riskless-yield-construction-example.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "stylish-belief",
   "metadata": {},
   "source": [
    "## Constructing a riskless yield curve for USD\n",
    "The first thing we need to do to price any option on a US equity is construct the so-called riskless yield curve for USD. This is because pricing of derivatives is done in _the risk-neutral world_ where all investors are assumed not to require a premium for additional risks, hence future cashflows are discounted using the riskless rate to obtain the NPV of the cashflow.\n",
    "\n",
    "I use the Fed Funds effective rate and US Treasury Yields as proxies for riskless rates. Ideally, using OIS swap rates might be better as treasury yields tend to be slightly lower given the preferred tax treatment of treasuries. However US Treasury Yields are available for free from [FRED](https://fred.stlouisfed.org) with daily frequency while OIS swap rates re not, and the difference is pretty small. Also it'd be better to use treasury spot rates (aka zero-rates) rather than treasury yields. However, treasury spot rates are not made avaliable by FRED.\n",
    "\n",
    "I use the following dataseries from FRED to accomplish the task:\n",
    "* DFF &mdash; Federal Funds Effective Rate (daily frequency)\n",
    "* DGS1MO &mdash; Market Yield on U.S. Treasury Securities at 1-Month Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* DGS3MO &mdash; Market Yield on U.S. Treasury Securities at 3-Month Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* DGS6MO &mdash; Market Yield on U.S. Treasury Securities at 6-Month Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* DGS1 &mdash; Market Yield on U.S. Treasury Securities at 1-Year Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* DGS2 &mdash; Market Yield on U.S. Treasury Securities at 2-Year Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* DGS3 &mdash; Market Yield on U.S. Treasury Securities at 3-Year Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* DGS5 &mdash; Market Yield on U.S. Treasury Securities at 5-Year Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* DGS7 &mdash; Market Yield on U.S. Treasury Securities at 7-Year Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* DGS10 &mdash; Market Yield on U.S. Treasury Securities at 10-Year Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* DGS20 &mdash; Market Yield on U.S. Treasury Securities at 20-Year Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "* DGS30 &mdash; Market Yield on U.S. Treasury Securities at 30-Year Constant Maturity, Quoted on an Investment Basis (daily frequency)\n",
    "\n",
    "In the `pricing.curves.YieldCurve` class I use cubic splines by default to interpolate when constructing the curve. See [this article](http://web.math.ku.dk/~rolf/HaganWest.pdf) for more details on interpolation methods if you want to know more. Cubic splines is pretty advanced."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "quick-switzerland",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Uncomment if running in Google Colaboratory, otherwise the import of the curves module in the cell below will fail\n",
    "#!git clone -l -s https://github.com/ilchen/options-pricing.git cloned-repo\n",
    "#%cd cloned-repo\n",
    "\n",
    "# Install the latest version of pandas datareader\n",
    "#!pip install pandas-datareader -U"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "welsh-collins",
   "metadata": {},
   "outputs": [],
   "source": [
    "import locale\n",
    "from datetime import date, datetime\n",
    "\n",
    "from dateutil.relativedelta import relativedelta\n",
    "import pandas_datareader.data as web\n",
    "import yfinance as yfin\n",
    "from pandas.tseries.offsets import BDay\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "from volatility import parameter_estimators\n",
    "from volatility import volatility_trackers\n",
    "from pricing import curves, options\n",
    "\n",
    "_ = locale.setlocale(locale.LC_ALL, '')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "automatic-uzbekistan",
   "metadata": {},
   "outputs": [],
   "source": [
    "today = date.today()\n",
    "\n",
    "\n",
    "# Constructing the riskless yield curve based on the current fed funds rate and treasury yields\n",
    "data = web.get_data_fred(\n",
    "    ['DFF', 'DGS1MO', 'DGS3MO', 'DGS6MO', 'DGS1', 'DGS2', 'DGS3', 'DGS5', 'DGS7', 'DGS10', 'DGS20', 'DGS30'],\n",
    "    today - BDay(3), today)\n",
    "data.dropna(inplace=True)\n",
    "\n",
    "cur_date_curve = data.index[-1].date()\n",
    "\n",
    "# Convert to percentage points\n",
    "data /= 100.\n",
    "\n",
    "# Some adjustments are required to bring FED Funds rate to the same day count convention and compounding frequency\n",
    "# as treasury yields (actual/actual with semi-annual compounding):\n",
    "# 1. https://www.federalreserve.gov/releases/h15/default.htm -> day count convention for Fed Funds Rate needs\n",
    "# to be changed to actual/actual\n",
    "# 2. Conversion to APY: https://home.treasury.gov/policy-issues/financing-the-government/interest-rate-statistics/interest-rates-frequently-asked-questions\n",
    "data.DFF *= (366 if curves.YieldCurve.is_leap_year(cur_date_curve.year) else 365) / 360 # to x/actual\n",
    "data.DFF = 2 * (np.sqrt(data.DFF + 1) - 1)\n",
    "\n",
    "offsets = [relativedelta(), relativedelta(months=+1), relativedelta(months=+3), relativedelta(months=+6),\n",
    "           relativedelta(years=+1), relativedelta(years=+2), relativedelta(years=+3), relativedelta(years=+5),\n",
    "           relativedelta(years=+7), relativedelta(years=+10), relativedelta(years=+20),\n",
    "           relativedelta(years=+30)]\n",
    "\n",
    "# Define the riskless yield curve\n",
    "curve = curves.YieldCurve(today, offsets, data[cur_date_curve:cur_date_curve + BDay()].to_numpy()[0, :],\n",
    "                          compounding_freq=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "normal-sixth",
   "metadata": {},
   "source": [
    "### Optional: Visualizing the riskless yield curve for USD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "institutional-aquarium",
   "metadata": {},
   "outputs": [
    {
     "data": {
