NBA_player_movement_tracking.ipynb

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     "text": [
      "/usr/local/lib/python2.7/dist-packages/matplotlib/__init__.py:872: UserWarning: axes.color_cycle is deprecated and replaced with axes.prop_cycle; please use the latter.\n",
      "  warnings.warn(self.msg_depr % (key, alt_key))\n"
     ]
    }
   ],
   "source": [
    "import requests\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from IPython.display import IFrame\n",
    "import matplotlib.font_manager as fm\n",
    "\n",
    "plt.style.use('ggplot')\n",
    "%matplotlib inline\n",
    "pd.options.display.max_columns=25"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The Play\n",
    "This play is from the Golden State Warriors - Memphis Grizzlies game on November 2, 2015. The Warriors wound up winning by 50 points, and the third quarter was a showcase of Steph Curry's talents.  In this play from the 3rd quarter, The Grizzlies' (Red) Mike Conley (11) dribbles baseline and kicks out to Matt Barnes (22) behind the 3-point arc who chucks up a brick that gets rebounded by Steph Curry (30). He begins to lead the offensive attack, and quickly three other Warriors are even with him at half court leading to a 4 on 3 break. Curry stops at the 3-point arc, drawing two defenders. From his left hand, he takes the ball behind his back, and the two defenders are convinced he's passing to Andre Igudala (9), but Curry brings the ball to his right hand and threads a pass between defenders to a cutting James Michael McAdoo (20) for the dunk. Watch the play below, or on nba.com [here](http://stats.nba.com/cvp.html?GameID=0021500051&GameEventID=383)"
   ]
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       "\n",
       "        <iframe\n",
       "            width=\"900\"\n",
       "            height=\"400\"\n",
       "            src=\"http://stats.nba.com/cvp.html?GameID=0021500051&GameEventID=383\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
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       "<IPython.lib.display.IFrame at 0x7f22c61c2590>"
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     "execution_count": 2,
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   "source": [
    "IFrame('http://stats.nba.com/cvp.html?GameID=0021500051&GameEventID=383',width=900,height=400)"
   ]
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   "cell_type": "code",
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     "data": {
      "text/html": [
       "\n",
       "        <iframe\n",
       "            width=\"700\"\n",
       "            height=\"400\"\n",
       "            src=\"http://stats.nba.com/movement/#!/?GameID=0021500051&GameEventID=383\"\n",
       "            frameborder=\"0\"\n",
       "            allowfullscreen\n",
       "        ></iframe>\n",
       "        "
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       "<IPython.lib.display.IFrame at 0x7f22c61bc590>"
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     "execution_count": 3,
     "metadata": {},
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   ],
   "source": [
    "IFrame('http://stats.nba.com/movement/#!/?GameID=0021500051&GameEventID=383',width=700,height=400)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "[u'moments', u'visitor', u'gamedate', u'gameid', u'home']"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "url = 'http://stats.nba.com/stats/locations_getmoments/?eventid=383&gameid=0021500051'\n",
    "response = requests.get(url)\n",
    "response.json().keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# tracking data\n",
    "Our keys returned are:\n",
    "* moments \n",
    "* visitor\n",
    "* home \n",
    "* gamedate\n",
    "* gameid\n",
    "\n",
    "Let's move home, visitor, and moments to their own variables. Then print out gamedate and gameid to see if there is anything else they contain."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2015-11-02\n",
      "0021500051\n"
     ]
    }
   ],
   "source": [
    "home = response.json()[\"home\"]\n",
    "visitor = response.json()[\"visitor\"]\n",
    "moments = response.json()[\"moments\"]\n",
    "print response.json()[\"gamedate\"]\n",
    "print response.json()[\"gameid\"]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## gamedate & gameid\n",
    "Nothing of interest in gamedate and gameid (we already know this information just to look up the data).\n",
    "\n",
    "Let's examine home data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
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    "collapsed": false
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    {
     "data": {
      "text/plain": [
       "{u'abbreviation': u'GSW',\n",
       " u'name': u'Golden State Warriors',\n",
       " u'players': [{u'firstname': u'Leandro',\n",
       "   u'jersey': u'19',\n",
       "   u'lastname': u'Barbosa',\n",
       "   u'playerid': 2571,\n",
       "   u'position': u'G'},\n",
       "  {u'firstname': u'Shaun',\n",
       "   u'jersey': u'34',\n",
       "   u'lastname': u'Livingston',\n",
       "   u'playerid': 2733,\n",
       "   u'position': u'G'},\n",
       "  {u'firstname': u'Andre',\n",
       "   u'jersey': u'9',\n",
       "   u'lastname': u'Iguodala',\n",
       "   u'playerid': 2738,\n",
       "   u'position': u'G-F'},\n",
       "  {u'firstname': u'Jason',\n",
       "   u'jersey': u'1',\n",
       "   u'lastname': u'Thompson',\n",
       "   u'playerid': 201574,\n",
       "   u'position': u'F-C'},\n",
       "  {u'firstname': u'Brandon',\n",
       "   u'jersey': u'4',\n",
       "   u'lastname': u'Rush',\n",
       "   u'playerid': 201575,\n",
       "   u'position': u'G-F'},\n",
       "  {u'firstname': u'Marreese',\n",
       "   u'jersey': u'5',\n",
       "   u'lastname': u'Speights',\n",
       "   u'playerid': 201578,\n",
       "   u'position': u'F-C'},\n",
       "  {u'firstname': u'Stephen',\n",
       "   u'jersey': u'30',\n",
       "   u'lastname': u'Curry',\n",
       "   u'playerid': 201939,\n",
       "   u'position': u'G'},\n",
       "  {u'firstname': u'Klay',\n",
       "   u'jersey': u'11',\n",
       "   u'lastname': u'Thompson',\n",
       "   u'playerid': 202691,\n",
       "   u'position': u'G'},\n",
       "  {u'firstname': u'Harrison',\n",
       "   u'jersey': u'40',\n",
       "   u'lastname': u'Barnes',\n",
       "   u'playerid': 203084,\n",
       "   u'position': u'F'},\n",
       "  {u'firstname': u'Festus',\n",
       "   u'jersey': u'31',\n",
       "   u'lastname': u'Ezeli',\n",
       "   u'playerid': 203105,\n",
       "   u'position': u'C'},\n",
       "  {u'firstname': u'Draymond',\n",
       "   u'jersey': u'23',\n",
       "   u'lastname': u'Green',\n",
       "   u'playerid': 203110,\n",
       "   u'position': u'F'},\n",
       "  {u'firstname': u'Ian',\n",
       "   u'jersey': u'21',\n",
       "   u'lastname': u'Clark',\n",
       "   u'playerid': 203546,\n",
       "   u'position': u'G'},\n",
       "  {u'firstname': u'James Michael',\n",
       "   u'jersey': u'20',\n",
       "   u'lastname': u'McAdoo',\n",
       "   u'playerid': 203949,\n",
       "   u'position': u'F'}],\n",
       " u'teamid': 1610612744}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "home"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## home/visitor data\n",
    "visitor/home - contains all information about visiting/home team\n",
    "* teamid - teamid from the API\n",
    "* name\n",
    "* abbreviation\n",
    "* players\n",
    "  * playerid - playerid from the API\n",
    "  * firstname\n",
    "  * lastname\n",
    "  * jersey - jersey number\n",
    "  * position - position the player plays (C,F,G,G-F,F-C)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "251"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(moments)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 8,
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   "outputs": [
    {
     "data": {
      "text/plain": [
       "[3,\n",
       " 1446527673002,\n",
       " 132.22,\n",
       " 7.09,\n",
       " None,\n",
       " [[-1, -1, 14.64474, 44.48211, 2.25707],\n",
       "  [1610612744, 2738, 18.86386, 23.97772, 0.0],\n",
       "  [1610612744, 201939, 18.87993, 41.50729, 0.0],\n",
       "  [1610612744, 202691, 5.05095, 29.13419, 0.0],\n",
       "  [1610612744, 203110, 12.88533, 34.84216, 0.0],\n",
       "  [1610612744, 203949, 8.88615, 20.38291, 0.0],\n",
       "  [1610612763, 2440, 27.47547, 8.76582, 0.0],\n",
       "  [1610612763, 201145, 9.42341, 11.88861, 0.0],\n",
       "  [1610612763, 201584, 4.219, 16.40298, 0.0],\n",
       "  [1610612763, 201144, 16.38252, 44.27504, 0.0],\n",
       "  [1610612763, 201188, 19.68304, 35.52727, 0.0]]]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "moments[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## moments\n",
    "\n",
    "moments - contain tracking data. `len(moments)` is number of moments in the eventid (here, 251), usually .04 seconds apart. So for this data, I have about 10.04 seconds. __Note:__ this data can and did change from day to day. Previously, there were 275 moments, or 11 seconds.\n",
    "\n",
    "a single element in moments contains times and positions of all players and ball. Let's examine the output above:\n",
    "* the __first__ element `moments[0][0]` is `3`, the __quarter__.\n",
    "* the __second__ element `moments[0][1]` is `1446527673002`, the __unix timestamp__.\n",
    "* the __third__ element `moments[0][2]` is `132.22`, and decreases as moments increase. it is the __seconds left in the quarter__\n",
    "* the __fourth__ element `moments[0][3]` is `7.09`, and decreases as moments increase, then reset to 24. it is __seconds left in the shot clock__\n",
    "* the __fifth__ element `moments[0][4]` is `None`, and is that value for all elements in moments. I'm not sure what this value is __?__\n",
    "* the __sixth__ element `moments[0][5]` is a list of lists indicating __teamid, playerid, x, y, z__\n",
    "\n",
    "To reiterate, the first 5 elements:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[3, 1446527673002, 132.22, 7.09, None]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "moments[0][0:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`[quarter, unixtime, timeleftgame, timeleftshot, unknown]`\n",
    "are the labels.\n",
    "\n",
    "Let's look at the ball (element 0):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[-1, -1, 14.64474, 44.48211, 2.25707]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "moments[0][5][0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`[teamid, playerid, x, y, z]`\n",
    "\n",
    "the ball has a `teamid=-1` and `playerid=-1`, and appears to be the only tracked element with a z value.\n",
    "\n",
    "Some have speculated that the z coordinate is the radius of the ball, but let's look at a histogram of values:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
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    {
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w1CVJyoShLklSJgx1SZIyYahLkpQJ79ImSRlbcdP19C65uZ7CN92MNQsfW0/Z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\nAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2298489f90>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ball_zdat = []\n",
    "for m in moments:\n",
    "    ball_zdat.append(m[5][0][4])\n",
    "fig = plt.figure(figsize=(8, 6))\n",
    "plt.hist(ball_zdat,bins=range(1,20))\n",
    "plt.title('Histogram of Z values of basketball')\n",
    "plt.xlabel('Z values')\n",
    "plt.ylabel('Frequency')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looking at the histogram, it is likely that the z value is the height, in feet, of the basketball from the floor. The most common values are approximately waist height and below. A few values above the height of the rim (10ft.) would indicate a shot or lob pass. For the ball, let's plot the x,y,and color it by z."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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4iEi7mFEiUhEtrRTT2io+ItImBkpEKqOFlWKhXMXnXQAuSR0zbkRE3cVAiUhl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\nhBAigAIlQgghhBAB/w9rk4kILDynNwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f22c61bcfd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use('ggplot')\n",
    "fig,ax = plt.subplots(figsize=(8, 6))\n",
    "#scat = plt.scatter(y=ball_zdat,x=np.arange(0,len(ball_zdat))*.04,c=ball_zdat,cmap=plt.cm.RdBu,s=100)\n",
    "scat = plt.scatter(y=ball_zdat,x=np.arange(0,len(ball_zdat))*.04,s=100)\n",
    "\n",
    "court = plt.hlines(0,0,len(ball_zdat)*.04,colors='k')\n",
    "hoop = plt.hlines(10,0,len(ball_zdat)*.04,colors='orange')\n",
    "plt.autoscale(tight=True)\n",
    "plt.tight_layout()\n",
    "plt.ylabel('Ball height (feet)')\n",
    "plt.xlabel('Time from start of event (seconds)')\n",
    "plt.legend((hoop,court),('hoop rim', 'court'),fontsize=12)\n",
    "#cbar = fig.colorbar(scat,orientation='vertical',fraction=0.05)\n",
    "plt.title('Ball height over time',fontsize='x-large')\n",
    "plt.savefig('img/NBA_ballheight.png',dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can see some of the action in the plot above.\n",
    "* The dribble drive begins it\n",
    "* A lob around 1.75 seconds\n",
    "* A shot around 3 seconds\n",
    "* The shot bouncing off the rim at 4.5 seconds\n",
    "* A few dribbles\n",
    "* A pass and shot from 9 seconds on"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Jycmcfvrpqh5GOMuy8Hq9EZkglke6FCMnxOVyUbNmTWrWrMmll17KI488wpQpU3jxxReL\nVBQ3b97M5s2befPNN+nbty8jRoygSpUqqiCHmcvlolu3bnTr1i3coYiIhNzZZ5/N/Pnzwx2GHMFx\nHPbv389TTz3Fa6+9VqQr+mExMTH06dOHIUOG0Lhx4zBEKaeS4zjhDuGEGIYZmgqiETnFsciJVEq1\nOnXq8J///IeNGzcycuRImjVrFhzCCJCRkcGYMWNo2bIlEyZMYPPmzRqHLiIiUsbl5eWxefNmxo0b\nx/nnn8+kSZOKJIfx8fE0bdqUIUOGsHHjRqZMmaLksIyK1OLA4S6mobhFClUQJaRq1arFU089xe23\n3878+fNZtGgRK1asCCaDO3fuZNiwYcycOZMbbriBTp060axZM6KiosIcuYiIiISK3+9n7dq1LFiw\ngHnz5rFx48Yij8fHx9O6dWuuuOIKunbtSuPGjTWMtIyL1ApieaQEUULONE3+8Y9/MHz4cK655ho+\n//xzZs+ezVdffYXX6wUK5x889dRTzJ8/n3//+9/cfvvt1KlTJ8yRi4iIyMn69ddfmTlzJu+99x4/\n/vhj8LcfIDY2losuuohevXpx6aWX0qhRI/WlKCciuYKoJjUiIXI4UWzQoAFXXXUVn3zyCWPGjGHD\nhg0AeL1evv/+ezZu3Mibb77JwIEDue2226hYsWKYIxcREZG/Kzs7mxkzZjB16lR+/fXXo9YsbNq0\nKQ888ACXX3451atX1+ihciZSK4iGGaI5iBF0ISRyIpWI5Xa7qVWrFr1792b16tW88sorRdZI9Hg8\nbNq0iSFDhtChQweWLl2qhXBFREQihMfjYcmSJVxyySXcd999bNmyJfg7HhUVRcOGDUlNTWX9+vX0\n7t2bWrVqKTkshyK1glgeqYIoJcrtdtOnTx+6du3K9OnTefvtt9m4cSMFBQU4jsOqVavo0qUL3bt3\nZ9CgQZx11llUqFAh3GGLiIjIH+Tm5rJp0yZefPFF3nrrLfLy8oKPxcXFcfbZZ3PttdfSt29fqlWr\nFsZIpTSI3AqiC0IwP1ZDTEX+hGEYVK9enQceeICrr76ad999l7feeotNmzbhOA55eXnMmjWLZcuW\n0bt3b3r27MlZZ52lyesiIiKlgGVZbN68mblz5/Laa6+xa9eu4GOGYZCcnMwNN9zAddddR3Jysn6/\nRSKMEkQJG5fLRfPmzUlOTqZTp068//77vPbaa+zZsweAHTt2MG7cOBYtWsQNN9zAwIEDiYmJCXPU\nIiIi5ZfX62Xq1KnMnTuXtWvXFpkSUqNGDW677TauueYazjvvPP1mS5mgJjUiYRATE0OrVq0499xz\n6dq1K6NHj2bx4sVYlkV+fj7ffPMN69atY/78+UyePJlmzZqFO2QREZFyZ+3atQwaNIhvv/22SGLo\ncrno2LEjjz32GM2bNyc2NlbzzaTsMM3QJHdqUiPy9xiGQVxcHK1bt+ajjz5izpw5NG7cmOjoaADy\n8/NZvnw5/+///T+effZZ0tPTsW07zFGLiIiUbbZts3//fsaNG8ell17K559/XqQBTd26dZk2bRoL\nFiygdevWxMXFKTkUOQmbNm2iY8eOpKamFtn++eefk5ycXCIxqIIopVL37t1p27YtEyZM4N133+Xn\nn3/Gtm2ys7N57LHH+PLLLxk4cCCXXnop8fHx4Q5XRESkzPF6vSxbtoypU6fy0UcfBdczNE2TOnXq\n0K1bN+677z7q168f3kBFTqFQDTE9nn14PB7GjBlD27Zti2z3+Xy8/PLLnHbaaScfx3FQBVFKrVq1\navH4448zdepUevXqRWxsLFD4Jfnggw/o168fo0aNYu3atWGOVEREpGxZs2YNjz/+OP369eO9994L\nJoexsbH07NmTF198kaefflrJoUgIxcTEMG3atKO6/r700kv07t27xJaHUYIopVpCQgJXXHEFY8eO\n5fXXX6dly5bBx3bv3s2kSZPo27cvc+bMoaCgIIyRioiIRD6v18s777zDgAEDGDduHDt37gw+1rhx\nY6ZPn05KSgpXX301iYmJYYxUpGSYhoFphuB2HEOvTdMMTq86bMeOHWzdupUrrriixJYKUYIoEaFG\njRpcd911LFiwgAEDBgSriZZlsXLlSgYMGMBTTz1VZA0mEREROX45OTk88sgj3HHHHaxYsYJAIAAU\nVg3vvvtuPvvsM2666SZq1qypeYZSbhimEbLbiRgzZgwPPvhgiD/Vn1OCKBHDNE1q1qzJCy+8wLx5\n82jevDnmoY5Q2dnZPP3007Rv357vvvtO1UQREZHj5PF4WLNmDV26dGHs2LFkZWUBhb+7TZo0YcqU\nKaSkpFCzZs3g766InHppaWns2LGD++67j549e5Kenk7v3r1P+fuqSY1EHLfbTZcuXWjQoAETJ07k\no48+Cq6duHLlSjp37sywYcPo0aMHZ5xxhq5yioiIFMO2bX755Rfmzp1LSkoK6enpwcdq1apFx44d\nGTJkCOedd14YoxQJL8M4/D8nu6O//5IaNWqwaNGi4P327dvzxhtvnHwsf0EJokSsc845h8mTJzN/\n/nymTp3K119/TSAQYO/evYwePZqVK1cyfPhwLrjgAl3xFBEROYJlWXz99ddMnDiRRYsWkZubCxRe\nhG3Tpg133XUXXbt2VadwkRK0Zs0aRo0aRUZGBi6Xi7lz5zJ79mwqVaoEUGJFDyWIEtFiY2O5/vrr\nad68OWPHjuXNN9/E5/ORm5vL/Pnz2bBhA48//jjdu3cPd6giIiKlxjvvvMMjjzzCtm3bsCwLKOyg\n2KtXL4YNG0bjxo1xu3WaKGKaBpzg/MGiO/rrfTRv3pwFCxYc8/FPPvnk5OM4DiqrSMSLiori7LPP\n5tVXX+XVV18lJiYGgEAgwI8//kiPHj0YOHAgeXl5Jdb9SUREpLRxHIfs7Gxuu+02evbsyU8//VQk\nOZw5cyYzZszg7LPPVnIocpgRogY1ETTlSQmilCk33XQTy5Yto23btkWGxUyfPp2ePXuyatUqfD5f\nGCMUEREpeT6fj5UrV9KzZ09mz54d3B4fH88ll1zC8uXLuemmm8IYoZR16gkROZQgSpnTqlUr3nzz\nTe6++25OP/10oHCuxYcffkj//v2ZN29esHW3iIhIWefz+UhNTaV///4sWrQoWDU8/fTTGTRoEG+8\n8QYXXnhhmKOUsi5SR3GFe5mLcND4ASlzDMOgbt26jBw5khYtWvDEE0+wadMmHMdh9erVPPDAA/z4\n44/cf//9JCUlhTtcERGRU+bAgQP85z//ITU1lbS0tOD2c845h0ceeYSOHTtSuXLlMEYo5UWkVhBN\nwwhJ7I5hYIUgnpKgCqKUWZUrV6Z79+68//77dOjQIbh9z549jB8/njvvvJOdO3eGMUIREZFTZ+fO\nnfTt25fJkycXSQ47dOjA//73P6699lolh1JiIrWCWB4pQZQyze1207hxY959910GDx5MbGwsAF6v\nl3feeYd///vffPnll9i2HeZIRUREQsO2bb744gv+/e9/M3/+/ODc+9jYWIYMGcK7775LgwYN1IhG\nSlSkVhDL4xBTJYhSLiQmJvL444/z5JNP0qBBg+D21atX079/f95//328Xm8YIxQRETl5Pp+P999/\nnwEDBrB69erg9nr16vHEE0/w2GOPkZiYGMYIpbxSBTFyKEGUciMpKYnBgwczadIkLr744uCVrA0b\nNtC/f38mTZpEZmZmmKMUERE5MVlZWbzwwgv079+fDRs2BLe3adOGCRMmMHjwYM29l7BRBTFyPr/G\nFki5EhUVRefOnWnUqBHPPPMMqamp2LZNeno6o0eP5tdff+XBBx+kZs2a4Q5VRETkuKWlpfHcc88x\nbdo08vLyADBNk+uuu47HHnuMJk2aYJqqC0j4RGoF0TAMzBAkd3YEJcg6Uki51KRJE1JSUhgxYgRx\ncXEA5OXl8dJLLzFo0CC2b98e5ghFRESOz88//8zgwYOZMmVKMDmMjo7m3nvvZdKkSTRt2lTJoYRd\npFYQyyNVEKXcql69Oo888gixsbG88MILZGRk4PP5ePfdd8nNzWXKlCk0bNhQBzQRESm1tm/fzr33\n3sv//d//BbclJSXRv39/Ro4cSaVKlcIYncjvIraCaBbeQrGfSBFBoYqEXkJCAg8//DBjxoyhUaNG\nwe0ff/wx119/PV9//XVwQWEREZHSwrIsVq5cyU033VQkOaxXrx5PPvkko0ePVnIopYouuEcOJYhS\n7kVFRXHnnXcyZcoU2rRpE9y+evVq+vbtywcffEAgEAhjhCIiIr8LBAJ88MEH9OnTh2+++Sa4vU2b\nNkyePJm77rqLmJiYMEYocrSIrSAahcntyd/C/UmOnxJEkUM6duzIpEmT6Ny5c3CuxsaNGxkxYgRz\n5szRMhgiIhJ2fr+f9957jwcffJAff/wxuL19+/ZMmDCBq6++WvMNpVSK1AqiaRohu0UKzUEUOcQw\nDFq2bMnzzz+PZVksWrQI27bZsmULQ4YMwe1206NHD1wuV7hDFRGRcsiyLN5//30GDRpEWloaUPjb\nddlllzF16lTOPPPMiD0Jl7IvUiuI5ZEuMYkcwTAMGjZsyLRp07jyyiuJiooCICMjg/79+zN37lw8\nHk+YoxQRkfLG6/Xy3nvvceeddwaTQ7fbTfv27Zk+fTqNGzdW5VDkFDCMEK2DGEEXb3QkESnGGWec\nQWpqKrfffjsVKlQAICcnhzvvvJOpU6dy8ODBMEcoIiLlRXZ2NjNmzODWW28lKysLgPj4eG6++Wbm\nzp1Lw4YNwxyhiJQlGmIqcgyVK1fm2WefpVq1akyZMoWDBw9SUFDAU089hc/nY8CAASQlJYU7TBER\nKcNycnKYPn06zz77bHCNw4oVK9KvXz8efPBBqlatGuYIRcq2wxXAUOwnUihBFPkTSUlJjBgxgtjY\nWFJSUsjKyiIzM5OxY8fi9/sZPHgwFStWDHeYIiJSBuXl5fHyyy8zZswY9u/fD0CFChW45557GDp0\nKFWqVAlzhCJln2EYmCEYHupoiKlI2WAYBklJSTz00EMMHDgQt7vwmkpGRgajR49m+vTpmnQtIiIh\nZ9s2r732Gg899BDp6elA4ZzDAQMG8Oijj1K1atWImtMkIpFDFUSR4+ByuRg9ejR+v5/p06eTnZ2N\nZVk89NBDxMfH07t37+BcRRERkZORl5dHamoqw4cPx+fzAYWVw9tvv52nn36a6OjoMEcoUn6UxyGm\nqiCKHKfo6GjGjBnDgw8+SPXq1QHw+Xzce++9TJ48mezs7DBHKCIikS4nJ4dp06Zxzz33BLtmV6lS\nheHDhzNhwgQlhyIlLCQdTEOUZJYUJYgif4PL5eKee+5h2LBhwcYAgUCA8ePH8/rrr2sJDBEROWEe\nj4fXX3+dMWPGBCuHlStXZsiQIdx3331ah1dESoQSRJG/KSEhgbvuuoshQ4aQmJgIQHp6Ok8//TTz\n5s3D7/eHOUIREYk0fr+fefPm8eSTT7Jv3z6g8PfmnnvuYciQIZrGIBImpmFgmiG4RdCcYSWIIn+T\nYRgkJiYycuRI7rjjjuAV3b179zJ06FCWL1+ObdthjlJERCKFbdssW7aMoUOHkpaWBhSOWLnlllt4\n+OGHSUxMVEMaESkxShBFTpDL5WLMmDHcdtttxMTEAJCZmUmvXr1YtmyZupuKiMhfchyHZcuWcfPN\nN5OZmQkUznm/6aabSElJ0ZxDkTAzjMLiwMnfwv1Jjp8SRJGTEB0dzYQJE+jTpw9xcXEApKWl0b9/\nf5YuXRrm6EREpLT79NNP6devX7ByGBMTw6233sqkSZOCvysiEj6GGbpbpIigUEVKp8TERB555BFu\nvfXW4JXerVu3MmrUKFatWhXm6EREpLRasWIFo0aNYtu2bUDhOoc33ngjjz76KElJSWGOTkTKKyWI\nIiFw+umnc//993P55ZdjGAaO4/DNN9/wzDPPsGvXrnCHJyIipczPP//Ms