{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# ProMo - A Speech Prosody Morphing library for Python\n",
    "\n",
    "*An introduction and tutorial*\n",
    "\n",
    "# Section 1.2: Pitch manipulation tutorial"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "TABLE OF CONTENTS\n",
    "\n",
    "**[Section 1.1: An introduction](tutorial1_1_intro_to_promo.ipynb)** (opens in a new notebook)\n",
    "\n",
    "**Section 1.2: Pitch manipulation tutorial**\n",
    "- <a href=\"#basic_manipulation\">Basic pitch manipulations</a>\n",
    "- <a href=\"#basic_manipulations_problems\">Some problems with basic manipulations</a>\n",
    "- <a href=\"#adjusting_for_duration\">Adjusting for duration</a>\n",
    "- <a href=\"#adjusting_for_pitch\">Adjusting for pitch range and average pitch</a>\n",
    "- <a href=\"#prosody_morph_with_textgrids\">Morphing selective regions using textgrids</a>\n",
    "- <a href=\"#intermediate_morphing\">Intermediate morphing</a>\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Settings things up\n",
    "from os.path import join\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "import IPython\n",
    "inputPath = join('..', 'examples', 'files')\n",
    "\n",
    "from praatio import data_points\n",
    "\n",
    "# Some convenience functions -- we'll be using these a lot\n",
    "def pitchForPlots(pitchFN):\n",
    "    pitchTier = data_points.open2DPointObject(pitchFN)\n",
    "    x, y = zip(*pitchTier.pointList)\n",
    "    return x, y\n",
    "\n",
    "def doPlot(axis, title, pitchFN):\n",
    "    axis.plot(*pitchForPlots(pitchFN))\n",
    "    axis.set_title(title)\n",
    "    axis.set_xlabel(\"time(s)\")\n",
    "    axis.set_ylabel(\"F0(hz)\")\n",
    "    \n",
    "def displayAudio(audioTuple):\n",
    "    for title, wavFN in audioTuple:\n",
    "        print(title)\n",
    "        IPython.display.display(IPython.display.Audio(wavFN))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "# A Tutorial\n",
    "\n",
    "If you haven't already, please read section 1.1 for an introduction to ProMo and some conceptual basics behind doing pitch manipulations.  Here, we're going to jump right in and get our hands dirty with some code and data!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "<hr>\n",
    "<a id=\"basic_manipulation\"></a>\n",
    "\n",
    "### Basic Pitch Manipulations\n",
    "\n",
    "The most basic manipulation is when the source values are replaced wholesale with other pre-defined values.  This requires just two things: a source file and target values.  In later examples, we will see how to generate intermediate manipulations or to selectively manipulate sections of a source file using sections of a target file.  Baby steps.\n",
    "\n",
    "**The results of such basic manipulations aren't going to be useful except in very limited situations**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's take a look at the output:\n"
     ]
    }
   ],
   "source": [
    "import io\n",
    "import os\n",
    "from os.path import join\n",
    "\n",
    "from promo import f0_morph\n",
    "from praatio import audio\n",
    "from praatio import data_points\n",
    "from praatio import praat_scripts\n",
    "from praatio import pitch_and_intensity\n",
    "from praatio.utilities import constants\n",
    "\n",
    "# We need to use absolute paths when using praatEXE\n",
    "inputPath = os.path.abspath(join('..', 'examples', 'files'))\n",
    "outputPath = os.path.abspath(join(inputPath, \"pitch_tutorial_output\"))\n",
    "if not os.path.exists(outputPath):\n",
    "    os.mkdir(outputPath)\n",
    "\n",
    "########\n",
    "# STEP 1: Load all the pre-defined parameters\n",
    "\n",
    "# Pick your poison\n",
    "praatEXE = r\"C:\\Praat.exe\"  # Windows paths\n",
    "#praatEXE = \"/Applications/Praat.app/Contents/MacOS/Praat\"  # Mac paths\n",
    "\n",
    "# Audio file to manipulate\n",
    "inputWavFN = \"mary2.wav\"\n",
    "\n",
    "# Pitch file for manipulation\n",
    "flatPitchFN = \"mary2_flat_pitch.PitchTier\"\n",
    "\n",
    "# Final output wav file\n",
    "outputWavFN = \"mary2_flat_pitch.wav\"\n",
    "minPitch = 50\n",
    "maxPitch = 350\n",
    "\n",
    "########\n",
    "# STEP 2: Create the target pitch contour\n",
    "# To do this, we need to obtain pitch values at regular intervals\n",
    "# Generally, you'd extract this information or use a stylized curve\n",
    "# but here we'll generate an unnaturally flat pitch.  It will be noticably weird.\n",
    "duration = audio.getDuration(join(inputPath, inputWavFN))\n",
    "frequency = 100.0\n",
    "pitchVal = 100.0\n",
    "pitchList = [(timeV / frequency, pitchVal) for timeV in range(int(duration * 100))]\n",
    "\n",
    "targetPitchTier = data_points.PointObject2D(pitchList, constants.DataPointTypes.PITCH, 0, duration)\n",
    "targetPitchTier.save(join(outputPath, flatPitchFN))\n",
    "\n",
    "########\n",
    "# STEP 3: Do the resynthesis\n",
    "\n",
    "praat_scripts.resynthesizePitch(praatEXE,\n",
    "                                join(inputPath, inputWavFN),\n",
    "                                join(outputPath, flatPitchFN),\n",
    "                                join(outputPath, outputWavFN),\n",
    "                                minPitch, maxPitch)\n",
    "print(\"Let's take a look at the output:\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The original audio file:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 54500 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The new, resynthesized audio file (yikes!):\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 54500 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "displayAudio(((\"The original audio file:\", join(inputPath, inputWavFN)),\n",
    "              (\"The new, resynthesized audio file (yikes!):\", join(outputPath, outputWavFN))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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khHH/d4bTKymWH/5nIZt37WuS64qIBNHjwJSDtt0CzHbO9QVme68BMLNI4M/ArKYKUERE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\nAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d8ee575dd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, plotList = plt.subplots(1, 2, figsize=(14, 3))\n",
    "\n",
    "x, y = zip(*targetPitchTier.pointList)\n",
    "\n",
    "mary2PitchFN = \"mary2.PitchTier\"\n",
    "pitch_and_intensity.extractPitchTier(join(inputPath, inputWavFN),\n",
    "                                     join(outputPath, mary2PitchFN),\n",
    "                                     praatEXE, minPitch, maxPitch)\n",
    "\n",
    "doPlot(plotList[0], 'Original pitch', join(outputPath, mary2PitchFN)) \n",
    "doPlot(plotList[1], 'Resynthesized pitch', join(outputPath, flatPitchFN))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In some situations, it might make sense to algorithmically generate a pitch contour, as in the previous example.  But unless your data is simple or your pitch generating function sophisticated, the results might sound not unlike the flat pitch used in the previous resynthesis.  We'll approach this issue in the next example.\n",
    "\n",
    "<hr>\n",
    "<a id=\"basic_manipulations_problems\"></a>\n",
    "### Some problems with basic pitch manipulation\n",
    "\n",
    "In the previous example, we resynthesized a recording using a flat pitch contour and it sounded terrible.  In this example, we show how to use a naturally produced pitch contour.\n",
    "\n",
    "This comes with some important caveats, as will be discussed.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's take a look at the output:\n"
     ]
    }
   ],
   "source": [
    "# Skipping everything above 'STEP 1' from the previous example\n",
    "\n",
    "########\n",
    "# STEP 1: Load all the pre-defined parameters\n",
    "\n",
    "# Pick your poison\n",
    "praatEXE = r\"C:\\Praat.exe\"  # Windows paths\n",
    "#praatEXE = \"/Applications/Praat.app/Contents/MacOS/Praat\"  # Mac paths\n",
    "\n",
    "# Audio file to manipulate\n",
    "inputWavFN = \"mary2.wav\"\n",
    "\n",
    "# (*NEW*) Audio file supplying target pitch contour\n",
    "targetWavFN = \"mary1.wav\"\n",
    "\n",
    "# (*NEW*) Pitch file for manipulation\n",
    "mary1PitchFN = \"mary1.PitchTier\"\n",
    "\n",
    "# Final output wav file\n",
    "outputWavFN = \"mary2_to_mary1.wav\"\n",
    "minPitch = 50\n",
    "maxPitch = 350\n",
    "\n",
    "########\n",
    "# STEP 2: Create the target pitch contour\n",
    "# (*NEW*) Extracting pitch from target file\n",
    "pitch_and_intensity.extractPitchTier(join(inputPath, targetWavFN),\n",
    "                                     join(outputPath, mary1PitchFN),\n",
    "                                     praatEXE, minPitch, maxPitch)\n",
    "\n",
    "########\n",
    "# STEP 3: Do the resynthesis\n",
    "\n",
    "praat_scripts.resynthesizePitch(praatEXE,\n",
    "                                join(inputPath, inputWavFN),\n",
    "                                join(outputPath, mary1PitchFN),\n",
    "                                join(outputPath, outputWavFN),\n",
    "                                minPitch, maxPitch)\n",
    "print(\"Let's take a look at the output:\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The original audio file:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 54500 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The target audio file:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 49128 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The new, resynthesized audio file (still yikes!):\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 54500 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "displayAudio(((\"The original audio file:\", join(inputPath, inputWavFN)),\n",
    "              (\"The target audio file:\", join(inputPath, targetWavFN)),\n",
    "              (\"The new, resynthesized audio file (still yikes!):\", join(outputPath, outputWavFN))))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In some ways better than the output with flat pitch but in some cases worse.\n",
    "\n",
    "**Why did the naturally produced pitch contour result in bad output?**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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vjEcu6oGvl7vNzx/o48kH1w4iJTqQGz9czaId+Y0fpJRSqk3Zvr+Ui1/+lV0F5bw9OZX7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\nzKwEd5bMzMzMzMxK+H9JIPgS6aTfHwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d8ee5754e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, plotList = plt.subplots(2, 2, figsize=(14, 6))\n",
    "\n",
    "resynthesizedPitchFN = \"mary2_to_mary1.TextGrid\"\n",
    "pitch_and_intensity.extractPitchTier(join(outputPath, outputWavFN),\n",
    "                                     join(outputPath, resynthesizedPitchFN),\n",
    "                                     praatEXE, minPitch, maxPitch)\n",
    "\n",
    "doPlot(plotList[0][0], 'Original pitch', join(outputPath, mary2PitchFN)) \n",
    "doPlot(plotList[0][1], 'Target pitch', join(outputPath, mary1PitchFN)) \n",
    "doPlot(plotList[1][0], 'Resynthesized pitch', join(outputPath, resynthesizedPitchFN)) \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So what happened?  Notice the axes.  The original pitch and the target pitch have different ranges for both the x axis (time) and the y axis (F0).  \n",
    "\n",
    "Resynthesizing pitch in this way is problematic for several reasons:\n",
    "\n",
    "1. If the target and source don't match much in content, you can get weird effects like pitch movements in improper places, etc.  In this case, the target and source do match in content, \n",
    "\n",
    "2. The audio files must match in length or else the target pitch will be clipped or there will be some remnenants of the source file's pitch after the end of the target pitch data.\n",
    "\n",
    "3. Individuals have different average pitch and pitch range.  Men tend to have deeper voices (lower F0) with smaller differences between the pitch peaks and valleys than women, due to both physiological and cultural reasons.  However, even within gender there are large variations in pitch.\n",
    "\n",
    "In the next example, we'll look at how to address the last two issues (the first issue is your responsibility when you're collecting your data)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "<a id=\"adjusting_for_duration\"></a>\n",
    "### Adjusting for duration\n",
    "\n",
    "Let's repeat the previous procedure, but this time use the f0Morph() function.  Using it, we can correct for differences in duration, pitch range, and mean pitch.\n",
    "\n",
    "We'll show this in two steps.  First, let's not bother with messing with pitch range or mean pitch.  Let's take care of duration first.  We don't need to do anything special, the f0Morph() function maps to the target pitch in relative time, so the source and target contours don't have to be the same length, and all pitch events will be preserved from both."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's take a look at the output:\n"
     ]
    }
   ],
   "source": [
    "# Skipping everything above 'STEP 1' from the previous example\n",
    "\n",
    "########\n",
    "# STEP 1: Load all the pre-defined parameters\n",
    "\n",
    "# Pick your poison\n",
    "praatEXE = r\"C:\\Praat.exe\"  # Windows paths\n",
    "#praatEXE = \"/Applications/Praat.app/Contents/MacOS/Praat\"  # Mac paths\n",
    "\n",
    "# Audio file to manipulate\n",
    "inputWavFN = \"mary2.wav\"\n",
    "\n",
    "# Audio file supplying target pitch contour\n",
    "targetWavFN = \"mary1.wav\"\n",
    "\n",
    "# Pitch file for manipulation\n",
    "mary1PitchFN = \"mary1.PitchTier\"\n",
    "mary2PitchFN = \"mary2.PitchTier\"\n",
    "\n",
    "# Final output wav file\n",
    "outputWavFN = \"mary2_to_mary1.wav\"\n",
    "minPitch = 50\n",
    "maxPitch = 350\n",
    "\n",
    "# (*NEW*) The list of steps\n",
    "# A lists of values between 0 and 1.0 where 0 corresponds to 0% morph (all source contour)\n",
    "# and 1.0 corresponds to 100% morph (all target contour)\n",
    "# For now, let's go with the simplest possible stepList:\n",
    "stepList = [1.0, ]\n",
    "\n",
    "########\n",
    "# STEP 2: Load pitch data\n",
    "# Notice that this time we're using extractPitch rather than extractPitchTier.\n",
    "# The result is the same except the form of the output. extractPitch() returns\n",
    "# a list of the form [(timeV1, pitchV1), (timeV2, pitchV2), ] whereas\n",
    "# extractPitchTier() returns\n",
    "fromPitchTier = pitch_and_intensity.extractPitchTier(join(inputPath, inputWavFN),\n",
    "                                                     join(outputPath, mary2PitchFN),\n",
    "                                                     praatEXE, minPitch,\n",
    "                                                     maxPitch, forceRegenerate=False)\n",
    "\n",
    "toPitchTier = pitch_and_intensity.extractPitchTier(join(inputPath, targetWavFN),\n",
    "                                                   join(outputPath, mary1PitchFN),\n",
    "                                                   praatEXE, minPitch,\n",
    "                                                   maxPitch, forceRegenerate=False)\n",
    "\n",
    "########\n",
    "# STEP 3: Prepare the pitch regions\n",
    "# (*NEW*) Wrap the pitch data into a list []\n",
    "# extractPitch() returns a list of pitch data points\n",
    "# f0 morph expects a list of lists, where each element of the list contains the pitch\n",
    "# values for one region of the audio data. (e.g. the pitch values in fromPitch[0] would\n",
    "# get morphed to the pitch values in toPitch[0] and the pitch values in fromPitch[1]\n",
    "# would get morphed to the pitch values in toPitch[1], etc.)\n",
    "# In this example, we only have 1 region containing all of our pitch data.  Thus:\n",
    "fromPitchRegions = [fromPitchTier.pointList, ]\n",
    "toPitchRegions = [toPitchTier.pointList, ]\n",
    "\n",
    "########\n",
    "# STEP 4: Run the morph process\n",
    "f0_morph.f0Morph(fromWavFN=join(inputPath, inputWavFN),\n",
    "                 pitchPath=outputPath,\n",
    "                 stepList=stepList,\n",
    "                 outputName=\"mary2_to_mary1_morph\",\n",
    "                 doPlotPitchSteps=False,\n",
    "                 fromPitchData=fromPitchRegions,\n",
    "                 toPitchData=toPitchRegions,\n",
    "                 outputMinPitch=minPitch,\n",
    "                 outputMaxPitch=maxPitch,\n",
    "                 praatEXE=praatEXE)\n",