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SJOk4HW2JFIG7QghPhRBuOfhkCGEM8EfA/xx0agywsc/3m9LH7gYmAo8BXwwh3AA8HWPcMrD4f3DP0lR3tX8/pP0mVhaxzj2RJEmSJEmSjkuIMfY/KIQxMcbNIYQaUgXQ+2KMD/Q5/xPg32OMj4UQvg38Osb40xDCh4GCGOM/pcd9DNgXY/y3Po/NBe4EbgT+ERgP3BpjvP0QOW4BbgGorq4++7bbbjtw7t8XttPU1svnLikkhHDg+Dee7+CF5h7+c37R0X8qx6ilpYWSkpKT/joDlcRcScwEycyVxEyQzFxJzATJzJXETJDMXEnMBMnMlcRMkMxcScwE5hqIJGaCZOZKYiZIZq4kZoJk5kpiJkhmriRmgmTmSmImOPW55s+f/1SM8ZxDnowxDugGfBL48EHH1gLr0rcWUkvaXg28Cfhqn3FfBd500GP/EngbcBWp/ZOygd/3l6OhoSHut7e9K079u9/GT/9qcTzYl+5bGSd85Nexpb3rZedOtPvvv/+kv8axSGKuJGaKMZm5kpgpxmTmSmKmGJOZK4mZYkxmriRmijGZuZKYKcZk5kpiphjNNRBJzBRjMnMlMVOMycyVxEwxJjNXEjPFmMxcScwUYzJzJTFTjKc+F7AwHqaL6Xc5WwihOIRQuv8+cDXwwkFF1KQY48QY40Tgp8C7Y4y/IDXD6OoQwogQwoj0Y+/s89wjgOuAW0ntkdRLaulcYX+5+npwxTY6e3pfsh/SfhMqUzOQ1rukTZIkSZIk6ZgdzZ5ItcBDIYRFwBPAb2KMd4QQ3hVCeNeRHhhj3EFqw+wn07dPpY/t93HgMzHGXlLl0iXA88B3B/Im7l7aSHlhLudMGPGycxMrU1doW+cV2iRJkiRJko5ZTn8DYoxrgDmHOP6Vw4x/20Hffwv41mHGfrDP/XZSM5UGpLunl/uXNXH59Bpysl/eiU2sSpVIa71CmyRJkiRJ0jE72quzJdbTG3axs63rZVdl268kP4fq0nzWOxNJkiRJkiTpmA36EumepY3kZgcubag67JiJlUWsa3ZPJEmSJEmSpGM1+EukJY1cUF9JaUHuYcdMrCxmrTORJEmSJEmSjtmgLpFWb2thTXMrVx3iqmx9TawqZtveDlo7uk9RMkmSJEmSpKFlUJdI9yxpBOCKw+yHtJ9XaJMkSZIkSTo+g7tEWtrIzFFljKkoPOK4iVVFAO6LJEmSJEmSdIwGbYnUE+Gp9Tu5sp+lbOBMJEmSJEmSpOM1aEukfd2R3ghX9bOUDaA4P4fq0nzWNVsiSZIkSZIkHYtBWyK1dUFtWT6njSk7qvGTKoudiSRJkiRJknSMBm2JtK87cuWMWkIIRzV+YlURa90TSZIkSZIk6ZgM2hIpwlHth7TfxKpimls6aOnoPnmhJEmSJEmShqhBWyIFYG595VGPP7C5tvsiSZIkSZIkDdigLZEKcwIFudlHPd4rtEmSJEmSJB27QVsileYd3V5I+02sKgJg/Xb3RZIkSZIkSRqoQVsiFeYMbHxRXg41pfmsdTmbJEmSJEnSgA3aEulYTKwqdk8kSZIkSZKkYzCsSqRJlcWsczmbJEmSJEnSgA2rEmlCVRHNLR3sbe/KdBRJkiRJkqRBZViVSJPSV2hzc21JkiRJkqSBGVYl0sSqVInk5tqSJEmSJEkDM6xKpAmVRQCs326JJEmSJEmSNBDDqkQqysuhtiyftc0uZ5MkSZIkSRqIYVUiAUysLGadM5EkSZIkSZIGZNiVSJOqil3OJkmSJEmSNEDDrkSaUFlMc0sne9u7Mh1FkiRJkiRp0Bh2JdKkqtTm2uvcF0mSJEmSJOmoDbsSaWJVMYD7IkmSJEmSJA3AsCuRJoxMl0jNlkiSJEmSJElHa9iVSIV52dSVFbDWmUiSJEmSJElHbdiVSAATq4pYv909kSRJkiRJko7W8CyRKotdziZJkiRJkjQAw7NEqipme2sne9q7Mh1FkiRJkiRpUBieJVKlm2tLkiRJkiQNxPAskaqKAFjnvkiSJEmSJElHZViWSBNGOhNJkiRJkiRpIIZliVSYl82o8gJLJEmSJEmSpKM0LEskSF+hbbslkiRJkiRJ0tEYviVSVZF7IkmSJEmSJB2l4VsiVRazo7WT3fu6Mh1FkiRJkiQp8YZviVSV2lx7vUvaJEmSJEmS+jV8S6TKVIm01s21JUmSJEmS+jVsS6QJlUUArGt2XyRJkiRJkqT+DNsSqSA3m9HlBS5nkyRJkiRJOgrDtkQCmFBZzFpLJEmSJEmSpH4N6xJpYlUx69wTSZIkSZIkqV/DukSaVFXEzrYudrd1ZTqKJEmSJElSog3rEmlC+gpt61zSJkmSJEmSdETDukSqr0qVSGtd0iZJkiRJknREw7pEGl9ZRFaANZZIkiRJkiRJRzSsS6T8nGzGjihizbaWTEeRJEmSJElKtGFdIgHUVxezZpszkSRJkiRJko5k2JdIk6qKWdvcSm9vzHQUSZIkSZKkxBr2JVJ9dQn7unpo3Nue6SiSJEmSJEmJNexLpMnpK7S5pE2SJEmSJOnwhn2JVF9dAuDm2pIkSZIkSUcw7Euk2rJ8ivKyWe1MJEmSJEmSpMMa9iVSCIFJVcWsabZEkiRJkiRJOpxhXyJBaknb2maXs0mSJEmSJB2OJRJQX1XMpp37aO/qyXQUSZIkSZKkRDqqEimEsC6E8HwI4dkQwsJDnH9zCOG59JhHQghz+py7NoSwPISwKoTwt32Ofz/9mH/uc+wfQgivPs73NGD11cXECOu3t53ql5YkSZIkSRoUcgYwdn6Msfkw59YCl8UYd4YQXgF8DTg/hJAN/DdwFbAJeDKEcHv6dffFGGeHEO4OIZQDRcD5McZ/OuZ3c4zqq/5whbZpdaWn+uUlSZIkSZIS74QsZ4sxPhJj3Jn+9jFgbPr+ecCqGOOaGGMn8CPgRqALKAwhZAG5QA/wKeATJyLPQE2qLgZwc21JkiRJkqTDONoSKQJ3hRCeCiHc0s/YPwd+l74/BtjY59wmYEyMcSmwDXga+BUwBciKMT591MlPoJL8HGrL8lmzzRJJkiRJkiTpUEKMsf9BIYyJMW4OIdQAdwPvizE+cIhx84EvAxfHGLeHEF4HXBtjfHv6/M2klqy996DH/Qp4J/CnwBzg7hjj1w/x/LcAtwBUV1effdtttw3s3R7Bvzyxj84e+NjcwmN+jpaWFkpKSk5YphMlibmSmAmSmSuJmSCZuZKYCZKZK4mZIJm5kpgJkpkriZkgmbmSmAnMNRBJzATJzJXETJDMXEnMBMnMlcRMkMxcScwEycyVxExw6nPNnz//qRjjOYc8GWMc0A34JPDhQxyfDawGGvocmwvc2ef7jwIfPehxN6afswH4VvrYnUDRkXI0NDTEE+mj//dcnP3JO2Nvb+8xP8f9999/4gKdQEnMlcRMMSYzVxIzxZjMXEnMFGMycyUxU4zJzJXETDEmM1cSM8WYzFxJzBSjuQYiiZliTGauJGaKMZm5kpgpxmTmSmKmGJOZK4mZYkxmriRmivHU5wIWxsN0Mf0uZwshFIcQSvffB64GXjhozHjg/4CbY4wr+px6EpgaQpgUQsgD3gjc3udxucAHgM8DhaSWzQFkA3n9ZTuR6quK2b2vix2tnafyZSVJkiRJkgaFo7k6Wy3w8xDC/vE/iDHeEUJ4F0CM8SvAx4FK4Mvpcd0xxnNijN0hhPeSmlmUTWqm0eI+z/0e4DsxxrYQwnNAUQjheeC3McZdJ+YtHp3J1ampYWubW6ksyT+VLy1JkiRJkpR4/ZZIMcY1pPYpOvj4V/rcfzvw9sM8/rfAbw9z7j/73I/Am/pNfJLU779C27ZWzpk4MlMxJEmSJEmSEulor8425I2pKCQ3O7C6uSXTUSRJkiRJkhLHEiktJzuLCZXFrNnWmukokiRJkiRJiWOJ1Ed9VTFrtjkTSZIkSZIk6WCWSH3UV5ewYUcb3T29mY4iSZIkSZKUKJZIfdRXF9PVE9m0c1+mo0iSJEmSJCWKJVIf9VXpK7S5ubYkSZIkSdJLWCL1UV9dAuDm2pIkSZIkSQexROpjZHEeFUW5rLZEkiRJkiRJeglLpIPUVxWz1uVskiRJkiRJL2GJdJBJVSUuZ5MkSZIkSTqIJdJB6quLadrbwd72rkxHkSRJkiRJSgxLpINMrk5doW1ts7ORJEmSJEmS9rNEOsj+K7RZIkmSJEmSJP2BJdJBJlQWEQJeoU2SJEmSJKkPS6SD5OdkM3ZEIWu2eYU2SZIkSZKk/SyRDqHeK7RJkiRJkiS9hCXSIdRXF7O2uZXe3pjpKJIkSZIkSYlgiXQI9dUl7OvqoXFve6ajSJIkSZIkJYIl0iHUVxUDuKRNkiRJkiQpzRLpEOqr95dIbq4tSZIkSZIElkiHVFdWQFFeNqudiSRJkiRJkgRYIh1SCIFJVcWsabZEkiRJkiRJAkukw6qvLmFts8vZJEmSJEmSwBLpsCZVFbNp5z7au3oyHUWSJEmSJCnjLJEOY3J1MTHC+u1tmY4iSZIkSZKUcZZIh1FfVQJ4hTZJkiRJkiSwRDqsSdXFAG6uLUmSJEmShCXSYZXk51BTms+abZZIkiRJkiRJlkhHUF9dzBqv0CZJkiRJkmSJdCT11SWs2dZKjDHTUSRJkiRJkjLKEukI6quK2b2vix2tnZmOIkmSJEmSlFGWSEdQn95ce62ba0uSJEmSpGHOEukI6qtKANxcW5IkSZIkDXuWSEcwdkQhudmB1W6uLUmSJEmShjlLpCPIyc5iQmWxM5EkSZIkSdKwZ4nUj/qqYtZscyaSJEmSJEka3iyR+jGpupgNO9ro7unNdBRJkiRJkqSMsUTqx+SqErp6Ipt27st0FEmSJEmSpIyxROpHfXUxAGvcXFuSJEmSJA1jlkj9qK8uAXBzbUmSJEmSNKxZIvVjRFEu5YW5rGm2RJIkSZIkScOXJVI/QghMqSlhVaPL2SRJkiRJ0vBliXQUGmpLWNG0lxhjpqNIkiRJkiRlhCXSUWioLWVXWxfb9nZkOookSZIkSVJGWCIdhWm1pQAsb9yb4SSSJEmSJEmZYYl0FBrq0iXSVkskSZIkSZI0PFkiHYWqknwqi/NY6ebakiRJkiRpmLJEOkoNtaUuZ5MkSZIkScOWJdJRmlZXysrGvfT2eoU2SZIkSZI0/FgiHaWG2lJaO3vYvGtfpqNIkiRJkiSdcpZIR2laXQkAK1zSJkmSJEmShiFLpKM0pSZ9hTZLJEmSJEmSNAxZIh2l8sJcRpUXsGKrJZIkSZIkSRp+LJEGIHWFtpZMx5AkSZIkSTrlLJEGYFpdKau3tdDd05vpKJIkSZIkSaeUJdIANNSW0tndy/odbZmOIkmSJEmSdEpZIg3AtNrU5truiyRJkiRJkoYbS6QBmFJTQgheoU2SJEmSJA0/lkgDUJiXzYSRRaywRJIkSZIkScPMUZVIIYR1IYTnQwjPhhAWHuJ8CCF8MYSwKoTwXAjhrD7n3hpCWJm+vTV9LD+EcEcI4YUQwrv7jP1a38cmUUNtKctdziZJkiRJkoaZgcxEmh9jPCPGeM4hzr0CmJq+3QL8D0AIYSTwCeB84DzgEyGEEcA1wEPAbODm9Ng5QHaM8eljfC+nxLS6UtZtb6OjuyfTUSRJkiRJkk6ZE7Wc7Ubg1pjyGFARQhhFqiy6O8a4I8a4E7gbuBboAoqAXCCkn+PTwMdOUJ6TZmptKT29kTXbWjMdRZIkSZIk6ZQ52hIpAneFEJ4KIdxyiPNjgI19vt+UPna443cDE4HHgC+GEG4Ano4xbhlY/FPvwBXa3BdJkiRJkiQNIyHG2P+gEMbEGDeHEGpIFUDvizE+0Of8r4HPxRgfSn9/L/ARYB5QEGP8p/TxjwH7Yoz/1uexucCdpGYz/SMwntSsptsPkeMWUsvlqK6uPvu22247pjd9PLp7I++8u41XTMrldQ15LznX0tJCSUnJKc/UnyTmSmImSGauJGaCZOZKYiZIZq4kZoJk5kpiJkhmriRmgmTmSmImMNdAJDETJDNXEjNBMnMlMRMkM1cSM0EycyUxEyQzVxIzwanPNX/+/KcOs5URxBgHdAM+CXz4oGNfBd7U5/vlwCjgTcBXDzcufewvgbcBV5HaPykb+H1/ORoaGmKmXPUfC+Kff/uJlx2///77T32Yo5DEXEnMFGMycyUxU4zJzJXETDEmM1cSM8WYzFxJzBRjMnMlMVOMycyVxEwxmmsgkpgpxmTmSmKmGJOZK4mZYkxmriRmijGZuZKYKcZk5kpiphhPfS5gYTxMF9PvcrYQQnEIoXT/feBq4IWDht0OvCV9lbYLgN0xxhdJzTC6OoQwIr2h9tXpY/ufewRwHXArqT2SekktnSvsL1cmNdSWstzlbJIkSZIkaRg5mj2RaoGHQgiLgCeA38QY7wghvCuE8K70mN8Ca4BVwNeBdwPEGHeQ2jD7yfTtU+lj+30c+EyMsZdUuXQJ8Dzw3eN+ZyfRtNpSNu7YR2tHd6ajSJIkSZIknRI5/Q2IMa4B5hzi+Ff63I/Aew7z+G8B3zrMuQ/2ud9OaqZS4jXUpTbXXtnUwhnjKjIbRpIkSZIk6RQ42quzqY8DV2jb6pI2SZIkSZI0PFgiHYNxI4soyM1ihfsiSZIkSZKkYcIS6RhkZwWm1JS4ubYkSZIkSRo2LJGOUUNtqTORJEmSJEnSsGGJdIym1ZbSuKeDXW2dmY4iSZIkSZJ00lkiHaP9V2hb0diS4SSSJEmSJEknnyXSMdp/hTb3RZIkSZIkScOBJdIxGlVeQGl+Diu2WiJJkiRJkqShzxLpGIUQaKgrdSaSJEmSJEkaFiyRjkNDbSkrG/cSY8x0FEmSJEmSpJPKEuk4TKstYWdbF9taOjIdRZIkSZIk6aSyRDoOB67QttUrtEmSJEmSpKHNEuk4NHiFNkmSJEmSNExYIh2HqpJ8KovzvEKbJEmSJEka8iyRjlNDrVdokyRJkiRJQ58l0nGaVpe6Qltvr1dokyRJkiRJQ5cl0nFqqC2ltbOHzbv2ZTqKJEmSJEnSSWOJdJym1ZUAsLLJJW2SJEmSJGnoskQ6TlP3X6Fta0uGk0iSJEmSJJ08lkjHqawgl9HlBaxwc21JkiRJkjSEWSKdAA11pSzfaokkSZIkSZKGLkukE6ChtpRV21ro8QptkiRJkiRpiLJEOgEaakvp7O6lqc0SSZIkSZIkDU2WSCfAtPTm2ptaejOcRJIkSZIk6eSwRDoBptSUEAJssUSSJEmSJElDlCXSCVCYl82EkUXORJIkSZIkSUOWJdIJ0lBbyua9lkiSJEmSJGloskQ6QabVlbK1LdLe1ZPpKJIkSZIkSSecJdIJMnNUGb0Rlm/dm+kokiRJkiRJJ5wl0gkye1wFAIs27cpoDkmSJEmSpJPBEukEGV1eQFkeLNq4O9NRJEmSJEmSTjhLpBMkhMCk8myecyaSJEmSJEkagiyRTqBJ5Vms2tZCS0d3pqNIkiRJkiSdUJZIJ9Ck8ixihBc2u6RNkiRJkiQNLZZIJ9Ck8mwAl7RJkiRJkqQhxxLpBCrLC4wdUciiTc5EkiRJkiRJQ4sl0gk2Z2wFizbuynQMSZIkSZKkE8oS6QSbPbacTTv3sb2lI9NRJEmSJEmSThhLpBNs9tgKAJ5zc21JkiRJkjSEWCKdYKePLScEeG6jJZIkSZIkSRo6LJFOsJL8HCZXl3iFNkmSJEmSNKRYIp0Es8eWs2jTbmKMmY4iSZIkSZJ0QlginQRnjKuguaWDLbvbMx1FkiRJkiTphLBEOgkObK69cVdGc0iSJEmSJJ0olkgnwYxRpeRmBxZtcnNtSZIkSZI0NFginQT5OdlMrytzc21JkiRJkjRkWCKdJLPHlvP8pt309rq5tiRJkiRJGvwskU6SOWMr2NvRzdrtrZmOIkmSJEmSdNwskU6S2ePKAVjk5tqSJEmSJGkIsEQ6SaZUl1CYm81zbq4tSZIkSZKGAEukkyQnO4vTx5SzyM21JUmSJEnSEGCJdBLNHlvOki176OrpzXQUSZIkSZKk42KJdBLNHldBR3cvy7fuzXQUSZIkSZKk42KJdBLNGZvaXNt9kSRJkiRJ0mBniXQSjR9ZREVRLs+5L5IkSZIkSRrkLJFOohACp48p59mNuzIdRZIkSZIk6bhYIp1kc8ZWsLKphX2dPZmOIkmSJEmSdMwskU6y2WPL6emNLN7ivkiSJEmSJGnwskQ6yc4YVwHAIjfXliRJkiRJg5gl0klWU1ZAXVmBm2tLkiRJkqRB7ahLpBBCdgjhmRDCrw9xbnwI4f70+edCCK/sc+6jIYRVIYTlIYRr0seqQwgPhRBeCCG8us/YX4YQRh/ne0qc2WPLec6ZSJIkSZIkaRAbyEykvwSWHubcPwC3xRjPBN4IfBkghDAz/f0s4FrgyyGEbOBNwFeA84APpMdeDzwTY9wy8LeRbHPGVbC2uZXdbV2ZjiJJkiRJknRMjqpECiGMBV4FfOMwQyJQlr5fDuwvgm4EfhRj7IgxrgVWkSqOuoAiIB/oCSHkkCqTPn8M7yHxZo8tB+C5zbsyG0SSJEmSJOkYhRhj/4NC+CnwWaAU+HCM8bqDzo8C7gJGAMXAlTHGp0IIXwIeizF+Lz3um8DvgLuBHwC1wEdIzVTaE2P8dj85bgFuAaiurj77tttuO/p3egq0tLRQUlLysuOtXZH33NvGa6fmcv3kvMTkyqQkZoJk5kpiJkhmriRmgmTmSmImSGauJGaCZOZKYiZIZq4kZgJzDUQSM0EycyUxEyQzVxIzQTJzJTETJDNXEjNBMnMlMROc+lzz589/KsZ4ziFPxhiPeAOuA76cvj8P+PUhxnwI+Kv0/bnAElKznL4E3NRn3DeB1x302BGkSqUS4OvAT4G5/eVqaGiISXP//fcf9txln78vvuM7T566MH0cKVemJDFTjMnMlcRMMSYzVxIzxZjMXEnMFGMycyUxU4zJzJXETDEmM1cSM8VoroFIYqYYk5kriZliTGauJGaKMZm5kpgpxmTmSmKmGJOZK4mZYjz1uYCF8TBdzNEsZ7sIuCGEsA74EXB5COF7B435c+C2dCn1KFAAVAGbgXF9xo1NH+vrY8BnSO2T9BDwVuCTR5FrUJk9tsLNtSVJkiRJ0qDVb4kUY/xojHFsjHEiqU2y74sx3nTQsA3AFQAhhBmkSqRtwO3AG0MI+SGEScBU4In9DwohTAXGxhgXkNojqZfU/kqFx/m+EmfOuAq27mmnaU97pqNIkiRJkiQN2ECuzvYSIYRPhRBuSH/7V8A7QgiLgB8Cb0vPglpMaobSEuAO4D0xxp4+T/MZ4O/T938I/AXwJPCFY82VVHPSm2svcjaSJEmSJEkahHIGMjg9Y2hB+v7H+xxfQmrZ26Ee8xlSZdGhzr2+z/0m4MKB5BlMZo0uJzsrsGjjLq6aWZvpOJIkSZIkSQNyzDORNDCFedlMrSlh0aZdmY4iSZIkSZI0YJZIp9CcsRU8v3n3/qvSSZIkSZIkDRqWSKfQ7HHl7GrrYsOOtkxHkSRJkiRJGhBLpFNoztgKAJ7duCujOSRJkiRJkgbKEukUmlZXSlFeNgvX7cx0FEmSJEmSpAGxRDqFcrOzOGfiSB5dsz3TUSRJkiRJkgbEEukUm1tfyaqmFpr2tmc6iiRJkiRJ0lGzRDrF5k6uBOCxNTsynESSJEmSJOnoWSKdYqeNLqMkP4dHV7ukTZIkSZIkDR6WSKdYTnYW500ayWPuiyRJkiRJkgYRS6QMmFtfydrmVrbudl8kSZIkSZI0OFgiZcD+fZEeXdOc4SSSJEmSJElHxxIpA2aMKqOswH2RJEmSJEnS4GGJlAHZWYHz6yt51H2RJEmSJEnSIGGJlCFz6yvZuGMfm3a2ZTqKJEmSJElSvyyRMuTAvkguaZMkSZIkSYOAJVKGTKstZURRrkvaJEmSJEnSoGCJlCFZWYEL6it5bPV2YoyZjiNJkiRJknRElkgZNHdyJVt2t7Nhh/siSZIkSZKkZLNEyqC59e6LJEmSJEmSBgdLpAyaUlNCVUm++yJJkiRJkqTEs0TKoBACF9SP5FH3RZIkSZIkSQlniZRhcydX0rS3gzXNrZmOIkmSJEmSdFiWSBnmvkiSJEmSJGkwsETKsElVxdSWuS+SJEmSJElKNkukDAshMLe+ksfXuC+SJEmSJElKLkukBJg7uZLmlk5WNrVkOookSZIkSdIhWSIlwNz6KsB9kSRJkiRJUnJZIiXAuJGFjKkotESSJEmSJEmJZYmUACEELqiv5LG12+ntdV8kSZIkSZKUPJZICTF3ciW72rpYtnVvpqNIkiRJkiS9jCVSQsydXAnAo2tc0iZJkiRJkpLHEikhxlQUMn5kkfsiSZIkSZKkRLJESpALJ1fy+Nrt9LgvkiRJkiRJShhLpASZO7mSve3dLNmyJ9NRJEmSJEmSXsISKUHm1u/fF6k5w0kkSZIkSZJeyhIpQWrKCqivLnZfJEmSJEmSlDiWSAkzt76SJ9ftpLunN9NRJEmSJEmSDrBESpi5kytp6ejm+c27Mx1FkiRJkiTpAEukhLngwL5ILmmTJEmSJEnJYYmUMFUl+TTUlrgvkiRJkiRJShRLpAS6ZGo1j6/ZQWtHd6ajSJIkSZIkAZZIiXTljFo6e3p5cGVzpqNIkiRJkiQBlkiJdM7EEZQX5nLP0sZMR5EkSZIkSQIskRIpNzuL+dOquW9ZEz29MdNxJEmSJEmSLJGS6sqZtexo7eSZDTszHUWSJEmSJMkSKakubagmNztwt0vaJEmSJElSAlgiJVRZQS4X1FdyzxJLJEmSJEmSlHmWSAl25YxaVm9rZc22lkxHkSRJkiRJw5wlUoJdMaMGgHuXNmU4iSRJkiRJGu4skRJs7IgiZowqc18kSZIkSZKUcZZICXfVjBoWrtvBztbOTEeRJEmSJEnDmCVSwl05s5beCPcvd0mbJEmSJEnKHEukhDttdDm1Zfnc45I2SZIkSZKUQZZICZeVFbh8ei2/X76Nju6eTMeRJEmSJEnDlCXSIHDVzBpaO3t4bM2OTEeRJEmSJEnDlCXSIHDh5CoKc7O5Z4lL2iRJkiRJUmZYIg0CBbnZXDK1inuWNhJjzHQcSZIkSZI0DFkiDRJXzqzlxd3tLN6yJ9NRJEmSJEnSMHTUJVIIITuE8EwI4deHOf/6EMKSEMLiEMIP+hx/awhhZfr21vSx/BDCHSGEF0II7+4z9mshhLOO5w0NVZdPryEEvEqbJEmSJEnKiIHMRPpLYOmhToQQpgIfBS6KMc4CPpA+PhL4BHA+cB7wiRDCCOAa4CFgNnBzeuwcIDvG+PQxvZMhrqokn7PGj7BEkiRJkiRJGXFUJVIIYSzwKuAbhxnyDuC/Y4w7AWKMTenj1wB3xxh3pM/dDVwLdAFFQC4Q0mM/DXzsWN7EcHHljFpe2LyHF3fvy3QUSZIkSZI0zISj2ag5hPBT4LNAKfDhGON1B53/BbACuAjIBj4ZY7wjhPBhoCDG+E/pcR8D9gH/CdwKzAD+FWgBzooxfrKfHLcAtwBUV1effdtttx3t+zwlWlpaKCkpOWnPv6Wll797aB9vmZnH5eNzE5PrWCQxEyQzVxIzQTJzJTETJDNXEjNBMnMlMRMkM1cSM0EycyUxE5hrIJKYCZKZK4mZIJm5kpgJkpkriZkgmbmSmAmSmSuJmeDU55o/f/5TMcZzDnkyxnjEG3Ad8OX0/XnArw8x5tfAz0nNLJoEbAQqgA8D/9Bn3MdIlVB9H5sL3EeqoPoP4KfADf3lamhoiElz//33n9Tn7+3tjZd9/r74lm8+PqDHnexcxyKJmWJMZq4kZooxmbmSmCnGZOZKYqYYk5kriZliTGauJGaKMZm5kpgpRnMNRBIzxZjMXEnMFGMycyUxU4zJzJXETDEmM1cSM8WYzFxJzBTjqc8FLIyH6WKOZjnbRcANIYR1wI+Ay0MI3ztozCbg9hhjV4xxLalZSVOBzcC4PuPGpo/19W5Ss5IuAHYDbwD+6ihyDTshBK6cUcujq7fT0tGd6TiSJEmSJGkY6bdEijF+NMY4NsY4EXgjcF+M8aaDhv2C1CwlQghVQAOwBrgTuDqEMCK9ofbV6WOkx44gNdPpVlJ7JPUCESg8rnc1hF05s5bOnl4eXLEt01EkSZIkSdIwMpCrs71ECOFTIYQb0t/eCWwPISwB7gf+Osa4Pca4g9SG2U+mb59KH9vv48BnYoy96ee4BHge+O6x5hrqzpkwgvLCXO72Km2SJEmSJOkUyhnI4BjjAmBB+v7H+xyPwIfSt4Mf8y3gW4d5vg/2ud9OaqaSjiAnO4vLp9dw/7Imenoj2Vmh/wdJkiRJkiQdp2OeiaTMuXJGLTvbunh6w85MR5EkSZIkScOEJdIgdGlDFbnZgXuWuKRNkiRJkiSdGpZIg1BpQS4X1Fe6L5IkSZIkSTplBrQnkpLjqpm1fPyXi1nVtJcpNaWZjiNJkiRJB8QY2dfVQ2tHD60d3bR2drOvs4eO7l46unvo6Oqls6eXjq709929B27dPb30xEhvb6SnF3p6U98fuN8LW7d28KumRWQFCAECgawsgEAIkBUgKwRys7PIzc4iLyeLvOyDv88iNydQkJNNUX4ORXnZFOZmU5SXTVFeDoV5qfu52c69kPazRBqkrplVxyduX8yvFr3IB6+yRJIkSZJ04nT39LKzrYudbZ2s2NlDz9JGdu/rYve+Lvbs6059bd//fRctHd20daYLo45u2rp6iPHYXjsnK5CVFcgO4Q/3999C6mt7ew/r2rYTY6Q3QiQSI/RGgNSx3hjp7ol09vTS2d17zJ9FbnagOD+HsoJcygtzKStM3S8ryKW8KJeyghzKClPnNjb3UL1lN1Ul+YwoyiMvxwJKQ4sl0iBVW1bA3PpKbl+0hQ9cOZUQvEqbJEmSpEOLMbKnvZtte9tp2tPBtpYOtu3tYEdr58tvbZ3saut66RM8vvAl3xbnZR8oTsoKcqkrK6AoP4fivGyK01/7fl+Ul5rpk5+TRX5u+mv6fl52Fvm5qe/zsrOO6nebBQsWMG/evAG9/+7eSFdPL13d6WIpXS61d/XQ1tnDvs6eAzOm2jp7aOvsTn9NlWN72lOF2Z72bpr2tBwo0tq7XlpQ/dvChw7cLyvIobIkn8riPEYW51FZkk91aT61ZfnUlRVQm75VFueR5ZW3NQhYIg1iN54xmo/87Hme37yb2WMrMh1HkiRJUgbs6+zhxd37eHF3Oy/ubmfr7n007umgaW87TXtTZdG2vR10HGI2Tk5WYERx3oGSY8boMiqL8xhRlEdlSerr+pVLueT8s9OzcHIpLcgZdEu8QgjkppezkXdin7uju4e97d3sauvivocfZ/zUmWxv7WR7S6qUa25JlXXrt7fx9IadbG/tfNksrZysQE1pPrXlBdSWFlBXXsDYEYWMHVHE2BGFjBtRRHlR7okNLh0DS6RB7NpZo/jYLxbzy2e3WCJJkiRJQ1Bvb2RbSwebdraxccc+Nu/ax5ZdfyiMXty97+WzhoCKolyqS/KpKcvn3IkjqSlNzYCpLs2nprTgwP2ygpx+Z/4s2LmCOeMqTtI7HPzyc7LJL8mmqiSfTSOymXfaqCOO7+7pZVtLB417Oti6u52mve1s3d1O454OGve0s3pbCw+taqalo/sljystyGHsiCLG9SmXJlYVMamqhLEjCgddsafByRJpECsvyuWyadX8+rkt/N0rZ5Dt9EdJkiRp0NnV1sm67W089mI3i+9fxaad+9i0s41NO/exeec+OnteOoNoZHEedWUFjKko4OwJFYwqL2RUecGBr3XlBRTkZmfo3ag/OdlZ6Z9VIYw79JgYI3v2dbNxZ9uBPwsbd6S+rtveykOrmmnr7PnDc2YFxo8sYlJVcepWnfpaX1VCPNbNqaRDsEQa5G48YzR3L2nk8bXbuXByVabjSJIkSTpIjKnZROu3t6Vvrazb/7W5lT3tfWacLFpOZXEeY0cUMnN0GVfPqn3JkqYxFYUU5lkQDXUhBMqLcikvKue0MeUvOx9jZEdrqnxc29zK2uYW1ja3smZbKw+vbn7JPk0F2TB9ycNMqy1lam0J0+pKmVZbSnVpvnvrasAskQa5K6bXUpyXze3PbrFEkiRJkjJoX2cPa5tbWb2thTXbWlnT3MLqbS2s3dZKa59ZI9lZgTEVhUyoLOLGM8YwobKIiZXFNK5ezB9dcylFef6apiMLIaQ27C7J5+wJI15yrrc3snVPe6pUam7l908voy03m3uXNfLjhRsPjKsoyqWhppSGuhKm1ZYyc3Q5M0aV+udPR+SfjkGuMC+bq2fV8dvnX+Qfb5xFfo7/KiFJkiSdTDtbO1nZ1MKKxr2samo5UBpt3rXvwJgQYHR5IfXVxZxzzkgmVRUfKIvGHGb/mgVNS/0FXsctKyswuqKQ0RWFXDSlinHta5k37wIAmls6WNG4lxVb97KiqYUVW/fyy2e3sDc9Gy4rQH11CaeNLmPW6HJmjUl9LS90U2+l+F+oIeCGM0bz82c288CKZq6aWZvpOJIkSdKQsLO1kxWNe1nZ1MLKxr2saGxhZVMLzS0dB8YU52VTX13CORNH8IbqcdRXp/ahmVRV7LIzJU5VST5VJfkvWcUSY2TL7naWbNnDC5t3s3jLbh5fu4NfPLvlwJhxIws5bXQ5p48t58xxI5g9tpzifOuE4cif+hBw8ZQqRhbn8ctnN1siSZIkSQPU0d3DqqYWlr24l+WNe1n64h6Wbd3Ltr0vLYum1JYyf1o1Dem9ZabWljK6vMB9ZTSohZBaXjmmovAlv09ub+lg8ZY9vLBlN4s3p77+7oWtQGrGUkNtKWeOH8GZ4ys4c1wFk6tLyPJiT0OeJdIQkJudxatOH8VPntpIS0c3JTbCkiRJ0svEGGna28GSLXv4zZpO/u/FZ1i2dQ+rt7XS05u6glVeThZTa0q4dGo10+pSRVGDZZGGocqSfC5tqObShuoDx3a2dvLspl08s2EXz2zYyW+e28IPn9gAQGlBDmeMSxVK502q5KwJFS7PHIL8iQ4RN5wxmu8+tp67l2zlj84cm+k4kiRJUkb19EbWNreyeMtulry4hyVbUrftrZ0Hxoyp2Mn0ulKumlnL9LoyZowqZWJlMTmH2K9IEowozmP+tBrmT6sBUpt4r2lu5ZkNO3l2Y6pc+tL9q+i9bxU5WYHTxpRz/qSRnDdpJOdMGEl5kXsrDXaWSEPE2eNHMKaikNuf3WKJJEmSpGGls7uXFY17eX7z7vSeLntYtnXPgcuc52YHGmpLuXx6DbNGlzFjVBnNq5/jVVfNz3ByaXDLygpMqSlhSk0Jf3zOOAD2tnfx9IZdPLF2O0+s3cH/PryOrz6whhBgWm1pulSqpKczZji9joUl0hCRlRW4fs5ovv7gGra3dFBZkp/pSJIkSdIJ193Ty8qmFp7ftJvnNu/i+U27Wbp1L53dqcKotCCHmaPKeNN545k1upyZo8qYUlNCXs5LZxct2ODSNOlkKC3I5bKGai5LL4Nr7+ph0cZdPLF2B0+s28FPntrEdx5dD8BXlj7IJVOruGhKFedOHOlm9IOAJdIQcuMZo/nK71fz2xe2cvMFEzIdR5IkSTouMUbWbW/j2Y07WbRxN89t2sXiLXvo2F8Y5ecwa0wZb7twIqePKWf22HLGjyxy7yIpQQpyszm/vpLz6ysB6Orp5fnNu/ne3U+ypSeHbz28lq8+sIa87CzOnjCCi9Ol0uljysl2o+7EsUQaQqbXlTK1poTbn91siSRJkqRBZ3tLB4s27eLZDbt4dtNuFm3cxe59XQAU5WVz2uhybrpgArPHlnP6mHImVhZ7NShpkMnNzuKs8SPYMzmPefPm0tbZzZPrdvLwqmYeXNnMv965nH+9czllBTlcPLWKedNqmDetmprSgkxHF5ZIQ0oIgRvPGM2/3bWCzbv2MaaiMNORJEmSpEPq7O5lyYt7eHr9Tp7ZuItnN+5k4459wB8uH/7K0+uYM7aCM8ZXMLWm1FkJ0hBUlJfzkuVvzS0dPLJ6Ow+t3MbvV2zjt89vBWD22HLmTavh8uk1zB5TboGcIZZIQ8wNc8bwb3et4FeLtvCuyyZnOo4kSZIEQNPedp5en7os+NMbdvLcpt0HlqWNKi/gzPEV3HT+BM4YV8HpY8u9NLg0TFWV5HPDnNHcMGc0MUaWvLiHBcu3cd+yJr5030q+eO9KKovzuGxaNZdPr+GSqdWUF3rVt1PF/zIPMeMrizhjXAW/fNYSSZIkSZnR0xtZvnUvT63fwW8WtfOxJ+47MMsoLzuLWWPKuOmCCZw9YQRnjR9BXbnLVCS9XAiBWaPLmTW6nPfMn8LO1k4eWJkqlO5b1sT/Pb2ZnKzABfWVXDOrlqtn1VFb5n9PTiZLpCHoxjNG84+/WsLKxr1MrS3NdBxJkiQNcfs6e1i0aRcL1+3gyXU7eXr9TvZ2dANQkR+YO7Wct1wwkbMmjGDW6DIKcr0Ck6SBG1Gcx41njOHGM8bQ0xt5duNO7lnaxJ2Lt/KxXy7mY79czBnjKrj2tDqumVXHpKriTEceciyRhqBXzR7Fp3+9hNsXbeGvrp6W6TiSJEkaYna0dvLkuh0HSqPFW3bT1RMBmFZbyg1njObciSM5e8IIVi16nPnzz85wYklDTXZW4OwJIzl7wkg+cu10VjXt5Y4XtnLn4kY+97tlfO53y2ioLeGaWalCadboMq/ceAJYIg1BNaUFXDSlil8+u4UPXdWQ6TiSJEka5Br3tPP42h08sXY7T6zdwYrGFgDycrI4Y2wF77iknnMmjuDs8SMpL3rp3iSr/aVN0ikwpaaU915eynsvn8rmXfu4a/FW7ly8lf++fxX/dd8qxo8s4vo5o7h+zmim1ZZaKB0jS6Qh6vo5o/mbnz7Hsxt3ZTqKJEmSBpEYI5t27uOxNanC6Il1O1i/vQ2Akvwczp4wghvPGMN5k0Yye2w5+TkuTZOULGMqCvnTiybxpxdNYntLB/csbeTXz73IV36/hv++fzVTa0q4fs5orps9ivrqkkzHHVQskYaoa0+r4x9+8QK3L9rCZW6LJEmSpMPYXxo9uno7j61J3bbsbgegoiiX8yaO5OYLJnD+pEpmjColJzsrw4kl6ehVluTzhnPH84Zzx9Pc0sHvXtjKrxZt4f/ds4L/uHsFp40p4/rZo3nV7FGZjjooWCINUWUFuVw+rYZfLXqRSy7yX4ckSZL0Bxt3tKULox08tmY7m3elrpxWWZzHBfWVvKt+JOdPqmRqTQlZWS75kDQ0VJXkc/MFE7j5ggm8uHsfv3nuRX713It89nfL+OzvljG1IosthRt41exRlBfm9v+Ew5Al0hB2wxmjuWPxVpZuL+DyTIeRJElSxjTuaeeR1c08smo7j67ZzqadqdJoRFEuF9RX8s7L6rmgPlUauU+IpOFgVHkhb7+knrdfUs+G7W386rktfP/hFfzdz5/nk79azNUza3ntWWO5ZGqVMzD7sEQawi6fXkNpfg6PbOnmPZkOI0mSpFNmV1snj63ZzsOrtvPI6mZWb2sFUsvTzp80krdfPIm5k6ucaSRJwPjKIt4zfwoz2Ujl1DP52VObuH3RFn793ItUl+bz6jNG85qzxjJjVFmmo2acJdIQVpCbzXVzRvOzhRvY095FWYHT8SRJkoaits5unli7gx8t6+Tfnn+QxVv2ECMU5WVz3qSRvOHccVw4uYqZo8osjSTpMEIIzB5bweyxFfz9q2Zy//ImfvbUJv734XV8/cG1zBxVxmvPHssfnTmGkcV5mY6bEZZIQ9wbzh3HD5/YwK8XvcifnD8+03EkSZJ0AnT39PL85t08tLKZh1Y18/SGnXT1RHICnD2xlA9c0cBFUyqZPbaCvByXYUjSQOXlZHHNrDqumVXHjtZObn92Mz97ejOf/vUS/uV3y7j2tDredN54LqgfOayWAVsiDXFzxpYztiTw44UbLZEkSZIGqRgj67a38dDKbTy0qplHVm9nb3s3ADNHlfFnF03iwilVtG98gWuumJvhtJI0tIwszuNtF03ibRdNYtnWPfzoiY3839OpJW+Tqop547njeO3ZY6kqyc901JPOEmmICyFwydhcfrhsF8u37mVaXWmmI0mSJOko7Grr5OFV23lw5TYeXNl84ApqYyoKeeVpo7h4ahUXTq6kss8vLQu2DJ9/DZekTJheV8Ynb5jF375iOr99/kV++MQGPvu7ZfzbXcu5elYdf3LeeObWVw7ZpcOWSMPAhaNz+OnKLn785EY+fv3MTMeRJEnSIXT19PLsxl08uGIbD6xs5rlNu+iNUFqQw4WTK3nXvMlcPKWKiZVFw2rphCQlUUFuNq85ayyvOWssKxv38sMnNvJ/z2ziN8+9yPiRRfzJ+eN547njqCgaWnsnWSINA6V5gatm1vLzZzbxkVdMIz8nO9ORJEmSBKzf3soDK5t5cMU2Hl29nb0d3WQFOGNcBe+7fCqXNlQxZ2yFl5eWpASbWlvKx6+fyd9cO407F2/l+49v4HO/W8b/u3sFrz5jDG+9cCIzRw+NK7tZIg0Trz9nHL99fiv3Lm3ilaePynQcSZKkYamts5vH1+xgwfImfr9iG+u2twGpJWrXzRnNpVOruHByFeVFXlVXkgabgtxsbjxjDDeeMYalL+7h1kfX8/NnNvHjhRs5b+JI3nrhRK6eVUvuIP6HAUukYeKSqdWMLi/gx09utESSJEk6RWKMrGxq4ffLt/H7Fdt4Yt0OOrt7KcjN4sLJVbztwolc2lDNpKpil6hJ0hAyY1QZn33N6fzttdO5beFGbn1sHe/5wdPUlRVw0wXjeeN54wflRtyWSMNEdlbgdWeP5b/uX8WWXfsYXVGY6UiSJElD0t72Lh5e1cyCdHH04u52AKbWlPCWCyZw2bRqzp04koJctxiQpKGuvCiXd1xaz59dPIn7lzXxnUfX8W93reCL967iujmjeMcl9cwYNXiWulkiDSOvO3scX7xvFT99ahPvv2JqpuNIkiQNCftnG92/rIn7lzexcN1Ounsjpfk5XDSlivdfUc2lDdWM8R/xJGnYys4KXDmzlitn1rKqqYVbH13HT5/axP89vZlLplZxy6X1XDylKvGzUi2RhpHxlUVcOLmS2xZu5L3zpwzZSw5KkiSdbO3dkbuXNHL/8iYWLGtiS3q20fS6Ut5+ST3zplVz9oQRg3rfC0nSyTGlpoRP3XgaH7qqge8/voFvP7KOm7/5BNPrSrnl0nqumz2avJxk/v+HJdIw84Zzx/GXP3qWx9Zs58IpVZmOI0mSNGisbW7lvmVN3L+sicdWt9EdF1Kcl81FU6p43xVTuayh2i0DJElHraIoj/fMn8LbL5nEL5/dwtcfWMOHblvE5+9Yzp9dPJE3njeesoJkXWjBEmmYuWZWHWUFOfx44UZLJEmSpCPo7O7libU7UsXR8ibWNrcCqX9BvnJCDm+58mzOmTgysf9aLEkaHPJzsnn9OeN43Vlj+f2KbXztgTX882+X8cV7V/Gm88YxM7s30xEPsEQaZgpys3n1mWP40ZMb+VRbl5ePlSRJ6qNpTzv3L2/ivmVNPLSymdbOHvJysphbX8nbLpzI5dNrGDeyiAULFvgPcpKkEyorKzB/eg3zp9fw/KbdfP3BNXzr4XWEGHly3/P8xWWTGTeyKKMZLZGGodefM45bH13PLxdt5i1zJ2Y6jiRJUsb09kZe2LKbe5emiqPnN+8GYFR5ATeeOYbLp9Vw4ZRKivL8a7Mk6dQ5fWw5X3zTmfz1NdP4+A8f5KcLN/HjJzdy4xmjefe8KUypKclILv/fcBg6bUw5s0aX8eMnN1oiSZKkYaets5uHVjZz37JUcdS0t4MQ4KzxI/jra6ZxxYwaptWWJv4KOZKkoW/cyCLeOiufz950AV97YA0/eGI9P39mM688bRTvnj+ZWaPLT2keS6Rh6vXnjOMTty/mhc27OW3Mqf1DJ0mSdKpt3rWP+5Y2cu+yJh5ZvZ3O7l5K