tutorials/01A_quickstart.ipynb

{
 "cells": [
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   "cell_type": "markdown",
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   "source": [
    "# 1A. Quick-start"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "> Authors: *Valentin Christiaens* and *Carlos Alberto Gomez Gonzalez*  \n",
    "> Suitable for VIP *v1.0.3* onwards  \n",
    "> Last update: *2024/06/04*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Table of contents**\n",
    "\n",
    "* [1.1. Loading ADI data](#1.1.-Loading-ADI-data)\n",
    "* [1.2. PSF subtraction](#1.2.-PSF-subtraction)\n",
    "    - [1.2.1. median-ADI](#1.2.1.-median-ADI)\n",
    "    - [1.2.2. Full-frame PCA](#1.2.2.-Full-frame-PCA)\n",
    "* [1.3. Is the point source significant?](#1.3.-Is-it-significant?)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This quick-start tutorial shows:\n",
    "\n",
    "- how to load Angular Differential Imaging (ADI) datacubes; \n",
    "- how to use algorithms implemented in VIP to model and subtract the stellar halo, and search for faint circumstellar companions in the post-processed images;\n",
    "- how to quickly assess the significance of a point source found in a post-processed image."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "-----------"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's assume ``VIP`` is properly installed. If not, follow the instructions [here](https://vip.readthedocs.io/en/latest/Installation-and-dependencies.html). We import the package along with other useful packages which are installed together with ``VIP``. The ``hciplot`` package aims to be the \"Swiss army\" solution for plotting and visualizing multi-dimensional high-contrast imaging datacubes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import vip_hci as vip\n",
    "\n",
    "from hciplot import plot_frames, plot_cubes\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the following box we check that your version of VIP is recent enough to run this notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "VIP version:  1.6.1\n"
     ]
    }
   ],
   "source": [
    "from packaging import version\n",
    "vvip = vip.__version__\n",
    "print(\"VIP version: \", vvip)\n",
    "if version.parse(vvip) < version.parse(\"1.0.3\"):\n",
    "    msg = \"Please upgrade your version of VIP\"\n",
    "    msg+= \"It should be 1.0.3 or above to run this notebook.\"\n",
    "    raise ValueError(msg)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\"> \n",
    "    <b>Warning: </b>\n",
    "<a class=\"anchor\" id=\"war1\"></a>\n",
    "    \n",
    "Your version of VIP should be >=1.0.3. If not, close the notebook and run for example `pip install vip_hci --upgrade` in your terminal.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`VIP` also allows interactive work with `DS9` provided that it's installed on your system along with ``pyds9``. A `DS9` session (window) can be started with: "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "from vip_hci.vip_ds9 import Ds9Window\n",
    "ds9 = Ds9Window()\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The *ds9* methods will allow interaction with the `DS9` window. For example, for sending an array to the `DS9` window you can simply use:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```ds9.display(2d_or_3d_array)```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\"> \n",
    "    <b>Note: </b>\n",
    "<a class=\"anchor\" id=\"war1\"></a>\n",
    "    \n",
    "If the above fails but you have `pyds9` installed (`vip_ds9` is only a wrapper around `pyds9`), you may find the [following troubleshooting tips](https://community.lsst.org/t/ds9-communication-via-xpa/2242) useful (e.g. step 4).\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`pyds9` is an optional dependency of VIP and needs to be installed separately.\n",
    "\n",
    "Instead one can also use ```hciplot```'s ```plot_frames``` and ```plot_cubes``` routines - as illustrated in all the tutorial notebooks - for visualization and interaction with your images/datacubes. \n",
    "The above can be used instead of ```hciplot```'s ```plot_frames``` and ```plot_cubes``` routines (the latter being used in all the notebooks) for visualization and interaction with your images/datacubes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.1. Loading ADI data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to demonstrate the capabilities of ``VIP``, you can find in the 'dataset' folder of the `VIP_extras` repository: \n",
    "- a toy Angular Differential Imaging (ADI) datacube of images (`naco_betapic_cube_cen.fits`),\n",
    "- the derotation angles required to align true north in each image of the datacube (`naco_betapic_derot_angles.fits`),\n",
    "- a non-coronagraphic point spread function (`naco_betapic_psf.fits`).\n",
    "\n",
    "The dataset was obtained with the NACO instrument of the Very Large Telescope (VLT). This is an L'-band dataset of beta Pictoris published in [Absil et al. (2013)](https://ui.adsabs.harvard.edu/abs/2013A%26A...559L..12A/abstract), obtained using the Annular Groove Phase Mask (AGPM) Vortex coronagraph. The sequence has been heavily sub-sampled temporarily to make it smaller. The frames were also cropped to the central 101x101 area. In case you want to plug-in your cube just change the path of the following cells."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's load a couple of utilities related to FITS files:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "from vip_hci.fits import open_fits, write_fits, info_fits\n",
    "from astropy.utils.data import download_file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To inspect or retrieve the data, the easiest way is to provide their local path to the relevant functions in VIP - as illustrated below.\n",
    "\n",
    "Here we use the `download_file` utility of `astropy` with the `cache` option - which equivalently stores the local path to the file after downloading the data from an online repository:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "url_d = \"https://github.com/vortex-exoplanet/VIP_extras/raw/master/datasets\"\n",
    "f1 = download_file(\"{}/naco_betapic_cube_cen.fits\".format(url_d), cache=True)\n",
    "f2 = download_file(\"{}/naco_betapic_psf.fits\".format(url_d), cache=True)\n",
    "f3 = download_file(\"{}/naco_betapic_derot_angles.fits\".format(url_d), cache=True)\n",
    "\n",
    "# alternatively, for local files simply provide their full or relative path. E.g.:\n",
    "#f1 = '../datasets/naco_betapic_cube_cen.fits'\n",
    "#f2 = '../datasets/naco_betapic_psf.fits'\n",
    "#f3 = '../datasets/naco_betapic_derot_angles.fits'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's first inspect the FITS file using the `info_fits` function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Filename: /Users/valentin/.astropy/cache/download/url/916f9dc5548cc5a02ae424dbd987fc6a/contents\n",
      "No.    Name      Ver    Type      Cards   Dimensions   Format\n",
      "  0  PRIMARY       1 PrimaryHDU       7   (101, 101, 61)   float32   \n"
     ]
    }
   ],
   "source": [
    "info_fits(f1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The FITS file contains an ADI datacube of 61 images 101x101 px across. The length of the derotation angle vector for this observation is thus also 61."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\"> \n",
    "    <b>Warning: </b>\n",
    "<a class=\"anchor\" id=\"det1\"></a>                                       \n",
    "\n",
    "The *convention* in VIP is to always consider you are providing **derotation angles** as input, not **parallactic angles**. Derotation angles are the angles to be applied to the observed images (with positive offsets measured counter-clockwise) in order to align them with north up. These are essentially the *opposite* values of the parallactic angles plus some instrument-specific offsets. The additional offsets can correspond to any internal reflections affecting the orientation of the field of view, or to a correction for the true north orientation which may drift over time and requires dedicated instrumental calibrations. These additional offsets should be checked in the manual of the instrument you are using.\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's load all the data in memory with the `open_fits` function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FITS HDU-0 data successfully loaded. Data shape: (61, 101, 101)\n",
      "FITS HDU-0 data successfully loaded. Data shape: (39, 39)\n",
      "FITS HDU-0 data successfully loaded. Data shape: (61,)\n"
     ]
    }
   ],
   "source": [
    "cube = open_fits(f1)\n",
    "psf = open_fits(f2)\n",
    "angs = open_fits(f3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As a reminder, you can use '?' after a given function to know what it requires as input, and what it returns as output. For example, to know how to write a FITS file:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[0;31mSignature:\u001b[0m\n",
       "\u001b[0mwrite_fits\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mfitsfilename\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0marray\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mheader\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0moutput_verify\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'exception'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mprecision\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m<\u001b[0m\u001b[0;32mclass\u001b[0m \u001b[0;34m'numpy.float32'\u001b[0m\u001b[0;34m>\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mverbose\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
       "\u001b[0;31mDocstring:\u001b[0m\n",
       "Write array and header into FITS file.\n",
       "\n",
       "If there is a previous file with the same filename then it's replaced.\n",
       "\n",
       "Parameters\n",
       "----------\n",
       "fitsfilename : string\n",
       "    Full path of the fits file to be written.\n",
       "array : numpy ndarray or tuple of numpy ndarray\n",
       "    Array(s) to be written into a fits file. If a tuple of several arrays,\n",
       "    the fits file will be written as a multiple extension fits file\n",
       "header : numpy ndarray, or tuple of headers, optional\n",
       "    Header dictionary, or tuple of headers for a multiple extension fits\n",
       "    file.\n",
       "output_verify : str, optional\n",
       "    {\"fix\", \"silentfix\", \"ignore\", \"warn\", \"exception\"}\n",
       "    Verification options:\n",
       "    https://docs.astropy.org/en/stable/io/fits/api/verification.html\n",
       "precision : numpy dtype, optional\n",
       "    Float precision, by default np.float32 or single precision float.\n",
       "verbose : bool, optional\n",
       "    If True prints message.\n",
       "\u001b[0;31mFile:\u001b[0m      ~/GitHub/VIP/vip_hci/fits/fits.py\n",
       "\u001b[0;31mType:\u001b[0m      function"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from vip_hci.fits import write_fits\n",
    "write_fits?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `info_fits`, `open_fits` and `write_fits` functions are wrappers of `astropy.io.fits` functionalities.\n",
    "After using `open_fits`, the FITS file is now a ndarray or ``numpy`` array in memory."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you open the datacube with ds9 (or send it to the `DS9` window) and adjust the cuts you will see the beta Pic b planet moving on a circular trajectory, among similarly bright quasi-static speckle. Alternatively, you can use `hciplot.plot_cubes`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
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       "    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n",
       "      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n",
       "      for (var i = 0; i < urls.length; i++) {\n",
       "        skip.push(urls[i])\n",
       "      }\n",
       "    }    var existing_scripts = []\n",
       "    var scripts = document.getElementsByTagName('script')\n",
       "    for (var i = 0; i < scripts.length; i++) {\n",
       "      var script = scripts[i]\n",
       "      if (script.src != null) {\n",
       "\texisting_scripts.push(script.src)\n",
       "      }\n",
       "    }\n",
       "    for (var i = 0; i < js_urls.length; i++) {\n",
       "      var url = js_urls[i];\n",
       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    for (var i = 0; i < js_modules.length; i++) {\n",
       "      var url = js_modules[i];\n",
       "      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    for (const name in js_exports) {\n",
       "      var url = js_exports[name];\n",
       "      if (skip.indexOf(url) >= 0 || root[name] != null) {\n",
       "\tif (!window.requirejs) {\n",
       "\t  on_load();\n",
       "\t}\n",
       "\tcontinue;\n",
       "      }\n",
       "      var element = document.createElement('script');\n",
       "      element.onerror = on_error;\n",
       "      element.async = false;\n",
       "      element.type = \"module\";\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      element.textContent = `\n",
       "      import ${name} from \"${url}\"\n",
       "      window.${name} = ${name}\n",
       "      window._bokeh_on_load()\n",
       "      `\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "    if (!js_urls.length && !js_modules.length) {\n",
       "      on_load()\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.3.4.min.js\", \"https://cdn.holoviz.org/panel/1.3.8/dist/panel.min.js\"];\n",
       "  var js_modules = [];\n",
       "  var js_exports = {};\n",
       "  var css_urls = [];\n",
       "  var inline_js = [    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "function(Bokeh) {} // ensure no trailing comma for IE\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    if ((root.Bokeh !== undefined) || (force === true)) {\n",
       "      for (var i = 0; i < inline_js.length; i++) {\n",
       "\ttry {\n",
       "          inline_js[i].call(root, root.Bokeh);\n",
       "\t} catch(e) {\n",
       "\t  if (!reloading) {\n",
       "\t    throw e;\n",
       "\t  }\n",
       "\t}\n",
       "      }\n",
       "      // Cache old bokeh versions\n",
       "      if (Bokeh != undefined && !reloading) {\n",
       "\tvar NewBokeh = root.Bokeh;\n",
       "\tif (Bokeh.versions === undefined) {\n",
       "\t  Bokeh.versions = new Map();\n",
       "\t}\n",
       "\tif (NewBokeh.version !== Bokeh.version) {\n",
       "\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n",
       "\t}\n",
       "\troot.Bokeh = Bokeh;\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    }\n",
       "    root._bokeh_is_initializing = false\n",
       "  }\n",
       "\n",
       "  function load_or_wait() {\n",
       "    // Implement a backoff loop that tries to ensure we do not load multiple\n",
       "    // versions of Bokeh and its dependencies at the same time.\n",
       "    // In recent versions we use the root._bokeh_is_initializing flag\n",
       "    // to determine whether there is an ongoing attempt to initialize\n",
       "    // bokeh, however for backward compatibility we also try to ensure\n",
       "    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n",
       "    // before older versions are fully initialized.\n",
       "    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n",
       "      root._bokeh_is_initializing = false;\n",
       "      root._bokeh_onload_callbacks = undefined;\n",
       "      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n",
       "      load_or_wait();\n",
       "    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n",
       "      setTimeout(load_or_wait, 100);\n",
       "    } else {\n",
       "      root._bokeh_is_initializing = true\n",
       "      root._bokeh_onload_callbacks = []\n",
       "      var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n",
       "      if (!reloading && !bokeh_loaded) {\n",
       "\troot.Bokeh = undefined;\n",
       "      }\n",
       "      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n",
       "\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "\trun_inline_js();\n",
       "      });\n",
       "    }\n",
       "  }\n",
       "  // Give older versions of the autoload script a head-start to ensure\n",
       "  // they initialize before we start loading newer version.\n",
       "  setTimeout(load_or_wait, 100)\n",
       "}(window));"
      ],
      "application/vnd.holoviews_load.v0+json": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n  var py_version = '3.3.4'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  var reloading = false;\n  var Bokeh = root.Bokeh;\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      run_callbacks();\n      return null;\n    }\n    if (!reloading) {\n      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    var skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n      require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n      })\n      require([\"jspanel-modal\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-tooltip\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-hint\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-layout\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-dock\"], function() {\n\ton_load()\n      })\n      require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n      })\n      require([\"notyf\"], function() {\n\ton_load()\n      })\n      root._bokeh_is_loading = css_urls.length + 9;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    var existing_stylesheets = []\n    var links = document.getElementsByTagName('link')\n    for (var i = 0; i < links.length; i++) {\n      var link = links[i]\n      if (link.href != null) {\n\texisting_stylesheets.push(link.href)\n      }\n    }\n    for (var i = 0; i < css_urls.length; i++) {\n      var url = css_urls[i];\n      if (existing_stylesheets.indexOf(url) !== -1) {\n\ton_load()\n\tcontinue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    if (((window['jsPanel'] !== undefined) && (!(window['jsPanel'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/jspanel.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu.js', 'https://cdn.holoviz.org/panel/1.3.8/dist/bundled/floatpanel/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    var existing_scripts = []\n    var scripts = document.getElementsByTagName('script')\n    for (var i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n\texisting_scripts.push(script.src)\n      }\n    }\n    for (var i = 0; i < js_urls.length; i++) {\n      var url = js_urls[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (var i = 0; i < js_modules.length; i++) {\n      var url = js_modules[i];\n      if (skip.indexOf(url) !== -1 || existing_scripts.indexOf(url) !== -1) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      var url = js_exports[name];\n      if (skip.indexOf(url) >= 0 || root[name] != null) {\n\tif (!window.requirejs) {\n\t  on_load();\n\t}\n\tcontinue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.3.4.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.3.4.min.js\", \"https://cdn.holoviz.org/panel/1.3.8/dist/panel.min.js\"];\n  var js_modules = [];\n  var js_exports = {};\n  var css_urls = [];\n  var inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (var i = 0; i < inline_js.length; i++) {\n\ttry {\n          inline_js[i].call(root, root.Bokeh);\n\t} catch(e) {\n\t  if (!reloading) {\n\t    throw e;\n\t  }\n\t}\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n\tvar NewBokeh = root.Bokeh;\n\tif (Bokeh.versions === undefined) {\n\t  Bokeh.versions = new Map();\n\t}\n\tif (NewBokeh.version !== Bokeh.version) {\n\t  Bokeh.versions.set(NewBokeh.version, NewBokeh)\n\t}\n\troot.Bokeh = Bokeh;\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      var bokeh_loaded = Bokeh != null && (Bokeh.version === py_version || (Bokeh.versions !== undefined && Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n\troot.Bokeh = undefined;\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n\tconsole.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n\trun_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "if ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n",
       "  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n",
       "}\n",
       "\n",
       "\n",
       "    function JupyterCommManager() {\n",
       "    }\n",
       "\n",
       "    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n",
       "      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
       "        comm_manager.register_target(comm_id, function(comm) {\n",
       "          comm.on_msg(msg_handler);\n",
       "        });\n",
       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
       "        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n",
       "          comm.onMsg = msg_handler;\n",
       "        });\n",
       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
       "        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n",
       "          var messages = comm.messages[Symbol.asyncIterator]();\n",
       "          function processIteratorResult(result) {\n",
       "            var message = result.value;\n",
       "            console.log(message)\n",
       "            var content = {data: message.data, comm_id};\n",
       "            var buffers = []\n",
       "            for (var buffer of message.buffers || []) {\n",
       "              buffers.push(new DataView(buffer))\n",
       "            }\n",
       "            var metadata = message.metadata || {};\n",
       "            var msg = {content, buffers, metadata}\n",
       "            msg_handler(msg);\n",
       "            return messages.next().then(processIteratorResult);\n",
       "          }\n",
       "          return messages.next().then(processIteratorResult);\n",
       "        })\n",
       "      }\n",
       "    }\n",
       "\n",
       "    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n",
       "      if (comm_id in window.PyViz.comms) {\n",
       "        return window.PyViz.comms[comm_id];\n",
       "      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n",
       "        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n",
       "        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n",
       "        if (msg_handler) {\n",
       "          comm.on_msg(msg_handler);\n",
       "        }\n",
       "      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n",
       "        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n",
       "        comm.open();\n",
       "        if (msg_handler) {\n",
       "          comm.onMsg = msg_handler;\n",
       "        }\n",
       "      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n",
       "        var comm_promise = google.colab.kernel.comms.open(comm_id)\n",
       "        comm_promise.then((comm) => {\n",
       "          window.PyViz.comms[comm_id] = comm;\n",
       "          if (msg_handler) {\n",
       "            var messages = comm.messages[Symbol.asyncIterator]();\n",
       "            function processIteratorResult(result) {\n",
       "              var message = result.value;\n",
       "              var content = {data: message.data};\n",
       "              var metadata = message.metadata || {comm_id};\n",
       "              var msg = {content, metadata}\n",
       "              msg_handler(msg);\n",
       "              return messages.next().then(processIteratorResult);\n",
       "            }\n",
       "            return messages.next().then(processIteratorResult);\n",
       "          }\n",
       "        }) \n",
       "        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n",
       "          return comm_promise.then((comm) => {\n",
       "            comm.send(data, metadata, buffers, disposeOnDone);\n",
       "          });\n",
       "        };\n",
       "        var comm = {\n",
       "          send: sendClosure\n",
       "        };\n",
       "      }\n",
       "      window.PyViz.comms[comm_id] = comm;\n",
       "      return comm;\n",
       "    }\n",
       "    window.PyViz.comm_manager = new JupyterCommManager();\n",
       "    \n",
       "\n",
       "\n",
       "var JS_MIME_TYPE = 'application/javascript';\n",
       "var HTML_MIME_TYPE = 'text/html';\n",
       "var EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\n",
       "var CLASS_NAME = 'output';\n",
       "\n",
       "/**\n",
       " * Render data to the DOM node\n",
       " */\n",
       "function render(props, node) {\n",
       "  var div = document.createElement(\"div\");\n",
       "  var script = document.createElement(\"script\");\n",
       "  node.appendChild(div);\n",
       "  node.appendChild(script);\n",
       "}\n",
       "\n",
       "/**\n",
       " * Handle when a new output is added\n",
       " */\n",
       "function handle_add_output(event, handle) {\n",
       "  var output_area = handle.output_area;\n",
       "  var output = handle.output;\n",
       "  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n",
       "    return\n",
       "  }\n",
       "  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "  if (id !== undefined) {\n",
       "    var nchildren = toinsert.length;\n",
       "    var html_node = toinsert[nchildren-1].children[0];\n",
       "    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "    var scripts = [];\n",
       "    var nodelist = html_node.querySelectorAll(\"script\");\n",
       "    for (var i in nodelist) {\n",
       "      if (nodelist.hasOwnProperty(i)) {\n",
       "        scripts.push(nodelist[i])\n",
       "      }\n",
       "    }\n",
       "\n",
       "    scripts.forEach( function (oldScript) {\n",
       "      var newScript = document.createElement(\"script\");\n",
       "      var attrs = [];\n",
       "      var nodemap = oldScript.attributes;\n",
       "      for (var j in nodemap) {\n",
       "        if (nodemap.hasOwnProperty(j)) {\n",
       "          attrs.push(nodemap[j])\n",
       "        }\n",
       "      }\n",
       "      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n",
       "      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n",
       "      oldScript.parentNode.replaceChild(newScript, oldScript);\n",
       "    });\n",
       "    if (JS_MIME_TYPE in output.data) {\n",
       "      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n",
       "    }\n",
       "    output_area._hv_plot_id = id;\n",
       "    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n",
       "      window.PyViz.plot_index[id] = Bokeh.index[id];\n",
       "    } else {\n",
       "      window.PyViz.plot_index[id] = null;\n",
       "    }\n",
       "  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "    var bk_div = document.createElement(\"div\");\n",
       "    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "    var script_attrs = bk_div.children[0].attributes;\n",
       "    for (var i = 0; i < script_attrs.length; i++) {\n",
       "      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "    }\n",
       "    // store reference to server id on output_area\n",
       "    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "  }\n",
       "}\n",
       "\n",
       "/**\n",
       " * Handle when an output is cleared or removed\n",
       " */\n",
       "function handle_clear_output(event, handle) {\n",
       "  var id = handle.cell.output_area._hv_plot_id;\n",
       "  var server_id = handle.cell.output_area._bokeh_server_id;\n",
       "  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n",
       "  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n",
       "  if (server_id !== null) {\n",
       "    comm.send({event_type: 'server_delete', 'id': server_id});\n",
       "    return;\n",
       "  } else if (comm !== null) {\n",
       "    comm.send({event_type: 'delete', 'id': id});\n",
       "  }\n",
       "  delete PyViz.plot_index[id];\n",
       "  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n",
       "    var doc = window.Bokeh.index[id].model.document\n",
       "    doc.clear();\n",
       "    const i = window.Bokeh.documents.indexOf(doc);\n",
       "    if (i > -1) {\n",
       "      window.Bokeh.documents.splice(i, 1);\n",
       "    }\n",
       "  }\n",
       "}\n",
       "\n",
       "/**\n",
       " * Handle kernel restart event\n",
       " */\n",
       "function handle_kernel_cleanup(event, handle) {\n",
       "  delete PyViz.comms[\"hv-extension-comm\"];\n",
       "  window.PyViz.plot_index = {}\n",
       "}\n",