    "print(\"Let's take a look at the output:\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The original audio file:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 54500 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The target audio file:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 49128 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The new, resynthesized audio file (better, but still yikes!):\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 54500 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "displayAudio(((\"The original audio file:\", join(inputPath, inputWavFN)),\n",
    "              (\"The target audio file:\", join(inputPath, targetWavFN)),\n",
    "              (\"The new, resynthesized audio file (better, but still yikes!):\", join(outputPath, \"f0_resynthesized_wavs\", \"mary2_to_mary1_morph_1.wav\"))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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T7R1OmxcX6sNF/aJ4d2kGlw6KoUuEv71DUkqdgnbbc3R+3448ML4H5/TscMJ9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\niIiICAD/B25roj78s+rIAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d8eeae46a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, plotList = plt.subplots(2, 2, figsize=(14, 6))\n",
    "\n",
    "pitch_and_intensity.extractPitchTier(join(outputPath, \"f0_resynthesized_wavs\", \"mary2_to_mary1_morph_1.wav\"),\n",
    "                                     join(outputPath, \"mary2_to_mary1_morph_1.PitchTier\"),\n",
    "                                     praatEXE, minPitch,\n",
    "                                     maxPitch, forceRegenerate=False)\n",
    "\n",
    "doPlot(plotList[0][0], 'Original pitch', join(outputPath, mary2PitchFN)) \n",
    "doPlot(plotList[0][1], 'Target pitch', join(outputPath, mary1PitchFN)) \n",
    "doPlot(plotList[1][0], 'Morphed pitch (this time)', join(outputPath, \"mary2_to_mary1_morph_1.PitchTier\"))\n",
    "doPlot(plotList[1][1], 'Resynthesized pitch (last time)', join(outputPath, resynthesizedPitchFN))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "<a id=\"adjusting_for_pitch\"></a>\n",
    "### Adjusting for pitch range and average pitch\n",
    "\n",
    "Now we're going to worry about pitch range and mean pitch.  It's really quite simple actually.  They take the form of two optional arguments to f0Morph(): **keepPitchRange** and **keepAveragePitch**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's take a look at the output:\n"
     ]
    }
   ],
   "source": [
    "f0_morph.f0Morph(fromWavFN=join(inputPath, inputWavFN),\n",
    "                 pitchPath=outputPath,\n",
    "                 stepList=stepList,\n",
    "                 outputName=\"mary2_to_mary1_morph_with_mary2_avg\",\n",
    "                 doPlotPitchSteps=False,\n",
    "                 fromPitchData=fromPitchRegions,\n",
    "                 toPitchData=toPitchRegions,\n",
    "                 outputMinPitch=minPitch,\n",
    "                 outputMaxPitch=maxPitch,\n",
    "                 praatEXE=praatEXE,\n",
    "                 keepPitchRange=False,  # (*NEW*)\n",
    "                 keepAveragePitch=True)   # (*NEW*)\n",
    "\n",
    "f0_morph.f0Morph(fromWavFN=join(inputPath, inputWavFN),\n",
    "                 pitchPath=outputPath,\n",
    "                 stepList=stepList,\n",
    "                 outputName=\"mary2_to_mary1_morph_with_mary2_range\",\n",
    "                 doPlotPitchSteps=False,\n",
    "                 fromPitchData=fromPitchRegions,\n",
    "                 toPitchData=toPitchRegions,\n",
    "                 outputMinPitch=minPitch,\n",
    "                 outputMaxPitch=maxPitch,\n",
    "                 praatEXE=praatEXE,\n",
    "                 keepPitchRange=True,  # (*NEW*)\n",
    "                 keepAveragePitch=False)   # (*NEW*)\n",
    "\n",
    "f0_morph.f0Morph(fromWavFN=join(inputPath, inputWavFN),\n",
    "                 pitchPath=outputPath,\n",
    "                 stepList=stepList,\n",
    "                 outputName=\"mary2_to_mary1_morph_with_mary2_all\",\n",
    "                 doPlotPitchSteps=False,\n",
    "                 fromPitchData=fromPitchRegions,\n",
    "                 toPitchData=toPitchRegions,\n",
    "                 outputMinPitch=minPitch,\n",
    "                 outputMaxPitch=maxPitch,\n",
    "                 praatEXE=praatEXE,\n",
    "                 keepPitchRange=True,  # (*NEW*)\n",
    "                 keepAveragePitch=True)   # (*NEW*)\n",
    "\n",
    "# And we'll go ahead and extract their pitchTiers now\n",
    "pitch_and_intensity.extractPitchTier(join(outputPath, \"f0_resynthesized_wavs\", \"mary2_to_mary1_morph_with_mary2_avg_1.wav\"),\n",
    "                                     join(outputPath, \"mary2_to_mary1_morph_with_mary2_avg_1.PitchTier\"),\n",
    "                                     praatEXE, minPitch,\n",
    "                                     maxPitch, forceRegenerate=True)\n",
    "pitch_and_intensity.extractPitchTier(join(outputPath, \"f0_resynthesized_wavs\", \"mary2_to_mary1_morph_with_mary2_range_1.wav\"),\n",
    "                                     join(outputPath, \"mary2_to_mary1_morph_with_mary2_range_1.PitchTier\"),\n",
    "                                     praatEXE, minPitch,\n",
    "                                     maxPitch, forceRegenerate=True)\n",
    "pitch_and_intensity.extractPitchTier(join(outputPath, \"f0_resynthesized_wavs\", \"mary2_to_mary1_morph_with_mary2_all_1.wav\"),\n",
    "                                     join(outputPath, \"mary2_to_mary1_morph_with_mary2_all_1.PitchTier\"),\n",
    "                                     praatEXE, minPitch,\n",
    "                                     maxPitch, forceRegenerate=True)\n",
    "print(\"Let's take a look at the output:\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The original audio file:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 54500 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The target audio file:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 49128 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The morphed audio from last time:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 54500 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "With source average pitch:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 54500 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "With source range:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 54500 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "With both source average pitch and range:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 54500 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "displayAudio((\n",
    "              (\"The original audio file:\", join(inputPath, inputWavFN)),\n",
    "              (\"The target audio file:\", join(inputPath, targetWavFN)),\n",
    "              (\"The morphed audio from last time:\", join(outputPath, \"f0_resynthesized_wavs\", \"mary2_to_mary1_morph_1.wav\")),\n",
    "              (\"With source average pitch:\", join(outputPath, \"f0_resynthesized_wavs\", \"mary2_to_mary1_morph_with_mary2_avg_1.wav\")),\n",
    "              (\"With source range:\", join(outputPath, \"f0_resynthesized_wavs\", \"mary2_to_mary1_morph_with_mary2_range_1.wav\")),\n",
    "              (\"With both source average pitch and range:\", join(outputPath, \"f0_resynthesized_wavs\", \"mary2_to_mary1_morph_with_mary2_all_1.wav\")),\n",
    "              ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So it seems that (at least in this case), the speaker's pitch range was the most important aspect of their voice.  I don't even hear a difference between the last two.\n",
    "\n",
    "What do these look like?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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PHpPeXcqBovJmj0Mp1XJoctSKVNcYHpmzkUAvVx4Z19Vm15mUEM2LE/vwZ3K29iAppZQ6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7cX/z6/H71jQnhhYTp3vbOaQN91DOkSTt/YMPrGhjI8sT0xYYFOh6rUMa3NLqBbZDDB/kdWOazj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\n1+jI21nBO0u2MaR7F+47d1RInUjzJ095cuXIOVcBpO21bSdN3etERILK6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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d8eee55588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, plotList = plt.subplots(3, 2, figsize=(14, 9))\n",
    "\n",
    "doPlot(plotList[0][0], 'Original pitch', join(outputPath, mary2PitchFN)) \n",
    "doPlot(plotList[0][1], 'Target pitch', join(outputPath, mary1PitchFN)) \n",
    "doPlot(plotList[1][0], 'Morphed pitch (last time)', join(outputPath, \"mary2_to_mary1_morph_1.PitchTier\"))\n",
    "doPlot(plotList[1][1], 'Morphed pitch (with source average)', join(outputPath, \"mary2_to_mary1_morph_with_mary2_avg_1.PitchTier\"))\n",
    "doPlot(plotList[2][0], 'Morphed pitch (with source pitch range)', join(outputPath, \"mary2_to_mary1_morph_with_mary2_range_1.PitchTier\"))\n",
    "doPlot(plotList[2][1], 'Morphed pitch (with source average and pitch range)', join(outputPath, \"mary2_to_mary1_morph_with_mary2_all_1.PitchTier\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "<a id='prosody_morph_with_textgrids'></a>\n",
    "### Morphing selective regions using textgrids\n",
    "\n",
    "The next wrinkle we're going to add in is the addition of TextGrids.  TextGrids contain timestamped annotations--intervals and points.  Anything could be annotated--the sentences, words, or phones being said, contextual information, stage directions, interruptions, whatever.  Using these annotations, we can selectively morph the pitch in one region to the pitch in another.\n",
    "\n",
    "This code uses **PraatIO** a python library for working with speech transcripts.  You won't need to understand praatio to use this code but for more information on praatio and it's capabilities, you might find it useful to see it's homepage (a praatio tutorial is also available there).  [Praatio's page on GitHub](https://github.com/timmahrt/praatIO)\n",
    "\n",
    "Back to the tutorial.\n",
    "\n",
    "Remember how we wrapped the pitch data in a list?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "fromPitchRegions = [fromPitchTier.pointList, ]\n",
    "toPitchRegions = [toPitchTier.pointList, ]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the earier examples we morphed one whole pitch tier to another.  However, we could split up the task into chunks--we could morph the first half of one to the first half of the other and the second half to the other second half.\n",
    "\n",
    "We doing this by specifying more than one region in fromPitchRegions and toPitchRegions like so:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "halfLen = int(len(fromPitchRegions)/2)\n",
    "fromPitchRegions = [fromPitchTier.pointList[:halfLen], fromPitchTier.pointList[halfLen:]]\n",
    "                    \n",
    "halfLen = int(len(toPitchRegions)/2)                    \n",
    "toPitchRegions = [toPitchTier.pointList[:halfLen], toPitchTier.pointList[halfLen:]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Why split up the regions to morph in the first place?**  Although f0Morph() can work on files of different lengths, if there is a mismatch between the timing of the content being said, undesired results can occur.  Consider a few cases:\n",
    "\n",
    "* He likes to eat pickles.\n",
    "\n",
    "* She likes to eat oranges, he said.\n",
    "\n",
    "In a case like this, we might only want to morph the segments that are structurally similar.  We could omit 'she said' from the morph process.\n",
    "\n",
    "* Constantinople was big.\n",
    "\n",
    "* Paris is enormous.\n",
    "\n",
    "The inbalance in syllables between the subject and the object may lead to segments of the mapped contour falling in places it wouldn't naturally occur on.\n",
    "\n",
    "In scenarios like these, we can create textgrid annotations that mark the regions we'd like to map.  These could be arbitrary regions, that we annotate, or could be something more typical like utterance, word, or phone-level annotations.\n",
    "\n",
    "\n",
    "In terms of the code, a special function will pull out the pitch samples at those times, but otherwise the morph process is as we've seen.  Let's try an example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's take a look at the output:\n"
     ]
    }
   ],
   "source": [
    "# This is a complete example that don't require the earlier\n",
    "# segments of this tutorial to run.\n",
    "import io\n",
    "import os\n",
    "from os.path import join\n",
    "\n",
    "from promo import f0_morph\n",
    "from praatio import audio\n",
    "from praatio import data_points\n",
    "from praatio import praat_scripts\n",
    "from praatio import pitch_and_intensity\n",
    "\n",
    "# We need to use absolute paths when using praatEXE\n",
    "inputPath = os.path.abspath(join('..', 'examples', 'files'))\n",
    "outputPath = os.path.abspath(join(inputPath, \"pitch_tutorial_output\"))\n",
    "if not os.path.exists(outputPath):\n",
    "    os.mkdir(outputPath)\n",
    "\n",
    "########\n",
    "# STEP 1: Load all the pre-defined parameters\n",
    "\n",
    "# Pick your poison\n",
    "praatEXE = r\"C:\\Praat.exe\"  # Windows paths\n",
    "#praatEXE = \"/Applications/Praat.app/Contents/MacOS/Praat\"  # Mac paths\n",
    "minPitch = 50\n",
    "maxPitch = 350\n",
    "stepList = [1.0, ]\n",
    "\n",
    "########\n",
    "# STEP 2: Load pitch data\n",
    "fromPitchTier = pitch_and_intensity.extractPitchTier(join(inputPath, \"oranges.wav\"),\n",
    "                                                     join(outputPath, \"oranges.PitchTier\"),\n",
    "                                                     praatEXE, minPitch,\n",
    "                                                     maxPitch, forceRegenerate=True)\n",
    "\n",
    "toPitchTier = pitch_and_intensity.extractPitchTier(join(inputPath, \"pickles.wav\"),\n",
    "                                                   join(outputPath, \"pickles.PitchTier\"),\n",
    "                                                   praatEXE, minPitch,\n",
    "                                                   maxPitch, forceRegenerate=True)\n",
    "\n",
    "########\n",
    "# STEP 3: Prepare the pitch regions\n",
    "# (*NEW*) -- using getPitchForIntervals()\n",
    "tierName = \"utterances\"\n",
    "fromTGFN = join(inputPath, \"oranges.TextGrid\")\n",
    "toTGFN = join(inputPath, \"pickles.TextGrid\")\n",
    "fromPitchRegions = f0_morph.getPitchForIntervals(fromPitchTier.pointList, fromTGFN, tierName)\n",
    "toPitchRegions = f0_morph.getPitchForIntervals(toPitchTier.pointList, toTGFN, tierName)\n",
    "\n",
    "########\n",
    "# STEP 4: Run the morph process\n",
    "f0_morph.f0Morph(fromWavFN=join(inputPath, \"oranges.wav\"),\n",
    "                 pitchPath=outputPath,\n",
    "                 stepList=stepList,\n",
    "                 outputName=\"oranges_to_pickles_with_textgrids\",\n",
    "                 doPlotPitchSteps=False,\n",
    "                 fromPitchData=fromPitchRegions,\n",
    "                 toPitchData=toPitchRegions,\n",
    "                 outputMinPitch=minPitch,\n",
    "                 outputMaxPitch=maxPitch,\n",
    "                 praatEXE=praatEXE,\n",
    "                 keepPitchRange=False,\n",
    "                 keepAveragePitch=False,\n",
    "                 sourcePitchDataList=fromPitchTier.pointList)  \n",
    "                # (*NEW*) If you aren't manipulating the whole pitch contour, specify the source\n",
    "                # pitch contour with *sourcePitchDataList* and it will sample from any regions\n",
    "                # not in fromPitchData\n",
    "                \n",
    "\n",
    "# And we'll go ahead and extract the pitchTier now\n",
    "pitch_and_intensity.extractPitchTier(join(outputPath, \"f0_resynthesized_wavs\", \"oranges_to_pickles_with_textgrids_1.wav\"),\n",
    "                                     join(outputPath, \"oranges_to_pickles_with_textgrids_1.PitchTier\"),\n",
    "                                     praatEXE, minPitch,\n",
    "                                     maxPitch, forceRegenerate=True)\n",
    "\n",
    "\n",
    "# Let's also morph the files without a textgrid for comparison\n",
    "fromPitchRegions = [fromPitchTier.pointList, ]\n",
    "toPitchRegions = [toPitchTier.pointList, ]\n",
    "f0_morph.f0Morph(fromWavFN=join(inputPath, \"oranges.wav\"),\n",
    "                 pitchPath=outputPath,\n",
    "                 stepList=stepList,\n",
    "                 outputName=\"oranges_to_pickles\",\n",
    "                 doPlotPitchSteps=False,\n",
    "                 fromPitchData=fromPitchRegions,\n",
    "                 toPitchData=toPitchRegions,\n",
    "                 outputMinPitch=minPitch,\n",
    "                 outputMaxPitch=maxPitch,\n",
    "                 praatEXE=praatEXE,\n",
    "                 keepPitchRange=False,\n",
    "                 keepAveragePitch=False)\n",
