{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Integration with Python\n",
    "\n",
    "This cookbook explains you how to perform azimuthal integration using the python interpreter.\n",
    "It is divided in two parts, the first part uses purely python while the second will use some advanced feature of the Jupyter notebook.\n",
    "\n",
    "We will re-use the same files as is the other tutorials.\n",
    "\n",
    "## Performing azimuthal integration with pyFAI of a bunch of images\n",
    "\n",
    "To be able to perform the azimuthal integration of some images, one needs:\n",
    "\n",
    "* The diffraction images themselves, in this example they are stored as TIFF files\n",
    "* The geometry of the experimental setup as obtained from the calibration and stored as a PONI-file\n",
    "* other files like flat-field, dark current images or detector distortion file (spline-fle).\n",
    "\n",
    "Image file: http://www.silx.org/pub/pyFAI/cookbook/calibration/LaB6_29.4keV.tif\n",
    "\n",
    "Detector distortion file: http://www.silx.org/pub/pyFAI/cookbook/calibration/F_K4320T_Cam43_30012013_distorsion.spline\n",
    "\n",
    "The calibration has been performed in the previous cookbook. The geometry is saved in \"LaB6_29.4keV.poni\".\n",
    "\n",
    "### Basic usage of pyFAI\n",
    "To perform azimuthal averaging, one can use the pyFAI and FabIO libraries, the former to load the geometry and later to read the image:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "image_file: /tmp/pyFAI_testdata_kieffer/LaB6_29.4keV.tif\n",
      "poni_file: /tmp/pyFAI_testdata_kieffer/LaB6_29.4keV.poni\n",
      "spline_file: /tmp/pyFAI_testdata_kieffer/F_K4320T_Cam43_30012013_distorsion.spline\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "['calib-gui',\n",
       " 'LaB6_29.4keV.dat',\n",
       " 'integration_with_scripts.ipynb',\n",
       " 'index.rst',\n",
       " 'LaB6_29.4keV.tif',\n",
       " 'integration_with_the_gui.rst',\n",
       " '.ipynb_checkpoints',\n",
       " 'F_K4320T_Cam43_30012013_distorsion.spline',\n",
       " 'LaB6_29.4keV.poni',\n",
       " 'pyFAI-integrate.png',\n",
       " 'calib-cli',\n",
       " 'integration_with_python.ipynb',\n",
       " 'integrated.edf',\n",
       " 'integrated.dat']"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# This cell is just to download the files to perform the analysis:\n",
    "from silx.resources import ExternalResources\n",
    "downloader = ExternalResources(\"pyFAI\", \"http://www.silx.org/pub/pyFAI/cookbook/calibration/\", \"PYFAI_DATA\")\n",
    "image_file = downloader.getfile(\"LaB6_29.4keV.tif\")\n",
    "spline_file = downloader.getfile(\"F_K4320T_Cam43_30012013_distorsion.spline\")\n",
    "poni_file = downloader.getfile(\"LaB6_29.4keV.poni\")\n",
    "\n",
    "print(\"image_file:\", image_file)\n",
    "print(\"poni_file:\", poni_file)\n",
    "print(\"spline_file:\", spline_file)\n",
    "\n",
    "# Copy all files locally\n",
    "import shutil, os\n",
    "shutil.copy(spline_file, \".\")\n",
    "shutil.copy(poni_file, \".\")\n",
    "shutil.copy(image_file, \".\")\n",
    "os.listdir()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pyFAI version: 0.18.0\n",
      "image: <fabio.edfimage.EdfImage object at 0x7f2d30b5ef98>\n",
      "\n",
      "Integrator: \n",
      " Detector Detector\t Spline= /mntdirect/_scisoft/users/kieffer/release/pyFAI/doc/source/usage/cookbook/F_K4320T_Cam43_30012013_distorsion.spline\t PixelSize= 5.168e-05, 5.126e-05 m\n",
      "Wavelength= 4.217150e-11m\n",
      "SampleDetDist= 1.181795e-01m\tPONI= 5.396318e-02, 5.540257e-02m\trot1=0.006087  rot2= -0.008146  rot3= 0.000000 rad\n",
      "DirectBeamDist= 118.186mm\tCenter: x=1066.678, y=1025.571 pix\tTilt=0.583 deg  tiltPlanRotation= -126.767 deg\n"
     ]
    }
   ],
   "source": [
    "import pyFAI, fabio\n",
    "print(\"pyFAI version:\", pyFAI.version)\n",
    "img = fabio.open(\"LaB6_29.4keV.tif\")\n",
    "print(\"image:\", img)\n",
    "\n",
    "ai = pyFAI.load(\"LaB6_29.4keV.poni\")\n",
    "print(\"\\nIntegrator: \\n\", ai)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Azimuthal averaging using pyFAI\n",
    "\n",
    "\n",
    "One needs first to retrieve the image as a numpy array. This allows to use other libraries than FabIO for image reading, for example HDF5.\n",
    "\n",
    "This shows how to perform the azimuthal integration of one image over 1000 bins:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "img_array: <class 'numpy.ndarray'> (2048, 2048) float32\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:pyFAI.io:Destination file integrated.dat exists\n"
     ]
    }
   ],
   "source": [
    "img_array = img.data\n",
    "print(\"img_array:\", type(img_array), img_array.shape, img_array.dtype)\n",
    "\n",
    "res = ai.integrate1d(img_array, \n",
    "                     1000, \n",
    "                     unit=\"2th_deg\", \n",
    "                     filename=\"integrated.dat\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Note:* There are 2 mandatory parameters for this method, the 2D-numpy array with the image and the number of bins. We specified in addition the name of the file, where to save the data and the unit for performing the integration.\n",
    "\n",
    "There are many other options to integrate1d:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on method _integrate1d_legacy in module pyFAI.azimuthalIntegrator:\n",
      "\n",
      "_integrate1d_legacy(data, npt, filename=None, correctSolidAngle=True, variance=None, error_model=None, radial_range=None, azimuth_range=None, mask=None, dummy=None, delta_dummy=None, polarization_factor=None, dark=None, flat=None, method='csr', unit=q_nm^-1, safe=True, normalization_factor=1.0, block_size=32, profile=False, all=False, metadata=None) method of pyFAI.azimuthalIntegrator.AzimuthalIntegrator instance\n",
      "    Calculate the azimuthal integrated Saxs curve in q(nm^-1) by default\n",
      "    \n",
      "    Multi algorithm implementation (tries to be bullet proof), suitable for SAXS, WAXS, ... and much more\n",
      "    \n",
      "    \n",
      "    \n",
      "    :param data: 2D array from the Detector/CCD camera\n",
      "    :type data: ndarray\n",
      "    :param npt: number of points in the output pattern\n",
      "    :type npt: int\n",
      "    :param filename: output filename in 2/3 column ascii format\n",
      "    :type filename: str\n",
      "    :param correctSolidAngle: correct for solid angle of each pixel if True\n",
      "    :type correctSolidAngle: bool\n",
      "    :param variance: array containing the variance of the data. If not available, no error propagation is done\n",
      "    :type variance: ndarray\n",
      "    :param error_model: When the variance is unknown, an error model can be given: \"poisson\" (variance = I), \"azimuthal\" (variance = (I-<I>)^2)\n",
      "    :type error_model: str\n",
      "    :param radial_range: The lower and upper range of the radial unit. If not provided, range is simply (data.min(), data.max()). Values outside the range are ignored.\n",
      "    :type radial_range: (float, float), optional\n",
      "    :param azimuth_range: The lower and upper range of the azimuthal angle in degree. If not provided, range is simply (data.min(), data.max()). Values outside the range are ignored.\n",
      "    :type azimuth_range: (float, float), optional\n",
      "    :param mask: array (same size as image) with 1 for masked pixels, and 0 for valid pixels\n",
      "    :type mask: ndarray\n",
      "    :param dummy: value for dead/masked pixels\n",
      "    :type dummy: float\n",
      "    :param delta_dummy: precision for dummy value\n",
      "    :type delta_dummy: float\n",
      "    :param polarization_factor: polarization factor between -1 (vertical) and +1 (horizontal).\n",
      "           0 for circular polarization or random,\n",
      "           None for no correction,\n",
      "           True for using the former correction\n",
      "    :type polarization_factor: float\n",
      "    :param dark: dark noise image\n",
      "    :type dark: ndarray\n",
      "    :param flat: flat field image\n",
      "    :type flat: ndarray\n",
      "    :param method: can be \"numpy\", \"cython\", \"BBox\" or \"splitpixel\", \"lut\", \"csr\", \"nosplit_csr\", \"full_csr\", \"lut_ocl\" and \"csr_ocl\" if you want to go on GPU. To Specify the device: \"csr_ocl_1,2\"\n",
      "    :type method: can be Method named tuple, IntegrationMethod instance or str to be parsed\n",
      "    :param unit: Output units, can be \"q_nm^-1\", \"q_A^-1\", \"2th_deg\", \"2th_rad\", \"r_mm\" for now\n",
      "    :type unit: pyFAI.units.Unit\n",
      "    :param safe: Do some extra checks to ensure LUT/CSR is still valid. False is faster.\n",
      "    :type safe: bool\n",
      "    :param normalization_factor: Value of a normalization monitor\n",
      "    :type normalization_factor: float\n",
      "    :param block_size: size of the block for OpenCL integration (unused?)\n",
      "    :param profile: set to True to enable profiling in OpenCL\n",
      "    :param all: if true return a dictionary with many more parameters (deprecated, please refer to the documentation of Integrate1dResult).\n",
      "    :type all: bool\n",
      "    :param metadata: JSON serializable object containing the metadata, usually a dictionary.\n",
      "    :return: q/2th/r bins center positions and regrouped intensity (and error array if variance or variance model provided), uneless all==True.\n",
      "    :rtype: Integrate1dResult, dict\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(ai.integrate1d)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The result file contains the integrated data with some headers as shown:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# == pyFAI calibration ==\n",
      "# Distance Sample to Detector: 0.11817947569514631 m\n",
      "# PONI: 5.396e-02, 5.540e-02 m\n",
      "# Rotations: 0.006087 -0.008146 0.000000 rad\n",
      "#\n",
      "# == Fit2d calibration ==\n",
      "# Distance Sample-beamCenter: 118.186 mm\n",
      "# Center: x=1066.678, y=1025.571 pix\n",
      "# Tilt: 0.583 deg  TiltPlanRot: -126.767 deg\n",
      "#\n",
      "# Detector Detector\t Spline= /mntdirect/_scisoft/users/kieffer/release/pyFAI/doc/source/usage/cookbook/F_K4320T_Cam43_30012013_distorsion.spline\t PixelSize= 5.168e-05, 5.126e-05 m\n",
      "#    Detector has a mask: False\n",
      "#    Detector has a dark current: False\n",
      "#    detector has a flat field: False\n",
      "#\n",
      "# Wavelength: 4.2171495713063666e-11 m\n",
      "# Mask applied: False\n",
      "# Dark current applied: False\n",
      "# Flat field applied: False\n",
      "# Polarization factor: None\n",
      "# Normalization factor: 1.0\n",
      "# --> integrated.dat\n",
      "#       2th_deg             I\n",
      "1.668236e-02    2.742935e+00\n",
      "5.004708e-02    2.763854e+00\n",
      "8.341179e-02    2.027486e+00\n",
      "1.167765e-01    2.828063e+00\n",
      "1.501412e-01    2.858796e+00\n",
      "1.835059e-01    2.676403e+00\n",
      "2.168707e-01    2.498860e+00\n",
      "2.502354e-01    2.823416e+00\n",
      "2.836001e-01    2.751592e+00\n",
      "3.169648e-01    2.811967e+00\n",
      "3.503295e-01    2.864722e+00\n",
      "3.836942e-01    2.790787e+00\n",
      "4.170590e-01    3.016608e+00\n",
      "4.504237e-01    3.085250e+00\n",
      "4.837884e-01    3.127071e+00\n",
      "5.171531e-01    3.036138e+00\n",
      "5.505178e-01    3.003028e+00\n",
      "5.838825e-01    3.027691e+00\n",
      "6.172473e-01    2.930282e+00\n",
      "6.506120e-01    3.160540e+00\n",
      "6.839767e-01    3.100977e+00\n",
      "7.173414e-01    2.905571e+00\n",
      "7.507061e-01    3.072437e+00\n",
      "7.840708e-01    3.025366e+00\n",
      "8.174356e-01    2.891713e+00\n",
      "8.508003e-01    2.989543e+00\n",
      "8.841650e-01    3.104775e+00\n"
     ]
    }
   ],
   "source": [
    "with open(\"integrated.dat\") as f:\n",
    "    for i in range(50):\n",
    "        print(f.readline().strip())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Azimuthal regrouping using pyFAI\n",
    "\n",
    "This option is similar to the integration but perfroms N-integration on various azimuthal angle (chi) sections of the space. It is also named \"caking\" in Fit2D.\n",
    "\n",
    "The azimuthal regrouping of an image over 500 radial bins in 360 angular steps (of 1 degree) can be performed like this:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:pyFAI.azimuthalIntegrator:Method requested 'None' not available. Method 'IntegrationMethod(2d int, pseudo split, histogram, cython)' will be used\n",
      "WARNING:pyFAI.io:Destination file integrated.edf exists\n"
     ]
    }
   ],
   "source": [
    "res2 = ai.integrate2d(img_array, \n",
    "                      500, 360, \n",
    "                     unit=\"r_mm\", \n",
    "                     filename=\"integrated.edf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{\n",
      "  \"EDF_DataBlockID\": \"0.Image.Psd\",\n",
      "  \"EDF_BinarySize\": \"720000\",\n",
      "  \"EDF_HeaderSize\": \"1536\",\n",
      "  \"ByteOrder\": \"LowByteFirst\",\n",
      "  \"DataType\": \"FloatValue\",\n",
      "  \"Dim_1\": \"500\",\n",
      "  \"Dim_2\": \"360\",\n",
      "  \"Image\": \"0\",\n",
      "  \"HeaderID\": \"EH:000000:000000:000000\",\n",
      "  \"Size\": \"720000\",\n",
      "  \"Engine\": \"Detector Detector Spline= /mntdirect/_scisoft/users/kieffer/release/pyFAI/doc/source/usage/cookbook/F_K4320T_Cam43_30012013_distorsion.spline PixelSize= 5.168e-05, 5.126e-05 m Wavelength= 4.217150e-11m SampleDetDist= 1.181795e-01m PONI= 5.396318e-02, 5.540257e-02m rot1=0.006087 rot2= -0.008146 rot3= 0.000000 rad DirectBeamDist= 118.186mm Center: x=1066.678, y=1025.571 pix Tilt=0.583 deg tiltPlanRotation= -126.767 deg\",\n",
      "  \"detector\": \"Detector\",\n",
      "  \"pixel1\": \"5.1679e-05\",\n",
      "  \"pixel2\": \"5.1265e-05\",\n",
      "  \"max_shape\": \"(2048, 2048)\",\n",
      "  \"splineFile\": \"/mntdirect/_scisoft/users/kieffer/release/pyFAI/doc/source/usage/cookbook/F_K4320T_Cam43_30012013_distorsion.spline\",\n",
      "  \"dist\": \"0.11817947569514631\",\n",
      "  \"poni1\": \"0.05396317577947509\",\n",
      "  \"poni2\": \"0.05540257053937799\",\n",
      "  \"rot1\": \"0.0060865362452917245\",\n",
      "  \"rot2\": \"-0.008145586908306525\",\n",
      "  \"rot3\": \"8.66882838910645e-08\",\n",
      "  \"wavelength\": \"4.2171495713063666e-11\",\n",
      "  \"r_mm_min\": \"0.09608558187064897\",\n",
      "  \"r_mm_max\": \"77.68411700260273\",\n",
      "  \"chi_min\": \"-179.49997779626557\",\n",
      "  \"chi_max\": \"179.49994461241516\",\n",
      "  \"has_mask_applied\": \"False\",\n",
      "  \"has_dark_correction\": \"False\",\n",
      "  \"has_flat_correction\": \"False\",\n",
      "  \"polarization_factor\": \"None\",\n",
      "  \"normalization_factor\": \"1.0\"\n",
      "}\n",
      "cake: <class 'numpy.ndarray'> (360, 500) float32\n"
     ]
    }
   ],
   "source": [
    "cake = fabio.open(\"integrated.edf\")\n",
    "print(cake.header)\n",
    "print(\"cake:\", type(cake.data), cake.data.shape, cake.data.dtype)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From this it is trivial to perform a loop and integrate many images. \n",
    "\n",
    "*Attention:* The AzimuthalIntegrator object (called ai here) is rather large and costly to initialize. The best practice is to crate it once and to use it many times, like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:pyFAI.io:Destination file LaB6_29.4keV.dat exists\n"
     ]
    }
   ],
   "source": [
    "import glob, os\n",
    "\n",
    "all_images = glob.glob(\"LaB6*.tif\")\n",
    "ai = pyFAI.load(\"LaB6_29.4keV.poni\")\n",
    "\n",
    "for one_image in all_images:\n",
    "    fimg = fabio.open(one_image)\n",
    "    dest = os.path.splitext(one_image)[0] + \".dat\"\n",
    "    ai.integrate1d(fimg.data, \n",
    "                   1000, \n",
    "                   unit=\"2th_deg\", \n",
    "                   filename=dest)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Using some advanced feature of Jupyter Notebooks\n",
    "\n",
    "Jupyter notebooks offer some advanced visualization features, especially when used with *matplotlib* and *pyFAI*.\n",
    "Unfortunately, the example shown hereafter will not work properly in normal Python scipts.\n",
    "\n",
    "### Initialization of the notebook for matplotlib integration:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/mntdirect/_scisoft/users/kieffer/.jupy37/lib/python3.7/site-packages/IPython/core/magics/pylab.py:160: UserWarning: pylab import has clobbered these variables: ['f']\n",
      "`%matplotlib` prevents importing * from pylab and numpy\n",
      "  \"\\n`%matplotlib` prevents importing * from pylab and numpy\"\n"
     ]
    }
   ],
   "source": [
    "%pylab nbagg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from pyFAI.gui import jupyter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "### Visualzation of different types of results reviously calculated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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XeW1+F1FDL+fmI62nFLMTWvA3LQGl/cLYya5csy7ut6Vjd/5jAWZNS6tlsWWi+n5eTqlEf+SMdHVlx+2wwtjJrlnannmpjWgLacU/29OGXbOvAxv/nI4VpXm9PhsLRu//0vGRCzIrHFtyL7QevG5vDbv6nrMu7retT+fMe/qerwwZlIoLy231u2XmYlQOzEf5v/YqOmhsmsaHS+sh5bjl5kJrCrNwdy0Bvw6a0K3NnthzCQ8Nmq6u6bjh2NN89b++JeMiW4M8FnsH7Yny87+Y98yL6ZhuVkf3s80T6c0unyi2pLl1LGl9Xk6pRGPjZru+pd9Oe/qeizIrMGS+Hh01mRiz60X4bV7z8OGSWOwvCgfv86agMXjivFyw1WuPJqnftcPr/86awIWZNaExvq/ZEwM9dOdF98YGmc6VllHOwcwPeup9WVbaJs+lzoFd158oyuD3sf/tT3ZxlomfR++fP6N3fqA35mntjvz5JzF61o/toPWVce+lol5cYzaOUXnDz6DZebY1Wdrn/K71kPbU9v+mdSJCIIABw8e/HOrFC9/BvEA0Euv5NChQwiCAE+nNGJ+2nTMT5uOhZmTsSBjKppTZ6IlvRHNqTOxMHMyWtJPplmQMRXPpMzCMymzQmnnjGzC/LTpofueSZmFlvRGPJMyC/PTpqMlvRGtsXq0pDdiUVYDlo2rwaqCCmxN5ODVL6bh4G3D8c7dF+P1667AgZsuw7Hvno2OkmIsymrAgoyp7rMoqwELMye7jz53UVaDe+aCjKlYmDnZlaMlvRELMqa6/9tide4+1m9+2nQ8kzILzakz0Zw6E62x+m71WpAx1dWHZZmfNh2LsyfilcmZePWLaVg2rgZri0uxqqAiVAY+g3Vi2y7MnOyewfwXZk5Ga6zetR/LxLTsD+bFMvGvfSbbvy1W535jH7ItF2U1uLSsl5aTZeDzm1NnYlFWAzZUFLh07Cfey7HA9Myf97KsHFO8xradM7Ip1CbMi2OJ5bT1Yd15TcewthfLqO3P8jFNS3oj7hs6O1SXtlhd6P45I5tcPnwfmFZ/43O0XxZlNWBJTi06SoqxNZGDLTW5WF9eiFUFFe53pl2am3DjTevAOrOcbCOOZ9aJ9eG4WZTV4D4sr23T+4bOxqKsBjf+tf/5v/Yx66/jkdfYviviVS7/Z1Jm4b6hs0PPaUlvRHt8QigfXtc5xZaD3zl25oxscm3A7/qOaHn1fjvW9Tf+vW/obDyTMss9gx9tE30P2e7NqTNxw+BbXX20jPZ+HT86PzHP51KnIAgCHDrU/ZhBL//7xQNAL70SBYCqhBXo2IlXgSL/V4VglS6BmIIrKp5l42rQUVKMnfXX4kDTKHT96HQcXZuDg7cPw876a7GurAjL86qxOHuiU3JtsTp3vwI7Kj/9sFy8R5Wv1lPBiCplrYsCClUeCkwXZk7G+vJCtMcnOEXdFqtzIFInbpsfwSbbinmzXAq42eaqWBW087c5I5ucclVAzDT8zjpakMxnsrytsfoQ2FyeV40lObUOtPE+BYHa7mwHBSBaXr2/PT4h1LZsq+V51VhTVObu1TG4IGNqN7CoQFufrXXS9tYxrGNWAQLBxbqyolD9NW/mS7DOe/gMglsFzYuyGtAWq8OycTVYmV/pvi/KasCaorJQnzG9ll/rznbnOCCQ4BhnudSAYbm1j/W9V9DFNFovfb/0PjUGdZ4ggNb3jmNO+5VAVt9FBWlscwVsWlYF9Cwv28UaOxYsW3Cp75neo0ajvkcWECqAVMCnBrQCeDVs9V3Utp+b1uABYBKLB4CfIXn44YdxzTXX4KyzzsLgwYORSCTw8ssvh9IcPXoUN910EwYNGoQzzzwTkyZNwmuvvRZK84c//AGVlZU444wzMHjwYNx11104fvx4KM3ixYuRnp6Ofv364bLLLsNzzz33qcpKADjv6jDLdd/Q2aFJjN+X5NSis3Q87hs62ykV/j9nZFNo0rSMgE7KnORbY/XoKCnGroZrcOCmy3D8/7kIRx86DweaRmFHXQzryoqwOHuim8BbY/V4566hWF1YHgIGylxZxa1KxE6yav1ToSobp0BI/yoDZ1kOZZn4VxW1KiMFxlEMCa8vyal1aW8YfGs35awsiip3VTYKtJRBscBIWT8Foap4NV8tB8dAT+1iwas+X8ENAS/zVAZVgYwF0FbJszytsXrHFvI5HNN8NtNEMYOWMVNjyYJxHSNU2sp0KlixgJ6/Lc6eiKW5iZDhoW2v+dt+U7Zcy8fy87M8rzrURgr6luTUhtpM852fNh1Tzpvtyq9sndaZdXwmZVaoXbUsyjzrPdZoIYvJd2lzdZ7rZ2tktqQ3OmaNvzF/BXF2HGi/qOdA0y7OnogV8SrXNxbYWSNB2W07VvV91fdJ50rNW8ed3nPf0NkeACa5eAD4GZKysjI899xzWL9+PTo6OlBZWYlhw4bh3XffdWmamppwySWXoK2tDatXr8bYsWORk5Pjfv/ggw9w5ZVXori4GGvXrsWLL76ICy64APfee69Ls2PHDgwYMAB33HEHNm7ciMcffxynnHIKFi1a9InLqgygWt5qvetkbdkCm1YVuv1N7+PE2harw6qCCuysvxZv3TICB266DG/eeDn2TEvH5uo8dJQUOwDICX51YXk3tomTdhQ7pgqRoFXrSSBqldHCzMloi9WFAAzrvzyv2rnm7CStbaUgQstjGThVZrYPlH1heaPYCAu0lGFUkGDbRhW3Ak9lBtkW2kZRz2R59H+blm2j40WZy/XlhViZX4k5I5sccGYZbd0IZhQ8sc+UMd1Wm40909JD4MS2ibY7gcOU82Z3aycCUpad+dAYskCAdV2cPdEpdgUX2na2TDo+WmP1oX7X98kCUK27treOMQvuFOwTdGnbKLBVUKXvBuuufcT3jm2obcBnW4bNvp+8T8dRa6weW2pyXV+rEafsJMu2OHtiN4CvRp7W3RqvfO6aojLnmic7q2Xj/WwLrYsaApz7FMDzHgJSnVd0vtUysYz/kjHRA8AkFg8AP8PyxhtvIAgCLFmyBMDJhRennXYaXnjhBZdm06ZNCIIA7e3tAIAXX3wRffv2DbGCTz75JM455xx0dXUBAL7+9a8jNTU19KzJkyejrKzsE5eNAHBu2smJiK4HTsqcYF6bmRoCfzYWSt0mykYoaOIEyHupXFbmV6KzdDy2TxqL7ZPGYlttNjZVxdFZOh4r4lXYURcLKWC1+HUStQpCrWmdjHWytgyG1iNKETSnzsTi7Il4bWYqtiZyQmCOdWcMk95r24UKgQqEIFcVOtmvngA2lbSyA1Ry2gbKplmmgwpraW7CKS5lZ7UPtY0UiNlyWYBo62XHCtuJ6RRgKLOkQFP7kEDF9psq0ebUmVhXVhQCVVoHdYsqoLPMXFS9+GwFLWSsFNypgaDMEtOzHhYQqrtPx7l1A2q5FIRov9w3dLa7b9m4mm7txd/se8RYQ4JfZXAVIKsLmt/VYCGAZp/rWIxi61gmfaa6ebXuzEfBLvNri9VhTVEZ1haXYnH2RGckMI2+DzrGFYQuympAZ+l4HH3oPBy64xIsz6t2McQ6J3FMWcPPMrT8jX1iYxpZXzVwlIVVA8LHACa3eAD4GZatW7ciCAL8/ve/BwC0tbUhCAK8/fbboXTDhg3DnDlzAADf+MY3cPXVV4d+37FjB4IgwO9+9zsAQF5eHm677bZQmmeffRbnnHNOj2U5duxYaP8obgMzN+3D4G5rberEy+90G6k7Qr9rWv3OZygT0Rarw9LcBFYVVGBtcSnWFJVhdWE5ludVuwULyiRQuS3Pq0ZHSTG21Wa7GEEtg4IFVTYEjjoxa32t0qfiUoWq7kJVosqqqBLTvFpj9Vg2rgZrisqwqqACqwoqupVflZcqJl0IYBW19ov2pWUDFSAoCNcyMh9lV5mWbA7LybZgG7fHJ2BlfmU3dpBjwLrJFPxZt64FIpYB0Wu2jqqEFTwxBlUZL1WmBCmsH92JZOA0T83X9rkNF9C21TTsBztGFdASYChg1jFiQZIdA8p0cQySybag1xpNjGdV8LUiXuXu07GrfaLxdVHAncaU9ouOYe1nG67BtmadluYm0BqrDy2UYH0WZk7GsnE1eGVyJg7fMwRbanJdfKmWhWXWd4yAsiX9ZBjG0twEttTkYmNlfojl0zrbOmqf0fjV9raxyFpvZQHVkNB089NOrkT2ADB5xQPAz6icOHECVVVVyM3Nddfmzp2Lfv36dUublZWFr3/96wCA66+/HqWlpaHf33vvPQRBgBdffBEAMGrUKDz88MOhNAsXLkQQBDhy5EhkeR588MHI/aPIANJ9wgnHKjxOzjqp68cqa2vhW2aQQGRJTi3aYnVYnleNpbmJboH1ZKM48S/OnohNVXG8c9dQvPfABVgRr3LltCDJggQFd6pwdNJWFksZHqZRpatMn9ZZmTplYRZnT8S6siLsqIthb+MYbJ80NrSogemVUbLswKqCCizNTWBzdZ57ngbJK0DU8tww+FasKSpDa6wenaXjsaGiwC0uYB9FLQLguFAgal2mLFdHSbFbHGKBowVwCmoVhCnY4hjRcch25WpmOw6VGbMuXws02acEesrm6eIJBUAsL+ukzNickU0OYHDszBnZhPuGzna/K/M8P+1kXGcUC6dtRLClgN7GvrFOzE9Z3ijW6ZXJmSHXowJZgtKluYnQAiIFtOvKirClJhfbJ411wJmALQp8K5hVQ0vbSeum91u2Xt+7KFZxzsgm58Jvj0/A9klj0TXndOyekoHledWuTMpaKjutbmWWQ923Oq/oGLFtr+WzxoMFfVHAj21q5zKm9zGAXjwA/IxKU1MThg8fHtqg888JAHtiAO+8+MaQe0gZO518OAGqla6AT4GgAiCdzFUJcILVPAhAFMippczfttVm4/C9F2FzdZ4LWuckrROoPtdOrJqnKl4FOgQgVELaHlpuCxT52ds4xikkshUbK/Px3gMXoOs/rsC+GVdiXVmRU6C27Aq0dVGBugypyFh/Baa8rzl1pnOFcWWy3t+TAlLQZBkPBXZ8vgI9DSnQcvA605LltcyGZUBYNrreWD8br2XdZKrYFeRxXCjg1Y9l4ghCNN8owG2Vt15nmykrx7wtoLMMmjKBWm5riGhdtQx2jGs9V8SrsK6sCCvzK7GqoAJLcmpD76i6KXUOYJvQeCBIXJJTGyqnMl12GxZ959R4Ykzl/LSTbmgFgXaMaF68/4bBtzpQuTK/EmuLS7G2uLRbfysbrO+B5sd2mzOyKRSPaec/fdeVQVTDgve1xepCzDWfzXZnG6obWOvNcf10SqMHgEksHgB+BuXmm2/G0KFDsWPHjtD1P6cL2ApjAB8b9eFEqkpFJ2YFdpY90YlJA9Cj4oXsNVUudrKlouF3plmcPRHt8QlYEa/CsnE1ziJnPpz0rcJTJkMnZbIW+nxddMGy6KRvQZIqdWWfVAm0xerQFqvD5uo8dD16Bt5/sh/2TEvHmqIy1xbKTi3MnIyluQkXg7U1kePy0Bg9CwIs4FBAqfcowNB4LWWAtN84PnQxhcZcWdCmKzmZ1pbPsiWqhJWF7Ekh6xhS1laZLNYpysWsDCvrp8/WdrJjwAIX64JX8KaMoQIj1k8BsjJi+iyOU9s3/J9xaWp4aTkVqCuTag0lBXDKGlrQw7ZT4LapKo5VBRXYUFGAztLxLi7VGjYKtLVtbZva8WHbNwq02//57qkBZcesAi81YqLctOqOt8DbAjRtwxsG39rt3WTIi5aH42JtcWlo8ZLda5VzrY8BTG7xAPAzJH/84x9x88034+KLL8aWLVu6/c5FIP/8z//srr388suRi0Bef/11l+app57COeecg2PHjgE4uQjkyiuvDOU9derUXi0CeTrlQ2ZE458sCORkaBkGnUDtwgedHFfEq7pNzpY54WpTtZjVRUmmQdOqa0gt+Ch2SxWEAgJ9hiomBYdaJ1VaUYCDSkcBADf61c1+1xSVOWWr+TenzsSqggrsbRwTai+7IC3BrAwAACAASURBVCYKjPOZFgwpQFVFasutffRRcXlWUWv7apsTXLK/okCgdbWpIaH1VGaY9WKeNhBf21THoo45q7x7Yna0jLqKmUaKsudaZi2HGj/a9jrWFmdPDBkTqvCVvdT79G8UG6r1VFe19rcd/3q/jj3LhlnQtiSnFpuq4jj+r4Nw+J4hWDauplt72jrZ6zoWrMeB93E8qbFijT2GXFgwb4Gv9osy2tZo0nGvBqWOVb1PDQ81arU/FmWd3BCf9aE3g/tBriqowIKMqa4d1RBjf9958Y0eACaxeAD4GZKvfvWrOPfcc/Hv//7v2Ldvn/uoW7apqQnDhg3DSy+9hNWrVyM7OxvZ2dnud24DU1paio6ODixatAiDBw+O3Abm7rvvxqZNm/DEE0/0ehuYF8ZMCk2aCzI+3B9L3bcKCmnRKtugkyInSnUP6dYSnMQ1X05suuDCKjsGe+tEysmbizCsstTTBVRZ6HdV1Kr8LNuijJM+R12knNTXFJVheV41FmU1uLgoLh7hYhDeZ/dK40cXXOi2EVTAqhR4v25PwbrY1dhWsWlb89MenxBiTalwrDK3YNSCIAUSzEf7nOXTflBWjPcpOFRlzjyUleyJdWQ5rGGgYMS6BxWUEBzYOllDge2i23qwfhbsKCul/c+tRqJOEVGDTYG2GhzaJ3xnFOhxYYLWTcs55bzZoXIuzU10A9TaF5w31hSVYfeUDGyfNBbL86rRnDrTxeMpaFJXrAIsvm8KZm2s58r8Shy8fZg7KYj1UENE+zMKyFngb40AG7pi+4guava/bQ/mH3UaCdPyHV42rsZtcr62uNQtbOGYb43Vu9X6NvbRxwAmt3gA+BmSng7q1k2auRH0wIEDMWDAAEycOBH79u0L5bNr1y5UVFTgjDPOwAUXXIA777wzciPoMWPGoF+/fhgxYkSvN4J+LnWKm6yWjatxk5Qq8ObUme5YJgUdOmn3ZOUvzp6IZeNqQps6WyWveapFrkDCMi9Mo89WZc//9bQEVQAanM3fNYZOGQAtm1ryVAy6KnhVQQW2TxrrTjThgggFC/xf22NDRQE2V+c5JoB7Derz7X5mBMyWdVIXuCo6y6SoO1dZqoWZ4f0RdbsVKiV1ryrbqIyWBRdaPt3jkeDdxoDadrKAU4/qo6K0zKWCDQWYVMjar8pi8hl2bzb+r0pdWWi7sEgBnQ2h0HdGvyt40XLZPtU4TwW7lunSMisw0XeK9ysDqcyYLspiWs2bz6UBtGxcTcjQUnCnbaN1UXCm7WJX/7bF6rCpKu5OTOFvUQvVOC40XwXf1jhRT4Ytr2UGWTcLzNVI1rGm41gNRh6JuW/GldjVcA06S8eHYirfmJUS2gCboHrOyCa8MGaSB4BJLB4AeumVKADkSsX5aR8GX6uCW55XHbKKFVDxO+/TyVCBCidWBRLW6lbGzYJJOxmrq1rz1QnaTuLqplGG0y7AsBM+J2uNCbIuagKqztLxOHzvRTg+72zsargmtLJW2Ttub8E8dtZfiyPfHITN1XlYX16Ig7cNDyn1BRknt+Wg64vASWPGlPHRtrRsyMLMk9tjbKvNjlxBTMWl4MqCYu039ocyIFFK3rrrW9I/PDKPjJcCUQX/bH8FSgqq7MIejkfLyCnzaAGKZQOZrwbsWyZR3wMCCY05tODYGhWWlbIG1Py06Y4NYn4KwKNYKqbR9lcjSq9Z17iCUTWIFHir0aNjQdNaQKeuTb2u41s/WhY7L7CuUSvEn0mZhfb4hNB4VkNA5xLtQ5u/zjP67vJ3rTtPR7HjVZ/LsWTZ8SU5tVhbXIpdDdfg+C8vwKE7LsHGynwszU1gTVGZS2PnJnpg/DYwyS0eAHrplRAA3nnxjQ40KDtg/9f4P52I+HkmZRZuGHyr+2uZDeuG0QmX6XuKr+MnagWhKlJlLnm4vAVB6qrT+iiIVKBHYKITOgO6NW1z6skVqivzK7GlJhc76mLYUFEQ2sZGGRqWh8e7kdlgnZTZaElvxMr8SmyszMf2SWPRUVLswJ9dNc37dRWlBRjPpMzC4uyJeP26K9wpFbrthd1+wipS9oUyLgpAOQ7oZtS2VhapLVaH1YXlWFNU5rbDiQIA2saqkKlYtZzt8Qluq5yeGBeu5mTeCugUCO5tHNMNYMxPO7kgZ3ledQiwqAGyOHuiCwHQsabjW0EeDRPruoxiCDletE35bK7e5f36bigTqu5N7SNlKLU9LNDX985uc8L89X41VmxMn4J6bWN19/N3llWfqcalglHtm6h3wBoBdtzZ+1g2uz2Qvst2LOrztF81JnNh5mSsiFdhQ0UB9kxLx66Ga7ChosBth2WBuo6XOSOb/CKQJBcPAL30SpQBtAraxtzoJ8rVFfVRRUDgpQDEgij+ptt8RE3YyspZpoT3WRcon2m3JrGAk+yXMg92/zHL5BFIbKzMx/ryQizPq3YrldX1pGVRJWiVE4GvtnVbrA7rywvx5o2X4/22y7Cr4RqXv7o7VemwTXVrHAUz9vnaBtquys6o4te+VQVK1y7Lpkpd3W7clmb7pLHYPSUDO+uvdS49jgtlO7XfyCYxP13FzGsKHPlsjkHtC94fBQIVxGqbkJ2x/dRZOt4t7jl423C8MSvFhQD0xIAqELPjQL/rPnn6fkW5K/U3jbuzz2Kb8F1kWnWV8zoNA2U8bV2si31tcWk3A0zHigWkdEHrO2ZBbpQxxRjAlvTGUOwi+0c9FwRODG3QPNl+bA/OF8zbstu2XlHtYg1KLdeqgopQzG1n6XisLix3xos+m23DuYNeC78NTHKLB4BeeiXKAOpEpe4kZQiiAJdaqKpYdJKzCyZ0gtxWmx0CLR