00_dx_quickstart.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"http://hilpisch.com/tpq_logo.png\" alt=\"The Python Quants\" width=\"45%\" align=\"right\" border=\"4\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Quickstart"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This brief first part illustrates---without much explanation---the usage of the DX Analytics library. It models two risk factors, two derivatives instruments and values these in a portfolio context."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import dx\n",
    "import datetime as dt\n",
    "import pandas as pd\n",
    "from pylab import plt\n",
    "plt.style.use('seaborn')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Risk Factor Models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first step is to define a **model for the risk-neutral discounting**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = dx.constant_short_rate('r', 0.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We then define a **market environment** containing the major parameter specifications needed,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "me_1 = dx.market_environment('me', dt.datetime(2016, 1, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "me_1.add_constant('initial_value', 100.)\n",
    "  # starting value of simulated processes\n",
    "me_1.add_constant('volatility', 0.2)\n",
    "  # volatiltiy factor\n",
    "me_1.add_constant('final_date', dt.datetime(2017, 6, 30))\n",
    "  # horizon for simulation\n",
    "me_1.add_constant('currency', 'EUR')\n",
    "  # currency of instrument\n",
    "me_1.add_constant('frequency', 'W')\n",
    "  # frequency for discretization\n",
    "me_1.add_constant('paths', 10000)\n",
    "  # number of paths\n",
    "me_1.add_curve('discount_curve', r)\n",
    "  # number of paths"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, the model object for the **first risk factor**, based on the geometric Brownian motion (Black-Scholes-Merton (1973) model)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "gbm_1 = dx.geometric_brownian_motion('gbm_1', me_1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some paths visualized."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "pdf = pd.DataFrame(gbm_1.get_instrument_values(), index=gbm_1.time_grid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "pdf.iloc[:, :10].plot(legend=False, figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Second risk factor** with higher volatility. We overwrite the respective value in the market environment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "me_2 = dx.market_environment('me_2', me_1.pricing_date)\n",
    "me_2.add_environment(me_1)  # add complete environment\n",
    "me_2.add_constant('volatility', 0.5)  # overwrite value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "gbm_2 = dx.geometric_brownian_motion('gbm_2', me_2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "pdf = pd.DataFrame(gbm_2.get_instrument_values(), index=gbm_2.time_grid)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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rFc0lSAhVxPf5g/TaJ64R+N6JNrz+IA9cX8zd2wpRxUwv1FFIEp++ZQnXLcugqWuIH75w+rIuCS3dQ/zg+dO4vQE+f8dSykuMbCxLR6tWsv9MZ1jL0CIAEwRhTnQ7ewnIAVYal5ERmzbhcYUJ+aTrjZzuq2LY55zFEQpXs+oWGzKzs/x4oZvW5ZIcr+HdE230TRIkXEu8vgB17QNkp8ai10anBMWo0Yr4ExVkdXn8fHCqA4NexdYVmTO+jkKS+MytpWxamkFD5yA/fOHMWBDW1uvge7+rwOXx8/htZaxbEvr7pVXHsHlZBnaHlzP1lqmvMePRCYIgXIF2RxcA2bGT/5GUJIlNmevwB/0c766YjaEJ14BzTaE3wKWLwt8tFwlqlZJ7thfhD8i8vG9hLJub2+yQVYWn8H18weguvWanjpSimCAPbP+ZTpwePzesyUE9Qb5XuBQKicc+UcrGsnTqOwb40YtnaOwc5D+fq2DY7eczt5aycWnGRa/ZsTobgA8rJm7uPnb+KxqdIAjCDHU4QonKOYapP6VuyFyDQlJwqOvYgq2zJIRvtP1QrDaGgozwSgJE0oaydBZlGjhW3Ut9x8CsX3+2VTR0oUxrZxgbZ/vPR/VaOWM9IS+fAfMHguw53oZGpWRn+fgpDdOlUEg8dlsp60vTqGsf4LtPncDh8vHIbhNbxplhyzHGUZyTwLlm21he3ITnjsgIBUEQpqnD0Q1AVmzGFEdCvNrA8tQyOhxdtA2Fl+AqLFzdVieWQQ+lBckTth+KJoUkcf+uYgCe31t3zX9oONN3HkkRynk61BndwslJBg06Tcy4xViPnOvBNuRh+6qsadXwmopSoeDx28soL01Dm6HnlhuKKC9Ln/DnunN0FmyKZHwRgAmCMOtkWabD0UmqLgVtTHgtRTZnrgPgkEjGF6ZwvtkGEHb9r2goyU1kjclIQ+cgx2t652wc0dZjdTKsaQUgWZtEjbUOq9sWtetJkkS2MZYeq2uscTpAUJZ562gLSoXETetyI35dpUJB7so0EpemUCF7+bczTfxTRSM/Pd/Ki43dfNhpxWwP9alcY0rDoFfxUWXXRWO8lAjABEGYdQPeQYZ9TrLjwk+SLU0uIUEdz/HuCryB2WsXIkSXxWUlGIxsjbeqxpH8rylaCUXbvTuKUCokXvqwYdI34qvZifpOFAl9JChTuSl/16wUTs4xxhGUZbosHy/xnanvp8viZENZ+oz7RE7GFwxyxjpEXIySHZlJLE2KJUEdQ5fTS4VliD0dFn5T18nh3gFUMQq2rMhk2O2fNPgWAZggCLOufSiU/zWdAEypULIpcy3ugJuK3rPRGpowA7Is45zmDtVORzc/PfME3zz8bzx15uWIjcXhcVITOIihrBK1fm5rcaUl6bl+TQ79A27ePTF1UvbV6HhnJZICEuNv4q3OZAyxn+Rgr56Xm7rZ12XlrHWITqcHbwS7A1zYkmjUW0dCs3C3bMiL2HUudN42jDsQpDw1nptyUnlocRZfXZbPt9cU8dfL83l4cSYqhcTBbhtBWWb7qmwk4IOKiZchRS9IQRBmXedI/lfONAIwgE1Z63i75X0Odx1nQ+aaaAxNmIG9bft5pf4NChMKuC5rPeVpK1Ar1eMea3PbeaPpXY50nUBGRikp2VO/n82pG6+432etrZ4nzj6PIm0AP/Dvx/8fX1jx6IQ15mbD7dcVcKiqm1cPNLG0IJn8OdgUEC0eX4AeuYFY7Vbs/liSNSoGvWr8chwn+4cuOlatkPhieSEZ0pXP+4wl4veHEvHr2u3UdwywsihlrGF3pJ3qHwSgPPXigq5KSSJFqyZFq2ZVioHjfYPU2IcpS4pjaWEyVY3WCc8pZsAEQZh17Y7RGbCsab0uVZdCSWIRdfZGep190RiaME1uv5s9zR8QIylpGmjh6eoX+PuD3+V58yu0DX3cksfld/Faw1t858h/cLjrOBmxaXxpxWf4pOlP8Af97Gn54ArG4OF586v8uOIXDPkG8XUWsiFpGwOeQX5w8mec7DkdiVudkVitisc+UYo/EORnr1ZdUxXyTzd2ok3NQa0yka3X8OWleTy6OJaBoSfI01TycHEmt+amssGYQFCGn5xs5Kx1aOoTT2E0yBqdARub/dqYf8XnHo/d46N+0ElurJY03fgfLAA2p4c+QBzqsQNw/RQ7McUMmCAIs67D0YVWqSF5BjMem7LWUWtv4HDXCe4suiUKoxOm40DHEYb9Tm5bdBPrMso53HWcw53H2d9xmP0dh8kz5GBKWsyhrmMM+5wkahK4bdFNY6VFAsEA77Z/yKHOY9yUv3Pas2B1tgaern4Ri9tKRmw6QzWlDPXH8skHtrLaXsiT557jiXPP0uHo5rbCm1BEYAZmulYuTuUTm/J543ALT7xZzbc/v2nWxxANe7sa0MWuRYWPR0oWoVYqRgonJ1NtPcnDpbdQmhjaCLE8OY5nGrr4XUM3nkCQtcaEGV83TqciIU5NR5+Djj4Hp+v7KcqOpzhn5uecTIVlCBlYkzp5O6N0nYaieB0Ngy66nR5WLk7l/z5UPuHxEf9NNJlMKpPJ9LTJZDpgMpmOmUymO0wm02KTyfTRyGM/M5lMipFjvzVyzCGTybQ+0mMRBGH+8QZ89Dj7yIrLnNGb4SrjcnQxOo50ncAjkvHnlDfgY2/bfrRKLdtzriNVl8zthTfz/23+Ol9c8WmWp5bSNtTBu60fEggGubPwFr618f+wKWvd2M9eqVByT9kt+OUA70xjFswT8PJC7av8qOJ/sLpt3Ji3g8eKH6e/S0tpfhKqGAXLU8v4m7V/QaouhXda3ucXZ5/C5XdH69sxqbu2LsKUm8ip2j5e2984J2OIpMZBJ0P6DGTZw/1FKRhUofmciwon93xcOLkwXs9fry9Gq1Tw++ZeDnZf2U7JnNRYLIMeXjnQBMCtG/KRpMiXHJFlmVP9g6gUEiuSp17evHQWrCR34g8U0fgo8CnAYjabtwK3AP8N/AD4x5HHJOBOk8lUDmwHNgAPAD+JwlgEQZhnuod7kJGnnf81Sq1UsSVrA4PeIZ46/zuCcmR30AnhO9R1jCGvg205m9CrPu4BqFQoWZ5axhdXfIbvXvf3fHbpg3xn099xU8HOcXPDtuavJ1WXwqHOY9jc9imv6/Z7+P7Jn7Cv/RDp+jT+es2fc9fiW6luCuXpLC/6uPp9Zmw6f7v2L1mSVMzZ/vN87+RP6HNO3SYm0pQKBV+4cynxsWqe/OM56tuv3gKtvS4vT9V1AhJ+xzHKktMven50dvNw58UlYwoSY/l8aQ4GlZI32vrZ22GZcY200WXIU7V9ZKboWVmcOqPzTKXZ4cbi8bE0MQ5tzNSV9U0JoVy405YhnFPsfI1GAPYi8I0L/tsPrAH2jfz3W8ANwBZgj9lsls1mcysQYzKZjFEYjyAI88hoC6KsGQZgALcV3kRxYiGn+6p4vfGdSA1NmAZ/0M97LftQKVTsyt064XGJmgTWpK8iTh074TFKhZJbCq4nIAd4u+X9Sa8ryzK/rXmRDkcXGzPW8vV1X2FRQmjn29mR8hPLCy8uPxGr0vNnKz/LzpwtdA/38J8n/wu7Z/YDoMQ4DV+4YymyLPOz16oYcl59M7gOn5/f1HXgDcq43PsxjdPHNV5tYHlKKe2OTlqHLt79ma7T8IUluSRpYtjbaeXNtv4ZBWGjPSEBdm/IQxGF2S+4IPneOPny4yiFJLEpLQG/LHO8b/LfsYjngJnNZgeAyWQyAC8B/wh8z2w2j36Hh4AEIB648GPI6ONTZtYajdfOLpJwLcR7hoV733Dt3ru1rR+AZTlFGFPHv8dw7v3rO/6Mf3jvP9jT8gFFaTnsLNwc0XHOhavpZ/5+4yFsHju3luyiMHvmwfSoW5dt4922DzjcdZwHV99Oauz4Nbxer3mPU72VLEkt4stbHiVGGXob8/gC1LTayU03ULp4/ObuX0p/iMzqVJ6tfJWDvYf4dPl9Vzzu6TIaDXTZXTzzVg2/eaeWb31u45xU658JTyDIL4/WYvP4CbjM+Px13LflwXF/b3eXbufMgXNU2E6zprB07HGj0YAR+Loxjh8eq+dgjx1JpeTh5dMLopYVpwE1JMdruX37YlRhzE5Nl8cfoOqUgxSdmg2FaWGP76ZEPe91WjnWP8jdyyYuixGVJHyTyZQLvAL81Gw2P2symf7jgqcNgB0YHPn60sen1Nd35bsoriZGo2HB3TMs3PuGa/ve6/takJDQ+xPGvcfp3Pvnlz3Kf574b35x4lk0fj3FSUWRHu6suZp+5oFggJer3iRGUnKdcdMVj9toNGC1OLkpdxdPVT/PsxWv80nTn1x2XK2tnt9WvkK82sAjpk9is7rGnjvbaMHrC1CWnzjpeDYkr+dt7T7ebTjAlrQtJGhmP+i9d1cJZ8x9nDL38us/nOWO6xbN+himyxMI8ruGLpoGnCyJV3NkcD8qTwrxithxv9/ZylwS1AYONB/jluybUStVl/2Of3ZxFk/WdvBRu4V4SWJLRvidCwxqBZuWZrDGZMRum14NunCd6h/EEwhyXVIclv7Le09OZnWKgSO9A+yr62KXafzd3tFIwk8H9gB/Zzabnxh5uMJkMu0Y+foW4ABwELjZZDIpTCZTHqAwm839kR6PIAjzR6gFURdGXQqaCepETUea3sjjyx8B4JdnnxalKWZJRW8lfS4LGzPXkqiJ3M6ztemrSNOlcrjzOBbXxUnaNredX1X9FoDPLXuYBM3FS0JnG0ILKisKU5hMjCKGm/J34gv62du6b9Jjo0WhkHj89jKS4zW8dqCJ880T14qaD/pcXn56vg3zgJPF8XpwVCNJUKhbMuFrlAolGzLX4vK7Od03fuHkWJWST5dko1Mq2NthZcgXfomOGOVIf8aS6GUunZyg9lc4NqVdnIw/nmjkgP09kAR8w2QyfWgymT4ktAz5HZPJdBhQAy+ZzeaThAKxw8DLwJ9HYSyCIMwjds8ATr/rivK/LlWSVMQnTX/CsN/Jz878muFpVmQXpicoB3mn5QMUkoIb83dG9NxKhZLdI7lgey7IBfMF/fyy6mkcvmHuKb6dosSCy15b2WhBo1ZSPMmus1GjgeOBjsMMeac3sxEpcToVX7pzGQqFxM9fO0ev3TX1i+bAOZuDn55vo8/t5br0RB4tzuKcrQpZhu2LJi+GvClzLcBlyfgXilUpuTEnBU8wyDtt82cOxur20TTkYpFBR7Jm+o29jTo1JQl6WhwT77qNRg7YV4CvjPPU9nGO/Tbw7UiPQRCE+Wm0AOtMd0BOZFPWOnqcfbzb+iG/PPsUf7Hqc8QoRJnDaDjbf57O4W7WZ5STqot8r8W16at4u3kvh7tOcFP+LlJ0SbxY+xotg22szyhne/bluX49Vie9Nheri1OJUU49r6AamQV7ofZV9rbu567FtwJQY3ewr8vGTTmpLDLopjjLlSvKTuChG0t46h0zP3rhDH//8BridNN/s4+GoCzzbruFfd02VAqJ+wszWJliwOKy4lD0IjlSWJ43eSHlNL2RxYmLqLU30Oe0YGT85d71xgSO9w5wyjLE+rQE8uKi/72fyklLaPZrqtpfk9mSnkTtwMQfCEUlfEEQZk3HSAui6fSADNcdRbtZZVxGnb2R35lfmfH2dmFisizzdvP7SEjcHOHZr1FKhZJbFt1AQA7wTsv7HOo8zsHOo2THZfJJ05+MW+upcnT3Y9Hky48X2py5jgS1gX0dh3D4hqmxO/htfRctDjdP1nZQOzA89UkiYMfqbHZvyKPb6uS/f38Wn3/uy6oM+wI8WdvJvm4byRoVXyrNZWVKKHj6sCnUaDsrphilYuoQYnNmqMTnka6JZ8EUksRt+aGNE6+39BGc4/93g7JMRf8gGoWCZUkzb220OEHPl5dOnIQvAjBBEGZNxwxbEIVDISl4pOwB8gzZHO46TmX/+YhfY6GrsdbROtTOKuMyMmLTp37BDK1JW0maPpXDXcd5vvYV9DE6Pr/8kQn7S46Wn5gq/+tCKqWKG/J34A14+X3DSX5b341CkrgxOwVZhqfrujhnm53lyT/dUcRak5HaNju/frN6Tj88dAy7+cn5VuoHnSxJiOXPy3LJ0GvGnj/ZW4ksS2zMXiUwtCQAACAASURBVBXW+VanLUer1HKk+yTB4MTB5SKDjpXJBjqcnrHcq7nSOOjC7vWzPDkOdRgzqpO58Ht3KRGACYIwazocXehitDNqQRQOjVLNo2UPICHxVvN7YhYswt5q3gvAzQW7onqdUF2wGwjKQQLBAJ9e+iCpuvGDK48vQE2LnWxjLMnx2mldZ0vWBgyaxVQPpiEh80hxFjuzknm0JAulBM/Vd1ERRjDQPdzLk+eeo7Lv3LSuP0ohSXzutjKKsuM5cr5nrLr7bPIEgrzV1sfPqtsY8Pq5ITuZTxVnorugvEOf08JAsJfgQAprF4fX4FytVLM2fSV2zwCVPdWTHntLbipqhcQ77f1TFjG9EtU2B3s7LLQ6XOPOto0GgFey/BgOEYAJgjArvAEvvc5+smIzo9IyZFRGbDqr05bTNtTBOUtN1K6z0NTbm2gYaGJZyhJyDdlRv97a9FVsy97EQ0v+lKUppgmPM7fa8AeC05r9GtU27CdGvQOQMRm6KYrXA1AUr+ezpmzUSgUvNfVwrHf8gpq+oJ83m97lX4/9kOM9FTx5/rnLdm+GS61S8pf3rMCYqOWPh5o5cKZz6hdFgCzLnLEM8cOzzRzotoM3SEq/l6ThIMHgxcHJ0a5Qa6GkQAEJseHvYt44koz/YfORSY+LV8ewKysZpz/Iex3R6VZg8/h4rqGbvZ1Wfl7dzr+cbuSFhm5OWwZx+gO4/AHO2RykalXkxU0voJ8uEYAJgjArukZbEBkin/91qd0F1wOhGRsxC3blvAEvL9a+BsDNI9/baFNICu433c2mrHWTHlfZMFr9fnoBWOOgk6fqOpEkiaDvABU97+Hyf7wTMS9Ox+NLctDHKHm1pZcDl/QurLc38W/HfsQbTe8Sq4plW/ZmPAEvz9S8OOP2WPF6NV+7bxWx2hieesfMuSiXp+h2evhfcwfPN3Yz7Avga3fQ+VEnVWd6+K+Xz/JX/32QZ/aYaegcQJZljnaeRg5KrE5bPq3rFMTnka43crzjDE7f5Ls9N6cnkapVcbR3gC6n50pub1xvtvXhl2W2ZSSxzhhPjKTgtHWIFxp7+OeKRn5yvg2/LFOeEh/VD4oQpUKsgiAIl2ofy/+KfgCWHZfJKuMyTvdVUWOtozSlJOrXvFbJssyzNS/T7ujkuqz1FCbkz/WQxsiyzNlGC1q1ksU54dcjaxpy8VRdJ0FZ5qHFWbTai3mtsZ597YfGgneATL2Gx5fk8IS5g7fa+vEGgmw06vhD09t81HEECYlt2Zu4o2g3WqUWq9tGlaWaAx1H2J4zs84MGcl6/vKeFXzvdxX89JWz/N+H1hCrjaHH5qLX5hz5d+hrX0Dmb+5fRUrC9GZq3P4A73VaOdJjJwikSUqqD7UTcAV48PrFLM5J4FBVN8fO9/D+qQ7eP9VBanqQ4fxegoNG1myYXg6nJElsyFjDHxrf5lTvGbZkb5zw2BiFxG15Rp6s7eT1ll4eX5ITsUCofsDJOdsw+XFabs5JQZIkZFmm2+WldmAYs32YVocblUJidZSXH0EEYIIgzJKOkR6QsxGAQWgW7HRfFW82v8eS5OKof5q9Vn3YfpDjPRUUxOdxb8ldcz2ci3RbnfTZ3awpMYZVfgKgfdjNb2o78MsyDxVlsiQxloK4TbzXuo/3Ww+wI+c6tDEfBzRpOjWfL83hVzXt7O20srflMAPuKjJj03lwyT0UJhSMHfvgknv47tHv82r9G5Qml5Cmn1mD6JLcRD77iVJ+8YfzfOuJY+MeE6OU8AdkDlR2ctfWwrDPPewL8N/nWhnw+UnWqDBYvRw90kysNoYv3b+SsoJQaZGCjHju37WYc01WDlV1c3rwCEogZiibRZnTD07WZ5TzeuM7HO0+OWkABlCSEEtpYizV9mEqrY6xHZhXIhCUeb21Dwm4Pc849vdAkiQy9Roy9Rq2Zybj8gfwBmUS1NEPj0QAJgjCrGgf6kJCIis2Y1aul2vIZnlqKWf7q6mzN1CStHhWrnstqbM18Pv6P2JQx/H48odRzbPaamcbQ0t00yk/8UGnFW9Q5sGiDEpHSgxoY7TszN3KH5veYX/HYW7K30kgGKBlqJ1aWwN1tga6Bm1o9XfjlzK4vTCbG/K2X1ZrLkETz/0ld/Hr88/xTPULfLX8iyikmWX6bCzLwO0NcPBsF8kGLenJOtIS9aQl6UhP1qNRKfjafx3k8Llu7tyyKOwPGNV2BwM+P6uS4mg52c3RJhtZqbF8+Z7lpCXpLzpWqVCwoiiVFUWp/MvR9+gcVvDFHbtm1LsySZvI8vQlVPZU0+PsI10/eQX7T+QaqRtw8lZbH0sSY9Fc4W7Ew712+txe1hvjyYqdeMZQF6NktqqQza//mwRBuCbJskzncBdp+tQJSwlEwy0FN3C2v5o3m94TAdg0Xdr6J5IthyJltPxEuPlf/mCQhkEnqVoVy5IvnlXZkbuZvW37eK9lH7W2BhoGmvEGvGPPZ8Sm45d86DSF3JxfNGHAsyZ9FRV9VZzuO8sHbR9xfd62Gd4d7FiVzY5VE294KC8xcvhcN/UdAxTnhLezuG6kMOipg230djlYtTiVx28vQ6eZOBzod1noGO6kLNnEsvyZf4DaXrCRyp5qjnWd5Pai3ZMem6xVsTUziQ86rbzc1MP9RRkoZziLPeTzs7fTik6p4Mbsmc1KRoNIwhcEIeqsbjsuv3vWlh9H5cfnUpZsos7eSL199rf2X618AR+/rHqaIZ+De4pvZ3Hi/GsW7fEGMLfayE2LI8kwca2lCzUNufAGZUwJsZc9p4vRsTN3K8N+J9XWWlK0SWzL3sxjyz7Fv235Jt/Y8NeUJiXhCsj0u30TXkOSJB4w3U2cKpY/NL5N93DvjO9xKpuXhYKhw1XdYR0flGXqBpwE3X56uxx8YlM+f3HP8kmDL4CK3lAvx9VpK65ovOtzVqFVajjafSqsjQo7MpMoiNNSZXPw+6aeGRdo3dNuwRMIckN2CrEq5dQvmCUiABMEIeo6ZjEB/1K3LLoBgLea3pv1a1+NZFnmhdpXaRlsY0PGmnFb/8wH1a02/AF5WrsfzSOzP6bEywMwgN35u/jyqs/zb1u+yT9u+GvuN91FedoKDOrQUuVoe6Jmx+Q7+QzqOB4w/Qn+oJ+nqp8nEIxOTavS/CQS49Qcr+kNq4J+x7AHdzCI2+Lmk9cXc8/2IhRhzCpV9J5FISlYYSy7ovFqYtSUp63A5rFTa2uY8niVQsGjJdnkxmqpsAzxWkvvtHc1tzncnOwfJEOnZn3a/JrFFQGYIAhRN9sJ+BcqTMjHlLSYGlsdTQMts379q81HnUc51HWcXEM2D0zQ+mc+ODtSfmLFNPK/zPZh1AqJggl6DSoVSkzJi8cCrksVjAZgQ1M3zl6dtpy16atoGWxjb+v+sMc4yuV382Lta/y88kl8Qf+4xygUEhvLMhh2+6lsmLqRdZVlCACVM8DO8vBquVlcNlqG2ihJLCJONX7gOh0bRmqCHe0+GdbxGqWCT5dkkanXcLxvkDfa+sMOwoKyzOutoRnI2/KMM17CjBYRgAmCEHWjAVhOFFoQheOWgpFZsJFK7sL4GgdaeLH2NeJUsTy+7BHUyvnRGPpSwaDMmYZ+dJoYirLD25HX7/Zi8fhYHK8nZgZJ5ABGrRp9jIKmMAIwgPtK7iJebeCNpj10OsJbJgQ4Z6nhn4/+gA/bD3K2/zxma92Ex44uQx4KYxnydHeonte2ovB3jVb0VQJQfoXLj6OKEgpI1SZzuvcsbr87rNfoYpR8tiSbNK2aQz129rRbwgrCKvoHaR/2sCI5jsJ4/ZTHzzYRgAmCEHWhFkS6OUvkLk4qZHHiIs5ZamgZbJuTMcx3sizzTPULBOUgn136ECm6pLke0oSqmqxYBz2sW2IMqyE0hGa/AJZMsPwYDoUUmj2ze/3YPBPngY2KVel5cMk9+OUA3z/5E543vzppIObwDfOb87/jp2eeYMA7yNr0UL/Fyfqa5qTFkZsWR2WDBYdr4jENeXwMSkECQz5umCSx/1Kne88iIbHCuDTs10xGkiQ2ZK7BG/SN5ZaFI1al5LEl2aRoVOzrtvFB1+RFat3+AG+3W1ApJG7JnT+J9xcSAZggCFHlCXjpc1nIiYtuC6KpjM6Cvd38/pyNYT4z2+rpcfaxPqMcU/L83jG673QHANunEUiYB0IBWMk4CfjTMZ1lSIDlqWXcW3InGqWG/R2H+OdjP+Bb73+fE90VFy0tnuqt5LtHvs+x7lPkGbL5v+u+wqNlDxCniuVs//lJk9Y3Lc0gEJQ5Vt0z4TFvne9CkiSyteopk+5H2dx2mgZbKU4qmnBZdiY2ZKwBwl+GHGVQxfCYKZskdQzvdVg50BXqTiDLMp5AEIvbS8uQi3M2B6+09DLsD7AzM5kE9fycyRVlKARBiKpORzcy8pzkf13IlLSYwoR8KvvP0T7USY5hbpZD56sDHaE+fVunKJI512xDHs7UW8hPN4RdENQTCNI05CJLryH+CgtsXpiIH2619B0517E1ayNnLdUcaD9MdV8d1X31xNX9gc1Z6+l19nG6rwqVIoa7im5lV+5WlIrQbr1lKaUc6T5By2A7ixLyxj3/xqXpvPhhPYerutlVfnmT7KAsc7p7AFK1XF+cHva9VvSFZqjKp9l6aCopumSKEwupszfS77KSqksO+7WJGhWPLcnhF9XtvNXez+FeO8P+AL7g5UuSKRoV12WEV55jLogZMEEQourjHZBzG/BIksRN+TsBONg5fnXxhcruGaCy/xw5cVkUxI//Jj9fHKgMtRDavir836eGQScBmXHLT0xXhl6DWiGFPQM2SqlQssq4jL9c/Tg/vvU77MrdSlAOsqflA073VVGUsIivr/8aN+bvGAu+gLGdh5X95yY8d2KchrKCZBo6B+mxOi97/kx9P4HYGBRBmVJj+FXlK0aWH1cal03jTsMz3WT8CyVrVHxuSTaZOjVBOZSbV5KgpzzVwLaMJG7NTeW+wnS+VJaLKswl6rkgZsAEQYiqj3dAzk4F/MmUJZswqOI42XuaPy2+/aI3uoXsYOcxgnKQrdkb5+2uRwgl3+8/04lGrWRDWfgzOTUj+V+mxCtPxFZKEvlxOuoGnTh8fuJU038bzTSkcU/x7dxeuJszfVVjwdl4VfOXJJegUsRQ2X+eO4tumfCcm5dmcK7JyuFz3Ze1Jnqroh3lojgW6bVh7wS0ewZoHGimOLGQePWVtwK61Grjcl6ofZWjXSe5peD6aXcMSNWq+ctl86cv6UzM39BQEIRrQrsj1IIoc5ZaEE1GqVCyNn0Vwz4n563muR7OvBAIBjjUeQytUsPa9NVzPZxJnW20YB30sLEsPew8JlmWqR0YRh+jJGeSFjTTsWiaeWATUStVrMtYTXnaigkDEI1SzZLkYrqHe+h1TlxqorzEiEal5PC57ot2CDZ1DdLpDSXnr0gLv4fj6d4q4MqLr05EG6NhtXE5FreVBntzVK4x34kATBCEqJFlmU5HF+l647wpabAuIxRkHO+umOORzA9nLdXYPQOsz1iDNia8ivJzZd/p0HL2ZO15LtXl9DDoC1CSoA+r6Gg4RhPxm4bCK6NwpVakhnYgTrYMqVErKS8x0md3U98xMPb420dbUaeEAs/iaZRiqOirREJiVRSWH0fNNBn/WiECMEEQouZs/3ncAc+8SnjPM+SQpk+lsv8crjDrEF3LDrQfBuZ/8r110M2Zhn4KMgzkZ4S/JDZW/T4C+V+jcmI1xEjSlBXxI2VZaikSEpV9E5ejANi8/OLWRL12Fydqe9EmazFqVSRqwvsQNOAZpMHeTGFCAQma8GfNpqs4qZAkTSKnes/QONCMxWXFG5i4lIYsyzh9Ljod3Zy3mDnadZIBz2DUxhdtIgdMEISoGPAM8tual4hRxIwlv88HkiSxPr2cPzbt4UxfFRtHkoEXol5nHzW2OooSFpE1D3L0JnOgsgtZZlrJ9xCq/yUBJQmRK8QZo1CQG6eleciFyx9AFxPdXMJ4tYFFCXk0DjQz5HVMWBKiNC/UmuhYdS+fvKGYd4+3oUrQgEKieBoB6Jm+KmRkVkd49+OlFJKCjZlreKt5L98/+dOxx3UxWuLV8cSr44hTxTLsc2L3DmB3D+ANXhyglaWY+POVj0V1nNEiAjBBECIuKAd56vzzOHzD3Ft855yXoLjUuozV/LFpD8e7KxZ0APZRx1EAtkV59ssbCKIOs/L6eALBIPvPdKKdZvL9sC9A27CbvDhtxIOkgjgdTUMuWh3uCXtLRtKK1KU0DrRQ1V/Npqx14x6jUEhsXJrB20dbOVTVzYHKThKKQ2UYprX8OFIgNZrLj6NuyNtOnCoOm8fOoHeIQc9Q6N/eIXqcHzcyj1PFkq43kqBJIFGbQKI6gVO9Z6i21NLvspCqC78l1XwhAjBBECLu/bYD1NjqWJqyhO0586+Zc6ouhcKEfMy2euyegTmr0D+XvAEfR7pOEKeKZWUUZzqahlz8b007DxdnzbgK/dkGK7YhDztWZ6OdRh2vusFhZK6s+v1ECgxa6Ard3+wEYGW82vAmlf3nJwzAILQb8u2jrTz7Xh0+f5CEjDjc0scbB6Yy5HVQZ2+kMCGfJG30a2hpY7TsyL1u3OcCwQAOnxO9SodKcfnPPVmbyFPVz/NRx1HuWnxrtIcacSIHTBCEiGodaucPDW9jUMfxcOl987aswbr0cmRkTvScnuuhzImK3kqG/U42Z60f980tUmrsoSCo0jo043OMVr7fMc3lx7HyExHM/xqVF6dDwZXvhAxXemwa6Xoj1dZavAHvhMeNtiby+YPo49Q4JJkCgzbsGcjTo8uPxuguP4ZDqVCSoDFM+PtZnraCWJWew13HJ2xYPp+JAEwQhIjxBLz8+tyzBOQAj5TeH9H2JZFWnh7a+r9Qd0Pu7ziMhMSWrA1RvU7bcGijQ/2Ak2AYDZQvZR10U9loYVFmPHnp4SffB2SZugEnCaoY0nXqaV93KhqlgqxYDe1ON97AxG2CImlF6lJ8QR81kzTnho8bdC9fGVquXRwfXgAqyzKnekPNt1dFOf8rElRKFZsy1+HwDVMxMu6riQjABEGImJdq/0Cvs59duVspSzHN9XAmFaeKZWmKiXZH56QNkq9FbUMdNA+2sjTFRMo02sBMV0CW6RgJwBz+AD2uiWduJrL/TOeMku/bHW5cgSCmRH3UZmEXGXQE5Y+DzGj7uCr+5LshU/LsxG94nx5dqDfkorjJA1C3383+9sP86/EfUWurZ1F8Hsna+duM/UJbskL5i6OttK4mIgATBCEiTvVWcqjrGDlxWdwxScXu+WRdejkAx3sW1izYgY7R0hObonqdHpcXX1BGP5IAXzdweZucyYwm3+s0SjaUhp98D1AzMFr9Pnr5WQVx4RVk7XF5sLinH3xedr34PAzquEmbczcNtPBMze8I4McZiCcYHObHFf/OszUv0WBvvqhIa4eji+fMv+fvD36X52tfoWu4h9VpK3ik7P4rHutsMepTKE0uoXGgeazrxtVCJOELgjClakstz5l/T5o+lYL4PAricymIzyNOHXpzs7ptPFvzMmqFis8sfTCqOUWRtDy1DK1Sw/HuCm4vvHna7VDC4Qv6cfldUWnnMhMuv4vj3RUka5OiPkvZ5gjNDG1JT2RPh4X6wWG2ZYY/s1LZYMHu8LKzPBuNenq7GM32YWIkiSJD5MpPXCp/rCDrxAFY/aCT39R2EJRhWXIcOzOTMTKz3wWFpGB5ShmHuo7RNNBKUWLBRc/3u6z8vPJJAnKQ+0yf4a0OBanqQSx+DQc7j3Gw8xhGXQqrjMuptzfRNNgCQJImkRvzdrI5a11U635Fy9bsTVRbaznQcYQHTHfP9XDCdnX8lRQEYc64/G6eqXmRAc8gFreVamvt2HOpuhQK4nPpdfbh8rt4cMk9ZMSmzeFop0etVLEqbTlHuk7QYG+mOKlw6hdNg9vv4fsnf4LNY+cbG/4PCZq5D8KOdp/CG/SxJWtDVALOC7UNhwKTJYmxnLU5aB5yT6skxUwq3wPYPT66XV6K4/VXVP5iKvoYJRk6NW3DbvxBmRjFxUudHcNunqnrBCQydCrOWh2ctTpY1T/A5pT4GbVGWmEMBWCV/ecuCsCcPic/PfMEDt8wD5juJigZAQvX55SwPHk1Zls9R7tOcrqvindbP0RCoizZxNbsjSxNWXJV90VdlrKERE0Cx7pPclfRLWhjItNyKtpEACYIwqReb3wHu2eAWwtuYHvOdTQPttI82EbzYCstg21juwhXGZezOXP9HI92+tanl3Ok6wTHe05NGoC1DLaRpE0MeyZLlmWerXmJzuFQftm7rR/wp8V3RGTMMxUIBtjffhilpGRzVvR/Vm0OD2qFRJpOTXG8ni6nh2aHi5IwdiV29g9ztsFCUVY8uWnT28xRO1r9fhbKQxQYdHS7vHQ63eTFfVzqweL28mRtJ76gzANFGSxLiqN2wMn7nVZO9wxwumeAkgQ9OzOTyTfocPkDWD0+LB4fNo8Pi9uH1eMjKMuUJMRSlhRHmk6NKakYtUJFZf857l78CQD8QT+/PPs0Pc5ers/bxtbsTfyyph0JWByvRyEpKE0uoTS5BJffTa2tgey4jKuydtZ4lAolW7I2hGr79VREfWk9UkQAJgjChJoGWtjffoh0vZGbCnahUsSwLLWUZamlQCjI6HX10z3cQ2lyybwtOTGZ4qRCEjUJnOqt5N7iO1Fd0rNy0DvES7V/4GTvGRI1CXx19Rcx6qd+4/qw/SAne89QmJCP3TPIRx1HuDFvx5wu8bzbuo8eZy+bM9dFfYeqyx+gz+2l0KBDIUksTtCzv9tG/YAzrADs1Y+akIFbN+WHdT2L20v9oJO6AScNg6GZN1MEq99PpMCg40jvAE1DrrEAbMjn59e1nQz7A9yRb2R5cihoNyXGUpKgx6KAV6o7qB1wUjvgRKtU4J5gJ6UENDvc7OmwkKpVsTQxjsKkNdRYjtA93Eu63sizNS9Ta29glXEZdxXdiicQpNXhIkuvIVZ18cyWLkbLSuPSqH5P5sLmrPW82fweBzqOsCVr41Xxt0gEYIIgjCsQDPBszcvIyHzSdM+4eV2SJJGuN5KuN87BCCNDISlYk76Sva37OWepGdt+L8syh7tO8Er9H3H6XaTpUul19fPjiv/hq+VfmHT2oN7exO/r/4hBHcdjyz7Fuf4anjW/zJ6WD7i35M6wxlXVX83L9a9zd9EnWBGBN8xORzdvNr1LgtowNnMSTe0jOwNzR5bZ8uO0qBQSdYNTJ+K3dA9xoqaXRZkGVi1OHfcYTyBI3YCT+sFh6gddWD0ft6hJ0sRwXUoiKdrIl5+41IWJ+NszwR0I8GRtJ1aPj11ZyWxMu7iYqSRJlKYaSF0i0TzkYl+XFavHR36clmSNKvSPVjX2tS8oU2Mf5rzNQd2gk33dNmA5hthCnm/oJCB30uVMI9lwH/ZgCt+taMITCCIDxbMQgM4XCZp4VqYupaLvLE2DLRQmFMz1kKYkAjBBEMb1Xus+Ooe7uS5rfcRzo+ab9enl7G3dz/GeClalLafX2cdzNb+n1t6ARqnm3pI72Za9ifda9/Faw1v86NT/8LXyL45bwmHAM8ivqp4B4LGlnyJRk8CGzDW83fI+H3Ue5cb8HVNW3nd4h3mm+kWGfA5+WfU0j5Y9wNr0VTO+v0AwwNPVzxOQAzy45E/Rq6L/xtw27AEgNy4UgKkUChYZdNQOOBn0+omfpKL9qwcaAbh7W+G4MxmyLPPz6raxshYapYKyxFgWJ+gpjtfPSuA1Kl4dQ4pGRYsjlN/2TF0XXU4P643xXJ81eYmPAoOOAsPk+W0qBZSnxlOeGo83EKR+0MkZi50zVjc9npHvbUwskhQq+xGvjkGnVGBQxbDOuLA6PGzN3kRF31n2tx8RAZggCFenXmcfbza/R7zawF1F0Z8tmWvZcZlkxWZQ1V/NG417eLf1Q3xBP8tTS7m/5O6xliw35e8kKMu83vj2yEzYFy+qlxQIBvhV1TMMeoe4Z/FtY4FrjCKG3QW7eLYmNAt2X8ldk47npbo/MORzsDFzLWf6qnjy3HN4Az42T9KCZjJ7Wj6kdaiDDRlrxpaPo619ZAfkaAAGoXyk2gEn9YNOylPHX4pt6BjgTIOFktxElhaMH8D0ur30uLzkx2m5JTeV7Fgtyjlcciow6DjZP8ivzB20DbtZmhTLHflpEV8GUysVlCXFUZYUR9fJP9I02I9GqeCrqz9LjmF+N1OfDSVJRaTrjVT0nuFPi28f26U9X4k6YIIgXESWZZ4zv4I/6OfekjvRq8LrIXc1kySJdRmr8csB3mx+D22MlseWfYovLP/0Zf3wdhfs4rZFN2Fx2/jxqf/B5raPPfdKwxs0DDRTnraCnblbL3rdxoy1pGiTOdhx9KLXXOps/3mO91SQb8jlQdM9fHn159GrdPy25kU+bDs47XvrcHTxVvN7JKjjZ20TgCzLtA67SVTHYFB9/Dl/dElssnpgr4zOfm1dNGEAM9piaL0xgbw43ZwGX/Bxn8W2YTcFBh33FWagiPKYrstah0bp5XPL7hXB1whJktiSvRG/HOBw1/G5Hs6URAAmCMJFjnafpNZWz7KU0nnRD262bMhYS1ZsBtdlreebG/6G8rQVEwYAtyy6gVsLbqDfbeVHFf+D3TPAiZ7TfND2ERn6NB5acu9lr1UqlOwuuB6/HGBPywfjntfpc/Fcze9RSko+VXovSoWSPEMOX139ReLVBl6se409zeO/djyBYICnz48uPd4za8G0zePH6Q+M5X+NStOqiVcpqR8cvy1RTYuN8802li5KxpQ3cb2wavswErOzyzEchYZQX8gMnZqHF2eiUkT/rXVD5hr+Y+u3WZJcHPVrXU02ZqxBpVDxUefRCYvVzqY6W8OEz4kATBCEMUNeB7+v+yNqpZr7TXddFTuJuaUDQQAAIABJREFUIiVBY+AfNvxV2DlSty66kd35u+h3WfjhqZ/z2+oX0So1PL78EbQxmnFfsyGjnFRtMoc6j407C/ZK/RsMeAfZXbCLrLiPZzWy4jL4WvkXSdIk8lrjW7ze8PZFFc0nsqflA9ocnWzMWDtrS48ArSP1vy5cfoTQDMXiBD3D/gDdTs9Fz8myzO/HZr8mzjl0+Py0OdzkxWnHKuzPtUSNij9bmscXSnPRzeKYol3H7WqkV+lZk76Sfpdlyp6Z0XbOUsOPKv5nwufFT08QhDEv173OsN/JHYW7r5pecHNFkiRuK7yZm/J30u+y4A36eLj0vkkL0SoVSnYvugG/HODtlvcveq6yu5pDXcfIjsvkpvydl702TW/ka+VfIlWXwtst7/Ny/euTfsIPLT3uJVGTwD3Ft8/8RmegzTGSgD9OodHikcbQl+6GrGqyUt8+wKrFqRRmTVyqo3bAiQyUzpPZr1FZeg2aKBZ9FcK3baQO2Edz3B/yYOexSZ8XSfiCIAChdkPHeyrIM+SwPWfzXA/nqiBJEncU7iZJk4hKETNWwmIy69P/f/beOzyO68zTfatzQkYj59QgQIA5ihSpSCoHKwfashzGY1sO45m9e+fujnfu3LV3ZpzHGstBo2DJyjlQVKAoMSfknDMa6Ax07q66f4CERBGRBEmTqPd5+ABEn6o6p0Odr7/w+1aws/tDDgwe4dqcK0jSJxCIBHns2DMoBAUPlN6JappWTkn6BH648lv8uvoP7O7by9HhakoTi1mSWEJpYvGkxtiFCj2epN8bQCFAhvF0T2Bh7MRc2tw+tqRPJNlLksQrn3xW+TgTTa5xAErjz62OmczFS25sNhnGNBocLQQigQuijD8WGqfO1kimKX3aMbIBJiMjQ1iM8HzrqygEBfeV3iGHNuaBIAhcnjV35W1JErgyYysvdLzMa627uL3gVt4f2smo1861uVeQE5s14/Fx2li+v+KbvNHxLvX2Zo5YqyabiWcY01iSWEIgGqRvfJAN6WsoTyo9q/XNl4goMugLkq7XTpkLZVKryDBoJ2UbNEoFB+uH6RkeY+2SlBlV7yPihPZXklaNWaeedpyMzDJzOe92f0ijo5WVKZXn/fpHho8jSiIb0qevXJYNMBkZGT7s3cOo387WrMvIjsm40NO5ZJAkidf3dvFp7RCBUJRQOEpUlAARbaWBY6PHOXwkgqqghoyYVK7Pu3pO543RmLh/yZ1IksSgd5gmRyvNjjbaXZ0M9k20PpoIPd54Dlc3NUO+EFFJOi3/6/MUxxoY9AXpGvNTHGfgmZ1NCALcsil/xnN3jvkJiRKl8cZFlZ8oM38qTxhgNaP1590AkySJ/UNHUApK1qSumHacbIDJyCxy7H4nO7s/IkZj4ob8ay/0dC4pPjzWzxv7ujHqVCTF6tBqFGjVSrRqJV5W0qfYi6qgBoBvrX0QtTQ/r44gCGSa0sk0pXN1zhZC0TAd7i46XF1UJpejV51/CZG+LyjgA0SiIkqFMGk0FcUZ2DPspM3jwzk4Rs/wGJctTSM9aea8rpPyE6V/ZflfMn99ZJsySdQl0GBvJiJGpg3rnwt6x/oZ8lpZbq6YUYtMNsBkZBY5r7S/SVgMc2/h7YtC8+t8Uddp5y8fthFr1PA/dqwmKe5Uj1BULOefDzZjC9gwjhVjSS5kdHTsrK6pUaonmy5fKHrHT62ArG638R8v1yEIYNSpMOrVmAxqhKIYjg448VaNolQI3DyL90uSJJpcXnRKxWT7HxmZ6RAEgWXJ5ezu30urs4OyJMt5u/aBoaMAbEhfPeM4OdFDRmYR02RvpXq0noK4PNamrbzQ07lkGLR5+d3r9SgVCr57e8VpxhdMVEQ+WHYnJl8RtpZcHJ7ABZjpqbS6vRwddc9J4mI6+r1B9EoFSVo13kCYJ99tRqGA/PRYDDo1Y74w7X1u/I4AIZWAMxhh+4Y8zPEzG1XD/hDuUISSOANKhRx+lJmdk03Ha0brz9s1Q9EwR61VxGliZ/0iJHvAZGQWKWExwgttryEgcHfJ4tL8OpeM+UL86qUa/MEo37ipjMLM6fvxFcXnc3Xadfylvo1D9UOsLp668fT5QJQkXuy04o1EGfGHuC47ed7vifFwBEcwTEmcAUEQeP7DdtzeEF/aUsANG/I+u5Yo8fGAgw+GHdxxUyn3rCnA5fTOeO6mE+HHJXL1o8wcKYzPx6Q2Umtr5G7ptvNSXFQzWo8/EmBz7gaUipk14WQPmIzMJcZr7e/wbPPL+ML+Gcft7v2UEZ+Ny7M2kCUn3i8IkajIb1+tZ9QV4KaNeawvn71FzIoTRtfB+uFzPb0Z6fcG8EaiAOy1uni9Z3RKtfrZzgET+V/1nXb21g2Rk2pi29qcU8YpFAJLk2MAcAoiatXsW1GzaxwFUBJ37huJy1waKAQFFclleEJjdHv6zss1T7ZAWj9L+BFkA0xG5pKiw9XN+70fs2/wEP/78C9od3VNOc4ZcPFu9weY1EZuzN92nmd5aSJJEk+910Jrn4vVFjO3bJ45p+kkyXF6clJN1LaP4gtEzvEsp+ekh+m2vBTS9RoOj7p5uctKdB5G2EkB1hStmid3NqNUCHz1+iWophAoNevUxKlVtLunbkv0eTyhCP3eIHkx+vOqNC9z8XM+w5B2v4NWZweFcXmkGsyzjpcNMBmZS4i3u3YBE42fXUE3vzz+O97u3EVUjJ4y7uX2twiJYW4tvF5OvF8g3jvcx97aIXLTYnj4xrJ5NWNeWWImEpWo7bSdwxnOTLPLi0oQWJYYw9dKs8gyaqmyj/F8xzARcW5G2MkKyONVQ9g9Qa5bn0NOasyUY0+2JfJHRXpnaM4N0OKWqx9lzozShGI0Sg01o/Vnlds4Fw4OH0NCmlH76/PIBpiMzCVCm7ODFmc7SxJLeLDsLr6/8m+I18bxTvcH/LLqMex+JwDNjjaqRmrJj81hXfqqCzzrS4PqNhsv7m4n3qThkS9VolXPz0uzsnji23JV64UxwBzBMFZ/iMJYPRqlAr1KyVctmeTF6Kl3jvNs+xBhcebGxqIk0ecNEKtUsufYAOlJBm7aOLMXsDh2Ipy4f8Ax47jmyfwv2QCTmR9qpZryRAujfjtDXus5u44oiRwcOopGqWHFHHXHZANMRuYSQJIk3jrh/boh/xpgIsH7/177fVakVNLp7uYnR37BkeEqXmh9HQGBuyy3yor3C0B7v5vfvVGPWqXgkTsqSYiZuhH3TGSajaQnGanttBOOzGzonAuap0hw1ymVfKU4g+JYA81uL0+3DRKKTj83WyBMMCriHvEiAA9dv2TW3C5LvJFErZrdPaN8MjS1ERYWRdo9Psw6NUk6zfwXJ7PoWWZeCkDNaMOsY9/o2Mn/3P8TPh04eFrkYDr8ET+vtr+NI+BkZUolOtXc7gHn7O5rsVjWWSyWj0/8vtJisQxYLJaPT/y7+8Tf/8lisRy2WCz7LRbL2nM1FxmZS51WZwftri7Kk0rJj8ud/LtBbeDh8vu5v/ROomKUJxr/gtU3wqbM9eTEzNzyRmZ2eq1j/PLFGiIRib+5ZSl5adM3kZ4JQRBYtzSNYChKU49zgWc5O82T/RVP9TBplAoeLE5nSbyRdo+fx1sGcAbDU57jZPhxzObnmjXZFM1Q/XkSrVLBw5ZMEnRqdvbbOTjiOm1Mh8dHWJTk6keZM2ZpcilKQUmNbeY8sBZHO+/1fIQ94OS5llf4yZFf0mBvnjZ0GRWj7Onfz48P/Csf9X1KvDaOa3O2znle50SGwmKx/APwIHCyrngl8POWlpaffW7MSmALsA7IBl4G5hY4lZGRmWQq79fnEQSBjRlrKIzL5cnG5xkLj3NTweJNvBclaV75WdNhdfj4+fPV+IMRvn5TGcvPUkJi/dJ0XtvTwfHWUSoLk856fnMlEInSOeYn06AlVnP6lqBSKLivMJ2XuqzUOMb4VX0P27KSWZcSd8rz2DDiAcAozt5Q+/MkaNX8cG0xP93fwhs9o2gUClYmf2bINsnq9zJniV6lpyShkCZHK3a/kyR9wmljApEAzzS/iEJQ8I2KHdSONnJg6AiP1jxOaUIxtxffONlYW5Ik6myNvNbxDlbfKDqllpsLtnNF9mY0yrl3szhXOmAdwO3A0yf+vwqwWCyWW4A24PvAJmBXS0uLBPRaLBaVxWIxt7S0jJ6jOcnIXJI0O9rodHdTmVxObmz2tONSjSn8w5rvEhWjs+rTXIrYAyHeH7BT5xgn3aBlaYKJpYkmks8grOXwBPj356rw+MI8eG3JnOQmZqM0L5FYg5rqtlHEbRYU50lstNXjQ5RmNnCUCoG7ClIpjjPwdu8ob/aOUucY4/b8VJJ1GiJRkWbbGJJGwY7Li+adA5dm0vFVSyZ/bO7n5S4rGoXA0sQYJEmixeXFoFKQM0NvSRmZ2VhmXkqTo5VaWwNXZG867fFXO97BHnCyLfdKKpLLqEguY2v2Zbza/jZNjlZ+cviXbEhfzcqUZbzX8xFtrk4UgoLNmRu4If8aYjTz99CeEwOspaXlZYvFkve5Px0G/tjS0nLMYrH8I/BPgAuwf27MGBAHzGqAmc1TV9VcyizGNcPiXTfMbe2SJPFe9QcAPLDyFswJl8bztZCvuzsY5q22IT7tsxGVIFmvweoPMeizs2vATlaMnlVp8axKjyd9Di1u3ONBfvGnw9g9QXZcv4Q7r1q4tj/rKzLYdagHhy/CkvzEBTvvTHQPTNyGN+anYJ5FY2tbSizrC1J4pr6XKqub3zT0cktJBs4uN5JOiVEU2Lomd8ZzTEdlbjI/iNPzs0NtPN9pJTnBSKxWjSccZX1mIqkpZxbe/Wtlsd7bLtS6rzCt5fmWV2lyN3PXyutOeax2uIm9AwfJjstgx5pbUZ/wYpnNMSzPL6F6qIGnq19m/9AR9p/Q+VqVUcH9y24jKzb9jOd0vpTwX21paTkZ3H8V+A3wOvD5VyKGCaNsVs62X9rFhtkcs+jWDIt33TD3tdfbmmhzdLPcXIExEn9JPF8L9boHIlE+GXayz+oiLEokadVcm5VEeYKJYFSkyeWl3jFOm8fH621DvN42RIpOw/U5yZTETe0N8gUi/OtfjjMwOs72dTlsqUhbsOfcbI5hSXYcuw7BR4d7SDbNrzH3mRCVJGqsLuLUKnTByJzXcke2mVKTnjd6RnmpeQAxEEGhU1GRGntGz8fJ19wEPFiUzhOtgzx6rJPC2AmDOF+nuSTe2ydZrPe2C7tuBXmxOTSOtNE1MDzZJNsfCfDbQ0+hEBTcV3wHLkcAOLUtWKYqh79f+QgHho7Q6GhlS+ZGLIlFEJybPTKd0Xm+SqDe+1yS/VXAMWAfsM1isSgsFksOoGhpablwIjgyMhcZkiTxdtcuBIQpc78WKxFR4tNhJ/9W283HQ050SgW35qbw/aW5VCTGoBAE9ColK5Nj2VGSwT8uz+euglTK4o3Yg2GebhuaTEr/PMFwlF+/VEOvdZzLl2Vw59bCBW/fVJaXgFaj5Hjr6FlpFs312N7xAP6oSGm8cV5rEQSBisQYvr80l6SogEI38V0+fwFU6gtiDTxQnI6ERIvbh1KAYln9XmYBWGYuR2Iif+skr7a/jTPo4trcK8iJnb4wSalQsilzPd+o2DFhfC0A58sA+xbwyxNVkZcB/9LS0nIM+BQ4wEQC/rfP01xkZC4Jam2N9I4NsDKlkgzT2ecgXSq812/j3T4bErAtK4m/q8hjbUrctA2cdSoly5NieaA4g6+UZKAQ4Jn2U40wUZL4z9fqae13s3ZJCju2Wc5J70y1SklFQRIjLj+Dtpl7I06HPxLlX2u7ea9/9u+zTc6JNS5JOLMEdyki0nlggECTk3XJsQum01USZ+TugnQUQFGsAZ1y8eUsyiw8k3IUJ6ohm+yt7Bs8RKYpnevyrjrv8zlnIciWlpZuYP2J348DG6cY82Pgx+dqDjIyF5qoGKV3rJ/c2OwF1dwSJXHS+3V9/tULdt6LHUcgzMERF4laNd8uy55325rCWAM7ijN4qm2QZ9qHuL8ondJ4E3uqB6ntsFOen8jXbiw7pwnyK4uTOdo8wvHWUTLN80/sbXJ5cYcifDLkpDTOSG7M9HltzW4vGoVA/gxjZmLnoV78wSi3lKZxbX7qGZ1jOpYmmnhEn4tpngn9MjLTkWJIJsOYRpOjDVfQzTPNL6EQFDy45C5UivOVkfUZsgqjjMw55M3O9/j3Y7/l/zv0c45ZqxGlhRHZrBltYGB8iNWpy0kzLuzGdzGza2Ai0f6azKQz7hlYGGvgy8UZKASBZ9qHODrk4qWPO9BrlTx8w9R9DReSysJklAqB421nlpHRcMKrJQGvdI8QmUbBftQfwhYIUxRrQK2Y/5o83hAfHOsj3qRh64rMM5rrbKToNRjk3o8yC8gyczkRMcKvq/6AM+hie+6VZMecm/fvbMgGmIzMOSIcDbN/8DBqhZoRv43HG57lJ4d/yfGR2rMyxMJiZNL7dZ3s/ZpkwBug1jFOpkFLReLZiXYWfM4Ie6VvBDFGxR1bCok3zV/lfr4YdCpKcxPoGR7D4QnMfsDnCEVF2tw+zDoN61PiGA2E2D00tbDrpPp9wpk9V+8c7CEUFrlhQx4a2Uslc5FQeaI5t9U3QqYpnW15V16wucgGmIzMOaJqtA5vxMeWrI38z3V/z7q0VQx5rfyp/s/89MivqD6D5rCiJPLnphcY8lrZmLGGVIP5HM3+4uO9/gk5hW3ZyQsitFoQa2CT0YgoSiRUJpOaH3/W55wrK0+Iuh5vnZ8sYpvHR0SSKE8wsi0rmTiNij1DDoZ9wdPGNrknWgZZziDB3TkWZHfVAEmxWi5fljHv42VkLhTZpkySdIknQo93X5DQ40lkA0xG5hyxd+AQAJdlrMNsSGJH2d38j/U/Yk3qSgbHh/lD3VP8nyO/on9scM7nfKtzF0et1RTE5XJn8S3nauoXHW1uL+0eH8WxBopiF6ZiLhiKsuujLjy1NlQKBX/pGKLFdWaJ8fNl+cnm3PMMQzaeCD+WJZjQnqj+FCV4pduK+Dlj3xeJ0jPmJ9ukw6Se/wb01oFuwhGRmy7Ln7Xfo4zMXxOCIPDNyi/zvRXfJDvmwn55kD85MjLngCGvlQ53F6UJxaQYPmtRk2ow85Xye/h/1v0dq1OX0zc+yM+PP0qDvXnWc+4bPMR7PR9h1ifxzYqvTIoFLnZESfrM+5W1cC18Xt/Xhd0T4MqSNL5SkgEIvNt3fpRyEmK0FGTE0tLrYtw/de/FLxIVJZpcXuLUKjINE6FSS7yR5Ykx9HuD7Ld+JrPY4vIiwRlVLdrcfj6pHiQlXs/GpXL1rczFR6YpnaL4/As9DdkAk5E5F+w76f3KXDfl42nGFB4qv4+Hlz6AKIn8rvYJPh04OO35muytPNfyKka1gb9d9tVJEUEZqHOMM+gLsjwxhgzjwrSr6bWOsetwH8lxOm66LI+CWAOWOAMjgdCU4bxzwSqLGVGS+Nlz1VgdvlnHd435CURFliScqul1Q44Zg0rJ+wN2HCcaaZ9Nf8U393UTFSVu3pR3zgsSZGQuZeRPj4zMAhOKhjk4fIwYjQlTOIvH3mjAH4xMOXZlSiWPrPgmBpWe51pe4bX2d05L0O8fG+SP9U+jEBT8TeVXSJHzviaJiCK7BmwoBbh6gbxfoijx5M4WRElix3bLZF/DyqQJNes6x+kireeCq1dlsakynR7rGD9+4ggHGoZnHN9wQres/AtJ9Ua1khtzkgmLEq91W4mIE4n6iVo1KfPsg2l1+thXN0x6koH1ZbL3S0bmbJANMBmZBaZqpBZ/xM/a1NX88Y1mDjVaOdoyMu34grhcfrTqO6QYknm/92Meb3iWUCQEgCvo5j9r/4tANMiXy+6hIC7vPK3i4uDwqAdnMMK6lHgStQsTkt1dNUDXkIf1Zakszf/MqCuNM6JRCNQ6xs5KpX6uqFVKvnr9Er5xUxkC8Ic3G/nT240EQqcb86Ik0eT0olcqyJtC02tZYgyWOAPtHj+vdo8QFEWWzFP9HuCNvV2IksQtm/LPW7NwGZlLFdkAk5FZYPYOHkRAYLw/DZt7QkagsXtqKYCTmA1J/GjVdyiMy6dqpJZ//vhX2Px2Hq15HFfQza2F17MypfJ8TP+iIRCN8tGgA61CwRXpC9O42jkW5OU9HRi0Ku6+qviUxzRKBaUn2hUNnqcwJMD68jT+6aE15KbFsK9umH9+4ii91lP7zw14g3jCEUrjjSinMKoEQeCW3BQ0CoEq+8Sx8w0/Dti8HGywkmU2sbo05cwXJCMjA8gGmIzMgjI4Pkynu4c8UwGfHHaTHKcjzqihsdtxShXaVBjVBr674uusTl1Oq72T/3Xw3xgYH2JT5nquztlynlZw8fDpkAtfJMrl6QkYF0iH6tn3WwmEotx1ZRFxxtPDc5WJE2HIWsf5bSicmmDgHx9cxbVrshl2+PiXp47x4bH+SU/cyerHL4YfP0+8Vs22rImCEJ1SQZ5pdvX7YCjK0eYRfvd6Pf/y1FEk4LbN+Qsi8yEjs9i5cAIYMjKXIHsHJxLpXd2piJLEg9ssHGq0sr9+mP6RcXJSY2Y8Xq1Q8ZWye8lNyuDlxncoTyrlruJbzknfwYsZTyjCXquTGLWSy1IXRp+rY8DNsdZRirPi2FSZPuWYkjgDOqWCWsc427IWRm9srqiUCu65qpgluQn86e0mnnm/lYYuBw9dX0qDaxy1QphVgmNdShzD/iApOs20vTH9wQg1HTaONY9S12knFJnISTTH67h8Qy7Li5OnPE5GRmZ+yAaYjMwCEYqGODx8HJ1gZLDLxNolKVQUJDHuC7O/fpiGbsesBhhMhIvurriJitgKEnXxKBWLV2U8Kkm4gmFGAyFG/Sd+BkJY/SHCosT12UloFqgSb1/9RJL7TZflTWtYqRQKyhKMHLeN0TcemLHP4rliWVEy/+ura/nDmw1Ut9v4p2ePoVuWTFm8cdbnQiEI3JZ3eusqUZJo7HKwp2aQmnY7keiE0ZWWaGB1qZnVlhSyU0zyFwEZmQVENsBkZBaIY9Ya/JEA0nARBo2Ge68uAaAsLwGAxi4H163LnfP5zIaF07S6mBAliUbnOPutLnrGA0S/ELpVAIk6NcuTYlhtjl2Qa4YjIocbrcSZNJTlzpxPVpkYw3HbGLWOsQtigMGETtiP7lnBzsO97OyeUMsfH/YSKRDnJQ3hHAuyt3aQT2qGsJ9oe5SRbGRNaQqrLWYykuefqC8jIzM3ZANMRmaB2Dd4CCQIDmey48rCyRyiOJOWLLOR1n434UgUtdxceEr8kShHbR4O1/dg909UgWYYtKTqNZh1GswnfiZq1agWuAKvpt2GLxhh+7KcWav7CmMMGFQK6hzj3JBjvmD5UAqFwPXrc2nRiYyEwhw5NIi1w8U3by4nLXH6UKQoStR12tlTPUhthx1RktCqlVy+LJ3Ll2WSnx4jG10yMucB2QCTWVS09rlITzIQY5if/tFsDIwP0eXpJeo2U5SSxuYv9Mcry0ukf7SP1n435XkLU7F3qTDqD7F/xEWVzUNIlNAoBNaYY9mYGk+q/tw3vwYmNbbmouyuVAgsTTBxeNRD15ifwgVqfXQmuENhRsMRCmL0FJelsrd2iB//12Huu7qEpfmJWJ1+Rl1+Rpx+Rpw+Rk78HghFAchNi2HL8gzWLUlFr5W3AxmZ84n8iZOZE/2j46Qm6M+L90aUJD6pGWTQ7ue2TXkLtjG09rn46TPHKcyM5b8/sGpBPRcf9+4HQBzN5stfKj3t3OX5iew60kdjl0M2wE4gSRIvd1s5bpuoKIzTqLgiJY7tpZn43f7zNo8xX4jaDjvZKSayUqavIvw8lYkxHB71UOsYu6AGWKNzQtF+aWIMG5ZkszQ/kSd3tvDEu1O3ttKoFJgT9BRnxbNlWQa5abPnJMrIyJwbZANMZlaqWkf5zSt1XLsmm3u+oI200AzavDy5s5m2fjcAkXCEHdtLz/q8kiTx8p4OADoGPHxaM8iW5ZlnfV6AYDTEoaHjSGEt20pXk5F8ur5SSXY8KqVAQ7eDOxfkqhc/7R4fx21jpOg1XJWRSFmCCaUgYNKoOH/mFxxuGiEqSvPqa5gXoydGraTeMc7NOSnTVhTOBUmSCERF+j0+ul1e3KEI7nAEdyhMOCqxMTV+2lyzhsnm2xPvubVLUinIiOXVT7qIiiIpCXrM8XpS4vWkJBiIN2nk8KKMzF8JsgEmMyO+QJindrUAsL9+mDu2Fp6T/m/hiMg7B3t4+0A3kajEaosZmyfIx9WDrLSYT1EkPxPqOh209bspyY6n1zrGSx93sKLYTOwUWk/zZWfLAaJCGO14KTdfPXWDV61aSVFmHM29Ljy+ELELHAK9GNkzNCFOe2d+KpkL1MPxTNhfP4wgwLqy06sDp0MhCFQkxrDf6qLd48NyBj0VAapsHt7oGSUoitOOqXOOsyo5lm1ZSZjUn92yfZEo3WN+soxa4jSfdQFIjtPz9ZvKzmg+MjIy5w9ZiFVmRl7Y3Y57PERCjJZxf5i6DvuCX6O9382P/+swr+/tIsag4bu3V/C3t1Xw/XtWoFQIPPFuM77A1L0U54IoSbyypwMBuP+aEm67vABvIMKLu9vPeu42v4MPBj9AEgXuXXHVjCHa8vyJ0GPTLKr4i4HecT+dY36KYw0X1PgasnvpGvJQnp9IvGl++WaViRPhyjMVZfVForzZO4qERGm8ka05yVybmcSd+ak8bMnkhxW5fL00i3S9hmM2D7+o6+HwiHtS0LfZ5UUEyuLnFjaVkZH560I2wBYRngP7GPj1L4h4PHMa39jt4JOaIbLMJr5zewUw4S1YKPzBCE/vauEnfz7GsN3HFSsz+ZevrWNFyUSz6cKseG7YkIvDE+T5j9rO+DpHm0foHRlnXVkq2SkmrlyZSW5qDPvqh2npPXNjKBAJ8mj1fyEqgsS5V7K2cGbTgYJyAAAgAElEQVSJiZMGWEO344yvealw0vu1JT3hgs5jPsn3XyTbqCNeo6LR6SU8gwdrOj4edBCIilydmcSO4gzuX5rD1oxEViTHUhhrIFmnIT9Gz9+W53BDdjKiBK/1jPBYUz+D3sCk+n3ZDOr3MjIyf73IBtgljChKODwBWvuc1Pz+SYb/9Ae8tTXYPvxw1mODoShP7mxGEOCrN5SSlxZDltlIdbuNcX/4rOfmC0T46TPH2X18gLQkA//9gVU8eK3ltIT7GzfmkZNi4tPaIWrPwPsWFUVe/bQLpULg1s0T4UGlQsGO7RYE4Kn3WiZFJ+eDKIk81fQ8Vr+ViDWHq/Mum/WYnNQYTHo1DV2O89LM+a+VYV+QJpeXbKOO/AukowUTntED9cPoNEpWFJvnfbwgCFQmxhAURVrdvnkd6wiGOTDiJkGjYn1K3IxjlYLAZWkJ/KAil8pEE33eAL9t7KPZ7cWsU5Oil8PZMjIXI7IBdokgihJt/S5e3tPBvz57nP/2u/18898/5r/9x6c0/OxX6A/vxqmOISSoGPjgI4Zt4zOe79VPOxl1Bdi+Noe8tFgEQWDj0nSiosSRJutZzTUSFfntq3X0jYyzuTKdHz+0lqKsqTchlVLBV29YciIU2YQ3MD/jb1/dMFaHj83LMkhJ+KxaLT89lq0rMxmy+3jvcO+81/BO1wfUjNaj9psR+5ewdsnszYkVgsCS3AScY0GGHfPbsC8lPhme8H5tTU+4oAnhbX0u7J4gqy0paM+wl+RkGNI+vzDk+/12opLENVlJqBRzuw3HalTcU5jOV0sySdKpESVYmiBXMcrIXKzIBthFjDcQ5mDjML9/s4Hv/fpTfvLn47x9oIfmXhehsEhxkoqvuz6mfLybYFoO2m/9CE9eOTHBMZ763Zs0ThMK6xh08/7RPlIS9Nyy6bOk8nVlqQgC7G848zCkKEk8/k4TTT1Olhcl8+XtpahVM78Nc1JjuPmyPFzjIZ77YO6hyHAkyhv7ulCrFNy0Me+0x790eQGxRg1v7utm1DX3urvjI7W82/0Bcep4PE0VVBaY56wrNhmG7FqcYUhHMEytfYxUveaME9cXipOthzacQfjxJOkGLck6Nc1uL6E5elIHvAFqHGNkGLSTzb3nQ1GcgUfKc/hycQZXZFzYEK6MjMyZI1dBXoQcaxnh/aP9tPd/lpCbEKNldWkKywqTKc2NR+G0MfCrXxB2WIlZs5air34NhVqD33AjfT+twWJv4efPp3HfNcVcuTJr8tyRqMgT7zQjSfDQdaVoTngGRFEiIUZLWV4iDV0OrA4fqTOobU/Hy3s6ONhgpTAjlm/eUj6r6vhJrlufy/E2G/vqh1llSZlTQ+DdVYM4PEG2r8shIeb0BGuDTs09Vxbx+zcbeeb9Vr53R+WsHpm+sQGeanwerVJDcfhqhiPjbCif+wY+2Zao28nVq7PnfNylwqdDTkQmcr/OVIdNlCT21g7ROehhRXEySwsSUc7Ri3SSUDjK0eYREmO1WHLOvJn3yTDkR4MOmlxeliXNbFBJksS7fTYArss+82beKoXighuwMjIyZ4dsgF1kHGsZ4dFX6wEoyIylsjCZZYVJpzTK9bW20P/bXyN6vSRefyNJt96OcGKD0hUWoUnPYMlIH/vUEf68q5WBUS/3Xl2MSqng7QM9DNi8bF2RSXaKiX11QxxpHqGhy8HlyzPYUJ5KQ5eD/fXD3HZ5wbzm/uGxft492Etqgp5H7qikpddJj3WcG9bnzmqIqZQKHr5hCf/8xBGe3NlMUdY6THr1tOP9wQhvH+hGr1Vy/frpk+PXlaVO5pcdb7WxyjJ9LpAnNMZjtU8SFsN8fekOnnzBhUGrYlnR7MbgSZLj9KQm6GnudRKJzq9v38XOWDjCMZuHBK2KijPw/ADYXH4ef6eJ5l4XAJ/UDBJr1LChPJXLlqbPWUi1qs1GIBTlqlVZZy3IW5Fo4qNBB0dtbpYmTmiZTUebx0fnmJ+SOMMFFXCVkZG58MgG2EVEa5+Lx95oRKNR8g/3riA//dRGxNHxcdyffIz9jdeQJInULz9E3OYtp4wRBIHYTZuxvfg8j5SE+L3VzO6qAYbsXm7dnM+b+7ow6FTYXH6+9+u9RMUJD5teq2T38QECwSgatYIDDcPcsjl/zpvXsZZRnn2/lViDmh/cvRxRgv98vYFgKIrHG+K+q4tn9T5lmU3csimfl/d08uwHrXzjpvJpx75/tI8xX5hbN+fPaKgJgsAD15bwT48f5tkPWinPT0CnOf1jEREj/KHuaZxBFzcVbEPlTcc9PsLW5RmzhlC/SFl+IruPD9A56KEk+8y9Lxcb+4ZdRCSJzWkJMxopUyFKEnuqBnhhdwfBcJTlRclcvTqLqlYbBxuHee9wH+8d7iM3NYaNFWmsL0udMSx8spr3TKofv0iqXkueSUeHx89TrYPcU5iGfgo5ElGS2NlnQwC2Zc3daJeRkbk0Uf74xz++0HOYLz/2+UIXeg7nFaNRS2uPg589V00kKvLIlypP2bgDXZ3YXn0J63/9CV9DPQqtlozvfI+Y1WumPJ86JRXnB7sQxtxs//Y9DNl91Hc52N9gRZQmRFFHXH6yzSauWpXFjm0Wrt+QR1OPk/ouB4mxWmzuAEtyE0iOm72Kra3fxW9eqUOlVPCje5eTmWzi+Y/a6BjwoNcqae1zY9CqKMw8NRHfaNTyxde6MDOW+k4H9Z0OqttteP1h4oyaU4yscX+Y371ej16r4ps3l89qIMUYNESiEjUddsIRkaUFp4u+PtfyKrW2BlalLOOO4pt5fW8X/aNe7ru6hMTY+elYRaMSh5smwl+luVPn8Ey19osZfyTKC51W9EoFdxSkzmiAfXHtNpefR1+r58PjA2jVSr58nYUvbSkkJcFAZWES16zOJjfVRDgi0j7gprbDzvtH+rC5A6Qlnt730z0e5M+7WslLj+GGDXkLsr7yRBNWX4hWj49G1zhFsQaMX0jsP24f48ioh5XJMaxLOd3wvtRe8/mw2Na+2NZ7kkW87v811d9lD9hFwIjTxy9eqMEXjPD1m8rw9rv5sHaA1ckuXLs/ItjdBUwYVvFbryT2sk0ojdPnh6hiYzEtW8748WMIQ/18+/YK/vfTx+gc9GDQqti2Loc1pSmkfSHH60f3rOAXL1TTMTihI7a3bghLzsxJwEN2L79+qZZoVOLbd1SQlxZL/8g4n9QMkp5k4Ht3LuMnfz7G8x+1kxirY3XpzNWESoWCb95Szp93tdDU7aRneIyX93SSZTaxutTMKksK++qG8Aej3HNVwZz7SN6wIZdDTVbeP9rHurLUU7yLR4er2Dd4iCxTBg8suZNAKMrx1lFS4vUUZsbOcNapKc2ZyH9q6HZw6+b5hXEvVg6OuAmKIldkJKGeY76WJEl8XD3IC7vbCYaiLCtMYsf20tPy+dQqBassKayypODxhjjYaGV31QB7a4fYVzvE8uJkrlufS9EJA/9QoxVRkti4NH3B1qdTKnmgOJ1d/XY+GXbyn0193FuYRnHcxOcwLIp80G9HJQhcnXF2XR1kZGQuDWQD7K+ccX+Yf3vuMM6xIHddUcTyvAQ+fvpFsh31WMUgCALGZcuJv+IqDGXlk7lesxG3eQvjx4/h/nQPVVYlnYMeUhP1/OODq6cN2Rl0Kn5493J++WINbf1uDjQMc+9VxRh0U4+3uf38/PlqvIEID11fSmVhEpIk8fxHbUgS3H1lMSnxer5/xzJ++sxx/vBWI/Ex2smNcjpS4vX88K7ljPvDVLfZONYyQkO3g9c+Hee1TyeM0cRYLVesyJjTcwGgUSt56LpS/s+zVTz+ThP/9JU1qJQKRn12/tLyClqlhoeX3o9GqWFf4xChsMiGpWlnJKNg0KnIz4iha3AMXyCCQXdpfwwbe53stTnRKRWsnUXz6iSSJPHYGw0cbhrBoFXx8A1L2DiH5zvWqOHaNdmT4cl3D/VQ1Wajqs1GSVYc29fnsr9+GKVCmJN0yHxQCALbs5NJ1Wt4tXuEJ1oHuT47mY2p8ey3unCHI2xJSyBeO31IXEZGZvEghyAXAF/Yj0qhOm1zCIWjvH+0H8dYAJNePWVu0UyEwlF+8UIN3UNjXLsmmxsrEuj62c9IsjYSFVQMJJZT9IPvkrLtWjQpqfMyBtRmM569n+Lt7ORxewpxsXr+r/tXEjdLOxa1SsHa0lQONgzjC0Rp6HJwWUXaaVVoDk+Af/1LFTZ3kC9tKZis+KvrdPDm/m7K8xO5dVM+giAQb9KSkxrDwQYrx1tHWWkxY9KrZ3VXa9RKclJjWF+extWrs8kyT3gbxnxh7rumhOyU+SV6J8fpcXtD1HXYEQQoyo7h0ZrHsQecPLDkTkoSigB4/qN2bO4AD11XinGG/LKZcHgCNPe60GmU5KfHnPb8nStXvS8SxROKYJihZdJU9Iz5ebp9iHaPF3sgTFgU0SoVaGYpIthTPcCTR7pRJurYmBJH6RxU241GLe8d6ObtAz0UZsTy3+5fSUl2/Lze34IgkJFsZHNlOktyE/B4wzT1ODnUaMXtDbGsMJnLl83dQJ8P6QYtRbEGmt1e6p1enMEwR20eNEqB+wrTp9X9WqzhGVh8a19s6z3JIl63HII8FxwePs6Tjc8Rr42jOL6AkoRCiuMLSdYn8tKeDj442j85Ni3