    "\n",
    "pitch_and_intensity.extractPitchTier(join(outputPath, \"f0_resynthesized_wavs\", \"oranges_to_pickles_1.wav\"),\n",
    "                                     join(outputPath, \"oranges_to_pickles_1.PitchTier\"),\n",
    "                                     praatEXE, minPitch,\n",
    "                                     maxPitch, forceRegenerate=True)\n",
    "\n",
    "print(\"Let's take a look at the output:\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The original audio file:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 242904 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The target audio file:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 158872 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Morphed without textgrids:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 242904 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Morphed with textgrids:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 242904 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "displayAudio((\n",
    "              (\"The original audio file:\", join(inputPath, \"oranges.wav\")),\n",
    "              (\"The target audio file:\", join(inputPath, \"pickles.wav\")),\n",
    "              (\"Morphed without textgrids:\", join(outputPath, \"f0_resynthesized_wavs\", \"oranges_to_pickles_1.wav\")),\n",
    "              (\"Morphed with textgrids:\", join(outputPath, \"f0_resynthesized_wavs\", \"oranges_to_pickles_with_textgrids_1.wav\")),\n",
    "              ))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Hear the difference on \"he said\" between the last two files?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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oUe2VXcdp7exhzRALMfSJCbfT4zC0dfW6KTKllCZHyu/lH62nu9ewYgDzjfokROlaR0qp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\nzF1LON+NRQn6ijIcqWlldop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3Istr9//wSC0ldW18/RLvL3PhC9pzpNTQBfag23O4dEYi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\nZgGzALKzsz0bqVKnK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      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d8eea04cc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, plotList = plt.subplots(2, 2, figsize=(14, 6))\n",
    "\n",
    "doPlot(plotList[0][0], 'Original pitch', join(outputPath, \"oranges.PitchTier\")) \n",
    "doPlot(plotList[0][1], 'Target pitch', join(outputPath, \"pickles.PitchTier\")) \n",
    "doPlot(plotList[1][0], 'Morphed without textgrids:', join(outputPath, \"oranges_to_pickles_1.PitchTier\"))\n",
    "doPlot(plotList[1][1], 'Morphed with textgrids:', join(outputPath, \"oranges_to_pickles_with_textgrids_1.PitchTier\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With the the textgrid method, we get the target pitch over the first portion \"she like's oranges\" but we get the original pitch of \"he said\".  Cool!\n",
    "\n",
    "One thing you might have noticed.  There is some funky pitch over the region 'he said' in the pitch track for \"Morphed without textgrids.\"  It doesn't correspond to the target or source pitch.  I was surprised myself--but I opened it up in praat to see what was going on.  There isn't a lot of voicing in that region and the pitch tracker seemed to struggle a bit.  I'd chalk it up to a pitch error.  Going into more detail about pitch errors is the topic for another tutorial."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "<a id='intermediate_morphing'></a>\n",
    "### Intermediate morphing\n",
    "\n",
    "So far, we've looked at examples that replace the source pitch contour with the target pitch contour.  But what if we wanted something inbetween the source and the target?  It might be difficult to think of a situation where we would want such recordings but such 'intermediate' output is commonly used in speech perception experiments.\n",
    "\n",
    "Earlier we used the code snippet:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "stepList = [1.0, ]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Values in stepList should range between 0.0 and 1.0 where 0.0 means the output will have a contour that is 100% from the source file and 1.0 means the output will have a contour that is 100% from the target file.  One output file will be generated for each step in the stepList.\n",
    "\n",
    "Let's see an example:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's take a look at the output:\n"
     ]
    }
   ],
   "source": [
    "# We'll use the same setup as in the previous example, which used textgrids\n",
    "stepList = [0.0, 0.33, 0.66, 1.0]\n",
    "minPitch = 75\n",
    "maxPitch = 350\n",
    "\n",
    "\n",
    "fromPitchTier = pitch_and_intensity.extractPitchTier(join(inputPath, \"carrots1.wav\"),\n",
    "                                                     join(outputPath, \"carrots1.PitchTier\"),\n",
    "                                                     praatEXE, minPitch,\n",
    "                                                     maxPitch, forceRegenerate=True)\n",
    "\n",
    "toPitchTier = pitch_and_intensity.extractPitchTier(join(inputPath, \"carrots2.wav\"),\n",
    "                                                   join(outputPath, \"carrots2.PitchTier\"),\n",
    "                                                   praatEXE, minPitch,\n",
    "                                                   maxPitch, forceRegenerate=True)\n",
    "\n",
    "tierName = \"words\"\n",
    "fromTGFN = join(inputPath, \"carrots1.TextGrid\")\n",
    "toTGFN = join(inputPath, \"carrots2.TextGrid\")\n",
    "fromPitchRegions = f0_morph.getPitchForIntervals(fromPitchTier.pointList, fromTGFN, tierName)\n",
    "toPitchRegions = f0_morph.getPitchForIntervals(toPitchTier.pointList, toTGFN, tierName)\n",
    "\n",
    "########\n",
    "# STEP 4: Run the morph process\n",
    "f0_morph.f0Morph(fromWavFN=join(inputPath, \"carrots1.wav\"),\n",
    "                 pitchPath=outputPath,\n",
    "                 stepList=stepList,\n",
    "                 outputName=\"carrots1_to_carrots2_morph\",\n",
    "                 doPlotPitchSteps=False,\n",
    "                 fromPitchData=fromPitchRegions,\n",
    "                 toPitchData=toPitchRegions,\n",
    "                 outputMinPitch=minPitch,\n",
    "                 outputMaxPitch=maxPitch,\n",
    "                 praatEXE=praatEXE,\n",
    "                 keepPitchRange=False,\n",
    "                 keepAveragePitch=False)\n",
    "\n",
    "# And we'll go ahead and extract the pitchTier now\n",
    "pitch_and_intensity.extractPitchTier(join(outputPath, \"f0_resynthesized_wavs\", \"carrots1_to_carrots2_morph_0.wav\"),\n",
    "                                     join(outputPath, \"carrots1_to_carrots2_morph_0.PitchTier\"),\n",
    "                                     praatEXE, minPitch,\n",
    "                                     maxPitch, forceRegenerate=True)\n",
    "\n",
    "pitch_and_intensity.extractPitchTier(join(outputPath, \"f0_resynthesized_wavs\", \"carrots1_to_carrots2_morph_0.33.wav\"),\n",
    "                                     join(outputPath, \"carrots1_to_carrots2_morph_0.33.PitchTier\"),\n",
    "                                     praatEXE, minPitch,\n",
    "                                     maxPitch, forceRegenerate=True)\n",
    "\n",
    "pitch_and_intensity.extractPitchTier(join(outputPath, \"f0_resynthesized_wavs\", \"carrots1_to_carrots2_morph_0.66.wav\"),\n",
    "                                     join(outputPath, \"carrots1_to_carrots2_morph_0.66.PitchTier\"),\n",
    "                                     praatEXE, minPitch,\n",
    "                                     maxPitch, forceRegenerate=True)\n",
    "\n",
    "pitch_and_intensity.extractPitchTier(join(outputPath, \"f0_resynthesized_wavs\", \"carrots1_to_carrots2_morph_1.wav\"),\n",
    "                                     join(outputPath, \"carrots1_to_carrots2_morph_1.PitchTier\"),\n",
    "                                     praatEXE, minPitch,\n",
    "                                     maxPitch, forceRegenerate=True)\n",
    "\n",
    "print(\"Let's take a look at the output:\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The original audio file:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 218672 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The target audio file:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 199852 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "100% source, 0% target:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 218672 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "60% source, 30% target:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 218672 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30% source, 60% target:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 218672 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0% source, 100% target:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 218672 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "displayAudio((\n",
    "              (\"The original audio file:\", join(inputPath, \"carrots1.wav\")),\n",
    "              (\"The target audio file:\", join(inputPath, \"carrots2.wav\")),\n",
    "              (\"100% source, 0% target:\", join(outputPath, \"f0_resynthesized_wavs\", \"carrots1_to_carrots2_morph_0.wav\")),\n",
    "              (\"60% source, 30% target:\", join(outputPath, \"f0_resynthesized_wavs\", \"carrots1_to_carrots2_morph_0.33.wav\")),\n",
    "              (\"30% source, 60% target:\", join(outputPath, \"f0_resynthesized_wavs\", \"carrots1_to_carrots2_morph_0.66.wav\")),\n",
    "              (\"0% source, 100% target:\", join(outputPath, \"f0_resynthesized_wavs\", \"carrots1_to_carrots2_morph_1.wav\")),\n",
    "              ))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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EZJ3t61zgWWCiiOwAJti+hza2uN6Hy3cREeDN+D6RJz+4AYld/NmWU6yT75RSSiml2onn\n5m2ltKKa928YTkSAT6POcXMT4sL8SM/TEUWu5rBFYI0xiwFpYPf4eo5vM4vrZR0oY8H2PO4e27NR\n6xo1JDEygOJy6+S7Lp0b959HKaWUUkq1TuuyDvHFur3cNbbnkXlEjZUQ7sfGPYUOikw1llOq1bU3\nn6zcjQCXD2/ekLpaibaiDNu0Yp1SSimlVJtmjOHpbzYT5u/NbWN6NPn8hDA/sg6UUVltcUB0qrE0\nOWqiymoLs1ZmM653BN2COrXoWolasU4ppZRSql34fuN+Vu06yENnJuLv3fTBWQnhflgM7D6g845c\nSZOjJpq/OYf8kgquGtG9xdcK8fMizN+brZocKaWUUkq1aa8vSCMx0p/LUmJOfnA94sNs5by1Yp1L\naXLURB+t2EW3oE6MTrTPGksp3YP5bXseNRYtyqCUUkop1RYVlVexcW8h5/SLwt2toSn3J3aknLdW\nrHMpTY6aICO/lCU7C5g6PKbZP/jHunBQV/JLKliaVmCX6ymllFJKKedavesgxsCI+JBmX6NzJ0/C\n/L3I0J4jl9LkqAk+XrEbDzdhSjO7S+szrncE/t4efLmu1a53q5RSSimlTmBFxgE83ITBscEtuk58\nmB/p+VrO25U0OWqkiuoa5qzKYmJyJBGB9iu77ePpzll9uzBv437Kq2rsdl2llFJKKeUcKzMO0K9b\nZzp5ubfoOglh/roQrItpctRIP27K4WBZFVeOaFn57vpMGtSV4opqFmzLs/u1lVJKNUxE3hWRXBHZ\neMz2u0Vkq4hsEpHn6mx/VER2isg2ETnL+RErpVqb8qoa1mcXtmhIXa34cD/ySyopPFxlh8hUc2hy\n1EhfrN1DVGcfTu0RZvdrn9IjlDB/b75K1aF1SinlZNOBs+tuEJGxwCRgoDGmL/CCbXsycAXQ13bO\nayLSssfESqk2b13WISprLAyLa3lylGAryqC9R66jyVEjHCit5LfteVw4sCtudirEUJeHuxvnD4ji\npy25lFVW2/36Siml6meMWQgcOGbz7cCzxpgK2zG5tu2TgE+MMRXGmAxgJzDcacEqpVqllRnWXyEp\ncS2bbwTWtY4A0vN03pGraHLUCN9u2Ee1xTBpUDeH3WN4fAiV1Ratba+UUq6XCJwuIstF5DcRGWbb\n3g3IqnNctm3bUUTkFhFZJSKr8vJ0uLRS7d2KzAMkRQYQ5OvV4mvFhvjh7iakaXLkMpocNcIXa/eQ\nGOlPn6gAh90jLtT6pCCzQJMjpZRyMQ8gBBgJPAzMFpFGDxswxkwzxqQYY1LCw+2zJp5SqnWqrrGw\nZtdBhtthvhGAl4cbPcP92by3yC7XU02nydFJZB0oY/Wug1w0uBtNaBubLC7MF4BMHWOqlFKulg18\nZqxWABYgDNgD1F3LIdq2TSnVQW3eV0RpZQ3D7JQcAfTtGsgmTY5cRpOjk6hdf+jCgV0deh9fLw8i\nA73JyC9z6H2UUkqd1BfAWAARSQS8gHzgK+AKEfEWkXigF7DCZVEqpVzu4xW78XJ345QeoXa7ZnLX\nQHKLK8grrrDbNVXjaXJ0AtU1Fj5ZmcWI+BCig30dfr+4UD8dVqeUUk4kIh8DS4EkEckWkZuAd4EE\nW3nvT4DrbL1Im4DZwGZgHnCnMUYXqFOqg8o+WMacVdlcPiyGMH9vu123b9fOAGzaW2i3a6rG83DU\nhUXkXeB8INcY08+2bRaQZDskCDhkjBkkInHAFmCbbd8yY8xtjoqtsb7fuJ/sg4f50/nJTrlffJgf\n8zfnOOVeSimlwBgztYFdVzdw/DPAM46LSCnVVry2IA0RuH1MD7teNzkqEIBNe4sYkxRh12urk3NY\ncoR17YhXgBm1G4wxl9e+FpEXgbopcZoxZpAD42kSYwzTFqaTEObHxD6RTrlnXJgfBaWVFJVXEejj\n6ZR7KqWUUkqpptlz6DBzVmUxJSWGrkGd7Hrtzr6eRAd3YvM+nXfkCg4bVtfA2hEA2Kr+TAE+dtT9\nW2ppegEb9hRy8+kJDlnbqD5HKtZpUQallFJKqVbrjQVpANwxtqdDrt+3a6BWrHMRV805Oh3IMcbs\nqLMtXkTW2taUON1FcR3x1sJ0wvy9uGSI49Y2Ola8roqslFJKKdWq7Ss8zKyVWUweGkM3O/ca1erb\ntTMZ+aWUVFQ75PqqYa5KjqZydK/RPiDWGDMYeAD4SEQC6zvRGYvrpeeV8Ou2PK4dFYePp7tD7lGf\n7qG15by1Yp1SSimlVGv0xoI0LMZwh53nGtXVt6v1Y/AWHVrndE5PjkTEA7gEmFW7zRhTYYwpsL1e\nDaRhXaH8OM5YXG/2qmzc3YQrhsec/GA78vF0p2tnH61Yp5RSSinVCuUUlfPxyiwuHRJNTIjjKhkf\nqVi3RyvWOZsreo4mAFuNMdm1G0QkXETcba8TsK4dke6C2KiusTB3TTZjkyKICPBx+v3jwvx0WJ1S\nSimlVCv0+oI0aiyGOx0016hWZKA3IX5euhisCzgsOWpg7QiAKzi+EMNoYL2IrAM+BW4zxtRbzMHR\nFmzLI6+4gsuHObfXqFZcmK51pJRSSinV2uQWlfPxit1cMrgbsaGOXf9SRKxFGXRYndM5rJR3Q2tH\nGGOur2fbXGCuo2Jpilmrsgjz92ZMkmOG7J1MfKgfh8qqOFRWSZCvl0tiUEoppZRSR3tzYTrVFsNd\n4xzba1QruWsg7y7OoKrGgqe7q8oEdDz6N11HbnE5v2zN5dKh3Vz2QxinFeuUUkoppVqVvOIKPly+\ni4sGdaO7bekVR4sK9KGqxlBcrhXrnEmTozq+XLuXGothSoprhtQBxIfZKtbp0DqllFJKqVZh2sI0\nKqstTus1AvDztg7wKtVy3k6lyVEdP27eT3JUID3C/V0WQ0yIL/7eHsxZlY3FYlwWh1JKKaWUgvyS\nCmYu28WkQd2OrEnpDEeSo0pNjpxJkyObgpIKVu86yMTkSJfG4e3hzuPn9eH3tAJmLM10aSxKKaWU\nUh3dWwvTnd5rBNpz5CqaHNn8sjUXi8HlyRHAFcNiGJsUzj++30paXomrw1FKKaWU6pAKSiqYsXQX\nFwzs6vSRRX5e7gCUVtQ49b4dnSZHNj9tyaFLoM+RFYldSUT456UD6OTlzgOzU6musbg6JKWUUkqp\nDuftxRmUV9dwt5N7jUB7jlxFkyOgvKqGhdvzmZAcgYi4OhwAIgJ9+NukfqRmHeKN39JcHY5SSiml\nVIdysLSSGb9ncv6ArvSMCHD6/f28auccac+RM2lyBCxNK+BwVQ0Tk7u4OpSjXDCwK+cPiOLfP+1g\n455CV4ejlFJKKdVhvL04nbIq1/QaAfh51w6r054jZ9LkCJi/JQc/L3dGJoS4OpTj/G1SP0L8vHhw\ndioV1frkQCml7ElE3hWRXBHZWM++B0XEiEiY7XsRkZdFZKeIrBeRIc6PuOkKSiqYuTSTN35L4+Wf\nd7BlX5GrQ1Kq1TtUVsn7v+/i3H5RJEY6v9cItFqdq3T45Ki6xsL8zTmMTgzH28Pd1eEcJ9jPi39e\nOoBtOcW8NH+7q8NRSqn2Zjpw9rEbRSQGOBPYXWfzOUAv29ctwOtOiK/ZjDF8s34vE/+1kD99uYln\nv9/KS/O3c9Xby8ktLnd1eEq1au8szqCkopq7x7um1wjA28MNdzfRniMn6/DJ0YJteeQVV3DR4G6u\nDqVBY3tHMHV4DNMWprMq84Crw1FKqXbDGLMQqO8X67+APwJ1F5ybBMwwVsuAIBGJckKYTWaM4aE5\n67nro7XEBHfim7tPY/Nfz2LefadTWlHNI5+uxxhdS0+p+hSWVTF9SSbn9OtC7y6uK9QlIvh6uWu1\nOidrdHIkIhEicrGI3CkiN4rIcBFp88nVrFVZhPl7M653hKtDOaHHz0smOrgTD85J1ScISilVD3u1\nUyIyCdhjjEk9Zlc3IKvO99m2bceef4uIrBKRVXl5eU29vV38ui2XuWuyuWV0AnNvP4V+3Trj6+VB\n7y6BPHpOb37dlsfMZbtcEptSrd27SzIorqjm7nG9XB0K/t4e+rnPyU7aaIjIWBH5AfgW65CCKCAZ\neALYICJPiYjr6183Q25xOb9szeXSId3wdG/deZ6/twcvTB7I7gNl/P27La4ORymlWg17tlMi4gs8\nBjzZ3HiMMdOMMSnGmJTw8PDmXqbZaiyGZ7/fSnyYHw+flYTHMe3bdafEcUZiOM98u4WsA2VOj0+p\n1qzwcBXvLsngzORIklvB8i6+Xu6UabU6p/JoxDHnAn8wxuw+doeIeADnAxOBuXaOzeE+X7OHGovh\nspQYV4fSKCMSQrn5tHjeWpTBmX27cEai8xtdpZRqhezZTvUA4oFU29IO0cAaERkO7AHqNhjRtm2t\nytzV2WzPKeG1q4bU++BPRPj7Jf0Z/dyvfLB8F4+e08cFUSrVOk1fkklxeTX3jHd9rxFYH46XaM+R\nU520u8QY83B9DY5tX7Ux5gtjTJtLjIwxzFqVRUr3YHpGOHfF45Z48MwkekX488dPUyksq3J1OEop\n5XL2bKeMMRuMMRHGmDhjTBzWoXNDjDH7ga+Aa21V60YChcaYffZ6H/ZwuLKGl+ZvZ1BMEOf0a3h5\nim5BnZjYJ5LZK7Mor9Kn0koBFJVX8c7idCb0iaRft86uDgcAXy8PyrRanVM1Zc5RjYg8K3VWSRWR\nNY4Jy/FW7zpIel4pU4a1jV6jWj6e7rw0ZRAFJZX8+avjKs8qpVSH1Zx2SkQ+BpYCSSKSLSI3neDw\n74B0YCfwFnCHHcK2q5nLMtlfVM6j5/Q+6aLm147qzsGyKr5Z36ryO6VcZsbvmRSVV3NvK+k1Ams5\n7xItyOBUTZlos8l2/I8iUrsgUIO/eetbO0JE/iIie0Rkne3r3Dr7HrWtHbFNRM5q6htpqhA/L64e\nGct5/VtloaET6h/dmbvG9eSLdXv5boM2akopZdOkdgrAGDPVGBNljPE0xkQbY945Zn+cMSbf9toY\nY+40xvQwxvQ3xqxyyLtoporqGt5elMEpPUIZkRB60uNH9QilR7gfM5dmOjw2pVq7kopq3l6cwfje\nEfSPbh29RmBdCFZ7jpyrKclRtTHmj8DbwCIRGcrRJU6PNZ161o4A/mWMGWT7+g5ARJKBK4C+tnNe\nExGHLjqUEO7P0xf1P7LAVltz59ieDIjuzOOfb9D1KpRSyqqp7VS78uXaveQWV3DbGT0adbyIcM3I\n7qRmF5KadcjB0SnVur3/eyaHyqpazVyjWn5arc7pmpIcCYAxZhZwOfAekNDQwSdYO6I+k4BPjDEV\nxpgMrEMWhjchtg7H092Nl6YMpLSyhsc+26DrVSilVBPbqfbEYjG8sTCN5KhATu8V1ujzLhkaja+X\nu5b1Vh1aaUU1by9KZ0xSOANjglwdzlH8dJ0jp2tKcnRz7QtjzEbgdOCeZtzzLhFZbxt2F2zb1qi1\nI6B1rB/RWvSMCOCPZyXx05Zc5qzOdnU4SinlavZqp9qcn7bkkJ5Xyq1nJJx0rlFdgT6eXDiwK99t\n2KdPp1WHNWPpLg6WVbWquUa1/Lw9OFxVQ41FH4I7S6OTI2PMahE5RUSuFJFrsfb2NNXrWMukDgL2\nAS829QKuXj+itbnx1HhGxIfw1683k31Q16tQSnVcdmqn2qQ3fksjOrhTs+bRXjo0mrLKGr7fuN8B\nkSnVupVWVPPWonRGJ4YzODb45Cc4mZ+XdfqHzjtynqZUq5sJvACcBgyzfaU05WbGmBxjTI0xxoK1\n0k/t0Lk2sXZEa+TmJrxw2UCMMTw0JxWLPllQSnVQ9min2qKNewpZs/sQN54af9yCr42R0j2Y2BBf\n5uoIBNUBfbh8FwdKK1tlrxFwZG68Dq1znqZUI0gBkk0LJreISFSdNSEuBmor2X0FfCQiLwFdgV7A\niubep6OJCfHlyQuSeWTuBqb/nsmNp8W7OiSllHKFFrdTbdHsVVl4ebhx6ZDoZp0vIlwypBv//mkH\n2QfLiA72tXOESrVOhytrmLYwndN7hTG0e+vrNQJrtTqAUu05cpqmPGLaCDS8otwxGlg74jkR2SAi\n64GxwP0AxphNwGxgMzAPuNMYoylyE0xJiWFc7wj+OW8rO3NLXB2OUkq5QpPaqfagvKqGz9fu4Zx+\nXejs69k+sU+4AAAgAElEQVTs69QmVl+s1UEbquP4cPku8ktab68R/G9Ync4JdJ6T9hyJyNdYS6EG\nAJtFZAVQUbvfGHNhfecZY6bWs/mderbVHv8M8MzJ4lH1ExGevaQ/Z/57IQ/OXsfc209p1vAKpZRq\na5rbTrUH32/cR3F5NZe3cEHzmBBfhseHMHfNHu4c27NJRR2UaosOV9bwxm/pnNIjlJS4kJOf4CK+\ntT1HOqzOaRozrO4Fh0eh7CIi0IenL+rHXR+t5bUFaa2uVr9SSjlIh22nZq3MIjbEl5HxJ1/09WQm\nD4nmj3PXk5pdyKBWVs5YKXv7aMVu8ksqePXKwa4O5YT8vbXnyNkakxwtPNn4bRGRjjbGu7U6f0BX\nftyUw8s/72Bc7wj6dWs9qzwrpZSDdMh2KiO/lGXpB3j4rCTc3Fre0zOuTwQAy9MLNDlS7Vp5VQ1v\n/JbGyIQQRiS0/MGCI/nWDqvTOUdO05hxV7+KyN0iElt3o4h4icg4EXkfuM4x4anm+OukvoT4efHA\n7HWUV2k3rFKq3euQ7dQnK3bjJjB5aPMKMRwrzN+b7qG+rNl90C7XU6q1+mTFbvKKK7h3fKKrQzkp\nf61W53SNSY7OBmqAj0Vkr4hsFpEMYAcwFfi3MWa6A2NUTRTk68U/Jw