIwPP/wQOzs7mJ6exoULF/CZz3wGP/jBD4ZqVZpr0oTztvPmevNiBF5rXPepmYstCljf/08SMQDenNk8D2CI+M2PaKIHAEP96mO66q7uhx/hm9/8Jn7rt35LFu2Pf/xjvP322/jc5z6Hl19+GblcDru7u8IUstksZmdnpcAr7QP0KPT7fWQyGQAQH/zf/u3fwnEcLC0tAYAYzhzHkYQg6t8M5mGFJxrjisWi5F4wVoDp06xlwMQpGtnq9TqmpqaQyWSwv78vcQ2cB8ZQRCIRMe4xRZtBTsViEYPBQArZlkolrK6uCkOk3YGBXLlcDs1mExsbG1K0htWm6Ilg2DPdugzG6nQ6+Lu/+zv84he/EAZKYyi/D+0pFBxf+MIXcPnyZVG5MpkMut0uXnvtNbz++ut444038JWvfAXz8/P4nd/5HWxubuJXv/qVMDGbeqvXml5Leo3a1h/XrW09mvfr+8x1bj6XeSY6B+RR25lkDDaDjMlpbc30M+v+TM7spWaYkE8jkrm5Obz00kti/d/f38e9e/cQj8fxqU99SgJ9CHmr1Srm5uYkilDH+A8GR9WLqWNXq1W0Wi0cHBzg+vXrCIVCWF5eHtpBSu8ezUi9YDCIRqOBarWK7e1tVKvVob0sabRjmXjCdV1pynEcKeRClYQeC2aDkijq9ToKhQISiYTkTzAIijkefM9yuSzekW63i93d3aHEKNouYrGYvCOZleM4krpNz4TruhKuvbKyglu3bgEAcrnc0HyyVoReF7SBMGpSf+9AIIBr166JmlKtVvHkk0/ixRdfxK1btySc3MyJ8FJxbUjBC/l6MZFRjMe0V+h+bAlgj9rOJGPg5GhJr91FwMOuHNuH0c2cbNv15m/t/fD7/XjuuefEkEZDXigUwsWLF8UtVywWJTCnVqshk8mg3+8LnO50OkMcnZKLaKDVaqFSqWBlZUWCmFijkcyEBkNKz2aziUqlgkKhILUT2u22EATPkanw2boQDKMI+c4s/aYrOrNoayAQEIImcTBGgkTPd6IdhHtHHBwciIeD46GxFQAmJiakOC3rTrLsG5lZpVLB22+/jQ8++AB+vx+zs7OiKvEaVpJichn7IwKhEa/VaomqRo+MnoOXX34ZN27cwBtvvCHMic0MhOK6MqG8lu58ro15mOvbZjfT9KFpwzaWx2lnkjGYPl/AHvDEZvs4/O01uSfRx7QLc3l5GS+88ALq9boE+wQCAUxOTortgJKHJdS5nXw+n0coFEKhUEC9Xkcmk4HjOLLvIscVjUYxMTEBn++w3sGNGzewvr6OGzdu4JVXXsHy8rI8nzkXhORUDVgrsl6vi5RzHGcoXsHn8yGdTsN1XRQKBQCQ/S4Hg8OScywzx9gDxpTQAOnz+YTJMcrSrFxNRlapVCQuYHd3V0rJ8ZnBYBDVahWu60rQU7PZFHcriT4ej+PevXv4m7/5G2xubuLZZ5+VKM5gMIiVlRUEg0EUi0U8/fTTeOaZZ/DBBx/g3XffFbXlE5/4hBhPyVxZH/Lu3bvi5uX1MzMz+PrXv4433nhjaL3Y4L1N6Oj1C8BqKLcFQdkMkKbaYRo5+RzO/+O0MxkSPQr2ezEH/q/v4UTaGIwJ67zgnOseRhAuLS1hYWFBrN7r6+uIx+NIpVKIxWICUdlXtVoVd95gMEAulxPJtLi4iLGxMfF2EEIDkEi+2dlZ5PN5BINB/PznP8f3v/99fPDBB+j3+9jZ2YHrupKXQIs9d7rmu9BQWa/XpRhLq9VCqVRCuVxGr9dDMpkUgxztBDQgttttVKtVsfCTKQSDQUllJmphgpZWpahmEAUVi0XJDSHqotQm2qCHgvYMRm76/X588MEH+Mu//Et88MEHePbZZ3Hx4kUAkA1uAci9nU4HOzs72N7elqSyxcVF5HI5eW48HkcoFEK1WkUikRiqq1mv12V/joWFBVy8ePEhe5Sp3pKAzfV13JrT12h7mim0qH6Z57xUl8dpZ5IxAHYdzDYhwPFp1+Y9JsOw9aOfFY1GpRJSOp1GtVrFzs4OdnZ2UCqVhiQocAh5a7UacrkclpaWJJtwbm5OaiFqNML8BAYpMQ7B7/fj4sWLyOfz+PDDD/Hnf/7n2NnZQb/fl0xIlnNjzgAlBasxM+eAIdC0FTjOYbozg7IYu1CtVrG/v49SqYR2uy0oSFc7ajQasm0eGQKNfkQrALCwsICZmRl0u13xkpA5MfS53W6j0WgglUphenpaYiRIoHRv7u/v46//+q+xurqKJ554AouLi6hUKtjY2MCtW7dw9+5dBINBlEolsUm888472N3dRSaTkRBzorRkMinrgciHSVrZbFZSu3O5HKanp/H888+LysW1YoP7XuuWTa81bcfyup79aRSt14/u96NQIdjOJGMwX5i/TQ7JZuOOto+hP4CGaCYyMTk3pTh14VQqhWeffVaKg4yNjQ252fb397G3tyeL7Nq1a5iZmcH09DSuXbuGDz/8ELdu3RKjJOslMh4gHA7LDku0Yzz11FMIBAL47ne/i9dff13gNiF4JBLB1NQUwuGwEBNDmkl8OpNTMztGK1IdocuUfdA4SMLX+z90Oh3ZbVqXbHNdF7u7u5IL0mg0JN2cMRl6j4mJiQnZys51XVHX6vU63nnnHXzve99DKpXCK6+8gsuXL2NqagoTExNiZGWqN92Pd+/elQSpS5cuIZFIYH19HVtbW0JYhUJBalz4/X5MTU1JrYypqSkpq5dKpfDiiy9iYWFhqKq117qjZB9l1zLXpxnNaxK6Xrs6wMmM1B1FE4/SzqSNAXg4hlxzU1Pi21QKrRKwL1NNOO6ZbIlEAjMzM5icPKx5W6lU5DpmOlIKMqimXq/j/fffH9q2nolE1WpVyqcBR7s80YDHEu7b29sIBoO4dOkSrly5gmQyiR/+8Ie4d+8egsGghFCzJFoqlRICIbSmXYDBSCRqBkSxqrR2BwKQTWccxxnaIJfMgfETTByjW5MLl7YDIiGqTZTKvAY4TCFnhCYZJAAUCgX89Kc/RbVaxeTkJJ588klsbGyIkZEJbBsbG3j//fclboIBWowlGQwGKBQKsmUeGSGL0lCV014WFp1h7sbMzAzm5+dx586dh+wBtnXq9bcNUdhQB4/b1qpGELZ7Rq3xk7Yzyxi4SMw2Ci3Y1AwvYxH70r/19fpvRuDRBcmIOYY202c+GBxWXdrc3MTW1hay2SzC4TD29vbEv6+rH9XrdTFasloSGUQgcLjjNX3xDAL60pe+hHfffRc/+tGPcHBwgMuXLyOfz0tsRD6fx8bGhgQdacnCXAESBhkSpT5w5CGg9O90OhKWTAMYF2a9XpeiKvRCcB8Kx3EkMrHT6UhsQj6fFxsGbReZTEY8EJzze/fuYXV1Fd1uF0899RSuXLmCWq0mbtJkMik2l8997nPodDr4xS9+gWw2K3aVSqWC/f197O7uolKpYHl5Gc8//zy2t7fRbrfF/kNjXTweF2Ok9rgAhxWnl5eX8eabbwrT5fzqNaN/m540c43ZmIVXv+xT2xtsNgZzPZ+2nVnGYG4ppifCNuE2TgzY4xVsRiTddD+ue2gpZwFREh83aKUuqoOWtra2sLm5KXs4zMzMYG9vD7dv38b6+jp2dnaEGBhBSEJlNiEzDan7ktCy2SxeeeUV+Hw+vP322/jBD36Aq1evYnl5GfF4HFNTU7hy5Qo6nQ5KpZJITnoZSAhkDowS1AVjqUczFJvHmIvBeTD3hKD3goyDAUHMEKUrkipNIBCQKENmR7bbbdy5cwcbGxuYnZ3F7/7u7yIcDqNSqaDb7WJmZgb379/Hj370I9RqNXz44YeS+k3vSLFYxPz8PJ5++mlBBNlsFu+88w4ODg7w6U9/GnNzc2IgZrQkEQ7dqLQ9AIcMkxvo0IZirhX9v3Zr2q4ziV7nZNgYgrlWbTEUH6XL8swyBpMBHKc2mPeaUl/3Z15r9mm6NMfHx5HL5aSOIvVa1z2sM0DbABcUYfb4+DiAQ+/A2toa1tfXUSwWBTXQd04iTaVSAtVZd5Fqwfr6OiqVCiKRCHK5HC5cuIBKpYIbN27g3XffRaVSwcLCghjastms7EjNMGJCdD0vHAMJlWHSrJHA4CRdb4AqEXVwXdWaOjj75bzTdpFOp6VaFXeNchwH+/v7cN3DyMk7d+4gmUzi6tWrGBsbk6CtdruNvb09rK6uyv4YdC/SZsFNd4jeotGoMFky8729PUF9Y2NjQzUfaJwlktI1IBhyzfezSXWz2QyKeo1S+nulVNvWrlZfvGwJ/2RtDDZIbzvmpQ7wmM3wqNtJGMXc3Bzm5uaQTCbFUEhozHHQiOY4jsQvsE7A2NiY6LT7+/uo1+uCBLiXhOu6Q0FHVF0Ia5mFSB07k8mI12NjY0NqN1y5cgUTExNYXFwcMohSXdGqgJkApAN4mKtAYyiDsgBIpCPVBEYZsl+qBGREDAXXyVCRSAQXL15ELBaTvS1arRb29/eRTqfx1FNPYX5+HhsbG9jd3UWz2cSdO3fEu0I3KFUX5lwwHmRtbQ1bW1tIJBJot9uYnJxEOp1GJpNBqVRCv9/HwsKClK1vNpsS1EW1SCeLRSIRJBIJpFIpT0RqHjOvMxGujQmYiMJEtLY+NfPwWsOP2s4kY9AvZoNUx8Ekr4AR2wczUYlpFQ4EAhK9WK/XZedmLhjCT0baVatVbGxswHEcIZytrS2sr69LsI7rulJHgffTSEZUQInFwKRarYb5+XlMTU2hUqnA7/dLLATLud29exdvvPEGstmswF7q8qFQCPv7+5L96LruUFVkeiUYTqsrVMfj8YdiD5LJpBREAR4O3KFUJUFNTEzIPp2RSERcgqurq5K/0Wq1kMlk8PnPf15SwCn5e70eMpmMeDdYJr5cLosqR7RTqVQwMzMjXh26ZCcnJ3HhwgXMzMwI8qNXgvUaXPcom5bMPplMot1uIxaLYWxs7CE9XzczCtG2hr2I26QBrT7bVF7zvv9fqBImcQPebh9TL9OTo3U9k/jNa/UH4N/BYBD5fF42RWUwDiE0JSu3dNvb24PjOFhcXESxWJSYhq2tLezs7KDb7Q4l+9BK3u/3MTExIYuURBgOh1Eul8W1du3aNal9yMQspjbPzs6i3W5jfX0de3t7ePrpp4WREaFQxyfj4jtq2E//PQkjk8mgXq9LcBDzL5gkxVgMEhMZDRf2+Pg48vk8AEjf7XZb9tigW3R2dhZzc3OYmJhAOp1GoVBAuVyWZ+risZVKRRiiZk65XA6NRgNbW1viWWE26+7uLra3t3H16lWMj48LgqLbmGiDTFMTWiqVktRtvquXeqD/N9cl16uJYG1qs+5Dr3Nb//p+3f9p25llDIA9NNSEXSb8Mu8zOecopmJDFrQrMMmHOxfxWsJN6nyFQkHKj+3s7Ehkny4iS8KmikHJu7u7K3sfMMowlUohFAqJS25iYgKZTEZ0/+3tbcmEHAwGwixY42FiYkLChGm74NjJEOixYFr31NQUotEodnZ2sLCwgEQigVu3bon9guoOXbBs3H2ac0zGyeQpEiq3whsfHxdEoL0fDJ5iLIgO8QYg8Qbtdlu8EIyVoKuRaMzn80ktTQBixGWsRiaTkUzYXq+HXC6HUqkkJfaJpICj5KRHjR2wqQMmUbPZELLtmV5IwuzvtO3MMgb9sho9aGK3wSXzvFegyXH2Cf4dj8dlhyaG6cZiMSlMwrJliUQCxWIR169fl4g+Fiq5e/cuDg4OBLZyETNpKhKJ4JOf/CTa7Tbq9br0PTk5icFggI2NDQCHeQ6rq6vY2dmR4Klut4utrS0hjlKphGAwKDstUb8HIP3u7OwgHo+LS5ISl96GSCSCra0thMNh1Ot1XL9+HdVqFQsPAnw4ZiaAMRmM6eAAZFPbdruNW7duIZ1O4+mnn8b8/Dzm5uaQTqdx69YtrKysoFQqiVcCgCAcqg80HFL9qlQqiEajaLVaWFtbw/z8vGyuw/mbmZkRZjc1NYU7d+4I41hfX0c4HMb09LTUpiAyi0aj2NraksA1cwNfqlhsXvq8lu6260cJL2AYQXgZOW1JVUR+/2RVCRMJeOlXXtBLc1vbB+K1Nm6tf9PgpN18zWZTNqGl0TAYDGJzcxPValUIntGDdPmxGpGOe4hEIhgbG0Mmk8EHH3yAYrEo29YzFJiVn/g/re8HBwfw+Q63l9vc3ESlUpHCKZVKBalUCpOTk5ibm8PLL7+MaDSKn/3sZ9ja2pJwZxI3Yw18Pp8kZjGykvEIjE8oFosAIOHCrI2oi9QGg0GUy2UcHBzg6tWreOGFF3Dx4kXMzs6i2+3ivffew09+8hMpn6+Ns4FAALlcDlNTU4IWKK01SgkEAlhbW0Oz2cT09DTi8TgODg7Q7XYRjUZlExluT8dQcm5oy8rYREDVahW5XA4AhEmVSqUhlMVYh5MgBlPf95L4ej2ba5HnvAKaNOowDcqP084kYzAnxUvim9ea93shDC9GYZtQJkrpRKJSqYTx8XExDFJasmw6AAlVLpVKEgTFD0eIPRgMJJ6BG67Sj07XmU5OYoQjg4sqlYq4O5lJyXgK7gBFgs7lcrhy5QquXLmCa9eu4fr16ygUCojH40gkEmg2myJR9/b2pKhsKpUa2vS2Xq+jWCzKYmQKNgBBSsytaDabcBwHFy5cEK9OuVzG3bt3cf36dYlvoNeF80kG57quzBuvAyBojKiFzIQqGIljbGwMyWQSt2/fBnCY5Uq3KRPBmEzmOI7UzGAqO7NYgYerMI+S/F7XjPIW2IyIWiDa1GYbAj4JmjlJO5OMgS9jC/awGSPNuAPzvO1eNv0ME5oxMEZvmcaQYhqhAEjyzsrKCtbX17G4uCgMhMlOXPRsjH8gEVNNcV1XysBxE9wLFy4gFAqhVqtJ0haJlMVNyWy4Y1MgEBDXaLFYxM7ODubm5vDss8/imWeekWIuels2Gg+Bo+3wiBbolWEyFACJv9DeDS5GMjHu95BIJHDhwgXcvXtXjKPNZlP2hCDzJTqoVquSrr20tCSbwTBNvNlsolQqYWpqSoiWhJ1MJhEIBFCpVCSGgyoQN7JdWVnBpUuXxJA5MzMj755IJFAulzE/P4+JiQlBi9FoVL6jXksm7NcBdNoQOEp10ETspQ7YEIdpePyo2plkDGwmzLfBfq+gJfN/k8OyeaEHYDidmcE8JAZKccYXVKtV2XlpdnYWq6ur2NjYEF87/eUsGkJDnxltB0BsBcBhDAV9791uF9lsVhCK3rKOHgwdhTk+Pi71GVg+LZ1OAwD29/fFEq/ni1KRc02PCedfR6TSoKeDbeil4ZhIkOVyGffv35dYBKo6LPlGtBIOhyVYibUW7t+/LxC/2+3KFndM7pqenpb3Bg6rRtEmoPNXGBvC+WaMBpPAOFaqIayFqXfiImLT0vw4G5aeH32NzrC1rddRSMNkEmaqtteaPmk7k4zB5IK2j2Bmo+nzNnhn8zqM4rJc5CwcQr2Wabzj4+NSpoyuMIYsr66u4v79+0PFSgaDgXgYuBcDbRW5XA7lchnvvfce2u02rl69Ktvaua6LWq0mPn7+Tys9N8cFMKTf04aRTCblHtohXnzxRSSTSfFmkPD1DlCcA84V60Iy0EmjOh3OS4ImAZK5drtdqURNGwnrPQ4GA9nTwu/3I5PJCDoCIEyNyVzdblfej1GmnCNW4C4UCoIe8vm8PJe7XdHgOTY2JnUiiDL0zt7cEIjvqMPBjyNAL7uYXuNeKoLpLbMxId0fUZ++5nHamWUMx0l5k5Pa7A/6fy8jzyj9jGXXeR2lMxNsgCO9ulgsSnUmSm5CferxNBBxT0oyG+467TiOFIQdGxsTNxoXeafTEXcpYTJjAFg4lYiADIk2jcnJSbiui/39fWxvb8tmtrqeon4nXX9BG15px2DjOZNh8xraP3Z3d2U+aLtg7UVdHYrPpJuYfeoS/rRdkEC57yV3z4pEIpiZmZF3Y4YncFTJulQqiXeGBlcyUZ28p2tHJhIJ5HK5oWeba8ym9nrZzEj8ev684ndszEEbGjUqMYXkadqZZAwmMZvNZkQ006VH3WtKPPOZvIZ+cC5YVhVmJByJjvs1uK6LiYkJaTfbHAAAIABJREFUCV6Kx+NYXFwUF1iz2UQ0GpWq0NVqFe+9955UZ85msyLZfT6f7BdByzqhMREDw5jplnQcZ0glIQOjhObY1tbWBGqzSCvnQgf2aJirFyejMkkgek5pkKSdwefzPeQeZf1FEjFhPnDkDSDs13Uf+b6E/SRMeiGAo/0kdF4HmRnVAl63tbUl36JWqw3VuOT7sEI362a4rjtkcPUSXqPsCKaQMpGviZS1t8EUcl5MyaaiPEo7k4wBeNhF44UIeG4UZ7RNtn6G7kM/Jx6Py1ZnwJEezypLAKQeYalUkniH27dvS7UkGisZkUcpT8LJZrNScbpQKEhE4crKimQLcts6GhPpoqTE15Z44CiXAYBEIhJGLywsYHV1VVQTWvTpsuQ86CQhzgc9DlzIVCu0+sHj/J9xDnTtcncr5m+wP+1u06hD11YolUrCsIGjHbm4v+bi4iJisRi2t7eRSCQwPz8vmwxPTEzIXhREIERdoVAIa2trsn8oazI4zuHuWUR5ZGBkiNpoa6ICvR510pVesydZ1zyn+zUZgKmiaEZtK11wknYmKzixecF+23XAwyGpPGaiCRuHNj+U4xyWdEsmk5J9R2nKPimluEGs4ziSxkxiBCDRjdxARm9jTwMeISrvJ+Nggo8uakJmwm3kiWrIIEhQJsNk5CCDtWgcpFdBE6jWgbXk0QlSJGI+G4CgAq0i0HDnuq4wVl5LnZ0ogMcAyD1kbjQEc6y8jsFNRCuJRAK9Xk8iF0kgLK/HIrSFQkFyU3q9Hra3tyVzVhuNaW/SkaJcI/xWZoizTXqb6rApqPTc677YyDj1GjaZgtn3aduxjMFxnHnHcf5fx3FuOI5z3XGc//bB8ZzjOH/rOM7tB7+zD447juP8r47jfOg4zq8cx3n21KPDaHhmSjQbR6UOrA09ul/9UfREMxeCPvNmsymqACUl9VV6Gxh11+/3pfhqqVTC/v6+1F2YnJyUOATuGkUrPOP6aS/Q783gHjIUZndqAgEwpKfrOdMbsLAYC63tej8G7X404ahZ1oxzpu0TrusK+qDtgsSu1TMAQ6iGxjwyNpZb04ydcR1mzAK3s2s2m9jd3RVJvrOzg3K5LAV1bt68KV6NQCAgdgbGbPAdaJ/RBEeiZVyJDSnwWq1i6WPm/7Z1refSRugmcznJdadpJ1ElegD+e9d1f+44ThLAzxzH+VsA/xrAD1zX/VPHcf4YwB8D+B8A/DaA5Qc/nwXw7x/8PnHjh7DpTmwmkdsiHG2Tbxpm9LN0CwQCkqWYSqUkAxCAFE5xHEeSgfr9voQwr62tiXRm0VGWUQsGg9jf3xe1QBdCoepAa/7e3p4cDwQCkq9BY5su1qrnhAyEdhC+D4OdgCNXYjQalbgELn7q8qYkIpFTkvNv7bbUuRccC9+LQUW8jmoGGQbdp2QKGoLrb8x9KmgvoP3B5/NJtiXVBdqE+N1YJIeZsGtra5icnEQ8Hsf29raoagAkBoJeFSIljs1UUc015bVmTeK2oVWTsE0mZa5j9vNRRT4eixhc191yXffnD/6uArgBYBbA1wB898Fl3wXwLx78/TUA/9E9bP8VQMZxnOlHGZQXU7ChB5MZ8Jxtcs17zWfovogY6BbjwnCco01UGGTUaDTEDcaoQF3pWBspaStgMA49H5OTk5icnMT09DQymYxAfV1aHjhCBADErcYxk8GQKDiXJFaeJyER4nNBUcqRGLVLmAyDBM+ai0xWMm0SnFNKWc6jrg2p++WzTHep/p/vr9ULzgNVPqp3fH/aIJjA1W63sb+/j2q1KklxTOPW0Zqs+aA3DGJxHr6L/hY2OO91TiMIU9qb93qtV42kdB+PY3DU7ZGMj47jLAB4BsBPAUy5rrv1YEBbjuNMPrhsFsCaum39wbGtEz7DU4rbOKrXB7FN7ihEARz55B3HEUOULm9Gt1cwGBT/u5ZWrGXI6se0IfB55XIZzWZT9pokYRNeM7hG68uU/iQaugzNsZpSVUNS6vB6HDToaYObDt7SMRhkBlyU9Bgw0pJzABwhETbq/ERQenzAsBdC24I0rKdqARwFXHW7XUklpzpEdEUkRTVQP5eqAOMWkskkisWiZHSWSiXJh+AzmCznuq7smWnOsW09mWoqj9mEnSnpbUjZpkZ4CUSbmvMo7cSMwXGcBID/G8B/57puZcRDbSceEt2O43wLwLc8nnV4k4cOZeOUXrqX1wSaRh/zHGv8XbhwAQCkZiKlP4mGGZE+n09iF3SxUIYvM9qPBVRpNEyn04jFYhI9Wa1W5d5UKiVx+6aVn4QJQLwFtEtoHVUvOKaH0zDIXa1pxCSDYWITw5P1QmN4dCQSQbFYlBJwlOJaDfH7/ZIGDkBCy4kCiCaIqlzXFVWJ/TBYKxAIoFgsSlAWN7+l4RA4CvLRxzh+zivRC1O9u90uisWiVIQuFArI5/OSI0IDpC6Rx1qQxxG5Dv6yqbC6eQkyUx22MRkv1PE4KsWJGIPjOEEcMoX/w3Xd/+fB4R3HcaYfoIVpALsPjq8DmFe3zwHYNPt0Xfc7AL7zoH/XOMfnmuMYmjAbA7D1o68xrzPtE2yxWEyyHKmzajcZg4xItJRCBwcHQ242litjWjFddwyCIrHogCdCX6IVEggwzBiIArRuT/WHzzZhO2MemCodCARw8eJFXL16Fe+//74EU7F2g97vUi86voupYmg0wHFQtSFDpGeBUl7Dau0GJMPpdDoyhwwhJ3ET2vN9yQgYv8B4D9oZ+DwaR9vtNkqlEhqNhlSEYm4LDbVEUNxTU68djVj1HJjrzlx/JyFaG9GbjEL3Y7r3H0etOIlXwgHwvwG44bru/6xOfQ/AHz74+w8B/Bd1/A+cw/Y5AGWqHB91exS4pLm5PmbT+wAMSWAWUuHEc0HpgrCO46BarUoQjOu6stksoS3Vi2Qy+ZABTksCM1sxEonI5jCUqITeOkyZqg0JS3sDtIrGeWDdROYpUMrScElmqPVZPpOp2QDE5kJVShMA1SBufsMCMyR8zj3tKVSvmA7O8OVqtSrBYXpTXL4ngKFAKdd1RdI3Gg1JRWfOSSwWk7iGcrks6IhzEI1GJbiMqiPrQ3A3Mc6ntsc86rpk00LPXLc2ArchFc67OZ7TtJMghi8A+G8AvOs4zjsPjv2PAP4UwH92HOffAlgF8C8fnPs+gK8A+BBAA8C/edRBmciAzQadzKYRwKg+9LP03+wzm81ienpakmwYpxCNRsXNxbHwmoODA1n4um4A3ZOBQADpdFrsESRqXWiVwTUMB6ZuTWlE9YG6sqmrM5eAyUN8J1ZX0pKeEpyEncvlZM/GWq2GcrksxAdgKAeDkplj0yoHx0HbSa/XE08KmZfrukO1DThGogi9aQ6jNoGjOAqmXNMGoZEJ1QX+3W63UalU5D7u4cHdyTudDjY3N2UsRF9k0FrV4Zh0mXy9tsx1qd/PRsy26zl/JkOwHTORnNczHrUdyxhc1/0R7HYDAPhnlutdAN8+9Yjw8KQ9igvGNlGj1Aw9mfoDUoUg9x0MBgIrmTNBCUeXH8uckxhISFy41J0ZwUc7Aw2RjuOIIY9QWHN/wmaqFdrgp0vRa0OjtilolEJorfM4pqen0ev1JAuTO06RyEk0OuSYahTPabuGjqnQ0pXzw/0ZdNSj/o4kBJPgzCAqIhtuuKsNqYPBYbm7nZ0d7O3tScJZpVKRepvNZlMK5GQyGVFLiBa4sxhtFTRGm2tLCy4TQfC3GaPg1XSMiIn2zGazV3it+5O2MxsSDQz7z23wzGbEMe837RWm+mAz+rAyNCEji7qydBg/EBc26wSUSiVRF4AjqeI+MGY6jiMLjPBaj4sqCw1rhOY8rwlIp/9yfjRS0rYIPY+0GUSjUZH0lIhjY2OSYahL2Q8GA9kXkszNZMAkav5NxEQPBsPIyTD5HuxDIyiqFlpv5zyTAREh6YpYjEYNBoOiJnW7XaRSKdnxu1KpyL6g2WwW8Xgc9Xodu7u7iEQiyOfz8Pl8QyiRc8t6nDp03Fw7psQ+zg6m1ybn2oZozX5swsxm3zhtO5OMwXxp/m2qEebfJ4FrmvOanJULIBAIYGpqSnZqrtfrmJ6eRrlcFrTAas9MaGIZNJ/PJ7tO6xLz+/v7KBaLCAQCUs2IC12XL5+dnZV8CernOkaf0lJ7ZmgkdJyjPAKe1zENHDerQw0GA+RyOUxOTsomMxMTE7hy5Qpu3rwpUp16OdUBEiWbjgTk8xmlSOZiqhE6alO7KvkN+Fv/kCHwWWQmZGwsustn0mvBJCtWvSIDcJzDUm3T09NSxv7atWsSIco9K6LRqKiIrLTNLFe9Xs11arMX2JrX+vViCvqYSR86BuVx2plkDNqIwmZDD6Mm0st24IUgTOnH3a11pWDq6RsbG6jVapiZmUGlUpF8fqoVtPgz7ZdGrl6vJ0VNqSrQbsBzLEKi348SkeO2ISetf/JeLZFpe9BBRkQUDM9mhaJsNotUKoW9vb2hwB9dHZt980cbQhnSzeuJTky/P9UbXQCFTfen3xE4MspyLLrmpM66ZJ9+v192klpbWxM3KQ2OOs+F9Sxd9zBFndWlgsGgqCecPxN5msLKXH+276bXorkmT6J2mH2bjPi07UwyBt20nqkJxkbQ+h6TsbB5GWv05AeDQUxPT2MwGEg6NSMfWUqNxMIdoBi/zySoWCwmNgG6NHXqL6E1VZNWqyWbqNDOQIlKKW0mSlEt0OHLbCRCPlcb8yiRaaDb29uTcu4sRKPdkIwC5f/6u3Du+JxkMimbzjYaDTnH+A+totiKnmiEoN9Nu2Q1AymVSigWi/D5fFKxmwyH8J9oZ/FB5ezd3V0pV8+cFr7H5uYmGo2GVN9mtWnOv442ZbMhAxusHwXzbQJLn/NiLHpuHkd1MNuZZAwm4dugmv4fsLtvvJiAXli68Xw+n5fyXru7u5Kr3+l0sLOzA+CwqtDKygo2NzdRKpUEnjMFmJ4FQjsGMvFebhJDRgBAdl820Q7Do/keWj3QlnnHcaQv4CigyXXdoet19SPGTMTjcbRaLWxvb8PnO0zrTqfTGAwGaDab4nUgc9AeD6KafD6PsbExNBoNNBoNqVJ1cHAg29wx1oL7X/p8Pgmt1oRvqpMMeKKEZ3VnlofX2Y8sbkNXMWM+6vU6nn32WXS7Xezt7eHJJ58UJkDjcL1ex+uvvw6fz4e5uTnE43FUKhWsrKwgk8mIamjzDujfNlXXJFxtEzLX90lUZc2c+U312v8nZWMgBzQn3rQDmFxUw2fgYYOl+RG0TqZ1ZsdxpHQbCYaFSVnqKxaL4c6dO1hfX5fAl4ODA7GM0/LP/SeoZpAY0um0uDL7/T6KxeJQMRDg0LBJPV1LScY1OI4z5H7kNdzlipWhmZ8BYMhgqUOF+X6XL1+WDWEZYMU5ob2A34EMgh4LlsBn4Bd3u5qdnZVyaa7rSpSo4ziCKmq1GqampqQSNou68FvpOAkSAACk02mJeWC5eqpK3LC20+lgY2NDak5qBloul2X8dDE7zuEGu4lEAjMzM8hkMigUCnjzzTfx1FNPIRaLDdWQ4BxyTek1yPWnXbk2FGtGqpo2MM0U+FyTUdhCs71sGidpZ44xAEdJTDqSzEbUwLDrSqsPNEJpQ5bWiTnJeqHxXrqs7ty5g9XVVWSz2aFx8MM3m00AkGAg6tfUf13XlX0ZzBDmZrMpejgDjFi3UFvz9XgppSkZaLys1WriTiUioPrAaECz0TPAwKmdnR2JJDRdkWQ8VAX0tyEy4sYwTGOemJjA0tKSSHraSeg14DfTkZocF9EZ1SXuGUpJzdoKZMI0ROpISqpdhP7MLt3Y2JD+aUviOmKkaSQSweTkpDCr1dVVFAoFsU3orQBI+OyDc6aZhraNaHvQKGRrW/fmeb1mTfqwqR6P0s4kY+Bka6mvubAmZFrjNec0VQXq2jYdTbsMgaNMPQCiK5dKJSEy+smLxSL8fr94Jeg2oxRvt9u4efOmuDDT6bS4Kgl76RPn1vCMXyBKoH5PwyGZC20OZEbMeaB0JNwlyqHqQWKiG4/7Sb711ltDqeSf/vSnZQNXqg30TpAZARDpOT4+jieffBLhcBi7u7twXRfb29uYnp7G9PQ07t27h/X1dczNzQnjpLeAm97u7+9ja2tLgsroCm6322IQLZfLADC036f+7iRMoijaeXK5HHy+w2I5ZOZEVjQ2MsuV34f7dN6+fRtra2v47Gc/i4WFBbTbbXHr6vJ2/BZa3+c6pk2IxG7WetCMQdeFMA3IZgo6aUEzcqIn2p9OW8HpzDEGU4cCIHDfdd2hKEEvu4KpXth0NJO7sm/g0ODFtFufz4c7d+4AOFxMLB5KOEl0o+sm0m7AikAsqkIJR4Oa3lSFz+ZuT5Si0WhUFhilJnBUNIV6NhcK+2m320NMj2XaaYRMJBLw+/14++23JV6iWCzK/pSBQEA22eW2dlQP9Nz6/X4sLy/j8uXLcF0Xd+/elXJqTG1OJBIoFAqSqKSTrcjEWGiVNRiJXAj1GaJONYDGTM4F55EMgvPEMGZKesaKuK4rbmFNnL3e4Z6Zt2/fxuXLl8WT02g0pIiuTgrTCWO6kA0ZBEPNySC4nrVaxvfVTGCUGgEMb0/HPvldOKbTMgXgDDIGE+7rBcLzeoKAYR2Pv3WuvD7OZk64fq7eeUnvVLS+vj606Sx1atZ95G5S/X4fW1tbqNfrYlgj+qBuz98TExNiOSdT4TsxpZlx/Sy8olOmWcLMDMAKh8NoNBpD6InqRbFYhOu6Ep/gui7K5TIuXbqEp59+Gq7rolKpwOfzyXZuFy9exPz8PFZWVqQOYjQaRT6fx4ULFwQlXbp0CRMTEygUCiKR+V6cHxaiLRaLoprQ88ECLPx+JEQtnZnxSA8Pvw8NmCQOqha07ejiupxvMmHg0MMxOzuLWCyGer2Ora0t+WbvvPMOXnnlFeTz+aFNZ4gW9BrSa00/R19HtUhLfI5Xq8CaIWgPjfbUafXvcdQH3c4cY7A1bWvQRkRz4vSEmbH7bNp4ZuplJEZWVqKOHwwGRZrdu3cP29vbEmtfKBQkVJofmSoCS8lTddCbx1I1IAEQnWijHsdDXVzbUXQYNBEH0QhhtpaetGEwgYljIXObnJzEzMwMdnd3JbjH5/Mhl8tJtF+pVMLCwsKQDYMEyLlkohQhLWMjGGBEaQ8c5YHoylI0ejJRitKY30sbWzmXOvKTcJpz3O/3xasSiUQk14W2HTJR9kmk2O12sbOzg/X1ddy6dQvLy8tYXl4WjweZl44ONZu2B+m1RmO3aSznMa1amAyAa9ur6Wc+TjtzjMGE/MCwe9FUH2zXmhzUplLoPkwGwy3jU6kUrl69Cp/Ph93dXeRyOdkSnmOikQw4ijKky5L2AG3Rp5TXsf2UDjqNWnsx6NaMxWLCfLioSaRacvK9qAdrAx0DtkhIjuNgbGwMTzzxBNLptBAox7K3tyfeDW4Yq41rlJ7MtkwkEtjd3X1onwYaNmmX6fV6omJpQx3nkgiBFafIIDV057swKpSwX/eljaRk9mQOhUIBY2Njsha4bwdtKltbW2JLevXVV5FOp7G/vy/Xm94sU4Lb7Agm4tX5JVoNMNepSSP8xrZn62OnbWeOMbCZ0MsG2/QEmZZabagx7Q825qM5NFuhUMDOzg5yuZwYvOg3r1Qq6Ha7mJycRCgUEpdYvV5HrVYbWoiu60pCDguyOI4jdQU4Ji5wcnxWEGKQFCWfDgIiM+I70aDXaDSwt7cnngdugMsoPlYkqlQqEm9BmwTdg3S7suy9niOqPK1WCysrK2J403UnKpUKlpeX8ZnPfAa9Xg+3bt3C9evXpQ4m4zOIhjg/VIH8fr/Uv9SogK5L4Eg9YqPk1/YVIi9ez015Dg4OUCgU5JuSafBdCoUCms0m5ubmEAwe7k/q9/slK1SvGy9C1MZE061pQwxkjNomode4uZ5ttoiPop1JxmDGKdgYAD+2GfgDPBwOakMKOohGwzjq6pSAOzs7os8z1yEcDkuFHxKB67qS90/Or42UOjWZ2ZTA0cawlGo0bHFB8Rk62pHeCu3mo1T1+Q53VdKZgQwiYgsEDgvdUpoPBgMcHByIOhaPx+Uc1QWqKEQs3MTGtP1odYn1FLmhzvLyMvb29nBwcCCRljTqMb+E4cudTkdClnVRGiIWzh3Pc445Z3wXrWLRnsCQ7Wq1KnNGdEb7BfcIZdwFVTC6MrnHpilQTIGlbQ56fZqo1aYm62YafXmf1zMfl0GcOcbgBYdsUMzUxUyOTNRg9sVrTC7tukeuRAYaES7SRUmpQb2UC1X7y/VO2ABk8bruYYDPwcEBUqmU1GYgNDb1RzIS6sv0fPDdqAszMYpGROY1EAkwFyMUCmFmZgaJRELK2mt0ovuhrk6jF6M+WXWZVbOpylAtIoHyW1SrVZHKPp8PTz31FLa2trC6uipeDm4DSAbEICeOX6eSs29+b5/vqKgMvx0ZKb8H79Ueg0gkgmQyKTEgvK9arSIej2NsbEzWRzAYxPr6urgxL1y4gPHxcayvr8v30E2Pjf+b57Xqqv/mOjANjCaCAIYjH/UYTGRxmnbmGAObjSHY7Af65TVk89L12PTf+j6mHW9ubg7ZA8LhMMbHx0Uyc6s4EgMlLt2AHBcXCImLer7jOFI6juiHMNk0VFGlINQmvNewnfkXVEdIXCxosvhgqzzHcYQ5bW5uClHrPAaqDY7jSJwGIXqtVpNArEAggHg8LmiKqIe7TG1ubqLdbmNzc1MK1YyPj+PSpUu4ePEiNjc3cXBwgO3tbdH3aUfR7lYSGhmYrofBADIGQpExs7oz0SWZCn90qbl2+/9r711jJL3OM7HnVN+mu6u7qqure/o6Nw7F4ZAiqZFF6kIZkrwKEmexigEZq+wiEQIDAhIE2MAINjYCJJtgA8T5ERvBLuwYcADvYtey1o5hQ7azMWQKFiVZ4k0ccUwOZ4YzPd3T90tV36/15UfVc+apd875quZCsqj0ARpd9dV3Od85533f572ePb9tH5l3oVBAsVj0jPrxxx9HW1sb5ufnMTk5iUuXLmF5ednPpa5bi1hj647rQ+c7ROiqNoZUCn0uf3vYLMuWYwzkmmzWoAPcC6eUaegxvQebvZceJ0NhZCJdgdevX6+z/HNhUi3gPQntVUIR7lJiEtKqdCXEZfAQFzGRBOH8wcGBj6Og8XJ9fR1zc3N1Hgz2I5vN+hyNwcFB7OzsYGtrCzMzM5iamsLm5qavVbC/v1+3EQ37ShsAcypozed40YXKfutuV7RDLC4u4uDgAMViEc5V3YqDg4MYHh7G7u4uFhcX8frrr3uGQyJgBiolOgvvJkniGQiZJNUIVp7a3Nz0HhUyfHp8GDKuTJVz1t/fj97eXu+6fOKJJzxD0FoWY2NjmJiYwLvvvuvXrVWrQoSrAk9bTLorqgitfR6zAjTtns20lmMMQHqmWUj3shArpD7ogNlzFYkwwnFtbc17Fba2trCwsOAt4TQqar0FPovSVf3s1h5SKBTqsi/JdJIkqbN0Uzfmtaz1WKlUfIowd8fq6+vDwcGBD1A6ODjAwMCA366Nm6kwIWhnZ+eenayIFGiboEGQezaw8hRdkFSFLCJi9eXR0VE/Bvv7+z4mZGNjA6Ojo7hw4QLW19exsbGBp59+2ldZYkwEy9wxwKlUKvmENhpkuffD7u4uVlZWPMrgPcgU6BKlAVdRItUgJmDRWHv16lWfBj89Xd0Roaury+e6nDx5EteuXbtnXdrPISYQWtv2NzY1nlrCDzEKde8/aGs5xmAhvnLKUOyBcsrQoFqYlzYplIaLi4u4evUqCoWCJ95MJuNdkTTsEbLrztOUPCRwtZp3dnZ6JKKJOJRkGj3Hz0QkNFaur697JMLoRBrtxsfHcf78eYyMjHhGQS/J7OysRzh7e3vo7u5Gf3+/3wejUqn4ytjctIVET5sKIzd15ymmL9NgyBgIoi56YUqlEvr6+vDss896/f073/kObt68iYWFBVy4cMFXzTo6OsL169d9XgPRFNUX2ntojyChEIlx3EulEpaWluqIhIZkoh+b4s78FY4pC9ESpRSLRW976e/v96n2qhIoegitMyv9rSBUu4NFtyEkos0i5wdtLckY1PVi/6ddZz+nGTH1PDVkkkhpP6ALC4APJybXJhxVFQKAt0lo4A9hL11tvC5JqinZDKOmjsxSamSGmgxFoyMjCcfHxzEyMoKJiQlcuHDB5wZwx6Xt7W2sra1henraRyTS80AYbmMq1DCrthrdU5IMk14KW41pY2OjToID8BmOk5OT3qUKVJkm+6pRgeVy2TNa5qQw+5JjTtQG3DVg2p27iSzVmKqBQGR4NFoeHlb3ArGojaoK78N0dTUaN/IIWGHGFiLkkOS3RksVeA/DDLS1HGOwL2kJPgS9mrmn/RxiJBpvfnBw4CXe1taW19W5vZzaA4C7/nN+5rOoKqhkBqqZmUyW4sKikZE6MG0N1Kvpg+dCLxQK6OzsxMmTJ/Hss8/izJkzXhc/ODjw+yVwkS8uLvraEUlSzfykxGc2J4laU65VXaPdQ92oVrIx8GpgYMDbFw4PD7G5ueldhblcDk8++SQKhQI2Nzexvb3tU8Xb29t9IBHjL2jbYSQpEVehUPBVtGi45bizL/o+zF7VoLRKpeLTwlnKLZvNYmhoyLtWWcKfrmwyOxpumZwValYYqa0sdo5dtyGVIbSe0+wY99NajjEA4TTUkAoQQxJqNwhdaydELcFq/ebuRSS2/v5+9Pf3+3p/zjnv997c3KyD2Oo/JwIh7GWG4+bmJtbW1rC+vu5hsDIV9b3Tu0AITW/C6OgoHnvsMWQyGVy/fh3j4+MA4Gs7TE1NYW5uDtPT054wKfkqlQqGhoa8BNZ9MDWrk7BaQ4BJhIzQpHE0SRJf3o7q1szMjDfsbW1t4ac//Slu3LiBM2fOYHR0FGfPnvVG1f545Jc4AAAgAElEQVT+fszOzqJcLmN6ehrr6+s+z4T9YWQpiZ+h3hx7GiGpCimTp3eHqIHvyV3Kd3d3/U5cp06d8tGjRCdEfVyDnE+6TBUh2maFmI27CRGyMl0b3xNb+48CPbQkYwDiocz8HLMTsMUMM/a+dnDJFLgY6BE4ceKEN9gpEdFgRyMXAH89XVnUSTmx9N9XKhUsLi7WFRthH3g/QnMudqYjs4hMLpfz+yKQUGmcvHr1Kqampjwj0xwHoJrAReMkn0F7AiWqBlJZ24gm+ygjIWKgRGWxk/39fRQKBY8Opqensby8jMXFRZw5c8ajEh4j46MrlmNHtMOU7L29PW8QVhclcDfXQIvUaOVt/hE1EI1VKhWP1DguNPhWKhXvaqbaxy0EYkZIXWdpdq/QOuY1IXRgaYDr+2HQAtCCjMESLo+FGEKIqNNQRey+lgNXKhW/ZRk9E8xHUIJlYtDW1lYdo7C7MXFxUd0g4QDwLjCqL7RLjI+Pe3cf7QnM32hvb/cb0zJuwrlqMdOVlRWUy2XMz8/j9u3bdUzBlpEj09HdnxgOTOSiC1KP0x6he2/QHqHRiUCVATEJi0Y71negcZTFXYiKVldXsbq66t2MzPakh2RpaQmbm5veJct9IDhXaoQD6lOzrR1FmZu6lm/duuUZzd7eHpaWlpAkiS/cQ48N3y20TnUthmwF2ppRodPUjbRn3W9rOcZg9ScOip3oNDil9wmhi5iqoddQMoyPj3vkwL0LnXN1OidLg5Ho+QwaILm4KM1p+OKzaKCjnYEbzGrQFKX23t4eVldXsb+/70ueT01NYXx8HIODg5iamvKSWHdcor2B78SoQjbVuXVMqRapAZFEoclLvJ7/qUowd2NsbAxANbUZqBZ5IcPY2trCu+++i9nZWZ+m3tnZ6cOWOVb0dJRKJZ9Udvv2be92ZV4J30P7qpGIzGylUdk55z/39PR4u0Eul/MGUTJN7mg1MjKCEydO4MqVKyiVSnUl+nV98v4hQqXwsG70EMPQ32IoI+26+20txxhCLWRz0D/LMCgBSGyhAQzZFez9uQfB448/7hcTAB80c3h4iMHBQU88mUymrp6ARRm0G2iglE4wGUR/fz/W19exuLjo7013HSUTVZXt7W3k83mUy2WsrKzg5s2bPgmJPniGLxMCk7mxcbyA+vRvK/nUfUmVge8N1FfKosGV+nhvby+Ghoa8J4d2Fz6zo6MDuVwOAwMDyGQy3vvT3t7uGZpl4JlMtTQb3aP0glBtY99C64dohyiOqIqb7vJ5ZDpk8JlMBqOjoxgcHPTjyt+4tmLI1AYeWbtXml0gJLzuRyW539ZyjMEOljbLABpdG1I/QrqafR5/p7usXC77Ai2sokS7A2ExS7/T/ZYkd0NwVZdVoqMeTknHKMnl5WUf3MN6CXS/6YYu3d3dKBQKcK4agEODZiaT8SiDUYBAtQLV8PDwPXkcDLUG6jeP4Rjwv7oubXSqJnrpu7ICVCaT8Z4PhjXTxQnAxxSogfTw8BBra2u+5gQAv9ckGRwb4wk0LRtAXb1Hvh/fm8iPSIiqFeMm9DPfm7aHN954w6tpmt2pDEHXmP4no+H5moFpmYpeYxFyiBmkoej7aS3HGEJqA1vMsGNbSO0IqQ9Wiui9uYC4GzSlJSH1yMiID8tlBSY2VRn4LNod6MbjAmNdRhIPq1BTajEsG7hL2JpCzBoCjCjkYt/Y2MDi4qL3v4+NjWFoaMh7EEjANEjyMxkax4cqjKoSmgvCPrLxWk3AIiPp7e3F6dOnsbS05O0NtKswToGRjRx/Eh4DyVRl0CCkTCbjDZv0QnDcqU7RXkQpT1tPkiS+iExfX59HD4wgBaoFbWhrKJfLXq2Ynp4OEnJM11di5ppTVJtmh9B1SlRk1RWNyfmZUiVCHK8ZDmgHjfey/2MDpuqFnVimWzNvQINvjo6OvI5JIlDLOBECg3Coy9J9yUVOoxfrJDjn0NPTg93d3bp9FBllyIKpR0dHdYlELANH1aFSqWYdDgwMeOlMoiVhqI7LfqtEUymsY6nGO7rxKKGtikGGw9JuLN+u6C2TqaY3k/BIfLRXqOckSRJPpGSqfHf2idCfzJ05Grlczo+F1regEbFYLPoQaTIUJoZ1dHRgYWEBlUrFGyN1Der/ELErYwipGqomhdRb/d2u1ZgK8yCt5RgDcBc1WPtA7CWtvmUbuavqgXqtctoQQ9ra2sLk5KQnWmYp3rlzx1v5WW+RxVxYmoxJTfv7+1hdXfW5AJSyLAzS0dHhGQFrRZL4stksNjY2vL+ehjEa6ZRISZTMbahUKsjn8367ewZnceHZuhEW8qrKoGiA6gftBYyzCKWN0x5DlyBLtq+urtZFGnZ2dqK/v997JTjftEFQpdDcDO03PStEC8oACd8XFxfrCJG2Bo4Ji9Z2dnZ6hsrQeOZJ3Lx502/rB6AuMzVEjBp/EApZtiggpo5YBmNzJpqhlWZbyzEGHZyQtTake8VUgtB1MeLX7yFO3dfXh66uLiwsLHiD2srKiv+dxM/riAi4YBiNyAWreiMJhpKeagGt/ZSSNKyxNgKJiuHMdEGS2FkhilvOAXcNiKEoR2WQClM5J7SJkMg0bBq4G/GprlgSLO9FNYaBYYwJIeM4ODjw5ftLpZK3I3DsyIQYN0BGyN/V0Mv51ncjEuE7kJHxNwaf0XNEGwOzRckAqRqSSdJjRFdtaE3qOrSCKLRuLeKydga1XYXo4GdKlbDNTnAjwg9dy2YZTcxww8/8zriFSqXiXZBMnALg7QA0fmncAe/FBUyXJAlGIT0XICW5WsaTJPGl5dUPr6XUdecqAD52gbYQa7RSBEDJS2RFBsAxI7GRSRDWayMTI7GRkdCoqhWqent7MT4+7nM3GLNBNMX9JmhroYEvk8l4GwT7ScK0CV5qK+F48TjHlkyCjEUzZhnGThsTmQKAexgRGZyWwVPGr2vXSv6YpFeUwf7qOZyfkD1Dz3+Q1nKMQQfPSvc0HSqEFkK6WYiD22doo7GQemmlUvGBOdyjEbhbCJZwnTCcBGizLoG7pcW5sHWjEO6/kCTVrD7VZw8PD9HX1+fVgmKx6IuyKHphGDczLUkIih64uCgxlYkpE3Dubp0Gvi+9EJT0dtxJEEzhJgOj8Y8eEuZD0HNBYyvfkbENrGDNvTA5f+rdUEKyc6p2B46FzgNzOjjP6q2gzWZsbMwzDV4DVMvc5/N5LC4uYnl52aPEkJRnX3TtKZLQMQ4xFmvnsc/g/XWt3W9rOcYAxF02MVuA/q5c2g56iLNq02u0D3RFKkQmI+DkcyFYt569t/WYUGfe2dnx6b0dHR0+vZvRfoxj4O90n1LXZ7+VKYyMjPg0YRKB+uP5PhYpEdFY7wPRE+/F39SuwD4outCYB4XoVCWov5OBkpHxfdvb25HL5bC3t+c9EBolqsSgNgXV162KqP1TpMT35r3p1eF+IUQz1p6SJInfeYuh6BqibdeDXqdrV1U4vpMiB2Vsul71M78/TGvIGJxzJwD8DYCu2vl/lCTJ/+icOwvgmwAKAF4H8J8lSbLvnOsC8K8AfBLACoB/mCTJrfvplLpcan0I2gistI8ZebSFkAiPh9rRUbWyshKSvT8nKQT3VHryd10Eeq19ByKAUqnkF5hzrm7T187OTu9KA+AZSFtbm7eu83m0rBOW2wVJKcMsRjIJohoyQDteHA8uXD1H9XqOJ+MZ+C50txKBqCpC42w2m8WpU6e8DYDp2c45j7hYq0IjILVGhhqzFQkR8eh3Go0rlWo4Nrel43EdO74z60EyonN+fr5OJbNjpk3jW5RZqMHcol1FE6F1+TCtGcSwB+BLSZJsOuc6ALzsnPtLAL8K4DeTJPmmc+53APwKgN+u/V9LkuS8c+5rAH4DwD+8n06FoJf+BoRDomOMJIYy9Bz9r/fv7OzE8PAwMpmMz0hU/dw556MdaTPgfbgo9HwuSEJ61YOVIBRqcmG1t1drJrIQi6ofvO/Kyoqvd9Db21sH8YH68uT8T6lIhMDy6AqriV5skBOJjefZCEB6LngvVq7igqZRlxKWdRypGtFOwvGcmJjA4eEh7ty5g/X1dZ/oRKTBNHmN1dC51vlVV6VlhKqiEPHQ1cxAN6pn+/v76OrqwuDgoN/d65d+6ZewtraGV199FW+99dY9zw4ZKFUFCglAi6ItrQD3hrQ/aGvIGJJqTzZrXztqfwmALwH4R7Xjvw/gn6HKGL5S+wwAfwTgXzjnXPIQbCz0kiGmwWbViBhTiCEPflY9+ODgoC4GgXH7Cu/tMzjRasHnolD4rxCWRkTCeb4n1YexsTFfhYibsNLKT1fm8PCwL2+vkjO08PhcZY7qIdBrKDHZZ+rCzH7UcVYvAgCv8ljERO8JK093dHRgdHTU6/SMglQm3tnZiTNnzmBnZwe3bt3ycR6Hh4fIZrN+w1oyPD6PTMrOE42WigRoYyDRczyI5GgQBuDdw6xURc/J6dOnMTAw4HNaeG81glvGpYhR17g9FnJr2vX7MK0pG4Nzrg3AawDOA/iXAG4AKCVJQuvGDIDx2udxANMAkCTJoXOuDGAQwLK55zcAfCP0PDtYVrUIna9ErtLWDp4dbA1a0iKvhM+FQuEeGK2QmxZoqgNqkFP1QReDEiv7RHcXcwQYp8D7MWlJS8KzT5Tw5XIZQ0NDfrPW0OKhAVCRFCW/xjSoS4/ohoRhmY0aLxUNKLPhMznmOrcAMDw8jLa2Nh8XQklMDwRL2+sc9vT0YHh42MeQMH6Bc6cojfOg4c0KxXX9qB1E60zQ45HP59Hb24uVlRV/T25iQxsEUK3t+cQTT+Bv/uZv8MYbbwTXYUzoWXuXRcX2d71Wz3vQ1hRjSJLkCMBzzrk8gD8B8GToNPYt5Te95+8C+F0AcM7V/a4DwYnT+AaeY1UBe1y5sH4HqhJseHgYIyMjKJfLfr8IrQE4MTGBJ598Et3d3VhYWPDPYYIQi3vwuSQmblun56vxTideGQAjGkmYrCSkUX+sx6DeDBY4zeVy6Ovrq9Prbe6A2io4rqo26VjreJM52THms3hvqhQ6H0RMOg7KtPmcvr4+5HI5nyjGlGaWxVdGq1sBslAKq2wlSeK3mmPxXtoPdG1kMncLtGjkpgoKEv7BwQFyuRyKxSIKhYJ/v9XVVYyNjWF0dBQHBwc+RHp4eBg9PT147LHH8KUvfQlzc3OYnZ2tQyShdauMSpl6DFnYdZ3GcO6n3ZdXIkmSknPuuwA+DSDvnGuvoYYJALO102YATAKYcc61A8gBWL3fjoUkvX4O2ReaVTkI806dOoVCoYArV654iUwIPzw8jMcffxxnzpzxW5XRWs6gJatna78psUmgJCrq9GrIpHUeuGuXYIkzwnQG8WgADwOgqLvrPpDKfNifkIRhH3UMyahiMFXHnwxQ3WzarPuN9+C4KWOhlB4cHKyrkkUPEJ8HwIeAM9agvb1aGJdFaclM+Tw1QrLvZAJbW1t+3nkdmQIbmUY+n/fZlR0dHbh8+TJGR0fR1taG5eVlbG5uoq2tDbOzs35n7Ewm4xmWrhc7R9piKnBsbccE5YO2ZrwSQwAOakyhG8DfQ9Wg+BKAr6Lqmfg6gD+tXfJnte8/rP3+1w9rX1DuGVMpdDBCDIPXdHV14emnn8ZTTz2FiYkJX12ItRFZk5D1CBn22tbW5ku9sWKQ9onwWHVYlQIancdNbpnmS2MjA4A05Jh9pr2AKEBtFwzRVr2f707CJ0QH7nUvalIWryNsJnPie/CdNflKvSpayFXfXYlA1TK1OxBN0Quhu0RlMhmfJAZU7TxHR0ce4THIiO+czWa9yseMUxaq4RiRGfT29vpYCgC+QG5fXx92dnbqCs9ks1mcP38eW1tbWFlZwfz8vLfnzM7OYmNjAwMDA1hZWfHl/pgabxmzEr4l5jSSUaFoaSNEDw/SmkEMowB+v2ZnyAD4VpIk33bO/R2Abzrn/jmANwD8Xu383wPwr51z11FFCl97kI5Z4g4dVxXB2hZi9/rYxz6G8fFxTE1NYWJiAhMTExgdHfULmJC3p6cHs7Oz2N/fx4ULF9DV1YXt7W2v51oJTKLnMRqk+HwaFbmRay6X85mU6jojoiiXy+jp6UF/f39dqDHfmaXMuBOU7ROvsWG/zrl7VAQa2gibSciUslRjyJAA1O2loRJfPSuheAISv3p1rD9evQQs4caCOBrfwbJ7fX19fgx0HlhBmxWi2tvbMTIyglKphL29PQwNDfn8E1aBYu2HfD6PiYkJXL9+3QeSzc7OIp/P48KFC3jrrbcwPT2N0dFRbG5uYnV11atARH/5fN5vnMvaGCFXvFUb0tavMgW9xgoEi7jvtzXjlbgM4BOB4+8BeD5wfBfALz9wjxBWC0K2A/u7XVycCG3MUtzd3fXbjZ06dconOeVyOSRJguXlZSwtLWF/fx/PPfccRkdHMT8/7zctIbpQaaqEwpoNKiFJuLlczhvBenp6vLFKg6RoDKQb1GZGcucom/KtKot6P6hOUJoTEVB3Z8gym3XZUWIToWjFIi5K5nuoR0XhvNpdFEXoHPF8jlVvby+Ojo58/UzdDwKAr7bEa5Q5EYEVi0W/GQ0rcGtuCXcpZ3AYERpdj2Ri3Hfj9u3bWFhYAACf/bqzs+NtS5VKxT9jfX3dG4vp3bJqsLXJxFRoe45FG/ZYDF0301oy8lGRQIhBhL6rHq1Wb0URlUrFc/XBwUHcunULSZLg3LlzOH/+PK5evepLh83Pz2NpackvXE304fMYAq32AgDeHw/A2wFYQ5K1GBjqqxOpkYAMu+7s7PTSWaG+rUcJwNs+NCaBMFtdpoT5eg4ZF8uz7+zsYGlpyaOkrq4u7xYkgZB5ZbNZbxNhPQSOGfunrttQ0pXq/xr9x+upvtG9mclk/E7UavfguzERinYBqhS9vb0+7oQuYBp1OT5U11SdOjg4wNDQEIaHh7G2toalpSWf7q67byVJ4tPJGfsCwLuSFdFYwWUJWQWhZQbqRtZzlX4eprUkYwgNDheM9U6EVAsrvdVlOD8/j1deeQVf/OIXUSqVMDU15Tn97OwspqamUC6XvduQ0YK0frNSs/rw1aBEgxYRAXMenHPY3t72FZdY6kwNhiQUBv1Qf6ZfnMiD8RR8V767hiJTIjNkW4utUGXQcdWIw8PD6j4UXODUuRkrUC6XvS+feQPOOZ9OrbYNhc9kUpxHTSwjU6JdgO9EGwOZDJkzGRgrMDGASqtdAfB5FydOnMDm5iYGBwe9m5njClTRBVEDQ7dLpZJ3P7IWZz6fx9WrVzE/P4+9vT1fUYqCgrYPRkqyIjZrRQJAf38/Ojo6sLpab5O3KoK1JaSdq+qafn/Q1nKMwQ5EyNZgmYI9V8NLCQOBu+hiYWEBi4uLvvw3dU7G4ivhc5HRFqD5/wwqInOw1n1KD93khBWKNCCKRMJFniQJCoWCh760SygxEuKSAQF31QyNQdD+0gCqXhGV1CSKtbU1D73ZP6pHqiKo/YK1FPgcxhFUKhVvmVekoB4di144dhQCateg9CYD1lgFupFVGHCsGAdRqVR8TU2iH743N5Oh0ZNGRXp+OK7b29u4ffu290AAd/cZVXcs98Sg+tnW1oYzZ84gn89jfn7eM1Vd+9aQqGvEogb+HrruYVvLMQY2a4yxzEG/hyCVjfLT3w4PDzE1NYXJyUkMDQ0BgM+SVCs5cLd0GTkwFySt27y3egxYnJQLn1mCvG82m/WFXHZ2dnzsAgBP+GQWrEdg4TIXJJv+xr4SxVg7C9OwqXromBJWq62DY6eGSdoZGAPAwrW9vb1e/VLGpfkKvJ/2mUyHhK2qh84f+8F5p8fC5hQoekySxJds09B1RS5sGsPBPSuovuhuVrQ/aC4KGSGZ18rKCvL5PDY3NzEyMoJLly6hVCrh5s2bdSqpEnMjKa8ILGS0VKH0MK3lGEOIASg8shyRRBBiBDawSSdhfn4eSVKNBTh37hwqlYp3KzFgCKhKgtXVVV/jkaGt1JW1vqPC5J2dHR81yW3USqUSBgYG0N/fX2c7IBIgZFXDoYX5lIZWaqtEUwSgqgVwt+CpRveREIC7+1z09PT45/NZfEdmQjrn6mpO0JtA/Z19UJsDG0OKNVJUkQPfVRm/MgA1UvI6IjrNhK1UKt7NTAZN4uKeHER8h4fVWp6ZTAarq6se+XR0dCCbzWJsbAyZTMYbHmlk5NpSVLS3t4e5uTn09fXh1KlTfq+PXC6HU6dOYWZmxvfFGhut/YDHlemFEEJIrX7Q9vBWikfc7AvroGnCkf7Z87RZXUsXHUOQe3t7MTAw4I1RulWbcw6rq6vo7u72278RJlOvbWtr83YBLgwSKYmChi9GN9KARv1ZU3R5T2WE1mCnkN3CTuq7RDjKPKjD87u6QLURPrNaEmE80Q0lqyIXhe8MkqI9gF4aqlxELOyLehRU+qsEJ+NR9YjjoMyF8w5UkRw36dH7kWmqkVHjH0j09FJovU6iRXWz6trl2lhYWMDCwgI6OjowODiIL37xi5iYmMDi4iLK5XJw3nS96vwrg1SV2a5tRboP01oSMYR0KP3NMoHQd4sSrLHm6OgIxWIRp0+fRjabBYA6QlG4trS0hHK5jMHBQU/YJAjaHqh7kqBptDs8PMT29ja6u7uRy+W8pKJRU3MRLDpgX7nw1eui6g2AOmJSBMDz1SvhnPMQWG0EGpjE51PHpgrFsSG6IaNKksSrSwrjOTZWBeQ1REcWCVjUwKb5GaF76neqDbRxkMkD8J4XMgAaKbe3t301aqqXLNZTKBTq1KwQrOd8EjXOzc15I+lLL72EqakpjzrtWrVqnxV+ShsWPegYhsbkflvLMYaQjhQzPlqrbQh+hZgGg2M2NzexsrJSF8BDP7fee2NjA3Nzc+jv70ehUECxWPSuvHw+j7GxMRQKBczPz/uItySpxuvTE3L+/HmcOHHCowatEG03eQFQxzBIsGrB1wXDfR01aEiNbqzRwGeqC1cjFSkhyfSYUUpjqYZ3Hx4e+g1XOK6UvM4574kh+lLDrY28BO4Wd7FNIz3tGlFGr0FWfGdlvmRm3F2qvb0d8/Pz6Ozs9PU1c7mcJ1p6FFi5+9SpU1heXsbrr7/uXZsWyus6pXuU96J6UiqVfN2INJuAXf/KJPQ776MxMw9rXwBakDGktRgXtJJDLbk2Ioy/7e/vY319Hfl8HjMzMzg8PPT7PKjeDMAX+ezv76/zTvA/cBd601B1dHTkYbzCX9ZkpLpAg5ZOLN1uVFV0IZAB2u/sg6oNei5/JwEpA1K0AdRXlVJEwXuSiImwVJ9nhWW7QK19SJmghhxzDGJlyWL6txqJlQGpCnV0dOQ9DUQT/Mz0+lKp5O0fnJ/+/n50dXVhbm7ObwZE43LI8K19Z/AUcDe/Iw35WlTAseJ3FQgcD8tcfmYZQ8gmoE0hHL/z3BBstZwWqBLE3Nwcdnd3MTY2hu3tbczNzfnUXZ2E3d1d3Lx5E2fOnPEZmWtra74SNA1NLE1eLBaRzWb9hJJ4crmcT5EmoahFnNBd35NQW41zOi5qmNOFwfFR6RkaYy5ExilQupLBcTHTPkCiJWHobtlkGIyWVHekzg/fRyMhVf1QF6oaXVUd4v1U9eBYktFYFYweo4GBAZ+NSaa/vb19j2Tu7u726maSJLh9+zZu3bqF5eXle5CPEijXJ/uqCLSZNa5zq4xCBZueY4WfZVgP0lqSMQBh14sOjOWUXHA8jy2EJlRyra6u+kSpEEPhgqLu2dfXh2w2i4GBAQ9VubXa2tqaz4+g8Y+lyWho5H+g3kCkhjy1MaiU5zESPpmLFmm1/bfX8FmKJDSugH3X4rE0QKpUpwpibRvsr6IpXbxc7GpLYR90TNT4qlLSGkqtlFWjaEi68veOjg4fY5Ikic9joXv46Kiaxn7y5EmcOnXKe6e4ZZ5dR6E4A0Vzdh2HApAaqQEh5mLXvNoeQipbs63lvBJA2NViJ8J+B+415ISaJRrLMELPIETe2tryeybqztcsElKpVLztQjMwnXPeE2Gt+CRKJTISFTm/dcOSCO0i4YJQnZPEGTJMqZ5MdEEkoO5GzfTUfmazWQwODtaVYaO7VcfRMgX2kfYAjbfguRosxGfq/FoCsv1TRsjn6Fiq50FjUrhPB7NsR0ZGMD4+jqWlJczNzdVVftax53O06Rqz0j+kguia03lqdF5oHTysOtGSjCGkPwP3JkrZhaLfQ1DKSh97vj5X29FRdRu6d955B11dXThz5gxOnTqFkydP+sSbJEm8US6Tqe40TaQBwOfjc4FSapGYNVDHGraoTrDPdmFqpqOiJystlWlwoSozopuRuRF9fX3I5/PeVmIXM9+bEaTMBqW01qxOlZIa1szdo9Q2oP2lO1PnX+0VuqeEjivfj7+1tbX55CjWceBeIDS4ZrNZH+laKBRw4cIFPPPMM2hvb8eNGzd8GjXfX9eVdS1aCR5bk1Y9iDGF0PmhFmIWD9JaUpWwUiGmToTUDXuONit57WfblAkdHR1hZWUFKysrKBaLGBoawsDAAMrlMjY2NrzEYu5/b28vFhYW6gqMWFipBGx1aWUGQH3oskpDhcwkHGs/0GdapKTwmkTKe9IAyvO0P8p4WHtSmZoyMoX3VCOAeherogMAdaHedo7UdqOGPo0DsQJE+350dFRnO9H7Ouf8Zjejo6O4ePGiz5ugemX7Elt/IVXBfk5bi2no1659i2DS1nUzreUYg9W/VK+1E2yZRUjixwZPCUwJKjSolPQsE8a9DJmLz+pOJ06cwNzcnDfiAajLTSARhvID1I1IIx6Zg/ZHJbwGvFQqlTpiAu76/BVm891p5FQiteNDj4p6GUIoht4Toier9yrz4fmheSGjJPQnMwq5BnkfogFVm/RcRQ6s6Um0wPvT47K1teUNtf39/bhw4QJ6enpw5coVv59FI2JX243tbzMoIISU7f1iqNrYYNkAACAASURBVNcK0IdpLccY0vQq/R7jorHBV0JSnY+TrYvYwkRlDD/60Y8wMDCAxx57DBcvXkSS3N2nkjUDuIlsLpfD2tqaL3POhB2LEEiEJB6rPtlxICOxjMUySJXyFm2Q4dgFqYyX6g2lKlUWuls1+jM0LzxX4zF4XJGRnTMbFBVyUfI+GqsA3GWcjM4ko2Ilpf39fV9yvq+vzxsbuSFxPp/36fG3b9/G97//fUxPT2N/fx9ra2tRJKBjHhNUIcSqay5EzHb+Y+jkYRGCbS1nY7CD2Uhva+Z+bCHEEOLG+jsnkwtuenoab731FpIkwalTpzA6OorTp0/XSSRCzsHBQZ9QxZgAGsBUKuiC4md1takU4Tkaf6DGPV0o9hq+Gw2KIQmj7lAiCw3DVuZxdHTk301RgEpNfZ7mZej8Ws8LGSXfybrkdG7VBmGZqx5XtyTnIkkSH2PCTMmenh7kcjk89dRTOHXqlH8uU7DtOtKx07WTFnug72mv0+/8HLtW7821+qgYRcsxhlDjYowNJFsIRlkCD7n1LKOxx/mdhqq33noLly9fxvDwMMbGxjA0NOTj8ZMk8THy3C9B8/Jp/CJxq7U8SRK/gLlwSUhKuEq81tKv76B/ZDY0cGp8Ae+rCINoQL0BdGPymayJwLgGXmMZA9/Jqm3qIlVVQD0ouuhtCxGMoii+Cz1E3AeEBE5DKxPK6ImYnJz05fx2dnZQLpdRLpfr+mMFlkVksbWpCK6RcNN1GLpfSL2Kjcv9tpZTJdjSiFyb5cj6P4Y6rA3C3jv2TBYGLZfL+Mu//Et8/OMfxzPPPIONjQ3cvHkTvb29dYv48PDQR0Fubm76iDrnXJ0LkNKW+rxKPiVYSkIlKBK5xujzWi5CG/BDpkSVQIOHNMBIE6z0vXgOx1HLw7FPtDnY+ARFA+prt+oC+2jtIxr/oHPPc6n2UX0g4mGtyM3NTZ/AdOLECaysrGB9fR0DAwPI5/N48skn8dnPfhaFQgE//OEPMTU15Y3IITtXCNFqs+swJtRizQone7+Q2snzHqa1HGKwkk5bSGrcz/UhqNZoYu19mYRTKpXwox/9CJlMBpcuXcLIyIhfmJlMxjORXC6HQqHgs/gYK0ADJW0MJBjq3CopKe2Y0BQL3gFQR+AhOE3paBcU76s2ECu5eZ5+1gSr9vZ2nz5uC8jwPfW9LLLQuVG93Kovyti0nzymmZZJknij8cHBAdbX1