med_pc_full.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "ec0f0e72",
   "metadata": {},
   "source": [
    "# Notebook 1: MED-PC Extracting the Recording Data and Metadata"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e96b039",
   "metadata": {},
   "source": [
    "# Importing the Python Libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "df497936",
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import glob\n",
    "from collections import defaultdict\n",
    "import os\n",
    "from datetime import datetime"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "56164412",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "from medpc2excel.medpc_read import medpc_read\n",
    "from moviepy.editor import *\n",
    "from IPython.display import Video"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "d2693f50",
   "metadata": {},
   "outputs": [],
   "source": [
    "# setting path\n",
    "sys.path.append('../../src')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "id": "2eca7742",
   "metadata": {},
   "outputs": [],
   "source": [
    "# All the libraries that were created for this repository\n",
    "import extract.dataframe\n",
    "import processing.tone\n",
    "import extract.metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "id": "b0110a2a-39cb-4318-8e67-8199457aa0cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Increase size of plot in jupyter\n",
    "\n",
    "plt.rcParams[\"figure.figsize\"] = (10,6)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52dd42ca",
   "metadata": {},
   "source": [
    "# Getting the Metadata from all the MED-PC Recording Files"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51a96419",
   "metadata": {},
   "source": [
    "- Every MED-PC Recording file has Metadata about time, data, subject, group, experiment name, script used, and the MED-PC box number on the top of the recording file. We will first extract that information\n",
    "    - Metadata can be background information or context about data(or files) that is often different from the actual data that is intended to be recorded.  \n",
    "        For more information on Metadata: https://en.wikipedia.org/wiki/Metadata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "id": "3d9606f6",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_med_pc_file = glob.glob(\"./data/**/*.txt\", recursive=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9737ddcc",
   "metadata": {},
   "source": [
    "- The path of the directory that this notebook is in. This will be where relative paths will be based off of"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "id": "e5ecf305",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/Users/kaavya/Documents/GitHub/behavioral_dataframe_processing/jupyter_notebooks/MED_PC'"
      ]
     },
     "execution_count": 129,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "current_working_directory = os.getcwd()\n",
    "current_working_directory"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ad90d16",
   "metadata": {},
   "source": [
    "- All the other files in this directory. If you want to use a folder in here such as the `data` folder, you'd type `./data/{name_of_folder}` where you replace `{name_of_folder}` with the name of the folder without the `{}`. You will do this in the cells following the one below\n",
    "    - The `./` means the path will reference the current directory that the command is being used from"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "932243dd",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['proc',\n",
       " 'med_pc_full.ipynb',\n",
       " '02_latencies.ipynb',\n",
       " '.DS_Store',\n",
       " 'README.MD',\n",
       " '.03_port_entry_precision.ipynb.icloud',\n",
       " '01_extracting_recording_data.ipynb',\n",
       " '.ipynb_checkpoints',\n",
       " '04_syncing_with_video.ipynb',\n",
       " 'data']"
      ]
     },
     "execution_count": 130,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.listdir(current_working_directory)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "005ccdc3",
   "metadata": {},
   "source": [
    "## NOTE: If you are using your own data, the following path must be changed to the directory where your MED-PC recording files are located(if they are not in the specied folder). It is recommended to create a sub folder in the `data` folder(that is in the same folder as this notebook) for each group of session you want to process and put the recording files in there"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07578f1d",
   "metadata": {},
   "source": [
    "- Use the cell below instead if you're using your own data. You must change the cell below by clicking on the cell and then pressing the `esc` key. Then press the `Y` button on your keyboard. If you want to switch it back do the same but press the `R` button instead. This switches it from a cell that is run as if it's code, or back to a cell where it's just treated as text\n",
    "    - **NOTE: If you are using a different folder, then change the path in the cell below**\n",
    "    - The asterisk is called a wild card which will tell the computer to find all files/folders that match this pattern. The `*` means that any pattern of any length can be replaced with it. The `**` tells the computer to look in all folders that are in the specified folder. For more information: https://linuxhint.com/bash_wildcard_tutorial/\n",
    "    - For more information on finding the path of your folder that contains the recording files: https://www.computerhope.com/issues/ch001708.htm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "id": "3ce543a6",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_med_pc_file = glob.glob(\"./data/**/*.txt\", recursive=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "29194eda",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['./data/2024-05-29_12h17m_Subject p2.txt',\n",
       " './data/2024-05-31_11h49m_Subject n4.txt',\n",
       " './data/2024-05-29_18h36m_Subject n4.txt',\n",
       " './data/2024-05-29_09h11m_Subject p1.txt',\n",
       " './data/2024-05-31_11h49m_Subject n1.txt',\n",
       " './data/2024-06-07_16h00m_Subject n3.txt',\n",
       " './data/2024-05-31_11h49m_Subject n3.txt',\n",
       " './data/2024-05-31_11h49m_Subject n2.txt',\n",
       " './data/2024-06-07_11h04m_Subject n1.txt',\n",
       " './data/2024-06-04_11h34m_Subject n2.txt']"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_med_pc_file[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "062be1de",
   "metadata": {},
   "source": [
    "- Example of what the MED-PC Recording file looks like"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "1c7118af",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "File: C:\\MED-PC\\Data\\2024-05-29_12h17m_Subject p2.txt\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Start Date: 05/29/24\n",
      "\n",
      "End Date: 05/29/24\n",
      "\n",
      "Subject: p2\n",
      "\n",
      "Experiment: fiber_photometry_p2\n",
      "\n",
      "Group: mPFC\n",
      "\n",
      "Box: 3\n",
      "\n",
      "Start Time: 12:17:02\n",
      "\n",
      "End Time: 13:19:01\n",
      "\n",
      "MSN: C57_reward_training\n",
      "\n",
      "A:    4399.000\n",
      "\n",
      "D:    9000.000\n",
      "\n",
      "E:       0.000\n",
      "\n",
      "L:       0.000\n",
      "\n",
      "M:       0.000\n",
      "\n",
      "O:       0.000\n",
      "\n",
      "T:    3660.000\n",
      "\n"
     ]
    }
   ],
   "source": [
    "with open(all_med_pc_file[0]) as f:\n",
    "    lines = f.readlines()\n",
    "    for line in lines[:20]:\n",
    "        print(line)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23b6a4cc",
   "metadata": {},
   "source": [
    "- We will be extracting the first 10 or so lines that look like:\n",
    "\n",
    "```\n",
    "File: C:\\MED-PC\\Data\\2022-05-06_12h59m_Subject 3.4 (2).txt\n",
    "\n",
    "Start Date: 05/06/22\n",
    "\n",
    "End Date: 05/06/22\n",
    "\n",
    "Subject: 3.4 (2)\n",
    "\n",
    "Experiment: Pilot of Pilot\n",
    "\n",
    "Group: Cage 4\n",
    "\n",
    "Box: 1\n",
    "\n",
    "Start Time: 12:59:58\n",
    "\n",
    "End Time: 14:02:38\n",
    "\n",
    "MSN: levelNP_CS_reward_laserepochON1st_noshock\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f1404cfd",
   "metadata": {},
   "source": [
    "- We will just find all the lines that start with `\"File\", \"Start Date\", \"End Date\", \"Subject\", \"Experiment\", \"Group\", \"Box\", \"Start Time\", \"End Time\", or \"MSN\"`. And get the metadata from those lines. And then stop once all the metadata types have been collected"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "67503081",
   "metadata": {},
   "outputs": [],
   "source": [
    "# This makes a nested dictionary of file paths to each individual metadata type\n",
    "file_path_to_meta = extract.metadata.get_all_med_pc_meta_data_from_files(list_of_files=all_med_pc_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 135,
   "id": "35ff0f55",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "File path: ./data/2024-05-29_12h17m_Subject p2.txt\n",
      "Metadata types and associated values: {'File': 'C:\\\\MED-PC\\\\Data\\\\2024-05-29_12h17m_Subject p2.txt', 'Start Date': '05/29/24', 'End Date': '05/29/24', 'Subject': 'p2', 'Experiment': 'fiber_photometry_p2', 'Group': 'mPFC', 'Box': '3', 'Start Time': '12:17:02', 'End Time': '13:19:01', 'MSN': 'C57_reward_training'}\n"
     ]
    }
   ],
   "source": [
    "# The metadata for the first file\n",
    "for key, value in file_path_to_meta.items():\n",
    "    print(\"File path: {}\".format(key))\n",
    "    print(\"Metadata types and associated values: {}\".format(value))\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2c00edf5",
   "metadata": {},
   "source": [
    "## Making a df out of the Metadata"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3298bae3",
   "metadata": {},
   "source": [
    "- A df is essentially a \"programmable\" spreadsheet. But instead of clicking on cells, you will have to tell Python how you want to interact with the spreadsheet\n",
    "    - For more information: https://realpython.com/pandas-df/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "id": "6fcb3201",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Turning the dictionary into a Pandas df\n",
    "metadata_df = pd.DataFrame.from_dict(file_path_to_meta, orient=\"index\")\n",
    "# Resetting the index because currently the file path is the index \n",
    "metadata_df = metadata_df.reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ac4297a",
   "metadata": {},
   "source": [
    "- Getting the numbers out of the column that contains the cage information"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "d0655375",
   "metadata": {},
   "outputs": [],
   "source": [
    "metadata_df[\"cage\"] = metadata_df[\"Group\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5b3ecc2",
   "metadata": {},
   "source": [
    "- Getting the number of files that are associated with each subject"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "6285ade1",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
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      "text/plain": [
       "         index  File  Start Date  End Date  Experiment  Group  Box  \\\n",
       "Subject                                                              \n",
       "n1          10    10          10        10          10     10   10   \n",
       "n2          10    10          10        10          10     10   10   \n",
       "n3          10    10          10        10          10     10   10   \n",
       "n4          10    10          10        10          10     10   10   \n",
       "p1           9     9           9         9           9      9    9   \n",
       "p2           9     9           9         9           9      9    9   \n",
       "p3           9     9           9         9           9      9    9   \n",
       "p4           9     9           9         9           9      9    9   \n",
       "\n",
       "         Start Time  End Time  MSN  cage  \n",
       "Subject                                   \n",
       "n1               10        10   10    10  \n",
       "n2               10        10   10    10  \n",
       "n3               10        10   10    10  \n",
       "n4               10        10   10    10  \n",
       "p1                9         9    9     9  \n",
       "p2                9         9    9     9  \n",
       "p3                9         9    9     9  \n",
       "p4                9         9    9     9  "
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# How many files there are for each subject\n",
    "metadata_df.groupby(\"Subject\").count()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd4bc5a5",
   "metadata": {},
   "source": [
    "## Looking over the MED-PC scripts"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73d599c4",
   "metadata": {},
   "source": [
    "- MED-PC has scripts(lines of code that act as the instructions for how to operate the MED-PC boxes) that contain the descriptions of what each value in the recordings are. We will extract the descriptions from the MED-PC scripts so that we can label the data points in the MED-PC recordings  \n",
    "- Below is a list of all the MED-PC Scripts. We will only be looking at the first one    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "id": "09460401",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['./data/C57_reward_training.MPC']"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_medpc_scripts = glob.glob(\"./**/*.MPC\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c78aaf6c",
   "metadata": {},
   "source": [
    "- Example of what the MED-PC Script looks like that was ran when recording the behaviors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "8dee131d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\\v3 stop tone with poke\n",
      "\n",
      "\\v3.2 monitor port entries AND exits\n",
      "\n",
      "\n",
      "\n",
      "\\INPUTS\n",
      "\n",
      "^port = 8\n",
      "\n",
      "\n",
      "\n",
      "\\OUTPUTS\n",
      "\n",
      "^fan = 16\n",
      "\n",
      "^houselight = 11\n",
      "\n",
      "^tone1 = 2\n",
      "\n",
      "^tone2 = 3\n",
      "\n",
      "^tone3 = 4\n",
      "\n",
      "^tone4 = 5\n",
      "\n",
      "^pump = 9\n",
      "\n",
      "^whitenoise = 1\n",
      "\n",
      "^csout = 5\n",
      "\n",
      "^peout = 15\n",
      "\n",
      "^cs1out = 17\n",
      "\n",
      "^cs2out = 13\n",
      "\n",
      "^cs3out = 14\n",
      "\n",
      "\n",
      "\n",
      "\\EXP SETTINGS\n",
      "\n",
      "^ncsNoShock = 0\n",
      "\n",
      "^initCS1trials = 3\n",
      "\n",
      "\n",
      "\n",
      "\\ARRAYS\n",
      "\n",
      "DIM P = 20000 \\Port entry time stamp array\n",
      "\n",
      "DIM Q = 2500 \\US delivery time stamp array (absolute)\n",
      "\n",
      "DIM R = 2500 \\US time stamp array (relative to last CS)\n",
      "\n",
      "DIM W = 2500 \\ITI values used for CS\n",
      "\n",
      "DIM S = 2500 \\CS presentation values (absolute - every time light turns on)\n",
      "\n",
      "DIM N = 20000 \\Port exit time stamp array\n",
      "\n",
      "DIM K = 2500 \\CS type\n",
      "\n",
      "DIM G = 2500 \\controlled_stimulus_seconds computer clock time (seconds on clock every time light turns on)\n",
      "\n",
      "DIM H = 2500 \\controlled_stimulus_minutes computer clock time (minutes on clock every time light turns on)\n",
      "\n",
      "DIM I = 2500 \\controlled_stimulus_hours computer clock time (hours every time light turns on)\n",
      "\n",
      "DIM B = 2500 \\port_entry_seconds computer clock time (seconds on clock every time light turns on)\n",
      "\n",
      "DIM F = 2500 \\port_entry_minutes computer clock time (minutes on clock every time light turns on)\n",
      "\n",
      "DIM J = 2500 \\port_entry_hours computer clock time (hours every time light turns on)\n",
      "\n",
      "\n",
      "\n",
      "\\Original List of ITIs\n",
      "\n",
      "LIST V = 80\", 90\", 80\", 75\", 100\", 95\", 90\", 80\", 90\", 100\", 90\", 120\", 90\", 85\", 90\", 95\", 120\", 80\", 95\", 80\", 90\", 80\", 75\", 100\", 95\", 90\", 80\", 90\", 100\", 90\", 120\", 90\", 85\", 90\", 95\", 90\", 80\", 90\", 100\", 90\", 90\", 90\", 90\", 90\", 90\", 90\", 90\", 90\", 90\", 90\", 90\", 90\", 90\", 90\", 90\", 90\", 90\", 90\", 90\" \\, 100\", 108\", 117\", 121\", 133\", 145\", 165\" \\CS ITI values (tone + houselight)\n",
      "\n",
      "\n",
      "\n",
      "\\Counter and Flag array\n",
      "\n",
      "DIM C = 10\n",
      "\n",
      "\\All counters are zero-indexed!! Meaning, if C(0) = 3, there were 4 port entries\n",
      "\n",
      "\\C(0) counter for number of port entries\n",
      "\n",
      "\\C(1) counter for CS presentation number\n",
      "\n",
      "\\C(2) counter for US delivery : this is 1-indexed,  meaning number indicates number of sucrose deliveries\n",
      "\n",
      "\\C(3) flag to indicate if sucrose is in port =0 if no port entry was made, =1 if port entry was made (i.e., no sucrose)\n",
      "\n",
      "\\C(4) counter for number of port exits\n",
      "\n",
      "\\C(5) number of CS1\n",
      "\n",
      "\\C(6) number of CS2\n",
      "\n",
      "\\C(7) number of CS3\n",
      "\n",
      "\\C(8) number of sucrose deliveries\n",
      "\n",
      "\n",
      "\n",
      "\\Z-pulses\n",
      "\n",
      "\\Z1: start task after initial delay\n",
      "\n",
      "\\Z2: start of CS\n",
      "\n",
      "\\Z3: port entry\n",
      "\n",
      "\\Z4: port exit\n",
      "\n",
      "\\Z5: trigger CS1\n",
      "\n",
      "\\Z6: trigger CS2\n",
      "\n",
      "\\Z7: trigger CS3\n",
      "\n",
      "\\Z8: turn off all CS triggers\n",
      "\n",
      "\\Z12: INX trigger TTL\n",
      "\n",
      "\n",
      "\n",
      "\\Variables\n",
      "\n",
      "\\A - Time since last CS\n",
      "\n",
      "\\B -\n",
      "\n",
      "\\C - Counter array\n",
      "\n",
      "\\D - Current ITI value\n",
      "\n",
      "\\E - CS ITI values for first few trials\n",
      "\n",
      "\\F -\n",
      "\n",
      "\\G -\n",
      "\n",
      "\\H -\n",
      "\n",
      "\\I -\n",
      "\n",
      "\\J -\n",
      "\n",
      "\\K - CS type\n",
      "\n",
      "\\L -\n",
      "\n",
      "\\M - CS type repo\n",
      "\n",
      "\\N - Port exit time stamp array\n",
      "\n",
      "\\O -\n",
      "\n",
      "\\P - Port entry time stamp array\n",
      "\n",
      "\\Q - Sucrose delivery time stamp array (absolute)\n",
      "\n",
      "\\R - Sucrose delivery time stamp array (relative to last CS)\n",
      "\n",
      "\\S - CS presentation time stamp array\n",
      "\n",
      "\\T - Session timer\n",
      "\n",
      "\\U - Time since last CS presentation\n",
      "\n",
      "\\V - List of CS ITI values (tone + houselight)\n",
      "\n",
      "\\W - ITI values used for CS one each trial\n",
      "\n",
      "\\X -\n",
      "\n",
      "\\Y - Beam break monitor variable\n",
      "\n",
      "\\Z -\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "DISKVARS = A, B, C, D, E, F, G, H, I, J, K, L, M, N, O, P, Q, R, S, T, U, V, W, X, Y, Z\n",
      "\n",
      "DISKCOLUMNS = 1\n",
      "\n",
      "\n",
      "\n",
      "\\Detect port entry\n",
      "\n"
     ]
    }
   ],
   "source": [
    "with open(all_medpc_scripts[0]) as f:\n",
    "    lines = f.readlines()\n",
    "    for line in lines[:100]:\n",
    "        print(line)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ee62e6c",
   "metadata": {},
   "source": [
    "- We will be using the comments in the MED-PC script(Everything after the `\\` for each line) to create a name for the variables. By default, MED-PC uses a single letter as the name of the variable(programming object that holds some information).\n",
    "    - This will use the medpc2excel library found in https://github.com/cyf203/medpc2excel\n",
    "- Example of the variable names and their comments in the MED-PC script that we will get the descriptive names from:\n",
    "    - MED-PC will squish the first few words to create the name for every variable\n",
    "\n",
    "```\n",
    "DIM P = 20000 \\Port entry time stamp array\n",
    "\n",
    "DIM Q = 2500 \\US delivery time stamp array (absolute)\n",
    "\n",
    "DIM R = 2500 \\US time stamp array (relative to last CS)\n",
    "\n",
    "DIM W = 2500 \\ITI values used for CS\n",
    "\n",
    "DIM S = 2500 \\CS presentation values (absolute - every time light turns on)\n",
    "\n",
    "DIM N = 20000 \\Port exit time stamp array\n",
    "\n",
    "DIM K = 2500 \\CS type\n",
    "\n",
    "DIM B = 2500 \\shock intensity\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0caaa9b0",
   "metadata": {},
   "source": [
    "- In the MED-PC recording files, there are values that are labelled with letters. These data type of these letters is described in the MED-PC script file that we just looked at."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "7d7b57bd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "File: C:\\MED-PC\\Data\\2024-05-29_12h17m_Subject p2.txt\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Start Date: 05/29/24\n",
