{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "135dd79e",
   "metadata": {},
   "source": [
    "# Surface tension using PC-SAFT Helmholtz energy functionals\n",
    "\n",
    "## Goal of this notebook\n",
    "\n",
    "- Learn how to compute the surface tension for a planar interface using the PC-SAFT functionals.\n",
    "- Learn about the `SurfaceTensionDiagram` that allows convenient calculation of multiple surface tensions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9ad1bb1d",
   "metadata": {},
   "outputs": [],
   "source": [
    "from feos.si import *\n",
    "from feos.pcsaft import *\n",
    "from feos.dft import *\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "\n",
    "sns.set_context(\"talk\")\n",
    "sns.set_palette(\"Dark2\")\n",
    "sns.set_style(\"ticks\")\n",
    "\n",
    "colors = sns.color_palette(\"Dark2\", 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7ec9a5b",
   "metadata": {},
   "source": [
    "### Water parameters for PC-SAFT \n",
    "\n",
    "In this example we will calculate surface tensions for water using the 2B association scheme. The parameters that we use, [were adjusted to vapor pressures, liquid densities and surface tensions](https://pubs.acs.org/doi/10.1021/acs.jced.0c00684). Parameters are available [here](https://github.com/feos-org/feos/tree/main/parameters/pcsaft)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "837c7770",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Equation of state object.\n",
    "parameters = PcSaftParameters.from_json(\n",
    "    ['water_2B'], \n",
    "    '../parameters/pcsaft/rehner2020.json'\n",
    ")\n",
    "pcsaft = HelmholtzEnergyFunctional.pcsaft(parameters)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "79b57b8b",
   "metadata": {},
   "source": [
    "Let's first compute the critical point. We will make use of the critical temperature later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d6ed65fa",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "|temperature|density|\n",
       "|-|-|\n",
       "|677.34347 K|18.70466 kmol/m³|"
      ],
      "text/plain": [
       "T = 677.34347 K, ρ = 18.70466 kmol/m³"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cp = State.critical_point(pcsaft)\n",
    "cp"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ad0235c",
   "metadata": {},
   "source": [
    "As you can see, the model overestimates the critical temperature."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c00eed3",
   "metadata": {},
   "source": [
    "## Surface tension for single VLE\n",
    "\n",
    "To compute the surface tension, three steps are needed.\n",
    "\n",
    "1. We need to compute the vapor liquid equilibrium (VLE) either at given temperature or pressure.\n",
    "2. Then, we need to initialize a density profile. We will use a hyperbolic tangent with the VLE bulk densities as limits.\n",
    "3. We solve the DFT equations to yield the equilibrium density profile and calculate the surface tension."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8fa8d790",
   "metadata": {},
   "source": [
    "For the VLE, we use the `PhaseEquilibrium.pure` method. Here for $T = 300$ Kelvin."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f834af33",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "||temperature|density|\n",
       "|-|-|-|\n",
       "|phase 1|300.00000 K|1.51670  mol/m³|\n",
       "|phase 2|300.00000 K|55.38975 kmol/m³|\n"
      ],
      "text/plain": [
       "phase 0: T = 300.00000 K, ρ = 1.51670  mol/m³\n",
       "phase 1: T = 300.00000 K, ρ = 55.38975 kmol/m³"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "vle = PhaseEquilibrium.pure(pcsaft, 300*KELVIN)\n",
    "vle"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21fb88cb",
   "metadata": {},
   "source": [
    "Next, we initialize the density profile. For the surface tension, a 1D DFT calculation in Cartesian coordinates is conducted. Thus, the density profile will be an 1D array (we have a single substance). \n",
    "\n",
    "To solve the DFT equations, the density has to be discretized which can be controlled by `n_grid`, the number of grid points. The surface tension is not very sensitive w.r.t the number of grid points but you should make sure to pick a large enough value. When in doubt, run multiple calculations varying the number.\n",
    "\n",
    "We also have to provide a width of the calculation domain, `l_grid`. The domain should be large enough that the bulk densities can be observed in the limits. You can check the resulting density profile to make sure that's the case.\n",
    "\n",
    "The critical temperature is used to come up with a good initial estimate for the density profile."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "25c9d99d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 502 µs, sys: 35 µs, total: 537 µs\n",
      "Wall time: 544 µs\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "interface = PlanarInterface.from_tanh(\n",
    "    vle=vle, \n",
    "    n_grid=512, \n",
    "    l_grid=100*ANGSTROM, \n",
    "    critical_temperature=cp.temperature\n",
    ")\n",
    "initial_density = interface.density"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "303bb746",
   "metadata": {},
   "source": [
    "The above method does not yet run a calculation. If we try to extract the surface tension, it will return `None`. Let's store the initial density profile for a later comparison."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f915e37c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "interface.surface_tension == None"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a321fe5",
   "metadata": {},
   "source": [
    "To calculate the equilibrium density profile, we have to call the `solve()` method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "77c08d7f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 21.5 ms, sys: 693 µs, total: 22.2 ms\n",
      "Wall time: 22 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "surface_tension = interface.solve().surface_tension"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "19402ba2",
   "metadata": {},
   "source": [
    "`solve()` calculates the equilibrium density profile and returns the `PlanarInterface` object so that we can readily extract the `surface_tension`.\n",
    "\n",
    "The `PlanarInterface.density` contains the equilibrated density profile. Let's compare it to our initial density and zoom into the interesting region between 40 and 60 Angstrom. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "61992d8f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fXQ+Nr7OH8H+NzUDr63h/5OUvB5OZ8kAZDKyGCZthYMOE1TDSXxsmbKS/thomUl3cOOZbCsNID6mYzMSlpXIpOsJRk2aYsBpm0kwmUg1z+vtM5svbTVgr16VaibIYZhcMiyuG2YX5R3eyJzqCNOPye0zpx0kz0t+X/n4zKSYzfl7+fHfHYxgu7phc3DFc3DmXmszti7/EbLZkCp8mw4TlcgB1NZlxMZlxNVt4ILgFd1VrkOl789vx3Ww4E4aL2YKbyYyL2YyryYLr5T8d48vH6FqxdpZJEc7ER+NuccHT4oqryayQKyJyE9wtLrhbXG7qGNkFyuvharak/+L3FpSfP2NsNhtjxozh999/xzAMgoOD6datG9WqVaNu3bqcOHGCV1999abPk1P4zG7CmIyAFxoaSrVq1bLsv9K/w+L1fO9Kly7N7Nmz2bZtG6tWrWLDhg3s2bOHVatWsWrVKubMmcPUqVNxcbmx/6/269ePb7/9lvnz5/Poo4/y22+/kZiYyL333ptlEh0pfG7N/3qI3CibFRcg1/+5S4SUmLOZNrkA9a7nnKe3celfmzpd/sqt439+lmXbj0CqYSLFZLn8ZXb8mWqykGhyIcnsQqLZFb+91Thfuhomd28MVy9Mbl5cOH2YY+dPkGRyIdGc/pVkdiHJ5EK8xY14ixs245+weHzoW1l6aD33XVJt6dNpmwwDD7MLHhZXPC2ueFz+R1DG626V6nB/cItM7w+LjmBP5Bl8XN3xcXHH19Udbxc3fF3d8bS4KoyKiEiB+Pnnn/n9998pW7YsU6ZMyTL76ddff31Tx8+44pjTM5NX3tKZIeMW07Zt2zJmzJibOn9uNGrUiEaN0i8bxMXFsWzZMl5//XU2btzIsmXLcpw051qCg4Np0KABO3bsYP/+/fz2228AmiiniFB4LATCqrbMNDYbBqEBV9zXbrdjtdvYE3kGAOPyb7nS/7Rj2G2OsYEd7HZKunlSyt0r/TdidhvY7UQmxRKVFA+OOjCwpf+ZcQzs6ce12ynj6ZP+0OzlY9jtdi4kxGC/4j0GwOU/M46RcXxXw4S72fxPDzYbadY0rNZUTHYrht2GKQ9uUSlMXOw2XKwpeFlTrl4YsZ+oXZk3tbj8dTUJZhfizW7EWdw5depPzJ5+mDz9MHn6g7sP9xzbSLzFjTiL2+U6N2JcPIh08STO4nb5VuR01f2yzoC38uQBXtn0S7bnNhsmR5DMCJeftBtAeW//THUbzobhajIT4O5FoIcPXgqdIiKSjev52fD3338DcPvtt2e7bMbatWsBrroe49W0atUKs9nM5s2biYyMzLJsyMqVK7O8p3nz5o59Tz31VJbPc/bsWYYMGULp0qX59NNPM02Ok1unT59m1KhR2Gw2Fi1a5Nju7e1Nnz592LhxI/Pnz3fcQpuTa32v+/fvz44dO/jxxx/ZtGkTdevWJSQk5Lr7lVuPwmMh0OPlP3NVl/Xu+etzs+8HqHrtkuvyT7C0YrdZr/gz7V/jf/7EZsVut4L1XzX2f9Vm7Lf/672OP9PS/7SmYremYU9LBWtK+jjt8p+XX3PF6yu32dLSX9v+/b60lPSatBTsqUkYacnYU3M39bozeVpT8bSmEpgSR9LhrDciP3KV96YZJqJdPIhy8SDGxZOg0xs5d2AJFp9AzD6BmH1K4XLuBFXiL1yu8ch0pdNqtxGdkkh0yj8P8We3ltiTa2ZzJiHaMXY3uxDk4UMpD28CPbwJ9PAh0MObMp5+hJQoQ5MgzeImIlIcZdwSGRcXh81mu+pzeyVKlADgzz//JDEx0THDa0pKCp988gnr1693jG9EQEAAvXv3Zt68eTz77LNMmjQJb29vIH0ynSvXXczQvHlz6tWrx65du3jppZd44YUXHJPtxMXF8dxzz3H8+HEqVqx4Q8ERoFy5csTGxnLy5EmmT5/OsGHDHPvOnTvHhg0bgPTJea4mY2KjmJiYbPffcccdvP3223z//ffYbDZNlFOEKDzKLc0wDLj8PGJRv9Zkt9vTQ2VqUpYv27/HKYnYk+OxpSRgS4pLf335y54cd/l1wuXtcZe3X96f4pzZ6ix2GyVT4imZEp++IeoE0YfWZqppdfkLwIZBtIsHF9y8ueia/nXBzeuK1z74psRj9/DJ9BvNS8mZ+02ypnIiLpITcZmedgXgrqr1aRI0KNO2zeeO8f3BTVTyCaCidwCVfQKo5BNA0L/OIyIihVvZsmXx8PAgOjqagQMHUqlSpRzXe+zfvz8zZ87kwIEDdO7cmYYNG5KWlsaOHTuIioqiVq1aHDx4kIiIiBvuZ/z48Rw8eJB169bRpUsXmjVrRlRUFJs3b6ZRo0aOq59X+uijjxg6dChz585l+fLl1K1bF7PZzN9//01sbCyVKlXirbeyPmZyPd566y1GjBjB22+/zezZs6lRowYJCQls3bqVxMREevfu7bgKmpOMyXr++9//snXrVnr37k2XLl0c+z09PbnzzjuZNWuW47UUDQqPIrcIwzAwXNzAxQ3wy7Pz2G1WbImx2BKjsSVEYb38py0hGmtC9D/bEy5vT7xie/wlrPGR6Vdpr5MJOyVSEyiRmkDNLNM1pTv59wwMF3csJSvhUrISpoCKPHr+JCddPAkzu3PK3Z8IN5/LM/ZmVdYz6/dtT+QZfjyc9Qe0m9lCJe8AKvqUoJpvKWr4BVHdP5CGpSricZMTWoiISP5zd3fn/fff5/3332fv3r2Eh4dz6dK/ZyVIV65cOX766ScmTZrE33//zdq1a/H09KRmzZrcfffd9OnTh9tuu42DBw9y7NgxqlSpct39+Pr68t133/H111/z888/s2bNGkqWLMmjjz7KPffcQ9euXbO8p2LFisyfP5/p06ezfPlytmzZgouLC+XLl6dbt27cf//9+Pnd3L8RWrRowcyZM5k6dSp///03K1euxNPTk7p163LvvffSu3fvax5j2LBhHD16lNWrV7N27VqqVauWKTwCNGnShFmzZtGjRw/HVVcp/Ax7Xsx7LFn07duXPXv2EBoammXhVJHCxG6zpYfL2AissRGkXf7TGnPBsS3965+xPe3GbvvJ9vxmV6wlypPgX45onyAiPEty0sOPw66+dG7QjX7BmX9b+vaW3/nfrtW5Pv66e56lim/JTNu2R4RTwbsEpTz0w09ERCQ3Ro4cyapVq5g1a5ZjYh4p/HTlUUSui2EyYfYOwOwdAGWDr1lvt9uxJcWmB8nos6RdOk1a1BnSok47XlujTpN66ST2pLhrn9+aguXCUXwvHMWX9Gd1M5aIMZa+ybEytXAtG5L+VS6EjhZvTLVbcTwpnuOxkZyIjcxyK2wGV5OZit4lsvQ/eOlUolOSKO3hQ2jJcoQGlCM0oCx1AspRxTcAk3Fj62GJiIgUJUlJSbi7u7No0SJWr15NvXr1FByLGIVHEclThmFg9vDF7OELQdVzrLPb7dgSokm7eJzUiydIuxhOauQJ0i6eIPXiCVIjjmKNPpvj+wHsaSmknNxNysndjm0BQB/DhGuZWrhVaoBbxQZYyzUkIqAiJ3DheFwkR6IvcDj6PAZGlkl7TsZdIjolfTKjc4mxnDt5gJUnDzj2+7q60yiwEk0CK9E0qDKNAivic5PrsImIiBRGvXv35syZMyQnJ2MymRg3blxBtyROpvAoIrcEwzAwe/lj9vLHrVKDbGtsyfGkng8j9fwRUs6HkRpxhNTzR0g9d5jUC8fSl43Jjt1Gypn9pJzZT+zG2UD6f/xq+gZRt2J93Ko0waN6C9yrZV3c5FxCLKXcvbmQw1XRmJQk1pw6yJpTBwF4plFXnmrY+bo/v4iISGHXqFEjTp06RZUqVXj66adp2rRpQbckTqZnHvOJnnkUyVu2lERSzx4k+fS+9KB4eh8pZw6QevbAdT1zaSlZCffqLfCo1gL36s1xq9wYk6sH5xNi2RN5mj2RZ9gbeZrdF09zNOYidjL/J/SH7iNoWy7zmmGf7VrDqbhLtClXg9ZlquPn5uGUzywiIiKSn3TlUUSKBJOrR/ptqf+6amm3ppF67jBJJ7aTHL6T5PAdJJ/YgTXqTLbHSbt4griLJ4jb9GP6BrMF96rN8QxpT/OQ9rQPbo3J7fK6W6nJ7IgIZ8v542yNOMH2iJM0LJV1xdS5h7dyMOo83+z/C5Nh0LBURdqWq0H78rVoElgp2/UtRURERG41uvKYT3TlUeTWkhZznuQTO0g+sZ2ksE0kHdlI2qVT136j2YJ71WZ4hrTHI6Q9HjVvc4RJu92eZe3IswkxNJ2d85pcpdy96VapDrdXDuW2stVxNet3eiIiInJrUnjMJwqPIre+1EunSDqy0REmk45uwZ6S/cysGQyLKx7BbfGqdzue9XvgWjYkU4CMSUni12O7+OP0IdadPkJkcnyOx/JxceOZxt0YUec2p30mEREREWdReMwnCo8ihY/dmkbyie0k7F9D4v41JB78A1tizFXfYylZGa/6PfCq3wPP2p0wuf+zNqTNbmNv5BnWnj7M2lOH+OtsGGl2W6b3f9puIH2qN8yLjyMiIiJyUxQe84nCo0jhZ7dZ08PkvjUk7l99zTBpWFzxqNMJnyZ98GrUG4tvYKb9UckJLA/fz+/H97D61EGsdhs77vs/fP+11Mf//bUID4sLA2o2pbpf5mOIiIiI5BeFx3yi8ChS9NitaSQe3kDCrt+J3/k7ySe251xsmPAIaY9Pk754N7kbS4lymXYnpKawO/I0zUtXybT9UnICTWa9SYrNCkDToMr0r9mEXlXqaz1JERERyVcKj/lE4VGk6EuLOkP85SCZsHsZtsToHGvda7TGp9k9+LQYgMW/bI51X+9dz/9tXJRlu4fFhf41mvBQaBuq+pZySv8iIiIiV6PwmE8UHkWKF7s1jcSDfxC7ZR5xW+fnuDQIhgnP0M74thqMd5M+mZ6RBLiYFMf8I9uZfWgL+y6dzfp2DLpVqs2jddvRLKhyltleRURERJxF4TGfKDyKFF92m42ksI3EbZlH7JZ5pF04lm2d4eqJd5M++LYejGedzhhXLNtht9vZE3ma2Ye2Mj9sO1HJWWeBbVCqAt90GUYpD+8s+0RERERulsJjPlF4FBFID4HJJ7YTt3kuMRt+IO3i8WzrzH5l8G19P37tH8K1TM1M+xLTUpl3ZBtT9vzB4egIx/Za/kGsuHuMrj6KiIg4WXZrORdHpoJuQESkODEMA/fKjSh175tUfe8wFcavxq/9Q5g8/DLVWaPPcum39zk2LoTwd7oQu3E2ttRkIP15x8HBzVnZZwzfdBlG6zLVAHg4tG2WH2yJaSmkXZ5sR0REsrdx40aCg4Pp3bu3Y9vJkycJDg6madOmmWqDg4MJDg4mJuaf2bY7depEcHAw+/btc0o/8+bNIzg4mFGjRjnleAXp008/JTg4mDfffLOgW7mqnL7nhw8f5sEHH+TUqVMF1NmtxXLtEhERyQuGyYRncFs8g9sSOHgS8TsXE7P+O+J3LAZrqqMucd8qEvetwuxTCt/bhuLX4SFcy9TCZJjoXDGEzhVD2HXhFDX9g7Kc44Nty1kRvp9nG3fj9sqh+q2piIjIdRg8eDBRUVEF3cYtQ+FRROQWYHJ1x6dpX3ya9sUaF0nMhu+JXjOFlJO7HTXW2Atc+v0DLv3+AR4hHfDv+gTeje7CMJmpV6p8lmOeiY/m633rSbam8ciq72hYqiLjmnSnTbka+fnRRERuefXr12fx4sW4ublds3bx4sUAeHvn3fPlXbt2pUGDBnl6Dsksp++51aq7d66k8CgicosxewdQousT+Hd5nKQjfxG9egqxm+ZgT0l01CTuX03i/tVYSlWhRJcn8G33IGbPzLe+rj19iJQrfuhtvxDOwCVf0bZcDSY0u5PaAWXy7TOJiNzKPDw8qF69eq5qc1t3M3x8fPDx8cnz88g/9D3PHT3zKCJyizIMA48arSjz0DSqfXSSoPs/xbVCvUw1aReOETHrGcKersT5b58k5ewhx74BNZuytPdoulWsnek9f5w+TI9Fn/DG5sUkpKbky2cREbnS1q1beeKJJ2jdujV169alY8eOTJgwgdOnT2dbf+nSJd577z26du1K/fr16d69O1OmTCEuLi7Ls4qQ/XOJGaZPn05wcDDjxo1zbMvumcecXO3Yqamp/Pe//6Vz587Uq1ePbt268eGHHxIbG5upLuN5ymHDhvHHH3/QvXt36tatS9euXTlw4EC2z99dq8dRo0YRHBycaWLGjOcNf/31VzZs2MCQIUNo3LgxzZo1Y+TIkRw5cgSATZs2MXToUBo3bkzr1q0z7cutw4cPM3bsWNq2bUuDBg3o378/K1euvOp7Tp06xcsvv0ynTp2oW7cuLVu2ZNSoUWzbti1LbcZnWbhwIVu2bGHEiBE0a9aMBg0acM899/Djjz9meY/dbmfWrFncd999tGrVivr169OlSxcmTJhAeHh4ptp/f88zxhl/d507dyY4OJiTJ0/St29fx/c1O7/99hvBwcGMHj06V9+7wkThUUSkEDB7+ePfZRSVX99GxRf/wKfFADCZHfvtSXFErfgfx8bX5tRHvUjYuxK73U7tgDJM6zKUhT0fo2WZqo56q93G5N1r6bTgQ5aHO2eCBxG5OltyAtb4qEL1ZctmWaCbNX36dAYPHszy5cspW7YsnTp1wt3dndmzZ9OnTx927tyZqf7MmTP079+fr776isTERDp06ICPjw/vv/8+L7zwgtP7uxnjx4/n008/JSgoiA4dOhAbG8sXX3xB//79iYyMzFJ/4sQJHn/8cdzd3Wnbti0mkylPrmz+/PPPDB8+nAsXLtC6dWs8PDxYtWoVDzzwALNmzWLo0KFERERw22234erqyqpVqxgwYAARERHXPjjpwbZfv3788ssvlChRgvbt2xMdHc1jjz3GkiVLsn3P5s2b6d27N7NmzcJisdChQweqVKnCypUrGTRoELNnz872fcuXL+eBBx4gLCyMZs2aUbNmTXbv3s1LL73E559/nqn2lVde4eWXX2b//v2EhobSvn177HY7s2fPpm/fvhw7dizHz1SpUiV69eqFi4sLAF26dKFXr154enrSr18/gBxXUJg7dy6Ao64o0W2rIiKFiGEYeNRsjUfN1pTq/w5RKz8nevWX2OIvpRfY7cTvWEz8jsW4V2tOiZ7P4d2oN02CKvNjj0dYefIA//fXIk7Epf8j5mRcFMOWf8N9tZrx3m33FOAnEynazs8cQ9Ty/4LdVtCtXB/DhH+XJwga/JFTDrd582YmTpyIr68vn332WaaZTL/55hveeust/vOf/7BkyRLc3d0BePXVVzlx4gTdunXj/fffdzyXuGjRIp5//nmn9OUsx48f58svv6R9+/YAxMXF8cQTT7BhwwYmTpzIu+++m6n+1KlT9OzZkw8//BAAm82GyeT8azurVq3iySef5PHHH3f01bNnT86ePcvLL7/M2LFjeeSRRwBITExkwIABHDhwgF9++YXhw4df9dhJSUmMHz+ehIQEXnzxRYYMGeL4LB9++CFTpkzJ8p7o6GiefPJJYmNjmTBhAoMGDXJM6LZ582ZGjhzJa6+9Rr169ahTp06m9y5dupSRI0fyn//8B4slPcpMnz6dt99+m6+++oqHHnoIFxcXzp49y+zZs/H39+fnn38mKCh9Ujmr1cq4ceNYtGgRX3/9Na+++mq2n6tp06Y0bdqU1atXk5qayvjx46lQoQIAvXr14t1332X9+vWcO3eO0qVLO9535swZ1q9fT/ny5WnduvXV/2IKIV15FBEppFxKViSw31tU+/AEQcM+x7Vc5ttTk8I2cebTezn+Un2i130D1jQ6VwxhRZ+neKJ+ByzGPz8CGpaqmN/tixQrUSv+V/iCI4Ddlt67k0yZMgW73c4zzzyTZQmMoUOH0q5dO86ePcvPP/8MpP9DfNWqVXh6evL2229nmtDmrrvuuuWu7AwcONARHCF9Up133nkHi8XC4sWLuXTpUpb3DBs2zPE