RBR_Processing_Report_Template.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "c09cdf94-02c0-48f5-83f3-c38a28069663",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "source": [
    "# Changes to the original steps:<br>\n",
    "Changes to Notebook in Docoumnets/GitHub/RBR-Processing <br>\n",
    "To call functions from the python file rather than have them embedded into the Notebook\n",
    "* Check profiles plots and pressure difference FIRST so that we can correct ZOH and spikes in the rsk file if needed<br>\n",
    "* new function called first_corrections\n",
    "* Call plotting and write file functions from outside this notebook<br>\n",
    "* changed made to write file function so that they could be read in IOS Shell<br>\n",
    "* Clip doesn't match exactly because IOS Shell CLIP is subjective.<br> \n",
    "* Rounded the Pressure for BINAVE to 0 decimal places, was getting 0.1 or 0.9, need whole numbers or 'bin value'.\n",
    "* Original Binave had the upcast in the averaging process, Delete 'should' get rid of the upcast, removed the upcast <br>\n",
    "  the Binave function.\n",
    "* Added rsk.derivevelocity() to the read_rsk function and add the velocity channel to the 6lineheader.  To be used in DELETE\n",
    "<br>\n",
    "# TO DO\n",
    "* create a copy of the original rsk file, use the 'if exists' function so we don't overwrite it.\n",
    "* Add pH <- Is it even used?\n",
    "* look into Binave <- DONE\n",
    "* call functions in python file similarly to how they are called in Jupyter <- DONE\n",
    "* delete all the lines that have been commented out?\n",
    "\n",
    "\n",
    "\n",
    "**------------------------------------------------------------------------------------------------------**"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cf8d8db-77d3-4876-a4da-7b47d81bb42c",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "show"
    ]
   },
   "source": [
    "**RBR CTD DATA PROCESSING NOTES**<br>\n",
    "Cruise: 2024-017<br>\n",
    "Locations: Clayoquot Sound <br> \n",
    "Project: Clayoquot Weather Station Network - ACRDP  <br>\n",
    "Party Chief: Cooper G.  <br>\n",
    "Platform: Doug Anderson  <br>\n",
    "Date: February 4, 2024 - February 7, 2024   <br>\n",
    "  <br>\n",
    "Processed by: Samantha Huntington <br>\n",
    "Date of Processing: May 23, 2024 - May 23, 2024 <br>\n",
    "Number of Raw files: 52          Number of Processed Files: 51 <br>\n",
    "\n",
    "**Instrument Summary**<br>\n",
    "Equipment: RBR Maestro CTD (s/n 232531) with a Turner Cyclops Fluorometer (s/n 2111617) and a JFE Advantech Rinko III oxygen sensor (s/n 0480).  <br> \n",
    "Sampling frequency was at 8Hz.  <br>\n",
    " \n",
    "**Summary of Quality and Concerns**<br>\n",
    "A cast list of times and locations was provided, “2024-017CTDTapLogFile_Final.csv”. The log file contained 56 casts, 5 of which were zooplankton <br>\n",
    "nets, these five casts were removed when making the header merge file. <br>\n",
    "The winch stopped working at 20m for cast 18, it was brought to the surface and restarted, creating an additional profile.<br>\n",
    "<br>\n",
    "The data overall look good with some spikes in Fluroescence.  There is a lot of noisy data at the surfce during the CTD soak. <br>\n",
    "\n",
    "\n",
    "**Processing Summary**\n",
    "\n",
    "*All processing code is available on request in RBR_Processing_Report_2024-017_suggested.ipynb.<br>* \n",
    "\n",
    "File **232531_20240206_1745.rsk** contained the 52 profiles. All profiles were extracted using python function READ_RSK().  <br> \n",
    "Profile numbers were matched to the event numbers provided in the log file. <br>\n",
    "<br>\n",
    "A dummy profile of 918 was assigned to the rsk profile for the first attempt at cast 18 using the header merge csv file.  <br>\n",
    "The extracted csv file from this function ws then deleted before the next step. <br.\n",
    "<br>\n",
    "\n",
    "File **2024-017_header-merge.csv** was created, based on the information provided by the chief scientist.<br>\n",
    "* Column “File_Name”: entries were derived from the event number.\n",
    "* Column “LOC:LATITUDE”: latitude was provided and reformatted to “XX XX.XXXX N !(deg min)”.\n",
    "* Column “LOC:LONGITUDE”: longitude was provided  and reformatted to “XX XX.XXXX W !(deg min)”.\n",
    "* Column “LOC: Event Number”: entries were event numbers. \n",
    "* Column “LOC: STATION”: entries were taken from the Log file. <br>\n",
    "\n",
    "A 6-line header was inserted using python function ADD_6LINEHDR_2().<br><br>\n",
    "A Metadata Dictionary was created to hold information for the header files **2024-017_METADATA.csv**.  Python function CREATE_METADATA_DICT() was used to add addtional metadata to this csv file and it was saved as **2024-017_METADATA_filled.csv**.  Additional information is stored in the python function for later use in the creation of header files. <br><br>\n",
    "The sampling site was mapped (Figure 1) using from **2024-017_header-merge.csv** using python function PLOT_TRACK_LOCATION() to check the location of all casts.<br>\n",
    "The presence of zero-order holds were checked using Python function PLOT_PRESSURE_DIFF().  Zero-order holds were found (Figure 2.) and confirmed with python function CHECK_FOR_ZOH.py(). <br><br>\n",
    "Profiles were checked using function CHECK_PROFILES().  A few Spikes were found in Fluorescence but were not related to gain changes and most were within reasonable limits. There was a significate spike in cast 52 and despiking was applied while corrections were made to the zero order holds and the spikes in corrections by re-running READ_RSK() and adding corrections rsk.correcthold() and rsk.despike(). from the pyRSKtools package.<br><br>\n",
    "After the corrections were made, a new csv file was created **2024-017_CSV_DATA-6Linedr_corr_hold_spk.csv** and the corrected values were checked in python function Plot_Pressure_Diff().  Zero-order holds were found to be removed (Figure 3.).<br>\n",
    "<br>\n",
    "Cast variables were created from the output csv so they could be used in further processing using python function CREATE_CAST_VARIABLES().  A plotting templates were also created using functions FORMAT_PROCESSING_PLOT() and DO_TS_PLOT(). Pre-processing plots were examined with python function FIRST_PLOTS.py()<br>\n",
    "<br>\n",
    "Raw data were plotted and examined:<br>\n",
    "* Salinity looks good with some noisy data during the soak for many casts.\n",
    "* Temperature looks good with bad data the surface of many casts and the bottom of cast 43.\n",
    "* Conductivity looks good with some noisy data during the soak for many casts.\n",
    "* Oxygen looks good with some bad data at the surface of many casts.\n",
    "* Fluorescence looks good with some spikes in the downcast of many casts. <br>\n",
    "\n",
    "**Data processing**\n",
    "* Correction to Pressure: there were no negative pressures found at the surface so pressure was not calibrated in in python funcion CALIB.py() .<br>\n",
    "* All cast times matched the Log so there were no corrections made in CORRECT_TIME_OFFSET.py(). \n",
    "* CLIP: Pressure is steady for a variable number of scans. Records were removed from the beginning and end of the cast using CLIP_CAST.py().<br> \n",
    "* Profile plots were examined after CLIP. <br.\n",
    "* Filter: a *moving average* filter, with a *window width of 6*, was applied using function FILTER.py() to temperature, conductivity, and pressure and fluorescenc. Salinity will be calculated in the next step. <br>\n",
    "* SHIFT: Based on suggested values in document “Guidelines for processing RBR CTD profiles”, the alignment of temperature and conductivity was<br>\n",
    "corrected by applying a shift of -2 scans in conductivity using SHIFT_CONDUCTIVITY.py(). <br> \n",
    "* SHIFT: Better alignment with Oxygen profiles was found by advancing it by 11 scans using SHIFT_OXYGEN. The advice given in document “Guidelines for processing <br>\n",
    "RBR CTD Profiles” was that an advance between 2 and 3 seconds is appropriate. T-O plots before and after alignment were compared. <br>\n",
    "* Convert Oxygen: Oxygen saturation was converted to Oxygen concentration in umol/kg and mL/L using python function DERIVE_OXYGEN_CONCENTRATION.py()<br>\n",
    "* DELETE: Pressure reversals and swells were detected and delted using python function DELETE_PRESSURE_REVERSALS.py(). Plots were examined before <br> and after delete to confirm that reasonable values were shown. <br>\n",
    "* Despiking: No date despiking took place on Fluorescence. <br>\n",
    "\n",
    "**Final Checks and header editing**\n",
    "* Time, Date, Cast_direction, and Event_number were removed from the channels using *2024-017_vars_to_drop.csv* and python function <br>\n",
    "DROP_SELECT_VARS.py()<br>\n",
    "* Python function BINAVE.py() was used to metre-average the data. <br>\n",
    "* FINAL_EDIT.py() was used to calibrate conductivity unist to S/m, edit header information, and reorder the channels. \n",
    "* Processed data was examined after in had been plotted using function PLOT_PROCESSED.py(). \n",
    "\n",
    "**Write IOS Header Files**\n",
    "* Python function WRITE_FILE.py() was used to write the final files in IOS Header format. <br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "a9c73041-2695-46af-b2cc-1ddb1a9d5248",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [],
   "source": [
    "#import cartopy.crs as ccrs\n",
    "#from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter, LatitudeLocator\n",
    "import sys\n",
    "import os\n",
    "import pyrsktools\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "from mpl_toolkits.basemap import Basemap\n",
    "from copy import deepcopy  # copy,\n",
    "from scipy import signal\n",
    "import gsw\n",
    "from matplotlib import pyplot as plt\n",
    "from datetime import datetime\n",
    "import random\n",
    "from o2conversion import O2stoO2c\n",
    "from seawater import eos80\n",
    "import shutil\n",
    "import pandoc"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "734180bf-6ed9-4847-9cb8-1e39f8c825ba",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "source": [
    "**Set the parameters for this cruise**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "456e5070-ca77-40f1-942e-8f7535e03053",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [],
   "source": [
    "year = \"2024\"\n",
    "cruise_number = \"017\"\n",
    "#dest_dir = f\"C:\\\\Users\\\\huntingtons\\\\Desktop\\\\RBR_Processing\\\\CURRENT_PROCESSING\\\\{year}-{cruise_number}\\\\Suggested\\\\\"\n",
    "dest_dir = \"C:\\\\Users\\\\huntingtons\\\\\\Desktop\\\\RBR_Processing\\\\binave_delete_June2024\\\\template_July2024\\\\\"\n",
    "skipcasts = 0\n",
    "rsk_start_end_times_file = None\n",
    "rsk_time1, rsk_time2 = [None, None]\n",
    "rsk_file = dest_dir + \"232531_20240206_1745.rsk\"  # \"232531_20240223_1125.rsk\"]\n",
    "sample_rate = 8\n",
    "left_lon, right_lon, bot_lat, top_lat = [None, None, None, None]\n",
    "start_time_correction_file = None\n",
    "verbose = True\n",
    "shift_recs_conductivity: int = 2\n",
    "shift_recs_oxygen = -11 \n",
    "drop_vars_file = \"2024_017_vars_to_drop.csv\"\n",
    "calib_param_file = None\n",
    "processing_report_name = f\"{year}-{cruise_number}_RBR_Processing_Report.docx\"\n",
    "# 5 lines of processing comments are added here and included in the write_comments function.  If more lines are needed, adjust the function. \n",
    "processing_comments1 = \"       \" + \"Cast 18 stopped at 20m and was brought to the surface and re-started.\" \n",
    "processing_comments2 = None # format is \"       \" + \"Your text here\"\n",
    "processing_comments3 = None\n",
    "processing_comments4 = None\n",
    "processing_comments5 = None"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "253847d6-40bc-4206-86ec-0fc66cf9771a",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [],
   "source": [
    "# Set Global variables\n",
    "VARIABLES_POSSIBLE = [\n",
    "    \"Salinity\",\n",
    "    \"Temperature\",\n",
    "    \"Conductivity\",\n",
    "    \"Oxygen\",\n",
    "    \"Fluorescence\",\n",
    "    \"Oxygen_mL_L\",\n",
    "    \"Oxygen_umol_kg\",\n",
    "]\n",
    "VARIABLE_UNITS = [\"PSS-78\", \"C\", \"mS/cm\", \"%\", \"ug/L\", \"mL/L\", \"umol/kg\"]\n",
    "VARIABLE_COLOURS = [\"b\", \"r\", \"goldenrod\", \"grey\", \"g\", \"grey\", \"grey\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6230737a-34f7-46d9-ac09-dc0817b5e323",
   "metadata": {
    "editable": true,
    "raw_mimetype": "",
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "source": [
    "# Create a METADATA DICTIONARY and a Records In Records Out Dictionary\n",
    "Read in a csv file and then populating it with more information from the rsk file.<br>\n",
    "The Metadata Dictionary also stores information in a dictionary for use in functions futher in the process.<br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "94ba3e22-579a-4870-bce6-56ec22cfe0a5",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [],
   "source": [
    "from RBR_CTD_IOS_2024 import CREATE_META_DICT, add_recs_out\n",
    "meta_dict = CREATE_META_DICT(dest_dir, rsk_file, year, cruise_number, rsk_time1, rsk_time2)\n",
    "dict_recs_out = {}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37156ba7-710c-4de5-a340-daae93435057",
   "metadata": {
    "editable": true,
    "raw_mimetype": "",
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "source": [
    "# Read the rsk file\n",
    "Inputs<br>\n",
    "*dest_dir, year, cruise_number, skipcasts, rsk_time1, rsk_time2, rsk_start_end_times_file<br>\n",
    "<br>\n",
    "This function reads in the rsk file and takes the cast numbers from the header merge csv file and outputs a <br>\n",
    "csv file for each profile. <br>\n",
    "In this first instance no corrections will be made to the rsk data. For this cruise we are running it first since we need to <br>\n",
    "delete one of the output provile csv files before proceeding. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "badfceb9-af5d-4a96-9dc4-ef37b070c4e0",
   "metadata": {
    "editable": true,
    "raw_mimetype": "",
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "232531_20240206_1745.rsk\n",
      "no corrections being made\n",
      "Using original values\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "'_CTD_DATA-6linehdr.csv'"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from RBR_CTD_IOS_2024 import READ_RSK\n",
    "zoh=False\n",
    "fix_spk=False\n",
    "fill_action = None\n",
    "fill_type=None\n",
    "spk_window=None\n",
    "spk_std=None\n",
    "spk_var=None\n",
    "READ_RSK(dest_dir, year, cruise_number, skipcasts, meta_dict, zoh, fill_action, fill_type, spk_window, spk_std, spk_var, fix_spk, rsk_start_end_times_file, rsk_time1, rsk_time2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bdaa54f6-a0b1-49c9-bf20-5ae449c88cea",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "source": [
    "# First Steps\n",
    "**Merge** all the profile csv files into one data file. <br>\n",
    "Create a **Metadata Dictionary** by reading in a csv file and then populating it with more information from the rsk file.<br>\n",
    "The Metadata Dictionary also stores information in a dictionary for use in functions futher in the process. <br>\n",
    "Add a **6LINEHEADER** csv file that can be used in IOS Shell if needed. This will be archived with the output files. <br>\n",
    "**Plot Track Location** to create a plot of the stations sampled.<br> \n",
    "**Plot Pressure Difference** to have a look at the pressure differences and determine if a correction for zero order holds is needed.<br>\n",
    "**Check for Zero Order Holds** is an additional check to determine if a correction is needed. \n",
    "**Check Profile Plots** is a quick way to determine if there are any large spikes in the data. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b9d5f0c4-f15b-4739-bdf2-a223da42c232",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "show"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of pressure records: 96128\n",
      "Sum of zero pressure differences: 458\n",
      "zoh, True\n"
     ]
    }
   ],
   "source": [
    "from RBR_CTD_IOS_2024 import MERGE_FILES, ADD_6LINEHEADER_2, plot_track_location, PLOT_PRESSURE_DIFF, check_for_zoh \n",
    "MERGE_FILES(dest_dir=dest_dir, year=year, cruise_number=cruise_number)\n",
    "ADD_6LINEHEADER_2(dest_dir, year, cruise_number, output_ext=\"_CTD_DATA-6linehdr.csv\")\n",