88+y8qVK3EcB8MwaN++\nPaNGjaJ27drhDk9EDjFC0aBGy1yIlD+GYdCgQQPGjx9PixYtgMKmA++99x5PPfUUGRkZYY5QRERK\niwMHDvD000/z/vvvB5uanXvuuYwfP55GjRqpIY2IhJUSRJEQSk5OZvLkyTRs2BAobD4wc+ZMJk6c\nqDUSRUS/Y2uRAAAgAElEQVQEj8dDSkoKr776anBbgwYNmDp1Kk2bNg1jZCKnVqRe+DCMYy98/7du\nEfT5lSCKhFibNm2YPHkyjRs3BsCyLMaNG8fUqVMJBAJhjk5ERMLF5/MxadIkJk6ciGVZADRu3JgX\nXniBNm3ahDk6kVMrUru7h6aDaRlMEDdt2kTHjh1JTU0FCtd76927NzfffDNDhw7VwuAif3DFFVfw\nxBNPUKtWLaDwivGYMWOC3yERESl/3nzzTcaOHRscUVK7dm2efPJJrrrqqjBHJnLqRVKCVN79ZYJ4\n+MS2bdu2wW3PP/88vXv3Zvbs2dStW5d33nnnlAYpEmlM06Rbt27cc889xMfHA7Bv3z7Gjh3Ll19+\nGeboRESkpH311VekpKRw4MABABISEhg6dCjdunXDNDWgS8q+SK0ghqJBzeFbpPjLI1JMTAzTpk2j\nWrVqwW0rV67ksssuA+Cyyy7jq6++OnURikQgwzCIjY1l4MCB9O7dm6ioKAA2bNjAU089xZYtWyL2\nQCkiIsfPcRx++uknnnjiCdavXw8UrqF7yy230L9/f2JiYlRZkXJB/51Hjr9MEE3TDK7tdpjH4wme\n8FatWpX09PRTE51IhKtUqRKjRo0KXlABWLx4MSkpKWRnZ4cxMhERKQk5OTlMmDCBJUuWBLd16NCB\nhx56iAoVKoQxMpGSFakXxkPSoKa8LXMRqf/YIiWlTp06pKSkBLvTWZbFrFmzGD9+fJgjExGRU+2F\nF17gtddeCzalOffccxk7dix16tQJc2QiJStSK4imaeAKwa1MDTEtTkJCAj6fD4C0tDROO+20kAYl\nUtacc845vPzyy5xxxhkAeL1exo8fX6TNuYiIlC2zZ89mzJgxwaY0Z5xxBi+99BJnn312mCMTKXkq\nKkWOE0oQ27Rpw6JFiwBYtGgRF198cUiDEimLLrroIp555hkSEhIAyM3N5dFHH+W7777TQVNEpAxx\nHIcffviBkSNHkpOTA0CFChUYN24crVq1CnN0IuERqRVElxGaCqIrgj7/XyaIa9asoUuXLsyZM4dp\n06bRpUsXBg0axPz587n55pvJzs7mmmuuKYlYRSKay+WiU6dO9O3bl9jYWAD27NnDM888w549e5Qk\nioiUAY7jsHv3bp588kn27NkDQGxsLH379qVjx464XK4wRygSHpF6nuMyCU2CGEHNit1/9YTmzZuz\nYMGCo7bPnDnzlAQkUpZVrlyZu+66ix9//JHFixdj2zYLFy7kpZdeYsSIEVSsWDHcIYqIyEnIycnh\npZde4uOPP8a2bQzD4NJLL+Wuu+6icuXK4Q5PJGwitYJYHkVQLitSNvzjH//g0UcfpUaNGgDk5eUx\nffr04LBtERGJXAsXLuSVV14hLy8PgFq1avH4449z5plnhjkykfCK1AqimtSISIlo3bo1zz//fHBx\n5LS0NB566CEtGSMiEsH27dvHgw8+SFpaGlC4VNiECRO48MILwxyZiMjxU4IoEgYul4sePXowbNiw\nYJK4detWunXrFuwQLCIikcPn89GtWzd27NgBFCaHDzzwAN27dw8e50Uk8oRm/mHhLVLoiCUSRsOG\nDeOqq64KnjysWLGCcePG4fV6wxyZiIgcL6/Xy7hx41ixYgVQmBx26tSJIUOGhDkyETlZLsPAbZ78\nrUx1MRWRU6d69eoMHz6cs846Cygcnz99+nSWLl0asWP1RUTKE8dxWLp0KS+//HJw21lnncWwYcOo\nVq1aGCMTkUi0adMmOnbsSGpqKgC//fYbt99+O71796ZPnz4cOHDglMegBFEkjEzTpHXr1tx2223B\nDqa7du1i0qRJbN26NczRiYjIX9m2bRsvvPACv/zyCwAVK1bk9ttv56KLLtLQUpEyoCSHmHo8HsaM\nGUPbtm2D255//nl69OjBG2+8weWXX14iK0noyCUSZnFxcfTv35927doBYNs2ixcvJjU1lfz8/DBH\nJyIix+LxeJg3b15w2SKAiy++mH79+hEXFxfm6EQk0sTExDBt2rQiow8ee+wxrrzySgCqVKlCVlbW\nKY9DCaJIKVCpUiWee+45kpKSAAgEAkyaNIm1a9eGOTIRETmWtWvXMnHiRPx+PwBJSUmMGTOGSpUq\nhTkyEQmVkqwgmqZJdHR0kW1xcXGYpolt27z55pt07tz5VH3U3+M45e8gIsclOTmZqVOnBoeaZmZm\nMnToUPbt2xfmyERE5I8OHDjAiBEjgssTJSYm8uKLL9K0adMwRyYioWSaJq4Q3E5myLlt24wYMYLW\nrVvTunXrEH664ilBFClFevTowe23316kq+nYsWODQ5dERCT8bNsmJSWFL774Aig8gbz11lu58cYb\nwxyZiJRFI0eOpEGDBtx9990l8n5KEEVKEcMw6NevX5GrQzNnzuR///tfGKMSEZEjffTRR7z88svB\nbtMXXngh/fv3D3NUInIquIwQDTM9wVUu/ve//xEdHc2gQYNC+8H+hLvE3klE/pJhGCQnJzNgwAA2\nbtxIZmYmGRkZjB8/ngsuuIA6deqEO0QRkXItLS2N8ePHB1vNV6pUif79+9OkSROMCFrnTESOT6gW\nuT+efaxZs4ZRo0aRkZGBy+Vi7ty52LZNTEwMvXv3xjAMzjzzTB599NGTjufPKEEUKWVM06Rz584s\nXryYN998E8uy+O6775g1axbDhw8nNjY23CGKiJRLXq+XV199lW+++QYAl8tFp06d6Nq1Ky6XK8zR\niUika968OQsWLAh3GBpiKlIaVa5cmYEDB1K/fn0A8vPzSU1N5dtvv9V8RBGRMHAch++//57Zs2eT\nl5cHQN26dRk4cCBVq1YNc3QicqqYIepgaoagCllSlCCKlFKtWrVi8ODBwSFLP/30EzNmzMDj8Rz3\nPhzHwbIsLMvCtu3gfBkREfl78vPzmTlzJhs3bgxuu/fee/nnP/8ZxqhEREJPCaJIKeVyuejTpw8d\nOnQACrvmzZs3j+XLl//p62zbxuPJJ2f/b+T98hPeHWvwbvuegp/Xkf/bz3iyMlWFFBH5m7788kvm\nzJkTPH5edtll3HnnnRpaKlLGuQwjZLdIoTmIIqVYQkICr7zyCs2aNSM7O5v8/HwGDBjAli1biiyk\nats2gUAAb0E+Tn427qy9xGSnYXB0xdB2RVFQpS4knU5cpSpqqiAi8hd8Ph8DBw4MDi09fGyuUKFC\nmCMTiRyRer5hGqFpUmNG0OdXBVGklDv99NMZMmQIUVFRAOzatYsnn3wSv9+P4zjk5+eTm52FLzcT\ncg4Q++taorL3FpscApiWn6j0bbh2/kB+ZrqGnYqI/Am/38/o0aPZvn07AFFRUQwZMkRdpUX+Jp1v\nRA4liCKlXHR0NDfeeCMXXnhhcNvMmTPZvn07ubm5BHxeohwvTkE+MXt+xHAKhz85GFjR8VixFbFi\nErHd0UX2a/rycf+yFs/BjBL9PCIikWTFihXMnDkzeP+CCy7g5ptvLjKKQ0T+WqRWEEOyBmKIlsoo\nKUoQRSJAw4YNueGGG0hKSgJgxIgRVKtaFWyLKMeLHbCIStuCgYPtjqEg6Qzyk+rhIQ6P38ATcJEf\nVYX8Kg3xJVTFofAgZfrycTJ3Y1lWOD+eiEiplJGRwbRp00hPTwcgKSmJm266iYYNG4Y5MpHIowpi\n5NAcRJEIEB0dzQ033MCHH35Is2bNuKFnT2JjY3H8HkworCIGCvBUrovlt3B++wV783fgyS2yH6ta\nbezGLfBXrk90XjpRvlyiMn/BW6UW8UnVwvPhRERKqSVLlrB48WIsy8IwDNq0aUPPnj1VPRQ5AZFa\nQXSbBu4QVP9CsY+SogRRJEJUr16dAQMGUL9ePZKSkvB5C4jBwm85mFl7KahcHysjHWvlQjhWl9L9\nu7H274aESjhtu4LpIqogCycvC6dS1Yg9eIuIhJLjOOzdu5e3336bffv2AVCxYkX69etH9erVwxyd\nSGSK1AqiGaLhoVoHUURCzrZtLrusPWeeeSZWIIDhFA4LtSwbKyoe60Aa1ooPj50cHikvC+uzt/BG\nJxFwxWLm7NcwUxGRQxzH4YsvvuDDDz8MbuvUqRNdunQJY1QikU0XoSOHEkSRCFBQUEBefj7g4HK5\nsGwLEwfLMcCxsHx+rJWL/t5OfQVYX/6Pgkq1IeCN2Ct7IiKhlpuby8SJE4PLWtSsWZOHH35Yax6K\nnIRIPc9wGSFqVBNB+bGGmIqUch6Ph4BlY5oubMcpPMA6AA6WA7btYO/YAH888EbFQP2mEJuIYwWC\nm42oaMj4DX79CXIP4mQdIJAQT5Su7ImIAPDqq6/yzTffBO/fc889NG3aNIwRiUQ+VRAjR4kniG+8\n8QbffffdUf+RGIbB+PHjcbuVs4oc5vV6sSwbl8sVvPJmWxamaeBYBrZjQ24Wzs8bfn+RaUKT1jiW\ng/XTapyczKP2a5xWB9c5/w8jLxN762oCF/0L09SAAhGRtLQ0Hn/88eCw+2bNmnHLLbeEOSqRyBAI\nBHjwwQeP2u44Dhs2bCjmFaVfeZyDWOLZ2NKlS1m6dOlR203T5LnnnlOCKHKI4zj4/X5MV9HvhAOY\nBlgYGDg42Rm/zzt0R0Hzywj88HmxiWFwH/t+JbDvV8zaDXHVrg952bqyJyLlnmVZPPfccxw8eBAo\n7CDdr18/TjvttDBHJhIZAoEAKSkp4Q4jpEK1hmEkrYOobEykFAgEAni9PmzHxgGMQ7fD6xUe5jgO\nhmFgGAYOLmwCOF5P4YOGAee2w7/q06LLW8QmYNZLhrgKhTv1ebF3b4OD6di7t+NYFsZpdfDl5RBT\noWIJfWIRkdJn/fr1zJ8/P3j/n//8Jx07diQqKiqMUYmIlKwSTxAbNGhAlSpVjqpWmKapIW5S7vh8\nPgp8PizLwTZMMH7/DphWgOjo309KinxnHHC7DHwBfp97WKcxgS3rgsmhcVodjLpnYefmUvDj9zi5\nWWC6iTq7BVEt2mFWrIyTnUHg+2XYaXuw6mjhZxEpvwoKCpgzZw6//fYbULisRdeuXWnYUMdGkeNl\nmibnn3/+UdsdxyEjI4OdO3eGIaqTowpiCejbty/dunUrdg6irtBJeZLv8eD1W9gYhfMG/8Awjp7Q\nbbpcOLZNwHGIdrlwTBdGbFxhz5oqtXA2rSl83rltCRw4gP+TBeByEXX+xcSe0xIzqQpEx1LYwNiB\nmvWIOqsF+Arwev3EHapQioiUN+vWrWPRokUUFBQA0LhxY6699lqdm4j8DVFRUcyePfuojqWO4/De\ne+8xatSoMEV24kwjRHMQI+j8qsQTxNNPP53k5GRVC6Vc8xQUUOAP4Bh/r2W6aboIWBY4hQfbKJcb\nX8XqOIlVcDLTC59z3iX4Nq/H+m0XUS3aEt3sQtw16oArCkxX0WTUsXFsG2LiMIHsrCxiYmOJjY0N\n4acVESndvF4vS5YsYe3atQC4XC6uu+466tatG+bIRCKLYRg0adLkqO2WZVGzZs0wRCQnQnMQRUpY\nIBCgwOf/28nhYS63m4DfT8B2cLtd+CtVwWjcksDKTzAanI1/13bsrEwq3DoUV+WqEJsI7qjiK4OG\nC8zCDqm2HQDHwe8rXBMxLi7uJD+piEhk2LlzJ/PmzcM+1PCrdu3aDBgwQCMqRERDTEXk1CvwerH5\n6wr6sZaTNQwTt9td2OHUMIiKicOufDoUeDCq1yGmVjQxHTqDOworNrEwAbQC2EV3gmm6gic/hmHg\nmG6wLQK2DT4fXtMkJibmpD+viEhpt3DhwmD10DRNRo4cSVJSUpijEhEJDyWIIqeQ4zgEAgECloVj\nO2CAP2CB+ddfPQejcM1D19GVRsN04Y4y8Pt9RJkmxCVArQZE1/8HLtPBF5tEgTsBK2AANqYBUYYD\npomDCQ64bAuX4WCaJsahZNExXWA72Dj4fT6io6N1BV1EyjSPx8PUqVOD1cPmzZtz8803hzkqESkt\nVEEUkZBwHIcCrxefL4DfcbCdQ5U6x8YwDY7nEOEYJgHLIrqYBBEKr3Ib0TEEAgHMmFiiO3TH544h\nl9jCjqhHliAdKABclkOcK4BhmliGC8txcFk2bieA6XIHk0THtrAPrcMYHR190n8fIiKl1auvvsrm\nzZuBwtEUw4YNo0KFCmGOSkRKCzNECaKpBFGk/AoEAuTme/DZRmErUgwOZ4QGhUNEj4th4Dhg2xam\nWXySaNs2noBFgRmHhYnjgGHYRGMTwDxqKKuFQa7lIta2iXJbOIYLi8LOqFEcThJNHGwcx8F3qIoo\nIlIWeTwennjiiWDHxZYtW3LxxReHOSoRkfBSgigSQoFAgJw8D37ncHJ4cmzDhT9gEeU2inT+tSyL\nXK+fg16Lg77C4ai/lwwL71WKtklwmwQcs7CieIQCxwTLJspVmCTahknAtogyLAzTdSg5dQo7nIqI\nlFGvv/466emFHaCjoqLo3r07NWrUCHNUIlKauIzQDA91RU4BUQmiSKg4jkNu/p8nhw4c1/DSIMPA\nxoU/EMBlmhiGgW3bZHoC7PEcO3lzgIM+OOizqRHrYBocVU0ssE2iTDsYkIWJ2/49QcQBBwdHayOK\nSBmUnp7Of//73+Dcw+TkZNq1a6fmXCJS7ilBFAkRr9eLz+ZPK4cOJtgWuI7zq+c4+A9VCw/kB8j1\n29iOQ7TLICnGhWma5AUM/qzOl1bgUCPWKkwS/1BJ9FvgNmwwTDAMLAyMPyxuq+RQRMqiJUuWsGHD\nBqCwenjJJZdwzjnnhDkqESltTMPAFYJzITOCzqeUIIr8Tc6h5i0FPj+244BTmBPalgXGX3ylDANs\nh0OTBf+4YxzHJmDZFDY8dcguCLAxs4CMguJSQD8JboOGSdHEuVzkWcc+8KQVONSOt/H9sYroGFR0\n7GDiaDkmLtsKzpM8vnY6IiKRJSsriyVLlgSHl1arVo3OnTuTkJAQ5shEpLQxDSMkyZ0SRJEyyHEc\nCgq8FPj9+G2wjhhKajgOriOa0fwZ2zALu5karsM7Jt/rJ8PjY2O6h8yCALYDMS6DMypFUy3GhW07\nHPQdvTJiXsBh3X4vNeNd1KkYQ07g2AEUWA5ul4NdJEgD2/k9+XQO3YxDia/pLr45johIpHIch/Xr\n1/PFF18Em9Oce+65dOzYMcyRiYiUDkoQRY6D4zjk5uWT7/+92nZknmXg4BznlSEHA9O2wDDxBQLs\nyvSwYncuuf6jq4Rp+QFMoGHlaM5KimHLQX+xw0l/y7cwDR81KkSTf4xKYqbXoWa8jY+/SPqcwvUa\nDcMhLi7uuD6TiEik8Pv9rFixgq1btwKFw+j79euH6xhLColI+eYyQtNgJpKa1Bxnv32R8utwcpjn\nd46aw3fEs/g77WcyPH52pGfz494c9uZ4OTMpmhrxx1jKAtia6ePbPXmcVTnqmO+yOy8AzrFnI9pQ\nOCT2uDiYhlmkc6qISFmQmZnJ22+/XaQ5zb/+9a8wRyUiUnqoghgia9eu5csvvwQgMTGRXr16FWnu\nsWPHDhYuXAhAfHw8HTp0oHbt2iGN4YsvvmDdunUA1K5dm86dO4f0BD8nJ4fFixeTlpYGFK4X1apV\nq5Dtv7Ty+fzk+22cP12/8PAyE8dOEgOWxYHcAn7an89nO7LIP6JiaBrQ9LR4zqseR7bfZvtB31Gv\nz/XbfLsnj+Y14tmaHSj2PXZl+6lbyTxmFfHo9LCwQ+nh7SbOoeGlDhWSko75WUREItW3337L999/\nH7w/ZMgQjZYoxb777jvWrFkDQPXq1bn00ktJTEwM2f4ty2LRokXs3bsXgKZNm3LRRReFbP8Av/32\nG5999hkejweADh06ULdu3eDjjuPw1ltvkZubC0Dr1q05++yzQxpDaRCpTe9M0wjJIveh2EdJUYIY\nIkuXLmXkyJEA1KpVi169ehV5fPXq1QwbNgyA0047jQYNGoQ8QZw3bx6vvPIKUHhw+de//hXSBHH/\n/v2MGzeO1atXAzB06NAykyAWLgrvp8DnO6LKZhDlMglY1h/m7RXzegxMx8Y5xtMKfH5+2J3Fgk0Z\nxSRphX1r1qXlsy4tn0ZVYmlRswI/7PMc9bxsn02ezybGZeC1jt7T/gKLhknHX810GxRpluPCwsAh\nMTExYg/kIiJ/Ztq0afh8hRfhzjjjjKN+r6V0effdd5k4cSIA5513Hs2aNQt5gjhu3Di++eYbAO68\n886QJ4g//fQTI0eODDZFSk1NLZIgAjz88MPs2bMHgGeeeaZMJojOcY9iKl3UxVROmN/vD14ZOvz/\nR7Isq8jjlmWFPAafzxd8j4KCgpDv37ZtCgoKgu9x+Ac2kjmOQ77Hg9dv4bEcLAyOTK7MQIBow/nL\n7qSOYRTO3TuyO6njYNk2+3M8/JbtJacgwGX1K7I9s4Cfs479d7cto4A8n0WbuhVZk370v+PGAx7O\nr5nA9mNUEQsCxz4Am8CR/+XFmjbOocOA4diYOFSoUAG3W4cGESl7tm3bxv/93/8F7994442qHpZy\nPp+P/Px8oPD86fDQ4FDyeDzB9zgV5zaWZZGfnx98j0Dg6N/vIx/3+/0hj6E00IXnyKGzQCm3HMch\nOzePHP/hzp5HH7jcOFh/1dTlEBszuIZgboGPPVkelm3P5Iufs7AP5WymAS1rV6BDw4pkFVh891te\n8LEj7c31s/WAh1oJUezJK/pD4gk4GH9yEc4ptkYJUUbRg7Pr8PDSQ8ltFAEqVayoRg0iUmZNmjQp\nmGBUr16dbt266aRVpIREcgVRy1yIlAOHk8Nsv4PzJ8MxDTju7qQ2BlEE+DWzgClf/8rOg96jn+PA\nql9zWfVrLrUrRtO5STU+2ZFVbNVvfVo+1zWtelSCCJDnt4gyoZjGp8dcu7ByjIH/UF8qE4cEt4Nt\nuMBxiFFyKCJl3N69e1mwYEHw/iWXXEKDBg2UIIqUkEj9rrkIURfTk99FiVGLQimXCgq85PjtP00O\nj4vjkJXjYdOvGaz5+QBfb8vgu11ZNK4aR3zUn3+9dmf7SP0hjcsbVCr2wOMA6Xl+KhSzH5/l4D7G\ngdZdzNuaQJRZ2IzGbThUcBd2ZHVhE+dySKqk5FBEyraFCxcGG5HExcXRrl07qlevHuaoRMqPSK0g\nRpoxY8YUu33w4MHHvQ9VEKVccBwneDMMgwK/H/s4ro84hS8u0silcJPNbwdyWbc7h3nf/UZGftH5\nAqclRnN5clXiY90s2pJJjq/4Oae5Pou31+3jqrOqsmxnzlGPr9qdS/tGlfnxQNG5iFEug5ximtTE\nuAzcpsmRiyUaQM14E9OAiqaFY1u4jSiiokziY2M031BEyjy/388HH3wQnJ9fv359WrRooeOfSAmK\n1AqiEaIupsYp7mL67bffsmrVKt5//30qVapU5LGsrCw+//zz495XiR8ZU1JSmDNnTkm/7Sm3c+fO\n4J8PHDjAlVdeWeTx/fv3B/+clZXF/fffT+XKlUMaw+bNm4N/3rhxI506dQrplzE/P58tW7YE77/z\nzjvB1tOlVe/evfn3NdcQsBz8joPtgOE4hxq1/HXFLICBGxvn8HMdB8e22LEvm5c//4WdmQUUFDPO\nc1+OjzmrfiM+yuT2tnVYuDWT/fnFN5U5kB/Ash2iXQa+PyR9+X6b6GLCTIgySSs4OulsWCmavCOW\nuDANqBPtJzYrHTsQ4I35H/LeRwuZOHEiLVu2/MvPLyJSFvzwww9s2rQpeJHw3HPP5bzzzgt3WGHl\n9/uZM2dOqT8nO/LcZtu2bfTp0yekjYUcx2HTpk3B+x9++GHI18U8cOAABw8eDN7/z3/+w4wZM456\nzmEzZsxgyZIlIY2hNNi9e3e4QyjTqlatisvlwufzFclLANxuN+PGjTvufZV4grhhwwY2bNhQ0m9b\norxeL4sXL/7Tx7/99ttTGsPBgwdP+cFlx44d7Nix45S+x8kY9cijXNT2Yg76Ds8zLEycorEIHOfo\nahsDAwuvz2ZPRh4//HyQH/dkk1tgUSHGRdem1Yhym3y+LZNdmUfPOcz320xb/gv9LzmD9zdlHLOS\nuHz7QVrVrcS3v+Ud/eAfCoUxLgPD+GM/Uoh2GVSMdpEVgGjDobpZQFwgn6jcAvZk5dOlx03s2LGD\nxMREVqxYwXnnnadhpSJS5lmWxYoVK4InTAkJCVxyySVUqFAhzJGFl23bbNy4MbhGcyTIzs5m2bJl\np/Q9du3axa5du07pe/zwww9/+vjGjRvZuHHjKY1Bjl+kNKlp0KABffv2xefzMWjQoJPal8ZWSJn0\nwuQXubLbtcTEVzhGT89jfUkPp5KFawnats3mvdmkfv0rK7YdPOrZX2zJJNpt0r5JVdo3rkrqt7/h\n/0MVMGA7vPrlr9zYujZvb9h/1D4A9uT4qBhzdLLmNg3+WJ9MrhrLnj9UI90GtD49joQYN1UdhxjD\nIdqViDu2GtHRMWTu2BFsq52Tk8OKFSvo0aOH5t+ISJm3f/9+VqxYEVyEvEqVKlx11VVhjkpEIoXL\nCFGTmhIYYWsYBh999FHkJYjNmzcnOTk5YschS+l39jnnBJPD4+eQm1vArn25fLPlAL8dLMAwoGal\nWKpUjKZirJtot4kvcPRwUl/AZuG6dKonZnHHP+swY8Xuo5LEfL9NfkGA+CiT/OJajwJ+6+jtzU6L\nZ0/u7/Mb490mSbFu9mX9vq1ClEHrWonUqVoR0yy+Mlq/fn3atWvH7NmzgcJx6rt27VKCKCJl3i+/\n/FJk1E67du2oX79++AIqpRISErjiiivCHYaUUY7jsHXrVtavXx/uUMq8K664gn79+nHJJZccNRex\nS5cux7WPEk8Qb7rpJu677z5NDJdTwrZtVm/YeBzJYWGFECA3r4DvtuznlU93sCfz6IXpARqeFk/v\ni2qxfk8u3+w4upIIkJ7jY/ZXv9KrVS1mfbPnqMc/2XSAS5pUZfHW4l9fnAZVYlmdXhhTrNugTZ0E\nNh8sTA7rVIiiUeVYqibEUCkh7k8vupimyU033RRMEDdv3symTZto0aLFMZNKEZFIZ1kW69evLzJ/\n/ugNgFQAACAASURBVMYbb9RxrxhJSUm8++674Q5DyqhAIEBKSgoPPvhguEP52wwjNMNDS6o2dviC\n2KJFi/7w/kbpTRBFQuWPnUkNw8Dj9VK9dt1jDCstZAMHDmRzIMdLQUGAvVke9uf4if2TZSm278vn\nhYXb6HL+6Vx6VhU+25xR7PPSc3zs2JdH3coxR81J3JfjIzHq2HP+/pjg/X/2zjs8inLtw/fupvdC\nSIWEFlpCB0WKIEUB6ehB2mdDRIUDKCpSRUXBCnoAERCwgdKkBumdhBqCISEhCYQUSN0k28t8f0QG\nwm40SMgmMPd17cXOO7PvPll2dub3Pi3QzZ6Sv7yNdT0ceDTYDTdne+p6g51cjoeLI4729hX2xvfq\n1YuQkBCuXbuGIAhs27aNwYMH4+LiUqHXS0hISNQ0tFptmRy7kJAQevXqZUOLJCQkJO4vP/zwwz3P\nIQlEiRqH0WhErdWhN5owCbd8gXayv0RjOdVJDXoD124oOR6fzZp9yRRrbuXxOdrL6d06mD4t6nLu\nSjFHkwqszrH1TDbDHgkmMtiNuIwSq8fsu5jH/3Wuw4+nsiz2mczWpaudXIbDbcHpTnZyejTwwoyM\ndiGeBHg64+LoeE+h2XZ2dgwePJivv/4agEOHDlFQUCAJRAkJiQeWgoKCMkVNhg0bJkUwSUhI3BUK\nuQxFJbSoqIw5KsLMmTPL3ffBBx9UaA4pxkKixmA2myksKiG3WE2h3ozaLEcnyNELpf+qzTIM5bgO\nS0o0rNufyKhPD/C/7QllxCGAzmBma0w6n2+MQzDqeK5jULl2rI/OoGP98luU6I1mDEYTzlY8kuX9\nNDxSx534XA0A7g4KXmkXQKsQb7qFB9DA3xtXJ6dKydsdMWIE9vb2AGRmZrJ///57nlNCQkKiurJ/\n/36ys7MBsLe357nnnrOxRRISEjUNOTKxkuk9Pcq9C6xc/P39yzycnJyIiYnBx8enwnNIy2gSNQKz\n2YyyWEWxCcpb15BxswbpTQSKi9UUKtVczipEMJkY2rEOUWezUGmt9yQE2BebRVuVnmEdAlkfY+kF\nBEi5XkJdHyeu5lvPWUzKVhHk6cjlv0TfTcprtBru58KJayqGNKtFM383wmp73ZdCTo0bNyYiIkIs\nsb1mzRpGjRpV6e8jISEhUR34+eefxecRERGEh4fb0BoJCQmJfyYhIYEJEybw/PPPM3LkSLKzs5k6\ndSqCIODn58eCBQvExX5rWKtgOn78+LvK/5QEokS1RxAElCU3xWH5oumm89BsMpF9o5C4lBss3Xae\njNxboaB1/NwY0akh9vb2bD+dwZUcK30HgdPJeTQIcKdBbRcu31Bb7N91/gYvPBHGmmPWm76qdCZc\nnMueXt4udmisVEEd0NSXhrVc6NrQjwAvt/taPMHZ2ZmePXuKAvHgwYPk5+ff1aqShISERE0gPz+f\nffv2idu9evWq1AbrEhISDwfySmpzUZEIU41Gw/z58+nUqZM4tnDhQkaPHk3v3r358ssv2bBhA8OH\nD7+r9/b29iYlJaXCx0sCUaLao9XpUBmhPHEoQ0CpLEGj1WPQG7hRoOKn/Ykc+TML4Y6Q0/ScEhZv\nPYejvYLnezfn0nUXjsTnWJ1384mrvNqvOZdvWDbM1RnMCOXkE0JpTqPujrYVPZv4cvRqUZmxgc1r\nMaxlMLW9qqZhs6OjI927d2fx4sWoVCr0ej2//fYb48aNq5L3l5CQkKgqNm7ciF6vB8Dd3Z3u3bvj\n4OBgY6skJCQkysfR0ZFvv/2WZcuWiWMxMTHMnTsXgO7du7Ny5cq/FYgzZswoE4VmMplISkoiKKj8\n9Kk7kQSiRLVAEAT0egM6g0GsSqqQy3B2ckKrN2C2Ig5NRgOZWfmcTrjG0s0xZOWVegoVchkdm9fh\nvwMiySnS8fuJVEo0hjKv1RlMfLv9PM91b8Kj4b6cuJRnMb/eaEanM+DqqEClM93V3xPi48yJ28Sg\nvUKGp6sDRbrSsYa+zgxrUZvWdXzxcqu6FW2ZTEZISAhNmjTh9OnTAERFRUkCUUJC4oFj+/bt4vPw\n8HBCQkKkHswSEhJ3zc0cwsqY5x+PkcstFrI0Go0YUurr60tOjnXHxk0CAgIs5mzdujV9+vSpsK2S\nQJSwKWazGY1Wi85gQmsSMCLjVjahGUddMSbh5tgtlIVF/Bx1huVbT2O8w1NnMgscibvKkbirBPm6\nM3FQB1btvURmnmU46S/7E5gytC0XrxWhVBss9u85l0HncH92xf39yXgn/p6O5P81nwyY0C2UAr2J\nMW0CaFLbjfp+7ni5/X3vwvtFSEgIrVq1EgXi+fPnuXbtGiEhIVVui4SEhMT94Nq1a8TGxorbrVu3\nln7jJCQk/hXVqYqpcGdonBVu5iBeu3aN/Px8fH19CQ4Ovqv3kQSihM0wGo0UqdSoTLK/isuUPXEE\nZJgE/hKNpSNGnYHcvEJOJ1xDo9HzaLNgjl5ItwglvUlmXjEfrtrPu6Mf5/s9l8hRaiyO+WnfRfo9\n0oifD6VZ7Luh1ODtaj0R2MHOeq5gq7oexGWVejPt5TKm92lIlyb+ODmU9iy0dYNmLy8vmjZtipOT\nE1qtloKCAk6cOMGwYcNsapeEhIREZXH8+HEKCkrbFTk7O9O8eXM8PT1tbJWEhITE3ePq6oper8fB\nwYHr169Tu3btvz3+zz//ZMqUKRQWFuLu7o5SqSQgIIAvv/yShg0bVug9JYEoYRNMJhPKv8Th3xWe\nKfUlChTkK7l89QY/7jzNqYRrqDR6XJ0daF7Pn6n/6UiOUsOmwwkUllhWFTWYzCz46RDTxnTj41/P\nWuy/XqDGz90BmQwLoWk0CdhZyUxuFepJfJZlH0SFXEb3prX46VQWzz8azKMNfIioWws7hfXejLZA\nJpPRvHlzAgICSEtLo6SkhOPHjzNkyBCbi1cJCQmJe8VsNhMTE4NKVRo1EhgYSEREhBReKiEh8a+Q\nyypWYKYi8/wbOnbsyK5du+jfvz+7du2iS5cuf3v83LlzefPNN+ndu7c4tm3bNubMmcOPP/5YofeU\nBKLEfcdkMokucZlMhkwmEz2HfycOoTQvMToujelLo8jOKy6zt7BYy9HzVzh6/gr+Pm6MH/gIW48l\ncSH1hsVMOoOJ6D+vEhnmS1yaZb5h9MUMWtXz4WxKfplxT1cHijSWLTE6N/Vl1R0VTOUyeLtPA4J8\nnFk6qiVhtT1RVCNheDuRkZGEhISQlpaGwWDgzz//JCcnB39/f1ubJiEhIXFP5OTkcP78eQyG0jD/\nOnXq0Lx5cxtbJSEhUVORy2QoqigHMTY2lhkzZpCfn49CoWDt2rWsWLGCd999l3Xr1hEUFMTgwYP/\ndo7i4uIy4hDg6aefZvHixRW2tcoF4smTJ1m1apXkqXjAkcvlhIaFERxSB2c3d+zsHEAuw2w0YtRp\nUDi5guLO0E0BjUrDlWs3SM8uQKs3YDQYKVLr6NsxnI0H/6Sw2Hrfwev5JXz4/V4mDe+MWRCIT7PM\nGdx98jJvjuhqVSCm55TQopFl+FHXiABOpRaWGWsU4Eq+2sjtRUx93eyZ/nQ4nZsF4ehQfm+a6kJg\nYCBNmzbl+PHjmEwmrly5QmJioiQQJe4ZvV7PjRs3uH79OoWFhSiVSrKyssjMzBSPyc7OZsuWLQQG\nBuLp6YmPjw/BwcG4u7vb0HKJB4XExESuXLkCgEKhoFmzZg/9b5sgCGi1WjIzM8nNzUWpVJKbm8v5\n8+fFY1QqFfPmzcPOzg47OzucnJxwcnJCoVCIxeNu/7ci3Pma8v6t6rkqOmdlzvUgfG73MpfZbObM\nmTMVep+HmZYtW7J161aL8ZUrV1Z4DicnJ86dO0erVq3EsdjYWJycnCo8R5ULxB07dpTpSyTx4NG5\nc2femzGL4LD6KOzLVmKSO9jhbG+HVii7QKAsUBJ3KZ2lvx3m1MV0izkDfN35T49WuDg5snhTNDq9\n9Ub3C9cdYeYLPbmSXYhKW7bojNFkRqXW4uxgh+aO1+sNJhztLb19df3c2RJ7y6sY5O3EwPZBLDlw\nFYVcRrswT57tEEJ4oAchfh41ZuFDLpfTsWNHfvjhB0wmE5mZmaSlpdG1a1dbmyZRw7hx4wYnTpwg\nLi6OS5cukZ6ejlKpRKVSodPpxEdR0a2qvomJiUybNg0nJyccHBxwcnLC09OTgIAAQkNDadCgAc2a\nNaNt27aSaJS4a1JTU8nKygLAwcGBjh071pjf5spCp9Nx/vx5zp07R3JyMikpKWRnZ1NcXIxGo0Gn\n06HValEqleJrlEolc+fORS6XI5fLUSgU2NnZSaG5EpWGRmNZB6ImUJVVTCuDd955h/HjxxMYGIiH\nhwcFBQXk5eXx1VdfVXiOKheIarUatdqy8bjEg8GgQYN4/6OP8QsMAWsngiBgFgT0Wh3pGTfIKyxB\nq9VxPa8YpUqLWqu3Om92XjH/+/UwAb7uTB/zOAt+OkyJxvJYQYDVO04xoHNjftlzwWJ/Zm4Rvh5O\nXMstmz/o7uJA8R2tMNo3qsWZq7fCWh8L92Fyv0a4uzjSrXkA9nZyfD2c8XBxqpEX0K5du+Lo6IhW\nq6WoqIikpCS0Wu1drTBJPJxcunSJbdu2sW3bNs6cOYNarcZsNmM2myu0Em0wGLhxwzIUHBBvTuVy\nOV5eXjz22GMMGDCAAQMG4OvrW9l/isQDhlqtJiEhQVyQcHR0fGgWvvLy8ti9ezfbtm1j//795Obm\nljkv/+ncFAQBnU5XRdZKSEjcLx555BH27t1LbGwsBQUF+Pr60qJFC5ydK95WrcoForOzM66urlX9\nthJVQJOmTZnz4Tz8gupYP0AQyM9XkpiSwaotR/nj+MUyFywHewVPd2nBoMcjOBKbyqGzKRZTZOcV\n8+mavbw1ugcfrtpv0eIC4Ep2ISNre1g1QaMz4Oxg+bXv0CSA/fG3PIW+7o70aBXCsv1XGdO1Dj0i\nA2gS4o23u0uNFIPWaNCgAWFhYWIp+HPnzpGXl3fXpZAlHmyMRiP5+flkZGQQFRXFTz/9RHx8/D/e\nbNrb22Nvby96IFQqFUZjqefezs4OFxcXzGYzRqMRvV6P2Vx6Lt+8oYVS7+TmzZvZvHkzcrmcRx99\nlFGjRtG1a1cCAgLw9vZ+6DxDEn9Pfn4+cXFx4nb9+vUJDQ21oUX3B7PZTFFREXl5ecTExLB69WqO\nHDkiFuYpD5lMhoODA/b29igUCjQaDXr9rcVWR0dHBEEQz827QS6X4+zsjKOj4wNznZSoPARBQK1W\no9VaTxWqzihkoKiES42Vmof3BaVSyaJFi5g2bRp2dnZcv36djz/+mClTpuDl5VWhOapcIPbq1YsR\nI0ZU2+IdEv+eyJat8KgVYH2nIJCReYNpX63n0Jkkq4foDSY27jvLxn1nGdazDc/1bs0vf1hWHS0o\n1rB212me7tSEzYfirc51+uI1Wjb0Jzb5eplxT1cn4jMLyozJZBDg4871wtIcqSBvJ94eUJ8LZ48y\n2F+P8tRhLmma46voiJdbowfqwte9e3dRIMbHx1NQUCAJRAmgNBTo4sWLxMTEsHv3bg4fPlxuc14n\nJycCAwPx8/OjVq1a+Pj44O/vj6+vL25ubmi1WpYvX86lS5eA0pv2l156CXt7ewoLC7lx4wY5OTnk\n5uaSl5dHfn4+OTk5YpERKL0hPnbsGMeOHaNOnTp0796dJ554grZt2xIeHm7RWFji4aSgoICLFy+K\n2927d7ehNZWP2WwmNTWVmJgYDh48yJ49e7h8+bLVY+3s7PDx8aFWrVr4+vri6+uLn58ffn5+eHt7\n4+zszA8//EB0dDRQKh7ffvtt9Ho9Op2OkpISioqKyMnJIT8/n7y8PG7cuFFGUN6Oo6MjISEhhIaG\n0qJFC1q0aCHd60mImEwm1q5dy44dO2xtyl0jq6QQ06q6f3znnXfKLIx5enri6enJu+++y9KlSys0\nR5ULxEaNGjFkyBDs7at/IQ+JimM2mykoVqEXrH/5s7JzePWD1cQlZVrdfyfr95yhb+cIBnZtzu+H\n/rTYf+FyFkOeaMnmQ9Zffyk9h9ZN6loIxLoB3mw5VdaGjk0DOXEpj9qeTvSLcMWYc4kR/f6vzEXQ\n3d2dNm3a8MQTTzB06NAHpiJev379xJj09PR0rl27RvPmzR8oESxxd5jNZg4dOsTmzZs5fPgwcXFx\nZYTaTfz8/GjVqhWtW7emcePG1K1bV7z59PX1xcHBQfwepaSksHnzZlEg+vn58cwzz1CvXj3xPYuL\ni7lx4wZ5eXnk5eWRkZFBcnIy586d49y5c2XEaXp6OmvWrOG3336jVatWdO/enWeffZYWLVpI392H\nGEEQuHbtGunpt/LYn3rqKRtaVLlcuHCBjRs3cvDgQc6cOUNhYaHFMT4+PrRo0YLmzZvTpEkTQkJC\nypyXXl5eomgrKSlh79694mtlMhlz584tM19JSYl4Xubk5JCZmUlycjJxcXHExsaSlZUlevw1Gg2J\niYmkpaWRl5eH2Wymf//+dOzYEUdHx/v4yUjUBPR6PbGxsTVSINY00tLSyghBJycn3nzzzbv6PZTa\nXEhUGEEQ0BsM6HR6zIKAIJR632R/NRDUm0u7Ft7JtYxsjp5J5MlHm/Hko82Qy0ubxf9+IJaLqdnl\nvt+OIxd4a0xvvN2dKSi2TGy+kJxJ0zA/LlqpWKrSGHB2LPv19nF3plhrwnRb+VEvN0de7hsJyKnj\n64i+OI+dO2Np1KgRFy9eFC98xcXFHDx4kJiYGNatW8fIkSN54YUXCAwMrOCnVz3p1KkT7u7uFBcX\nYzAYOHHiBL1795Zush9SLly4wJdffskff/zB9evXLYShg4MDHTp0YPjw4XTr1g0vLy+8vLxwdna+\np1BPuVwurnA2atQIKBWNarUapVJJYWEh+/fv5+eff+b06dPi4o1Go+H48eOcPXuWX3/9lYEDBzJh\nwoQHMqRQ4p8RBIETJ06I31tPT086depkY6vunYyMDL7//nt++eUXUlNTLQp9yOVymjVrxqhRo+jR\nowf+/v54eHjg5uZ2zx48Nzc33NzcqF+/PnArTFCpVJKXl8eJEyf45ZdfOHLkiPi563Q6Tp8+TWxs\nLJs2baJPnz5MmjSJhg0bStcWiRqJQkaltLmoqhBTOzs7Ll++TIMGDcSxCxcs63L87RwVOWjBggWc\nOXMGk8nEK6+8QmRkJFOnTkUQBPz8/FiwYIHkEXzA0Wq1pW0nzGBGBrK/bgaF0odJryP1Wi6X0rLI\nLSjBYDTi7uqEh6szWw+eY+uh85hvE2aO9nY8/XgLnu3dlo17zxKXbN2z+NOOaAZ3a8XKrTEW+6KO\nJ/DiwI5WBaK7iwMldxSdGfx4M7ZGp4nbPu5OLJ/Sm0cjQm+7uQ2jbdu2zJgxg7i4OP73v/+xbt06\nlEolgiCg0WiIj49n+vTprFq1ii+++II+ffogl8tr5IXP2dmZdu3asX//fgCOHDly16W9JWo2giBQ\nVFTEF198weeff26RwySTyfDz8+OVV17h5ZdfrjLxJZfLxZvT4OBgmjdvzhtvvEFSUhJLly5lzZo1\n5OXlieX7k5OT+fzzz1mxYgUffvghL774Ik5ONbOAlMS/w2w2c/ToUXG7TZs2d1WUoTpxMw9w8+bN\nvPXWW6SlpZXZL5PJ8PT0ZPjw4bz++utERERUiV0ymQxXV1dcXV0JCgoiMjKSsWPHkp+fz9KlS/n+\n++9JSUkRcxhTU1NZvHgxK1eu5L333uPtt98uE10gISFR+bz99tuMGDGCoKAg3N3dKSgoIDc3l6+/\n/rrCc/yjQIyOjiY5OZm1a9dSWFjI4MGDxUIBTz75JF9++SUbNmxg+PDh9/THSFRfVGo1GoMJM3KL\nvvYmo5ELiVf4NSqaX6Ji0BtMFq9/tEV9pr/cj+Oxl9kTXZobojMY2bDnDBv2nGHCc0/g7eFqNTcx\nK1dJgK+b1d46aq0eJ0frCxOtwoO4kJYrbjcM9sHVxYUcpQZnBztG92zKkM7htAwPLvdCFRkZyZIl\nS5g6dSpLly4lKiqK5ORkMcE6KSmJoUOHMmrUKCZOnEijRo1wcXEp/4OspnTr1k0UiHFxcRiNRilv\n5CGhpKSEkydPsmDBAvbs2SMWpZDJZHh4eNCwYUOGDBnCq6++io+Pj42