0lxW6y46SvVrwqBF5XRaATNZkee68qbI1f40RuXXNtsTrsqIuFQIOmW5JTiw0VBdiayHFHbHGCVteVAgx1R6kCsiBQ3cwdJcXYPSUDr34xDZur89yh9GxjuuQsiFOFq+DGPof/6/Yk2hdRbBTLp+5OZRD1Pu1Hsn876mJ4e/aleP+Jfjh8zxBsrMx3zIeyUa2xeizPqw4Bdv1NGTFtU41V0zhAHRM2Pkvdiiw3WTc1jBRcazstymrAyvxK7G0cgwNNo9xCIO3fjpLiELul7401pCxzRaMiCjTqO6rjQNPb7VC0PbUu1k1qT7qxWxHpu7eurKibUanjQ40JGx4RBSR13G2qirs+tC5g5kOWUN9Zffe1fy34U/CvdYgCewqYmacurOHcyTRR7Ky+v62xeizOnhi5cph52/hWHwOY3OIBoJdeiY0BtDF1qoAs0NPJVid5BXc6kSoQtDFFCoR00rfgMSp+pqdtQZQl0WdaVoEKQldTKqCkS5db2Ch4WJAx1Z3IceRbA0MnBGhsnsYicUNbfldGhwqW1zS+bUHGVLdKcH15IdYWl2JFvMqBCyocjQvTe7XMXIChCo3XrXLUNmL9LdBnmdmG3KeQfavloLt6SU4tVsSrsKvhGhz7u7Pw/pIUF//I81q1b6NYQd3MmmUhe6vtyv5k+6rbmPVWhavjU8eTto+2uTUgmGZlfqXrH11EsbdxjDsthHXk2NHV2hoTqWA1qj81zkzHuIYRaIiDMqXaxhaY0PCzK/j5fAXP/M62X1tcGnpHFZiyTlGbwXPRmBo0+r7o/KAbUrPOCugs02gBpn0/1FjR7zTsaNQps23fEeZvQabOR+wrnRMVHOtKfl1ExvblmJ5ynj8JJNnFA0AvvRK7D6CNxaHLgcqeyoDp9PgsBWAa/6OsomUQ6V7hd13RyUnYTtzWrakKnhO0AgK1llWJKri1rmZVEtZ1ZoP5+QxlodSdxXoooxLF9rEMyuhw42cqHG4K3VFSjHVlRdhQUeBihZbk1IZAEgEzYwFVOSpDpvXjwhQL3tlGttxWWTJfrmDmtiGLsyeGTjUgQFw2rgYdJcXY1XANXpuZij3T0rG2uNSdUcvAd44DBYbKQBFgcKwq+FblrquaFVSwr5eNq8HqwvLQWbGqoBUw8poysDaGb2Hm5JAiVyWv4JZGhhpUCu70+QpuFVRoeyj44Xuq490CLj2j1v7O9++Gwbd2Y8YtgIoC1hYcM7xDQaGyzmyLt2dfim212c5giAJ5W2pyQ2OVZSfYVoCmQFTHhjUaNTyBz7ZtY41HsqMKAhXMs42VkdRFZ2r4KqDX6xY867vpYwCTWzwA9NIrIQCcd3W9A050Waglz0nHnkzAiV4nSAVPUWBBla6m16BozdMCS2tx87q60whqrDLViVsnWlUiqiR0grcKUSd7VX6qkHldXXZWWWl9WR6CMFWoy8bVYGluAuvLC7FnWjoO3HQZDjSNwp5p6Q4MKouj7If2n4IfGzen4JGgVIGP9p0aCgRXrbF6tMcn4NXpV+G9vxmMV7+Y5p6vilyvUeFzEYgyP7yHK0fXlxdiQ0WBA4nKAFpDQcGfAm0yiJbhWzauBltqcrFvxpUOiNIVF8VwKyjRcaxgT+ugwI2Ah4tv1ADh39ZYvYuPVJBtXbf2fbOuw6iyWiClxoqew6xjk991PCjbpUDOAkA+Y3H2RLw6/SrsrL+2G4PKsrekn1zE8/p1Vzg2WNk+a3DwN13drKBc31Fla7X+Oq65KGltcWnIqCIopDEUlZc1KmxZW9JPbvWk8YCsl21XOw/asa4G2byr6z0ATGLxANBLr0QZQE5YNgBblZJapktzE6FYIk5eUUe3LciYig0VBaE4QgVbPApJlUYU66HKl2XVSdSCSesStaybKgFVrPp7lEuVzGhz6ky3rYiCyQUZH55Wwt9YXrIc+mxlDBSwKkO3pSYXy/OqsaGiAAeaRuH4P/TD8X88E2/PvhRbEzlu2wvdLsQyQZa109Xdtr+07VrSG7uBUm1H5rd7SoY7vWBFvCpUBu0TLhLhWNHNsfmbMjGrCiocOHtjVgp2T8nAqoIK55brCdCwPa3buiW9EasLy7E4e6JT+svzqvHmjZfj+L8NxftP9MPm6rwQELUKns9m3XTcKmBSpk+ZcD5XDQPtH7bpkpza0LO1vTdX54UYbrK41oCx77MCEDVYopgoC/ztKu1FWQ3u/bXGlQWHrbF6bE3k4LWZqdhYme/GvBqfynbbbWY0lECNQM5HavDwL+saVT9r+CzIOBm7ePD2YXhlcia21OS6oyb13eRfAjH1kmgcKNloCz4VvKvBpfkznXoO7HzBfP0ikOQWDwC99ErsWcAKAnULBt0CRZWNKlROspaVs6cTqDtVwUZP4ExBn43b4W9UerpSMyoGTIEqn8dnc5PrKPcLy66uLmUfLLOoTIF1VSvwiVL4VCYsP4FXW6wOK+JV2FKTi4O3D0NX+9U4/qvP4eBtwx0A1GOvLMDsCWBoOo0BI0PINlRFZhkKgk8FytouzakzQwsGtF58rsZVUYGS/essHY99M67E8af64djKdBy+Zwi21WY7EMbxybZX1oTPJ1DaURdDS3oj3piVgtdmpmJRVgM6Soodc/n+4/1w4KbLsKGiwC2y0frwaC51P1sgZUEp07ONNL5Ry6pji/3I73wO07XF6nCgaRQO33sR2uMT3LOUGVKg1pJ+chuhKBaQbR8VJ6cAmuXVUIOluQm8eePleGVyJlbEq0K/8b1RBpKudraBBXNMo2caL8iYik1V8dA1bSO2m2VHo8C/zgHKFDL9injVSUPg5wNw6I5L0Fk6Hu3xCSEjQLfhUSCnz1UXr4I4jnnu76f7bVpGVUMzFMzad9kDwOQWDwC99EoUAGowtyoOxiYpKCBIWRGvClnlCuyiWDwFSpzkGJ9kJ2J7Vqla8lY5KsPEvBgvp+Wy4JTXCMjsGazK4HDPN5bHureoGLX+FuRRISrIVGBlXezKdvIoqHVlRXj1i2k4eNtwvD37Urw6/SqsLy/E4uyJjtHStlBg2hProYqWwIZlVbCnijtqkYvtLwI51pHPIrAk6LCsoiropbkJbKgowGszU3H8n87BsTUxvHP3xdg+aaxTzKr4lWW2+bakN7oVxnriCFnJVQUVzs3Mk2v0NAbtTwXGzFfj25iW5eCxfwp+9X1TZo99pm5Na/iQHVQgqm0dBRptPRRMWECkQFbdkxwXCnhaY/VYW1zq2oLp6NqMMjaYhzKkapxo3RdkTEVn6XhsTeS4uNAoQ8TG/1qwqMbe7ikZ2FKTG2pvjoNNVXG8MSsFO+pizjhgDGsUE6t9qO9glNGl7WFZWmX37BwTlaY59aQHwruAk1s8APTSKyEAfHjEdSHLU9kcBTbK/GkMkyp+qyB1ElRAoSDI7smlMX2655+eVmJdIjqRry0uxdHvnINNVXE30RK0KlugcWTKVFjLXdkQXahit5mwysayfnZyt/VQ5aVlYdtwdeTa4lJsq83G5uo8d26oxl9ZRaNK3pZP+0uVfWusHqsKKrCmqAzNqTOxMr/SxeIpsFcXt62DVYIW5GvZtA0XZk52QI3M59ZEDvZfPxoHmkbh1S+mYX15YSheUPtE2Wjm3xarc33MtOou1zbRuM0otonltouHLMOs37fVZmNHXcwBCZ79qkBbYwIVhGvbabksANHvHOMKNHRBkdZLgQbHuR1/mo8aVPwow0vXp8Y+8h3TLVG0vB0lxXhlcmaoPXQsLcycjI6SYhcrqv3Fj8YIakgGP2r4dZQUY0tNLlYVVHQD0VzEtKaoDJur8/DK5EysKytym3orq6jzpHoONE5PPRD0itDwtWw582iPT8CGioLQzgL6HrO+z6TM8otAklw8APTSK9F9ALnwQyctKk0FFFQsFgCohW8nQOsuUbChK4GjQAT/t0eycbK+b+hstMbq3SQ7Z2ST26SXypbPUrZqYeZkbK7O6waGFIwpS2fdVRYAWMZBgTK/K1hUkM121RW4yoSoa5YgsD0+ASvzK537VdtE8+RfCyDIHiiLoqzcnmnp6PrR6dhZfy06SorRUVKMlfmVofZRVoVtaGO/ohhhZXM1zIBnHyvo4OKS1YXl2FQVx9ZEDjZUFGB1YXk3dsQaHAqKlDHScapsowIprmDW/tbxr8wVr7EuOo6V9VWAouNyVUFFyI2tLKGWuS1W51hqHW8EAvquav0VjClQ0fAM7Tsd+7a/o8C9fixLZtuDc4v2C42xvY1jHODhdWXGrXGkDK9uY8Xf1LjhvfouKvCzzOTS3AQ6S8dj//Wj0fWj0/HazFSsiFe5MmtfK5jVtlBDJGrs6fthgf+ycTVYmV/ZrX0VTPL+Oy++0QPAJBYPAL30StQFzElFWQs9eUAnVu4hp8qHE6O6EFUJRCljgj97XV0pVKwKftRaVsVHRW4ZG2UhrNJrTp3plC8XdFh3orKUFvBykmY7qUsyCjxoPJQynnalpgb3qwKhMic7RteiZfxUSbBc2i7KJC3MPHkU1Z5p6Viam8DqwnK3oleBKPtdjQDN3wLhjpJit5LTnojCNrfAg+CHe58RbC3Pq3b7Hq7Mrwy5XBW8aptru1swwO/alwqMtUw6LjlOFOTr9i98Bwjg7Ikvmk6NmJ6MEJaRiyVsHjo+tC0UoCkYV7DLvHmaDcchT9Kw7CI/CkI1jQXWCuJYV9ZLj3NT4GbbU8GR5kuDR8eVjUOmUWsBoBp4+g6wnrzGfSrfnn0pjn33bBy+Z4hbuKMLV3jf8rxqV1aNxVTQzflR3ejWHa59xe2S9LodKz4GMLnFA0AvvRICwBfGTAopnCi3pSoCqxQtA6CTtFq2FgyqMrDgRRkHdUfpKkcqMM03ysWoCkonWb3O72QuVWmqiyzKFafbqTAt81hVUOEWGCjAiyqTVZ460RPA0eVJpaCnZthFHBqrxzZV8EZFS5drZ+n4ELtilbCCJravutV5PNvK/EosG1eD/dePxpFvDXQrghWory0udYs8tK2pCJknwSP/qrubi5UU0Chg5fghmOQ40zERxTzr2LNsmIIPZYK0zRX4sP2mnDe7G9uo7j991vy0k3Fq3A+Rv22szA+9W2q00JhQ8KRgSMcemSyOCT0OzYIq+y5ZJsq2kY4vDZ94/bor0FFSHDKOtD3V87AgYyp21MXcohXNX+ckW56oucWCaR3T+g7ou64hKYwLXVdWhFUFFa5M2re6MEjnCoJZptW+ZPsoKFWjz3pk9Brbi/V7bNR0DwCTWDwA9NIrsdvA2MmSICZKSaqStgBOJ1QFMcrQKRjg3yiWjXnaEwPscxS02XQ2vQbhW6ZO01mXkmX5+GyCRlVIVCBvzEpxK/7sSlgFfQqiVZm1xj7co5GKmW5uPkcBspZNlZGtF3+zK0NtjFlUO2rfrIhXucD8ztLx2Fl/res/nvZhFZ8qYAvYdDzYODYFXxbEKrulfaC/sQ46lni0lo4DVdoKJPmbGjRR49iyutpm2s/qulcDyTI8dnGQGl7KRmkbKrul/cfyqrHwTMos5/Lmd2uQWEOHddR3ieVQQ0gBno4DBUfKWjKfpbmJ0FY/+tGNre27rEaJ7Xt7P9tGy6VtZwGxvk/2wzJYUGpjf3WefSZlllsFbN3IanAoINc6sg98DGByiweAXnolGgPICcpa56o0rDJQBkQnNzsR6gSsEzWVuJ14eY2M0jt3DQ3FWKmCUSWm97akh/dZ03LrfQpE1A0VFa+zpqgsBE7JvujETcWvLAsBi7rUNW8thwUSnPwVpBL0aRkt2ND2UeXH1a7a/pY5UuBtwTTzWJ5XjY6SYrc1jTKzbAe6jC0QYRl1QY+ynnqiBfuRzB/bg2yLHq1ngZ4CDVXK6g5fNq4mdE1j7+im1DbibxoXahWyBQuWLdetarSvWEYeZxfFXilItvXUexToNafODLl1tQ94bUHGVLTHJ7iV3qwHWSgFwna8qNuWz9Zxqu+8Ahv2mV0sYevM/S/t3ETgqmyY1kv/KrDVsWXHuB0/lu3Tdtd+5XyoYJJhLCyrllvnSwv6bb9qf+mzCP79KuDkFg8AvfRKCACrzrohpIQJbjjB2ElIJ1AqResu1omKFjcnrWXjaropTWXbLIhTJbk0N4HledXur55pa4EQJ3dduWsZElW8zEP3v+Nzbxh8K5bnVXdjZaj0FLQQYPH5UcqO+SiY1N+Zn26loYpIAYHGFtq8tQ0IoHTBjAXIvH99eWHoOQoU9l8/2i3CWBGvCuWpyqs1Vu/AjLJ5lhXWdlLlpq5JAgStP8eRtpftP+siVvBsjREFAxqzpoAxCpTz3nVlRaFxZgG5sun2uWwLZa8skLTAWNuS6blND/uV6fUsX2vURYEnpqcRZVl5HZM6PrRcOmZ0bOjCJl5TJls/XDW8KKsBWxM5IbZW+0zvZX66hY+OwYWZk0PxrdqXzKezdLz73pw6MxRvqm5pdWtblteGHGi9dO5gv+u5xnb8aL30XXsmZZZ3ASe5eADopVdCAPhc6pQQSFEgpwpZ45s4qdHyV2CjzIgFEWr5WuXTnPrhpsJ0j+hk2Rarw5qiMmyrzcbGynysiFdhc3VeN5dJlEuzp9ghW04qYF0AosyFKldVBgp8lEnU1dDz0z7c6kNBbRTrqts/MF+2K5Ui8+F+cHqMlypEdQury1LbXwEB3frKMhIMkCmicrXn3xKE6NjQvo5qe96r/UYXN+vChRVa7qj4PwIWjWXUPlcWmIpbQYbep3WyzJsFL/xNwwT4LnAsaHszrfa5XWmu7KO2mR3HFjCQMdV7NK0CKM2P7cl3ZlFWA1YVVODV6VdFAi8FLzpHWCaP7wnLYcGhsmkco2qkMX/LIquxo6Bcx83S3ARWxKvcJtUsR1R4i85tmo++p/adtHMb5wj+r4BYmUBlBPV+zhnWoFPDUOef5lS/CjjZxQNAL70SPQtYrU1lCaz1zv+5cjBq8mJadc0Q1BGkcDKNCpJWRcfA5/lp07FsXA02V+fh+PP9sf/60VhTVIa2WF0obk0VHe/X/BWcRQEkrSNBqHXn2b25FJwpk6Vto8pEXXlsM2XHbHrWnyyJgts1RWUuQJ1nl3aUFHdz82r7UMEo68LyqqLXMigLpit4FWApsLEsj02vbadKTcefMi+WxdNwADLIbbE6vH7dFaF2UzCohoL2gwI3La+CK8sSquGgwKEncG+ZT7rA9Z1jeW8YfGtoRTrv13ALO1YUFNh+1/eBZ+sqE2qBBfNhjF9n6fjQvpN0ESvYVXCrfaxMYU8xkdoPlinT99IaNzpOlJHXHQQ6SoqxZ1o69kxLd4uctF85TpRdt+yoGkV270ltX21zfa+1bfSvglv+r++6GtYEuUyvY/nhEdd5AJjE4gGgl16J3QaGkyZXWEaBQU6gnAjVwuc2LQsypmJVQUU3a1oZIYIDnXytpa0WNpmNrYkcHPvu2XhlcqbbxJUTr/6vzJUFsdaK5+SqAM6ynppeFT/Lpe2gbAIVkn2mlo/KQuPo9Pf5adNRe/YtIcXHffO2TxqLvY1jsLdxDDpLx2NlfqVTgApaNOCeeWpbP5MyCxsr87u5N+2CFwVyFvBo3RTsavvpmFDly+/MR59D9lGfoXF0umKZ40BZI7KmzN8qZgs8lKGxIMAaCLaddGWy5k+jwTLICiIsQFXDybKktgwWiFiAysVEUYyWAlMFP/q3s3Q8NlfnuT0YLRhR9lZBIJ+n77S+kxqTy3a3Y4Fzh33/FAASPGl/tccnYGsiB+8/3g/Hn+2PrYkcFzOoddP33fa/AmplFnV8ML01hi2zqIBTQ2vsCSYKDHmNfxmXqvOPXwSS3OIBoJdeCQHg3LQPA7VVGarS1glN45T4e0dJMdaXF2L3lAyszK8MxVlxQif7oMxQc+pM1J59i3N5qXtG03BhxY66GLYmchzQUVZBmSlVcMqcETgoy6HKwAIkVaQKBumW1OB4VT62DTUvdZFZ4KQgTevAsunmzZuq4ifPLf2Hfjj+8wHYWX9t6GQDLYfGGCnIteCNdbPuuih2RVeS2jZQt5ztE20bO5bmp03HyvxKtKQ3Rm7AbftKgakCcpab2+RwKxjebxeGKFBVEKMgXNkntpsyNvzO9rhhuWHAFgAAIABJREFU8K0hdpd9pywUy6PbflgFb8eHMrfWINHxynfKusP1XebqX2UB6RKvPfuWkBdgUVYDNlQUYG1xqVsApICT5SETrf1sx4cFmdYVqwyjPoOspDWoWC99n1fEq7ChogCvTr8KB266zJ0fTaCu7wjz1zFtWVS7GpvvlYIzNQoU5GsMoY51LbfOEWwDTafzFb8vyJiKuWkNHgAmsXgA6KVXokfB0Y1iA8jVKtegZk5CtEjXFJXhlcmZeP+Jfm6i3T5pbMiKt5O/WrpWGZIx4XVVKHYLC1VenFB1clYrnQqWz9T/GTel5dIVisoSLMycjNWF5S5YnGXVEx2oNKz7mcrCKjAtc09s0A2Db3Xn1G6oKMBbt4zA+4tH4fiz/bGz/tpum8YSeFgAtSBjaqjN7CIefb4aAspIKGOhgIULETg+rLJUgEJQzT4j6Ivan4358DxqbVvGq/Hs1pb0Ruyoi2FbbTaOfHMQtk8aG3LfbazMx/ZJY11dGE5ANveZlFnuSLD3HrgAS3MTWDauxp1WEgVqrJHAcaAsmG4yrX2hIM+CQ03H9822u+Zp2Wx9X6MMPAUeZLd0/PL94xxBYLQ8rxrrywvx/v/t787d1ufrPMK2iQKstlx6sklL+sk9FC0QVoaOxoYCY9aHYRIbKgqwIl7l9pO0DCnbfElOrTMuLQi0ANsaWQquWQ8FgtrXChp1TohiEvke7mq4JvTuMb13ASe3eADopVeiANCeMmAVEydY6x5RwLW+vBBbanLRHp/gAJyyFNa1FuX6uGHwrc7SJRhQZaeuY1VaClYsc6LlJCvCyVkn5qh6KWhR11YUEFqYGd7axE7m6gqLAn8KAvV0CFV0zKc1Vo9NVXHsargGb8xKwb4ZV2JjZT7a4xNC5Webt8cnYGluwimNngA2wQVjKxVcKFBT9tAqRAVqUSyNMrDatup+VkDI+7jfoIIAMssdJcXYVBVH15zTsTWRg9ZYPd6973M4/lQ/HH++P3bUxRzbxboSNDKeVd2WbbE6xzDzNz2fmCCXQIjgo6OkGOvKilwohB27rJsFQwqAlCHUsADLUFpm0jJLljXUs4/1vbT9o6BP3fgKcPn/mqIyHLx9mAPdbbE6rC0uxYaKAqwpKuu2FZB1USvg5TjT98aGE6ihoYBsQcZUbKgo6LbamfUmKzlnZFNoZTPTcMHIzvpr8eaNl2NDRYE7SlKNRba3ngSi5ea7o6yyznOsg7aBZfxsn/Aa66Jt2Jw607uAk1w8APTSK1EAqBOvMn0WFClLp65MKm+7956CIbXqLTNhgZ6CTr3GCdtOomQrmOa+obND1rWCDY3BobK3qyaVOSQo0mtc5BDFmChwYd1Ybqbl9ijc345tSEWgKwm1L1rSGx3IWJJTi+V51VhTVOZOHLHKlbFzVDz25A1VzlR0VHDq3mpJb8Ta4lLsqIt1O7dWlZi2IcdOlMvTgmcFeqrwFmRMDbkp1ZWrSrMtVoeNlfk4fM8QbKvNduBlQ0UB1pcXdmO9OIa03pZZ64nlm5823bFKLemNbuwsymrA4XsvQtePTseuhmtCK5K1Tnx/CNx0jOo7pXFiCvAsKFqQMdWtLufvup8h77MLcxT4a/iBxgva8WePb1SQuCDj5MbgexvH4NAdl+DVL6ZhU1Ucy8bVhPpN29waiFoeC5D5znMcWyZR06uRYN/BNUVleO9vBmNtcWkIBLLs7z/eDxsqCrA8rxqLsk4eQ6isprrFtQ76Tmm72XlI66tzqt6rbCjPO1fDV98l7wJObvEA0EuvRE8C0dMEFDCpi43MjTI8yiKQLdFJW8FGVGydjfPS31RhWMAxP+3DLVW0XKpcdGK17hwqLwVvqkAsOLJWt4IIBsTr1jHKxGj5CWZUaTAPBb7KACmT05J+MraJDN2irAbHVvGaBWRU0szPMjsKynWzas2f95AFY1k4NqL60AIUqyz5GxWcZTgJGpR11eB4XTBAULAyv9KtgNZ+Y13Y5xYcMT2fpeEA+gy2mY5P7S8yrQr+9fnsn4WZk7GlJtd915hZ7RONO1Pwx3rops22vPadUdClYEbdx/oe2XGvDJb2r/bF+vJC7L9+NN7dlsDB24dhayIH22qzsaaoLLRwjHONNezUaNR3g++pMv9aPy2Tvgf2vSZjvH3S2FAfcz6hcbW6sNy5g7fVZjtGkMCcZbUGi/aDBYRquOp1/XAsEYQrGNStkfR5/izg5BYPAL30SnQfQGVfqHhsHJIyJZzE1JWlilGD5XV1nv6mk7xd+GEZA1Vui7IanItNwZQCFp4bq0wHJ13d54yKxy5a0UmdStYujrBgVdvAurmV0bMsncYuaV04wXeUFDvGg+W1cUnMk/sBqptTFSXrqIyCVfLsdy4ooStMlQ7Lq0BU87FHyhEEsR8JhvgsdUFbd5+Wk3kqcCewUwWrY1jHJJ9nmRd9toL/nsAPf9O9F8nqRj1DQY6+J0tyarGurAhrisqwPK/axRjqKmc9cUbz0r0YFexzA25rrChrynrzGVGxp5alVde9jm91h7bHJ2BHXQxv3ng59jaOwYGbLsM7dw3FvhlXYn15YchDoPMKDQEFpjRILCtmGXetjxquaijYuqiRp9f4/pBV7iwdj65Hz8Abs1Lcohcd0/qOaxmaU2d228eUf1lmvU+BrwWFNC7JJKoHw7uAvXgA6KVXYlcB20UTOkGqglArl0pf2S4FMspuqQLTxRXqZl4Rr3LB+QqyNB6tOXWmizkiGCAImJ823cXBcaJUsKRgwU7mqnB5H08MUIDA8hO06GbT6uZWRlDPn1UApQqL97MsS3MTWF1YHmKDohhW5qOxWwTQ9nkKQnUBjmUvWtIbsTyvOtQHBKrMg+3IlZV8Hp/FOlOhcqEA24bAkeygsiR2iyHrMoxiYy1LxzGmLlMFE/zoghLNk2NQQZaysrY/9GOZNmUM2Y4KYJXN1HquLS51/WKPpdMxq2BawRXzj8qb7x/v0zNyFeQpSFfwps9Q44BbFO2ekoHjPx+Aw7sacPieIdhcnddt5bB9lo5jHa8Kyvk8fY8tmNd71chURpB9wDhFOxfw/ef2N3aBlZaNz+aG5Wwv9psaBBru0FFSHCqvMqpq+FqAruPJM4DJLR4AeumVKANI0KMbNaslboGbMgAK/JheY+BUQSqY4f+qdNtide5ILR6UrgBJFaAq+QUZU7G6sBzrywsd+FHmy8bwqLJWBcbPqoIK7KiLherMcurzLXhkGjKOarnb9tOJn4qC7aJgaWHmh4tLLJtqwcyKeFW3UzxYXo0T00UwZGUs2GfQPAEK68prCzJO7ve4qSqOjZX5boUlF5joqloyqWxnjXO0AF0VPBWxMoZR7I3mR5BvATbLrOyKTdcTE6i/K9hRJpxp1c3JskWBHh2f+g6oYbH/+tFYmpsIgTjGca6IV7l3dklObQjAkgm3eetYZZvqsYPKoimQ1XGk8bo6HhXcLs6eiK2JHBy8fRi65pyOA02jsKkqjqW5idC+mArk7XMVGGpajtGtiZwQWLMg8ZmUDzdyVwNIf9dxzzLQ5axsN40ULYeN09U8ohhOln1zdV63ftGxpWBR20WNZh1b/ii45BYPAL30ShQAckK5b+jsbofRq4WrgFCVt05ampem4/3LxtU4JWLzU+CiblsFiKrA6J5sSW/EroZr8P7/7Y/O0vEhxbs4e6Jzr/HsWmUzdBImwFmZX+n2o9NJXZkuXSihzJqyRPPTPtyuQd1/mkYZnpb0kzF+naXjQ4BB8yZA0P3u2B6qoFSZsC3tCmhlqpSxUMWuiznIcBJsbqvNxoGmUTh423Dn4iPbx7LoKRNkiKJAEJ+lK191ayJbL7bLnJFNIfaKgEb/j+pvgqkocGlj47StLEBRBU+QzRguBZitsfpQHFwU2FEGlCdX6GdbbbbbZqktVocV8SqsKyvC+vJCrCkqc3WxgE3BWluszhlJ1l1txzj73J5sw3zYp2uLS0PvaWusHqsKKrC5Og+7p2S4OEBdhGSBdBSDp2ODrL6OQWU9WdaeGEMF/vzdgnBtBy2PLopRIGhXuuv4VZCnDC/z5oIaC9B1IYyCY12Ao+Pny+f7o+CSWTwA9NIr0UUglrlSRkAnbLXSlaFS5WVdNxo7p4wM7yXbxTTKLnAiJJukwMouPlg2rgZbanLdZsWLshrQHp+AdWVF2DMtHUe+NRAdJcUhBkPdRwocFHCRsVLlr4pOJ2WyLhobZRnIKDDB2C99plUsqpAtM6OLC7RfFGAoM6ZAkc/TxR4ErtZ9qmVcXViOvY1jcGRDEY7/45nYPmmsixtkeXRfP82L+ZC5U1DPsrL/GfPJ3+3+fwsyTsbSbZ801vUB+4aAY1FWg3Opv3P3xVieV435adOxIl7lgH5HSTF21MVc/ci8bU3kYPeUDOcKZDusiFdh2bia0FjS/ib4bY3Vu9XaGyvz0VFS7NyJdixwXNuxb8cj67apKo63bhmBrkfPwJ5p6aEYQq27spD6HvK56pLW97MlvdG9nxwDGs6gIF+3FlqSU4u2WB2W51VjRbzKbQ1lF8Xo3KLMKfuPYyZqc3M1xNSYZFkJmNSA0Xt1QQnrvTh7YoihtGwe66igTuc6fa8IipmPGsfavjTmuM/kmqIyrC4sx9LchAOfylo2p84MGek+BjC5xQNAL70SZQA5wSpo4+SlW4loGk6CGlujFq6mIRtIVxUVuYIYZeF4nb9RUXDiI9CiAlB3pgLSjpJi7JtxJd688XLsqIs5Zo2Tsm6SrMBPJ2lbb9ZXY/ZYdlVCvFddsgQ9jBVSV5+6tKjEuJhFVw+rO9YqdW1H6/bSMhF0qSLXdrQshjJCbP8V8Spsrs7DG7NS8NrMVLdSckHGVLcSV0Es81FFrH3NNmK5dQGLggFlLzmOCCQVZCorR/CxNDeBztLxobhNdf0pQLcgW8u3KKsBK/Mr0VFSHLqH5Viam8DGynxsqopjSU4tOkqK8crkTBxoGoV9M67E5uo8xxYq+6V/Ldupz2G99jaOwfFn++P9xSfz5Sbh3IuPWwPp+6RhG9r/amAoy6RzgvYJy7E0N4EddTG3qln7XFdz69YtrbF67Ky/FiviVaEFWHyXdP5RNlld7Zpex7IaQXyugjVl1hTkaVuo54G/6Tuj99i5Q9tX/yoYtIbgkpxarC0uxa6Ga7C3cQy21Wa74zQV6HKMKQj1ADC5xQNAL70SywCqRcqPLmrgpGMnOAuadJKLCl5WZaSTrY0n0lWVWq4oF5IqaLI3ZASPffdsdLVfjTdmpaCzdLy7Vy1rzVMna12dq0pTJ+YoZaSTtCottpMqUnV5ap6LsydiZX4l1pUVYW1xKdrjE0LbmSjYU2BHgKmgRs8HVuZDWT4yRzcMvtXtP9acOtMd4acxfFTirbF6dJQUY01RmdtsV2PYlD1h+3HlsJaT9xHwqjK2bJMqeR0/On4JGDVf3YpFASKvKfBWcLqmqCwEiJSp0nFj2fI5I5vQHp+AlfmV2FBRgIO3D8OR3+fj+PP9sWdaOpbmJkIxeDZfy3zxfdJyrysrwqvTr8Lr113h9j9cU1SGY989G+/e9zm3b6P2A/uO9WUbcixYNl9X0WpZmaYtVofD9wzBq9OvwqqCim4gLYrpW5qbwBuzUrBnWno3l6e6WPU3697VfrfspS2/pqdhRZc5x5eycnz3FShqGsvM67uowM+OTb1fjarF2ROxqSqOt2dfivfbLsOBmy5zxgPDXBZlNYQWljFvfxJIcosHgF56JQoArWVqFZFa5Oqu60lJ24lPAVtHSXFowlQQY1kenVzVHaPl0/wVZHSUFGNzdR7euftivHP3xXhlciba4xNCLmfLLunqOwW+a4rKujFCCmxUudl4Hi2zZZnYtgpyGSe5Il6FXQ3XYP/1o7G3cQzWFpdibXFpN/cZy6/uQdZhzsgmLM1NhFymqky5WIB7nPH5VOyLshrcMWoEU/oM3q+nZrB9bbmozBZkTHVKjS7OZ1JmYUddDKsLy0NMDtuRbAg/ysCoe9oC1CU5tY4VWzauxq0Qt2k1Vk/HFMGqnm+r4FLrYAEkx0lz6kx0lBTj9euuwPGn+uHod87BzvprsaGiIAR2yV7THWhBqrJQLOvS3ISLGWWM3bqyIhz9zjk4ujYHr06/yrWptqttsyiGiwylLuphH+t4n582HasLy7E8rzr0DJ1LOH+oYci86C5m26mLmONL5yQ1xDQ2T4GgplXjk79zTDGs5KNYQXXxK9DnmNT5Sxe26ZymMYAKVnltaW4C68sLsW/Gleh69AwcvG04tiZyXJvbeVnr98KYSR4AJrF4AOilV0IAOO/qDzcPVgCglrYyX9Ztp5MsAQmvqztP2QcFiZyQNV9+twsbdOJTkKAKhmwXNwXeXJ2HrYkct5/e4uyJ7lxQneCte0gne1Wgtr7KUlBpsh0JHBS8UKlqXrxXV+CuKSrD27MvxXubSnD8lxdgayLHAShlFpmfAmBl/7ReVPS64pvtTtBBRpLxbQTUCgKt23RR1odHpdl4sPlp0922Lx0lxdjbOMYd22WVooYbqEuXK4x1Cw1lUcmitKSfdKcRGK0pKnMxVSvzKx3YsNsaMT/WRccfAevyvGoXW6cGjX5XZob5EhR3lo7HttpsbE3kYG1xaTd367JxNY4ZI3u9q+EaB6yUIWS+avCw/bnR8atfTMPGyvzQhtr6PAv4nkmZ5Y6103Fh3ztlDnXeUOZTWW2N39R3iu2mm5Mr+7oiXoVVBRVYmV8ZCu2wTLy+i/RQtKR/GLvIsqu737J+Go5iGT7L7HEO21QVD72/akDp9lb8jd+jXOytsXqsiFdhQ0UBtk8ai83VeVhTVBYyGK3hyXnabwOT3OIBoJdeid0H0DJwnKR0tSsVDydKtah1koqKyaG1rkDPukuYt058GvenzIXmwXuoxDdVxd0EujQ34U5oIEPyyuRM97tllqyFzjg/VVJ0YWp6fldlp8pBXZIWbLP8qhBWF5Zjz7R0dD16Bo58ayA2VuY7BW0BsW1Ty+hY9kJdgFpmBawEosoOksljf2j/LcmpRWus3gFvHqW1NDfhzi1me+vJIMrAKgizbK/G4CnI4CIRgiTuQ9dZOh5banKxoy6G7ZPGYlNVHO3xCW4lrvY9Y+V0DLKcy8bVuBMiOkqKnStemUS6yKOYRea3JKfWneLCRSgWlGnf7b9+NN5vvdSxz8oyWqaSf9lGZDu5l6OGDOjG3hrioCy4BULK+CnY4fuuC0W0T8luaf4Eq2wLfa+Y19riUmxN5GBn/bXYXJ2H5XnVoXGoRiJBlYItNSoUmKvRxbrq+6EgU8GoGn/6v+4Tqn2o4FHHiJ0PtB5cgEKjhcA/KtRDmUcPAJNbPAD8jMmSJUswYcIEDBkyBEEQoKWlJfR7EASRn0ceecSlGT58eLffv/vd74by6ezsxLhx49C/f38MHToU3/ve9z5VOaNcwLrJLRdvKKuhVmwUI2AtfTthWhDJ+xU0KgCzW2aoFcy4JVWaHSXFWF9eiFcmZ7qYJgU/i7MnYt+MK3H8+f7YWJkfmoRtvvxfY6BUeWgclNZXlYCyE7aN9JmalmxQe3yC29uQqwLpsmLbKMvKe9WdpmykjWUiq2bjPKec9+H2PbpNjzLAdiUywfmqggrsmZaOY393FnbUxUL9SdCkjA/bl+BdGVAq0fuGznZskR1zCzJObkezpSbXLe4gAN2ayMGBmy7DkW8OwuF7hmDfjCvRWTreGQPaT1oWHRNLcxNYU1SG3VMycKBpFN688XJsqcl1YNcewadMtCppPocsqm5fpGNbQdmqggo3RtUAYZ+R+dV+ZdsRDCkQ0n6ybJmOb31/7bngFhBZ16uNheNYX1tciqW5CSzJqcWqggp0lBQ7A0FZTRoWm6ri2H/9aBx96DwcvG04ttVmY2V+ZQj0Kjtt2Ur2pRphCuz0XWdeCmx5HxdwWW+IMqRq+CmI1zlP5y4+W1e5248yjTYOWcfqnJFNfhFIkosHgJ8xefHFF3H//ffjX//1XyMB4L59+0KfZ599Fn369MH27dtdmuHDh+Nv//ZvQ+neffdd9/uhQ4dw4YUXorGxEevXr8cvfvELnHHGGXjqqac+cTkJAL98/o3OFcOJz+5RR8WtLhHrKrZn4VolocqCE12UW0a3UNEJlArLxhcyv7dnX4oDN12G9viEbqsVlZng1jBLcxOR+72xHOvKikIMmoIpLpJQlyjLQ1DK+lkApkwW7+OJACzD9klj3apKBbrKGLCtLCuqyojXeT+fT0VCgLUg48MFIVpGvUdZM1WErCtZy2OPnInjv/ocXr/uCqfAemKsdLUxlaLmb5lVZavmjGzCsnE12DMtHe/e9zm8dcsIt/J2fXkh9kxLx/tP9MM7r34Zx38zDO/cfTG21WZjdWG5YyDV7c6yLs+rdi651lg9Nlbm4/A9Q3B0bQ662q/GgaZR6Cwdj72NY9z9CgAVEClwtsyssrAaMqFg14JtZTsJfgic9f1S17yy6gowtF11NTtBtTLrUa5XZdQU0CuAtowXTwjZN+NKbJ801hk2bD8C6q2JHBy8bTiO/D4fR745CDvrrw0d7WjnADtXWACm7W4BunXT2jFq3a76fAW8dp5TV7COfQV4LeknFxntbRyDlfmVIaNMy6mst/b1MymzPAOY5OIB4GdYogCglUQigaKiotC14cOH44c//GGP9/zkJz/BwIED0dXV5a7dc889GD169CcuGwHgwyOui2R89DgxPZOT6SxQU/eZToo2XmtbbXbImlalzslbVy5ay5pKURk5sjXryooiA+Z1Ml2SUxtyQaqSbk6d6ZSflkf/V4ViJ38qXevyUeZMgbGCQXUL0R2kDADdgKpQFFQqQCQI4LUotyHTWFBqt7JRNklX6SrbxLi75XnVznWnG/9qrJWCnubUmVhTVOZYQXWjsi7qTmc52TYdJcV465YReHdrFY7/8gLsargGh+8ZgvXlhdjbOMaB0ePP9MM7dw3F5uo8rC0uDW1GrUwdxwXdlHRfv3PXULy3uRxdy6/EW7eMwPryQmyoKHCAinVU97mChSiGT8/FVSDBd8iy7WT8+H5YtlTHnBpzlp3WsilgWZlf2Q3AzhnZFGLYLEuq/cjrbFcde5wbNlQU4PC9F+H4wovx1i0jnJGj74bGir51ywi8MSsFm6vznJueZdRti1g2O0fY2D79KGBWBlJBJD8WAGsbW2PLzlkKgm1Zm1NnYmV+JboePcMdN8e5jOBeDWY19ljWeVfXewCYxOIB4GdYPg4Avvbaazj11FMxd+7c0PXhw4fjwgsvxKBBgzBmzBg88sgjOH78uPv9S1/6EhKJROiel156CUEQ4K233op81rFjx3Do0CH32b17twOAusWCWqoEEeoKJhuorhBVAlGTICdXTuJMp0eccXIlu6YTswJEncDVelf2gadD2HqxzNZVZV2xBKAKhvhdF3Bo3bRcOtlbVy/LqYCB9bYuI/aBxiopG2dZGQXwWsYoJkTZN21bVZ68TsChwe1sJwWgBIl2IYjWWdueZVQQpqB6aW7CgU9lkVrSG7GxMh+rCiqwt3EM3rn7Yrw9+1K3cpJu4ddmpuLATSe31Xj1i2lubzxdrBPFWnFRCVeT72q4BgdvH4aDtw/D7ikZbtsbBah69jHZLAX2BK3sb8ZbqitQGTwFIEtzE65dmKeNCdQ+ty5Ry5wpOOT7rfl2lo4PMbxMyxhUbTd9hsbp2bHF+LbXr7sCXXNOx5FvDsL2SWNDIQv82xarcxtnM56XC3CU4YzySFgQS/BpjSA1LDgulZnVsahtoDGU1oC1rKACNfaLGpsE84xN5bZBdJOvKqhwG5LrnKLl9gxgcosHgJ9h+TgA+L3vfQ8DBw7E0aNHQ9d/8IMfYPHixejs7MSTTz6J8847D1/72tfc7yUlJbjhhhtC92zYsAFBEGDjxo2Rz3rwwQcjYw/npjV0m6js7voWCFmrl39tbKC6GKPAjw0414lT3VI6eVpmQ9MuyJjqVphSKXMbEFVW/J/spCoRXVxgmTZ9pjIoCr4U6DINV6hqfhaQqkLi8XEsk7rvFJjzo5sKsz5c6avKMcplZV1SjAG0TKqycMpKRgFqdVOrYRDFzLLM3FaDjBPvUVaQZSXAXJJTi/Xlhe48Yi4+WZJTizVFZdiayHGfjZX5WJlfiWXjatxRagr81MBRIMYVvFydubEy321grMpYGSxlvtnWr0zOxL4ZV2LPtHQsG1eD5XnVbp9HrtZVo0KNHbtYQ8GdAnEFFjpOtM90rNn82LbsPwU4akhp7KgaOBbg6H2tsQ+Ph9vbOAZ7pqW7d1Xfb+bD/iXQ1jFlwZANi9A5I2qu0mepEaf9x3t10RvHuYI9Oyeo0RnlDlYGkHmR9VtTVIbO0vHYUFGALTW5buGRrkDXNmhOnekZwCQXDwA/w/JxAHD06NG45ZZbPjaff/iHf8Cpp56KY8eOAegdAOyJAZyb1hCazJSRsC5UjX1RgKPnVCrA0Pw4ieoEqZMZ4+DsBKmuHGVBlBHjhweta1kYfN4Wq8Pm6rwQ40bFRIBI1tCWQzfk1UndTuQWsCj7pveqm1Djv1RRWcXF35Vt5W/q7mVfkcHTkxCs0udiBuuCI/jlAgemXxGvwg2Db3VtSBaKK2NZriU5tdh//eiQolXXuCq91lg99s24Eu8/0S+Ur8bIsV3VgOB45PYpul9dW6wOqwvLsba41B1F1lFSjBXxKudKJUDSWFQFgbzOLXC4tQzBI0+oUJBmjRgFDpbdW5TVgJ311+LV6Vfh8D1DsGdaOjZX52H7pLEu/ELHoR0b6tZVAKdlYR5cfLG6sDy0AMUaVQqO2Nbt8QnuWDPtP323bexce3yCe4YaVBwbK+JVDgDr8+anfeiGZ15RYzaK2VTQaUNE1Ajhe8eV2PyNc4wF4Cy3GiVq7ClTqoBX89A2VmOGvzPmlKvl982L5TLwAAAgAElEQVS4Eq/NTMXexjHYmshBZ+l4LM+rdqyyttljo6Z7AJjE4gHgZ1g+CgAuXboUQRCgo6PjY/NZv349giDAyy+/DKB3LmArGgOo1vOGigL3v1rMyvBYtkldOArU7He12HlqgFVoyk5w4mQ6GxxtmTAth3VFbU2c3BhXwUgUg2ljt6gQbEydBadaXgVi+pdlswfBs47atupeZNmYvyofBR6WIbTgUduPZaTL1jIpGm/FPJSBU8CrSnNh5uQQyGC76Ka2i7IasCJe5cpCgKLjkOXVdlXArcDXAgZ1lXM7DQIPBXkWeFs2mPWhkaCLNAiQtY3I3nL88C/BeGusPrQwaFFWAzpLx590VTeNwhuzUrCpKo7VheXuOD1tM5aLRgZBj7LlClYIXtrjE/DmjZfjQNMorCsrcu5oHctsYwXeZAvZtnYrJv6vWxjZ9lDwpu+zxkAy3Q2Db3XPVyPRusetm1W/a2yeDS2gN4KAn32lHwWSDCfQdtK5wfazpuHz2D8KmAl0dU5YmV+J7ZPG4rWZqTh0xyV4977P4dAdl+C1manYUpPrFi/p3NOS7vcBTHbxAPAzLB8FAGfMmIHMzMxPlM/P/z/23j22yvPK96czmlybllahTVKSKDdC48TFNmbj2/b2xnh7e/sGtmzAKcgRAU4U0iiTKkomv05HVWcyo/4yOWf0a6eD5pxKtNNw5pzSeuQZKsogGDO2ZSxjC2NxpyEQciHh0iSAR2f9/rC+D593eTOasXSkSH4fybK99/s+73N71/qu71rPen76U/u93/u9AO60CeTatWvhmpdffnnGm0DyCWgKV2/h083jXR50weRjF1gHASUtZykI3u9dz/xfMVZDqawNJHPT8tlJkehZvo3qp/pEQEXr3rMwAkUEaVJC+XZPqt/D6UzIIeaD+BnwrSS624u6IswIY8kI2KQs31u/MDB2VIZqjxIzE2TqcwE49onzRRehQBhZU4IysXE+ZY6UK+eGfRI4ENgRG6exoCtMG0g4FgTcvFaueDGFmne6R7lW9Lnvk1+LXKNc11wbdIVqHLcXTaWGufzyXba7bEWIsVMuuMHqBjvVsTjEI/LUinyGgNYdwfLWgm7bV9VkH2xcYNd+dJMdbSmPJEnmOtKYkb3S368/vMkGkjk7WF9jPcWrbSKXtJPtSyLjJGDC8aEn4Ubvr94png1MQEe3teSC6qWc4twLfGltbVm43jbMe+6G4FFjy/d9T3mrXfuvN9t4NmW7y1aEtrDdDDfh3HtDks8UAJSc2l22IsSafvjsg3blL263K8MJu/Zfb7aLL9xrb3WWBBaQa3Vb4Vr7WWFHDABncYkB4GesXL582UZGRmxkZMTmzJljr7/+uo2MjNhvf/vbcM3Fixfttttusx/96EfT7v/Xf/1X+8u//Es7cOCAHT9+3H7605/avHnzbO3ateGaCxcu2Fe/+lX75je/aQcPHrQ333zTbrvtthmlgfnDezYGINJX2RxJGUKQROFO4ETFS4VI4eyt8p7i64Ht3pVFBUeL2TMdtPAZrH96VbEdrK8JbZPSpxIhcONuXbIgGpN87iiCQwIwKmOCWYIqPUv30K3E+CO1fVeiLbLzVmPLDRgEGocaqm1/TX14jp4v5UZwJQXdU7w67EAkA0Lgyn6rP9o5yg0pundnYuqYr482PxBJGs1kwlKEjCn04EbP1tjQZU7AQte+GDuCSYYKELCQyaZy1TgQGJHRJOChMcS55HgSEJBNFTBlXzUGGueJXNION1XZWCZtb68pCilqPFuptUf2clvh2kh82f6a+gCKCJjIsKkd+YCbxmsgmbMTbYmwbvz7zz6oXgE8jr83FLVLn++KZ3m3F02lTuI75Vluxtv5fIcCh9uLuiJsPA1dtflQQ3U4D1r1EthxbRPoe+BHuap2aB52JtpttG6ZnWxfYh9sXGBXXvu8XRlO2ORPb7NL377H3l5TZKN1yyIMrH5iBnB2lxgAfsbK7t278262WLduXbjmxz/+sd1666124cKFafcPDw9bIpGwL37xi3bLLbfY17/+dfvTP/3TEP+nwkTQX/va1+y11177T7VTAPB/FKwKwopWsGfqJCSpnMleESx416x3nSgYX8+gEO4pXh05EzafG5AKRG6aY61l9sl3v2xX37jFTrYvCUqS7dC93kVKZSGlTZc22RAp877KZjvWWhY2uqhusghktAgYyTASVHE89TyCDYJLMhXM+0Y2jOBDQGVnoj1sMiEzx0S7BBNkePIxGQJxetZQKhs5J1VtUhv8jnLVxQ0TWwu6Q51k46gwCVR49BhBgxgW9YN5CRnrqPYpvnFrQbcday2zsUw6xP0xVlTriYmSVS+BD+ea4+rd6zSm1H6yVxpHtfu99Qvt7TVFgZEkmPD18/3lfHrjwJ8ZTPer35CzM9Fub68psssv3W1n1z4ROSvZ91fjRaNNc6x2c92pzYwV9TJEdQg4E1TzveE8cT17QM85IHjT76FU1o40V0TkGQ21fG1UeAhliK9X78CO0g7bX1NvE7mknX2y0C6+cK998t0v2+9e+Yqdf+YhO9Wx2A7W14QdwVxbMQM4u0sMAOMyo0IASIBBK5qfebaFIIAAiZ+T9RNwEQCjwiKLKIVGcOYtbgpuJXc+2b7EPn51nn3yJ1+yUx2LA6CREKbLSAKbGznIKOlHcVgEkLxW/RNjQSUk4MddjASIBA7qu+qUpa/x9gCWIKS3ZMr9/cr8zYHt1Bhrs4Law7FQO9V2tZMuV64DskFSqr0lnfbOusfD+bVi/ah41Q8xJVwPmgP1mf/rM7GWI7V1drJ9SQCXZCnl6hZLqDGgkaDxU6JwtZXxcAQyR5orbDybsnefesy2Fa61k+1LImNPAMr160EI1yw/Yz+9W09zl4+V6i3ptMHqBttb0RIAAa/nM2kg8H5+xrXq0wupf3oG2V0dkTdSWxdxvXswrPnmWNHQ4rtMcOP7LjY9n4zK90OwRoDGdhGkekOWruLekk6byCXD2pZLmQCbaX/UPrrDvTHAdikVzGjdMjvaUm5nuhbZu089Zu8+9VjYCDKUyobNbKpjw7zn4k0gs7zEADAuMyo8Co7CVgCPCokgUEJzKJWdFtxMNygBE61+Cm+BBNbNFDT5BLSAnOJhdpR2hCTQx1cutRNtCRutWxaAkXft+R3FfK5nKvS9gKoYogPLayNgiiDAM2b6XIwb+5OPGSK4oeJSewQm1DeOt2ehCBLpJv1g44Lg8vfXCkx4lyndlJrLE20Ju/zS3Xb+mYci+dx0zYZ5z4WxGE5nIiyWby9ZGT1nb0VLYBTfXlNkV/7idrvw/H2Rk1Po+t1acD2w3/ffg3b9TSOA//u50Gee2eE12wqvn27Cte4ZOe8ypVHDtaL3j88maGMs6+6yFfbBxgV2tKV8GutGEEUAQuab7NhgdUPk3ee74ceLjLw3EDzYoYHnz072u2b5HBpM6i83cBDQqR66XAnEdA/DWfT++4T3fCZlCNeP+s95pnHi14b3rnB9Kn3RWCZtR5or7HBTlU3kkuEMavWH7HnsAp7dJQaAcZlREQB88xvRXXUSUhvmPRdR9lKuElzj2VRkx6OEKJktCjnvWpEbsrekM+S5orAUC/bvMXV7ylttX1VTOFj+wPLasIOS9xKYqr1ktPQ/4wHpaqKyULwOP2NcHNkVxqzlAzq6luBQitgrZYIJASMpD7JFao9++7llfkAqKgIeKnjGOHFThtqqjSp9lc0RQEGGhqyZlCWVK9koDySVQPhUx2L7YOOCcOZvPnZM7WayXo0D16N3Bep5mgMPuMikcT1w/XjQlw/AcxwFqJlYnMCOjBrXJDfD0EjRtT3Fq0PaG21c4HgSLOlZZPTpRtZvsaQaFz6brmqNjfrJd1q7aT0QozuY86V1xv99HjyyrTS+dB/HhXJMn22Y91xkHXrXrJ8DXXv2ycJIjk2yk/QgUB5SnlI2sG7lPdRmNv2WfBRDzfbGDODsLjEAjMuMigDgzwqju+lWzd0chJc/SqmnePU05olMCmNTCFzyMV0ERQfra6adrCDBTrenlKAUgnYiHl+5NACirQXRI+kokKUkyLDxeVJabLvcYgQtBFXqx/GVS+3Ka5+306uKg1tVwE67bpUGhACUCpdjpHrJwmlDiBShjzmUUtSzCdR0LRlX5sGjgiN4YdwbATFdgnw+GSeCJs94kLkTsyql9sr8zRFg4uP/GOhP8KL61UcfV0hg43cvc/wIMDTOdPn6uNR8/fbMIevmPGoeZAgRQHOdEuTQ3cy+q5+9JZ0hnRMBUr7rfdwv30s+Lx+Y5ftDA62neLUdWF6b97g7vmtaH5QpnE//o81QzG1Jo6W3pNPef/pRu/Ti/PAO8D3gXGk9+dAUvt/qF3dCyyjJ50ngxho903tTuDZ0rQ8HEBso0CdWnjGY6nPMAM7uEgPAuMyo0AUssCfFSXaLApOKMR9rpvu9pS/ByyPkdJ2EqVdMUtz9yUbbX1MfAS57ylutr7LZznQtsk+//wW7/PJddqS5YhrLQSWsZ0twE3BQmVEh69gwKUBumuC47ClvtfObHrG31xTZ1TduCTFpZBKYEoUAjoBYbB4BGAHiaN2yiNJjG6RA2H8q7L0VLWGuyNZpDqiAxXIebSkPybXVBoE1AmyOJ5WZ1sSO0g4by6RttG6ZHWqoDnPuAXk+5ch1wd2bcktzgwLdfh60UlkTXKmtNB48+OH6YX0eUHG9k51Sv5Ro3IOLrQVTcY6KYVU6GG8scNz1zhLIsE360W57HafmY+nUH8Zrcj2pbR9tfsCONFeEDQvaoc41TmA6kUuGfrA+ygGygARHNCi4xvqTjbavqsn6KpsjwFNzKpA4WN0w7T3gnHNTFAGm5sWDULZd69l7ODinSulzqKE6Iou0PrUGJPe0XmjA8f2S3BnLpKeNT3wSyOwuMQCMy4wKASDdH1TIntmhi4eCj65QXUuAIeUiwcZdmxKYFJS+Dip1/fQnG+1M1yK79qOb7PLLd9l4NhXiAlmH75tnILnhgkybYnEO1tfYYHXDtBQtVBbaUCCXqGdbthZMxSzKPc08e2J9qLh1j9pDdkCbOshe6V6yRAK7ZP/EHlBh0x2s/u0onTpV5aPNDwTgwHvEAGqt8JkEDRqj8WzKJv/udrv04ny78he320htXWROtE7yMV2ekRKjyrVHlxtDBPK5PQkwCQpZH+eX4C2f21c/dG3fiNFV/CDBBZnFkdq6kHOOIFbvUD5XKcEqQYM3wNgmbR7xRoPWgtaAxlaARkftjdTWRRJji9HkfAkgDaWyEZe6ABCNKM8+CyAqxITywrNrXJd813U8Yr7NImoL557rxINFtk3rQwCcMX+cU8kojj3XDNtGo0/zsrtsRQDZ+eSYdtT/4T0bYwA4i0sMAOMyo8JdwIrHowVOlsMrMiZEpQUu4ah4FypZfefZKSpnPt8rA14nlo4slax+ukWlFHhWLoPTybDR1by/pt5Oti+xjzY/YOc3PWJHmisiqWMIlqjEfHJjjZU2MVx6cX44C5axgQRvUlA641bjT/eU2rqtcG04u5fgWMwM2VrPLjCGieBqf019eA6BKl1k+RgV9YPnHlNR76+pt/PPPGQXvnW/Dacz0wC/Z13UFypLsmKeteH6UYydj4Fk21W35m3V3M1BqZO9FeDQ9T5/3rbCtRFmj/0hk02AyHdIbSHLKIChzz3I8WmMVLfc+Yz947vHNb+nvNV+98pXIkCKm5RoCHL8JnJJu/Ct++1EW8IGkrnws7eiJZJLUu2hcZBvVyzXDo1LGpAeLPJzyhEPwPU8vvN+7vkczQE/p0GmtcBn6VoCTPZTsoAGrTc6fP9kQLEPjAvlDv0YAM7uEgPAuMyoCAD+t0euBymL5SAYlLDrq2yexnroWv3kY978b9XJDSS05Kl4qfA9i6EYmb7KZttdtiKcK0th6l0rbBeVvRS4hPtYJm3vP/2oXdv5gF370U329poiG0plI8qfTAFZFipcKcDRumX24bMP2sXzz9vFF+4NGxkYHySlKGWkk0JUr1zRfqMNFfe2wrWB3fHKMV/iXwHivRUtdnzlUjvcVBUB/PpbG0c8q+nBNIE3mRHFMu2vqQ+MolgaD1Co8AVKqfTIJAlseJch16AH9z5+j6wSlbLatb+mPqwNrl+uRbmOCSYICvzYEfgqro2AgWuVYJTjrKTK3PXMuDQaIWTN+HOstcyuvPZ56082Wl9lc2SnNhlUAvE95a12oi0Rjih7q7PETq8qtqMt5TZSW2d7ylsja4CpnjiOaqf+95uGPLtHppdGiTcCBIYJ9jim+t7LMg8MKaPUJraFYJXvAP/metH60Gfsu39naExzzfBdUR3xJpDZXWIAGJcZFbqAKZRocQrY0b0kgSRAIbcWs+1LSA6lstOAH10ZnvEZz6YCKCFTlY+VkdLVZ2K9JMh54gTbThcRGRcG/I9nU/bBxgU2+eYddvmluwPbQSUihSD3KMEQ875JWb/VWWIfbX7A3l5TFNy+BBwaMwFtKWKNrWcVpaQFME60JSL947h6xd+fbAxnMXtFTwaK7mG6Wb0yygdMOe9cM3oWgQaTHatuxvYJPPQUT50gQ1eYB0hk2Agm8qXt8eBBjGc+lyqBgQcgBK+6nzuRmTaGY0bgr3UgoKB2MzSADPHll+8KDLFO9/DgiC5wAmeNw0AyZ0eaK6w/2WhHW8rt41fn2Ym2ROSdY/Js1dtX2Wzj2ZS9t36hXfvRTXb1jVtCjKA/htGDcW328mypN2QIeBVC4plP9Ws4nQnjrzhbgialiRqtWxbYZ603jYV2uJOxpXFHeUW3sDckKKP4nebCt4391HrKB/hpNHB+YwA4u0sMAOMyo+JjABl3k4/hoOKnYqAVTUBF4e/j8gh69Iy+ymZ7q7NkGhNEcEFQR0AkZkFCncKYQpzAiayEWC4pmeF0xo61ltk76x63t9cU2UQuGYAZFbOPVyOgkkCXQhpOZ2wil7SD9TUhGbGAK923uk/xfgQZUuLePSaQpPEhQPJ1yUW8o7QjbBDYUdphg9UNId0H50BzR6Xu06xsWbg+MFn6XIaE75MHbQRUUvSeBdT8eIWo53Dt+us41z68QGuCRgtZNxkUGgO6bT1w1/qn+49uXO+2vhHDw/XNtcr4PB8WcfbJQttX1RTyI5KVZ180Nn4Dw+6yFXama5FN/sNddnbtE9Pmh3GVun5/Tb29//SjNvmTm+13n/6/9vF37rQTbQnbV9UUDDMCR8kRvdMDyVyIcSM45jtNtt4bjQJSzN3HMVGfBVjffeox+/T7X7DDTVVh3dNgIAPp5Qb/12eUGxojPVvr04NH/+6S+fRz5V3IdOnT8I0B4OwuMQCMy4wKXcBSVH6Dh7fU9flQKmsXX7jXhlLZYBFLKDJFARUPASRdUxSe3sVKq1iCj6DAu9ckFMkYbiu8njTWW+6qQ+BGde0uW2FDqWzIKygXpu7ZXbbCPv3e3CDs9aNdlmInBf5Ut9zUBDBq50htXQBlBAc6aUF1CYAxxk1K2bNAPLHhUEO1DVY3WH+y0QarGyJAva+yOSSFVjwoAXI+UKLNLAJ2mgMywwRrZHCoyPW9QCXngorcg1KuDX1G1lrKmqwS1yMVMuMWvaGge1k3lT4NHb92qaz1bniGlG3zbSfr5l3UNKiYLkTjwPdF/R5KZaelAVIdSqQuEEnjbFvh2sh625lot31VTXayfYmdf+Yh+/g7d9oHGxfYsdYyG0jmIiwf31e1vT/ZaFd/cKud6lgccY3T4PQ/fsy2FnRHTj/R+3mkuSICnHaUdthIbZ19tPkBu7b7kXBKEOsi8yZQRzDq3cVsA8GbmF/KOM4pk3tzFzLr9sCU3hBvUMQAMC4xAIzLjArzAJI1EgCQsiGgkAAfz6bs/acfDUCCbBTja3ycGxWdt4yZQsaziBJ4ZHi4iYFsENk/ClO2Qd/Thcr2E9jpbzF1Y5l0YO5Uj2dUdD03n2gslP9N7SW7IjcUlRJB89aCbjvaUm4TuWTkuWQPqFDlHlR6kas/uDW45clcEdxREVN5qX0HltdGxp3joHvz1UkQSJDDufPjfqOxZTvpSuY6pbtUAErgnUwj89Dp5BLWT8ZXIFzgQ8YD6ydTxo0QXJcEgRwztZ3MaW9JZ1hHaq/eB60pXaf51I5cupL9Bg+OqVgyMsXqL+dO7RZzp01Yx1rLbDybsuF0xt596rEAqH0/1a/+ZGPYEKU+cd3o3SfLqu8UV0h3MK+jAau+7S5bYYebquzsk4X2VmeJvbd+ofUUT8X+8lrKD7+WtJZ9DKP/oeHANcT1y7HPZ5T6Ne/lAWVSnAdwdpcYAMZlRoUngVAxecFD4UXWjoKXiktKiIyFP91BwpJ5sDxLI2FM1yNBIV0xFLgeNPl6dQ+fSctc7SQQEMNAsOZzAgr4igGQApXVTnZLSv34yqURd60AhpSCj+NS28hq+Ws4Z9rteXbtE3bpxfn27lOPRViTnuKphL1iwcjC+rmfyCVD/QR7Ajl6fusdzwaFSSBExo5jzblkAL9n1/xcywDwYJNt88yTX+desTL+VXkxdY9fM1sLuqcBrXzsFdc3QRCNLTJaajfXhdohA4huQ25eIrgjSFf9WoucV405d6iSZdQYkcEmu7avqskGqxtCCiaen03G1cdLisXmiT9igdV/uoH5XnvG1MsjvUPsl/qg94wsu2f7xPL6efTrxBu2HD8vS+nWzSe/uM7IQBIA+vmMGcC4xAAwLjMqBIDKMSZw4UEWhRaVJ4UfgSFdogSJBIZkP3yKAwpiggYyU7qWMTJkvryb0FvgbCdz9/mTJtR+JYUm66J+cMyOtZYFBSb2Qc/YXbbCBpK5sMNXbVNMnmeuBMoONVQHxodKn9eyf1IU2nk7WN1g+2vqIzsy1UYletbYMX6LdROEc1w80PasDcEowaXmTc+SgiQbxro9iCRjzOvl7pcLniCeTJaAgGdwPPgSkCeTRlDPtUUgqzHzR7cRzGjNecDKUAjWzfVNo4Z1sC8EzgIYNBoI+P1nvP/0qmI71bHY3ln3uB1tKQ/uVoHCvspm21vREpkLPq+neHUELGt+uK74vmqMxEDy+EFvnHgmTtfyPGter3HeV9UUnsc8pR6Q0bDIZyQTiKv+Qw3VdqItEfrGOgkgPfPnjRXKLvXFt+NPH3wqBoCzuMQAMC4zKn4XsAQoXRL64VFhciHyGv3tmR0yRhSWAoe0nCV8Cf54r48JI6NB5Uq3I91PErwErNxdSDcP2RkyHWL3fIyhT1RL5S5lc6ih2k6vKrbjK5cGMCnXntLv6P58TJnqk7JUvjf9TRegnr8r0WaD1Q0RhXEj9xw3aLAfnB+Oq3fveoaMoEasFcGN+sVUGwQAulfjS1c/QS5BhBQx71fsHesmiOfudfXRh0BQSet+D2TzgTUCDg9W1C7NQb7NDGwH5yEfS0ejRKDQ/6+TZLSGOBcE8XRnby/qCmEEk7/4sn38nTvDJiYxzP70GvaXY72vqimcpKHxI6PId5D99h4Azhf7359stK0F3TaeTYUkzDQwuJ7V/oFkLuIBUBs4x0xFRQOWbaTsef3hTdOMD64FyjFvPOkeeke4LrxhGruAZ3eJAWBcZlQEAP9+0cq8bg7vyvWuMwIOMhmegeAuSro5pAi8AvcMHwEez4elMiaA9ewRgYRXLtuLuuxcd0GEGSL74hWahLpAl4CpBLmC8QlmlLD6XHeBffzqvLBbUrF0YpekNKic8jGpAg1U4FQu7LcH6VIwBBn+Oyoe9p39IVPE/rIuz+YRsHHNePbYz3W+XIMCdmRdPEAiI7Yr0WYjtXWBhWT/2E8PID3QYD+phLn+BLDZHt7L48D0HujZ3s1HAKDYRd82feeNMhpQfo4JLAmAPTOpd39not36k412qmOxHV+5dNoRbz41T76+7yjtCKmKvMFImUNDTe2mnOHY59ugROORbfDrbEdph/UnG+13r3zFxrOpUB93cqsuzgPXiMaPa5/eA39ijTdwb/QsySGubbKG+uyV+ZtjADjLSwwA4zKjwpNAJJS8y4NWrlInCAhtK7x+LqYSyEqAkzH0rIKEM11jjD+i8tBuQgFFulKoOARGyBJScRBM8V7l4/PKnrF66odngij06b4iKybX7+GmKrv80t128f1nbfInN4fE0hpT1q22qu9sjxQOY84IaHk2Lr/3YE598wyoFA/nY3vRlAtOLCVZECpNjj+BDFk09tWzTAQpaoPG0rObZHUIUP08ahyPr1xqH3/nTjvXXRDS3WhMtQlE/dRnZDq1hrgW2D795uYSKe18a0hhAZ7xI1ih+1LtYEiEN1I8863PBRr9nHnji20kQ871vLtsxdS51888ZOPZVOSYMjLe+qEL84ONC6bJFjJhnpH0TCLXOt8zMoB+jih3+P6onpHaOjtYX2N7ylsju7z5vHyfsW72UfMpY2532YowTgrn8EYDf3Pdcqc+n813e3tRVxwDOMtLDADjMqNCAEhlzYBtsgfa0OAFMYEBBXs+QEiLXO4o1U/mSYr9RpsGJIAFXMh28H9Z4sybJQErkOKFLFm1/mRjRHmobUr3ImUja5wsoeraU95q49mUffjsg3b1B7faxRfutSPNFSEAXn3oq2yO9FUMANtDZovPkCtLSqavsjkCrJi3T8qIYJuuZYFIgToPJDnX3IBCACJWikqX8Ydk3Ai8PBAkM6a1p3p1n+4hgN5T3mr7qppCHNjZJwvt2q6H7PymR+xQQ3Vww2uc5OIn+7StcG1gurhLtbekM6RK4Y/u9+fDEhBReXtWnOCCoQeqU8DCAy4ZYp7xI6NE5nLDvOemseRn1z4R3gXurmUbCaYE1i69OD/E9uk+PpPzovmgu5djos/57vO91HrletPn/CEw1JxRNpF1Vd84dpQvNFQ5Dt5Y9d4RrdOhVNZOti+xQw3VkfARGlaUU2zbrkSbHdhwNqwAACAASURBVGqojvSH50GLEYwZwNldYgAYlxkVbgKh0iV7JYXIeCJ9T1AmMEAwpSB9BpRTyWvXIBUgmQvGFXkwxzZ6ZUOwRtCpHzICUtaeBdtWOJVKQ7nVqAD0I8VHNw1jzVTPjtKpJMtHmivsVMdiO9ZaZqN1y0LslMZgV6ItxOyRbaWi9gpRoFxt5JjRTUvQuyvRZvtr6gPgzJdOQ+0W05uP3fSMBEGA+kNGRJsydD2D2vl8skicOwXri4V6b/1Cm8glrT/ZaMdXLg316X7+Hk5n7HBTVUjhwx8P4H26FI49gcSB5bU2kMxF3NDbCtfaYHWDffInX7LRumXTGEqGWhBA6F3JF8rgN3CQHdU7QcCieggWCag5d2SvVA/j3chQca61FgaSORusbggpZHwf9U4TGN7IWHtl/ubIuy1DRiCXjCbZaoJJPptxsaN1y6Yxkv490Xqn0UE2kR4BAWk+l6Bc83qwvsYmf32fvfvUYyFBtsZgW+FUOq18G340BgLrlHPeHR4DwNldYgAYlxkVAkDG1FAAE0RROcl96BkGKg0fU+TdRUOpbBCedAtvWXg9JQldUVS0qpeB80qRwXgZMVlUPFTWBBZqM89W9RtipFgFcDzYpIvUg86+yuYQPO93Kqruoy3lNvl3t9tAMheJf2QfpWTkuiJgYTwRmQoplVVzp0DO1ddvseMrl0aUIePLqKSkTD17xw0FGgsqao0/lS3BDfMHEugSrHJtCWC//vCmMI7K4yYwoDx+uk6MpuaPAMCDVfaNSpjhDGyP+ioGVu1T2p2xTNqONFfYUCpr7z71mJ1eVTyNrSZA0xixDwSiBN4c43xJqdlGvzb5ruo+5v7bUdoRdvTq3cjHrHH9D6cz4WhBhS541pSGnoAd14eAk5hxGXvj2VTYqe6NGs0708dwLLUGBehoyHLteWbOA1QP7mg09ZZ0TjPY9PyhVNbGsykby6TtcFOVHW6qmmakabzpkvfsIEMeKJO2FnTb/yhYFQPAWVxiABiXGRUBwD+8Z2MADXRpkA1SXjQBDAIHMlIEP3TXSLCJZSBrod+8nnUSeO6vqY9Yv97dxJgtD57UNrqgJFjV5x2lHXZgeW0E8FKZUEGQ3aJrjOBQZ5RKKUpxMgZM7Jhi1Y61loUUFWJ8BLjV18NNVfbJn3zJDtbXRMZQSt27wKmUthd12YHltRFgJOCcLwcggaSAOedLLKRXrJ7R1fgTiFP5M0ZKYycgxEB8XweNEhodnCvWyzV1I1AkAOnXDxWvZ7k4zmTK+pONduW1z9vklptsIJmzoVQ2jD0VPsEL17z6LvaIGwv027OzAoNsBwE43xu+J5xPAnOCUL4vTMOkdZ7v+EKOCxkyjrnqElCjS5pn/fJe9kft9eEeesd2lHbYRC4ZAXd6Dlk9v/bzsaaenea75uWiwOLxlUvt41fn2UAyF6lza8FUPsm31xRF3lsCaNapsdL/cQzg7C4xAIzLjAqPgvNKUrE6UjrelUVwIqEoQEYh7ZlFKlOvqL0LmQHh24u67K3OkoiiI1tEpsa70Shs87lz6NLamWgPOQH1XCpB78LjphSNiSx3CX09n2CTfewpnkrGPFjdEIlJlLVPd+jORHtIR8Oj36hsuIlDGxzkBlU7PIPC+dOP5n5PeWsEQLO/BDtir/SZxtEbCLqeR9u9+9RjdripKjyDIIPAwyfIzeeq01rQMwmCFZzvd/tyLUnBMmky6/JAigrZjwmBsGepuE7ygSKCN//u6PvDTVUhHZDmVGuU7wlBKwGmD91QPK++I2gjMKL7fmtBdySx8u6yFXayfUlICM11TybQryHPWPv3zl/L7wlq+b9kgownsq56X3UfPRr+nfYsLO+lccjzxMk2ar4pW2hQeENF7ewt6Yww2ZQJel/f/EZ7DABncYkBYFxmVHgUnAQf3V1UtBJE+tH3dMsSHJIlIhuoa73QlkKRdeyVw9aC7uBiUlsk1Kk8vSCW8GZ8F1kq/a1drt7C9ta3V1RUQBL8I7V1IVGuWC3PyvgcYXIhMS+cV3YE57rPK2nNjRS5gB+BBNNJECxRCXEcBS6ojP2GDrWbAGzDvOcC0+VZ4S0L19tYJm2ffv8L1lfZbMPpTFgrBF0aW80fwdmWheunuZ65S5YbIzTHdMHy/GuxPx6gEOwT6BKsEVhJSW8t6I5svFF7BZ70W/Uq/k19ETNFlprvxZaF662vsjmyFrhO+V6SlfJGC0GsBzMMzeA6pLdgW+FUHBtdk6/M32xvrymy0bplkT5xDAmMOOYEegp5UP80t1y7ZO/0WxucGIMqwO/fZd+v7UVTLKbOzuY7R2OTbfRr4FhrWQhv8f30BiplAN9HGrD6juuR7/LPCjtiADiLSwwA4zKj4tPAUCl6pkuCy7vCKNT3lLcG4EPmh+f3UuBJKAvQccOBPyJOyiCfxUwhKWBIN6+vh0qSSpUnPPB+zySR1SAzpv93JdpsX1VTxG25taA7sntVdcodTGZOsYEa1+1F19PV8Gd32YrgKmYMG2Pr9la0BGXEZNee5RAoWTU3mhbGj78H8Xoej/QS6JDiJGu7ZeF6219Tb0OprB2sr7HhdCaMkZhLtVtj4UEYx4YKlfGPnlFh/JRP4q2dlwRrqofsk9Ys2bh8u2zpxvSsHsfIz6cC/nWvxk7Gger791yQHA8aReo3QQljY/W/2sI0OAxv0MYhPUvu1ny5D/UcrjvGknKsuEFIwNj3i7vAuSZoyHkm1xtSGnufzSCfbBOI16YjGhs0EvKBZhptmjeuK65nrkc+g0BX/e8pjsZDbytcG58EMstLDADjMqPiTwKRgPKWPoEe3S5U/vtr6m20bpkNVjcEQc4EzXL3qU7GJDFrPhUjlYWuJwj0rh66DQlwpJx0P5UBFTBdiRToUvxeUVDpkQEUkCXrxvx8+XIS0t09kMxNYyQuvTjfjq9cGmEwqERVl/q3K9FmQ6lsxMWZj1n1sWsaA4Jj9lHtEtgiaJZi7atsjig+zd2+qibbW9ESgI3Gh+OhtnuWUf1gvwXcfMyY1jJ3n3O+/dx7VonAwG+K2pVoCxtp2C6CARpNBGICcTQY/PUaL/ZF60pgnwBXDPPushUB1Oi9IRD3gJCgwht6usYbOVq7ep/9pgWO64Z5z01Lh+RjPPmO6R0Qq8t3TX97dlb/e6PNp5Pi2iVjyPkiE6h3dn9NfTjmrj/ZaPuqmmxfVVNEnhDo6Xl6BzUWfMfI4J3qWByRra/M32wDyZxtL+qyweqGyHxw3rkmtxZ0xzGAs7zEADAuMyqMAeS5qp5ho4KgopYbaiyTttOriu1cd4Gd6lhsQ6lsAIGehSCAEmDxln4+pUmWhbtjyTh4F6AUAhWVFB5ZAeWCk4IgwCBAI1vAODvGDfn8gN791VM8lQ/tZPuSaWNNVsK7oHn8Ht1ZHA+vyLSzkMwGma58jAXr1vPkAiaI1PjvLlsR2DrvajzUUB3mYm9FS+QcZQE/jaVAhRhk/8M1t7Vg6ui8tzpLIs/T80+vKo6wSB7skVmky3Vb4VTqny0L19ue8tYAMPW9B9A0RLx7n88kGBao0vwS1GjNepc8N33onr0VLfZWZ0lIKK7neJaXBgzBA9eS+kdQIdCmfvM9IwOpdam66XLX3PaWTG3oufrGLba/pj7STvVVa4EAn2uO612AeDidCUCJMoD98MZiPkbZ/8257KtstgPLa+34yqX2VmeJHW6qsgPLa4ORw5AAAlyCfAJqz04rNEDr3xsiXlb1FK+OhKpsLYjzAM72EgPAuMyokAGUICKgIRtAZSKBujPRbkOprB1tKbcLz99nk7+80z7a/IBN5JIRhUnhRQuc7AOTBguU0Kpm3JbaxtxpZFOk2LVZgkyQB1jvrHvcPv3e3KA49Lmy8OdrBwGTB4cU9j5prxTKW50lNlJbF+4hIBAIkULpq2y2jzY/EJSJBzzqq3ctk2XhHBL0UdnkY7w45gJPSmYr9/NQKhtSgIjlHaxuCC5MMaJijAi01G652AQS5fb0DJAHOWRQ1SeNA3czv/7wJjuwvNYOLK+1373yFftg44Iw/j3Fq+1cd4GdfbLQjrWW2eGmKvtg44Jp+efIWPr5925xsUC6hmvAM6sCpBpTsrPqL9eW/j9YX2OffPfLNvm3N9lwOhNYwD3lrZFx9qy43mG5Gz0LR08AAQgBLMFSvvNu+b36dmB5rU3++HpbyeYSfGqcjraU24HltZEx58YdvUvcICPjj21Q2wVUBabVFwJi/S0jbk95qw0kc3Z85VI7v+kRu/zyXfbBxgV2uKkqpCHi2PpwEQ9ofR8pO7xrmAYNmURvJG8rXBungZnlJQaAcZlR4VnAZLwYL0X2iGwRAeCR5gr79HtzbfLX99n5Zx6yg/U1QZETfOVTevw/H7tyo9/52BuCIblYBpK5CJilq1mK4VBDdQRAkcUQyyW3j5SjAM3Wgm47u/aJAHrE2KhfBAnc5OIZFfWJIEYsngdnPcWrQ6oOxQaSGSF7ovb7efDpXnQPXWxkXckEC7QdWF5rZ7oW2bnuAjvRlggusoFkLgAR/r27bIX1JxvD/3IHC7joaDylSaFRwLQpchH6DSDsr9qsXdETuaQNpzMhzQ7ZPNUvwKo1ozkZrG4IrJtOZ1DyY7KDBHwEYGSEtAbJSjFmk6wgwwJolG0rnNqZfaih2o62lNuJtkR4DpMp0+jSfPI5BP7K+8drOK4C6ASXGh+NA98hsXt090smKCUS17M3oHYl2mwil7RDDdU2WrcszLtn+hQeMZDMRQxUAvJ8Gzg4BmSEGdqwK9FmB5bX2ulVxfbp9+bav/2fn9qn35sbWFcmiFe97BPBKlMZaZzzMYJsG8MA6BFRPfo+jgGc3SUGgHGZUWEiaDIDtEQpUCmsaC0faqi2d596zM4/85CdXlUcTrlg4LSUAhkECji/6YBuQaaioUvHu4n5WV9lcyRtAq1pXkeLXM+h4iaTISVO5nJvRYud6VpkH3/nTttX1RTYSIHafBY/wQLd4RpPAkb11e+2Jou6rXBqJybZB4413V4E81TWajdBttovZkVjoniuE20Ju/Jnd9jkr++zD5990MYy6QDuekuubwoSAN1X1WR9lc3heLU95a2BPTywvNYmcsnAwumUDc2/AIDaf+Fb99vRlnL75E++ZLvLVthYJn1DQMg17Y0Gus+pXAUiyTj3FK+2/TX1AcyK5SRDuL2oy95eUzSNHRYLKtflcDoTWFAZLnyv2CYaO9sK14bNIkwi7teX5lPtVmyu1jnfKQIQznFP8ergkt9b0WKTvfdEdjbTyKGrmW3yRs6O0g7bX1MfOQJR659yQm349Htz7dKL86cx3+rXnvJW+/jVeTaRS0aMFjKA+f7WGOh5yjDA5+9KtNlwOmMn25fYpRfn29U3brFLL84Pxg7BLeWj1hWZP80Pmfee4tV2tKU8YlzTEKTsUJyzZ2xjBjAuMQCMy4wKdwFvL5raaXr2ycKIK5hskKx6umR03uXB+ho71FBtB+trAstzpLnCTrYvCQwKLWIpNe9ipWKhkCOgUWwWlQIZiJ7i1ZFEynQFSXhKeLNNaoffIUhFQQUjZuTdpx6zD599MOy2VRsJ1tgWKT+vhNX+8WwqbG4gW6m2qM1UqhwvKWHVR5c6wScZWLImetaquZsjO7W5M3RvRYudaEvY5JabbPKXd9q57oKgRHcl2gJ421PeGtiygWQuAEDlRNtdtsIGqxvs+Mql9t76hXbxhXvtg40L7PjKpXZgeW1wtWm8telkPJuy8WwqMEucRzKdnoEl0OOckmUl0NbYMCci16+AHZlEP58Cu7vLVtix1jK79O177OPv3GkH62siBk++9nAed5R22Kq5myPzJZetAKs22qi/eqfEoGouCbJoFPkNQfpROAJBlmcCCfa8i5M/Ymn7KpsDe6i1QqNFHoYDy2ungUU9U23zngO67zWeaheNUhkHqsO/U4PVDTZSW2cn2hL2VmeJnWxfYmOZ9DQjz4NdbmDzbDNllvpKeaP2ag41z5K/NMp7ilfHm0BmeYkBYFxmVBgDqA0dOgWDKT+4u5BuYLqM9lU12WB1Q3AV9VU22+WX7rbJn95mR5orpjEaZAsI3rz71d9DRS4BuGXh+qBopKilyHl6iWcGbgT8PAvacPszIYZISkQ/cl0SqKhOui1ZL5UG02psLei2A8tr7Vx3QeQ+gR61W9enbt0QGRfOi8abbdDz1dcdpR3WcPsz1nD7M9OAoD/6TSBH7jLFR73VWRKC43W2s0BRf7LRhtOZEH83Ultno3XLbDidCYBoV6LNRmrr7O01Rfbxq/Ns8pd32tU3bglHqcmYkFuWSpJKV99xDMjAqt10txP0kon2rA0BpNYFd5N7Nx2NJrJ024u6bCyTtmt/dZNNbrnJRuuWhfNheZ6zj78TKzxY3RBhwQhEPWu8o7QjGEEEwfqtsSKb5gEW3xV+TlDKnf1so9ql71Q3XbLHWsvswrfuj2z24PzI6NhT3moH62vswPLaiBeADBvbRJab60QyzMsuPt/HC3Oti6Um2+xjOvnOUB7QYOX7Tjnm1zDZRd9feg5iBnB2lxgAxmVGxTOABFZeAVAReBcEQYcAQH+y0T793lz73StfsfFsKsI40cr3ljgtYK8IvbUs4au0HHJX0X2regQCmfyXip+uMC/IyZRQKBMUUPlQ+Xsw69kCtUkARcBLiki/xVaSLVWbyBZuL5pyf29ZuN76k40RFoLPpSKSYuR3XslvL5o6dYJnxIp9YWoX5UDsTzbaUCprI7V1dqih2o40V9iR5goby6TD7k0p95HaOju79gm79lc32eW3Vtu1H91k7z/9qI1nU9afbIywMwItBGBcOwS5VK6cQ4I/KlMqW40nn7mtcK2d6VoUeVdotHD9ipXTOHEs5eYeSOZsLJOOzIefJxoBWiucH7+znkxZb0lniKFjzkiCDI6NnuMZUl+n2sF3iAbUvqqm4JL1zBvX457yVjvTtcjGs6kwx8PpjI1l0naiLRHp+8n2JXb1jVvCOGh+CZo9MOT//FtjzF3rXs4wX6PWt9hszavqJWtKOei9BWRZuVZoEHsvg3eL87euiRnA2V1iABiXGRUygBRG/CFo8xnq8wkqxoodaa4IyoeuN39MF92mTPEi5UHXJsGngIDfbDGWSU8DjzwKSn0hS+GtbO82ZW4xzz7Skme/CAb0OVmRgWQu7HYdTmempftQfXI7UllopyKf7dO3UEES2NC1zM0FPK1C9WgX9fai65tJPODgRo6difYA/g4sr7XDTVV2qmOxnX2y0M50LbITbYnAAmqXdn+y0Y61ltlHmx+wj79zp3347IN2elWxjdTWBcBJFoeAnTvB1aZjrWWhX0oMrrU0Wrcskq7EGyT55o/uNwEiP86eVdK6Jfghu6RYSQFIbT658Px9NlJbF0kzpPlm6hgxxwQ4NBK01voqm+1EW8Imckmb/OVUnKqMDAEOtZMAQ/OqvnqASiBHEC23qIAt2T8PstXGDzYusGOtZQFkHWstCxtb6CGYyCWD4UC5oGeoLWOZdGRcadh6dk9/c1NXb0mnvbPu8Ygru6d4ddiYdLSlPPSB69K/UwTnArJqv8ZG7dea0KYvtcmDWMon/R8zgLO7xAAwLjMq3gUsAejdFPzhd97tQVbvwPLaCPPhFaWEJ8GXnueZBdWj9tG9S7edmAq/k1bPoauLCtqzmVKQVNBKcJxPmVFJaTeiZx782A2lsvbuU4/Z22uKwu5KMn50HTEOzbvVyAR5ZpFsFxkRjjkZPt5Pt/rJ9iV2uKkqorSpyMkQKaavP9loh5uq7O01RXbh+fvs6hu32JW/uH1afJ9AhpjCk+1L7GhLuY1nU+FIPcVLcj7IInnGUkrUgw8qVbmp/fcyDvIxOGQTPQvsASTn3rvPCZy4xhVGQfAltskDeo4J2SAZKqpfaXv2VrSEMdX8eSPJM5VisNU3GlpcP/k8B2OZ9LT3m4YIf59eVWxnnyyMxAuqLXpHtxWuDUmY/fixvz7dkDfqvBzwdRBIcizIYOp/zQHHxMf1CrRLvr63fqFN5JJhzjSmNBq4dshE811VX7YsjI+Cm+0lBoBxmVHhWcAU9gQWFIwS4mImdibaA0NDIbqjtCO4fakUxGTQjUrh5wUegRSFt9gYz0pQabCNVNZkFneUdkxL5eFZBwJV3StFRCbCAwHfN6U00Xejdcts8s077NPvzQ1gmcfoESirH2wT3VBii/wz6S7X/EpJ6nMyhGRLFAB/ftMjIY5QIMMHpvM+rYnRumV2qKHa3lu/0CZ/fJP92//5qV289P/Yx6/OszNdi0JaFuX+2122wkZq62w4nbGR2rpw8gLnhW1VHwlCPRBh6g2yXQKBOmKNwFv91Pxy3XjGUGwoDRcCKipz1U0WnXnr6GrdVjgVYyhW9XBTVWRjFpkhxszJBa81SyDKsdL9GluCGa1VjZOAjwexWxaut+F0JvLO+mf1lnTawfqa8L+YV80Jx3wsk7bRumURI0v9UF1sK+WHnukZNRkkhxqqI0aT5lh5EPk8D1QpYyjj+L0+6082hnXgjV3K0T3lrZEE0Fw/NDQ0tvQgEPzps9gFPLtLDAA/Y2XPnj3W2Nhod999t82ZM8e2b98e+X7dunU2Z86cyE8mk4lcc/78eVuzZo3dcccd9sUvftGeeuopu3z5cuSa0dFRq6ystJtvvtnmz59vf/7nf/6faqcA4P8uXjGNwSAjIGGkM3bJwtCVkc8dQ7aEDIZYFq9cVQcFKBkpbyFT4RNE0q0nZai2e7eNZzKpJKRwCJAlhP1uQt4v1lDtY3yPdjeeaEuEWDA+X3VzTDyb1FO8OrCDHCcyW2QGuZGHGx04BwJIPEqM/aXLmWBrR2lH2Hkql652hp9/5iG79lc32dV/ecwm/+cX7OIL99qpjsU2WrcsJAwny6cNIoy1IrvIseI8sC36XomC+ZnGV/czFRH7xbXC9cdd2HymmGiCEoJFPouuXa4fjb2vR0aH5mxvRUsIaRBYEzPm2To9V3NOZpcsqsCjNudo7LmJKJ87VX1TOwhO9O6QGdNv9s0bLQR/BLfeva0x59xJ/hCUqW1su/pOUMh507uk9UXZyPACMpLeCKNs4eYTzZeXQZS1flwoFz0wjV3As7vEAPAzVv7xH//R/uiP/sh+8Ytf3BAA1tfX2zvvvBN+Pvzww8g19fX19o1vfMMGBgbsX/7lX+zhhx+21atXh+8vXrxoX/3qV62rq8sOHjxoP//5z+3WW2+1H//4x//hdjIRNIXVQDJno3XLgguOAofKlwKTgINWMoXWQDIXNib4eDXPIjAGSkKTrF9P8dSmjwPLa21/TX1gBQgi6WYh6+UVDhW5F7Ab5j0XAUQcJyoLJeClEqOrmuBsIJkLuz+lWMh0iC0kkCPDqWfS3Uel6a8hACIzJCAkha3n8nk0DDgfVMIEymr/h88+aCfaEvbJd79sHz77oF1+6W679OJ8e/epx+xYa5mNZdKRGEj1V7kjh9OZSK49gjvvWtxfUx82OBDQ3Ih9IfDydek6sk7bi7rCcWt+8wmZaoEszZu+H0jmwlwPpzNhDggKtO4ZN0ajioaN2FA+Q0Bf/eO7wjAAAlH188DyWjvWWmZHW8ptOJ0J6Vl0uosHhPmML77rWjuehecaZBvo4s5naDH2kaeUELCTHWefCTTFPrIOfs+1oLhRgn9dSwNNqa/EXPLdYsodjbvm3Z+24t9JGZ1Mmq75Up9VXwwAZ3eJAeBnuNwIALa0tNzwnkOHDtmcOXNsaGgofPZP//RP9rnPfc7OnDljZmY//OEP7Utf+pJdvXo1XPPSSy/Zo48++h9uG3cBS7goLcf7Tz9q76x7PByJRmG4taA7JKOl60uCmIqBaTnIhN3IVUIGSsJSgpFgckdph/UnG+2T737ZznUXhJ2vVAZ00xG48TPtIGYfqFTI9pDJZJqUfCA2n4tbsWk6Po2Cf1vhVN49shejdcumCX0pSe8q4hhLwVLxS3lSKSn9i+ogaPSsiuaGoJVKWs8QgDvUUG0TuaQdbqqyk+1L7EzXIjvTtchOti+xI80V4bQPxQEKOAqEct4JWgi0tIYEiBj3eKy1LBJXt7tshZ3pWmQH62vC2DG2i+DPM1PHWsvs/KZHps0rx5xg5uzaJwJwVd5DpkcSIBCj7kGI/1sMkgwAhV3wnVLaJr5/GhuynJpPATkd5fjJn3zJPn51nh1fudT219TbcDpjA8lcOOFGTBfDHWhAeDBIxptGHcHp6w9vsg3znouAbdU1WrcszL2uocu4t6QzsKB8dzlvfJe57j0757/3wJv3vf7wJju79okgK8cyaZv8yc1BTnowT6NSwI/vmw910bu+v6bexjJpO9xUFRKsa70ebqqK9CM+CWR2lxgAfobLjQDgF7/4RZs3b54tWLDANm3aZB988EH4/m//9m9t7ty5kXsmJyft93//9+0Xv/iFmZl985vfnAYi//mf/9nmzJkzjU1UuXLlil28eDH8nD59OgBACfLdZStsPJuyyf9+s1369j0RwcYYGy/w+TmF/taCqXNR91a0RI4t825E/qbLSUCGMVBSQsPpjH386jw7u/YJG0jmwndi4V5/eFPYkKC2SphKiTHuiuwFY858ygta655VFEBRe5nW5cDyWjvUUB2YFboCCdzkuvrdK1+Z5rLyTCHBM+OFOM66hsBJOfjIhBFw0BVH8CcFpXHivUeaK+zCt+63sUza9la0hJQeY5m0TeSSNp5NhR3AQ6ms9VU2RzZiaNz3VrRM2xBAEMjzZ9WuE22JkIxaAFljJ4AnACGWTNesmrvZGm5/JjBymhutUa4Rvx7IXA5WN4Rk2D3Fq22kts5Oti+x06uK7UhzhR1YXjvNrc33hoYRGUwCrVfmb47s4u0pXm1jmXSIWfQgi+1Xm+VqVwysAODkf7/ZTnUstkMN1YERvF7+lgAAIABJREFUVJ+05phqSWOi9vFs4XzAi/F27D/7zvXI3zQuCQK5PhirSmNR656Gob73a1p15tuIpnq4/ntLOu3DZx+M7N7V5zScvMHkwTn7uLeixY62lNs76x63D5990M51F9h4NhVYQBoIvSWxC3i2lxgAfoZLPgD485//3H71q1/Z2NiYbd++3b7+9a9baWmp/du//ZuZmX3/+9+3BQsWTKtr3rx59sMf/tDMzJYvX24bNmyIfD8+Pm5z5syxQ4cO5W3LH//xH0+LPdRRcAQiI7V1dqy1zMazqWk7XyW4vGDuLem0/TX1QVhKqPWWTB2zJADAHaeqj9a2V4ieJVQ7thZ0BxfwaN2yaYBF7VOCYsXxKKEz85x5JeIVspSmPiNoUTvoRpQypOt4IJmzq6/fYme6FgWA45Ueg9sP1tfYe+sXhrrFAOmZnnkkCCRoUHu90txX1WQn2hJBuXsWlgDKb4Zg3QJt/clGu/TifDtYX2O7Em02WN1gA8mcDaWyNpTK2mjdMhutWxbCAHQqCHeyqs59VU2R9nj3IZWgGJSR2rqwvnyMo4+dIojnM8i+ehesvuccsE0cK+2EPtxUZZdfvsuu/dVNdn7TIzaRSwYASLaZbkK1hWyyPytYbmitGW0W6U822oXn74vk4NtWeD0ZuOoUs6f6xjJpO9ZaZifbl9i7Tz1m7z/9qJ1/5iE7111gR1vKQyiITnPRGHHjiDfm+M6wLeorQZk3MClDCJL5XvK3N3b4fmt8CbQY6qB7eR4451Zt3Jlon5a0nYwo333/2wNStY9yjfM5kMzZyfYldvGFe+2T8bRdfvkuO9GWCLKYsnd7UZf9zcKuGADO4hIDwM9wyQcAfTl+/LjNmTPHfvOb35jZ/z0AeCMG8GeFHREhJDcTGSO6fDxgECikIpeLuLdkKs+Xzn/1bqFthddjoTwDSAHM/xknIxbMx8X4NBkEiARDEsxUEFT2uoabMnwsHmOweopXB9ceFdTeihZ7q7MkgGTv8lEbyHh68EWQQFDoWUDOpZ8rjcPhpiqb/MWU+1zuNLlRCRQ1lopF0u7coy3ldvbJwsDiEQxpPfD4t6FUNrhjdRasWEy5Sxnr5udM8zyczkSYJbKj7KvWFeMYBSLUVu2o1RqQkcDx5jwyFs2vI+UIZH9OdSy2yZ/cbBfPP2+ffPfLdqItYYPVDWFMBc70XLWTbkGuPzLVeifIFu5MtNuZrkX23vqFkXo0hsx9qbUl925/stEOLK+106uK7eoPbrVrOx+wK39xu7371GM2kUuGY/u4E9vH0WkctD49W+XdoeyHB3sEgH7DhGdHtyxcH07j8WCQAJ3AzO/AJTtHOcM1KNbUG45sq773Ofz0jnnAKsabBrCMs/efftSuvnGLfbT5ATu+cmlkDRCIxgBwdpcYAH6Gy38EAJqZ3XnnnfbXf/3XZvZ/zwXsi2IA//TBp6a5KBiMrdgVpimQ4GWMnBSsXFBS1PuqmkIQvQDShnnPTQOUG+Y9F5I46zoFbfvnCEx4Rkc/ZEnUViosClwPPJmMWn3QM8VoEnQKjDFeTQqxp3i17a+pt6Mt5RFma1vh2nCu65aF623DvOciCpvghiwr/+amDAITsleeYRNQGEpl7VhrWWR3KZkNgScFo8sVOFq3zMYyaTvSXGHvrHvcRuuWBdBGt6OeI+ZI8W908ep7zQeBpNzUHlTQvZ6PqdNa9SwL3cacN/2QkdVcqh0ETVLyuoZgRMyWQMtELmnvP/2oXX75Lnv/6UdtIpcMG0IYzzaeTdnxlUunGR7e+KGhoPdH65DgVX15Z93jIXaPBhSBlO7VsX1vrymyqz+41S5eeNmu/svUGdeHm6oioF31aIOY1ivHyr9X3sBiO+juJXMoIKXn7ijtiMQe897+ZKO9//Sj01yvnpEji0igyvb4+VZ9x1cutYP1NdPklgwntonygbKV77He96Mt5REDbXfZCjuwvNaOr1xqb68pspPtS2x/TX1k7Cn3/n7RyhgAzuISA8DPcPmPAMDTp0/b5z73OfvVr35lZtc3gezfvz9c8+tf/zrvJpBr166Fa15++eUZbQL5WeH1BMtkGHzaF8au8OgwKlyxEnJ/6ju6LbnT0QtoAhH+T8ZHQfmXXpwf2AG6ebyApvDV93KDefAoRsiDRt0vYb9l4Xobqa0Lz9d4yPJXHQIeAtL6PF+MFDfIiDHQs+g2I1BU2xUoT1ecxkOAQrGP2uWpcfMxdXqe7u+rbLbDTVXhpI4zXYtstG5ZiHtiHJWAmwCJmEPGVQp06Dq65HiWrPpKAMv52FrQHTEkCIgE+ggsPGtFZvtGLA7/13UepBDUaIx7iqd2qY9nU3aoodrGs6lgQLz+8CbblWgLQHjyxzfZ5D/cZSO1dTZSWxfcrGonc2eSOVbKGOVe1LxpDeoUEK4xz+RrvsQAHmstswvP32dXXvu8Xf3BrSFx8VAqG/rGcSBD5lNDadx86ALBMpkyjiXd5L7f3n3Mz33b8qXU8Swh4/v0PwGt2qc2EXhyLMkc87N8+f30fvk2kS0dSmVDGAXziGoNn+laZEeaK2IGcJaXGAB+xsrly5dtZGTERkZGbM6cOfb666/byMiI/fa3v7XLly/biy++aP39/Xby5En7zW9+Y8XFxfbII4/YlStXQh319fVWVFRkg4OD1tfXZ4888kgkDcyFCxfsq1/9qn3zm9+0gwcP2ptvvmm33XbbjNLAKAaQ7o18FrL+JntGV872ousxdLrHx+Z5toDuFH5PwKD6lY5hT3mrXXj+Pjv/zEMRtoyCWsya2DzPgu0uWxHcngS9dOtJqVAZSfHuKW+199YvDCCGYyIGprdkaqMKz0L2z1Gfz659ImxgyAd6CUjoElNb6e4SaFE+Ph3LNpDM2f6aehutWxYUq0AqXXsCtFJIQ6msvdVZYpP/a659Ovlj+2jzAzaeTYX7GHOn8IEdpR0hYbZil/qTjZFdsf3JxpCnTalfNHY+Vx0VpMZAY6zrvatPfaT7kW5ugkZdq+TQAlIM1CcrR5bTAxsPVpTuhqeQaLx2JqbOBj77ZKEdbSm3C9+6395bvzCkwfFMHY0xrUUaYBvmPTcNBPYUr54Wf0vmUOcEi+F9q7PEznUX2DvrHreT7UtsPJuygWQugFYPVDQmZBu5Pr0ByB/2j+CR45nPTSwDlewajTg+m/JhR+n1JPVkkCmz+G4KcKkdlH++jd6Q5frSvLFdBH9cw/wtRpBySv3ZlWiz99YvtP9dvCIGgLO4xADwM1Z2796dd7PFunXr7JNPPrG6ujqbN2+e/cEf/IHdf//99vTTT9u5c+cidZw/f95Wr15tn//85+0LX/iCdXd3/7uJoL/2ta/Za6+99p9qJ9PAiFnjWaEEZGSIKNSkYCVEtyxcbwPJ3DT2zQf60/olyNJzyAJK0flAbt1LlkBCnvVsL+qyoy3lEZef2BOymtsK11p/snFa6pp87EBvydRxd1Qc6hsVilKQ8Bo9ly5PtVkgjywp6yQQ4S5i9lVAZyiVtVMdi+3DZx+0M12LAmNJcMJj77jzle7Q3pKpc1gvPH+fffLdL9vZtU+Enb4Eu6qTAMQzeAqm76tstsHqBnt7TVEIwBcg8X30GwK4Y5dsE6+hsiUAUB8VvkB3MoEimT+6CHW0mthHrW2FK3gw4tklsr/e2DncVGWTP73NrvzZHSHVBxlPGQFkz9lX5pmjq1F9O9RQHcaTa0kMoBgn7dqeyCXDxh2ePcy1ToODa5Qs6o1csTQe6V5WveyjB2Fc81wjHHvdp2f4cAhd42M79f4RkBLoUf7R8JNc83KS1/Izzdcr8zfbUCob0vvwneQ4sU8Ekr8saYkB4CwuMQCMy4yKAOB/e+Q6e0eGQeCIeeso4PSbwEM/B+tr7FBDte0uWxGEKa1er0A8gCIIkHKhy4mWO91+ijHzDEU+dy6ZELF157oLwkaDnuLVITZPoEa/6eqle1y59dR2sgN0h7Md7I+uJ1NFxcGYSM98EgToOLaPNj9gH08st4+/c6cdaa4IbJuUIRWpH/ftRV3heK7B6gY70Zaw4yuX2qGGauurbLY95a3hh4CHYF4gkfFpJ9uX2KmOxba1oDu4FdkHMiNkagRY6aImOy1Ap/ETMNBOaoFcApl8QIrjkbp1wzRm2LsFVT/Xodz9G+Y9F8ChZ4k9gN9fU2+Hm6rsaEt5SJOjM5h9Tjkyb35HqY/VpZHDmE+5f8U27S5bYXsrWmwgmbMDy2sDeyyGkPPsx0EJ0/k53wG1RXGDHgjReOAa0pF4NHC4GcWz/FoDuoZrheBRefW8sUk2X31hCEBvyfUNPzyijeCUhgBlqWSAjAKtZdU3kMyFROE0fPUs/e/Bb3wU3OwuMQCMy4yKAODfLIye8CFWTcrxYH2NjWdTEcXpFTAVzs5Eu03kknastSziIpSiletGQlOCUIrNu4KoTMg2CCQxDlB1ki30v/UMKoPekk47vnKpXX3jlhCQT/aKoI5Z/6nMCGjZN/XBs6kaa+bjI4iV8Jfr27NLZFPkvtyycH1wN+ootsm/vck+2LggcmKBZ7fkciXAECOpjRzaeKMdoRwfxiapLsbgqU4ez6brPHvZW3I9XlHjSPcXARpBPMeELFs+o0brm2uPxo3643eL0vBQLKziEDk3WuP6nEaCrvMJjuliJfAQ6CE4IVMl8MXx07wwV6TG7lhrmR1fudROdSyediJNT/HqwNDqRy59pikiW5ovREKudIIf7xLV+03WMF+8HNe5+q4zvJm0nODXzydBnv4WQCQjzHeVTCDfd1+vZ5tpuHHzHEG8rvPrW6mRyE5SXghsE1THeQBnd4kBYFxmVOgCzqdYJLQkyGi1k82iW4vKlVavFCLdGFS0FIK8js/jM6RAxRJ41kFK2TMNPuaH7NzushU2lMpGWCUCJLJ+HtAKqKktYj7pxqVi4MYID8LIggroEtTsKW8NR1VJeWrOdN3eihb75Ltftg82LrBjrWXB/Uv3LgELXU1ULmqH2CF95/NDksEjKJTCletZLAuVLVlUKkeOt3fX5TstRnMhQC3lq3HTjwwHv96UpoOGjGdGBcx1PePx2E4aPeoHwZPGSgyQxkCAjUBR4GtHaYcdX7nU3ln3eCT2kGuMLCfHVQB5R+nU0XSXvn2PXXj+PhvPpiJgWe3rq2wOYyAQSEZVm3sIyLm+ydB5Npzrhetme1FXYBn1DpM1I8jyhhbnTYYT69Z60LWUGeoXn6HneiPEb5Tj+lS7xahSBuoa/U15qzkjQKURQYApwE/5E58EMrtLDADjMqNCFzDdHq/M3xwBGBROspT5v1dYAmesg4KVOxYpaGlVkxkic0Irm0qHrJAUs5SEUkcILFJxbC3oDjE4UmoCAhL+qkfuMm+Rq8/M50ZwQ1AjxXC4qSrinpaw9y4esoI+zozjrr/JiA0kcyHxMt2+BA9UemozARPbQ8ZO1xxqqI4odI4PFf5Hmx/IG1Pn+8pYT/aP/ZaSJ9jhmdX+Pj6PbkEyfNuLuuz8Mw+Fc4x1CguBVV9ls53qWBw27IgBFHPDse9PNtrORLutmhtdixoPstAEoXpfyJpq7ncm2u3sk4V29Y1bIgBEa1Tj598jz8RuWbje9pS3huP6tBueRwzqPWUaFrF72ljCtcJ55PpX3zRXjLfzc7ytcIoFVcoo74r1DKJnIbn+9cMce4zfJdCix8MDesoM/7lnBdk3zqn/zf4yXyrHgvPnjQZdJ+Aau4Bnd4kBYFxmVMgASjh5ZoSsBi1qKikKZVroFFpMQiv3jQAGT8wgi0elxZgZzwJQ8XBHKq/dVrg2bHBhahYCJykatZPM2+lVxXbhW/dHFC0BaD4lSAap9Y5nI0qAbk72U8qMgIxKlXUSIBDo7Ey0276qpgA0xLIyAN7Xqf4yt1vq1g2hrbqHrB+fT0VFJczx6C25HkdJBljsoNaDP+tW7SeTKqNB48F4RsWz9ZZ02lgmbduLuuytzhI70lwRGKye4tXhWDq5V4+2lIcxGE5nQuLfiVzSdiXa7EhzhV369j127f+7yU6vKo7sWiZg0fwRXBPwacy4m5vrWaBLY0c2VQB+Z2LqaMHxbCpsXNIYajx3l60IzLa+31HaEalf9eg0EaacIfPIuWVMrNhApgTSvHGDFpkyxkmqzwTwWkvemKJ80DXeiCEzqfXhN374940gmtdofLysoazk9fQq6HquS77XBLA0gPQsGtmUyf7oxN6STvtZYUcMAGdxiQFgXGZUCADp9iMQlEAS40K3qhdOPJydLmNZ1mK6vHuGYIfgispxPJsKAlNMBBkVD159gD2ZI99uCWelsKGbtPWOZ21fVZNdfuluu/zS3RHFwjGji8e7+DR+6rcAMPtMRSYF4Jky7gYkk0BF2VvSGQLg87nKOKYEFec3PWJnnyy8IZDhveyn2uKBKusQQOMZtuobFTnT0WyY91wkPpIAhwCT3xFoHayvsTNdiyLHZ+UDU+yP5lHt0/cCiEro/faaIpvIJW2kti4C2Dx44Fiyfr0DapPWpGctuamC481NCUOpbAC2fLbAgsZbdQgMcr3IKKObny5j/qaBpbU8WN1gY5m0HVheGwkNUBvFoHE89I4eaa6I9I/pf2hYkfWivPCGJoGdjy3Wb8+mMeZO61yygHMp4O7fXQI/rkvKPX3uQ1VoYInR07vu313eJ6NvR2lHDABneYkBYFxmVAQA/ynREEkvQYVEFofsFxU5wZR3nRA00EVDxUbWy7t7eopX24m2RGBLeI/qoQuZAfXePbyjtCMAC6/gPRNDxaI4KCkKsp90P/m+kvGhgmHwOZUb45DYN7EzHCcqDwbxyzXpWUQpFc2xxlYKf7RuWRgHsnnMB8gxYV+kLHXcG/st5a9xEztFwMQYSo3D9qKp0x1G65ZFkhD7xN9yZ8stSeNA83D2ycJpTJLWJxOa63sZARxvz35z/MneCKTryD///uwuW2HLb/svYXxoTOUDqH5tqk7OLxlrGgaMp2PbuTGLsY47SjvsRFvC9tfUR/rHkzj8+htI5uxUx2K7/NLd9s66x22kti5iMPhx9SDVexI86CNQ5XpWW8g4at7ERup+zqH+p4uVbeV1ap9n4ujCJVOZL1SF75+e4+NfOZ56X7Qu/XrLJ2fjTSCzu8QAMC4zKgKAuytrwy5fz/B5wUPAx7gXCiuxgbRcKUjJ+tA9JGWgz727lyyJ4pXUTiaF3ZVosxNtiQi4IqvA332VzSGOTfX7/svNRaDGsdpX1WTHWsumPYdMiPpJZSEARUXhn+3HljF5ZL6oaPKBZAJqKveD9TX2VmdJBECor9o04sdM4y8F/PrDm8J4E8irTqbtoLHAvwkQ9IwjzRX2/tOP2rnuAjvcVBVh8wSqqci5azofE8yx5WYlgSYF1zMOa8O856bt4uQzeR3BJYGG1jVZPwE8zjvXuI5L3F7UZavmRjc5sU0E4nqeN7L4nnH8dC2ZrYlc0o6vXBrO1ZVLlaluGM4xnM7YBxsX2MXzz9vV12+xiVwyAoD8+iWA1HoW6GF/uEmDc6c6PIBSPzjvuocuYLHKXGt8Rwnk6YrlfKtOhmPQcOa6knFI5pTvJ9emX58ekBJcsj0xAzi7SwwA4zKjwjQwBBUSUnQd6YfMFpUb3WYSVhTedKsSCFIg+pQJEtraqUjhumHec5EjzDxQpUVOwEZQqOOvjjRXhHb6mCEqfClPnk08Ultnh5uqbDidCW3vTzYGQE2GkMpZcW5UkjobmH3g2BLICehuK1xrB5bX2vtPPxpSbxA4q98EJtuLpvL77a+pD2e8cnw8o0u3E9smhombX9RmD5CoIDWufrMOQebORLudXlVsV/c9bpN/d7udbF9ig9UNEVDtYzzpBvVGCjf/cCzJ3tFg4ZqngaC20cUtECzgoj4RpG0v6gq5GdXO0bplgdn0oQkEiPqbAIIgjmPHOSCT6Fk0zoXS0Whejq9caue6CyI74v0pIqq3r7LZjrWWTYVIvHyXjWXSEWOEIMkDc64rH0Kh9mrMeopXh/UtA4RzyPeJAFF191U225Hmikj+P74TDD8gMFN7FVNKIMpnyWjiffnkIp/JuvSZNxLI2veWdEa8Kvr5w3s2xgBwFpcYAMZlRkUA8O8XrYzE1EmIiYmg0ieAonXshSMtdMb0eRckFaR333klQvZwKJW1k+1LIjn0PDD1CliKWu288Px9NpZJR0CA+rIz0W7D6Yz1Jxsjlr13/1z69j2BQcu3w1HC3acUEZNCALy9KMpkUtHoes+qqJ1XXvu87atqiuQP3FY4FaPF/7cWdNtYJm0XX7g3uLUF6hm7SfaIaVPyAUTGWhHgEbgSvG4t6A4KW+uDTKOuH8+m7KPND9i57gI7WF8Tnqk1wnXE83O5tphz0o+rnn2j9aKd7ATwvM6zPHoe2SOxP3LvkSUWeJdBw2cRUMuA0nphehDNm9zw7Lvy9wkIaRzUDv0IBDJ59rtPPWZHW8qn7WynbBB7PVjdYIebqmwilwzzynjgVXM3R9Y9mWKuJc6PWEkdUUdA70GTAJx+vMGkfl9++a7I+6P5ohy6kRFJZt0bLB7Uany8QUUjWnNOtz3lBuMmdY+Xlfr7zW+0xwBwFpcYAMZlRsXvAhYDJtcfARUtYwIiKm3vopDi8mBPgs2zHp6FIWvhmYJ31j1uV39wa9ipSRBFNsG3kwpBQI8uZj3zXHeBXXj+vsjuRM807Uq02bHWssjOSfVDz5IiJAMg5UaQJSCr+CztyBTI84pyT3mrHW6qstG6ZdPq5A+Z1t6SqXiuweoGO9WxODLPBPQaA31OkPHBxgV2YHlteB7ZDq4TsqdkXKjk/HgSNAt4jtYti8wRx5YKWn3dV9UUgJTGXuwO54eGAJU7/2aqGdWv0Ab2R/Pm2TgdN8h+Mq5WCbYnckl7q7PEDtbXhDb7PHUcX/8u6vk0HsgYDqWyoV0E92RR2S7WsaP0+hnEqoM/6p9iP5WA3F/vQQuNQxo5HoARNKpt/cnGyLoRQ8cj1LgOGfOr90xjwB3TZN74zvrNV2QK2Q7JKB9/y7HkWmKffZ3+xxvLNLTiPICzu8QAMC4zKvlcwIPVDTZat8wOLK8NLj4PBj2Lor/52daC7gCMpKSpbLwbI5+bVc/JB0L7k412oi0RWL184G/DvOcix9uxTrXLb9BQP480V9jxlUtty8L1ERZEbVg1d3M4GUNxUnRzUhmQQfDWPcEkQTPHVG3SfBxYXmunOhbbeDYVAWxUMAKfVGpyb6v/3nVLpkLAg4p0sLrBzm96xAarGyLA0rMV24u6ImlMCDDULm4C6Slebee6C0JaEbrOvBL0SlJt9EYJ16EHH96wIJiia5F90ukLup5HdGltacPOjtIOO9pSHp6pOSZDTADQn2y04XTG9lU1RTbOeEDmwZo+47rWmtJ3BOJcbxwb9tkDk96SzrCxSO+mf4851gSW+Rhurtd88sPLGI63+uTdxRxPgX2Gh/CZ/vQZGhL+1A2OP98NMqesf095q1184V4by6SnMc7bCtfacDoT1okHiJw3zjFjB9k+zeGe8lb7m4VdMQCcxSUGgHGZUREA/FnhlIIYrG6wY61l9sHGBfb2miI7sLw2CDgpAAKGGwlJKl2f5NkzgrqOioxMigQdmQACN+8S9cHjPlhedR5qqI4wQhSyUhQHltcGBUpwqjqUKJeKj8rDJ3UmoKFi5Jj52Cjdwx26x1rLbPLNO+zyy3cF5knKT+1RbJrA5a5Emw0kc5ETTQgEODYaa2020CYO5vDTOCj2iQCFStGzv3IxDqczkfEViNb9dFnnA5Z0sQo0qS0eyGqDhubDX6d69DcZVzKMZ9c+ERkfrm/OKZldb7ho3HpLOoPb1jOEBBliIbmOOD6evVs1N+qCJniiIcA598YY145YTIIqMmJaa75NPGJOY8451Y9n61gPDSex4nw3yNSpP4PVDXawvsYON1WF9mrMyZILhO1MtNtAMhd513SPZ97Ud84/ZdhAMmcXX7jXjrWW5WXzKNe0LrhWNWd6vn+feC1BcpwIenaXGADGZUaFAFCA5511j9vV/m8ES1bKgGCJwtqzLBJyCryXkGKslf5nzi/PcBysr4nk5/LgixsAyB5IgHogSiVFoEEhTqaACpNuS/VDClHt9d9LARxfuTSS04ttz8eGeLZHbe+rbLahVNYGkjk7sLzWjq9cagPJXMTNK4WrHZtK0Lu/pt4+2vxAxOWtZ6iP+fIzqn9y/fqNPOoL3bw7Sq+nLuE46/8tC9dbX2WzjWXSdrC+JoBrxUiSWfFjT/crQQhBPNcFgRXT0eTrv8ABgSLr2FY4deoJDRqya0wR5I0OzQfnl/OgOscy6dD/vsrmCKulupjbj4aJYg/JBm8t6A4pUegeVcocGmYChQR+BLSqk4CK75jGk8B2IpeMjANlBOeX68QbhVqbHpiRzWQs8o7SqaTtkz+5OcSFegCo+yhfvLGp7wUSJc88MCNz11M8FZusMec66Cmeyk3J57BfHCOOw9aC7siRl17+xi7guMQAMC4zKj4R9P6aeju9qtiu/NkddnbtEzZSWxcBaRKk3KjBc07J8Hg2kNY8mQC6SggyvYuQgtHXS4Uv5eFBhAcLjH97Zf5ma73j2Qgo3JVoi+z2petFbiaBLH3u3WM7Sjvs7JOFkX748aQlL5Djx2NH6dRpFB+/Os8uvnCvDacz1lO8OiQoFvsgsLavqikcqTWeTYVUL1R43FRANocKk/niCJQFBKXgpMDVHtbBvknZy6jgdWIX91a0RPIaEoiJBaLRIMDlAQnXC4GO5tMDCDI0GgcxoAQX7LdX1KyTIJnXEmTkO5GGRkFvSaddenG+9ScbI8Cup3i1rZp7fTeo3Jd8L8myEVzIQOCmpHwuSdW3o/R67kw9m2EdGjeND40bAii2kawd31GOI4EePQ9bFk4dY5cvdlDvaH+yMexG9gx68ylXAAAgAElEQVRgPqNSa02/fXoXb5gwjlCfccPP9qKukEuRa6q3ZCqFj3Y1c93SQKXngJtpyPzJaOgt6Yx3Ac/yEgPAuMyocBewmIrhdMaOtpTbwfqaYMnSSqbQk5CUhSpmhoJdQIqKyLtBqHh6ilfb/pp621fVFFEUdM1JqMrdSxDpN6IIkEioC2ARIFKxEVSqDgIlCfiT7Usi91BB0/InayaFJrCme+jW9ApQfZ3IJW3yH+6yj1+dF06gUP27y1bYtsLrefv6KpttpLbOjraU2+lVxTaRS9pwOhOAq2e9lGhaLjkqRMW1bS/qCueqakypuAlcCWC8W43xcIpDZMJi7/4XWN+ycOrUiL7K5gggJ/jU89XGgWQuEsdIYNtbMpXDjiyjmDT2y8ddkSXk81X/qrmbIxs5CP7IbvkYSQIevm9cq94FSOOHcYPe+OK4+HXFuvLtXCVw5/uv8Vk19zorpfaQTaXhpXdL75AH0gRmbBuvpaHn4z4J2sRyCvDpPZQbeWeiPcLI6fl6fxmK4edHz9A6U9gF5+ZYa1moy2dS0MY19ZGyicYBzyD2HhSOUZwIenaXGADGZUbF7wKWW1M7UL2VSqVDJemVFRWF/5xxTVROukYsj3YuUkFTCXv3sZQKGShuPCBTxPuoYKnsyAYSrAokCTT56/yP2BYpLjEgaifHl+NKgLOnvNUGqxtsIpe00bpl1lfZHImb48kHeytarD