    "plot_track_location(dest_dir, year, cruise_number, left_lon, right_lon, bot_lat, top_lat)\n",
    "PLOT_PRESSURE_DIFF(dest_dir, year, cruise_number, input_ext = '_CTD_DATA-6linehdr.csv')\n",
    "zoh = check_for_zoh(dest_dir, year, cruise_number, float(meta_dict[\"Sampling_Interval\"]))\n",
    "print(\"zoh,\", zoh)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5453f76d-2d76-4f79-b46d-3e9c62b3b63d",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [],
   "source": [
    "from RBR_CTD_IOS_2024 import check_profiles\n",
    "check_profiles(dest_dir, year, cruise_number, name1=\"Pre_Processing_\", name2=\"Pre_Processing_\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "bf40d3fb-af45-448e-ae67-6f3b632c77f1",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [],
   "source": [
    "# if you need to check the channels\n",
    "# rsk.printchannels()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5a0f68cb-4982-4d44-b812-9a8973569327",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "source": [
    "# Make first corrections\n",
    "* Correct the hold using rsk.correcthold(), this will correct holds in all channels.<br>\n",
    "* CSV files will be re-generated and replaced and merged. \n",
    "* Despike Fluorescence and any other channels if needed.  The default is 2 standard deviations in a window of 11. Add channels if needed. <br>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9759662a-6fd0-4026-af54-db42abd0f757",
   "metadata": {
    "editable": true,
    "scrolled": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "show"
    ]
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Is despiking needed? True or False True\n",
      "Is zoh correction needed? True or False True\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "232531_20240206_1745.rsk\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABWwAAAJOCAYAAAAjyk6bAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMCwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy81sbWrAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOzdebwN9f8H8Ne5u4t77btkL2SJikpCCImyFEqiX4m0SJsWlFJ9Vapv+LagRZIlWm72PVps1TcRIQnZXXFxl/n9Md+5Z5s5Z5bPLOfc1/PxuI9z7pw5n/mc2ef9ec9nfJIkSSAiIiIiIiIiIiIi1yW4XQEiIiIiIiIiIiIikjFgS0REREREREREROQRDNgSEREREREREREReQQDtkREREREREREREQewYAtERERERERERERkUcwYEtERERERERERETkEQzYEhEREREREREREXkEA7ZEREREREREREREHsGALREREREREREREZFHMGBLREREhZYvX45BgwbhoosuQvHixVG1alV0794dGzduVB1/06ZNuO6661CiRAmUKlUKN998M3bt2hU0zm+//YaRI0eiefPmKFWqFMqUKYOrrroKc+bMiVqfp556Cj6fD40aNTL0O/TUCwAmTpyIm2++GTVr1oTP58O1116rWt61114Ln8+n+Xfw4EFd9friiy/QrVs3VKxYESkpKShTpgzat2+PGTNmIDc3FwMHDow4HeVv4MCBYfVKSEhAyZIlUadOHfTu3Rtz5sxBQUGBofkGAGPGjAmaVnp6OqpVq4ZOnTrhzTffxKlTpzS/m5ubi0qVKsHn8wUt3+nTp+v6XRdeeGFQeZdeeil8Ph8mTJhg+HdIkoRp06bh8ssvR/HixZGRkYFLL70UCxYsCBrP5/NhzJgxhf+vXLkSPp8PK1euNDxNIy688ELccMMNpr+vzNM9e/aIq5THKevmkSNHhJV57bXXam73gfbs2QOfz4fp06cLm7ZRVtcZIiIiih1JbleAiIiIvGPy5Mk4evQoHnjgATRo0ACHDx/GK6+8gpYtW2LRokVo165d4bjbtm3Dtddei6ZNm+LTTz/F2bNn8cwzz6B169bYsmULypcvDwBYvHgxvvrqK9x+++247LLLkJeXh1mzZqF3794YO3YsnnnmGdW6bNmyBRMmTEDFihUN/Qa99QKAKVOmoHjx4mjXrh2++OILzTInTZqE7OzsoGFnzpzB9ddfj+bNm6NSpUoR6yRJEgYNGoTp06ejS5cuePXVV1G9enWcPHkSK1aswNChQ3HkyBE8/fTTGDJkSOH3Nm3ahGHDhuGFF15A27ZtC4cH/oZatWphxowZAIDTp09j9+7dmD9/Pnr37o3WrVvjiy++QGZmpr6ZF2DhwoXIzMzE+fPnsX//fixbtgyPPvoo/vWvf+GLL75AkyZNwr7z5Zdf4u+//wYAvPfee+jVqxcAoGvXrli/fn3QuK1atUKvXr3w8MMPFw5LTU0tfL9lyxZs3ry5sKyRI0caqv+9996L6dOn46GHHsL48eORl5eHn3/+GWfOnIn4vUsvvRTr169HgwYNDE2PiIiIiEgYiYiIiOh//v7777Bhp06dkipWrCi1b98+aHjv3r2lcuXKSSdPniwctmfPHik5OVl69NFHC4cdPnxYKigoCCu3a9euUnp6unT27Nmwz3Jzc6WmTZtK999/v9SmTRupYcOGun+D3npJkiTl5+cXvm/YsKHUpk0b3dOZPn26BEB69913o4770ksvSQCksWPHqn5+4MABac2aNWHDV6xYIQGQZs+erfq9SPNm6tSpEgCpT58+UesXaPTo0RIA6fDhw2GfbdmyRcrMzJQuuOAC1eXWtWtXKSUlRerQoYOUkJAg/fnnn5rTASANGzZM8/Nhw4ZJAKSuXbtKAKRvvvlG92/47LPPJADSrFmzoo4LQBo9erTuskWpUaOG1LVrV9PfnzZtmgRA2r17d8Txzpw5Y3oaIp05c0Z1PyBJknT69GldZURaN81q06aNru1+9+7dEgBp2rRpwqZtlNV1hoiIiGIHu0QgIiKiQhUqVAgbVqJECTRo0AB//vln4bC8vDx8+eWX6NmzJzIyMgqH16hRA23btsVnn31WOKxcuXLw+Xxh5V5++eU4c+YMjh07FvbZiy++iGPHjuH55583VH8j9QKAhATzp0LvvfceSpQogVtuuSXieLm5uXjppZdw0UUX4emnn1Ydp1KlSrj66qtN10XNnXfeiS5dumD27Nn4448/hJTZpEkTPPnkk9i7dy9mzZoV9Nn+/fuxcOFCdOvWDY888ggKCgpM3z5+9uxZfPzxx2jevDlee+01AMDUqVN1f//111/HhRdeiD59+hietlqXCAMHDkSJEiWwc+dOdOnSBSVKlED16tXx8MMP49y5c0HfP3/+PMaNG4eLLroIqampKF++PO68804cPnxYdXoLFy7EpZdeimLFiuGiiy5S/Z3ffvstrrrqKqSlpaFKlSp44oknkJubGzaecsv8vHnz0KxZM6SlpWHs2LG6f/t3332Hbt26oWzZskhLS0Pt2rXx4IMPBo2zdu1atG/fHiVLlkR6ejquvPJKfPXVV0HjKN01LF68GIMGDUL58uWRnp6Oc+fO4dprr0WjRo2wevVqXHnllUhPT8egQYN01xEA/v77b/Tt2xeZmZmoWLEiBg0ahJMnTwaNc/bsWTzxxBOoWbMmUlJSULVqVQwbNgwnTpyIWv7+/fvRp08flCxZEpmZmbjlllt0d3sSqKCgAOPGjUP9+vVRrFgxlCpVCo0bN8brr79eOI7SzcPmzZtx8803IyMjA5mZmbjttts015lAkyZNQlJSEkaPHh113I8//hitWrVCiRIlUKJECTRt2hTvvfde4eebN2/GDTfcgAoVKiA1NRVVqlRB165dsW/fPgBAs2bN0Lp167By8/PzUbVqVdx88816ZgsRERHpwIAtERERRXTy5Els2rQJDRs2LBz2+++/IycnB40bNw4bv3Hjxti5cyfOnj0bsdwVK1agfPnyYUHirVu3Yty4cZg8eTJKlChhqK4i6qXHjh07sGbNGtx6661R67hhwwYcO3YM3bt3Vw1c2+nGG2+EJElYs2aN0DIBYPXq1UHDp0+fjvz8fAwaNAjXXXcdatSogalTp0KSJMPTmDdvHo4fP45Bgwahbt26uPrqqzFr1iz8888/Ub+bl5eH9evXo1mzZnj11VdRo0YNJCYmolatWpgwYYKp+gBy4P3GG29E+/btsWDBAgwaNAivvfYaXnrppcJxCgoK0L17d7z44ovo168fvvrqK7z44otYsmQJrr32WuTk5ASV+eOPP+Lhhx/GQw89hAULFqBx48YYPHhw0LzdunUr2rdvjxMnTmD69OmYMmUKNm/ejHHjxqnWc9OmTXjkkUdw//33Y+HChejZs6eu37do0SK0bt0ae/fuxauvvoqvv/4aTz31VGEXFwCwatUqtGvXDidPnsR7772HmTNnomTJkujWrVtYAB8ABg0ahOTkZHz44YeYM2cOkpOTAQAHDhzAbbfdhn79+iErKwtDhw7VVUdFz549Ua9ePcydOxePP/44Pv74Yzz00EOFn0uShB49emDChAm4/fbb8dVXX2HEiBF4//330a5du7Age6CcnBxcd911WLx4McaPH4/Zs2ejUqVKURtm1Lz88ssYM2YM+vbti6+++gqzZs3C4MGDVYPGN910E+rUqYM5c+ZgzJgxmD9/Pjp16qQamFd+48iRI/Hggw/i3XffjRqYf+aZZ9C/f39UqVIF06dPx2effYY77rijsDHn9OnT6NChA/7++2+89dZbWLJkCSZOnIgLLrigsN/qO++8E2vXrsWOHTuCyl68eDH279+PO++80/A8IiIiIg2u5vcSERGR5/Xv319KSkqSNmzYUDjsm2++kQBIM2fODBv/hRdekABI+/fv1yzznXfekQBIr7/+etDw/Px86YorrpD69u1bOMxIlwhW6mWkS4THHntMAiCtX78+6riffPKJBECaMmWKrrIDWekSQZIk6euvv5YASC+99JLuaUa77TwnJ0cCIHXu3LlwWEFBgVSnTh2patWqUl5eXlA5y5YtUy0HEbpEaNeunZSWliYdP35ckiT/7f/vvfde1PofOHBAAiBlZGRI1apVk95//31p2bJl0pAhQyQA0qhRo8LqEdglgjLPV6xYUTjsjjvukABIn376adB3u3TpItWvX7/w/5kzZ0oApLlz5waN98MPP0gApEmTJhUOq1GjhpSWlib98ccfhcNycnKkMmXKSPfcc0/hsFtuuUUqVqyYdPDgwcJheXl50kUXXRTWJUKNGjWkxMREafv27VHnU6jatWtLtWvXlnJycjTHadmypVShQgXp1KlTQXVp1KiRVK1atcIuD5TlNWDAgLAy2rRpE3G9iERZp15++eWg4UOHDpXS0tIKp79w4ULV8WbNmiUBkN5+++2g+gRu95MnT5YASAsWLAj67v/93/8Z7hLhhhtukJo2barrNz300ENBw2fMmCEBkD766KPCYUqXCGfOnJF69uwpZWZmSkuXLo1aj127dkmJiYlS//79NcfZsGGDBECaP3++5jhHjhyRUlJSwrahPn36SBUrVpRyc3Oj1oWIiIj0YYYtERERaXr66acxY8YMvPbaa2jevHnY55EyRrU++/rrrzFs2DD06tULw4cPD/rs1VdfxY4dOzBx4sSI9SooKEBeXl7hX35+vuV66ZWXl4f3338fDRs2RMuWLS2VZTfJZDap0TJXrVqFnTt34o477kBiYiIAORvP5/MZ6soAAHbv3o0VK1bg5ptvRqlSpQAAvXv3RsmSJYPK0loHCgoKAADZ2dmYPXs2BgwYgHbt2mHy5Mno0aMHXn31VV2ZuqF8Ph+6desWNKxx48ZB3U18+eWXKFWqFLp16xZUt6ZNm6JSpUpB3SwAQNOmTXHBBRcU/p+WloZ69eoFlblixQq0b98+6OF7iYmJmhmfjRs3Rr169Qz9tt9++w2///47Bg8ejLS0NNVxTp8+je+++w69evUKyipPTEzE7bffjn379mH79u1B39HK7i1dunTQAwyNUrK8FY0bN8bZs2dx6NAhAMDy5csByF1ZBOrduzeKFy+OZcuWaZa9YsUKlCxZMmwa/fr1M1zPyy+/HD/++COGDh2KRYsWhT24MFD//v2D/u/Tpw+SkpKwYsWKoOFHjx5Fu3bt8P333xd2TxHNkiVLkJ+fj2HDhmmOU6dOHZQuXRqPPfYYpkyZgq1bt4aNU7ZsWXTr1g3vv/9+4XZ2/PhxLFiwAAMGDEBSEp9nTUREJAoDtkRERKRq7NixGDduHJ5//nncd999QZ+VLVsWgBw8CHXs2DH4fL7CYFugRYsW4eabb0aHDh0wY8aMoODp3r178cwzz2D06NFISUnBiRMncOLECeTl5aGgoAAnTpwovKVcudVa+VOCFmbrZURWVhYOHjyIu+66S9f4SkBu9+7dlqZrhhL4q1Kliq1lKv1g3nTTTYXLLTMzE1dffTXmzp2rq99QhdKNQq9evQrLUroj+Oabb7Bt2zYAwLPPPhu0DtSuXRuAHAz0+XzIyMgIC6h37twZZ8+eVQ1GRZOenh4WzExNTQ3qYuPvv//GiRMnkJKSElS35ORkHDx4EEeOHAn6vrK+hpYZ2HXC0aNHUalSpbDx1IYBQOXKlQ39LgCFfaVWq1ZNc5zjx49DkiTV8pV1IXS706qLmToGCp1vqampAFA4344ePYqkpCSUL18+aDyfz4dKlSqp7h8UR48eDQqOK7TmdyRPPPEEJkyYgG+//RadO3dG2bJl0b59e2zYsCFq+UlJSShbtmxYXX/77Td899136Ny5Mxo1aqSrHnqWb2ZmJlatWoWmTZti1KhRaNiwIapUqYLRo0cHdcswaNAg/PXXX1iyZAkAYObMmTh37lxYcJyIiIisYTMoERERhRk7dizGjBmDMWPGYNSoUWGf165dG8WKFcPPP/8c9tnPP/+MOnXqhAW3Fi1ahB49eqBNmzaYO3cuUlJSgj7ftWsXcnJy8MADD+CBBx4IK7d06dJ44IEHMHHiRIwZMyYoiFyyZEnT9TLqvffeQ0pKCm6//XZd47do0QJlypTBggULMH78eEf7sf3888/h8/lwzTXXCC0TAK699loAch/Hc+fOBQBcdtllqt/5+OOPdfVTGvigMq0HGE2dOhUvv/wy7r77btxwww2Fw5WgXbFixVC3bl3Vh0Qp2cFWHjYXSbly5VC2bFksXLhQ9XNlPTWibNmyqr9F6yFYZtYvJbCpPFxKTenSpZGQkIADBw6EfbZ//34A8u/XUxe7t4GyZcsiLy8Phw8fDgraSpKEgwcPaq6nyne///77sOFmHjqWlJSEESNGYMSIEThx4gSWLl2KUaNGoVOnTvjzzz+Rnp4eVH7VqlUL/8/Ly8PRo0fDgtOtWrVC7969MXjwYADA5MmTo67Pgcu3evXqmuNdcskl+OSTTyBJEn766SdMnz4dzz77LIoVK4bHH38cANCpUydUqVIF06ZNQ6dOnTBt2jRcccUVaNCggbGZQ0RERBExw5aIiIiCPPfccxgzZgyeeuopzSePJyUloVu3bpg3b17hA2kAOUtWuZ090OLFi9GjRw9cffXVmD9/fmFwLVDTpk2xYsWKsL8mTZrgwgsvxIoVKwqDtBdeeCFatGhR+Fe/fn1T9TLq4MGDyMrKQo8ePVSzI9UkJyfjsccew7Zt2/Dcc8+pjnPo0CF88803luoWatq0afj666/Rt2/foNvurfjxxx/xwgsv4MILL0SfPn0AyMHYnJwcPPfcc6rLr1y5crq7RVi0aBH27duHYcOGqZbVsGFDfPDBB8jLy0OVKlWC1oFLLrmksJyePXsiOzsb69atCyo/KysLJUqUCHqAnkg33HADjh49ivz8/KC6ha6nRrRt2xbLli0LevhXfn6+6kO+zKpXrx5q166NqVOnaj6Qq3jx4rjiiiswb968oAzggoICfPTRR6hWrZrhrhjsomTcf/TRR0HD586di9OnT0fsRqBt27Y4depUYcOE4uOPP7ZUp1KlSqFXr14YNmwYjh07hj179gR9PmPGjKD/P/30U+Tl5RU2jAS644478Mknn2DatGkYMGBAWJcwoTp27IjExERMnjxZV119Ph+aNGmC1157DaVKlcKmTZsKP1O6wJg/fz7WrFmDDRs2YNCgQbrKJSIiIv2YYUtERESFXnnlFTzzzDO4/vrr0bVrV3z77bdBnwfeYj527FhcdtlluOGGG/D444/j7NmzeOaZZ1CuXDk8/PDDheOtXbsWPXr0QKVKlTBq1Chs2bIlqMwGDRogIyMDpUqVUg1OlCpVSjNwoUZvvQBgw4YNhYGT7OxsSJKEOXPmAJCzRWvUqBE0/vvvv4+8vDzd3SEoHnnkEfz6668YPXo0vv/+e/Tr1w/Vq1fHyZMnsXr1arz99tsYO3YsrrrqKkPlAvJt4MpyysnJwa5duzB//nx8+eWXaNOmDaZMmWK4TADYuHEjMjMzkZubi/3792PZsmX48MMPUaFCBXzxxReFGdLvvfceSpcujZEjR6pmLw8YMACvvvoqfvzxRzRp0iTiNN977z0kJSVh1KhRqt043HPPPbj//vvx1VdfoXv37prljBw5EjNmzEDv3r3x3HPPoVq1apgzZw4+//xzTJgwAcWKFTM4N/S59dZbMWPGDHTp0gUPPPAALr/8ciQnJ2Pfvn1YsWIFunfvjptuuslQmU899RQ+//xztGvXDs888wzS09Px1ltv4fTp00Lr/tZbb6Fbt25o2bIlHnroIVxwwQXYu3cvFi1aVBhMHD9+PDp06IC2bdti5MiRSElJwaRJk/Df//4XM2fOdDR7PJIOHTqgU6dOeOyxx5CdnY2rrroKP/30E0aPHo1mzZpFzI4fMGAAXnvtNQwYMADPP/886tati6ysLCxatMhwPbp164ZGjRqhRYsWKF++PP744w9MnDgRNWrUQN26dYPGnTdvHpKSktChQwf88ssvePrpp9GkSZPChpFQvXr1Qnp6Onr16oWcnBzMnDmzcJusU6cOAGDnzp0A5AauUaNG4bnnnkNOTg769u2LzMxMbN26FUeOHMHYsWPx5ZdfYtKkSejRowdq1aoFSZIwb948nDhxAh06dAia9qBBg/DSSy+hX79+KFasmGZ/ykRERGSBa487IyIiIs9RnuCu9Rdqw4YNUvv27aX09HQpIyND6tGjh7Rz586gcZSnoGv9rVixImqdGjZsaOh36KmXJEnSHXfcoVkvtafB16tXT7rwwgsLn0Zv1IIFC6SuXbtK5cuXl5KSkqTSpUtLbdu2laZMmSKdO3cubPwVK1ZIAKTZs2erlhe6vIoXLy7VqlVL6tWrlzR79mwpPz/fcB1Dl1dqaqpUuXJlqWPHjtLrr78uZWdnF477448/SgCkBx98ULO8bdu2SQCk4cOHBw0HIA0bNqzw/8OHD0spKSlSjx49NMs6fvy4VKxYMalbt25Rf8fevXulW2+9VSpdurSUkpIiNW7cWJo6dWrYeACk0aNHF/6vzPPA9fKOO+6QihcvHvZdZV4Fys3NlSZMmCA1adJESktLk0qUKCFddNFF0j333CPt2LGjcLwaNWpIXbt2DSuzTZs2Ups2bYKGffPNN1LLli2l1NRUqVKlStIjjzwivf322xIAaffu3VHL1Gv9+vVS586dpczMTCk1NVWqXbu29NBDDwWNs2bNGqldu3ZS8eLFpWLFikktW7aUvvjii6Bxpk2bJgGQfvjhB9XfZ3R7Vijz+/Dhw6rTC5wXOTk50mOPPSbVqFFDSk5OlipXrizde++90vHjx8PqEzq/9+3bJ/Xs2VMqUaKEVLJkSalnz57SunXrNPcLWl555RXpyiuvlMqVKyelpKRIF1xwgTR48GBpz549Yb9p48aNUrdu3Qqn2bdvX+nvv/8OKk9t+a5YsUIqUaKEdP3110tnzpwpHK9GjRph9fnggw+kyy67rHC9bNasWeHv2bZtm9S3b1+pdu3aUrFixaTMzEzp8ssvl6ZPn67626688koJgNS/f3/d84OIiIj080mSDY8PJiIiIiIioojGjBmDsWPH4vDhw2F9ABMREVHRxT5siYiIiIiIiIiIiDyCfdgSERERFQEFBQUoKCiIOE5SEk8N400sLPdYqGMgSZKiPugrMTHRM336EhERUexhhi0RERFRETBo0CAkJydH/KP4EwvL/dlnn41aR+XhgF6watWqqPV9//33dZU1ZswYSJLE7hCIiIgoCPuwJSIiIioC9uzZgyNHjkQcp0WLFg7VhpwSC8t9//792L9/f8RxGjdujJSUFIdqFNmpU6ewffv2iOPUrFkTZcuWdahGREREFG8YsCUiIiIiIiIiIiLyCHaJQEREREREREREROQR3um936MKCgqwf/9+lCxZkg8OICIiIiIiIiIiKqIkScKpU6dQpUoVJCTYlwfLgG0U+/fvR/Xq1d2uBhEREREREREREXnAn3/+iWrVqtlWPgO2UZQsWRKAvCAyMjJcro29cnNzsXjxYnTs2NETTwwmIvO4PRPFD27PRPGD2zNR/OD2TBQ/jGzP2dnZqF69emG80C4M2EahdIOQkZFRJAK26enpyMjI4AGHKMZxeyaKH9yeieIHt2ei+MHtmSh+mNme7e42lQ8dIyIiIiIiIiIiIvIIBmyJiIiIiIiIiIiIPIIBWyIiIiIiIiIiIiKPYB+2RERERERERERUZOTn5yM3N9ftapBH5ObmIikpCefOnUNCQgISExPdrhIDtkREREREREREFP8kScLBgwdx4sQJt6tCHiJJEipVqoS9e/fC5/OhVKlSqFSpku0PFouEAVsiIiIiIiIiIop7SrC2QoUKSE9PdzUgR95RUFCAf/75B8WLF8fZs2dx6NAhAEDlypVdqxMDtkREREREREREFNfy8/MLg7Vly5Z1uzrkIQUFBTh//jyKFSuG4sWLAwAOHTqEChUquNY9Ah86RkREREREREREcU3pszY9Pd3lmpDXKeuIm/0cM2BLRERERERERERFArtBoGi8sI4wYEtERERERERERETkEQzYEhERERERERERUUwZM2YMmjZtWvj/wIED0aNHj8L/JUnC3XffjTJlysDn82HLli2qw7yIAVsiIiIiIiIiIiKPGjhwIHw+H3w+H5KTk1GrVi2MHDkSp0+fdrtqnvL6669j+vTphf8vXLgQ06dPx5dffokDBw6gUaNGqsO8KMntChAREREREREREZG266+/HtOmTUNubi7WrFmDu+66C6dPn8bkyZODxsvNzUVycrJLtVTnVJ0yMzOD/v/9999RuXJlXHnllRGHFRQU2F43o5hhS0RERERERERE5GGpqamoVKkSqlevjn79+qF///6YP39+YbcAU6dORa1atZCamgpJknDy5EncfffdqFChAjIyMtCuXTv8+OOPheX9+OOPaNu2LUqWLImMjAw0b94cGzZsAAD88ccf6NatG0qXLo3ixYujYcOGyMrKAgBMnz4dpUqVCqrb/Pnzgx7UZbZO0bz44ouoWLEiSpYsicGDB+Ps2bNBnwd2iTBw4EAMHz4ce/fuhc/nw4UXXqg6zKuYYUtERERERERERBRDihUrhtzcXADAzp078emnn2Lu3LlITEwEAHTt2hVlypRBVlYWMjMz8Z///Aft27fHb7/9hjJlyqB///5o1qwZJk+ejMTERGzZsqUwC3bYsGE4f/48Vq9ejeLFi2Pr1q0oUaKEofqZqVMkn376KUaPHo233noLrVu3xocffog33ngDtWrVUh3/9ddfR+3atfH222/jhx9+QGJiIlJSUsKGeRUDtkRERERERERERDHi+++/x8cff4z27dsDAM6fP48PP/wQ5cuXBwAsX74cP//8Mw4dOoTU1FQAwIQJEzB//nzMmTMHd999N/bu3YtHHnkEF110EQCgbt26heXv3bsXPXv2xCWXXAIAmkHRSMzUKZKJEydi0KBBuOuuuwAA48aNw9KlS8OybBWZmZkoWbIkEhMTUalSpcLhasO8iAFbIiIiIiIiIiIqsu69F/jrL2emVbUqENLtrC5ffvklSpQogby8POTm5qJ79+548803MWnSJNSoUaMwMAoAGzduxD///IOyZcsGlZGTk4Pff/8dADBixAjcdddd+PDDD3Hdddehd+/eqF27NgDg/vvvx7333ovFixfjuuuuQ8+ePdG4cWND9TVTp0h+/fVXDBkyJGhYq1atsGLFCkP1ihUM2BIRERERERERUZFlJoDqtLZt22Ly5MlITk5GlSpVgh7iVbx48aBxCwoKULlyZaxcuTKsHKX/2TFjxqBfv3746quv8PXXX2P06NH45JNPcNNNN+Guu+5Cp06d8NVXX2Hx4sUYP348XnnlFQwfPhwJCQmQJCmoTKVrhkBm6kR+DNgSERERERERERF5WPHixVGnTh1d41566aU4ePAgkpKSIj5Yq169eqhXrx4eeugh9O3bF9OmTcNNN90EAKhevTqGDBmCIUOG4IknnsA777yD4cOHo3z58jh16hROnz5dGJTdsmWLsDppufjii/Htt99iwIABhcO+/fZbw+XEigS3K0BERERERERERERiXHfddWjVqhV69OiBRYsWYc+ePVi3bh2eeuopbNiwATk5ObjvvvuwcuVK/PHHH/jmm2/www8/4OKLLwYAPPjgg1i0aBF2796NTZs2Yfny5YWfXXHFFUhPT8eoUaOwc+dOfPzxx5g+fbrlOkXzwAMPYOrUqZg6dSp+++03jB49Gr/88oul+eRlDNgSERERERERueDee4Hx492uBRHFG5/Ph6ysLFxzzTUYNGgQ6tWrh1tvvRV79uxBxYoVkZiYiKNHj2LAgAGoV68e+vTpg86dO2Ps2LEAgPz8fAwbNgwXX3wxrr/+etSvXx+TJk0CAJQpUwYfffQRsrKycMkll2DmzJkYM2aM5TpFc8stt+CZZ57BY489hubNm+OPP/7Avffea2k+eZlPCu14goJkZ2cjMzMTJ0+eREZGhtvVsVVubi6ysrLQpUuXoL5QiCj2cHsmih/cnoniB7dnCnXVVUC9esC0aW7XhIzi9hx7zp49i927d6NmzZpIS0tzuzrkIQUFBcjOzkZGRgYSEhIiritOxQmZYUtERERERERERETkEQzYEhERERERERERkWsaNmyIEiVKqP7NmDHD7eo5LsntChAREREREREREVHRlZWVhdzcXNXP9PRxG28YsCUiIiIiIiIiIiLX1KhRw+0qeAq7RCAiIiIiIiIiIiLyCAZsiYiIiIiIiIioSJAkye0qkMd5YR1hwJaIiIiIiIiIiOJacnIyAODMmTMu14S8TllHlHXGDezDloiIiIiIiIiI4lpiYiJKlSqFQ4cOAQDS09Ph8/lcrhV5QUFBAc6fP4+cnBycPXsWhw4dQqlSpZCYmOhanRiwJSIiIiIiIiKiuFepUiUAKAzaEgFyFwg5OTkoVqwYfD4fSpUqVbiuuIUBWyIiIiIiIiIiins+nw+VK1dGhQoVkJub63Z1yCNyc3OxevVqtGnTBsWKFXM1s1bBgC0RERERERERERUZiYmJngjKkTckJiYiLy8Pqampnlkv+NAxIiIiIiIiIiIiIo9gwJaIiIiIiIiIiIjIIxiwJSIiIiIiInKJJLldAyIi8hoGbImIiIiIiIhc4PO5XQMiIvIiBmyJiIiIiIiIiIiIPIIBWyIiIiIiIiIiIiKPYMCWiIiIiIiIiIiIyCMYsCUiIiIiIiIiIiLyCAZsiYiIiIiIiIiIiDyCAVsiIiIiIiIiIiIij2DAloiIiIiIiIiIiMgjGLAlIiIiIiIiIiIi8ggGbImIiIiIiIiIiIg8ggFbIiIiIiIiIiIiIo9gwJaIiIiIiIiIiIjIIxiwJSIiIiIiIiIiIvIIBmyJiIiIiIiIiIiIPIIBWyIiIiIiIiIiIiKPYMCWiIiIiIiIyCWS5HYNiIjIaxiwJSIiIiIiInKBz+d2DYiIyIsYsCUiIiIiIiIiIiLyCAZsiYiIiIiIiIiIiDyCAVsiIiIiIiIiIiIij2DAloiIiIiIiIiIiMgjGLAlIiIiIiIiIiIi8ggGbImIiIiIiIiIiIg8ggFbIiIiIiIiIiIiIo9gwJaIiIiIiIiIiIjIIxiwJSIiIiIiIiIiIvIIBmyJiIiIiIiIiIiIPIIBWyIiIiIiIiIiIiKPiLmA7aRJk1CzZk2kpaWhefPmWLNmTcTxz507hyeffBI1atRAamoqateujalTpzpUWyIiIiIiIiIiIiL9ktyugBGzZs3Cgw8+iEmTJuGqq67Cf/7zH3Tu3Blbt27FBRdcoPqdPn364O+//8Z7772HOnXq4NChQ8jLy3O45kRERERERERERETRxVTA9tVXX8XgwYNx1113AQAmTpyIRYsWYfLkyRg/fnzY+AsXLsSqVauwa9culClTBgBw4YUXOlllIiIiIiIiIiIiIt1ipkuE8+fPY+PGjejYsWPQ8I4dO2LdunWq3/n888/RokULvPzyy6hatSrq1auHkSNHIicnx4kqExEREREREUUkSW7XgIiIvCZmMmyPHDmC/Px8VKxYMWh4xYoVcfDgQdXv7Nq1C2vXrkVaWho+++wzHDlyBEOHDsWxY8c0+7E9d+4czp07V/h/dnY2ACA3Nxe5ubmCfo03Kb8v3n8nUVHA7ZkofnB7Joof3J4pXCIKCoDc3Hy3K0IGcXsmih9GtmentvmYCdgqfD5f0P+SJIUNUxQUFMDn82HGjBnIzMwEIHer0KtXL7z11lsoVqxY2HfGjx+PsWPHhg1fvHgx0tPTBfwC71uyZInbVSAiQbg9E8UPbs9E8YPbMymOHbsKSUk5yMra5HZVyCRuz0TxQ8/2fObMGQdqEkMB23LlyiExMTEsm/bQoUNhWbeKypUro2rVqoXBWgC4+OKLIUkS9u3bh7p164Z954knnsCIESMK/8/Ozkb16tXRsWNHZGRkCPo13pSbm4slS5agQ4cOSE5Odrs6RGQBt2ei+MHtmSh+cHumUBMmJKJqVaBLl0puV4UM4vZMFD+MbM/Knfh2i5mAbUpKCpo3b44lS5bgpptuKhy+ZMkSdO/eXfU7V111FWbPno1//vkHJUqUAAD89ttvSEhIQLVq1VS/k5qaitTU1LDhycnJRWYnXJR+K1G84/ZMFD+4PRPFD27PpPD5gIQEIDk5Zh4vQyG4PRPFDz3bs1Pbe0wdFUaMGIF3330XU6dOxa+//oqHHnoIe/fuxZAhQwDI2bEDBgwoHL9fv34oW7Ys7rzzTmzduhWrV6/GI488gkGDBql2h0BERERERERERETkppjJsAWAW265BUePHsWzzz6LAwcOoFGjRsjKykKNGjUAAAcOHMDevXsLxy9RogSWLFmC4cOHo0WLFihbtiz69OmDcePGufUTiIiIiIiIiIiIiDTFVMAWAIYOHYqhQ4eqfjZ9+vSwYRdddBE7ASciIiIiIiIiIqKYEFNdIhARERERERERERHFMwZsiYiIiIiIiIiIiDyCAVsiIiIiIiIiIiIij2DAloiIiIiIiIiIiMgjGLAlIiIiIiIiIiIi8ggGbImIiIiIiIiIiIg8ggFbIiIiIiIiIiIiIo9gwJaIiIiIiIjIJZLkdg2IiMhrGLAlIiIiIiIicoHP53YNiIjIixiwJSIiIiIiIiIiIvIIBmyJiIiIiIiIiIiIPIIBWyIiIiIiIiIiIiKPYMCWiIiIiIiIiIiIyCMYsCUiIiIiIiIiIiLyCAZsiYiIiIiIiIiIiDyCAVsiIiIiIiIiIiIij2DAloiIiIiIiIiIiMgjGLAlIiIiIiIiIiIi8ggGbImIiIiIiIiIiIg8ggFbIiIiIiIiIiIiIo9gwJaIiIiIiIiIiIjIIxiwJSIiIiIiIiIiIvIIBmyJiIiIiIiIiIiIPIIBWyIiIiIiIiKXSJLbNSAiIq9hwJaIiIiIiIjIBT6f2zUgIiIvYsCWiIiIiIiIiIiIyCMYsCUiIiIiIiIiIiLyCAZsiYiIiIiIiIiIiDyCAVsiIiIiIiIiIiIij2DAloiIiIiIiIiIiMgjGLAlIiIiIiIiIiIi8ggGbImIiIiIiIiIiIg8ggFbIiIiIiIiIiIiIo9gwJaIiIiIiIiIiIjIIxiwJSIiIiIiIiIiIvIIBmyJiIiIiIiIiIiIPIIBWyIiIiIiIiIiIiKPYMCWiIiIiIiIiIiIyCMYsCUiIiIiIiJyiSS5XQMiIvIaBmyJiIiIiIiIXODzuV0DIiLyIgZsiYiIiIiIiIiIiDyCAVsiIiIiIiIiIiIij2DAloiIiIiIiIiIiMgjGLAlIiIiIiIiIiIi8ggGbImIiIiIiIiIiIg8ggFbIiIi8qw9e9yuARERERERkbMYsCUiIiLPqlnT7RoQERERERE5iwFbIiIiojhw7Bhw5IjbtSAiIiIiIquS3K4AEREREVl3773AyZPAwoVu14SIiIiIiKxghi0RERFRHCgoACTJ7VoQxZaOHd2uAREREVE4BmyJiIiIiKhIWrLE7RoQERERhWPAloiIiIiIiIiIiMgjGLAlIiIiIiIiIiIi8ggGbImIiIiIiIiIiIg8ggFbIiIiIiIiIpfwgZFERBSKAVsiIiIiIiIiF/h8bteAiIi8iAFbIiIiIiIiIiIiIo9gwJaIiIiIiIiIiIjIIxiwJYpxCxcCzZu7XQsiIiIiIjKK/dcSEZEaBmyJYtyBA8CmTW7XgoiIvIAX/kREsYf92LrjvvuA2bPdrgURkToGbImIiIjiAC/4iYj0+fprYMIEt2tBbvviC+Cnn9yuBRGROgZsiYiIiIiIqMhYvhx47z23a0FERKSNAVsiIqIY89VXzAwiIiIiIiKKVwzYEhERxZilS4Fp09yuBREREREREdmBAVsiIiIiiogPuCQiIiIicg4DtkREREQU0ZQpQPfubteCiIiIiKhoYMCWiIiIiIiIiIiIyCMYsCUiIiIiIiIiIiLyCAZsiYiIiIiIiIiIiDyCAVuiGOfzuV0DIiIiIiIiIiIShQFbIiIiojghSW7XgIiIjOK+m4iIQjFgS0RERBQHeMcFEVHs4b6biIjUMGBLRERERERERERE5BEM2BIRERFRVLxll4iIiIjIGQzYEhERxSAGz8hJvGWXiIiIiMg5DNgSERHFGAbPiIiIiIiI4hcDtkREREREREQUs1auBE6ccLsWRETiMGBLRERERERERDGrbVtgyRK3a0FEJA4DtkREREREREREREQewYAtERERERERERERkUcwYEsU4/jwISIiIiIiIiKi+MGALREREREREREREZFHMGBLROSwl18G7r/f7VoQUTySpNgsm4iIiIiI/JLcrgARUVHzyy/Arl1u14KI4o2dXeSw+x0iijdshCIe24jIy5hhS0RERERERERFDgP3RORVDNgSERERERERuYRBQyIiCsWALRERUQzixR0REVHs4235RESkJuYCtpMmTULNmjWRlpaG5s2bY82aNbq+98033yApKQlNmza1t4JEREQ248UdERGReTyOEhGR18VUwHbWrFl48MEH8eSTT2Lz5s1o3bo1OnfujL1790b83smTJzFgwAC0b9/eoZoSERERERERERERGRdTAdtXX30VgwcPxl133YWLL74YEydORPXq1TF58uSI37vnnnvQr18/tGrVyqGaEhERERERERERERmX5HYF9Dp//jw2btyIxx9/PGh4x44dsW7dOs3vTZs2Db///js++ugjjBs3Lup0zp07h3PnzhX+n52dDQDIzc1Fbm6uydrHBuX3xfvvjDd5eT4ASVxuMaSgIBEFBUBubr5t0+D2HN8KChIgSQnIzc1zuyoOSC7y67He7bmgIBGSZM++JT8/AUBRWeeoaHF2H8Pjszfk53vnOCpJ9p8XFg3JyMvLQ26ukU7+k5CfX4Dc3AJTU+T2TBQ/jGzPTm3zMROwPXLkCPLz81GxYsWg4RUrVsTBgwdVv7Njxw48/vjjWLNmDZKS9P3U8ePHY+zYsWHDFy9ejPT0dOMVj0FLlixxuwpkwM8/VwdwKbKystyuCun011/NcPx4cWRlrbV9Wtye49OuXQ1x+nRFZGUtd7sqDujO/dv/RNueDxxojuzsVGRlaTdkm7VjR33k5FyIrKxFwssmcpc7+xgen921a1cDnD5dyRPH0SNHrkRe3jlkZW10uyoxrjs2b96M9PT9ur9x5kwH/P77n8jK2mZpytyeieKHnu35zJkzDtQkhgK2Cl9ID/GSJIUNA4D8/Hz069cPY8eORb169XSX/8QTT2DEiBGF/2dnZ6N69ero2LEjMjIyzFc8BuTm5mLJkiXo0KEDkpOT3a4O6XT0qLz+d+nSxeWakF5z5ybi3Dl7lxm35/i2cmUCtm9PKDLbfVH5nVr0bs8zZiQiJcWe+bVpUwJWrSo66xwVLU6u1zw+e8Pq1QnYutUb+7TXX09E+fJAly4Vo49METVr1gxdujTVPX56ehJq166DLl1qmZoet2ei+GFke1buxLdbzARsy5Urh8TExLBs2kOHDoVl3QLAqVOnsGHDBmzevBn33XcfAKCgoACSJCEpKQmLFy9Gu3btwr6XmpqK1NTUsOHJyclFZidclH5rPFCSx72+zFq2BL791u1aeENCgvx04uRk+7sR5/Ycn/zrUNFYtkXld0YTbXtOSFDGE79vSUz014Eo3rixXvP47K7ERO8cR30+ef/txHlhvEtKSoLRRZqYmIjk5ERL0+X2TBQ/9GzPTm3vMXNUSElJQfPmzcPSk5csWYIrr7wybPyMjAz8/PPP2LJlS+HfkCFDUL9+fWzZsgVXXHGFU1UnIgDffed2DYjMW2t/7xVElqnccERERERERDEoZjJsAWDEiBG4/fbb0aJFC7Rq1Qpvv/029u7diyFDhgCQuzP466+/8MEHHyAhIQGNGjUK+n6FChWQlpYWNpyIiCiS1q0BycgzLIiIiIiIiIhMiqmA7S233IKjR4/i2WefxYEDB9CoUSNkZWWhRo0aAIADBw5g7969LteSiIisePllYMQIf3cfREREREREREVJzHSJoBg6dCj27NmDc+fOYePGjbjmmmsKP5s+fTpWrlyp+d0xY8Zgy5Yt9leSiIhMe+wxICfH7VoQERERERERuSPmArZERETELhqIiIiIiIjiFQO2REQuYLCNrODDpYiIiIiIiOIXA7ZUZCxe7HYNiGQMthFRLGJDExEReRmPU0QUTxiwpSKjUye3a2APBv+IiMhuPNYQEdmHgUYiIgrFgC0RERERkUP27XO7BkTkJWwQIyIiNQzYEhERERE5pHp1t2tARERERF7HgC0REXkObw0kIiIiIiKioooBWyIiIqI4wcYOIiIiIqLYx4AtERERURyIxX4QT58Gzp1zuxZEVBSxgYti8bhJREUHA7ZERC7gRQIREdCtG/DMM27XgoiIiIjIWxiwJSJyGFvziSjQF18A27a5XQt3HD8O/POP27UgIiIiIvIWBmyJiIiIXDRkCDBrltu1iE7vnQEHDthbDyIiIiKieMeALRERUQxitxrkJCN3BlSpYl89iIiIROL5FBF5FQO2RETkOTx5jozdarjn6FG3a0BERERERPGOAVuiGMfADRGRc8qVA/bscbsWRERkBc+fjXv1VfY5TkTkJAZsiYiIiAzIz3e7BkRERM56+GHgzz/drgURUdGRZOZL586dw/fff489e/bgzJkzKF++PJo1a4aaNWuKrh8RERERxTF2gUJEREREFMxQwHbdunV48803MX/+fJw/fx6lSpVCsWLFcOzYMZw7dw61atXC3XffjSFDhqBkyZJ21ZmIKOYxQEFEgYrqPoG3JRMRERERhdPdJUL37t3Rq1cvVK1aFYsWLcKpU6dw9OhR7Nu3D2fOnMGOHTvw1FNPYdmyZahXrx6WLFliZ72JiGIWAxREFEjkPqGoBn6JiIzw2r7Sa/UhIiL36c6w7dixI2bPno2UlBTVz2vVqoVatWrhjjvuwC+//IL9+/cLqyQRERERRcbGICKi2MN9NxERqdGdYTts2DCkpKQgPz8fq1atwvHjxzXHbdiwITp06CCkgkREJNbMmcDvv7tdi8iYaULkHL3BAm6XRERERETO0B2wVSQmJqJTp044ceKEDdUhIiK7DRwILFzodi2IKJYwA4yIiNhwR0TkHMMBWwC45JJLsGvXLtF1ISIiIiIiIiIiIirSTAVsn3/+eYwcORJffvklDhw4gOzs7KA/IiIiIiIiIiIiih1XX+12DUih+6Fjga6//noAwI033ghfwD1ykiTB5/MhPz9fTO2IKCrepkpUNPG2RIoXXJeJiIiIvOGbb9yuASlMBWxXrFghuh5ERESkExtq4k9RDVpyXSYiIiIiCmcqYNumTRvR9SAiKlKKanCGiMIxaElERGQdz6+JKJ6YCtgqzpw5g7179+L8+fNBwxs3bmypUkRE8YzBmeh4wk1ERERERERFlamA7eHDh3HnnXfi66+/Vv2cfdgSERERERERERERGZdg5ksPPvggjh8/jm+//RbFihXDwoUL8f7776Nu3br4/PPPRdeRiFxw9KjbNSAiIi9h5jsRUdHG4wARkXNMZdguX74cCxYswGWXXYaEhATUqFEDHTp0QEZGBsaPH4+uXbuKricROaxcOZ6UERHFGrv22+zKhYiIiIjIOaYybE+fPo0KFSoAAMqUKYPDhw8DAC655BJs2rRJXO2IiIiIKK6xcZCI3MB9D7Exkoi8zFTAtn79+ti+fTsAoGnTpvjPf/6Dv/76C1OmTEHlypWFVpCIiIgo3okKHMTaxWes1ZeIiIiIyAmmukR48MEHceDAAQDA6NGj0alTJ8yYMQMpKSmYPn26yPoRERERxTUGLYmIiIjIiuxsYMgQ4OOP3a4JiWIqYNu/f//C982aNcOePXuwbds2XHDBBShXrpywyhERxSvehkexbswY+aSwUiW3a0JERBTbeF5IRFYdPQrMnMmAbTwx1SVCIEmSUKxYMVx66aUM1hIR6cBsuuh44eJ9Y8cC/+sdiYiIiEzieSEREakxHbB977330KhRI6SlpSEtLQ2NGjXCu+++K7JuREREpIFBbSIiInJSvJ17xNvvIaL4YqpLhKeffhqvvfYahg8fjlatWgEA1q9fj4ceegh79uzBuHHjhFaSiIiI/JiNQ0REREREFL9MBWwnT56Md955B3379i0cduONN6Jx48YYPnw4A7ZEGj7/HLjxRrdrQUSxjhkhFE+4PhORG9j4SUREXmaqS4T8/Hy0aNEibHjz5s2Rl5dnuVJE8ap7d7drQETxghea8SUWgpZ21JHrMRERERFROFMB29tuuw2TJ08OG/7222+jf//+litFREREVFTEQtAyFupIRKQX92lEROR1urtEGDFiROF7n8+Hd999F4sXL0bLli0BAN9++y3+/PNPDBgwQHwtiYiIiCgquzJ1YyEDmIiIiKioYkNU/NEdsN28eXPQ/82bNwcA/P777wCA8uXLo3z58vjll18EVo+IiIoiBoeIjLP7RJ0XAkREREREztAdsF2xYoWd9SAiKlIYkCQiIiKiWMLzVyIi55jqw5aIiMxjlhrFC164ERERERERiac7w/bmm2/G9OnTkZGRgZtvvjniuPPmzbNcMSLSh8E/IiIiIiIiIqL4oTtgm5mZCd//IkOZmZm2VYiIiIioqCnK2cpF+bcTERUFM2cCffu6XQsiotiiO2A7bdo01fdEREREZF5RvlOiKP92IqKiol8/BmyJ7MZzqvhjqg/b3bt3Y8eOHWHDd+zYgT179litExEREUXBrERyGtc5IiIiIiJnmArYDhw4EOvWrQsb/t1332HgwIFW60RERDbzeuDF6/VzG1vQyWlc54iIiIiInGMqYLt582ZcddVVYcNbtmyJLVu2WK0TERHZiIEXIiIiIu+IlYbqWKknEVE8MBWw9fl8OHXqVNjwkydPIj8/33KliIjiHU94iYiIiIgN6UREpMZUwLZ169YYP358UHA2Pz8f48ePx9VXXy2sckRERERERERERERFSZKZL7388su45pprUL9+fbRu3RoAsGbNGmRnZ2P58uVCK0hEFI+YTUFEgURl3cdi9n4s1pmIiIjIS3h9GX9MZdg2aNAAP/30E/r06YNDhw7h1KlTGDBgALZt24ZGjRqJriMRERFR3BJ1gh2LJ+qxWGciig9sLCIeg4jIy0xl2AJAlSpV8MILL4isCxEREcUQXuwSERERERGJZyrDFpC7QLjttttw5ZVX4q+//gIAfPjhh1i7dq2wyhFRdGwZJiIiIiIiIiKKH6YCtnPnzkWnTp1QrFgxbNq0CefOnQMAnDp1ilm3RERkGTM3ibyH2yURWdG2LZCT43YtyAoeB4iInGMqYDtu3DhMmTIF77zzDpKTkwuHX3nlldi0aZOwyhERERGR+3g3B1HRcPgwMGiQPWWvXAmcPWtP2URERPHGVMB2+/btuOaaa8KGZ2Rk4MSJE1brREQU95ihQERERF6zbx8wbZrbtSAiIiJTAdvKlStj586dYcPXrl2LWrVqWa4UEVE8Y6YaicCgf3zh8iQiIiIis3iNGX9MBWzvuecePPDAA/juu+/g8/mwf/9+zJgxAyNHjsTQoUNF15GIiIgC8IQsvhT15clgNRERERFRsCQzX3r00Udx8uRJtG3bFmfPnsU111yD1NRUjBw5Evfdd5/oOhIRURFT1ANYREUFt3UiIiIionCmArYA8Pzzz+PJJ5/E1q1bUVBQgAYNGqBEiRIi60ZERERERORpBQVy4wMbIIhiD+/yICKvMtUlgiI9PR0tWrTA5ZdfzmAtEREJw5NnInO47VAsmTgROHbM7VpY16QJMHeu27UQg0FnioTHGCIi5+jOsL355pt1Fzpv3jxTlSEiIqLYwQs3b2GghWLNQw8Bl10GXHWV2zWxZts24OhRt2tBRnhtf8njKRERhdKdYZuZmVn4l5GRgWXLlmHDhg2Fn2/cuBHLli1DZmamLRUlInVeO+EkIqL4xIBCfMnIAP7+2+1aEBHP5YlIBO5L4o/uDNtp06YVvn/sscfQp08fTJkyBYmJiQCA/Px8DB06FBkZGeJrSURERBTHvB4M5UVA/Dl1Cjhzxu1aEBEREZEaU33YTp06FSNHjiwM1gJAYmIiRowYgalTpwqrHBFRvPJ6cIaIyClO7w/Hj3d2ekRERERERpkK2Obl5eHXX38NG/7rr7+ioKDAcqWIiOIZM9WIKBT3C84ZNcrtGhB5F/dFRKSYMwcYO9btWhAVXbq7RAh05513YtCgQdi5cydatmwJAPj222/x4osv4s477xRaQSIiIiKKXwwQERERec833wBLlwKjR7tdE6KiyVTAdsKECahUqRJee+01HDhwAABQuXJlPProo3j44YeFVpCIiIoedhlBREREoY4dA0qXZkMPETnP5wOys4GSJcWVWbGiHBivU0dcmRQ/TAVsExIS8Oijj+LRRx9FdnY2APBhY0QUN+rWBXbscLsWRJExqE1EVnE/Qk6zus6VLQts2QI0aSKkOmQQ9xlU1OXliS3v0CHg5EmxZVL8MBWwDcRALRHFm5073a4BUWTMLHIX5z8RkXtEB0zcxiCoOJyXVJTx/DT+6H7o2PXXX49169ZFHe/UqVN46aWX8NZbb1mqGBERERFRPGJQgbyqqFzwe20bjJX5Hiv1JCKKB7ozbHv37o0+ffqgZMmSuPHGG9GiRQtUqVIFaWlpOH78OLZu3Yq1a9ciKysLN9xwA/71r3/ZWW8iIiJymdcueJ1ix++OhXkZC3Wk2MP1ioiIiCic7oDt4MGDcfvtt2POnDmYNWsW3nnnHZw4cQIA4PP50KBBA3Tq1AkbN25E/fr17aovEVFccPMClRfHRN4iMmPJru3bzqwq7pOIiIiIiIIZ6sM2JSUF/fr1Q79+/QAAJ0+eRE5ODsqWLYvk5GRbKkhEkfHWpNjDZUZEdojFfUss1pmI3CWqkYeNRcRjEBnF/QY5ydJDxzIzM5GZmSmqLkRE5ACenBIRERERERF5l+6HjhERETmFrddERPbjvpZCsVGXIuE+g8i7uP+OPwzYEhEREREREREREXkEA7ZEREREREQUE+IxyzMefxMREVnDgC0RERGRy3ixXrRweccfLlMyK95vY+a2QURkjumA7YkTJ/Duu+/iiSeewLFjxwAAmzZtwl9//SWsckRERETxLt4v1qPhxTwRERHFAp6zkJOSzHzpp59+wnXXXYfMzEzs2bMH//d//4cyZcrgs88+wx9//IEPPvhAdD2JiIgoAE8YyWl2rHNFPVhN5DXcJomIiLzBVIbtiBEjMHDgQOzYsQNpaWmFwzt37ozVq1cLqxwRUbxisI2s4AU1OY3rXHzisYiIiIjIm0wFbH/44Qfcc889YcOrVq2KgwcPWq5UJJMmTULNmjWRlpaG5s2bY82aNZrjzps3Dx06dED58uWRkZGBVq1aYdGiRbbWj4goGgY+omMQgYioaIiH/T2P686Kh3UmVnHeExE5x1TANi0tDdnZ2WHDt2/fjvLly1uulJZZs2bhwQcfxJNPPonNmzejdevW6Ny5M/bu3as6/urVq9GhQwdkZWVh48aNaNu2Lbp164bNmzfbVkciIiIit/Bimoi8jPsoIiIifUwFbLt3745nn30Wubm5AACfz4e9e/fi8ccfR8+ePYVWMNCrr76KwYMH46677sLFF1+MiRMnonr16pg8ebLq+BMnTsSjjz6Kyy67DHXr1sULL7yAunXr4osvvrCtjkROK8pZHbt2uV0DIiLvKMrHAyIiIjPYiEBG2LG+cB0kLaYCthMmTMDhw4dRoUIF5OTkoE2bNqhTpw5KliyJ559/XnQdAQDnz5/Hxo0b0bFjx6DhHTt2xLp163SVUVBQgFOnTqFMmTJ2VJGIHFa7tts1ICISgyfrROQFbPghIiLyhiQzX8rIyMDatWuxfPlybNq0CQUFBbj00ktx3XXXia5foSNHjiA/Px8VK1YMGl6xYkXd/ea+8sorOH36NPr06aM5zrlz53Du3LnC/5WuH3JzcwsziuOV8vvi93cme+C3ia9DXp4PQJINv010Xe2Y/3YtU3vXlYKCBEhSAnJz82ybRuTtOQn5+QXIzS2wbfrWJP9vn+t2PQJ5Yf/hl5+fAMDedSi6ZOTl5SE31+5Io7fmvR3rp88XeZvUe3wuKEiEJAG5ufkGaxB9Hhtb5/QvM0lKREGBmTpb4fY6JU8/wVTahPh6uLt5ObUfiVwH6+uD/uOq18+35WrZe35lrWgx64w3jqMyd/aDZiQjL8/48pMbJJ3Y75pZN6ydE3t9e7bKiWuWUFOn+jBokFdbse04boo7Dorbf7t9nuQOI9uzU/PHcMA2Ly8PaWlp2LJlC9q1a4d27drZUS9NvpBmX0mSwoapmTlzJsaMGYMFCxagQoUKmuONHz8eY8eODRu+ePFipKenG69wDFqyZInbVbBJd2RlZcVdHTZvrgLgMht+m+i62jH/7Vqm9q4rf/zRGNnZpZGVtcq2aSjUtueCghvwyy+/ICtrt+3TN6c7li1bhtKlz0Uf1TFe2H/4/f77xThzpiqyspa6WIvu+O6773D27BHbp+OleQ90x8qVK7F9+xlhJZ4+3R67dh1AVtbWiONFOz7v29cMx48XR1bWWoM1iD6Pt22rg9zcusjK+lpIeYrjx1vjzz//QVaWk88XcHud6o6vvspCYqKLVfhfPVatWoXffjvtah3Wr1+P7OxjrtbB6vogSd3w3//+F1lZe3R/x6vn23v3lgTQzrbzqyVLliAjw8qFbnd88806HD583FJNdu9ugNOnKyMra5mlckQ4fLglTp3KR1bWD25XJYruWLv2Gxw4cNLQt+SArbnt7MiRNJQte1Zn5nd3bNmyBSVL/qW7/NOnr8OuXX8hK+tXw3UL5NXt2arduxvh1KnyyMpa4dg0hwzpjkqVFjg2PWO6Y+nSpcjIOC+0zG+++QZ//33CcknHjqUB6CRg/+32eZK79GzPZ86Iuw6IxCdJxm/Cq127NubNm4cmTZrYUSdV58+fR3p6OmbPno2bbrqpcPgDDzyALVu2YNUq7cDHrFmzcOedd2L27Nno2rVrxOmoZdhWr14dR44cQUZGhvUf4mG5ublYsmQJOnTogOTkZLerI1xKSjLOn3e3pciOOsye7UP//knCyxVdVzt+u13L1O51ZfjwBHz3XQK+/97eDFut7blkySS89FIBhg71ZoZtSkoy9u7NRaVKbtfEzwv7j0BPPZWA2bMTsH27e5lBKSnJWLgwD+3a2ZsF4bV5n5KSjF9/zRXaJUuDBkno3r0A48drZ9jqOT4PHpyI338HVq40lqWlZx6/8koCXnopAYcORV/njCyzNm0SUbcu8O67zmWWub1OpaQkIycn1/WAbUpKMn75JRd167pbh+XL83D11e5lU4lYH4oXT8JrrxXg7rv1Zdh6+Xz7l1+AZs3sO786cCAXZctaK2Pt2jxcfrm1dWbUqATMn5+ArVvdz7C94YZEFC8OzJrl7QzblJRkfPddLpo1M/Y9SQJSU82tUykpydi0KReNGukb98MP83DLLfrXjYsuSkLPngV4/nnzGbZe3p6tGjkyAcuWJWDzZue2E7eP0ZGkpCRj//5clCsntsz16/PQvLn14+CBA0CNGtbnn5eXgZ2MbM/Z2dkoV64cTp48aWuc0FSXCE899RSeeOIJfPTRR471B5uSkoLmzZtjyZIlQQHbJUuWoHv37prfmzlzJgYNGoSZM2dGDdYCQGpqKlJTU8OGJycnx+VOWE08/1Yv/C7RdUhKsqdcO8qMhTraXS6AwttgnVgftbbnxMREJCe7nt6lKSkpGR7YXIN4Yf+hUAI9btcpKSnJkeXk9u8MJW9XYsvUs01GOz4nJMj9TyYnG7/XPto8TkyUL7r1Lgu94/l8cr3N1NkKt9ep5ORk1wO2Sj3c3ryc2o9EImJ9MHJcVbYlt9dDNUqV7Dy/slq0iHXGK8dRwL39oBmJicaXn5IeZnZeGzknNLNuiDgn9ur2bJX/vMLZ3+bleWnHcVPUcVDk/tvLy8BuerZnp+aPqYDtG2+8gZ07d6JKlSqoUaMGihcvHvT5pk2bhFQu1IgRI3D77bejRYsWaNWqFd5++23s3bsXQ4YMAQA88cQT+Ouvv/DBBx8AkIO1AwYMwOuvv46WLVsW9nVbrFgxZGZm2lJHIqJo+EAPIoo13G8RiXPTTd09m73EbZ2ISBsfEktOMhWw7dGjh+Bq6HPLLbfg6NGjePbZZ3HgwAE0atQIWVlZqFGjBgDgwIED2Lt3b+H4//nPf5CXl4dhw4Zh2LBhhcPvuOMOTJ8+3enqExEREREREREREUVkKmA7evRo0fXQbejQoRg6dKjqZ6FB2JUrV9pfITIkLw+YPRvo29ftmhARxTYvtPB7oQ7xgvOSiipmdJJR8bi/jMffJAr3EURUVHm/oxyKK0ePAv36uV0LIqLYxouX+MLlSUUZA1VU1PEYIA73J0QUT0xl2CYkJMAX4ciSn+/tJ1wSxROe5BERkSIWL1Zjsc7xgvOeiIi08BgRWxgXiD+mArafffZZ0P+5ubnYvHkz3n//fYwdO1ZIxYjilSRxZ0pEROLF4rElFussAi+CyauK6jZJRETkNaYCtt27dw8b1qtXLzRs2BCzZs3C4MGDLVeMiIiKLgYziIiIyE481zAu3uYZGyjIqHjbBsjbhPZhe8UVV2Dp0qUiiyQiiks82BMREcWPeDmu2/07RATI4mVeE8WCeNne/vwT2LLF7VoQGSMsYJuTk4M333wT1apVE1UkEVFcYms+EcWieLloIyL3cD9CRvG8mUSYOBHo29ftWhAZY6pLhNKlSwc9dEySJJw6dQrp6en46KOPhFWOiKw7cgQoXhwoVsztmhARkRavBzF4wUxERERE5BxTAdvXXnstKGCbkJCA8uXL44orrkDp0qWFVY7ij9cvSOPRlVcCt98OPP202zUhIiI1DIYSkVFdugBZWeLL5f6IiNzCWAFRMFMB24EDBwquBpG7GjQAtm51ZlqS5OzJcE4OkJfn3PSIiIiM8PoF2rx5QM2aQLNmbtdEPK/Pe9L29ddu14CIKLZ49Zgnql5scIs/pvqwXbhwIdauXVv4/1tvvYWmTZuiX79+OH78uLDKETnl11/droF9vHpgIndxvSARuB6p272bDWV6xcLFxWOPAZ984nYtyMu4L3QW53fREgvHCfI+UesR9z/kJFMB20ceeQTZ2dkAgJ9//hkjRoxAly5dsGvXLowYMUJoBYnIOp7oxIe//hJTDtcHIjEKCtSH16oFLFrkbF3IPvF8ccbjgTicl+RFWscps9zYH8bzPpiIKBJTAdvdu3ejQYMGAIC5c+eiW7dueOGFFzBp0iR8zftziDwl8CRHknjSE6vOnAGqVbP/gnDlSuD998199+xZ4PRpMfXgehod55H7EhO1t0kuH4qE64dfPMyLSMfme+4xV+bp00B+vrnvEikSE92uARERmWUqYJuSkoIzZ84AAJYuXYqOHTsCAMqUKVOYeUvxY+VKYP16t2tBWvQE8D76SH4dPhx4+GF760P2COiFBn362DeduXOBV181993HHgNuvllsfUidkcD9jTcCJ07YVhUKcdtt8ms8BKFI9vvvbteAYtnbb5v7XrNmwJQpYuuiBzOFyWu4TrrLyflv97mTiPK5PpKTTAVsr776aowYMQLPPfccvv/+e3Tt2hUA8Ntvv6FatWpCK0juGzcOeP318OF79zpfFzJOkvwXm7t3AwsWANdfb73c7dvldYDdVgP//jfwzDPGvmP0hCHw5GD2bGPfdco//wAnT7pdCwr1xRfAsWNu16LomDFDfjW6jUcaf9KkBJw7J5+yRbu9lYFi64YP979fvFh+9fnkP85fd+zZAxw65HYtnLVjB3DffdbK2LCB+38iIoCBVopNpgK2//73v5GUlIQ5c+Zg8uTJqFq1KgDg66+/xvUiIkHkKQkJcpAv0D//ADVquFOfWCf6Ys9IeT6ffNEjom/FgQOBwYOBMmWslxXrvvsOWLVK//hmThjcPsnYvBnYty942PTp8sWgwu06kjbRfdjFgjffNJ8tbtYrr5j7XrRt58EHE3HgQHEA8u2t58+bK8eqohKs/Pe//b+1U6fgz+JtHhj9PUaOdSLdfDMwenTwMFFd8BjhxO9v21ZcWa1aebeRl8gL4m2fTrFJ1Pkbr8Xij6mA7QUXXIAvv/wSP/74IwYPHlw4/LXXXsMbb7whrHLkDT6f3Dfle+/JAZu5c/0Ht6lTjZVl9aB44gTw7rvWyihqQue5qMDNt9/yKeiKM2fsz2BROwD/8YccSHVCr17AW28FD3v6aeDzz4FBg+Qs7t9/l4PXZD+R2Zvxavly+c8uu3b53/t8cl+TI0f6h4me57NmXVT4Xul2IZSdy7moXQTk5ACHD/v/P3dOfv3zT+DXX92pkxdcey3Qsydw8KCz0928Gdi2zf//L78AJUo4WwdA/v1m7NgBPPKIvnFXrjQ3DS1Fcf+vl5f2a24tp/Ll5fNJL7N7OXlpPfAazptwRXWfKkm8s9YNpgK2mzZtws8//1z4/4IFC9CjRw+MGjUK57XSPihmJfxvLbnrLqB6dTlwU66cPGzwYP97J1x9NfB//+fc9OLNV1+JKefAAfnVqwfxgwe1M9BE27MHmDcP+O9/7Z1Ogsre+vnngdtvFz8tPSciixbJDTjPPQdMmwbUqSP+ItOInBw5899pr70m3wK/fz/w/fdAgwZyPbZvt/9hMZG2v9On5X22wumTy2++kZeJ0/74A3jnHfm9JNm7j6pdO/j/mTOD/xc9z7/7rlLh+0i3hnt1vxxJtHkVeFv4889rB6yt+ve//ec0zz4LNGni/2ziRPn11lvlv2uuked1Uewfet48OXDt5PkfIB9jlHXFqfn++OPA33/LGb5XX22+nOeeAyZMMPdd0Q1PR46IK+v0aX95P/0EPPmkuLJjzVdfAU88Ye67bu63jxwBTp2yVoYb51+k3+7d4XfJeVWk84FLL7VWdix2a7RqFZCb6/8/J8d8v+hWrV/PO2vdYCpge8899+C3334DAOzatQu33nor0tPTMXv2bDz66KNCK0juU7voDgyGHT3qXF1++cW5aYWqUsX+aQTO14YNgfbt5YCg1yjLQdQJ5tmz8gWgKLVq+R+0ZrfA2yPt7L91587wYe+8Y98tofv3yycIkiRnBgHy/82aye/d6P3mzBl5nVMCJ4r16+XMpV69nK/TvHly8LpGDbmv719/lU8oL7oISEryZ+U57dQp+a4IhdMnqFdfDfzwgzPTCpzHa9YAd98t/96CAvWGDruENp688orY7aSgIMH2hiE36DmOBGb379snb2cPPCC+Lq+/7j+neeklf+NkoG+/ldetNWvk///3DF4hJk4Eli3T/vySS+TXU6fkoLGb/vUvZ8//FMqdPVaCp0a89JJ8/P3sM7khyqwPPzT/3fbtzX1v8GD1O6HKl4/8PT3bZEGBfP7x3HNy/aZPlxs4XnjBVFU9qWdPfedYSsD622+Bjz+2t06hRF0jWD2fL1kS+Plneb244gpj3129Ovo4sfAgKj1++02eVmgDr90GD5YfDOyUEyfka1or+0w1WncVnjtnvb9vkXw+cXehXntt8DXgH38A99wjpmyj2B+6O0xdyvz2229o2rQpAGD27Nm45ppr8PHHH2P69OmYO3euyPqRB7jVX1kguzPVQv33v0CbNsG3vKpduImWmiq//vgjsHWrnFVRs6a1MpWTkGHDgocHttYZNXCg/JqdLb9aDSL8/rt8Yhzojz/kkz8zcnKAWbPCh3/6qfgshsCTvFKlxJS5ZIn/ATdKf8N33x08jnKhLDqTOC9PDtZWrQp07y43HNSrJwcljh4FtmyJXoaIbjfUTp6VwMhDDwUPv/JKOXiyaBHwySfOZqokJsr7p7w8/4WaEuAGgLQ0uU6A9QwWI0Ln3513+t9v3iwHue0WGCwN7QddpLQ0/63ryjQTEoCvv/avC0eOOLMPD7R2LbBihdgyL700GUBw39FOcSsrJTAb8NAhYMoUeXtTeuDauFHctBIT9Y0XeMwTOV+efRa47rrgYefPA19+GTzdEyfUj3F2CwzGKcee7Gxn18eUFPlhuAon+ucODQ47sS3s3m29DLVuy5YssV4uIG8rVavK2+LZs8HHGLfNng3MmSMvp337zDdsz5sXuSG+dWu5gaV8+eDrBbtUrux/L0nyOZHVawTF2LH612ut8S67TD7//v57Y3fYtGkjv+bkyOuSl/z0k9zVkagM4vr15VvK+/WT+9l/+mkx5arJzpb3l4C8zJxqwB47FihdWn6GwNVXAzfcYO/0vvpKvqMstNs2K06fNn+XmJJUYmSbctLx4+avrwOvY44ckeMVZD9Tm64kSSj43xnS0qVL0aVLFwBA9erVcUTkfTZUJKllpCUlBf9vx8W/slPdskXOYlm9Ghg1Sr61+fvvxU8v1OTJ8mvv3sD/2kOE+Ptv+VV50rXC7EnRnDnAX3/J75WLtPvusxYkCz0obtsGDB3qDwybsXixfEH5wAPyBcWgQcAtt5gvD5DXg23bgoOkyhPhRerY0f++Sxf1A75yK+r+/WKnPWWKPxj89df+vhoPHpRvgQWAPn0ilyHiQlNNpIabn36SX/v2lV8rVpSDkuvWAVddZU99ALlBa+/eyOPs2iUHlDMy7KtHqNAgxvr18nZwyy1yBvCVV4qZTqST0cDsux495HVo3z65DqIyj+fPl1/nzJEvqAL7UM7L8++XypeXu6vIyXG36w5R3HjYEuDObbuBF8pKA5ayvQNAixbipqU3YBtI5AWZ2nH511+Bbt2CGxyysuRXpdHULufO+acFBN/urpyHLVggB2qcfLBhYJAjMdF/TuIU0VljamrVsvb90OPw6tXynSiB5xdWnTwpZx7/76ZL0/LzgfR0OZFgxQp9mWmRtrsPPpD/atWSu3IL7B7IKLVjVb168uvatf4Glvx8uSEh2vmAGefPy9cjgf1G33QTkJkpbhqzZ8sBvRMngE2bzJVx7py/X2mjx/hPPpHXAa0HWrvVZcSvv8p3y5QsKW5fryzH776T1xlRD0fNz5eTX5SA4dmz8jZ16pT8mRMB20WL/A1qSvcgorrjU+zdKy8L5Zrk7beNXYtFW45vvy2vx+np5uqnJJUcOyY3svh81u8iVdZ/SbK2P3vnHXnfaPYaIHDeffAB0LWr+bqQfqY23RYtWmDcuHH48MMPsWrVKnT939LavXs3KlasKLSCVPSkpQEDBsgHsuuv9x/YAg8027aJb7V6+GH5JFG55RuQM1guukjsg5206j10qPw6Z464aQUKvaX+pZfMlTN+fPgwq1nYStBFueC7/Xb5ItHqCdqpU3IWVnKy3M+qFfn58m1eF18sH/Byc+WWxaVLrZUbjdO3dUei3Krr1hOnA9eHn3+W9w9aWZOHDsknJFddJQdt7TzZX7s28uerV8v9XQJygOX8+ch9kIqg7GcCpzN2rJxlrhg40N4HB/boEfxwpsqV5YvnTz+V9/Mi3HST/