9ge04J/5q/3dXhKKWUo3W4\ndqqovIqPlu/mnH5RRAb62O26Q2KDWbP7EO2sk02pI8qranj9tzSGx4cwqkfr7jWC/8050nWOnOek\nw+qMMeXAa8BrIuIJhAGHjTGHHB2car6xSRFMHR7LtEXpjO8TyfD41jvZUCmlWqIjtlMfLd9NcUU1\nt53Rw67XHRIbxOdr95B98DAxIVrSW7U/s1dlkVNUwUtTBrk6lEaprVZXonOOnKZR5czEagRwATAK\na3luLWXTyj1xXh9ign15aE6qTuRTSrVrHamdqqiu4d3FGZzaM5T+0fadVzrEttaLDq1T7VFFdQ2v\nL0gjpXswp7SBXiMAdzfBx9ONskodVucsJ02ORORMrEMT/gKca/t6Cthh26daKT9vD164bCBZB8t4\n5rstrg5HKaUcoqO1U5+v2UNucYXde40AkiID8PVyZ80uTY5U+zN7VTb7Csu5d0KvNlWu3t/bQ3uO\nnKgx1er+A0wwxmTW3Sgi8cB3QB8HxKXsZHh8CH84PYFpC9OZmBzJ2KQIV4eklFL21mHaqaoaC9MW\nptO3ayCn9Qyz+/U93N0YGB3Emt3tdkSi6qAqqy28/utOhsQGOeT/jiP5enlQpsmR0zRmWJ0HkF3P\n9j1A85fjVk7zwMREEiP9eeTT9Rwqq3R1OEopZW/NbqdE5F0RyRWRjXW2PS8iW0VkvYh8LiJBdfY9\nKiI7RWSbiJxlt3fQCMYYnvh8I+n5pdw73nFPvod0D2LzviKdAK7soryqhs/WZLv85+nT1dnsLSzn\n3gmJbarXCKwjgUq0Wp3TNCY5ehdYKSKPiMiVtq9HgOXAO44NT9mDj6c7L00ZxIHSSp78cpOrw1FK\nKXtrSTs1HWu1u7rmA/2MMQOA7cCjACKSDFwB9LWd85qIuNvvbZzYawvSmLUqi7vH9eTMvl0cdp+h\n3YOpsRjWZxc67B6qYzDG8PjnG3lgdio3vLfSZQlSZbWFV3/dyaCYIEb3alu9RgB+Xu4uTy47kpMm\nR8aYfwBXAoJ1kuso2+urbPtUG9CvW2fuGd+Lr1L38u36fa4ORyml7KYl7ZQxZiFw4JhtPxpjaj+J\nLANqFxKaBHxijKkwxmQAO4HhdnsjJ/Dluj08/8M2Jg3qygMTHbs2y+AYLcqg7GPWyizmrslmXO8I\nVmYe4Pr3VrqkQNRna7LZc+iwQ3tcHcnP20MLaznRSecciUisMWYLoDP627g7xvTg5y05PPHFBobF\nBxMRYL+1MZRSylUc3E7dCMyyve6GNVmqlW3bdmw8twC3AMTGxh67u8kW7cjjoTmpjIgP4bnJAxz+\n4S7Yz4uEMD/W7NJ5R6r5Nu4p5MmvNnF6rzDeujaF7zbs475Z67h/1jqmXZvitDiqaiy88utOBkR3\nZkxSuNPua09+3u7sOaTD6pylMcPqvqh9ISJzHRiLcjAPdzdenDKIssoaHp27QRf5U0q1Fw5pp0Tk\ncaAa+LAp5xljphljUowxKeHhLfswlpp1iFtnrqZHuD/Trk3B28M5o/gGxwazdvdBbSdUsxQeruKO\nD9cQ4uvFvy8fhLubcMHArtw5pgc/bs4h60CZ02KpXberrfYagXWtI+05cp7GJEd1f5ISHBWIco6e\nEf788eze/Lw1l9mrslwdjlJK2YPd2ykRuR44H+vQvNoMYQ8QU+ewaNs2h0jPK+GG6SsJ9fdixo3D\n6dzJeTWQhnYPpqC0kl0FzvsQq9oHi8Xw4OxU9h46zKtXDSHU3/vIviuGxyKC0z5/VNdY5xr179aZ\ncb3bbrVeHVbnXI1JjkwDr1UbdcMpcYxMCOGvX2926tMbpZRyELu2UyJyNvBH4EJjTN1fkl8BV4iI\nt61MeC9gRUvv15AAH0/6devMjBtHEBHo3GHQQ7pbC/TpvCPVVNMWpfPTlhweO7cPQ22LCtfqGtSJ\nMxLDmbMqmxqL4z9SfrFuL7sKyrinDfcagXVYXWlljfbkOkljkqOBIlIkIsXAANvrIhEpFpGihk5q\nSnlUEYkTkcMiss729UbL35pqiJub8MJlAxERHpqTisUJv6CUUsqBmtVOAYjIx8BSIElEskXkJuAV\nIACYX7dNMsZsAmYDm4F5wJ3GGIdNBAgP8GbGjcOJD/Nz1C0a1CsiAH9vD02OVJMsSy/guXlbOa9/\nFDecGlfvMZenxLC/qJyF2/McGkt1jYVXftlBclQgE/q03V4jsK5zVGMxVFRbXB1Kh9CYanXuxphA\nY0yAMcbD9rr2+8ATnDqdRpZHtUkzxgyyfd3W1DeimiY62Jcnz09mecYB3vs909XhKKVUs7WgncIY\nM9UYE2WM8TTGRBtj3jHG9DTGxNTXJhljnjHG9DDGJBljvnf8u3MNdzdhUEyQFmVQjZZbVM5dH60l\nLtSPZy/t32BPzfg+kYT6eTFrpWOH1n2VupfMdtBrBODvba2fpkPrnKMxPUfN0sTyqMoFLkuJZnzv\nCP45bys7c4tdHY5SSqlWZEj3YLbuL9IPZOqkqmss3PXxWkorqnn96qEE+DQ8P87Lw41Lh0bz05Yc\n8oorHBJPjcXwyi876d0lgDOTIx1yD2fy9bIWYimr1Ip1zuCw5KgRbgTqPnWLF5G1IvKbiJze0Eki\ncouIrBKRVXl5ju2Sbe9EhH9c2h8/L3cemJ1KVY121yqllLIaEhuExVgr5il1Is//uI0VGQd45uJ+\nJHUJOOnxU1JiqLYYvljrmHom36zfS3p+KfeO74WbW9vuNYL/9RyV6IMKp3BJclRPedR9QKwxZjDw\nAPCRiNQ7FMKeJVIVRAT48MzF/VmfXchrv6a5OhyllFKthC4Gqxrjx037efO3dK4cEcslQxo3IKhn\nhD+DYoKYuybb7kUGaiyGl3/eQVJkAGf17WLXa7uKry05KqvU5MgZnJ4c1Vce1bbaeIHt9WogDXDs\nEuDqiHP7RzFpUFf++8sONmQXujocpZRSrUBnX096RvizZnfze45WZR5g76HDdoxKtSa7Ckp5cE4q\n/bt15snzk5t07qVDo9m6v5hNe09YM6XJvt2wj7S8Uu5pJ71GAP7e1mF1JRU6rM4ZnJocNVQeVUTC\nRcTd9joBa3nUdGfG1tH99cJ+hPp78cDsdZRX6X8+pZRSMDQ2mDXNWAw260AZf5ixislvLGXqW8so\nPFzloAiVq5RX1XD7B2twE+G1q4bg49m0BYovGBCFl7sbn67OtltMFovhvz/voFeEP+f0ax+9RmCt\nVgdQpsPqnMJhyVFTyqMCo4H1IrIO+BS4zRhzoN4LK4fo7OvJPy8dwI7cEl78cZurw1FKKdUKDOke\nxKGyKtLzS096bHWNhcU78vnjp6lM/NdvLN6Rzw2nxrHn4GEempOqa7S0M3/5ahOb9xXxr8sHEhPi\n2+Tzg3y9mJAcwVepe6m0U4nq7zbuY0duCXe3o14j0DlHzubhqAsbY6bWs/mdBo6dC8x1VCyqccYk\nRXDViFjeXpzBhD6RjEgIdXVISimlXGhIrG3e0a6D9Aj3b/C4pWkFPPxpKtkHD+Pv7cEFA7py/8RE\nugZ1IjrYl799s5k3F6Zz2xk9nBW6cqA5q7L4ZGUWd47twbjeza8GN3loNN9t2M+Cbbmc2cL5QdZe\no530CPfjvP5RLbpWa6PV6pzLldXqVCv02Ll9iAn25aFPU/UJhVJKdXA9wv0J9PFocN5RRXUNf/9u\nC1e+vQxPdzdeu2oIq56YwPOXDaRrUCcAbjw1jvP6R/HcvK0sTStwZvjKATbvLeKJLzYyKiGU+ye0\nbHr46F7hhPl7M8cOQ+t+2LSfbTnF3DO+F+7tqNcIwE97jpxKkyN1FD9vD16cMpDsg4d55tstrg5H\nKaWUC7m5CYNjg1lbT8U6i8Vw90drmbYwnSuHx/LtPadxbv+o4+aeiAj/nDyAuDA/7v54LblF5c4K\nX9lZUXkVd3y4ms6dPHl56mA83Fv2MdLD3Y0rhsUwf3MOq3c1vyqixWL4z887SAj34/wBXVsUU2vk\n7eGGu5uQV1zBb9vzmLva/lX+1P9ocqSOMywuhFtOT+DjFbv5dWuuq8NRSinlQkNig9mWU0xR+dFF\nFZ77YRs/bs7hyfOTeebi/kcmjdfH39uDN64eSmlFNXd+tEbX1WuDjDH8cc56sg4e5tWrhhAe4G2X\n694+pgddAn144ouNVDfz5+LHzTls3V/M3eN6trteI7A+YPDzcmf675lc9+4KHpyTyq/b9POZo2hy\npOp1/8REkiIDeGTueg6VVbo6HKWUUi4ypHsQ5pjFYD9dnc0bv6Vx1YhYbjg1rlHXSYwM4NlL+7My\n8yDPzdvqoGg7nkNllU5JNt9ZnMG8Tfv5v7N7MywuxG7X9fP24M8XJLNlXxHvL93V5PONsa5rFBfq\nywXtsNeo1sNnJXH3uJ7MuHE4kYHevLck09UhtVuaHKl6+Xi68+KUgRworeRPX25ydThKKaVcZFBM\nECKwZpc1OcotLuexzzdwSo9Q/nJhX0Qa/6R+0qBuXDeqO28tyuD7DfscFXKH8d2GfZzy7C9c/uZS\nissdVy59ZeYB/vH9Vs7qG8nNp8fb/fpn9+vCmKRwXvpxG2ubWDp+/uYcNu8r4q5xvVo8zK81u2ZU\nHA+emcToxHCuGdmdRTvy2Zlb7Oqw2qX2+1OkWqxft87cO74XX6fu5evUva4ORymllAsE+HiSFBnA\nGtu8ozmrsqmstvD0Rf3wbMaH0cfPS2ZQTBAPf7qe9LwSe4fbIdRYDM//sJU7PlxDbIgv67MLufbd\nFccNfbSHvOIK7vxwDTHBnXj+soFNSoYbS0R46sK+uLkJF7/2O2NfWMCjn63noTmp3PPxWn7fmV/v\necYYXv5lB91DfbloUPvtNTrW1OGxeHm4Mf33TACqaixs2lvo2qDaEU2O1AndPqYHA2OC+NOXG3US\nrVJKdVC1RRmqayx8vGI3oxJCSThBae8T8fKwVrXzdBdu/2ANZZVagaspCg9XcfP7K3n11zSuGBbD\nl3edyqtXDWHjnkKueXu5XRfcrbEY7v1kLYWHq3jtqqEE+nja7drH6h7qx6I/juXZS/oTHezLD5ty\n+H1nPot35nPdeyv4qp6HtL9szWXjniLuHNuzXfcaHSvU35tJA7syd/UeVmUe4OLXlnDey4vZuEcT\nJHvoOD9Jqlk83N148bKBHK6s4ZG567U6ilJKdUBDYoMoKq9m+u+ZZB88zJUjYlt0va5BnXh56mC2\n5xbz+OcbtW1ppB05xVz06hIW7cjn6Yv68Y9L+uPt4c5Zfbvw2lVD2byviGveWU5hmX0SpH/N387v\naQU8fVE/krsG2uWaJxLk68UVw2P54OYRrPnTRH5/dDy/PjSGwTHB3PvJWmYu+9+cJGOsFepiQjpx\n8eBuDo+ttbn+1DgOV9Uw+Y2lZORZF2neocPs7EKTI3VSPSP8+b9zevPrtjxmrcxydThKKaWcbGh3\n62KwL83fTqifF2e1cMFOgNN7hXP/hEQ+X7uHD5fvbvH12rsfNu3noleXUFxexUd/GMnVI7sfNcRt\nYnIkb14zlK37irnqnWUcLG1ZMaVftubwyq87uTwlhstSYloafrN17uTJjJuGM753BH/6YiMLbFXa\nFmzLY312IXeN7dms4Z1tXd+unbl0SDQXDOzK/AfOQAR2FZS5Oqx2oeP9NKlmuW5UHKMSQvnbN5vJ\nOqD/+ZRS7YOIvCsiuSKysc62EBGZLyI7bH8G27aLiLwsIjtFZL2IDHFd5M4VH+ZHsK8nZZU1TE6J\nxsvDPh8f7hrbkzFJ4fz1682sy6p/odmOzmIxvDR/O7fOXE3PCH++vvs0hsfXXy1uXO9I3rx2KNtz\nShjzwgL+/t2WZrXZWQfKuH9WKslRgTw1qW9L30KL+Xi688qVQ0iKDOChOevJL6ng3z/voFtQJy4e\nHO3q8FzmxSkD+e/UwXQN6kRUoA+79fOZXWhypBrFzU14/rIBiAgPzknFYtEhEEqpdmE6cPYx2/4P\n+NkY0wv42fY9wDlAL9vXLcDrTorR5USsi8ECTB3WsiF1dbm5Cf++fBDhAd7c+eGaFvd2tDfF5VXc\nMnM1L/+8g8lDo5l16yiiOnc64TljkyL47PZTOK1XGO8szmDMCwt4bt5WKqprGnXPiuoa7vhwDRZj\neP3qIcct6usqPp7uvDx1MEXlVUx5cympWYe4c2xPuyXqbV1MiK8+vLYT/YlSjRYd7MuTFySzIuMA\n7y7JcHU4SinVYsaYhcCBYzZPAt63vX4fuKjO9hnGahkQJCJRzonU9W47owd/Oj+ZuDA/u143yNeL\n168eQl5xBffOWkeNPnwDIC2vhIteXcKv23J56sK+PD95QKMTlX7dOvPqlUNY/MhYLhncjdcWpHF+\nIyfs//XrzWzYU8iLlw2ke6h9/61bKqlLAI+f24f0vFK6BXVi8tCO22t0rNgQX+05shNNjlSTXDY0\nmgl9Innuh23syNGJf0qpdinSGFO7CM9+INL2uhtQd+Jltm3bUUTkFhFZJSKr8vLyHBupEw2PD+Gm\n0+y/xg3AgOgg/nxhMgu35/HfX3Y45B5tyc9bcrjolSUcLKvig5tGcN0pcc0qoR3V2Vp+e/oNwygu\nr+b691acsHfu87XZfLh8N7eekcCZdphX5gjXjurOveN78dzkAdprVEdsiC85RRWUVzWuh1A1TH+q\nVJOICP+4pD/+3h48MDvVKatyK6WUqxhrGbUmdWUYY6YZY1KMMSnh4eEOiqz9uXJ4LJcM6cZ/ft5x\nZNJ9R2OxGP778w5unrGK7mG+fH33aYzqEdri645JiuDd64dxqKyKv32zud5jtucU89hnGxkeH8LD\nZya1+J6OIiLcPzGRU3uGuTqUViU21BdAh9bZgSZHqsnCA7x55qJ+bNhTyCu/7HR1OEopZW85tcPl\nbH/WflLfA9Qt2xVt26bsQER45qL+JEUGcN+sdWQfdM2HPGMMP27azwfLdvHR8t2syjx21KVjlFRU\nc/uHq3lx/nYuGtSNT287hW5BJ55f1BTJXQO5Y0wPPlu7h1+3Hp18llRUc9sHq/Hz9uCVqYM71JpB\n7UVMiDU50qF1LefQn36tAtR+ndM/iosGdeWVX3eyPlsrDCml2pWvgOtsr68Dvqyz/VpbezUSKKwz\n/E7ZQScvd16/eig1NYY7P1zT6CICxyqpqOazNdn8sGk/67IOUVnd+FEOn6zM4paZq3nii4089vkG\nrnx7ucMXQc/IL+XiV5fw05ZcnjivDy9NGeiQQgh3jutJYqQ/j32+4cjwOmMMj8xdT2Z+Ka9cOZiI\nQB+731c5XndNjuzG0Y8GpqNVgNqtpy7sR7i/Nw/MTtUxrkqpNklEPgaWAkkiki0iNwHPAhNFZAcw\nwfY9wHdAOrATeAu4wwUht3vxYX48f9lAUrMLGxwCdiI1FsMdH67hgdmp3DpzNRe9uoTLpy1tVDu1\n59Bhnvl2C6MSQlnx2Hi+uutUaiyGaQvTm/NWGuXXbblc+Mpi8ksqmHHjcG4+PaFZ84saw9vDnecm\nD6SgpJKLX1vCztwSpv+eybfr9/HwWb0ZmdDyIXzKNUL8vPDzcte1juzAocmRVgFq3zr7evLc5AHs\nzC3hhR+2uTocpZRqMmPMVGNMlDHG0xgTbYx5xxhTYIwZb4zpZYyZYIw5YDvWGGPuNMb0MMb0N8as\ncnX87dXZ/bpwy+gEPli2m8/XZjfp3H/N387C7Xk8eX4y39x9Gk9d2Je1uw/x6GcbsE4hq58xhv+b\nux6LMTw3eQARgT4MiA5i0sCufLh8NwUlFS19W8fd77UFO7lx+kqig3356q7TnDKPZlBMEB/fMoKS\nimoufnUJz3y7hQl9Irl1dILD760cR0S0nLeduGJQaYuqAKnWZXRiOFePjOWdJRksSy9wdThKKaXa\niT+elcTw+BAe/WwDW/cXNeqcHzbt55Vfd3J5Sgw3nBpHv26due6UOB6cmMjna/ecsAfovSWZLNqR\nz6Pn9jkyfwPgjrE9Ka+u4e3F9lvCorSimrs+Wstz87ZxXv8o5t4+6qh7OtrQ7iF8ceepRIf4EhPi\ny4uXDcTNzTG9Vcp5tJy3fXi48ubGGCMiTaoCJCK3YB12R2ys/RaiU8332Ll9WLQjn4fmpDLvvtH4\ne7v0x0oppVQ74OHuxitTB3Pefxdz+wdruGJYDLsOlFF4uAo/L3f8vT0ZGNOZMxLDsRj4z0/b+WD5\nbgZGd+apSX2PGpp217iebN1fzD++38oX6/YyOjGMcUkRpMSFYIzh2e+38vbiDMb1juCq4Ud/tugZ\n4c95/aOY8XsmN50WT5i/d4ve1+6CMm6ZuYrtOcU8ek5vbhntuGF0JxId7Mu3d59GlcWCt0frWOhV\ntUxsiC+/bc/DGOOSn6n2whWfYnNEJMoYs685VYCMMdOAaQApKSm6Ulwr4OvlwYuXDeSyN5fy9Deb\nefbSAa4OSSmlVDsQEejDK1MHc807K/jH91sJ9vUk2M+LsooaCg9X8e6SGtzdBG8PN8qrarhyRCwP\nTkw6rpiBiPDilIEMiO7Mr9tyeWdRBm/+lk6onxeRgT5s3lfEdaO688T5yfX2oNw9rhffbtjHiL//\nTGJkAH2iAujcyZNAH08uS4kmOrhxvT6LduRx10drAZh+w3BGJ7q21Lubm+DtpolRe9E91JeKagu5\nxRVEamGNZnNFclRbBehZjq8CdJeIfAKMQKsAtSkpcSHcOroHb/yWxpl9IxnXO/LkJynVRPsLy1mW\nXsC2nGIuGdyNXpEBrg5JKeVgIxJCWfn4BMQNAn08j2y3WAzrsg/x85Yccosq+MPoBBJP8DvBx9Od\nW8/owa1n9KCkoprftuUxb9N+NmQf4p+X9ufyYQ2PRknqEsDc209hwdZc1mYdYllaAcUV1ZRUVPPj\n5hy+uutUPE9Q/toYw1uL0nn2+630ighg2rVD6R7q17y/EKUaULectyZHzefQ5MhWBWgMECYi2cCf\nsSZFs20VgXYBU2yHfweci7UKUBlwgyNjU/Z3/8ReLNiWyyNzN/DjfcEE+3m5OiTVxuUUWZMh69cB\nMvJLj+x7Z3EGD05M5ObTE3DXsfJKtWudfT2P2+bmJgyJDWZIbHCTr+fv7cF5A6I4b0Dj6z7Vd695\nG/dz2wereXtRBreP6VHveYcra3hk7nq+St3Luf278Pzkgfjp8HPlALG1yVFBGcPiQlwcTdvl0P+d\nxpipDewaX8+xBrjTkfEox/L2cOfFKQO56NUlPPHlRl69UpeqailjDDUW02EW5PtfMnSA5ekFpNuS\noQAfD0bEh3DViFhGJoQSEeDNE19s5B/fb2Vl5gHevCZFEySllNOd3a8LZ/WN5N8/beecfl2ICzu6\nNyjrQBm3zlzNlv1FPHxWEneM6aFzQZTDdAvuhIiuddRS+uhC2VXfrp25d3wvXvhxO2f13cuFA7u6\nOqQ2aV/hYT5bs4e5q7Mprqhm/v2jCfJtfz1xuUXlLMs4wNK0gqOTIW8PhseHMHV4LKN6hNInKvC4\n5OfNa4by7pJM/vbNZp79fguPn5fsireglOrg/jqpHxNe/I3HPt/AzJtGHPldlZp1iOvfW0G1xfDu\n9cMYmxTh4khVe+ft4U5UoI8mRy2kyZGyu9vO6MFPW3L50xcbGREfouNeG6m8qoYfNu3n09XZLN6Z\njzEwtHswmQWlvPLLTp44v+1/+M8tLmdZ+oEjQ+XS8/6XDA2zJUMjE0JJ7np8MnQsEeGm0+LZXVDK\nW4sy6BUZwJSUmBOeo5RS9hYZ6MMT5/fhkbkbuG/WOl6aMpD0vFKue28FAT4ezLhxBPFhOr9IOUdS\nlwB+2pzDyswDOrSumTQ5Unbn4e7GS1MGcu7Li3hk7nreu36YDiNogDGGNbsP8enqbL5J3UtxRTXd\ngjpxz7heXDokmthQXx75dD3vL83k2lFxxIY6bx0Me8grrqgzZ6iANFsy5G/rGbpiWIw1GYoKbPbQ\nwT+dn0xaXimPf76B5KhA+nXrbM+34DKV1RZEOOEkb6VU63D5sFgOlFbxz3lbKSmvYtPeIrzc3fjw\nppFt7ve2atuevrg/17yznKvfXs7rVw/RAlnNICdaLbq1S0lJMatW6QLlrdX0JRn85evN/P3i/lw5\nQtekqmvvocN8vnYPn67OJiO/lE6e7pzbP4rJQ6MZER9yVCnZnKJyxjy/gHF9Ilr9PK684gqWZ/yv\ngMLO3BLAmgwNiwtmZEIoIxNC6du1+clQfQ6WVnLOfxbh6+XON/echq9X637uU15Vw8ylu5i2KJ3Y\nEF/un5DIqT1DjzxEyCuu4PJpS/H39mDWLaPo5NXyUrulFdVMW5jO52v3cP/EXlw8OLrF16wlIquN\nMf8mwxgAACAASURBVCl2u2A7ou1Ux/Lekgye+nozQb6ezL511Amr5ynlKAUlFdwwfSWb9hbx2e2n\nMDAmyNUhtQqNbas0OVIOY7EYrn5nOeuyDjHv3tFNfnpWUlHN6l0HKTxcRWW1BYsxeLoL4f4+R32Q\nbCsOV9bw4+ajh82NiA9h8tBozukfdcLFc/81fzv/+XkHs24ZyYiEUCdGfWL5JRUsrzNMboctGfLz\ncmdYfMiRZKifnZOh+vyels9Vby/n8pSYVrvWVnWNhc/W7OFfP21nX2E5p/QIJTO/lL2F5QyPD+H/\n2bvz8CrK64Hj35M9JJAAgbAkEJaw7yKCioiggvvWuvuzVal7q21dqrXa1bprrWtdqq1LVcQddwEV\nRPY1LGFNCCQBQhJC9vP7YyZ4iQm5gdzMvcn5PM99uHdm7syZSTKHd+ad8946pT/pyW254Ol5ZOYV\nU15VzalDu/KPC0ce8u+7qvLmwiz+PnMN+cVlpLSPJWv3Pi46qge/nJROZHgY4WFCu5iIQ96GNY7q\nZ3mq9ZmzLo+uCbH07RzvdSimFSssrWDcXz/n1GFdue+84V6HExSscWSCQnbBPqY8PJuBXdvx6rSx\nDT5HUlhawTuLs3l36TYWbymgsrru38+/nTOUC8c0/m7Upvy93DljBfnFZXz0y/EBb2A53eZ2u93m\ncigqqySlfSznjkrZ323OH3vLKpn66BzKKqt4/4bxdGp7eCO0H6qdxWV8t9FpDM3NPLAxNDqtA+P6\nNF9jqC73zczgia8yeeinwzlnVNPdGTlcqsonq3Zw/8drWJ9bzPDURG6d0p+j+yRRVlnF699v5bHP\n15NfXEanttEUlJTz7GWjWZVTyH0z1/CL43rTo2Mb1ucWExsZTrfEWHonxTE8NbHeksCqStbuffzu\n7eXMWZfPET3bc8epAxnWPYEHPlnLU7MyD1h+zZ+nEB1xaHeorHFUP8tTxhiv3PLmUj5YlsP3d04O\n+h4VzcHfXGVHygRU98RY/nDGYH7zxlKe/3ojVx3XG3AaKTsKS/ffBSmvrOa+mRn897st7KuoYkCX\ntkw7rjfH9k2ic7sYosLDEIGqauWWt5Zx70cZnDQomY7x/jUSqqqVf83ZwEOfrqW8qhpV2JC/lz6d\nAnNlrzHd5vwRFx3Bk5eM4pwnvuWGVxfxnyuOapbGx87iMuZv3MVc987Q2h1OY6hNVDhHpnXgnFEp\njO3dgSHdE4Li2ZibTuzHoi27+c0bSwkT4ayR3b0OiXkbdvL3mRks3lJA705xPHXJKE4e3GV/wzw6\nIpzLxqVx3hEpPP/1Rl6dv5WHzx/B8f07M6FfJzJyinh69gbAOe7lldX7LxqEhwkDu7alZ4c4uibE\nsLe8iszcYrbsKmFXSTnlldW0iQrnT2cO5uKjeu7/vbtt6gAmDezMmu1FVFUrldVKZJj3Pz9jjDFN\n59xRKfxvQRYfr9zepF2pWzq7c2QCTlWZ9vJCZq3J4/0bj6W8sppLnvuOgpIKfjo6hWuP78tv3ljK\ngs27OWdUdy4/Oo1hKfX3j127o4hTHp3DOaO6+3WrOLeolJtfX8rX6/M5aVAylx+TxkXPftfgiOiN\ndTjd5vz11sIsfv3GUi4c04M/njm4yRsku/aW853PoKtrdhQBzn/KR6d1YGxvp6vc0CBpDNWlpLyS\nK15cwLyNO7nz1EGcNyqlzgEka+QVlVFUWgFAu9hIknwa3GWVVeQVlZFfXE5ZRRXdEmPpkhDj176v\n2lbIfR9n8NWaPLq0i+FXk9M574iURjdqK6uqWZpVQJeEWLolxFCtzu90xvYiFm7azdKsArJ372Pb\nnn3ERIbTt1M8aUlxdIyPomNcFKcM7UpK+8A+EG53jupnecoY45XqauX4B74itUMs/71yrNfheM66\n1Zmgkl9cxkkPz6ZDXBS5haW0jYlkypAuvPDNRqoVYiLDuP+84Zzu57hIf/toNU/P2sCNJ/QlIjyM\nssoqSiuqKa2ooqzywH9XbiukpLySu08fzPlHOqWej/jzZ5wwoDMP/OTw+uGqKgs3u93mluVQfIjd\n5hqjZt+HpyTw6AUj9w86uKOwlDnr8lm8ZTfrcovJ2bOPU4d245oJfeptHOzaW878jTv3l9fO2O40\nhmIjwxntFlAY1ye4G0N12VdexbSXFzBnXT7hYcLI1ETG9OrAqB7t6dGxDVHhYWzdXcK/v93E5xm5\n+J4GO7WNplfHOHIK95G9ex+1e3aGhwnj05O44MgeTBrY+UfHZcvOEh76dA3vLN1Gu5hIrj2+D/93\ndBoxkYdfVCFYWeOofpanjDFeeuQz55nlr289ge6JsV6HQ3FZJf/8cv3+7vgjUhObLT9a48gEnZkr\ncrj6P4vo0aENr1x1FCnt27Bg0y5e+GYT1xzfp1ElmEvKKznrn9/s7+YVESbERIYTHRHm/BsZRnRE\nODGRYXSMi+aWKf0PqBo07aUFrN1RxFe/nXhI+5JdsI+3F2Xx1qLsJuk211gfLc/htunLKSqtIC46\nguiIMPKLywFoGxNBv+S2tI2JYNbaPOKjI7jgyFSO69eJfsltWbylYH8BhboaQ2N7d2RYSmg1hupS\nXa0s3lrAV2tymb02j5XbCn/0DFuHuCguGtOD9GSne2VeURmrc4rYvHMvXRNj6dWxDd3bx5IUH01U\nRBg5BaWszyvm3SXb2F5YSlrHNjx0/ghG9WhPXlEZj3+xjlfmbyE8TPjZMb24ekIfEmLrv2vVUljj\nqH6Wp4wxXtq6q4Tx933Jb07qx/UnpDe4vKoG7HnsgpJyLn/he5ZmFey/KBkfHcHFY3twxTG96Bzg\ncTGtcWSC0ldrchncLaFJCgpUVlVTVllNdERYo7sqPTt7A3/5cDXz75hE57b+/THuK/9hkNZvMgPT\nba4xthXs47Xvt1JUWkFpRRVpHeM4Nj2JgV3a7W+crc4p5OFP1/Llmlwqqn74Wz+wMdSBod0TiYoI\n7cZQQ/aVV7E8ew+5RaWUV1YTGxnOxAGdD+mKVWVVNV9k5HLPe6vI2bOPqUO78mVGLmWV1Zx/ZCq/\nnJTeqgY/bqmNIxG5CbgSUGA58DOgK/Aa0BFYCFyqquX1rcPylDHGaxc8M5dFWwo4d1QKV47vVe/z\n1o9/sY7Hv1zPKUOci71je3dssou9eUVlXPrcd2zI28vjF41kTK8OLNi0mxlLsvlweQ4RYWEc0bM9\ng7q146heHThxUHKTN9KscWTMQSzespuzn/iWJy8exdShXetdzotuc4Gwt6yS+Zt2kZlbzIjURIal\ntPzGUHMoKq3gnvdW8ebCLE4d1pVfn9iP3gEq8hHMWmLjSES6A18Dg1R1n4j8D/gQOAWYrqqvichT\nwFJVfbK+9VieMsZ4bVvBPh77fB3TF2dTXllN98RY0pPjOS69Ez87Jg0RIWN7Iac99jV9O8eTvXsf\nRWWVXHFsL35/2iC/t1NaUVXnBces3SVc+tx8tu8p5dnLRnNsetIB8zfl7+XfczexaEsBGTmFlFVW\nc8nYHtx9+mAiwsNYkb2Hl+du5s9nDzmsXi3WODLmIMorqxl2z8dcNKYnd53+4z/8mm5zby7MYtPO\nEtpEhTN1SPN1mzOhpbC0gnYxLb/7XH1acONoHjAcKARmAP8A/gt0UdVKERkH3K2qJ9e3HstTxphg\nkV9cxvRFWazcVsiqbYWsyy3m0rE9+cPpgzj3qbls3VXCZzdPoE1UOHe9s4I3F2bx7vXHNvjYw4rs\nPTz06Vq+yMjlqF4duHJ8byYN6ExYmJCZV8yl//qO4rJKXvjZGI7o2f6g66qsqt4/3MQJAzqTEBvJ\njCXZJMRG8tq0sQzo0u6Q999KeRtzEFERYYxITWTB5l37p+0rr2LmyhzeXJjFt5k7UYWxvTtw/Qnp\nTB3Spd7xZIxpzQ2jlkpVs0XkAWALsA/4BKcbXYGqVrqLZQE/qhcvItOAaQA9ejRdRUxjjDkcSfHR\nTDuuD+D0jPnbRxk8M3sDCzbvZnVOIY9eMIIOcVEA3HHqIL7IyOXOGSuYfs3RdV4Uzi0s5Z73V/HB\nshwSYiO5dGxPvsjI5aqXFhAVHkZcdDj7KqqIj47gtWnjGNSt4YZNRHgYt00dQEr7WO56ZwWR4WFc\nPaFPsz7Da//bM63W6J4deHJWJnPW5fH+0hw+WP5Dt7lfTkrn3FEppHYIjW5zxpimJSLtgTOBXkAB\n8AYwxZ/vquozwDPg3DkKVIzGGHOoRITbpw4gMlz455eZTOzfiTN8KgYnxEZy+9SB/PqNpfxvwVYu\nGONc6FFVdu4tZ+aK7fx9ZgZlldXcOCmdK8f3ol1MJH+oqubjlTtYll1ASVkV1apccWyvRnc5v2Rs\nT0b1aE+HuCi6JDTvM7zWODKt1ui09lR9qVz63HzaRP1QbW5MmnWbM8YwGdioqnkAIjIdOAZIFJEI\n9+5RCpDtYYzGGHPIRITfnNTfrVKb+KMCCOeM6s7r32/lD++u5MlZmYSLkFdcRlGpc/N8XO+O/PWc\nofRyhxQB587PqcO6cuqw+p/n9pc/d5oCodkbRyLSH3jdZ1Jv4C4gEbgKyHOn/05VP2zm8EwrMq5P\nR644thcDu7azbnPGmNq2AGNFpA1Ot7pJwALgS+A8nIp1/we841mExhhzmESE8emd6p334E+H8+Ss\nTErKKqmoVo6NiyKtYxwDurRlXJ+OASv77SVPCzKISDjOVbejcEqkFqvqA/5+3x50NcYY77XEggwA\nInIPcD5QCSzGKevdHadh1MGddomqltW3DstTxhgTHEKlIMMkIFNVN7fElqcxxpjQpap/AP5Qa/IG\nYIwH4RhjjGkGXg90cgHwqs/n60VkmYg87z4M+yMiMk1EFojIgry8vLoWMcYYY4wxxphG86xxJCJR\nwBk4FYAAngT6ACOAHODBur6nqs+o6mhVHd2pU919JI0xxhhjjDGmsby8czQVWKSqOwBUdYeqVqlq\nNfAs1m3BGGOMMcYY04w8K8ggIq8BH6vqC+7nrqqa476/CThKVS9oYB15wGY/N5kE5B9GyF4K5djB\n4veaxe+tUI7f39h7qqrdyq9DI/PUwYTy71Ftti/Bp6XsB9i+BKtg2Be/cpUnjSMRicMpk9pbVfe4\n017G6VKnwCbgFzWNpSba5oJQraYUyrGDxe81i99boRx/KMfe0rSkn4XtS/BpKfsBti/BKpT2xZNq\ndaq6F+hYa9qlXsRijDHGGGOMMeB9tTpjjDHGGGOMCQqtqXH0jNcBHIZQjh0sfq9Z/N4K5fhDOfaW\npiX9LGxfgk9L2Q+wfQlWIbMvnhVkMMYYY4wxxphg0pruHBljjDHGGGNMvaxxZIwxxhhjjDG0sMaR\niEwRkTUisl5Ebqtj/s0iskpElonI5yLS04s469NQ/D7LnSsiKiJBVRLRn/hF5Kfuz2CliLzS3DEe\njB+/Pz1E5EsRWez+Dp3iRZx1EZHnRSRXRFbUM19E5DF335aJyKjmjvFg/Ij/Yjfu5SLyrYgMb+4Y\nD6ah+H2WO1JEKkXkvOaKzR/+xC8ix4vIEvdvd1ZzxteahHoe8xXqOa1GqOc2X6Gc52oL9bxXI9Tz\nn69Qz4X7qWqLeAHhQCbQG4gClgKDai0zEWjjvr8GeN3ruBsTv7tcW2A2MA8Y7XXcjTz+6cBioL37\nubPXcTcy/meAa9z3g4BNXsftE9txwChgRT3zTwE+AgQYC3zndcyNjP9on9+bqaEWv8/v2BfAh8B5\nXsfcyOOfCKwCerifg+ZvtyW9Qj2PNXZf3OWCMqc18mcStLntEPYlaPNcHfsT0nmvEfsR1PmvMfvi\nLhO0ubDm1ZLuHI0B1qvqBlUtB14DzvRdQFW/VNUS9+M8IKWZYzyYBuN3/Qn4O1DanMH5wZ/4rwL+\nqaq7AVQ1t5ljPBh/4legnfs+AdjWjPEdlKrOBnYdZJEzgZfUMQ9IFJGuzRNdwxqKX1W/rfm9Ifj+\ndv05/gA3AG8BwfR7D/gV/0XAdFXd4i4fdPvQQoR6HvMV6jmtRqjnNl8hnedqC/W8VyPU85+vUM+F\nNVpS46g7sNXnc5Y7rT5X4FxRCBYNxu/eEk5V1Q+aMzA/+XP8+wH9ROQbEZknIlOaLbqG+RP/3cAl\nIpKFc8XjhuYJrUk09u8jmAXb326DRKQ7cDbwpNexHKJ+QHsR+UpEForIZV4H1EKFeh7zFeo5rUao\n5zZfLT3P1daS8l6NYP6bb1Co5MIIrwPwgohcAowGJngdi79EJAx4CLjc41AORwRO94Pjca58zBaR\noapa4GlU/rsQeFFVHxSRccDLIjJEVau9Dqy1EJGJOMnhWK9jaaRHgFtVtVpEvI7lUEQARwCTgFhg\nrojMU9W13obVeoViHvPVQnJajVDPbb4szwWpEM5/vkIiF7akxlE2kOrzOcWddgARmQzcAUxQ1bJm\nis0fDcXfFhgCfOX+QnUB3hWRM1R1QbNFWT9/jn8WTl/ZCmCjiKzFSSjfN0+IB+VP/FcAUwBUda6I\nxABJBPGtYR9+/X0EMxEZBvwLmKqqO72Op5FGA6+5f7tJwCkiUqmqM7wNy29ZwE5V3QvsFZHZwHDA\nGkdNK9TzmK9Qz2k1Qj23+Wrpea62kM97NUI8//kKiVzYkrrVfQ+ki0gvEYkCLgDe9V1AREYCTwNn\nBGGf4IPGr6p7VDVJVdNUNQ2n32kwJZEGjz8wA+fKGiKShNMVYUNzBnkQ/sS/BefKOSIyEIgB8po1\nykP3LnCZW71nLLBHVXO8DspfItIDmA5cGop3K1S1l8/f7pvAtcGWDBrwDnCsiESISBvgKGC1xzG1\nRKGex3yFek6rEeq5zVdLz3O1hXTeqxHq+c9XqOTCFtM4UtVK4HrgY5yk/T9VXSkifxSRM9zF7gfi\ngTfEKUlb+6TgGT/jD1p1xQ9MFJFtIlIhIi+683aKyCrgS+BF4BsRKRGndOj+krQiEu2WhCwUke0i\ncrPPvFS3X/cuEXnQNw4R+UgOoRysn8f/18BVIrIUeBW4XNUpvdKcRGSSiGT4HjcReRWYCwwUkSoR\nyXZjv9r9WgHQH1gPPAtcW8d67xaR/zTbjhy47VeBhcBgEckSkStE5Gqf+O8COgJPuH+7QfUfKJ/j\n37+e+INaQ/Gr6mpgJrAMmA/8S1UPWqrVNF6o5zFfoZTTROQCEVktIntFJFNExvvMngBE4lR52wN8\n4rMfL4hIPvCgs5r9ue1Z4Lnm3o+GNGWeE5H7RGSrm6M3i8jvas0fIc7ziSXuvyN85l0kIjkiskmc\nrmI10/uIU6o6vL59EJHLReRr931D590PcRqp9ea9xhKRNHHKzjdZzys/9iOo85+vUM+F+/lT0s5e\n9jqUF3AOcBbOg3cv1pqXhJNofoJzZep+YJ7P/L8Bc4D2wEBgOzDFnfcETgnbBJyENdqdfj7wRBDs\ntwBhAVp3vccN6Apk4FQauh54350egXNVNq2Bdd8N/OcwYos4zH07Hsjy+udnL3vZq/W8gBOBzTil\nnsNwHtjv7s4L2Pm2mfbtsM7JDay7PxDnvu8OrATOcT9Hucf0JiAauNH9HOUeny3u8TsNn5LPwAfA\nUQ1s93Lga6+OCZCGU9EvYMfWXt6/PA/AXi3/Bfy5jsbRNOBbn89xwD5ggPt5G3CSz/w/Aa+57z8C\n+rvvXwN+6iaoxUBiA7EI8DBO/+lCYDkwxJ2XALyE04VgM3BnTSOndsOh9gkS+Ar4C/CNux99gQ7A\nC+6+7AZm+Hz/NGAJzh2db4Fhfh7Leo8bTlenV93pA4BV7vvfAL9rYL1TgHKgAigGlrrTf4ZzhbEI\n5wrcL3y+czxOX/tbcRqvL7vTbwFy3P2+0j1Ofd150cADbnLcATyF84B/zX5Uu9svBrp5/btrL3vZ\nq2W/3PPvFfXMC8j51l1uDLDAzUM7gId85p2B09gocHPLQJ95+8+n7ucXgT+77+s7J5/p5ptCnAuK\nNRcaE3DucOXgPIvzZyD8EI5hd5xceov7+SR3feKzzBY3zyQDc91pMUCJ+/484JkGtjMQp+R7lZsj\nCtzpp+Lk/0Kc6nR3+3wnzT1mV7gxzHanX4aT53cCvwc2AZPdeWHAbe6x2onTE6aDz36oT54a5/Xv\nsL2a/tViutWZkDMYZwA6ANR50DsTp1tVe5yrSkt9ll/qfgdgBXCiiCTiVNBaidN4ekQbrg50Es4g\nZf1wEsNPcU5+AP9wp/XG6UpxGU7jwF+X4iTTtjgn3ZeBNm7cnXEaZTXPDDwP/ALnVvnTOA8iR/ux\njXqPG07XgaHucZkMrBSRVJx+5Q8cbKWqOhP4K86AkvGqWjMCdy5OQ64dzrF4WA4cZbwLTiOwJzBN\nnBK2N7vb74vbD9/HvTjHfoQ7vztwl7sfU4Ft7vbjVXWbiBwrIqFY8ckYE+Tc7lujgU4ist7tBvS4\niMS6iwTkfOt6FHhUVdsBfXD+A46I9MPpzvYroBNO17D3xHlGyB+1z8ljcC76/RZnMOfjcBoC4DSs\nKnHOxSNx8uOVfm4HEblNRIpxGmRxwCvurMHAMlX17Y63zJ2eB3QUkRScu3YrRaQtzsXI2w+2PXW6\n916N07iKV9VEd9ZenHydiNNQukZEzqr19Qk4jauTRWQQTg+Ui3H+r5HAgSW+b8Dp9TIB6IZzcfOf\n7rzj3H8T3RjmikgPESkQ59kg0wJY48h4JR6nu4KvPTgNi3ifz7XngdPlbjwwC+cEFwUMw0kgr4jI\nbBG5vp7tVrjrGYBzVWu1qua4SfIC4HZVLVLVTTj9yC9txD69qKor1enXnYTzn/2rVXW3qlao6ix3\nuWnA06r6napWqeq/gTKcbh0Nqfe4qVPB5i84I0+finMF81Gcq4hni8gsEXnHTUp+UdUPVDVTHbOA\nT3COfY1q4A+qWqaq+3Aamy+4x6EE544b4HTId/f9JlXdpapFOA2yCw6y/a99EqAxxjSlZJznic7D\nOa+NwGkk3OnOD+T5tgLoKyJJqlqsziCl4HQP/0BVP1Wn+t0DOHfXj/Zzn2qfk68AnnfXV62q2aqa\nISLJwCnAr1R1rzrFPR7mIOfj2lT1Xpx8OgrnYmDNsTrYcavG6Rb/Js4xuwq4B+fi5DBxnqP9WESG\nNCKOr1R1ubt/y3Aal7VL3N/t7uc+nJ/3e25+Kcd5pse3IXc1cIeqZqlTDfJu4Lz6njNS1S2qmqju\nINkm9FnjyHilmB9G4a7RDqf7VrHP59rzcP9jfb57d+NRnJPqDTi3wVfgXMW7WpxKOwdQ1S+Ax3Gu\nAuWKyDMi0g6nMROJc8enxmYaN2Cc72BzqcAu/WFUa189gV+7V5oK3DsjqThXqBpysOOGqr6qqqNU\ndSpOmdwynO4GDwCnA2/g31VNAERkqvxQ/KIAJ5km+SySp6q+I9t348Dj4Pu+E86dtIU++z3TnW6M\nMc1tn/vvP1Q1R1XzccZeOsWdHsjz7RU4d9EzROR7ETnNnd4NnzzkNia24n8uqn1OTsW521VbT5yc\nl+NzPn4ap5eD39wLZ4txjuU97uSGjtvnqjpWVSfgNEpG49zFegnnmaI/4ZSt9ouIHOU2qvJEZA9O\n4yap1mK+ueiAPOVeyPMtj90TeNvnuKzG6cqX7G9MJrRZ48h4ZSXOOCkAiEgcTteClW6DIsd3vvt+\nZR3rmYbzgOwKYCiwwL0StNz9/COq+piqHgEMwklOvwXyca7k9fRZtAc/jImwF+c/9jW61LVqn/db\ngQ5ul4vatgJ/ca801bzaqOqrdcVbS73HzXcht1vIX3EqD6UDW1W1EKeU67B61n1ARSK3m99bOMk9\n2b2D8yHOc1t1fgfn5+Z7pdR3jIl8nAQ62Ge/E1S15k5hs1f+M8a0Xm6uyeLAc4/v+4Cdb1V1nape\niNMY+Tvwprv+bfjkIfeOeyo/5KISDp6Lap9Ht7ox17YVpzGX5HM+bqeqg+tY1h8RPttZiXMXyDdX\nDOPHx01wLlbeiNOYCVfVzTQiT7lewSnbnaqqCTjPstYeYdT3ewfkKffn19Fn/lac8YR8c3SMqmbX\ns33TwljjyASMOGOixADhQLiIxPjcln4bGCIi57rL3IXTRznDnf8ScKeItBeRATi33l+stf7OwHX8\n0HVrI0758HicK1E/GmdCRI50rzJF4jR4SoFqVa3C6fP9FxFpK05Z8ZuBmtLWS4Dj3L7FCTTcNzoH\np3DEE+4+RIpITV/lZ3HubB0ljjgROdXtd42IvChO6fO6NHTcatyJ081vG84DpP3dbhQT6zourh1A\nmjgj14PTXTEap494pYhMxemTfjD/A34mIgPFGQ/n9z7HpNrd94fdnx0i0l1ETvbZfkf3+BpjTHN4\nAbhBRDqL87zrTcD77ryAnW9F5BIR6eSeF2ueq6zGOYeeKs6QDZE4Da4ynMIR4OSii0QkXJxnPGt3\nH6vtOZxz8iQRCXPPuQPcHPUJ8KCItHPn9RGRCW58NSWr0+qIPUxEfuHmNhHnuabrgM/dRb7CudNy\nozjDctR0c/+i1qquBBap6hKcOzex4jwP1FCeSpEDn8Fqi9NTo9SN5aIGjsmbwOkicrS7nrs5sDH1\nFM7/BXq6+9tJRM505+Xh/Jx6N7ANE8o0CKpC2KtlvnBOOFrrdbfP/Mk4pVD34ZxM03zmReMULaip\n5HNzHet/CfiJz+dU4DuchycfqiemSTgPhhbj3Mn4LxDvzmuP0xjKw7lydBc+JblxuuIV4DyIe5W7\nP9e7877FuWvlu60OwL/d+HcD033mTcG5OlaAcxXrDZz+2OAkmNeAy+rZh8lufBW1j5s7f4C77nCf\naTV3x1YBQ+tZb0fgazfWRe6069z4C3D6lL9GrcpIdazndpxKSdtw+pYrzhU9cKoT/RUn8RXidFe4\n0ee7z+MkyQKcrg/jgWKvf5ftZS97tcwXTteyJ9xzznbgMSDGZ369ecqdf6jn2//gFLwpxrmjcpbP\nvLPd7+7BebZ2sM+80e7yRe45+dWDnZNxihQ8zQ95rxg42Z2XgDPURpa7rcXABe688TiFGyLrFjoo\nHwAAIABJREFUiD0Mp0t0zQXGtcDvOLA63UicXFkBLAJG1lpHEk43+HY+0y52fwabgIn1HLconJLf\nu4B8d9p5OF0Ri3Aato/jVpelntLbON33tvBDtbpsYLzP/t0MrHHXmQn81ee7f8T5f0IBzrPCPdzj\n2sPr32d7Nc1L3B+0MaaR3Ctq76uq3w+O+rHOKJzqSBXAKHWKO9S1nOAknGPU6S8dlNznvlYA0fXt\nizHGmMA41DwlInfiPL/0dD3zI3ByUEvIU/E4DZ10Vd3odTzGe9atzphDdy/QR5wRq98QkRWwfwTv\nGSLynohsFJHrReRmEVksTnGDDu5yfURkpjijh89xuzqUA7/EuXNT6S53o4isEpFlIvIaOA/B4lzF\nPK2uwLwkIme7XSna4/Slf88aRsYY44lDylM4A6o/XVeectd7AqGdp04XkTbiPOf1AM5zypu8jcoE\nC2scGXPobgMyVXUETjcKX0Nw+j2PwSn3WqKqI4G5OOMxADwD3KBOcYjf4HTtADgGWFhrOyNVdRhO\nFZ4aCziwrHaw+AVOd5FMnH7n13gbjjHGtFqWp+p2Jk7X7204RTQuUOtKZVx11mw3xhy2L9UZx6dI\nnNKi77nTl+NU8YnHGbfiDfmhoE/NILBdcZ7FqbEM+K+IzABm+EzPxb/y381KVad4HYMxxpgGteY8\ndSWNGPDWtC7WODImMMp83lf7fK7G+bsLAwrcq3m17cMpXFDjVJxRuc8Afi8ig92uDDH8ME6HMcYY\n0xiWp4ypQ0gXZEhKStK0tDSvwzDGmFZt4cKF+apqg/nWwfKUMcYEB39zVUjfOUpLS2PBggVeh2GM\nMa2aiGz2OoZgZXnKGGOCg7+5ygoyGGOMMcYYYwzWODLGGGOMMcYYwBpHxhhjjDHGGANY48gYY4wx\nxhhjAGscBVR5ZTUvz93EpAe/4levLWbX3nKvQzLGGONDRJ4XkVwRWeEzbYSIzBORJSKyQETGuNNF\nRB4TkfUiskxERnkX+eHLLtjHI5+t5dLnvuOIP33Kh8tzvA7JGGM8Z42jAFm1rZATHvyK37+zkpjI\ncD5YnsOJD83ik5XbvQ7NGGPMD14Eag9cfB9wjzu+y13uZ4CpQLr7mgY82UwxNqnyymqe+Go9kx+c\nxaOfryO/uJzwMOGJr9YTysN7GGNMU7DGUQCUVVbxy9cWU1ZZzb9/Pob3bziW928YT5eEGK5/dTF5\nRWUNr8QYY0zAqepsYFftyUA7930CsM19fybwkjrmAYki0rV5Ij18VdXKjMXZnPzIbO6buYZj05OY\n/duJfPTL8dwwKZ0V2YUs3lrgdZjGGOMpaxwFwCOfrWNdbjH3nTeMCf06ISL079KWf1w4kooqp6ud\nMcaYoPUr4H4R2Qo8ANzuTu8ObPVZLsuddgARmeZ2x1uQl5cX8GD9sbO4jFMencOvXl9CdEQYL1x+\nJM9eNprUDm0AOHtkd+KjI3h5rg1ZZYxp3axx1MQWb9nN07MyOX90KhP7dz5gXu9O8UwemMxL8zaz\nr7zKowiNMcY04BrgJlVNBW4CnmvMl1X1GVUdraqjO3VqcDD2ZvGPL9azPq+Yxy4cyYc3jmfigAPz\nU3x0BOeO6s4Hy3LIL7beDcaY1ssaR02otKKK37yxlC7tYrjjtIF1LjPtuN4UlFTw5sKtdc43xhjj\nuf8Dprvv3wDGuO+zgVSf5VLcaUFty84S/vvdZn46OpUzhncjLEzqXO7ScWmUV1Xz+veWn4wxrZc1\njprQI5+tIzNvL/eeO4x2MZF1LjO6Z3tGpCbyr683UlVtD74aY0wQ2gZMcN+fAKxz378LXOZWrRsL\n7FHVoC/x9vBnawkT4VeT0w+6XN/O8YxPT+L5rzey26qrGmNaKWscNZGlWwt4ZrbTne64fvV3oxAR\nrhrfm807S/g2M78ZIzTGGFObiLwKzAX6i0iWiFwBXAU8KCJLgb/iVKYD+BDYAKwHngWu9SDkRlmd\nU8iMJdn87JheJLeLaXD5O04dyJ59Ffzx/VXNEJ0xxgSfCK8DaAnKK6v5zRtLST5Idzpfx/ZNAmBF\ndiHj04OjP7oxxrRGqnphPbOOqGNZBa4LbERN6+lZmcRHRXDNhD5+LT+gSzuundiXxz5fxxnDu/3o\n2SRjjGnpAnbnSERSReRLEVklIitF5Jfu9A4i8qmIrHP/be9OD9nB9WYszmZdbjF/PHNIvd3pfCW0\niaRrQgxrthc2Q3TGGGNao8LSCj5asZ0zR3YjoU3DuanGdRP70C85nt+9vZzC0ooARmiMMcEnkN3q\nKoFfq+ogYCxwnYgMAm4DPlfVdOBz9zOE6OB6VdXKU7MzGdytHZMH+n+FrX+XtqzZURzAyIwxxrRm\n7y/Noayymp8ckdrwwj6iI8K577zh5BaVcfv05TYwrDGmVQlY40hVc1R1kfu+CFiNMx7EmcC/3cX+\nDZzlvg/JwfU+XbWdDXl7ueb4PojUXQGoLv27tCUzt5iKquoARmeMMaa1emPhVvolxzMsJaHR3x2R\nmsivT+rHB8tyrHqdMaZVaZaCDCKSBowEvgOSfar7bAeS3fchN7ieqvLkV5n07NiGqUMa147rn9yW\n8qpqNuXvDVB0xhhjWqv1uUUs3lLAT45IbdSFO19XH9eHY/smcfd7K1m7o6iJIzTGmOAU8MaRiMQD\nbwG/UtUDHrJxH25t1P36YBpcb27mTpZm7eEXx/UhvJ5xI+rTv0tbANZYwjHGGNPE3liYRXiYcObI\nboe8jrAw4aHzhxMZHsbTszY0YXTGGBO8Ato4EpFInIbRf1W1ZkC9HTXd5dx/c93pITe43tOzN5AU\nH805o350g6tBfTrFEx4mrNlujSNjjDFNp7KqmrcXZTOxfyc6t224fPfBdG4bw4R+nZizLs+ePTLG\ntAqBrFYnwHPAalV9yGfWuzijj+P++47P9JAZXG99bhGz1uZx2biexESGN/r7MZHhpHVsQ4Y1jowx\nxjShbzJ3kltUxnlHpDTJ+sanJ5FbVMa6XCsiZIxp+QJ55+gY4FLgBBFZ4r5OAe4FThSRdcBk9zOE\n2OB6z3+ziaiIMC4+qschr2NAl3Z258gYY0yTmr4oi4TYyCYbo+hYdzy+2Wu9fc7XGGOaQ8AGgVXV\nr4H6HsSZVMfyITO43u695UxflMXZI7rTMT76kNfTv0tbPlieQ0l5JW2ibDxeY4wxh6eotIKPV27n\nvCNSiI5ofK+GunRPjKV3pzi+Xp/PleN7N8k6jTEmWDVLtbqW5pX5WyitqObnx/Y6rPX0S3aKMqy1\n8Y6MMcY0gY9WbKe0oppzRjVNl7oa4/smMW/DTsoqq5p0vcYYE2yscdRIVdXKy3M3Mz49aX/FuUM1\noKZi3fbCBpY0xhhjGjZ9URa9kuIYmZrYpOsdn96J0opqFm7a3aTrNcaYYGONo0aasy6P7YWlXDTm\n0J81qtGjQxtiIsNYs93uHBljjDk8WbtLmLdhF+eM7H7IYxvVZ2yfjkSECXPW5zfpeo0xJthY46iR\n3lqUTUJsJCcMPPwHXcPChCHdEqxEqjHGmMM2Y7Ez+sVZIxs/vERD4qMjGNWjvRVlMMa0eNY4aoTC\n0go+WbmdM4Z3a7IHXX96ZCrrcouZt2FXk6zPGGNM66OqTF+czZi0DqR2aBOQbZw0OJmV2wpZurUg\nIOs3xphgYI2jRvhgWQ5lldWc20RjRwCcMbwbiW0ieWnupiZbpzHGmNZlWdYeNuTtPaRByf11/pGp\ntIuJ4KlZmQHbhjHGeM0aR43w1sIs+nSKY3hKQpOtMyYynPOPTOWTVTvI2bOvydZrjDGm9Zi+KIuo\niDCmDu0asG20jYnksnFpzFy5ncw8e1bWGNMyWePIT5vy97Jg827OPSKlyR90veSonlSr8sp3W5p0\nvcYYYw5ORJ4XkVwRWVFr+g0ikiEiK0XkPp/pt4vIehFZIyInN3/EP1ZRVc17y3I4cWAyCbGRAd3W\n5cekERUexjOzNtQ5v7yymite/J55G3YGNA5jjAkUaxz56fUFWwkTOGdk044dAZDaoQ2TBiTz6vwt\nVFRVN/n6jTHG1OtFYIrvBBGZCJwJDFfVwcAD7vRBwAXAYPc7T4hI0zyAehhmrclj197ygHapq5EU\nH835R6YyfXEW2/eU/mj+hvxiPs/I5fczVlBp+cwYE4KsceSH8spq3liwlUkDk+mSEBOQbZw+vCv5\nxeWsz7WuCsYY01xUdTZQuyLONcC9qlrmLpPrTj8TeE1Vy1R1I7AeGNNswdZjxpJsOsRFcVy/Ts2y\nvcvG9aSiSvlqTe6P5m3K3wvAutxi3lqU1SzxGGNMU7LGkR8+WbWd/OJyLj7q8Mc2qs/Aru0AWLO9\nKGDbMMYY45d+wHgR+U5EZonIke707sBWn+Wy3GkHEJFpIrJARBbk5QW29HVFVTWz1uRx4sBkIsOb\nJ6X36RRPQmwkS7N+XLVuY34J4OS0hz5dy77yqmaJyRhjmoo1jvzw33lbSGkfy3Hpgbsq1yspjshw\nYc0OaxwZY4zHIoAOwFjgt8D/pBEPm6rqM6o6WlVHd+oU2Ls5CzbtpqiskokDDn/sPX+JCMNSEliy\ndc+P5m3K30tSfBT3nDGYHYVlPP/NxmaLyxhjmoI1jhqQmVfM3A07ueioHoSFNW0hBl+R4WH06RRv\nd46MMcZ7WcB0dcwHqoEkIBtI9VkuxZ3mmS/X5BIZLhybntSs2x2RmsjaHUU/ujO0cede0jrGMaZX\nByYP7MxTX2Wya295s8ZmjDGHwxpHDXjluy1EhAk/OSK14YUPU/8uba1xZIwx3psBTAQQkX5AFJAP\nvAtcICLRItILSAfmexYl8EVGLmN7dyQ+OqJZtzs8JZGqamXltgPvHm3K30taUhwAt04ZwN7ySh7/\nYn2zxmaMMYfDGkcHsaekgtfmb+GUoV3p1DY64Nvrl9yW7IJ9FJZWBHxbxhhjQEReBeYC/UUkS0Su\nAJ4HervlvV8D/s+9i7QS+B+wCpgJXKeqnj1Us2VnCetzi5nYv/m61NUYluqM97dk6w/PHe0tqyS3\nqIxebuMoPbktPzkilZfnbWLrrpJmj9EYYw6FNY4O4sVvN7G3vIprju/TLNsb0KUtAOvsuSNjjGkW\nqnqhqnZV1UhVTVHV51S1XFUvUdUhqjpKVb/wWf4vqtpHVfur6kdexv5Fxg4ATmjG541qdG4bQ7eE\nGJZm/XDnaNNOp1JdWse4/dNuOrEf4WHCA5+safYYjTHmUASscVTXwHoi8rqILHFfm0RkiTs9TUT2\n+cx7KlBx+WtvWSUvfLuRyQM7768kF2j93cZRhnWtM8YY04Av1uTRu1Pc/m5szW14aiLLfCrWbXTL\neKcltdk/rUtCDD8/phfvLNnGiuwfF3AwxphgE8g7Ry9Sa2A9VT1fVUeo6gjgLWC6z+zMmnmqenUA\n4/LLK99toaCkgmsn9m22bXZPjCU+OsKeOzLGGHNQJeWVzNuwkxM86FJXY1hKIpt3lrDbLbhQM8aR\n750jgKuP70P7NpHc+1FGs8dojDGNFbDGUT0D6wHglkT9KfBqoLZ/OMoqq3h2zgaO7tORUT3aN9t2\nRYR+yVaxzhhjzMF9u34n5ZXVzVrCu7bh7nNHNeMdbcwvIbldNHG1ikO0i4nk+hPS+Xp9PrPXBnbc\nJ2OMOVxePXM0Htihqut8pvUSkcXugHvj6/ticwyuN2tNHrlFZVw1vndA1n8w/bu0Y82OIlS12bdt\njDEmNHy1Npe4qHBGpzXfBbzahnZPQASWuuMdbXLLeNflkrE9SGkfy70fZVBdbfnNGBO8vGocXciB\nd41ygB6qOhK4GXhFROp80Kc5Btd7d+k2OsRFNfu4EQD9k+MpKKkgt6is2bdtjDEm+KkqX2bkcXTf\nJKIjwj2Lo21MJP2T2/Lh8hwqqqrZlL93f6W62qIjwvntyf1ZlVPIO0s9HRrKGGMOqtkbRyISAZwD\nvF4zTVXLVHWn+34hkAn0a+7YwCnE8NnqHZwytAuR4c3fduzfxWkTWlEGY4wxdcnMKya7YJ8nJbxr\nu+nEfqzZUcRjn69j597ygxaHOH1YN4Z0b8cDH6+ltMKzCujGGHNQXtw5mgxkqGpWzQQR6SQi4e77\n3jgD623wIDY+W72D0opqzhje3YvN7y/nvdynApAxxhhT48sMp0v58f0D03uiMU4alMzkgZ15/Etn\noNf6utUBhIUJt00ZSHbBPl6eu7m5QjTGmEYJZCnvugbWA7iAHxdiOA5Y5pb2fhO4WlXrLOYQaO8t\n3UbXhBhG9/SmH3f7uChG92zPW4uy7bkjY4wxP/LV2lz6JcfTLTHW61AQEe4+YzAxbve++rrV1Tg2\nPYnx6Uk8/uV69pTYgOfGmOATyGp1PxpYz51+uao+VWvZt1R1sFvGe5SqvheouA6moKScWWvzOG1Y\nV8LCxIsQALjoqB5szN/L3A07PYvBGGNM8Ckuq2T+xl1B0aWuRkr7Ntx+ygC6tIuhZ8c2DS5/29QB\nFJZW8MSs9c0QnTHGNI5XBRmC0scrt1NRpZ51qatxytCuJMRG8ur8rZ7GYYwxJrh8sz6fiiplQhB0\nqfN12bg05t5+AjGRDReIGNwtgbNGdOeFbzaxrWBfM0RnjDH+s8aRj09W7iClfSxDutdZKK/ZxESG\nc86o7sxckcPOYqtaZ4wxxvHmwiw6xkUxumcHr0P5EWcIQ//cfGI/UHjo07UBjMgYYxrPGkeukvJK\nvl6fz4mDkht1gg+UC8f0oKJKeWtRVsMLG2OMafGyC/bx+eodnH9kKlERoZ2+Uzu04bJxPXlrURYZ\n2wu9DscYY/YL7bNrE/p6XT5lldVMHpjsdSgA9Etuy+ie7fn3t5vZV24lT40xprV75TunwttFR/Xw\nOJKmcd3EvsRHR/D3jzK8DsUYY/azxpHr89W5tI2JYEyv4Omq8OuT+pNdsI9HPrduB8YY05qVVVbx\n2vytnDAgmZT2DRc9CAXt46K49vi+fLkmj7mZVoDIGBMcrHEEVFcrn2fsYEK/Tp4M/FqfcX06cv7o\nVP41ZyMrsvd4HY4xxhiPzFyxnZ17y7lsXE+vQ2lSPzsmja4JMdz70WobvsIYExSCpyXgoSVZBeQX\nl3PioODoUufrd6cMpH2bKG6fvpzKqmqvwzHGGNNMCksreGdJNje9voTfz1hBWsc2HNs3yeuwmlRM\nZDg3ndiPpVl7+GB5jtfhGGOMNY4APl+9g/Aw4fh+wTNuRI2ENpHcfcYglmfv4cVvN3kdjjHGtCgi\n8ryI5IrIijrm/VpEVESS3M8iIo+JyHoRWSYiowIZW9auffzytSXMWpvHCQM68/hFozwdgy9Qzh2V\nQv/kttz/8RrKK+0ioDHGW62+cVRdrcxcsZ0j09qT0CbS63DqdOrQrkwa0JkHP1nL1l0lXodjjDEt\nyYvAlNoTRSQVOAnY4jN5KpDuvqYBTwYysIFd2/Lu9cfw/R2TeeSCkQzpnhDIzXkmPEy4dWp/Nu8s\n4dX5Wxr+gjHGBFCrbxy9t2wbmXl7ueDI4K3+IyL86awhhAncMWOF9cs2xpgmoqqzgV11zHoYuAXw\nPeGeCbykjnlAooh0DVRsIsKwlETCW+Ddotom9u/MUb068Njn6ygqrfA6HGNMK+Z340hEOovI2SJy\nnYj8XETGiEhIN67KKqu4/+M1DOrajjOGd/M6nIPqlhjLb0/uz+y1ebyzZJvX4RhjTNBpqjwlImcC\n2aq6tNas7sBWn89Z7rTa358mIgtEZEFeXl5jN98qiQi3nzKQnXvLeXb2Bq/DMca0Yg0mDRGZKCIf\nAx/gdCnoCgwC7gSWi8g9ItIusGEGxstzN5O1ex+3nzIgJPpxXzoujRGpifzx/VXs2lvudTjGGBMU\nmjJPiUgb4HfAXYcaj6o+o6qjVXV0p06dDnU1rc6I1EROHdqVZ+dsJLew1OtwjDGtlD9X1E4BrlLV\nI1V1mqreqaq/UdUzgOHAYuDEgEYZAHv2VfD4l+sZn57E+PTQSF7hYcK95w6lcF8Ff/5gldfhGGNM\nsGjKPNUH6AUsFZFNQAqwSES6ANlAqs+yKe4000R+e3J/KqqqeeTzdV6HYoxppRpsHKnqb1W1zick\nVbVSVWeo6ltNH1pgzd+4i5KyKm6dMsDrUBplQJd2XD2hD9MXZTNnnXXXMMaYpsxTqrpcVTurapqq\npuF0nRulqtuBd4HL3Kp1Y4E9qmr1p5tQWlIcFx3Vg9e/30pmXrHX4RhjWqHGPHNUJSL3ioj4TFsU\nmLAC78RByXx7+wkhWf3n+hP60jspjjveXsG+8iqvwzHGmKBwKHlKRF4F5gL9RSRLRK44yOIfAhuA\n9cCzwLVNELap5cZJ6cREhHHfzAyvQzHGtEKNeVB1pbv8JyLSwZ1W74M6dY0dISJ3i0i2iCxxX6f4\nzLvdHTtijYic3NgdORRJ8dHNsZkmFxMZzl/PGcqWXSU88tlar8Mxxphg0ag8BaCqF6pqV1WNVNUU\nVX2u1vw0Vc1336uqXqeqfVR1qKouCMhetHJJ8dFMO64PH6/cwcLNdRUSNMaYwGlM46hSVW8B/gXM\nEZEjOLDEaW0vUsfYEcDDqjrCfX0IICKDgAuAwe53nhCR8EbE1uqM7d2RC45M5V9fb2RF9h6vwzHG\nmGDQ2DxlgtSV43uRFB/N3z7MsOErjDHNqjGNIwFQ1deB84EXgN71LXyQsSPqcibwmqqWqepGnC4L\nYxoRW6t0+9SBtG8TxW3Tl1FZZaOKG2NavUblKRO84qIj+NXkdBZs3s2nq3Z4HY4xphVpTOPoypo3\nqroCGA/ceAjbvF5Elrnd7tq70/waO8IcKKFNJPecMZgV2YW88M0mr8MxxhivNVWeMkHg/CNT6Z0U\nx99nZtgFQGNMs/G7caSqC0XkaBG5SEQuw7nb01hP4pRJHQHkAA82dgU2uN6BThnahckDO/PQp2vZ\nuqvE63CMMcYzTZSnTJCIDA/jlin9yczbyxsLs7wOxxjTSjSmWt3LwAPAscCR7mt0YzamqjtUtUpV\nq3Eq/dR0nfN77AgbXO9AIsIfzxxCmMDv3l5ufbONMa1WU+QpE1xOHtyFUT0SefjTtZSUV3odjjGm\nFYhoxLKjgUF6GP/7FpGuPmNCnA3UVLJ7F3hFRB4CugHpwPxD3U5r0y0xllumDOAP765kxpJszh6Z\n4nVIxhjjhcPOUya4iAi3nzKQnzw1l+e/3sj1J6R7HZIxpoVrzDNHK4Au/i5cz9gR94nIchFZBkwE\nbgJQ1ZXA/4BVwEzgOlW1AXwa4ZKxPRnZI5E/vb+aXXvLvQ7HGGO80Kg8ZULDkWkdmDwwmadmbWBn\ncZnX4RhjWjhp6AKbiLyHUwq1Lc6zQvOB/WcnVT0jkAEezOjRo3XBAhtmosaa7UWc9o85nD6sGw+d\nP8LrcIwxrYSILFRVz7qvWZ5q+dbtKOLkR2Zz2bg07j5jsNfhGGNCkL+5yp9udQ80QTymGfTv0par\nJ/ThH1+s56yR3Tmunz2TZYxpFSxPtXDpyW356ehU/vvdZn5+TC96dGzjdUjGmBbKn8bR7Ib6b4uI\nWB/v4HDdxL58sDyHO2Ys5+NfHUebqMY8VmaMMSHJ8lQrcNOJ/ZixJJv7P1nDPy4c6XU4xpgWyp9n\njr4UkRtEpIfvRBGJEpETROTfwP8FJjzTWDGR4fzt7KFs3bWPRz5b53U4xhjTHCxPtQLJ7WK44the\nvLd0G8uyCrwOxxjTQvnTOJoCVAGvisg2EVklIhuBdcCFwCOq+mIAYzSNdFTvjlw4JpV/zdnAiuw9\nXodjjDGBZnmqlfjFhD60bxPJvR9l2NAVxpiAaLBxpKqlqvqEqh4D9AQmASNVtaeqXqWqiwMepWm0\n26YOpGN8NLe+tcxGFjfGtGiWp1qPdjGR3HBCOt9m7mTWWhsI3hjT9Pwq5S2Oo4DTgXE45bkloJGZ\nw5IQG8k9Zwxm5bZCnv9mo9fhGGNMQFmeaj0uHtuD1A6x3PtRBlXVdvfIGNO0GmwcichJOF0T7gZO\ncV/3AOvceSZITR3ShckDk3no07Vs2VnidTjGGBMQlqdal+iIcH5zUn8ythcxY3G21+EYY1oYf+4c\nPQpMVtWpqnql+5oCnOjOM0FKRPjTWYOJCAvjjhnLrX+2MaalsjzVypw+rBtDuyfw0KdrKa2wMeON\nMU3Hn8ZRBJBVx/RsILJpwzFNrWtCLLdM6c+cdfm8bVfYjDEt0yHnKRF5XkRyRWSFz7T7RSRDRJaJ\nyNsikugz73YRWS8ia0Tk5CbbA9MoYWHCbVMHkF2wj5fmbvI6HGNMC+JP4+h54HsRuVVELnJftwLf\nAc8FNjzTFC45qiejeiTyp/dXsbO4rOEvGGNMaDmcPPUiTrU7X58CQ1R1GLAWuB1ARAYBFwCD3e88\nISLhTbcbpjGO6ZvEcf068c8vM9lTUuF1OMaYFsKfanV/Ay4CBOch13Hu+4vdeSbIhYUJ9547jOKy\nSv78wWqvwzHGmCZ1OHlKVWcDu2pN+0RVK92P84AU9/2ZwGuqWqaqG4H1wJgm2xHTaLdNGUBhaQVP\nfLXe61CMMS1EREMLiEgPVV0N2P+qQ1i/5LZcM6EPj32xnrNGdmdCv05eh2SMMU0iwHnq58Dr7vvu\nOI2lGlnutNrxTAOmAfTo0aP2bNOEBnVrx9kju/PCt5u47Og0uifGeh2SMSbE+dOtbkbNGxF5K4Cx\nmAC7dmJfeneK4463l1NSXtnwF4wxJjQEJE+JyB1AJfDfxnxPVZ9R1dGqOrpTJ7sQFWi/Pqk/AA99\nstbjSIwxLUGDd45wuibU6B2oQEzgxUSGc+85w/jp03N5+NO13HHqIK9DMsaYptDkeUpELgdOAybp\nD6U+s4FUn8VS3GnGQ90TY7n86DSenbOBK8f3YmDXdl6HZAyqSsb2IhZvKWDFtj2ECcRHR9K3czxT\nh3QhLtqf/4IbL/jzk9F63psQNKZXBy4c04Pnvt7IGcO7MzQlweuQjDHmcDVpnhKRKcAC16bCAAAg\nAElEQVQtwARV9R0k7l3gFRF5COgGpAPzD3d75vBde3wfXpu/hb/PzODFn9ljYMZb2/eU8ts3lzJn\nXT4ACbGRRIQJhaUVVFQpd72zggn9OlFZrewsLmN3SQU7i8uIj47g4rE9uWhMD9rHRXm8F62XP42j\n4SJSiHNlLtZ9j/tZVdUu0YSY26YO4PPVO7ht+jLeue4YIsL96V1pjDFB65DzlIi8ChwPJIlIFvAH\nnOp00cCnIgIwT1WvVtWVIvI/YBVOd7vrVNUG2QkCiW2iuG5iX/72UQbfZuZzdJ8kr0MyrdR7S7dx\n54wVlFdWc+epAzlxUDI9OrRBRFBVFm3ZzRsLsvh6fT7x0RF0iIticLdYkuKjycwr5v6P1/D4F+t5\n7v9Gc3Rf+z32ggRqYFAReR6nS0Kuqg5xp90PnA6UA5nAz1S1QETScB6kXeN+fZ6qXt3QNkaPHq0L\nFiwIQPQt30fLc7jmv4u4feoAfjGhj9fhGGNCmIgsVNXRXscRjCxPNZ/SiipOeOArktpGM+PaYwgL\nk4a/ZEwT2VNSwV3vruCdJdsYkZrIw+ePoFdSXKPXs3ZHEdf8ZyFFpZXM/NVxdLA7SE3G31wVyFsG\nL+Ln2BGuTFUd4b4abBiZwzNlSBdOHJTMw5+tZcvOkoa/YIwxxgSxmMhwbj6pP8uy9vDB8hyvwzGt\nyDfr85ny6GzeX5bDzSf2482rxx1Swwic6sKPXTiSgpIKbnlzGYG6iWHqF7DGUSPHjjDNTET405lD\niAgL43dvL7c/PmOMMSHv7JHdGdClLfd/vIbyymqvwzEtXGlFFfe8t5KL//UdsVHhvH3t0dw4Kf2w\nH1cY3C2BW6cO4LPVO3hl/pYmitb4y8uHTX4OfOTzuZeILBaRWSIyvr4vicg0EVkgIgvy8vICH2UL\n1iUhhlun9Ofr9flMX2QFl4wxxoS28