/ZaBO5pF369j12ZThhH21+wPbX1If2knUjW+OZSs1vPvc550ZKi9eRXRGY15oS8CNjy13Qcl1qnqncCUbEwPI7D9gUE+fbzbWg+gl+uTbYn9Y7no2AECp+AWEpfc29gEJP8eoQj8iNFxp/5sH0zKYHm3qe36hD0JcPaNJQ6k82BpDCe2loaX4ZkqD+63u2k+1VWMm+qqZpIE9/05igoUAXP9cpQRbXI9l3vju9JVNpasj4i9neV9U0zXOQzyXt5YkH2fk2tRFkC8D5ezl/BNXqn4CjZ6Dl7hcLHCeCnt0lBoBxmVHxLmAJGLJjEmA8Dsq7RP1vMkhS4HRPUcD6NCxkwHhPPpDlFQrbT3cOQaJYMNXhjwIjqJXCYLu1Y1P1U8H6domZk7KiYiIgIehiX5Um5FTHYvvdK1+xoy3lNpTK2q5EW3C37kq0hXNcFSPYV9ls49mUffjsg3btRzeF1C1yrwqYUAELoOh7MhRiKcV0yB1IV7jWCePSdpR22OGmqgh7RHBA9m5vRUvoh+pWag6NBeeE7lPNuwduXF9ab9wYoHkZy6RtPJuy99YvtIsv3BuYou1FU+7Eyy/dbQPJnJ1oSwRmSW1T7jyCBc07AQOBN5P50lWrNbajtCOwk+oL1xc3Qwwkc5GdpWInfVoX7WImy6b5ktHA94JjqfeYwP1QQ3Xop2f3CJpU3+6yFTaWSYecfvyOrK/GTaBHnxHY816CR36ntXR85dLIu7SnvDUYb3qHxDL7vntjiM9i3B/ZPb7DnA+uy70VLTZY3ZA3XIbg2MtgyUStY41bvAt4dpcYAMZlRoVpYCSwyeDobwk8KjkvqL3lLaXM2KR8jJtijLzriQpdYELKhSwEgZvu9wK1p3h1xNKmcJd17pkGuhSZUuKddY9HFKkHiXSjEtT63GXsP5kxja3irgaSOTv/zEN2+VSHnelaZP3JxgDgxAxKsQ2lstZX2Wz7qprsaEu5HWsts7NPFtqR5opwqoMUOceOCm5Peat9/J07p53gkI/hUT9oEJDN2JloD4BJCosMntoiYL6vqimwz2TJBAY1PponxUERdHLDzYHltdafbLT9NfV2uKnKjraU20QuaX2VzTaQzAVgsDPRbkdbym04nbFjrWUhjrK3pNP6k43h3rNrn7DhdMY+/d5c+2jzA+GIQAEcxoMqflDvg9zYeibBv9aCwKQHGmIWBb7JznHcud4FOoZS2YiBRAaSTKgMLwEWz7pvL4rmE9Ra4XrO55LVd3srWmzyJzfb5ZfuDuuP8aUE5Iyn5BrsLekM6XW4DnUtU8DsTLQHYCsDQ++HALRAoebPpwCiQchxltzjePv2E+hLxuheGQlsu5dJ3mj2oFQyrad4dbwJZJaXGADGZUbFM4BSop6No7Cl+4eMT77rKdh8ihcqPQl4HyBOsEI2xbswfVwSGUBa5QSr6q/aolQnAiR6Pus+1loWcuDxWaqTClFKRe2gdU8AxWsJWncm2m0sk7b31i+085sesffWL7TRumW2t6LF9pS32r6qJhtI5my0bpkNpzM2nM7YoYZqG6xusP019eGz4XTGBpK5oOA0ngT4UlzD6cw0NxRBiO4n0B5KZQPTtreixXaXrbCR2rppm2cIqvT33oqWkEtR/SIbKIUsNodj7QP3e4pX23A6E1zHioVUDjsyrB7caJ7Ud64rAZVdibZQ976qJntn3eN2sL7G3ln3uO2vqQ/s6t6KlohxQqOFGxkIuMguCaQJhLG+bYXXT/cgu72jtCPMAxkkMvaecdT/XN/qPxMn7ylvtVMdi6cBffXtRFsizBPfJzJUWq+ffv8L9s66x60/2Riexdhe1cvx525kb+z1VTbbh88+GAFJNBZlFOlnpLYuMOF7ylutP9kYjAutAYFSzh9BocZN4E5gUu2ikcR14A1D9sUziQS4nEfG+/Jd+PtFK2MAOItLDADjMqPCTSAELjyyirFvUjayPqk0CQzyMX0S9rT4yaS9/vAmG8ukA0PBewUA6a4lcKFF7YEfg6q9Re0BCgEdgZoU+2jdsgg7SQteSmNnoj1y7uzWgu5wSgI3O3gA6FmxnuKpjR/X9iy0yf8110Zq60LewcHqBhusbghKbaS2zg7W19jB+ho7varYLnzrfhtI5mwolQ0sFU/DIEvCOeCYSGFJ+TDQ3Ss29eFcd4FdenF+UPh6ln7vLlsRgJ1c1VLO/cnGwF4KBDIx9GB1QwRoqA27Em3BzdefbAxASECT7fO7OzXn3NUpFs4rZMVk6flyiev/8WzKhlJZO9GWsH1VTWGnJw0WGk+a/4bbn5nGJHu3oAAH3X9M+XJ27RN24Vv3R9yNNJ4ILhkXq3XPd1igUoC7t6QzwmQxX+OO0qld7toQRVcqkyUT/DAEQ+9pPoaM4MjHOXK9Mocf51Dss96R/TX1NpZJ22jdMhuprQvvhmf+CJK9Iaf2qP17K1oCwy5Wlwam5JPeHfaDspMxqkx4TUNc7eH60fqMXcCzu8QAMC4zKgKAvyxpCbtA6XLhjkju7mUMH4UWrVYqUDEfVHIUbjqMXnWTnSJw9PFSBJmqV4wJ7xeLROHMPuSzxgkUxSaxzV5ICzjTxUm2gs+UFc/r2HddP1jdYOe6C+zsk4U2lMoG4CaGbyyTtolcMrh7j7WW2UQuaWOZdGDjxITwOC8qpx2lHTaeTYUzXHmuL+dQMUtS7nRBblm43obTGbv04ny7+votkfOIGTsmpkXu0r7K5ghbKVArhmYolbXdZSvsYH2NnelaZCfblwRX9o7SjsBsSsmyb3K5EqSP1NaF9URjQG31DDFBI5luMTF8B8iA7yidStszkUuGer3b8/9n792Dszyvs1+l7RhjmwRnm9hOiBkfUS0sIwl40enVAZ2FDiBVAmSLLY+MqQdsN9upxyRNvjSTxElTkrbTdPIx7pep3MZM945SzSghmyHaEFGggpFEJYjAHAIGfMLh4AOgjNf+Q3Pd/J6l119T/cWMnmfmHcT7Pof79Kx1rWsdbm+gcLzVfv3m2VQaYwLYPobQx/PpOr/G+Q6JceQWhARW+4pqIsZPT/ZExr62BlS7yXLqHfHAxb+3bMPWzOhuOZwHjhPPJ8AWoNM+wiNVJeE9GasrtEM1RTZUXmYDxdWBSWdMKo08tduXH9KaHqsrtGMrl0a8HYzxpAHAdbUj0WTHmxKR+eFHz9f1lDkaR4HlGABO7yMGgPExpYMMIBUYFSdZDgo1Cjyf1CEhTTBHwU+lSGFOZUCWif96oS8BKtbSW+lSiGSrdI7ax6QIuq125TcEplMKYtviloirmrUCBTLJkJCBTAX4tP2YztG9+nJX2Fhdoe1JLg9bhAmI7i6ss9HqYjtcm7STLYvs7GOZ9t6mz9j7X55jR+rzbbhiWbiOyRR6PsdRSt+zpz5jmuCGQEngb0eiyQ6UVk5KJuCz5Ebdm6y1XfkNYTeQ0erisP2g4vb0GSiutrOPZdr4/z3brm6+2cbqCkORZA9wvPuOylRzLlAi8CXWiuwsmUvGw/mscv0tl61n/ARctA71HGascy3T3am2qR0sEcL3qDurLbhU+Ty6DdUvvR+MQdScD5ZVBCZK4IbgWffzoSBaP3xfCNZSASAybp6R3F9SFfrgs6AJiglo1W++IzIgDpRW2uHapJ1/+n47t3aBnVu7wE615tjh2qQNlZdZf0G97cpvsMO1ybB7CJlXAjGuObGMBMoCvwSpXnZyfb3RkREBnuqLd9unAoKUwzEAnN5HDADjY0oHdwLxTJgXfFIkCpqWoKIy9O5fMmYUip4FoWKh21X31PMExrwCoQvIu249k+gZDBWWJWgj8KEiolAn6ydwR1BH5oIK05c10ZiRwerOmgi4VzFbgQeN/0BxtR2uTdqxlUvt/PoH7cOvz7YPv/FJu/DsPDvRvCTU/ZN7ixm/BMA+iJ1KxYN2Xa++MAuW57K8i+ZXblxlLCsgf7himY1WF9tYXaEdb0qEJI2DlaV2oLQy1IM81ZpjH3ztdrvw7DwbrS6OZGxqvjTuHGfOGcGfWGcqZIEHrRuysUwu0IeuOpZuIUOnNaD/j1YX27W/u8nG/+VWO7d2wSS3oWckuf5TgVG1X2wkd5bQ+0NDyscgyvUq17F25yEjSrf/oZqiSe5WPXNXfoO9viZrEnhLZQhqfrRWlKHM94ogmu+02u8BJgGUAODeZK0drCy1YyuX2rW/v8ne/8odE+/Jc/fYmbaFNlpdHJJEZADICCOQJnvJsjXqp8bRG6bela3vlfTWndVmY3WFEdBPwE0vg9aZ73NPdpwEMt2PGADGx5QOJoGQzfMMB5UbgZxiimjFEzR1Z03sCUrFSHCne6UqpOpLaPh2SQj6os3+Xwpj33YJ9wOllYGR1DkCjD3ZqwMgEXtCYNuV0TGp/QKEHBfPmhIEekUv9yazFcUyqFj3kfp8e6Mjwz74H5+2azvut6t7HrX3v3KHvdGREbJ+lVxBBoesCQEC26s2SimSxfRgRX2iAvNAXc8TKylmZrS62E40L7FzaxfYW53p9kZHhp1elW1jdYV2sLLU9pdU2ftfucMOVpbakfr8AGylHAncBD49WyUQymK8ZEU9u0IjSMpXY6bMbI4B16Vfc+vmPBPGVUD42MqlNlyxzF5fkxUAoNZZb05rmHe1m8CIrBeLQH8c8NC75o2o7qyJ5AX9zRAOjh0TOVKxmxw7jYkyhVVA3IdsbJq7MTDqY3WFETBPOUM2mu89GWgxloybJVDfm6wNu+Bcen6ujb86y64MLLKr37/Z3nnqIXutMTe4gvtyVwT2keDKez4I8LmeKHNS7SBEQ5Tjd7wpEXZ6Ieuo/3ujlmtW58QM4PQ+YgAYH1M6BAD/9sFohXsJGTE+jGmhgvGWuf/Xl4lRHKGUIl1QYgU8CCEr5Z9By1/3SVVYmUqaJU8IFqjMyN5sW9wSYnUIcjgWq2ZvjLCcGkPdi0KbQJv1wchaSYlJgbNMzL6imuDWeqsz3a68dJtdfPd5u/T643blO7fam088HGKc5JoT86a+KjFE/+dcqu8ab40VA/cZz0fFre81xlvSO+3yC3eHxI8diaZQR/FwbdJea8y1N5942N7b9Bm7uvlm++Brt9v59Q/a8aZEKHotIKtruf7IsAoEFM9cF5Qwz/MMsUAKQdL2RHNwtxPUaK6okD3A15rg2l81e2MkhlDrQffamdcY4gTp9ks1J705rZY784mIYcaxZ98EWt984mG78Nw9k9aiTyaR+5qu557s1aGEDNcA+0lGUW0hG87ySVz33VltdqC00q71PWinWnMibSPTScbLJ3BpvDRvArT6Wy7p0epiO9WaY5dfvMuu7nnUfvfRKza+5Sa78Nw9dmzl0pAQ0l9Qb4drk/bhNz5pY3WFEUOP8o8GE+Uk54sMHeXcqtkbIwaTwicEzAkQvezyxiLBcgwAp/cRA8D4mNLhy8AIpFGRSdFtW9wSrHcGtdM6l8DT94yrowuDVfG7syZimKhYqChSMSwEoGTjpIzkFlM8EBkvxh7uTdbaubULIs/zwlYubypGuqioqMhGbknvjAAkz5IRLPK56g+ZJvWvL3dFBECdW7vALr9wt42/fJON/+MMu/T8XDvb/ogdrk3a/pIq25usjbBiBExScAQYdPdR2ev/VHisR6d5apy1IZKM4OdRpV8OlFbaSFWJvdaYa7/deK+Nb7nJ3j9cHra6U2alAKB2PtF46hmMN9VaY3/YDv0m1kjuS8VyieEki81r1Q+CJM2zZ66V1CQDSM9gvKfA0pb0Tju2cqkNlZdZb06rvf3k/MBq8Z3qyb5efFp9FOhlewi+enNaQ9KM+qGxIzNHgMP3V8/3LnGOFwGLwNGFZ+eFupd6D+Sm1vu3I9Fko9XFIZ5TwIiua91XxoVnNikP2I7+gnrrL6i3PcnlgWU+//T9dnXzzfa7j16xK9+51c4/fb8dW7k0ZKDvzGu0E81LbPynd9iF5+4JIRSSgZ590/M4HzToKGc8Q5vKqPIGrt5FZq5TbhAkvvpocwwAp/ERA8D4mNLBGEDG+0g5SVCJsfCCh7FPjHuTsGRhWAI1WdWe5fPWr5gC/p7qHLJscpNSSXiQpfNYAoLKjO5Dto+uOq8YPfDxIErjRMDM77qz2uxs+yOBbdJ3zM5WGZWh8jIbqSqxYyuX2m833msXnp1nv914r51tf8SOrVxqo9XFtr+kKmyBRSbGs3secHu2VQBDWeFkR9U+jQVZHCoq3UvlYfoL6u1gZamdbFlkF56dZ+M/mmG/++gVu/jmenv/y3PsTNtCO1KfbwcrS4NypiubwITzSSNDz2aRcV/Tja5Vxn0xBpL3EkNNUM73Ru3hHtoCBZ511vnKWu/Jvl4vT3sYE3B51pvAVWtNQNCXS2If5dblWlSfNe9MHNGzNK98f/le6Tm7C+vswrPzwm456jvDH5QsRbAut3eqbSLVV82xxlDyh3HEAs8aSxlLr6/Jsrc60+3dDffZO089FEINWBLmZMsiG/+nCSZapZs8w+dBnL6jMZTKTUtQ698h7+L3MaXeQ8HxjF3A8REDwPiY0sEsYLETFERkMQSAyI6RkfAbnvMjxUyXDq13KThl8norl/E9jH1KdT8pKdVh6866vmNEKhcLgZzuL+Um9kRCmUqf2Y4EcrqegJXgU3Fhui8BI8EAx0cKXqVTFEN3qKbILjw7z062LLJTrTl2pD7fRquLQ8yiXL9kbeWiJbNEMP5xu7ZQUfEcslwcX7rnCAJU6mW0ujiSxPK7j16xa38/4Zo72bLIxuoKIyVhxDoKcCqJg8Ccz1Y7mcUtkMX1pfWr8VEiBGvYEeRqnXJdkl0m0BPLKgOJcWx0SZPdVnmQN5942E40L7E9yeUR9nnzA+sjSRN6vjJwNa+8RsYOWScaJwQdBJQeQPr1rGdprGkwHawsDffWvSQv2HaNkxg3jalALD0ABH9898h+bk80hzqSuq/KJR1vStip1hw70bwkGBhkAJVx/s5TD0WywinnKAdoIFHeCUxTphAA+3P5vdYKZSflG+WCxv9/ZayKAeA0PmIAGB9TOugCpjCXcDvakBexQAkEVJjWu2aZCEA2gqyWhJcyaAkyBKIIQgigCJDUXi9kt6R3hir/eh6LW3dntQVw51lOMl9SPB/HVkqhqk1ykTfO2hAAqo8FIjOl7zc/sN6GK5bZsZVLI2NMZpFKbmdeo51elW0jVSV2sLLUDtUUhbg/lbboL6gP28RJgfUX1AdA019QH4Cxnqc5IoBQfONodbENlZdF4o/096a5G8PG9IyP0ndqv7Z6E3g9VFNkp1dl2xsdGXbhuXvs3Q332Zm2hXa0Ic8O1RSFXTwIdAjOqER35jUG4M65I7PL9aT+CZQSJHqQ5hkdATUqZzKMLEnEOfegU+EVfD/6clfYUHmZvf+VO2z8n262S1/8bBgHGkI0RghExdISdCsZQ/chgGN75LrWfctv+dPIGtT4MBSEYNqXjxIrSbnAd0yG11ud6Xb1uzNDzCHXlp5N447vEndK0Rgx03xfUY2NVheHbPNDNUV2sLLUBssqQtkixn3qev++0yAli8o1pfbRteuNKII+ssGUo5S5XGO6P13+WzPbYxfwND9iABgfUzroAhbI8YLNxw8xzkWCUezeprkbI/fRfqgEFd5y57Mo7AUQPbiUG4tuNQJDuqlomdM9yd8lbL3bhcqM7KJ+a5y1YRJQ5d8El2T89ByBRN3zaENeyAzVeJHd0n16sleH0ihScPuKamyovCywawJ4KnGh/ukjcMqx90qIQFv79IoNUTwid8YQgCDwEUjoyZ7IAN62uCXszzpYVmGj1cV2tCHPjjbk2YnmJXaieYkdbciz0epiGyyrsH1FNQHI65lkZATuFEfm3bOehdY6EKgX8Nq2+PoeuWTyvBFDkKc+cl9ixhcySUBt1fz5rHmtdf1/2+KJrd1Y3JshGWSbaYSQfdZ6V3/Vv96ciRg9ATAacSzeLcOEwJXrmi5YygbvfhYo8+86w0p2JJpspKokxNv6PYVZssczZWrT9kRzOE8GQV/uirCGuG2i1pYyrnWuxtGzelpPdLt68Oflkca3K6PD9pdURdahZw4pFwgmU72Xeofpso/LwEzvIwaA8TGlwzOAHsx5JUo2Sr9RIFMZELx465XXCVAI4HiLmf+XsqPg1L0onLctbrGRqpJILBuLLasPBFm6Ts/cXVgXSTLYmtluNbc+HdmCi8zZ1sz2EMfkhbkU3ro5z0SyCzVW2xPNoXYZgaY+DLrXuYdrk+Ea7WuqItHc5kruP7ppCZo5L1RKUvr9BfX2WmNuhM3kPJOd4ZiQ3RATqd1JXmvMte2JZhuuWGZjdYU2Wl0c3NdyYWvnE+1MoXaKVdyaOZF9TWZXY8+gfbWBYE9zxhhOKXmuWYHKgplPBpAmgOVBoJ9vKnaCGs8MaU0THPA87TZx6fm5kbIsBAO9Oa0B/NCAYTgF1yTZOzFlHiwTUNN4e6szPVK2JNXYqb9b0jvtaENepEwS3Zt+HR6pz4+MH1l5MpZ6BxtnbYgYR3LhM4ZR+00rAUnFxVWMnEkyPilDbCflmca7v6A+jIs3VCmLurMmvA0Mn+Ha4rj5ZBOuRY6fB4xxDOD0PmIAGB9TOgQA/2d6VCkIEHhLncHIBHXeYmWRXF1L4CiAoP1iKTzFIlFR0D0pa19gieyC7tOXu8LefnL+JBeVBLvcYhTYUrYHK0vt3Q332fGmRAjmJ0um9jB+jkHo6j/BEFlQAhI/dj74vjfnet3BnuzVoa7ZieYlEbeuYp4EmvoL6m1vsjYoVgXR67lUHmKe6EqUi29LemfIwtU4qH1kX9hXtZ0Mm1ybr6/JsuGKZSGbWbGMI1UlNlReFnYDUfyilDfHlwwy16P6KFZS4+7Lh4iN41okiPCsK9e62qF3hVslclwJjvUc7jVNFohgmawZ3xl93nzi4UjZG1++xYNf//7y/R6tLo6sQa5JMtoaC7la3+jICHGl9AxwjGmwjVYX22uNuZPAr8ZRzKhc1NrL2Rs/XHsaD+7aQYZcjLPei+2J5pARr72mZTDpdxoDmmux1mTEWdlAIRU0qmg8CTz6cADGB6qPvTnX65HKAKexRXCu37Q+/vbB9hgATuMjBoDxMaXDJ4FQQbzVmR4pCeOVvYQZrVcyDgQBVFIEkufXP2gnWxZF2CICPzE+BC50tzD+jvcQSyhFoz5Rcek7CX+ya+889ZCN1RVGAuXVP4LKVFY63YI+Tsq71vW73Fne/cRxV1svfuHzNlpdHJ6pEhsC0wJ/Ahwsl8G+kNmQYuO4b0nvDBnIUjRksXQPzgcD+MnKKq5qtLo44gYWC7M3WWv7S6om1fyTghZIUN06D7gJgLSGCNo09qoVR7ekALDmX2tHz+E8qg0sR0MgR7cr3e5c/xo/JoiwDwSkfnx3JJrsrc50O9qQF9rGOn5qH6/VO6FYTg9SaNh4A45tIZtKQOb7TlZQY3O8KWHHVi6N7MetZ5HB3ZNcbuefvt/6C+ojtTUpc/g3+6m1R3e75l9zprWm9ah5JOjbmjlR+mmkqiSyNZyXYfp4I3Rr5vXC0JJFmx9YHymRlCr0QvUAvdfFjxfXitoVM4DT+4gBYHxM6RAAfPXR5ogw6s1ptf0lVRGBN1BcbUfq80PNPikPZnl+HHOSSuF0Z7XZsZVL7WTLoiCEyUJ4dlFJJ1J6BJteKVERCSxI8e/Kbwi1AcXiCLxIYItp49Znvu1D5WWTgJVXgHTD6TfFMKpv+0uqImUmyEL4cVNRWykuMgjqmxShL8jMsSVwF2OqPsgQ0DN4ngconnUlG0dQpXapn9qjWEDwQGml7U3WhqxfBeWLxRHQUD+l9HV/rhUCP8/O+VI/XRkdIVN6d2GdjdUV2pH6/MA6knH264wKmetRbkiu6VRrkwwfFTuNlp15jZG4um2LW+xgZamdXpVtR+rzA9jQPWmwafw9CN2brLXurLaQSaz4Sc4d3yutGYZLsO8EULoPjaIdiSa7/OJdNv7zuTZWVzgJQBFA78pvmKhl+VhmhCXkHBLc+zmnEevd+zKM9L3azX3AySD2ZK8Ou870ZK+OGKJcV57hU//IoOq98e8hx5nrgEBX59PgkZyQfI4B4PQ+YgB4gx07d+605cuX2913321paWnW3d0dfrt27Zr9+Z//uS1YsMBuueUWu/vuu+3xxx+3M2fORO4xb948S0tLi3y+9a1vRc4ZHh62goICmzFjhi480W4AACAASURBVM2dO9e+/e1v/7faKQD4f332qQCQCD7o9nj7yfl27W9m2KGaouB+JECkAvBCSwqBSpkWNYGF7uM3VpdwJiikkhJTJHeVAAOVNcu9kCmSwN+Z12jn1i4IQMQLYf1/qLzMDlaWBqXtFYdYCCpugjnvKmNcmu4lwKS+bU802/n1D9rV798cACS3nKNrXIDW75nLXRoI1NUOtkUZoVoPbLevQUcmaNXsjQGUaDswuaO3ZrYHJczdRKTo9xXVhH2ZtXsI6xjSTav+c20QgOk3rT31nS7SHYkmGyiutkvPz7Uj9fk2/sotNv4vt9pIVUnkvrvyGyLMneZV4IkJHGR3GffFkAMxYQTQAmtqM5M52GbN8YHSyghAYYkkvjcEJHomz/fzL6ZZ61r/5+8C4HpH1H6628nSn2xZZB9+fbYdrCydVAqGc7k9MbETy+HaZCR+V22lnNA4SVb4d4xhHZwXMcEykpglTyZbjCFBpJcH/n3275B33xI49+WusFWzr5e90rzIOPWsK5l5ys2tme0xAJzmRwwAb7DjZz/7mX3pS1+yn/zkJ5MA4IULF6ysrMy2bt1qv/71r23Pnj22ZMkSy8nJidxj3rx59pd/+Zd27ty58HnvvffC7xcvXrQ777zT2trabGRkxH784x/bzJkz7Yc//OHv3U5mAVPgeuW0PdFsg2UVoS4ZBRPBWE/26sDUedeFBJxnongPXbcrvyEoXQpyPifV9QQTdN0IOEiwC0CRWejJXm37imrs8gt3BxebFBtd41sz2wNIoUBXHwmqJNzl0vTK1issnwRAkLW7sM5eX5M1Semrb7ov3cGvNeZGgBEVqK/5KEXfl7vCzj6WGZ6bKi5RoJ5uU7FJ7M++ohrrzmoLW2DRJScgrhp/3J9XDCALdYv5EwjTHHAuCYj1PLWpN2diVwzt93p6VbYNlZfZ8aaEjf/0Dhv/xxn2/pfn2HubPmND5WVh7E+2LLLXGnODS5CJAwQHAk0EREwqIGsjNkjzp7lkvBmBhA+v4Nipb2T/yC7pnkxU8a5nAj6+W3qu3msaaHz/+Q542aC1phJA/r3Re6nn7yuqsWt/d5MNVyyLsJE6j2EFfP91T46dlxlkBnUP1pgUKKQspJHD95d95735nvgwhe6stkgIA+UgmVEfU0k55qsVbFvcEtcBnOZHDABv4MMDwFTHf/zHf1haWpr95je/Cd/NmzfPvve9733sNT/4wQ/s9ttvt6tXr4bvXnjhBZs/f/7v3TYCQG/FSsh0ZXTYqdacCCMoZaPffekJCjUqHAo3MkdeeHvLnQrAC30BPyn/geLqAG7k3vEWPMEjrfpti1vsQGml7SuqCdY2FaraReBFkKr7+RgqneNdRRozjaPuQ3awN6fV9iSX25m2hRFA6Nks9nN7otn2FdWkdKVxLMgI6nN6VbbtTdZG2kbwK2Cr69UeZoz25kwkC/CZfI7cxdrhQ7/LTSegoLklE6kPS3ZonjlX/QX1dqo1x97b9JmwKwWLYJNpPlybtMGyCttfUmXDFcsiQJbhCCpJQ4ZY7CznkEwwWTYxWanYchla+k2hCT7ZQ79rfWitsuQSAY5nbJXgoxqcWqfHmxIREMm1RsDh16Zfs357OLKYqk9JAEqgKybwzSceDsW3ZRAyJpDPS+U+9bKM7aT7d9viFjvTtjBSb5IMOWOMNQ/cAUXzwY+eqbAAnUNw3ZXREfE00J3LmFWNidaQ+kmGcfMD62MAOM2PGADewMfvAwC3b99un/jEJyIv8Lx58+zOO++0T3/607Zw4UL7zne+Y+Pj4+H3xx9/3BoaGiL3+eUvf2lpaWn27rvv/l5tYxmYbYuv79VKYSMBymxUggEJPO9OYkkI7wLZtrjF9pdUTQJO3DuXIFT3kkCk4lfCgwK89yZrI8keikGTMPeJI1QUKgxLgS22RQKa40AlRIXrx47AkGNCEEcw6oHjQHG1vb4mK7RF7kImm0iJCEiwpIwUvtpLAMznaLcEuUDZVo0RQThjEMnqvL4mK+xtSxBB4K9+qH0EgsrAFBDUdwQ0+l7XCdjo3BPNSwKYpCucDBCLFXM96DwCSgFIKnud15UxkWB0pD4/AnrVPz1fgEvPZ9wgE1g0r35HGa1/znVP9mobqSoJsX3qB+dY15Cx5HwJjKsNHAc9l5n9ajPnVOtBBiLZL63DkaoSG60ujrjGPSvJ96ovd0XE2NDcElBzHPw7KRlBwEfjZ3dhnY3/4wx7fU1WZJ1zfAnOCWY9y6c5J/sqmcHYvz3J5bYnudzOtj9ix5sSge1mm3m9jAh6ZDyrHAPA6X3EAPAGPv4rAPjhhx9adna2rVmzJvL9X//1X1tfX58NDw/bP/zDP9js2bPtz/7sz8Lv5eXltm7dusg1o6OjlpaWZocOHUr5rCtXrtjFixfD5/Tp0yELmMyBBL0EGAW+hJMEFuvrpVJOdIFIEEq50v1CFkDxZ/5DECJWQy45MTgjVSVB4bLmnp5FBoWsooCWBDuVvICAYpTIjpF9IJvI38j0eCXH52xb3BK2iiOAPb/+wciexRorHwOnrF0fU0nwRICicVXixbm1CyaxpuyL4tgIRGgUqE0nWxZFxpr9V5+YpELgyzhGPZMsK9k1/U5GlN9vW9wSsqs5ZzpPTB/Lg3gmiAqYyRSeDVO71C+x0qwNSdbIG0lkHPVslRnZkt4Zskj5fule2xPNITSA7yzfG713Yuxp5PAd8cCPY5+qnJFPxlLb1E4VoFa5JLVX13IsOId7ksvDdm58F2Ts6Z1j7CP7qt9UA1PvCZOy+nJX2BsdGXblO7dGmGaW0yF4JNDUOPD9Vr8JJrsyJhJvFDPck73aDtcm7YP/8Wn77cZ7g8yhx0VxppR53ojmHPw/2StiADiNjxgA3sDH/w4AXrt2zerq6iwrK+u/fHlffvll+6M/+iO7cuWKmU0NAH71q1+dlFjCLOBUwkaC2FvsZP48m0QGkcKZ7jkxOQSKXqBSuTJWSQJ5R6LJ9hXV2JH6fDvTtjBkR5IVZHA6d8bwLlomT6ifA8XVERArcCFgoTaxz1QiYkOoFFljryd7csykFJ2eu7uwzvaXVEVcllTQBKCejevOaou4ecUuEax2Z03s27onudze6kyPKHsqMV/LjS4q9ffYyqV24dl5wc1HEEkQTWZNbKYYNmZeyzgQ8GTGqhT6bzfeGymQrGdyG0CuI61HuumlTMlCeZAn8CVAqbaq7WRvtqR32oHSShv/0Qw70bwkzIvmnMxmd1ZbiHklOPGAjPUaCXi7s9pCVjXniIyRZ+aVAUzWnkYI93rme8n50/3IxrJNBG0EomITxcxJBmie5YkYKK62Nzoy7EzbwrBVn+5zsLI0vP8e6HpGTrGlaqsPe5DBcbCyNFzD5DH1ie+nZ4z1oVGl91Lvu9b8tsUtdrQhz8Z/NMM++NrtdrCyNDKmMshoEPNdVHvUj62Z8VZw0/2IAeANfHwcALx27Zo1NjZaZmamvfPOO//lfUZGRiwtLc1+/etfm9nUXMAfxwD+c2Y0AUSKojen1Q5WloY9gZWdqF0HyO5JMK6b80ywZLmlE4Hjh9/4ZASYMaaQoJFAgewKGZzDtUl7oyPD3v/KHfbeps/YubULwsbyVAISmhTkVBYHSitD+Q9fb1DAgbX6FMzt2TSOhcZGYyfXmJ4jJexd3ALcAgvDFcsCC0X2VfclYzdaXRzGkCC0O+t6XUa62ulOE+NEhSZFNlReFvpP4EylOFReFraM09hKmaq9jGcTg0ymTaCHLByztxnf6YHG1sz2MMbqLxlntZXPEADwTJd3B7MvdBt7plW/K2lnuGJZyJwnu6f51DixDXSNs+agX2vsQ0/26rCTihKoyDbqmSxNRJcmkyDI6Gv++R4SjNEo6s1pDf3QbiHecFRffRY557Ivd8VEVva/3GpXXrrNDpRWRlhhurIVm+fZZgIvFjJnvzW3bz8533678d4IiKcs9MwfPwRmOk+yU0bGjkRTJIlmoLg6bHm4u7AuhEtoLBTHLPBHFzDDPPTsf124MgaA0/iIAeANfKQCgAJ/GRkZ9tZbb/1e93nllVfsD/7gDwK4UxLItWvXwjkvvvjilJJAvnnfEwEcSND4LZDIaklQ0uVD1ybdUKwftmnuxrBPrQQkAZOEmv6mC5VsE912x5sSduG5e+zqnkdt/J9utt9uvNcO1yYDKyIhr+vJOEpwd2V0BAVNoMCAbwliKgMBq5GqkgjTx781HhobMk9SCrqGAEnPP96UiOzaoC3lpOSoHARk/ZhJAQsQaYyVOOBjq1R7Tm2VwvVsktbEQHG1jdUV2lhdYeQeYuKobPW7XF2KZZSrlMylZ1TEHA2Vl4U1JXAohcnSO7xOY86+6v4aD8bsERjTaNB1qZgtuuQ9ILzw7LxJ7CbBlzciaDAR7JOVU/v8utJ2bRxPrlmCVgJ4tVUMlGfw+Z77d4gs1tbM9kj9RoEqGWCvNebaoZqiMEcCcgSZo9XF9lZnup19LNMGyypsT3J5ZFeYVIaI1ijbw7HiWMiI2J5otve/coedaVsY+sw1JJDuDR6NtdYuDRbGCusdZGiB1u1IVUlEJvk+SI7S++HnrSd7dbwTyDQ/YgB4gx2XL1+2wcFBGxwctLS0NNu8ebMNDg7ab37zG7t27ZrV19fb3LlzbWhoKFLmRRm9//7v/27f+973bGhoyI4dO2avvPKKzZkzx9rb28MzLly4YHfeeac9/vjjNjIyYq+++qrdcsstUy4DQ0FJNw5dogR/sk4FIuhWJJtFIdiV0WGDZRWhPIkXcFIE3o1FACJh2pe7wgaKq4Pb8drOdLv63Zn2zlMP2eHapO1N1oa+7Eg0hUxQCXG6YaX01X66Nxm75XcSaZy1wbakd0YKKTOmiW4hKnLWfCNoppKRUldJGrpMdS/GXzLDmODBxy9p/vSs/oJ6GyyrmMTyUNGQbeHcSAG+vibLLj0/N5LdKyZHa4TsKNvrMy2pcAUu1WfNOcMLtBbl7leMGwsoy3VMxU1ASyZYa54xaUwWUR9qbn06koSjUjcCPwISGovdhXWTAB9ZK4YJsLizj30UO8zv9f4JdCjBijFvNHA8I6ff1815xvpyV4T9mD3DyXdcbaZ7lEw0n+PbqiQf3lextVpTCu8YLKuI7OWr8SGYJiDkhxnfaifZQLXtSH1+eM8Iqmm46H7emBOjp1g+9onvNcdA7yJ3dKF8o1HtQy28kdCb0xq7gKf5EQPAG+zo6+tLGWu3du1aO3HiRMrf0tLSrK+vz8zMDhw4YIlEwj71qU/ZzTffbH/8x39s3/zmN0P8nw4Wgv7c5z5nL7300n+rndwLWIKFwETuNAEhAhYCA+/eExtBF5EU5cHKUjv7WKZtTzQHYEAFQsDpmQq6WhTjN1yxzE615tiFZ+fZ20/Ot+NNCRuuWBZKjGxbPJEpOlJVErmfBDuVMlkVsmiplKYYI4Iysih0BZE92ba4JYCY4YplEbDHuJ+e7NWRGnapwKLaINeolAljhshaiC1k+RbtwOGBP8E3FSb7153VZufWLoi4s8VckhEh67YrvyESx8Y5Ifjbnmi2YyuXBgDlWR2tLyb66B5keVIZEFLccssTTPq5puuNLlQxqlTSLAnj3YliX9Xfg5WlYa9pjRuBlUCZXJy6r8qLbFs8EU+6avbGlGuDwMXfnwyY5orAmIkzBP5qlxhojZX6Jvc/3x/NE5nEXfkNduWl20LMIvut9SNPwUBxddgfeqC4OgIcmQjhjR6OCf/25+n/g2UVtm1xSzDyaDQREOre9HIQ9JPhpveAxgO9GP0F9REvidqpnYZoTHJu1f7ND6yPC0FP8yMGgPExpYMAUIrQs3ZSoGRU6Cr1rk6CP69wtma221hdoe0rqom4P3WP06uyI647KVEqD+0uIbftQHG1HawstbG6QjtUUxS2FZNLUQppb7I2tJvuZQIQMpgeaBEIaRy8S1jX8DoCkt6c1khgP8eNbREQlqvTKyYqeJ0rheKBsgfYnLu9yVo72/5IZL63Zk7sG5vKTUhQL5CgGpECJARMdOl7QJbKtUrl2Je7wj78xiftg6/dbsMVyyJGCPssMKS1oXsxuUbXEJATlDDphpmuAp5kBz1rxt1byMb5vnE3k+2J5sgWgEzyEbvYm9MaKd2j9URQRdBLI6sro8OGK5bZ1c0323DFsgCW1C6NE9cv76lnDZWXRdhIjo/+LwDJeaC7k2NGoC4jjS5QsmW78htsX1GNHW3Is1OtOXZ6VbaNVheHHWIUs6q/tSbVP7WZ2bRcXwSvNPQ4vkzOYia4jD7N0YHSyrC7Cz+UCQSBbAO9DhoDAX6dwzqrBIWai7gMzPQ+YgAYH1M6uBewF0i04PUdtynywlKAjhmVBEe9OROlHU6vyg7uJQplKUm6dnStWDO6YuS23ba4JWyNJYaAuw5I2YhN4zP1YW0/AgO6cel69e47ggzeg4rZK2kKdG6tJ1ZI9cI4nmTAGG9IoM1kCCoMtntrZrsdbcizyy/cbYdrk5E+07XL+3l2TeOrIrrqN+eTzyO765lY/c2MUrFkh2uToRyIn38BF7JABJtMtKAS9gpaitcz0mK6tma2R9YI+0DQybnwWcY6j4DoaEOeHaopsvEtN4UQhVRgyI9Rb06rDZZVRPpJULY90WzDFcsisYA0NFLVF+RYaI1+8LXbbayuMLSX2cAEplyPzMzVvDDUQv/vzWm1I/X5ESCq/imubrhimb3RkWHvbfqMXfriZ+1s+yMhcUKGIQ1F/25yTXpGlwygwCpjNsn8+Wv1m48PpOuWrJ43FLn+OId8jylv+JvuT0D+z5ktMQCcxkcMAONjSocA4L8uXBmpIScGRkKRFjMVGL8neKAVLKG+PdFsh2uTdvW7M8OuFnoWkybINnh2jGwN77u/pMr2FdVEarlp1wFuJ8b7MG5ICoWuLyrFVCCKSpmgg6yDdwEPFFfbO089FFFaUkQCXSpGfaimKOw8wZgxAnQpLAExKjZfUoQAZPMD6+3NJx62s+2PhG3VCAQ4tz52SfF7imnTHNB95dk9rguV5RBDyCQRMiRyJwoMeJaGsWf60OVGJStFKVBGVkfXrpvzjPUX1Nu6Oc8Etpsu3FWzN0bWve6pdSxwKRetDBSdy3EkCL30xc/aW53pgUEi+yNALLe93OcEAXq2B0Bam4rDpLvagyIyhxy/M20LIzFzetb+kqpQtkY7imgstf0fAU6q91njS/eqwL+yqA/XJu3iFz5vV3/1sF3bfq9den6ujdUVBoZf2f16BplcAmcaM2Ti9H8aD1xLjNf0oJeAdmtmux0orQztoCFLFk/j4pOsvKHtAR4Bvu7FMIDYBTy9jxgAxseUDjKALNsgBbK/pMoO1RTZ/pKqiLXqXYT6jUomFXA6WFlql56fG2pu8Xq6t7xVL5AhS10MlJTAzrxG25Ncbv0F9SFTUKwRrelUjEpf7opI8gKViNpA1yqtcil1MlK7C+uCkmVRZylZKXH2aW+yNoChQzVFdqJ5iZ1sWWQjVSUBYJAFVNt9rJ7c4x7AqR8EqjvzGm20ujgk1Hg2SYCLilXPUgY22eBUpTh0rcC2WGQqUZbT2Z5otqMNeRGXN5WuQJx3haoNHGcyJ4zLI2ATKNC6VTwd2VayfMy4ZpKFd6XqPK49MoZKHBLjyISlxlkbwlome6Y50LiTZdL4qAQTQTiZLA+MyZQRPPo543xprnW/Lemdkb2eGV/q1yyNFo3HsZVLI+tNiTx7ksttrK7Qzj99v43/4wy71vegXXh2no1WF9veZG0AfxpngmWuVc/s6//sH/vswRjfJc27vB3ewKFcScWu8nkEflzDHph7uUOXtdZAXAh6eh8xAIyPKR0+CYTxTNsWt9jpVdk2/tM77NjKpbYj0TQp+JuMAYUkBVhXRkcQWgPF1bY3WTsppnBnXmNw9RF4+dgxL3ilMF5rzI3EHSl+6GBlqb3WmBvclAJz6t9AcbUdKK20ky2LIuwj45IYx0Y2km4rAhK6AumiEnCi0qYy0rZ2Z9sfsaubb7bxH94U9imVW5iKWeCGMZJ6LufSl8DwcXGedSUr0ZvTGtnBgd/vym8IYFPzQyNAgNCDR+7yQoUnt+XRhryUW9xpPJlgo+/4O68hiOO6FDDvyugImdwcV42HwKbWna9bqXuo/eovgZjayhqUYokYV6rxVJu5XjiPWjdb0jvDuuD4kpnVevR19/gM/a53zidG9ea0Tuov157OZZwu50dstgAqwZUMOYFaratd+Q22J7nchsrL7ETzEnvnqYfs3Q332etrssK2dxo/JmyQaWR2LQ0mfkf3L41Wfu+NLV1LkM8SWmoHDQStLW8s8d3xiSJqp+7hE3HoYo4ZwOl9xAAwPqZ0sAwMBb2Uz9GGPLv84l2ROnSp3E/8V0BNf/PcrowO21dUY0PlZRE2YqC42q5+d6YdqimaZAWnErBUgv0F9XZu7YKgkJQ9OFReZpe++Fm79MXP2onmJRGWTucdb0rY5Rfuttcac0OMFwsVk10goGWsFtvqAZr+1d9konQvKqiB4mp7qzPdrvU9aOOv3GJnH8uM7FySSgmQraQS9u4rxr+RlUjFBElJyUXG2K8t6Z2RuEECENaYU3tSsSkC7mJexZQdKK2cVIBYLsytme0BWPVkr7ZVszdG7k1gQneqrmUNRK0VH+ulhAaOi4ARwZpAFkEiQSDHmuCTQE01EMlSKpZVJVG4ngheujI6QtwoCx6TdSOQUF+8G1NtYoye5kTnc5cV1u3kOyC3Ofe19YYRGVB6CQaKq+3KS7fZUHlZJA5vd2FdMOKONuTZa425NlZXGOp7ijFX38nu+XXN/mjuWUKJbCAB4lB5mfVkrw5jwnhcnassbRqtdPHze77z/J5rS21nohMZSz2bRkEMAKf3EQPA+JjSIQD480RNxG0mYbknuTyULJHgkZKTkiIQ8jFaVM4CVnSnSlD25a6wS1/8rL395PxJSl1tYlA0n7E9cX0LKRbyHSyrsItf+HwAeNyeTEL9rc50G+/9rJ1elT3JpaP/e0BHhoOMpHfhUBFIeSipgyyBzlf7jzcl7PzT99tbnel2tCEvbIOldnAMyaSR8fJ1CTXGVCR0iQks8V5qFxW2lK5c+IyR4zjQ7U0WMJVbkX+T8fLKj+NOkKKP1ol2qiH48AH5mg8aLRpTjYPWFMdW7mKOMdcTx0DuZIFPjdfWzOuJEoyvVT9fa8y1vtwVYW3594osnkAx4xu1fjUPPdmrbbhiWQiNEGChQeKz+8nyM36W3xPochz1G8ddbdqS3hlYQBkAMv6UcSxQoxjePcnlNlyxzAaKq21fUU0knk9ld+hiTsWm6aO1TJCsuScg1tx4Y41MnjcMaZzQeKBxqPdHY05gzPdRbU3VN294d2V0xDuBTPMjBoDxMaVDAPD/zZ1IoiC4YvwOg7wlxCngPi5LTUKTQIQCVIpByoC7QVDg6ToKXCk3tVuB1325K2xPcrkNllXYaHWxHa5N2khVSYi9k1LakWiysbpCO9WaY4dqiiYpAQI4CXYWi6YbmC4vXUelTUBJJi0V+zJcscyu/c0MG6kqCXFwGuOjDXkRME6FTLeRlD+/VzsGyyrs9KrswIh1ZUzEvtEFJiY0FbOohAwCXgEKgicpM64LutE072K6ZGjQ3aVn0AUrJa7+ca1sfmB9cOlufmB9CJbXdZvmbgzfkaXTb3oWQxo0LmQTGVOndaPfPAgSONA9yXJpLglq9bvGRjGTZK049gQnAqpct1oD+4pq7FRrTniXOQ40etQ/9Unv2a78hkh7uV4EcMRGMjNagIYMrTcc9xXVRAC1xkEAcHdhXXgXxP4JcFMu0EjkXHhgyzhZ9YnJSKmYYt5H68HPA0Ehn6+wlAOllWFs9Zxd+Q125VuzJsk+yggPTrm2erJXx4Wgp/kRA8D4mNJBAKhq9hRcAkp0o3lhREuUAJKMRU/26kjpFwlQKSxvuVMQklHzW6xJQDJjeX9JVYglO9qQZ2N1hQFcpHKl9GSvtsGyigioowKUsiBTJhccLXmyR1KiUqpkSnzCAIHygdJKu/ziXfb+V+6IJJiQhdQ+zFJYu/IbIs/Vc8Q4CdjoXufWLrATzUsmKS9lczJ2jMqnO6st1F1jIWUyLAS6dHVJMXrXtRQvAYvWmPrNWFCCbY4nk4+4C4gHAQKR3lAh0CVYYLvU7m2LWyK7gKjvBI6M79M5MnAYasH3hQZCb06r7SuqCWydwAHd6wLA3k1No4tsV3dWW4gp9XPFNtDg0n135jXaieYlkQQePV/j7Lc1TBVXp3nlO9KXu8LeeeqhsMYlE3SuEr3E9mnd0DVOJpgGl/rjv/dubTK1ek+4dr3BQ6CqserOur4/NT0eWzPbbbCsws4/fb+9u+G+ED6hcd6RaAq1OCVbtI74ztAY4brsyuiI6wBO8yMGgPExpUMAcHTlQntv02dsuGJZROHKOvcMF4U62ZXX12QFoeoF5oHSykiMDt2fvTmtgaHTc3V/ASYKerVBgfOysBVDdbJlkb3z1EN24dl5dnpVth0orYy4i8gy8HkS/nTjsLyKb5v6IyDDTEQqWLWRIFTjQ5fWWF2hjb98k51qzQmAgUwXgbkHRWQTfaySzt+2uMUO1yYDQOjJXj3JNc4acQIecrdxjgS2COA1FgJSHmhr7qQcNX8CRmKBpATFuAps+zVFwMsaft5gSFV2g65tGh4E6IxpJJigy5TuTj2D8/FxTCgZNrJN6oOy08kAq+9i4Nk2AggCBrrf9W4QnBI8aQ2rDQxXONG8JBTkJgjle0rAK5DF8AW9M95lvW1xSzC09D5oPPSv2H0m3qgNukaGAOPjaEDxPaJx5dcq14AYTc7hxzHafbkrQiwjZcRwxTK78q1Z9uE3Phky77l++D5yTj2j6Nuv32MGcHofMQCMjykdAoBnvvAZu/r9m+1gZWkEro20VQAAIABJREFUAB6sLLUzbQsjwkcCiOyWvpcg9AqaLFcqIcb/ewaQGYi0nPU8Aoz+gvqwify1f7jJrv7qYbv0xc/aoZqiAKYImsQu6Ppd+Q0BHEhRMZ5N51EZq40EHwStVM7bFrdE4tPErjI+koVuBb70bMYAilUia0XAwaQHxRP1F9Tbtb+/KcQVEjDKFazvBbykPMXWaD4aZ20ISlfzIGDCfkvxMqZOY6x4QtVQ05iI9ZJyp0LWvKjNYt66MjoihZvJlsh9q3Wo+DyOmQe/Wmtkf8QQiYX1rlaCMCl3AVPNGV3fqQCJWJ+ujI6wPrmzhQ+hUDkZzhuZLQKW3pxWO9qQF0oV0QhRW+Su9gBX4Ix/a+w5Bhon3psZuXQj851SdQCyqGQTyQay/3Q5e0ZT60Pz7MeC4JtuVQ8Ivczhe09ZuCu/wd7qTA/Z3JIBfbkr7HhTwsbqCoPRwwQpMtFah56l1fcEzvr+pzkNMQCcxkcMAONjSocA4K+KS0McHBXtoZqiwAiwtAkFJbPwfPwUXT8SqgRgdAGTtfGAk8KdglyMkdooAPjOUw/Z+Ms32fjP59ql5+eGeDoFtEvoerZTWa9S4mIV2VfFkan9VA7cHoqKkIyQzwgUuNV5irUiC8Jx1jwcqikKySsEMfxb9xBDO1ReZtf+7ibbk1weScjgHHq3tZT47sK6wAAyFk1jSTBD0DBQXG2j1cVh31n1c6SqxPaXVEXAk9aI3PBkedQ+uskY68cYPf29avbGyHkf5y6mkaKx07O1pjVWmbesmaSkPShLBa61dpRBLLCoNSOQx7HbmtluI1UlgXnjWHMe/Hr27KhiCvsL6sOe2KlYR/3rQRPBOYGw7kGZwferN6c1uDwJHnUuAZhKwfA9lGeAoQJ7k7WhTQJXOpd94jhqDXiZ5Y1VzZ8He3xXdY48I+yr2ktArPH1cYssgcX2+fFkWR+2hYZkzABO7yMGgPExpUMAsCfnerV/KnAJJwo/Wte0+n1cCgPl6XYlm+VZPwlLb+X6jDwpI5ZykPAdKK62E81L7N0N99mF5+6xky2LQnkRMVkS1n6HCSmL7qyJeLfzT99vRxvyIoqBAIFAhEwelSNdbUfq8yNgmS7P3pzWkLQipkPtouLXPfeXVNmFZ+dF2i/FyXGl0hLDSdAsJaS+EKSrXXuSy0MtOc2tfiOLo3tJCUtp6zsWRX7ziYcD8+eLB6udNBC8O1tjojYTwHkjRSBPpWN4Hu8psCeQQ3ZRz6G7WIBWoJIgg8wrf/Przbsu6Sbvy11hr6/JihR/Vr/EQtJAoXuW4JVM8kBxdQDeBE3a6cSzfBqbw7XJCKvlGWYl4FCOcP15tyhdud1ZbTZaXRzihHWdB5lyY7/95PwwnizSTQ+Bz2wmSNd7THlHwKj3xRtqXDtk4DygpIzQeX6bQd2HRo+uV9t35TfY+1+5w/aXVEXc+zSCujI67Jv3PREDwGl8xAAwPqZ0EABKMLF4Lt0SEsi0rik8CQTIbPFfX5yVgp2uQz6HglYKiIwChbDAymBZhR2pz7fDtUk7WFlqe5O1tiu/IcJ6ScjTrSiAKDbx9KrswDgwsYJ9IJNBNovCngV7U7mcti1usT3J5fb2k/Pt6vdvtuGKZZGsRPaR7ATjqng/D5rVRoFKxj5K0QusUKFpLk+vyrbX12QF0C3DgO3ZX1IV7k2AIzDNJAUV+OUcKM7Px8TRDSfQw1g+uofp7lX7e3NarXHWhgi7TMVOFyavZ5yaFLPOXzX7OnPIupFkXOl2Vl/4LgmEaO70OxmjxlkbJq1XjTfLv3xcvUeBEc+8MRtV52snILFtmk8BY/XxYGVpmHvdm+CY8yUQq3MI0nmdmD0fT6r1IjfwqtkbbaC42gbLKsJzBJbIjnmwz7nRNVrzNGQ5hsMVyybJM44r58UbZwTHZPsITD2g5LrUPbakd9q+opoIuFU/CGDjOoDT+4gBYHxM6eBewJ6VI/CQMJMio/UuZeUVFUESGSUKTQl5KkV9GPxMgEMQ1Z113Q3MOCHtqqHkDyZoSAjTTSpwREBLsOcZBn5PlpJJJmq3Eijk/qEiItgaKK62t5+cb5dfvMsGiqsngTW2jXGLBKZSZlSOZMx0DxZgJitFcCqFtzOv0c4/fb+9/eT8MCcEaTQYUhWv1Z6+uu/uwrpQYFcxkWwTgaNna7iGCCrI3JKN49olQJcCJUvkmVw+X+1imIMYNo6zPnQ1C7wQ0BCcaaw0j1ybAttdGR3BFdhfUB+AEsde4JwgXOuRc70lfWIv3yP1+ZNAqXe/a05opJ1pWxiYXb7jniHV92qXnwMCLq0ptZ9rmqzolvTOSIY11ynniG5trQvvniZw88bbnuTyUINT3+leSkbRs8n+6X1IJUf1t7Kw9ZHr3xsHZPvIJlJ2iiGPs4Cn9xEDwPiY0uG3gvMgjMLSK0QFX/P/OtcLKrI0H1fhnuDIsyZSiFQ2aqu+l0tXArm/oD4Ian086ydX47bFLeFv3pPnU1HTjUP3K5Ul20XA6EGOlJMA6/6SqqAICTgJXsRgkJnoyZ4IpBeAITNLpo9uQiobKhgf43d6VXaItdKuDxwrttGzJLqPXGB7kssDO9lfUB9cmARYBBxSkt5lq2s8m0eAqPVJxoljqfupTxxfXk820YNdJm1szWy3402JSeyOFDWBgcDe9kRzxD3I/uicTXMnmC+VYVGcGd85uoj9+8cElC3pnXambaEdqc+PMIAcQxZrJ6vWndVm59YusD3J5ZF1R3BLUC7Dhu5V9f1s+yMRhndHosmubr455TvC5KHjTQk7XJucZLRwvUpuECx6F7yfa4HNLekTuwtd/e5MO1hZGgl7oEzszWmN7BzDPnLrRoI7feeNLIF1MnsEnQT1NO50z5gBnN5HDADjY0oHGUBa/hKoQ+VlkxgZWrMEZhRyOofB4mRkfAyNBGGqLGG6EyUYpRQkHLl3rK4Re0IgQeBJFy4VL+PofCwPgROViGendB/FSjHejqyPhP/OvEbbV1QTyqEw8UagTW0SqyMFoHHw80R2UWDLz6PYKbImHO+e7NWhNJD+zzHmmPt5S7UeenNaQ/A8Aaxn6jQGLOZMgEIAKsBIl60Hf57ZI3uo+/L5BIcElJpjX3Jm3ZxnrC93he1INFnuzCci60btU4Yy3X0+fpFFtgUIGHencaNhQQDBAsdqPzO59Y6989RDdvX7Nwcgp/MFSMn8kQ3VeZpzFtqmC5vAketV7dhdWGcHSisj7tBti1tCiRquJcqQrZntdmzl0pAYQsBE4ETwSkbWyzACZsbY7Ug02cmWRba/pCqAfI43200jWWtKpZWONyUmGa6cGx8iw9hnvj+SFX4d6j7/nNkSA8BpfMQAMD6mdHAvYK8AqUi8Ul0355mgBMkQeAXrQRHjgCjoKLT1O89jTJf+leKTAGYJDQGV80/fPwm0CBwSlJHNYZYogapXKlKuFMSe/SA7IzAnxc7YJCn2vcnaCGNDRoxKgeMnhUXly0QXnSMXtMZNDAn7yHpnOmeguNoO1yatK+N6LJhnn9SvVO5NuXe7MjrC3q5kUbRu/NZrXG8EclpTnCPF3JGp0jol+8z70K1IIEE2U/NNNxyvVeID2SS5tNk+nau6imKOPNOsddyTvToYA5oHru/urIm4UrpElelLpogAkcki2j/7wrPzIuEKqVztWgs0XGgEkdUiI841pvZ1Z7XZcMWywD6yv91ZEwkt3BNYY0ogrnZofDTXep73KPCd4f/5/nRldERYT8kIHyvL98kbPPrsym8IO/boPfYGFMeM65MySM8TuKec9CD/P1dkxQBwGh8xAIyPKR10AVPwMw6J8SaylCkIqRzohqICpPL27lGBI4I9CbsDpZURpeuFMYU670e3DdvpMxEJgKRkfcwN701Q6J/vWQW6cHQ+t6qiQhULQCaChXS3pHeGoHYCPAFXKSsmQFBZ6lyyJhofKW26ttWn/oJ6u/T8XDvZsijM58fFRdLNybHakt4Zqa9It5hAHsEq3ZuaAwbVE8SJIRK75tecvtN1BLB8PrMqydpxPmmQbM1sD9vnsQ9iuXge12NP9urIPNKIIQAhOBaoENBWMtPOvMYwt1xLBOgENOqX/r+7sC5kuNOoUZtpzLEkD0EWDRhuLUiwRKOI7lYmdGk97UhM7IXNdaix47rTu0Jjz4N4jod+49rWu6AaijQw+e7TnUz5pfHnetbcMayBoE3fsc8aZz8ebKvkoMadY9qV0WG/WFodA8BpfMQAMD6mdHgGkErOW6cSOgIkErIe9LDILF0dSgYgsyCWhtY0XU2e4SKok/Kj25SW+Y5EU0Rwqh0Cgj7b1Fv0o9XFdmzl0giYo/CmgqaVLxcZd9GgwKdS0r1PteaE3T+8EhKg0P22LW6xvcna0J79JVV26fm5NlZXGJQu58+zG5wXsmW6luBlqLzMjq1cavuKaiLzTZDEnRsYn0RQou8J7ggWOfYEYp7xY8YtmTUPPvi3ziMo1Nh4d6zYRN6brKa+I0CSG1QhB2LiyAjSbUoGUe5W/Z3KuCCjdqC00vYV1YRC4QR8jAkjC0YGmaCkN2eizqfWPxN8aIh48CKwovHQs/gM3Z/9Jasm8MT3VQBQSRIyxgj+enNaA4gnkBd4olufTKja4NcI+8Tr9K4q5lLnKw52V36DXXjunkiCFpNdaKRJvhGoemCov73XQc+mTCaI1zjESSDT+4gBYHxM6RAA/F8ZqyKgg0Lcly2g5eotbK8QJNj6cleE2mN0AxN4kaHS9zyHFjndWxTmvI8yb3WNPmQH6CpLBVa0DZwUJGN46ObTNbxHKqaEoFC/78xrtDNtC+3sY5m2NbM9sucprXwCKgaSH6wstfGfz7U3OjImMZ7Kij5cmwxAQzs40F2qnQt0b433UHmZHSitDO1nHUEPzmkosH0aq31FNRGGVtdrz9tNczdGsje5zrifsdpM9y0BnT4qGcMYQg+MGWPoQTENFbLiBA3qd/ktfxrWmuaL5+kZGheFT1DREyRqHgSKlPl7sHKiYPuR+nwbLKuwA6WVwSDjrjAEWJwngsqe7NV2qjVnkrvbu8DFQJFt07aOGheCFQJEzb8MG1/vkUCV485YSN6XYNAzk964YpvI4vGdTSVzOPYCrRyfnuyJkkUXv/