311Lu5YzizSXC6HS5cu4ezZs1hcXMSNGzdQKpXuyYQMCZiYdLfCyRJvSNCF1l5onCwCSzv/flvLIQarX93PS1rCD6GDmJrQbNvd3cXa2hqGhobw/e9/H6Ojo/j85z+PCxcu+JgFEvLs7KzfnIQp3lp5SAmXi11tDJx8K7m1qbRXg6L1WpCQeR8tGqstSRJvdEySpK7sPNPNrfRSJmPRjBI0rwmhOauT62/aR0VMRAfKzPQz/7OaNNU5MpOtrS0cHR2hp6cHJ0+exJNPPokLFy74BKuFhQVf3Yt9V7Uuts7YQkxEmYFd2/Y8vY+dI/scPf4obAwtxxiAey3wMenfSNqE7qfHrG4YIz4e433X1tZ8ebFvfetb2N3dxYsvvoiOjg68+eabPv16Z2cHKysrPiKQNRQJ34G7lZ+sDqqNBEY9X8ONtSncZlMGYYnKxk7wP9WETCbjt4ij+qBJQLQbqLeCjcZGzp/mLHAc7buyf7bSdQjd8NnqEclkMp6I6ZGgWsRandzTg+OYzWZx9uxZvPDCC/jEJz6BXC6H1157DT/+8Y99ur2uK7UfhFQLXSu6vtLsWLxG/4fWgTYdb9uHZuwXjVpLMgbr2oq9pLUL6ATofwvt7IRpi6EUXQRcaNvb28hkMrh8+TI+//nP49lnn8Xu7i7u3Lnjw2xJaAyPrlSq5deJAnZ2dnyVIM0t4DjQXagogESqTYOS+H7WIMn3U+lNwlJ7BIC6vlDtIcHyXU6cOFFnPCQC0khEIhnLtNlXnQOOPZmUDfAiU1B0ZMeBx9UOQbTG2ps9PT3Y3d1Fb28vJicnce7cOXzsYx/D2NgY5ubmcPXqVZ9Wz+eG0Kf+t6pETGixj4q89JpG68+uRWvoVLX0YVrL2RiAe6FZCBZZ7mt93yF4R8LU7zHUYK9T3ZjHZmdnsbOzg5mZGVy+fBm9vb147rnncO7cubrQYCYiAVXCY9yDTiqJnVZ9Smd1v1Fak/DUs2DVCRtMFBtj3ofP5ILi83d2djwT1LwG/q6Rm3xX3jdtHrmA1R6i5yhj0YhK9kHfTd21ZMTcW5Q7UNO2wnRrbkbz9NNP4+LFi3j88cfR39+P119/HVeuXMHy8rKv7GyZgPbfMoKQ/UHtHTwnxLR13mwLCbGQG9eu8QdtLYkY2JpRCXjcwjt7PO2eek0skIb/VXrs7u5iamoKh4eH+N73voejoyOcO3cOL7zwArq7u/Haa69hdXXVJ95wp2ruNQCgbp8G7Q+ZAIA6tYFJTqF6jhr3YPVNlS6haELV0fUdWY+SdhNN7uJ7aXFWNcCqVyKkY/N8K5F5jqZz07XLZ2mJeE1Vr1QqnunSC8HoVHoqGNU4OTmJ06dP45lnnsHExARef/11/OAHP8DS0pKft5B6qdLdrqXYmklbc2kqhr6XZUJp9/iZVCXYGr2c/h6CdPpbI6NObHLsJFjOv7e3h6WlJdy5cwezs7OYnJz0WYcMkGFxD93zgJWGaYjc3d31qc3U7SmVk6TeIKgQOpR7bxkYgDqprOfF0AQJQushkihpX6lUKr4kmpa74zMVrVh1QRkUmyIg/k5VioVoVQVRVEG1iONCRqL7R7S1tfnoRronL1y4gCeeeAJzc3O4cuUKlpaWfE4Mx81C/dCasuuOfeI4hsY6ZsgM3T82byEbRSP7RDOtJRmDJfiQKhFqjdCCPc9K1VA/QvezC2V7exs3b95EV1cX8vk8Ll68iJMnT+LOnTt+J2QSCQ1ijGlYX1+v80Jw4WuUII9pGTZFDNoXDT8O6aT2XZSxWFel9SRw81zCeaZn83mKSmISL9QHZRYhKEyiV8ZjGSMZBXeFKpfLdUgBqDKqYrGIkZERDAwM4BOf+AQuXryItrY2vPXWW3j77bexvr7utyYMhcfH1pYl7BhR2/UXQrQhFSyEDELf0wzo99NakjHY8GCgvhRYWgtxUF5vA1Nik2YtzyFkoQvg8LC6c9PMzAy+/e1vo1wu4/Of/zza29vx2muvoVQqeeu+c1Vj2Orqqi/DzuexpBoXOxc/JSEZgt0CjlDaEh29Ataqb/VfG0+g0prXEtXo/XQnKPU+8L76PBIugHvUByIv++68H/unTJDzRONte3s7lpaWvHuVUaa0O7By0+TkJE6ePIlnn30Wn/nMZ5DJZPD222/jL/7iLzA1NYVSqeRzXrR/90toIXXBIjl7X7smQ7+F0IJlqA/SX9tajjHYl7JQLsQcbBKKLsYYd7fHrJQN9Skk4fg8VnE6PDzE22+/jU9+8pM4e/YsDg4O0Nvb6wOUNBKQBM3CqiwWS2ajsFQ9ErrLEyE+jW76Lmr1t/BSrfeW8SkB8v1s0RjmGGj2qC5Q51w0dVq9NeyfGi2pvtgaFVrZmu+j3h2tlcDvNOiOjIzg7NmzPgHuiSeegHMON27cwPe+9z3vhVhZWYkSoF07jVCp/RyT+iEmYQWhfZauyRCqedjWcoxBW4h4Q1zUujZjcCtE0EB98pE+RwfeLmz7e5IkWFxcxODgIKanp/Hmm2/iq1/9Kk6fPo0nnngCh4eHuHXrlt+Dcm1tDYeHh764SSaTweLiIrq7uzEwMODRAFGFJhVRwnLTGtZj5Ma7NBLq/hjq8gRQF0VJ5qDWfz6P4c608pMoNQlLdX/VqTXmQeeC55EB2nqOytRZL5HMl33W4LByuewTuYC7YeKsej0xMYEzZ86gra0Nn/zkJ/HlL38ZAwMDePXVV/Hyyy/jjTfe8HaimI4fEi52PYbWXGz9pgmrmIphxyfWHoVXouXclfrSFgLbZjlwiKuGrglBOCVwq5vr7/a++pnusc3NTfz4xz/Gm2++iSRJMDY2hvHxcQwMDHgPBKX88vIy5ufn/caxq6urWFxc9EYz/rdjQgs7dX0a6Ei0RAwWYioB8rsyOZXgfCe6+kioLD5DxKP30XEh8eof+8RS/UpgfIZ6XYiykiTxKgOJpFKpYHV1FRsbG3VjdXBw4NOou7u7MTo6iiSppllfunTJb2X/zjvv4Pbt21hfX8fa2lodE0pbM/xsEaZdh9aFbpvOqV1joXUbEmr29zQUcz+t5RiDDrjVhe3gsFldK3Q8bcJjDEDvwwUca1wEjLC7desWvvvd7+Kdd97BiRMncPHiRYyPjyObzSKbzaKvr89H6hHuZrNZdHR0YGdnxy9U/mbDgkkkmu5MqU9mwU1xKeXTYjRCdgabl7Gzs4PFxUVsbGzcw0y0bzrmoWepGgGgDlmQoGi30DwMZVp7e3tYWVnxm8NoURomTLW3tyOfzwMAuru78fzzz+PMmTMol8t477338Nprr2FqagrLy8t1BYHTVAmdb9tCUN9+DzESXXex+IYQ8rK/x+jjQVpLqhIqQUIDYvW3EJdthBys3qf3UvRg7RehPmhfkyTB0tISkiTBq6++6isRf/azn0VPTw8KhQJ+8IMf+IXPvQp2dnZw/vx59PX1YX19HZubm3Xb17F/RAKE8oTMzNa06gDP15gBteJbtMSm79PR0YGuri5cv34dy8vL6Ovr88RJVUJTurX6ElAffEWit3OijE+DmIC7cRxELltbWz6ZjfEV3E1sdnbWG3vz+TyKxSImJyfx4osv4stf/jJmZ2fxwx/+EFevXsXf/d3feUanaEWZQ6M11mj9hZiD/c1K+hBTarT+7Lw9bGsaMTjn2pxzbzjnvl37ftY59yPn3DXn3B865zprx7tq36/Xfj/zsJ20EC40uPZz6LseD6kT9v5pUWh6L72WujAj527cuIHvfOc7uHr1Krq6ujA2NoZTp05hcHAQPT096OrqgnPV3a5WVlY889jY2EC5XPZhufv7+x7qZjIZD+OpNnDbNBI/cHcTHLUBaIgv4yQUldhELjIQog9KbH1vVRmIGJSxWG+D+viVqep4spHZ8DyOQ6lUwurqKra2tnxl54WFBayuriKTyfgdws6dO4fnn38ezzzzDPr6+lAqlXDr1i3cvHkT29vb2NjY8CpYzGZg10tMrQz1PybUrGoSW5eK5CzCUC/Uo0QLwP2pEv8EwNvy/TcA/GaSJI8DWAPwK7XjvwJgLUmS8wB+s3befbXQYOuLhybGErJVPax+Zo/ZQW+mb1an1M/ciGZ7exuvvfYaLl++jPHxcXzmM5/B8PAwisUiTp48iWw262Hy8vIyVldXvYRkyq8a1VTfV7clbQ5WYth3VLWBUYX8rzEQDA7iO6rFf2NjA+vr6z5YS+tZ6tjYsG0SnxpAGXdgCU/nURnjzs4OlpaWfLgyq2jt7e15z04ul8P4+Lj/e/rppzEyMoL5+Xm8/PLLuHr1Kubn57170xJp6HNo/vWctPP4Pvb9dT3G7h9Th5tF1A/amlIlnHMTAP5jAP8LgF911Sd/CcA/qp3y+wD+GYDfBvCV2mcA+CMA/8I555KY+A40iwpqffCfbZwBj+l3S6ixAQtBtNAC1X6knaPMaH5+HgAwODiIP/7jP8b8/Dy+9rWv4Stf+Qp+8IMf4Kc//ak/b2FhAVtbW7h69SoKhQImJydRKpUwPz+PSqWCfD7v4xLosSABc0MYSnbrOSDR2vgBhfjAXTivQU/U3enhoPFRXZHqxlR1hbYQIgqV/uyD3a2b1/K+qp5sbW1hZmYGm5ubOH/+PAYGBrCxsYFr165hYWEBnZ2dyOVy6O/vx8DAAEZGRvDss8/izJkzWFhYwEsvvYSXX34Z6+vrWFhY8HtLhmB8bC3E5j323UryGDqKrc0QMtZnWEYWU23utzVrY/gtAP8UQF/t+yCAUpIkTG2bATBe+zwOYLrW0UPnXLl2/rLe0Dn3DQDfCD2s2cEKXRNqjeBe6Ny0iU6zIlsGxm3QOzs78corryCXy+HrX/86Ll26hL29PczPz6O/v98bGg8ODryO3N3djc7OTiwtLeHw8BC5XM6rEQyYInKgRNeybzTqhXa+YlPLuS5eLjhuA++c87EYfGdFCjxGwycbUQ3vq8RPpqVBTLwHVR71NMzOzqJSqeCxxx7D0NAQyuUyZmZmsL6+jvb2dgwNDaGnpwfZbBaf/OQn8fM///M4ffo0FhYW8JOf/AQ3btzAwcEBlpeXsby8HFUdQsLFflcUYNFpaH2FiDyN6PU6VRlCcT1WuD2KkOiGd3DO/X0Ai0mSvKaHA6cmTfx290CS/G6SJD+XJMnPxZ4disqrXav9a0igoWtiqCR0P/0cs+7H1BIaGFko5PXXX8fU1BRyuRyee+45XLhwAYVCAfl8Hr29vX63qqWlJb8rc6VSwcrKCpaXl/39tSoR7QSKGKyxj8E+9h0I1TVd23qF+B7cnJWZovq+VBs0IEmrQlFd4ThpqLdGKCqTU0lICT8xMYHJyUmsra1hZmYGpVIJSZL4qty5XA6PP/44vvCFL+D06dPY2NjA9evX8e6772J6ehrz8/NYXFy8Rz216oD9HkMPFhGEGIC6h9PWi95bz0lb7zEm9LCtGcTwOQD/wDn3iwBOAOhHFUHknXPtNdQwAWC2dv4MgEkAM865dgA5AKsP0jkL70JN9Vf9bnVWy2HtBFhdMcQcFObaPob6RQI4ODjA22+/jfHxcezv7+MP/uAP8OUvfxmnTp3CF7/4RQwODuKnP/0puru7sbq66usSrq6uoq2tDfl8HpVKxRcOIVQmaiAhsdl6i1pbUrM2teaBtcaTQQB3azJQOjKYiMRtd7xWr4iOvYZ/sz9kSFr1SceWDMA5h09/+tN+LOfm5pAkCYrFot8seGxsDBcuXMCLL76I0dFRzM/P49q1a/jzP/9zLCwsYHt7GwsLCx71xIhdGZf+FmL8acSuazOGWkNEHRJyVtiEGBGf9ShaQ8aQJMmvA/j1Wqe+AOC/TZLkHzvn/h2ArwL4JoCvA/jT2iV/Vvv+w9rvf53cJwsL6ZrNQDP9jfeJXZP2bP1vnxODcHZyVPo6V/Wzz8/PY2JiAleuXEEul0NbWxv6+vpw5swZf61Wdtrd3cXW1hbK5TJ6e3vR19eHzc1N77/v7u72SENhPS3/RAYkNqoNJF7mEOgx9kElOxnM0NAQVlZWPDphtSS+P+8fkpjKsLUKNq8lE+HC3t/fx8bGhk9r5z4PpVLJ7/aVz+cxPDyMzs5OFItFfO5zn8Pzzz+P0dFRXLt2De+88w6uX7+O+fl5bG5u1uVB2HUTEkJpDCB0PIZaY6pD6PxQUF9orVuhx2OPAi0ADxfH8N8B+KZz7p8DeAPA79WO/x6Af+2cu44qUvja/d44BGVjsC5E7Gnf0yZSz42dF3quVUusIZR6H0u9ZTIZ/O3f/i0A4Atf+AKGhobQ3t7uPRJtbW2Ynp72lZ64YQ1/a2trw9bWFra2trC7u4vh4WH09vaiq6urTtKzD2RMjC/Q6EEWQ9XybBxfxktQXRkYGPCb9wJ34wr4HM1+1Hcno7JGY+2regc2NzexsbGBjY0NZDIZDAwMoL29HaVSybtvC4UCcrkc+vr6MDo6irNnz+LSpUsYHh72VbTeeustXLt2zXsxWAJe5yTm929GiOhYpaFadcvaebH3CbU0IaTXa98ftt0XY0iS5LsAvlv7/B6A5wPn7AL45YftmHV/xZhBSA8L9Cl6LKYy8LfYPawqkvabwurV1VX//eWXXwYAXLx4EcViEU899RSKxSIKhQL6+/uxurqKlZUVOOf83giVSsXnQRweHvrErWw2i/7+fuRyOQB3mZNNkqJawDEmnNf8BfUc8DfaOmjJZzYky9bxGVpUhsRHolBXKNWHo6Mjz+QYK7Gzs+PRVGdnp2cSvH+hUMDp06fR19eHc+fO4bHHHsOTTz6JiYkJLCws4PLly/jud7/rA7KWlpbqGJrq/KG5CwmCkBBolhhjCFb7YO+ZpurE1mIjRnY/rSUjH+1ANdL99b/qc7ow9XxLKI3UFD7T6p0hTq99jkkTliM/OjrClStXkCSJX+DDw8PIZrPeTdnZ2Yk7d+74Ha0YPwDAb89GoqIEP3HihN8MRt9T9WceY9NKSzrmRBNHR0col8te8q+urqKvr+qkYkKWc66O6TD7Uj0PjH3gPbkzFN2Rm5ubfou4TCaDtbU1X1Ohvb29zr4yPDyMF154Ac888wwGBgZw48YNXLt2DdeuXcP09DSWl5frwqY5hzp/ds2F1piur0ZCyK67RkyBzc5Js32wgrEZpNNMa0nG0Ajua4vp9jH7Q0hvS1MflLhD54YI3zIruwArlQpKpRKOjo5w7do1X1NxeHgYuVwOp06dwsWLF/Huu+96w97a2prfe5GExGxD5lxw34re3l709vZ64tIsSkViLLQCwGdOauEVqi57e3tYXl7G3t4eenp6sL297atPqY0ipEJwfNRToehje3vbRyAeHBx4hsZ8B41K7OnpQU9PD9ra2nyMwlNPPYX+/n6srKzg2rVrmJqawszMjC/9zpL+dp6sAS+ku+v8x9ZcjFhjRG3vE3uubY2ecz8000xzj+ImD90J5+o6oSXBtcX0LMuhQ8QfeW50wtKep88NPSvGzfU8HiP8z+fz+MQnPoFPfepTOH36NLq7u7G5uYkbN27g6tWrdUVZDw8Psbi4iNXVVe8hsM/p7OxEoVDwG+lS/WAdBTIH7ssAABsbGzg8rO6exfTwcrnsCWxiYgK9vb2+JiJQnavh4WF/X2WkGs9AxKIqEXNCCPOZMMUK2x0dHdjd3fVIYXh4GBMTE3jyySfxpS99CaOjo+jo6MD6+jree+89vPTSS3j77bdx69YtHzB2v7kDaQSYti5ixJrGYGwLPTO0hmPPt4wv0F5LUsIDtLUkYmCLcWCralh1Q8/jfRpBOXvc6pBp/bHHtD+WSVi1hDo7ALzyyitYWVnBpz71KbzwwgsoFos+TZu68tzcHPb29lAsFrG5uYm5uTlfioxSmfEATOBipaXd3V2flKUuRnoXCO/X19dRKpV8lKNz1boQQ0NDyOfzPgQbADY3N30QVzab9dmMfE/mcdBuQRSwt7fnU6M11qFSqXhmdnBwgJ6eHuTzeQwODmJ8fByjo6MoFAp+R6/FxUWsrKxgdnYW169fx82bN30ORYQ47pnntN9COr7OuV0Xac+IMQerdvJYTPA0QhWPorUkY9BBaVZPCzEO/R76TScjZNmNqSNpE6AMJYYW9DOZQyZTLQD77rvves/Fxz/+cQwODuL8+fMoFosYGBhAf38/dnZ2UCqVcHBwgEKhgEKh4I14m5ubdaXSDw8PsbW15Q2I1gbAOo6sj8A4BxIrk7Vot2C694kTJ9DX14e+vj7Mzs76yE2WVqMaomNKYykDs5xz9zAqxmWwLibT1MfHx/ELv/ALOHv2LLLZrM8jKZVKuHHjBt577z1f10JzRuz6sUTI36wtyhKqzrudw5h05z1j68iuA2v3CDXbx7T0gIdpLalKKAQFwnaCGMQKEV6I4Btx8kawLnaNTlZMXw3ptkAV/pP4GeL73HPP4cUXX6yT0vv7+1hZWfF++f39fSwvL3vIv7Oz47dfI7HqLs82epPuRPZRt6znczs7O30Nif39fSwsLGBvb89HahJhAHcDrGj/YJUmvjdzPVgSjsiF6g73v2Q26tmzZ/0fy+Rdu3YNy8vLuHz5Mm7fvo21tTXMzs5iZWXFqyI6xs2oAzFCC+nvjdCErrXQ9zS0EiPwNLVVzwlFC9faR1uVsIQY06PYQtCfn9OizvR7rB/8PY3B6LEYBNXfQ/dwznmC29rawujoKBYWFvDKK69gdHQU4+Pjvgo1C7AmSeL3fOjs7ERvby/m5+frSr7RlUkGQc+AMgMaEAF4KA9UGQY9G0mSeFsA/+h2JOpgJSmGR5PQiTB6enrQ2dnpDaH7+/s+8am7u9vnlFQqFeRyOYyNjeH06dNefWhra0O5XMb09DRef/113LlzB7du3fIuTu4zGSIaG3Ng50bnzEpvu/4swYbWX2yNxdRUe7/Qc+19gHCZwUfRWhoxpBEZW6j/aZy4kRoQkggN+h7sZwyqhs4B6qtYVyrVbMqhoSG0tbVhaGgIExMTdaXPx8fH/f6Y1Kl3dnZ8mjaTsRjnQMZAwk2SxNsinHPes0HipEqSzWa9bYDqhd0JigVbtOZCe3v7PYZPzbTs6OjwqkhfX59nLN3d3RgcHMTJkydRLBYxPDyMnp4eHB4eYnp6GktLS5ifn/fbyDGnZGlpCaVS6R743mit6DyGzkmSpKFK0AhJ2nNiLQ2BqMrS6J6PAjG0JGNQX3NM70uDZTFmoeekxZuHnq3Heb1+T2MQ9nMIxShK0oi8/v5+jI2NebidzWYxOjqKixcvYmRkBLlczvdhf38fW1tb3gW5vb2N9fV17O7u+v8aFMW8B0p46uabm5vetkCvB12bWreRfdX9L7nbFgCPDqgWtLW1eXdkR0eHL4Tb1dXlE6BOnDiBsbEx9Pf3wznnt5hj4BLjE0qlEkqlkt9gWNeNHddGYcZpGYsx4ktbH1YA8D4qHKyqE7qv9inEmGy/FNH8TKoSbGkDn6ZjpQ1c2r0aPRu4K9nT9NDQorGIQM/V6+3iLJVKqFQqyGazPstybW0N+/v7ePzxx1EsFtHV1YXBwUFks1kMDAx4tYQpyElSjSlQmwRjHnZ2drz3QYON2CfGQRBx2J25NReDYdXOVYu3MIeD6KGnpwcnTpxANpv1KkZ/fz/y+Ty6u7u9B6KnpwflchlbW1vY3t7G4uIipqam8N5772F5ednnj5TL5bpS8uxzSEhYgtXfbOBaiDDt2kiD+3o8bY61pT3HqtP2J2DaSQAAEzRJREFUHMvIHoWwb1nGECLw0KDY7yGoFdK/QugjDSHY+4YWQmjBsOnibQZS8pxMJoP19XW/YxWTq46OjjA3N4f+/n6cPn0axWIR+Xwe4+PjKBaLGBwc9PUQ6W2ganLz5k2PGk6cOIFKpVJXeJbVp5RwaIy0i5BRjx0dHd6OwM/ZbNb/7+7u9oFXdIFOTk4in8/7HA+qMzMzM1hcXMT8/Dzu3LnjPRCzs7NYXV29J5s0TcrrMTuvPKZMm79ZA3KMWSjhhtSJECKwfbZCplmVIXSPR9ValjHEWrNMgueGJsJel8ZhQwtK/+s5GlUY619ogdl72e+6aGk74H4P5XIZ8/PzKBaLGB8fx/z8PPL5PEZHR1EsFtHZ2YmhoSEfSdjR0YFisehdl4SdDHpyzuGxxx7D+vo6VlZWsLi46DMZx8fH0d7ejps3b2J2dhY9PT3epkBEwBL5LLHW39+Pnp6ee9yjRDla7ZqZo++++y7K5TI2NjawtraGzc1NrK6uolwu121ga8c1DUWmzWsIcYSYQuye9tkx1SP0XVFkI/Uk9i6xPj5Ma1kbQ0zC8zNbDII3OmaeH7xX6HNs8iLvVaf3xaBmrG9Wgui9qCZws9ajoyP09vaiWCz68vSnT5/GyMgI8vk8+vv76zZqob3g+vXr2NvbQ29vr0cPDA6ijWJsbAyTk5MYHh5GW1sbZmZm8Pbb1fKfOzs7vsYBGQi9DM459PX1+TBrVnKmauHc3a3wNjY2sLi4iJmZGdy4ccMX06XHYX19HRsbG3XM3raQ2hCbs0ZrQu9pdX07f2ktxmhCaJNz26hP9j3s+6fEMXy0jY9cMI0IJk1FCDwjlej0fmmfm3iXoKphf09b3DGmETvXOeddgr29vb5q8sjICAqFAnp7e5HP5z1hcldtlo7b3t5GklS9Cr29vSgUCnW2ADIT5k2Uy2WvRjBqksZLdVmyTiXdo845H+vAGpWshL28vIw7d+5geXnZV2bSUnJpY5rG6EMCJS3VOs0wHGuxOYvNW4gBpK3xRn2wv/3/hjHwGJA+6Gnv0szAhuBhM0xBmUGsjmCzENNeE+pfqG98fkdHh/9jUBLTuNva2tDT04OJiQkfi5DNZn0tBNZ0oMeAjEGZQ5Lc3XVKU7tJ/Nxu7+DgAJ2dnXXl5ug1ISPq7u72CVQrKyt+j42VlZU6z0iI8YcYcMinHyNYnatmdfqYZG90Xege9rOdVz3f3jtNbQIeDWNoWRuDTlxMWliIH1os+jltkdj7sVlkEWIwMQIO9RFI3xQkBiljcFR/A+DrPzIq8ejoyMc6tLe3o6urC2traz7hSSs0kQmQKVAdoPtTd6Cm+sKNbhi7wGIozt2NbGxra/Nb95FB7O3t+VTyxcVFr45sbW35TMvQmIbeWyF0I9iuc2pVA5shGpob/a/3CxGj7Wto7uyai6HfZpDSo2wtyRjIFOxEp0HGtAFNUwvs7/wequOg/xv1X58VWgR2IYT6aBdT6Lhteg+6HxmazGuo9+txIgLWc2Adxe7ubgCoKxLD2AQ1nGmRFwB+qz3GQDAsW6s+MR6CNgTNFNUWkuyheQvBbzsnOpZ6XSyMXcdVmbb+nsbEmxFMafNozw8xSH32o2otyRi0hZhBTHI3YiAA6hgO7x8b1BgTCU1GIzUhJj14nqKJ0P1i0DEER5WQqDLo77r9vO5RwcZkLAYlab8YaKW5D5p7QfTBplWbNIiK57N2pCY+hZgm/+t4894xBJdGPDFUECLoUF/sZ3v/ECoInRd7fuj+sec3817321qWMTSC7VbCsoXgvF4bQw/2WTa2PkTM+p/3C4Xkhq7j51CiTOh4Glqyz7eJQPb5+m4qoXVxMRFJ60My2Ende7p7FZEH76PJcFpCzo5zaK7TkBQ/W8LQ60NqaBqB2rmOrT2rasSQRIioYwwhba5CzE37EmI8j6K1LGMA0v3HzQ5ICL7r8dhEWMIPEbddiGncPgSH0yBvDD6H+h+D1Wl9DjEvXWgkcru9fRrSijFR20IG2kZEFRq7tPfV+zViljFpGxvDUB9D7x46386VfZ9mEEOIkT/q9miK0H+AzUoKNgsBY+dZhhIiDj0vhD5C91VJGWIs9lo2jZkPnaf9CDEUMqRQBas0WG7vHWshSaVjrP0PSdOYhLXPDuU52LFJe7cQweg7pEl629/Qu4fG0vbTrsHQ3Nt5DfXD9jnExG171KihZRlDjHjtOTGYGbqXPZ62KOz1loBs/2JMgiqB1fN5XWix2GO2fgJwL1QOSXz7rpbIQ8Slx2PoRo+HVB57TWgueR8ytpBV34YqE8WkzZM+I/R7Wp80arURA01DW2nMONSnGBKKrTdt7wdaAFqYMWiiUmhB63+2mMSOQdsQImj0LEs0jVQDvodlQsC9yVQhpBGSsPpsO0aWkPQe+pn/Y242S4RpklTfM3RuaIz0GYo80sZIGWQMlYUIJfZ7iBGnBT/pf94rRLz2WCMBFEIMMSEXe4+0cx+ktSxjAOIvahcXmxJso0GKEV6I8+s1Ic4eWvih/tnr9HsM5ehnXSyKSkKII60P9p4hyB87P4RwQsgn9I7AvSpX6JxmGJaeo8/lMWVUoSItofFJI7AYygqdH1pDobUUUw/S1m8IycWQzMO0ljY+AukqApBuENJjockMSX2eG0IBIQLQe6dJGntvvSaURxHrW+idQ/0PvXMz97L3DTWLWEJzlPbM2PMbSU2LkkJ9DRFujCmkPZPzYvth+9tonLQf9nNo/ELXxtYjP6sx91GhhpZFDApR9VgaodvrYwTCFiOS0EKMLfA0pmCPN8s4KBEpAWOLMbTI7L0bScFYUY9Y0ZMQFG8Wpdmm52vJOP3dqhKh97RzoPcJzbmV5jGBEkNRVlhoPxpJ7EZIwfYzrX+2r7FzH6S1LGNgswsvjUjZ0hhIiJBDE2AnUBeahd4xWBeyqusz7fmhqlC2n7Yfeo80ZhmSOrFU39jYxjwvsZiLUN+sJFTor/9DBBZSHfSZobkJMTJ7PDYGMZhuy/TZ89IQgj2mzw8JkUaCJ/ScR9FanjEA6bCWv8eOhyY8NthpEtdeG7uvwjoN3rH3DC0Y+8wQfAy9cyPoHCJO9jXt/WPPsc32qxnmaxmVRUGxgquWuEPf9XzLiBoRWDNjETLKhhBc7HrtU2hu9dxGiC/teQ/TPhKMwbZG3LEZCRhjGtrSJE9sUqynIeZdsQsqtKjsYrOL3p7brNpiFySfox6CELHFWkyqhvoSIuYQMrLIIYQC094PiBs6Q9dZJqJ9CDFrtlDgVCPVKoTklDmG+htias2s4QdtLc8Y0l70QXS6GCHp82Lcuxk41yw6sIsgNvGhe4cILaUA6D1NozRDBBpikPo+tm+h8Q0xFmUasXFiH0I2ghijtkRtj9nzbUtDgWnPtfObhvBifYitx9haaoZhPIrWsl6JRurD/ZyT9j0mEUMTk3auvWfoXraMlxJAM6gidG8GAYXgeKP+WiYVQiT6To3QQ+geIUaSdg+bSGWzbEOBYo0YryWq2Fxa4k8buxDiCt0/hPpiv4XGqRnU+KhQgraWZQxA3HjWTEs7PzYxVoqmSZDYYuT/GHwOSTd7b9vXkE8/bXHpMa1DaZ8Vuz62SY/e27rI0hZ5bDGHmKEdL3sP2zcL92NMz/bJjpf+HkMHMUGRxvzseWnM0q6NtHVmx4rr5FExiZZVJZpBAzwPiMO9WGtm8u15VjqkQeyYhAwt4Fi/Qwudnxv11eYw2PNCf6H+xvoTMsA1kmwx6Rd6N22hkPDQPXheiGD1u/YrTTjY8Q+dF5uDUB+baWnjY5GPfbfYGD1Ia1nGAITzC2ItRohsMWkUGnx739iisPcG7nW3WQYQkzqhZ1tUYJlICMbyPiFCCDV7f/s+tj/6njFkpN9D7kdeZxeyHQdeo3EJIXetvrNKTRtCzWMxYrZjpv2KMfeYpI+1tN9jyIt9jK3R90OlaIoxOOduOed+6pz7iXPu1dqxgnPur5xz12r/B2rHnXPu/3DOXXfOXXbOXXqQjsUGsNGg2+vtoIWkVKg1gpH2PJsMZCVNiGD0/FiLBfVY4rcEos9SBhKTQnp+2r3tNaH3Zb81UCs0pqG4CJV8OoeWCSjBpwUz2ViN0Dm2b/oOoWaZc1oLMaHQ/Nj+2D7GxvH9aveDGL6YJMlzyd1ikr8G4DtJkjwO4Du17wDwHwF4vPb3DQC//ag6C8QNTbFz035r9D22KGPSOTapockPxfRbBBAjUPvuIaLnn0rbEKMMvYvti32mHg8da9RXiyTsM/U626eYTSHUR3v/GOrT+dAWKqITa7F3T2M89txGz4hd8360h1ElvgLg92uffx/AfyLH/1VSbX8LIO+cG32I50QlViMO2mgAQ9zcEk+MMEPfGy2cUH9sBSMrifX6EPpgC6kwIXQQ6lfoe5pUTENiMSJvNHZ6LJR1yt/VQ2GJPyTpQ8ygGeKz948hv9h8hBBe7PwYU0nrWzPHHqY1yxgSAP+vc+4159w3asdOJkkyBwC1/8O14+MApuXamdqxuuac+4Zz7lVXU03ueaAQZYzrhwj3fhFF7JlpLTSRsWfzc6gvsfuE+pQmSUPP1O92jKwE13N57xg81/uFiCyEdGJ9s+jI9smOTQzd2PPsvez9lBmHCCq09hohoJBQCd3Xtgch6NBaaaSS3m9r1l35uSRJZp1zwwD+yjn3Tsq5oTe9Z0SSJPldAL8LAM7sKxE4t2EHG3Hd2D1CizMkWZqRNJbo7LMt3OYxvTaNicXUgPuFlo0ISokhRjj2fWJ9SWNeMcZir+NzbO5JDJ7bd2rEmGNzfz8C5UFbGmJrtB4f9tlprSnGkCTJbO3/onPuTwA8D2DBOTeaJMlcTVVYrJ0+A2BSLp8AMPsgnXu/Xjr0jGalNxBehI0WU+h+9p5pxKjP0e/NMIfYotLPzTIy29dmnqHX2feI9SXEMKyxMjQ/aYws1mwfQsgj7fxH0dLWD4+FbB7NrLsHaQ0Zg3OuF0AmSZKN2uf/AMD/DODPAHwdwP9a+/+ntUv+DMB/7Zz7JoAXAJSTmsrxs9KalSQPes/7uU+z534QTPZRtvsh5vu57n6f/0GO2/2ugUYM7GFaM4jhJIA/qXHidgD/NkmS/8c59wqAbznnfgXAbQC/XDv/LwD8IoDrALYB/BePrLfH7bgdtw+ktcrelRsArn7Y/WiyFQEsf9idaKJ9VPoJfHT6+lHpJxDu6+kkSYaaubhVciWuJk1utvlhN+fcqx+Fvn5U+gl8dPr6Uekn8PB9bemQ6ON23I7bh9OOGcNxO27H7Z7WKozhdz/sDtxH+6j09aPST+Cj09ePSj+Bh+xrSxgfj9txO26t1VoFMRy343bcWqh96IzBOfcfOueuumqa9q81vuJ97cv/5ZxbdM69Jcfe1/Tyh+jrpHPuJefc2865K865f9KK/XXOnXDO/dg592atn/9T7fhZ59yPav38Q+dcZ+14V+379drvZz6Ifkp/25xzbzjnvt3i/bzl3s9SCAwB/TD+ALQBuAHgHIBOAG8CuPgh9ufnAVwC8JYc+98A/Frt868B+I3a518E8Jeo5oZ8GsCPPuC+jgK4VPvcB+BdABdbrb+152VrnzsA/Kj2/G8B+Frt+O8A+C9rn/8rAL9T+/w1AH/4AY/rrwL4twC+Xfveqv28BaBojj2yuf/AXiTycp8B8O/l+68D+PUPuU9nDGO4CmC09nkU1ZgLAPg/AfynofM+pH7/KYAvt3J/AfQAeB3VUPllAO12HQD49wA+U/vcXjvPfUD9m0C1tsiXAHy7Rkgt18/aM0OM4ZHN/YetSjSVov0ht4dKL/8gWg3GfgJVadxy/a3B85+gmmj3V6iixFKSJIeBvvh+1n4vAxj8IPoJ4LcA/FMAzFYabNF+Au9DKQRtH3bkY1Mp2i3aWqLvzrksgD8G8N8kSbIey8zEh9jfJEmOADznnMsD+BMAT6b05UPpp3Pu7wNYTJLkNefcF5roy4c9/4+8FIK2DxsxPLIU7fexLdTSyvF+pZc/aHPOdaDKFP5NkiT/d+1wy/Y3SZISgO+iqufmnXMUTNoX38/a7zkAqx9A9z4H4B84524B+Caq6sRvtWA/AdSXQkCV2fpSCLU+PdTcf9iM4RUAj9csv52oGnH+7EPuk21MLwfuTS//z2sW30/jA04vd1Vo8HsA3k6S5H9v1f4654ZqSAHOuW4Afw/A2wBeAvDVSD/Z/68C+Oukphi/ny1Jkl9PkmQiSZIzqK7Dv06S5B+3Wj+BaikE51wfP6NaCuEtPMq5/yCNTxEjyi+ialG/AeC//5D78gcA5gAcoMplfwVVvfE7AK7V/hdq5zoA/7LW758C+LkPuK8vogoHLwP4Se3vF1utvwCeAfBGrZ9vAfgfasfPAfgxqun5/w5AV+34idr367Xfz30I6+ALuOuVaLl+1vr0Zu3vCunmUc79ceTjcTtux+2e9mGrEsftuB23FmzHjOG4Hbfjdk87ZgzH7bgdt3vaMWM4bsftuN3TjhnDcTtux+2edswYjttxO273tGPGcNyO23G7px0zhuN23I7bPe3/A/Oq/CGxW6paAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(slices_mr1[10].pixel_array, cmap=\"gray\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1b4065e2fc8>"