       "\n",
       "/**\n",
       " * Handle update_display_data messages\n",
       " */\n",
       "function handle_update_output(event, handle) {\n",
       "  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n",
       "  handle_add_output(event, handle)\n",
       "}\n",
       "\n",
       "function register_renderer(events, OutputArea) {\n",
       "  function append_mime(data, metadata, element) {\n",
       "    // create a DOM node to render to\n",
       "    var toinsert = this.create_output_subarea(\n",
       "    metadata,\n",
       "    CLASS_NAME,\n",
       "    EXEC_MIME_TYPE\n",
       "    );\n",
       "    this.keyboard_manager.register_events(toinsert);\n",
       "    // Render to node\n",
       "    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "    render(props, toinsert[0]);\n",
       "    element.append(toinsert);\n",
       "    return toinsert\n",
       "  }\n",
       "\n",
       "  events.on('output_added.OutputArea', handle_add_output);\n",
       "  events.on('output_updated.OutputArea', handle_update_output);\n",
       "  events.on('clear_output.CodeCell', handle_clear_output);\n",
       "  events.on('delete.Cell', handle_clear_output);\n",
       "  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n",
       "\n",
       "  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "    safe: true,\n",
       "    index: 0\n",
       "  });\n",
       "}\n",
       "\n",
       "if (window.Jupyter !== undefined) {\n",
       "  try {\n",
       "    var events = require('base/js/events');\n",
       "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  } catch(err) {\n",
       "  }\n",
       "}\n"
      ],
      "application/vnd.holoviews_load.v0+json": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            console.log(message)\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n        if (msg_handler) {\n          comm.on_msg(msg_handler);\n        }\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n        comm.open();\n        if (msg_handler) {\n          comm.onMsg = msg_handler;\n        }\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        var comm_promise = google.colab.kernel.comms.open(comm_id)\n        comm_promise.then((comm) => {\n          window.PyViz.comms[comm_id] = comm;\n          if (msg_handler) {\n            var messages = comm.messages[Symbol.asyncIterator]();\n            function processIteratorResult(result) {\n              var message = result.value;\n              var content = {data: message.data};\n              var metadata = message.metadata || {comm_id};\n              var msg = {content, metadata}\n              msg_handler(msg);\n              return messages.next().then(processIteratorResult);\n            }\n            return messages.next().then(processIteratorResult);\n          }\n        }) \n        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n          return comm_promise.then((comm) => {\n            comm.send(data, metadata, buffers, disposeOnDone);\n          });\n        };\n        var comm = {\n          send: sendClosure\n        };\n      }\n      window.PyViz.comms[comm_id] = comm;\n      return comm;\n    }\n    window.PyViz.comm_manager = new JupyterCommManager();\n    \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n  var div = document.createElement(\"div\");\n  var script = document.createElement(\"script\");\n  node.appendChild(div);\n  node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n  var output_area = handle.output_area;\n  var output = handle.output;\n  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n    return\n  }\n  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n  if (id !== undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<style>*[data-root-id],\n",
       "*[data-root-id] > * {\n",
       "  box-sizing: border-box;\n",
       "  font-family: var(--jp-ui-font-family);\n",
       "  font-size: var(--jp-ui-font-size1);\n",
       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
       "}\n",
       "\n",
       "/* Override VSCode background color */\n",
       ".cell-output-ipywidget-background:has(\n",
       "    > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
       "  ),\n",
       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "</style>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.holoviews_exec.v0+json": "",
      "text/html": [
       "<div id='p1002'>\n",
       "  <div id=\"ca17ccfe-96f3-4312-bd2d-f158f6b99efe\" data-root-id=\"p1002\" style=\"display: contents;\"></div>\n",
       "</div>\n",
       "<script type=\"application/javascript\">(function(root) {\n",
       "  var docs_json = {\"2389479f-43d4-41e2-9e59-3cb1f13d481f\":{\"version\":\"3.3.4\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"p1002\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"p1003\",\"attributes\":{\"plot_id\":\"p1002\",\"comm_id\":\"8b8368d0550c49068a15045939f65c8b\",\"client_comm_id\":\"72386ed53d1141ecab276b4bc8f60520\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"mode\",\"kind\":\"Any\",\"default\":\"warn\"},{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"copy_to_clipboard1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationAreaBase1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
       "  var render_items = [{\"docid\":\"2389479f-43d4-41e2-9e59-3cb1f13d481f\",\"roots\":{\"p1002\":\"ca17ccfe-96f3-4312-bd2d-f158f6b99efe\"},\"root_ids\":[\"p1002\"]}];\n",
       "  var docs = Object.values(docs_json)\n",
       "  if (!docs) {\n",
       "    return\n",
       "  }\n",
       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
       "  function embed_document(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "    for (const render_item of render_items) {\n",
       "      for (const root_id of render_item.root_ids) {\n",
       "\tconst id_el = document.getElementById(root_id)\n",
       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
       "\t  const root_el = id_el.children[0]\n",
       "\t  root_el.id = root_el.id + '-rendered'\n",
       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  function get_bokeh(root) {\n",
       "    if (root.Bokeh === undefined) {\n",
       "      return null\n",
       "    } else if (root.Bokeh.version !== py_version) {\n",
       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
       "\treturn null\n",
       "      }\n",
       "      return root.Bokeh.versions.get(py_version);\n",
       "    } else if (root.Bokeh.version === py_version) {\n",
       "      return root.Bokeh\n",
       "    }\n",
       "    return null\n",
       "  }\n",
       "  function is_loaded(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
       "  }\n",
       "  if (is_loaded(root)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (is_loaded(root)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "\t  var Bokeh = get_bokeh(root)\n",
       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
       "\t  } else {\n",
       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
       "\t    embed_document(root)\n",
       "\t  }\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
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       "       style='height:15px; border-radius:12px; display: inline-block; float: left'></img>\n",
       "  \n",
       "\n",
       "\n",
       "</div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ":Dataset   [x,y,time]   (flux)\n",
      ":Cube_shape\t[101, 101, 61]\n"
     ]
    },
    {
     "data": {},
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.holoviews_exec.v0+json": "",
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<b>0</b>\"}},{\"type\":\"object\",\"name\":\"Slider\",\"id\":\"p1018\",\"attributes\":{\"js_property_callbacks\":{\"type\":\"map\",\"entries\":[[\"change:value\",[{\"type\":\"object\",\"name\":\"CustomJS\",\"id\":\"p1026\",\"attributes\":{\"tags\":[[5710900640,[null,\"value\"],[null,null]]],\"args\":{\"type\":\"map\",\"entries\":[[\"bidirectional\",false],[\"properties\",{\"type\":\"map\"}],[\"source\",{\"id\":\"p1018\"}],[\"target\",{\"id\":\"p1016\"}]]},\"code\":\"try { \\n    var labels = ['time: <b>0</b>', 'time: <b>1</b>', 'time: <b>2</b>', 'time: <b>3</b>', 'time: <b>4</b>', 'time: <b>5</b>', 'time: <b>6</b>', 'time: <b>7</b>', 'time: <b>8</b>', 'time: <b>9</b>', 'time: <b>10</b>', 'time: <b>11</b>', 'time: <b>12</b>', 'time: <b>13</b>', 'time: <b>14</b>', 'time: <b>15</b>', 'time: <b>16</b>', 'time: <b>17</b>', 'time: <b>18</b>', 'time: <b>19</b>', 'time: <b>20</b>', 'time: <b>21</b>', 'time: <b>22</b>', 'time: <b>23</b>', 'time: <b>24</b>', 'time: <b>25</b>', 'time: <b>26</b>', 'time: <b>27</b>', 'time: <b>28</b>', 'time: <b>29</b>', 'time: <b>30</b>', 'time: <b>31</b>', 'time: <b>32</b>', 'time: <b>33</b>', 'time: <b>34</b>', 'time: <b>35</b>', 'time: <b>36</b>', 'time: <b>37</b>', 'time: <b>38</b>', 'time: <b>39</b>', 'time: <b>40</b>', 'time: <b>41</b>', 'time: <b>42</b>', 'time: <b>43</b>', 'time: <b>44</b>', 'time: <b>45</b>', 'time: <b>46</b>', 'time: <b>47</b>', 'time: <b>48</b>', 'time: <b>49</b>', 'time: <b>50</b>', 'time: <b>51</b>', 'time: <b>52</b>', 'time: <b>53</b>', 'time: <b>54</b>', 'time: <b>55</b>', 'time: <b>56</b>', 'time: <b>57</b>', 'time: <b>58</b>', 'time: <b>59</b>', 'time: <b>60</b>']\\n    target.text = labels[source.value]\\n     } catch(err) { console.log(err) }\"}}]]]},\"stylesheets\":[\"\\n:host(.pn-loading.pn-arc):before, .pn-loading.pn-arc:before {\\n  background-image: url(\\\"data:image/svg+xml;base64,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\\\");\\n  background-size: auto calc(min(50%, 400px));\\n}\",{\"id\":\"p1007\"},{\"id\":\"p1005\"},{\"id\":\"p1006\"}],\"width\":250,\"min_width\":250,\"margin\":[0,20,20,20],\"align\":\"start\",\"show_value\":false,\"tooltips\":false,\"start\":0,\"end\":60,\"value\":0}}]}}]}}]}},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"p1027\",\"attributes\":{\"plot_id\":\"p1004\",\"comm_id\":\"749644672f0d43618a91cbff694a61e8\",\"client_comm_id\":\"30de795c185c4109afa91095a2cf4243\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"mode\",\"kind\":\"Any\",\"default\":\"warn\"},{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"copy_to_clipboard1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationAreaBase1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
       "  var render_items = [{\"docid\":\"2f1f3266-d68c-4848-996b-86be3795b2f3\",\"roots\":{\"p1004\":\"acd83a6d-d961-4996-a511-0de627df6c31\"},\"root_ids\":[\"p1004\"]}];\n",
       "  var docs = Object.values(docs_json)\n",
       "  if (!docs) {\n",
       "    return\n",
       "  }\n",
       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
       "  function embed_document(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "    for (const render_item of render_items) {\n",
       "      for (const root_id of render_item.root_ids) {\n",
       "\tconst id_el = document.getElementById(root_id)\n",
       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
       "\t  const root_el = id_el.children[0]\n",
       "\t  root_el.id = root_el.id + '-rendered'\n",
       "\t}\n",
       "      }\n",
       "    }\n",
       "  }\n",
       "  function get_bokeh(root) {\n",
       "    if (root.Bokeh === undefined) {\n",
       "      return null\n",
       "    } else if (root.Bokeh.version !== py_version) {\n",
       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
       "\treturn null\n",
       "      }\n",
       "      return root.Bokeh.versions.get(py_version);\n",
       "    } else if (root.Bokeh.version === py_version) {\n",
       "      return root.Bokeh\n",
       "    }\n",
       "    return null\n",
       "  }\n",
       "  function is_loaded(root) {\n",
       "    var Bokeh = get_bokeh(root)\n",
       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
       "  }\n",
       "  if (is_loaded(root)) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    var attempts = 0;\n",
       "    var timer = setInterval(function(root) {\n",
       "      if (is_loaded(root)) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else if (document.readyState == \"complete\") {\n",
       "        attempts++;\n",
       "        if (attempts > 200) {\n",
       "          clearInterval(timer);\n",
       "\t  var Bokeh = get_bokeh(root)\n",
       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
       "\t  } else {\n",
       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
       "\t    embed_document(root)\n",
       "\t  }\n",
       "        }\n",
       "      }\n",
       "    }, 25, root)\n",
       "  }\n",
       "})(window);</script>"
      ],
      "text/plain": [
       ":DynamicMap   [time]\n",
       "   :Image   [x,y]   (flux)"
      ]
     },
     "execution_count": 8,
     "metadata": {
      "application/vnd.holoviews_exec.v0+json": {
       "id": "p1004"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "plot_cubes(cube, vmin=0, vmax=400)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's fit the PSF with a 2D Gaussian to infer the FWHM, determine the flux in a 1-FWHM size aperture, and get a flux-normalized PSF. This is done in the `normalized_psf` function defined in the forward modeling (`fm`) subpackage:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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MWN8kFqtlMxbtb/RR3lREQnIcy75VhjvGaDihxXB8cJpwKExhpH13vtVPcU0BSfZ4VpfX6L88shnDyWE3Af8GRZH2HRsXQ1lTEfbMZPwr63S/PUBLZKHd7fSwsrhGSSTp67s8THZRBqlZKQTWN+h4o4+WU7WYTCayCtOxZyZT1qhdO9A2SnqunfTcVK3NvtZD80M1mC1avOemvFRE2t1Q+xgp6UlkFqRR3lTE1Ve6aDhZRUyslYUZH27nLFWHSzfjnZBoIztyOHPbK13UHq/AlhCL17PI5NA0NccqKG8uxtkzQYzNutlmr7/WQ+XhEuITtTHi59usq38Ss8lMfqTNdrzRS1ljEQkp8awsrjJ4zUnjA9p4MjE4TTAYwhFps11v9eOozCU5PYm1ZT+9F4dojnxQNTU8ExkjCihvKabnwiB5ZdnYM5NZXw3Q+Wbf5qK92znLsneF0sZ34p1VmK6NEYEg11/roeXhespbivGMz+Od8f3cGDEaGSMi8X6lk6aHarHEWO44Rtz42asvdUTGiBgW3N7IGFGOf2ONV37GLQQJE9zFW/Td/KxCAQbPA97uJ788h5TMFNZX1+l8o3dzIW3G6WHJ+3N5wKVBshyZ7/TxV7u0nMFkYnZ8joUZH+WRuWbw6jCpOanv5AGvdNL0njoqWku0Pj4+R+Vhba4Zvj5KUlrSO3nAz9ppeLDmnT4+MkP1MW1uH+0cIy4xbrNM117uoOZ4JbYbeUDvBLX3a3PNWPc41lgreeXaONn+ahcVh8qIT47kAe1O6h/Q5prxvkkACiLjZOe5Hkoai7Q8YHGNgStDNL5Hm2smB6fZWN/AUVsAQPf5PvIrtPvkX/bT83Y/zQ9rudT0yAxry2sUR94o9V4YIKcki9RsOwF/gI7Xe96J99gsiakJm3/uvzxEZkE6abmpm/FuPl2P2WJmdmKehekFylu1cXKwbYTUrBQyCtI3v13X9J46bUyd9jIz5qHqSLkW73YnSfYEsiLz0tWftVN/sprY+Fh8Hh8Tg9PUHNfmmuT0JPLKc8iNzEvXXumk5ljFZrzHeiaoi8ztrp4JzFbzZizaX+umvKVEm5e8Kwxdd9LwoBbvif4pQqEQhdWRNvtGL0X1hSSlJrK2tEbfpSGaTmnxnhqaZt0foKhWa7Ox8bGUtxSTkpmCf8VP9/l+WiK5q3t0hpXFVUoibyb7Lg6SXZx5c7wjbTbLkYE9K4Wy5si8dGWY9LxU0vPeabM34j03Oc/c5AIVkXlp6NooKRlJZBZmUN5SckubdY96qDqqxXukw0lCcjzZxdqhsW0vdVB7fyW2BJsW74Fpau6rpKK1BGe3i1hbDLllWpt9t8eI5PSkO44RN/qYnjGiNJKP3mmMqGgt0T1GbOYBtxkjbpTpTmOEf2ONs6/8iF9E5QGKu80v5gHNzQ5stgSuXRujuiqXuPgYlpbWGB2dpb5em1tcY3OYzCYKCtIAaG93UVaWRWKijZWVdQYG3DQ1aePixMSClus7tKdMOzvHKXJkUFGRzdpagJ6eSVpatH46NeXF7w9QHHl/1z7mJj83ldSUePzrG7R3T2wu6k/PLLK07KeyVBu/egamyc5MJj01gY2NEG2dLg43OTCZTLjnl1jwrVAZmS/6ht2k2xPITE8iFApzpWOM8sjvnJ1fxjO3RHVkfh4YmSElKY7syMGjb/e4aK7JJ9ZqYc63ytSMj7rItUOuWeJtMVRFDuK+3OmiriKXeJsV79IazskFGiPj4sD8AlaLmcIs7X3vlb5xaoqzSbDFsLTqZ2B8lpYKbVx0Ti8AUJSTCkDbwAQVBRkkxdvwWgJ0u2Y4Uq7dmzGPl0AwSFmOFu9rI5M4MrXfsboeoH10mmOVkXsz52PFH6AiL4NQDLSPTZOflkxGUgLrG0Euj0xsLuxPLiySHBe7+efOcTfZKYlkJSeyEQxxcXicY2UFWMNmZnzLeBZXqC2I3JuJGdIT48m2J21++/tIWQFWi5nZxRWmFhapd2gx7J/0kBRvoyAhSYt37xgtZXnYYqwsLK0y5vHSWKLF0J4QhyPTTn6G9lT0pX4XDcU5xMXG4F1eY8Q9T3NpHpZ1GJ2ax2I2Uxg5P+Vq/zhVjiwS42JZXl2n3+WhpVKL95h7gVA4THGO1r6vDUxSlp9OSryNVX+ArmE3h2u0eI/PeFkPBCnN1+Jti7FQ5cgkNTmetfUN2gcnORpZIJ+cXWRldZ3SIi2n7BqZJi8jmbTkBAIbQa72T3CsxgEmyElLIjUpniqH1i57nG4y7Ylk2hMJhcJc6nVxpLoQs9mEx7uMx7tMTVGkfY95SE2KIzstiWpHFhe6x2itzCfGamHet8Lk3CJ1JVq8B8dnSYyNJS9yiPHFnjEay/OIuxFvt5fGslyqi7IYnpwjNsZCQaQ9Xe4dp64km3hbDIsrfkZcszRVaLmqc2oBswkKI232Wt8EFY5MEuNjWVlbp885Q0tVZDxxewmGQhTnRsaTgUlKC9NISYxjbX2DrsEpDkXyrIkZH/71DaoieUvn4BQF2XZSk+PxBza43je5+QHA9OwiS0t+KiIx7B6aJicjiXR7IhvBIFe7xznS4KCqJIuZ+SXmfStUFWsx7B3RxoistCSCoRBXO1y01hVgsViYW1hmZm6J6kg+NDg6Q3JS3Ga/v9TupLmmgJgYC/PeFaZmfNRW5LK+tsLFW9MAkTzga1/7Gl/5yldu+vs//dM/5amnntqxVw8+n48PfOAD/Lf/9t84cuTIu/q7fh61XY8O9vpr+oXV+bh6J7a+SMd2PYXVebh6J7e8Ru92PYVVebj6tnbp2a5Hj2cvt+sprMzB1T+99UU6YlRYkYNrIIpHB3o8erbrKazMxdU/Ff0X7uF2PYVVubj6opRJx3Y9uusm4RGq115v16Orv+pAl0fHdj3RPHfarmdusoG0tJ1/4Wx+PkR6Xof6mr5i1xgyD9hDj6RLskwSGK1eRvNIYrS6Gc0jxb3Y7++0XY/KAxRGYa+363E40hkbm9vyGj3b9RQVpOEcn9/yGj3b9RTlp+Gc2NoD+rbrKcpLwzm5tWsvt+spyU5lxL2w5TV6tuspyUxlxLO1R882KyVZqYzMbO3Rs11PSXYaI+7o92wvt+spzk1jdGrrMunZrqc4J43R6Sh109GE9Hj0bNejp157uV2Pnj4G+rbr0ePSc++jjSF32q5HIg9ITL9MYmLiTX9vs9mw2W7t2FLb9SwuLvK+972PX/mVX+GP//iPN39ObddzQFmaXxLyLIt4JF2SZZJgcX5FxrNgNI+x4gywKHTvpeom5jFYmwbj9dedenbz1bwbL4XiXkQuD5DxSLokyySB0eplNI8kRqub0TxS7Kd+r/IAxUFlcVFm5dW3ZCwPwOKynEsC38rtt+3YtmfVYJ4VY8UZwCd076XqJuYxWJuW7GNSrsUdjiESeYDNZiMlJeWm1+0W+AGys7M5dOgQ3/3udwH4wQ9+QGFh4U0L/AAf+tCHePHFF5mamiIcDvPss8/y4Q9/GNAO133/+9/P+9///psW+AHe//73c+XKFXp6egD4y7/8y82fk0It8huQ0iaZPfhKd7jv1W1dQvvwlTYZa7+y0oZCGU+9sTxlBtvrEKBMqD1K1U3MI9jPpJDqZ3KencUoGA7v+qVQ3IuI5QFCHkmXZJkkMFq9jOaRxGh1M5pHiv3U71UeoDiolJVliXgqSozlAaiIbDlnFKryZcpTnSfjqRLyVBYYK84AlQ6huhXuT48UFUJxBqgokun75cU789yNPOC5557jueeeo6qqii9/+ct85zvfAeDjH/84L774IgBlZWU8/fTTnDx5koqKCrKysnjiiScA+F//639x4cIF/umf/omWlhZaWlr47//9vwOQnJzMt7/9bX7t136NiooKXC4XX/jCF3YUmzuh9uRXKBQKhSEJRV67+fnt0t/fz0c/+lE8Hg92u52//uu/pr7+5gOIR0ZGePzxx7l69SqlpaW0tbXd9O/PP/88X/7ylwmFQjz88MP85V/+JTEx7/4WLwqFQqFQ7CfuRh6gUCgUCoXCGNyNPKC6uprz58/f8vff/va3b/rzmTNnOHPmzC3Xff7zn+fzn//8Hf2PPfYYjz322A5Kpg9DPcn/2muv8YEPfID8/HxMJhM//OEPb/p3k8l029dXv/rVOzqfeuqpW66vqal5l2uyO/ovD8l4rgyLeCRd/VdGRDxSDLSNyniuGcvTf3VExCOJWBsSqpuYR7CfSSHVz+Q8xovRnXjiiSf4xCc+QV9fH5/97Gd5/PHHb7kmJSWFP//zP+fv/u7vbvm34eFhvvCFL/D6668zMDDA9PQ03/zmN/eg5PsDlQdoiOUBQh5Jl2SZJDBavYzmkcRodTOaRwrV7xX3MioP0OiLdo6ZTnoFzowD6B2U8QD0DLvFXBJ0jcmUp3NcxtPlkvF0C9VLku4RobqN7k+PFD1CcQboGRYaQ4bkxhDF1hhqkX95eZnm5maeeeaZ2/775OTkTa+/+qu/wmQy8aEPfWhLb319/U0/d+MwBKOSWSBzOFRmfpqIR9IlWSYJMvJS96fHYHEGuTLtV48kRuuvO/WECBPcxWu7e/G63W4uXbrEb//2bwPaXntjY2MMDAzcdF16ejoPPPDALQf4ALzwwgs89thj5ObmYjKZ+OQnP8nf//3f76j+BxGVB2iI5QFCHkmXZJkkMFq9jOaRxGh1M5pHiv3U7/c6D1DcfVQeoJGZmSzjyUiS8aTLeACy0uRcEmTbb83nd+RJEfJIlcdurDgDZAvd++xUg3kM1qYl+1iWUN/fqUflAdvHUIv8jz76KH/+53/Or//6r9/233Nzc296/ehHP+L06dOUlZVt6bVarTf9XGamsfbM+kXSclMN5ZF0peXaRTxSpOXIlCct21iedKF6SZIu1Iak6ibmEexnUkj1MzlP6o5+Lhje/cvv9+Pz+W56+f23P9BqbGyMvLw8rFZtJzuTyURRURFOp1N3mZ1OJ8XF7+w9XFJSsq2fP+ioPEBjf+cBMh4pjFYvo3kkMVrdjOaRYj/1e4k8QHFvofIAjfR0mYXejDRjeQAyUhPEXBJkCi3OZyXLeDKFPBkpxoozQIZdpkyG8xgs1lL10lwy7TE9dWcelQdsH0Mt8m+H6elp/uVf/oXf+73fi3ptf38/+fn5lJWV8Vu/9VtRF1xutyi0lwQDQRnPhowHBMsk5JHCaLGW8mwYLM4gV6YNqRjt41gbrb/u1BMSeH3ta1/Dbrff9PrSl760uwopDIHKA/bOI+nat3nAPvVIYrS6Gc0jxX7q9xJ5gGL/sq/zgA2Z1rthMA/ARtBYPVOqPPvVI4nR6ibmCRkr1pL3fiMolAfs0KPygO1jCod3cNzwHmAymfjnf/5nfu3Xfu22//6Vr3yFL3/5y0xMTBAXF3dHz7/+67+ytLREdXU1k5OTPP3004yPj9PR0UFy8u2/BvfUU0/x9NNP3/L3p/ggVtMuD080W3b38xFMZpOIRxSLTN3MNpuIh/g7t4vtYJI6MFNogAwHAiIegLB/XUYkVDekJkjzPfv5ZXSEYmSkoX8jHOAV//fxer2kpKQAMDc3x8h4LalpO7+XC/Mh8jLbbtlWx2azYbvNOON2u6moqGBubg6r1Uo4HCYvL49z585RUVFxy/Vnz57l05/+9E0H7371q19lcHCQZ599FoCf/OQnfPGLXzT818KNyL7NAxQKhUJxExvhAGf50buSB5QUdJOebqwtlRT6MGIe8OBDf4LVurv3mIEk665+/gZhmbfehCxy6wob8TKu1QyZ93KrOTLvdzaSZd5/mQIy8bHNy73Xtc3KeGJWZGJtEloOCAn1j7BQqKXqBWAWWnoxCT3mLlGejcAal1/4Y5UHCHDProT91V/9Fb/1W7+15YQO2lf+fuM3foOmpibe97738ZOf/ISFhQW+//3v3/FnPve5z+H1ejdfY2Nj0sXfkuZTdYbySLqa31Mr4pGi6WSljOfErQuAO/MIleeBKhGPJM0PyRxwJdWGxMoj5JFELEZ32RPEtOuXzWYjJSXlptftFvgBsrOzOXToEN/97ncB+MEPfkBhYeFtF/jvxIc+9CFefPFFpqamCIfDPPvss3z4wx/eUf0VW7Ov84DT9YbySLokyySB0eplNI8kRqub0TxS7Kd+L5EHKPYv+zkPaG10iHgONQh56gtFPACHa+VcEtznkCnP/flCngIZz/GSAhGPJEeqZep2uEbGI1UeKY8UUvEBuf56uG5nHpUHbB+Zj5H3mNdff53e3l7+4R/+Yds/m5qaSlVV1S0HKf48d3rKc68wW2Q+e5HySLokyySBWL2EvllhFnqSwmzAJ9mN1oaM5pHEaHXbqScEhHbxgMFOHph47rnnePzxx/niF79ISkoK3/nOdwD4+Mc/zmOPPcZjjz3GysoKVVVV+P1+vF4vhYWF/M7v/A5f+tKXKCsr4+mnn+bkyZMAnDp1iieeeGLnlVDcFpUH7K1H0mW0MdNo9TKaRxKj1c1oHin2U7+/G3mA4t5gv+cBFqn3lmIewXHFZKxFN6kYWUxC46VQfMxC5ZFELNYG6x8Wg7VpqfiA4BiywxipPGD73JOL/M8//zyHDx+mubl52z+7tLTE4OAgv/M7v/MulEyG2cl5Gc+EjEfSJVU3KeamvDKeaZl9GuemhcoztSDikWR2ckHII9UWFwzlkUQuRnfXs9tP33fys9XV1Zw/f/6Wv//2t7+9+f8JCQm4XK47Os6cOcOZM2e2/bsV+tn3eYDUnGvEPECwTBIYrV5G80hitLoZzSPFfur3dyMPUNwb7Pc8wDO3ZCzPvIwHwLOwLOaSwL0kU57pFZkYuZdlyuNeNFacAWaE7r3hPF5jxVqqXgCeeRnXTvu9ygO2j6E+3ltaWqKtrW1zf+Ph4WHa2tpuOhjH5/Pxj//4j3z84x+/reORRx7h61//+uaf/+AP/oBXX32VkZER3nzzTX79138di8XCRz7ykXe1LrthQWihd17II+maF1oMl2J+ZlHG4xHySJVHyCPJvNtYbUisPEIeScRiZDCPYv+j8gCNhekFQ3kkXZJlksBo9TKaRxKj1c1oHilUv1fcy6g8QGNuYUXG4xXyCJUHYM4n55LAsyxTnpkVIc+qjGdWqF6SSN17sXYtVJ5Zg7VpqfiA8e6ZIjqGWuS/dOkSra2ttLa2AvCZz3yG1tZW/uRP/mTzmu9973uEw+E7TsqDg4N4PJ7NP7tcLj7ykY9QXV3Nb/7mb5KRkcFbb71FVlbWu1uZXVDeUiLiqWiV8Ui6KlqKRTxSlDfK7DFWXi+z5115g1B5hPZxlKSiWebeS7UhsfIIeSQRi9Fd9oR2uf9e6AB+cn+vo/IAjfLWUkN5JF2SZZLAaPUymkcSo9XNaB4p9lO/V3nAwUPlARpVZdkynlJjeQCqiowV97ocmfI0ZMrEqD5Tpjy1ucaKM0C10L2vLhbyCJWnxmGsWEvFB6BKyLVTj8oDto+htus5deoU4fDWGy594hOf4BOf+MQd/31kZOSmP3/ve9+TKJpCoVAo9phQ2EQovPOJeTc/q7g7qDxAoVAoFDdQecDBQ+UBCoVCobiBygO2j6EW+RUag9dGZTxtMh5Jl1TdpBjquPO+2tvydE4IecZlPB1jIh5JBq87o1+kxyPVP6TKI+SRRCxGd9kTZHf76AV3/JMKxd1lsG3EUB5Jl2SZJDBavYzmkcRodTOaR4r91O9VHqA4qPQPuWU8w0KeERkPQJ9zRswlQbdbpjydszIx6vLIlKdnylhxBugbkymTVBuSKk+vy1ixluxjfaN3956pPGD7GGq7HoVGalayiMcu5JF02bNSRDxS2DOShDyJQh6h8mTK3XsppMok1YbEymPEWEvFyGAeheKgkCrUZ6Q8ki7JMklgtHoZzSOJ0epmNI8Uqt8rFPc+qfYEGU+KjCdNyAOQliznkiA9Pl7EkxEnU6+MeBlPeqJMvSRJS5YpU6qQR6o8aUnGirVUfECu7xut3+9n1JP8W/DMM8/wzDPPEAxqn/80na7DZo3j+tkuqo6UEZcUx9LCMs5OF3UnqwFw9U5gNpvJr8wFoOP1HsqaikiwJ7DiW2Xw+hiND9YAMDE4TWgjSGF1PgBd5/twVOfT+kgDSamJ9FwYpPlUHQBTIzP4V/wU12l7tvdeGiSvLAd7ZjLrq+t0vtlH6yMNALidHpa9Kxz/P1rJLEin7/IQWYUZpOXYCQaCXH+tm5aH6zGZTHjG5/DOLFIe2TN74OoIaTl2MvLTCAVDXDvbRdNDtVQdLcNiMeOZmKfykLav5vB1J0lpiWQ5MgC4erabhpPVxNisLLh9TDs9VB8pA2C0y0VcYhzHf6WFzPw0rp3tovpYOXEJNhbnlnD1T1F7vAKA8WEP1hgruaXavl0db/RR3lxEfFIcy95VRrvHqbuvYjOGAPnlOVoM3xqguLaARHs8q4Ewg+1jNNxfEYmhh41AkMJK7dqeS8M03l9BRl4q/pV1eq+M0PRAlRbDsVlWl9cprsnDZLHQ1+Yk25FOakYSgfUgnReGaHmgEgDP5AJFVTlk5Nq1GLa7yMi1k5aVTHAjRPtbgzSdqMBMmLlpL/Mzi5t77w91jmPPSCIj1044DCYTpGYmYbFaWJhZZGZigcpmbX/9ke5JElPiyMzR3ii1vdZD3bEyYuNi8c0tMTkyQ3Xk3iSnJbKxvkFOUSYA19/oo/pQMbZ4G4sLy7j6p6k9WgaBAGP9U1isZvIjey22v9lPeZODhKQ4lhdXGe5w0XC/VtfxITfhUJjCCi2GnW8PUFyTT1JyHKvLfvqvDNMUad+TIzME1gIU1WjtOzYuhhibFXtGMv7VdbrfHqTlVO1mvFcWVymp1c426Ls0RHZRJqnZKQT8ATre6KPldB0mk4mswnR8nkXKmoo222x6birpealam321m+aHajBbzMxNLTA35d3cE36ofYyU9CQyC9IobypirHeShpNVxMRaWZjx4XbOUnVYi+FIl4uE5HiyI+277Ww3tcfLscXH4p1dZHLITc3Rcsqbi1jxrRITF0NeidZmr7/eQ+WhUuITbSwtrDDaM079fVoMXf1TmMwmCiJttuPNPkobHCSmxLOyuMbgdSeNJ7V2ODHkJrgRxFGVp7XvtwdwVOSQnJ7E2rKf3ktDNL+n9p0xYnWd4toCypuL8YzPkVeajT1Ti3fX+X5aH67fjPfSwjKlDVrb6rs8TJYjnbTsyBjxeg8tp+s2z+Lwzvgoj5w9MNA2SlpOChl5aZvxbnqwBkuMhflpL57xeSoPaT833D5GUlriZr+/+nLnbccIf2CNV/6DWwhiJriLz6KDbP11b4UiGu9KHtA2QuNDWr+dGJgitBGiMDJOdr3Zh6Pm5/OAAZpPa/12atit9fFIHtDzdj/55TmkZKZoecAbvbS+txGAGaeHJe8Kx3/1EBkF6fRdGiTLkflOHvBql5YzmEzMjs+xMOPbPA9o8OowqTmp7+QBr3TS9J46qo+VY7aY8YzPUXlYm9uHr4+SlJb0Th7ws3YaHqwhxhbDgtvL9MgM1ce0OXi0c0zLAyJluvZyBzXHK7ElRvKA3glq79fGvrHucayxVvIi42T7q11UHCojPjmOZe8KI+1O6h/Q5prxvkkACiLjZOe5Hkoai0i0J7C6uMbAlSEa36PlUpOD02ysb+CIzDXd5/tofE8dGQXp+Jf99LzdT/PDWi41PTLD2vIaxfXaONl7YYCckixSs+3avPR6zzvxHpulqL6QjIJ0APovD5FZkE5abupmvJtP12O2mJmdmGdhemFzj/LBthFSs1K0n40kAqnZ9s0xdWbMQ9WRci3e7U6S7AlkReb2qz9rp/5kNbHxsfg8PiYGp6k5rs01yelJBNY3yI3M7dde6aTmWMVmvMd6Jqg7ocXb1TOB2Womv0Jrs+2vdVPeUkJCSjwr3hWGrjtpuJG79k8RCoXeyV3f6KWovpCk1ETWltbouzRE043cdWiadX+AolqtzcbGxxJjs5KSmYJ/xU/3+X5abuSuozNaHtCgze19FwfJLs68Od6RNpvlyMDrWaTsxrx0ZZj0vFTS895pszfiPTc5z9zkAhWR/Gjo2igpGUlkFmZQ3lKCs3v8pjbrHvVQdVSL90iHU8sDIvvItr3UQe39ldgSbFq8B6apua+SitYSln0rxNpiyC3T2uy7PUYkpydpbfY2Y8SNPqZnjChtjMT7DmPEjbjpGSMsMRbmpxZuO0bcKNOdxgj/xhpnX/kRv4jKAxR3m1/MA5qbHdhsCVy7NkZ1VS5x8TEsLa0xOjpLfeSMNtfYnJbrF6QB0N7uoqwsi8REGysr6/RMzdJcr42LrskFgsEQxYXa/NHRM0FRQTqHmxwkJdro7p/iUOSstclpL2v+DUqLtDm3c3CS/JxUUlPi8a9v0N4zwZHI+6NpzyJLy35OHCklKyOJnsFpsjOSSU9NYGMjRFuXi8ONDkwmE+6FZeZ9K1SWaPNF37Cb9NQEMtOSCIVCXOl0cbylhMz0JOYWlpmZW6I6MtYNjs6QnBRHdob20NNbA2O0VOUTY7Uw71tlctZHXal27dD4LPG2GB5oKSErLZHL3S7qy3OJi7XiW17DObVAQ7k2LvauLWC1WHBkaO+vLw2NU1eQRYItlsU1PwOTs7SWauPi6MwCAMVZqQBcHZ6gIi+D5Dgb84nrdEy7OebQ7s3YgpdAMERZhnZvrk5McsxRQE5yEquBANcmp7mvSLs3414fK4EAlZkZhOLDtLmnKExOITM+gfVgkAtT4zxQoMV7YmmRqrQMchO1B/baZ6bJSUwiOyGRQCjI25Pj3J9fiCVoxr28zMzqyube+12eGTLiE8hJTCQMmICM+HisZjOe1RUmF5dozNbuTe/sLMm2WIpTtbicHx7jkCMPm9XK/MoqY/Nemgq0GNrj4wgEQxSkamsHF0ZcNBbkEB8Tg3d1jaHZeVoL84jJgBH3PBazCUemFsMrg+NUF2aRaItleW2dvgkPrWVavJ2eBcLhMMVZWgzbhicpz00nzRzLqj9A14ibw9VavMc9XtYDQUrztPZti7EQY7WQmhTP2voG7UOTHK2JtO/ZRVbW1qnI19p31/A0uRnJpKcksL4RpK1vgqO1DkwmyElPYmFpjSqHlg/1jLrJtCeSmZpIMBTmco+LI9WFmM0mPN5lPN5laooi7XvMQ2pSHNlpSVQ7shienKe1MtJmF1eYnF2kriTSvsdnSUiIJS9da98XesdoKssjLsbK/NIqrhkvjaW5VDuyWFpbJ9ZqoTAz0mb7xqkrzibBFoNv1c+wa47mCi1XHZ2ex2wy4cjW4t3WP0FlYSaJ8ZF4j83QWhkZT9xegqEQxblavK8PTlKalYY9KU6L9/A0h2u0Njvh8bG2vsGDzaVkpyXRMTRFYZad1GRtjLg2MMmxOi3eU7OLLC/5KY/k8N3DbnLSk0i3JxAMhrjSM87ROgfVkfWNed/K5r76faMzpKckkJmWSCgU5mqHi9aaAqwWM7PeFWbml6iJjCcDYx6SE+M4Gen3FzvHaKn+uTHC46OuLIf1tRUucysqD9g+pnC0Te8U+Hw+7HY7p/ggVlPM7mRmS9RLWh+u5+rLnVteYzJH/8pKy8P1tEXx6EWXyxK9bi2n62h7pWvLa8w223aKdmfi46KX58Eq2l7v2/IaU0z0e958spJrb/RvfVEw+peFmh+o4tq5rcsTDgSieloerKbt9d6o14X961Gv0YWOurWcqqXtbPfWF4VC0T062hDm6BOBrvLoQMqjG6EY6Rn6dcVaB9E8G+EAr/i/j9frJSVFS0Tn5ua4NNaCPTX6uHInvAtBjjjaSE9P37FDoQDhPEAHrY80cPWlDsN4JF2SZZLAaPUymkcSo9XNaB4p7sV+vxEOcJYfqTxAYVhu5AEPPvQnWK3R32NuRSAp+nOWh5scXL6+9farYR1d43Cjg8vtW3tClujrCkcaHFzSsR3sRnx019E6Bxe7tnatZshsOLGaE/39zokiB286ty7PRnL0918nCxy8Mb61xxSIHp8ThQ7edG3tsc1Hj8/9pYWcH46+NbFtNuoluohZiR7ro7UOLnZHiVH0UOvyhHT0j2M1Di70ROlnOpqiHo+eeunFHGXpRU98AExBHfdMR3+NVh6AI/UOLnXe2bMRWOPyC3+s8gAB1CK/DvZ6kV8Pehb59xwdi/x62MtFfj3oWeTXhY6FcD3oWeTX7drDRX5d6FjA1oWORf57FqEYGWnov9Mi/4WxVlJ2Man7FoIcc1w9UJO64t1hrxf5FQqF4iBxp0V+lQcojMJeL/LrQc8ivx70LPLrRc8ivx72cpFfD3oW+fWgZ5FfD3oW+XW79nCRXw9Si+F6Fvn1oGeRXw97ucivFz2L/HqQKM+dFvlVHrB99vFK2L1LU2T7jV17HpLxSLpubOViFBojW/ns2nNfuYznfiHPiUoRjySND1YLeWTakFx5ZDySSMVIqr8ard8rFEanKbK9jFE8ki7JMklgtHoZzSOJ0epmNI8Uqt8rFPc+LZHtfHbtqZPxtNYViHgADlXLuSQ4VihTnuN5Qp58Gc/RYmPFGeBQlUyZpNqQVHkOC3mkkOxjh2pkXK1CHkV01J78BsRilfnY0RIj9PGloEuyTBKI1csq83mZ2L0X8khiFSqTVeieiZXHiLE2WH/dqScYNhPcxeMTQQN9W0Gh2A53u++9m659mwfsU48kRqub0TxS7Kd+r/IAxUHFKvTeUspjEfrGvuYy1nOmVqHyxAjt2GAV+ka6lEcSqVgbzmOwWEvVC+T6607LpPKA7aMW+Q3I/LTXUB5J17xbrkwSLMz4ZDyeJRnPzKKQR6Zeksy7Zcok1xaFyiPkkcRo/XWnnhBmQrv4wlnoAB60o9gf7Os8QLBMEhitXkbzSGK0uhnNI8V+6vcqD1AcVOYWVozl8S6LeADmfDJlkmJ2WaY8M6syMfKsypRHql6SSN37Wa9Qu5Yqz6KxYi0VH4C5uxxrlQdsH2N95KQAYMYlszGalEfSNTM2J+KRYmZ8QcYzYTTPvIhHkhmXzL3frx5JxOom1F+N1u8VCqMzM+YxlEfSJVkmCYxWL6N5JDFa3YzmkUL1e4Xi3sftkXnwyz0r5BF6oA1gek7OJcHkokx5JpeEPFLl8cnce0mk7v30vJBHqjwGa9NS8QHBGM0aK0b7GbXIb0CqDpcZyiPpqjpcKuKRorKlSMbTJLPfYWWzQ8hTLOKRpOpQiYxHqA2JlUfII4lYjO6yJ4hp1y+F4l6k6ojM+SxSHkmXZJkkMFq9jOaRxGh1M5pHiv3U71UeoDio1FTkyHjKjeUBqC3JFnNJ0JArU56mLJkYNWbLlKchT+6eSSF17+uEPGLlKTZWm5aKD0BtqVCsd+hRecD2Udv1KBQKhcKQqD34FAqFQqE4uKg8QKFQKBSKg4vKA7aPWuTfDmYLmHZ3oIrJHP2TpJHOMV3XRWO43amnQPpcHa6o15qs0ZvTSM9k9OtsNl1lioYpPi7qNaPDs1GvC8dEr9fwyBzh+Cjl1jHADI/OE06M3/Ia02r0ezY6OINJTxyFBr3wWijqNcNd42CK0q51HFoz3DWu67qonk5X9ItCOurV7ox+3R4fxjPcMRb1GlO0ewGMdLqiXhfW0651lOe2bkyEdvHpe/gAfnKv2B/omr/30CPpkiyTBEarl9E8khitbkbzSLGf+r3KAxRGI5Bo1fXecCvCOpYTBsY8Ua8L61gvGBibjXpd2KLDMz6r67qNuOjX9M7MRr1uPS2qRheBvPWo13SaJ6Nel5wWfT/xsdhhkhxb78u/thYT1dMf48KSv/Xv85sSono61mfwp0d/L2vxCx3OHIh+Td+0h1CUEJh1ePonPERb9zVFrzqDY56o15l0LJcMjnkwB6NfJ0U4SjfrH/dEvQYAPWPIePQxRM++9/0Ts4S2GNPCd4ifygO2j9qux4Ak2qMP2nvpkXQlpmy9gL3XJCZH/yDgnvQYLM4gVybDeQT7mRRGG0OMGCOFwsgkCfUZKY+kS7JMEhitXkbzSGK0uhnNI4Xq9wrFvU9SosxDb0kJsYbyACRHezBuj0mJEYq1VeZ9vFR5km1y90wKqXuftE89UkiWRyxGgmOIYmvUIr8ByS7KNJRHc2XIeBwyHimy8lOFPHYhT6qQR+jxB0Gk7v1+9UhitLrt1KPto2fexevgfXKv2B9kCc3fUh5Jl2SZJDBavYzmkcRodTOaR4r91O9VHqA4qORkJgt5UkQ8uRky5QHITZdzSZCfKBOjvHhjefKTjBVnkLv3+9UjhWR5pPp+zg49Kg/YPmq7HoVCoVAYkt3vwac+x1YoFAqF4l5F5QEKhUKhUBxcVB6wfUxhPRsqH3B8Ph92u51T5v+E1RR9H7WtkNhrXxSde/LrUsXuLjabngSZr/Saouxtr5fd7rv4jkimq5lW/SIegPDampBHqExGG4507MmvC8k9+aXKJITEFLIRDvCK//t4vV5SUrSnV+bm5vjJyEMkp+68/y0ubPArJa+Rnp6+6zIqDjabeQAf3HUeoFAoFIqb2QgHOMuPVB6gMCw38oD7Hv2/scbsblsWPXvy6/IIrSuErHLrE/4UGddyoYxnrVjmPaqePfn1oGdPfj0EJ+W2QEuYlHmfapuXeR+vZ09+XUgtKxhs+Q4Qq5uecwv0eXZfoOD6Gle+/8cqDxDg4H2scQ9Qf6LKUB5JV939FSIeKeoOl8h4DhXLeA4LeY6Wingkkbr3dfdX7kuPJEarW/0J48VIoTAy9SerDeWRdEmWSQKj1ctoHkmMVjejeaRQ/V6huPdprMmX8VTLeJqq8kQ8AC3lci4JjmQViHha0xwinsPphSKeI3nGijPI3fvmiv3pkUKyPM2VQjES8iiio7brMSCx8TKHUkh5NJfMp862OGMduBEbJ9MFxDw2mThLeSSRuve2OKm2KOQR7GdSSJVJyhO7w3sfDJsIhnf++MRuflahuJsYMw8wXpkkMFq9jOaRxGh1M5pHiv3U71UeoDio2GJl3lsazQNgk/qWvBBxFqEYmYU8UuUR8kgide/3q0cKyfJIuWJ3OIaoPGD7GKs1KgDwehYN5ZF0eWflyiSBb07mq3dinvllGc/ckohHEql7bziPYD+TwmhjyE49ociBOTslpL6sprhH8Xl8hvJIuiTLJIHR6mU0jyRGq5vRPFLsp36v8gDFQWXBtyri8S7KeBaEPADzS3IuCeb8Mu/j59cN5lkzVpxB7t4v7FOPFJLlker7Ox2LVB6wfdQivwGZHJo2lEdzuYU8MyIeKSadszKesTkZj1PKI1MvSaTuveE8wzJ9QxKpMt1tTyhsJrSLw3J287MKxd1kYlBm/pbySLokyySB0eplNI8kRqub0TxS7Kd+r/IAxUFlYnpBxDMu5vGKeABcHjmXBKOLMuVxrcyLeJzLCyKeUa+x4gzgmhGK9T71SCFZHrEYuXfmUXnA9lGL/FvwzDPP8MwzzxAMBgFoOlWLzRrH9Ve7qTpSSlxiHEsLyzi7xqmL7Fnv6pvEbDaRX5ELQMe5XsqaikhIiWdlcZWh604aH6wBtIQ3uBHEEdkrr+t8H47qfFoerqfzjT56Lw7SfKoOgKmRGfwrforrtD3aei4MkFeWgz0zmfXVdTrf7KP1kQYA3E4Py94V3vs7DzLYNkrf5SGyCjNIy7ETDAS5/lo3LQ/XYzKZ8Ews4J3xUd6i7QU/cHWUtBw7GfmphIIhrp3tpumhGqqOlnHpp9fxTMxTeagEgOHrYySlJZLl0A6xaHu9j4YTVcTYrCzM+Jge9VB9pAyA0a5x4hJtnHjsEIPXnFx7tZvqo2XEJdhYnFvCNTBN7bFyLYbOBawxFnJLMrUYnh+gvMlBfKKNZd8qo92T1B3XvBORDx/yy7K1GL49RHFtHokp8awFYbBznIZj2v70U845AoEgjvIsLYZXnZz6YAuTo7P4VwP0tjlpul8rg9s1z+rKOsVVOYStFvquu8gpSMOekcjGepCOSyO0nNCu9Ux6Ka7KYXlRO8R2oGOCjJwU0rKSCG6EaL8wTNPxMsxmE3NuH/OeJcrrtHs+1D2BPT2RjBy7duisyURwI4jFamHBs8jMpJfKRu2ej/ROkZgcR3ZGohbvc33UHS0l1haDb26JSecs1ZH7mJyawED7GDmODACunx+guqUIW3wsiwvLuAbd1B4uJRxYx9U/jcVqJq80KxLvfsobHMQnx7HiW2W4a5z6+yo24x0OhSmoyInEe5DimjwS42NYXfbTf2WYpkj7nhyZIbAWoCiyp2RsXAwz43PYM5Lxr67T/fYgLadqI212lpWlVUpqtT0R+y4Pk12UQWpWCoH1DTre6KPlVC0mk4mswnTe/tdrlDVq+x4OtI2SnmsnPTfSZl/rofmhGswWM3NTC8xNeamIxGWofYyU9CQyC9Iobyrihf/1UxpOVhETq7VZt3OWqsNaexnpcpGQaCO7SGuHba90UXu8AltCLF7PIpND09Qcq6C8uZhX/uE8MTYreaVaO7z+Wg+Vh0uIj4wRo72T1N+n7Uvv6p/CZDZRUK7FsOPNPkobHCSmxLOyuMbgdSeNJ6s24x3cCOKI7IPZ9fYAjoocktOTWFv203tpiOb31L4zRqyuU1xbQHlzMf/y7ZfJK83GnqnFu+t8P60P12vxHptl2btCaYNjM95Zhemk5djZCARpf72HltN1VLSU8Pa/tmljRHPxZrzTclLIyEsjFAzRdraLpgdrsMRYmJ/24hn/uTGiXRsj7vvVVgbbRrn6cicNJ6u1McLtY9qpjRH+wBqv/AcKheG4JQ84XaflAWe7qDpSRlxSJA/odFEX2XPa1TuB2WwmvzKSB7zeo+UB9gRWfKsMto3Q+JDWbycGpghthCiMjJNdb/bhqMmn9ZEGOs/10nNhgObTWr+dGnZrffxGHvB2P/nlOaRkpmh5wBu9tL63EYAZp4cl7wq/9LsPMXB1hL5Lg2Q5Mt/JA17t0nIGk4nZ8TkWZnyUt5QAMHh1mNScVDLytT5+7ZVOmt5TR/Wxci7+axue8TkqD2tz8PD1UZLSksiKzDVXf9ZOw4M1xNhiWHB7mR6ZofqYNn+Mdo4RlxjHyV8/ysDVEa693EHN8UpsiZE8oHeC2vu1sW+sexxrrJW8yDjZ/moXFYfKiE+OY9m7wki7k/oHtLlmvG8SgILIONl5roeSxiIS7QmsLq4xcGWIxvdoudTk4DQb6xs4InNN9/k+Hv6tB5kYmMK/7Kfn7X6aH9ZyqemRGdaW1yiu18bJ3gsD5JRkkZptJ+AP0PF6zzvxHpulpNHB8oL29F3/5SEyC9JJy03djHfz6XrMFjOzE/MsTC9Q3qrNNYNtI6RmpZBRkP5OHhAIbo6pM2Meqo5o+cZwu5MkewJZkXnp6s/aqT9ZTWx8LD6Pj4nBaWqOa3NNcnoS/ZeHyI3MS9de6aTmWMVmvMd6Jt7JXXsmMFvNm7lr+2vdlLeUaLmrd4Wh604abuSu/VOEQiEKb+Sub/RSVF9IUmoia0tr9F0aoulG7jo0zbo/QFGt1mZj42PxjHlIyUzBv+Kn+3w/LTdy19EZVhZXKWkoAqDv4iDZxZk3xzvSZrMcGbz94yuU3ZiXrgyTnpdKet47bfZGvOcm55mbXKDikBbvoWujpGQkkVmYQXlLCS/8P//vTW3WPeqh6qgW75EOJwnJ8WQXa/lR20sd1N5fiS3BpsV7YJqa+yqpaC3h5b87R6wthtwyrc2+22NEcnqS1mZvM0Y88lsPMHB1RNcYUdoYifcdxoiKQ6W8/eMrusYIS4yF+amF244R9z92mIGrI3ccI/wba5x95UcoFEbjF/OA1sZCbLYErna4qKnIIT4uhsUlPyNjszTWav3UOT6P2WSiMD8VgGtd41SUZJKYYGN5ZZ1+p5vmyFw+PrVAMBiiqEB7P93RO0FRfjqHmxy090zQ1T/FoUi+Pun2subfoDQy53YOTlGQk4o9OR7/+gbtvRMcifTpaY+PpZV1Hn1PLX3DM/QMTpOdmUS6PZGNYJC2rnEONzgwmUy4vcvML65QFRnrekdmSLcnkJWWSDAU5kqXi8dONzA45mF2YYWZ+SVqInPLgNNDcmIcORlJAJxzumityCfWamFucYWJ2UUaSrRxcXBilnhbDKdbyukdm+Fir4uG0hziY2PwLq8xOj1PU1lkLjfNE2OxUJRqB+CCc5z63CwSY2NZ9Pvpm5nlcKEW75G5BQBK0rV4X3ZNUJWVQbLNxnz6Mh3z0xzP1mI4urhAIBSkwq7F8Ipngl8rqWV0aYHVjQBXZyc5kaPF0LXkZWUjQFVqJvFJa7R7JyiIt5Mem0ggFOTyvJP7MiLrDGs+KpOyWdzQ1gO6vJNkxyWTaUtiIxzi0twox9JL2AjE4F5bwuNfps6uxaXbO026LYGcuOTNdrcRDmE1mZn1LzO56qMhVYtLr2+GlBgbOYXavXrDNcaRvDxsFivza6uMer205GhzS6otjo4ZN4WRQ0zfGnfRnJNLvNXKwtoaQwvzHMrNIy7BzLBnHovZRFEkhpdGxqnJyyLJFsuif52+KQ+Hi7V4j84uEAqHKc1MA+Cqc5Ly7HQycmJZ8QfoGnVzpErLs1weL+uBIGV5Wvu2xViYml8iLSmetfUNrg9Pcqw60r7nFlleW6cyW7s3XSPT5GYkk56cQGAjyNX+CY7WOjABOWlJvH59hCqHlg/1ON1k2hPJtCcSCoW51OviSE0hZpMJj3cZj3eZmiKtzfa5PKQmxpGdlkRVURbf/bcrtFbmExNps1Ozi9TdaLPjsyTEx5KXod2biz1jNJblERdrZWFplTG3l8ayXKqLsvjp273ExlgoyNTa7OXecepKsom3xbC44mdoYm5zr/zRaW2McGRr8W7rn6CyMJPE+FiW19bpG5uhtTISQ7eXYChEca4W7+uDkxTnpGFPjGNtPUDn8DSHq7XxZMLjY219g0fvq6bXOUPH8BSFWXZSk+LxBza4NjDJsVot3lNziywv+6kozIzE201OehIZKQlsBENc6R3naK2DmuIsXr82zMLiKlVFkTFiNDJGpN4YI8Y4VFOAxWK+7RiRkhjHg4dK6R2d4WLnGC1V+cTEWJj3rTLp8VFXlsP62gpXUEhgCofDUudO71t8Ph92u51T5v+E1bS7fbxN5uh7QrU+0sDVlzp29Xt0e0z6PtlqfaSeqy91bq2KjR6b1tN1XH2la2tPgsxp8abE+KjXtJysoO2NgS2vCevYh6zlRDltbw5ufZGOrtZyooK2N7cuj2nVH93zQBVt5/qiXhdeW4t6jR7Ca9HLpOfe64mRLo8OdHlC0Y+cb324nqsvb903MAt+gixVJh3o8eiZQqJ5NsIBXvF/H6/XS0okEZ2bm+OFoV8iKXXnn0UvLWzwn8v+g/T09B07FAr4uTyAD+46D9BD63sbufqzdsN4JF2SZZLAaPUymkcSo9XNaB4p7sV+vxEOcJYfqTxAYVhu5AH3Pfp/Y42J25UrbIl+zZGmIi5dd27t0bGucKSxiEvtW3tC1uieow0OLnaMRb3OnxLddbzGwds9W7uWC2X20V4rjv4e9YHcYs5NjW55TXJa9C107sso5a3Z4a3LsxY9hzyRVcKbMyNbXhOcjL5ecrLQwRuu6PcsYVLmfaptPvp7Qj333hyI/ruO1Tq40B2lbjpWOXV5dDRFXR5JotRNb3lM0ZcVOFbn4ELX1i5TKHqwj9Y7uNh5Z09wfY0r3/9jlQcIoJ7kNyCjXS5DeTTXuIyne0LEI4WzX2Y7EueAlEfma9HO/ikRjyRS9954Hpm+IYlUme62Rx20ozioGDMPMF6ZJDBavYzmkcRodTOaR4r91O9VHqA4qAyPyWy9OuKS8Qy7ZLaUBRiclHNJ0Of1iHgGl2S2gh1YlClP/5yx4gxy935oYn96pJAsj5RreHxnHpUHbB+1yG9AbAk2Q3kAbPGxMp4EGY8UtniZJzJtcfvTI4nUvTecR6hvSCLWX++yJ4RpV4flhPQ8eqFQGJC73ffeTZfRxkyj1ctoHkmMVjejeaTYT/1e5QGKg0qcTWaZxhYr5BEqD0CcUJmkiLfIvG+OE/PIxCfeaqw4g9y9368eKSTLc7djpPKA7XPwTiG4B8gtyTKUByC3VKhMxZkiHilyCtMM5pH5GtGNvfiNhNS9N5xHsJ9JYbQxxIgxUiiMzI191I3ikXRJlkkCo9XLaB5JjFY3o3mkUP1eobj3ycu2G8qTn5Ui4gEoyJBzSeBIkolRQXyqiKcwQciTYqw4g9y9z8/cnx4pJMsj5coTHEMUW2Osj5wUCoVCoYgQDJsJhnf+WfRuflahUCgUCsXdReUBCoVCoVAcXFQesH3Uwbs62OuDd80WM6GgjlMwJDw6D97V49Jz8K4uzx4evKunPHoO3tUVax1dTVd8dBy8q7cN7eXBu3sZIz3o8ug45FaXZ48P3t3LGOmZQqJ57nTw7v9v4FdITN35mLu8EOB3Kn5yoA7aUbw77PXBu3s6zu2xS7JMEhitXkbzSGK0uhnNI8W92O/vdPCuygMURmGvD941m02EohxmqefgXT0ePQfv6vGAvoN3LWYTwSiuvTx412IyEYzyfkbPwbt6PHoO3tXj0XPwrh4P7O3Bu3ruvZ6Dd/V49By8q8ujoynq8kgS5VfpLY+eg3f1uPQcvBvNc6eDd1UesH0O3sca9wDVR8sN5dFcZTKeI6UiHimqmx0ynqZCY3laikQ8kkjde+N5ZPqGJFJlEvPscPy48cn9bl4Kxb1IzbEKQ3kkXZJlksBo9TKaRxKj1c1oHin2U79XeYDioFJXmSvjqRDylMt4AOpLcsRcErRk5Il4GuwFIp6mtHwRT3OO3D2TQure15fuT48UkuWpE3LVle2sPao8YPscvBrfA8QlyhyYK+WRdMUJHgYsgdjBu2Ke/XkIHMjde8N5BPuZFEYbQ4zW7xUKo2MT6ntSHkmXZJkkMFq9jOaRxGh1M5pHCtXvFYp7nzib0CGuQp54wYN343V8+38vibcKxUjo4F0xjwEP3pW693H71COFZHnixcYi47XH/YqKtAFZnFsylEfSJVkmCRYXVg3mif5VQH2eZRGPJGJtaF6mbmIeg7VpMF5/3akniJngLj6L3s3PKhR3k7vd995Nl9HGTKPVy2geSYxWN6N5pNhP/V7lAYqDim9RZktV35KMxyvkAfAuy7kkWPDLvI/3BoQ86zKeBaFteSWRuvf71SOFZHmkXDsdi1QesH3UIv82MJlNmEwy+8NtxVjvxN55dOzlBzDWPxX9Wh37jo8NuqNeZ7IIdUQd5XGNeKJfp8szG/06HXupu0Y8EK2N6SnPsI56QfTfpROTjnMLXMOeqNeFdez7OjboBkuUzSx1xHqsf0ok1mMD07J77gsw1je5LzyhsIlQeOdtdDc/q1DcTcZ6hPIAIY+kS7JMEugqj465cqx3Ivp1Os5BGuubAvPWc5ye851cA9OY9vApvrCO/Vj11I2wjvlbT6x17EN8oNv0Hrt26lF5gMJohC369tTf0qFjDB+dmo96nZ5dKEYn56JeF9JRn5HpeV3XBW3R6zY4vxD1uo14mf3NrbZg1GtG/TNRr7OYopfHueyJel1wI3oQ+xcWCAa3vs4ciB7nkZkFzBvRrzNFD5Eu9LTH4Zl5kfY4PBO9Peq4ZYzMzEftz3r2rR+dmo9+kSDR6uacnNdVf5OOXMk5MRf1Oj2/yzmxdZnu1FJVHrB9jLUypQCg7v4qQ3kA6u6rlPEckzsnQILa1mIhj8we+GKewyUiHklqhe69VBuqOy6zz6yURxKx/nqXPTc+ud/NS6G4F6k7IZQHCHkkXZJlkkCuXtUyHgPmgFKI1U0q1qpN75lrpx6VBygOKg1VMvuyN1TLeBorZfatB2gulXNJcChDZi/95jSZs/6kynMo31hxBrl731wm42kqN5ZHiqYKufI0Crl2OoaoPGD7HLwaKxQKhUKhUCgUCoVCoVAoFAqFQrFPUNv1GJA93a5Hr0tq247+KRGPFK6hGRnPsJBnyCPjGXSLeCRxDcjce6k2dLe3onk3GesVqpuUZ8fb9ZgJ6fnu5xY/r1Dci7iEtsiQ8ki6JMskgdHq5TJgDiiFVN0Md8/2aZuWdO3Uo/IAxUHFOTFnKM/opNx2JCPuvd3aJBpDizIxGlmWeR8vVZ6hOWPFGbRtn4zkkdpmZ6+364nGiGB/FYvRDsuk8oDtY6gav/baa3zgAx8gPz8fk8nED3/4w5v+/fHHH8dkMt30ev/73x/V+8wzz1BSUkJcXBzHjx/nwoUL71INZLBYd7nRn7AHwCK0T77FaqgmJ1YesfgYzCOJ0dqQEfuZFHIxurvtMYSJ4C5eoTvu7qcwKioP0DAL9T0pj6RLskwSGK1e5n08N0nVzXj3bH+2aUnXTj0qDzh4qDxAwyJ03pfRPJrLWP3SouO8nHvSY7Az40BwPcBg7dposZZcC7rbMVJ5wPYxVGtcXl6mubmZZ5555o7XvP/972dycnLz9fd///dbOv/hH/6Bz3zmM/zpn/4pV65cobm5mfe973243cZ70vkG+eU5hvJIuvJLs0U8UuQVZRjLU5wu4ynJFPFIkid076XaUH6ZsTySGG0M2alHO2jHvIvXwZvU73VUHqCRX5FrKI+kS7JMEhitXnd73H03Eaub0e7ZPm3Tkq6delQecPBQeYBGQW6qoTyFOXYRD4AjM1XMJUFxUqqIx5Eg8z5eqjzFqXL3TApHpkyZHFkynsJsY3mkcAiWRyxGOxxDVB6wfQy1Xc+jjz7Ko48+uuU1NpuN3Fz9ieL//J//kzNnzvCxj30MgGeffZZ/+Zd/4a/+6q/4wz/8w12VV6FQKBQKhRwqD1AoFAqF4uCi8gCFQqFQKHaOoZ7k18PZs2fJzs6murqa3//932d2dvaO166vr3P58mXe+973bv6d2Wzmve99L+fPn7/jz/n9fnw+302vvaT99R5DeQDaz/XKeN7sF/FI0XFxWMZzaUTGc1HI8/aQiEeSjvMy916qDbW/0WcojyRi/fUue3bz1bwbL8X+40DkAa91G8oj6ZIskwRGq5cRc0ApxOpmtHu2T9u0pGunHpUHKG7HQcgDrnW7DOVp6x0X8QBcGZRzSXDBIxOjK3OjIh6p8lxwGSvOAFcGZMok5bnabyyPFFf75MrTJuTa6Rii8oDtc08t8r///e/nb//2b3nppZf4i7/4C1599VUeffRRgsHgba/3eDwEg0Fycm7+enBOTg5TU3c+vPNLX/oSdrt98+VwOETrEY3ylmJDeQDKm4tkPE17G8tolNfly3hq84zlqS8Q8UhS3ihz76XakJxHpm9IItZf77InxG6+mmcmdG9NcQodHJw8oMRQHkmXZJkkMFq9jJgDSiFXt5J96ZFiP/V7lQcofpGDkgdUlshsByrlqSrOEvEAVBfKuSSos8vEqDpFZnuz+lSZ8tRlGyvOIHfvpTxVDmN5pJAsT1WRUIx26FF5wPYx1HY90fjwhz+8+f+NjY00NTVRXl7O2bNneeSRR8R+z+c+9zk+85nPbP7Z5/Pt6cSekBxvKI+kKyEpTsQjRXyizVieJGN5JIkXuvdSbUiunxmrTYPxxhDJsUhxsDkweUCKUN8T8ki6JMskgdHqtZ/HXbG6Ge2e7dM2LekyWowU9y4HJg+IjzWWJ07GA5Bok3NJkBQjU55Eq8z770SrTHmSYo0VZ4BEoXa0Xz1SJAr1e5Dr+1JjkSI699Qi/y9SVlZGZmYmAwMDt53UMzMzsVgsTE9P3/T309PTW+7jZ7PZsNnu3iLpim/FUB7NtSriWV6U8UixsrRmLM+iX8gjUx5JVoTuvVQbWpZq00IeSYxWt52OH8GwmWB455++7+ZnFfcG+zYP8ArlAUIeSZdkmSQwWr2k8i3JHFAKsboZ7Z7t0zYt6dqpR+UBimjs1zxgeUXmPaGYZ3VdxAOwvCbnkmAxIFOe5Q2Z999LQuVZ9BsrzgBLQvdeyiPVriX7hwRLkv31LsdI5QHb556uscvlYnZ2lry8229xEhsby+HDh3nppZc2/y4UCvHSSy9x//3371Uxt83QdaehPABD7TKu4Q6ZPeakGO6589c0t+XpNZine1LEI8lwp8y9l2pDwx1jhvJIMizVX4U8Ox0/wpgI7eIVPoB78B00VB6wNx5Jl2SZJDBavYzmkcRodTOaR4r91O/vRh7Q39/PiRMnqKqq4ujRo3R2dt72uueff57KykrKy8s5c+YMgUAA0OaYz3zmM9TV1dHU1MTp06cZGBjYUf0V0dmvecCA07MvPQB9E3IuCXq8bhFP3+J09It00C1Unh6PseIM0D8uU6Z+1/70SDEwJlceKddOxxC1HrB9DLXIv7S0RFtbG21tbQAMDw/T1taG0+lkaWmJ/+v/+r946623GBkZ4aWXXuKDH/wgFRUVvO9979t0PPLII3z961/f/PNnPvMZvvWtb/E3f/M3dHd38/u///ssLy/zsY99bK+rp5uGB2oM5QFoOFkt47m/UsQjRf2REhnPYSHPEZn9auuPlYp4JKm/T+beS7WhhhNVhvJIItZf77Lnxif3u3kp7i1UHqDR8KBQHiDkkXRJlkkCo9Wr4QGhcVcwB5RCrG5Gu2f7tE1LunbquRt5wBNPPMEnPvEJ+vr6+OxnP8vjjz9+yzXDw8N84Qtf4PXXX2dgYIDp6Wm++c1vAvDiiy/yxhtvcO3aNa5fv84jjzzCH/3RH+2o/gcRlQdoNNfInK8m5qmWOccOoLVMziXB0cxCEU9rmsz7eKnyHC0wVpwBWstlytRaIeNpqTSWR4qWKrnyNAu5djqGqPWA7WOo7XouXbrE6dOnN/98Yx+8j370o3zjG9/g+vXr/M3f/A0LCwvk5+fzy7/8y/zZn/3ZTV+lGxwcxPNzn1r+l//yX5iZmeFP/uRPmJqaoqWlhZ/+9Ke3HL6jUCgUCoXi7qLyAIVCoVDcLdxuN5cuXeLf//3fAfjQhz7Ek08+ycDAABUVFZvXvfDCCzz22GOb27188pOf5Itf/CKf+tSnMJlM+P1+1tbWsFqt+Hw+CgtlFu0OAioPUCgUCoVi5xhqkf/UqVOEw+E7/vu//du/RXWMjIzc8ndPPvkkTz755G6KtqdMDMhs2SLl0VwyXz8bH5L5+pkUE6MyXz+aGJ01lmfEWF8ZA5gQuvdSbWh8UKhNC3kkGZfqr0KenY4fobCJUHjnX7Hbzc8q7g4qD9CY6BfKA4Q8ki7JMkkgVy+ZbfKMmANKIVY3qVirNr1nrp16JPIAv9+Pz+e76e/vtN/62NgYeXl5WK3aW2STyURRURFOp/OmRX6n00lx8TtP7ZaUlOB0alsSfeADH+CVV14hNzeX5ORkCgoKePXVV3dch4OGygM0XFPzMp5JGc/Y9IKIB8A5I+eSYGRJJkbOZZn38VLlGZlfEPFIInXvpTxjbmN5pJDsry4h107LpNYDts/B++7CPUAodOfE5m54AELhkIgnLFgmCaTKs1Uyui2PVHkMFmeAcMhYbchoHknkYi3j2en4EcS865dCcS8Skup7Qh5Jl2SZJJCrl7FyN8kcUAqj1U216b1z7dQjkQd87Wtfw2633/T60pe+JFKv23Hp0iU6OjoYHx9nYmKCRx55hE9+8pPv2u9T7E+kurHQW1Qxj+Yy1vwUknofj7HWFUJC5ZHEaGsmYvnEPm3TmkvGs9PlRLUesH0OXo3vAQqrbn9w0N3yABRWCpWpwlhfiywozZLxlGTKeEqFPGUy9ZKkoCJXxCPVhgorhcoj5JHEaGPITsePG5/c7+alUNyLFArtfSvlkXRJlkkCo9XLaOO3JGJ1M9o926dtWtK1U49EHvDpT38ar9d70+tzn/vcbX+fw+FgcnKSjY0NQFuQcjqdFBUV3XRdUVERo6Ojm38eGRnZvOZv//Zvefjhh0lNTcVsNvPRj36UV155ZUf1VxxcivLTRDwOIU9RbqqIB6A4W6ZMUpQlp4t4ihNl3seXCpWnLM1YcQa5e1+cI+TJNVZ5pJCqF8j1/aK8nXnUesD2UYv8CoVCoVAoFAqFQqHYd9hsNlJSUm563W6rHoDs7GwOHTrEd7/7XQB+8IMfUFhYeNNWPaDt1f/iiy8yNTVFOBzm2Wef5cMf/jAAZWVlvPzyy6yvrwPw4x//mIaGhnexhgqFQqFQKKTo7+/nxIkTVFVVcfToUTo7O2973fPPP09lZSXl5eWcOXOGQCAAaB/8nzp1CrvdTktLy00/c/bsWeLj42lpadl8ra6uipbfFDba96UMiM/nw263c9r6IaymmHf998XGx7K+ur71Rabon8/o8pj1fbKlx2WKjdXhiWF9NbC1JyFeV5mioas8cTGsr21dHiw6Yq3Ho6Or6fIEo3/XSZcHIPKk0m4J6/Dsad10fB9MT1vU8/00XR5B9AzZ+uomFKNgUIdn6/FjI7zOy2vfx+v1kpKSAsDc3Bxf6Pj/EG+//RtxPax6/fxZw1+Rni7zRIzi4HIjDzjFB/ckD7DFx+KPNn/voUfSpctjknnqxmSxRL1mT/Mba/SjsHSNuzE6PHrzAKmt6/TkATrqFl6P3sb03LNwIHp5dLXFUPQ5TrKfSXAv9vuNcICz/MgQeUBvby+PP/44s7OzpKSk8J3vfIfGxkY+/vGP89hjj/HYY48B8K1vfYsvf/nLgLaP/LPPPktMTAx+v58nn3ySc+fOERMTQ25uLs8++yxlZWU7rofi7nMjDzj22J9hjYnblSus4zFLW6wV//ru36fp8QRjo8+5esuzlhq9crYYK/4oY/SazEPxBJKjz3FxVitrUeYws47pVI8nblZHrHXExzYfvV56PADWNaE8QEfqpqcdhWJkYhTUMXXo8ujpH3piLfhAuSlKaqL33lv8Mu3I4o+qieoJrq9x9XufN0Qe8PDDD/O7v/u7PP7447zwwgv8xV/8BRcvXrzpmuHhYU6ePMmVK1fIycnhgx/8IO973/v41Kc+xdzcHF1dXXi9Xj7/+c/T1ta2+XNnz57l05/+9E1/J416kt+AFNcVyHhqZTySruIaY32lubhSZusXw3mqjLUtEkBxtczX9ItrhDxCX0E3WpsGuTIV10iNRTv/mn5wF6+D+PU8xf6gqL7QUB5Jl2SZJBDLuaTGS7Hx23jb9YjVTSgnLRK690Zr0/up39+NPKC6uprz58/T19fHpUuXaGxsBODb3/725gI/wJkzZxgcHGRwcJDnn3+emBjtA2Cbzca3vvUturu7uX79Ov/+7/+uFvgV26a0UOYBFTFPgdwDM+W5xnr4plLoYaCKDCFPttB2PfnGijPIlUnKU54n5MkxVqwl+1iZUIzKdjiG7HUe4Ha7uXTpEr/9278NaN/cGxsbY2Bg4KbrXnjhBR577DFyc3MxmUx88pOf5O///u8BSE9P54EHHiAxMXFHdd4t0R8FUuw5SakyjSEpLUHEA5CUKuNKssuVSYJEu8y3BhJTdvdExzseqfLIeCRJFLr3+9UjiVQ/E+v3OxzTdruPnlrkV9yriOUBQh5Jl2SZJJCrl7HmFDU36fGoNr1XLpUHKBTbIylR5r2llCc5YedP0t7iipdzSZByh+27tu2Jk/FIxUfynkmRlGisuknFOsVgsZbsY1J12+k9k8gD/H4/Pp/vpr+32Wy33bpvbGyMvLw8rJFv35pMJoqKinA6nTdt3ed0OikuLt78c0lJCU6nU1eZBgcHOXToEBaLhY997GP81//6X3dStTuinuQ3IGtLa0IeHd+b0etalnGtCnmkWFuR+TqznEcmPlLlkUSsbkJtyGjlkUSqn8l5ZMY0heKgIJcHyPU9I5ZJAqnySI2XYnPcPp6b5GKk2vReuYwWI4XC6KyuybyXE/P45bYmXV3fu21O9bASkCmPVL3EPIL3TIpVPdsI6vEI1U0q1isGi7VkH5Oq291sj1/72tew2+03vb70pS/dlbIcOnQIl8vFlStX+Od//meeffZZvv/974v+DvUkvwHpuzxsKI+kq//qiIhHiv7rYzKedpexPEL1kqS/bdRYHqG2aLQ2DYJ1uyLU7y+P7OjnQmEzIT0bl27x8wrFvUjfpSFDeSRdkmWSQCy/kRovpcZvoblSEqm6ieXJl6Q8BmvT+6jfqzxAcVDpGXIbytM9LOMB6HTKuSRod8uUp31axtPhkvF0jRgrzgDdQmWSqlvnqJBnzFixluxjXUIx6trhGCKRB3z605/m85///E1/f7un+AEcDgeTk5NsbGxgtVoJh8M4nU6Kiopuuq6oqIjBwcHNP4+MjNxyze24cd4AQGFhIR/5yEd4/fXX+c3f/M3tVGtLVOZjQJreUyvkqRHxADQ9JONqeqBaxCNF433lMp7jMnttNh4XKo9QvSRpPFEl4zkp5ZFpi40Ga9Mg18+aHhTq9zscP4KYdv3aLv39/Zw4cYKqqiqOHj1KZ2fnba97/vnnqayspLy8nDNnzhCIPAUUCoX4zGc+Q11dHU1NTZw+ffqWPfwUimg0naozlEfSJVkmCcRyLqHxUmpOkZorJRGbm6RyUql7b7Q2vY/6/d3IAxQKI9BaJ3MehpTnkNC5MwBHKuRcEhwvkCnPMYeM52iZjOdwtbHiDHLtSKpuRyqF7pnB2rRkHztSJXTPdnjvJfIAm81GSkrKTa87LfJnZ2dz6NAhvvvd7wLwgx/8gMLCwpu26gFtr/4XX3yRqakpwuEwzz77LB/+8Iej1mdycpJQKATA4uIiP/7xj2ltbd1RbO6EWuRXKBQKhSG5sQffbl7b5YknnuATn/gEfX19fPazn+Xxxx+/5Zrh4WG+8IUv8PrrrzMwMMD09DTf/OY3AXjxxRd54403uHbtGtevX+eRRx7hj/7oj3YbCoVCoVAoDhx3Iw9QKBQKhUJhDO5GHvDcc8/x3HPPUVVVxZe//GW+853vAPDxj3+cF198EYCysjKefvppTp48SUVFBVlZWTzxxBMArKysUFhYyG/8xm/Q1dVFYWEhn/vc5wDtQ4PGxkaam5u57777+KVf+iU+9rGPCUVLQ23XY0CmhL4ONzU8I+KRdE2OeEQ8Ukw552Q8Y1KeWRmPUL0kmRqVufdyHpk2PWWwNg1y/WxyRKjfC37F993E7XZz6dIl/v3f/x3QPqF/8sknGRgYuOnT+xdeeIHHHnuM3NxcAD75yU/yxS9+kU996lOYTNrhPmtra1itVnw+H4WFMk9RKQ4OU0PThvJIuiTLJIFUziU1XkrNKVJzpSRSc5NUTiqWbxutTat+r1Dc80xMe43lmfFFv0gn47MyZZJizCdTnrEFGY9rTsYzPmOsOANMuGXa0bhHKEZCbdFlsDYt2cdcUrE2YHu8E9XV1Zw/f/6Wv//2t79905/PnDnDmTNnbrkuISEBl+v223A/+eSTPPnkkzIFvQNqkd+ArAsdSCLlAVgXOigjYLBDSaTKE/BvGMxjrDiDivVeIhZroTFkp7GW2IPP7/fj892cUNpsttt+RW9sbIy8vDysVm1qNJlMFBUV4XQ6b1rkdzqdFBcXb/65pKQEp9MJwAc+8AFeeeUVcnNzSU5OpqCggFdffXXHdVAcTKTmXCmPpEuyTBJI5Upy46WxyiOJVN3E2qJUvm20Nr2P+r3ak19xUFkPyLxPMZoHYH0jKOaSwC9UnvWgkEeqPAaLM8D6hlR7lKmbX8hjtFhLlkesPe4w1ioP2D5qkX8LnnnmGZ555hmCkQG76VQtNmsc11/tpupwKXFJcSwtLDPaNU59ZL9xV98kZrOJ/ArtCc+Ocz2UNRWRkJLAyuIqg22jNEb2bZ0YnCa4EcRRnQ9A1/k+HNX5tDxcT+cbffReHKQ5sofl1MgM/hU/xZF99XouDpFXlo09M5n11QCdb/bR+kg9AG7nLMveFU5/5H4G20bpuzxMVmE6aTl2goEg11/roeXhekwm8Ewu4J3xUd6sLVgNtI2SlpNCRl4aoWCIa6920/RgDVVHy7j0b9fxjM9TeagEgOH2MZLSEskqTAeg7Vw/DScqiYm1sjCzyLTTQ/XhUgBGuyeIS7Rx4gOtDF5zcu21HqqPlBGXEMvi/DKu/mlqj2n72rvGFrDGWMgtydRieH6A8kYH8Uk2ln2rjHZPUBfZu35iUHsKK788W4vh24MU1+aTmBLPmj/IYMc4DZH98qdGZwkEgjgqtGt7roxy7L11TI7O4l9dp/eqk6YT2kKe2zXP6oqf4qpcMJvouzZGdmE6qRmJBNaDdF4cpuWkdq1n0ktxVQ7Li2taDDvGychJIS0rmeBGiPa3h2i6vxyzycSc28f8zCLl9dqeZENdE9gzEsnIsRMOhzGZTOSXZGKxWljwLDIzuUBlowOAkd5JEpPjycpN2Yx33ZFSYuOs+OaWmRydpbpVO+wjOTWBgXYXOQ7t3lw/P0h1iwNbfCyLCyu4Bt3UHi6BYBDXoBuLxUzejXi/PUh5fSHxSTZWFtcY7pqgPhLDiWEP4VCYgvIsLd4XhymuyiUhycbaip/+ttHNvfenRj0E/AEcVXkAxMbFYM+cJyU9ifW1dbovDtP8YHUk3nOsLq1p8Qb6r46S7UjHnpnMxvoGHecHaHmoBkyQVZDGhX9rp7RB6wuD152k59hJy7ETCoW4/nofTQ9WYzabmZ/2MjftpbxJi8twxxjJ6Ulk5qdR3ujgB1//dxrur8Qaa8Xr8eEem6OytSTSZseJT7SR7cgA4NqrPdQeKyM2Phbf7BITQ25qjpZR3lTE2X98mxhbzGabbT/XS2VrCXGJNpa9K4z2TFB3XGsv4wPTmMwm8su0dth5vp/S+kISUuJZXVxjsH2MhhOVAEwOuQkGQxRWanHpvjBIYUUOyWmJrK2s03v5nRhOjXrwr65TXJNPeXMR//L8q+SVZmHPSMK/FqDrrQFaT9Vuxnt5YZnSei2GfVdGyCpMIy3bzkYgSPu5XlpO1VLRUszb/3oNr2dxM4YD10ZJy7aTkZeqjRGvdNL4YA3WGAtzUwvMTsxTeUjr90PtTpLTErnv/zjE4LVRrr7cScPJKmJsMSy4fUyPeqg+WoY/sMbL2sPzNxHGRGgX++mGMfG1r32Nr3zlKzf9/Z/+6Z/y1FNP7di7FZcuXaKjo4Px8XFSUlL4wz/8Qz75yU9u7uunuLe4JQ84XaflAWe7qDpStpkHODtd1EXO+XD1TmA2m8mP9NuO1yN5gD2BFd8qg20jND6k9cWJgSlCGyEKayJ5wJt9OGryaX2kgc5zvfRcGKD5tDa3Tw27tT5+Iw94u5/88hxSMlNYX12n841eWt/bCMCM08OSd4WH/88HGLg6Qt+lQbIcme/kAa920fpIA5hMzI7PsTDjo7ylBIDBq8Ok5qSSkZ+22ceb3lNH9bFyLv5rG57xOSoPa3PC8PVRktKSyIqMk1d/1k7DgzWRPu5lemSG6mPa2DfaOUZcYhwnf/0oA1dHuPZyBzXHK7El2licW8LVO0Ht/dr8MdYzgTXWSl55DgDtr3ZRcaiU+OR4lheWGekYo/4BLZca75sEoCAy13Se66GkwUFiaiJry+sMXB3ejPfk0DQb60EckXh3v9XPfb96iInBadaW/fT+XLynR2dYW/JTXF+IyWql99IQOcWZpGalEFjfoOONPlpPaznajGuOkvpClr0rgHbAbEZ+Guk5djY2grS/3kvzQzWYY2OYm1pg3u3bHFOH2sewZyaTkZcK4TCYtPnBEmNhwe1jZvydeWmkc5xEezxZJdoc3PZqD3XHy4mNi8E3u8TkyMxm3pWclshAm5OcYu3eXD/XR/WhEmy/mHeFwrj6p7FYzeSVal4t7yokPilOywM6XdTfp93HiSG3lgdUaPem6+1BimvySEyysbrsp//qyObe+5MjWh5QVP3zeUCyNi+trtN9YYiWyPlR7rFZVhbXKK7SvH2XhsguyiQ1O4WAf4OON3ppOV2HyWQiqzCdt3/SRtmNeenqCOl5qaTnpm7mrs2n6jBbzMxNLTA3OU9Fa2Reuj5KSkYymQXplLcU88L/+BetzcZaWXD7cDs9VB3R2vdIxxgJSbFkF0fi/VIHtfdXYkuw4fP4mBiYpua+SipaS3j5784Ra4sht0wr/7s9RiSnJ+Ff9t92jLjR7/WMEaWNRZF4336MqDhUyts/vqJrjLDEWJifWrjtGHH/Y4cZuDpyxzHCv7HG2Vd+xC8ikQcoFLvhF/OA1rpCbHEJXO1yUVOWTXxcLIvLa4y45miMvKd3TsxjNkNhbhoA13rGqSjKJDHBxsrqOn1ON8212lw+PrVAMBSiKF97z9bRO0FRQTpHGhxc752ga2CKQ/Xae8FJtxf/+gYlhdq43tU/SUFOKvaUeNbXN7jeO8GRSJ+e9vhYWlnnlx+ooW9khp7BabIzkkhPTSS4EeRq9zhHGhxgMjG9uMy8b4WqyFjXNzpDekoCmWmJhEJhLne7eO/xKgbGPMx6V5iZX6KmRHsfMzDmISUxjuz0JABeHx/nUHk+MRYLc0srTMwt0lCkjYuDU7PEx8bwcFM5Pa4ZLva7aCzOIS42Bu/KGqPueZpKtPmiJzBHjMVCUZodgAuj49TnZZEYG8vimp++mVkOO7R4j8wtAFCSngrA5bEJqrIySI6z4bWu0+l2cyyy777T6yUQClGept2bq1OTPFJayqjXy+pGgLapae6PfAPX5fOxEghQlZGBKQjXJ6cpsCeTkZBAIBjkomuCE8XavZnyLVGZlc6if127j1NucpOTyExMYCMY4oJrnPschcSlmZnxLeNZWqE2X4t3z8QM6UnxZKckba4HFGWkYrWYmV1aYWphkfpCLYb9Ux6S4mwU5WrxvtA9RnN5HrZYKwuLq7g8XhpKtbnFnhhH96ib/Ext7eByr4v6khzibDH4ltcYmZqnqTwPy3qY0cl5LGYzhTlavNt6x6kqyiIhPpbl1XUGnB6aI+17bHqBcAiK8rR4X++fpLQgnaREG6trAbpH3Jt770+4faxvbFASad+2GAtpyfHYk+Pxr2/QPjDJkbpIDD2LrKytU1qsvZ/uGpkmNyOZ9OQEAhtBrvZPcLTWgQnISUvi9esjVDm0a3ucbjLtiWTatTZ7qdfF0apCzCYTHt8yM95lah1am+0b92BPjCMnNYnqwiz+9qUrtJbnE2u1MLe4wuTcIvXFWrwHJmeJS7KRn54MwNv9YzQX5xEXa2V+aZUxj5emklxqCrL4yZVeYq0WCjO0GF4cGKfekU2CLQbfip9B9xytkfY9MjOP2WSiKFOL4ZXhCaryMkmKi2XZv07P+AyHI2czOGcXCAbDlGZrbbZtZJLSvDTsCXGsrQfocE5zpEJrsxNzPtbWN3j0cDU9rhk6RqcozLSTmhiPP7BB2/Akx6si8Z5fZMW7RmVBJN6jbnLSkshI0drs5f5xjtU4qHFk8Xr7MPNLq1QXRtrs2AwZKQlk2RMJhsJcbXdxqLpAa7PeFdzzS9RGxoj+yBjxUEspvc4ZLnSN0VIVibdvhUnPIvVlOayvrXCVW1F5wPYxhcPh8N0uhNHx+XzY7XZOWz+E1RTzrv++1kcauPpSx9YXmaJ/ItX6SD1XX7r9oZGbmPU1+taH67n68tYuU2xsdM+pWq6e7d7akxCvq0zR0FOelgcqaTvXv/VFluixbjlZQdsbUQ7X1NHVWk5W0vZGlPIEQ9E9euoFIPRpeliHp+WhGtpe69n6Ij11e08Nba9G8YT1eGppe3XrtkhIxz07VUtblDYtiZ4hW08/IxQ9Rq2n67j6StfWF+l4aiXa+LERXuflte/j9Xo3T5yfm5vjyStPYrPf/lAcPfi9fv5H/f8gMTHxpr+/05P8brebiooK5ubmsFqthMNh8vLyOHfu3E1P8n/1q19lcHCQZ599FoCf/OQnfPGLX+TcuXM8+eST5Ofnb+7D39nZyS//8i8zPj6+43oo7j438oBTfHBv8oD3NnL1Z+2G8Ui6dHlMMgm5yWKJXh4dOZeu/EbHeGmyRn+2RtecEqPDo2euBF3znB705AF65qbw+np0j46cNKzjqVNd+XZIxxwn2M8kuBf7/UY4wFl+9K7kAV8/9HXS09N37FAo4J084Nhjf4Y1Jm5XLj0Plh5pLOJSu3NXv0evJxgbfc49Wu/gYudY1OvWUqNX7niVg7f7tnatZUbV6CKQHH2OO+lw8MbY1uUx6/gy0oliB2+Obu2Jm40e6/sqHLw1sLXHNh+9XsdqHVzojn7PrGtCeYCO1E1POwrFRBfpqVtQx9RxvNrB271RPDr6x31VDt6K0qYl15pNUVITPX0MwOKPfu+P1zh4u2drl8UfVcOxOgcXuu7sCa6vcfV7n1d5gAAH77sL9wA9b0dZLNbtGRTxAPRcECrTxSERjxQ9V0eFPLtPwjSPVHlkPJL0XB6W8VyS8si0RaO1aZArU88FmTFEavzYCTabjZSUlJtet1vgB8jOzubQoUObT93/4Ac/oLCw8KYFftD26n/xxReZmpoiHA7z7LPP8uEPfxjQDuF5+eWXWY8sVP34xz+moaHhXayhYj/S85aOD2n30CPpkiyTBGI510Wh8VJq/BaaKyWRm5uk8mQhj9HatOr3CsU9T2f/pKE8HQNTIh6A9lE5lwRXp2TK0zYh47nulPF0DBkrziDXjtqF6tY+InTPhDxSSPax9mGhWA8aK0b7GbXIb0BufD19955sEQ9AXplQmcrkyiRBfrHMYwJinhJjlUeS/Mg2AIbxlEl5jNWmQa6fSY0hOx0/buzBt5vXdnnuued47rnnqKqq4stf/jLf+c53APj4xz/Oiy++CGgL+U8//TQnT56koqKCrKwsnnjiCQA+9alPUVpaSnNzM01NTbz00kt84xvf2FH9FQeX/AqZOVfKI+mSLJMEYjmX0LgrNadIzZWSiM1NQjlpvtC9N1qb3k/9/m7kAQqFESjMSTWYxy7iAXBkyrkkKLbLlKc4VcbjyJDxFGYZK84ADqF25Mg2VoyM1qYlyyMWox3eM5UHbB+1J78BsWcmG8oj6bJnJIl4pEhJT4x+kS5PgownTao8Mh5JUtJl7n2KUBtKSZdp01LlkUSqn9kz7u5YFAqbCOn57ucWP79dqqurOX/+/C1//+1vf/umP585c4YzZ87ccp3NZuNb3/rWtn+vQvHzpET2TzWKR9IlWSYJ5PIbY80p+3puErpnKWIeY7Xp/dTv70YeoFAYAXuKzPa1Up7UZBkPQGqinEuC9HiZ8qQJbTmcJhQfyXsmhV2oTKlJxop1mlB5pJDsY1J122l7VHnA9lGL/AbEv6JjUytdnuj7mup2rcq4pDxS+Fd1bLCnx7O2Pz2SrK/J3Pt1oTZkNI8kRuuvOx2LQrCrg3ainzqgUBgTuTxAxiPpkiyTBGL1MticouamPfTs0zYt6dqpR+UBioOK3y/0nlDKsy5zjhuAX8eZKXvJmtAZdWtC9ZLySN4zKaTKtCblkbpnBou1ZB8Ti/UOPSoP2D7q4F0d7PXBuyaTKfrhmjoO3tXl0Xnwrh6XnoPpdHn28OBdXTHScfCuLo+OrqbLo+NwWl0e2NODd/e0bjoO3tXl0XEgoe5YC6Hnd+mrm1CMdBy8G81zp4N3P3Hp/4vNvvPDzfzeNb555H8dqIN2FO8Oe33wrtS4Ijk+7WmZ9vDg3T3Nb3QcvKsrPjoO3tV9v/bw4F09ZdJz8K4uj443uPrmyt3PcXvNvdjv73TwrsoDFEZhrw/eNZl0vXUU8eg5WFRvefQcvKvHtZcH75qAaFfpOXhXj0fPwbt64qPn4F2992wvD97VUyY9B+/qatc6zmrd0/6xhwfv6r33eg7e1ePSc/BuNM+dDt5VecD2OXgbFN0DtDxcL+SpE/EAtJyWcbW8p0bEI0XzyYroF+nxnCgX8giVR6hekjQ/WC3jeUjKI9MWmw3WpkGun7WcqpXx7HD8uPH1vN28FIp7kZZHZA5rlvJIuiTLJIFYziU0XkrNKVJzpSRic5NUTip1743WpvdRv1d5gOKgcrihyFCeI3UOEQ/AsUo5lwQnHDLlub9YxnO8XMZztMZYcQa5diRVt2NVQvfMYG1aso8dqxa6Z7U786g8YPuo7XoUCoVCYUhC7O6wnJD6HFuhUCgUinsWlQcoFAqFQnFwUXnA9lGL/AbEPeoxlAfA7RQq09hs9IuEtpDR83V/98gMBKJ8/84c/Wv6btd81O8xhWOjb/Ew7V6Mfp0ej89P2K7jgDsdW7bowaRjv8eZBT+mlCiH3K2uRfe4lzDFbf39u/BG9K/Xu6d8ELP1vTXp2KppZmY5+hZTOrZo0ItJx3fvZubXMEeJdXg9+j1zzyxjSohyqLQ/+vfz3JPeLbe7MIWB29z68C4/fQ8fwE/uFfsD9+iMoTy6XXrmXacn6nUmq8yWSOb46F/vnXEvYY4yzpns0Q8NnVncwJyx9VeBwymJUT3uDTM48ra8JhQXfU6ZDlkIlWztATBtCOUBy9Hnb/dqCFPO1nswmLxLUT0zc2uYU7a+J+HFxagez+QC5ig5VUjHtv3usTkwR9kaSse2P1Lseb9/Fz0qD1AYjbBJ37YkW0uiXzLt9kW/Tkc5pmd8uooUjSlP9DEVwLIevXJuty/qdfFCw1iyM/o1SzOLpLu3vibBHX19YmNonvyJra+Lm16J6gkOWsgf8255jVnHuYL+Scgajb72ErLJ5FyBtOg5l9c8T+Lk1mX3p0fPcWbHvMQubZ2/rMRFfx8/Mb8YtT/7M6JqGAkvRr3OnyGYB0TpZv32BbzV0X9fjDd6jAbiFlks3voaPdtQjQaXWMu483VB/+3/TeUB2+fgfaxxD7CyuCrkif6Ga69dkmWSYHVJpjyryzIHk4l5lox34J5YrPepR5LVJal2JBQjg/V7hcLoyOUBMh5Jl2SZJJAan+TGXZn5e8Vgh8GC8eYmsdzWZ6w2rfq9QnHvsyx0MLiYZ03uvaWkS4IVofKsrBhr/paacyWRqpvR2vWy31hteknH+UZ77VoyWIz2M2qR34CUNMjse1XSUCjiASipl3GV1BWIeKQoron+lJsuT1WukCdHxlOZLeKRRCxGUvesJl/II1MeSYqrDRajHfb7EKZdvxSKe5ESoT10pTySLskySbDT8ekWT7XQHCc0f5eU7+c8QGZuEstthfJ2KfZTv1d5gOKgUlYkc/KslKe8UMfjzDqpyJdzSVBeIFOe0mKZWEvN30ZcDygtzRLxSLVrqbZYlWWsNl2dLnRyNVCVKVO3ytydeVQesH3Udj0KhUKhMCS7PSznIB60o1AoFArFfkHlAQqFQqFQHFxUHrB91JP8BqTv0qCQZ0jEI+nquzIi4pGir03HRn16PNfHRDz97eMyng4ZjyR97S4Zj9A9628bFfFIlUeSvmvGilG/wfq9QmF0+i4K5QFCHkmXZJkkkBqf+q4J5QFC83df14SIR5J+oTxAbP6Wym0F820JVL9XKO59ugenjOUZmhbxAHSOyrkk6BqRKU9Pv0yspeZvI64H9PYaq11LtcX2SWO16WszMvEBaJ+SqVvHmLFitJ9Ri/wGJFvo60dSHklXtsNYX2XKLtz6kDzdnoI0GU9+qqE8kojVTeqeGcwjSXahUHuUitEO+/2NT+5381Io7kWyhb7yLeWRdEmWSQKpvMRweUCuXcQjieHyAAPm2xLsp36v8gDFQSU3M/qB7/eiByAvPVnMJUFuhkx5crJlYiQ1fxtxPUAqRlLtUaot5tuN1aYLkuT6a36KUIzSduZRecD2UYv8BiQ1W2ZgTxUaRCVdqVnGGgBTM5NkPBkyHntGoownXcYjiVSMpO6ZPVOmLUqVR5JUoWRVKkb2HfZ7NakrDipyeYDcQq8RyyTBTsenX0RsbhKav1MNmAfYpXIlqflbKrcVzLcl2E/9XuUBioNKmj3BWJ6UeBEPQHqyTJmkkCqPVKyl5m9DrgekGSvWUvc+I8FYbTozXq48UnVLT9qZR+UB20ftyW9AAv6AkGdDxCPpCqzLlUmCwHpQyCNTrw2h8kh5JAkEjNWGNoQ8Um1IEqPFaKcetQef4qAilwfIeCRdkmWSQG4uMFYeYMS56W7PKb+IWJs2Wm67j/q9ygMUB5VAQGgukPJsyM0p64IuCaTqJuaRWg8QuveS7Nd2vR40VqzXQ4L9VahuO+33Kg/YPqZwOBy+24UwOj6fD7vdzmnrh7CaYu52cTRMQl/CMMs1elNsrJBHJsamGKF7ZZOpV1ioXkh5AEIhEY1J6g3l6pqIJiw0YZssQv3MKvh5qtCQHV4Xumd+/64VG+F1XvJ9F6/XS0qK9kTk3Nwc/+XNPyQ2JW7H3nXfGv9w4sukpxtvSyXFvcWNPOAUHzROHmBETDI5hckqE2Nz/M7Hj5/HZJd5UjucIvNUXShObk4xbQjlAcsy8zfeJRFNeHFRxBOSmisF33DvRzbCAc7yI5UHKAzLjTzg6Af/DGuMzNyya4Texgdj5dYDAgkyrpBQqmVdlfEkuGU+zI2bXhHxmFflPswN2WSCHUiT6Rf+dJkcZyVT5n38aq5Mm/ZnCOYBQiu4MV6ZGMXN7j5GQf8a3X/5RyoPEEA9yb8FzzzzDM888wzByKdXTadqsVnjuP5qN1WHS4lLimNpYZnRrnHqT1QB4OqbxGw2kV+RC0DHuR7KmopISElgZXGVwbZRGh+sAWBicJrgRhBHdT4AXef7cFTn03K6ns43++i9OEjzqToApkZm8K/4Ka4rBKDn4hB5ZdnYM5NZXw3Q+WYfrY/UA+B2zrLsXeG9v/0Ag9dG6bs8TFZhOmk5doKBINdf66Hl4XpMJvBMLuCd8VHeXAzAQNsoaTkpZOSlEQqGuPZqN00P1lB1pJRL/96OZ3yeykMlAAy3j5GUlkhWZG/UtnP9NJyoJCbWysLMItNOD9WHSwEY7Z4gLtHG/b/aytB1J9de66H6SBlxCbEszi/j6p+m9liZFsNhD9ZYC7klWVoM3+ynvMlBfFIcy95VRnsmqDteHomhG4D88mwthm8PUlyTT6I9nrW1DQbbXTTcp107NTpLILCBoyJHi+HlEU5/6AiTIx78q+v0Xhml6WSlFkPXHKvL6xRX50JMDH3XnGQXppOakURgfYPOi8O0RK71TC5QVJXDyqK22DnQ4SIjx05aVjLBjSDtbw/RdH85JlsMc+5F5j1LlNflATDUPYk9PZGMnJTNwToYDGGxmlnwLDEz6aWysQCAkd5pEpPjyCrS9g9ue2uIutYiYm1WfPMrTLrmqG7U2kdySjwD3RPkRPYIvn5xmOqGQmzxMSx6V3ENe6htcUA4jGt4BovFTF7E23FphPKaPOKTbKwsrjHcN0X9Ye2eT4zOEg6FKSjV9lbtujpKcXk2SXExrK2u09/uojFyH6fG5gisb+CI3JsYm4XZKR8paYn41wL0XHXSfL92b9wTC6wurVFcUgRoh9lmF6aTmhmJ99tDND9QhckEmXmpXHypk9I6LS6D7S7SslNIz0khFAxz/c1+mk5WYraYmZ/2MTftpbzJobXZznGS0xPJzEulvL6AH3zjZRruK8caa8XrWcTtmqOyResLoz0TJKQkbO5vf+1cPzVHSrDFxeCbW2ZixEPNoWLKGgp59Z8vE2OzkhuJYfv5ASqbi4hLiNXa7JCHuiNaDMeHZjCZTeSXaDHsvDBMaW0eCclxrC75Gewcp+G4FsPJ0VmCG0EKIzHsvjxCYVkWyamJWpttc9J0fwUA02Oz+NcCFFXmUtaQz79+9zx5RRmkpCex7g/QdXGYlge0cWpmYp6l2UVKarWxp7/NSVZBGqk32uybA7Q8WEV5YyEX/qMT7+wSZQ2F78Q7K5n0XDuhYIjrL3fQeLIKS4yF+Wkvs5MLVERiONzhIjktgeOPNjN4fYy2s900nKjU4h0ZI6oOl+IPrPHST7iFECZCu3gHs5ufVSjgNnnA6TotDzjbRdWRss08wNnpou5kNQCu3gnMZjP5lZE84PVIHmBPYMW3ymDbCI0P1QIwMTBFaCNEYU0kD3izD0dNPq0PN9D5Ri89FwZoPq3N7VPDbvyr6+/kAW/3k1+eQ0pmCuur63S+0UvrexsBmHF6WPKu8Eu/8xADbSP0XRoky5H5Th7wahetjzSAycTs+BwLMz7KW0oAGLw6TGpOKhn5kTzglU6a3lNH9dFyLv60Dc/4HJWHtTFq+PooSWlJZEX2tb/6UgcND9YQY4thwe1lemSG6mPaGDXaMUZcUhwnf+0IA22jXHu5g5rjldgSbSzOLuHqm6D2/kgu1T+NNdZKXpk29rW/1kNFawnxyXEsL6ww0umi/qR27XjkoLuCSLw73+ijpL6QxNQE1tZDDF5z0hC5dmp4ho3ABoVV2hzcc2GIh//LcSaGZ/CvrNN7aYimh7Qcze2cZXXZT3FtPqbEhFvnpQvDtDwQyQMmFiiqzmVlUVvoHmh3kZH7c3nAW5E8IDmBuZlIHlAbyQN6prCnJ5CRfZs8YHaJmSkflfVa+xjpnyYxKY7MYi3vunphmPpmB7E2K96FFSZd89Q0aHNjUkocAz1T5Eb25L12eYTqugLiInnA2OgsdU2FmIIhxkZmsVjM5Du0+a79ipPy6lwSEmNZXvIz3D9NQ6s2P4875wiHwxQWa/e8s22M4vIskmIsrK2s099x5zwgNtaCZ1rLA9bXAnTflAfMs7rkp7hZK39/2yjZhenYM5PZWN+g461BWh6sApOJrLxULvysk9L6SB5wfYz0HDtpOSnavPRGP83vqcVsMTM3ucDc1AIVrVr7HrruJCUjicyCdMqaHPzgaz+l4WRVpM36cDs9VB3Ryj/S6SIuzrq5537by53U3l+JLT4Wn2eRicFpao5XUNFSzMt//yaxcTHklmp1vf5qN1VHSolLjIwRHU7RMSI5PQn/sv+2Y8Qj/+cDDLSN6BojShsjedcdxoiK1lLe/pcrusYIS4yF+amF244R93/gMANtI1z9Wfttxwj/xhpnX/kRv4jKAxR3m1/MAw7VFRIbl8DVLhc1ZdnEx8WytLzGsGuOxsh7+rGJeUxmKMyNvIfoGaeiKJPEBBsrq+v0j7hprtXm8vGpBYKhEEX52rje0TdBUX46RxoKud47SdfAFIfqtfcxk24v/vUNSgq18bdrYJKCnFTsKfGsr29wvXeCI5E+Pe3xsbSyzqMP1tA36qFncJrsjCTSUxMJbgS52j3OkQYHmExMLy4z71uhqlh77903OkN6SgKZaYmEQmEud7v48PtaGXR5mPWuMDO/RE2JNtYNjHlISYwjO13bju3NYRetFfnEWi3MLa4wMbtIQ4n23ntwYpZ4WwynW8rpHZvhYq+LhtIc4mNj8C6vMTo9T1OZNjcOzs4TYzFTmKlt9XV5YJxaRzYJthiWVv0MTMzSUq7F2+leAKAoOxWAtsEJKvIzSIq34fcF6Bl1c6hKmy9cM142giFKIvemfWiSR++rweX2srYeoGNomiM12r2ZnPWx4g9Qnp+BLS9Id/8UudkppNkTCGwEud45zuFmLd5uzyJlxZksLWvrAX2D02TeiHcwRFuHi9ZGB3HF68zOLDI/t0xFtTYHDPZNYU9NJDM7mRvP34aCYSxWM/Ozy8xMe6mq0+o6POAmMclGTpr20ED09YBJcgq0uNxpPSAcY2VsdBaLxUR+ZF2n/aqT8qocEhJtrCz7GeqfpqFFq+vE2Byh0M/lAdfGKC7LIi4/hbXVdXr7pmlujrTZyQUC60GKItfGxliY8Sxityfg9wfo6pqgtVV73zg97WNlxU9hoxaX7sEpcjMj8Q4EudbzTpvNTk/izSvDVETWi/qG3WSkJpKRlkgoFOJKp4ujlYWYzSY8vmVmvMvUOrQ22zfuwZ4YR05qEtUFWfzty1c4VJ5PTKTNTs4tUl+stdmBiVks6TYKIvvSnx8Zo6Uwj3irlbnVVZzzXlryc6nNyeT/7ezDZrXgSNXa7AXnOA152STExOBb89MZmuFIrnYfh7zzmIBSu9YOL0yNU5ueSXKsjaXAOp0eN8fztPs44tPGiPJU7d5cnp6g3J5Oqi2OlY0A19xT3J+vxXts0cvqxga/VllNl8fDVfckxSmppMfFsxbc4NLUBA8URPK5JR+rgQDVWVqO0zHlJjclicyEBDZCIS6MjXN/sYO6nCzODg4zt7JKbbYW7y73DJkJCWQnJRIKh2mbHedIWQFWixnP4jJu7zJ1hZF4T3pIibdxqq6UngkPb/WPcag0MkYsrTA+t0hjUQ7rqyt0cysqD9g+6kl+Hez1k/ytjzRw9aWOrS/S8SR/6yP1XH2pc+uLdD7J3/pwPVdf3tql50n+1lO1XD17u+778569e5K/5cEq2l7v2/oiHU/yt5yspO2N/i2v0fMkf8uJctreHNz6Ij2e+8poe2so6nV7+SR/y4kK2t4c2PoiHU/y67lnep7kb3momrbXere8Rs+T/Lra0B4/yd/yQBVt56LESMfTiXpipOdJ/pZTtbRt0e/v9CT/f37jj4jZxSf3Ad8aL5z84oH65F7x7rDXT/K3vreRqz9rN4xHt0vHk/x6PHv5JH+08Qn0Pcnf8kAlbeei5AE6nuTXM3/reZK/9VgpVy8MR71uL5/k15UH6HiSX8/cpOdJfj25rZ4n+XXl7Xv4JP+e93sBz52e5Fd5gMIo7PWT/Ecai7jU7tz6Ih1v4/V49DzJf7TewcXOsajX6XmS/3iNg7d7tnbt5ZP8x2odXOjeujx6nuQ/3FzE5Wtbx1rPk/x65m89T/LrXQ/Yyyf5Dx0q5sqV0S2v0fMkv552redJ/uPVDt7u3fre63mS/0SJgzdHtvbs5ZP8DxQUcW48yviBvif5TxQ7eHN067rpeZL/vkoHb/Xf2XOnJ/lVHrB91JP8BsTjmjOUB8AzLlSmiXkRjxSeSa+MZ0rK45PxTMt4JBGL0eSCwTwy9ZLEM7Ug45GK0Q77vdqDT3FQ8bhmDeWRdEmWSQKpvEQsnxCavz1ulQdE9UjltkIeKfZTv1d5gOKgMjMrs+WYlMc9J7OVGsD0gpxLAve8THlmZmU8UvO3IdcDZozVrqXa4tSisdr05LJMfECubtM73I5R5QHbR2jDaYUkPqFByyc00Ui6fIIJggSL88vG8izI7NMn5ZFErG5SsZ4z1r2XRKxuYh5j9XuFwuiIzblGzAOEchwppMYno+UBvgWhjYgFEcsDhOam/dqmjdnvVR6gUGwH75LMOSfeRSGPUHmkXRIsCJXH55OZd6XmbyOuB3iFYiTWroXOE1oQOldQivk1ufJI1W1B6uwmRVQMtcj/2muv8YEPfID8/HxMJhM//OEPN/8tEAjw2c9+lsbGRhITE8nPz+d3f/d3mZiY2NL51FNPYTKZbnrV1NS8yzXZHWWR/fF37ykS8QCUNcm4yhocIh4pSiP72+3aUyvkqcmV8VTLeCQprcmT8UT24t+1p17II9SGJDFcjHbY7298cr+bl+LeQuUBGnJ5gIxH0lXWXCLikWKn49MtHql8Qmj+LqvKEfFIIpYHCM1NYrltk1w/k8CY/X5nHpUHHDxUHqBREdkff9eeEhlPZeRsEgmqCuVcElQ5ZMpTXioTa6n524jrAeWRM3p2i1S7riqQufc12cZq03UZMvEBubpV5+/Mo/KA7WOoRf7l5WWam5t55plnbvm3lZUVrly5whe+8AWuXLnCP/3TP9Hb28tjjz0W1VtfX8/k5OTm69y5c+9G8RUKhUIhSCi824n9btdAsV1UHqBQKBSKG6g84OCh8gCFQqFQ3EDlAdvHUHvyP/roozz66KO3/Te73c5//Md/3PR3X//61zl27BhOp5Oiojs/jWO1WsnNNd4nmXdi4Gr0g9J0ea6MiHgABq7KuAaiHEaz1wy2u2Q8nVKerZ9E0e3pnhTxSDLYOS7jkbpn16MfHqXLI1QeSQY7DBajHfb7cNhEeBefvu/mZxV3B5UHaAxckcoDZDySLskySbDT8ekWT4fQHCc0fw/07OM8QGhuEstthfJ2KfZTv1d5wMFD5QEafcNuQ3l6R2Q8AN1OOZcEPULl6RuU8UjN30ZcD+jvnxbxSLXr7jEZT+eUsdp0h0euPJ3TQrF27cyj8oDtY6gn+beL1+vFZDKRmpq65XX9/f3k5+dTVlbGb/3Wb+F0Gmuh+RdJz02T8eSlingkXem5dhGPFGk5KTKeLBlPelayjCczScQjSVq2UKyFPOk5Mm1Rqg1JYrQYSXkUil9k3+YBUnOuEfMAwTJJIDYXZBtr/k7PlCmPJOlSMZKam3JTZTx5Mnm7FKrfKw4S+zUPyEhNNJQnU8gDkGmXc0kgVZ6MdBmP1PxtxDxAKkZS7TpL6N5nJRmrTWcnyJUnW6humSnGitF+5p5d5F9bW+Ozn/0sH/nIR0hJufOC1vHjx/nrv/5rfvrTn/KNb3yD4eFhHnzwQRYX73xIlt/vx+fz3fTaS4yYUIu9ETLYYl+61GKo2AK2zGScJvRhgSRiH2BIfTAj5JG695KItUepWO/ww70Qpl2/FPuX/Z0HSH3YL7f4aMQySbDT8ekXERt39/OH/UIPRIjN32IPsMh4pNhP/V7lAYqt2M95QEaa0GKolEdwkV9qYVUKsUV+oVhLzd9pWcbLA9IzZMokFWuphWephXApJBf5sxKFPgjZYaxVHrB9DLVdj14CgQC/+Zu/STgc5hvf+MaW1/781/2ampo4fvw4xcXFfP/73+f3fu/3bvszX/rSl3j66adFy7wdQsHQnnlMJn2NPhwKR782FP33hTaC0a+T2jjLFhu9PBZL1Os2clKjegL2hKjXrebHR/WsOFJYqt/6UBJ/siWqZ6Esidn19KjXWQIysY53B6Jes5aVxFpJxpbX2CajJ9DB+DjCqVsvgpiWVqN6whYLpjjb1hfFRB8iQzExkLD1vQ0lxEX16EbHR7PBpDhCGVsvgphW16N6QvFxEDXW0dtjOCYWU2LCnR0hK9zm1u/2sJyDeNDOQUHlAXvr0esyWXSMB+Ho15njhcbM7K3nHIBQclLU6/yF0Rco/Tl2/FEOlFsqiJ6XeEsTmVvb+vetp0Qf2+Yq43ETfTHc4o96iS4SpzaiXrOal8xK1dY5TrwzyrwMhFKSCOdsfc9MYR05aWwspihvzE2LS1E9YZMJU5R8Ibwu1xcJb5277XW/fzc9Kg9Q3Im7lQeYwtprN+hpliEd76v1eIKhUPTrdNQnFAzrui5mOfpFppVQ1OtiVmTGnvjptajXJCSsktazvOU11mlvVE+sPZnE7q23JAmv6HiPWpyK2TWz5TUma/T3qOHFFUze6HOYOT76vKuH2EAw6jWW2RVi3VvH2rIWvTwxuWskTGx9b9eT7vze8wamtTDWKE3EnxW9XmspG1Gva2gYjerRS2rsypb/XpsUgvzeqJ5r0wVRr7GmpxKXsrDlNcsD0R+YWckIsrx6534dWrv9v6k8YPvcc0/y35jQR0dH+Y//+I8tP7W/HampqVRVVTEwMHDHaz73uc/h9Xo3X2NjMnt/6uXa2S4hT7eIB+DaqzKua6/1iHikuH5+UMRz7bLMoH2lQ6atXe4x3j7xbddk6nb9gsz+sFL3/vpbQyIeSa5dHBHxXH9bpm7X3+zf0c/d2INvNy/F/uNA5AGvdBrKI+mSynGkkBrn2tpktn643C0zf1/sN14ecLVdph+JzXHn+kQ8UjmyFIbs9zv0qDxAcTsOQh5wRei8tytdMh6puUnaJcG1KzLv46+/JfTe8o2dvW+6xfPmndv33UJq/r52RSbnutQr0xbPTxqrTXcvRV/g18uFuRERz3nXzmKk8oDtc08t8t+Y0Pv7+/nZz35GRkb0J7R+kaWlJQYHB8nLy7vjNTabjZSUlJtee0nzqTohT62IB6D5PTKu5odqRDxSNN1fLuJpPlws4jnU4BDxHK4pFPFI0tIsU7emY6UyHqF733RfmYhHkuajJSKepuMydWs6USniUSgOTB5wut5QHkmXVI4jhdQ419Jy5wMft8PhWpn5+2il8fKA1kaZPEBsjnugSsQjlSNLYch+L1gmxcHmoOQBh+plxvBDdTIeqblJ2iVB8yGZ9/FN9wm9tzwp876p6USFiEcSqfm7+ZBMznWkWqYt3p9nrDZdm1Qt5jqWXiLiub/QWDHazxhqkX9paYm2tjba2toAGB4epq2tDafTSSAQ4D//5//MpUuX+N//+38TDAaZmppiamqK9fV3tp145JFH+PrXv7755z/4gz/g1VdfZWRkhDfffJNf//Vfx2Kx8JGPfGSvq6cbs0Xmtkh5JF2SZZLAbBaql1nmE0Ipj0XII4nR2pCYR6gNSSLWri1C7XqHnnDk63k7fR3ET+7vdVQeoGG0cU7SZbg8QGwuMFYeIOWRRKxuBpu/92ublnTt1KPygIOHygM0pMYni8He60q7JJCbm/bnHCeJVN2M1q4tJmPF2ixYHrPO7b3fLY/KA7aPofbkv3TpEqdPn97882c+8xkAPvrRj/LUU0/x4osvAtDS0nLTz73yyiucOnUKgMHBQTwez+a/uVwuPvKRjzA7O0tWVhYPPPAAb731FllZWe9uZXbB3OSCoTySrrkpGY8Uc26ZQ5TmPNH3u9PD7PzWe9TpxbMg45FkblYmRvMzdz4kazuI3Xuh8kgy55Ep07xbKNbTO4t1mN1NzOEDeNDOvY7KAzTmJucN5ZF0SeYmEszPCM0Fc0J5gND87fEaLw+QynGk5t15HXss68Fwua0h+/3OPCoPOHioPEDDaO8JpeYmaZcEUu9R54TeN4nNTULvdSWRmr9nhe6ZVK7kXjVWm14IyLQhgBm/TKzdyzuLkcoDto+hFvlPnTpFeIvDpLb6txuMjIzc9Ofvfe97uy3WnjM3Zbw30lJvYOam5AYcCcTe3AtNNGIJnRHf3M8Z7M29VCJmyARKKFkVi/XOYqQO2jl4qDxAY39/2C+3ACmB1Jvy2VljLcjM+PZxHiD0YMWc1EKKwT64MmS/36FH5QEHD5UHaEgthBvtwwJplwRiD6JJPUC2w4ejfhFDvkeVmr+Ntsi/Yqw2LbnI77nLi/wqD9g+xvpeiQKAilaZPccrDpWIeAAqWmVcFS0ye95JUS6032FFda6Ip6osW8RTUyzjkaSyMkfEU16XL+NpiH6avC5PvYxHkoraO+8xuh3K64Vi3aj24FMotkPFIak8QMYj6ZLKcaSQGsP//+z9aXRj2X3eCz+YJxIAQXAC53meaq7qanW3pESxYqs9yl6OLLd81ZZtyWspftebRFI8yLItLTuJlMTt1a1IbseR7etE9pX0Oo6v3ZK61WONnOeZBEECBEAMBEDM74eDYqu6u3BOgU9VnS6e31r8wOLGU/vsc/b//+yNffZm5bjuFk7+7m2Unw/oaufUiZbjhjh7+rI8MgtZ9ntinRQUTgJdrZx42c3SIeUmthaDji7OOJ42thzinF/TPiC/8Rcrf3eS7llPE+dZHKiU1zPdYub4GwDotXLaeqBaXm30MCOrlfwKCgoKCgq3yOeFn+N8XkFBQUFBQeHdieIDFBQUFBQUTi6KD7h7lEl+GbI6sUHS2aToAMDqJEdrdWqLosNibc5D0Vld8lF0ltf3KDqLW37xQveZlRVOG63N73B0Zjn3nlUfJquLuxSdtXmSzux2SZ/LQYXcMfbRO85nFRQeJDwfwNFhajHrxIAVw1k5bmmTk78Xt2XoA9Y4Hmd1gZSbZtwUHZZHZvEw9XvFByicVJY3OPFyiaVDyk1sLQary6Qx6hxpjDpT2rjpbToljr/uJaz8vUK6Z6w5k9kgp5+x2Ezw5twWol6Kzpy/tLZWfMDdo0zyF+GZZ57BM888g2w2CwAYerwXBq0Rky/Noet0K4xlRhyEYtiY3Ub/pS4AgHtxB2q1Cq4O4bWW6Vfm0TbUBLPVjHg0gZXxDQw+2gMA8Kx4kc1k0dgtbIkx+/oiGrtdaBtqwtbCDhaurWD48T4AwO76HpLxJJr7hNeu5q+toq6tGjZnOVKJNGZeW8To+/oBAL7NAGLhOM79yDD23EEs3lhDVYMDFTU2ZNNZTP5gHiPv7YdKBQR2wwjvRdA+LGyjszy+gYoaKyrrKpDL5jDx0hwGH+1BXWsVFq6vIuDZR2fhldvVqU2UV1hQ1VAJABh7aR4Dl7qgM2gR2ovAu+FH95k2AMDG7DaMFgMGLnVhbzuIiZfm0H22DUazAdHgAdzLXvSeaxfacM0PrU6L2han0IavLaF9uAkmiwGxSAIbcx70nW8vtKEQ4F2FV8Bnr6ygudcFi9WEw7waKzPbGDgn1GF3M4B0OovGQtn5sQ30nW1F4iCJZCKFhfFNDF3sENpwO4hELIXmrlpkKyxYmPWgps4Oe4UZ6XQW0+NbGD3bAgDY80ZgtZnQ1inoLs3vwllVjopKC7KZHCbHNjF8uhmZKiP8wQMEw/GjVzCX1nywW82oqixDPp/HXvAALQ2V0GrVCIbi8AWi6GkXtgBY2fCjzGKAo9EGALg6u4XhzjoYdFqEogm498IYaBOeu3Qmiz2THi6nFQBwY96NvtYamAw6hGOH2NjZx1BHHdSZPDZ29qHRqNFQLeiOL2yjs7kKFqMesUQKy5t+DBee0S1vCPk80FRrBwBMLu2gtd6BygYtDhMpLCx6MTwsvGK4sxNCOpVFU7PwfEQjCTidZbDZzEgm05id9WB0VHjuvN4I4vEkulqEA7CWptyodtlhqyxDJpXB9I0NjFxoA1QqaLVqLE1vo7VHeN1vZdYDR1U5KqrKkcvmMHl1DUMX26HWqBH0RbDvix69Prk260F5hQXOOhuctTa88M3r6D/XCp1ei5D/AL7tfXQV6r+xsAuT3YJql3CtE6+voGe0CQajDpH9GDwbAfSMNMFZZ8PYK0vQ6bWobXQAAKaurqJzsAFGkx6xSAJr22H0jwqvzbnX/VCpVahvEtpl+uYGWrtqYCkzIh5LYmV+F4OnhXbxbAaRzebQ2Cr0hdnxLTS2OVFuM+HwMIWF6W0MnxH6465nH8nDDJrbqlBVY8XLL8yirtEBm73Q3uNbGD0v9AXfbhjxvShaumsK7b2Nqjob7M4yZDM5TF1dw8jFdlTV2TE/sYlwMIa23lvtvYMKZxkc1eXIZfOY+u40Bi+2Q6PVYN8XRWA3hI7Ca6Zrsx6U283oOdMCvyeE8ZcX0X++7c323gqia7QJyXQCL/wt3kY+f8yDdk7gHnwKXN7mA57oE3zAi7PoOtN25AM2Z9zoe6QbAOBe8ECtVsPVWfABLxd8gM2MeCSBlfF1DL6nFwDgWd5FLpNDQ0/BB7y2iMYeF9qGm+Ge92D+6jKGnxBy++6aD8lE6k0fcGUJrvYaWJ1WpBIpzLy6gNH3DwIA9jb9OAjHce6Do9jbCmDx+gqqGp1v+oCXZjH6vgFApUJgO4jQXgTtIy0AgJWxNdhr7Kh0FXzA92cw9FgfatuqsXhtBf7tIDpPC7FkbXIDZRVlqGoU4tn4i3MYuNwNnUGHkC8s+ICzQr7emHHDWGbAwCPd2HMHMfH9GXSf64DRUvABizvovdAJANjeCAo+oFXICdOvLgo+oMyIWDiBjblt9F0Q8rVnRRh8uAq5cvaNZTT31sNiMyGhM2BlxoOBc4U4uRlAJp1Fw5EP2ET/6RbEYwUfMLGFoQtCfX3b+0jEU2jurEHGWYb5+R3U1tpgtws+YGrKjVOnhFi9txdFebkR7QXdxcVdOJ3lcDgsyGZzmJjYwshIE5LVOvj3YwhG4uhqFq5tcWMPFVYzqiosQB7w7R+grd4BjUaNYDgOb/AAvQXPsLIVQJlZj8pGIbdfWdjCSFvBBxwksOUPY7BFeO5SmSzKjHq4KoWy15fcGGiugVEv+IB13z6GW+ugTgMbu/vQqN/0AWNL2+hqfNMHLLn9GOks+ABfCLlcHs21FQCAieUdtLkcqKrRInGYxsKyFyOFLQJ2vGGkUlk0F3Jj5OAQzsoy2KwmJFMZzMx7cKqwZY53L4J4PIUeV6FdprdRXWeHvdKCdCqD6ZubGDnfClXBByzOeNBW2CpxeW4HDmcZHAUfMHFtHUOXu6BWq7HvDSPoDR9tzbM240a5wwJnXQWcLjte+L/fwMCFDmj1WoT9UfjcQXQWtpbcmPfAWGNBdZOQg8e/P4veCx0wmPQI+6PYWfWi51wHqhocuPHCNPQG3dEzO/mDeWGsYDHgIBTHxsTaW2KECq7OuhJixAIau10od5QhGUu+Y4w484Fh7G0FJMWI1kGhXe4UI6qanJh/Y0lSjNDoNNjfDb1jjOi71IW9rQDGXpjCwKM9b8aI9T10n+tAMnOIF7//bbwVxQcoPGje6gNG+xpgMJoxNutGT1s1TEY9orFDrLuDGCyMlzY9+1CrgYZbcXJ+Gx1NTljMBsQTKSxu+DDcK8TJ7d0QsrkcmlxCnJxe9KDJ5UBnsxMbnn3MLu/iVH9hbOULI5nKoKUw9p5Z2UF9jR32chOS6QwmFzw4OyD06d1ABAfxFC6NtMAXOMDcqhc1lWVw2CzIZLMYm9vGmYFGqKCCNxLD/lvyksNmhtNuQS6Xx405Ny4MNSMQiiEQjmNv/wA9hS13lrf8sFqMqHaUAQCuzWxhpNsFnVaD/UgCO/4I+tqE/Ly6HYDJoMNIVz28wShuzLrR314Lo0GLyMEhNndDGCjMoWyvBKDVqlFfGHOOz7jR1VYNs0mPg1gSq5t+DPUK47stj3DWT6NLaO/JuW20NTlRZjEg6znA8sIuBkeEdtnxhJBJZ9FYGJ/OTW9jYLgB8VgKycM05mc9GC7kdu9uGIeJFJpbq6AJxbA4sYXqhgrYK8uQTmUxc20NI48IXsS/E0Z5hRmthfHS8vQ2KmusqKgqF8ZWV1YxdKEdqkwawd0w9veiR9uZrk67YassQ2WdHcjn4d8Jo6mrFhqdBqG9CPa2Q+gs1H991gOL1fRmXnplEX1nW6E36BAJHmBnM4DuQg5LpzMw74ZRU/Bok68vo3ukCQaTHtFQDO4VH3pPtyJv0MG9ugeNRo26QrtMX1tDe68LpjID4geHWJvfRf+ZFgCAZ8OPfC6P+kK+m725geaOalicViTiKSzNeDBUmCfZce8jncqgqU0oGw0nUFltha3CjORhGnMTWxi5NT71hBCPpdA0LNzXhbkdVNdaUVFhEXzXxBZGTzdDpVJBo1VjcX4X7R2FOZXFXTgqy1BZWYZsLoeJm5s4090AtVoFfzgGfzh2tDXP4pYf9jIjqivKUF1Rhr97bQ6jncIzG4zGsRuIoq+lMP+yHUC5VYv6MsFLverZxKmaOpg0OgSTCWyEQxitrkOdpQw/2N6AQaNFU7ngpd7YcWOwqhoWrR7h1CF0ag96ywQ/un3ogxoq1BkLbRhdRYvZBbPGiEQ2idW4G/3lgh/dSfqRy+dQbyx414M1NJuaUKa1IJlLYTW2ht5ywV/sJf1I5VIYtPYjmN7HSmwN1YYqlGvLkMqlsRRbRn+54C8CqSDcegs6ywXdmfAOao1WVBosyORzuB7cwPnKVtQZbZgMuRFMxdFjFdplLrILp6EMVYYy5PJ5fB/7OF9fD61ajb14HN6Dg6Pteeb9ftiMRpyqrcPOQRSvbm3hrMsFvUaDQDwBdzSC4ZoapOJxvNNyAMUH3D2qvJTTa044kUgENpsNT2h/ClqV7p7/f6PvG8DYd6eLF1KJH6cw+r5+jH13priMRtqxDKPv7cfY94prQaMR13miD2Pfny1eJ71eUp3EUFnLRMuMPNKJ8VeXipbJ1NhFdUbPtmDs2nrRMgmXSVTnzFATrousCEuWi7fzub5GXJ0V/wZXk+Z0f5MvLVrm1Klm3LxZfCWXYUf8gKCRi+0Yf32laBnVQUJc53Inxl8pfu+hE/8edORSB8ZfWy5aJmc2iupIRkKXHT3fhrErq0XLqBIpUZ2RS+0Yf02srePiOo92YfzlxTv+PZNL4YXdryIcDsNqFUxUMBjE4//0+9CWi/ebO+pGE3jxn30ODoejZA0FBeBNH/A4nrw/PuD9gxh7YUo2OlK1VFrxmCnF46jN5ruq2x2prhQtIiWGpxoqRHWk5LiDenF/c7a/EddmiufvlFV8wHK+uxFXFiT4gKRoEUlYdjOiZU4PN+GGyFumpk3xg5BHL7Rh7A2RHLcrvqpu5D09GP/BfNEyuaj4gXNSPHI+JZ5zJSMydLvf/Z6hk8mn8SK+rfgABdlyywec+9AXoNUdz9dLmXM6M9iE61PF42Vewpjg7EATrk0X18lpxSskJTdJRYqWLp6j/F8m76FomdEzLRi7vl60jFbCQe0jj3Rg/NXifiIflzBGfU83xn+wULSMFL81crkL46/cefx1VCeTQbSMFPJGcR0p+TtrFdc5daYFN0XuWahL3Eue623E1bniz6L/rPizeNnVhFc8xfvZwADvLTu7vvj4u7+8FzPROVGdCa/4ORIXKlvxRmCtaJnYsk1U55HGRry6dee2zh0eYuNz/17xAQSUlfwyhPW9C/PrG16d5PWdEq0+LBkZ3nsatLaWVxvlWTefiPye69I+l8urkDvGt+/H+ayCwgNFZvGSqSU3HyC765LhrZcbvLaW2b1nIcN+X6qO4gMUTiys+ERKKswoJ7OISYMWemV275nIbU6Jdstk1tZMX8Jro9JQfMDdo6zkl8D9XskvCQkr+SXJSFzJLwkJK/mlcD9X8ktBykp+KUhZyS8FKSv5pXI/V/JLQcpKfilIWckvCQkr+aVwv1fyS0HKSn5JOhJW8otxp5X8j/6/f3Dsb+5f/sBnT9Q39wr3hvu9kv/dipSVZVK4nyv5pSBlJb8UpKzkl4KUlfxSuZ8r+aUgZSW/FKSs5JeClJX8UrifK/nfjdxpJb/iAxTkwv1eyS9JhzQmkLKS/35zP1fyS0HKSn4pSFnJLwWW3wLu70p+KUhZyS8FKSv5pSBlJb8U7udKfqlIWckvBSkr+cW400p+xQfcPcQZXgUWA5e7ZaUDAAOPdHF0LnF0WPSfbaXoDIw0UnSGezmBdqTLRdFhMljYd/C4DBT2qz8u/ec4976/sOegnBg41cTRKey9eFz6C3st3i239uA7zo+CwruRgcLZPXLRYWoxvQkDVpxj5ThW/j7VLj8fMNTP8Ti0HFc41+HYOo/I7JmWY78vUUfxAQonleEeTrxk6Yx083IKU4vBwDBnHE+bVyicPXhc+s+VNv66l7Dy9yDpno12cp7Fc7Wcfsai29JJ0zpVwblnZ12ltbXiA+4eZZJfhugMnFWCOgPvG1451omBTs+pj07HWV3P0tFreav9WbCuTcu6Z7R7L69nGuDVSasnPdektlZQOCnwci7vrQM51okBLafIzAfo5OgDSHVi5RTavZebt1X6vYLCux65jQmZOUVu+YmWd0njJi0pp8hx/CW7uRfSs6hXy+uZ1qp59551bXrSrh8K4siv5ysg5OO8DhbycbY+YWqF9nh1YhAKcF7DDu1zXpnaD3N0ghGODhNWG4VZ98xP0iHVh0koGKPohAMcnVLb+rjfvp/Eb+4VHg54PoCjw9Ri1okBLaeESD4gwnmVPxiVnw9geZwQKTeF/ZytgZh+m8HD1O8VH6BwUpHbmJCVm9haDFhjVNaYMLxHyk0Bjg4TVv7e3+fosLyS/1BeniuS5t37YIrT1oESt6pSfMDdo0zyyxDfpl9WOkwt32aAosPCt73P0dnlDIJ2SV+C7MowqXtJg2CfJ8TRYd17Un2Y+HZCHB1WW7uDJX0uf8yDdk5iUld4OPBtkHIuSYepxfQmDFhxzusl5W8/R2cn+BD7AFaOKzE3vU1Hbs+0HPt9iTqKD1A4qbBygdx02FoMWON433aIo8PKTW7OWJcJLX/vymvOZPtAXs+0P8Wbc/MkOP1jO1paGyk+4O5RtuuRIV1nOPuwdZ3h7cPG0uo6zdmrjkXXEGc/t67eOopOb0ctRaevtYaiw6S7m3NtnaR9j7tIe/l1kerDpIu073HnIEena6S0vfzy+eP/KCi8G+k6S/IBJB2mFsvjsGDlFFaO623j5O/+Zvn5gJ5OTht1DZBy3AjnjB+m32Ygy35foo7iAxROKr3tpDFhm7xyE1uLAWsc3zXE8ROdo6TcNMzZS50JK393k+5ZXwvnWRx2cvoZizZLC01rwMY5t2CoprS2VnzA3aOs5L/fqCR8r6JSiZdTS/hGSqUSL6eW+D2PSiVeVoqWBB2VQS+tTiJkq+2iZXJ2i2i5wGCZqE60xYTAYfFy+/3iEaalQYVtu0j71ByK6kSqUwg0iZfLRjl7pNpmDaJlos06BFLFy1Wlxds6azUi7SxeTpfJiurk9VrkjSLPmoS97aXoZK3i7SOVvEa8n2UtemRsxU+h10jYyzBvNiBnFdHJ5kR1oNcDJuOd/547ed+wKyjIBpXE/qdSiZZVacVjpkqjES2nspZLq5MIqXq7aJlspQVpkXL+wSLxq0CkVQ9/uni5cH9GVCfkysPrKB5XTU7x18JTzgQOG8RXqCWinPyUWBDXibRp4c8X9x1OiN/7ZJUJiabi5SxxcQ+kMptEnzVVQoKOhGc6nxa/95LJi3scBQWFe0S+8HMcpAy/VYWfIuS04vk7p5FQTooNkFAfANDFxccF2lQeukTxcsa9pIRKiaORsIWOOpoQLSdl/JVXq0XL5VxV4joOm2i5bJn4fEmmzo6UhC9UVDnOLKjWK2HFdyoN1WHxe6sLhERlNA026Na8RcsYq8W/5NDHcjCGRHKqRULONWYBS/E8/4t1r4nrSOSUwVP07wbdAZLlPxDV+QvLGdEyLeYcGm0TRcv8WfyCqA4qU0C2iKeS4NsUpKFM8suQ9Wk3R2eGowMA67OkOs1uU3RYrK/sUXSWPZxXohaDHJ2FsLxeHQeApV3Ota2tca5tY7G4MZCss+Sj6DBhtdH6CufaNhZ3S/qc8O37cV7PK/mjCgoPlPXpTVnpMLWY3oQBK14u7ZDy9z6pPlH55aYlL8kHkLaQKTU3vRWWR2Yhy35foo7iAxROKqukbcBW3Jy4y9IBeNfGgjYmZOUU0viL5W+YsNpoY36HosN6FhfCnDklFunsHE1rL7lB0Sl1fkrxAXePsl2PDDGXi68Yu586glbx1bzSdXh1YmC2cFawWcRWhEvV0XF0ykg6TCykNzTMZo6OiXTvTWW8VfosWG1kNrPaqLR+f+ugneP8KCi8G+HlXI4OU0t2PoAUL1k5jpW/LVr55SbZ+YASc9NbMZfx+hkDefb70nQUH6BwUrGYSLmANUYl6QCAmXRtLOQ2JmTNT7ByJRNWG9HyN+lZLNPJy3OpVZw3YgHAoDZTdEr1t4oPuHuUSX4ZUt3s5Og0cXQAoLqxUlY6LKprrRSdOgcnkNaXk3TMnOti4qrgXFtNDefaqiVs4yBJp85G0WFCayPStVW77BQdBYWTQnWz+Ovc91OHqcX0JgxY8dLF8gFlpPqY5JebXHaSD6gi5ThSbqpukpm3lWO/J9ZJQeEkwIpztU5O3GXpAEAt6dpY0MaErgqOTi0nf7P8DRNaGzVwdFjPotzmXjRq3pmBVh0nf8utjR5mlO16FBQUFBRkyXG3PT2Bb+cpKCgoKCg8NCg+QEFBQUFB4eSi+IC7R5nklyHj35vl6HyfowMA4y9y9vUaf2meosNi/Po6RefqwhZF5zU3ScfH2TuNyZVlzrWN3eRc28TrqxydKxwdJqw2Gr+2RtGZeH2lpM8d9xW7k/h6nsLDwfh3p2Wlw9RiehMGY2OceHlliZPjXvVw9kB/w8+J30zeWOG00c1JThuVmpveCssjs5Blvy9RR/EBCieVG6TzMK7PcuIuSwcAbkzxzg1hQBsTsnIKafzFGg8yYbXRxCtLFB3Ws/iqV15tnUy/TNNaj09SdEqdn1J8wN2jbNcjQ3ovdMhKBwB6z7dzdM61UXRY9A5yXmUaaquj6JyqJelU1lN0mAw3c66tr59zbb0jjRydYY4OE1obkfpHz2hTaR/ME34UFN6F9F7slJUOU6v3PM+bMOjr48RLVo47Ve2i6IxU8F7VZjHSxGmj/h5OG5Wcm94CyyOzkGW/L1VH8QEKJ5SBTk68HOyQlw4A9HdxYjgL2piQlVOGOPmbNR5kwmqjntMtFB3Ws3jKKa9nWq87Q9NqMHZTdEqen1J8wF2jTPLLEAPpkBQD8VAblhazTgwMBs7LLEYdSUdL0tHI7yUdVhux7pnepOPoGDk6TFhtZCBdG0tHQeGkYCAdes3SYWqxPA4Lmg/Qc3RMNB8gv7hL8wGktqblOLl5W1n2e3kdSqigIHcMBlJ8YsVLkg4AGEl5l4XcxoS0ey+zdgaIbUS6Z6xn0SQzz6VCaYfdvxNaNSd/y3F+6mFFmeSXIWF/VFY6ABAOkOoUOKDosAiHEhSd/QOSziFHJ5jk6DDZj3HqFA5zdCLBOEdnn6PDhNVG4RCrjWIlfS4P1dEreiX94OS9nqfwcBDxR2Slw9RiehMGrHjJ8gFBkg/YT8kvN9F8QITkA0rMTW+F5ZFZyLHfl6rzIHzA0tISLl26hK6uLpw9exYzMzPvWO7rX/86Ojs70d7ejqeffhrpdProb1NTU3j88cfR29uL3t5e/O3f/m1J169wcmHFuVBUXjoAECJdGwvemJCUU0jjL5a/YcJqo0iQo8N6FoNJeXmuXD5A00pkOT6g1PkpZT7g7lG+TinCM888g2eeeQbZbBYAMPR4LwxaIyZfmkPX6VYYy4w4CMWwMbuN/ktdAAD34g7UahVcHbUAgOlX5tE21ASz1Yx4NIGViS0MPiq88uJZ8SKbyaGxW3j9bfb1JTR218HpcsBg0mPh2iqGH+8FAOyu7SGZSKG58Fr5/PVV1LVWw+YsR+owhZnXljD63n4AgG8rgFg4jupGB2zOcizeWENVowMV1TZk01lMvjyPkSf6oFKpENgNI+yPon1IeHVqeWIDFdU2VNbZkcvmMPGDeQw+2g1zuRHZTA4Bzz46R1sAAKvTWyi3W1DV4AAAjP1gAQOXOqHTaxHai8K76Uf36VYAwMacB0aLAVX1FbBVlmHiB/PoPtMGo1mP6H4M7iXv0VY+bncIOp0Wtc2VQhu+sYL2wQaYLAbEIofYmPegr1B2e3UPAFDfJpz6PXt1Fc09LlisRsQsZiwv7GKw8FrYznYImXQWjS2C7tz0NkwmHUbPtuDwMI2FGQ+GTzcDALw7YRwm0mhucyLSasL0uheuynI4ys1IZbIYW/bgfI/wat/u/gEOEqmj32c3fai2l8FpNSOTy+HG4jbOdDcg3gD4YjHsJeLodxbq699DpcmMGosFeQDj3l2cd9VDq1bDn4hjJ3qAwepqAMBCIIBygx711UYAwKu+DZyurIdRo0UwmcBmLIQRh/AsueNhNFvsaLDYAABv7G1i2FEHk0aHUOoQq9EATlXWI1euxUo4CI1KjRarHQBwZdeNfkc1yvR6RFNJzAX9OFcrPHfrkRBy+TzabMKJ9te9HnTaK+HqNCOeSmNmy4ez7UJZdzCMVDqLthrh+VjaCaDb5USFxYTDdAYTGzs43yG0mWc/ilgyhVOnC9c6v4uaGivsFWak01lMTboxeqoZKhUQjSRgs5nQ3iGUXVr0wlFZhspKC3K5PMbHNjF0vg1qjQr7viiCe1G09wuv0K3N76Lcboaz1gq9XovV+R0MnGmBVq9BOBCDzxNC56BQ/41FL0x2C6rrhDacuLKK3uFG6I06RPbj8GwF0TPUAL1Bh/B+DDq9FrUNQrtMXVtH54ALRpMeseghVv1R9Be2vtnaDEKtVqH+VtmJLbR1VMNiMSAeS2J52YehwhZA29v7yGVzaGwSntmZ6W00tDhhtRpxeJjG/NwORgrP9+5OGMlkBs0tldDrtfB4QnC57LDZTEgmM5iZ3sapwvPt80WQ2DtAa6ENF2c9qKqxoaLSgmwmh8mbGxg52wKjQYd0KotwKIb2LiGmLS/sosJhQWVVOXLZHKZfmMXguVZotBrs+6MI7EbQMSC04drCDsptZjjrbLBWWDD+2jL6z7ZAp9MiFDiAb3sfXUONSKYSeOEdtp/M54WfUjnOZxUUgHfwAU/0CT7gxVl0nWk78gGbM270PSLkdveCB2q1Gq7Ogg94ueADbGbEIwmsjK9j8D1Cbvcs7yKXyaGhsP3I7GuLaOxxwVnvgMFkwPzVZQw/IeT23TVfwQcIsWT+yhJc7TWwOq1IJVKYeXUBo+8fBADsbfpxEI6jqtEJq9OKxesrqGp0oqKm4ANemsXo+wYAlQoBzz5CexG0j7QAAFbG1mCvsaHS5RB8wPdnMPRYL8zlJmQzOfi3g+g8LeTgtckNlFWUoapRiFETLy9i4JEu6Aw6hHwReDf86D4rlN2YdcNoMaKqQfAmEy/OovtsO4wWA6LBA7iXdo+28nH7EtDpNG/6gCuraB+of9MHLOyg76zgL7bX/ACA+lan0IbX1tDcXQeL1Yio3YylJS+Ghgq5ZkfwAU2FmDo764HJpMOpU804TBZi6kghpnoFH9DS4kS4zYCpTS9cFeWoLPiAm6seXOgq+IBQFAeJ1NHvs1s+VNsscFotyGRzuL6yjbMd9Th05eGNH8CfiKO/Uoi/MwEfKo1m1FrKkM/nMb63iwu1DdCq1dhLxLETi2LIWSPc86AfVr0BLYXfX/ev4VRFAwwaHfZTcWzF9zFkF+LvdjyEJnMF6s12AMDVwDoG7S6YNHqE0wmsHgQwWtGAlEWHlUgQGpUKLeVCXrric6O/ohplOj2i6STm9vdwrlp47taj+4IPsAq5/freNjptlahpLxd8wLYPZ1vf9AHJTBbt1ULZRW8APbVv+oDxzR1caC/cm5DgA04PCzl3fmkXNdVWVNjMSGeymJzZxulh4d5Eo4ewW01obxW81OKKD5UOCyorBB8wNrWFoQttUKvVCO5Fse+LoL2wbcHa/E7BB9igM2ixOrdze17yhNBVyNcbi7swlqlRXXhexl+cQ+/5dhhMeoQDUeys+NBzrh16ow7hvSh0Rh3qWoQ6Tb48j85TrTBZDDgIxbE+toq+O44VFgpjBZMwVhjfwOCjPUK7rHiRy2TR0F2IEa8vorGrFuWOMiRjyXeMEbf6vZQY0TootOmdYoTBbEA6mXmHGGFHpavih2JEHzQ6DfZ3Q3eIEUKdxl6YwsCjPYUYEYZ3fQ/d5zqQzBzixe9/G2/lQfiAT3ziE/jlX/5lPPXUU/jmN7+Jp556CteuXbutzNraGn7zN38TN2/eRE1NDZ588kl89atfxSc/+UnE43E8+eST+PM//3NcvnwZ2WwWwWCw9ItQeKC81QeM9jfAYDBjbNaNnvZqmAx6RGOHWHcHMVjop5s7+1CrgIZaIaZOzG+jo9kJi8mAeCKFxS0fhnuFOLO9G0I2l0OTS4iT0wseNNU7UFVhgcGgxezyLk71C3FyxxdGMpVBS4MQk6bWd1FfbYO93IRkOoPJxR2cLZT1BqI4iKdQU1kOe7kJc2s+1DjK4LCZkcnmMDa/jTP9jVAB2AvFsB+Jo6u5EFM39uCwmuEsxNQbc25U2iyw95sQCMext3+AnhYhhy1v+WG1GFHtKAMAjF/bwHBvPXQ6DfbDcez6Iugt+KG1zQCMRh2qK8tgt5pwc2oLfV21MBp0iEQPsenZx0BhXmR3YhdarRqueqENJ8c30dFVC7NZj4ODQ6yv+jFQ2NbGvSX0r4bGQhtOutHS5kRZmRFJTwgrMx4MnGsRdDeDyKSzaGgXrnV+bAtGsx4jl9qRTKSxMCHkDwDwbYeQiKfQ3FkN5IHFyS3UFOYyMqkMpq+vY+SS4Fv8OyHEoodHvy9Pb6OyxoqKqnJkM1lMXV3D0Pk2qMpMCOxFsR+MoaNbaJeVxV3YKixwVpUjjzwWpj0YOtUMjVaN/WAMe94wunoLY9llHyxlBjhbhWfg5o0N9A/Uw2DQIhxOwOMJobdXaEPvbhgulx21hbHs+NgmenrrYDTqEIkcYmszgP6BeqjyeWxtBKHWqFHfYBfae8KNjo5qmC16xGIprC77MDhceGbd+8jl8mhsEtp7ZmobzS1OWNurcBhPYWnajcHCXM3uVhDpVAaN7cLzsr64i7beOlgrLEgdpjE3tonhi8KWdz7PPhIHSbScEp7hxfFNVDc4YHeWIZ3KYObKKoYvdwnzAaE4bJUWtBbmxlam3KiotsJRY0Uum8fka0s4NdAItVqFwH4Mgf0YutoKz+z6HqzlRlRXlkOv02B5fe/2Z3Yvgt5Cfl7d9ENXrkW92QpA2Hv/lNMFk0aHYDKOjYMQRitdMGo0CCQTMGg0aLIIbfiGbwuDjhpYtHqE04fQqAxw6IcBAAeZDQBqlGmFaw0kx2HVd0KnsiCTjyGcWkSlYRQAEMu4kUcWZVphHB9MTUKnHYRaVYF8Po5UZgwG3SMAgExuE/l8Ahq1C2pdJVKZm9BqmqFWVSKPQ6TSV2HQvQcAkM25YdHYUWUQdHcOl2HVOmHR2pHLZ7GZmEaLaQg6lQEZfRrxTAQ1RsF7ew9XYdHaUaZ1IJ/PAQDOOxsF73oYgzdxgIGKgncN78GmM6LOXA6HwYRXfRs462yAXq1BIBmHOxbGsKMOqVgC77RrvzIfcPeo8vmTeNl3RyQSgc1mwxPan4JWdcxXcVTiL0+Mvq8fY99951UjR6jFv5EafW8/xr5XXEel0YjqAMDoE30YEzssT4LW6OO9GBM5oExtMUuqkxjZxmrx+pxtwdi19aJl/ENlojrnexpxZb74gUT7/eJd7ZGGRrwqcviuqiYprlPdjFclHG6SjXJeLbPNin9feKGzEW+IHExYNSb+De+p0824eaP4tel2w6I6I5faMf6ayOE/ErYWGLnQhvE3ih/YlLHzXpnLa8RjiJQ20sRTojqj51oxdrX44U8aCSsyRi51YPy15Tv+PZNL4oW1/4pwOAyrVTBRwWAQp/6f/whNWenxIHsQx82f+P/A4XCUrKGgALzpAx7Hk8f3ARIYff8gxl6Yuj86KmkrXKRoqQ3ir/RK8SZqZ6WkOomRahf3AadONeOmyOF0e0PiMfxCVyPeWCye48L9GVGdy64mvCJy+K7JKb5i7KKzFa9LOHw3EeW8hm1ZENe52N6I10UO33VOpov+HQBODzfhxkTxNrLM74nqiOUmAMh5xXWkeORc4lBURzK5bPH6kOIHU0tMJ5NP40V8+574gNc/+ClYLJbb/t1gMMDwDvHK5/Oho6MDwWAQWq0W+XwedXV1eOWVV9DR8eZ5In/0R3+ElZUVPPvsswCAv//7v8cf/MEf4JVXXsHXvvY1fO9738Nf/uVfllxvBflxywec+7EvQKszHksrL2H4fWawCddFDgXN6sTz99n+RlybETk0V4INkKQDQBfPiZY5M9SE6yIHqBt94uNdKWj3xN+0kjQmlDBlJimnlIvHMynjr2yZ+DZxUsaDAKDKcaYDtV4p42/xNlJJeOtv5NEujL+8WLRM9Lz4/v9SnkX3jxfPuQBwuaYZr4gcvvtHl/6XqI5UThk8Rf9u0L0HyfQPRHX+Iiy+d3+LeRjr8YmiZf5s+oKojtj8VC5+iI3/6/eU+QACynY9CgoKCgoKCgoKCgoKCg8dX/nKV2Cz2W77+eIXv/iOZbe2tlBXVwdt4WwMlUqFpqYmbG7ePgm0ubmJ5ubmo99bWlqOyszOzsJgMOBHf/RHMTIygo9+9KPY2xP/skhBQUFBQUFB4bgok/wyZHOu+DdzknXmOTpMrc2FHYoOi811P0VndZfzGu7yPkknwtuHjcWql3NtGxuca9ta5gy4tlblN3BjtdHmGqd/bK34SvtgXnX8HwWFdyGbc25Z6QDA5iypTkRvwmBjkxMvWTluKcSpz8oBJ34zWfGRfMAWR6fk3PQW5PZMU/v9g45FBB/w6U9/GuFw+Lafz3zmM5TreicymQxeeOEFPPfccxgbG0N9fT1+9Vd/9Z79fwoPJ+tuTi5Y93DiJUsH4F0bC9qYkJVTSOMv1niQCauNtpa8FB3Ws7gks7mXdLb4Ww53gz8p/gaPFEqen3oA8wHHPZtnfX0djz/+OGw2G0ZGRiR/joUyyS9DWKeO60knswOAjlQnHbFODPR6zrEUeq20bY/EMJBOHWfpMNHrOG3Eumc6A0mHVB8mtOdaz7lnpbbRrT34jvOjoPBuhJW/mT6A5U1YsZeFXsK2bJJ05OYD1Jz6MDGQ2uhB56a36ZD6Bgtqv3/AsYjhAwwGA6xW620/77RVDwA0NjZiZ2cHmUym8P/nsbm5iaam27d9aGpqwsbGm9sOrK+vH5VpamrCE088gfr6eqhUKnzkIx/BG2+8UdL1K5xcaLlJZjpsLQZyGxOychxrPMiElndJ94z1LBokboF9v1CBsxUjAGjV4ltDSaFUf/sg5gNunc2zuLiIf/tv/y2eeuqpt5W5dTbPyy+/jOXlZXi9Xnz1q18FAFitVvze7/3eO27bV+xzLJRJfhlSWzhITC46AI4OEju+jpOiw6LWZafoNDhtFJ3Gwv5jx9axcOrDpMHBqVNdHUentrGCo9PA0WFCa6N6Uhs1lrgHXp7wo6DwLqS2rUZWOkytulbxffLvJ6x42VDJ0WkqJ9XHLL/cRPMBNSwfwNmfleWRWcix35esc599QHV1NU6dOoVvfOMbAIC/+Zu/QUNDw2378QPAT/3UT+E73/kOdnd3kc/n8eyzz+Lnfu7nAAAf/vCHce3aNUQiEQDCfv3Dw8N3f+0KJxoXKc65qjhjS5YOwLs2FrQxISmnsMZfLH/DhNZGTZyzm1jP4q3DduWCVtMsXkgidh3HB5Q8P0XwAclkEpFI5LafZPKdz/3w+Xy4fv06PvKRjwAQ8v3W1haWl28/S+Kb3/wmPvShD6G2thYqlQq/8iu/gr/6q78CADgcDly+fPlt5wGJfY6FMsmvoKCgoKCgoKCgoKCgcOJ57rnn8Nxzz6Grqwtf+tKX8PzzzwMAPv7xj+M73/kOAKCtrQ2f//zn8cgjj6CjowNVVVX4xCc+AUBYyf/Zz34Wly5dwtDQEL73ve8dHdCroKCgoKCgcH+532fzFKPUz90N8nuHRwGTL81zdH7A0QGAyZdJdXplgaLDYvImp0NdX9ym6FzxkHT2OHunMbm2wrm2iXHOtU1dXePoXFun6DBhtdHkjQ3xQhKYurpa0ufyeRXyx9hX/zifVVB4kEy+OCsrHaYW05swmJjgxMtry5wc98YOZw/0awFO/GZybY3TRuPTnDYqNTe9FZZHZiHLfl+izoPwAd3d3Xj99dff9u9f+9rXbvv96aefxtNPP/2OGr/wC7+AX/iFX7jr/1tB4RZjpHNwbs5z4i5LBwDGZnjnhjCgjQlZOYU0/mKNB5mw2mjq9WXxQhJgPYtv+OTV1sn0azStzfg0RafU+SmGD/j0pz+Nz33uc7f9+5227XsYUFbyy5Cu062y0gGAzlMcrc7RFooOi67eOopOXzNn+4HBapJORS1Fh0l/I+fauro519Y5UE/ScVF0mLDaqKuP0z86BxtK++AD2K7nuAftAMDU1BQef/xx9Pb2ore3F3/7t3979xVRONF0nWmTlQ5Tq/N0C0WHBStesnLckJPzWvSAnRO/mfTXc9qou4PTRiXnprfqkDwyCzn2+5J1lG37FE4oPW2ceNlL2iKPpQMAPe28LcUY8MaEnJzCGn+x/A0TVht1DjeJF5IA61kcdMjrmdZreVvE1Rk7xAtJoOT5KYIPuN9n8xSj1M/dDcpK/rtBpRZ+jiOhEf+8yWoSLyfhcA+T1QyVVuQWq6Vdj6ncJPp/Srq2cgnXZjJKqpMY8XqTaBlVYxni+8XL7feLjxCyDVrsm4uXe/yS+LegvWVZ2Nrmipb5scpxUR2n4Tz8ySui5b4X7hUtI4W/S58SL1SvQUSfLVrEuil+MJu2xoSkt3g5XUA8tBnLTYDYYTsq8W+NjWaDaLm8mreiPK+VUKcyvWi5vIT+arAYJJUTrY+ptAN7HsQKvlsH7Tz11FP45je/iaeeegrXrl27rcytA3Nu3ryJmpoaPPnkk/jqV7+KT37yk4jH43jyySfx53/+57h8+TKy2SyCwWDJ16BwMjGWcfKgJB2JvsZYZhIvqxOP4SarRbRcvtwsqU5iHLgkrNKpN+MgVLxcuDcjKpN3qRE2Fy/3Y2fGRHW6LCnUx975y8VbfNA+KarjMFxAMCl+2OfrMc7g7c/zF0XLqGuBmClVtIx5V/wZUtcaEd8vnr9NbvFn3+AoQ06kj6iC4n7CZDVDJeInVEmiD8gV/zsrfjC1StVR3uhTkBt5jfBzHDJG8edSX64XLSdJx6ZH2lK8nFo8xcFg0SOrF///DGHxcbNZq4U6Xbyc5uCd98u+a0hjuUy1+JkE+no7MjvhomViEnxJvt2GaKK4Ttos7t1yrRaED8VjrzFcfHwulTK/eMcwlhlF55QyO7uiOrrDKtFyRp/4xLutCTD6ij9r+aT4ONacNyCfLH5PKjUHojpSadWVFf17TlsJtap4GQCo04VEy9Tosshli5fTaESMCYAyvbZoOdUd/na/fcAPn83z1FNPFT2b5/Lly/id3/kd1NTU3HY2TzFK/dzdoKzklyEHoRhJJ07RAYCDMEcrRtJhEY1xDEQkxdGJZzntk85FKTpMwslDig7rnsWinPrEIhwdJgcHnDod0NooQdG51zAO2vnLv/xLXLhwAZcvXwYAaDQaVFXJ61BGBfnD8wEcHaYWy0+wiMY5OSVM8gGJh9kHkNqIdc9oOU5mz7Qs+z2xTgoKJ4EDUpyLkHRYcRcADkhjORasMeFBlNXWpDEz8Z6xYI0JabmJdO9Z/oZGPkKTSpH8ZCQtvzmTO3Hcs3ni8TgaGhrwMz/zM5idnUVDQwM+85nPiH6OhbKSX4ZszHk4OsS98zbmSXVa4OiwWN8KUHSWSCt1PYec9olmVig6TJb2OW3Eumcbyz6OzgpHh8nGBqeNNtf8FJ2S2/q4r9rngWQyiUjkdqNjMBje8RW9Ygft/PC398UOzJmdnYXBYMCP/uiPwu12Y2hoCP/xP/5HZaJf4a7YJO0RytIBgM1Zjqdg+QkWa9uc3LS0z4m7u0lOO8cynP1qmSyFOW206uHcM1b+lpu3pfb7Bx2LCD5AQeHdCCvOre6QdEj1AYD1TU4uYEEbE65zxk1rbvndMxasvMvKTax7thSS1zOtyvI8YCi9TtFZjpbY1g/ABxz3bB6z2Qy3+87PaLEzfRgoK/llSP/FTo7OBY4OAPSf57zO3XeOo8NisIezn/rpWs7eeR0WTvs49CMUHSZnajltzbpnfaOcvc9YOkz6+zl7S/YNcfZN7DvVLF7oHVEd++crX/kKbDbbbT9f/OIXj3U9xchkMnjhhRfw3HPPYWxsDPX19fjVX/3Ve/b/KTyc9D3SLSsdAOi71EXRYfkJFkOdnPx9poaTm1rNHO9m149SdJicqeK00XAH5571j5B8gMy8LbXfP/BYdHwfoKDwbmSIFOdG2jk6rLgLAAO98jrPjDWW6x/kjL+GuuSVK5n0jZY6JnyLDik39ZPO5jlTLa9nOq+VsJWyRKoNgxSdU45S21rxAXeLspJfQUFBQUGeEL65//SnP43Pfe5zt/2zlIN2tFpt0YN2VlbefFvmhw/MaWpqwhNPPIH6esHof+QjH8EHPvCBY1yEgoKCgoLCCUVZya+goKCgoHByUXzAXSOrlfw/+MEP8GM/9mNwuVxQqVT41re+ddvf8/k8fuu3fgt1dXUwmUx4//vfj6WlJVHdZ555Bi0tLTAajTh//jyuXr16j66Ag3txh6OzJH5oiWStZS9FZ3uZVycGm559is5aKETR8SY57XyQ2RAvdJ9ZDXPamnXPttc5r9WxdJi4tzivZ7o3OTrba3sUnVIwGAywWq23/dxpkv+HD9oBUPSgne985zvY3d1FPp+/7cCcD3/4w7h27drRFkF///d/j+Hh4Xt4hQ8Xig8QcJO2/2DpAERvQvITLDZ3QxQdVo7bS3F8UjyzTtFhshrhtNGGl6Pj3uC8pi83b0vt9zKMRQoPN4oPEGDlJla8ZOkAwNY2T4vBNmnLli3SuGlzR373jAWrrVk5hXXPWP6GhSq7RtOKpDcpOmsH8ts+6mFFVpP8sVgMw8PDeOaZZ97x73/4h3+I//Jf/gueffZZXLlyBRaLBR/4wAdweHjnQxz++q//Gr/xG7+B3/7t38bNmzcxPDyMD3zgA/D55LeP9i1Uas5tUal5r6awtFjXxkKtIl0XqalVpNeJWDpMWDWi3TPaMy3DtibV6YG3dZ7wc5cc96CdpqYmfPazn8WlS5cwNDSE733ve3j22WdLu/4TiOIDBNSkXMnSEbQezpjJyt+0eMnLliQdHqw24nm3h9TbUvv9A45FD8AHKDxYFB8gwEqVrDjHirsAz0+woLURyyfJzJcw4bU1KzfJr39QUPF8gIqkpS7V3yo+4K6RlSv9kR/5Efze7/0efuInfuJtf8vn8/jKV76Cf//v/z2efPJJDA0N4c///M/h8Xje9g3/D/Of/tN/wtNPP42Pfexj6Ovrw7PPPguz2Yw//dM/vYdXcjzqO2o4Ou0cHQCob6um6LhIOiwa6uwUnRYbR6fawGkfi1Z++8S32iooOqx75mpyyEqHSX09p61djSSdZmdpH8yrjv9zl9w6aGdxcRHXr1/H4KCwD+HXvvY1fOhDHzoq9/TTT2NlZQUrKyv4+te/Dp1Od/S3X/iFX8D09DQmJyfxf/7P/0FjY2Np138CUXyAgKuzVlY6AODq4Gix/ASLxho7RafFytFx6jnezSxDH9BSbqfoNFZzdOqbKik6cvO21H7/oGPRA/ABCg8WxQcINJByUxMpXrLiLgDUk8ZyLFzNnFxQ38AZNzXWknSI94wFq61ZuYl1z1j+hkVezTn7AADKtZxzC5rLSmxrxQfcNbKa5C/G2toadnd38f73v//o32w2G86fP/+OJx8DQCqVwo0bN277jFqtxvvf//47fgYAkskkIpHIbT8KCgoKCveXfP74PwoPD4oPUFBQUDhZKD5A4YdRfICCgoLCyULxAXfPu2aSf3dX2O+ypub2FU41NTVHf3srfr8f2Wz2rj4DAF/84hdhs9mOfu73KszpVxc4Oq8tUnQAYPp18b0OpTDzBkeHxcTcNkXn2g5nX7ilGKd9gskxig6Tq7uctmbds5mbnHMLWDpMpqbcFJ3piS2Kzsz1dYqOwsnmRPmAl+dlpQMA06+QvAnJT7CYIO3retXLyU2rcU47h5I3KTpMrvo4bTS+xLln02MkHyAzb0vt9zKMRQonl5PkAyYWOXFubJmjw4q7ADA5y8kFLGZucHLB1ARn/DW+IK9cyWTmxjpFh5VTpkhjXZYHZKHKXKdpeQ8nKDrXA5y2VhDnXTPJfz/5zGc+g3A4fPSztXV/H8jWQc4r1q0DPDPSOsB5Tae1n6PDoqPUbUTeQm8lR6fRxLlnVl0nRYdJr4PTRqx71trFec2PpcOkra2Ko9PB2YKgtafU1/QJPwoKJfCgfUDbEMcHsHSYWiw/waKjieQDSDnOZeS0c5mui6LDpLeCk5s6G0g+oJOzNZLcvK0c+33JOooPUHhAPGgf0NHIiXOseMnSAYD2Fk4uYNHazRnLscZNLF/SSXqGmNDampWbSPes1yGvZzqv6aFpOfQdFJ0ea4ltrfiAu0b7oCsgldpaISB4vV7U1dUd/bvX68XIyMg7fsbpdEKj0cDr9d72716v90jvnTAYDDAYDMevdIlYrCZZ6QCApZyjZSbpsLCYOfe5TK+n6BjVRoqOVl1G0WFSrue0NeuemcvkpcPEYiFdG0unrNTn+rj76J28PfgeZk6SDzDbzLLSAQAzy5vIzQeYOPm7XMd5XoxqTvvI0gfoOG3NumeWknPT7cjN21L7/QOPRYoPUHiTk+QDWHGuzCivuAsAFjNPiwFrLGexkO6ZiVQf0r1nUvqY8C06pNzEGjOz/A0NFc8D6tQWik5ZyT5Z8QF3y7tmJX9raytqa2vx3e9+9+jfIpEIrly5gosXL77jZ/R6PU6fPn3bZ3K5HL773e/e8TNyIB5NyEoHAOIHhxSdBEmHRSyR4uikOTqHOU77ZPIxig6TA1Ibse5ZIpaUlQ6TeJzTRvHYg21rVf74PwoPDyfKB0RIPoCkAxC9icx8QPyQE+dYOS7J8gG5h9gHkO5ZnOUD5PZMM/v9A45Fig9Q+GFOlA8gxTlWvGTpAECcNJZjwRrLscZNtPkJ4j1jQWtrVm4i1Yflb2gQ54LSJD8Zy5TWRooPuHtktZL/4OAAy8vLR7+vra1hfHwcDocDTU1N+PSnP43f+73fQ2dnJ1pbW/Gbv/mbcLlc+PEf//Gjz7zvfe/DT/zET+BTn/oUAOA3fuM38Iu/+Is4c+YMzp07h6985SuIxWL42Mc+dr8vTzIrE5scnUnea4UsrZUpee3Ftbzmo+jM7O1RdLYSnPaJpDh7+jKZ8XPamnXPVubvvA/ng9BhsrxMaqMlr3ghKTqz8tsTUkGeKD5AYGV8XVY6ghZnz1qmN2GwuMHJ3zMBTtx1H3LaOZqW3x7oM/uctl7c4uisLJB8gMy8Lbffc7SYdVJ4uFF8gMDiJifOLbjlFXcBYHmVp8VgZW6HosMafy1tcHSY94wFq61ZOYV1z2aC8mprVXaWphVMLYsXksBsmDOvoCCOrFbyX79+HaOjoxgdHQUgJOTR0VH81m/9FgDg3/ybf4Nf//Vfxy//8i/j7NmzODg4wD/8wz/AaHzztZ+VlRX4/f6j33/2Z38W/+E//Af81m/9FkZGRjA+Po5/+Id/eNvhO3Ji8HI3R+cR3n6sg5c4e7wPXJTXXvHDfZx9VM+56ik6nRZO+zgMpyg6TM7Xcdqadc8GTjfLSofJ0BCnjQZHOGdEDJxtLe2Dyh58Jw7FBwgMvqdXVjoAMPgoZ39Plp9gMdLNyd/nazlxt93M8YAVhtMUHSbnqzltPdrJ0Rk8RfIBMvO21H7/oGOR4gNOHIoPEBjp4sS5Ux3yirsAMNTP02IwcKaFojM0zPEBIz0cHeY9Y8Fqa1ZuGhrmjHXP18irrfPaszStGuMwRedsZYltrfiAu0ZWK/kff/xx5PN3vgsqlQq/+7u/i9/93d+9Y5n19fW3/dunPvWpo2/yFRQUFBTeJeSPuQffsfbvU3gQKD5AQUFBQeEIxQecOBQfoKCgoKBwhOID7hpZreRXEPCscF5l8axyXj8CAA9pi5Qdkg6L7d0QRWcjHKbo7KU4r3rFMvJ6dRwA1iMhig7rnu1sBWWlw8TjCXF03PsUnZ3NAEVHQeGk4FnmbCPC0gGI3kRmPsDt5eRvVo7zpzjtE5ejD4iGKDpuH+eeeVg+QGbPNLXfyzAWKSicBFhxbmuPo8OqDwBs74RoWgx2Njm5YNsdoui4vSQd0r1nwhoTsnLK9jZnrMvyNyxUOc723wAQzbgpOpsxTlsriCOrlfwKAtlMjqSTpegIWqQ6ZTk6LFj1yeZZOpx7lgfv3rPI5uT1DPH6mbyeaYDXRrkH3dbHfcXuBL6ep/BwkCPFFZaOoMXJK3KLmbTcRPIBOZoPyFB0mGSLrM69Kx25+QmZeVtuv3/AsUjxAQonFFqck5kOW4uB7MZNMtNhQmtrVm5itbXMnmnkeR6Q5UszpfpkxQfcNcok/92gVgGqY77uodGIFmnsrYd/t/g3ryqd+K1r7G1AwBctXkgl7WWOxp56BLwiWmrxtmnodsG/GylaJq/XSaqTGCmL+LXVtVfCfRgvXqhK/NT1tppa7HiLfzP9ZOVNUR2n4Tz8yeLlPmQRqS+AnHYI6syKaLlUflG0jBT+zjooWqa9xoodb/FvcDNGvahOfUslPDHxNhCjodUJv7f4swgJCbuhpRJ+kRUpauKAO58Tz1TNtXYERFaTqA/TojpNdXYExFa3pMR1Gpoq4N/037lA7g4aSlJXOKE09Liw5z7+aicpOioJuRsoeBNP8Riu0ojn3cZuFwIiHiev59jTdJkEX9LmwHYqVrSMznEoqtNVVQv/XpE4B+D9thlRHcEHFC/3L8ziviSnbYA6I2UlF+dAtf9ZLn4WUK+zDvv+4m2UNYh7wMbGCnjiB0XL5CX47Ya2auz5i997lQSf3NBZB79HPismWfGDqVWyjuIDFGRGTq9CVne8+YC0RUJuanFgO1k8PknRqW91YCtbXEcjnlJQ3+KAWyRXAkDeL16npoZK+AIisZc1dpI6lhPxNxmTeE5xdVZh56D4GDVWK65T0+XE2mKiaJmc+JAZdR0ObCyL3zNNirO5R94onr8bumuxFyp+bSqthHmu/kbR+TJ1XHyM2lxjQ3C9+FhXEzWJ6nTanfB5i1/XlXi7qI5U1Kqlon+36dsQTom/7fBKWPxMob6yXswezBUtkwoYi/4dAJpcddgM3Pme5O7UfIoPuGuUSX4FBQUFBXmiJHUFBQUFBYWTi+IDFBQUFBQUTi6KD7hrlD35ZcjsFc6qqrmr4iu5pWutykqHxdTSDkXnpn+borOfmqDoqDJjFB0mN0htxLpnc+Oc/Yrnxnh73rGYmea09ewEqY1urFN0FBROCrOvcd6yYukAwOzrHC2mN2EwscrJKWNBxQeIMbbPaaOJNc49m53k7DMrN29L7fcyjEUKCicBVpwb3+DosOoDANPzHpoWg7mxDYrO9Cwnx43L7N4zmZ3g5F2WJ2XV5+aOvNo6muZ5wOUYx7ff8Mmr3z/MKJP8MqSxs5ai00DSEbRqZKXDormugqLTVl5J0bFoWyg6eU0rRYdJu5XTRs0uzj1raHXKSodJY5ODo9NCaqP26tI+mFcd/0dB4V1IY49LVjqAsM0OA6Y3YdBSQ/IBZZy4+zD7gNYyjg9g3bPGFk595OZtqf3+QccixQconFBYca61iqPDqg8ANNVz8iWLhtYqik5TI+e6Wqvlde+ZsPIuy5Oy6tNWIa+2NhE9YJ2R49vbbSX2D8UH3DXKdj0ypNxRxtGpsFB0mFrMOjGwlonvHyYFu4Gjo1fbKDpQ2Tk6ROx6ThtZLRydcpv4/nqSdOxmig4Tq5V0bQ+4jVR54adUjvNZBYUHCc0HkHSYWnLzATZSTrHpOfHyofYBOlJbm0k+gJUrZfZMy7Lfl6ij+ACFkworzslNBwCs5TwtBqyxnLWck1NovoR4z1jQxpas3ESqj90or7bWqu00LYuG43FKnS9TfMDdU/JK/itXrjDrofBDHMYlnH4jgWSCowMAyXhKVjosDpOck8cTGfGDXaSQyYsf7ieJfPGDXx4EcVIbHaY49yyZ4NQnmZDXMw0AhxIO1ZWmQ+r3pbZRnvCjcM9QfMC9Ixkj+QCSDgAcsupE9CYMEhIOD5ekk1V8gBisNmLdM1aulJu3Zfb7Bx6LFB8gWxQPcG+h5aY0a/zF0QGABCn2smCN5Vg5hXbvifeMxSFp/M3ypKz6JNKc+QkWOaIHTOY4/aPk+TLFB9w1JU/yX7x4EV1dXfjCF76A1VV57UX5bmfh+hpHh7gP9sJNjhZLh8Xsqvip41KYCHL2YQunpik6quwkRYcJq41mVzj3bGGaswffwhRHh8n8LGfPuwXS3v4LpPMPFOSF4gPuHfNXOWfzsHQAYOEaZ09OpjdhMLPupehM7nPi7sPsAyZDnDaa2eDcs4UZUo6Tmbdl9ns5xiIFeaB4gHsLK85Nb5F0Njk6ADC3xBnLsVhgnc+ywBnrstp62s27ZyxoeZflSUn1mfDK65mOpnkecC3OmZsc35NXGz3MlDzJ/41vfAOdnZ34whe+gM7OTjzyyCN49tlnEQwGmfU7kQy/p4eiM3S5m6IjaHXJSofFqd4Gis6F6iaKTqXhDEUnrz1P0WFykdRGrHs2dJazV93QuTaKDpORU80UneEzpDa62E7RUZAXig+4dww/0S8rHQAYfryPosP0JgzOdHFyynknJ+4+zD7gfCWnjc50cu7Z8OkWio7cvC2138swFinIA8UD3FtYce5sG0fnTAdHBwBODTbStBgMneeM5UaHOWPds6S2Zt17JsNnWjg6JE/Kqs+FBnm1tU3P84A9ZRzffrFOXv3+YabkSf6f//mfx//+3/8bHo8H//k//2fk83n82q/9GlwuF378x38c3/zmN5FKyev1VQUFBQWFdw+39uA7zo/CvUPxAQoKCgoK9xLFB8gXxQMoKCgoKNxrFB9w9xz74F2n04lPfepT+NSnPoWVlRX85V/+Jf7iL/4CP/uzPwubzYaf/umfxkc/+lFcvnyZUd/7yjPPPINnnnkG2WwWADD0nh4YdEZM/mAeXadbYbQYcBCKY2NuG/0XOwEA7qUdqFVquDpqAADTry6gbbAJZqsJ8WgCqzMeDD4irPjxrPqQzWTR2FUHAJi9sozGzlo4au3oPd+OhetrR6v6dzf8SMZTaO4VThJfGN9EXasTVkc5UocpzF5ZwchjvQCAve0gYuE4HLU2jDzWi6XxdVTVO2CvsiKbyWLq1UWMPNYDQIXAbhhh/wHaBoVvH1cmt1BRbYWj1oZcLofJlxcx+EgnHLU2NPe6ENgJoaPwLfXazDbK7WY464XTxMdfXsDAhQ5oDVqE96LwbgXQdaoFALAx74HJbICjxoaRx3ow+fICuk+3wmDWI7ofw/ayFz1nhW/R3f5DaHUa1BZOqJ++tob2fhdMZgNi0UNsLHnRV1ip7Fn3AwBcLU6hDW9uoLmzBpZyI3xNJsyv+zDaUw8A2PaFkcnk0OwS6ju9vAujXouz/Y04TGYws7KL031CO+z4I0gcptHWUIlwTRoTgR00WGyoNJqRymZxze/GIzVCHXbiURykk0e/Twe9qDGVocpkQSaXw5W9LVysboLTcB6H2T0kcwHYdMJ9DacXYFBXwKipRh5APOOBQ38aapUWyWwQiewu7Hrhm+pIegk6dTlyWqH+qsxryGtOAyoDkN+HKruJvHZYeHjzCeTVTcirGwplryCvGQJUJiAfgiq7hrx2FNUGC6KZDaigQZlWKOtPjsGm74JOZUE6H0M4tQSnYQQAcJDZQh45lGuFaw2kJlCubcPlmmbEMmlMBXdxoVr4lnbzIIRkLotOq3Bqvf8whj57NRwGExLZDG76t4/abDsWwUEmhbP9wuntc6te1DqtqLCakM5kMb7gwZn+RqgAqFQq2MtN6GwS7vnCug+Vdgucdgty+TxuzLoxdK4VarUK+3sHCPqjaO8V+tjawq7wzNZY4XCWAwAGTjdDq9MgHIzB5wmhc0B4XjaWfDBZ9Kh22QEAE2+soHe4CXqTDpH9GDybQfQMN8LhLEdldTl0eu3RMzt1bQ2d/fUwmvWIRRJY24uir9DH3FtBqFUquBoKz+HEFto6qmG2GBCPp7Cy5MXgsNCGnu195LI5NDQJbTg7vY2GlkpYrSYcHqYxP+s5WrW/uxNC8jCD5lYnHJUWmMx6uFx22OxmJJMZzEy5caqwWsHnjSDhjaC1U4hTi7MeVNVYUVFZhkwmi6kbGxg51wpHVRkaW50I78fR3i3cm+X5HVRUlqGyqhy5XA5T/+8UBi+0Q6NVY38visBuGB2Fa12b20G53QRHjRUjlzsx/soS+s+1QafXIBQ4gG8riK6RJiTTCbzwTbydvEr4KZXjfFZBMifKBzzRB4PWiMkXZ9F1pg3GMiMOQjFszrjR94iw0sW94IFarYarU+gz0y/Po22oCWabGfFIAivj6xh8j5CvPcu7yGVyaOgRcvvsa4to7HHBUWdH38UuzF9dPloBu7vmQzKRQnMhT81fWYKrvQZWpxWpRAozry5g9P2DAIC9TT8OwnE46uwYff8gFq+voKrRiYoaG7LpLCZfmsXo+wYAVcEH7EXRPiLEkuWxdVTU2FDpqkAum8PEi7MYek