D50E6f4LNtcYtdeO6eSfJAbeb9eW+CP52vOVU5KoF9Gjj/unBlDACn8REDwPiY0iEA+LcPXgdQFEQSzrRc5Y4iWCSoIsMkxUOh74U6S2l40EnmT9951x6VBwUwY4iomOSGJOtFgeuBBkEhY+SoWKg8qBgV0+Qz/8hQSDGdbFkUxs4DDZUA2ZrZbvuKauzc2gUB0Io1kWuQ7Kbawv1HyUCQLSJro34LtNHd5sGPgIeAJO9DJS+2ln2XctM4+DhAPkdj6hUjlSGZQPU9FTjQDiAskyP2T4ydviNDTWNI7BrHp2Dmk5E27kg0RVyMAn9i/PgO6f7ehU7WbKyu0N556iH74Gu32xsdGTZWVxiYJ61vsvQ0egQ8BLRXzd5op1pz7EBpZRgTuvFpVDF8Q6CIRgrlgQC/rlV7ZPxoXmkwakzI8HLd8P0n2Of64PxrXcuA4Hv9cUCezKLWD9eixtP31zOuvu0ErtsTzXaieYmdW7sgkshCY9Kz8lrDlDE0OrsyOuIkkGl+xAAwPqZ00AXshR9ZAwnA3pzWwIp5IU9LnNa3hJcCo6k0CCBZe4xt0bkCbhSELB7sma9UJWC6Mjrs/NP3R9g6b92rT6ypJtCic3U/tZljxl0vLr9wt116fm7ICiQzKsUhsC0AR6VEBlAK/O0n59u7G+4LfRZ7J2VPxkFjc+HZeRGAy9g9AiDtOKHf6ZITMJcClTuX7AxBswBJX+4K25nXGLaR07h55omMpcAQwQcVvJ7RldERgAvXnJ5DNy/BtQCAtopTv1huhu5EggTdS0BI992RaLJFM9cGsMK4wi3pnVZz69OT3hG1letHzKXGQ2viQGmlnWxZZFdeus2uDCyyD752ux1vSoRt/bZmtgemkGuepUpoVMkF/EZHRlhHZKwJAD3T3l9QHwAMwaJnHT8O0GhsPOuu5/Md4324thUGQSDGNe8TmgQ0aaDqXDKvNFYlQwj4dK5c/QTfNB694bglvdOGysvs8ot32fgrt9jh2mRElvE69kt/v9aYO8m41rjHZWCm9xEDwPiY0iEA2FdQFrGSGWRN4Z0KnEgASonRmpVA3ZFosktf/GzE+peSpNuPrjbGH9L1o/ZJ6JJNpNBkSQWeQ0FP5aK26d7+eg94qYykJKhYenNa7d0N99mZtoWRuEkGiOs+fbkrIiU81GeNg8a0N6c1gMlUSofxVmpXb06rDZZVRBg8KZ5VsyfXMSPwZrwWXZJsk9ggucj1UT9Gq4vt8ot32elV2QGA8FrNMxW+gMvWzPbADpEt9OCQrJDW5eYH1geAR3eZxkF9JLtHY4esmF+XfIZAATOhyWYJ1Kyb80wAXyzvo/ZsmrvRVs3eGNaV7img2Z3VZqdXZduHX59tv/voFbv29zfZqdac4BokqPKGC9c9QaeY496c67F1PgaNrO+6Oc9EYgUpDzxw1FqRm53stL9Oz2GBcIYKkF1MBTa5dgnMNYdehumd8/KMRuSxlUttrK4wPJ/vFbdqZL849gTMvTkTISmDZRX2RkdGqKVI+UcZ4+WDxlvnMq6wJzuuAzjdjxgAxseUDmYBU4FIoZJpkZKhUpSlTbesmJVUDIeEKXdToBL0sXW0hMnypWJ1yCyqrh4FtxSXlAOr+dMVSJeMrqfrR/3i+VQgXRkdIVbuTNvCUEePII6KoXHWBuvOarO9ydrwG4U7lYOUGQGRZ6sIjOTyFmjUXLG0BsdNz26ctcG2LZ5I3OE+wWRMmIxDJlHPEZt3pD7fxn8+1862P2K7C+uscdaGEANHtx7HletD69IDNCaKaK3KZStmUPOaKkmEQM4zoQxLoIGge9KoYOa4+kP3skC2ruF2dmQvCaq03plQsj3RbIdqiuzc2gV2+YW77fz6B+1wbdL2l1SFeFcCHL1PYsk5T1p7wxXLbKyuMALKeI76w3Wp+RdjqPeJQIkyQ+tN1xJI+fd+3ZxnwraNNOholBJYebfoprkbQ71LXcei5gSCOkcsqzfy+nJX2IXn7gn9kStez5VhtCPRFGSNxs8bo3r3ty1uCbv8EGwSnNIQZX+9USsDavMD6+3VR5tjADiNjxgAxseUDgHA//P/eCq4/ui6SqUgZVVLgelfKW0qH8+i8Tu67RRfo/OkgH3xXJ1LpkOClMH+g2UVoeCwB4dSdIwdk+AVUyGhLIHvy5B41pLB6FRwY3WF9vqarEgRXCYAsG1eyVKJkdnwDAHZLYEQgR4xHby3YtyUQEDAQCW9PdFs+0uqIn0io8I1wSB7zlNf7grbV1Rjx1Yujew/65ko7/ZjW+n25foUw6d5F4PGLF6uY/1NZUpWT/flOvLrhCCCrB3dtgQRGhOuec2V5tMbFgQnei/03e7COhupKrGjDXl2tCHPdhfW2e7CusBKaSxZw467yghQEtQwpIPsG40jjp/W4jtPPTQpu5ysvzfm9L3WykBxdQBRNLa0TiSPdK3P9BXrTEZQ653z5Mec742MO40/ZZLGhP0TKN+eaLbdhXU2UFxtuwvrIuEmYoI1B5QLHF++3wTEXD8E4TRMZXirvXEW8PQ+YgAYH1M6BABfffS6ICW4YoYfmQoxH2R8PCtHAaX9M6V0CKYU+8bnkjEUEPTKjMLUs3XdWW1BMXrFLUHKuDzFB+m+Kuehe1NBMohfSsXHGwqsHCitDKU2CHo848O+CiRqTMgY0iVHpkXPJSgWU6NSFl6peFeo2q0xPdG8xN5+cn5EoRKQam1sW9wS4szIEKlm3d5krR1buTQADTJcBD9cT6mYRc/OEfySSSPgIxDzLIrWLAGkPjR0dB1BIAHNqtkbQ9vFfHN3EgJaMT+MZaURoFCBTXM3WvktfzoJwGrdDhRXhy0D+3JXREAyXaAcUwIcJlQx/tEbHZpnuullzAyVl0Wym2kEeVZX61LtOFBaGQwQvWdaD3uTtZEiyXpHKJ9kXPh1zfI7+n8q4K7vPFPJmF6Ogdov1nNfUY2NVhfbWF2hDZWX2f6Sqsg2lDTa1GaCVbWd65CAmQaA1ojuo3O0TrdmtscAcJofMQCMjykdLANDloWsHRVfKjeEB1dSFFJsO/MabaC4OlKcWS4z3lfXSIAyyYDP44fPI6jyrCPPEeiUciMgI3iiIlTcntrtQShBEZUMkyjoWmJZE53nWRQyohL+2xa3hC20BLy8YvPzxb4JFBDocmylhHbmNdr5p++3D78+2/aXVE0CqBpXsl4+/lAK/djKpTb+oxk2VlcYQDeZQrHImjfvyiazSeZRv/NfrkG6ff15mksVc+7K6AgMGplquZT5XAGYnXmNEUAqACEwRQaRa4TsrVhOfedrRhL4MUlo8wPrbbhiWUgG0hpitrkAi1hGgU66zLUedJ3WHdl/ARZfumRPcnlgN/07w/XnQX5P9mo7WFlqg2UVEVaL5/cX1EfYMyYMqc18V/3ciyH2BhFBV1/uinCOX1c0+jgufbkrbE9yuR2uTdpbnel28QuftzefeDisbTKVfOdorNGg8bJN5/q20BiXjNP3W9I7YwA4zY8YAMbHlA5fBoYMDJknWuL6P4UbhSuBgvb8vPzC3ZPcPWTFlLFHwENQQiHNe0j4C7TQ+uZz1HYJ3l35DaEuoRScwBlBpfomgEY2QICMQJZgQxmC/J2gj2O3u7AuomAJEsicSBExEYPKnHPTk73aRqpKAhAQwKEC7M5qs/PrH4wwnf0F9TZcscyuvHSbXXh2XgjMFwij0hSo4viKJdH5g2UVdrwpEZgdBr7TPU3mw7vePHNFNsuDDhow+l7rxAMrrmcxKgJ/NBg4xhq/7qw2a5y1IdJn3tPPH8HfUHlZiM3z+/dyjek7rkWBjP6C+lD8W30k065xIyBhXK/WzqGaorAnsO7PmFKCYpaIGSovC+tL7wLni4Be7eNaJsCSwacxOlKfHwGUfP+6MiZi34YrltlwxbKQBc055v1pMNIAIAPN/rEfh2qKIu3eld9gwxXL7EzbQht/+Sa7eOkv7Mq3ZoVYX2Vh68Ox4780Usle9ua0BoORclAuZQJGAt64DuD0PmIAGB9TOlgGxrtw+C+VMEEiLWUpBlq/3VkThX6v/f1NdrwpEZSePlR0Psia9/NCjwkk3tVCBUQWU/1TcoLfP5cs4c68xrDDiBSqru8vqI+UemH7qHS8+4hjon5oHJRs4QGND07X36kKz3IeNFYEVzpXioZtJvDYtrjFTjQvsWvb77UPvz7bhsrLrL+gPsJoSIGRsSLjJuWna1jzjHNJZch5JxARSyv3qk84oivMJ22oz2ybjxH0651xZwR8+tczS4yZ1fiTmVVmr/5/pD7f3t1wn3VntYWYRblCNV4CaiyX83FFvlk2R2MsgK/29WSvDhnRNJK2ZraHTGICZIIVumcF9rcnmu1Ua46dbFkUmTcaCkqU0Dwcrk2G0AquabKPatvbT86PMGWMoZVMOdv+iF37h5vscG0ylBjimu4vqJ80x3pP6Jqni5zvbE/2RFYy313tLnSmbaFd+5sZdvHCiwEACtSTceT76eWpf6+9nCVw94Y2Db3urDgGcLofMQCMjykdBIAEGB7YUQh5FoxCSwJLSlYAaqSqJFjqBB8CEXR1eaBAa1hCkFazitsKuEk5MrtPbjCCTd5fQlrtG6srtLc60yMKkLsrqJ10dUvosxjtzrzGsG0XwRnZkZ7s1fZaY26IISLjKOVOcMq5IYPqQTMZJO48IjDr+6J77Ug02d5krZ1pW2hjdYUhK5PnsO6g2DO/NvS72EcxrJwbzZ/O9bGgqYwQsW9cdzQeyDoRwHkwoLGka9mzjnQdC9h4oNiXu8IaZ20I86PvGZdHYCz2juO1PdFsu/IbIgkOHpQQJJI15nnFM9dF3p89yeVhHHflN0RiejVee5O1dun5uZG1w0xnjqXmqCd7dQBhOscbaGy3wJSMJ4JAPqM7a8K9/vqarEksGcHrzrxGe6sz3a7uedSONyVsd2FdBNSzLeyr74/WDmWP+khjV3JsV35DiP97oyPD3v/yHHv7yfk2VlcYSQbpzmqz1xpzI/ch+6q1T2aY76evyLAj0WRvdGQENt4bUnEh6Ol9xAAwPqZ0MAaQgoVKV4DOC51UFi0tVLqIVZqByomKXt+zfpcEJu9JkModRnRvCdS9yVo7WFkaXDIDxdUprX0JdlrYfbkr7GTLIju9KjuiePVMtX9LemeknIMUuVxU3VltdvX7N9u5tQvCNQIAVLbbFrfY6VXZdqJ5yaTECPVdilPtIdtBhac+kRXTuOnDrFayIFLKAmR9uStCaRr2UeNB0Mbi3eoTwQrPIYAU0NC5zMLmOiMLR/aUYJv99cHzulbjzqB6XefjKWXE6G8CCJZCUhuYWEF2Vv0i60TAyXhDsYIcbwGm7YnmkBxEAL03WRuJx+R68HGVWk8EOWLLGFdH9o990z31rgpg9mRfz9z37HJP9kSR84OVpTZWV2gHK0tDAgvPEbD74Gu32/iWm2x/SVUERBL8qSTOqdYcGyyrsF35DZEC15RJbLdnnwn6Nc8EpQSHGneN+UhViR1budQOVpZOAn800AjiKf/IontGmu2XAScD2q/HGADGRwwA42NKh3cBk2WiG4/xVr70At2PZFD4t5Q/g+bJvnnGR2BEO1OQLaArSNfSZTZQXG1vPvGwXfnOrXa4Nhnu6RUTs+98e8REyEonM0AFIkbLs6US2qPVxfZaY24EuHn3ZFdGhx2uTdqR+vwIiNXv3KFB478lvTOSwJEKpAkIeNegZ7+8spZrUUyqYgU9IBM4EZATe0gg2JO9OiQASakSGHrAoQxrgkQBNh/zR6VJ5dmb0xpMETZ1AAAgAElEQVTZdUNzvGnuxkhCh/rv6wwSbGq8VI5GgFUhBuvmPBPGV8B709yNYY66s6Lb+HkXLF2SLD/D+adbXM/SmtiTXB7Aq4AK3fUCwh48e4AthpduXr6PDKHwzLFYYI1hza1Ph2v0zozVFdr5p++3i1/4vJ1bu8BGq4sDkKP3YEt6px1tyLPzT99vBytLQ5+YjU0jROtK7zJBnta71hdBP40K/saMbH3vXch6prKxBZ69d0Pg0Wcyc117+ZoKCJJN1VyzXT3Zq2MX8DQ/YgAYH1M6CAAZLybBJcves0wSTmSzvMuOIHJvsjbinqHr1DNZBI6e8ZHiUYmRroyOAFZ0373JWnt3w302/ot7wnZL/p5yGdKlLCErYPf6mqzQR9+/VKDU92FrZnsI6PZuS89EMHGCYMRn2qbKQpZC4jjpPn5vXT27v6A+sJRH6vPDNVRWiksU88j+8zk+VozrgTGdbDcVu8aH4984a0OkpAfXAhU5gZp+UxvJgnLc9S+ZN52reeIOIpoH1aQksJJxw37onnTjaZz8+0U2LZXx5N8JZnD35a6wsbrC0CYPULh2/HuktqjdBNoC6Hp/abhwjRO8+H10Oeb9BfV2vClhH359tl26/DV7/yt3BLct44513Y5Ek7395HwbqSqJ/MZEG75zMlTIfvJ9oAFEGUcgrnFnSRx6C/jxDKzapXGje5sJSWSTabDRgFLb2Ad6GvTOsL3dWW32tw+2xwBwGh8xAIyPKR2sA0hmhWCEQonWNYEH2QEqOAkqAS4pGgpkKREliPh76+MZPApKKqPenNZQImN3YV2ECVAsHxkpKkC5ZnYkmgLwEcD07JwHNFTeHiylUsRsu1gEKkICRrkVN83dGJRBV0ZH2GVCbMXZ9kcmuZHIlOg+XpmTMdJYCTzzPM0R+8K+i/nwjCL3je3K6AgMHUGi2ifWkQyNB05k78iGUHlzrBlnSraHIIHAiH1SfKOuV/FpPY+lUHQeS7uo8DbjL7nOGe+5M6/R+nJXhHnV+urLXRHmRucfrk3a+1+eE9yf3iDR+LJdfPfUTyVEEazTG9BfUB8B6Jr7A6WVtiu/IQJIdH+dI4D0WmOuvbfpM/bBfxbZ+1+eE2LmWLCa61DPIbDl+9WVMbGN3XDFssi60rUq78P4YG9IkjmWrOEYMW6Xc6F/mQDGcyhLtDa5fig7fDsoJ+jmFcglc8m2f/O+J2IAOI2PGADeYMfOnTtt+fLldvfdd1taWpp1d3dHfv/oo4/sL/7iL+yuu+6ym2++2ZYtW2ZHjhyJnHP+/Hlbs2aNzZo1yz71qU/ZE088YZcvX46cMzw8bAUFBTZjxgybO3euffvb3/5vtZMxgF44SjEyzsozCQSJvI4MBpknCliCBIJHz4D4NgnUeLZQQlIKoyujI8Qpedaiv6A+Uj6CcWpSSnJbS6ATyDGWjKBBVr7apGtZb1CCXK4cKY1VszdGFIf605VxvUAwgQzHRp/R6uIwhozTI4DQvPo9nD1Y3ZusjcRf6m8qNc67/1vjzXI4W9I7I4yZzmOMFdugMSVb50EglaJP9tD4bEnvtMZZGyYxKwSPBIh6HsGk7iNXsgD5tsUt1jhrQ3gGGSvW3mO7BLrE/tFIIljTR4CDgGBPcrmdfSwzrHWCcq1RAjv1nayf1qsAt9YyGXqGPei3rowOG6srDEk8NFgILmV8DJWX2anWHDv/9P12pm2hHawsDVnv6p8+iisUeBOA84yu1grnzrN7aq/Wic7TeqcM4jm67tzaBaG/HEOtVe4nzD4QwEoOpEoI4dhyPdMY0bonWNbYxgAwPsxiAHjDHT/72c/sS1/6kv3kJz9JCQBfeukl+9SnPmU//elPbXh42Orr6+3ee++1Dz/8MJxTVVVljz76qO3du9d+9atf2QMPPGCrV68Ov1+8eNHuvPNOa2trs5GREfvxj39sM2fOtB/+8Ie/dztTuYAJ0HxGIxUB3WIUxGTBJPDkrqUAJICjkPVCmCwdBSPvT2VJNsKDSAFHxa6RhZPS0d6ee5LLbVd+Q8TtRiu8N2ditwwVBKYrlIBKipvsGxmV7qyJjEElqvAZZDzJrnLsBoqrI0DIJ5KwiC/LsaTab5XPUVvYbo6pwK2SFhjfJoC0NbPdDlaW2khVSQAaUrZqs8CHxl4gUcwZizWTteO8MtZLIIcMpf5VHB/ZaYJKAj9dwzWu/wvsdWV0WGLmdUAhgC3gkirr1gM8jifdxh7gaHwELvckl4fdbsgw6Z5c33xXaLToHLGcah+NHrJvng1jUgnX/dbM9sgaUEH0A6WVNlBcbQPF1eE5ZIw1Vto1huNGJtazhhojz86rnR6kch15g1VtVixsKmDLd4vMn/4drS62i1/4fHjHCDb9e6p3SGuZLneC8cGyisi7yXc+dgFP7yMGgDfw4QHgRx99ZHfddZf91V/9VfjuwoULNmPGDPvxj39sZmaHDh2ytLQ0GxgYCOf8/Oc/t0984hN25swZMzP7wQ9+YLfffrtdvXo1nPPCCy/Y/Pnzf++2kQFkhqsC2cmUUEgyg5MAikHVniHyljIBIS3dVHvNyiWlZwjAHCitjDBSjLVjRi6taSmVofKyCPDTZ2+y1s6tXWBjdYVhv1KdQ6WjD12RZLXIbDCmiAHgOudQTVFg7xgbRhCusaRLli4ytYtMH9kugg6dQxAilkHP355oDq5Ilj/hfamI9QyyHb05rXb2sUzbX1IVYUuGK5aFOaKrWc9gnUaCOylGJm6QXWW/BNT89XQr8z4eLHJdkjUSMyW2b92cZ4LL1ycJrZq90QpmPhnZTk/t0lhpret9Y8wamWSBEc2NgKAHNZ551bhorZL5681pDf0Q8JDR4teMN+yYwa3fOBfegNuV3xAKTtMY8+yhmEu1ifdS3wS2KKP0HL4XXOt0i/Pd5HPZX90j1XZyatdvN94b2Fmy16dac+yDr91uQ+VlEWApll/zLTmpseTz2B/em++h7hsDwOl9xADwBj48ADx27JilpaXZ4OBg5LxkMmnPPPOMmZm9/PLLNnv27Mjv4+Pj9od/+If2k5/8xMzMHn/8cWtoaIic88tf/tLS0tLs3Xff/b3aRgBIl5jYGmaaCshICFFReRcMBSsBGl0YUma6RkxSKsHP/Vn12V9SFcCGBKSPyxHYo3Ljd3ST7sxrDLtgvP/lOfZWZ7qNVJXYvqKaELDOhBCykhojHxunmC6Ng3Y7ECDRGMmdxHGk0iEgZgyblIZ2LCALoflim6joNMeejVSfxNpqzglKBWjE1HBHD42PFLwSdpiMQ9aJ7jDNeSolyHO51rQWNSbMpvWMF68lQNDfBMwyhASMPeuyae7GwNyozWqnxp7P1brfmddomx9YHwEvWrsEmaxVyTg9rfWdeY3BXSqgJ0OJYJkgXc8lS6b543uRCuBrzsiwKv5Q88owBc41++XdoR7U8N0kWNO6ZbLFnuTySPkZjTfZU449wTDdwVszr+8CRKNqtLrYDpRWRoCnru3JXm0Xv/D5SWBVIRfM9tX77tcaWetULGEqeag+6t+tme32P9PbYgA4jY8YAN7AhweAu3fvtrS0NDt79mzkvD/5kz+xlpYWMzP7xje+YQ899NCke82ZM8d+8IMfmJlZeXm5rVu3LvL76OiopaWl2aFDh1K25cqVK3bx4sXwOX36tKWlpdm/LlwZYQ98fJQEp3dvkhmh0JciIPNCQUzQJNDC53vAod8IUM4+lhmEIjeQ781ptaHyMju3dkEQnuwLFQgz9vYma21/SZW91phrZ9oW2rm1C+zYyqU2VF5me5LLwzN0jdxXntEj6KULiWCGbInaJODAcSFo07V7k7URRskrOD1H/3Ic1XaymYzHTDXX/J3jzznidmb86DcBGD1bcy620WcBa7zIzOkc/t/3mWPh157WmNY32T/GGArc6NodiaZQnobP68roCCVP1JfND6wPLmMBRpWQoYLXvNfc+nSEBdJH9yueuW6Su5PM2bbFLaE2IAGBQCtBC59NVunCs/Mi76DawsQurgM9Y2deo137u5siY0z3usaZzKPmhkaU4lEZdkKAQyDNNX+opmgS0+7d0GTX1B++rwRonmnsyV5tY3WFNlpdHHm/dM66Oc8Ew4f34ThSpvkwCgI6vk8yvPx65XtH+dyV0RHXAZzmRwwAb+DjRgKAX/3qVy0tLW3S5xdLqyNCl2BACtHHlvnYKbrYWBvNuzDIDlKh60Nl15XRMUl50n2m50vgEpxS0QoI8R603PtyV1h/Qb0NlZfZGx0ZE8VofzTDLr94lx1vStjBylLbk1wegAxZTYHdVOyC2BACTypRusxTKTAyXWQbpQgENnSP7YnmSSVRtH2VnkcXO5UxGQz9f7CsIhJsTgWvf8UIkqHbkt4ZsqjZL7XLFw0mg8c59C5zrgO6dsXUeQBCQEuA593A+lvrjbXWpHxXzZ5w+xLUcR0QrG/NnHANq62rZk+whQK7eq/4bM8CKbtY7LTaprEkG0bgJDDI7GK+IwSyGtuTLYsiwIQhHx6g6re+3BU2WFYRMVS0RgiWOLacUwIkudU11ufXPxgYOf/e0qXLWns0eDQuDM3g+6M5UHsoZ9guZVlThjFWUu3lO8xn8V33DD7BnObv7GOZk+Qo3cOaO7LaW9I7YwA4zY8YAN7Ax43kAv44BnBfWYH1F9RHLFjGT0nAe1aqK6MjZJjSXSxloPsNFFdHypfoGT72i6CKlj0BE1kM/eZZpd6c1lBIltm22oJr2+IWu/DcPcHV1l9QbwdKK+1QTZGdX/+gjf/wJvtw/Id29bsz7VRrjh0orQzV/mn10yWo8SCD4GuyyZ1HoMd+0H0pEKDfFGek8+neUxs8c6JxVjkcjZXGQy49KjAyUG8/OT/0U+2V0lMbNPYCgh7IkGXU/Zk8QPAiJlEuYw+sqKipWOk2pwGgtSLg6xM8PHvl4znplifYUyZwV0aHld/yp5EyMmR3e7JXh0xhtUUZw10ZHaGMCd3s3mVN8KDx7croCElDmkPP/OpagREWYxc41edAaaV1ZXSEvYn5LnJdaU2LGdUewrqG4JTt8CwtmTQaf0q8uPLSbWHsaRwQ2Gvd8X76jaAxlQGp9e/LE6mN+k7vHN9fD3J7slfb8aZEZOw1znw3PVtJQKo2vtGREZGHniH08aG6VwwAp/cRA8Ab+Pi4JJDvfve74buLFy+mTALZv39/OOcXv/hFyiSQa9euhXNefPHFKSWBnFr/edtfUhWE8NbMdjtUUxQEmizt3YV1KV0SFLgUolI8e5O1wR3qQZOEMUGe/q8kDDIKCqQWA0C3JtkwAhDuVau6dMoEFphTXbE3OjLs/a/cYeMv32TvbfqMHW9KhF1BmMhAgCKgLIXi3ToCzlQGGiOd4xWZ3MsaL84DlbsUj9x2UlhkwHQfspV0d5H5IND3gE7tF7sncEOQp/g/MiC78hvCOhAAZNyj5pxsnwwLKVyyrKlKcJBNU1IGAbV340qJazePrZnt1jhrg/3hH3w6lIzpL6iP7ALi177iVvXRlocse6P+k33iWAroM5aPa4PxlDJAerJXh9CEVbOvJ2zpHWOsqoAc14xfZzQs1DYPNDyY53rxdTXVd43ZtsUtQXZ4Bk79J4OmGDoBcrpY1Z+3n5wfjDzKE44b2+LX8I5Ek51sWRS2nKNRobHcXVhn+4pqAkjztTqZPMbx1jkyFugW9qw4mVH20TP0mjtv5GxJ74zLwEzzIwaAN9hx+fJlGxwctMHBQUtLS7PNmzfb4OCg/eY3vzGziTIws2fPtn/7t3+zgwcPWkNDQ8oyMFlZWbZv3z7r7++3Bx98MFIG5sKFC3bnnXfa448/biMjI/bqq6/aLbfcMqUyMP+5IiuULJCw2VdUE4kz8UkfdK/RjcEMVB/PI0FMISYmg1YvmUQKOiqAA6WVIcuOjAkZDP2mv717i6zYtsUtdqC00g7XJu31NVl2bu0CO9G8xIYrltneZG0khs2zpBTUvGd3VlvYmkvgQePiXTkE0TyfCpMKiApT4y0FIYZHY0nwREVD5U4mQmBkpKokUqBbAJR74UrBa/zJDGo8yGTq2ZwHX5tO33mGj2tAANQzdJwTrl/exwMRgsOMW1oi7lnFe+kdYJvELBI4qO96X9TO7qy2CHDm+6SyNxp7D1YaZ20I8695ufLSbZO24tM6Urs1j7qXxoTs71B5WUhM0Xd0YzNGj0CMBp9ALQG9gJsMivNP35/y/fZGpDc6aPAQuL/5xMN2uDYZeTcoj9hOzQdlwt5krV39/s02VlcYYflUp1KFqgna1AatP5XhobGjcxU7qOd7Rk+gV89ltQKOK9/tVO3Ykt5prz7aHAPAaXzEAPAGO/r6+lLG2q1du9bMrheCvvPOO23GjBm2bNkyGxsbi9zj/Pnztnr1arvtttvsk5/8pHV0dPxvC0F/7nOfs5deeum/1U4BwP+vsCyieOjOYkYp3Q4SQFTOHmhJyQq0ETgSxFC5SyimiqvTOVJGZx/LjFj/EppyIap9UkwEmmQ0FAe4M6/RBoqrbaSqxA7VFIWN3mXl0w3qFSHbz7HRdQJOVKT6bU9yue1JLo8wXlSOjBXUc+VyV3/I5nmQeLQhbxILKYBAkETmYld+g51elW1HG/IC28b5k9In6GWM2Ka5G21XfkNg7zQ2ZDt1PylasiYCN5wrPk8fMn+6h9ycnHP1jW5vgS4q1uyZj0famQpgaieTroyJRJDenFYrmPnk/8/eu8boWV15vqhHgpCEHDoNUcIQooaQWBQ4VBWmqCrX1XUv18V2qcrGOUZG3IIwoFzEhNPTl4n6otEI9UWtKI06PZLTUls9M+72TKXdx8ey7LGPbdkeX2Rj+YLxcDGQhARCCBf39DofSr/N71n1MmemvkX1PlKpqt7L8+y99t5r/dd/rb12bG74MMS79toPcy29yQeQkR0cFzp2bTw7H3xvX8dYqUFpBgogRN9cwshMLWFn7knfnEbBZwGqtXbiM6f4Xmb0+b322k0VdpPdyw69wjhfWNMSr99/W4VVzOkSWxvXx8Xpu0o6BusPnWGd5DXi3c6Huofj8vevilfW3zlvbm5u2BinhrvjUPdw6Y/XllnzWoAsh3/5gZH2axnsunSP2WJkZQeLcaifBby4rzoArF8LugCAf9c8MY+VsSI1MDObgPI1M1WLDbPRzgaZ83Kdz+bNEyg8/rbidOjFDNSOlql4caa5GCYzK3zX+V0YScK8BzpHy2HvHNEFKILJAXxYPnvaJyqA5tklD1TAjQ1YloeNtA0Cr/H+s0semFf/jT54DCx7G0aMNoyDx3q2eab09fxka1z+hxvj8g8+HicGeyssnw2lZW8wivEy8CC053IgZiQBAbxGu3l2LVaQvnonsj/nzRrIC0aOfvR//GtFtoR1HUqnrS5PQ+4fY8zayJtDnl3yQJwa7q60m7nnDRq18swAwRQkZ27uaZ8oOamMGRsp9i4fL/0CtDFfCPcCgsm5Y26aqXro+scrp8XUAv0AkeyweQ7aAfT7Bk5Ok7g4fVe8fG9j6YPvt63pwyPYfvl7vx7HB1bMS/dAdk5RMcNu/XFquDtODPYWZttrmSjDbPNchQDayVr25qo8/y1DM87ZAfX3HEmoNR/sjPj7mxs21hnARX7VAWD9WtDlOoAoIcKHDrdZeVlRORxSa/eflT1skEHD9mXT8eMHv1xRhDbsKFqUIPcnj4/NGZmF29a0roReMXo53w0lapBhcLK/c2VhBc0AmrHMStmv0d5D3cMVNtIMgFkt+gkbaXDjHc/bmuaSzm1MuGdmquiT6xECsrIxNCjd2rg+zox1xOVnr4z3/vCaONbfNw8gOInd4a/sOPAeGwYMEH0fQEkGlsgA2ZjZ2da0rrBLlqtP78g7fs2u5jm6tXF9CbcaGHvekXcGQ0MtwOdGumLL0g3lhBCcGIcoGQ+Pm5kzy5g8VUoQHeoejqN9A7G/c2Uc6h4u89PgibnKHMpMeE4BONbfF4d7hiolUvh8LceJ7/IcjzWgyw4B4NmA3Y4OeoZ77mpdFW8+eVO8+eRNFVl4LJjXrHvrouyg2CnMbJz75NC2Ix+nhrvLuuEehNz3dYwVZh2n0LKy42K9xHjjcADQ3Sa3y/PfY2D2tA4AF/dVB4D1a0GXAaDz2qwkrUwz+2cv3r8zs4QhcTjMBq+WAga8UYjVjAPPgp3DMGBUT492VsqQGOhghM22wfwZ5LGhg+e52r8NJUyLWbGc65iBrY0+bcZo2/Dm3YwYjMM9Q5XcpByecm7RnvaJuLCmJV5a21QBJAYDyN9s4Y6WqTg13B0f/PmV8cLU3RUWBjkyTr5PZi0MYPkeRtT5agb4nmfOb2O+5HwuACVjC6DMIcuco4mMsvPCM6kBmEHC9mXThSHzLlzPF8uBMjAPXf942cTkdjgESh9goA90jsaR3sFyMs3xgRWlJBGgiefm9QQwhr0GbMBWf/AnV8V7f/TJ2Lt8vMj6lfV3Vv53WSHGJe9kr1VQnH6ZrfI9DGQ8j1+97/Y4P9la7g2odH4im4q88cvAMzNsmf1jvmSnEfnMNs8d83hmrKOsp30dY6UNyDk7JXbAzBZaHxzuGSrAMbOc2dHNffHmIoPheiHoxX3VAWD9WtCVGUB7qDtb1sRzI11xpHewsGkGMrV2tm5ZumFeyA3wgoJ2XSvnDllh19rs4PY5vOQTE7gnoTMAHYbMGzj8eQyxw7UYAwCRc5hyfhjgDSXunCVOSzCDYEDrEiDOg0O5myXBWPjINoy/mS2XyPBnDKwIhWYgbzC3r2Ms3v72Z+P8ZGvlpASDOxtxA/xtTdX6gDbyZoi2Nq6P7qsfqjB/teSc0wxyGNH5fAYj5MMxN/kuuzrpE5/jmLe1126KkU88WkKxlH6B+eNezpOjDYyN+8MP89AGnH5a9qQfHOkdjBODvXF6tDPOjrfHS2ub4sRgbxzuGYpD3cNlZ7DZI+fy2ZnLjNrr998WF9a0VJwNr1MDmjxHGGMAmZk+5sfe5eMVRi0z5MjS84rd7wbkWce4LfSL+Xe4Z6gyl1z2KOuw4wMrKuCQ13e2rIk3n7wp3vvDa4pzyJyxo+Xx8pz3BhDGnPn8/Op74o1Hbi3Pc1TC8s7OosdtW9OHaQ5P37ipDgAX+VUHgPVrQRcA8K+XfqicCXfu6xiLd79zbbw401xAForcG0JQbi75kEPEZkQc2kO5OSneoTszjTARKHsrYoCGgRXK0uFCgy+zQmZPaFMO/Ro4WikjN97n/FwbsLef+ly5v1kuDE9OGkdm3p0KWLTxxbA5REmbzKTSVrNNyNJG0aFY+kr+GSCBewGWax147w0zHk/L0awIMqUOXf/Hv1Y2UQBG9nWMFVDj7/LjXLHMAtIuQIKZReYeuXE5/9Bjndk9wvu0KedJMm9ZMzBlyJLPIFfmMcfnHevvizNjHXFx+q54Zf2dcWnDHfHS2qY4M9ZRwrdH+wZKfUuXJWEtkpfK82AZqeNnJprXM/tMv8xSIRMYeL7jueDvm8Xy3MC5RAboGp9k4mcyt3626TcL8LWT9sLU3ZW1hTPksCuspY/vM/M+2zwTJ4d64vnV91ScVOsIZIpjyDxy37LTM9s8V4uUdAg7omb/cpoCwNhA1zq0XgdwcV91AFi/FnSZAcwMwLH+vjg/2RrH+vuK4ULh5zCvjZ5zkqx4tzauL7v/HALb0z4Rr953e6kThiLE865lWFD4hLPMOnH/fJKADZjDWA7xuh6bDRUAxkeaZUAJ8DXzhoI/2DVSk7XwUXKwDC6YjfI3S2Rwa6PmXCK+a8aRPmEUkaFBm5kTgBSbD/iMGQr/2FB6PmTGKLMlzy55oGyqyflqfN7Po8+8xr1h1gAkBtZms3gdVtjhxVyQGVnwnByS5p7PfPGRsjPYjKrbyD0B7sidEDPsIYBiZ8uaOD3aGWfGOuK1jQ3x1tc/H29/+7PxxqO3xCvr74yTQz1xqHu4lCsB6DHHzfiy1jL77M943DzOvgftdh/tPPhZBp1mbwHCdiABrGYts27xDnOiEwZJ3vjjeZ2dGtq6u20yXpxpLo6F224wlseZex7qHo7NDRtLzrTnF3PSQDzPCbd9a+OHURLPPWRoZpV2WA/86a0b6gBwEV91AFi/FnSZATQzRk7bwa6R4kFnI2wlbUYuMzKAqDNjHXFpwx0V1hCm7Z3fuj5ODvVUQhvUILMRtlJ0wejsdaOIjw+sKMrZLILbbtYhs4PnJ1sr4UcreDNKVu4YR0Lhfg8DYhbJzAYbDLhv7rfvZaNogMJzONIMEEc9w1PD3QUwcZatx84hKf72rmaeYabRn6NfnCxjMLx92XS8sv7OONA5WmFmCa1aNvRntnkmJq95rMLC8Zt+mlFjvGwoqbvH/Z1D5bN7n75xU2EhAWU4B9ua1pWj4DIgdFv5IVyIoQcsMKbkDzoPFBC/s2VN7O9cGaeGu+OFqbvjra9/Pi5/78r4p3/+Qbz/zMfijUdujbPj7XF8YEU5ZSc7NAZstebewa6RimPiuWpHgPlmFs9gxKDQc5N7nBrujvf+8Jo41D1c5GSQ5XVzbqKtkrdokIozcHa8Pd545NZKyNTgMOsiUiY8v3FwP/izK8tRb7SXv19a2xQX1rSUecb8xVlzu3kuc8hALYe9mR9m9rOOsOOZHS1eZ74888VH6ptAFvlVB4D1a0GXASCMiOuRoZRcUw3wgDLNzEpOiuY75ydb4+L0XZWwKuzdkd7BEo5yorNZIUCVNxpk5Yqhgl0jmT0rUdpuMIgxs7E7P9kaxwdWVEAhhsiMgUEBwMwAs5asrPiRB4YtJ/J/FINmMJ43pmBcti+bjpNDPfHud66Nn3/zxlJ2h8+YYTGr8+ySD8vNHOoervTFxozxdFvoEyEyM0swimaKmVO5HqAdj21Nc5spAFZOBTBrSNsZU0AgINOnqexomYrJax6r5AZmVguHiD4hU8r044QAACAASURBVEAK84Z7mOkDzMCaM1+evnFT9H/8awWAw/7BTO1pn4gDnaPx3EhXvDjTHG9/+7Nx+T9/Nv7pn38Ql//yynjziS/E+cnWUp7HoVvmiHdV037mpxnlvAOYfjEm2SlyCkBmVrmf5+COlqm49NWlxSGwk2HG1P0wiGcOMKYvzjTHq/fdXoAZzmAec88j5mpmn4/0DlZYajtkbzxya1z+/lWl3bSNDTTOs83sotl/O6SWZZ5v3MeF173GWaMGscy9v71zdR0ALuKrDgDr14IuAOA3bni4kmuDYjebkD1Qg7DM+uVdeSQ/c3KHFaFzYDCiVuYYFBL0aR+G1HlpBjWUwbAhc7J8Dq3a4yav7YWpu0uOksOG9sABds7PMbuRWUkrf9qAAQKw5rxCfucSPBgd5AIzkfPrzo63z9X0+/dXxZHewUquoGumcV8AP+3Z1rQujvYNVJ5pg4+MzfBsbvjwtAMDta2N6+NYf1/ZOMBu7ZzfZNYnM5QOqZkNtMNhdsqg206Dc/eYUxytxliPfOLRaLm6ytawA9ile2gvdQRtqPOxdWaNLLudLWtiX8dYOYLs+MCKuDh9V7z19c/HB392ZVz+D9fGu7//qfjxg18ueYAAehcGZw4jVwO3HS1TcaBztBRSZj4TikVOzg+l7TtapuKd37q+7ArPQM5gzqww7fM6o02MwWzzTGE/MxgzW35uoi3efupzZd54TnI/rzGzdDlFgfnqfvL/nvaJUiIHQGdHhxBwBrL8jxNqRpTne+yz42Ig6Xt6PdNP1m09B3BxX3UAWL8WdAEA/+Dm+4ti+ijFntkRjJaNdM6P4jW8YnvIPAuGKIc7AScOpzikaGNuMGPwmRUuBs/fy6yeAcy2pnVxerSzwmaYbeJ/b3pAVvQR1gnFDcjhPW88ONA5Wt73D/LwLk4ztb63k9z5f0/7RLx8b2O8/dTnCtNqg2wgiyEEyNCfU8Pdpc1mw2ycMFoYKACI0wFgFgn5O9SYw34GgowRz+3/+NcqAIN6fGafMuNk4Mfce/rGTeUey69+sLQFOZqtBigSkga88B4bgAAKOCn0yWvAoAaQ6FInu1pXxaHu4XhupCte29gQP9v0m/H2U5+Lnz52c7w40xynRzvjaN9AAUzkP8J00Yc8row9RYy96SI7dGawtjXNhfXf+e3r4uV7Gyu1AA2qtjWtK2OLXABLDoGaJWbuOtxrJ8eA/2jfQLx+/23lPjgRdjbcB4+l+2IQxr29TtEzdhStIw027XTwHVhXgz/6bEaQH+tG65Y8fzPjuLVxfX0X8CK/6gCwfi3ocgjYXrNLM2BMXO8sG32zXvb+7clbCaKEYfMAFlZsVtxul0FmbkcGTy/f2xhH+wYKy+I+2SBlYGADcGKwtwJI7O3TRofOLB8AhNkgFDh9NMM12zxTwks2APTZOZEusQGLxz0MFF2IeF/HWBwfWBEnBnvLc2zsa4Wk6BubDZC1d/86zFYrF4v3+HtHy1S8sv7OCvuZdyRzb5geOwg2oMwJxsFALzsk7p+ZJ8CTQTufIeRMm8xaci+cE3IgqdHn/jPnCJ1aHgZGhMf3Lh8veYAvrW2KF6bujovTd8XF6bsK+3egc7TUBARcADBcJ8+pFWYFDbgyU+W1hRND382cu9/8nBzqKWDZ69+AynPM8rXTxucdzj3QOTpvTvi3Q9hm37OD6TZlxtL6DJm6zd50xhyANc5j7nVpUGudw3zwuvWYeBe+1zx9qx8Ft7ivOgCsXwu6AIB/saSaNO1cO/8YXOHloqgcAsQgoxBJdnd+C++jPM3U2Xjzmkt6GGjQLufd8MwjvYNxqHu43MeMCErUbBX3wQjbSNjYm00wm5N35zk3kHshX4xqZs8Odo1UGFeMl0N0GG5YBgMJ99XGYnfbZJwZ64h3v3NtvP3U50qxbPLFMki1AXXYy2Er2uDvm9FziMztdImP7Gg4VG5DaeCHQ5LDbs47zXOWsLZD99ua1pX8u9nmuU0frVffX8Z+8prHyriyQcSAkmc+dP3jxTgzvoyTgZbZYcvZDBPAgZNAjvX3xZHewXJsGf8f6R2M/Z0rCzCrFYYGcJrtOtA5Gj997OZ5sjPgMzNmUOaNJtlpyiFLnu//M2NohtHlVTyXs454caa5Uig6jzdycF1O98PzMffd7JodLsvE8siMfmYxLRvfxznCXn+ZLaQtGST77y1LN9QZwEV+1QFg/VrQBQD8m69MFdCUGScbUSsfjJmVP8Aj/w1YwHjksIeBkw29laYVHs+2UXUBWXveePUOSRpgZaVv5W7gYmPiULPvBethgJjZyloMi0EgzI3HgN+18trIRzPL5RDS1sb15Ui7l+9tjA923RqX//4z8cLU3SVPLBvRbU3rSojPctnfuXIeu+cxsdNAWC7vms0sDWfXkpsGOOz/+NfmhfDNHGeQbDCeAWEGhoy3nQo+Y0eC77CLeEfLVLRefX8ZI88z5oXnpp8FsMPoGzDtaZ8ouYfeVHNquLtyHi3HwLFpija4liHrKz9ra+P6cobwicHe0iYAsMGfnTwAyo6Wqbi04Y441t9XYeI9F6wLPMcz++U1hgzM6uLw2JkDBL73R5+MF6burox/dl6YX8yVi9N3VXSV0z3MZBqgZoaQz7AZxOxqXgP7O1dWQJ/75jnpzUeZgXdEwQ6odSpyqgPAxX3VAWD9WtAFAPx/V3RWPNzMlAFAMsNjo25AUAsg2CgZiGVwmEM0tcIyKFQYLO7tdmAQqCfoUMzmho1xsGskzo63FxaF7xn0bG6Yy32rFV50GMgGx8DRYaDDPUPlWDsAGvJ8dskDpX7dcyNd8fzqeypgzgwZRj7LFUNhA2yWZHfbZDw30hU/fezm+MnDXyrnnBJ2NPDD6DJOjAn9BuwyJmZKDNIyC1gr/Hakd7AcacY8c/I89/Z3aB/GmM/UKvWCvM38mMEkd9CgBlbP4+iQm+eXjbdBkecv/eB1s6r8wNIig91tk/HqfbfHgc7RONA5GnuXj5dQ9f7OlRX2FHYuM59eb6wvPu957jVkB4z7wKiRdmBQST/4nVlxv2aHiD7beeJzeVe9dYrnNb8dLcivZVab/nitZ/Zya+P6srmG/nJfTl5hXdhxQHfC4HrueQ6SsmFZZWfRDKQ3d8Fm086nb9xUrwO4yK86AKxfC7oAgH9664bKbtecl+YNB4Ruc1iuFpvnEA0GxgbSYCkzYih952CZ/XLJGrM7zt/KIAKgx3uvrL8zXlrbVJSx86RopxPYc+jGwM9AmMR8ywJ2C2AFwIBZojzK+cnWeOe3r6tpKPl+LVbWoD2PA/fa0z4RxwdWlOP9MguCfGCyDPJ4DucQO8ybmRUMZQ7TZ5YGIPvW1z8fZ8fbKyywDSCGjtfNeNJOt9GniHiOUuPPANeM7eaGjXHX1feVeUefPFbMHQo/+3UDFzNEZroyG+xjAgEpFDp++d7GwpAe7RsoeZsGwj7DmnHwTlr+3t02WfI4vfnCYJu19fSNm+L8ZGvFkbuwpiWO9g3Mm5MGM6xp7m22zPMzAzaXADIw8wlBAEmfQ4z87Wgw5ywf6wzamGXO/4TemecZHFrXWHe57dua1pUd9M7rs0OS8/2yU+V+Hewaia2N6+PCmpbKmuKnzgAu7qsOAOvXgi7nANpQYjgcsjP7QcjN/2MIUVpmU6zkNjdsLKcWOE8N40W4x2xEzh10jpONAPdz6DrvLMSAwQxyikIOtfB/Vv42YhmAGUhYuVMA2LmFBtSbGzbG6dHOYrzPjrcXuXsThgFoNii1gNa2prk8NvrkEz1smAGh+R5mVNkte3H6rnh+9T0VmWLoLf9aIIjnYTDJ49vVuioOdI7Gvo6xCtuGDLKhN5NjEOfPmJ0xYGEuw34iD4+LgbAdIkAN9zDIdEjSm0R8bjNyzqwO94XRPtbfV3ZdG0QBqmk7YXbGwKASWdLHE4O9JWxsVhPQ4rkN87u7bbIiQ1536JjvO8WCfiMjxol5Z+ds+7LpwrYRzjZIBlgZqNMvr387l4A+rwM7Mu6H77ejZSrOTbTFhTUthVG1o8pcNLjO+ZwG1QaKZtoN/N0n5q2PlXOx7txvvlsvA7O4rzoArF8LupwDiIJxPlUGfFbIVqi5BpsNthm3WmwdRmB/58pioDI4yiFGg4KcQO66ZgZvBjNmrHI5E4eObBQdTsuAEKBiMOg8IzZ9mC00CwIQBYyQ/E+fMDbbmtbFyCceLeDY75lZzQATxot2khOYQRXPt6FD3jz/ra9/vgD4fR1jZRfq4Z6hSuK9Dbyf7w0LPB+DzNm6ee64OLCdA4NsmDKDfMaZ9uA8IBucDQwubFoePzOCk9c8Vtqy9tpN5XMwhdzLIUCAAmPtTR8u9E27D3UPV0KNdkQAKgDDzMTyHO9c3dY0Vz8vp0j4XowV64E2bm7YGCcGeytHIwKeAGteQ56HBkW1GFDad36ytZJ/x3P8+S1LN8Tzq++pAFj0g8F03k1ugMz/Tr9gLtD+cxNtJSrAfAW4+rlOKfEzPY52HHxeuTc8GaR7fJDR3uXjZb1Zbl4/9RDw4r7qALB+LehyIWgbXBTVQ9c/Hsf6+yqGGgVoz9SMghW7PXSDAJgVPnO0byBevrcxXr63MfZ3rqx41NzDOTP2wq04absN1f7OlaXsCR44YADFTVFi948+GWjWMhr+cXtz381Yue8odbMYNtD5feeSAc5e29hQMd6EymyQzdpihGyszHq6/cjALA87UA/3DMXhnqHSP+eZZWaSHDtez/dl7ABLdi5gFfmcAYvr+Nm40h7v3CW8yVylHT5+0KCN77qtnAzhTSoPXf94CTuTP+hx8yYkgD47h5GV2bMMol3SJZcgyTmw3vXLz67WVSWv1Eyhw+fIzSkGzN19HWOVc7DtXJhNYy55jmZnz0DGP3a6HJK2I8JZ4qwNA0V+GEPrJDuamaX0et2+bK7s04U1LZUwuqMUjP/utsmKs+goSH4+68usn9c+48Z3vN5//OCX480nbyqft7PAWNUB4OK+6gCwfi3ocg6gWTuU8DNffKQUjDWbtWXphhI2NUvlnXtm7fjhfbN8s80zcXq0M979ztwpByeHeuYp9hze88Hv9prNFtCmwz1DcWq4uyTOZ6+bDRrUycPgWkljmGwUslGzYcTAmHVDpt6paQOHMcD4U+jXCegYGrNbtVhCAx/f04aZHECHWf0cM6jeCclnYevYsby5YWOcn2wtGwWQATJ+dskDpayKAb6BMLtNz463l40QPB+ZZ5bVAJzXvWGJ+eJnjHzi0UremR0LOzBbG9eX4s5mwZEpjJ9ZbgCggS4y43s4HvQBts/AzvPeqQMOpzs0OfKJR+fNB4BF3rFsmXnNAnyRAfczqPR6MNPmuUONyAx2MrBlLr98b2OZQ2bLkZ9BlZ3JzDg69YPPOlyLDjAzmnXHsf6+ePnexnnAMju6no9mAQ0YnRbCeBg4GxBbRsiUtXC4Z2he2NcpKPWzgBf3VQeA9WtBlwGgmTHviESJmhHKRpfv5jBvDvkCyGw0YZReve/2eP3+22Jfx1jFsNvAWMnayBmw2bgApH70wJI4NdxdDBC5VhhTkuPpv/uMMbKhyOFkg1MzkoBJH3FH280+mNWiX28/9bl4799+ooAn+u0QewYLzmOz8eJ/A9ETg71xuGcotizdUE624LMGLJnRoT1bls6VKTEQoUAxbeG+lptDY2YVAZP5s8jK4cbMjvI8A0qcDDsLHjMAHaFc958fNn/QX9rgcKvbwtGDsDduv1kms14AaIAaMjjSOxiT1zw2L4/SbJ+BBTJAjqyLg10jFdmaKXT4GseMMc9AzW02eDf7a0DE/4DsSxvumLdOnHtpJo3xM0DPmz8IxRs0u51evwDA3W2Tcah7OI72DVTec2rCmbGOclqO+0xfmX+ufek1xlgZZHo9Wl86BO/30H8nh3pKLig/tNeg9D82raoDwEV81QFg/VrQ5ZNAYCEMSFDUeTOEwQWKCIVqhiB/B8W3r2OsGCEM2uGeoQqrxPe9mcSedw4xmfkws3Fuoi1++tjNcWFNSyWPz8rW+Wec8Wo58CyHhm0MbcAwqP6NbAghXfrq0kr7Df7Izzs/2Ronh3oqwHa2eSbe+vrnK2xLLRYms4bI08Ams00AYzsCtXKSkPOh7uF47w+viZfWNhXgAKjAeGc5wTDRZwAwbA7y53uAF55tBpZ8Q+5jAGPDTQ0//qdf3smemRvmjnO4eA1m1SFp2Dv6s79zZQGDNtq0ldA1fXJ9Rc85AA9hR4CwQZZDuC55tLNlTRzqHo5j/X2VzSIZqCC3PBeQoXcY5754rhnwnhnrmMcW5tA172e5eL6bfX5pbVMZQwBzdozyOs3M/LamdXFquLtUPPDa4T7H+vvKM0m58Ppzv617vM4cMqY9lmktZ4DP0o7ty6bLWc+Zpbce3LK0ngO42K86AKxfC7oAgP9P22C88egtcWaso6L07OHbiKNUbVRyTpU958zmmdXw+1ZqmYlDkaL483soxVygdk/7RFycvisOdo3UzL3b1rQuDnaNxHMjXXFyqKeEga34DWYBcm6rAZzDVja225dNl7A5Se/Ix4wbbXp+9T3x08durrAzgA2zDga1ZgUsAwO3h65/vISm/T0AVS7cbGYxh652tqwpOaJmo1y3MbOqZrIMnOwQbG2cKyR9bqIt3n7qc3Gwa6SS/M9vAKtBoBlHWCKXLLF83H8MOvIhBM4GHefgMT/4yQy5Wa0cNuY11o83J5jdy+yax8vAOfcbpmtP+0S889vXxfOr76nkf/rsbca0FpvoOYM8CM/a4eA9h22damGWN4eytyzdUClG7jYwfgaK3ojCb77H/PW45rxXg1tk4HvsaJmK1zY2zFs/MMWZZWZezTbPlDxiz7XZ5pl5JYl4z47RlqUf7hw3yDTAz/mX7uc3bni4DgAX8VUHgPVrQRcAcFvzePzi6c/ETx7+UuzrGKuAHJSbiwWbZeEHxZfzsqywsuKr5emjlKkvhoHPnndmHg1QbTi5/4U1LRUjDIDYu3w8zo63x+v33xY/fvDLcWFNSxwfWDEPSOWwHgraBt6hXgMoh9lmm2fizFhHJRfQABfDtKd9ouxGNDOQmU6DHwBRljPtBkAapLrmH4ntZloMdg0ckc2ZsY7Yu3w8fv6tGwoD4s0eyMAhN+5nkIiRQ3Y+3eJYf1/sXT5eAIB3ncJ2eVMF3zXDRx9d9w5HBVbFG0QsVwMz/8/4IUeeB0h0OZgdLVPlODr64HmaWWynKDDHYNG86WVb07pywgcy2tcxFge7RuLShjsqu5H5rMEIa8a70gFUdioy++2SPpsbqrl7DkVT4gV224AuM4deL1573M/rwM4Fzze4y/3xGjA7b8DmsLOdFOs9O5q8dqR3MN79zrXl2MnsnCIjp0/gUGQ95zl3pHewohPNIPL39mXT8bd3rq4DwEV81QFg/VrQBQD8j02r4uRQTwk3oHhheJ5ffU+cm2gru/Cs6FFEmV1zXpsZEhStQZtrtGVGz0xFZqZgPKwYc3gRI3W4Z6hSq47w26Hu4bj01aVx+T99Oj7YvSR+8vCX4lh/X8nNwujmPCmDNhsde+mZFaQvr953eyU87P4BSrY2rq9sXMnha4NAgyxvsLk4fVeF9bFBMshGJgbHDhebeTIjxQYGwuZmcBw69zMfuv7xStmMzDyZjTNjTHkc0hTMgtDHzK64UDigxY5IBnYOoSNzhy2ZCzBf3Hv7sunY1zFW2uYcR+6xr2OsjA2hWmRpg06I2QDTY+SSJLB9BzpH40jvYJwc6onjAyvKecEUMzbQtPOSUwmyDOxM5I0PZu9oi/WGGX7mNHoDkOVwtmXgcfVaoo12yvJ76Ac7lJ63teYyY+s6fdlBMYPtNm9umEvreGX9nRX2mXs4/QLdidPlcUG3wJLual0V5ybaKhtqrFO85usAcHFfdQBYvxZ0AQD/qmFtbG2cC5fu71xZjMye9ol4fvU9cfk/zO3QPTHYW/G+Hdb1BgMDQjN1/J9DXFmhZ2Dke3uDSs6tgQUwS2UQYhCFgT8+sCJeWtsUl793Zbx7fHn86IElpWyMQYMVrks72GgZFDtUzndtvAykc+jNR9MZQJkhMOA202GZmYWwAcxsKTUBDbLzGPM/cuF+hP8oPGzwvblhYyU0592RtCWDYwxhHrPZ5pk4Ndwdb3/7s3F2vL2wSWZInFtnEOmQLO2abZ6JkU88WnFQAKjkqCJ319sDQHpzgceTuWrWGmBnmfMdcgU9n7Yvm6spCKvpue6NUKzTk0M9pX7dizPNcX6ytZz2YrCSmam8NvJ6wxFDZsx777Yl7GngC2B0TqU3PZ0Y7I1Tw92VoxzNKCLLp2/cFHuXj1eYu9wWrwM7mf6btnot8prn8sv3NlbSF7yuMhB1DqBZPjOPufZlfrZ1oZnVnS1r4mjfQBzuGSr1LXEC6IN1Xz0HcHFfdQBYvxZ0AQD/9s7VsXf5eFxY0xKvrL8zTo92Fmbn7Hh7/PL3fj3eeOTWODHYW0KIKKEM/GxMMlNjw2NwY3DgXZ7stAO0+Li62eaZcn6uQQ2G28wgHrXBKGG4nS1r4vRoZ7yy/s54/f7b4ux4ewnlOORoVsRlMXIhaYwmrJQZksyyePeyZUF7vSsTVsWMArLiM5QlscwdRoPxw6AZrB4fWFEBCgbhfN7sAwwVRo8Q8oHO0ZolTZCVjZ1ZEN+bHwNAGLRj/X3xy9/79bj8vSvj0leXVmq6+VneUOBj5Fy2hvcxppkl5fee9ol5xchdmgRngvlk0ABQMXMIIKLPfB/G2aCUH3bBetPHrtZVcah7OI4PrIgfP/jleO+PPhnv//HH4vX7b4vTo51lvdB2hzhrnZaRwYnHyLKxk7Ctaa72Xi7BgnwNXrYs3RAHu0bmxm/2hjgz1lEJSSPDWuFxRwnsRNkBY3zzPHIeYF5vzHnn8eb5l6MP9NX3zbmgma1zJMPM8o8eWFLeZ0PQ+cnWeG1jQ1z66tKyacVOWWYD62VgFvdVB4D1a0EXAPC/LFsZxwdWxFtf/3y8/19vi5fvbYxD3cMFpBztG4gjvYPx2saGStjEStEgMNcAxAijgDF62Vhwb4xhDgMRArOnbcVo5iIzk4TjnLiNIdnTPlF2TLLzdMvSucRsvHiHcLyBw4Yxh3Uz8+cQMYDGzAbhHwoOm5Wjrc4ZstEzQwFL57Co2cItS+fCcgaAtQwc8svgx0CV13a1rooXpu6OD757ZVycvquwaL6328w4A+Z5nU0YnheEXgEk5By+fG9jnB7tLDIzqDE4cY7bjpapyqYGj53HeXPDxgprZWcks7aunWfgRP8BYsiLXETmUffVD80L8+XQYzb6BqfnJ1vj7W9/Nn55qjfePb48fv7NG+PMWEcc6R2MzQ0bY+21mwrw44xay8iOi+e1gTQspuey15sdvlr5b8jjUPdwfPDdK+OD3Uvi/GRrpS98F2eQMkJmdpGfdQ5yyZt9ajlWdhbd9+3LpuPseHuFSTfLCeD2mvN37dyYCXcY3GAbUE9bSCM4PdoZbzx6S7y/7/Z457eujxem7o79nSsrLDltwOn5q