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(slices_mr2[10].pixel_array, cmap=\"gray\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Ok, so clearly that CT is a different antomy than those MRs. In fact, this is a CT of the abdomen while the few MRs are MRs of the brain. It should be safe to call that CT an outlier and get rid of it. We have found one outlier and have a partial **answer to our Task #7**\n",
    "\n",
    "We also have an **answer to our Question 1** - the images were produced by MRI modality except for one outlier which is a CT.\n",
    "\n",
    "Now, let's try to find the answer to Question 4:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['19880512',\n",
       " '19910103',\n",
       " '19910702',\n",
       " '19920505',\n",
       " '19930622',\n",
       " '19940112',\n",
       " '19950329',\n",
       " '19951017',\n",
       " '20150116',\n",
       " '20190101']"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "study_dates = sorted(np.unique([inst[1].StudyDate for inst in instances]))\n",
    "study_dates"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So, we have our **answer to Question 4**: the oldest study is 1988 and the most recent one is 1995. \n",
    "\n",
    "\n",
    "But we also see something interesting - two studies are much more recent than the rest. Let's take a closer look. I suspect that one of them would be our outlier CT study. Let's check this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['20190101']\n"
     ]
    }
   ],
   "source": [
    "print(np.unique([inst[1].StudyDate for inst in instances if inst[1].Modality == \"CT\"]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Indeed! What is the other one then? Let's visualize the image:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "slices_odd_mr = [pydicom.dcmread(inst[0]) for inst in instances \\\n",
    "             if inst[1].StudyDate == \"20150116\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['1.3.12.2.1107.5.2.33.37105.2015011616025092819028166.0.0.0']\n",
      "36\n"
     ]
    }
   ],
   "source": [
    "# Let's check how many series we have in this study:\n",
    "\n",
    "print(np.unique([s.SeriesInstanceUID for s in slices_odd_mr]))\n",
    "print(len(slices_odd_mr))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So, it's all one volume. Now, let's plot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x1b408e3f188>"
      ]
     },
     "execution_count": 133,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.imshow(slices_odd_mr[15].pixel_array, cmap=\"gray\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Well, you might not know what that is, but that is clearly not a brain image. In fact, if you stick with this course till the end - you will learn exactly what that is in the last exercise of the last lesson :)\n",
    "\n",
    "We have found another outlier and have the final piece of the **answer to our Task #7**  \n",
    "\n",
    "Finally, let's print out the sizes of our volumes (along with some extra data)!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "metadata": {},
   "outputs": [],
   "source": [
    "volumes = dict()\n",
    "\n",
    "for inst in instances:\n",
    "    sid = inst[1].SeriesInstanceUID\n",
    "    if (sid not in volumes):\n",
    "        volumes[sid] = dict()\n",
    "        \n",
    "    volumes[sid][\"StudyDate\"] = inst[1].StudyDate\n",
    "    volumes[sid][\"Width\"] = inst[1].Columns\n",
    "    volumes[sid][\"Height\"] = inst[1].Rows\n",
    "    volumes[sid][\"PatientId\"] = inst[1].PatientID\n",
    "    \n",
    "    if (\"slice_count\" not in volumes[sid]):\n",
    "        volumes[sid][\"slice_count\"] = 0\n",
    "    else:\n",
    "        volumes[sid][\"slice_count\"] += 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'1.2.826.0.1.3680043.2.1125.1.45859137663006505718300393375464286': {'StudyDate': '20190101',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': '123456',\n",
       "  'slice_count': 138},\n",
       " '1.3.12.2.1107.5.2.33.37105.2015011616025092819028166.0.0.0': {'StudyDate': '20150116',\n",
       "  'Width': 448,\n",
       "  'Height': 448,\n",
       "  'PatientId': 'OPA135179',\n",
       "  'slice_count': 35},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.250698293053013179878447218670': {'StudyDate': '19950329',\n",
       "  'Width': 280,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-003',\n",
       "  'slice_count': 21},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.170099978014836890431312652906': {'StudyDate': '19950329',\n",
       "  'Width': 280,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-003',\n",
       "  'slice_count': 21},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.105521800202421035670670758706': {'StudyDate': '19950329',\n",
       "  'Width': 280,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-003',\n",
       "  'slice_count': 21},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.149455479236394071679725178532': {'StudyDate': '19950329',\n",
       "  'Width': 280,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-003',\n",
       "  'slice_count': 21},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.293816446347585254079913156086': {'StudyDate': '19951017',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-003',\n",
       "  'slice_count': 23},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.951760044234185587156102946949': {'StudyDate': '19951017',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-003',\n",
       "  'slice_count': 23},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.874630167789792163807785802052': {'StudyDate': '19951017',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-003',\n",
       "  'slice_count': 23},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.249332750522009823872986282200': {'StudyDate': '19951017',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-003',\n",
       "  'slice_count': 23},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.223133215495128411564518210326': {'StudyDate': '19940112',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-004',\n",
       "  'slice_count': 22},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.295423364175091911131452091831': {'StudyDate': '19940112',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-004',\n",
       "  'slice_count': 22},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.728364200801418237396977783812': {'StudyDate': '19940112',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-004',\n",
       "  'slice_count': 22},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.283146136537679072065477030736': {'StudyDate': '19940112',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-004',\n",
       "  'slice_count': 22},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.290881399408626464415134513575': {'StudyDate': '19930622',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-004',\n",