83O4tKGay6fXMG9aNZUl+ZmOKUnSIdWVF/Dx62fy7vmT+dZDa7n10fX85vkXuWJ6De+5fApnjR9xSnJYIg1Trz5jDJ/57VJ+snCjJZIkSRpyensjz2/ezb1LG7l7aRNLX9wDwITKIm46fwJXzKjhXDfFliQNMlUl+fzNtdN556WT+c6j6/jWw2t5zZcf4eIpVXzwqqmcPWHkSX19S6Rhqrwol2tn1fGLZ7fw0VfOoCA3O9ORJEmSjkt7Vw8Pr2rmnqWN3Ls0tUwtK8DZE0bw0VdM54oZtUyuLnaZmiRp0CsvyuX9V0zlzy+exPceW8/XHljDa//nUS5tqOaDV07lzJM0M8kSaRh7w7njuH3RFu5cvJUbzxiT6TiSJEkDtm1vB/cubeSepU08tGob7V29lOTncGlDFVfOqGXetBpGFudlOqYkSSdFcX4O77xsMjfPncCtj67nq79fzR99+REun17DB69s4PSxJ3blkSXSMDa3vpJxIwu5beFGSyRJkjQoxBhZ1dTCXUsauWdpI89u3EWMMKaikDecM44rZ9Zy/qRKl6lJkoaVorwc3nXZZG66YALfeWQdX3tgDdd/6SGunFHLB6+aesI24LZEGsaysgJ/fPY4/uPuFWzc0ca4kUWZjiRJkvQyPb2Rx9Zs554ljdy9tJH129sAmD22nA9d2cCVM2uZXufV1CRJKsnP4T3zp/CWuRP434fX8Y0H1/CqLzZy7aw6PnDVVKbXlR3X81siDXOvPXss/++eFfzkqU186KqGTMeRJEkCoLWjmwdWbOPuJY3c+UIbrV2PkZedxYVTKnnHJfVcOaOWuvKCTMeUJCmRSgtSeya99cKJfOuhtXzrobXcsXgrrz5jNH919bRjnkRiiTTMjako5JKp1fxk4Ubef/kUcrKd+i1JkjKjaW879y5t4u4ljTy0qpnO7l4qinKZU53DzfNnc0lDNSX5/vVVkqSjVV6YywevauBPL5rIVx9Yw7ceWstvn9/KzXMn8N75UxgxwH0D/X9hcdP547nlu09xz9JGrj1tVKbjSJKkYWT1thbuWtzI3Uu28kx6f6NxIwu56fwJXDWzlnMnjuChBx9g3un+HUWSpGNVUZTHR66dzlvmTuD/3b2C/314Lbc9uZF3zZvMn100icK8o7tiuyWSuGJGLWNHFPK/D6+zRJIkSSdVb2/kmY07uWtJI3cvaWTNtlYATh9TzgevbOAq9zeSJOmkGVVeyOdfN4e3X1LP5+9Yxr/euZzvPrqeD141ldeeNbbf1UmWSCI7K/DWuRP5zG+XsmTLHmaOPr6NtiRJkvpq7+rh4VXN3LW4kXuXNdLc0klOVmDu5EreduFErpxRy+iKwkzHlCRp2GioLeUbbz2XJ9bu4LO/W8pHfvY833hwLX9z7fQjPs4SSQC8/pzUVdq+88g6/uV1szMdR5IkDXI7Wzu5d1kTdy/ZygMrmtnX1UNJfg7zplVz1cxa5k2robwwN9MxJUka1s6bNJL/+4sLuXPxVj5/x3LecevCI44/6hIphJANLAQ2xxivO8yY1wI/Bc6NMS5MH/so8OdAD/D+GOOdIYRq4OdABfAPMcZfpMf+EviLGOOWo82lE6O8KJfXnDWGnz61iY+8YjojB7i5liRJ0sYdbdy1pJG7Fm/lyXU76I1QV1bAa88ew9Uz67igvpK8HC/iIUlSkoQQuPa0UVwxo5YfP7mRm//l8GMHMhPpL4GlwCHXOoUQStNjHu9zbCbwRmAWMBq4J4TQALwJ+Arwf8BvgV+EEK4HnrFAypy3XTiR7z++gR89uYF3z5uS6TiSJCnhYowsb9zLnS80cteSrSzesgeAhtoS3j1vClfPquX0MeXubyRJ0iCQm53FTRdM4OYjjDmqEimEMBZ4FfAZ4EOHGfZp4F+Av+5z7EbgRzHGDmBtCGEVcB7QBRQB+UBPCCEH+ABw/dHk0ckxtbaUi6dU8d1H13PLJfX9bqglSZKGn97eyNMbUhtj37l4K+u3txECnDmugo++YjpXz6pjUlVxpmNKkqSTIMQY+x8Uwk+BzwKlwIcPXs4WQjgL+PsY42tDCAvSYxaGEL4EPBZj/F563DeB3wF3Az8AaoGPkJqptCfG+O1+ctwC3AJQXV199m233TaAt3rytbS0UFJSkukYLzOQXM80dfOFpzt4zxn5nFt38rbMGgqf1amSxEyQzFxJzATJzJXETJDMXEnMBMnMlcRMkMxcScwEh8/V3RtZsr2Hpxt7eLqphz2dkewAMyuzOasmmzNrsqkoOHn/+JTEzyuJmSCZuZKYCZKZK4mZIJm5kpgJkpkriZkgmbmSmAlOfa758+c/FWM855AnY4xHvAHXAV9O358H/Pqg81nAAmBi+vsFwDnp+18Cbuoz9pvA6w56/AhSpVIJ8HVSeyrN7S9XQ0NDTJr7778/0xEOaSC5unt648X/cm/84/955OQFikPjszpVkpgpxmTmSmKmGJOZK4mZYkxmriRmijGZuZKYKcZk5kpiphhfmqulvSv+etGW+L4fPB1P+/gdccJHfh1nfux38d3feyr+4plNcfe+zozkSookZooxmbmSmCnGZOZKYqYYk5kriZliTGauJGaKMZm5kpgpxlOfC1gYD9PFHM1Uk4uAG0IIrwQKgLIQwvdijDelz5cCpwEL0uvd64DbQwg3AJuBcX2ea2z6WF8fI7VM7k3AQ+kS6f+Aa44im06w7KzAW+dO5J9+s5QXNu/mtDHlmY4kSZJOkb2dkdsWbuSuxVt5YGUznd29jCzO4xWn13HNrDoumlJFQW52pmNKkqQM6bdEijF+FPgoQAhhHqmlajf1Ob8bqNr//UHL2fYBPwgh/AepjbWnAk/0GTsVGBtjXBBCmAO0AxEoPO53pmP2x+eM49/vWsF3HlnHv/7xnEzHkSRJJ9GWXfu4a/FW7li8lcfXtBF5jjEVhbz5/PFcM6uOcyaMcJ9ESZIEDOzqbC8RQvgUqSlOtx9uTIxxcQjhNmAJ0A28J8bY02fIZ4C/T9//IfAL4G+Bjx9rLh2/8sJcXnv2GG5buIm/fcV0KkvyMx1JkiSdQKu3tXDHC1u5a/FWFm3aDcDUmhKuq8/lna86n1mjy7yimiRJepkBlUgxxgWk9jwixnjIoifGOO+g7z9Dqiw61NjX97nfBFw4kDw6ed46dyLfe2wDP3pyI++ZPyXTcSRJ0nGIMfLC5j3cmZ5xtKqpBYA54yr4m2uncc2sOiZXl7BgwQKXskuSpMM6eZff0qA2tbaUS6ZW8d1H13PLpfXkOo1dkqRBpac3snDdDu5c3Midi7eyedc+srMC500cyc0XTODqWbWMKncHAUmSdPQskXRYb7twIn/+nYXcuXgr180enek4kiSpH53dvTyyupk7F2/lrsWNbG/tJC8ni0umVPGXV07lyhm1jCzOy3RMSZI0SFki6bDmT6thQmUR3354nSWSJEkJ1dbZze+Xb+OOxVu5b2kTezu6Kc7LZv70Gq49rY5502ooyfevfJIk6fj5NwodVlZW4C1zJ/LpXy/h+U27OX2seyRIkpQEu9u6uGdpI3cs3soDK7bR0d3LiKJcXnF6HdeeVseFk6soyM3OdExJkjTEWCLpiP74nLH8+13L+fYj6/j318/JdBxJkoatpj3t3LUktb/Ro6u3090bqSsr4I3njuPa00Zx7sQR5LiHoSRJOokskXREZQW5vO7ssfzoiY189JXTqSrJz3QkSZKGjQ3b2w5cUe3pDTuJESZVFfOOS+u5ZlYds8eUk5UVMh1TkiQNE5ZI6tdb5k7k1kfX88PHN/C+K6ZmOo4kSUNWjJEVjS2p4uiFrSx5cQ8AM0eV8cErG7j2tDqm1pQQgsWRJEk69SyR1K8pNSVcMrWK7z62nnfNm0yuU+UlSTphensjizbt4s7FqaVqa5tbCQHOHj+Cv3/lDK49rY5xI4syHVOSJMkSSUfnTy+ayJ99eyG/WrSF15w1NtNxJEka1Hp6I4+sbubOF7Zy5+JGtu5pJycrMHdyJX9+8SSunllLTVlBpmNKkiS9hCWSjsq8hhqm15XypftXceMZY8h2/wVJkgakvauHh1Y2c+firfzuuTZauh6nIDeLS6dW8zenTeOK6bWUF+VmOqYkSdJhWSLpqGRlBd53+VTe84On+c3zL3LDnNGZjiRJUuLtbe/i/uXbuPOFrSxY3kRrZw+l+TmcVpXN266Yw6UN1RTl+dcxSZI0OPi3Fh21V6Q38/zSfSu57vRRXg1GkqRDaG7p4J4lqf2NHl61nc6eXqpK8rnhjDFce1odc+sreeShB5h32qhMR5UkSRoQSyQdtayswHsvn8Jf/uhZ7ly8lVec7l9+JUkC2LSz7cDG2AvX7aA3wtgRhbxl7gSuOa2Os8aPcCm4JEka9CyRNCDXzR7NF+5ZyRfuXck1s+qcjSRJGpZijKxsauGOF7Zy5+KtLN6yB4BptaW8d/4UrjmtjpmjygjB/5+UJElDhyWSBiQ7PRvpQ7ct4p6ljVw9qy7TkSRJOiV6eyPPbtrFnYu3ctfiRtY2twJw1vgKPvqK6Vwzq46JVcUZTilJknTyWCJpwG6YM5ov3LuSL963kqtm1vqvrJKkIauzu5fH127nzsVbuXtJI417OsjJCsydXMmfXTyJq2fWUltWkOmYkiRJp4QlkgYsJzuL98yfwt/89DnuX97E5dNrMx1JkqQTpq2zm98v38adi7dy77Im9rZ3U5ibzaUNVVwzq44rptdSXpSb6ZiSJEmnnCWSjskfnTmGL967ki/eu4r502qcjSRJGtR2tHZyz9JG7lq8lQdXNtPR3UtFUS7XzKrj6pm1XDK1msK87EzHlCRJyihLJB2T3Ows3j1vCn/38+d5cGUzlzZUZzqSJEkDsnFHG3cvaeSuJVt5Ym3qimqjywt403njuXpWLedNHElOdlamY0qSJCWGJZKO2WvPHsOX7ktdqe2SqVXORpIkJVqMkaUv7uWuJamNsZe8+Icrqr173hSumVXHaWO8opokSdLhWCLpmOXnZPMX8ybzsV8u5tHV27lwSlWmI0mS9BLdPb0s29HDA79awl1LtrJp5z5CgHMmjODvXzmDq2bWekU1SZKko2SJpOPyx+eM40v3r+IL9660RJIkJcK+zh4eWLmNuxY3ct+yRna2dZGXs56Lp1Tx3vlTuGJGLdWl+ZmOKUmSNOhYIum4FORm867LJvOPv1rC42u2c359ZaYjSZKGoeaWDu5b2sRdSxp5cOU2Orp7KSvI4fLpNYxmO+/+o3mU5PvXHkmSpOPh36Z03N503nj++/7V/Nd9qyyRJEmnzLrmVu5aspW7lzSycP1OYoQxFYWpjbFn1nLupJHkZmexYMECCyRJkqQTwL9R6bgV5Gbzzkvr+cxvl/LU+h2cPWFkpiNJkoag3t7IMxt3cc/SRu5e0siqphYAZo4q4/2XT+WqmbXMGu3G2JIkSSeLJZJOiDdfMJ7/+f1qvnjvKr7zZ+dlOo4kaYjY19nDQ6uauWdJI/cua6S5pZOcrMD59SN58/njuXJGLeNGFmU6piRJ0rBgiaQToigvh3dcUs+/3LGMZzfu4oxxFZmOJEkapLbt7eD+Zan9jR5atY32rl5K83O4bFo1V82sZV5DDeVFuZmOKUmSNOxYIumEuXnuBL76wGr+/a7l3Ppn57mcQJJ0VGKMrGhs4Z6ljdyztJFnN+4iRhhdXsAbzhnHlTNrOX9SJXk5WZmOKkmSNKxZIumEKcnP4f2XT+VTv17CPUubuGpmbaYjSZISqrO7lyfW7jhQHG3auQ+A2WPL+cAVDVwxo8b9jSRJkhLGEkkn1M1zJ/DDJzbw6V8v4ZKpVRTkZmc6kiQpIXa2dvL7Fdu4Z2kjv1++jb0d3eTnZHHRlCrePW8KV8yoobasINMxJUmSdBiWSDqhcrOz+MT1s7jpm4/zzYfW8p75UzIdSZKUITFGVjW1cO+yJu5b2sTC9TvojVBVks8rTx/FlTNruWhKJUV5/nVEkiRpMPBvbTrhLp5axbWz6vjSfat4zVljGFVemOlIkqRTpKO7hyfW7uDepU3ct6yJDTvaAJg1uoz3zp/C5TNqmT2mnKwsl6lJkiQNNpZIOin+/lUzuG95E5/73TK+8MYzMx1HknQSNe1tZ8Hybdz2TDvvue9uWjt7yM/J4uIpVbzzsnoun17jPyhIkiQNAZZIOinGjSziXZfW88X7VnHTBRM4d+LITEeSJJ0gvb2R5zfv5r5lTdy/vInnNu0GYER+4MYzx3HF9BounFxFYZ774kmSJA0llkg6af5i3hR++tQmPvHLxfzqfReT7dIFSRq09rZ38eDKZu5b1sSC5dtobukgBDhzXAUfvrqBy6fX0rj8KebPPz3TUSVJknSSWCLppCnMy+ajr5zB+374DD9+ciN/cv74TEeSJB2lGCPLG/eyYPk2FixvYuG6nXT3RsoKcrhsWg2XT6/msoYaRhbnHXhM0wr/sUCSJGkos0TSSXXd7FF897H1/Oudy3jV6aMoL8rNdCRJ0mHsbe/i4VXNLFi+jd+v2MaLu9sBmF5Xyp9fMokrptdy1vgKcrKzMpxUkiRJmWCJpJMqhMAnr5/Fdf/1IP/vnhV88oZZmY4kSUqLMbL0xb0sWJFaovb0+tRso9L8HC6eWsUHrkzNNqorL8h0VEmSJCWAJZJOupmjy3jz+RP47mPredN545lWV5rpSJI0bO1q6+ShVc38Pj3bqGlvBwAzR5Vxy6X1zJtWw5njK8h1tpEkSZIOYomkU+JDVzVw+6It/OOvFvP9t5+f6TiSNGz0pK+kliqNmnh24y56I5QX5nLJ1CoubahmXkM1NWXONpIkSdKRWSLplBhRnMeHr27gY79czB0vbKUw04EkaQhr3NPOgyubeWDFNh5cuY2dbV2EAHPGVvC+y6dy2bRq5oyt8KqZkiRJGhBLJJ0ybzpvPN9/fAP/9JulfOJcf3GRpBOlvauHJ9bu4MGV23hgRTPLG/cCUFWSx/zpNVzWUM0lU6tfciU1SZIkaaAskXTK5GRn8ckbZvHGrz3G79bmcnWmA0nSIBVjZNPeXr7+wBoeWLmNJ9buoKO7l7zsLM6dNII/Oms6l06tZnpdKVnONpIkSdIJYomkU+qC+kpeNXsUv37hRd7duJeptW6yLUlHo3FPOw+vauahlc08tKo5vSH2UqbWlPDm8ydwaUMV50+qpDAvO9NRJUmSNERZIumU+8R1M3lg2Yu874fP8Iv3XERBrr/wSNLBWjq6eWLtdh5c2czDq5pZ0dgCwMjiPC6aUkV1TzPvuP5iRpW7y5wkSZJODUsknXI1ZQW84/R8/uOpvfzzb5fyqRtPy3QkScq4rp5eFm3cxcOrtvPwqmae3rCT7t5Ifk4W500ayWvPGsvFU6uYUVdGVlZgwYIFFkiSJEk6pSyRlBGzq3N4+8Wj+cZDa7loShXXzKrLdCRJOqV6eyNLXtzDo6u38/DqZp5Yu4O2zh5CgNNGl/OOS+u5ZEoVZ00Y4YxNSZIkJYIlkjLmr6+dxmNrt/M3P32O08eUM7rCf1GXNHTFGFnT3Mojq7fzyKpmHl2znV1tXQBMri7mtWeN5aIplZw/qZIRXkVNkiRJCWSJpIzJz8nmv950Ftd98UE+8KNn+eEtF5DtVYQkDRExRtZvb+OxNdt5dM12HluzncY9HQCMLi/gyhm1XDi5kgsnV1FXXpDhtJIkSVL/LJGUUZOqivn0q0/jQ7ct4r/uW8kHrmzIdCRJOiYxRjbu2PeS0ujF3e0AVJXkc0H9SOZOruSiyVVMqCwiBEtzSZIkDS6WSMq415w1lodWNvPFe1cyt76S8+srMx1Jkvq1f6bRE2t38Nja7Ty+Zgebd+0DoLI4jwvqK7lgciVz60cyubrE0kiSJEmDniWSEuFTrz6Npzfs5AM/fpbfvv8S9wORlDi9vZFV21p4fO0OHl+znSfW7qBpb2p52sjiPM6fNJJ3XlbPBfWVTK2xNJIkSdLQY4mkRCjJz+G/3nQWr/mfh/nIz57jqzef7S9gkjKqu6eXJS/u4c51Xfzg1oU8uW4HO9MbYdeVFTB3ciXnTRrJ+ZOcaSRJkqThwRJJiXH62HI+cu10/uk3S/neY+u5ee7ETEeSNIy0dHTzzIadPLluJ0+t38EzG3bR1tkDwITKvVw5ozZdGlUybmShpZEkSZKGHUskJcqfXTSJh1Y18+nfLOWciSOZMaos05EkDVFbd7ezcP0OFq7bycL1O1iyZQ+9EbICzBhVxuvPGcc5E0fQtWUZf3Tt/EzHlSRJkjLOEkmJkpUV+Lc/nsMrvvAg7/vhM9z+3osoyvOPqaTj09XTy5Ite3hq/U6e3rCTp9fvZEv6ymmFudmcMa6C986fwjkTR3Lm+ApKC3IPPHbBjhWZii1JkiQlir+dK3GqSvL5zzecwU3ffJz3//AZ/uems8nNzsp0LEmDSHNLB0+v38lTG3byzPpdLNq0i47uXgBGlRdw1oQR/Pn4EZw9YQSzRpf53xhJkiTpKFgiKZEumlLFp26Yxcd+uZi//ski/uP1Z5CV5f4jkl5uX2cPi7fs5tmNu3hm4y4WbdzFpp37AMjNDswaXc6bz5/A2RNGcNaECkaVF2Y4sSRJkjQ4WSIpsW6eO5E97d38653LKc7P4Z9efZob2UrDXE9vZM22lgNl0bMbd7Fs6156eiMAYyoKOWNcBW+ZO4Gzxo/gtDHlFORmZzi1JEmSNDQcdYkUQsgGFgKbY4zXHXTuQ8DbgW5gG/BnMcb16XNvBf4hPfSfYozfCSHkA78ExgJfjjF+OT32a8BXYoxPH9/b0lDxnvlT2NvezVd+v5rSglz+9hXTMx1J0inS2xtZv6ON5zbt4vlNu3lu824Wb95Na/qKaaX5OcwZV8G7LqvnjHEjmDOunJrSggynliRJkoaugcxE+ktgKXCoy2U9A5wTY2wLIfwF8HngDSGEkcAngHOACDwVQrgduAR4CPhn4GHgyyGEOUC2BZIO9pFrp9HS0ZUuknJ4z/wpmY4k6QSLMbJhRxtPbO3m0d8t5flNu3l+8272tncDkJ+TxczRZbzu7LGcNqacM8dXUF9V4jJXSZIk6RQ6qhIphDAWeBXwGeBDB5+PMd7f59vHgJvS968B7o4x7kg/z93AtcAuoAjIBfb/BvBp4F0Dfgca8kIIfOqG02hJL20rLcjhLXMnZjqWpGPU1dPLqqYWFm/Zw+Itu1m8ZQ9Lt+xhb0eqMMrLXsf0UaXcMGc0s8eWc/qYCqbWlrj5tSRJkpRhIcbY/6AQfgp8FigFPnzwcraDxn4J2Bpj/KcQwoeBghjjP6XPfQzYB/wncCswA/hXoAU4K8b4yX5y3ALcAlBdXX32bbfd1m/2U6mlpYWSkpJMx3iZJOY6lkzdvZH/fraDZ5p6eMfpeVw0Jrf/B52CXCdbEjNBMnMlMRMkM9epyrSvO7Jpby8b9vayfk8vG/b0sqmll/SF0sjLgnGlWUwoy2J8WRY1uR1MrSkmN0EzjJL484Nk5kpiJkhmriRmAnMNRBIzQTJzJTETJDNXEjNBMnMlMRMkM1cSM0EycyUxE5z6XPPnz38qxnjOoc71OxMphHAd0BRjfCqEMK+fsTeRWrp22ZHGxRi7gT9JPyYXuBO4MYTwH8B44NYY4+2HeNzXgK8BTJs2Lc6bd8Q4p9yCBQtIWiZIZq5jzXTxJT382bef5FuLd3D2nNO59rS6ROQ6mZKYCZKZK4mZIJm5TnSm/fsXLXtxD0u37mXpi3tYtnUPG3fsOzCmvDCXWaNHcNWcMmaNLmfW6DLqq0vI7lMYDYfP6kRJYq4kZoJk5kpiJjDXQCQxEyQzVxIzQTJzJTETJDNXEjNBMnMlMRMkM1cSM0Gych3NcraLgBtCCK8ECoCyEML3Yow39R0UQrgS+HvgshhjR/rwZmBen2FjgQUHPf+7Sc1KugDYDbwBuA94WYkkFeRm8/W3nMObv/E47//hM3zzbedwydTqTMeSho0YI9taOljZ2MLyrXtZ0biXZVv3snzrXvZ1pTa8zgowqaqY2WMreOO545leV8r0UWWMLi/wCouSJEnSINZviRRj/CjwUYD0TKQPH6JAOhP4KnBtjLGpz6k7gX8OIYxIf3/1/udKP24EcB2pvZOuB3pJbcBdeGxvR8NBcX4O3/7Tc3nj1x7jlluf4ntvP4+zJ4zMdCxpyNnV1smKxhZWNKbKov2l0c62rgNjRhbn0VBbwhvPG8eMujKmjyqlobaUgtzsDCaXJEmSdDIM5OpsLxFC+BSwML3s7F+BEuAn6X9l3hBjvCHGuCOE8GngyfTDPrV/k+20jwOfiTH2hhDuBN4DPA985VhzaXioKMrj1j8/jzd89THe/I3H+dxrZvPqM8dkOpY06OyfWbSqqYVVTS2sbEx/bWqhuaXjwLiS/Bwaaku49rQ6GmpLmVZbSkNdKVUl+RlML0mSJOlUGlCJFGNcQHo5Wozx432OX3mEx3wL+NZhzn2wz/12UjOVpKNSU1rAT941l/d8/2k+8ONnWbRpF3/3yhlewUk6hJ7eyKadbazZ1srqbS088EIHX1r6CCubWti97w8zi0rzc5hcU8L8adVMqSmhoS5VGI1yKZokSZI07B3zTCQpCapK8vne28/ns79dxrceXsuSLXv40p+cRXWpsyM0PLV0dLM2XRQduDW1snZ7K537L4kGlOTCzDGBV80exdSaEqbUlDC1ppTasnzLIkmSJEmHZImkQS83O4uPXz+T2WPL+dv/e47r/+shvnLz2ZwxriLT0aSToqunlw072li7rZW1za2saW5lbXMLa7a10rT3D0vQsrMC40cWMbm6mHnTqqmvLmZydQn11SU89+QjzJs3N4PvQpIkSdJgY4mkIePVZ45ham0J7/zuU7z+K4/y6VfP4g3njs90LOmY9PRGNu/cx7rtralbcxvrtqdKow072ujpjQfGjizOY1JVMZc1VDOpupj6qlRZNL6yiPwcN7iWJEmSdGJYImlImTW6nF+992Le/6Nn+MjPnmfRpt184vqZ/iKtROru6WXLrnbWbW9l/fZW1qaLonXbW9m4o42unj8URYW52UyoLGLmqDJedfooJlUVHyiMKoryMvguJEmSJA0XlkgackYU5/HtPz2Pf7trOf+zYDVLX9zDV246m9qygkxH0zDU1dNLY2sv9y9vYn1zK+u2t7F+eyvrt7excedLi6KC3CwmVhbTUFPK1TPrmFRVxITKYiZVFVNT6l5FkiRJkjLLEklDUnZW4CPXTmf2mHL+6ieLeNUXH+JvXzGd15w5hqwsfxHXidXe1cOGHW2sSy81W5cuidZvb2Pzrn2ppWcPPglAcV42EyqLmT6qlGtOq2NiZaoomlhZ7KbWkiRJkhLNEklD2itOH8XkmhL++ieL+PBPFvGth9byD6+awYVTqjIdTYPM7rYu1u9IlUP7C6P1O9rYsL2NrXvaXzK2vDCXiZVFzBlXwQ1zRtPevIFrLzqbCZXFVJXkWRRJkiRJGpQskTTkNdSW8vN3X8SvntvC5+9Yzp9843GumF7DR185nSk1pZmOp4SIMdK0t+Ml5VDqa2oJ2u59XS8ZX1Oaz4TKIi6aUpWaTVRVzISRRUyoLHrZHkULFrzIORNHnsq3I0mSJEknnCWShoWsrMCNZ4zhmll1/O/D6/jy/au45j8f5E3njeMDVzZQVZKf6Yg6Bbp6etm8c9+Bcmj99jbWbW9jw47UMrT2rt4DY7OzAmMqCplQWcT1c0YxYWQx4ytTJdH4kUUU5fmfT0mSJEnDi78FaVgpyM3mL+ZN5vXnjOUL967k+49v4BfPbOHd8yfzZxdNynQ8nQBHtT9RWkFuFhNGFjOhsphLp1anCqLKYiZWFjG6opDc7KwMvhNJkiRJShZLJA1LlSX5fOrG03jL3Il87nfL+Pwdy/n+YxuYP6qHM9o6vWR6wrV0dB+4wtm67a2sb059XbGljZ133PGSsWUFOUysKj6wP9H4yiImVhYzobLIK55JkiRJ0gBYImlYm1JTwjfeeg6PrG7mc79bxveW7ua2z9zLlTNreN3ZY7l0ajU5zkbJiF1tnX8oidIzidan9ydqbul4ydiqknwmVhYxszKbC2bVv6QoshCUJEmSpBPDEkkCLpxcxS/fcxG3/uo+1oU6fvnsFn77/FaqSvJ59Rmjee3ZY5kxqizTMYeU3t7URtYbdrQdmFW0vs/9gzeyrisrYGJVEVfOqGFCesnZhMrUPkUl+an/lC1YsIB586Zm4u1IkiRJ0pBniSSlhRCYUJbNW+fN4qOvmMGC5U389KlNfPuRdXzjobXMGl3Ga88ayw1njHYj7qPU0tHNhu1tbNzZxsYdbWxI3zbuaGPjzn10dh9+I+vUTKLiAxtZF+RmZ/CdSJIkSZIskaRDyMvJ4upZdVw9q44drZ3c/uxmfvr0Jj716yV86tdLqK8u5sxxIzhrQgVnjhvBtLpSsrOG1946vTHStKedzbv2sXnXPrbs2seWXe1s2pm+v3sfu9peOpuoND+H8ZVFTK0p5YoZtYwbWcS4EYVMrCxmzAg3spYkSZKkJLNEkvoxsjiPt100ibddNIllW/dw79ImntmwiwXLm/jZ05sAKMrLZs7YigOl0hnjKwbtbKUYI3s7umna007jng4a97TTtDf9Nf194952Xty5j+47733JY0vzcxgzopDRFYWcNaGCMRWpWUTjRxYxbmQh5YW5bmQtSZIkSYOUJZI0ANPryphel9obKcbIhh1tPLNhF09v2MkzG3bxld+vOXAJ+ZL8HOrKC6grKzj01/ICRhTlnZQZTDFGOrp7aevsoa2zm7bOHlo7utnb3s3Otk52tnayo62LXW2d7GzrYmdrZ5/jnbR39b7sOUvyc6gpy6emNJ8zx43g9PJu5s5uYHRFqjQaM6KQsoLcE/5eJEmSJEnJYIkkHaMQQnrPnmJefeYYAPZ19vD85t08t2kXm3buY+vudrbuaeehlc007W0n3S+9RG52ID8nm4LcLPJzssnPzaKgz9e9e9r55urH6emN9MZIby/0xP33Iz0x0tMLHV09tKYLo7bOngNl1uHzQ3lhLiOK8hhRlEtdWQEzRpUxoiiX2rICqkvzqS0roLasgJrSfIrzX/qfiwULFjBv7sQT9XFKkiRJkhLOEkk6gQrzsjlv0