6L4IjQIUKFTLdAuvt7U3Hjh0BqFGjBg8//LBjn4eHB507dwbg6NGj1zz2ypUrOXXqFC1atHAER0j/LGPHjiUkJCTLe3788UciIyO58847GTx4cKaZwDNuqU1LS2PatGlZ3lu5cmXGjBnjCI4AgwYNwtXVlbi4OM6cOQPA+fPnsdvt+Pj44O/v76g1m82MGTOGCRMmcNddd13z82XH29ub22+/HZvNxsKFCzPtmzdvHjabjb59++bZ32dBKnqfSESkmDG5eeLf4REqv7mL8s/8jmdol0z7U07v49xXD3L0+VpcWvZf3KxpjGvSg997P0mzoMo0C6rMfbWa5nB0EXEG/86Pg1EI/9llMqf37gRWq5VNmzYB0KpVq2xrOnToAMBff/0FpN8OCdC8efNsZx690X/855W77747y7bSpUtTr149UlNT+fvvv7Pszy5cOVuDBg2yLNUUEBAAQO3atbPs8/NLn4AtJeXaz8Vn/F1l/N1dyTAMunbtmmX7hg0bAHK8MpcRbDOOfaWGDRtm2ebq6kqJEiUASEhIv9W6Vq1alChRgvDwcO655x6+/PJL9u7di91up1y5cgwePJgmTZpc8/PlpH///kDmW1ftdjvz5s3DZDJx77333vCxb2W6bVVEpIgwDAOvul3xqtuVpGNbifxlInFb54PdDkDaxRNEzBxN5KI3KHH7M9TqPIqf7niU6ORETP/6R21SWiorTx7gjip1C+KjiBQ5QYM/otS9b2JPK1yTVBkWV0xunk45VlRUFImJ6bNGd+nS5aq1GRPnZDxzV7Zs2Wzrqlatmu32glKxYvZ3cZQrV45t27Zx7ty5TNu9vLxwdXXN874ywuCVMgJjRui6URmfqUyZ7GfwzrjV80oZVwdfeOGFqz63GhERQWpqquO5QwBfX99sazOuRNov/8xzd3fnv//9L08//TQHDx7kgw8+4IMPPqBkyZK0b9+ee+65J8vV7+vRsGFDatWqxcGDB9m2bRuNGjXir7/+4uTJk7Rr1y7H70dhp/AoIlIEuVdpQrknfiTl9H4if3uPmPXfgTUNAGtsBBfmPM+l3z8k4M5x+HV4JMv739zyG1/vW0/f6o14s2VvfFzd8/sjiBQ5JjdPcFIQK4xstvTbdi0WC7fffvtVa8uXz7x2bUYg+Lcrb1283j7yQk7rRGb0f2UIAufepnq1z3Uj3ydnye7cGb22a9cu22B7pbS0tEzft39fJb2apk2bsnz5cv744w/WrFnDxo0bOXbsGPPmzWPevHmMHDmSMWPG5Pp4/9a/f3/eeOMN5s+fT6NGjfjpp5+AojlRToYiFR7/+usvhg4dmuN+T0/PLFP/Ll68mBkzZhAWFobVaiUkJIQhQ4bQvXv3vG5XRCTPuZYLocyIqZS8+xUu/f4h0WumONaLtMacI+L7MVz67X0Cer2AX7sHMSyuLDuxl6/3rQdg3pFtbD1/gv+1H0jDQD0XKSI3zt/fHxcXF6xWK2+++WaOQetKGSHy5MmT2e7/95W8DIZhYLfbSUtLy7IvOjr6Orq+PufOnaNy5cpZtmf0n9MV1NzICJo5LVqfl5/rajImi7mev6PAwECOHj3KsGHDuO222/K0P1dXVzp37ux4jvPs2bP88MMPTJ48mS+//JJBgwZlmvDmetx111289957LFu2jPHjx7Ny5UpKlizpuO22KCqEN9/nbM+ePQDUq1ePXr16Zfm64447MtW/++67jBkzhgMHDtC4cWMaNGjAjh07ePLJJ5k0aVJBfAQRkTzhUrIiQYM/our7RynRYyyGyz9XEtMuneL8jMc5Oq420WunUdsviOalqzj2H4+9yN2/fs7kXWuxFcYJP0TkluDi4kKjRo2w2WysWrUq25p33nmH3r17M2PGDCB98hSLxcLmzZu5ePFilvqc1hH09Ey/wpvdUhPZPXfoLGvXrs2yLTw8nN27d+Pu7p7t83q5lfGZLly4kOVKbGJiIvv377/hY9+MNm3aAOmzoGYnu7+jFi1aALBixYps37N06VJ69OjB+PHjb7ivFStW0L17d15++eVM28uUKcOYMWMoX748Npstx19AZLjalU4/Pz969OhBZGQkH3/8MfHx8fTu3TvLFeaipEiGx9GjR/P+++9n+XrzzTcdtevXr2fq1KmUL1+eX3/9lcmTJzNt2jTmzp1LiRIl+Oyzz9ixY0dBfRQRkTxh8Q0kcOC7VH3vMP5dnsCw/POsTdqFY5yb9jCpb7Xh68BAxjTohOnyD800u403tizmgaVfE5EYm9PhRUSuasSIEQC89tprjslwMixdupRvv/2W/fv3U7du+vPWgYGB9O3bl+TkZMaOHetYsB1gy5YtfPHFF9meJ2MSmunTp2cKWjNnznRM2pMXJk2axK5duxzjS5cu8cwzz2Cz2RgwYEC2k/7kVtWqVXF1deXSpUssWLDAsT0lJYUJEyY4JorJbx06dKBatWrs2rWLjz76KNPts1OmTGHLli1Z3tO/f3+8vLyYNWsWM2fOzPR3dOTIEd544w2OHj1KlSpVbriv4OBgjh8/zoIFC7L8wmDjxo2cOXMGLy8vqlWrdtXjZFwhj4mJyXZ/xsQ5Gb/wKMq3rEIRu201Izxm/AfnaiZPngzAmDFjKFeunGN7SEgITz31FC+//DLTpk3TFUgRKZIs/mUJun8SJW5/hsif3yL6j2mOZyJTzx3i3P/6079WW9p1Hc2osP2cSUi/HWrN6UPcsei/fNN1KHUCyl3tFCIiWXTo0IFRo0bx2WefMWTIEOrUqUOFChUIDw9n3759ADzzzDM0btzY8Z5x48Zx6NAhNmzYQJcuXWjWrBkxMTFs3ryZsmXLZhuaHn74YbZt28a8efPYsWMHNWrU4NChQ4SFhdG3b98cF3e/WTVq1GDAgAE0a9YMb29vNm3aRExMDM2bN2fs2LE3dWxPT08eeOABpk6dyrhx4/jxxx8JCAhg27ZtJCQk0L17d5YsWeKkT5J7rq6ufPDBB4wYMYLJkyfz+++/ExISQlhYGAcPHqRx48ZZwltQUBAffvgho0eP5rXXXmPatGkEBwcTGxvL1q1bsVqtdOrUiQcffPCG+6pQoQKjR4/m448/ZtCgQTRs2JCgoCDOnz/P9u3bsdvtjB8//pqBvlq1akRERPCf//yH0NBQnnnmGSpVquTY37RpU6pVq0ZYWBhNmjS5Zhgt7IrMlce4uDiOHz9O+fLlrzlrVFxcHFu2bMHFxYVOnTpl2d+tWzcMw2Dt2rV5+lC1iEhBcylZkdLDPqfqxP34th2WaSmBxIN/4Pe/e5l7YTv9AoIc288kRNPn18ksD99XAB2LSGE3evRopk+fTqdOnTh79iyrVq0iOjqajh07MmPGjExrDkL6jKQzZsxg7NixBAQEsHr1asLDwxk5cmSOC7x37NiRqVOn0rJlS86cOcMff/xByZIlmTJlCgMGDMizz/a///2PoUOHEhYWxpo1awgMDOSZZ55h6tSpuXrG81qeffZZJkyYQEhICLt27WLz5s00bdqUefPm5eriSV6pU6cOP/30EwMGDCApKclxq+rEiRMZOHBgtu/p0KEDCxYsoF+/ftjtdtauXcuRI0do2LAhEydO5NNPP73p2z8fe+wx3n//fZo1a0ZYWBgrVqwgPDycrl27MnPmzFxdJXz55Zdp0qQJERERrF+/nrCwsCw1GUt+FPWrjgCGPafpqwqZzZs3c//999O6dWuaNWvGb7/9xokTJ/D29qZ169aMGjXKMZ3zjh076N+/P1WqVMnxNzRt2rQhIiKCJUuW3NQl8wx9+/Zlz549hIaG5tlvu0REblbyqb1cmPM88TsWZ9puWFw50agvT7gGEWtJ/weQyTCYf8djNAmqlN2hRETy3MaNGxkyZAghISFZFmsXyQ8pKSm0a9cOq9XK2rVr8fDwKOiW8lSRuW0145bV9evXs3XrVpo1a0bZsmXZs2cPixYtYvny5UyePJkWLVo4Hoy92sxKgYGBREREEBERkWN4nDVrFnPmzMlVf0eOHLm+DyQiUgDcyteh/JifSdi7gogfniU5PP3Zb3taChU3z2Kepz9fVmrFT0F16FWtEY01A6uIiBQzaWlp2O127HY7EydO5NKlS4wYMaLIB0coguGxcePGfPLJJwQGBgLpvw2YOHEiM2fO5KmnnmLZsmWOe+Ov9heccWvB1R4+joiIcJxXRKQo8azTmUqvbiZm/Xdc/On/SLt0CgBzQhSP7f+NPhH7adCu73WttyUiIlIUXLx4kY4dO2IymUhNTSUwMDDL7dZFVZEJj2+++SajRo0iMDAw04Ovrq6uvPjii/z999/s27ePRYsW4ePjk+vjXu2Zx8DAQEJDQ3N1nCNHjpCUlJTr84qIFDTDZMavzVB8mvXj0pKPiPz1HezJ8QCUuXiUc2+2IanjSErd8wZmL38AYlOS8HF1v8pRRURECregoCDKly/P2bNnadKkCa+88so151wpKopMeHR1dXU80/hvZrOZDh06sG/fPnbt2kXXrl0BrhrmkpOTgX/W1MnOwIEDc3wI+N8ynnkUESlsTG6elLzrRfzaPUjErGeJ/euH9B12O9ErPyduy08EDniXVWXq8fKmX/i263DqlSpfsE2LSLHQokULDhw4UNBtSDFjGAbLli0r6DYKRJGZbfVaypYtC6QvoprxrGN2C8dmOH/+PJD+mwUREUlf3qPsyO+o8NwyXMoEO7ZbY85zdsowUj/tg9fFYwxcMoXtEeEF2KmIiIjkhSIRHjMWR3388ce5ePFitjVnzpwB0kNkjRo1sFgshIeHO64wXikyMpKLFy/i4eGRaR0XEREBzzqdqPz6Nkrd+yaG6z/PjtePOsGUrd/Q69BK7v/tC7aeP16AXYqIiIizFYnw6Orqyrp161i+fDkrVqzIsj8lJYXFi9OnnW/Xrh1ubm60bNmSlJQUVq1alaV+yZIl2O122rVrh9lszvP+RUQKG5OLGwF3jqPKm7vxaninY7vFbuPBY3/y1uavef6niWw6d6zgmhQRERGnKhLhEWDQoEEAfPDBB+zfv9+xPSkpiRdeeIHjx4/TvHlzWrVqBcCQIUOA9MVLjx//57fj+/fvZ9KkSQA88sgj+dW+iEih5BJYhfJPLaTc6PlYAv5ZtiMk9iwfb5rKvCkPs+H0oQLsUERERJzFsNvt9oJuwhnS0tIYPXo0y5cvx2Kx0KhRI0qUKMHff//NhQsXqFatGjNmzHAs4QHw6quv8v333zuuRFqtVjZu3Ehqaipjx451anjMmDAnNDSUefPmOe24IiK3CmtCNBE/PE3MH9Mzbd/rV4HSI6bSqn6XgmlMREREnKLIhEcAu93O3LlzmTt3LgcPHsRqtVKxYkVuv/12HnzwwSwzp9rtdubNm8cPP/zA4cOHcXNzo2bNmgwfPpzOnTs7tTeFRxEpLuK2/0L4Vw9hjvtnUrIkk4XkO8bRtO/LGKYic9OLiIhIsVKkwuOtTOFRRIoTa9xF9nz5IO47f8m0Pal6a+qM/gmLr2ayFhERKWz0618REXE6s3dJ6j+9kNjBnxLt8s9dH+5H1nN8QhMSD64rwO5ERETkRig8iohInmnSdRTGuFXsKFvXsc0adZrwiZ2I/O1DdPOLiIhI4aHwKCIieapp9abc8+Y2Agd/DGZL+kablQuzn+X0p/dgjY8qyPZEREQklxQeRUQkz5lMJkp0/Q8Vx6/JtKRH/N8LOfFKM5KO/V2A3YmIiEhuKDyKiEi+8ajRksqvbcUltKtjW2pEGOFvtCFq9Ze6jVVEROQWpvAoIiL5KtrizohqXZhapQ1WDADsacmcn/4Y578Zhd2aVsAdioiISHYUHkVEJF/5u3kQHFCOmZVb8Vz9fkReMRtr9OovOT3pbmxJcQXYoYiIiGRH4VFERPKVyTDxUdt+tChdlW0lKvNok6Hs8Snr2B+/8zfC3+5IWtSZAuxSRERE/k3hUURE8p27xYWpnR+gpl8QF928GdtgAH+UquXYn3z8b0683prkU3sKsEsRERG5ksKjiIgUCH83T77r9iClPXxIMbvwap1eLKrUwrE/7eIJwt9oS8LelQXYpYiIiGRQeBQRkQJT3tufb7sNx8Pigs0w8XHVdsyt3weM9Il0bInRnPzgDmL+/LaAOxURERGFRxERKVB1Asrx3m33OMaflajBks5jMVw90jdYUzk7ZRgXF76hpTxEREQKkMKjiIgUuLurNWR47daO8TupBuce/Bqzb5Bj28X5L3Nx3gQFSBERkQKi8CgiIreE/2t2B00CK2EyDF5oeju3tbiXii/9iUuZYEdN5M9vcXHeywqQIiIiBcBS0A2IiIgAuJotTO44mLCYC9xWtnr6tqBqVHxhDSff7ULKyd0ARP78JhgGJfu8gnH52UgRERHJe7ryKCIit4yyXn6O4JjB4htIheeW4Vo+1LEtctEbXFzwan63JyIiUqwpPIqIyC3vuN2gwvPLMwfIha9zYb4CpIiISH5ReBQRkVtWms3KG5sX03H+h6yNuZQeIMvVceyPXPgaFxe8VoAdioiIFB8KjyIicssat34+k3evxWa38581szhvdssSIC8ueJWLC18vwC5FRESKB4VHERG5ZT0U2gYPiwsA0SmJPLNuLmbfoMsBsraj7uL8V4j89d2CalNERKRYUHgUEZFbVkiJMrze4i7HeO3pQ8zY/xcWv9JUeG45rmVDHPsu/DiemL9mFUSbIiIixYLCo4iI3NIG1GxKt4r/XGV8ffNiwqIvYPEvQ4XnV+BSuoZj37mvHiTx0J8F0aaIiEiRp/AoIiK3NMMweOe2vgS4eQGQZE3lqT/mkGazYvEvQ/kxv2DyCgDAnpbMqUl9SDl3uCBbFhERKZIUHkVE5JYX6OHDO7f1cYz/jjjB57vWAuBapiblR8/HsLgCYIu7yKkP78Qad7FAehURESmqFB5FRKRQuL1yXe6t3tgx/mDbMnZfPAWAR602lH5ommNf6rlDnP7kHmypyfnep4iISFGl8CgiIoXGqy16Uc7LD4A0u43Ra+eQlJYKgG/L+yjZ9581HxMP/sG5aQ9ht9sLpFcREZGiRuFRREQKDT83Dz5s088xruQTQJI11TEO6PUCvm2GOsaxG77n4oJX87VHERGRospS0A2IiIhcjzblavCf+h2p7BPAgJpNMQzDsc8wDEoPm0zqxXAS960EIHLh67gGVcP3tiEF1bKIiEiRoCuPIiJS6DzfpDsDazXLFBwzGBZXyj3xI67l/lne4+y0R0g8vCE/WxQRESlyFB5FRKTIMXv5U37Mz5h9g9I3WFM58/kgrHGRBduYiIhIIabwKCIiRcKfpw+z48JJx9glsCrl/jMXTGYA0i6e4OzUBzWBjoiIyA1SeBQRkUItIjGWJ9fOZsCSr3hm3VzSbFbHPo+at1Hq3jcd4/htPxO1dFJBtCkiIlLoKTyKiEihdizmIvOObANg36WzTNu7PtP+Ej3G4lm/h2McMWcciWGb8rVHERGRokDhUURECrVmpaswoGZTx/j9bcs4HRflGBsmE2Uf/gZLifLpG6ypnPnfQKzxl/K5UxERkcJN4VFERAq9F5veTgk3TwAS0lJ4edPPmfabfUpRZuTMK55/PM7ZqSP0/KOIiMh1UHgUEZFCL8Ddixeb3u4Y/3Z8DyvC92eq8QxuS6m+rznG8X8vJGr5f/OtRxERkcJO4VFERIqE/jWb0CyosmP80l8LSUxLyVRT4o7n8KzbzTGOmPUsSUe35FuPIiIihZnCo4iIFAkmw8RbrfpgMdJ/tIXHXeKTHasy1RgmE2Ue+Qazf9n0DdZUznw2EGt8VD53KyIiUvgoPIqISJFRO6AMD4W2cYwn717LoajzmWosvkGUHTkTLofM1IijnPtmZL72KSIiUhgpPIqISJHydMMulPfyByDVZuWFDQuyTIzjGdKekne/7BjHbfqR2M0/5WebIiIihY7Co4iIFCmeLq681qKXY1zOy48ka2qWuoBe4/EIbucYn//2P1jjIvOlRxERkcJI4VFERIqc7pVDeajObczu8TCT2g3Aw+KapcYwmSk9/EsMF3cArDHniPjh6fxuVUREpNBQeBQRkSLplRa9uK1s9avWuJapSckrlu+I+fNb4nf+ltetiYiIFEoKjyIiUqyV6DYat6rNHONz00diTYwpwI5ERERuTQqPIiJSLNjtdnZdOJVlu2G2UGbEV2B2ASAt8iQX5ozL7/ZERERueQqPIiJS5O2NPM3gpdO4/edP2XLueJb9bhXqUrLXC45x9KovSNi3Oh87FBERufUpPIqISJFmt9t57s/5rD19CIDXNv+aZekOgIA7x+FaoZ5jfO7rR7AlJ+RbnyIiIrc6hUcRESnSDMPgxWa3O8Z/R5zgl2O7stZZXNNvXzXSfzSmnj/CxfkvZ6kTEREprhQeRUSkyGtVphrdK9VxjN/e8jvJ1rQsde5Vm1Li9rGO8aUlH5N4ZGO+9CgiInKrU3gUEZFi4YWmt2O5fFXxRFwk0/etz7au5N0v41K6ZvrAbuPc1IewpSbnV5siIiK3LIVHEREpFqr7BXJ/SAvH+JMdK7mUFJ+lzuTqcfn2VQOAlNN7ufTbB/nWp4iIyK1K4VFERIqNpxt2wcfFDYDolCQ+3rEy2zqPWm3w7zTKMY785W1SL2Vd5kNERKQ4UXgUEZFiI8Ddi/806OQYf7NvA2HRF7KtLdn3Ncw+pQCwpyRw4ccXsq0TEREpLhQeRUSkWHmwdmsqePsDkGa38fbW37KtM3v5U/Ke1x3j2PXfkXj4r/xoUURE5JZUpMPjk08+SXBwMPPmzct2//r16xk+fDitWrWiUaNG3HPPPfz444/Zrv8lIiJFg7vFhXFNejjGS07s5WhM9lcf/dqNwK1iA8c44vsx2G22PO9RRETkVlRkw+OPP/7IkiVLctw/c+ZMhg8fzubNm6lTpw4tWrTgyJEjvPTSS4wbNy4fOxURkfzWu2oDGpaqSLtyNfn9riep6lsq2zrDZCZw8EeOcVLYJmI3fJdfbYqIiNxSLAXdQF44evQob731Vo77w8LCeOONN/D19eXbb78lJCQEgNOnTzN06FAWLFhA+/btueOOO/KrZRERyUeGYfB99xH4urpfs9YzpD3eTe8hbstPAET8+ALeTfpicvfO6zZFRERuKUXuymNKSgpjx47FZDJRp06dbGumTJmCzWZjxIgRjuAIUK5cOSZMmADAtGnT8qVfEREpGLkJjhkCB7yLYUmfpdUadYbIXybmVVsiIiK3rCIXHj/66CP27NnDhAkTKFu2bLY1q1evBqBbt25Z9rVu3RpfX1927drFhQvZPwMjIiLFi0tgFUrc/oxjfOn3D0k5H1aAHYmIiOS/IhUe169fz9dff03Pnj3p3bt3tjUXLlwgMjISNzc3qlatmmW/2WymWrVqABw4cCBP+xURkVvH1vMnGL9+PjZ79hPiBNz5PJYS5QGwpyVzYfZz+dmeiIhIgSsyzzxGRkby3HPPUaZMGV555ZUc686dOwdAYGAghmFkWxMYGAhARETEVc85a9Ys5syZk6v+jhw5kqs6ERHJX6k2Kw+t+JYVJ/cD0LpsdXpVrZ+lzuTmRal+b3H2y6EAxG2dT8K+VXjW7piv/YqIiBSUIhMeX3jhBS5evMg333yDr69vjnWJiYkAeHh45Fjj5pb+XEt8fPxVzxkREcGePXtuoFsREblVuJjMeFhcHOMPty3njsp1MZuy3pzj03IQUSs+J+lI+nqP579/msqvbMYwF5kfpyIiIjkqEj/tZs6cyapVq3j44Ydp3rz5VWtN2fxjICfXWu8xMDCQ0NDQXB3ryJEjJCUl5frcIiKSf8Y07MKvx3Zjx86h6PMsPLqDvtUbZakzTCYCB39E+GutAEgJ30n0mq/w7zQyv1sWERHJd4U+PB46dIh33nmH0NBQRo8efc16Ly8vgKsGueTkZAA8PT2veqyBAwcycODAXPXZt29fXaUUEblFBZcoTe9qDVgQth2Aj7av4K6q9bGYzFlqPao1x/e2IcT8OQOAi/NfxqfVIMweOd/1IiIiUhQU+vD4/vvvk5ycjLu7O+PHj8+0LyOszZkzh/Xr19OsWTO6d+8OcNWZVM+fPw9AUFBQHnUtIiK3mjENO7Po6A5sdjtHYy4w78g2+tdsmm1tqX5vEbvlJ+zJ8VhjLxC19BNK9n4pnzsWERHJX4V+ttWEhAQAtm7dys8//5zp6+zZswBs27aNn3/+mW3btuHv70/p0qVJTEwkPDw8y/GsVithYenTr9eqVSv/PoiIiBSo6n6B3HPFraofb19Jqs2aba3Fvywluj3lGF/6/QOscZF53aKIiEiBKvTh8dtvv+XAgQPZfnXu3BmAt99+mwMHDjBxYvqizh06dABg6dKlWY73559/EhsbS2hoqK48iogUM6MbdMZspP9oPBEXyZxDW3OsLdHjaUye/gDYEmO49PsH+dGiiIhIgSn04fFGDBo0CIvFwueff87OnTsd20+fPs3rr78OwMiRmvxARKS4qeJbkv41mzjGk3asINmalm2t2cufErc/4xhfWvoJadHn8rxHERGRglIsw2NISAhjxowhNjaW++67j+HDhzNy5Eh69uzJiRMnGDhwIN26dSvoNkVEpACMbtAJl8sT5ZyOj2bWwc051pbo+h/MPulrA9tTEoj89Z186VFERKQgFMvwCPDQQw/x2Wef0bhxY3bs2MHmzZupXr06EydO5OWXXy7o9kREpIBU8C7BfbWaOca7Lp7Ksdbk7k3AneMc4+iVk0mNPJmn/YmIiBQUw36txQzFKTKW6ggNDWXevHkF3Y6IiFzFmfhoxq2fz5MNOtEkqNJVa20piRx9rhbWqNMA+HV4hNLDPs+PNkVERPJVsb3yKCIikpOyXn5803XYNYMjgMnVg5J3vegYR/8xjZTzYXnZnoiISIFQeBQREblJfu0exFKqSvrAmkbkwtcKtB8REZG8oPAoIiJykwyLKyXvnuAYx6yfSfLpfQXYkYiIiPMpPIqIiFzDjgsneXjltyw+tjvHGt/W9+NaNiR9YLdxcf4r+dOciIhIPlF4FBERuYpPdqyk58//5bfje/h05ypymmfOMJkp2eef2brjNs8l6fi2/GpTREQkzyk8ioiIXEXnCiGO17sunmLt6UM51no3vRe3ig0c44vztPSTiIgUHQqPIiIiVxFashwdywc7xp/uXJVjrWEyUbLvq45x/I5fSTz8V572JyIikl8UHkVERK7hifodHK//OnuUreeP51jr1fBO3Ku1cIwvauZVEREpIhQeRURErqFFmao0L13FMf7vztU51hqGQcm+rzjGCbuW6NlHEREpEhQeRUREcuHxeh0cr5eF72Nf5Nkcaz1Du+JWpYljfOnXd/OyNRERkXyR6/BotVpZu3Ytv/zyC+fOnXNs37BhA88++yyPPvoon332GXFxcXnSqIiISEHqVCGYOgFlHeP/7VqdY61hGAT0fM4xjt08l5Rzh/OwOxERkbxnyU1RfHw8Q4cOZc+ePdjtdtzd3fn888+JiYlh9OjRuLm5kZaWxpo1a/j111+ZM2cOXl5eed27iIhIvjEMgyfqdWDUmh8AWHR0B8827kpln5LZ1ns36YNLmVqknj0IdhuXFr9H6eFf5GfLIiIiTpWrK4/Tp09n//79PPPMM3z88ceULl2a119/nSlTpvDxxx+zbds2tm3bxgsvvEBYWBhff/11XvctIiKS73pWqUeVy2HRZrczedfaHGsNk5mAO551jGP+nEHapdN53qOIiEheyVV4/P333+nbty8jRoygR48ejB8/nrCwMJo1a0aPHj0wmUy4uroyZMgQOnbsyPLly/O6bxERkXxnNpl4rF57x/hE3CVsdluO9b6t78dSojwA9rQULi35OK9bFBERyTO5Co8nT56kbt26jnFISPqCyY0bN85S27x5c44fz3kKcxERkcLs3hqNubd6Yxbc8Rgzuz2Iycj5R6lhcaVEj6cd46jVX2CNv5QfbYqIiDhdrsKjyWTCarU6xm5ubgB4e3tnqfX09MxUKyIiUpS4mS183K4/TUtXzlW9X/uHMHkFAGBPiiNq+f/ysj0REZE8k6vwGBQUxNmz/0xJ7uXlxf/93/9RrVq1LLWnTp0iICDAeR2KiIgUYiZ3b0p0/Y9jfGnZJ9iS4wuwIxERkRuTq/AYGhrKtm3/LHDs6urK4MGDKV26dJba9evXU7t2bed1KCIiUsj5d3kcwy19FnJb3EWi104r4I5ERESuX67C49ixY3n22WevWXfx4kVq1KhB//79b7oxERGRwmDnhZM8vuYHFoXtyLHG7F0Svw4PO8aXfvsAe1pKfrQnIiLiNLla57Fs2bKULVv2mnUlS5bk7bffvummRERECoP/7lzFxK1LAAiLvkCvqvUxDCPb2hLdx6Q/72hNJS0ynJgN3+PXdlg+disiInJzcnXlUURERLLqVCHY8XrXxVP8de5ojrUuARXwve0Bx/jS4vew23Je5kNERORWo/AoIiJyg+oElKNtuRqO8Ze7/7hqfcAdz8LlK5MpZ/YTt21hnvYnIiLiTDcVHlNTU+nVqxcrV650Vj8iIiKFysOhbR2vl4XvIyw6Isda1zK18G7S1zGO/OUd7HZ7nvYnIiLiLDcVHu12O4cOHSImJsZZ/YiIiBQqHcrXpKZfkGM8Zc+6q9YH3DnO8Tr56GYS96/Js95EREScSbetioiI3ASTYeLhum0c4x8P/01kUs7rOLpXaYxnaGfH+NKyT/K0PxEREWdReBQREblJfas1oqR7+jqOSdZUvt3/11Xr/bs95Xgdv20RKefD8rI9ERERp1B4FBERuUnuFheGhrRyjKfv30CyNS3Heq96PXApUyt9YLcTtfy/ed2iiIjITVN4FBERcYIhIS1xM6cvnxyRGMeCsO051homEyW6PukYx6ydhjVR8weIiMitTeFRRETECUp5eHNP9caO8YYzV78V1fe2BzB5+gNgS4ol5o/pedidiIjIzVN4FBERcZKHQ9vQo1Io8+8YyUdt+1211uTujV/7hxzjqGWfYrdZ87pFERGRG6bwKCIi4iQ1/YP4qvMDNCtdBcMwrlnv3+VxMJkBSI0II377L3ndooiIyA1TeBQRESkgLiUr4d2kj2N8aamW7RARkVuXwqOIiEgBKtFttON14v7VJB3fXnDNiIiIXMVNhUdXV1dWrFhBt27dnNWPiIhIkbHn4mme/fMnLiXF51jjXqMVblWbOcZRy3T1UUREbk03feWxfPnyeHp6OqMXERGRIuPRVTPpvugTfji4me8Pbs6xzjAMSnT7Z9mO2L9+IC36XH60KCIicl1026qIiEgeqOEX6Hj9zf4NpF1lJlWfZvdi9i8HgD0thehVX+R5fyIiItfLkhcHTUlJISwsjLi4OOx2+1VrmzVrdtX9IiIihdEDIS35387VpNltnI6PZsmJvfSsUi/bWsPiin/nUVz86SUAolZ+Tomez2NyccvPlkVERK7K6eHxo48+YsaMGSQlJV2z1jAM9u7d6+wWREREClwZT196Vq3HwrAdAEzbuz7H8Ajg3+FhIhe9gT01CWvMeWI3zsKvzdD8aldEROSanHrb6vTp0/niiy9ITEzEbrdf88tmsznz9CIiIreUB2vf5ni98dxR9kaezrHW7FMK39secIyjln5yzbt3RERE8pNTrzzOmTMHwzDo27cvjz/+OEFBQVgseXJnrIiIyC2vcWBFGpSqwI4LJ4H0q4/vt7k3x3r/rk8SvXoKAMkntpN4YC2eIe3zpVcREZFrceqVx/DwcEqWLMnrr79OuXLlFBxFRKRYMwyD4bVbO8bzw7YTeZVlO9zK18GzblfH+NLSSXnan4iIyPVwanj09vYmMDAQk0mTuIqIiAD0qlqfUu7eACRb0666bAekX33MEL/tZ1IvhudpfyIiIrnl1JTXrFkzjh49Snx8zr9VFRERKU7czBYGBzd3jL/Zd/VlO7zq9cAlsGr6wG5z3MYqIiJS0JwaHkeNGoXVauXVV1/VQ/4iIiKXPRDSEouR/iP3TEI0a04dyrHWMJnw6zjSMY5eOxV7Wkqe9ygiInItTn0oMSQkhEmTJvHEE0+wfft2brvtNgICAjAMI8f3PPHEE85sQURE5JZTxtOXu6o1ICE1hQfrtKZVmWpXrfdrO4yL8yZgT0vGGn2WuL8X4NO8fz51KyIikj2nhse4uDimTJmCzWYjPDycWbNmXfM9Co8iIlIcfNy2HyYjdzf8mH1K4d28H7HrvwMgasVkhUcRESlwTg2PH3/8Mdu2bQMgMDCQcuXK4eLi4sxTiIiIFEq5DY4Z/Ds95giPiQfWkHxqD27lQ/OiNRERkVxxanhcvnw5hmHw1ltv0adPH2ceWkREpFhxr94Ct0oNST6xHYDolV8Q9MAnBduUiIgUa06dMCcyMpLKlSsrOIqIiFzDgUvnWH3qYI77DcPAr9M/E+fE/DkDW1JcfrQmIiKSLaeGx6CgIMxmszMPKSIiUqQcjDrHgN+n0HnBRzy77qerLtvh22oQJg9fAGxJscRsmJlfbYqIiGTh1PDYvXt3wsLC2LNnjzMPKyIiUmT4uXqw8exRIH3ZjqUn9uVYa3LzwrfNUMc4auVkLYUlIiIFxqnh8bHHHqNSpUo89thj/P7778THxzvz8CIiIoVeaU9felat5xh/s3/DVev9Oj7qeJ0SvpOkw1evFxERyStOnTDntddeo2LFiqxbt44xY8ZgGAY+Pj54eHhkW28YBqtWrXJmCyIiIre8oSGtWBi2A4A/zxzhUNR5avoHZVvrVq42HrU7krgv/edl1MrP8ajZOt96FRERyeDUK4+LFi1i3bp1ANjtdmw2G9HR0Zw9ezbHLxERkeKmWVBlapco4xjP2P/XVev9r5g4J27zXNJiIvKsNxERkZw49crj22+/7czDXTebzcbs2bOZO3cuR44cwTAMqlevzt13383AgQOxWLJ+3MWLFzNjxgzCwsKwWq2EhIQwZMgQunfvXgCfQEREigPDMBhauxXj1s8HYO7hrYxr0h0vF7ds670b9cbsXxZr1BnsaSnE/PE1AT2fy8+WRUREMOxF6Mn75557joULF+Lu7k7jxo1xcXHh77//JjY2lubNmzN16lRcXV0d9e+++y5Tp07F09OTFi1akJKSwqZNm0hNTWXUqFGMHj3aab317duXPXv2EBoayrx585x2XBERKZziU5NpOvstYlOTAZjYqg/3h7TIsf7C/FeIXPg6AJZSVaj67kEMk2Y4FxGR/OPU21YL0sKFC1m4cCHly5fnt99+4+uvv+bLL79k2bJl1K5dm02bNjFjxgxH/fr165k6dSrly5fn119/ZfLkyUybNo25c+dSokQJPvvsM3bs2FGAn0hERIoyLxc3+tVo4hhP37/hqjOp+rV/CC6HxbQLx4jf+Xue9ygiInKlIhMe589Pv/VnzJgxlCtXzrG9RIkSPPLIIwCsXbvWsX3y5MnZ1oeEhPDUU08BMG3atLxuW0REirGhtVs5Xu+/dJZN547lWOsSUAHvRr0c4+hVk/OyNRERkSyKTHj88ssv+fnnn+nSpUuWfTabDQAXFxcA4uLi2LJlCy4uLnTq1ClLfbdu3TAMg7Vr1zreKyIi4mzV/QJpU7aGY3ytiXP8Oj3meB2/8zdSI47mWW8iIiL/VmTCo6urK7Vq1cqyLMiRI0f49NNPgfTnDjO2Wa1Wypcvj5eXV5ZjBQQEUKpUKRISEjhx4kTeNy8iIsXW0NotMTDoXCGE/jWbXLXWs3YnXMrUSh/Y7USvmZoPHYqIiKRz6myrt5Lnn3+eI0eOsHv3bjw8PBg/fjw9e/YE4Ny5cwCULl06x/cHBgYSERFBREQEVapUybZm1qxZzJkzJ1f9HDly5Po+gIiIFAtdK9bmz3ufpZJPwDVrDZMJv/YPc2H2swBE//E1Je9+GcPiktdtioiIFM3wGBcXx4IFCxxjwzA4ceIE8fHxeHl5kZCQAJDlKuWV3NzSp0vPqM1OREQEe/bscU7TIiJSLFlM5lwFxwx+bYZw8acXsaelYI0+S/yOX/FucnfeNSgiInJZkQyPrq6urFu3Dk9PT3bt2sXEiROZOXMmBw4c4LvvvsNszv3U5ld75jEwMJDQ0NBcHefIkSMkJSXl+rwiIiLZMfuUwrtJH2I3zgYgas0UhUcREckXRTY8BgYGAtCyZUu+/vprevXqxZYtW1izZo3jOcerhbnk5PR1tzw9PXOsGThwIAMHDsxVTxnrPIqIiFzLmfhoynr55bjfr/1DjvCYsGsJqReO41Kqcn61JyIixVSRmTDnakqUKEH79u0B2L17t+NZx4iIiBzfc/78eQCCgoLyvkERESn27HY7y07sZfDSaTSfM5HDUedzrPUI6YBL6RoZbyT6j6/zqUsRESnObvjKY4cOHW765IZhsGrVqps+TkpKCu+//z5nz57lvffeczyveCVXV1cA0tLSqFGjBhaLhfDwcJKTk7PUR0ZGcvHiRTw8PKhUqdJN9yciIpIb7/69lH2XzgLwzf6/eL3lXdnWpU+c8xAX5owDIGbtNEre9RKGuUjeUCQiIreIG77yePbsWad8OYOrqyu///47S5YsyTaMpqSksH79egDq1auHm5sbLVu2JCUlJdv6JUuWYLfbadeu3XU9HykiInKjDMNgaO1WjvHcw1uJT03Osd73tiFwOSymXTpF/M7f8rxHEREp3m74V5Rvv/22M/u4aYMGDeKjjz7irbfeonbt2lSunP7sR0JCAq+88grHjh2jVq1ajiumQ4YMYd26dUycODFT/f79+5k0aRIAjzzySIF8FhERKZ76VGvIm5sXE5uaTGxqMvOPbOf+kBbZ1lr8SuPdqDdxW34CIHr1FLwb9crPdkVEpJi54fDYp08fZ/Zx00aMGMH27dtZtWoVPXv2pEmTJri5ubFr1y4iIyOpWLEin332meNKYvv27Rk0aBDff/89vXr1omXLllitVjZu3Ehqaipjx46lbt26BfypRESkOPFycaNfjSZM25d+t8z0/RsYHNwcwzCyrffr8LAjPMbv/I3UyJO4BFTIt35FRKR4yZOHI+Li4vjuu+9Yvnw5R48eJSEhAU9PTypXrkz79u0ZOnQo/v7+Tj2ni4sLn332GXPmzOGnn35ix44d2Gw2KlWqxH333cfw4cPx8fHJ9J4JEyZQt25dfvjhBzZt2oSbmxsNGzZk+PDhdO7c2an9iYiI5MaQkJaO8Lj/0lk2nTtGizJVs631rNMZl8CqpEYcBbuNmD++pmTv/8vPdkVEpBgx7Ha73ZkHPHjwICNHjuTMmTNkd2jDMChTpgyff/45ISEhzjz1LS1jqY7Q0FDmzZtX0O2IiMgtbODvX7HuzGEAeldtwP863Jdj7cWf3+biTy8BYAmoSNX3j2CY9Ly+iIg4n1OvPMbGxvLoo49y5swZSpUqxT333EPdunXx9vYmOjqa3bt3s2DBAs6cOcPjjz/OwoUL8fb2dmYLIiIihd7Q2i0d4XHx8d2cT4glyNMn21q/tsO4OP9lsFlJiwwnYfdSvOrfnp/tiohIMeHUdR6/+eYbzpw5Q6NGjVi8eDFjxoyha9eutGrVih49evDMM8+wePFiGjZsyOnTp5k1a5YzTy8iIlIkdK1Ym7KefgCk2qx8f3BTjrUW/7J4NbzTMY5aPSXP+xMRkeLJqeFx+fLlmM1m3nvvPXx9fbOt8fX15b333sMwDH7//Xdnnl5ERKRIsJjM3B/c3DH+7sBG0mzWHOv9OzzseB2//RfSos7kaX8iIlI8OTU8Hj9+nGrVqlGhwtVneqtYsSLVq1fnxIkTzjy9iIhIkXFfrea4XH52sZZ/aS4mxedY61m3G5aSldIHNivRf0zPhw5FRKS4cWp4tNvtuLi45KrWYrGQmprqzNOLiIgUGUGePrx3W1/W9h3L991HUNoz+zt6AAyTGb92DzrG0Wu+wm6z5UebIiJSjDg1PJYvX55Dhw4RGRl51brIyEgOHTpE2bJlnXl6ERGRIuXeGk2o5heYq1rftsPBSP+xnnbhGAl7l+dlayIiUgw5NTy2a9eO1NRUJkyYQFpaWrY1aWlpvPTSS1itVtq3b+/M04uIiBRbLgEV8Gpwh2McrYlzRETEyZwaHocNG4aPjw8rVqzgnnvuYdasWezatYtjx46xa9cuZs2aRd++fVm1ahXe3t4MGzbMmacXEREp1vyumDgnbtsi0mLOF2A3IiJS1Dh1ncfSpUvzySef8Pjjj3PgwAFeffXVLDV2ux0vLy8+/vhjSpcu7czTi4iIFEk2u421pw/zzb4NdKlYm8FXzMR6Ja96PTD7l8MadRqsacT8+S0Bt4/N525FRKSocuqVR4BWrVrxyy+/0L9/f4KCgrDb7Y6vUqVK0b9/fxYsWMBtt93m7FOLiIgUSR9vX8n9S6exLHwfX+9bj91uz7bOMFvwazvMMY5ZOy3HWhERkevl1CuPGcqVK8drr70GQHx8PHFxcXh5eeHt7Z0XpxMRESnSeldrwIfb0yfA2X/pLJvOHaNFmarZ1vq2HU7kz28BkHJmP0mH1+NRU7+wFRGRm+f0K4//5uXlRenSpRUcRUREblB1v0DalK3hGH+zf0OOta5B1fCo3ckxjl47LU97ExGR4iNPrjympKQQFhZGXFzcNW+XadasWV60ICIiUqQMrd2SdWcOA7D42G7OJ8QS5OmTba1f+wdJ3LcSgNiNcwgc9BFmj5zXiRQREckNp4fHjz76iBkzZpCUlHTNWsMw2Lt3r7NbEBERKXK6VqxNWU8/ziREk2a38f3BTTzVsHO2td6N+2DyKoEt/hL2lARiN87Cv8Mj+dyxiIgUNU69bXX69Ol88cUXJCYmZpooJ6cvm83mzNOLiIgUWRaTmfuvmGX1uwMbSbNZs601ubrj22qwYxyz9us8709ERIo+p155nDNnDoZh0LdvXx5//HGCgoKwWPLkzlgREZFiZ1Bwcz7esZJUm5WzCTEsPbGPO6rUzbbWr/0Iopb/F4CksE0kh+/ErWL9/GxXRESKGKdeeQwPD6dkyZK8/vrrlCtXTsFRRETEiQI9fDKFxatNnONWsT5uVZs6xpo4R0REbpZTw6O3tzeBgYGYTHk+iauIiEixNDSkleP1n2eOcCjqfI61fu0edLyOWT8TW8q15yMQERHJiVNTXrNmzTh69Cjx8fHOPKyIiIhc1iyoMrVLlHGMV586kGOtT8v7MFw9AbDFRxL394K8bk9ERIowp4bHUaNGYbVaefXVV6+5RIeIiIhcP8MweLRuO4aEtGT53U/xcGjbHGvNHr74NLvXMY7RrasiInITnPpQYkhICJMmTeKJJ55g+/bt3HbbbQQEBGAYRo7veeKJJ5zZgoiISJF3b43G3Fujca5q/dqPIObPGQAk7F1BasRRXAKr5mV7IiJSRDk1PMbFxTFlyhRsNhvh4eHMmjXrmu9ReBQREck77jVvw6VMMKln029vjV77NaXuea2AuxIRkcLIqeHx448/Ztu2bQAEBgZSrlw5XFxcnHkKERERuQ6GYeDX7kEuzHkegJh10ynZ52UMk7mAOxMRkcLGqeFx+fLlGIbBW2+9RZ8+fZx5aBEREcmG3W5nw9kw9kae4aHQNtnW+N72ABd+ehGsaaRdOkX8riV4N7gjnzsVEZHCzqkT5kRGRlK5cmUFRxERkXwQHhtJ5wUf0f/3KbyxeTHnE2KzrbP4lca7YS/HOGbt1PxqUUREihCnhsegoCDMZt0GIyIikh/KevkRl5oMQJrdxvcHN+VY63vFmo9x238hLfpcnvcnIiJFi1PDY/fu3QkLC2PPnj3OPKyIiIhkw2Iyc39wC8f4uwMbSbNZs631qtcdS4ny6QNrGjF/fpsfLYqISBHi1PD42GOPUalSJR577DF+//134uPjnXl4ERER+Zf7ajXD5fLkN2cTYlh6Yl+2dYbJjG/b4Y5x9NqpWpNZRESui1MnzHnttdeoWLEi69atY8yYMRiGgY+PDx4eHtnWG4bBqlWrnNmCiIhIsRLo4cMdVeqyMGwHAN/s38AdVepmW+vXdhiRi94AIPXsQRIPrsMzuG2+9SoiIoWbU8PjokWLHK/tdjt2u53o6Giio6OzrTcMw5mnFxERKZaGhrRyhMc/zxzhUNR5avoHZalzCayKZ2hnEvasACBm7TSFRxERyTWnhse3337bmYcTERGRXGgWVJnaJcqw79JZAGbs/4vXW96Vba1fuxGO8Bi7+UcCB3+M2dMv33oVEZHCy6nhUUt0iIiI5D/DMBhauxXj1s8HYO7hrYxr0h0vF7cstV6N78bkFYAtPhJ7SiKxG2fh3/HR/G5ZREQKIadOmHO9Tp06VZCnFxERKTL6VGuIz+WwGJuazPwj27OtM7m44dv6fsc4eu20/GhPRESKAKeGxx9++CHXtTNnzqRXr17XLhQREZFr8nJxo1+NJo7x9P0bcpxN1e+KNR+Tj24h+cSOPO9PREQKP6eGx9dff5158+ZdtebUqVMMGzaMN954g8TERGeeXkREpFgbWrsV7mYXBtZsyift+uc4MZ1bxXq4V2vuGOvqo4iI5IZTw6PNZuP//u//Ms26eqUffviBXr16sXHjRux2O/369XPm6UVERIq16n6BbBv4Iu+3uZc6AeWuWut7xdXHmPXfYUvRL3RFROTqnBoe/+///g+bzcYLL7zA4sWLHdszrja+9tprJCQkULFiRb755htee+01Z55eRESk2PNxdc9VnW+LgRhuXgDYEqKI2zo/L9sSEZEiwKmzrQ4ePBiLxcIrr7zCc889h4uLCxcuXOC9994jMTERk8nEsGHDePLJJ3FzyzoDnIiIiOQPk4cPPs37EfPHdACi136Nb6tBBduUiIjc0pwaHgEGDBiA2WxmwoQJPPnkkwDY7XZCQkJ48803CQ0NdfYpRUREJBt2u53N549Tr2Q5PCyuWfb7tRvhCI+J+1aScv4IrkHV87lLEREpLPJkqY57772Xt956y/Ggfrdu3fjpp58UHEVERPLJwrAd3L7oU/ounsy8HJbtcK/RCtdytR3jmLVf51N3IiJSGOXZOo9333037777LiaTidWrV7Nhw4a8OpWIiIj8y6Zzx9gdeRqAaXv/zHbZDsMw8G37z8Q50eu+wW5Ny7ceRUSkcLnh21Y7dOiQqzqz2UxqaiqPPfYYJUuWzLTPMAxWrVp1oy2IiIhIDobXbsU3+9N/cXsg6hwbzobRumzWW1J9b7ufC3NfAGsq1qjTxO/6He+Gd+Z3uyIiUgjccHg8e/bsddWnpqZmeU9O60+JiIjIzanhH0T78rVYc+ogANP2rs82PFp8g/BudBdxW34CIHrNVIVHERHJ1g2Hx7ffftuZfYiIiIiTPVi7tSM8Lg3fS3hsJBV9ArLU+bV70BEe43f8SlrUWSz+ZfK1VxERufXdcHjs06ePM/sQERERJ+tYoRZVfEpyLPYiNrudb/b/xUvN7shS51m3K5aAiqRFhoPNSsyfMwjo+VwBdCwiIreyPJswR0RERAqWyTAxrHYrx/iHg5tJTEvJUmeYzPi2He4YR6+dmu0EOyIiUrwpPIqIiBRh/Ws2xevyGo/RKYk5Ltvh13YYXJ6LIPXcYRL3r8mnDkVEpLBQeBQRESnCfF3d6VeziWOc07IdLqUq4xna1TGOXvNVvvQnIiKFh8KjiIhIETe8dmvH6wNR51h/NizbOr/2Dzlex22ZhzXuYp73JiIihYfCo4iISBFX3S+Q9uVr4Woyc2/1xpT28Mm2zrvRXZh9SwNgT0sm5s/v8rNNERG5xd3wbKsiIiJSeLzWohe+ru4E5hAcAQyLC75thnJp8btA+q2r/t2e1LrMIiIC6MqjiIhIsVDdL/CqwTGDX/sRjtcpp/eSdHh9XrYlIiKFyA2Hx759+zJp0iS2bdum6bxFRESKCNfSNfCo3ckxjl6tiXNERCTdDYfHEydO8PnnnzNo0CBatWrFM888w8KFC4mMjHRmfyIiIpIH7HY75xNis9135dXH2M0/Yo2PyqeuRETkVnbDzzxu3LiRv//+m9WrV7N27Vp++eUXfv31VwzDoG7durRv3562bdtSv359Z/Z7TQsXLmTu3Lns37+fxMRESpYsSatWrXjkkUeoVq1alvrFixczY8YMwsLCsFqthISEMGTIELp3756vfYuIiOSHVJuVX4/tYsqedVxMimPdPc9iMZkz1Xg36YPJuyS2uIvYUxKJ3fA9/l1GFVDHIiJyqzDsTrrn9Ny5c6xevZo1a9bw119/kZCQgGEYBAQE0LZtW9q1a0ebNm3w9fV1xumysNvtPPPMM/zyyy+4uLhQt25dAgIC2L9/P6dOncLDw4PPP/+cVq1aOd7z7rvvMnXqVDw9PWnRogUpKSls2rSJ1NRURo0axejRo53WX9++fdmzZw+hoaHMmzfPaccVERG5Hqfjo2n94zuk2W0AfN5hEL2qZv1Fb8QPz3BpyUcAuFasT+XX/tbEOSIixZzTwuOVUlNT2bJlC2vWrGHt2rWEhYVhGAYmk4n69evToUMH2rVrR+3atZ12zoULF/Lcc88RFBTE1KlTqVWrFgBWq5VPPvmEyZMnU6pUKZYtW4anpyfr169n+PDhlC9fnu+++45y5coBsH//foYNG8alS5eYM2cODRo0cEp/Co8iInKr+M+aWcwP2w5Aw1IV+fnOUVmCYcrp/Rx7IdQxrjhhAx7VmudnmyIicovJk9lWXVxcaNWqFePGjWPx4sUsX76cl156iTZt2rB//34++ugj+vbtS7t27Zx2zrlz5wIwduxYR3AEMJvNPPXUU9SsWZMLFy6wfn36rHGTJ08GYMyYMY7gCBASEsJTTz0FwLRp05zWn4iIyK3ikdC2jtfbL4Sz5fzxLDWu5ULwqPVPnSbOERGRfFmqo0KFCgwePJgvvviCjRs3MmXKFAYPHoyHh4fTzuHr60v16tVp0qRJln2GYVC1alUAzp8/T1xcHFu2bMHFxYVOnTplqe/WrRuGYbB27VpsNpvTehQREbkV1CtVnlZl/pkH4Ivdf2Rb59fhIcfr2I2zsCVmP8GOiIgUDzc8Yc6NcnV1pW3btrRt2/baxdfhf//7X477rFYre/bsAaBs2bIcOXIEq9VKxYoV8fLyylIfEBBAqVKliIiI4MSJE1SpUsWpvYqIiBS0R+u2ZcPZMACWnNjLsZiLVPEtmanGu+k9mL4bjS0hCntyPDEbf8C/wyMF0a6IiNwC8uXKY0H7/vvvOXXqFCVKlKBly5acO3cOgNKlS+f4nsDAQAAiIiLypUcREZH81KlCMNV8SwFgx85Xe9dlqTG5euDb+n7HOHrN1HzrT0REbj35fuUxv23YsIF3330XSH8e0sPDg4SEBICr3jbr5uYG4KjNzqxZs5gzZ06u+jhy5EhuWxYREclzJsPEw6FtGL9hAQCzD23hmUZd8XfzzFTn1/4hopb/F4Dko1tIOr4N98qN8rtdERG5BRTp8Lhq1SqeeuopUlJSGDRoEP369QPSJ9HJras98xgREeG4HVZERKSwubdGY979eymXkhNITEvluwObeKJ+h0w1bhXr4V69JUlH/gIges1XuA/J+VEREREpuopsePz22295++23sVqtPPDAA7z44ouOfRnPOSYlJeX4/uTkZAA8PT1zrAkMDCQ0NDTH/Vc6cuTIVc8nIiKS3zwsrgwJacmkHSsB+Hrfeh4JbYOrOfM/D/w6POQIj7HrZxI44F1MblnnDBARkaKtyIXHtLQ0XnvtNWbPno1hGIwdO5ZHHsn8cH/Gs45Xe57x/PnzAAQFBeVYM3DgQAYOHJirvjLWeRQREbmVDA1pxee71mCz27mtbHXiUpMJ+Fd49Gnen4jvn8aWGIMtKZbYjbPxa/dgAXUsIiIFJU/CY0pKCidPnsRut1O2bNmrXr1zpqSkJB5//HHWrVuHu7s777zzDj169MhSV6NGDSwWC+Hh4SQnJzueb8wQGRnJxYsX8fDwoFKlSvnSu4iISEEI8vThk3YDaBxUmXJeftnWmNy88Gk1iOiV6WskR6+eovAoIlIMOTU8Hj9+nHfffZc1a9ZgtVod26tUqUKHDh249957qV69ujNP6WC1Wh3BMSAggC+++IL69etnW+vm5kbLli1Zt24dq1atyhIwlyxZgt1up127dtf1fKSIiEhhdGfV7H9eXsm/wyOO8JgUtomkY1txr5J1bWURESm6nLZUx7Fjx+jXrx8rV64kLS0Nu93u+Dp69CjTp0+nV69evPTSS8TFxTnrtA6ff/4569atw9PTkxkzZuQYHDMMGTIEgIkTJ3L8+HHH9v379zNp0iSALLe7ioiIFFdulRrgXqOVYxx1OUiKiEjx4bQrjx999BExMTFYLBaGDBlCx44d8fb2JiIigt27d7NixQr27NnDTz/9xI4dO5g2bZpjLcWbFR0dzdSp6WtPBQUF8cUXX+RY27t3b9q2bUv79u0ZNGgQ33//Pb169aJly5ZYrVY2btxIamoqY8eOpW7duk7pT0REpDCx2+0kpqXi6eKaabt/x0c5e3gDALF//UDggPcwe/kXQIciIlIQDLvdbnfGgVq1akVUVBQTJ06kd+/e2db89ddfvPTSS5w8eZJ69eoxe/ZsTKabv/i5bNkynnjiiVzVjh8/nmHDhgHpPxznzZvHDz/8wOHDh3Fzc6NmzZoMHz6czp0733RfV8qYMCc0NJR58+Y59dgiIiLOYLPb+O34Hv67czU1/AL5tH3mSeFsKUmEPV0JW9xFAAIHf0yJrv8piFZFRKQAOC08hoaGYrFY2LZt21UDYWRkJAMGDODkyZO88sorDBgwwBmnv+UpPIqIyK3ut+O7eXjldwCYDRN/3PMMlXwCMtVEzH6eS7+9D4Br2RAqv7UbwzDyvVcREcl/Tnvm0d3dHVdX12teSQwICODFF1/Ebrczf/58Z51eREREblLXirWpfDksWu02Ju9em6XGr+M/8wGknNlP4v7V+dWeiIgUMKeFx4oVKxIXF8eJEyeuWdu2bVtcXV05dOiQs04vIiIiN8liMvNYvfaO8exDWzifEJupxjWoOp71ujvGmjhHRKT4cFp47NOnD3a7nQ8//PCatWazGXd3d93mIiIicovpV6MJpT18AEi2pjFlz7osNf6dRjpex/29gLSoM/nWn4iIFBynhcfBgwdTq1YtlixZwiuvvEJqamqOtUeOHCEmJoYaNWo46/QiIiLiBG5mCw+HtnWMZ+zfQFRyQqYarwY9sQRUTB9Y04heMzU/WxQRkQLitPBosViYNGkSvr6+zJ49mzvuuINvv/2WU6dOZao7fPgwTz/9NADDhw931ulFRETESe4PaYGfqwcA8WkpfLNvQ6b9hsmMX4eHHePoNVOwW9PytUcREcl/TguPAFWrVuWHH36gRo0ahIeH89Zbb9GlSxdatmxJr1696NSpE7169eLMmTO89dZbdO/e/doHFRERkXzl7eLG8DqtHeOpe9eTkJqSqcav3Qgwpy8XnRZ5kvjtv+RrjyIikv+cGh4BqlWrxvz583n11VcJCQnBbrcTFRXFoUOHOH36NHa7ndjYWD766CNGjhzJpEmTWLZsGSdPnnR2KyIiInKDRtRujYfFBYDI5Hi+P7gp036Lfxm8m/RxjKNWaeIcEZGizmnrPObk/Pnz/P333+zZs4e9e/eyZ88eoqKi/mngiklzfHx8qF27Nt98801etlQgtM6jiIgUNq9u+sUxYU5ZTz/+vPdZXC9fbQRI2Leak+90doyrvHMA19Kaz0BEpKiyXLvk5gQFBdGjRw969Ojh2Hb69Gn27t3L7t272bt3L3v37uXChQvExMSwadOmqxxNRERE8svDoW2Zvm8DNrud28pWJz41OVN49Ahpj2u52qSc3gdA9KovCRz4bkG1KyIieSzPw2N2ypUrR7ly5ejSpYtj27lz5xxXJkVERKTglfPy48M2/WgaVImKPgFZ9huGgV/HkUTMHA1A9B9fU7Lvq5guT7YjIiJFi9OfebxRpUuXpmPHjjzxxBMF3YqIiIhc1qd6w2yDYwbf2x7AcPUEwBYfSdzmH/OrNRERyWe3THgUERGRwsfs6YdPy/sc46iVXxRgNyIikpcUHkVERCTX7HY70cmJmbb5dxrpeJ105C+Sjm3N77ZERCQfKDyKiIjINdnsNn47vps7f/kfQ5dP58rJ2t2rNMa9ekvH+NLSTwqiRRERyWMKjyIiInJNOy6c4uGV37Hjwkm2nD/O6lMHM+337/ofx+vYjbNJizqb3y2KiEgeU3gUERGRa2oUWJH25Ws5xu9vW5bp6qNP03uwlCifPrCmErVqcn63KCIieUzhUURERHLlmUZdHa93XDjJ8vB9jrFhccG/8yjHOHrVF9hSkvK1PxERyVsKjyIiIpIrjQIr0qViiGP8/rZl2Ow2x9ivw8MYLu4AWGPOE7txVr73KCIieUfhUURERHLtyquPeyLP8PvxvY6x2bskvq3vd4yjln2a6dZWEREp3BQeRUREJNfqlixPj0qhjvEH/7r6eOXEOckntpN48I987U9ERPKOwqOIiIhcl7FXXH08EHWOX47ucozdKtTFM7SzYxy1dFK+9iYiInlH4VFERESuS+2AMvSqUt8x/nD7cqy2K68+Pul4Hff3IlIjjuZrfyIikjcUHkVEROS6Pd2oCwYGAIejI1hwdIdjn1f9O3ApXSN9YLcRtfx/BdGiiIg4mcKjiIiIXLea/kHcXa0BJsOgX43GNAms5NhnmEz4d/nn2cfotdOwJcYWRJsiIuJECo8iIiJyQ55v0p1VfZ7mo7b9qeJbMtM+vzZDMXn4AmBLjCb6zxkF0aKIiDiRwqOIiIjckAreJajuF5jtPpOHD77tHnSMo5Z9iv2K5yJFRKTwUXgUERGRPOHf+XEw0p+LTD13iPidvxVwRyIicjMUHkVERMQp7HY7K08eICktFQDXoGp4NbrLsT9q2ScF1ZqIiDiBwqOIiIjctD9OH+KuXz9jyLKvmbZvvWN7iSuW7UjYs5zkU3sKoj0REXEChUcRERG5aSvC97MtIhyAT3esJDIpHgCPkPa4VWzgqItaqquPIiKFlcKjiIiI3LTRDTrh5+oOQGxqMh9uXw6AYRj4d/tn2Y6YP2eQFnWmQHoUEZGbo/AoIiIiN62EuxdPNujkGH+3fyNHoiMA8Gk5CLN/OQDsaSlcWjqpQHoUEZGbo/AoIiIiTjGsdmsqeQcAkGa38daW9NlVTS5ulOg+xlEXvXIy1viogmhRRERugsKjiIiIOIWb2cL4pj0c4yUn9rLhbBgA/h0exuTpD4AtKZboVZMLokUREbkJCo8iIiLiNHdWqUfjwEqO8RubF2Oz2zB5+KSv+3jZpaWTsKUkFkSLIiJygxQeRURExGkMw2BCs56O8Y4LJ1kQtgMA/67/wXD1AMAac56YddMLokUREblBCo8iIiLiVE1LV6ZnlXqO8Ttbl5CYlorFNxC/tg86tl/67QPs1rSCaFFERG6AwqOIiIg43fgmPXAxmQE4nxjL1vPHAShx+1i4vD014iixm+YUWI8iInJ9FB5FRETE6ar4lmRY7Vb0rFKPlX3G0KZcDQBcSlXGp+V9jrrIX9/FbrcXVJsiInIdLAXdgIiIiBRN/9fsDkxG1t9TB9zxLLHrvwMg5eQu4nf+hneDO/K7PRERuU668igiIiJ5IrvgCOBWoS5eDe90jC/9+k5+tSQiIjdB4VFERETyTbI1DbvdTkDP5x3bEg+uI/HgugLsSkREckPhUURERPLF6lMH6TT/IxYf341HzdZ4BLdz7Iv89d0C7ExERHJD4VFERETy3P92rub+pdM4HnuRlzf+TFxqMgE9n3Psj9/xK8nhuwqwQxERuRaFRxEREclzt1eui5s5fZ6+swkxfLBtGZ71euBasb6jJnLxewXVnoiI5ILCo4iIiOS5an6lGFWvvWM8be969kaeyXT1MXbjLFIjjhZEeyIikgsKjyIiIpIvHq/XgSo+JQGw2m2M37AAr6b34BJYLb3AZuXiojcKsEMREbkahUcRERHJF+4WF95qdbdj/HfECX44so2AO8c5tsWsm0HK2YMF0J2IiFyLwqOIiIjkm3bla9K7agPH+O0tv5HS5B5cStdI32C3cXHBqwXUnYiIXI3Co4iIiOSrCc174uPiBkB0ShJv/r2Ukne/7Ngfu3G2Zl4VEbkFKTyKiIhIvirt6ctzjbs7xnOP/M3uSk1xLR+avsFu58L8l3N4t4iIFBSFRxEREcl3Q0JaUr9kecf4/R0rKdnnFcc4/u+FJB3dUgCdiYhIThQeRUREJN+ZTSbebt0Hs2FiYM2mTO30AN5N+uBWuZGj5sK8CQXYoYiI/JvCo4iIiBSIBqUq8Mc9z/B+m3sp4e6FYRiU7PuaY3/CriUkHlxXgB2KiMiVimx4PHbsGA0bNuTNN9/MsWb9+vUMHz6cVq1a0ahRI+655x5+/PFH7HZ7PnYqIiJSfFXyCcg09qp/O+41WjnGF36aoJ/LIiK3iCIZHi9cuMCoUaNITEzMsWbmzJkMHz6czZs3U6dOHVq0aMGRI0d46aWXGDduXI7vExERkbxjGAY+V8y8mnhgDYn7VhZgRyIikqHIhcd9+/YxaNAgjhw5kmNNWFgYb7zxBr6+vsydO5epU6cyefJkFi9eTKVKlViwYAGLFy/Ox65FRETEbrcz+9AW2u/8C1vN2xzbdfVRROTWUGTCY3R0NO+99x79+/fn+PHjVKhQIcfaKVOmYLPZGDFiBCEhIY7t5cqVY8KE9Ifzp02bluc9i4iIyD9e/GshY9fNJTI5ng/L/DNxTtKRv4jfoV/qiogUtCITHmfMmMFXX31FQEAAn3/+OXfffXeOtatXrwagW7duWfa1bt0aX19fdu3axYULF/KoWxEREfm3HpVCHa8Xmzw4U7mpY3xx/svYbbaCaEtERC4rMuGxTJkyPP/88yxZsoROnTrlWHfhwgUiIyNxc3OjatWqWfabzWaqVasGwIEDB/KsXxEREcmsXfmaDKv9z2Q5r5as43idfHwbcVvnFURbIiJyWZEJj/369ePBBx/E3d39qnXnzp0DIDAwEMMwsq0JDAwEICIiwrlNioiIyFW92PR2qvmWAuCgT2m2lPnnauSFnyZgT0stqNZERIo9S0E3kN8yZmD18PDIscbNzQ2A+Pj4qx5r1qxZzJkzJ1fnvdoEPiIiIpLOw+LKx+36c/evn2Oz2/msQnO+OrcPk91G6tkDRK34jBLdRxd0myIixVKxC48mU+4vtl5rZreIiAj27Nlzsy2JiIjIFRoHVuI/9TsyacdKjnmV4pcy9bjrzA4ALi54FZ9Wg7D4BhZwlyIixU+xC49eXl4AJCUl5ViTnJwMgKen51WPFRgYSGho6FVrMhw5cuSq5xQREZF/jG7QiRXh+9kdeZqvq7Shc8QBvNKSsCVGc3He/1F62OSCblFEpNgpduGxdOnSAFedSfX8+fMABAUFXfVYAwcOZODAgbk6b9++fXWVUkREJJdczRYmtRvAHT9/SrSrJ9Mrt+LxI6sAiF7zFX4dR+JeuWHBNikiUswUmQlzcsvf35/SpUuTmJhIeHh4lv1Wq5WwsDAAatWqld/tiYiIyGXBJUrzXOP0ZbUWlGvEOZ/0XwBjtxPx/ZhrPl4iIiLOVezCI0CHDh0AWLp0aZZ9f/75J7GxsYSGhl7zyqOIiIjkrYfqtKFduZoMCW1LvRFTHNsTD6wlbvPcAuxMRKT4KZbhcdCgQVgsFj7//HN27tzp2H769Glef/11AEaOHFlQ7YmIiMhlZpOJ6V2G8nrLu/Bv2BOvBj0d+yJmP4ctOaEAuxMRKV6KZXgMCQlhzJgxxMbGct999zF8+HBGjhxJz549OXHiBAMHDqRbt24F3aaIiIiQ/vxjhsD73gezCwBpF09w6fcPCqotEZFip9hNmJPhoYceomrVqkyfPp0dO3ZgGAbVq1dn8ODB9O7du6DbExERkWy4lqlFia5POkJj5K/v4NtmGC4lKxZwZyIiRZ9h19Pm+SJjttXQ0FDmzZtX0O2IiIgUSna7nW+2L6X2Z/dSIjX9llWflgMpO3JmAXcmIlL0FcvbVkVERKRwSramMfP4Pr6q2taxLfavWSQeXFeAXYmIFA8KjyIiIlJouFtc+LLT/Wyo1JSD3qUd289+9yR2m7UAOxMRKfoUHkVERKRQqepbig/bDeTTGp0c21JP7CBq1RcF2JWISNGn8CgiIiKFTrdKdejY9n5WBNV2bDsz6zlSI44VXFMiIkWcwqOIiIgUSs826sbWVsOJsbgDYElNZOdn96G5AEVE8obCo4iIiBRKZpOJ924fyZx6/yyx5XN0E5sXvlmAXYmIFF0KjyIiIlJolXD3YtTwT9gSGOzY5vrzm+w6tKkAuxIRKZoUHkVERKRQq+JbirojvyXu8u2rntYU3H4ar9tXRUScTOFRRERECr361ZuQcteEfzbsX03MuukF1o+ISFGk8CgiIiJFQotez+FZr4djHPH9WFIvnSrAjkREihaFRxERESkSDMOg9PAvMHn4AmBLjOb89JHEJCditdkKuDsRkcJP4VFEROT/27vv+Kaq/g/gn5vRpCNt6YSyV9h7CsoSBERBeBRRBBQQHMgQHxRQRBzAI6CCAwT1QX4glKGC4AOKQKEsmYXK6IDSAbS0dDfNur8/SgJp0yYpoWmbz/v1yqvNveeec3JOTpLvHedStSEPqIPgUUvMz/PO7sLCVS9j3rEdvAaSiOg+MXgkIiKiasW313h4tR5gfv6vqJ+x4+wfePfodhhFHoEkIiovBo9ERERUrRSdvvotBKUKAOCr1+DNmD1Ye+Ew5hz5lQEkEVE5MXgkIiKiakceWA/Bo/5jft4jPQ5PJ53A/106hlmR2xhAEhGVA4NHIiIiqpb8er8MrzYDzc8nxx9Am8wkbIw5gTcPbuEkOkREDmLwSERERNWSIAioNelHyALqAgCkEPHehe2ooc3FlrhTmHYwHHqjwcW1JCKqOhg8EhERUbUlVQWh1pRwQCoHAARp8/DuP79BIhrxS/wZvHFgE3QMIImI7MLgkYiIiKo1z0ZdEfL8Z+bnHbISMeHKQQDAjqtReOPARt7Gg4jIDgweiYiIqNrz6/cKVN2fMz9/LvE4etyKgQAB/eo0gyAILqwdEVHVwOCRiIiIqr2i23esgkdYS/Oydy/vxuctu2Bk084urBkRUdXB4JGIiIjcgkThjbApmyEofQAASl0BOv/2EYzaAot0PIWViMg6Bo9ERETkNjzCmqPm+NXm54WJZ5G67g3zc6NoxJSIjdgcc9IV1SMiqtQYPBIREZFbUXUdCf8BU83Psw/+gNt/fgUAWHRyN36NP4sZhzZj8cndMIq8FyQRkYnM1RUgIiIiqmjBzy6G5srf0MQeAQCkrZ8GjVKF8MRr5jQrovYhPvsWPn/kGXjKPFxVVSKiSoNHHomIiMjtCDIP1Hp9E2QBdYsWiCJyfpiEXxq3QDP/UHO6nVfPYcSuVbiSfctFNSUiqjwYPBIREZFbkteojTpv/Q8Sn8CiBQYddN+9hE0tu6B3bbU53bn0ZAz6dTm2xp12UU2JiCoHBo9ERETktjzCmqP2m79BUHgDAMTCPGSuGIHVLbvipRY9zOny9FpMi9iE6RHhyNUVuqq6REQuxeCRiIiI3Jpno64Ie2MrIJUDAIy56bix7AnMa9oBK/uOhp+H0px2S9wpDPp1OaJuJbmqukRELsPgkYiIiNyed+sBqDVpLSAIAAB9RiKSlw7G4KAw7B42DV1C6pvTXs1Jx9+pCa6qKhGRyzB4JCIiIgKg6vYsQl5YYX6uTbmA5GVPIkwmx+bBkzCtXT8IENC/bnOMv+eUViIid8FbdRARERHd4f/oq9BnpyLj1wUAAE38MaSsGIGwqT/j3x0fw8NhTdDMPxTCnSOUJrm6QnhK5ZBKuF+eiKovfsIRERER3SPwqXnw6/eq+Xl+9F4kLe4PQ84tPFSzEQKU3iW2efvwNgzb+Q2i01MqsqpERBWKwSMRERHRPQRBQMgLX0DVfZR5mSb+OK59/Ah0aVdLpD+QfBm/xp/FmVuJeHzHl/jw+E7kcUZWIqqGGDwSERERFSNIpKg56UeLI5C6G5dx7aOeKLx21iLtoZQ48/8G0YhV0QfR9+dl+OPaPxVWXyKiisDgkYiIiMgKQSJFyJgVCBzxoXmZIesGEhf2Qf6FfeZlc7sMxvrHxqO+KsC8LCUvCy/t/RHj/1yLmMzUCq03EdGDwuCRiIiIqBSCICBw6ByEjl8NSKQAAGNBNpKXPo6c45vN6XrXVuPPp2Zgatu+kN9JBwB7Ei/g0V8+w5sHNyMp93aF15+IyJkYPBIRERHZ4NdrPMKmboPg4QkAEPVaXP/mOdz+40tzGk+ZHLM6DcTuYVPRLbSBeblRFBEeexK9ti7B+kvHK7rqREROw+CRiIiIyA4+7Z9AnVl/QOJ95/RUUUTa+mm4+eMUGLUF5nRq/1BsHjwJK/s8j0a+QeblWqMBbQNrV3S1iYichsEjERERkZ08mzyEunMjIAusZ16W9dc3uLbgIRQm350gRyJI8ETDtvhr+Az8p+cI1PLyw5MN2qJNkGXwKIoibmvyKqz+RET3g8EjERERkQMUYS1Q991DUNTvaF6mTTqHax90Reb+byGKonm5TCLF8+quOPivt/DRQ0NL5HUgJQZdwhdh9uGfEZ+VViH1JyIqLwaPRERERA6S16iNuu8egv9j08zLRG0BUv/7Kq5/9SwMeZaT4yhlcgQqfUrk8+35g9AYdFh36Rh6b1uGl/5ciyM34i0CUCKiyoLBIxEREVE5SOQKhDy/DGHTt0OqunttY+6JrUiY1xEFMYfL3P52YT7+ybhufi5CxB+JF/DM799iyI4vsTXuNAr0ugdWfyIiRwkid21ViBEjRiA6OhqtWrXCtm3bXF0dIiIiciJ95nXc+HYc8v/Ze3ehRIrAoe+ixuOzIPFQWt1Oo9dhW/xprD5/CDFZJe8H6euhxNCG7TCyaSd0CKoLQRAe1EsgIrKJwWMFYfBIRERUvYlGI27v+hS3tr0HGA3m5fLgRgge9Sm8Ow4rNfgzikbsT47Bt+cP4tD1WKtp3uvyOCa37vVA6k5EZA+etkpERETkBIJEgoAn3kbdORGQBTUwL9elxSNlxb+Q9J/HUJh4zuq2EkGCfnWaYeOgidg9dCqebdoZXjIPizSP1WtZYjutQe/U10BEVBYeeawgPPJIRETkPgz5WUj/eT4y//oauDfAEyTw6zsZQcPnW1wnaU2erhA7r57DppiTAICtj0+2WK8zGtBl00K0DgzDoPqtMLBeSwR7qpz+WoiITBg8VhAGj0RERO6nMOUC0ja8ifzzeyyWS7z8EfjU+/Dv9wqEYkcYrdHodVDK5BbLIpJj8Pye78zPBQjoElofg+u3wsB6rVBPFeCcF0FEdAeDxwrC4JGIiMg9iaKIvLO7kPbTTOhuxlisk/qHoUb/KfDrOwlS7xoO5Tv/2A6s+Sey1PUNVIF4JKwJHglrih61GsFf4VWu+hMRmTB4rCAMHomIiNybqNci88+vkP7rAhgLsi3WCR5e8HvkJfgPnAaPkMZ25ac3GvB3agJ+v3oe/7sWjZS8rFLTSgQBB//1FuqrAu/rNRCRe2PwWEEYPBIREREA6LNTkf7zfGQf/AGiXmu5UhDg03EYagx6E8omPey+NYcoiohKT8bvCeexO+GfErf9CPXyxYmRsy3y0xr0WHjyf+gUXA8dQ+ojzNvvvl8bEVVvDB4rCINHIiIiupc+6yYy936NzL++gTE3vcR6Rf2OUHV/Dqquz0AeWNehvJNzM3EwJQYHr8fiUEos+tZuhs97jbRIcyrtGob+9rX5eZi3HzoF10fHkLpoHVgbLWvUgp/Cs3wvjoiqJQaPFYTBIxEREVljLMxH9uF1uL37C+huXLKaRtmkB1TdRkLV5WnI/Gs5lr9oRJ5OC5WH0mL56uiD+OD4zjK3retTA60CwtAqsBZGNe2CWjw6SeTWGDxWEAaPREREVBbRaERe1C7c3v05Ci7ss55IEOCp7gVVt2fg3WYw5MENyl3evqRL2BJ3CidTE5CUm2kz/f7hb6KJf4jFsg2Xj6OGwgtN/EJQXxUAD6ms3PUhosrP7Uf4lStX8NVXX+HkyZNIT09HzZo1MXjwYEyaNAne3t6urh4RERG5CUEigU/7J+DT/gkUJp1HzrFNyDkeDt3N2LuJRBEFlw6g4NIBAIAsqAG8WvSBV/Pe8Gze16HTW/vWaYa+dZoBAG7kZ+NkagJOpV5DVHoy/slIQZZWY06rlMrR0NfyvpRG0Yj3j+1AgV5XVBdBgnqqANRXBaKeqgbqqQKKHj5Ff4sf+SSiqsetjzxGRUVh3LhxyM/PR7t27VCzZk2cOnUKaWlpUKvV2LBhA1Qq59xsl0ceiYiIyFGiKKIw4TRyjocj51g49OkJZaaXhzSGZ/Pe8FQ/DGW99vAIa2HXfSStlZuUexvRGdcRnZGCfL0O73V53CJNUu5tdN+82O48p7Ttg3c6DbJYFpOZitT8bNTy9kctb194lqOuRFRx3PbIo06nw/Tp05Gfn49FixZh+PDhAACNRoMZM2bgr7/+wtKlSzF//nzXVpSIiIjcliAIUDboCGWDjgh6ZiE08ceRczwceWd2lrhnJADoUuOgS41DdsT3RQukcijCWkJRry0UdduZ/0pVQSW2LV5uXVUA6qoCMKh+K6tptAYDHqvbArFZaUjIyYBBNJaZZ4hnyR3yP10+jm+jD5mfq+QKBHmqEOzpg2BPFYKUPvf8742BpdSFiCqG2x55/OWXX/D222+jZ8+e+P777y3W3b59G/369YNOp8Phw4fh6+t73+XxyCMRERE5k+52Mgou7Ef+xQMouLgfutQ4u7eVeAdAHtzQyqMR5IH1HD5aWWjQIyEnHfFZt5CYm4FrObdxLSej6JGbgUKDHmv7v4hH6za32O7VfRuw42qUXWWo5ApceOEDi2V5ukL03rYUfh6e8Fd4wV9h+uuFGgpP+Ht4wU/hCV8PJXzkCtRTBSDYShBLRPZx2yOP+/YVXYj+2GOPlVhXo0YNdOvWDfv27cOhQ4fw+OOPl0hDRERE5EryGrUh7zEavj1GAwB06YkouFgUTBZePYXClH8Ag87qtsa8DBTmZaDw6kmr6yXeAZD5hULqV7Por28oZH41IfUNgdQnEBIvf0i9/M1/PZQ+UPuHQu0fWrIs0Yi0glz4WrnmUeWhRE0vX6QW5MBo43iGv8KrxLLMwgLcyM/GjfzsMrc1ebfz43ilTS+LZUtO/4FNl0/AW+4Bb7kC3jIP+MgV8JIriv7K5FBK5VDK5FBIZZjU6hGL+2WKooijN69AIZUVpbvzVyGTQSGVQy6RQi6RQCJI7KojUWXmtsHj5cuXAQDNmjWzur5p06bYt28fLl26xOCRiIiIKj15YF3Ie46Bb88xAABRr4U25QIKE8+i8FoUChOjUJh4FoacWzbzMuZlQJuXAaRcsK9wiRQSTz9IvfwgyD0heHhC4lH0V5AX/Z/l4YnsO/+b0sz28MSc4ACI8lrIFgXkGPTI0uuQrdchU1eI2zotbusKkaErhErUQnP1FASpDJDIIEhlyMxOR4gmGwZBAhGAKAAihKKHAAACjPf872vUwViQA0gkAARAEHA7JwNpuRlIBSDeCQqL8gBwT5AIAHKJFJNbWwafetGIZ37/1mYTSQUJ5BIpXmnTC291GGCx7qfLf+P7fyLhIZVBJkggl0rvBJ13H7I7QahcIsO7XR4vEYyvOLsPGoMOUkECqSBAeidglUCAVCJAIkjM6xr5BqFnWBOL7ZNyb+PMraSi9PdsLxUESAUJJIIAyZ3/BQhoEVAT3nKFRR4xmakoNOggQLjTdEXbmJ4X/QdIBAFKmQfCit36RaPX4ZYm15xOEISiB2DOw5wfAG+5osQMvxq9DkZRvFuecDcvk3t7VSaRWmwviiJEWO7IEGD5PhCKvS/cidsGjzdv3gQAhIaW3EMGAMHBwQCA1NTUCqsTERERkbMIMg8o6rWDol47oGfRMlEUYci6CV1aPHRpV+484qFLuwpdWjz0t5OA8lzRZDTAmJcBY17GfdXZA0DwnYc113bNt3guB7DRkQIilyO22KJxdx6lMeJOMCkUBZQxB5fBFHhCkACCgJ06rc2ixTvxhsfBzxAjtQxY2hkM+NSov5sWZQcnN9cpkApYBLcP6wpR+tVoxYJgqRSxUrnFMp3RgFqlHKkuToSAJLkCUonl0dRcrQaGe+pQ1jtJLpEi3xR83nkdeqMROffM8lui3GLNopIr4VGsLXO0GmiNBtsvAkWBaI1iR7QNoojMwny7tgcAL5kHPGWWbZmn00JjZ1sCQIDCu/h+CmRo8iza797VXVbn2p23s7lt8FhQUAAAUCqtTxttWp6fX/qbZ+PGjQgPD7ervLg4+69DICIiInoQBEGAzL8mZP414dm0R4n1Rl0hDJnXoc++CUPWjTt/U6HPugFD9k0YslNhyLsNY34mDPmZEAvzXPAqKlZReCSag2pRXzJQ9HQkQ4MOYrG4QgbHfpSLBm2JwMyhG8wZioLie0kBOHQ1qF5TIg9Hb3Jn1Fq+fyQA/KwntU5XgOJhotedh70M2pK/9f3vsw7KOw97GXUFJZY51A4VyG2DR6lUCqOx7FnBAJSxBwdIS0tDdHS0M6tFRERE5DISuQKS4AaQBzewK72o18KQnwVjfmZRQFmQBVFbAFFXAKO24M7/mnv+v7NcVwCxMB9G3T1pdBrAoIdo1Jv/igY9UOyvaNQDRkPRMgeO7hDR/XPb4NHb2xuZmZkoLCy0ul6jKTpk7uVV+r6L4OBgtGpl35TRcXFx5jyJiIiIqgNB5gGZbzDgW9qJpg+eaDRCNOjuHBm8c4RQNAKma9fueW5aL1pdZiyWx51l9zy3mq9dlXTkVGA709qZp/03VnBuueXJz3S9oWmRCMCIov4SzX1zZxkAxZ1rRO+Vp9dCZ9AXXQMrAndytForCQQEKi2Pl+pFIzI0efekL/Y6ij318VDCu9jsxFnaAuTdcyqzrTzCvP1KXEeZlHvbanJX3ybDbYPHkJAQZGZmIi0tDbVq1Sqx3nStY0hISKl5jBo1CqNGjbKrPNOtOoiIiIjIeQSJBIJEYTshuQVHThctjU8lqEMT20lcwm3nDDbNshoTU/IGuwAQGxtrkY6IiIiIiMiduW3w2KdPHwDAnj17Sqy7ffs2jh07BoVCgYceeqiCa0ZERERERFT5uG3w2L9/f9SuXRv79+/Hxo13J3nWaDSYO3cu8vPzMXLkSAQEBLiwlkRERERERJWD217zqFQqsXjxYkycOBHvv/8+wsPDUadOHZw+fRqpqalo3bo1ZsyY4epqEhERERERVQpue+QRALp06YLNmzdj4MCBSElJwf79+6FSqTBlyhSsXbsW3t6O3q2GiIiIiIioenLbI48marUay5cvd3U1iIiIiIiIKjW3PvJIRERERERE9mHwSERERERERDYxeCQiIiIiIiKbGDwSERERERGRTQweiYiIiIiIyCYGj0RERERERGQTg0ciIiIiIiKyicEjERERERER2cTgkYiIiIiIiGxi8EhEREREREQ2MXgkIiIiIiIimxg8EhERERERkU0MHomIiIiIiMgmBo9ERERERERkE4NHIiIiIiIisonBIxEREREREdnE4JGIiIiIiIhsYvBIRERERERENjF4JCIiIiIiIpsYPBIREREREZFNDB6JiIiIiIjIJgaPREREREREZBODRyIiIiIiIrKJwSMRERERERHZxOCRiIiIiIiIbGLwSERERERERDYxeCQiIiIiIiKbZK6ugLto2LChxV8iIiIiIqKqRBBFUXR1JYiIiIiIiKhy42mrREREREREZBODRyIiIiIiIrKJwSMRERERERHZxOCRiIiIiIiIbGLwSERERERERDYxeCQiIiIiIiKbGDwSERERERGRTQweiYiIiIiIyCYGj0RERERERGQTg0ciIiIiIiKySebqClDZZs6ciStXrri6GkREREREVEk0bNgQS5curfByGTxWcidPnsT169ddXQ0iIiIiIqokMjIyXFIug8dKLj8/HwCgVCrRuHFjF9fG/cTFxUGj0bD9XYh94HrsA9djH7ge+8D12Aeuxz5wPVMfmGKEisbgsZKrU6cOsrKy0LhxY2zbts3V1XE7I0aMQHR0NNvfhdgHrsc+cD32geuxD1yPfeB67APXM/VBnTp1XFI+J8whIiIiIiIimxg8EhERERERkU0MHomIiIiIiMgmBo9ERERERERkE4NHIiIiIiIisonBIxEREREREdnE4JGIiIiIiIhsYvBIRERERERENjF4JCIiIiIiIpsYPBIREREREZFNMldXgMo2cuRIpKWlITg42NVVcUtsf9djH7ge+8D12Aeuxz5wPfaB67EPXM/VfSCIoii6pGQiIiIiIiKqMnjaKhEREREREdnE4JGIiIiIiIhsYvBIRERERERENnHCnAowdepU7N69GwsXLsSIESNKrD98+DBWr16NixcvQqPRoFGjRhg1ahSefvppCILgUFnnzp3D119/jfPnzyM7Oxt169bFsGHD8OKLL0IulzvrJVU5ZfVBQUEBfvjhB+zevRsJCQkwGo2oU6cO+vfvj4kTJ8LX19fucpYvX46vvvqq1PV9+vTBqlWryv06qrKy+sDZ7ebMMVWdWOuDpKQkPProo3ZtP2XKFLzxxhs2023duhVz5swpdX3Tpk3x22+/2VfpKu7o0aMYN25cqeu9vLxw+vRpi2W7du3Cjz/+iPj4eBgMBjRv3hxjx47FwIEDHS6fY8HxPsjIyMCaNWuwb98+JCcnQyKRoH79+hgyZAjGjRsHhUJhd9lvv/02fvnll1LXjx49GvPmzbM7v6rI0fZ3dps5czxVVfb2wbFjxzB27Fi78iztN21x/F10V0ZGBr799lvs27cPKSkpUCqVaNu2LSZNmoRu3bqVSF9Z4wMGjw/Y5s2bsXv37lLXr1+/HgsWLIBcLke3bt0gl8tx9OhRvPvuuzhx4gQWL15sd1l79+7F1KlTYTQa0blzZ/j6+uLvv//GkiVLEBkZidWrV7tlAFlWH2RmZmLMmDG4fPkyfH190aFDB0ilUpw7dw6rVq3Crl27sH79eoSGhtpVVnR0NACgb9++8PHxKbG+ZcuW5X8hVZitceDMdnPmmKpOSusDLy8vPPnkk6Vul5GRgcjISAiCYHc/mPqzW7duCAkJKbG+Vq1adta66jO1RZs2bdCgQYMS64sHIv/5z3/w3XffwcvLC926dYNWq8Xx48cxdepUvPbaa5g2bZrdZXMsFHGkDxITEzF69GjcvHkTgYGB6N69O7RaLc6ePYulS5di9+7dWLt2rdXPqbLKHjJkCCSSkid7tW3bthyvqGpxdAw4s82cOZ6qMnv7ICgoqMzvg6SkJJw+fRpyuRxqtdqhst39d1FcXBzGjRuHtLQ01K5dG71790ZSUhIOHTqEyMhIfPnll+jfv785faWOD0R6YOLj48X27duLarVaVKvV4tatWy3Wx8XFic2bNxc7d+4sXrhwwbw8OTlZ7N+/v6hWq8WdO3faVdbt27fFDh06iK1atRIjIyMtlj/zzDOiWq0Wv/32W+e8sCrEVh/MmTNHVKvV4pgxY8SMjAzz8qysLHHChAmiWq0WJ0+ebHd5PXv2FFu0aCHm5+c77TVUdbb6QBSd127OHFPViT19YI1erxdfeOEFUa1Wi8uXL7e7vJEjR4pqtVqMi4srb5WrjRkzZohqtVqMiIiwmTYyMlJUq9Vi3759xeTkZPPyCxcuiN26dRPVarV45swZu8rlWLjLkT4YN26cqFarxRkzZoh5eXnm5Tdu3BCHDx8uqtVqccGCBXaVm5+fL7Zo0ULs2bNnueteHTjS/s5sM2eOp6rOkT4oTW5urjho0CCHvkNEkb+LRFEUdTqd+OSTT4pqtVr85JNPRL1eb163efNmUa1Wi506dRILCwtFUaz88QGveXxAtFotZs6cCYlEUupeldWrV8NoNGLChAlo3ry5eXlYWJj5lIzvv//ervL+7//+D3l5eRg+fDh69OhhXu7v74+FCxcCANauXQuj0Vjel1Tl2OoDjUZjPnVu0aJFqFGjhnmdr68vFi9eDEEQcODAAWRlZdksLzU1FWlpaWjcuDE8PT2d90KqMHvGgTPbzZljqrqwpw9Ks2LFChw/fhxdu3bF66+/btc2BoMBly5dgo+PDxo2bFieKlcrpr3urVu3tpl25cqVAIAZM2YgLCzMvLx58+aYPn06APvfvxwLd9nbB0lJSThy5AhUKhUWLFgALy8v87rQ0FDMnz8fALBjxw67yr148SIMBoNdfV+dOTIGnNlmzhxPVZ0jfVCa+fPnIz4+Hk899ZRdp6sC/F1k8scff+DSpUvo0qULZs+eDalUal739NNP45FHHoGvry/++ecfAJU/PmDw+IB89tlniI6Oxrx580o9RWv//v0AgMcee6zEuh49esDX1xfnzp3DrVu3bJZXVl6NGzeGWq1GWloazp07Z/+LqOJs9UF6ejpatWqFjh07WnyxmAQGBsLPzw9Go9GuPnDGh3N1Y884cGa7OXNMVRf29IE1cXFxWLNmDTw9PfHJJ59YPX2stO0KCgrQsmVLt7mmrjS5ublISEhA7dq1LXZOlZb2xIkTkMvl6NevX4n1jz32GARBQEREhF1f8hwLRRzpg/T0dHTo0AE9e/a0enpdo0aNAABZWVnQaDQ2y+Z3gmPtDzivzZw9nqoyR/vAmiNHjmD79u0IDg7G3Llz7d6OY6DI77//DgCYOHGi1fVr1qzBX3/9hfbt2wOo/PEBg8cH4PDhw/jhhx8wZMgQDBs2zGqaW7duISMjAwqFwureealUav6iunTpks0yY2JiAADNmjWzur5p06Z251Ud2NMHtWvXxoYNG/DTTz9ZXZ+QkIDMzExIpVKr120VZ/qQ9PX1xXvvvYcBAwagTZs2GDBgAJYsWYKcnJzyv6AqyJ4+AJzXbs4eU9WBvX1gzccffwydTofJkyejbt26dm9n2nMaGhqKxYsXY9CgQWjbti169+6N+fPnIzU11aF6VGUXLlyAKIqoX78+vv76azz55JNo164devbsiX//+9+4cuWKOW1cXBwMBgNq164Nb2/vEnkFBAQgKCgI+fn5uHbtWpnlcizc5UgftGvXDhs3bsQXX3xhNa+oqCgARXvslUqlzbJNn21SqRQzZ85E37590bZtWwwZMgSrVq1CYWGhE15h5eZI+wPOazNnjqeqztE+KE6v1+Ojjz4CAMyaNcuhSQT5u6jI+fPnAQDt27dHZmYmNmzYgHnz5mHBggXYtWsXDAaDOW1ViA8YPDpZRkYGZs2ahZo1a5pPcbHm5s2bAIDg4OBS984HBwcDANLS0sosMzMzExqNBhKJpNQgx5SXO/xws7cPbFmyZAkAoGfPnlCpVDbTmz4k//vf/+LPP/9E06ZN0b59e9y6dQurV6/G008/7RbtDzjWB85qN2eOqergfsbB0aNHERkZicDAQLz44osObWv6ktyxYwfCw8PRoEEDdOrUCQUFBfjpp58wfPhwxMbGOpRnVWV6bx8+fBgrV65ESEiIeUa97du3Y8SIETh27BiAu+/fsibnsvf9y7FwlyN9UBaDwYDPPvsMADB48GCHyv78889x6tQptGrVCi1btsS1a9ewbNkyjB07Fvn5+eV5WVWGo+3vrDZz5niq6u53DPz666+IjY2FWq0uczKdssp2599FWq0WycnJUCgUiI6OxqBBg/DBBx9g06ZNWL9+PWbMmIFnnnnG3A5VIT7gbKtONmfOHKSnp2Pt2rVl7p0pKCgAgDLPATfNfpWXl1dmmaa8ytoTalpX3b+oAPv7oCwrV67Enj17oFQq8dZbb9m1jemIy3PPPYc5c+bAw8MDQNEHwZtvvokTJ05g9uzZ+O6778pVp6rEkT5wVrs5c0xVB/czDtasWQMAmDBhgsPXqZj6c8CAAVi0aJH59L+cnBzMnTsXu3fvxrRp07B9+3aL6z6qI9MPp44dO2L58uXmL2mtVotFixZh/fr1mD59Ov744w/zZ7M9719bn+McC3c50gelzaAqiiI++OADREVFISAgAK+99prNcgsLCxEXFweg6Jq7SZMmmU/9jo+PxxtvvIEzZ85g0aJFWLBggTNeaqXkSPvL5XKntZkzx1NVdz9jQBRF87V1r7/+usOXIvB3UdFpwwBgNBoxZcoUtGvXDm+99RYaNmyIy5cv4+OPP8a5c+fw2muvITw8vErEBzzy6ETr16/Hvn37MGHCBHTt2rXMtPZePwQUDd6Kyquqc6QPSvPFF1/gs88+g0QiwSeffFLqof7idu7cie3bt+P99983f0ACRXs+lyxZAk9PTxw6dMj85VhdOdoHzmo3joO77mccxMbG4uDBg/D398fzzz/vcNnff/89du7ciWXLlln8EFGpVPjkk08QEhKC2NhYHDp0yOG8q5qPP/4Y//vf/7B69WrzDzYA8PDwwNy5c9GiRQtkZGQ4HEjbukaLY+EuR/rAGr1ejzlz5mDTpk1QKpVYvny5XZcxKBQKHDlyBDt37sQrr7xi0SeNGjUyT7O/detW84/L6siR9ndmmzlzPFV19zMGIiIiEBsbi8aNG5frvpj8XVQUpAOATqdDvXr1sGbNGrRu3Rre3t7o0KEDfvjhBwQFBeHcuXPYu3dvlYgPGDw6SUxMDBYvXoxWrVrZdd8g0zn4ZV10bzq3/94Z38rKq6xrAUzl2MqrKnO0D4rTarWYNWsWvv76a8jlcnz66acYMmSI3dv7+PigWbNmVvfM1apVyzzTZXWetKg8feCsdnPmmKrK7nccmGYgfvzxx8s1O55SqUSTJk0sfiiY+Pj4oHv37gCq9zgw8fDwQMOGDa0e0ZJKpejTpw+AorZ4EN8J7j4WAMf6oLjs7GxMnjwZ27Ztg7e3N1atWoUuXbrYXbavry+aNGlidV3r1q1Rs2ZN6PV6XLhwwe48qxpH299ZbcYxcNf9jAHT98GIESPKNQEafxdZHkEcPXo0ZDLLkz5VKhWGDh0KoGhioqoQH/C0VSdZsmQJCgsLoVQqMXv2bIt1plMGwsPDcfjwYXTp0sW8B6esmZJM5x/b2svp4+MDHx8f5ObmIj09HYGBgeXOqypztA+effZZ8/r09HS8/vrrOH36NHx8fLB8+XL07NnTqfUzzXRZnU+RuZ8+KI297Wa6tsUZY6oqu98+2LNnDwCYv8yczdSfptNp3Nm9bWF6/5Z1DYu971+OBfuV9n5MSEjA5MmTceXKFYSEhGDVqlVOv5l5rVq1cOPGjWr9nWCLo58H9raZM8dTdVdaH2i1Wuzbtw8SicThax0dLbs6jwEfHx94eHhAq9WiTp06VtOYlmdkZDj18/tBxQcMHp3E9MY/efIkTp48aTXN6dOncfr0achkMjz77LMIDQ3FzZs3kZiYWGI2Q4PBgPj4eACAWq22Wb5arcapU6cQExNj9c1hmqDC3lMwq6Ly9AEAXLt2DS+++CKSk5NRu3ZtrFq1yjz7lL1iY2Px3XffQSKR4OOPP7aa5vr16wDg0O0SqhpH+6BTp05Oazd/f3+njqmqqrzjAAASExMRFxeHsLAwdOjQweGy09LS8MUXXyArKwufffZZiT2sgHuMA6Doh9dHH32E9PR0LFiwwOrn8r1t0aRJE8hkMiQmJqKwsNB8TYtJRkYG0tPT4enpiXr16pVZNsdCEUf7wCQqKgovv/wyMjMz0aJFC6xcuRI1a9Z0qOwTJ05g8+bNCAkJwcyZM62mqe5jwdH2d2abOXM8VWXlHQNA0XdITk4OOnfuXObEQ6Xh76IiUqkUTZs2RXR0tHkynOJMgWJgYKDTP78fRHzA01adZN26dbh06ZLVx6OPPgoAWLhwIS5duoRFixYBgPlUAdOe/ntFRkYiJycHrVq1smtvQFl5xcXF4fLlywgKCqrW99opTx/cvHkTY8eORXJyMtq0aYPNmzc7HDgCRafqbdu2DVu2bMHVq1dLrL969SrOnDkDLy8vh057qmoc7QNnt5szx1RVVZ5xYHLmzBkARRMrlIdKpcKOHTuwZ88eq7P3ZWVlYf/+/RAEAY888ki5yqgqPDw8cOjQIfz555/Yu3dvifVarRa7du0CAPTq1QsKhQLdu3c37+0vbvfu3RBFEb169bLrei6OBcf7ACiarn7ChAnIzMxE7969sWHDBocDR6DoOrpffvkF69ats3o7gqNHj+LGjRsICwsr13dOVeBo+zuzzZw9nqqq8owBk7NnzwIAOnXqVK6y+bvoLtPnsbXrSkVRREREBACY5yio7PEBg0cXev755yGTyfDNN9+Y7x8FACkpKfjwww8BAK+88orFNjk5OYiLiytxX6IRI0bAx8cH4eHhFh+UmZmZmDNnDoCim5NaOxLgzv7973/j+vXrUKvVWLt2rdW9MsVlZGQgLi4OKSkp5mV16tRB7969AQDvvPMOMjIyzOtu3LiBqVOnwmAw4KWXXip1Rj93VN52s9YHQPnGFN1luu6kTZs2NtNa+yxSKpUYMWIEAGDBggVITk42r8vKysLUqVORnZ2NYcOGoX79+k6ufeVjmnBo6dKluHjxonm5RqPBnDlzkJCQgK5du+Khhx4CAIwdOxYAsGjRIiQkJJjTX7x40XzvwUmTJlmUwbFQNkf6QKvVYvr06cjOzsbDDz+Mr7/+2q7rgFJTUxEXF2cx1X3nzp2hVqtRUFCA2bNnW5yWFxMTg3feeQcAMGXKlHJdS1ZVONL+5W0za+0PlG88VUeOfg6ZOPJ9wN9FZRs1ahR8fX3Nt0sxTU4jiiKWL1+O8+fPo379+ujbty+Ayh8fCGJ1n2qtEnjttdewd+9eLFy40PzDymTNmjX49NNPIZPJ0LVrVygUChw7dgz5+fkYNWoUPvjgA4v027Ztw+zZs1G7dm389ddfFut27tyJt956C6IoomPHjggICMDff/+NzMxM9O3bF19++aXbBo/W+iAyMhLjx48HUPRFX9ZpE2+++SbCwsIAACtWrMCXX36Jrl27Yt26deY0qampGDNmDK5evQqVSmU+7e/48ePQaDQYOHAgli1bxj4oNg7K026l9QHg+JhyJ2V9Ft27ftmyZTYniyrtsyg3NxcTJkzAmTNnoFQq0bFjRyiVSvz999/IyclBp06dsHr1aqs37q5u9Ho9pk2bhj///BMymQwdOnRAjRo1cOrUKdy6dQuNGjXCjz/+aDED4gcffIANGzaYj5wYDAYcO3YMOp0OM2fOLPFjl2OhbI70QXh4ON577z0ARUdh/Pz8Ss33ww8/NE+E8c477+Dnn3/G8OHDLY7mx8bGYuzYseZrjdq1a4eCggKcOHECOp0OY8eOxdy5cx9sA7iYo2OgPG1WWvsDjo+n6qg8n0MAMGzYMFy8eBGbNm1C+/btyyyDv4tsi4iIwBtvvAGNRoP69etDrVbj8uXLSEhIgL+/P1avXo22bdua01fm+KD691YlN3HiRDRs2BD//e9/cfbsWQiCgMaNG2P06NEYNmyYQ3kNGTIEoaGhWLVqFc6cOQO9Xo+6devi1VdfNe/FoLvu3QNz4sSJMtNOmDDBHDyWJiQkBFu3bsWaNWuwZ88eHD16FHK5HC1btsQzzzyD4cOHV+s9zOXl7HZz5phyN6Y9wyqVqtx5+Pj4YN26dVi3bh127NiBU6dOQSKRoGHDhhg6dChGjx4NuVzurCpXajKZDF9++SW2bNmCLVu2IDo6GgaDAXXr1sVzzz2H8ePHlziyNW/ePLRu3Ro//fQTjh8/DoVCgfbt2+Oll14yn3ZsL44Fx/rg3u8E02lkpZk3b57N2YibNGmCX3/9FatWrcL+/ftx8OBBeHp6okuXLnjhhRcc7s+qyNEx4Ow2c+Z4qqrK8zkEOOf7gL+L7urVqxe2b9+OlStX4vDhw9i/fz+CgoIwcuRITJ48ucRkOpU5PuCRRyIiIiIiIrKJ1zwSERERERGRTQweiYiIiIiIyCYGj0RERERERGQTg0ciIiIiIiKyicEjERERERER2cTgkYiIiIiIiGxi8EhEREREREQ2MXgkIiIiIiIimxg8EhERERERkU0MHomIiCo5vV6Pzp0746mnnirX9r/99huaNWuGZs2aYd68ec6tHBERuQ0Gj0RERJXcqVOnkJOTg969e5dr+61bt5r/37FjB3Jzc51VNSIiciMMHomIiCq5AwcOAAB69erl8LYpKSk4evQo/P390b59e+Tn52PHjh3OriIREbkBBo9ERESVXEREhDn4c9S2bdtgNBrRoUMH9OvXDwCwadMmJ9eQiIjcgczVFSAiIqouLly4YPd1iTNmzMArr7xiM92NGzdw+fJlDBkyBFKp1KH6iKKIn3/+GUDRUcuHH34Yy5Ytw4ULF3DmzJlyBaNEROS+GDwSERE5ydWrVxEUFFTq+oKCAuTl5QEAWrZsaVee93PK6tGjR5GUlASJRIJHH30UoaGhaNu2LaKiovDTTz8xeCQiIocweCQiInKSwYMHY/DgwVbXJScnY9y4ccjLy0OfPn3QvXt3u/I8cOAABEHAI4884nB9TBPldO3aFaGhoQCAJ554AlFRUfj9998xZ84c+Pn5OZwvERG5J17zSERE9IAlJiZizJgxSExMRP/+/bFixQp4eHjY3E6r1eLIkSNo3bo1AgMDHSozJycHf/zxBwBg6NCh5uVPPPEEpFIpCgsLzae0EhER2YPBIxER0QN05coVjB49GsnJyRg8eDC++OILuwJHADh58iTy8/PLdYuOnTt3QqPRQKlUYuDAgeblgYGB6NGjBwBg48aNDudLRETui8EjERHRAxIbG4sxY8bg5s2bGDp0KJYuXQqZzP4rRu7nekfTKat9+/aFj4+PxTrTkcgrV67gyJEjDudNRETuicEjERHRA3Dx4kWMGTMGaWlp+Ne//oXFixc7PFvqgQMHEBAQgDZt2ji0XUxMDKKiogBYnrJqMmDAAHh5eQHg0UciIrIfJ8whIiJysujoaIwfPx6ZmZkYNWoU5s+fD0EQHMojMTER8fHxGDp0KCQSx/b1mo46AsCrr75aZtq9e/fi1q1bZc4SS0REBDB4JCIicqqzZ89i4sSJyM7OxtixYzF37txy5RMREQEADl/vqNPpsH37dgCAr68vPD09raYTRRGpqanQ6XTYsmWLXfecJCIi98bgkYiIyElOnDiBSZMmIS8vDxMmTMCsWbPKnVdERAQkEgkefvhhh7Y7cOAA0tPTAQDff/99mae8PvHEE4iJiUF4eDgmTZrk8BFOIiJyL/yWICIicoKjR4/i5ZdfRl5eHl599dX7ChwLCwtx7NgxtGvXDv7+/g5tu2XLFgBAs2bNbF4r+dxzzwEougel6UgnERFRaRg8EhER3afIyEhMnjwZ+fn5mDZtGqZPn35f+R07dgwFBQUOz7KalpaGgwcPAgBGjBhhM/2wYcM4cQ4REdmNp60SERHdp88//xwajQaCIGD9+vVYv359qWmXLFmChx56qMz8ynu94y+//AK9Xg+5XG51ltXifHx88OSTT2LTpk2IiIjA9evXUatWLYfKJCIi98Ejj0RERPfBYDDg8uXLAIomobl161aZj3r16tnMMyIiAsHBwWjZsqVDddm2bRsAoF+/fggICLBrG9OpqwaDAZs2bXKoPCIici+CKIqiqytBRERERERElRuPPBIREREREZFNDB6JiIiIiIjIJgaPREREREREZBODRyIiIiIiIrKJwSMRERERERHZxOCRiIiIiIiIbGLwSERERERERDYxeCQiIiIiIiKbGDwSERERERGRTQweiYiIiIiIyCYGj0RERERERGQTg0ciIiIiIiKyicEjERERERER2fT/6F2/BOY5APwAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "plt.plot(interface.z / ANGSTROM, (initial_density / (KILO * MOL / METER**3))[0], linestyle=\"dashed\", label=\"initial density\")\n",
    "plt.plot(interface.z / ANGSTROM, (interface.density / (KILO * MOL / METER**3))[0], label=\"equilibrium density\")\n",
    "\n",
    "plt.xlim(40, 60)\n",
    "plt.ylim(-5, 60)\n",
    "plt.ylabel(r\"$\\rho$ / kmol m$^{-3}$\")\n",
    "plt.xlabel(r\"$z$ / A\")\n",
    "sns.despine(offset=10)\n",
    "plt.legend(frameon=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc985a88",
   "metadata": {},
   "source": [
    "## Comparison to NIST data using `SurfaceTensionDiagram`\n",
    "\n",
    "We can use the above steps to calculate multiple VLE's and then - for each VLE - calculate the surface tension. We provide a utility object, the `SurfaceTensionDiagram`, that you can use to do exactly this task. Let's load some experimental (correlation) data obtained from the NIST Webbook and see how the water model compares to that."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "caa1fda7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Temperature (K)</th>\n",
       "      <th>Pressure (MPa)</th>\n",
       "      <th>Density (l, mol/l)</th>\n",
       "      <th>Volume (l, l/mol)</th>\n",
       "      <th>Internal Energy (l, kJ/mol)</th>\n",
       "      <th>Enthalpy (l, kJ/mol)</th>\n",
       "      <th>Entropy (l, J/mol*K)</th>\n",
       "      <th>Cv (l, J/mol*K)</th>\n",
       "      <th>Cp (l, J/mol*K)</th>\n",
       "      <th>Sound Spd. (l, m/s)</th>\n",
       "      <th>...</th>\n",
       "      <th>Volume (v, l/mol)</th>\n",
       "      <th>Internal Energy (v, kJ/mol)</th>\n",
       "      <th>Enthalpy (v, kJ/mol)</th>\n",
       "      <th>Entropy (v, J/mol*K)</th>\n",
       "      <th>Cv (v, J/mol*K)</th>\n",
       "      <th>Cp (v, J/mol*K)</th>\n",
       "      <th>Sound Spd. (v, m/s)</th>\n",
       "      <th>Joule-Thomson (v, K/MPa)</th>\n",
       "      <th>Viscosity (v, uPa*s)</th>\n",
       "      <th>Therm. Cond. (v, W/m*K)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>275.0</td>\n",
       "      <td>0.000698</td>\n",
       "      <td>55.502</td>\n",
       "      <td>0.018017</td>\n",
       "      <td>0.13978</td>\n",
       "      <td>0.13979</td>\n",
       "      <td>0.5100</td>\n",
       "      <td>75.903</td>\n",
       "      <td>75.915</td>\n",
       "      <td>1411.4</td>\n",
       "      <td>...</td>\n",
       "      <td>3271.50</td>\n",
       "      <td>42.830</td>\n",
       "      <td>45.115</td>\n",
       "      <td>164.06</td>\n",
       "      <td>25.580</td>\n",
       "      <td>33.980</td>\n",
       "      <td>410.33</td>\n",
       "      <td>558.89</td>\n",
       "      <td>8.9986</td>\n",
       "      <td>0.016879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>285.0</td>\n",
       "      <td>0.001389</td>\n",
       "      <td>55.479</td>\n",
       "      <td>0.018025</td>\n",
       "      <td>0.89678</td>\n",
       "      <td>0.89681</td>\n",
       "      <td>3.2139</td>\n",
       "      <td>75.397</td>\n",
       "      <td>75.533</td>\n",
       "      <td>1454.3</td>\n",
       "      <td>...</td>\n",
       "      <td>1704.30</td>\n",
       "      <td>43.078</td>\n",
       "      <td>45.445</td>\n",
       "      <td>159.52</td>\n",
       "      <td>25.736</td>\n",
       "      <td>34.170</td>\n",
       "      <td>417.48</td>\n",
       "      <td>408.81</td>\n",
       "      <td>9.2941</td>\n",
       "      <td>0.017535</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>295.0</td>\n",
       "      <td>0.002621</td>\n",
       "      <td>55.384</td>\n",
       "      <td>0.018056</td>\n",
       "      <td>1.65110</td>\n",
       "      <td>1.65120</td>\n",
       "      <td>5.8154</td>\n",
       "      <td>74.765</td>\n",
       "      <td>75.361</td>\n",
       "      <td>1487.7</td>\n",
       "      <td>...</td>\n",
       "      <td>934.36</td>\n",
       "      <td>43.324</td>\n",
       "      <td>45.773</td>\n",
       "      <td>155.38</td>\n",
       "      <td>25.898</td>\n",
       "      <td>34.374</td>\n",
       "      <td>424.46</td>\n",
       "      <td>304.01</td>\n",
       "      <td>9.6018</td>\n",
       "      <td>0.018214</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>305.0</td>\n",
       "      <td>0.004719</td>\n",
       "      <td>55.233</td>\n",
       "      <td>0.018105</td>\n",
       "      <td>2.40440</td>\n",
       "      <td>2.40440</td>\n",
       "      <td>8.3264</td>\n",
       "      <td>74.038</td>\n",
       "      <td>75.300</td>\n",
       "      <td>1513.1</td>\n",
       "      <td>...</td>\n",
       "      <td>536.20</td>\n",
       "      <td>43.568</td>\n",
       "      <td>46.099</td>\n",
       "      <td>151.59</td>\n",
       "      <td>26.069</td>\n",
       "      <td>34.596</td>\n",
       "      <td>431.28</td>\n",
       "      <td>231.32</td>\n",
       "      <td>9.9196</td>\n",
       "      <td>0.018918</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>315.0</td>\n",
       "      <td>0.008145</td>\n",
       "      <td>55.034</td>\n",
       "      <td>0.018171</td>\n",
       "      <td>3.15730</td>\n",
       "      <td>3.15750</td>\n",
       "      <td>10.7560</td>\n",
       "      <td>73.235</td>\n",
       "      <td>75.301</td>\n",
       "      <td>1531.7</td>\n",
       "      <td>...</td>\n",
       "      <td>320.58</td>\n",
       "      <td>43.811</td>\n",
       "      <td>46.422</td>\n",
       "      <td>148.10</td>\n",
       "      <td>26.252</td>\n",
       "      <td>34.843</td>\n",
       "      <td>437.93</td>\n",
       "      <td>180.66</td>\n",
       "      <td>10.2460</td>\n",
       "      <td>0.019646</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 25 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   Temperature (K)  Pressure (MPa)  Density (l, mol/l)  Volume (l, l/mol)  \\\n",
       "0            275.0        0.000698              55.502           0.018017   \n",
       "1            285.0        0.001389              55.479           0.018025   \n",
       "2            295.0        0.002621              55.384           0.018056   \n",
       "3            305.0        0.004719              55.233           0.018105   \n",
       "4            315.0        0.008145              55.034           0.018171   \n",
       "\n",
       "   Internal Energy (l, kJ/mol)  Enthalpy (l, kJ/mol)  Entropy (l, J/mol*K)  \\\n",
       "0                      0.13978               0.13979                0.5100   \n",
       "1                      0.89678               0.89681                3.2139   \n",
       "2                      1.65110               1.65120                5.8154   \n",
       "3                      2.40440               2.40440                8.3264   \n",
       "4                      3.15730               3.15750               10.7560   \n",
       "\n",
       "   Cv (l, J/mol*K)  Cp (l, J/mol*K)  Sound Spd. (l, m/s)  ...  \\\n",
       "0           75.903           75.915               1411.4  ...   \n",
       "1           75.397           75.533               1454.3  ...   \n",
       "2           74.765           75.361               1487.7  ...   \n",
       "3           74.038           75.300               1513.1  ...   \n",
       "4           73.235           75.301               1531.7  ...   \n",
       "\n",
       "   Volume (v, l/mol)  Internal Energy (v, kJ/mol)  Enthalpy (v, kJ/mol)  \\\n",
       "0            3271.50                       42.830                45.115   \n",
       "1            1704.30                       43.078                45.445   \n",
       "2             934.36                       43.324                45.773   \n",
       "3             536.20                       43.568                46.099   \n",
       "4             320.58                       43.811                46.422   \n",
       "\n",
       "   Entropy (v, J/mol*K)  Cv (v, J/mol*K)  Cp (v, J/mol*K)  \\\n",
       "0                164.06           25.580           33.980   \n",
       "1                159.52           25.736           34.170   \n",
       "2                155.38           25.898           34.374   \n",
       "3                151.59           26.069           34.596   \n",
       "4                148.10           26.252           34.843   \n",
       "\n",
       "   Sound Spd. (v, m/s)  Joule-Thomson (v, K/MPa)  Viscosity (v, uPa*s)  \\\n",
       "0               410.33                    558.89                8.9986   \n",
       "1               417.48                    408.81                9.2941   \n",
       "2               424.46                    304.01                9.6018   \n",
       "3               431.28                    231.32                9.9196   \n",
       "4               437.93                    180.66               10.2460   \n",
       "\n",
       "   Therm. Cond. (v, W/m*K)  \n",
       "0                 0.016879  \n",
       "1                 0.017535  \n",
       "2                 0.018214  \n",
       "3                 0.018918  \n",
       "4                 0.019646  \n",
       "\n",
       "[5 rows x 25 columns]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "literature = pd.read_csv(\"data/water_vle_nist.csv\", delimiter=\"\\t\")\n",
    "literature.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96ae9524",
   "metadata": {},
   "source": [
    "For the `SurfaceTensionDiagram`, we need to provide the VLE's. We compute those using the `PhaseDiagram` object (here for 50 temperatures between 275 Kelvin and the critical temperature) from which we get a list of `PhaseEquilibrium`s via the `states` filed. The `SurfaceTensionDiagram` is nice, because we can reuse equilibrium density profiles from prior iterations as input for the next iteration. It's therefore typically faster and more stable than an \"naive\" implementation by hand.\n",
    "\n",
    "The `SurfaceTensionDiagram` takes the same arguments `n_grind`, `l_grid` and `critical_temperature` as discussed above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c0a7854c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 434 ms, sys: 4.12 ms, total: 438 ms\n",
      "Wall time: 437 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "vles = PhaseDiagram.pure(\n",
    "    pcsaft, \n",
    "    275*KELVIN, \n",
    "    50,\n",
    "    critical_temperature=cp.temperature\n",
    ")\n",
    "sfts = SurfaceTensionDiagram(\n",
    "    vles.states, \n",
    "    n_grid=512, \n",