RgCUnfuJfdsKU0ggniYoiv3u9gfYBN1tWZHGD2UfPj/8nivExRow56G+9l7ZDVoJHHFyflzlvT4ygUBBYshLV/g9YFuzj1rvunnMuk1aj5Nu3V/DPTxylxzrOb16u4zu3V0xKVrjGg/zbc9WMugLcfFneZJ5NVBR5/qM2BAHuvqLolDlXFibxwLYSntrZwi9eqOEfH1zFfLTJ9VoV68vTWD8PSYipuHNrIbUdNt4+0IM7tpresX7Wpa1ibdpK4ITh1OOkKCuOGIOGvbVDHGgYJhSOct81JacVRkxHQcbEuFc+6WR31QA3bshlU+X8E/rnw5AvyBOtA/gjIt9bmkOSbm7aZaIk8Vr3CNZAiCFfkAand/KxWLWKDKOWdIMWBRARJcKSRFgUsY8FaRpwYsqPRYqKjLQ6IWf2V9Xq8PGXD9vQa5X8zS1LZ/yczIYgCFhyErDkJNA3Ms7OQz3UtNu5Zs25lQDJNun427Jsnm4bouqESOsN2cno5mn4ysjIXLosKgPsWMsI3kCEDeVpC7LRSZLErp7dKAQFETHCEWsVR6xVAJhUsbgcJhJz09mSt5q2vjHa+t3sqR5kT/UgACkJehJMWpRKAYVCQKVQoFAIKBUC7vEgrf1uynNiuS1Yx9Cv3wSlipbkdUiV67lpaylDIyF6Ox20NVgpmWc1V8eAmyescXwNuEY1SKZ5Zs+EFIkgqD57u+SlxZKbZqJneJz6Lgc/f76a73ypElGS+PfnqrE6fFy3PucUIddPqgcZsvvYsjxjSrmArcszsbsDvH2gh9+8XMdPv7t5XmtaCPRaFTu2lfLrXR9w2H6MFH0yd5XcOvn4/vphJCASEfnBb/YSinwmvvmTPx/jnquKuWLFzAbxkN3LX04IyqqUAl5/mKd3tfLOwR5u3JjHZRWz5yb5AmG0GuWc9a86PT6ebh8ieEIsdGe/jfuLZvYA2Vx+ajvtHBp2MWbW4h/yUqHXs25VJkP+IIPeIIO+AM0uL80u75Tn0KacyCMc9vFxg51leYkzynaIksSvnqsiEIry1euXkBS3cI26s1NMfH2GytmFJk6j5hulWbzVO4o7FGHdHMOvMjIyi4NFY4B1DXl49LV6JAne2NfFjRvz2FSRflY6TG2uDoa8VlalLOOh8vsY8lppc3XSbG+jdqQNVbIHP4Oo0838cMOVREWRnuFxWvqctPS6aOt3M+KcXoG9IgFu63ib4Z4u1KmpuNbfRn9DgCtO5MJcvq2E5/90hL0ftJOVn4jBODePxqDNyy9frMGvMBHNLUbZ00ZoeBhN2tRGnGvPx4w+/yxxmzZjvveBSeNiU0UGPcOtZKeYaO138/8+cQSFQoHV6eOa1dncsaXwM22yQIRXP+1Cq1HOmHh+2+UF2NwBDjVa+fmzx/jq9tI5i7UuFDlZKgwl9UREBRbpSnQqLVanjw+P9vPR8QmPZvfwGKkJejaUp7F+aRqjTj+PvdHAn3e10t7vZsd2y5Qh59oOO4+9UY8/GCUlXs+Iy8//2LGSQ00j7K4a4MmdLbx9oIf7t5eyNDcepUKBNxCme3iM7iHPiZ9j2D0B1pWl8s2bZzcoGp3jPNcxjITE3QVpHBhx0eD00unxUfA5LSpRkmjpdVHXYaemw8aQ3QcKMG9IRylK6Owh9lodBL1hvnZj2eSXmLFwBKsvBAKoBQExKvL4W00M2bzcubmArcszsdq8/Euzgz+93cQ/P7yW+GlC3R8e7aeuw8byomQuqzh7iYgLjUap4Pb81As9jTkx7g/zhzcbCYWj/PDu5efUGysjI3OJ5YAFoyF+euSXOINuShOLJ/8eiYr86sVaPN4QG8pT6R4eo6rVxoGGYXRaJVlm4xmJMb7S/hbDvhHutXyJRH0CMRoTebHZNNfqaTuexPqsZQzTTESMsCFjDQpBICFGS3FWPOvL07hhQy43X5bHjRvzuH5DLtevz2X7uhyuXZvD5aph8j9+johtFPPWLaT8zbfZs3+UcDjK1utKUakUaHVq1BolXa02vGMBCmepIITPcrM83jBfub6U4twkxo8fRdBoMJadupmL4TAjzzyF483XIRol0NWFoFJhKLEAYI7X8f6RPmL0ataXp1HX6cAbCLO8OJmHb1hyihfotU87aex2cuumfCqmkHk4iSAILCtMpq3PRXWbDY8vTGVh0nnrGShKIr+vfQpbcBTlUDkdTXry02L4xQs1tPS5kJhY9w/uWsYdWwspzU3AqFOTkqBnXVkqHYNu6jodHG8dZUluwqQEgiRJvHe4j8ffbkJC4OEblpCTGkNdpx2jXs3dVxazqWKi12ZLr5MDdcMcqB/mw2P9vPRxBwfqh2nqcTJk96FSCujUE4UTq0tTiJ1B7+rIqJsXO62oFAIPFmdQlmAiTa/liM3DkD/EGvNEn89wROTRV+t55ZNO2gfchMJRluYnUrIqHacSNqcnsmNdHu39E+vrHHSzotiMWqVAq1SQqFOTqFUTq1Hx7LsttHY52VqRwe2bC1ApBOJMWnRaFcdbR+kfGWd9+ekJ9UN2L4++Vo9Jr+b7dy2bd87kxc6FzI8Zcfn5t79U0Tnowe4JIEkSZXmJ5+36iy03aLGt9ySLeN1T5oBdUgbY3sGDHBo+htU3ylU5l0/e4N852MOhJiubK9N5+MYyNlemE4lObHTHW20cbrRi1KvJTDZOu9FHIlHGPUGcNh/WwTHa2gepru8k01OEyhpPamYsGq2Kxm4Hz7zfRkayiUduWUOTs4WesX6uzN6ESnH6hiIIJ8KPSgVqlQJh3IPz6ccZf+9tUChI3fEQxQ89QG+vh+MHeikoScbyuXCjOS2G/m4nfZ1OklNNJCRNr67t8Yb42fPVjDj93LG1kKtXZaNOTcG1+yNCgwMkXHXNZBVl2Olk8Fc/w1tdjTY7h4xvfxdfYwPeqmOok81os3PQqpX0DI/R0ufGF4ww7g8jAKMuP0lxOnJSJ5LgR1x+/vhWIwkxWr5+UznKWbyOSoXAypJkmnvdVLWNEomev81gZ/eHHBg+yrLkcrZnbedQ0whHm0cJhKOUZMdh9wR5+IYllOUlnvZe0WtVbFyaRiAUpabDzr66YZLjdaQm6Hn8nSbeO9xHvEnDD+9eTmVhEmmJBo40W6lpt5OfHkteWgyVhUlcVpGOUq2kodOOJEmUZMWxdkkq167J4e4ri7htcwFpiQYON40QDEVZWXJ6XpUkSewZcvJ2nw2DSsFDJVnkn/B2xWpUOIJh2jw+4jUqUnQafvd6PdXtNkpz4tmxzcKD2ywsX5LCzhEnaoXAfUXpGDQq1i5JpX/US12ng6YeBytKzKc0sn7t0y72VA9SmhPPN24+tdVUQXos3cNj1Hc50GlUpzRgj4oiv3qpFrsnyA/uW0nmGbS5uti5UJtT56CHf/tLFQ5PkGvXZOMaD1HX6aCyKGlaT+VCs9g25sW23pMs4nVf2gaYKIk80fAXfBE/ITFMeVIpCbo4huxeHnujkRiDmu/eUYlGpUSnUU1udKGISHOPk6Mto1S321henHzKN29Jktj5SgMfvdVM3dEBmmuH6WgeZah7DON4IspxAw6bF6fdR1ZhIr94oYZgSOR7d1YSZ9DQNTxIf7CPgrhcUg3TJyBLooj7490MPfobQn196EssZD7yQ4xlZRiNWvZ91I510MO6LQWnGFmCIJCaGUtTzRCDPS5KK9NRfSF0EAxHee9wL797vR7HWJBrVmdz2+aJCkRBqSTidOJvbkKXm4cmPR1fawsDP/9XwsPDxKzfQMa3H0FjTsFQvpSxQwcZO3YUXUEhmpQUlAqBI80jjPvDbChP4+6riqhqtXG4aYSoKFGaE89T77XQP+rlwW0WctPmlqSuVim5al0e+2sHqW6zoVIK51w1vt3VxdNNL5Cgjedvlz9MRmIsu6sGCISjlOclMmjzolYp2bHNMm1YVKEQqChIIjPZSHW7jUONI+yvH6at301+eix/f+8KMpKNJ9aooCQrnn11w9S021i3JBWDToVeq2Lr6hy2VE54STdWpFOWl0hGshG9dqLaNjXRwNGWUZp7XGxcmnaKFIgoSbzTZ+PjISdxGhVfs2SRYTx1I8026jg06qZnLEDNoQGqW22U5SXwvTuWkZ5sRKlQ8H6/nc4xP9dmJU22zVEqFawuNePwBKjtcFDdZmNZURIGnZrDTVae/aCN5Dgdf3fP8tM02ARBoCw/kQP1E+utLPxsg39rfzcHG6xsKE/l/u1LFutN+ryvu6p1lF+/VEsgFOWBa0u46bJ8Ms1G9tcP0zHgZvOyjPOSArDYNubFtt6TLOJ1X9oGWPVoPXsHjxFvug0JIybVOEXxBfz2lTps7gBfu3HJaZu//kQfv43laYz5wzR0Oalqs7Gi2IxBpyIcirLrtQa62+2TxyQmGylblU6Nbj+e9AEeuvkGxpwB+rqcNA24aRn1csOGXFKUSt59uZ6RgTFc5gFMaiPlSaVTLig4OMDgo/+Be89uBI2GlHsfwHzPfahiJjxIep2at16qRalUsGV7yWk3RP2JEFR3u51gIEzeiSRnUZT4tHaIR1+t53irDZ1GxZe2FHLTprxTQq6q+Hjce3YjhoKI3nGG/vAYUiiE+e77SP7SnShOJN+rYmLRFRYxdnA/48ePYqyoJD03jZZeJxUFSXz5OgupCQZWlCRT12mnus1GW/+EMnlBRiz3XnVqu6E6WyP1tiYK4qbu1ZiUYKAkI5ZjrSMcb7URa9TMucpwvgyMD/FY7ROExTDfqnwIsyGZ37/ZSM/wGEqFgNXpJxgW2VyZMadG4BnJRlZZUmjpdWJ1+tm4NI3v3L70NNmKeJOWGIOaoy2jdAy62bg0DYVCwGjUEvCHp/XICoKATqPkWOsoUVGisnBiTsO+IK/2jFBlH8Os0/D10swpqx21SsVEuNPjY9jhoyBGzyN3LJv0ZjmDYV7sshKnUXFnQeop7xeFILCiOJlwRKS63cbRllFijRqeeKcZlUrB39+7AnP81B0StGolWSkTG3xzj5NNlekMjHr541uNxJu0fO+OSuLj9Iv1Jn1e1/3B0YmQuFIp8O3bKiabyqfE63GNB6nrdCAITNutYSFZbBvzYlvvSRbxui9tA+yZphfxS0WoVPkolam4/Y1ErWZ2Vw2yqsTMLTMkfht0alaWmBGliSa9x1tHKEqJ4aPXGhjqdwNQviIDSZKwj3ppizQzkNLMpsLVrMpaSnp2PA3VgwRcfpRxOtL8UeqO9BOJiMSoYhhKbMcb9rI157JTriuGw9jfeoPhPz5GxG7DtHoNmY/8AIOl9JSNd7jfQ9XBXkor0sifZvNPzYylq81Gb6eD9Ow4Om1efvtqPZ/WDiGKEtvX5fCtW5ZSmptw2qauiotjvKYaf0sz3rpalCYTmd/9PrFr1502Vp2UjCY1jbFDBxivqSJuzVq2rC9keVHy5CYdY9CwriyV9n43rX0TTZO/dcvSUyra+sYG+I+aP9Fgb2Z92ioM6tM3bKNRixQVqSxM5nCTlaPNI6Qm6smapWJzvrS7uviP6j/gDfu4s+QWVqRU8NLHHXxSM0hJdjw3bsil+oQRfv81JXOWRTDp1VxWkc6KEjNXrsycNvSamxbDiMtPXacDfyhCRUHSnG5U6UnGSe9acXEiOwftvNVnwxYIk2vS8VVLJjHqqfOooqLIe7u7cGlAl6jjG5uKiNd/Zqi92TPKkD/IzblmMoynVyIKgkB5fiJatZJjLaMcbx1FFCW+detSLNkzb9gpCQaCJ8K0Dk+A3VUDuL0h/va2pWSaTYv5Jn1e1i1KEs9/1M5re7uINWr4u7uXs+QLRpYlO56DjcPUdTpYXpQ8qz7g2bLYXvPFtt6TLOJ1X7oGWKe7m509RzAarkCnVBKVwBtRUH3QikahmVNCryAILMlNQKUUaG214agfIeALIwig0CjZYxtDl2oizmyg3XCAiDpIbs9ysjPNiEqBD6oGiImCPhjBPxYivySZ7beVky64GGtsJXbUSmqPC//RY3j2fopr94fYX38NX20NqvgE0r72DZJuvBmF7vTN7ti+HqxDHjZdXYRpGq0uhUIgJT2GptohmhpHeKthGI8/zObKdL5zeyUrS8wzVzUJ4K2pRpuXT9aP/gFdds60Q7WZmSh0OsaPHcXXWE/M2vUoNKd6WbRqJevLUwmFRSqLkie/XQP4IwF+U/0HxsMT0gVpxhRyYrNOu87JD6tJr6YsN/FEPtYIOakxp7VJOlNqRhv4fd0ThMUIO8ru5rKMtf8/e+8dHcd1ZXv/OuduNDohZ6CJQDDnTEdyv7gAACAASURBVIlUFpWpYEuyLYfxWB7b42884c2yx/NN8oTnZ9PZHku2lbNEiZKYcwSJDDRyDh3R3egc6v0BkhJEgMEi/Uam91pYi6yudKvq3nvuOfvsw94zw7yyv4esTDV/+eB8yvIMuCaiZOoV3Lys4IoSAiQSMUad4qLHnDNmTne4aOz2kGvWUJJvZFfvOCPhGPFUGrn4QtFTsVjERCJJR6+Pem+QgFpCvkbJliILN+WZZxVJTaXT/HJ7GyfbnNi0CpJ6OaFUmrmZUx7X4VCUtwZc5KgV3F5guei9l+UZMBuUtPX7uGdtKWtqL0/c1F6QQWO3h+ZeL8Fwgg0Lctl0Vqz3Oh6kr3m7E8k0P3+zhYONo2Sb1HzroQUzStDIpGJyzhr4PaMBVtdmX9NQ5PX2zq+39p7DddzuP14h1p39B1AqVwJi7i228c5ALz7yEFnbeaCy5rKJpIIgkC+VMkckJi0IhEQiNAL0xBNEJWJOd7gRa30oqgKIJmzUd0bp6TzKEAKTgAERCkQsWJZHtcaD5wf/Qnx4iA1nzx/m/Q8uJhIh0erI2HgjprvvRaKaOWSTiKdoaxpFZ1Biu0TdQV8ihVME1pTAfKmUG+6uxl56eXXnDGvWocjOQVFUhFh2aTmLjE03kfB6mNi1k5Ef/YDcr38TsWx6eE0mlfDgDeXTtgmCwHPtr+CKeFhoreW0s5E2bwerc5df9HqFWTq+dn8t//l8PT95vZlvPDDvknUoL4XDw8d5zvEqMomMP5v7GFUmO43dHn73vgOdeioT71xZps/fUfWxrnUpKOVSvnz3XP7x6ZP89zttJEwK3h50T9tHI5VgVcmxqeRkKmS0+CbpE8cRy8REh0N88UY71WbdRQ2mdFrgV2+3cbx1nLJcA1+7qYrf9IzR7JukNxihSKtkx9nr3pxvvqzs4FVzs1lRk3VFmcRSyVRNz3946iQZGjkPbCi77GP/hN8PsXiKba820tLnoyI/gyfvnYtmljJiADUlJlbPzeZQ0yg7jvVzx6riWff9E/6EP+HK8Yn3gDnDLl7raUCpmE+5Xs2mXBPjYx6GUyIUehWPLSi7rJVbMpli/w4HZ44PotLIyKqyEh4LEgUCOjn/+MQy1s7LoUc4ziReYr1VBOJq3EAcUAGr52YRcIdwDbrR7n0eUcCHbtkKIrVz2ZHlZCCviPWf+zrmLXdjvuc+Mm+5Fc3c2gsMlw+ju91FV5uTuYtyySua3eCo73Lzw1ea8KcFFlRYCLlCjPX5yC00orkMA1QkEiEzmRBJLk+pWyQSoa6qIT4yTLi5ieTEBNoFCy953KGR4+wc2EeJoYgv1T7OibHTjIWd3JC/FrHo4uV4THolRVlTJYtOtjvJNmnINs1edHw2CILAu327eaVrO1qZhq/Mf4JyYykD40H+90sNiEQivvHAfPJnEIu9ltCr5ZgMSk44nIxqxUilYrYUWbEq5aikEmKpNGPhGEOhGJ2BMP54kkqjlhK9iu6BCXL0SiouEf57dlcnBxtGKc3R842t81ErZdhUCk65A4yFY2TIZewb9VFhULPxCopG/z4yIVqVjDVzs9m4KA/lhwj712qVLAgCbY2jvP96C9FwAmu27pIZuX9IXEvvQDia4L9erMcx6Gd+mZmv3jf3smQ+7AUZHGmeCkUurLCgv0ytwSvF9eYZud7aew7Xcbv/OEOQb3TvxJOsQSyS8VhFLp7RIC+820vaMoZUkY1GKiZfO7N36cPY+UYrXW0uLFk67nxoHqdPDJIMJRhAYFIQsGSo2NvcTa/0MEJEi9RZRXVRJjkmNclogiJPJxXN76CJ+XFpCklkFbH4q4+SsW495spqXvIex6WJUSZdhrVgStfKORFhMpJArbiwjuQ5HNvXg98XYd3NdlTqmQ21oy1j/OyNFiRiEU/eV8u6lUWo1DK62110tjqxZuvRz0KK/jgQnS0EHmpuItzUiCI/H3n27CGoweAIv2z+LSqJkq8u+DxqmZqxkJMefz9VJjtG5fQsx5k6q9WoJsek4WS7i2Ot47gnIswpMJ4Pr6bSAmc8QdQS8YxlX9JCmpc63mDnwH6MCiOPFD9OXx+8fqiX1w70kkym+eKd1dR8RKts9Oc/wfnsM6QmfEiNRqT6a5MMkG/V0puIE1KKMYTT3F+VS5lBzTyTjpW2DNZkGak2ainRqdmYk8nqLCNlWXr2nhmibzTIxoV5sxoVnUMT/OY9BzlmDX/10MLzRcANH5KlaJ8IkRYEHi7LnpU/djWhlEsvCI1fi0E6Fk2y9512zhwdJBZNMjrop71pDKVSismq/YPpzF0M12py8ofi/Mfz9fSNBVleZeMLd1Yju8ySSDKpBFummmMt4/SeC0Veg2d1vU3M11t7z+E6bvcfnwE2GQ/xfFcHUmkBa7OMqMYjvPdyM6qkgDLXTVRmYWAyzjJrBrKLlGwZGZzg2N4ebLl6tjw8n/eO9OPpdBMXi1mzqYzGbi9nOt245S1IDF4WGVbxV1s2sqo2m3naGHP2/o5SVzuyVAKX0Yoiv4xxvxhzoZVMy5S22GBghJH4CJFmNfNqinj7WD/bXm1id90Q7x4f4HSHi+7hAM6JCLF4CrlMTCqe4uD7neTkZzB/2cy163bXDfHUjnZUCilf3zqPysIpvSxrtp5Ms3rKCGsZJyNTTablyr1Fl4JIIkFVXk7g4AHCrS3oV65GrLjQ4xZJRtlW/wuCiUmeqPkUhfqp9qTSKU47GzEqDFQYS6cdM1tnzTFrWGi30DMSoKnHy7HWMfIsWiwZKg6O+XhrwMUpVwCdXEq2Sn5+ck0LaX7Z+BxHHf0oPVUIgzXsOeGkudeLayJCrkXD/RtKWVY1XYE94XYx/vSvEWJRoj3d+PftYbKxAVIpZFbbBfy3j4N4Ks0+f5BEMk3/sVHqO1ycdrho7PHQ3u+jdzSI3xeBaIq8TDUKmQSZVEw0nqK514tBqzhfZ/LDSKbS/OCVRoLhBE/eU4vtIxy6PI2CEy4/8bTAQpOOZdbpxrDHOcnRvd1Ys3TIFdfWMLucQbq3w0Vr/ShqjRy19uLPf3wkwFvPNzA2FCArT8/tD9SiUMkY6Z+gx+Gmr8tDRqbqmixSrgTXYnLy+KN879nTjHjCrF+Qy+O3zrns8lXnkJWpxukL09zrRSGTUJ539eVgrreJ+Xpr7zlcx+3+4zPAtvceYSxeglIisFGqYefrrQDIEFFhs9EhbkEkySMtCJQbZjY+BEFg1xtthIIxNt9VxbFONw2H+1AhYt3NFSxfkEdprgGJRCBoPoFUIuFryx5DKZORmpxk6N//jaTXg2H9Rg5UbGZHyIIpW484EGeoz8ec2ixkMgkJIUGDuwVxUEFbfYo9bU5MegXzy8ykhanyQH1jQVp6vRxtGeO9E4M4GsdQJQUKa2zk5hmmhVIFQeCtw328tK8bvUbO//fQggskGjLNGrLzDPR0uOhscaJUSrHNMDl/XEh1esRyOZNnTpNwOtEuWTrNoyAIAr9te5Eufy+bCtazNm/l+d8MCj27Bg6QSCdYmbN02nln66zJRArX4AS3ry9BIhHT2OXhcPMYvskYZxJR5Gc9Kk2+SUbDMTIEqGtz8bvdjbScUZDy5BILThkg88rM3LS0gE/fZOeW5YXkW3UXXG9iz24i7W1YH3kU/erVCPE4kQ4HocYGJna9T3x4CIlej8x0aXmKS+HQuI+2iRDr88z4h4OMuEOMeSMMu0L0jgbpGJyguXdqQVDncLKyJgu5VEKeRcvu00MMOifZuDD3grD7eycGONY6ztp5OWxcdGHCg1IiQSER444muK/YNs17mIgneePZekYG/AQmIpRXXdvSOhcbpJOJFAd3dXF0bw/jIwFa60cY6vMikYjJyFRf0EcaTgyx+602YtEkC1cWsPG2Oag1CnILjdhrbETDCQZ7fTiax/GMT2LJ1qJUzU4JuJa42pPTmDfM9547jdsf5ZblBTx0Q/nv7b2yFxg53DxGQ5cHbzBKgU13gc7bx8H1NjFfb+09h+u43X9cBlg8GeeZriFEYgObVBqOveUgnRYYVUkxy6T4RxL4DI1IVcUMh1PMy9ShnsHt3tvhpuHkECV2Mx6JmDd3dVKAmEyblo03VSASibBmqEjphjnpPM3a3BXUWqoQ0mlGfrKNWH8fpi13Y7l/K1X2bFr7fDT1T1BVksmkM0TQP1UiSCvXsGfwIIIgQj9oQZ+t4y8fXsjKmmw2LMjl1hWFLKu0YS8wkp2pRqOUInaFkSLw/qCP9+uGGHQGSabTZGgVvLK/m3eODWA2KPmrhz8Q9/wo9BkqCkoy6e100+Nwk0qlySkwXBBycYU9PO94FZPSSIbiyosGK4tLiDjaCbc0IbdaUXwoi/ID3lchj1U9OI3rJRPLaPN20BcYYH3eKmSSDya/2TrrycN9HN7VjUYjZ+3yQuaWmugcmqCl10toLMzqUguLdBo6HG5az4yx9/gQTT0e/ME0IlWIdfNyeXCDnYc3VbC8KovCrNknE0EQGP/NrxESCbI+93mUBYXol63AsHY9Ep2epMdNpMNB4PAhlKVlyK2XLgc1G6LJFM91jyETi3hyaTmrKq3cvrKIW5YXsnFhHqvnZrO00sqCcgtKuZS2fh9DzhDLKm0oFVL8kzFa+3zYMlXTDEn3RISfvN6MWinlyXtrkctmDj/la5WstGVcELo98F4Hw/0TSGVivK4wthw9BuO18xbN9t597hDbX2xkoNuLyaJhxcZSUsk0w/0T9Ha4aakfIRZNYjCqSKfTvP96Ky1nRlCp5dx8bw1V83KmffdyhZQSu4XC0kx8nhBDfT5azoyg1Skw2y40xK81rubkNDAe5N+fO8PEZJx715Vw15qSjxVmlcsklOUa6ByeoKXXx57Tw4SiCQqydNMqIfy+uN4m5uutvedwHbf7j8sAe723gdGYmYxokNB+J6lkiiGZmC9/ehE5WVq621wYUyZG9c1IZSUEEklqM6cPqul0mndfayEeTZJRaeX5vV2Ui8XIBdi8pWpaSOLZ9lfxxwI8VvUgGpka7/Y3CRzcj7qmFtunH0MkEiERi6ktNXGizUnrWBB7ppqxQT9Gk5rJhITjI2dIqAJYx0pYWGbFXvnBZC0WidCp5eSaNVQWGqmw6XDUDZOZrWfOglzGPSE6h/ycdjgZ7K9DkujHmiHnz+5ZgiXj4mRxtVZBid3CQLeXvk4P3W1OVGo5RrP6/KD8VMtzNLpbaXC1sMBaO6Mu18UgEolQV8zBf+gg4eYmlEsWk5BLGJwc5tctz57lfX0BtexC+YiJ2AQdE90U6PPI1nzgXZmps6bTafZsbycRT+GfiFCzMBejTsmcChMnxiaIeaJ0dHo41eok6I0iTgsoTErU+TqUpRPMqw7yuZU3YjaoLis5I9rdhe+9HegWL0G/bMX57WKlElV5OYYNN6AqKyd48jjh5ib0y1fOKCVyOdg36qMzEOaG3Ezm5RgJh+OIRFNlqlQKKXqNHLNBRbZJQ22piZ7RAM09XtKCQGVhJjkmDbvrhhn1ToWbRCIRgiDwy+2tjHjCPHqTndLcKzOuu9tdHN/fi9mm5aa7q2lvHMU5GqBq/rVTSP/oexcEAUfTGO++2kwoGKd6QQ6b76rGmq2notpGRbUNsUSMeyzIUJ+PprohWutH8bpD5BcbuX3rPEwXSajQ6BTMmZtFpkXDUJ+PHoebvELjrJIv1wpXY3ISBIHDTWP89M1mwtEkn95cweals0vKXAky9Uo2LMjFkqGib3SqpNTeM8MkEmkKbbqPVbz7kz4xJxIputucSKTiy/KgftLb+/viOm73H48B5guGeb7bhTgqIuuMn2QsxZBExBMPL8CUKcZk1uAenSQwkiKsGCLTWsJAKEW+LIyWCFL51GDcWj9KR/M4hhIjbzeOYpFLsSQF8ouNLFpVBEAkGaHN08Guwf3UmOawLn8VoZZmxp/+NdJME3lf/+Y0zpNSLqUiP4MjLWO44klsYjHdHS7ebhwloQgh1k9gFXLxdscpq7TO2lmbTg0xOuhn1YZS7r65khVzLCwqCLI0+yTzsocpNU1gN48Q9x0n7O8gEXGSTkURixWIJBfqTimUMsqqrMRjSYb7J+hud9Hb4UatUzAsDLCjbxcZCgOBeJA2bwdLbPOneaNmgzvi4Yf1v+LVrrd4b/wIflmK4v4QTS37+aH4KEdHT5EW0nyu5pHzvK+PQiqWcWT0BCqJklrLB3IPM3XW/i4PbQ2jSEkRiaTIyjNgMKp4vd9FUCvhtpocJCmB6uJMtqwu4bGb7CyvyaYhOo5EkUNKlEeBVkWG4vLCTN7tbxHr78PywIMzerdEIhFyqxWxQsHk6Tpiw0Poli2/Ym9DKJHihe4xlBIxW0uy0GuVFx2oRCIRtaUmTrU7qe/0kGfRUpZnYNwXoa3fR5ZJjUwiZl/9CPvqR8jKVGHSK6lzuGgf9J0vDH8xI2oyGOOdlxoRAbdvrcVs0xEJxxno8SFXSMjKu3JP6eXgw+89Hkuyb4eDuiMDSGVibrijigXLCxB/KNFAqZKRX5zJ3EW5GIwqQpNxJgMxlq0rYe1NFchnyPYTBIF4LEXAF8HtnDwbXo0ilojwecL0d3kor7bNeOzVhMc1iaNpDJNFg17/8SoAeANRfvZmK++dGEAqEfO526pYfZm6bJcLkUhEgU3HhgW5GDRyukcCNPV42F8/TDSepG80OBUF6PZQ3zUVJj/Z5uRku5NYIoUtU410hiSRT+rEHIsmaDg+yM432uhsddLeOIpGp8Bsu/ii+JPa3o+L67jdMxpgIkEQ/tD38nEh/J8jp2h1CmTVjSEJw7BIYOv9c3FJW3mj512UEgWrMlYx+q6MmDiKeF2YkXQ1d732CzICHlRzK9CvuI3X9/uZiKdwiCEpDbBUoSXhEyFdPY5XMY4n4iWUDJ+/8JfnfY4KkZn+734bIRol/1t/i7J4ZoX9Y61j/PzNVmxSCQVJgbgISjer2OF7haXaZYT3mCixm7np7hpgagXlHgviHA0yPhJgoMeLIAg8/uQqdGovfa1vEQ8NASI0mfNQ6kuJh0eIhQaJh0dBSJ2/tlRhwlx0L3J11oz35vdFOHWoj46W8alr60IM57Tw5I2f4vhYHXsGD1KeUcJX5j8xYwHxcxgIDvHjht8gyDYjF0XRiZqQigSW7ujE2u/Dsb6C8Xn5zDVXsSx70aznSQtpvnXwH1BIFPzjyr85b7xYLDpcruC0fd97/iSqYzuwhftotqxBvWAxFZtL+ZVjmGKdiifsuRcYP73+fv6j7sfkGW4klC5CIhbxaHnO+fqGs95XIk7PN/4CkUJByff+63yh8pkgpNMM/+D7hJsbMd/3AJk334ogCERTaZKCcMmMwh2Dbg6O+bgt38yqLOOMbZ8JQ85J/v/fnkIkEvH3jy5GAP7+l8cveRyASiGhutjEvFITc0tM0yQGBEHgrecbGO6fYM3mcmoW5gIQjSR47ufHSaUEHvrC0suSOLlSnGu7ezzI+6+34vdFsObo2HRn1WUT5VPJNJIZPDIe5yR732lnwhshEU/NcOQHMBhV3P/ZxciuQohtJrjGgrz1fAOxaBKtXsGWBxegz7xyr5sgCBxqHOX5PZ1EYimqi4w8fkvltMoT1wqxeIrdp4fYcayfUDR5yf1VCinLq22src2hMOuDiMTlfu//UxAKxmg4OUhr/SiJeAq5Qkp5tZXOlnHisRT2GhtrNpcjm8WA/6S192rhOm73jCvdT5wB5o3Ehb/eeQbLaQ+KYIoxBNbemkNTci+dEz1oZGrSgkAkGSFrtBzzYDnirCGyVTHm7DyIIBYhSk+1OSpV0J5loq0EIhojhZ1L8BvHGCw/jVQsxaTMxKya+svT5rLcMp+hf/8Xoj09WB95lIwNGy96r6/s7+bto/3MUcnRRZJk5evZk/US+fpsytpXMz4coLzais8VxuOa5MOvQqmSsmi5lixzG9FAJwAqg52M7I3IVNOLegvpJPHIGLHQILHJQSL+dkRiGabCu1FnzFx/EsDrDrHj/ToCA2kAsvMNbLjNzguDL9PgamZp1kIerdw6ozen3dvJz5ueBrEdpXJKRDVfo+Sxihzkk0H6vv13CIkEhd/+LnLbzIbgh/HL5t9xxtnI3y/7JlmaKU/TRzurp+4Mw7/4BcqzRnFKIuN47u1M3DUPZyzBn1flkztD2ZyfNj5Fk7uVv1jwRdIiG890jSECPl2ePWtyBkDw5AlGf/ZjjDffiuW+B2bdL5JM0RUI4/f4yPzRvyMOhzj2wOfoN2YRS08920VmPTfnmdHMMJkH4kn+s6kPtUTCN2oLkYnFVzRQnWgb56dvtGDLVPP3jy5m75khuocDuCYiDLtDVBcZWVmTjU4tQ6eWEwjHaezy0NDtxu2PAiACirL1LLZb2LQkn+ZTwxzd201hqYlb7quZ9g20nBnhwHsd2GtsbLy98rLu8Upgsejo7Xbx0q9PEY0kmb8sn6Vriz+2ZlcinuSlp+rweyOYLBq0egUa3dk/rQKtXoFUKp7yjJ9dnMgVElZuLKOixnZVNcPc45O8+Vw9sWiSsior3W1OBAGq5mezYkPpZWeaegNRntrRTnOvF6V8Svh4TW32H1xWIxxN0D4wgUQsQi4VIz+bnSuXSZBLxcQSKY40j3GoaRT/5JQHpNCmY+38HJZV2ijMN34iJuYJb5j644M4msdIpwQ0Wjm1S/Kpmp+NXCElMBFh5xutOEeDZJjUbN5SNWP4+zo2RK7Xds/YIT9xIcin61q/Ez/mRulP4CVN3tokR0LbcUbc1Jqr+cr8J9hUsA6dTEMX7cjdGYgnzOQOnEIXCvLO1kcRFQfxCVF0gRi5vkkM/gKILEAQiVi/SM89y+5jS9mtrM9fxZKsBVSb5pCvy8X1wnNMnq5Dt2wF5nvuu+QgN6fQSGWhkc3rS/B7Igz1+jBKMumRt3HPgs10NbvxukLEYkms2TpK7BbmLs5l+foSykvakcT3kYx50RpLMBbcjd62EonsQoNBJBIjletRaPLRGKuRqWxE/O2EfU0gkqDQ5M98r/IULwSeIWAcp1JdzWi/n6E+H/esXU9nsJtWjwNEogvkIU6OneFXzb9DEMCsuw1EYqqNWjoDYTr8IWqyzWgtVoInjhPt70O/avUln1U0GaXJ3YpVbabYMMVZOeeuTsdiOF94Dt9LzyFOJ0ktvZGcm28gXHcSfcJFvX0u8ywZrLBdmB4/MjnGy51vUqwv4PaSm7CoFORpFDR6J2n0TpKjVmCeoVg1gPvlF0g4x7E9+jhS3czZo+ORGL9oH+KkO0BnNIUr00pZRyPGgV68tQvJ1WuRikV0BsKccvnRSCVkqaeHiN8bcjMwGeXWAjP5WhXpZISg6zjjPW8ikWouMLg/ilyLllgiRUOXmxF3iEc2V5Bt0rD9aB9Wo4q/+dRCCrP0WI1qMrQKbEY1taUmblycx9JKG2aDimQqTc9IgJY+L4ODE4w1j6NUybhta+0FYTizTUt/p4fBXh/5xVefK6VUyHjp6Tr8vghrNpezaGXhVeGbHXivg+G+CeYtyePme+dSXm2jqMxMTkEGliwdBqMKnUFJid1CSYWZrjYn8ViKvi4PjuYxxCIRJotmWvjz94HHNclbz015vjbcamfZ2hIKy0y4xyfp6/LQ2To+FZK8iLdPEAQONo7yg1caGfGEqSnO5Btb589Y6/UPAZlUQrZJQ1amGkuGiky9EoNWgVYlQ6WQolPLqSrKZNPiPIqz9MQSKTqH/DR0udl1ahCdRk6u6eqUF7uaEAQB9/gkrfWjHN3TxfH9vbjHJ9FnqFi+oYQNt85Bb9HQNxakuceDOVPNgsV5JBIp+rs8tDeNoVLLMNuma81dx6G467XdfxwcsGffbP2ObiRCWpTCVVZPn6wJiUjKQ3PuZUvpLSikCqRiKUW6XKrTY0yKegiN5RLFSCijnxOFg3Qq4nTmKGnNqMSvWIlXVYQ0HafKeRjjyX1EDx4mPjIMqRRSoxGxTEbgxDHcL7+IPCeX3Cf/ArH00itUkUiE2aBCJpVQUJpJX5eb+JiUuDxCSbmVpXMrqV6Qw6obyqian0NBSSYmi5aY/xhB5xFkSgumgi2U1NxBPHn5k5xMaUalLycS6CTibycZ86HSlyP6iNL82z07afd1clPFOm5bvZJYNEF/lxevM8w9a9bT4G6i0d2CWZlJnm6KS7JrYD/PO15FKVVwc8njdAVFLLUYuKfIRjiZot0fptUXYn61HYlrnHBzEyKpFHWF/aL3rJVNZYmKRCKWZC0Apjqrp7md4e//J+HmJiJKI015m1j1Z/egKS4i6vUi7m5HFQ6xZsMa1DO4+1/p3M5IaJQH7XdjO+tZMynl5GuUNPqCNHiDZKkUWFTTjbCkfwLnM79FUViE6bY7ZrznDn+IpzpGmEymWGXLYF22kYX2EpSCAC2NzBcnWbVpPUusBlQSMd2BMM2+ED2BMHlaJVqZFF8swSu94xgVMu7MVRIcO4Cn/3WCHgfpZJhE1I3WvOgyjP0Muob8NPd6Adh5aghfMMaXttSQNUu1ANHZxI+yPAOra6cU6QfGgggDfqQCrLt1DlkzyJaIRCIyzWram8bwOCepnHd1PS6Hd3fhaBmnvNrKsnUfL3vvHLrbnVPJBFYtm7ZUXdKgU2vklNgttDeNIaQFUsk0/d1eWhtGSSXTZFo0SH+P0KTXHeLN5xqIRhKsu7mCynlT/UqjVbBqQxmhcIyBbi+O5nHCoTg5+YYLQqlj3jA/eb2ZXXVDyKRiPr3ZztaNZagvUlbofwrEIhFZJjXLqmysmZeDRimlZ9jP0eYxVArpFSeJXAskEykGe300nBjkwPsdNJwYYmRggmg4gTlHT5bdTMqq5szgBK8c6OG1Az0caR6jsduDayLKiposCkoyMdu0DHR76G53MT4SwJKtQ6WeGmeuY0Pkem33H7YWpN1uXwb8m8PhWG+3H/Ey2QAAIABJREFU28uApwABaAb+3OFwpO12+7eB24Ak8DWHw3HiUufV94VIidJ0zj1EUhlCHsjE0juPiYCKwJoIBqOadDKCq/cF4pMDLCvOY/+JLiYUZcTy1qKSuYk7szB1ZWIVppqfnzvKwkUKdNHbCDc3M9nQQPDoEYJHj4BEgqq8gmhvDyKFkpwvf2VGodFLQa6Qcsu9c3nxqZPk9FXT3NXDgpVzL9gvGujBP7oPiUyPtexRJDLN7zUBydVZZNmfwNXzAmFfE8mYF0vJViSyKXe4O+Jl7+BBjIoMNuSvAWDlxjICvij93R4a9iv50urP8F+nf8wz7S9jVBpocrexZ/AgBrmeL8/7LG8MJBERY5UtA7FIxB0FFlQSCXtHvfysbYjH730QSUcHntdfRW6xolu6bNb7NSozyFJb6fR1k0gnkaZh4NnnGXzpFUinkS1bx15XPmVzc1GcnWgcG25F1eagwlGP++3dmB+4ddo53REvdc56cjRZVJumh2LLDGoeK8/hN50jPNs9yoMlWdR8KEs2ePwYpNPoV66a8X6POSfY3u9CLBKxtSSLeaYPjhXuuptEp4PgiWOoq6oxrF7D6iwjNUYtbw+6aPGF+PmpNjb6xxGGB5HbF7I0y89462EgjUSmI6tsE56xDqKBTuKRURTqi5OpJWIxX9pSzXefOsWbh/sAWFZlo7o486