8vHHV2tPQ3wO/ZR+cp4S2ftclNlFVYUNUoxKiJK2sYuNgJrV6LsD8C72YAXYWyG/MemCyGI28y+fI8us+0wmAyFHzALnrOCm/9bMVz0Oo0qCvEyakbG+jorYPJrEcsmsT6ig/9I0Kc3N4QVo3WNwvxd2Z8Cy3t1bCUG+BpNmB+y4fTnUJcd++Fkc7m0For6E6u7sCg1+J8TyMSqTSm17w42y20rycQQSKZRrurErGqQ0zue1BvtqPSYEY6l8W1wBYuVbUI9yYRwUEmefT7dGgXtaZyOA0WZPI5XPVv4oKzWZY+wGHQIZZZgwpamLVCm+4nb6Bc1wOt2oJM7gAH6UXYDacAAPHMJoAczFrhWkOpMVi0HbjkbEE8m8Z0aAfnKpsK9zGEZC6DjjIhXweScfRYa+DQCz5gfN+Ni05BZzsRQSyTxGC3UIeZDS/qHOVwlJuRymQxtuLBue5bPgCoKDOhq17QndvyocpmgdMq+IBri24Mn2mGWq1G0C/4gI4ewQesLnphtZvgrLaiwikc3Dcw2gSdToPQfgy+nTC6+oT+uL7ig0VTjeoG4dma+MECes+2Qm/SIxI4gGdtDz1nWuGotaGyzg6dQYvaZqFOU68uonOkGUaLAbFwHGvXl9B/SfD/7sUdqNUquDoKMeKVQoywmhGPJrAyvoHBR4Xnw7PiFcYK3YUY8foiGjoaUe4oQzKWfMcYcavfS4kRrYPCvbpTjHDU2dHUW4/QXgTtI8K9Whlbg73G/maM+P4Mhh7rg0anwf5uCP7tIDpPtxVixAbKKsqO6jT2whQGHu2BzqBDyBeGd30P3ec6kMwc4sXvfxtvQ/EBsudh9gDA233AqZ566I1m3JzfRm9rNUwGHaLxJNa2gxjqFOLM5k4IKjXQWGMHAEwseNDR5ITFpEc8kcJ00I9THUJe2vKHkc3m0FIjxPWJtR201FTAabNgqLUWMxveo1X924EIkukM2mqFmDS250WDw4YKiwnJTAZj6zu40CHE0J1QFAeHSVRZLbjQ0YgZtxe19nJUlpmRyeVwfXUb5zsaoIIKfv8B9g8S6K6vAgDMu/dQWW5Glc2CXD6Ha0vbcJSZcL6rEYFoDL5QDL2N1QCAJY8fVrMBNXZhXDW3sYahvnrodRrsh+LY8UXQ1yXEurXNAIxGHSorLDgz3ISbk1vo7aqFyahDJHqIze19DBRi9V4sB61Wg9rGwnjp+jra+1wFH3CIjWUf+kaF+OXZCAAAXM2F8dLYJpo7qmEpNyIRjmNlxoOBc4IX2d0MIJPOoqFdqP/82CYMRi1GLnUgmUhhYWILQxcEL+Lb3kcinkJzZw3SNeWYW9hBbY0NFXYz0uksJqfdOD0qeCffXgSxWPLo94WlXVQ5y+GosCCTzWJi0o3R4UbEWgzwhWMIROPobSi09/YeHGUmVNvKkM/nsR2I4Ex7PbQaNQLROHZDUfQ31hy1d5nJgJoqob3fWN7CaHMdDDot9mMJuINhDDYK7Z1IptHosKHeYQUAXFt1Y6ChBia9DuH4Idb29jHSXAdjRQ4bO/vQqNVoqLEBAMYXttHVXAWzUY9YIoXlTT+GC3loyxtCPg801QrP9+TSDlrrHagrdyCRSGNpxoOhM4V5ku0Q0skMmtqE3LgfiKGtqwa2CjOShxnMTW5hpHBvfDthxGNJNL9vAICQl6qbnLBX25BOpjH9ygJG3tsPlUoFlVoFm7McbcO3vOsaHLUVcNTZj7zr8JkWqDUqBPcOEPQfoKNXaJfVRS+sNhOchbEvUPABeg1CwYIP6C/4gGUfWux21JcL7f3a1hZO1dXBqNUimEhgIxzGaG0tqi0W1FgsMGi0aLQJ7X1lexuD1dUw63SIJJPQqvSoNwp+LpjehgoqVOiE/8d9OIMqfSsMajNSuTh8yVU0mIR2CKV3kEMWDl0hDhzOwaLtg1ZtRy6fQDQ9ebRyP5l1I5s/hF5dDZv+Eg7SEzBomqBTVyCXTyKavgGb/lKh7A6sWisajEIsWk+sw6FzwKq1IpvPYiG2iN6yXth1NtQZ6hDNRNFkEuLLRmITNq0Vdp0dOeTwIoALtQ3QqtXYS8SwGzvAoFN4ZueCe7AZjKg2W3DZ1YRXPJs4V1sPvVoD/2Ec7mgEI1W1SMfj+F94BxQfcNeo8vk87bsNj8eDv/qrv8L/+B//A5OTk6ioqIBWq4Xf78epU6fw3//7f0dfH+fVmvtJJBKBzWbDE4YPQ6vSHUtLpRX/XsVRa0dwN1RcRydFx4bgblikQtJe5pCkpRbvQJJ0nA5JdRIjeMYpWsZpt8AfihUts/cvxA92qTaWwXd4ULTMly/8taiOQV2FZG6vaJkPWeKiOnlVNVR5n2i5/3lgEy0jhX/3+k+Jlqk2WuA7LN7Wtf9HL6oj5Z7ZJ8VfFXZUlSO4Fy1eSEJ4lKKTtZlEdaSSl9DPKivLEAgUfx41B+LPtZRrUwdF2hCAo8aKoDdyx79nckm8sP0swuEwrFbBGAWDQYw++yfQWMyi+nciG4tj7Fd+DQ4HJ6YoiPOw+4DH8eSxfYAUHK4KBD3790VHii8BAEedHcGdUNEy6jKLuI4EH5Bvdkmqkxh75+yiZZw2C/zh4jkl8r7ifwek+YD/cPqdvs28nfvtA/4hbhAtI4V/PfZh0TLVhjL4ksXbyPxCmahOlc2CPZF7VnX1zjnnFg5nGYL+4vVRr4ufIyDlmc5FxXOlVPKZ4gf8seIHU0tMJ5NP40V8W/EB73IeVg8AvOkDTn/496DRGY+llSoX9/JS4lzaIkGn3IK9aHEdjYQzTKusFuxFxHOhdUP8ANLKCgsC+8W1LKsh8UpJQcLhs47qcgR9xWP0YYt4DKl0WBAIFr+uYK94zpXS1jnxIbOkew8AFk9OXEwC9lmROR4AjqoyBPeK5938zJK4jgRPqhoQ30pPig9Y+ohVVKfaYoEvVrytn/7Ad0V1pHLRUryNdOpqpHPiHvB536OiZexaG0KZ4vf2xZu9ojrVZgt88Tu3US5xCPdv/JbiAwiUvF3PLaLRKJ5//nm8//3vR3NzMz772c+ipaUF3/zmN7G7uwuPx4O//uu/hs/nw8c+9jFGnR96bq3WPy5N3RwdQatOVjosWus5nb3TVknRKddx9gTMazooOky6bOJfukiBdc+a2qs4Oh3VFB0mza2ctm5uI7VR4Y2BuyZP+FG45yg+gM+t1fpy0WFqMb0Jg/Y6Tk7pKOfE3YfZB7Da6NYq1uNCy3Ey87Zy7Pcl6yg+QPYoHuDewIpz7TUcHVZ9AKC1iTNuZtHUUeI45S20NHNyXLvM7j0TVt6l5SbSfECnzCaQzVqeB3QZOb69y15iv1d8wF1T8nY93/72t/EXf/EX+Lu/+zscHh7i7Nmz+MpXvoKf+7mfQ2Xl7Tfwp3/6p7G/v49PfvKTx66wgoKCgsIJ4biJ+QQm9fuJ4gMUFBQUFO4pig+QLYoHUFBQUFC45yg+4K4peZL/J37iJ9DY2Ih//a//NT760Y+iu7v4qcvDw8P4V//qX5X6350o5q+tUnQWbqxRdAStdZIOr04MZlZ2KTrjgR2Kzn5qmqKjykxQdJiMkdqIdc8Wptwcncktig6TuVnx7QWkMM9qo7HNkj6nwvEOyzl5O/DdXxQfcO+YvyL+qvL91AGA+avLFB25+YCpNU5OmdjnxN2H2QdMhDhtNLXOuWfz09sUHZZHZkHt9w84Fik+QL4oHuDewopzU1scnekNjg4AzC5yxoQsFiY4Y7m5ec51TZHamnXvmcxPcfIuy5Oy6jO+K6+2PkjzPOBqnOPbx/ZK6x+KD7h7St6u53vf+x42Njbw+7//+6JJHQDOnTuH559/vtT/7kRRR3qNqY60ZQcA1LVwtOpaONfGoqGasyd9c5mdomPRcl49y2uaKDpMWG1UT7pndQ2c1+rqGuX1eh4AuAqHBR8X1rXVNcvrtVwFDooPuHe42jmvjrN0AKCujaPF9CYMGqo4OaXJYqfoPMw+oNFcQdFh3bNbBzsfW4fkkVkw+70cY5GCPFA8wL2FFecaHCQdJ0cHAFyFA1vlQl0TZ7zjqiO1daW87j0TWt5leVJSfZps8mprA9EDVhlIWyyV2yk6CuKUvJL/8ccfJ1ZD4YexVZZTdKwOjg4AWCvFD0K7nzosbOWcA1ErDBwdvdpO0YGKk7CYOEhtZCfdM2tF6Qe43K4jftDk/cZm51wbS8fqKLGNlNfzZI3iA+4dVqf4IV/3UwcAbE75eRMGFWUkH6DnxMuH2gfoSW1t4ejQcpzMvC2z3z/wWKT4ANmieIB7CyvOsXTsJB0AsFt5WgxYYzmbjZNTaL6EeM9Y2Ejjb5YnZdXHYZJXW+vUPA9YruF4HIexxDZSfMBdU/Ikv8K9I3mYouikSDqClvjJ9PdTh0UqlaHoJLMcnWw+SdEBS4fIIamNkmmOTipJ0pHZMw0ASdK1JZOsfl9ifZSkrnBCSSVIPoCkw9RiehMGrJyi+ABxDnOKD7gfyLLfl6qj+ACFEwotN2XkFXcBIEkaf7NIkcY7rOui3XviPWPBGqOychOrPoekfsYiR/SA6Tynf5Q8F6T4gLtGmeSXIbOvc/YYm72yQtFhajHrxGBiibN33nU/Zz+3/dQ4RUeVvUHRYcJqo0nSPo6zJe4Tf690mMyQ9tKfHefsUTl7vbS9/FT5Y+7BdwKTusLDwcyrC7LSAYCZ1xYpOnLzAeMrnJxyI8iJuw+zD7hJaqPxVdIZP6R9mOX2TFP7/QOORYoPUDipsOLc2DpHZ3yNt4/+1BznfBYWszc2KDrTM5yx7hiprcc25HX2AcAbW9I8Kak+N3bk1dbRNM8DLsU4c5PXvaX1e8UH3D0l78mvcO8YfaKPojPyWC9FR9DqkZUOi7P9jRSdR2qaKTpOw3mKTl57iaLD5DKpjVj3bORCG0fnYjtFh8mpMy0UndHzpDa63EnRUVA4KYy+f1BWOgAw+r4Big7TmzA438PJKZeqWig6D7MPuORsoeic7+bcs9FzrRQduXlbar+XYSxSUDgJsOLchQ6Ozvkujg4AnBmW15kxI5c6KDqnRzlj3Quktmbdeyaj5zl5l+VJWfV5pFFebW3T8zxgXxnHt192yavfP8woK/nvApVGDZVKc0wNCZ9Xq8XLSdHRqMXLqSSeN61WC3rHRiX+f2azhP8H0B6Kf22nSYmXy4f14v9ZmU603AvhflGZLkszFmMHRcuk8+KroaoMZuwlxfc//T/BIdEyUlDvibeRyqgVLaePit97bSInXk7K64nZrGg5VUa8PqpUGiqR7Sc06vv7fao6loI2fFi0jCqWENVRxQ+hjsSLlsknxHXyqVTRcvncHdovDyAvMUbd6fMKCgpFyeekdZR8Li+57LHJcv4fjYS3ldVp8XLpqEFUJ1umEy336kGXqE5HrgHL8f2iZTSqeVGdSoMegaRRtNw/hTkD5cOA+F6rKYNBtJw9Kn7vtYk89CLl1BK2X1ClM+LlpHjSXE603H3rOw8big9QkBlZnQrQH+OZBJAxin8+q1eJlsuKpybkdNLKsXSyBgnXplNJKsdAJWFMqMpkRctpE+K5QJPKipYzBnOiOrpoTrRcVsIzqIvmYQiKB0FDhDP3opKydV0qK15OKz5FqdJooBIpl9eKj7/zarVoOV1EXEcbV4uW+3+2hkV1pPI9Q/HDzkdtnRgLix8oveSuFi2TranHK97i/cO8JX7PDDpN0XLZ5B3+pviAu0aZ5Jche+6grHQAYG+bVCeSDguvP0LR2T7g6OynAxSdRHaXosPEE41SdHx7HJ09T5ikE6LoMNnbkde1lRyLlD34FE4oe5t+WekAwN4WJz/JzQfsBjg5xRPj6IQynHuWyMrr1XEA8Bxw2shLume0XEn02wyo/f5BxyLFByicUHZCnDi3EybpkOoD8MbfLFjjHZ9XXjluN8i7Zyz2dkIUHR/Jk/q8HB/gIfUzFnvJEE1rO87pryXHIsUH3DXKJL8MiYXFV8ZK0olwdJhazDoxOIhzDm2Jpjg6h9niq6alks4VfxvgQRBNctroIM45SCYWLb7S/X7rMIkdyOvaSu33yh58CieVgzAnF7B0AOAgxNGKEevE4CDBySmRFEeH5QMyMvQBrDZieTdariT5dhbUfv+AY5HiAxROKqzcFD0kxV2SDsCL4SxiUU4MPyDlFFb7sJ4hJrSxJSk3xQ5I/Swpr7Y+yPJ8SZTk3UqNRYoPuHuUPfllSEt/PUenj6MDAC29pDqRdFi0NzkpOj0Ojk6dkbOfm1XH2VuQSbezkqLT1sxp65buGpJOLUWHSUunvK6NGYsUFE4CrYOcfStZOoIWJz+19DVQdFh0NJB8QAVHp9bAuWflOvmdhcLySu2NHD9By5Uk386C2+/lF4sUFE4CnXWceNlVw9HprOXoALzxN4uW7jqKTlt7FUWHleM66uXVzgDQ0sUZW7YOcDxpa7v4djVS6K6WV1u3mjnPNAD02DnPNSsWKYijrORXUFBQUJAnyut5CgoKCgoKJxfFBygoKCgoKJxcFB9w1yiT/DJkaWydozO+QdEBgKUJjhZLh8X8ipeiM7nH0dlKrFF0Qqk5ig6TKZ+PorOwzGnrpaltko6bosNkacbD0SFdW6mxSHk9T+Gksnh9RVY6ALB4Y5WiszS+TtFhMbvOyU2TAU5uch9y7lk4NUPRYTLp57TR3BrnntFyJcm3s6D2+wccixQfoHBSmdnixMtpD0dnxs3RAXjjbxZLU1sUnYV5zpl4rBw3R/I3TJamOePvxRucOZPFOY4PmCL1MxaLB5xnGgAmg5znutRYpPiAu0fZrkeGVNWLn4QtScdVQdFhajHrxKDaWUbRqSvj6Nh1nNfzTFrOK+hMWG1U7Syn6FTV2Ug6dooOk6paK0eHdG0l9/s84UdB4V1IVSPnlVaWDgBUNXDyE8vjsKipIPkAMyc32XWce2bUyG8ruToLp41qHJx7VlVL8gEye6ap/f5BxyLFByicUGrtnHhZZ+PosOoD8MbfLFjjnepqzviLleNYOkxo4+8G0nxZDeeesfoZiyqDnabF8rclt5HiA+4aZZJfhthJCYKlAwD2KlKdSDosHDYLRafKxNEp13Lax6CW14ATAJxmM0Wnws7RsZMMJkuHib1SXtfGjEUKCieBihrOIIilw9SSmw+otHFySpWJo1Om4bSzQcP5UoYJq40cpHtmr+R4N7nlODn2e2adFBROApXlnDhXaSHplHF0AN74m4WdtICswiGvHOew8u4ZC9YYlZabSF+EOEn9jEWFjvelQ5WR019ZsUhBHGW7niI888wzeOaZZ5DNZgEAQ4/2wKAzYvLleXSeaoXJYsBBKI6N+W30XxAOOHMv7UKlVqG+XVhJPf3aIloHGmGxmhCPHmJ11oOBS0LZnVUfstkcGjqF1VZzV1fQ0FmL1v56JOMpLNxYw9Cj3QAA74YfyUQKTT0uAMDCxCbqWqpgrSxD6jCN2SsrGHmsBwCw5w4iFkmgtXDY5dL4BqpcFbBXW5FNZzH12hJG3tMNqFQI7IYR9kfRVji8ZGVqCxVV5XDU2pHL5TD5yiIGL3Witc+FfV8YgZ0wOoaFw7PWZt0ot1vgLKzSHf/BPAYudECr1yLsj8K7FUDXaAsAYGPBA5PZgNY+of6Tryyg+3QLDCYDoqEYtpe96DnTJrSh9wBanQa1TcIAdfrqGtr7XTBZDIhFD7GxuIu+04KuZ90PAHC1CCuEZm+so7mrFpZyIwIuMxZWfRgpHPLn8YaQzuTQXFhxNb24g7qqcpwZbMJhMo3ZpV2cKrTD7l4EicM0WhsrEawHxn27aCi3wmkyI5XN4uruNi7XC+3gOYjCpNUe/T6150WNpQzVZgvSuSyu7GzjoqsBXZYkIpkQIpkwGozNAIDtw02Uacth0wptmMtn0WHugVqlQTQTQSgdQKOpVXheDrdg1JhRZRCS2l7yKhz6YWhUBqRyIcQyblToBwAAWrUFFm0DzBqhvf3JG6jQ90OjMiKVi+Agsw6Hfgh9ZW3YSe5Co1KjWi8cPLMYW0KTqRFGtRGJXAJbCTe6LMIz6036kEcetQbh+V6KLaPe6EKusRHxdBpTPh/O1wvP3VY4gmQ2gw6Ho1AnNXqdTjhMJhxmMri5s4NLjUJ7b0ejOEilcHpYaIf5pV3UVFtRYTMjnc5icnYbp4eaABVQWWGB3WpCe6twCMziig+VDgsqKyzI5fIYm9rC0Pk2qDUq7PuiCO5F0d4vtMPa/C7K7WY4a61o6arF+GsrGDjTAq1eg3AgBp8nhM5Bof4bi16YjTpU19sBABOvraBntAkGkw6RYAyejQB6RpvQ2l2HrWUfdAYtahuFa526sorOwQYYzXrEIgmsu8PoGxWej+31AFRqFVxNQtmZmxto7aqFucyARCyJlfldDJwWno+drSCymRwaWoXne258Cw2tTpTbTEgm0liYdmPorPB8eLf3kTzMoKm9Cq2dNViYcqOuwQFrhRmpZAazY5sYuSD0sb2dMOK+0NHBuktTblTV2WF3liGbyWHqyiqGL3WgtacOAW8E4cAB2gp9d2XGgwpnGRw1VuRyeUz84wQGL3VCo9Ng3xtBYDf0ZoyY2Ua53XwUi8ZfKsQIgxbhvUKMONWCZPoQ3/0O3o6yB5/CA+ZtPuCJPhi0Rky+OIuuM20wlhlxEIphc8aNvkeEfO1e8ECtVsNVyO3TL8+jbagJZpsZ8UgCK+PrGHxPLwDAs7yLXCaHhkJun31tEY09LrQONiEZS2L+6jKGn+gHAOyu+ZBMpNBcyGnzV5bgaq+B1WlFKpHCzKsLGH3/IABgb9OPg3D86LDLxesrqGp0oqLGhmw6i8mXZjH6vgHBB+yEENqLon1YiDsr4+uw19hQWVeBXDaHiRdnMfRYL1qHmrC/G4Lfs4/OU0LcWZvaRFmF5WiV/+S1dQxc7Cz4gAi8mwF0FcpuzHtgshjQG20IKAAA5QtJREFUWjikdPLleXSfaRV8wH4M28u76DnbDgDYimah1WlQdyumXl9HR2/dkQ9YX/ah/1ZM3QgAAOqbhTrMjG2ipaMalnIjvA0GzG/4cKpb+D/dvjAy2Rxa6oRcM7WygzqnFef6GpFIpjGz6sWZXqF9d/wRxJNptNdXIlSXxbh/Fw1lVjiNBR/g28bluoIPiEVh1uqOfp8KeFFrLkOVyYJMLoc3vG5crG1Eh/kQkcw+DrIhuAxCu3iS6yjTWGHVOpBHHllk0WrugwYaHGTDCKX9aDAK7bKb3IRRY0ZlYYVWIPkG7PrRgg/YRzzjhl0vPAMalQVmTSNMWuHag8lrsOkHoFGZkM6FcZBZQ4V+BF2WFviSHqhVGjj1Qm5fic+j3tgMo9qEw2wcnuQm2swFj5naRT6fR7VBONRtLb6IWkM9LruaEE+nMen34kKd0Iab0TCS2Qw67cK90arU6HNUwWE0IZHJ4KbPg0dchft4EMFBOoWz/UJun1v1otZpRYXVhHQmi/EFD870NUKlAirtFtjLTegsHN64sO6D025BpV3wATfm3Bg61wq1WoX9vQME/VG09xbqu1DwATVWtHTWYPyNVQycboZWp0E4WPABAwUfsOSDyVCN6sIhiBMvzaP3XBv0Jj0igQN4Vn3oOduG1v56bC3sQGfQobbgR6deWUDnaAuMFgNi4TjWri+j71KX8Bwu7kCtVsHVUYgRrywIMcJqQjyawMr4BgYfFdrbs+JFLpNFQ3chRry+iMauWpQ7yu4YI271e0aMaB1sQmA7iNBeBO0jLcLzMbYGe40dla5CjPj+DIYe6xN8wG4I/u0gOk8LfmNtcgNlFWVH/8/YC1MYeLQHOoMOIV8Y3vU9dJ/rQDJziBe//228DcUHKDxg3uoDTnfXQ28048bCNvpaqmEy6BCNJ7HqCWK4Q4gzG959qFUqNFbbAQDjSx50NjhhMekRO0xhKuzH6bbCeMkfQiaXR2t1YTy9voPW6gp01lUikUpjesuLs+1CTN0ORnCYzqC9RsiNY3u7aHTYUGE2IZnJ4ObmDi62CWOrnXAU0cMkumoK42mPF3W2clRazMjkcri2vo0LbQ1QQQV/4ADBgwR6XIX469mDs8yMKqsFuXwOV1e2j/5PfzQGXySGvvrCuHHHD6vZgNrCKt3ZjXUM99RDp9NgPxzH7l4EvYVYt7YVgMmoQ0dhjH9zegt9nbUwGnSIHBxi07OPgS6hDYPBLLRaDWobhXaZvr6O9j4XTGa9MB+w7DsaW3kKPsBV8AGzY5toLviAw0AUKzPbGDgnxKTdzQDS6SwaCweuzo9toKahAiOPdCKZSGFhfBNDFzsAAL7tIBKxFJq7apGtKsf87A5q6myoqDAjncpiatKNU2cE7+TzRWE06o5+X1zwwuksg6PSgkwmh8nxLQyPNuHQZYB/P4ZgJI6u5sJYdmMPFVYzqiosQB7IZnM41VMPjUaNYDgOb/AAva1CfVe2Aigz649WoF+d28JwRx0MOi1CBwm498IYaBXa22LUo6HKBpdTKHtjwY3+1hoY9TpEYodY393HUHsdjHVZbG4HoVGrUV94q2FyZhsdbVUwm/SIxVNYWd/DUGE8t70TQi6XR2N94d7MedDSVInKKgcO4ykszWxjsDA+3XUHkU5mjtpbo1GhracW1goLUodpzI1vYviC4HF8nhASsSSa24Wctnh9FdVNTtirrUgn05h+dREjT/RBpVKhotYGm7McbUPCM7A8tg5HrR2OOruQl16aw/DpZqjVagQDUQT9B+goHLC8uuSF1WaCs9qK1o4qjF1bw8BII3Q6LUL7Mfh2w+jqFXLu+qoPcNhRX3i+X1/bwkhDHUw6LYLxBDb3wxipr0V3dSWW/UEYNBo0VghzNVc3tjFQVw2zXofIYRI+dRBDNuH52Iz7oVap0GAq+IvwOjrKamHRGBHPJrEY3cGIvQUA4E4EkM3n0GwWnpep8CY6LJUo15qRzKUwH93CsO2WTwwimUsfHbw7f7AJl7ESVq0FqVwaM9F1jNqEeZ29ZAj7BvPRwbqTwV3UmctRZbQgncvhyt4WHqlpQretCruJAwQO4+ivEO7j9L4XVUYLakxlyObzGJ/34WxLPbRqNfwHMXgjMfS7hLILXj9sJsNRLHp9dQunm13QazQIxOLwhKIYrK9BKhHHEt4BxQfcNap8Pn8CL/vuiEQisNlseK/556BV6Y+lpdKSvlfRkXRUKo4OEztnRVRkmHNauucJigx+9MJNis5j1gWKDgD8XXCYovPyK/0UnYbvZyk65sUARUeV4dQnbzZSdJioYgmKTj56cGyNTC6F7wb/DOFwGFar0P+DwSDO/dGfQGMuffVANh7D1f/vr8HhkN+bLQrvLm75gMfxJLQq3YOuDhe1hialsXJWROUb6ig6wVOcLQJ9j2YoOh8+c42i857yeYoOAPxTeICi8+1rpyg6tT/gvGRcMR6k6MDN2Ys2exCj6AAAchxvIicy+TRexLcVH6AgW275gJF/9fvQ6I/n65M2zvg7Q1oYq0lydADAusGJT9a5fYoOa7yTJm1ZGGnhjAmzet4cjsXH8TjmZc49y29wzoTLD3RQdDY+yJmbsl3gnZFgMxxSdJbcnPky0/zxn+ts8hBL//Gzig8goGzXI0Nurcg/ts57uik6ADDyKEeLpcPiTGHl/nF5xMXR6bJwJsurDOcoOkxurdo/LqcL39gfl5GL7RSd4UscA8Fk5HwbRYd1bcxYpKBwEhh9H2filaUDAKPv5eQnlsdhcbaX5ANqObmp3cy5Zw7DeYoOk0fqOG19po+jw8qVcnumqf1ehrFIQeEkcL6zgaJzoY2jc76DowPwxt8sWOOd0cKb2MflLCnHneuRVzsDOHqr/Ng6T/RxdM62UHQutvD6B4Nbq/UZPFLD8besWKQgjjLJL0dYq+uZq/TlWCcGpPqo5HZdMoTWQiyhh/SRBiC/a5NlIykoyBg55lxeQCDpcJBbU6tI7cPSYcLySrJ7FOWW4+TY7+XWRgoKMkduuYCaU2QWDx7e3ETSYSKzuRda/5DZM81EljFEoSjKnvwyJLATkpUOAAR2OVosHRb+4PG3GgGA3RhHJ5zhvOaWyO5RdJh4Sa+q+wOctg54IxydXY4Ok4CPdG2sNio1Fil78CmcUALbnK1GWDoAEPCQ6rTDyXMsfPskHxDn6EQynHY+zPJeC2fB8kp7+xw/EfBFOTpEv82A2u8fdCxSfIDCCcUX5sRLL2FbTQDwRTg6AG/8zSLgDVN0/HvyynF7IXm1M8AbW/o9HC/p3+P4AFY/YxFIcZ5pANhNPOBYpPiAu+Zdt5K/paUFKpXqbT+f/OQn37H8n/3Zn72trNEov/2xf5iwnxNsWDpMLWadGOxH4hSdwCFH5yDDaZ9UTl6TKAAQSHDaKBTh7K0YDnIMVFhmRhUAwkFOW4dJX6iU2u9V+eP/KDx8nAQfENrjDIJYOoIWywfIK2aGopycEjjk6BxkOfcsleNN9LJgeSWWd6P5AJl5W26/f7CxSPEBCm/lJHgAAAiS9pLfJ+kEDzg6AC+GswgHOLkgFJJXjtsn+RsmYdIXGGFSbmLVh9VfWYTSvHOAaN6txDZSfMDd866b5L927Rp2dnaOfv7pn/4JAPAzP/Mzd/yM1Wq97TMbGxv3q7ol0TbI2T+NpQMAbaS981g6LDpbOIeN9FdydOqNnD3PbLouig6Tvqoqik5HK0enrZdzsGNbn4uiw6Stp5ajQ7o2ZixSUDgJPqB9pEVWOgDQPszZa1Zu8aCriZNT+h0cHZehhaJj1clrn3iA55W6mkk+gJUrZfZMU/u9DGORwsnmJHgAAOhxceJcTy1Jh1QfgDf+ZsEa73R0yivHdTXy7hmLth7O+JvlSdu7OD6gl9TPWLRbePMT/RWc55oVixTEeddt11P1lonCL33pS2hvb8djjz12x8+oVCrU1nI6sIKCgoLCfeQEfvuuUBzFBygoKCicIBQfoPBDKB5AQUFB4YSh+IC74l23kv+HSaVS+MY3voFf+qVfKnrYxcHBAZqbm9HY2Ignn3wSMzMz97GWd8/K5CZJZ4uiAwArUxwtlg6LxTXOnrXTfo6O+5CzsiScXqDoMJnZ45wTsLTKaeuV2R2OzoyHosNkZU5e11ZyLMoTfhQeah5aHzC2JisdAFgZX+foTHE8DouFDU5umglycpMnyblnkfQcRYfJTIDTRouke0bLlSTfzoLa7x90LFJ8gEIRHlYPAABz25w4N7dD0vHwzntjjb9ZrMxsU3SWF+WV4xY25XdG38ocZ2y5PM6ZM1le3KXozO7Kq61XYpxnGgCm970UnZJjkeID7pp39ST/t771LYRCITz11FN3LNPd3Y0//dM/xbe//W184xvfQC6Xw6VLl+B2u+/4mWQyiUgkctvP/aSi2iorHQCoqCqXlQ4Lh91M0akycXSsWhtFx6B2UHSYOM2cNmLdswpnmax0mMjt2kqNRcoefApiPKw+wF5jl5WOoMXJTxVVPG/CwGHj5BSnkaNTprFTdPRqJ0WHiZPklRxWmfkAot9mwO33HK1SdRQfoFCMe+UBgAfvA5zlnDhXWUbKcSQdgDeWY0Gb53DIK8exdJhUVJLybg1pvsxhoeg4LfJqa7uON+dWZeS0UamxSPEBd8+7brueH+brX/86fuRHfgQu1533nLp48SIuXrx49PulS5fQ29uL5557Dl/4whfe8TNf/OIX8fnPf/7tf8jlAFXu2PUWw1Frx+b88VcXOWpt2FzgrFJy1NqxKfZNZ168B0mpk+owdTdVuyMmb1K0TH2DHl6RctYF8YDU2mWFd7H4Keb/P/WoqM5lVxNe8RTf9+zv7f2iOo9UN+NVn/g33Hkv5+Cpirk7r565RXtPGfzz+0XLGL3iB7LUNemxK1JOlRC/95U2I7bEykl5ph0WbKbSxeuTI8aNrLhWpbkOW+Hih1vmE+JtXWFtwEZUROdQvK0dDjM2ipTL5zl9XuHkcd99wH2i0lWBzdniExD3UwcAKusqsDlbfGVQPp0R1XFUlWNjuvjbPWrSAWZmn/ggp8FlhNdXvN5lSzpRnZZ2O3ZWih/A+j9VZ0R1Ltc14ZWd4ttKfMc2KKpzydmC1/zrouUOAybRMlKwzYoPKdo6bfAtFZ8os3gORXUaag3weYrnDVVE/NC5SosLWyLlcinx/ORwlmFDrFz+3o8fbkHt9zKMRQoKt7hXHgC4tz5AynRCdbkFqzvFD1CXMnlVU27Bqq+4Tl7Css8quwXLfvED3TMm8TFhRU0ZlgPFx4TZMoN4pSSglTAmdNTasLlSfJWxJiyem6pMBrhFypW7xdunqVoPv7t4vTNGjQQdA/Y8xceoAGAIireRFFQSxoSVdhO2RMqpKsUXKzq7muD2FW/reKX4PIe1zYFkpPhYVyNhmFprsmAtVbx/eNd5izB9meLPUU19E5a2xX2Z0Sv+HDW0ObC1WtwrmfziwajRaYbHH7jj37OpEzgbf494167k39jYwAsvvICPf/zjd/U5nU6H0dFRLC8v37HMZz7zGYTD4aOfra37u8VMTsIk3v3UAYAcaZKSWScGuRwnmGRJ7ZOVMKkshRxJhwnt2ljPIunes+rDhHZtDzoWKa/nKRRB8QH3T4ep9dD6ANIkbpZWH/kFQFYb8fK3vHIli4eq3ys+QOEO3EsPADx4H0AbW8pMB5DfODWXlVcukFuOY8Ibx8urrZn9gwHLbwG8ti7Z3yo+4K55167kf/7551FdXY1/+S//5V19LpvNYmpqCh/84AfvWMZgMMBg4Hx7XAqTL3P2U598ZZGiw9Ri1onB+BhnH9Vry5x9z17f4RjI1/fktT8sAFxf4KzgmrjB2YNv8rXi5v5+6zChXRupv078YL6kzx33FbuT+HreSeJh9gET3+fsF8zSAYCJF2c5OiXGg3vFGOn8oqurJB/g5dTnSoCTK5mwvNL4OMfjsHLlxEvyOv+A2u8fcCxSfIDCnbiXHgB48D6AFS+vrpF0SDkOAG7Myeutnsk3Vig6E9fWKTqsHMfyN0wmX+e0NSt/0zwgqZ+xeN3D62NX1jnXdn2xtDopPuDueVeu5M/lcnj++efxi7/4i9Bqb/+e4qMf/Sg+85nPHP3+u7/7u/jHf/xHrK6u4ubNm/jIRz6CjY2Nu/7W/34y+EgXR+dSJ0WHqcWsE4OhkUaKzpn2eorOhdoGis55J+e6mJzu4rTR0Kkmis7ghXZZ6TChXRur31/uLu2Dyjf3CnfgYfcBQ4/1yUpH0Oql6JQcD+4RwwOcvHu2leQDajj1OVfJyZVMWF5peJjjcWi58tEeig4Lbr9/wLHoAfiApaUlXLp0CV1dXTh79uwdD2n9+te/js7OTrS3t+Ppp59GOn37thj5fB7vfe97Ybfb774SCkV52D0AwIuXZ1tIOqQcBwCnunlaDAbPt3F0zjRTdIZIOW54kOMnmNDampS/WW3E6mcsztfx6nO2maN1urNEHWU+4K55V07yv/DCC9jc3MQv/dIvve1vm5ub2Nl5c8/3/f19PP300+jt7cUHP/hBRCIRvPbaa+jr4xlgNhqd+N5Y91MHADRa+dWJgVbD6QI0HbW8dJiw6qTRkJ5FLak+pL7BhHZtpP6qlVm/V3j3o/iA+6sD8GKd3OKBlhQv5Za/taqH2Qew8jeprWX2TFP7vQxj0b3mE5/4BH75l38Zi4uL+Lf/9t++46Gua2tr+M3f/E28/PLLWF5ehtfrxVe/+tXbynz5y19Ge7v8FoI8DDzsHgCQ4RiVpAPwYjgLWi5g+SQZ3jMWtDklpa2LolPzcu7D2kYPM+/K7Xr++T//58jfYS+3F1988bbfv/zlL+PLX/7yfagVj31v8QNcpesUP9zsrrR88qsTg2BQ/GA2KfglHPAmhb0ESeeQo8PEH4lTdPYDxQ/HkayzV/yAROk68nqmAeK1kfprsNSYdtxv30/gN/cnhYfeB+yGZKXD1Co5HtwjgvukvHvA8gGcXLmXlKEPiHLqxPJurFwZJPYzBnLs9yXr3Gcf4PP5cP36dfzjP/4jAOCnfuqn8KlPfQrLy8vo6Og4KvfNb34TH/rQh1BbKxyS/Su/8iv4gz/4A3zyk58EAMzMzOBb3/oWnn/+efyv//W/jnEBCu/Ew+4BAN7YkhV390g6ABAIc/IcC1ou8HPGqKwcF9yXVzsD8ht/s9qI1c9Y+EhzSgDgJ/nbkueCHsB8wNLSEn7xF38Rfr8fNpsNf/Znf4b+/v63lfv617+OL33pS8jlcnjve9+LP/mTP4FOpyv6txdffBE/8iM/gu7uN99sfv3112EymUq+xLeifJ0iQwI7IY4O0eQHdjiDcmadGPhJydgX5gS/3RinPt4ER4eJL8Spk59kDgK7rGdaXhNWAPPaQhwdz35Jn7u1B99xfhQU3o34t4Oy0gEAf4n9+K2UGg/uFX7SF8c+0oTMbpyT47yHHB0mLK/k98vMB8jtmWb2+wccixg+IJlMIhKJ3PaTTCbf8f/b2tpCXV3d0RYwKpUKTU1N2Ny8fY/szc1NNDe/uTVHS0vLUZl0Oo2nn34azz33HO3tU4WTByteekm5iZXjAGBvX17j1ABpUVPAx9FhzU/4A/LzAQHSQg9W/ma1EaufsfCS5pQAYgwpcS7oQcwHHPeNPrG3/bq7uzE+Pn70w5zgB5RJflnSMcLZz61jmLcfK0uLWScGXV01FJ2+xmqKzqCTU5+BCo4Ok74mTht19tRRdDpIe/B1DMrv/APatZH6a+doS2kfVPbgUzihdJ7m7FnK0gGAzlOtHJ1S48E9oquDky/7XSQfUEnyAbZaig6TvgZOG3V1ca6NlStZfYMFtd8/6FhE8AFf+cpXYLPZbvv54he/eLwLKsLnP/95/ORP/iR6eznnmCicTFhjy/56eekAQE8LT4tBxwBnz/HOPhdFhzU/wfI3TDpI5yCxxt80D0jsHwxYc0oAz9+WPBd0n+cDbr3R95GPfASA8Ebf1tYWlpdvP+z5h9/oU6lU+JVf+RX81V/9lejf7gfvyu16FBQUFBQUFBQUFBQUFBSK8elPfxqf+9znbvs3g8HwjmUbGxuxs7ODTCYDrVaLfD6Pzc1NNDXdvuihqakJKysrR7+vr68flXnppZewubmJP/7jP0Ymk0EkEkFLSwuuXbuGqqoq8tUpKCgoKCgoFOPWG30/jMFgeEcvUOyNvh/etq/YG33F/gYAKysrOHXqFDQaDT72sY/h137t1zgXWkCZ5C/CM888g2eeeQbZbBYAMPSeXhh0Rkz+YB6dp1tgshhxEIphY86D/oudAAD34g5UajXqC98KTr+6gNbBJlisJsSjCazO7WLgklB2Z9WHbDaHhk5hRdLc1RU0dNbCYjWh91w7Fm6sYehRYa8m74YfyUQKTT3CN8QLE5uoa6mCtbIMqcM0Zq+sYOSxHgDAnjuIWCQBi9WEkcd6sDS+gSpXBezVVmTTWUy9toSR93QDKhUCu2GE/VG0DQjfhq5MbaGiqhyOWjtyuRwmX1nE4KVOWGxGNPfUIbATPlrduzbrRrndAqerAgAw/tIcBi50QGvQIrwXhXcrgK5TLQCAjXkPTGbDUZ0mX15A9+lWGMx6RPdj2F72ouessMrHvRmCTqdBbXOl0IZXVtE+UA+TxYBY5BAbCzvoOyusmtpe8wMA6ludAIDZa2to7q6DxWpE1GrG0uLu0Qn1Hk8ImUwOTU0OoeyMB/k8cOp0Mw4PM5if82BkVLi23d0IDhMptLQ6Ee4wYmrTC1dFOSrLzUhlsri56sGFLkF3NxSFL3xw9Pvslg/VNgucVgsy2Ryur2zjbEc9Dl15eOMH8Cfi6K8UvsmcCfhQaTKj1lyGPPKYC+7hQm0DtGo19hJx7MSiGCp8Ezu/74dVb0BDtREA8KpvA6cr62HUaBFMJrAZC2HEIaxy9x/G0Wyxo8FiAwC8sbeJ4QoXTFotQqlDrEYDOFVZj7xOj9XQPjQqNZptQtmrnm30V1XBotPjIJXCXMCPs3XCc7ceDiGfB1rtdgDAjd0ddFY4UN9jRDyZxuyGD2e6hNUQbn8YqUwWbbVCe2/thdDV4ERFmQmH6QwmV3dwrltos51gFLHDFEbPCvdxcc6D6lob7BUWpNMZTI9vYeRsC1RQIZlMwWY3o61TaJflhR04nGVwVJYjl8th4sYGhi51QK1WIeiLYN8XRXthhcbarAflFRY462wwlwuvRfWfa4NOr0EocACfex9dhedlY2EXJose1fVC/SdeXULP6WYYjHpEggfwbPjRM9oCi9WIylobdHotapuEZ3bqjWV0DjXCaDYgFoljY9WPvtMthWd2DyqVCq4W4Vpnrq2htbcO5jIjErFDrMx4MHBO6As7G34hRrQJz8vczXU0tDhRbjcjmUhhYXwLQxeFQ928W0EkD9No6qyBxWqCyWJAXXMlrA4LUocZzF5fw8hlIfbseUI48O2jpU9olzvFCIvVhMauWiFGFFZMrExuoaLaCketDblsDhMvTGHwcje0Og2C3jACnv2jlbqr01sot1tgsZkw+kQfxr4/i4FLXdAZtAjtReDd8KP7TBuS6UN87x/wdpQ9+RUeMG/zAU/0waA1YvLFWXSdaYOxTPABmzNu9D0i5Gv3ggdqtRquQm6ffnkebUNNMNvMiEcSWBlfx+B7hBWenuVd5DI5NBRy++xri2jscaHMbkbfxS7MX13G8BPCHpC7az4kEyk09wmroOavLMHVXgOr04pUIoWZVxcw+v5BAMDeph8H4TjK7GaMvn8Qi9dXUNXoREWNDdl0FpMvzWL0fQOCD9gJIbQXRfuwYEZXxtdhr7Ghsq5C6OMvzmLosV6U2c1o6W+A37N/tHJ5bWoTZRUWVDUIsW/iteV37OMAsDG7DaPFcBQPJl6aQ/fZNhjNBkSDB3Ave9F7Tohn7kBS8AGFfD19dQ3t/a43fcDiLvrOtAB4Bx9wfR3NXbWwWI0IVZqxuOLDcGHlmGcnjEwmi6ZGQXdmfgf5fB6nR5pweJjG3OIuRocKud0bQeIwjdbmSkRatZhyF3yAxYxUNosb6x5cbC/ksHAU3sjB0e8zHh+qrRZUlVmQyeVwbW0b59rqkarLwhuPwX8YQ7+j4AOCe6g0mgQfkAfm9v24UFPcB7Q4BR/wmn8dpxwNMKq1CKYS2IrvY9guPEv+ZAxN5go0mIXcfiWwgSG7CyaNDqH0IdYOAhitqEfKYMBKOAiNSo0Wq10ou+tGv6MaZXo9oqkk5oJ+nKsV8sV6JIRcPo82m+D9rns96LRXwtVpRjyVxsyWD2fbCz4gGEYqnUVbTcEHBELodjlRYRF8wMTGDs53FDzafhSxZAqnTgnXurCwi5oaK+x2M9LpLKam3BgdbYJKpUIymYbNZkJ7u9CGS0teVFZa4HCUIZfLY3x8k+YDjHYtqpuEZ2v8+7PoPd8Bg1mPsD+KnVUves51wGIzodJVAZ1Bi7pWoU5vHSusj6+9JUao4OqsKyFGLKCx24VyRxmSseQ7xohb/V5KjGgdFHzvnWJEmd2Mpt56hPYiaB8R+tzK2BrsNXZUugox4vszGHqsDxqdBvu7Ifi3g0cr99cmN1BWUXZUp7EXpjDwaA90Bh1CvjC863voPteBZOYQL37/23gbBB9gMBhgtVolFa+ursapU6fwjW98A0899RT+5m/+Bg0NDbcN7AFhZd/ly5fxO7/zO6ipqcGzzz6Ln/u5nwMAvPzyy0fl1tfXMTIygvX19WNchMKD5K0+4HR3PfRGM24sbKOvpRomgw7ReBKrniCGO4Q+veHdh1qlQmO1HQAwvuRBZ4MTFpMescMUpvf9OF2Ik5v+ELK5PFqrC+PptR20Vleg3KjHcEstpje9ONsh5LDtQASH6QzaC2Orsb1dNDpsqLCYkExncHNz5828FIoiephEuUGPi+2NmN72otZWDmeZGZlsDtfWt3GhrQEqlQq+4AGCsQR6XcKXUHOePVSWmVFttSCby+Hq6jZMOi0udjRiLxqDLxI7Wrm8sOOH1WRAnb0cADC5u4GRLhd0Wg32IwnsBCLoaxXi+up2ACaDDuVmA872NeLGnBv97bUw6rWIxA6xuRvCQLvgnYL729DqNKirF9pwamwTHd21MJn1iB0ksb6yh/7hQrtsCduB1d/K7RNutLRXwVJmQMqzXxhbCb5ldzOIdDqLxnbhWufHNpHP5zHySAeSiTQWxjePxlY+9z4S8RSau2qQNxqwMLWNGpcd9koL0qkMpm9uYvSCEOv2dsPw+6JHvy/NelBZbYXDWYZMJoup6xsYPtuCvN2IQOAA+/sxdBTmi5ZXfLDbzHA6y5AHsLq6h6HhRmg1auzvx7C3Fz16g21tbQ8WiwGVDUK73BjfxECfCwa9FuFIAp6dMHq7b7VhHK46O+pqhPg3NrmF3u46GA1aRKKH2HQHMdDrgi6axtZGABqNGq4G4TmcGt9Ce1cNzGY94rEkVpd9GLg1p7K1j1w+j4aCR5uZdKO51QlrZxUO40ksTbkxeF5ow92tANLJDBoL17qzEUBbnwvWCguSh2nM39zA8CUhvvq295GIJdFcyO2LE5uobqiAvbIc6VQGM1dXMXy5U5gPSKRgc1jQWhjLrky7hfFptVWYw3ptGaNDjVCrVQgEYwjsx9BV0F1e24Ot3IQqZxksZmGSd6i/HjqdBvuhOLy+CHputfeGH+bKMrgKz/cbK1sYaaqDUafFfiyBzWAYw421KDfoUV1ugUGrQYND8F3X1rbRX18Ns16HSCKJSY0PZ2qEXL4aFmLELd911buNXocT5ToDDtIpzAR8OF8rPN/rkRCy+RzabUJ73/B50GGvhN1gRDyTxoRvFxddwr3ZioaRyGRQbtDjcn0Txnw7aLba4TCacJjN4PquB5frhby/fRBB6iCDrhrB40x7vKizlqPyVozY2MbF1gaUG/Vod1YgGE+gp7YQI3YKMaLcglwuhymfG6c766HVqOGPxOELHRyt3F/c9sNqNqLMpMf5nkZcmd/CaIcLeq0GwWgcnkAUAy01SB3GMYl3gOADvvKVr+AP//APb/vn3/7t38bv/M7vHEO4NE6dOgW32w2bzQa3240PfvCDcDqd+PCHP0z7P1T5O51ao3BEJBKBzWbDe40fhlalP5aWSi/++YbOGriXvMUL6cS/n2noqIF7WURHpRLVkawl4VGSoqMi7UmVahFfLdPY6MDWVvF9QvdGzaI6LdV2rPtCRcuEezOiOm22CqyGi+/tqrGnxHXKHFg9EN//NO81ipaRQsW0+HPUXFOBDW/xa3NOiO+L19BcCfdGoGgZza74/rgN7VVwr+wVLyTlmW6vhnvFV7yQlrgnazYnWkTKteUTCXEdCf01f/jO+9reptNZC/fS7h3/nsmn8L3YXyEcDh8NxIPBIC799p9Aa7KI6t9RNxHDa5//NTgcDsmfYRy0AwD5fB7ve9/7cPPmTYRCoZKvQUEe3PIBj+NJaFU68Q8ck4ZuF9wLnvujo5YWnxq66+Be2CkuZRLPKWLxAADU1U5JdRIj3i3+anBjfQW2tovnDP+Q+D1vcdqx7g8VLXPQJSF/WyuwGileH6NNPO62ljmwJsEHHAY4nss2K+5LW6rsWN8LFS3jnDwU1ZHi3QxinhXScmXOX9xvAEBDVy3ci8Wf6dwd9oAvCRFvwoofTC0xnUw+jRfxbVn4gIWFBTz11FMIBAKwWq14/vnnMTg4iI9//OP40Ic+hA996EMAgP/23/4bvvSlLwEAHn/8cTz77LO3+QDgzUl+xQe8+7nlA0b+1e9Doz/e+ClVLj5ukjK2zEjoGq1OO9ZEcpNKfIgqKccBgGVXfJzSXFuBDZGxmm2Rsw+4VsIBrQ1tVXCviuQCi3iubGiphHu9eM7IVIrrSMlxGaO4d2tsqMCWW3xMbAhy8pNG5HkFpLU1MllxHQnj7/iA+PZJUtpob1R8/k5KP4s1SehoElFliseQNnsFVkPi997oFX+OWivtWAuEipYx+8TnTMTmgrKpQ0z+2efuiQ/4/mf/L1gst2vcaSW/z+dDR0cHgsHg0Rt9dXV1eOWVV277wv+P/uiPsLKygmeffRYA8Pd///f4gz/4A7zyyitF//ZWvvjFL8Lj8eC//tf/WvI1vhVlT34Z4qyXbkSL61RQdAAcrdY/tg6xTgyqqsspOrV2jo7LwtGpM3N0mNRWlFF0qqqlrcYSw1lnl5UOE9q1kfprVUOJMe0B7Ml/3IN2bvHlL38Z7e3td18BBQUAVY2VstIBcLRa//g6HI/DorqKlHdtMvMBRk6uZMLySlWke8bKlay+wYLa7x90LHoAPqC7uxuvv/46FhcXcf36dQwOCm8/fO1rXzua4AeAp59+GisrK1hZWcHXv/71t03wA8Ir+soEv0IpsOJlLSk31ZHqAwDVDs6YkIWzzkbRqaol6ZByXLVTfvMBcht/s9qI1c9YsLwkwLu2kueCCD7g1ht9P/xzp237fviNPgBF3+j7zne+g93dXeTz+dve6Cv2t52dHeRywpeh0WgUf/d3f4fR0dHS2uYOKJP8CgoKCgoPLbf24Pvhn+QdVlQyDtoBgJmZGXzrW9/Cv/t3/+7eXZiCgoKCgoKCgoKCgoKCggKN5557Ds899xy6urrwpS99Cc8//zwA4OMf/zi+853vAADa2trw+c9/Ho888gg6OjpQVVWFT3ziE6J/+5u/+RsMDg5ieHgYFy5cwD/7Z/8MH/vYx6j1V7brkcD93q5HEhK265GExO16JEF6lO7ndj1SkLJdjxSkbNcjBSnb9Ujlfm7XIwUp2/VIQcp2PZJghcf7vF2PFKRs1yNJR8J2PWLcabueR37z+K/nfagsKnkPvhs3buDnf/7nsbCwcPRv586dw5e+9CW8973vPfq3X//1X4fL5cJnPvMZAMDs7Cz+xb/4F9jc3EQ6ncZjjz2Gr3/96zCZTMpr+g8J93u7nvuKxO16JElJ2K5Hks593K5HClK265GClO16pCBlux6p3M/teqQgZbseKUjZrkcKUrbrkaRzH7freTdyp+16GD7g1S/c3XY9CgrvxP3erkcKUrbrkYKU7XqkImW7Hincz+16pCBlux4pSNmuR5KOhO16pHI/t+uRhITteqQgZbseKUjZrkcK93O7HqlI2a5HClK26xHjTtv1KD7g7lFW8suQWwfzHlvnQod4ofusxawTg8GhBorOqTZOErl1sN1xOevkXBeT0Q5OGw2MNFJ0+guH28pFhwmrTrR+f6mrtA8SXs/79Kc/jXA4fNvPrcn5e8HnP/95/ORP/iR6e3vv2f+h8PAz8GiPrHSYWiXHg3vEUD8n755uIfmAak59zjg4uZIJyysNDnI8Di1XPiKvZ1qW/b5UnQewXY+CghxgxcvTzSQdUo4DgJEunhaD/rOtFJ2BU00UHVaOY/kbJqy2ZuVvmgck9TMW5+p49/5ME+faSp4LUnzAXUNaDq7ARKvn3BatgXd75VgnBjod59tLPWmltp60opKlw4TVRjrSWyw6Pak+pL7BhHVtrP6qO47OMRPzrT34pNDY2IidnR1kMpmjg3Y2NzfR1HS7aW9qasLKysrR7+vr60dlXnrpJWxubuKP//iPkclkEIlE0NLSgmvXrqGqivN2kcLDj87AWTnO0gF4se5Y8eAeQPMBGpnpyNEHkK6Ndc9oPoDYzxhQ+70cYtEJHKArKNDGljLTAQAd8w1nAnIbE9JyHEmHCa2NZNbWzP7BgOkBWf31WG2k+IC7QlnJL0PCe5wtS1g6ABD2y69ODEL7cYpOIMrR8R+S6pPk6DAJktootM95fTMUOCDpyOuZBnjXxuqvIdKrsvcaxkE7L7/8MjY2NrC+vo5XXnkFVqsV6+vrygS/wl0R8oVlpSNocfqx3OLBfoiUd2MkH5Ag1SclPx8QOCD5ANI9o/kAUt9gwe338otFCgonAdbYkhV3WToAsB/hbBnKgjcmJI1RSTmO5W+YyG38TfOAxP7BgOUlASBI8resuSAFcZRJfhni3fRzdLY4+4gytZh1YrC7yxl0ePY5icYd5QwU3TH5DaY8pGTs3QlRdHxbQZIOaf9/Iqxro/X7jdJimorwc7cc96AdBQUG3vU9WekAgHeDVKcS48G9Ypc0QUvzATFOfbbjIYoOE0+Q00Ys70bLlTJ7pqn9/gHHogfhAxQU5AArp3hCJB1SfQBgJyCvL0Z9bs5YzusJUXRYOY7lb5j43PIaf9M8IKmfsWDNKQHANiuGlDgXpPiAu0de70zLnHweyB/3XZGM+IEbXSNNGPv+bNEyUh7WrqFGjL84V7yQWtpj3zXUiPGXRLRU4t8ZdY00Y/yl+aJl8knOwXQ6CQmy/1IHxl9bLlqmaly8jU6drsbN8Y2iZcw+g6jO2YE6XJveKlomaxA/sOdcXyOuzhbXAQB9lHM4knlH/JvZ0TNVGJtZL1pG4xdPSL3dHRh/tfg9y6fTojqdg20Y/8FC8UI58f7eOSBBh3ngnoQY0nlavL/m0xJi0cV20ViErPjhSN2nWjD2vZkilbmDxnH30Svhs93d3Xj99dff9u9f+9rXbvv96aefxtNPP11Uq6WlRTl0V6Ek/v/svXd4ZFd9//+eXjWjOiONNGqj3rW92usCNtUGQjEQMAGHfAMJ/EggGEgo/hKTSgiYktBCEqohNl9acFnba+96q3bVe52i0YykmZE0mj6/P+6sdte7q3slfVZ7Vjqv55nn2XL10jnnnvK5Z+793No9Veh4umtzPGlp60Dt7kpRVzomPvfWtNWg45lV5gMA6QWaO710k+Lrbuu+SpzvH131mHyYRT0724pwtnNy9fLMiKcs2VNfglN9q6/fCa24Z1etHScHxOMA8wLNM9BGt/gLc3fssOJc1+qxklrCZkuThNgtHRK/mKzeUSIaJ6elxO07ytDxTPfqB23iy3Kp5g9K17o9NyEO4HBWQxFPQ7HBjqWUcENrW6kFJ/vF5nDxa9S2YiteHhTxSNgOaC2z4uUh8TUlqRaX1dUUiq5z0fyNvdz4IvKIhGvCvZXoOLl6HCBfEH/6oK6tWPQaVSVhn6PxgAPnj4+seoxKJt7OrfsdON+zugcAZBJiNymk1eKxSfWuCtG6JUryRD2OXWU4d2b1eCJsES9PU0OJ6J6JTEKY3GKz4sTI6h6dizCVtkh33Fdlw8vjEvaCQuJz2e46C05Oru5SRsQ9LRUWnF6lrWWx6zh4HLBm+CY/h8PhcJhElhY+G/l5DofD4XA4tyY8DuBwOBwOZ/vC44C1w9P1MMhEn4vI4ybxAMBEP42LykPFxJCXxDM+RvOo9qiTJj3KiIuttEgAMDFG88j3xCDNOZvo9zDloYRsvPYSzUW9ThIPh7NdmOgRv/tmMz0AMCHylJlkTw/NvELFxPAMiWdsgmj9dhN5POzFAePjNLESVexGFSdP9LC1xpGOewbnIg5nO0C1FgwTrQXD03RryihR3aiYGKGJA8iuUYeIykMU31BCVTeqvReqPZOhGbb69LCXrjxUc9Eog/tTWxW+yc8gWoP44+VS0BF5KF2UZaJAp1eTeLQ68cfBpKDT0Hj0RB5KtDqatqY6ZzoDlYetPg3QlYlqLtIa1vnIbZrgw+Hcgqx7zNwgDwBojVRlYmvOJFtTJKTQkQLV+k0VT1BC1UZ0cQDRGmdkq0+TjvubPRfxOICzTWHtmpDy2pK19Ym5a1QqD1G9KCHbe9HSeMjGh4RURZsJZXmoxuu6PTwOWDN8k59BrKX5JB5LqXg+M8kuO42LykOFpTiHxFNYKJ6vVwpFBSYaTz6NhxIrURtZSmjOGV2fziXxUEJVN2sZzVy0bg9f1DnbFGt5AVMeSpe1nGZeocJiyybxFFqJ1u88Go8tdwvHAUSxG1WcbC2jG2cUsDnu1+nhcQBnm2JjbC2w5dCtKVTrHBVWojiA7Bq1OJspDyVUZSosYmvPpDibrT5NOV6p5qJ1tzWPA9YMz8nP4XA4HCbhOfg4HA6Hw9m+8DiAw+FwOJztC48D1o4snU5vw2qvjVAoBLPZjDs0b4NStrHHVWQKhegxcrkMqdTqp0WmFP9+RooHcvE3s0t2ycQfDJHkkVA3SZiNJOWJF2WTeJZs4o9zy2UypESGZFIjfs6keABAvSDhdfES0HtEXvEOaW2knA6QeNLLERIPxP5fqidN084AgERC9BBJbRSn8SCZ3LAnkY7h2chPEQwGYTIJ3/LPzc3htr/6OpRag6j/ut7IEl74uz9Fbi57T1twbi0uxgFHcN+G4wApSBp7VB4ZXRwgU4q3jRSP3JwlqUyiWMTv1JZSnuVS8TvQJcUBhRJiNwnrd0JC5hPpcQDNZYDRHRM9RkobqafmSTyQkB9XiicVDpN40hLWbiqo5g9Kl3gcEMdzeJLHARxmuRgH7Hzb/4VCtbE0VnEdzbVcQk90TSghDJC6pqgWJVw7SXAZpmnmTJ1zQbw8UuKSBZpr3bSSZi9ISuwmdf6WxeKix0ghraLZn0pYxO/4luIJVurEPRL6YriIZpwlCS8flCLdUXIMGKIZr8rIxj3JWATnfvIZHgcQwNP1MEjt7koazy4aj+CqoPHspPFQUdtqJ/HU1ReReBqrCmk8lVYSDyV1DTYST21bKY1nRzlTHkrIxivVXLTbsb4f5I/ncbYpdXurmfJQumr3rHM+uEHUNpeQeOpraNbvJqL1u7mcwTigjiZWoordqOLk2j1VJB4qWBz36/bwOICzTWmqIFoLyog8pXRrClXdqKhtLqbxUF2jUq1xLTQeSuj2Xmj2Faj2TFrsbPVpFsdro2OdcTKPA9YMT9fDIFo9zQu8NEQvNgEAjY69MlGgIXohjZboZXJaDc2QZO2FRgCgIWojDdFLjqn6Imt9GqAbr1Rz0XpftMkfz+NsVzRELwSl8lC6WHvxLtWaQhYHEL0sjcpDCVUbUcVuVOs3c32awXG/Xg+PAzjbFR3RHM6aBwC0jF2nUr3ElewalTEPJWQxl46tPROdiq22piwP1djXqtd3zngcsHb4Jv8qPPbYY3jssceQzKSjaLmtDhqVFp0v9KNmZwW0Bg0WA2FM9LnQuF+4Q8U55IFcJoetSvjGq/ulAVQ2l0Jv0iG8sIzRbheaD9YAANyjM0gmkrDXCHc29Z4chr2mCDaHBZFwFANnxtB6Wx0AYHrCj2g4hrLMt5YDHZMoqiiAKc+IWCSO3peH0XakHgDgc85hKbgMW6UFADDUMY6C4lxkW0xIxpPoemkQbbfXATIZZqcDCPoXUdksfKs60jWJnAITcguzkUql0HlsAM0Ha2CrLMD8TBCzngCqWssAAGM9TmRl65FfLDz6cv6FATTtr4JSrUTQvwDv5CxqMnc5T/S7oTNoYKsQXrzVeWwAtTsroNGrsTC/BNewF3WZu4ado34oVQoUZl7O131iGI4WO3QGDZZCy5jo86Bhb+VKGwJYqWvvyVGU1RfBYNJhGXKM9LjRtEe4q3l6chaJeBIlDuHY/o5JmHMNaDtQhehyDAMXptCyT7jDcMY1j+VwDGXVViRzDejv86Cw0IzsHD3i8SS6Op3YsVNoB9/MAtJprPx9cNCL/HwjcnMNSCRS6Lwwhbb2UsQK1PDPL2EuGEZN5gVkgxM+5GTpUZBrQDoNhBYjaK8vhlIhx1wwDO/sIuozdRuZnIVRr0ZB5kUzp3qn0FpVBI1aicDCMpy+IJoqhW9IZQBKLGbYMi84OdvvREOFFTqNCsHFCCam59FSVQRlOI1J9xwUcjmKC7MBABf6nKgut0CvU2NpOYrhCT9a64Q7HJzT80ilgdIi4cVCXQNulJfkIr9YhshyHIP9HrS0C3cxTLsDiMUSKM2cx1g0Dke1BSazHtFoHH3dLrTtFPrHjDeI8FIMDodw7GCnE5biHGTnGRCPJdFzegytB6ogkwF6oxbmXAMqMk9PjHS7kGMxIdeShVQqjc4TI2g5WA25Qo55bxBz3hAcmTsZxnpcyMoxIN+WjaKyPJwH0LTXAaVGiaBvATPOOVS3C+dxok/os5YSoX9fODaI+l3lUOvUCM0twj3mR93Octgq8jE1OA2VRoXCMiE1RNfxIVS3lUKr12ApuIyJfhcaMnevuka8kMllsFUI57Xn5DAqGoqhz9JheTGCke4pNO0T5hPPuA/JRBIlmSc8+k6PoqTChqwcA6LLUQycHUfLoVoAgHfSj+hyDKW1NtgqCzBwdgxFFfkw5WYhFomh9+QI2m7PzBGuOSzOLqCiUbiDdfDcOApKcpBjMSMRT6LrxQG0HamHrbIAfncRgv4FOFqE8zp8YQI5FjPyirKRSqZw4WgPmg/XQalSYG46gFn3PKp3CGNutGsSWTmGlfHZ8WwPmg7WQKVRITATgnfCj9rdlYjGI3j29+BwmOOqOOCOBmiUWnQ+14uaXZXQGrVYDCxhsseJhoPCWHQOuCGXy2GrFsZt97F+VLaUQm/WIxxaxsj5cTTfJoxF9/A0UokUSuqEtb33+CDsdTbYqgoRXYqi/9QwWu9oBABMj80guhxDWYMwbvtPDsHmsMKUb0JsOYaelwbQfnczAMA36cdiMAxbZu4YPDOCAns+cqxmJONJdD7fi/a7moQ4wD2PgC8ER1s5AGCkYwzZVjPybLkrY7zl9nrYHFbMTwfgd82heqewBo91TsCYY0RB5mXf55/rR9OhWqg0yivGOABM9LigNWhgcwjx0YWjvajd44DWoMHC3CKcg9Oo3yfcEe1yhaBUK1CYeaFp94mhTBygzcQBbjTsFebUq+OAEZTV24Q4QK3BSK8bTbuEuk1PzSORSKKkQlhr+i9MCXHAvkpEl+MY6HKiJRMzzLgDQhxQZUHMYkDf4DQKLSbkZAtxQGePCzszd+3N+BaQTqdX/j447EV+nhG5OUIccKHbifYWO2J5SvgCS5gLhVFbmokDpnzIydKhINuINIDgUgQ7ajJxQCgM79wi6suFug27/DDqNCgoFNIZnRyYQltlETQqJQKLy5jyB9FcnokDZIA937zywrQzQ040lVmhVasQXIpgfGYerRVFUC6nMeGZh0IuR4lVSEt0fsCFmtKCTBwQw/CkH621Qh91egNIpYDSTCrDziEPKm25KChUILIcx8DgNFozd+p5PAHEYkmUZdbGWDQBh8MCs1mHaDSB3l4X2jNrrtcbQjgcQ3WmLw11OWGxZcOcZ0QilkD3mXG07XcAMhn0Bo0QB2SeDBjpcSHXkoWcAhNSyRQ6T46i5XCtEAdMBzHnDcLRKpybse4pZOUakW/LQVFFAc4/14emA9VC7OpbwMzULKovxq69LmiVJlgyL48//2wP6vdVQaPXIOhfgGfEi7q9VbA5rJjsc0GtVaEws7Z3Pt8nXCtk5oiJzgnSOSIr13jdOeLiuJcyR1Q0l646R9iqCjHrmrvGHJGNPFvOZXNEAxQqxXXniItl6ni6C02H6zJxQBDecR9q91QhmojguaNPgsNhjVfGATvqiqHW6nGu34X6Cgt0GhUWwlGMuebQUi3MSZOeAGRywG7NBgBcGHCjqjQfBp0a4eUYenx+7KgSrq2mfEEkUymUW4VrqwujHpRbc1BSYMZyLI6ecS921Qjrvms2hEgsAUdR5trb60VJnhk5Rh2i8QQ6xjzYV5OZf+cXsLgchT3PDNQAPVNeFGZnIS9Lj0QyhTMjLuytLoFMJsNMcBFzS8uoswnrUp/Lh7wsPSwmA5LpFE4Pu2DLzcK+ajv8C0uYCS6hoUSY6wY9fph0GhRmC+vS2Y5JtFfboFIqMB8Kwz27gMbMncCj7lnoNCrYC4S15ky/E00VVmg1KoSWhOvTZofQhjNxH5RKBWyZF7Zf6HGixmGBTqvGUjiK0Qk/musz16duIc1biS1zfdrnQmVZPgx6DVI5AQz3edCcueb0OOeQiCdhz+xJ9HVOwZyjR/veSkQiMQx0udC6W4gDvO4AIssxlDkskC1HMXhhCpaSHGTnGVeuT9sOCnGL3xNEOp1e+ftwtwt5VhNyCrKQTKTQdXIULfsckKkVmJtZwLx/EY4Goa6jfR6Ycw3Is5qANLAQWEbzngoolHIE/IvweYKozjxtMD7ghSFLi4LMy4LPnxhBw44yqDVKhObD8EzNobZF6C8yuQxFpbmwZl5W33lqDLXNJdDoVFgILsM56kN9eylkiQScoz4oFHIUZdbr7lNjcDTYoDNqEF6IYqzfg8bdQhu6x2eRTqdRnImles9OoKzaCn2uAZFwDEPdLjRf3H+Zmkc8moC9SmjvWCSByroimHL1iC3H0Xd+Cq37hfVixhXA8lIU9l1CXDDQNw1LoQk5OXrEY8L+S/vOMshkgE6vgTlbB0dVZr9rwIvcPCPy8g1IJtO40DGJnXUlUMhl8AeW4A8uoa4s02en/Mg2amHJMaLYYgZ6p9BWY4NaqcBcKIzp2QU0ZPrsiHMWBXka2DL9++XRKbTai6BTKTEfXsbkbBCt9kLY88wY8c1BrVTAniP02dNjLjQWW6BXqxCKRDE4N4f2UuGcj/vnIZPJUJYnnMezE27UWvNh1KqxFI2hb9qHXWXCOZ+cCyCZSqMiXziPHVMeVOfkwKzXYjkeR/eUF7srM3PEvDBHlOYJZeiamkZJrhk5Bh2iiQQ6xj3YV5WZIwILiKYjqC7OnMeJGVhzjMgzCXPE2SEX9tTZUVJgxkxgEfOLy6gtEc5j/5QPeSY9CswGJFNpnO+cwo7aYigUcswGw/DNL6LuYuw65YfJoIU9E2OezrS3MEcswzMbQkOFFbFIGOfAoYDn5JfAZufk1xo0iCxFV/dIyFuv1WsQCa/ukZqTX6tXIxIWybcqISe/JM8m5uTX6tSILK9eHik5+bVaFSKR1fPZScnJr9OosBxd3SMlJ79Oo8RyVDyX4Wbm5JfSRlJy8kvpQ1Jy8kvqixLyGErybHJOfkltJCEnv5S5SEpOfjHP9XLy3/6XG8/B9/w/bq8cfJwbw2bn5Jc09qg8EnPyS4tNxNtGimczc/JrdSpElldfm6Tk5JcUB0jIyS9l/ZaSk1+nVmI5JiUO2Lyc/FLaSEpOfimxm5Sc/FLiZCk5+aX06c3MyU81f1C6xOOAa+fk53EAhxU2Oye/lDlcSk5+SWuBhDBA6poiJSe/FNdm5uSXEgdIyckv6fpLQk5+SWuchNhNkgebm5NfSpmk5OSXEk9IyckvJeaSkpNfSp/ezJz8kmNACTn5pbik5OQX2+e6Xk5+HgesHZ6Tn0HqifLV1u2hy8lft96c2ld56MpEQV07Te68hkaavHBN1TQ5fS/eBcES9U00+Q6pzlkdUd56Kg8lVOOVai6q37u+fMUXH8/byIfDuRWp31/DlIfSdfFufVaoI8oP20iUb765ksbTUsFeHNBA9G4esjiAKE6u30eXA58CJsf9Oj08DuBsV1qI1oLWciJPGd2awtp1aj1R7nqytamdqDxt7OXkp6pbQxNNPEHVF9vsbPXp1lK68lDNRU3rzMnP44C1w9P1cDgcDodNNvqynG24qHM4HA6Hs2XgcQCHw+FwONsXHgesGX4nP4NMDXhIPM5BGg8gvGuAxjNN4qHCOTJD4pmcFH8sXArjbvHH1CV5PDQeSqYmaNpoasRH4nEOeZnyUEI1XqnmoqkBN4mHw9kuTPW5mPJQuqb62ZoPnGN+Es/k1ByJZ3yaZv0e87IXB1DFSlSxG1WczFqfZnLcE5aJw9kOjBGtBaNemrVpdIbGA7B3nTo1RnNtSXaNSuUZpfFQQlW3yQmimIuoL4766MYHBWOE5aGaiyYYG/dbGX4nP4Mo1eK52iR5JORF22wXZZkoUKqI2lpCfj0pqBQ037spiTyUULW1iuqcMeahhGy83uy5iH9zz9mmKNVUY5gwDmCwTBRQrd9kHqL1myqeoISsjcjWb7bWSiq21LjncQBnm6JSUq0FVNeodPMcVd2o4Neomwfd3gtbeyaU44MCJYPjdd3njMcBa4atGZYDACiqsJB4CjNvjSdxldO4CsvzSTxUFJaKv5RPCrbMG+43SrFV/OV+Uiix0HgoKSJqo8JSmpemUPVF1vo0QDdeqeaiosr1eXgOPs52pchhZcpD6VrvfHCjKLTnkHhsRUTrdwGRJ5+9OIAqVqKK3aji5KJKunFGAZPjfp0eHgdwtitUc7idypNHt6YUE61zVBSVEF1bUl2jUnns7L1olKputuJsEg/Vnok9l60+TVkeqrloveOexwFrh63bqTgcDofDuQj/5p7D4XA4nO0LjwM4HA6Hw9m+8DhgzfA7+Rmk68UBEk/3S4MkHgDoPk7j6j4+ROKhovvUGImn88IUiaeDKGfpuQH2cp92nZ8k8VCds+4Tw0x5KKEar1RzUdexfhIPh7Nd6Hq+lykPpavrBbbmg+4z4ySeC91OEs+5QZr1++wwe3FAZydNrEQWBxDFyV0v9JF4qGBy3BOWicPZDpwdopnDz4wQeUbp1hSqdY6KrrPjJB6ytenUOI3nNI2HEqq6dZ6niSeo9kxOj7PVp8+M0ZWHai7qYHB/aqvC7+RfC8kkINvY9yJSvkhy7CxH/6mR1Q9KpcQ9bQ5xj8R8XY62UvSfHl39ILl42zjaStF/ZnWPLC1eN0kEF8XLs7McAyILuzoaF/XUtpdioGP1TWyVVyPuabVjQOwLAwk5bWtbSjDQKWHDIZEUP0YCspiENmorxYDYRn80JupxNJZh4NyE1KJd39Nsx8C58dUPktAXHc2lon0IEtpHKulEQvQYR6tdfLxKmEOqpMxFEqhqX59HBkCWXv/X77J1/ySHc3Op2lGJ/pMb/1JckkfiGKtqrxB1pZPia4pjVwX6T67+5Wh6cUlSmcSQMgdIiQP0EfG1qbbNjoHe1ddvrVsr6qlrLkZ/1+oXQmkJsVtdUzH6u8UvqOQSYhwpyBbCosdIiZXSCwuiHseuCgycWX0zJbUcEfVUNovHyVR9ejOhmj8oXev18DiAwxryaBqK1MZuDZVJuNRtdBSgZ2R69bKIXxKgqbIA3aOre1ISdoSaKgrQPba6B4CkzY46u0XUFTPR5BSX2bJEj2moLUTvwOrlUc+pRD1VjTb096z+InbFkoRrXanX8USeRLZ+w78LAJaLdKLHNFQXondo9bZesoqf++byQnSNi/ShbPEVoMVuQeeUd9Vj0hIWknpbATqdq3vU4uGNZJRLqw80qeNVISEEbKy0iM4hUqgrW5+HxwFrh2/yM4jOKH4RuJkeSpfOKL7RvZnoDDTlIfPo1Ux5KNEZiOpG1dZEfVFnoBtnVLA2h6zbwx/P42xTdFlEY4/IQ+mijE0ooJrDdXqqOICteIISupiLrfGhyxLf2NhMmBz36/XwOICzTdFrxTeVJXk0NB4DkQegqxsVOh1b19+seSjRE7U1VR8yqGnKY9Cw1dYsjlfdej08DlgzfJOfQZaC4ndDbaaH0rUUWibxUEFVnqWQ+B1jkjwLbHkoIasb2Tljy0MJa3PIej0bfVnOdnzRDmdrcLPH3o10UZaJArK1gGqNW2TLQwlZrBQi6osBKg/NkydUbKVxz+MAznZlcVn8jm9pniiJZ4HIA9CViYrFJZryLC0SebbwfgBVW1P1x4UIWx4qSMdrmMa13jmNxwFrh+fkZ5DxHpq8rlQeABjvpcmhReWhYqLPQ+MZIPIMrf6Yl2TP8AyJh5IJkccgJXv6idq6b/XHKTfbQwnZeGVwLuJwtgPjXTTvMKHyULrGu2nyqFJBthYM0qxx40Tr9/iwj8RDCVmsRHTOyNY4xvo0k+OesEwcznZgZMpP4hl2zdJ43DQegK5MVIxN0LT1+AjNukt1Hc/ifsDoJE1bjxD1xyEvWx4qWByvI06ac88R55ba5P/c5z4HmUx2xaeurm7Vn/nZz36Guro6aLVaNDc34ze/+c0mlXb9NB6oYcoDAI37q2k8+6pIPFQ07K2k8eyuoPHsKKPxtJeSeChp2FVO49lDdM72OpjyUEI2Xm/2XJQm+HC2FNsmDji0ep0220PpajxYS+Khgmwt2FlO4mlso1m/G9vsJB5KyGKlvTSxZONBojWOcJxRwOS4X6+HxwGcV7Bd4oDWGhuJp62KxtPuoPEAdGWiormhmMTT2FpC4qG6jmdxP6Clnqat24j6444ytjxUkI7XahpX63o9PA5YM7fUJj8ANDY2wuPxrHxefPHF6x57/PhxPPDAA3j/+9+Pjo4O3H///bj//vvR3d29iSXmcDgcznq4+HjeRj6crQePAzgcDmd7wOMAzrXgcQCHw+FsD3gcsHZuuU1+pVKJwsLClU9+fv51j/3KV76Ce++9Fx//+MdRX1+PRx55BDt27MDXvva1TSzx2nGJvHF8sz0A4BqmSSPjGqHxUOEepXmMzTVG83iee4LmcSgqDyWuMZpHtFyjRG09QnPuqfoQJWTj9WbPRfybe8412BZxwCBNWhMqD6WLMjahgCwOGCda4yZp1m/X5ByJhxKyWIkoliRb4wjHGQVMjvv1engcwLkG2yEOmJoOkHgmvTSeiRkaD0BXJiqcrnkSj2uKZt3dyvsBU26atqbqj+OzRB4/jYcKFsfr1Ho9PA5YM7fcJv/Q0BBsNhsqKyvxrne9C5OT18/xeOLECdx9991X/Ns999yDEydO3OhicjgcDofDuQHwOIDD4XA4nO0LjwM4HA6Hw7k2t9Qm/969e/H9738fv/vd7/CNb3wDY2NjOHz4MBYWFq55/PT0NKxW6xX/ZrVaMT29+p070WgUoVDois9mUlxdyJQHAIqrrOIHSfE4aDxU2CotJJ7iigISj60sjykPJcUV17/LZk2eSqK2dtCce6o+RAnZeL3JcxF/PI/zSrZNHFBTxJSH0kUZm1BAFgeUE61xpTTrd3FpLomHErJYiSiWJFvjCMcZBUyO+3V6eBzAeSXbJQ6wF2aTeEqtNJ4yC40HoCsTFSXFOSSeYjvNuruV9wPsNpq2puqP5XlEnnwaDxUsjlf7Oj08Dlg7yptdgLXwmte8ZuXPLS0t2Lt3L8rKyvDTn/4U73//+8l+z6OPPorPf/7zZD4Oh8PhrIONPmK3DRf1rQ6PAzgcDmcbweMAzivgcQCHw+FsI3gcsGZuqTv5X0l2djZqamowPDx8zf8vLCyE13tl3k6v14vCwtXv3Hn44YcRDAZXPlNTU2RllkLP8UGmPADQc2KIxvPytc/VzaL35CiN5/QYjefcBI2n4/qPrd4ses+M03hOEZ2zkyNMeSghG683eS7i39xzxNiyccCL/Ux5KF09Lw2QeKggWwvOjpN4es7TrN895ze3z0qBLFY6SRNL9rxEtMYRjjMKmBz36/TwOIAjxlaNAy4Mukk854dpPB0jNB6ArkxUdPW6SDw9F5wkHqrreBb3Azr7aNr6PFF/PDfBlocK0vE6ROO6sE4PjwPWzi29yb+4uIiRkREUFV37EdD9+/fjmWeeueLfnnrqKezfv39Vr0ajgclkuuKzmZQ3ljDlAYDyhmKmPFSU1dM8hlxWS+SppnkEvayKvRQyZbU0j8WX1RG1db2NKQ8lZOOVwbmIw7mcLRsHNJcy5aF0lTfZSTxUkK0FNTRrXDnR+l1eRZMahxKyWInonJGtcYz1aSbHPWGZOJzL2apxgMNOkwKuqpgmZUuVjS71C1WZqKgoo2nrcgfNukt1Hc/ifkBlKU1bO4j6Y7WVLQ8VLI5XRwnNueeIc0tt8v/lX/4lnn/+eYyPj+P48eN405veBIVCgQceeAAA8J73vAcPP/zwyvEf+chH8Lvf/Q7/9E//hP7+fnzuc5/DmTNn8OEPf/hmVUESBrOeKQ+ly2DSkXiooCqPwaSl8WSx5aGErG5k54wtDyWszSHr9qTTG/9wthQ8Drg5HkoXZZkoIFsLqNY4I1seSshiJRNRX8ym8hhIPFRsqXHP4wDOK9gucYBRpybyaEg8WUQegK5MVBgNNOUxGIk8W3g/gKqtqfpjlpYtDxWk41VP41r3nMbjgDVzS+XkdzqdeOCBBzA7O4uCggIcOnQIL7/8MgoKhG9NJycnIZdf+t7iwIED+OEPf4jPfOYz+NSnPoXq6mo88cQTaGpqullVkMTyYoQpD6VreTFK4qFieYmmPGSecIwpDyXLS0R1o2pror64vEQ3zqhgbQ5Zr2ejj9htx8fztjrbJg5YIBp7RB5KF2VsQgHVHL4cpooD2IonKKGLudgaH8sLyyQeKpgc9+v08DiA80q2SxwQjsRpPFEazxKRB6CrGxXLy2xdf7PmoSRM1NZUfWgpRlOepShbbc3ieF1ep4fHAWtHlk5vw6821kgoFILZbMYdyrdAKVNtTKZQiB6iVCmQiCdXPUYmk5F4pJRHsksu/mCIpLopiB4wUYl/WyipPBK+mZXiSUv4RlWpVCCREGlnpYQ+pJQjkUiJHgex3yURWUx80pbUhyQskJLaOiVed0nlSYq3jySPhPaRSjqRED1GUpmo2kgCYp5EOoZnIz9FMBhceRx6bm4O93zgMSg167+LMBEN43+//SHk5uau28HhAJfigCO4b+NxgAQ2a+yRu+Q0MY5cTdPGMqP4HdaS4gBTlrhHwvqdknB3vZT1Oy0llpQYB8iJLgRlC2HRYySt3wsLJJ7UkvjGu6TyJIjim0283Nr0cU/gSaTjeA5P8jiAwywX44Dd9z0CpWpjd0inVBKu4xVyJJKrz+EJDY0nJeG2TykeAJBJuPyU4lIt08yZmoCEazkJ66V6TvyLSikehYSb3iRfxxN5kgaap0aWi8SfjJRy7pesEmIcCZ5YNs34SItroJTLkRC5tlYS3g+gXFp9fEgdrwoJIaAUlywlPl7FPMlYBOd+8hkeBxBwS6Xr2S40H65jygMAzYdqaTwHa0g8VDTtr6Lx7K2k8ewup/HsovFQ0rSngsazz0HjoTr3+6tJPJSQjVcG5yIOZzvQfHsDUx5KV/Nt9SQeKqjmcKo1rnlnOY1nRxmJhxKyWOkATSzZfBvRGkc4zihgctwz1kYcDuu019G8X2tHDY1nZzXde/WoykRFaxPN+1ma22nePUJ1Hc/ifkAb0btwqPrj7nIiTwVbfZp0vNbSuNqJPBxxbql0PRwOh8PZRqSk3RG02s9zOBwOh8O5ReFxAIfD4XA42xceB6wZvsnPIJ7RGaY8AOAZIyrTmI/EQ8X0uJ/GMzFL45maI/LMk3gomZ4kqhtVW5Ode7b6NEA4XlmYi3hCOc42xDPiZcpD6fKM0pWJAqo5fHqKZm3yOGnWSo+LwTiAbP2mOWdkaxzhOKOAyXG/EQ+PAzjbENdMkMTj9BF5/DQeAHARlYkKt4emPB5XgMRDdR3P4n6AazpA4qHq11NzbHmooByvTqK5aEPjnscBa4Jv8m82EnJ8JyIx0ePSMvFMS/FIDGmxXFwSc4TGl6OiucClvCcgsRwB4qsn/0qnpL0nQAwpucESS2EguvqL4NIp8XMWD6mRDovko42Iv3AuoZUD86FVj5FJyMmf0MogE/EAkPxOBlEknPt4JA6I9UcJ5Ykn06LHyST060QiKdpnRccPgISEeqUljHvJSMiln4jGJR0n6omL5/+/kR7+oh3OdiURIxp7RB7JLgnrZSISEz0uRfT+MtnCougxsXkVUiLHyZbFc/HGFAmkvKtfUMvmxfPeJpNRyNyB1T2iFiAVC0Mu4sn8Qgk2Cb9PwvtiYpo0UrOrt1FawkvwYgENUotLq3sk1Csejojn3JcST0Tjm5pzX4xNH/c30MPjAA5ryDZ6VykAeVy8YyYjSdHjVEkJHXwxAVVYLCe/+KqSXkhCFRb/fWkJl5apSBIKkbpJeU+AFCK54gVaNAKR+OrHxUzi7/gJ5mqwqBY5Li2eW1yda0DQvHr7JLTie0GKHCNmreLnNmaWElWIE8kTP0aeJYPPtvrJTejE+5nemELILPK7JIyPJX0SMZE9I3VAwh5XPCk6LyiJ3jMBiOfST0VSkvLtS9k8TyRSJJvs633PBI8D1g7Pyc8g9jobUx4AsNcSlYnIQ0VJTRGRp5DGU20l8diraDyU2KssjHlo2qikmubcU8LaeGVt3HM4rGOvp8lbSeWhdFGWiQK6eY4oniBaU9hcm2jaiCxO3qp9mo97DueWp6yY5iWR5TYqTw6JBwDKiuhcFFDVjc5DdM4Ya2cAcOTT1M2RS1M3Rx6Np7KArZe6Up57Khdr434rw+/k53A4HA6bpNMbuzuSoTsrORwOh8PhrBEeB3A4HA6Hs33hccCa4Zv8DNL38hCRZ5jEAwB9J2lcVB4q+k+N0nhOE3nOjNF4zo6TeCjpPzfBloeojajOPSWsjdf1evjjeZztSt+JQaY8lC7KMlFANs+dGiHxkMUTLK5NRG1EFidv1T69hcY9jwM425XuQQ+Jp2uIxtM9PE3iAYDuEToXBVR16xqi8hCd+xEaDyUdTpoydXiIPG4az/kpttqa8txTudY77nkcsHZ4uh4GYS2FDLB1Hx8vJkqPU0yU+qXYQZOKhspDSXFlAVseqrZmMDUSa+OVtXHP4bBOCVEKGSoPpYuyTBSQzXNUcQBjHkrI2posTt6ifZqPew7nlqeUKPVLKVGKjNLCbBIPtYsCqvKUFlF5qM4Ze+lRKojS41TkEHmI0v6U57PV1qVWuvJQ9SPWxv1Wht/JzyBZuUamPJQuyjJRkJUj/hKdW9KTLf5Sn82GqkzMeYjOGSWsjdd1e9LY2It+tuE395ytwU0fezfQxVwcwFi9WIsnKCGrG1Vb57F17qnYUuOexwGcbYrJqCXxmIk8VOUBAJOBzkUBa21N5mGsnQEgW0dTpmwtYx6ielFB1YcAun607nHP44A1wzf5GSSyFGXKAwCRMHtloiAajnHPJhFdJqobax4G25q1OWS9Hv54Hme7EiUae1QeShdlmSggi2+IPFs5DmAtltyqfXorjXseB3C2K5FonMSzTOSJRBMkHgCIxOhcFFDVbZnMw9a5p2Q5RlS3+Nb0UEF57snmkHWOex4HrB1ZOr0N30SwRkKhEMxmM+5QvgVKmeqG/z65XIZUSuS0yMQzLUnyyGVkZZLJxF2SyqRQSCqTGDIJHknlUYl/FyatrWnKI1MS1Qsga2tQnXsJ05EkT0J8EZHiSUfFN0kkeWKEmy3JpOghks8/I55EOoZnIz9FMBiEyWQCAMzNzeG17/4qVOr1P3ERj4Xxm//6M+Tm5q7bweEAl+KAI7iPnThgEz2ULqr1UgoyovVbpiTyqNUkHilI9khYU6SQplp3JayXkjxUayVVXLKJ3IrjPpGO4zk8yeMADrNcjAP2vOERKFUbu7M1LSFhslwmQ0pk/qHypJQSruMkeAAgLWH5luqiQJYSP0ZKeeQS9icl1UvKmiLBk9BK2AuS2M4xs7T9IDEieeLHSKqbjqaN5BLCGykedYBmfGgCdH1eIfK9ueQxJuEQKS4ZQb9OxiI495PP8DiAAJ6Tn0Fa72gk8jSQeACg9QiNi8pDRcttdTSew7U0nkM1NJ6D1SQeSloOVLHlIWojqnNPCWvjlbVxz+GwTuudTUx5KF2UZaKAbJ67vZ7EQxZPsLg2EbURWZy8Vfs0H/cczi3PjiY7iWdnI5GnoYTEAwA76+lcFFDVbWcjlYfmnO1irJ0BYF85TZn222k8+0ppPHsr2WprynNP5WJt3G9leLqeVXjsscfw2GOPIZm5G6jlSD00Si06n+9Dzc4KaI1aLAaWMNHrQuMBYXPWOeiBXC6DrUp4uVj3i/2obCmF3qRHeGEZI+cn0HxY2Fh2j3iRTCRhz7yMqvfEIOy1NjjayhBZimLg9MjKxef0uA/RcBRlmUWo//QoiiotMOdnIbYcR8/xQbTfJVz0zEzOYikYhqOtDAAweHYMBSW5yLGakYwn0flCP9rubIRMBvg9AQR9IThahWOHz08gx2pCXlEOUskULjzfh5bDdXC0lWHeG4TfNY/qHeUAgLGuKRhzDCgoEb4VO3+0F00Ha6DSqBCYCcE74Uft7koAwESvE1qDduX3XHiuF7W7HdAaNFiYW4RzaBr1e4XN26khL5RqBYoqhBejdr04gKq2MuiMWiwFwxjvdaFxv7BB6xr2Arj0grmeE0MobyiGwazHcjiGkQuTaDoonJvpMR8S8cTKC9v6T43CVin8jmg4hoEzoyub/jOTs1heiqKs3gYoFRg8Nw6rPQ/mgiwkogl0vzyMttuFY/2ueRhMupW/D1+YRF5hNnKsJiTjSXQdH0LLoRrIlUrMTQcx71uAo1k4j6PdTpjzjMgryl75Zr/5QBUUSgUCvgX4XPOobisFAIz3uWEw6WApFb4mP39sEA27K6DWqhCaW4Jnwo/adqF9s7L1KCrPh9UunJvO48OobSuFRq/GQiAM57AX9bsqALkczpEZKJQKFJUJ3u6To3A0FkNn1CC8EMFYnweNeyqEPjvuRzqVXnn5be+ZcZTVWGEw6xEJxzDUOYXmfQ6hvSfnEI/GYc+83FitVaKywQZTrgHR5Tj6z02g9aBwzmdc81hejKKsRjh28MIULCU5yM4zIh5LoufUKFoPVkMmA/Jt2TDnGlDRIIybkW4XcixZyLWYkEql0Xl8GC0HqyGXyzA3E8K8N7TS3mO9bmTlGJBfZEZlUzHOHxtE414HVGoFAv5FzDjnUJNp74l+D7QaBSyZ/n3hhQHU766AWqdGaHYR7jEf6nZVwNFix9TgNFQaJQrL8oU++9IgqtvKoDVohD7bNYHGfUKfdQ5NQyaXodgh1LX7+CAqmuwwmHTCHNE5heZMn3WPzghzRKbP9p4cht1hQVauUZgjzoyubJpMj/sQXY6hrL4YjtYy9J8eQVGFMEdEl2PoPTGE9jszc8SUMEdUZC4gLp8jEvEkuo71o+2OBjhay+B3z4vOEc2H66BUKTA3HcCsex7VO4T+Mto1iawcw8rPdjzbc805IhqP4Nnf4yr443mcm81VccAdDUIc8FwvanZVrsQBkz1ONBwUNlWdA27I5XLYMi8Z7T6WiQPMeoRDyxg5P47m24Rx6x6eRiqRQkldJg44Pgh7nQ1V7eWILkXRf2p4ZUNzemxGGOMX44CTQ7A5rDDlmxBbjqHnpQG0390MAPBN+rEYDKOqvRwAMHhmBAX2/EtxwPO9aL+rCZDJMOuaQ8AXgqNNOHakYwzZ1mzk2TJj/GgPWm5vQFV7OeanA/C75lC9U1jbxzonYMwxosAurB8dT3eh6XBdZowH4R33oXaPMM9P9ExBa9CulOnCs92o21sNzcU4YMCN+v3C3Dc1MC3EAZXCPNn1Qh+qdlRcigO6p9CYaW/X0DQAoDjT3j0vDaC8yS6sS5E4hjvGV+Iuz+gMEvHEStzVd3IYtsxcHAlHMXDqUtzlnfAjshRBWUMJZAoFBs6MwlqWj+wCE+LRBLqPD6I9czOFzzkHg1m38vehjnHk2XKQe3FOfXEArbfVQa5RC3HATAiOFmH+He1ywpx/MQ4Q+l3zwepMHBDKxAHCHDre64LBpLsUdz3fj4a9DiEOmF2EZ9yP2p1C+2blGFBUUQBrJmbofHEQtTvKhThgfgnOIS/q91QCqRScQ9NQKOQoysRE3ceH4Gi2Q5elRTi0jLEe50rc5R6dEeKATNzVe3IYZXU2GIwaLC9FMXRuDC0X23vch3gkjtJM/1ZrVahsscOcJ6xLfSdH0HZEGAszU7MILyyjrKZwpc9aSvORbTEjHo2j+8WBTOwqQ0FJLsz5Wai8uC51jCG3MAe5RdlCn32uF613NEKukGPOM485TwBVF9elC+Mw5WUhvyQPjrbyq/rszIQfNbuFOGa8exJ6oxaWMiHmOf9MN+r3V0Oj1yDkD8E97EXdvmpUtZdjss8JtUaFwkyfvdFzRFau8bpzxMUxJmWOqGguXWnva80RVe3lkucIhUpx3TniYpmuN0dEExE8d/RJvBIeB3BuNq+MA9obS6DR6NHR60SdwwKdRo2FpQjGnXNozqwtk555yGVASeaFlRf6Xagqy4dBp0F4OYbByRm0Zja8XNMBJFMplNqEeb170I1SWy5qygsQicbROzyNHZlNX89MENFYAuUlwrzeM+JBsTUb2Vk6ROMJdA64sbtJGNPTsyEshmOoKRfmr75RL6x5RuSaDUgkk+joc2FXkx0yyOANLWE+FEZNZq4bnPAh16xHfrYBqVQaZ/ucqLIL1zizwTB884uoKxfWi+EpP0wGLSyZ926c6p9CW40NKqUC86FleGZDaKgQ5sVR1yx0GhVqM7/nbJ8TjY5CaNVKhJYimJwOoMkhzIsTnnkolXIUF5gBAB0DLtSVWaDTqrC4HMOI04/WaqG9p7wBAIDdmi2095AbjpJ8GHVqLC/HMTA+g/a6YqG9Z4KIJ1Ioz7zYuHt4GiVW4XdEogn0jEyvbPp7/CEsR+KoLMmDPAn0jnhRWGBCrkmHWCKJC/1u7M5cS3lnF2HUa1b+3j82g4IcI/Ky9UgkU+joc2FHQwkUMhl884uYC4ZRm2nDwYkZ5Jj0KMgxIp0JBNrri6FUKDAXXIJ3dhH1mbVleMoPo16NgiKhzKd6p9BaXQSNSonAwjKcviCaKoU2NBm0KLGYYcsX7oo+2+9EQ4UVOo0KwaUIJjzzaKkqQtwgw/jMPBRyGez5QhueG3GhtrgABq0aS5EYBt1+tFdm+rcvgHQ6jTKL0IbnxzxwFOZCa9UgHIuj2zODPWVCe0/NBxFNJlGVL/RvjVKBOms+cvU6LMcTOO/0YH+F0Gau4AKWojE4MjFO57QXxaYs5On1iCWTOO1y40CpHTIARVlG5Op0qC8Q+mX3zAwsBgMsBgOS6TRennJiX2kJ5DIZfItLmFlaQqNVaO/+GT+ydVoUZhlRbynA8Ykp7CqxQa1QYDYchju0gObCzJ6EfxY5Cg1s2VkAgJdHp9BqL4JOpcR8eBmTs0G02gtRbyvAiG8OaqUC9hzh3Jwec6Gx2AK9WoVQJIqppVm0OYRr+gnvPGQyGUotQnt3DLtRXSz02aVIDANTPuyozrShL4hkKoXyzMt0L4x6UGnNgdmoxXI0jt4xL3bWCX3W7Q8hEkugtlQYY92j0ygpMAtzRCyBC8Me7GkQ2nt6dgGL4SiqSoQ27B2fgTXXiDyT0GfPDbiwu96O2tICzMwvIrCwjJqMdyAzRxRkG5BMpXGubwo7aouhUMivO0dcHPene689R8QiYZzD1fA4YO3wdD0S2Ox0PbYqK9yZzevrIiFdj81hhXtExCMxXY8Ul5R0PZLKtInpemyVFrhHZ1Y/SMLj/raKArjHfKsfJCH9gBSPlHQ9tvJ8uMf9osdtZroeSWWSMB1J8khIG2CryId7bHWPlHQ9tsoCuEdXP2ebna5H0jiTwGZ5rpeu53Xv3Pjjeb/+4fZ6PI9zY9jsdD22qkK4h6eZ8VC6JHk2MV2PpPhGQroeKfGElHQ9UtYUKUj2bGK6HpvDAvfI6m0kZb2UEidLSdcjqS9KiUsIxxkFt+K4v166Hh4HcFhhs9P1lBRmwzkd2LjHmg2nd3WPlHQ9JVYznN6g6HFS0vWUWMxwzoi7KJCSrkdK3aSk65HURhLWFCnnTEq6HrvFjCkJ7byZ6XrKcsyYmF+9TFLS9ZRlmzEREDlnEsIbKR4p6XpK88yYnF3ds5npeqSeeynpeqS4pKTrERv310vXw+OAtcPv5GeQyCJbLyYTXBGmPFQsE7XRMtHL5OjKw94L98jaiKytadqI6pxRwtp4Xa+Hf3PP2a7c7LF3I12sxQF09WIsDmBybSKKb6ni5EXepzfLxeMADmdtLEfYevkqiy/ypGKrtnWYsXYGgDDRC2qZ8xC9UJgKynNP5Vpvv+ZxwNrhOfkZpIwon1tZYzGJB8BKegBWPFSU1dtoPHVUniIaT20hiYeSi4/gM+MhaiOqc08Ja+OVtXHP4bBOGVE+VioPpYuyTBTQzXM0MRddPMHg2lRP1EZUcTJRzmvm+jQf9xzOLU+FXcJt0RKoLCHyFNN4qF0UkLURYx4HY+0MANUFNGWqyaPxVOcTeSxstTXluadysTbutzL8Tn4Oh8PhsEkqLXw28vMcDofD4XBuTXgcwOFwOBzO9oXHAWuGb/IzyMDpESLPKIkHAAbO0Lgoy0TB4NkxGs+5cRpPxwSRZ5LEQ8ngeZoyMechOveUUI2zm+5JQ1KuwFV/nsO5BRk4NcyUh9JFWSYKyOIbIg9ZPMHi2kQWSxLFyVu1T2+lcc/jAM42pY/ovRq9I0Se0Y2/o2vFNUbnooCqbr0E7zETPDTnrIfwnFHR6aIp04VpGk+nh8bT5WSrrSnPPZVr3eOexwFrhqfrYRBrWT5THgCwlrJXJgrI6kX0SKXVTvNCEAuRhxJLCVt1oyqPtZS9R89Ym0PW67mYg28jHw7nVsRaXsCUh9JFWSYKWItvqNYUvjZJ8GzVPr2Fxj2PAzjblcICE1OeonwaDwAU5dG5KKCqG3vnLIvEQ0lxNk2ZSkw0nmIzjceWw1ZbU557Ktd6xz2PA9YO3+RnkGyLmchDt4BSuSjLRIG5gGbSIvMQTaLZ+UYSDyVUZcrOI/IQlYfqnFHC2nhlbdxzOKxDFwfQeChdlGWigGyeI7oop1pTmFybiNqItb7IXp/m457DudXJMetJPLkmGk+OSUfioXZRQFWeXDIPW+eekjwDTZny9Ix5iOpFBeW5Z3EO4awOT9fDIHGiN1jHowkSD6WLqm5UJGI09UoQtQ9VeeJEHkqoyhSPJZnyUJ0zSujmkJvsSaeFz3rZyM9yODeRmz72bqCLtTiALr5hKw5gcm2iigMY64vs9ektNO55HMDZpsTjNNcpsQTRdRORh9pFAVV5qNqaNQ8lZHVLbk0PFZTn/qbPITwOWDOydHob1nqNhEIhmM1m3KF8C5Qy1c0uDi0y9h7mkCmIyiSn8ciURN+FqWg8MrWaxAMA0BC5iNoaqRSNJxIl0aTDyzSeWIzEAwBUU7ZMJiPxUJQnkY7jaPSnCAaDMJmEOz3n5ubwxj/4ClSq9d89EI+H8cvHP4LcXPbSV3FuLS7GAUdw39aLA7YyRPMcVawkkxOVh5A01QvJ0kTrN78s2ZYk0nE8hyeZiAOGhobw3ve+F36/H2azGd///vfR2Nh41XHf+c538KUvfQmpVAp33nknvv71r0OlUuHZZ5/FJz/5SSwuLkImk+F1r3sdvvSlL0FOFStzbgoX44A9b3gESpV2Q640a12BcGlKE61zKaLL75SSpjxJokvmuIGmPFHCS5tYPtGGsJHmS+F0nGaAqPw08brOQ3PONAG6+EaeIHJRhckEIWAyHsHZn35mS8QBG/k/ClhbYjgA2u9qYsojuK7u1DfTQ0X7HQ0knrYj9TSe2+toPIdrSDyUtB2oovEcJPIQtRHVuaek/U6i8XqzPWmCD4dzC9J+dzNTHkoXZZkoIKsXY7EbZQxIBWt9iDUPFVtq3N+EOOCDH/wg/viP/xiDg4P4q7/6Kzz44INXHTM2Noa//uu/xrFjxzA8PAyv14t/+7d/AwDk5OTgxz/+MXp7e3H27FkcP34cP/jBD9ZeEM62Zldz6Zb0AMDuJjuZi4I9DTTl2VtH49lXTeM5UM5WOwPAIWsZjaeIpj8eKGXrnFGxu5GuPLuJxse6y3QLxgHr/T8q+CY/h8PhcDgcDofD4XC2NTMzMzhz5gze/e53AwDe8pa3YGpqCsPDw1cc9/jjj+ONb3wjCgsLIZPJ8Cd/8if40Y9+BABob29HZWUlAECr1aKtrQ3j4+ObWg8Oh8PhcDhrhyIOWO//UcE3+RnENzXLlEdwzTHlocLnpCmP30XlmafxuAMkHkr800Eaj4fIQ9RGVOeeEqp+7XMSzUXrLI8snd7wZ60MDQ3hwIEDqKmpwe7du9HT03PN477zne+guroaDocDDz30EOJx4RHVZ599Fnv27EFDQwMaGxvxiU98AimqNFScbQObcQB7ZaKArF5U8+UWbWeAvbqx5qFiK417ijggGo0iFApd8YlGr53WcWpqCkVFRVBmUnXKZDKUlpZicnLyiuMmJydRVnbpjtTy8vKrjgGA6elpPP7443j961+/rvpzti8zswtb0gMA3tlFMhcF3jma8kzPE3kCNG3tCdGdMyrcYZoyuZdoPNMLbJ0zKmYIx9gM0fhYr+dWjAPW+39U8E1+BlmcX2LKQ+miLBMFCwGa8izMh2k8AbY8lCwEierGmofo3FNCNc4Wbva4TxF81gh/TJ/DAotEF4pUHkoXZZkooKsXW3ESa/EWwF4fYs1DxZYa9wRxwL/8y7/AbDZf8Xn00Uc3ViEJhEIhvOENb8AnPvEJ7Nq164b/Ps7WYmExsiU9ALCwROeiIERUnlCYyLNM8265INE76igJxmjaKBijaiO2zhkVVH2a0rVuzy0cB9ws+CY/g1S00OQYo/IILppcXFQeKiqJcgJWNJXQeBqLaTwNNhIPJRW1RTSeOiJPPU0bUZ17Siqaafp1JVH+zfWWZ7Pv5OeP6XNYoaKFJmcplYfSRVkmCsjqRTVfMhgDUsFaH2LNQ8VWGvcUccBHP/pRBIPBKz4PP/zwNX+f3W6Hx+NBIpEAAKTTaUxOTqK09MrxVFpaiomJiZW/j4+PX3HMwsIC7r33Xtx333342Mc+tq66c7Y3jrKCLekBgKrSfDIXBdV2mvLUFBN5img8dRa22hkA6rNp+lF9Dk3dagvYOmdUUI6xKqLxsV7PrRgHrPf/qOCb/BwOh8PZsvDH9DkcDofD2b5oNBqYTKYrPhqN5prHWiwW7NixA//1X/8FAPj5z3+OkpISVFVVXXHcW97yFvzyl7/E9PQ00uk0vvnNb+Id73gHAGBxcRH33nsv7r33XnzmM5+5sZXjcDgcDoezKpsdB6z3/6jgm/wMMnRujCmP4BpnykPFUMc4iWf4/IT4QVI8F2jycQ13TpF4KBnudrHlIWojqnNPCd14pZqLxtf3g+mNf/hj+pxbkaGzo0x5KF2UZaKArF6MxW6UMSAVrPUh1jxUbKlxTxAHrJVvfetb+Na3voWamhp86Utfwve+9z0AwAc+8AH88pe/BABUVlbi85//PA4ePIiqqioUFBTggx/8IADgK1/5Ck6dOoVf/OIXaGtrQ1tbG774xS+ur/6cbcvAqHdLegCgf2yGzEVB3zhNeXoniTxOGk/3NFvtDABdc9M0nlma/tjtZeucUUE5xvqJxse6PbdgHLDe/6NCSWrjkJBvyyHJpUrloXRRlomCPFsOFgny1+cVZdN4Cgk9weUNeyjJKzRhMbTxMuVZTSR1yyuiaSOqc09JfnEOFgneN0E1PtZdnnRa+KyXzON5n/70p6/45+t9c3/543lKpXLVx/NGRkZW/s4f0+dQk1+cS7PmEnkoXZRlooCsXozFSazFWwB7fYg1DxVbatwTxAFrpba2FidOnLjq37/97W9f8feHHnoIDz300FXHffrTn74q7uBw1kpBrhELSxvP882aBwAKcuhcFFhyjFgIb7w8lmwij9lAkuPdmmVAiLG8/FZ9FoLBjZepUJ9Fkpe/0GhE6DpPeK8FqnNGRQFRn6Z0rXvc34JxwEb+jwK+yb8Kjz32GB577DEkk0kAQMuRemiUWnQ+34eanRXQGrVYDCxhoteFxgM1AADnoAdyuQy2qkIAQPeL/ahsKYXepEd4YRkj5yfQfLgOAOAe8SKZSMJeK+QG7z0xCHutDW13NkKXpcPA6RG0HmkAAEyP+xANR1HWIOT/7j81jKJKK8z5WYgtx9BzfBDtdzUBAGYm/VgKhrHr3lbkFGZj8OwoCkrykGM1IxlPovOFPrTd2QiZTAa/O4CgLwRHm5B6YrhjAjlWM/Js2UglU7jwXB9abqtDzW4hx7TfPY/qHeUAgLHOKRhzDCiw5wIAOp7pQdOhWqg0SgRmQvBO+FGb+bmJHhe0Bg123duCnEIzLhztRe0eB7QGDRbmFuEcnEb9PuERGOfQNJQqJYoqLQCArmP9qGovh86oxVIwjPEe50p7u4aEb4OLq4X27jk+iPLGEhjMeiwvRTF8fgLNh2oBAJ6xGSRiSdgzueH7To2gaX81cq1mRMJRDJweRevt9QAA76QfkaUoyuqLAYUCg2fHYC3Nh7kgC4lYAt3Hh9B2RDjW75pDSU0hcqxmoQ3PTyCvKHulvbteGkTL4VrINSrMTQcxPxOCI/NugtGuKZjzs5BXlC1MQDIZTLkGKFQKBGZC8LnnUZ05N+O9LhhMOljKhXY5f2wQDbsroNaqEJpbgmfCj9p24disbD1i0TismXPTeXwYtW2l0OjVWAiE4Rz2on5XBaBSwjnqg0IhR1FZntBnT43B0WCDzqhBeCGKsX4PGncL59w9Pot0Oo3iCiGnWu/ZCZRVW2Ew6xFZjmGoy4nmPcI5n56aQzyWgN0hlFetUUKhkMOUY0A0Ekd/xyRa9zuEPusOYHkxgrJq4djBTicsxTnIzjMgHkui5/QYWg9UQSYD8ovMCPgXUVEvnMeRbhdyLCbkWrKQSqXReWIELQerIZfLMDcTwrw3BEezMG7Get3IyjEgv8iMyqZiTPR70LjXAZVagYB/ETPOOdS0CZu1E/0eaJVZsNiFdrnwfD/q91RCrVMjNLsI9+gM6nZXwtFSisVAGCqNCoXlQrt0vTiA6vZyaA0aoc92TqBxf/XKHCGTy1FcZRXa+6UBVDSXwmDSCXPEhcmVPivMEamVPtv78hBKqguRlWu8qs9Oj/sQXY6hrL4YjrYyeCf9KKqwCHNEJIae40Nov7NRaO+pWYRDy6jIvJNi8OwYCkpykWM1IxFPoutYP9ruaEBVWzlSqbQwR7SWrfTvHKsJeUU5SCVTOP9cL1oO10GhUmDeG4Tfddkc0SXMEbvuaUGO1YyOZ3vQdPCyOWLSj9pdlYjGIzj6FK5ClhY+60WWvvR4nhQufzzvwQcfXPXxvEOHDuFzn/scrFYrf0x/C3NVHHBHgxAHPNeLml2VK3HAZI8TDQeFcesccEMul8OWWZe6j2XiALMe4dAyRs6Po/k2Ydy6h6eRSqRQUpeJA44Pwl5nQ/tdTdBn6dB/ahitdwjjdnpsRhjjF+OAk0OwOaww5ZuEOOClAbTf3QwA8E36sRgMY/dr2oQ44MwICuz5l+KA53uFmEEmw6xrDgFfCI62cgDASMcYsq3ZyLMJY/zC0R603N6A2j3CfO13zaF6pzDPj3VOwJhjREFmnux4ugtNh+ug0qgQmAnCO+5D7R5h/Ez0TEFr0K6U6cKz3ajbWw3NxThgwI36/cLaPtXnglKtRJFDmCe7nu9F1Y5K6LIycUDXJBoPCbGUa9ADACiuEebJnhf7Ud5cKsQBixEMnxtD8+1CLOUZ8SIRS8BeL7z/pu/EIBoP1SKnMBvRpSj6Tw6h9U4hlvKO+xBZjKCsyQ5AhoHTI7CWFSDbYkI8lkD3sf6VuMvnnEVJrQ05hdkAhLvo8205yCnMRjKRROfzfWg90gCFSoFZ9zzmvUFUtWfa+/wEzAVZyC/ORTqdhkwmgykva2VO9TlnUXOxvbsmYTDrYcnkWu14phuNB2qg1qkR9C/AM+pFXaa9s3KNiEbiKCwX8t9eeK4XtbsvxV1TA2407K9BOpUW+qxSAdvF9j7WD0dbGfRZOoRDyxjtnETTxXVpeBqpVBolmfbuPT6I0oZiGLP1iCxGMHhmFC0XY9dRL2KROEozfVatU0GhlMOUb0I0HEXfiSG0XYxdJ3wILyyjvDGzLp0egaUsH9kWM+LR+KX2lslQYM/DvDeIyovr0rkx5BZlI7foUp9tvaMRcoUcc555zHkCqNpRAQAYvTABU54R+SV5cLSVY7x76oo+OzPhR81uoa+Pd09Cn6WDJZOL+vwz3ajfXw2NXoOQPwT3sBd1+6pR1V6OhflFqDUqFFYKbXij54isXKPQZ68xR1wcY1LmiIvvkrjeHFG1owKpZErSHKFQKTA/HbjmHHGxTNebI6KJCJ47+iReCUUcwOFshFfGAe2NJdBo9OjodaLOYYFOo8bCUgTjzjk0Z67pJz3zkMuAksIcAMCFfheqyvJh0GkQXo5hcHIGrfXCvOiaDiCZSqHUJlyzdQ+6UWrLxa4mO/Q6NXqHp7EjMy96ZoKIxhIoLxHW3N4hD4qt2TCbdIjFEugccGNXZkx7/SEshmPY11aO3GwD+ke8sOQbkWs2IJlMoqPXhV1NdkAmg39+EfOhMKoz15iDYzPINeuRn2tEKpXCuR4ndreUITfbgLnAEnxzi6jNzHUjEz5kGbWw5GUBAE73TKG1zga1UoG50DKmfSE0ZNaWUecsdBoV9reVIS9bj7M9TjRUFUKnUSK4GMGkJ4DmzLw46p2HSilHsUW4vu7od6G23AK9VoXFcAwjTj9aa4T2npoOAADsmTX4wqAbjpJ8GPVqLMUT6J+YwY5aYd13zgSRSKZQXiScm64RD1qri5Bn1mM5GkfPqBe7MufG4w8hHI3DUZyHlBLoHvfClpeF3Cw9YokkOobd2FsnnJvp+UWUW7ORb9IL52ZyBpZsI/JNeiSSKZwdcmFXTQnSejl8oSX4F8KoLxbWln63D7kGHSxmI9JIQwYZsvU6KBVyzC6EMR1YQKNdaMMhjx9GnQb5dqG9j49PYWdJETRKJebDy5gMBNFqE9owW6tFNJ5ESbZwHXRywokWmxU6lQqB5QjG5ubRXlyEhCmFkeAcFDI5yk1CG56cdqIxzwKjSo2FeBR9c37ssQptOBaaRzoNVJqFNjzjdaM6JxdmsxJLiTi65qaxzyK0y+RiANFUEtUmoc9qFEooZXLkanRYTiZwzu/CQauwlruWQlhMxFCTn4lb/NMoNpiQr9Mjlkzi1IwLBwtLIZMBRfos+JaX0JArHNs9OwOLzgCL3oBkKo0T3inss5dALpPBt7SEmaUlNFqE/t3v8yNbp0Wh0YiGggIMzs5id7ENKoUCs+Ew3KEFNBcK7T3on0V+vgZFOUJ7nxyeQmtZEbQqJeaXljHlD6KlrBB1xQUIhaNQqxQoyRX67OkRFxrtFujVKoSWo3AuzaK1SoidJrzzkMtksFuE9j4/5Ea1PR8GrRpLkRgGp3xor870WV8QyWQKZZn5pHPEg4ribJiMWkSiCfSOTmPHxT7rCyESS+BAqzDGekamUWIxw5wlzBEXhjzYnZlPvLMLWFyOwZGZT/rGZ2DNNSLXpEcymcK5ARd2N9hRW1aAVCqN+YUwakqF9h6c9CHXpEd+tgGpdBrnepxorysW+mwwDN/8Iuoy88nwlB8mgxb7W8qQZ9bjdM8U2mptUCkVmA8tw+MPoaHSilgkjLO4Gh4HrB1ZOr2Rr0W2B6FQCGazGXco3wKlTHXDf1/LbfXofKFvczwyaRmbWm6rQ+cL/QRlEvfIFERZpOTinubDteg6NrB6eZTi34U1H6xB10uDqx+kkuA5UI2u40Orl0etFvfsd6DrxIjocdCIuyQhpa33VKDrlEj6gFRK3LO3El0nRR77lnDXQvP+KnSdGF71mHRY/E5/Kec+HYuJeqQiZcpuOVyHzmMi40wmE/U0H65Dl4iHojyJdBxHoz9FMBhc2ZCfm5vDm17/z1Cp9KL+6xGPh/E/v/oYcnNzJf/MwMAAHnzwQczOzsJkMuF73/sempub8YEPfABvfOMb8cY3vhEA8O///u/40pe+BAA4cuQIvvnNb0KlUuGLX/wiPve5z6GxsXHF+da3vpXf1XeLczEOOIL7NicOuL0Bnc/3MuOhdFGWSRQJ81zL7fXofH7jsZIUj0wuoTybGQMCSKeILgPS4uu3pLaWsqYw1hc3tU9L4FYc94l0HM/hSSbiAA7nWlyMA/a84REoVdoNudISLnXbG4rR0bvxFKWSPOJLE9rri9HRJ16etIR1ToorRXQrakopXp4dtcU4N7B6eZISLpl3Vhfj7NDqnrhBvDy7KotxZnR1T1TClLantBinJsXPWSw/KS6TgjEuesjeAjtO+lZPmZuOiw+QfdYSvOx1rnqMyi8er+8pKcYp5+ptpPPQnDNNgG7bVZ5Y3bWjrhjn+iXMHxLGvpTxIRMPAdFeV4yOVcqUjEdw9qef4XEAAXyTXwKbvcm/qUjc5N9MNnOTXwpSNvklIWGTXwpSNvkls4mb/JKQsMkvCaJHE6Vs8kvybPImvxSkbPJLgaI8193kf90/bXxR//VfbKtFnXNj2OxNfg4RRPMcVawkZZN/s9nMTX5pHn5Zsh257iY/jwM4jLDZm/ybCuHSJGWTXwqbuckvBSmb/FKQsskvBSmb/FLZzE1+KUjZ5JeClE1+KUjZ5JfCZm7yS4YqTCYIAa+7yc/jgDXD2hLDAVZS9LDiEVz1THmoaL2tjsTTcriWxnOohsZzoJrEQ0nLvkoaTybFz4Y9B2naiOrcU3Ixhc+t7pGlNv7hcG5FLqbfYMVD6aIsEwVk9WIsdqOMAalgrQ+x5qFiK417Hgdwtis7Gku2pAcAdjTQuSjYWUdTnl01NJ49jmISz94yGg8l+y2l4gdJ8VjtJJ59drbOGRU76+nGGJVrvR4eB6wdnpOfQeREd7JTeShdlGWigLV60XnYu1tQTnS3v5zoDhEyD2N9GmCxP67TcxNetMPhsMBNH3s30MXanMlavVjzUMJa3VjzULGlxj2PAzjbFLrrJrY8AKBg7Kk2qvJQeajaWsFgxgYF0ROWZG1NVB7K8UEB1T4HQNlG6/TwOGDNsNUbRXj00Uexe/duZGVlwWKx4P7778fAwOr51L///e9DJpNd8dFqN/aI3Y1m1j3PlEdwBZjyUDHrCZB45qapPEEaj5fGQ8ncTIjG42XMQ3TuKZn1EM0hjHk4HB4H3BwPpYuyTBTMuudoPFTz5RZtZ4CwrRlrI9bamo97zlZmu8QB/vlFtjxzNB4A8M0vkbko8AVoyuMLEnlCNJ6ZRbbaGQC8yzT9yBtmq42ozhkVfsIx5icaH5Rl4qzOLbXJ//zzz+NDH/oQXn75ZTz11FOIx+N49atfjaWl1TuMyWSCx+NZ+UxMTGxSidfHPNEGLZWH0kVZJgrmZ4jqRbSBTebxLZB4KJn30yzqZB4fW+eMknmiLzBuuidN8OFsKbZLHBDwBpjyULooy0RBgCguofJs1XgLoGzrwJb0ULGlxj2PAzivYLvEAXOBMFueII2H2kUBVXlmQzQe/wKRZ4mtdgYAX4Row5jKE2brnFExR9QXKV3r9vA4YM3cUpv8v/vd7/Dggw+isbERra2t+P73v4/JyUmcPXt21Z+TyWQoLCxc+Vit1k0q8fqoai9nyiO4ypjyUFHVSlMeRwtNfjlHC01+OUcTW7kOAcDRYKPxNBJ5iNqI6txTUtVGNF5vskeGNGTpDXy246q+xdkucYCjvYIpD6WLskwUkNWrrZzEw2IMSAVrfYg1DxVbadzzOIDzSrZLHFBTYdmSHgCoLS8gc1FQW0ZTnjo7jae+mMbTYGWrnQGgKYdm3DXm0vTHBgtb54yKGqI+DQA1pTSu9ZaJxwFr55ba5H8lwaBwR5DYm5IXFxdRVlYGu92O++67Dz09PaseH41GEQqFrvhwOBwOZ5O5mINvIx/OlobHARwOh7OF4XEARwQeB3A4HM4WhscBa+aW3eRPpVL46Ec/ioMHD6Kpqem6x9XW1uK73/0unnzySfzXf/0XUqkUDhw4AKfTed2fefTRR2E2m1c+djvN3dVSGTlP8/gglYfSRVkmCkY6J0k8o11TbHl6XCQeSkb73DSeXiIPURtRnTNKRi4QjVfGPBzO5WztOGCcKQ+li7JMFJDVi2q+3KLxFsBeH2LNQwUf95ztwlaOA4bGZ7akBwAGJ3xkLgoGJ2nKM+Ck8fS7aTx9XrbaGQB65mn6Uc8cURv52DpnVFCOMarxwdq438oob3YB1suHPvQhdHd348UXX1z1uP3792P//v0rfz9w4ADq6+vxrW99C4888sg1f+bhhx/Gxz72sZW/h0KhTV3YzQVZCM1uPKe6JE86Jc2Vb0TIL3IHg4Q3uJsLTAjNrp5TPZ2UViZRJHxrZ8o1IEiQl9+UrUNQJN+oTMIbxc05eoTEcsVLqJc51yDazlJdkkiJnzNzjl68TImkuMesQ0jknQPpRELUY8rWiZ77dFK8PKYcvbhnk79BljTOpIyP/CwE/SJzSEpCf8zLWv2cXa8sqcxnvRBNJRw22cpxQHaBCSGxsbeJHkoXZZlEkTDPZednSVh3xdeC7DwDQjOB1TUS5iRzrh5B78ZfUkrloURSW0vxMNYXN7VPS2BLjXseB3BW4WbEARdTQGyItPg1YU6WHqFQZKMa5Jj0CC6s7pGSzSInS4+gSHkAQCbhuiDXqEMouLzqMfK4eJmoyNXrEAqsXp6UQryxc/U6BIMibSThnOUadQiERc69Urydc0xazMVXrxcApBU016kSqoY8rR7zMZEyxcT3lPL0BszHoqseo1wSL5FFp8fC0uoeVVi8fSwmLZbCq9dLEdu8/YBco/j8Idll0CMk0q/l4mEy8vR6LASu70ldb/uGxwFr5pa8k//DH/4wfvWrX+Ho0aMoKVlbXm2VSoX29nYMDw9f9xiNRgOTyXTFZzPJL179ccPN9lC68otzSDxU5NtoykPlySsi8hSaSTyU5FlpxhFV3fIKs0k8VOeeEtb69XrH/Yby71FchHGYZavHAXlEay6Vh9JFWSYKWKsXax5KWKsbax4qttK453EA53ps9TigINdI4slnzEPtoqAgx0Djyaapl8VM47Ea2WpnACjU0ZSpUE/U1llEHqJzTwVVn6Z0FeSuz8PjgLVzS23yp9NpfPjDH8b//M//4Nlnn0VFxdpf4pRMJtHV1YWioqIbUEIaqO76pbx7mK5MJBoy2GvrrdnOAF2Z6JqatXNPB2v9msEm4tyibJc4gL0Jk9DF2oTAWr1Y81DCWt1Y81DBxz1nC7Nd4gCy6wvWPNQuAhi7jN/S119pqr0Ospepbs22piwOY1svHAnI0izuUF2HP/3TP8UPf/hDPPnkk6itrV35d7PZDJ1OBwB4z3veg+LiYjz66KMAgC984QvYt28fqqqqEAgE8A//8A944okncPbsWTQ0NEj6vaFQCGazGXco3wKlTEVfsa2ChHQ9m4qE9DhSkCkUNB41Td+RabUkHgCARk3jkdG0tZR0PVJIR2geT0svE3kkpA+6ZZHwWK4YiXQcR+M/QzAYXLlTam5uDn9w599BpdSt2xtPLOPxZ/9K9GVsnFuHmx0HHMF9PA7gcDgcYhLpOJ7DkzwO4Ihys+OAva//ApSqjV2LpYmuUaWk69l0iMpEVbeUikaU0NB4YmYaT6SAbgsvlkdz/S3T0VzvppdoMorrPDQe/TRNW6sWb5lt1zUjJV2PGIl4BGd+8RkeBxDA2K7s6nzjG99AMBjEkSNHUFRUtPL5yU9+snLM5OQkPB7Pyt/n5+fx0EMPob6+Hq997WsRCoVw/PhxyQv6zaDltnqmPJSultvqSDxUtBymKU/z4Vrxg6R4DtbQePZXkXgoad5bSePZ56DxHKim8RyiOfeUUPVrMs96x306vfEPZ0uxbeKA22nKRuWhdFGWiQLW6sWahxLW6saah4otNe55HMB5BdslDmhrKCbxtDPmAYD2ejoXBe11NOXZUUPj2VVJ49ljZ6udAWBvAc37rfYVri1F1/XYXUbTRjur2Wprqj5N6Vr3uOdxwJq5pV68K+Whg+eee+6Kv3/5y1/Gl7/85RtUohuDQkVz5ziVh9JFWSYKqMqjVBK1D5mHve/vqMpE5yE694z1aYC98bpuD3/RDucV8Djg5ngoXVs1DtiqHkpYqxtrHiq21LjncQDnFWyXOEBJ9CS5gjEPQHcNRoVSQXNtyZxHzt5+gIqoTFR1I/MQnTMqKMtz0/s1jwPWDFu9kQMAmPcGmfJQuijLRMH8DFG9ZkIknoCPyrNA4qEk4F9ky0PU1lR9iBK6fr01xz2HwzosrrkslokC1urFmocS1urGmocKPu45nFufueDSlvQAwFyAzkXBXDBM4wnReGYXaDz+JRoPJb4Izbn3LRO1NVEbzRKdeyqo+jSli7JMnNW5pe7k3y74nLNMeShdPucciYcK3xRNeajq5XMRedwBEg8lPk+AxkNUN597nsbjpPFQQtavb/b4SKch28gjdtvw8TzO1sA35WfKQ+miLBMFrNWLNQ8lrNWNNQ8VW2rc8ziAs02ZIbqpiTUPAMzM0rko8M7RlIfKMx2guVlveoGtdgYAT5imbp4lIk+IxuOdZ6utqfoipcu73nHP44A1wzf5V+Gxxx7DY489hmRSeJNEy5F6aJRadD7fh5qdFdAatVgMLGGi14XGA0IudeegB3K5DLaqQgBA94v9qGwphd6kR3hhGSPnJ9CcyXPtHvEimUjCXmsDAPSeGIS91oa2OxvR89IgBk6PoPWIkCtwetyHaDiKsgYh/1j/qWEUVVphzs9CbDmGnuODaL+rCQAwM+nHUjCMu//wMEbOT2Dw7CgKSvKQYzUjGU+i84U+tN3ZCJlMBr9rDkHfAhxtZQCA4Y5x5FjNyLPlIJVM4cJzvWi5rR41uytx5ncX4HfPo3pHBQBgrHMSxhwDCux5AICOZ3vRdKgWKo0SgZkQvBN+1O4W8rBP9LigNWhw4P6dGDk/gQtHe1G7xwGtQYOFuUU4B6dRv0/IIz/V74ZSrURRpQUA0PVCP6ray6HL0mIpEMZ4jxONmdz1rqFpAEBxtdDePS8NoryxBIZsPZaXohjuGF9pb8/oDBLxxEp7950cxpG37YN7xItIOIqBU5fa2zvhR2QpgrKGEsjkcgycGYW1LB/ZBSbEYwl0vzSI9juEY33OOZQ3lmAp8+3kUMc48mw5yLWakUgk0XVsAK231UGuUWNuOoB5XwiO5lIAwGjXFMz5RuQV5UB4d7kMyUQSCqUCAV8IPtccqtvKAQDjvU4YzHpYKqwAgPPHBtGwuxJqrRKhuSV4JvyobRfOY1aOHsOdTljtwgtGOo8Po7a9FBqdGguBMJzDM6jfVQ6oVHCOzkChkKOoLF/os6dG4Wi0QWfQIrwYwVifB427hXPuHvcjnU6juKJA6LNnx1FWbYXBrEMkHMNQl3Ml9/701Bzi0QTsVcJ5VGuU8HtCMOXqEY3E0X9uEq0HhPz6M64AlhejKKsSvIMXpmApyUF2nhHxWBI9p0bRerAaMhmQb8vG6ad7UdEgnMeRbhdyLFnItZiQSqXReXwYLYdqIJfLMe8NYs4bhKNFaO+xHieycg3IL8qBo6kEP//602jaVwWlWomgfwEzzjlUZ8bCRL8bOqUZllKhf59/rg/1ex3Q6NQIzi7AMzKDuj0OOFpLcfQnL0OlVaGoXCh/57F+VO+ogM6gwWIgjPHuSTTuF94B4BzyQC6Tw1YlnMfulwZQ2VwKvUknzBEXJlfy/LtHvEgmU7DXFAnt/fIQ7DVFyMo1Cn329Chab6+/NEcsx1BWXwxHWxl+/e/PoqjCIswRkRh6jg+h/c5Gob2nZrEUDKOiSciLOHh2DAX2XORYMnPEsX603dGAqvZynPzNeQR9IThaM3PE+QnkWE3IK8rMEUd70XJbHRQqBeang5k5ojwzR0zBmGPAvje0Y+T8BDqe6bnmHBGNR3D0aVzNRvPobcNFnUPLVXHAHQ1CHPBcL2p2Va7EAZM9TjQcFMatc8ANuVwOW2Zd6j6WiQPMeoRDyxg5P47mzHtu3MPTSCVSKKnLxAHHB2Gvs6H9rib0vDiA/lPDaL1DGLfTYzPCGL8YB5wcgs1hhSnfJMQBLw2g/e5mAIBv0o/FYBives9tGO4Yx+CZERTY8y/FAc/3CjGDTIZZ1xwCvhAcmbVmpGMM2dbsS3HA0R603N6A2j0OnP7tefhdc6jeKczzY50TMOYYL8UBT3eh6XAdVBoVAjNBeMd9qN0jrO0TPVPQGrQ4+KbdGO4Yx4Vnu1G3txqai3HAgBv1+4W1farPJcQBDmGe7Hq+F1U7KoU4IBjGeNckGg8Ja7trUMi7XJyZJ3te7Ed5cykMZj2WFyIYPjeK5kw+cM+IF4lYAvZMXtC+E4M48o6DcA9PI7oURf/JIbTeKcRS3nGfEAc0CvPkwKlhWMsLkG0xIx6No/tY/6X2nppFebMdS4FMHHB2FPnFucgpzF5p79Y7GiFXyDHrnkfAG4CjXVhXR86PI7vAhLziXGHOksmQjCeFOdUbhG/Kj5pdwlo51jUJo1mPgtL8lfZuPFgLtU6NkD8E94gXdXuFtSYr14ihs6MorBDW4AtHe1C3p2qlvaf63Wi4GLv2uyFXyldi164X+uBoKxfWpWAYo52TaLoYuw5NI5VKoeRi7PrSAEobS2DMNiCyGMHgmVG0XIxdR72IReMorRf6rFqnhn/KD1O+CdFwFH0nhtB2MXad8CG8sIzyJmG9Hjw9AktZ/pXtnemzBfY8nPzVOVReXJfOjSG3KBu5RZf67MX2nvPMY84TQFUmdh29MAFTnhH5JXlwtJXj8X/8f1f02ZkJP2p2C+093j0JfZYOljJhbT//TDfq91dDo9cI7T3sRd2+alS1l+PZH74ItUaFwkqhz97oOSIr1yj02WvMEXe96xCGO8YlzREVmXj0enNE1Y4KnPzVOUlzhBAHBK45R+x/404Md4xfd46IJiJ47uiTuAoeB3BuMq+MA9qbSqDR6NHR40SdwwqdVoWFpSjGp2bRnBmnk+55yGUylBRlAwAu9LlQVZYPg16DpeUYhiZ8aM3Mi67pAJKpFEptwjVb96AbpbZc7Gq2o7Pfjd7haezIrEOemSCisQTKS4Q1t2fYg2JrNswmHWKxBDoH3NiVGdNefwiL4Rhec1s9Bsd96B/xwpJvRK7ZgGQyiY5eF3Y12QGZDP65RcyHwqguF9aLwbEZ5GbrkZ9jRCqVwrkeJ153RyNGJv2YCyzBN7eI2sxcNzLhQ5ZRC0teFgDgTPckWuuKoVIpMB8MY9oXQn1mbRmbmoVOq8Jtux0YHPfhXPcUGqoLodWoEFqMYNI9j6bMWj7unoNKKUexRWjDjj4naiss0GvVWAxHMTLlR2utsJZPTgs3XJUW5gjtPeCCw54Po16DxUQcA+MzK3nFXTNBxBMplNuEY7uHp/GqfdVweoOIRBPoGZnGzkyc5fGHsByJo7IkD0mVDD1jXtjys5CTpUc8kUTHkBt76oVz451bhKM4F4vLMQBA38QMLNlG5Jn1SCRTODfowq7aEqSy5PCFluBfCKO+WFhb+t0+5Bp0sJiNSKfTkMlkSCRTUCrkmF0IYzqwgEa70N5DHj+MOg3yyowAgOMTU9hZXASNUon55WVMBoJoLRLaO1urRbd3BiVm4SWmJyedaCmyQqdSIRCJYGx2Hu3FRUiYUhgJzkEhk6PcJLT3yWknGnMtMKrVWIhF0Tfnx55CoQ3HQwGk0mlUmoU2PON1ozo7D9lZSiwl4uiam8Y+i9Auk4sBRFNJVJuEPqtRKOEJLyBXo8NyMoFzfhcOWoW13LUUwmIihhqzUNcL/mkUG03I1+oRSyVxatqFgzY7ZJChyJCFZ6ZG0ZArtGH37AwsOgMsegOS6TROeKawt7wYcpkcvsUl+BaX0FAo9O9+rx85Oi2sJiPqC/Px3RMd2FVqg0qhwNxSGO7gAppsmfaemUW+RYWiXKF/nxqYQktFEbRqJeYXl+H0BdFcUYhaewF+e2oAapUCJflmoV0GXWgos0CvUSEUjmJqeBYt1UWZPhuATAbYrZk5YsCNqtJ8GHRqhCMxDE740Jbp305vEMlUCmVFQnt3DXlQVpQDk1GLSDSB3tFp7MjMJ25fCNFYAvccqMXghA89I9MotpiRnaVDNJ5A56AHuzPziXd2AYvhGByZGL5vbAbWXCNyM322o9+FXY121JYV4KXz45gPhVGTiYcGJ3zINeuRn21AKpVGR7cT7fXFQp8NhOGbX0RdJv4cnvQjy6DF4Z0VGBz34XT3FFrrbFArFZgLLWPaF0KDw4pYJIwzuAY8DlgzsrSUxHbbnFAoBLPZjDuUb4FSprrhv6/9riZ0PNPNjEeySyae/an9rkZ0PNNDUiZR5OJvr2+/sxEdz65eHpmEHITtdzSg42jv6h61eN9pu70e55/vW92j1Yp7Dtfg/LFB0eOgUYsfIwWZeFu3HazC+ZeGVz8oIf5q9rZD1Tj/4tCqx6QjEXHPbXU4/0L/6p5lcY+Uc59OJEQ9lEjp12SelPgSIjbuE+k4jsZ/hmAwCJNJCETn5ubwB4e+CLVSt6YyX04ssYzHX/w0cnNz1+3gcIBLccAR3Lc5ccDdzeh4uosZD6WLskwUsFYv1jyUsFY31jxU3IrjPpGO4zk8yeMADrNcjAP2vv4LUKrEr8VWIy3hGnVXcynOdE2u7hHXSPJIQbKHqExS6iaFlEpctLvRjtM9U6sek9CIe/bU23Gqb3VPzCzu2Vdtx8tDq3siBeLXXwfK7Dg+sboHAGJ54tffUpDpxK93D1nL8KJ3YtVj0kvi9yEfspXiRffqfUjnEffsr7DjxNjqbaSfFm/rvXV2nOxf3aNa3LxtVyl9mtIll9CFdjfZcbr7+p5EPIIzv/gMjwMI4Dn5GWSMYCGm9FC6xrpoJhsqxlaZaNbk6XGSeMZ7iTx9HhIPJeMD0zSefpq6jfe5SDxU554Ssn5N5WFs3HM4rLO14wC6MlHAWr1Y81DCWt1Y81DBxz2Hc+szMkmTKos1D7WLgpEpmrTEwy6aeg15aDwDPrbaGQD6Az4azzxN3QZniM4Z0bmngqpPU7qGCcvEWR2+yc8gBrOeKQ+li7JMFJDVy7T+bxev8JCVZ2N3mNwIDFk0ZSJra8Y8lLA2Xtftufh43kY+HM4tiJFo7FF5KF2UZaKAtXqx5qGEtbqx5qFiS417HgdwtilGPc3T1qx5qF0UkLWRTsOUx6Sh8VCSpSaqG5Eni6iNsojOGRUsjtd1e3gcsGb4Jj+DWDK5VlnxULou5jdnBYudpjxUnoJimseICopzSDyUFNiy2fIQtTXVuaeEtX697nGfBpDawGf7remcLUIB0ZpL5aF0UZaJAtbqxZqHEtbqxpqHii017nkcwNmmWPNNW9JD7aLAmnmfwEYpzKXxFGUTeUw0HkqK9TTn3mYgaiMzW+eeCqo+TekqXK+HxwFrhr94l8PhcDhMIkunIdvAt+8b+VkOh8PhcDg3Fx4HcDgcDoezfeFxwNrhL96VwGa/ePeWRcKLdzcVCS81koKUF+9K8kh48a4kj4QX70pmE1+8KwkJL96VgpQX70rySHjxriTPJr94d1OR8OJdMa734t237n8EasUGXrSTXMbPTvz1tnrRDufGsNkv3uVwOJztxPVevMvjAA4rbPaLdyV5iC6/SCEq02a+eFcKUl68KwUpL96VgpQX70plM1+8KwUpL96VgpQX70pByot3pbCZL97dbKS8eFeM6714l8cBa4exXVkOADQeqGHKQ+miLBMFjQeqSTwN+4k8ex00nt2VJB5KGnaW03h2VdB49tC0UcP+KhIPJVT9ms6zznHPc/BxtimNB2uZ8lC6KMtEAWv1Ys1DCWt1Y81DxZYa9zwO4GxTmmttJJ4WxjzULgpaqotIPK1VNJ72chrPzmIaDyW78otpPFaaPrTDTtNGbQ622rqlhq48VK51e3gcsGZ4uh4GUeto7q6m8lC61Dq27oBUa2nqpdHS1IuqPGote0Obqkx0Hqpzz9bLowDKfnSTx30qDcg2sDATPGXA4dwMtnYcwNacyVq9WPNQwlrdWPNQsaXGPY8DONsUjZroeocxD7WLAqq21qgY8yjZamcA0CpoykTloWojqnNGBWV5yPrjescZjwPWDFu9kQMACPoXmPJQuijLRAFZvWZpPKE5Ks8SiYeS0FyYyENTt9DcIomH6txTwtp4Xbdno9++b8Nv7jlbg5A/xJSH0kVZJgpYqxdrHkpYqxtrHiq21LjncQBnmxJcWKbxhNjyULsoCBC1dWCRxjO/RORZZqudAWAuSlOmuQhRG4WJPETnngqqPk3pWreHxwFrhm/yr4F0IoH0RnOPy8Xzu7uHp5EW+cZJJiGXn2fUK7lYJK50StwzMi3pOBJS4tmoPCNe0W/30hBPMuYenkY6KXJcXPycuQenkY6L5bMTzxPvHnBJy0ufpDkXMoWEth5yA5HoqsdIyV3vHnQhLeJBLC5enkGP6HGSyjPkET9uk79BltKvyTwU436z5gQO5xbBPUKzflN5KF2UZaKAtXqx5qGEtbqx5qGCj3sO58ahDiWgVG4s93jMJL4F43bPQ5YU2Q+QsC3h8cxDLuKR8o4Atzcg7WZaCce4pwOQiYX+RDn55XHxAnlcAdHjpGyaTTsDUEZF2lrCPWbTkwGoIiIehXgDeZdC0ETFj5Mlad4/mFKLe1yzYShjmlWPUYQl1G1uEdrY6mdFMy+qwUw4CI3ItoJyWbwPTU8FoBQ5Z/LE5u0HeNwBst8nxSUlJ7+YZzPbZ6vDc/IzSN0emhzfVB5KF2WZKKjbQ5MDv243lYcmT3ztTpq89ZTUtpfReHbQ1K2WKLc/1bmnhKxfk3nWOe55Dj7ONqVuL837MKg8lC7KMlHAWr1Y81DCWt1Y81CxpcY9jwM425QGojzxZB6ifPPULgoaicrT6Cgk8TSXE3nsNB5KWgtpytRaTONpKqPxNFay1dZUfZrSte5xz+OANcPv5OdwOBwOm/DH8zgcDofD2b7wOIDD4XA4nO0LjwPWDN/kZ5CJXidTHkoXZZkomOh10Xj6qDxuEs/kAI2HksnBaRrPgIfG00/TRlTnnhKyfk3mWee45y/a4WxTWFxzWSwTBazVizUPJazVjTUPFVtq3PM4gLNNGZuaZcoz7qTxULsoGHMRtbVrjsQz4iHyeGk8lAzP0pRp2EfjGZ2m8Yy52Wprqj5N6Vr3uOdxwJrh6XoYRKNfPU/ZZnsoXZRlokCjU7Pl0bNVHkro2lpF5OFtvWkexsY9h8M6rI1hShdrcyZr9WLNQwlrdWPNQwUf9xzOrY9WQ3MvJpVHo6a7N5TSRQFVeag8WiqPiq12BgCtkq26kbX1Fu3TlC7Wxv1Whm/yM0hheQFTHkoXZZkoKKxgq16FZfkkHmspjYcSqz2XxkNUNytRW7PWpwHCfn2zx0c6LbyUd92f7ffNPWdrUFhhYcpD6aIsEwWs1Ys1DyWs1Y01DxVbatzzOICzTSmymLekh9pFga2Apjy2AhOJpziPyJNL46GkxExTppJsGo+NqI2K8tlqa6o+Tela97jnccCa4V+ncDgcDodNeA4+DofD4XC2LzwO4HA4HA5n+8LjgDUjS6e3Ya3XSCgUgtlsxhHcB6Vsg6lC5AoJh8iRSqZWPUYml5F4pELloiyTKDLxB1UklYeorWUSHk+T5JHweJrkdlbRPD4tU9C0dTqRIPEgFifxpKJRmvJsci64TR2vafHfI+ZJpOM4mvg5gsEgTCbhToi5uTm8tflTUCu0ayrz5cSSEfys62+Rm0vzFAln+0IaB0iAxTWXxTJRwFq9WPNQwlrdWPNQcSuO+0Q6jufwJI8DOMxyMQ44fNvfQKlcf58EgJhJwrWcXIaU2PWD+CWqJE9ayrWulPJIRFKZJNRNCmkJeSuklCelEi+QQi5DUsQT19N4YmYaj+CiOa8pCdsKCpkMSZHtR0VYQt0keLQS0uRLaSNNQHwNlOJRRDdvP2Czx6s8uXFPIh7BqV/+NY8DCOB38q/CY489hsceewzJpNBrW+5ogEapRedzvajZVQmtUYvFwBIme5xoOFgLAHAOuCGXy2GrLgQAdB/rR2VLKfRmPcKhZYx0TqH5cB0AwD3iRSqRREmtDQDQe2IQ9lobmg7VYvDMKPpPjaD1SAMAYHrch2g4irKGEgDAwJkRFFVaYc7PQmw5hp7jg2i/qwkAMDPpx1IwjNvfug+T/W4Mnh1FQUkecqxmJONJdL7Qh7Y7GyGTyeB3zSHoW4CjrQwAMNwxjhyrGXm2HKSSKVx4rhctt9WjotmOC8/1wu+eR/WOCgDAWOckjDkGFNjzAAAdz3Sj6VAtVBoVAjNBeCf8qN3tAABM9DihNWqw+55WTPa7ceFoD2r3VEFr0GBhbhHOQQ/q91UDAKb63VCqFSiqtAIAul7oQ1V7BXRZWiwFwxjvnkJjpr1dQ8JLWIuriwAAPS8NoLzJDoNZj+XFKIY7xtF8m9DentEZJGIJ2OuE9u57eRiH3rwbs+55RJaiGDg1gtY7hPb2jvsRWYqirLEYkMkwcGYU1tJ8ZFtMiEcT6H5pAO13NgIAfM45FFUWIBET+snQuXHkF+dcau9j/Wi9vR4KtQqzngDmZ4KoahXae6RzEub8LOTbcpBOpxFdjkGpUkKpUmB+Jgifcx41O8qF9u5xwmDSwVIuPPJ8/vk+NOx1QK1VIzS3AM+YH7U7hXOj0akwOeBZSW3T+eIAaneWQ6PTYGF+Cc6hadTvcQBKJZzDXigUchRlUrN0vzwMR1MJdEYtwgsRjPW60LhXOI/uMR/SqTSKHUIZek+Noqy2CMYcPSLhGIYuTKJ5f5XQZydnEY8mYK8WzmM6ncbCfBimXAOikTj6z4yj9ZBwzmec81hejKA0c+zQ+QlYSnJhzs9CIpZA98vDaDtcC8hkMOcZcP6FAVQ0lqy0Ya7VjByrGalUCp0vDqLlcC3kCjnmp4OY8wbhaC0V2rB7Clm5RuTbclBaU4Rf/tuzaDpQDaVaiaBvATNTs6jOtPdErwtajRyWTBueP9qL+n1V0OjUCPoX4Bn1om5PFUrrbHjxiTNQa1Qr6W06X+hHzc4KaA0aLAbCmOhxovGAUFfn4DTkchlsVUJdu18cQGVzKfRmHcKhCEYuTKD5cO3KHJFMpGCvLcrMEUOw1xYhK9co9NnTo2g9Ui+095gP0eUYyhqKUVpnw+9/cAxFlZbMHBHPzBGNmTliFkvBMCqa7QCAwbNjKCjJvWyO6EfbnY0oq7fh3DM9CPpCl80RE5k5IluYI472oOW2eihUCsxPB645R+x8VTMm+93XnSOiiQiOPg0OhzluSBxwfhzNtwnj1j08jVQihZLMutR7fBD2OhuaDl6MA4bReocwbqfHZjJjXJj7+k8OweawwpRvEuKAlwbQfnczAMA36cdiMIwjb9uPiT4XBs+MoMCef2mMP98rxAwyGWZdcwj4QnC0lQMARjrGkG3NvhQHHO1By+0NqGwpxfmjPfC75lC9sxIAMNY5AWOO8VIc8HQXmg7XXRrj4z7U7hHWhImeKWgNWux5TRsm+ly48Gw36vZWQ3MxDhhwo35/DQBgqs8FpVqJIkcmDni+F1U7Ki/FAV2TaDwkrO2uwUwcUJOJA17sR3lzqRAHLEQwfG4UzbcLa7tnxCvEAfXFAIC+E4M4/Af74HfNIboURf/JIbTeKcRS3nEfIksRlDUK8+TAqWFYywuQbTEjHo2j+1j/pfaemoXNYUU8JnxRPXR2FPnFucgpzF5p79Y7GiFXyDHrnkfAG4CjXZgnR86PI7vAhLziXCCdRjQcg1KtFOZUbxC+KT9qdglr8FjXJIxmPQoy61LH011oPFgLtU6NkD8E94gXdXuFtUajU2Oi17mSJuXC0R7U7alaae+pfjcaDgjt7ex3Q66Uw1Yl9NmuF/rgaCuH3qRDOBjGaOckmi7GrkPTSKVSl2LXlwZQ2lgCY7YBkcUIBs+MouVi7DrqRSwaR2m90GfTqTQW5hZgyjchGo6i78QQ2i7GrhM+hBeWUd4krNeDp0dgKcu/sr0zfdacn4WOZ7pRmYmlhs+NIbcoG7lFl/rsxfae88xjzhNAVWZdGr0wAVOeEfkleSitK8aTX/vdFX12ZsKPmkzsOt49CX2WDpYyYW0//0w36vdXQ6PXCO097EXdvmqU1Rfj2C9OCnFAJna90XNEVq5R6LPXmCNue8teTPS5JM0RFc2Z9r7OHFHWUIJzT3dJmiNW4oBrzBG7Xt2CiT7XdeeIaCKC544+CQ6HNV4ZB7S22qHR6HHhwhRqawqh1amwuBjBxMQsGhuFtcU5NQeZXIbi4hwAQFeXE5WVBTAYNAiHY+ibmUVrZi13TQeQTKZQWixsQHUPuFFanIuWOhv6R7zoHZrGjiZhHfLMBBGJJlCRWXN7hz2wWbORbdIhGkugq9+NXS3CmPb6F7C4FMVdB2sw7pxD/4gXlrws5GbrkUikcL7XiZ3NdshkMszMLyEQCqM6c405ODaD3Gw98nOMSKVSONfjxH13N2PKE8BcYAm+uUXUZua6kQkfsoxaWPKyAABnuibRWl8MlVKB+WAY074Q6jNry9jULHRaFfa1l2PcOYdz3VNoqC6EVqNCaDGCSfc8mjJr+bh7DiqlHDZrNgDgfK8TtZUW6LRqLIajGJ30o6VOaO8pzzwAwF4ktHdnvwuVpfkw6jUIR2MYGJtBe2Ydcs0EEE+kUG4T2rtryIM79lbBP7eE5WgcvcPT2JlZ9z2+EJajcVSW5CGlBHpHvSjKNyHHpEM8kcT5ATd2Z46dmVtEcYEZ8Uw/6R+fQUGOEXlmPRLJFDr6XdhZX4K0Tg5fcAmzoTDq7MLaMuD0IceogyXbiDSASCwOlUIBpUKO2VAY3vlFNJQJ52bI5UeWToM8u7AJ+vLwFNrLiqBRKTG/tAznXBDNdqG9NUoFRmfmV9L2nB51oqnECp1ahWA4gjHfPNrKipAwpDE6Ow+FXI6yHCGlyukpF+otBTBq1FiMxtA/48cuu7AOTcwHkEqnUZErtPc5pwdV+bkwGjVYjsfR5Z3BnpLMuQkGEUsm4chssKbTaQQiEeTodIgkEuhwe7C/VGhDd2gBi7EY6q1CjNPl9sJmzkKeQY9YMokzk27sLy+BTCZDjl6LE2NO1GWO7fHMoCDLAIvRgGQqhZMTLuyuKoZcLoc/tARfaAn1JZn+7fIj26CFJduISmsOfnSsEzsqbVApFZhbCMMzv4DGUqF/D3tmkaNRovBi/+6bQrOjCBq1EsHFZUx5g2hyFKLCloujZ4ahVilX0jadG3ChvtwCnUaFxXAUE2OzaKkR2nDSMw+ZDLAXCm14fsCFqtJ8GHUaLC3HMDQxg7Y6oc86vcIcUXaxzw66UWrLhdmoFfrsyDR2NmTa0BdENJbAkT3VmHDNoWfYg2JrNrKzdIjGE+gccGN3Js6ang1hMRxDlV1ow75RL6x5RuSaDUgkk+joc2FXkx3lxXk40z2J+VAYNZl+ODA+g1yzHgU5RiRTKZzvcqKtoRhKheK6c8Se1jKMO+euO0dEI2Gc+iU4BPA7+SWw2Xfyt9/VhI5nulc9Rsqd/FI8UqFyUZZJFAl38rff1YiOZ3pWP0hKW9/ZiI5nV/dIuZO//Y4GdBztXd0j4U7+ttvrcf75PtHjNvNO/rbDNTh/bHDVY6Tcyd92Wx3Ov9C/+kES7uRvO1KP88+t3kZS7uSXcu43+05+Sf2ayiPhTn6xcX/9O/kfhlq+gW/uUxH8rOvRbfXNPefGsNl38rff3YyOp7uY8VC6KMtEAWv1Ys1DCWt1Y81Dxa047q9/Jz+PAzhssNl38u9qKcWZzsnVD5Jwt7sUj5Q7+Xc1l+JMl0h5JCLFtZl38u9uKsXp7tXLI+VO/t2NdpzumVr1GCl38u+ts+Nk/+oeKXfy76uy4+Xh1T2Ca/Pu5D9QasfxydXLJOVO/gMVdhwfW90j5U7+vTV2nBxc3SPlTv7dDXac7hWp1ybeyS+lT1O6pNzJLzbur38nP48D1gq/k59BFuYWmfJQuijLRAFr9SLzzC+ReChZCISJPDR1o2oj1vo0wGB/XK+H5+DjbFNu+ti7gS7W5kzW6sWahxLW6saah4otNe55HMDZpoQWIzSeBSIPUXmoXRQEqdqayBNcIvKE2WpnAAhGaMoUWGarjUJE54wKqj5N6Vr3+OBxwJrhm/wMMjXgZspD6aIsEwVTAx4azyCRZ2iaxOMk8lDiHJ6h8Qx5iTw0bUR17ikh69dknnWOe76oc7YpU/1Eay6Rh9JFWSYKWKsXax5KWKsbax4qttS453EAZ5sy6ZJwG7IUj5stD7WLAqryTGTSBm2UcS+NZ8xH46FkdI6obrNstTXVuaeCxfG6bg+PA9aMhAeYOJtNQyYnLSseShdlmSho2F9N49lH5NlbReKp3+Mg8VBSv6ucxrO7ksZD1EZU554Ssn5N5mFr3HM4rHMxVzorHkoXZZkoYK1erHkoYa1urHmo4OOew7n1acq894QZTw2Nh9pFQTNReZoz7wjcKK2VNJ62MhoPJe02mjK1lxC1dQWNp7mKrbam6tOULtbG/VaG38nP4XA4HDZJpQCI50Fc/ec5HA6Hw+HckvA4gMPhcDic7QuPA9YM3+RnECeDqXF4uh4RD1W6HiKPc5jBdD0jROl6iOrG0/Vspoc/ps/hrAUnUYoMKg+li7JMFLBWL9Y8lLBWN9Y8VGypcc/jAM42hSxdD2Npf6hdFEzwdD2bBlW6nlGqdD0zROl6ptlqa6o+Teni6Xo2D56uh0HkSgWJR0HkoXRRlokChZJmCCgURB6qdiYqDyVbtY2YbGuqfk3mYWvcczisIycae1QeShdlmShgrV6seShhrW6seajg457DufVh7TpFIacbw5QuClhrIyqPUi4j8VCipGojGU3dFERttFX7NKWLtTbayvCWZhCbw8qUh9JFWSYKWKuXrdJC4imqoPFQUlSeT+QpoPEQtTVrfRpgsF+v13Pxm/uNfDicWxBbVSFTHkoXZZkoYK1erHkoYa1urHmo2FLjnscBnG1KcWH2lvRQuygosWYTecwkHnsBkScvm8RDSWk2Td3KcrNJPPZ8Gk+JhaZeVFD1aUrXusc9jwPWDN/kZ5j/HP4qnkr8GE8lfizp+N/HfoTfx36EHwz+6w0uGYfD4WwCqfTGPxzONuDV7z2Cp1I/w1Opn+EPP/vWm+bgcDgcUngcwOFI4lMffg1e/MXH8eIvPo72Rrvo8V/9wttXji8sMN3w8rU32vHS43+Jlx7/S7zzvt03/PdxOJwtAo8D1gzPyU9AfnEu/vCzb8WOu1uQZ8tFbDmGgC+EyT4nBs+M4L8eefzSwamkqK/r+Z7McZd1yFf8XBqrp79Ip9LofL4PaaJOLcUlk/C4U9exfpLyUNF1bED8IAlt2PVCv+hx6URC1NP5fK/4cRK+jex6vhfpmPjvQ1zCMRJIS3j8qvPZbqTEyiThxShdR7vF65aUMM6e6xH3EJ17pDf3hS9dL/SR/E4pHilzjNj8kb5On06nU0hvoB4b+VkORyp/+Nm34j2ffdvK38/+/gI+ee//veKY6h2V+PqZv7vi316reyfi0fg1nV0v9JGUjcpD6aIsEwWs1Ys1DyWs1Y01DxVbadzzOIBzK/De9xzCe997+Ip/SyZTCIWWMTTkxS/+5zROnRpd+T91SPz6q/flCagTq1/PxI2XtnJkl4fSKUCW+dHOLufKn6/gsuNlyTRkydXj+c7uKdFjBNl1/vmy64D5wNIVf78mVKlmJBT5Qp/zyva7VnEkXDJ39rhEj1OFJVxbdjqhSqx+nJTy9ASd0Ip4AEC1KO6SQkopfs563W4YkqsfJ5dQ5h6/E3qR/qgMi2rQ3eGEWuT3KSPi5enudEIp4rnmOLxBdHY7JfURmZR9pa4pKAjq1tU5teq5lcf5fgAV/E7+DZJjzcbXTj6K137gbhSWW6BSK2Ew61FcVYj9b9iFd//1H6zZ6WgrX1dZPnr7Z/HR2z+LR97+5YynbF2ea5eJxkVZJgocrUT1IvOU0nhaaDyUOFrE7yrZVA9VWxOde0pYG6+sjXsO50bSdlczLKVXpid77UN3rcmx3jjgRnkoXZRlooC1erHmoYS1urHmoYKPew7n5qNQyJGTY8CePZX42y++DQcOVK/p56uq1pZW9Ac/O4E//eQP8aef/CGGRr2XPEQpXKk8AGAy6shcFFSX09StuowmpWxNKZHHTuOhpLaEpkxUHqq2pupDVFCWh8U5hLM6/E7+DXL/n70GebZcAMC5pzvxy6//L5YXI7CWF6BuTxUO3LdnzU69aX0LX89LV96Vrs+iW0CpXJRlokBv0rLlIWtnmvJQojey1kZEHqJzTwlzbbReTyoNSbfgrPrzHM7molDI8Zr334X/+OxPAABavQZ3PHBoTY71xgE3ykPpoiwTBazVizUPJazVjTUPFVtq3PM4gHOLcfLkCP77h8dhNuvw3vccRlWVFXK5DG+6fyeOHx+S7NHr1Wv6vU5PAE5P4Kp/N6zRcz0MOhoPACgZexG3nqhuVG1EVh4t3TmjwqBhq25UHqpzRgVleaj69brnIh4HrBm+yb9BqtorVv78jY/9B8a7J1f+/ttvP4Ovf+R7K3//x2c/h9YjjQCAd1f8KbwTPgBXPur/D+97DBO9U1f9HlNeFj74j+/B/jfuglwux8u/Podv/sUPEPCFVo65mLt/etyHP6z6M4RDy3j1e27Hx7/7fwAAP/jC4wj6QnjrX7wB5oIsdL3Qh3/5P99GwBfCQ4++E3e+8yBUGhVO/fY8/vVD38bC/NKK++B9u/GuT70ZNocVprwspNNpeMd9ePGJU/jRo08guhy7orxv+OCr8JaPvg55thyMdU/iu5/+Me5+92G8+j23AwD+8u4voPOyR3ebDtbirX/xBtTvrYbBrMesaw4vPXka//23/4PFwBJuFOHgMlueEI1nichDydICW3Wj8lCde0rCIQnPJ26qZ51tlMbGXpaz/dZ0zk1mKRSGwaTHqx88gh987qdIp9O4/e0HYDDpV/7vWhx+yz688U/vQVV7BdQ6NUL+EF564jR++MWfY246cMWxbXc04QNfehcqmkvhd83h51/+FSJL0Wt6w8EwCssteOBTb8LOV7UipzAbS8EwLhztwX9+/qeY7HdJrls4SDQfEHmoYK1erHkoYa1urHmooCzPTW8jHgdwbjHmA0vo7nYCAOQyGT7/+bcAACyWK/PeV1YW4J0PHEBraylMJh2CwTBOnhrBf/zHi/D7F7CUWdfVaiXe9+BhHDxYA4vFhGQyhUAgjOFhL377Yh+OvSx8cfCpP38NXnNXEwDgzz79Y5zvFvYTwssxvO8dB/CGV7cgy6hF76AH//rtZ69Z9vZGO776f98BAPjNs93426/+duX//uXzbwcAeGaCeOsH/w0AkJ9rxEPvPITaSivy84ww6jUIL8cwND6Dx399DsdODV/z9yQuS0NkMmrxx+86jH07KpCXbUQ8kcTs/CL6R7144vcXcL7XKbXp181S+Nox1FpZfMV+yHpZYsxDyVKEpkyLVB6qtibqQ1QsLdOVh6pu6/bwOGDNsPU1qkQee+wxlJeXQ6vVYu/evTh16tSqx//sZz9DXV0dtFotmpub8Zvf/IasLMuXbVy+75F3oPFgHZSqS9+dvHLzWwqjnZNX/dvfP/03ePV7jyArxwiDWY+73nkIX/rdp6FSX/97mld67nrnIfzZV/8IheUF0Bm02POadjzy5Cfwqf/+M7zpz18Dc74J+iwdjrxtP/70Xx684md33NWM1tsbUFCSB41ODa1eg7KGErzrU2/GI7/8xBXHvvnPX4M/++ofweawQqNTo253Fb74q0+iZpfjmuW893134B+e/hvsf/1OZBeYoFIrUVhhwVs++jp85djnYcw2SGy5tTPadXVbbwXPWPfVXxTdbMa6aYI0qrqNMXbOKLnWHHJLetIp4T0N6/1swxx82wWW4oDLefHnJxGPJWCx52P3vW0AgNc9dDcA4OiPX7rmz3zgS+/C3/zsL9B2RxOM2QaoNSrkF+fhvg/di6+f/XsUXvbIbcP+GnzxN59C7e4qqLVq2ByF+LOvfQBv/ujrrumWyeX4+tm/w2s/cDesZQVQa1TIsZhx5O0H8NWTj6J2d5Xkut30+eAGwVq9WPNQwlrdWPNQQVmem95GPA7gXAdW44ArkF3KPe6fvZT4fM+eSnz9sQdx550NyMszQqVSID8/C697bRu+8fUHUVhoxuiocDPgn//5q/H2t+9DSUku1GoldDo1ioqycfhwLY7srxEtwmvubMYfPXAQBXlZ0GpU2NFciq/97QOwvuJLh/Vgzc/C6+5qRlWFBdkmPZRKBUxZOuxsLsOjn3wT7s3c3PhKQouXNvu+8JdvxP33tKGwwAyVSgG9Tg27LRevOlSP3S2bk+5zeNK/JT1DThoPJYNuorq5iNp6iq1zRsXwBF15qFzD4+v08Dhgzdxym/w/+clP8LGPfQyf/exnce7cObS2tuKee+7BzMzMNY8/fvw4HnjgAbz//e9HR0cH7r//ftx///3o7u4mKc+5Z7pW/nzgvt34l2OP4MnQD/DlFx7BH3zs9dDqNWt2Nh2uu+rfdEYtHnn7P+PvH/zayt37jtayVfP8Nh2qveLvxVWF+Mk//BJ/c/8/wOecXXHse90OfOvj/4m/fde/IpL5hu2Otx+44tHajqPd+NJ7voZPvf5L+Is7P4+/vv/vcfI35wAA7Xc0oSETZBjMejz4+UsvIPzlN36PT7/x73DsFydR3lByVRnzbDn48FcehEIhx1IojK995Ht4+LV/i999/zkAgL22GO975O2ibbZeXtlGN91zkMhzQDzo22ya9q8tF+V1PUR1I2tronNPSdOhq+eQm+thr404ty6sxQGXMz8TxMlfnQUAvOb9d6G8qRT1+4Q567fffuaq4+v2VOHtn7gfgHBTwLf+8j/w12/8EobPjwEA8opy8GePfWDl+A/+43uh1qgAAGef6sRn3vAovvfXP0J547XfVfKpH34EWTlGAMDP/umX+KtXP4J//6v/RDKRhD5Lh7/87p9Krtu1YpP1QOWhgrV6seahhLW6seahgrI8W7WNOLc2LMcBOdkGNDWV4ODBavzhuw+u/PuvftUBANBolPirT7wearUSiUQS3/7Oc/j4J36EH/34BAAgL8+Ij3zkHjQ3C9fNBzO5/KenA/js536Bj3/iR/j7f/g1/vf3XVhYjKxaltLiXLzxnlYAwouAv/PDl/CJL/wcPQNu2KzZG67r7PwSvvGD5/Gpv3sCH/mbn+DPPvNj/N9//Q3mg8JT+O/9g33X/LncbOGpRp1WhR1NwjvSBka9+Ku//QX+4pGf4R+++XscPTGISDS+4TJKobWumMTTVmsj8bQSedqqaTyUtFfSlKndQdRGNUTnjKgPUUFZntZ6GldrA1tttJW55dL1/PM//zMeeughvO997wMAfPOb38Svf/1rfPe738UnP/nJq47/yle+gnvvvRcf//jHAQCPPPIInnrqKXzta1/DN7/5zQ2X53ffeRbNh+tx97tvW/k3tUaFpkN1aDpUh9f/yT348J5PbjjlzL/8yb+hI/OFglKlwMf+XUjBc/C+3Xjysf+V5Og5PoBvP/xDAMDOV7Xgvg/dAwA4+uPjePzLvwYA3PnOQ9j3uh1QKBUoLC9YufNm6Nwo9r62HY0H65BjNV/1BEHNzkr0nRzCzle1QGsQcpQPnh3F1zLpis4+1Ynmg3UosOdd8XO3vWUf1JlcaMd+cQojFyYAAL//j+dw5K37oDVoccfbD+Brf/49pDfymA6Hw7n1SG8wBx+fM7YkrMUBr+S333kGh968F3tfvxOJuPBI+siFcQyeGbnq2DvfeXjlz7/8+u/w+D//CgCgUCvwqf/6CNRaNXbd04qsHCMUSvnKF+qxSAxffMeXsTC/iJO/Pgd7bfEVcQgAOFrLUVRhBQAMd4zhpSdOAwB6jg+i/9QwGg/UorzRjuodlRg6N0reDhwOh7NheBzAuQYsxwF79zqwd++lp9fn5pfwrW89i6NHhTS1u3ZVICdHeEr97NlxdHYKTyifODGMI7fXo6goG7t3VeLXvz4PAEgkhLtQFxejcLvnMTk5i3g8id/9rhNx4+pbOYf2VEEuF54meP7EIL7/k+MAgM4+J/7ne/8Hug3mI5/2hTAbWMLbXr8TjrICGPSald8HAHZbLvQ6NcLXyWyQTKUz1/cyBEPLcHrm4fTMI5lK44mnOzdUNg6Hs0XgccCauaU2+WOxGM6ePYuHH3545d/kcjnuvvtunDhx4po/c+LECXzsYx+74t/uuecePPHEEyRlSqVS+Lv3fBVPfu23uO2t+9F2RxMqW8uhUAgPSRRXFeJtH38jvvvpH0l2uoemr/q3/pOXXtTTf1l+u8JV3lLtHp5GQfGlTfX+05c2GBbmLz0yOHj20sV9yL+w8ueLaXIspfn4P//03lVfnmnMfCNfdFl5Li9nKpnCwNmRqzb5S6qLVv5874NHcO+DR67hNiDPlgO/a+66v3+9uIe9W9LjGqHxUOIavfbdNWv2ENXNxdg5o8Q9fPUcckt6UimkZRt4xG4bPp631WExDnglp393HjOTflhK83Hk7QcAXPsufgAovmwNvHydHz47Bs/oDMoaSiCXy2GrKrziwtk94r1iHR84PXzVJn9xzSV3VXsF/uXYI9csQ2l9saRN/mvFJuuBykMFa/VizUMJa3VjzUMFZXluehvxOIDzCm6FOOByss16lJfnr/y9pCR35c+v/ELgInK5bGXN/+1vL+Dd7z6Iqior/v3f3o9kMoUp5xxOnx7Ff//qDGbnr38jYVGheeXP/ZfF4kvhGKZc86hxWDdUt7e9YSf+/I/uXPWYLIPmqk3+pbDw91gsgadf7Mc9tzdgT1s5/vur70c8nsTYlB8vnR3Fj/7f6ZVjbyROzzyJZ+oV71Bat8dL5Jmh8VAy6Qsw5aFqa6o+RIVzmq4813qh97o87nV6eBywZm6pTX6/349kMgmr9coFyWq1or+//5o/Mz09fc3jp6evH2xGo1FEo5dyxYVCoesee5H+U8Mrm9rZFjP+/LEP4PBbhEfUqtorAeCKO9HlikuZksz5V+bES6VW74hSv4xKveJN0kuXvfTq8v+77ksxM3kEX/2e21Y2+HtODOInf/8kQnOL2P/6nXj7x98oHCq/OvMT5Z33WsPa0x5J4ZVtdNM9RJNQmsG3iFOVic5D09ZU554S5vr1ej38m3vOK2A5DrhIOp3G/37/KP7wb94quJZjePq/XpD884AQB6xlDd3Ieit1fRWLTaRC5aGCtXqx5qGEtbqx5qGCsjw3vY14HMB5BazHAb/730784z/+Bjt2lOPzn3szdDo1HnjHfnR3O3HixLVfRHst1Jl3/H33ey9gbNyHw4dqUVlpgc2WjfKyfJSX5WPHrgq8///7DyTXEWdfK25IXzbWLr+xwHydG/3+4LU7Vv783784iZPnx5FIJPGxP34VqsoLAACyy95LcOn3XOJvv/ZbXOidwv6dlaiw56PIYkZNpRU1lVbUVxXiL77487VWbc1QTRNkHqIpPMXg/Ee1P0TloWoj1pqacnuCqo3W7eFxwJq55XLybwaPPvoozGbzysduv3auWwBoPly/kp7mIoGZIJ76wfMrf7+4oX/5JntuYTYAYeHbcXfLFT9fco08bHV7Lr0cr37vpT9Pj13/7uiSy+7i2wh5tkt3HPzoS0/gxP87i56XBmAwXb3gu0cv3dVce9mLduUKOWp3Xn2ngnPIs/Ln/3zkcbxa/cBVnzeY3wvnoOeqn6WgpKaQLU81zTkrqaYpDyUlVRu7W2TFQ1Q3qvFBde4poasbWx4OZ7NYSxxwLX733WeRTApXacd+/vIV6//luC5bA2v3XHpvSc0uB2yZO+xSqRTcw9PwXLbeF1Var3gpfd2eq9954rps3bzwXA9eJX/rVZ/XG96FX//b05LqdK3YZD1QeahgrV6seShhrW6seaigLM9WbSMOR4yNxAGpVBpnzozhJz85ufJv73tQeNrO6bz0ZPrv/rcTd9716FWf17z2HzB32dN6R4/24QuPPIEH3/dveN3r/wnPPy+k/nGUF8BefOk6/ZV4poMrf66tunS9YtCrr/lzi0uX7prPuyzG2Luj4pr+/DzhnT+BUBjf+M8XcK5rEoNjMyjI/Pv1MOovpQlKJlP45VOdePhLT+AdH/o2XvOer6Kz3wUA2NNaDm3mPUQ3Ersth8RTWpTNlKfMSlMvSsosNGUi8xTSeKj6EBWlRXTlKaUaH8VstdFW5pa6kz8/Px8KhQJe75XpMbxeLwoLr73RVlhYuKbjAeDhhx++4pG+UCh03YX9tQ/djb2v24EXHn8Znc/3YNY9jxyrGQ88/OaVYwbPCN/au0cu3S3woX/9I/z2O89g3+t2wi4h8P3INz+I737qv6HWqvG+//vAyr8f/+UZ0Z/dKDOXvS38TR++F4lYAnV7qnDvH91x1bHnnu5CZCkCrUGLuj1V+JN/fA/OPnUBd73r8FWpegDg2C9O4v1ffAfUWjXe/vE3Ip0G+l4ehEavQWF5AVqPNEKjVeOTr/3bG1pHDofDIKk0IOPf3HMuwWIccC1mJv342oe/jZzCbBx7/OXrHnf0Ry/iTX/+WgDAfR+6F7PuObiGPHjXp9+y8r6aM/97YSU1T9/Lg6jfVwONTo1P/+ij+J+v/haO1jLc8Y6DV7lHLozDM+ZFUYUVrUca8YnvfxgvPH4CiXgSheUFqN1ThYP378Gb894nuV4cDoezqfA4gPMKbpU4AAD+54kzePvb90KnU6OqyopdOytw9uw45ueXkJNjwKtf1YyFhQjOnh2DXC5HodWMpqYSVDos+NrXfg8A+Oq//iGGhr3o7/fA71+AXqdGWdml9D8qpeK6v/+l08P4Pw/eDgC4fX8N3vu2/RgYmcabX7sDet3V+fg9MwEkkykoFHLsaC7FH7/rMMLLMbz7zXuv6ff6QrDbcpFt0uPdb96D4XEf3vr6nde98/9a/PTrD+G5lwcxPO6Df24ROWY9bBYhzZBcLoNKpdi0F/ByOBwG4XHAmrmlNvnVajV27tyJZ555Bvfffz8A4Q63Z555Bh/+8Iev+TP79+/HM888g49+9KMr//bUU09h//791/09Go0GGo309DBZOUa87qG78bqH7r7q/2Y98/iff/0tAOElvW/+6OuhUMhRvaMS/3979x4WVZ3/Afw9oqCpQK55YRW8omV4Vx6s3VrT1O1J3VwvZSm7Vuai6WP9tJui1SZltaW5RqXgpRS1IrXymqh5R3BBUARFQOUSKsh9Bvj+/iAmJmaYM/CdmXPg/Xoensc55zsfPufDOTMfv2fmnN6Dqy7jk37hGrzv7WJ8TuKxpFpxRGUllmx7yWRZanw6vv/c/HV+ASDx+CU8NNnydip14MujeOrVv6FlazcMGd0fQ0ZXffPg/LGLuP+BviZji/KLER68DS+8PwMA8MSL4/DEi+Ng0Jcj/eJ1eP/uTt+512/hk/nhmP/fZ+Ha0hUzlv691u//3+HEBm+DJQnHk60PcmScE5LinJQTR6aEU8q/olpnHEnbJq3Wkv72MiUcv6SqOIn1jSMqAfAafPQbtfYB5uwO3W91zIVTyYh4LxJTF02EWytXzPkw0GT9zczbWB30hfHxZ4s24b0DwWjh2hxDxwzE0DEDAQDXLt1AF9/aHxgIeXoV3t79Ktre3QajZzyE0TMeqvf2mOtNnBlHFrVtl9riyKS2bVNbHFlk5uP0GrEPoN/RUh9QUFCKvXvjMXHiEADAlKn+iF6Uivfe+x7Llz8BV9fmmPz34Zj89+Emz8vKykNCQtWn2T09W2PihCHAhNrxU9NzcTntF4u/P+3aLeza9z88/ugANHdphmenPwgAKC0zICe3AB3atzUZX1Ssx0/HLmL0n++Di0szzPh71aWHUzNy0cbMpf127otD0K/303vhmar+4nZ+MdKu3YRPl9of7qt2u8a3Gzvc446nJg43O+5kbCoKCkstxpElPumGlDhxkq48EJcsJ87/UuxzJYSGOJcqJ6dzVyTVSFKtZe1DssjMJ/6inFjxF+oZh32AzTR3uZ6FCxfi888/x4YNG3DhwgXMmTMHRUVF+Mc/qj6JNmPGDJMb8cyfPx979uzBBx98gIsXL2LZsmWIjo622ATYavOb2/HZok2I3nsO11OyUFJYCn2ZAddTsrBz7V4EDXsFt3+9oUf6xesIefpjXE/OhL7MgNT4dLw15QNEbTtuEtO7X5dav+flvyxDVMRxFOUXo+hOMQ5tPYZFY/4NQx1ntr3v+6PFdbb4JeMmPlkQhgunU1BaXIbrKVn4OGgdflx3yOz4b1b9iNXz1iPzSjb0pXokx1zBkgnvIaPGi01ZjZvo7Ak7hJdGLsfRb0/hVlYeyg3luJWVh4unU7D5319j9YvrpWyHOT73yqmR6uL0lRNHJp++cr6qLWvbfO6VlI+kv5lMPpKOfVlx6vtaJCpFg3+o8VFbH9BQX7zyJd6a8gH+F5WAovxiGPTlyL1xC9+t2YN/DVmErKu/Xabn/M8X8fpj7+DS2SvQlxmQdTUHny/ehK0h35qNbTCU44VB/4ddn+7DjctZ0JcZUHC7EKnx6dj16T783yPLFedprjepD1lxZFHbdqktjkxq2za1xZFFZj7OrhH7ADJHS33Ajq/PGC/fN3RId/Tq1RGnTl/GC3PCsG9fPHJy7sBgqEBeXjGSk7OwbfspLH8zEj4+VZPkX205jp+PXUJWVh5KSvQwGCqQmZmHnTtjMP+NCKv3vdq1Lw7hEceRe6sQZWUGxCVew4Il23Ddwo1C//PFQfx07CKKS/QoKCrFj4fOY+7rW82OjdgVjc++PIrMnHyUlOoRE5+O+cERuJVn+WbAAExOGHz25VGcik1Fdu4dlOnLUaYvR9q1m/gy8jSWfLCzzjiydO9i+ZJHNsWp49JJzojTw0tOHJl6dpKTU8/Okmok628maR+SpZvEfLqZuRqHI+OorQ+orKzEvHnz0LNnT/Tq1QuffPKJxbHJyckYMWIEfH19MWzYMCQkJCha161bN/Tp0wcDBw7EwIEDERERYVOOmvokPwBMnToVv/zyC5YuXYqsrCwMHDgQe/bsMd5MJz09Hc1q3AR2xIgR+Oqrr/DGG2/gtddeQ+/evREZGYn7779fSj7XU7Kw/f2d2P6+sjehqIjjiIowndTHjpPYtHy78eGgUX4AgGd6BJkM+/eT//ntQbPaX80b3XyayeM2nq2xb+Nh7Ktxf4Bqm97cgU1v7qi1fOWstVg5a22t5TnpuXhxxBu1lteMratxg55dofuxq8anGJu3cMHC0OcB/Hp94SumX5lMPHEJiSfkfGrYFm3uvktdcTzVFUemNh7q2raa17NuUBxJf3uZpG2byuIQAerrAzYt327yHl6X0c0mm11+ZMdJHKlxWZ9Bo/wQeyDe7NjYg/EIGra41vK94VG1lrXxbI3k6CtY9a/Prea2b0MU9m2oHaNmLBnU9nqgtu1SWxyZ1LZtaosji8x8GmuNSNvU1gds2PgzNmz82ey6GzduY/Sj79ZafvVqLkLe3W0x5uDBPgCAH3+Mw48/xpkdY2jz21TOO6t+xDu/Xj2gptZ3uWLdV8ew7qtjJstffOO3SSNR42OfdwpKsfT9XbXiLAiOQHRcusmyykqBjTtOYmPNyxLqgHlLa09IxSZk4MEnVgIAhvb3Ni7/KvI0voo8XWu8aFb7hr320uZ391esr7Zmvu1Qrzh3qSuOTG1bSdo2WXEk1UjWPiRLW4n5SNuv26hvf6yPzZs3IzExEZcuXUJ+fj4GDRqEv/zlL+jXr1+tsbNnz8bzzz+PwMBA7NixA4GBgThz5ozVdQAQERGBgQMH1itHzU3yA8DcuXMtnnmPioqqtWzy5MmYPNn8f6zVqFTS19JKi+R9vc2WWCOffAD9AvrgyNcnceNyFu7u6IkpLz+ODt5V1w+MPXgeBbcKrURxjNLCMnXFKZITp0RSHJlk5SQvjqTjTNLfXiZpryHOfi1ywtfzkpOTMXPmTOTm5sLDwwPh4eFm37TXrVuHkJAQVFZWYuTIkfjvf/+LFi1aWF1HcrAPcGwcmbFk5iSD2rZLbXFkUtu2qS2OLI3quOfX9MmCRt8HlMi5Dn1JqbriyI4lQ0mp3vogRXEk1VrSPQhkxZGpRC9p22TFkVVrSfuQLCVl8vJx+muIyvqAiIgIPPfcc3BxcUG7du0wdepUbNmyBW+//bbJuJycHERHR2Pfvqr7q0yaNAlz585FSkoK3N3dLa7r1atXg3PU3OV6moJL0VckxUmVEsfWWC7NXfD4C6Oxcv8SfHllDT458W/8eVLVNf1uZeVh1bx10vJqqEtn5dRIbXGSY+T97WVJjr0qJ46kbUs+e1VKHFl/M5nUtj/W97XIGV/Pqz6rfunSJSxevBiBgYG1xqSmpmLJkiU4evQoUlJSkJ2djc8++8zqOiKl5PUBcuLIjCUzJxnUtl1qiyOT2rZNbXFkaUzHvdq+pk/kKEmXsqTEuZiSbX2QkjiX5cSRHUuGi1dyrA9S4EKquuIkXpUTR6aEdDk5JaRJqpGkWsvah2S5eFlePrKO1/q+FsnoA8rKynDnzh2Tn7Ky+n1QMz09HT4+PsbH3bp1Q3p6eq1xGRkZ6Ny5M5o3r/pcvU6ng7e3N9LT0+tcV23GjBnw8/PDrFmz8Msvlu+9Yg4n+VWo/8P3yYnz0L1S4tgaK+XcVRz95hSy036BvlSP0uIyXE3IwLYPduGTBWHIVNGLYP+H+lof5Mg4f5YU509y4sjU/8E+cuJI2jZptZb0t5dJ1rHv9DhCVJ19r/ePbf+5rz7j/vTTTwOoOquekZGBlBTTm0bv2LED48ePR6dOnaDT6fDCCy9gy5YtVtcRKSWtD5AUR2YsmTnJoLbtUlscmdS2bWqLI0ujOu4d3AcQqcWAAV2lxBl0v5z7agySeK8PmbFkGHSfnHwGS7pP22BJ958b0kd9940b2ktOTkN7S6qRpFrL2odkkZmPrOO13q9FEvqAjz76CB4eHiY/K1asMPvrAgIC0L59e7M/GRkZDaiAckeOHEFcXBxiYmLQvn17zJw506bna/JyPY4mfm0Qy2EAHNArlpWXolxY+TqLgq+dKIojMSedqLp2XnLcZQRPXWl2TP+H75WWk3XWz2GVGeTUSFEcYf3agkri6ESFwjhKvqYl6XqHQmmtreSkZL9WFEdOjYSC/xwq+9s79uviso59JXEU1chKnOp1v49lgL5Br7kG6I1n7mtyc3ODm1vt6wLWdVa95lfn6jqDr/TsPmmLKvsAB8aRGUtmTjKobbvUFkcmtW2b2uLIosXjvhz26wOIZDD2AeWOuUxnWVkxysvrvsxVucH6VE5ZWTHKDXXHUfDfOEVxACj6r6WynOT8H1XJtulL5eSjKI6C1zN9aTEqrMSpUFBofWkxKvTW/2YVkqYDKisV5FRiPSdRbr1ISrZNp+DlX1Ecg/X/xyv52+usT09Io/R41Sn5f7yCWEq2zVqc6nX26AMWLFiA119/3WS5ubkAADhx4kSd8by9vZGWloaAgAAAwNWrV+Ht7V1rXNeuXZGZmYny8nI0b94cQgikp6fD29sb7u7uFtdV/w4AaNGiBRYsWABfX1+btlknlMzQNHHXrl1D165yzqYTEZF5GRkZ6NKl6iy/EAK3b99ucMyPP/4Yb775psmy4OBgLFu2rNbYs2fP4qmnnkJSUpJx2fDhwxESEoKRI0cal82bNw9eXl549dVXAQCJiYkYO3Ys0tPT61xH2sU+gIjI/uzRB9x9993Q6Rx3E09qnNgHEBHZn9r7gPDwcGzatAn79u0z3nh39+7d8PPzqzX24YcfRmBgoPHmuiEhIYiOjq5zXVFREQwGAzw9PQEAH374ISIjI3HkyBHFOfKT/Ap4eXkhIyMDbdu2tbhz3LlzB127dkVGRgbc3d0b9PuGDRtmcmdle8WxJWdH5aREY661muoMsNYy8lFCZp1l5aQkjqxaCyFQUFAALy8v4zKdTod27drVL/EaXnvtNbz00ksmyyydua/rjHtN3t7euHz5svFxzTP4da0j7WIf0HhfM9VWazXVGWCtZeSjhBrrrCSWFvoAIhmaeh/gyNcVJVjrhuejFGvd8HyUUGOdlcRqan3AM888gzNnzqB3797Q6XRYuHChcYJ/586d2LlzJ7744gsAQGhoKAIDA/HOO+/A3d0dYWFhxjiW1mVnZ2PSpEmoqKiAEAI9evTAxo0bbcqRk/wKNGvWzHg2yRp3d/cGH5QuLi5SJvqUxlGSs6NzUqIx1lqNdQZYaxn5KCGjzoA2a+3h4WFzfkpYujSPOR06dMDgwYOxefNmBAYG4uuvv0aXLl1q3eV+0qRJePDBB7Fs2TJ07NgRn376KaZNm2Z1HWkX+4DG+5qptlqrsc4Aay0jHyXUVGdbYqm5DyCSoan3Ac54XVGCtW54Pkqx1g3PRwk11dmWWE2lD3BxccGaNWvMrhs/fjzGjx9vfNynTx+Ll/+xtK5Hjx6IjY1tUI688a4KBQUFqSqOzFgyc5JBbdultjgyqW3b1BZHJrVtmxprZEloaChCQ0Ph6+uLkJAQ41n1Z599Fjt37gRQ9ea7fPlyPPDAA+jVqxfuuecezJ492+o6IqXUeOypMScZ1LZdaosjk9q2TW1xZOFxT6R9ajv21Pi6IovaaqS2ODKpbdvUFkcWNR6vaqtRY8Zr8kty584deHh4ID8/X+oZU3vSYs6ANvPWYs6ANvNmzo6j1byJ7EGLx4MWcwa0mbcWcwa0mTdzdhyt5k1kD1o8HrSYM6DNvLWYM6DNvJmz42g178aMn+SXxM3NDcHBwYovC6EGWswZ0GbeWswZ0GbezNlxtJo3kT1o8XjQYs6ANvPWYs6ANvNmzo6j1byJ7EGLx4MWcwa0mbcWcwa0mTdzdhyt5t2Y8ZP8REREREREREREREQaxU/yExERERERERERERFpFCf5iYiIiIiIiIiIiIg0ipP8REREREREREREREQaxUl+G6xZswbdunVDy5Yt4e/vj9OnT9c5fvv27ejbty9atmwJPz8//PDDDw7KtMqKFSswbNgwtG3bFh06dMDEiRORlJRU53PCw8Oh0+lMflq2bOmgjIFly5bV+v19+/at8znOrnO3bt1q5azT6RAUFGR2vLNqfOTIETz++OPw8vKCTqdDZGSkyXohBJYuXYrOnTujVatWGDVqFJKTk63GtfW4kJWzwWDA4sWL4efnh9atW8PLywszZszAjRs36oxZn31MZt4AEBgYWCuHsWPHWo3rrFoDMLuP63Q6rFy50mJMR9SayJG01AdosQcA2AfYE/uAKvZ+b9JiD6Akb/YBROwDHIF9gP2wD6jCPqB+ebMP0AZO8isUERGBhQsXIjg4GDExMRgwYADGjBmDnJwcs+OPHz+OJ598ErNmzUJsbCwmTpyIiRMn4vz58w7L+fDhwwgKCsLJkyexf/9+GAwGPProoygqKqrzee7u7sjMzDT+pKWlOSjjKv369TP5/T///LPFsWqo85kzZ0zy3b9/PwBg8uTJFp/jjBoXFRVhwIABWLNmjdn17733HlatWoVPP/0Up06dQuvWrTFmzBiUlpZajGnrcSEz5+LiYsTExGDJkiWIiYnBN998g6SkJIwfP95qXFv2Mdl5Vxs7dqxJDlu2bKkzpjNrDcAk18zMTKxfvx46nQ6TJk2qM669a03kKFrrA7TaAwDsA+yFfcBv7PnepMUeQEne7AOoqWMf4DjsA+yDfcBv2AfYnjf7AI0QpMjw4cNFUFCQ8XFFRYXw8vISK1asMDt+ypQp4rHHHjNZ5u/vL2bPnm3XPOuSk5MjAIjDhw9bHBMWFiY8PDwcl9TvBAcHiwEDBiger8Y6z58/X/Ts2VNUVlaaXe/sGgshBADx7bffGh9XVlaKTp06iZUrVxqX5eXlCTc3N7FlyxaLcWw9LmTmbM7p06cFAJGWlmZxjK37WEOZy3vmzJliwoQJNsVRW60nTJggRo4cWecYR9eayJ603gdooQcQgn2Ao7APGCA3OQu02AMIwT6AyBz2AY7BPsAx2AcMkJucBewD2Ac4Gj/Jr4Ber8fZs2cxatQo47JmzZph1KhROHHihNnnnDhxwmQ8AIwZM8bieEfIz88HALRr167OcYWFhfDx8UHXrl0xYcIEJCQkOCI9o+TkZHh5eaFHjx6YPn060tPTLY5VW531ej02b96Mf/7zn9DpdBbHObvGv5eamoqsrCyTWnp4eMDf399iLetzXNhbfn4+dDodPD096xxnyz5mL1FRUejQoQP69OmDOXPm4ObNmxbHqq3W2dnZ+P777zFr1iyrY9VQa6KGagx9gFZ6AIB9gDOwD3Dse5OWewCAfQA1PewDHIt9gOOxD2AfYAv2AerFSX4FcnNzUVFRgY4dO5os79ixI7Kyssw+Jysry6bx9lZZWYkFCxbggQcewP33329xXJ8+fbB+/Xp899132Lx5MyorKzFixAhcu3bNIXn6+/sjPDwce/bswdq1a5Gamoo//elPKCgoMDtebXWOjIxEXl4eAgMDLY5xdo3Nqa6XLbWsz3FhT6WlpVi8eDGefPJJuLu7Wxxn6z5mD2PHjsXGjRtx8OBBvPvuuzh8+DDGjRuHiooKs+PVVusNGzagbdu2eOKJJ+ocp4ZaE8mg9T5AKz0AwD7AWdgHOO69Ses9AMA+gJoe9gHsA5RiH8A+wBr2AewD7Km5sxMgxwgKCsL58+etXv8qICAAAQEBxscjRozAvffei9DQULz11lv2ThPjxo0z/rt///7w9/eHj48Ptm3bpugsobOtW7cO48aNg5eXl8Uxzq5xY2QwGDBlyhQIIbB27do6x6phH5s2bZrx335+fujfvz969uyJqKgoPPLIIw7JoSHWr1+P6dOnW71BlBpqTUTa6QEA7b9usA9wDi31AVrvAQD2AURawz7AcdgHOAf7AMdiH6Be/CS/Au3bt4eLiwuys7NNlmdnZ6NTp05mn9OpUyebxtvT3LlzsXv3bhw6dAhdunSx6bktWrTAoEGDkJKSYqfs6ubp6QlfX1+Lv19NdU5LS8OBAwfw7LPP2vQ8Z9cYgLFettSyPseFPVS/oaelpWH//v11nrU3x9o+5gg9evRA+/btLeaglloDwNGjR5GUlGTzfg6oo9ZE9aHlPkDLPQDAPsBR2Ac4771JSz0AwD6Amib2AewDlGAfYP059sA+wLHYB6gbJ/kVcHV1xZAhQ3Dw4EHjssrKShw8eNDkDGxNAQEBJuMBYP/+/RbH24MQAnPnzsW3336Ln376Cd27d7c5RkVFBeLj49G5c2c7ZGhdYWEhLl++bPH3q6HO1cLCwtChQwc89thjNj3P2TUGgO7du6NTp04mtbxz5w5OnTplsZb1OS5kq35DT05OxoEDB/CHP/zB5hjW9jFHuHbtGm7evGkxBzXUutq6deswZMgQDBgwwObnqqHWRPWhxT6gMfQAAPsAR2Ef4Lz3Ji31AAD7AGqa2AewD1CCfQD7gPpgH0BSOfOuv1qydetW4ebmJsLDw0ViYqJ4/vnnhaenp8jKyhJCCPHMM8+IV155xTj+2LFjonnz5uL9998XFy5cEMHBwaJFixYiPj7eYTnPmTNHeHh4iKioKJGZmWn8KS4uNo75fd7Lly8Xe/fuFZcvXxZnz54V06ZNEy1bthQJCQkOyfmll14SUVFRIjU1VRw7dkyMGjVKtG/fXuTk5JjNVw11FqLq7ube3t5i8eLFtdappcYFBQUiNjZWxMbGCgDiww8/FLGxscY7z4eEhAhPT0/x3Xffibi4ODFhwgTRvXt3UVJSYowxcuRIsXr1auNja8eFPXPW6/Vi/PjxokuXLuLcuXMm+3hZWZnFnK3tY/bOu6CgQLz88svixIkTIjU1VRw4cEAMHjxY9O7dW5SWllrM25m1rpafny/uuususXbtWrMxnFFrIkfRWh+gxR5ACPYB9sQ+oIq935u02ANYy7sa+wBqytgHOAb7APthH1CFfYDteVdjH6B+nOS3werVq4W3t7dwdXUVw4cPFydPnjSue+ihh8TMmTNNxm/btk34+voKV1dX0a9fP/H99987NF8AZn/CwsIs5r1gwQLjNnbs2FH89a9/FTExMQ7LeerUqaJz587C1dVV/PGPfxRTp04VKSkpFvMVwvl1FkKIvXv3CgAiKSmp1jq11PjQoUNm94fq3CorK8WSJUtEx44dhZubm3jkkUdqbY+Pj48IDg42WVbXcWHPnFNTUy3u44cOHbKYs7V9zN55FxcXi0cffVTcc889okWLFsLHx0c899xztd6g1VTraqGhoaJVq1YiLy/PbAxn1JrIkbTUB2ixBxCCfYA9sQ+oYu/3Ji32ANbyrsY+gJo69gH2xz7AftgHVGEfYHve1dgHqJ9OCCHMfMCfiIiIiIiIiIiIiIhUjtfkJyIiIiIiIiIiIiLSKE7yExERERERERERERFpFCf5iYiIiIiIiIiIiIg0ipP8REREREREREREREQaxUl+IiIiIiIiIiIiIiKN4iQ/EREREREREREREZFGcZKfiIiIiIiIiIiIiEijOMlPRERERERERERERKRRnOQnIiIiIiIiIiIiItIoTvITEREREREREREREWkUJ/mJiIiIiIiIiIiIiDSKk/xERERERERERERERBrFSX6iRqCkpAR9+/ZF3759UVJSYlx+69YtdO7cGSNGjEBFRYUTMyQiIiJ7YR9ARETUdLEPICKAk/xEjUKrVq2wYcMGpKSk4PXXXzcuDwoKQn5+PsLDw+Hi4uLEDImIiMhe2AcQERE1XewDiAgAmjs7ASKSw9/fH4sWLcK7776Lv/3tb8jOzsbWrVvx0UcfwdfX19npERERkR2xDyAiImq62AcQkU4IIZydBBHJodfrMXToUBQWFqKwsBD33XcfDh06BJ1O5+zUiIiIyM7YBxARETVd7AOImjZO8hM1MtHR0Rg2bBhatmyJxMREdO/e3dkpERERkYOwDyAiImq62AcQNV28Jj9RI7N3714AQGlpKZKTk52cDRERETkS+wAiIqKmi30AUdPFT/ITNSJxcXEYNmwYpk+fjnPnziE3Nxfx8fHw8PBwdmpERERkZ+wDiIiImi72AURNGyf5iRoJg8EAf39/3L59G3FxcUhNTTW+wa9fv97Z6REREZEdsQ8gIiJqutgHEBEv10PUSLz99ts4d+4c1q9fj7Zt26J///5YunQpwsLC8MMPPzg7PSIiIrIj9gFERERNF/sAIuIn+YkagZiYGPj7+2POnDlYtWqVcXlFRQUCAgJw/fp1JCQkwNPT03lJEhERkV2wDyAiImq62AcQEcBJfiIiIiIiIiIiIiIizeLleoiIiIiIiIiIiIiINIqT/EREREREREREREREGsVJfiIiIiIiIiIiIiIijeIkPxERERERERERERGRRnGSn4iIiIiIiIiIiIhIozjJT0RERERERERERESkUZzkJyIiIiIiIiIiIiLSKE7yExERERERERERERFpFCf5iYiIiIiIiIiIiIg0ipP8REREREREREREREQaxUl+IiIiIiIiIiIiIiKN4iQ/EREREREREREREZFGcZKfiIiIiIiIiIiIiEij/h+Y20+IDKKCIAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1800x600 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FWHM_y = 4.926059872957138\n",