    "    l_grid=100*ANGSTROM, \n",
    "    critical_temperature=cp.temperature\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "caa7026e",
   "metadata": {},
   "source": [
    "We now can extract all surface tensions via `surface_tension` as well as the liquid and vapor states via the `liquid` and `vapor` getters, respectively. Let's store the results in a pandas `DataFrame` to make plotting easier."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "6626c4c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "dft_data = pd.DataFrame(\n",
    "    np.array([\n",
    "        sfts.liquid.temperature / KELVIN, \n",
    "        sfts.surface_tension / NEWTON * METER\n",
    "    ]).T, \n",
    "    columns=[\"Temperature (K)\", \"Surf. Tension (l, N/m)\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "279a66a3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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fjh8/Tps2bYDU5NPAwIB69epRvXp1Dh8+zOnTp2nbti1+fn4EBARQpEgRqlSpohfL2NiYp0+f4u3tjb+/P/fv38ff359r164pBbh0389Z0X3vajQaPv744wyvMzQ0JCUlhTt37qSZcc2LPd5CCJEZST6FEOI9ZW5uToMGDWjQoAFffPEF48ePZ9euXXh7e+Pr65tpopETzycY2aXValm6dCmLFi3Sm8lTqVSULl2azp07s23bNr3XREREKF+nN6uYnqioKCDt8t2MREZGvlLyqZvde/jwIQ8fPsz02uTkZGJiYvSWlQJ6M9bpeX7WsWLFimzfvp1Fixaxb98+IiIilOJEv/76K2q1mkmTJmVZbVY37szO/nx+nDExMXrJZ1ZjfnHcWY0ju2PJ7lLezDRv3px58+YpBYaCg4Px8/PD1dWVggULUq9ePQ4fPsypU6do27Ythw8fBlKT1uc/OIiOjmbq1Kns2LFDSaAh9b1xdXWlYsWKHDt2LNvj0n3vJiYmcuHChSyvf/7PkU56HwgIIURekuRTCCHyse+//55Tp07RtWtXZb9jeszMzJgyZQpeXl5oNBru3r2bJvnMKDnIi32iCxYsUPaztWvXjsaNG1OuXDnKlCmDpaUl/v7+aZJP3bJFyH7SoXvNp59+ypgxY3Jp9Fnf77vvvqN37955fj9IXYb6008/MWXKFK5cucKZM2c4efIkp0+f5ubNmwwcOJA9e/ZQtGjRDGNYWlry9OlTJeFJz/N7Ip/fX5qbno8bFRVFoUKFMh1LboyjYsWKFCtWjMDAQO7cuYO3tzeAcoSJ7v+65cC65PPFpbBDhw7l9OnTmJmZ0bt3b6pWrUr58uUpVaoUxsbGbNiwIUfJp+57ydXVlc2bN7/KIwohxGsjez6FECIfS0hI4N69e8pew8xYWVkpP6w/X3hEdyTL87M1z3v8+HEujPQZjUbD0qVLARg2bBhz5syha9euVKlSRRlfevtSCxQooCQjuiWJ6Y21e/fujBo1iqioKOXokYyuBwgPD+f8+fMEBQVla3YuM9m538OHD/H29laWEL8srVbLgwcPlBk7AwMD3NzcGDhwIEuXLmXHjh1YWVkRFxeHl5dXprF0hZF8fX0zvEZ3jEnBggX1Zj1zU8mSJTEyMtK7X2Zj0e15fVW6fbbHjx9Xkkxd0uni4kLhwoW5e/cut2/f5sKFC1hbW+sdOePt7a28btGiRYwdO5a2bdtSrlw5ZVY4p3utnz82J6Mly1qtllOnTuHv709iYmKO4gshRF6Q5FMIIfIxXfGaK1euZDk7cvz4cSIiIrCxsaFq1apKuy6RuHPnTprXJCcnK8Vockt4eDixsbFAxnsMN27cqHz9/A/euqI2umq2L/r333+VsyCtra2VpOLkyZP4+fml+5rZs2fTq1cv+vTpk+3kU7fc8sXrdffbvXt3hst8x48fj6enJ6NHj87WvTISERFB69at6d+/P5cvX07TX7p0aWUJcVb7DHXj3rp1q94Mp05iYiLr1q0DoFGjRq807sxYWFhQt25dAFauXJnuNffv31e+J9MrcvQymjVrBqTu9Txz5gwmJiZ6S5V1Y5o5cyZJSUl4eHjoLTV+8OCB8nV6e1Xj4uKUyrwvFrV6vnDW899PtWrVwtrampiYmAz/bO/YsYN+/frRtm3bXC8kJoQQL0OSTyGEyMcaNGhA69atAZg4cSJTp07V+0EYUmdHN23axJdffgnAl19+qbdcUVcR89atW6xcuVL5Afjp06eMHz8+20dDZJednZ1y0P3y5cv19nKGhYUxefJkdu7cqbQ9Xx104MCBmJiYcO7cOaZMmaK3JPjo0aPMmTMHgAEDBgCpR000bNiQpKQkBg0apLd3LjExkYULFyqJ7qBBg9KtoJse3fsXFBSk196uXTvUajWRkZEMGDBAbwY0OjqayZMnc+LECVQqFYMHD87WvTJia2urJILjx4/XS65TUlJYs2YNN2/exMDAIMuEsWfPnjg6OvLkyRM+++wz7t+/r/SFhobyxRdfcPPmTSwtLRkxYsQrjTsrw4cPx8jIiOPHj/Pdd9/p7QO9fv06gwYNIiEhgQoVKtClS5dcuWft2rWxsrLiv//+IygoiGrVquntl9TNgma05Pb5I3UWLFigt4rg9u3bDBo0CH9/fyDtMvbn9y8///1kYWGhfI9MnTqVTZs26X2IsH//fiZNmgRA27ZtKVmyZI6fWwghcpvs+RRCiHxu1qxZWFhYsHXrVlauXMnKlSspVqwYhQoVIiEhQVmSZ2xszOjRo9NUffXw8KBmzZqcO3eOqVOnsmzZMmxtbblz5w4ajYYRI0Yo+zNzg5GREV988QU//PADZ86coUmTJjg7O5OYmMi9e/dISkqiUqVKPHz4kPDwcB49eqTMkJYrV45ffvmFb7/9ljVr1rBlyxbKlClDaGioUuCnW7du9OrVS+/9+eyzz7h06RI9e/bEycmJggULcv/+faVIyyeffJLhERnpqVixIgAXLlygTZs2lCtXjvnz52NsbMzChQsZOHAg165do0OHDpQuXRpzc3P8/f2VGd9x48blyqzdlClT8PT05ObNm3To0AEnJyesra0JCgoiPDwcgFGjRmV51meBAgX4888/GTx4MBcvXqRVq1aUK1cOIyMjbt26hUajwcbGhtmzZ+Ps7PzK486Mu7s7U6dOZeLEiWzYsIHt27dTtmxZYmNjleq2arWa+fPnY2Jikiv3NDExoWHDhvz777/As2RTp379+srXxsbGaX7vKlWqRNu2bdmzZw/Lli1j8+bNODk5ERERoXwY1KBBA/777z9iYmKIjo5WiiY5OztjYWFBbGws3bt3x8nJialTp1KhQgUGDRrE/fv32bBhA+PHj2fmzJk4OTkRHBysLIevUaMGU6dOzZX3QQghXpXMfAohRD5nYmLCjBkz2LhxI59++imurq4kJiZy/fp1Hj16ROnSpRkwYADbt29Pd7bNwMCApUuX8uWXX1K+fHlCQ0MJCgqiXr16rFu3jo4dO+b6mHv16sXy5ctp0KAB1tbW3Lp1i9DQUKpWrcr333/Phg0b8PDwANKeh9m2bVu2bdvGRx99hK2tLTdu3CAqKoo6derw22+/MX36dL0qpLa2tqxZs4YpU6ZQu3ZtoqKiuHHjBkZGRnh4eLBw4cJsnYX5vC5dujBw4EDs7e158OAB165dU2alSpQowZYtW/j222+pWrUqISEhyqxh69atWb16Nf369XvFdzCVg4MD//zzDwMGDKBcuXLKvUxNTWnfvj3r1q3L9gxrpUqV2LlzJ8OGDaN8+fLKMSGlS5dmyJAhbN++nYYNG+bKuLPSpUsXtm3bRvfu3SlcuDC3bt0iPDyc6tWr8/333/PPP/9QokSJXL3n87OZLyafxYoVU5LuunXrpqlQDKnLt3/88UeqVKmCVqvlxo0bJCYm0rRpUxYtWsSyZcuUZdDPL2W3tLTk999/p0KFCsTGxvLgwQMlYVWpVPz4448sXbqUli1bYmRkxLVr14iJiaFatWpMnDiR5cuX6xXjEkKIN0mlfdXqCW+Ru3fvsmDBAs6fP09oaChFihShbdu2DB48OMcV74KDg1m4cCEnTpzg0aNHFC5cmGbNmjFs2DC9Qhw6Wq2WTZs2sWHDBm7dukVSUhJOTk60atWKQYMGpfsPkRBCCCGEEEK8L/JN8unj40O/fv2IjY2latWqFClShAsXLhASEoJarWbt2rWZngn2vICAAHr16qW8tnTp0ly9epX79+/j6OjI33//naYk/ZgxY9i6dSvGxsbUrFkTMzMzLl68SEREBKVLl2bt2rXpJq1CCCGEEEII8T7IF8mnRqOhdevWBAYGMmPGDLp27QqkFqEYNWoUBw8epGfPnkyePDlb8Xr27MmFCxcYMWIEw4cPB1Krz02ZMoX169fTuHFjlixZolx/5MgRBg8ejL29PStXrlQKC0RGRvLZZ59x4cIFevXqpWz8F0IIIYQQQoj3Tb7Y87lr1y4CAwNp0KCBknhC6qHp06ZNw8LCgn/++UcpHJGZs2fPcuHCBcqUKcPQoUOVdkNDQyZOnEixYsU4evQot2/fVvp0h0J/+OGHehXtChQowLBhwwA4c+bMKz+nEEIIIYQQQryr8kXyqSs20apVqzR9tra21KlTB41Gw/Hjx7Mdq0WLFmlK6hsbGysFB54vBqC7Lr0DwcPCwgCUYwOEEEIIIYQQ4n2UL5JP3RlzLi4u6faXL18egBs3brxyLF05+udj6SoubtmyhcWLF/PkyROio6PZv38/M2bMwMDAgE8//TSbTyOEEEIIIYQQ+U++SD51M46Ojo7p9tvb2wMoZ17lRqyQkBClrUGDBowePRpjY2Nmz55NgwYNqFGjBsOGDcPCwoLly5enOXBaCCGEEEIIId4nRm96ALkhLi4OSN3jmR5du+7w7ryI1bhxY06fPs25c+eoUqUKZmZmXLlyhfv377NkyRJcXFwyXXq7fv16NmzYkOX4AB48eICFhQU1atRg9uzZ2XqNEEIIIYQQQrxJ+SL5NDQ0VA7vzkx2CvsaGhpm657P3+/IkSMMHz4cZ2dndu7cqRxsHRMTw/fff8/OnTsZNGgQGzZs0DvY/HkhISH4+vpm694AT58+5e7du9m+XgghhBBCCCHepHyRfFpaWhIREUFCQkK6/fHx8QBYWFhkKxaQZSzddUlJSfzwww8kJiYyc+ZMJfHUXTNt2jR8fHzw8fHh6NGjyv7QF9nb2+Pq6prl+AD8/PyUcQghhBBCCCHEuyBfJJ8ODg5EREQQEhJC0aJF0/Tr9no6ODhkK5avr2+G+0NfjBUQEEBgYCAODg5UqFAhzfWmpqbUq1ePgIAALl++nGHy2aNHD3r06JHl+AC6deuWo1lSIYQQQgghhHjT8kXBIV1l2lu3bqXbrzuTM6MKtunFev4cz8xi6c4ONTY2zjCmbimvRqPJ8v5CCCGEEEIIkR/li+SzSZMmAHh5eaXpCw8P5/Tp08oMZHZj7du3L80eUY1Gw4EDB/Suc3Z2xtDQkMDAQK5fv54mXlJSEqdOnQKgUqVK2X0kIYQQQgghhMhX8kXy2aJFC4oXL87hw4dZv3690h4fH8+ECROIjY2le/fu2NnZKX0ajQY/Pz/8/Pz0ZiTd3d1xc3Pj5s2b/Pbbb0oCmpyczNSpU3n48CFNmzZFrVYDYGNjQ/v27QH49ttvefjwoRIrISGBKVOmcOfOHUqWLEnTpk3z9H0QQgghhBBCiLeVSpudErDvgLNnzzJw4EDi4+NxdXXFycmJixcv8vjxYypXrszKlSuVIkGQelyJ7uzNAwcO4OTkpPT5+fnx8ccfEx4eTpkyZShfvjzXrl0jICAAJycn1q1bp7d/NCoqik8//RQfHx+MjY2pVasWpqamXLlyhZCQEAoXLszSpUvT3RP6MnR7Pl1dXdm8eXOuxBRCCCGEEEKIvJQvZj4BatWqxcaNG2ndujVBQUEcPnwYa2trhg8fzooVK/QSz6yULVuWTZs20a1bN6Kiojh06BAqlYq+ffuyYcOGNIWLrK2tWbNmDePGjaNChQp4e3tz/PhxLC0t+eSTT9i6dWuuJZ5CCCGEEEII8S7KNzOf7xOZ+RRCCCGEEEK8a/LNzKcQQgghhBBCiLeXJJ9CCCGEEEIIIfKcJJ9CCCGEEEIIIfKcJJ9CCCGEEEIIIfKcJJ9CCCGEEEIIIfKcJJ9CCCGEEEIIIfKcJJ9CCCGEEEIIIfKcJJ9CCCGEEEIIIfKcJJ9CCCGEEEIIIfKcJJ9CCCGEEEIIIfKcJJ9CCCGEEEIIIfKcJJ9CCCGEEEIIIfKcJJ9CCCGEELno9OnTuLi44OLiwv79+zO9dvny5bi4uDB27FilbfPmzbi4uNCnT590X3P//n2mT59Ox44dqVGjBm5ubnh4eDBs2DB27txJSkqK3vXz5s1TxpPd/+bNm/fqb4QQQrzA6E0PQAghhBAiv/r++++pXr06dnZ2uRJv586djB07Fo1GQ9myZalXrx4qlYqgoCAOHjzI/v37Wb16NX/99RdWVlYAuLi40LFjR704cXFxSmL8Yp/uNUIIkdsk+RRCCCGEyCOhoaFMmjQpV2YS79+/z9ixYzE0NGTRokU0aNBAr//u3buMHDmSixcvMmnSJGbPng1Aq1ataNWqld61Dx48UJLPWbNmvfLYhBAiO2TZrRBCCCFEHrCzs8PExAQvLy+2bdv2yvG2bduGRqOhe/fuaRJPgNKlSzNnzhwAdu/eTURExCvfUwghcpMkn+KtczXsISOOrGeO937C4mPe9HCEEEKIl+Lg4MCoUaMA+OmnnwgODn6leKGhoQCoVKoMrylXrhw9evTgo48+IiEh4ZXuJ4QQuU2W3Yq3zsRT2zgT7A/AwstH6ONSh8GVG1PEosCbHZgQQgiRQ5988gkHDhzg3LlzjB8/nqVLl750rEqVKgGwbt06ypcvT8eOHTEzM0tz3Q8//PDS9xBCiLwkyad465SytlOSz7gkDYt9j7P82kl6qGvxeeXGlLDOnaINQgghcldcUiKJyclvehg5ZmJoiLmRSZ7ENjAwYMaMGXTq1Injx4+zdu1aevXq9VKxOnXqxLp16/D19WXixIlMnTqVmjVrUrNmTWrUqEHVqlUxMcmb5xBCiNwgyad460yv15UyBexZ4nucsITUZbeJKcmsvH6KtTfO0K2sO8PcmlC2oP0bHqkQQgidSad38L9rJ0jRat/0UHLMQKWif8X6/FAnbdXX3FCiRAnGjh3L999/z8yZM2nYsCElS5bMcRxTU1NWrFjBzJkz2bRpE3FxcRw7doxjx44BYG5uTsOGDRk8eDBubm65/RhCCPHKZM+neOuYGRkzompTTn00hkm12+P43HLbJG0KG26fp8nmX/n80FquhgW9wZEKIYTQWX7t5DuZeAKkaLUsv3YyT+/h6elJ48aNiY2NZcyYMWnO4swua2trpkyZwrFjx5g+fTqdO3emePHiQOrxKfv27aN79+4sWrQoN4cvhBC5QpJP8dayMDZhkGsjTnz4LTPqdaWEla3Sp0XLDn8fWm2bS//9K7gQEvAGRyqEEOKTivUwyKQQztvMUGXAJxXr5fl9pk6dio2NDRcuXOCvv/56pVh2dnZ069aNX375hYMHD3L48GF++ukn1Go1Wq2WX3/9lZMn8zahFkKInJJlt+KtZ2poRO8KdfBU12TbHW/m+xzm9tMQpX/f/Wvsu3+NRsXKMcKtKfWKlMm0EqAQQojc90Odjoyt0Vr2fGbCwcGB77//nq+++oq5c+fi4eGR7dfGx8dz+/ZtEhISqFGjRpr+okWL8tFHH9GlSxcGDRrEyZMn2bp1K/Xq5X1SLYQQ2SXJp3jrxN0+Sej2nzB1csOu/bcYWqbOeBobGPJhuRp0LePOnntXmOtziKthD5XXHQu6zbGg29R0KMUIt6Y0c3KRJFQIIV4jcyMTzOUni0y1b9+effv2sWfPHsaMGUOHDh2y9brAwEA++OADzM3NOXv2LMbGxuleZ2xsTNeuXTl58qSc8ymEeOvIslvx1glZ9zWxPv8SvvsX/MdW5OnRZWif2xtjaGBAh9Ju7O00khUtPqG6vX7RhnOP79Fv/3Labp/Hbv8rpGhfbl+NEEIIkRcmT56Mvb09165dY+XKldl6TalSpbC3tycuLo4NGzZkeu2dO3cAcHFxeeWxCiFEbpLkU7x1TEtWVb5OjgoheNkg7v/UgPi75/SuU6lUNC9RgW3tP+fv1gNpULSsXv+VsCAGH1pN621zJQkVQgjx1rCxsWHq1KkABAcHZ+s1RkZGjBgxAoBp06bx119/ER8fr3dNSkoKmzdvZtmyZVhYWLz0kS5CCJFXZHGMeOs4fPwbxoWdCd3+E9r/P2ol/s4ZAqbUpWDjART+cCqG1oWV61UqFQ2KlaNBsXKcf3yPuZcOceDBdaX/WvgjBh9aTSW7ooyq1pzWJSthoJLPXYQQQrw5Hh4efPTRR2zcuDHbr/H09CQsLIz58+czc+ZM5s+fT5UqVShUqBAxMTH4+voSGhqKjY0Nv//+O0WKFMnDJxBCiJyTn8DFW0dlZIJd+29xnn4V69rdn3VotTw98hd3x1Yg4uAfaFPSFrWo4VCKFS0/4d9OI2hbylWv72rYQwYdXE2b7fPYc+8K2nf0SAAhhBD5w9ixY3FycsrRaz7//HO2b9/Op59+SpkyZbh9+zb79+/Hx8eHYsWKMWLECP7991/q1q2bR6MWQoiXp9LKT+DvnG7duuHr64urqyubN29+08PJc7HXDvF41UgSg67qtZuWrIZDn3mYl6+f4Wuvhj1kjvd+9tzzTdPnaleUUdVa0LpkJSlMJIQQQgghRB6T5PMd9L4lnwDaJA0RBxYSunUyKXGRen0FGvSl8EfTMbLJeHnR1bAgfr14gH8D0k9Cv6rWglaShAohhBBCCJFnJPl8B72PyadOUsQjnmwcR+R/+tUBDcwLUKjLZGyaD0VllH75eQDf0CB+9d7P3oCrafoq2xXjK/cWtCxRUZJQIYQQQgghcpkkn++g9zn51Im79R+PV40kIcBbr92kuCsOvediUbFJpq+/EhrIHO8D6SahVQoV56tqzWkhSagQQgghhBC5RpLPd5Akn6m0Kck8PbyYJ5u+IyUmXK/Puo4nhT1/wdgu80IOkoQKIYQQQgjxekjy+Q6S5FNfctQTnvwzgadHl8Jz384qU0sKdZyATesvMTA2zTTG5SeBzPHej9f9a2n6qhZ2YrR7S5oWV0sSKoQQQgghxEuS5PMdJMln+uLvnOXx6pHE3zmj127sWB6Hj3/D0q1NljF8njxgjvcB9qWThNZ2dObb6q2oW6RMro1ZCCGEEEKI94Ukn+8gST4zpk1JIfL4cp5sHE9yVIhen6V7Jxx6/Yqxfeks4/g8ecCv3vvZf/96mj6PYuX5pnorqtmXyLVxCyGEEEIIkd9J8vkOkuQza8kx4YRumUzEgYWgTVHaVUam2Lb/Frt232JgapFlHO+Q+8y84MWRoFtp+lqXrMQ31VtRwTbjI16EEEIIIYQQqST5fAdJ8pl9Cfd9eLxqJHE3j+m1GxUqhX2v2VhV75KtfZwnH93hl/N7Ofv4nl67ChVdylTlK/cWlC5QOFfHLoQQQgghRH4iyec7SJLPnNFqtUSdWkfI32NIjgjS67Oo3BKHj3/HpKhLtuIcCrzJzAteXA4N1OszVBngWb4mX1ZtRjErm9wcvhBCCCGEEPmCJJ/vIEk+X05KXBShO6YSvncOJCc96zA0xrbVFxTqNBEDc+ss42i1Wnbfu8KsC/u49fSxXp+poRF9XOow3K0phc2tcvsRhBBCCCGEeGdJ8vkOkuTz1SQGXefxmi+I9d2v125oUxR7z1+wrtszW0txk1NS2HLnIr9ePEBAdJhen4WRCQMqNeCzyo2wycbeUiGEEEIIIfK7fJV83r17lwULFnD+/HlCQ0MpUqQIbdu2ZfDgwVhaWuYoVnBwMAsXLuTEiRM8evSIwoUL06xZM4YNG4adnZ3etS4uWS/ZBOjatSszZszI0TjSI8nnq9NqtURf2ErI2tEkherv4zRXN8Khz1xMS7hlK1ZichJ/3zrHb5cOEhwbqddX0MSMzyo3ZkClBlhmcdaoEEIIIYQQ+Vm+ST59fHzo168fsbGxVK1alSJFinDhwgVCQkJQq9WsXbsWa+usl1QCBAQE0KtXL+W1pUuX5urVq9y/fx9HR0f+/vtvihYtqlz/9ddfZxgrLi6O/ftTZ9i+++47evfu/WoPiiSfuSklIZaw3b8QvusXtEkJzzpUBtg0H0qhrpMxtLTNVqy4JA2rrp9ivs9hwhJi9PoKmVkysmozervUwdTQKDcfQQghhBBCiHdCvkg+NRoNrVu3JjAwkBkzZtC1a1cA4uPjGTVqFAcPHqRnz55Mnjw5W/F69uzJhQsXGDFiBMOHDwcgOTmZKVOmsH79eho3bsySJUuyFevrr79mx44duTbrCZJ85oXEx3cIWTeamIvb9doNrQtT+MNpFGjUH5WBQbZiRWsS+Mv3OIuuHCVKk6DXV9LKjm+qt6JzGTcMVNmLJ4QQ4t1x+vRp+vbtm26foaEh5ubmFCtWjLp169K/f3+KFSuWYSxfX1+2bNnCmTNnePToEbGxsTg4OODu7o6npye1a9d+6XEeOHCA7du34+3tTVhYGKampjg6OlKnTh169OiBWq3OMoaXlxcjRowAYOLEifTp0yfDazN7X15UoUIFtm3bxtixY9myZUv2Huj/TZ8+nW7dumXr2mvXruHp6cm0adPo0KGD0h4YGMiSJUs4fvw4jx49wsTEhHLlytG1a1c8PT0xeO7ngcyey8LCgsKFC1OnTh0GDBhA6dL654zHxcXRvn176tevz08//ZSj5xTiXZUvks+tW7cyZswYGjRowLJly/T6wsPDadasGRqNhhMnTlCgQIFMY509e5bevXtTpkwZdu3apfcXjEajoVWrVgQFBbFr1y7KlSuXaayNGzcyceJEypQpw5YtWzAzM3v5h3yOJJ95J8ZnD4/XjEITrH+up2npWjj0mYt5mez/Qx+eEMufl4+y7Np/xCVp9Ppc7YoyvmZbGhcrn639pUIIId4NumTEwsKC5s2b6/WlpKQQExODt7c3ERERFCxYkOXLl1OpUiW962JjY/npp5/YtGkTACVLlqRUqVIYGRlx584d7t1L3S7St29fJkyYkKPxaTQaRo0axb59+zAxMaFq1arY29sTGRnJ3bt3CQwMxMDAgK+++opBgwZlGmvgwIGcOHEClUpFyZIl2bNnz0u9Ly8qXrw4o0aN4u+//+bs2bN6faGhoZw4cSLDOD169KBmzZqZxofUCYrOnTvj6OjIypUrlXYfHx/69+9PdHQ0RYsWpWLFikRFReHt7Y1Go6Fp06bMnz8fIyOjTJ9Lq9USFxeHn58f/v7+mJqasnTpUmrVqqU3jgMHDjB06FDmzp1L69atsxy3EO88bT4wcuRIrVqt1q5bty7d/s8++0yrVqu1u3btyjLWzz//rFWr1dpZs2al2//jjz9q1Wq1dtGiRZnGCQ0N1daqVUvr4uKivXjxYpb3zYmuXbtq1Wq1tmvXrrkaV6RKTozXhu6Yob05yEp7o5+B3n8Plw7Uap4+zlG84JhI7fgTW7Sl/jdOW3zZGL3/PPcs0XqH3M+jJxFCCPG6nTp1SqtWq7VNmzbN8JqYmBht79690/23XKPRaHv27KlVq9Xadu3aaU+dOpXm9YcPH9bWqFFDq1artTNmzMjR+ObPn69Vq9VaT09PbWhoqF5fSkqKdtu2bdpKlSpp1Wq19tixYxnGCQwM1FaoUEH74Ycfaj/99FOtWq3WnjhxIsPrs/O+ZEduxZk1a5bWxcVFe/XqVaUtOTlZ26pVK61ardZOnz5dq9FolD4/Pz9t06ZNtWq1Wrt06dIcjeevv/7SqtVqbbNmzbRJSUlp+vv06aOtX7++NjIy8pWeSYh3Qb5Y93fz5k0g48I/5cuXB+DGjRuvHEs325lVrF9//ZWnT5/y4YcfUq1atSzvK94eBsam2HUYg/OMa1jX8dTrizy6DP+xFQjfvwDt88e1ZMLBwpqp9bpwsOtXdHTWL2J0/OFt2u+Yz9DDa7kb+STXnkEIIcTby8LCQpmx9PX15f79+0qfrnCis7Mzq1evpk6dOmle7+Hhwbx58wBYsWKFMhOaHboVU5MmTUpTQFGlUtGpUyf69esHwNq1azOMs2nTJlJSUmjcuDHt27cHYPXq1dkex5sUFBTE8uXL8fDwoGLFikr72bNn8ff3x9nZmW+++UaZ3QQoU6YM33zzDQDbt29PEzMzn376KY6Ojjx48ABfX980/UOGDOHJkyfZ3tIlxLssXySfwcHBADg6Oqbbb29vD8Djx4/T7X+ZWCEhIRnGCAgIYNOmTZiYmCh7IcS7x9jOiaKfr8VpzAFMnCor7SmxEYSsHsm9STWJvXE02/HKFCzMH017sbPDMOoXKaPXt/2uD003/8qEk9sIiYvKtWcQQgjxdipVqpTy9ZMnqR8+JiYmKgncV199ha1txgXv6tWrR+vWrWnSpAmPHj3K9n1DQ0MBMt3y0alTJzp27EjVqlXT7U9JSVGS2Hbt2tG6dWssLCw4dOgQDx8+zPZY3pRly5aRmJhIjx499Nqjo6Nxc3PDw8MDQ0PDNK8rUyb13+7s/Dz5PJVKRZEiRQCIiYlJ01+vXj1KlSrF6tWriY6OzlFsId41+aLsZlxcHECGeyp17bGxsa8l1tKlS0lJSeGjjz7KMIl90fr169mwYUO2rvXz88vWdSJ3WFRsQqkfzhNx8A9CN39PSlzqcSqJDy7zYHpTrOv2xN7zF4xsMy4a8bxq9iX4u80gjgTdYtq5PVwNS/2HOkmbworrJ9l4+zyfVW7EZ5UbYyXHswghRL6kW2kFKEWHjhw5QmRkZLb2RQLMnTs3x/etWLEiFy5cYNy4cUyePDndBLNChQrMmjUrwxjHjh0jKCiIatWqUbZsWQDatGnD5s2bWb9+PaNGjcrxuF4XjUbD1q1bsbCwoEGDBnp9zZs3z/R99/HxAVASyeyKiYnhzp07mJmZpdnfC6nJafPmzVm2bBm7d++me/fuOYovxLskXySfhoaGpKSkZHmdNhu1ldL7pCs9Gd0vIiKCrVu3YmRkxODBg7MVC1JnUtNbiiHeDipDI2xbjsC6dnee/DOeyGPLlb6oU+uI9t5BoU7fYdtqJCojk6zjqVQ0Ka6mcbFybLlziZkX9vIgOgKA2KRE5ngfYOX1U3xZtTkfu9TGRI5nEUK8A1ISYtEmJb7pYeSYysgEA1OL13a/sLAwpkyZAqTOeuk+qNZ9uFy5cmW9JZ+5afTo0fTv35+rV6/SvXt3ihUrRp06dahRowY1a9ZMU5E1Pf/88w8AH374odLm6enJ5s2b2bhxI8OGDcPEJOt/C98Eb29voqKiaNiwYY7GGBsby8KFCwFo27Ztltdr/7/g0M2bN/n111+Jiopi9OjRFCxYMN3r69aty7Jlyzh27JgknyJfyxc/0VpaWhIREUFCQkK6/fHx8UDqHovsxAKyjKW77kX79u0jPj4eDw+PHH0yZm9vj6ura7au9fPzU8YhXi+jgo4UGbCUgh6DeLx6JAn+5wHQxkfzZMMYnh5dhkPv37Cs3Cpb8QxUBnxQ1p0OzlVYdf0Uv186SHhC6qx6aHwM353ezl9Xj/Nt9dZ0LF1FjmcRQry1Hq8ZRcT++aDN+sPgt47KAJsWw3H4eE6uhQwPD09zDnhycjIhISFcunSJxMREihQponfEhm7rj26LT16oWbMma9asYfLkyfj6+hIUFMSWLVuUI02KFStGhw4dGDRoULonBDx58oRDhw5hYWFBu3btlPZq1aqhVqu5efMme/bsoXPnzunePzAwMMO6GkCuHk2XnlOnTgHo7fXMSmJiIqNGjSIoKAhnZ+d0z2zP6rk+/fTTTCclKlSooDc+IfKrfJF8Ojg4EBERQUhICEWLFk3Tr1ub7+DgkK1Yvr6+Ga7nzyrW3r17gdT9EjnRo0ePNHsPMqI7akW8Oebl6lLy+5M8PbqUJ/9MJCU6dQ+N5tENAme1xapGF+x7zMbY3jlb8UwNjRjo2pDu5Wvy5+UjLPY9Tnxy6vEs96LCGHZkHX9eOcqEmm1pWCzzI36EEOJNiDiw4N1MPAG0KUQcWJCryWdsbCw7duzQazMyMsLKygpXV1caNWrExx