LHfRhalYzFmRpa+/2MI/DssT6+UZAxY/mZ7PyMs5wXJ22No1TNuzpk7+52J8cP9mI0q1l3VgZmJjSfHqav082azRWXlMQI+qPs29GBVCrmxi2VM3LDZoLBqGLzXVW8/WITCqWM0koLjqZxTh7s48yxASprs6ldknfZvDSfJ8ybz9UTDSdYe1M5VfOnPzOpVMKytSUUl5vZ83Y7rWdGGOz2MHdJHhXVNmQKKe8c62f7kX6SqTTzy8x8anMFmX/gbM2rBaNOwRyjms6EQKdYxPO7O0mnBW5ednWyNmeDcyJCQ6ebZVW2C77t0SE/b7/YeJ4fqFBKqai2YczWcrTPyztdHhieOL9/hlbO3BIT+VYtp9qnRJ2j8SRKuRSzVcuc2mya64YZ7PXxwq9OsfWzizHOIhn0J1x/uCYeMLvd/lfA3wPCk08++ctt27Y9BfyTw+H49rZt2+4ApNu2bVMDXwDWADuBp5988slfXOrcB951fGessIVJvZfEgJ1IfxXelJRWV4iddUMcqBugvbsRr38Spa6YLEktqp2vMphRDpFMdP4CjCMK9EjQZ6rYfEcRedltJKLdpFQBTKvvwXTr3WjnL0BqNJKORIh2dUIqRfYTX0Btn51TdSkoVTLMNg2dLS6io2Kqa/KmcT2S8QDO7t8hCCmspQ8jU04Je/6+qwaxRI4ms5ZkfIJosIuwrwWltgiJTMuzjlcYCY3xkP1u8vVTBGuRSERRuYmBbi/93V4yNQaWVdZwYvw0x0fr6A30k6W28rWFXySU0rJ/zEe1UXteNV0kElGqVyMXi2mZmKRpMsbCZYtJnzlF8NQJlMXFyK2zi3i6wm66/X1UKHKJ/PJpPPv3IzUayfnzr9IUz8PtjrB6Uzk6g5JgIsnzvU48ecUUt9RDTzv6RYuR6j4whN7seZf+wCD3lN9+3oP3YRgVMop0Khq9QRq9k5iVcmzqKeN6/LdPkwqFyP7ME9MM7rQgsH3Aze4RL2qphM/Yc7BnTB9QRWIx6spKAocPEWqsR7tgERKNBtHwEIUtp6k4+D7VB95F096MZmQAU8BFYdEgcpWZjJwbMRXciS1vDtGoiLCvGZFIjMowvaj5TFDIJNjzp2r3KWQS/uK+2suq93cO/d0ejuzuxmhWoyk10dTj5UyXm/llphm9K9YcPa31I4wO+Kman430MsvbzIYJb5h3XmpCIhFzx9Z5aHQzGxYDPR52vdlGYCJKZ+s4thw9ulkI5+m0wLuvNJ8PZxaUXH59SwCDcUrcta/Lg1Qi5q5PL0CtkeNxTemGNdcN4/OG0RuUF01ImPBOGV+RUILVm8qoWXihGO65fq7RKaiszUYQBAZ7fQz0eGk4OcTBk4M09HqRq6U8cXsVd60p/kR4vS6GI7u7iUxEMQgQVkg50+VGLhVfE7V9mPoe/uP5MxxuGmP36SECk3FyzOrzz/HAux343GFqF+exfH0JC9cU0eAM8uLhPoY9YUpz9Ny0JJ9blhWwdWMZd64qZkV1FlVFmQTDCdoHfMhiKTpODnFoVxfjwwFEYlCqZSTiKRxN49hrs8kwqq9XT9D12u4/qAesG7gH+O3Z/y8C9p/99w5gM+AA3nc4HAIwYLfbpXa73eJwOFwXPbPEh8gS4jN5N5DKkODKj+MKJHFNpPGGxPgiChqGM2ggA9ph68gzFKfj+KRuDMk8JBMxRIA3X0Px6kLyCq0I6cfxDe9k0n2SMccvMRXdhbrQjrKwCNMdW0hOTJAKBqaJi/6+KCwxI670IWrLZPvL9dx233zSqTSJeAJnz5tEQzJUxlUMDcpRqnwX1S+6HIjEUkyFdyFTWvCP7mG889fEc27njLORYn0Bi2zzp+0vk0u55b4aXv3NaY7u7eZmYzWPzLmP37a9SImhkC/VfgaNTM32gREAVloMdLe7MFk1ZJwtb7Mm24hSKub1Pie/Dkl46DNfRPSLHzHy423kff2bqMorZrzXSlMFJx37iW37BSKXn8xlSzA+8hmSYhnd249iMKrIzp8KUewa9hBPC6yoseOddxPWM9sZ3PZDSr79HcQKBf5YkKOjJzEpM1lknTfr8ynSqfisPZdfd4zwQs8Yo+EYhQE34qFBNPMXIvmQQRdLpXm+exSHP4xVJeex8hyMs8hZyMwWbI99ltGf/ojh7/8HQipFyu8/+07EyIpz6bcZkfV6ye7rwZB8kIw5N03z+Cj1pUikWkK+Zoy5mxFdJCP1HAqzdHz78SWIxSIMV5ChOBmIsmd7G2KJiBvvqMJk1aDTyHnnWD//8rvT/OXW+ReI/Wp1ChavKuLYvh5OHupj9Y1TRmIqlSboj+L3RQj4IgQDUazZekrsZsSzZJImEinee62FRDzFPY8snNVLEJiIsOvNqfuctySfhhODvPV8A2tvqqByXvYF+5852s/okJ/iCvOMv18OFq4owDUWpLfDTd2hflZvKqdmUS7dbU7qjw/S1eqkq9WJIVOFWi1HqZahUstQnf23QiHl+IFewpNxVt5QytwZKhF8FBKpmGXrSiifm8Wr29vwjwRQx0XYEaMWSUiNhwjadP/Pyyd9HAT9UYb6fGRaNAT9USpFIrp0Cl7a100qLXD7yqKrfs2DjSMMjE9SlmvAF4yx+/QQ++qHWV5lY31NFoO9Xqw5OpZtKGF//QhvvNbEZCSB2aDkvvWlLJljndEr6xoLknaFADhweohSxGTl6bHPzaLUbkUmF/PMT48zGYjx0n+f5M//+uIJXH/C9YFrYoA5HI5X7HZ70Yc2ic4aWgBBwADoAc+H9jm3/aIG2KLhg1jX6xFHjoIEckyACUQiCVKFjkRSQZ+riKbuDKIjAxSHR+lXZdGRyqEQASmwen0Jp7RwyOVnfUU2+XodVtsDeEZK6W99BXfPC2QV30BO2eYp3pTl6qpiL15bwPvOdhjP47c/OvqhX/LO/sWA1vNbdXol1mwd1mw9tmwd1hw9FpvuirKyrNZbcBr0DLa/TsfQewB8bslWrOYLOT4Wi46HP7+Mp350hN3b23nsyytZdttcMtVGpGIJo5NR2v0hLCIxh37XwGQwhlor57NPribz7MR5q0WHxajhV/V9PJXWsOyuh6l89XeM/PD71PzTd9GWFF9w3XkBI1t3+lCG02TdejMlT3wWkUTCyUO9pJJpFq4oJCyX0OYJcsoVIFur5JbKXAY/dQfHe7rIc7YTeO0Fyp/8c95v2EUyneTu6pvImoGc/9H2Zho1fP9kF/vHfCw5sodqYFdOOZLeMfL1anK0St7vHWc4GKXarOcLC4pRX4IDZLllI0JfJ2Pvvo/MYMC0cT2G+bVMqvvx+Zook6Sw3Xgbvf/8KybfPkDZ5rsQyz4w6KxWA/G8JYz37UWa7ifzI8byxdpzJUgl02d5SUluu28ulTVThsqf3T8fm1nDr7e38m/PnuE7n19ORYFx2rEbb5lDR/M4zadHCAVi+DxhJnwRhPSF2dVGk5rla0uYvzSfRFpg54kB3jncS0GWjjlyGV5XiMUri85LXnwUyUSK1393hlg0ye3317JweSE1C3J5+elT7NvhIBpOcOPtH/C7Bvu8nDzcj96g5L5PLzrPv/l98MBjS/jvHx6iqW6Y3HwjS9cUk5VlYOX6MrodLo7t72Fs2M+ozz9FtJgBm+6oYsX60pl/PItz725wPMjB+mHePdqHLxij0KbljrVl+AYnaD4zQt2RfuqO9nPnA/OZv3Rmfb3/6Wg9MwrAqg1lTAaj7N3h4M55BbzTMc6rB3pQqeU8uOni3NErwWQ4zmsHe1EpJPyvzy3DoFVw4MwwL+/p4HDzGL3NY+QiRpuj57tPn2LIOYlKIeWx26q4c03JBRUkUsk0bU2jnDjUy1CfDwEBpVhESCzii19fhy1r+tj6pW+u4wf/tJtIOMGv/s9Bnvjamo/1TX5ScaXj0x8zrpkMxVkD7HmHw7HcbrcPORyOvLPbtwCbgA5A6XA4vnd2+xlgk8PhcF/svIe33CsoFhRjfvheJFItEpkWiVSDSKK8YGUyvO0HhOpPE7/zM7w+7iEaUFGZl80jW+efJ1DnqhV8qSofydlj4+Ex3L0vkYz7UOpKMBXdg0R6dbNzxsMu/vHIfzLXs5JiRSmkAyQjvcgUCvSWecgVciRSMeHJOB7XJBOeMIGJ6LRz6DOU3PHgvCtaAadTUQYb/53xZJJmVQWfrXnkovv3drp595Vm1Fo59z66EK1eyYQ3zLMtQwwpRZgaPWQEEuQVGelxuDEYVdz96QXTBpXBySi7Rzx0+MMUd7WwdvcbCFotBd/6W9TZH3gkwm2tjPz4h6QjEQ7O13Df5/+F4pwcGgfcvL67A69MhGBVETs7sUtE8Gh5DuUGDYIg8OIvjlHW8DK6mAfjY4/xr+k9yCVyvrviry9LUBYgnEzR75+E7/4d6XSaHZ/9Bt7k9P6x3GrgtgLL+e/lUhDSaRJOJzKrlUTUibvvFZIxD3J1Dqaie5ApMhl/5jf49+7BfP9WMm+6BfggXTsRdTPa9mOUuhKsZZ+6rGteKQ7t6qTp1DDl1VZuuL3ygn50oGGEp99tRy6T8JW7517AKxvo8fD2i03AFHldb1RhMKowZCjRG1WoNXK62l04GkdJpQREUjHjQprhVJpzylEGYLlNz32fXkhWtmHGVPV9Oxy0NYwyZ24W62+1n79Pvy/MOy83M+EJU1CayaY7qxAEeOnXpwj6o2x5eD45BR8/pBX0R3nlN3VEwwluuqeG4vILa3+m0wKxaIJIOEE0nCASjhMJJ86XBLsYkiIx7x7u4UTbOENnvSlyqZjbVxZx87KC8wKmiXiKHoeLQ7um5Gke+vxS1NdAj+1aQhAEnvnpcSLhOI99ZSVWm55t/7yb0GSczQ/O5Sdvt+P2R7lzVRFbVhdfFg9WEAQi4QSBiQhBfxSVWk5e0QcLhmd3drCrboj71pdy6/LC89vTgsCZDhdH32yDVJp6BAQRrJufy12riy/giYUmY7TWj9JaP0L4rKRGQUkmNYtyOdTjYXfdEH+5df6M/MvxET+v/uYMAJlmNVseWXBJ5XxBEP6fZLZeC/xJhmI6rq3M8wc4Y7fb1zscjn3ALcBeoAv4nt1u/w+m3D7iSxlf5xA704v0rgwUubO78mPDw4TqT6MsLqH8jrU4urazZ3Avi+Z/HoAKg4YFJh1nPEGOjk+wOmuqo54jr7v7Xyca6GTM8QssxfcjvwQJ+kpgVZnJUOnpyq7jscVLcXW+CYjIsn8emfJCjorFomNo0IvHFcLrDDE67Ker1cnrz9Rz50Pzzof+LoUkYgZTAgVSCcX5Ky+5f3G5mZUbSzmyp5u3X2pCZ1DSM+BjZGUWsmiKjbU5VNfmIFdIOb6/h9NHB9jxcjN3PDTvvHhlvlbJ4xW5jIZjHDTpOB6LsvzQu3R8718Jf+lrzCnKw3/0CPHnfgNA8803056Tyc/aRoi1uogk05A9ZWSaZFJq9SqKdSpKdGr0Z/lNIpGImiUFnBxfx4qRt/E8+zu0NxpYvfiGyza+ANRSCflDvYyEJjFtvIFvLigjnEjSPVxHv6cXHWFWWG+/bOMLzoYbbTYm3SfxDe8EIYXOupyM7BsQiaeekXnLPQRPHMf71hvol69AavjAWJApzcg1eUSDPSTjfqTyq5sl1t3upOnUMEbT7KT3tWez1X72Zivff6mBR2+2s+ZDCusFJSYe/coK5HLJrMKTcbmEtlCM0Q43lmQKKyJsYgl5JUb2d7nxAMMqCcIsj7atYZS2hlHMNi1rNpdPu0+DUc09n17AzjdaGej28upvT2PIUBH0R1m4suCqGF8AOoOSW++byxvP1rPrzVbuemQBlqzpq3mxWIRKLZ+2CBkfCRD0Ry+YSNOCwIg7RFOPhxNtTvrHpiYmqUTE/DIzSyutzCszX1CnVCaXYJ+bRSKR4uD7nRze082mO6v4JGFkYIKgP4q9xoZcIUUmk7BiYynvv95K+8lhvvXwQr733GnePNyHVCKeMRzZ3+1hoNtL0B8h4I8S9EdJJtLT9plTm8WaTeWMTUTYc3oYq1HFpsXTPYZikQibQookJZBVnElOto5llVZyLdPpH4l4kgPvddLV5iSdFpArJNQuzqNmUQ4G49QYHJGK2V03xOkO14wGmC3HwOpNZRza2YXXHeat5xu486F55xOLPgznaIAju7vx+yLc/mAtJsvHo6P8Cf/zcM1kKLZt25YB3HeWhF8H/Ne2bdu+CPiYyo4c3rZtWwnwr8CDwFeffPLJgUud19/c8p2Y00WouRHD2vWIJDOHgVwvPEd8eAjrpx5FkT2VJn9i7DRyiRy7sQyJWEKRVkWdO0BnIMy8TB2qsyRikViG2liDSCQm4nfg9bQQEWnRay8tKHo5EIlEjIbG6An0kxvpRZOOYi66B6V2Zo6ZRqMgFk+iMyix5ugptVuQysT0Otz0tLsoKM2c1ZUtCAIjoTH2DR7mhY7XiSZClMulaFU2FNpLhy5sOXoi4QQD3V783gjpGhOTWim3FltZas86n1GWW5hBYCLKQI8XnztMyRzLtMlGJ5NSbdRSUGlnIJLA4Ggh3trM6b5hrO+9SUImZ9fND9CZX4VEYiSWBpNKQUYwibTdx73l2WypyqUyQ0uWWoHiI+FXo0lNfYObiMKAxdtNxWCM6mU3o8y80EtxMbhfe5n46AjWRx5FYjAwOfIeYu9BsqUhMvCSSgTQGGsu+3zpZBRP/6sEXccRS1WYi+5DZ1k6TRJELJcjVqmYPF1HajKIdsGi6WRVQSAS6EAsVaHUFs5ypSvHOdK7WCzijgfnoZ2F9A6QY9ZgL8jgdIeLE21OBEHAXpBx/h3L5dIZQ+K9owF+8VYLrx7oYdgTRm/RsGJ1MaWFRibcIdyjk2QAJqWMDneIQU+INfNziUQS58/hGgvy3mvNyBVS7nxoHqoZsjKlUslUqa1okv5uLxPeKfX8jbdVXtWalRqdgkyzho6Wcfo6PZTOsaBQzmx0JpMpju3rYd87DnocLgYHJojJxJzu9vD20X6eeb+D908O0trnYzKcYIHdyi1LC/jMrXNYXZtDnlV70fqKZpuOwR4vg70+snKvbYF093iQ4/t7cTSPUVxh/tjP9OTBPjyuEKtvnEqq0WgUyFVShvsnGOrzUVJmYsPSAuocTs50uqksNJ5X9hcEgdNHB9i3w4FzNIjfFyGdEjAYVdhy9RSWZlJeaSUcijPQ46Wv083+Xg+eYIwnbq+6gMsIcHx/D153mE23V7JkbvaMmb9njg7QVDdMhknN0jVFbLxtDkXl5mkeLKNewd7Twzh9YTYtmVl/0ZqtIxJK4BoLEg7FGeqboHSO5XwSy2QwxsGdnRza2cVkIEYikaKv002JffZv7ZOCP5Hwp+MTp4QfGhgQ6r/6DRAEpJkm8v/u75EZpq9w4y4nfX/7LeQ5uRR++7uIxGIS6SR/dfA7xFNTL18r02BUGJDJyvAk7RhlUbYUqKnInOJouKNxHBMhWj1u+sNp0oixqxPcUVpO5lXIPDo5epqn2p5nrVLO5sJ1GHM3zbrvbG7bplNTmTZKtYw7H5xecHgsNE7deAN1zkbGw04A5GIZSy1VrIr3INfkklXx2cu613Q6TVvDGHqzmqfdHgQBvjWvGPlHJtxUKs3bLzYy3D9BzcJcVm8qm3EAEgSB0RefZ3LnFBctqTcQfPxLaPPz0csk/Lj+hwhClB/f9s/873/YiUwm4VNfXj4rgfsc3n67joGmIArFLla1DiNRKMj56tfPa5ClUmm8rhAZmWpk8gsN99TkJD3f/Boyq5X8b38Hb/9rRPwOZEobltKH8PS9Qiw0iK38cRSzGMsfhav3JSITbSi0hZgK70Yqn1nQVUinGfjH7xAbHCD/b/4XBcsXnH/n6VSM4ab/RCLTkV31lUuGI5LJFGKx+KKTZDKR4tXfnMbjCnHDHZVUVM+enQogpFJEOhxMWAr4/kuNuP1RVs3N4rGb58xY288fivPK/m4ON44iADXFmdy0tICqog+EQve/66C1fhSFUkosmkQAnAgUVtl49PY5SMRiopEELz9VR9Af5db751JYeuksxtb6ETpbnWy41X7NSOqNp4Y4vKsLo1nN3Z9aeMHE6BwNsGd7Oz5PmJhGxkgqhedsG8/BkqGkPC8De34GCyosFBdkXnF4xjUW5JWn69BnqHjgc4s/dibqh5FOC/R1umk8W5f2HG65r4aisitb2HwY8ViSp394BLVWzsNfXIZIJDo/xrnGgrz8VB2ZFg33/1/23jtMris97/zdWzlXdcXOOQHdSI0cCAIkwTjkMAyHw4kKz9qWLNvr9dq7K/lZ2Stv8K69u1qvJEs7kmYkTU6MQ4JgAIicOufcVV2hK+dctX8U0ESzu4EGhzPWSPP+heeprot76p57zne+7/3e99f6mHXH+F//5iZVOgX/5tf3o5RLOf/ONKP9brR6BQ891Y3Zptkwg1QoFLnw7izn+5eZpUyrXcvv/tr+dX+XSef5xn+6iMGo4vO/uW/D9yuXLfDXf3wZgC/9o4N3dSr4+htjXBj28rtf6aO1ZuOMtUGv4o//jw+IhtIA2Gv1PPm5XoZvLNN/eYlCvoTZpuHIQ234vQkuvT+LoUrFs1/a/UvNG/tVCXItfumEWOUGw+/T0kn86mVKiTjR999FotejqG9YfXECP/x+xUD5pZdR1leyPBJBxKGxIROlaGUaiuUigXSIYHoeicRKDjNXfDdJFAy85QrxrjvEdCxFJA/VKimqYoilvIYr/gi5Ypk6rQLpPQKCzZBNush73uFaMoq/JPBw95fvWirb7NRgr9Gj0cqZHfczM75CXZMJZ26JPx3+Jq/Pn2Y6MkeumGWHZRtPtpzii10vsMu+m0xigVzSidayB1Fyb+6IIAjYqnVMZDOMhJMcdRjpMK4/RYqiQFO7hcXZIIuzQWTyjQ2bBUFAu72Hci6LKFfQ8M/+OQ1N9dhUcgxyGe6Ei7nYIrZIIwtjEXr31lLftDl/Jl8q8NrsW3wQ+gBHqJbunjINew+T6h8hdvkSS0k114ZjnD89zchNN25nhI7t9nUBSuzieZID/RgefogEl8km5lFom7G1vYxEpkGmsJAMDVDIBtFU7UIQBMrlMoszQWYn/eRzRZQq2apAZyoyQcx7FoWmHlv7V5BIN88wCYKAoraW2IUPybqcVD/6MKlbWSBBlJLPBMkmF1HqmhGlBiaGvEyN+Jga9TI24GbououbFxe5cm6e6+cXGet3k0rm0eoVGy7YZ9+ewjkfZtuuavoON96633FCS29QLheQKSyrJVKA0Buv4fuLr1PVWMuxU/uYcoYZmg0x646yu926mqkpFEucvubkj38yzJw7Rq1Vwz98poenjzRjM6lW31HnfIgL785SZdXw0m/ux2hWE/QlkGWL5PwJ+sf9dLZZ+OCnk/g9cfqONLJ919ZoAFaHjq5ex4ab8qcFe42ebDrP4mwIvzdOW7cNURQoFktcv7DAe69PkE7lsXZauOSLkyqUsOmV6Asl7GXYV2PkN57v5dAtT0S5TPKJsgMarYJspsDSXAhREKhtNN37S/dANpNn5MYy7742ztigh0QsS12TiW27anAthJGIAs0dd3dnuBsmR7zMTwXYub9+tTy8KsGhVZCIZXDOh9Fo5XR12iiXywzMBAlEMgRGV5geW8Fs1fDMy7sw27SbBp2iKFLTaOSVgWVyhRK1yTzFdIHaJtOad39swMPSbIg9hxo2NZgfuu5icSbInkMN1N9DW08Aro6voFNV1P83gl6vwmRRMzHsQUAgEcsyctONcz6MQinl6MPtPPBoRePOUWegcEtZf3kxQlu3bctadn/b8KsM2Fr80gVgwO/n5Br0h48QO/8h5WyW5OAA6YlxlC0tlAtFfH/59YoMwJe/uuY049DY2Gnt4UB1Hw/WHeHRxpM8WH+UFp2GkXAOiaQGT7pAoVSm06DhmMPEM402jlWb2akrIA+fx1cyM50oct0fQyUVqf6YrczdUCrmiLjPEHK+jqSYRqauYTIVokSZ7qqNpRng7pPW6tCh0yuYGfczPb7C+cz7+Msr9Fi6eLzpYb7Y9QIHqvuo1tiR3NpQy6UcmdgMUnkVCs3WNrVSucz35nzkSmVeanWsKwHehlQq0tRmZnZihbnJAMYq1YbchUK+RK66BUnPXpQG7ZryVbaYY9A/gnTMTj4BJ5/s2nQzdSe8/NHg1xnwj2DS6njAUqLG4iYpBBn1d1MVWUQ2O4wnrUReXYPOoMTnrqT+G9vMq0FUdmGewI9OfwTKAAAgAElEQVR/QDGRQDgqp1AKojb1Ym1+AVFSCWCkcgO5tJdMfA6JwsHcVJ4zr40zcmOZ5cUI02O3ZQl8rLijBJzXEcQitV0vIJXfm78hM5vJ+bykRkeQWyyI1R9xHEWJkmRokERC4IN3UozcdONzxwj5k8QiGXLZAlKZBK1eicmiJpnIsbwYYeSmG9d8CEGoCItKJCITQx6un1/EYtdy6tntiKJIqZhjZfZvKGQDZGLTxAPXKRVSyJRmhLIUz5/9CeVslmIyie3Egxzc5mDZn2R4LsTQbJCdbWamXRH+8IfDXB33oZBJ+PzJNr72eBc201qOYjaT5/XvDVEslHjic73oDEosNi09fTUoNXKWFsIIqTxD111Ew2nqm00cf6xzi0TsEiHvdYZGr2K31SHZwgHjk6KuuYqgL8HSXIhkIoveoOTNHwwzO+5Hq1dw8FQHPxlYJpcv8S9e2s1Lj3RwcGc12VAa72KE8cFK9s/q0CEIwifenBy1eqZGvTjnw7R12+5J6t4MhUKRq+fmV7l0pWKZrh0OTj7Vza799Thq9YwPeQn6k+zcX/eJy5AfvjNNMp7l5JNdq5mkO8dur9YxNuDB46zoy3U3VzEyG2R0IUw6lKa90cSTL25civ443ri0yOBckBM7qjEUyyzOhnDOh6hvrkKhlFIulzn71hTZTIGTT3VtaLyezxd555UxRFHgkae33TPLaNYrOX3dSSSR46FNJEc0GgVlyugMKuZuKS+VimU6euw89eIOHLWGNfO9rslEIl5xSVjxxFYD/l82/CoAW4tfygAslcohUalQ9/QQvXgBgEIwQPTcWdLjYxTCYawvvIiyab3UwZ0QBAG5RIZVpcemkjHov0apMMzv7XmQPquRGo1yNdCQKYzYFCLNsdeQSWW4SmZGw0nGwxUBT5NcetcNIhOfY2X2W2Tis0gVVVhaXqSr9kGu+/qZCE2z27YDrXxj7aN7TVqLveJjNzPuQ+23saezgy/ueZZabTXSDbSjJDItcf8VyqUCWvPmGll3YjyS5Io/yh6Lnl3mjctotyFXSKlrMjE95mN20o9EIrI4G2R80MPA1SWunJ3n6rl5RvvdjA14uHlpickhD875MAFfHEVew7R7CfVSNbWNRnbsW89VK5VLvOf8kD8f+WuiuRhHavbz6x2fQZL6gEJBRCYroKmRkDQ9iGp5Ent8lt2P7KTnsb0szYVYmg2hkpaQzwyw8s2/JPT6qxTjcSSdBsR2KXr7EUx1jyN8LMtZFiyM3Fzh4jmYmQiTyxbo6HGw90gjxio1EolIOJjC703gWzGw5KxmbDBMIV/EYt/8tH4bypZWouc+IDY6hv7YA4iyyiYjyvSMDbi4dLGKeDRPa5eVh57qpu9wI/sfaGbf0WZ27qtn++4aOnsd7NhbR5VVQy5bwO2MsjAdZPjGMpFgxUxYKhN5+gu7VrNjsZULZGLT6KwHUOpbyae9ZONzxP1XSdwcJDe0CIJAIRhAd+gwCr2OfV02Euk8g7NBPhhY5sKwl1Qmz8k9tfzj53bQ2WBC3OCdOPvWFF5XjL1Hm2jf9lHpUxAE7NV6jj3UwTs3nZAtIFNIefblXev8KDdCNrmMb+Z7/OmZPO+OG/F65+nbtnEZ/NOAIAg0tVlwzlfm0+2uuK4dDk4+vY2vn5liJZzmCw+3c+DWOOVyKW3dNgwmFa6FMHOTARZnQ/iWY7idUTyuKOFgkkQsQzpVyYDei/cjkYroDEpmxlYIB5J09Njve8x+b5w3vjfE/FQQlUZO3+FGHvpMN23dttU5IgiVTI3bGcFeq99y88+dCAeSXDk7T32ziZ47gpM71zjZrbV0YSZIsVjGZFbj7HeznC0QFwW+9LkdGLeg/h+IpvmTV0fRqWT8zud20rOrhkQsy9JciKlRLy2dVqLhNDcvLdHcYaVrx8Y6caP9buYmA+w8UE9j671LrxKJyII3zrQryv5uG7oNMtC3x2u2aRFFAVEUiEUyFAslevbUrvMbFQSBxtZKwO+cDxMOpmjptP7c5vbPC78KwNbilzYAA5AajMgdDhLXriLq9UhUKvI+L1JTFY6v/ca6zfNusKmUJLJzTIT6sWks1G+gnC5X2REpY0pcokeVAF0n07EM/cE4I6EE6WIJg0y6SuaHCgk75PopkeXTlItZ9LbDmJufR6aoQiJKqFKauO4bwJ8OsM++e8MXaiuTNqmM8F74PQyhatJOCS2dlk25AqJESTo2TS7pQmvdhyje+8T8owUf0VyBF1vsaGX33gzVGjm2aj3Toz6c82G8riihQJJ0Mn/rMx11TSbsNQZkcgmpVJ6AL4FvOYZrNoIxVPn9k80uhjL9DAfGGQ1OMh6aYjI0w9uL73HBfRWNTMOv97zMww3HiS6/RSHjR219ColUghQn1dtqMR98msSN68SvXkZuNNDUZka4fAbtpVdJD/VTTMRR9XQgHlQh2amjqv5xDI61BuKpRJZr5xd5/6eLrPgNQJmuXhWPPr+Pzh4HJouG2kYTnT0OuraVMMjfxVQlYLS1EQ1XmhNG+z2USiUsdu2mJQSJSoUgiiQG+inn8mh6d5BKZDnz6gSTEzIkkiKHj2s59NAuNDoFcsXG5HdRFKiyair30+tArpAQCaXwOKOUSmUeeWY7jlu+e8V8ksDCDxElCqwtn0elb0Nn3Y9UUUUhFyH1xhAki8gP1VF0xcjmlynbchQyK3TXCiiVCsaW0nQ1GPknz+/g6I6adZpJtzE/5efK2XmsDh0nnuza8BRvMippqZPw3nyQiXgBqRS6Gjcv+xQLKSKutwm73uSno1ZGvDakYglXWIbTu0JfV83PLVsgkVQyvnOTAURJJUOy60A93zg9yeh8iKO91Tz3MT9LQRAw27R09NiJhtO4lyIEVhK4FsK4FsIszgSZGfczOexl6LoLgJp6w103W6NZjd8bxzkfxlCl3rKAc6lU4sbFxUrJNJmnZ08tjz/fQ22jaUOvS7lcwsSQF1Ei0txx/zywgStOvMsxDhxvocr60YHz42uczaFjesyHayHM9JiPbDxHW0sV86EUi74Eh3sdGwb3d+Iv35rEtZLgS6c6aKkxILl1zwqljPmpACueOIlYhoAvweGH2jZsYigWSrzzyijlcplHntm2YYZsIxSKJW5OBTDpFHTUr+/CvXO8NfVGOnocqw0k+XxxQ8cGQRBobrfgcUZxzodIp/I0tlb9UgVhvwrA1uKXu6UC0O3dT/Yzy4ReewV5WzvGEw+jau9AuGWWXS4USE1OkLh5g8RAP4raWmr/2X+zYXB2rPYQZ5bOctZ1gYOOjQ2Q9Y4HyGdDEB7mhPIiB7uf5Jw3wmQkyTvLQd5ZDlKvUdJrlNNcnqEcukKpkECmsmNu+Mw6OYsdlu10V3UwHppiKDDKTuvWO+xuo1Qu8d2pnxCt8vBYw0OMvhfizCvjPPeVPZtu9GpjN7mUm3R0Cq357gKfC/E0i4kMnQY1dtXWSzp1TSae/+oeAitJ9AYleqMStVax6WaYzeQJB1KEgkmG5qeZDs/hk05QXtm4UaTXso0vdr2ATq4lm3SRjowjV9dird9FubQd75SfuP8K8sZa6v/lf4frP/7vrPxNxZzBDqSlWlbMXez68m7SmfcRUWFpeh61ca3dVDKR5YffuEnyluDs7gN2TPIfo1ApUGv2rvnbUilPZPkNdLo0bX0PoNDUks8VGLnpZuDKEtc+XGDomoud++vp7avdkMxrfPgUiUvnibz/LuGmPi5eDZBJF6ht0NLZfAajyY4gbO6r+XHoDEr2HWum70gTy4thSqXyGjJ7zHeecimHsfrEKidQEKVozTuRRDQVY/gOO0KvDK4LpPunKPWkV9+PnTroPCnBYGrBat5cDiGdyvHBW1NIJAIPPdWFRCJSKqTJptzkMyvk037ymRVcQwFKxRyf75Xx9Ss7eeXCErLMTY702FHqW5CraxEEkXK5TDI0QGT5DKVimuGVVi4vVlNtVvNPnq7lj39ynf5Z+E8/HOK3nu3dNChcc4/ZAlKJeNfuw49DrVXw0i3ytkQq8taVJS6P+mit0fPlRzcvnWq0Ch5/vndVN0yllON1R0mn82TTedLpPDNjK1w/v0AuW+DwydZNryUIAkcfaWd58RoX352hsbXqnhy4cDDFe6+Ps+KJo9HJOfFE1z35TfZaPRqdnPmpAMXHSvclBl0qlZga8aFQSmlqv3szhUQqcuhEK2//eLRi3/RwGz19taRfHeXq+ApvXFzk6aObVzhG5oNcn1ihtUbPoZ6PutcFQWDHvjp8nhgzYyv4vXG0esUavbA7MTHsJRnPsXN/3X2R33e0WhAFgZtTAZ481LSl7xw43szSfIjh68s0tVk2vCepTMLjL/TwyrcGGOt3o1LL2H/s7pWeX+FvL36pM2C3oeroJLfsIjU6gsxmR3/0GMmRYUJvvo7vm39B7NxZsosLlPM58isryKurN9QQU8tUuBIepsKzdJs7MCnXn1wEQUClbyebWCQTn0EvE9nfuINDNgMWpYxsPsVSMs90PMf1uAp3sYqUpodi1RHyQuVUKhfF1dObIAg06uo4777CfHSRIzUHV7lat3GvU8MlzzU+XL5En20nn939CMl4Jc1eOUltvKCKUg2JwDUol9FUbR70lctlvjfnJZor8EKzHeMm1jubQa1VYLFr0RmUyBV3L9NKpRUOk9Who6eriadOHuCg9QAn6o9yvO4ID9Qe5EjtAQ5V7+N43RFO1B1FIVVQLpcJLv6EYi6KufFZZAoTgihBqWsmGRokHZtEW78Xw75jpOdmUbW0Yn3pi0R3PkSQAFXG64iiDFvrF9Z5LubzRV7/7hCRUIo9hxt47NkeapssQIZMfAZRolwj5xF1v086NoXOehCtZTdQyZJU1xnYvrsGmVyCbznG0myI8UE3xWKJWCSNzx3D44riXoqw7IwRNzYxHVUz6pFSBo6cbOXYqU5K2QWyiUXUpp77FggWBAGDSbWmdFTIRQguvoJEbsDc+MwaeQyAwA++R27ZRc3XfhvLzufIr6yQm13CvO9pdC0HUOiaUWjqkIpFsok5UpFJlLqWdfdWLpd59/UJAt4Eh0600thmJhnsZ2X2WyRDA2Tic+TTXoqFJEq1FbmmCZOlm65akZtzRUaW1VgkIyjSl4n7r5BLLhP3XyERuA6CSFT6IN+8oEYpl/Ivv7Abu9VCt2WJBU+MCTfMLEfZ02HdNLDyBJN8590Z/vS1UV6/uMC5QTc3Jv2ML4ZZ8MZZiaRJpPKolbINAzlRUuk6HZkL8vU3xzFo5fyLl3aj2QIfSyqVoFTJqK4xIFNKsNi1OGoN1DWZaOmy4pwPsTgTJBHP0thq3vQdUihlFd/K6SDZbJGmto2DnHK5zMiNZU7/ZJR4LEvHdjtPvNBL1RZ0pgRBIB7L4HFG77sMeZuG0L3DQXP7WhL/Rmuc0axGqZaxY18d7dsrZdXuJhNXxnwMzgTZ1ly1xog8lszx4ZCbb5+Z5s3LSwjAbz/XS9UG8ip1jUbGBjwU8iVaOq20bNBUUCyWeOeVMYqFIo98dvuWyuC3IZdJmHRGmHZFeWBnzTott43GK0pE7DU6JoY8uBYjdO1wbEhZkEolNLdbmJ8KsDAdJBHLUNdouq9g+L8UfpUBW4u/EwGYIAhoeneSGBokNTxI+J23iV+6QNa5hKiuEPatL7xI1RNPETn7PpmFeQzHT2yoIaaTa7jivUGumGO3bceGN1AxR+4gHZ0gHZ1ElKoopl0oAm/TnL3KNmEGg0ykIDWxXNCxnJMzGU3RH4xzcSXCWU+IG8EYk5EkiUKRZr2JYjnHaHACiSihw7TWruRukzaZT/Gfh/8SQRD4Rzt/DaVUSW2jiblJP4uzIew1ulWRwDshkapJRcbJppbRWQ9s6jM4FU1x1humy6jhePXdT8efNgw6NYVMGaVUiVqmQivXoJfrMCoM6OW61Y0oE5sh5juPUt+OwXFs9fsSqRqZ0kIqPEwmNoe+/gimBx9Gt+8AMqsVpTiMUXWDXF6G03eMlu071mxu5XKZM6+Os7wYpqvXwZGH21a5GQp1NfHgTXLJJbTmPQiijFzKQ3DpVSRyI5bmF9Z0EVbuR6Sm3sj23TVIZSJeVxTnXJiF6eAtcnCY5cUI7qUInkCOlNyILhPg1ANW2g523bo3kXR0AlEiR6lr+Zl/47DrbfJpD1V1jyFXr+XAFCJhfN/8S+TVNVg+93kEQUSi0RG7cB5Roqbq8GMo1DUotY1oqnbcau6YIhkeQq5yIFN8NF+mx1a4eWmJ6joDh0/YCS3+kLj/CoIoRW87iM56AEP1cUy1p2jqOgHyVpTaRizWZtrrzVwa9TGxYmdHqw2NNEEu5aKYj6M2bkNme47/57UA6VyR33mul5Zbrf9qXT1NsnfxxaVMuEUml8L0dVqR37GpuQNJvn1mmr86PYlzJUG1WU2NRUMmV8QdSOH0J5h2RRmcCXJp1Mfpa05mlqMUiiUsBuWaa/nCKf7jdwcpl8v88w28M++Fjd5zuUJKa5eV5cUwS7MhIsEUTe2b63DZqnXMTflxzoUoFooszYWZm/QzPbrC5LCH0X43/ZeXmB5bQa6QcPKpLvqONN2XfIVMLmViyLta0tsqLn8wRySY4oFHO9YZl280dkEQsNes1TeTSyU02nVcGPYwvhhmb5eN/mk/339/lr8+PcXQXJBIIsv2JhOff6id7k1K11KphKkRX8WxIJ2ne0f1umrB1KiPyWEv23fX0tZt2/I4byOTKzI8F8RmUtFcvZY3u9martEpKAOLM0GSiRxyk4pLo16UMgk6tWx1fZLJpTS1mfE4oyzNhZib9OOoNdzVEP6/JJzzIa6dn6ehyUyxVLr3F35G5LIFblxaZHbCTzScJpPJI4rCKr/wbggHknicUYxm9c9c3s0Xirx2YYG+bsff3QAMQJBK0fTuIHHjOqJSgeHoA1hffAnr57+AducuZBYrEq2WYipFamQYiUaDqrVt3XWqlCYG/CPMROc5XLMP5SbSAaIoQ6lrJRUeJh2dIBOfo1TKoanqxd5wis66vex3WDlgM7DNqKVZp8KhVmCUS5FLRJKFIt50jplYiksrEazqOgLJMabC0+yz70Yt+2jRuVsA9sOZ15iNzPN062NsM1f0riQSEUetgYlhL865EB09jo11rwoJsokFZCoHctX6BaZULvOdWQ/JQpGXW6u3xP36NLGV01K5XCIw/wNKhSSW5s8hka09xcuUFsrlAunYFPmMH7VpOwAR9xlivg+RyPSMzRxgeqKIRCpSfQdf4+q5ecYGPFTXGzj12e1rdMgEUYYApGMVOxiFrgn/3HcpFeJYm15Aptp8Y5JIRWoaKoGYyayhqd1MW7eN9m12OnsddO2o5siDbTTaRMxn/hxheQHj8RMIoohUUUU8cI1CJlAJnH+GBSKXXiHsfAOZ0oap/vF11wq99VPSkxOYP/s8qqZmisUScouF+OVLZBbmMZ58eNW7spIZbkWqMJGKTJAKDSGIUuSaepKJHG9+fxhBLHPqCYi6fkAhG0Cpb8PW+kXUxm5kKmvFUkwQ1z13s0GJw6zh8tgK4141Jx/4DJbqPWjNfShNffzhD8fxBFO8eKKNw70fBZGCKEWu0NMoP0e8YGHMVWJkLkRfh5VANM23zkzx16encPmT1Fm1fOlUB1881cGxHTU8sq+eJw83cmxHNXs6rHQ1mKi3aUnnikw7owxMBzh91cmcO0axVEarkvF/fX+QcDzL1x7vZtcn0MnabL7LZBLaum14lyubrd8bp7nDsin3z2zVMDHsxeuK4VuO4fcmCAWSRMNpErEspVKZpjYzT7zQi30Tnaq7QatTMD7oIRRIsmPf1roh06kc596aosqiYd+xpnVz7X4yIxaDikKxxOBMkNPXnNycCrASSdNUrePxA4382hPdnNxTR7V58wA4HEhy7fwCOoOSRCxLKplbE0yWSmXeeXWMfLbII89s+0QCqEatnNPXnBSKJQ73rD3c3G28jlo9S3MhnHMhLk77OT/p5/3+ZS6OeAnGMsikIiadApVKTlevoyJRMRtiYtiLTC7BXqP/W8ULi0czvPrtAfyeBKP9y1TXG9DoPp1AMZ8rIIrC6njL5TKzE37e/MEwS7ckYpzzIabHKo4f/ZeXmBlfwbUQZsUTJxxMkYxnyeWKCAIszYZ48/vDFakTmxbTfR6iPo4P+t384INZXn606+92AAYgUasxPnIK08On0PT0Iqtan65XNjUTPfs+6elpDA88iChfW9cXhMrDHA6MoZAo1mWj1vx/UjVyTT2FXBSddT/mxs+iqepFKv+IMCuXiBgVMqrVClr0arabtOy1GjjmMHHIbkQtlbCSzjGfyFEoK8nm51iMBzhYvWv1Gpu9rIsxJ9+Z/DEOjZ2vdL+IeEf5SKNVIJNJmJ8KEAokad9mW/dbiFIVicANBATUpvXcnaFQgsv+KLuqdBy4h6H1zwNbaj4IDZEM3kRTtROdpW/Dv1Fom8gmnGTiswCkQsMkAteRKizY279CfWszM+MrzE8FsDl0GKvUTAx7ufTeLAaTis+8tHPD8oNMXU0yNEg2sUipmCYdnUBTtRO9/dCWxieVVspNFrsOs7Xyshur1OiNKqprjUi0akrxeOXAoFajam1DECQUc1GyiYVK6U9uolQqU8gXyeUKFe5QKodMLrnnxhhyvkYhG8Tc8BlkyrUBQymfx/v//WcEqQzHr/8m4yMr/OibN5mfDqBVgMw9i9RsRdXUtOZ7cpUdpa6VTGyGdHSCaMDD5Q8LZFIRTpxYopTuRxCkVNU/gbHmkQ210TZ67rUWDUq5hBuTfkbnQxze0YhCqeWbb08yMBPk4HY7L55Y3/EoVVrIp5Zp0Y1RVHQyspDi/LCHt686WQ4kabBr+fKjnbz0cDu1Vu2a74uCgFopw2JQ0WDX0dVo4sFdtRzabseglRNP55lyRumfDnD6mpNEOs/De+u2zPnZyrhvQyIVaeu2EVipyF54nFGaO6xINyip6gxKmtrMtHbZ6O2rZef+OvYcamTfsSb2P9BM3+FG2rptm9pG3QuCIBCPZnA7ozjqDFtS4B/rd7M0F2L3oYbV5o87cb+lqY56I3OeGFKJwEN9dXztsS6eONREa60B5RbG1X95Cd9yjAcebScerTTJVFnUVN3acGcn/IwNeOjaUU1nzydzQFEppAzOBJhzx3ior25NtvRu4xVFgeo6A6MDHmTZAuYGI03Velz+BJPOCBeGvbx/cxl3IIlCLqGvrw57TcUV4XZzQV2TacND923czV+yUChSKpbXdWJ+EpRKZd764QjRcJqWTgs+T5zpER8ms/pnDm4CvgTf/fo1XAthmtvNJONZzrw6Tv9lJ6Viib1Hmjh8spXaRhNmqwaNVo4oisQiGYIrSXzLMZxzIWYn/IwPehi86mJu0k/plt+w2xlh266aT6y5Vi6X+fob46SzBV461fl3PwCDjwKozSDK5SCKJAcHoFxCs309/8mhsXFu+RKuhJsH646sCWw+DqncgNa8E4WmbkvdhHdCJoo06lQctBupUStIFfUE0ouE0ov0h1QYFVU41IoNX9ZSucSfDf8VkVyU3+j5Ilb1+hO3vUaPzx3DOR9GrpCuW/hEqYZUeIRc2oPedmgN/6dYKvOtWQ/ZUomX26pRf4oK27dRKBQpFsubchfutSiXSwUC89+nXC5gbXkRUbJxtrKSnWkjFR4lE5sin/YiV9dga/8yUpkOmVxCdb3hlr1MAK1eyQdvTiKTS3n6C7vQbdLyLgiSSkdpdIJcahlRqsHa8tJ9z4O7jV3Z3FKRV5mcqMhSKBTE4wKF1Ah+1wzv/jTAhfd89F9eYuCKk6FrLoZvLDM76adju23T0lI2sUTE/S4KTQOGmpPr3pn4lcvEr1zCePJh0rYW3v7xKBKpSCaVx5eUUh8dwzPtZiBpJ5PKI5EK+L0JZsZWGB2MMjVlQKsOo1J40CiXaW91IRUjKHWt2NpeRqlbnwX5+Ng/jtYaPalMgcHZIHPuGMlMgTcvL9Fo1/E7z/VuqMgvCAJyTR3J4A3aTF7kxj7GFyM0OXR85dEuPn+yjRqL5r4yBhqVjI56Iw/uruXgNjsGjZxUpkB7nYGvPt51z+68Ta97j/kuSkRau6xEw6lKhmQ+hK1ah1ojX59R0irQG1VodBUh3tvdsp9WZkQqlzA57EUiETY0Jb8T5XKZs2/fXWvrfgMwURQ43OPgob46uhpMaO9D+6xYLPHe6xNIZSIPPt5FbaOJiWEPS3Mh2rfZkMklnHl1nEw6zyPPbP/EumoA8VSesYUwdRYt9Xd0pt5rvHKllHduuNAWyjQYVbz8XA+PHWiko86AQi5lJZxi2hXl0qiPGouGbe1WOnochPwVmYqpUS8ms4ZCvojHFWNxJsjUiJehay6unV/g0nuzzE8FSCayyBVS1Lc01SaGvLzyrQEGr7mIhNLI5BVe7iedN/2Xl5gYrthXPfrsdto67YwNuZkeXUEqFXHUfrJsXaFQ5PXvDZGM54hHM0wMeRm85iIaqugGPvG5Xlo6rWi0CqqsGmoajLR0Wtm2q4bdBxvYtruGlk4rDS1VWOxaEvEs2XQBUSKgVMko5EsU8iXi0QytXZ9MdHh8Mczpa04ObLPzwO66vx8B2FagaGwkdvki6fFx9AcPIVGvjcSlooR4LsFkeAa72kqtdmN9mE8LoiBgU8npsxqo1tRwc+U66byPqUQdKomELrth3ct60X2V8+7L7LXv4uGG4xteVxAE6pqrmBrxsjgTpLHVvIYjIAgChVyMbGIRuaZmTRbkuj9GfzDOfqsBS7zA2bcmkUjFNa3j94NSqUw4kGJxNsjYgIdr5+e5cGaWsUE3nb2OT7Qox1eukI6OobMdRHMrg5fPFRgf9OBeiuL3xQn6b5VfIgVypTrC/hUUmhpquj6PRHpHmVenQKurCNouTAdAEHjijnoAACAASURBVG6VaO6ueSZT2UlFxigVUlQ1PL1lYdt74fbYRbkcQS4n2X+TUiaDW+Lg7Z8sIIoF7LYQ9XU+LNYScnU9JosBi0OLWiNfTa+3da/PfFaaFn5MMR/D0vQcUoVh3ee+b/w5xVgU81d+gzdemSaTLvDY8z088GgHtkYr6alpNJFlJvMO5pZSjA14mB5bwb0UIRJKI0rklMQ2tLoSWpUPiVRWyXrVbpz12mjsH4cgCGxvrsJ1SwB2dD6EXi3jX768G+1dOtQkUhWUy2Ti03Q3aHj02AM8ur+eavP9BV4bQXtHMLav2/6Jgy/YWhAi3lKhTyVyt7THPEwMe4lHMkikIlr91oWhfxZo9QrGBj2E/HcvQ6aSOQavOJmd8NPUbqF7E62tXyQ5e37Kz+SIj227a2hsM6NSy1CqZMxN+gmuJJDLpYzcWKZju53unT/b2q9RyXj/5jKCAPu7P9K8u9d4Lwx5eG98hQatgpg/ycJ0gJp6A031Rna2WXhkXz1dDSYuj/mYc8d4cHctSqWU9u0Vc/PFmSBToz7GBjzMTvhxLYTxexPEoxmkMhGDSUUokMS9FGFswMPYLbP7iWEvMpkEhVKKxxllasTHxJCHVDKHWiNfDdS2ghVPjHdfm0CtkfPkizuQySQ0NFVhcehYnA0yPxUgEc/S0FJ13zIxl96bq+xpbWbSyRzZTAGAwydbOXaqHaVq8/sUBAG5XIpWr0ShkHL9/AIhfxJHnZ7nvtLH3qNNCKKAeylCKJBErpBsmLW9F77z7jTeUIqvPtZFnUP/qwDsNgSJBIlOR+L6NYrxOLq+vev+xqa2cNZ1kUi2IvL5i4JDYySRS7AQm0EuwnRcj0QUqFV+NKES+SR/OvQNREHgH+742qY8NQCZXEKVVcPUiA/3UoSu3uo1GSdRIicZrJSFbssv5EslvjXjgUyB2ukY188tEI9mmJ/yY63WbbnzqVwuMzbg4dL7s1w4M8PQdRcL00H83jiZdB6dscK/yGYKNG1wir7bIlUqZAgsfB9EKZbmzyGKMtxLEd743hDTo5Ua/9JcpXtsfirA3KSf+ekEy24rszM6Rm56cS2EiQRT5HMFZDIJZpuG0X4PxUIJi03LwQdb7rmZCYKA8lYnoNq0/VPb/O4cu7Khkfj1ayTHRriyrKGs0rD7yFGqm3vJpTwoJG5sFift2+vp2tVL+3b7KsFfKpNQ/TF7lUxsmtjKRVSGDvT2I+v+78zsDKE3XkOzew83Ew48rhi7D9bTs6cWiUTEYFKj1CpI3LxB974mqg/1odLIaW63sGt/PYdOtrLvaDPt26sx1/Sg1DZiqD6OUtu4pd/nbs9dEAR2tVmYWIoQS+X5p5/bSd0WNK8UmjpSkVEysVmqrN1I5bp7fucXja0GIYIg0NhmxmLXIogCIX+FNDw54mP05jLhYAoAnV5x32WkRCxDKplDobw7WVkQBOKRSjdkdf3aMmS5XMa9FOHyB3OcfWuK5aUIMrmE4491ot2E+/OLCsBSiSxv/3iMfK7Ig090rkpLWB1aArdETpfmKi4Ajzyz7Wf2XdSpZFwZ87HkS3BqX/3q2nu38RaKJf7oxyPkCyV+6yt9CKUSS3MhJoa8QEUKRCKKWIwqUpkCw3Mh1AopbXUV6ouj1kBjq5l8vkh1vYH2bhvbd9ey53ADh060sudQI9t317Bjbx1Wh5ZCoUTQlyCTrgQxglhp5qiuN6LSyImF0ywvRRjtdzM/6UcQhcrcu8v8yOcKvP7dITLpPI8917N6cNdoFCBA2zYb7qUoS7MhPK4oTW3mDXXnNoJrIcSHp6dRqqQEV5KUSmXsNToS8Rx+b5yaBtOm8+xO+L1xXv32AJFQms4eO49+tmd13tc0GKFcxu2MVuyhFBLs9xGEBaJp/vr0FC1WDbKVJLv2NfwqALsT8ppakoMDpMZG0ezYidS4VnNFLVOzGHMxFZmlx9yFUXH/EfAnRbOhkcve68SzSxSL80wGi5TQ06pXU6bMtyZ+yGLcyTOtj68S7+8Gg0m9KvKXSubWiPdJZDqSwX7ymRV0toMIgsj55RDOQR+W4RDRQApHrZ59x5pYmq90VNU13XuCl8tlLr0/y9Vz88SjGQwmFY2tZrbtqmbf0SaOPtxOb18t81MBnHMhGlqq1l3zbotU1HuWTHweY/VxpKpGLr0/y7m3p8llC+w6UM+uAw00d1hoajfT0FpFQ3MVtY0mqusNqDVyspk8fm8CjyvKzLi/Urq7vkw+X0StlRMNpzcMXjaCRKpGrrq3+nipVCYaTuNxRpibDDB6083QdSfRUBqlSoZK81GX051jTybzDE4mMa1MYhCSHP7HL1Jdb0Qq16M170YiVZOJz1eaQWIzyNUOmjubmBmrlFRrGozoDMpbz+V200LqVtPC+oxm4PvfJedeJn3wCfrHEjhq9Zx8qnvNKVVmtRF5/12Kfh/tX3yO5g4rNQ1GjFXqNXw5QRCQKkxb8hy9jXttxhKJyOFeByd2126501AQxIqXZ3iIXNqLxrzrF5Ipuh/cTxAiCAIms4aWTis799dTXV8RNI6G03hdUWbGVxi67sLvjVMqltDqFZuWo6PhFOODHi6cmeHS+3OM3FhmYthLJJiiVCyj0Sk25MHIZLfKkFKRpnYLmXSe0X437705wdA1F+FACpNFw96jTZx4ouuuXLFfRABWLJR48/vDhAMpDhxvpqXzo9KSIAjUNZmYGvGRzRRo7bLSs6f2Z/4/BUEgHM8ysRShpcaAw1w5vN5tvGcH3Vwe83Gyr5aDPQ6a2izYa/QsL1Y6ppfmgjhqDZVDT42ecwNuJp0RHthZjeJWEKPRKmjptNLYasZRa8BkVqPWyNccviVSkYAvwfANF6VimeYOC3WNJlLJHCueBAFfglg4TbFYRq2Vo1BKiUXSLMwE8S7HqG0wbmpK/uHpaVwLYXbur2P77lpikTTjgx6UShmiVECuqGTrwsFUhbs2HaC6zoD6Hl2cmXSe174zSD5folAoodHK+cwXdrL3aDManZy5CT/TYz4sdu2GiYJyuUwklGJy2Md7r4+TzRQ4dKKFgyda1x1WahtNrHhiRMNpnPNhMqk89c2mLa0bb15eYtoVZbdGid8V4/ijf084YFuFIAjI7Q5iFy+Q8/nQHz6y7ofVyjRc9d0kXyqw6xMIpH5SyCUy9tp3kS3mcMbmyRVmmY1M4U3LuO59n37/EA26Wl7ueuGu/LQ7UdtgZHEmyNJciMGrTtxLEWKRDOUyyOVZ8qlFlJpGllxFzr86gXoljVIp49ijHRx9uA2rQ0eVVcP0qI/5qQDNHZZNuRGlUplzb08xctON0azmha/10Xe4keYOC7ZqPRqdYrVzpcqiYXLYS8CXoGtH9ZpnsNkiVcjFCC78GIlMQ176EG9+f4SluRDGKhVPfG4HXTuqMZnVVFk1WGxarA4dtho9jjoDNQ1GWrus7NhbR29fLXVNJozmStCQyxVobDNz6pltzI6vsDAdwFGnR2+8N8n44yiXK8HW7ISf4esublxc5OJ7swxdczEz7md5sZLeTsSyeF1RxgbczEz4yaTzqDUyzBYtqVSO5cUwr39nkJW0gmppDE1oEWNXO3JHpTQiCAIKTS1a8y6K+QSZ+CzJYD/FrJOGhiga5TJR/yRyiYd82kkqMkYmPrtp00I+FML3V3+JxFbN2XgLcoWUp7+wc92zFqRS8oEA6ckJVG3tyG3336a/GbZUihMEFHchGW8EqcJEPhMgE58Dyih1f7sELD9pECKKFX23xjYzO/fV0dBqRqmSkkzk8LpizE8FGLzqwuOMks8VUWsVJOJZRm+6Of/ONFfPLeBaCJNO5qhrMmF16IgEU3hdMWYn/AxedbK8ECaVzJHPFys6dvMh/J4YgZUkAV+CqVEfVz+cZ2kuRCFXpH27nQdOdXDgeDP2Gv2GzQKfxti3inK5zLnT0yxMB2nrtnLkofUNGzKZBKtDSyiQ5Ogj7T9z9us2FHIJHw55QIC9nZX3ZLPx5gtF/ugnI5RKZX7rsz2rDQUGk4quHY5K6XkuzPiQB4lEpK7BhFwqoX86QD5fYkfr3QVub6NQKPLh6WmunptHIhV5+DPd7D/WTGOrmR1769i+q5rqOiM6oxKJpNJ0kblljSWRikRDaSaGPGh0CszWtaX8uUk/lz+Yw2zT8MjT2xFFgbd+NMr4oIf+K0uM9rsJBVIICOzcVwdUtOsmhryUimUcdYYNS5Llcpl3XxvH700AUHXLkP02md/q0GG2aZmd9DMztoJOr8Ri1xKLpJmbDDB4zcn5d2bov+ysmMpLRR59dvu6fedO1DebGB9wUyyWWfHE8XviNLWZ70rMzxeK/NlrY1gEAUU8R22jkT0HGjcMwIRyeWOV8b/FKPv98U/tYst/+H+SHBqk5nf+GdqdaxXhS+USf3DlPxBMh/iDI7+LbguGyp82fCk/P3W+y7XlmwCIgoEatYZ/uucfrJGq2AoSsQw3Li7icUZXyxQAggB6XQyVRoPXI6EMVHWaefbx9SbYYwNuzr41hc6g5Lkv7153YqkQXMeZGfdjsWt56vM77rmQnXl1jOmxFY4/1sG2XR9xqKxWHR9/1uVyCf/s35CMLLLkO8nYcGUR27m/jv3Hmrecxr4XvMtRXvmbAeQKCc9/tW9LQVg8mmF5saLltbwUJhn/aIGVSARMFg1VFg0mSyU4rLJoUKnlLM1VrGcWZ4MUCxWNHHuNniqrhokhD4IgcPhkKx01Aou//6+RWaw0/dt/t+r2cCcy8QXCrrfIZ1Y2vU9BkFK97beRytdn9wI//iGhN15joek4s9JmHn+hh6ZNJBXSszM4/5c/QLf/ANX/1T+65++zVWz03D8tFPNJvFNfp5iLYKp7DJ31F0cvuBd+HuMOB5LMTQWYnwrg966/tigRqG8y0dJppan9o0NVqVRmxRNblUNY8dz9vmRyEWOVelVK5X6J6z/PZw4wcnOZD09PY7Fr+eyXdm/ZUujTQKlc5vf+7AreUIrnHmjhqcNNm473netOvn1mmscONPDiifUySQDz0wHOvjVJOpnHYtdiq9ZxYWKFaLbAy491Ul9jQKOrNF5kMwWS8SyJWJZEPEPi1r997hjRUBqLTcupZ7dtqBW5ZgylMuFgkpsXKzIOnT125qYC5HNFmjssHH+sA5VaTjKe5Xt/fo18vsQLX+ujyqLB547xo2/exFato6bOyOSod9XnVBSFWyVsNYuzQZLxLFVWDSee6MT2Me20kZsuPjw9A0BNg5HHntu+oduDxxXlze8Pk8sW0OoVJGLZ1c9Uahm1jSZqG40VTvQWSpUTw17ef2MCpVpGJpWnyqrhkae3bcqHvjDs4RtvjLNHIkUiwud/Yx+t7bYNI7y/9wFY1r3M4v/4e8gd1TT+/v+0Tpz1A9cFvj/1Ck81P8rjzQ99av/v/aCsyvJ77/4h8ZxAsVTZWPfb+/jyts9tOQP2caRTObzLMbyuKB5nlBVPhHJZJGeQk9lWxX99tAP5JvyR6+cXuHZ+AYtNyzNf3LWahi7ki5z+ySiLsyEcdQaeeKF3S/o5yXiWb//ZVURR4OV/cGB18d5okYp6zuKavkb/8C7icSkGk4oTT3ZtqVR4vxjtd3Pu7Sksdi3Pfmn3uuCuVCrjdUVvid4GiUUyq58pVTJqG43UNhqpqTdiqFLfk2iayxZYmAkyM7aCc6HCQ1Fr5Zz67PbV8a1866+JvHcG64svYTr12KbXKpeLlEt5SsUc594ew70UoKvHQs9uGxK5DplyfWdPKZ9j/r/95+SyBc7Vv0DvwWYOn9xchqVcLrPwr/97CoEALf/h/0ai+dnaym/j570Z57MhfFN/QamQxNz43F2dIH6R+HmPOxHLMD8dYHEmiEwuobnDSlObedMy0p1Ip3I458PEImnUGjkqjRyNVk4skuadV8bZtqua44/dmw6xGX6eY19eDPP6d4eQK6W88NW+1XL8LxL+SJp//62bBGNZnnughV97pnfdeLP5Iv/qTy6RzRf59//w0IYm3reRSef58PQ0M+N3O2jB3bZ3qUXNnmNN9DSbt5xNTsQy/M2fXEFvVPL4C7188OYkHlcUlVrG8cc6GLnpxrUQ5tgj7fT0VUq4b/1ohPmpAJ95aSe79zWwshLD742zMBNkaTa4mtGSySv80oAvgSDAroMN7D3SiFQqwe2M8Mq3BqAMTe1mTn12+12V/0P+JG/9aIR0Kk9tg/HWWmzCZLl/cdVyucyr3x7EvRShvqUK51wIURTYe6SRXQcb1txHuVzm337jOlJvgioEjj7SRm9fHVar7lcB2GbwffMviJ47i+3LX8N4/ME1n2UKGX73wr9DKkrpNLWRKWbJFLJki1kyxSzZQpYSJdoMzWy3dLH9U+aLLcVc/MnwXxDNxjlRf5LFpJGFyDlKpQBNxiP0WA+jk0nRy6To5FL0MgkGuRTpfRiRA/jmXuMdp8iYqp3PNNo4dBfdr9vp/LF+N7WNRp783A6KxRI//cEwbmeU+mYTjz7Xc1+nzIErTi69P7tmIf/4opyJzTFx/VWu9/eQz0vp3VvLgeMtP7fTbLlc5oOfTjIx5KWjx87JJ7tuEYyjzE76mZ/0r57k5AoJNQ1Gahsqp6sq68/WYafVKBgddGOr0a3JIBYTCeb/h38F5RJN//P/hlR39y5NqAR2P/jGDaKhNI8+u32V+1IulymEQuQ8bnIeN+mpKRL9N1gw9pLYcYJnvrjrnvYmoTdfJ/CjH2D70lcwPnjyE4/3Tvy8AxGAXMqLb/oblEt5rK0vodJvnG34ReIXMe5PG6VSmW/+vxcpl+Crv3NojVjx/eDnNfZYJM0Pv3GDXLbIZ76wk5oNjLF/UbgzCPvKE908+LGO0LeuLPG992d48lAjzx/f/OBzJzLpfCXDFc/ygzPThMIp9rVZkd/6TKWSodUrKl3eeiXxXIHvnJ0llClwe+eXSgQ66o30tpjpaTFTcw8F+PffmGBi2Mupz26nucPC0DUnV87NUypWrtjQWsUTL/QiCAKRUIpv/+lVrA4dz391Dzabft1zTiayTI34GLzqJJ3KI0oEpBKRXK74/7N33uFxVNf7/8zM9qpd9WoVV7nbuIGNMc1gOoRAQoAEQoAQ8iMkJCEh/ZsOCUlICBBKIBAg9F6MsTHuvci2bFm9a7W9787M74+1hY3VJXe/z6PHfqSZO3v2ljn33HPeF0e6iUkzC1n+/m4URT2o7b6w37cZjlxPT2eYF59Yh9Gk5fQFZaxcspdQME5GloWzFo0hMydV1LO32cc/nt7ASERyCuxcfl0q17QnB+ykzQE7EIYRJXiXLiFaXYXjnPMOEurWiBrCyQi7PHtoCbXREXHhjfmIy3EEBIxaA6IgUeOvZ5trJ0salrOtowJvzIdW1GHXWwc9ACo6d/GPrU8QSUT54ujLWVSygOmZebTHc2kN7sIbraYpksbeoMR2T5CNLj+r2n2sd/kpTzP3yt0Vl+O0hTuo8dVR0bmLDf42NsU6MYsi5+t3Y7QUIkrd78AEQaCo1Im7PUR9tRtPZ4jtG5pobfJTOiaDhZdPGPBRYGaXhIqHEWVOzNaD+c+ScT9bV77Jug1jUVQN51w0lqmzRxxW/TNBECgscdC4rzKqrSXAyo+q2LG5hY7WABqtxOjx2cyaX8q880czenwO2fm2bnmZBgp7mgmtQTrEuTyQliLe3oZl6tRuJbUOxH4JpMptrfi2bMGy41O8771Nx4vP43nvHQKrVxGu2E68tYWYxkR14Zksum5Gv46RNBmZeBd/gBwIYD+zezqUgeJIJGRLWgt6SyFhz3bC3h0YrCVodD07s8mYF3/7SpRkBK1xcLxAfeF41MkTBAH/vmrIvMK0QeVLwuGxPRGXeev5LQR8MeadP5qyMYen3/oLs0HL1FGZbNrdwertrV2OD6RE4B9+bTuSJHDbZRP6JRwPKXFuk1lHmtNEbr6Nt7c0E9GK3PzlqZRPzmNUeTYjytLJLUyj3hfh0Xd3EUrIfOncUVw0pxi7RUckmqSqyU9FjZuPNzaxYlsL7Z4IOo2EsxsOsLR0E9s3NuH3RinflytWMjqD9pYAkiiw6OpJXYU4q5dW42oLMvfckTgzLd3Lbek0Ka3cafkYzTo621MVmYIAkXCCuqpOVBXSs8xcft3Ufq+tfXGCDgRGkxZVTUlEmS16zrt8PNFIgvpqNzu3tCDLCjkFNl5ZUoWlM4JWEg9Kv+lJC/JUBGwf2p97Bu+Sj8j/zvcOIWdVVAV31INW1KKX9Ogk7SFHf+1hFxWdu9ju2skebzWyKgNg1Vo4v3hBn4SuB0JVVT5tXs2Lu19HEkT+35ybKdEfvCPa46nhr5sfwagx8YXR30DGQCCRpDOaYJsnSK5Rx23lhWgPcCZ3uffwbu1i2sMu/PHuv0MRgQVGLaeZrDjyz03pHPbEmJyQefOFrbQ2+gAYMzGHsy4cPehdcFOdhzf+u4WsPCtXXv/ZbklVFdZ++DKbNmUgSgILr5jIiH4mmw4Hgv4o/3tqA9FwApNZR+mYDErHZJJbaB+0rX2ht4iAmkzS+MAfiOzZjaFsJHl3fBuNrfdImKoo7P7XfxDWLgFAEURCWjthnZ2Q1k5Il0ZIl0ZYZ2PhVZMHpPHX+OADhLdvY8Qvf40+b+iVY0cyEhT2VeKqfhFRMpA96quHOFfxcAv+9lWEPRWwL2ZgckzAWbAIsQ8+s4HieIyAwWfzdqDHkIqi4HNH8LjDlE/MIxpL9PveaCRBxcYmgsE4NrsB6wE/RlNq4/DBazuoruygfGoe8xeOHrBdhwsd3gj3v7CZDk+Eq+aXctGcYt5eVcvLy6q5bG4Jl80dfHHIY29WsKqijZsvGscZB8hyfbShkecW70Yridx62Ximfk4M3RuMsb3azbbqTipq3IRjKUoKq0nLtNGZTB+TkuPaT3b8/qvbqa50ccm1kygo/kxvU1HUrlSLUDDGfx5ejdVm4NpbZiKKQr/GuJxU2LWtlU2r6gjsy9/S6zV86daZw1YYMRjISYUXnliHzx0BQKMVEUWBRFxGVVP5lB5ZwY5AflEaI8uzsNoN2NIMjBydfeoIsjeEd1fS+IffYj9zPtk3fG1IbUWTUXZ5qqhw7WRzx3bCyQjFtiKuG/sF8iy9y1o0Bpp5cffr7PXVYNaauG3S15g1ckK3g3Zx/TJerXqb0Y6R3Dnl610O3mu1bazt8DM9w8ZVJSnyvzUtG/jPrv+hqipOg4NMYzrpRicZBid7AhL1IS2lVqhxf0ggEWSMTseFJi1WSyHOwovQGbMPeT5ALJrgozd3kp5lYeaZJUPecXz4egVVOzs468IxnHnuaNrb/az6YAlbNknodAoXXTN9UKR4Q0XAFyUUjB0xnbW+FiolEaftyScIrF2NJj2d/DvvQl9Q2O21cjBIy78eIbx9G4oljcrCBSiZ+RjNBoxmLUaTDqNZi8ms6yoUGAgC69fS8s9/oC8aQcF3vodkHRrH1pF2RIKdm3HXv4GktZI9+mtIWjvRQDX+tpXEgjUAaA1ZWDJnEOrcTDzchKS1k158OQbLiGH7HMerA6YoKk8/tBIVWHhFKjdHkkQkjYgkCV0VYx5XOEWM3B7C1e7H7QqjpPapiKLKqPIspswq7pXsORKOs2VdI9s3NJGIy91eo9GIGM06Ar4ouQV2LvnS5MMaKR8MZFHkhw8tp9Mf4+LTi/l4YyMAv7/tdEyD0J3cD7c/yr2PrsZi1PKbW2aj1Yq8tHQv762px2bS8v+unnyIMPjnkZQVKhu8bKjsYGNlO/59aRZmg4YpozKYPyUfuyTy0lMbyB+RxqVfmtJtO6uX7mXT6gbOXDia8VNTxVUDGeOyrLCnoo3dFW2cdkZxipvrKKOzPcja5TXEIkkSCXmfBJxMNJzokjBKoJJSCv4MP33gklMOWK+NKgrV93wHZIXSBx7s81invwjEg7y05w3Wt21GEiQuKD6b80csQCMePMnCiTBvVn/A8qZVqKhMzpzAVSMvId3o6HHQqqrKo9ueZqurgguLz+Xi0vOBFJHqIzsbaQ7HuGJEJp7wJl6vfheTxshtk75GWVpxVxsr27y8Vd9BgVnPLWMLCCUCPFnxHFXeGpwaPZcaRbI1mn1s8+MRtdYu0eTDgaA/yn8fW4tGI/Gte8/mnZc+ZcfWEEZjnEu+NIP0LEffjZwA6M9Cpaoq7rfeoPP1VxH0BnJvvQ3LpIMXw1hDPc1//xsJVwemCRPJ/fqtSJbhreZVFYW2Z57Cv/wTdHl5FNz9fTRpg18sj4Yj4m9bibd5MRq9E0HUkoi0AaC3lGDLnoPBWoYgCKiqgq/1E/ytywEVW/YZ2HPOQhCHvl583u6Ibw/Bzo1YMk7DaOtfTlBfUJQE/pZlyMkgWmMOOmM2WmPOQaoQg8En7++mYlNzv68XRQWLJYTNEsJkVmlqshMKpyrxikqdTJ5ZSP6ItK7NTjgUZ8vaBrZvbCKZUDCZdUyZVUhBsYOAP0rAGyXgi+L3pf4N+KIYTVouu27qgNjbjxQyM63s2NPelRMGdEXDhoqXl+3l7VV1XDRnBO2eCOt2tZPjNHHXFyeTNcAjYkVR2dPoZX1lBxsq2/EG4wgCXHlmKXKtl6Y6L1feMO0QxZBYNMl/Hl6FpBH5yu2zuzjojtdNRm9QVZUn3t7Jlu2tjLEYuGTRGCRJJOCPEfSn6Duu+PK0Uw5YX2h79ml8Hy+h4LvfxzTuUHHqoWCbawfPV76KN+Yjz5zDdeO+QLGtCEVVWNWyjjf2vkcwESLblMnVoy5jXPpnIfPeBm04EeZ36/6CO+rljsk3d93njiX42/Za/OGVRBMVOPRp3DHlZnLNn0Wy9vrDPFnZhFEj8a3xhdh1qdC9rMi8VfMBH9R9jEaQOM9iZaKUOFioWGNG0lqQNBYkrRVz+uRhiwZsWl3P6qXVWGw6gv44FkuYi66eiDO7+wjPnZFP/gAAIABJREFUiYiBLFSBdWtpfeIx1GSSzC9eS9q556dyc1atpO2Zp1DjcZwXX0r6pZcflN84nFBVlY4X/ot38QdoM7Mo+O49aDMGl3NztBZpT9NiAu0rAQFTWjm27NPRmbqXoomFGuisfY1k3IPOmEt68RWHCJoPFPvtVpQE3qbFBF3ruv5mTBuHI39hr3lqfSEZ99FR/SKJSMshf5O0dnSmlDOmNxdisJYMaJMVDsWp3NZKIi6TTCoocoooU5YVkokYsVAbBl07NksQqzVIWnoa1vTxmBzlSFobce9Ktq7dTHVtIW5PKsKdkWVh4owC3O1BKjY1dxFvTp1dxLjJucNGOXM0sL+vU4n5m1BUlV/fMqtfQuJ9IRJLcu8jq7oiV6MK7Nx51aQB6WV2B0VV2Vnn4Ym3d+IJxBibb8fY5GfUqEwuuOrgtJ39a/is+SVMm/PZe+FEdMBe/7SG1z+toSTXxve/PLWLDPdAnErC7wdErRb/qhUIej2WSZOHte1sUyan580gnIxS0bmLVc3rCMRDvFuzmE+bVyMIApeULuSG8mvINh/84uotQVUraSm1F7O6ZT0VnbuYkTMVg8aARlDY0vYW7eEdaCUnd0+7ldwD2vXEEjyxu5mkqvLV0fnkmD7jQxEFkbHOUYywFlDRuYsd0QBhQy7jMsrR6x2IkhFQkON+kjEXiUgrIc929OZCNPqhR6iycq3s3dWO3xsjLc3HBZfmkZ43dsjtHk8YSFKyPj8fU/kEQls3E9ywHtnnI7yjAtfL/0PU6ci97Q7SzjpUcHs4IQgCpvETQFUJbd5IcMMGzJMmIVkGfhx5tJLRDdYS9KY80nIXYMmYhqTt+bNrdHbMXeS3VYTcm5G0lh4dtv7AbNbjddXTvvdZov4qtIYsnIWLSCb8xALVBDs3IAgiOlP+gCPQ0WA97VX/QY67MadPJWPEFegtI9DqnQiiDjkRIBFpIRasI+zZRtC1gWTCjygZkbR9FxJpdSnViPwRDgpLnBSVpVM8KoPCIhGz8AbZ6dXk5mvJKx1PTtlC0nLnorcUIkqpJO/covHoTWYyrCvIdLajium0tcrU7HbR1uzHZNExa37pPsqZtAFLLB1r2D/GzQYtC6bmM39KHkb90Byk/dBqRMxGLZv3uJg5LotvXTkRYz+oRvqCIAhkpRmZMyGHutYAuxq8+CWRhCvE2LFZXflZclLhwzd2AHDupeMOUmA4HgtNesOnW1t4/qM9ZNgNfP9LUzF3w0sGp5Lw+9ewLFP93btAFCi9/8HDFi3Y49nLs7teoiPSCcCM7KlcPnJRj/QV/dk1LG1Ywf/2vE6ZvYRvTLyBx7Y/TZW3hnRjIQlpAeMdTq4bmWL8jcsKj+5KHVFeOiKT2Vk9Hxe5ox4e3/4stf56nAYH1465kvEHyB8pcpxooAZX7UsIgkjWyOvRmwsG8a18BkVJULPtTeqqfJRPdpBddtkxJxtzuDGYnWLC3Unz3x4k1tAAgC4vj7xvfhtdTu95h8MN93vv4HrpRSSrjYK770FfOLDI5fG2Sw57duBueAtFjmLLnoc996xBcQ0p4Y007XkXVAVL5kzS8s5BFLWoqkrIvQVv82KUZBiNIQNnwYX9ZvIPujbgbnwXVBVHwUIsGTO6/XxyIkg80krEt4ewZzuKvC/ZWJ+O2TkRs2PigDZY8XAr7XufRUmGsOeejT1nbo/X7u/zZNyLq+Yl4uFm4nIersAcbE4HY8bn9Mo+frzhSIxxtz+Kw3p4xNllReHVT2p4Z3UdIjAr384t16eUNXZsaWbZu7uZPLPwEB7B421u94aKWjcPvrgFg07iR9dPJze959zFUxGwfkAQRRLtbUR278Y0rhxt+tCOFHpCutHJ6XmzsOosLCw+m7OL5vUqqN2fXcMIWyEtoTZ2uCv5tGkN7REX07ImcceUr9IYktntD6MXRYosBl6paWePP8xpGTbOzU/vdYIaNUZm5UxLCWu7K1nbupGOsIuytBL0kg5BlNAaMtAasvaV9O/EaBuJpB1cnlEy7qej6llIVFNUkk568RWI4tB3b8cbBrNTlIwmbLNPJ+nzoS8uJu/2bw0pF2uwMI4chWS1EVy/lsC6NRjHjEXrcPZ94z4cb7tkrTETY9o4or49RPyVyHE/Rvuofr/4knE/rpoX8bSsQ9SYyCi5GlvmTAQhFTkQBAGdKQdz+lRUJUbUv5eQeyuJWCeCqEOSTAjdzBFVkfE0voevdRmiZCCz7FrMjgk9fi5R0qHVOzHaR2HNmo3elA+qSjzcRDRQTaBjLdFgDRq9A42u93EVCzXQvvdZVDmCo2ARtuzZvV6/v89FyYDZORlFiSFHdmEz7SUr14HemIEgDk+E6FjAkRjjRn3vgupDgSgIlBc7Kcwys2FXO/X+GC5PmPEl6Xz89i4SMZnzLis/hOT3eJvbPaGxPcifX9yMoqp854tTKM7pPTWgpwjYKQfscxA0WgKrVyLqDZgnTjpsz5FEiRJ7EU5D3zvK/gxaQRAYlz6aje3b8McDLCiYy5fHXoVW1DDKbmJLZ4Cd3hDeeJJNnQEKzQa+PDIHqR9RPlEQGeMcyaSMcuoDjex072ZVyzrseht55hwEQUBryECjd+xzwnZhtI9B0vQub/F5xMLNdOx5mmTcjdk5hdHTbyQaPe4itMOCwS5UgkaDZeo0LFOmditVdKRgKClBm5lJYN1aAmvXoMvORpeb168XQn9sj7e1EtqxHV1e/jERHZU0RkyOCcSCdUT9e4iHWzDax/SanK8qMsHOTXTW/I9kzIU9s5z04i+hM3UfsRRFLUb7aAz2USQirUQDewl7tuFvX0HIU0E83IScCHRRoLtqXiDi3YnWkE32qOsHdDwqCCJaQzomRznWzJlo9BkocpxYsI6QewvxSAs6Y063czwaqKZj739RlQTpIy7HkjG1z+cd2OeCIGK0jURjyCDi203Uv5tAx1qSsU4kjQlJe2QqkQ8nThRHJDfdTKZGYketm+qOEJt2tSN7IkyYmMOYCYeO4xPBbk8gxh/+u4lAOME3Lh3PpLK+AzWnHLB+Qut04l3yEfH2Nhz7kpmPNvo7aLWilqlZEyl3juHMgjldtBR6SaTAbGCTy09zOIZVK3HzmAKMvRC1dgeb3srpeTMwaQzsdO9mY/tWavz1lNmLMWmN6IzZJEUdze4d7O3YSm0izmbXTmJynBxz72LNIU8FruoXUJQoaXnnkZZ3DhaL8bifrIPFibBQ6QuL0OUXEFi3huC6NYQrtqHNzOozOb8v2+VgkIbf/gr/ik+RTCaMZUefxR5SESSTYwLxcAvRQBXRQA3GtLGIn4vcqEqSoGsDrtqXCHu2A+AovJDSCZcTjXXX8sHQaK2Y06egN+Wl9DwFDclYJ/FwM1F/FaHOjQQ6ViPHfRjTxpFZeu2gI9IAgqhBZ8rBkj4Zg62MZNRFNFBD0LUeORFEZ8rrIm0OeyvpqHkRUMkouRqzY3y/ntEtQacxC0v6VCSNiWTcQyxYS8i9mbB3B6oqo9GnH/LdHi84Eeb3fuTmWunc1ko4IdMWSdABjCh2MHqE45D35/Fudzia4IHnN9LmiXL1WWWcNbV/vIencsAGgNYnH8e/YjmFP/wxxpGjDuuz+oPhOjdf3e7lkxYP15blUGQZWtm5K+Lm+cpX2OnejU7UkmPOwh31EkyEur3+2jFXMi//0GMIVVXxtS7D