tLaVRo0Z8/vnnTJ8+na+/\n/ppNmzZx+fJlSkpKKxMXFhby5ptvcvjwYSZOnEibNm2kyrwPCQaDQcyphpqbf6jRaEhOTubrr79m\n9erVFkVkGjRoQJ8+fXjttdeoV69etRBbPj4+vPfee4wdO5Yff/yRn376ieTkZLGNhlarZdasWezd\nu5dp06bRsWNH3N3dq4XtEhL/RE1rc9G1a1cOHDjAmTNnKCgowNvbm7Zt21ZuH8T27dvTokULADw8\nPFCr1Zw8eVKMU+/evTsrV66UBOIDilqjQaM3YRY9hgKCYEaj0aHR6riUmslbn//GlSzL5vM3OXE+\nhRPnU3i2dzuG9WrL+t2ny+z/+pd9THjuCQqKVFY9iWcuXqFZPX/+TLEMRy3P2xVetzabjyYD0CjY\nh//+pxMX05V8+erjtGjgT3gdP+zt/9mBLpPJaNCgAfPnz2fMmDFs3ryZXbt2cfLkSfR6PXq9npUr\nV3Lo0CHGjh3LqFGjCAwMrFEXvS5duogC/MaNGyQmJornvMSDS0JCAqtWreL7778v03LCwcGBJ554\ngr59+zJgwADq1q1bLb/PPj4+zJw5k1GjRrFx40a2bdvGsWPHMBqN6HQ61q1bR3R0NC+++CKjR48m\nLCzM1iZL3GcSEhLIzS1dGJTJZDWuvYUgCGRnZ7N27VqWLVtGQkKCuM/e3p7WrVvTt29f+vfvT8uW\nLavlQp6fnx+TJ09m+PDhbNiwge3bt3P06FGKi0tbRh08eJBLly4xatQoxo4dK4aUS0hUZ+Tyyqli\nWpVFt52dne8pxP4f75Bvli0GWL9+Pd26dePIkSNiSKmvr2+5le0kajZmsxmt3lgqDgWBQmUxl1Iz\n2bD7FGcTrqLW6nF3daJ7+8bUCfDhWGwy+08mlgklvZ1f/zjF8Kfa80SHJuyLSSiz7+tf9jHn1QFW\nBeKN/GJ8Pd0sxn09XSkqsezZFNkggAupObi7OPKfrg0Z8/QjNK1f6in8t6GgcrmcyMhImjdvzpAh\nQ/j9999ZsWIFKSmlrTiSk5OZN28ep0+fZsaMGURGRt71e9iKsLAw/Pz8RJGwb98+SSA+wOj1eqKi\noli4cCEHDx7EZLrl9W/fvj3jx4/n8ccfJywsrNq3kJDL5TRo0IDJkyfz9NNPc+DAARYvXizmWqSl\npfHBBx9w8uRJJk2aRNeuXbGzk1LvH1T27dsnPvfz86txiwIXLlxg3rx5REVFiQVoZDIZ9erV46WX\nXqJfv35ERkZW+/MSIDAwkPHjx9OvXz92797Nt99+y5kzZwDIyspi4cKFREdH8/rrr/Pss8/a2FoJ\nCYk7qfCvzJ49e9iwYQMzZ84s47WR8pUeXDQaLUZBhl6n58jJCwydtIghk//HTzuiiU/JIi0zj7ik\nDFZtOcYHy7ah1Rn46I3B+HiU3+dybdRJOre2nqh+LvEqkQ2DLMbNZsHq8YO7tyAq+lKZMUd7BWMH\ntKdJbRnDI80UXtxN/eBa2NnZoVAo7tkTcrMYwJQpU1i/fj2DBg0S9ymVSjZs2MCgQYPYunXrPb1P\nVeLi4kJ4eLi4fehQOaVhJWo8Go2Gb775hvHjx7N//35RHLq7uzNp0iTWrl3LmDFjqF+/fo24Cb2J\nnZ0dTZs25eWXX2bDhg2MHz9e7LdrMBjYvn07Y8eOZc2aNVIj8AeYAwcOiM8bN25co/IPt27dyqBB\ng1i/fn2Z6qRDhgxh/fr1TJkyhRYtWtSo81KhUFCvXj1eeOEFtm7dyty5c8U0DL1ez6FDh3j99deZ\nPXu2GCIuIVEduRliWhmPmkKFfmkOHz7MsmXLWL58OW5ubri6uoox8devX6d27dr31UiJ+48gCJhM\nJgwGA0ajsbR5tdGIQW/g6Kl43l+ylWvXLUtq387Rc5f5aPl2pj7/JN4e5efiHTx9iS5tLMNKth+O\no18Xy0R7Xy83lCVlG6vKZDICa3mSlVcsjjk62LFyxrOs+Pw9PnzzRT79cCZ5eeWHvv5bZDIZTk5O\ntG7dmk2bNrFw4UK8vb2RyWSYTCZSUlIYOnQoixYtQqfTVftFFGdn5zJtO44dOyZWb5V4cFCr1bz7\n7ru89dZbZGZmIgilCy9hYWEsW7aMTz/9lPr161fLsLWKYm9vT3h4OIsWLWLZsmWEhoYik8kwm82k\npKQwbtw4Pv30U9Rqta1NlahkzGYzJ06cELebN29e7QXizQJLn376KUOGDCElJQWj0YhMJsPb25sl\nS5awfv16WrduXaMLLtnb2xMUFMTMmTOJiooq0x8xNzeXTz75hLfeeovs7Oxqf72UkKhJZGdnEx9v\nvV/4P/GPArGkpIRPP/2UpUuX4u7uDkDHjh3ZtWsXALt27aJLly7/6s0lbI/ZbEal1qAsLqGwRI1S\nrSNXWcKpC5f5afsJ3vniV77fcoJGYYGMG9aNaS/1IaJh+Y3US9Q65q3YwVtjepd7zKHTSTzeNtxi\n3GA0WQ1PbdcslAuXs8qMPfloYw6dSxO3u7Wpz8aPx9C3cyTHjh4tt5Hv/WDixIls2bKF7t27izck\nBoOBWbNm8eGHH5KTk1OtL3rOzs5ERESINx/Xr1+3qJgnUXMRBIHLly8zZswYFi1aJH4X3d3dGTBg\nADt27GD48OEPVOilnZ0dI0aMYOvWrfTt21f0JhqNRmbOnMmrr77KlStXbGylRGWSnJxcJv8wIiKi\nWgvEmznfs2bN4oMPPhALRLm4uNCzZ0927NjBq6++amMrK58uXbqwfv16xowZg6enJ1DqTfzuu++Y\nMmUKSUmWxeokJGyNjJtt3e7xUUX2pqenM3ToUPr3788rr7wClFY2vVmQsCL84x3Bjh07KCwsXuxF\nRAAAIABJREFUZNKkSeKK8/z585k+fTrr1q0jKCiIwYMH//u/QsJmqDVadHo9RkFe+s0VBJJSM1ix\n6Si/7j6NwWhZkdTBXkHfTs15tnc7Pl29i2KV1uKYYpWWw2eS6BBRj5gLqRb7BUFAp7dsvA1YCEQf\nDxeK1XqMplseraZh/nRq1ZCdJy4xdeTjPNGuEc0bBOLp7mqzFdbHHnuMJUuWsHDhQtasWUNJSQlK\npZJFixZRXFzMrFmzqk0VyDuxt7cnNDQUT09PMbQpOjpa7HslUXMRBIG4uDhmzpzJ9u3bxfGQkBDG\njRvHhAkTxJu0B5HIyEjWrFnDwoULWbFiBRkZGQD88ssv6HQ6Zs+eTdOmTWusZ0biFtHR0eJzT09P\nQkNDq/WiR25uLh999BGrV68WC7h4eHjwwgsv8MYbbzzQv7+NGjViwYIFRERE8MUXX5CRkYHZbGbt\n2rUUFBTw8ccf06pVK1ubKSEhIkeGvBLkXWXMURGmTp3KSy+9RN++fenTpw8AEyZMYMKECRWu7vyP\nv57PPvus1QTilStX3qW5EtWJEpWKy+k5xKdkcvhMMtl5Spwd7ant7U79EF86t2rAgdNJFp4vvcHE\n5gPnOXA6iekv92Pe8u0UWRGJu09cZNpLfawKRCj1Firkckz/EMr4nyfbs/FAnLjdrW1D5k8cSIi/\nD2/8pxv29nbVIidDLpcTHh7OrFmzqFevHtOmTcNoNFJUVMTy5cvJzc1lyZIlohe+uuHr64u/v78o\nEM+fP89zzz1nY6sk7gVBELh48SLvvPMO+/btE/MN69evz+zZsxkyZIjoWXuQ8fb25q233iI0NJS5\nc+dy5coVjEYjv//+OyqVis8++4zGjRtLIrGGc/78efF5YGAgtWrVsqE1f09hYSETJkxg69atYriz\no6Mj77//PiNHjsTPz8/GFt5/atWqJfZvnDBhApcuXUIQBKKiolAqlcyfP1+KTpOQ+Jfk5+fTt29f\nAPHaVqdOHQwG684Za1Tf5TWJSsVkMqHV6VFr9eTkFbL3ZALzlu+ioNh6Lk7nVg348LX+fL/lOMnp\nllVqC4s1zF+9m3df7MP0bzZbCEmT2Ux+kQpfT1fylCqL18vlcsxWwi4Vt9UR7tiiPnqjwI2CEoZ0\nb8Govu2JbBRCUG2fansz5+/vz8SJE2ncuDGjRo2iqKgIlUrF2rVrUavV/Pjjj9WyV2KtWrUIDAwk\nMTERgIsXL9rYIol7paCggHHjxpXJKQ0KCmLp0qV069ZNrET9oCOTyXB3d2f06NEEBgby0ksvkZWV\nhU6nIyoqCr1ez8aNG3Fzs6yULFFzuP03KygoqNoKxOLiYkaMGMGuXbvE89LT05Mff/yR3r174+Dg\nYGMLqw5HR0d69uzJTz/9xOuvv05MTAwAJ06c4M0332Tx4sW0a9fOxlZKSNwKEa2MeaoCDw8Pjh8/\nTseOHcWx8+fP39X9p+1dLxL3DUEQKFAWc/RMInOWbuHJ176m1/hFvPzhWs4lZvLG8G706xKBnZXm\nLkfOXWbWkm0M69Ga5vUDrc6vLNESdTyBrm2t9zG6mJJFvWDrF2kHO4WFqHRxcsBgLL1g9ukcwfSX\n+zLoiVYc+HYi304fyZOdWhDs71ttxeFNHBwc6NevHz/99JPYQ85kMrFt2zbefvttsXFwdeKmQLzJ\nlStXpEIeNZjCwkKeffZZjhw5It6E1q9fnx07dtCrV6+HRhzejr29PX369GHz5s3UrVsXKF042717\nNyNHjqSoqMjGFkr8W9RqNVevXhW3q6sHUalUMnXqVPbs2YPZbBaLRP3000/07dv3oRKHN5HL5bRr\n147//e9/dOzYUezJe/LkSebMmcPly5erdQ6/xMOBTAbySnhU1e3rtGnTmDRpEgMHDiQrK4thw4Yx\nYcIEZsyYUeE5JA/iA4ggCOh0Ok6cv8z81Xs4eOayxTHnLpXm4rQKD+aD1/qz5LdDXM0uKHOMyWxm\n/urdzHz5KXIKS7iRX2wxz9HYFN57sTcHT12y2Fei1uHq4mgx7ursiM5gtBgf0qM1GdcLWTt/LO2a\n16NOYM0Ns5HL5fTu3ZtPPvmE6dOnk5qaisFg4Oeff6ZOnTq89tpr1Src1NPTk+DgYBQKBSaTiZKS\nEtLS0mjWrJmtTZO4SzIzM3nvvffYu3cvUOpBa9WqFd9++y0tW7a0sXW2p0OHDqxbt45x48aJYYlb\ntmzhvffeY/bs2Q9FeN+DRmpqqrigpVAoCAwMrFa/rwBFRUV88803rFu3TgzzqlevHvPmzaNXr17V\nIlXClrRr144vv/yS119/ndOnTwOwc+dOAgIC+OSTT6ql4JeQqK60bduWffv2cerUKYqLi6lduzYt\nW7bE0dHynrw8Hu5fpBrGTeGnVqtRqVRo1Gr0er24uiYIAmqNBmVRMcdjk3n3m62cSbj2t3Oeu5TB\nnO/+4IWBnQgL8rX6nl/9vJ8RT1kP8xAEgawcJcG1vSz2uTo7otJYVhMd2rMNG/aeKTNmb6dgaM+2\nLJw2gkE92tdocXgTBwcHBg0axPTp0/H1Lf1sCwoKWLRoERs3bizToNzWKBQKgoODxap/KpVKqmRa\nA8nLy+OLL75g3bp1QKk4bNu2LQsWLKBNmzY2tq760L59ez7++GMiIyPFse+//54lS5ZInsQayOXL\nl1GpSlMZnJ2dCQoKqlbtWoxGI7/++ivffPONmOddq1YtZs2axcCBAx9Kz6E1HnnkERYtWiQWqDGb\nzaxZs4Y5c+ZI/UslbEqlVDCtQg9ily5dWLhwIe7u7jz99NN06NDhrsQhSAKxRmAymUpFYUkJJoMe\nmWBGjgCCGYNeh0pVQnFxCecuprFu91ne/mY7C387Tr06AbwwqBPTXuhNm8Yh5c5vMJr4eNUexg7u\nhLOjZehZkUqLk4M9DvbWL7gxf16hRSPL+RuH+XMls2wfQicHO+oF17IYXzZrDL07tcLb073ah5De\nDc7OzowYMYLPPvtMrKiXmZnJ7Nmzq12eX3BwsFi0RK1WSwKxhqHX69m0aROrV69Gqy0tHFWvXj1m\nzpxJ165dq9UNs61RKBT06NGDGTNmiOGmarWab7/9lp07d1arxRuJfyY9PV30ILq5uRESUv71zhbE\nxsYyd+5csrOzgdI2LJ999hn/+c9/cHJysrF11YvHHnuMxYsXEx5e2grLYDCwfPlyvv76axtbJiFR\nc/juu+9wd3dnzpw5dO/enU8++YTY2Ni7mkMSiNUcvV6PRq1GJpixU8iRy+XIZDLxIZfJSLxygw9W\n7uapKd8z6attrNsbx/4zqew4foklm2L46rcTBAXU4oPx/fD1tF610Ggys2r7SQZ2a2F1//YjF+jX\n2bKJPZQKSA+3sv2mZDIZtX08yCm4FZaqkMt57+W+LP3toDjmYK/gh49eYnDP9tjbP5gRz87OzowZ\nM4Z58+aJY1euXGHEiBFoNBobWlaW0NBQMSxLo9GILQEkagZJSUl8/vnnYi84Jycn3n33XZ5++mnJ\nQ2EFR0dHhg4dyhtvvCF+PpmZmSxYsIDLly3D8iWqL1evXhV/S93c3ETRXx3QaDSMHj2a9PR0cWzu\n3LmMHj1aEofl8MgjjzB//nwxrFSn0/HVV1/dVQ83CYnK5Gabi8p4VAVNmjRhwoQJbNmyhTVr1hAQ\nEMBnn31Gjx49KjyHJBCrMXq9HoNOh51CXsarJggChSUaEtNzOXL+Cn/EXMZoBncr+X5QKv52xSTz\n2dpjTB75BP4+1nMzLl/LIzzU3+q+uORM6odYzwFwcrRHoy0bStqtXTgHTiaK2+6uTrw/vj/f/36M\n63lF+Pt6MH/SMPaveJuhvR/BxfnBvlDK5XLGjRvHiBEjRE9OXFwcEyZMEEOjbE2dOnXESo56vZ7M\nzEwprKeGUFRUxPTp00lISABKPWTjxo1j7NixD31u09+hUCiYMmUKI0aMED+nM2fOMHfu3GpzXkr8\nPTqdjuvXr4t5fW5ubtSpU8fGVpWiUql47bXXxGgRhULB8OHDef3116Xz8m+Qy+U8+eSTTJgwQay6\nmJGRwbx580hOTpaK1khUOTUtxPQmRUVFnD17lrNnz3LlyhXRM18RHkyXzQOAyWRC/5c4vIkgCKRl\nFxKflsOybWc5lZgl7vNxd2JQt0h8PZzYHZ3E6URL749aa+CTnw4zbVQ35i7babVQzNnETFqGhxB7\nyTJ3UVbOyke9IF+uXb9V4MbZ0Z7eHZszbdFGmjUIZOJzPagb4IvBZGTB5GE4OznSoE5t6oX4P1QX\nSXd3d958800uX75MTEwMgiCwceNGOnXqxOjRo23e1Nnf379M0/T8/HwKCgoICAiwoVUS/4TZbGbR\nokVs2bJFHOvTpw/vv/++Da2qOSgUChYsWMDVq1fZt28fAGvXrqVDhw5MnDjRxtZJ/BN5eXnk5d1K\nWfD29q4WhYaMRiPr1q1j8+bNQGlUTbt27Zg6dWq1K6BTHXF2dub555/n3LlzbN5c2krryJEjrFq1\ninfeeUf6DCUk/oZVq1axd+9e4uPjeeyxx3jyySeZN2/eXfU+lgRiNUEQhDJeQp1Oh0J+a1tvMHIw\n9gqTv9lNQYllY/r8Yi3fR8Uhl8kY2KkREQ38Wb3jjMVxOr2Rn3efp3+XCNbvO2exPzYpk44RdawK\nxPJo36wuc78tjW12crBj2azRBNTy4sDKt6kXXJsAP+8HKq/w3yKTyWjRogWTJ09mypQpZGZmUlBQ\nwMqVK+nQoQPNmze3qX1yuZzg4GBxWxKINYPjx4/z6aefiqvqLVu25KOPPioj9iX+Hj8/P+bNm8fz\nzz9PQkICJpOJuXPn8thjj0l92Ko5BQUF5Ofni9shISE2X2wDiI+PZ8WKFWJRmsDAQCZNmkRkZKR0\nPawgdevWZdasWcTFxZGcnIxWq2XVqlX06tWLxx9/3NbmSTxE3GxTURnzVAXnzp1jxIgRdOvWTSw+\neLc8PO6baoYgCGg1GlRFSkqUBaiLCilRFqAqUqJRqzCbTOJFxGg0sTMmmRfnb7MqDm/HLAhsOnKJ\nlOwSRvdpbfWYS+l5NKlv/aa/RK3D3cUy3NPb3QWV1jLcsI6/N1eySnOeWjWuw++LJjDsyY483iGC\nx1o3IbAaN7W3BXZ2dvTv35+hQ4eKoaYxMTGsX7++WoS0hYSEiP9fBQUF4s2NRPVEqVTy4YcfipU3\nvby8ePPNN6X2JP+C1q1bM3HiRDGkLS8vj3nz5kn9QKs5hYWFFBSURrDIZLJqEV6qUqnYsGEDp06d\nAkq91IMGDWLAgAEPZQ/Se6Fly5YsXLhQjDbKyMhg/vz5NrZKQqJ689VXX+Hv78/y5cuZM2cO33zz\nDXFxcXc1x0MhEAVBwGg0ig9bxq8LgoBGrUJVVAjaYuzNOhwEA/aCofRfsw6zTo3sr2NzCtUci88g\nKaOQicM6MGFIexoFe//j+xyPz0BnhDaNg6zu/zM1h4gGgRbjLs4OVoXgsJ6t2bzfsgLSK0M64eHi\nzM7Fk9j6zSS6dYiQqiX+Ay4uLsyePVtMwNfr9SxdupTExMR/eOX9JywsTHyuVCqlkv/VGEEQ+PHH\nHzl+/DhQenPct29f+vTpUy08KDWNm21pnnrqKXHswIEDrF27Vsp5qsYUFRWhVCoBxMbztiYhIYEl\nS5ag15fm5gcGBjJ37lxx8UGi4tz8Xfu///s/cWznzp1899130nl5l1Sne+GaiKwSHlXF8uXLeeut\ntygpKcHPzw+lUsmECRP45ZdfKjzHQ3EXcfXqVUaPHg2UhtEtWLCADh06VLkdgiCgVpUgN2hwuOPb\nYhZA+GvAiIz07ELi0vL5dkcciddueXGcHBQ81TaUod2bc+piBntOp5b7fpuPJDF5WDvOJGZa7IuO\nv0aP1nW5cDmrzHjjUD9SM3LLjMlkMgJqeZCVW1YszB7Xl2G92hHs74uDg7Qqejf4+voyb948Xn/9\ndbRaLdnZ2SxcuJCVK1faVGCHhoYik8lKCyEVFoo3XhLVj6SkJH777Tfx/6hu3bqMGDFCaih9DwQG\nBjJy5Eiio6PJyMigoKCAtWvX0q1bN+rXr29r8ySsoFQqywjE0NBQm9pjMplYsGABOTk5QGk14fnz\n54u9cCX+HW+//TZHjhwhKSkJgGnTptGzZ0/q1atnY8tqDqdOnWLGjBliG58VK1bY/HypKcj/6hpQ\nGfNUBZs3b2bTpk1lUk3Gjx/PmDFjeO655yo0x0PhQSwqKuLw4cMcPnyYI0eOiOEoVY1GpUJh0KD4\n6/shCKDUmjmdrmLJgQwmr03gldXxzN6QSFRsNomZSorVhjJzaPUmNh9P5YtNcZjkDkwY2qHcqkhm\nQaCwRIefl2VSarFah6ebZSjpY5FhnIhLKzM29IlW7DmRIG67uzjyzbv/YfyzPahXJ0ASh/+S//u/\n/6N///7i9vr16zlzxjJvtCpp0KCBGGKqUqkoKCjAbDbb1CYJS/R6PXv37uX06dNA6Y3xwIED6dmz\np40tq/n07duX/v37i+dBdHQ0+/btE6tkSlQfTCYT+fn5YhiwTCajYcOGNrXp5MmTYmEagGHDhjFi\nxAgbWvRgEBYWxquvvipW2s7Pz2fx4sVSz9K7IC8vj71794oPKULowcVoNFrUIfDx8bmr8+WhEIjV\nAYPBgGDUiQmqOqPA0ZQSJvx4kTFLz7F4Txp7L+RyIimf7Wdv8O3+a/x+Xkmvjk14rX9Lq6sOR+Oz\n2R+XzRuD25f7vpuOJjGgS1OLcScHO9Tasjc8IbW9ylQjBejUqj5e7s4cj0ulaVht5rzYje0LX+XF\nwY/j5VHxakgSligUCiZNmiQWgVGr1cyaNcumF7y6deuKOTKCIJCVlSW1uqiG5Obm8ttvv1FSUgJA\n7dq1mThxIo6O1lvdSFQcJycn/vvf/+Ll5QWULjBu2LChTKVMieqBTqcjMzNTDJVzdHQkJCTEZvaY\nTCbee+89MbQ0ODhYqoRbSTg5OdG/f3+xaJQgCERFRXHhwgUbWybxMFDT2lw0adKE2bNnk5iYSHZ2\nNgkJCbz//vs0bWqpB8pDEoiViNlsxmAwlPYvNBhEz4sgCCiLSki6ruLkVTXH0lTsSypie+x1Llwr\nfwWnRGtkw8lsDqeoePOZdla/WJcylMRfK+KJ1mFW58gv0lgtOhMa4EVGTtkCJC8O6MCGvWeB0qb2\nrwzpzORnO+JlzmZSnzpEuGTgZsqlXYvGD1V7ivtJs2bNyngR9+7dy549e2xmj7OzM7Vr1xa3c3Jy\nxJsdierDzWiIm7z22mtSCGQlEh4eziuvvCJu79u3j+joaBtaJGENvV5Pbu6tlIiAgAAcHBxsZs+u\nXbs4dOiQuD1s2DCaNGliM3seNOrXr0+fPn3EUv3Jycls3bpVinKRkLiD999/H0EQGDduHL179+a1\n115DJpMxZ86cCs/xUOQg3k8EQcBgMKDT6//KI4TS5EIBBIH8Yi2Xb6jYEJ3BkUv53J4SXNfXiecf\nD8UsCGw4kUG+ynoIU2qOhl3xMl7uE8l3OyyrEB3+M5vJgyLZdzbN6uutCcue7erz+Q97xe3Jzz3O\nxr1ncHSw46PnB9ClTSOcZDrGvvwSMTExALRo0YL5H38gicNKxMvLi0GDBrF161ays7MxGAwsWbKE\nHj162KzQSGBgIFevXgVKPVVSaF31wmQy8cUXX4j/L8HBwUybNk2qFlyJyOVyZs2axcqVK8VFkq++\n+or+/ftLv3/ViDsFYmCgZeG1qsJoNLJs2TIxAiQkJIS+fftK/foqEYVCwbBhw1i9ejXx8fFotVp2\n7drF0KFD78ozIiFxt8ipHI9aVV09PD09mTt37j3NIV3p7gGz2UxxiQq1To8JOcgVyOQKZHI5yOSk\nXC/mvz+cZ9IPcRy+QxwCXM3T8v3hdH6NyeKF7mGE+ZVf4Szlhhq5gxPebtZDyNJzVIQFVKzvmYer\nIyq1FoPRRJCfJytmPsewnm1YMef/OLxyKpPHPEXb5vU5e+Z0mbK4zz33HEFB1quiSvx7WrduTZcu\nXcQbz/Pnz9vUW3F7iFZ+fr4kEKsZx44dExdt5HI5r732mlQ6/z7g4uLC2LFjReF98OBBzp2z7B0r\nYTuMRmOZmgK2bHFx/PhxYmNLK33L5XK6du1Kq1atbGbPg0r9+vUZMmSIuB0bG8u5c+ekXESJ+4oM\nGTJZJTyqqJZpWloaEyZMoHPnzrRo0YIuXbowefJkrl2reI9zSSD+S8xmMyUqFWaZvFQU/nUTIQgC\n+UVqzqbkcDw5nx4Rfox7IpR29bzK/Vpo9Cb+tyeVwR2CqO1Zfg5R1PlcBj5mPQF/x6mr9HmkkcV4\nm0b+/JmSXWbs+T6tyVeqWDvv/9iz+A3+89QjtG5Wj8jwUMJC/JHL5RQVFfHHH3+g0WiA0hyn28tM\nS1QegYGBPPXUU2LO0/Xr1zl48KDNLni332RJArH6sXDhQvF5vXr1GDRokA2t+Xs0Gg1xcXEcOXKk\nTA5ffn4+J06cICkpCaPRaEML/55nnnlGPB8EQeDrr7+2sUUSt2MwGMoIRFstYBqNRg4cOMD169eB\n0mIQffr0KROuL1F5vPTSS+L1sri4mL1794r52BISEjBlyhTq16/P8uXL2blzJ8uWLaNu3bpMnjy5\nwnNIIab/AkEQ/hKHt4Sh2WwmPbeEhKxifo7JIKvoVt6WDGhVx503nqxPRr6GzaeyMN/hTjQL8N3+\nK4ztFsqXO5Ktvm9eiR4/H39kstIKqLej1hlxsLdsj/BE61A+/fGAuD12QHue7dmSID8vfLw8yg1L\ny8nJYffu3eL20KFDbRq+86DTu3dvFi5cKFbki46OJisryyYFF24XiIWFhZJArEZcvny5TI5qjx49\nqt15qdVqOX36NNu2bePcuXNkZ2eTl5dHdvatharLly/z3nvv4efnR3BwMO3bt6dfv35ERFSvPqp1\n6tShe/furF69GoBt27aRkZFBcHCwjS2TAEuBWLduXZvYkZGRwYkTJ8QF1dDQUHr16mUTWx4GwsLC\nGDhwoHhe7tq1i+nTp1tUbZSQqCxkMsQik/c6T1VQXFxcRgwGBwfTtGlToqKiKjyH5EH8F+j1esx/\nfXRmk4kilZYLV/P5el8KX+5NLSMOoTQv8Wx6Md9HZ5KQq2Hik/VxtLP86PUmgSt56r8NNb1RbCg3\nzPTOL56vhzP5ShUms4Cjgx2zX3yCKc91JaJRXXy9Pf82Z2nr1q1iHye5XM6UKVPKPVbi3gkKCqJz\n587i9tmzZ0lMTLSJLbeL0oKCAkkgViM2bdokrpS7u7vTpUsXcSW9OnD8+HGGDBlC//79+fzzz4mK\niuLcuXOkp6eX+R7p9XrS0tLElgBz586lZ8+ejBw5kosXL9rwLyiLt7c33bp1ExucFxYW8vvvv9vY\nKombGI3GMr1abRVimpCQUKZF0eOPPy55D+8zU6dOFdMyMjIy+OOPP2xskcSDTE2rYtqyZUvOnz9f\nZiw+Pp42bdpUeA7Jg1gOgiCg1+swajUgmEtddjIZyOXozTKyivQk56rZcykXpdaEXAbe7g680DkE\npdrInvhcCjWWoVNXC7Rsisvh1Z5hfL0rxcKTuOfPXIY/EsSyvWlW7SrRmnB3diC/+O9bDyjkMl7t\n34rNBy/w5X+fpl3TEJqEBVaoZ6HZbObnn38Wtx999FGpGe19Ri6X88wzz7B06VLMZjPXrl3j7Nmz\ndOnSpcqr8t1eDbOoqEgSiNUErVbLH3/8IYYeN2nShIiICJsXpzGZTGRmZjJr1izWrFljUVFQLpdj\nZ2eH0WgU98nlchQKBUajEUEQ0Ol06HQ61q1bx4YNG3jxxReZMWMGQUFBNvUoyuVyIiIiaNy4MWfP\nnsVoNBIVFcXYsWOlvM9qgF6vL9PLzRYCUafTcfr0adFDfvO33Nbn5YOEIAji42YuV5MmTWjdujUF\nBQX8d/QoGiKQsWc3MpkMhZsbLqFhuPn7I5PJMOh0FKemoruRjaA3IFMoUHh44hYWhpO3N1plIaq0\nVIxFRQhGE3IHBxz8/HCpUxdNVib669mY9XpkcjkKD08Unh6Y8vMwa7UglyFzcQWDHhkCgp09gtGA\nzNkFudkIRj0yuQyZgxP2tQJwreUvFbqSuG+88MILyGQyjEYjI0aMICwsDG9vb5RKJampqXTs2LHC\nc0kC8Q4EQUCnUWPSaVEY1dgLJjF3UADSNQr+SFHx+4UctMayN0KpwJmMEjyd7Hi6lT+Z+Rr2JeZb\nvEeeysCeS/kMaBvI5lNZZfZpDWbsFOX/eDjZy9HoLYVnRKgPiVdKq7nZK+R88XpPWjUKZHiv1gT6\ned3VxSojI0NMtgcYPny49INWBXTp0oXw8HASEhIQBIFjx47xwgsv4OvrW6V23B4+ZzKZKCws/Juj\nJaqK+Ph40tPTgdJqfq1atbJ5CX21Ws2BAweYM2cOJ0+eLLPPz8+PRo0aER4ejouLC1u2bBET5G/m\n3arVaq5cuUJSUpIYsXCzGmRcXByzZ8+mS5cuogfPFjRr1oyWLVsSGxuL2WwmJSWFhIQEIiMjbWaT\nRCmFhYVlcrVtIRCVSmWZ1hYRERE8+uijVW7Hg4YgCBi0GopSUlBduoQ+OxtBr8fO2wuXhuE41a3L\nstmz0Jw5g130ccxaLVdve719QCD+z7+A3MmJkuholPt2I9ye7yyTU2vESOx8fFDujkKbdEnc5dig\nIe6PdiJ3xzaKD+9H0OlQeHji2acf6HWoog9j1mrw7N0PmVyGNiEOl8g2yFycsa/lhxwzwsXzmK4k\ngPnW91Pv4YMushOKwFDc69bHzk5aZKop1JQqpgMGDBCfDx482GL/3WgBSSDehiAIaEqKkWuLcBBK\nf0gEoNCo4JoarqtN5Kl1uDraMapdIDnFOvYmFVCiL1tMRKk1suFCDh1C3OkbUYsdF3It3utKvpbu\njXys2qE3mVHIZZjudC8CtdzsKSix9B4+0TKIRb+doP9jjXipX2s6Rtb7120Sdu7cKV6WjGeUAAAg\nAElEQVR0vby8aN++/b+aR+LuUCgUDBw4kISEBKA0zFSlUlW5QPTx8UEmk4nNp28P4ZKwHX/++adY\n0t/V1ZWWLVvi5GTZ47Sq0Gg0/PLLL8yfP5/k5Ft50wEBAfTt25cePXrQvn176tWrx59//snx48dF\ngVi7dm0mTJhA06ZNxVDTnTt3EhUVJRazOXHiBJMmTWLGjBkMGzYMR8fyC3jdT1xcXGjRogUuLi6U\nlJSQm5tLfHy8JBCrAfn5txZgZTIZPj7Wr6n3k+Li4jKhXEOHDq1yG2o6giBgNptFD6HZZCQ/9jy5\n27dSdOQw3BGV4NKiBc6Nm6Jb/ytyQcBaF0Tnxo0pORVD0f59FvtkdnbUGjka5b7dGDIzyuxzbdsO\nh4BA8n9ZI47Z+wfg+VRflJvXIeh1KLy88Rk2gpKojchd3XDr9iTGK0k4d+iMkBCDOfuK1b9TVpSP\n6ehWTAo7lI8Pxr15Oxycbbf4JfHgYU0U3s5///vfChe2kwTibaiKizCoSzADCuxQmSCp0MiuywVc\nK7JsFu7lpGBIy9qYTALrzl3HeIegi7lWTNd6XrSt68Hpq0UWr/8zq4RWdT04d8c+k1nAzopAtFfI\nkJkNGO7wXHq5OdK0rg9bPxlO07AAXJwd7ym8Zfv27eLzJk2a4OfnJ4XLVBHPPPMM8+fPByA9PZ3k\n5OQqL7zg6OiIk5OTWHDh9pswCdtgMplISEgQC3J4eHjcVS7B/WDLli3MnDmTrKxbURCdO3dm+vTp\ntG/fHm9v73+MPHBwcCA8PJyGDRvSq1cvBg8ezEcffcTZs2cRBIGEhATee+89XF1dbVqttU2bNnh4\neFBSUkJ+fj6JiYmYzWYpssLG3B7d4OTkZJOw34SEBLF6KUgC8W4wGgwUpaaiupSI6mI8RqUSx5C6\n2Pn6kP3tEgthCODUoAFODRqS99u6cud1a98BGVgVh8hk+D43koIdWzHl55XZ5dSkGfZ+tVHu3CaO\nKTw88XyqL4XrfwSzGZmzM15PD6Z4y1rkzi64Pd4b/cUzuHZ9EuHsflDe5hCQycHeAQz60lSlm5iM\nGPf9RrHRgEfrztjbaPFLouLcDG2ujHmqgoSEBBYsWEB6erqY2qHRaO6qL+tDLxAFQaBYrSWzUEXC\nDRWpSh16k4C9XIa/qx1uDnIC3B3ILtFzhy6jUGtif1oRXo4KXukYzIroDHTGsqLuUGoho1r7WxWI\np9OLGN7a30IgOtrJ0d35ZkD3Zr5ExaSWGVPIZXw5rgu92jeqlFwdrVbLsWPHxO2IiAi8vb3veV6J\nitGyZUtq167NjRs3MJlM/PHH/7N33uFxVXfe/9w2vaiMinvvBQzGgME2GBswEAIY4phAioEkQLIh\nmyUkZLPLS9jsbsi+8CYLJEBCEjA1FNOCTcdgG9yNjW3cZVlWl0bT55bz/jHSaEbFlkHWyDDf55nn\nmXvvueceje4993x/5ftbwdy5c/t8HG63O00Q8yGmuUdtbS07d+5Me/YDgQDTpk3L2Xg2b97MkiVL\niEaj6X1XXnklf/rTn/B6vcf8EpRlmdLSUi6//HLmz5/PN77xDV5+ObVIq6io4Jvf/CZr1qxh4sSJ\nvfp39BTTp0+nsLCQqqoqdF1nx44dNDQ0UFJSkpPx5JFCZnSDz+fLyRhWrFiRXoANHjw4X7C9BxBC\n0LhjBw2vr6Dx1ZcRyZQBXi0qwjF6DNV/uL+zVHsrfLPmUPuXP3fbt2Sz4Rw/nobHH+vyuOe0GUQ2\nrO1EDpFkvKfNoGHpX7N2+y+6hOALT6XJqu/8iwkvfx4MHffcC4m+/RK+q76N2LUhRQ5tDpQJ01FK\nypFVDRAIWUVIMlYkgrlrM6KmAowkxsplhAsCFIybmjfC93PIvaRi2ht99AS/+MUvmDt3Lt/97ne5\n/fbbueuuu3j++ef59re/3eM+vnQE0el0Ul4SIBpsxLJMKkIWbx1owTRhTLGDCQEnkAot3dMYZ2td\nnBKXwqIppazY1URdtLNgR3PC5J39LXzntIE8uOZQJ+GZg8EEw4ud7G+IZe23BJ3aAti6yEF0aDLj\ny5w892a7pLdNlfn9Tecw95RRvSbk8OGHH6aJgaZpTJ06tV+pJH7RIcsyZ511Fs8//zyQKs6dC3g8\nnnQ4Y6YIRB65weHDh9mzZ096+9RTT81ZeGlFRQVXXnllmhw6nU5uuOEG7r333s+9yJFlGZ/Px7Jl\ny/je977HY489RjweJxQKsXDhQt58882c1Lpzu91MnjyZbdu2AbB7924OHz6cJ4g5RiZB9Hg8ORnD\nypUr09/POOOM/EK/CwghSITDxGprsXSdRHMTlb/5L8wOxseCeedT//ST3ZJD5/gJRLdtPeK1fGed\nTcu773R73DF2LA1PdCaP7pOnEV73UdY+2eOFRAyRTKX1SDY7siwjohFkXwFEQtjGTELSE4jq/ain\nnYcSKENxupA0DVQ7QnMgS1JKwRIQI8ZgGCbGoX3oG95F3/IB+rAx+VDTPHoV4XCYm2++GUhFhc2c\nOZNp06Zx/fXXs3Tp0h718aWJjxk2bBgP3ff/WPnKs4x3xlAObWV3XYQtNVEmlrgYUuhgT4vOzmDq\nsyuoU+6zM3+Un8E+O+8fDDN3VCGl7q5DWEJJk231MWYM6WzFXH0gyOyxXXvhOr5Lpg3zsXZPU9Y+\nmypz49wh/PGlTQBoqszXzxnLk7dfxMUzx/VImbSn2LJlS1q1MhAIMHTo0HwYVR9CkqQsgYNt27YR\nj8f7fByZYQh5gph7NDQ0cOhQe67MzJkzczKOcDjMb37zG/btS0Uy2O12Fi9ezC9+8YteXRjLssyd\nd97J5Zdfnlbx3b17N3fffXeW17IvkfmbV1ZWpnMl88gdMmsgHkvoVG8hGo2mc8YBzjrrrD4fQ3+G\nEIKWykoOv/cun97x72xf8h2a135E5X/9ZydyKNntIIE4wvvOM3064fXrjnhN++Ah6IcquzymDRxE\n8nBVl8ecEyaR2JldYsc7aw6R1e0GAPfpM4ltXA2Aa8ZZJDZ/iG3sZGisRjvncmzDx2D3erApApx+\nFJsDuyzQJAsZgSkpGIoNYXchj5iI/StLUMdNI1rT9Xjz6D+QevHTF7DZbGzcuBFIOXsOHz6Mw+HI\nqkd8NHwpPIguh43XnnyE0V6QhIUwE+xyjKTJUElKBociBiP8NsrdWvq/JwEtSZMdTQkcisT8kX7e\n2d/CvNGF/H1rHUmzs4Vrf3OCC0YWsKZDyGiqbXe3Rfb+GSML+d/l7Z6CgYUObrlwBLsP1nPtvPEM\nKfEyaXiAcUNLcNh7v/xBxzC28vLyXr9GHkfGlClTkGUZy7IIhULs3r2byZMn9+kYMgsO50NMcwvL\nsqipqcnKBc1VeOmqVat49dVX03PE9OnTueWWW46LJ628vJyf/vSn7Nu3jzVr1mAYBi+//DKXXnop\n5557bq9f72g49dRT09/r6+tpbGxMi2rkkRuEQqH091x4ELdt25aOuFEUhalTp/b5GPorDMOgbu1a\nDt79G4xWY4pz4kQiH2/BbOksfOY76+yUIM0RIEyzy7zENqhFxeh1Nd0e95w2g+AbnQuFSzYbVjTS\nuT+fFzPYboRQS0tJbvggdY7TBYqC4nKieoailQ3EqbdgKjZ0TwmalFojGijoig0LBRMJXUiYkPIO\n2O2oQyagmgaxeByH/bPpRySTSRoaGjAMg+Li4pyqPufRP3DLLbfw/e9/n5UrV3LZZZexcOFCiouL\nGT58eI/7+MITxGQ8RqmSxOWxUnGjQNhWSLOw05gwGFfkIKoLEBKa2v5gCkAgcXKpC9MS7GyMc84I\nH+sOhZk+yMuqLnIKAZoTBgN9Nqo6iNp09cwPK3JQ2dBuDb9gSgkb9zUjSxLnTi7hqjMGM3agn4EB\nHzC2tZ/eSZTtDpWVlXmCmGOUlZVRVFSUDvHcvHlznxNEp9OZ/p65CMuj76HrOgcOHEg/l5qm5SQX\nr6WlhRdffJGKipSYvN/vZ8mSJUycOPG4zEmSJDFlyhSuvfZatm3bRigUYv/+/bz66qvMmDEDt9vd\n69c8Ek466aS04UbXdQ4ePIhhGPl6iDlEZnRDLjyImeWgSkpKKC4uzhsMSBm1aj94n/133gkZpSU8\n06dT/0TX4W1aSQnBt97stk/JZkvVHTwCFJ8Po7l71W3ZZuvSQ6l4PF2SVtGBjEoZOUGSsJA9PlBU\n1IEDcSWbsCQZ3R1Ik8OE4sCU7ZiWRVxIWMhICBRhIUitSS0hSEoKejiGEonhcTlxOnpGFLdt28ZD\nDz3EqlWrCIVCWJaFw+HgpJNO4uqrr2b+/Pk5rSP7RYLUSzmIfTU9nHfeeaxatQpFUViyZAnTpk2j\noaGB2bNn97iPLzRBtCwLvakaV7Q2a3+tvYxgxGKAW0ORJLx2mdqoQSxj3nAoMNyrAhIJS3BKmRtT\nCOaPKiCSNPjwYAtdOBH5pC7GKYN9VH2SXdqiq4j6WSML+fM7KTnkRWcM4qunDEDTVGyqTHmRG3cP\nJ4neQnNzc1bITlFREaWlpX12/TxSi2Kn00kgEEgTxO3btx/lrN5HJkFsCznOIzfQdT1dHgJg+PDh\nfV7yQQjBnj17WLlyZZqoTp06lW9+85vHdQGiKArXXXcdf/nLX1i7di2GYfDGG29wzTXXcNJJJx23\n63YFj8fDoEGD0rUo9+/fTzKZzBPEHCKZbDfE5uL/8Mknn6S/l5eXZ82bX2Y0bNnCgbvuyiKHSkEB\nZih0RA/gUdFNbmKHRp+h48+4zpIktNJy7EYYSVgkXdnk0FLsGKZFTMhIgCoMTAFhEzQJZARRA2Jm\nSo9CAmyxGEWOOB67htft7JTiI4QgmUzy0EMP8e///u9dqoxv2bKFp59+mu985zvccccdlJaW5g0X\nnxOS1DsKpH35b8h8N3+WqKMvNEFMRFqwNVVk7TNUB2FLptAOmqJwIGxkCcUoEgz1qiRNwadBA72L\nucyjSnx3xiC2VodZeSDb6hTRTTy27AWTLIHSYQJy2RSSuslJQ31cPXMIp44qodjftxbxjqirqyMc\nDgOpHKCioqL8Cy8HcDgclJSUpHNb2vK9+hKZNTSNzOLCefQ5dF3PKiUxcuTIPh+DEIJdu3axc+fO\n9L4bbrjhM9daPRbY7XaWLFnC2rVrgZR89969e9Oh2H2JESNGpAliVVVV/tnIMTJ//764Fzti//79\n6e9FRUU5q9XZXyCEIFxbS92rr6aVSdvgGDGC2I7PbuwUySTyUdYjZksLytix3R63kkkkuwORyPYi\nmpEwSlcquFIHciZlRplJYJoomooaTyCQEIodCUFCtiNUO4aRIocIgYJFyJBACJyyoCkJyQ7rSwHE\nLaiKCuRokpK4Tok35VFsQyQS4d577+W///u/0+u19HAz6hcnEgkefPBBGhoa+J//+R+GDBlypJ8u\njzw64QtLEIUQiGgI2cp+gbc4AqjICEViXyj7mCbDcK/Gnha9S2LYhrABYUMwtNjNV5wKL+1ot+Ao\nkoTVwcp12mAfa/a2e+ZkCX48dxiDC5xcN3cMfo+zX1h3mpub04IoqqrmpOhwHimCGAgE0tuZNbb6\nCpmLrWSycw3QPPoOpmlmCaL0dV1MSC021qxZQyKRUvMrLCzk4osv7rPrX3nllfzsZz8jGAwSj8dZ\ns2YNCxYs6HMl10GDBqW/19fXp72peeQGuSaImXNzIBDImbJwriGEoHnvXsI7dpBsbCT45hud2ihu\nD0ZDfRdnt3WSKmAvjmB0kRQVZLlbL6TR2ICtrPu0mMj6dXhOP5PQe29nXzqRSCmWdoAViyF7vFjh\nVJqFGQwiFxRhNTeCZaEOG41qxpGAhN2PKqVIniWrWIIUOQRULFoMCRmwy4La+JH9nHZZoMkQ0y1q\nghGKDAOvO5VXuG7DRgoCpfz67v8hEY+z/qMPaWpsYOzYsWiaxv79+1m5ciV1dXVYlsWzzz5LeXk5\n99xzzxGumMfR0JdlLqLRKLfddhvBYBBd17n55ps5++yzP//FjxFfCIJoGAbJlkZEPIKwLCRJwlLt\naC2d1XpCihcZif3N2ZOQTIoc7grqXYaOQsr9X+yQ8dkkzNb5KeB0c+ssFy0Jk5ghUBUJBYmRATeK\nlFI3LffaqWyMMXeCyetba/nWzKHMmlCO3db7IjOfB5FIJE0GFEXJEirJo++gaVpWTa+6urqcjKEN\neYKYW5immSUUVFZW1udjSCQSbNiwIb09c+bMPjUgBQIBzjjjDJYvXw7Apk2bSCaTfb4gz/ztW1pa\n8gQxx8gkiLnw3rWlAUAqJ9fWz97pfQHTNKlbv579d/wfzGiUkkVXdUnyrGQC6Qi/T2jtR3jPmEnL\n++912ya8YR2eU04lvG5tt20SVYfQBg5CrzrU6Viy8iC+c7oWuIrt3IF99FgSuz9tH9PKd/GdfTah\nN/8BQGT1Snzzzif65ivE1q+h8BtLsJkpkSJLtaNJAl3SQFYxTQuBgiYMWowUK3BIVrfk0CULXKrA\nFNAQN6nVU98VCfxRg7JogoQpkAeOZfyA8enzZn5lEaVOiUK3E7/bSV1dHRs3buSXv/wlGzZswLIs\n/vznP3P55Zd3+5vlcXT0lgJpT/p4/vnnGTlyJD/+8Y+pra3lW9/6Fv/4xz964erHhhO6foGeTBCu\nOUhi9wbkrW+hfroKbfca1F2rkWr3ohixTucIRaEm2vmlXuZSqAgb3ZLDgS6Z4V6FSNJkW0OSHU1J\nggkTS8CBsMmnLSYHoxb1cYFdk/G4bDSYMiFUdoVMYpoNye3kuvNGMXqAl6TRPgYhRNYnV4hGo+l8\nM0VRclZX6ssOTdNyXmYi0xqfz0HMLYQQWaUdiouL+3wMhmGwd+/e9HYurJmZJQR27dqVk/syMyc7\nEomkC6TnkRtk3gO5IGcdRXK+bPmoQgjq1q1n789+jtnSgur1YjR1rXqt19WhDRjQbV+JfXuxjxxx\nxOvFPvkE1+QpR2zTsvI9fLPndHs8vmc39jGdw1Aj69finnFG1j6zuQnZ64fW96EVjSCpdtA0jJoq\nZKcbSbTOAa1RYKasgSSRFBKQInkCCRVBSO9MDl2KoEiz0GSLfSGDXUGDxoTAsKDQJjHYo+DWZHYH\nTQ6ELZIie9ketWT2RyQ+rotT1RSmOBBgwYIF3H333WmRwUgkwkMPPXTE3y2P/oOioqK0HkgwGPxM\nxth33nmH2267jQsuuIDp06czffp0zj//fH7605/y5pvdi0Fl4oT1ICYiYYyqXaiHPumakcsKiOwF\nhEBCFzLNyc4E0alKRCNdk7MRXpXqiE5jon0xMNyrEjUFWxsT6X2lToUiu8LOJr3TJCBLMNCt4FQl\nqloS1IQTeLUQqiwRM0U6pNWhyhQ6NYq9Luya2qehp7qupy2ysix/6fMpcgVZlrMWGrmo+5Z5/Xye\nVW7RJkrQhlwYbkzTzBKwGjduXJ+PYdKkSenvdXV1OfHeZSqnJhKJnBr08shtiKkQIl3iAlJz5pet\nZnDz7j3s/z93pPMNJZsNK5nosm1i3z78c+YQXvVBt/3F9+zBNWky0W1bu23T8v5Kii79Ko0vLuvy\nuEgmie3ejWfmWV1eK7xmNSXXfgu9rhYrs4STZRHdshnvufMIvd0eIht8/TX8X/0awWcfT13/zeX4\nL76S8ItPoldVIoYWt65BU3OBaE0zMpFQhEXUTB3VJEFThynLpwqSpklCSBwIpw5KQLkrJWqTtARR\nQ9DY9U+aBUPAp806hhVmSLGXk046iQULFvDII48A8Oyzz6Y9inkcO2Qk5F5Yj8s98CEuWLCA559/\nnvPPP59QKMSDDz7Y4/737NnDrbfeiqZpzJs3L13eAqCxsZHNmzfz0EMP8fvf/567776bMWPGHGGs\nJyCSsShG5fbuySEgmTpI2WIxlmInond+ofs0meZE1w/NMI9CZTibHA72KIQNi8OR9pdTsUPBb5PZ\nFexMDkf4VEb7NBpiJh/XJ6iJGkjAnmCS9w5FWVsdY1Nt6rOmKsJre5p5b08d+2qbiSeTmKaJaZrH\n/cE2TTNrwfNle9n1FyiKkmUNz0WIZ6ZxIB9Gl1sIIbIWwrnwUnRcDOciPzkz5D0ej+eEnGU+l7qu\n5wlijpFLgtjRcKYoSr/QEugrWJZFcOvHmC3tZZDMSATF1b3YXvLQIbQBA7s9HvrgfVxTp2IbNLjb\nNvHdu0hUHKDo8iu6bRP+cA2SquGdc07ng0JQ/8TjFF16BWqHMl7RLZswIxG8552f3mfU1xNa+R7+\nKxaDomAGmwi9/QaerywitnUTppy67yTTwGpbkQpBqvp1iihKiE66Fh5VEDEsbEo7OZQlGOJRqI2Z\nVMdMHIrcI3KYib0tBjXNYfx+f5YhL5lMsnPnzvycdQLgxRdfpLy8nBUrVvDII49w55139vjcW265\nhdtuu42nnnqKG264gRkzZjBq1ChGjRrFaaedxvXXX8+TTz7Jv/7rv3Lrrbcesa8TzoMohCBZX4V2\n+NMjtpMjTeglQ7Cb7U+XUBTiRueHo8ghs7els5fErULUsGjJkJpSZXCqMgdC7Yt2GRjoVvmksfNC\nfnyhxsGQniag5W4Vjyazpf7IT71uCRqiSZriOoYFIOFQJYrsCooipeshqrJMgdtxXF6O+YkkN+gY\napwLop63MvZf9Ifnsj+MIRfIJADHuyZtHkdH5n3Y13NWx//9l+VesCyL4N79hA8dou7Jp7KPhcOo\nRzAeBVeupOTqb1D31z9326b+qScJLPo60a1biX68pcs2kU2bMIItlH57CXpDPc0rliMS2WuqyNaP\nKV9yPf5Zcwit+oDgu29Dq7FT6Enq/voIxYu/geb30/TaKyQP7AcgvGYVjvETKVp8LcmDFYRXf0Dy\nwH6CkQj+ry7CbKwn8uH7BF97Gd/5l5CQXWhmAlu8mbitrUC9RCrANAVFgszANZlUiQsZqIm237dD\n3DIHwin1/KEehbrEZ5tnD4Z0/M5k/j3em5B6qURFD/rYsGEDs2bNAmD8+PFUV1cjhOjRHPP000/3\nqPrA9OnTeeKJJ47Y5oQjiMlYBPnwzqO2kxMRdElrteK0QohOCqPpQ13sK3Wq7GjKnnQGu1UOhLJD\nVwd6VA6GOufDjCnQONCipwlmoV3Bq8nsau7eI1TsUBjqs1EfN9kXSs0oqgSDPCqmJdjRaNCSYYqS\nJRjli1HkVHHaVJw2DbtN+0y1yVRVTZMRIUTec5QjtBXibkMuQn0zr/9ly6vpb5AkKet/ED9Ksejj\nNQaXy0UolPIWVFd3FgA73shUjHS73TkxnGR6UfMFqHOPXJbjyXxfQucInC8i9FicqrffY9cvf82g\nb32N5KHOQjB6fT1qIIBR31mxVMTjhD54n6LLrqDxhee6vohlUf/E43jPOJOSa79F4mAFoVUfZJXN\ncI4bT8nCK3GPHo1rwEA2jBlHw6c7UYVAUVUGjxnD4JOn4S4vR5Ik9NPPIHTZ5SRrarD0JJKioHp9\nuIePwFlcTGDWHCL792G0BBGmiazZsJWW4vrqFcQWXkWyujpVIkOWkcdPomDehZhNjVjxGLouEJKM\nLEwk00BSLSQ5RQDbIEFWOTWPKmhICAptEGl1WpQ4JKqiFrqVaq/KnRXxe4qIAU3hKB9//HH7NT0e\nzjzzTN54440v/H16PCAJgdQLv1tP+hg2bBibNm1i/vz5HDp0CJfL1WMD1NHI4VNPPcWiRYt61Lbf\nE8RMb4okSegtjWjRrpOgO0JqqcN0OVH11EtdtgzsPVzrKhKYwsp6qCHlPYx18EIW2BUOR7LJlEeV\niOrZ3sfBXpWPj+A5HOBWKXSo7MnwZjoUieHeFCnNrJmjSDDApeDSZKKGYE9QxxI6ihyj2KFQ7NLw\nO+047LYe31iKomQRxLx6ZW5gmmYWCchFLcpchzTmkY3MhXAmSenL65eVlaUJYluNzr7Ep5+2R42U\nl5fnhKBFIpH0d7vd/qXxGvVX5FpMK1NFN5FIfKGNqnoyycGXX+PTn9+ZKlhvdf23Bt9+h6KLL6Lh\n2b93eTy2cycoCoGvL6Zx2QtY3cxnoTWrCW9YT/n3b6b0yq8hWSaYJrLNjqO8HGdBQfr5W7l9O3fc\ncQfRaJSRI0fy4IMPMmFgeyirzeGgeMJEmDCxy2u5AwHcGaWlMuH0+WDchG5/F9M0SdQewBGpRYs1\nYqo2UGzYJEFbRpMgu7yBIqW8iJkpTw5FIpoKF6PIIRNMfj4y0hA12LZtW3r7iiuu4IorruCtt976\nQt+nXwQsWrSI22+/nWuvvRbTNPnVr37Va30f6sKo0x36JUEUQqDHoiSbahDBekhEAAnh9CKLnt/Y\nSrCGZMFUFCOBJCwkM0mRZnKwg4/XFCkvXSbvK7TLVHcgfW5VokXP3udUJSIdq52S8iruyAge99lk\ngt3kOQIU2GWKnSoV4fb+bTIM86rs7pDX6LfJlLsV6mKC5o45lRZUhk0qwyZ+W5Lhfo3SAm+PrO1e\nrzftrTJNM70YzKNvoet61m9fUFDQ52PIdX2xPNqhKEqWqm1tbW2fj0FVVUaMGMHu3bsBeP/99/v0\n+kKIrGsOGzYsJ/dlZskZr7dn82oexw+5FtMqLCzk8OHDQEpt8ItoVLUsi5aqwzRt3sqnv/hVihwe\nqX0kgpVIYh81isSePV22iX3yCXptLYUXXYKkabSsep9kRUX6uDZgAKVf+zqeCRPwDR+BehSF2nA4\nnCY9NpstS0zqeENRFBR/GUkjgS0RRI0H0RUHqqygWwKlVcnUIUME0CSIGqk6h20E0aOSRQidikTz\n57R3xIRMYWEhkDJk3HLLLTmpqfzFgQDRGyG7Ryf+LpeLe++993NdxTCMLt+RV199dY/76Hcrv2Qs\nQqJ6P9LeTUiNh7JUdCx3AZSP7HFfEgKtcjvxwRNxRGuRhEWh0YJN9md54+piJuVuhcoMcqbJkOxQ\n80JTJBId9jkUiZiZfdMoEikVq4ymgz1ap3DVTAzz2dIhpW0Y7lPZ25JNDgtsMmn+xuUAACAASURB\nVMUOhUPdKK5qMpQ4ZBQ5FQPfFDOwzCBelw3dSIXYShLIkoTLYcOmaWkrnMfjSYswGIaRpVqYR99B\n1/Us+fRclDXIXOjkPYi5haIo6Rc9QFVVVZ+PwW63c9ppp/H6668DsGbNGmpra7PKPhxPVFdXs2bN\nmvT2aaedlpOyBm1kAFLkIB9mmlvk2oMYyPA6tbS0fKFKAgkhaNi+k6aPNtC8fjOJw9WQudaRujeO\nNC5bRsm114AQJDLK42TCqK+n/umnkWw2vDNnUvbtJTgCJSgOO5rXh7u0tMce+ubm5jRBtNvtfUoQ\nAewuNwmGkGjWsEfrMTUnwlmIJoNTEYRNGUVOhY7KEhiWaI1SS63j/HaZ/RnrP1miU/TaMUOS8PkL\ncDgc/NM//RPTpk3jtdde+5yd5nGi4NJLL+XVV1/N2meaJpdffjmrV6/uUR/9iiAmQkGSu9ah7Fnf\nTYvMtN+eQTKTqJXbiA2agGrG8cZqGe7282mGcyxuCpxKFxNRD3bJktTJoFZol6ntotZidw+8W5NI\ndGjuUiWiusg6x65IlLgUDkc7d+RWJQIOGQsIGalcbEWCYrtEwoLmliRGVv0cgTum49VS0r2yLFM+\naAi//q//5v/+9m7ee+89mpqasCwrbyXvY8TjcRoaGtLbgwYN6vMxJDIS/vMexNxCUZQsI8HBgwf7\nfAw2m43TTjsNj8dDOBwmEonw2GOP8c///M99cv2nnnoqHd7p8XhyRhArMrwcgUAg/2zkGLnMQQQY\nkFHXr6GhIWvePJFhWRbVH67jk5t/it7YxNBbvkfDqyuy2ugtYZSCAszmrlN+6h59jOIrrsA9ZQrB\nd97BDAa7bOeeOpXAggUUnzwNLSNkt6cwDIPGxsY0QXQ4HDmJurG7POjqUBLRAtR4CKLNCGcBlmUh\nIUgKCY8q0s4JU4Aidb2mNa22NKfPMSDTJBIOcc011/Av//Ivn6OjPIBUFGIveBB7o48j4ZlnnuHh\nhx/m0KFDXHDBBVnHIpHIMSmQ95u3mx6Pkty94QjkECQ9jlCO3ZshmTq2ii2YTj+JokGUqAa1No3m\nDJd+c8Ii4JCpj6f+ebqVImSZ+YYJU+DVFKCdzSUtgVPLJlA2RSLcIez0SM/5MJ+Nwx0IZblL4WA4\n+4U30K1QG+vcU7FdwqnJNGYYL20yBOwyIVNCdKC1NkngVlOKSFFLTh03AcXBlDNm8ce/nkxNZQVV\nlRUEg0EKMmL98zj+iMViWWGER6pTc7yQDzHtP9A0jYEZ+TRtYZ59CVmWGTNmDJMmTeLDDz8EYOnS\npVx77bWUlJQc12vX1NTw6KOPprenTp3K2LFjc2K42r9/f/r7wIED889GjpEp4JULgjhiRHth95qa\nmpzkB/c2hBDUrNvI1ut/hBmJogWKSNZ2Fpype2k5A668iKZu6hECNDz3HEpBAQXnnoPi85GorMSM\nRJA1FfuQIfjPPBP/6DHYPZ7PvMYIBoM0NjamtSp8Pl+fRTZ0hGazodkCWFYRRMMIw8AmS/hVQbMh\n41IFySRoskRIF3g1KS1Sk4mQbuHRZIKfwyGdaK7l4osvZvHixVme7jw+I4TVOyGmx5kgXnXVVZxz\nzjksXry4U+6iqqrHVMO437zd4rWVyLvXHrlRMoalfHarsRIL0lIj2K/EmDp+Mh/XRWlqzQtsTFgM\n96rEDEHEEDQlLAa5laz6iDFD4OlABsNJiyEeNYvgCXFscriKJHWyFCkdQgxkUpOK2cFdWWSXsKvZ\nE4kqQcAh02JIdPR5OmWBUwUdpdMxBYFNtnD5PBRMnMS4iZNIImhqCaEpCk6HPb8g6gPE4/GcE8RM\nkRzHZ7Dq5tF70DSNYcOGpbcPHjxIPB7v8//L2LFjmT9/PuvWrcM0TXbs2MGf/vQnfvaznx3X6z70\n0ENs374dSP0W8+fPz8kz0dTUlKXeOnjw4Hz4dY6Ra3Xf0aNHp79/UQhiS+Uhtv/zv2JGogDYSkuI\nH+oc1q43NCG5PKCqcARybjY30/D8CyDLaCUlKB43QjcoveprlE075XOPt76+nuZWL6YkSRQVFeUk\nuiATsizj9PhwkvLGRiIRJAyChkSBTZA0JRoTgkJb1wvFFl1Q4pQIdlG3u6cYNaic2T/6EbIs5w38\nXyLceOONPPDAA4wcOZIZM2Z8rr76xWpfTyahcudRy4NIgNRSj2lzoyQjR2ndNXY0xEg4QgQKvExT\nFWpCcfY2J4mZgv0hgxE+lfq4RXPCQpHkTm7+sG7i1WRCraUmBClvo00mHTqQMAUOVaIlI19dPobn\nMxWjnr2vxKnQ1KEmjiqB1ybTsfxiiUPqkhzaZYEjTQ7bISFwyhZIMkJSER0mkySQNATxUBSbIuF2\nOdOTTn7i6V0IIaisrCTYGo4jSRLTp0/v83GEw+H0d5/P1+fXz6MdmqYxfPhwVFVNe0k2bNjAzJkz\n+3wc8+bN45lnnmHnzp1Eo1GeeuopzjnnHGbMmNHrHj3Lsli9ejXPPPNMeuE9ZswY5s+fnxND1caN\nG9PfbTYbI0aMyBPEHCNzbsqFqFrmAqyxsZG6uroe1yvrj7DZbDR9vJ1EZTshlB12rHjX4jvVTy1j\n4Deupv6xvx29c8tCr6lBr4GBP7iZogndK4MeC6qrq9MpGYqiMHLkyH71+8uyjNfrxWWa2MJRYoaJ\nLAnsMkQN8GkSLUmLApuUFdUW0a3WdeWx/y0Bh0R5oCCfI92bEOKoAk097uc4Yvv27dx2221s2rSJ\nX/7yl1226akqar9ILks21iBXHb22IYB8eBemv+wzXUfXXLzy9gdAauFd6HUzbkARZw31M73MybhC\nGwKJoR6Vk4ptmCLlHcxEVcRkqDd738GQzuCMdk0Ji1JXdpuEKXCqPXvQ5VaRm0y4NZlYhzzFEmfn\nEASbDIboTA4lBB4VjC7JoUDIKkJWOrs+hUASFhomqpwixOFojFA4QigUIhwKEY/HMQwjX1unFyCE\nYMuW9uLABQUFDB06tM/HkUkQMxU08+h7tFnFM0M5M8lKX2LmzJksXLgwTdA+/vhj7rnnHioqKnr1\n+RdCcODAAe655x62bt0KpAjqVVdd9bmtop8Vmb95SUkJfr8/J+PIox2Z/4PMOauvMG7cODweD5C6\nZzdv3tznY+gNlJWV8euf/JTlv/8jhx57OuuYGY6geLoWfUlUVVPz0usEvnEN9ISMSBIDf3Az5QsW\noPVS+abDhw9T31pzUVXVnEQX9ASKolDo91Je6MPntFPmlAkbEHDKRPSUdkUmauMWJQ65J3XVs6BK\nMMhrQ8tHe30p8bvf/Y6hQ4ciyzJlZWVdfnqKfnEHWZFmlB7G5UqWCY2HMbylqKGey70LReX96gT3\nPfgQ8xZc1N6fJOH3uPC5U5NV5iJHN0xqg2FCepSG1txEU0BDPEUSK0Ipa37cFCCB3yYRTAoEKQ+g\nTZZItsaJVrToDPdrfNrU2RLXcQIwrFSR1KPBrkiEO5DGAptErAuLk0sBXUgdLpbyHApZ7TomVghs\nmCiKjCSn1E6FEAhDRxIWKmZKNshMkACErKKoGnaHM6ueop5MIkwDJJAUDS1DOTWPzsiU8582bVpO\nrICZi61MBc08coNAIMCQIUPSKprvv/8+N998c5+PQ9M0brzxRtatW8eKFSswTZMXXngBgHvuuScr\nV/Lz4ODBg/zsZz/jpZdewrJSc+8555zD9773vZx57TKV34YMGZLP6+kHyBQjyVR+7ivYbDYmT56c\nVtj94IMPTjhBkOGDh3Ddj24l8vDTuJeUUbs6O9UnXlFJ0XmzaX6n69I20R27qApHGHD1NRiHq2hZ\n+R6ig1iPpKoUnD+f4nnzKJwyBVsvkcNkMsm+ffvSIaaapjFt2rRe6ft4QZZlfB43qqoStyLUxy2G\n+xQiuoVDgXjrms4SUBE2GOpRqYqKHskzqhKML7IR8Hvza6zehuilMhfH2ZHidru5+eabGT16dCeR\nmo7Yu3cvI0d2XxmiXxBEzGNLLleqd2MOnojuK0NrOXpdF0u180GDYNGS67utU9T2MGU+VHabzOBA\nAQ6bxsbDIQ5HUuOsi1kMcCmM8Gnsa0m58HY160wotCFh0JwUVIYNRvo1drQSwqQlUGUJTU6FpGai\nIW7g02RaMuLNj8YPvZpEzBR0pJey1FmUBsCugN7BYawhEJLcJTmUhMAmWShqOzG0DB3ZMrBjdTpF\nARAGVsIgmkwiFBVJjyMlQqihWiTLACSEohHzliG5fNg9/rxCagfous5HH32U3p43b15OxpG52MqF\nIlwe2Rg8eDBjx45N3xsff/wxjY2Nx6RI1ptjuf/++zn//PPZu3cvyWSSZ599lgMHDvDAAw987gXa\nli1buOGGG1i/fn1amXDIkCHcf//9WaqRfYnq6uqsotPjxo3LibpwHtnIDDHNhQcR4Nxzz80iiCcS\nzKTOpUNGU/WbB1r3dA6js+IJhGkhOx1Ysa7zPBOVVez/zX04hg+l5KJLUWxq+2JaknBPmULZGTOw\n9XLedFNTE5s3b07PE+Xl5UycOLFXr3G84HLYGVIgkIMx6mMmAYeMW5XZ3WKk05oSJhwIGQzzqrTo\nglA3ojUSUOqUKffYCPg/u+BPHt3jRFExveWWW7j00kuPWO8wFovx+OOP8+KLL7JsWfciU/2DIH6G\nm1mp/ASzZBiJwEiUeAtKuL4TLbI0J+bAsbQIG5eefzKxWOyYvTGSJFHi93C6qlAfjrOnKc7hiMHh\nqEmhXWZysZ1Q0qIyrLO9KclIn0apS+JQWCduCga41TSx/LQpweRiB1vq41kCNFVhg6klDlr0dndg\nWBe41XaFq6hu4VSkdJhpeyhpD34rqbuaiQIhdfF7CIEmWSiqmp5ohKGjCZ3uomSFAEOIlLXfiKNE\nm7BF65A6WkuMOGoihJAU4v6ByIUDcLi9GIaOEY+lkt1VFdXuRP0S5ve89957aWuoLMtceOGFfT4G\nIUTWYisfSpd7FBUVMX78eGw2G8lkksbGRjZs2JAzA8KoUaP4+9//zsUXX8zhw4cxTZMPP/yQ+fPn\n8+tf/5prrrkGp9PZ44WKEIJYLMaTTz7J7bffnlXQubi4mL///e9ZgiB9jQ0bNqTrwtpsNsaOHZv3\nrPcD5DrEFOCCCy7gP//zP4GUYMqqVas466yzcjKWY4EQgvq1m6i6+w9Hbdvw2psUXzCXuhdePWK7\n+P4KDt7/SNY+W1kJp371q71ODiFVWiQzJePss8/OuUDNscDjcjBMkSmIxmmIGSRNi/EFKp8GjbQj\nIWnBrqCB3yZR7lAwBSSsVAk0TZbw22UKnBoFbmdeRDAPnnzySe6++27mzZvHqaeeypQpU9KG5Kam\nJj7++GPWr1/PvHnzWLp06RH76hd3k6TZj96oCyh1BxB1BxCFA0mMPT1FhCwTJBlJtSF7CnF5fOzb\ntu1zq4v53U58LgcDC3QawzFihoVlCWRZYpAXJgScxFoL0cuSxCCvDd1Khak6FIl9LTqGBTsaE0wN\nONjemCDRaiYSQMywcCqkCWBN1GSkT2VfaxhrbcxkVIFGrLUGoiRBRztEd1UiFcDq6GlEpArddrGA\nU7FQM8ihdRRyaFgCyzRRjSigoAarUPVot7+lQMLQXIh4lER9FfGqBFLVbqirACMJqo1EyRDkoZPQ\nisuxe/1fGovYs88+m/4+evTonISxxePxrILPeQ9i/8DYsWMpKiqiurqaUCjEli1bckYQIVVu4k9/\n+hM///nP2bp1K6Zp0tDQwA9/+EOWLl3KDTfcwMknn0xJSUmXkRvJZJK6ujrq6+vZuXMn999/P+++\n+266raIojB8/nrvuuotTTvn8aoefFW15wW0iKIFAgPHjx+dsPHm0I7M+aFsufF8vkocPH87QoUPT\nNTKXLVt2QhDEaEMTn977YAePoQSyDFb26iJeUUnJVy7ANrCcZFU1PYWkKIy56xf4hvS+t10IQW1t\nLfv27Uvvu+SSS3r9OscbDrsNh91GsdcgGImRME0mFcmEkyYHI2a6RnYwKQgmDTQZBroUAi6VArcD\nl8PxpVkf5RQnSJkLt9vNHXfcwY033sibb76ZJoRCCIqLiznjjDP4xS9+QXl5+VH76hcEUSkowbK7\nkRLHrkwqAcJIYi8qxeE5vp4OSZJw2m0MsvfcQiWEYHAszqhwnIpggt3NCbbWxxlZYEOTJarCOk0J\ni11NSU4udXAwbJK0UuQvYggK7TJNCQsLMC3RKmCTylPUVMiMOOgccNo28M67VKl776EitYfaCiGQ\nLPOI5BA9gcOMkURFDR3ulhxaikbS7keYFoQaMG1u2PweckvnGkuEGhF7N5Pwl5I8eS7OwaMw43Hi\n9fUIPQmKgh5LYsXiWEkdWVXRCvz4R43o3NcJgkgkwvLly9Pb06ZNw+3uWhzgeKIt4b8NmYuwPHKH\nyZMnEwgEqK6uJhqNsnnzZkKhUM5EhBRF4fzzz8ftdnPvvffy4osvYpomyWSS9957j5UrVzJ27Fim\nTZuGz+fLKt1SU1PDgw8+SDweZ8uWLWzfvj3LKKEoCgsWLODHP/4xs2fPzqllPBgMsmXLlrSRMRAI\nMHny5JyNJ492dDRe1dfX92jh05twu92cfPLJWQTxzjvv7PflgRp3fErTumxRndr31+I/63SCK1d3\nal/5x78y9Mffp/qp50keOnzU/iVNY/z//IoBs2YeFwIjhOCtt95Klzdxu93MmTOn16/TV1BVlWJ/\n+1wuhGBQJEZLPIlupnIQZQlcmkKhx4mWYcTPow9wghDENpSVlR0xzLQn6BcE0eYtJDL8JNSdqz7T\n+WLUKdjd/VOKX5IkPC4nHpeTQUUGY0NRYrqJaaUMdUN8dgSpOvUAAafF9sYkLbrgcNRkmFcFAU1J\ni6qIyRCvyuGoIKwLBtraE5rbIehIFS2RUivNGlc345URWXmBwkopmHYF0xIpcm7GUle1DNRuyo8k\n7T5ME9RDO7BkDd1VDOuWHz0eOxokuXsr4X0VtLz9OkYwiOPkM4jVNFL74nKMxqb2sdvtlC+6nCf/\n626Wvvk6y5a/duS++xneeuutdCFuTdOYNWtWThb/Bw4cSH+32Ww5Ial5dMbIkSMZP34827Ztw7Is\nNm7cyCeffMLpp5+eszEpisLs2bMZOnQo5557Lr/73e/YvXs3kFrg7Ny5k507OytUV1VV8fDDD3fZ\n55gxY7jpppu45JJLchpW2oatW7eyadOmdPmCSZMmMXz48FwPKw9SOYhtYdcAFRUVfU4QfT4fc+bM\n4ZVXXsE0TXbt2sXKlSuZP39+n46jpxBC0FJdQ9Xydzoda1q3mYE//0GXBFEYBhX3PMCgG76J3thM\nwz/ewIx08b6XZYrnzWHwN79O6YxTj5vImq7rPPPMM+nt2bNnf6GMmW0Cin6PK9dDyeNLipwTRMuy\niBzcjRmPoWh2JD1x9JMyIOxulMLyE8KSoqkq5YVHJrJCCAo9cZqiCSpbklSEDAa6FYbbVaqjJvUx\nkxKHQl2867zCsC6wKYJkRn6iIToTwu50lBQsZCXDQ2p2LIyRccgS2I2Ut9CQVNRw16EnSbsPKxZF\na6xESDJ6QTmsX3FUcmi6/MSLxlL3+KNYLUHsk6bBwHHs+e0fwOx8rpVIUPW3J/EB/zTrTE76p1v4\n+OCBzh33Uzz66KPp7yNHjuSkk07KieekzRIOqRyfEymn44sMu93OJZdcwgsvvIBhGOzcuZONGzcy\nffr0nNe7Gj58ON///ve58MILeeKJJ3j44Yc5ePDgMfUxZMgQrr/+ehYvXsywYcP6xX1nGAabNm1i\nz549QMrKv2DBgn4xtjxSBiyv15uug3fgwIE+L4PSppw5dOhQ9u3bhxCCpUuX9juCKISgfucuGtZv\nofbtD4jXN3XZLrS/EseIocT3VXQ6JgyTygcewT6wnLKvXYZk14jtP4gZDiM7HHgnT6T4rNMpGDca\nm8t1XNdl7777Lp9++ml6+7rrrjtu18ojj5SAU294/06ccnA5JYhCCMIVu7DeeQJJktGnzkHbu75V\n8bIH56t2xPSLcBV/trqI/RGSJOFzO/G6HAzwGwSjcYzWAp0DPIKEaRHXLYZ5JJqTFh4tVUunDWED\nBmiQzHL6SRiWQJJFWuHUEqRKi3QVZpp1puhSQ8gSIFl6mnhalsDWRWipodgxdQOtsTK17S2FXeuP\nSA6F3Y05dDKxGNQ9dB+YJraxE0niovqRJ7oep6bhn3M22rChmIYJEnzV7+O8uedRu3s/oeo6jHgS\nRVNwFRYwYOJo3D5fvzEsbN++nU2bNqW3TznlFCZMmJCT8bV5MSEVwpVPfO8/uPzyy/nJT35CQ0ND\nOpRz4cKFWTUScwVN0xgzZgz/9m//xq233sqrr77Kiy++yOrVq6mtrSUcDqfVBhVFwe12U1ZWxpln\nnsmll17KRRddhLOX5O97Cw0NDbzzzjtpD1VBQQFXXHFFjkeVRxs0TcPv96cJYmVlZZ+PQZIkJkyY\nwLRp09L5cB9++OFRJeT7EpZlUbVmHWuv/2eS9Y0UnjkdM9m1JObBZ15i0i9+RM2f/obRFOyyTaKq\nmkMPP4qkadgHlKF43JRf9VWGXPEVnP7jH80lhOB///d/0yVwRo8endNIijzyOFHQFgnTE+R05Ret\nO4z1/rNIrWUuxLYP0CedhXZw61HzES2nD065EPeAYf1mkd+bkCQJm02jxJat5CmEQAiBaZqEo3Ei\nSYOEaaZqHLYirFs4VYhZ7aGiYQMKbBZ6qz/QQMJGz2rrdAXDEtiNDOEfq+swVN3uQz24Nb1tKnak\nYF2XbQUS1shTMCJR9LBB/V8eAtNEstlRRkzi4G/v73SO7HRQvPAydNXGvlfeounxVwDwTxpL2UXn\nUbt1FS88/jMSoZTC3chZpzHxvJlUrlyDq8CP3evGP3wI7iI/iiSBJKE6HHgHDeizEhymabJixYq0\ncqPH4+G0007LWbjMoUOH0t+LiopyVncuj87w+Xxcfvnl6fDMlStXcuDAgX5BEDPhdDpZuHAhCxcu\nxDRNNm7cyHe/+910sfkpU6bwhz/8oV94P4+Effv2ZZUuWLRoUT7kuh9B0zSKiorYu3cvkB0e35co\nLy/n9NNP57XXXiMajVJTU8Obb77J8OHDc17KSQhB1YfrWfONmzAjKSOuGQ6jdlMiRxgmO377Byb8\ny/epXfo0ycPdlxITuk68opIRt/2IwV+5sE/IIaTqt61YsSK9fcEFF+TVtvM4vrCsTuJNn7mfPsA1\n11zDY4891mn/7NmzWblyZY/6yBlBFEJg1FchJdq9TlIiitj8Nvqok5GcXuTGSuRgTdpLJQCraBBm\nwQDQHLgDA7+Q5PBIkCQJSZKQZZlCv4bfsrCrIfaH2mWRQwYoUqsqaitJtJDQTYGiWJjIgNQqeiOy\nlEwFUs8sDMLqkNfYmWoKSYFkPF3qwrR7EA2Husx/FEiY484ksWkNQpaJhiREq2iF89QzOPzMS53O\n0YoKKfrm1Wz4vw+TyAiXKZt7NsagATz3y3vS+6ZeNp+Rp06mfvV6tv/2DyAEQ845k6FnT6fmow00\nvfEuequ11DNxLMO+/00cA8uw+72oLheegQOPW9mNyspKli9fnq49OGjQIM4999zjcq2ejqcNBQUF\neYLYz3DTTTfx6KOPkkgkqKys5KmnnmL69Om5Hla3UBSFoqKiLO+g2+2mtLS0X5NDgKVLl1JdnQqd\ndzqdfO9738vxiPLIhKqqWUI1ufAgtmHu3Lk8+OCD7Nmzh+bmZl577TUuvvhiBg4cmLMxATTtO8C6\n7/80TQ4BInsOMHT2mdS907XugxGJsvXXv2PkksU4vC6a3niH2K69WW1kl5MBV19Jybw5FE2egN3j\nOa5/Rxssy+K+++4jkUilIxUWFjJ37ty84SaP44oTpQ7iCy+8wLJly9i2bRtLlizJOhYOh4/JYJUz\ngpgIBRHbV3ciC5JpwKfrUoShfATmkKnZDeoOwv63QFZJlA5BKx/SZ2Puj5BlmUCBD02N0hzTqY2Z\nGAKadfAKC68GCQuSQiJkgk8SKHKKJCaFhEuYWFL7bWAgo5omyjGHFXamfUm7H6Wm/aVi2VxIh/Z1\nagdgjTyFxKbViMZaOGkO4cfa8/GkwjLiB7LzmWS3i6JvXs1Hd/4OM96etxo4YxrxQDEf3Nd+/uyb\nrkFUVvHxf92XOldTOf2nN5L8aD019/4x3a5w1gyKzp6B1VRP9QP3YbYSNrUkQNnVi/FMGI+ttARn\nUTGqpqWJ+ucxUpimyQcffJAutAxwzjnn5LTYb6YHMRAI5AliP8PUqVO58MIL0wVu//rXv3LTTTcx\nYsSJq+DbH7F79+6sOlEXXXTRCVOE+8sCm82WFWmROXf1NaZMmcJZZ53Fnj17EEKwcuVKPvroIy69\n9NKceRGFEDRt3UGigxfQjMaQZQXZYceKd637IHSDPX98FFnTKF9wLuXzzgVDTxmUBRSeOZ1Bs87s\n8/fD5s2befXV9nqMM2bMYNq0aTn31OaRR3/ARRddxPDhw/nBD37AV77ylaxjqqpy6qmn9rivnBFE\nvbkeqbn70AUJAdV7U5+uYBlYTbXwJSeIkPIqFnjd+NwWRbE44YRO0hCYIpU/6NckZBlMIaVyDyWB\nDZOkkEmYYMNEyEpbZ5iWidzqRRSygmmZKEfjQHJnT4AlK2h6PLuN0bkemnC4MSLhFDmUFYxwDIxU\n2LE6YCChbbs6nRNYtJD1dz+YRQ5lTaXgnLN44fbfpved8e2FmHv2Uf3+2tSfJ8ucefsPaHr82fbQ\nGUVhxC3Xoe/dRcPSv6XPdYweReE5s5BMneS2DUTNKEmPm2BjHZIiow0ehuIrQPEXIGt2ZEVGEgJJ\n1bD5C7F7vEclj01NTTz33HPpItyapnHLLbfkVAQjH2Lav6EoCrfeeivLly8nHo9TV1fHr371K/78\n5z/nemhfKPzHf/xH+rl0uVz85Cc/yS9C+xk0Tes3BNFut/PDH/6Qv/0t5vzruwAAIABJREFU9Q6p\nq6vjhRdeYM6cORQWFuZkTNHmZvb+6fEujx1+5Q0GXHQeh557tcvjbbB0naoXV1CVsc81dBAjvvX1\nPn83WJbFc889l86T93q9XHDBBQwbNqxPx5HHlxAnSJkLm83GySefzLJlyz53mlLu3nbGsamVdgVh\nJBDixFEEOt6QZRmf28XAIj/DSvyMKPEzrKSAAYECyooKGFDkY1Cxj/IiP2VFfkq9djw2GQWBYhnp\ngrkGMqI1p1BS1HTeYhak7ABTWZYw1A4CEx3/N8IEtTPxsQaMQ/9kQ2rD4cJoakwfU7wFxKuyDQmy\ny0ksbpDskEA/4Pw5rH26/WXnKQtQXORPk0OAKdctouWFV7PyKkb+5HtEVr1HeP361osqDLju2/gn\njSK8/AUkycI1bjT6xpUkd2xCKy5GsWsYOzdj1VaR3LqO0GP/j9BzjxDduo7IxlU0r36LurUrady1\nHcPoXnRp27Zt/OMf/0hvL168OKdFuMPhMHV17TmipaWlecXGfogxY8Zw4YUXpreXLl3Ktm3bcjii\nLxa2bduW5T284IILGDVqVA5HlEdXsNlsWfm3tbW16bp4ucD06dO57LLL0tvLli1j167OBs6+QnDP\nfhpXr+vyWHTvfjwjhuIcdGxlQWRN4+Tf/jv+QQN6Y4g9hhCCTz75hLfeeisdXjpq1CguvvjivOEm\njzw6YO3atZx//vlMnTqVyZMnZ316itw9Vb3B6/LcsFt0Ff7Ylr/Y9nHY7RT6vAQK/RR4XLhVCZtk\nQWu+omWarV5EGbPDb61IErpsT2+rwsDwdBDK6OA9kxNRRGH2y0hIMiYKxFP5EZKqYmWqqykqogPB\nKpw/lz3Pda5x6Jo0jkObPklvT190Cfueebn9+jYNf3EBsT370/sGfP2rRNetIXmo1T4qywz87nXE\n1q0k+tEqCi+7EuvwHmIrX8N15rlohYUk3n0FDAOloJDE+//ACjZin3EuckExiQ9WkHj/NZLb1mFU\nVxLfvon691ZQu24VwYp9adU1gJaWFv7t3/6NaDT1txcVFXHnnXd2+rv6Em1iD5DyVA0YMCBPEPsh\niouLufLKK9P5V8lkkrvuuotgsGvVwTx6jmAwyK9//Wv01hzooqIiFi1aRCAQyPHI8ugIu93OgAHt\ngmKGYWTNYbnAXXfdla5f29zczK9+9StisdhRzuo9CCGINjVzaPVHBLcfmZzu+f3DjPjO13EO7hnZ\nkx12TnvotwyZdUaf6z/EYjGeffZZ1q1LEV5JkrjiiisYO3Zsn44jjy8pWqsJ9MqnD/Cb3/yGn/zk\nJ7zyyissX74869NT5E7FVP38oQmSZuvRJBUIBLjhhhuAlJdt8ODBn/vaXzRomoamaQghiCUSGLqB\nZVlYCJBVkkJgE0Y61FSRJZKqHZIpS55EitwZqhO1Vd1UsXQsuxu5VZFWSYSRSoZBRTuJw+nFbGj3\n5olEHKWg/WUlYmHUjspogQDhiuxQIkegiLqK9iAYWVEoKPJxsLE5vW/kRecSfP2d9pMkCffIIdSv\neju9q/RrC4l9+C5mbQ2+BZeg79qMeegAnouuxNi+Aau+GtspZyMiQYx9O7CfOR+z+iDxt18EQB1/\nMnLpIIyKvUTfeBGluBTJ7QNFIYpEdNwkHGMm4xkygvvuu4/3338/NV5Z5vrrr895qMzevXvTXnmv\n10tBQUHeOtsPoSgKs2bNYs6cObz00ktYlsVbb73Fyy+/zOLFi/P/s88Iy7J46aWXeP3114HUczl7\n9mxmzpyZ/037IWRZprCwELfbTSgUAlJzWC5zRSdNmsQ111zDAw88AMBrr73GX/7yF2688cbjfu1k\nNMbhDz5kz/2P0LhqHcN/sOSI7YVu8Olv/peRN32HeF0DVcv+P3vnHR5Vlf/h904vyUwa6QmkUEOR\nXqQqCAZREcWCBUSxgG0FVFbEdUF/uoKKZV2VsmIDRVhAEKT3TuhdSEjvZWYy9d7fHwODQyotCTrv\n8+R5mHvPPXPuMOfO+ZxvW4nTVDGDvCCXE3XXQOJG3k9U1471MhcOHjzI3LlzPSVnmjVrxmOPPVbn\n47iRiYqKYuTIkZ5yQ/Xl+nxDIl2jOoh1JBD1ej0DBw68qj7qTSAqjMHY/AIRTJUXa60JSZAhN9Zu\nRzc0NJR3333X89qvjrJt3YgIgoBOowGN+7Xdbsdut1PudIFcgUJyosBtHJTJZDhkKpSi+4GtlJzY\nAqIQis8hd9pQ2kqxBscgyzzm6V/utOEyhCCU5rsPKNVIf9xdtZWj/IPLkD39HMZeyRRv2uY55nJW\nLKmhDg6kJDvf8zqiXQsK9x70ahPWsik5q9d7Xgf27IzlwMXagzKdDoVeTXlWBjK9HwqdmvKMVLRd\ne+P6/QhifjbyyFgEuYDzzDFUXW/BefYErqxUQEDVYwD208dxHtyLKqkT6j53YEtNxVlYAC4RmZ8e\nodSMc882TGdOcvzAfo9FsUOHDg3ix+5CoWcAo9GIwVA3act9XD7R0dE8+uijbN++nZycHPLy8vjv\nf/9Lly5daNq0aX0P74bk5MmTzJ07l/x897OkUaNGPPLII0RFRdXzyHxUhdFoxGg0UlZWhiRJnlqE\n9cmYMWPYuHEjhw8fxul0MnXqVLp3785NN9103d7TWlrG7wsWc+T1dz2LUKEWQk5yODn90ZdooyNp\n8uh9CGoV5t9TcZaZkWs1BLRtRVif7gS3bIZKq6m3zPFTp071xB4qFAqmT59ObGxsvYzlRqV58+a8\n++67nt/4P2YA9vHn4oEHHuC7775j2LBhqNXqmi+ohHoTiBpjEPaW3WFX9QHSVSE0TkIdUju3CLlc\n7tspuUJUKhUqlQq1Ws3yFSvQqNUkxsdh8NPhr9XgVGgRHCIKyYkAqCU79oAYXOZClOWFoFAiyeQI\n52MaFWW5uJp1Qtqzyp3uV3QiKLy/vHKnBXlQCK7CfHA6kCtBrtfjMp/f2axkB0aQyRBdF4WjPigQ\nW0GxdyOHd2HgwG4dKJx/MYA/sH8/LDvdNc/8bu6NLWW7uy5iaAS2I263FlXL9tg2/4o8ojGSuey8\nOARVt1uxHdyDoPVD1X0gZRvX4szJ8h6jWo0jKxOZMQBtq9a8PuphMrKy2LxjJ4899liDcJU5d+5i\nttgLCy8fDROZTMbdd9/NggULmD9/PpIksWHDBlatWkWTJk18yYUuE7vdzooVK9iwYYNnAdWvXz/u\nvvtun/WwAWMwGDAajaSnpyNJktczrL5ISkpi1KhRvPbaazgcDrKyspg+fTqzZs26Li77ToeDtF9W\nceTv/+d13HTiNIY2LSg9eKyKKy9Snp7JmX/PRVAq0YSHojD44Sq30nzcKCI7trvmY74c5s2bxy+/\n/OJ5fc8993D77bfX44huTC7N+uuj9twoZS6SkpLcoWGShCiK/POf//SUk7pQwu7QoUM19OKmXgSi\nJEmUF+TiconIFCqESjJbVns9II9vi1J1ZarYx+WjVCppHBvLnXfeyblz54iIiODxUSMZM2YMgcYA\nRLsJpcuKAKgkO6LeiE0XCA4bjvCmqM5bEQVJRFmWg6NdX6T968BqRhYSwR9tgtKZgxj69KNo0Y8A\nWPduo9GQAWT/sBig0sWavaQUv+beVpNLdzorbHyK3pZITVQEpbs2gCCgDAnCsbcIVbMknGePu6/X\n+SHZrCCJKJq1wbbJvbkhj03EmZWOYAjCJdNQ8uO3Xv0qYxqja98FyeHAmZeDaLPhyMxCKciZ9c5U\nps75miFDhqC47NIi154Liyxwx175dhgbNjKZjLfffpvVq1dTUFDgiUXs2LEj3bp1q+/h3VBs27aN\nadOmeZJKhYeH8/777/vEYQMnMDCQoPNF3yVJIi0trZ5H5P69vOuuu/j1119Zs2YNkiSxfPlyZs2a\nxejRo6+5SCw8dpJDr0ytcDx/9Ubixo2ulUC8gORwUH7OHcIRNqgfQc3rzxtBkiS2b9/O888/7/ld\nSkhI4PXXX/fNSx8+KmHVqlXXrK96mWG2ogIsa3/CueUXxObdkYTLG4bQvj+ayCbXZ3A+qiQxMZEx\nY8bg7+9PVlYWb7/zfzz19DPkFRahDAzDoQ/BrvJDQoZMcqHCgUqpQDKGYo9o7skpJLdbUFoKocNt\noPFD7uePVx1FmxWVVoE6IREAV34uuqhgtE3j3de7nCj9vd2ELZk5RCRejN8zFxahDvG2Gl9qePQS\nkIKA5HDHU8r9DYgl7kyq6qYtcZ11B/qrkjriOLIbQasHWzmcdw9VNGmOsygfSReAaeMaT5cyvR8B\n9z2ColE4xUt+omTZz5h3bKE8ZTfm7ZsoXvg9RR//i4md2mKwW+s9I6/D4fAUBQe3QLyw8PLRcImP\nj2fatGke1/ns7Gz+9re/NQhXuxuFkydPMn78eI9rqZ+fH9OmTfO5lt4ABAQEeHkIZWdnexIM1SeJ\niYk88cQThIaGAlBYWMh//vMftm/f7pWs7GqRJInCPQcQbZWUkHK6cJrMqIKvzIOqySP3ofarvwL0\nv//+O2+88YYn+ZbBYOCJJ54gPj6+3sbk46+KeLHUxdX8cX0tiFFRUURFRZGZmVnpX1ZWFsePH/fE\n8lZHnQvE+MYx2PauQ0w7AVYLzv1bEFv1QpLXbD2RANr3R9O8I0q1tqbmPq4xfn5+PProowwcOBCF\nQoEkSWzcuJHPPvuMsjITOkMgmsAwRGM4Tv8wHH5huAyh6IIj0DRujTOhC6LK/WMjd5SjLkpDntAa\nIbARsibe7pXS0R0E9O6NKt4tEs2/LSXy3tvRtWhKyW9rSBg2qML4HBmZBDVxJyDK2n+MwJu80/lK\nKqWXGVESLwoymUYD5yeMoNMhnc+q6haB5+M59H5IplIUTdtgP+qOXRT8jbiKi1C27EDpbxfdpWX+\nBgx3DKN48QIsu7aBq2LcJIBks1G+cys538ym4ORxnE5nvQnF7OxsryyYwcHBPhfTG4RRo0bx5JNP\nelxJtm3bxquvvkpxcXENV/rIz89n4sSJnuyIcrmcMWPG8PDDD9fzyHzUhsDAQK8Ms8XFxeTm5tbj\niC5y5513MmbMGM/rAwcO8M4773g2Iq4FpRlZnP606hqoGd//TMLYUcjUl2e1bD5xLOFdO9ZbzGF+\nfj4ff/wxW7ZsQZIkFAoFgwYNYsSIEej19SdaffxFuRbi8FrVUqwFU6dO5YknnuDxxx9nwoQJjB49\nmieffJK///3vjBw5kj59+niSJFZFnQvELs0TEA/vvHigrAjn7nW4EjojxrdHUlUUfpJMjhjdErH9\nQFTNOqLW+9fhiH38kZiYGF555RViYmIAsFgszJ07l2XLluFwOJDJZGh0erR+BnT+BrR6fxQKBUqN\nBn10IkKbfjia9cAZFIOo8UduM6Gy5KG8qSdc4jIipawnsHtnAu68B7khANOyBYT170rY0NsJatqk\nQgB+xtLf6PLgEABEl4vigmI0IRctYGfWb8fYo7PntShKCOeDd0WbDc67/UgOR7VZdmV6fySTe+Gt\nbNYO++mjOAsKL5ooFQqMg++h+KfvkKxVpDeXy9F17k7AsIfQtukACOTPm83ZTz8gZ/N6StPPXdNd\n5tpw5swZTybAC+njfXFsNwZKpZJnnnmGfv36eY4tWbKEGTNmeGqG+aiIzWZjxowZXrVI+/XrxzPP\nPOP77t8gqFQqr3I8ZWVlnmQm9Y1Wq+Xll1+mf//+gNvat3r1aiZPnnzN3sOSlUP5JVm9/4jLXM6Z\nz7+m2cRxKAy1Wzu1mPQCTR+7H00t219rHA4HS5Ys4ZtvvvGUCImNjWXixIm+LPQ+fNSCAQMG8Le/\n/Y19+/axfv169u3bx4QJExg+fDjbtm1jxowZXsk7K6NOBWJkZCTB9lIqFDC0mnHtWIXj6D6c4c1w\nNeuGq1nX83/dcMV3xJF+Fue6n3EW5VXat4+6QRAEOnXqxPTp0z0xAAUFBTz33HNs3bq1WuuXIAho\n/I3oI5qgbtUDRbtbkbW9FWXbWzE0a4tm0EMVAgWlIztQ5Z0kZPAgQh4eiVxwonSVYowJodNbL3u1\ndZoskJlFy0G9Adj1w1Lih9/hOZ+1dQ+6zu09r3OXrcbQs6f7hSgiKN0LDLGsFJn/eZecP97OhX/L\nZHDB+qjWoExIwrR1k6eZtn1nTJvWItkrX5irEpoRMOwhHFlZFC34lrJ1v1G+fy/lB1MoW/cbWdPf\n4cykv5Gx6EdKM9LrzKKYlpbmEYg6nc6XIe4GQhAEmjZtyssvv0yTJk0AsFqtzJw5ky+++KJBuNw1\nNBwOB1988QWfffaZR0THxcXx8ssvk5iYWG+WEx+XhyAIxMbGotPpADCZTA0iDvECRqOR77//3uMW\n6XQ6+eKLL3jxxRc95QauBFEUKTqTiiU7p8a2jrwCznz0JXGPP0CTJx9GHdaoQhuZSoX/kP70+PEr\nmj/+EPpG9VP380KyrRdeeIGCggL32GQy3n//fTp2rD+Lpo+/OBfKXFz1X92s55YuXcpjjz3myW0h\nl8sZMWIEixe7c3l07969RjfTOhWIzz3+KPrfD1TdwFKGuH8zzh2/4dyx+vzfb7h2rYGiXJBEnNlp\n9R6r5QOGDh3K+PHjPa4epaWl3H///WzevNmT5KEqBEFAoVCg0mhR6/xQqdUoVSoMrTuhvfNx0Oi8\nL7CakY7uQHZkEzpXIX5+Ino9xN85gG7/muwlKtMX/UpCYixt7rgFc14hOVn5RPS5mKwjfd9hAvq5\nRaHl1FmUERdjjGw5BcgDg5DsdpArQCZza8Lz7s+urFRkUXFIVguC9sIYBZArEM1lnn5UMU2wp52t\n9N7VrdqibpJA0fdfY0+tOkZMLC0hf94sMj79gNLUs3Xync/MzMRicbvW6nQ6j9DwceNwyy238PTT\nT3tcg0tKSnj//fdZtGhRjfPyr4TT6WTx4sW8//77HrfqgIAAnn76aW699dZ6Hp2PyyU2Nhat1u19\nZDabyczMrOGKuiUoKIjp06cTGRnpOfbVV18xc+ZMz6ZcbXE6HOTs3c+xf89h+52PULr/cO2uKzPx\n+0dfkfXTUsIH9iXxxTEkjHuchOdG0+zNlykaM5zXdq4jpk+PerMculwutmzZwogRIzCZTIC7nttL\nL73E0KFD62VMPnzAxSym1+Kvrpg/f75nHtlsNhYvXuwRhV9++WWNSQjrVCCGBweBvQqXu1oiFuXV\nueudj8r5xz/+wZNPPunZuc3JyWHkyJGsXr36ihajCpUaY1IHDA//De2QkQgRTbwbaHQo2/dCN+gh\njDcPJCg2lqSHhzFw0SyaPjwMmdIt5M5+/RPheg13vfUSBWfTISaK6IF9ADjzy1rsYaEYzrua5q/e\njHHAAACKfluDrqtbPJp370LVoh3W/btQtnTXrnKcPIwyoRXOM8dRJCa5xyQ6kf4gUBVRMTjOVb57\nrYiIQt04ntJVtS/tYj1ykKzZ/8aUdX0XPA6Hg4yMDI87j16v9wnEGxCVSsW4ceMYN26cx+UuLS2N\nV155haVLl9bz6BoOK1euZNKkSR5Lk0Kh4Nlnn2Xs2LE+19IbkPj4eM9mZXl5ORkZGQ1qQ0QmkzFg\nwAAmTZrkSVpjNpt5//33+f777zGbKxanrwybyUTqol/YedejnJr6AY78QiSXC5mm9hndncWlpM/7\niTMffcnZT+dw9pPZZBQW8PSbr3PoyJErur9rgcvlYv369YwePdoTQ6rVahk1ahRTp1bM0OrDh4+q\nmTFjBgsWLKBTp060atWKdu3a8dVXX3nm0qFDh3jnnXeq7aNO8+orrkVaYocvnqahoFarmTBhAiaT\niXnz5mGz2Thz5gwTJ05kypQpDBky5LLTectkMvzCo5DCIrHFt8BRWozkdIJchlytRRsc6pXeWqXV\nEN+3B9HdOtBy9AMUHT/NyYOHkZAoc1lp/9wIGoWEYi8uJWHoIFKXreHgnB9pMXww4U88TMHi5agj\nQjH07kPpxg24nCAPCcV2+iR+N/fCcvwg2k493G8mSYjmMiRbOfLgMByA8+wJZE0vuq2q4xIpP7Cv\n0nvTd+tF8c/zL/tzLj+QQtnhA/hFRF4395rCwkIyMjI8lsrAwEBfrMcNil6vZ/z48QC89957OBwO\nzp49y0svvURmZiZjxoz5y4ogl8vF3Llzeeeddzh9+jTgdr2ZOHGil0eEjxuL2NhYz264KIpkZWVR\nXFzslbymvtHr9Tz00EOUlJQwdepUysvLyczMZNq0aZhMJp5//vlqSx05bDbS/vcrR8e/6XU8f+V6\nwpL7k/XzL5VfWAMyrYbTVrOnRlp94HA4WLFiBW+++SanTp0C3JtdDzzwAK+88soVF/r24eOaIYqe\nzPVX3U8dkJSUxMKFC7HZbJSUlODn5+cx5gB89NFHNfZRpwLRdi129LR+Ph/0BoIgCERERDBlyhTy\n8vJYunQpoihy6NAhXnrpJcDtinol9YouxCtq/GuXRVOl0RDVvg1R7dvQ4dHhSJKE0+lk6NChzJs3\nD71ejyRJJN19O7lHTmDKykESJYJ6d0MsLMKWkUnY6NEUrlpF6F13YFqzjOJflhCYPBTbicMo23TB\ncXAn9n3b0PYdjDP9d+RRcbgyzqDs1M+d1MbpQKbVIVoq7gbL/A2IJlOtHg6CRoO+W08UwSHgdIIg\nYM/LpeDIIQKaNkdxHQotFxYWkpNzMZYlPj7e96N8AxMQEMD48eOxWCzMnDkTl8tFamoqU6ZMwWKx\n8MILL1yXgt0NGafTyaeffsq0adPIy3PHsguCwFNPPcWECRN8NT9vYDQaDbGxsZ5MtFlZWRQUFDQo\ngQjujbcLsXUzZswA3Bb+KVOmUFhYWK2lLHfXPo6+8s8Kx61n0ggfdgdZVzimgLsG8tqC76/w6qtH\nFEWWLVvGiy++yLlz5zxC9ZZbbmHy5MlERUX51nw+fNSSmTNn8vzzz/P6669XOW/++c+Kz5HKqFOB\nuHXfAQb3a42sMLvmxlUgD4v2PSwaEIIgEB0dzccff0xeXp6nxtO5c+cYPXo0crmcgQMHeuJD6gKX\ny1WpG7IgCGj0OmI73+R1XJIkXC4XLoeDsOSBWM6monxgJJZtGyle/RsBtw1CLMlH0eImnMdSsO7a\ngLpTLwS5wu3ynJ+Fvkt3zFs3IjkcCEoV0iWZI/XdemLeurHacQsqFYbb7wTAvH0zzhzveVK8aAGl\ntw7Cv1sPDE1boL6G1o68vDyysi4uMZo1a1ZNax83AhdEYkFBAfPnz8dms1FQUMC0adOQy+U8+eST\n+Pn9+TfcJEnCbDYzd+5c3nrrLQoL3TVOlUolw4YN47XXXvOJwz8BLVq08Pw7Ozvbk+CkoaHX65k+\nfTplZWV8/fXX2Gw2TCYT06ZNw263M2XKFHQ6nde8dFitZP78S5Xlkkp2pxDS72by1225rLHI9Voc\n7ZpzYubJq7qnK8Vms7F+/XpGjRrliQWWyWR07NiRTz75hLi4uHoZlw8fFZCka5Ng5jrnkwgODgYg\nPDz8qvuqUSBarVZeffVVCgoKsNvtPPPMM7Ro0YIJEyYgSRKNGjXivffeq5XL0jcLfmLio/cTeKUC\nUeuHMtQnEBsiMTEx/PLLLzz77LP873//w2KxUFJSwn333cfYsWMZN24ccXFxnjptDYkLSXMUCgXq\n6GiMUVG4XC4cPW7GnHYWy/EjSEo9ipgEFBGx2PZswrZ9HZpeA9HcOhTrpuXoug3CvHUjzsJ8FKFh\n2E3eiQdkWh2u0pIqRgAyvR8BQ4dTsmRhle0kh4PywwcQdFpsmRko/PyQaTQoDAH4xTZGqdVd0dyQ\nJIm8vDyysy/Oyw4dOlx2Pz4aHpGRkfzrX/8iMDCQr776CrPZTElJCX//+985deoUY8eOJSkpqb6H\neV05fvw4n3zyCXPmzPFKwvTYY4/x97//naioqBp68HEjcNNNFzf+MjMzyc3NrVe3yZr48MMPiYmJ\n8WyugtvtKzU1lYkTJ9K2bVvPuqro+Cmyf1pWZV9F67cSPeYR7PmFlB48Wqv3l6lUtPvsXd787r9X\nfzOXiSiKpKamMmfOHN577z1PFmGtVsvgwYP55JNPCAsLq/Nx+fBRJReymF6Lfq4jI0aMAGDcuHGA\ne7OssLCQVq1aXXZfNQrEtWvX0qZNG0aPHk1mZiajRo2iQ4cOPPzwwwwcOJAPPviAhQsX8sADD9T4\nZo1jY9EHh4JKA3br5Q+2fR+0waGXfZ2PuiEgIICZM2cSERHBnDlzKCoqwul08tlnn3Hs2DHGjx9P\n7969G7xrm0cwGgxoW7dFbNUaa3ERTrsNl8OJqnkbxOIC7EdTQKNB038YktWCtmM3yvfvxpg8FPvv\np7w7reaZICiUBAwdTtHC75HKK0/ipGndDm1SGxwZaZT+ugScfyhbIAjoOnbF2Pc29HHx6EJCL2tR\nZLfbOXnypCdRglwup3PnzjVc5eNGITQ0lClTpngyKZaWlmK1Wvn88889tZGSk5PRaDT1PdRris1m\nY9WqVbz33nueYtsA/v7+vPjiizz//PMNzgXRx5XTrVs3BEFAkiTKyso4c+YMTqezwcbb6nQ6nnvu\nOQwGA//617/IyMjAbrezcOFCUlNTGTduHA8++CByuZyy46fd9XmrIf2LeUSNfghNVAS5K9dVuxDV\nRIbR7qOpGG9qjemLT6/1rVWL3W5n69atzJgxg5UrV3qyKhqNRkaOHMnrr7/um5c+fFwl6enpvPDC\nC6SlpaFWq9m8eTMTJ04kOTmZvn371qqPGgVicnKy59+ZmZlERESwa9cu3nrrLcBdVHj27Nk1CsTE\n+Hj++9ZrsHI+Qrd+SHvWUu2q+VJCIlElJF1RPJuPuiM4OJjXXnuNoKAgZsyYQWFhIQ6Hg9WrV5Oa\nmsqzzz7LM888U20wfkNDJpOhCwr2OiZJEq6OPchMT+frHxewa9duXnh4BEFlJYgOOzKd/pJYxKq/\n6/79BlC6YmmV4tCvz63gclCyqIo4EUnCsns7lt3b0XfrScDgocg9apKnAAAgAElEQVQVyvO1HZVo\ngkNQ+/lXKRotFgsHDx70vI6Li/Pt3v7JCAwMZPz48URGRvLmm296EhJt376dl156iUOHDjFmzJhr\n4pbSEMjPz2f27Nl8/vnnnDlzsZxMWFgYb775Jo888ogvIc2fjMjISGJiYjyZaQ8ePIjFYvGUfGmI\nBAQEMHr0aIKCgpg4cSLZ2dm4XC527NhBWloaKSkpTJgwAUdxca36y5j1HcYu7Wk6/mmsOflkLVmJ\ns7jUfVIQaDSgN40fvpeAls0wxkTVOnvqtWT27Nl8/PHHHD9+3FMHMjAwkOeee46xY8d6XOR8+GhI\nCFybEhUCdZOkZvz48YwePZrk5GRuv/12AJ577jmee+65aycQL/DAAw+Qm5vLv//9bx5//HHPrlxw\ncLDHPaI63n7xWSIObUaSJOwHdqJq3wcpZWPtTLYhkWgHPIA+NLLmtj7qFUEQCA4OZvz48XTu3JmR\nI0eSlZWFy+Xi2LFjTJw4kVmzZvH555/TrVu3mjtsoFitVr799lvefvtt0tLScLlc/Pjjj7z58ksM\ndzjxv2UgJct+vniBIIBC4U4680cEAXlAAM6CyueQvntPREsZ1v17qh2POrE52rbtEctKyJ3+D0Sz\n6eK5Vm0x3pqMNjYefXhEhU0Wq9XK8ePHPa9vvvlm30bMnxCdTsfIkSNp3bo1L730Etu3bwfcSTKm\nTZvG8uXLmTFjBj169KjnkV4dW7Zs4eWXXyYlJcXjugZuC9MHH3xAx44dG6xVyceVI5fL6d69u0cg\nHj58GKvV2qAFIoCfnx8PPvggvXv35pFHHmHTpk0AFBcXU55fwI7vf6Sxs/YeISU791Gycx+q8FCi\n7xmMXO+O/w/u1Y3QDm1R11PccUpKCuPGjWPPnj1YrRc9yBo1asTs2bMZMGAAKpWqwboE+/BxI1FY\nWOgx8F2YUzExMThq8ET4I7UWiD/88IPHTfCPRbtrW8A7JvOEx+VBzMvClrIDdacBSBknIPMslVpY\n1DqEZu1RJ3XBLzLW9+C4QRAEAbVazW233caePXsYMWIE27Ztw2q1YrVa2b9/P4MGDeLFF19k1KhR\nREZG3jALNpPJxMmTJ5kyZQorVqzwqrUVGBiIU6sn8r4ROLIzcJlNmNatAsCybzf6jl0w79jq1Z82\nqS3lh/ZX+l4yfwPKsHBKly+qdkz+/ZMRzSWULfuxUrci25ED5B45gMwYQKPRzxPYrgMKxcXP22Qy\neQnEW265peYPwscNiUKhoFu3bnz77bdMmDCB5cuXY7Vasdvt7Nixg759+/L444/z6quvEh4ejlqt\nbvDPXUmSsNlsZGdn83//93/MmjXLa15qNBoGDx7Me++9R3x8fD2O1Mf1pm/fvsyf7y4ldOLECU/M\naUNHoVDQuHFjli5dyjvvvEOESk1zlQ7lms3Y138JT4287D7t2blkzv3B8zp8QF80/v7XcNQ143A4\nyMzMZM6cOXz44YeeRDTgnpc9evTgm2++ISIiok7H5cPHZSOJ1ygGsW4siAaDgW3bttG9e3fPsQMH\nDniVuqiJGgXioUOHCA4OJiIighYtWiCKInq9HrvdjkqlIicnx1P4tTokUzHoL8a4SEV5WH/7GXnj\npihu6otgLwdLKZLLiaBSgyEE0WLGvnc7spgWCNENe5Hio3IiIiL4/vvv+fDDD/n55585ffo0LpeL\nkpIS3n77bVauXMnDDz9Mt27dSEpKapBxUJIkkZ+fz/79+/nll1/4/vvvvUpCKJVKevTowSOPPMLw\n4cPx9/eHwEC0jcLJbxRG0c8/4Dh3Fn2XHhUEorppc4oXLaj0ff1u7o1p87pqx+bfPxnHudM4fq9F\nFjqnk5L1qxABXXQsSp0etZ8/R48exWRyWxzlcjl9+vSpuS8fNzTx8fHMmjWLjz76iMWLF3P48GEc\nDgcOh4P//Oc/bN68mYceeog+ffrQoUOHOs1CfDmUl5ezf/9+1q1bx7x58zh69GKCDqVSSevWrbnr\nrrt48cUXG7wlycfV07dvX08cYnFxMadPn76hMmH6+/sz7s6hHHthEo68fOznj8vUKrcXyhUmuNA3\nT8S/cd3VtbXZbBw6dIgdO3bw9ddfs2fPHs+mjVwuJzExkXvvvZfnn3++VutHHz7qnRtMIL722ms8\n++yzhIeHk5WVxb333kteXh4zZ86sdR81CsTdu3eTmZnJpEmTyM/Px2Kx0KtXL3799VfuvPNOVq5c\nSa9eva7wFiRcqSdwpZ4AjQ6Z3h/kCiSbFalsh6dmnOPMUVzNkxpkBkwfNRMWFsbkyZMZMGAAc+fO\n5ccff8RqteJwONi+fTs7d+6kbdu23H777dxxxx20b9++wSxIS0tLWbt2LYsXL2bVqlVepSAAmjRp\nwujRo7n//vtp2rSp1zl9SAjqocMxdOiM5cQxyk+fQJPUFuvhAxcbVfWDLwjIDUbE0qpjT9QtkhBL\nC2sUh8rG8WjbdUKyWbEfO0Dx159SLAjIDAH49x2EweWgebNmHD9xgqioKF9Wx78IAQEBTJkyhcGD\nB/P1118zf/58cnNzAbd73htvvEFiYiLJycnccccddOvW7bJ2H68ndrud3bt3s3jxYpYvX86JEye8\nXGcaNWrEfffdx6hRo+jUqVM9jtRHXRIXF0doaKhnA2/Dhg3079+/nkdVOyRJIndvCkfG/A2XyeR1\nrnT7bgJ6dKZ4y84r6rvx04+hD7v+Qsxut3P48GGWLFnC4sWLOXTokJc1X6VSMXz4cEaPHk3Xrl0b\nzO+8Dx9/Njp27MjatWvZvXs3ZWVlhIaG0q5du8uqb12jQHzwwQeZNGkSI0aMwGaz8eabb5KUlMTE\niRNZsGABkZGRDB069KpuBACrBdFauTuIK+0Upvx8jL7EGTcsOp2Ofv36kZSUxPDhw3nrrbfYvXs3\nkiQhiiIpKSkcPXqUBQsWkJSUxJAhQxg2bBiBgYF1PlZRFDl69CgLFy5k1apVnDlzhpycHE9APbjT\ncd99992MHTuWjh07Vmn5VKhUBDZtTkBiM8y5uVjycsif/R9sNYg6VZN4bL+fqLaNNqktZUvmV91A\nJsM/+R5cuRmYVy0G0buGllhSRNG8fxOu92fZ+9Moc0mIFhP5m9YgUypRBIegi25SbYIbHzc+HTt2\nJCEhgYEDB/Lee++xcaO7XqfL5eL48eOcPn2aRYsW0aJFC5KTk7nnnnuIjIys8+/EBUv+kiVLWLp0\nKYcOHeLcuXOeLIgX6Nq1K6+++iq9e/eul+eHj/pDLpfToUMHVqxYAcC6ddV7YDQkStPSOfLi3yuI\nQ4DSXfuIeeHpKxKIcn8/AtolXdf5ajabWbZsGYsXL2bfvn2kpaVRfknStTZt2vCPf/yDHj16EBp6\neZm2ffiod0SxwhrqivupI44fP47ZbEaSJHJycli1yh3yNGTIkFpdX6NAVKvVTJ8+vcLx2bNnX+ZQ\nrwK7FXNqKgbfQ+WGRhAEwsLCGDx4MH369OGHH35g2rRppKamAm63lNOnT3P69GmWLVvG+PHjueee\ne3jooYe4+eabr/tuo9VqZdGiRcyZM4dt27ZhsVgQK5nMPXr0YOrUqfTq1Qu5XF6r76QgCPiFhaEP\nDUX90kTyfvyesk3r3G5DleC2HlZdN1EeHIKrqJpC0IKA4c7hlO/ciJifU3kbmRx9v9tBocC6eRXa\nArf16I82S1WzJPz7DkIf3xxdiM8V6M+IIAgEBgaSnJzMbbfdxuLFi3njjTc4duwYAE6nk7Nnz3L2\n7FlWrVrFpEmTGDx4MA899BD9+vVzu1RfR2w2G1u3buXbb79l0aJFFBcXVzovmzZtyuTJk3nggQdQ\nKBS+34q/IDKZjD59+ngE4u7du7FYLA3G8l0VkiRRcvQ4tvTMqhpQvGkbEQ/eTdb3i2vdr6CQ0+az\ndwlqnniNRnoRh8PB/v37+eabb/j2228pKiry2kS9QGRkJBMmTOCxxx4jICDANy99+KgDxo8fz/bt\n22ncuLFX0kFBEK6dQGwQqFTYc3Kwlpai9cWR3PAIgoC/vz9PPvkkd911F7NmzWLevHlkZGRQVlbm\nsSqWlJQwZ84c5syZQ1BQEF27dqV///706NGDwMBANBoNWq0WjUaDWq1GoVBUmX3T6XTicDiw2WxY\nrVbKy8spLy8nMzOTLVu2sGXLFjZt2uSVXe0CSqWS4OBg2rdvz7PPPssdd9xxVfdujGmM5qlxmAYN\npjw1FU3LJKxHD1/asFpfdX3n7li2rK36fJ/bsKbsqFocKpX43zEcy+bfEAvzq+zHfuIwBScOY76p\nK8FDH8YvMtpzHz7+XAiCgFKp5L777mPgwIF89913zJ07lxMnTlBcXOyZlyaTifnz5zN//nwMBgOd\nO3fmlltu4ZZbbsFoNKLVar3mZXUJqERRxOFweOZjeXk5NpuNkpISNm/ezObNm9m6dWulmbIvCNum\nTZvy6KOPMmLECF+c4V8cQRDo1q0bKpUKu92OzWZj7dq1V/XMrguspWVkfPdTtW3K9qSgMPoTMeIe\nsr79udq2ADKdlvA3XyZVJWA6dgyNRuP5zdRqtdXWI5YkCbvd7kksV15ejtVqpaioiD179rB+/Xp2\n7NjhKZfj9b4yGX5+fkRHR/Pggw/yxBNP/GnK5/j46yKJItI1sP5diz5qw86dO1m1atVVbY7dGALR\nEIKjoID0LTvYVZxf6e6xjxuXmJgYRo4c6UmWUV5eXiEVb2FhIStWrGDFihWoVCpCQ0OJjo4mMjKS\nqKgoQkNDMRqNaDQarx+stLQ05s6di91up6ioiJycHDIzM0lPTycjI4OCgoIqv0+BgYEkJSXRuXNn\nbr31Vnr37n3NrCVqvR/qVm1wNW+FTKetIBBFkwmZX9XvJShVSNbK6yaiUCL3N2DNTKviYgH/5Hsx\nr1uOVFa1ldLTXVwz5BExlOzaTKlShUyhRKbTo46MQR/TBGU1Cw0fNyYGg4Gnn36aIUOGsHLlSjZt\n2kRKSgonT570qp1WWlrKmjVrWLNmDYIgEB4eTlRUFNHR0V7z0mKxeOIbAfLy8vj555/R6XQUFhaS\nnp5Oeno6586dIysri7y8vCozZPv5+dG0aVPatWtH3759GTBgAJGRvhJIPtwCsVGjRiQkJHgSFv36\n668NXiCaUtMo3ritxnZFazfh36Et8a+Mo2TPAQrWbYFLrHYKoz+KO/qTFeTH4y8/T0FBAYGBgZ7f\nypiYGKKioggJCUGhUJCRkeG5VpIkvvzyS5xOJ0VFRWRmZpKRkeE1L6tLk69SqdDr9SQlJXHXXXcR\nGRnJ2rVVb2T6+Gvhcrm8EondUEiua+NiKl2DPmpBdHT0VdcbvyEEoqgx4iospPzcAbLtJibP+Fd9\nD8nHdaI24t9ut3sWlJdyIYPdBfbu3cvevXtrXY5FpVLRsmVLevXqRa9evWjTpg0JCQnV7rZeDXK5\nHP+mLShoFIoz7+IC2nb2NIF334vtyIFqrq4cbfsuWA9UHauiTmqP9fDeGsWhonEimtYdsJ86iumX\nSkpoyBXou/dF37U3+iaJOEqLER0OBEGGXKtFGxxSqUX3wv+FzwrZ8ImKiuLxxx/ngQce4MiRIxw4\ncIANGzawfft2T0biC0iSRFZWFllZWezevdurn0vn5alTp5g0aRIOh6NWc1MQBBISEujRowd9+vSh\nbdu2JCUl+ZJc+KhAYGAgrVq18ixEN2zYgMPhaNCllFyWKjb7KqFs7wHK9h5A36YVcS88gehwgiQh\nM/iT7bSTkpPJR9/M8RJ+BQUFFBQUcPDgQa++Lv1MJEniqaeeqvXvZWVYrVb27dvHvn37rrgPH39e\nLo0Z93FtWbp0KQCdO3dm9OjRJCcn4+fn59WmwbmYClodcPmWPyE8htIDh5CFxeLIL6B9YhMkSaoQ\nAO3DB1Ssy1mbH7rg4GA6duxInz596Nu3LxEREQQFBWEwGOpExPhFRBLx/ETS356MdOF77XQi2uwI\nWh1S+eXV8lJGRmPfv73q83GJmJdX786katkOeWAIZUt+qKaVhKvcjOXYIUo2/Eb53h1uq6ZMhjwg\nCMNtQ9A1T0IfG4dCpaIsPR3L2d9xlhQj2u3ItTpUYWH4NYlHGxTk+awlSaK8qBhLdrb7M5DLUfjp\n8Y+NueodMR9Xhk6no1OnTrRv35677rrLY13YsGEDa9asYdeuXdXWnLt0HoqiWONCQavV0rp1a7p3\n787tt99OYmIigYGBBAQE+DJa+6iSoKAg2rRpw8KFCwFIT0/n5MmTtGrVqp5HVhFRFDHn5GA3mWtu\nfAnmg0cwHzzieR099gkS770DY14eskZBrFmzhh07dlBYWFhlH5VZA69GHPoW/z7+tNRxkpolS5Yw\na9YsFAoFzz//fK3Ljy1Y4F02bfny5V6vG2QMoqxVNzi2teaGXhfJIK4tzlNrsZzdj2AwULZyEx/9\nYyrPTnrl+gzUxw2NJEleVg2ZTOZJJCOXywkODiYxMZHExEQ6d+5M586dadmyZb3WXxQEgaCk1vDa\nP8ic/jauEneaGNPWjei79ca07tcK1zhyc1BEROPMqmhFxeWseOw88kZhuPJzqzwPoIhNQB7UCMvG\nVVWPWafH77ahmLasw7xts/dJUcRVmE/RD3Mo1ugw3D8KZ24+hUsX4SqpaLXUJCQSfPcw/Fu3xVVu\npezocTK+mY/5wCFPG5leR8SD9xHUqwfGpolojAYkSaI0KwdrQRGi3Y5MpUITFIAhMtxnnbxOXJhD\nF+ZR7969mTx5Mlarld27d7Nz504OHDjAyZMnOXXqFMXF7u+yJEk4nU78/f0ZOjiZxpERKORysgsK\nWLpqNXa7nVatWtG2bVvatGlD+/btadWqVYOsi+qjYaNWq0lISCAgIIDi4mJsNhvbtm1rUALRYbNR\ncvI0xfsPkjHra4KTB151n9rwUJo0aUJcXBxdunTh5Zdfxmq1curUKfbu3UtKSgpHjhzh6NGj5OXl\necpPuFwuL8+dC5svvmeoj+uBKIo3ZJiY5HIhVZKE6Ur6qYni4mI+/fRTFi9ejNlsZubMmbUWiPPm\nzbvaIXqoM4FokqkJa9cTcf/mmhsDCDJknQeQM/9H9Df3I+PdfxP60L0UHVhN+7tvZ+u6DVjryJfX\nR8PH4XBQVlaGxWJh7NixFBUVATBixAheffVVGjVqREBAQIN1M5LJZAS3aYfizXewHD9GweIfcWa7\nM9qp4hKxnznl1d6yZwcBg++mrDKBWA3qFm2xpuyoto2mTcdqLYeCWoPfwHso+d/8quMgOS8iBw0j\nd9aXlQrDC1hPnyLnu3mU3zaEcx9/gauktEIb0Wwh46v/kvHVfwkdMZzAfn0pPfE7xz+ehfnsOU87\nXeNoWjz/BCEd2qBuFIKlqBiXzY5cqUQbaCQgwl0qx+lwYCkpw2Wzo9Co0BoNDfa7cSOg0Wjo2bMn\nPXv29DrucDgoLCwkJzubsym7CZPshOecQTKVgCQhxAUw+csP0SQmoYuMQanR+hamPq6a+Ph4oqKi\nvATiyJEjG4Tl2ZSTQ/qPi0n/Yg7SeQue+dhx/Nu3oWzfwRqurhq/5okV5o5Go6F169a0bt2aRx99\n1HPcarWSl5dHRkYGH3/8Md999x3gds9955138Pf3x2g0XrfQCh9/TURR5Oeff+aLL76o76E0aLZu\n3erJ3K/VannrrbfqZRx1JhA3pBwgLCoMvy63IR3ehmQuq7pxQDCyFl3I/WkRcmMAphNnQRSRBRhx\nmsyY0zIIDAqg09Bk32LCRwUmTJjgEYhRUVEkJCRcVnHQ+kIQBALiEjA2icfYoTOWc2dxmc3oOnSm\ndOVSrIdSLjZ2OhCdTgSNtqJIq8ZFSNDqkcqrdmeSRzfBkfp7tePU3XoHpb8srFYcolDgN+ge8r6d\nh1iN6yG4S3boe/Tj7DszwFX9zqJ/l05Y7RIb73sS0WqrcN5lKafg+CnyzmVy4teNZO+5uOAKaplI\nzzdeRJIkTixby7kde3FYylH56Ynr241Wdw8krFUzynPzKEtNx2W1I8hkqAIMGONjceTmY88vQHQ4\nkCmVqCPDUfrrkazlSE4XglKJOjgYv7DKy/G4XC5cTqfb2qlWoVAoK8RoOuw2rPm5SA47CCAoVGhC\nQlEoVUiShCRJCILg+buAKIpYC3NxWcrcFmSZHJlaizokHIWiovCVJAmH1YLocLuEyZTq6yLOFAoF\neslJ8Ik9+B/ZDC6nV6CBZC2n/LdFlK9ejDmpI/633Il/TBPfc93HVdG8eXMSEhI4fPgwoihy+PBh\n0tPTady4cb2Oy5STy+mP/0Puwv95HS/dtpPIJ0ZesUAM6NkV42WUstBoNMTExBAaGkpsbKznuE6n\n46mnnrqiMfjwURNOp5OUlJSaGzZERPHa1DCsRR8ZGRmUl5fzzDPPUFZWxtixY+nevfvVv/dlUmcC\ncepHH3HXgh+xb1qPNiEeTYtQyD4NRblIdjuCWo0QGo0UFIXlTBolX85GGR6BIq4VmTO/QtssgfzD\n5wuHywR2fTibJj27YggNqatb8OGjThAEAX1oKPrQi3UHDU3iKTt5jOJfl2I74Y47MW9eh2HQ3ZT+\n7wdvUai88l1fTVIHTCsXVXleFhCEq7gI0VTNBg+g7dCdol9/rVEcAhgHDCb1w//UKA79OtyEMzCE\n3z+ZU+l5Q+sWBNzWj+2f/BdrkbfFMrBpE1o9dDdrJr9PwYkzFa5V++kJigjlzPeLObfkN1w2t/hM\nuDeZkKZxZHw6i9Lte9zjaNOSRrf3pXR/CiVr1+Esvlg5Uh0TTcQjI/Bv2xpdZCSCJOFy2LFmpGE5\nsAfbycNIdhuCTo++x60oG4UhV6tBrkA0FeM8noLj8G5PrIMsJhFr6y7gsIKpBEQXgt6APDIOQS5H\ncjndbQuz4MRuBPtF0e6UK7C36o4Q1gSZTIYgE0CuRHS5EErz4ex+BLsFEJA0eqxxNyEPjkQdFOaJ\n9RRFEVtpEaLTbemQK1Wo/AOqLCdzKaasdIp/mo0z7VT1DSUJ+6HdFGWmIj00FkPjeJ9I9HHFXIhD\nXLlyJTabjczMTA4ePFivAtHpcJCxaEkFcQiAKOIsLUUV1gh7TsWSLjUR/diDaAyGazBKHz581DeS\nJFFcXMxnn31Geno6jz76KOvWravzcdSZQBRFkR9Xr+b+mDgcxSaKVqxA16IlqqhYZFoNLrMF6/5T\nWE8sR1Cq0He7GZegJW3mVwAE9O/LvhlfAu61cPbuA5zdvpfWd/Sv9WLFh48bFX1YOLrQMIxt2mNO\n/R1nQb7bgqjVEfDQExR/95VHJDrOnUUe1RhXRmqFfiRzGTJ/I2JpcYVzgFtsVOMjr+nQA9OG32oc\nr6xRBPZzVccwXkCd0JSS3fs9rlZVITf4o2rblsPvflbpeb8Wieh6dmPDP2dWOBfYNI6mw25nzeTp\nldYgajaoDxFNojj67qdex9u9+ASOPSlkLr94v2HDBqMK0JL33bcVdgIFtRp9myScpYXk//gduJzo\nO3bEumsjjjMnAZAZA9F16YVMq8W2YzXlBXno+t+F6/hepPysi30FhqJs3wMx/RTO9Qs9/7fy5h0Q\n/Iy49m9wlzMJCIaTexG4JDlTaGOIiEOwlCBsWYjktCM264zgtCLLPIFwSbC9UF6KVJKLI7IZ9uDG\noDciuByQdw7OHACbW0g6NDpszTohC49D7heAaLWct1jKkKk0qI1B7veXJGwlRZT8Mr9mcfgHxMI8\nin/8EtnD4/CPiK71dT58/BFBEOjevTt6vR6bzUZ2djZHjhwhOTm53tYLJadOk/757CrP5y9aStSz\nT5L6wX8QLyMJX+y4Jwjp0sG3oeLDx/VEukZJaqqpb32BkJAQ2rdvjyAIxMTEoNfrKSwsJCgoqMZr\n9+7dW2ObDh061GqodZoS8IM5s3n4h5/I/vgrQm4bhEKjwHJkP67SUneaZn8DxjvuwemQyF22hvLT\n7p3+gNv6kbP/KKLdgaBUwPk4grSN29GFBpHQtaPv4ejjT48gCGiNRrRt23sdd9psqCOiKFm5BOuh\nfZSn7MIw+B7MlQhE66G9aG7qQvnmKkReDQnsBLWmxqyqipg4yk+crL6j82hv6kTax7NqbBfQ/xZO\n/ffHSs/JVEpC7xnMmtenVzin1Oto9fBQ1k75oFJxGHtzR8Kjw/n9kr5bP/Mo1s3bsBw54TkWOnQQ\nMslK0YoNFfrRt21NcN+bMW9dT9mBrSgahWEcOIiyhXM9glvZOAFt+y7Yt68+n+1Vjm7QvTj3rgeL\n6eL9hEahaNYW17YVf7AMCyi63Aq5Z2H/EYiIR+7nj3ByT4WxSIkdEJxWhCObEXD/l0oteyDL/R1Z\nWX6F9qJajxjV0v27lXYMlP5w9gDknOXSp6rksCGWFSPajuHMPgs5579jKi1SQjushiCkghwkqwkx\nMArH8f0V3q8mxJwMbGdP4hcedc2f65VlaHS5XLjsdgSFArlcjkwmq1CKxV5uwVleDkjINTrUOp3v\nN6eB07NnT4xGI4WFhdjtdg4cOEBBQQGNGjWq87FIkkTJwSOItopu8RcQbTay5n5D45ee4ty/5+As\nqrlGbeOXnqHxg8PQGo3Xcrg+fPi4BEl0IV0DgVibPm6++WYmTZrEk08+SXFxMRaLpVbiEGD8+PHV\nnhcEgTVr1tSqrzoViGazmZ2FuXQZ+SCp73yAZHdg6NoeVXATEASsRcXkfPYN4h9qAgUOupVyQUH6\nCncmx4jb+nB8mbvwqjW/iOV/m8rw/84gvGl8Xd6KDx8NBoVaTchNnTA0bYn53BnKTxxFUihQNknE\ncdbbeiOWFCHzN4IgVBGrWI1CVCoRa1FyQ928Nfk/L66xnaBU4TSVV2uxdDcUEAICsWZX7noVOqAv\n+79bUun9NLtnEHu++qFScSjIZLQa2JvD73zidTygZSLKkmJK/iAOtfGN0YYHUfC/JRX6MXTphF+z\nxpT87E70IKjUBCQPxrRsvmfHURHdBG2bm7CtX+q5TtOjP6PD7aoAACAASURBVM79m73EoeBnRNGi\nPa6d3tZXRce+kHECoTgXFCpkUfEIhzZVGIsUfxOCuQhZ/sXEPVLjNsgK0ioXh8YwXMGxcGgbuBzQ\n/hY4vQ9ZeSWJgnRGSGgPh7eD9eKYpaYdkWQypJP7oNx9XAqJxpZ1+a5yFzBv+hV9i7ZoA4MrPe+w\n2Sg+cZryjMzzpVBkKAOMGJomog8N8RJvDoeD7KOnKDx7Drnowp6Xj1ypRBdowJWTQ9muPTjLTPh3\naIdfiwQkcxmuslJkBiOayEhcZSWYtqxDLHbHNcsMRoy334WyUSgKpQIkEFQqNMGhqP38fMKxgWA0\nGunSpQtnzrg3mg8dOkRmZma9CERzfgEZX39XYztnUTEZn39FxIjhiDYHectWYc/K8WojqFSEDRtC\n6OABBLdtjcbgf72G7cOHj3ogLCyMgQMHMnz4cARB4I033qj1tWvXrr1m46jzomJZ2dmou/Uk6KHh\nCKYyCn9ZhbPoEnc3QcC/awf8Oncka8c+MldfzHzqn9SC/IXnF08ClGXnkpFyhLDEON8Ps4+/LIIg\noPbzQ92yDWLzJERRpKxVWwrmfIzjnHfMnf3YQVStbsJ+uJJCxtVk+ROUKiR71TvgnnZyhTvJSg3I\n/f2x51UULZeib9OKnG0VLWUX0LZIJH/B8krP+cdGUZyaUem5+Ft7kL26osiKG3wrBV96p4oOHTKA\nwiUVYzPVsTEY2rag7NeLcUV+3W7GsnXNRXcUhRJ9995Yf/vD9QolMo0Gscz72ado0xXXXu9YAyG8\nMUJ5CRS7y5MI8a0RzlRMZiEZGyHI8BaHggD+AciyjlZoL/qH4DJGQsp5i2iLznD2YOXiUOMH8TfB\n3rVeLjJSqx6IGacg/5LPOLQJzn1Vx7LWhJibiTXzXAWBaC0ppeDAYXKX/0bOwqVIl9Rd0zVvSsyT\njxDQrjX+TWI5u2Mfp9ZuwU+nwXriNLm/baDl2MdwpJ8jbcOm85uUHQkZ0AvLvl3krnUL+MDBQxDz\nLeT/sgDpD1YfbdsOaJq3xHY0hdLvtnvNB1WLNhj63o4qKgZBAtHpcNfw1OjQhjTyhULUA0OGDGH+\n/PkAnDp1itTUVNq0aVPn/xeO0lJsqedqbgiI5VayZn2N3E9P8G23oggORnI4kOt06OKaoG8SQ0DT\nBJQ3QOI1Hz7+NNRhkhqA4cOHM3z48MvufvLkyTW2+ec//1mrvuql6nRIUgsy1mzmzIJfiBuWjC7A\n4KndJgGSQknmxp0cf/sTL6tA7P13cXrNxVqKmpAgygtL2PLRbGK6tCO0cUxd34oPHw0OmUyGTCYj\noEkC8jEvU7xuBeZNq+B8nJ/91FH8Bg7FmZeNmJvlda1kcydQkSwVM51KVisyjbYWI6hdoWVBpUKy\n1SwklY0aYd5auauivkkMOccrJp0BCOvYhvSdVbs4xnXvyPF/ecc0Kv31KBwOr5hImU6LTCF4CYUL\nhAzqT9klSX1U0VGYD/7hOXVTF+wp2/nj56JK6ojr1AHvzpQq9yaX0zseUx7XAg5u9LwWDEEIaYcr\n3lBMc4STu7yPhccjy634+UiCDFdEc9h93tVYrgC1FpmpYlFtCaBpZ9h3iThMbI+YebqiOAQkp7Pa\nbLq1wVXm7WJnys7h7Nc/cO6zquO4LMdPcnz8G/h364wqeSBbP5pN5/uSOT393wDcNPkFChf8hPP8\nxkRQ/75owowU/fitp4+gocNw/H7Mu7SMIGAcMgxX+u+Yl3sXIgYQNFoUjcKxpp+lbP1y7KePeRYC\nMmMQ/gPuRJPYEn10LAqV+nyXgm9T8zqTnJyMwWCgtLQUs9nMmjVruO222+q0vqYkSYgul3tOXAYu\nk5m8ny96LPi1a03CE4+i1tbmGezDh4+/ImFhYdesr3oRiBqjgRajHsBaUMyx/3xTq2uihyZTUmYm\nfctuzzF1gAGHpZyMnSmcWLsFVfKtBITVvfuIDx8NEUEQMETHontgFKabb8H6+0lMW1YjmsooT9mB\nrs9ArHu34Txz0ZXSum8b2o49sGyqJEZRdCHT6mp8X9FajtzfgKusoiXKq53ZjLKJX833oVLhqkJI\naiLDyDiTVum5oGZxnFq3vdJzcrUKzBVFcETPLpRt2uZ1LPjWnpRuqVi/Ve7vD06bl4usKj4R5znv\nMiGq6Mb/z955h0dxnfv/M7O9qgv1RhECgeiY3pvBYHBPXGMnTlzSbux7/bupTm5ubpod3zh24o5z\nY9xNtU031RRRRW8qqKC+2t5mfn+skFjtiioDwvN5Hj9mp5w5WzRzvud9z/fFezxcqKqSUgh2iAKq\n+w4m2OE4DCYEn6ddbMUmIdgiUzdljQ5BCkaYz8jxaYjHtkYcLyXnwYlzrp+ZD6ePRBwHIMelQk1p\n+AJ9tQZZo4e66HU4r0watrYRbB9QuxqbOPnKQipfu/DzQp0YD0OHsOpnf2LiE/dx7H9eBFlmwNPf\no+n9dnFoHlKEITUW+/r29RiWseMJVJZG1B2NmXs7vpIdBGsixbAqIRnjhBm41n+KZIsU2FJLE679\nOwm6XTj37URyuxAAVWw8uuw8jJk56K2xilj8CoiLi2P69Ol88MEHAHz++ef86le/uioCUZIkbKdK\ncRw/TsAfQDTokdyey25PHR+HSqnVqqBwTZAlqYvWIHZBFPI8PPHEE+fd//vf//6i27omAhEgPjuT\nzPk3o89IpXrZqrD1PudiLehN2pxplG7dTek5qaYpw4so/bI9Ra7+aClba99n0pMPoTcqM2wKCmdR\na7TE5vVGzu3FKb2F1/7+MsGgROWfXuT3z/6S9BkqHBtX4T24O7RGMSYuFN3zRYqyYGMtqsQeBOvP\nRLlSCO/eHVjGjaN5xfLz9itob8GceuHZLsnlQmM146mOvKao1xGoaYp6ntZswueIXvNRH2vF2xjp\n5KqPj8V3IDwdU5eSjK0k0hksftpk3Ds2hx+blYO/tD26p0pORWqoiThXkCMfNKIlhuCxcIGhyikI\nF24GM7iilBhJ64VQFcUYSApEGM0ASNYkOHZOBDMmEbEqukAkJQ/2bQjbJGcVIEdJcz1LV2gdobXU\nhizL1G7edlHiECDhkQdY/MwfGPPkg5x8/hWQZUzZ6dBYj7+2PaU5YeKosMghgoChZx62j98Ja884\nfBSB0iNRxaEYE4dx3DQcSxdFdbhTZ+WhLxqBt2Q39iWLIjsrqjBMmIkuNx9BJSKKKkStFm2PVIw9\nUnBWVRFwOJCDwVDtzcREDPHxbTUxoT1jQCE6DzzwAB999BGSJHHkyBH27NnDxIkTv7LrybJM4+Ej\nNGzYyJlF7xG0OzAOKMQyuAjblm2X3W78+DGozrMEQEFB4StEDnaRi2kXtHERVFdX87e//Y2Kigqk\nVlHqcrmoqanh6aefvqg2rplAFASBpPw81v/n74nNyaDP7Kn46xrwNTYhyzK6+Dg0yUnU7D/Chv95\nGckXnnaVM2siq375fFh7n/30T/SeeBO9Rl6chauCwtcJQRD4y19fbFuTk5eXR06/QmJiYogpGIDz\ndDlBRwsyMpp7v0fTm3+NuCF6dn2Jcdx07Cs6X18WbG7EkJR4HiOcdmR7E5oeSfjPU/vLdfgISSOH\nYj9yIvJadic6a/QopM/hRGs24W1xRN0fFQE6xr9EnSZqGQ5NnBVfU7igEw0GAp52ky1VfCJSU5T3\ndpEKSjCYwgWhIEZ/wBjMUBOlnESU68gGK9gawjd28uCT1Rrw+yK/R3Ms2KMLcwBBpQqlrQYvLa3u\nXFStJTOc9Q2U/z167cuOxN86m/rGFhBEdLJE0BNKC86+dSa2Je3pesZ+ffF2iBIa+g/AcyQydVeX\nm4dzeWRaKYBpyhwcy9+N+vlpevdHnZKB/ZMo5iQqFcax00FrwLlrO82LP2rbpe3ZB8OgEdQ022lc\nuoygPfT9q+PjiZl9CxgtNH65G29tHca8bMyDCvH5AghqNZpYKwGvF0GtwRBrxRAfS2xmKjqjsc2h\n9evGmDFjyM7ObjOrWbhw4VcmEGVZpnbPXo7/v5/hP2d9tWt/CSkPPXjZAlHQaokZUKhEmRUUFC6K\np59+mszMTObOnctzzz3H97//fT799NNLMry5ZgIRIDY9lRl/fZYPbv02x5asQh8Xgz4+ZNfsabRF\nFLs+S/8Hb+fQp+vDQ7WigCxJHF27hdxhRcpMm4JCB+rr61m5st0dc/r06eh0OgRBQGsyo83v17Yv\n4PejMppoePW5UEmGVmSvB7weNFm5+Mujr/0D8B0twTR8BM7t5x8QObZuJPHmaVS/0bnDn/9MHXFZ\nqVH32Y+eIP22uWGp52dpOl5KcmE+9qrIyKOnuQVdfGzk9qYWDPGx+OvbhV+gxYnKZGobqLcRZbAm\neb0IWl3ocyJk7IMvShTzYnMwhbOFKlrxecAUxbVQFKMvfo9yHVlvjhR3nQ08dSZwdUgVVqmRvReo\n01Z9PGSEtD/ye7kYVBl5GNKyALAdOYaz5PAFz7GMG40/N489Ly5kwO2zqFka+q2LWi06vYaWc2rL\nJUwei23ZB2Hnm4qKsC8LL3eiycolUBk9hVmT0wvf8YMQZW2ZKiUDTXo2zjXLIvYJegOm6fNp/nQZ\nwYbwyQPThGn4Gh1UvfRKmCiPnXsr7hY3R557A39TM5aB/YibPpEzew9RsuKv5N42G6/Hw6GPVxKb\nk07O+JF46xpoOV6GqFXTY9hA4vvkYclMIy43E0tS0tdGbOj1eqZMmcKrr4ZqKi9fvhybzUZMF5eG\nkGWZ+gMHOfbUMwSaI7MTfLW1aNNS8VVVRzn7/PS4bS6xvXt2RTcVFBQuh6tsUnOl1NbW8vbbIbO9\nV155hTvuuIOpU6fyk5/8hNdeu3BpMYBrOp0oCAJZQ4u4+c0/Yc5IxdNko/lEOc0nyjsVhwO/8w3q\nyquo2Nqe8hWbk4GtKuTwt/H51zm+fXfUelcKCl9nVqxYQVNTSBjodDqmTJmCrhMnPLVGQ8LgE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EEeMXPs+ZDds4/s+PCHq87P7Dy/T+xq2kThqLfcNWHHtKKP3TP8h6/EF8FeXYNm7EsXsvhpxs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\ndheTmsOHOzF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yoFEjByIFomnocNx7I9fnazKy0KZn4Nq8Nuq1NFl5xNz2TbRZ2bjWLcO1\nejHOTz/AtugVGv7+B6p//ww1S96l6dihNrfWa8HUkcNJ2rL2vOuDZJ8X+2efkPzAA4itJjYXIuH2\nO0m9/U4MsUras4KCQveiW0YQITQT2m/mBDa8+DZNZZXYKs9c9LkjvjGXxi+2RmwvX7mR3DHDaVge\nmr2uXbaK7O89QPmRE2HHBVsciOe4mnnKK/E2NkH6+dd2KCh8VTz33HNUVlYCoNfreeyxx65xjxQU\nzo+gUhM3aCT69Gy81RW4t60jePok/u1rMUy4BffmlUjNjRfVlnHyLcSMmIC6C0xubnQEQSA+Px/x\nl7+i5oP3EE1mUKkgGET2+RCifYaSFOHyDWC6aQyOFR9GvY6u30C0mVk4V7zXeV90eoJuF859O/GU\nn0SlN6IyGND2SMOUenUii7Is4yo9hdRy4RIrkr2FlqXvkzj/VgJ2J7Yv1rdHX88iiljHjSd+6nSs\nBQUYYhRxqKDQ3ZFlqUuif/Jl1FO9VnRbgQiQVdiXb737v7wy/1FaqiML+UajcNYEkk06Kpbvidjn\nbWxqiyACyD4fQa8PldlE0NFhTUaHbBHJqxjVKFwbDh8+zEsvvdT2etSoUcraQ4VugSiKmHqkYUxO\nxdSrH35HS6jWlEqFLq8A17a1eIo3QyelK8S4RMwzbsc6YAg6s/Uq9777IggCsT17Yvrhj2k5dRIB\naHj3/0L7tJrwY7VaJI87og3RGoPsckaNummye6LNzMK9IfoSD1VCEoZRk5BsjXi3r0fu0L5gNGOa\neDP6giJMWbmIooggCG3/70q89hZsK5dd9PGyx03Lsg8QTRbiJk9AMJhRWWJQ6fWIWh26tDQsuXlo\n9HolrVRB4QZBDkrIwS4QiF3QxtWiWwtEQRDoNWIw3132Oit++TwHlq3tdPG7zmJmzEO3obc1U/He\n0s4ajFhj0bhuE7FjhtPw+frz9kXs8FBVULhavPTSS9TXh4pdG41G7rzzTlJSorhEKihcpwiCgM5s\nQWcON6gxZ+XgGj0VT+kxPLu3ILtdoFajTkrDMHQM+rQsjInJykD8MhAEAa1eT2JBPwzJPSDgp+HD\n9/CcPIkmOxd/2amzR567TLQN001jce/YHLVt4/BROJe/G3WfOiMHw8BhuFYt7tTRT5WQjBQM4Ny1\nGfv6ZeBxI5qtaHP7oMvuhSktC3UX1CYE8DQ24jl06eUrJKcdx9pQ6SzrlJlkPPJERM1KBQUFhe7K\nVReIfr8ft9sdNXVEfxkzboIgkDu4kPve+AP7Fi3h9IFjHFy9GXdzC6JGTWx6CkUzx6MN+qlevJKG\nc9YdRlw/IY5Ac0vYNl99I9bB4VW7VBZzWMRQl9oDbZySRqJw9dm9ezcrV65sW78zfPhwJk2ahEaj\nTFgodH80Wh0xub2xZPckMGYqkteNIKpR6XSoVCpFGHYRpoQE0u+8B31OLmfeeZuY8RNpbhWIss+L\naNBHnKMyGpHskWmZmpye+MuiO3urEpIxFA3HtfLjqPsFkwXj5NkESo/h+WJZRHTSu3sLdqMJ97Tb\nUFljEIKBUOqrRos6NgFDWiZaoynUb1lGluW2upCd/VZk/5Vn/wSam68rZ1YFhWuJLMt4PJ6I7ZIk\n4fdHrnHuDshBuYsiiN3nPnHVBeJjjz3GE088EbFdpVLR1NSEXh/5ILoQgiBgjY8jITmBE//7GsNH\nDkJjtSD5/fjqGzn98kKki6hVmDV9PLaPOkQXWx8w55J0y3Tql7e77GU//hAWZf2hwlXG6/Xy4Ycf\ncupUaCBnMpmYM2cO+fn517hnCgpdiyiKaLVa6KKokUIk+pgY0qZOxzpgIM7yMrwnjuHe02pMI6qj\nZthEw1A0DNfqxVH3GUdPwrUyeqkMwRKDcdJs3GsXgy+KS6hKhX7MdARRxLNlFXJzfccWsBcOxTBs\nHHjdBGurkJx2BK0edWIPNOk5GFMykAI+3NWnkZx2CAYIyFce9ROUdFIFhTa8Xi/JyclRJ02CUdYy\nK1yfXHWBGAwGo/5ArvRHIwgCiQMLCLg8VC5ddcnnixo1BrORJps9bLsmPha/LTyqqEtNxlsdMsUR\nNBpihxYp1uoKVxVZlikpKWHFihV4Wy3X+/TpoziXKigoXDaCIGBJScXcIwV9jxRq3ngFZ/F2XPv2\noO8/EE/J3vaDOxOLshQ1dVSMSyTY1BA9rVSlxjR5Dq7VH0G0CINGi3HafLzb1iG3NEXuR0A3agog\n4/zoDWRnS8QRmsFj8KRmETiyl+Cpw+2XLhqwSah8AAAgAElEQVSNaI25KJOaztBlZisCUUHhHBwO\nx7XuQpfydTSpuaFUTWLvPAZ8/1uXdW7W7CnY1myI2B4/cQy2rcVtr5MXzKZp3Za213k/eYy4vr0v\n65oKCpeLx+NhyZIllJSUtG2799576dkzsiyLgoKCwqUgCAKx2TlkPPoEPR59gkBdLfqCgWHHyJIU\n6XgqCJ2WijAMGYVvz7ao+3SFQ/Ds3hxdHIoixqm34t2yKro4FAT0k+fiP3kQ3/Z1keJQENBNmINc\nW4n3s3fDxCGAdGwfljETovbrohAEjH37K5PECgo3MGdNarriv+7CVY8gPv7440yaNCniZioIAjrd\nlVmUi6JInztu4cyXu6hcvfGiz4st6E1iVhrVn68J75NahdpiJtAcmlmMnzoeZJmWXfsASHvgTtLv\nuAXNFfZbQeFSqaqq4pVXXmnL5+/Xrx+PPvroNe6VgoLCjYQ5NRXjzbcQM2w4ztOnsc5ZQMuyjwBw\nbt+KYchI3F92mFjtJJAmaDTI3kg3VABVWhb+Q5F1FgG0/YbgO1CM7LRH3a8bMx1fyXbkhuilrnRj\nZhA4WNzpftnlQBMXC6J43jqInWEoGoo5O/eSz1NQuFHR6XT861//itguSRLr16/n1VdfvQa9UrhU\nrrpAPFvA+6uabYvLzmD0//w/dv72fzn14YoLHp80bCC5k0ZR+eLrEfsSp02kcc1GVFYzKXfOw1dd\nS+3HK9DEx5Lx4B2o3Wfw1VVDSo+v4q0oKERFkiR+85vfUF0dMlxSq9U899xzmEyma9wzBQWFGw1R\nFLGkpGHukYorrydqs5nGRQsJnKlGPWFy+MGyjCB2sqavk5RUVUo6wdqqTq+vSs8mcGRv1H1iTDyy\n192p+FNl5CHV13S6v61rpYcwjxmPY+P68x4X2QEVcbPmtRnjKCgohAI+99xzT8T2YDCIz+frlgJR\nKXNxg5DYM5fR//Uf9LprLkf/72PKl66KyB3uMXoYGeNHEiiroPKvr0W0YeyZQ8zIIUhOJ0GPl6aN\n21AZdPT6z8dRC168e7fia7HRkphITJ8CJYqocNXYunVr2Ozc3LlzmTRp0jXskYKCwo2OIAiY4hNQ\nz56PoVdf7F9uxH3kEPpBw/Hs2dF2nCzJoNZAoGO6aHSBqE7PJVh+NOo+VY90pLrOncc1hcPw7Y5e\nagNA3bMf/k2fdv6mWpHOVKAfcBOB/gPxHNh3weMBEASSv/N94gqLlPWHCgoXieL22324IQUigDUl\nGUuPJDLGDKfuiYdoKS3HVV5J0OFErdPi3LGbmhf+EXVW0zKwHzmPfZPAyYPIwQCCUYdx6kCkliZ8\nW5bhP0dsOreso2nUeJKKhnTpQ0KWZdwtdtwNjUj+QMhEJz4OQ4xVeRh9jbHZbPzsZz/D1+rKm5qa\nyve+9z3U6hv2T1lBQeE6Qmc0kjR4KHH9B2AvO4W3qRHZ48F7OFRL0FW8FX3RCDzFHYSbED2yKBgM\nyB5X1H2a3oX4dm2K3hGVGkGjgU7SVgWTBdzOi3JeBQju/xLzgJtQx8Xj2PzFec8TTRaSvv0ECUNH\noFZKCikoXDTddfwqSxJSFziwdoXRzdXihh5VCoKA3mQic/gg5GFF2E9X0binhPLX/4Xty+KI482F\n+aTOnYoq6MCx6O8Xd5FAAPfhEppMZuJ69bniH7/X7ab+4FE8tXU4SivwNTRRvXojztJyYgf2o9fD\n3yC+sC9xudnKovivIYsWLWLbtpDRgyAIzJs3j6FDh3bbm66CgkL3RK3VEtc7H1mWMWdm07ByKfa1\nKwhUnUY1emLEmj7Z70XQGyPFoM8HGi14I+umCRoNdFKnUIxPOm9qqrpnfwLH9l/Sewru/xJdajb6\nb9yPv7ER+6YvkOztpjdCdh7a8VNJGzQUc3qG8gxWULhEumsEUZa6yMVUEYjXH4IgYM1Mx5KRRvLY\nkTQfPoa3phaf3U6woRa1SQ8NlXi3rSBwibMEksPOmddfQvODf8eScmn1EAN+P41HjmM7fBxfs42A\nw0nQ7UYOBKlZtgpPZTVJU8eTfvMUbEdPsO07T6GJtVL07NPkzJqC3mq5pOspdF+OHTvGW2+9hcsV\nGmDl5uZy6623Ehsbe417pqCg8HVFEATMqWno7n4Qx5iJuI8dxrFjM6Zp83F+/mHbce7iLRgG34Rn\n69qw84PNDYjxyQQdkaUpOslKDV1Xb0D2RI8eAohGE8FOjG3Oh1RdBtVlqEwWEubfjisxje3bttPs\ncLB59x4qd/yF1157DasiDhUULhllMrv78LURiGcRBAFjXCzGUcMBaNi7i6rfLeRKAsdyMIi/sgLb\ngf3oYuPQ6vUXPMfv9VJbvJfqT9dS/vb7SO7w2VPRoCdl9lSMd86l8r0l1H66FnNBb/o/8ySH/vQy\nOx5/Bu+zT5N/3x3oLeYr6L1Cd8Dj8fDOO++wa1fI6U+j0TB37lymTJmi3HAVFBSuORqdjrhe+cTk\n9cY9YjQ+hwN1UjK2d/4BwSBScyOCNRZUaggG2s7zHz+IacYC3OXHI9qU/397dx5nY90+cPxzn2X2\nfTWLJUNjbywTGtvIEiqRyhK/UlQMoUSLLCkeQiSkeCx5yhJSjyVkUITHGsk6ZCyz79vZ7t8fo1MT\nwjgzxzHX+/U6r9fMfe7lOjP3Oee+7u/3e30NhTdOBM0mcHX7h4iUW+5eej1qXg6Ws0cJbtGOHz7/\nN4sWLcJsNuPm5sbXX3/NsGHDcHJyKvX+haiIHLYFUYrUVDyKDT7gNa5uWAryydu1gySdE/k4o3Vx\nRuvkhJu3J5jNKIqCk4c7noH+FOXlcXnnz5xf+BWG1LRrkkMAS0Ehl1Z9h6LVcl9cf1J/+JHsX45j\nSE6l9shXOPbBLI68OwXXkGBqdH1Eurrcw1RV5eDBgyxfvpyioiIAIiIiePHFF2XsoRDirqLRaHD3\nD8TdPxBTWDguYVUoOHmM3M3ryP9xK+7tnyB/09d/Jm8WC5a8XBR3z2umsjAcP4S+diOM1ylEY8nJ\nQh9a9YY3dy0FeShuHqg5maV/LZ4+uHp4MnjwYOLj4zlz5gz5+fksW7aM2NhYmjRpIjfohLgNjvp+\nUS02ShCli6njcA4KRhdaGdOlC6Xeh+LkDBYLBUf2o69SHY1nAOkXU8gzmTEYTahmM3nnL3L55wPU\n79sdNw83MvccoCA7F5fKYVTr0g7jlRSS1m3ClJNbYt+q2czZmZ8RMXwgxuwcCs4ncnHRCiL69+b0\n/KUcGTeVoMYN8KkSfqd/CnGXKioqYuHChRw/fhwo/oAdPnw4devWtXNkQghxYzqdHt+atfGOiCSv\nYTMMyZcxW8x4Pv0iOav+bW1JLDy4G9fmsRTGf1die0tGKhof/+vuW83JQuPtd8Njm84exynyAYwH\nbn1O5L9zbtAUrVZLw4YNefXVVxk6dCgAR48eZfHixTRo0OCO528WoiJx1BbEiqjCNzu5+QXg06V7\nqbfXV6lO0dmrXWMsFlSjEa2xgPQ5C/EyFJH18370Tk6cOfwbkb268tP7s9n0xiRytXo86kZyacM2\njv5rDr9v3knIc88Q0L71dY9z9uMFhD31GACFFy+jd3dF4+xEwcUrpB37Td5097Dt27fz1VdfWf/H\nHTp0oE+fPnaOSgghbo1Go8EzNBz/qGiCGjUjsGU7Al4dh8djvVA8PFFzsjAmnMKpSctrtjWdO4H2\nvsjr7tecmIAmpMp1n1NzMlE8vIDStVgoru44h1axtng8//zz1umELBYLS5Ys4aefbjzFhhDiWo7b\ngqhaC9Xc2cNxrtUrfIKoKAqu1WuiuLiWanuXB5qQf+h/f9khZG//gfvejOPyzPlUj6pD4rpNNOnR\nifi5y4h+czBYLPzyxRoSDp+gWv/iyUQLLl3h+IzPMGl1BD/e4ZrjqCYzRUmpOFcKAiB5w1ZCOhVP\nUnx26Sry0jJKFb+4uxmNRoYMGUJubnHLspubG9OnT8fdXSZmFkI4Jq1Wi2/NWgQ/0o3g4e/h99Io\nPGLa4VKvCW6dnganP1vljCePoqtSA+U6LYnGk0dxqtuEGyWBxcllrVLF6PxQB9yCQ62/e3h4MH36\ndNzcisc95uTkEBcXh9H49/kehRA3Io0ZjqPCJ4gAXlWqEThwGNzmnQ2XqGgM585CiaqnCkWnTqLV\nqAR0fpgrny6mwZOdOT5vCU17d2Xnp19S74WeAFz8+QAXT/9OYGyMdevE7zZj0jvh3bjBNce7vG4j\nlbp2BCD/VAJeEVUByD5+iiv7DmCSL6p7isFg4M033+TUqVMA6HQ6hgwZQvXq1e0cmRBC3Lm/tiwG\nNG1JYMOmBLZ7nIAh4/B6egDaoOIEreCHdTg1ikFb6W9DKVQLhkO7cXqo/XX3bzp3Em3l6uB1466o\n16OLqIN7gwevGdsfGRnJK6+8glZbPKfj8ePHS8xLK4T4Z47agmgxW2z2uFVFRUW0b9+etWvXluEr\nuzFJECn+kvJv9CB+/ePgFot+uDR8EMXNg/z9e6zLnKrXpODMGQBMGel4PVAbVJXM/35PpUb10ZlN\n5KWmo/PxQqMr/oI5szEe7yYPlNj3+eXr8GsTw9+ZsnLQ/mW8g2oqTkxN+QVc+X4Hqb+euL0XLu5a\nqqqydetWli1bZl0WFRVFr169ZMyLEOKepdPp8K5yHwEPtSV40NsEvj6ZgGHv4dHgQbyeeQmv3oPR\nVa9tXd+cdBHTmd9wbtWleD7FvyncsR6nRi1Q/INv6fj62g3xerQ3boHXru/i4sKzzz5Lw4YNrcuW\nLFnCtm3bpGVEiFvgsO+Tq0Vq7vTBbRSpmTNnjl2nMavwRWr+oHN2xrthNJaCAorO/EbBgT1wnRY5\nfbUIXBo0xnAugbz4LSWec6nfiJQ/LuhVKDjxGx4N6pB75FcqD3+Z/Z8vp9HTXfhlfTzVOrTm7Pri\n+aCuHD+NZ83q5Jw6a91X9rkLuFYNp+B8YoljqOq1J5fe0wNjVjZp+48Q3KCuw96hEX9KSEhg9uzZ\nJCcnA+Dv788LL7xA7dq15f8rhLjnKYqCq68/rr4lu5aq4VVxv78uhZcvYMnPRTWbUXR6FB9/3Oo1\nwXjpPPk/bsCSmlS8gcVM4U/f49blGTCZMeyLx5KUeM3xdBF1cYluhWvl6rj6Bdwwpjp16vD8889z\n9uxZ0tPTSUpKYvbs2URGRlKtWjVb/xmEEBXQ2bNnSUhIoHXr69clKQ+SIP6Fu58/OZ7eZCck4NH+\ncTRaLZaCfFSzCY2rG4qTM0WnT5K5ZsXfupWCxssbU3YOWCxoPD0x5+WTtetnAnv1IvfIr5gvXATA\nPzSIXZ8v54EusdYE8cS6LbQa+lyJBDHx283UeqEX5+cuumncPlF1yfn1JJkHfyGsfWt8KofZ7o8i\nyl1hYSGrVq0iPj4ei8WCRqOhbdu29OrVS+bdEkJUaIqi4OLhiUvNOtd9Xq1yH26R9TFmZ6KajCha\nLRoXN9yDQ1EUhcK6jSi8cgFLbg6YTSg6PRpvX1xDKuPk5n7TG3BOTk707NmTzZs3880332CxWPjh\nhx9YtWoVcXFxuNzCPMhCCMdS3vMgTpkyhXfffZfVq1ff8TFLSxLEv1AUBZ8GUeQd2U/W2hXFy5yc\nQKsrnqj3Rk3jOj1enbuRsvQLADxjWpH83ZbiJPJqi5/p4mXcQ4JQTcVlvU2GP1snzYVF18zlZM4v\nQNVe2wNY0Rb/yxS9Dq6Og/CKjODKN5sAyL1wSRJEB6aqKidOnGDu3Lnk5+cD4OPjw9ixY/H29rZz\ndEIIcXdTFAU3vwC4QSugq48vrj6+d3QMPz8/xo8fz7Zt28jKyiI/P5+5c+fSoUMH6tevL708hBCl\ntnbtWqKjowkNLR6Dba9uuTIG8W9c/fwJeOIZ3B4qbtZVDQbUgvwbJoeKiys+T/Ym7euvsRTkg6JB\ncffClJZe/PzV7wm1yIDWxRnldkpu/+2YzsGBGNOLq5UGPtyKy5vi8a4bSfaxk9Z1LFcnUheOKS8v\njylTpnDu3Dmg+G716NGjZc5DIYS4izRo0IC33noLvV4PFHcJ+/DDDykoKLBzZEIIWyvPaS62b9/O\nxo0beeaZZ1i5ciVz585l9+7d5fAqS5IWxOvwrlyForYd0QeHUXj8MEW/HbtmHY27O25NW6Dx8iXl\nyy+xXJ2GwCOmBZk7//xH/pHjKZ7uGM5fQaV4wS2liX87jyo93pGLK9cB4F43kgtbdlD3zaEc/2Cm\ndR3laquicEzz5s1jxYoV1t87d+7Mq6++aseIhBBCXM/QoUPZuXMn3333HQBffvklDz74IHFxcXaO\nTAhhS6rFRl1Mb6FIzYwZM6w/z549m/DwcJo3b37Hx75dkiBeh6Io+Nd/gMLEi5gMCl5P9AKTsbi7\nqKKARos5v4Cs7fGY0tKs27nUrotF60zeL8UJpcbVxVpp1KVOJFnb/0eQTo+LtycYTdbtnL09Uf5W\nJlvRaq2VTgG07q5o3d0wZWZTqXtnUn7eT+03BnNm3mLUq/tStFr0Xh5l9ncRZev7779n0qRJmK52\nQ65VqxZvvfWWjDsUQoi7kIuLC++88w4nTpzg1KlTmEwmxo8fT926dYmNjbV3eEIIUWqSIN6ATqfD\n78GmmHLzSF/5FeacbFA01jGFJSgaPGJaoGqcSV7x53wlPrGtSf5uCxpXFwotEPJQY46s30bjZx7l\n1Or11vXq9OjMlW83l9hlpbYxpO8obolUdFoihg0kYc5igh5tj1NoJYLrRHJm7mIMKX8mqCGPtsO3\nZoSN/xKiPJw7d44xY8aQnl7cNdnd3Z3XXnuNqKgoO0cmhBDiRho1asTIkSMZPnw4eXl5pKamMnbs\nWO6//37CwqQegBD3gvIuUvMHe/ZGkDGI/8AjKAgnX39cm7XC76neOEeUTL40np54P9IFn+7PkHvy\nd5JXlpzMUh8SRuH5RHwfactvazbhG1WPi/uP4hcWTO7FqyW4FQXf0CAKLieV2Na/UT2yDx1D6+5G\nzdFDSInfxX1DX8CvVTMy9h/h+HszSiSHAGGPdUDvKhXUHE1BQQEff/wxhw4dAorn5Xzqqafo1q2b\ndXyLEEKIu49er6dbt250794djab4kmrv3r188sknFElNACGEg5IWxH+gKApedetw5eu1JP3vIN4x\nzfB+7MniAYQqmPPySf5ui7UgzV/5dupI2g8/4hRWCUtICAGNzRzbuovY4f05vXqDdb2Gzz9Fyubt\nJbYNaN4YY1IKEa+/gktIMGaDCc+G9Tnz+X8ouHDpurF6N6hNxs49JFcOJbhhA6mi5iBMJhPfffcd\nK1aswHC1m3HdunV5+eWX8ff3v8nWQggh7C0gIIBXXnmFAwcOcOzYMYqKivjyyy9p2rQpXbp0QaeT\nSy0hHJnFYsFyG5Pc/9N+HIV8at2EV3gYEW+M4PSEyWTt+ImsHT/ddBvvNq0wZhdSdDkZn15Pknj0\nJBn5hYQ2iCTryHHSfzsDQJ2nu6DPyiLtyHHrtr5Rdan96ouk/byfS5viKbycTFFy6j8ez61yGGGP\nxJIwbS7pP/5M9OLZ+EfWuLMXLsrFyZMnmTlzJomJxRM3Ozs7M2zYMKKjo+0cmRBCiFvVtGlThg8f\nzqBBgzAYDJw7d46ZM2dSt25datSQ72MhHJlqUW1UpMY+U1aUhnQxvQlFUfCtEcH9740hdGB/tB7u\nN1xXHxRI8HN9MRnB4u6Gd5+nyC40YPL2IrxhXTL2HiJx5148w0NoMXoQrnl5XNnwQ/FxdFqq9+1B\nzLwpVGn9EN51Iyn4/dJNk0OfRvWp2vNxzs36DICCcxdI23/YbvOmiFtnMpkYO3ZsifLFzz33HL16\n9bJ2VRJCCHH302g09O7dm759+1qX7dixg4kTJ9oxKiGEKB1pQbwFiqLgU60qnq8MILhjO7J/O0HK\nhu8xpaaDVoNTcBAeUVFYUDCZLLi1CqMIDQajCb1ej/b8Rc5/txW/mtVo9MIzFJxOIHHJcsz5hbhV\nDuX+AX0Iat4E/1o1cXZzJS89g6SV31ClR2e0Xl4kbdlJ5uE/p9rQ6PUEd2yDT52a5P12inPT55WI\nN2HOv6kUG4NXSKXy/lOJ2/Duu++yZs0aa5eDmJgYPvroI1xcZBypEEI4GldXVz7++GMOHz7M//73\nP8xmM1988QWRkZG8+eab9g5PCFFaZjOq2WyT/TgKSRBvg1arxbdmDXxqRBDWqSOmwiIUjYKi05UY\n86fRaKy/WywWDPkFaHRadE5OqKpK7uVk6rzQG0UBvbsbnsFBJVqMsk6cJm3bLti2C0Wnxa9NDJXa\nvFjcKqiqgEraDz9ybsOW68aZfzqBrOOnJEG8S5nNZlavXs20adMwX/2wqF69OjNnzpTkUAghHNgf\nSWLPnj05f/48ZrOZ8ePHU69ePTp37oxW5ioWwuH8MdG9LfbjKCRBLAVFUdDpdOg8bv7n02g06Lw8\nSyzzrfLPpa8N6ZnWn1WTmbQtO0jbsuO2YjRkZN58JVHuVFXlwIEDvP/++9aiNIGBgYwaNYp69erZ\nOTohhBB36oEHHuC1115j/PjxpKWlUVRUxIQJEwgPDycqKkqKyIkKS859xyEDne5Cqtl0x/uwmO58\nH8L2Ll26xEcffcSvv/4KgJOTE08++STdu3fH2dnZztEJIYS4U66urjz99NN07doVJycnAI4cOcKM\nGTO4dOn6lciFqAgctT7GH0Vq7vhxrxWpKSoqon379qxdu5YrV67Qt29fnn32WYYPH47RaCzrGCsc\njdOdJwpaSTbuOvn5+cybN49vvvnG+r5p2LAho0ePJiAgwM7RCSGEsJXg4GBGjx5NnTp1ADAYDKxe\nvZoFCxZQUFBg5+iEsA9pQXQct5QgzpkzBx8fHwBmzpxJ3759+eKLL6hSpQpff/11mQZYEbmGBqO5\netexVDQaXMNk/OHd5ocffmDKlCnk5eUBxa2Hc+fOpUqVKnaOTAghhK3VqFGDOXPmWGsM5OXlMXny\nZHbsuL0hI0LcKxy2BdEWrYdXH47ipgni2bNnSUhIoHXr1qiqyr59+4iNjQUgNjaWXbt2lXmQFY1v\nZA1Cn+la6u2DOrTBt9b9NoxI3AmLxcKuXbvo27evddyht7c3y5cvp2HDhnJHTQgh7kGKotC8eXPm\nz5+Pp2dxLYKCggJ69uzJ3r17HfZiWYjSctTrHYvFgsVsg4cDFam5aYI4ZcoURo8ebf29oKAAvV4P\ngL+/PykpKWUXXQWld3am0qMdSr19eO/uOP/DfI2ifB04cICXX36ZzMziwkFeXl6MHDmSLl262Dky\nIYQQZa1fv37ExcXh7l78vZyZmcmAAQM4cuSInSMTonzJTRHH8Y8J4tq1a4mOjiY0NPS6z8s/uuwE\nNKhN1Zf63fZ2IU8/jl+Dug57l+Zec+bMGSZOnGgtSuPs7EyvXr0YOHCg9UaLEEKIe5dOpyMuLo5u\n3bqh0xVXPz927BjvvfceCQkJdo5OiPLjqNemf0xzYYuHo/jHeRq2b99OYmIi33//PUlJSej1etzc\n3DAYDDg5OZGUlERQUFB5xVqhuPr6UmNgX8z5BSQuXXlL2/i3icElwJecM2dxC/SX+ZbsLCMjg08+\n+YRNmzZZ5zts2rQpw4cPl6I0QghRQSiKQqVKlXj99dc5efIke/fuxWw2s379eiIiInjrrbfw9va2\nd5hClDlpWHIc/9iCOGPGDFauXMny5cvp0aMHgwcPpnnz5mzcuBGATZs20bJly3IJtCLyCgulzsg4\n6nw4FtdqlW+4nnNoMNUGP4+LnzeXFy7jSP8hXN7+k0P1db7XGI1GlixZwuzZsyksLAQgNDSUDz/8\nkMjISIe9iyaEEOL2aTQaHnjgASZNmmS9QVhQUMCMGTNYvHgxJpmaSlQAjnrto5ptNM2F2XES5JvP\n9P43Q4cO5Y033mDFihWEhobSrVu3sohLXKXotOQePIx/s0a4PP04uacSMKSlgwp6Px887q+OMSmZ\nlOVrMOfmAqAWGfh1yCj0S+YS3DjKzq+g4jEajaxZs4Z3333XOp1FYGAgU6ZMITo62s7RCSGEsJe2\nbdsybtw43nnnHTIzMzEajYwZM4bKlSvz6KOPytADcU9z2BZEi2qb5M6B5kG85QQxLi7O+vPChQvL\nJBhxrczfTpL89XfW353DQ9H7eIOiUHT8Clmbtlx3O3NePknrN+PfoC46+cIpN2azma+//ppBgwaR\nnZ0NFCeHEydOpE+fPnaOTgghhL0NHjyYgoICJk6cSFZWFtnZ2QwYMIC5c+fy5JNPWqfFEOJe46gt\niBXRbbcgivJjMhpJ3RJfYllR4iWKEi/d0vaXl60itMfjBNSOLIPoxPWsX7+eMWPGkJGRAYCnpyfD\nhw/n2WeftXNkQggh7hYvv/wy2dnZTJs2jfz8fNLS0hgzZgyenp488sgj9g5PiDLhqC2If0xTYYv9\nOAq5TXUXyzqTwOX/rC719pbCQnKOn3TYN6Sj2b9/P++//z5nzpwBQK/X06dPHwYMGICrq6udoxNC\nCHG3cHd3Jy4ujmeeecZaUO7kyZO89957HDp0yM7RCVE2pAXRcUiCeBczZudguVrgpLQKEy9JglgO\nTp06xahRo9izZw+qqqIoCh07duTdd98lICBAPhSFEEJYKYpCUFAQEyZMoF27diiKgqqq7Nq1i5Ej\nR3Lq1Cl7hyiEzTnq9ahqUW32cBSSIN7FVJP5jvdhzi+wQSTin1y8eJGRI0eydetW67LGjRszdepU\nQkJC7BiZEEKIu1l4eDjTp0+ncePG1mVbtmxh5MiRXLp0a8NJhBBly2JRsZht8JAEUdiCxtnpjveh\n9/WW1qsydPbsWYYOHcq6deusyx566CHmzJlDrVq17BiZEEIIR1CnTh3mzJnDQw89ZF22bt06hg8f\nztmzZ+0YmRCiopIE8S7mEhyEc9idtUC516huo2jE3124cIHRo0ezZs0aa7eJZs2aMWPGDJnOQggh\nxC2Ljo5m2rRp1pZEVVVZuXIlb775Js40xv4AACAASURBVBcuXLBzdEJUbLaZA7H44SgkQbyLeYWF\nUOWl50q9vXPlMLwia0oLYhlIS0tj4sSJfPPNN9bkMDIykvfff58mTZrYOTohhBCO5sEHH2TSpElE\nREQAxUni2rVr+eCDD6yVsYUQ5U81g2pWbfCw9yu5dZIg3sUURcG7UQMUp9J1NQ1/4Vk8QivZOCqR\nlJTEuHHjWLhwIQaDAYCIiAimTp1K27ZtZQ4rIYQQt02j0dC+fXsmTZpE1apVATAYDCxYsIAJEyaQ\nkpJi5wiFEBWFXMne5Xwja1Jj/Kjb3s6jXm3MBXlknjnrsFWj7kbJycmMHz+eOXPmYDKZAAgJCeH9\n99/nscces3N0QgghHN2TTz7JuHHj8Pf3B8BoNDJ79mw++OAD0tLS7BydEBWPaqMiNVLFVNiMTq8n\nvEsHqo95/Za3ca8TiW9sDImz5nFizHtknTtfhhFWHOfOnWPkyJF89tlnWCzF/cgjIiKYNWsWTz31\nlJ2jE0IIcS/QaDQ8++yzTJ8+nbCwMABMJhOffPIJo0eP5uLFi3aOUAhxr9PZOwBxcy5eXoR17Yzi\nrCdp5TpyDx+77no6Xx8CH+uIRq/l8ueLAMg9fJRLa77FY+gr6HTy7y6thIQERo0axZo1a6wthxER\nEXz00Ud07txZupUKIYSwGZ1OR58+ffDw8GDYsGFcuHABo9HI4sWLKSoqYvLkyYSGhto7TCEqBNVs\nQdXceYEZRypSIxmDg8i7kMj5KTPwbv4g/g+/QtHlJIouJ6MaDWi9vHC/vzrmvDzSN27GmJZeYtvL\ny1YQ3OUR/CNr2il6x5aUlMSYMWP4+uuvrS2HISEhTJ48mc6dO0sRICGEEDan0Wjo2rUrBQUFjBgx\nguTkZIxGI19++SVubm68//771m6oQoiyY7HYZg5DR5oHURJEB2CxWMjYvReMJrJ27CJrxy70/n7o\n/P3Q6PUUnk0ma+cOuMGdCUt+PtnHjuN3fw1JZm7TmTNnePvtt1mxYoV1LGfVqlX54IMP6N69u7Qc\nCiGEKBOKoqDVaunVqxdFRUWMHTuWxMRETCYTn332GQaDgbFjx1oL2gghhK1IgugA8lJSSV69rsQy\nY1r6NS2F/yRp7be4NWqIk6sL3oH+ktjcgiNHjvDGG2+wadMm67Lw8HAmTZrEM888I39DIYQQZU6j\n0fDcc8+h0+l46623uHjxIhaLhUWLFpGRkcEHH3xA7dq17R2mEPcs1VI8TYUt9uMoJEF0AObCQkyZ\nWXe0D1NGJr/v3MO5Q7/iXTmUiJgmhNW9Hxc3NxtFeW/54YcfGDduHDt37rQuq1+/Ph988IGMORRC\nCFGu/ihc4+HhwTvvvMPx48dRVZVvvvmG7OxsxowZQ5s2bewdphDiHiFXuQ5AURTQ3FnXUEWjwS8k\nAH1mJlqzmc+eGMjyuHdJPH5SpsH4C4vFwubNmxkxYgQ//vijdXl0dDSffPKJJIdCCCHs4o8xifPm\nzaNJkyYAqKpKfHw8I0aMYOvWrfJ9LkQZsJgtNns4CrnSdQA6V1f0/n53tA+9vx+5u34mvEZVjBcu\n0uG1F/hl7fcs6jmE07v/h6GgwEbROi6LxcKuXbsYPHgwhw8ftn7R1qtXj+nTp9OyZUtJDoUQQtiN\nVqulVatWTJs2jbp16wLF310HDx5k8ODB7N6921pMTYi7jcPWwTCDalbv+IHZ3i/k1snVrgNw9fcj\npPfTd7QPjwfqk7JqDU4uejQXLlBw5hztXn+Ry7+cYPWwCRxc+CWn1m/myrHj5KSkVri7kLm5uaxa\ntYru3btz6tQpoPhubatWrfjiiy9o0aKFnSMUQgghirVq1YpFixbRrFkz60X3iRMn6N69O6tWrSI3\nN9fOEQpxrYp2benIJEF0ABqNBu+GDVD0+lJtr/P1wZSTA2YLxgu/Y7ySjI+HK5aMbPwjqvD7/34h\nKy2LHf1e5adXRnP+mw2cXv41Vw4cIj8n555/QyclJTFjxgz69+9PSkoKUDwHVdeuXfnss8944IEH\n7ByhEEIIUVKTJk1YsGABXbp0QavVAsXfZ/3792fWrFkkJyfbOUIhSnLUFsQ/itTc8cOBitRIgugg\nfGpEEPzUE6XaNvDxzqRv2gpA5radhHRqy5VV3+Hq6kTjHp0BOLxpJ4GtmpF59ASHpsylMCOLo/3j\nOPPxp1z68SeyLly4J7utnDx5kjfffJOpU6eSl5cHgJubGwMHDmTatGncf//9do5QCCGEuL46deow\nY8YMBg4ciNvVonN5eXn861//YuzYsSQkJNg5QiH+dK83ONxLJEF0EHoXF8Kf7Yl7/Tq3tZ13TDMM\nySmY0jMAUA0GNBoFU04urs56XN2dURSFc7sP4NGoAQBFqekcm/8lfk88yqVF/+HSV6tJXLKUxP/+\nl4KsO6umejc5d+4ccXFxfPHFF+Tk5ADg4eHBiBEjeO+996hWrZp9AxRCCCFuIiIigokTJzJs2DDc\n3d0ByM7OZuHChQwePJjz58/bOUIhijlqC6IUqRF3Na8qlQnp2wvPJo1uaX2/9m1xCgq0th5aXa2I\nmvnjHpzd3HH28gCgqKDIukre+UTMzq4oej3pm+MxFZlJXrWSC8uWkZGQ4NB3gYxGI7/99hvdu3dn\n8+bNGI1GALy9vXn77bd599138fPzc9gPMiGEEBWHoij4+fkxbtw4XnvtNTw9PQEwGAxs2LCBbt26\ncebMGet3nRD24qjXjqpFtdnDUUiC6EA0Gg2WrBz0fj6EDxqAd4vm8LeqmoqTHr+ODxM+eACm3FxS\nv/nvNfv54/1pSE5Dp9Xg5O5avPxv+dD577bgE9sSgKRV3+LZ7CFSl39FyqaNJG7bRqEDtiampqay\nZMkSYmJiOHjwIFD8d61Xrx4LFy5k9OjR6Es51lMIIYSwF71ez/jx4/n444+pVauW9SbnwYMHadas\nGUuXLiU9Pd3OUYqKTG68Ow6dvQMQt05RFFyqhJMx6UMytsTjXr8OYQOeQzWZ/lxJoyEjficZm7dd\ndx96fz8MGdkAqBYzWldnCrOKu1cqf7uxkXX8FLonOhSvazJhzM5D4+FB2po1+D/xBBdOn8L34XZo\nLCqoKhpnJzxCQtA5Odn+xd8hVVVJTExk1qxZLFy40PolqdPpiI2NZezYscTExNg5SiGEEOLO/N//\n/R+VK1dm3Lhx7Nq1C7PZTGpqKqNGjeL06dPExcURGhpq7zBFBeSoLYgWi4qFO4/d4kAtiJIgOhiv\nmhE4V61C0fnfyfvlV/J++fW2tvdp/zBnvlgDgN7HG8XZGUNeAYpGg7PLtYmd2fBnl5SUb78nqHNr\nsjZtBEVD6sqVoNejDw3n4uxPMaakEfBYJ/wfboN3zRq43kXdNI8dO8aoUaPYsWOHtfy3i4sLvXv3\n5vXXX5diNEIIIe4ZrVq14uOPP2by5MmsXr0ag8FAamoqs2fP5sSJE0yZMoWIiAh7hykqmLvlmvB2\nqWYL6t+72ZVmPw5U7FG6mDoYj0rBhPd/tnQba7WoLq4YM4q7hvq0bMb5g8UJZuTDD5H9097rbPTn\n3Q5DcgpaTy8Asn/ciVdMDKnLlmG8eIHwl54n7OXnyTt+guMDh/DLqyNJPfrrXXG3aOfOnXTp0oUN\nGzaUmBtqxIgRzJo1i1q1allLhAshhBCOTqfT0aBBA+bNm0f//v2ty3Nycli7di2dOnWyDrMQorzc\nDdeE4tZIguhgFEXBL7oxno0b3va2gT17kLh6Q/F+9DrcImuwZ/HXANRuFU3a3mu/LBSuf8fEcOEC\n+uBgVKMRtaCApAWfo9HrcK8dgX/nDuQdOcrxuOGkHD5ilw8Ei8VCSkoKY8aMoV27dvz++++oqopG\no6FatWp8++23vP/++7i7uzvsHS0hhBDiRhRFwdvbm7lz57J06VLCwsKKaxlYLJw6dYoWLVowefJk\nMjIy7slprMTdx2GvtyzYZB5EHOhtJgmiA/KqUpma74zEvUG9W94m4MknSPnfUfLOnAMgqGMsl85f\nojArhzodW1L464lrttE4OaFz+qdeyMVv9Kzt2/GIfpD0tWvQOjuhWAz4PtwGU0YmJ0eNIePU6dt5\neXfMbDazb98+Bg8ezIcffojBYADA2dmZhx9+mK+++oouXbqUa0xCCCGEvfTp04elS5cSExNjLcSW\nn5/PxIkTGT58OEePHpUkUZQ5aUF0HJIgOiBFUfCtWYNaH4wl7JUX0Xp73XBd15oRhAwaSNLeI6T9\nWNyF1PW+Kvh2asf6MdOJaNmEyLo1SNrwwzXbVu7yMNnbdlh/d4usieHSxWvWMyYlofP1xZicjM7X\nl9y9e3CtGoY+wB/D5StkHiq/VkSj0cj8+fMZMmQIq1evprCwEAAvLy9eeeUVPvroI6Kjox33LpYQ\nQghxmxRFoWXLlsycOZO+ffvi6lpcvTwvL49ly5YRFxfH0qVLMZvNdo5U3Msc9drLYlZt9rgVU6ZM\noWfPnjz11FNs3ry5jF/d9UmRGgelKAq+91XD65UX8WoaTebe/eT/ehxLbi6KTocuIABdpUpk/nKC\nYx/MRr06/5FH7ZqEDerP0kHv0mrQs3hbTJxf+OV1jxFQ736Sdm7/8/f2rcn4ZhUAzlWrYrh86Zpt\n8g4exL1hQ7K2fI/fI+1I+mI5l/69lMAWzfEs46ppV65cYfz48Xz11VdkZmZalwcGBjJ9+nS6dOmC\nr69vmcYghBBC3I10Oh1RUVFMnjyZRo0a8eabb5KTk4PJZGLnzp0cP36co0eP8vbbb+Pj42PvcMU9\nyFFbEFWL5Zqp4Eq1H/XmrfR79uzh9OnT1mvZbt260b59+zs/+G2SBNHBabVaQps0xMXXh/TwcC59\n+z0F5y5QtP84hZeSrOu5R1QjtM+T5Khw+ddTPPJCD5K/3UTi5eTr7jeiTzfydu/58zieHmAxwtUp\nNbxiWpC6csVftih+0+f/8guBvXuTd+AAek8P0GoxXLxEzqkzZZYgWiwWtm3bxtChQzl+/HiJD6AO\nHTqwePFigoODHfbOlRBCCGELiqIQGBjIoEGD6NChAz169ODIkSNA8TzB06ZNY/v27XzyySdER0fb\nOVohKp7o6GgaNGgAFPd+KygoQFXVcr+GlQTxHqAoCv41quMXcR/BDzYk4/hJCi4nYy4yoHXSow/w\nozC/kPNrNmBISiH98DFUo+mG+6vWowuuZgOZh45Yl4X370P25uICNxpXV1STydoqqfP1w5zzZ3VQ\n9eo8L3lHD+PZ8AFy/ncAY0YmtqaqKhcvXmTRokXMmDGjxATAwcHB9OvXj9dff52goCCbH1sIIYRw\nVIqiULNmTdavX8/EiRNZsWIF6enpqKrKvn37eOKJJxgzZgxPPPEElSpVsne4QtiVzeZBROUGtR+t\nNBqNtQv4ypUrad26tV0aOCRBvIcoioJXSCW8Qoo/zP96xyEnORWN2czRGfNvmBx616rBfd0foeiX\no2TG7/1jp4S/9H/k7f8ZU0ZxAubfrRsZf+kT7d2mDZlbru0jbUpNRVe5eJ4l1cbjGgoKCti+fTsf\nffQRW7ZssY6bUBSFqKgoXn31VXr06IG7u7tNjyuEEELcK8LCwpg0aRINGjRg9uzZ/Ppr8dRXly5d\nYujQoWzevJlXX32Vpk2b4uzsbOdohag4tmzZwurVq1mwYIFdji8J4j3sr3ccPIMCqNXjMcJaNiXt\n15Nc3rmHvPOJqCYTLgG+eIaHYDxzlrR/L7W2DLrXjiTo8Y5kx2/F8Pt5APy6PkHekV8wpaQU71ir\nRePuhjkn54+DomiKj6uazWiciqulKVerptlCYmIiCxYsYMmSJZw9e9a63MPDg759+/L888/TqFEj\nmdtQCCGEuAkfHx9efPFF6tevz+eff87y5cspLCzEaDSyevVqfvvtN5577jn69etHcHCwvcMVotyp\nZhXVBi2IKuotZV47d+5k/vz5LFiwAA8Pjzs+bmlIgliBKIqCV6VgvCoFU7VNDEaDgexzv5N58DBp\n32/DnJODZ1R9XCqH4lotHEPCGVKXLQazGX1QEL6dO5OzZw8Fx49b9+n7SCeyf/rJ+rtb/Qbk/1r8\nvNbDA1N2ceLoEhpik9ewYcMGJkyYwJEjR8jPz7cur127NmPHjqVjx44yuF4IIYS4DXq9nhYtWlC7\ndm06duzIhAkT+O233wD49ddfmTBhAhs2bGD8+PG0bNnSztEKUb5Usy06mIKK5aaZV25uLlOnTmXR\nokV4enra4KilIwliBaXRaHB2cSGw1v3431+DsC4dyTpxkrzjv5J36CA5P2xGcXLCo3Fj3GrXwZic\nROqKFVj+kpR5tWqFOTuLooQE6zKPhlEkL1kCgFuDB0hZuwHPB5vgXbNGqWM1m81kZGQwYsQIli5d\nWuI5vV5P+/btmTVrFhEREaU+hhBCCFHR+fv706tXL6Kiohg6dCjx8fGYTCZyc3PZtm0b27dvJy4u\njvHjx+Pl5YVGI7OlCWFL69evJzMzk2HDhlmHik2ZMqXcxwJLgijQaDS4eXnh0rgRaa4umDPS0Xl7\nYykqwpiSQvLiRSXXd3fHt1NnDBcvkrN7l3W5PjgYY1oaqCpoNGhc3TFlZlHpmSdx9rr9uyCqqpKe\nns6GDRuYNGmSdWwEFJfrvu+++3j11VcZMGAATk5OpX79QgghhPhT7dq1WbduHTNnzmTBggUkJCRg\nNpuxWCzMmjWLnTt3MmrUKNq3b4+vr69UCRf3NNUCFhtM0XErU2U8/fTTPP3003d8rDslCaKw0mg0\nBNSti0tAAOn795N38ACFmZlo3N3RODmhDwrGI7oJlsJCsuK3YUpN/XNbNzf8Hu9K8qJ/A+AR/SCZ\nO3bj16EdvvXr3faXh9lsZteuXXzxxResXr2a1L8cKyAggMcff5z+/fsTExNjmxcvhBBCCCtXV1dG\njx7NQw89xOeff85///tfa7XwgwcPMmTIEJ566il69uwp3U7FPU01q9hiCkdVcZx5ICVBFCUoioJn\npUpomzfHUlhYXGjG3R3VYMSUnkbKV19Z50L8g87XD/8ePUj58j+oRiO6gACcI2piKjBRLe4lPCrd\n3qD2X375hc8++4wtW7Zw8uRJa4VSgBYtWjBkyBBiY2MJCAiwyWsWQgghxPW1bNmS+++/ny5dujBr\n1ix27SruOZSSksL8+fPZtm0bnTp1YsCAAdSqVcvO0QohbEESRHFdbn5+hD3yCBnVqpGxYzuZ8d+j\nFhWVWMcpLAyvli3BYiF58SJUgwF9pUr4PtoVRaulxujX8QoLveVjZmdns2jRImbPnk1CQgKmvySi\n3t7evPfee/Tu3RsfHx+pUCqEEEKUA0VRqFSpEj169ODhhx9mzpw5TJ48mYKCAkwmE8ePH+f06dN8\n9913DBs2jH79+skUU+KeYlFVLDZo/LNNqZvyIQmiuCEnd3eCGzfGr3590lq3ofD8OYypqagmE4pO\nh/FKEmlr1qAWFaHz98enYyfc69TBvWpVvMLDbmnwuqqq5Ofnc+LECUaOHMm2bdtQ/9KO7+rqStOm\nTfnwww9p1KiRjHMQQggh7ECr1RIQEMA777xD69atGTVqFIcPH7ZOiXHy5EmGDBnChg0bmDp1KlWq\nVLFO+C2EcCySIIqb0js5UalRIyxRUeReukTumTMYU1LQ6J0IGfgSToGBuN13H+4hIeh0ultK4v4o\nQHP48GFWrlzJ4sWLKSgosD7v4uJC48aNefrpp+ndu7d0JxVCCCHuAhqNhtatW7NmzRqWLFnCmjVr\nOHToEEVFRZjNZr799lu2b9/OwIED6datG3Xq1MHb21tu8AqHZVZVzDZo/DNLC6K4F2k0GrzCw/EK\nD0dVVWv53dIUoNm0aROrV69m48aNXLp0ydpqqNFoeOCBB+jZsyfdunWjZs2aZfFShBBCCHEHQkJC\nGDVqFI8//jirV69mxYoVHD16FIvFQnZ2NtOmTWPVqlU8+uijPPnkk7Ru3VqSROGQLGCTBNHiQKe/\nJIiiVEqbGMbHxzN//nz27NlDYmJiiQI0gYGBDBgwgKeeeoq6deui1+ttHbYQQgghbKh27dqMHDmS\njh078tVXX/Hvf/+b9PR0VFXl3LlzfPrpp2zcuJG2bdvy8ssv07BhQ3uHLIS4CUkQRblITExkypQp\n/Oc//7F+cfxV69atef/994mOjkav18tdRiGEEMJBODk50bhxY+rXr0+3bt0YMWIEe/fuBcBoNHL6\n9GnOnj3LunXrGDhwIHFxcQQGBto5aiFujc26mNpiroxycvMqIkKUgqqqZGdnc+rUKUaMGEHDhg35\n+OOPSUtLs3ZN9fHxoW3btmzYsIH4+HhiYmJwcnKS5FAIIYRwMIqi4OzsTExMDHv27GH9+vW0bt0a\nLy8vFEXBYrFw5coVJkyYQFRUFOPHj+fcuXPk5uZec9NY3Jvk+s5xSAuisClVVcnMzGT//v2sWbOG\nVatWkZycXGIdb29vWrVqxdNPP81jjz2Gt7e3naIVQgghRFno1KkTTZs2ZfXq1axcuZIff/yR/Px8\nAC5dusS4ceP4/PPP6dmzJ507dyYqKgofHx9JIu5hjnojwKLaaAyiA718SRCFzRQWFrJ161bWrl3L\n1q1bOX/+PBaLxfq8q6srLVu2pHfv3rRv357Q0FufI1EIIYQQjsXPz48XX3yRdu3asWnTJr744gv2\n7dtH0dV5lRMTE5kxYwarV6+mXbt2dO3albZt2+Li4mLnyEVZcNTkvyJ2MZUEUdyxlJQUVq1axYoV\nKzh16hRXrlwpUXzGycmJDh06MHDgQKKioggLu7U5EkXZKywslC9iIcQ9qaioiNzcXPz9/e0dSoVX\nrVo1XnzxRdq3b8/PP//M3Llz+fnnnzGZTJjNZs6ePcvChQv573//S+3atenZsydPPPGE/O/uMY7a\nglgRyVW6KLX8/Hzeeecd6tevz6BBg4iPj+fixYslksPWrVsTHx/PN998w6OPPkrlypUlObxLfP75\n54SEhNCoUSOOHDli73CEEMJm9uzZw/3330/lypWZNm2avcMRgFar5b777qNXr15s376db775hrp1\n61qfN5lMXLx4kS1btjBgwACioqL44IMPSsyRLByb47Yg2u7hKMq9BXHPnj04Ozs77Ekiiu/KxsfH\ns27dOjIyMko8p9VqCQoKomHDhrz00kt06dIFrVZrp0jFjVy5coVFixaRmZnJ0aNHWbp0KVOnTrV3\nWEIIYRPLly/n8uXLGI1G1qxZQ69evWRYw13gj2s/RVHo3LkzHTt25LvvvmPevHns37+f1NRU6zzL\niYmJvP3228ycOZPOnTvTrl073Nzc7PwKRGmpqsqBAwfsHYa4ReWeIH766ad8+umn5X1YUcZcXV2p\nV68eTZs2pUOHDrRq1UqKz9zFcnNzrWNALBYLOTk5do5ICCFsJz8/3zoG3mAwSCvUXUqr1dK1a1di\nYmLYsmULW7duZffu3Zw8eRKj0QhAcnIyixYtYtGiRfYNVlRYFhuNQbQ4UBdbGYMo7oibmxtt2rTh\n8ccfp1mzZtSuXRsnJyd7hyWEEEIIBxEQEEDPnj3p2rUrBw8eZPfu3axbt449e/ZYb2YKYS+26h4q\nXUz/gY+PD3q9vrwPK2zAYrGQnZ1tvatXs2ZNpk2bxoMPPoi/vz86ndxvEEIIIUTpuLq60rx5cxo3\nbkyvXr2Ij4/nnXfeISEhAQC9Xo+rq6sMU3JQ0prvOMr9in7SpEkMGDBAxqU5oMTERJ577jm2bt0K\nQNeuXXnsscfsHJUQQggh7hWKouDs7ExoaCi9e/fm4MGDfPjhhwDExsaycOFCwsLC7ByluF1ms5nF\nixfzwgsv2DuU2yYtiEIIIYQQQghhY47a8mvBNnMYWm6+yl1D5hsQQgghhBBClCmZB9FxSAuiEEII\nIYQQQlxHRexiKi2IQgghhBBCCCEAaUEUQgghhBBCiOuy3TyIAI4xDlMSRCGEEEIIIYS4DuliKoQQ\nQgghhBCiwpIWRCGEEEIIIYS4DrONupiaHaiLqbQgCiGEEEIIIYQApAVRCCGEEEIIIa7LYqMxiBYH\nGoMoCaIQQgghhBBCXIdtu5g6BuliKoQQQgghhBACkBZEIYQQQgghhLguy9WHLfbjKKQFUQghhBBC\nCCEEIC2IQgghhBBCCHFdFhuNQZQiNUIIIYQQQgjh4MzYpsCM+c53UW6ki6kQQgghhBBCCEBaEIUQ\nQgghhBBlTFEUe4dQKhVxmoubJoh79+7l1VdfpWbNmqiqSmRkJC+++CIjR45EVVUCAwOZMmUKer3+\nlg5YVFREbm4uWq32joMX5SsvLw+z+c8GcpPJRF5enh0jEqVVUFCAxVJcT0tVVflfijKVn59f4rPD\nbDZTUFAg55woMyaTCVUtvhqzWCxyvjkwo9Fo/bmwsJDExMQSy4RjUFWV9PR0e4dRKhbVNsmdI41B\nVNQ/PkFvYO/evSxbtoyZM2dal7355pvExsbSoUMHZsyYQUhICD179rzu9omJiTz88MOcPXsWk8lk\n2+iFXbm7u+Pi4mLvMEQpmM1mcnNzre9JFxcX3N3d7RyVuFf9/XxzdnbGx8cHjUZGOYiykZWVRX5+\nPgB6vR5fX1+5Me2gsrOzJbm/x+h0OqpXr87WrVsJDw+3dzg39EcO8/DvRtxskMLk62BrFf1d/7rh\nFruY/j2H3Lt3LxMmTAAgNjaWhQsX3jBBFPeuvLw8+dC+RxQWFlJYWGjvMEQFUVRURFJSkr3DEBWE\n0WgkOTnZ3mEIIRyUdDG9gTNnzjBo0CCysrIYPHgwhYWF1i6l/v7+pKSklGmQQgghhBBCCCHK3k0T\nxKpVqxIXF0enTp24cOEC/fr1K9FV9CY9VK3jTqZOnUpycnKJcSjCsXl7e+Ps7GzvMIQQdzmLxcL5\n8+fJzs4GwMPDg9DQUIctWCCEEKL0cnNzWb16tcPkBBVxDOJNE8Tg4GA6deoEQOXKlQkICODo0aMY\nDAacnJxISkoiKCjohtv/0bo4WwVqIgAABXhJREFUd+5cG4UshBBCCCGEcGQpKSlUrVrV3mHclHQx\nvY5vv/2W8+fPExcXR1paGmlpaXTv3p2NGzfy+OOPs2nTJlq2bHnD7evVq8eyZcsIDAyUAeJCCCGE\nEEJUYGazmZSUFOrVq2fvUMQN3LSKaV5eHq+99hpZWVmoqsrgwYOpVasWo0aNwmAwEBoayqRJkyT5\nE0IIIYQQQtwT/qhi2vB3A86mO2/+K9IpHKzi5BBVTG+aIAohhBBCCCFERZKZmUmHDh3Iysqy2T69\nvb35/vvv8fHxsdk+y4IkiEIIIYQQQgjxN5mZmeTm5tpsfx4eHnd9cgiSIAohhBBCCCGEuEpj7wCE\nEEIIIYQQQtwdblrF9E5NmjSJw4cPoygKb731FvXr1y/rQwpxjSlTpnDgwAHMZjMDBw6kfv36jBw5\nElVVCQwMZMqUKej1enuHKSqYoqIiHn30UQYPHkyzZs3knBR2tW7dOhYsWIBOp2Po0KFERkbKOSns\nIj8/n1GjRpGVlYXRaGTw4MHUqFFDzkchykmZdjHdt28fCxYsYN68eZw5c4a3336br776qqwOJ8R1\n7dmzhwULFjB//nwyMzPp1q0bzZo1o02bNnTs2JEZM2YQEhJCz5497R2qqGBmzJjBrl276NOnD3v2\n7CE2NpYOHTrIOSnKXWZmJs888wxr164lLy+PWbNmYTQa5ZwUdrFs2TKSk5MZPnw4ycnJ/N///R9R\nUVHyvS1EOSnTLqa7d++mXbt2AERERJCdnU1eXl5ZHlKIa0RHRzNz5kwAvLy8yM/PZ9++fbRt2xaA\n2NhYdu3aZc8QRQV09uxZEhISaN26Naqqsm/fPmJjYwE5J0X527VrFzExMbi6uhIQEMCECRPYu3ev\nnJPCLvz8/MjIyAAgKysLPz8/+d4WohyVaYKYmpqKn5+f9XdfX19SU1PL8pBCXEOj0eDq6grAqlWr\naNOmDQUFBdauKf7+/qSkpNgzRFEBTZkyhdGjR1t/l3NS2NPFixcpKCjglVde4dlnn2X37t0UFhbK\nOSnsolOnTly5coUOHTrQr18/Ro0aJZ+RQpSjMh+D+FdSMFXY05YtW/j6669ZsGABHTp0sC6X81KU\nt7Vr1xIdHU1oaOh1n5dzUpQ3VVXJzMzkk08+4eLFi/Tr16/EeSjnpChP69ato1KlSsyfP58TJ07w\n9ttvl3hezkchylaZJohBQUElWgyTk5MJDAwsy0MKcV07d+5k/vz5LFiwAA8PD9zd3TEYDDg5OZGU\nlERQUJC9QxQVyPbt20lMTOT7778nKSkJvV6Pm5ubnJPCbgICAmjYsCEajYbKlSvj7u6OTqeTc1LY\nxYEDB2jZsiUAkZGRJCUl4erqKuejEOWkTLuYxsTEsGnTJgCOHTtGcHAwbm5uZXlIIa6Rm5vL1KlT\nmTdvHp6engA0b97cem5u2rTJ+kUkRHmYMWMGK1euZPny5fTo0YPBgwfTvHlzNm7cCMg5KcpfTEwM\ne/bsQVVVMjIyyM/Pl3NS2E3VqlU5dOgQUNz92c3NjYceekjORyHKSZlWMQWYPn06e/fuRavV8u67\n7xIZGVmWhxPiGitWrGD27NlUq1YNVVVRFIV//etfvP322xgMBkJDQ5k0aRJardbeoYoKaPbs2YSH\nh9OiRQveeOMNOSeF3axYsYKVK1eiKAqDBg2iXr16ck4Ku8jPz+ett94iLS0Ns9nMsGHDuO+++xg1\napScj0KUgzJPEIUQQgghhBBCOIYy7WIqhBBCCCGEEMJxSIIohBBCCCGEEAKQBFEIIYQQQgghxFWS\nIAohhBBCCCGEACRBFEIIIYQQQghxlSSIQgghhBBCCCEASRCFEEIIIYQQQlwlCaIQQgghhBBCCAD+\nH6Mhm0ZPUshdAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f2297aaa490>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ball_xdat = []\n",
    "ball_ydat = []\n",
    "for m in moments:\n",
    "    ball_xdat.append(m[5][0][2])\n",
    "    ball_ydat.append(m[5][0][3])\n",
    "\n",
    "plt.style.use('seaborn-white')\n",
    "fig = plt.figure(figsize=(15, 11.5))\n",
    "\n",
    "scat = plt.scatter(x=ball_xdat,y=ball_ydat,c=ball_zdat,\n",
    "    cmap=plt.cm.RdBu, s=300, zorder=1)\n",
    "plt.style.use('grayscale')\n",
    "court = plt.imread(\"img/fullcourt.png\")\n",
    "img = plt.imshow(court, zorder=0, extent=[0,94,50,0])\n",
    "plt.style.use('seaborn-white')\n",
    "cbar = fig.colorbar(scat,orientation='vertical',fraction=0.025)\n",
    "cbar.ax.invert_xaxis()\n",
    "cbar.ax.set_ylabel('Ball height (ft.) above court')\n",
    "# xaxis is 0-94 ft. yaxis 50-0 feet (inverted)\n",
    "import matplotlib.font_manager as fm\n",
    "# zorder should be less than zorder of scatter, so court is drawn first.\n",
    "annotation_font = fm.FontProperties(family='Bitstream Vera Sans',style='normal',size=10,weight='normal',stretch='normal')\n",
    "#scat.annotate('[START] Connelly drives baseline',\n",
    "#              xy = ball_xdat\n",
    "\n",
    "#\n",
    "#plt.imshow(court, zorder=0, extent=[0,94,50,0])\n",
    "\n",
    "#plt.xlim(0,94)\n",
    "plt.title('Ball movement',fontsize='x-large')\n",
    "plt.savefig('img/Ball_movement.png',dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[-1, -1, 14.64474, 44.48211, 2.25707, 0, 132.22, 7.09]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "moment_data = []\n",
    "for m in moments:\n",
    "    for p in m[5]:\n",
    "        p+=[moments.index(m), m[2],m[3]]\n",
    "        moment_data.append(p)\n",
    "\n",
    "moment_data[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>teamID</th>\n",
       "      <th>playerID</th>\n",
       "      <th>xloc</th>\n",
       "      <th>yloc</th>\n",
       "      <th>zloc</th>\n",
       "      <th>moment</th>\n",
       "      <th>gametime</th>\n",
       "      <th>shottime</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>14.64474</td>\n",
       "      <td>44.48211</td>\n",
       "      <td>2.25707</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1610612744</td>\n",
       "      <td>2738</td>\n",
       "      <td>18.86386</td>\n",
       "      <td>23.97772</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1610612744</td>\n",
       "      <td>201939</td>\n",
       "      <td>18.87993</td>\n",
       "      <td>41.50729</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1610612744</td>\n",
       "      <td>202691</td>\n",
       "      <td>5.05095</td>\n",
       "      <td>29.13419</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1610612744</td>\n",
       "      <td>203110</td>\n",
       "      <td>12.88533</td>\n",
       "      <td>34.84216</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1610612744</td>\n",
       "      <td>203949</td>\n",
       "      <td>8.88615</td>\n",
       "      <td>20.38291</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1610612763</td>\n",
       "      <td>2440</td>\n",
       "      <td>27.47547</td>\n",
       "      <td>8.76582</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1610612763</td>\n",
       "      <td>201145</td>\n",
       "      <td>9.42341</td>\n",
       "      <td>11.88861</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1610612763</td>\n",
       "      <td>201584</td>\n",
       "      <td>4.21900</td>\n",
       "      <td>16.40298</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1610612763</td>\n",
       "      <td>201144</td>\n",
       "      <td>16.38252</td>\n",
       "      <td>44.27504</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1610612763</td>\n",
       "      <td>201188</td>\n",
       "      <td>19.68304</td>\n",
       "      <td>35.52727</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>14.33244</td>\n",
       "      <td>44.58121</td>\n",
       "      <td>2.58479</td>\n",
       "      <td>1</td>\n",
       "      <td>132.18</td>\n",
       "      <td>7.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1610612744</td>\n",
       "      <td>2738</td>\n",
       "      <td>18.88402</td>\n",
       "      <td>24.07005</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1</td>\n",
       "      <td>132.18</td>\n",
       "      <td>7.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>1610612744</td>\n",
       "      <td>201939</td>\n",
       "      <td>18.58140</td>\n",
       "      <td>41.39098</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1</td>\n",
       "      <td>132.18</td>\n",
       "      <td>7.06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1610612744</td>\n",
       "      <td>202691</td>\n",
       "      <td>5.04115</td>\n",
       "      <td>28.73857</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>1</td>\n",
       "      <td>132.18</td>\n",
       "      <td>7.06</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        teamID  playerID      xloc      yloc     zloc  moment  gametime  \\\n",
       "0           -1        -1  14.64474  44.48211  2.25707       0    132.22   \n",
       "1   1610612744      2738  18.86386  23.97772  0.00000       0    132.22   \n",
       "2   1610612744    201939  18.87993  41.50729  0.00000       0    132.22   \n",
       "3   1610612744    202691   5.05095  29.13419  0.00000       0    132.22   \n",
       "4   1610612744    203110  12.88533  34.84216  0.00000       0    132.22   \n",
       "5   1610612744    203949   8.88615  20.38291  0.00000       0    132.22   \n",
       "6   1610612763      2440  27.47547   8.76582  0.00000       0    132.22   \n",
       "7   1610612763    201145   9.42341  11.88861  0.00000       0    132.22   \n",
       "8   1610612763    201584   4.21900  16.40298  0.00000       0    132.22   \n",
       "9   1610612763    201144  16.38252  44.27504  0.00000       0    132.22   \n",
       "10  1610612763    201188  19.68304  35.52727  0.00000       0    132.22   \n",
       "11          -1        -1  14.33244  44.58121  2.58479       1    132.18   \n",
       "12  1610612744      2738  18.88402  24.07005  0.00000       1    132.18   \n",
       "13  1610612744    201939  18.58140  41.39098  0.00000       1    132.18   \n",
       "14  1610612744    202691   5.04115  28.73857  0.00000       1    132.18   \n",
       "\n",
       "    shottime  \n",
       "0       7.09  \n",
       "1       7.09  \n",
       "2       7.09  \n",
       "3       7.09  \n",
       "4       7.09  \n",
       "5       7.09  \n",
       "6       7.09  \n",
       "7       7.09  \n",
       "8       7.09  \n",
       "9       7.09  \n",
       "10      7.09  \n",
       "11      7.06  \n",
       "12      7.06  \n",
       "13      7.06  \n",
       "14      7.06  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pm_df = pd.DataFrame(data=moment_data,columns=['teamID','playerID','xloc','yloc','zloc','moment','gametime','shottime'])\n",
    "pm_df.head(15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>playerid</th>\n",
       "      <th>lastname</th>\n",
       "      <th>jersey</th>\n",
       "      <th>firstname</th>\n",
       "      <th>position</th>\n",
       "      <th>team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2571</td>\n",
       "      <td>Barbosa</td>\n",
       "      <td>19</td>\n",
       "      <td>Leandro</td>\n",