Dp0qJw5Fvrc0/nzg7MS09PFPoE9Gnbrb51yy+/+/eH7QtFBQicDtmrfC5z+wYNA//7+BlylW6bz5/0NsUuX2rtve/jh6BdkAwbIr24+tKhaNbkB2Y4+3dXEwnYdeBfVvffKjYZ2PLTXTGZp6Lq/fbs/u7JdO/mczcp6nZ8v/15l36F1d4ueaQQGzn0+4MYb5btoQu+esDOT7vPPg8+9p06VG0rsOH6/+SbQvLn1coxeFyiN7XafGxkVuFwHDJC7vTCqoEA+X1Xma8OGwWUHNopF8tlnwXcXKL78Ul43//pLDgw+9ZRctlJ+Roa8Pfh8chZqYHdZIsyf739mwPXXq6+XIo9TNWrIx8cLLgDGjJG3D73bn556WAkwBzYwnz3rP1aH3kVq1uOPm28wlCT/3ZoFBeYafJRzruPH5fdO3jlYlJkKA0ycOBGbNm3CfffdhyeffBJ16tQBAMyZMwdXikrboSLtww/lA86iRf5bugJ3xo8/Hp4xapaStffaa9oHsSFDxEzLS8ycdNhFuUj96Sf5IkM5wFntE1bkxXxgf1N5eUCrVtYyob14m4wodgUQAstdtEj+s5KF7RQlKxCQT5BSU+UMYDsp2VXVq/uHhZ7ov/++/Q/La9BAO+Paat+fSlcTiptvVh9P6ffT67T2CWZvXfMqIw1QkuTvl65qVfnW1EBmAqyRmJnXIvflyu/ZsUNu4FDrD/PKK4HRo+X3od3DmBGp/kpj6syZ0btRsZoRalXLlnLf9YFZ9naJxeP3mTPefUCectu20rBpRU6OfHdQ4G+1ei74zz/+848vvpBf27ULHidS39NW9e7tfz9smL3Ptnj/fTHl9OgR/H8sbjNA8J1dH30kn/sbtWCBfB4Ymrms7N/1rjurV6v3favcaadkJ58+LR9nQ8ddsEA+norK6FXcdJO++RLYXVgketYVpdFs7Fh9ZRoRuMy19h1adQx8bkFolzRWGvpyc+Xv61lXtK7BlDo/+KB8PDBzh46yDMuUkcuz+y4fkpkK2DZu3Bg///wzTp48idHKWSOAf/3rX3hf1J6eijwlc1HribOiMhwCe/GI9lCzbt30H3CcEik4FumWJLMnl3Y8+V25gL/8cjmgpdzmovagLSNEZkYHtiJOnWqt38RYfIq71zzyiPwqquHGDXb2eafMn2j7SeWOAit9WkejtR1a3Zc+/LC173tJpH3Ctm3O1cNOShcZRi7cW7YMPi4H3hIcSHkAmBtEBiKU9UC55VpN4LHHjtuvAyldDfTrJ64bFTUi5qFykd2ypb13DkTipaBUaF1C7wSJdH7k9DmKErAN7SPfzPysXz98mNWAbcmS0cdx6gGjkybJD3oTJfTY//vv8qtTD3nW25OiW+fNeh+sOGRIe82uJJQgv120Gi5DG/SURoytW8XXQU9DWWBXRlZdeKG4skIFZtgajTUcP679mZWHdDZuLCd7BB7/RSQltW1rrCEvcDk/+qj8Gm9JBV5k+kbbEydO4N1338UTTzyBY/97ZNzWrVtxyGv3MpCniDyZFdXCfNll/vdvvhl53C+/jHwhZZZdfb/Z0QofeIuzKMrJRm6u2IBwp07iygpsKbV60iH6ok50P7ZW2XVi7aWLYRGsPm010vwwkmX2wgv+C2Y7iLoVLJTX1vuiwOw2ePCgv99tI+Xq7T9eRGaeWSL3S17KgDSzH1fujol3sXAsCq3j6tXB/4t6+JgIycnqwyOdb6otg2XL/A3+gcycYxs9Pou+zdwpWgEpkcG1SIYPd2Y6Zqmtm2p3Phw8WAJHjqjvNK12yRaNV7pNi8apRo1IfD7t/bfysOdAIuet6Gsjo8+iUfvdK1fKDbJWyrB6NyxFZ2o1/Omnn1C3bl289NJLmDBhAk787wzzs88+wxNKD9NENnvsMTHlqJ3cOS2wX0mRYiGTU5LsfUqqKKKfgi1y2Wj14+oWuxogYuEi2YjQhykaIXL90bqLwW7xtjztYnQ+2TVfRTxY0u6+7dzA9djPK88dtnuZWG1si0RUtpJWEFQxd66Y6YigletjNEFAeQBYKDPLy+itvnZ3L2QXrfM1p/bLXt9/qs0HOxJXrPBCIFSP//zH7RrYL1IQ1cy1msjrO60G4e3b9Zehtr/w+jYcD0wFbEeMGIE777wTO3bsQFrAk0M6d+6M1aFNuEQ2sePWfLfY9cTvQYPsKVckN3b0om6z8wonn86th9UnRgPqyyjeTgpiJSsiHtnZBYSbvBr8nDRJfm3f3t162CHe9ktW2DUvjPZ3bfcyeecd+8oWlUQQ7cGOVm7PFS2wn/dAejPsozHThZXXzqvsojyEKJTSHYoakduXqGVsl+XLw4dpdUHgxLEgljMc9QYfrcxHt4/Hkbo609rPKdTq/tZb2uMb3Udpda9lpHu2orJf9BpTl4s//PAD7rnnnrDhVatWxUGtDsaIBIvVYIfaDjnwqZIihfYH5kVu7PzNPNVSeUK3F7l9ghKqbl17yvXa77RK9AOTSD/lYUrkDCUDKB7b9ONtv+RFZp+KbZdI/RR6RbT1MrA7MLdpnQc6kbWqNZ8CHzwUz0If3qlw6unvXggARWro/Prr8GFafdXaTauesZJh68QzYER3BSjy+G5mnyLyXFXE3bw833GHqZBXWloaslXuFdm+fTvKly9vuVJEelSr5t60Re+w7DphiYWAkBsna2aeTr9ihfh6iOKFE14nxNuJQixsn/FKeVgCkVWxvl8SWX8zx1Y9jD74xe5lYmf5osq2cl4QLVNfdEbfBx+oD7fzwZzRuNVVkFc4FQT0evKNWpBNa/1361hgpXuteBNt32X0LqR589SHm1nWZgK2kR7+F6kvXjVWHpYdSVG5BnWTqd1k9+7d8eyzzyL3f/cU+nw+7N27F48//jh62vV0ESoSjJyU2/105EhEP1jDroN8LBzE3egLKtYvsEOJ/D1eOXlWO+GIt5MCr8zrosiOBzJa5bX90p13xm/XEV7gteUtwvTp9pRrNHhk97y181gk6o6raPPASgapiG6PAmnVJdJvsHsZR7t9Od5dcIEz09G7HN3q7kdtWzey7TiRqcxzSfuI6lMcAIoVE1cWYPw4JKIbHLWHecfbtZkXmdrEJ0yYgMOHD6NChQrIyclBmzZtUKdOHZQsWRLPP/+86DqSy6L1gyWSkY2+Rg376hGNkQ669bDrxDMWDuJu3FoUqW8up4hc5iIPlpGe5K6XXSfW8RbgKOoZtvG2PO3i1nyaPt34U4i1eLVvXRG4HvupPVROD9HrRywHbJ26+J092/x3RScDaC1/0efaRhh96Fi80cp6Fs3r+0+rAdulS8XVBVCfX/F8fHWblxut1641Nr5WH7ZGqO0Xi0r3MW4ydcjNyMjA2rVrsXz5cmzatAkFBQW49NJLcZ3W4zkpptWvD/z4o5iyRB6Y3ex9Q3R/piNHii1PEemJzcWL2zPNWOD2wzZEn1yJvMCrX1/7ic1u8/qJvVGx0KASjZVlsm0b0KyZuLrEOq39Qryt9/GGy8fPri4RsrLsKdcsI41tRo/PotYnO9dL0Y2NDDh5j1PnJ17ff6ptv1oNU3b/Fq3tJB7OJQNZmY96ukQwUr7IxinRjXFVq4otTw+1h6CdOOF4NYocw6thXl4e0tLSsGXLFrRr1w7t2rWzo17kIVo7ts6dgQsvBPbts39aasxmcogQD+n/om/NIPeIXB9TUsSVJZrXT+yNireTbKPWrwf69nW7Ft4XD8ebaBdRsbxte6HukuSNoFf16vaU+/nnxsa3e5mUKqV/XKPZR6KOC3bOA9HHrtq1xWR/xTov7EsUGRnOTMdLv1mN2vZrJOvS679Pj3j4DWZdeaX57950E/DZZ/7/s7KAxx6zXidFerq4svRSa5R1s6/xosLwITcpKQk1atRAPvOfiwy1HXVBgbwTmjhR7LTWr9c/rpsHECu3SHjlwOeVTdgLF5mxTuQ6dfXV4soSbedOt2sgVrwGbGMhwNixo9s10M/NY0Zo/2121MXMMcDNLpFCObV8GjTQ/uynn5ypQzR27dOMZjl5qUsEo+daovafdmepifTVV2LLi0VW5qkd63u/fs5Mz+t92Kq56CL94/75p3318LpHHgHGjXN2mqLXEyvXyqF1MRLj8Cq141PDhs7Xo6gxdWr11FNP4YknnsCxY8dE14c8LPBE3OcDUlPFZ+ONGaN/XDcvYitUcG/aocwenLzcLw+5J1JQQK+tW62XobZ9r1gRPqxDh/BhycnOPeHYCi8++EoEva3tbl6AVavm3rSNcvNYd9VV/veRlteyZUDbttqfR/qumd9nVyanGR99ZG/569YBx4/LT4sePFh9HJF3Ollhdl2N9j2j+wo3ArZadQy8G+yRR6KXHQtdInjhgbYifp9XEiisEvk7lAcHOnV81psk4KVlVbOm+nC1On73nb110Zqu28aOBZ5+Ovbv5jT6QMRu3fzvfT5g9Gj/uKKvu40u90suUR9upGuFAQPCh3nheBDvTAVs33jjDaxZswZVqlRB/fr1cemllwb9UXxRdghOHBDOn9c/rptZXPHQViHqScSxyIsnN1Z47ffMm+fMdM6dAxYvDh8uSXJjktrTTJ1y/DjQp0/kceL1GZ16s/3syMa7+ebg/8uUAf7zn/DxOncWP227eG37VnPddcDKlea/bzQ44NTtunr88Ye4svr1A/7+O3hYq1b+W/ADgxurVvn7G3ciO0/tlvVXXjFXllHRzvdCLz28tM0Y7b5rzhwx05UkoFEjMWWFCg3CHDwovyrBvmi8tHyMciNL7s471YcrxzEr87NiRaB9e/n9888Dd9whv3cq0GbllnO3WOkSoUkTa+fIasu6Th31cdevVz//sVOrVvJrnz5AyZL+fXdmpn3TlCR5PTYyvl5GM2wDj8U+n7FENCP+7//01SFQYAO8onVrY8/R6d49fFgs789jhanLpe7du2PkyJF44okn0K9fP3Tv3j3oj+KLkxuikYCtXbf0q3WevWpV8P8XX2zPtEPF6y3TgT7+2O0aWLNunfwq8qLdKKPbaKTxAz8rUQL497+N18ep1tbADH8lq/Puu/2/YfRoZ+qhqFdPfn3rLTnAMmtW5PGtZrBY3TeHBoZE0do3hz6ssWRJ8dN+6SX5VQnoffqpvE6IprXsrGR+ai1PngzLAi98Pv1Ufh0xQuw06tc3/h2RmWgffxz5gU7KunDNNfKf8vBVJ7LhAtdtZV/34IPyU6NPnQqun2iBfca2aOF/rzTYTZliz3S1GPmdx48bK3vhwuD/zQZdp00D/vtf+b2RW7j1CP39SrAknvokVzv/3rsXaNnS///FF4t/AJuaadOA++/3///uu/K55/jx8v9WtrtHHwWefFJ+37q1/DppkjuZkYG/MZSXukSw8tDBLVuAcuXk98OGGZuu1jwoXVp9eMuWwec/HToAaWnGpqmIto4pDU3r1snjKvucMmXkVyPzLNq0rrsuvKuFIUPkV6vryauvAr//7v/faINb4PlvaF3atDFfr0CbN8sBcKPbfZMm8nkDAFx/vfxqNM8yNdV/XfjEE/LrhRcaK4OMMxUOGjNmDEaPHq35R2RW797+988+G/xZYMfdgH1BIbVWQGUH5zTlYiwWmF0e2dny6+OP+0+E9+4VUyeRlP682rSRW9eVvh2V1mTRJ7fZ2UDPnnLLeWg/kiJEOqlp3Fh+veIK4wdzN1x4of8WtcAnwLZoIZ8c20nJRilVyn8i7MSFhd5paDWI3Hab3LVLly7i6qRQGt6UE8JQSuBHxD5840b/+5o15YfXJCUBJ0/KwwLnU2BXNnYEltq1M7/virQ8c3KMleXFW4XNlBd4oTR5MjBqlPz+jz+A4sXl9w88YL1ugbZv1zeenX19B64LoduQMh9DG5Ht9u238gNOlFv6lXOihAS54aVEieD6iXbLLf73gUEd5RbPyy4LHl9kPQJvcTVT/urVxqYXui8w23C/e7f/fWqq/72ZRthQgb+/bFn/e9HHviuusPb9X381/93A+b5+vXx7t3LsUo4vc+cCL77oH8/OgHVgRt3gwfK5Z5Mm8oONrK7vynJTygk8j4o0fiC17USPwGxVN556b8Ttt8vru1ZGq9o8C2zoUhI7AoO4FSsC114rrIqF1yTDh/uHBV7DJieLm1Ygrf3UDTfIryL3ydWqyY0MgV0Eibob+KGHgveXRpPDlPE7dgzfTpo3N1+vdu383c01bWpuX1uqlD+A//XX8us11xibZ4EPOFW60GNSgf0MnQacOXMGw4YNQ9WqVVGhQgX069cPR44csatu5BEiu0QIzRwINX++/32XLsHZJKG3zdgRFHnuueD/+/f3v7/lFmDJEvHTVFO9utxi+uGHzkzPrMB+nMxmGTRpIr+OHw8sXSq/r15d/dYNo+rXl0+yP/pIPolRAmpm1uWEBPn77dvLAaFGjYIDKaL7nStZUm6x3rFDntY99wSPl57uP7lVLpbNTEdt+KOP+t+3ahXeeFKsGPDGG8bLtiowQ1OpIxB8YRq4X0hO9q9fdklMlE98rrvO/7vVbs06elR+0vmff/r713UisBt6Afnaa/Krsm/56ivxmbYbNsivWVn+YenpckbEhg2Rb+UyyucDmjWT3+/aJf+vdbtipHXWrLvu8r+vXVt+FX3LrJGAjah1SvQT25WMWCMC+6G+5BL/heYFF/iH27EN1aoVfRy9fftGEmk/uWiRetlOZmErDXeAP3D28svO1wMIvqupbt3gz5Tj8Ecf+TNK7b6ANFJ+4P5Iz/dCG2jMnlsFBmYCA0RKFmUk0dbpwN8Rqe9qMwK7Cgq9KyOawHOhTp2sZRYH7ncbNAg+D1Lu4Lj4Yvl2YuXJ70pDkh2UQFDoOhQtuBqN2nfNllmpEvDmm8a+ozzp/o03goOMXlS+PPDCC/Lv1Csw4Kccu+rVkxu/JAmoXNn63UaBy0o5Jwk831G2Z58PuPxya9MySqmbyG4M335bfq1d299gpCwTEf2hB5ZhNGCrJAao1cNsEtb118vPCVDubFGY2UZDt+3SpY2X4/PJ111OdplZ1BkK2I4ePRrTp09H165dceutt2LJkiW499577aobeYTIDTHw4lbN99/73we2RKllkygHeVFuugno2tX/v9LiuWaN/PrJJ3JQxqpo83PpUjlL69gx662udmYBAcDDD/vfi7gtLPBkV0S/Vlu2yCfZ/fvLt+lYDRQFtiwCwbcWieyWQE3oE3sTEvwnKEbnvd4nQCsXSy1ayP1RTZwY/n2tLEo7BAYQtJ5K2q+f/Vm1gSRJ3lcVL+5fpqH9qHbqJN8W1q2bnBmgdOXg5C1+v/0m35qrduuc6L7Fjh4N/r+gADh9Wu6Hr3lzsQ9tLCjQvy316iVuuso0r73Wv20qfcW1bBl8t4ioaQFAyZLOnBmL7iP+wIHIn6stw9AHnaqx43ZkvRd0ysWXHRcryjapN2Brhxo15AbDUDfeKH/mpFtvlV+3bAk+N/T5/Mfh/v39xwXR88nKcc7qnQQiAraAfA5rh9mz/e+tHtMuu8x/my0QOViitoxvucV/14ieB7xFEjjfozWavfgicPasfdmLgPat2SICtkYzbLVs3+6/NV0vZd7Wqxf5TjUvdIlw773G541aA3LlynLjV+D81ktt2sqwn35S//w//5H3mz6fff1at2unPlx0wLZbN/92FrgslPVOz7IxsvyMPqC2YUM5bhB6vTh8uD+5wIixY9X7wRW1PZh9oOeFFzJQ6yRDAdt58+bhvffew9tvv4033ngDX331FebPn498uzoTJU9x62D511/yq3JSXlAgZ1JEC/4aNW9e8M5U2dnaHfQMJfJhKmb7KtJLmV//+pf20yejCd3hT50qv4pY37R+v5WMKK3vGjlwiXhieuB6IjK4Ejj9adPk186d5f5Yb7pJ/v+pp+SA+osvytmlTmVFBNZN6zdnZppfF80IXCdKlAjvgqBhQ+1+Me3cp4YGGMqWlW+HcmI/Hpp9EjpNIw+HiCY/X14GQ4eqfx54IWpHcK98eX9wNvB3hjawWBG4rv/nP/n417/Ele0FetZJZZzQfqGrVAFE3+jl8wHPPCO/lyT5NthAyi2uSlBV9EVLYqL/94ZmhTud2aqWSbZggXbmot0XcE2ayBfrZhoArFBuH/32W+PlK7eN6qX0+agw2yVC4B1QBQX+foBFdZkS2l93uXLWn7vw/ffB+wOj5zaBx2PlQVpmBR4v9OyjUlPtPb46EbBV5ne0MrU+y8gw3kChlNWhg7HvOU2S5K4QIs2bSMFULUbWmWjXH8nJ6tOrX18OsPl8/juBRIvW8H/JJcHPnYhE7/ocuCxCGx2sUMoYOza4/3S1cbSGh14v1qtnbv/o82l/T1SikNkuEczWg4wztOr8+eefaB1wL83ll1+OpKQk7N+/X3jFyDvc3hCVLD8lQOXzydm18fpALtGZTXZSsmBHjjSfNffLL8H/az0N1witLgJE3L4hImAbiVY5odNt397fZYfobVSZltaJ9xNPyK31ym2ADRsGX9yIPGHSGqa1nTjdsKScvCh/oV0QRAry210vxalT4UEAOynrgt3HjowMOevarXkMyP2UqenRQ1z/z4HrepMmki39Dlth1zErcP1Rlm+fPuHjBfahKUrgzWMffOB//9RTcl3uuQeYPl0eJno9z8z0/97Qi2s7ArZmvqv1HafOX5RAstPbvdI1hJGGfCNPlAf8v6l7d7nhx2xD0xVXAK+/Lr/Xc+w0Qm35Hz4s/rzcTMBW1I2f//zjf++F6w2tvsxFBmxFlWl0+kD0eaxWnx07gIMH/c/CsEPnzsH/G503kZJwRJ67PPus3JCmVaYyvHNnuZ9Wpyjz6l//kgOgIqktC9HrrZmgqFIvEYFNvdeEeqlt60brExocdztOVBQYOgTl5+cjJaR5JCkpCXlGH6FHMeXsWbdroM7uHYRbQYDAE1SRT5EP/D333KN+i4Ub1q1TH27HBaidF7V2r4+B68JHH8m3iCpZhSKnbbYsny/4yap2CNw2vHKCEBiw1aL1mVP7l8AGDC/cVihq2bVpI2fRG9lXKw2AItcfrWmHdg1hlv8hbrtRt675ZZiXF9wvrBlq882uIN2PP/rfO7XeXnON3BAW+juVW+2VC7FatcT0s64lUsOg1sW4k5zO9DXK7npoNVCrTdfsJdL8+XKjqdlgYWBd8vP9DyOyq0HVDmYCtqEP9rHyoB+FF46bWv3jeqlLBLPTN6tePfkBTHZez4Sug0bnjRONWJKk744PkVmoeoVeh4pkJmBrpA9bK0HR0GO123d2RhrfaDkM2DrP0I0LkiRh4MCBSA14fN7Zs2cxZMgQFA84ksybN09cDcl1e/a4XYNwdp9MSJIcDHCDVt+cZmjNI5HZAqK7plDYGbA1W7bIA2ekaagJnG7gw/DGjRMfsDV6+40yXM/DeqyYMMH/3osZtmZPeuzgdpBYDzdO8v76S9w8UJ6KrVVekyb+p0LroTU/QrNhzNZ/9Ghg8+bgh8EZoTVdu3rF2rQp+rRFu/lm+RgcuixWr5b7lw+9I8QukfbBTm7DRqfllf2Lly4grWSA33673Pf4N9+Y+37gre5Kpp+eAFK05ejlgG1o3UV0M+aF9VrrdnI7AravvCL3s9qjh/lyjUxfD61lUFAAzJwJvPqqPfVQC9gaKUPvOmxl3x66DCM16rm1Lttx3W42w9ZIPawERUVl2KotM5EZtmbnh5eOs/HOUMD2jjvuCBt22223CasMeVOVKoDXer1wovXXjR1RrVrGTy7N9IeakGDt9119NbB2rfz+nXfMlxOJ1zJsle+L6kso0jSMsOskyInvGLV7t39aXgzYqtXJrRMaIwFb0fMsWj9lReUkz8jD3ET0YxfNsWPA33+b+24kdgVs3eoeSG1bLlNG7o5hzBj7b8FU6mCEXdtUrG6rXjo/VPqNNHMHiogH3QLBXfW4da5iRqR9gN5bha30XV6jhtzo5oUuEbSIOAcMDdj++qv8oFInWK374cNi6qHF6nmdnuNYQoI8np51VW3aerI51QLzTrAzUBxa5ogRztw9FYkyn0PrYSSzV0Q99JbPLhFig6GA7TTlCTRUpGRmejNgG6u0dmw1a4r/XcpDIa65Rn5VDiJWTz6//hooWTJ4mOi6251BbeY7TmTYatGarnKiJ4rZeeME5XdabXAQKTBgG+lzr3CiLtdfL2eFOXXbtNvz2OlsZiv775MngSefBJ5/PvJ4gXU/dChyH+VPPmm+PpGI7B5Ir2gXIE7dKuz1gK0d23A0RvqEtnsZGTnmGq1L9+7+h6+KkJjof95AYH3q1DFfpldvl1c7FljZXwY+O8NNVapo330nIsNW7b3T+1yvMtIlgtEMW2V9NRKw1RItw1YZx811We+yNpvx6ZWuPJR5LCrD1sxnWqx2qcSArTsMPsuRiiKvbogi63XhherDnTqwdesGXHwxILo3kSZNgOXLgbZt5f8DDyJuXHCpSUwUn6FlZ4at210iTJ4cPtxrGbZ27TMCA7ZezLDVk/kQyI0TZyem6fMBFStGH8/qevLFF/5y3AxwOb18rZT755/ACy9ED9gGOnw4csB2yRLz9YlE6bsXcL4bgEj7FzvPiZRuNrQ43Thh9Fjq9D7NreCD0YCtkXp26QIEPN/ZNGUZHTsW3MAu4iJbacC205Ah/oe86WU0YBttuSif6w362rU+Nm+u/RBYO7pEeO01uX94J+jdlryyrVu5hVzrMyNJCNECblr7G7duZQ/MsBU93dD5pmcaesaxMq+09q8iuruIlkVthpXrPQZsnePhmzzIK+y8ncEs0Tt+L+xsRNyqoEZtB291/olcFzp0UB8uKmNAbbiVh3iICtgaHV+Z7pAh4cPd3hac2n6UC5ZIARUt0QIhZgUGbLVunStqAVutW8ICPxdZF6/NY9HTVh4WpJW1YYSZ7/7735E/37nTXF0Cqa0rSkAe8HaGrdk7HCLtN432YRvrGbZ6XH65/nG9cE6nKCgwvv6KvBjPyFBvULVyZ06k+XvjjebLDdS4MVCqlLHvqG0f/fvLCRFWeDnb1I6AbfnyQOnSkb8jipe2VTVqgTcjdY62nSkZtlYSV0KXYaQuEdxIagDs6xLBzgxbq10iiMiwjVQPUdedVhsgvL4NxwMGbCkmORGkciOTxe7pbdkiv1q9pVxkPe24INQ6QVLKrFnTXLmiAraR5p+ZQK4dGbZKkMjId9Tem6X2m556CnjxReCll/zdfESqhxP0nATbFUwUdTuUHfQEbEVmpXupQVEhqt/D++4zVq7o/cFnn0X+/Nw5a+VrLbvc3Ojj2MFMg5AddVBjR8BWTwaY1eFWPfkkcO+9+se3+wLS6AWusswCH5wpomwzJEnOmG/QwHo5RoYHUluHA55nrTmOnjqFfq9JE+Cmm4yXFVgHvXVxujFN+Z7ogG3oezs5Hez56CNj41vNsNXTJYKIc0G9AVvlvR3q1lWfrtp7syIFQbdvB06ftj4Nq3XWCtharUvoNMwI/Z6ZjHG71yMKx4AtReXFDVL0xZsXfqPI1jit7yt9YFkNJIhq7YvEjgvQ4sWtl2n3bzd6cLar8WLdOu3PQvXoAXz+ubg6aElPl5+4/eCDcvaNGreyVrWWg137lmi/08h6ZNf+1MkLPjcDtm3aAMuWhQ8XmUGst1y7pinKgAH6x3WrD9tI+1Q7Gsi0pqPG6xm2di0no9PzWsDWKDsv9AsKgClTgJ49rZUteh6HnpdGSywwkmgRr8FHQGzANrBMp9gxz7TKPHkSuP12a2WJzrDVmo7R8aIlTTiRYav2oLrAayervzFUaJmffw7MmRP9O3qZbTRSXkOXiZl1XVSikNb4Rn+jWsDWCzGUeMeALUXl9Aap92BaFDJs7WiNBIA9e4Bx48yVp3VruRNZz1a/+8ILxrJ01GgFu+3OyNJaF+14AJfR9b5KFaBjR7F1UKNnm3Tzdi+j+5GUFPvq5WYfv9GCXrVr2zM9t5QsCbRrFz7czIlwpOE+n2SqXMWpU+ayYf/+29z01HTqpH9cNx865lYftoHTUePGeYkXvPCC3P+yXl4L2BpZZiLrHi3TzqxIddRTttr3Qx+4JCrD1mzjpvJd5cFjXmVXhq1TnJxmVpb68EjriJcybPUE7iKdR7ixnKMluxgtK7DuastCxG+zkmEbeP4r6jeLTLQQ0aDFgK3zGLAl3Zy4SBgyBBg/Xl9dRO4gnLz9Uc/B1O5pbd5srVyRBw+tOo4aZa68SGWmpcnBFbPrTs2aQJky5uulh5kMW5Hrr12NBCJYCdjamYEWLcNWq07FitlTJ8C5gG2k36w1z5WnvYvMSo+0fWh9x26iMjmMZNhG8t//mvteaF3eeMP8bYdG6u5GwFaZ1gUXAJ9+qv5Z6PKoVcueOqhRW9dvuslaHYyse9GG2+nHH8OHudVQo7Xf0ztuNHb9ruRkoEQJ+b0djeKAv+sto+rVC/7fbGO06Hl38qTY8kQTGbBV9rlONUwp03eK8juNHL8uvhi47rrgMoxs69ECtpG+q1doMNatDNtorC7raFmrdeuKeWBjYPlmvycqwzZSPaxm2O7aZS2xoFMn4KKLGLB1AgO2FJWTG+KUKUBOTvTxnMjmdCNrK3R6ycn2PCwhM1N8maKXiZ6nzGuxY52VJGDTJu0McJHBJyPsOLF2M8gViZVt0okgstH9iJ1PYQ7NVlLUqQP06mXfdBVOX/C5eRGiRVSdQuej2S5t1AJeeqapBHiU3/PAA8C+ff7PjTQ8GJkngQ9hUfte5cr6y9JLWZdSU4HevcM/D12vJ00Crr5afD2MBGwbNBDXX3KoaP3BB7r0UuCKK+ypB2AsyOJWhq2I7CU7zyVycoCmTcUE+bS+v3evuTIHDgz+38rtyHqHR9OihfZnXgnkijjWxkIQT2QdlWOaHtWry89OCKyHmQzb4cPVPxedhdm9u3pjo9UMW6tJOaJ+Z+CxLrTMHTvMNxgFspJMEZh1Kuo3qxFxLaQ8z8XsHSMXXgj07WuuHmQMA7YUldMp7ydPAq+/HnkcL16cW6U1f9U6cbda5g03aJ886OFUQE+r+wUrrJzcJier//ZRo+QAsx31VUTKILS78cIoL2bY2kWpU9Omxh6E9uyz2uOLkJqqviybNgVmz7ZvukD0DFtAfqidqOCO1npx++3yCaXWd+wmKogmKsM20JVX6h/3n3/Ch91wg/+9ladbR6Jc6H7/vfoDkvbvt2e6kTjVEJGZqf6UdqcbJ7TWYbV5cNttQLly9tXl/PnwYWrzYvBg9wK2WuOWLWus/NDfZfbcIrQcpSFPxHFU9DwWUZ7a9mF2exk3Tl6XtKh1leDGtYmI4Hvoe6u/o6AAuPFG/eN6nZVMSWXcN97Q/szI/I6WGHDBBcHH59Bx3DhHVntvtqzA+rdoEX4t+913kcvQ8/srVTIf+wisY+h6Y0akY76o6zWzAVsz3ydzktyuAHmf0wHbhATg/vvVPzt1yv9eZH3efFNcWWZ17WotOKtFbUefkBD+RF4R0zGzTOzKhtVix8nK88+LK0ur7vXqAW+9FT7cjoCtVxtEvByw/b//U//888/VL9Zr1dLOgnWaE90khLrxRqBUKTHTu+IK9X3nBx9of8eJ45ldGbYiyl2/3tr3d+70v1cLpIUaPhy4/HLtzyPdSnrZZcbqZkW0fYza/taOdalKFeDYsfDhkW53NSvSd8uWBQ4cCB9eurQcGAhk94VbtWr6xktO9l7A9vrrgaeeArp0EVu2FXatM2aCy9dcA/TpEzzMTJcIatvHyZPA0qX6ulsLLcuuzHWRRHWJUKtW8LlKpDK9kiRQubL6/knktNSOv0YyuaMFpI1kvUY7Nun9vpMBNlFBaWV4YDktW8p/er5rdBzAepcIRqcbKTFH77iRqE3fTDkM2DqPAVsyLDfX3vIjnSAF3popcgeh9rTcefPkE3+nXHddcD9JCrM7+EjsOAk1u0zcCA7G4sElIwMYOjR8uJMPHbPzIVl66AnYOn2BFa1ODRs6Vxez7AjY+nxylw/Tp0ceT4SPPjL+HSf2AQMGAJMnWy9HkoCWLQvQuPERANU926ASSfnyQP36wO+/h3+m9XvsytyNxOjx1sqyMLMOJicD6eni6qBHpUrhw7p1Azp3FjcNPfOiWTN9ZTmxfRi58DWT2Wb3bxAR5OvTB7jrLjH1qVEjvIsgUQGJFSuADRvMlWW0Dm5l2Fqh/M7AfbOTv0NtmeXlAUk6IhSZmcYCtoHB01On5Gda6KmflQBVpIDtCy/I3ZQ8+aT+8tToqc/778vnx3q6HRRJ5HW0nm3S7cx/ZfwXXgjuftBqlxJqdRF1zW0mYzywvFi8po41MdB2SG4L3RD1HESt0BNwcWIHUbGi/Q+YspvWPLIa5NNq7TNTZtu25gIukVx+OTB1qvpnIg6aIhhpoY/E53PuoWNVq+rrR9Ctfpv+/NPfJ5NTrGQke+Ukx46LM59P3s/ccYdz0zTCiXnfsqW4blJGjChAy5bylalbASmr5Rk9Rlx0kdg66OWFDFst//d/wC+/hA93el/i84VfiNt9XqZ2nHOqeyYAGDvW/37PHv3fU9Z9vcdpUXW3c1lIktyI3LixuPJCmVmfJEm+c6V/f/+w1q3lcxczdXL7OOUEO7L2jXxfbTy9jXVG70q87Tb/+8A7NiOxGrCNNG7Fiv5um0RkSUdSoYK/yxonjxcXXABkZ4uZbkFB9BhBtHXH7oYzZVm0bet/wG7gZ2bLU+pzySXW6hbKaDlFZb/oNQzYUlROb5jFi0cfJ5Z3Fm5cWIWy2uIp6vYMQD741qhhrT6hKlYE7rxT+3Ozy0DUehepHDMBW6cybIHw7K5Q7dsb6x/TiGi/s1o19brbmRls9uTF7n2YkXXCrgxbPeO5xamLURFlql0wetXCheLKUuvD1W7R1t3Q/a3TyyI1Vc5WDq1TUaAW8FQ7l7ErcPzMM/73RvpPNhqwBew/1xB1G73WZ1bL+/VX8wGJxMTgJICKFYFbb7VeJy+zO9hnlJEAsJlbxwPpDbyG0tsllZGArdngs6gsaT3cWKdLlhSXyCEiw1bE8SFSGXZtTwkJwE8/6atDtLICGW2AYJcIzmPAloL06NHdldsQA1WooG887iCiU5tHBw/K/UdamX9JSf4W02jTi0ZPi6lIsXICrpfog6XVsnr3Dg8oiGL2wuLcOfF1UcRDhq1oen6X29uhiICtyN8QrREn8HM9t3G6RatvXDPzy6vbh5sZtlq8UAfA3nqEnptKkvrT3r12ASlJ8jmO0xm2kUTbFvVsq0b6W4wmdP+gZNeLCEhYOT67fZzSw45gn9tdIhhhtkFe73WHnV0ihE7HynhGlpmZxBARrP5GUQFbI8xk+asxe1wSsbwjlWWmXgzYOo8BW/IcPQc37iD0C92pV6wopluL0KCB2QN6QYHzJ8UiD5qieT3D1k1evYDyYoatET6fuFv3gaKTYevUMgydVnq62OXlBOU3qD1ZXYsbTw93O8NWVMaMG+yuR+3a+uvhpfND5RzH6QzbaPPAalamaCIadEQ3Xntl21KoPYgQsP677egSQS9JAm64Ifp4ogN1Zm+NN5phK7IBW0RWu1v7RycybFu10rcu6SWi8ckqu5MDrO53vXa8jVcM2JLn6O0SgTuI6ES39NlByT5xipUDnxMn75IU3M9WNKIfOmb3rUJWy/XaBVQsBx3tJCKDyy7vvWe9DDcDtnrGt7MukUSrZ5cu+qflVsA2ErVjpxe2Qy/UATBfj2jrzU03AdWriynLTloBG58PqFPHfBlmudElgtnyQokMlojopsEL1LqJEZFhK7pMo9MP7G5EGWZUXp6Y+oRSC1AZofeuVae2R6+t00ZE+5233gpcfHHkMpy400dtGlYybEV2P2O1HHaJ4A4GbClM6I7ByQ2xWzf9/QqJcuONzk7PKKsHV6/f2hQrGbZeZTRzR2+Zbnw3Gi9eQLnVJYJX5kOkAIVXZWbGXoatXnbWyUrZyvzySuA5EjczbN3I1hc1n72077d73VEe3qOHUvd69YCePfV9x83zcD2cyiIzcztyUesSAXA++C5yfQy9BujTx1xdjHbnZ+T2fCvbo8gM20jTsHv/a5WIwJ6eLvT0TENvPUR1O2D1u1oBYBHlm9n2Y2W/GE8E3BhN5Lyi1KJj187fK7fRO51h63VGD4ZeuCXXKV5dV8wGWeyc117LMrMynmii5r1XM2xFTVN0eZF+g9r0vNolAmnzwt0Vdu9bJ0wAmjbVP35gY4VdGcha041UntcybEUEWkXWy0xZbuwf7Ar2Odklgp6MvWhZhnY9f8VIRqGV45jV8yYvNWjZRc/x2Y5zF6Pji86wNfOZFhHbOjNsnceALYUxs3NyWizvIJyut8gDRzSxsEzcyIa0ezpeCb4rRNQnFjM3jfLS9rJihbiy9CwnN5ejiGl7YT/uhUDu6dP6vxvp9mw90/KCDh2AYsWCh3mhnl6og1cybO0+P0xKMh4ccSuYYrZLBD31dSK7XFSwRPStyHYxu+xFB9+dvjPPSgDI6Qxbo/XT+1wWPUQcK2O5MV9Eg6qohBir+0+9IgWAzZSlVo6VjPFYjsfEEgZsybJYbFEu6ryWYes0J7NczNTB6AmFyHlotSy7t8142fa99jv++UdseXp+n5sneVanbcfFfLSLlMDPvbL+3HOPvvHMzG+7MqYiibZcGzaU/xRWu4kQwSvrAlA0MmyV+hgZNxYyNY1wIost2jzQ26gbK10imJ1WUcmw1apPaqr8atcdGU4EbK1ys1FIL1Hbkpn9gpHPrYqUAS362lNEhq3VLhG8fqyKFx68uZS8xqstJ16tl5fYceCwQyycFDtVB6MnXnYEjbwwj9R4aZ31OreDoV7PsPVawNbMPsELjV3Z2cH/R7qwMDq/vPjQMVHfEc0LdfBKY51X6qFQ1n29+x0nlqXbXSKETlvkPs7NLhHc4uaytMpqQFTpJsvOBj4vdYmg9V2v7B/tFG0e2bGPFZXlb1ak63hRZVltgPTC+Ue8Y8CWXNG2rfpwL2VQxAozgZF47xLBjhMSr/w2NV7JllZ4IcsqFnhpnerYUVxZepeTW7/fiwFbo9Nycjv4v/8TU46ZQJcb3GwwM8MLdVC4cUu3E+VZKd+tDNtod/F4Kchn9/7UzG9144G4ZtiRYevFLhGi1cnOLhFC6yE64GdXlnSk8Z3mxHW76PVWZNa7HZn+bmTYhn4nFvaR8YABWwrjxI585Upr32fAVh+teZSQ4J0gnxeyxPRy4sBkJsNWZFaYl7tEiKeArdd+h3JboQhOXKBYISoY4mTA1shw0dOsUUN9nJwcc+Xp5cWHjml9R+T0nfye1e8G8so+TeT5oYhy3Aym2LlM7A6OiFqOsdIlghV2nLc52SVC4MNkzS53vceLBQuMlWs1A1hvINlsAFnhVoat09dwVrtEMBr8NJNha+azSN8RGQDWmoaVcRmPsR8DtuQpejf6WDmJ8gKtHb0bF8NailqXCJE40SWCl29XjySWLqD0iOeTHK8vJ2bYGpu+2vv09PCLUZFdIsTC9uGFjB4vbWteWGaiA7ZWt73ALhH0cqJbh2gZuJF4ISPaiSxqo8uha9fwhxLazY47opzcp4RmMpvdfn/9Vd94CQYjH0YCtmaDWVaDrSKDika/Y+S63WpQWlSXCHrLNtvtgFPnBSKWu5mMcWbYOo8BW4pZojIfnObkNCO1xMZzlwjRxEo99fJChpcT4ilgGy+/Q01R6BJBKccJWvPTqQxbrfdGRZpfauXGSoYtybwy3+wO2CrDjZShBIn0fM9L2cGR2N0lglsZZIHfMVqHhg2BAQOMT8sqqxn2Rtdx0eecIrpEWLJE3/S0tsVIQUIrAWWRfdjqrWMk8Zxhq3fZiMgSNdrgJfpuSFHdNZhtgAwdRvZiwJbCnD4d/L8XN0SRJ+Reuciwi8gDh9Hp6OHF9UuNk7eHOdElQrQyrbCrMYXBlNigZzm53SWCiAxbJ3khw9bnA3Jzgz/76SdjZajR+i2xErD1wjHMC3UAvFEPL2Q9BzLTF6qo36BVjtV9oB0ZtnY1SjnZJYIbxzUR52tuHo+tBkQDy9EjMdF4uXYHbK1m3xtdhrGa5KEnw9YsreXkRPZytPLszqw2Wg4zbJ3HgC2FyctzuwbRiQpSeeHiwg12ZdiaFStdIjhRTzMBW9HTt8LOeeT2hYVodgYN3b4AEzmeaKICtm5n2EYa34hnn41cRqTy9u3TP51YDIRG44X9kRfqAHinHoC9WapWbyE1M03RROwDvRYYFy3ezje02J3dbGb6dgZsExLkB2kamYZXMmwj8XqGrVPXnWaDumayurXKEZ0opVWeiLJEnJfFwrlarEtyuwLkPUkxsFaIOuDE+wlZpFsp7NjB2nmSJZIXDi5ebuH28jbh5boZYfV3eGU+mL1dKx4ybJ268DGSfWamTqNHB/8/cCBQrlz0eqnRczHUrZu+suI9w9bLx4BY5kSXCGbKMFIvM9M8eRLYuhVo1co/XbvYkUUWSvRyVBOtmxazARunWc2WdrrLnUjT11ru0eqjt5ExIcFY0Cq0LDMNNtFYbdBxMwvU6WtJEV0iqNF6OJyZ8kSeG0aavhsZtvEeN/EqZthSmORkt2ugj6gM23jf8Wi1zIm+GPZS5qpXgtFaRF4keHHe2XWiH29BiVi6oDY6bS/vV70YsDW6T7Bz/q5aBWzfHjx9EZQ66627lx6MqcUL67kX6qDwwj7a7oCtnvl97lzkMqJN04wvvgCuvDJ4mNkuEfTUV3RQwq6GkmjlGm0oszItO7BLBH85ejjdJYJWIFBtOtFEahAtChm2ZrNn9VBbTiIbbKys13Zn2FoJ2Hrtjt14xYAtFVIujmJhwxO5g/DSxY5oWvMoISE2lrMdRB807WA0YOulDFt2iaBPvPwONXqXk1v7IC8GbKNNy8jwULt2GZ/ml18an04kerOfAsV7hq1IVjPsRPDKPk30MdFM9mFaWvC4TgT+fvlFfj1yBFixIvr4XlhvFVqBcbcbHhNMXCXHWoYt4H6XCIHz2ey0jQbw9Y5vJEBlNvvV6aC71zNsIzHbABPt+yL7sHW7McsIM2V75VhflDBgS4XmzpW3QC+dxGkRdSIXiydWRonuSycSO1vFvcCJg5Tb88Pt6UcSTwHbeObEBYoVsRiwNXoLZ2DfsrVrG5teaNl65tU110Svl9H5FQsBWy/sj7xQB4UXjh9O3Y5qpAylSwQ7p/nii/LruHFAu3bWM2gjsWP/Z3djr5nvFJUMWyPDRQt9KJ/dGbZqXSJEK9dK/diHrX+6TmTYiuwSwUhXGdG+Z6VukTKrjRDVJUIgtxvWigoGbKnQmTPyq5sbntMHnHgIAJk5oBSlrExR03JquzATMBDdWm7XBYBV8bC9Bornk5x4z7BVynGC1nqv9RsOHACqV5ffP/mk/Prjj+rjKoHWaNOPxmrWi9nMJJJ5YV55ad8san6IyPwMLMNoFqAZr78uv+bnm+8SwWl21sXKOZ/IW6LtZDXD3s27Cpy+xVrpEsGpDFs9AVur2bGiAndmeGk/YqVRTNQD10XPD63yRo0CPv3UeHlWs+nj7TosVjBgS2Fiod84QGzmQzxzMsM2VjiVbRGrvBB81zopjZdlEC+/Q42e5RQPGbZO0nuSnZ8P/PWX//8XXpBf33xTffw1a/zvmzcHli0DcnODxxH9W0+ckB+QpDB6i6Kd3A5emOGlfYnZeSG6CwO7u0QwMp5btyv37GnfdJzIsHX7PLUoZdi6Oe9FBWztyrBV6mSWyOOYiH2MWxm2IsrU8ztFZtiaKS9SHUVee7ZrBzRrZrwsq/VyuoGFZAzYUphY2PBE7iC8dLEjWqQMW9EXw6dOAU89Zfx7sbC+Ac4FC72QYetV8RSwBbw9r63Qu5xiOcPWyXXRSIbt8uXqZWzdGn06mzYB110X3J1CerqxebV7t/rwwN+wZg1w993Ry4qFxuN42h9Z5ZV5IfKYKDIxwK6uNtq2NV4nLzeo6WXlNl6932GGrf3cCNhaKdeLXSK41ShkpCwnAnt6pqE1n0IbqiONq6ceZsoykqjSuTNQs6b1uplZLrFwfIg3DNhSIWUDDD24eDGoIGrH78XfJsLOnf7fpnXg2LMH+PlncdPct087iysap7tEMLrca9f2dsBWNK8ejN2+sBApXn6HmqKQYRvpdmOzjGSVGM1KXb/eXJ3WrNF3wdm6tfw6dap/WKSnY4deHKk9GI0ZtrFVB8Ab9TC7fW/dqu9C2+gt0dG6RFi40NrtuCtXGt9WrO4DnTgWu911jRsZtmZ+rx0Ztk7SG7CNNm+MBmxjtUsEq2XEQoatWVZ+m1rAFvBGQoyddy5aPd9hhq0zGLClMEUpq8XtExW71K0LZGdrf56QIF+IN24sbprxvMNWggleXVe8cEIhugwtXl0GXsP5pE3ECeaVV4qdx2plDR4sB3Ls2p70HOvT0vRNf9Cg8GFXXCEHk5o3lxvzAn/jkSPB427YEP59M7ciWuWFBjOj3AgS2VEPUczWY8wY+XXUKP8wrXlz333a5QR296GUESmrr3Nn4PDhyNPMywPOn9cuQ237A7yzTEIF/sbvvwe++MK9uqhp315u5HIyw9bKshIdfI92jAzsdscqvQHRQ4f8fbNrlaOH1S4RjJ4/GAkMm+XGsdJoWU7d2aRnGlr72FB61pPQcSLd2WqG6DiF3ru1FCdPyt1Y2VUf0ocBWwoTK4E3Ny7OAkXKHoo2TTtMmBD8/1NPiT9w2MGO+eGl36fFSDZdJHa0blqZf3bO+1jZN+ll5+9xc17Z1SVCly7m6hNK1Dpqx7p+7py/gWjqVOCZZ4x1ibB3r/5p/fln9HESEvzTibS81AJSGzcCH38sd7Vw7lzwZ4F954rsO86oH36Q5/dttwEffeTv89fu6SrfmzQJeO45c98XUYd4ZWZ+zJ4tv44f729QOHJE/UJeLSMckAO5LVr4///rL3ldV7ZfrX1GtAz6r78GevfWrvv776sP37hRe3p659H99wNZWXIDkmiffSZvg2rc7Npi+XL5LjSnM2zNcCPDtm9f89PLywtuLFRr0FBbXqdO+bvr6drV/PTNZNgGsqNLBKvdGRhZhrGQYWul0UNklwiRRJqOyHkcadk6cQfCkCHAgAHa32GGrTMYsKUwdmXYhu4UfvhB7n8l8OnVTveFYyVg++WX1qevEJFdMGVK8P///rf8arYvHaOsLA8vd4kQqWuJUKdP6z85kySgf3/55PXWW4EZM/zTczPDy8sH3nhq2fX5gN9/t6dsJ5eh2YsHM8vx66+Nf0fNmTPAG29YL0fkuvjjj8BbbwFz58pdsChP/92+HXj8cf1dIgQ6dMh6vXw+/z7NzAVKpKxAxfHj6sONNoqaWe9vv12e3zNm+ANHTu5/164FVqywVoaX9olm9z2TJ2v3v2yUiPPD8uWB//4XqFEDmDcvvPxIdu70v69WDZg4Ufs7//wTXuZddwGbN4ePu21b1GqHmTRJ+7PFi/WV8eabwC+/APPn+4eJOhbffHPkbGWjRNzyqzDb7Y2VdU+rIUDkNPPz5aDlkiX+YWaOL2b17h3cSFVQYLxLhKysyJ8D4Q9kUj63M8PWbJcIWt+NVI/Q71oN+urVo4e5skSsU9F+p5VpaHVLo/X7jB6vjB6XVq6UG9xEJl4ZWW8Vf/8dfB7n5WvEeMaALYVRNsajR83v/KZOBW66yf9/YDaNYtkyuQV72TL/dPW2cFk5IT971v/eykmn0da4QKVKBddBhN9/B955J7hfWtEZtoG37YUy+zteeEH7gv38eX3lHj0qX1jZQTnZ+vzz6OMuXy5njOjx229y9lluLrB6dfBFnlt+/RXIyfHOLbahhg/3VnDCim3bzGXzBVKbz+3bh18AOe2ll4CDB6OPZ2Q90RP40+vPP+Vjj1V2zON16+TXW26RX5UMOaO3sQFAxYqRP9dTf70ZtlplBWb+aS3D0PKXLgX++EO+VdoIM/14bt8e/n2rfboZ/W7g9Mw23nrhIsrK9jBnjhw0//NP4MAB//AzZ+RyjcwXUQ36l1yiPvzYMeNlKfMmtF5lyiQDkIMFs2b5h//2m/FpGK3P0qWRPwfk7rUA8evXjh3AqlXWyhAZnFVj5jhqdfq//GL8O0anee218rzr2FF+fftt9fHs2qf88Ufw9jxlivmMvcBjSuD+/+OPgS1bgsfdsUN+TUw0VN0weur3wQdyAkdovSKVaYWTGbYLFsjX0co8MHLcNbpOhd6ZI2oaRrpE6NRJvYzt2/0NbqFli9gPPfmknHhld5cI0dbns2fDM+KZYes8BmypkLLB7dolb4lKP1xGbrFU7NkT3CfdNdeEj6McNOfPl/sl6tBBfviCHlZ2XsWK+d9b2RGa3UEVFAT3cabnojSw/5hIHnkEGDo0eJiIDNsFC+TXChWMfS8aZR6qHfQAYNGi8OwWNadOyeupzyd/J5L8/ODMAi1KBoDR5az1WwIFlpmQIF+gvvuuHLz95x9nAgZPPy1ndwVq0EDOYvRKlwh79sgBqx9+iH5LqR4iTiqefx749lv/nQFmAyyBQQkz1ObDk0/KjQZmLjSzs609+EZx5oy8vP7738jjGa3fpZfKrzffbK5egYw+JVrL/v3Rx/nii8j9iYd6663g///4Q34VnQHVrVtw46WWwJNxo10ihDp1Sn24Uu6cOfL0OnYEXnklenla5ZilZPTm5Oj/ztq1wOjR5qcp4mJMkqw1+H3wgT94bfUOK6UfWDOmTgUuuAAYOdI/rEED4+XY3VgVKdCpVY9odTpwQL7TRqG2PYkM4p45o288Zb167DE5UK00SEdab3/9Vd6WI/nmm8gJAEBwdr9VevcNH34o99sNmG/4zM+3ti96/HH/7z53DvjXv6KfZxiZXuB5X7168quZ35mQoO98N9TmzfJ5XeD5hpkA0IYN2uf7Sgbu4cPyedGmTf79u1aXCC+/DIwdK3eNE8hIlwh33JH0v1d52xkzRv+dIkbXmfPng7chI8uwoMDaOlq9ujyPd+yQ55ld0tLkfePSpZG7hFFYCR4aTcL617+ABx+U37/2WvTx9dTt3//2xweU5SkiAWPnTvm8Su0YEq3swP1Zp07yfIqXxJlYwoAtFfrpJ3kLvPbaJEyeDDz7rP+ztDT/BXMotUyqwKwcLUrAds0auV8iJdNWL6sXZ6dPyycboa2wevXpY+57pUvLr8uWAd99B7RsGXn8L77wfyeakyeDT8aee079ZCHazjawGwCfT74FJtrJtR6SJAc59u2T+6Dq0EEeHumkPNptJ6VKBV9gX3995GzYmTPl/n2jeeYZOZienBx93EB6LjBefdX/Xrk42LdPzkxs29b4rU1GHwBx/rwcROrYUZ5X773nn89r1hgLMKnp1cva9wF5+5o4UT7xvfde/3CzJwoiTjBee01ed4YPB5o2tVaW6BbpM2f8Gbvff+9vZNFr1arwblX0CA3CTZ6s/7t65oESWFAyj/RmsEeiHHuUDBiz1G7LVCMiez50v/LDD0C7dtbKfOed6OMkJPinrXanjCJw+9K68NHKbFIyn5RjqiTJt2EbpXWnhl5KlwhG9n/LlgVn6Rrxzz/yby0oAFq1MlcGIGem3nmn8e8px03lYvOii+TjIyDf9WGUz2f+fCrQxx/L5xvr1vkbLIyyM+PHTNnRGhwvu0x+veuuyOOJsmlT5M+1uku4+WY5QzPS+rFzJzBsWOTyt22TzzsiycnRfpgaIJ/r+Xzy+u/zaQe0I83Lc+eCk1IGDPBn9Zm528jnkxtAjHbfI0n+oOxLL8n7yuXL5duRH300+jT1UEsOUY5NRrPulDrffbf8/syZ8GuNaNmRgefWegK2SjdvCmWbiWTLFvm8qH9//3EsUpcICxbI3eQMGiQfxw4elBsgjASUA49/Y8fqOz5s3Aj89FP08QB5n5iXB6Smykk0p08b2yf5fPI+Ntr2F8mRI/Lxq149/d1LGQmmBs7Dq66SrxXnzInewHnkSPTEL59P7i7q1Cl5vVX6K3/ySfVxI1Hm4YgR8rZ66FD4A1aN+Ogjfz2++Ubej0yfrl7e+fPR7/xU1vk9e+REpTfeMH631vffy8t62DD5uPDvfweXcfasnABA9mLAlgolJfnfDx0afCvjVVcFZ6YG+uGH8NtLAy/ytDzyiKlqApB3Fs89pz8jTNkZKf15HT4MlCghH5S3bjVfDyNCp3PdddGDtSKoZQtFO5jccUf4MCW71kq/iAkJQNWq/tbZwO4wtGj1wda2rfx68qSxLBwjF9dXXKF/XEWkC4xonn5aPuiHnphGsmGDnP1iRGAmWffu8kVi+/b+zwNvzXTLpk3A66/LgbrAB6e4mWE7YoT8qtw9YKUuyv7x77/Nl5GbK+8DX3gBKF7cP3zIEHPlmbkds2/f4GzhwOy4SHJz9WXjqQXhzpyxNt+UDBuzD440KtqxMPBuFC2hGdm7dskNfqGUBqBovvjCWH/bQORgeeC2EPqACoVWwNZIRmsk06ZZ+76e5RDKTJBYyWyuUkXuq3jFCjlrX+8dRqGiZbNrUesW5Lbb5AapNm3kQIXdtPbJFSrI551m/POPsborQVK9tOocKUCl1SVCKCUAIOouAC3Ktqi1D4jUv/qqVXKDdqTtRes8UWkkmz49+vquZJqF1jH0vH/4cPm1fv3I5YXKzZUbz/Pz5eCoiLvRFHruvgikdrfDkCFijlHKwyWvuEL79+j9naH1nDlT/m7x4uENmHr6SFauKyIFRJXjgxLQ1mrcUjtvVq67tm0DGjWS36ttW0qjodJ39LRpQEoKULlyeOOEJAGjRmlvy8odkUa6cdJ7Hq8sy8Bgd4kSckO50XXVyN2ze/fK54dG7hqwIrA7p927/e+rVNHuwgOQ18GpU/VNIyNDXm/Ll5ePw1b7UK9UKXI3VD6f3HCgJnBZ/Pijf94q57lq++ldu4KTf9SMHw/cc4+cnKMILUvPPuHbb/3X4r//HlzGmTPWuogkfRiwpUJvvqm9OkRr1apZ0//QJEDfrUxWbnVS6qI3i0zZmSit/soTRs1eICm0bvFUo7f11Kho2UApKeHDol0MfPih9mdqQQIg+OFxoex4uvDKleLLBPRl33qJ0dvYrQS6vMDohZAiO1vu69iMwH6hRVECPYEPcjFizBi54Sk5OTwzwGwAx0iGbeDFSpUqckNFYFZktBO4w4e19yWB1OZP8eLyybFZdgdDQkU71ikXYZEsWKCv0nq6OVBEy7ID9DW+KuMptO7GCGwUtoOerm4A7YsmhZELUbXjazRa9ezc2XhZgYwGd7QCbkrgw2hmuJkLeKXPZpEmTNBuNFCj9oCvSNS2h2+/jfyd0DsP1q2LPLP0zMvQh/8YoQRstRrEn38+ehmffGJ8uka6tFGO9aHr9dNPB/8f2Gii1XVAtEB5YIN1ILN92JrpTzuU3tvNX3vN39ewGjMPqzt2TP3YG9idmwjKsSJSIHDUqOD/I21rodeEyi3rgbS6RIgksE7R7mhTgtCXX66/fEDfNeIHH6gP37LFeB+2gYHQaNQaa5V+9vXy+eQAo10PNgf0HQOVu0gCaf0WtYarl16KPg212ECk3/3AA/73oV3VAerdIkZaf5WuQp56Sg5wB44b2u0WoK9Lh0CBiU9a1/52LueiKOYCtpMmTULNmjWRlpaG5s2bY02ke/QArFq1Cs2bN0daWhpq1aqFKWbu+Swi8vK09/Z6+mR6913/ez1dIlihHHACM+8iSU0N/l+59dEqI8Gyvn3FTDNUtAsTtVv6ne5/JlqLp9lAmh30BJGscCqrT4vayUAoK+uH1SeeRwteRdnla1q50nwfzI0bm/teJMoJnegLIKfMnRv8/7RpwP33+/+PlqX98cf6piPyCeIKKwFbMw1F0U5c3cpO0PNb9N7GGLjP0OreyMrdGXrozRCPtu4Z2f8Z7TIHsO/cyOixxUy3B5GY2ZeJ6Ddbi97GCz0NF4HULsajBT+U464SULz22sitF3rWQaPd3gRSGk9EdHVlhJLJqIdWlzVGu4Dy+Yx11RP6XTOMNJxFEnino1l67noJ3Q6XL1fv1sHKviu0b9hAgXdfvPFGcLapkeOjniBkQoIc0FIygI0ELgH/fjZwXnz2mfudej70kLHx3XpQlJFEJ6OiHQMlyVgChloDkJ6kF7V9V6TM4GjZ2Gp3J0Xq0iJSo/SXXwb/b2YfF9j1Uei1ACB30WT14X4ULKYCtrNmzcKDDz6IJ598Eps3b0br1q3RuXNn7NXI69+9eze6dOmC1q1bY/PmzRg1ahTuv/9+zFVbuygiPRcCgRd/x4/be3Gm7NxE3UoZz9SCE17rMHz9erdr4BcpU9iL9DwQKJCeLiGsrB9WLzACg35qtLpmiTVKI4XR7iy84quvrH1f7XZspygnkmbWczN9dVkJrCjcurhKSFDPyAilZ17a3Tgh6u6BSLeDi5jmp58a/44eRtdnrWwts5QuY4ywuh+JxGqfxlrU+ukV3ehi98WulX2gFUaCYxMnyq+hdTSbuWVmH2p2WoEZc3rYuX/Xk7mpdZu0lT7qQw0cqP1Z6HXK7Nn+90aC33oaYxMS5LsHlP539VyrBo6jtk6sXev+RZXexhBl2QbeFesEvd3CWBGtAdBINxWA2LoabRgIJPJ4EHqnk5ljQLTuo6ZPN14mRRZTAdtXX30VgwcPxl133YWLL74YEydORPXq1TFZ4wgyZcoUXHDBBZg4cSIuvvhi3HXXXRg0aBAmTJjgcM1jn9HMDbNPTtdL2SkrJ3RuiYWUf5H9chUFIjJOnFwvlBMKvdPUsy1XrWq+PlZFy5Izk9HmRbGaWasw0v+Z11jJsDXzVOxo3V7o2SZ/+cWdnbbeY4XeC+VYENpfcCTRHqyjxukLZS1GL16jMXNxa1fXRoD1h2caYeSYr2c+2dENTyAlAGBmf+Y2sw+LjNYYrMZopqzZc2u3GuS0aPXzHvgwajump8bIA6n1nFepPWAtmsBAoPI+cJlt3cqLKr1EZZ+riXaHpNHt0+x2qTadSHcPRuvGTGTAtk2b4P/NNDaa7XaN/r+9+w6Tokj/AP6dZZclr2RYCYIBUAQVBVEQTIAgYM4YT+WnCMp5ip6enKeCnuKdOYcz4SmeERUMCAqKEhREhVOCSEZgyWzo3x91vdPT2z3Toaq7Zvb7eR6eXWZ7qmt6uqur365+KzjFGcXk2bNnD+bMmYMxY8akvN6vXz/MdEmCNWvWLPSzZloG0L9/fzz99NMoLS1FgcOV/+7du7Hb0gMv+V+Pr7S0FKU5n1XZPRJiGBX/a7jyHLZD8n3m3xYvLkj5f7qy7bxsZ5G+IR/9+lWgtNRLNDn9+v19t8mydu0q9dHYBa2DfVv6K3fz5jKUlqaedcTFRbpyg9Q1eHnl5W7fo+w6ZiozfbmZ9xPx3h07Squk4TCJzl7m48HrPllengegBnbtKk3Jp2i+315ORYVYPp3zzvOzX9uJz7ZnT2mgi5datfIBuL/RMMpRWhokIp7pe8/8XjdByszPT35OFXXyX66/7VNWVgOZ7vmmL8vr+uRv+4oKcf7YsyfIfp5aHy/1X77cQGmp+9AP83yWzhln2I9nUY/Nm0tTJpzzc671oqysFEAB1q0rTVu2uVw6hmGei/z1D7x9x3723/Trq6jw08YEaVdk79PJNjfI++TVxX/b//XXcvuG1np8910Z2rf3csXtdzuI5ZcuLUWrVuIVL8ewKKMAK1ZkPlZmz3Zep9NrmThtN8MQ9d2wIX3fK0jZQfttbtcWu3eXpgROMp177OWYfa5//cvAhAllluXS1weA73OEtUw/x464eRLPNYJYf+rnrKgQ27i83P75/dSxAL/8UorWrTO/t6zMup7Uz7NsmZd1imW2bi1Hpv5teXly+dLSUk/HrnU77Nollt+2rRR16ojXVq7MHFHTpT9kvQbx26aGWbd5bLz+ejmuvDLT+TXY56yoSP+5vBzz1veWlop++g8/lGK//cx1ZL6GKitzuu52Pz+uWJG+TjVrOrVDwdrZkpLUNt9sezZsKEVRkbcyUtcrllu1qhRNm3qpm/7crp/TLata1gRsN2zYgPLycjS3TcHXvHlzrFmzxvE9a9ascVy+rKwMGzZsQMuWLau8Z9y4cfirQ5b3KVOmoI7ZMuesoa5/2bRpMxIJA0BjTLZPBWp5X/JvQx3/70XV8qv68ceGAI5BjRrLMXmyl9m80q/fyzqdyvroo4+w115eh6kErYN9W/or95VXvsemTctSXhOd33TlBqlr8PKWL/8VkyfPl1qmiu2ZeT8R7/3ggw9QUODcISkvTwAYkqEc7/vkrFlHAmiOV1/9BI0bV711PdU2w83ixQcA6JS2zBkzpmPZsqBDb8Q2eOOND1G7tv+Evbt2HQOgoevfly79BZMnLwpcL3/Heup73QQpc/v25OdUUSf/5frbPuvX9wLQOMT6va5P/rb/9tuWALr/77zuN4lman281H/nzkTa5X7+uSmAo9KWUlgoho4kj2dRj+uu+wmnnGJ9ht/7udaLqVM/BdAPF164EkA71+U++mgqgIFpy5o79xvk56+F3/6Bt+/Yz/6bfn1LlvyEyZO9JtsM0q7I3qdFee+//z4KCvwMCVLThrz9tp96yO0bWsucO3cOatZ0vj7wW4fUdYvljziiDE8/LRJhfvttGwCHeihjKI46aje8BECc1un0mr9yhIUL2wI4BO+8sxuTJ09xeFfwsoP22+zL77NPXyxbVoRnnpmBNm2Sz+bv3HkIgLaey9m4sRaA/ti1qyLlbyJQl74vNn/++1i40PsxtW1bPoBBjvVIZ+fOGgBOTruMqmsEAPj440/RrFkyx9yKFYcCaINHH52Ngw/eUPn6/vsfgyVL3Ptn9v3z8MPL8eyzH2asx0cfTUHt2mUpy5ll1ao1CLt2uYcrzOMKAObOXYl0+wYATJv2CYD+le9dvFhcT6bzxRefY/VqMYBr3rx9AHTFHXfMR69eYma8LVuOB1AvbRm69Id27Urua37b1DDrXrOmDoATMXbsHrRu7dTmeF9f0GOhtDTzMW99b0lJfwC1cOCBBXjzTZHb6uefOwPYN20ZX3zxBdav3+xYt+ee+xTNm6fmc+zYsRd+/NG9P/3ll/La2W3bNmHy5ORkJr/+Wg/A8fjDH5bjkkusjzh6/Q7EckOHbsQtt3yV8lqwaxt92K+fnezYsSOCmgAJw9DtQQxnq1atwt57742ZM2eiZ8+ela/feeedeOGFF/CjwzSYBxxwAC655BLcdNNNla998cUX6NWrF1avXo0WDtNMO42wbd26NTZs2IAGDRpI/lR6qVnTvQPZo0cF8vKAWbPyqozisL5vzx5xJ7ywMHXER7qy7byMEvniiwSOPTYff/hDOR55JPNImEzr9zMyxVrWr7+WwnZPQHodzPdl+rubv/+9HKNGVd1G6coNUtcw5V1ySQUef7xqcE92HTOVmancTPuJ+d6tW9OPsK1Tx9uIBy9OO60G3n03D7//Xop6lv5iaWkppk6dihNPPDHlaYK77srD2LHp7w5//nkZuncPdmowt4G9Pl717VsDM2e6j5754x/LMW6c/xG2mb53L+91E6TMo46qgW++yVNWJ7/l+t0+vXvXwFdfuX9Po0eXY/x49+/J6/pUbPs33kjgnHPysX69fURBZvb6eK1/uuUWLQIOOST95/zoo13Ytu3DyuPZLPfuu8tx3XXJ7eznXOvFokWlOPDAAlxxRTmeeMK93Vi/vhRNm6Zf95QpZejb16iyTWR8x37230zre+GFMpx9trf2L0i7Inuf9nLeCVIPv3Uxy9u+vdRz6hrZfUNrma+9VoahQzN/j363g7l8q1YGfvlFBJmeeSaB4cPTj4HZs6cUNWsWYP/9DSxZknkIstM6nV7zU47pqacSuOqqfDRrZmDlyqo3rcKUHbTfZl/+iCPy8e23CcybV4qDDkq+/uyzCVx5pfu2tpfz229Au3YFuPXWctx6a7KtLC0F6taVeyxu3gw0a+a/Tdi6FWjcOJ5rBABYvLgU++yT/P9ll9XACy/kVbbZposvroGXX3Y/79v3z5YtDSxfXpaxHtb+YpDzg7nMY4+VZTwOly8vRdu2yXXMnp1Ar17p3zN7dikOOUT8/sgjebj22hp48cUynHWW2DaDBuVh6tT0/ep0+0OU/aEdO4C99vK3j8o4V/zyC9CxYwH23tvA0qXpb5Srur7bsweoV8972U2b5mPLlkTK66NG5eHRR/1fQ5l1W7KkFG1t9xQGDKiBTz7xdlzZy/Pbzj7ySBn+8Idk3b7/Hjj00IIqffZ0ZdSsaWDbttTjeuDACrz5ZnnGumUDt+tnJyUlJWjSpAm2bNmiNE6YNSNsmzRpgho1alQZTbtu3boqo2hNLVq0cFw+Pz8fjRs738koLCxEoUOPt6CgIOOXltvyKofwp9sOBQUFKY8uBdlmXt5jJs1+6qkaePLJ8Mldgn63NWoUSMupmakOQetYXl4DBQXu20j2dxSkvBo18lBQ4H6yUrEfqdo3zeXC7hde17VyZfp12tsue8J5J+vX54euf35+sG2QKeCQn59+f85ERTsepEzr96Dq3KJyHz/99PT5wjp29PY9hf3sYbZ9kOO0qCg1T56fNsH9b5nfn/+/StuP5xo1wh0PmbRoUVC5nnS8XNDVqZParsjYdmGWddO8uf/2T+YxHLQsGecdGXVRUY8gdcnLC38eS7/uROXrXvIzm8vm52cO1ublOa9TVptuHs7l5YlQ+67MvqB9eTMvsL0vkWlb28sxU0UdcID/ttL/Zwj2Xi/9MlXXCGL9qdvY3PY1avg7hqrWwdv+VbNm1TbDfN9ee4lAuJd1FhRk3pDmgCLzvV62/QEHJOvXrJn4ad02gwaVI9NgPC/bIcx3ePbZXtchZ31Vy01flnkchm1z0q2roEDciHH7u5chitb3WvO8m697qXq3bu7HTZDzo8x2tnbt1LqZ+39envf28d//rvod5uVVvY7P9riZl9hfVJ8xS6aAAGrWrIlu3bpVGZ48depUHHWU86OEPXv2rLL8lClTcPjhh2f9ThS1W28Fnn7a27JRjNk213HCCerXlY6fiSa6dlVXj3RUJnj3qrg4/d8PTf8kYdaJ8rkFv5OTeMkt2L17sLrIcOaZ6f8eZNSujrJlAiY3TZrEXYPwghynbdrIr4fOGv7v6ddM7YaXdsVpe+v4jJfqSTk7dlRbftx0+U73Tf/UqlSZ2nPr6EUv+9d114WqTkbmefSSS9SuJwyzf23fn4JO6up38uQggu77cR8z9vWbeWdlbftM0h0/fs65XiZStI/x8tIXy/QkTrt26b/AKI6zyy5Tvw4ZVF4L+3nCxAszR7mVl2OgVi33v8V9rNtvUAQ5po88Mvn7VVeFqw95k1WXjKNHj8ZTTz2FZ555Bj/88AOuu+46rFixAsOHDwcA3HTTTbjwwgsrlx8+fDiWL1+O0aNH44cffsAzzzyDp59+Gtdff31cHyFrtW6d+SLj0kujqQuQbGDinM0e8NfwWieEipIOAdtMd7AzBXSddOgQrC7ZwJL1JSNzH5TZCQjyfdgFrU+m77V27WDlhpErQWKZMgUd+vePph5hBNlHVVz0x9GB1yXDU6bP7jXlUFy8jM6yu/JK+fUA5O9HN94ot7yoNXRPtRmK07GTKQjx9tvJ3718T17OOV72PYfMbwCS7bf90VzVbr7Z+7JuAdug/X5VwUYZ68i0Txx+eLByg67fPM/ZX+/b11+51n5CuoEZ6foTfm5uewnY2vltJ5z63Jn6pffe628dQXi9blBxQ/KZZ7wvG7ZdfvZZ97+FvUm3bFnq/w88sOoy3boFK7tXL/e/WW/oqWZ/WMqtnU3HGs84Jn36Z5IkqwK2Z599Nv7xj3/g9ttvxyGHHILp06dj8uTJaPu/Hsfq1auxYsWKyuXbtWuHyZMnY9q0aTjkkEPwt7/9DQ888ABOP/30uD6C1latErlGatWqetR6aeAbNRI/o7z49DMy87rrgCVe5xHxyM9nPfjg5O8D08/N4kumAFeQxtScddyS/jmUTPP11a/vv8wjjgCuvdb5b6NG+S/PyVBLzvUhmecJk6JNG2DmTO/Ly74IkdWZkzXS5H/341z/H4WLLqr6Wth9rMzvXFcOnn8e2LgxfDlhHXIIsGFD6muZRsXIuCv/6qvB3hfmHKXioj9Ifdq3D7fO447zt3xcI2xfeCFzuXEKcqEV9wgb0wEHiJ/m7NdAsj+xYAHwl79EX6dsYI758BOwsfb/KiqAM88M35B4GbWXqZ3NkOnEVdOmwIgR/t/nZ7SkWyAh3ei1dOUEubnil8yA7eOPJ38P0++55JLM35W93m7byrzOM40fn/w9083M/fev+tr334uf6R56dfrsbqNJ7cF8S0gAADByZNX3pGuPR48G3n3XeXn7+y6+eKFrOSr2vZ2p81ZFcl6xB0vNgVpe2iKzjxDkGuOXX5K/p+u7XHCB/7KBZP/VfgPLMqVRpaCDRuzHjtWxxwYr083gwe7l2m84urVZ1lDZ2Wenjqq1Bt3d9u1+/TLXk7zLqoAtAFx11VVYtmwZdu/ejTlz5uAYSzTqueeew7Rp01KW79OnD+bOnYvdu3dj6dKllaNxqaomTYA333wLJSVl+Oyz5OsNGwKdO4vf050Q/JwsZI188BP0qFlTXJjs3Cka4bPOCnanzAxmAv4Dtn/7m/jdbOB++w0p2zqITHU4/nj/ZZqPldx1V/LkdMklQO/e/ssCqj5ib+aAMqU7AafbVwYMED8NQyz3xRciMJ/ubrb1wimTCROSdZPVGTIM5xPZ998DJSXybyo4rR8AbrtN/HzzzdS///WvatefiX07m/tOiZigN+X4i4q1TvffD1x9tej4FxYC55wTrExzJEiYx9jy8qp2Ag8/HOjRI3lsqNKmTfKG2WOPAY0biwvpu+/29v6HHw6+bsMQ7fgZZwQvwywniveo8PPP4d4/erS/5RMJ7xcqfi4+Mm1PvyO6ZPBzQVkaYk6NsWOrvjZrlv9yHnpI/PS7b158sTivf/ed+P+qVcCPPwKrV4s+X6YbrXZBLmStfYOFC4HPPxfrNwW9AAe8bw+/x8Lll/tb/o03qr6WaQStrBunbv1Lc9ukW8+6dc6vX321+ExXX+2/PuZ6zzsP+Pe/vS3r9j2uWCGeILOO7nvkkarLmdcJboMb/PQJM5EZsD333OTvYfaHunXFTYYZM4CTThKv2QNsQVMfmKPw+/XLPBLWvo4HHhAjGA0j/Y0Dp3QEEyaI933xRerr9icZzdQOZr/2n/8UP60j4g0DOOww53Xfdx8waFDqa0cfnXyftYy8PPGC2S967jnxc+dOeU+0WK8d8vKST2u0aOE9KGweD0Ge+rz4YhGkr10buOce76kS/TruOHE+2rJFDGBp2xb4v/8D5sxJf9Pn+uuTwcpMDCP5z2VaI8dzWrrzSro0jWYaMaf3162bPH4ef1zcEAOAK65wL8+L++9PPmX7hz+In/YBY+axbm9jrNcWEye698XMfoL1cw0eDLzzTqAqk4usC9hSNI45RtwN7dRJNNCZOgv33uvvYsHaOJqzv37wgff3m518PwFbs0NQq5Y4Ub36qmhc/T5CYe2U+OmcGUZyXWYQtbhYnPytdw/9sm9364iKQYPcT8rpUlwMGwZ8+aX43ezoPP008NRTwJ//HLyuprVrRb0XLxb/T7d/uT3mIzpIyf///jtw1FGiI5eu4+Llkal27UT57dsDH38M9Onjff/ea6/My1pHFE+eLLbpgQeK1/12ovw+Mmzus2PHinoOHSpeO/VU8XrYgJT52cKMsP3nP0W7MHIkcMopIogRxeiYdHUCxLF67bUiQNK+vegIvfJKsDLNGxF+gyJW1v3/hx/Ez+7dxT771lvBy/WiZk0RrN6yRQSIATH7sKzR7aZRo4D//lf8nkgkRwPWqhVPHmBdRthG7aGH0geZrG242znVaboBw6h6ATZ/fvJ3P9MNBMm93bMn8PLLwJgxydf85NgLGrB9663k4+pffy1+btmSOorFq6D7z777ir6IeVFqluP2GH0mZuDLT33MZY86SrT5Rx8t1j9smOiDXnSRuHiN4nF2r5y2T7rPbO/fiL6F+xu8PvLvZTu79S3N97qlROjUyT1P+UMPicd7w+RibtQoma/eDCLademSWleTYYhrjtatxU1TM/i4aZMI6tilu0447TRxw+L338W2qqgQ5QQVNIemYSRvsrZuLSbZMvtS7dqJ7yMoc/v16iX6mxUVydG7bn3wdMFy84aF2VfdtAn48EPnddvLtd5IvuYab/U3+3716om6jxuXDIDazynW+pqB3ooK8bSAtQ0ZNy71PdabjOYoUrcbFm5PVSQSwLhx5Zg7F9i2TbRdhuF9RLiX5QoLxY2OY44R2//hh8WNi9Wrvd8wM/ucfttUsz248UbR1/vTn8T/33vP2/v9XK/vtZeIEzRoIM7ReXniZoxbYN2P008Htm6t+rrTTfCXX05fljmvfVGR+K6ffx7417+cl023vQ1DXF/36SNiLosWiTYg3XvMgXTpyuzaNdkmnXeeKM9+TGbaD8ybMm5PBjulP0sk4r1my0UM2JKrxYvFSe6sszIve+KJyd+9dCINQzQSK1eKURWA6EyYjV8m5onJz0hdpzu4+fn+A2TWIIHfC5MWLcQF3ogRycmiatQQHTI3jz2WuVwr6+Pb6R4nTff4Un5+cttaR2IccABwxx3p6+NWx5dfBubNA9avT76+//7pJ81auxZo2dK9zCCjDm64wb1Mkz1IMHEi8MQT3srPNDmB3YABwbapyW+uUKeTcyIhLprq1AEsacADCTuy0/xehw8XZTVsKIIYtWolR4IFceihwfP1GYa4wfPAA8HXb2d2PIPOf3nggeJiExAdxAMOEG3Lgw+Ku/Wqc2ab35N15EgiITqHMgOQ5nrGjhX7gcz8a2Fz2HoJ7HkNvmQaSXrwwXKjukE+u9dt73YB4HQONgyR3sY0e7bYrnPm+J/YLki+25kzxUg2a4oJP+sNGrA1gzF5ecknToKOwgqax1z2jQJzVFCQOthHyv3rX6IPevzx4kkklRPBydgOhuF+s8oebHNbn9/pNbzU2xwN6Pe9++0ntrmKCWUeeyx1dLnbDZ7bbxc/nQK29vPm6NEiyOPES97xhg1FPzyRcC/Hi6DvNYzkOfuKK1L7kc8/729eA6eyrcdPIpHcfq1bi+sua1oUIH1ey969gddfT/Zh/Hxm86bfk096fw8gRlEvXy7qbr25Zvr1V/HTMMSowrVrRcALcH4U35qb1Nw+5mAO8xovU/DdPsIWAP74R7HhVD4JduaZyZHzNWokRxF7ZZ6H/QRsTz5ZbFMnXlP8mdvXa1uuss13uvnslGaqVq2q/Rbzu7711uTv5j5TXCxuNjrJ1OYmEsC0aaIdaNJEtAHprsf8nLfWrxd9TKdtal4XuZVnpj0xn7C1PyHrNnBC9eSt1Q0DtpTWOedkHvExZIgIoPrt9CYSyYtZwxAnOD8XXM895/4YgxOnRuWmm/ynJLB2TvyOsDXvOuXlZb47Zso0QYm1o3XttamjjNIFtDM9jibbSSeJXJf2i2Gv28Eu6EXWpZdmnsDBfjHQokXmIK/Jy2NhiYToAAHhT2rmY+Fet4fbPnv55cD27eGT3wcNHljfn0iImxrWkTeJRLhHF+fOTY7YCeLoo+Xc3Tc1apT8F8S++yZHZAwbJvY7s23JJeb+cNtt4jFc1SOHM7EeP9aRoG685nY1L8jN5a0jQJ56yj3Pt9NFo+m339zX6eW8d955qf9P91nc/maOwnFjfr/duonR6mbw9rDDUm/u6SrIBEjm93TIIaKda9NGtL1ByRrJEjSfqSlIm5+pD2UNLkVRH7t27bwHX+zLjRsnJtmyP4pvPoZ7ww2zUVxsIC9PTEr2978n/yaL22AAr+t4+GHglluS/w864Y5V69bJvvvHH7ufs8xAt9tNZqv77nNfX5B88X5vFoVlDdhav7NTTvGX99etbKf22Rz92bx51b8fckhyGaeyTj/df/oWwxApk+6/331UtZv8/PR9JbN/btbPHlSys35e8z0FBSINXPfu4rVMN9Ds2yZsXz7qAJefdiaRCN+3dMoH60bnp47Mup1wQvJ3L8eC+SSan8/Wu7f78n7iD02auO9fbnEXw3AObLsF7u3vZcBWrhy7tKM4vPVW1ZOfGzOA6JT43a9Ewl/D53QxUreu/1Ehkycnf/c7wlZFA2ZezJxySuoEAGZA0I3ZIcvk6qurJu53ku5xnjAn33Tvbdw4fGfWSdALxMJC7yNs33lHTqdk8GDg/PO9L6+6IyQrYKsTFXUaM0bePhCHqL4n63patAj3aKhT2X6pSomQlydmKDZH6dWrJ56WOOoo73mO7XUrLva+rFu9grC+7667Mi+bSADffBM8H3QQs2fLKee++4IdB4mEuIAzcyqGSY1iBnrCjJouKQk2QtkqSE5pL6Mf/QqSGsPJ7beLUb5envxy2vZjxgB33um8rGEAjRvvwrJlZdi923vexUzr9PteL2WYgzaWLBHHqUzHHSe2s3kcOHEKGvph9uf8vO/mm4NNhhuU06hhAPjPfzI/GfT++5nL99tG+elT+lnv3nuLgSV+bnQFSbGSif1JSbOeN93kPdVHupulfr3yipybIX5E3fc0A7Zeb2Lrdh1gsj512rixuAGRafJvwDldi73MIPVQyZ4mQsZkyRQMA7YUizgCtrJGnlnvuuoQsDXVqZP6CI+shN9163p75MY+Y6lV0M+e7j2GIR4DX77cf7mZBA3Y7tolTtxRd4T8bFvVuQAZsPUmLy/4fqaDKL8n2etRdQPJiZ/H/9q2FSMhzNFBfs9ZfkfM+F3G6whbsx4nnyxGRh12WDJfpZ2s/cjv6HtZo1KPOy7zzVHVvEz448S6v8gITpm5RP3shyrOR199JfJjeq2HfblPPxU//+//xH7ilrvZHrAx9+O//z3z+qzLO+2Lfo8Jv49Fn3BC6gixdGrXTs0fLltRUfprArdRnl4dcIAIxGUq16pu3cyjNGUyjOBtUqY0VHHeFJYV1PT6fXvdN/yc29Kty/aK/0L+55xz5E3GrSszhVScKRFkB0Zr1hQ3IGTw+3mjupazCvsUDgXHgC1JkylQIzunoowRtmHpFLCVEQQ3qejgqQi6qNqeKgNpcY+ojOMk7/f9OgZss7FsP5wuaHWg27ZXMSLQus/XqpW8Kej3WMj0eaxPVTiVax/Ja1/G62RU9nrUrev+BIas491vfmu34EiYCUDj0rq1mGtAl7bEDxXHE+B/n5o3L/m7mU/abz/AXGejRsC777ovl0x7EO4Ls37fbqPw3faJ4mL3myh2xx4rJsSTQVbAxO/365bWwq2cSy9N3SdUs6ZEUFF20DZWdpsiJzDqXq7Xz+o2wjaobGx7o+Z1UjRA7fb0+127jfAPmnNelij2OZn9TwqHAVuSwstBfdBB8tcZxwhbqyA5bFVYuDCZHwcQEzCEFffkPnFSPfIxzoAkA7b+qaqTTp8zSCc26pQIspx0UvB8xmaA6amn5NXHesxccw3w9dfi97vvFo9KBinHyemnJ3+3b9MHH8w8qV66UXzp0iKlq1dcx3uNGqmP5davL/6fbgJQWXS6IRp3G6T6fOSFYYjv337e99NntH+ngwalX1b2fn/bbcHe5zUYJjM9QDYEx/Lzo0+JoDL/vKyArU7B3zDrcMphG3ZdcbeluSRs+6j6Rv+rr3qbdNbt/TLocO6k6Eh6KIwo8whb2Z0RBmyT7MHwdBMwxEFFJ0/l9lQ10kElr8eC6pN8utmFvVD5vYbZB9kZT5XNAdt69cTEg0H2UXP/9ppX1ivzM9asmWx//D6Sm+nYtj5lYt+m7dplzqPq57FUq9tvd3+svKIivoDtypXJ/591lphANSo6PO6pw41UXUbQJxLAddclb0ps3eq+z7qty8/xkW75vn3FY/xeygHExF2ZlnGSrr6yUmqpICvAphOV59MoUwBler+Xz9i7NzBjhv/3meuLaoStrHQP5CzMTUiZx5PMmxZe1+HFX/8KXHCB3HpYcZ/WC0fYkhReT5AyG4C4UiKEaah1C/oEmegiKBU5bHVMieB3v4ya6oDtKaeEe7+uFy461kkm3domK51GN6v4vmTt84ZRNQ+eORv3lCnJ9v7CC6uuzzp5Y58+/tdtH7HUs2dy8pZjjwWOOMK9znEFbK3y8oJP/KXDsaNDHUx+jhFV56Mg2+Puu4ERI8TvfoK1QHI/PvpobxMqpUuJ8NJL3ibgM7fzcce5L3Phhd7K0JmMlAg6HR9OrO3g/vurKztOXvc1+9MrflIieCVjhG3YOlRXXraTjn111evwW6asiQHTydYnd3IRA7YUmURC7kGcbTlsqzNVQQ5VVOewlX0y0ynPkDnxTNALcV0uLqKg0+fUOSWCTmX73a+j/I4NQ0xANWVK8rXJk8XrJ54ING0qXnvooar1MiftOu00MdIwP99f3e0XwG++mXnyJXNZHQK2uSDICNu42yBVOWz9kNXGJBLA558D/ftnXp/fbX/HHcHqlC5vpKqby7In4bO3ubnY77buD927yy9f5g3KOAatyG6nzBG2GzYwh23UvG5rnVMi6Fq3MPyksvJbFoXHgC1JYx6gixY5/1125zCulAjWhjpXc8jIbmxV5b3ScYSt7qLaZ3VMiUDudA7Y6jCawaR60rEwzPQCJ56Yfrn69d3XN2kSMHQocNddYmSsH8cfL376fTy8ugVsdcphq4Kfuqg8H/lNiRCmfL+jiv3u907LGgbwn/9Uff0PfxA/L7ss/czzqvaZ666TW14UjyTHTdcni8IGcWS0dX7K8JvDtmlTmSk2GKXSgeqnHHVJiSCb7JszJBdz2JIU1oP6iy+cl4k7h62KCzS/OWyzSZyjQL28R9cctrqf4KIa0bR0KdC8uf/36XgxpuvFVHWg27ZXMcJW1j5g3Vbr1qVfNlO9/vSnqq+9/Xb68swy/V5gV7eALaBHDltVsi0lgqygkv/vNPyK7elLmjYF2rcHmjTxNjFi1PtMkPXJCiTocnw4UX2e06FP5TeYGnQdUeWwta+XvFG9L0YRsFUh7mNU9oA6kosjbEka82B3O+jjvkBRMemY3wauujZi1S0lQrq6qeo8e90eUY2wXbMm2Pt0ubiIgk6f87vv/C0f5fek0whbHQJMVvZRftaRQ+mWVbFNrRMO6j7CVuWM7HEIGsCKuw3K5hG2QcswUyKELdtexoAB4meLFsn80X7LlCFTuUGe5kj3fy/i3s8zUX0s6nK+U9VO+b1ZaE/hE4T9fbrvY9WF6u8hV1Mi2DElgl5yrMtKcfFy8lMxYjPuEbZslLzTKegCpP/umBIhPKZE8EaXNqSszN/yUdVbt5ESKo4fWfu8YXgPRAbdrm6TMSUSwPXX+y+bAVt5dGlL/NDtBkhQfvd5GSkR7K/37i3KvfhiYPp073XJRrnWR9DtSZJ071WR3ixq1vb/L38BfvjBfxlBU6KQeqq/D6ZEoKjlYJeV4ubW8KhIieCHigu0XM1hK5uKO3VhOriZgv0M2Ma3HpUXLrp1PsJc+OjwWbI9h60uAdsw7DnVVX8nH3zg/reTThI/581LX4/770/+LvP79VNOnAHbXM9h64cOx1PQ78M+UMHPCFv7+4Ow1zs/X6RzsqYnSUfVo8Oqgxk6BDdky5aUCGFz2Ibps8tkLe+994DXXvNfBkfY+tegAXDooWrXkY05bIH49x+Z7WzcnyUXMWBL0pgHt1sHPC9Pfo6UOEbYBn2UJps6mbLrGvQEpyqHrcqArdcLJZmiztfnhY4BW476lSeqbaJb51j3EbZR5IfL9PrixenrcdBByd/jCibIDNjq8oh2kGBK3PVQmVNd15QIsti/v2uuAebO9f7+dPUdPDh4vaII2DKHbTRly9xmQXPYqrjOkn3DLop9S+f916u77gI6dVK7jmzNYStTkOPdqW+rQ7tBAgO2JEU2pERgDlt/4gwqehH27p/KEbaZctjGqTqPsNVR3PuDSddtrlsAX9WkY1GkRJCxr9nLGDLEfxnWx7XjOt7jnnRMNl2P30x0SIkgI4dlXDfvrZ+zdm3/E31GPcI2yPpkPKqr+/Ghaw5b2Y9Jqx5h63U7yjrfppapvjOn+36sg2wcYatikBTlFgZsSRqzgYgyJULcOWw/+UR+mblI1clDVecvG1MieN3G1TmH7TvvqCk3qDgufNx07epv+SgDbTqNsPU7IjDKCyw/KRHatAm2jsaNU//vdl5PV4/ff0/+Xh1TIqiSjRdpGzeqKXfCBOCxx7wvLyM9gd+UCGGFLSeu1EN+11udUiJs366m7Djea3+/jBsjssho/619aY6w1UcUfS6d+qSyhG1nrcvH/VlyUQ52WSkO1XWE7cqV3petzidbFY9khb3QjzOHbZwns+ocsA1KtzqpaEvq1vVfh6hSImRj2aaoR9imK6dpU2DSJPH7CScEW4d99vkOHcRPP/UPmvszk6gfgTft3h1/eqSgj4jr1K7J9uOP0a7PT8BW1j4gOw+ujmSlRNCZ+Znq1FFXdtD3pvu/X6q/t6BpF7JFttbbKtuD2yran0svTT8/QBRkjqbPhvNKtmHAlqTL9RG2QXPY2t9b3ajIYRumLnHlsI37RKYyZ6BVmJQIuTj6zU3c+4PudMthq0JUKRHy84HTTksuK0MiAbRvX3W96T6PqoCtHzLbmClTgFmz/L0n7tyxKulSD69UpArxtqz3N61aFW6dTlQ9OhzF48LMYeuPTue7TJxy2MquP3PYxmPjRmDzZrXr0D2HrdP7d+wAFi0KV25Y1eFJhmxWjS6LSTUvKRFk5+6Ke4RtrjZo2ZJPJ0xKhHR1qlkzWLmmqPcLP9shqhG2a9YEe18UM93rQqeUCEEeU41qhK1OOWx1ptOxk64ehYXJ3+O6QSN7O6l4lNmPXAtgRU33lAhff131tVde0escEpUg20/3z6rreS5ssDzqNsbr+mQM4KmawzZ8mZnEsR/L/A5vu01MjqhSuus7WTfncvGGq8wRtrq3t9mIAVuSIhtSIqgYYRtV8CsOMr8v3R5hizuHbXVIiXD99cHep9u+opJhAIsXx12LYGR1Lr3sjxxhm/69MsqJkjnKF4ivztmwnaLA7SAvt6bKbVlWpqbcbBxhmy3tnB+qA7a6pEQIys/NEC/L2pc59VT/dbKvV7U4A3oy903V1yCyc2irKsMul+IJcQefcxEDtiRduoBtFI9KuVExisdPA1vdGzDdcuHElcM2js8Txfpl0fFiTFWdvv8eePXVYPWRTXbKEq+WL0//d50fbfMiyn1Zp2MnXT2s5+JcSIngV9znAKoqylywQb4nt4CtjiNsZaeyUpUSQafjRdeUCCoe/1ZZht9lZ8wQvzdp4q9OTutKJNTvUNk+wjYqOuewVTn6Nwyd20diwJYkypQSoWNH4Kij5K0vrhG2Vsxh603Qhl/lBUVcOWzjpvtdXJ2CTuQu21Mi6LSPDR8O/Ppr+HL8pBewtn/r14dftx+7dqXWIxdG2PotL+71A7n7aKdfUT8mW1Hhf52qcs/H8V0FSb+T7v9h1qnLeSCbUiKoFuV3Yq4ryAhb+9MtquXKCFvVn0P3HLZRlCsrRVLQ9Ce6tKu5JD/uClBu8JIS4aKLgLZtgYYN5a0zm0bYVme6BeFUBmwBvS9Ydd9nddtXdBV3wOfZZ4EePeTWwcm2bXpeyMq0YIH49/DD4copLfUf2LnnnmCji0zHHAPUrVv19XTf2e7dyd9lHu9+yonzaR9VdKhDtorjMVk/y7sd12FH2OrytIYfudhH0DUlgpOot73KbWOWe9JJasqXTea5MleeyrOLImCre/sj40mGbPvecx1H2JI0mQ7uXMlha5WrDZpOnfg46hJm0rEXX3SeIMTP+v3yU57uAduyMj07QzqN8tSh3Zk0Sc6stpm2wX/+A2zdGn49ftercj1jxgCvvy5/XTfcADzxhLdlzX3IKdjq1emniwvdW26p+rd02/eAA1LrIeu78HNc6NjGhJFrn0eGb76Jbl2qUyK4nbd1TIkgm9Nnz5a6e6UqCLRpk/gZVw7bqPsqftfXuDHQqlX06417HXE+ERLFCFuVqkNKhLFjxc9ca2ezGQO2JIWXEbayR7j6bUhUTDrmR9yNsV86nKATCREAVUHlCNuVK4OtN6hPPwU2bvS2rO4B28suAz78MO5apMq2YzcqUXXmsuERND/eeENNMGnDBvllphM06NyuXfJ35rCNr9xsGCkUxrp13paLOiVCkPV16OD/PV5kw7nt/fdT/x+0zrNnAy1ahK+PCqqOxUaN4k2JEPWxBfhbtkOH4OmIrJ/tlVfyMH26hMhvBnE8jaKqjZg3D/jLX9SUnY1B4bhHwVu32V//mh3nhuqEAVuSLl3AVvYdwrhTIjCHrTfffafXZ1edEiHqz7p8OTB5srdldQ/YAsDmzXHXIBo6jY6Ka9IxL1Q8HRFneyTzPPjxx8CWLeL3adPklRuWn+BVLqdEMIzwueG8CDJiyutNvupARs4/lQHbs892fl2nc4gq9sB7kDYjkRA3tNaulVcvmXRNiRBF2yWz/CiDTNZ1TZqUhwULmka2PpnWrgX27Em/jIrvfPZs4M475ZebrTlsZZKREgHInnNEdcCALUmTadKxuFMiyArYWj9HNgS/dJBpJvioxR2wjfMk+Pbb8a3bK7cZsUmduAK26cow21cVAVsgvo63zIvzDz/UK1DrV66nRDjkEJHWIwp+9+edO9XUQ1fWye6sZLQD8+cDq1Z5W9YtiB+HqFNOzZqVvMHkVXUIJKge7Z5r20sH2Twhm/V6+IADgOeec18224KfzGEbjC7nJHLGgC1J4SWIqSIlQtw5bL0EbFu3lr9eQIxa3bgReOcdNeXnskz7TpgctpmoOinmUgfi00/jrkFVOm3f6tKxMifa0e3xs7AjOWV3+MOMpoizPbrjDuDii/U6tmRbuND7o/lhTJrkPzBcUZHb296udm33vwXdDhUVQLNmwKhRwP33e3uPeczFMdGZ/b1Rn0tefhl47z1/75E1GY7O503VI2xlvTeOHLaq043o6K23xLnDSuZns16P79iReZCEqj6YTvOleDVqVNU0LX5EsY/K2Aa5cizlCgZsSRrdRtju3Jn6+JOsgG3DhmKGdMBbwNbMZ/r883LWb+raFXjkEbllmh54QE25fqmeGdZNfr6a9aqk44V3eXmw0bLWWeR1wCC7M9kBh61bUx/TnjFD/Gyq4EnDrVuDjzAMe/NRh4BtUVG4dXbqlP7vXj7frbeKEXeytkWcNy/T9XuimH1582bgX//y9x5VTwhVpws9wwDWr/f/Hr90u2kVR7mmoO2nzk/EZVNKBJ3FlRJBtpEjgYkTq74eR+A02/q/zz+v/hp23jz5ZcbdJ6wOTzJkMwZsSQovB3VeHlBYCLRvL2+dhgEsWwbUqVP17w8/LB5HNMkK2Obni1FBgL9G8eef5Td+KjugudxQl5Wl/+7CBmx1TokQpWuuAYYP97789Onip84XVrrQYR+SXYcxY4DBg5P/X7RI/FSRf/zZZ4GbbvK27Pbtqf/3U58oRtgG4XTO9MP8bsIqK5O/LX78UW55KsT9/QPZF4xRJcx2kJH7Noyw+1EcI9z8nt9lBBKmTgXefdffe6Kka8DW7ptv/N+g8MteV78jbHVoW8NyCqJWVMh7WsPah3EL2DZtmvyuVQQTVX5PbhPJTZworsXDUlH3uM/HUdxYpuAYsCXp0o00qVNHTmNpXZfbSKnSUvHP1LatvPVa1++H7ECU+ciwTv70p7hrkNmrr4oOvBtZKRHOO6/qa9XpJLhqFbBmjffl+/QRPzNNgCDDzz97v4CbPz/+EU777it//VY6TDpWVpbaZqvOZbxjR+r/t21zXq5evdT/h735p8MIW1P9+vLqYRXnBGCZRv/mKqft+Ntv7k8srFqlpl2Lov2WLcogjy4B27gCWyUl/paXEUiYOlXeTSYVdM1hW1EhJrY0t/kDD/gbyZ/L/V2Vn83p+5oxA/jsM/nluwVsN2wQfSLZnzOKfcJtHZdcAsydG778bJkYzw+n+EQu3PzIFQzYkjROKRFKSoA5c8TvskdJ/f47cO216RsU69/CPgLqxPpZTzrJfVIL01tvyV2/zADw1VfLudC6997wZXgR9qS3ebP738JOOmZ65RU55XihYydAxzqZJk0CLrzQ27ILFqitixe//JL8XZftqnqUgeqArf2Gl9fgZS6kRDC1bCmvHkHlwkWBn5QI778fXVCzXTvgxRed//bUU8CKFfLXecEF8stUKY6cqH7fq2N+UzeZ6hqm/UwkRBBJx8EKYWzdKgJkKoTNt3nCCanXNlH1PwwD+Mc/9M1hK3td9u/fXr7M60cvAVu35WWt263MV14Jn96ookLtk3oq+k250A8idRiwJSmsDY214X/rLeDww8XvsgO25mOqbo2ceZL3OhFEENbP+sEHmXMiuo3gCkrmCemRR1Lrp0OQymswXjZZAVs31eXErOPjadZj1KmTun07cMYZ0dUnKN22qwz2z2QdbatC0PYz7IWajseFbHGOsNWJ08XwjBnAhx9Gs/7S0vT7q4pcfE6P7W7dqv4GTBhxjLCtjpOOAVWfbMjEXscrrgBGj5ZXHx387W8ijZsK27YF30/efFP8tH4HUe0zZWXAddf5e082B2xnzUrOeeJ0bL72mrx12QO2bgwj+hy2Trl7/Xr+eeCqq8KX42T8eOD//k9+uR06yCsrjknHrDcc3n47/PopFQO2JE3Uk46ZAeBMAVuzY6eiQ26/4M/UwMkOWsseZWCt/6ZNcsvWjfWzPvwwMG1a8v+qA7Yq6Bj0CBqYOuII+XUxWTvETkpKxOjbKDjV4euvo1m3ndv22LXLvZ1REXCwHpdBJwXzKuiFSNh66TTCNog33si8DAO26akIXrptx3T9jtdfl18Pp9HDhx8OPPqo/HXFKcxj5rLWJSslgsxR0ZnqJGOSNlWjUeOydava8oPuJ4sXi5/W70D1HANmXYOe13LhfOIUsJW5z9vPCW7b2jDEIAaZ54mo+isqnh6Rwenz33wzcMstwcvcuDE5GbrbOoLUy8+xtHCh/3WSdwzYkhRuI2ytZAcrzTyC6QK2VlEkCY/6wlllx0ll0CyMq68Gnn5abpkTJogR0qawAdtMd6yrkyDHXcOG8uvhlVsAMV0KDZm6d8+8TJT7UN++4rFEJ7/9Jndd9m1vn+xLtigmt3ObdEymqNuUU0+VW1625g8N45lnoltXuu0r+6kfwPnCbcMG/yMro6LLPuHVhx8CL78sfpc16dhLL4Urx4lbrki/dVbVTldUJG/gxuW558Rovbhu1GZibvugAVsZx5auT6SoaDesA5Hs5cvsF3tNiWAY8iY6S1cHFVS1G1GPOPbim2+ASy8Nt36/A9AoWgzYknRRBWzNxs2tXPtJPooRtpl8+22868/E+t2FnVhn2DA1I2qmTZOTrsH6We0dFlmTjrlRsS/GfeHhJGhHu3Zt+XWxc+uk2uurcpRnmFEvKkbGOfntN/dJYsLmGctE9URrcXVIDUP++TAoVRdNuo2wNQzgv/9V953bJzk1ubUzUe57ugQ7dL4A1GUbeTFgAHD++eJ3HScdM9u2m29Off2EE1L/HoaMOSmmTwe+/DJ8OV7s2CHWZ7dgAfDpp+rXH3Y0eNCUCFHd6DZlc0oEIH3AVkUe2UzlGob8fOsyU8J4WY9MpaXiCYEwde/cueqk12FvStjfG6SssCNsSS1NLhkoF+iaEkHV+s11pPu/XZjHIJ3K9vtomZd1mLl5wm6vuXPFBXIYTnXIy5NzIrYGu+2do+bNw5Wdrn5r14rZuWW75x75ZYbl1glZskTNyC4/vObv+/138VNFgC3oMfb553LrkU5FhdrgYrqUCAceCNx3n7p1xznCNptTIsgWxf5cUgLsv7+67/zKK53z2rl9z/n58usQJCVCVHS+8JP9xE4mMvNCyhphaxfmZpzbI+3mKFK//R+nOnbu7L9edpkmCZZp1iygT5+qr0d1XMhM3xH1+cbP+fLKK9XWxerjj8XcHzKlC9iqkmmE7WefRVMP2VSc619+WTyRGZb92j3sd52uH+1Vtvcjc50G3TjKBXGkRMgUsM30NxmizGHrVPaWLcHLMz35ZLJzbhjJRzXDnuwSCTUnTBXl2veTsCM80+13nTpVvbuaq9yOh86dxaQAcdi9W/z0OsLWzC0XxQ2fTK+bvvhCfl3cPp/qgG26OqhedxQBWydr1wJr1sgrL0xHW4cRtrJTazgxv2tV3/nq1f5yDHbqpKYeTnQJlup8QRh2RFLPnsApp3h7X3If9L5BVHyHqkd/uw1o8Hu8qxr5pXpSS6tsTZMVdoRtEGG/23Hj5NQjkw8+AB54IPn/Jk3C53yJKmBrHfmcKWAr+ykz84mtbB1hC6hrj+MUNsWjzu1YLmDAlqRxGmFrbYDiyGFr/ZuKES1+H50/5hi565fR4XzqqeSMjrIef9m1S12HQ1W5ZpkyJhx77rnwZeQKrzmmo2I+SurGXt8uXZxfVynTtlGRC1KHgC1QNVdeLgZsKyrkj8whb1R+5+nSM9mFTTnkR9wXgrrUQaUTTwRuvTXuWvij6txsHWFrfULCPPYOO8xfecuXV02vIKP/oEPA1tqflX2N4nYtFqSMKCcdc6uDV8uWKamGI2vdGjQIf/FkTRegywhbc5BDtlF1/SmDU3A07pQIXspNhwFbtRiwJSncRthaf1eVw9ZrwFaFQYP8LV+3bvB1OTWGspLQP/VU1XWEaXy3bk2OhJXdiMvqyLjlsB0wIHzZH38cvoywnnoqgS++KI61Dk7H4M6dmW8KqDzxL10qfnodYWumMYnyjnqmz/+f/8ivi5uKCrXtaLq0NaoDtnF3MKdNEz/PPBP4+efg5cT9OZzo1tE316Ey2OD0md3amcLCaNZvf720NPeDp1GyBrS8tlVh9nfZM5871UXWZI8ffQRcf734vaQkWa7fwOTChVVHTcpoM8KkKPPLS8A2qvOsH+Xl4meY7V1RET4NmK5tluxz19ix4qfT5zXTc8lm3QdnzgTuuiv5t2wO2Kp6wtP6Myj7fjN5cvJYC0LG8RF2hG2UN8CqIwZsSbqocti6lbtsmdwcYX7WnWmdZ5wRfF1OZbdoEby8TOsIc7JbsUJMplBREe5k7xZQUxmwzRWvvJKH2bMl7yA+OQVsL7ss+bd071NZJ5PTo15u7ZTsYy2duEZ+OvETiAhj5cqqgXzVAVs/TxN8802wdaQ77x17rPi5117h0rCUlamZ4DEMBmzdXwOS7aBsixYl12l+VmsdVE+omY4O59gVK0QA0C5s/9TPja0w2+GXX4K/186tvkuWyC939erk7zrsB0C4m2R+ebmZImMflM0pJYJf06YBe+/t/3267CdurOnZLrmkApde6tCw+CR7XhK/ZswA7r8/+X/DUJPred26qvv7okVy15FNI2wXLAg3QZ+sgO3SpUD37sHKNQzgp5/C14OcMWBL0mRKiRBFvprSUqBdO3HxH9U607E+DjZ4cPhZz8vLU2fHlTFCwMvoaL+s+8Lppwcvx6kDyoBtenF3+KyC5l1WedxaR7M43dGOY+Ke7dvFjQ2zsxPHvhgkJYKMmbpNrVsDkyZ5X7cM332X/u/NmwMbN4rfr7022Dq87sth9vlFi4Crrgr2Xl1HLgXlNkrFPKZkj1C08rOv+n0s3Kt3303+PmeO+HnPPfF/z3Gv33T33cCwYfLL9fNEV5gBBRMnBntfurrYhc1Z2apVuPfbOR3TMs6RqkYsmk4+Ofm7lxy2Yc915k1FpxHSYScdk3E94JXTQBhd2g8787M1bWqgfv3wKRGsn3PbtuQcCqqYufTNz/HCC6nf17JlwJdfyl9v8+ZVv9ODDpK7DsMQeeVl5siXNcL2hReAH390Ltsv84nWsAxDzK9gTg4ZhKynM6gqBmxJCregn9syMpmN8QsvJEePvPlmNCf5TI8QmI+Dvfhi+HWZM1ybCduB8Plm33kH+Oqr5P9nz07+3rFjuHIB8Z1Mnhy8HCd5eXI669aTUlSPpam2ciXQrJn43elzyJikzo90x2C67zCqgG3U63ary5AhwA03JI85nW4epBs5pmq0waJFwPTpovMX5wz369YlO6CJhPiOwvjlFzWjoKKaZMWPuEbYbtuW/u8qgzROn7msLPWcbZKRK91p/U59sW+/lb+uINy+57DHVdA6VFQkR4/JeMTVbxlB1vn44/7fk279Tt9J2DbKnu4jkUidKDPo8W72d2vVSg2GBiVjvoZ03nsv+bv5XZ96auoyiURypG/Yc515nVGvXtW/hQ3YmvLyxAR7foRNx6AzwwA6dJCXOiqREH2OHTuAJ54ALrlEbAdVj5tPnSquC8xj8vvvxU1qcyT/KaeINAnZaPt2oGlTcQPJOkp4v/2ClymrPzp1KvD+++J38+mDoPtPgwbyArbWtvn114OVkc3X0DpjwJakcRphayX7IDbX849/iJ/WC7GRI8VJ6Ndf5a4zqI8+Cl/GsmXAFVekvvbYY+HLtZo3L/l7mElRbr9d/Ax7d9gtJYKMoMfzz4ufFRXADz+kX2e2sHdw7Z8lzCM3QQQN2F55pZr6mOvdvj34iEkVNm8WMw6bdNoHrSkRPvkk9W+y2nSz/E2bxMXrWWcBffqIn99/L2cdfp12Wur/P/8c+Pvf/ZdjbqM33hBPWNgf+ysvF3+TRWZZ2ShTe9O2rbp1//vf4gLbOnK7tNR5MioVwYjp05O/JxJAjx6pf9ehXbn9duC111Jf+/Ofo1t/eTkwf74YNfbqq+FSkdi3p445SDOV+ac/VW3XVdxUsqYAsfdjvTIDwVdeCZxzTvg6RZGbc+1aERg2J6J98033ZcN+xy+9lHzC6q23gDZtwpUHJPeFJ58U+VX/8hf//bOgQS7zHKxDu+XEvOGxeLHZ1w1f0URCBNzNJ0G2bwcmTAD69QtdtCNzwI59G5vzcKjMS2rd36++Wn755hMmgGjnzUE6YYKuMtths6zi4vBlm+8NMyjAMJJPJ9vL9WrKlGDrpswYsCUpEolkhyTqEbbmBep116W+/sADatZnZX5W8yLcmvvLekFmBgfDMrfxkUcmX7PPnhuGGWjVhVvAtqwsOYo3LDOorGun0I8jjkj+Pn161eY9jjuf9nW6pWywPqp86KHq6rNzpxi94OaEE8TP3bvFxZZK5raZO1d0+k3WffGmm9TWwV4XO2taguOPV7/erVtTRyRGfZPBZE7sJqtdMFPD2C+ASkrEiJZ0+6QfQXIFxk1mmgJ7Lt9ly8RFr3kBqrqdf+651FRIptLS1Edca9VSs/50o1WdzpnWCWZUW7MGuO02cfPj3/8WAebBg8UIoahMnSp+Dh8OvPJK+PLM0VGqBweoOndv2pR8lL6sTJzzVOdQv/zycO//5z/Db48dO5ITkKrUogUwZgzwzDOZlw37mX7/PfmE1SmnVA2+BGG2l198IY6dsWP9j0w2P5ffPvuHH1YtQyfWSZWXLElIqaM95ckHH4jH+s0JSmUz+3b20ZVR3Mz497+Tvz/yiPr1jR4tfsoI2Mr4rhcvlreP9+0rfh51lIgJvP22/zK2bhWDJMKQGY+gVAzYknTmiFcgNVeYjifcMAYPBg48UPxungh6907+/dJL1a3bmsYg17arlfXCwcz59/XXwLPPyluHtcOiIv/r5MnJII3q/LL28qdPbw1ABL1WrYp+tKJhiE6ZtYPvlh/JOvJN9QRfThekGzaIR4fnzhX/f+opoFMntfVwCx5Z6zd+fPL3bdvU3YhyakfKy8U68/JSZ3lWHZyI8smITCNInP4edAIyoGqAzEybI+szm6M1vMq188fDD6f+f7/9xI1I82mUKG7MFRSINu/ii5OvnXuuGEVkBiebN1dfDzun1Ewqbwht3ZrsGyUSwEMPid8feAA4+2zgwQfVBwbuvjv1/2aQ7ttvUwNIQY6D9etF7m1AbFtrG5nJhAkhHmGSxPzMZuDkH/8Q596wAds4Jvz145//BOrWBT77TF590rFO4gSk3gi2bus40/+4MfuUhpGcM8Pv0wG33eZveft365RSRhfLl4ufb7+dp+xcar2Zb083EtaDD4qfN92Uuv9dc43c9ThxC+Cryttrph7x007byfyOH30UGDBAbtlr16Y+aeOHeTPTKtf6h9lMw9MD5SrZnZG4R0R26wb8979ishfrXTLzAv9f/4qmHvbOYC6pUyf5+7x54SfDsHvhheQJaetWMTpB1