kjOmzTyZee6e3ppbulk6552tu7ex4u729m9r4uO7l7au3r+8LWrl47uHtrTX1u7Ijnt3WRnBbJDICsLckIW2VmBrBDSX6EgN5vivByK8lNfC/OyKc7Lpig/58Dx0vwcKoryGFmcR3lh7rDbx0mSJEmSdOwskaRTJCc768AyNsZVHPXjUpetv+jkBZMkSZIk6Sh4KSRJkiRJkiT1yxJJkiRJkiRJ/bJEkiRJkiRJUr8skSRJkiRJktQvSyRJkiRJkiT1yxJJkiRJkiRJ/bJEkiRJkiRJUr8skSRJkiRJktQvSyRJkiRJkiT1yxJJkiRJkiRJ/bJEkiRJkiRJUr8skSRJkiRJktQvSyRJkiRJkiT1yxJJkiRJkiRJ/bJEkiRJkiRJUr8skSRJkiRJktQvSyRJkiRJkiT1yxJJkiRJkiRJ/bJEkiRJkiRJUr8skSRJkiRJktSvEGPMdIZjEkLYCyzPdI6DVAHNmQ5xCEnMlcRMkMxcScwEycyVxEyQzFxJzATJzJXETJDMXEnMBMnMlcRMYK6BSGImSGauJGaCZOZKYiZIZq4kZoJk5kpiJkhmriRmglOfa0KMsfpQJ3JOYYgTbXmM8ZxMh+grhLAwaZkgmbmSmAmSmSuJmSCZuZKYCZKZK4mZIJm5kpgJkpkriZkgmbmSmAnMNRBJzATJzJXETJDMXEnMBMnMlcRMkMxcScwEycyVxEyQrFwuZ5MkSZIkSVK/LJEkSZIkSZLUr8FcIn0t0wEOIYmZIJm5kpgJkpkriZkgmbmSmAmSmSuJmSCZuZKYCZKZK4mZIJm5kpgJzDUQScwEycyVxEyQzFxJzATJzJXETJDMXEnMBMnMlcRMkKBcg3ZjbUmSJEmSJJ06g3kmkiRJkiRJkk4RSyRJkiRJkiT1yxJpgEIIifzMkpgriZmSys9KkiRJkpR0ifzFNYQwLYQwItM5+gohnBFCqIsx9mY6S19JzJXETOCfq6EkhBAyneFQkppLRyepPz9zDX5+VpKkUyGp/3+TxH8wT2ImSO7PsK/EfXAhhKuB24FL099n/ENMZ/oVcFP6+0R8bknMlcRM4J+rgQghXBhCeFcI4bIQQlGm8wCEEOaFEP4uhPDmEEJlTMgVARKcK4k/wyRmSurPz1xHnylxf67Az2ogQghnhhBuCCFMCCGUpo9l9P8Pk5gpnWF6COHiEEJ+CCE303kgmZkgmT/DJGZKai7/XA0o08UhhHeGEC4JIdTEGGOmM6VzXRFC+GgI4U0hhPExxt5M50pipnSuRP4MjyRR4dK/VH8WWA+8ASDTf/FKZ/occBdwVjpTb6ZLiCTmSmKmPrn8c3V0uW4AvgqcDXwIqM9kHoAQwvXAF4D/396Zx+s1Xnv8u3IyIycyGIMQFYIaaug11dQkDUqJkEQGaigRtAgx1dDqgEtruJ1R89yqqS1Kq2q6qLGKVFGkiJgjwbp/rLWT7W1yzvsmeZ+93PP8Pp/zOWcPsr/Wevbaz7ieXsCXgI1L16os71G5IvowIlNU/2Wu+pnClSvItmpEznURMAI4BPi2iCxfZcU+IpNz7QxcDUwCzgQmi0ifqniiMkFMH0ZkisqVy1VDTMOB84F1gNHAhSKyRoBytS1wHtAF2AD4nYisW7GtwjE5V0gftitVDfEDbA08B6zvx3cD+1TMtDnwNLCRH98HHB/AVuG4IjI5Ry5X9XMtDdwArOfH5wETgRWBXhUx9QAuAzb145OAKcDawDJ+rlPmCu3DiExR/Ze5PsXlKtuqYa7uwMWlb+EWwL3AJcCAzPQJrt7Ar4F1/XgM8L/AqUD/zBTbhxGZonLlctUw18nAJP+7D3Ak8CCwhp+Tiri+AZxcOp4M/Lvk1yrqMuGYIvuwvZ9IvVv/AvZQ1Yf9+FJgEFQ6+vqMMz3gxycDy4lI74p4CkXkisgEuVw1otlYA2gzEemLjbTsApwBHF/RKNDHQD9guIgMAMYCmwJHAOeJyIpaTT6pqFwRfRiRKar/Mlf9iliuINuqESmwPLARgKreBTwMzAD2F5GWzDRXc7CZbZ9xrkuxwagewA5QSZ0mIhPE9GFEpqhcuVzVoZIN3gRWcaYZqnoa1tY5TUT6qfdCVMD1AtBanFfVs7H2zqUiMiDldzAiUw1XKB/Wq8o7kUSkVUSWVtWnVfXe0qU7gLEiMryCF2A5n544XVUfLF16HNgEGJ6SJzJXRCbnyuWqfq5uItJTVd/FltiNB34FXKCquwBnY42iQQmZWkWkt6p+ABwGDAV+ClylqrsBJwDT8Y955grpw4hMUf2XuepnCleunCvbqn6usq1OBUaKyMkicobzXAusgTXaOiyTc5V9eD6wq4gcIiLfcZaHsSWTpKrTRGRyrnA+jMgUlSuXq8ZUssEVwJ4ickjp8kXY92allEw1XH8EthWRqWAdJqp6DnArsF5HZ6rhCuXDelV1cquRwFXAzSKyj4isW1xT1cewl3WsJJyhISK7OdN1IjJFLHdNwfQP4HvAgSKyciqmqFwRmZwrl6vGuK4Arve/78KWAP4BeNb5/oyNACVpaJT8d4uIHADMUNXNgZuwmWWo6gvYmuYVUzAF54row4hMUf2XuepnCleunCvbqn6usq32AWYChwOdgddVdTdV/QOwJIkqzxGZnKvswy8DD2Gj04OxZRejVfVCoIck2nk2IpNzhfNhRKaoXLlcNcS0rYgcVRyr6ovAzsDeInKon5uOxfZ1UjA515dE5IclrunONVlEppY6TLqQrt4Xjsm5QvqwUXWu6sEisiI2MjcBm7b4FWB1sdkjf/Tb7sXWwvbDXtxmM/UFjgP2waZTfhHrCe+jqpf7bXdiSa8GAc83mykqV0Qm58rlqn6u1bFpnF/FpuhOxJKtXoQ1fg4QkQ+ceTBmt2Yzlf3XivlvoIhcCdwCnC2WZO7fWILY05rNFJwrog8jMkX1X+aqnylcuXKubKv6uWpttQu2ZOUqVT2mdN84rEH2dkdk8ueVfbiC/74DuFpVbyrdN8Gvf9QRmfx54XwYkSkqVy5XDTFtB1wD3C82O2oqgKo+JCITsU64lYEPsFmvJzWbybk2A34OvCQiF6vqXs41TUS2AK52e3bGdsk+pyMyOVdIHy6MKutEwhKUvQs8oqoficjLwChgmIi8qqpPqupfReQ+LMdACrUAbwH/UNWZIvI6sD3wBRH5t6rerqqvisjdwLRETFG5IjJBLleNqBUbSbkHQEReAPbDOrN+iyUh3x+YBUzwGVPNVq3/XsL8tzs2SnUmtlTkDWBvVX06AVNkrog+jMgU1X+Zq35FLFeQbdWIFmSrkSLynqr+TUS+AhwMjFPVGR2UCf7Th89jPhwlIj/D6hTjgKOBUar6Vgdlgpg+jMgUlSuXq/rVG1uafB1wrIh8V1WPBvC2zWZYaoxlgJGq+kwCJoAlgBOBC4GLReRSVR3jXNPEdh/bABsoP1NVn+qgTBDXh41LK8zqDfwPcAzQ3Y8H+7nxFTL9APgZsIQfr4AFrm9UbKtwXBGZcrlqiEmwnB2jga5+bmNspPpLftwdWDKS/4CuQLdo5aoKrog+jMgU1X+Z69NfrrKtFrut+pB4p6OgTPPz4UbAzcBOftwfWK0jMwX3YTimiFy5XDXM1LNkowuB75WuVbK7mD+7V8kmVwKX1V7LTLF92OhPJTmRROZmI/8VtqRojIj0UOsFvBYYLyI9EzMVtjgX6/U+SkSWUNWXsJG7nSXhOtzIXBGZnCuXq8b1v1jjYksR6aaq92MBbV8/nqWq76QAacd/12H+W1JVZ6slOEyiqFwlhfFhRKao/stcC6Uw5QqyrRpRnd/npdR2pnmxozLVqNaHD2AJhyeKSHdVfVVVU85eDscU0YcRmSJzuXK5qlOq+p7/+TC2BGs5ETlKbCnUwSJSySoj9RliajOyDgI6i8iPnOtoEememeZyhfRho0raiVQ0qNW72rAEjw8BQ4CpItIFWBp4j0RLjUpMxfOexQJED+BHItIPy7r/IenW4c71SxQuEVkyGlOJrXarzwjlSiCercp8/h5egOWFGoHliQIbNZ/tbMnUTlzojfkvKVNErqJsRfJh+R0MxFTP96Y3uVwhIt2CcoUr62VFslWhT6mtiu/znI7MVGd574b5MAlXnbE9KZNzNdKe6LDlqoHYnporXFkvK6Kt5sP4IdYJcQxmszOBO/x8pVLV11R1d2AbjOtyVZ3V7OcuyFZVMrXFFdmH9UjmvSdNfIjI2sArqvq6iHRS1Y9FpLOqfigiy2FrEncE1sXWMO6nn9wCvRlMWwF/V9VXSuda1Na9DsCmvk3AAkcf4MBmMznD9liW/1uKwl01l4hsg63PPBb42P0XwVaDgXeA2ar6qp+rulz1AWaVepkRka6qOrtiW/UEPiqPhpe4+mEJAzfFpuq2AhNV9aFmczlHp6KzrWr/OUN3rJzPLp2LwNULmKOq75fOdVHVOVX5UERWA15T1beKymAApk2Aaar6WulcBP9ti1U87y0qqEG4tgHWVtVzSnG96ji6Mpak9B1VnePnKi1XztADi6Pl2FDE0apsFTa2O0uY+J5je0NM4WK7c4WL7zm2N8SUY3v9TH2x9sS7pXOF//oA76nqLLFd404ChqnqE81kquFrUdWP/O+ibb885tu3RWQX4L+xJYmPN5mlN9YWLLe9KmVyhuWwvFrvlGJDwVW5DxdZ2vx1f0OwXUkuA5b1cy3+ezssc/oyfjwA6J2AaSjwD2DT0rmiQ21bbDvHlf24Fc9jk4BrGPAi8MXSuU4lWyXncqaXsaC/Zg3TNhXaaifgAWzJwHFAz1K52r6icrUz8BtsxtE4YKPStUr858/a1Zluxz6Cg0rXvoj1fLf68RCgfwKmrYB9SsedSn9vW4X//Fk7YtvK3g5s7edagnBdD/y+iA+l93D7iny4oceG7wB9amxVFdNQ4FFgvdK5IrZX8r3xZw3HYvuw0rlK41XJXjOwXUAG1JSrSso78GUs8fPvsAZE5eXKn7Wzx4Zr3G6rlK5V9c0JF9v9WeHiOzm2N8IULrb7s8LFd3Jsb4Qpx/b6mXZ1O92BJRkvt1e3xXbaXM6PxwDrJCxXU0vH5dj+Bex7tKofjwAGJ2DaCbgB2+V6DLBUKS5UwuTP2gH73tyI7c7dwifbz5X4cLH+PyYwYmfgciyx8JWlYLYstq3syKT/w9Yp8lfg837creTUpYB7KmASLMnlNcBufq7Vf/p7wbsH2D0x107Ag1jm+snA1XgiTqCv+2/XlEz+7MHAY9iIwIZYR1Jfv9bLuVLbag2scjMEq0CfhnWcbgl0cf/tVoGtVgX+jq013wvLzfRNt11/4L4KbDUU26noTuDwmmvLO1MVthruPtwSmISt0R8cgGtHfw8/j1Um/sK8BO0rV+FDf3ZvLK/Xd7CdJvpXyYRVUB8ENvTjltK1qr43gs0s/T3zEhov4d+drlXFq5pyNQSY6j4skppWUt6B9UuxfUesEr1UDdOoCmy1nseGzwJfwRocpwNrYt/pKspWuNjuXOHie47tDXOFiu3+7FDxPcf2hplybK+faQXgKax9MxRb6vQjrKO0pzNVEa+2wiaF/A04vXS+BVtZkbxNiA2WPIYlqN4d2zxiU79WZTt1B2wZ5MZYx9XtwNJ+rV8V5aoZP01N3CQiLVjnCFhv6meBk0Xkcj8/UlVfKK2JTaEvAj1U9R4R6Q+cCvQSkT9ilZ7hatuwJ2Py58wSkX8C94jlH/oV9rJ+iI1SfUFVP0jF5dO+twemqOqzInIX8DnsY/2O2tLEnVX1lcT+A6sgv6iqj7qtBgHnisg0rHI4wvlSchVMTwCIJcs+CNsO9FVgZ1WdXoGtejnX/cD9IvI3bLrwLlh5H6+2TWlKrtWB7wO3YNtbHq6qZ/i1WcAeqvqP8jKIZsvL+zDgFFX9E/AnEVkBC/5PYVPVR6nqcyltJbb+fhvgGI9ZL2INxhNF5LfONVZVn07M1QkbIJiNzeochCXsvQNYDthLVf+euFyNBFZU1Qd9ecg3PcZfBzxJBd8bVVURmYWN6v/Wp1xfhI0OP4tVnHdQ1dcS+29pbKTzSFV9Qmxp8CisMgjwPhWUd2AV4AmP7f/EZpn+UETuA16qiKnM9QjwiJercdg3+lpgtNqWwSm5IsZ2CBbfPbYPJ15s70zM2N5CvNgOweJ74NjemxzbF4YrUmzvCjyvvlxORJ7B6qe7AYp1IL0oMjf3aiquAVhak2uBK0XkDFU9XG1J2wwR2UVVX/b6oTaby5+zJdah9QDwgIgMwjqT7vV2YFKmkjYGjlfV+31JWyvwPY+jL2Btwlcq8OFiVVMTa6vqR2q7f9wMfKCqJ2GdR1cBXTzgd0ppPFU9AviziNwP/BrrKbwWG2EZAbyZmqmkztg28KdguxIcjtlqJJa5PWXjZxa2/fytfuphbJTl5NI9r/jv1Lb6M7CUiNyKfawvxta4vgRsDcypwIcPAu+JyHF+vAE2SjwLGKiq0yG9rVT1r1iZPtiPH8DK/UrYlqXJGxmqeh62Reqj2K4EnxeRKX7tDcyPpOpA8mfNAs7GKoNFXHwLaxChqm+q6nP+d0pbzQGOUtVbRGQpbLbiPcAjWINjtdSNDOf6WC0nxc1YZflc5s0KfNsbGalj+3jgbm9M/wZ4Hrgfq1BvmLoDqcT1IZbQ/8fAWVhM/67zbQXMrsBWbwAHq+ptfnwd1kA8zY9nVlHesdG5/iJyBdYwvB77Pq8ErOWNjCq+z48AH4rIOD9ezvnWw5b7TIM0tvKO5SK2z4gS20Wkq3Och8WDyuO7WP6QWc5zc5TYLpYD5kOsAylEbPdOraLeHia2l8rVeKwDsPL4XrLVh1hy5RCxXSxHzUzgkCixvfAfln6iT5TYXuJ6HPNThNje15/1HBbbT/fjadjMrenASmodSJ3UlYCrn3NcClylqq8DXwXWE5GzSre+7/d93GwuEenr35CzgevEhX1flind+kYqJucqbHWiqt4glrPwOmxJ26+AdYAtgOkpfdgsLfZOJBHZXER2FZE9S6d7AOuKyObAf2EjVKNFZPlEFYmCaS8AVd0b+/jcqKrnqeoV2Au6FTblM9Xsh4JrjHMdAvwTmwZ3q9q2kXdgs5FSvQBz/afzEqZ18Wd/DVhaRIY2m6MNrtHOsiXW2fY7Vf2+qt4H3IqNKnROXK72VEuI+UNgUxG5HthAVSdjnUuji97mFBKRrUVkgoh8zU+dDwwSkVEAaiPX9wCTSr5NxXSAM8z0CthfgPOAjUVkbxHZHRhVquyn4JooIvuo6jRvUBRl5zEsIR4iskfKcl/i2s/thKq+jc0uOEpVL8KWG+xRgQ/3K53ug00jHogtyfgLsHXpA5+K6SAAVf0K1gj7s6r+QFXPxhpDe3qDMlUFteA60E8dh80sGAJc4Q3+Il61JPzmFOVqX/UElDJvK9lJWCV/rRQsNUwTnOkVYDy2BP5uVT1VVX+DlfUviEjPxLaaICJf9Ur9rcCuIlJMl98fG9AYm4LHmXYAThIbbQW4BFi9ythe4jpRLBkzqvpW1fHdmU4RkQGq+rSqvh0ktu+AzcgfqJ4MPUBsn8tUOt0Xm30+kApie4nrRBH5DICqjqTi+F6yVfEOnoI1nquO7TsA3xaRVdQG7+d2OFNdbC/8t4qq/gvYlxixveBaGevw+yPVx/ZhwKlFJwS2lHQJETkCQFWfxTriRotI94S2GoaVqz7OMdN/PwfsD6wjIieIyEjggFKZazbTqSLSiiX/f7PUGfMUvmueiIzGvjctbfxzi5vr22IzvQHwetbuqnqCqt6ELX/dnIR9Dc3UYv2Qi8gI4CdYT9vxInKaX7oKm5lxLfANYCKWl6jpjq1hmioiZwKo6kHYiEGhvthW601/AebDdax4jzNwBjaN8ufe8TAU+4g3fbu/+fjv+2CzIZzlPWxG0vrNZmmH63TvVb4TeEdEjvZbV8fW8qcuVyeIyLdU9U5V3QkLrLv6rUsBMxNW5kdgo7/dsfK+P3AbtoZ5cxE53G99H9vZrumdW/NhOrS45pXou4ETgKOwmXgPJeqAKLi6YVPjD625ZTbwkVgn78lYB2/TVcN1bA3XM6UOSQXepMkzSmuYujvTYX7pCmyd/iXAIVhOFiXdO1gwTSlVtkZh/izsJNjMg1Qdk2Wuo0VkMrbk4XrMLmf7rWth8aqpy8rnw9UNOK4oV2o7vQjwurNskYKnhqk7Fkcnq+oLaqPnM/zdA1u61YJN80/N9U0R2Rf4JdaoOAJbMgZmrzdTMLm2xPKJbC8iK2IDck9is32O8HuSxfYFcBWN6yK+/4UK4rsz7QCMKDO55lBBbK/hGlpjq6dKnWvJYnuJaUdn+oyfuxxbbncpiWP7fLi2EZE1YW58P7Zkq6TxvcS0nYisipWdX/u1c/x30the4hoBDCvKlfruZ1iC7aSxvcS0IzBcRFZV1ec8tr8qPqhP4the4toJs1dfVf0pNvvvMCwvEiSM7f69+RZwmc7bdfBJrM28hoj80M8ticWuVJ0iZa4ZNdda1GZIjQAOAH4K3FQqc81murzoPKq55WPgYxGZiH137ismRCTiukxtxm1Z00v10b7OmKSvoenSxZRcCfgM1ku6hR8PxAJrP6whPQXL6wMW9LsurmcvBNOyeOZ2Pz/J71u32UxtcF3PvOTQ3bEOih9jveFN52rDVv1rbDUMmIYtbZMKuYqM9kP9+HZshOqzFfpv2Zr7DsM6S1OXq238eCxwIPN21fsSNp3yNuAJbLZUFUwHAJ+rue8AbERoSIW2+gSXl/V3sU6utSrm2qjmvn39vqbv5tAG0/pYResHzEssKqTZNXJBTJvU3Lcf1cT2MtfXirjk1y/COt8eSBGv2rFX7Xu4Bza9vwdNju/t+RCbLn8tNtMgSWxvg+vA+byDR2Dxfe0UXCWb3IbNLj3K378VsE6tq0kY29vgOgLffZR5Oy8lje/tMHXG8j0mje1tcPXGkuUWG7wki+1tMC2JpXj4EfN2jEsS29vh6lNjq6TxfT5MU5ynFUsYfX7q2N6GrWrfwWSxfQFMR7r/emH5Qq/CkiAni+1t+LA3n9xkKVlsx5bzvYbveIYtp/s8sJ0fD/bYfhO2RDhJbF8A1yZYztnyfbsBz1Voq08wYbMn3/bYvmYwWx2E5e1NFq+a/VNsgbfI8tGLDVT1Sp861htbA7ivqj4mIl1VdbZPz21qT2U7TDc40+M+krEEcBJwvqo+WiHXjcBXVfXx0n09sKD2bkVMZVvNXWsuIr1U9a1mM9XJ1QX7KK4HPKOqL1fEdCO2pfETha18ZPgWVX2s2UzOVWw9+piILItVGG7CdvF5QFW/XuKfobauuQqmG7GOt8fVZgTiM1tuS/gOtsvl5y8DJpffywBca2AVnx+ksFcbTKsBd6nqVL+vRROM+LTDNJB5dloBG4k6N0C5WhX4q9oS1yL3wZyEcbSu99DvXVr/cyQtJdOqWFLMI8WW16yL2e75ZjO1w7UKloC1iFknA9eo5SZqNlPxTRmIdW7/CTgUa9h3wXKgvO2x4fUUsb0dLsUai5NU9Q0R+Tq2RD9FvGqLqRVrQLZisydTxvb2bDUZG7Q7EjirYlsJNlp+gqr+W2ypWNNnw9fBVdjqYKzz5njgnIpthbPsr6rviy1Hmp0wttf1Dvq9qWJ7W7bqhLW5umIz+R9OGNvrjVenAFcniu2t2BLujbG0KvtgAwHDgd+q6iS/rz9WrlLNjloQ1zCsrv41v28c1r54MgKTiHTDOt2OSVjvq4drWeBo4BepuJJoUXuhsNGKLlii7OJc0Tl1MZYcEGD9RX3WYmRa1f8uRoc7BePaMKCt1kvF1GC5SsbVgK1SjwIXXD38uAs2Q2uUH/fEEpBPDMTUA3gGmBDMVgXXOL/WGoxrNFYJ6xGAqShXyXzYgJ3G+nG3IFw9nWvvVLZq0F7jAzH1xGa7jg1qqwkJmVbCGlvFtu+rYPlgwGZHvQNciG/BHozrAqBfQKalsU6SXsG4ehXlLAjThSn916CtWv1c0+N7A0xR38E+wZh+iXXSR7RV34RMKztTdz+eBMwEDvPjnlh+nwmJbVUP19+AcQGZ9vLj7oG4nsJ2+INS2/H/y88irSEWS052E5Y48eJizTLz1gH3AXr62tervCe1qaqTaQlnusaZNBjXFQFtdXUKpga4yuVqmdJ60yqZCltdmYKphutc4AIRWVNtpt+f1GdKqSV2uwTfpSAI0/tYroWZKZgWgusdVZ2jCUZ9GuR6Xy0f2PsBmIpyNbOZLA0yFXZ6F+bmZInA9Z5zzWjr36qAq7BXqtHNem11MVaxT6KIMcuZbsbyrJwvIkNU9Z/ADWI5mg7FRvRbsOShqfJF1cvVGUsO3XSuBpn2wpb4NH2mSINc48Vm6qeI7fWWqz0kQaLcBrk6A+PcVk2N7w0yjQpqq9EpuBpg6gSMDRqv9kwYr4rvzYUisrqqngvsqKpnlb6D15Co3t4g17VUU2doj+ltmLvbchSua7B8wmiiVVhJtTA9T9gozkrY+sytsRxDh2PJQ9cu3fcLbFrZXTR5vWREpqhcEZmickVkaoPrCOdax+8p1nePBh4CVu9oTJkrM2Wu6rkiMkXlaodpEDZLcjawi9+/MbBixbaqhCsiU1SuiExRuSIyReWKyBSVawFMR2Lb0g/xe4rvzRhsI6OqvoOVckVkisxV1c+iGLIFS/68IvOW9BwK/AsY7MdnYNO/UyW3CscUlSsiU1SuiEx1cK3hx2OwRG5JknRGZMpcmSlzVc8VkSkq1wKYvo4lMO3HvOU8SZbiR+aKyBSVKyJTVK6ITFG5IjJF5VoA02F88nvzZdIn1w/HFZEpMlcVPwtjvNWxHtu+2C4EU2quT8HWUrdgu0GtlsCh4ZiickVkisoVkakBrguwacOfAwZ0RKbMlZkyV/VcEZmictXBdAy2o1BP50q1y1I4rohMUbkiMkXlisgUlSsiU1SuOpiK700LtpnECkFslZwrIlNkrip/GjXgjth2jHdi60u/jPXoTi3dMxD4abL/gYBMUbkiMkXlisjUINdPOjJT5spMmat6rohMUbkaYPoxiRpjUbkiMkXlisgUlSsiU1SuiExRuRpgyt/BgEyRuar+KZICtysR2Qw4DRijqg+JyE+ATYDNgHvEtjq/HNgC2EBE+qhqU5OIRmSKyhWRKSpXRKaF4NpQEmznGpEpc2WmzFU9V0SmqFwNMn0O6E2ChKsRuSIyReWKyBSVKyJTVK6ITFG5In5vonJFZIrMFUIN9MJtRmmLcKA/cKP/vRqWWPg8LG/Auil6wCIyReWKyBSVKyJTVK6ITJkrM2Wu6rkiMkXlisgUlSsiU1SuiExRuSIyReWKyBSVKyJTVK6ITJG5Ivw0YsQWoFfp7wHYTiXL+7lVsC0SWxM6NhxTVK6ITFG5IjJF5YrIlLkyU+aqnisiU1SuiExRuSIyReWKyBSVKyJTVK6ITFG5IjJF5YrIFJkrwk8n6pSqfqSqb/mhADOBGar6sojshSUq66Kqb9b7by6qIjJF5YrIFJUrIlNUrohMmSszZa7quSIyReWKyBSVKyJTVK6ITFG5IjJF5YrIFJUrIlNUrohMkbkiqNiabuH+Y5ELgJeBodhUr0cXE9dCKyITxOSKyAQxuSIyQUyuiEyQuRpRZqpfmat+RWSCmFwRmSAmV0QmiMkVkQlickVkgphcEZkgJldEJojJFZEJ4nKl1kJ1IomIAF2AJ/33dqr69GJm+9QzQUyuiEwQkysiE8TkisgEmSszNUeZ69PNBDG5IjJBTK6ITBCTKyITxOSKyAQxuSIyQUyuiEwQkysiE8TlqkqLOhNpInC/qj6+2IgWURGZICZXRCaIyRWRCWJyRWSCzNWIMlP9ylz1KyITxOSKyAQxuSIyQUyuiEwQkysiE8TkisgEMbkiMkFMrohMEJcrtRa1E0l0Uf6BJigiE8TkisgEMbkiMkFMrohMkLkaUWaqX5mrfkVkgphcEZkgJldEJojJFZEJYnJFZIKYXBGZICZXRCaIyRWRCeJypdYidSJlZWVlZWVlZWVlZWVlZWVlZXUM1b07W1ZWVlZWVlZWVlZWVlZWVlZWx1XuRMrKysrKysrKysrKysrKysrKale5EykrKysrKysrKysrKysrKysrq13lTqSsrKysrKysrKysrKysrKysrHaVO5GysrKysrKysrKysrKysrKystpV7kTKysrKysrKysrKysrKysrKympX/wcwbKZ3fLD/AQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 1440x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.ticker as mtick\n",
    "curve_points = curve.get_curve_points(120)\n",
    "ax = curve_points.plot(figsize=(20,10), grid=True, title='US Treasury Yield Curve on ' + cur_date_curve.strftime('%Y-%m-%d'),\n",
    "                       xlim=(curve_points.index[0], curve_points.index[-1]),\n",
    "                       xticks=curve_points.index[::4], xlabel='', rot=45)\n",
    "ax.yaxis.set_major_formatter(mtick.PercentFormatter(1))\n",
    "_ = ax.set_xticklabels(list(map(lambda x: x.strftime('%Y-%m'), curve_points.index[::4])))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "domestic-surge",
   "metadata": {},
   "outputs": [],
   "source": [
    "assert curve.date == BDay(1).rollforward(today).date()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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