4a1dQC4iK86AKxfC7oAgH/XPBGnRzvjtY0N8cF3r4wLa1rKblg88iO9g/HOb18XP33s5oriNCOQd9thVPJuYRt/57fZs7eiy4rboUMr5JzkbzbSJURs2GCmyOHa1vThsWIYd9pAyIr+8iyHxbgn7B/9AyT4c2za8O5Xs4M2+oBYswsGsQ4tHukdLKwVfbZBMuuGUWPnqENbBpdO+Oc9drHual0Ve9on4oWpu+Pyf/5svHxvY5wa7i67dw0mHeo0O0qpEjPAyI02Pn3jpsIuOjcTFgmQ4fHPTI+BA9836+bXMkPmcDagAMP+7JIPC10D+phze9onKvmAeX6bZfb85LWnb9xUHBHvoN/TPhF7l4/HyaGeeOPRW+Lyv78q3n/mY/HGI7fGcyNdsbttsuROsj59LB1zwvPT9fbs3DE/Ya2RQZZJniOWP896bqSr5BQz92E//VmPCbJhPWVAbKCeQafzdJ3b+OySB0qY3Rt6DMDNMnpsrOtIlbHjaaCH7AymPUd5b1frqjg/2RpvPnlTvPX6I/GLpz8TF9a0xMGukYrTYeC7ZemG+Isl6+sAcBFfdQBYvxZ0AQD/Ysmc4j8+sCJODPbGoe7hwjQ57AQ7lvO3siK20ch5K1bkmSmETbKxRsnmHYdmDgwqeJbz5Xim88b4PmwGBp0+0o58b5S67+2+Y1zMtGWGk//ZdGNQ6f8drt3XMVYBwAY1vOYQnI2NNyzQTkDrlqVz5TYAe5zk4Xw93xdw4xA1bdzRMhUnBnvjF09/Jt79zrXx0tqmAtiYN/Qzb/yhH4BqyyCDeYMANqAAjp4b6YqL03fFkd7B8jyMPWDWDA+5ZjzLm3FyLqZ3KQNe2HX77JIPixXn8cHJ2Na0rhR35n364vnO7mFkDzNM23AcnC92frI1Xr63MS5tuCOeX31PHOoeLuNkme1um4z9nSvjUPdw7GmfqIBv5+N5PvPbYw3Q8vry62bdnY5hQGxm1zluzIVX1t9ZmccGUQbTOTRtZpLxcn6h9dXkNY9Vchs9z1165VD3cEUOnkf0w0z8lqUb5ukbQJznlNf57rbJODHYGy/f2xhvPHpLXNpwR5wc6inOBO1y/7c21k8CWexXHQDWrwVdeRPIjpapwqa4fhe/Udw2DJsbNs7LZTMTgGJHcQK2fPIGnreVt0OGDlFhxBxqMqvCDl4DSgM+nzXs3xlIASBdusK7V7mvQ0Q5Cd4sgMNBKO/dbZOlKLQNFGCDz25ZuqGUhDATYfaGPCGegVxhN2irGQpkyGs7WqbizFhHBYwYCMByeZyQFW0+OdQT7/3hNfHzl//P+MnDXyoAEHaPNhtYuCQOQN0hN2TrHCvu6e/DJu5dPh6vbWyo5IgyBh5fgNS+jrF44kyCIQAAIABJREFU/48/VsldNPPH3PCuXOdxsQvXzGQOpTscboC1d/l4ZROF54rnhIEHPzzr/GRrHOoeLmkMe5ePx4HO0QIk6eP+zpWxu20yDnaNxKHu4TjYNRLH+vtiT/tE7GmfiOdGuuaVjTHrxL3s4ACAmB8eIzt6OBXWH2b8vRa5D8DaDkl2JL0OfB9SCexkeFz9LEcrnHKB42Kd43XBXPDGKH7M9LtEFuvVDizjjZN9tG8gTo92lkLQzAvnrnpd/vXS6ToAXMRXHQDWrwVd3gSSWR4bHhS3laZrn6EobRgy82RQB+PivDwMoHMFbVzMYBlo2YvGa7eBNYDc2rg+Tgz2Vu5hReqQFd/zsyybbU3rSu0zM5zeocx3auVEYvh+tuk3K0aB+5EvaLBsgAdgdoiWv5Gzd0zno+cy4DBAhd0z8COkzJhYZmYCD3UPx/Or7ymbicg5A3jzfUJ+BucG5dkQ0y6Aoccpl5Uxy7h92XSMfOLRyjyzY0ItyBODvYXBOznUE6/ff1tcWNMSe5ePx/nJ1ri04Y441D0cR3oHy0kqnPjhuoH0xzlf7gfjBGC28+KQIfLwsYUwbGaej/X3xa7WVQXcMXawf2bdqBd4pHewsP1H+wbKsYAHu0ZKKoDBLuPB/wYsvJ9D+56T3iwBoLEDYYYSZyIzi8jOOof1R+oCP7XWNO3xHKG9TouwLjLQcyjaLPrbT30unl99T5GR+2Vmk/6YIQUkoj+5567WVaWuY95Y5KhHaV/zeB0ALuKrDgDr14Iuh4A5s9YlLqzMzB4Z3BhsmEUzE8D7KDKU1/7OlZVjsDLIM5Ng4OI8HYcfac+BztEK2DJAdOgThe3Puv32uP3alqUbClOK4XLOnuXD32w6wFDSJnYhT17zWOmT83xyOJo2m0XIG2Wcb1VrIwjjCZiwgeV7ANwMWs2qbG1cX2pDZnZz7/LxONbfF6dHO8uGIvfbgDYzgjtb1lQYYYfO2HBiUGLQZPC+rWldqWOYGV6OPmSn+9G+gQIwL311aXyw85b45e9+Ok6Pdsbl710Z7/3RJ+PCmpZyH9oKkwvTCohERp4bT9+4qVL2hb4gD/qTy+B4ThjkHO0bKODOnzMbDatJ6PfkUE+cGOyNs+PtcW6iLc6MdcRzI11xoHO0hITJ6eQ5ZvdZZ17jft9ghTYQSs2bk+xgmfWebZ6Js+PtZdwd9vRcN5DLUQaD0uywbG7YGEf7Birrx/PDbDEOgh0UPxtAa73msHPOa3Tuqh1OZAR4Jw/Z69Mg1A7iwb7ldQC4iK86AKxfC7oAgH/zlWoCuhW5laaBgb1de9coNodTcqgWJUoYCgVuY23jbnCSf/MZh9bIzaINzkMye+HvO6zm12CObAxtdHw8lgGGQ0s2HoAxAOHBrpF49/c/VU6zMKg12/rskgdKGBiQ5fCYAThGgpw4h6jcJod43c4M/Amxwq5608S+jrF5YX4DvQOdo/HiTHMFhJktBWTnNnjcmRc5JcHj6/Aa9/FRc2aaeAZ5bzCRPPe5ka549b7b4+RQTwmXHu4ZqrBClg0G2Xlp7ge/fUIJzzRo494PXf947G6bLECCuc2ztjauL3LnmfQDpo8xB4zD/J0c6onzk63x6n23x+v33xaXvro0zk+2xvGBFXGwa6QUTOcHwGImc3PDh8fYIW9v9LLTBCCG/TPb6XQPj5sdHoMygzrPYTZyGBgyX3wPOwa8bl1g9px7H+vvizNjHfOcWs8rwJjZZzOoZhBzFIH7mOl1yZ88bw1A97RPxJHewXjj+5+sA8BFfNUBYP1a0AUA/NNb52+osMI1QDIbiNKzks0gwKApK+nty6ZLzT0+Y3bPoMVsIr/ZvGA2z7XUAAn5b0rbuKaewzI7W9bEgc7RSgiU55jhyCEmSpGYsTAL43xE5LStaV3JL4IhNKB85ouPlO/PNs/Ekd7BStjXMibEZCN1cqgnLn11aZER4VfGjmf6b4fvvDua+eCQbGYUDRIYu1PD3bGnfSIO9wxVwIwNo4G5wd22pnVldy33Ztwt92zAbdjNVuMksMvdIPjpGzeVMaRPZjQZUwCLQYqNNf8biDCv6DMy8CYZGKDMECEfy2t322Qc6h4uQI1nmkXb1bqqMH+Eejn28O2nPhfvfufa+Pm3bijhek4QoQQRADPvYN6+bDrOTbRV5r9BoIEWbT430VYBsMjN6SYGjmbmPJecW2s5m+nnHrTd93bolHbWqsmI/M5PthZdYOeM++TTQ/ysvLvcLDnzP+vCg10jZYMR98AJzXN7d9tkHO0biNf/r/+jDgAX8VUHgPVrQRcA8Bs3PFxRvg7FmrEiBGpgZq/YoREzNj4VwGzCmbGOeewYIJHXzUj5xyFQA0uzJn6eDfqu1lXx1tc/XzYBGCRgQMhdc//IZ6oVoj3W31cBXrVAsfsJ4MPQ+/OZBUTmAB3aZnYFmZpZ8m/65dMXXCbGrBvyONbfF5f/8so4O95eAUoGkB4fxgNGJreD/DReM2uMHAjN2oHIoJVxRS6AfhhZ5+MBvvic2UA2SXgsAYFmCvO8PDXcPY/ZBeDRF4chkTX9pk+8N9s8t5EjM0b85gxhg7EMkAAs3J8fQOCh7uE4PdoZL0zdHW99/fNx+ftXxT/98w/i8l9eGT997OZ4YeruONbfV/IacUoMtJhDgJUMTDMzikMw2zwTl766tPJ5O452YHwP5EeqAv3nPZ/lzPrwuiE8jiwMwDyu2eE1K3tquLuimzKYdGg+M4LeBWwnwZ/lM6eGu+OV9XfGS2ubSl6nv2OHxo7Bjpapegh4kV91APgrdn3hC1+IK664Yt7Po48+GhERXV1d8957+OGHK/f47//9v8fIyEhcffXVcf3118c3v/nNuHz58v9WO8wAYkQM3nJ4kB8bGRgrFB9KEmXuEhtmBrnvkd7BeayA81xshBxm4bdLexgwGEzB7pi5eWltU/GyHerCiJwe7azJevrznLdqVsC17ACkZvPMWlkWGCrajLz4nAHH3uXjcXxgReU7BjWzzTNxYU1LJRfRgNljasbEgHT7srmSOK9tbIhD3cOVzTiEqv1MjLOfl4E9DNWe9ok41t8X+zrGYk/7xDwWhfC9x5vP+NxhpykAEjwWhOczo+Swsh2VnPbA/GXsmB9mi8wGMf7O6csMJE6HWTrmi5+bgdCBztHYvmw69i4fL+DMANsOhDdt0ab9nSvj9GhnvDjTHL94+jPx/n+9bQ4A/vur4icPfymeX31PHOkdjAOdo4UdtUNoAOaxzuyXcwTznMR5MqNsFi87BN45btBoUGSHiufRZpdxQbaWM+NjBtVM59bGD4uq2yEwE2rm2WkQebOHowluFzK7sKYlPvizK+P9P/5YZSd+1ssGj8jjh3eP1gHgIr7qAPBX7PrRj34Ur776avnZsWNHXHHFFbFr166ImAOADz74YOUzXtz/9E//FLfffnv09fXF0aNH44c//GFcd9118e1vf/t/qx0AwL9e+mFIwiAMZsNKFEUMs4IxQLnCFpoZ4nsoMbOFnCFrsGAAacNg9jEbD9prhpG2+hQIDMux/r5ijPnxxgPu7fANHvuWpRviuZGuuPzslfHmkzdVwm61WEgbCLOrZv4I/2Vmafuy6Vh77abCKmGIX763scJeZCaP7xoc53GsBVBoz+aGjSXPDNCc2Qj+9vMBPg5Pe2fl7rbJOdn9w41xcfquOD/ZWk5FMXDGgBoAwCwa2JsVMkNj+fteNv5mgniffuYQJeNgdo42O3/P8+D0aGecHu2sgCGvIQOPPA9ybt/RvoF5zFkGq2aizIqxQ/jUcPdcoeEnvhAffPfKuPz9q+KXv/vpuPTVpXF2vD0O9wyVz/pZ5CTCnpvhzaF2s3Xui2VgUM588UkrrFmH2Rkzg2WPdXYivQPa97DesJ6xkwoo4zvWL8jXIVnmVa4baRYcRpB7o3u2L5srI3Nuoi1+8fRn4q2vf76cbuM+ZbCJvLcvm67vAl7kVx0A/opfTzzxRNxyyy3xz//8zxExBwCfeOKJj/z8D3/4w/i1X/u1eO2118pr3/3ud+NTn/pUvP/++//LzzUAtCFEKaOgOU4L4+bwsBmH7LUa9OXXuJdZGzODgAiHd31/n+yRQ9Ao5FPD3RXmkX7NNs/E86vvqXn+rQ3rkd7BONI7OI+12dywMQ73DMUHf3JVXFjTMo85ApBko2JWyMCCcO6r990eB7tGKkbNTKJZQ7OkyIsi1m4LpSS4FzswMcze+Wtjxrg6ZJkNZd59jGHkf7NHZmwPdo3EL3/303F59ob44M+vjNOjnRXQwDjCdPV//GulMHMOLSMX5gLji7Ng4GsGMM/3WiDYjLCBM/Kh1pxTHQweDnSOxqnh7gqoBpwYSBocMQf5ztG+gTg30VaTMTQTn9MPYLxnm+c26uxum4zDPUNxbqItLm24I3626Tfjra9/Pt545Na4sKYlTg71lNyznEbABqDty6YrdTQzQ5hlzXvMC+aX1xpjaLbaAJHTX8z68znLiTnt+cu9kYVBFM5NBtDcc1frqjIv/WwDQeRPn637vOb8/VoRlO3LpuNI72CcHW8v5yMbONuRyrLd2bKmXgdwkV91APgrfL3//vvxG7/xG/H7v//75bWurq647rrr4jd+4zeioaEh/tW/+lfxzjvvlPf/9b/+1/GVr3ylcp8LFy7EFVdcEf/tv/23/+Vn+yg4K/WdLWvi+dX3xLNLHqiUQMCQW9H6exhAA4Ls9VspZsNhxW92y0bFgMJApVbojPCy2SKzhtTbygzMM198JI70DsYHf35lvP/vro5j/X0VppHP7m6brOTUuU203aylwazBL/ek5pxBFoAKthX2hfYD6sxOIANyx7wb0kfU8VkfNp9ZRdf+M0PJWDkny8DQDInHhTDo86vviXd++7q4/P2r4v1/d3W89fXPx6nh7socyXl/NrTI0OFgv2c2kL66ODDtxLnh/jbwPNv3slF+6PrH5xV79vyiDw6ZMn/NTjGX6J/LBZmphAV2KBMATNFrA3KzdPs6xkpI/9xEW1xY0xIvzjTH86vviVPD3eUcbLNUMHqsrxdnmuPseHuljqFrTXqsGR/v8qfvBtbMIRw6O0t2HMzgIycAkTd62UF1MWbL/EjvYLx8b2Nlo5c3Wxj8Wj9Z9tYzdnqyU2oQTfje4XmvH/JfMzvK8+zs+XSbv71zdR0ALuKrDgB/ha8tW7bEv/gX/yJeeeWV8tr3vve92L59e5w4cSJ+8IMfxL/8l/8yVq1aVd5/8MEHY2BgoHKfd955J6644or44Q9/+JHPeu+99+Ktt94qPy+99FJcccUV8X+3DpVclxzCyAAqe7y1GDwDGBsDG16+g2LGWPEZMwYOSVkhmoHwb2qZAVq2LP0wB86f+cnDX4pX1t9Zdrrawz/QORpvPvGFePPJm8rxaGw2wHhxRisy4agwA2IzUt5EkhlFQsQGlAbYZv0wBqeGu0u9MG+yqcUowUpx0gOfQT5832By+7K5A+odXqW9ZjsMwOlfrbw6h3iP9ffFcyNdcXq0M85PtsbPv3VDnBrunhf+5B60OTsN9A8D7b7vaZ+YN5/cDgNaz1n/cBqF5972ZXObRZAN8nno+sdj7bXVjQkeNz+LI9gOdo3Egc7Rcl9YHeTPvfw9wKc3uCB75OF5yP2ozXh8YEWcHOqJk0M9Bfwd7Rso4MTH/NHuI72DcWKwt1LvMoeiPWeRCXKG5fNa3b5sLs+Uc4Hzd7xerZf8PzKALfaasaPjPMNdraviWH/fvLQMAyzWi/vnSAP/53QD9w9ASv3FcxNtpSwTc9x6zHM/Rz0MhA2oNzdsrDOAi/yqA8Bf4WtgYCBWrlz5P/3Mzp0744orrojz589HxMIB4O/8zu/U3Hzywv03x/7OlZVwIyADBZRBFkrKn6kV4jUjYeUNmAAwmGGzQT7QORqv339bJazKj0NzNjwksXuXoPPQtiydO0/1zSdvist/eWWcHOqpAAN2gm5rmstR5GxVK2uAlw2hWTVAbTZ6Zv4ymLZx4b4PXf/4PEbPn82G2qEu3p9tnintdx8AGYxBrVpuGKlsDHmO2ZHMzOSxsWPBxgCKDh/pHSzhLxgT7mmm0Q4Gz2Uu8dla/aDfgHLXXDTz6Tlq9pnxpVg6MvAJK147mXF2bh79Pj6wIs5PtsYLU3fHcyNdZYOMi0nbYWJuMicAm7zvXMjM2h7tG4gDnaOlJMyh7uE42jcQJ4d64lD3cIUJB+SZneJeeRy83j2vDnSOlnWXnUU+u6t1VZwZ64jL/3BjnJtoK3PNY2aw6TJJzFucA+sFxs5rj5JF25dNx+GeobIenK+cnSfPWwCpQZv74ZxB+gCzeWq4O17b2BDv/Nb18cYjt8bJoZ55ZYSYZ9ZB6Czf18CTOVhnABf3VQeAv6LXxYsX49d+7dfi7/7u7/6nn/vFL34RV1xxRWzfvj0iFh4C/igG8IX7by6nZziMUuvHSsieNkbCydywEBhF7m1Wg+8e7hmq7AZF4cJcOFS6rWldMYJ72ifi4vRdhZVBkdqYZGPFvY4PrIiz4+2VM2Mz6/bS2qa4/HfXxXMjXfNCmmaEDJQI45lZyMaK3zbyGACzbWbyMKI5xxBjkkPBNrYGebXYRYcdeYbZPYwSY+oSOvQB9rIWU2xwZYYQAAuQuzh9Vxzr7yt14wCD25rWxZmxjrg4fVcZJ+bAmbGOODPWUXE2sqNiIGHG0yyOjbtzy9iQQB8svwweGXezuA7dMo77O1fGizPN8f4ffyze+7efiB8/+OVyji/z0eF4vgvwMUuWAavD75yNDOimSPTutsnCQu5dPh6HuocrxYjNWAL2PVbIKOeqMR+dA5c3mNlB3NmypuTZAvpZB9Yv/smAyGuFvhtE2jkhHA4rmXUNzp2d3cz+ZVCWHWeDuT3tE/H86nvi59+6Id768WPx9lOfi7Pj7ZWQN6yvgatB7eaGjbH22k2VsXab6gzg4r7qAPBX9Pqd3/md+OxnP/v/W75l7969ccUVV8Tx48cj4sNNIK+//nr5zPe+97341Kc+Fe+9997/8vPJAdy1vK+yI9EJ/c5dskIihGoFa8Nq5ezX+AzKlvse6h4uoTAzYLWUofOJ9neujF88/ZlKPo+BQGbIbCQyE2kwwHsHOkfj0oY74mDXyLwwtPPOKE9Si80zCMyMBH01e7ijZSrOTbTF+cnW2NM+EWuv/fD4tczI8YzDPUMVAGtmFvBioOn8vmzoeB4hbTO9ZmzdhgxgDdJgYjHe3iUMyAGYAjS2L5urwfbS2qZSiw3Alx2UcxNtsa9jrMIMGvDBpPJcQIaNNxuGNjdsLHlrzm3LOZAGHAZeyNI7wwE6yG5322Qc6R2M1++/Ld7fd3u89caT8c5vXR+nhrvLvLCsAFVm0WebZ2LymscKGDNYNOu4fdl0OeKNUPCe9onYu3y8vA4gRP70a8vSDaV4N8/1GmAd+XxijyWORc5p9Fw24+uNX56XBr4uQeRd4ZlpN3sLmGZO41AC2O3QvLL+znhtY0PpowEX48lY+z1AJKkktGtP+0ScHW+PNx69Jd77o0/Gjx/8ckl18JnWdrytK607zFgyr3a0TNUB4CK/6gDwV/D6H//jf8RNN90UTz31VOX18+fPx7/5N/8mDh8+HC+88EL8/d//fdx8883R2dlZPkMZmIGBgTh27Fhs3749rr/++gWXgfnbO1dXAIuVj1k0g6sczvF3MEYADCfeozzt8frZ9sYNMLzpxIzb5oaNxWhmtsThPBtzGyvnO5kJMrjavmy6FNk1s2OlbDbLDBKfM2uH0eQZmxvmNijw7D3tE/Hzb90Ql//Tp+O5ka4K6+C8MOeAUe4js6ze+YrcMIyAWE4bMSDDSBuouV9maJC1QSBhTMvQDCMbPsy8mTF7dskDcah7ON545NZSow6DZ7AOk5WdDLMwyAk5ePzpb97Iw9zI4WXPY893s2YZMCA77rerdVWcGOyNHz2wJD748yvj3d//VLx63+2FBaf9OYUipxoYOJi15XOUWAIc+0hArzkXFAcE+t5eD5YDQN3937t8vHJWsx2OLEPL1owar2cmku/wv9eTWXNkCGC3c7W7bbKkiHgt0Gc2yyAb6yn3w1EP5oJZT352tEyVHb4vTN0dp0c7K+f8muE2q08+MEDX4+HNKPUQcP2qA8Bfwesf//Ef44orrogzZ85UXn/xxRejs7MzPv3pT8dVV10VX/ziF+Nb3/rWvMV98eLFGB4ejquvvjquu+66+MY3vrHgQtB/1bB2HptjAGQGjl1/eTMG75mZQVk6POJwkcNwWRn7vlbA2Zg4LGIQauYrA0bahBLOR505jwsl/eJMc2EovemBPB8YIp+ukcO8gBuHclHiZgNmm+dOTnjvjz5ZAUq12DrkTrHfzJRZvoybw5E5NAfQNdNqoMMuSb5vhtDG1nMDpgbWIzsQmfkw+4IBPjPWUeTs0jaMM22mLbTbDKyBoUEGfXW7nN/Jd32yBffIIM+AKzOa5ydbS7jzSO9gPDfSFS/ONMeFNS2VDT2erw9d/3jl+EHailPjfE9vuLGj5r7uaJkquaQeI8qtMP52InyP7Nx5vO3wAI48tpnBZhMMcjLT5fngMD5sI46L5W5dYH1h1teOpPVSBvN5HlovZDbUTlN2BNAv+zrGSg5mLhGDXN1n6zSzfoyVWc2/alhbB4CL+KoDwPq1oMsA0ArU3vjJoZ54caa5GFmDJxsZG53dbZMV5WxDZQNtUOQfAxLuCXuyrWldCeHAAOU8JCt/h34wJOQqWtnSX9rgMNbmho1xYrA3Ln116byzgG0sDGowHN7VZyNq4MW9cg7koe7heHGmOY70DlaMVK51ZgaC9wDouR6ei9W6fQBSh2+94zMbO/6HWTzSO1jqlxl40c+1124qjBCy99mxMLnO4TKApX9blm6I1zY2xI8f/HLsal1V8rUAF3YgzBg+dP3jBax7vgIOACAGGc7x3NY0dyaxQ43eHWwwijzJ++TYtOdGuuL4wIoKY0wfDnaNzGP2zIh6HLzmAHO1GDzaZ9aW014MFpFhDtOyzlivXsOs4+wgmsnic3amkN2BztEKqM2pJrTbAIw+MQ8YJ7OGzjt2u3a0TMULU3fPY/+sM3J/+J/UDqIFdry4vwGgnQbmJeueNW72tRazDNikrQbZnnPPLnkg/uDm++sAcBFfdQBYvxZ0AQD/5isf7uxzWBMltr9zZTEWme3z/1ZaZpDMDHyUl2+DRQ6ajUGte2E4bCxRuA49Oc/J/TDLYWaF/80s7V0+Hq9tbChGIDOlBh1mQxymwpg+u+SBuLThjiIHMzQG4tua1sWBztE4OdRTwJUZCzNBMAPZWBpIESpnXHe2rClsAsCB92EzDT5s/GuBgGeXPBD7O1dWQpeUnaGfedzpq+eTwVwGPnYydrRMxdnx9jgx2BuzzTOlZItrpHmueA7Sb8uOzz90/ePzcjQ9dvSX8QCsAKwurGkpodBj/X1xerRzHpPGPc38ZuDsz3suGxgwtgBBy8+AwsCMsTYb59p0BtK0x5/nvoBJ5+zBMDKX+J5zi3NYmPs6L866hDHwrmTLKOeTMvbWZV6fmf1DXyCzvIEH+ZwZ66jIwfPUc9Tfo13uh9lDg0avE4NTzwOcKAPXv/nKVB0ALuKrDgDr14IuAOBfLKkyYWbTrJgMfvg8Bt5esQ29Fa1BiXPyMAqzzXM1s6z8bQjdJitAhzVrMQ4Hu0bixw9+OX784JcrxaHNFKC0CS2hmB1iIoE8h+RglfihLplZOhQ3Rt+sgQEUwIrn8XlK1cAi8Ky1126aZ7BPDPaW5/Pc2eaZimE2W2JAbENmcGMAyJhlJpdabNR0o02Wr1lONgfk9pgp4m+zHzaaBg6zzTNxacMd8ep9t5e8Nht8zzXkZ6Brp8OMlstxzDbPFOCzd/l4vLS2Kc5NtMXBrpF449Fb4p3fvq7UjzQjy3gCTii+DWhi7nG+s8OKbotBkTdXmAHc1rSu5I059Gt2mXYYRG5tXB+HuoeLfJFtLRaQdZ/njEOlmdHzbxwagzvYZM9L9I37RnthV5Gfv49sPT/pV45cGIA5amHG3Iy615TXk3VcdjD9PgzhRznJ/LaTZ1la5802z9QZwEV+1QFg/VrQ5U0grj2GwbPxckK8QaGVpo2Rw5wYBTNjNuR8zkxeZi1sBLMnbVDo3ZcY12P9ffHL3/10vPuda+P4wIoKA+LyHla8ZmXcLp/YYKCEQXUIzgDPjEUG2wbcgBLeM7NkuWXZ5/D5z791Q/z8mzdWwJsT5bkPDBj3NFPhdjJ+Bpr5Hgbo+zrG4pX1d1YYSYwzTI7H0iHAnFdmxgvWclfrqsqua56xr2MsjvX3xav33R6vbWwop7Uc6R2sgD/GcrZ5prIrlOfkMP32ZdNxqHu4OEHbl03Hsf6+uPwPN8Ybj9wa+zrG4tKGO0opl30dYxUQsr9z5bwyRQb7OAWZPapVHsTgjPkFCHY42vPKQMSAxCHxXCQc4AiwMvOJjDyfauV/el0zrw347axxT34MeMw0cs9Tw93xxiO3xuGeocpz+dtA7GjfQGWeGNyy4cIMp3d325HzOvaP1471C++zWcksZHauresYV+Ru/ct65L06A7i4rzoArF8LugCAf3Dz/UUhW+laqVGKI3v2NkoGFrU2G9iIWdlZERpweLOBS7fY6DscaQXsMM/OljVxrL8vTgz2VvLOat3L7JDDLTYCLjScw0o5L8j32bJ0QwnT8lyXP7Hxpv/c+3DPUDHIyMFgxoAYQ0po1MaZsDY5eZaxAdClDXeUMGktRsqgNrO8AJLty6YLYDaz4fHy/DHz5/Crw3kf5RQgV9p/oHO07HrdsnRD2WBhWb1+/23xyvo7Sy28vcvH493vXBsHOkfL7s2ff/PGePOJL8RzI10lrAuTSZHfwz1DZaz2Lh8v8nI9PAM7wJCBsFldAyLLwaAfULHAFFE1AAAgAElEQVR3+fi8jTmZLcohXDs7s80z8cr6O+OV9XdWGCrPK88t7zrf1rSuUkTd68fPcWiWOUy/vJZyjcoMlsxUbmtaFxen74r3//hjcWaso8LaeZ5Zv+BAOI+PNtBGOzLZqaFfTpXwmsl6gjZwbzYRORLAd7OuNJhmbnvteFPTn966oQ4AF/FVB4D1a0GXQ8A5LGGjj+L331aSJNDzWvbAUXoZXBo05dcMAhxyefPJmyqhRYMrg4PsvW9ZuqGwMhhRQCXt3L7sw6OpSNx3zp3ZG9oFM+HQt8Ebf5uxsmHO+WmZDc1MjUtsEIo0ALXhONI7GD96YEmcGu6uCZzMaDx946Y41t9XGDqH4mmr2SA7AAa+OeRK282y1RqrDPrMWDln0d/DeHNf58FxXwNPlyNy6JmxJ8+Lfh7oHI0La1rKJhzmEjLLYNgbpRwW5D2DfULJBg7IxYDDID//djHhbU1z6QDe3OS55DWUQ9OcTGFHju+7PXaWdrasiYNdI3F+srXSLuak1z7y39q4vrKTnnXsuYOsPEc+am0c7BqJM2MdcaR3sMxLs+LZoasVpj3QORrnJtpKPULrPjsU/ts6wfqNZ7g0THbu3Aff16xoXhsGz5ltf3bJA/UyMIv8qgPA+rWgCwD4p7dWE/xt1KywUfBmXaycUFhm6pzz56K1/M/nzUCi4PDU3a7nRrqK8drRMhVrr50zOD603mDIYMKgwiEdnrezZU2cn2yNy3//mXhh6u4K6Mjs1s+/dUMlJGU2zIYkh2Ddnm1N64ohRbk7xLa5YWPFoMMEmpExS2k5Uhbm0oY74vxka6WN/mwGZLTXYewMyizbh65/vAKKDPS3Ns5tTtjfuTLOTbTFicHecgQXcyIzfxQO5n6WBTKgzI3HLgM+g3yDbQCu54RZK/qyp32iIoucK5r7bDbIMjaD6TnizTPuW94l6rEnVOkct9nmmTjYNVLuxXjkPDRAkD9Ti2GjPa5N5/Av/XnjkVtLiN8gJjsiyI1j6wzEcv88nzP49dy1joFpNsPmdtAHM2f0c1frqnI0G/czsCPfz2vYRe8NkpHZlqUbKg4DThXzOucD81ze570cLTETj2xoQz0EvLivOgCsXwu6XAbGnmY2rGZOzFI4rGmlbpbQoYsc0rJSM7AwO+AcOZcYscH237WMOe3DgJBvhVGx5364Z6jUawOAGjRyH85uzSEiG1uzi9ngGiAD/gxIzIpwz12tq+L0aGcBFLPNM5XcMYfXeB/5cd6rWVFAOPJ3GMq7Jn/+rRti7bWbKuNuZi3fM98L+ZE353bAvBk45DNfkSf3d5jP426AxVmqBhWeW4BL2m+Q43xYHB2eaQfD4Dgbar9mNiyzap5bGTgiH753qHu4ciThnvaJyuYnh7gN4Aj3G+SzRr1znHYb5GSAva1p7lzh95/5WLx+/23l83bmDMT43/PdAMcOooGXj5S0o5lZY9rK6w4jnx7tLDIx4OL7OLhmws3abWuaY9G9MYR15blnAOwzfO0cIic/x4xiZsGdfpFlle/1F0vW1wHgIr7qALB+LejKhaCzYrJhR5m7Vpw9cYyVWa7MIDnnLIc6AC4kolOUNhtYGBxveOBMUz5vRW6wZQCGsTCQcf+ca8ePjfeOlqm4tOGOSvJ4LdYs73w1Q2VDkzelYPTYzYtMyGEyY8J4sYOZUKTBwBuP3hKXn72ysEVmh8z8ZBaVNrskTjaSeR7k/tFe5ES4jbHb3LCxsjPa4ca8GYD2+ugygzOzVp5fdkhoH/2yIeZEFkCN2SLG02NpUIeT4rUE8HVZGbeL71F6xvKELdq+bLqyaxbw6u/nvuXyPgaUZh8zMM3g3Q4Jc+/MWEecHOopczOX3UHejF0Gp7VAsNen20U72R3N9znGLjuYyIbxJ0xei7GrpV9YA6xD/vYa8fp2yBrZwfRl3ck8y32sNX8B6I6iWJcBfLc1rasXgl7kVx0A1q8FXbkOIHlaGLocMvRrDnFayWcgkI043/Wuz6xUAWc/fvDLFVbCAI3/+XGhaBthDAgKGaM12zxTCuBmBcw9X5i6u/TJTCSA4Fh/X9kUAOPi0z0MbgEQZkFpN2wOBsuG3EyK8+8c+nL72XjhMPf2ZdPx3EhX2TEJWHQbzFwZ6ADMDTzzGHOvfKyek+v5HrlwfI+xyoya2R3L1zmQnjvZqDpEakCD7AF7Bml5bhs0IXszPZsbNsbkNY/F1sb1JcTp8L/D4+6X5/jaazdVwAZtw0GavOax8r2cjmC2GzBgEFYrBYJ5BaiBBc1nEJs5o1+87h3pgEOHknkm93R0wXLwnMuMMZ9hfphJf+aLj5QTNRhTvnu4Zyheve/2uDh9V/leBtweW4AWc4s+IQsXGuf5HkfkbnbRwNTjbdbOzK8ZQLcrA3v3lfWwtXF9nQFc5FcdANavBV0AwG/c8HDFw82gjPdybpsVu424jb1DJrA9ZiS8I9AMokGIjZfZINpro28QADNhww0w2dq4vmz0MCOxZemGYgjOjHXEsf6+Sv9h5TCGZmIcrqQvO1vWxKUNd8Tzq++p9Jf+AVAw3LTVcrA8MTCwgTbUDt3DYGHQ+P67v/+pChsDsAAAIWsbVdpzcfqusjnEYMKf93hRY485YofCgMlMkBkaM0lmUvJctFwNiDiRBoMJMwN4y3lymQlljufyJTCttfL4DMr4zo6WqVIj0bJyuNJ1C3/62M2VjTMZbNT6H3lkppt75jVlNsqfy+wffeHoOodrPRZeo4zL7rbJONwzVJPtymDHKRCuPWhWkr7BPmZHdUfLVDw30hXv77s93n/mY6UoOfdymabNDRvj/GRrZS147nstZ/YQ2Xk8+cnOmx0z5kcGmnZ47ITYubbey2HkOgBc3FcdANavBV0AwH+8Z7iS12UDizI32LH3ublhYzx0/eOlyLANyI6WqUrZFStQbwjJ7IwVnT3gDBa8uy4DxGyYzDY5POg+GXxhiN/6+ucr3vozX3ykEq7cvmy61BZEdtnIbWuay98yCOKeAAazCNuXTce5ibZ4aW1TBdDZKBgY0rZdrasqOV08P4PObU1zOyhdQNfg38AOOebkdzNMlrlDWNlg4RBwZrHHGqA+2zxTNork9AI+x3NqMXt5fA0sHeLjNX/e8985aeya9XM8t82YeVwASwYMZm4zWAaIX1jTUsYzg+vMLlo21Ed0CDozSbw22zxTjkX7KHDBetnfuTJODXfHjx/8cgnfe/4DvrgPRa4tM88L9EoGpwAjr1scNoMll9bxeGxu2BjH+vviwpqWODPWMU8OnisO65qJM7AymM6gjnYj+wxqzSp7bexqXRXnJtqKM+xUkwwwWXcG7ZYn87ReBmZxX3UAWL8WdAEAf3j3aEXpOb8ke6Jmt5yQb8OCkuY1jC7Gy4rWxs3J4g5RwgRlRbmtaV28ONNcUeIodVgeh49ycjv9MItiJu7NJ2+KC2taKmFKh1a5z3MjXRUgRd/zcWJW4ij4WnlI+V4O9drAINds6M2qGiwCWA50jsbF6buKwTVzSi4aBpFnmWE0qCc3jHF1X80WY/A4VpC+G0Q6rLuzZU0c6ByNfR1jlXniDUmWB33d0TIV5ybaCqDy+BOuNJt4oHO00gaANsYVYJpDzgZAXh8AM4N8A3TW1O62yWLYD3aNVEL/NvjbmqpHIwIICF8jE9rr2nKElw3Y7Lh5Hhuk+Z5bG+fSE6hvaDnl9cncO9bfFy/f21gB+cg+M4t2Ohg/y482M0b5LG6DSu51qHu4whqjW2CdkYlZvBz2z9EFP8+OQn7/UPdwqT/plBHPMdJGzLjSFju0nrfWi7ls1jdueLgOABfxVQeA9WtBlzeBWFlubtgYu9smC7DBiKF8axmUzMoZZBkEGmiitB36tRGcbZ6JI72DldIhH8VmmOFxaO7ShjsqLA+fxVA6TI0CRrnuaZ+IY/195Xk26A5XHuoejpNDPfPYlpxbl78HIAAw2wBj2J6+cVPJD0S25BS6/WajCJHZ0AEcPIbsKs7gN7OoGSw7FLunfaKyycXGDJk5PMt3cz/z+CCrU8PdcW6irYT8AGSWldt5qHu45H/52YAUz0PmHkDOwMSbRnhttvnDzSdmqsyE1WL6LJNtTXNlWOjHjpapEurN4ILxNtjinoCIzCaTA7qtaV28sv7OkubgEKTZI4f+OV/Z/T3W31dx0nCkDFKYS4zl2fH2ynixocmMGHPftQzdxwycnE6AHqjF/mdm1+9vXzYdp0c74+L0XZX1xnPNsBmI0g5klll47kHh8Esb7qicMmKncbZ5Zl49Susrg2I7I9ZPjDvPr28CWdxXHQDWrwVdPgrOBhoA+PNv3li8WXvANvAGglnhZmYKpQXIMvCy8bdxzkbcz0RR21M3mMQI5FAdShSQZ9aE5/lvhwjNVpl1NHvg3aNW3mbTaCvGzQyEv2MjjxHEkFomhAB3t03Gzzb9Zskvc56ZjT3J7YBcAzOH2pgXzsdinNnQkQ0yddBc3sXzw7KpZfgMyLYvm46TQz1xacMdcWq4O86Ot8eBztEKEKP/ZqkNjGC0ZptnSrFog0ezlp6j7iefccFzs7YZ/NJfs6b7OsYqx615Drjd2cHinoAl5hB5jTgbO1rmTi8hn5ANP9zXc5BxdKjV6xSAafbTrBZ6wfcizw45ZIfNzqLBW2bJXcvQZY4yM2d94fFyZMJtmG2eqQDArPNwpNgJbkeD9eF82ax3jvX3xQd/fmW8fG9j5Sxwfli/PCv3xfPLDkBmna0/tzaurwPARX7VAWD9WtBViwFEKW1rWle8eAyoPVYULB4+AMRGwoAr76LDwzWYMgjKBhkAZoXI52EGHLquZXTMOqJwD3aNxMmhnlKbzuDB+Tk21Aau/I+xBEw6PxFlj8EFkGKEzLw5pGtZGCBxPwMR/jaLg3EhLwwgktlXgKINN+PhjROwV7UYCc+V/Z0rKyFNA+ccNsusLX3zXOK7W5bO5ZedGu6O06OdMds8U2HCaBfPdsFj5kcurO2/M9viNAY+67kK6EJ2AKDzk63xxqO3xJHewQqYIIRn0JBLfWxu2FhOrMF5MYOLDM2oMc+P9ffF5e9fFT95+Etlk5BD0F7jZgJzDugLU3fHoe7hMj9oG8ylwZV36R7qHq6sIcstzwWvA+SRT0txnUbGqJYzaPaOte4UEv82cM06LzO2LqXj9BWeD7PJHNnVuiqO9A7Ggc7Rcn/mkPNO7SzZgdvauL6sI8Ci14X1gNnQeiHoxX3VAWD9WtDlk0AAVzYGABMnXWdgVQuM8V08ajNE/izK1GddOp+M912s2F63jZ/ZR+fMGECRr8Yzty+b29l6+ftXxdnx9pLsz3288eJg10gBO24DhvjZJQ/Evo6xcn8Mh9k/G1x2qGZAZmNmY8n3nFjvkDpt8SYA7m25GRBva/oweZ86c2bl/AyeSQ6Sx8f9tUzMohhkcS+HtA1YDQoBFw5Lbm38sDgwc81n0mJADTbzqQ7OR/soNjCDBMvPz+f/bU3r4vjAinj1vtvjp4/dHCeHeiqlldw3pwMYjDqE6bGzrLmPgd32ZdNxoHM03nzypjg30VZps0GknSmDHcDHuYm2ePOJL5ScP49vZt6QqRkuxsvzePKax4qTYKfDMjdAzQyo54ydAoPovcvH4/nV91RYX9oJ222HEv3k8bPjk3c6u8+0ce21m+a1y8yz15HnMa/lXc7MAcuVz1onWt7bl03XN4Es8qsOAOvXgi7XAXSyu8OPNjYANBSTw1289uySB+Jg18g80GMGLzNaNsAoaHLbUHgwW2aOYIrsYXt3sYGE84pQnjtapuL0aGf89LGb41h/XzGU5ybaKuzCrtZVsad9orQTowybYANwYrC3sisYJd3/8a+V/sAUOkfQxoPvZcOfx8agy6AP443RdYFsh+y8u3Vb09ypBwYP/u1cLNgPG9WP+jFb4/wysxgOU9rYmbk1gLJxhXm1wwLooeg1IMGnRrAp4FD3cOXsWbO13M8OC3PRYPFYf19sXzYdh3uG5m0usEOCzNxP5g6f41mwl2b+7NjAcs02z8SFNS2FETX4yaFWA0azUayjPe0T8YunPxNvPvGF0o/MNBvMAqSZz7BgvGagbyfQbCPzwKeJuN8Gihmw89nslHgsGcOdLWvi5XsbKyFq6xLmUXbs3BbYXoNV5MvRkYBERzSQtx1kAzozwZaZZew0kdnmuZ3Z9L8eAl7cVx0A1q8FXQaABk/PLnmghPrMotkQ2hhhRDDoVmh41vzYe891rwgzubAsz7w4fVe8tLapcoyYjef+zpWxd/l4hWFAefOMDCIBJTAEfN/3JySD0T073l4pcMvzAKwYQ4Np/jb4+ShWFfBh45zZMRsUsxP877Au9yH3zbucAWSZjckFhxkHh6qZFw5jOyS7uWFjKcWBkWdeOQk+h3gz82rwS1iM+3gOcY6qj5HzLmdkwtgRqr08e0OcGOwtAGD7sunYu3y8bKLZ1zEW7//xx+KFqbvjmS8+UgAjMjdINjjBMcFJMKDIjg5y81piPfE3sgC0A/B2tEzFL57+TGF++ZxD+gZvmRVkvhzpHYydLWvmbWgyiKSdZvmY15Su8bx1IW++b1aVcaXvBkO1WE6vOZ/wgc6yM+W0gM0NG+P4wIrKaSoGxMwLO7VOc/H6MovI2O9qXRUXp+8qZ3o79cMOk/tmx4r5YUcgA26v9eMDK+LShjvKd+oh4MV91QFg/VrQlRlA1yLDuNhoGPBkj9xsjUEj4MfKzGEw59FYuRocbG2cy2PD63VYBWNo4GaWDCWPgXAujn9yztWWpRtKiMfhZc4/zf3lHgAih2JtwHnv2SUPxMgnHq3IycwNcoV9ANzwLLOzGBjnvO1omTuyi2R0y9ehfY+PdwhTbNqMiEG5x52xwOgjK9oOKHb5mByGy0yfjaSZLW8OceqA5yLMp0PffM7h9AOdo/HS2qYKu4JsHRp0iNqA2/lo/KZki8c8zzmPh8GRjfxs80y8fv9tFTDB+B/tG6jkz2VQk9lws0o8g7bDIP7ydz9dCXeapUcm/J9BC2OI3MzAbW7YGCOfeLTcx/LLoWLPUbPbZvUzq+zn2RGx3JCnHVyemZlSz/WsU/wMj/ls80w5qs47d63zPK8c4nU/ec8yse6hbTgorMV6CHhxX3UAWL8WdAEA/3rph8bUJxaggMxwWOn7ByWZ64PZM+f7KEiHIwEwKFQDLOeb0T4bWBSkPXwDDTOSKG8MChsDzL6ZDeM9+uDadfbiHRoHSL98b2MBUu6/2wejY7BNDhLjwRjAfJk1sVEz8MaoIA/AqZkY2C7+5vO8v7ttsoSTDcIYv1q5ls7XynUdL07fVcbB48p9PcccQnMYHAeFNngcvVkF5o337QCYfbQTwPFiyM4goP/jXyvfZ05h9LNztKNlqjDZAGH6TcF0nBPm+s6WNaXtBmCZCZttnokzYx3zADJ9Acy67z4xZk/7RKk7yOs/emBJJWXCTClrGnaOz9FPrzPkasfBa88gmHHACbGz5/nJdy7/5ZU1HcQTg70VB846IesYp1k4YsEaoG3e+W9HzGycAWFmCN0GOyfcz5vLnG/oz+Twt0PUBrFbG9fHH9x8fx0ALuKrDgDr14IuAOBfLPlwV+Yr6+8sigblZGNfy4BbMdpbhWXgswaSZiec22KvOCtQh218aoBBGN/DqNpAZcVpsMSZrmZBbXxnm6tH22EUMPSuDwbwIbSYAQ6yAAwc6++r1CvMMrGRMTtAewy6c1gSY72nfSL2tE/Eoe7h2Lt8vOQK0p8dLVOxp32iUuYCQ7S/c2WFpUBOgITnV99TaatZMQC2+2A2yePlkFyWledPZphyfTg7DjCumWE2eN67fLwAJYctzcYYvBuMccIMwNFjUQuw8Pr2ZXObNtgkcqBztCJ3P8PyqBVGpn0G+HZG6M/hnqF4fvU98ep9t8cLU3dXnBMAnucqz6AWpseedQJDagCVHS0z34wd89/6gRAz9zPQ8lo1SNrRMlWOfKPdlmEGUtybvmYnAzkYqAK+HJqtpVfsFOb8VjO9jJfHzxt07Ezldee2I9t6CHhxX3UAWL8WdLkMTDbImYkwY5UV7dG+gVLfDEVmw20Gz0rPQMFsEIbXoSIr2G1NH+a3bVn64YYEg0grToe8rNgzsMC4uZ4ZBsAFa2ebZ4rRQQ4YPRttGy//pm+050jvYLz55E0lh8gsiMNmBmvPfPGRAoInr3msGB2MF7lwgK2z4+3xwtTd8cr6O+P8ZGsc7Bop/TJbaEABCDrQORqHuofL5geHHM2W8pvxYy74nsjRbJMdgswQ4XDwPuyMn1cLtJi5teNiNs5gFfmaKcr5WjDAgD7PLUCAwaZz2bypY8vSuXI9R/sG4uRQTxzpHSw1Ar0Tnbn5yvo7K7uJzUzZCeLHuWju09nx9vjgT66Kd84MxZtP3lROzLDMLU/mxMGukZJKwIaoDIhgjB1SdQ4c7Qb0mVnz2jUI5Tfvmwk1s5lTVuzcwRqbpTYAM9uWmVyDfo9drTlvptTfc3uyQ2zmGl1Ty+HgnrC7fI95WT8LeHFfdQBYvxZ0OQSMUrZSNeNhZW7wxucxmCjPzOCgaK2I+XGIaMvSDWWjgAFYzhUDFOWQHe3e0z5RSVTP7GIGZShYg0yHjmx0MPqcaWvAC/ihHWaRDPysxGeb5wrUHuvvq4Rc/dshM0JrZhQyS2j57GxZEycGe+OXv/fr8f7+r8SbT3whzk+2xtnx9jjcM1RCnz6ZxKzG5oa50PuFNS1xacMdlRpxGLNssMwkOk3AoXLG1mydw8AOb/IedfWyceW5sHIZRDt/EnnlZxpIZsBtw8+8d2iQ/jA2ZpQygzfbPFdW6Pxka7y2sSF+8vCX4qW1TaWIM2CLucb3WWeEWL3Byf2x/JjXL61tijef+EL88nc/He/94TVx6atL43DPUGWeeyxzu59d8kDZ6OGNXdYHnocZuBn41Gqz+5nBkPvkTUeMBWuNZ+H8uB12COkj7KV1EpuYHPI1oLTOyKydwS/neJtldCjdO4W5vyMqvieAMDsVPLu+C3hxX3UAWL8WdBkAWrHs71xZybXj9WP9ffHC1N2VXJushM3qobj5QfkaZDnM4Tw254blEglblm6IN5/4Qgmb2mPGmJlpyobRoID+bW1cX3IQAXiHe4ZKuRYMpY0V98N45tcMJna3TcbTN24qDFEGGjwTAMjzHN7k+eQhYoRcksUharMzxwdWxBuP3hKXv3dlvPHoLfHmkzfFTx7+Upwdb4/jAysqADAze/x/rL8vfvl7vx6v339b2QzzUQDfuZT0Y1vTuspZwHwX2RgUAFx2tqyJ/Z0ry72dX8XzXT4kn5sLQ2wwS1u8YSWDjcy6Mg89313Umb7mTR1mknl/R8vcebk/emBJfPBnV8YHO2+Jd377ujg/2VpqSXqjTh4HOyUeZz975BOPlrVAbb83n7ypHK3HRhKz88xhSh6ZbX9tY0MJU1uWXt+ZDTWwNhj2Mz2eXmOAbINfZOfX7FSYZd7fubKsjQzivEbcF8uAKEDuI/fAAfB6tVN7erSzPIv7W28A5ph3TnXxfQxerWfs5P3jPcN1ALiIrzoArF8LunIhaNiFI72D8fzqe0qICEW4s2VNnBruroQXrfjMxhh42VjlEI2NqlkCQMD2ZdPzTiDASFH41c8yi8NnHQIyC+eQjY0geXmnhrvjzFjHPENvgGOWwbUCXXuPfhho5Pw1wAjsioGogVEGzQYbNmwG7rPNc7sUTw71xCvr74z3/vCaeO/QXfHBn1wVr953e5wc6pm3a9nG0EB/R8tUnBjsjbef+lwl5xJZGsAb+DMmR3oHi2z8ebOsZj9fvrcxjvX3VcDB1sb1MXnNYyXHMwM+ZOf28z5ydEiZtnjO+TXaSL4njkJmnwCbhMonr3msyMfMzpHewTg51BM/fvDLcfkHH4/3jrTEL3/v1+P8ZGsl1OtSJMwv5hSAyGFqACtrlVSFfR1jpUYhzHU+QQWW1+10WNwOWj4Bw6FjO3MG1QbegEhyS7c2fpjTy+dom4GkgVnWMQZErNs8Rtk5MoP5UWkJrsfJs/a0T8Sp4e4yrpn5nG2ulss5NdxdYYQ9VwwSzYA6pzg7GAaGz3zxkfjbO1fXAeAivuoAsH4t6HIO4LamdbGvYyyO9A7Gzzb9Zrz91OcqxWVRjLAG2Tvlfyu4nGtljxrFidKGJaq1sxDF6dAfYBXA8NLapoqCxNgZVJhtw4DCyMEYwCBsWbohDvcMxYU1LXF8YEUF6LndmaGhbz4SjjY5xOxyFQa3z3zxkTjSO1hAj+VsAAgI5xkYDzZ22ODBKB3pHYxLG+6I9/7ok/HWT78Zl2dviJ9t+s04Ndwde5ePz8thdB/dd/LwCAW7nIsNKobdTAftMFB2/pgB797l4/GjB5bETx+7ueSYMuaeXzb+zK/MRpqJ2bJ0rlwLsgSI0A+3nf+P9g1U7ufwn9lu2kIdTTOVzLc3n7wpfvm7n47nV/9/7L17bNbnle9rVRrSNC1DMxA1KSXKrUExcWMbeLGNX1/w7bXxBWzZBuc4xwgaSkNTNemkQW3Tzmg61Wgrmu5qFHUze7p1mG4NndnHMz4y8hy2h+KNZSNDsRkbau4Fwi2lJBASAp1Z5w/r+/D5Lf84p9vS/iPHv0eybL/v7/I867ms7/qu9axnhf3mxS/ata2P2aWubButrLDB4vppcXkEMuwPMmhkTnvy1tnh6nI7Wpe2weL68Jk3DGigqP3ada55wO/Zr6oHAR7XChqDvMYbZ5yTmmP3Oq5PhhjbKrnsLWyy/SW1NlDUaJP1xRH50YBhfeie5TXcWU/jVODucHW5nV+fO21+0iAkW+d3Zvt3xslLchCYJxD0/Z3EAM7ukgDApMyocBewFqqD5dV2ZeNiu/7NR2y8psyG03URBeIXZYI6KXK/qOk6gREunIw1ilsUubB6dxtj7XiNngvQigYAACAASURBVHmgrCbCNKmNzE+nz/U/4666c6d28uo0DbkXvRJTHQV2pFzE6AmACADRsie4pruJ7ljWU21hjkLJ3MtCYETu3ZHSjE3WF9uVjYvt5rcX2I3XP2c3Xv+cHaqoCrsvqYhYP8mU7I/AH/uY7i0+hwqQ75B7lopdoEtML9N07MieCkWQK5mghPWnYUJWikwvgQdZILqvV96/KZIWhOOQxoWYK4YgqH9GSjN2rj0vMHIjpRkbq1plw+k6m6wvtqN1aTtcXR52ZysGkGNLf2vsMtEzfxRDOF5TFowIgi+6j33/Emz25K0Lc587WtnXGnOcl2o/ZUSgSEaOY5PrQxzgpDxoNOmdR2pL7Oa3F9j59bk2kSmNtI3AnOy6jACCXK5b+ltjYvviqVOOJuuL7XB1eeT5HpgyfINjmnKgvMno6RpmYPBjmuPwZzmtCQCcxSUBgEmZUWEMYE/euqA8htN1Nl5TZoPF9YHJ8m4TKgoqJs8seFcLQR3BANkMsl10K3FxlqIQADnblh9hn5iyhQwElXjTZ16KKG+vfMRO6TeVJpVab35bUN5a9MmmiWXUtX3LWm2wuD6S+88v7lKuXoH568XSqs5M5iz2QLF0A0WNdqCsJsSBHWsosuONhTaUXh0BWjwaTX27I/tuGo++Za1hxypBnhS5PotTpn4MePe6ABU3cnglScUv+WrTyc6czgDY+UwfP6V6fHnB16blcKS86YqMY3o1xrYv3hjJQ6l665nD6brwHMlP4H1PwZrAwAo8qQ8lD8mTciNI6smbStcyWlkRdhIzDlVy4/wVqBEzqbZKFno/DRg/tyk7z0jqM9WDLnsxbQSvPoenzg7mmiJ5MKykO7fDjjUU2Xvf+IKNVlaE57GvOHc5FigX3SOGWu3UPNVcGq8pCyDdM3ty03Nu+/dynSIYpvFCA1FzkKCRMksYwNldEgCYlBkVngTCBUkKROCPixdzeclC5aHoUnJiBqVAtIASWNBi1rVkDARoGINI5cXjrAjSuHATkHCh13dayOnGEvhTnjQutgSl+k5MmEC0AAxZOMlVMj1YXh2JoaTrSL/JMNE1R6ZT1xCkDKfrIqBQsutb1hpSuoyUZkJ6D208EIilkqJLlvUUYGD/Sjb9qWYbTtfZybUrIn0tOfG0GQISgn31PZW5xqGeqWTG6tsDZTUR8KNrCBQ8Ayj3HJ+psUg578yZChM43lgYAJxkofF64fmccA42czT6tmnesJ4KM2C/6f1KXaPn0eUtALxvZUMA8B700TAgiCIbprOAyYLT+PAsGuWpz2jEeGbMs2+aywTW3gjUnPMsIJ+7M6czbK7aX1I7bdONNxr4PAJejjMCzm0LtwaZq+6UH8GfB50aY96IpftaY9DXiSwf+5rvlOGRnAQyu0sCAJMyoyIA+N/y7h6zJoWiBVtKXEqZSk2KkdbunoI1gd2im0bX6NxdAUqewhEH3PS9d8kQuDGVA8EY3XRU8GI6tZgTXHBzh2ShZ+8pWBN7xJgWcNX5YHl1eJ7f5CK5KvkwAaXaz40QUshK0qzP9MyevHUhJ2Ecw0KZqK5D6dXhHrJWZFX1fPaP+lFtVz18YHpv/lSak2MNRXaooiqkm9EzGNgv+dMVTFe2V/yeiSN7wj4n40Mw48GD2tyfarb3tz1kxxsLI+OCjOFIaSaizCk3Mncc7wQ0HlhynAkoCOh5ZoqhChpbQ+nVdrC8etp4V/towBE0SGYEkhrnBHgEk5xLrDfHlmImGYtIORDkeWaO488DXMbQSkaeEfXv4XzXM3l8HoE9x4Ovlwwr9i+fr+9pyOh7soPbFm6N7HSn7NQOGbtkwtV+D2jVR/2p5gQAzvKSAMCkzKiQASQrwxQqE5nSyCYDLXJSWASCWvwn64sj7ksqFrEdUg5c8JkXj4s8XUpk3qQ4qViYx9AzE56BIHuh9qjdZOCkePeX1Nr1bz4SACpPfSAwkyIkoNQ7CUgkb4K/vYVNkU0VOi1EgNWzpWQ7KD+yCGJ0yHwS/In5IThQ35FZJVj2MpLiY148PWeyvtiubn4qAgi4IYZu5H0rGyJJm8nS6Jq4UAPVlXUmeOcYIwvTkzfFYHv2hUy1rpEiFnMnl7927tIw8GPfg5mevLtsMZk//fB/xaoRfByuLg+74H2fEZBwl2xc/j4ZFxwzBKB6rz73uSLZbgEsxcKSxfLAiS5sGnd69pnWpTaRKbXdqZZp6Zr4oxAIgjuNZW8Y+vrQeNCawz4km6l2eZe35E2mjwaY+l/y6E81T0uGTY+H5DlZX2zHGopiUw35uiV5AGd3SQBgUmZUBAB78hvs6uanbLK+eFpeq8sbnrGb350f3IS0mqlEpVh0pi8XKq9M6FrzCkyLIwGLWBEtegQMsrR78taF2Da5V6lQdmR3hZ2kVIKemSDzwZisOKVHpUS3ThzbQcUvcEJg4uPQBFLIcPSnmm1/Sa2dblkeXLB0tZO9k1zIKNBtrrbQrUpwyLqRnWG/SV5UsvxhH13d/JSN15TZQFFjyOtHUOL7Ra43An/P8EiuArEMwJe8/HPJ3Ekhk20hgPBgm/0h+ZLZ1efMPae/VXfOGQJ6jh/VT4aH5E/QyP5lvzAcgGwgGUTVbd/KBjveWBhYeW7QomFFA8YDVMnJJ07mJiCNMW4ok9x5VKDqp7l8uLo8wkATLAmMHq4uj+yO95vKuP7E9bHGeZybmuwgWVa64T241ZGSvJdj2INFAU/VVe3/4HsP2od/NjeykY3GJg2x5Czg2V0SAJiUGRUBwH9ekbEbrz1sF19YEtnVKUv0+jcfsbGqVREXoxY9pnohq0B3BpkHAi0COjI7XlGKxRCAYRoMXTNQ1GgXns+xD773YDjlgK61OPZAAICuLv34I6p4ZBOBgX4IDNUWujQFVAhaqBw9+6Q6CoRKCZ1ty7dbP/y0DRQ1RhgPH7vHPvJKlKwmZcj66Vq1gUwE3bdKR6NNNJL5zpzOAOa93I7UlgQmaaQ0EwGbBM1sA1O0SM4EJFLQYrPE/rFvGEcngKn3kC3sW