      "\n",
      "End Date: 05/29/24\n",
      "\n",
      "Subject: p2\n",
      "\n",
      "Experiment: fiber_photometry_p2\n",
      "\n",
      "Group: mPFC\n",
      "\n",
      "Box: 3\n",
      "\n",
      "Start Time: 12:17:02\n",
      "\n",
      "End Time: 13:19:01\n",
      "\n",
      "MSN: C57_reward_training\n",
      "\n",
      "A:    4399.000\n",
      "\n",
      "D:    9000.000\n",
      "\n",
      "E:       0.000\n",
      "\n",
      "L:       0.000\n",
      "\n",
      "M:       0.000\n",
      "\n",
      "O:       0.000\n",
      "\n",
      "T:    3660.000\n",
      "\n"
     ]
    }
   ],
   "source": [
    "with open(all_med_pc_file[0]) as f:\n",
    "    lines = f.readlines()\n",
    "    for line in lines[:20]:\n",
    "        print(line)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3480b276",
   "metadata": {},
   "source": [
    "## **NOTE: Please make sure that the corresponding `.mpc` file (aka the MED-PC script) that was ran to create the log file, is also in the same folder as the recording files. This notebook will fail to extract the data from the recording file if it is missing**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da040878",
   "metadata": {},
   "source": [
    "- Spreadsheet of the data from the MED-PC recording file for all the files combined into one.\n",
    "- **NOTE: Each row does not correspond to the same data point. Each row represents the \"n\"-th data point for each category for each file. AKA, the first row is the first data point for the time the subject entered the port and the first data point for the time that the tone that is played, two seperate things. The second row is the second data point for all the categories, the third row is the third data point and so on. This repeats for all data points in a given file, then it starts over to the next file where the first row of that file is the first for all its data points.**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "0c38d1eb",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "concatted_medpc_df = extract.dataframe.get_medpc_dataframe_from_list_of_files(medpc_files=all_med_pc_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ffd4b0b6",
   "metadata": {},
   "source": [
    "- Combining the recording and the metadata into one df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "id": "ecc68d3c",
   "metadata": {},
   "outputs": [],
   "source": [
    "recording_and_metadata_df = concatted_medpc_df.merge(metadata_df, left_on='file_path', right_on='index')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21801f5b",
   "metadata": {},
   "source": [
    "## Getting the cage numbers and the dates so that we can include it in the file name"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb7824da",
   "metadata": {},
   "source": [
    "- We will get the metadata from the recording files and use it to name the files we will create. This will help organize the files and make it easy to know where each file came from "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c61465d5",
   "metadata": {},
   "source": [
    "- Getting the group numbers(original cage names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "9247d864",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'NAc_mPFC'"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# removing blank spaces\n",
    "group_numbers = [\"_\".join(number.split()) for number in recording_and_metadata_df[\"Group\"].unique() if number]\n",
    "# sorting numbers\n",
    "group_numbers = sorted(group_numbers)\n",
    "group_numbers_for_title = \"_\".join(group_numbers)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1e2b5741",
   "metadata": {},
   "source": [
    "- Getting the cage numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "345e7b37",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'NAc_mPFC'"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# removing blank spaces\n",
    "cage_numbers = [\"_\".join(number.split()) for number in recording_and_metadata_df[\"cage\"].unique() if number]\n",
    "# sorting numbers\n",
    "cage_numbers = sorted(cage_numbers)\n",
    "cage_numbers_for_title = \"_\".join(cage_numbers)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a04a431",
   "metadata": {},
   "source": [
    "- Getting the dates\n",
    "- NEW NOTE: Keep earliest and latest date as they are later used to arrange dates in order to calculate date difference (not used in file names) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "25a3de9f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Getting the first and last recording date to get a range\n",
    "earliest_date = recording_and_metadata_df[\"date\"].min()\n",
    "latest_date = recording_and_metadata_df[\"date\"].max()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "536bf2d3",
   "metadata": {},
   "source": [
    "- Getting the subject names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "86fa047c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['p2', 'n4', 'p1', 'n1', 'n3', 'n2', 'p4', 'p3'], dtype=object)"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recording_and_metadata_df[\"Subject\"].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 148,
   "id": "b71f8d49",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'subj_n1_n2_n3_n4_p1_p2_p3_p4'"
      ]
     },
     "execution_count": 148,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# removing blank spaces\n",
    "subject_numbers = [number for number in recording_and_metadata_df[\"Subject\"].unique() if number]\n",
    "# sorting numbers\n",
    "subject_numbers = sorted(subject_numbers)\n",
    "subject_numbers_for_title = \"subj_{}\".format(\"_\".join(subject_numbers))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "49c8e80f",
   "metadata": {},
   "source": [
    "- Getting the experiment name"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "794d3dab",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'fiber_photometry_p2'"
      ]
     },
     "execution_count": 149,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "experiment_names = [\"_\".join(name.split()) for name in recording_and_metadata_df[\"Experiment\"].unique() if name]\n",
    "# sorting experiment_names\n",
    "experiment_names = sorted(experiment_names)\n",
    "experiment_names_for_title = \"AND\".join(experiment_names)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a6d60334",
   "metadata": {},
   "source": [
    "- Getting the script names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "id": "ca537218",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'C57_reward_training'"
      ]
     },
     "execution_count": 150,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# removing blank spaces\n",
    "script_names = [\"_\".join(name.split()) for name in recording_and_metadata_df[\"MSN\"].unique() if name]\n",
    "# sorting names\n",
    "script_names = sorted(script_names)\n",
    "script_names_for_title = \"_\".join(script_names)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "631a7b61",
   "metadata": {},
   "source": [
    "## Saving the dfs(spreadsheets to files) with the metadata as part of the name"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d0ee9b9",
   "metadata": {},
   "source": [
    "- Making necessary directories\n",
    "    - If you want to use any of the other metadata as part of the name, you will have to swap out the variables in the `format()` and change the name of the folder to match your new name. The variable names are the word that's in front of the `=` at the last line of each cell. The `{}` are where the metadata variables will be inserted into the file name. For more information on formatting strings: https://www.w3schools.com/python/ref_string_format.asp\n",
    "    - You can also just manually rename the files by replacing everything in `\"\"` and removing the `.format()` part\n",
    "- **NOTE: You may get an error that the file does not exist. If this is the case, it could be the file name is too long(an issue that may happen when using Jupyter Notebooks on Windows)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "4dced6c1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'./proc/extracted_recording_data_and_metadata/experiment_fiber_photometry_p2_cage_NAc_mPFC_date_20240529_20240607'"
      ]
     },
     "execution_count": 151,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "output_directory = \"./proc/extracted_recording_data_and_metadata/experiment_{}_cage_{}_date_{}_{}\".format(experiment_names_for_title, cage_numbers_for_title, earliest_date, latest_date)\n",
    "output_directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "6a5db606",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.makedirs(output_directory, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "8a56980a",
   "metadata": {},
   "outputs": [],
   "source": [
    "metadata_df.to_csv(os.path.join(output_directory, \"metadata_cage_{}_date_{}_{}.csv\".format\n",
    "                                (cage_numbers_for_title, earliest_date, latest_date)))\n",
    "# metadata_df.to_excel(os.path.join(output_directory, \"metadata_cage_{}_date_{}_{}.xlsx\".format(cage_numbers_for_title, earliest_date, latest_date)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "aa534438",
   "metadata": {},
   "outputs": [],
   "source": [
    "concatted_medpc_df.to_csv(os.path.join(output_directory, \"MEDPC_recording_cage_{}_date_{}_{}.csv\".format\n",
    "                                       (cage_numbers_for_title, earliest_date, latest_date)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "id": "4a449324",
   "metadata": {},
   "outputs": [],
   "source": [
    "recording_and_metadata_df.to_csv(os.path.join(output_directory, \"recording_metadata_cage_{}_date_{}_{}.csv\".format\n",
    "                                              (cage_numbers_for_title, earliest_date, latest_date)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b8a9d10-5e1c-415c-b060-7ad5edf1585e",
   "metadata": {},
   "source": [
    "NOTE: If you changed the directory of where the MED-PC recording dfs, then you must change the directories in the following paths\n",
    "- This will get all the files in each specified path.\n",
    "- The * is called a wildcard, and it can be replaced with any number of characters.\n",
    "For more information: https://www.malikbrowne.com/blog/a-beginners-guide-glob-patterns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "id": "3b632fe6-88b2-441c-a08d-9d9d9289623f",
   "metadata": {},
   "outputs": [],
   "source": [
    "concatted_medpc_files = glob.glob(\"./proc/extracted_recording_data_and_metadata/*/MEDPC_recording_*.csv\")\n",
    "metadata_files = glob.glob(\"./proc/extracted_recording_data_and_metadata/*/metadata_*.csv\")\n",
    "recording_and_metadata_files = glob.glob(\"./proc/extracted_recording_data_and_metadata/*/recording_metadata_*.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04cf2877-5b68-4dd3-9646-bd150bc79070",
   "metadata": {},
   "source": [
    "NOTE: If there is more than one MED-PC recording dfs, then you must manually change the path in the pd.read_csv() for the corresponding variables. Verify if this is the correct file that you want to use"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "6ae49697-8df5-4016-abd0-a6024d8caf3d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'./proc/extracted_recording_data_and_metadata/experiment__cage__date_nan_nan/metadata_cage__date_nan_nan.csv'"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "metadata_files[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "eddf568f-e322-4afc-8354-1aeea3b11e5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'./proc/extracted_recording_data_and_metadata/experiment_fiber_photometry_p2_cage_NAc_mPFC_date_20240529_20240607/MEDPC_recording_cage_NAc_mPFC_date_20240529_20240607.csv'"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "concatted_medpc_files[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "id": "ea063fd5-08d2-4364-93e2-7a177dbfb050",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'./proc/extracted_recording_data_and_metadata/experiment_fiber_photometry_p2_cage_NAc_mPFC_date_20240529_20240607/recording_metadata_cage_NAc_mPFC_date_20240529_20240607.csv'"
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recording_and_metadata_files[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "id": "d3e74330-25cb-456c-9f3a-812c6ea529b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "metadata_df = pd.read_csv(metadata_files[0], index_col=0)\n",
    "concatted_medpc_df = pd.read_csv(concatted_medpc_files[0], index_col=0)\n",
    "recording_and_metadata_df = pd.read_csv(recording_and_metadata_files[0], index_col=0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0c440ff-5461-418b-98f9-7b1e1b4aff15",
   "metadata": {},
   "source": [
    "The df the contains the metadata(columns) of each recording file(rows)\n",
    "We will mostly use this to get the cage number for each subject"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c8141d3-da37-4565-b0b7-6298d3659316",
   "metadata": {},
   "source": [
    "The df the contains the recording data for all the files.\n",
    "The 1st row is the first data entries for each type of data(with the type being specified by the column label). This does not mean that all these are related or occured for the same trial. i.e. There can be many port entries and exits for a subject before and after a tone is played.\n",
    "Each recording session will usually have a few thousand rows(although, most of of the columns will probably be blank by the end). And then after the last row of one session, the next row will be the next session with a different file_path"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "83cbcfc7-57a0-4b06-ab6b-752777781066",
   "metadata": {},
   "source": [
    "GETTING CAGE NUMBERS & DATES FOR FILE NAMES \n",
    "Seeing if any rows have NaN values for the cages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "id": "88412d80-618f-412a-b72a-9dcc91a6eba8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>(P)Portentry</th>\n",
       "      <th>(Q)USdelivery</th>\n",
       "      <th>(R)UStime</th>\n",
       "      <th>(W)ITIvalues</th>\n",
       "      <th>(S)CSpresentation</th>\n",
       "      <th>(N)Portexit</th>\n",
       "      <th>(K)CStype</th>\n",
       "      <th>(G)controlled_stimulus_secondscomputer</th>\n",
       "      <th>(H)controlled_stimulus_minutescomputer</th>\n",
       "      <th>(I)controlled_stimulus_hourscomputer</th>\n",
       "      <th>...</th>\n",
       "      <th>Start Date</th>\n",
       "      <th>End Date</th>\n",
       "      <th>Subject</th>\n",
       "      <th>Experiment</th>\n",
       "      <th>Group</th>\n",
       "      <th>Box</th>\n",
       "      <th>Start Time</th>\n",
       "      <th>End Time</th>\n",
       "      <th>MSN</th>\n",
       "      <th>cage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>0 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [(P)Portentry, (Q)USdelivery, (R)UStime, (W)ITIvalues, (S)CSpresentation, (N)Portexit, (K)CStype, (G)controlled_stimulus_secondscomputer, (H)controlled_stimulus_minutescomputer, (I)controlled_stimulus_hourscomputer, (B)port_entry_secondscomputer, (F)port_entry_minutescomputer, (J)port_entry_hourscomputer, date, subject, file_path, index, File, Start Date, End Date, Subject, Experiment, Group, Box, Start Time, End Time, MSN, cage]\n",
       "Index: []\n",
       "\n",
       "[0 rows x 28 columns]"
      ]
     },
     "execution_count": 161,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "recording_and_metadata_df[pd.isna(recording_and_metadata_df[\"cage\"])]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fbe5002-b7d5-4160-bd88-bc5b41bef870",
   "metadata": {},
   "source": [
    "Dropping the NaN values so we can get the cage numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "c1512b31-be6f-4690-b43e-14cf441ae08d",
   "metadata": {},
   "outputs": [],
   "source": [
    "recording_and_metadata_df = recording_and_metadata_df.dropna(subset=[\"cage\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7db4d1d-9dd5-4e6f-a03b-f0451762632e",
   "metadata": {},
   "source": [
    "ADJUSTING THE DAYS AND CAGES LOOKED AT \n",
    "- List of all the subject names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "id": "d7f872fa-3475-4553-b5b6-3708c7a2e8c4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['n1', 'n2', 'n3', 'n4', 'p1', 'p2', 'p3', 'p4']"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_subjects = sorted(recording_and_metadata_df[\"Subject\"].unique())\n",
    "all_subjects"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2f9650f-8e55-45eb-8cae-fc8e4da25a4b",
   "metadata": {},
   "source": [
    "- List of all the cage numbers\n",
    "- NEW NOTE: cage can take in string as well, not just integer "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "id": "dddcc561-30fc-4eac-84a9-22722976bd5e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['NAc', 'mPFC']"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_cages = sorted(recording_and_metadata_df[\"cage\"].unique())\n",
    "cage_numbers = sorted(all_cages)\n",
    "title_cage_numbers = cage_numbers\n",
    "title_cage_numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "id": "f415f47f-e675-4730-8376-2e91ba53c09a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[20240529,\n",
       " 20240530,\n",
       " 20240531,\n",
       " 20240601,\n",
       " 20240602,\n",
       " 20240603,\n",
       " 20240604,\n",
       " 20240605,\n",
       " 20240606,\n",
       " 20240607]"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_dates = sorted(recording_and_metadata_df[\"date\"].unique())\n",
    "all_dates"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b356b67-213e-47fc-9db4-a876e2b7f8e0",
   "metadata": {},
   "source": [
    "FOLLOW DIRECTIONS BELOW IF YOU WANT TO CHANGE WHICH CAGES OR DATES TO PLOT \n",
    "- You must change the cell below by clicking on the cell and then pressing the esc key. Then press the Y button on your keyboard. If you want to switch it back do the same but press the R button instead. This switches it from a cell that is run as if it's code, or back to a cell where it's just treated as text\n",
    "Then from above, copy the numbers that you want to use for the cage numbers and the dates"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b105c00-bc09-498d-993c-ddcbe18fdc8e",
   "metadata": {},
   "source": [
    "GETTING THE CAGE NUMBERS AND DATES TO NAME THE FILES \n",
    "- earliest and latest dates have been removed, processes all the dates in the files instead"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd211a8d-a6c5-483d-b23a-3cbef17c7e50",
   "metadata": {},
   "source": [
    "GETTING THE TIMES THAT THE TONES ARE BEING PLAYED \n",
    "- Getting all the rows that correspond to one of the files paths. This will be the equivalent of getting all the rows for one session\n",
    "- Everything looks normal enough\n",
    "- (S)CSpresentation is the time that the tone starts playing. MED-PC starts inputting in random numbers that are in the 1000's. So we will remove these\n",
    "- (S)CSpresentation then starts adding blanks(NaN) so we will remove these too\n",
    "- We will use a function that removes the NaN and the tone times that are divisible by 1000. This will get the tones time that were actually used for the recordings"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "669f0847-8ef7-4b8d-98d3-3299573e30ae",
   "metadata": {},
   "source": [
    "## GETTING THE FIRST PORT ENTRY AFTER EACH TONE \n",
    "- With these tone playing times, we will get the first port entry that comes after the tone playing time\n",
    "--This was done by getting all the port entries that came after the tone. And then getting the port entry time that was earliest in time(aka smallest number)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "id": "4af8ce20-9166-4a18-b1db-381605208b85",
   "metadata": {},
   "outputs": [],
   "source": [
    "concatted_first_porty_entry_dataframe = processing.tone.get_concatted_first_porty_entry_after_tone_dataframe(concatted_medpc_df=recording_and_metadata_df)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e648f7be-ca02-48c9-8391-8513769166ad",
   "metadata": {},
   "source": [
    "GETTING LAST PORT ENTRY BEFORE THE TONE\n",
    "- We will do the same, but get the port entries that happened before the tone\n",
    "- Example run for one session\n",
    "- Getting all the port entries that happen before the tone for all sessions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "id": "ee1198e5-b251-48f2-b04c-fc7e72ea8ea5",
   "metadata": {},
   "outputs": [],
   "source": [
    "concatted_last_porty_entry_dataframe = processing.tone.get_concatted_last_porty_entry_before_tone_dataframe(concatted_medpc_df=recording_and_metadata_df)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d8bd8d7-9169-4d48-9117-3a70fb8eb551",
   "metadata": {},
   "source": [
    "## Merging the dfs for the first port entry after the tone and the last tone before the tone"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "id": "18e58321-b3de-4a13-8cae-30d62a4ebeff",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Combining it based on the tone times and the file path\n",