      "FWHM_x = 4.675778895005929 \n",
      "\n",
      "centroid y = 9.010992107833063\n",
      "centroid x = 9.01917912265807\n",
      "centroid y subim = 9.010992107833063\n",
      "centroid x subim = 9.01917912265807 \n",
      "\n",
      "amplitude = 0.10032285220380603\n",
      "theta = -38.446187060503874\n",
      "\n",
      "Mean FWHM: 4.801\n",
      "Flux in 1xFWHM aperture: 1.307\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "from vip_hci.fm import normalize_psf  # fm is the forward modeling subpackage, with various tools for the characterization of point sources and extended signals.\n",
    "\n",
    "psfn, flux, fwhm_naco = normalize_psf(psf, size=19, debug=True, full_output=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "4.800919383981533\n"
     ]
    }
   ],
   "source": [
    "print(fwhm_naco)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\"> \n",
    "    <b>Note: </b>\n",
    "<a class=\"anchor\" id=\"note1\"></a>                                       \n",
    "\n",
    "The `normalize_psf` function performs internally a fine centering of the PSF. The input PSF should nevertheless already be centered within a few pixel accuracy for the fine centering to work.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's visualize the normalized PSF with `hciplot.plot_frames`. Feel free to adapt the `backend` argument throughout the notebook: `backend='matplotlib'` (default) allows paper-quality figures with annotations which can be saved, while `backend='bokeh'` enables interactive visualization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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tP+bQZVrSxWs5Zx/1X0etCe4lSUOKEFlLahKtLVdPy+dTU0oVAFIHj+Lctp6mo4qPAYuISHA3R/4pnPxWwPDHgEVEJDiHLMHOS4JEROTpeA+LiIiE0FfyYTFgEREJrq/M1s6ARUQkOF4SJCIiIfCSIBERCUFWkfKek98SEdGPUnl5OZKTkxEbG4vExESUlZW1W27btm2IiYlBVFQUMjIy0Nz8r0kAvvzyS0yZMgUjR47EyJEj8fbbbytqAwMWEZHg7N8/h6V0USIzMxPLly/HmTNnsGbNGqSnp7cpU1VVhXXr1uHIkSOoqKhAbW0ttm7dCgC4du0aZs+ejY0bN+Lrr7/G6dOnce+99ypqAwMWEZHgFGcbVnjPq66uDiUlJVi0aBEAIC0tDWazuU0uwqKiIqSmpsJgMECSJKxYsQK7du0CALz++uu45557MHnyZACAt7c3AgICFJ0nAxYRkeDUphdpbGyEzWZzWRobG9vs32w2Izg4GD7fz3cpSRKMRiNMJpNLOZPJhPDwcOd6RESEs8xXX30FnU6HX/ziF4iPj8fixYvx3XffKTpPBiwiIsE5AMUZhx0A8vLyoNfrXZbc3NweaWNLSws+/PBDFBQU4PPPP8ewYcPwyCOPKNoHRwkSEQlO7XNYq1evxtq1a12235pfsFVYWBhqamrQ0tICHx8fyLIMk8kEo9HoUs5oNKKystK5Xl1d7SxjNBoxdepUDBs2DACwaNEil+S7XcEeFhGR4BxQcQ8LXtDpdPD393dZ2gtYgYGBSEhIwM6dOwEAe/bsQWhoKKKjo13KpaWlobi4GBaLBbIsIz8/H/PnzwcA/OpXv8Jnn30Gm80GANi3bx/i4uIUnSd7WNQhTfmCAEgtLRoqa3hGxKuf+roA5H6+6iv7avhKacmldaNJ/XEB4Ebb+xZdJbeozz8meWv8m1lDDjFJw/stN2nI1wYA7dwn6gpJBnCjnfao6GHJCssXFBQgPT0dzzzzDPz9/VFYWAgAWLZsGVJTU5GamorIyEjk5ORg0qRJAG4m5c3MzARws4f1xBNPIDk5GV5eXhg2bJhzBGFXSbLWX6U+wGazQa/XY6pPGnwkDT9makkavtRe6n/4pX7afvglDT/8kq+G91nHgKVYHwxYWt5vdwWsFrkJB2w7YbVa4e/vDwC4dOkSln76X+jn76doX022Gyic8EcMGTJEVVvcgT0sIiLBOVTMdMEEjkRE1Os4+S0REQmBAYuIiITAgEVEREJgwCIiIiFw0AUREQmhN57D8gQMWEREgusrlwQ5NRMREQnBowLWxx9/jFmzZiEkJASSJGHv3r3O15qbm7FmzRqMGTMGd9xxB0JCQrB48WKcP3++031u2LABkiS5LCNGjOjhMyEi6j1q04uIxqMCVkNDA+Li4rBly5Y2r127dg2nTp3CunXrcOrUKbz99tv49ttvkZqaetv9jh49GjU1Nc7l6NGjPdF8IiK3cMhqgpa7W62cR93DmjlzJmbOnNnua3q9Hh988IHLts2bN2PChAntTnN/Kx8fHxgMhm5tKxGRp5BlSfEgChEHXXhUD0spq9UKSZIwaNCgTsuVl5cjJCQEkZGRWLhwYZssmT/UXhZOIiJPpTx5o/Jh8J7Ao3pYSty4cQNr1qzBggULnLMWtycpKQk7duzA8OHDUVNTg5ycHNx77704ffo0Bg4c2G6d3Nxc5OTk9FTTe5WkJU2Hw9F9DVHKr21Onq5qCdRrOvT1kP6q6zb9RP3fgF4aJgAfUKdttvZ+59X/USY1XNdwYG3ZDxwDlM1Q7kLDn+vSdW3vt3RV3cElhzfQzn8VRwl6sObmZvzqV7+CLMt4+eWXOy07c+ZMPPTQQxg7dixSUlKwb98+XLlyBW+++WaHdbKzs2G1Wp2L2Wzu7lMgIuo2rZcElS6iEa6H1Rqszp49i4MHD3bau2rPoEGDEBsbi4qKig7L6HS6drNuEhF5or7y4LBQPazWYFVeXo4PP/wQP/3pTxXvo76+HpWVlQgODu6BFhIRUU/xqIBVX1+P0tJSlJaWAgCqqqpQWloKk8mE5uZm/PKXv0RJSQlee+012O12WCwWWCwWNDX963rytGnTsHnzZuf6o48+isOHD6O6uhrHjh3D3Llz4e3tjQULFvT26RER9QgZKi4JctCFNiUlJZg6dapzPSsrCwCwZMkSbNiwAcXFxQCA+Ph4l3offfQRpkyZAgCorKzEhQsXnK+dO3cOCxYswMWLFxEQEIDJkyfjxIkTCAgI6NmTISLqJX1l0IVHBawpU6ZAljt+mq2z11pVV1e7rO/evVtrs4iIPJos31yU1hGNRwUsIiJSjulFiIhICH1lpgsGLCIiwfEeFhERCaGv3MPyqGHtREREHWEPi4hIcLyHRUREQugrAYuXBImIBNc6l6CSRWnAKi8vR3JyMmJjY5GYmIiysrJ2y23btg0xMTGIiopCRkYGmptvpiE4dOgQ+vfvj/j4eOdy/bqymf7Zw+oNksa/C7w0/CXkpeHYWuoCkHzVp47QkiLk4pifqK4LAJdHa7gbHdiouqrjqvr3a1CZhjQbAIY2q08l46slDY3G9CJ2f/WTVMve6j/f3r7equsCgHeLXV1FR/u/Bb0x6CIzMxPLly9Heno6ioqKkJ6ejs8++8ylTFVVlTMrfFBQEGbPno2tW7di5cqVAIDhw4c7p95Tgz0sIiLB3QxYSucT7Pr+6+rqUFJSgkWLFgEA0tLSYDab22S9KCoqQmpqKgwGAyRJwooVK7Br165uO08GLCIiwanNh9VedvXGxrZXCcxmM4KDg+Hjc/OinCRJMBqNbbK3m0wmhIeHO9cjIiJcylRWViIhIQGJiYn4y1/+ovg8GbCIiAQnq1zy8vKg1+tdltzc3B5pY0JCAs6dO4dTp07hnXfeQX5+fqeJdNvDgEVEJDi1PazVq1e7ZFe3Wq3Izs5us/+wsDDU1NSgpaXl++PJMJlMMBqNLuWMRiPOnj3rXK+urnaW8ff3h15/8950aGgoFixYgCNHjig6TwYsIqI+SqfTwd/f32VpL9t6YGAgEhISsHPnTgDAnj17EBoaiujoaJdyaWlpKC4uhsVigSzLyM/Px/z58wEANTU1cHw/QOfq1at47733MG7cOEXtZcAiIhKd2muCChQUFKCgoACxsbHYtGkTCgsLAQDLli1z5iqMjIxETk4OJk2ahOjoaAQEBCAzMxPAzSA3ZswYxMXF4Z577sHPfvYzLF26VFEbJLkrSab6OJvNBr1ej6k+afCRVAzDdeOwdslbw/BbLXUBeN0xQHXdFmOg6rp9c1i7tidUhpZeU13Xt9am/sAah7W36NUP59c0rP1a0+0LdVb/Ur2qei2ORnxYvRlWqxX+/v4AgEuXLuHud/8A758o+77Z66+hZPajGDJkiKq2uAOfwyIiElxfmfyWAYuISHB9ZWomBiwiItHJ0s1FaR3BMGAREQmOlwSJiEgMKkb9KS7vATisnYiIhMAeFhGR4DjogoiIxNBHLgkyYCkheal6CFjS8IAiAG0P8GrIaaW53QP6q656bZj6h44v36Xtm3h/8peq684YrL7uR9aRquvua45XXRcABpr7qa7re0n9z4gsafsrX8vDv7KPm/LMAYDa8+6gHntYREQkBvawiIhIDNL3i9I6YvGoUYIff/wxZs2ahZCQEEiShL1797q8LssynnzySQQHB6N///6YPn06ysvLb7vfLVu2ICIiAn5+fkhKSsKnn37aQ2dAROQGvTD5rSfwqIDV0NCAuLg4bNmypd3Xn3vuOfz5z39Gfn4+PvnkE9xxxx1ISUnBjRs3OtznG2+8gaysLKxfvx6nTp1CXFwcUlJSUFdX11OnQUTUuxiwet/MmTOxceNGzJ07t81rsiwjLy8Pv//97zF79myMHTsWr776Ks6fP9+mJ3arP/3pT8jIyMDSpUsxatQo5OfnY8CAAdi+fXsPngkRUS9qnZpJ6SIYjwpYnamqqoLFYsH06dOd2/R6PZKSknD8+PF26zQ1NeHkyZMudby8vDB9+vQO6wBAY2MjbDaby0JERO4lTMCyWCwAgKCgIJftQUFBztd+6MKFC7Db7YrqAEBubi70er1zCQsL09h6IqKe0zqXoNJFNMIErN6UnZ0Nq9XqXMxms7ubRETUsT5yD0uYYe0GgwEAUFtbi+DgYOf22tpaxMfHt1tn6NCh8Pb2Rm1trcv22tpa5/7ao9PpoNPptDeaiKhXqLknxXtYPebOO++EwWDAgQMHnNtsNhs++eQTTJw4sd06/fr1w/jx413qOBwOHDhwoMM6RESikWR1i2g8qodVX1+PiooK53pVVRVKS0sxZMgQGI1GrF69Ghs3bkRMTAzuvPNOrFu3DiEhIZgzZ46zzrRp0zB37lysWrUKAJCVlYUlS5bg7rvvxoQJE5CXl4eGhgYsXbq0t0+PiKhncKaL3ldSUoKpU6c617OysgAAS5YswY4dO/DYY4+hoaEBy5cvx5UrVzB58mTs378ffn5+zjqVlZW4cOGCc33evHn47rvv8OSTT8JisSA+Ph779+9vMxCDiEhYzDjc+6ZMmQK5k6ErkiThqaeewlNPPdVhmerq6jbbVq1a5exxERH96PSRHpYw97CIiKhv86gelsfzktSlBdCSHgSA5Kvhv0lFOhQnL42pHzS0u/kODccOaFRfF8Ccn55UXffnAzqeJux2muUzquvu879LdV0AsOt8NdVXS7LbNdX3alZfX7ar/4xJjc2q6wIAmlTWd3RQr4/0sBiwiIhEx4BFRERC4KALIiISgZrnqkR8Dkv1DY5PPvmkO9tBRERq9cLUTOXl5UhOTkZsbCwSExNRVlbWbrlt27YhJiYGUVFRyMjIQHOz6303WZZx//33Y9CgQcoaAA0Ba+LEiYiNjcXTTz+Nf/zjH2p3Q0REAsjMzMTy5ctx5swZrFmzBunp6W3KVFVVYd26dThy5AgqKipQW1uLrVu3upR54YUXEBUVpaoNqgPWzp07ERMTg6effhoxMTGYNGkS8vPzcenSJbW7JCIiFXp6aqa6ujqUlJRg0aJFAIC0tDSYzWaXmYkAoKioCKmpqTAYDJAkCStWrMCuXbucr5eVlWHv3r14/PHHVZ2n6oD17//+73j//fdx/vx5vPjii5BlGb/5zW+cUyUVFRWhqalJ7e6JiKirVCZwbC/3X2Nj28dCzGYzgoOD4eNzc9iDJEkwGo0wmUwu5UwmE8LDw53rERERzjLNzc3IyMhAQUEBvFU+6qP5weGhQ4di1apVOHbsGMrLy7F27Vp88803mDdvHgwGA5YvX46jR49qPQwREXWzvLw8l9x/er0eubm5PXKsnJwcPPjggxg5cqTqfXTrTBf9+/fHgAED4OfnB1mWIUkS3n33Xdx3331ITEzEV1991Z2HIyIiQPWgi9WrV7vk/rNarcjOzm6z+7CwMNTU1KClpeXm4WQZJpMJRqPRpZzRaMTZs2ed69XV1c4yhw8fxksvvYSIiAhMnjwZNpsNERER+O6777p8mpoD1tWrV1FYWIjp06cjPDwcTzzxBCIiIlBUVASLxYLz58/jjTfeQF1dHWdIJyLqCSoDlk6ng7+/v8vSXi7AwMBAJCQkYOfOnQCAPXv2IDQ0FNHR0S7l0tLSUFxcDIvFAlmWkZ+fj/nz5wMAjhw5grNnz6K6uhpHjx6Fv78/qqurERAQ0OXTVP0c1rvvvovXXnsN7733Hm7cuIHExETk5eVh/vz5+OlPf+pS9pe//CUuX76MlStXqj0cERF1QIKK57AUHqOgoADp6el45pln4O/vj8LCQgDAsmXLkJqaitTUVERGRiInJweTJk0CcHNC88zMTIVH6pjqgDV37lyEhYXhP//zP7F48WIMHz680/JxcXFYuHCh2sMREVFHemFqpuHDh+P48eNttv/P//yPy3pGRgYyMjI63VdERASuXLmirAHQELAOHjyIKVOmdLn8hAkTMGHCBLWHIyKijnAuwc4pCVZERNRz+srUTJxLUAHJ2wuSpPz5AUljehFN6UnUpEPpLg6H6qrejeq/TQ6btlQZB62jVNfVlCLk0hjVdb2+66e6LgD41reor6w2VQYAya7+MwIA3l7uSeknNVzXVF++rq6+7Ojg2VYZKia/VdUEt2ICRyIiEgJ7WEREouM9LCIiEgHvYRERkRjYwyIiIhGwh0VERGJgD4uIiITAgEVERCLoK5cE+RwWEREJgQGLiIiEIFzAioiIgCRJbZaOUpfs2LGjTVk/P79ebjURUQ9SmQ9LNMLdw/rss89gt9ud66dPn8bPfvYzPPTQQx3W8ff3x7fffutcl9w5vx4RUTfrK/ewhAtYP8xOuWnTJkRFReG+++7rsI4kSTAYDD3dNCIi9xEwACkl3CXBWzU1NWHnzp349a9/3Wmvqb6+HuHh4QgLC8Ps2bNRVlbW6X4bGxths9lcFiIij9VHLgkKHbD27t2LK1euID09vcMyw4cPx/bt2/Huu+9i586dcDgcSE5Oxrlz5zqsk5ubC71e71zCwsJ6oPVERN2j9ZKg0kU0kizLAjb7ppSUFPTr1w//+7//2+U6zc3NGDlyJBYsWICnn3663TKNjY1obGx0rttsNoSFheH+AfPhIynPOyT5aLzy6quhvhvv10n9+6uu2xQRcPtCHfhunPrjAoB1lPrcUN7+HeQr6gK5Vv1goCFfavt//ukXV1XX9bZcVn9grT8/PhpyxWnIxaU2n5Wz/o3G2xdqR4vchIMNu2C1WuHv7w8AuHTpEu555i/w7n+Hon3ZrzfgxBO/wZAhQ1S1xR2Eu4fV6uzZs/jwww/x9ttvK6rn6+uLcePGoaKiosMyOp0OOp1OaxOJiHpFXxl0IewlwcLCQgQGBuLnP/+5onp2ux1ffvklgoODe6hlRETUE4QMWA6HA4WFhViyZAl8fnC5bfHixcjOznauP/XUU/j73/+Of/zjHzh16hQWLVqEs2fPYtmyZb3dbCKintFHBl0IeUnwww8/hMlkwq9//es2r5lMJnh5/SsOX758GRkZGbBYLBg8eDDGjx+PY8eOYdSoUb3ZZCKinsPJbz3XAw88gI7Gihw6dMhl/YUXXsALL7zQC60iInKPvnIPS8iARUREt2APi4iIhMCARUREQlDzIDADFhER9bo+0sMSclg7ERH1rvLyciQnJyM2NhaJiYkdzsm6bds2xMTEICoqChkZGWhubgYAHD9+HPHx8YiPj8fo0aORmZnpMqNQVzBgEREJrjfmEszMzMTy5ctx5swZrFmzpt05XKuqqrBu3TocOXIEFRUVqK2txdatWwEAcXFx+Oyzz1BaWoovv/wSdXV1+Mtf/qKoDQxYRESiU/ngcHuZKdrr9dTV1aGkpASLFi0CAKSlpcFsNreZ4q6oqAipqakwGAyQJAkrVqzArl27AAADBgyAr68vgJuZNq5fv644NyEDFhHRj4GKWS7y8vJcMlPo9Xrk5ua22bXZbEZwcLBzZiFJkmA0GmEymVzKmUwmhIeHO9cjIiJcylRXVyMuLg5Dhw6FXq/Hb37zG0WnyIBFRCQ4SeWyevVqWK1Wl+XWqe26W0REBP7v//4PFosFjY2Niicv5yhBBWS7A7Jk7/Xjakoc4aWhtqTt7xm1KRQAwNdiVV034P9UVwUADKhTP1N/i059ahOdTX26iwE111TXBQDvC+qTlMrf31RXxaFxqJrCm/YuWtSnkZGb1dcFANhV/o7IHdRTOUpQp9M505R0JiwsDDU1NWhpaYGPjw9kWYbJZILRaHQpZzQaUVlZ6Vyvrq5uUwYAfvKTn2D+/Pl47bXXMH/+/C43mT0sIiLB9fSgi8DAQCQkJGDnzp0AgD179iA0NBTR0dEu5dLS0lBcXAyLxQJZlpGfn+8MSBUVFc4Rg01NTXjnnXcwduxYRefJgEVEJLpemK29oKAABQUFiI2NxaZNm1BYWAgAWLZsGYqLiwEAkZGRyMnJwaRJkxAdHY2AgABkZmYCAA4ePIhx48YhLi4O48aNQ1BQENatW6eoDUJnHO4tNpsNer0eU3W/go/kq7i+5K0hKyo0Zix24yVBaGn3oIGqqzaH6NUfF0BDsJZLgurfb22XBLVlwPWxXFFdV75+Q/2BtV4SlNW/ZyJeEmyRm3DwxpttMg7f+/hf4OOnLONwy40GHNkkVsZh9rCIiEgIHHRBRCQ4phchIiIx9JG5BBmwiIgExx4WERGJgT0sIiISAXtYREQkBvawiIhICH0kYPE5LCIiEgJ7WEREguM9LCIiEkMfuSTIgKWE3a5qfj3NnwuHhvnStMxj6KXtirGkZZ63K1dVV+3XpCHdBQBfi/q5BOGt4T1rUZ+6RtJ4zmhs0lZfLS2fEQDQcN6yhrkENX0ne4AEQFI4LaymtEVuwoBFRCQ69rCIiEgEfeUellCjBDds2ABJklyWESNGdFrnrbfewogRI+Dn54cxY8Zg3759vdRaIqJe0gv5sDyBUAELAEaPHo2amhrncvTo0Q7LHjt2DAsWLMDDDz+Mzz//HHPmzMGcOXNw+vTpXmwxEVHP6umMw55CuIDl4+MDg8HgXIYOHdph2RdffBEzZszA7373O4wcORJPP/00EhISsHnz5l5sMRFRD2MPyzOVl5cjJCQEkZGRWLhwIUwmU4dljx8/junTp7tsS0lJwfHjx3u6mURE1M2EGnSRlJSEHTt2YPjw4aipqUFOTg7uvfdenD59GgMHtk2pbrFYEBQU5LItKCgIFoul0+M0NjaisbHRuW6z2brnBIiIekBfGXQhVMCaOXOm899jx45FUlISwsPD8eabb+Lhhx/utuPk5uYiJyen2/ZHRNSj+siwduEuCd5q0KBBiI2NRUVFRbuvGwwG1NbWumyrra2FwWDodL/Z2dmwWq3OxWw2d1ubiYi6GwddCKC+vh6VlZUIDg5u9/WJEyfiwIEDLts++OADTJw4sdP96nQ6+Pv7uyxERB5LltUtghEqYD366KM4fPgwqqurcezYMcydOxfe3t5YsGABAGDx4sXIzs52lv/tb3+L/fv3449//CO++eYbbNiwASUlJVi1apW7ToGIqNv1lR6WUPewzp07hwULFuDixYsICAjA5MmTceLECQQEBAAATCYTvG6Z/y45ORmvv/46fv/73+OJJ55ATEwM9u7di7vuustdp0BE1P36yD0soQLW7t27O3390KFDbbY99NBDeOihh3qoRUREHsABSErn4/Ws+Xu7RKhLgkRE1HcJ1cMSll192ggAkFWkNPlXZfX9fknSloBAdqhPbSI51Ldbdmh7v3Hthuqqko+GdC5aUsFo/L/ScmylaS1uJdu1/Zkva/lueViKEM0EvMSnFHtYRESC641BF+Xl5UhOTkZsbCwSExNRVlbWbrlt27YhJiYGUVFRyMjIQHPzzZxlBw8exIQJEzBq1CiMHj0ajz32GBwK/2hgwCIiEl0vDGvPzMzE8uXLcebMGaxZswbp6eltylRVVWHdunU4cuQIKioqUFtbi61btwIABg8ejN27d+Orr77CyZMncezYMbz66quK2sCARUQkOLU9rMbGRthsNpfl1mnpWtXV1aGkpASLFi0CAKSlpcFsNreZtKGoqAipqakwGAyQJAkrVqzArl27AADjxo1DZGQkAMDPzw/x8fGorq5WdJ4MWEREolM5W3teXh70er3Lkpub22b3ZrMZwcHB8PG5OexBkiQYjcY2k4+bTCaEh4c71yMiItqdoNxisaCoqAi/+MUvFJ0mB10QEQlO7eS3q1evxtq1a12263S6bmxZWzabDbNmzcJjjz2Gu+++W1FdBiwiItGpmWpJlp3T0N1OWFgYampq0NLSAh8fH8iyDJPJBKPR6FLOaDSisrLSuV5dXe1S5urVq5gxYwZmz56NrKwsZe0FLwkSEdFtBAYGIiEhATt37gQA7NmzB6GhoYiOjnYpl5aWhuLiYlgsFsiyjPz8fMyfPx/AzblfZ8yYgRkzZuD3v/+9qnYwYBERCa43hrUXFBSgoKAAsbGx2LRpEwoLCwEAy5YtQ3FxMQAgMjISOTk5mDRpEqKjoxEQEIDMzEwANzPAf/rpp3j77bcRHx+P+Ph4/Pd//7fC85QFnLK3l9lsNuj1ekz1SYOP5Nv7DdDy4LCX+gdKtT44rOlhVC0P0fpqvNLtpaHdoj44rOVnoKVF/WEbm9QfF4DcpKG+xgf63aFFbsLBG2/CarU6L+VdunQJP//3l+Dbb4CifTU3XcP7r/+/GDJkSE80tUfwHhYRkeCYcZiIiMTgkG8uSusIhgGLiEh0TC9CREQi4CVBIiISg8rnsETDgEVEJDgJKnpYPdKSnsWAJQJZQ94eh/oh8bLGi9xavhBanrbQ/EXU9OSChqHpWobEe2l8pFJLbigNw9o1Dy3XUF/TZ0xrrjiVxxawU9StGLCIiETHQRdERCQCSZYVZ37WkinaXRiwiIhE5/h+UVpHMAxYRESCYw+LiIjEwHtYREQkBD6HRUREIugrM10wHxYREQmBPSwiItHxkiAREYlActxclNYRjVCXBHNzc5GYmIiBAwciMDAQc+bMwbfffttpnR07dkCSJJfFz8+vl1pMRNQLWntYShfBCBWwDh8+jJUrV+LEiRP44IMP0NzcjAceeAANDQ2d1vP390dNTY1zOXv2bC+1mIioF8gqF8EIdUlw//79Lus7duxAYGAgTp48iX/7t3/rsJ4kSTAYDD3dPCIit5Cg4sFhASOWUD2sH7JarQCAIUOGdFquvr4e4eHhCAsLw+zZs1FWVtZp+cbGRthsNpeFiMhj9ZFLgkL1sG7lcDiwevVqTJo0CXfddVeH5YYPH47t27dj7NixsFqt+MMf/oDk5GSUlZUhNDS03Tq5ubnIycnpqab3Li2pSSRtf8/Idg3HduOXSfLSkDpCS7vdVRcAWjSk6dCQXkTWmF5ES4oQtx7XobJ+R8ftI3MJCtvDWrlyJU6fPo3du3d3Wm7ixIlYvHgx4uPjcd999+Htt99GQEAACgoKOqyTnZ0Nq9XqXMxmc3c3n4io27TOJah0EY2QPaxVq1bhvffew8cff9xhL6kjvr6+GDduHCoqKjoso9PpoNPptDaTiIi6kVA9LFmWsWrVKrzzzjs4ePAg7rzzTsX7sNvt+PLLLxEcHNwDLSQicgMZKu5hubvRygnVw1q5ciVef/11vPvuuxg4cCAsFgsAQK/Xo3///gCAxYsXY9iwYcjNzQUAPPXUU7jnnnsQHR2NK1eu4Pnnn8fZs2exbNkyt50HEVG34kwXnufll18GAEyZMsVle2FhIdLT0wEAJpMJXl7/6jhevnwZGRkZsFgsGDx4MMaPH49jx45h1KhRvdVsIqKexUEXnkeW5XaX1mAFAIcOHcKOHTuc6y+88ALOnj2LxsZGWCwWvP/++xg3blzvN56IqKeoGXChsIdVXl6O5ORkxMbGIjExscPHg7Zt24aYmBhERUUhIyMDzc3NAIDq6mpMmTIFer0e8fHxqk5TqIBFRETt6IXnsDIzM7F8+XKcOXMGa9ascekotKqqqsK6detw5MgRVFRUoLa2Flu3bgVwc8ahjRs34vXXX1d9mgxYRESi6+GAVVdXh5KSEixatAgAkJaWBrPZ3Ga0dVFREVJTU2EwGCBJElasWIFdu3YBuDnBw+TJk3HHHXeoPk2h7mEREVE7VA66aJ3V51btPdZjNpsRHBwMH5+bIUOSJBiNRphMJkRHRzvLmUwmhIeHO9cjIiJgMpkUnkzH2MMiIuqj8vLyoNfrXZbWEdaeiD0sIiLRyVA+6k8GVq9ejbVr17psbm/ShLCwMNTU1KClpQU+Pj6QZRkmkwlGo9GlnNFoRGVlpXO9urq6TRkt2MMiIhKc2qmZdDod/P39XZb2AlZgYCASEhKwc+dOAMCePXsQGhrqcjkQuHlvq7i4GBaLBbIsIz8/H/Pnz++282TAIiISXS+MEiwoKEBBQQFiY2OxadMmFBYWAgCWLVuG4uJiAEBkZCRycnIwadIkREdHIyAgAJmZmQCAa9euITQ0FA899BC++uorhIaGIjs7W1EbJNld0x0LxGazQa/XY6pPGnwkX3c3p/donK1dEw0zpkve3poOLfVT/38saclmreunvq6Xxv+rZg0zrt+4ob7udfV1AW0zxbuVytnaW+RmfNT8FqxWK/z9/QEAly5dwkMTctDPu7+ifTXZr+OtT9ffNj2TJ+E9LAXklhbIkoofUi+NP6Ba0l1ooSU1iVYO9T/AMrSlrECzlvdbww+whnQskrfGVDBafvibmt1zXEB9mg53U/vd6qgep2YiIiIhMGAREZEQGLCIiEgIDhmQFAYgAS+ncpQgEREJgT0sIiLRybLygRy8JEhERL2O97CIiEgIfeQeFgMWEZHwVPSwwIBFRES9jZcEiYhICAxYREQkBIcDivOLONw49ZpKfA6LiIiEwB4WEZHoeEmQiIiEwIBFRERCcMhQPEydz2FRuxza8jPJ0JZPSy235eHSSuMXUVOOJi1/tWpJoqg1gaOWG/B2DZ9vrT+a7szZpoGs8rw7yrcryw7ICt8LpeU9AQMWEZHo2MMiIiIhyFBxD6tHWtKjhBzWvmXLFkRERMDPzw9JSUn49NNPOy3/1ltvYcSIEfDz88OYMWOwb9++XmopEVEvkB03L+sqWQS8JChcwHrjjTeQlZWF9evX49SpU4iLi0NKSgrq6uraLX/s2DEsWLAADz/8MD7//HPMmTMHc+bMwenTp3u55UREpIVwAetPf/oTMjIysHTpUowaNQr5+fkYMGAAtm/f3m75F198ETNmzMDvfvc7jBw5Ek8//TQSEhKwefPmXm45EVEPaR3WrnQRjFABq6mpCSdPnsT06dOd27y8vDB9+nQcP3683TrHjx93KQ8AKSkpHZYHgMbGRthsNpeFiMhjORyQFS6cmqmHXbhwAXa7HUFBQS7bg4KCYLFY2q1jsVgUlQeA3Nxc6PV65xIWFqa98UREPYU9rL4rOzsbVqvVuZjNZnc3iYioYw5Z3SIYoYa1Dx06FN7e3qitrXXZXltbC4PB0G4dg8GgqDwA6HQ66HQ67Q0mIuoNsorZ2jlKsGf169cP48ePx4EDB5zbHA4HDhw4gIkTJ7ZbZ+LEiS7lAeCDDz7osDwRkWhkh6xqEY1QAQsAsrKy8Ne//hWvvPIKvv76azzyyCNoaGjA0qVLAQCLFy9Gdna2s/xvf/tb7N+/H3/84x/xzTffYMOGDSgpKcGqVavcdQpERN1LdqhbFCgvL0dycjJiY2ORmJiIsrKydstt27YNMTExiIqKQkZGBpqbm7v0WlcIF7DmzZuHP/zhD3jyyScRHx+P0tJS7N+/3zmwwmQyoaamxlk+OTkZr7/+OrZu3Yq4uDgUFRVh7969uOuuu9x1CkRE3ao3eliZmZlYvnw5zpw5gzVr1iA9Pb1NmaqqKqxbtw5HjhxBRUUFamtrsXXr1tu+1lWS3NFsiuRks9mg1+sxBbPhI/n2fgO8+uDkt5Ib/5bScN6St4b/K0nD+y3o5LeyXeN9FAHvwwDqJ79tkZtxyPE2rFYr/P39AQCXLl3Cg0N/DV9J2X33ZrkRb1/YjiFDhty2bF1dHaKjo3Hp0iX4+PhAlmUEBwfj6NGjiI6OdpZ7/vnnUVlZifz8fADAvn378Mwzz+Do0aOdvtZVQg26cJfWmN6CZvfMv+WmL6Uku3O2djcGLA3nLclaZubX8H7LGt8vLZ8xDees+e9lUQOWyvNukZvbrd8sNyoept6MJuczp7dqb9CZ2WxGcHAwfHxuhgxJkmA0GmEymVwClslkQnh4uHM9IiICJpPptq91FQNWF1y9ehUAcBRumoPQXd9JMX8LiH70rl69Cr1eDwAYPHgw/vfia6r28+KLL+Kpp55y2bZ+/Xps2LBBaxN7BANWF4SEhMBsNmPgwIGQ2rlsY7PZEBYWBrPZ7OymU8f4finH90yZH+v7Jcsyrl69ipCQEOc2SZK6dFmvPU888QT+67/+y2Vbe4/0hIWFoaamBi0tLc5LgiaTCUaj0aWc0WhEZWWlc726utpZprPXukwmzaxWqwxAtlqt7m6KEPh+Kcf3TBm+X93vvvvukwsLC2VZluW33npLHj9+fJsylZWVcnBwsFxTUyM7HA551qxZ8ksvvXTb17pKuFGCRETU+woKClBQUIDY2Fhs2rQJhYWFAIBly5ahuLgYABAZGYmcnBxMmjQJ0dHRCAgIQGZm5m1f6yqOEuwGraMIbx25Qx3j+6Uc3zNl+H79OLGH1Q10Oh3Wr1/P6Zy6iO+XcnzPlOH79ePEHhYREQmBPSwiIhICAxYREQmBAYuIiITAgEVEREJgwNJoy5YtiIiIgJ+fH5KSkvDpp5+6u0kea8OGDZAkyWUZMWKEu5vlMT7++GPMmjULISEhkCQJe/fudXldlmU8+eSTCA4ORv/+/TF9+nSUl5e7p7Ee4nbvWXp6epvP3IwZM9zTWNKMAUuDN954A1lZWVi/fj1OnTqFuLg4pKSkoK6uzt1N81ijR49GTU2Nc1EyU/OPXUNDA+Li4rBly5Z2X3/uuefw5z//Gfn5+fjkk09wxx13ICUlBTdu3OjllnqO271nADBjxgyXz9yuXbt6sYXUrbRM1dHXTZgwQV65cqVz3W63yyEhIXJubq4bW+W51q9fL8fFxbm7GUIAIL/zzjvOdYfDIRsMBvn55593brty5Yqs0+nkXbt2uaGFnueH75ksy/KSJUvk2bNnu6U91P3Yw1KpqakJJ0+exPTp053bvLy8MH36dBw/ftyNLfNs5eXlCAkJQWRkJBYuXKg4vUBfVVVVBYvF4vJ50+v1SEpK4uftNg4dOoTAwEAMHz4cjzzyCC5evOjuJpFKDFgqXbhwAXa73ZnpuFVQUBAsFoubWuXZkpKSsGPHDuzfvx8vv/wyqqqqcO+99zrTt1DHWj9T/LwpM2PGDLz66qs4cOAAnn32WRw+fBgzZ86EXUPSSXIfphehXjNz5kznv8eOHYukpCSEh4fjzTffxMMPP+zGltGP1fz5853/HjNmDMaOHYuoqCgcOnQI06ZNc2PLSA32sFQaOnQovL29UVtb67K9trYWBoPBTa0Sy6BBgxAbG4uKigp3N8XjtX6m+HnTJjIyEkOHDuVnTlAMWCr169cP48ePx4EDB5zbHA4HDhw4gIkTJ7qxZeKor69HZWUlgoOD3d0Uj3fnnXfCYDC4fN5sNhs++eQTft4UOHfuHC5evMjPnKB4SVCDrKwsLFmyBHfffTcmTJiAvLw8NDQ0YOnSpe5umkd69NFHMWvWLISHh+P8+fNYv349vL29sWDBAnc3zSPU19e7/OVfVVWF0tJSDBkyBEajEatXr8bGjRsRExODO++8E+vWrUNISAjmzJnjvka7WWfv2ZAhQ5CTk4O0tDQYDAZUVlbiscceQ3R0NFJSUtzYalLN3cMURffSSy/JRqNR7tevnzxhwgT5xIkT7m6Sx5o3b54cHBws9+vXTx42bJg8b948uaKiwt3N8hgfffSRDKDNsmTJElmWbw5tX7dunRwUFCTrdDp52rRp8rfffuveRrtZZ+/ZtWvX5AceeEAOCAiQfX195fDwcDkjI0O2WCzubjapxPQiREQkBN7DIiIiITBgERGREBiwiIhICAxYREQkBAYsIiISAgMWEREJgQGLiIiEwIBFRERCYMAiIiIhMGAREZEQGLCIiEgIDFhEPeT69esYMWIERowYgevXrzu3X7p0CcHBwUhOTmbmWyIFGLCIekj//v3xyiuvoKKiAmvXrnVuX7lyJaxWK3bs2AFvb283tpBILMyHRdSDkpKS8Nhjj+HZZ5/F3LlzUVtbi927dyMvLw+xsbHubh6RUJhehKiHNTU14e6770Z9fT3q6+sxatQofPTRR5Akyd1NIxIKAxZRLygpKUFiYiL8/Pzw1Vdf4c4773R3k4iEw3tYRL3gb3/7GwDgxo0bKC8vd3NriMTEHhZRD/viiy+QmJiIhQsXorS0FBcuXMCXX34JvV7v7qYRCYUBi6gHNTc3IykpCZcvX8YXX3yBqqoqZ/Davn27u5tHJBReEiTqQRs3bkRpaSm2b9+OgQMHYuzYsXjyySdRWFiIffv2ubt5REJhD4uoh5w6dQpJSUl45JFH8Oc//9m53W63Y+LEifjnP/+JsrIyDBo0yH2NJBIIAxYREQmBlwSJiEgIDFhERCQEBiwiIhICAxYREQmBAYuIiITAgEVEREJgwCIiIiEwYBERkRAYsIiISAgMWEREJAQGLCIiEgIDFhERCYEBi4iIhPD/A3US19luX1e3AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 400x400 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_frames(psfn, size_factor=4)#, backend='bokeh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's finally define the pixel scale for NACO (L' band), which we get from a dictionary stored in the `config` subpackage:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.02719 arcsec/px\n"
     ]
    }
   ],
   "source": [
    "from vip_hci.config import VLT_NACO  # config is a subpackage with configuration files and parameter/dictionary definition\n",
    "\n",
    "pxscale_naco = VLT_NACO['plsc']\n",
    "print(pxscale_naco, \"arcsec/px\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.2. PSF subtraction"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When loading the ADI cube above, we assumed all calibration and preprocessing steps were already performed. In particular, the star is assumed to be already centered in the images. If your data require additional calibration/preprocessing, check out tutorial `2. Pre-processing`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\"> \n",
    "    <b>Warning: </b>\n",
    "<a class=\"anchor\" id=\"note1\"></a>                                       \n",
    "\n",
    "VIP's convention regarding star centering is:\n",
    "\n",
    "- for **odd** number of pixels along the x and y dimensions: the star centroid should correspond to the central pixel of the image;\n",
    "- for **even** number of pixels: the star centroid should be located on coordinates (dim/2,dim/2) in 0-based indexing (i.e. on the top-right pixel of the 4 central pixels).\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2.1. median-ADI"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The most simple approach is to model the PSF with the median image of the ADI sequence, subtract it, then derotate and median-combine all residual images ([Marois et al. 2006](https://ui.adsabs.harvard.edu/abs/2006ApJ...641..556M/abstract)):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "Starting time: 2024-07-04 11:56:20\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "Median psf reference subtracted\n",
      "Done derotating and combining\n",
      "Running time:  0:00:02.456235\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n"
     ]
    }
   ],
   "source": [
    "from vip_hci.psfsub import median_sub\n",
    "\n",
    "fr_adi = median_sub(cube, angs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualize the final images:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_frames(fr_adi)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Strong residuals can be seen near the center of the image, with a faint potential point source in the south-west (bottom right) of the final image."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\"> \n",
    "    <b>Note: </b>\n",
    "<a class=\"anchor\" id=\"det1\"></a>                                       \n",
    "\n",
    "As per usual convention, north is up and east is left in all images shown in the tutorial. Note that for the images of some instruments, te x-axis may be flipped (i.e. east would be right instead of left). This is for example the case for Gemini/NICI or VLT/ERIS-NIX. Double-check your instrument manual.\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.2.2. Full-frame PCA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's try the Principal Component Analysis (PCA) algorithm ([Amara & Quanz 2012](https://ui.adsabs.harvard.edu/abs/2012MNRAS.427..948A/abstract), [Soummer et al. 2012](https://ui.adsabs.harvard.edu/abs/2012ApJ...755L..28S/abstract)), and set to 5 the number of principal components `ncomp` considered to create the model PSF."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "Starting time: 2024-07-04 11:56:23\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "System total memory = 17.180 GB\n",
      "System available memory = 3.217 GB\n",
      "Done vectorizing the frames. Matrix shape: (61, 10201)\n",
      "Done SVD/PCA with numpy SVD (LAPACK)\n",
      "Running time:  0:00:00.041111\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "Done de-rotating and combining\n",
      "Running time:  0:00:02.377683\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n"
     ]
    }
   ],
   "source": [
    "from vip_hci.psfsub import pca    # psfsub is the subpackage containing PSF modeling and subtraction algorithms\n",
    "\n",
    "fr_pca1 = pca(cube, angs, ncomp=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's visualize the final image. This time let's set the `grid` option on, to better read coordinates from the image. Alternatively, use the `backend='bokeh'` option for interactive reading:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plot_frames(fr_pca1, grid=True)#, backend='bokeh')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The improvement is clear compared to previous reductions. Very low residuals are seen near the star, and the companion candidate appears as a bright point source surrounded by negative side-lobes."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1.3. Is it significant?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's see whether the candidate is significant. For that let's first set the x,y coordinates of the test point source based on the above image:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "xy_b = (58.5,35.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's compute the signal-to-noise ratio at that location, following the definition in [Mawet et al. (2014)](https://ui.adsabs.harvard.edu/abs/2014ApJ...792...97M/abstract), using the appropriate function defined in the `metrics` subpackage:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "S/N = 7.7\n"
     ]
    }
   ],
   "source": [
    "from vip_hci.metrics import snr\n",
    "\n",
    "snr1 = snr(fr_pca1, source_xy=xy_b, fwhm=fwhm_naco)\n",
    "print(r\"S/N = {:.1f}\".format(snr1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One can also calculate a S/N ratio map over the whole image (this may take a couple of seconds depending on the size of your image):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n",
      "Starting time: 2024-07-04 11:56:25\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 600x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "S/N map created using 5 processes\n",
      "Running time:  0:00:03.034012\n",
      "――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――\n"
     ]
    }
   ],
   "source": [
    "from vip_hci.metrics import snrmap\n",
    "\n",
    "snrmap1 = snrmap(fr_pca1, fwhm_naco, plot=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-warning\"> \n",
    "    <b>Warning: </b>\n",
    "<a class=\"anchor\" id=\"war1\"></a>\n",
    "    \n",
    " S/N ratio is **not** the same as significance ([Mawet et al. 2014](https://ui.adsabs.harvard.edu/abs/2014ApJ...792...97M/abstract)) !\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's convert the measured S/N ratio (Students statistics) into the equivalent Gaussian \"sigma\" in terms of false alarm probability. This first involves calculating the radial separation of the candidate, for which we use the `frame_center` and `dist` convenience routines to infer the pixel coordinates of the center, and the radial separation of the point source, respectively:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "from vip_hci.var import frame_center, dist   # var is a subpackage containing various utility routines\n",
    "\n",
    "cy, cx = frame_center(snrmap1)\n",
    "rad = dist(cy, cx, xy_b[1], xy_b[0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's use the `significance` routine in VIP to operate the conversion:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "At a separation of 16.8 px (3.5 FWHM), S/N = 7.7 corresponds to a 5.2-sigma detection in terms of Gaussian false alarm probability.\n"
     ]
    }
   ],
   "source": [
    "from vip_hci.metrics import significance\n",
    "\n",
    "sig = significance(snr1, rad, fwhm_naco, student_to_gauss=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-success\"> \n",
    "    <b>Congratulations! </b>\n",
    "<a class=\"anchor\" id=\"det1\"></a>        \n",
    "    \n",
    "The detection is significant! You obtained a conspicuous direct image of an exoplanet! Although from this image alone one cannot disentangle a true physically bound companion from a background star, this source has now been extensively studied: it corresponds to giant planet $\\beta$ Pic b (e.g. [Lagrange et al. 2009](https://ui.adsabs.harvard.edu/abs/2009A%26A...493L..21L/abstract), [Absil et al. 2013](https://ui.adsabs.harvard.edu/abs/2013A%26A...559L..12A/abstract)).\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You're now ready for more advanced tutorials. If you wish to know more about:\n",
    "\n",
    "- basic usage but using an object-oriented framework --> go to **[Tutorial 1B](https://vip.readthedocs.io/en/latest/tutorials/01B_quickstart_with_objects.html)**;\n",
    "- pre-processing functionalities available in VIP (star centering, bad frame trimming, bad pixel correction...) --> go to **[Tutorial 2](https://vip.readthedocs.io/en/latest/tutorials/02_preproc.html)**;\n",
    "- post-processing algorithms leveraging Angular Differential Imaging --> go to **[Tutorial 3A](https://vip.readthedocs.io/en/latest/tutorials/03A_psfsub_ADI.html)** or **[3B](https://vip.readthedocs.io/en/latest/tutorials/03B_psfsub_ADI_as_objects.html)** (the latter for Object-Oriented example usage);\n",
    "- metrics to evaluate the significance of a detection or the achieved contrast in your image --> go to **[Tutorial 4](https://vip.readthedocs.io/en/latest/tutorials/04_metrics.html)**;\n",
    "- how to characterize a directly imaged companion --> go to **[Tutorial 5A](https://vip.readthedocs.io/en/latest/tutorials/05A_fm_planets.html)**;\n",
    "- how to characterize a circumstellar disk --> go to **[Tutorial 5B](https://vip.readthedocs.io/en/latest/tutorials/05B_fm_disks.html)**;\n",
    "- how to characterize a companion in a disk using JWST observations --> go to Tutorial 5C (to come soon);\n",
    "- post-processing algorithms leveraging Reference star Differential Imaging --> go to **[Tutorial 6](https://vip.readthedocs.io/en/latest/tutorials/06_psfsub_fm_RDI.html)**;\n",
    "- post-processing algorithms leveraging Spectral Differential Imaging --> go to **[Tutorial 7](https://vip.readthedocs.io/en/latest/tutorials/07_psfsub_fm_IFS-ASDI_planets.html)**;\n",
    "- the difference between FFT- and interpolation-based image operations (rotation, shifts, scaling) --> go to **[Tutorial 8](https://vip.readthedocs.io/en/latest/tutorials/08_imlib_and_interpolation.html)**."
   ]
  }
 ],
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