3/oJgqgjo/hKjPZUJeeJlC8wUJxItsdbmnG99grBDesBMI2fQMYVX8BQXNzt9b2S0KoqLQ8/RHDjBpAkUFUK7r4H09hxh+vjDxiqKuOuf5OQeysafTpZZV9Go3ekHK/OjfjbViAnAgiCBkvGdGzZpyNprUPqc1VVScZcxEJNxMPNJCJtGO1jsGbNGfZNpKqqRHy78TYvJhnrRBC12LJOR9LZcNe/hSBqyCy5BoOttN9t9mW7qqrEgrUEXRsJ+3aBKoMgYc2cSVreucfERnkgOJHmN8C2DY18+mEVblQaJYjJKqMK7Nx00TiyDxD6Pp7tDkeT3P/ccmrbVWaXRbjxotPQm7rnx/w8TuWADQSSRGDNakSjCfOEiYf3Wf3AcO0aCswGTs9OI20Yqm1MWiMzsqeSacpgj6caT8yHTW+l0JLPGOdIxuiNlBNiiiWDOhk2tW8jXZ9GnikTVU2gKHEUOYqn/k2CrvVIujSyRl6PwVLU9Yzjfbc0FJxItktWK9YZMzFPnETC5SK8owLfJ0uJNTWiLyg4hLi1N9v9yz/B8947GEeNJuemW/CvWklo62asM2YhmQZ25H24IAgiRvsYUGUivkpCnh2oaoLO2lcJe3cAKtbMWWSUfAGToxxRSlUgD6XPBUFA0pjRmXIw2kdhSZ+K3lJ4WByT/SkHlozTkLRWYqEGov49RHy7ESQDWSOvw2AtHlCbfdkuCAIavQOTo3zfc80koi6i/iqAAT/vaONEmt8AzkwzO7a0oE0ofOULE4nICttr3Czf0oxBJ1Gcmzo2Pl7tDoTj3P/fDdS1J5iY28FFY7YRdm8gEetEa8jqM93mVARsAFASCarv/jai0UjJ7x846rurY33XoKgKwEFSS6qq4ml8j6BrHe1JmeeCEeIqXGo2MPZzXDd6cyEZJV9E0h5cRXKs2304cSLbHt65A9crLxGtqQZBwHHeQjK+8MWuquOebI+3tlD3y58haDSM+Nmv0Kan4/34I9qffQZ9cQmFP7gXUXtskW4GOtbiaXwPAEHUYc2cgTVz9iFjHY7fPlfkGP72VcQCNTgKLjwkh02Jx/GvWoFhRAn6ESO6XU8HY7ucCNG2+wmScQ/OwouxZEwbkh1HEsdrX/eGhho33s4wE08rQFVV1u1q55n3KwlFk4wtSuNri8ZRPirruLPbF4xx//ObaXKFmJbfyg0XjEOrM+NtWUoi0goImJ2TseeciUafKk6RE0Ei/r1E/XuIhRqZsuAnpyJg/YUgScRamonu2Y154mS0jqPLvn6s7xq6Ez0VBAGDbSSoKmZJoERvZXvYx654giJrITnWQnTGLIxp40gvuqRbXb1j3e7DiRPZdm1mJrZ5Z6IvLCJWX0to6xZiDfVYJqcKB7qzXU0mafrLn0m6O8m56Zau1AB9cQlJt5vwti0kPR7MU/ov1nskoDfnozPloTVkkV58OSb7mB5F7o/XPhdEDQZrcSpfq5tcM9erL9P5ykv4PllKYPUqZL8PyWJBsn2WTD8Y20VJh8E2sqv6OvU9HzmN2AMR72jHv/JTIJVH3BeO177uDXaHsYsRXxAE8jMtnDEhhzZ3hO01bpZuaqam2Yciq2TYDcecPFR3cPuj/OG5TbS4w8wqauby6SHSiy5KRYDTp6EzZpOItqeqhF3rSERd+NtW4G36gIivkkS0A1FjJKf4zFNJ+AOBIIoE1q5BMpkOEec+0jheJ6sgCBisJVjSp5CbdRojHWWsb9tCRcTL+BEXUpQ3D4O1uEdSyePV7uHAiW67IAjoc/OwzTmDaE014e3bCO/agXnKVKwO2yG2u155ieCGddhOn0v6xZcc1I5pwgRCFdsJb9uKxmbDUNL/3KMjAa0hHYOlqM+E8ROxzxOdnbT+6xE0djvmSVOI1tcS2bUT37KPCaxdgxzwIVlt2HIyB2W7pDGht4wg7N5G2LcTg60MTS8EusMJJREnsH4d7c8/i+uF/xKu2I5/xXKUWAzj6NG9ytmdiH3dHQw6DTPHZZHtMNHkCrKz1sO6Xe18uKGRZlcISRLJsBu6BLyPJbR7wvz+uU10+KKcNdrHuSMrySy5Eu0+LrzUUXwmlozpaPXpJCJtxIJ1yIkQeksR1owZOAoWYs9dcOoIcqBQEnH23vVtNDYrxb/5w1HdVZ9I4eqd7t38c8uTiILIHVO+zsi0nskkTyS7B4qTyXY1maT1qccJrF6FNiubib/8CUHNZ5GU8M4dNP7pj2gzsxjx058jGg4tIEm4O6n/1c+Rw2EKv/cDjKNGH3INpHQrlXB42PUwhwMnYp+3PvEY/pUryP7a17GfMRclFiO0bSuB9WsJbd2CGk85IXmXX4rl4isH/ZywtxJXzYuIGhM5o28aFkWOnhBrqMe3/BP8q1ehhFNFR8bRY7BMnYZ3yUckOtrR5ReQc/MtGIq6l2c7Efu6L6iqSiip8v7KGtbsaMPliwJg0muYPDKDdLsek16LyaDBpNdg1GswGTRYjVoyBqhhOVS0dIb443834Q3GuXiGhdOc72G0jyGz9Joe71FVhXi4Ga0hA1E6+ESnpyT8Uw5YL2h59J8E1q6m6Ke/6HEiHQmcaJN1m2sHj257Gp2o5c6pt1BsK+r2uhPN7oHgZLNdVVU6X30Z9ztvobHZyP3W/8NYWoYcDFL78/uQAwGKfvjjXqNb4V07afzTH5GsVkb85Odo0hwosRjR6r1EqvYQqdpDtHovSiSC7Yx5ZH3lBkTtsUNjcKL1eayhnrpf/gxdfgEjfvqLQ5RFlGiU0NYtdL7xGvHWFjKv+RKO8xYO+nmBjnV4Gt9Fo3eSPfqmAfMQ9oVYcxNtTz6eyl0EJJsN2+lzsc89s0ttQolG6XjpRXxLl4AkkX7JZTgvvOiQaNiJ1teJmBtPw9skY17SCs7HZB/T7XX77VZVlZqWAGt3trF2ZxveYO/RwJnjsvjahePQ64ZH/9MbjFHXGiApqyRl5YAflURS4d01dQTCCa5ZUMpEy5skEz5yx94+6CPuUw7YIBDYsJ6Whx/CuehiMq78whF5Znc40SYrwIa2LTxZ8RwAueZsRqaVUJZWwsi0ki5JphPR7v7iZLXdu2wp7c8+jaDRkHvLbfhXriC4aQMZV34B56KL+7zf88H7dLz4X3Q5uQh6PbGGelCUrr9rs7NBEEi0tmIoLSXvm3eiSTu6OZ77caL1eeODDxDevo38u77bazV5orOTxt/9Hwmvl9zb7sA6/bRBP9PbtBh/+0p0pnwyi69F0vcsDzMQhHZU0PLwQyiRCOZJk7HPm4954qQeyY5D27fR+tTjyF4vhtJScm76xkGSYCdKX6uqSqBjLb6WJahKouv3xrRxOAouOOQ4+PN2K3Icv2sDDU2NyLpiVG0RkYRCOJokHEsSjibZ3eCltjVAYZaFO6+cOKRomKqqfLq1hec+2kMsLvd4nQBcv3AM0/Lq8DYvxpo5C0fB4DcHpxywQUCJxdj7nTvROBwU/9/vjtox5IkyWT+PLR3bWdqwghp/PYkDJm+6wcnItBImF4zFQTq5lhy0J5kc0Yna5/2BVLebXb+/v+t4yjh6DAXf+0G/tFlVVaX1X48SWLMKJAnDiGKMI0dhGDkKY9lINHY7SjxO29NPEli9CsmeRt7tdyDodESr9hCtr0PjcGIsG4mhtOyIUlucSH0e2lFB05/+iGlcOfl339Pn2mkMdLD1h/eBolDwvR8MiFxXSSSINzURra8lWldLzFGHkC+gtMcQEya0jiz0WXlo7KmjIVHSI4gaVCWBIsdQlTiKHE/9q8RBVTFYSzDYyhBFLb7ly2j7z9MIgkD2V2/CNvv0fn0uORSi/bn/EFizCkGnI+u6G7CfkdLDPBH6OhF14a5/k1ioAVEy4ii4EK0xC0/D28RCDQiiPkWonTG9q//32y0nggQ61hJwrUeVo11tSlobtuzTMadP7cqZTMoKz324m6Wbm7EYtdx+2XjGFfdf2mw//OE4/353F5v2uDDqNZx3WgFmgxaNJKCRxNSPRkQjCmQ6jOSmCTTveAhBEMkr/xaiZvCO3ykHbJBo/uffCa5fx4if/wp9wcBEhaM11XiWLCZtwbkYSwefGHwiTNbekFSS1Aea2Outocpbw15fLZFkpOvvoiCSa86mwJJHoTWfAkseBdY8jL3oZx7vONH7vDdkZlppWLeVpr/8GVWRGfGzX6J19j/0r8oysaZGdDm5iLpDKw7lcJjI3io8H7xHZOeOnhsSBHR5+SlnrKwMY9kotNnZh20jdqL0uaoo1P/fL4jV11H0k59jGFHc5z2ZmVZql6yg6W8PIpnMFN57H7rsnkku5WAQ9/vvEq7YTqypEeQDohlaCf3lRQhZQ+snQdQiBgxEVlRBh0DeN+7ENPqzozVVVUhE2omFm4iHGolH2tBbirDnnHnQ8Wdg/TrannkKJRwm/9vfwTxx0jHd1ylnNIGoMXU71lVVIdC+Gl/LUlQ1iSmtHEfBBV0VsKqqEuzciLd5MaocQ2cuwFl4MTpjFlZTlLpdiwm6t4AqI2pMWDNnYrSPIdS5maBrA6qaRNSYsWbOwpp5Wlc+1dJNTTz74W5UFb549kjOO62g33NxS5WLJ9/ZiT+cYGxRGjdfVE66vff3h7vhHYKu9TgKLsCaOXOA3+LBOOWADRKBdWtpeeQfOC+5jIzLrujXPXI4jOvVl1N5AKqKaDJR+IMfoc8vGNRnOJYn6+GAoiq0hNpwKe3sbKmmMdBEY7DloCiZJEhcVnYhZxfOO6ZoB4YLJ1ufH4iuXXIkgppMoLEeLHSb9PuJNzWCJB30QuwPAhs30Prow6jJ5Ge/3KedaCofT8ZVV5P0eYlWVRHZW0W0prorEgegy8sj7Zzzsc05vVvnbijob5+rioJ38Yd4Fr+PvqAQ+/wFqeOwfkQIjwT8q1fS+q9Hsc6aQ+4tt/brnv22e5ctpf2Zp9BmZ1P0w/sOIelVYjE8iz/A8947KJEIglaLvrAQfVExhqIR6IuL0eflgyShJIPEPR2Eq3YSqd1NrLkOBBl0IoJegy4rD0NhKYaiMiSdEUHSIYo6VCVJ2LOTQMNaMO4/vhYx2Eox2kYhJ/zEQo3Ew80HHbulDq5URMmAPWc+lszTugTVI9XVNP7xtwiSROG9P6Fgythjcn5Hg3X7dDzjCIIGSWdHo0tDo7Mj6exIWitB13ri4WZEjRln4SJMad2rUMiJAJ7G9/eRD4voLYXEgvWAikbnwJo9B7Nz8kHVwXIitC8ythZVjiFIeqwZMzA7J6LRZ1DV5OPvr27HH4pzxoQcbrhgDNpeJPVicZkXluxh6eZmNJLAlWeWcf7MQsQ+3hmJSActu/6JRu8kd9xtXf04WJxywAYJJRpl73fuRJuRyYhf/F+vi5yqqgTXraX9heeQfT60OTlYT5uB+603kdLSKLr3PrTpfQt3fh4n68v4QLsVVaE93EFDoJmGYBPrWjfhjweYkT2NL4+9Cp107CRTDwdO1j6Hz2xXEglitTXEmhqJNzcRa2oi3tSEHPzse8m5+RvY5vTvSCjW1ET9b34JgOOc81LHkqVlyKEgzQ/9lXhLM6Zx5eTe+s2uKkk1mSTW2EikuopI5S6CmzeBLCNaLKSdeRb2BecMG09gf/o83tpC65OPE91bhaDVoiZSDoDG6cQ+bz62uWceVd5CJRGn9r57kX0+iv/vt33qfu7Hgba7XnkJ9ztvYSgbScF3v4+o06Emk/iWf0LnW68j+3yIFgvpiy7BvmBBv8l31WSSSNUeQtu2ENy0iUR7GwCCXo9l8hQs02dgnjgJJRal+aG/Et1bhWHKKKyXzCQaqSYRaTuoPa0hE525AL0pH525AK3eScC1Hl/rMlQ5hsaQgSP/fIy21HGqf+1qWh/9J9qMTKb++Q94Y8fWxjEaqKWj+r+oqozRNpJkPIAc96LIkUOuNTkm4ihY2K9Ch4hvD+7Gd5DjPky2Qkzps1NC9T3QDwEocpRAx3oCHatRkmEgdTxpsJYSEYt54qMIta0hSnKtnDu9EEEEURAQ93FSiiIkkgqvfFJNuydCQaaZWy4ZT2FW/6qf2/c+R9RfRUbpNT0WFAwEpxywIaDp738ltGkjosWCaWw55vLxmMaPP8iZire10f7cM4QrtiNotTgvugTHwgsRtVo8H7xHx4vPo83OofCHPzpkR98XTtaXcW92e2M+Htv2DLX+eoqs+Xxj4o04DGlH+BMePpysfQ4p29ua3TT87tfE6mo/+4MgoM3IRJefjy4nF98nS1FiMQq++/0+I2FyOET9r39Joq2N3Nu+ifW0g48U5EiE1scfJbR5E5qMDPK+eWe3lc9Jrwfvx0vwLvsYJRgEScJ62kwc552PoThFqaKqKmoigRqPo+z7V9Bq0DicvUZre9XAVBQ8H7xH52uvoCaTWE6bSdZ1XyHp8eBb9jH+1atRY1EQRcyTp5A2/yxM5ROOeFTM/f67uP73Ao7zLyDzi9f2+74DbVcVJZXHt3Y1lumnYZ0+A9drr5Bob0PQ6XCcvxDH+RcOKT9PVVViDfUE168jsG4tiY52AAS9AdGgR/b5sM6aQ/ZXb+qqlE3E3MQCtUg6O3pz/iFUA/shJ0L4WpYS7NwIqBhso3Dkn4/WkI7r9Vdxv/k6tvHlZN95d49J/Eca0UBNKvKFQkbJ1Qc5HYocJxn3Isd9JOO+FK+dtWf6oO6gKAnkRIDc/CJcruCA7gt7dhD1VxENVHc5gwlZ4N3dk9hY3zvnm4DK2ZOtXH3uNHTavr9rVVUJeyrorHsFvaWErJFfGZYTllMO2BCQ8HjofO0VwjsqSHrcXb/XZmdjKh+PaDDi/fB91GQS0/gJZF13A7qsrIPa6HjpRTzvvZOSTPne97vlMuoJJ+vLuC+7E3KC53e/yuqW9Vi0Zm6ZeEOvvGLHE07WPoeU7TsefhzPe+9gmjAJ64yZ6PPz0eXmIer1XdeFd+6g8cEHEA0Giu79yUFVZgdCVRSaH/oLoa1bcFywiMwvfLHH6zrffB33m68jaLVkfeXGrqTpz0OJx/GvXol38QfEm5sBEE2mlOOVSHR7j6A3oMvNRZ+Xjy4vD11ePvq8PDTOdARR7LHPY81NtD31ONHqaiSrjayv3HBIpaASjeBfswbfso+J1dcBYJ09h5ybv3HEjujlYJCaH30fgJLf/GFAXGuHVMclEjT9+X4iuytTv5Ak7GeeRfrFl6CxD+9Ga78zFli3luD6dSQ62nFechnpl14+pO8uHmnD0/g+sWAtIGJQU430AAAgAElEQVR2TsRoH4vn+Q8Ird+Abe48sm+86ainUET91XRUP4+KSmbJ1Rjt3XPoDQeGKjifiLQQ8VcTDewlGmygqsOGP6pHQUBVBVQVFEQEQY+KhgJbC4VpAbTGbOzZ8zCmje028qbIMULurQRd60lEOwCBnDG3HCKrNViccsCG48GqSqK1hdCOCsI7KohU7kKJpio4JLudrGu+jGXGzB4SF1XannoC/4rlmMaNJ+/bd/Wbg+hkfRn3x25VVfmkaRUv7XkDgKtHXca8/NlHfVEbKk7WPgfQu5rYdu99aDMyGPGzXyEaek6W9X26nLanHkeblU3RvYfmDAF0vvEanW+8hql8PPl3fbfPqFBwy2Za//UISiSCfcHZZF3z5R4jFaqqEt5RgXfJYhIdHQg6HaJOh6DVHvB/HUo0SrylmXhry8EJ44Cg1aJJS8OQkY5qtqJJS0Njd6BJSyPh6sD99puoySTWWbPJ+tJX+nRsorU1tP3naWK1NWRddz1pC87p9frhQsf/nsfz/ntkXH0NzoUXDuje7sa7HArR8sg/kGw20i+94pBN7eGAqqooodCwEfWqqkrEtwtv02KScQ+Q0gSlKU5saxvO6YtwnnfRIfcpsRiB9WvxLfuYpNeLff4C0s4+F8k4vISkEf9eXNUv7HO+vojRPmpY2/88hnNdU+Q4sVADoCJqTEiSKVU4IGq71v94pA1/2wrCngpARaPPwJZ9BmbnBARBIh5uJejaQMizNZXPJ4iY7OOwZs1Gb84fls8JpxywwwI1mSRaU0O8vRXL1Ol9hsRVWab54YcIbd6EdcZMcm65rV9HBMM1aINbNuNdshjr9BlYZ80+KJpwLGIgdu/x7OVf2/9DMBHi9NyZXD36suM6L+xkdcCUaJTG//s50bY2Cu75Yb+S7PfnDBlHjSb/7nsO2tgEt2ym+W8PosnIYMR9P+/3izXe1kbzP/5GvKkRQ9lIcm+7Y1hyq1RZJtHRTqy5mXhzE/HmZuLtbSS9HmS//yDOsv2Q7Hayr/8qlilT+/2chMdD/S9/mlIG+MGPh1SF3R/EW1up+/l9SDY7xb/+7YBF0U/08a6qCvFQI2HfLiLeyi5nTJVVdFI2xuwxqEqCZMhLrKWJpLcDVVAQtCJoRFBVEEQ0dhuSzY4gppLCBUFC1JqRNBYk7b4fjQVJa0XSWhA15h43oxF/FR3VLwCQWXpNV67a4cTR6udEtBN/2wpC7q2AgqRLQ9JaiIcaAZC0diwZ03rUMx0qTjlgxwiUeDwVWt+zG/uCc8j6ct9nzAcO2oSrA9+nyxEkCeeii3vVGzsQgY0baHnkH127b9Fkxj5vHvazzkaXefh3loPBQCdrZ8TDY9v+TUOwGavWwoLCuczLn4NJO/Bdo6ooJNrbiTXUd/0gSZgnTcYyecqwH4N8Hif6C6kntP3naXxLl+BYeCGZV/cs+3EgVEWh9bF/Eli3FuusOeR8PXXsFm9tpf7Xv0BNJim8974Bq1kosRht/36SwNrVSFYbubffMeCqy4Egw2mitbqZpNdL0ucl6fWiJhLYZs8ZVEQmtKOCpj/fj8bhZMRPf3FY5JdiTU143n8X/5pVIMsDKoo4ECfTeFdVFYsxSP2mjwg0rUdM781ZFRAEDaosoyoyoKZ+J4kgiqD2TCYKKSoNjc6JRu9Ao3ei1af+LyfDdNa9hoBARuk1GG1lw2lijzja/ZyMe/G3rUrl56kyBmsZlszTMNpG9VoUMFSccsCOIcjhEA2//y3xpkZM4ydgmTIN86TJaNO75zrKcJqoXbIC79KPCVdsS+2GANP4CeTeejuSqXe258CGdbQ8+k8EjZacm28hVl+Hb9lS5IAfBAHzxEmknXMepnHlx0wpOwxussblOO/VLuGTppVEklEMkoF5+bNZUDgPu77nhE05GCS0dQuR6r0ph6uxATUW6/5iQcBQWoZlylQsU6aiy80b0GfsD472QnU0EKrYTtOf78dUVEjevT8ZUBRFicdpvP/3RKv34rzkMpwLL6D+N78i3tw8aKcAUi9L70cf0vG/F0BVU0d68xcMqq2+cDj6vPPN1+l8/VXMEyeRd+ddwzK/VVUlsmc3nvfeIbR1CwDanBycF16E7fS5gzr+P9nG+357A+vW0vrfR8GigYSCvqAY+4zTMU+ahqQzgSB1fZ9KNIL344/xfPAuciCAoDeQds45pC08B1WIIyeDyIl9P8kgctxPMu4lGev8HF1GCoKgIbPsWgzWIydef6z0s5wMo6ryERNuP+WAHWNIej00//1vXbpiALr8glSEZdJkDKVlJH0+/J9+QmDFJ8Q7U8n/hrKR2OfNJ7hxPaGtW9Dl5JJ35109khYG1q+j5dGHEbQ6Cu76LsZRqTN+JZEguGEd3iUfEa3eC6QW0dyv39pVzTVU7E9uVcJhtFlZaNIcA3oBDGWyRpIRPm1aw0cNnxCIB9GIGmbnTOfcorPINKUc3USni+CmjQQ3bUwl++6fC5KELicXfVERhsIi9Pt+lEiE4OaNBDdvOuh6bU4O9tPn4rjwomHLPTtWFqojBTkUou7n95H0+5l8/++IWPtHX3Agkn4/Db/5FQlXB/rCQmINDaSdex5Z11435M8X3l1Jy8N/Rw74ybr+xsPihB2OPlcVhaa//IlwxXbSr7iK9IsuGXRbSiJBaOsWPO+/Q7Q6tW4ZRo7CufBCzJOn9Di3U9HkNrTZOT3Oj5NtvB9or2/5MuItLdjmzktxmPUBJRbDt2wp7vffQfb50OXmkfuN29EXdk8UrqoqSjJEMuYmEfOQjHUiJ0NYnJPRW7rX4T1cONn6eT9OOWDHKBKuDkJbtxDcupXIrh1dBJGiyYQSiYCqIhmNWGbNIW3+WegLUxNGVRRcL/8Pz/vvIprN5N3+LUxjDybEC6xfS8uj/0TU6ci/67sYR3afYBmtrcG75CP8q1Ygms0Ufv9H6PMGF9VRVZV4YyOBdWsOKu+GVLKxNjMLbVYWuuxstFnZGEtH9rhwDHSyyoFAKoJVXweCgKjTk9Rp2Cy18olchVsJISCwIF7IaWs7uqrFIOXYWqZMw1Reji4vv88Cif0Rs+CmjYQqtqHG42R/9Sbsc8/s9+ftDSfbQtXy2CME1qwi/fIrGfu16wZte6y5mYbf/golEklJGN19z7CV+seam2j84++QAwGyb/wa9nnzh6Xd/ThcfS4HAtT98mckvR4K7r4H07jyHq9Nej1Ea2tJuDtJdrpIdHaSdHeS6OxE9vm6rjNPmYpz4aKuDV13UBWF4Pp1dL79JvGmxl6pKU628T4c9irxOK6X/4f3ow8RNBoyv3gt9gXnHNMFSCdbP+/HKQfsOIASixHetZPQ1i2EK7YjWizYz5xP6aJzcQeT3d7j+/QT2p75NwDZX7mh66UQWLeWlsf2OV/f+V6/tNV8y5fR9u8n0TicFP7wxz0eiXaHeGsLgbUppyvekirL309wqM3IJN7eTqK9jUR7W1fl6H7YF5xN5lVXH0LN0RcvUrypiUh1FdG9KdbyRFtbt9cCKALsKdKzYrKFgEXizI0hzpBKsEybjmXyVDRpg8/pSrjd1P30RyBKFP/qN2js9kG3tR8n00IV2LCOlof/jqGklMIf/pisnLQh2R6p2oPv0+VkXHHVsPTFgYg1NdLwx9+hhEJkf/XmHmkqBoPD2eeRvVU0/OG3SCYzI372i4MEyOVAgMDG9QTWrCayZ/dnkeD9kCS0Tiea9Az0efmkLTi712N3VZYJrF2D++03U1WfoohkNiMHAmRd/1XS5p91yD0n03iH4bU3uHkTrU89jhIMYp46jZwbbzos+X7DgZOtn1VVRfb5yB1VeMoBO17R16ANV+6i+eGHUIJBHOctRF9cTOvjjyHq9anI1wCEbd3vvYPrpRdTpLE/+BEaW++ksbGGBtqeearrGFPQajFPnIR15izMEycfUmmpqipyIECirY14Wwue998j3tKMxplO9g1fxTxhYq92Jzo68Hz4Hv5VK1MRwn0QjUYMpWUYy0aiLy5BkCTUeAwlFkOJxVFjMZR4jM6knyfslQTUGDeWX8vMnGn9/m56g3fJYtqf+w/WGTPJvfWbQ27vWFuomoItLGtcgV7S4zQ4cBrScBjScBocmHvQjOsPkj4vtT+7DzUWY8TPfokuJ/eYs/3ziNbX0Xj/H1AiYXK+/g1ss+YMS7uH227P4g/peP5ZjKNGk3fHtwlt24J/zRrCOyu6inOMo0ZjmjARbUYm2vR0NOkZaOz2/gmhJ5P4V6/C/c5bKZZ5ScI25wyciy4GoOE3v0IOh8i/67uYy8cfdO+x3ufDjeG2N+Hx0PqvR4hU7kLjcJJzy62HtWBksDgZ+lkOhwjv2EGoYhvh7dtJetyc8frLpxyw4xX9kihpb6f5bw92RZ9Eo5H879wzqPLzLtLYohEU3PPDbrlnVFnG/e7bdL75OsgypgmTsM2ejWXK1AGRzCqJBO6338D97jsgy9hOn0vmNV9CMpsPsjtaV4vn/XcJrFsLqorG4cRUPn6fUPJIdLm5/c4vawq28OeNDxOT49w26auMTx/b78/bE1RFoeH3vyG6t4q8O+/CMnnKkNo7lhaq3Z4qHtn6b6Jy90UJOlGL0+hkRvYU5hecjlHTd/+rqkq0ag+uV14ismc3mddeh+Pc84Bjy/aeEK2tpfGB36NEo+TeevshzPqDweG2W1VVWh75B8H167r0LwH0I4qxzpyFdcbMAYmeH4hw5S5an/wXSZcrRZo690ycFy46SIoosmcPjQ/8HkGrpfDenxyU5nA89Plw4nDl+7nfeYvON14DVcV50SVYZ8xE43AOSTVgOHEi93OsqZH2Z58hUrWni05GtFgwl09g0o/vOeWAHa/o76CVw2Fa//UI0Zpq8r/9HQwlg6tuUVWVtqefxL/8E4xjxpJ/190HVaTFmptpfeIxYrU1SGlp5Nx4E+aJkwb1rP2I1tfR9tQTxOrrUqS2191AyfnzqVu2Gs9776Z26YC+sBDHBYuwTp8xpNyeKm8ND21+DBD49tRvUGofGEVBd4g1NVH3y5+isdkp/tWvB+SIfh7HykK1pnIpzza+i6qqnLPGT15OGeoZMwiYBDxRL+6oF0/UQ1vERVyOY9QYWVA4lwUFZ2DSHrroJ70e/CtX4FuxvOvI+PMVeseK7X0hUl1N05//iBKLkXvbHVinTR9Se0fCbjkSofGBP6DGY1hnzMI6Y1aPCgL9RXjXTpr++mdUWSZt/lk4LljUoyO3X6hbm5FJ4Y9/gmSxUumpYkZpOQFv9woCJyIO63Fz1R5aHv0nSXdn1+9EgwGN04nG4UTjdKJNz8A+98whpV4MBsfL3B4oonW1NP7pjyihEIaykZgnTMQ0fiKG4uL9KhdH3wEbM2bMJmB/JmcN8AjwFyAJfFBZWfmLfjRzygHrA6qiDLncXFWU1G55w3rMU6aSd/u3QBDwfPg+na++nGLmnj0nxcxt7p0Go9/PlGU8779L5xuvoSaT6DIyiLtcAJjGleO4YBGm8vHDlmS6zbWDR7c9jUHS851pt5NnGbrshOu1V3C/9QZpZ59L1pe/Muh2juZClXC7Caxbw9L6T/moNI4uqXLxqjBlqpN4UyMIAra580i/9IouctJIMsryxlUsblhGKBHGIBk4q+B0FhTNw4SO0JbN+FcsJ7Q9RaMiaLVYpk3HPvdMjGPGHjRej6dFOrK3isY/3Y+aTJB9w9ewzZo96I3B8WT3foQrd9H0lz+hyjJ537yzX5Hf/XqIutIyFl9YyCbPDibnlHPLuBuP6QTy4cTh7ms5FMK3fBmJjnaSbjcJt5ukx40SDnddo8vNo/De+45odOx4HON9IbK3iqYHH0CJRlPFOd0UYh11B2zMmDEGYFVlZeXUA363GbgKqAbeBu6rrKzc2EdTpxywIwQlkaD5r38mvHMH1hkzSXq9RPbsTunRXX/jkHf8PSHe0kzrv58kWr0X62kzcCy8EMOI4sPyrNUt63lm54uk6e3cPe2bpBuHxnauJOLU/eKnJNraKPzhjweUf3cgjmSfJwN+YnW1RGtrCe/cQXh3JSsnmVg/3ow5IXKT9SxGT1+AoEs5Uq6X/0e8pTkljHzu+TguuLCLiy6ajLG8YSWL65YSVCLoZIFJe6NM2+rHGFcxlJRimzsP64yZPfLXHW+LdHh3JU0PPoAajyNZrFhmzMQ2ew6G0rIBORTHpd1/+RNqMkne7d/qN1O/qqrU/vOvJDZsYtcIPUvmppNQk9ww7hpm5R6eNeVYw1Fb06NREm433iWL8S1dgmnCRPLvvKvfhN5DxfE2xvtCeNdOmv72IGoikeIbnDW72+uOBQdsFvA0UAdogJ8Dj1RWVo7b9/f/B+gqKyv/2EdTpxywIwglGqHh/j8Qq60B/n975x0nZ1Xv//f0mZ2Z7bvZlk3PSSOVQAIEIhAkiihFmogIioIF5arXfvUnem3XchHwCgIKKKJSpAoxIQkJ6T0mJ2U3yfY+W6aX5/fHM7vZ9M1md2Z3n/N+veY1szPPzHw/e57nnO+c8z3fL3jmnU/h7Xdg9Z4+OH8gyM/NoLk1cOYDz5FlR1by4oHXKMzI54G59+G1n9sOosA+SfVP/xt7aRljvvO9fs2InK7N44k4Gxq2ku/MYVLOsRmsw1VHaPjjU0Qa6vXlhpwcfQdbztHlBxJxQocOET58mNDhQ8csVcRN8M6SMnblRyhw5PL5ufeQ78o95ju0eJyOte/S/PKLxH0+zG43ue9fSiISIbhPEqqsIJKIsmuii81TM/BnWMhIWLmu9AoWTrn8rCo/DBfCtbW0r1pB5/r1eoJjwFZQiHfBQjIXLMQ+6ujsqpZIkAiH9Y0h4TBmhwNrdvaw0h3cv5/qX/1cd74+ex+eOX13nPa07uMP25/h6n/WUtIcw7l0Cb/K34PVZOU7C75yztffcCDdba3F49Q89CsCu3aSfeVVFN5yW0q+N926BxL/rh3UPvwQWiJxxmtgKDhg5wELgMeBScAbgE9KOS/5+l3AeCnlt8/wUcMuaG24E+3o5NAfniZ79izyL7loRC4TPLP9Rf6x9y3KMov5ysX3UJJ5bsuRBx75LQ3/fJvyj93K6JtuHCAr4WDrYX638VkqfVUAnF8yk9tnXUexu4DqF16i6rnn0WIxnCUlRH0+4r2WHCJWE3vGOWnOsWKLadijGk6rg8ycfDILisguHs3q+GF2tOxjYu5Yvr7oPjKdp6keEA5T98prVL/wInF/8ntMJtxjx5A5bSqZ06biFJNY3rKd53e9QiQeZU7xDD4971by3bmn/NzhjBaP49u+g6Z3VtGybj2JZDUFe14uiUhU35UbiRz7JpOJ4ms+yJjbb8VymsLj6SKhJahoPcK2+t10hf1cEC2k/RePoUWjiK/+B3kLL+zT52iaxqvyXzyz4wUsJgufmvxhMn/zd8KNjcTGFnM41kJWTiEzx8/B6vFg9XqwerxkTpmMo6DviXlDsTB7mvbTHuqkxDuKksxReOwDEyYxkoj5/ez42jcJVlcz4XP3UnTVlSm3IeJrx7dtO4EjR8iaMZ2smedhHqC8fYNJy7r1yJ/9ApPZzJRvfI2cuWec/U27A+YAzFLKYPLvLUCOlHJc8u/7AZuU8udn+Cg1A2YQUqlb0zReOPAqy6tW47Q4uH3qTcwpPO/MbzwF8YCfQ9/5Fgl/F2O+9+BZBzofrz0UC/Na5VusqHoXDY35o+bSFm7jgK8SM2bm1FmYt6YWjyuLojuPboqIB4M0Nh5iVd16NgT2EeLk+eR6Mz1vCnfPuB2HpW+lgOJdXXRu3IA1LxfXxEknXVpsDrbw570vsLdtPw6LnWsnLOXS0oWYT1J/baSc74lQiK5tW+hY9x6RulrMDgcmuwOz4+jN5HAQ3L+PaEMDzqJR5H/sE6dNlJoqOiNd7Gndx+6Wvext3U9X1A9AUXOUjyz3YYtrdN50FTMvv7FP50kkHuVPe//OxoYtZNm9fPq8OxiXNYZwbQ21Dz+kp6041VhkMuGZO4+cK6/COXHSCT8AE1qCqs4a9rbuZ0/rPirbDxM7rkai1+6hKKOQUe5CijIKKXDl4bG7ybBm4LZl4LI6T3ouDhZD5RyPNDZy5IffJxEK6Ul6xbnvCD8deTkuqtZvI7BrJ/7duwgfPnTM62a3G8/ceXjPv4CMKVNTtjR6NnRsWEf947/DZLNR+oUvnZAA/WQMhRmwe4HzpJT3CSFKgOXowfcf5mgM2PellOvP8FHKATMI6dC9qWEbz+79G5F4hCtGX8qHJyzFYu5fJ9CTYHTCRHKuWAJmE5jMmJL3mPVs/a5Jk0/oaHpr39W8h+fki7SFfRS48rhV3IDInUgiHue9Fc/xWmAL7R4LzriZpeOuZPH4xVhMFio7DrO86l22N+0ioSXw2j1cVnoRswpmEEvECMXDhGKh5H2YUDxEhtXFwuL5/dZ8OjRNY139Zl7Y/wqBWJDxWWP42JQbKXIfW0bLaOd7IhKh5R8v0fbWm5BIkLnoUgo+ekvKUwdomsbGfz6Db+dWOuMBEiYTCRPYbQ5yM/LIy8jDtm4bRKK8cXEm+8sdOC1OLiiay6LSBT2bWOKJOG3hdtpCbbQmd8pua9pJdVct4zLL+dR5HyfbcWyC3Pw8N9v37OTRdY+Sqzn55LjrsIQixH3tdKxb21O1wjFmLDlXXoV3/gXsbJNsbNiKbD2AP6bPwJowUeYtYWruZHKdOTQGmqgPNNLgb6I11IZ2igUUEyYyrC7ctgyyndncMPEayrwDX+O1m6F0jgf27qH6lz/H7HJR/q3vYi8oHPDvCFVW0Pr6awTlnqOz8hYLrkmTcU+fgb20jMDuXXRu2ki83ae/7PHimac7Y8dv1EkXHe+tpf6JxzA7nZTe/8Apq8scz1BwwOzAU0A5+jLifwIJ4FeABX0X5Lf68FHKATMI6dJd21XP47uepiHQxISscdw942NkOc4+5k3TNGofeQj/1tPvK3GOn0DRpz6DvfBox1dQ4OVAdS1/3/8PNjdux2wys6R8MVePvQK7xUa0pZn6J39PcO8eNK+HgzcuZHl8H8FYkHxXHm5bBoc79GXKMk8Jl49exNxRs7CZ0z+93x7u5K/7X2Zr4w6sJgsfmnA1V4y+tGdmw6jnu9PXwN5fPkSkphpLdjajbv9EnwPbz5WuiJ/VT/+MCe8dOv2BJhPFn/4ssZmCtXUbWVu7AV9Y39he5B5FKBaiPdxxUkdnYfF8bhbXnfQc7G7zVyve4o1Dy7i09CJuFh8Bjhb/9i17i66tW0DTiLgdbB5vpbbQRkHMxVhzDqPiGWRHrJi6AsQ72jFZLWRMm457+kyc48cTJU5joJn6QCMtwVb80QD+WIBANIg/6scfCxKIBuiIdOKyurhv1l0Dkp7mZAy1c9y36h0a//gU9pISRn/jOyfN/dhfOjduoP73v9NDI4pG4Zg6Hff088iYMuWEVD1aIkHwwH46N26ga/NG4h16PKVj7DgKb7mtzw7PYNC5eRN1v30YsyuDsge+inPs2D6/N+0O2ACiHDCDkE7doViIZ/b8la1NO8m0e7lr+seYlHP2edUS4TBdmzeRCIfQNA0SGiQSaFoCEhqhQxV0bd5E3OUkcdMH8Y0vpLqrjoZQPRVtVUQTUcZllnPrlBso9RSTCAVpffMN2t56Ey0SwT17DqM+fifWrCy6on7eqFzGqpr30DSN8/KncfnoS5iYPX5Ixu1tb9rNX+QLtEc6uah4PreI67GYLSPufO/uY/uy+aCxrk1PcPzqPyAexzPvfBxlozFZrZgsVkxWC/Q8tmJ2ubC43VgyMjBnuLG43We96WNf60F2PPMbZu5oI+ixU/rZz5OZXYAWT0AijhY/erPl5GLrFY8VT8TZ1bKH1TXr2O+rINPuJceR3VMtITdZLSHflUdhRv5ptTc1dRJNxPjxhl/REGjiy3PvZUL22GOOO3JoF9teepJxshVH9NRjl8luR4vHezL8m10u3RlL5mey5Z46BnFD/Rae3vM8VrOVz5z3CabkDvygP+hJdxMJEn4/Zre7zzNHjc89i2/Z22TMmEnpF7907qmMNI22N16j+YW/YXI4Kf7MZxl3xaI+69YSCYL7JO0rV+gJuAHvBReSf8NNZ1UmbyDw79pBzUO/xmS1UfYfX8U1fsKZ39QL5YANY0bagNRX0q1b0zRWVK3mxYOvA3BZ2UWUe8sYlVFAgSufDFv/fyW2BNuQbfvZ13aQI40HaIx3oJmPXqNmk5mijEIuKV3AotIFmOIJfKveofWVl4l3dmLJyqLghpvwLjxxU4Qv3I6maeQ4U5tksT+0hzt4dMeTVHXWMCVnEp8673bKiwtHzPkeiUd4bOfTHOmsZsmYxVxauhD7KWKmep/v4Zoajvz+UbQj1Wf9nSaHA4vbjWf2HPI+9BEs3pNvpEhoCd6oXIb/by8ye1+QaK6XiV/7Lo78vge8DxS9tVe0H+IXmx+lMKOAb8y/H5vFhqZprKxZy4sHXiOWiHFl4QIubfSitXdgzcrCkpWFNTMLS2YW1qwszE4niVCQwJ49+HftxL97p56lP4lz/HhKPvdFrFknv0a2N+3miV3PAHD3jNuZWTD9pMcNhN7+oiUShKuriDY1Em1uJtrU1PM41tKMFothstuxFxVjLy7GXlxy9L5w1AmOeu+dkbaiIuwFhVhzcrBmJ285OVizs7EVjjqhxNwJtsViNDz7RzpWr8Kak0PpF7+MY3R5v3UHD+yn8bk/ET5UiclmI+f9S8m9+gOYU7BppTvNDJpG6f0P9Cnm63iUAzaMSbcjki6Giu4Dvkqe2PUM7ZFjbfHY3BRmFFDoyifflUeOM4tsRxY5jiyyHFk4rUc7KX80wL62g+xt249s3U9T8GjqB7vFTqkjn5zKZnIONTMq5uLiO++F0ZPRNI2ujRtofvHvRJsaMTmc5F69lJyrrj5jJzhcCMXCPI0t/+UAACAASURBVPXvP7GzeQ8l7iK+/b4voAVs6TbrnAnHI/x2+5Ps8x3EhAkNjUy7l/ePuZyLSy88YSmuoMBLQ2M7u5r3sLxqNQdaD1LYGsMe03CZbJRnFFOeUcJo1ygcWNGiURLBAPFAgETAT9zvJxEIEPf7ibW1Ee/swOxykXvNteRcseSYAdcXbuepnX9izFvbmV4RgqJCxn/1m6d0SAab46/15/e9xMrqtVw99gouH72IZ/b8lR3Nu/HY3Hx86k3MyD+7QVDTNKIN9fh37aRr21aCe/fgmjKVsge+esqZnr2t+/m/HU8R0+LcMfVm5hcN3HLwufRtsc4OOt5djW/limOcym4sHi/W/Hys2dnEWpqJ1NejRY+rMmA2JzeF2DHZbJitNkw2G1gsRJsaSYQjEDt5ZQKTw4l3/nwyL7pEj1897gdgPBCg7tGHCezZjaN8DCVf+FJPwuZz0a0lEnSuf4+mv/+VuM+HJTubgus/infBwkGLDwtVVlD9Pz8lEY1S8rkv4pk5q1+foxywYcxQcURSzVDSHYyFONRxhMZAM02BZhqCTTQGmmkNtZHQEid9j8vqJNuRhdlkprarvicuxmlxMClnAlNyJjE5ZwJF7kLMJvPRWm7J+ppZly0mdPiwnoPNYiH7ssXkXvPhMxZIH44ktAR/2/8KK6vXkO3M5DMz7qQ8syzdZvWbcDzCo9ufYL+vglkFM7hVXM871WtYUbWacDxCjiObpWOvYEHx+VjMFkKxMLu7dvHKnmU9zvmUnEmcP2o2VV017GreQ0uoDdADxsszy5iWK3Anyz1paKDpZ5iGBvE43k2SrJXbMIfCxHIy6Xr/QqJTxhHRYvzz4NtcsqqeyUfC2MaUU/7lr2HxpC//1om7fkM8uP4XtEc6yLR78YXbmZw9gU9Mv+WEAP6zRdM0ah/+X/zbtpJ7zYfI/8gNpzy2ov0Qj2x/glAszM3iOhaVnjzR5tnSrTccj7D8yCpquurw2r1k2j1k2r1kOrxk2r14k39bTBZCBw7ge+dfdG3e1DO75Z03H8focmwF+djyC7EV5J80rira0kykrpZIXR2RujqiDfUkQkESkShaNHmLdd/HwGSi6O57cJSPIeZr0x36dh/R1lb8O7cTa9HPUVtBIZkXX0Lmwoux5eURbWmm5te/IFJbi3vmLIrvufeYWaqB6NMT4TCtb75O25uvo0WjmOx2HKVl2MvKcIwux1E2GkdZ2SkTPfeVcE01VT/9bxKBwDnXe1UO2DBmKDkiqWQ46I4lYrQEW2kOteILt+MLteMLt9MWbqc93EFbuJ1IPMK4rHKm5ExC5E5ijLfstLsMQ5UVND75GKHaOgA8519A/nU3YB816pTvGSmsqHqXv+9/BZvZyl0zPsZ5+elPyXC29Ha+Zhecx13Tb+tp785IF28feYdV1WuJJmLkO3OZmifY1LCNYCyI1Wxl/qg5vG/0JZR6ins+U9M06gON7Grew+6WvRxsP3RKx783jnCCC3f6mbk/iEWD6kIba2d5mP/vAONqwjgnTab0i18e0KDr/nCya31X8x4e3fEkZpOZD45bwlVj3jdgqSLifj+Hf/BfxJqbKf3SA7hnnLqWbVVnLb/Z9hhdUT8fmfABloxZfNLjEtEoJoulT7Mx+fkelv37Pf62/xXawr5jX9Q0rHFwRBI4IxplzXHmHYzibdF3D9qKisl+3+VkLrx4UHbKhg4fouqn/w2aRtlXvo5r/LGxrz2xWWtW685gJAImExlTphKuqSbe0UH25VdScMttJ/wvBrJPj7a00Pr6q4QqDhCure2J9+vGmpdHxtRpZC++4qwC5gEiDfVU/eRHxDs6GPXJu8m6eNE52aocsGHMcHBEBoORojuhJc564Mj12jj4wqu4Jk7qd1H14Upl+CC/fu8JYokYN06+lsVlF6fbpD4TioV5dMcTHPBVMqfgPD7Zy/nqTXu4g38eXs67NeuJa3G8Ng9XT76MeTnz+pQJPhANUtF+iGgipmd4NJmSmR71e5PJRELT0NB0R62xBcebq7Dtrez5jIzpMyi57wtDYin7VNf6tqZd5DqyB2U2NHToEFU/fhCT08mY737/lAXEAer9jTy07TF84XZK3UXMNpcxKeQhuzVEtLZWj8VqbATA4vXqsWiZmVgyM5OxaZmYzBYS4RCdXW1UNu+jvaMVewyKrNlk4+xZQiYYxBQ/1rmOm+DgaAc7JrnoKM1B5E1iau5kpuZO7tcO7TPRtX0btb/5NRaPl/JvfueYjRfH2BUM0rV5Ix1r3iW4fx+YTBTcfBs5Vy456fGD1adrsRiR+jrCVVWEq5O3I4eJd+rf5Rw/nuzFV+CZPx+z7dR567RYjNCRw9T99hFirS0U3HY7OZefe4Ja5YANY0aKI3K2GFU3KO2bDv6bR7c/SWe0i6Vjr+SD45YMyZ2cvQnFQjyy/QkOth9iTuFMPjnt1jPmU2sNtVHnb2Ry9nhKinIHvc39/95Ny0svYCssZNQn7sJsGxqxduk6330rltP47B9xTpjI6K9+/bQ7SOu2vseRF/6Mp7ETW/zYcTPhcuAoKcVishDv6CDe0U4iFOq7IRZLcidrBpYMt37vdmPOcGPLz4e5MzmQaOxJNtuRjEe1mCx8cvpt55Q0+lT4VvyLxmefxl5UrBftdp9+SS/S0IAWieAYPfqUx6Q0uXYiQWD3Lnwr/oV/5w7QNCweL5mXLCJ78fuw5uUTbW4iVFlBqLKSUMVBwkcO98TL5V9/I7kfuGZAbFEO2DDGqIOxUXWD0t7U1ElzsIWHtj5Gc6iVy8ou4sZJ16Y0W/nZEIqFeHj7E1S0H2Je4Sw+Me2Ws05mq9o89do1TaP+sd/SuWE92UveT+HNt55wTLStjaa//JmuTRvAZMJWWkooP5P6TNjraOeQO0SXy6yX4bLpmfU9NjdenGRFLWRFzDiDcfa27MNHEKfLy7WzP0CZZyJmpwOzw4nJZuvzDwxN06j117OndR+vV75NPBHn3ll3DUq6jKbnn6PtrTdxTRaUfvkr5+ywp6udo01N+FauoP3dVSS6usBkwpyRQcLvP3qQ2YyjtAznuPFkTJ+Bd975A/b9ygEbxhi1YzaqblDau7W3hzv4zbbHqfXXM3/UHD4+9aZBydLfH7qifva1HWRf20F2t+ylNdTWb+cLVJunS3siFOTwg98nWl9P8X1fwDtXL6qsxWL4li+j+eWX0MIhnOMnUHj7HTjLjyZn1TSNhkAju1ske1r30Rby9SR4PT5Gz2qycGX5Zbx/7OWUFuUNiN69rft5dPsTmM0W7p9zD2Mzy8/5M3ujJRLU/d8jdG3ehPfChRR96p5zmolO9zmeiEbo2rQR3zsriHd04Bw7Fue48TjHTcBRXj5oy/HKARvGpPukTRdG1Q1Ke2/tgWiAR7Y/SWXHYWbkTeHuGR/Hbkn90lkoFuaArwLZdoB9bQep7qrtec1hsXNh0fncOOlD/XYQVZunT3u4ppojP/x/mCwWyr/zfeLtPhqe+SORmmrMbjcFN9xE5iWL+pzuIKElCMXCdEX9ukMW9VPsLiLPde7pGI5nW9MuHt/5NBlWFw/Mu/eE0l5ng6ZpVHfV4rG5e/IIJiIRqn/+E0IVB8+4a/RMpLud04VywIYxBj5pDakblPbjtYfjER7b+Uf2tO5jQtY47p11Jy5ranbuxRNxVlav4bXKZYTielyP1WxlfOYYRO5EJudMPOPO1r6g2jy92tvXvEvDk49j8WYS79RL4GQuupSC6z96ymS2/WWg9a6t3cize/9KtiOLB+be1+Po9ZWmQAsbGrawoX4Lzck0KBOyxnL+qNnMKZyJK5yg6kcPEm1qJO+6G8i69DKs3rMP/h8K7ZwOlAM2jDHwSWtI3aC0n0x7NBHjD/9+jq2NOyjzlPC52XeTaR/YgfF49rUd5Pl9L1HnbyDD6uKS0gVMyZnEuKwxAz4Lp9o8/drrn3qCjndX4RhdTuHtd+CaMHFQvmcw9C47spIXD7xGoSufB+bdd8bdtIFogC2NO1hfv4WK9kMA2M02ZhZMpyPcyX5fBRoaZpMZkTORCy1jyXn8RT1uymTCNWkynjlz8cyZi62P1ROGSjunGuWADWMMfNIaUjco7afSntASPCdfYE3tBrLsXqblTWF81hjGZ42hMKNgwIL020I+XjzwGpsbt2PCxEUlF3Dt+Kvx2M8tuePpUG2efu1aPE6oogLn+PGYLIMXazhYel8++AZvHV7BaE8J98/9TM8ssaZp+MLt1HTVUd1Vx5GOKna3SmKJGCZMTM6ZwIVF85hVMKOngocv3M6Whu1satjO4c4qALJDJi5tymRcVQgOV0PSf3CMLtedsfPn4ygpPaNuTdMIxIK0htpoCbURjoWZWTAdl3XwSwulA+WADWOGSueUaoyqG5T202nXNI3XK9/mX1WrCMcjPc9nWF2MzSpnfOZYxmWVU+op7lNOrd7EEjGWV63mjUP/IhKPMCZzNDdP/ghjMk+9tX6gUG1uHO2Dlg9L0/izfIE1tesZnzWGcm8ZNV111HbV448Fjjm2yD2KC4vmMn/UnDPWjW0MNLO5YTsbG7bSENDznU00F3BZRwEFFc2E9u7VM+gD7vNmkrP0gz1lilpDbexvq+BwZzVdiQ7q2ptoDbURioeP+Q6vzcM1469iYfH8IbPRZqBQDtgwxmidUzdG1Q1Ke1+0J7QEtV31VLQfprLjMBXth3viV7rx2jwUe4oocY+ixF1EsaeIQlc+/lgAX6idtrBPr1wQ8iVnCOppC/vw2Nx8eMJSFhSfn7LUF6rNjaN9MPUmtARP7HqWrU07AT01b74rl1JPCWWeYko8xZR5isl15pz1jkZN0zjgq+Cd6jVsb9qNhobblsGivLmc3+omtma9npAV6CzOZvM0N9sL9Uz53TgtDnKdOeS5csh16rdgLMTyqtVE4hFK3EVcP/EapuZNHrh/SppRDtgwxmidUzdG1Q1Ke3+1d0Q6qWw/wuGOKmr99dR11dMcau3z+50WBxcWz+OacVeRYRv4Mi+nQ7W5cbQPtt54Is7etgNkWJ0Uu4t6lhUHktZQG6tr1rGmdj3+aAATJrIdWTirm5j3bz8TavTZaX9OBuFL51F08eVMHTeBgC9+UsevPdzBqxX/5L26TWhoTMsTXDfhg+QHzFg87p7ajgktQVuonaZgMy3BVvJcuUzIHndMcftEOEykvg5rVjbW7PQUmO+NcsCGMUbrnLoxqm5Q2gdSeygWpj7QQG1XA3X+epqCLbhtGeQ4sslxZJHt1O9znFk4Lc60ZdxXbW4c7SNJbyQeZVPDNlbVrKU11MaErHFMyhnPhJAH++pNdK5fB/E4luxsiq+6EtvcC08btF/VWctLe/+BaftuZu8LUtiqL22G3Xbasu00eDSaM820Zlloy7TiDCco6oBJYQ/FHWYyWrpINLfo8WlmM545c8lefDmuKVMH/NqOxCPUdNVT1VlDdVcNrSEfswtmsKD4fKy9HELlgA1jRtLFejYYVTco7UbUblTdYDztRtIbbW2h7a1/0rFmNYlgUC/cPXUaWYsuwz17zjHZ9aNtbbSvXE77yneId3aSMMGhYjtmDXI7YmT6z1yAPmg30ZHrwlI0isw6H/aGNkCfiaucVsC+CW7azWHMJjMFrjzyXXkn3LusTqKJGMFYkEAsqN9HgwRjIdojHVR31lLVVUuDvxGNE32oHEc2V41ZzMKSC7CZrcoBG84Y6WLtjVF1g9JuRO1G1Q3G0240vaAvC5r27aT69bd64sTMHg+ZCy4iY8pUOjeso3PzJojHMbvdZC26DO9lizlgasFpdVKYkY87biFaX0+4tpZIbQ2Rhnosbg+O0lJCBVlUuPzsClcjfQf0DTqaRlFzjJn7A0w6EsaagKjVxKEJWRwa46bRGiTgMBN0mNDMR30ki8lCXIufVo/DYqfMU8pobwll3lJGe0rIsLlYUfUuq2vWEU1EyXZksaR8MR+de7VywIYrRrxYwbi6QWk3onaj6gbjaTea3m66dUfqaml/dxUda9cQ7zz6f7CXlpFzxRK8Fy44p7JAsUSMyvYjhONh3LYMMmwZOENxYus20r7yHWItx27W0UyQcDqIZtgJOkwEHWY0hx2Tw4HJ6cDicGJxZWB1ZeDIymXUzPkUZI465QadzkgXy46sZFX1WiKJKM/f/KhywIYrRr9YjYjSbjztRtUNxtNuNL3dHK9bi8Xo2r6V4IEDeGbNxiWmDHoMppZI4N+1g1BlJfGuTuIdHcQ7O4l3dhLr7NCLdZ8Bs9tN5oULybxk0TG1QY+nM9LFtqZdXD97yUlFWU/2pEKhUCgUCsVgYrJa8c6bj3fe/NR9p9mMZ+ZsPDNnn/R1LR4nEQiQCIWO3sLBnseRulo63luLb/kyfMuX4SgfQ+Yli8i8YAEWz7F5B712D4tKF5zSFuWAKRQKhUKhUAAmiwWL13va+p/5192If9dO2tesxr9jO01/eobm55/DPWs2romTsJeU4igtw5KVddoZPeWAKRQKhUKhUPQRk9WKZ/YcPLPnEGtvp2PdWjreXU3X5k10bd7Uc5w5w42jrIyCn/3opJ+jHDCFQqFQKBSKfmDNyiL3/UvJuepqInW1RKqrCddWE6mpJVxbQ6iy4tTvTaGdCoVCoVAoFCMOk8mEo6QUR0kpXi7sef50Gx1TU+RMoVAoFAqFwmCcLgZMOWAKhUKhUCgUKUY5YAqFQqFQKBQpRjlgCoVCoVAoFClGOWAKhUKhUCgUKUY5YAqFQqFQKBQpRjlgCoVCoVAoFClGOWAKhUKhUCgUKUY5YAqFQqFQKBQpRjlgCoVCoVAoFClGOWAKhUKhUCgUKUY5YAqFQqFQKBQpxnS6QpEKhUKhUCgUioFHzYApFAqFQqFQpBjlgCkUCoVCoVCkGOWAKRQKhUKhUKQY5YApFAqFQqFQpBjlgCkUCoVCoVCkGOWAKRQKhUKhUKSYIeuACSFM6bYhHQghhmybDAZCCJsQYkq67Ug1Sd3XCCHc6bYlnRj1OjcqRmxvo2lO9m3l6bZjODBk8oAlT9JJwDellHem2ZyUIYS4D5gL7JVS/jzd9qQSIcSdwD3A81LKX6XZnJQhhLge+C8gX0pZmm57UokQ4rPATGC/lPKX6bZHMfgIIaYBn5dS3pduW1JB8hyfBmySUv4x3fakEiHEHcBngGeklI+m256hTtpnW7p/HUgpNWA8cIcQYknv10Ya3bqEEDcAVwE/A24QQvxH8vm0t8tgIYQwJ38hfRv4AHAt8BshhCvNpg06QogiIcTLwA3A94Gnk89b02rYINN9PgshPgl8CPgfYL4Q4utCiLy0GpcihBAmIUSZEOJxIUROuu0ZbI7ru6cB9wghFiVfG3H9W69z/PPoffozwF1CiE8nnx+RYxn09OkOIcTDwGLgA1LKR3uNcyNW+7mS1gsh2RHZko89wGXA74EfQ49TNqJIarYn/7wEWC+llMATQJ4QwiWlTKTNwEGku72llFEgBtQAtwNvAn8VQiwWQjjTaeNgIITIEULYgDDwIynlx4B9wCIAKWUsnfYNJr2vcWAqsE5KeRD4NnArsHAkDsjHk+zLxqGf70vTbM6gIoTw9npcjN6vP5q8MdL6t9560Z3Nl6WUG4BXgbgQwjYSxzI4ql1KGQYigA+4UwjxBvCSEEKMVO0DQdo6PiHEfwIvAw8KIW6QUnYBy6SUnwaahRBfTR43YrznXpp/KIS4Fvgu8BMhxBzgK8Bo4BEhxKQ0mjko9NL+IyHEB4BfAzcC2VLKK4F/ANegD1Ijht7nObBESrk++VII2CCEyE2bcYPMcdf4R4E16D8ycqSUFcABYJaUMjGSrvNuhBAeIYQj+TgD3eF+ErhNCDE6rcYNEsmZ7efR23yulLIOeENK+QX0fn1EzfL30vsDIcSFwE+Ap4UQlwJfQ58R+p0QwpI+KweHXtp/JISYij5xcgOQJaVcCmwD7ktOrihOQlouAiHEbOBS4CbgLeAmIcSHpJT/Sh7yVeBTQoi8keI9H6f5TfRf/1cnfw0eBOZLKT8OFKA7YiPG+TxO+xvAJ4EF6LMBLwBIKX8HzAFGTFD6cbrfBq4TQtyYfDkbmCqlbE2XfYPJSa7xDwICaAIeF0L8C1gJfFgIUTJSrvNuhBDZwH8D1yefigDvSCnvBWrRQy1GhBPSjRDiMmAe+vVdB9wthLhYSvl68pAvAV8QQrhHgtN9nN564OPA+GSfvhcQUso7gPnocY8jhuO0VwNfQJ/9uxf4C4CU8r+Ay4GSNJk55ElXBzAZ2CClrAeWA88CX+z+lSCl3AGsJTllPUI4XvOf0QPQAbIAjxCiEIiiz46MpCXY3tpXoMdHfB19RiQshJiaXKpqBrrSZ+aAc7I2/4wQwiKl3ARERnCMyPFt/jfgCuCnwEPos7//B6wD2tNl5CCyCD0WaIEQYkxymXlr8rWfAe9jmA/KJzlnzwdWJ9v8eWAz8IluR1NKuQ29X38q+few6t/OoPcvwBb0H9YAFvTlxyJgN+BPmaGDQB/aeiO69rfQ+7UyIUQB+jnvS6mxw4hBd8B6/8rr9fgQ8EEhhDP5a2EZ+izQdb3e+nn0hh12nI1mIcTNwELgMeBF4EUp5doUmzxg9EF7HH02qBK9vRcBj6DPCr4mpdybWosHhrM8zz+afP2PwIVCCPNwG4x60wftMXQH9DB6EH4X8DlgNbBFSjmsB6dTUI7evoeBDwNIKYNJ53s/uuP5FSGE/TSfMWRJzvDlJR93L69tQZ8BQUrZiK7Rjz7b3c096M74sOIs9HYlQyyuRR+/nkfv1/al3OgBoo/a16Nf11cBN6NPqrwEvJ18XXESBtUBS8aA/Di5Ng5gEkKYkgGKB4BvAEgpA+jT8q3J91mklH4p5XC8UM9Gcw3QLKV8HrgfuHQ4b1vuh/ZWKeXj6EuRFw1X7f04z5uSxy0D7hnOQclnqb0aaE/O/j2E3uZPpcHsAeP4ZcReMwV/AX6D7ohOEELMSz7f/foPgaellJFU2DmQCCHuQo/vubbXc2Yp5QpglxDiweTTe9FDCjqTx1iklF1Syr+k2uZzoR96q6SU/wd8C7h8uPZr0G/tPwbuQx/Pnk61zcOJQdn+LvTkko8AjegxPtkAydkPhBAz0X8F3S/0XFA+4Grgnd7HDSf6qXkp+iwAUsoDqbd6YBgA7TWpt/rcOYfzfGXyuGE7NX8O2lclj3sv9VYPLEnnM08I8Xcp5frkwJQAkFI2J4/ZiJ5eZ6kQYouUMpY8Lgj8M33Wnz1CiMXo8blV6MvG6+GYNp+Gvrnm90KIFejjy8Tk/bDr1/updxLJXe5Sys2pt3pgGADtu1Nv9fBjsPIPWdFns/6AnpTNn1wPfh74OXqw9UfQAzXnoQeqfktKuWqQ7EkF/dX8TlqsHViMqr2/ulemx9wBxahtfjrnM5F8fREQkVKul1JWCSF2ouufC2wexjOec4H/kVIuF0J8EygGdieXqH4MTAeWAP+Bvuz4PuAHUsqtp/rAIU5/9Q5bx6sXRtaeMs7ZAUsuN2hCz/7bJaV8BhgLTEAPut0MSOCbwBTgl1LKyuTb30vefnOudqQSI2ruxqjajaobjK39FJzJ+TwP+Gyv49cAu6WU1ak2tL8c1+ZBKeUfgF8ldy/a0dMrvJk8PB/4q5SyW/NLydsPU213fzGa3t4YWXu6OecYsF7Bw1cA30hOr28HgsAtwOvJ5YafANO6O2YxjPOiGFFzN0bVblTdYGzt4mg2788KIW5PPj2WY53Pl9EDj7+L7ny+T0opuz8jGfc0bJwvOKHNv9a9vCqEcCTj1tagV7JASnlAJlMIDdc2N5re3hhZe7rptwMm9O213Y8vRU8hUM3RX7oPAk70qUrQt6Vv6X7PcIsHAGNq7sao2o2qG4ytvRujOZ+nafPuWq3dVRv2Au1CTzDbw3Brc6Pp7Y2RtQ8VzroYtxCiDPgeUAi8gp5YM4K+TfUw+s6nS6WUB4QQX0TvnMcADuD7wzEGxIiauzGqdqPqBmNr70YIUST1HEfdg9Ot6MH0B6WU9wkhzkNPM/GAlHJFcrdYiZTywVN/6tClj21+cS8Hcyn68uunpZRNJ/vMoYzR9PbGyNqHGv2ZAbsTfSv9/eiBef8JBKSUe6S+1fz3wC+Txz4MfBn4WXJa/p1ztjg93InxNHdzJ8bUfifG1A0G1i6SBbPRy8d8OjlY7QX+Fz1v3UeEEBOllDvRywrdIoR4Ez0L+rtpM/zcuZO+tzlSyjeA3w/jAflOjKW3N3diXO1Dij7NgAkhPokeiHcQvVbfD6SUFUKIieiJ9WqklL/udXwrcIeU8tVBsToFGFFzN0bVblTdYGztvRF6fTs7unPVXRrsG1KvVYsQ4gfAbCnlh5LLjA5goTxaRm3Y0M82/7iU8rV02HuuGE1vb4ysfShzxhkwIcSP0XM2/RqYBXwCfToS9PXiZcAYcWxR4VuAioE1NXUYUXM3RtVuVN1gbO2gD05CiD8IIb6LHlz/VHL55U/osV53dx8rpfwOcLEQ4hopZVxKGRimzld/27ySYYjR9PbGyNqHOn1ZgswCfiel3IIefPswcJsQYraUMoSeC8eJXoLBBCClfEtK+e/BMjoFGFFzN0bVblTdYGDtBnY+jdbmRtPbGyNrH9Kc1gETepmNF0hmwUXfav0G8APg10KIycCV6MF7FjmM69l1Y0TN3RhVu1F1g7G1JzHc4GS0Njea3t4YWftwoM+7IIUQmei/Bq+VUtYLIb4F5AKjgK907xgaSRhRczdG1W5U3WA87cnB6QpgnZSyUwjxW+AfQBnwMeDT6DXw5gN3Sr180IjCgG1uKL29MbL2ocrZZMIvRW+8LCHE/wK7gK9LKaODYtnQwIiauzGqdqPqBoNpl3pJoLehZ3CaC3xPSvm60DPbfwZ9cLp/JDpfSQzV5hhPb2+MrH1IcjYO2KXAWdURNAAAANhJREFU19E7qaellM8OjklDCiNq7sao2o2qG4yt3aiDk9Ha3Gh6e2Nk7UOSs3HAIsC3gZ9LvTyBETCi5m6Mqt2ousHY2o06OBmtzY2mtzdG1j4kORsH7CkDBugZUXM3RtVuVN1gbO1GHZyM1uZG09sbI2sfkpx1KSKFQqEYaQghTGpwUigUqUQ5YAqFQqFQKBQppj+1IBUKhUKhUCgU54BywBQKhUKhUChSjHLAFAqFQqFQKFKMcsAUCoVCoVAoUoxywBQKhUKhUChSjHLAFAqFQqFQKFLM/wdH+zd9KNW2wgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pdf.iloc[:, :10].plot(legend=False, figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Valuation Models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Based on the risk factors, we can then define derivatives models for valuation. To this end, we need to add at least one (the `maturity`), in general two (`maturity` and `strike`), parameters to the market environments."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "me_opt = dx.market_environment('me_opt', me_1.pricing_date)\n",
    "me_opt.add_environment(me_1)\n",
    "me_opt.add_constant('maturity', dt.datetime(2017, 6, 30))\n",
    "me_opt.add_constant('strike', 110.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The first derivative is an **American put option** on the first risk factor `gbm_1`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "am_put = dx.valuation_mcs_american_single(\n",
    "            name='am_put',\n",
    "            underlying=gbm_1,\n",
    "            mar_env=me_opt,\n",
    "            payoff_func='np.maximum(strike - instrument_values, 0)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us calculate a **Monte Carlo present value estimate** and estimates for the option **Greeks**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "15.013"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "am_put.present_value()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.5411"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "am_put.delta()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.0082"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "am_put.gamma()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "51.1584"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "am_put.vega()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-3.7421"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "am_put.theta()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-71.1355"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "am_put.rho()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The second derivative is a **European call option** on the second risk factor `gbm_2`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "eur_call = dx.valuation_mcs_european_single(\n",
    "            name='eur_call',\n",
    "            underlying=gbm_2,\n",
    "            mar_env=me_opt,\n",
    "            payoff_func='np.maximum(maturity_value - strike, 0)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Valuation and Greek estimation for this option."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20.641978"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eur_call.present_value()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8496"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eur_call.delta()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0057"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eur_call.gamma()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "48.2888"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eur_call.vega()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-8.7493"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eur_call.theta()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "54.3995"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "eur_call.rho()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Excursion: SABR Model "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To illustrate how general the approach of DX Analytics is, let us quickly analyze an option based on a SABR stochastic volatility process. In what follows herafter, the SABR model does not play a role.\n",
    "\n",
    "We need to define different parameters obviously."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "me_3 = dx.market_environment('me_3', me_1.pricing_date)\n",
    "me_3.add_environment(me_1)  # add complete environment"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# interest rate like parmeters\n",
    "me_3.add_constant('initial_value', 0.05)\n",
    "  # initial value\n",
    "me_3.add_constant('alpha', 0.1)\n",
    "  # initial variance\n",
    "me_3.add_constant('beta', 0.5)\n",
    "  # exponent\n",
    "me_3.add_constant('rho', 0.1)\n",
    "  # correlation factor\n",
    "me_3.add_constant('vol_vol', 0.5)\n",
    "  # volatility of volatility/variance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The model object instantiation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "sabr = dx.sabr_stochastic_volatility('sabr', me_3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The valuation object instantiation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "me_opt.add_constant('strike', me_3.get_constant('initial_value'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "sabr_call = dx.valuation_mcs_european_single(\n",
    "            name='sabr_call',\n",
    "            underlying=sabr,\n",
    "            mar_env=me_opt,\n",
    "            payoff_func='np.maximum(maturity_value - strike, 0)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some statistics --- same syntax/API even if the model is more complex."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.025849"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sabr_call.present_value(fixed_seed=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8151"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sabr_call.delta()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-0.0385"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sabr_call.rho()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# resetting the option strike\n",
    "me_opt.add_constant('strike', 110.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Options Portfolio"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Modeling"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In a portfolio context, we need to add **information about the model class(es)** to be used to the market environments of the risk factors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "me_1.add_constant('model', 'gbm')\n",
    "me_2.add_constant('model', 'gbm')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To compose a portfolio consisting of our just defined options, we need to define **derivatives positions**. Note that this step is *independent* from the risk factor model and option model definitions. We only use the market environment data and some additional information needed (e.g. payoff functions)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "put = dx.derivatives_position(\n",