    "concatted_first_last_porty_df = pd.merge(concatted_first_porty_entry_dataframe,\n",
    "                                                        concatted_last_porty_entry_dataframe,\n",
    "                                                        how='left', left_on=['current_tone_time','file_path'],\n",
    "                                                        right_on = ['current_tone_time','file_path'], suffixes=('', '_y'))\n",
    "# Dropping all columns that are duplicates\n",
    "concatted_first_last_porty_df = concatted_first_last_porty_df.drop(\n",
    "    concatted_first_last_porty_df.filter(regex='_y$').columns.tolist(), axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1889261f-9dc3-4909-812e-bee1dbbe4076",
   "metadata": {},
   "source": [
    "- Getting all the rows that have port entry to port exit time that overlaps with the tone playing\n",
    "- This would be the port entries that came before the tone, but had a port exit after"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "id": "e3644e14-7c0f-4016-8857-8ba842bcfd4c",
   "metadata": {},
   "outputs": [],
   "source": [
    "overlapped_port_entries = concatted_first_last_porty_df[concatted_first_last_porty_df[\"port_exit_after_last_port_entry_before_tone\"] >= concatted_first_last_porty_df[\"current_tone_time\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4210f1af-4645-4d11-8666-ae3badc55d8c",
   "metadata": {},
   "source": [
    "Getting the Latency for Each Session of a Tone Playing\n",
    "- To calculate latency, we would just subtract the time of the first port entry to that of the tone playing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "id": "9d0cad49-be7d-4278-8503-858149960248",
   "metadata": {},
   "outputs": [],
   "source": [
    "concatted_first_last_porty_df[\"latency\"] = concatted_first_porty_entry_dataframe[\"first_port_entry_after_tone\"] - concatted_first_last_porty_df[\"current_tone_time\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a401f6b1-fa70-4388-8e55-86620caac713",
   "metadata": {},
   "source": [
    "For all the latencies that are are greater than 30 seconds, we changed the latency to 30 seconds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 171,
   "id": "0231dc33-82ac-4ac0-8f82-1ca97fca5778",
   "metadata": {},
   "outputs": [],
   "source": [
    "concatted_first_last_porty_df[\"latency_adjusted_greater_than_30\"] = concatted_first_last_porty_df[\"latency\"].apply(lambda x: 30 if x >= 30 else x)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eaf04d7d-d23f-473e-8aad-6d0533c38dea",
   "metadata": {},
   "source": [
    "Seeing which port entries and port exit durations overlap with the tone\n",
    "Making a column that states whether or not the last port entry before the tone has a port exit after the tone. This would mean that they are overlapping."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "id": "9ce73029-9146-40b8-bfda-5e6b986146b8",
   "metadata": {},
   "outputs": [],
   "source": [
    "concatted_first_last_porty_df[\"overlapping_port_entry_with_tone\"] = concatted_first_last_porty_df.apply(lambda row: True if row[\"port_exit_after_last_port_entry_before_tone\"] >= row[\"current_tone_time\"] else False, axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c1c7f322-ed47-424f-b2f6-8692d54b357b",
   "metadata": {},
   "source": [
    "Comparing the latencies of the first port entry after the tone between these two groups:\n",
    "- Those with the last port entry before the tone that has a port exit after the tone(\"overlapping\" group)\n",
    "- Those with the last port entry before the tone that has a port exit before the tone(\"nonoverlapping\" group)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 173,
   "id": "9776a968-5ef5-4866-8699-aba180abd9a2",
   "metadata": {},
   "outputs": [],
   "source": [
    "overlapping_df = concatted_first_last_porty_df[concatted_first_last_porty_df[\"overlapping_port_entry_with_tone\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "a169019f-d0d8-44f1-bdec-97e61df88b7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "non_overlapping_df = concatted_first_last_porty_df[~concatted_first_last_porty_df[\"overlapping_port_entry_with_tone\"]]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24561e7e-0e01-4e06-b659-79c5c477e79a",
   "metadata": {},
   "source": [
    "Latency between the tone playing and the first port entry after the tone"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "id": "581c8db6-2da3-423a-a3f6-13261454024c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9.583242506811892"
      ]
     },
     "execution_count": 175,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "overlapping_df[\"latency\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "d6b5380c-0649-4883-a3d5-743fcb2a0b65",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.840949197860882"
      ]
     },
     "execution_count": 176,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "non_overlapping_df[\"latency\"].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48cfeffe-8fe3-401d-b56d-1bd2744b4d12",
   "metadata": {},
   "source": [
    "Latency between the tone playing and the first port entry after the tone. This had been adjusted so that all latencies that are greater than 30 seconds were adjusted to be just 30 seconds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "id": "e42e6335-9ddc-45b4-90b8-918fae0aa62b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8.642009536784647"
      ]
     },
     "execution_count": 177,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "overlapping_df[\"latency_adjusted_greater_than_30\"].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "8f0f74c5-b4e6-4435-9a51-40fbcfcbe342",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.497399732620241"
      ]
     },
     "execution_count": 178,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "non_overlapping_df[\"latency_adjusted_greater_than_30\"].mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a4f67516-97f3-48da-91d6-65824504fa62",
   "metadata": {},
   "source": [
    "Adjusting the Latencies if the Port Entries/Exit Overlap With the Tone Times\n",
    "For all the rows with overlapping last port entries before the tone, we will adjust the latency of the tone to the first port entry after the tone to 0. (Because the first port entry after the tone would be considered to be the same as the last port entry before the tone)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "7d4520c5-febe-4ad3-bd4d-f1aedd4012a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "concatted_first_last_porty_df[\"latency_adjusted_overlap\"] = concatted_first_last_porty_df.apply(\n",
    "    lambda row: 0 if row[\"overlapping_port_entry_with_tone\"] else row[\"latency_adjusted_greater_than_30\"], axis=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7575843f-fc04-40bf-9363-44639d63ec43",
   "metadata": {},
   "source": [
    "Labeling if a row's latency is less than 10 seconds or not\n",
    "- We will be getting the ratio of latencies(from the time that the tone played, to the first port entry after the tone) that are less than 10 seconds for each session.\n",
    "- So we will label all the adjusted latencies that are less than 10 seconds as True, and the those with latencies that are greater than 10 seconds as False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "cd2548a4-11d0-4fc2-9f2b-c141f5ffa21f",
   "metadata": {},
   "outputs": [],
   "source": [
    "concatted_first_last_porty_df[\"adjusted_30_second_latency_less_than_10_seconds_ratio\"] = concatted_first_last_porty_df[\"latency_adjusted_greater_than_30\"].apply(\n",
    "    lambda x: True if x <= 10 else False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "78d0612a-72da-42e5-afbd-1fee7f517b11",
   "metadata": {},
   "outputs": [],
   "source": [
    "concatted_first_last_porty_df[\"overlap_adjusted_latency_less_than_10_seconds\"] = concatted_first_last_porty_df[\"latency_adjusted_overlap\"].apply(\n",
    "    lambda x: True if x <= 10 else False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d88d383-8286-4e71-8bed-4376e0cc0eef",
   "metadata": {},
   "source": [
    "Making dfs that have Each Subject as the Row and Each Date as the Column\n",
    "- Pivot plots allow us to make columns out of each unique entry in a selected column. (For this, it will be the date column that we will turn into columns) The index for the rows will be each unique entry in another column. (For this, it will be the subject's ID) And the values will be the aggregate of the values that have both the values in the previous two selected columns. (For this it will be the latency columns and we will take the mean)\n",
    "https://pandas.pydata.org/docs/reference/api/pandas.pivot_table.html\n",
    "- Making a folder for all the pivotplots"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "03537206-3dfc-4a05-b7e2-ad4d06b91543",
   "metadata": {},
   "source": [
    "NOTE: If you decide to change the cage numbers or the dates used from the original ones from the imported dfs, you will need to change the subsequent path to the cage number and dates you are using\n",
    "\n",
    "NEW UPDATED NOTE: Wasn't sure if the dfs needed to be saved or not so I didn't take them out but shortened the folder path and file name "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "id": "748d95ee-d673-4399-a9aa-7216618e7d67",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'./proc/subject_date_dfs/first_port_tone_latency_cage_NAc_mPFC'"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "first_port_entry_to_tone_latency_output_directory = \"./proc/subject_date_dfs/first_port_tone_latency_cage_{}\".format(cage_numbers_for_title)\n",
    "first_port_entry_to_tone_latency_output_directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "id": "629c54d4-ab63-442e-9314-39399bc632e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.makedirs(first_port_entry_to_tone_latency_output_directory, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "e45e8c80-e0a1-4889-81ef-523cb4d28848",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'./proc/subject_date_dfs/latencies_10_less_cage_NAc_mPFC'"
      ]
     },
     "execution_count": 184,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "latencies_less_than_10_seconds_ratio_output_directory = \"./proc/subject_date_dfs/latencies_10_less_cage_{}\".format(cage_numbers_for_title)\n",
    "latencies_less_than_10_seconds_ratio_output_directory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "eeb7669b-14e2-4e29-8e7f-f62c67a322b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.makedirs(latencies_less_than_10_seconds_ratio_output_directory, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "id": "f51ce56c-5827-4037-b5a7-2e61879e47f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_latency_pivot_plot = pd.pivot_table(concatted_first_last_porty_df, values='latency', \n",
    "                                        index=['subject'], columns=['date'], aggfunc='mean')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7960433e-c951-4a5c-bad5-0db27bf4dded",
   "metadata": {},
   "source": [
    "- Getting the cage numbers for each subject and then making a dictionary out of it\n",
    "- This will be used to add the cage information to the pivot plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "id": "bfcc5ce8-746c-4812-9f01-9f99f69f3dee",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'p2': 'mPFC',\n",
       " 'n4': 'NAc',\n",
       " 'p1': 'mPFC',\n",
       " 'n1': 'NAc',\n",
       " 'n3': 'NAc',\n",
       " 'n2': 'NAc',\n",
       " 'p4': 'mPFC',\n",
       " 'p3': 'mPFC'}"
      ]
     },
     "execution_count": 187,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "subject_to_cage = pd.Series(metadata_df[\"cage\"].values,index=metadata_df[\"Subject\"].values).to_dict()\n",
    "subject_to_cage"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0c6fb22d-29bc-474a-90fb-de7e330c70ad",
   "metadata": {},
   "source": [
    "- Add the cage information with the dictionary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "dfba689f-0350-4f75-a801-0f452189ff2c",
   "metadata": {},
   "outputs": [],
   "source": [
    "all_latency_pivot_plot[\"cage\"] = all_latency_pivot_plot.index.map(subject_to_cage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "id": "693d5d20-54cf-4cc5-a619-3dab94f5dd85",
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path = \"original_latency_cage_{}_{}_{}.csv\".format(cage_numbers_for_title, earliest_date, latest_date)\n",
    "output_path = os.path.join(first_port_entry_to_tone_latency_output_directory, file_path)\n",
    "try:\n",
    "    all_latency_pivot_plot.to_csv(output_path)\n",
    "except:\n",
    "    output_path = os.path.abspath(output_path)\n",
    "    # Change path if using on Windows because it raises an error if the path is longer than 260 characters\n",
    "    # But adding this suffix bypasses this\n",
    "    output_path = u\"\\\\\\\\?\\\\\" + output_path\n",
    "    all_latency_pivot_plot.to_csv(output_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a45681d8-1112-4830-a6c1-bbe4fd848e3f",
   "metadata": {},
   "source": [
    "Making a pivot plot with the latency that were greater than 30 seconds being adjusted"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "id": "ba57d239-be36-479d-a15a-3c503df5a6a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "latency_greater_than_30_seconds_adjusted_pivot_plot = pd.pivot_table(concatted_first_last_porty_df, values='latency_adjusted_greater_than_30', index=['subject'],\n",
    "\n",
    "                    columns=['date'], aggfunc='mean')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "id": "217ceb19-e111-46a2-8524-97c7ca43edaa",
   "metadata": {},
   "outputs": [],
   "source": [
    "latency_greater_than_30_seconds_adjusted_pivot_plot[\"cage\"] = latency_greater_than_30_seconds_adjusted_pivot_plot.index.map(subject_to_cage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "5fdb9d39-eca6-4ae3-aace-95de7eceae13",
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path = \"subject_to_date_latency_greater_than_30_seconds_adjusted_cage_{}_date_{}_{}.csv\".format(cage_numbers_for_title, earliest_date, latest_date)\n",
    "output_path = os.path.join(first_port_entry_to_tone_latency_output_directory, file_path)\n",
    "try:\n",
    "    latency_greater_than_30_seconds_adjusted_pivot_plot.to_csv(output_path)\n",
    "except:\n",
    "    output_path = os.path.abspath(output_path)\n",
    "    # Changing path if using on Windows because it raises an error if the path is longer than 260 characters\n",
    "    # But adding this suffix bypasses this\n",
    "    output_path = u\"\\\\\\\\?\\\\\" + output_path\n",
    "    latency_greater_than_30_seconds_adjusted_pivot_plot.to_csv(output_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "806b33ca-8238-4d9a-a786-20d031d910ac",
   "metadata": {},
   "source": [
    "Making a pivot plot with the ratio of original latencies that are less than 10 seconds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "bdadc9c8-8505-4109-9e31-6c76588e776b",
   "metadata": {},
   "outputs": [],
   "source": [
    "original_less_than_10_latency_df = pd.pivot_table(concatted_first_last_porty_df, values='adjusted_30_second_latency_less_than_10_seconds_ratio', index=['subject'],\n",
    "\n",
    "                    columns=['date'], aggfunc='mean')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "id": "8201c6a9-3c20-453e-9ad8-044c6567cd8a",
   "metadata": {},
   "outputs": [],
   "source": [
    "original_less_than_10_latency_df[\"cage\"] = original_less_than_10_latency_df.index.map(subject_to_cage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "8e80b7c8-6e97-420c-ade4-7f145e07e24d",
   "metadata": {},
   "outputs": [],
   "source": [
    "file_path = \"subject_to_date_less_than_10_seconds_original_latencies_ratios_cage_{}_date_{}_{}.csv\".format(cage_numbers_for_title, earliest_date, latest_date)\n",
    "output_path = os.path.join(first_port_entry_to_tone_latency_output_directory, file_path)\n",
    "try:\n",
    "    original_less_than_10_latency_df.to_csv(output_path)\n",
    "except:\n",
    "    output_path = os.path.abspath(output_path)\n",
    "    # Changing path if using on Windows because it raises an error if the path is longer than 260 characters\n",
    "    # But adding this suffix bypasses this\n",
    "    output_path = u\"\\\\\\\\?\\\\\" + output_path\n",
    "    original_less_than_10_latency_df.to_csv(output_path)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a3be3686-94f7-41f1-8e87-0c5f69b2e66f",
   "metadata": {},
   "source": [
    "Making a pivot plot with the ratio of overlap adjusted latencies that are less than 10 seconds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "2af8e4f5-46bb-4918-8d0a-9b57a8509507",
   "metadata": {},
   "outputs": [],
   "source": [
    "overlap_adjusted_less_than_10_latency_df = pd.pivot_table(concatted_first_last_porty_df, values='overlap_adjusted_latency_less_than_10_seconds', index=['subject'],\n",
    "\n",
    "                    columns=['date'], aggfunc='mean')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "id": "648bc25e-650e-40b0-a202-8be11199020f",
   "metadata": {},
   "outputs": [],
   "source": [
    "overlap_adjusted_less_than_10_latency_df[\"cage\"] = overlap_adjusted_less_than_10_latency_df.index.map(subject_to_cage)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "34396b66-9283-456e-b0e5-c91216c58ec8",
   "metadata": {},
   "outputs": [],
   "source": [
    "overlap_adjusted_less_than_10_latency_df.to_csv(os.path.join(latencies_less_than_10_seconds_ratio_output_directory, \"subject_to_date_less_than_10_seconds_overlap_adjusted_latencies_ratios_cage_{}_date_{}_{}.csv\".format(cage_numbers_for_title, earliest_date, latest_date)))\n",
    "overlap_adjusted_less_than_10_latency_df.to_excel(os.path.join(latencies_less_than_10_seconds_ratio_output_directory, \"subject_to_date_less_than_10_seconds_overlap_adjusted_latencies_ratios_cage_{}_date_{}_{}.xlsx\".format(cage_numbers_for_title, earliest_date, latest_date)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0f9e7375-af0a-476f-8410-5798652630b1",
   "metadata": {},
   "source": [
    "Plotting the latencies\n",
    "Getting the averages for all the trials in one subject and one day\n",
    "- We will plot a line for each subject. With the X-axis being the days since the first session. And the Y-axis is the latency values averaged across all the trials for one recording session\n",
    "- Grouping all the rows with the same subject and date(aka, all the trials in one session). And then getting the mean for each value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "de84a610-30e7-4c89-aeed-2b89959f6a11",
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped_averaged_first_port_df = concatted_first_last_porty_df.groupby(by=[\"file_path\", \"date\", \"subject\"]).mean()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0d4e0ff1-097e-4c3c-8ed7-60e1151b51db",
   "metadata": {},
   "source": [
    "Reformatting the df for plotting\n",
    "Resetting the index so that we can use the data as a value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "360d170f-c238-4132-8d16-d00ef14163b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped_averaged_first_port_df = grouped_averaged_first_port_df.reset_index()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "575fb92e-bf7a-4ccd-a70f-ab8818a085f0",
   "metadata": {},
   "source": [
    "## Turning the date column which is a string, into an integer\n",
    "Allows us to use the date as the X-axis for plotting\n",
    "How date is calculated:\n",
    "- pd.to_datetime = converts entire column of data strings into \"datetime\" objects\n",
    "- then calculate difference between earliest date (first date in row) and rest of the dates\n",
    "- dt.days = extracts number of days from datetime objects\n",
    "- add new calculation into df "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "id": "aa8e365a-5167-44c2-8c83-c9abb0bbf1f7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     0\n",
       "1     0\n",
       "2     0\n",
       "3     0\n",
       "4     0\n",
       "     ..\n",
       "71    9\n",
       "72    9\n",
       "73    9\n",
       "74    9\n",
       "75    9\n",
       "Name: date int, Length: 76, dtype: int64"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped_averaged_first_port_df['date'] = pd.to_datetime(grouped_averaged_first_port_df['date'], format='%Y%m%d')\n",
    "initial_date = grouped_averaged_first_port_df['date'].iloc[0]\n",
    "grouped_averaged_first_port_df['date int'] = (grouped_averaged_first_port_df['date'] - \n",
    "                                                            grouped_averaged_first_port_df['date'].iloc[0]).dt.days\n",
    "grouped_averaged_first_port_df['date int']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a1180b74-a8a0-412f-9fb0-eebf8d1acdf5",
   "metadata": {},
   "source": [
    "Adding the cage information\n",
    "We will make one plot for each cage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "id": "8c1ef2df-5994-43df-9554-aa596b6f161b",
   "metadata": {},
   "outputs": [],
   "source": [
    "grouped_averaged_first_port_df[\"cage\"] = grouped_averaged_first_port_df[\"subject\"].map(subject_to_cage)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5f79eea-527d-4334-b2f3-4385851fd000",