9YaFK8HDnpG3Jj68oKvhXpIaVNZM7RC8qO8Oa5oQLF/BG41znyiY4K4Hdldgd0kiDjVnLLhdJ1deD4ntJsAgyDbb+5im9RvnD/bF2+MMN26lsnL1Qc0BgnOB4vr7UhtyTRwq3dwBzSBuTdOtSGEaw3HFj0dPNGIBgGBGw1Bykv9SE8Cxy5BpQeauscD1sn6YjvXnhdxzWtMSHaKDU12Ac/ukgDApMyo0AWs9BQCHHSzHiyvDhsLyMQR4IgB0DFuBDOymJm7js8j4NL3BARc4L3C0/v3l9TaO5uettv9T9iN1x4OCZy16DPeToCCCy43B+h7nxJG72ZMoVeI+rxv2VQy6aN16ch7pUwJXKTQqUwZa0U2SSxgT95dV7MUngdbfJZcaWRdqaCoyPTDTTtinqhgJRf1k0AoFR3rR4AhGWnMcWx5tzhZGAEpGQIDRY02WFwfdjITgKldZF7I1qi/9V4yMWS0fFyb5Mh8cQKVZF01jjxbqv7gmOS40Hw4XF0ecfWr7noWx57GEg0pjWUx8nL1/+bFL0bYLPUFk3n74xg9q8uNEZ6R8oCF84MMu67xrOfVLU/YWNWqSEopXf/mk5vtUEWVvbPp6YjR5sey+owMn8Bs3Jxhn6rdZOckb4YQEOjTCOZ4ImtJ+cmgYb9yjujUFd/vWls5VhMGcHaXBAB+zMobb7xhWVlZkZ+nn346fP/hhx/ali1b7MEHH7QHHnjA1q5da5cuXYo849e//rXV1tba/fffbwsWLLBXX33V7ty58z9VD54EIkWps2GpOAleqDx78qZONSC7Q9ePXFKeMZCComKVQtGiKYaLeee0gEvxkpnozW+z0y3L7eqWJ+zyhmdstLLC+lPNwSXjFcW59rxIgLhXIFR0Pjhd13JDCAEbgQGDvD1QJKsopSCXtxgqslR6l1KGeDZSioonSHim1YNPKnHvhtIPd62O15SFthDMUbl7xopGA5kPKUGNoZHSzLSj0Fhnylw7X7URYqCo0faX1Iaj+8TocBezxg5BHcegwh/IiBFMsf92p1rCCTWMU/P9RQNHsXx6lowMAmLJbbC4PsLaStbt87ZGjrKji5lzVe/mc7VLlqyXfwfHt8YugZD6WnLROCDzxTFHZkz3CZAK/BKoqR84dgkuu3OnTkQ50VQQAWDc/UvjUf3u54jkKbaPIFNt9GEPYrQlCx2v6FlhziUydWwnDY4d2V1hvuskGRmONApkAJM13JGduIBne0kA4MesvPHGG5adnW0XL14MP++88074fvPmzfaFL3zB+vv77cCBA7ZixQorLCwM3//ud7+zJUuWWEVFhR06dMh27dpl8+fPt9dff/1/qh5kAHvzp3LZnV+fa2fb8kO8HJkOKXZ9rgWYik4uIAIzLaxaSMnEyCLnQu/dLWTHPLChIhlKr7ZDFVU2nK4LOQz9oiwmRO5uKQO6OFlvvV+nEzA1jJSrZ5uorPjbMyNkAdSeofTqiGJWnT2LqXeJSSLzEAecpEQIygh+5YbWubxU9nE5yAaKGu3dry8KZ0MTSLA9rA9j6AjI6a5VHjsxuHLPqo5KW7OnYI0dqqiyiUypHa1L23hNmY1VrbKR0owNpVdHmBMyXKwnx5cHNATqqpvcr1LmbFdv/t0k6HL1CqSR9WJ/9eSts/e3PWTXv/mIXerKjjCFPn2M+sqDewI2jg89329E8gYPWUB9z3ACyonPosGj99DAIrDifPXgWvUVsPdjheCMY55jS2OILDbbTJaxfd7WyKYoGmYEvqOVFXapK9tGSjMRJpuG4OHq8pAWiOMmDgRy/dE1Plm66q0QGhof7B8CwO7cjmQX8CwvCQD8mJU33njDvvSlL8V+9+6779of/MEf2N///d+Hz44ePWpZWVk2NDRkZma7du2yT3ziExFW8K233rK5c+faRx999HvXg0fBacHVOaU+ZYJnHag8qdD98VyM29MZqgSHjOPh9z4IXYrKu4Dp3qPCEyDkotk+b2uol3ZuUrl4txoteA8c9F6yblRcAs0CBdsXbww7fAksVWcyGAw41zsJ4igfMq1qp/qHSpFMCFlLsWlsC5Wh+pdMjcbJh3821y48nxOpk3e/qe1kJgludPyfZ5nffHJz5OxbAROl8TlYXm0TmVI73bLcLr6wxC48n2OnW5bb4ery4A4m+6UTWbjJiEwsDRSyaQTcAoCeDeY8IAAgC6q6TGRK7URTQWiPTpUQ4+fZRhpdeofGiAd+aiP7jkCDhgyfr+fy9BnJhyCKhiDjWNnXY1Wr7ELns5H4X/Uzx6iMEQIxgXT/vQe83qjUmCULJ9YtDohr/Ot+b4T25K2zU80pu/N/Phjc8HTj+jVMc4lyEEjm+PWGkeTDdYXjiODPj1k+JwGAs7skAPBjVt544w371Kc+ZQ8//LA99thjtn79evv1r39tZmb9/f2WlZVl165di9yzaNEie/PNN83M7Dvf+c40AHnq1CnLysqyX/7yl793PQgAuYB6y5WxK/xN14QUPC3TnryppMS/felxO1JbElFgfoGkS1iLG129+pysQnfu3aPWCMxU/4GixnDAve4hk8PNF3Hsg4/t8WwilS8Vo0Cv2qM6i3Eko0UlTBA1nK4LSYXljvI5BQnOBPhUfz2fgEdtoaykHJkyQ4CSCkf9Rdem3K3aNLG3sCmSuNsDbDLAHlDHAXG5R1UXvW/fyoaw4/vqlifs9ltz7PaP59i7Lz9qxxqKArgnk8o+8nGs3GTDOEb1tWezCK7EHvOMYsl+T8EaO7l2hd3+8RzbUzCVa1OpW1gHjQeFAKhOZGsFXMi0EygQ/ChfIecUZcv6c26T6eIc5hjQc8ieSVajlRV2vLEw4r7XtRwD7HvP5HvDRvdILho7TMRN965nO7lWcZz5cUlgPFKasVt//hk7XF1u/almO95YGGTGfmH7NN8J3n27CNq8weXnpP7nusd+oLGVnAQyu0sCAD9mZdeuXfbzn//cxsbGrK+vzwoKCmzRokV2/fp1+9nPfmZz5syZds+yZcvsj//4j83MbNOmTVZVVRX5/ubNm5aVlWW7du2653tv3bpl7733Xvg5d+5ciAH0ipHKg1YsFzTGsMjilpLRYjmUXm1HakvsysbFdqiiKrAiBIFiDqhUaPGSHfTglKBV9dOiOVDUGALfycyIQdH7evLuJlPWQi/wKXDoA8jpMhQIlVKi+0r1EgM4XlNmk/XF4ZkEQ1L8fcumUmaQFfSuJb+RgIqejKT6kW4qz7TwHilTAmOCBD6XCm0ovdo++N6DdqZ1aYRlIbjl/2RfJFfGg5KVo+uzJ29qQ8qBsho707rUrr+60D6YKLfrN75vH3z/s3aqOWW/efGL4aQTyoeGhN5N5osMnwcRGi9yQ09kSm1PwRobraywC53P2rsvP2r7VjaE8SaWeaQ0Y8PpugjQpVuT4JTMVBxY4mfcvOHrp3GneqhPxYh7QE7wQ/ZeY1nP1BjkGOHaMFa1yg6WV4e2cD5zvonZm8iUBsBNQ1KGDzf0aLxzHBGMk/FWnRRawDpyLZBsCKLVJxwTPq5ztLIiAjj1bHlNvIuaY4nM8u7U1MlAYrq1MY5y9TL269L2xRvt777UkgDAWVwSAPgxL9euXbO5c+faX//1X/8vBYBxm090FjBZBC5eVPJ0tZDd8i4Rb3VPZErtvW98IQAfKlYtYjyyi5YuwaR3/ZAdYPJkKrhDFVU2VrUqAn7IJhCceMubypIxX1z0+Z2C06lg9LdOSDnWUGRH69KBpdIir7+pwHbmTJ2Hqs0JPH6tO3dqd6eS7np2SrKiK199LMDqlYqeISaRz9J3cul55qg7t8Mm64vtdMvyiKIWUB5O14WdjZIvZUtQ5Flf1U+AQDuhj9SW2OUNz9itP/+MffTmJ+3a1sdCHkgl0dW4Ga2ssA++/1k7XF0e3iuG8XTL8nDurBS52t23rDXiBpT8T65dEdzQt/78M3bjtYdt38oGG07XBZmoTewfD2wIqHgNAbtn3iRbAVbOEbJIZLo0ZshAeWONzCfZuLgYUIIQtYMbk/gu/WieipnfW9gUxrU2ffmYWM1DPpNyigPtXK+894LrlWc7CZy5hvG3jFltVCETyI0enqHVukngqnko+eu93sDSEX/eENQ7kkTQs7skAPD/B2Xp0qX2rW9963+pC/heDODPcloj7A5dL1q4/KIoBSH2gO5F70Lrzu0IqUsIsrTYkY0SsCEY5CJOgEbGkXVjiorhdF1gGg6WV0dYEypVshViCD3TQHaRIFFA40zrUrv+zUfs4gtLwnu4aCuuTSkuyEhQJnT5SDZyHVKhMK8dlbXYBSoT7VSVi5bsCNmn3vy7SarZ3h3ZXZHYTzK4fI/qol3YYnSubFxsV7c8EfqALBzZGTJdaguNEMlbIHC8pszOr8+18+tz7VRzyg5XlwcmhYzQ7lRL2GAjGcqlfG3rY+F8ZJ4iQpZQ15Mdo/IWONdY+vKCr0UYZs6FbQu3hvx8VPScZ3oHGSiBgKH0ajvWUGS9+W12qSs7Es+qsU9mjICRc4rzmGCOmxMYVkDgxzmhMUpWijn2BNJ689vs7Y7nwsYKghkCTsrA78Rlfcl80zAlgNR7WD/u2iX7yPqrXpInwa/3gnAeEmAT+DHEgn25beHWaTu+aYx6hpxtlEGVuIBnd0kA4Me83Lhxwz772c/aj370o7AJ5B/+4R/C97/61a9iN4Fcvnw5XPOTn/zE5s6da7du3fq938sYQAESLUzaMOEXVzIJWui9a08LlBZHbdzwbkBayIxv07PJ8hH40F0joOM3YXDBV7D9zW8vsP0ltRGly1g3KhkqODKBZDSk6LVQ7ylYY5e6su1sW35skP5EpjTSbu74o7JiDB2Bt3cv0T1PACnFJlAiAMi2SHET4JH5bZ83PQdcb35bUN5iF8l4EOjoHYPF9TZeU2a3f3Sf3fmnh8IxgJS3fpNBoXtWClSuOcYCDqVX23hNmR2tS9vB8mobKc0E1lRMk2TAtpBh80m0yaCyLdoBLEAjIM24UgJZuk4pd/2t78kykZni+cgKQRgoarRbf/GAnW3Lj7B9mndMe0N3K+cWjSWNDfWl2i5GVP+TFfaglm5jfhYHxrRBhEYXGV9dL2+BxgCNKG5GIetPF66Aedx6QgNRfdafarbxmjJrn7c1GDseKDNkg+OFBqoMYqaskjy5rvC+0cqKcBY71wyOQb2f64nkkgDA2V0SAPgxK6+88or94he/sNOnT9vg4KBVVFTY/Pnz7cqVK2Y2lQZm0aJF9i//8i924MABKygosIKCgnC/0sBUVVXZ6Oio9fX12YIFC2acBuan2e1h0aSLh6BNwIPMmJQKdxkKfNC9QnZNi7YWNcbS8LlkEf3mErIwnmWhEmIi2bGqVfabF78Y4qAIbqlEtXCrbqqvd1WSrWPb+pa12qGKqmmA2FvyerbOOxVDRRCwI7srkoNwtLLCBovrI8qNwEvKnkl1qaA9k0Kwpj7xipRMrO9HKThd59lD5VDsW9ZqR+vSdryxMLBz3BCja8mA0NXNeETF4AmA9ua3BbAnho9MnGQixRzH3lFGaoP6iCdrUPGyTgR+nvnyLDPBTpx7ksyQFL6O0JM8eNKOD8UgG8v5syO7K8I6cuxwDu0pWBMAIceK5oMHemSEmYia83sovTq4x+mCVR8SEEk2PCuY8iKbzbWFrHLc2Oda5gErXf5xDCnlIUOP84GsHfuB840xmwyj0PihvHrz22ywuD7ktaTRSCCv9iYAcHaXBAB+zEpbW5s9/PDDNmfOHPv85z9vbW1tduLEifC9EkF/9rOftU996lO2Zs0au3jxYuQZZ86csUwmY/fff7/Nnz/fXnnllRknglYeQC10jKnjwuwX0Z05nYER8qBNCoJuFh8L5f/m86WwCVZoeVNxaUHU4ukXYylmgS2BCylugg8pVCoOKjm2IY5R687tCKwTAZ/cdFL0ZNwGi+ttrGqVDaVXT4tnojuuO7cjBMgfKKuJsD0CDlTu3kVOpU8Xk4A926tnkYkgm6HnS46sq2KbyJR6VqM7tyOwdQQUytXm+4EgnS5FjVntQCY4I7giyFACZ/2wX9ivAlZ6nnLV7S1ssoGiRtu3siGAMRpJUuQEWOwXuiQJSnUdwxZONBVYf6rZhtN1kbgygUSCHgIXsuWcJ/pO45j9TcCq5xBQE1xxjqmvuaFDz+bpNQJ1Po5V92qusq9YRxpG/IxzlEbNtoVbIwYrXbSqO/t9R3aXNX3mpQjA6s2fOglJayKBmAdmrCPZXjLQYhaZa5N1VjzkZH2xXdm4OIRM+Hms+vUta7VXHnkxAYCzuCQAMCkzKgSASrCrRMpyL1ChUMG8+eTm4Or0FrMy/RN00DLWYibWSgugFA3jbTwTdS8QSWZRC/rh6vKIgpAyI5uj77Qgq92eDSWA8QyiZym46HfndgRQQkUhUDqUXm1H69J2+6059u7XF4XNEnw/f3fndthQenXYzEAFRNeWB19UImQyvQKkLAXOKCeC6jiFRPDI77nJQHUQ43SqOWV9y1rtYHl1hH0ma0aZqc4CEnL5sq/I+viYVrK2cYyu5EA2Su+T+3l/Sa0Np+vsQFmN7S+pDeOCconLHUdXJOWq6weL6220ssI++stPhmuY+5LPk5ueY8OzunxnXL9zHqjth6vLAwO6p2CNHaktCWmcPLj0gJn9r/997k6CMM1pyoSgiOy1Z9skB13Ls8r9OFT7/Xd0O3NN0joxkSm122/NsYsvLLHti6diWwW81N/3YtM1JylvtoGsM8Hh3sIm+82LX7TbP7ovGAIcJ3qm2pAwgLO7JAAwKTMqAoA9+VPpKo41FNnpluV2pLYkwuxRIXOh40IqZUKmg8DC71TVD4+Y0iLJHbJa4KlUufhTAWqTApkfgkeCnX0rGyJB/Vqs1SYpTQI5tqc3vy0cR6VF2QMVAUbuxCUY2lOwxvYWNtnxxkK7808P2Z2//ZQdri4PGzTIEpGt6FvWaufX59rRunQAGcwlRwAkhoVsKp9NGZJF1PviEh/ze33Xm3/3GD/vKuZYkML0OQ0Hi+vD93TPEtBK8fq+4PV0oxGQ8Kg2spvqN8mAMa4CAgNFjdafarbB4nrbt7LBxqpW2WhlhR2uLrdDFVV2oKwmsI/qd8rKgxgymXQFik0VmNE4olHB8dCb3xb612/c0G/OO6aK4ZwgCOIYFij/4PuftZvfnW8jpZl7tsX/L2BO4M/5SNZQ9eZpIANFjcGtHDeGCHgZVrG3sCnibmWoBMcDDQQyl925HYGx3F9SawfLq+1C57OR9fBeQNKzgly3PIMqVzDni+rQt6zVjtSW2NG6tA2n68L1PgWTnpUAwNldEgCYlBkVAcD/XjiVzuK3Lz1ut9+aYxc6nw3uUs8GaXHzp3r4/FT9qWa7tvWx4MLQvT71AcGgrttb2GTn1+eGOjA+zbt8+F791oJPJUfQurewyS50Pmsn164IikdsjxTMWNUqO9ZQNE0BaYH3m0Vo/VNBeaXgWZPu3A47WF5tp5pTdqyhKOSuE/gg4CLA0nP2FjbZ4epyu/ntBcFN6AGeFIzqRrDklYnaKKbLs3tkjAjo2Jce4Aj0Ekzzx7v62D4d7XauPc+O1qUjZ+fq3GCybcwXKADlZU8lStaYYFD1YUyWTiCZrC+2M61L7fz6XDu5doVNZEptOF0X8kDeyxhSPXyuPIU7aNzoc4FY/1ssKOVOQ4p/e8aV8vcAju2Xa304XWfn1+faiaaCaQnM2V9iQQl0FKsp2Xvgr36crC+2G689HAAgjR2NW7KBageNPW3Q0fvksqVRp99+/tHI2FOwxo7Wpe3yhmfs7Y7n7EhtSSTFlB+7WhvYLh9j69PoaB5yrKrNk/XFNlKaCfPfhwzQQ6L3JCeBzO6SAMCkzKgIAO5aXmfjNWV2dfNT9uGhg+3gNQAAIABJREFUQrvUlW0TmdIQ40TmTwumd/95V2V/qtkudD5rZ1qXRsCIFjzmQmPgvFwg17Y+ZjdeezgEv8sy1sLpWQyCMS6qcZ+PlGbs2tbH7LcvPR4UhY89mqwvtrGqVYGNoxVPVkdt0f10iZPB6smbSgzMDRpUctpRqvp4hk2gcKQ0E3mu6vru1xfZxReWhBhO767zAIMsBRWQZ8Ko1OLYDILz9nlbI7kKaTTwt55Pl7VkIIVHgLCnYI2daCqwC8/n2M3vzrdz7XlBTrtTLSHljAwPvZ/ufr2HOzn1uz/VHBhC1Y/pVAgCj9SW2Pn1ufbeN75g7297yN7Z9LSdXLvCxqpW2XC6LjC6Yow0NvQ/4+DUN3o32y/WkUzojuzobm4CcS9XPp/GEWNABUQ0TiQjbubQbmsZSQzZ6E8120BRo41WVgSDQX3AeefZ692pFtu3ssHOtuXbkdoSu7rliZA/02+w4HiQjBQHq89rH9gSYVNpjBFQktn3YFTj/UBZjZ1fn2u3dz9m72+b2rXuXbAEjJS//+F6QbfwvpUN0+Suukr2XE8197hBjYZCAgBnd0kAYFJmVAgAD5ZX24mmAnu747mgwKRsyEiIQZMyk6LxrkcyHHQbURHT5UG3SnduR2B9yGJwMSSjxGOYuIDSFalFXopLu+zEOhC4iQmQ4j5SWxJxKZElomtKQed0xwrU9eSts4svLAnpO7iQU85SUDrPliySd31JXv2pZjtUURUUC88c9gyklLPaPFDUGOopcKA2cuejZzYETvQOKUkpWfYVZcD6C6zeC8hISRPssl4aG3K/alwSOJ5cuyICughYOZYI6DnmNcaVJ/BYQ5Fd2/qY3fn5XPvg9l/Zh3821y6+sMSO1qXtaF065CZU8mjtciaT5Tcy0DAiWCGLFMfYcXyTmdZYUd+RBRWYFOtIYMbxRcaKjDTH+3hNmV3qyrZ3Nj1txxsLA1vG+UpGV2Nud6rFDpZX2zubng5xxDyPmuOVYRRiPwlCaeSR3abhQxZ7R3ZXOCqPn+k5B8ur7fz6XPvg+58Nrl8lfea6xj6R3Ai0yWJTprtTLSHlVlyfKiE2ZcVx4Q2p7tyOBADO8pIAwKTMqAgA/mP+VL60/SW1dri6PCx6VOxadMgUCITQGuZi55klKj0pOYEdLqaK/VGCVLmTtLDLGiYDqPu56HqmxLuRevKmcvNpUacbUc8U40PlJ6aGjIiObpOyImNBZSYWUMpKwEBtlmwvvrDELnVl28HyajtYXj1NyTAGScCzO7fDjtalbbK+OMJ66d2MIfObEQgKCZQJ0tmfuobyfPPJzVb7wJaIm5bA0ccd8r2M8fTjReBa6TNYf89u6n6BWzF0Q+nVoR56t2R+rj3Pzq/PDWBNCvhAWY0NFtfbUHp1iAU725Y/dfzcv5bYjbPr7NZfPGCXurJtrGpViBHULmG1lwqebB5ZVr1X90juHM9iJgkMCYAIfgkW9D69J07GMp4oc97P8Aida3yiqcA++g/3253/63P2zqanw4YFjmsCevaTjg5U7Kfq6OMVD1VUhQ03ZOlpJLC9/N57JWQU0J2r8avnKaTieGOhTWRKQ/3YdxxH/PHMOsE+P1Ndh9N1kf7XGNW1Sp0jNpjsPBnXBADO7pIAwKTMqMTlARwsrg8LjIBJHKii4lCMC5UTv6fLhIHnUoL9qWY725YfUXqeMSRrIsaHSWH9c7WI+nQLeoY+V6wTGQ9a7wLBAn1sO5WO6uWVrxSHZ3NONBWEtjJVhd7tQSHBia8j+2WgqNFONadC6gqyWewTJfqWUlXbhtKrI+ymFJLv4z0FayJpSATO9hSssZHSTOSZek5c/BUBCcEPWU4ydxovBKpye/oNLDIu9q1sCHXlOcNS5krBs6dgjR2qqIoYL5LJUHq1XXg+x47UltjbHc/Zze/Otw//bK5d3fJEOBZOu7c9O0mXPttOY0l1UjsYItGTty5iAPGcWhpF+iGYJGiRTBTWQNBFw0Dt5gYOpdlRW0ZKM3a6Zbl99JeftDv/ON8udWXbgbKa0Cf+XF4PiNTv6m/GrorhHU7X2fHGwggzyTHCPpIsyO4SABIAM2+pNzRk1DGdEOVDRt4bxvxMslM9fN9wrutvjvHhdJ0dayiyk2tX2GR9cchxKSNtpDRjh6vLbX9Jrf23vDUJAJzFJQGASZlR8QCQDB5dtN5NReVFwEaAR4DEhZApH7SRhM/kpgsu+FIq3nVCZozMCutCJrM79+4GFiqKM61LwyIsJcdYQ7lnCB6ouKVQvCJS27w7lad0MK0DWUNtvtlTsCacoEF3LN28VEyUjQCuZMFNMwLCBIZkRAQWBMC865Jt8qCOz/FjhqCS7ydooauRrlOxQ/4e9QU3DHg2iKwXxzgZOG5SYt0VCzdSmrGxqlV2cu0KO9uWb5P1xTZeUxbi4XQf40K1SYAsEMMVJE+9n6BeYIW5FtkPlAGNHTLEHB8EvjxCkPXSmCRIo2GlEIPD1eV2qjkVdqQrSTmZRqaA0Y5psnNcc2RA7cjuCmd4+9AMjgPe45PRezZO80Ft95u4BGpZd8ndG3uSBz/zbaLRpL5gUnH90BUvWQ8UNdrRurRdeD7Hrr+60H7z4hdtsr44xEMPp+vsRFOB3frhp+1SV7b93wU1CQCcxSUBgEmZUREA/I9PRRklMTpx4MAzYARtnmmg8vM718j0UBF7oEkmROCA7IUWfe6Q5W5AMoRauLXokhnzweb6UYoPsoNsnwe6BHlUCHTJ0pVDkEoGQd8zRo7MgRRK+7ytEQDmmcH9JbU2kSm1vYVNIfZISobv6c1vC+DHH8unfqALUj+T9cXheD29XzIgA0PQTEDo2SfKg8CAfUwWrCdvXWScMlaSAJ/v4HvU7zp2zYN5vV9AWjkAD1VU2WhlhR0oqwkJrbkxxbNDBAue3SNI0T19y1pDnj/KST8EujSw9H6COAIovY8xqOoLP5ZZN4UQSJbbFm61M61Lwwks3MHrAZnkfbpl+bQNIuwXzZM9BWvswz+dZ6eaU5G1gIBPz+aGJ7LObCPdtt5w0HzSe70XgoCTjD3/914HykzvHyhqtAvP50yrK41i1W3fygabrC+2q1uesJuTNXbj9c/Z8cZCG0qvtr5lrba/pNZOrl1hd/7LffbRX37S/nthdQIAZ3FJAGBSZlQEAP/T4o6gOHmKg4CPFjj/27vqdmR3BWBB9kMgkDvtqEzIpOl5BHFaGBkz5ZUmmTGCPYJSvUdtoyUvhUBg6ZlIz1JIeZDBIdugzQ9D6dU2UpqJuMXiFMZwui4868sLvhZhKj3bwCO0WGcyGGqPdmr+9qXHQz33FjaFhN1kXdk2gYjdqRa7vOGZEB4g+XrgLvedZ5X0LI0FKnHvFmO/SnlyV6t/HoGnQITqxZhKAncykDuyp04GkfuaG0w0PsXmyf2sDUTq14GixhCTRfchxxDbqLHPdjB3Hcep6kGQT2BJQEMgRzeuPzGEoJ9AWeNF84xsPcc5NycwtyCBFw1DfceNJgRR+s2sA9rtzjaSNY1j4byrViw5DUVvRJKxp/xoINDw4nV6n06u8X1CY03PU2oa1YPjgAD4WEORXerKtve3PWRXNi62Yw1FIb5038oGG62sCJkKevIbEgA4i0sCAJMyoyIA+LOc1oibMI614ALmGTmyO1ocqZy9Inz364si7lS/qFKB6T06Lo0KmUBUbAAVoD73QIks1s6cu/FKTCUi5eLdnGKKqHDoXvRg8WB5tR1vLAw5/jyT4RkOurC4ocHHkalOkgWVMZP/qm0TmVKbyJQGNyX7jTKPi7fStXsLm2wiUxoS5IoVE2tI4C4l79ligRvGRrFd+t+zOPxeIJIsjZ4vkEE3Ot1taqf+luGjflB/021H0Nafag5gXmBPfSl5kN3x8iV4kyxovJB5JfCn25djjW1kvjk/hz0jSdbLs73exTpWtSrUXbG3BMjcmcv0Nd25HSFhNo0Tjnk9c3eqxa5sXDzNbR4XCsJ1QeOMYR8Eu97VS6Dr1x3GPXuwzjXF1yFujGn3+pWNi8PZ4DSKyOISdArkHqqoCon5TzWngjtc83GgqDHEZf4spzUBgLO4JAAwKTMqZAC9subCK2Xhj6Qi0NNCTjZMi7kHSD62i8qAzA+BAFlGKRvGBEpBcIEW+NFv1kOMEV1IPs8W4wap8MjKsC36TspIgdy3fvhp++B7D9rJtSsiQE11YZoSMUnjNWV2pLbEDpZXR3ZKShn1LWuNxFxRrnRpC+DQ9bYje+q4L7G1ZN3InpHlFOiSy29/Sa0drUvb6Zbldri63IbSqyPyocuSoERnw+oassxU8DQ0PPCNM04oR45j/a94Qypfsk9qo8CjvqebXqBSAGigqDHC8gio6zO1TQxjHOPpY225+YAMHcGw+l/9JMZY40kbcih7DwYF7lgv3iMgrTrpnGrNWZ50o/8PllfbybUr7FhDUYSh5hzWmCDI9Mw+DUDPFBPgMU6U7ZPsjzcWRoAw1zVdd+H5nEgfExyqnupDyZVg0K9hNAgVs8d+Y7sJvDkutA4cKKuxsapVIcTA95H6/6fZ7QkAnMUlAYBJmVHxLmCCMC60smbJePlF3LuhxNqJLaHipKKnQvI7UlUHxnTFxZERhHq3NAHbvRhOgga6ndhmMQ3eNcdgf7IbO3OmYnm0U/LmZI293fFc5Pg5giyykTqV5drWx+xM69Kwu1RglnWT7OJ2/FLBCtzo3ao728/Ad4EK309i3nbmTMUXnmgqsHdfftTOtC4N5/FyDCnmUn2jlDUCvOxjDxgE3DyD6FkkAVfPEBGMUflqLAoUMkZM9dL9PkTAg3z2BfvEhwpwLsUZUTRaOFc8YPRARjLxMbacEwzBINPP67kLuW9ZayRmlOOTcWsEzoPF9XaiqcBu/+g+u/7NR2y0siLIh/OWBoUfu34zEQ21uHmu3wz1GCyut8Hi+mlhDdyEo/Yr1RXXFrVVBi8NTzKtZBMZj8m+u7rlidCfDKXx8abduVMb09gvvfltIa+lB650M/fkrUsYwFleEgCYlBkV7gImYNJC6Y8e8wrJu9u4KPWnmqcOUv/xnLBRQKyD7iMAoELwCkOLpxZBshaqDxWrFBcVP8GSdwsTwKn+dGXGuYvopj1SWxIBZoxzOlRRZefX59qlrmw7WpcOljxZDLZ5KL3aTrcstzs/n2s3Tq21KxsXBxdc37JWW3n/pgAeWSe/45KAnArUs7FjVavs/PrciFz8M9TXZI64m/hUc8qubn4qpFAhuFFbCUh938kNyWO7pEiliFU3D2AYY0UQw7pzzApskjniuCZA9mBEYIVsMseMd10TPJAp9OwkAbDmggfFbCvdxvr+aF06bFiiQcX+8zJUOIDeSzZc7m0CdYIkGgrduR02WFw/tTHhJ3Ps4gtL7EBZTWjjaGVFGL8yemQsqC4yUigfrTtqh1hXfeY3hPUta7UTTQV252/uC6mIBMbZF735bTZaWRFhWQlA2RdaA3UN17m4+avfkhPd5BpjjPn07noacFwXufZ5AJ6cBTy7SwIAkzKjQgaQixUXGjIyHgiK5dPRcQQKu1MtNpEptfe3PWSnW5ZP282qhY+LLo/pIttEy53AYbymLCy6DNRnnakI6eKRkqNy17W8Vzvv6KbVAkxFyFg8KhDlxRtO14VNFKpfHNjYt7LBjjcW2vVXF9qHfzrPfvPiF+1oXToS70fZMQhfjBUTUbMv6VLUe8X2dOdOudQHihojshEQINNG4ExWUfFf6rP+VHPYOcu+J0NGl7beq7/pGiawUlvJFAoAcJOAB1s7c6bco3SX6h0CE3of+4QuQoFoz0DKzesNDw/U49hCyZpAIS72UXXgRoK9hU12qKLKTq5dEYl7ZOyb+l7/s64aj/tLau1UcyokXPbHnxGMkoFS3KNS5BypLQmArydvyuVPN7fGzcHy6kg8oWckz6/PnTZHyH7uzOm0Ly/4WmQ3eG9+mx2tS4fTXzyzpzowt6DmE93kfIcH8nGGlVg9XcdNTkdqSyJGDzcm0UAh8COo5FpGIEgw+oPHNyQAcBaXBAAmZUaFDCAZBi7EZGbIpBBAXNm42A5Xl0fu78lbZ4PF9TZaWRHOSPUWtGccyQhy0WRAvZS13sEjwPQZF3I9x7tSpCwFPAeL68MCrbpwR6eAjhZrMRmqX9+yqePCVFcFaiueR88kg6Igbirnnrx1Ib5usr7Y3t/2UIgd9EwFQRUVxtG6tPXkrbOxqlWRc3JVb+8iVt0m64ttsLjeLnQ+G6kTGVQqN44VskUCcjxPVz/cZeuBOvuPIIvtIxBkf6ie3AhE16r+pzuamwx0jWQkRpdxoQJmZITIfuvHu/iYuFnMZtx4JSPEzzVP9AyeXqPxJlcj5w3nKOeWUjwRYO0tbLKzbfmBFVRddqemji5Tm8gkqw+UAkZjgxt0OCYEGLWpQW1T//v0KjS0KAuCJxpvJ5oKIoCdXgOGW2iscBNG3AYcGiH+fQRvTZ95KfytlEsaO57VFXvOd3Hs+FhsGgAE0mQHk5NAZndJAGBSZlQEAH/w+IZpCyYXW4FAutCotBm0rkVOz+NZrrK2PeDpzu0IMVlSLHqeMt5rQZTSliLvW9ZqxxqKIqBR4IN19CkppOxp4XNh5/soC7p5pOy0aEthkkUS4JH8BF7FwnhApPoojmm8pmzaZhfJkUqCCktxhjdee9huvP65sImEjBnvFVjQu7XDl8yUlI76SWPBgzGBHV2r9whoeyaSrId3q3F3p2TAeguk+Wf5zUgcYzQw1G6fzkYgjbFlBFFkpAhs2H9qgxgwfc4xoPtp3BAwE2zq7wNlNWFzA+cenx03LyUfzu8DZTW2O9USWF+OC8mFwEjgWP2oHdC6Z0d2V0gtRNlrDosRVn+yzzT+VL+4+GKuTwRznKusS9z896BP41ltJujTtZqnPgk854b68HhjYcTIoseEBrAAIe/Vu9kGfy0NGz0zcQHP7pIAwKTMqDARNBeauKBrMjXe/SZLnYyDPqdyphLyyoZsIJmJgaJGu7b1schC6q/VKQ1SuN5dQ2BGEOrdZB6E3es7KQ7JQkDFKzOCkJ05nZFdqG8+uTkC7KScpBi9zCUrsS2qV1wMpsDlWNUqO1JbEgE8bB8VrWdvyeD4PqIRwD7XcwiMPJimS1SnQlAmDD1gX5EB8RtD6O7T577uipH0gfz6W3Xg7lXJgHLz/aKxzs1ABDb83xsa/EyAigyqvvMpgDxrSLChzwigaOSo7hyznLMEkWSgKG+5fdnveidZUsnzXHue3fnnRXa0Lh3u53xin3mQ7+vOn8Hi+jAXOd8lB9VnoKgxMJscJwTPfI/q6Fl+Lwt9zjFMsKa/uY6wz70B5xlPz4JzjeVYSADg7C4JAEzKjAoZQAEUf3oAF2Qt7lyAZPGTTSHwIZsjBkELImNdvJuLSo7/U8npGdwkoMWbCs0rB76DFrnAZNxmEykzAUeBSgIdMjhsCz8jMNGzJRevwKSkBPIIOAeL621nTqe1z7t7lBQVsZ6l6/etbAjP3VOwxmof2BJRRALHdOkRzLI9BPJUqFJ4HAME41L2HgRJ7mQA9b7u3LtuY44HggwaGF6J+zoqVotj1Y9LxobqGczxx3HBcbczZ2rnN2NBqbAJrmTUqB0Hy6tt38oG25nTaYery+32j+6LzAGBFD2Lu7HjGEmNO8ZacgOLZ5/5bN8/O3M6baCoMRK/RtAjAM4xw7F+sLzaLnQ+a/tWNkwLQfAsLfuPP/4EmpHSjN387vzIuyUjxqX25rfZ/pLa8LkHb16Geo4fNwTaBG363O+YppHGNcK31wNK/8N5pusHihojcyQBgLO7JAAwKTMqZACl0DwQIUAiC0AmhdYsWRgyEfqb1jCBgXerSCnp3Yql4ykLBB76TAuxD+ruW9ZqX17wtQg7SWUX9+MBb3duh13ofNYmMqU2VrUqwviw3R6IaJFnQLyXL0GCd1FKiaiNu1Mt4f1UWtysoTrI9aq66tQK9Z1nLLzC6s7tiNyvfryycXEI4lc7CADUbip2ARrdozg0/fiNQYzp0/jgWOFmBzJ6bAtBmN5Lw0MAmoBAMiPgPFBWE+lLz1Bx/PI6z+JwjPMZ+1Y22FB6dQS0axxz4403eCRTMqsEb5KhD9vwYIv/d+d2BLZ628KtNl5TZscbCyNtY931DjJsdOfuLWyaxrBxjHAMCpT7dDlx41pzfWfO3Z2+u1Mttr+k1obTddaTNxXbSLexB7cebJL19X3G8aUcmvda+7zRo2fSy8K6eGNYsiDDSUOUTHASAzi7SwIAkzKj4jeBaOEnM8b4FL/YcaHyzIGPU9Pv/SW1kXxxfoHvTzWHM1bpIt2ZMxU3dKiiKrKoUxHuKVhjp1uWhzp7V7YAQ2/+3ZMg6EYVs+KVAZXnkdoS219SG8m7J4VMRodKQJ8T2JAd0PPp6tMzGDtI4NCfarbD1eXh/zjmhYwbmaBjDUV2pnXptJQhVPB0X/lnij3avnijnW3LnzZePAgie8JNL+pTgRqyUZQFwQMNCjI6nkERY8Rd0goPoLK9lwucLJqevbewKQJG9V7OD4JO33bGJhKEqC1qD4G92sM0IpIJ7yMjKDDEneseyGh8+dhLAWXJj5us9E4aWZIrZRHX/wRqZMg8YKXrk6yZnk1AzzVGMjpcXW4XOp+1U82pANr1vZ7D+GAyyXq3N87IFGvMcPey5Ku6cC6NVa2yyfpi27eyIVJX9gHXUMqDhgPX1n0rG8Lu4jef3Jwkgp7lJQGASZlR8QwglR2Byr1+eJyWBz1aoP3CKbaA7lMG2B+tS9vN7863dzY9HeL6vAuECz5Zsv5Us7378qMRheHv80Hg/vm0/PV902deCu9gULwUr0AGXWq01glgqCx0reQugHGktiQ8g+4sulP1fvaV5MpzjikvMnJ0Z/G5AmhUOGTXJCcBlD0Fa+xC57N2pnWpnWpO2Y7srnBCiZ5NdyHBDdk9ggS6B8l0SOH7z7TBgEqd4E0/3hDQjwCM+obGgR/zbL9nw8Teia329ee45fvoZhbbo7HtAa0HVPrxrujdqZbIcX3aMMPQCNZdgJEGjxKQn2gqCCww2WKOEc4bgnWOTRqQBNkaYwKfkgeBOkGY5quSiu/I7rKR0oz15rfZqeaUffQ/nrFLXdlhPhHgaRzot8Cun1v0QhCgco2jvLkW6rfO7WU8p9rlj9NjpgXGFfp6eRC/ffHGxAU8y0sCAJMyo0IAGBfkTKvfsztvPrk5cpSUZ434LK+0qNy1KIsBG07X2TubnrbRyopwRigtYSr3kdLMtM9lFdMdRSWldjAWicH9jB3y4EvuZ+4a1WcEMUyDQVeQdk0KQKht3G3bk7fODpTV2N7CpvB93GYcKn4CCQFOnjjiz7dV3cZryqYBMw/0yDASLJAZ3L54Y8h1eKo5FQEKBP503wqU6H72F/tB/6vuTOdB44EuU6VxoWyYvkZ10UkgVPDsxx3ZXXaoosp68taF/HgE8pQxQRTBtme7dqdaQtysDAh9znHOOlAmulafMVWRxj7jRVU/z8bTcOLc0DN1ogbPOiYjS7cqP+O7vKFFNzHXBrk6Oe4I+LtzpzYM7S+pjbDW+q0xMZRebSOlGTvWUBQxCgiqvPHK53iAzzhf1pehLGQIWffe/DY725YfiZ/1QM6z0TRSCBY53nm96pi4gGd3SQBgUmZUuAmEsSZaZBiD4kEHLVbGV8majVtUCQjIGGgxlHLQJgSCNClxLb5+MdVCTcDlF0y6wng2Lt22AgFqM91bBCJkA7cvjiZfVp2ZXkJs2bGGokgKDD1HgESKUHJk/eMYJSoisW9UzHLpU6H05EXPse3OnYofVAJftVdxTvwR8OezvJucBoG+k6tQcZxxx8b5PiUDo/7tTzUHVy7bKRnG9amAGlkptYXuTgJbsteMcaNLmSBZY0Dy5nvIcvkdvXKv0nBSe8aqVkVc45onY1Wr7PqrC0PKEboWaTAQyPCdAoV6n4/9pFucLlnJj2BH7eEYZh/6TUpk82SoiYX17JaOIuTc4/1qK9lUgXDKmfcQVG1fvDEcwcYxyP7QXOnNbwt5Oyknylpy5BpC2bHNcTGeXCv9SSE07hga8OaTm+2VR15MAOAsLgkATMqMit8FTCVP0ETQxQVSSke/uQiSISAo8W4Wxs1Q4ZAt8gCDClrP9CBNCvna1sfCvaobd3TuyI4mf6bCYT09m0g2gEwF2T21S595poXAVc/Q8+QOlBLyefAEHlgvASDmdfOxfXHMHvvkcHV5eA7ZSvVLb35b2Mzi60+ALaChvlO+ueONhfbu1xfZ8cbCwCBLscl9yk0PjPXyOz71HVlg9pHGkOpGhd2Tty5yeoPqK9ChMazxSQDFtkqBe5aOLBFZ6568qdNeyPxJjnQH6m8fDzheU2aXN0y5OHW8IscTk28r9Q0NLI5FgnS1zW/M0dxiqiHODw9ACR45NiWTuBAMjk16HAiK+A49U2l9uGHHGxDeEOUa5+vu66kxqQ06cQDQA1EP/pkXkawmDVW6jdl2jcHhdJ29+/KjdnLtCjtQVhOYa137v/9RAgBnc0kAYFJmVAQA/+5LLbELpuJ+aD1z8RdAIQDi4s6FTGdz0u1EBaEFVxY8XYV6h+JpuKGCzA2fK2A3WlkRYYq8K4VsnVxJPk6KwEbtVn0JoAh6dC3/JiAhE6P3EvDKBUzFRlCgHbgCGAQa+psgVHLSpgsCAvab0n0QzO4tbArvItDV5hcBM8ayebe63n1t62P20f94xs625duegjVW+amvhDaxvpKj+nZ3qsWubn4qMIeUlQe0UuDt8+7mXZRMGPtHAEz2jQCJBgWNH7LDUvoaD7qf/SeZyLWqXapigwle9Z7xmrIw1rkB42B5dWSuap6SgSJAIbunuXih89mIcUJgR3mpjdsWbo300f6S2iA7tZlzivWLY8k03hjvp3nUPm9rBIyGjIwaAAAgAElEQVRKJuwXzumxqlXTYujIJHoGkkCShmR3bvSYvKH0ahutrLCJTKmdaCqwiUypDRbX21B69bS1RPXbkd0VOYdY/eO9IgTDTKXFtUvfHyirsVt/8YBNZEoj40SA8Wc5rQkAnMUlAYBJmVHhWcC0Zuk2oZuCiyddcF6Z7sy5m/Kk8lNfmaYQtLjTFcMYJS2IZAf3l9TaRKbUxmvKwgLrXc8Ep35B9TE1AmL8jidcqP1kpHQ/2Ry6frmDmu+Vy5KMjndZMt6IcUf6nu5kKXIPNKkUqEgIkDzboZ+jdemIwvTXE8wLMJON8cwPGSLFY+3M6bSD5dV2cu0KG6taFb5XrOfVLU9E3OJ8vp5JhkunM7CPdL12qpLpoyuWoILKnIaEBxqe9VG/9i27e+yf7iEw3ZHdFdySE5lSO78+N5yfrQ0zvflt4ThFnZhxrj0vcowfWSLJ3DNcfmMW27FvZYONVlbYaGWF7VvZEAEePpny7lRL2MTQndtho5UVAYjqb91Hg0B9RAAmmfu+9AYg56hnAfUsvw6xHzk3KCcapX6N03sJYnvz28LZxqeaU3Z5wzN2dcsTdqHz2XBcIuc9YzLZJs59MrFkXr3xwTAcyW53qsVGSjMRtpubV5JdwLO7JAAwKTMqAoA/y4keJ8WFW/FeXLy1EFEJECiQLaOF61lGz/JQYZGF6E8122R9sV3ZuNje2fS0HWsoCmf3yt2qRVWsVNyiz/eRQaRbSq5WglK6n8Xm0OKne1TuTMlG9ac7Vp+R9WQiWf7QNeblRVBDNyD7krKgsmcwveqk55Al1Gfn2vMiu3b3FjbZSGkmKCiBYSo0HtcnpabdsT4OUjIYraywo3Vpm8iU2mR9cQDqHBfsM4ElMYxqi97nxxP7NS54n+8goPfjhoCJLCfBGN3vewrW2P6SWnu74zm79RcP2EdvfjLsnj7eWGj7VjYEICxwSzaNDKRAB0MN6D73RpDkrVAMslB+rBFYDhbX22R9cQgLEBC5uuWJaW5N9rPq5V3DahtDCgiaxE6yTzSH/XiMC21gv7KvvSHFOcM6yGBSW8eqVtnFF5bY+9sesjv/9QF77xtfsFPNKTtYXh2Jj+Uc8rLn8zwDqPnB+alrZNhMZEojeSG9Yfbmk5uTTSCzvCQAMCkzKj4NDFkEb937RdgDDVquXPS1ENJ9pvvlVqJbjoycFOu+lQ02WV9s119daDe/vcCONRSFjSIEn3sK1tjxxsIII6l6USmRpdT/ZJbIHnx5wdemxQn5mB29zyd5ZuyZ3HdsP3ehaqMCd0oyFokyV92G03Uh1xmZv/Z5WyOuNsqVSoRtYb3o2iN7RoV7ecMz4dQLH5TvQRsZGSo6sijqc8ngNy9+0U40FdiJpoLwDAI81oegjsftqf/okiV4jAMIVNJxrJOulQueIEtgNI4NFPt2dcsT9tHQl+zOz+fapa5su7r5Kbv+zUciTB9j9QhWNKZkfEku+p917smbciFr5yzzIrKtBLy9+W0R+R1rKLI7P59rN787P6SEkQHkQSRj8QQEOd+ZXsgbTbyWrB77kSDVu67JFHsA7hPb0x0b9y59NpyusyO1JfbOpqftzn+eY3f+cb5df3WhnW3Lt8PV5ZHNO+wnyoXGA8cJ3zlaWTEN3Gld6s1vs3PtecEgo6FHtjRJAzO7SwIAkzKj4gGgFAUVIeOI6AYkyBJg1DUEPlyg9Z3iuLTokQXQYsgFuj/VbOM1ZXaiqcCONxbaeE2Z7VvZEFHcjBkU0OK5wHSxkD2ie9YzlwQuZDy4EHNBlwx8Lj0xZocqqiIMkkAImR61lwBJoEfv2Z1qsfZ5U+BZZ/0SwEu2VHC6hqCQ6VJUBzKjBDEEuFTAAgQCblT+lAE3TdBN6Bk2XSOQp++1cUfJr6V01dce5On0CTKxZProZtM1ZBEpT8lO7RbY487Vnrx1dn59rl3e8IydblluF57PCYBLshosrrezbfn225cet6tbnrBTzamQvy6OseUOZcrR96/mk+SyO9VihyqqbKxqVSQfIQ0xspZ8nj7fmdNpZ9vy7U7vI3bjtYdtf0ntNLDu2VMCSu7C5bXeQ8Dxx/4j46rnKiUNmTYajgS1nPME7zTiJDOy7Bo7ewub7EBZjZ1fn2vXX11o119daO9setpONBUEdyxDBQTa2I8EqzKUuGlKbdL4IUu4M2cqiTTZUs/Uai37weMbEgA4i0sCAJMyo0IA6ONm6L5k/A4VCa1/MSv6jC4gfz/BoXdFacfbUHr1NBdpf6o57KCksvSWNhUDlYBAh1y4WkC5cBOEEpCQNdEPwRsBBhWMfkYrK+y9b3whwnoxFo2uvD0Fa+xUc8rOtefZjuyuCBD88oKvBYWitmrnKuvF/5V7jmwFwZues7+k1obSq+1geXVQtOw3z0bq2Xou8xwqTpOpfOKUGAE2607wTIaWu3TJwJARkZGh8SJFS5aM9e/Jm8rzd7C82obSq20iU2oTmdLA5FEh96eabX9JbSQmTvU/25Zvp5pTEfCiTUxirA+WVwcXt06UYdJnuclpZOlvjp2h9OrgOu5b1moHympCPdUH7DsaGBwnTONCBlHA8mhdOoBUzhPWhQCeBoP6hrvZWZejdWn74HsP2nvf+EIAYJ6R1z37S2rt4gtL7HB1eSyT5plCGkUao2TP/DpHQ1KbrAaL6228pszOtecFV/1Y1SobLK4P6xgBrZ5DllPtFWAcKGq0sapVkThfyVbPGShqnGbgihnsyVsX3M/6LokBnN0lAYBJmVHxu4C1+PrFfPvijTaRKZ3m+iTDpO+42JLhkfLgwhsXxN6farb3tz1kJ9euCApAMTC0qKW4qNgU2zacrpvGNgnU+Z2zXoHoxATGCvEoLDEsZAI9M0q2jTul/ZFakq1kIVntyO6y442F9nbHcxHmSfUnQ8k60E1IVse7oBjbSKB/pLbErm5+yt7Z9LSNlGZCnCLBFetPRar6CBRRGetasrt0/XnGUUpRfaBdyIqR43jic/VuxgVSTnTT6X8yifpsOF0XlLzct735bSGH42hlhR2uLg/smq+HlLc2UhAgKMmyUosI7LFPyfRp7OtdquuHfzrPrmxcbCfXrojsupbMCTo0hjU+9RnngGcEVRe/CUXjh2yWxiDly3mlZwlQ9y1rtaN1abv9V3Ps3a8vCuyiz/tJhnGkNGOXNzxj4zVlkTnPdcR7E+JYR60dkhNBJ2WuMTScrgvGwUBRow2lVwfZch3Re+ia9/2pzWx3/uY+GyyujxiCBKCT9cXhFBc9l+uP2qy1LHEBz+6SAMCkzKgwD6AWSaXOEGMmcKNNF3GAw+/w0//KWaX7GOtHQON39g0UNQYFLFBI1yXdOR6EERiQmWRCZ94jFpAuGL2X1jld43wv3Veq35tPbg6xZ3o/ARmTVnvGQAwf26S8fmK/2Eb+T8ZyIlMamCW68f29Uu57CtbY5Q3P2J3/+oDd+Zv77NrWx0JKGMmJ4MKDVv6WTNmG7typc6CVgJpHt5G1IXNDBkyy5s5tz/rwKD7GlpJR5Pgji+0ZSgIhKX2yV5KtGD4aPGRW41gmAl26VPUdx5fmCIH1cLrOLnQ+GxhJgRZvIGjsaT7tW9kQgKCerdg+35cE+XTl+nhXycnL0M+LgaJGm6wvtmMNRTacrrP+VHOoE3PrsW76jJuMyJxxzWDbaeRwDtPA5ZzW57tTLTaUXh0AmDco/CYPvVvP8XHQrMPOnKn4VBla+owhE1pnL76wJIw5yp0GJoFysglkdpcEACZlRsWngVGcCncSkknTIkVQRcXh3UOegaLbVwsnrXMyVFr8RkozNla1KqSj8EqJz4pjBPyRT1x4aaEziF3P0N9iBQk6aeXLxUqWU7FpBDpkBSTvvmVTaTXYboJLHxdEkEkZ0/Xendthk/XFwQ3Ptnv2g27Myfpiu7b1MTu/Pje4Q5mgmP1MAEnwJTaK93h2rm/ZVNoU3bN98UY73lgYMToka4JJjSsyh4zf82wc+0o/ep4UNscD60l2mQCPLFdP3jobKc1E4tbItqo9ZIF87KPGoQdUNBD0v/L/+dADMdcMgdD7+1PNdrQubefa8+xce17IJeflqTHhgRLr5Ocd5y3Bu9qjtWGwuN4mMqV2dfNTduuHnw51oHdAf2tcc97Qu8A68Z00VDwgZD94w1V9IYA5kSm1j978ZMhTSXDHOUCm37OqnCd6pwf9Gpc0KsU+n1y7IgJc/fzn/NuR3ZWcBDLLSwIAkzKjQgBIF4RX8J6RILMiV5C+p3uRTAQXPCpmWr90C2rBO7l2hd36iwds38qGCDu0M6czgCyCUiWR5TM8YKMLuydvnZ1oKojUk4qIyo4xhHLn6t3Ke+jjwqR4KA+1czhdZ+M1ZQFAaFe0j5nSc9gH+kyfe3aPAIH15HPI/u3I7gp533j2q0DF/pLaaa5UD9z5PYGz6kLmUPXy8ZbsY441xatRmfrrCM642Yd9Treo+oSMon5zw0ccINR7x6pWTTMM9B13dJOZIlglAyw2jywkx7tnXbtzp9hhghpu+pABdaHzWbvzD/PszvY5dn59bsg9SOCrvqLx4w071d8DIdZVY0z/9+a32emW5Xb7r+bY5Q3P2I3XHg6bUwjm9Ky+Za0hlZO+pxFAEOTzDXLs+HlB0OeNWrKWI6UZO92yPKRf8WykQhMkJ407rkWcG5Rld+7d1EhkSMlYkjXXmkAZ0HiREZ64gGd3SQDgx6z84Ac/sKVLl9qnP/1pW7BggTU2NtqvfvWryDUlJSWWlZUV+XnxxRcj1/z617+22tpau//++23BggX26quv2p07d37veggA/v1za6ct5FSIBHtkTbQQcnGSq9XvXtRCRpCihW9PwRp7f9tDIXaPSnBvYVNwh4jREtBSXXliABdVKlqxHgRKVLgEt/yfrILfAMEF3gM8r7ypRCQLuXbl7vZKVfXVc7lD1StCgmzGgxGw7ciOJqRVG8XM8R4CFZ8zkOlU5Aql8mcAP+vvXVccW3q2wOfu1NTRcYcqqgKrqBxxqqMPuueOUcpCINdvSPHsEd3LZHB0v+TiYxlVFw8QKReGF3iWmzGbnhHyQPtefUzjgIBzKL3azq/PtVs//LTd+uGnI8mld+Z0BkZWjBtdkgTBqhsNK++S5HznZ8cbC+3a1sfsRFNBSKFCV7fe7Y/6I3stGft1iWyorvFMOvvOs6QaQ8cbC0Ncp07h4ZqhNUYhGh64cdz5cc3xoO9oDNGI8carH5Oqi+Zdd26H/d2XWhIAOItLAgA/ZqW6utp++tOf2vj4uI2Ojlptba0tWrTI3n///XBNSUmJbdq0yS5evBh+OMF/97vf2ZIlS6yiosIOHTpku3btsvnz59vrr7/+e9eDDKBnHQgSPCvnv6cypRLxjB2VCF2wypGmxZvvkDJgEmLWi0qEZw4zQJ8Km8/V555V2pF9N05PdfLtp6IhO6DvPTtBBk6bAchAiJWhEqUyUR/QtUlWhEqGwILsHIG3fntl42O4vCtK9/mNMewHbtTxLB/bzDGg67QDU58pQfKxhiJ79+VHbaQ0E07MUJ/1LWsNiaPpZva7vgnKfGwq+091pZGh96jv6H7l/CBo5EYiub0VVynguTt197xev4GAjDTHnv7mBiOy8H6DwtG6tJ1ty7czrUttvKbMBooap40HP0fYbtVN7aMBpraqLd7A252aOkt338qGsMuc40xjdCJTGoAhwSzHDA0H/S85E1BLhtwcwwTbXBcmMqW2M6fTLnVl24GymnCvxo5nEFkXGlBcO7jOcF5KdjLEtMnKG6BabxjWQu8IPQvbF29MYgBneUkA4Me8XLlyxbKysmzv3r3hs5KSEnv55Zfvec+uXbvsE5/4hF26dCl89tZbb9ncuXPto48++r3e6wGglBrjgMiycPElCPIsl0ALAQiVLNkuD0B88LZnz7jIUvHsyO4KJ45QQaoOTPpMIOCB1vbFU4eve8DIa6hkCLC4iJMhoMy8C08Mm3KPEdjoudqYI2XjZSRFQDCqtCf6odKka1Jsh9xujKljihD2lXe9q51icwXQCCa429LLU8pMStpvxlG7tBFJ7xxKrw5AVOBKIPRce5799qXHI/no6L6jIaI+IDDW+yUvsjGqOzcd7ClYE87X5Wfsz978tsjuZIFVvUd95fvWs0tk6Bhjtrewyc6159mxhiIbKc1EjIuh9OqQdoYpmmgQEbRwjnqmzgNCjWn2H+VDYM/rCFR3p1psvKZsGoglAPL3cc5xLGqc6jqGEOg6yYDxmx50ax55mevdGveUFdcNrg9kAuNANccW19M4Q5rhDTuyk6PgZntJAODHvBw/ftyysrLsX//1X8NnJSUlNn/+fPujP/ojy87Otm9961t28+bN8P13vvMd+9KXvhR5zqlTpywrK8t++ctf/l7v9TGAWrS5uOg349O4ENGyJTtH0EDFRaUhQCCFQUubrJt3udCNou/4ud7DTQYEH54J0mKsevj6ePBGhe2VlI/tIYvJBZ1Mn5TCnoI1NpEptWtbHwttZ4JZ7/JU2whm9LfYFAFxyoWsg/qcjJiXmd4p1kL9LfDGfurJm8qpN1DUGPpI40ZjQopX91KZEsjTiCBjROXJHHV6/oGyGrv1w0/bzW8vsP5Us+0pWGMjpZkQL6fn6jmXNzxjb3c8F+lXuds1FnQEmOQ8VrUqAia0qUVufYEAujWVy5Jxofotl56Mlrj5Q9aQ/SmAdbC82vaX1IY0NGSmmDaJrDGBBcdpHKAhkyoZ6lq56xXOQJCkPtDxgTrPm6wlQS/bTiaO1zD/pF8nfJomrV0EWrqP/+u5DF+IY3Z5v/pf7/JrkuYaAXecjDVXaPRq7jFu0f/evjg5CWS2lwQAfozLv/3bv1ldXZ0VFRVFPv/JT35ifX19dvjwYfvbv/1b+/znP29r1qwJ32/atMmqqqoi99y8edOysrJs165dse+6deuWvffee+Hn3Llz4SxgD9qY44sLFRdLMgb6n+db0qUZx7Z5xowuN4LQOAAnZR6nvBgArvqKXdtTsCYoSjI+dEnqfikt7Yb1C7fqTOYtLv7OKyrd691WZAUZRyelRpZDzyYA3F9SG2Llbrz2sF14PiewZGIEqTg9uCZoFhihzMlYkqVg/xHg8j7JKY59Iphg/JdnSFhftUfMJVkqAR8xcFTu7CPJmQwd+1HATAwt4wj1PDJxAo1kfegOV/soC41x/U2Zka0l07ozpzMATR6Px5AG9TNTrBDgcu4yvQrZZxoWXAeU23D74o12rj3PRisrwjxhG8kq78yZSjR+rj3Pbv/VHHu74zkbKGqMsN40cPh+jQnl+SS49OEUlDPnidqtk2R0nY/h4/v5bLaLcqHRx3VQ84DzX2OaMuecJ1tMYExwyXVXfycu4NldEgD4MS6bN2+2Rx991M6dO/f/el1/f79lZWXZiRMnzGxmAPCNN96YtrFEDCAVBVNxUCnRnStGR4s7TwyJcx1zsaWVK3DjLWiyR3GAhSwegR+VnQcPWpQJ0sgmEEiKNbjx2sP20V9+Mhz/xMWawIcAlm5myZKMVxzwYjC7AENvfls46aHpMy8F4Lu3sMm2L7674Yauru7cDjtQVmPvvvyoXdm42IbTdXa0Lm1HaktCcmevqKgsGX9E1lX3nGldGmRAZsWzmewX/QgQsM8JNlR/AhkqZz5fSpyyFXOmoH+NCTI6anPc+GH/8zqCEQIQKXe6JuPqS1eldyHGsU2e+ZLLvX3e1sh1nq2iQcG2ClwRjBHknmvPswNlNdNYbPYNx6vu7cmbSoOjXIIElKoTf0ZKM3bxhSX24Z/Os3PteQHEsp/JOmtM+FRIXJdosHrAL4OUsr/Q+WwIG+D6EsfScez7NYaGnOZh3LgnAJU81Wa1mxtGuE75eaL3s3935nQmLuBZXhIA+DEtX/3qV23hwoV26tSp/89r33//fcvKyrK+vj4zm5kL+F4M4H9a3GGXNzwzzXrVgkOXA901uoZKSQpHz+I9XPA8o+dBHZkHPcsrSSpoPpdgQqCA14udYAwjQZwW2f5Us7379UX20X+43w6WV4cFWQpG91Ix0E1MENWb3xZxefbmt0UUJWUTx4T1LWu18ZoyO9ZQZIPF9RH2gfIRazVSmgkpLa6/utCubnnCzrQuDSyN6sKNClSsvn8I2ql82CaBEvYZn6d+JtPL+lM2BAFk66hQPcPIMaP+Y/yjnkFZi5GUIcBnEQiQzfEsrN7l0/fQWGAfEWTxh6yhXKR0IdOl78EzWStey13VMtw4rsguMvWRDAwfk8j+ZTwr572fl3p+37KpkzB0DB7l6pmwOADFMaFr+JkH7hqfNPROtyyP7ILmOkcjhoy7B76+vzgOaBARKOt/po/y45jjnKCU67FfQxMXcFISAPgxK//+7/9uX/3qV+2RRx6xY8eO/V737Nu3z7KysmxsbMzM7m4CuXz5crjmJz/5ic2dO9du3br1ez2TJ4FwQdSCpOTGBANUZlqQdM4sFymCL+/y9UyJwJGeIcWybeHWwIBxESf4EgPDGDCyPwQEXKxpiRN0UQZSWoPF9eEEC694deKH7vM7+7hYK7Es5SfwIPBIxoFsyO5Ui733jS/Y7b+aY8caiiLt4XWU80BRo51fn2t3/nmR3d5z94g3yZsASLIjk6Y20M1MhszXwTMbZJH1HCZGJoMlYEEAzZNP1DaCSoKDbQu3hnhJBtSzv2kMbFu41drnTTE3TI1DVsizmx4sSS5+s5Fn2yg/bkrRO8625QdwQEbWg2vKnePNG20EQHRF6pxijhWNM4Javw4QzHp207s6eT2NI89C6t7e/Lawfnj2S2NG/S42j2OPc4ZsmurAvHtxBqTGDYGx5kccG0jmj2sP38V6kd3jWsT+8vLneksA6BPna74maWBmd0kA4MesfOUrX7E//MM/tF/84heRNC8ffPCBmZmdOHHC/uRP/sQOHDhgp0+ftn/6p3+yxx9/3NLpdHiG0sBUVVXZ6Oio9fX12YIFC2aUBuan2e3TlDoVtxZKLvr8jv9zgaQCIKCgW4buPikmWuJ9y1pt38oGO1hebZP1xTZaWTHtDFYpHy24zEHIuJo4i551FcMnhtC3lbs6CWzpMqMiIRijQiYwIcNDRoDykxxONBWEfGqDxfWBIVJbCWh35nSGkw2uv7rQrm19zM625YcNAh5skv0hy6H2CUBJpnQZMq6Qv/046c1vCwqXciG40rV+x6jqxThDz/DQsCDzqN/9qeZp45jjU0nExdzwN9O3CLQTXJLxpIGgODKl+RGrfLQubYPF9QHk+vACgcM4YMQUQz1560KfEnQT5HgwdS+3Ma/jmNCcGKtaFXFJxrk2CYYVP6c2ss4EWh5sMv2JgI+uI4jjKR38279DZ0mrfUwsLblpXJCFUx2YTkjXNH3mpSAbfeeNHeYnJfgjUNT/bK9CGggCPUvKeZ64gGd3SQDgx6zExeFlZWXZT3/6UzMzO3v2rKXTaXvwwQftvvvusyeffNK++c1vTpvgZ86csUwmY/fff7/Nnz/fXnnllRklgv7B4xvuCZ480OOiT2u3O7fD2udtnaakyOz5LPx0kYq92b54Y1AYum9vYZNN1hfb7bemTjLYX1IbAZsemBJYaCHmd4zHYzs8o7V98UbbW9g0DcT6OCAt4GQIqFjlVvaxgrpGC7nkum3h1mlMUXfu1I7Xg+XVNpyuCwl+T7cstz0FayJnJ7OtOnt0rGpV5DQPvZN9TBBGMEZ2kO3UPXFuvzj3OFkVyYHA37MfHpyTBdS9PsTAx3eyT/V8AlwaCHEbNjz7TYOFYETgVKC8N78tuOrlvh+trLCD5dV2qjllw+m6AHAFpshKk/nzRsTOnM4AkAlkCOL5QzDkGTq6ZwVoeF3fstawUYMy9SEQBJ50qatd6jP9LxBEQ059S9DPucVrCbQ4bjn+vZFHGfM7GoVsn67z4Q8Mi+G1nh3lGsEf/26OQZ9An2sc28x1NAGAs7skADApMyoCgP/xqbuAx7sruPjQlUWl2D5va3CFalGi8vWK2bs0PJij0pVCPd5YaDde/5wdbywMQIbgTQCFCp4ARz/D6bpI27xLkwyBriFAEQiSslf9BVoJvBhLxmcR6DD+jQqOcZT8X88eKc3Yh386z27/eI6da8+zO//HJ+1YQ1GkD7gpxisbXycfE0WlKzmRmaLs1CYydB6QE4B5Vy5BqX8nmTDJn64z/b5XMmDvjiRoIutDBau2ignemdMZzmf14JFASO/kDlM/RgmGPJtJsEdjwjNtvr6MV5vIlEZADscbWUY/1zwjyKTqAh0yYsgIe3AlQLsju8sOlNVEXJi+L1k37wKlMUNWj3PMrx16776VDXamdamNVlZMG59+zHjWzj+LfevHisYSZcJQCF3D2Ei69yV3ehM8wJV7XIYm1w5dm7iAZ3dJAGBSZlTIAHoWRgpBbjuxC7RQyQpSqWuB1f9SzgR2ZCuoPMjYEYgNFDXa4ery4IrTgln5qa/EbhZhvkJvOZM50sLuN3eQYRLg83FE3oVKyzyOOSODtjOnMyzuAi1eEVLOngHoyVtno5UVNl5TZhOZUruycbGNVlaENvlgdbadP3ofU5hQueg3d/DSpefjGc+158UqMwISxkfRECBIJDCWbMSkejBEwEjF3JO3LiS6JqPE9+t/3UtGjn0iwCY50k2oOmkcEujEKXX+L8bbs3fsH8qZblMfpuCBozdiCFwU/0hWXvNOz6bhwHnvAVJc3dQ/nEuqH3NbEuQxlygBvWf+/DgmqOrO7bDxmjI73lgYdstzgxZlox9voCgnozwafv1iqIY3cnx/sE1cl/w1BNqeEX3zyc2hb7RmSF5vPrk5YQBneUkAYFJmVDwDyDgZLrpx+eA8iNMCSfbDAz4CSQJNXaM0F2Q+qNypVKRkuWBSaUnhxAEFMna0wskuMa6QipAAjKwZGULGi0k+ZEB1vxShT2nfZBsAACAASURBVFgt4EK5eaXgmTIecbUzp9MOV5fbgbKaCAj0qVeozDxby52o+tyzV2w7FbIHOmRR2F8aW6wPGWbdy1gqD4I9K0bGT58x9s/X08c+ktWSUaDPuRlJn7POMiQ4Nn0evzhWUjF2Gk9klNQOMcqsh3LJKTZVY4EAhe9Vf+sZl7qy7eqWJ6bFN5LN9PGgHL/9qeawSYuAU5tZaITR0CBTSgaR45rjxLuumc8xzlPBGEfK2nsnPKsXB1rZfvY976O72//miTxkTiVb/aY7nYZonLG6I7srkosxyQM4u0sCAJMyo0IASOZH1qZnO2gxcycfQZNX0LR49b1PuSBLW4qeO0IFgKh8yKLpXQwE91a57vHB5XoOFbbu5W5jXksFwHgmup29C47sIlkDDwjpGtqR3RWOoaKikQKkstOGBDIjhyqq7FhDUUiYLQXimRwCNAK3I7UlduP1z9nRunSEWWMAvXepsV2UnRQXd3vqeepbuvcEeCh7ggQqZAIo3Uf22hsUZF18+33fCsDFgUudyMH2ekChZ3A+MdaObn0ZJGKfpOA5XgmSOA4oO/Y1204goe/f7njOzq/PDeyv2uHb6o0//YxVrbKdOVPxiFobOD5UJ7Vf44dzW3Kim5RAkKCJ8mK/bV88dXyjjgqkYcnYXRptBFzsM/0tgMnQFs1x1UUgWH2jea7k4QJ/GpOMAdb9BHnew+DXCtZR829nTpIIeraXBAAmZUaFR8GRkWHqBC3aBC+eNePnWqhqH9gSUbY+rUKcYifLRvbHu278wuk/i1P0eg/BnxZRPefLC74WFIrfsKA2inERWCVo2r54ox0sr46wn5KJBy+SLYEY5adneNBHtxCv9WwWWb+D5dXWm98WFLZ3R+l+siBjVavs8oZnbCJTOk0GHpBQ1h5Qsg2SA8eY2M59KxsiLmG6fP17KcM4gEIWzG++4djS91S0Ur4EHB60+s/J9lGOql8ciGNcG0EcDRGyorpfG0w4nvy4IbChe783vy2Sh+78+lwbSq8O4EWyonGl9qrunGN8j+pAQEQjkuPHs8B6jwfQvl/Zfxy/dPGz7nHv1zohRpjsO8cAjVr2QXduR4hB9gypniUZ71vZYEPp1WHjFk/QkSxpqMr4psHFMerd7ppviQt4dpcEACZlRoUMIEGKV0CebfMgkJ8xyJvWP5kuKRkPXPy7dD8ZDrKQVAb6X7t2tajyqDDv5iWYiFOmniHoyVtnt9+aYyOlmXDaRJwrlMrEy4ftk4ImsNF3cRtkCIAJHryrSMwhg9z3FKyxyfriaa5LD5QJAqXcPEtH8MH6iNli3e81fvh8Aeve/LZIHJpXeqzvwfJqO95YaCOlmSCb3amWSIoNL2Pv6vfgT9cQ3BA0SMn7e1R/boDQfXQJv/nk5nAN2U2NYYYqeGAuhjDO3U2AQ/Dbk7cuJP7WvZwrHmD5McV5xrGgcaWNUAK+Aqd6jgejul9103u6cztsT8EaG07X2XhNme1b2TCNjaMs2K89eesCs8yx6K/X/3o/jReCKtad6wPXvL5lU7lBdVTk7lRLOKFHrKDaMllfbMcaiuxIbUk4K1lzkDkE2TdMpUPPglIoeYMoAYCzuyQAMCkzKmQAvaUsZcKgeQIKv4OSbkn9ZlyTX5zJehAQ6T59561kr3hlSVNZ6HNuJhGDQBBDgEUlEFdnLcp0Q8kK96DOK1aCQdWFioZgSGyMryeVqQfgdO3GbahQXeTSkrKZyJROq68HXnLveaBO8OGZUM9qkJ2RLD1wobKl+1F1JavUk7fOxmvK7M7P59rRurTtzJlinAU+2W96LmMq466hjMjQEECSvZEBIOCmZ/k4PspBfSy3IkGLZMz3xoH8e4VZCHjsLWyysapV4Tk8K9jPWbpKGbIg4MFQBl1LdyZdlvqh8UQw6xlD7+4dKGq0M61L7eZ359uBspowD2hweJlRNgLInI+snwfbZAT9OOB8Y3gAQwuG0qttf0ltSO1zsLw6GAeDxfV2sLzaTrcstwudz9rFF5bY2x3P2WR9sR0srw5jh4YxPR2sjzdI44zwHzy+IQGAs7gkADApMyp+FzCZhTjlrO+lYLTgSsEKdBGseUWsxY/KRu9WXJRf5AlOaamTxfGB1LTiCV7kqrvQ+Ww43o1Kd3eqxUZKM7a/pDYS20QF6t8f5zJmm8mYkfXS8WFMJ8Pn6/xfMUlU2HxuHLD2So59yeS1dEuR5eM4UJ+wrVSWepbkTCaN40DvoOLzbA37ncYGwaSevb+kdhrz5gGoB/gDRY0BuIuJ8fXW2BF75sG6wIAP8BdoYkybxjQ3Aah+uk4ATv/zPRov3lCgkUBQtadgTWRHN8ECgQyZSs5TxqD5zTfduR0hvm20siIc6SY3MkEejag4g41Ac2fOFEN98YUldqHz2XBMnH+e5Esvg68fjUGytQLKkoueMVa1yg5Xl0eMDt5D40b1HyhqtJHSjJ1cu8LOtefZmdaldqyhKHgG9pfU2ommAru84Rm78drD9uGfzbV3X37UTrcst/Gasmmbdvx7yZyP15TF7j7nHEqOgpvdJQGASZlR8S5gghgqQgE3xqPJ3UN3JGPAfI4zLZ5UTF5Bc6Em+GAcjrf8CVTIFnkWzIMDKWYxUrpXiug3L34xpFUhYPXuT7JTHjh5wLYje2qjC3MECiToR8BQzyQzKLmSrejNbwusHhUvQRBZDCoa9Z/6UhsvCCzYV1K+3LkrUEt2jveTuVG9eK2XmWeJOAYZzydgznFCwO8ZZQ8Q9D3TjXiXZRzz5wGOwIS+U99JDgJMuidud7jGI+eAQFHcXPRjmO0TEPOMm37UVhpgZMb0LsqeMY6DxfU2XlNm59fn2oXnc+xM61I7UlsSwLLGy/bFG8N40lrgxwbn9M6cTtu3siEcu8i+jGPgJIc4o1XXT9YXR9otmR2uLreTa1dE+lLXfHnB1yI7t/0871s2dZ7xZH2xXerKtve3PWQ3v73Azq/PtdHKChsoarQDZTV2oqnAfvvS43bnP8+x6+f/N3t/20P2dsdzdqS2JCRtJyjlfJFReKCsJuzE9yED6r++Za2JC3iWlwQAJmVGhUfBUdGJ/dApEwKGVOTeReYXZJ+jjIu/Z4cIMOIUuFe4XAi9YqYC04Kvuko5c0H34FNJp2//eI5N1hdH7qebm64zxrVRDoydU92krHv+n/bOPUir6kr7b8ZKE0nENoFPQQOfKMpMI9oNdNvd9AVo+gZ0N5dpQCYQKLmM11SIOmYmcaZSIU7NlDUZE3Nxolb5+YmTfBKpwmHKEAIDgS5gmna4REVQOuAtRAhRJAbX9wf1HH9n9SFqB1HzrqfqrX77vOfss/fa++z17GftvU/J7GS7DO+MvUJD+yi/3HjaK3PKLwmMJ1kifVJKNlVPThwS5wiKFEtx8otqlLYPn+l62VyE16tRnrBT7SRZ9aFS/caV456Ec5Ws2gRVR9a76p71Ktv41xX6ti6bkahoXpjmivnfSRqp6HDQk0V2SHb1G9udbMUykljomEiarqFS7Amw8rF6TLttG99g3bNKkk3IX73xYts7vcw6appTbYxbDvEZ98qXJ7deHVxRPMcOf2Fwai4cB5fqa5RH9hE6V/dRHlaPabdnWitSqi6fPdrJ91+rRs20LbVNtqet3I7eNtDe2FZmr//DeXbwr0ba9ol1Sfj3qSlV9srCy+31v/+0Hftaob1648XWPavEdjbV2vrK1tQASu2CfSbnFrP+/aD3waL5oQDmOYIABnqFrFXAcgDrK1uts66+h2Lk1a8spcmHneiUpYJ5Z+wdEUfIJEFSTbzDktPJcpbMH8vBVZt0lhvGtlhX/QTbMLYlRSRJSjjxnKsnqRb5OYhKiyodSahIllQdTRSnw/aKDhUlr6p5RYnKG0mVJ2ZcSLNq1Mxk4jqJgV/cw5W2JByqU26Iq3yTFGeReW49pLDtg0XzU1vb+JXPnpx5J8prlLZWf3OQojxJhfNE3g9qGF7Um1q66idYZ129balt6rGFCfdt5L1lT21povmCJE+az+jVQU/uOuvqe5A7ElHVGW3lBx98FteWT7UdjePsxflFdnzjCPvtnlZ77e8GWPeskuTVdqxvT0zZ5kjYSGa4CGjVqJm2o3GcPdkwPtU/aDqGHziq3HwO+WxkfaeipjbHtub7nu5ZJUmI91eLL7Pf3V1gh5YMs30zSpM+Y1P1ZOuqn2D7Z46yl68dbq8svNwOzr3Cnm6pTM4hUedCNx3bMLYlCWEzssIthXR86aDFQQDzGEEAA70CQ8BerVIHLMJFQqAOmiP7rH3w5GjZWZM0ULHyyp5X+Bj+9L+REJJc0eGy42ceSP5IMEXq+B5hddB+bpvKohAfiYgPJ3F+2ObqSdZVPyEhAFR8qDiQkFCJpP29XejU6eikamU5Qt3Xh6ifmlKV2n6EJNzv6ehtRbuSIKi+tHBBRFCrev8QmaOaRUWEjpx5kc28wuwVHl3v51ixjVIhYtvUb6tGzbRt4xtsT1u5vTBvhL04v8j2Ti+z7RPrEkJPQs7QJsO5fm9JEnnZLavevWLEj0LGHTXNKUKpcnripHtKBV09pt22T6yz/TNH2dHbL7BjXyu0VxZebnvaylPRAf4lMSVJ5xZEPF/EkaF6Kvr8jeSRzwGfa+7jx0ELnx3fbzBt3ZPEfVP1ZNs+sc72tJXbc+2jbe/0MtvROM621DbZuoo2Wz2m3TaMbUmtAtYCEIW4Pflle/dl5QCSyq2+Rwg4vxEEMNArZC0CoWrEjpDqgn6jmrC+sjXVidEpqtNVR+bVIBIppi/iQ0LhnZ0PhXmlUoSHTpydOh0xnReJhOZw0S50OHRcVIWUPgkTw9F72srt0JJhidojW4pIehv5laWe0HjSlTWPSuXhamSSPxJcOscVxXNs96RqW1/ZmtiT6h9VHG8/1SOJkxTTtnNuSOyqD9/0QPIoe2hxzuox7alNsEmGqPL5kLbIgCcaan8+5CubiKTxmMojUrq+stW66ifYy9cOt2NfK7RjX+9nh5YMSybzv7TgL2zVqJkJUfCEVR9usaJ6psqo50j25oINXc96WFfRZusrW1OEkCFQ5kF1ozSZ7qbqybajcZw91z7aDsy5yp5uqbSOmubkGWE5/NxPEl8OMpUHPtM+n+xvSITZDlmXspdvjwytkuTy2csiz0pX275sqp5snXX1ySpgLRrTPqFry6fahrEttqW2ybaNb7AttU22YWxLQv7YN7L/kPqoe3LbFw64SNJjI+j8RhDAQK+QtQ0MOxo6G4VAGYaUc9hYNcVe/4fzbE9beeLoqVyoI6MKIHKS9T5THafKozxRTdRfpu3DJXz7hEKXVAM0UZ1lVj5IWGiLLDVQdtE2IyRhtAM7/DVl021j1ZTEtn6bGhILr0TIWXh1lbbxqovuLdvKBlptzG1euK0MF0porhfbysaqKSlCkUVC6fB1f9qTSocIMokrByYkRSRy3EBaduG9pYLxHCm9+ksiyvvJtro3FVqG4ddVtNnTLZV2+OYhdnzTlXZ84wg7/IXBtqu5JtnfzitaWaSGRMlPGRA59qFo5psDJy3aog39c+zVsKyBg9LZUtuUfDZXT0pe7yYb8Vr/XHlCpvqR+ikyyHmVTI+DDr7OkZslk9CzTen3RQNuSoWi1Yf46Sa8J22lebFSrzX45cBP7USLgFRfbD98PrzKlxXq9Wqh8hnbwOQ3ggAGegURwIdGtievY2OHw1G0V1BIBp8om2Fd9RMSdciPmrmFijoxdcIMsWZtL8J8scP0KiBJGMN2HOUz33QcJC0sN50WyZbyRMWMCqCuYdmkXHGuINUWhUBlN81LU3l8aNITAr4H2YeJaCeFHFleH/qjM5V9vErG8ikPUubokHVv1nFWiJVKTNs5N/RQafz9s8ghFSOlp3tRVaGarfZOtVCEju2Bjl32oCqoxQHrKtqss67eumeV2K9vGGqHvzA4WSDAdEncVDYqfiIPLMsfKrMU5dVj2hN1kXUq5Vf/c0NmPtteWePAQcRTIWHNU6Mi7Z99P3DJqiOVk6RUezpygEByrHQ96WRZ/KBTRP9U7YqDSJE1kV7ml3+VF+2SwOke/njWgpQsVZR1QXXTX6M8f/4zMQcwnxEEMNAriAAuHbS4h2Nlp8iOW8fZEWp060M3HKWy41eHRyLCUTbz4e/LFXp+kYB32LoPw47sZL3z8ITS7/HnFQlvI3baOk8hH6/YqPxyNF595DleiWDIiluwMJxHu9JZqTwkYcqDHKYW6VBRYn1SaWUoneok7ZkVHubAQvaWmubnFWaRSh/+1j1oR9lQdqFy5Fd6qh2pPatNsWwkcCQmXKTxRNkMW1fRZk82jLenplTZ7knV1llXn7QD2VX5ZBiY5VNeSCb89fx9bflUe7JhfFJe1hXLzrdJqEy6lnUqG5EMcgsePxeU5Ikkk4Mi1p3qnKvRWd8k5axPPmeyB+tXgyoO3thOOFjjM+z7hZUls23b+Ab7zS2DbGdTbY+6oE04EFSZNFVAzyefZz5bevbY1/l2t7l6UvKMc3CmcsUikPxGEMBAr8BFIHQ46vypErDT5ajUO36penQ+JHPcTFkdJImbDyH5EbMnb95hMBxIlcU7AqZFNZMdPNVOT1ZZJnXMnoSw/HJKfjuQdRVtSThJHxKlrO8MVZJs0+FtrJqSOqZ80RY+DMZyk+h62/j3M4tQkox5MuDTXlGcXm3s7+WJFpUZqh9eLTkV0fCDAZVfZCiLcOm7zuFqZbZRlZn7OK4pm26ddfW2YWxLMm+MhJ2EgTZieTgY8O+TpVpHZckT5azBC+uXBNyrjH5QwnZIG3lVbkXxnBTJ9oMO2YptwbcV1rP+p/2Vf9lc6bCefEjXD05WFJ9URU81jWDD2BZ7akpVMneS+aSa7skn1Xzlh+VSmTi/797h1yY24zSWlSUn38vtBx+s69gGJr8RBDDQK3ARCDtJPxKmKqROkOTIh1XooOngGHrjKJcKDDt/78zpsDzpJImgOsE5gFRtSGqUrg+NUmnz9/bKZpbaoJE9Q6ZSiDT/b+u4xmT/sPWVrUkIkAqflBrlzxMbOkhPzBX24upTKqaygUKbtJ/fLoVEPUsBY3jUh3lJ0pQP//5fKiq0Ne/lSTbrnGSfSrMcpfLA+VZsP5qH5sP5njzyeuZPapbmxHErH+ZN1/IZ4UKjR0bOTeYLrimbbhvGtmTuDZg1JYAbSlOpl91JWDiQoiKm/PHDNrd6TLvtaq5JtUU/GORqZg6CsiIHWeSe+dHKcD+YFJn1bYWkNSua4KdhUJHV+Xvayq17Vomtr2xNTdPgc+6VQ31Yr165Y/5Ixjnwy+r7qJpTdb93+LWxCCTPEQQw0CtwDqDvWNURsnNXx0OSp9EyyR+VPd/xkixSxSCZkdOh4yIZIhHxHb0czNMtlYkTpbNlnrjtBpU23lMTvElgV5a8vQ+eRuzslNWxkwTQvqtGzUzUhefaR9v+maPs6ZbKZJsIOXs6SG3UTOLhFSXWDcn7qRwKySzrWWXlAhPanWoNya+fm+bn3flwIsnhypLZtr6y1XY21dq+GaUJmVpf2WovXzu8xxs0WIcKvard+PNEwGgnny+ez3bHOvO/05asC22ZwmsY6vMqGueNSS3kcbZP5lOkgM8q65+qlCfMXGVOcu5XJntC5f9SaVfZaWMNEFePaU9eucbn3kcWfPnWlk9N9UfsL7yaSWLHjaiVHhdi+HpQPbL8XA3OumJd6D4c3Kpc7A90veb2kkTqu1fi/eBH5VEUReV9aGR7EMA8RhDAQK9ABVDEzG8fce/wk4se2CnL8aijI3niiF4dmVbr6XwfYuRfTzTUoZLkSU3zStC9w69NbXHSVT8h1aGzg6Yz9/fzI3YSP3XSDA1nkWI/j41k44myGbZ9Yp398ppiO/a1Qjt6+wV2cO4VqTePiNyQTEgloirLPNLx6jcRPaoYciDepnJqqluFpbyyJjWNBJykWGkoTwxf+fA41ZfVY9ptbflU2za+IdmAWQrQiuKTm+MqPU/+aRdPEBRq5sCE9ejJoMrGgQnfrytixnR0ruZ/qe4YWhbBJTkgWaBNPPFj+/LhXJ3rCT8JrK9j5p8LX7yyrefHq45U5EncqOL54/qr9uzLJSWMGz/z2eJzq2s8ufcDHj5zbDO+7WjAsWFsS8o+XOTiVT/miQNW2YrtJ+v58/2d70dpc/UpjAIo7VAA8xtBAAO9gn8VHFUaKkAkNOywuVUICYjOowKmjnFt+VRbV9GWCtmxs/YjfY7Q6XCpFFBFolrAc7kIg/klueS2EsqvJwnsgH06/O7JGdPU+0gPzr3C3nzsf9mRl5bYqzdebM+0VqQUQCoCctTc01D3pI04T4qky4dwqfhQAfShZaXN3xi29Qoa2wfnznFwwHMY0qIqKBKbpSSTjK8smZ0i/Wqz2ltRA5p1FW3WVT8heT+s2gHJx8qS2dZZV98jz7TvE2UzkrdebKyaYjubalNtUe/E9YROgxOFMzk48GoPnwlPOvwiFyqNXGTgFUKlwVCr0iehJImkuk/Cr7aoa0k0aS/dg4SX5dNfKZQi2jqm/Hnixmfaq2kMU7NsvGfWAHBH47hks+4sMs126e3GNL0SyOeH7ZzHqV6y7jwR9MQ2CGDALAhgoJegAkgyQcfDkTpH9eqwREY4etUEcnaQ2k5hXUVb8n5UbZzqnQQ7TIZHOPJnR+tJS5bqIMWMo/msjlkhX5JgOkTdR0qdHLLKRkVm9Zh22zejNCEFssPa8qnJ+0R/fcNQO3rbQHtxfpE9NaXKttQ2JfOOpF5pa49N1ZMTpULqh+xKO9CB+HlqdD4kDSyfJyRZ5M6nQ9uLSGSpRN72ftCgehLJ0ECD4WUScdmebUNqKfPSVT/B9rSV25628h5thQMcHd/VXGMvXzv8lArQiuI5dvjmIckCAW9nOupTqXT+O+1M+3nFXAMMr3xxzh6VbKquJN2sC5Itth8RZQ4kSOwY+iZ5eaa1IlV2tTU/EKFixmdf52kQoIETibXSzpqSwN+9GkcCKBt3zypJzfNUeTk3VgTa38f3RyStbOuqB9a1HwDrOkYQVF8aoLJ/uuvSJUEA8xxBAAO9gn8VnDo97xS9wkXVhKqBCB/3/JOD3lQ92baNb7CdTbW2q7nGdjbV2oaxLckcH5EYOiZ2guycGW6hUqeOdm35VNs6rjHZl03X+A6Zby+gA+LEch+Oo9Og0kf1j/ZYWz41efm7fpcKqleG7Z1eZk9NqUpstKNxnB267pJkr7Vt4xts96Rq29VcY5119ck8MU8UuICEao+cpLebL5scD+fK0bHRYZGYePup7cixUckTefYKDEPFXjH0eRAB9a/2UrujKppFCtiuda2f4yeirTSoevlFJPxw6oBXxFg3JCK6l1fm/PkriuekbOefQ9nXr6xX2/DPiSeAXk1mfeg4y765epJtHddoj4yca/tmlCavhGObYBRAdazfGFbPWmHN/HvlX3Xkn0dtZ8R+gW2E/YfKzHqjPUn2Ve9Z8/T0f9ZASJ9TET1PRD1xJFH0/a/yFHMA8xtBAAO9At8EwhG+V8nYWWmkT9WI1/gQ1IriOba+stU6aprtmdYK655VYi/MG2H7Z46yHY3jbHP1pIS4yDlIPaRiRzXEOwoSmZUlJ7fMOHzzEHth3gjbNr4hFYKm4kcnoA5f6W4d15iaSK7700Z0cLq/lJkHi+Yn7yGlzaiarK9sTUjfpurJyVysrvoJ1j2rxHY21dqTDeNt34xSe3F+kR2ce4U9O+3q5JVSdIIPFp3c+mVPW7kdvW1gauUk9yojqebKRxJe1p1XymQjHx6lIuHDVkxT+fAqjVdxpR4xlEySSofKTbNFLORM5bSpNCkdT3pEsPx8N348KaANuPUH0+T9RFRlk6dbKm1LbVNKweN31gnJqPKRtWk1BzkkK9yqx5MpEj1Pwvwm7vq8OL/Ijt5+ga2vbE1WtjPvsg1Ji9rA1nGNtr6yNUVkqLCxz/G29yqmJ/xZyqnajFTzDWNbksEABxrMt+pUBJH7ZKoeOMiQUsk68CovCSTt4/cu9CSSERf2dfcOj1XA+Y4ggIFewc8BpOrg/1cnLgfpiQBH8uzoVpbMto6aZnuyYbwdmHOVHb39Ajv+L5+wwzcPsWenXW2ddfVJGNOPeL2yQTKysWpK6jVuj4ycm4SVO2qa7fAXBtvxf/mEbZ9YlznJXmWgipNVXt/xkvDQEXuyLOWRJEAORQSQ6g8Xe2irmI1VU+ypKVV26LpL7PjGEXbsa4X2y2uKk3ev0vYq4+ox7Qnp1ZzLQ9dd0sMZe1LknQqVF53nlbJTDRKyFAyqOCSKOo9zHkk89J1zs2Q7n2+V78Gi+dZZV58qC8mTbMZJ9QqV+i1ClDYXP1BRJKnxdlBeRUh1XOFpPide6fIbJLN8HIBJ3SPpYPsiYWO+fb3wQ9sqnC4Vm0R7+8S65E0XbAdqm5oSod82V09K3oji5+bpmeMz6tu22g63k/FKmi8f09rROM72zxxl28Y3JOQzq71yeorSYvtUXtUu2AbVJpiWH2QoDQ1cWB7WGZ89Djw8EQ4FML8RBDDQK1AB9B0mHQA7fs7j8YqAfufxVaNOviLryYbxdvCvRtprX+1vr+2eaK99tb891z7auuon2MaqKT3mAWWlLbXDqy0ritObqq6vbE1CqR01zany+M1hdY3K6tNVR+9XR9Nps9OncukVSpINETSSCOVrfWVrEibe2VRrh667xN58oI8d+1qhHZhzlW0b35ByTsoPt/ZQ/jZVT7aDc6+wLbVNCanQ+0tJuHw9e/Uwq33IGSudVaNmpvaLpDJLxSwrxCznp+v9dABdS0fJ9sn2IpJEZcaHbb3iS3VZ9ceQ8qIBNyWhTN2Lc+J8vqiWZhFj3se/Z1t/2Vap7imffgsWtmUSDqpguo8nP55kyf7aq3JLbVMP0qYPbXvXpUtsS22T/rNKhwAAHi9JREFUbR3XaJurJ6Wep3uHX2tbaptS5M2THj1DDJNyEOAXSFHlZLp8bu8dfq3tbKq1PW3l9tSUqoSQryyZnbwZRel31DTbzqbaVFmZ1yyFjvmhUimSp+OPjEy/spF1rfS/fNGN1lU/oUeomYMblU2v04yNoPMbQQADvYII4PIr394Cgp0eSQE7Yt8R0tnIOXDvu/WVrbZ9Yp3tm1FqL1873I588bP2q8WX2bPTrrbtE+tSr8naOq6xR2iE5IjKikgPHYV/MbvIhF9N6sNScpAMR+ne2k8wS4lkR/2H1Ba/txuJgg9B6Z3B6ytbbUttkz077eokBKyQIYmlD7mRWOo3kef1la326o0X22t/N8DWVbQljo+hK9paDt7P62Sd+DbCtqC68s6cxFD3Vh5lK+ZL5fTOl3livn0eeH8/CKBC49sIV1AzLJ1FRtk2aZ8sldm3E082OBjy9pbqRsLE1br67vci1DU+tE1yTtK9YWyL7Wkrt1cWXm7PtFYkz4Ef8JHErKtos92Tqu2lBX9he6eXWUdNc49QLImS5gUq71QhlVfl+4myGbaxaoptrp6UvIeYe/p51ZKDgG3jG5ItevzggwO9rvoJ9rtvFyQLrrjqWtdyhbJv+8w7SRvzonJLdea0EA0IWP8cAMnenGt6f9GsIIB5jCCAgV7BzwGkoyAZ8ArGXZcuSTpfKmAMx6iD0obHm6snJaPw7lkltnd6me1qrrEttU3JZHA6L25BQ4L0yMi5SYgpS73iSJwEkWmQzGmOGTtcr27QNlKolDaVPB/CpIqQ9bYUKRFefSNx2VQ92Trr6pOFM1JVOJmeBIEKng8Ligi+MG+EPdNakdQbQ6pUWWQvv6KWBIIKk78325PaBBdueLWJ5I8qJOtebUNkieTBK9W6p8rZ/MnrUnPOqKbx40OM/OgefhBEkiPywcEEHTkJAR2631ZI5WfbUV2wnflwpJQkXa+8eMKj80jiaJfN1ZPs4Nwr7PjGEfZc++hk+xsOmPw2NBvGttgL80bYmz8qtJcW/IVtn1iXKosfGHHg458BT05Xj2m37RPr7OmWyuT9yp5scdDBLWpof4Ve/f0fLDo5j1ak1Q8svKLrw/crS95+xZ1fLUzCq/Kvq2hLFnRx8OafY5J/3k+fUADzG0EAA71C1kbQCluQ0Mg5sfNeUTwn9dJzdaR+jpLICle+bp9YZ5119ba5elKidvk5bZwrR5WLSgUVIXaO7DAZoqHK4pUXkhrvZEmSHiyanwpt0dmSxCpEQ7todO9VIx1XuFzXk4xtqp5s6ytbk3mPJJd+PzR99+oIHRAd28G5V9i+GaU9yK/SYR2Q8HgHp3bCtqR7a16j6sJPI1g1amayWEgT9OU0SXB1rq71irT/6+t6w9iWTGJHle9UahxJvciq2jjrUjYgWTyVSuqVOA54SCz4nc+fFl+QwKl9iFh64sm8sOwqjxTmNWXTbUfjOHumtcJ2NI5L5t16Mqe8a87qruYaOzDnKnumtSJ5LZ5IuCdEWaSez7P6nSfKZtj6ylY7MOcqe/MHBclUCL+Sf0XxybmG3bNKbPek6tRzz43l2S5enF/UQ23zz6dva2zzJPJ+YOAHDtpaZsPYFts+sc52NtUm73nmQMy3ZdlCtrnr0iXJu4OXDV0QBDCPEQQw0CuIAP7wqmkpRyinRgdPcqXOjeERzaXxI1QRBREVhTilnolYiARuGNti6yraUqEcdsD865UCho5JdDiS1m9esfJqH8vJ7W2oXPjtTOQIfHpUGqkK0TYkzFRMRAxFtmU/hla9ermjcZztnV6W7FGXpXryf84n9CSD5FFk1zsoPzeJtpZ91pRNt19eU9wjJKv/N1dPsicbxtuz065OlGGSBl2jMntCxZXOHKQwJMd5YyRAPJfEmcST6XJgwPYg0u+VIq7UlTqURaD8s8OBDhc8rS2fapuqJ/ewg9JnG+agjGSUg7Su+gm2smR2smBKz77eV72penLyhha2C9rjufbRtntSdbLZ9dZxjT0II+9Le3Muo1f99HmibIZ11DTbnrZyO3zzENs7vSxZqa9yqn3saBxnR28bmLx6js8jBxF+QMu68iSVbc2Tdk/keZyqJNvJ1nGNtqetPNkRoat+Quo5FGElseXUBf4ei0DyG0EAA70C9wGkU6ODV0dNRYPzinwHLmfMCfIaqSrk6UmOwsna7+6pKVXWUdOcEB69io6dqb5nhV+z1DCSR47WdT2dPucV6l4KSXOekkiKVwuobJEEd9Q091gB6a8lseZHauCK4jmpV5sxhK101pZPtRfnF9metvJUOdaWT02IpCcOrC8RV87jJFHkvbPUNpVd5WBaPJ+qyvaJdfbi/CJ74xvn2KHrLkkm4ouQsA45583PVVQdnYpMZSk7T5TNyNxz0rcT7WcoAqH7SMUmYaHTp4rD+V1Up6TaUd3kxuJsmxz0sM14lUntRWWRHbXqXveX+kRSqDrjdAd9VpacnBdLhXlz9aQe+xlykEPVmoPKrAGaf1WazhO5fLJhvG2fWJd67R7bgiIOGiiRbOo+HTXNtnd6WWpA4svPASDrUTb16jTJotLz6qMGuloU9+b/6WuvfbW/7WyqTbaCylJos9RT3ScIYH4jCGCgVxABXDpocdKBUemgikNnT0WPHSNJhDpdESeGL+iwdO7Gqim2q7nGfvfNPnZoybBko2iSOK9EUhX68kU3phYrMJ8+DZJCkgUqclQGpArMKuy5/5dXtEiEsuwhssuyc+6XV4IYjvbOSQ6LzkAOR2oqy9BVP8F2T6q2reMaE8eptDgvSsRH9+yqn5AiKt7hsW3I2VFp8kqZ7MfFDNsn1p2cO/bop+03twyyXc01qfmbylfWXMosMiH7MKxGNYyEwJMSfkggtVpXZaLqpL38ssgw64ckg2FPKlXKE+ebss17dZtl04fkXfenSkqCKmVaeVY7Zz0zrK1wvSdpXL1LWyiPLA+nbHCwoLwon2r/ema056DK5zcupxJN1VH35FQTP9hlWZQ2CRfbAvOfVWal5ftN5WFN2XTb01ZuB+deYftnjrKOmuZkLrR/trjPJduU+o0ggPmNIICBXkEE8KGR7UlHxnlrVG8YbmKnKbLhlRZ2qCRqIo5UhRTW3NlUm6xQ1YiYyg07Qb/gws8H5L290zxVaFbH+Go1T+5IeEjYqC758NL2iXUpm9J501mLiGWpb1n2p8JCZ87QvK7bOq7RXll4ub35fz9pv7ymuEeYUyogw2lKW45djv+VhZcnjpfqlcrHsF+WIySBVltQ/e+dXma7J1Un4UbOY9O1yqvqjEoMiSbVL85jZSiQdcnXful82Vpk1dejysdVmSpXR02zffmiGxPFVmlr9fWp8kEixXJw4MJ2TFLH+zB/VARJMmhL1gdJFOtZv3Gupz4kYyRyJECcTsG24fPLRTF83v1z70k8B5o6znaogYX6Og0YdS+/VY5/HzqVYt8nyEZss7xOaa0onpNsAq8tdrQTAhVFpu9VP/3/5YtujFXAeY4ggIFegauAqditKJ6ThG3pqOiU2AFrDhGVI80JpLNh+JAORepKR01zstpV846oRHlCRIelECedFIkf1RA/2qfK4tUJrzLpf5XPb2gsB0elR9cxtEuC5Cfmkzx6FUXl8MoJCZDytLLk7VfVba6eZPtmlNqhJcPs2WlXJ3Mr6ZDp6OUIWX/cXsTfa11FW3K+Vot6gpw1MOBvG6um2PrK1h4hySzyQwKsvPm2ynpRmDerLh8smp9Sd70q9mDRyf0UN1ZNSdWjQq0kIfyuhTU6x6+CpqLp58NRefekhCSCbXhN2XR7dtrVKYVVafnBB+3DehGpeGTkXHumtcL2Ti9LPQccXGQRFU9qSbpFgPQ/1WI/YFPe2s65IaW28hldNOCmRJ2mEqd5mBvGtiT55bQJ1pWu4z1I6FkX/lz2NZ7sUcHzKrhXdbm5Ptu32qRXKtk+Fw24KVYB5zmCAAZ6BYaASdboCKj00WmQZJ2qY8xy/H7E7tU5rWrkNXQKVBCZJtUEqgFeLfDn0yH641Td9F0Kqc4VcWLnrP+pjOoeLCvnLz1YdHIPtQ1jW1JzwehcVDavRFEd86F2zpFcV9FmHTXNtrFqSqo+pYiwbj05o31YBl/PGhB4m3hbe4WQBJjHdQ0dZJYjzFJLqDhxHqsP4dG+Pi05YL+gwCu/Xu2icv1g0duKrr+vX8gj8kICTnWRJHH7xLqElG6qnmyv//2nk3l6bHMimCR3bDNKm8R2Tdl0O/yFwYkKTztJ5X2waH5CMmXrteVTU88dB0hqt5xDrDxoOxTfrkiIWK/+eFb9b6ltStmOg0K2Qw3kGCrm860865hXn1nPJPB+8Mq8+sU6fGZJHj2B98/hvcNjI+h8RxDAQK/ARSBU+9jJ+hEtO1iFKznKp+NiB8qOU9d6VYfhLqlXVCIXDbgp2VmfKpCcJlWbrI6So/isjpqqhQ9RUZ2QDfw5VCeYx63jGlP5kNOZVfg2efFO2YeevXrpiRDrhU7Jq7acx6Wy8n3Cvp45v4o28qE41V3WtiMkNz5cSWIkEuXn+ZGkkFCxvbD8pwqFMrTq881VslIU2cayyAZJHomqv5bOW+eQSPI3LhDyzwZDhJpaQBtR0dMxTiVg+/SkypM0DbTYHn3fQNVS8yqp3HJwI9ur7bPdilDSZsyX2isVaJVFeeUzrWeUW/4wXM58+b6B7YXvlPaKtieVfC71P5XbR0a+ve8nyS/Lu6u5JpUmBwccZJDIPjJybrwLOM8RBDDP8a1vfcuGDBliffr0sdLSUuvo6HhX1/FdwOzY1XmROFCNIMlgp8l5VuzIODeGHR/vQ7LpCR6JGdUXKhb6TWRQBM3PiaNjZT7pPHhf/s95YV75ZHiHpJgO3RMrKjBKg9fTBgwTk2CShHgVjcSCJIWOis5FTlyqoE+TeWU98sOyktxoEr8+28Y32Kbqyan7+1XGVCHp+HUPqnq01V2XLrGt4xqT8igPHBSwTbDtert4m3llhuf4tsO5k3xNn455Mqk6WFs+NdnDTkRkw9iWHgpo1gCFoXASBZbZk3fl1avxXMBFku7VVd+uaScNzGTTWYU9w8D+1XtcIOafWU/q/Vw72WlF8RzbNr4hOc5raT8+uyRt7B84gPVqH/tEPpuqb13PsnlSycEHnzlf3rZzbkgd0/2DAOY3ggDmMZYvX24FBQV233332c6dO23hwoVWWFhoL7300jte618F5x2LyBNH6+p4qOyxk6WjYHokW3SudC5Z6gA7fp+eFEgdo8Pi5sw+Tf5GguF/Y4edFfaRQ/AqGxUFkgevoCjPUjWVdxIWOmLvhJU/ESFPREhEqUQw/57I0SZZiwb0G5U9kQruc0glTh+SSSlFVK6o5vj5a1npMQ9Smfi7J+okpFTjWGZ/voiv6pHzH7m1itoh0/CkX+esGjXT9k4vs/0zR9nGqikpwv7IyJOLkDSP0qfj80PiyHpZWTI7sSFJp68Hkqys372i79u4rtOzSFLKvoSDFT7LJHgcOJDgcFCR1R+RZFGNU96Yruyg/HPAyDpmHrLIqO8P+fyyPv3gke2K/aY+nC/oSa9XAx8ZeXLFdoSA8xtBAPMYpaWldv311yf/nzhxwgYNGmTf+MY33vFavwqYo1Q6Vh9WywovenLk1RWqDlQZGN7jaJf35nGSGKa/smR2DyfkHS8JG/PgSSvDkZ7A8lyvorDD96SHnXaWY6Sj4m/Ml3euLL+f76hzONfoibIZKZLGMiocLdv4OXyejGYpP55M+3lODCWSfIlscpU4iY6IA+8lZYyk0at3dLhZcwizyuHDuiTMfs85P6eNio/yqc2Uef6GsS32XPtoOzDnqtT7mFcUz0mFOZkn1r8PdbI9cO8/tkOSEhJ3f9y3MdmXW9ZwoEQ1y/cJDJvyGWT7Zntn+uyHvJJG0kci7BeUUMVmmiRbvt/ScQ5ouRiDzwTtTILoowb+d/aXj4xM7w1JkuoHaSyLntM1ZdNt+ZUzggDmMYIA5imOHz9uZ511lq1YsSJ1fO7cudbS0tLj/DfeeMOOHDmSfPbv32+5XM7uGT7dlg1dYEsHLbZlQxfY5z+z2L4/fI59f/jJF43r86/D5tr9RbNs2dAFyXed9/3hc2zpoJPX/euwubZs6ILkO69dOmixff4zi5Njy4YusOVXzkjO/+FV02zZ0AX20Mj25DefzkMj2+37w+ckf3Wcn/uLZtmPR7Um16psKouuv79olv3wqmlJXpTW0kGLk7SWXzkjVV6Vg/n19lLedL3S5r1UluVXzrClgxanyuzLpjT97/pfaSpfD41sT9n8X4fNte8Pn2P/r2Sqff4zixMbKw39VX50ncrH8ut35U92VBlYX7yH8uDbDvPi61L34z1Z/zrG9sO02D7ZlpYNXZCqb5aHx2j3z3/mpD2UFtua0pXd2SaYrq5VHbD8ahvKP/PL9q/jsrfyxDyw7LSRbKr8KA8sj3+OWY9LBy3uYTPWtcrv2wnLynwoPdqd7YR9jj78TbZQ2vcXzUruq3T4PMg2/sO+gn+Zb+WDfaD6FaWr6z7/mcWJ/fjc8hnxz4d/tpkH3pt1+dDIdvvq//4ry+Vydvjw4TPlegIfIgQBzFMcOHDAcrmc/fznP08dv+WWW6y0tLTH+XfccYflcrn4xCc+8YnPn9inu7v7TLmewIcIQQDzFO+VAHoF8Pnnn7dcLmf79+9PHY/P6f90d3cnnfQHnZc/5U/YOez8p/R5N3Y+fPiwdXd324kTJ86U6wl8iBAEME/xXkPAHkeOnJwDeORIzB15vxG2PjMIO58ZhJ3PDMLOgXdCEMA8Rmlpqd1www3J/ydOnLALL7zwPS0Cic7l/UfY+swg7HxmEHY+Mwg7B94JQQDzGMuXL7c+ffrYAw88YLt27bJFixZZYWGhvfjii+94bXQuZw5h6zODsPOZQdj5zCDsHHgnBAHMc9x99902ePBgKygosNLSUtu8efO7uu6NN96wO+64w9544433OYeBsPWZQdj5zCDsfGYQdg68E4IABgKBQCAQCOQZggAGAoFAIBAI5BmCAAYCgUAgEAjkGYIABgKBQCAQCOQZggAGAoFAIBAI5BmCAAZ6hW9961s2ZMgQ69Onj5WWllpHR8cHnaWPDLJeq3f55Zcnvx87dsyuu+46+/SnP22f/OQnbdq0aT225nn++eetubnZzj77bBswYIB96UtfsjfffPNMF+VDh3Xr1tnkyZNt4MCBlsvlemx0/tZbb9lXvvIVu+CCC+wTn/iETZgwwZ5++unUOYcOHbJrrrnGzjnnHDv33HNtwYIFdvTo0dQ5XV1dNnbsWOvTp49ddNFF9o//+I/ve9k+THgnO8+bN69HG29oaEidE3Z+ZyxbtsxGjx5tn/rUp2zAgAHW2tpqv/jFL1LnnK7+Yu3atVZcXGwFBQV2ySWX2P333/9+Fy/wASMIYOA9Y/ny5VZQUGD33Xef7dy50xYuXGiFhYX20ksvfdBZ+0jgjjvusKKiInvhhReSzyuvvJL8vmTJEvvsZz9ra9assa1bt9rVV19tFRUVye+///3vbcSIEVZXV2ednZ32+OOPW//+/e3222//IIrzocLjjz9uf/u3f2uPPvpoJjG588477dxzz7Uf//jH1tXVZS0tLXbxxRfbsWPHknMaGxvtyiuvtM2bN9t//dd/2aWXXmqzZ89Ofj9y5Iidf/75NmfOHNuxY4c9/PDDdvbZZ9v3vve9M1bODxrvZOd58+ZZY2Njqo3/+te/Tp0Tdn5nNDQ02P333287duyw7du3W3Nzsw0ePNh++9vfJuecjv5i79691rdvX/viF79ou3btsrvvvtvOOussW7169Rktb+DMIghg4D2jtLTUrr/++uT/EydO2KBBg97VG0QCJwnglVdemfnb4cOH7eMf/7j98Ic/TI7t3r3bcrmcbdq0ycxOOt8/+7M/S43yv/Od71i/fv3s+PHj72/mP0LwxOStt96yCy64wP7pn/4pOXb48GHr06ePPfzww2ZmtmvXLsvlcrZly5bknP/4j/+wj33sY3bgwAEzM7vnnnvsvPPOS9n6tttuS6m4+YRTEcDW1tZTXhN27h1efvlly+Vytm7dOjM7ff3FrbfeakVFRal7zZw5s4dqG/jTQhDAwHvCH/sO4cBJAti3b18bOHCgXXzxxXbNNdfY888/b2Zma9assVwuZ6+++mrqmsGDB9tdd91lZmZf+cpXehDIvXv3Wi6Xs//+7/8+M4X4CMATk2effdZyuZx1dnamzquurrabbrrJzMx+8IMfWGFhYer3N99808466yx79NFHzczsc5/7XA9y89Of/tRyuVwPlSsfcCoCeO6559qAAQPssssusyVLltivfvWr5Pewc+/wzDPPWC6Xs//5n/8xs9PXX1RVVdnNN9+cOue+++6zfv36vV9FCXwIEAQw8J5w4MABy+Vy9vOf/zx1/JZbbrHS0tIPKFcfLTz++OP27//+79bV1WWrV6+28vJyGzx4sP3mN7+xhx56yAoKCnpcM2bMGLv11lvNzGzhwoVWX1+f+v21116zXC5njz/++Bkpw0cBnphs3LjRcrmcHTx4MHXeX/7lX1p7e7uZmX3961+3yy67rEdaAwYMsHvuucfMzCZOnGiLFi1K/b5z507L5XK2a9eu012MDz2yCODDDz9sjz32mD355JO2YsUK+/M//3MbM2aM/f73vzezsHNvcOLECZs0aZJVVlYmx05XfzFs2DBbtmxZ6pxVq1ZZLpez119//XQXJfAhQRDAwHtCEMDTj1dffdX69etn//Zv/xYE8DQiCOCZQRYB9JD6+pOf/MTMws69wZIlS2zIkCHW3d2dHAsCGPhjEAQw8J4QIeD3B6NHj7a/+Zu/iRDwaUSEgM8M3g0BNDPr37+/ffe73zWzsPN7xfXXX28XXXSR7d27N3U8QsCBPwZBAAPvGaWlpXbDDTck/584ccIuvPDCWATSSxw9etTOO+88++Y3v5lM6v7Rj36U/P6LX/wic1I3V11/73vfs379+sWL34FTLQL553/+5+TYkSNHMheBbN26NTnnP//zPzMXJ/zud79Lzrn99tvzdnHCuyGA3d3d9rGPfcwee+wxMws7v1u89dZbdv3119ugQYN6bFdkZqetv7j11lttxIgRqbRnz54di0D+xBEEMPCesXz5cuvTp4898MADtmvXLlu0aJEVFhb22HsqkI2lS5faz372M9u3b59t3LjR6urqrH///vbyyy+b2clQz+DBg+2nP/2pbd261crLy628vDy5Xts61NfX2/bt22316tU2YMCA2AbGTpLpzs5O6+zstFwuZ3fddZd1dnYmi2zuvPNOKywsTOantba2Zm4DU1xcbB0dHbZhwwYbNmxYanuSw4cP2/nnn2+f+9znbMeOHbZ8+XLr27dvXm1P8ofsfPToUfvSl75kmzZtsn379tlPfvITKykpsWHDhqUGKGHnd8Zf//Vf27nnnms/+9nPUlvqMCx7OvoLbQNzyy232O7du+3b3/52bAOTBwgCGOgV7r77bhs8eLAVFBRYaWmpbd68+YPO0kcGM2fOtIEDB1pBQYFdeOGFNnPmTNuzZ0/yuzZ2Pe+886xv3742depUe+GFF1JpPPfcc9bU1GRnn3229e/f35YuXRobQdvJzWz9BsS5XM7mzZtnZm9vBH3++edbnz59bMKECfbUU0+l0jh06JDNnj3bPvWpT1m/fv1s/vz5f3CD4gsvvNDuvPPOM1XEDwX+kJ1ff/11q6+vtwEDBtjHP/5xGzJkiC1cuLDHADHs/M7IsnEul0tt0ny6+ou1a9faVVddZQUFBTZ06NDYCDoPEAQwEAgEAoFAIM8QBDAQCAQCgUAgzxAEMBAIBAKBQCDPEAQwEAgEAoFAIM8QBDAQCAQCgUAgzxAEMBAIBAKBQCDPEAQwEAgEAoFAIM8QBDAQCAQCgUAgzxAEMBAIBAKBQCDPEAQwEAgEAoFAIM8QBDAQCAQCgUAgzxAEMBAIBAKBQCDPEAQwEAgEAoFAIM8QBDAQCAQCgUAgzxAEMBAIBAKBQCDPEAQwEAgEAoFAIM8QBDAQCAQCgUAgzxAEMBAIBAKBQCDPEAQwEAgEAoFAIM8QBDAQCAQCgUAgzxAEMBAIBAKBQCDPEAQwEAgEAoFAIM8QBDAQCAQCgUAgzxAEMBAIBAKBQCDPEAQwEAgEAoFAIM8QBDAQCAQCgUAgzxAEMBAIBAKBQCDPEAQwEAgEAoFAIM8QBDAQCAQCgUAgzxAEMBAIBAKBQCDPEAQwEAgEAoFAIM8QBDAQCAQCgUAgz/D/AeTPyCeodSk5AAAAAElFTkSuQmCC\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2cb9299b70>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jupyter.display(img.data, label=img.filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<img 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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2cb90047b8>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jupyter.plot1d(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        fig.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f2cb8fbca90>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "jupyter.plot2d(res2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Side note.\n",
    "If you have tried to reproduce this, you may have noticed a couple of unconstiencies: \n",
    "\n",
    "* The image is called \"tif\" while the content is an \"edf\".\n",
    "* The caked image has wavy lines meaning the calibration is far from perfect.\n",
    "\n",
    "The first issue maybe corrected in uploading a properly converted image. \n",
    "The second issue is related to the spline file provided which was wrong (actually it is flipped up-down)\n",
    "\n",
    "## Conclusion\n",
    "\n",
    "This cookbook exapline the basic usage of pyFAI as a Python library for azimuthal integration and simple visualization in the Jupyter notebook."
   ]
  }
 ],
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    "version": 3
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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