shd06BBYqRDIpEc/RClGTMSuOkmsb8OHBjtus1RbYWFqaPCAXGcqHrMKxNr+hSzEzd+PHDcccnXd+yIb3SnW27snj2BUaPUrtvMg5lIAPn54rVrrxVtHSBuFpmPWlo7m0FZZw93ojp/Ws2aYlSi20Q5ThNudOsWfH32UdvmyCtZ5zO/E/6o6pDH1dE3A9/DhgE33iiCC/fckwzOGIbam6mAWNf336c+WTNpUnR9Ajf2VAQq/fqr2A733y9uWq5bV3WZ119X/wjlmDHelpPx6K/fPu7atXUyLxQB89FhM9dx2LZI94Bt3OmQrDekrWl2dA6OzJ6dnOPC7/cbNjB+ww3ZMZmRjJQITqyDHKIY+Ro1+4htWU8b2Zl9zaA3AH77LTvS3syaJacc0kt+3BWg3OClodG5MxLUBRdUfc2c+MxOdiDQpOrkpgMzv5yZ37OO5OubCy9MPoIkY2I4q/nz5ZYX1PHH56N379QJx5wmpVDNOiocEB3PqVNFQMWaL7lrV/V1GTky+ftbb4n/2x9jjnIiHLs77xTB0D59xP/NQMDChfHVyTwGrYF3GRPgHH54+r+bgWKVrBfNF18sRlebws4obz/vzZgRrjzyxq09b9dObcoVQOyzxxyjdh26s+bPHDQovnqYMgWZZKQB8Buw/e67puFXGoK9bTKDYmEfi9U9YKuDzz93ntBLV9YbLnEMljEnwdKZ6om1c5V11PApp1S9VtCF9Wb4zz8D3bvLLT/b2zRSS+PTA+UaVZOOUe476SR1ZZuTV8hOrm8NCrRvL7fsTOzBxhkzUkcnq5ih3C+zU5Zvu20oexS1E+sd/T/+MXO+p333VVsfu/HjgfPOExMY6cKab8yUix3M55+P5/iI63yWi99hJtbJNVXZtk39Osg7t1Q8JhmTwPk9lvLzvUeJVU06ZmXm7d60KVy5DNhm1rs3MGRI6mtmeg3dmWkAomR9ilFfvCgN66234q6BN7t2yS9TxzZNxzpVVwzYkhRxjLCNO2DLhoyCMvNWqpJpNvugszSHZR2lYR1xbh1Va83XpYo9x5M5IZQbM21ClFatCjZxQFCZ2rM4tkF1Etf5TNXkV0S6+OQToEeP9MvICNj6HSFZo0ZuBnh0DNjqMMrbzvrUEwA88UQ89fDL76Rjfjl9t9Y0VrriNWH1oSI1hc4j7Cl+3D2IiCIW90zuRx8dz3rdJtr57rto65Et0l2kyA66B7nY4AVKZl63UceOauvhZNs2+Y/1ecVjnqJy/PGZl5ExCZz/gK1eI2xl0TFg+957auohU43456HzREb6EL9UB4lliHsQEUVHxf6oY39axzpVV8xhS1Klm8E81yYd+/HHeNdP2SvuO6lxHzsk+J0gyuqII+TVAwiWBoCdOXnsqUGiULdu9Os0HXxwfOsmspMx0txvwK2gIIbIV47IxXNPtkwoFUfAVsYIeCJZeA1FUeMIW5LC7Dylm8E8zg5WmFm93WzcKL9Mqh7iziHLzoYeOnUK/l7Zo3FOOUVueSR4PdZ4TBJlN783Yv3ksFUhm0fY5mJ7uX593DXwJo5t72edd9yhrh7p5eBdBHKUTU88hKFjnaorBmwpMnEe+BMnxrduIru+feNdfy5e7GSjMG2i7FHaQUZ4sjOX2cKF3paLY9SSV2EnIcrkqqvUlk8UBZU5bLMpQMCAbTDZ8pmKi9WW77Rf+hlhu//+8uriR7Z8fxReNrXHlBsYsCUpdJ90TEVuqAUL5JdJ1UPNmvGunx3L7BfHI/RUPe21l0jBoWqywn/+U025RFHyOzFjXl5unoij6F/ofIPrpJPiroFaJSXRr9NLypJjjwU2bMg8iawqOuZuJqLcwIAtRUb2iWaffbwvqyJgu3q1/DKpeog72HboofGun8Jjxz23ZMNNFFX7XNztIZEMfnOQxh2wzeYRtjrnNG3SJNj7suEcAAAffxz9Or1M1PvJJ0DjxnFO3qa+U9a7t5xyzjpLTjkkj459eh3rVF0xYEuRkX3g9+zpfdm4c4YSWcU9G7Cfmx1UPQRpn3W+aCYiipLf83rcOWxVqe4pEYKO/o17MlqveIMtPiNHyimnTRs55VRX7PtS1LLk9EC6iyMlgh8M2JJO2OGlsHS48127tvp1VJf84zoHIFRRlWKBqEeP6NfpN2Dbrds6z8uqaO/XrJFfJgA0aKCmXCud28ugAVsdzuleqE5hky3bwS6KfbJtWznlMOBIlF0YsKVqIegjSkQqMGBLQLgLEx0uaqIYKR5FUFgHcee1zkTFxejjj8svkygufkdIFhV5z6GgIsCya5f8MoFo2uy99pJTTlGRnHKscj1gW1gY/TrjfirNiwYN9sRdBc90zgFdXWXL8U/xYMCWpGBDQ+RdNnQ+iXRw8MFx1yAaTZvGXYP0CgvVPKmi80g5Ij/8Bmzj7jdnyyP4Tho3llOOivYnaJmHHy63HqrEsd9mw76aTQHbdu3irkF2Y7+FosZxXpTVPv8c6NUr7lrES8UIAVKLAVsKS9YFq0nXDijzLevhrbfiGVlFFEQc7ZnKoJKKzxN3wDhXBR29WFwstx65hH1mQdbo9UaN/C2fLTcToqKiPWZeYUonC+5ZEbnr3Bm4/PK4axGvbEj30KFD3DXQSzaMFiC9HXRQ3DWQ55prgB07xO9mW/Hvf4ufDCrooXFjoF69uGuRvTp1irsGpFq2tVXshwBnnim/TF1vfmYLp+No//2jr4eOZOWwzeTqq1P/P3NmNOuNwvPPhy/Db8DbC1lpXig38XRNUsTVUS0qAm67zflvBQVAw4bR1iedsrLwZdx9d9XXvv46fLkULY4WyC6nnhp3DarKldE4w4YBDzyQHDnyxz8CrVqJC2le+JIs77yT/D3Kp1JatYpuXRQvlf1gFftRtgWYVahVS36ZzA8q36GHxl2D+AwcKPbTtWvl3TTNdOw/9FDqcrLSIV1wgZxygnjgAfFTxo0q2emhdJ/DgOLHgC1lvb33dn69oAC48MJo65KOjCDdDTdUfU2noLSbsCdIp9GEkyaFKzNOPDlnl3vuUVOuU6d5xAg168rEDI6+9574uc77BOahXHxx6v8vvxz49ddo1h3E+vVx14DSWbYs9f8vvSR+nnwysG2b+L116+jq88or0a1LF+Y292LePHX1iJrKEasqUsNU94DtE08Ap5wiv9w4A7aLFlV9LRfOWTo/Lq6ybiecIG427twJNGumbj1uZs4EPv1UXnlubaSquQr23Te5TvNpVBntnoz6btiQ/P3mm8OXZ6VT7IPkYMCWcsKJJ1Z9bcUKoH796OviRMYjGKZ168TJW6XjjpNbXtiRcn/6U9XX3AL1catbN/MyHGGrN3unMqrH0AAxmuKMM8TvY8YAP/yQ+ndVFwfmMTpwoPhpnwTL3obJGulh3dZLl8opU5bRo5O/X3ed+KkiBc3nn8svs7pq2xb48MPk/615d822ecoU9fV47DHx08yx36EDcPvtQMeO8Y3YnzgxmvW0a5c8TjZudF7m+OPFz0MOiaRKAETQXqVsSzEQR8A2qn3Qi8svFwEx2ez93fr1nT+37H1/x47U1CvmdYKMc9batcDq1eL3IP35fff1/549ljm8+vTx//6ofPYZcN995VLL3L5dDNC55pr42pVvvwWOPBLo21f9uuz7qKxJ0b78ErjjDvF7z57iZ79+4cvt0iXY+8xUChs2iDRTV10FrFrl/qRwJk7B9N9+S44mptyRZd0L0lXcd+rN9VsbfdmT8mTiFhy++265d7uaNhWPx7z5prwyTbffLn6GCSg6jQQpD9mXqVEDyLdMkXj33cARR4Qr05QryfSPPNLbcitWqK1HLjDvfJsd5ajat3/9S+zXf/+7+P+4cSLAYzVunPp62Dt7F1+c2oa9+iqwdaucdVm3bZwTjDld1FrzG06YAEyfrmbdRx+tptw4TJsWdw3EBZlhAHPmAIMHA//9b/JvW7cCLVvKX+ezz4rgz9FHiwumbt2SfystBd54A7jlFnED5o035K/flG7kz9lnp/7/D39QU4dEIpm+qVGj5Oc1b7LWqwdcdJGadafz4IOp/5f9dJLKHIS5MumYfR/06sYbxc+gwSPrZz3nnKoj8WXq3Tv1/wcdVPUG59q1YvR9+/by1mv/PmUF+rZvF6M7W7QQwSW/1we1a/t7Skn2Y/iq7bMPcM018oZVf/QRUKeOaEOHDJFWrG9Bg5LpOLU5/folb6yuWCEGLFx6qZz11akD3HSTuCm+zz7i2tk+GMGL9u3FOV4WMz7x8MPh+iN9+1Y9NxQX+0/7ZL2+DuqXX5K/y9xWJDBgSznBPAmYd3E/+yza9VdUACUl4vcxY1L/FuTk4MXQofLLNB/HDpMv6sgjgfPOS30t7CNiZ54pLoJNo0bJ64w+9ZT4OWeOnDuvceXd9DriMcrHgXWTbuS4NZedPd90FBe2++8v8rk2aSI6lps2pf596lRxN15VXaz77TXXiJ9btoifZudLRZqEuG/2mcwRxNaRQEcembpd7BfisshqM2Q/VhdEnTpx1yDpsMNE+hnrd6pq4jTDEDcm27YVF0wdOgBPPy3+lp8v9vMo9nU/N3RkXKQ5MYzUJ02sN8//+lcRNB82LNpz5V/+ItrVzz5Lrte8gA/q3HOTv3/wgbybyE6s22rUKDllRtX2DhxYdRIjv8aPFz979AgX4DjjDBEoVfnUTN264thatUr8f+bM1G1tGCIA2rEj8PPPwLXXylmvdR27d8vrI1vb9CDbftSo5JMGuaJBg2Te/Vzy7LPivKmS9Qb13/4mBgA88YT4f+vWwGuviZubYRlGct811xn06dTJk5PXD2H7gddfH+79TsIO4HI6F3t5WtStDHuqMwqPAVuSwt7x698/9f8qR5QA4mJ78ODk/485Jvl7FKO2rJ//rruAxYud/yab7JkqzdyqTpObeXXjjVVz2P3lL8HLA8Td12bNRP0eeST1MdcwDAPo2lWUd9hhIggu467+8OHOr+/cmezEy5ZI6DG6TWePPSbuAtsvZFatSr2p0KSJuCtvHruqjmFrufZ12EdrnXCCuBsfpQYNUv9v3nzKxcnAEgnxeYcPFyOJrGSnLBg8OPlI+Lp18vYvXYLf1dXddydv2NavL2+UkB9m27bffsnHvU87zXlZlal5DjoIuPJK8Xvv3sCjj0bbbhiGCM79+KMY4Ww+cmr2DbdtAzp3Fn8L6tZbgebNxe/9+0cXwPnHP+SUky6gN2iQnHUAIh3AhAnu/SI/evUSqQz8MttGVTdsrMz93OxLJhLikf7jjnOeLPT448V1Q1jmZ3z/fdFXzs8HNm8OX25Y48YFH7Tx5pvRpqTy429/U1NulO3k1Knip5k2oF8/MXglKueeK/q6rVsn007pZsgQcf1p7sOffBK8LMNQk1YrbH5jp+Pz3Xejrwe5Y8CWlOjQIfm7YajP2da8uQgm2C9Ya9dWn8fWHIUGiJGpiYQYLWeSdZfb6bFZt/xwYbz/vryyzFycslJCfPQRcPrpcsqy2rVL/Bw4EHjhhfDlWfOImQ46SIzmUfE4LpC8KNDVhx8mLx5kPU7v1/77i9xYr72W+nrLlqmd5ERCdCBVB2yt0uXVtNctTs8/L3e0TNyfx6pPH7F/mLn6TLJTFtStm/zcMoM8Om3L6iaRECMsVU2e4pV5g7pFi+TF+KRJyZFFI0cml73sMnX16Nw5mcc3kUgG66LcRxs2FH3R/Pyq/bC6dcWob+ccNQAAIqdJREFUz3vvDd5HLC4G1qwJX08vokiJYA3gd+0avnwzoFVYKAKIjz4avszjjxejtIOKcv+zrqtuXXFDxynId/LJ4gaxLAMGJH/3+2i0KnXrJnOI+jF0qNr0FTpSEdBzc8IJIgXXqFGijXG6oaCS9emXCROiXbdXb70lziX164tR8WGeTDEMNW1QkGPLyuwLWAcnBEk/c/bZwQK9lBkDtqTEP/8Z/Tpvuil5gWD64x+BGTPUrtc6Cm3u3OTvZudXVsBWRT4hQDxGa476zMtL7eyFNXGi3ABl795q7+Dts0/wHGvpPPUU8MUX8su1cuoE9Oq1Env2iCFEqkYDpDNzZvJ3a56qKEa5pON0TL7ySuojrscdJ0ZzA+rTEBhG/KNIvAYELrxQ7oR/ugQZEwng7bfl3xCy72uNGokOv+zzQ6tW+mxLik+nTmJW+H//O/V189F/a8qEMKmP0nFrSx59NDUvtGqZ2rQePcTj6GY6K7/M4+2ZZ4K9PwiZ53F7rlDzCSvr38Iw8xTLbJeClmXuC1G0keY66tZNzUF6+OFqR93L/mzt2skLJNevn9ofTKc6n8fmzo1mIkbrNr7++nj65LoGaN00blx1EmDdBB208+ST4qf5xEhQDzwg9+kMSmLAlqTQ4QS7335iVMCLLyZfKyyM7w5zWZk48dofrw1K1Uyh558vgqq7dql5pE9VCgBdWe+gXnSRGF3er5/6/dAc1bt9u7hjPnBgBa6/Pvlsk6qAfzo9e6bmVqpZMznxS5SPXdk5TQ5z+unAyy8nH5Ht0CHYo5eqDRkiZu+VzS24ETb3oM6sAQp7R1XWiDbrOgAxIu/BB5NpY2ScO5s3Fx31Aw4IX1ZY2TJRTC5r0iR5o9S8ENPBkCFVJ1FUJcrA3CWXqF+XSUaefZNZ/wcfFP0D6zaTkSdXxRMqYdN4RHmtUquWGJ0XFdmfLZEIP/9ErurUSQwesU/QSt6pTIHQpo26snUWNi3efvuJvm8upj3LdoqmHCCKz/nnx12DpHnz5JWlKmBrkpUX1uw07t6tNkdeWKoDqOeeCzz3nNp1mIqLk0HIOnXEHfNRo8oxebJ4be1aYNasaOpiN3RoMsCYl5ec2M5pYoP8/Kp5U1Ww5rh2qoOVihQcYdSpE23w/aGH1JYf182+pk1FUKJFC7WPhtsVFKTeMJDRRp54opxULjLIeJSa5PnDH1L/b16IjR4dfV0IOPBAEejxe2HtdAF9553h6mK2vZdfLoLOK1aI9qh9ezmT5Vonm5PhhhuC3xBKJNQ9jqwLFQHbOGRDkNjsT+fy/pStTjhB/vwusqhsgxYuVFOuVwzyqsWALUnh1AB16AD89FP0dclVfmdsjJt9ZFl18/LL0a0r04myWbN4T6ZeA4yvvBL+kRwv/HSYXn9dj3qoVt06W+a2jzJYu3x56v9lbPP99guXU002nfZpcnfffXHXIPsF2dcTiWDHqzV9jvWnDHl5or+2335yyzaf2ArbJpjvDzMZrknG7POZxHUuVdH2xvFZysujX6dfPM8FV51HcKoM2B50ULj379ghpx6kBlMikHTmBC0//hhvPXKNqlF1uXJXXhdxdES8dAJ07CCNH5/8fdMmMUld797R1iHOBPk6fidRi7O9iGL7q17HiBHA4MFq10GUbaI4toO0XYYhJr98990y+RXSlKyAbRhmLtm4c8Vnk7w8BmxzVVz9rup+fagzFSkRSR4GbEk66yyDJI/O6QUoXl4CtgMH6ncT5cYbk7875ZWNAhPkU1RUXPxefjlw2mnyyyUKigGX9AoLgX79/DUG2XxzL2yQRkY6sBYtnNMwqZArwTAzjUTU2H7krij2p4ICXi/HgcF4tTR6kI6yGQ9U9Y47Lu4aeJMt+4KqesaVJy3TOgsLRZqSKFx2GfD009GsK4hEAjjnHGDixLhroo9ceoxTJ9btKitPOBGlp2u78uqrwW5OmkFLme10VNtIhxG21UGupEQoqz6Dz6sl1cfzSy+pn/MlqFzPo03qaLpLE5Gd7AkcTLJPHjrlU0wnl06auo2+eeop/epkF9eIXl1Vt4Bt1OstLxejvCg36XA+ueKKuGtQvQT5zjt3Blq18v++4mL/78kV2TZ/Q6447TTgiCOiX6/ufUcKR/X327Ch+kmlw9Chr6ACj1u1siS0Qrpza4C2bIm2HrksW+7MdewYdw28Ubkto/6esmXfcHLwwfGc6LN1e5E8Ueaw1XXEB8kR98VKrVoiGKiDuLdFVKI8h2Tr+ercc8O9v3Vr4JRTwtejuuyTMo0bF896998fWLo0nnWTWtnajhHFjQFbUqpBg7hrQFGqXz97TsjZElj2IpsDtq1bixmqo5at20sVjrAlIvIujjYk2wKPL78c7v316snLRxnV93XaabnVv4xaIgHss0/ctcht7P/EI9vab9IHA7ZEWUJVQy/zxF1SIq8slWrUAIYNU1N2HMHTbA7Y1qgRT91VpRjJVnXrAs2bR7/ebN1vvWIHnSh6URx3ud526SLbtnPz5vGcS4m86ts3/M0U8q9rV6Bly7hrQdmIAVuSIts6VNmIF/7Zg4/4e/fss/HU/aijgD59ol+vrvbaC1izJu5a5B622xQV7muUa2Tt09naPyJSoWXL8OlKgjj1VGD9+ujXq4vPP4+7BpStGLAlyhK8GJNH5baM43vK5n0jrpGuAwaIfxSvOC+ks/m4Ib3EHRDyun5Zj5frLorvI+rvvE4dkXYqG7BtJSK7IUPirgGpMG0a0LZt3LXIbQzYkhRxX6xQcNX1u+OkY0TVF48XdUaOjLsG1ZOXIFmtWgymyRJ1G7J9u9zyqlMbyH2eiEgNPq2oHuctJgrhwgujWxc7nPIMHw506RJ3LeRhwJbIvyja1OrYbv/zn3HXIHpxf886tf9xb4uo6LTNcxm3M1UHRx4JNGkSdy2ISEdZE7DdtGkThg0bhqKiIhQVFWHYsGHYvHmz6/KlpaW48cYbcfDBB6Nu3booLi7GhRdeiFWrVkVXacppTZtGOxNsdbkIisLDDwM9e6opO47gaceOQLNm0a6TSIa4LsajWi/bbYoK97VoMZCoHvdpqi5mzQJat467FkSko6xJiXDeeedh5cqV+OCDDwAAV1xxBYYNG4Z33nnHcfkdO3Zg7ty5uPXWW9G1a1ds2rQJ1157LYYMGYJvvvkmyqpXC9W14xrl51bVca2u310u+eILfo+UneLab6dPBxo1imfdlHvibn/jXr9uunUD9t1XXfkvvwzkZc2Ql+zFp4eIiKi6y4qA7Q8//IAPPvgAX375JXr06AEAePLJJ9GzZ0/89NNP6NChQ5X3FBUVYerUqSmvPfjgg+jevTtWrFiBNm3aRFJ3ym1R3v3nSIPsEMcFBi8cifxRGcyheFT3SS/YR0h65BG15ccxw3p1xYAtERFVZ1kRsJ01axaKiooqg7UAcOSRR6KoqAgzZ850DNg62bJlCxKJBPbaay/XZXbv3o3du3dX/r+kpASASLFQWloa7ANkCfPzBfmcFRUAUBD4/dkpH+XlFSgtrYhgXQXYs6cU+dKP2IL/7duyy5Xn+uvzItrGskS5X7gLczxTNMRXU1CNv6MClJfr3f6E9eSTCbz1Vh5KS8tDleN8POvffkdpyRLEtC0KUFZWhtLS+CKmiYQe553Fi8Vjvdwn09Ph/FxWlgCQr/X5p6IiHxUV4ffr8vI8GEYidDusLx37EQXo378ih7d5kg7HMxHJ4ed4juqYz4qA7Zo1a9DMIUFjs2bNsGbNGk9l7Nq1C2PGjMF5552HBg0auC43btw4/PWvf63y+pQpU1CnTh3vlc5i9pHJXoiA7VAAwOTJk+VWSFN79gzATz/9jMmTl0SwtqH44IMPUauW7I7PUEyf/hmWLJE8/bBEvXoB2bRLGcZgLFy4EJMnL4u7KgCCHc8UjZ078wEMqjZtZlVD8cUXX2D16i1xV0SZJk2Ayy6T14alHs9D8eGHH6KwMPcviHXWs+cRWL/+Z0ye/HtsdSgrG4RFi37E5Mk/x1YH06JFcdcge8R5fp43rxjAEVqff3bsOB6//LIakyeH26lWrOiKkpIiTJ48XVLNdDNUu++xY8deKC3djsmT58Vdlciwv02UO7wczzt27IigJjEHbMeOHesYHLX6+uuvAQAJh2diDMNwfN2utLQU55xzDioqKvBIhuekbrrpJowePbry/yUlJWjdujX69euXNtCbC0pLSzF16lSceOKJKCgo8PXeCsvN74EDB0qumZ5q1sxHhw4dMHDg/pGsr1+//qhXT365ffr0wX77yS+3ukokEujcuTMGDjww1nqEOZ4pGlu3ip/Vpc10cvTRR+PQQ+Ouhf7cjuf+/fujmtxL1pY4fJvGWoeCghro1KkTBg709sQZxUuH8/POneL6SefzT506+Wjfvj0GDtwnVDnvvpuHjRsTWn/WsHT7bHffXQN7790QAwe2jLsqyulwPBORHH6OZ/NJfNViDdiOGDEC55xzTtpl9tlnH3z33XdYu3Ztlb+tX78ezZs3T/v+0tJSnHXWWVi6dCk++eSTjEHXwsJCFBYWVnm9oKCg2jTCQT6rNXdaddlOAFCjRg0UFNSIZF35+QVQsWnF9y2/3OrKMKLdLzKpTm1XtjG/lur8/dSsyfbHD/vxzO1HJp3OO+RNnOdnM8WW7uef/Pzw+3VensiFW1CQmwn/i4r0+x7z8sS/XN3mTtjfJsodXo7nqI73WAO2TZo0QZMmTTIu17NnT2zZsgWzZ89G9+7dAQBfffUVtmzZgqOOOsr1fWawdsmSJfj000/RuHFjaXUnAnJjMoRc+Ay64TYl8oYT5hERkZNbbgH2l/AQmxmwzVWbN8ddAyIiUiUrcth26tQJAwYMwOWXX47HH38cAHDFFVfg5JNPTplwrGPHjhg3bhxOPfVUlJWV4YwzzsDcuXPx7rvvory8vDLfbaNGjVCzZs1YPkuuSiSAdeuq38y5Uc7KzBmgiSiX/PorsPfecdeCiIh0dNFFcsoZPx6wzCdNEXj0UaB27bhrQUSU/bIiYAsAL730EkaOHIl+/foBAIYMGYKHHnooZZmffvoJW7aIyUtWrlyJt99+GwBwyCGHpCz36aefom/fvsrrXN00bQp89FHctYhO1HfrGbDNDoaR2yM5SJ5atYArr4y7FvFp1SruGhDlDvYRiJwVFcVdg+rn4IPjrgERUW7ImoBto0aN8OKLL6ZdxrD0VvfZZ5+U/xNlO1W7M4OLRPEoKAAeeyzuWhBRtuN5nPziPkNERKQ/Zo8jIpKI94mIiChqPPcQERER5RYGbIkCivriiBdj2YMjV4iIKCo85xARERHlHgZsibIEUyJkh6uvBrp0ibsWRERUnfCmLhEREVFuyZoctkTVWf36QM2acdeCvLDNhUhEpEweb7sTeOOViIiIKBcxYEsUUJQXSCUl0a2LiIj0xxGVZMX9gfxgkJ+IiEh/HJtBVM2x005ERJS9eB4nIiIiyj0M2BIRERERZTGOsCUiIiLKLQzYEhERERFlKY6wJSIiIso9DNgSBdSsGVC3bty1CI8XekRERNnrxBOB/fePuxZEREREJBMnHSMK6MsvgcLCuGtBRERE1dnEiXHXgLINb9YTERHpjwFbooByYXQtERERERERERHphSkRiIiIiIiIqokuXYCbb467FkRERJQOA7ZE1RwfiyMiIiKqPvbdF7jzzrhrQUREROkwYEtERERERERERESkCQZsiYiIiIiIiIiIiDTBgC1RNVerVtw1ICIiIiIiIiIiU37cFSCi+FRUMIctEREREREREZFOOMKWqBpjsJaIiIiIiIiISC8M2BIRERERERERERFpggFbIiIiIiIiIiIiIk0wYEtERERERERERESkCQZsiYiIiIiIiIiIiDTBgC0RERERERERERGRJhiwJSIiIiIiIiIiItIEA7ZEREREREREREREmmDAloiIiIiIiIiIiEgTDNgSERERERERERERaYIBWyIiIiIiIiIiIiJNMGBLREREREREREREpAkGbImIiIiIiIiIiIg0wYAtERERERERERERkSYYsCUiIiIiIiIiIiLSBAO2RERERERERERERJpgwJaIiIiIiIiIiIhIEwzYEhEREREREREREWmCAVsiIiIiIiIiIiIiTTBgS0RERERERERERKQJBmyJiIiIiIiIiIiINJEfdwV0ZxgGAKCkpCTmmqhXWlqKHTt2oKSkBAUFBXFXh4hC4PFMlDt4PBPlDh7PRLmDxzNR7vBzPJvxQTNeqAoDthls3boVANC6deuYa0JERERERERERERx27p1K4qKipSVnzBUh4SzXEVFBVatWoX69esjkUjEXR2lSkpK0Lp1a/z6669o0KBB3NUhohB4PBPlDh7PRLmDxzNR7uDxTJQ7/BzPhmFg69atKC4uRl6eukyzHGGbQV5eHlq1ahV3NSLVoEEDnnCIcgSPZ6LcweOZKHfweCbKHTyeiXKH1+NZ5chaEycdIyIiIiIiIiIiItIEA7ZEREREREREREREmmDAlioVFhbitttuQ2FhYdxVIaKQeDwT5Q4ez0S5g8czUe7g8UyUO3Q8njnpGBEREREREREREZEmOMKWiIiIiIiIiIiISBMM2BIRERERERERERFpggFbIiIiIiIiIiIiIk0wYEsAgEceeQTt2rVDrVq10K1bN8yYMSPuKhFVG+PGjcMRRxyB+vXro1mzZjjllFPw008/pSxjGAbGjh2L4uJi1K5dG3379sX333+fsszu3btxzTXXoEmTJqhbty6GDBmClStXpiyzadMmDBs2DEVFRSgqKsKwYcOwefPmlGVWrFiBwYMHo27dumjSpAlGjhyJPXv2KPnsRLlu3LhxSCQSuPbaaytf4/FMlD1+++03XHDBBWjcuDHq1KmDQw45BHPmzKn8O49nouxQVlaGW265Be3atUPt2rXRvn173H777aioqKhchsczkb6mT5+OwYMHo7i4GIlEAm+++WbK33U7fhcsWIA+ffqgdu3a2HvvvXH77bfD9xRiBlV7EydONAoKCownn3zSWLRokTFq1Cijbt26xvLly+OuGlG10L9/f+PZZ581Fi5caMyfP98YNGiQ0aZNG2Pbtm2Vy4wfP96oX7++MWnSJGPBggXG2WefbbRs2dIoKSmpXGb48OHG3nvvbUydOtWYO3euceyxxxpdu3Y1ysrKKpcZMGCA0blzZ2PmzJnGzJkzjc6dOxsnn3xy5d/LysqMzp07G8cee6wxd+5cY+rUqUZxcbExYsSIaDYGUQ6ZPXu2sc8++xhdunQxRo0aVfk6j2ei7PD7778bbdu2NS6++GLjq6++MpYuXWp89NFHxn//+9/KZXg8E2WHO+64w2jcuLHx7rvvGkuXLjVee+01o169esY//vGPymV4PBPpa/Lkycaf//xnY9KkSQYA4z//+U/K33U6frds2WI0b97cOOecc4wFCxYYkyZNMurXr2/ce++9vj4zA7ZkdO/e3Rg+fHjKax07djTGjBkTU42Iqrd169YZAIzPPvvMMAzDqKioMFq0aGGMHz++cpldu3YZRUVFxmOPPWYYhmFs3rzZKCgoMCZOnFi5zG+//Wbk5eUZH3zwgWEYhrFo0SIDgPHll19WLjNr1iwDgPHjjz8ahiFOhHl5ecZvv/1Wucwrr7xiFBYWGlu2bFH3oYlyzNatW43999/fmDp1qtGnT5/KgC2PZ6LsceONNxq9evVy/TuPZ6LsMWjQIOPSSy9Nee20004zLrjgAsMweDwTZRN7wFa34/eRRx4xioqKjF27dlUuM27cOKO4uNioqKjw/DmZEqGa27NnD+bMmYN+/fqlvN6vXz/MnDkzploRVW9btmwBADRq1AgAsHTpUqxZsyblOC0sLESfPn0qj9M5c+agtLQ0ZZni4mJ07ty5cplZs2ahqKgIPXr0qFzmyCOPRFFRUcoynTt3RnFxceUy/fv3x+7du1MeASWi9K6++moMGjQIJ5xwQsrrPJ6Jssfbb7+Nww8/HGeeeSaaNWuGQw89FE8++WTl33k8E2WPXr164eOPP8bixYsBAN9++y0+//xzDBw4EACPZ6JsptvxO2vWLPTp0weFhYUpy6xatQrLli3z/LnyfWwDykEbNmxAeXk5mjdvnvJ68+bNsWbNmphqRVR9GYaB0aNHo1evXujcuTMAVB6LTsfp8uXLK5epWbMmGjZsWGUZ8/1r1qxBs2bNqqyzWbNmKcvY19OwYUPUrFmTbQKRRxMnTsTcuXPx9ddfV/kbj2ei7PHLL7/g0UcfxejRo3HzzTdj9uzZGDlyJAoLC3HhhRfyeCbKIjfeeCO2bNmCjh07okaNGigvL8edd96Jc889FwDPz0TZTLfjd82aNdhnn32qrMf8W7t27Tx9LgZsCQCQSCRS/m8YRpXXiEi9ESNG4LvvvsPnn39e5W9BjlP7Mk7LB1mGiJz9+uuvGDVqFKZMmYJatWq5LsfjmUh/FRUVOPzww3HXXXcBAA499FB8//33ePTRR3HhhRdWLsfjmUh/r776Kl588UW8/PLLOOiggzB//nxce+21KC4uxkUXXVS5HI9nouyl0/HrVBe397phSoRqrkmTJqhRo0aVO3nr1q2rcteAiNS65ppr8Pbbb+PTTz9Fq1atKl9v0aIFAKQ9Tlu0aIE9e/Zg06ZNaZdZu3ZtlfWuX78+ZRn7ejZt2oTS0lK2CUQezJkzB+vWrUO3bt2Qn5+P/Px8fPbZZ3jggQeQn5+fcnfdisczkX5atmyJAw88MOW1Tp06YcWKFQB4fibKJn/6058wZswYnHPOOTj44IMxbNgwXHfddRg3bhwAHs9E2Uy349dpmXXr1gGoOgo4HQZsq7maNWuiW7dumDp1asrrU6dOxVFHHRVTrYiqF8MwMGLECLzxxhv45JNPqjwi0a5dO7Ro0SLlON2zZw8+++yzyuO0W7duKCgoSFlm9erVWLhwYeUyPXv2xJYtWzB79uzKZb766its2bIlZZmFCxdi9erVlctMmTIFhYWF6Natm/wPT5Rjjj/+eCxYsADz58+v/Hf44Yfj/PPPx/z589G+fXsez0RZ4uijj8ZPP/2U8trixYvRtm1bADw/E2WTHTt2IC8vNfxRo0YNVFRUAODxTJTNdDt+e/bsienTp2PPnj0pyxQXF1dJlZCW5+nJKGdNnDjRKCgoMJ5++mlj0aJFxrXXXmvUrVvXWLZsWdxVI6oW/u///s8oKioypk2bZqxevbry344dOyqXGT9+vFFUVGS88cYbxoIFC4xzzz3XaNmypVFSUlK5zPDhw41WrVoZH330kTF37lzjuOOOM7p27WqUlZVVLjNgwACjS5cuxqxZs4xZs2YZBx98sHHyySdX/r2srMzo3Lmzcfzxxxtz5841PvroI6NVq1bGiBEjotkYRDmoT58+xqhRoyr/z+OZKDvMnj3byM/PN+68805jyZIlxksvvWTUqVPHePHFFyuX4fFMlB0uuugiY++99zbeffddY+nSpcYbb7xhNGnSxLjhhhsql+HxTKSvrVu3GvPmzTPmzZtnADAmTJhgzJs3z1i+fLlhGHodv5s3bzaaN29unHvuucaCBQuMN954w2jQoIFx7733+vrMDNiSYRiG8fDDDxtt27Y1atasaRx22GHGZ599FneViKoNAI7/nn322cplKioqjNtuu81o0aKFUVhYaBxzzDHGggULUsrZuXOnMWLECKNRo0ZG7dq1jZNPPtlYsWJFyjIbN240zj//fKN+/fpG/fr1jfPPP9/YtGlTyjLLly83Bg0aZNSuXdto1KiRMWLECGPXrl2qPj5RzrMHbHk8E2WPd955x+jcubNRWFhodOzY0XjiiSdS/s7jmSg7lJSUGKNGjTLatGlj1KpVy2jfvr3x5z//2di9e3flMjyeifT16aefOl4zX3TRRYZh6Hf8fvfdd0bv3r2NwsJCo0WLFsbYsWONiooKX585YRj/y3xLRERERERERERERLFiDlsiIiIiIiIiIiIiTTBgS0RERERERERERKQJBmyJiIiIiIiIiIiINMGALREREREREREREZEmGLAlIiIiIiIiIiIi0gQDtkRERERERERERESaYMCWiIiIiIiIiIiISBMM2BIRERERERERERFpggFbIiIiIiIiIiIiIk0wYEtEREREOWvdunW48sor0aZNGxQWFqJFixbo378/Zs2aFXfViIiIiIgc5cddASIiIiIiVU4//XSUlpbi+eefR/v27bF27Vp8/PHH+P333+OuGhERERGRI46wJSIiIqKctHnzZnz++ee4++67ceyxx6Jt27bo3r07brrpJgwaNKhymSuuuALNmzdHrVq10LlzZ7z77rsAgI0bN+Lcc89Fq1atUKdOHRx88MF45ZVXUtbRt29fjBw5EjfccAMaNWqEFi1aYOzYsSnLjB07tnKEb3FxMUaOHBnJ5yciIiKi7MQRtkRERESUk+rVq4d69erhzTffxJFHHonCwsKUv1dUVOCkk07C1q1b8eKLL2LffffFokWLUKNGDQDArl270K1bN9x4441o0KAB3nvvPQwbNgzt27dHjx49Kst5/vnnMXr0aHz11VeYNWsWLr74Yhx99NE48cQT8frrr+P+++/HxIkTcdBBB2HNmjX49ttvI90ORERERJRdEoZhGHFXgoiIiIhIhUmTJuHyyy/Hzp07cdhhh6FPnz4455xz0KVLF0yZMgUnnXQSfvjhBxxwwAGeyhs0aBA6deqEe++9F4AYYVteXo4ZM2ZULtO9e3ccd9xxGD9+PCZMmIDHH38cCxcuREFBgZLPSERERES5hSkRiIiIiChnnX766Vi1ahXefvtt9O/fH9OmTcNhhx2G5557DvPnz0erVq1cg7Xl5eW488470aVLFzRu3Bj16tXDlClTsGLFipTlunTpkvL/li1bYt26dQCAM888Ezt37kT79u1x+eWX4z//+Q/KysrUfFgiIiIiygkM2BIRERFRTqtVqxZOPPFE/OUvf8HMmTNx8cUX47bbbkPt2rXTvu++++7D/fffjxtuuAGffPIJ5s+fj/79+2PPnj0py9lHziYSCVRUVAAAWrdujZ9++gkPP/wwateujauuugrHHHMMSktL5X5IIiIiIsoZDNgSERERUbVy4IEHYvv27ejSpQtWrlyJxYsXOy43Y8YMDB06FBdccAG6du2K9u3bY8mSJb7XV7t2bQwZMgQPPPAApk2bhlmzZmHBggVhPwYRERER5ShOOkZEREREOWnjxo0488wzcemll6JLly6oX78+vvnmG9xzzz0YOnQo+vTpg2OOOQann346JkyYgP322w8//vgjEokEBgwYgP322w+TJk3CzJkz0bBhQ0yYMAFr1qxBp06dPNfhueeeQ3l5OXr06IE6derghRdeQO3atdG2bVuFn5yIiIiIshkDtkRERESUk+rVq4cePXrg/vvvx88//4zS0lK0bt0al19+OW6++WYAYlKy66+/Hueeey62b9+O/fbbD+PHjwcA3HrrrVi6dCn69++POnXq4IorrsApp5yCLVu2eK7DXnvthfHjx2P06NEoLy/HwQcfjHfeeQeNGzdW8pmJiIiIKPslDMMw4q4EERERERERERERETGHLREREREREREREZE2GLAlIiIiIiIiIiIi0gQDtkRERERERERERESaYMCWiIiIiIiIiIiISBMM2BIRERERERERERFpggFbIiIiIiIiIiIiIk0wYEtERERERERERESkCQZsiYiIiIiIiIiIiDTBgC0RERERERERERGRJhiwJSIiIiIiIiIiItIEA7ZEREREREREREREmmDAloiIiIiIiIiIiEgT/w9CSqGTugHvxQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using despiked and zero-order holds corrected variables\n"