   "metadata": {},
   "source": [
    "## Plotting the latencies that were adjusted if they greater than 30 seconds\n",
    "Once a plot is created, it SHOULD save each file (saved by file name) into a general \"plots\" folder, this applies for all the different types of plots generated below ."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "id": "d8f6805a-ab74-459e-9924-5c719353ed70",
   "metadata": {},
   "outputs": [],
   "source": [
    "original_average_latency_output_directory = \"./proc/plots\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "id": "27b7cd06-ea79-4319-969e-aed2a559276b",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.makedirs(original_average_latency_output_directory, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "id": "0dd55930-165b-4217-85f9-7a33b2ecb7a5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0     0\n",
       "1     0\n",
       "2     0\n",
       "3     0\n",
       "4     0\n",
       "     ..\n",
       "71    9\n",
       "72    9\n",
       "73    9\n",
       "74    9\n",
       "75    9\n",
       "Name: date int, Length: 76, dtype: int64"
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped_averaged_first_port_df['date int']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "id": "06ee1558-6a30-4ec8-be9a-a00f2c3c5dcc",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting for each cage\n",
    "for cage in grouped_averaged_first_port_df[\"cage\"].unique():\n",
    "    fig, ax = plt.subplots()\n",
    "    # Getting all the rows with the current cage number\n",
    "    cage_df = grouped_averaged_first_port_df[grouped_averaged_first_port_df[\"cage\"] == cage]\n",
    "    \n",
    "    # Plotting a line for each subject\n",
    "    for subject in cage_df[\"subject\"].unique():\n",
    "        # Getting all the rows with the current subject\n",
    "        subject_df = cage_df[cage_df[\"subject\"] == subject]\n",
    "        # Making the dates into days after the first session by subtracting all the dates by the first date\n",
    "        ax.plot(subject_df[\"date int\"], subject_df[\"latency_adjusted_greater_than_30\"], '-o', label=subject)\n",
    "\n",
    "    # Setting the Y-Axis to only plot from 0 to 30 because we adjusted the latency to always be under 30\n",
    "    ax.set_ylim(0, 30)\n",
    "    # Labeling the X/Y Axis and the title\n",
    "    ax.set_xlabel(\"The Days After the First Session\")\n",
    "    ax.set_ylabel(\"Adjusted Average Latency of First Entry to Tone Onset\")\n",
    "    ax.set_title(\"Latency of Port Entry to Tone: Cage {}\".format(cage))\n",
    "    # To show the legend\n",
    "    ax.legend()\n",
    "    file_name = \"average_latency_plot_cage_{}_date_{}_{}.png\".format(cage, earliest_date, latest_date)\n",
    "    plt.savefig(os.path.join(original_average_latency_output_directory, file_name))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "361b3cf7-1146-40b1-ad89-33bc707a92ca",
   "metadata": {},
   "source": [
    "## Plotting the original ratio of latencies that are less than 10 seconds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "id": "f6d21232-a563-43ca-adea-aca42cd13332",
   "metadata": {},
   "outputs": [],
   "source": [
    "less_than_10_second_original_latency_ratio_plots_output_directory = \"./proc/plots\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "id": "e020cd5a-b904-4165-88f0-f24ea494505f",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.makedirs(less_than_10_second_original_latency_ratio_plots_output_directory, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "id": "76582808-2e75-474d-9cc8-5c83df6b29d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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g23Cc3LaZmppKdHR0gcau0Wjua/md6xctWsSFCxdYsGAB/fv3R6/XM3fuXGrUqMG2bdsAOHfuHKdOneLVV18FyPacRkREZA5r/Pvvv2nbti3VqlXLdb+bN2+mevXqNG7cOMvyfv36oZTKVsSja9euaLXazNt3PzenT5/mypUr9OrVK8tj9vPzo3nz5lm21bhxY65fv84rr7zC6tWrsw2zfFgXLlygV69eeHl5odVq0el0PPHEE0DOr5G7rVu3Do1Gw2uvvZblOHt5eVGnTp1slce8vLyyHcfatWtned3+/fffVKlShfbt29/XY1m3bh1t27bFx8cnSyydO3cGyHx9FNYxfeGFF7Lc3rVrFykpKdmGcfn6+vLkk0+yadOmLMs1Gg1dunTJvG1paUmlSpXw9vamXr16mctdXFzw8PC4r6FMd3uQ2Lp165Zl2d3P27p16yhVqhTdunXLcvzr1q2Ll5dXgVShU0pl+5zIT2z5ec7z+/q5l4yMjGzHryDk5716+vRpIiMjefHFF7Pct1y5crRo0SLLsoJ4vgriNfvSSy+h0+mws7OjdevWGAwGVq1alfm5ecuYMWPYt29flr8mTZrcM0YhHoRU1RMiF7GxsWRkZDB//nzmz5+fY5tbX7ITJ07E3t6eH3/8kUWLFqHVamndujVz5szJLIv6yy+/MHPmTL799lumTJmCg4MDzz33HB999BFeXl4FFrerq2uW27fGyKekpACm67E6dOjAlStXmDJlCrVq1cLe3h6j0UjTpk0z293PNgsq5tjYWDw9PbOsi4uLw8XFJV/b8fPzY/jw4Zm3V65cySuvvMLbb7/N3r17M69Neuutt3jrrbdy3Mat5zQmJuaeldliY2NzLBHu4+OTuf5O9zqOt9rn9Hrw8vLKvHYIoHfv3mRkZPDNN9/wwgsvYDQaadSoETNnzuSpp57KM+57uXHjBq1atcLGxoaZM2dSpUoV7OzsCA8P5/nnn8/X8x4VFYVSKtvzeUuFChWy3L772IDp+Ny5r5iYGMqVK3efj8YUy9q1a9HpdDmuv/WcF9YxvbvC3q3nOafKez4+PmzcuDHLMjs7O2xsbLIsu1VO+W5WVlakpqY+cKwFEZu1tXWWGKKiorh+/TpWVlY57jOvBPXW8x0SEpJn3GFhYdkqZ+Yntvw85/l9/RQENzc37Ozs7vl4b8nve/XW85rT+9HT0zPL/h7m+bqlIF6zc+bM4cknn0Sr1eLm5pZrZdSyZcvmWH4c8v/6ESK/JHESIhelS5dGq9XSu3dvXn/99Rzb+Pv7A6azaePGjWPcuHFcv36doKAgJk2aRMeOHQkPD8fOzg43NzfmzZvHvHnzuHjxImvWrGHChAlER0cTGBhYZI/r2LFjHD58mKVLl9K3b9/M5bcuWDeHWrVqAXD06FGqV6+euTwjI4NTp07xyiuvPNB2X3zxRWbPns2xY8cA048SMCW6uZUuDggIAEzlmC9dupTn9l1dXYmIiMi2/MqVK1n2l1+3kofIyMhs63Ja1r9/f/r3709SUhLbt29n6tSpPP3005w5cyazB/FBbN68mStXrrB169bMM9dgKsyQX25ubmg0Gnbs2JHjBe45LbuX/DwnucVSu3ZtPvjggxzX30p0oXCO6d09Ibee59xeO/f7uilIhRGbm5sbrq6uuX7OOTo65npfb29vatSowYYNG0hOTsbOzi5bm127dhEVFUXPnj3vOza493N+P6+fh6XVamnXrh1///03ly5duufJm/y+V289r3cWtrnl7s+Wh3m+ClKFChVyTYjyq2HDhri4uLB69Wpmz559z9ELQtyLDNUTIhd2dna0bduWgwcPUrt2bRo2bJjtL6ez5KVKlaJHjx68/vrrxMXFZekluKVcuXKMHDmSp556qsjnX7r1xXH3D9evv/66SOO4U5MmTfD29mbp0qVZlq9atYobN27cc36WnH7kgelsbHh4eOYPm4CAACpXrszhw4dzfD4bNmyY+aOgc+fObNmyJVtFwju1a9eOEydOZHsOv//+ezQaTZZ5cfIjICAAb29vVqxYgVIqc3lYWBg7d+7M9X729vZ07tyZyZMnk56ezvHjx+9rv3e7n9dIbr2PTz/9NEopLl++nONxvpUs34/OnTtz5syZbEMg7+Xpp5/m2LFjVKxYMcdYcvrhW9DH9E7NmjXD1taWH3/8McvyS5cusXnzZtq1a1dg+7pfhRHb008/TWxsLAaDIcfjf+tkRW4mT57MtWvXcuwlTkpKYvTo0djZ2fHGG2/cd2x3yu05z+/rp6B64idOnIhSisGDB5Oenp5tvV6vz5wTL7/v1YCAALy8vLJVD7148WK2z5aHfb6KE51Ox/jx4zl16hQzZszIsU10dDT//fdfEUcmHlXS4yRKvM2bN+eY3HTp0oXPP/+cli1b0qpVK4YPH0758uVJTEzk3LlzrF27NvMHXLdu3ahZsyYNGzbE3d2dsLAw5s2bh5+fH5UrVyY+Pp62bdvSq1cvqlatiqOjI/v27SMwMLDIJ22sWrUqFStWZMKECSilcHFxYe3atdmG4BSE5ORk1q9fD5B5Pdi2bdu4evVq5o8UMJ1l/eijj+jduzdDhw7llVde4ezZs7zzzjs89dRTdOrUKc/9fPDBB/z333+89NJLmaWvQ0JC+PLLL4mNjeXjjz/ObPv111/TuXNnOnbsSL9+/ShTpgxxcXGcPHmS4OBgfv31VwCmT5/O33//TevWrZk0aRK1atXi+vXrBAYGMm7cOKpWrcobb7zB999/T9euXZk+fTp+fn789ddfLFiwgOHDh1OlSpX7Ol4WFhbMmDGDQYMG8dxzzzF48GCuX7/O+++/n2343uDBg7G1taVFixZ4e3sTGRnJ7NmzcXZ2plGjRvfc1/nz51m1alW25dWrV6d58+aULl2aYcOGMXXqVHQ6HcuXL+fw4cPZ2t9KgObMmUPnzp3RarXUrl2bFi1aMGTIEPr378/+/ftp3bo19vb2RERE8O+//1KrVq0swyrzY+zYsfzyyy90796dCRMm0LhxY1JSUti2bRtPP/10ronq9OnT2bhxI82bN2f06NEEBASQmppKaGgo69evZ9GiRZQtW/ahj2l+lSpViilTpjBp0iT69OnDK6+8QmxsLNOmTcPGxoapU6cW2L6KQ2wvv/wyy5cvp0uXLowZM4bGjRuj0+m4dOkSW7ZsoXv37jz33HO53v+VV14hODiYTz75hNDQUAYMGICnpyenT59m7ty5nD9/np9++inb8M/8yM9znt/Xj6OjI35+fqxevZp27drh4uKCm5tb5nBeS0tLnnjiiXte59SsWTMWLlzIiBEjaNCgAcOHD6dGjRro9XoOHjzI4sWLqVmzJt26dcv3e9XCwoJp06YxdOhQevTowYABA7h+/TrTpk3D29s7y5QND/t8FTdvv/02J0+eZOrUqezdu5devXplToC7fft2Fi9ezLRp07Jd6yVEjsxYmEIIs7pVVS+3v1vV2EJCQtSAAQNUmTJllE6nU+7u7qp58+aZk/AppdSnn36qmjdvrtzc3JSVlZUqV66cGjhwoAoNDVVKmUrVDhs2TNWuXVs5OTkpW1tbFRAQoKZOnaqSkpLyHfODTIB7q/LQnaW2T5w4oZ566inl6OioSpcurXr27KkuXryYrSLUrap6MTExOR67uyvW3S2vqkc5Teb6008/qdq1aysrKyvl5eWlRo8erRITE/Pch1Kmyluvv/66qlOnjnJxcVFarVa5u7urTp065Th57uHDh9WLL76oPDw8lE6nU15eXurJJ5/MVnkpPDxcDRgwQHl5eSmdTqd8fHzUiy++qKKiojLbhIWFqV69eilXV1el0+lUQECA+vjjj7NMupvXRI13H3OllPr2229V5cqVlZWVlapSpYr67rvvsk2Au2zZMtW2bVvl6emprKysMmM7cuTIPY9XXq/7W7Hs3LlTNWvWTNnZ2Sl3d3c1aNAgFRwcnO21lJaWpgYNGqTc3d2VRqPJ9rr47rvvVJMmTZS9vb2ytbVVFStWVH369MlSfviJJ55QNWrUyBZnTpP+Xrt2TY0ZM0aVK1dO6XQ65eHhobp27apOnTqV5zGNiYlRo0ePVv7+/kqn0ykXFxfVoEEDNXnyZHXjxo2HPqZ5VdXLbXLZb7/9NvP17uzsrLp3756tJH9u7/ncjllOceQltxgfJrZbnxt30uv16pNPPlF16tRRNjY2ysHBQVWtWlUNHTpUnT17Nl+xrl+/XnXp0iXzvVamTBnVu3fvHKcxyG9s+X3O8/P6UUqpoKAgVa9ePWVtba0A1bdv38x15KMc+Z0OHTqk+vbtq8qVK6esrKyUvb29qlevnnrvvfdUdHR0Zrv8vleVUmrx4sWqUqVKWT5bunfvrurVq5el3cM8Xw/7ms3vpMz5nQD3ltWrV6uuXbsqd3d3ZWlpqUqXLq3atm2rFi1apNLS0vK1DSE0St0xHkQIIYQQQpQI169fp0qVKjz77LMsXrzY3OEIUezJUD0hhBBCiMdcZGQkH3zwAW3btsXV1ZWwsDDmzp1LYmIiY8aMMXd4QjwSJHESQgghhHjMWVtbExoayogRI4iLi8POzo6mTZuyaNEiatSoYe7whHgkyFA9IYQQQgghhLgHs5Yj3759O926dcPHxweNRsOff/55z/ts27aNBg0aYGNjQ4UKFVi0aFHhByqEEEIIIYQo0cyaOCUlJVGnTh2+/PLLfLUPCQmhS5cutGrVioMHDzJp0iRGjx7Nb7/9VsiRCiGEEEIIIUqyYjNUT6PR8Mcff/Dss8/m2mb8+PGsWbOGkydPZi4bNmwYhw8fZteuXUUQpRBCCCGEEKIkeqSKQ+zatYsOHTpkWdaxY0eWLFmCXq9Hp9Nlu09aWhppaWmZt41GI3Fxcbi6umbOuC2EEEIIIYQoeZRSJCYm4uPjk2Uy6Jw8UolTZGQknp6eWZZ5enqSkZHB1atX8fb2znaf2bNnM23atKIKUQghhBBCCPGICQ8Pp2zZsnm2eaQSJyBbL9GtkYa59R5NnDiRcePGZd6Oj4+nXLlyhIeH4+TkVHiBCiGEEEIIIYq1hIQEfH19cXR0vGfbRypx8vLyIjIyMsuy6OhoLC0tcXV1zfE+1tbWWFtbZ1vu5OQkiZMQQgghhBAiX5fwmLWq3v1q1qwZGzduzLJsw4YNNGzYMMfrm4QQQgghhBCiIJg1cbpx4waHDh3i0KFDgKnc+KFDh7h48SJgGmbXp0+fzPbDhg0jLCyMcePGcfLkSb777juWLFnCW2+9ZY7whRBCCCGEECWEWYfq7d+/n7Zt22bevnUtUt++fVm6dCkRERGZSRSAv78/69ev54033uCrr77Cx8eHL774ghdeeKHIYxdCCCGEEEKUHMVmHqeikpCQgLOzM/Hx8XKNkxBCCCGEeKwZDAb0er25wzArnU6HVqvNcd395AaPVHEIIYQQQgghRP7cuHGDS5cuUcL6SbLRaDSULVsWBweHh9qOJE5CCCGEEEI8ZgwGA5cuXcLOzg53d/d8VY17HCmliImJ4dKlS1SuXDnXnqf8kMRJCCGEEEKIx4xer0cphbu7O7a2tuYOx6zc3d0JDQ1Fr9c/VOL0SJUjF0IIIYQQQuRfSe1pulNBHQNJnIQQQgghhBDiHiRxEkIIIYQQQoh7kGuchBBCCCGEEDkyGBV7Q+KITkzFw9GGxv4uaC1K5vA/SZyEEEIIIYQQ2QQei2Da2hNExKdmLvN2tmFqt+p0qultlph+//13vv76aw4cOEBsbCwHDx6kbt26RbJvGaonhBBCCCGEyCLwWATDfwzOkjQBRManMvzHYAKPRZglrqSkJFq0aMGHH35Y5PuWHichhBBCCCEec0opUvSGfLU1GBVT1xwnp2lzFaAB3l9zghaV3PI1bM9Wp813Zbs2bdpQs2ZNAH788Ue0Wi3Dhw9nxowZaDQaevfuDUBoaGi+tleQJHESQgghhBDiMZeiN1D9vX8KZFsKiExIpdb7G/LV/sT0jthZ5T/tWLZsGQMHDmTPnj3s37+fIUOG4Ofnx+DBgx8w4oIhiZMQQohCoQwGkvcfICMmBkt3d+waNkDzEBMPCiGEKBl8fX2ZO3cuGo2GgIAAjh49yty5cyVxEkII8fhJ2LCBqFmzyYiMzFxm6eWF56SJOHXoYMbIhBCiZLLVaTkxvWO+2u4NiaPf//bds93S/o1o7O+Sr33fj6ZNm2YZ2tesWTM+/fRTDAYDWjOegJPESQghRIFK2LCBy2PGgso6Oj4jKsq0/PN5kjwJIUQR02g0+R4u16qyO97ONkTGp+Z4nZMG8HK2oVVl9xJVmlyq6gkhhCgwymAgatbsbEmTaaVpWdSs2ShD/i5QFkIIUfS0FhqmdqsOmJKkO926PbVb9UJLmnbv3p3tduXKlc3a2wSSOAkhhChAyfsPZBmel41SZERGkrz/QNEFJYQQ4r51qunNwtfq4+Vsk2W5l7MNC1+rX6jzOIWHhzNu3DhOnz7NihUrmD9/PmPGjAEgLi6OQ4cOceLECQBOnz7NoUOHiMzru6eAyFA9IYQQBSYjJiZf7SLeew+7evWw8vfHyr88VuXLY+Xnh4W1dSFHKIQQIr861fTmqepe7A2JIzoxFQ9HGxr7uxT68Lw+ffqQkpJC48aN0Wq1jBo1iiFDhgCwZs0a+vfvn9n25ZdfBmDq1Km8//77hRqXJE5CCCEKjKW7e77a6cPCiA8Ly7pQo0FXpowpmSpfHiv/8lj7+2Pl74+lp2e+5wARQghRcLQWGppVdC3Sfep0OubNm8fChQuzrevXrx/9+vUr0nhukcRJCCFEgbFr2ABLL6/ch+tpNGhdXfGcOAH9xYukhYSQHhJKekgIxhs30F+6hP7SJZJ27Mh6N1tbrMqXx9q/PFblb/VSmf7VOjgUwSMTQghR0kniJIQQosBotFo8J4zn8tg3clhp6jHyem9Ktqp6SikMsbGkh4TcTqZCTQlV+qVLqJQU0k6eJO3kyWybtXR3v9lD5Z859M+6fHl0ZcuisZSvOSGEEAVDvlGEEEIULIubdYc0mizV9Sw9PXOdx0mj0WDp5oalmxt2jRplWaf0etLDL91OpEJvJlehYRiuXiUjJoaMmBiS990154hOh5Wv782hf36Zw/6s/P3Rli4tQ/+EEKIY2rp1q7lDyJUkTkIIIQqMUorYxd8A4DJkMA7NW5ARE4Oluzt2DRugeYBSshqdDusK/lhX8AfaZllnSEjITKjSQkMzh/2lh4ai0tJIv3CB9AsXsm3TwsnpZs+U/x3XVJkSLClQIYQQIieSOAkhhCgwybt2kXrsGBobG1z79sXS5d4zyj8MrZMTtrVrY1u7dpblymgkIzIyyzVUtxIsfUQExoQEUg8fIfXwkawb1GjQ+fjcMfTvZoGK8uWx9PJCYyGzeAghREkliZMQQogCc/Vmb1Opnj0LPWnKi8bCAp2PDzofH2jRIss6Y2oq6WFhN6+jCrl5XdXNAhWJiegvX0Z/+TJJ//2XdZs2NqaE6q6Kf1bly6N1dCyw2JXBYJoP6yF76oQQQhQsSZyEEEIUiJQjR0jevRssLXHt38/c4eTKwsYGm4AAbAICsixXSmGIi7tdoOLOoX/h4ajUVNJOnSLt1Kls29S6uWGdOdzvdm+VVdmyaHS6fMeWsGEDUbNmZ6lKaOnlleu1YUIIIYqOJE5CCCEKxNXFiwFw7tbN1NPziNFoNFi6umLp6opdw4ZZ1im9Hv3ly9mG/qWFhmCIuYrh6lWSr14lef/+rBu1tMSqbNlsFf+s/P3RurpmKVCRsGEDl8eMzVJQAyAjKsq0/PN5kjwJIYQZSeIkhBDioaWdO8eNoE2g0eA6aKC5wylwGp0uc5jeXfUpMCQmmnqnbhWpuKOcukpNzVzHli1Z7mfh6JhZkMLKz4+4H37IljQBpmUaDVGzZuPYrp0M2xNCCDORxEkIIcRDi/12CQCO7dthXbGimaMpWlpHR2xr1cK2Vq0sy5XRSEZU1B1D/8JMPVUhIeivXMGYmEjqkSOkHjmSy5bv3JgiIzKS5P0HsG/SuJAeiRBC5MBogLCdcCMKHDzBrzlYlMwTOJI4CSGEeCj6K1eIX7cOANchQ8wcTfGhsbBA5+2Nztsb++bNs6wzpqaSfvFi5rC/Gzt2kHLgwD23mRETU1jhCiFEdifWQOB4SLhye5mTD3SaA9WfKfJw9Ho97777LuvXr+fChQs4OzvTvn17PvzwQ3yKYIi41FUVQgjxUGK/+x9kZGDXrGm2XheRMwsbG2yqVMGpYwfchg3FffTofN3P0t29kCMTQoibTqyBlX2yJk0ACRGm5SfWFHlIycnJBAcHM2XKFIKDg/n99985c+YMzzxTNEmc9DgJIYR4YBlxcVxftQoAN+ltemB2DRtg6eVFRlRUztc5aTRYenpi17BB0QcnhHg8KAX65Py1NRrg73eAHD6PUIDG1BNVoU3+hu3p7OCOYjh5adOmDTVr1gTgxx9/RKvVMnz4cGbMmIGzszMbN27M0n7+/Pk0btyYixcvUq5cuXzt40FJ4iSEEOKBxX3/PSo1FZtatbBr2tTc4TyyNFotnpMmmqrnaTTZkyel8Jw0UQpDCCEenD4ZZhXUcDZl6on60Dd/zSddASv7fG992bJlDBw4kD179rB//36GDBmCn58fgwcPztY2Pj4ejUZDqVKl8r39ByVD9YQQQjwQw40bXFv+EwCugwdlKa0t7p9Thw6U+Xwelp6e2VfqdNhUrVr0QQkhhBn4+voyd+5cAgICePXVVxk1ahRz587N1i41NZUJEybQq1cvnJycCj0u6XESQgjxQK7/8gvGxESsKlTAsX17c4fzWHDq0AHHdu1I3n+AjJgYtG6uXF2wkJS9e4mY/C7lli1FYyHnPIUQD0BnZ+r5yY+wnbC8x73bvbrKVGUvP/u+D02bNs1yMq5Zs2Z8+umnGAwGtDd73vV6PS+//DJGo5EFCxbc1/YflCROQggh7psxLY3YpUsBcB00SH7MFyCNVpul5LhVmTJceKY7yfv2ce3nn3Hp1cuM0QkhHlkaTf6Hy1V80lQ9LyGCnK9z0pjWV3zSLKXJ9Xo9L774IiEhIWzevLlIeptAhuoJIYR4APF//Ikh5iqW3t44P93V3OE81qx8ffEYNw6A6E8+Jf3SJTNHJIR47FloTSXHAbh7GPbN250+LLSkaffu3dluV65cGa1Wm5k0nT17lqCgIFxdXQslhpxI4iSEEOK+qIwMYpeYJrx17d8fjZWVmSN6/JV+tRe2DRugkpOJmDIFlVPlPSGEKEjVn4EXvwcn76zLnXxMywtxHqfw8HDGjRvH6dOnWbFiBfPnz2fMmDFkZGTQo0cP9u/fz/LlyzEYDERGRhIZGUl6enqhxXOLDNUTQghxXxIC/0EfHo62dGlK9czHGHjx0DQWFvjMnMmF7s+SvGs311f+SumXXjR3WEKIx131Z6BqV9M1TzeiwMHTdE1TIQ/P69OnDykpKTRu3BitVsuoUaMYMmQIYWFhrFljmj+qbt26We6zZcsW2rRpU6hxSeIkhBAi35RSxH7zDQCle7+Gha2tmSMqOazKl8f9jbFEfziH6I8+wqFVS3Q+BVVaWAghcmGhBf9WRbpLnU7HvHnzWLhwYZbl5cuXN2uPuwzVE0IIkW9J27eTdvo0FnZ2uLz6qrnDKXFcevfGtm5djElJRLw3VYbsCSFEEZLESQghRL5dXWzqbSr18stonZ3NHE3Jo9Fq8Z71ARorK5L+/Zf43/8wd0hCCFFiSOIkhBAiX5IPHCDlwAE0Oh0uffuaO5wSy7pCBdxHjwIg6sMP0UdFmTkiIYQoOFu3bmXevHnmDiNHkjgJIYTIl6uLFwPg/Nxz6Dw9zBxNyebSrx82tWphTEwkUobsCSFEkZDESQghxD2lnjpF0rbtYGGB68AB5g6nxNNYWuIz6wM0Oh03tm0j4WaVKSGEEIVHEichhBD3FHvz2ianTh2x8vMzczQCwLpyZdxefx2AyFmz0UdHmzkiIYR4vEniJIQQIk/pYWEkBAYC4Dp4sJmjEXdyHTgAm+rVMcbHEzl9ugzZE0KIQiSJkxBCiDzFfvc/MBqxb90Km2rVzB2OuINGp8N79izQ6bgRtImE9evNHZIQQjy2JHESQgiRK310NPG//w6A25AhZo5G5MQmIAC3oUMBiJoxk4yrV80ckRBCPJ4kcRJCCJGruGXLUHo9tvXrY9ewobnDEblwGzIY64AADNevEzljprnDEUI8RgxGA/si97H+wnr2Re7DYDSYOySzkcRJCCFEjgzx8Vxf8TMArkPk2qbiTGNlhfesD0CrJfGff0gI/MfcIQkhHgNBYUF0/K0jA/4ZwPgd4xnwzwA6/taRoLAgs8X0/vvvU7VqVezt7SldujTt27dnz549RbJvSZyEEELk6NpPP2FMTsa6ShUcnnjC3OGIe7CtUSMzwY2cPp2Ma9fMHJEQ4lEWFBbEuK3jiErOOsl2dHI047aOM1vyVKVKFb788kuOHj3Kv//+S/ny5enQoQMxMTGFvm+NKmEleBISEnB2diY+Ph4nJydzhyOEEMWSMSWFc0+2w3DtGj4ff4xzt6fNHZLIB2N6OqEvvEDa2XM4de1KmU8/MXdIQggzSU1NJSQkBH9/f2xsbFBKkZKRkq/7GowGnl3zLNHJuU9z4GnnyR/P/IHWQnvP7dla2qLRaPK17zZt2lCzZk0AfvzxR7RaLcOHD2fGjBk5buPWb/ugoCDatWuX4zbvPhY53T8/uYFlvh6BEEKIEuX6qt8wXLuGztcXp86dzB2OyCcLKyu8Z80i9KWXSfjrL5w6d8KxfXtzhyWEKAZSMlJo8lOTAtteVHIUzX9unq+2e3rtwU5nl+9tL1u2jIEDB7Jnzx7279/PkCFD8PPzY/BdU2Kkp6ezePFinJ2dqVOnzn3F/yBkqJ4QQogslF5P7P++A0zzBGks5Rzbo8S2Vi1cBw4AIOL9aRiuXzdvQEIIcZ98fX2ZO3cuAQEBvPrqq4waNYq5c+dmrl+3bh0ODg7Y2Ngwd+5cNm7ciJubW6HHJd+GQgghsohf9xcZVyLQurvh/Nxz5g5HPAC3kSNJ3LSZ9AsXiJo9G585c8wdkhDCzGwtbdnTK39FFA5EHWDEphH3bLeg3QIaeDbI177vR9OmTbMMy2vWrBmffvopBoMBrVZL27ZtOXToEFevXuWbb77hxRdfZM+ePXh4eNzXfu6X9DgJIYTIpIxGYr/9FgDXvn2xsLY2c0TiQVhYW+Mz6wOwsCB+9RoSt241d0hCCDPTaDTY6ezy9dfcpzmedp5oyPm6JA0avOy8aO7TPF/by+/1Tfllb29PpUqVaNq0KUuWLMHS0pIlS5YU6D5yIomTEEKITImbNpF+/jwWjo6Uevllc4cjHoJt3bq49O0LQOR7UzEkJJg5IiHEo0JroWVC4wkA2ZKnW7fHNx6fr8IQD2L37t3ZbleuXBmtNuf9KaVIS0srlFjuJImTEEIIwPTFE7v4GwBK9+qF1sHBzBGJh+U+ZjRWfn5kREcTJcP1hBD3ob1fez5r8xkedlmHv3naefJZm89o71d4hWfCw8MZN24cp0+fZsWKFcyfP58xY8aQlJTEpEmT2L17N2FhYQQHBzNo0CAuXbpEz549Cy2eW+QaJyGEEAAk79lD6tGjaKytcenT29zhiAJgYWOD96wPCHutN/G//Y5Tp044tGpl7rCEEI+I9n7taevbluDoYGKSY3C3c6e+R/1C62m6pU+fPqSkpNC4cWO0Wi2jRo1iyJAhpKWlcerUKZYtW8bVq1dxdXWlUaNG7Nixgxo1ahRqTCCJkxBCiJtiFy8GoFSPHli6upo5GlFQ7Bo0oPRrr3Hthx+ImPIeFdatld5EIUS+aS20NPJqVKT71Ol0zJs3j4ULF2ZZbmNjw++//16ksdxJhuoJIYQg5egxknbuAktLXAf0N3c4ooB5vDEWna8vGZGRRH/0sbnDEUKIR5IkTkIIITJ7m5y7dkVXpoyZoxEFzcLODu+ZMwG4vnIlSbt2mTkiIYR49EjiJIQQJVzahQskBgUB4DpooJmjEYXFvkljSvd6BYCId6dgTEoyc0RCCJHd1q1bmTdvnrnDyJEkTkIIUcLFfvMtKIVDu3ZYV65s7nBEIfJ48010Pj7oL18m+tPPzB2OEEI8UiRxEkKIEkwfEUH82rUAuA0ZbOZoRGGzsLfHe+YMAK799BNJe/aaOSIhhHh0SOIkhBAlWOz//gcZGdg1aYJtnTrmDkcUAfvmzSl1c76TiHffxZicbOaIhBDi0SCJkxBClFAZ165x/ddVALhKb1OJ4vHO21h6eaEPDye6mF5LIIQQxY0kTkIIUUJd++EHVEoKNjVqYN+8ubnDEUVI6+iI94zpAFz74UeSg4PNHJEQQhR/kjgJIUQJZLiRRNyPywFwHTwYjUZj5ohEUXNo1Qrn558HpYiYNBljaqq5QxJCiGJNEichhCiBrv/yC8aEBKzKl8fxqfbmDkeYieeE8Vh6eJAeGkrMF/PNHY4QohhSBgNJe/YSv+4vkvbsRRkM5g7JbCRxEkKIEsaYnk7c0qUAuA4ehEarNW9Awmy0Tk54TXsfgLilS0k5dMis8QghipeEDRs41649F/v25cpbb3Gxb1/OtWtPwoYN5g4NgKFDh6LRaIps3idJnIQQooSJ//NPMmJisPTywrlbN3OHI8zMsW1bnJ7pBkYjVyZNxpiWZu6QhBDFQMKGDVweM5aMyMgsyzOiorg8ZqzZk6c///yTPXv24OPjU2T7lMRJCCFKEGUwELtkCQCu/fuhsbIyc0SiOPCaNAmtmxvpFy5w9cuvzB2OEKIQKKUwJifn68+QmEjUzA9AqZw2BCiiPpiFITExX9tTOW0nF23atGHkyJGMHDmSUqVK4erqyrvvvptlG5cvX2bkyJEsX74cnU5XAEcnfyyLbE9CCCHMLvGff9CHXUTr7Jw5l48Q2lKl8H5/KpdGjiL2u+9w7NAB21o1zR2WEKIAqZQUTtdvUEAbM/U8nWnUOF/NA4IPoLGzy/fmly1bxsCBA9mzZw/79+9nyJAh+Pn5MXjwYIxGI7179+btt9+mRo0aD/oIHoj0OAkhRAmhlOLq4m8AKN27Nxb38SUmHn+O7dvj1KULGAxETJqEMT3d3CEJIUooX19f5s6dS0BAAK+++iqjRo1i7ty5AMyZMwdLS0tGjx5d5HFJj5MQQpQQSTt2kHbqFBo7O1xee9Xc4YhiyHPKuyTt3k3a2bPELlqEuxl+mAghCofG1paA4AP5apu8fz/hQ4bes53v4q+xa9gwX/u+H02bNs0yTUazZs349NNPOXDgAJ9//jnBwcFmmUZDepyEEKKEuLp4MQClX3wRbalS5g1GFEuWpUvj9d4UAK5+vZjUEyfMHJEQoqBoNBos7Ozy9WffogWWXl6QW3Ki0WDp5YV9ixb52l5BJTlbt24lOjqacuXKYWlpiaWlJWFhYbz55puUL1++QPaRF0mchBCiBEgODiZl/wHQ6XDp38/c4YhizKlTJxw7dACDgSuTJqNkyJ4QJY5Gq8Vz0sSbN+5Kem7e9pw0sdCms9i9e3e225UrV6Zfv34cOXKEQ4cOZf75+Pjw9ttv888//xRKLHeSxEkIIUqA2JvXNpV6tjs6T08zRyOKO6/3pqAtVYq0U6e4+s035g5HCGEGTh06UObzeVje9Z1h6elJmc/n4dShQ6HtOzw8nHHjxnH69GlWrFjB/PnzGTNmDK6urtSsWTPLn06nw8vLi4CAgEKL5xa5xkkIIR5zqafPcGPrVtBocB040NzhiEeApZsbnu++y5W33uLqoq9xbP8UNgFVzB2WEKKIOXXogGO7diTvP2Ca/8/dHbuGDQp94vQ+ffqQkpJC48aN0Wq1jBo1iiFDhhTqPvNDEichhHjMxd7sMXDs2BGrIhgDLh4PTl27kPD339zYtImISZMo/8vPaCzlZ4MQJY1Gq8W+Sf7KjhcUnU7HvHnzWLhw4T3bhoaGFn5AN5l9qN6CBQvw9/fHxsaGBg0asGPHjjzbL1++nDp16mBnZ4e3tzf9+/cnNja2iKIVQohHS3p4OAnr1wPgNmSwmaMRjxKNRoPX1PewcHYm9fhxYpd8Z+6QhBDCrMyaOP3yyy+MHTuWyZMnc/DgQVq1akXnzp25ePFiju3//fdf+vTpw8CBAzl+/Di//vor+/btY9CgQUUcuRBCPBpilywBoxH7li2xqV7d3OGIR4zOwwPPiRMAuPrll6SdPWvmiIQQwnzMmjh99tlnDBw4kEGDBlGtWjXmzZuHr69vrt1yu3fvpnz58owePRp/f39atmzJ0KFD2b9/fxFHLoQQxV9GTAzxv/8BgKv0NokH5Ny9O/ZPtEbp9VyZ/C4qI8PcIQkhHmNbt25l3rx55g4jR2ZLnNLT0zlw4AAd7qrI0aFDB3bu3JnjfZo3b86lS5dYv349SimioqJYtWoVXbt2zXU/aWlpJCQkZPkTQoiSIO7771Hp6djWrYtdo0bmDkc8ojQaDd7Tp2Ph6EjqkSPELVtm7pCEEMIszJY4Xb16FYPBgOddJQ49PT2JjIzM8T7Nmzdn+fLlvPTSS1hZWeHl5UWpUqWYP39+rvuZPXs2zs7OmX++vr4F+jiEEKI4MiQkcO2nFYCpt8kcM6yLx4fO0xPPCeMBiPn8C9IuhJg5IiFEfimlzB2C2RXUMTB7cYi7v8yVUrl+wZ84cYLRo0fz3nvvceDAAQIDAwkJCWHYsGG5bn/ixInEx8dn/oWHhxdo/EIIURxd+2kFxqQkrCtXwqFNG3OHIx4Dzs8/j33Llqj0dCImT0YZDOYOSQiRB+3NkuHpMol15jHQPmQZdbPVFXVzc0Or1WbrXYqOjs7WC3XL7NmzadGiBW+//TYAtWvXxt7enlatWjFz5ky8vb2z3cfa2hpra+uCfwBCCFFMGVNSiPv+ewBcBw9GY2H2c2TiMWAasjeNC92eIeXgQeJ++AHXfv3MHZYQIheWlpbY2dkRExODTqfDooR+FxiNRmJiYrCzs8PyIadUMFviZGVlRYMGDdi4cSPPPfdc5vKNGzfSvXv3HO+TnJyc7QHfyhylG1IIIUyu//Y7hrg4dGXK4NSli7nDEY8RnY8PHm+/TeT77xMz73Mc27bFys/P3GEJIXKg0Wjw9vYmJCSEsLAwc4djVhYWFpQrV+6hh62bdSa7cePG0bt3bxo2bEizZs1YvHgxFy9ezBx6N3HiRC5fvsz3N8+cduvWjcGDB7Nw4UI6duxIREQEY8eOpXHjxvj4+JjzoQghRLGg9Hpiv1sCgMvAATJhqShwpV56kYTAQJJ37yZi8ruU+36Z9GoKUUxZWVlRuXLlEj9cz8rKqkB63Mz6jfrSSy8RGxvL9OnTiYiIoGbNmqxfvx6/m2evIiIisszp1K9fPxITE/nyyy958803KVWqFE8++SRz5swx10MQQohiJWH9ejKuRKB1daXU88+bOxzxGNJoNHjPnMGFZ7qTvH8/135agctrr5o7LCFELiwsLLCxsTF3GI8FjSphY9wSEhJwdnYmPj4eJycnc4cjhBAFRhmNXHjmGdLPncf9jTdwGzrE3CGJx1jc8uVEzZiJxs6OCmtWY1W2rLlDEkKI+3Y/uYH0rQshxGPixpYtpJ87j4WDA6V7vWLucMRjrvQrr2DXqBEqOZmIye+ijEZzhySEEIVKEichhHgMKKW4ungxYPpBq3V0NHNE4nGnsbDAe+YMNDY2JO/Zw/WVK80dkhBCFCpJnIQQIi9GA4TsgKOrTP8ai+fcNcl79pJ6+Agaa2tc+vYxdzgAGIyKXedjWX3oMrvOx2IwlqiR4SWClZ8fHm+MBSD6o4/RX75s3oCEEKIQSbklIYTIzYk1EDgeEq7cXubkA53mQPVnzBdXDmJv9jaVeuF5LN3czBwNBB6LYNraE0TEp2Yu83a2YWq36nSqmX3OPfHoKv3aayQE/kPKwYNETHkP3yXfPnTJXyGEKI6kx0kIIXJyYg2s7JM1aQJIiDAtP7HGPHHlIOXYcZJ27gStFpcBA8wdDoHHIhj+Y3CWpAkgMj6V4T8GE3gswkyRicKg0Wrx/uADNNbWJO3cSfxvv5k7JCGEKBSSOAkhxN2MBlNPEzkNLbu5LHBCsRm2F/vNNwA4deli9spmBqNi2toTeR05pq09IcP2HjPWFfxxHz0agKgP56CPjDRzREIIUfAkcRJCiLuF7cze05SFgoTLpnZmlnYhhMQNGwBwHTzIzNHA3pC4bD1Nd1JARHwqe0Piii4oUSRc+vXFpk5tjDduEDF1KiVsthMhRAkgiZMQQtztRlT+2oWav1hE7JJvQSkc2rbFpkoVs8YCEJ2Ye9L0IO3Eo0Oj1eLzwQdodDqStm0n/s/V5g5JCCEKlCROQghxNwfP/LXbNgc+rgR/DIPjf0JaYqGGdTd9ZCTxa9YC4DpkcJHuOzcejvmbnT6/7cSjxbpSJdxGjgQgavZs9FHRZo5ICCEKjiROQghxN7/mpup55FEZTGcL1k6QEgeHV8CvfeGjCvDDc7D3G7geXuhhxv3vf6DXY9eoEXb16hX6/vKjsb8Lzra6PNtogDPRiXKd02PKdeAAbGrUwJiQQOS0aTJkTwjx2JDESQgh7mahNZUcz7HEgcb099xieOcC9F0HzUaCSwUwpMP5zbD+LZhXExa2hM0z4fIBMBoLNMSMa9e4tvJXAFyHDCnQbT+MgxevcSNNn2cbBUxdfZznFvzH4fDrRRKXKDoaS0u8Z80CnY4bmzeTsO4vc4ckhBAFQqNK2KmghIQEnJ2diY+Px8nJydzhCCGKq9D/YGmX7MudykCnD7PP46QUXD0LZ/6G039D+B5QdyRLDp5QpRMEdAb/J8DK7qHCi5n/JVe/+grr6tXw/+23YjFvzqVryXT/8j9ik9Kp51uKiPhUIhOyzuP0btdqxCSm8emGMySmZaDRwCuNy/FOxwBK2VmZMXpR0GIWLODqF/PROjtT4a91xWJ+MSGEuNv95AaSOAkhxN0Mevi6NUSfgAb9oGYPU8EIB0/TMD4L7b23kRQLZzeYEqlzmyD9xu11lrZQoY0piarSCRzzeU3VTcakJM4+2Q5jfDxl5n6GU+fO93X/wpCUlkGPRbs4GZFAdW8nVg1vhrWllr0hcUQnpuLhaENjfxe0FqYELzoxldnrT/HHwcsAuNhbMaFTVXo0KIuFhfmTQPHwlF5PyIsvkXbyJI5PPUWZLz4vFgm+EELcSRKnPEjiJIS4p11fwT+TwNYFRh0AO5eH215GGoT+a+qJOhMI8Xdd/1SmAVTpbEqkPGvAPX5cxv5vKdFz5mDl50eF9X+h0eYjkStERqNi+PID/HM8CjcHK1aPbEmZUrb5uu/uC7G8t/oYZ6JMiWX9cqWY8WxNavg4F2bIooiknjxJSM8XISOj2CT5QghxJ0mc8iCJkxAiTwkR8GUjSE+Ebl9Ag74Fu32lIOoYnA6E0+vhSnDW9c6+t4f0lW8JltZZVhvT0znf/ikyoqPxmjGd0j17Fmx8D+CzDaf5YvM5rLQWrBjShAZ+95do6g1G/vdfCPOCzpKcbsBCA32alWdchyo42eRdaEIUfzFffMHVBQvRli5tGrLn8pAnIoQQogBJ4pQHSZyEEHn6bRAc/dXUCzQwCCwKuYZOYqSpF+p0IFzYAhl3zG9k5QCV2pl6oyp3AHtXrv36K5FT3sPSw4OKQRuxsDLvdUFrD19h1IqDAHzSsw49GpR94G1FxKcw86+T/HUkAgB3R2smd6lG97o+MsTrEabS0wnp0ZO0M2dw6tKZMp99Zu6QhBAikyROeZDESQiRq9B/YWlXQANDtoBPEZf4Tk+GkG2mnqgz/2SdiFdjgSrTmAs/xJMeFY/H+Hdw7d+/aOO7y5FL1+m5aBdpGUaGtK7ApC7VCmS7O87GMHX1cS5cTQKgaQUXZnSvSWVPxwLZvih6KceOE/rSS2AwUGb+Fzg99ZS5QxJCCEASpzxJ4iSEyJFBD4taQcxJaDgQnjbzWXGjEa4cvF2lL+oYCRdtuLzTBQsrI5X62KGt1cU0pM+3KWgtizS86IRUnvnyPyITUmkb4M63fRtlFn4oCGkZBr7dEcL8zWdJ1RuxtNAwsKU/o9tVxt66aB+rKBjRn80ldvFitG5uVFi7BsvSpc0dkhBCSOKUF0mchBA52vklbJgMdq4wcv/DF4QoYOpaGCEv9yEtLBq3mkm414y/vdKmlGkoX0AnqNQebAq3sEKq3sBLi3dzOPw6lTwc+H1E80K7Fik8Lpnp606w8YSp983b2YYpT1enc00vGb73iDGmpRHy/Auknz+P0zPdKPPRR+YOSQghJHHKiyROQohsEiLgy4amkuHPzIf6fcwdUTY3dvxL+ODBaGxtqfT3aixjD5iujTrzD6TE3W5oYQl+LSCgiymRKl2+QONQSvHGL4f489AVnG11rH69BeXd7At0HznZfCqKqWuOEx6XAkCrym5Me6YGFdwdCn3fouCkHD5M6Cu9wGik7IIFOD7Z1twhCSFKOEmc8iCJkxAim8yCEA1h4MbCLwjxAMJ69yF53z5c+vbBc+LE2yuMBgjfe/O6qEC4eibrHT2q36zS18VU8OIhH9vCreeZE3gKrYWGHwY0pnmlopvUNFVvYMHW8yzadp70DCNWWguGtK7A620rYWtl3pLsIv+iPvqYuO++w9LdnQrr1qJ1ltLzQgjzkcQpD5I4CSGyCNkBy57GVBBiK/jUNXNA2SUfPEjYK71Ap6PSxg3ovLxybxx73nRN1Om/4eIuUIbb6+zdoXJH03VRFduC1f31FAWdiGLwD/tRCmZ0r0HvZuUf7AE9pNCrSUxdc5xtZ2IAKFvalqndavBU9fubSFiYhzE1lZBnnyM9NBTn557DZ/Ysc4ckhCjBJHHKgyROQohMBj0sagkxp6DRIOj6qbkjylH48BHc2LIF5xeex+eDD/J/x+Q4OBdkSqLOBUFawu11Wmuo8MTtOaOcfPLc1OnIRJ5f8B9J6QZea1qOmc/WesBHUzCUUvxzPJLpa09wJd5Uwr1dVQ/ef6YGvi52Zo1N3Fty8EHCXn0VlMJ38dc4tG5t7pCEECWUJE55kMRJCJFp53zY8K6pIMSoA2Bb/Kp8pZ45Q8gz3UGjocJff2Fdwf/BNpSRDhd33u6Nuh6Wdb13HdNwviqdTP+/o/BCXFI63b/6l/C4FJpVcOX7gY3RaYvHcMbk9Ay+2HSOb3dcIMOosLa04PW2lRjSugI2Ohm+V5xFzZ5N3LLvsfTyosLaNWgdpdy8EKLoSeKUB0mchBDAXQUhvoT6vc0dUY4uv/MOCWvW4tihA2W/+LxgNqoURJ+8Xer80n7gjq8CpzJQpSMEdCHdtwW9lx1mT0gc5VzsWP16C0rbm3fS3Zyci05kyp/H2XUhFoDyrnZM616TJ6q4mzkykRtjSgoXuj+L/uJFSvXsgfeMGeYOSQhRAknilAdJnIQQAKwaCMdWQdlGMGBDsSwIkX7pEuc7dgKDgfKrVmFbs0bh7OhGtKk635lAOL8Z9MmZq9IsbNmir8m/Fg3p328oFf0fsMerCCilWHP4Ch/8dZLoxDQAOtf0YsrT1fEpZWvm6EROkvbu5WKfvgD4LvkWhxYtzByREKKkkcQpD5I4iZLKYDQQHB1MTHIM7nbu1Peoj9aihA5lCtkOy7qBxgIGbymWBSEAIqdP59pPK7Bv3pxy3y0pmp3qU03H58zfJB9di11azB0rNaZEM6Cz6c+9apYhfdkYDRC2E25EgYMn+DWHInjNJabqmbvxLMt2hWIwKuystIxuV5kBLfyxsix+CXJJFzl9Btd++glLH28qrFmL1qHwy9sLIcQtkjjlQRInURIFhQXx4d4PiUqOylzmaefJhMYTaO/X3oyRmYFBDwtbwNXT0GgwdP3E3BHlKOPqVc61a49KS6Pc0qXYN21SpPv/9+xV+v5vD1VVCNMCwmiYtgciDmdtVLo8VLmZRPk1B+0dk+CeWAOB4yHhyu1lTj7QaQ5Uf6ZIHsPJiASm/HmM/WHXAKjk4cCM7jVpVtG1SPYv8seYlMSFZ7qjv3yZUq+8jPfUqeYOSQhRgkjilAdJnERJExQWxLit41BkfatrMPUUfNbms5KVPP33BWycAnZuMGp/sSwIARD96WfEfvMNNnVqU/7nn9Hk1bNTwEKuJtH9y39JSM3g+Xpl+PTFOqb9x182Dec7/bepV8qQdvtO1s5Qub0pkTJmwJ/Dgbu/Xm4+hhe/L7LkyWhU/BZ8iQ//PkVsUjoA3ev6MLlLNTycbIokBnFvSbt3c7FffwCznCgQQpRckjjlQRInUZIYjAY6/tYxS0/TnTRo8LTzJPCFwJIxbC/hCsxvCPok6P4V1HvN3BHlyJCYyLm2T2K8cYOyX87HsX3RJbbxKXqeW/AfF2KSqFeuFCsGN825Ol3aDbiwBU4HmpKp5Kv53IPG1PM09miRDNu7JT5ZzycbTvPjnjCUAkdrS954qgp9mvlhWUwqBJZ0EVPf5/ovv6ArW5YKa1ZjYSdl5YUQhe9+cgP5thDiMRYcHZxr0gSgUEQmRxIcHVyEUZnRhndNSVPZxlCnl7mjydW1FT9jvHEDq0oVcXjyySLbr8GoGL3iIBdikvB2tuHr3g1yL+lt7QDVusGzX8FbZ2DgRmg5DpzL3WMvChIum659KkLOdjpmPFuTNa+3pI5vKRLTMpi+7gTdvvyPA2FxRRqLyJnH229h6e2N/tIloj+ba+5whBAiG0mchHiMxSTH3LsRsOrMKkLiQwo5GjO7sA2O/WYqCNH1k2JZRQ/AmJpK3LJlALgOGoSmCOOcvf4k287EYKOz4Js+DfFwzOdQNgst+DaG9lNNf/lxI/eEvjDVKuvMH8ObM+u5Wjjb6jgZkcALC3fx9q+Hib2Rdu8NiEKjdXDAe/p0AK79+CPJ+/ebOSIhhMiqeP5yEEI8NKUU56+fz1fb9SHreebPZ3j6j6f5ZN8n7IvcR4Yxo5AjLEIZ6bD+bdP/Gw0yTfBaTF3//XcMsbHofHxw7tq1yPa7cl843/5rSp4/7VmXmmWcH2xDDp4F264QWFho6NWkHFveasNLDX0B+PXAJZ78dBs/7g7DYCxRI9iLFYdWLXF+4XkArkyejDElxcwRCSHEbZI4CfEYunD9AoM2DGLx0cX3bOtk5UQz72ZYWlgSlhDGshPLGPDPAJ745Qkm7JhAYGggiemJRRB1Idqz0FRFz84N2k42dzS5UhkZxC35DgCXAQPQ6HT3uEfB2B8ax+Q/jwIwpl1lutb2fvCN+TU3XcNEHsUsLG3Ao9qD76OAuNhbMadHbX4b3pzq3k7Ep+h5989jPLfgPw6HXzd3eCWW5/jxWHp6og+7SMznX5g7HCGEyCTFIYR4jCTrk1l0ZBE/HP+BDJWBtdaaJ8s9yd8hf6NBk6Wy3t1V9W6k32DnlZ1su7SN7Ze2cz3temZbS40lDb0a0sa3DU+UfYKyjmWL+qE9uPjL8GWjmwUhFkC9V80dUa7i16zhyjvj0bq4UGlTEBa2hT9p66VryTz71X9cvZFO55pefNWrPhYWD1nB78QaWNnn5o1cvmJKlYOeS6FMg4fbVwHJMBj5cXcYn244Q2JaBhoNvNK4HO90DKCUnZW5wytxbmzbRvjQYaDR4PfTcuzq1TN3SEKIx5RU1cuDJE7icaSUIuhiEB/t+4jIpEgA2pRtw/jG4ynrWDbHeZy87LwY33h8jqXIDUYDh2MOszV8K1svbc12/VOlUpVo49uGNr5tqOVWCwtNMe68/rU/HP8dfJtA/8Bie22TMhoJ6d6dtLPncB87Brdhwwp9n0lpGfRYtIuTEQlU93Zi1fBm2FlZFszGc5zHqQw0GQb7l8C1ULDQQcdZ0Hhw3hPpFqHoxFRmrz/FHwcvA6ZeqQmdq9KjftmHTyjFfbkyfgLxq1dj5e+P/x+/Y2Ej5eOFEAVPEqc8SOIkHjdhCWHM3jOb/678B0AZhzJMaDyBNr5tsrQzGA0ERwcTkxyDu5079T3q57sEeVhCmCmJCt/KweiDGJQhc52LjQtPlH2CJ3yfoJl3M+x0xaiE8IWt8H13U0GIIdvAu7a5I8pV4uYtXBoxAgt7eypt2Yy2kD+fjEbFiOXBBB6PxM3BitUjW1KmVAH3cBkNpup5N6JM1zT5NTcVkki5Dqtfh1PrTO2qPwvPzAeb4vOZvPtCLFP+PMbZ6BsANPArzYzuNanuU3xifNwZrl/nfLduGGKu4jpoIB5vvWXukIQQjyFJnPIgiZN4XKRmpPLt0W/57th36I16dBY6+tfsz6Bag7C1LLwhXvFp8ey4vINt4dv49/K/3NDfyFxnZWFFE+8mmUP6PO3NVwCAjHRY1AKunoHGQ6HLR+aL5R6UUoS90ouUQ4eK7AfiZxtO88Xmc1hpLVgxpAkN/FwKfZ9ZKAW7F5omIzZmgEsF6LmsWCW3eoOR//0XwrygsySnG7DQQN/m5XnjqSo42RTN9WclXeKmTVx6fSRYWFD+5xXY1i4+rw8hxONBEqc8SOIkHgfbwrcxe+9sLt8wDSdq7tOcSU0m4efkV6Rx6A16DkQfyOyNuhXPLdVdq9OmrGlIX1WXqmiKcjjWv/MgaCrYu8PI/WBbquj2fZ+S9u7lYp++aKysqLQpCEt390Ld39rDVxi14iAAn/SsQ48GZrxmLXwfrOoP8eGgtTYluPX7FpuhewAR8SnMXHeSv45GAODuaM3kLtXoXtenaF/TJdTlt94mYd06rCpVxP/337GwkmvOhHiUPcwImMIgiVMeJHESj7LLNy4zZ+8ctoRvAcDTztN0nVK59mb/AaeU4tz1c2y7tI0t4Vs4GnM0SzEKTzvPzJ6oxt6NsdZaF14wdxaEeHYh1C2+k90CXBw0mKR//6XUyy/h/f77hbqvo5fi6bFoJ2kZRoa0rsCkLuavbkdyHPwxDM7+Y7pd+yXo+plpkt1iZPuZGKauOU7I1SQAmlZwYUb3mlT2dDRzZI+3jGvXuPB0NwyxsbgOG4rH2LHmDkkI8YByuuba086TCY0n5HjNdVGQxCkPkjiJR1G6IZ2lx5fyzZFvSDWkYqmxpHeN3gyrPax4XVN0h6spV9lxaQdbw7eyK2IXKRm352OxtbSluU9z2vi2oXXZ1rjYFPAwsV/7wfE/wLcp9P+72BaEAEg5fpzQF3qAhQUV/wnEyte30PYVnZDKM1/+R2RCKm0D3Pm2byO0xaXggdEIO7+ATdNBGcCtCrz4fbEoW36ntAwD32y/wJdbzpGqN2JpoWFgS39Gt6uMvXUBFdYQ2ST8s4HLY8aAVkv5lb9gW6OGuUMSQtynoLAgxm0dl+WkKmSv8lvUJHHKgyRO4lGz88pOZu+ZTWhCKACNvBoxuclkKpaqaN7A7kOaIY09EXvYFr6NreFbiU6JzlynQUMd9zo84fsEbX3bUsG5wsP1np3fAj88ayoIMXQ7eNV66PgL06Wxb5AYGIhT166U+fSTQttPqt7AS4t3czj8OpU8HPh9RPPieZ1O2C7T0L3ECLC0hac/K5Y9huFxyUxbe4Kgk6azpt7ONkx5ujqda3qZvff3cXXrvWIdEID/ryvRyJA9IR4ZBqOBjr91zNLTdCcNGjztPAl8IbDIh+1J4pQHSZzEoyIyKZKP933MhrANALjZuvFWw7fo4t/lkf5hppTiZNzJzOuiTsadzLK+rEPZzFLn9T3ro7O4jx/3GemwsDnEnjWVve48p0BjL2jpoaGc79wFlMJ/9Z/YBAQUyn6UUoxbeZg/Dl7G2VbH6tdbUN7NvlD2VSBuxMAfQ+D8ZtPteq9B54/Bqvj1rm46GcX7a48THmfqUW1V2Y3p3WviX5yP7yMqIzbWNGTv2jXcXn8d91EjzR2SECKf9kXuY8A/A+7Z7ruO39HIq1ERRHSbJE55kMRJFHd6o57lJ5az4PACUjJSsNBY0KtqL0bUHYGj1eN3LUVkUiTbL21nS/gW9kbsJd2YnrnOUedIyzItaePbhhZlWuBs7Zz3xv6dC0HvPxIFIQAipkzh+q+rcHjiCXy/XlRo+1m49TxzAk+htdDww4DGNK/kVmj7KjBGA+z4FLbOBmUEjxrw4jJwq2zuyLJJ1RtYsPU8i7aeJ91gxEprwdAnKjCiTSVsrcx3wfPjKP6vv7jy5ltgaYn/ql+xqVrV3CEJIfJh/YX1jN8x/p7t5rSaQ5cKXYogotskccqDJE6iONsXuY9Ze2Zx7vo5AOq61+Xdpu8S4FI4PRHFTbI+mV1XdrH10la2X9pOXGpc5jqtRksDzwY8UfYJ2vi2oZxTuax3jr90syBEMjy7COq+UsTR3x99VBTn2j8Fej1+Py3Hrn79QtlP0IkoBv+wH6VgRvca9G5WvlD2U2gubIPfBkFSNFg5QLfPoVYPc0eVo9CrSUxdc5xtZ2IAKFvalve71aB9dTOW5X/MKKW4PHo0iRuDsK5eDf9ffkGjK4ZDToUQWUiP0yNKEidRHF1Nucqn+z9l3QXThKClrUvzRoM36F6pOxaa4lvYoDAZjAaOXj3K1vCtbLu0LTOZvKWCc4XM66Jqu9VGu2oAnPgTyjUzFYQo5sMZoz6cQ9zSpdg2bED5H38slH2cjkzk+QX/kZRu4NUm5fjgueJ9vVeuEiNNyVPoDtPthgOh4yzQ2Zg3rhwopfjneCTT157gSnwqAO2reTC1Ww18XYrfUMNHUUZMjGnIXnw87mPH4DZsmLlDEkLcw6awTYzdOjbX9XKNUzEliZMoTjKMGfxy+he+PPglN/Q30KChZ5WejK4/+t7D0kqY8MTwzOISB6IOkKEyMteVtrSn1bUo2qSk0fyV1diXLdqzVfcr49o1zrVrj0pOxnfx1zi0bl3g+4hLSqf7V/8SHpdC0wou/DCwCTrtI5yEGzJg24ew/WPTba/apqF7LhXMG1cuktMz+GLTOb7dcYEMo8La0oKRbSsx5IkKWFvK8L2HFb9mDVfeGY9Gp8P/99+wrlz8hnAKIUx+P/s703ZNw6iMOa6XqnrFmCROorg4FH2ID/Z8wKm4UwDUcK3Bu03fpaZbTTNHVvwlpCfw3+X/2Bq+lR2Xd5CYnpi5Tmeho7FX48wCE172XuYLNBcxX37F1S+/xLpqVfz/+L3Ai32kZxjpvWQPe0LiKOdix+rXW1Da/jGpQHY2CH4fDClxYO0E3b+C6s+YO6pcnYtOZMqfx9l1IRYAfzd7pj1Tg9ZVCneS48edUopLw0dwY+tWbGrVovyKn9BYSjl4IYoTpRRLji3h8+DPAXiu0nO0KNOCj/d9nKW6npedl2lOSpnHqfiRxEmY27XUa8w9MJc/zv0BgJOVE2Pqj+GFyi+YdebsR5V++ycc2vkRW5xd2erhR/iNy1nWV3WpyhNlTUP6qrlWM/vQR2NyMufaPokhPh6fTz/BuWvXAt2+UorJfx7jpz0XcbC25PcRzanyuE3QGn8JVg2A8D2m202Gw1PTwbJ4JodKKdYcvsIHf50kOjENgC61vJjydHW8nW3NHN2jSx8VxYWnu2FMTMT9zXG4DR5s7pCEEDcZlZGP9n3E8pPLARhUaxCj641Go9FgMBoIjg4mJjkGdzt36nvUN+vvH0mc8iCJkzAXozKy6swqPg/+nIT0BACerfQsbzR4o+AngC0profDV41NBSGe+xpV+yVC4kPYeslU6vxwzOEsQwPcbd15wvcJ2pRtQxPvJthYFv01MnHLlhE1+0N05cpRcf1fBX6W/Ptdoby3+jgaDSzp25Anqz6mhQkMetNkuTu/MN0u0wB6LoVS5fK8mzklpuqZu/Esy3aFYjAq7Ky0jGlXmQEt/R/tYZRmdP2334mYPBmNlRX+f/6BdYXiOXRTiJJEb9Az+d/J/B36NwDjG43nteqvmTmq3EnilAdJnIQ5HI89zsxdMzkWewyAKqWr8G7Td6nnUa/IYjAYFXtD4ohOTMXD0YbG/i5oLYp3AYV7WtkHTqzOtSDEtdRr7Li8g63hW/nv8n8kZyRnrrPR2tDUpyltfdvSumxr3GxzLtFdkGfGVHo65zp0JCMyEq9p0yj90osPtJ3c/HfuKn2+24vBqJjYuSpDn3h0Jkl+YKfWw5/DIDUebErBc19DQCdzR5WnE1cSeG/1MfaHXQOgsocD07vXpFlFV+Axfa8WEqUU4UOGkrRjBza1a+P+xlgMsXFYurtj17ABGq304ueHMhhI3n+AjJgYOXbioSTpkxi7ZSy7I3ZjaWHJBy0+KPLy4vdLEqc8SOIkilJ8WjzzD85n5emVKBT2OntG1h3Jy1VfxtKi6MbjBx6LYNraE0TcrPIF4O1sw9Ru1elU07vI4ihQ5zbBj8+DRgtDt4NX3teGpRvS2Re5zzTx7qWtRCZFZllf2622qTfKtw2VS1VGo9EQFBbEh3s/zDIW29POkwmNJzzQWOzrv/1GxOR3sXR3p+KmICysCm5oWcjVJJ796j/iU/Q8X68Mn75Y55GeKPm+XAuDX/vBlWDT7RZj4MkpoC2+ZaqNRsVvwZf48O9TxCaZ5i57tq4PzSq6Mi/o7OP1Xi1k+ogIznfqjEpLy7Lc0ssLz0kTcerQwUyRPRoSNmwgatZsMiJvfybKsRMPIi41jhFBIzgeexxbS1vmtZlH8zLNzR3WPUnilAdJnERRMCoja86vYe6BuZlzEXXx78JbDd/C3a5oLwoPPBbB8B+DufuNfusn9cLX6j96P8gy0mBhc4g9B01HQKfZ93V3pRSnr502JVHhWzkeezzLeh97HyqWqsiOyzuy3fdBq/8og4ELXZ8mPTQUj7ffxnXgveezyK+EVD3PffUf52OSqFeuFCsGN8VGV8LOFmekw8YpsOfmRMLlmkGP78DJx7xx3UN8sp6PN5xi+Z6L5PZt/Ei/V4tAwoYNXB49JvuKmycOynw+TxKAXCRs2MDlMWPJ9uKTYyfu0+Ublxm6cShhCWGUti7NgvYLHpliV5I45UESJ1HYTsed5oM9H3Aw+iBgmm9ocpPJNPZuXOSxGIyKlnM2Zzl7fScN4OVsw7/jn3y0hgLt+NR0fYu9B4zaDzYPV7o9Ojma7Ze2szV8K7sjdpNmSMuz/YPMN5EQ+A+Xx47FwsmJSps3o3Wwf6iYbzEYFQOW7mPbmRi8nW1YPbIFHo7Fb36jInP8T1g9EtITwc4Vnv8GKrUzd1T3dPDiNV78ehd6Q85fyY/se7WQKYOBc+3aZ+ktuZu2VCk835+KxkKuI7uTMhqJfH8axuvXc26g0WDp6UmlTUEybE/k6XTcaYYHDScmJQYfex8WPbUIf2d/c4eVb/eTG9z3WKHAwEAcHBxo2bIlAF999RXffPMN1atX56uvvqJ06dIPFrUQj7gb6Tf46tBXrDi1AoMyYGtpy/A6w3mt2mvozDRkaG9IXK5JE4ACIuJT2RsSl3l9RbF3PRy23ZzLp8PMh06aADzsPOhRpQc9qvQgJSOFH47/wPxD83Ntr1BEJkcSHB2crxnOlVLEfvMNAKVf7VVgSRPA7PUn2XYmBhudBd/0aViykyaAGs+CVy34tS9EHoUfX4DWb0ObCVCMq1am6o25Jk3wiL5Xi0Dy/gN5Jk0AhuvXuTL2jSKK6DGiFBmRkSTt3IVDq5bmjkYUU/sj9zN682gS9YlULl2ZRe0X4WHnYe6wCs19J05vv/02c+bMAeDo0aO8+eabjBs3js2bNzNu3Dj+97//FXiQQhRnSin+DvmbT/Z/QkxKDABP+T3FO43eMfscQtGJuSdND9KuWPhnEmSkQLnmULtgiysA2FraUtaxbL7axiTH5Ktd0s6dpB4/jsbGBpfevR8mvCxW7g/n239DAPi0Z11qlpFJkwFwrQgDgyBwAhz4H2z/CC7ugheWgGPxrDKY3/fg5evJgCROt2TE5O89qCtfHksXqV56p4y4OPShofdsFz5sGDY1a2BXtx629Ux/Os/H94exyL9NFzfxzrZ3SDemU9+jPvPbzcfJ6vEezXXfiVNISAjVq1cH4LfffuPpp59m1qxZBAcH06VL8a6aIURBu3D9ArP2zGJPpGk+GT8nPyY2nkiLMi3MHJmJNp/FAa5cTynkSArIuSA4ucZUEKLrJ9mq6BWU/F6Hlt92sYtNvU2levYssB9v+0PjmPzHUQDGtKtM19py7UsWOhvoNg/8msPasRC6A75uZUqe/FuZO7ps8ttTOH3tCS5fS6V3Mz9cHpdJjR+CpXv+3oPe06Zh36Toh0sXZ0l79nKxb997NzQYSD18hNTDR2DZMgB0Pj6ZSZRtvbrYBATIBMQlzKozq5ixewZGZaStb1s+av2RWab4KGr3/Sq3srIiOdlU0jcoKIg+ffoA4OLiQkJCQsFGJ0QxlaxP5usjX/P9ie/JMGZgrbVmcK3B9K/ZHytt8fgxs+VUNJP/PJqvtnMCT3Mo/DrvdatBmVLFdELOjDRY/47p/02GgWeNQttVfY/6eNp5Ep0cjcpWVsPEAgvsdHb33FbK4cMk79kDlpa49u9XIPFdupbMsB8PoDcoOtf0Yky7ygWy3cdS7RfBu66pdH3MSfj+GWg7CVq+CcXompfG/i54O9sQGZ+ayysOtBpISM1gbtAZFm47R88Gvgxs6U95t4Ib+vmosWvYAEsvLzKiorIXOIDM63TsGjYo+uCKufweu3LLlpJ65AgpBw+SfPAQaadPo79yBf2VKyT89ZepqZ0dtrVrY1uvLnb16mFbpw5aZ+kBfxwppVh8ZDFfHvoSgBcqv8C7Td8t0krB5nTfxSGeeeYZ0tPTadGiBTNmzCAkJIQyZcqwYcMGRo4cyZkzZwor1gIhxSHEw1BKseniJubsm5NZzrpN2TaMbzw+38O7CluGwchnG8+wYOt5AHxdbAmPS0EDWX6Q3eqraVfNgy2nYzAYFbY6LaPaVWJQywpYWRafH5UAbP8ENs8AB08YuR9sCvf9GxQWxLit4wByTZ7sdfZ80faLPAt/hL8+khubNuH87LP4fHh/1f9ykpSWQY9FuzgZkUB1bydWDW+GnVXJ+MJ6KOnJsP4tOGSaxZ6K7UyFI+yLz7C3WxUwIef36pe96mFQsHj7eY5dNp2o1GigY3UvBreuQAO/knmNcWZlOMiaAEhluHt6kGNnuJFE6tEjJB88SErwQVIOHcJ440a2bVtVqmhKom4O8bPyL19ypkh4TBmMBj7c+yE/n/4ZgCG1hzCy7shH/nkt1Kp6Fy9eZMSIEYSHhzN69GgGDhwIwBtvvIHBYOCLL7548MiLgCRO4kFdTLjIrL2z+O/yfwCUcSjDhMYTaOPbxryB3SEqIZVRKw6yN8RUAr13Uz8md63G1tPRec7jdDoykSmrj2Xer6K7PTO616R5pZwnhS1y18Phy0ama5ue/6ZQrm3KSU7zOHnZeTGq/ih+P/s7B6IOoLPQMaf1HJ7yeyrb/dPOnuVCt2dAo6HCurVYV3y4CWmNRsWI5cEEHo/EzcGK1SNbFt8ewuLq4I/w11um15KjD/T8H5Rrau6oMuVnzjWlFLsuxPLN9gtsOX37Gp+GfqUZ3LoC7at5lrjKezIX0YN72GOnjEbSzp0j5eAhUg4eJOXgQdLDwrK105YqlTm8z65eXWxq1sTCVj6/HhXphnQm/TuJf0L/QYOG8Y3H82q1V80dVoGQcuR5kMRJ3K/UjFSWHFvCd0e/I92Yjs5CR/+a/RlUaxC2lsXnQ//fs1cZ8/NBYpPSsbfS8uELtelW5/YcNgajYm9IHNGJqXg42tDY3yXLjyulFH8cvMys9Se5esM0IWe3Oj6827Uank5mHrf8y2twci34tYB+fxXatU05MRgNBEcHE5Mcg7udO/U96qO10JJmSGP89vFsurgJDRrebfouLwZkTeiujB9P/Oo1OD7VnrLzc6/Sl1+fbTzDF5vOYqW1YMWQJjTwk4vdH0jUcVjZF2LPmq6Xa/8+NB9VpK+rvNzrvXqnM1GJfLvjAn8evEK6wQiAv5s9A1v606NB2RI1n5cyGExV9mJisHR3x65hAymjnU8Ffewy4uJIOWRKpJKDD5J69CgqPT1rI0tLbKpVuz28r149dF7mLagkcnYj/QZjt4xlT+QeLC0smd1yNp38O5k7rAJT6InT+fPn+d///sf58+f5/PPP8fDwIDAwEF9fX2rUKLzrDgqCJE7ifmy/tJ1Ze2Zx+cZlAJr7NGdSk0n4OfmZObLbDEbF/M1n+XzTWZSCql6OLHi1PhXcHR5oe/Epej7bcJofdodhVGBvpeWNp6rQt3l5dFozDN87GwTLXzD9wB32L3hWL/oYcmEwGpi5ZyarzqwCYESdEQyrMwyNRoP+8mXOdegIBgPlf12Jba1aD7WvdUeuMPIn09xgH/eoTc+Gvg8df4mWlmgqGnHM9NxRpTM8uwDsHs1kNDohlaU7Q/lxdxgJqRkAuNhb0aeZH72b+uHqYG3mCEVJptLTST150jS87+AhUoKDc6yIaOntjV29utjWq49tvXrYBFRBozPPdB7C5GrKVUYEjeBk3EnsLO2Y13YezXyamTusAlWoidO2bdvo3LkzLVq0YPv27Zw8eZIKFSrw0UcfsXfvXlatWvVQwRe24pQ43c9ZRVG0Lt+4zJy9c9gSvgUwzfMzvtF4nvJ7qliN5Y1JTOONXw7x77mrALzU0Jdp3WsUyFnmY5fjeffPYxwKvw6YErLp3WvS2L8If1hmpMGCphB3AZqNhI4fFN2+80kpxVeHvuLrI18D8FLAS0xsPJGYD2Zzbfly7Jo1xe8hp2k4eimenl/vJFVvZHArfyZ3LT7J4yNNKVO58r/HgyEdnMtBz6VQ9tEtJJCUlsHK/eEs+TeES9dM1TKtLS3o0aAsg1pVwL8EF5IQxYdSiowrV0i+Y3hf6qlTYDRmaaextcW2Vq3M6n12deuiLVXKPEGXQOGJ4QzdOJTwxHBcbFxY0H4BNVyLdwfJgyjUxKlZs2b07NmTcePG4ejoyOHDh6lQoQL79u3j2Wef5fLlyw8VfGErLolTfsaxi6KXbkhn6fGlfHPkG1INqVhqLOldvTfD6gzLVwW1orTnQiyjVhwkOjENW52Wmc/W5IUGBVugwmhUrNwfzpzAU1xL1gPwfP0yTOxcDXfHIjiDvf1j2DyzyApCPIwVp1Ywe89sFIpupVvTZ8p/qLQ0yv3vO+ybPfjZueiEVJ758j8iE1JpE+DOkr6N5ARLQbtyyDRh7rVQsNCZJlZuMrTYDN17EBkGI4HHI1m8/QJHLsUDpofTobonQ1pXkGGeotgxJiWRcvTozep9B0k5dBhjDtWarSpUwLZ+vczhfVbly6MpRhUyHxen4k4xbOMwYlNjKeNQhq+f+rpYjbYpSIWaODk4OHD06FH8/f2zJE6hoaFUrVqV1NTiPZFmcUicblVOuvvA3/qKXvhafUmezGDnlZ3M3jOb0IRQABp6NmRyk8lUKl3JvIHdxWhULNp+nk/+OY1RQSUPBxa8Wp8qno6Fts9rSel89M8pft4XjlLgaGPJ2x0DeLWJX+H9iL9+Eb5sfLMgxLdQu2fh7KcA/RP6DxN3TOSFLak8v1Ohq1GNiqt+e+BeylS9gZcX7+ZQ+HUqeTjw+4jmONnIsJVCkRoPq0ea5gkDqPYMdP8SbB7tkspKKfaExPHN9gtsOhWdubx+uVIMaV2Bp6p7SSIuiiVlNJJ+4cLt4X0HD5IeEpKtndbZGdu6dW/PK1WrJhZ2xetE56Nmb8ReRm8ZTZI+iYDSASxsvzDf8xY+igo1cSpbtiwrV66kefPmWRKnP/74g7feeovz588/VPCFzdyJk8GoaDlnc5aepjtpAC9nG/4d/6R8mRWRyKRIPt73MRvCNgDgauPKW43eoqt/12I1LA9MCcy4lYcyK2k9X68MM56tib110ZSjPnjxGlNWH8sshVyzjBMzutekXrlCKIP886twah34tYR+6x6Zs/97zm3F8oXh2KXBij6+jH7jJ9xs7786oVKKcSsP88fByzjb6lj9eosSPV9PkVAK9nwNG94Fox5K+8OLy8C7jrkjKxDnohP5dkcIvwdfziwkUd7VjoGtKtCjfllsraSQgijeMq5dy1K9L+XoUVRaWtZGWi02VauaqvfVv1l0wltORufXhtANTNgxAb1RT0PPhnzx5Bc4WhXeidnioFATp3feeYddu3bx66+/UqVKFYKDg4mKiqJPnz706dOHqVOnPlTwhc3cidOu87G88s3ue7ZbMbgpzSoWn/lFHkd6o57lJ5az4PACUjJSsNBY8ErVV3i97uvF8kPiQNg1Rv0UzJX4VKwtLZj2TA1eauRb5Mmdwaj4aU8YH/1zmsTUDDQaeLmRL+90rEpp+wKa/PfsRljew1QQYvh/4FGtYLZbBK5+8w0xn35GhJuWsYOgjKMvXz/1NeWcyt3XdhZtO8+Hf59Ca6HhhwGNi09p+JLg0gH4tR/EXwStNXT+EBr0f2SS93uJTkzl+51h/LA7jPgU0xDc0nY6ejcrT59mfrhJIQnxiFDp6aSePn17eF/wQdOEvnex9PLKUr3PpmpVKTqRg5WnVzJz90wUivbl2vNh6w+x1j7+nweFmjjp9Xr69evHzz//jFIKS0tLDAYDvXr1YunSpWiLeelPcydOqw9dZszPh+7Z7vOX69K9bpnCD6iE2he5j1l7ZnHu+jkA6rjX4d2m71LVpaqZI8tOKcWSf0P48O9TZBgV/m72fNWrPtV9zHu9z9Ubacxef4rfgi8Bph9e4ztV5cWGvlg8TG+pPtVUEOJaSLEtCJEbY1oa59q1x3D1KlbvvclI69+4dOMSLjYuLGy/kOqu+SvqEHQiisE/7EcpmNG9Br2blS/cwEV2yXHw53A4E2i6XasnPD0PrB+sWmVxlJyewa/7L/HtvxcIjzMVkrCytOCF+mUZ1Mqfig9YmVMIc9JfuZJleF/qqVNgMGRpo7GxwbZmTWzr18e2Xl1s69bFsnTJnEAaTL8zFh5eyMLDCwHoWaUnk5tMRmtRvH/TF5Qimcfp/PnzHDx4EKPRSL169ahcufIDBVvUzJ045bfH6fOX6tK9niROBe1qylU+3f8p6y6sA6C0dWneaPAG3St1x0JT/C4ujU/W8/aqw2w4YTqD1rW2Nx8+XwvHYnSdy96QON5bfYxTkYkA1CtXihnda1KzzANeG7LtY9gyExy8YNR+sC5+vX+5ufbzz0S+Pw1Lb28q/RNIrCGB4UHDORV3CjtLOz5/8nOaeuc92erpyESeX/AfSekGXm1Sjg+ee7gy5uIhGI2waz4ETQNlALcq0HNZsSqJXxAMRsU/xyP5evsFDt+soqnRQPtqpkISDf1KF7thy0LklzE5mZSjxzKH9yUfOoQxPj5bOyt//9vV++rVw6pChRJRdMJgNDBrzyxWnlkJwPA6wxleZ3iJes/LBLh5MHfidOsap8j41GzFIe5kpdXwetvKDH2iQomawLCwZBgz+OX0L3x58Etu6G+gQUPPKj0ZXX80ztbF8+LvI5eu8/pPwYTHpWCltWDK09V4ralfsfww0xuMLNsZytyNZ0hKN2Chgd5N/RjXIQBn2/tI8q6FwVdNTAUhXlgCtXoUXtAFTGVkcL5TZ/SXLuE5aRIufXoDpokDx2wZw97IvegsdMxqNYtO5XOeODAuKZ3uX/1LeFwKTSu48MPAJuaZO0tkFbYLVg2AxCtgaQtdP4V6r5o7qgKnlGJf6DUWb79A0Mnbw53q+poKSXSsIYUkxKNPGY2kh4aSEhyc2TOVfuFCtnYWTk7Y1q1zc3hffVPRCfvH6zrTNEMaE7ZPIOhiEBo0TG4ymZeqvmTusIpcgSdO48aNY8aMGdjb2zNu3Lg823722Wf3F20RM3fiBLer6gFZkifNzdsBng6cjroBgJ+rHdOeqUGbAI8ij/NxcTjmMDN3z+RU3CkAarjW4N2m71LTraaZI8uZUoofdocxc91J0g1Gypa2ZcGr9aldtpS5Q7unqIRUZv51krWHrwDg5mDFxM7VeL5+mfwlfLcKQpRvBX3XPlLXlMSvXceVt99GW6oUlTZvylLVKc2QxsQdE9kYthENGiY2mcgrVV/Jcv/0DCO9l+xhT0gc5VzsWP16i4K7Zkw8vKSr8PtgOL/ZdLvua9DlY7B6PKt3nYu+wZJ/L/Bb8GXSM0yFJMq52DGolT89GpTFzqpoCtIIURQyrl0j5fDh24UnjhxB3V0lWqvFJiAgs3qfXb26WPr4FMuTmfmRmJ7ImC1j2Be5D52Fjg9bfUiH8h3MHZZZFHji1LZtW/744w9KlSpF27Ztc9+YRsPmzZvvP+IiVBwSJ8h7HqeONbxYeySCmetOEJ1oqhbTqYYXU7pVp0wpW3OF/Mi5lnqNecHz+P3s7wA4WTkxpv4YXqj8QrEdt5uYqmfC70f560gEAE9V9+STHnVwtis+Q/Py479zV3lv9THOxyQB0Li8CzOerUmAVx7D7s5sgJ96goUlDPv3kSoIoZQipPuzpJ05g9voUbiPGJGtjcFoYPbe2fxy+hcAhtQewsi6I9FoNCilmPznMX7acxEHa0t+H9G8UMvLiwdkNMKOT2HrLFBG8KgOL34Pbo/GUPUHEZOYxg+7Qvl+dxjXb87lVspOR++mfvRpVr5o5nMToogpvZ7U02duD+87eJCMiIhs7Sw9PG4P76tf31R0wqr4n/CKSY5heNBwTl87jb3Oni/afkFj78bmDstsZKheHopL4gSmYXt7Q+KITkzFw9GGxv4uWYZBJKbqmRd0lqU7QzEYFbY6LaPaVWJQywpYWcrwndwYlZHfzv7G58GfE59mGsf8bKVneaPBG7jYFN9JH09cSeD1n4IJuZqEpYWGCZ2rMrCl/yN7Nis9w8i3/15g/qZzpOgNaC009G9enrFPVcHh7vLpdxaEaD7KNAHpIyRxyxYuDR+BhZ0dlbZsRuuc8/BPpRSLjixiwaEFALxQ+QXebfouP+25xHurj6PRwJK+DXmyqmdRhi/uV8h2WDUQkqJBZw/dPn8k5hl7GMnpGaw6cIlvd4RwMS4ZuFVIogwDW1agkocUkhCPN31EBCmHDmUO70s9eRIyMrK00VhbY1OrZmb1Ptu6dbF0KV6/Oy4mXGTIxiFcvnEZVxtXFrZfSDXXR+dEZWEo1MQpPj4eg8GAy10vhLi4OCwtLc2ejNxLcUqclMFA8v4DZMTEYOnujl3DBmhyqEp4KjKBKX8eY1/oNQAqutszo3vNElue2GA0EBwdTExyDO527tT3qJ/Zg3Q89jgf7P6Ao1ePAlCldBXebfou9TzqmTPkPCml+GVfOFPXHCctw4i3sw1f9qpPA7/Ho8LP5espTF97nH+Om66Z8HSy5t2u1Xm6tvftpHDbR7DlA3D0hpH7HqmCEAChvV4lJTgYlwED8Hzn7Xu2X3l6JR/s+QCjMlLHpSW7dnfCYLBkYueqDH2iYhFELB5aYhT8NhBCd5huNxwAHWeDzsa8cRUyg1Gx4WYhiUM3C0kAtK/mwZDWFWlUXgpJiJLBmJJC6rFjJAcfzOyZMuRUdMLP7/bwvvr1sKpY0WxFJ07EnmB40HDiUuPwdfTl6/Zf4+vka5ZYipNCTZw6d+5Mt27dGHHXUJRFixaxZs0a1q9ff/8RF6HikjglbNhA1KzZZERGZi6z9PLCc9JEnDpkH2OqlOL34MvM/vskV2+kA9Ctjg/vdq2Gp9Pj/UV9p6CwID7c+yFRybcvXPa082R0vdEcuXqEladXolDY6+wZWXckL1d9GUuL4jsWPzk9g3f/OMbvBy8D0CbAnc9erIvLY3hty5bT0by/5jhhsaaz1S0ruTGtew0qWsbCV40hI/WRKwgBkLx/P2Gv9Uaj01ExKAidZ/6uRwwKC+Lt7e+QYdSTkeRPe5fxfPFSc/nR+SgxGmDrh7D9Y0CBV23ThLkuFcwdWaFTSrE/7HYhiVu/JOr4lmJIqwp0rOGJpRQ2ESWIUor0kFBTEnXINLwv/dz5bO0sHB2xrVs3s3qfTa3aaB0Kv+jE7ojdjNk8huSMZKq5VGNB+wUPNDn746hQEycXFxf+++8/qlXL2q136tQpWrRoQWxs7P1HXISKQ+KUsGEDl8eMhbsP/c0fTGU+n5dj8gQQn6Ln0w2n+XF3GEYFDtaWjG1fmX7Nyz/2X1JBYUGM2zoOlWc9Quji34W3Gr6Fu517EUX2YM5GJTJ8eTDnom9goYG3OgYwrHXFh5sDqZhL1Rv4etsFvtp6jvQMIzqthvUeC6l8bfsjWRAC4OKQISRt30GpF1/Ee/q0fN8vIVVP18VLuebwNRptGpVKVebrpxbhYSeFYB4554Lg9yGQHAvWTtD9S6je3dxRFZnzMTdY8m8Iqw5cyiwk4etiy8AW/rzYyFcKSYgSyxAfT8rhw5mT86YcOYJKScnayMIC64AA7OrVzeyZ0pXJZ0GlfAoMDWTSjknojXqaeDVhXtt5OFjJ8NpbCjVxsre3Z/fu3dSqlXVukaNHj9KkSROSk5PvP+IiZO7ESRkMnGvXPktPUxYaDZaenlTaFJTjsL1bjl2OZ/KfxzLn3Kjq5ciMZ2vSqHzxGktbUAxGAx1/65ilp+luWo2WRe0X0dQn73lyioPfgy8x+Y9jpOgNeDha88Ur9WhawdXcYRWZi7HJvL/2OOrMP/zP6mMy0LK74xpaNG3xSPW4pJ48Schzz4OFBRX/Xo+Vn1++7mcwKgYs3ce2MzF4uMZi6/sdcWmxlHEow6L2iyjvXL5wAxcFL/6yqWR5+M15+poMh6emg+Xj13ucm6s30vh+Vxg/7Arl2s1CEs62NwtJNPfDw7HkjI4QIicqI4PU06dvV+87eBD9lSvZ2lm6u2ep3mddvToWD1h0YsWpFczeMxuF4im/p/iw1YdYaUvO51J+FGri1KZNG2rVqsX8+fOzLH/99dc5cuQIO3bsuP+Ii5C5E6ekPXu52LfvPduVW7YM+yZ5VzgxGhW/7A9nTuCpzGpHL9Qvy8QuVXFzeLwqHe2L3MeAfwbcs913Hb+jkVejIojowaTqDUxdfZxf9ocDpuFqc1+qWyIrUyl9CinzGmGXFM6ijKf5MKMXbQPcmfZMTcq5Pholni+PG0fC+r9x6tKZMvcxFcMHf53gmx0h2OgsWDWsOc5OCQzbOIyLiRdxsXFhQbsF1HCrUYiRi0Jh0MPmGfDf56bbZRpAz6VQqpxZwypqKekGVgVfYsmOC4TeHJprpbXguXplGNzan0oej9Y1jEIUJn1UVGYilXzoIKknToJen6WNxsoKm5o1M4f32darh6Vr3idblVJ8eehLFh9ZDMBLAS8xsfHEYltV2JwKNXH677//aN++PY0aNaJdu3YAbNq0iX379rFhwwZatWr14JEXAXMnTvHr/uLKW2/ds53PJ5/g/HTXfG0zLimdjwJP8fM+049xJxtL3u4YQK8mfo/NZIXrL6xn/I7x92w3p9UculToUgQR3b8LMTcYsTyYU5GJaDQwpl1lRj1Z+bF5ju7b1jmwdRbKwZvPqy/nq/+i0BsUVpYWjGhTkWFPVCzWkz+nh4VxvnMXMBrx/+N3bKrlryrRr/vDeXvVEQC+6lWfrrW9AYhNiWXEphGciD2BnaUdc9vOpblP80KLXxSi04Hwx1BIvQ42peC5RRDQ2dxRFTmDUbHxRBSLt58n+OL1zOXtqnowuHUFmvi7PFI9zEIUBWNqqqnoxM3qfSkHD2K4di1bO51fOezq1svsmbKuVDFzpFKGMYOZu2fy29nfAHi97usMrT1U3m+5KPRy5IcOHeLjjz/m0KFD2NraUrt2bSZOnEjlysV/LgtzJ04F2eN0t+CL15jy5zGOX0kAoFYZZ2Y8W5O6vqUeJNRi5VHvcVp7+AoTfjtCUroBV3srPn+5Hi0rl+CLMq+FwldNTAUhenwHNV/gXPQNpq45xn/nTNdJ+rna8f4zNWhbTCd/jnhvKtdXrsS+dSvKLV6cr/vsD42j1zd7SDcYGd2uMuOeqpJlfZI+iTFbxrAnYg+WFpbMajmLzv4l7wf3Y+H6Rfi1H1w+YLrdfDS0ew+0j9acbAXlQFgci7dfYMOJ24Ukapd1ZnCrCnSu6fXYX6MrxINSSqEPCyM5c3hfMGlnz2VrZ+HggG2dOljVrcUPFvv4VXeINBst7zZ9l55VHu/pEh6WzOOUB3MnTpnXOEVFZS8OAfm+xik3BqPix91hfLLhNImpGWg08HKjcrzTMYDSj2ilNr1Bzyf7P+GnUz/l2kaDBk87TwJfCCxW3dBpGQZmrjvJD7vDAGjs78L8V+qVqEqIOVrxCpxeD/6toc+azIIQSinWHYlg5l8niEowTf7csYYn73WrUawmf9ZHRXO+fXuUXo/fjz9g17DhPe9z+XoK3b/8l6s30ulc04uvetXPsRBIuiGdyf9OJjA0EIAJjSfwarVXC/wxiCKQkQ4b34M9C023fZuaThQ4lzFvXGYUcjWJJf9e4Nf9l0i7WUiibGlbBrb058WGvtjfPcebECIbQ0ICKYcPZ07Om3L4COquGgNGDWT4l8GjSavM4X26smWl1ykHhZ44GY1Gzp07R3R0NEajMcu61q1b3+/mipS5Eye4o6oe5FhZL6+qevkVk5jG7PUnM8tcl7bTMb5TVV5s6PtIVW2LuBHBW9ve4sjVI5nLNGiyVNbTYHo8n7X5jPZ+7Ys8xtxcjE3m9Z+COXrZNK/DiDYVGfdUFTmzejoQVrwEFpYwfCe4B2RrciMtg8+DzvDdf8Vz8ueojz4m7rvvsK1fn/I/Lb9n+6S0DHos2sXJiASqezuxanizPCuNGZWRD/d+yIpTKwAYXGswo+qNki+8R9WJ1bB6JKQlgJ0rPL8YKhWfzypziL2Rxg+7w/h+VxhxSaYpNpxsLHmtqR/9mpfHo6SfXBLiPqiMDCKO7uGHXyZT+mw0VS9rcL9uzNZO6+Zmqt53c4ifTc0aD1x04nFSqInT7t276dWrF2FhYdx9V41Gg8FguK9gFyxYwMcff0xERAQ1atRg3rx5eV4nlZaWxvTp0/nxxx+JjIykbNmyTJ48mQED7j2MC4pH4gQ5z+ME4Dp4MB5vjiuw/ey5EMt7q49zOioRgHrlSjHz2ZrU8HEusH0Ulu2XtjPp30nEp8XjaOXIzBYzM39Q3lldz8vOi/GNxxerpOmf45G89ethElMzKGWnY+6LdWlbtXgOOStS+hTTEL3rYdBijKnqWB5ORyYy5c9j7A2NA4rH5M+G+HjOtX0SY3IyZRcuwLFt2zzbG42KEcuDCTweiZuDFatHtsxX75lSim+OfsP8g6ZCPM9Xfp4pTacU63nJRB7iLsDKvhB5BNBA67egzUQoRj3k5pCqN/Bb8CW+3RFCyNUkwFRIontdHwa3rkAVTykkIcS9hMaHMixoGJdvXMbN1o1F7RdRQV+alEO3q/elnDiRveiETnez6EQ9U+GJunWxdC/eU7kUhkJNnOrWrUuVKlWYNm0a3t7e2c6AOjvn/wf5L7/8Qu/evVmwYAEtWrTg66+/5ttvv+XEiROUK5dzFaLu3bsTFRXFzJkzqVSpEtHR0WRkZNC8ef4uoi4uiROYhu0l7z9ARkwMNzZvJmH9enRlylDhr3VY2BTc2Ta9wciynaHM3XiGpHQDFhro06w84zpUwcmm+I23zzBmMP/gfL479h0ANVxr8MkTn1DWsSxgKk0eHB1MTHIM7nbu1PeoX2yG56VnGJkTeIol/4YAUL9cKeb3ql+shpmZ1dYPYetscPSBkfvA+t7zSCil+OPgZWatLx6TP8csWMDVL+ZjXaUK/qv/vGcv0Gcbz/DFprNYaS1YMaQJDfzub8qAVWdWMWP3DIzKSBvfNnzc+mNsLOVs/CNJnwr/TIT9ps82yrcyTfrs6GneuIoBo1ERdDKKxdsvsD/s9oXwbQPcGdy6As0quEqPqxA5OHb1GCOCRnAt7RrlHMvx9VNfZ/5eupMxLY3U48dvD+8LPoghLi5bO52vb5bqfdaVKz/QpSOPkkKfx+nw4cNUqlTpoYIEaNKkCfXr12fhwoWZy6pVq8azzz7L7Nmzs7UPDAzk5Zdf5sKFC7i4PNh8RcUpcbqTMSmJ8126khEVhdvrr+M+amSB7yMyPpWZf51g3ZEIANwcrJnctSrP1i3YidYeRlRSFO9sf4fg6GAAelXtxZsN33wk5hy4fD2FkT8Fc/Bm9ajBrfx5p1NVdCV9aN4tcSGwoOnNghD/g5rP39fd41P0fLbhND/cnPzZ3krLG09VoW/z8kV2jI3JyZx7sh2G69fx+fhjnLs9nWf7dUeuMPKngwB83KM2PRv6PtB+N13cxDvb3iHdmE59j/p88eQXOFsX/15jkYujq2DNaNAngb0H9Fhiut5PAHAg7Brf7rhA4PHIzNHsNcs4MbhVBbrW8pbhzkLctPPKTsZuGUtKRgrVXauzoN0CXG3zNyekUgp9eDjJwcGZ1fvSzp7NdgmJhb09tnXqZFbvs61TG63j49UTXKiJ05NPPsk777xDp06dHirI9PR07Ozs+PXXX3nuuecyl48ZM4ZDhw6xbdu2bPcZMWIEZ86coWHDhvzwww/Y29vzzDPPMGPGDGxtcz6jn5aWRlpaWubthIQEfH19i13iBJAQGMjlsW+gsbKiwrq1WOXS6/aw/j17lffWHONCjGlYRBN/F2Y8W9PsQyJ2Xt7JxH8nEpcah73OnmnNp9GxfEezxpRfW05F88bKQ1xP1uNoY8knPev8n727Do/i6gI4/NvduJMQw4O7u7s7FCgUaHEoUkoprsWtFC/WYkVKcXenuDsJEiDuxHd3vj+G0o9iCezubJL79snTSTI79xCW7J65955DgyJeSof1hv+f4bRwd8eubBnT3kX6owPc3ws+NaDL9tcFIVLr5vMoRm+7ydX/a/48sUVRyvsYp/nz///c4q9cJmLdH1hmz06evXtQWbx/2dzN51G0XXKGhGQ9Pav5MKpJ4c+K42LgRQYeGUhMcgx5XfKypO4SPO3FTEWaFXIf/uwKwbdBpYaaI6HaEFCrQa+DJ2fgZRA4eELOyhlySd/j0FhWnHrEn5f8SUiW92tkdbGlW1Uf2pfLjsN/Ckno9BLnH4UTHJOAh6MN5X1cM267ByHd2+O3h1GnR6HVa6noXZG5teZib2n/WdfUxcQQf+36v8v7rl1DHxv75kkqFdb58v27vK9UKSxz5EjVDXjF34/8h1ETp61btzJ69GiGDh1KsWLFsLR8c6lX8eLFU3SdFy9ekDVrVk6fPv3GMrspU6awatUq7t2799ZjGjZsyLFjx6hbty5jx44lNDSUfv36Ubt2bVauXPnOccaPH8+ECRPe+ro5Jk6SJOHfvTuxZ85iX6M62ZcsMdpMUKJWx/KTj5h/5AEJyXos1Cq+qZKLQXXzv/ViZGw6vY4l15fw67VfkZAokKkAs2vOJqdTTpPG8Sm0Oj2zD95n8TFfQC4Bv7BjabNr4PquPXUWXl54jhzx2YVIUuTeXljfAdSWrwpC5P/4Yz5Ar5fY9Kr5c8Sr5s+tS2dlRKNCBm0m/L69iC7t2uE98e3fK/8Ijk6gxcLTBEQlULOAOyu6ljPIG7h74ffoe6gvIfEheNt7s6TeEnI75/7s6woKSYqDPUPh6lr58zx1oGgbODoJol/8e55TFmg4HQo3VyZOhYXHJrH27yesOvOYsP8rJNHpVSEJTycb9t0MYMLO2wREJbx+nLezDeOaFaZhUW+lQhcEo1h7ey3TL0wHoFGuRkyuOhlLI7Q6kHQ6Eh88+Hd535WrJPv7v3Wexs3tjeV9NkWKoLZ+92ux4u9H3hWTMRMntfrtKXKVSoUkSakqDvFP4nTmzBkqVar0+uuTJ09mzZo13L17963H1K9fn5MnTxIYGPh6L9WWLVto27YtsbGx75x1SkszTgCJfn74tWgJyclkW7QQx9q1jTres4g4Ju68zYHbcrEFLycbRjctRJNib+9fM4bQ+FCGnxjOucBzALTN35Zh5YaliT0cQdEJDPjjyuvCBV0r5WRkk0JYW5jXneHXVRzfUcERMEgVxw9KZUGI1IiITWLGfrn5sySB46vmz50M0Pz5vT83+GD1y4RkHR2W/s1V/0jyejiwpV9lg+4lfP7yOX0O9uFx9GNcrF1YVGcRxdyLGez6ggKurIPdQ0Ab/54TXj2X263OsMkTyP+2tlx+zvKTfvi9KiRhqVFRNqcrZ/3C3jr/n98Ai78qLZInIV2QJIl5V+ax/MZyQN7OMKz8MNQq0y1f1YaEEHf16uvlfQk3byL9p+gElpbYFi787/K+UiWx9PBQ/v3Iexg1cXry5MkHv58zZ8pmCT5lqV7Xrl05ffo0Dx/+2/jrzp07FC5cmPv376eoAa+57nH6f8GzZxO2bLlRCkW8z9G7wYzbcYun4XIfgGr5MjO+eRHyuH988/6nuhB4gR9P/EhofCi2FraMrTSWprk/vGfEXJx8EMJ3G64SFpuEg7UF09oUo2nxLEqH9ZbXfcP+M2Py2mf2DUuRo1Ph+LRUFYRIrStPIxiz/SY3n8vNn4tmdeKnFkUplSPTJ13vU39ukiQxZNM1tlx5jrOtJdu/rUKuzJ+3dOJdwhPC6XeoH7fCbmFrYcucmnOomrWqwccRTCjgBiyrCXrte05QyTNP393IkMv2/p9eL3H4bjDLTvi9vnH1PirAy9mGU8Nqi2V7Qpqm1WuZeHYiWx9uBWBQ6UF0L9pd8T3q+qQkuejE5SvEX71C3JWr6EJD3zrPIksWdOHhSAkJ77gKpnk/8h5ppgFuhQoVKFOmDIsWLXr9tcKFC9OiRYt3FodYunQp3333HcHBwTg4yG++tm/fTuvWrXn58uV79zn9v7SQOOljY/Ft0hRtYCCZ+/XDfeAAk4ybkKxj8TFfFh/3JUmrx1Kjolf13PSvlQ9bK8M9ifWSnhU3VrDg6gL0kp68LnmZXWM2uV3Mf8mRTi8x7/AD5h15gCTJ+2sWdSpNbiMmmJ8j9tx5nnbt+tHzLPPkRuNghD+DNhECbwISuOYBu09LZFJEgtCXibyISkCvl3+tuTlYkcXZFo0mdS8supcvSfb1++h5OVatwr5C+defLznuy7S9d9GoVazpVt6oZdPjkuMYfGwwZ16cwUJlwU9Vf0ozNx6Ed3h0Elal4O+v6y7weX/LjoxmzdnHjNl+66Pnre9ZkUp5UrZpXhDMTbw2nh+P/8ixZ8dQq9SMqzSO1vlSV2DJVCRJIvnZszeW9yXevw//6fv6Pv99XTWF1OQGn7SZZc2aNSxZsoRHjx5x9uxZcubMydy5c/Hx8aFFixYpvs73339P586dKVu2LJUqVWLp0qU8ffqUPn36ADBixAieP3/O6tWrAejYsSM//fQT33zzDRMmTCA0NJShQ4fSrVu3FCVNaYXa3h7P4cN5/t13hC1fjnOL5lilcCbvc9hYylXKWpfOyrgdtzh2L4SFR33ZduUF45oVpl5hz8++sxGREMGIUyM4/fw0AM3zNGdUhVHYWZrXnqB3CYlJ5LuNVzj9UF4S8mX57IxrVgQbS/O9+6sNCUnRecm+fiR//LRP9GqZWpg/8PbaaENyAN7YPRUByf4Y7c/2/z/fw3eCmL5PXmI8vllho/easrO0Y0HtBYw6PYq9j/Yy4uQIwuPD6VKki1HHFYzkZdDHz0nNeRmEk23KlsEGx7znLrcgmLmoxCgGHBnAleArWGusmVl9JrVyfLh/oJJUKhVW2bNjlT07zs3lpcW6ly8JW7qMsKVLP/r4lL5vUUqqE6fFixczduxYvvvuOyZPnvx6T5OLiwtz585NVeLUvn17wsLCmDhxIgEBARQtWpQ9e/a8Xu4XEBDA06dPX5/v4ODAwYMHGTBgAGXLlsXNzY127doxadKk1P4xzJ5jg/rYV65M7JkzBE6eTPZffzXZdGxON3t++7ocB24HMXHnbZ5HxtNrzSVqF/RgfLMin1z44ErwFYYeH0pQXBDWGmtGVRhFq3ytPv5AM/C3XxgD1l8hJCYRW0sNk1sVpXXpt/skmJuUNrLL/N132OT/vIINb3l+CU7MAJUFNJ4BTlkNe/2PuB8Uwx/nnvAsQt43ktvdnk4VcpLT7eNL5xLu3yd07tyPnvfPz/d+UAwD119BkqBThRx0rpTrc0JPMUuNJdOqTcPNxo21d9Yy8+JMQhNCGVx6sOLLN4RUckhhhcSUnpdBeDimbCl7Ss8TBHMSFBtEn0N9eBj5EEcrR+bXnk8ZzzJKh5VqGgcH7KtUSVHiZO4NeFO9VK9w4cJMmTKFli1b4ujoyLVr18idOzc3b96kZs2ahL5jXaM5SQtL9f6R6PcIvxYt5EIRCxfgWKeOyWOIS9Iy/8hDlp/0I1knYW2hpl/NvPSukTvFMy2SJLHq1irmXp6LTtKRyykXs2rMooBrASNH//n0eonFx32ZfeAeegnyeTiwqFNp8qWRbvaK7XFKjoeF5SHyKVT5Duq9vwKdMb2r+XPnijn5vn4BnD9wp/r1zy0o6L3FIf75uUUk6Gi58DRPw+OomNuVNd0rmLx3lyRJrLi5gl8u/wLIM7njK4/HUm1+Da6F99DrYG5RiA4A3vWyLPY4vYtOL1F1+hECoxLe+VMDubqe2OMkpDV+UX70OdiHgNgAPGw9WFxvMfkzGfgGpwml5nXVnPc4pfrV/dGjR5QqVeqtr1tbWxP731rvwmexzu2D29dfAxA0eQr6+PdVXDIeOysLhjUsyN5B1amcx41ErZ6fD92nwdwTHLsX/NHHRyVGMfDoQGZfmo1O0tEoVyM2NN2QJpKm8Ngkvvn9AjP3y0lT61JZ2d6/SppJmgBUGg2ZOnV8zzflNxGeI0cY/pfUqZ/lpMkpK1Qfathrp4KlRk2Park58kNNmpXIgl6CVWefUGf2Mf669Iz33TdSaTR4jhzx6pP/vNn6v5+bFhX91l3iaXgcOVztWNypjCINj1UqFT2K9WBi5YloVBp2+O543RRRSCPUGrnkOPBvPbj/aDhNJE3/oVGrGNdM7pH2vrRobNPCImkS0pTrIdfpurcrAbEB5HLKxZrGa9J00gQpf11Vsp9TSqT6Fd7Hx4erV6++9fW9e/dSuPDnNXgU3pa5bx8svL1JfvGCsGXLFIsjr4cD63pUYN6XpfBwtOZJWBxf/3aBPmsu8Tzy3W/ObobepP2u9hzzP4al2pIxFccwvfr0z27QZgqXnoTTZN5Jjt8PwdpCzfQ2xZjdrgR2VqbtcfW59ElJRG3fDoDqP9UZLTw9jVP6M9wPTs2VjxtMMUoVvdTydLJh/pelWNejAnnc7Ql9mcSQP6/R/te/uRcY887HONWvT9Zf5mLh+ebSqH9+bo716jFuxy3+9gvHwdqC5V3LksneyhR/nPdqla8Vc2vNxVpjzYlnJ+h1oBdRiVGKxiSkQuHmcslxp3eUzi7fK0OXIv+QhkW9WfxVabyc370c72Xi+yoVCoL5OfX8FD0O9CAyMZJimYuxutFqsjiYX9XeT/Gx11Wl+jilRqqX6v3222+MGTOG2bNn0717d5YvX46vry9Tp05l+fLldOjQwVixGkRaWqr3j+j9B3g+aBAqS0ty79ppkkIRHxKTkMzcQw/4/cxjdHoJW0sNA+rkpUfV3FhZqJEkiT/u/sGsi7PQ6rVkc8jG7JqzKexm/om1JEksP/mI6fvuotVL+GS2Z1Gn0hTyThvPlf8KnjuXsCW/onFzw2f7NpJ8/YzbqVuS4I928OAA5K4Fnbe+fWdJYUlaPctP+TH/8EPik3Vo1Cq6faD58/s6nK8++5ix22+hUsHyLmWpU8h89p5cCb7Ct4e/JSYphjzOeVhSbwle9l5KhyWklF4HT87IhSAenYDLqyCTj1zO3whNLtMLnV7i/KNwgmMS8HC04Yp/BDP23cPJxoKD39fA00nscxLM2y6/XYw5NQatpKVKlirMqTknTRTPSq33va4qxejlyJctW8akSZPwf9U9OGvWrIwfP57u3bt/WsQmlBYTJ0mS8O/Rk9jTp7GvXs2khSI+5G5gNGO23eTC4wgA8rjbM7JpLnYHzOPgk4MA1MlRh4lVJuJkZf4/66i4ZH7YfI2Dr5oBNy3uzdTWxXA0YPNSU4q/dYvH7dqDTkfWeb+Y5k7O3T2w4UtQW0K/s5D5473VlPI8Mp6JO2+x/5b89+3pZM2YpoVT1Pz59MNQuqw8j04vMbxRQfrUyGOKkFPlYcRDeh/qTXBcMF72Xvxa99c0UfJf+I/El/BLCYgLheYLoHRnpSNKM7Q6PW0Wn+HasyjqFPRgedeyZvHaKQjvsvrWamZenAlAk9xN+KnyT1iKGyUmYbI+TqGhoej1ejw8PD71EiaXFhMngMRHj/Br/qpQxIL5ONatq3RIgJzUbbn8nKl77xCe/BjbbOtQW4WhUWn4oewPdCrUKU28UF1/Fkm/dZd5FhGPlUbNmKaF+KpizjQR+7tISUk8avsFiffv49ioIdl+/tn4gybFwcIKEPUUqg6GuuONP6YBHL0XzPgdt3gSJjd/rpo3MxNa/Nv8+b93sd0drWmz+AxR8cm0LpWV2e1KmO3zJOBlAL0O9uJx9GOcrZ1ZWGchJdxLKB2WkFpn5sOB0eCSA/pfAgtll4SmJfeDYmg67xRJOj0/ty9Bq1LmXw1VEf8/y+ngCTkri/10JiJJEj9f/pnfbv4GQOfCnfmh7A+oVabfL5tRGTVxql27Nlu2bMHFxeWtQVu2bMmRI0dSHbAppdXECSB4zs+ELV2KZZYs5N69C7WZ9K6SJIk1tzYy+9IM9CSjT3ZBFdyZwdXr0bVSTiwU2CyfUpIksfrsEybvvkOSTk92V1sWdSxDsWzOSof2WULmLyB04UI0mTKRe/cuLFxdjT/okcly+XGnbND/PFiZ/162fyQk61hy3JdFx/5t/tyzWm4KeDkybe9dAqL+7QGjUavQ6SVK5XBhfc+KZt3HC+Teaf0P9+d66HVsNDbMrjmb6tmqKx2WkBpJcTCvpPymtulcKPuN0hGlKQuOPGDWgfs421py8PvqojT5f93eAfuGQfSLf7/mlEUuViL21RlVsj6Z8WfGs8N3BwCDywzmmyLfmO3NuPTKqImTWq0mMDDwrVmm4OBgsmbNSnKy8dpoGkJaTpz0cXH4NmmKNiAAt7598Bg0SOmQiEuOY+LfE9nttxuA0pkrE/a4DTf95edBQS9HJrUsStlcJnjjnkoxCckM/+sGu28EAFC/sCczvyjxwTLVaUHC3bs8avsFaLVknTMbp8aNjT9omC8sqgS6RHlze+GU93MzJ0/CYhm/4xZH7328Ad/0NsVoXy6HCaL6fHHJcQw5PoRTz0+hUWmYWGUizfOIN0Rpyt9L5De3Ttlg4GWwsFY6ojQjWaen1aLT3HweTYMiniz5qox4Y/qP2ztgUxfeLoH/6ufTbrVInowkXhvPD8d/4MSzE2hUGsZVGpdmelumN0YpR379+nWuX78OwO3bt19/fv36da5cucKKFSvImtW0DS4zGrWdHZ4jhgMQvnwFSY8fKxrPg4gHdNjdgd1+u9GoNAwuM5jfGi9mR996TG1dDBc7S+4GxtB2yVmGbLpG6MtEReP9f7deRNFs/il23wjAQq1iTNPC/Nq5TJpPmqTkZF6MHAlaLY716uLYqJEJBpVg7zA5acpTGwql3RfZnG72rPy6HIs7leZj1YvnHnqATv/JK51Nys7Sjnm159E0d1N0ko5Rp0bx+83flQ5LSI0yX4OjN0Q/g8urlY4mTbHUqJnZtgSWGhX7bwWx63qA0iGZB71OTsbf2QHr1df2DZfPEwwqKjGKngd6cuLZCWw0NvxS6xeRNKURKU6cSpYsSalSpVCpVNSuXZuSJUu+/ihTpgyTJk1i7NixxoxVABzr1cO+alWk5GQCJ01+bx8aY9v+cDsdd3fkUdQjPGw9WNlgJd2KdkOtUqNWq/iyfA6ODKlJh3LZAfjr8jNqzzrGmrOPFX2zKUkS688/pdWiMzwOiyOLsw2b+lSie1WfdHEHMmzFChJv30Hj7IzX2LGm+TPd2wMPD8oFIRrNNLsqeqmlUqlwsbPiY0/TgKgEzj8KN01QBmCptmRy1cl0LdwVgNmXZjPrwiz0kl7hyIQUsbSBakPk45Oz5SbTQooV8nbi21p5ARi34xZhZnQjTzFPzry5PO8tEkQ/l88TDCYwNpAue7twLeQaTlZOLKu/jBrZaygdlpBCKU6cHj16hK+vL5Ikcf78eR49evT64/nz50RHR9OtWzdjxiogv6nzHDUSLC2JPXWKmEOHTDp+vDaesafHMvr0aBJ0CVTOUplNzTZR2rP0W+e62lsxrU1xtvSrTJEsTkQnaBmz/RYtF57mqn+kSeMGiE3U8v2ma4zYcoMkrZ5aBdzZPbAapXNkMnksxpBw/z4hCxcB4Dl6FBbu7sYfNCkO9sqzoFQeAJnzGn9MEwiOSfj4Sak4z1yoVWp+KPcDQ8rIb8BX3V7F6FOjSdab9xJr4ZXSXeSlejEBcOl3paNJc/rVzEtBL0fCY5MYu+OW0uEo72WQYc8TPsov0o+v9nyFX5QfHnYerGq4ipIeJZUOS0iFFCdOOXPmJFeuXOj1esqWLUvOnDlff3h7e6Mx806/6Ym1jw9ur5LUoKlT0ceb5s7jo6hHdNzdka0Pt6JWqfm25LcsqrMIN1u3Dz6udI5M7OhflQnNi+BoY8GN51G0WnSaEVtuEBGbZJLY7wfF0HzBKbZeeY5GrWJYw4Ks6FpO8YalhiJptQSMHAXJyTjUqoVT06amGfjUz3IVPadsUP0H04xpAindPJ5WN5l/XfRrJledjEalYaffTgYeGUhccpzSYQkfY2H977+zk3PkGxdCillZqJn1RQk0ahW7rwew90YGX7LnkMLecyk9T/igq8FX6bKvC0FxQfg4+7C20VryZkofNxszkk8ud3b79m327dvHjh073vgQTCNz715YZPFG+yKA0F9/Nfp4e/z20GFXBx5GPsTNxo2l9ZbSp0QfNCksV6pRq+haORdHhtSkdamsSBKsP/+U2rOPsfHCU/RGXL63+dIzmi84hW9ILB6O1vzRowJ9a+ZB/bFNLGlI2G+/kXDzJmonJ7zGjzfNEr0wXzg9Vz5uODVNVdH7mPI+rng72/C+n6IK8Ha2obyP+RU9SanmeZozr/Y8bDQ2nHp+ip4HehKZEKl0WMLHlOwklyWPDYaLK5SOJs0pmtWZvq/6ro3ZfpNwE928M0s5K4Njlg+f45RVPk/4LCeenaDngZ5EJUZRPHNxVjdcjbeDt9JhCZ8g1VX1/Pz8aNWqFTdu3EClUr3eY/PPGzWdzrw3Eablqnr/FX3wIM8HDERlaYnPju1Y+/gYfIxEXSIzzs9g0/1NAJTzKsf0atNxt/u8ZWDn/MIYu/0W94JiACidw4WfWhalSBbDlQGPT9IxbsdNNl18Bsj9eeZ2KElmh/RVjSrRz49HLVshJSXhPWUKLq1NsMFUkmDdF/Lepjx14Ku/0vzepv/adzOAvmsvA29unf7nT7n4q9I0LJr2X/iuhVzj28PfEpUYhY+zD7/W/VW8oJu7y2tgR3+wywyDroG1g9IRpSmJWh3N5p/iftBLWpTMwi8dSikdknK29oFr69///QKNoMP6dPf73ZR2+O5g7Omx6CQdVbNWZXaN2dhZ2ikdlvB/jFJV7x+DBg3Cx8eHoKAg7OzsuHXrFidOnKBs2bIcO3bsU2MWPoFj3brYV6uGlJxM0OQpBi8U4R/tT+c9nV8nTb2K92JpvaWfnTQBVMjtxq6BVRndpBD2VhouP42k2fxTjN9xi+iEz99v4RvyklaLTrPp4jNUKhhcNz+rupVPd0mTpNMRMGIkUlIS9tWr4dyqpWkGvrtbTpo0VtA47ReEeJeGRb1Z/FVpvJzfXI7n5WyTbpImgBLuJVjdcDWedp48inrEV3u/4mHEQ6XDEj6kxJeQyQfiQuHCMqWjSXOsLTTMbFsCtQq2X33BwdsZdA9PXLhc3AfAxuXN7/3z+b29sG+EfLNMSLXfbv7GqFOj0Ek6muVuxrza80TSlMalesYpc+bMHDlyhOLFi+Ps7Mz58+cpUKAAR44cYciQIVy5csVYsRpEeppxAkh6/Bi/Zs2RkpPJOn8eTvXqGeS6h54cYszpMbxMfomLtQtTq02lataqBrn2fwVGJTBp9+3XJWIzO1gzqklBWpbM+klLznZce8GIv64Tm6Qjs4MVv3QoRZW8mQ0dtlkI++13gqdPR+3gQO6dO7D0NsGb+aQ4WFgeovzlKl910nc1TZ1e4vyjcIJjEvBwlJfnadLRMs9/BMYG0vtgb/yi/HC0cmRhnYWU8sjAd+LN3bUNsLU32GaCQdfBJu2/npnatL13WXLcFw9Haw4OroGzXdpuR5Fq+0fB2QXgUQR6HQP/c3IhCAdPeXne5VWwa7B8brme6fYmmTHoJT1zLs5h1e1VAHxd5GsGlxmMWvXJO2QEIzLqjJNOp8PBQV4WkDlzZl68kEtZ5syZk3v37n1CuMLnsMqVC9fu/1coIu7zNgsn65KZfn46g48N5mXyS0q6l+TPZn8aLWkC+Q7+go6lWdu9Arnd7Ql9mcjgjdfosPRv7r9aypcSCck6Rm+7wcD1V4hN0lHBx5U9A6ul26Qp8dEjQubOBcBj2I+mSZoATs2Rkybn7P+WR07HNGoVlfK40aJkVirlcUuXSROAl70XqxutpoR7CWKSYuh5oCfH/I8pHZbwPkXbgls+iI+A88bf55oefVc3H3nc7QmOSWTirttKh2NaEY/h/FL5uP5EsLACn2pQrK38f7UGynaD5vMBlTyzuft70Iv2BR+TrE9m1KlRr5OmIWWGMKTsEJE0pROp/lssWrTo60a4FSpUYMaMGZw+fZqJEyeSO3dugwcofFzm3r3/r1DE0k++zouXL+i6rytr76wF4Jsi37Cy4Uq87L0MFeoHVc2Xmb2DqjG0QQFsLNWcexRO419OMnn3bV4mal+fp9NLnPUNY/vV55z1DUOnl3gSFkvbJWdY+/dTAL6tlYd1PSrg4ZQ2q559jKTXEzB6DFJiIvaVK+PStq1pBg7zhdO/yMfprCCEAM7Wziyrv4zq2aqTqEvku6PfsfXBVqXDEt5FYwE1X7UCODMf4iMVDSctsrHUMKNtCVQqudfgkbsZaMne4YmgS4LctSBv3fefV7oLtFwEqODiStg1SCRPHxCXHMeAIwPY5bcLC5UFU6pO4euiXysdlmBAqV6qt3//fmJjY2ndujV+fn40bdqUu3fv4ubmxoYNG6hTp46xYjWI9LZU7x8xhw7xrP8AsLQk9ycUijjuf5yRp0YSnRSNo5Ujk6tMplaOWkaK9uOeRcQxcedtDrxae+7lZMOYpoVRq2DirtsERP3bP8fFzpKEJB0JWj2Z7CyZ074ktQp4KBW6SYSvXkPQlCmo7ezkJXpZsxp/UEmCtW3A93C6LQghyJL1yYw/M54dvnKl1O9Kf0e3ot3SRZPodEWvg8WVIeQu1BgOtUYoHVGaNGnXbZafeoSXkw0Hvq+Ok006X7L3/BIsqw2ooM9J8Cr28cdc2wjb+oCklys7Np8vz0oJr0UkRPDt4W+5EXoDWwtbZteYTbVs1ZQOS0iB1OQGqU6c3iU8PJxMmTKliRfV9Jo4SZKEf+/exJ44iX2VKmRfvixFfx/J+mTmX57Pb7d+A6CoW1Fm1ZxFVgcTvBFPgaN3gxm34xZPwz++BNEnsx3relQki4utCSJTTtLTp/i1aIkUH4/XuLFk+vJL0wx8Zyds/EouCNHvb3DLY5pxBUVIksTPl3/mt5vy74bOhTvzQ9kfxHITc3NrK/z5NVg7yRX27NJuiXylxCfpaDzvJI9CY2lfNjvT2xZXOiTjkST4vQk8OQ0lOkKrxSl/7I3NsKUXSDoo3h5aLhbJ0ysvXr6g98HePI5+jLO1MwvrLKSEewmlwxJSyKh7nN7F1dWVu3fviqV6ClKpVHiNGoXK0pLY06eJOXjwo48JjA2k+/7ur5OmToU6sbrRarNJmgBqFfTgwODqDKj98SZxCcl6PNPp0rx/vF6iFx+PXfnyuLRvb5qBk+LkykoAlQeKpCkDUKlUfF/me34oKzdcXXN7DSNOjiBZ9/lVLwUDKtQCPItCYjScXah0NGmSrZWGGW2Lo1LBxov+nLgfonRIxnNvr5w0WdhA7dGpe2yxttB2Bagt4PpGOYnSaT/+uHTuQcQDOu/tzOPox/Je0YarRdKUjhns1mFSUhJPnjwx1OWET2CVMyeuPboDEDR12gcLRZx5foZ2O9txJfgK9pb2zK4xm+Hlh2OpMb8lCjaWGirn+XiBh4CoBM4/CjdBRMqJ2LCBuPPnUdna4j15Eiq1ie7+n5ydoQpCCP/qWqQrU6pOwUJlwZ5HexhwZABxyZ9XhEYwILUaar66qXFuCcSGKRtPGlUulytdK+UCYMSWG8QYoC2G2dFp4dA4+bhiP3D+hJukRVrBF7/LydPNzfBXd8jAN1MuB12m676uBMcFk8c5D2sarSG3i5hESM/Emot0JnOvXlhmyYI2IIDQJW9XWtLpdcy/Mp8+h/oQkRhBQdeCbGq6ifq56isQbcoFxyR8/KRUnJcWJT17TvCs2QB4fP89Vtmzm2bg0IdwZp583HAaWIkeFBlNszzNmF9nPrYWtpx+cZru+7sTnpC+b1KkKQWbgFdxSHr5779VIdV+bFiAHK52PI+MZ+reu0qHY3iXV0HofbBzg6rfffp1CjWDdmtAbQm3t8Hmb0CbZKgo04xj/sfodbAXMUkxlHQvyapGq0xWTEtQjkic0hm1rS2eo0YCEPbbbyT6PXr9vdD4UHod7MXS60uRkPgi/xesbbyWHE45lAo3xTwcU7YEL6XnpTWSJBE4dgxSXBy2ZcuQqVNHUw0Me4fK1Zfy1pPfoAkZUtWsVVlefzku1i7cDLtJ171defHyhdJhCSAXaak1Sj4+vxRepuOlZkZkZ2XB9Dby/qY/zj3lzMNQhSMyoMQYODZVPq4xHGycP+96BRtDh3Xyntc7O+HPrqBN/Pw404itD7by3dHvSNQlUiNbDZbWX4qz9Wf+TIU0QSRO6ZBD7drY16gOyckETZqEJEmcDzhP2x1tOR94HlsLW6ZWm8rYSmOx1lgrHW6KlPdxxdvZhveVu1AB3s5yc9L0KPLPP4k9cxaVtTVZJplwid6dneB7RH5xbDRdVNHL4Iq7F2dVo1V423vzOPoxnfd05n7EfaXDEgDyN4AspSE5Dk7PVTqaNKtSHje+qijfTPzxr+vEJqaTPTyn50FsCLjmgbLfGOaa+RtAh/WgsYZ7e2BjZ0hOv6s+QL6JufzGcsaeGYtO0tEyb0vm1pqLrUX6Lkol/CvF774yZcqEq6vrez+qVRMlF82FSqXCa+RIuVDEmTNsWTaUngd7EpYQRl6XvGxouoGmuZsqHWaqaNQqxjUrDPBW8vTP5+OaFU6XzUmTAwIInj4DAPfvvsMqVy7TDJwU+29BiCqDREEIAYDczrlZ02gNeV3yEhwfzNd7v+ZS0CWlwxL+f9bpwnKICVQ2njRseKNCZHWx5VlEPDP2pYMle9EBcHaBfFx3PBhyL3O+utBxo1xs4sF+2Ngp3SZPeknPjAsz+OWy3Muwe9HuTKw8EQu1hcKRCaaU4nLkq1atStEFu3bt+lkBGVt6LUf+Lk/nTCd26e+EOsLgXhoaFmrJqIqj0vSdkX03A5iw880+Tt7ONoxrVpiGRb0VjMw4JEnCv1dvYk+exLZkSXKuW4tKY6Lyr4cnykUhnHPAt+fE3ibhDVGJUQw4MoArwVew1lgzo/oMaueorXRYGZskwYr68Ow8VOgjzxILn+TUg1C+WnEOgI29KlIht5vCEX2G7f3hyhrIXhG67TPOygG/47C+gzzjmbsWdPgjXb1mJOuSGX16NHse7QHgx3I/0rlwZ4WjEgzF5H2c0pKMkjhdCb7CiIPfM2JeIB5RENa2BlUnLVE6LIPQ6SXOPwonOCYBD0d5eV56nGkCiPxrCwGjRqGyssJn21asTVXyP/QhLKoI+mT5BVDsbRLeIUGbwNATQznmfwy1Ss3YimNpk7+N0mFlbL5HYU1LefnUwCufVjlNAGDEluusP+9PTjc79g2qjq1VGuxZFHQbllSRG9d2PwjZyxtvrMenYd0XkBwLPtXhyw1gZW+88UwkLjmOwccGc+bFGSxUFkyqOokmucVrYnpi8j5OgvnQS3p+u/kb3+z7hufaUPY0l2dh3LafeaNQRFqmUauolMeNFiWzUimPW7pNmpKDggiaNg0A94EDTJc0/VMQQp8M+epDgcamGVdIc2wsbPi55s+0ytsKvaRn/NnxLLu+jAx2P8685K4JOSqDLhFOzVE6mjRtRONCeDvb8CQsjpn77ykdzqc5OFZOmgq3MG7SBJCrCnTeAlYO8OgErGsHiS+NO6aRhSeE031/d868OIOthS0L6ywUSVMGJxKndCQqMYpBRwYx59IcdJKORj6NGDN0Bw41arxRKEIwf5IkEThuPPqYGGyKFcP1669NN/idHa8KQliLghDCR1moLZhQeQI9i/UEYN6VeUw7Pw29pEen13Eh8AJ7/PZwIfACOr1O4WgzAJUKar/a63RpFUT6KxtPGuZkY8nU1sUA+O3MIy4+TmMl+P2OwcODctnwOuNMM2aOitB5K1g7wZNTsK6tXNEvDXr+8jld93blZthNXKxdWFF/BZWzVlY6rHRBp5c46xvG9qvPOesbhk6fdt6biqV66cSNkBv8cPwHXsS+wFJtyfDyw/ki/xeoVCqSnj7Fr2kzpKQkss6di1PDBkqHK3xE1I4dvPhxGCpLS3y2/IV1vnymGTgpFhaUh+hnUP3Hf9+ACUIKrLuzjmnn5VnSku4leRH7guC44Nff97TzZHj54dTNWVepEDOOVc3ku/5lvoZmvygdTZr2w5/X2HzpGbkz27NnUDVsLNPAkj29HpbWgMDryux3e3YJ1rSCxCjIVh6+2vz5JdBN6F74Pfoe6ktIfAje9t78Wu9XfJx9lA4rXTDHveoGX6oXHR1tkMAEw5MkiXV31tFlXxdexL4gm0M21jZeS7sC7VC9mimwypEDtx49AAiaNg19bKySIQsfoQ0JIXDyFAAyf9vPdEkTwIlZctLkkgOqDjbduEK60KlQJ2ZUn4FapeZqyNU3kiaA4Lhgvj/2PYeeHFIowgykptzPjytrIeKxoqGkdWOaFMbTyRq/0Fh+PphGyu/f2CQnTdZO8k0wU8tWBrpuBxsXuVjJmlYQH2n6OD7BpaBLfLPvG0LiQ8jrkpc1jdaIpMlA9t0MoO/ay28kTQCBUQn0XXuZfTcDFIos5VKUOGXKlIngYPkFsHbt2kRGRhozJiGFYpJiGHJ8CNPOT0Or11IvZz02NdtEYbfCb53r1qsnllmzog0MJHRJ+igSkR5JkkTAhAnoo6KwKVwYt+7dTTd46AM4M18+bjg9XVVEEkynfs76OFu9+86yhLzAYfr56WLZnrHlrAR5aoNeC8dnKh1NmuZsZ8mUVvKSvWUn/bjyNELhiD4iOR4O/yQfV/se7BWqCJilFHTdCbau8PwSrG4Bcea93PHw08P0OtCLmOQYSnuU5veGv+Np76l0WOmCTi8xYedt3rXM7Z+vTdh52+yX7aUocXJwcCAsLAyAY8eOkZycbNSghI+7E3aH9rvac/DJQSzUFgwvP5zZNWbjaOX4zvPVNjZ4jpKXXYX99juJfn6mDFdIoeg9e3h56DBYWuI9dQoqSwP22/gQSYI9/xSEaAAFGplmXCHduRx8mYjE97+xlJAIjAvkcvBlE0aVQf0z63RtPYT5KhtLGlenkCetSmVFL8GPm6+TkGzGif+5JfLKAads8jI9JXkXl5MnOzcIuAqrm5tt8vTX/b/4/tj3JOmTqJm9Jr/W+xVn67SzvNDcnX8U/tZM0/+TgICoBM4/Ms/nxz9SlDjVrVuXWrVqUatWLQBatWpF7dq13/khGJckSWy6t4mv9nyFf4w/WeyzsLrhajoV6vR6ad77ONauhUPNmqDVikIRZkgbFkbQT5MAyNy7NzYFCphu8Nvbwe/oq4IQ00RBCOGThcSFGPQ84TNkLydXxpR0cHyG0tGkeeOaFSazgzUPgl8y7/ADpcN5t9gwOPmqmmLt0WBpBn0bvYpC111g7w6BN+T9d7GhSkf1miRJLL2+lPFnx6OX9LTO15qfa/6MjYWN0qGlK88j41J0XnCMeTdQTlHitHbtWsaPH0/ZsmUBKFKkCCVKlHjnh2A8scmxDDs5jJ/+/okkfRI1stVgU7NNFHMvluJreI4aicrKitgzZ4nZv9+I0QqpFfjTJHSRkVgXKEDmXj1NN3BSLOx/dWe66nfgaqKy50K65G7nbtDzhM9Uc4T8/xubICSN7M8xUy52VkxqWRSAX0/4ceNZlMIRvcOJGZAYDV7FoHh7paP5l2dh+Ho3OHhC0E34vSm8DP7444xML+mZen4q86/Iy9R7FuvJ+ErjsVBbKBxZ+qHV6dl00Z9pe+6m6HwPR/NOWFP0zLC1taVPH3m69+LFi0yfPh0XFxdjxiX8x/2I+ww5NoTH0Y/RqDQMKj2IrkW6olalrqK8VfbsuPXsSejChQRNnYZDtWqo7dN+g7q0Lnr/AWL27QONBu8pk1FZWZlu8BMzIfq5KAghGERpj9J42nkSHBf8ek/Tf2lUGmwtzOBOeEaQtTQUaAL3dsPx6dB2hdIRpWkNi3rRrEQWdl57wdDN19jRvypWFmbS2SXMFy4sl4/r/QRqM4nrH+4F5ORpVTMIuSMnT113gqMye4iSdEmMPDWS/Y/3o0LFsPLD6FSokyKxpEeSJLH/VhCzDtzjYbDcz0utgvdtYVIBXs42lPdxNV2QnyDV/6qOHj36OmmSJEks9zKBrQ+20ml3Jx5HP8bDzoOVDVbyTdFvUp00/cOtZw8ss2VDGxRE6OLFBo5WSC1tRASBEycC8t+NbZEiphs85D6cWSAfN5phHss6hDRNo9YwvPxwAFS8e8mnTtLRZW8XNt7dKF5DTKGm/PfBzb8g+I6ysaQDE5oXwc3eiruBMSw4+lDpcP51eIJcDCRvXchTS+lo3i1zPjl5csoKoffg9yYQbfpKarHJsfQ73I/9j/djobZgevXpImkyoDMPQ2m56Ax91l7iYfBLXOwsGdW4EHPbl0QFb70y/PP5uGaF0ajNe6vAJ73zXr16NcWKFcPW1hZbW1uKFy/OmjVrDB1bhhevjWf0qdGMPTOWBF0ClbNU5s9mf1Las/RnXVcuFCEvzQr7fRWJvmLTsJKCJk1GFxaGdb68ZO7Xz3QDSxLsfVUQIn9DURBCMJi6Oesyp+YcPOw83vi6l50Xk6tMpmb2miTrk5l0bhLDTgwjNlm0SDAq7+JQqDkgwbFpSkeT5rnaWzGxhbxkb9HRh9x6YQZL9vzPy3tVVWqoN1HpaD7MLY+cPDlnh7AH8HtjiHpusuHD4sP4Zt83nAs4h52FHYvqLKKRj3j9M4TrzyL5avk5Oi4/xzX/SOysNAysnZcTP9aiZ/XcNC+ZlcVflcbL+c3leF7ONiz+qrRifZxSI9UNcOfMmcOYMWPo378/VapUQZIkTp8+zcKFC5k0aRKDB5v3Up+00gDXL8qPIceG8DDyIWqVmn4l+tGzeM9PnmV6F/++/Xh59Ch2lSqSY+XKjxaXEAwv5vBhnn3bH9Rqcm3cgG2xlO9X+2y3tsKfX8sFIb49B66iT4VgWDq9jsvBlwmJC8Hdzp3SHqXRqDVIksTq26uZe2kuWklLLqdczK45m/yZ8isdcvoVdBsWVwYk6HNa3rAvfJa+ay+x92Yghb2d2N6/CpYahZbGSRKsbAD+56DUV9BioTJxpFbEE1jVFCKfQqZccgEJl+xGHdI/xp8+B/vwNOYprjauLKqziCKZTbjKI516GPySOQfvsedGIACWGhWdKuTk21p5cXe0fut8nV7i/KNwgmMS8HCUl+cpOdOUmtwg1YmTj48PEyZMoEuXLm98fdWqVYwfP55Hjx6lPmITSguJ026/3Uw4O4F4bTxuNm7MqD6D8t7lDT5Okr8/fk2aIiUlkfXnOTg1EndcTEkXGYlvs2boQkJx69kDjyFDTDd44ktYUA5iXkCN4VBrhOnGFoRXrgZf5YfjPxAUF4S1xppRFUbRMm9LcRPHWP78Bm5tgYJNocM6paNJ80JiEqn/83Ei4pL5vl5+BtYxYbPy/3d7B2zqDBa2MPAyOGVRJo5PEekvJ08Rj+V9tl13QaacRhnqbvhd+h7qS2h8KFkdsvJrvV/J6WScsTKKF5Hx/HLoAX9e8kcvyQV5W5XKyuC6+cnumnZ6QaYmN0j17ZGAgAAqV6781tcrV65MQID5d/w1Jzq9jguBF9jjt4cLgReIS45j4tmJDD85nHhtPOW8yrG5+WajJE3wqlBEr14ABE2dhu6lWC5jSkFTp6ELCcUqd24y9+9v/AH1Onh0Em5shp0D5aTJJadcSU8QFFDSoyR/NvuTKlmrkKhLZOyZsYw+PZq45JSVrRVSqeZwQAV3d8GLK0pHk+a5O1ozvrk8WzH/yAPuBkabPghdMhwaLx9X7p+2kiaQZ5i+3iNXc418Ku95Cjd8n8kLgRf4Zt83hMaHkj9TftY0WiOSps8QHpvEpF23qTnrGBsvyklTvcKe7BtUnTntSqappCm1Up045c2bl02bNr319Y0bN5Ivn0J3W9KgQ08O0eCvBnTb341hJ4fRbX83qqyvwp/3/0SFil7Fe7Gs3jIy22Y2ahxuPbpjmT072uBgQhcvMupYwr9ijh0javt2UKnwnjwJtfXbU9kGdXsHzC0q39n7q7u8SRygaBtREEJQVCabTCyqs4hBpQehVqnZ4buDTns64RcpmnQbnHsBKPaFfCz2OhlE8xJZqFfYk2SdxNA/r6PV6U0bwMXfINxX7pFUZZBpxzYU56xy8uSWD6L85Wp7BmzYfPDJQXof7M3L5JeU9SzL7w1/F+0QPtHLRC2/HHpA9RlHWX7qEUlaPRV8XNnSrzLLupSlgJej0iEaXaqX6v3111+0b9+eunXrUqVKFVQqFadOneLw4cNs2rSJVq1aGStWgzCHpXqHnhzi+2Pfv7dUb+/ivelfygQzEK/EHDvGsz59wcKC3Nu3YZ0nj8nGzoh00dH4NWuONigI16+/xnP4MOMOeHsHbOoC73y+qaDdaijc3LgxCEIKXAi8wI8nfiQ0PhRbC1vGVBxDszzNlA4rfQl9CAvLgaSHHkcgWxmlI0rzgqMTqPfzCaLik/mxYQH61cxrmoETomFeSYgLgyazoVwP04xrLDFBcqny0Hvg6C2XKs/8eTfkN93bxKS/JyEhUTdHXaZVn4a1xsg3KtOhRK2OdX8/ZeHRh4TFJgFQJIsTPzYsSPV8mdP88mqjLtVr06YN586dI3PmzGzbto0tW7aQOXNmzp8/b/ZJkznQ6XVMOz/tvUkTwPaH29HpdSaLybFmTRxq1QKtlsCfJonywEYWNH062qAgrHLmxH3QQOMOptfBvmG8O2l6Zd9w+TxBUFg5r3L82exPKnhXIF4bz8hTIxl/ZjwJWvPuJJ+mZM4LJb6Uj49NUTaWdMLDyYaxTQsDMPfgAx4ExZhm4NNz5aTJLR+U7mqaMY3J0VOutudRGGIC5GV7wSlrmvpfkiSx+Opifvr7JyQk2uZvy6was0TSlEo6vcSfF/2pPes4E3fdJiw2CZ/M9izoWIqd/atSI797mk+aUivVM05pndIzThcCL9Btf7ePnreywUrKeZUzQUSypGfP5EIRiYlknTMbp8aNTTZ2RvLy5Cn8e/YElYqca9dgV8bId3sfnZSX531M113gU824sQhCCun0On69/itLri1BQqJApgLMrjlb7EkwlPBHML8MSDrodgByVFA6ojRPkiS6/X6Bo/dCKJndhb/6VjZulbCo5zC/NGgToMMfULCJ8cYytdhQWN0Cgm7KSxC77ADPwil+uE6vY+r5qWy8txGAPiX60K9Evwz3Bv9z/NO8dvaBezx41bzW08ma7+rmp22ZbMpVkDQSo844CZ8nJC7EoOcZilW2bLj16glA0LTpolCEEeheviRg7FgAMn31lfGTJoCXQYY9TxBMQKPW0K9kP5bUW4KrjSv3Iu7Rfld79j/er3Ro6YOrD5R61exTzDoZhEqlYkrrYjhaW3DVP5IVp4y8R+/oZDlpylEZCqSzG532meVlel7FITZEvvkXeDNFD03UJTL0xFA23tuIChWjKozi25LfiqQpFc74/tu89kHwS5xtLRnZuCDHh9biy/I50l3SlFoZ+0+vgJRuSFRi46Jbjx7/FopYJApFGFrwzFloAwKwzJ4dj8HfmWZQB0/DnicIJvS66bdHaWKTY/nh+A9MOTeFJF2S0qGlfdV+ALUl+B2Dx6eVjiZd8Ha2ZXTTQgDMPnAfv5CXxhko8AZc/UM+rj9JrgGd3ti5QtcdkKWUvBxxVVMIuPbBh8QkxdD3UF8OPjmIpdqSWTVm0aFgBxMFnPbdeBZF5xXn6LhMbl5ra6mhfy25eW2v6nmwsdQoHaJZEImTiZX2KI2nnScq3v2LToUKLzsvSnuUNnFkoLa2xnPUSADCV68m8eFDk8eQXsWePUvkRnnZgPekSajtTFSqM2flj5SnVYFTVvk8QTBDHnYerGiwgu5FuwOw/u56uuztwrOYZwpHlsZlygmlO8vHRyfLTVSFz9aubHaq5ctMolbPj5uvo9Mb4ed6cCwgQZHW6bu4h20m6LwNspaB+AhY1fy9ZfRD40Pptr8bFwIvYG9pz+K6i6mfq75p402jfENe0m/dJZotOMXJB6FYalR8XTkXJ36sxQ8NCuBsa6l0iGZFJE4mplFrGF5+OMBbydM/nw8rPwyNWpnM3rFmTRxq1xaFIgxIHxtLwOgxAGTq+CX2FYzTl+ud1Boo8r6iLa+efw2nyecJgpmyUFvwXZnvWFhnIc7WztwKu0W7Xe048vSI0qGlbdWGgMYKnpyGRyeUjiZdUKlUTGtTHAdrCy4+iWDVmceGHeDhYfA9Is8W1hlr2GubI1sX6LwVspWHhEhY1QKeXXrjFP9ofzrv6czd8Lu42bjxW4PfqOAt9u19TEBUPMP/uk79n0+w50YgKhW0LpWVI0NqMr55EdwdRSGNdxGJkwLq5qzLnJpz8LDzeOPrnnaezKk5h7o56yoU2as4Ro5AZW1N3LlzRO/Zo2gs6UHw7DkkP3+OZZYseAwZYtrBE2Pg5hb52Po//RWcsohS5EKaUj1bdf5s+ifF3YsTkxTDoKODmHVhFsn6ZKVDS5ucs0GZr+Xjo1PErJOBZHWxZUTjggDM2H+Xx6EG2jOs172abQLK95L3qmUENs7QeQvkqASJUbCmJfifB+BO2B2+2vsVz14+I5tDNtY0WkMht0LKxmvmImKTmLz7NjVmHmPDBX90eom6hTzZO6gac9qn7+a1hpDqqnqxsbFMmzaNw4cPExwcjF7/ZrM3Pz/zblqodFW9/6fT67gcfJmQuBDc7dwp7VFasZmm/wpZtIjQefOx8PAg9549aBzslQ4pTYo9f56nXeQysTlWrsC+somXxB0YA2fmQaZc0OcMvLgsF4Jw8JSX55nJ800QUiNZl8zPl39mze01AJRwL8GsGrPwsvdSOLI0KDpA7gWkTYCvtkDeOkpHlC5IkkSn5ec44xtGeR9XNvSsiPpzq+xdWQfb+8mJxMCr8j6gjCTxJfzRHp6cAisHzjWexKDbvxKbHEsh10IsqruIzLaZlY7SbMUmallx6hHLTvgRk6gFoLyPK8MaFqRMzkwKR6es1OQGqU6cvvzyS44fP07nzp3x9vZ+q1LJoEHm3bnanBInc6ZPTMSvWXOSnz7FtVs3PH8cqnRIaY4+Ph6/Fi1JfvoUly++wPuniaYNIPguLKkCei103AT5G5h2fEEwssNPDjPm9BhikmNwsXZhStUpVMsmyuqn2r6R8PdCyFoWehxKn8UGFOAfHkeDuSeIS9IxsUURulTK9ekXS4qTS8jHvIB6P0EVI/cANFdJsbC+A/uDLjDCIzPJKhXlvcrzS61fcLByUDo6s5So1fHHuacsOPJm89qhDQpkyD5M72LUxMnFxYXdu3dTpUqVzwpSKSJxSrmXJ07g36s3WFiQe+sWrPN9XgfvjCZo6lTCV63GwsuL3Dt3oHF0/PiDDEWS5A7sj09CgSbw5R+mG1sQTMg/xp8fjv/A7bDbAPQs1pN+JfthobZQOLI05GUwzC0O2njo+CfkF5vqDWXVmceM23ELOysN+7+r/unLoE7MgiM/gXMO6H8BLG0MG2gasuHWaqZcnIkE1ItLZGq9RVjnVXaLgznS6SW2XXnOnIP3eR4ZD4BPZnu+r5efJsW8P38GNB0xah+nTJky4eqawaaHMyiH6tVxqFNHFIr4BHGXLxO+Wl5G5P3TRNMmTQA3/5KTJgsbaDjVtGMLgglld8zOmkZr6FBALju87MYyeh7oafJeeGmagweUl/v4iQp7htW5Yk7K+7gSl6Rj+Jbrn/Y6+jIETs2Vj+uMzbBJkyRJLLiygMmvkqb2KmdmBgVhvaGTXDBDAP5pXhtIo19OMOTPazyPjMfTyZoprYpxYHB1mpXIIpKmz5DqxOmnn35i7NixxMXFGSMewcx4jnhVKOL8eaJ3i0IRKaFPSCBg5CiQJJxbt8ahmomXDiXGwIHR8nG1IXLZYUFIx6w0VoyqOIqZ1WdiZ2HHxaCLtN3Zlr8D/lY6tLSjyiCwtIeAq3BP/K43FLVaxYw2xbGxVHP6YRjrz/un/iLHp0NSDHiXhKJtDB5jWqDT65j490R+vf4rAP1K9mPUl4fQ5Gsg78/7owM8OKRwlMo76xtGq0Vn6L3mEveD5Oa1IxrJzWs7VhDNaw0h1Uv1SpUqha+vL5IkkStXLiwt36zvfvnyZYMGaGhiqV7qhS5eTMgv87Bwdyf33j1oHMQ64g8JmjGT8JUr5cIau3aiMfXz7MBoODMfMvlAv78z7N1JIWN6HPWYIceHcD/iPipU9C3Zl17FeplN4R2zdmgCnJoDnsWg9wlQizdZhrLi1CN+2nUbB2sL9g+uTlYX25Q9MPQhLKog71Xtugt8Mt4evkRdIsNODOPw08OoVWpGVRhFuwLt5G9qE+HPb+Debrm0fvu1GXI/741nUczYf5eTD0IBsLXU0K1qLnpVzyP6MKWAUfc4TZgw4YPfHzduXGouZ3IicUo9fWIifs2bk/zkKa7ffIPnsB+VDslsxV+7xuMvO4JeT7bFi3CsVcu0AQTfgSVV5RfZTpshXz3Tji8IZiBBm8C089P468FfAFTyrsTUalNxs3VTODIzFxcu73VKinnVqqCF0hGlGzq9RLtfz3LpSQTV8mVmdbfyKduUv6ET3N0F+RtCx43GD9TMRCdFM/DIQC4FXcJSbcmM6jPebtmiTYK/usGdnXJ/q3aroWBjZQI2Md+Ql8w5cJ/dNwIAsNSo+LJ8DvrXzouHo7hpmlJGTZzSOpE4fZqXJ0/i37MXaDT4bN2CTf78SodkdvSJiTxq3YYkX1+cmjcj64wZpg3g/wtCFGwKHdaZdnxBMDM7fHcw6e9JxGvj8bD1YHr16ZT1Kqt0WObtyGQ4MQPcC0HfM2LWyYB8Q17S+JeTJGr1zGhTnHblsn/4AU/Owm8NQaWGvmfBo6BpAjUTIXEh9DnUh/sR93GwdGBe7XmU8yr37pN1ybClJ9zaCmoL+OJ3KNTMpPGaUkBUPPMOP2DTxWfo9BIqFbQsmZXBdfOTw030YUotoxaH+MelS5dYu3Yt69at48qVK596GSGNcKhWDYe6dUCnI0gUinin0IWLSPL1RZM5M14jR5o+gP8vCNFgiunHFwQz0zxPc9Y3WU9u59wExwfT40APVtxYgV7Sf/zBGVWlb8HaGULuwO2tSkeTruRxd+D7evJNx5923yYwKuH9J0sSHBwjH5fukuGSpifRT+i8tzP3I+6T2TYzvzf8/f1JE4DGElovh6Jt5RUXm7rKSVQ6ExGbxJQ9d6gx8xjrz//TvNaDvYOq8XP7kiJpMoFUJ07BwcHUrl2bcuXKMXDgQPr370+ZMmWoU6cOISGiilF65jl8BCobG+IuXCB6126lwzEr8TduErZiBQBe48aicXExbQCJMbB/lHxc7QdREEIQXsnjkof1TdbTLHczdJKOuZfn0v9wfyITIpUOzTzZukDl/vLxsWmg1ykaTnrTo1puSmZ3ISZBy8itN95/E/L2Nnh2QS7YUVOBG3EKuhV6iy57u/D85XNyOOZgdaPVFHAt8PEHaiyg9VIo3gEkHWzuDjc2Gz9gE4hN1DL/8AOqzzjK0hN+JGn1lM/lyl99K7G8azkKeokVVKaS6sRpwIABREdHc+vWLcLDw4mIiODmzZtER0czcGAGbciWQVhly0rmPr0BCJoxHd3LlwpHZB70SUkEjBwJOh1OjRvjVE+BfUXHpsHLQHDNDZUHmH58QTBjdpZ2TK46mfGVxmOtsebk85N8sesLroVcUzo081ShD9i4QOh9eSZbMBiNWsXMtsWx0qg5cjeYrVeev32SNkku1AFyo1tHT9MGqaAzL87QbX83whPCKexWmNWNVpPd8SNLGv+fWgMtF0HJTnLytKUnXEu7e8MStTp+P/2IGjOPMvvgfWIStRT2duK3b8qxsXdFyuQU7YFMLdWJ0759+1i8eDGFChV6/bXChQuzcOFC9u7da9DgBPPj2q0bljlzoAsJJXTBQqXDMQthS5aQ+OABGldXPMeMNn0AQbfh78XycaOZooqeILyDSqWiTf42rGu8jpxOOQmMDeTrvV+z+tZqsfT4v2yc5DfsIN+U0WmVjSedyefpyKC6ckP5CTtvExz9nyV7F1dAxCNw8IRK/RWIUBl7H+3l28PfEqeNo4J3BVY2WPlpBV3UGmi+QF7iKOlha2+4mraawOv0En9dekad2ccZv/M2oS+TyOlmx7wvS7FrQFVqFfBIWXERweBSnTjp9fq3SpADWFpaoteLdePpndrKCq/RcnIQvmYNCffvKxyRshLu3CF06TIAvMaOwSJTJtMGIEmwZ6h8Z61gU8gnuqcLwocUcC3AhiYbaJCrAVpJy8yLMxl8bDDRSdFKh2ZeyvcCOzcI94XrafeOvbnqXT03xbI6ExWfzKhtN/9N3uMj5b5NALVGgnXGaP+x7s46fjzxI1q9loa5GrKoziLsLe0//YJqNTT9Bcp2AyTY1g8urzZYvMYiSRIH/q957bOIeDwcrZncqiiHvq9Bc9G8VnGpTpxq167NoEGDePHixeuvPX/+nMGDB1OnTh2DBieYJ4dq1XCsV1cuFDHxpwx7t1ZKTubFyFGg1eJYvz5ODRuaPoibf8GTU2BhCw2nmn58QUiDHKwcmFl9JqMqjMJSbcnhp4dpt7Mdt8JuKR2a+bB2lJvigvxGXpesbDzpjIVGzcwvimOpUXHwdhA7rr16T3VqDsRHgHtBKPmVskGagCRJzLs8j2nnpwHQsWBHplefjpXG6vMvrlZDkznyTQAk2DEALq78/Osayd9+YbRefIZer5rXOtlYMPxV89pOFXKK5rVmItV/CwsWLCAmJoZcuXKRJ08e8ubNi4+PDzExMcyfP98YMQpmyHP4cLlQxMWLRO/apXQ4ighdtozEO3fQuLjgNXaM6QNIiP63IET1IeCSw/QxCEIapVKp6FCwA2sarSGrQ1aev3xO5z2d2XB3Q4a9GfSWcj3A3h0in6S5pU5pQUEvJ/rXkpfsjd9xi7DnD+HvJfI3602Uix2kY1q9lvFnx7PshrxqY2CpgQwvPxy1yoAJgkoFjWZAxX7y57sGw/llhru+Adx8HkWXlefpsPRvrjyNxMZSTb+aeTj5Y2361MiDrZVo3m1OPrmP08GDB7l79y6SJFG4cGHq1k0bS4REHyfDCV3yKyFz56Jxz0yevXvROGSMJQUACffu86htW0hOJsusWTg3bWL6IPaPgrML5IIQ/f4GC2vTxyAI6UB0UjRjTo3hiP8RABrmasj4yuM/b6lQenF2EewfAc7ZYcBlsDDATIDwWrJOT4sFp7kdEM1G95VUiDkEuapB153ym/50KkGbwNATQznmfwy1Ss3YimNpk7+N8Qb8p7z7mVc3+BtOg4p9jTdeCviFvGT2wfvsvi43r7VQy81rB9TOi4eT2KtsSqIB7geIxMlw9ElJPGrWnKQnT3Dt2hXPEcOVDskkJK2Wx+07kHDrFg516pBtwXzTb9IMug1Lqsp7mzr9JfY2CcJnkiSJNbfX8POln9FKWnI55WJWjVkpK4OcniXHwy8l5aqdTeZAue5KR5Tu3HoRxciFa9lu+arseK9jkKWUojEZU1RiFAOPDORy8GWsNdbMqD6D2jlqG39gSYLDE+DUz/Ln9ScpUoU2MCqBXw4/YNNF/9fNa1uUyMLgevnJ6SZu1ijB4InTvHnz6NWrFzY2NsybN++D55p7SXKROBnWy5On8O/ZEzQafLZswaZAfqVDMrrQX5cS8vPPqJ2dyb1zB5YeHqYNQJLg9ybw5LRcEKLDOtOOLwjp2NXgqww9MZTA2ECsNdaMrDCSVnlbZewKVueWwt6h4JRVnnUSlTsNS5J4OrcuOaIuskdVjQpD/sLNIX2uIAiKDaLPoT48jHyIo6Uj8+vMp4xnGdMFIElwdDKcmCl/Xnc8VB1skqEjYpNYctyX3888JlErF1OrU9CDHxoUoJC3eD+qJIMnTj4+Ply8eBE3Nzd8fHzefzGVCj8/v9RHbEIicTK8ZwMGEnPwILZly5BzzZp0/QYj8eFDHrVqjZScjPe0qbi0bGn6IK7/CVt6yAUh+p8Xe5sEwcAiEyIZeWokJ5+fBKB5nuaMqjAKO0s7hSNTSHICzC8N0c/llgcVeikdUfpy/wD88QVJWFIrYRalS5Rg/pfpb8bJL8qPPgf7EBAbgLutO0vqLSF/JoVuth6bDsemyMe1R0P1oUYbKjZRy2+nH/HrcT9iEuXS/uVyZeLHhgUpl0v0YTIHYqneB4jEyfCSX7zAt3ETpIQEssyYjnPz5kqHZBSSVsvjjp1IuH4d+xrVyb5kiemTxIRoWFAWXgZB7TFQ/QfTji8IGYRe0rPy5krmX5mPXtKTxzkPs2vOJo9LHqVDU8aFFbD7e3DwgkFXwdJW6YjSB51WXnYdcofgYr2pdKkmOr3Er53L0KCIl9LRGcyNkBv0O9yPyMRIcjnlYkm9JWR1yKpsUCdmwpFJ8nHNEVDTsNsNkrR61p9/yvwjDwl9mQhAQS9HhjUsSM0C7un6JnNak5rcINWlSyZOnEhcXNxbX4+Pj2fixImpvZyQDlhmyULmvvImy6CZM9HFxCgckXGEr1pFwvXrqB0c8J4wQZlfesemyUmTax5F1mYLQkahVqnpUawHK+qvwN3WHd8oX77c/SU7fXcqHZoySnWWC0S8DDTrks5pztV1EHIHbDPh0XgkvavnBmDU1ptExiUpHJxhnH5+mu4HuhOZGElRt6KsarRK+aQJ5FmmuuPl42NT5STKAHMJOr3ElsvPqDPnGON23CL0ZSI5XO34pUNJ9gysRq2ConltWpbqGSeNRkNAQAAe/9nXERYWhoeHBzqdzqABGpqYcTIOfVISj5q3IOnxY1y7dsFzxAilQzKoRL9HPGrZEikpCe/Jk3BpY8TqP+8TdAuWVJMLQnz1F+QVBSEEwRTC4sMYfnI4fwf8DUCbfG0YXn44NhYZbK/PpVWwc6BconzQNbASG9k/S1IszCstJ6MNpkKlfiQk62g6/xQPg1/SulRW5rQvqXSUn2WX3y7GnBqDVtJSOUtlfq75s/kteT2zAA68au1RdTDUGfdJFQ0lSeLQnWBm7b/HvSD5BrK7ozUD6+SjfdnsWFmIPkzmyqgzTpIkvTNTvnbtGq6uYq1mRqW2ssJz9GgAwteuI+HePYUjMhxJpyNg1CikpCTsq1bFuXVrBYKQYPcPctJUqJlImgTBhNxs3VhSdwn9SvRDhYq/HvzFV3u+4nHUY6VDM62SHSFTLogNgQvLlY4m7TuzQE6aMuWSe2YBNpYaZrYtjloFW6485/CdIGVj/Axrbq9hxMkRaCUtjX0as6D2AvNLmgAq94eG0+XjUz/LZctTOfN0zi+MNovP0HP1Re4FxeBkY8GwhgU5MbQWnSvmFElTOpLiv8lMmTLh6uqKSqUif/78uLq6vv5wdnamXr16tGvXzpixCmbOoWoVHOvXB52OwIk/pZsmkhFr1xJ/5Qpqe3u8Jyq0RO/Gn/D0jFwQosFU048vCBmcRq2hb8m+/FrvV1xtXLkXcY8Ouzuw7/E+pUMzHY0l1BgmH5+aC4npc1m2ScQEwelf5OM6497oj1UqRyZ6VJOX7I3ceoOo+GQlIvxkkiTx86WfmXFhBgBfFfqKqdWmYqmxVDiyD6jYBxrPko/PzIf9I1OUPN18HkXXledpv/RvLr9qXtv3VfPavjVF89r0KMVL9VatWoUkSXTr1o25c+fi7Oz8+ntWVlbkypWLSpUqGS1QQxFL9Ywr+cULfJs0RYqPJ8v0aTi3aKF0SJ8l6ckT/Fq0REpIwGv8eDJ1aG/6IBKiYEE5eW9TnbFQbYjpYxAE4bXguGB+PPEjl4IuAfBlwS/5oewPWGkyQHNYnRYWlodwX/H76HPs/A4u/QZZy0KPQ28tDUtI1tH4l5P4hcbyRZlszPyihDJxppJWr2X8mfFs990OwHelv6Nb0W5pZ0/PxZWw61V58vK9oNGMdy7bexQay+wD99j1f81rO5TPzsDa+UTz2jTIaFX1tFota9eupW7dumTLlu2zA1WCSJyML3TpMkLmzEGTOTN59u5B4+iodEifRNLredqlK3EXL2JXsSI5flupzC//fSPg70Xglhf6ngGL9NnfQxDSEq1ey8KrC1l+Q16yVsStCLNqzCKbY9p8bUyV65tgS0+wcYHvboCNeC1NlZB7sKiSvPT6m32Q8903nS8+DueLX8/Krfu+KUfNAibuGZhK8dp4hh4fyvFnx9GoNIyrNI5W+VopHVbqXV4NOwYCEpTtBo1ng1peoBUULTev3XhBbl4L0KJkFr4XzWvTNKPtcbKwsKBfv35mXwBCUJbb112x8vFBFxpKyPz5SofzySL+WE/cxYuo7OzwnvSTMklT4E0496t83GiGSJoEwUxYqC0YVHoQC+ssxNnamVtht2i3sx1Hnh5ROjTjK9oGMueHhEg4t0TpaNKeg+PkpKlg0/cmTQBlc7nyTWW5d+aILTeISTDfJXtRiVH0OtCL48+OY62xZm6tuWkzaQIo3QVaLgJUr2agBhEZm8DUvXeoPuMof5x7ik4vUbugB3sGVuOXDqVE0pSBpHq3WoUKFbhy5YoxYhHSCZWVFZ6j5Qo1EWvXkXD3rsIRpV7Ss2cEz5kDgMeQ77FSYoZVkmDPPwUhmkPeOqaPQRCED6qerTqbm22mhHsJYpJjGHR0EDMvzCRZb75vcj+bWvNvz5szCyA+Qtl40pLHp+D+XlBp/i2F/QFDGxQgp5sdAVEJTNljnq+lgbGBdN3blashV3G0cmRZ/WXUzF5T6bA+T8mO0OpXJJUaLq/m2Mz2LDv+kEStnrI5M7GpdyVWfl2OwlnEbGtGk+rEqV+/fgwZMoQFCxZw9uxZrl+//saHIAA4VKmCY4MGoNcT+NOkNFUoQpIkAkaPQYqLw65cOTJ9+aUygVzfBE/PgqUdNJiiTAyCIHyUl70XvzX8ja6FuwKw+vZqvtn3DYGxgQpHZkSFW4F7IUiMgrOLlI4mbdDr4YBcfZay30DmfB99iK2VhultigOw/vxTTj0INWaEqeYX6UfnvZ3xjfLFw86D1Q1XU8qjlNJhfbYkrZ7VcRUYpRqEVlLTkmMsc1zOyi6l+LNPJcr7iCrSGVWq+zip1W/nWiqV6nWZcnNfxif2OJlOckAAvo2bpLlCEREbNhI4fjwqGxtyb9+GVc6cpg8iIQrml4XYYLniUrXvTR+DIAipdvjpYcacGkNMcgzO1s5MqTqF6tmqKx2WcdzeDpu6gJUjfHcd7MSbyQ+6sRn+6i7/vAZeAQf3FD907PabrD77hKwutuwfXB0HawsjBpoy10Ku8e3hb4lKjCKXUy6W1luKt4O30mF9Fp1eYse158w5eB//8HgAujhdYXzyz6glLRRtC61+BY3yP3/BcIzax+nRo0dvffj5+b3+vyD8w9Lbm8z9+gIQNGMmuuhohSP6uOTnzwmeIZdQ9Rj8nTJJE8DRqXLS5JYPKvVXJgZBEFKtTo46bGq2iSJuRYhKjOLbw9/yy+Vf0Oq1SodmeAWbgVcxSIqRSzgL76dNhMMT5OOqg1KVNAEMa1iQbJlseR4Zz/S9yi/ZO/HsBD329yAqMYrimYuzutHqNJ00SZLE4TtBNJl3ksEbr+EfHo+7ozU/tSjC6B9Hom73O6gt4Oar5FeXjpfiCh+U6sQpZ86cH/xIrUWLFuHj44ONjQ1lypTh5MmTKXrc6dOnsbCwoGTJkqkeUzAdt66vCkWEhREyf4HS4XyQJEkEjBmLPi4O21KlyPTVV8oEEngTzr8qCNF4xhv9PQRBMH/ZHLOxutFqviwoL/NdfmM5PQ70IDguWOHIDEythpoj5eNzv0KseS0jMyvnl0LkU3DMAhW/TfXD7a0tXi/ZW/P3E876hhk6whTb4buDgUcGkqBLoGrWqiyrv4xMNpkUi+dznfMLo+2Ss3RfdZG7gTE42lgwtEEBjg+tSedKueTmtYWaQbs1oLaE29tg8zegTVI6dEEBn9TK2NfXlwEDBlC3bl3q1avHwIED8fX1TfV1Nm7cyHfffceoUaO4cuUK1apVo1GjRjx9+vSDj4uKiqJLly7UqSM2y5s7lZUVXmPkNd0R68y7UETUX38Re+YMKmtrvCdPRqVRoHHd64IQeijcAvLUNn0MgiB8NiuNFSMrjGRmjZnYW9pzKegSX+z8grMvziodmmEVaATeJSE59t+GrsKb4sLhxEz5uPYosLL7pMtUyZuZjhVyADDsr+vEJZl+FvP3m78z6tQodJKOprmbMq/2POwsP+3Po7RbL6L4+je5ee2lJxFYW6jpUyMPJ3+sxbe18mJn9Z/leAUbQ4d1oLGCOzvhz67yTKKQoaQ6cdq/fz+FCxfm/PnzFC9enKJFi3Lu3DmKFCnCwYMHU3WtOXPm0L17d3r06EGhQoWYO3cu2bNnZ/HixR98XO/evenYsWOaaLgrgH3lyjg2bCgXipj4k1kWikgODCRo2nQA3AcOxDq3jzKBXN8oCkIIQjrSMFdDNjbdSIFMBQhPCKf3wd4svroYnd689wOnmEoFteQqqpxfBi/T2ayaIZycLe9b9SgCJT6v2NCIRgXJ4mzD0/A4Zu6/Z6AAP04v6Zl1YRazL80GoGvhrkyuOhlLtaXJYjCUx6GxDFh/hSbzTnHsXggWahWdKuTgxI+1GN6oIC52H1jlkb8BdFgPGmu4twc2dobkBNMFLygu1YnT8OHDGTx4MOfOnWPOnDn8/PPPnDt3ju+++45hw4al+DpJSUlcunSJ+vXrv/H1+vXrc+bMmfc+7rfffsPX15dx48alaJzExESio6Pf+BBMz3P4MFR2dsRfvkzU9u1Kh/MGSZIIGDcO/cuX2JQojuvXXZUJJD7y34pLNX4E5wzQSFMQMoCcTjlZ23gtbfK1QUJi0bVF9DnUh9D4dLK0LV89yFoWtPFw6melozEvEY/lZXoA9SbKpdw/g6ONJVNfLdn7/cxjLjwO/8wAPy5Zn8zoU6NZdXsVAEPKDOGHcj+gVn3SoiXFBEUnMHLrDerOOc7Oay8AaF4iC4e+r8HkVsXwdLJJ2YXy1YWOG8HCBh7sh42dRPKUgaT6WX/nzh26d+/+1te7devG7du3U3yd0NBQdDodnp6eb3zd09OTwMB3l3B98OABw4cPZ926dVhYpKyiydSpU3F2dn79kT179hTHKBiOpZcX7q8KRQTPnGVWhSKitm8n9vgJVJaWZFFqiR7AsakQGyIXhPiENfCCIJgvGwsbxlcez5SqU7C1sOXvgL9pt7MdFwMvKh3a51OpoNarvU4XVkB0gLLxmJPDE0GXBLlrGqwXX4387rQrmw1Jgh83Xyc+yXizl3HJcQw8MpCdfjvRqDRMrjqZr4t+bbTxjCEqLplpe+9SY6bcvFarl6hVwJ3dA6sy78tS5Mr8Cc1r89SCjpvk1SEPD8H6DpAUZ/jgBbOT6sTJ3d2dq1evvvX1q1ev4uHhkeoAVCrVG5//U9b8v3Q6HR07dmTChAnkz58/xdcfMWIEUVFRrz/8/f1THaNgGK5dumCVO7dcKGKeeVRgSg4OJmjKVAAy9++Pdd68ygQSeOPfu5KNZ4qCEIKQTjXL04z1TdaTxzkPIfEhdD/QneU3lqOX9EqH9nny1IbsFUGXCKfmKB2NeXh+CW7+Baig3k9ygmkgo5oUxtPJmkehscw5aJwle5EJkfQ80JNTz09ho7FhXu15NM/T3ChjGUNckpaFRx9SdcYRlhz3JSFZT5mcmdjYqyK/fVOeIlmcP2+A3DWg02awtAe/o7C+PSTFGiZ4wWylOnHq2bMnvXr1Yvr06Zw8eZJTp04xbdo0evfuTa9evVJ8ncyZM6PRaN6aXQoODn5rFgogJiaGixcv0r9/fywsLLCwsGDixIlcu3YNCwsLjhw58s5xrK2tcXJyeuNDUMYbhSL++IOEO3cUjUeSJALHT0AfHY1NkSK4de+mVCCw+5+CEC3lO1mCIKRbeVzy8EeTP2iWuxl6Sc8vl3+h/+H+RCZEAqDT67gQeIE9fnu4EHghbeyH+v9Zp0u/Q9QzRcNRnCTBgTHycYkO4F3coJd3trVkautiAKw49YjLTyM+63r/fc49i3lGl31duB56HWdrZ5Y3WJ5m+pElafWsOfuYGjOPMXP/PWIStBT0cmRF17Js7lOJCrndDDdYrirQeQtYOcCjE7CuHSS+NNz1BbOT6ga4kiQxd+5cZs+ezYsX8hrRLFmyMHToUAYOHPjO2aL3qVChAmXKlGHRon+7jhcuXJgWLVowderUN87V6/VvLQVctGgRR44cYfPmzfj4+GBv//HpVtEAV3nPBg8mZu8+bEuVIue6taje0VTZFKJ27uLF0KFgaYnP5s3YFEj5TKZBXV0P2/rId636XwDnrMrEIQiCSUmSxNaHW5lybgqJukS87L1ol78dG+9tJCgu6PV5nnaeDC8/nLo56yoYbQr93hQen4Sy3aBpBt7vdHcPbPhS3gcz4JLR9qx+v+kqWy4/J4+7PbsHVsPGMvVLzQ89OcS089PeeM6pVWr0kh4vey9+rfsruV1yGzJso9DrJXZce8Gcg/d5Gi4vm8vuasuQegVoViILGrXhZvze4n8e1raBxGjIUQk6/QnWjsYbTzCo1OQGqU6c/l9MTAwAjo6f9uTYuHEjnTt3ZsmSJVSqVImlS5eybNkybt26Rc6cORkxYgTPnz9n9erV73z8+PHj2bZt2zuXDr6PSJyUlxwYiG/jJkhxcXhPnYpLq5Ymj0EbGopfk6booqLIPHAA7v36mTwGQC4IsaCsvLep7gSo+p0ycQiCoJh74fcYcnwIT6KfvPP7KuQ3fHNqzjH/5Onxafi9sdzvZsAlyKRQE3El6bSwuBKE3oeqg6HueKMNFRmXRL2fTxASk0jfmnkY1rBgqh5/6Mkhvj/2PRLvfis4ttJYvsj/hSFCNRpJkjh6L5gZ++5xN1B+X5rZwZqBdfLSoVwOuQ+TKTy7BGtaQWIUZCsPX20Gm89cDiiYRGpyg09+NgUHB3P16lWuXbtGSEjIJ12jffv2zJ07l4kTJ1KyZElOnDjBnj17XjfSDQgI+GhPJyHtsfTywv1bOVEJnjlTkUIRgRN/QhcVhXWhQmTu2dPk4792dIqcNGXODxUVSt4EQVBUAdcCrGu0DmuN9Tu//8+b2unnp5v/sr1cVeRCCPpkODlL6WiUcXmVnDTZucmJkxG52FkxuWVRAH497ss1/8gUP1an1zHt/LT3Jk0AS68tNevn3PlH4Xyx5Czdfn+zee2JH2vS5Z/mtaaSrQx03Q42LvDsvJxExUeabnzBJFI94xQdHc23337L+vXr0evlzawajYb27duzcOFCnJ3NO7sWM07mQUpKwq9Va5J8fcnUqdPrvU+mEL1vH8+/GwwWFvj8uQmbQoVMNvYbAq7D0hry3qYu2+U3G4IgZEgXAi/Qbf/H91mubLCScl7lTBDRZ3h6DlbWB5UGBlwEV/Nf5mUwiTEwr5R8Q6zRDKjQ2yTDDlx/hR3XXpDf04GdA6pibfHxJXtp+Tl3+0U0M/ff5eg9+ca9tYWar6vkom+NPB/uw2QKAddhdQuID5ebQ3feCnauysYkfJBRZ5x69OjBuXPn2L17N5GRkURFRbFr1y4uXrxITyXv3AtpyhuFItavN1mhCG14OIETJgKQuVdP5ZImvR72DJWTpiKtRNIkCBlcSFzKVm6k9DxF5agAeeuCpIPjM5WOxrROz5OTJtfcUOYbkw07vnkRMjtYcT/oJQuOPEzRY4LjUtas2Jyec0/CYhm04QqN553k6L0QNGoVHSvk4PjQWoxoVEj5pAnkQiBdd8ozjgFXYXVziDN+vy3BNFKdOO3evZuVK1fSoEEDnJyccHR0pEGDBixbtozdu3cbI0YhnbKvWBGnxo1Arydw4k9IeuOX4w2aNAldRATW+fKRuU8fo4/3Xtc3gP/fckGI+pOVi0MQBLPgbueeovOcrc17VcdrNV9V2Lu+AUJT9kY+zYsOgLML5OO6403aVsLV3oqJLeQle4uO+XLzedQHz/eP8eePO3+k6NopfW4aU3B0AqO33aDO7ONsvyoXJmv2qnntlFbF8HJOYfNaU/EqCl13gb273G5kVTOITScNrzO4VCdObm5u71yO5+zsTKZMmQwSlJBxeAwbhsrOjvgrV4jatt2oY0UfPEj0nr2g0eA9ZQoqK4XuTMVH/lumtuYwUUVPEARKe5TG087zdSGI95n892ROPT9loqg+Q7YykL+hPKt+fLrS0ZjG0cmQHAfZK0Ah0/c7alzMmybFvNHpJYZuvk6S9u2bkYm6RBZfW0yr7a24Hnr9g9dTocLLzovSHqWNFfJHRcUlM33fXarPPMrav+XmtTXyu7NrQFXmf1kKn09pXmsqnoXh693g4AlBN+WKky9TNssnmK9UJ06jR4/m+++/JyDg387ggYGBDB06lDFjxhg0OCH9s/T0xP3bbwEInjULXdSH75J9Km1ExOslem7du2NbrKhRxkmRo5MhLhQyF4AKfZWLQxAEs6FRaxhefjjAW8nTP587WTnh/9Kfvof6MvjoYAJjA9+6jlmpOUL+/40/IcQ4TVrNRtBtuLpOPjZws9vUmNCiCK72VtwJiGbxMd83vnfq+SlabW/FoquLSNQlUsG7AsPLD0f16r//98/nw8oPQ6NOfYnzzxWfpGPRsYdUm3GExcfk5rWlc7iwoVdFVnUrT9GsaWTm1b2AnDw5ekPIHTl5ign6+OMEs5Xq4hClSpXi4cOHJCYmkiNHDgCePn2KtbU1+fLle+Pcy5cvGy5SAxHFIcyPlJyMX6tWJD30JVPHjniNNXwC/vzHH4nesROrPHnw2fIXaut3V68yujcKQuyQO48LgiC88q6eOl52XgwrP4yK3hVZdG0Rf9z5A52kw9bClt7Fe9OlcBcsNZYKRv0BGzrB3V1QpDV88ZvS0RjP2rbw8KA809R+jaKh7Lj2goHrr2ChVrFzQFVcHGOZcWEGh54eAsDD1oOh5YbSIFcDVCrVB59zpi5/n6zTs+GCP/MPPyA4JhGAAp6ODG1QgDqFPFLVK9SshPnKy/Win4NbPnkPlJO30lEJrxi1j9OECRNSfO64ceNSc2mTEImTeYr9+xxPv/4a1Gp8Nv+JTeHCBrt2zJGjPOvXD9Rqcq3/A9sSJQx27VTR6+G3huB/Lv2/iRAE4ZPp9DouB18mJC4Edzt3SnuUfuOu//2I+0z+ezKXg+Wbk7mdczOqwijKe5dXKuT3C7wJS6oAKuh7GjyLKB2R4fkdk6uoqS3g2/PglkfRcCRJoveaSxy4/ZzsPhdIsN9Pgi4BjUpDp0Kd6FeyH/aWby5x+9hzztj0eomd1+XmtU/C5Oa12TLZMqR+fpqXyGrc5rWmEv5ITp6i/OXiIV13iaX6ZsJkDXDTIpE4ma/n3w8hes8ebEuWJOcf61CpP7//gi4qCr+mzdCGhODarRuePw41QKSf6Mo62N5PLggx4CI4ZVEuFkEQ0jRJktjpt5PZF2cTniBX7Grk04ihZYeaxWb+N2zqCre3mcVsjMHp9fIqgsDrUL43NJ6hdEQA7Pc9yQ9HxoOVvKemtEdpRlUcRf5M+ZUN7D/+aV47c/997gTIPR0zO1gxoHY+vixvwua1phLxBFY1hcinkCmXnDy5ZFc6qgzPJInTpUuXuHPnDiqVisKFC1OqVKlPCtbUROJkvpKDgvBr1Bh9XBzekyfj0qb1Z1/zxYiRRG3dilWuXPhs24raRqHKO/ERML+svLep3k9QZaAycQiCkK5EJ0Uz//J8Nt3fhF7SY29pz7clv+XLgl9iobZQOjxZ8B1YVAmQoPdJuVxzenFtI2ztBdZOMPAq2LspGk5wXDCzLsxi7+O9AOi1DuhCmrD964EU8DKv9zwXHoczY99dLjyOAMDR2oLeNXLzTRUf7K3N5LlrDJH+cvIU8RhccsjJU6acSkeVoRk1cQoODqZDhw4cO3YMFxcXJEkiKiqKWrVqsWHDBtzdzexO13+IxMm8ha38jeAZM9BkykSefXvRfEZD5ZcnTuDfqzeoVORctxa70spVBmL3D3BhGbgXhD6nwFz3IwiCkCbdDrvNpL8ncSP0BgD5M+VndMXRlPIwk5uam7vDzc1QoDF8uV7paAwjOQEWlJWXXtUZB9W+VywUrV7LH3f+YNG1RcQmx6JWqWmXvx3371bl+N2XlMjuwl99KmGhUX4G505ANDP33+PIXXk2zNpCzdeVc9GnRh4y2ZtBHyZTiHouJ0/hfuCcHbruyFiNos2MURvgDhgwgOjoaG7dukV4eDgRERHcvHmT6OhoBg4Ud9GFz+Pa+Sus8uZBFxFByC+/fPJ1dDExBIyV99i5dumsbNIUcA0urpCPG88USZMgCAZX2K0waxuvZVylcThbO3M/4j5d9nZh1KlRhMWHKR0e1BgGKjXc2wPPza9w1Cc5t0ROmpyyQUXlKqReDrpMu13tmHlxJrHJsRTPXJz1TdYzquIopreqgKONBdf8I1lx6pFiMcKbzWuP3A1Go1bxZflXzWsbF8o4SRPIe5u+3iMXiojyl6vthfl+/HGC4lI94+Ts7MyhQ4coV67cG18/f/489evXJzIy0pDxGZyYcTJ/sefO87RrV1CpyLX5T2yLpH4zccCYsUT++SeWOXKQe/s21La2Rog0BfR6WNkAnp2Hom2g7Upl4hAEIcOISIjgl8u/8NeDvwBwtHJkYKmBfJH/C0VKS7+2pbfcEDdffej0p3JxGEJcOPxSEhKjoOUSKPmlyUMIiw9jzqU57PDdAcjNkQeXHkyrfK1Qq/69L77poj8/br6OlYWaPQOrkdfDwaRxBkcnMO/IAzac90erl99yNinuzZB6+cntbtpYzE5MkFwwIvSeXLK8607InO/jjxMMyqgzTnq9HkvLt++YW1paote/3WxNEFLLvkJ5nJo0AUkiaOJPSKl8Xr08fZrIP+UXZe9JPymXNAFc+0NOmqwcoP4k5eIQBCHDyGSTifGVx7O28VoKuRYiJimGyecm03FPR26E3FAusBo/gkoDDw6A/wXl4jCE4zPkpMmrGBRvb9KhdXodG+5uoNm2Zq+Tpjb52rCr5S7a5G/zRtIE8EWZbFTP706SVs+Pm6+h05umJlhUfDIz/tO8tvqr5rULO5YWSROAo6fc58mjMMQEwO9N0n/PszQu1YlT7dq1GTRoEC9evHj9tefPnzN48GDq1Klj0OCEjMvjxx9R29kRf+0aUVu3pvhxupexBLxqxJypY0fsyytYnjc+Ag6OlY9rDhdV9ARBMKkS7iVY32Q9I8qPwNHSkdtht+m0pxMTzk4gMiHS9AG55fl3ZubYFNOPbyjhfnBhuXxc7ycwQAXYlLoRcoOOezoy+dxkYpJiKORaiHWN1zG+8nhcbFze+RiVSsW01sVwsLbg8tNIfjtt3CV78Uk6Fh/zpdr0Iyx61by2VA4X1vesyOq01LzWVBzc5Zkmz6LwMkhOnoJuKx2V8B6p/te+YMECYmJiyJUrF3ny5CFv3rz4+PgQExPD/PnzjRGjkAFZenqQecAAAIJnzUaXwiWgwbNnoX0RgGXWrHgMUW6jLgBHJkFcmFwQokIfZWMRBCFD0qg1dCzUkR2tdtAsdzMkJDbf30yzbc3Y8mALesnEK0WqD5X7HfkegSdnTTu2oRyaAPpkyFsX8tQyyZCRCZFMODuBTns6cTvsNo6WjoysMJL1TdZT3P3jVQqzuNgyqkkhAGYduMfj0FiDx5is07P27yfUmHmU6fvuEp2gJb+nA0s7l2FL38pUyqNsxUGzZp9ZTp68ikNsiFw4IvCm0lEJ7/DJ5cgPHjzI3bt3kSSJwoULU7euabtLfyqxxyntkJKTedS6NYkPHuLyZQe8P9JQ+XUTXSDH779hX7GiCaJ8jxdXYVktkPRyqVGfasrFIgiC8MrFwItMPjeZh5EPAXlWanTF0RR0LWi6IHYOgku/g091+c1iWuJ/AVbUlQtd9Dll9Ia+eknP1gdbmXt5LpGJkQA0z9OcwWUGk9k2c6quJUkSnVec59TDUMr7uLKhZ0XUBmgs+77mtd/Xy0+Lkumkea2pxEfAmlbw4grYZoIu28G7hNJRpXtGK0eu1WqxsbHh6tWrFC1a9LMDVYJInNKW2PPnedrlVaGIP//Etui7X6T0cXH4tWhJsr8/Lu3b4z1hvGkDfSMYPaysD88uQNG20HaFcrEIgiD8R7I+WS5dfXURcdo41Co1HQp0oH+p/jhaORo/gEh/mFdKnrVJSzeWJAlWNgT/v6HUV9BioVGHuxN2h0nnJnE95DoAeV3yMrriaMp4lvnka/qHx9Fg7gniknRMaF6ErpVzffK1JEni2L0QZuy/97p5rZu9FQNq5+XLCjmwtlCwEElaFh8Ja1vD80tg4wJdtkEWM2krkE4ZrTiEhYUFOXPmRKfTfVaAgpBS9uXL49S0KUgSgT9NfG+hiOCf55Ls74+FtzceQ38wcZT/cXWdnDSJghCCIJghS7UlXYt0ZUfLHTTM1RC9pOePu3/QbGszdvru5BMXoqScS3Yo01U+PjpFTkjSgru75KTJwhZqjTLaMNFJ0Uw5N4UOuztwPeQ6dhZ2/FD2BzY12/RZSRNAdlc7RjSSZxen7b3L01czRKl18XE47X/9m29+v8CdgGgcrS0YUi8/J36sxddVfETS9DlsXaDzVshWHhIiYVULeHZJ6aiEV1K9x2n06NGMGDGC8PBwY8QjCG/xGDoUtb09CdeuE7Vly1vfj7t4kYg1awDwnjgRjYOClXriwuHQqyWFNUeAk7dysQiCIHyAp70nM2vMZGm9peRyykVYQhgjT42k2/5uPIx4aNzBq34PGmt4egb8jhl3LEPQJcPBV7/bK/c3SrEfSZLY6buT5lubs/7uevSSnoa5GrKj5Q66FumKpdowPQA7VchJxdyuxCfrGPbXdfSpqLJ3JyCa7r9foO2Ss5x/HI6VhZpe1XNz4sdaDKiTD3trC4PEmOHZOEPnLZCjkly9cU1L8D+vdFQCn7DHqVSpUjx8+JDk5GRy5syJvb39G9+/fNm8G9uJpXppU9jvvxM8bToaFxfy7NuLxsUFAH18PH4tW5L85CnObVqTZfJkZQPd9b3c7Na9EPQ5KZrdCoKQJiTpklh9ezW/XvuVBF0CFioLOhXqRN+SfbG3tP/4BT7F3mFyE9ls5aH7AVCZ8V6Y88tgzw9g7w4Dr4C1YZc0Pox4yORzk7kYdBGAXE65GFlhJJWyVDLoOP94EhZLw7kniU/WMallUb6qmPOD5z8Ni2POwXtsv/YCSQKNWkW7stkYWCcf3s4KtvxI7xJfwh/t4ckpeRVLp82Q0zjPiYzMaHucAMaPH4/qA7/cxn1kA7/SROKUNsmFItqQ+OABzu2+wLlJU7QhIcQcPEjM/v1YeHqSe+cONEr+nb64AktrAZLclyFXVeViEQRB+AQvXr5g+vnpHPE/AoCHnQdDyw2lQc4GH3zt/yQxQfBLCdDGQ6e/IJ+ZFplKiJb3ZMWFQpPZUK6HwS4dmxzL4quLWXdnHVpJi43Ght4letOlcBesNFYGG+ddfjv9iAk7b2NvpWHPoGq8iEwgOCYBD0cbyvu4olGrCI5JYP7hh6w///Tf5rXFvPm+fn7yiD5MppEUC+s7wKMTYGkPnTaJ9xcGZtTEKa0TiVPaFXfhAk86d3nn99x698Zj8HemDej/6fWwoh48vwjFvoA2y5WLRRAE4TOdeHaCqeem8uzlMwAqeVdiRIUR+Dj7GHag/aPg7ALIUhp6HjHPWafDE+HkbHDLB/3OGmQlgSRJ7H+yn5kXZhIcFwxA7ey1GVZ+GFkcTNPzT6+XaL/0LBceR2BloSZJ++8eYk8na0rlcOH4vVDik+V97dXyZebHBgUplk30YTK5pDjY0BH8jsp77DpuhNw1lI4q3TBKcYi4uDi+/fZbsmbNioeHBx07diQ0NPSzgxWElNJGRLz3e2FLlxJ94IAJo/mPq2vlpMnKUW6IKAiCkIZVz1adrS220rdEX6zUVpwNOEvrHa2Zd3ke8dp4ww1U5TuwtIMXl+H+fsNd11CinsPZV9Xz6k0wSNL0KOoRvQ/2ZujxoQTHBZPNIRsL6yzkl9q/mCxpAlCrVTQtLo/3/0kTQFB0IvtuBhGfrKNkdhf+6FmBNd0riKRJKVZ28OUGuXeYNh7+aCf3QhNMLsWJ07hx4/j9999p0qQJHTp04ODBg/Tt29eYsQnCa5JOR9CUqR88J2jKVCQlKj7Ghf+7abiWKAghCEL6YGNhQ7+S/djWYhtVs1ZFq9ey7MYyWm5ryZGnRwxTfc/BHcr3ko+PTja/CntHJ4M2AXJUhgKNP+tS8dp45l2eR+sdrTkbcBYrtRV9S/Rla4utVM9W3UABp5xOL7HkuO8Hz8lkZ8nmPpWonCd1PaMEI7C0gQ5/QL4G8nPyjw7w4JDSUWU4KU6ctmzZwooVK1i6dCnz5s1j9+7dbNu2TZQmF0wi7uIltIGB7z9BktAGBhJ3UYGSnUd+gvhw8Cj87xsAQRCEdCK7U3YW1VnE3Fpz8bb35kXsCwYdHUT/I/3xj/H//AEqD5Q3vgdel0t+m4vAG3D1D/m4/qRPXkYoSRJHnh6h5baWLLuxDK1eS9WsVdnWYhv9SvbDxsLGgEGn3PlH4QREJXzwnIi4ZC48fv9qD8HELKyh/Roo0AR0ibDhS/OcqU3HUpw4+fv7U63av03qypcvj4WFBS9evDBKYILw/7QhIQY9z2BeXIGLv8nHjWeJKnqCIKRLKpWKOjnqsK3FNnoU64GF2oITz07QansrFl9bTKIu8dMvbu8GFfrIx0enyntGzcHBsYAERVpDtk/rn+Qf40//I/0ZdHQQL2Jf4G3vzdxac1lUZxHZnbIbNt5UCo75cNKU2vMEE7Gwhi9+h0LNQJcEGzrB3T1KR5VhpDhx0ul0WFm9WeHFwsICrVZr8KAE4b8s3N0Nep5B6PWwewggQbF2kKuK6cYWBEFQgJ2lHYNKD+Kv5n9RwbsCibpEFl1dRKvtrTj1/NSnX7jSt2DtBMG34M52wwX8qR4elveQqC2hzthUPzxRl8jia4tptb0VJ56dwEJtQY9iPdjWYht1ctQxfIXCT+DhmLKZrpSeJ5iQhRW0/Q2KtAJ9MmzqDHd2Kh1VhpDiTmWSJPH1119jbW39+msJCQn06dPnjV5OW97RoFQQPpdd2TJYeHmhDQp69xp4lQoLT0/syn5eV/VUubIGnl+SC0LUFwUhBEHIOHI752ZZvWXsf7yfGRdm4B/jT99Dfamboy4/lvsRb4dU7vW0c5WTp2NT4dg0KNQc1BrjBP8xet2r2Sbk5deuqaskeOr5Kaacm/J6GWMF7wqMrDCS3M65DR3pZynv44q3sw2BUQm8a2eZCvBylkuTC2ZIYwmtl4NKAzc3w6au0HaFnEwJRpPiGaeuXbvi4eGBs7Pz64+vvvqKLFmyvPE1QTAGlUaD58gRrz75z526V597jhyBSmOiF9q4cDg0Xj6uNRIcvUwzriAIgplQqVQ09GnIjpY76Fy4MxqVhkNPD9FiewtW3FhBsi45dRes2BdsnCHkLtzaapygU+LaBgi6KcdS/YcUPyzgZQCDjw6m76G++Mf442HrwczqM1lWb5nZJU0gN7Ed16wwICdJ/++fz8c1K4xGrfzsmPAeGgtovRSKdwBJB5u7w43NSkeVrok+TkKaEn3gAEFTpr5RKMLCywvPkSNwql/fdIHsGgwXV4JHEeh9Qv7lJQiCkIHdj7jP5L8nczn4MiDPSo2qMIry3uVTfpETM+HIJHDLC/3Omf53a1IczC8DMS/k1hJVBn70Icm6ZFbdXsXS60uJ18ajUWnoVKgT/Ur2w97S/qOPV9q+mwFM2Hn7jUIR3s42jGtWmIZFRZXYNEGvgx0D4Oo6UKmh5RIosja7SAAALeFJREFU0V7pqNIM0QD3A0TilPZJOp1cZS8kBAt3d+zKljHdTBPA88uwrDYgwdd7xN4mQRCEVyRJYqffTmZfnE14QjgAjXwaMbTsUNztUrAHNTEG5haD+Aho9SuU6GDkiP/jxCy5UqpzDuh/QS4B/QHnAs4x+dxkHkU9AqC0R2lGVRxF/kz5TRGtwej0EucfhRMck4CHo7w8T8w0pTF6PewaBJdXAypouQhKdlQ6qjRBJE4fIBIn4bPo9bC8jtyssXh7eYpcEARBeEN0UjTzL89n0/1N6CU99pb2fFvyW74s+CUW6o/MIp36WV4KnclHTl5MVa30ZQjMKwVJMfLekeJfvPfU4LhgZl2Yxd7HewFwtXFlSNkhNMvdzCwKPwgZlF4Pe4bIK2JQQfN5ULqL0lGZvdTkBine4yQIAnBltZw0WTvJyzgEQRCEtzhZOTGq4ijWN1lPsczFiE2OZcaFGbTf1Z4rwVc+/OByPcEuM0Q8kvcbmcrx6XLS5F0SirZ55ylavZbVt1bTfFtz9j7ei1qlpkOBDuxstZPmeZqLpElQlloNTea86ikpycv3Lq5UOqp0RSROgpBSbxWE8FQ0HEEQBHNX2K0waxuvZVylcThbO3M/4j5d9nZh1KlRhMWHvftB1g5Q9Tv5+MQM0CYZP9DQh3DpVU+++pPkN6D/cTnoMu12tWPmxZnEJsdSPHNx1jdZz6iKo3CyEitYBDOhUkGjGVCxn/z5rsFwfpmyMaUjInEShJQ6PFFed+9RRL4jKgiCIHyUWqWmbf627Gy5kzb55JmcHb47aLatGRvubkCn1739oLLdwcETIp/KG96N7dA40Gshf0PwqfbGt8Liwxh1ahRd93XlQcQDnK2dGV9pPGsar6GwW2HjxyYIqaVSQYMpUHmA/PmeH+DvxcrGlE6IxEkQUuL5Jbj0u3zcZJaooicIgpBKmWwyMb7yeNY2Xksh10LEJMUw+dxkOu7pyI2QG2+ebGUHVb+Xj0/MAm2i8QJ7chbu7pKrkdWd8PrLOr2ODXc30GxbM3b47gCgTb42cgKYvw1qlXgLJZgxlUreUlB1sPz5vuFwZr6yMaUD4l+9IHyMXge7hwCS3CshZ2WlIxIEQUizSriXYH2T9YwoPwJHS0duh92m055OTDg7gciEyH9PLPM1OHpD9LNXlcKMQJLg4Bj5uHQX8CgIwI2QG3Tc05HJ5yYTkxRDIddCrG28lvGVx5PJJpNxYhEEQ1OpoM44qD5U/vzAaLn4ivDJROIkCB9zeTW8uPKqIMREpaMRBEFI8zRqDR0LdWRHqx00y90MCYnN9zfTbFsztjzYgl7Sy6XAqw2RH3ByNiQnfPiin+L2Nnh2ASztoeZIIhMimXB2Ap32dOJ22G0cLR0ZUX4E65usp4R7CcOPLwjGplJB7dFQc6T8+aHxcr804ZOIxEkQPiQuHA6/WrpRa5QoCCEIgmBAmW0zM6XaFH5r8Bt5XfISmRjJuDPj6LK3C3fD78qzQE7ZICbg3+XShqJNgkPy73d95QFsCTxNs23N2Hx/MxISzXI3Y0erHXQs1BGN2oS9AgXBGGoOkxMokJtMH5umbDxplOjjJAgfsnOQ/GLtWRR6HRd7mwRBEIwkWZ/MH3f+YNHVRcRp416X+u5PJhz3DgN7Dxh0Td7/ZAh/L4Z9w7nr7MWkfKW5FnYTgLwueRlVYRRlvcoaZhxBMCf/9EkDeQlfrVHyrFQGJhrgfoBInIQUe3ZJbnaLBN/sFXubBEEQTCAoNohZF2ex7/E+ANxs3BgSFkbT4Keo6k/6t1LY54iPJGZ+SRbYwAZnJ/RI2FnY0a9kPzoW6oil2kRNdwVBCWcWwIFR8nHVwfI+qAycPIkGuILwufQ6ufs2EpT4UiRNgiAIJuJp78nMGjNZWm8puZxyEZYQxkh76OblwcOzv0Diy8+6viRJ7DzwHc3c7PjD2RE9Eg1zNWRHyx10LdJVJE1C+le5PzScLh+f+lkukJKx5lE+mUicBOFdLq8SBSEEQRAUVClLJf5q/heDSg/CRmPDRVsbvnCzYdbensQmx37SNR9GPKTb7k6MjLxEmIWGXDbuLK23lJk1ZuJpL/awChlIxT7QeJZ8fGY+7B8pkqcUEEv1BOG/YsNgfmlIiJS7b1forXREgiAIGdqLly+YfmgAR6LuA+Bh687Q8j/SIGcDVK+WGOn0Oi4HXyYkLgR3O3dKe5R+XdQhNjmWxVcXs+7OOrSSFhu9nt4qV7p8dQgrC2vF/lyCoLiLK2HXq15P5XvJ73sy2LI9scfpA0TiJHzUjoHyjJMoCCEIgmA+dFpOLC3HVMt4nlnKy+kqeVdiRIUR+Eb6Mu38NILigl6f7mnnybByw9ChY+aFmQTHBQNQOzaOYeERZOl2GLKUUuSPIghm5fJq+b0PEpTtBo1ngzrjLEoTidMHiMRJ+KBnF2F5XeSCEPsgZyWlIxIEQRD+cWMzCVt6sNLNnRXOTiTpk1Cr1HLfp4/I5pCNES+TqP7oIhT7AtosN0HAgpBGXP0DtvUDJLkNQNNfMkzyJIpDCMKn0Otg9z8FITqKpEkQBMHcFGmFTeYC9AsNZptXQ6pkqZKipKl38d5sLdxfTpo0VlB7jAmCFYQ0pGRHaPUrqNSvZqD6y++LhDeIxEkQ/nHpdwi4CtbOUG+C0tEIgiAI/6XWQM3hAGS/uJpuedum6GEVPMpic+SnV5/0hkw5jRWhIKRdJdpD62Wg0sDVdfIMlEie3iASJ0EAuSDE4VfV82qPBgcPZeMRBEEQ3q1QC/AoAonRhN7cmKKHhNzdBiF3wMYFqg0xaniCkKYVawttV4DaAq5vgC29QKdVOiqzIRInQQA4PF6uoudZTN4YKQiCIJgntRpqjQDA/d6BFD3E/eY2+aDGj2CbyUiBCUI6UaQVfPG7nDzd3Ax/dQddstJRmQWROAmC/wV5PS9Ak1miip4gCIK5K9gUvIpT+mUknmpbVLy7fLIKFV4aO0pHBIBLTijXw8SBCkIaVagZtFsDaku4vQ02fwPaJKWjUpxInISMTa+DPa+WbZTsBDkqKhuPIAiC8HEqFdQahQYYHhwESG8lT/LnEsOCgtAA1B0HomeTIKRcwcbQYZ1cUOXOTvizK2gTlY5KUSJxEjK2S79BwDW5IERdURBCEAQhzcjfALKUpm5MJHNcyuJh9+beVE87T+Y4FKNuTARkLQNFWisUqCCkYfkbQIf1oLGGe3tgY2dITlA6KsWIPk5CxhUbCvPLyHubGs+C8j2VjkgQBEFIjQeHYF0bsLBBN/Ayl+NeEBIXgrudO6XV9mgWVwVJB9/shZyVlY5WENIu36OwvgNoEyBvXWi/DixtlI7KIEQfJ0FIiUPj5aTJSxSEEARBSJPy1oFs5UGbgOb0PMp5laNx7saU8yqH5tBEOWkq0EQkTYLwufLUgo6bwNIOHh6Sk6ikOKWjMjmROAkZk/8FuLJGPm48W+4NIgiCIKQtKhXUGikfX1gJN7fCjc1wdhHc3yv3o/lfe/ceV1Wd73/8jSgX5SYoKJMSZhqIpsD8TBwt856VlhNmXsexk3PoolSTTd6yki6naU41WjpeumlUWnEarRjNK44piXqU4yXxkgMiaCBqqPD9/bFlj5uLyxsshdfz8VgP9/7u71rrs/bePtxvv2t9F/flA66OVrdLwz6TGjSS9n4nLRoinT5hd1U1iuCEuqe0RPp7ouNxx+FSy8721gMAuHyt7pCatJVKT0ufjXZMnfzNs+e9drONxQG1zI1dpRFLJA8fKWu19FG8VFxkd1U1huCEumfTPClnq+TlL/WaZnc1AIArkfk/Ut7Oyl/7cYW0I6Vm6wFqu5a3SSM+lzz9pP1rpY9+KxUft7uqGkFwQt1yIk9a8YLj8Z2TJZ+m9tYDALh8pSXS189cuM/XEx39AFw9Lf6fNOILx6zEB9ZLH9wv/VJgd1XVjuCEuuUfUx1/sZt1YEIIALje7U+TCv91gQ5GKjzk6Afg6rohRhr1peQVIP30vfTBfdKpn+2uqloRnFB3HPxe2vyh4/EAJoQAgOte0eGr2w/ApQntJI36H8k7UDqULr0/UDp51O6qqg3BCXXD+RNCdBruGGIGAFzffEKubj8Al655B0d4ahgkZWfU6vBEcELdsGmelLPt3IQQTE0LALVCWJzkFyrJrYoObpLfr7iPE1DdmkVJo76SGjV1TMD13j2O68prGYITar+iI/+eEKLnFKlRE3vrAQBcHfXcpX6vnHtSPjyde97vZU7NBmpCSKQ0+u+OEd7D/ystuFsqyrW7qquK4ITa7x/THBNCNL9Vivmd3dUAAK6myHul+Pclv+au7X6hjvbIe+2pC6iLmrZ1hCff5tKRTEd4Ol57rjF0M8YYu4uoSYWFhfL391dBQYH8/PzsLgfV7cAGaV4fx+Pf/0Nq8Wt76wEAVI/SEsfseUWHHf/jHRbHSBNgl/wfHafrFR6Sgm52XANV/j83rhGXkg0YcULtVVoiLX3S8bjTCEITANRm9dyl8G5S+986/iQ0AfYJuskx8uTfQsrfLS24Syo4ZHdVV4zgZKfSEilrjbTtM8ef3KDv6nJOCBEg9ZpmdzUAAAB1R2C4IzwFtJSO7nWEp58PXte/f+vbXUCdtSPFcbfz82/c5xfquMiV87GvXNERaXnZhBCTmRACAACgpjUOk0Yvld67Wzq2T5p9h2M0+Px7q11Hv38ZcbLDjhTpk5EV73ZemO1o35FiT121yT+mSsVMCAEAAGCrgBaO8OQTIp3Mq3hD6uvo9y/BqaaVljhGmlTZnBzn2r6eeF0NW15zDvxTyvjI8XjAnznPHQAAwE6+zVT1/daun9+/BKeatj+t4kiTC+OYgWT3tzVWUq1Sclb6+1OOx9EjpRti7a0HAACgrtufJhXlXKDDud+/+9NqrKTLwTVONa388GRVFj3ouPty0M1Sk9ZSUOtzj2+WGt8ouTeo1jKvW5vmSYfPTQjRc5rd1QAAAOBif/9ebD+bEJxqmk/Ixfc9ccSxHCiXvt3cHeGpyc2OQFX2Z9DNkk+w5FbVUGgtV5QrrXjR8bjnFKlRkL31AAAA4OJ//17K72QbEJxqWlicY/aQwmxVfp2Tm+P1P6RJx7KkvD2O+e/z90h5ux03FDtzQjr6o2Mpz9PvXIhq7RqsAm+SPBpW99HZK7VsQoiOUsxou6sBAACAdPG/f8PiarqyS0Jwqmn13B1TLn4yUo6L5M7/8pwbKer3suQdIHl3kkI7ua5vjOMaqfxzgSpvz78f/3xAKi6U/vWDYynP74Zzp/2VBapzj/1bSPWu88vd9q+XtiyU5MaEEAAAANeSi/39e43/fnMzxlQW+2qtwsJC+fv7q6CgQH5+fvYVUul9nH7l+NJc7jz2Z4sdNxhzjk6V/blbOnWs6vXcPR13eC5/2l+T1pJ348urpSaVnJVm3y4d/l8pepR075t2VwQAAIDyquP37xW6lGxAcLJTacm5WUYOO87pDIurvqR98ui/Q9T5weroXqnkdNXrNWziOjpVFqwah0v1Paqn1ku14V1p2R8dIe/RdK5tAgAAuFbV5O/fi0BwuoBrKjhdC0pLHKf4nT86lb/HcQrg8QtMm+7m7rgbdPnT/prc7PhLUFMTVBTlSm/FOE5RvPsNKXZMzewXAAAA171LyQZc41TX1XOXAsMdy829XV8rLjp3/dSecsHqR+l0kWO06uheafc3rut5+DpO/Wty87lgddO/R6o8Gl15zef/T0XGR47QFNrJcZoeAAAAUA0ITqiap48U2tGxnM8Y6XjOuckpzgWpssc/75dOH5eyMxxLeb6h5U77OxesAlpe3DBtZefGSlLkwGv+gkIAAABcvzhVD1fX2WLp2L5/j06dP+vfyfyq13P3lAJbVbzZb1BrqWGgo8+OlHOzsVQxjWX8+7ZdWAgAAIDrz3V1qt7MmTP12muvKTs7W+3atdNf/vIXdevWrdK+S5Ys0axZs5SRkaHi4mK1a9dO06ZNU9++fWu4alSpvqfUtK1jKe/kUdfRqbJgdXSvVFIsHcl0LOV5BzoC1OH/VeWh6ZyvJ0q3DGDkCQAAAFedrcEpOTlZ48eP18yZM9W1a1e9++676t+/v3bs2KGWLVtW6L969Wr17t1bM2bMUEBAgObPn6977rlHGzZsUKdOnSrZA64pDQMdS4tfu7aXlkgFByu52e8eqfCQdOqo9NP3Fhs3jr7706TwyoM3AAAAcLlsPVWvc+fOio6O1qxZs5xtERERGjRokJKSki5qG+3atdOQIUM0ZcqUi+rPqXrXmdMnHKNUmz+Qvp9t3X/wXKn9b6u/LgAAAFz3LiUb1Kuhmio4ffq00tPT1adPH5f2Pn36KC0t7aK2UVpaquPHjyswMLDKPsXFxSosLHRZcB3xaCQ17yBFXOS1Sz4h1VsPAAAA6iTbglNeXp5KSkoUEuL6QzckJEQ5OTkXtY3XX39dJ06cUHx8fJV9kpKS5O/v71xatGhxRXXDJmFxkl+opKruD+XmuPN0WFxNVgUAAIA6wrbgVMat3I1SjTEV2iqzaNEiTZs2TcnJyQoODq6y37PPPquCggLncvDgwSuuGTao5y71e+Xck/Lfj3PP+73MxBAAAACoFrYFpyZNmsjd3b3C6FJubm6FUajykpOT9fvf/16ffPKJevXqdcG+np6e8vPzc1lwnYq81zHluF9z13a/UKYiBwAAQLWybVY9Dw8PxcTEKDU1Vffdd5+zPTU1VQMHDqxyvUWLFmnMmDFatGiRBgwYUBOl4loSea9jyvH9aVLRYcc1TWFxjDQBAACgWtk6HXliYqJGjBih2NhYdenSRbNnz9aBAwc0btw4SY7T7A4dOqT3339fkiM0jRw5Uv/93/+t2267zTla5e3tLX9/f9uOAzWsnjtTjgMAAKBG2RqchgwZovz8fE2fPl3Z2dmKiorS0qVLFRYWJknKzs7WgQMHnP3fffddnT17VgkJCUpISHC2jxo1SgsWLKjp8gEAAADUEbbex8kO3McJAAAAgHSd3McJAAAAAK4XBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsEBwAgAAAAALBCcAAAAAsGB7cJo5c6bCw8Pl5eWlmJgYrVmz5oL9V61apZiYGHl5ealVq1Z65513aqhSAAAAAHWVrcEpOTlZ48eP13PPPafNmzerW7du6t+/vw4cOFBp/6ysLN11113q1q2bNm/erD/96U96/PHHtXjx4hquHAAAAEBd4maMMXbtvHPnzoqOjtasWbOcbRERERo0aJCSkpIq9H/mmWeUkpKizMxMZ9u4ceO0ZcsWrV+//qL2WVhYKH9/fxUUFMjPz+/KDwIAAADAdelSskH9GqqpgtOnTys9PV0TJ050ae/Tp4/S0tIqXWf9+vXq06ePS1vfvn01d+5cnTlzRg0aNKiwTnFxsYqLi53PCwoKJDneJAAAAAB1V1kmuJixJNuCU15enkpKShQSEuLSHhISopycnErXycnJqbT/2bNnlZeXp+bNm1dYJykpSc8//3yF9hYtWlxB9QAAAABqi+PHj8vf3/+CfWwLTmXc3NxcnhtjKrRZ9a+svcyzzz6rxMRE5/PS0lIdPXpUQUFBF9xPTSksLFSLFi108OBBTh1EteP7hprGdw41ie8bahrfueufMUbHjx9XaGioZV/bglOTJk3k7u5eYXQpNze3wqhSmWbNmlXav379+goKCqp0HU9PT3l6erq0BQQEXH7h1cTPz4+/cKgxfN9Q0/jOoSbxfUNN4zt3fbMaaSpj26x6Hh4eiomJUWpqqkt7amqq4uLiKl2nS5cuFfp/++23io2NrfT6JgAAAAC4GmydjjwxMVF/+9vfNG/ePGVmZmrChAk6cOCAxo0bJ8lxmt3IkSOd/ceNG6f9+/crMTFRmZmZmjdvnubOnaunnnrKrkMAAAAAUAfYeo3TkCFDlJ+fr+nTpys7O1tRUVFaunSpwsLCJEnZ2dku93QKDw/X0qVLNWHCBP31r39VaGio3nzzTQ0ePNiuQ7hinp6emjp1aoXTCYHqwPcNNY3vHGoS3zfUNL5zdYut93ECAAAAgOuBrafqAQAAAMD1gOAEAAAAABYITgAAAABggeAEAAAAABYITjaaOXOmwsPD5eXlpZiYGK1Zs8buklBLJSUl6de//rV8fX0VHBysQYMGaefOnXaXhToiKSlJbm5uGj9+vN2loBY7dOiQhg8frqCgIDVs2FAdO3ZUenq63WWhFjp79qwmTZqk8PBweXt7q1WrVpo+fbpKS0vtLg3VjOBkk+TkZI0fP17PPfecNm/erG7duql///4u068DV8uqVauUkJCgf/7zn0pNTdXZs2fVp08fnThxwu7SUMtt3LhRs2fPVocOHewuBbXYsWPH1LVrVzVo0EDLli3Tjh079PrrrysgIMDu0lALvfLKK3rnnXf09ttvKzMzU6+++qpee+01vfXWW3aXhmrGdOQ26dy5s6KjozVr1ixnW0REhAYNGqSkpCQbK0NdcOTIEQUHB2vVqlXq3r273eWglioqKlJ0dLRmzpypF198UR07dtRf/vIXu8tCLTRx4kStW7eOMzdQI+6++26FhIRo7ty5zrbBgwerYcOG+uCDD2ysDNWNEScbnD59Wunp6erTp49Le58+fZSWlmZTVahLCgoKJEmBgYE2V4LaLCEhQQMGDFCvXr3sLgW1XEpKimJjY/XAAw8oODhYnTp10pw5c+wuC7XUb37zGy1fvly7du2SJG3ZskVr167VXXfdZXNlqG717S6gLsrLy1NJSYlCQkJc2kNCQpSTk2NTVagrjDFKTEzUb37zG0VFRdldDmqpjz/+WD/88IM2btxodymoA/bu3atZs2YpMTFRf/rTn/T999/r8ccfl6enp0aOHGl3eahlnnnmGRUUFOiWW26Ru7u7SkpK9NJLL2no0KF2l4ZqRnCykZubm8tzY0yFNuBqe/TRR7V161atXbvW7lJQSx08eFBPPPGEvv32W3l5edldDuqA0tJSxcbGasaMGZKkTp06afv27Zo1axbBCVddcnKyPvzwQy1cuFDt2rVTRkaGxo8fr9DQUI0aNcru8lCNCE42aNKkidzd3SuMLuXm5lYYhQKupscee0wpKSlavXq1brjhBrvLQS2Vnp6u3NxcxcTEONtKSkq0evVqvf322youLpa7u7uNFaK2ad68uSIjI13aIiIitHjxYpsqQm329NNPa+LEiXrwwQclSe3bt9f+/fuVlJREcKrluMbJBh4eHoqJiVFqaqpLe2pqquLi4myqCrWZMUaPPvqolixZohUrVig8PNzuklCL9ezZU9u2bVNGRoZziY2N1bBhw5SRkUFowlXXtWvXCrdY2LVrl8LCwmyqCLXZyZMnVa+e609od3d3piOvAxhxskliYqJGjBih2NhYdenSRbNnz9aBAwc0btw4u0tDLZSQkKCFCxfqyy+/lK+vr3O009/fX97e3jZXh9rG19e3wvVzjRo1UlBQENfVoVpMmDBBcXFxmjFjhuLj4/X9999r9uzZmj17tt2loRa655579NJLL6lly5Zq166dNm/erD//+c8aM2aM3aWhmjEduY1mzpypV199VdnZ2YqKitIbb7zB1NCoFlVdOzd//nyNHj26ZotBnXTHHXcwHTmq1VdffaVnn31Wu3fvVnh4uBITE/Xwww/bXRZqoePHj2vy5Mn6/PPPlZubq9DQUA0dOlRTpkyRh4eH3eWhGhGcAAAAAMAC1zgBAAAAgAWCEwAAAABYIDgBAAAAgAWCEwAAAABYIDgBAAAAgAWCEwAAAABYIDgBAAAAgAWCEwAAAABYIDgBQA3Zt2+f3NzclJGRYXcp15wvvvhCrVu3lru7u8aPH29bHW5ubvriiy9qbH8LFixQQEBAje3PLitXrpSbm5t+/vlnu0sBgMtGcAKAq8DNze2Cy+jRo6tt3wsWLHDux93dXY0bN1bnzp01ffp0FRQUVNt+L1Xbtm3l4eGhQ4cOVXjtkUce0W9/+1sdPHhQL7zwgkaPHq1BgwZVWy3Tpk1Tx44dq2375ysLDeWXSZMmaciQIdq1a9cVbf9i36vc3Fw98sgjatmypTw9PdWsWTP17dtX69evv6L9X4y4uDhlZ2fL39+/2vcFANWlvt0FAEBtkJ2d7XycnJysKVOmaOfOnc42b29vHTt2rNr27+fnp507d8oYo59//llpaWlKSkrS/PnztW7dOoWGhlbbvi/G2rVr9csvv+iBBx7QggUL9NxzzzlfKyoqUm5urvr27XvV6zx9+rQ8PDyu6jYv186dO+Xn5+d87uPjI29vb3l7e1e5zpkzZ9SgQYOrsv/BgwfrzJkzeu+999SqVSsdPnxYy5cv19GjR6/K9i/Ew8NDzZo1q/b9AEC1MgCAq2r+/PnG39+/QntWVpaRZBYvXmzuuOMO4+3tbTp06GDS0tJc+q1bt85069bNeHl5mRtuuME89thjpqio6JL3d/jwYdOkSRMzbNgwZ9uyZctM165djb+/vwkMDDQDBgwwe/bscb7eo0cPk5CQ4LKdvLw84+HhYZYvX26MMeavf/2rad26tfH09DTBwcFm8ODBlu/J6NGjzcSJE82yZctMq1atTGlpqTHGmO+++85Iclluv/32Cm3fffedMcaYn376ycTHx5uAgAATGBho7r33XpOVleXcz6hRo8zAgQPNjBkzTPPmzU1YWFil71f57c+fP98YY4wkM2fOHDNo0CDj7e1tWrdubb788kuX9bdv32769+9vGjVqZIKDg83w4cPNkSNHqjz2smM8duxYpbWc/9lNnTrV3HrrrWbu3LkmPDzcuLm5mdLSUvPpp5+aqKgo4+XlZQIDA03Pnj1NUVGRmTp1apXv1fmOHTtmJJmVK1dWWacxxvz888/m4YcfNk2bNjW+vr6mR48eJiMjw/l6RkaGueOOO4yPj4/x9fU10dHRZuPGjcYYY/bt22fuvvtuExAQYBo2bGgiIyPN3//+9yrfg88++8xERkYaDw8PExYWZv7rv/7LpZawsDDz0ksvmd/97nfGx8fHtGjRwrz77rsXrB8AqhOn6gFADXvuuef01FNPKSMjQ23atNHQoUN19uxZSdK2bdvUt29f3X///dq6dauSk5O1du1aPfroo5e8n+DgYA0bNkwpKSkqKSmRJJ04cUKJiYnauHGjli9frnr16um+++5TaWmpJGns2LFauHChiouLndv56KOPFBoaqh49emjTpk16/PHHNX36dO3cuVNff/21unfvfsE6jh8/rk8//VTDhw9X7969deLECa1cuVKS4xSuspG5xYsXKzs7WykpKYqPj1e/fv2UnZ2t7OxsxcXF6eTJk+rRo4d8fHy0evVqrV27Vj4+PurXr59Onz7t3N/y5cuVmZmp1NRUffXVVxXqGTJkiJ588km1a9fOuf0hQ4Y4X3/++ecVHx+vrVu36q677tKwYcOcozLZ2dm6/fbb1bFjR23atElff/21Dh8+rPj4+Ev+fKqyZ88effLJJ1q8eLEyMjKUk5OjoUOHasyYMcrMzNTKlSt1//33yxijp556qtL3qjwfHx/5+Pjoiy++cPlsz2eM0YABA5STk6OlS5cqPT1d0dHR6tmzp/P4hw0bphtuuEEbN25Uenq6Jk6c6BwRS0hIUHFxsVavXq1t27bplVdekY+PT6X7Sk9PV3x8vB588EFt27ZN06ZN0+TJk7VgwQKXfq+//rpiY2O1efNm/ed//qf+8Ic/6P/+7/+u4N0FgCtgd3IDgNrGasTpb3/7m7Nt+/btRpLJzMw0xhgzYsQI8x//8R8u661Zs8bUq1fPnDp16pL2Z4wxs2bNMpLM4cOHK309NzfXSDLbtm0zxhjzyy+/mMDAQJOcnOzs07FjRzNt2jRjjDGLFy82fn5+prCwsPKDr8Ts2bNNx44dnc+feOIJl1GwstGQ80dKykaOzjd37lzTtm1b52iVMcYUFxcbb29v88033zjXCwkJMcXFxResqWxkpzxJZtKkSc7nRUVFxs3NzSxbtswYY8zkyZNNnz59XNY5ePCgkWR27txZ6b7KRlsaNWrksuTl5VU64tSgQQOTm5vrbEtPTzeSzL59+yrdfmXvVWU+++wz07hxY+Pl5WXi4uLMs88+a7Zs2eJ8ffny5cbPz8/88ssvLuvddNNNzpEeX19fs2DBgkq33759e+f3pKr3oGzE6aGHHjK9e/d26fP000+byMhI5/OwsDAzfPhw5/PS0lITHBxsZs2aZXmsAFAdGHECgBrWoUMH5+PmzZtLcly4Lzn+J37BggXOEQIfHx/17dtXpaWlysrKuuR9GWMkOSavkKQff/xRDz30kFq1aiU/Pz+Fh4dLkg4cOCBJ8vT01PDhwzVv3jxJUkZGhrZs2eKc3KJ3794KCwtTq1atNGLECH300Uc6efLkBWuYO3euhg8f7nw+fPhwLVmy5JJnWEtPT9eePXvk6+vrfG8CAwP1yy+/6Mcff3T2a9++/RVd13T+59OoUSP5+vq6fD7fffedy+dzyy23SJJLDZVZs2aNMjIynEvjxo0r7RcWFqamTZs6n996663q2bOn2rdvrwceeEBz5sy5rOvlBg8erH/9619KSUlR3759tXLlSkVHRztHedLT01VUVKSgoCCX48vKynIeW2JiosaOHatevXrp5Zdfdjnmxx9/XC+++KK6du2qqVOnauvWrVXWkpmZqa5du7q0de3aVbt373aOjkqun4Wbm5uaNWvm/CwAoKYRnACghp1/sX9ZoCk7Va60tFSPPPKIyw/sLVu2aPfu3brpppsueV+ZmZny8/NTUFCQJOmee+5Rfn6+5syZow0bNmjDhg2S5HKq29ixY5WamqqffvpJ8+bNU8+ePRUWFiZJ8vX11Q8//KBFixapefPmmjJlim699dYqQ9COHTu0YcMG/fGPf1T9+vVVv3593XbbbTp16pQWLVp0ScdSWlqqmJgYl/cmIyNDu3bt0kMPPeTs16hRo0vabnnlJ2Nwc3Nz+XzuueeeCjXs3r3b8pTF8PBwtW7d2rnUq1f5P8Hl63d3d1dqaqqWLVumyMhIvfXWW2rbtu1lBWkvLy/17t1bU6ZMUVpamkaPHq2pU6c6j6158+YVjm3nzp16+umnJTlmI9y+fbsGDBigFStWKDIyUp9//rkkx/dm7969GjFihLZt26bY2Fi99dZbldZhjHF+989vK+9CnwUA1DSCEwBcQ6Kjo7V9+3aXH9hly6WOouTm5mrhwoUaNGiQ6tWrp/z8fGVmZmrSpEnq2bOnIiIiKh25aN++vWJjYzVnzhwtXLhQY8aMcXm9fv366tWrl1599VVt3bpV+/bt04oVKyqtYe7cuerevbu2bNni8mP8j3/8o+bOnVtl7R4eHi4jD2Xvze7duxUcHFzhvbnUaa4r2/7FKPt8brzxxgo1XGlguxA3Nzd17dpVzz//vDZv3iwPDw9nYLncY5GkyMhInThxQpLj2HJyclS/fv0Kx9akSRPnOm3atNGECRP07bff6v7779f8+fOdr7Vo0ULjxo3TkiVL9OSTT2rOnDlV7nft2rUubWlpaWrTpo3c3d0v61gAoLoRnADgGvLMM89o/fr1SkhIcI5kpKSk6LHHHrvgesYY5eTkKDs7W5mZmZo3b57i4uLk7++vl19+WZLUuHFjBQUFafbs2dqzZ49WrFihxMTESrc3duxYvfzyyyopKdF9993nbP/qq6/05ptvKiMjQ/v379f777+v0tJStW3btsI2zpw5ow8++EBDhw5VVFSUyzJ27Filp6dry5Ytle7/xhtv1NatW7Vz507l5eXpzJkzGjZsmJo0aaKBAwdqzZo1ysrK0qpVq/TEE0/op59+uti32Ln9rKwsZWRkKC8vr8oJE8pLSEjQ0aNHNXToUH3//ffau3evvv32W40ZM+ayw4uVDRs2aMaMGdq0aZMOHDigJUuW6MiRI4qIiHAeS/n3qrz8/Hzdeeed+vDDD7V161ZlZWXp008/1auvvqqBAwdKknr16qUuXbpo0KBB+uabb7Rv3z6lpaVp0qRJ2rRpk06dOqVHH31UK1eu1P79+7Vu3Tpt3LjRWcf48eP1zTffKCsrSz/88INWrFjhfK28J598UsuXL9cLL7ygXbt26b333tPbb7+tp556qlreQwC4GghOAHAN6dChg1atWqXdu3erW7du6tSpkyZPnuy8FqoqhYWFat68uX71q1+pS5cuevfddzVq1Cht3rzZuW69evX08ccfKz09XVFRUZowYYJee+21Src3dOhQ1a9fXw899JC8vLyc7QEBAVqyZInuvPNORURE6J133tGiRYvUrl27CttISUlRfn6+S/Aqc/PNN6t9+/ZVjjo9/PDDatu2rWJjY9W0aVOtW7dODRs21OrVq9WyZUvdf//9ioiI0JgxY3Tq1CmX+yNdjMGDB6tfv37q0aOHmjZtetGnDYaGhmrdunUqKSlR3759FRUVpSeeeEL+/v5Vnnp3pfz8/LR69WrdddddatOmjSZNmqTXX39d/fv3l1T5e1Wej4+POnfurDfeeEPdu3dXVFSUJk+erIcfflhvv/22JMeo1tKlS9W9e3eNGTNGbdq00YMPPqh9+/YpJCRE7u7uys/P18iRI9WmTRvFx8erf//+ev755yVJJSUlSkhIUEREhPr166e2bdtq5syZlR5TdHS0PvnkE3388ceKiorSlClTNH369Gq9UTQAXCk3U9lJxQCAOu3gwYO68cYbtXHjRkVHR9tdDgAAtiM4AQCczpw5o+zsbE2cONF5OhYAAOBUPQDAedatW6ewsDClp6frnXfesbscAACuGYw4AQAAAIAFRpwAAAAAwALBCQAAAAAsEJwAAAAAwALBCQAAAAAsEJwAAAAAwALBCQAAAAAsEJwAAAAAwALBCQAAAAAs/H9z7BJYnO/EHgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting for each cage\n",
    "for cage in grouped_averaged_first_port_df[\"cage\"].unique():\n",
    "    fig, ax = plt.subplots()\n",
    "    # Getting all the rows with the current cage number\n",
    "    cage_df = grouped_averaged_first_port_df[grouped_averaged_first_port_df[\"cage\"] == cage]\n",
    "    \n",
    "    # Plotting a line for each subject\n",
    "    for subject in cage_df[\"subject\"].unique():\n",
    "        # Getting all the rows with the current subject\n",
    "        subject_df = cage_df[cage_df[\"subject\"] == subject]\n",
    "        # Making the dates into days after the first session by subtracting all the dates by the first date\n",
    "        ax.plot(subject_df[\"date int\"], subject_df[\"adjusted_30_second_latency_less_than_10_seconds_ratio\"], '-o', label=subject)\n",
    "    # Setting the Y-Axis to only plot from 0 to 30 because we adjusted the latency to always be under 30\n",
    "    ax.set_ylim(0, 1)\n",
    "    # Labeling the X/Y Axis and the title\n",
    "    ax.set_xlabel(\"The Days After the First Session\")\n",
    "    ax.set_ylabel(\"Proportion of Latencies\")\n",
    "    ax.set_title(\"Less Than 10 Seconds Latencies from Tone Onset: Cage {}\".format(cage))\n",
    "    # To show the legend\n",
    "    ax.legend()\n",
    "    \n",
    "    file_name = \"10_less_latency_ratio_cage_{}.png\".format(cage)\n",
    "    plt.savefig(os.path.join(less_than_10_second_original_latency_ratio_plots_output_directory, file_name))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f43b699-f467-45d4-a178-668b0d4e7253",
   "metadata": {},
   "source": [
    "## Plotting the Adjusted Latencies for Entries that Overlap with the Tone\n",
    "Plotting Latencies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "id": "8ac3b485-58a3-4a49-8b16-93bcda44444c",
   "metadata": {},
   "outputs": [],
   "source": [
    "overlap_adjusted_average_latency_plots_output_directory = \"./proc/plots\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "id": "91eeb333-7237-4214-88e9-a939f8c02d60",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.makedirs(overlap_adjusted_average_latency_plots_output_directory, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "id": "17f30d62-d2ed-4998-917d-75404e03c773",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting for each cage\n",
    "for cage in grouped_averaged_first_port_df[\"cage\"].unique():\n",
    "    fig, ax = plt.subplots()\n",
    "    # Getting all the rows with the current cage number\n",
    "    cage_df = grouped_averaged_first_port_df[grouped_averaged_first_port_df[\"cage\"] == cage]\n",
    "    \n",
    "    # Plotting a line for each subject\n",
    "    for subject in cage_df[\"subject\"].unique():\n",
    "        # Getting all the rows with the current subject\n",
    "        subject_df = cage_df[cage_df[\"subject\"] == subject]\n",
    "        # Making the dates into days after the first session by subtracting all the dates by the first date\n",
    "        ax.plot(subject_df[\"date int\"], subject_df[\"latency_adjusted_overlap\"], '-o', label=subject)\n",
    "\n",
    "    # Setting the Y-Axis to only plot from 0 to 30 because we adjusted the latency to always be under 30\n",
    "    ax.set_ylim(0, 30)\n",
    "    # Labeling the X/Y Axis and the title\n",
    "    ax.set_xlabel(\"The Days After the First Session\")\n",
    "    ax.set_ylabel(\"Proportion of Latencies\")\n",
    "    ax.set_title(\"Overlap Adjusted Latency of Port Entry to Tone: Cage {}\".format(cage))\n",
    "    # To show the legend\n",
    "    ax.legend()\n",
    "    file_name = \"overlap_latency_cage_{}.png\".format(cage)\n",
    "\n",
    "    plt.savefig(os.path.join(overlap_adjusted_average_latency_plots_output_directory, file_name))\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5240f4b-0e5d-48dd-b9b9-fa3555e6cdd6",
   "metadata": {},
   "source": [
    "## Plotting the ratio of overlap adjusted latencies that are less than 10 seconds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "id": "5b92ffe3-614a-431c-8357-c63ae7dbc135",
   "metadata": {},
   "outputs": [],
   "source": [
    "less_than_10_second_overlap_adjusted_latency_ratio_output_directory = \"./proc/plots\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "id": "52fa6169-c15e-466d-a722-db63049e2f9c",
   "metadata": {},
   "outputs": [],
   "source": [
    "os.makedirs(less_than_10_second_overlap_adjusted_latency_ratio_output_directory, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "c99134bd-3615-45d7-95c1-2529d10d1f7d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting for each cage\n",
    "for cage in grouped_averaged_first_port_df[\"cage\"].unique():\n",
    "    fig, ax = plt.subplots()\n",
    "    # Getting all the rows with the current cage number\n",
    "    cage_df = grouped_averaged_first_port_df[grouped_averaged_first_port_df[\"cage\"] == cage]\n",
    "    \n",
    "    # Plotting a line for each subject\n",
    "    for subject in cage_df[\"subject\"].unique():\n",
    "        # Getting all the rows with the current subject\n",
    "        subject_df = cage_df[cage_df[\"subject\"] == subject]\n",
    "        # Making the dates into days after the first session by subtracting all the dates by the first date\n",
    "        ax.plot(subject_df[\"date int\"], subject_df[\"overlap_adjusted_latency_less_than_10_seconds\"], '-o', label=subject)\n",
    "\n",
    "    # Setting the Y-Axis to only plot from 0 to 30 because we adjusted the latency to always be under 30\n",
    "    ax.set_ylim(0, 1)\n",
    "    # Labeling the X/Y Axis and the title\n",
    "    ax.set_xlabel(\"The Days After the First Session\")\n",
    "    ax.set_ylabel(\"Proportion of Latencies\")\n",
    "    ax.set_title(\"Overlap Adjusted Less Than 10sec Latencies from Tone: Cage {}\".format(cage))\n",
    "    # To show the legend\n",
    "    ax.legend()\n",
    "    \n",
    "    file_name = \"10_less_overlap_latency_cage{}.png\".format(cage)\n",
    "    plt.savefig(os.path.join(less_than_10_second_overlap_adjusted_latency_ratio_output_directory, file_name))\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}