DDh1qkD2LKrhFe+2+x1OKYFW5G9h9P+8TUvfLOJy49O44Mb\nxjPs/9m77/A4qquBw7+z6r1bli3LsiT33ruxKcbGgOkxLRB6CQkkoYV8hJCQQEI1oQYIgYTeOwbj\nXgBXucm23OWmLqvX+/0xI7OWJatYq11J532efbw7M7t7dryau7edGx/eaq//iwmJjE+K4rF52ygu\n1+VX2pJbKkf1rB1xEEgwxgwHfoOVDajeCbS6fkTrunxsT0b2jOAvn28mp6jc3eEopZRSJ2VqnxjG\nJ0Ux97t0Cssq3R2O6mCqqmt4ZkE65z2zjMKySl67ZgwPnDuQAF+vVn0fh0O4c0ZfcosreG2FVvTb\nUptXjpzWjri8du0IY0y5MSbHvr8aK1lDn7aOrTNyOISHLxhMUXkVf/5ss7vDUUoppU6KiHDvWf3I\nLa7gxcU73R2O6kD25BRzyQsr+MfXW5kxqCtf3z6FKX1c11A/IiGCU/rE8MLiHRRp71GbadPKkdPa\nEec6rx0hIjEi4mXfT8JaO0KvaG2kd2wIN09N4aN1B1i0TYcqKqWUat+GxIdz9pA4Xlqyi8wjZe4O\nR7Vzxhje/GEvM59awvbMIp6aM4x/XjaC8EDXZ5K744w+5JdU8p/lu13+XsrissqRvXbECqCviGSI\nyLXAP4EQrLUj1onI8/bhU4BUEVkHvAfcZIzJrfeFlUvcOi2Z5Jgg7vtwAyUV2jqhlFKqfbvzzL5U\n1dTwxLfb3R2KaseyCsu57j+ruPeDDQxPCOfr26cwe1j3Nnv/YT3CmdY3hhcX76SsUpdVawuuzFZ3\nqTEmzhjjY4yJN8a8bIxJMcb0qJuy2xjzvjFmoL1thDHmU1fFpern5+3FwxcOISOvlMfnbXN3OEop\npdRJ6RkVxOVje/LOqn2kZxa5OxzVDn296RBnPrmYJenZ3H/2AF6/ZizdwgPaPI5rJvWioLSShVt1\ndE9bcGe2OuVhRidGctnYBF5ZtovUjHx3h6OUUkqdlNtOTSHAx4u/f5Xm7lBUO1JYVsld763nxtdX\nExfmz+e3TeKaSb3ctrDw+KQoIoN8df2uNqKVI3WMe2b2IzrYj3ve30Blta4RoZRSqv2KCvbjxilJ\nzNt8mFW7dbS+atwPu3KZ+dQS3ludwS+npfDhLRPpHRvi1pi8vRycObAr87ccprRCh9a5mlaO1DFC\n/X14cPZANh88wstLd7k7HKWUUuqkXDu5F11C/Pjbl2m64LlqUHlVNQ9/mcbPXlyBQ4R3bxrP787s\ni6+3Z/xUPntIHCUV1SzcmunuUDo8z/gfVx5lxqA4pg+I5YlvtrEnp9jd4SillFItFujrze2n92H1\nnjzmbT7s7nCUB9p6qJDznlnO84t2MGd0D7789WRG9ox0d1jHGNsrkigdWtcmtHKk6vXg7EH4ejn4\n/YcbtKVNKaVUu3bJqHiSY4L4+1dpVOmQcWWrqTH8a/FOznl6KVmFZbx81Sj+dsEQgvy83R3acby9\nHMwY1JX5WzJ1aJ2LaeVI1atrmD93zezHsvQc3l+z393hKKWUUi3m7eXgrhn92JFVzDurMtwdjvIA\nGXklXPbSSh76YgtT+8bw9e1TOK1/rLvDOqFZQ+IoraxmgQ6tcymtHKkGXT4mgVE9I/jL55vJLip3\ndzhKKaVUi00fEMvInhE88e02Xc+vEzPG8MGaDGY+uYSN+4/w94uG8MKVI4kK9nN3aI0a2yuK6GBf\nPk/VoXWupJUj1SCHQ/jbBYMpLq/iz59tdnc4SimlVIuJCL8/qx9ZheW8vEQTDnVGecUV3PrGGn7z\nznr6xYXw5a8nc8moHoi4J0V3c3k5hJmD4pifdlgr+C6klSN1Qr1jQ7hlagofrzug3bhKqQ5HRF4R\nkUwR2ei0LVJEvhGR7fa/EfZ2EZG5IpIuIqkiMsJ9kauWGNkzkukDYnlh8U5ydEREp7JwaybTn1zM\nN5sPc8/Mfrx1w3h6RAa6O6xmO2twHGWVNXyXpr/JXEUrR6pRt0xLJqVLMH/4cCPF5dpSoZTqUF4F\nZtTZdg8w3xjTG5hvPwaYCfS2bzcAz7VRjKoV3TWjH6WV1Tz9Xbq7Q1FtoKSiij98tIGr//0jkYG+\nfHzrJG46JRkvNy3oerLG9IokOthPh9a5kFaOVKP8vL342wWD2Z9fyuPfbHN3OEop1WqMMYuBuquD\nzgb+Y9//D3Ce0/bXjGUlEC4icW0TqWotKV2CuWRUD/73/R5drqKDW7s3j1lzl/K/7/dy/eRefPzL\niQzoFurusE6Kl0M4a3BXvkvL1AZrF9HKkWqS0YmRXD42gX8v28X6ffnuDkcppVwp1hhT2yx7CKhN\nYdUd2Od0XIa97RgicoOIrBKRVVlZWa6NVLXIHaf3xtvh4B9fb3V3KMoFKqtrePybbVz0/Aoqqmp4\n47px3DdrAP4+Xu4OrVXMGhxHeZUOrXMVrRypJrt7Zj9iQvy454MNVOo6EUqpTsBYC701a7E3Y8yL\nxphRxphRMTExLopMnYwuof5cN7kXn6Ue1Aa/DmZHVhEXPrecufO3M3tYN768fTLjk6PcHVarGpUY\nSZcQHVrnKlo5Uk0W6u/Dn84dxJaDR3hJM/0opTquw7XD5ex/a5tn9wM9nI6Lt7epduiGKUlEBvny\n8Jdputj5SaquMaQdOuLW82iM4bUVu5k1dwl7c0t49vIRPH7JMEL9fdwWk6tYQ+viWLA1kyIdWtfq\ntHKkmmXGoK6cOTCWJ7/dxu5sHautlOqQPgGusu9fBXzstP3ndta6cUCB0/A71c6E+Pvwq1NTWLEz\nh4XbdPhjS6VnFnHx88uZ8eQS/rtyj1tiOHykjKv+/SP3f7yJcUlRzLt9CmcN7tjTAWcNsYbWzd9y\n2N2hdDhaOVLN9uDsQfh6Objvow3a2qaUatdE5E1gBdBXRDJE5FrgYeAMEdkOnG4/BvgC2AmkA/8C\nbnFDyKoVXTa2Jz2jAnnkyzSqa7Q8a46q6hqeX7SDs+YuYUdWMYO7h/GXz7ew9VBhm8bxeepBpj+x\nmB935fKX8wbx76tH0yXUv01jcIeRCRHEhurQOldwaeVI14/omGJD/bl7Zj+Wpefw3uoMd4ejlFIt\nZoy51BgTZ4zxMcbEG2NeNsbkGGNOM8b0NsacbozJtY81xphbjTHJxpjBxphV7o5fnRxfbwe/m96X\ntEOFfLhWR0g21bbDhVz43HIe/jKNaX1j+OY3U3jl6tGE+Ptw25trKKusdnkMBaWV3P7WWm59Yw2J\n0UF8/qtJXDGuZ7tZ0PVkOewFYRduy6KwrNLd4XQoru45ehVdP6JDumxMAqMTI3joiy1k60J6Siml\n2qlZg+MYEh/G4/O2tsmP+vassrqGf363nbPnLmVfXilPXzqc568YSZcQf2JC/HjskqFsO1zEQ59v\ncWkcy9OzmfHkYj5NPchvzujD+zeNJykm2KXv6YnOHhJHRVUN87do1rrW5NLKka4f0XE5HMLfLhhM\nSXk1D3662d3hKKWUUi3icAj3zOzHgYIy/rN8t7vD8VhbDh7h/GeX8ei8bZwxIJZ5d0zhnKHdjump\nOaVPDNdP7sXrK/fw1cZDrR5DWWU1f/5sM5e99D0Bvl58cPMEfnVab7y9OucskREJEXQN9efzDTq0\nrjW549uk60d0ECldQrhlWjKfrD/Agq3aaqGUUqp9mpAczdS+MTyzIJ38kgp3h+NRKqpqePLbbZz7\nz6UcKijjuctH8MzlI4gO9qv3+DvP7MeQ+DDufj+V/fmlrRbHxv0FnPP0Ul5euourxvfk89smM7RH\neKu9fnvksLPWLdqaxcKtmToPvJW4taqt60e0fzdPTSalSzB/+HCjrtSslFKq3bp7Rj8Ky6t4duEO\nd4fiMTbuL2D2M8t48tvtnDU4jnl3nMLMRrLA+Xo7mDtnOFXVNfzyjTUnXdmsrjE8syCd859dRkFp\nJf+5Zgx/mj2IAN+OsaDrybpiXAJRwb5c/e8fmfnUEv753XYW6Tykk+KOypGuH9GB+Hl78fAFg9mf\nX8pj87a5OxzVQRljraGxLD2bkgqthCulWl//uFAuGB7Pq8t3t7jHo6yymi0Hj/D6yj3c+sYaHvkq\nrZWjbBsVVTU8Pm8r5z2zjOyicl68ciRPzRlOZJBvk56fGB3EoxcPZeP+AmbNXcqGjIIWxbE3p4Sf\nvbCCf3y9lekDuzLvjimc0kcbxp0lxQSz6M5pPHrxUBwiPDpvG1e98gPTn1hMQalWkFrC2w3vWbt+\nxMMcv37EL0XkLWAsun5EuzEqMZIrxiXw6vJdzB7WrdN3c6vWcSC/lKXp2Syzb9lFVuujj5cwPCGC\nqyckMmNgVxyOzpGZSCnler+Z3odPUw/w2LytPH7JsBMee6SsknV780nNyGfj/iNsPniEfXkl1I5s\n8vESHCLcOb1vs65TxhiyisoxBny8HE2ukLSW1Ix87nw3la2HC7lgRHfuP3sA4YHNj2Hm4DjeDQ/g\n1v+t4cLnlnP2kDjOGdqNAd1CqayuwdvhIDbUr97scsYY3lm1jwc/3YzDITw1Zxjn1pnfpH7i6+3g\nopHxXDQyniNllSzbns2tb6zh8Xlb+dPsQe4Or91xaeXIXj9iKhAtIhnAH7EqRe/Ya0nsAS6xD/8C\nOAtr/YgS4BeujE21rrtm9OObzYe5+/1UPr1tEj6ddHKkarkjZZWs2JHDsvRslqZnszPLWmQ4OtiP\nSSnRTEyJJibEj5U7c5m36RC3/G8NA7uF8sC5AxmdGOnm6JVSHUH38AB+MSGRF5fs5LpJSQzoFnrM\n/rziCt5fk8EHa/az5dCRoxWhxKhABncP47zh3UmOCWJYj3CWpefw+w83cKCglPiIwCa9/4H8Uu7/\neCPfOmUfu3dmP248JbnVPmNDyiqreWr+dl5cvJPoYF9euXoUp/aLbfyJJzCsRzif3jaJf3y9lc9T\nD/BBnXTpwX7e9O0awo1Tkpg+sCsAWYXl3PtBKt9uyWRCchSPXjyUbuEBJxVHZxLq78PMwXFcOa4n\nr6/cw0UjezA4PszdYbUr0p4nb40aNcqsWqXLTHiKrzcd4sbXV3PXjL7cMjXF3eEoD1dRVcPavXks\ntStD6/flU2MgwMeLsUmRTEqJZlLvaPrGhhzXWlhdY/ho7X6e+HYbWYXlvHbNGMYmRbnpkygRWW2M\nGeXuODyRllPtT0FJJVP+sYDB3cM4Z2gc32zOZH9+KaUVVRzIL6OiuoZhPcI5tV8XRiREMKRHGKH+\nPse9zsqdOcx5cSWvXTOGKU0YCvbR2v3c9+EGagzcMCWJ2FB/3v5xL5mF5Sy5a5pLM7Kt2ZvHXe+l\nkp5ZxCWj4rlv1gDCAo7/TCejoqqGpelZHCwow8fhoLyqmu2ZRSxLz2ZHVjG3TE1mSHw49324gcLy\nKu6e0Y9fTEjU0QEtVFBayWmPLaJ7uD8f3DIRLz2PTS6r3DGsTnVQZw7syoyBXXnq2+2cNSiOxOgg\nd4ekPIgxhq2HC1m63aoMfb8zl9LKahwCQ3uE88tpKUxMiWZ4QgS+3if+EeDlEC4cGc/UvjFc8sIK\nrvvPKt68YRyDumvrmFLq5IQF+nDrtGT++kUaS9Oz6R4eQP+4UAJ9vThjgB8XjIinf1xoo6+TFGOV\ngbuyixutHK3ek8fv3l3PiIQIHrtkKD0irZ6mqGBfbnx9NfPTMjnT7llpTWWV1Tz+zTZeWrKTrqH+\n/OeaMS6b0+Pr7ai3J6qsspo/fbrpaCKMgd1CefNnw+gTG+KSODqLsAAf7pvVjzveXs87q/Zx6ZiE\neo8zxrAsPYflO6wRG7klFZzSJ4Zzh3Y7+j3sbLTnSLWqw0fKOP3xRQzuHsb/rhur44M7uYMFpSzd\nnm0Plcs5umBwUkyQ1TOUEs3YpKiTaqE8kF/Kxc+voLSyms9um6TDL9xAe44apuVU+1RRVcNHa/cz\nsHsoA+JCW1SWGWMY/MA8LhzR/YTzPvKKK5g1dwleXsJnt00+5npYVV3D5L8vIKVLMK9fO7ZFn6Uh\nq3bnctd7qezMLubSMQn8/qx+hNTTA9ZWPlybwcGCMq6blNRoA5lqGmMMl7ywgp1ZxXz3u6nHfbc+\n33CQFxbtZPPBI3g7hISoQAJ9vdi4/wgA3cL8Se4SzJD4MM4b1p3eLqqwFpdXsXBrFmv35lFQWklp\nZTWn94/l7CFxrdpjqj1Hyi1iQ/25Z2Y/7vtwI++uzuCSUT0af5JqVE2NYW9uCT2jAj26wnmkrJKV\n9ryhJcfMG/Jloj1vaFJKdKtWYLqFB/DatWM49+ml3P72Ot68fpwOH1BKnRRfbweXjD658ktESIoJ\nYmd2cYPH1NQYfvvuerKLKnj/5gnHNRR5ezmYMzqBJ77dxu7s4lYZkVFSUcWjX2/j38t30S0sgP9d\nN5aJKdEn/bon6/zh8e4OocMREf54zkDO+edS5s7fzv+dPYDSimreWbWPfy3ZSUZeKckxQfz9wiGc\nO6wb/j5WevR9uSV8tfEQmw4UkJ5VxPOLdvLMgh0MjQ/jt9P7MqVPDMYYPt9wkPX78pkzJoHkmOBm\nxZaRV8LCrVks3JrFku1ZlFfV4O/jIDzAF4Phs9SDPDpvKzMHdSU80JfQAB/OHdqt1Yd71kcrR6rV\nXTo6gY/XHuChz7cwrW8XYkLqXyhONcwYw/bMIlbssLq6V+7MpaC0kl9OS+F3Z/Z1d3hH1c4bqk2i\nsD6jgOoac3Te0GVjEpiYEk2/rsfPG2pNyTHBPDh7EL99dz3PLEjnV6f1dtl7tYZDBWW8vnI376zK\nID4igGsm9mLmIGvIzJGyKtZn5LNmTx5dw/y5eGSPVmlFLaus5uWlu/hw7X6m9Y3hmkm9iAvTXjal\nXKlXdBCrduc1uP/FJTv5Li2TB2cPbHDS/JwxPXj6u+387/s93DdrwEnFs3JnDne/n8qenBJ+Pr4n\nd83oR7Cf/hTsyAZ1D2PO6B78Z/luvBzCe6szyC2uYERCOPefPYDT+8ceN6+rR2Qg109JOvo4q7Cc\nT9Yf4LUVu/n5Kz8wY2BXcorL+XF3HiLw8tJdzBrSjRB/b/bkFFNTA/ERASREBtIzOoiEyEBKK6o5\nkF/KxgMFLNqWdbTxtHt4AHNG92DGoDhGJ0bg7eWgpsYwPy2TFxbt4LUVeyivqgFgap+YNqkc6bA6\n5RLpmUWc9dQSzhzUlacvHd6s51ZW15CaUcCaPXmsz8invKoGh0CQnzdxYf50Dw+kb9cQ+seFEOjb\nMS7qxhj25JSw3KkyVDsErUdkAOOTosgtrmB+WiZvXj+OcW5KPmCMYdvhIpZsz2JZejbf78qlpMKa\nNzQkPpzJvaPteUPh+Hm37QJ9xhhuf3sdn6Ue5M3rxzGml+dlsFu7N49Xlu3myw0HqTGGaX27sCOr\niN05JTgEapwux7WPe0YFcuu0FJJjgokM8qVbuH+zzu3BglIWpGXxwuId7MkpYXD3MDYfPIIAKV2C\nCfT1IsDXi5evGn201bC5dFhdw7Sc6tye+nY7T87fxpYHZxz39/Xj7lzmvLiSGQO78s/Lhp+wAemm\n11ezem8eP/z+tBY1NBWXV/HIV2m8tmIPCZGBPHLhEMYnaxKbziKnqJypjy6ksKyK0/t34cZTkluU\n5bW8qpqXluzi6e+2E+znze+m9+XU/l14eckuXl+5Bz9vBz2jgnAIZOSVkllYftxr+Hk7GJsUxZTe\n0Uzt24XkmKBGv9NlldUcKaskKsjvpEaG6LA65VYpXYK5dVoKT3y7jQuGd2davy4nPL6quobPUg/y\n5caDLEvPoajcWuize3gAoQE+GGM4UlrJ4cJyqu1fkCJWq9yAuFAGdgtjQDdrbHh76anan196tGdo\nxY4cDhaUARAb6sfk3tGMT45ifFLU0QmRxeVVnP30Uu54ex1f/npyi9adaIkG5w1FB3HRyHgmpkQz\n7iTnDbUGEeEv5w0iNaOA619bxbs3jfeICb2V1TV8ufEQryzdxbp9+YT4eXP1hESumpBIj8hAamoM\n36VlsmZvHv4+XgT6ejGgWyjDeoTz/a5cHvkyjbveSz36eiJWi1yv6GCSY4JIigkmNsSP6BA/qmsM\n2YXl7M8vZfOBI6TuLyA9swiA3l2Cj2bN2pdbwusr97Aru5iyympKKqo1/b5SLtArJghjYHdOMf26\n/pTEIaeonNveWEuPiAAevnBwoz8OJ/eJ5qtNh+zh1c0bWrc8PZu73k9lf34pv5iYyJ1n9u0wDYuq\naaKC/fjg5gmIQEqXlpeLft5e3DothZ+P74mPl+Nohf/es/pzz8x+x32Pyyqr2Ztbwp6cEoJ8vegW\nHkBcMxv4APx9vFrceNcS2nOkXKaiqoZZc5dQUlHNvDumEOTUdb8vt4T0rCK8HcLhI+U8uzCdnVnF\ndAvz55S+XZjSO5qRiRF0CfE/5jWrawwH8ktJO1TIpgMFbD5gLbyXkffTauZdQvyOVpQGdgujZ1Qg\n2UXlZOSVsulAAWv35hPq78PbN45r0/k7mYVlrNiRw8qdOSzfkcOenBIAIoN8GZ8UxfjkKCYkR9Er\nuuFWlA0ZBVzw3DLGJ0fz4pUjXXKxOFJWyfc7c1m6PYuldopVgKgga97QJLt3qLuHJj7Yl1vChc8t\nRwTeu2mC27Lt5BVX8MYPe3l9xR4OHSmjV3QQV09I5MKR8c0axlJdY9h84AjZxeXkFFWwL7eEXdnF\n7MgqYmdWMaWV1fU+LzbUj4HdwhiXFMnUvl3o3SXYZd937TlqmJZTndvG/QWc/fRSnrt8BDMHxwHW\nPKOrX/2RlTtz+ODmCU3KsrntcCHTn1jMoxcP5aKRTZubU1hWyd++TOON7/fSKzqIv180RNeEU52a\n9hwpt/P1dvDwhYO56PkV/PGTTUzuHU1GXinzNh9m/b78Y47tGxvC81eM5MyBsSf8AeflEHpEBtIj\nMpAzBvyUErSgpJLNB62K0uYDR9h0oICl27Opqjm28h/q70238AB+2J3LpgNHXJr6Oa+4gu93WRWh\nFTty2G634If4ezMuKYqrJyQyPjmKPl1CmryOw+D4MP48exD3friBn7/yAy9dNare9TWMMVRU1zSp\ndaaiqoZ1+/Kt9Ya2Zx2dN+Tv42BsryjmjE44ut5Qe1hvokdkIK9fO5aLn1/OrLlLmNInhsm9oxnZ\nM5Kk6KCjn6GovIrthwtJzywiv6SSovIqvBxCt/AAooN9ybJ7YIrKqqisrkFEiAnxo0uIHyN6RpDU\nQCV266FCXl2+iw/W7Ke8qobJvaP56wWDmNqnS4vOn5dDGpyLUFNjOFxYRnZhBdlF5Xg5hOhgP7qG\n+RMZ1DY9i0qphvWyEyg4J2V4btEOFm/L4i/nDWpyGZQSE0xYgA+rduc2qXK0eFsW935gLUB7/eRe\n/OaMvgT4tu1QZ6XaK60cKZca2TOSK8ZaqzS/tzoDgAFxodwzsx+jEyMxxuDlEIbGh5/UD++wQB9r\nGJrTGOryqmq2Hy5iX24JMSF+dAsPoGuoP3klFYx+6FvmbT7cqpWjwrJKftiVaw+Vyzm6enqgrxej\nEyO5aGQ8E5KjGdAt9KTGzM4Zk0Cgnze/fWcd5z2zjBEJEQT7eZNfUsHe3BIOFpSRU1xBRVUN0cF+\n9O0azITkaC4bk0BEkO/ReUO1laG684ZuPiWZiSnRjOjZ9vOGWkvfriG8ecM4Xlm6myXbs/gs9SBg\nVY5D/H3IL6mguKL+Hpe6An298LEniBbawz0BEuwK+oUj4unXNYQFWzN5ZdkulqXn4O/j4IIR8fxi\nYqJLh/Y5HEJcWIAmVnAREbkDuA4wwAbgF0Ac8BYQBawGrjTGVLgtSOXRgvy8iQ31Ozr5fOXOHB6b\nt5Vzhnbj8rH1rztTH4dDGNUzgh93557wuCNllTz02RbeXrWP5Jgg3r95AiMSIk7qMyjV2eiwOuVy\nFVU1rNmbR1SQL11C/d0+NwXg4ueXU1RezZe/ntzi1yitqGbVntyjPUMb9ls9Lr7eDkb1jGB8UhQT\nUqIYEh/ukvkci7dl8fev08gtqqCwrIqwQB8SIgPpFh5AVJAvQX7e7MstIe1QITd1M7cAACAASURB\nVBv2F+Dv42BCcjQb9heQVfjTvKHaFNvjk90/b8gVjDGkZxaxdm8+6zLyKauoJjzQl+gQX1Jigukd\nG0J0sC9Bvt5UVNdwqKCM7KJyooP9jhsbXVZZzf78UpbvyGFBWiZLtmdRWW0IC/ChoLSSuDB/rhzf\nk0tHWxXRzqIjDqsTke7AUmCAMaZURN4BvgDOAj4wxrwlIs8D640xzzX0OlpOqUtfXElZVTUvXjmK\nWXOXEOznzSe3TWp2lrjnFu7gka/SWP2H04kKPn5u7YK0TO79YAOZhWXceEoyvz6td5vO01DK0+mw\nOuUxfL0dbsuu1pAzBsTy1y/SyMgrIT6iaXNSyquqWbc3/2hlaO2+PCqrDd4OYViPcG6dmsy45ChG\nJES0SYE0pU9Mo6uu19p2uJCXl+xi+c5sxiVFMTklmgkpUU3+7O2ZiNA7NoTesSGNrlvi7/AiMTqo\nwbVE/H28SI4JJjkmmCvH9SSvuIJP1h/gx925nDmwKzMGddXEBh2LNxAgIpVAIHAQOBW4zN7/H+AB\noMHKkVK9YoL4PPUgd7y9joLSSv5zzZgWpc8elWj1AK3ek8f0gV2Pbi8oqeTBzzbz/poM+sQG88KV\nExnaI7zV4leqs9HKkeqUTu9vVY6+3XyYqyf2qveYquoaUvcXsMKuDK3ak0tZpZVWfFD3MK6Z1IsJ\nydGM6hlxTLIJT9QnNoRHLhri7jA6nIggX66yM8+pjsUYs19EHgX2AqXAPKxhdPnGmNrxlRlA97rP\nFZEbgBsAEhKaPnRKdUxJ0UEUlFayND2bhy8YTP+40MafVI/B3cPw9XKwyqly9M3mw9z34QZyiiu4\n7dQUfnlqSrsdDq2Up/DsX3RKuUhSjJUG+ZstP1WOamoMmw8esSpDO3P4YVfu0ZTi/bqGcOmYBCYk\nRzOmV2SHHH6mlPqJiEQAs4FeQD7wLjCjKc81xrwIvAjWsDpXxajah+SYYADOH96dnzXSe30i/j5e\nDIkP48fdueQVV/CnTzfx0boD9OsawitXj3ZpgiGlOhOtHKlO64wBXXlpyU5eWrKTH3fn8v2uXPJL\nKgFIignivOHdGJ8UzbikyHrHdyulOrTTgV3GmCwAEfkAmAiEi4i33XsUD+x3Y4yqHZiYEs1D5w/i\n/OHdTzqd/qjESF5eupMznlhMfkkFt5/em1umpuDrrcN5lWotWjlSndaZA2N5ftEO/vL5FnpEBjB9\nQCwTkq3EBLGh/o2/gFKqI9sLjBORQKxhdacBq4AFwEVYGeuuAj52W4SqXfD1dnD52J6t8lrjkiJ5\nftEOYkP9eO2aMQzo1rIhekqphmnlSHVawxMiePuGcXQLD3DbQqFKKc9kjPleRN4D1gBVwFqsoXKf\nA2+JyF/sbS+7L0rV2ZzSJ4b3b57AkPgwTf6ilIu0eeVIRPoCbzttSgLuB8KB64Ese/vvjTFftHF4\nqpMZ62FZ9JRSnsMY80fgj3U27wTGuCEcpRARRvbUdYuUcqU2rxwZY7YCwwBExAtrvPaHWIvrPWGM\nebStY1JKKaWUUkopd/fJngbsMMbscXMcSimllFJKqU7O3ZWjOcCbTo9/KSKpIvKKnUb1OCJyg4is\nEpFVWVlZ9R2ilFJKKaWUUs3mtsqRiPgC52KtHQHWCuPJWEPuDgKP1fc8Y8yLxphRxphRMTExbRKr\nUkoppZRSquMTY9yzPp2IzAZuNcZMr2dfIvCZMWZQI6+RBTR1SF40kN3MMD1Fe44dNH530/jdqz3H\n39TYexpjtLWqHs0sp2q15+8MtO/423Ps0L7jb8+xQ/uOv7PE3qSyyp2pvC/FaUidiMQZYw7aD88H\nNjb2As0pjEVklTFmVLOj9ADtOXbQ+N1N43ev9hx/e47dU7Sk0tjez3t7jr89xw7tO/72HDu07/g1\n9mO5pXIkIkHAGcCNTpv/LiLDAAPsrrNPKaWUUkoppVzKLZUjY0wxEFVn25XuiEUppZRSSimlwP3Z\n6trSi+4O4CS059hB43c3jd+92nP87Tn29qy9n/f2HH97jh3ad/ztOXZo3/Fr7E7clpBBKaWUUkop\npTxJZ+o5UkoppZRSSqkGaeVIKaWUUkoppehglSMRmSEiW0UkXUTuqWf/b0Rks4ikish8Eenpjjgb\n0lj8TsddKCJGRDwq7WJT4heRS+z/g00i8kZbx3giTfj+JIjIAhFZa3+HznJHnPURkVdEJFNE6k2B\nL5a59mdLFZERbR3jiTQh/svtuDeIyHIRGdrWMZ5IY/E7HTdaRKpE5KK2iq0pmhK/iEwVkXX23+6i\ntoyvo2rPZZaWV+6jZZX7tOeySsupZjDGdIgb4AXsAJIAX2A9MKDOMdOAQPv+zcDb7o67OfHbx4UA\ni4GVwCh3x93M898bWAtE2I+7uDvuZsb/InCzfX8AsNvdcTvFNgUYAWxsYP9ZwJeAAOOA790dczPj\nn+D0vZnZ3uJ3+o59B3wBXOTumJt5/sOBzUCC/dhj/nbb6609l1laXnl87FpWuS9+jy2rtJxq+q0j\n9RyNAdKNMTuNMRXAW8Bs5wOMMQuMMSX2w5VAfBvHeCKNxm/7M/AIUNaWwTVBU+K/HnjGGJMHYIzJ\nbOMYT6Qp8Rsg1L4fBhxow/hOyBizGMg9wSGzgdeMZSUQLiJxbRNd4xqL3xizvPZ7g+f97Tbl/APc\nBrwPeNL3HmhS/JcBHxhj9trHe9xnaIfac5ml5ZX7aFnlRu25rNJyquk6UuWoO7DP6XGGva0h12K1\nTniKRuO3u5d7GGM+b8vAmqgp578P0EdElonIShGZ0WbRNa4p8T8AXCEiGVitKre1TWitorl/H57M\n0/52GyUi3YHzgefcHUsL9QEiRGShiKwWkZ+7O6AOoD2XWVpeuY+WVe2HJ/3NNkrLqZ+4ZRFYdxOR\nK4BRwCnujqWpRMQBPA5c7eZQToY31lCFqVitKYtFZLAxJt+tUTXdpcCrxpjHRGQ88LqIDDLG1Lg7\nsM5CRKZhFTiT3B1LMz0J3G2MqRERd8fSEt7ASOA0IABYISIrjTHb3BtW59Deyiwtr9xOyyo3a6dl\nlZZTTi/UUewHejg9jre3HUNETgfuA04xxpS3UWxN0Vj8IcAgYKH9pe0KfCIi5xpjVrVZlA1ryvnP\nwBp/WwnsEpFtWIXPj20T4gk1Jf5rgRkAxpgVIuIPROOB3c/1aNLfhycTkSHAS8BMY0yOu+NpplHA\nW/bfbjRwlohUGWM+cm9YTZYB5BhjioFiEVkMDAW0ctRy7bnM0vLKfbSs8nDtuKzScsrWkYbV/Qj0\nFpFeIuILzAE+cT5ARIYDLwDnetD44VonjN8YU2CMiTbGJBpjErHGsnpKQQNNOP/AR1itcIhINFYX\n6M62DPIEmhL/XqwWCUSkP+APZLVplC33CfBzOxPQOKDAGHPQ3UE1lYgkAB8AV7bH3gpjTC+nv933\ngFvaUYED8DEwSUS8RSQQGAtscXNM7V17LrO0vHIfLas8WHsuq7Sc+kmHqRwZY6qAXwJfY52Md4wx\nm0TkQRE51z7sH0Aw8K6d6q/uBcVtmhi/x6ovfuBeESkUkRK71S0eyBGRzcAC4FVgmb1/gTilqRWR\nO0Uk207HONhp+0QRafU/1iae/98C14vIeuBN4Gpjp0RpbSJyuoisEZFiEckQkUuc9g2zx9OW2P8O\nE5E3gRVAPxGpts/d4yJyk/20NGAYkA78C7ilnve8WkSWuuLzNMaO/wdgoP15rxWRm5zivx+IAp61\n/3Y95UcWcDT+FUDfBuL3aI3Fb4zZAnwFpGL9P71kjDlhOlh1Yu25zOpg5dVWrFE0P4hIvog8ah/2\nNVZm6TLgELCgthdARHxE5HsR6VHPy7dl7C4rq0QkTkQ+EZEDYqViT6yz30+s1MpHROSQiPymzv7T\nRCStbvluX2tSsa71lSJyf+21RkQmYiXC2EkDZZWIPCAi/23OZ2lNIjIfK1tgQ9d6jy2rtJxqBuMB\n6fn01jFvwEDAz77fD6uAGWk/jgYKgIuxWrX+Aay098Vh/ZgPxSoEPrO3e2O1QCZ6wGfzduFrD8Aa\n/jDT/sxRQLK9zxfYA9wB+AG/sh/72sfutc/f2TiluwQ+B8Y28r5XA0vddU6ARKwsSy47t3rTm970\n5nzDqjy8jVUJnWSXSwPtfV/Y1+HuQA7Q1d5+N3CXB8TuynIoFqtiMt6+LifW2f83YAkQAfS3y/cZ\n9j6Xle9YySb+665zhtWbmOHu/3u9ufbm9gD01jluQF/gIHCJ/fgGYLnT/iCg1K5EjQXetLf3Azbb\n938H/L4J7zUGWAUcAQ4DjzvtOxfYBOQDC4H+TvsMkOL0+FXgL/b9qVjjWe+2C4HX7e2zgXX2e+1w\nKhzCgJftz7wf+Avg1cRz9Qbw5wb2TbdfT5y27cUaXx4LrLC3+QMl9v2LgBcbec/+WOl2q4EiIN/e\nPgtrrY8jWBmEHnB6TqJ9zq61Y1hsb/85VoUtB/g/YDdwur3PAdxjn6scrB7GSKfPYez3LwLGu/t7\nqze96a3j3uxypwLo47TtdeBh+/4WfmrgW2mXLT2xWqV9Gnltf+C/9nUuH2s4XKy9rxvW8LFcrB6S\n652ed7TcsR9PxenHuH09vRurdbwcq1LRA2soV5b9fv90Ov4a+3PkYfU29WzmOfKm/srRAWC60+M/\nA2/Z911SvmOVcxVApV1GrLe3/8L+jIVYvU431j1/HF9234VVPh8ArsOp/MdqeHzULpMOA89jTfCv\n/Rw1TuVUN3d/j/XW+rcOM6xOeSYReVZESrBaig5itcSB1au0vvY4Y02g22FvTwcGi0g4cDqwyR6+\nMAfrgtWYp4CnjDGhQDLWD3BEpA9WK+HtQIwdy6f2uO2m6ApEYhWON4jIGOA14E6sxcemYBVcYBVw\nVUAKMByrUnNdE99nnB3vBhE5KCL/FZFIe99AINXYV3Bbqr09C4gSkXjgDKzzFgL8Abj3RG9orO7o\nm7AqV8HGmHB7VzFWZSccq6J0s4icV+fpp2BVrs4UkQHAs8DlWC2EYRybhvU24Dz7Od2wCuxn7H1T\n7H/D7RhWiLXSe75Y47iVUqo19QGqzLFzQ9ZjXU8BNgLT7WtqIlYZ9RRwp7ESNZzIVVjXvx5Yvf83\nYf2wBmttogysa+BFwF9F5NRmxH0p1vU4HOtH/WdYDVKJWNfbtwBEZDbwe+ACrDJvCVYZeFJEJALr\n+r7eabPzeXNJ+W6M+Qr4K9ZiyMHGmKH2rkys0RKhWBWlJ8RKJV+rbtk9A/iN/f4p2HPLnDyM9d0Y\nZu/vDtxvf46ZwAH7/YONMQdEZJKItIcshqqJtHKkXMoYcwtW5qLJWC1btdmWgrG63Z0VACHGGtf9\nENYqzbOwWpSewmr5OV9EFonIx3aBVZ9KIEVEoo0xRcZaSA7gZ8Dnxphv7ILtUazWoAlN/Dg1wB+N\nMeXGmFKsHpNX7NerMcbsN8akiUgs1irftxtjio01kfoJrIt/U8QDVwIXYmVHCgCetved6LzVADdj\nTaT8HdbY7T/Zzx1ij/v+WkQGNTEOjDELjTEb7M+XilWw1k0n/ID9OUuxCvpPjTFLjbVA4f1YhXet\nm4D7jDEZxsq89QBwkYjUmznTGLPXGBNu7EXdlFKqFQVj9Yo7K8Aqs8C6jt6M1ctzBzARq3dil10G\nLRKRixt47UqsSlGKMabaGLPaGHPErghMxEqZXGaMWYeV2aw5a7LMNcbss6+5Y7AqWXfa1+EyY0zt\n3NGbgL8ZY7YYa67SX4Fh4jS/t4WC7X+dyyLn8+bK8v04xpjPjTE7jGURMA/rN0etumX3JcC/jTGb\njLXI8gO1B4qIYPV83WGMyTXGFGKdtwbLb7u8C29ov2p/OlIqb+WhjDHVwFKx1uq4GZiL1R0dWufQ\nUKyCB2PMm9gtXCIyC6tStZafWqfOxarc1HfBuhZ4EEgTkV3An4wxn2EVIHuc4qoRkX00fYG5LGOM\n80rvPfipJ8xZT8AHOCg/rRXg4NiF7U6kFOvCvQ1ARP4KfGvva+y8zQfm288bipWa806sHq1Jdswv\nYfdONUZExmK1og3CmtfkB7xb5zDnz9XN+bExpkREnFOZ9gQ+FBHn9TaqsYYEKqVUW2rseroHq6EL\nsbJfrcAaBfA01jylz4GNIjLfGJNb53Vex7revmX3kvwXKyV7N6D2R3etPVjX6qZyvub2APbYlZ+6\negJPichjTtsEq8zbU8/xTVVk/xuKNRy79n6h035Xle/HEZGZwB+xenscQCCwwemQumV3N6yh97Wc\nz2eM/fzVTuW3AF5NiUV1DNpzpNqSN9YwN7Dm/dR2iSMiQfa+Tc5PEJEArFab32L1ouwzxhzBGr89\npL43McZsN8ZcCnQBHgHes1//AFZhUfvaglWw1K6hUIJ1UazVte5L13m8z+nz1N1eDkTbvR7hxphQ\nY8zAeo6tT2qd93K+vwmrF8h5hbYhHH/eBPgnVsKGaKz5Tns4wXnj+M8H1vynT7BWug/DGntdd3U4\n5+cdxOr5qo0jAKv1tNY+rLUfwp1u/saY/Q28v1JKuco2wFtEejttG0qd66ntfuBfxpjDwGBglTGm\nAGt4XErdg40xlcaYPxljBmCNTjgbq3foABBpD3mulcBP5VAxJy6H4Nhr5T4goYHe931Y82+cr7cB\nxpjl9RzbZMaYPKxr/VCnzc7nzWXlO3XKCRHxA97HqkzF2j04X3BsOVW3bDmmnOLYdZWysRooBzqd\nszBjTG1vmZZTnYBWjpRLiEgXEZkjIsEi4iUiZ2KNk55vH/IhMEhELhRrgbr7sebSpNV5qT9grfR9\nAGtyZF972No0GlhzQkSuEJEYe5hZ7TjgGqy5R7PsFKM+WBfkcqC2oFgHXGbHO4PGV6N/G7jRfr3u\nIvKZiPQz1poM84DHRCRURBwikiwip9jxJUo9qVGd/Bv4tYj81m6tvAdrTDlYSSSqgRdE5CER+aW9\n/bs6r3EdsMYespEDBNjzgRo8b1gTT+PrzMEKwWrlLLPnWF3WyDl5DzhHRCbYr/MAxxZSzwMPyU9p\nXWPscfFgzZmqAZIaeQ+llDpp9hySD4AHRSRIrFTSs7F6fY6yr51TgefsTbuAU+2yqDdW2USd50wT\nkcEi4oU1dK8SqDHG7MMqc/4mIv5iLRh6LVbPEljl0FkiEikiXbHmyJ7ID1g/9h+2P4O//TnAut7e\nJyJ/tmPqKyIrnGJcKCIPNPTCdtnsZz/0sx/Xeg14TqxUyv2whnG/au+rLd//KiIP0YrlO1Y5lSgi\ntb9fa0c0ZAFVdi/S9IY+k+0d4Bci0t8uY/+vdof9u+FfWPOWutjnobv9G6b2/aNEJKyR91DtmfGA\nrBB663g3rK7pRViVkyNYXdzX1znmdKxEDaVYP/oT6+zvh9WC5OW07U6slp3NwOAG3vu/WBM0i7Ba\nqs5z2ne+/dwCO76BTvtG2ccXYhWOb1InW12d90nEGpqQaj8nHTjT3heGVZBm2O+1Fphj75uMNcyt\n3mxHWD1sh7Eu9ll2LBFO+4cDq7EqEmuB4XWeH401kTjUadvlWJl6dgPTGnhfX6xhIrlAtr3tIvsz\nFmJV0P6JnUaVBlJvY6UE38tP2er2A5PtfQ6sibBb7dfcAfzV6bkP2p85H2voX4L9/5jg7u+03vSm\nt453w5qo/xFWj81e4LJ6jlmA01IIWL0im+2y6DcNvO6l9nWu2L6ez629VmL1WnxmX2t3ADc5Pc8f\nq+HtiF223MHx2epOr/NeCfZnyLFjmuu07w6soW+1GUdfcdq3AzjjBOfG1L057Qu046/NCvubOs+t\nLd9rgMW0XvkeBSzFSuazxt52qx1DPlZ5+RYnKLvt7fdilYkHsIb7G6wRErX/B3/FqqAdwcqE9yun\n577CT1kIu2GV6UXu/i7rrfVuYv9HK6WaSUTewmpl3Apsx0oLPkhErsbKyOaFNVfnMayKx5VYPVXz\nsQrhb7EytcVgDem73lgJHaZjFdBX2+/zK6yJtVVYaU/n2NufwMou906bfOAWEJFgrAKktzFml7vj\nUUqpzuQE5dQdWD03y6m/nDrLGJMrIsl0/HKqP1aDop+pf+6W6mR0WJ1SLXcPsMMYMwyrxcvZIKwh\naGOwMvOUGGOGY03ozTLGvAC8CNxmjBmJlbHnWfu5E7F6hpzfZ7gxZghW4VNrFcdm5PEIInKOiATa\n48wfxeo13O3eqJRSqlNqqJzKs28NlVO12fM6ajl1voj4iZWW/BGsLKtaMVKAVo6UcpUFxphCY0wW\n1rC6T+3tG7DGSwdjTdJ9V0TWAS9grRuB/W+W02ulAv+zs/05X7wzsbr0Pc1srKEKB7DG488x2kWt\nlFKepjOXUzdixbYDax7vze4NR3kSTeWtlGuUO92vcXpcg/V35wDy7da8ukqxxjzXmoW1QOq5wP+J\nyEC7hcufnxYV9BjGmOto+oK3Siml3KMzl1Mz3B2D8lzac6RUyxXy06J3zWKsdKW7xF5AUCy1qU+3\nYKeGtTPy9DDGLADuwloRvTalaB+scdJKKaVUfbScUqqZ2nVChujoaJOYmOjuMJRSqlNbvXp1tjEm\nxt1xeCItp5RSyjM0taxq18PqEhMTWbVqVeMHKqWUchkR2ePuGDyVllNKKeUZmlpW6bA6pZRSSiml\nlMKFlSMReUVEMkVkY53tt4lImohsEpG/O22/V0TSRWSr00rESimllFJKKdUmXNlz9CpwTDYQEZmG\nleZ3qDFmINYaKIjIAGAOMNB+zrMi4uXC2JRSSql6G/JEZJiIrBSRdSKySkTG2NtFRObaDXmpIjLC\nfZErpZRyBZdVjowxi4HcOptvBh42xpTbx2Ta22cDbxljyo0xu4B0rEXJPFraoSOUVVa7OwyllFIt\n9yp1GvKAvwN/slMY328/BpiJtXZXb+AG4Lk2ilEp1c5V1xg27i+gPSdC6yzaes5RH2CyiHwvIotE\nZLS9vTuwz+m4DHvbcUTkBrslb1VWVlZ9h7icMYbnFu5gxpNLuOm/q6mu0S+6Ukq1Rw005Bkg1L4f\nhrWgMVgNea8Zy0ogXETiUEqpEzDG8IePNnL200t5+Ks0rSB5uLauHHkDkcA44E7gHRGR5ryAMeZF\nY8woY8yomJi2zxxbU2N48LPNPPJVGoO6h7JwaxZPfrutzeNQSinlMrcD/xCRfVjDv++1tze5IU8p\npWq9unw3b/6wl76xIbywaCePfLVVK0gerK0rRxnAB3ar2w9YqzBHA/uBHk7HxdvbPM67q/fx72W7\n+cXERD65dRKXjIrn6e/S+XrTIXeHppRSqnXcDNxhjOkB3AG83Jwne8IIB6WUZ1iyPYs/f7aZ6QNi\n+eLXk7l8bALPL9rBO6v2Nf5k5RZtXTn6CJgGICJ9AF8gG/gEmCMifiLSC2s89w9tHFuTvL5yD31j\nQ7j/7AE4HMKDswcxJD6Mu99PJauw3N3hKaWUOnlXAR/Y99/lpzmwTWrIc/cIB6WU53jkqzQSo4J4\n4mfD8HIIf549iJQuwXyy/kDjT1Zu4cpU3m8CK4C+IpIhItcCrwBJdlagt4Cr7F6kTcA7wGbgK+BW\nY4zHZTpIzchn4/4jXD4ugdrRgP4+Xjx+yTBKKqp54JNNbo5QKaVUKzgAnGLfPxXYbt//BPi5nbVu\nHFBgjDnojgCVUp5v04ECNu4/wlUTEgny8wbA4RCm9Y3hx115FJdXuTlCVR9vV72wMebSBnZd0cDx\nDwEPuSqe1vDG93sJ8PHivOHHDjFP6RLMr0/rzT++3so5Gw8xY1BXN0WolFKqOeyGvKlAtIhkAH8E\nrgeeEhFvoAwrMx3AF8BZWBlVS4BftHnASql2491VGfh6O5g9rNsx26f27cK/luxi+Y4czhgQ66bo\nVENcVjnqaArLKvlk/QHOGRpHqL/PcftvmJLE56kH+b+PNzKpdzTBfnpqlVLK052gIW9kPcca4FbX\nRqSU6gjKKqv5cO1+zhzYlfBA32P2jUqMINDXi4VbM7Vy5IHaes5Ru/XRugOUVFRz+die9e738XLw\n5/MGkVVYzjs/6iQ7pZRSSqnO6pvNhykoreSSUfHH7fPz9mJCcjQLt2Zp1joPpJWjJvpo7X76dQ1h\nSHxYg8eM7BnB6MQIXl66i6rqmjaMTimllFJKeYp3Vu2je3gAE5Kj690/rV8M+/NL2ZFV1MaRqcZo\n5agJcorKWbM3jxmDutLYskzXT05if34pX2lqb6WUUkqpTmdvTglL07O5cGQ8Xo76fzdO7dsFgIVb\nNd2/p9HKURN8l5aJMXB6/8bHhZ7eP5Ze0UH8a/FO7SpVSimllOpk/vv9HhwiXDYmocFjuocH0LtL\nMIu2aeXI02jlqAm+3XKYuDB/BnYLbfRYh0O4ZlIv1mcUsGpPXhtEp5RSSimlPEFZZTXvrNrH9AGx\ndA3zP+Gxg7qHsSu7uI0iU02llaNGlFVWs2R7Nqf179LokLpaF47ojggsS892cXRKKaWUUspTfLL+\nAPkllVw5vv4EXs4ig3zJLa5og6hUc2jlqBErduZQUlHdpCF1tQJ9vYkN8Scjr9SFkSmllFJKKU/y\n35V76N0lmPFJUY0eGxnkS0lFNaUV1W0QmWoqrRw14tvNhwn09WJcE77kzuIjAsjIK3FRVEoppZRS\nypOs2ZtHakYBPx/fs0mjjaKDrfWPcorLXR2aagatHJ2AMYbv0jKZ0jsGfx+vZj3Xqhxpz5FSSiml\nVGcwd/52IgJ9OH/E8Wsb1ScyyA9Ah9Z5GK0cncCWg4UcLCjj1P5dmv3c+IhADhaU6XpHSimllFId\n3Jq9eSzcmsUNU5IJ9vNu0nMig2p7jrRy5Em0cnQCC7ZmAjC1b0yznxsfEUB1jeHQkbLWDksppZRS\nSnmQp77dTmSQLz9vQiKGWkeH1RVp5ciTaOXoBBakZTK4exhdQk6cirE+8RGBADq0Tqk2cKSskh92\n5bo7DKWUUp3Q6j15LNqWxQ1TkghqYq8R/NRzlKtzjjyKVo4akF9SwZq9fHtILgAAIABJREFUeUxr\nQa8RWD1HAPtyNSmDUq6UnlnIuU8v5ZIXVvDEN9t08WWllFJt6t/LdhER6NOsXiOAYD9vfL0cOqzO\nw2jlqAGLt2dTY2Bqv+bPNwKIC/dHRHuOlHKlhVszOe+Z5RSVV3PmwFiemr+dR+dt1QqSUkqpNlFR\nVcPCrVnMGNSVQN+m9xoBiAhRwb46rM7DNO9/sRNZmJZJZJAvQ+PDW/R8P28vuobqWkdKuUp2UTm3\nvbmWHpGBvHL1KGJD/Lnvo408s2AH/eNCOXtIN3eHqJRSqoP7YVcuReVVnNav6ethOtOFYD2P9hzV\no7rGsHBbFqf0icHL0Xie+oboWkdKuc4jX6ZRVlnN05cOJy4sAIdDeOi8QUQH+/HVxkPuDk8ppVQn\n8O2Ww/j7OJiYEt2i50cF++mwOg+jlaN6pGbkk1tc0aIsdc7iIwK150gpF1i9J493V2dw7aQkUroE\nH93ucAin9IlhyfZsqmt0aJ1SSinXMcbwzebDTEqJJsC3eeth1ooK8iWnSBMyeBKtHNWjNutVS1sB\nasVHBHCwoJRKXetIqVZTWV3D/R9vJC7Mn9tOTTlu/9S+MRSUVrJuX74bolPtjYi8IiKZIrKxzvbb\nRCRNRDaJyN+dtt8rIukislVEzmz7iJVSniLtUCH780s5vX/LhtSBDqvzRFo5qseavXn0jAokOtjv\npF4nPiKAGgOHCnStI6VayyNfprHpwBHuP3tAvSlTJ/eOxiGwyF6nTKlGvArMcN4gItOA2cBQY8xA\n4FF7+wBgDjDQfs6zItKy5mKlVLv37ebDAJzav2XJuwCign0pqaimtKK6tcJSJ0krR3UYY1izN58R\nCREn/Vq1ax3t03lHSrWKz1IP8NLSXVw1viczB8fVe0x4oC/DEyJYuC2rjaNT7ZExZjFQd5Gsm4GH\njTHl9jG1Ne3ZwFvGmHJjzC4gHRjTZsEqpTzKN1sOM7RHeIvWw6wVZa91lKNrHXkMrRzVkZFXSlZh\nOSMSWpalzlntWkc670ipk5eeWcRd76UyIiGc+2YNOOGxU/vEkJpRQLaO41Yt0weYLCLfi8giERlt\nb+8O7HM6LsPedgwRuUFEVonIqqwsraQr1RF9l3aY1IwCZg89ucyokUHWKCUdWuc5tHJUx5q9eQAM\nb4Weo7iwABy61pFSJ62iqobb316Lv48Xz1w+Al/vE1+6pva1hjgs2a4/TFWLeAORwDjgTuAdEWly\n6lJjzIvGmFHGmFExMSeX2Ecp5XnKKqt54JPNJMcEccW45i38WldUcG3PkVaOPIVWjupYuzefQF8v\n+nUNOenX8vV2WGsd5eqwOqVOxtz529m4/wh/PX8wcWEBjR4/sFso0cG+LNqqlSPVIhnAB8byA1AD\nRAP7gR5Ox8Xb25RSncgLi3ayN7eEB2cParSxrjFHh9XpQrAew6WVo4ayANn7fisiRkSi7cciInPt\nLECpIjLClbE1ZM3ePIbEh+Ht1TqnJiEqkHUZ+ZpWWKkWWr0nl2cXpnPxyHhmDOrapOc4HMLInhGk\n7i9wcXSqg/oImAYgIn0AXyAb+ASYIyJ+ItIL6A384LYolVJtbl9uCc8uTGfW4LiTzmoMVrY6gFyd\nc+QxXN1z9Cp1sgABiEgPYDqw12nzTKyCpjdwA/Cci2M7TlllNZsPHGmVZAy1rhjXk51Zxby3el/j\nByuljvOnTzcTFxbA/eeceJ5RXQPiwtiVXUxJRZWLIlMdgYi8CawA+opIhohcC7wCJNkNe28BV9m9\nSJuAd4DNwFfArcYYTTGlVCfy4GebcYhw36z+rfJ6wX7e+Ho7dFidB3Fp5aiBLED/z959h0V1bQ0c\n/m167ypdihWwY69RoybRmN5Nj2k3yS3puekxvZeb8t3E3JjE9ERT1VijsXdAEWyAiKAIKJ2Z/f0x\naLBTZjgzw3qfx0c4U85Cmdmzz157LYDXgPuBhsspk4FP6gegFUCQUurk5ahsZFNeKXVmbdXJ0Xk9\nIugbG8TLc7dRXi0f0oRoik15JWzKK+W2kQn4e7k36bFJkQFobelDIcSpaK2v1FpHaK3dtdbRWusP\ntdY1WutrtNYpWuu+WusFDe4/TWudqLXuqrX+1cjYhRCta2FmIfMy9nHXmE5EBp05xbsxlFL1jWBl\ncmQvWn3PkVJqMrBHa73xuJsaVQXIlv4qxtDySnVHKKX498Qkig5V8/6SHVZ7XiHags9W5ODj4coF\nfZr+VpAUGQBARn6ZtcMSQgjRxliKMKST0M6Xm4clWPW5pRGsfTmxg6INKaV8gIexpNQ19zmmYkm7\nIzY21kqRWazeWUx8mC+hLWz+ery+scFM7BnB2wuyWLB1H71jgrh9VCeirHTVQQhnVFpZy6yNe7iw\nT1STV40AIgO9CPR2J2OvTI6EEEK0zP8t2cHuAxXMuGlAi4swHC/Uz1PS6uxIa68cJQLxwEal1C4s\nlX7WKaXCaWQVIFuVSK01mVmx4wBDEkOt9pwNPXNBCrePSiTQ251v1uZxzX9XckB6sAhxSt+vy6Oq\n1sxVA5pXJlUpRVJEgKwcCSGEaJG8gxW8syibc1LCGd7Z+uX5LWl18pnQXrTq5EhrvVlr3V5rHae1\njsOSOtdXa12ApQrQtfVV6wYBpVrrva0V2/qcEsprTAzv3PLKIycT5OPBfeO78dnNg/j0poHkl1Ry\n48erZR+SECdhNms+W5lDr+hAekQHNvt5kiID2FpQJtUihRBCNNvTP2WgsGyTsAVJq7Mvti7lfbIq\nQKfyC7ADyAb+D7jDlrEdb2lWES4KBifaZnLUUGpcCG9d2YfNe0q5e+Z6zPLBTYhjfL02l6zCw1w/\nNK5Fz5MUEUBVrZmd+8utE5gQQog2ZfG2Iuak7+Nvo223HSLUz4OKGhOVNVL80h7YulrdCVWAjrs9\nTmu9v/5rrbW+s74KUA+t9Rpbxna8P7L30ysmiEDvpu9taI5xyeE8NjGJ+VsLeXthdqucUwhHUHSo\nmmd/2cqA+BAu6N2ymixHizLIviMhhBBNVF1nKcIQH+bLzcPjbXaeo41gpdeRXWj1anX2qLSilo25\nJQy3QjOvprhuSBwX9onitd+3sSizsFXPLYS9evqnDCprTDx7YQ+UUi16rsR2fni4usi+IyGEEE32\n3z92snN/OU+cn4ynm6vNzhPiaykEJql19kEmR8DyHfsxaxjexfqb7E5HKcWzF/agawd//v7lBtl/\nJNq8RZmFzN6Yz+2jEunU3q/Fz+fh5kLnDn6yciSEEKJJ9pRU8taCLMYnd2CkjT8fhvrVrxxJryO7\nIJMj4I+s/fh5utE7xnr9jRrL28OVpyanUFJRy7yMfa1+fiHsRWWNiUdnpZHQzpc7zkq02vNKxToh\nhBBN9cxPGQA8aqMiDA39lVYnkyN70OYnR1prlmQVMSghBHdXY/45UjsGExXkzQ8bTqhcLkSb8fr8\nbeQWV/LshT2smr6QHBnA/sPV5JdUWu05hRBCOK8/sor4Na2AO0d1IjrYx+bnC6mfHBXLniO70OYn\nR6t2FpNbXMm4pHDDYnBxUZzfO5I/svZLnXvRJmXkl/HfP3ZyeWoMgxKs22usT2wwABtyS6z6vEII\nIZxPdZ2Jx2elExfqwy0jElrlnH6ebni4uUhanZ1o85OjGSt2E+DlxqRekYbGMbl3JCaz5ufNrdba\nSQi7YDJrHvp+M8E+7jx0bjerP3/3iAA83VxYt/ug1Z9bCCGEc/lw6U527C/n8fOT8XK3XRGGhpRS\nlkawklZnF9r05KjwUBW/pRVwaWoM3h6t8wI4lW7hAXQL92fWhnxD4xCitX26Yjcbc0t4dGISQT4e\nVn9+DzcXekQFsl5WjoQQQpxGfkklb83P5uykDpzVtX2rnlsawdqPNj05+nJVLnVmzTWDOhodCgDn\n945k7e6D5BZXGB2KEK2ioLSKl+ZkMrxzGOfbcPW2T2wQm/eUUlNnttk5hBBCOLZpP2/BrDWPtUIR\nhuOF+nnK1go70WYnR3UmM5+vymF45zDiw3yNDgeAyb2jcHdVPDE7HbNZGx2OEDb3+Ow06sxmpl3Q\n8p5Gp9M3NpiaOrOU9BZCCHFSS7P28/PmvdwxqhMxIbYvwnA8SauzH212cvT7lkL2llYxxU5WjQCi\ngrx5bGIS87cW8taCbKPDEcKm5qQXMCd9H/eM6UJsqG0HoiNFGdbnyL4jIYQQx6qpM/P47DRiQ3y4\ndWTrFGE4nqTV2Y82Ozka1jmMFy7uwehurZtTeibXDOrIRX2jeH3+NhZuLTQ6HCFs4lBVLY/PSqdb\nuD83D4+3+fnCA72ICPRiXY7sOxLHUkp9pJQqVEqlneS2fymltFIqrP57pZR6UymVrZTapJTq2/oR\nCyGs7aNlO9leVM4T5ye1WhGG44X6eVBRY6KyxmTI+cVf2uzkyM/Tjcv7x+JmUG+jU1FK8eyFPege\nHsA9X6xn94Fyo0MSwupembuNfYeqeO6iHq3WX6xvbLCsHImT+RiYcPxBpVQMMA7IaXD4HKBz/Z+p\nwLutEF+TFZZV8egPaayVCo1CnNHe0krenJ/F2O7tGd2tg2Fx/NUIVvYdGc2+ZgYCAC93V96f0g+l\nFLfOWCtXEYRT2ZBbwv+W7+LaQR2Ppru1hj6xQeQdrKTwUFWrnVPYP631EqD4JDe9BtwPNNwAOhn4\nRFusAIKUUhGtEGajVdTUceP/VjNjxW4ufvdP7pq5Xn7nhTiNaT9voc6seWxisqFxhPh6AkhqnR2Q\nyZGdignx4c0r+5C57xAPfbcJraVAg3B8tSYzD323mQ7+Xtw7vmurnrtPbBAAG3NLW/W8wvEopSYD\ne7TWG4+7KQrIbfB9Xv0xu2Aya+6euZ6M/DLevqoPd4/uxNz0Au77epPRoQlhl/7cvp+fNu3l9pGJ\nNt/7eiahfvUrR9II1nBujb2jUqo9MBSIBCqBNGCN1lpq49rIyC7t+OfYLrwybxu9Y4K4fqjt92YI\nYUsfLd3Jlr1lvHdNP/y93Fv13DHBloGvoEyuojsra4xTSikf4GEsKXXNjWMqlrQ7YmNjm/s0Tfbm\n/Cx+31LIU5OTmdgzEnqCp7srL83JZHNeKT2iA1stFiHsXa3JzGOz0okJ8eb2UYlGh9MgrU4mR0Y7\n48qRUuospdQc4Gcs+dYRQBLwb2CzUupJpVSAbcNsu+48qxNju3fgmZ+3sHrXyTI/hHAMucUVvPb7\nNs5O6sCElPBWP3+gj2UyVlohA4+zsfI4lQjEAxuVUruAaGCdUioc2APENLhvdP2xY2itP9Bap2qt\nU9u1a9fcH6tJ9pRU8t7i7UzqFcm1g+OOHr92cEcCvNx4e2FWq8QhhKOYvmwn2YWHeXxismFFGBoK\nqZ8cFcueI8M1ZuXoXOAWrXXO8TcopdyAicDZwLdWjk0ALi6KVy/vxeS3l3HHZ+v4+a5htA/wMjos\nIZpEa82/f0jDVSmePN+YvG5PN1d8PFw5WFFryPmFTVltnNJabwaOljGtnyClaq33K6VmA39TSn0B\nDARKtdZ7rfMjtMxLv20F4MFzuh1z3N/LneuHxvPm/CwyCw7RNdzfiPCEsCv7yqp44/csRndrz9gk\n44owNOTn6YaHm4uk1dmBM64caa3vO9mAU39bndb6B621TIxsKMDLnfeu6cfhqjru+GwdNXWSySgc\ny+yN+SzeVsS947sSGeRtWBzBPh4clJUjp9OScUopNRNYDnRVSuUppW46zal+AXYA2cD/AXe0MHSr\n2JBbwg8b8rl5eDxRJ3l93TAkDl8PV95ZKP3zhABLEYZas+bxSUlGh3KUUkoawdqJRhdkUEqZlFLP\nqwZt7JVS62wTljhe13B/XrykJ2t2H+TZX7YYHY4QjVZSUcPTP2XQKzrwmHQfIwT5uFMiK0dOqznj\nlNb6Sq11hNbaXWsdrbX+8Ljb47TW++u/1lrrO7XWiVrrHlrrNbb5SZrm+V+3EObnwe2jOp309mBf\nD64aGMvPm/dSUCp77kTbtnz7AWZvzOe2EQl0DPU1OpxjSCNY+9CUanXp9fefq5QKqT+mTnN/YWWT\nekVy87B4Pv5zF9+vzzM6HCEa5flft3KwopZnL+qBq4uxbxmycuT02tw4tWt/OSt2FHPz8AT8PE+d\nKX/NoI6YteaL1SddYBOiTag1mXl8dhrRwd6nvJhgpFA/Tw4clj1HRmvK5KhOa30/8F/gD6VUP47t\n/yBawYPndGNgfAgPfbeZjPwyo8MR4rRW7Szmi9W53DwsnuRI4ytlBfm4UyorR86szY1TP27MBywX\nz06nY6gvIzq3Y+aqHGpNkpot2qb//bmLbfsO89jEJLw9jC/CcDxJq7MPTZkcKQCt9ZfA5cB0IMEW\nQYlTc3N14e2r+hLk7cGtn66hRK6CCztVXWfioe82ER3szT1jOxsdDmCZHMnKkVNrU+OU1prZG/Pp\nHxd80r1Gx5syqCP7yqqZv2VfK0QnhH0pLKvi9d+zGNW1HWfbSRGG40lanX1oyuTo5iNfaK3TgOHA\n3VaPSJxRO39P/nNNXwpKq/j7lxswm536wqhwUO8t2sH2onKeuSAFH49Gt1SzqWAfD0ora+U147za\n1Di1teAQWYWHOf8Mq0ZHnNWtPVFB3ny6QlLrRNvz7C9bqKkz88SkZBpsS7QroX4eVNSYqKwxGR1K\nm9boyZHWeq1SaohS6iql1LXAZBvGJc6gb2wwj09KZlFmEa/Pl/4Vwr5sLzrMOwuzmdQrklFd25/5\nAa0kyMcDs4ayKkmtc0ZtbZyavTEfVxfFuT0iGnV/VxfFlQNiWJq9n5wDFTaOTgj7sXLHAX7YkM/U\nEQnEhdlXEYaG/moEK/uOjNSUanUzgJeBYUD/+j+pNopLNMLVA2O5tF80b87PkjQJYTe01jzy/Wa8\n3F14bKL9lEkFCK5vBCu9jpxTWxqntNb8uDGfoZ3CCPXzbPTjRnaxXKzYUiB7VkXbUGsy89isdKKC\nvLnzLPsrwtBQqK/ltSypdcZqSq5LKpCktW5UPopS6iMsjfcKtdYp9cdeAiYBNcB24AatdUn9bQ8B\nNwEm4G6t9ZwmxNYmKaV4+oIUthSU8fcvN/Dj34bZ9RUR0TZ8vTaPFTuKee6iHrTzb/yHttYQVD85\nsuzVk9eKE2rSOOXINuSWkHewknvGNG0/X0yIZW9SbrGsHIm24ZPlu8ncd4j3rulnl0UYGgrxq185\nkkawhmrKnqM0ILwJ9/8YmHDcsXlAita6J7ANeAhAKZUEXAEk1z/mP0op+/4NthNe7q68e3U/XF0U\nt85YS0VNndEhiTZs/+Fqpv28hf5xwVyeGmN0OCcI8rEMPNLryGk1dZxyWHPS9+HmohiX1LQfN9Db\nHX9PN/IOVtooMiHsR+GhKl6ft40RXdoxPtk+izA09FdanUyOjHTGyZFS6kel1GwgDMhQSs1RSs0+\n8udUj9NaLwGKjzs2V2t95NP7CiC6/uvJwBda62qt9U4s3ccHNOPnaZNiQnx484o+bCs8xIPfbqYN\nXDQVduqZnzKoqKnjuYt64GJwT6OTCa6fHEnFOufS3HHKUWmtmZtewKCEUALrV0MbSylFVLA3eQdl\n5Ug4v+d/2UpVnYknJiXZbRGGho6kyBbLniNDNSat7mUbnftG4Mv6r6OwTJaOyKs/dgKl1FRgKkBs\nbKyNQnM8I7q0495xXXlpTia9YoK4aVi80SGJNuaPrCJ+2JDP3aM70am9v9HhnJTsOXJathqn7FJ2\n4WF27C/nhqFxzXp8TIiPFGQQTm/1rmK+W7+HO0YlktDOz+hwGsXXwxUPNxdJqzNYYyZHS86Uv62U\nUk3J8VZKPQLUAZ819jFHaK0/AD4ASE1NlSWSBu4YlcjG3BKe/WULKZEBDEwINTok0UZU1ph45Ps0\nEsJ8ucOON7wGeLmjFJTKypGzsfo4Zc/mpBcAcHYTU+qOiAn2YVn2frTWDnE1XYimqjOZefSHNCID\nvfjbaPsdk46nlJJGsHagMXuOFiql7lJKHbNMo5TyUEqNVkr9D7iusSdUSl2PpVDD1Q0Gqj1Aww0K\n0fXHRBMopXjlsl50DPHhzs/XU1BaZXRIoo14c0EWOcUVTLuwB17u9rtd0MVFEejtLitHzseq45S9\nm5uxj94xQYQHejXr8dHB3lTUmOR1IJzWjBW72VpwiEcnJtlNn73GCvWTRrBGa8zkaAKWCnIzlVL5\nSqkMpdROIAu4Enhda/1xY06mlJoA3A+cr7VuuKY/G7hCKeWplIoHOgOrmvBziHr+Xu68P6UfFTV1\n3P7ZWmrqzEaHJJzc1oIy/m/JDi7tF83gRPtfrQz28ZA9R87HauOUvcsvqWRTXinjk5tfdyImxAeQ\ninXCORUdqubVudsY3jmMCSmOV58lxNeTA4dlz5GRzjg50lpXaa3/o7UeCnQExgB9tNYdtda3aK3X\nn+xxSqmZwHKgq1IqTyl1E/A24A/MU0ptUEq9V3+OdOArIAP4DbhTay3tgZupcwd/XrqkF+tzSnj6\npwyjwxFOzGzWPPTdZgK83Xn43O5Gh9MoQT7uUq3OyTR3nHJER1LqWlJ562g5bynKIJzQ87/WF2E4\nP9kh00Ylrc54jVprVJbfrgH8VSRhj1Jq1enyt7XWV57k8Ienuf80YFpj4hFndl7PCDbmJfDBkh30\nignikn7RZ36QEE302crdrM8p4bXLexFcX4LU3gX7eLCvTFJOnU1zxilHYzZrZizfTc/owBZtMI8O\ntqwcSTlv4WzW7i7m23V53DYykUQHKcJwvFBfSasz2hknR0qpccB/sKQnHNkHFA10UkrdobWea8P4\nRAvcP74rm/NKeeT7zXQL9yclKtDokIQTKSit4sXfMhneOYwLep+0uKRdCvJxJ7PgkNFhCCtqK+PU\n71v2sWN/OW9d2adFz+Pn6Uawj7uk1QmnYinCkE5EoBd3OVARhuOF+HlQUWOissZk901rnVVjVo7e\nAMZqrXc1PFi/N+gXwDFyadogN1cX3rqqD5PeWsptn67lx78Nc5ir+8L+PTE7nRqTmWcuSHGo1IUg\nbw9KZM+Rs2kT49QHS3YQHezNOVbYRxET4kOurBwJJ/LZyhwy9pbxzlV98fV0rCIMDf3VCLaaaA8f\ng6NpmxpTkMENS9+h4+0BmtZ9TrS6MD9P3r2mH4Vl1dzz5QZMZqfJMBEGmpexj9/SC7h7TGc6hvoa\nHU6TBPu4U15jkmIlzqXZ45RS6iOlVKFSKq3BsZeUUluVUpuUUt8rpYIa3PaQUipbKZWplBpvtZ/g\nDNbuPsia3Qe5aVg8bq6NGbpPL1oawQonsv9wNS/PzWRop1DO7eF4RRgaCvU90ghWLuIZpTHvsB8B\nq5VSDyilrqr/8wCwktPsIRL2o3dMEE9OTmbJtiJem7fN6HCEgztcXcdjs9Lo2sGfqSMSjA6nyYLq\nr8rJ6pFTack49TGWancNzQNStNY9gW3AQwBKqSTgCiC5/jH/UUrZPO9Fa827i7YT6O3OZakxZ35A\nI8QE+5B3sBKzXDATTuCFX7dSWWPiSQctwtBQiF/9ypE0gjVMY6rVPQdcBShgcP0fhaVP0XO2DU9Y\ny5UDYrk8NYa3F2Yzt77akRDN8crcTArKqnju4h64W+EKdmsL9rEsJJRUSsU6Z9GScUprvQQoPu7Y\nXK11Xf23K7DsXwKYDHyhta7WWu8EsrEUgbCpL1fn8vuWfUwdkWC1dKHoYG9q6swUSclg4eDW7j7I\n12vzuGlYPJ3a+xsdTov9lVYnkyOjNKYgQ6zWeguwpRXiETb05ORkthSU8a+vNjLrb34tqnYk2qZN\neSX8789dXDOwI31jg40Op1mCvC0Dz0EZeJyGjcepG4Ev67+OwjJZOiKPv6rjNYxnKjAVIDY29vib\nm2RzXimPzU5neOcwbhuZ2KLnaig65EjFugo6BDSvmawQRjOZNY/NSiM8wIu7xnQ2OhyrCPU7klYn\nFy6M0pjLvj8c+UIp9a0NYxE25uXuyrvX9MPdzYVbZ6ylvLruzA8Sol6dycyD324mzM+T+yZ0NTqc\nZguqXzk6KL2OnIlNximl1CNAHfBZUx6ntf5Aa52qtU5t165ds89fUlHD7Z+tJczXgzeu6IOri/XS\nhWKCjzSClaIMwnF9vnI36fllPHJed/wcuAhDQ74erni4uUhanYEaMzlq+G7seBsMxDGigrx568o+\nbC86zP3fbsKJWoAIG5u+bBcZe8t48vxkArwctxZLsOw5ckZWH6eUUtcDE7Gk5h15o9wDNNz0E81f\npcOtrvBQNW4uineu7kuIlSuNRgfXN4KVct7CQR04XM1LczIZkhjKxJ4RRodjNUopaQRrsMZMjvQp\nvhYOaminMO4b342fN+3lw6U7jQ5HOIDc4gpenbeNsd3bM8EKZYSNFCwrR87IquOUUmoCcD9wvta6\n4exhNnCFUsqzvkx4Z2BVS893Kl06+PP7P0fSxwYprF7urkQGepFddNjqzy1Ea3jxt0wqnKQIw/FC\n/aQRrJEaswbZSylVhuXKnHf919R/r7XWATaLTtjMbSMT2JRXwnO/biU5MpDBiaFGhyTslNaaR2el\noRQ8OdmxehqdjLe7JWWhpFIGHifS7HFKKTUTGAWEKaXygMexVKfzBObV/76v0FrfprVOV0p9BWRg\nSbe7U2ttstUPBVilbPepdI8IYMvesjPfUQg7sy7nIF+uyeWW4fF07uD4RRiOF+LryQEplmKYM06O\ntNbSntcJKaV46dJebHt7KX/7fB0/3T2MiEBvo8MSduinTXtZlFnEoxOTiApy/N8RpRRB3u6UlMvK\nkbNoyTiltb7yJIdPWf5baz0NmNbc89mT7hEBLNpWRFWtCS93GeqFYzhShKFDgCf3jO1idDg2Eerr\nwQ5Z1TWM49XhFVbj5+nG+1NSqao1cfun66ius+kFUOGASitqefLHDHpGB3L9kDijw7GaEF8P9stV\nOdHGdYvwx2TWZBfKhzDhOGauyiFtTxkPn+s8RRiOF+rrIQUZDCTdWk67AAAgAElEQVSTozauU3s/\nXrmsFxtyS3jyxwyjwxF25vnftnKwooZnL+xh1UpZRosN8SFHNqKLNq57hCXbUFLrhKMoLq/hpTmZ\nDIwP4fxekUaHYzMhfh5U1pqorJGL1kaQyZFgQkoEt41M5POVOXy1OtfocBpl9a5isgsPGR2GU1u9\nq5iZq3K4cWgcKVGBRodjVXFhvuwursBslhozou2KC/XFy92FLXvlvVQ4hpfmbOVwdR1POcH+19P5\nqxGsZDgYQSZHAoB7x3VhaKdQ/j0rjU15JUaHc1ozVuzmsveX8+C3m40OxWnV1Jl5+LvNRAV584+z\nnS+nOzbEh5o6M/sOVRkdihCGcXVRdA1vWlEGrTXzt+xjadZ+DlXJvj3RejbklvDF6lyuHxJH13Dn\nK8LQUKivpRGspNYZwzmTNUWTubm68OYVfZj01lJu/3QdP941zOp9NazhP4uyefG3TPw93diYV0Jl\njQlvD9lIbG3vL95OVuFhpl/fHx8P53ubiAv1BWDX/gopRCLatKQIf35NK0BrfcYr8QWlVdz3zUb+\nyNoPgFLQLzaY64bEMSElHHcbVtYTbduRIgxhfp78fWxno8OxuRA/y+cvKedtDHknE0eF+nny3pR+\nFB2u5u6Z6zHZWcpR3sEKXvwtk/N6RvDa5b2pNWnW5Rw0Oiyns6PoMG8tzOa8nhGc1a290eHYRMdQ\nHwB2Hyg3OBIhjNU9IoCSiloKyk6/irp6VzHjX1/Cml0HeXpyMp/cOIC7Rnem6HA1d81cz4gXF/Kf\nRdkclA9zwga+XJ3LprxSHjm3O/4O3IS8sf5Kq5PXkxFkciSO0TM6iKcnJ7M0ez8vz800Opxj5Byw\nbKC/emAsAxNCcHVRrNhxwOConIvWmke+T8PTzYXHJyUZHY7NRAZ54+6q2C1FGUQb15iiDFsLyrjx\n49WE+nnwyz3DmTI4jhFd2vHPs7uw4F+j+O+1qcSH+fLib5kMfn4+D323mW37ZB+TsI6D5TW8OGcr\nA+JDmNzbeYswNBTqdyStTvYcGcH58mVEi13eP5YNuSW8u2g7vaKDmJASbnRIAOwttVzZjAj0xt/L\nnZTIAFbuKDY4Kufyzdo8lu84wLQLU2jv72V0ODbj6qKICfaRlSPR5nWr37uxZe8hRnfrcMLtucUV\nXPvhKnw93Jhx08ATep25uijGJnVgbFIHthaUMX3pLr5dl8fMVTkM7xzGjUPjGdmlHS5OVO1StK6X\n5mZyqKqOpyYnO3URhoZ8PSzNyiWtzhiyciRO6onzk+kVE8S9X2+0mx4YR9I+IgItH9oHJYSyIbeE\nqlopdWkNBw5XM+2XLaR2DObK/rFGh2NzHUN92LVfVo5E2+bv5U5MiDcZJ1k5Kq2s5YaPV1NVa+J/\nNw44YxPobuEBvHBJT5Y/OJp7x3Vh275D3PDxasa+uphPlu+ivLrORj+F/ZKKmC2zKa+EmatyuHZw\nR7qFBxgdTqtRSll6HcnkyBAyORIn5enmyrtX98XTzYVbZ6zhsB0MantLKwn2cT/ayX1gQgg1JrPs\nO7KSaT9voby6jucu6tEmrvJ2DPUlp7gCreXDi2jbuocHsCGnhDqT+eixWpOZOz9bx6795bw/JbVJ\n1cFC/Tz52+jO/HH/aN64ojf+3u48NiudQc/N55mfMshtA+msxeU1XPzun1w3fZXRoTgss1nz6Kx0\nQn09nbJq6pmE+nmQtqeU537ZwmOz0qiukwvBrUUmR+KUIoO8eevKPuzcX859X280/EPk3pIqwhtU\nFkuNC8FFwQpJrWuxpVn7+W79Hm4bmUjnDs5dIvWIjqE+HK6ukytzos27qG8Ue0oqmbUhH7DsPXx8\ndjpLs/fz7EU9GJwY2qzn9XBzYXLvKGbdOZTv7hjCyC7tmP7nLka+tJBbZ6xh5Y4Dho8rtpBfUsml\n7/3J2t0H+SNrP2l7So0OySF9tSaXjbklPHxuNwLaQBGG48UE+7C14BAfLdvJJ8t3M3NljtEhtRky\nORKnNaRTGA+e041f0wr4YMkOQ2PZW1p1NKUOIMDLneTIQCnK0EJVtSYe+WEz8WG+3HlWJ6PDaTVH\nynnLviPR1o1PDic5MoA35mdRazLzxepcPl+Zw+2jErksNcYq5+gbG8zbV/Xlj/vP4taRiazcWczl\nH6zgvDeX8s3aPKe5Kl5nMnPl/62gsKyaD6b0w9PNhc9XOc+H2u1Fh/lk+S6bFwooqajhhd+20j8u\nmAv7RNn0XPbq+Yt7Mu8fI8h4agKDEkJ4e2E2FTXGZ/G0BTI5Emd0y/AEzusRwQu/bWVZ9n7D4igo\nO3ZyBDAoIcSh9x1prfk9Yx/Tl+0kPb/UkPz0txZksftABdMuSDmastgW/FXO2/lTfIQ4HaUU947r\nSk5xBU/9mMHjs9IZ3jmMe8d1tfq5IoO8eWBCN5Y/OIZnL+xBrcnMvV9vZOjzC3ht3jYKHbwxc3bR\nYXYfqODRSUmMSw5nUq9IZq3fYxep6S2xZW8Zf/t8HWNfXcxjs9IZ/cpivliVY7Mx6+W5mZRW1vLk\n+SltpgjD8QK93encwR93VxfuG9+V/YdrmL5sl9FhtQk2nRwppT5SShUqpdIaHAtRSs1TSmXV/x1c\nf1wppd5USmUrpTYppfraMjbReEopXrikJwnt/Lhr5nr2lFS2egxVtSaKy2tOmBwNjA+lps7M+pyS\nVo+ppQoPVXHbp2u5+ZM1PPljBue9uZRhLyxgb2nr/ftmFhzi/cU7uLhvNEM6hbXaee1BdLAPLgp2\nyeRICEZ1bUff2CBmrNhNO39P3ryiD6423Hvo7eHKVQNjmfuPEcy4aQA9o4N4Y34WQ59fwD+/2uCw\nqWhpeyyFLfrGBgGW1hPlNSZmbdhjZFjNtiG3hJv/t4Zz3viDRZlF3DYyka9vG0zXcH8e/G4zN3+y\nhkNVtVY95+a8Uj5bmcO1g+NIimw7RRhOp1/HEMZ0a8/7i7ezMLOQeRn7DPks1lbYeuXoY2DCccce\nBOZrrTsD8+u/BzgH6Fz/Zyrwro1jE03g5+nG+1P6UVNn5o5P17b6Sk1BfRnvhnuOAPrHh6AUrNzp\nOKl1Wmu+XZvH2a8uYWFmEQ9M6MYf95/Fy5f2oriihidmp7dKHGaz5uHvN+Pv5cYj53VvlXPaEw83\nFyKDvCWtTggsF8EeOa87ie18+c/VfQmub0LZGucd3rkdH13fnwX/GslVA2L5La2AiW8t5bL3lvPr\n5r3HFIqwd2l7SvF2dyU+zA+A3jFBJEUE8OmKHIfaX7VyxwGmfLiSC95ZxupdxfxjbBeWPTCaByZ0\no39cCF9OHcST5yezeFsRF7/759E+hC1lKcKQRqivR5sswnA6/xrXlcPVddwwfTW3fLKGf365weiQ\nnJZN+xxprZcopeKOOzwZGFX/9f+ARcAD9cc/0ZZ3jxVKqSClVITWeq8tYxSNl9jOj1cu68WtM9by\nxOx0nr+4Z6ud+0iPo8jjVo4Cvd1JighwmH1H+SWVPPz9ZhZlFtGvYzAvXtKTxHaWQTQmxIeiQ9W8\n8NtW5qYXMC7Ztv2lPl+Vw9rdB3nl0l6EtNIHIXsTF+oraXVC1OvXMYT5/xpl2PkT2vnx5OQU/jmu\nK1+vyeXjP3dx+2friAry5rohHbm8fyyB3va9MT89v5SkyICjq25KKa4aGMu/f0hjQ24JfWKDDY7w\n1LTWLMnazzsLslm1q5gwPw8ePKcb1wzqiJ/nsR8XlVJcNySOTu39uOOzdUx4Ywk3DYvnlhEJLSqe\n8M3aPDbklvDypb3s/v+6tSVFBvDLPcM5VFXH9GU7Wb7dMT73OCIj9hx1aDDhKQCOdJ2LAnIb3C+v\n/tgxlFJTlVJrlFJrioqKbBupOMH45HDuGJXIF6tz+aIVN5kWlFmWj8MDT2xMOighlPU59r3vSGvN\n5ytzGPfaElbuKObxSUl8devgoxOjI24eHk+3cH8en51u0xz1fWVVvPDrVoZ2CuWivm1zsytY9h3t\n3F/uNJvBRdNJ+rf9CfR25+bhCSy+7yzeu6YfUcHePPvLVgY/N59Hf0hje5F99N47ntmsSc8vo0dU\n4DHHL+gTha+HK5/ZabUxs1kzN72Aye8s47qPVpF7sIInJiWx9IHR3DYy8YSJUUNDO4Xx013DGN2t\nPW8tyGbEiwt5b/H2ZhUOKK2o5fnfttKvYzAXtdEiDGfSLTyA/nEh9I0N5mBFrTSJtRFDCzLUrxI1\naZ1Za/2B1jpVa53arl07G0UmTudf47oyvHMYj81KZ0Nu6+z1yS850gD2xCaEgxJCqa4zs7GVYmmq\nnAMVXP3flTz8/WZ6RAUy5+8juGFo/Enz+d1dXXjuoh4UlFXx9I8ZNovpyR/TqTGZmXZBjza72RVg\nVNf2lFbWcudn66mpc5zUHWFVHyPp33bJ1UUxISWcr24dzE93DeOclAi+XJ3LmFcWc/30VSzZVmRX\nqWo7D5RTUWMi+bh9Mn6ebkzuE8VPm/IprbDu/pyWMJk1szfmc84bfzB1xlpKKmp5/qIeLL7vLK4f\nGt/oAj0xIT68fVVffrprGL2ig3j+162MeHERHy3d2aSLlq/My6SkooanJie3iV57LZHY3nJhdYed\nXihwdEZMjvYppSIA6v8urD++B2hYMzS6/piwM64uijev6EM7f0/u+HStzUt6gmXPUZCPO94eJ75Z\nD4g7su/Ivvodmc2a6ct2Mv71JWzKK+XZC3vw+S0Dia2vknYqfWKDuWNUIl+uyeXHjflWj2v+ln38\nsrmAu8d0Ji7M1+rP70jOTurAU5OT+X3LPu6auc6uPriI1qG1XgIc/+YxGUvaN/V/X9Dg+CfaYgUQ\ndGQ8E7aVEhXIK5f1YtmDo/nH2C6k7Snj2o9WcfZrS/h0xW67KHF8pIhEynErRwBXDYilqtbMd+vz\nWjusE9SazHy1Jpexry7m7pnrMWnNa5f3YsG/RnLFgFg83Jr30TAlKpD/3TiAb24bTKf2vjz1UwYj\nXlzIV2tyz/jYtD2lfLpiN9cM6khy5In/fuJYifV72ux1FdXRGTE5mg1cV//1dcCsBsevrU9bGASU\nyn4j+xXs68H7U/qxv7yGu2aut/mG2b2lVYQHnJhSBxDo4073cPvad7S96DCXvb+cJ3/MYGBCCHP/\nMYKrBsY2epXm72O70Dc2iIe/22zVbvLl1XU8NiudLh38uGV4gtWe15FdOziOJyYlMSd9H6nT5nHj\nx6vJLDhkdFjCWC1K/xa2087fk3vGdmbZg2fx6mW98HJ34d8/pDH4uQU8/+tW8g2s4JWeX4aHmwud\n2vudcFtKVCC9YoL4bKVxhRmqak3MWLGbUS8t4v5vNuHt7sq7V/dl7t9HcGGfaNxcrfORMDUuhC+m\nDmbmLYOIDfHh/m828e8fNlN7is8JZrPmsVlpBPt48K+zrV8+3hlFBXvj4ebC9iIpKGQLti7lPRNY\nDnRVSuUppW4CngfOVkplAWPrvwf4BdgBZAP/B9xhy9hEy6VEBTLtghT+3H6Al+Zm2vRcBWWVJ5Tx\nbmhgQgjrcg4avnekzmTm3UXbOeeNP8gqPMwrl/Zi+vX9iQw6MR3wdNxdXXjjij6g4Lrpq8gutM7V\noVfnbWNPSSXPXdSj2VcHndH1Q+P56a5hXD8kjtW7ipn2yxajQxJ2ojnp37I31vY83Vy5qG80P/5t\nGF/fNpghiaF8sGQ7w19cyJ2fr2Pt7uJWn4Sk7Smle7ilL83JXD0wluzCw6xq5SyHipo6/vvHDka8\nuJBHf0ijfYAnH12fys93D+OcHhE2S2EbnBjKl7cO5taRCXy6IofrPlp10rLf367LY11OCQ+c041A\nHynC0BiuLor4UF9Jq7MRW1eru/IUN405yX01cKct4xHWd2lqDBtyS3h/8Q56RQdxbg/bZJjsLami\nR1TQKW8flBDK9GW72JRXSv+4EJvEcCZbC8q47+tNbN5TyvjkDjx9QQrt/U89oTuTmBAf/nttKnd8\nto4L3lnGCxf35Nwe4c3eI7Q5r5Tpy3Zy9cBY+nU05t/InqVEBZISFUhZZR1zMgrQWrfp/Vht3L4j\n1VKbk/6ttf4A+AAgNTXVfjbFOCGlFP3jQugfF0LewQo+Wb6bL1bl8POmvfSKDuSGofGc2yPC5heD\ntNak7SllYq/IU95nUs9Inv4pg89X5TAwIdSm8QCUVdUyY/luPly6k+LyGgYnhPL65b0ZnBjaau9t\nri6Kh87pTuf2/jz47Sau+XAVn9w44GglutLKWp7/dSt9YoO4pG90q8TkLBLb+7Jlr2Q52IJcOhYt\n9tikJHrHBHHf1xvJLrT+C7Wq1sSB8poTyng3NKB+QrTSgNS6mjozr/++jUlvLSW/pJK3r+rDe9f0\na9HE6IiBCaH8eNcwEtv7cefn6zj7tSV8tHQn5U2sZFdnMvPQ95sI9fPk/gndWhyXM+sZE0hJRS05\nVkxnFA5H0r8dUHSwDw+f253lD43h6cnJHKqu4+9fbmDYCwt4a36WTffH5hZXUlZVR8pp9st4e7hy\ncd9oft1cYNNYistreGVuJkOfX8BLczLpFR3It7cPZubUQQzpFGbIRZ9L+kXzn6v7kpFfytX/XUHh\nIUuRpdfmbaO4ooanJ6dIEYYmSgjzI6e4QooJ2YBMjkSLebq58u41ffH2cGXqjLVW75ZdWGYZRE5W\nxvuIYF8PuoX7s2JH66YrbM4r5fy3l/L671mckxLB3H+MYGLPSKsOPpFB3nx16yBevLgnvp5uPPVT\nBqNeXsSXq3MwmRt3UfrjP3eRtqeMJyYlS++IM+gVbVmh3JhXanAkojVI+rfz8fV0Y8rgOH7/x0g+\nvqE/3SICeGXeNgY/v4D7v9nIlr1lVj2f1poZK3YBnFDG+3hXD4ylxmTmm7XWL8xQWFbFtJ8zLJPB\nBdkMqy+zPf2GAXaRLTAuOZwPpqSybd9hRr20iEd/SOOT5bu4emDsSYtYiNNLbO+LyazJKZZ9R9Zm\n07Q60XZEBHrz9lV9ufq/K7n36428d00/q00Q8ksrj57jdAYlhPLl6lxq6sw2T6GoqjXx5vws3l+y\ng1BfDz6Y0s+mTVs93Vy5rH8Ml/WPYe3ug0z7OYMHvt3M56tyee2yXiS0O3ED8BF5Byt4Ze42Rndr\nz7k9bNtY1hl0DffH082FjbklnH+aFBnhHCT923m5uChGdW3PqK7tyS48xPRlu/hu3R6+WpPH4IRQ\nbhgax5juHU7aVqGxzGbN47PTmbFiN5enxpASFXDa+3fu4M+AuBA+X5XDLcMTqKg1kVlwiH4dm98c\ndk9JJe8v3s4Xq3OpM5mZ3DuKO0Yl0rmDf7Of01bO6taeX+8ZzmvztjFjxW6Cfdy5d5wUYWiOhKMV\n68rp1N7+/q8dmUyOhNUMSgjloXO68czPW3h38XbuGNXJKs9bUFrf4yjo9GlqgxJC+PjPXWzeU2LT\nq2Rrdxdz/zeb2F5UzmWp0TxyblKrbiLt1zGYb28fwuyN+Tw2K53z3lzKY5OSuKJ/zAkTUq01j81K\nRyl4anKy7KFpBHdXF5IjA9iUZ599s4QQTdepvT/TLuzBfeO78sXqXD75cxdTZ6wlNsSH64fEcWlq\nNP5eTXsfzzlQwWOz01iUWcStIxJ48JxujXqPvXpQLPd8sYGX5mby/bo9FJRV8Y+xXbhnbOcmnX/n\n/nLeXZTNd+v2oBRc3Dea20Ym2n2LhsR2frx9VV/uGXMIpRRBPh5Gh+SQEtpZ/p+lnLf1yeRIWNVN\nw+LZkFvCy3My6REVyPDOLWvUm55fypsLsvBydyHyDCtHA+ItG1xX7Ci2yeSooqaOl+dsY/qfO4kM\n9OaTGwcwoosxjYiVUkzuHcXA+FDu/XojD323mdU7i5l2YY9jekH9srmABVsL+fd53YkOPn1/JfGX\nXjFBzFyVQ53JbLXytkII4wX5eHDbyERuHhbPnPR9TF+2k6d+yuDVedsYl9SBuDBfwvw8OVhRQ9Gh\naqKCvBkQH0JSZADuri6YzJrNe0r5La2Aj5btxM1F8eT5yVw3JK7RMUxICSfE14N3F22nW7g/fWKD\neO33bdSZzfzz7C5nnGBlFhzinYXZ/LQpH3dXF64Z1JGpIxKaXBXVaPa4suVI/L3cae/vyQ4p5211\nMjkSVqWU4oWLe7Jt3yHunrmeH+8a1qwP5RU1dUxftos3fs8iyMedj67rf9IGsA2F+HrQtYM/K3Yc\n4M6zOvHl6hx+2rSXD6aknvGxZ/Ln9v08+O1mcoormDKoIw+c0w0/T+NfPuGBXnxy4wDeXpjNa79v\nI2NvGR9e35+oIG9KK2t54sd0UqICuL4JA7ew7DuavmwXWYWH6R5x+jQZIYTjcXN14byeEZzXM4JN\neSVMX7aLP7L38936v4oP+ni4UlFjOuZ7BZTXH5vYM4JHzut+xpTv43m6ufLixT3ZW1bFFf1jcFWK\nh7/fzFsLsgnz8zzlRGtTXglvL8hmbsY+fDxcuWV4AjcNj7dK8R/hmBLb+cnKkQ0Y/+lOOB1fTzfe\nn5LK+W8t5fZP1/H1bYPxcj/z5KSmzkx6fil/ZO3n4z93UVxew7ikDjx/cU9CfBu37D4wIYRv1uax\nbd8hHpuVTnWdmXcWZnPv+OblNB+qspQZ/WxlDh1Dffhi6iAGtUIJ1qZwcVHcPaYzPaMDuevz9Uz5\n70q+um0wr83bxoHD1Uy/vr+sfjRRr5j6ogy5JU43OdJaU2fWR4t5uLoo3FyUpFyKNqtndBCvXd4b\n+Ks6arCPOz4ebuwrq2LlzmJ2FB3mUFUdJrOmb8dghiaGEurn2exzjk3qcMz3z17Yg72lVbzw21bG\ndG9/zEXF1buKeXtBNou3FRHg5cbdYzpzw5A4ghs5LgrnldDOlx835kvrCSuTyZGwifgwX169vDe3\nfLKGR39I48VLeqKUoqrWxOY9pWzMLWF70WF2FJVTdLia8uo6DpbXUlPfQXtU13bcNbpzkzepDkoI\n5ZPlu7n+o1V4urkwvHMY7y/ZzgV9ok7atfx0FmUW8vB3m9lbVsXNw+L517iuLV6BsqVRXdsz/Yb+\nXPPhSi59bzk795dz07B4qQLUDHGhPgR4ubExr5QrBhgdjfWUVtZy1suLKC6vOeG2zGcm4Olmv7/f\nQrQGL3dXohqkp3UI8GqVwiwuLoppF6Yw7rUlPPJ9Gh/f0J9l2Qd4a0EWK3cWE+Lrwf0TujJlUMcm\n740SzqtruD+frawju/CwU6Up1tSZ+X3LPr5cnUvWPsveNKXgi6mDWmWLgEyOhM2cndSBu0Z34q0F\n2RysqCG/pIpt+w5RV3/FOtTXg/gwX7qHB+Dr6Uqwrwe9o4Po2zGYDgHNSxMYEG/Za5RfWsUrl/Zi\nRJd2jHnFUjL081sGNurKSmlFLU//nME3a/Po1N6Pb28fQt/Y5lcSak2pcSG8d00/bvlkDVFB3vzz\n7C5Gh+SQlFL0igliY65zFWXI2neI4vIaLkuNPrpp22SyrCS5ucjqohBGig724b7xXXnyxwzGvLqY\nHUXldAjw5NGJSVw5IAYfD/nIJo51Xo8Invl5Cx//uYtpF/YwOhyrqK4zce4bf7C9qJzIQC8GJYai\nUGitG5WFZA3yShM29fexXdhacIg1u4rpER3EWd3a0TsmmN4xQbTzb35KwqmE+XnSOyaI9v6eXNQ3\nCqUU903oxqM/pDF/S+EJqQzHm5tewCM/pFFcXsOdZyVy1+jOrfZitJZRXdvz7e1DCPByx9cO9kU5\nqj6xwby9IIuD5TVOk76Se9DS2PbWkYkknqb8uxDCGNcOjmNOegF5ByuZdmEKl/SLlhVdcUqhfp5c\n0DuSb9flcd/4rk5R+W/Jtv1sLyrn6QtSuGpAbItK7TeXfHISNuXqovi/a1Nb9Zxf3zYYF/XXHoor\n+8fw5vwsvlidc8rJ0YHD1TzxYwY/bsynW7g/06/v79DpaD3rG5mK5hvbvT1vzs9i/tZCLukXbXQ4\nVpFzoBKlOCZtSAhhP1xdFJ/fPAilkD0kolFuGBrPV2vy+GJ1LreNTDQ6nBb7cWM+wT7ulmIlBkyM\nACSPQjgdd1eXY15Qbq4uXNIvmgVbC4/2TDpCa83sjfmc/doSfkvbyz/P7sLsvw1z6ImRsI4eUYFE\nBHoxJ73A6FCsJqe4gvAAL4dbDRWiLXGRAimiCbpHBDA4IZT//bmL2vp9246qoqaOeRn7OKdHBO4G\nFpKSyZFoEy5LjcGs4dt1eUePFZZVMXXGWu6euZ6YYG9+ums4d4/pjIebvCyE5artuKQO/JFVRGWD\ncr6OLLe4gpgQ6XclhBDO5MZh8ewtreKjpTuNDqVF5m8ppLLWxKSeti+CcjryKVC0CfFhvgyMD+Gr\nNbmYzZqv1+Qy9tXFLNlWxMPnduPb24fQNdx5Kr0I6xifHE5VrZnF24qMDsUqcooriJXJkRBCOJUx\n3dozLqkDz/26lfcXbzc6nGb7cWM+7f09jxbXMopMjkSbccWAGHYfqOD8d5Zy3zeb6Bruz6/3DGfq\niETpAyROakB8CIHe7sx1gtS6qloTBWVVMjkSQggn4+KieOfqvkzsGcFzv27l9d+3obU2OqwmKauq\nZVFmERN7Rhq21+gIKcgg2oxzUiJ4YnYGO4rKefL8ZKYM6oiLwS9AYd/cXF0Y070987cUUmsyG5oD\n3VJ5BysBZHIkhBBOyN3VhTeu6IOXuyuv/55FVa2ZByZ0dZj9a3PT91FjMjOpV4TRocjkSLQdXu6u\nfHfHEHw8XIkIlGpdonEmJIfz3bo9jHxxIclRgaREBpIcGUBKVCAdAjwdZuDJLbaU8ZY9R0II4Zxc\nXRQvXtwTTzcX3lu8napaE49PSnKIcWr2xnyig73pHWN8tV2ZHIk2RXq7iKY6O6kD0y5MYeWOYtLy\nS/l9yz6OZCuE+nqQHGWZLCVHBpASGUhsiI9drkjm1E+OZOVICCGcl4uL4pkLUvB0c+WjZTuprjMx\n7YIedjkuHXHgcDXLsvczdUSCXUzkZHIkhBCnoZTi6oEduVhpXMoAAA88SURBVHpgRwDKq+vYsreM\n9Pwy0vaUkp5fxv8t2UGd2TJj8vN0I6l+spTaMYRzUsJtMigVHqricFUdZq1xc3HB19ONQG/3U1Zb\nzCmuwNvdlTA/x28SKIQQ4tSUUjw6sTveHi68s3A71bVmXrykZ6vsrzaZNQu3FpJVeJjcgxUkRQRw\nUd8ofDxOPeX4Na0Ak1kbXqXuCJkcCSFEE/h6upEaF0Jq3F/VdKrrTGTtO0x6filpe8pIzy9l5qoc\npi/bxVOTk7l2cJxVzr0pr4SP/9zFqp3FR/cQNeTv6cYrl/ViXHL4CbcdqVRnD1flhBBC2JZSivvG\nd8Pb3ZWX526jqs7E65f3sWm7EpNZc9/XG/lu/R4A/L3c+HxlDi/NyeTqgbFMHZFAkM+JF+hmb8yn\nU3s/ukfYR9VgmRwJIUQLebq5khIVSEpUIJf3txwzmTXXT1/FS79lMiE5nPYBXs1+/n1lVbzw21a+\nW7eHQG93hiSGcv2QOML8PHFxUdSZzJRX1/HN2jxu/XQt943vSvfwADbkltAzOpAx3TvU9ziSvXZN\noZT6B3AzoIHNwA1ABPAFEAqsBaZorWsMC1IIIU7jb6M74+XuyjM/b6Gmbi1vX9X3aCPwWpOZnzft\nZWxSB/w8WzYlaDgx+sfYLtw4LA4/TzfW7j7Ih0t38u7i7cxYvpsbh8VzSb/oo/tf95ZWsnpXMX8f\n08VuLt7J5EgIIWzA1UXx1OQUxr++hKd/3sJbV/Zp1vP8llbAA99uorLWxO2jErljVCL+Xu4nve+l\nqTHc+/VGXvwt8+gxXw9XFt43ipziCgYnhjYrhrZIKRUF3A0kaa0rlVJfAVcA5wKvaa2/UEq9B9wE\nvGtgqEIIcVo3D0/A092VR39I45ZP1vDBlFS83F149Ic0vlidy+WpMbxwSc8zPk9lzV8tIVxdFCaz\nZmtBGb9nFPLL5r1k7jvEv87uwl1jOh99zJFMi8yCQ7w6L5M35mfxxvwsuoX7kxQRwIHyGrSGiXZQ\npe4ImRwJIYSNxIf5cueoTrz2+zbGdm/P5N5RAGQWHOJ/y3exa385eQcrOVRVS2WtCa0taXv+Xm5E\nBXnj5e7Kgq2F9IgK5M0r+xAf5nva83m5u/LWlX2O5nf7e7lxwTvLeOT7NCpqTFKMoencAG+lVC3g\nA+wFRgNX1d/+P+AJZHIkhLBzUwZ1xMvNhQe+3cR101cxOCGUL1bnktjOly/X5HJBn6gTLqAdrq7D\nZNKg4Os1uby3eDv7D9fg6+FKQjs/thcdpqLGhFLQLzaYly/txSX9ok96/q7h/rw/JZWcAxXMzSjg\n9y37WLmzmAPl1QzrFGZXBbOUozWJaig1NVWvWbPG6DCEEOKUqutMXPLucjbvKWVs9w7EhHjzyfLd\neLm50CXcn5hgH4J83PGuT3OoqDFRWllL3sEKCkqrmNgrknvHdW12nvjTP2Xw4dKdAHx4XSpjunew\n2s92hFJqrdY61epPbDCl1D3ANKASmAvcA6zQWneqvz0G+FVrnXLc46YCUwFiY2P77d69u1XjFkKI\nU5m9MZ9/fLkBk1kzsWcEL17Sk/GvL8HdxYVf7hmOl7sr1XUmXpuXxQdLtmNuME0Y2imUc3tEkFlw\niO1Fh+nUzo/esUEMSQyjQwtSx7XWrZJS19ixypCVI8njFkK0FZ5urnx7+xCmL9vJG/OzqNxq4or+\nsdw/vivBvravHHf36M58ty6PgxW1snLUBEqpYGAyEA+UAF8DExrzWK31B8AHYLmIZ6sYhRCiqc7v\nFYmfpyUr4d/nJeHl7sq0C3pw7UeruPz95SRFBrI+5yBbCw5xcd9okiIDqKkz0zc2iIEJtknNtpe9\nRke0+uRI8riFEG2Nh5sLt45M5OJ+0VRUm4gNbb1JSqCPOw+f2523FmRLA9imGQvs1FoXASilvgOG\nAkFKKTetdR0QDewxMEYhhGiy0d06MLrbX1kEI7q046FzuvFLWgFz0gvwdHOxWaaBIzBqz5HkcQsh\n2pwwP08wIK360tQYLk2Naf0TO7YcYJBSygdLWt0YYA2wELgES6bDdcAswyIUQggruXVkIreOTARa\nL83NXtm+G9RxtNZ7gJexDDx7gVIsaXQl9VfiAPKAqJM9Xik1VSm1Rim1pqioqDVCFkII0cZorVcC\n3wDrsKR/u2BJlXsA+KdSKhtLGviHhgUphBA20JYnRmBMWl2z87hBcrmFEEK0Dq3148Djxx3eAQww\nIBwhhBCtoNVXjmiQx621rgWOyeOuv4/kcQshhBBCCCFalRGTo6N53MqybjcGyOCvPG6QPG4hhBBC\nCCFEKzNiz5HkcQshhBBCCCHsjkM3gVVKFQGN7a4XBuy3YTi24qhxg+PG7qhxg+PGLnG3PmvG3lFr\n3c5Kz+VUZJyye44au6PGDY4bu6PGDY4bu7XjbtRY5dCTo6ZQSq1xxA7ujho3OG7sjho3OG7sEnfr\nc+TYnZWj/p84atzguLE7atzguLE7atzguLEbFbcRe46EEEIIIYQQwu7I5EgIIYQQQgghaFuTow+M\nDqCZHDVucNzYHTVucNzYJe7W58ixOytH/T9x1LjBcWN31LjBcWN31LjBcWM3JO42s+dICCGEEEII\nIU6nLa0cCSGEEEIIIcQpOdXkSCk1QSmVqZTKVko9eJLb/6mUylBKbVJKzVdKdTQizpM5U+wN7nex\nUkorpeyi6khj4lZKXVb/756ulPq8tWM8lUb8vsQqpRYqpdbX/86ca0Scx1NKfaSUKlRKpZ3idqWU\nerP+59qklOrb2jGeTCPivro+3s1KqT+VUr1aO8ZTOVPsDe7XXylVp5S65HT3ay2NiVspNUoptaH+\n9bm4NeNrqxx1rJJxqvXJONW6ZJxqfXY5TmmtneIP4ApsBxIAD2AjkHTcfc4CfOq/vh340ui4Gxt7\n/f38gSXACiDVEeIGOgPrgeD679sbHXcTYv8AuL3+6yRgl9Fx18cyAugLpJ3i9nOBXwEFDAJWGh1z\nI+Me0uD35Bx7ibsxsTf4nVoA/AJcYnTMjfw3///27j/krrqA4/j7s55qxbRVD5g/JhNzFa3Z0uyH\nmpkRS2WjP4IyG4sRhLgoTQuiHxSCIaX/aD8UkX4OZvo4FfWvjYXtATe1qRuYOVirwFhtDmfmej79\ncc7gunafe+51O+fc0+cFD889P557P8/lHj58z/nee+cD24FTy+VWHJ9d/hnXrkpPtTZ7eqre3Omp\n+p/z2nuqS1eOzgGesf2s7X8Da4EVvTvY3mD7QLk4DZxSc8Z+BmYvfR/4AfCvOsPNokruLwI32/4n\ngO3nas7YT5XsBo4vb78J+GuN+fqyvQn4xyy7rAB+7sI0MF/SifWk629Qbtu/P/Q6oV3HZ5XnHGAN\n8FugLa/xKrkvA+6yvavcvzXZO2xcuyo9Vb/0VM3SU/VrY091aXB0MvDnnuXd5bp+VlOctWiDgdnL\nS84LbN9fZ7ABqjzni4BFkh6WNC1pWW3pZlcl+3eByyXtpjjLsqaeaK/asMdCG7Xp+BxI0snAp4Af\nN51lSIuAN0vaKGmrpJVNB/o/MK5dlZ6qX3qq3dpybFaSnqpu4lg/QBtJuhw4G7ig6SxVSJoD/AhY\n1XCUUUxQTFn4KMUZlk2S3mN7b6OpqvkscIftH0r6EPALSYttzzQdrMskXUhROuc1nWUINwFftz0j\nqeksw5gAzgIuAt4AbJY0bfvpZmMFjFdXpacak55qQHqqVrX3VJcGR38BFvQsn1KuewVJHwe+CVxg\n+6Wasg0yKPtxwGJgY/mCfhuwXtJy21tqS/m/qjznuynm5L4M7JT0NEUJPVJPxL6qZF8NLAOwvVnS\nXGCSFl2O7qPSsdBGkpYAtwGftL2n6TxDOBtYWx6fk8DFkg7anmo21kC7gT22XwBekLQJOBPI4OjY\nGdeuSk/VLz3VQump2tXeU12aVvcIcIak0yS9DvgMsL53B0lLgZ8Cy1s0pxgGZLe9z/ak7YW2F1LM\nc226cKDCcw5MUZyNQ9IkxeXRZ+sM2UeV7LsozlQg6V3AXODvtaYczXpgZflpQB8E9tn+W9OhBpF0\nKnAX8Plxu3Jh+7Se4/NO4IoxKByAe4DzJE1IeiPwAWBHw5m6bly7Kj1Vv/RUy6SnGlF7T3XmypHt\ng5KuBB6i+DSO220/Jel7wBbb64EbgHnAunLkvMv28sZClypmb52KuR8CPiFpO/Af4Jo2nGmpmP1q\n4FZJX6V40+sq241/a7Kk31AU+WQ5z/w7wGsBbP+EYt75xcAzwAHgC80kfaUKub8NvBW4pTw+D9pu\ny0cBD8reSoNy294h6UFgGzAD3GZ71o+BjVdnXLsqPVW/9FT90lP1a2NPqQXHUEREREREROO6NK0u\nIiIiIiJiZBkcRUREREREkMFRREREREQEkMFRREREREQEkMFRREREREQEkMFRREREREQEkMFRxMgk\nzZd0RXn7JEl3HsX7/oqklbNsv7T8rouIiIgjSk9FDC/fcxQxIkkLgftsLz7K9zsBPAq8z/bBPvuo\n3Odc2weO5uNHREQ3pKcihpcrRxGjux44XdLjktZJehJA0ipJU5LulbRT0pWSrpL0mKRpSW8p9ztd\n0oOStkr6naR3lvf7MeDRQ4Uj6cuStkvaJmktQPkN6BuBS+v+pyMiYmykpyKGlMFRxOi+AfzJ9nuB\naw7bthi4DDgHuA44YHspsBk4NA3hZ8Aa22cBXwNuKdefC2w97HGW2l4CfKln/Rbg/KP370RERMek\npyKGNNF0gIiO2mB7P7Bf0j7g3nL9E8ASSfOADwPripkHALy+/H0isKPnvrYBv5I0BUz1rH8OOOkY\n5Y+IiG5LT0UcQQZHEcfGSz23Z3qWZyiOuznA3vJs3uFeBOb2LF8CfARYDnxL0rvLqQxzy30jIiKG\nlZ6KOIJMq4sY3X7guFH+0PbzwE5Jn4bijauSziw37wDeXq6fAyywvQG4FpgPzCv3WwQ8OXr8iIjo\nuPRUxJAyOIoYke09wMPlG1xvGOEuPgeslvQH4ClgRbn+AYozcACvAX4p6QngMeBG23vLbRcC94+a\nPyIiui09FTG8fJR3RAtJuhu41vYf+2w/Afi17YvqTRYREZGeiu7K4CiihSS9AzjB9qY+298PvGz7\n8XqTRUREpKeiuzI4ioiIiIiIIO85ioiIiIiIADI4ioiIiIiIADI4ioiIiIiIADI4ioiIiIiIADI4\nioiIiIiIAOC/AOjnvNFuTM4AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d8eea307f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, plotList = plt.subplots(3, 2, figsize=(14, 9))\n",
    "\n",
    "doPlot(plotList[0][0], 'Original pitch', join(outputPath, \"carrots1.PitchTier\")) \n",
    "doPlot(plotList[0][1], 'Target pitch', join(outputPath, \"carrots2.PitchTier\")) \n",
    "doPlot(plotList[1][0], '100% source, 0% target:', join(outputPath, \"carrots1_to_carrots2_morph_0.PitchTier\"))\n",
    "doPlot(plotList[1][1], '60% source, 30% target:', join(outputPath, \"carrots1_to_carrots2_morph_0.33.PitchTier\"))\n",
    "doPlot(plotList[2][0], '30% source, 60% target:', join(outputPath, \"carrots1_to_carrots2_morph_0.66.PitchTier\"))\n",
    "doPlot(plotList[2][1], '0% source, 100% target:', join(outputPath, \"carrots1_to_carrots2_morph_1.PitchTier\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the original utterance, 'carrots' has *focus*--which we can by the pitch accent over it.  In the target sentence, 'vitamins' has *focus*--which we can tell by the pitch accent over it.  With the intermediate morphing, we can see the strongest pitch contour gradually change from 'carrots' to 'vitamins'.\n",
    "\n",
    "If you listen to the audio, the morphed production doesn't sound the same as the target sentence, even though they have similar pitch accent.  This is because of other differences in pronunciations, like the way the consonants and vowels were enunciated.  ProMo can't help with those sorts of issues.\n",
    "\n",
    "<hr>\n",
    "\n",
    "That wraps up the tutorial on pitch morphing with promo."
   ]
  }
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