     ]
    }
   ],
   "source": [
    "from RBR_CTD_IOS_2024 import first_corrections\n",
    "fill_action = \"interp\"\n",
    "fill_type = \"interpolated value\"\n",
    "spk_window = 11\n",
    "spk_std = 3\n",
    "spk_var = \"Fluorescence:URU\"\n",
    "input_ext = first_corrections(dest_dir, year, cruise_number, skipcasts, meta_dict, verbose, rsk_file, rsk_start_end_times_file, rsk_time1, rsk_time2, fill_action, fill_type, spk_window, spk_std, spk_var)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2f68a383-fad8-4c20-b137-3cc4db3f3111",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "source": [
    "**Create Cast Variables and Format processing Plots**\n",
    "* Set input_extension needed depending on a zero-order-holds correction\n",
    "* format processing plots\n",
    "* produce first plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "28bbdb49-82ec-428d-b082-e9f874ffec78",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "have_oxy: True, have_fluor: True\n"
     ]
    }
   ],
   "source": [
    "from RBR_CTD_IOS_2024 import CREATE_CAST_VARIABLES, format_processing_plot, do_ts_plot, first_plots\n",
    "\n",
    "cast, cast_d, cast_u = CREATE_CAST_VARIABLES(\n",
    "        year, cruise_number, dest_dir, input_ext\n",
    "    )\n",
    "dict_recs_out['ZEROORDER'] = add_recs_out(cast_d, cast_u)\n",
    "\n",
    "for cast_i in cast_d.keys():\n",
    "    have_oxy = True if \"Oxygen\" in cast_d[cast_i].columns else False\n",
    "    have_fluor = True if \"Fluorescence\" in cast_d[cast_i].columns else False\n",
    "    \n",
    "    #if verbose:\n",
    "        \n",
    "    print(f\"have_oxy: {have_oxy}, have_fluor: {have_fluor}\")\n",
    "    break\n",
    "first_plots(year, cruise_number, dest_dir, input_ext)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e07b129d-380d-4076-b05f-3a0fadca64a3",
   "metadata": {
    "editable": true,
    "raw_mimetype": "",
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "source": [
    "# Start Data Processing  \n",
    "**Correct Time Offset**<br>\n",
    "* This function will only run if there is a correct_start_time_file.<br>\n",
    "**Correct pressure and depth data**<br>\n",
    "* This function will only run if negative pressures are notcied in the pre-processing plots.<br>\n",
    "**CLIP**<br>\n",
    "* Remove the unstable measurement from sea surface and bottom<br>\n",
    "* Then PLOT the clipped cast for comparison<br>\n",
    "**examine plots before proceeding**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "60773a51-48b5-4bc6-b394-13bed228c3e5",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Casts clipped\n"
     ]
    }
   ],
   "source": [
    "from RBR_CTD_IOS_2024 import CORRECT_TIME_OFFSET, CALIB, CLIP_CAST, plot_clip, formula_10\n",
    "limit_pressure_change= 0.02\n",
    "\n",
    "# correct time\n",
    "if start_time_correction_file is not None:\n",
    "    cast_correct_t, cast_d_correct_t, cast_u_correct_t = CORRECT_TIME_OFFSET(\n",
    "                    dest_dir, cast, cast_d, cast_u, metadata_dict, start_time_correction_file\n",
    "                    )\n",
    "    dict_recs_out['CORRECT_TIME_OFFSET'] = add_recs_out(cast_d_correct_t, cast_u_correct_t)\n",
    "    if verbose:\n",
    "        print(\"Time offset(s) corrected\")\n",
    "else:\n",
    "    cast_correct_t, cast_d_correct_t, cast_u_correct_t = cast, cast_d, cast_u\n",
    "# correct pressure depth\n",
    "if calib_param_file is not None:\n",
    "    cast_pc, cast_d_pc, cast_u_pc = CALIB(\n",
    "            cast_correct_t, cast_d_correct_t, cast_u_correct_t, metadata_dict,\n",
    "            calib_param_file\n",
    "        )  # 0 if no neg pressures\n",
    "    if verbose:\n",
    "        print(\n",
    "            \"Correction values applied to the channels specified in\", calib_param_file\n",
    "         )\n",
    "    # Add recs out number\n",
    "    dict_recs_out['CALIB'] = add_recs_out(cast_d_pc, cast_u_pc)\n",
    "else:\n",
    "    cast_pc, cast_d_pc, cast_u_pc = cast_correct_t, cast_d_correct_t, cast_u_correct_t\n",
    "\n",
    "# Clip casts\n",
    "cast_d_clip = CLIP_CAST(\n",
    "        cast_d_pc, meta_dict, limit_pressure_change=0.02, cast_direction=\"down\"\n",
    "    )\n",
    "cast_u_clip = CLIP_CAST(\n",
    "        cast_u_pc, meta_dict, limit_pressure_change=-0.02, cast_direction=\"up\"\n",
    "    )\n",
    "\n",
    "plot_clip(cast_d_clip, cast_d_pc, dest_dir)\n",
    "\n",
    "dict_recs_out['CLIP'] = add_recs_out(cast_d_clip, cast_u_clip)\n",
    "\n",
    "if verbose:\n",
    "    print(\"Casts clipped\")\n",
    "\n",
    "   "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e68defe2-60ef-443d-bdc2-8a32755b282e",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "source": [
    "**Filter and Shift the data then derive Oxygen Concentration if needed** <br>\n",
    "* **Filter** the temperature, conductivity, pressure, and fluorescence (if available)<br>\n",
    "  data using a low pass filter: FIR (0) or Moving Average (1)<br>\n",
    "* Confirm the sample rate from the rsk file. <br>\n",
    "* Plot and save the files after filtering.  \n",
    "* **Shift** delay the Conductivity signal\n",
    "* **Shift** advance the Oxygen signal\n",
    "* **Derive** oxygen concentration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "823b5ba1-344b-4109-86d3-1888fadfc91a",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Casts filtered, assuming a sample rate of 8 records per second\n",
      "Conductivity shifted 2 scans\n",
      "Oxygen shifted -11 scans\n",
      "Oxygen concentration derived from oxygen saturation\n"
     ]
    }
   ],
   "source": [
    "from RBR_CTD_IOS_2024 import FILTER, plot_filter, SHIFT_CONDUCTIVITY, plot_shift_c, SHIFT_OXYGEN, plot_shift_o, DERIVE_OXYGEN_CONCENTRATION\n",
    "\n",
    "filter_type = 0 # Moving average, 0 for FIR\n",
    "sample_rate = 8 #from rsk file, could be 6Hz\n",
    "time_constant = 1/8\n",
    "window_width = 3\n",
    "\n",
    "# Filter\n",
    "sample_rate = int(np.round(1 / float(meta_dict[\"Sampling_Interval\"])))\n",
    "cast_d_filtered, cast_u_filtered = FILTER(\n",
    "        cast_d_clip,\n",
    "        cast_u_clip,\n",
    "        meta_dict,\n",
    "        have_fluor,\n",
    "        window_width,\n",
    "        sample_rate=sample_rate,\n",
    "        time_constant=float(meta_dict[\"Sampling_Interval\"]),\n",
    "        filter_type=filter_type,\n",
    "    )  # n = 5 should be good.\n",
    "\n",
    "    # Plot the filtered data\n",
    "plot_filter(\n",
    "        cast_d_filtered, cast_u_filtered, cast_d_clip, cast_u_clip, dest_dir, have_fluor\n",
    "    )\n",
    "dict_recs_out['FILTER'] = add_recs_out(cast_d_filtered, cast_u_filtered)\n",
    "\n",
    "if verbose:\n",
    "        print(\n",
    "            f\"Casts filtered, assuming a sample rate of {sample_rate} records per second\"\n",
    "        )\n",
    "# Shift C\n",
    "cast_d_shift_c, cast_u_shift_c = SHIFT_CONDUCTIVITY(\n",
    "        cast_d_filtered,\n",
    "        cast_u_filtered,\n",
    "        metadata_dict=meta_dict,\n",
    "        shifted_scan_number=shift_recs_conductivity,\n",
    "    )\n",
    "dict_recs_out['SHIFT_Conductivity'] = add_recs_out(cast_d_shift_c, cast_u_shift_c)\n",
    "\n",
    "plot_shift_c(\n",
    "        cast_d_shift_c, cast_u_shift_c, cast_d_filtered, cast_u_filtered, dest_dir\n",
    "    )\n",
    "\n",
    "if verbose:\n",
    "    print(f\"Conductivity shifted {shift_recs_conductivity} scans\")\n",
    "\n",
    "# Shift O\n",
    "\n",
    "if have_oxy:\n",
    "        \n",
    "    cast_d_shift_o, cast_u_shift_o = SHIFT_OXYGEN(\n",
    "            cast_d_shift_c,\n",
    "            cast_u_shift_c,\n",
    "            metadata_dict=meta_dict,\n",
    "            shifted_scan_number=shift_recs_oxygen,\n",
    "        )\n",
    "\n",
    "    plot_shift_o(\n",
    "            cast_d_shift_o, cast_u_shift_o, cast_d_shift_c, cast_u_shift_c, dest_dir\n",
    "        )\n",
    "    dict_recs_out['SHIFT_Oxygen'] = add_recs_out(cast_d_shift_o, cast_u_shift_o)\n",
    "\n",
    "    if verbose:\n",
    "            print(f\"Oxygen shifted {shift_recs_oxygen} scans\")\n",
    "\n",
    "# Derive Oxygen concentration    \n",
    "    cast_d_o_conc, cast_u_o_conc = DERIVE_OXYGEN_CONCENTRATION(\n",
    "                cast_d_shift_o, cast_u_shift_o, meta_dict\n",
    "            )\n",
    "    dict_recs_out['DERIVE_OXYGEN_CONCENTRATION'] = add_recs_out(cast_d_o_conc, cast_u_o_conc)\n",
    "    if verbose:\n",
    "        print(\"Oxygen concentration derived from oxygen saturation\")\n",
    "else:\n",
    "    # Rename the variables\n",
    "    cast_d_shift_o, cast_u_shift_o = cast_d_shift_c, cast_u_shift_c\n",
    "    cast_d_o_conc, cast_u_o_conc = cast_d_shift_c, cast_u_shift_c\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9eff0a8a-4f0a-4a24-b839-27e2a13bb1ee",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "source": [
    "**Delete Pressure Rerversal, Remove Channels, Binaverage**\n",
    "* **Delete** swells\n",
    "* **Remove** channels according to vars_to_drop csv file\n",
    "* **Binave** average the bin values\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fdbff92e-fe13-47b2-86b7-eac997807e44",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [],
   "source": [
    "from RBR_CTD_IOS_2024 import DELETE_PRESSURE_REVERSAL, plot_delete, DROP_SELECT_VARS, BINAVE\n",
    "\n",
    "cast_d_wakeeffect, cast_u_wakeeffect = DELETE_PRESSURE_REVERSAL(\n",
    "        cast_d_o_conc, cast_u_o_conc, metadata_dict=meta_dict\n",
    "    )\n",
    "dict_recs_out['DELETE_PRESSURE_REVERSAL'] = add_recs_out(cast_d_wakeeffect)\n",
    "\n",
    "if verbose:\n",
    "    print(\"Deleted pressure change reversals\")\n",
    "\n",
    "# Plot before and after comparisons of the delete step\n",
    "plot_delete(cast_d_wakeeffect, cast_d_o_conc, dest_dir)\n",
    "\n",
    "# remove channels\n",
    "if drop_vars_file is not None:\n",
    "    cast_d_dropvars = DROP_SELECT_VARS(\n",
    "        dest_dir, cast_d_wakeeffect, drop_vars_file, meta_dict\n",
    "        )\n",
    "    dict_recs_out['DROP_SELECT_VARS'] = add_recs_out(cast_d_dropvars)\n",
    "    if verbose:\n",
    "        print(\"Select variables dropped from casts specified in\", drop_vars_file)\n",
    "else:\n",
    "    cast_d_dropvars = cast_d_wakeeffect\n",
    "\n",
    "\n",
    "# Binave\n",
    "\n",
    "cast_d_binned = BINAVE(\n",
    "        cast_d_dropvars, metadata_dict=meta_dict\n",
    "    )\n",
    "dict_recs_out['BINAVE'] = add_recs_out(cast_d_binned)\n",
    "\n",
    "figure_dir = os.path.join(dest_dir, \"FIG\")\n",
    "if not os.path.exists(figure_dir):\n",
    "        os.makedirs(figure_dir)\n",
    "\n",
    "do_ts_plot(\n",
    "        figure_dir, plot_title=\"T-S Plot (after bin average)\",\n",
    "        figure_filename=\"After_BINAVE_T-S.png\", cast_d=cast_d_binned\n",
    "    )\n",
    "\n",
    "if verbose:\n",
    "    print(\"Records averaged into equal-width pressure bins\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3f8c04f-7cbc-4b74-850a-7f5aec9669f3",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "source": [
    "**Final Edits**<br>\n",
    "Conductivity is converted to S/m<br>\n",
    "Final edits on the header information<br>\n",
    "Formatting the channels correctly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "da001084-dd42-420f-992e-4f4b3eccb593",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Final edit completed\n"
     ]
    }
   ],
   "source": [
    "from RBR_CTD_IOS_2024 import FINAL_EDIT\n",
    "\n",
    "cast_d_final = FINAL_EDIT(cast_d_binned, meta_dict)\n",
    "dict_recs_out['FINALEDIT'] = add_recs_out(cast_d_final)\n",
    "if verbose:\n",
    "    print(\"Final edit completed\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "628841a9-0b7a-4e3b-8c77-7a7efe8ebb83",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "source": [
    "**Plot final casts**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "a71fd61a-f440-412d-8b1d-f812ffa28cc0",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [],
   "source": [
    "from RBR_CTD_IOS_2024 import plot_processed\n",
    "\n",
    "plot_processed(cast_d_final, dest_dir)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "7937a05e-b5a7-4c85-a5e3-18c7564304cb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ZEROORDER\n",
      "CLIP\n",
      "FILTER\n",
      "SHIFT_Conductivity\n",
      "SHIFT_Oxygen\n",
      "DERIVE_OXYGEN_CONCENTRATION\n",
      "DELETE_PRESSURE_REVERSAL\n",
      "DROP_SELECT_VARS\n",
      "BINAVE\n",
      "FINALEDIT\n"
     ]
    }
   ],
   "source": [
    "# If you want to confirm the processing steps\n",
    "# for steps in dict_recs_out.keys():\n",
    "    # print(steps)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37be002a-2c63-42b1-b6a1-49f0cb507100",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "source": [
    "**Finally write all the files from the final cast**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "215c8c02-6c0b-4ca1-9e80-c0290a28df11",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [],
   "source": [
    "import warnings\n",
    "from RBR_CTD_IOS_2024 import write_file, write_admin, write_location, write_instrument, write_history2, write_comments, write_data, main_header2\n",
    "\n",
    "# stop from printing warnings in the output, suppress this if needed\n",
    "warnings.filterwarnings('ignore') \n",
    "\n",
    "\n",
    "cast_numbers = list(map(lambda x: int(x.split(\"cast\")[-1]), cast_d_final.keys()))\n",
    "for i in cast_numbers:\n",
    "    # # Update have_fluor and have_oxy flags, since it could be different for different casts\n",
    "    # have_fluor = True if \"Fluorescence\" in cast_d_final[f\"cast{i}\"].columns else False\n",
    "    # have_oxy = True if \"Oxygen\" in cast_d_final[f\"cast{i}\"].columns else False\n",
    "    channel_names = cast_d_final[f\"cast{i}\"].columns\n",
    "    # print(channel_names)\n",
    "    # Call the main header creation function\n",
    "    main_header2(\n",
    "        dest_dir,\n",
    "        i,\n",
    "        meta_dict,\n",
    "        cast,\n",
    "        cast_d_final,\n",
    "        dict_recs_out,\n",
    "        channel_names,\n",
    "        \n",
    "        processing_report_name,\n",
    "    )\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fe988a9a-b42e-4da2-844a-9a22b27d4e12",
   "metadata": {
    "editable": true,
    "raw_mimetype": "",
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "source": [
    "**Create PDF**<br>\n",
    "* might need !conda install nbconvert[webpdf]<br>\n",
    "* **Copy** statement below into a command window <br>\n",
    "Jupyter nbconvert RBR_Processing_Report_2024-017_GitTest_local.ipynb --to=html --TemplateExporter.exclude_input=True --TagRemovePreProcessor.remove_cell_tags='hide'\n",
    "* once you have an HTML file you can print to pdf, directly creating a pdf does not have nice spacing. \n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "25fe77f8-9c92-4cb7-b1fa-64d4ba00d17a",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": [
     "hide"
    ]
   },
   "outputs": [],
   "source": [
    "# jupyter nbconvert RBR_Processing_Report_2024-017_GitTest_local.ipynb --to=html --TemplateExporter.exclude_input=True --TagRemovePreProcessor.enabled=True --TagRemovePreprocessor.remove_cell_tags='hide'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c25d68e0-eb9b-428c-a6ec-2237d1c938f1",
   "metadata": {
    "editable": true,
    "slideshow": {
     "slide_type": ""
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.10.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}