    "            name='put',\n",
    "            quantity=2,\n",
    "            underlyings=['gbm_1'],\n",
    "            mar_env=me_opt,\n",
    "            otype='American single',\n",
    "            payoff_func='np.maximum(strike - instrument_values, 0)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "call = dx.derivatives_position(\n",
    "            name='call',\n",
    "            quantity=3,\n",
    "            underlyings=['gbm_2'],\n",
    "            mar_env=me_opt,\n",
    "            otype='European single',\n",
    "            payoff_func='np.maximum(maturity_value - strike, 0)')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let us define the **relevant market** by 2 Python dictionaries, the correlation between the two risk factors and a valuation environment."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "risk_factors = {'gbm_1': me_1, 'gbm_2' : me_2}\n",
    "correlations = [['gbm_1', 'gbm_2', -0.4]]\n",
    "positions = {'put' : put, 'call' : call}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "val_env = dx.market_environment('general', dt.datetime(2016, 1, 1))\n",
    "val_env.add_constant('frequency', 'W')\n",
    "val_env.add_constant('paths', 10000)\n",
    "val_env.add_constant('starting_date', val_env.pricing_date)\n",
    "val_env.add_constant('final_date', val_env.pricing_date)\n",
    "val_env.add_curve('discount_curve', r)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These are used to define the **derivatives portfolio**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "port = dx.derivatives_portfolio(\n",
    "            name='portfolio',  # name \n",
    "            positions=positions,  # derivatives positions\n",
    "            val_env=val_env,  # valuation environment\n",
    "            risk_factors=risk_factors, # relevant risk factors\n",
    "            correlations=correlations, # correlation between risk factors\n",
    "            parallel=False)  # parallel valuation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulation and Valuation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we can get the **position values for the portfolio** via the `get_values` method."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total\n",
      " pos_value    91.269955\n",
      "dtype: float64\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>position</th>\n",
       "      <th>name</th>\n",
       "      <th>quantity</th>\n",
       "      <th>otype</th>\n",
       "      <th>risk_facts</th>\n",
       "      <th>value</th>\n",
       "      <th>currency</th>\n",
       "      <th>pos_value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>put</td>\n",
       "      <td>put</td>\n",
       "      <td>2</td>\n",
       "      <td>American single</td>\n",
       "      <td>[gbm_1]</td>\n",
       "      <td>15.029000</td>\n",
       "      <td>EUR</td>\n",
       "      <td>30.058000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>call</td>\n",
       "      <td>call</td>\n",
       "      <td>3</td>\n",
       "      <td>European single</td>\n",
       "      <td>[gbm_2]</td>\n",
       "      <td>20.403985</td>\n",
       "      <td>EUR</td>\n",
       "      <td>61.211955</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  position  name  quantity            otype risk_facts      value currency  \\\n",
       "0      put   put         2  American single    [gbm_1]  15.029000      EUR   \n",
       "1     call  call         3  European single    [gbm_2]  20.403985      EUR   \n",
       "\n",
       "   pos_value  \n",
       "0  30.058000  \n",
       "1  61.211955  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "port.get_values()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Via the `get_statistics` methods delta and vega values are provided as well."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Totals\n",
      " pos_value     91.2700\n",
      "pos_delta      0.5310\n",
      "pos_vega     225.1372\n",
      "dtype: float64\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>position</th>\n",
       "      <th>name</th>\n",
       "      <th>quantity</th>\n",
       "      <th>otype</th>\n",
       "      <th>risk_facts</th>\n",
       "      <th>value</th>\n",
       "      <th>currency</th>\n",
       "      <th>pos_value</th>\n",
       "      <th>pos_delta</th>\n",
       "      <th>pos_vega</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>put</td>\n",
       "      <td>put</td>\n",
       "      <td>2</td>\n",
       "      <td>American single</td>\n",
       "      <td>[gbm_1]</td>\n",
       "      <td>15.029</td>\n",
       "      <td>EUR</td>\n",
       "      <td>30.058</td>\n",
       "      <td>-1.1802</td>\n",
       "      <td>87.3484</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>call</td>\n",
       "      <td>call</td>\n",
       "      <td>3</td>\n",
       "      <td>European single</td>\n",
       "      <td>[gbm_2]</td>\n",
       "      <td>20.404</td>\n",
       "      <td>EUR</td>\n",
       "      <td>61.212</td>\n",
       "      <td>1.7112</td>\n",
       "      <td>137.7888</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  position  name  quantity            otype risk_facts   value currency  \\\n",
       "0      put   put         2  American single    [gbm_1]  15.029      EUR   \n",
       "1     call  call         3  European single    [gbm_2]  20.404      EUR   \n",
       "\n",
       "   pos_value  pos_delta  pos_vega  \n",
       "0     30.058    -1.1802   87.3484  \n",
       "1     61.212     1.7112  137.7888  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "port.get_statistics()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Much more complex scenarios are possible with DX Analytics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Risk Reports"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Having modeled the derivatives portfolio, **risk reports** are only two method calls away."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "gbm_2\n",
      "0.8\n",
      "0.9\n",
      "1.0\n",
      "1.1\n",
      "1.2\n",
      "\n",
      "gbm_1\n",
      "0.8\n",
      "0.9\n",
      "1.0\n",
      "1.1\n",
      "1.2\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "deltas, benchvalue = port.get_port_risk(Greek='Delta')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>gbm_2_Delta</th>\n",
       "      <th>gbm_1_Delta</th>\n",
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       "      <th>dim_0</th>\n",
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       "      <th rowspan=\"2\" valign=\"top\">0.8</th>\n",
       "      <th>factor</th>\n",
       "      <td>80.000000</td>\n",
       "      <td>80.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>61.767112</td>\n",
       "      <td>122.001955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">0.9</th>\n",
       "      <th>factor</th>\n",
       "      <td>90.000000</td>\n",
       "      <td>90.000000</td>\n",
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       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>75.421234</td>\n",
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       "      <th rowspan=\"2\" valign=\"top\">1.0</th>\n",
       "      <th>factor</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.000000</td>\n",
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       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>91.269955</td>\n",
       "      <td>91.269955</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1.1</th>\n",
       "      <th>factor</th>\n",
       "      <td>110.000000</td>\n",
       "      <td>110.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>109.161973</td>\n",
       "      <td>80.751955</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1.2</th>\n",
       "      <th>factor</th>\n",
       "      <td>120.000000</td>\n",
       "      <td>120.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>128.739235</td>\n",
       "      <td>73.195955</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "              gbm_2_Delta  gbm_1_Delta\n",
       "dim_0 dim_1                           \n",
       "0.8   factor    80.000000    80.000000\n",
       "      value     61.767112   122.001955\n",
       "0.9   factor    90.000000    90.000000\n",
       "      value     75.421234   104.903955\n",
       "1.0   factor   100.000000   100.000000\n",
       "      value     91.269955    91.269955\n",
       "1.1   factor   110.000000   110.000000\n",
       "      value    109.161973    80.751955\n",
       "1.2   factor   120.000000   120.000000\n",
       "      value    128.739235    73.195955"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deltas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0.8</th>\n",
       "      <th>value</th>\n",
       "      <td>-29.502843</td>\n",
       "      <td>30.732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0.9</th>\n",
       "      <th>value</th>\n",
       "      <td>-15.848721</td>\n",
       "      <td>13.634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.0</th>\n",
       "      <th>value</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000</td>\n",
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       "    <tr>\n",
       "      <th>1.1</th>\n",
       "      <th>value</th>\n",
       "      <td>17.892018</td>\n",
       "      <td>-10.518</td>\n",
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       "    <tr>\n",
       "      <th>1.2</th>\n",
       "      <th>value</th>\n",
       "      <td>37.469280</td>\n",
       "      <td>-18.074</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             gbm_2_Delta  gbm_1_Delta\n",
       "dim_0 dim_1                          \n",
       "0.8   value   -29.502843       30.732\n",
       "0.9   value   -15.848721       13.634\n",
       "1.0   value     0.000000        0.000\n",
       "1.1   value    17.892018      -10.518\n",
       "1.2   value    37.469280      -18.074"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "deltas.loc(axis=0)[:, 'value'] - benchvalue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "gbm_2\n",
      "0.8\n",
      "0.85\n",
      "0.9\n",
      "0.95\n",
      "1.0\n",
      "1.05\n",
      "1.1\n",
      "1.15\n",
      "1.2\n",
      "\n",
      "gbm_1\n",
      "0.8\n",
      "0.85\n",
      "0.9\n",
      "0.95\n",
      "1.0\n",
      "1.05\n",
      "1.1\n",
      "1.15\n",
      "1.2\n",
      "\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "vegas, benchvalue = port.get_port_risk(Greek='Vega', step=0.05)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>gbm_2_Vega</th>\n",
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       "      <th rowspan=\"2\" valign=\"top\">0.80</th>\n",
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       "      <td>0.400000</td>\n",
       "      <td>0.160000</td>\n",
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       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>77.334907</td>\n",
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       "      <th rowspan=\"2\" valign=\"top\">0.85</th>\n",
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       "      <td>0.430000</td>\n",
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       "      <th>value</th>\n",
       "      <td>80.843542</td>\n",
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       "      <th rowspan=\"2\" valign=\"top\">0.90</th>\n",
       "      <th>factor</th>\n",
       "      <td>0.450000</td>\n",
       "      <td>0.180000</td>\n",
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       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>84.336475</td>\n",
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       "      <th rowspan=\"2\" valign=\"top\">0.95</th>\n",
       "      <th>factor</th>\n",
       "      <td>0.480000</td>\n",
       "      <td>0.190000</td>\n",
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       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>87.812380</td>\n",
       "      <td>90.351955</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1.00</th>\n",
       "      <th>factor</th>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.200000</td>\n",
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       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>91.269955</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1.05</th>\n",
       "      <th>factor</th>\n",
       "      <td>0.530000</td>\n",
       "      <td>0.210000</td>\n",
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       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>94.708426</td>\n",
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       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1.10</th>\n",
       "      <th>factor</th>\n",
       "      <td>0.550000</td>\n",
       "      <td>0.220000</td>\n",
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       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>98.125972</td>\n",
       "      <td>93.137955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1.15</th>\n",
       "      <th>factor</th>\n",
       "      <td>0.580000</td>\n",
       "      <td>0.230000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>101.519533</td>\n",
       "      <td>94.045955</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">1.20</th>\n",
       "      <th>factor</th>\n",
       "      <td>0.600000</td>\n",
       "      <td>0.240000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>104.887072</td>\n",
       "      <td>95.013955</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              gbm_2_Vega  gbm_1_Vega\n",
       "dim_0 dim_1                         \n",
       "0.80  factor    0.400000    0.160000\n",
       "      value    77.334907   87.597955\n",
       "0.85  factor    0.430000    0.170000\n",
       "      value    80.843542   88.473955\n",
       "0.90  factor    0.450000    0.180000\n",
       "      value    84.336475   89.377955\n",
       "0.95  factor    0.480000    0.190000\n",
       "      value    87.812380   90.351955\n",
       "1.00  factor    0.500000    0.200000\n",
       "      value    91.269955   91.269955\n",
       "1.05  factor    0.530000    0.210000\n",
       "      value    94.708426   92.143955\n",
       "1.10  factor    0.550000    0.220000\n",
       "      value    98.125972   93.137955\n",
       "1.15  factor    0.580000    0.230000\n",
       "      value   101.519533   94.045955\n",
       "1.20  factor    0.600000    0.240000\n",
       "      value   104.887072   95.013955"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vegas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>0.85</th>\n",
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       "      <th>0.90</th>\n",
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       "      <td>-6.933480</td>\n",
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       "      <th>1.00</th>\n",
       "      <th>value</th>\n",
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       "      <th>1.05</th>\n",
       "      <th>value</th>\n",
       "      <td>3.438471</td>\n",
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       "    <tr>\n",
       "      <th>1.10</th>\n",
       "      <th>value</th>\n",
       "      <td>6.856017</td>\n",
       "      <td>1.868</td>\n",
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       "    <tr>\n",
       "      <th>1.15</th>\n",
       "      <th>value</th>\n",
       "      <td>10.249578</td>\n",
       "      <td>2.776</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1.20</th>\n",
       "      <th>value</th>\n",
       "      <td>13.617117</td>\n",
       "      <td>3.744</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             gbm_2_Vega  gbm_1_Vega\n",
       "dim_0 dim_1                        \n",
       "0.80  value  -13.935048      -3.672\n",
       "0.85  value  -10.426413      -2.796\n",
       "0.90  value   -6.933480      -1.892\n",
       "0.95  value   -3.457575      -0.918\n",
       "1.00  value    0.000000       0.000\n",
       "1.05  value    3.438471       0.874\n",
       "1.10  value    6.856017       1.868\n",
       "1.15  value   10.249578       2.776\n",
       "1.20  value   13.617117       3.744"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vegas.loc(axis=0)[:, 'value'] - benchvalue"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Copyright, License & Disclaimer**\n",
    "\n",
    "© Dr. Yves J. Hilpisch | The Python Quants GmbH\n",
    "\n",
    "DX Analytics (the \"dx library\" or \"dx package\") is licensed under the GNU Affero General\n",
    "Public License version 3 or later (see http://www.gnu.org/licenses/).\n",
    "\n",
    "DX Analytics comes with no representations or warranties, to the extent\n",
    "permitted by applicable law.\n",
    "\n",
    "http://tpq.io | [dx@tpq.io](mailto:team@tpq.io) |\n",
    "http://twitter.com/dyjh\n",
    "\n",
    "<img src=\"http://hilpisch.com/tpq_logo.png\" alt=\"The Python Quants\" width=\"35%\" align=\"right\" border=\"0\"><br>\n",
    "\n",
    "**Quant Platform** | http://pqp.io\n",
    "\n",
    "**Python for Finance Training** | http://training.tpq.io\n",
    "\n",
    "**Certificate in Computational Finance** | http://compfinance.tpq.io\n",
    "\n",
    "**Derivatives Analytics with Python (Wiley Finance)** |\n",
    "http://dawp.tpq.io\n",
    "\n",
    "**Python for Finance (2nd ed., O'Reilly)** |\n",
    "http://py4fi.tpq.io"
   ]
  }
 ],
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