       "  'slice_count': 21},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.338954569012020140657951382116': {'StudyDate': '19930622',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-004',\n",
       "  'slice_count': 21},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.201921745402287812448748810010': {'StudyDate': '19930622',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-004',\n",
       "  'slice_count': 21},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.231116285499203734317125269666': {'StudyDate': '19930622',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-004',\n",
       "  'slice_count': 21},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.158869091666854803918782490935': {'StudyDate': '19920505',\n",
       "  'Width': 280,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-005',\n",
       "  'slice_count': 21},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.148342356080268980546237840587': {'StudyDate': '19920505',\n",
       "  'Width': 280,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-005',\n",
       "  'slice_count': 21},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.732954519300668202085572772042': {'StudyDate': '19920505',\n",
       "  'Width': 280,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-005',\n",
       "  'slice_count': 21},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.108708982094690934070899838243': {'StudyDate': '19920505',\n",
       "  'Width': 280,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-005',\n",
       "  'slice_count': 21},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.276770677201759689184680286476': {'StudyDate': '19910702',\n",
       "  'Width': 260,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-005',\n",
       "  'slice_count': 23},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.167613564536106399232524912048': {'StudyDate': '19910702',\n",
       "  'Width': 260,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-005',\n",
       "  'slice_count': 23},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.292260123189044684287428848596': {'StudyDate': '19910702',\n",
       "  'Width': 260,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-005',\n",
       "  'slice_count': 23},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.165843183220097757648432257390': {'StudyDate': '19910702',\n",
       "  'Width': 260,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-005',\n",
       "  'slice_count': 23},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.137802635701410656176169562528': {'StudyDate': '19910103',\n",
       "  'Width': 260,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-009',\n",
       "  'slice_count': 24},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.211130119213590294311880514408': {'StudyDate': '19910103',\n",
       "  'Width': 260,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-009',\n",
       "  'slice_count': 24},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.214279913601315478068344395213': {'StudyDate': '19910103',\n",
       "  'Width': 260,\n",
       "  'Height': 320,\n",
       "  'PatientId': 'PGBM-009',\n",
       "  'slice_count': 24},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.285581607999649001090869568979': {'StudyDate': '19880512',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-009',\n",
       "  'slice_count': 21},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.131971402732874033229609248302': {'StudyDate': '19880512',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-009',\n",
       "  'slice_count': 21},\n",
       " '1.3.6.1.4.1.14519.5.2.1.4429.7055.111299569371716382165219422799': {'StudyDate': '19880512',\n",
       "  'Width': 512,\n",
       "  'Height': 512,\n",
       "  'PatientId': 'PGBM-009',\n",
       "  'slice_count': 21}}"
      ]
     },
     "execution_count": 136,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "volumes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "512x512x138  \n",
      "448x448x35  \n",
      "280x320x21  \n",
      "280x320x21  \n",
      "280x320x21  \n",
      "280x320x21  \n",
      "512x512x23  \n",
      "512x512x23  \n",
      "512x512x23  \n",
      "512x512x23  \n",
      "512x512x22  \n",
      "512x512x22  \n",
      "512x512x22  \n",
      "512x512x22  \n",
      "512x512x21  \n",
      "512x512x21  \n",
      "512x512x21  \n",
      "512x512x21  \n",
      "280x320x21  \n",
      "280x320x21  \n",
      "280x320x21  \n",
      "280x320x21  \n",
      "260x320x23  \n",
      "260x320x23  \n",
      "260x320x23  \n",
      "260x320x23  \n",
      "260x320x24  \n",
      "260x320x24  \n",
      "260x320x24  \n",
      "512x512x21  \n",
      "512x512x21  \n",
      "512x512x21  \n"
     ]
    }
   ],
   "source": [
    "# Or, more concisely:\n",
    "for _,v in volumes.items():\n",
    "    print(f\"{v['Width']}x{v['Height']}x{v['slice_count']}  \")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And that is the **solution to our Task #6**\n",
    "\n",
    "Note that this final check gives you another hint at how you could have found the outliers. Clearly, our CT image has many more slices than other volumes and our odd MR image (which is an MR of the knee) has in-plane resolution that is different from the rest of the volumes in our dataset. Also, the intuition we've got early on was correct - patient IDs for the outliers are different. In fact, different hospitals/research protocols usually use different schemes for generating patient IDs and that is what we are seeing here - images from three different sources."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Answers\n",
    "\n",
    "So, to summarize, here are the answers to our questions and solutions to our tasks:\n",
    "\n",
    "1. What imaging modality was used to produce this dataset?\n",
    "> Mostly MRI, one CT\n",
    "\n",
    "2. Data from how many patients does the dataset include?\n",
    "> 6 patients\n",
    "\n",
    "3. How many studies are in the dataset?\n",
    "> 10 studies\n",
    "\n",
    "4. What are the oldest and the most recent studies in the dataset?\n",
    "> The oldest study is May 12, 1988, most recent one is Jan 1 2019\n",
    "\n",
    "5. How many series are in the dataset?\n",
    "> There are 32 series\n",
    "\n",
    "6. List voxel dimensions of all 3D volumes (i.e. series) that the dataset contains as WxHxD\n",
    "> 512x512x138  \n",
    "448x448x35  \n",
    "280x320x21  \n",
    "280x320x21  \n",
    "280x320x21  \n",
    "280x320x21  \n",
    "512x512x23  \n",
    "512x512x23  \n",
    "512x512x23  \n",
    "512x512x23  \n",
    "512x512x22  \n",
    "512x512x22  \n",
    "512x512x22  \n",
    "512x512x22  \n",
    "512x512x21  \n",
    "512x512x21  \n",
    "512x512x21  \n",
    "512x512x21  \n",
    "280x320x21  \n",
    "280x320x21  \n",
    "280x320x21  \n",
    "280x320x21  \n",
    "260x320x23  \n",
    "260x320x23  \n",
    "260x320x23  \n",
    "260x320x23  \n",
    "260x320x24  \n",
    "260x320x24  \n",
    "260x320x24  \n",
    "512x512x21  \n",
    "512x512x21  \n",
    "512x512x21  \n",
    "\n",
    "7. The dataset contains two outliers. Can you find them? There is more than one way to find them. Type up why do you think these volumes are outliers and what approach you used.\n",
    "> We have two series:  \n",
    "Series UID 1.2.826.0.1.3680043.2.1125.1.45859137663006505718300393375464286: that is a CT series, and a different anatomy  \n",
    "Series UID 1.3.12.2.1107.5.2.33.37105.2015011616025092819028166.0.0.0: that is very different data range, and looks like different anatomy"
   ]
  }
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