       "      <td>G</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2733</td>\n",
       "      <td>Livingston</td>\n",
       "      <td>34</td>\n",
       "      <td>Shaun</td>\n",
       "      <td>G</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2738</td>\n",
       "      <td>Iguodala</td>\n",
       "      <td>9</td>\n",
       "      <td>Andre</td>\n",
       "      <td>G-F</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>201574</td>\n",
       "      <td>Thompson</td>\n",
       "      <td>1</td>\n",
       "      <td>Jason</td>\n",
       "      <td>F-C</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>201575</td>\n",
       "      <td>Rush</td>\n",
       "      <td>4</td>\n",
       "      <td>Brandon</td>\n",
       "      <td>G-F</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>201578</td>\n",
       "      <td>Speights</td>\n",
       "      <td>5</td>\n",
       "      <td>Marreese</td>\n",
       "      <td>F-C</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>201939</td>\n",
       "      <td>Curry</td>\n",
       "      <td>30</td>\n",
       "      <td>Stephen</td>\n",
       "      <td>G</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>202691</td>\n",
       "      <td>Thompson</td>\n",
       "      <td>11</td>\n",
       "      <td>Klay</td>\n",
       "      <td>G</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>203084</td>\n",
       "      <td>Barnes</td>\n",
       "      <td>40</td>\n",
       "      <td>Harrison</td>\n",
       "      <td>F</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>203105</td>\n",
       "      <td>Ezeli</td>\n",
       "      <td>31</td>\n",
       "      <td>Festus</td>\n",
       "      <td>C</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>203110</td>\n",
       "      <td>Green</td>\n",
       "      <td>23</td>\n",
       "      <td>Draymond</td>\n",
       "      <td>F</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>203546</td>\n",
       "      <td>Clark</td>\n",
       "      <td>21</td>\n",
       "      <td>Ian</td>\n",
       "      <td>G</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>203949</td>\n",
       "      <td>McAdoo</td>\n",
       "      <td>20</td>\n",
       "      <td>James Michael</td>\n",
       "      <td>F</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1713</td>\n",
       "      <td>Carter</td>\n",
       "      <td>15</td>\n",
       "      <td>Vince</td>\n",
       "      <td>G-F</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2216</td>\n",
       "      <td>Randolph</td>\n",
       "      <td>50</td>\n",
       "      <td>Zach</td>\n",
       "      <td>F</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2440</td>\n",
       "      <td>Barnes</td>\n",
       "      <td>22</td>\n",
       "      <td>Matt</td>\n",
       "      <td>F</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2754</td>\n",
       "      <td>Allen</td>\n",
       "      <td>9</td>\n",
       "      <td>Tony</td>\n",
       "      <td>F-G</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2757</td>\n",
       "      <td>Udrih</td>\n",
       "      <td>19</td>\n",
       "      <td>Beno</td>\n",
       "      <td>G</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>201144</td>\n",
       "      <td>Conley</td>\n",
       "      <td>11</td>\n",
       "      <td>Mike</td>\n",
       "      <td>G</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>201145</td>\n",
       "      <td>Green</td>\n",
       "      <td>32</td>\n",
       "      <td>Jeff</td>\n",
       "      <td>F</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>201148</td>\n",
       "      <td>Wright</td>\n",
       "      <td>34</td>\n",
       "      <td>Brandan</td>\n",
       "      <td>F</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>201188</td>\n",
       "      <td>Gasol</td>\n",
       "      <td>33</td>\n",
       "      <td>Marc</td>\n",
       "      <td>C</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>201584</td>\n",
       "      <td>Lee</td>\n",
       "      <td>5</td>\n",
       "      <td>Courtney</td>\n",
       "      <td>G</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>203210</td>\n",
       "      <td>Green</td>\n",
       "      <td>0</td>\n",
       "      <td>JaMychal</td>\n",
       "      <td>F</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>203893</td>\n",
       "      <td>Smith</td>\n",
       "      <td>2</td>\n",
       "      <td>Russ</td>\n",
       "      <td>G</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>203919</td>\n",
       "      <td>Adams</td>\n",
       "      <td>3</td>\n",
       "      <td>Jordan</td>\n",
       "      <td>G</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    playerid    lastname jersey      firstname position team\n",
       "0       2571     Barbosa     19        Leandro        G  GSW\n",
       "1       2733  Livingston     34          Shaun        G  GSW\n",
       "2       2738    Iguodala      9          Andre      G-F  GSW\n",
       "3     201574    Thompson      1          Jason      F-C  GSW\n",
       "4     201575        Rush      4        Brandon      G-F  GSW\n",
       "5     201578    Speights      5       Marreese      F-C  GSW\n",
       "6     201939       Curry     30        Stephen        G  GSW\n",
       "7     202691    Thompson     11           Klay        G  GSW\n",
       "8     203084      Barnes     40       Harrison        F  GSW\n",
       "9     203105       Ezeli     31         Festus        C  GSW\n",
       "10    203110       Green     23       Draymond        F  GSW\n",
       "11    203546       Clark     21            Ian        G  GSW\n",
       "12    203949      McAdoo     20  James Michael        F  GSW\n",
       "0       1713      Carter     15          Vince      G-F  MEM\n",
       "1       2216    Randolph     50           Zach        F  MEM\n",
       "2       2440      Barnes     22           Matt        F  MEM\n",
       "3       2754       Allen      9           Tony      F-G  MEM\n",
       "4       2757       Udrih     19           Beno        G  MEM\n",
       "5     201144      Conley     11           Mike        G  MEM\n",
       "6     201145       Green     32           Jeff        F  MEM\n",
       "7     201148      Wright     34        Brandan        F  MEM\n",
       "8     201188       Gasol     33           Marc        C  MEM\n",
       "9     201584         Lee      5       Courtney        G  MEM\n",
       "10    203210       Green      0       JaMychal        F  MEM\n",
       "11    203893       Smith      2           Russ        G  MEM\n",
       "12    203919       Adams      3         Jordan        G  MEM"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def players_to_df(players):\n",
    "    players_reform=[[rec[arg] for arg in players[\"players\"][0].keys()] for rec in players[\"players\"]]\n",
    "    df=pd.DataFrame(players_reform,columns=players[\"players\"][0].keys())\n",
    "    df['team']=players[\"abbreviation\"]\n",
    "    return df\n",
    "\n",
    "players_df = pd.concat([players_to_df(home),players_to_df(visitor)])\n",
    "players_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>teamID</th>\n",
       "      <th>playerID</th>\n",
       "      <th>xloc</th>\n",
       "      <th>yloc</th>\n",
       "      <th>zloc</th>\n",
       "      <th>moment</th>\n",
       "      <th>gametime</th>\n",
       "      <th>shottime</th>\n",
       "      <th>playerid</th>\n",
       "      <th>lastname</th>\n",
       "      <th>jersey</th>\n",
       "      <th>firstname</th>\n",
       "      <th>position</th>\n",
       "      <th>team</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>-1</td>\n",
       "      <td>-1</td>\n",
       "      <td>14.64474</td>\n",
       "      <td>44.48211</td>\n",
       "      <td>2.25707</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1610612744</td>\n",
       "      <td>2738</td>\n",
       "      <td>18.86386</td>\n",
       "      <td>23.97772</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "      <td>2738</td>\n",
       "      <td>Iguodala</td>\n",
       "      <td>9</td>\n",
       "      <td>Andre</td>\n",
       "      <td>G-F</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1610612744</td>\n",
       "      <td>201939</td>\n",
       "      <td>18.87993</td>\n",
       "      <td>41.50729</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "      <td>201939</td>\n",
       "      <td>Curry</td>\n",
       "      <td>30</td>\n",
       "      <td>Stephen</td>\n",
       "      <td>G</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1610612744</td>\n",
       "      <td>202691</td>\n",
       "      <td>5.05095</td>\n",
       "      <td>29.13419</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "      <td>202691</td>\n",
       "      <td>Thompson</td>\n",
       "      <td>11</td>\n",
       "      <td>Klay</td>\n",
       "      <td>G</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1610612744</td>\n",
       "      <td>203110</td>\n",
       "      <td>12.88533</td>\n",
       "      <td>34.84216</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "      <td>203110</td>\n",
       "      <td>Green</td>\n",
       "      <td>23</td>\n",
       "      <td>Draymond</td>\n",
       "      <td>F</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>1610612744</td>\n",
       "      <td>203949</td>\n",
       "      <td>8.88615</td>\n",
       "      <td>20.38291</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "      <td>203949</td>\n",
       "      <td>McAdoo</td>\n",
       "      <td>20</td>\n",
       "      <td>James Michael</td>\n",
       "      <td>F</td>\n",
       "      <td>GSW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1610612763</td>\n",
       "      <td>2440</td>\n",
       "      <td>27.47547</td>\n",
       "      <td>8.76582</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "      <td>2440</td>\n",
       "      <td>Barnes</td>\n",
       "      <td>22</td>\n",
       "      <td>Matt</td>\n",
       "      <td>F</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>1610612763</td>\n",
       "      <td>201145</td>\n",
       "      <td>9.42341</td>\n",
       "      <td>11.88861</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "      <td>201145</td>\n",
       "      <td>Green</td>\n",
       "      <td>32</td>\n",
       "      <td>Jeff</td>\n",
       "      <td>F</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>1610612763</td>\n",
       "      <td>201584</td>\n",
       "      <td>4.21900</td>\n",
       "      <td>16.40298</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "      <td>201584</td>\n",
       "      <td>Lee</td>\n",
       "      <td>5</td>\n",
       "      <td>Courtney</td>\n",
       "      <td>G</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1610612763</td>\n",
       "      <td>201144</td>\n",
       "      <td>16.38252</td>\n",
       "      <td>44.27504</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "      <td>201144</td>\n",
       "      <td>Conley</td>\n",
       "      <td>11</td>\n",
       "      <td>Mike</td>\n",
       "      <td>G</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1610612763</td>\n",
       "      <td>201188</td>\n",
       "      <td>19.68304</td>\n",
       "      <td>35.52727</td>\n",
       "      <td>0.00000</td>\n",
       "      <td>0</td>\n",
       "      <td>132.22</td>\n",
       "      <td>7.09</td>\n",
       "      <td>201188</td>\n",
       "      <td>Gasol</td>\n",
       "      <td>33</td>\n",
       "      <td>Marc</td>\n",
       "      <td>C</td>\n",
       "      <td>MEM</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        teamID  playerID      xloc      yloc     zloc  moment  gametime  \\\n",
       "0           -1        -1  14.64474  44.48211  2.25707       0    132.22   \n",
       "1   1610612744      2738  18.86386  23.97772  0.00000       0    132.22   \n",
       "2   1610612744    201939  18.87993  41.50729  0.00000       0    132.22   \n",
       "3   1610612744    202691   5.05095  29.13419  0.00000       0    132.22   \n",
       "4   1610612744    203110  12.88533  34.84216  0.00000       0    132.22   \n",
       "5   1610612744    203949   8.88615  20.38291  0.00000       0    132.22   \n",
       "6   1610612763      2440  27.47547   8.76582  0.00000       0    132.22   \n",
       "7   1610612763    201145   9.42341  11.88861  0.00000       0    132.22   \n",
       "8   1610612763    201584   4.21900  16.40298  0.00000       0    132.22   \n",
       "9   1610612763    201144  16.38252  44.27504  0.00000       0    132.22   \n",
       "10  1610612763    201188  19.68304  35.52727  0.00000       0    132.22   \n",
       "\n",
       "    shottime  playerid  lastname jersey      firstname position team  \n",
       "0       7.09       NaN       NaN    NaN            NaN      NaN  NaN  \n",
       "1       7.09      2738  Iguodala      9          Andre      G-F  GSW  \n",
       "2       7.09    201939     Curry     30        Stephen        G  GSW  \n",
       "3       7.09    202691  Thompson     11           Klay        G  GSW  \n",
       "4       7.09    203110     Green     23       Draymond        F  GSW  \n",
       "5       7.09    203949    McAdoo     20  James Michael        F  GSW  \n",
       "6       7.09      2440    Barnes     22           Matt        F  MEM  \n",
       "7       7.09    201145     Green     32           Jeff        F  MEM  \n",
       "8       7.09    201584       Lee      5       Courtney        G  MEM  \n",
       "9       7.09    201144    Conley     11           Mike        G  MEM  \n",
       "10      7.09    201188     Gasol     33           Marc        C  MEM  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pm_merge_df = pm_df.merge(players_df,how='left',left_on='playerID',right_on='playerid')\n",
    "pm_merge_df.head(11)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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yiomUYjJDritzZklovv5adSRErmv1apnSLVlSdSTkxpjMkGvr2lUKE9kRmMgY8+Zx6wJS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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f229783a690>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from matplotlib.patches import Rectangle, Circle, Arc\n",
    "from matplotlib.collections import PatchCollection\n",
    "import matplotlib as mpl\n",
    "import copy\n",
    "clr='red'\n",
    "\n",
    "def left_court_patches(clr='red'):\n",
    "    # creates the patches for the left hand side of an nba court\n",
    "    # returns: list of patches\n",
    "    rim = Circle((5.25,-25),radius=.75, color=clr, zorder=0, lw=.5, fill=False)\n",
    "    bkbrd = Rectangle((4,-28),width=0, height=6, color=clr, zorder=0,fill=False,lw=1)\n",
    "    ra_arc = Arc((5.25,-25),8,8,theta1=270,theta2=90,color=clr,zorder=9,fill=False,lw=1)\n",
    "    ra_t = Rectangle((4,-21),width=1.25,height=0,color=clr, zorder=0,fill=False,lw=1)\n",
    "    ra_b = Rectangle((4,-29),width=1.25,height=0,color=clr, zorder=0,fill=False,lw=1)\n",
    "    ft = Rectangle((0,-33),width=19,height=16,color=clr, zorder=0,fill=False,lw=1) #*16ft. outside\n",
    "    lane = Rectangle((0,-31),width=19,height=12,color=clr,zorder=0,fill=False,lw=1)#*12ft. outside\n",
    "    ft_ia = Arc((19,-25),12,12,theta1=90,theta2=270,color=clr,zorder=9,fill=False,lw=1,linestyle='--')\n",
    "    ft_oa = Arc((19,-25),12,12,theta1=270,theta2=90,color=clr,zorder=9,fill=False,lw=1)\n",
    "    three_t = Rectangle((0,-3),width=14,height=0,color=clr,zorder=0,fill=False,lw=1)\n",
    "    three_b = Rectangle((0,-47),width=14,height=0,color=clr,zorder=0,fill=False,lw=1)\n",
    "    three_arc = Arc((5.25,-25),23.75*2,23.75*2,theta1=292,theta2=68,color=clr,zorder=0,fill=False,lw=1)\n",
    "    return [rim,bkbrd,ra_arc,ra_t,ra_b,ft,lane,ft_ia,ft_oa,three_t,three_b,three_arc]\n",
    "\n",
    "def draw_full_court(ax=None,clr='red'):\n",
    "    # Draws full court onto axis\n",
    "    # returns: axis\n",
    "    if ax is None:\n",
    "        ax = plt.gca()\n",
    "        \n",
    "    #full court components \n",
    "    fullcourt = Rectangle((0,-50), width=94, height=50, color=clr, zorder=0,fill=False,lw=1) #base and side lines\n",
    "    midcourt = Rectangle((47,-50), width=0, height=50, color = clr, zorder=0,fill=False,lw=1) #half-court line\n",
    "    rest_circ = Circle((47,-25),radius=2,color=clr,zorder=0,lw=1,fill=False) #restraining circle\n",
    "    cent_circ = Circle((47,-25),radius=6,color=clr,zorder=0,lw=1,fill=False) #center circle\n",
    "    patch_list = [fullcourt,midcourt,rest_circ,cent_circ]\n",
    "    for patch in patch_list:\n",
    "        ax.add_patch(patch)\n",
    "    \n",
    "    #left-hand side\n",
    "    left_patches = left_court_patches(clr=clr)\n",
    "    for patch in left_patches:\n",
    "        ax.add_patch(patch)\n",
    "\n",
    "    #right-hand side transform patches by rotating pi radians around center point\n",
    "    right_patches = left_court_patches(clr=clr)\n",
    "    tr = mpl.transforms.Affine2D().rotate_around(47,-25,np.pi) + ax.transData\n",
    "    for patch in right_patches:\n",
    "        patch.set_transform(tr)\n",
    "        ax.add_patch(patch)\n",
    "    return ax\n",
    "\n",
    "plt.style.use('seaborn-white')\n",
    "fig,ax = plt.subplots(figsize=(9.4,5.0))\n",
    "draw_full_court()\n",
    "\n",
    "plt.xlim(0,94)\n",
    "plt.ylim(-50,0)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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KSko4evQoHh4eNbsSCyGEEELcqKKigsuXL9O9e/eaRSivZ9FkplWrVrWmkWZlZeHh4XHL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\nSUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f229783ad10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_moment(df,moment=0,tc=['cyan','yellow'],ax=None):\n",
    "    if df is None:\n",
    "        raise ValueError(\"Input 'df' to plot_moment is None\")\n",
    "    if ax is None:\n",
    "        ax=plt.gca()\n",
    "        \n",
    "    binary_mask = (df['moment']==moment)\n",
    "    moment_df = df[binary_mask]\n",
    "    teams = moment_df.team.dropna().unique().tolist()\n",
    "    for t in teams:\n",
    "        team_mask = (moment_df['team']==t)\n",
    "        plt.scatter(x=moment_df[team_mask]['xloc'],y=-moment_df[team_mask]['yloc'],\n",
    "                    c=tc[teams.index(t)], s=200, zorder=1, label=t, edgecolor=tc[teams.index(t)])\n",
    "        for j,x,y in zip(moment_df[team_mask]['jersey'], moment_df[team_mask]['xloc'], moment_df[team_mask]['yloc']):\n",
    "            plt.annotate(j,xy=(x,-y),xytext=(0,0),textcoords='offset points',\n",
    "                         zorder=2, ha='center',va='center',snap=False)\n",
    "        #TODO(maybe): just plot annotations with circular bboxes, no scatter\n",
    "    ball_mask=(moment_df['playerID']==-1)\n",
    "    plt.scatter(x=moment_df[ball_mask]['xloc'],y=-moment_df[ball_mask]['yloc'],\n",
    "                s=100,zorder=3,c='orange',edgecolor='orange',label='ball')\n",
    "\n",
    "plt.style.use('seaborn-white')\n",
    "fig,ax = plt.subplots(figsize=(9.4,5.0))\n",
    "draw_full_court(ax=ax,clr='gray')\n",
    "plot_moment(pm_merge_df)\n",
    "plt.legend(loc='lower right')\n",
    "plt.xlim(0,94)\n",
    "plt.ylim(-50,0)\n",
    "plt.title('Player and Ball position at t=0',fontsize='x-large')\n",
    "plt.savefig('img/Player_ball_positions.png',dpi=300)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "Python [default]",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}