9/jI2NjV4/QFJS9gravSw3Nzc2b97MtWvXOHLkCGfPnuXixYvExMQQFBTE4sWL2bRpE8uWLVOSIp0tW7ag0Wjo3Llzmg/iP/roI6ZOncratWszTD6zWlLs7u7+6g+YiaCgIACcnJyydX1sbCxffPEFR48excbGhoULF2Jubp7muvSeKy4ujocPH3L9+nWWLVvG48ePmT59erozro6OjpiamhIZGUl0dDRWVlYv8XRCvP3yRfLp4uLCzZs3uXXrFm5ubmn6b9++rVyXnViHDh1SXpOTWAkJCZw6dQoTE5Ns7dUQ7zaVgSE2TQZjXfNDnmz+nqeHFik/eEWf30qMz7/YdRiLbduvMTBJ+w9VegqYmPFtjdb0q1iPOd4HWHfzLMn/H/NyaCA99v5Fc6cKTKzVjvI2WX+YIoQQr4tN82Hv7syngSE2zYflasjixYtz8ODBHL1GN+OpKwqUU15eXnh5eaVpr1WrFp6enmnaK1asSMWKFRkyZAjJycn4+vri5eXF2rVrCQ0NZdiwYfz7778YGxsrr9Etub106RKffPKJXjxdPQxvb2/lPPIX2draZrqfNK/p3tuszn0HePToEUOHDsXX1xd7e3uWLl2q7HF9UWbP5e/vz6BBg9i5cye2trZMnDgx3eusra1JSEggNDRUkk+Rb+WL5LNJkybs2LEDLy8vPvjgA72+8PBwTp8+jampKfXq1ctWrD///JN9+/YxYsQIvWpwGo2GAwcOKNe9yNfXF41Gg7u7e7qfion8ydDKDse+8ynoMYDHq0YSf/sEAFpNPKFbJvP02HIcev2KpXunTKsLPs/RogAz6ndlkGtDfj6/l933rih9Bx5c53DgTT52qc1X1VpQ2Fz+gRJCvHkOH8+h8IdTZc/nK6hSpQoAV69eJTExMcs9iSdOnODq1avUq1cPV1dXbty4kWa2FVJnVD09PQkODubBgwc4ODhQokQJvWsMDQ1xc3PDzc2Nzp0788EHH/DgwQPOnz9P3bp1AThz5gz+/v4A3Lp1i1u3bmU4tjVr1jBt2rScPP5roZtVTk5OzvQ6Hx8fhg4dSkhICGXLlmXx4sXZni19kbOzM19//TUjR45k48aNjB8/HgODtNtodGPK65lvId6kfLGBrEWLFhQvXpzDhw+zfv16pT0+Pp4JEyYQGxtL9+7d9c6z0mg0+Pn54efnh0ajUdrd3d1xc3Pj5s2b/Pbbb0qRouTkZKZOncrDhw9p2rQparU6zTguX74MpBYKEO8fs1LulJhwlCKDlmNY8Nl+36Qn/gTN7Ubgr+1JfHQzkwhplS1oz+JmvdnWfii1HJ6V5U/WprDy+ikabprJfJ9DxCVpMokihBCvh4GpBYaWNu/cf29D4gmpM5Q2NjbExsZy+PDhLK9fvHgxM2fOZOnSpQCMGDGCGzdupPlPt4dy1apV9OrVi8WLF2cat3z58lSvXh1ILaSoo6vKP3To0HTvc+PGDf766y8Adu3apffat4VumXNYWFiG1xw6dIg+ffoQEhJC/fr1Wb9+/Usnnjq6c+Lj4+PTvXdycjJPnz7VG6MQ+VG+SD7NzMz4+eefMTMzY9KkSXTr1o2RI0fSsmVLDhw4QOXKldOU/Q4ODqZdu3a0a9dO2eCvM2PGDGxtbfnzzz9p164dI0eOpE2bNqxbtw4nJyelQt2LHjx4AGRvb6nIn1QqFQUa9MF5xjVs23wFz1Wpjb28F/8JboRsHE9KfM7O8arhUJLN7YawuGlvSlkXUtqjNQnMOL+XJptns9nvIinv4nI3IYQQQOoM5YABAwCYOXNmpmc+7t+/XylO06dPn2zFr1mzJgC7d+/O9KzKpKQkAgICAJQP258+faos6c2srkWDBg0oWrQo8fHxbNq0KVvjep101Xxf/NlP5+TJk4wYMYL4+Hg++OADlixZkq0lulm5e/cuAObm5ukml0+ePCElJYUCBQpQqFChNP1C5Bf5IvmE1E8LN27cSOvWrQkKCuLw4cNYW1szfPhwVqxYkWF12vSULVuWTZs20a1bN6Kiojh06BAqlYq+ffuyYcOGDJNL3SdZ1tbWufJM4t1laF4A+x4zKTXlIhaVntv/m6whfNfP+I+rROSp9dk6/kdHpVLRzrkyh7qOYnLtDhR8bh9pYEwEI4/+TcedCzn16E5uPooQQojXqH///ri6uhIQEICnpyfe3t56/Vqtlt27d/PNN9+g1Wrp1atXtov0eHh44O7uTnR0NH369OH06dNprgkLC2PMmDEEBgbSokULypQpA8D27dtJSEigSpUqmR7HYmBgQNeuXQFYt25dto7Ce510M7oXLlxI0xcWFsZXX32FRqOhW7duTJs2LVeOvHn06BGzZ88GoEOHDunGPH8+tXp+jRo1Xvl+QrzN8sWeTx21Wp3tA5ednJy4ceNGhv3Fixdn+vTpObr/7Nmzlb9chAAwLV6J4t/sJfrcJkLWfU1S2H0AksIDefTnxzw9tBiHPnMxdcr+Um2T/6+M+0G56sy9dJDl106iSUndJ3LpyQM+3LOY1iUrMaFmW8oUzLty/UIIIXKfsbExy5cvZ+TIkZw8eRJPT0+cnZ0pU6YMBgYG+Pr68vDhQwA+/vhjJkyYkO3YKpWKP//8k88//5wLFy7Qt29fihUrhlqtxtzcnODgYC5fvoxGo6F27dr8/PPPyms3btwIZK+af7du3fjjjz+4f/8+x44dw8PDI4fvQt6pVasWBQsW5MqVK8TGxuodw7dixQplIiEmJibNUTk6FhYWaVbBpXe0TkpKCiEhIXh7e5OYmEi5cuUYPXp0ujHPnDkDQMuWLV/62YR4F+Sr5FOIt5FKpcK61odYurUlbOfPhO+ZqRTkiLtxhHvfV8em+TAKdZmEoaVNtuPamlowqXYH+lWox/Tz/7LL/7LStzfgKgfuX6dvhbqMqtYcW7Psz/wLIYR4swoUKMCyZcv4999/2b17N76+vhw7dgxIPZKjS5cu9OjR46WOJbGxsWHt2rXs3buXffv24ePjw7lz50hISMDOzo7GjRvToUMH2rZtqxTJ8/Hx4caNGxgZGdG+ffss71GiRAnq1KnDqVOnWL169VuVfJqYmNC1a1eWL1/O/v379ZLpQ4cOKV/rjs5Lj7W1dZrkM72jdYyNjSlQoADVqlWjefPmeHp6pluQUqPRsH//fgoWLEibNm1e9tGEeCeotDlZ9yfeCrpzPl1dXdm8efObHo7IocTg24SsHUXMpd167YYFHCj80XQKNOiLKp0qeFk5G+zPlLO7uBhyX6+9gIkZI92a0b9SfUwN5fMmIYQQ77cnT57QsmVLXFxc9ApVvim7d+9m1KhRjB49msGDB7/p4QiRp/LNnk8h3hUmjuUoPmoHxb7chrHDs/PCkiMfE7x0APenNSbeP+1elKzUcnRme/uhLPToSQkrW6U9MjGen87tpunmX9lx1ydH+0yFEEKI/KZw4cL07duXixcv4uPj86aHw8qVK7G3t8924Sgh3mWSfArxhlhV60Cpn3wo1O1HVM8VD4q/fZKAH2oTvGIoydE5O2hcpVLRqUxVDnX9igk121LAxEzpC4gO4/PDa+my6480s6NCCCHE+2TIkCGULVuWadOmvdEPZXft2sXFixeZPHmynBEv3guSfArxBhmYmFGo03icp1/FquYHzzq0Wp4eWsTdMRWIOLQIbUrmh2G/yMzImM+reHD8g2/4pGI9jFTP/qifDwmg484FfHl0A49iI3PrUYQQQoh3hrm5Ob/++itXr15l27Ztb2QMcXFxzJw5kx49etCiRYs3MgYhXjfZ8/kOkj2f+VeM735CVn9B4sPreu2mparj0Gcu5uXqvVRcv6chTDu3h70BV/XaLYxMGO7WhEGujTA3Mn7pcQshhBBCCJEVmfkU4i1i6dqCUj9epLDnTFRmVkp7wr0L3P+pIY/++pSkp+kfjJ2ZsgXtWdq8L3+3GURF2yJKe2xSIr9c8KLpltns9L8s+0GFEEIIIUSekeRTiLeMysgEu7ZfUXr6NazrfazXF3l8Bf5jKxC+93e0yUk5jt2gaFn+7TSSGfW6Ymf67PiVB9ERDDm0hg/3LMY3NOiVn0EIIYQQQogXSfIpxFvKyLYYRT9bidO4w5iUcFPaU+IiCVn3Ffcm1SD2+pEcxzU0MKB3hToc++BrBrk21NsPejr4Lm22z+Pb/zbzJC46V55DCCGEEEIIkORTiLeehUsjSk0+i33vuRhY2CjtiQ+u8GBGMx7++TFJ4TmfrSxoas6k2h040HUUzZ0qKO1atKy9eYZGm2by5+WjJL7EDKsQQgghhBAvkuRTiHeAytAI2xbDcJ5xnQKNP9Xrizq1nrvjKhK2exbapMQcxy5b0J4VLT9hdatPKV/Q4VlcTQI/ndtNsy1z8Aq4KvtBhRBCCCHEK5HkU4h3iFEBe4p8uoQS353A1LmG0q6Nj+bJhjHc+86dGN/9LxW7SXE1Xl2+4Ic6HSn43Pmg/lGhfHpgJb28lnI9/NErP4MQQgghhHg/SfIpxDvIvGwdSn5/EodP/sDA0k5pT3x4ncCZrQma/xGa0IAcxzU2MGRApQYc/+Ab+lWoh4FKpfQdC7pN621zmXByG+HxMbnyHEIIIYQQ4v0hyacQ7yiVgSE2TQZT+ufrFGw2BJ5LFKPPbcZ/XCVCt08jRZOQ49i2ZpZMrdcZr85f0KhYOaU9WZvCiusnabhpFsuvnSQpJTlXnkUIIYQQQuR/knwK8Y4ztCqEY98FlJx0BrOydZV2bWIcoZu/495EN2J89rxU7Aq2RVjbagDLmvfF2bqQ0v40MY6Jp7bRbsd8zgT7v+ojCCGEEEKI94Akn0LkE2bO1Skx4RiOA5ZiaG2vtGuCbxP4awcCf++CJuRujuOqVCpalazEga6jmFCzLVbGpkrf1bCHdNv9JyOOrOdRbGSuPIcQQgghhMifJPkUIh9RGRhQsNEnOM+4jk3LEfDcGZ4xF3fgP74yoVunkJIYl+PYpoZGfF7Fg6PdvuajctX1+rbc8cZj0yw5mkUIIYR4D0gF/Ncnv73XKm1+e6L3QLdu3fD19cXV1ZXNmze/6eGIt1jCfR8erxpJ3M1jeu3G9qWx7zUHK/eOLx37XPA9Jp7axpUw/TNGyxW0Z0qdTjQuXv6lYwshxLvq9OnT9O3bN90+Q0NDzM3NKVasGHXr1qV///4UK1Ysw1i+vr5s2bKFM2fO8OjRI2JjY3FwcMDd3R1PT09q16790uM8cOAA27dvx9vbm7CwMExNTXF0dKROnTr06NEDtVqdZQwvLy9GjBgBwMSJE+nTp0+G12b2vryoQoUKbNu2jbFjx7Jly5bsPdD/mz59Ot26dcvWtdeuXcPT05Np06bRoUMHpT0wMJAlS5Zw/PhxHj16hImJCeXKlaNr1654enpiYPDsg93MnsvCwoLChQtTp04dBgwYQOnSpfX64+LiaN++PfXr1+enn37K0XO+Dn369OHMmTMsWLCAFi1aAKmJ0LZt2zh27BizZ89WrtW9D7rfu9fFxcUFgLNnz1KgQIHXdt/M5NaYHj58yC+//ELPnj1f6c/628boTQ9ACJF3TEu44TTuEFEn1xKyYQzJEQ8B0ITcJej3LlhWbYf9x79h4lA2x7FrOpZiV8fhrLt5lhkX9hKREAvA7ach9PJaSttSrkyq3QEnK9tcfSYhhHgXWFhY0Lx5c722lJQUYmJi8Pb2ZuXKlWzbto3ly5dTqVIlvetiY2P56aef2LRpEwAlS5bEzc0NIyMj7ty5w86dO9m5cyd9+/ZlwoQJORqXRqNh1KhR7Nu3DxMTE6pWrUr16tWJjIzk7t27rFmzhnXr1vHVV18xaNCgTGNt2LABQ0NDVCoVa9euzTT5zOx9eVHx4sUBcHd3JylJfzVNaGgoJ06cyDBOyZIlsxwDQHx8PF9++SXVqlXTSzx9fHzo378/0dHRFC1alEaNGhEVFYW3tzeXLl3iyJEjzJ8/HyMj/R+hXxyPVqslLi4OPz8/Nm7cyPbt21m6dCm1atVSrjE3N2fChAkMHTqURo0a0bp162yN/U06dOgQY8aMyVfJ0Ntq2LBh+Pr60qNHjzc9lFwlyacQ+ZxKpaJA/Y+xdO9I2NYphO+bC/9fpTbm0m5ifQ9g2+4b7NqPwcDUIkexDQ0M6F2hDu2dK/PLBS9W3ziDltTFFHvu+XLwwQ2GuzVhSGUPzI2Mc/3ZhBDibWVra8usWbPS7YuNjeWzzz7jzJkzTJw4UW8VU1JSEgMHDuT8+fOUK1eO77//njp16ui9/siRI4wePZqVK1diZGTEmDFjsj2uxYsXs2/fPtzd3Vm4cCF2ds+O69JqtezYsYNx48Yxa9YsKlasSMOGDdONExQUxH///UflypUpUKAAx48f5+TJk9SrVy/T+2f2vrzI09MTT09PvbbTp09z4sSJHMVJz4IFC7h37x6//fab0paSksI333xDdHQ0/fv35+uvv1aSzDt37jBw4EAOHTrEypUr+fTTT7P9XEuXLuWXX35h7NixeHl5YWhoqPQ1b96cOnXqMGXKFOrXr4+1tfVLP1Nu+/nnn4mLi6NIkSJKW0pKSrrXurm5sXv3bkxNTdPtf5/s3r0bACsrq1eKk5ycP08UkD2fQrwnDM0LYN9zFqV+vIh5hSZKuzYpgbDtP+E/oQrRF7a91N4CWzNLptfvyu6Ow6npUEppT0hOYvbF/TTfMgevgKv5bt+CEEK8DAsLC2XG0tfXl/v37yt9CxYs4Pz58zg7O7N69eo0iSeAh4cH8+bNA2DFihXcu3cv2/fWJbqTJk3SSzwh9cPKTp060a9fPwDWrl2bYZxNmzaRkpJC48aNad++PQCrV6/O9jjepKCgIJYvX46HhwcVK1ZU2s+ePYu/vz/Ozs588803erObZcqU4ZtvvgFg+/btObrfp59+iqOjIw8ePMDX1zdN/5AhQ3jy5AlLlix5ySfKG8WKFaNs2bJYWlpmea25uTlly5bFycnpNYzs7Va2bFnKli2rtzxbPCPvihDvGdPirjiN2U+RIWswtHm21yjpiT9Bc7sROKcDicG3Xyp2lcLF2dJuCL816o69+bNP/AKiw/j0wEr67Psfd56GvPIzCCHeD9rkJFISYtCEB5Lw4Aqa8EBSEmLQ5oPCZqVKPfug7smTJwAkJiYqCdxXX32FrW3G2xbq1atH69atadKkCY8ePcr2fUNDQ4HURDMjnTp1omPHjlStWjXd/pSUFCWJbdeuHa1bt8bCwoJDhw7x8OHDbI/lTVm2bBmJiYlpljNGR0fj5uaGh4eH3uykTpkyZQB4/Phxju6nUqmU2cOYmJg0/fXq1aNUqVKsXr2a6OjoHMVOT1xcHEuWLKFr1664u7tTt25devXqxZ49e/Q+BJ43bx4uLi5s2bKFn3/+mZo1a+Lu7s7nn38OpO75dHFxYf/+/cqvhw0bBsCZM2dwcXFRllqfPn0aFxcXOnfunGY8QUFBTJs2jVatWuHm5kaTJk0YNmwYPj4+aa4NCwtjzpw5dOvWjZo1a+Lq6kq9evUYNGgQR48efaX3Rfe8Gzdu5Pjx43h6elK1alUaNGjAiBEj0v1gAFL/XC5fvpwPPvgAd3d3qlatSseOHVmwYEG6v58uLi64uLgQGfnsFIBmzZpRqVIlkpKSWLZsGR06dMDNzY06deowcuRIrl+/rlyrey91bX379sXFxYXTp0+/0vO/LST5FOI9pFKpKFC3B6WnX8W27ddg+OzT3Viff7k3oQpPNn1Hyv/v48xp7A/LVedot68Z7NoQo+cq7h4OvEnzrb8x/dy/xGgScuVZhBD5U0pCDFFn/+H+1MbcHVWSexOrcndUSe5PbUzU2X9ISUj7Q9+75ObNm8rXuqJDR44cITIyMlv7IgHmzp3LwoUL050dzYhupm/cuHFcunQp3WsqVKjArFmz+Oyzz9LtP3bsGEFBQVSrVk2ZGWvTpg3JycmsX78+22N5EzQaDVu3bsXCwoIGDRro9TVv3pyNGzcyfvz4dF+rS5aeX4aaHTExMdy5cwczM7M0+3sh9d/N5s2bExMToyzZfFlPnjyhe/fuzJo1i8DAQOrWrYurqys+Pj58+eWXzJw5M81rFi1axKpVq6hRowYuLi5pCiPp1K9fX9nrWahQITp27Ej9+vUzHc/58+fp2rUrK1asIDk5mSZNmuDg4MD+/fvp0aMHBw8eVK4NCAigc+fO/Pnnn0RERFCrVi0aNWqEqakpR48eZdCgQezatesV3p1UBw4cYNCgQTx8+BAPDw/s7e3x8vKiR48eHDp0SO/aqKgoevXqxfTp07lz5w61atWiQYMGPH78mLlz5/Lhhx8SHByc7Xt/+eWX/PLLL1hYWODh4YGxsTF79+6lZ8+e3LlzB4DChQvTsWNHChYsCKS+7x07dqRw4cKv/OxvA0k+hXiPGZhbY+/5M6V+9Ma8YjOlXZuUSNiOafiPdyXq3OaXWi5rbWLG97U74NXlCxoWLae0a1KSWXD5MB6bZ7Pjro8sxRVCpJGSEEPI+m949OfHJAR46/UlBHjz6M+PCfn723c2AQ0LC2PKlClA6qyXo6MjAH5+fgBUrlw5TUGb3DJ69GhMTEy4evUq3bt3p2nTpowdO5aNGzdy9272zoL+559/APjwww+VNt3ezI0bN5KYmJj7A88l3t7eREVFUb16dUxMTLL9utjYWBYuXAhA27Zts7xeq9USGxuLt7c3n3/+OVFRUQwbNkxJKF5Ut25dIDWxfxVTpkzh5s2beHh4cPDgQf744w+WLl3Kli1bsLGxYenSpWlmHO/evcsff/zBokWLWL9+PV9//XW6sT///HNlSXbZsmWZNWuWMkuantjYWL755hsiIiIYPnw4+/btY+7cuWzYsIFZs2aRkpLCmDFjlO+XmTNn8vjxY3r27MmBAwf4448/+PPPP9m/fz+9evUCYPny5a/0/kBq0aR27dqxf/9+5s6dy9atW5k4cSKJiYmMHz+eqKgo5dpJkyZx+fJl3N3dOXDgAIsXL2bhwoUcPHiQli1bcufOHUaNGpWt+yYnJ3PmzBnWrl3Lhg0bmDdvnrL/OjY2lhUrVgDP3tuiRYsCqcuyZ82aRdmyOS8O+TaSgkNCCEyLVcTpWy+iz24kZN3XJIUHApAUGsDD+R9hUbkVDr3nYlIk58enqG0cWdd6ALvuXWHKmZ0ExTwF4FFsJJ8fXsu6YuX5qW4nyhS0z9VnEkK8m7TJSURf3MHTQ4syve7pwT8xd2mMdc0PUBm+fT/OhIeHp/khPjk5mZCQEC5dukRiYiJFihTRO2JDN4Nib593fx/WrFmTNWvWMHnyZHx9fQkKCmLLli3KkSbFihWjQ4cODBo0KN1jIp48ecKhQ4ewsLCgXbt2Snu1atVQq9XcvHmTPXv2pLv8ElKPMdEdRZGerl27MmPGjFd8yoydOnUKQG+vZ1YSExMZNWoUQUFBODs707t37zTXZPVcn376KYMHD86wv0KFCnrjexmPHz/Gy8sLCwsLZs6cqVfwpnz58gwaNIht27Zx584d3NzclL6yZcvSqFEj5de5tVfx0KFDBAYG4u7urhzJo9OxY0e8vLx49OgRfn5+VKxYEUdHRxo2bMioUaP0loUbGRnh6enJ2rVrCQwMfOVxOTo6Mm3aNL0PH/r06cORI0c4duwYu3fvxtPTk4cPH7J7925MTEz4/fff9fZIW1paMnPmTFq0aMH58+c5d+4cNWvWzPLen3zyCdWrPzsr3dzcnB49enDx4kVu3br1ys/2Lnj7/rYWQrwRKpUK69rdsXRrR+j2qYTvnQPJGgBir3hxb6Ibtm2/xq7DuBxXxVWpVHRwrkJzJxfm+xzmzytHSfj/PVtHg27RYutvfF7Fg+FuTaUqrhDvOW1SAuG7f8nWteG7Z2JVrcNbmXzGxsayY8cOvTYjIyOsrKxwdXWlUaNGfPzxx9jY2Oj1A2mOF8ltbm5ubN68mWvXrnHkyBHOnj3LxYsXiYmJISgoiMWLF7Np0yaWLVumJEU6W7ZsQaPR0Llz5zSFaD766COmTp3K2rVrM0w+s1pS7O7u/uoPmImgoNSzqbNbGCc2NpYvvviCo0ePYmNjw8KFCzE3N09zXXrPFRcXx8OHD7l+/TrLli3j8ePHTJ8+Pd0ZV0dHR0xNTYmMjCQ6OvqlKqWeOXMGrVZLrVq10p1hHThwIAMHDkzTnpNEPCd0exR1Z4S+SFc0S2fixIlpromKiuLWrVvKjLBGo3nlcbVq1SrdqrytWrXi2LFjnDhxAk9PT+X9rF27trI64Xnm5uY0b96cv//+m1OnTmUr+Uzv+9vBwQFI/X55H7x9f1sLId4oAzMr7LtPp2DDfjxe8wWxvqmFBnRLcSNPrMa+169YVe+SacGK9JgbmfBN9VZ8VK4GE09t43Bg6p6nxJRkfr90kC1+3vxYtxPNS1TIIpIQIr9Kjo0gISD9vYgvSrh3keTYCAxMs67G+boVL15cbz9bduhmPHVFgXLKy8sLLy+vNO21atVKc2QJpCYdFStWZMiQISQnJ+Pr64uXlxdr164lNDSUYcOG8e+//2Js/OxDQd2S20uXLvHJJ5/oxYuNTa0T4O3tja+vL66urmnu+apHpLwq3Xub3qzuix49esTQoUPx9fXF3t6epUuXZrj0MbPn8vf3Z9CgQezcuRNbW9t0kywAa2trEhISCA0NfankU1cISbdcM7syK2z1KnTj0e1pzo47d+6wbt06Ll26xL1794iIiACeFcjKja06zs7O6bbr3jfdCgTd+DP7oKJEiRJ612YlvQ8FdMWtMjrGJr+R5FMIkS6TYhUo/vW/RJ/bRMi60SSFPQD+fynuvA+xcGuDw8e/Y+JYLotIaTkXKMSqlv3Zc8+XSad38DA2dSluQHQY/fYvp01JV36o05HiVja5+UhCiHdASkx4zq6PjQDb4nkzmNesSpUqAFy9epXExMQs9ySeOHGCq1evUq9ePVxdXblx40aa2VZ4tmwxODiYBw8e4ODgoPzQrGNoaIibmxtubm507tyZDz74gAcPHnD+/HllP+KZM2fw9/cH4NatW5kuE1yzZg3Tpk3LyeO/FrpZ5azOUPTx8WHo0KGEhIRQtmxZFi9e/NLHiDg7O/P1118zcuRIpaBRektbdWN62Zlv3ety+sFwTq/PrpzOUq5cuZJp06ah1WopXrw4derUoXTp0lSsWJFixYrx0Ucf5cq4MlpWrEtsdSsQspPo6hLG7O4fzqv3+l0iBYeEEBlSqVRY1/oQ52m+2Lb7Nv2quJsnvXRV3HbOlTnc7SuGVG6sVxX33wBfmmyZzcLLR0jMB0cqCCGyz8AyZ7MwBhY2eTOQN6BWrVrY2NgQGxvL4cOHs7x+8eLFzJw5k6VLlwIwYsQIbty4keY/3R7KVatW0atXLxYvXpxp3PLlyyv70nQzTwAbNmwAYOjQoene58aNG/z1118A7Nq1S++1bwvdMuewsLAMrzl06BB9+vQhJCSE+vXrs379+lc+v7JcudQPauPj49O9d3JyMk+fPtUbY07pZs4zOnrn8ePH/P3331y4cOGl4ueUbjlpRuPx8fFh69at3L17l8DAQGbMmIGhoSHz5s3j4MGDzJ07l1GjRtGmTZt0j755WRlVp33wIPVDdt1MrW78uvb0BAQEAOSbSrSvgySfQogs6ZbilvrRG4tKz/a0aJMSCdv+E/4TqhB9cftLLYexNDZlYq12/Nt5JLUdnZX2uCQN087toc32uZx8dCc3HkMI8Q4wtLDBtGS1bF1rWsodw3yUfBoZGTFgwAAgtfJnZmc+7t+/XylOoztrMSu6PWm7d+/OdJlgUlKS8kO1Wq0G4OnTp8qS3k6dOmX42gYNGlC0aFHi4+PZtGlTtsb1OumOEckoATl58iQjRowgPj6eDz74gCVLlmRriW5WdJWEzc3N000unzx5QkpKCgUKFKBQoUIvdY8aNWoAqTPU6X3v7Nmzh++//541a9a8VPyc0n2A8eLxJTqLFi1izJgxnD17lkuXLpGcnEyFChVo1apVmmt1Z3zmxtLUw4cPp/vzyt69ewFo3LgxkPphkEql4syZM+n+eYmNjVWW1utWB+Sm/DpLKsmnECLbTItVpPg3eyk6dB2GNs/2cCQ98Sfo964E/daJxMd+LxW7gm0RNrX9jDkNP6KQ2bP9WzcjHvPRnsV8cfRvQuKiMokghMgPVEam2Lb7JlvX2rb7BpVR2sIh77L+/fvj6upKQEAAnp6eeHt76/VrtVp2797NN998g1arpVevXtku0uPh4YG7uzvR0dH06dMn3UPrw8LCGDNmDIGBgbRo0YIyZcoAsH37dhISEqhSpUqG50BC6pLGrl27ArBu3bq3bh+bLiFKb/YvLCyMr776Co1GQ7du3Zg2bVquHHnz6NEjZs+eDUCHDh3SjXn+/HngWQKp4+fnh5+fX7aK0ZQsWZImTZoQExPD+PHjiY+P14ujOyqme/fuL/0sZmZmAMosbWbat29P4cKFOXPmjDI7r7N7924OHDhAgQIFaNOmjbLv1M/PL82RP7t37+aPP/4AyJVjfK5fv87cuXP1EtAlS5Zw6tQpSpYsqRRIKl68OG3atCExMZEvv/xSb8Y6JiaGb7/9lrCwMKpWrUq1atVeeVwv0r3XkZGRuR77TZI9n0KIHFGq4lZpS+j2nwj3+g3+f2lszKXdxPoewLb9t9i1H4OBSdqKgFnF/qh8DVqUrMgv5/ey+sYZtKT+47DJ7yL77l/j2+qt6eNSB8NcKgUvhHi7qAyNsHLvSMGmn2V63ErBZkPe2kq3r8LY2Jjly5czcuRITp48iaenJ87OzpQpUwYDAwN8fX15+PAhAB9//DETJkzIdmyVSsWff/7J559/zoULF+jbty/FihVDrVZjbm5OcHAwly9fRqPRULt2bX7++WfltRs3bgQyn/XU6datG3/88Qf379/n2LFjeHh45PBdyDu6SrBXrlwhNjYWC4tn1dtXrFihJBgxMTEZnndpYWGhnNOqk97ROikpKYSEhODt7U1iYiLlypVj9OjR6cY8c+YMAC1bttRr1x1ns3LlSurUqZPl8/3444/06dOHvXv3cu7cOWrUqEFkZCTnz59Ho9EwYMCAbMXJiLOzMyqVihs3btCvXz9cXFwYP358utdaWFgwZ84chgwZwi+//MI///xD+fLlCQwM5MqVKxgbGzN9+nQKFChA7dq1qVKlCpcvX6Zz587UqlULc3Nzbty4QUBAAMWLFyc8PJzY2FgiIiJeemkypBYWWrhwIXv27MHFxQU/Pz9u3bqFra0ts2fPVpI+gB9++IGAgADOnz9P8+bNqV27NkZGRpw7d46IiAjKlCnDnDlzXnosmSldujQXL17khx9+YMeOHfTv3z/Pq0G/Dvnrb2whxGtjYG6NvefPFGjYj8erRxJ3LXVZjTYpgbBtPxJ1YjX2veZg5d4xx7FtTS2YXr8rnuVrMv7kVnxCU8/1ikyMZ+KpbWy4dY5p9bpQzb5EFpGEEO8iA1NL7HvMxLyCB+G7fiEhwFvpMy1ZDdv232JVrcNbWeU2NxQoUIBly5bx77//snv3bnx9fZWjJhwdHenSpQs9evR4qR9EbWxsWLt2LXv37mXfvn34+Phw7tw5EhISsLOzo3HjxnTo0IG2bdsqy/58fHy4ceMGRkZGtG/fPst7lChRgjp16nDq1ClWr179ViWfJiYmdO3aleXLl7N//369ZPr55aG6JZjpsba2TpN8pne0jrGxMQUKFKBatWo0b94cT0/PdI9p0Wg07N+/n4IFC9KmTZuXfTQgdZ+i7picvXv3cuTIEQwNDalatSp9+vR55fhOTk5MnjyZxYsXc/78eQIDAxk3blyG19euXZutW7eyaNEi/vvvPw4ePIilpSWtWrViyJAhSkVkQ0NDli9fzuLFi/Hy8uLs2bMYGhpSokQJhg8fTv/+/fn22285cOAAXl5erzR727JlS2rWrMmiRYs4dOgQdnZ29OjRg88++yxNZd6CBQuybt061qxZw86dOzl9+jQGBgaUKlWKAQMG0Lt3b70PMHLTqFGjePLkCefOnePYsWPUq1cvXySfKm1u1CwWr1W3bt2UEuabN29+08MRAq1WS9TpvwlZ/zXJEQ/1+iyrdcDh498wts94mVZmklNSWH3jND9f2Etk4rMlRCpU9HapzZgarbHJ4bmjQoh3gzY5CW1SAsmxEaTERmBgYYOhhQ0qI9N8N+MpXp8nT57QsmVLXFxcWL9+/ZseDrt372bUqFGMHj2awYMHp+mvXr06K1asUKohi5czb9485s+fT9++fXO0YkDkLlm3JoR4ZSqVigJ1e1B6+jVs23ylVxU3xnsn/uMrE7p9KimahBzHNjQwoF/FehzpNpoPyj77xE+LllU3TtNk869sveOdK2d/CSHeLipDIwxMLTG2LY5pcVeMbYtjYGopiad4JYULF6Zv375cvHgRHx+fNz0cVq5cib29fbqFo86dO0dycnKm+2yFeJdI8imEyDUG5tbY95hJqSkXMHd5tsxKq4kndPP33JvoRszljJcyZcbe3JrfG3uyoc0gyhd0UNqfxEcz/Mh6enstwz/y5Q5mF0II8X4ZMmQIZcuWVc6VfFN27drFxYsXmTx5cpoluRqNhnHjxjF27FisrKze0AiFyF2SfAohcp1pcVecxh6gyOCVGBZwVNo1wbcJnN2OoPkfoQm9/1Kx6xcty97OIxlXow1mhsZK+5GgWzTfOof5PofkbFAhhBCZMjc359dff+Xq1ats27btjYwhLi6OmTNn0qNHD6XC6vOMjY3ZunUrPXv2fAOjEyJvyJ7Pd5Ds+RTvkuTYp4RumUTE/gWgfVZyX2VqSaHO32Hb6gtURiYvFTsgKozxJ7dyOPCmXruLjSMz6nel1nPnhgohhBBCiDdLZj6FEHnK0KIgDh//RsnJZzErV09p1ybE8GTDWO59X53Ya+kfQJ2VktZ2rGrZnz+a9MLB3FppvxERTNfdfzLmv81EJMS+8jMIIYQQQohXJ8mnEOK1MCtVjRLjj+I44C8MrQsr7YlB13jwcwse/vkxSS9Uys0OlUpFx9JuHOr6FX0r1EWFSulbc/MMTbf8yrY7l6QgkRBCCCHEGybJpxDitVEZGFCwUX+cp1+jYNPPQPUsUYw6tR7/sRUJ3/s72pfYs1nQ1Jxp9bqwtf0QXGye7TMNiYtm2JF19N73P+5FSUEiIYQQQog3JV/t+bx79y4LFizg/PnzhIaGUqRIEdq2bcvgwYOxtMzZQdTBwcEsXLiQEydO8OjRIwoXLkyzZs0YNmwYdnZ26b7mwYMHLFq0iOPHjxMSEoKVlRW1atVi6NChVKxYMTceEZA9nyL/iL9zluBVw0m4e06v3aSEG45952NevsFLxdWkJLP4yjHmeB8gPlmjtJsaGjGqWgs+q9wIYwPDVxq7EEIIIYTImXyTfPr4+NCvXz9iY2OpWrUqRYoU4cKFC4SEhKBWq1m7di3W1tZZBwICAgLo1auX8trSpUtz9epV7t+/j6OjI3///TdFixbVe825c+cYPHgwMTExlC1bljJlynD79m3u3r2Lqakpq1evxs3NLVeeVZJPkZ9oU5J5euQvnvwzgZSYcL2+Ao36Y999ht4y3Zy4FxXK+JPbOJJOQaKf63ejpmOplx63EEIIIYTImXyRfGo0Glq3bk1gYCAzZsyga9euAMTHxzNq1CgOHjxIz549mTx5crbi9ezZkwsXLjBixAiGDx8OQHJyMlOmTGH9+vU0btyYJUuWKNdHRUXRtm1bQkJCGDt2LP379wdAq9Uyf/585s+fT+nSpfn3339z5Xkl+RT5UVJkCE82jiPy2P/02g0s7Sj80TQKNh6AyiDnOwW0Wi3b7/ow+cwOQuKi9fr6uNRhbI02FDQ1z+DVQgghhBAit+SLPZ+7du0iMDCQBg0aKIkngJmZGdOmTcPCwoJ//vmHyMjILGOdPXuWCxcuUKZMGYYOHaq0GxoaMnHiRIoVK8bRo0e5ffu20vf3338TEhJC586dlcQTUguhDB8+HLVaTVJSEg8f5ryYihDvC6MC9hQZ8BclJhzDtERVpT0lJozHy4dw/6eGxN+7mOO4KpWKzmWqcrjraHq71NHrW3XjNE22zGa7FCQSQgghhMhz+SL5PHQo9ZiGVq1apemztbWlTp06aDQajh8/nu1YLVq0wOCFWRZjY2OaN28OwMGDB5X23bt3AzBo0KA08VQqFTt27GD//v1pluoKIdIyL1+fkpPPYN/zV1RmVkp7/J3TBEyuzeM1X5Ic+zTHcQuamjOjfle2tvs8TUGioUfW0f/ACoKiI3LjEYQQQgghRDryRfJ582bqfi4XF5d0+8uXLw/AjRs3XjlWuXLl9GJpNBpu3ryJlZUV5cuXJzg4mP/973989913TJs2jSNHjuTsYYQQqAyNsG39Bc7Tr2Jdu/uzDm0KEfvm4T+uEpGn1r3UbGVNx1Ls6TSCsTXaYGpopLTvv3+dZlvnsOLaSVK0KbnxGEIIIYQQ4jn5IvkMDg4GwNHRMd1+e3t7AB4/fpxrsUJCQgAIDAxEo9Hg4ODAtm3baNOmDTNmzGDDhg2sWLGCwYMHM2DAAKKjo9ONJ4TImLFtcYoOXUfxb/ZiXESttCc/fcSjP3vz4JdWJAZdz3FcE0Mjhrs14UCXUTQqVk5pj9YkMOHUNrrtXsStiKz/vhBCCCGEENlnlPUlb7+4uDggdY9nenTtsbGxuR4rKioKSE1ax40bR+vWrRk6dChFixbl0qVLTJkyhePHjzNu3DjmzZuX4X3Xr1/Phg0bshwfgJ+fX7auEyK/sHRtQakfvQnfM5uwHVPRauIBiLt2EP/vqmHX9mvsOo7HwNQiR3GdCxRibasBbLx9nh/O7OJpYuqf/3OP79F62++MqNqUYVWaYGKYL/6qFEIIIYR4o/LFT1SGhoakpGS9TC47S/QMDbN39p/ufgkJCQDExMTg4eHBnDlzlGsaNGjA0qVLad++PV5eXly9epVKlSqlGy8kJARfX99s3VuI95GBsSmFOo2nQL2ePF49kphLqXutSdYQtnM6kSfX4tD7d6zcO+Yorkqlonv5mjR1cmHS6R1sv+sDQGJKMrMv7mfn3cv80uADajiUzO1HEkIIIYR4r+SL5NPS0pKIiAglEXxRfHzqLImFRdazIpaWlgBZxtJd93zMfv36pbneyckJDw8P9u7dy8mTJzNMPu3t7XF1dc1yfJA686kbhxDvG2P70hT7cjsxF7fzeM2XJIUGAJAUeo+g37tg6d4Jh96/Y1woZ8mivbk1C5v0omuZaow/uY2H/1/U6EZEMF12/UH/ivX4tkZrrIxNc/2ZhBBCCCHeB/ki+XRwcCAiIoKQkJB0K8rq9no6ODhkK5avr2+G+0NfjFWoUCGlz8nJKd3X6NrDwsIyvG+PHj3o0aNHluODZ+d8CvG+UqlUWFXvjIVrC0K3TyX839mQnARAzMXt+Pvup1CX77Ft9SUqI+McxW5ZshJ1i5Rhxvm9rLh+EgAtWpZdO8HegKtMr9+VZk7pFyQTQgghhBAZyxcFh3SVaW/dupVuv+5Mzowq2KYX6/lzPDOL5ejoiI2NDfCsWNGLnjx5AugnqkKIV2dgaon9R9MoNeUi5i4eSrs2MZYnG8Zyb1INYm8cy3FcaxMzptbrzJZ2QyhX0F5pD4yJoO++/zH8yHpC46WImBBCCCFETuSL5LNJkyYAeHl5pekLDw/n9OnTmJqaUq9evWzH2rdvX5o9ohqNhgMHDuhd9/zX27dvTxMvPj6e06dPA1C7du0s7y+EyDnT4pVwGnuAIoOWY2j9LFlMDPTlwfQmPPrrU5IiQ3Ict5ajM3s7f8GX1ZpjbPBsP/jWO9402fwrm/wuvtRxL0IIIYQQ76N8kXy2aNGC4sWLc/jwYdavX6+0x8fHM2HCBGJjY+nevTt2dnZKn0ajwc/PDz8/PzQajdLu7u6Om5sbN2/e5LffflN+sExOTmbq1Kk8fPiQpk2bolY/O/ahf//+GBsbs2nTJrZu3aq0JyYmMmXKFB49ekStWrWoXLlyHr4LQrzfVCoVBRr0wXnGNQo2GQwqldIXeXwF/uMq8fTIX2izUZzseaaGRnzt3pI9nUbgbl9CaQ9PiOWLo3/Te9//uB+V8ZJ6IYQQQgiRSqXNJx/bnz17loEDBxIfH4+rqytOTk5cvHiRx48fU7lyZVauXKkUCQJ48OABzZs3B+DAgQN6+zX9/Pz4+OOPCQ8Pp0yZMpQvX55r164REBCAk5MT69atS7N/dNOmTXz33XckJyejVqspUaIEvr6+PHr0iOLFi7NixQpKlChBbtDt+XR1dWXz5s25ElOI/CbO7zSPVwwlIcBbr92sXD0c+y3EtIRbjmMmp6Sw4vpJZpzfS2xSotJubmTMmOqt6V+xPoYG+eIzPSGEEEKIXJdvkk+AmzdvMn/+fM6cOUNsbCxOTk60bduW/v37Y2VlpXdtZsknQGBgIPPnz+fYsWM8ffqUokWL4uHhwZAhQzLcu+nr68uSJUs4e/YsT58+pUiRIrRs2ZJBgwbpzbq+Kkk+hcgebXISEfsX8GTL92if36NpYIhtqy8o1GUSBmZWGQfIwIPocMad2MqhwBt67TXsSzK74YeUs8m6uJkQQgghxPsmXyWf7wtJPoXIGU14ICFrvyL67D967UZ2Ttj3moNVja6onlummx1arZatdy4x6fQOwhJilHZTQyNGVWvBkMqNMDLI3rnBQgghhBDvA1kfJoTI94xti1Ns2N8U/2oXxg5llfaksAc8nP8RQXM6ogm5m6OYKpWKrmWrcbjbV3QpU01pT0hOYsb5f+m0cyFXwx7m1iMIIYQQQrzzJPkUQrw3LN3aUOqnS9h1mojKyERpj/HZg/+EKoTt/Bntc3s5s8POzJL5Hj34X/O+OFoUUNp9QgNpt30esy/uI/H/zyAVQgghhHifSfIphHivGJiYU7jbD5T60RuLSs2Vdm1iHE/+Gc+9STWJu3k8x3FblqzEwS6j6FG+ptKWpE1hjvcB2u2Yz6UnD3Jl/EIIIYQQ7ypJPoUQ7yWToi4U/2YvRT5bhWEBR6U9MdCX+9M8eLRsEMnRoTmKWdDUnFkNP2RNq08pbmmjtF8Pf0THnQuYdm4P8UmajAMIIYQQQuRjknwKId5bKpWKAvV64Tzdl4JNP9M/G/TostSzQY+vIKd12TyKqznQdRT9KtRV2lK0WhZePkLr7XM5F3wv155BCCGEEOJdIcmnEOK9Z2hpi2O/hZSYcBzTElWV9uSoJwT/9SkPZjQnMeh6jmJaGZsytV4XNrYdTCnrZ8cz+T0NoevuP5l8egexmpztLxVCCCGEeJdJ8imEEP/PvFxdSk4+Q2HPmahMLZX2uBtH8P+uGk82fU9KYlyOYtYrUob9Xb5gsGtDVKTOrGrR8tfV/2i57Tf+e+iXq88ghBBCCPG2kuRTCCGeozI0wq7tVzhPu4Kle6dnHckawnZM5d7EqsRc8cpRTHMjE76v3YGt7YdQrqC90n4vKgzPf5cw7sQWohLjc+sRhBBCCCHeSpJ8CiFEOowLlaT4F1soNnIzRnYllHbNYz8CZ7Xl4cKeJEXk7BzPGg6l+LfTSEa4NcVQ9eyv31U3TtN86xwOPbiRa+MXQgghhHjbSPIphBCZsKreGedpV7Bt8xUYGCrtUWc24D+uEhEH/kCbkpzteGZGxoyp0ZodHYZS0baI0h4U85Q++/7H6OP/ECmzoEIIIYTIhyT5FEKILBiYWWHfYyalJp/FrEwdpT0lLpLHq4Zz/6dGJNz3yVFMt8JO7Oo4nNHuLTB+Lqn9+9Y5mm+Zw5HAm7k2fiGEEEKIt4Ekn0IIkU2mJatSYuJxHPouwMC8oNIef+c09ybVJGTDWFISYrIdz8TQiFHVWrC74wjcChVX2h/GPuVjr2V8+99m2QsqhBBCiHxDkk8hhMgBlYEBNs2G4Dz9KtZ1ezzrSEkmfPdM/Ce4EeOzJ0cxK9oVYVuHoXxbvZXeLOjam2dosfU3jgfdzq3hCyGEEEK8MZJ8CiHESzCyKULRIWsoPno3xvallfakJ/4E/tqBoIU9clSQyNjAkJFVm7Gr43Aq2xVT2gNjIuix9y/Gn9xKjCYhV59BCCGEEOJ1kuRTCCFegWWV1pT6yQe7DmPB0Ehpjz6zMbUg0cE/0KakZDteJbui7Og4jNHuLTB6riLuyuunaLFVzgUVQgghxLtLkk8hhHhFBqYWFP5wKqV+OI9ZufpKe0pcJI9XDuf+1JwVJDI2MGRUtRbs6jhcryLu/ehwPP9dwsRT24jVJObqMwghhBBC5DVJPoUQIpeYOlWmxPgjOHzyh35BIr9TL1WQyLVQMXZ1HM4XVZvpnQu6/NpJWm77jVOP7uTq+IUQQggh8pIkn0IIkYtUBgbYNBmcawWJTAyN+KZ6K3Z0GIqLjaPSfi8qjI/2LGHS6R3EJcksqBBCCCHefpJ8CiFEHsheQaJH2Y7nVtiJ3Z1GMMKtKQYqFQBatCy9+h+tts3lbLB/bj+CEEIIIUSukuRTCCHyUJYFiQ4vznZBIlNDI8bUaM229kMpX9BBab8b+YRuuxfx45ldxCVpcv0ZhBBCCCFygySfQgiRxzIuSPSUx8s/58GMpiQEXct2PHf7EuzpNILPK3vozYIu8j1Gm+1zOf84INefQQghhBDiVUnyKYQQr4lSkKjvAgzMCyjtcTePc+87d55smUxKYny2YpkZGTOhVlu2tPucsgXtlXa/pyF03f0Hv5zfS2JyUq4/gxBCCCHEy5LkUwghXiOVgQE2zYbgPM0Xq5ofPOtI1hC27UfufV+d2OtHsh2vhkNJ/u00ks9cG6EidRY0Ratlrs8hOu5cwLWw7O8rFUIIIYTIS5J8CiHEG2BkW4xiwzdQ7IutGNmVUNo1j27wYEYzHi0bRHJ0WLZimRsZ813t9mxq9xmlrO2Udt+wh7TfMY+Fl4+QnM19pUIIIYQQeUWSTyGEeIOs3DviPPUyNi1HwnNneUYeXYb/eFciT61Dq9VmK1ZtR2e8On9BH5c6SltiSjLTzu3hwz2L8I8MzfXxCyGEEEJklySfQgjxhhmYW+Pw8RxKfncC0xJVlfbkyMc8+rM3gb+2RxNyN1uxLI1NmV6/K6ta9sfR4tm+0rOP79Fq2++sun4q28msEEIIIURukuRTCCHeEmZlalFy8hkKe/6CysRcaY+9vBf/CVUI2zMbbTaLCDV1cmF/ly/pXOZZMhublMi4k1vps+9/PIx5muvjF0IIIYTIjCSfQgjxFlEZGmHXdjTOUy9jUaW10q5NjOPJ398S8EMd4v3PZyuWrakFCzx68meTXtiaWijthwNv0mLrHLbe8ZZZUCGEEEK8NpJ8CiHEW8jYvjTFv9pFkSGrMbR+dpRKQoA3AT/UJWT9N6QkxGQrVofSbhzoMooWJSoobU8T4xl+ZD2fH15LWHz24gghhBBCvApJPoUQ4i2lUqkoULcnztOvUqDxp886tCmE//sr9yZWJeaKV7ZiOVhY87/m/ZjZ4AMsjUyU9p3+l2mx9TcO3L+e28MXQgghhNAjyacQQrzlDK3sKPLpEpzGHMDYsbzSrgm5S+Cstjxc1JfkqCdZxlGpVPRU12Jfly+pW6S00v44Lop++5fz9fF/iEqMz5NnEEIIIYSQ5FMIId4RFhWbUOrHi9h1GAeGRkp71Mk13B1XicgTq7O1h7OktR0b2gxiUu32mD4XZ/2tc7Ta9jsnH93Jk/ELIYQQ4v0myacQQrxDDEzMKfzhT5SafBbT0rWU9pToUB4t7kfg7HbZOpbFQGXAINdG7Ok0ArdCxZX2+9HhdN+zhClndhKfpMmTZxBCCCHE+0mSTyGEeAeZlnCj5Hf/Yd9rDipTS6U99ooX/hPcCP93TraOZVHbOLKtw1C+qtYCQ1XqPwlatCz2PU77HfO5GvYwz55BCCGEEO8XST6FEOIdpTIwxLbVSJynXsbSra3Srk2MJWT91wT8WJ/4e95ZxjE2MOQr9xZs7zCU8gUdlPYbEcF02DGfPy4fITklJS8eQQghhBDvEUk+hRDiHWdcuBTFRu1IeyyL/3kCfqhNyIaxpCTEZhmnamEndncawacV6yttiSnJTD23B8+9S3gQHZ4n4xdCCCHE+0GSTyGEyAeeHcviS4GG/Z51pCQTvnsm976rRuzVg1nGMTcyZkrdTqxtNQBHiwJK+6lHd2m59Tc2+V3MVlEjIYQQQogXSfIphBD5iKFVIYoMXIbTt14YO5RV2jWP/XjwS0seLRtEckzWM5iNi5dnf5cv6ejsprRFaRL44ujffH54LeHZmEkVQgghhHieJJ9CCJEPWVRqTqkfvbFt9y0YGCrtkUeX4T++MlFnN2UZw9bUgoVNevJ7Y0+sjU2V9p3+l2mx9TeOBt7Kk7ELIYQQIn+S5FMIIfIpA1ML7LtPp+Sk05iWclfak58+4uGC7gTN+4Ck8KBMY6hUKj4o686+Ll9St0hppT04NpJeXkv5/tR24uRIFiGEEEJkgySfQgiRz5mVcqfk96co/NF0VMZmSnv0+a34j6/M0yN/ZbmP08nKlr9bD2JizXaYPDeTuuzaCdrvmMeV0MA8G78QQggh8geVNh9Vjrh79y4LFizg/PnzhIaGUqRIEdq2bcvgwYOxtLTMOsBzgoODWbhwISdOnODRo0cULlyYZs2aMWzYMOzs7NJcv2nTJsaPH59hvPLly7Nz584cP1N6unXrhq+vL66urmzevDlXYgoh3g+Jj24RvHwIcdcP67WbV2yK4yd/YuJYLssYV8MeMuLIem5EBCttxgaGjHZvweeVPTA0kM81hRBCCJFWvkk+fXx86NevH7GxsVStWpUiRYpw4cIFQkJCUKvVrF27Fmtr62zFCggIoFevXsprS5cuzdWrV7l//z6Ojo78/fffFC1aVO81U6ZMYc2aNdSpUwcHB4c0MYsWLcro0aNz5Vkl+RRCvAptSgpPjy7lyd/fkhIXqbSrjM0o1HUytq1HoTI0yjRGfJKGXy7sZbHvcb322o7O/NaoOyWt035IJ4QQQoj3W75IPjUaDa1btyYwMJAZM2bQtWtXAOLj4xk1ahQHDx6kZ8+eTJ48OVvxevbsyYULFxgxYgTDhw8HIDk5mSlTprB+/XoaN27MkiVL9F7j6emJt7c3e/bsoUyZMrn6fC+S5FMIkRuSwoMIXjWcmAvb9NpNS1XH8dMlmJWqlmWM/4Ju8+WxjTyMfaq0WRmbMqVORz4qVwOVSpXbwxZCCCHEOypfrI3atWsXgYGBNGjQQEk8AczMzJg2bRoWFhb8888/REZGZhIl1dmzZ7lw4QJlypRh6NChSruhoSETJ06kWLFiHD16lNu3byt9ycnJ3LhxAysrK0qXLp1eWCGEeOsY2Raj2IhNFB32N4YFHJX2hHsXCPihNiEbx5OSGJdpjAbFyrGvyxd0LlNVaYvWJPDV8X8YfGg14fExeTZ+IYQQQrxb8kXyeejQIQBatWqVps/W1pY6deqg0Wg4fvx4mv6MYrVo0QKDF/YtGRsb07x5cwAOHnx2WLufnx9xcXFUqlRJPuUXQrxTVCoV1rU+xHnaFQo0+uRZR0oy4bt+5t537sTeOJppDBtTCxZ49GS+Rw8KmjwraLTnni8ttv3O8aDbmbxaCCGEEO+LfJF83rx5EwAXF5d0+8uXLw/AjRs3XjlWuXLl0sS6evUqAI6Ojvz888+0adMGNzc3PDw8mDx5Mo8fP87mkwghxJthaGVHkQFLKf7NXoztn63g0ATf4sH0pgSvHE5yXOarR7qUqca+zl/SoGhZpS04NpIee//ix7O7SUhOyrPxCyGEEOLtl3lFiXdEcHBqxUVHR8d0++3t7QGylQRmN1ZISIjSduXKFQB27NiBlZUVtWrVomjRovj6+rJu3Tr27dvHihUrlMQ1PevXr2fDhg1Zjg9SZ1qFECIvWLq2oNRPlwjdMpnwvb+BNgWApwf/IMZ7J46f/IGlW9sMX1/MyoZ1rQewxPc4M87vRZOSDMCiK0f5L+g28zx6UN4mbVE2IYQQQuR/+SL5jItL3ZNkZmaWbr+uPTY2Nk9i6WY+W7ZsyYwZM7CysgIgKiqKCRMmsHfvXr744gu2b9+OoaFh2qCkJrO+vr5Zjk8IIfKagakl9j1mYlX7I4KXDSLxQeoHbElh9wn8tQPW9Xvj0OtXDK0Kpf96lQGfVW5Mw6LlGH5kPbeepn7wdyUsiLbb5zGpdnt6u9SRbQpCCCHEeyZfJJ+GhoakpKRkeV12CvtmlBy+6Pn7LVu2jAcPHlCyZElMTEyUdmtra6ZNm8bFixe5ffs2x48fx8PDI9149vb2uLq6Zuvefn5+xMfHZ+taIYR4WeZlalNq8llCd0wnbOd0SNYAEHViNbFXvHDoPRerWh9mmES6FirG7k7D+ensblZcPwVAfLKGcSe3cvDBDWY1/IBCZlav7XmEEEII8Wbli+TT0tKSiIgIEhIS0u3XJWoWFhbZigVkGUt3HaTOhma0pNbKyoq6deuyfft2Ll++nGHy2aNHD3r06JHl+ODZUStCCJHXVEYmFO46Ceua3Xi0bBAJd88CkBz5mIcLe2BVowsOfeZjZFM03debG5kwtV4Xmjq5MPr4P4T+f/Xbffev0WLrb8xp1J0mxdWv7XmEEEII8ebki4JDDg6p+4ee34f5PN1eT9112YmV0f7QnMTSKVo09Ycy3ZJeIYR415iWqELJ7/6jsOdMVMbPtiVEn9+K//jKPD32v0xXl7QoUZF9nb/USzRD4qLp7bWMyad3EJ+kydPxCyGEEOLNyxfJp64y7a1bt9Lt153JmVEF2/RiPX+OZ2axQkJCmDhxIiNGjCApKf1Kjg8fPgSeJaFCCPEuUhkYYtf2K0r9dAlzl2erOFJiIwheOpDAWW3QhPhn+HoHC2tWtvyEH+p0xNTw2cKbv67+R4edC7ge/igvhy+EEEKINyxfJJ9NmjQBwMvLK01feHg4p0+fxtTUlHr16mU71r59+9J8iq/RaDhw4IDeddbW1uzYsQMvLy9Onz6dJt7Tp085fPgwKpWKRo0a5eCphBDi7WTiWA6nMftx6LcQAzNrpT3Wdz/+E90I3zcfbQb78A1UBgyo1ICdHYbjYvOsqvj18Ee03zGfZVf/y9b+fCGEEEK8e/JF8tmiRQuKFy/O4cOHWb9+vdIeHx/PhAkTiI2NpXv37tjZ2Sl9Go0GPz8//Pz80GieLfdyd3fHzc2Nmzdv8ttvvyk/BCUnJzN16lQePnxI06ZNUatTl46ZmZnRrVs3AKZMmUJgYKAS6+nTp4wcOZLIyEg6d+5MqVKl8vR9EEKI10VlYIBN088oNfWy3tEr2oQYQtZ8wf1pHiQGXc/w9RXtirCr43AGVGqgtCUkJ/H96R302fc/QuKi8nT8QgghhHj9VNp88hHz2bNnGThwIPHx8bi6uuLk5MTFixd5/PgxlStXZuXKlXpFgh48eEDz5s0BOHDgAE5OTkqfn58fH3/8MeHh4ZQpU4by5ctz7do1AgICcHJyYt26dXp7PqOjoxkwYADe3t6YmZlRvXp1zMzMOHv2LFFRUdSoUYMlS5bo3f9V6AoOubq6snnz5lyJKYQQL0ur1RJ1ci2P144iJTpUaVcZmVKo62Rs23yFyjDj+naHHtzgq+MbCYmLVtoKmVnya8OPaF6iQp6OXQghhBCvT75JPgFu3rzJ/PnzOXPmDLGxsTg5OdG2bVv69++vnL2pk1nyCRAYGMj8+fM5duwYT58+pWjRonh4eDBkyBAKFUp7tl1iYiKrVq1ix44d3L17FwMDA0qXLk2nTp34+OOPMTY2zrXnlORTCPE2Sop8TMjqL4g6s0Gv3bR0TYoMWIqpU+UMXxsaH83o4/+w/77+bGm/CnWZWKs95ka593eoEEIIId6MfJV8vi8k+RRCvM2iL2wjeMVQkp8+V0DI0JhCnSZi134MqgwSSa1Wy6obp/nhzE4Skp8VcHOxcWRBk55UsC2S10MXQgghRB7K9T2f586dY/78+bkdVgghxDvCqnpnnKddoUCDvs8akzWEbplEwA91iL93Md3XqVQq+laoy7+dRuJq96w6+I2IYNrvmM/yayelGJEQQgjxDsv15PPs2bMsWLAgt8MKIYR4hxha2lJk0P8o/tVOjOyebWtIuH+JgB/q8GTTd6RoEtJ9bXkbB7Z3GMZg14bPXpecxMRT2xhwYCVh8TF5Pn4hhBBC5L58Ue1WCCHE28nSrS2lpl6mYJPBzxpTkgnbMY2ASTWJ80t7RBWAqaER39fuwKqW/Sls9mzPvtf9a7Tc9jv/PfTL66ELIYQQIpdla8/nuHHjsh3wxo0bXLt2jWvXrr3SwETGZM+nEOJdFHv1AI+WDSbpif+zRpUBtq1HUajbDxiYmKf7upC4KEYd28jhwJvPXoaKYW4ejHZvibGBYR6PXAghhBC5IVvJZ4UKFVCpVNnea6NSqST5zEOSfAoh3lUp8dE82TSRiP3z4bl/U4wdy1NkwF+Yqxum/zptCkuv/se0c/+iSUlW2t3tSzDfowelrNNWIRdCCCHE2yVbyWfDhg2pXLkyc+fOzTLgokWLWLhwoSSfeUiSTyHEuy7u5nEeLR2IJvjWs0aVCpvmwyj84VQMzP6vvfsOi+JawwD+7i69SQcRQVGxgCjW2EWNvZJEURM1ibFrzNXEXmKLSYwxttgSDTaCJZZYUAElir2LBUUFRCnSBJaFZXfvH4RBAsoiS39/z5PnPn7nzJkz546DHzPnHKMCj7v9MgoTz+zG41cvhZiRti6+azMIg+o0LeFeExERUXGoNefT1dUVd+/ehY6OTqH/aWm9eSNxIiIiANB3bg/Hxddh1nMaIPr3R5FKhaRTaxE+rymk904XeFxjyxo41n8yhtRrIcRS5RmYHOSDqUG+SH3DIkZERERU9tRKPl1cXBAbG4vY2NhC6xobG6N69eqF1iMioqpNrKMPK68fUHPuWejYNRLi8rgnePZ9V8R4T4JSlprvOENtXfzU/kP82nkYTHT0hPjesGvoeXA1br58Vir9JyIioqJR67NbqVSKxMREWFtbQ1u74M3BqfTws1siqmyU8gwkHFqChCPfA6/N6dSyrAXbzzbDoFGXAo+LTEnA5KA/cSU2PPcYkRgzmvfAWNcOEIu4qDsREVF5odZPZQMDA9SoUYOJJxERlQixti4sP1gMh/nnoWPfWIhnvXyKZz+8jxjviVCmp+Q7rqaxOfb2GoOpTbtCLBJlH6NSYumVY/j4xFbESF+V2jUQERHR2/FXwkREVG7o1WoOx4WXYN5/LiDJXUMgOWADns5tAuld/3zHaIklmO7+Pnx7foHqBtWEeNDzh3j/wC/wj7xfKn0nIiKit2PySURE5YpISweWnt/CYf4F6NR0E+JZ8eF49kN3xGwbD0V6/jea79k64cTAL9HL0UWIJWSkYeSpbVhw8TAyFFml0n8iIiIqWLGST7lcjn79+iEgIEBT/SEiIgIA6Dm6w3HBRZgPmJ/3LejpTQif44a0OyfyHWOma4BNHh9jedtB0JPkThX57e45DDzyKx4nv8x3DBEREZWOYiWfKpUKDx8+xKtXnFNDRESaJ9LSgeWgBXCYfxG6NZsI8ayESESt6IXo38dAIU3Oe4xIhI/rt8bR/pPQ0MxWiN+Oj0KvQ6uxL+x6qfWfiIiIcvGzWyIiKvf0HJvCYcFFWAxamOct6Kug3xA+1w1pt47nO8bZ1AaH+k7EyAbvCbG0rEx8GfQnvvrHF2ncE5SIiKhUMfkkIqIKQaSlDYsB8+C44BJ0Hd2FeFbCM0St7IPo37/I9xZUX0sbS9sMxCaPj1HttT1B9zy6hl6H1iAk/nmp9Z+IiKiqY/JJREQViq5DEzjMOw8Lz0XAa/M6XwX9nv0WtIC5oL1rucJvwJdoYe0oxB6/eon+R9Zj691gqLHlNRERERUTk08iIqpwRFrasOg/B44LL0PXsZkQz0p4hqgVvRCzbVy+fUHtjcywt9cYTHbzgAjZe4JmKLIw7+IhjA7YjsQMaaleAxERUVXD5JOIiCos3ZqN4TAvON9b0OTTmwvcF1RLLMGM5j2wq8dnsNY3FuJ+EXfR4+AvuBTztLS6TkREVOUw+SQiogot9y3oJeg6NBXiwr6g3hOhlKXmOaaDXT2cGPAlOtVwFmLP05Lx4bGN+OWGPxRKZWl1n4iIqMpg8klERJWCbk03OMy/AIuBC/LuCxqwAeHzmkJ673Se+pb6Rtj+/ijMadELWqLsH4dKlQo/Xj+JoX5bEC3lNmJERESaxOSTiIgqDZGWNiwGzofD/AvQsW8sxOVxT/Ds+66I3T4Fyow0IS4WiTG+cSfs7zMONY3MhHhw9GN0P/AL/CPvl2r/iYiIKjMmn0REVOnoObrDceElmPebA4glQjzJfx3C5zaF9ME/eeo3s3KA34Av0a+WmxBLyEjDyFPbsPjSEWQqskqt70RERJVVsZJPHR0d+Pv7o3v37prqDxERkUaItHRg+cEiOMwLhk4NFyEuj3uMZ8s9ELvrf1C+tsKtiY4e1nceih/aeULvtcWLNob8g0FHN+Dpq/hS7T8REVFlU+w3nzVq1ICBgYEm+kJERKRxerVbwGHhZZj3nQn8O7cTKhWSTvyC8PnNkP7wnFBXJBJhmHMrHOk3CfVNbYT4zZfP0PPQahx+cqu0u09ERFRp8LNbIiKq9MTaurD8cClqzjsHHbuGQlwe8xCRyzoh7s8ZUGbKhHh9Mxv83W8iPq7fWoilyjMw/vQuzAr+C7Isean2n4iIqDIQqVQqlaYbzczMxOPHj5GamorCmm/ZsqWmT1/peXp6IiQkBC4uLti/f39Zd4eIqEJRZsoQf2AhEo/9BKhyt1TRsWsE2y+2Qq92izz1/35yC1+f24cUeYYQa2ReHRs6D4NTNatS6zcREVFFp/Hk8+eff4a3tzdkMlmhdUUiEe7evavJ01cJTD6JiIov/dF5RG/5DPLo0NygWALzvrNg0X8ORFo6Qvjpq3hMOL0Lt+KjhJiBlg6Wtx0EzzrupdltIiKiCkujn91u27YNGzduRHp6OlQqVaH/KbmJNxERlRH9um3g+O1VmHb/MjeoVCDh0BJELGqDjMjbQriWiQX+6jMenzVsK8SkWZmYEvQnpp/di/SszNLsOhERUYWk0TefvXv3xpMnT+Dp6YmJEyfC2toaWlpahR9IRcI3n0REmiW9fwYxv30OedyT3KBEG5aDFsKs13SIJLk/y46Hh2Da2T1Ifn2OqKkNNngMRz1T69LsNhERUYWi0TefkZGRsLCwwOLFi2FnZ8fEk4iIKgSDBp3guOg6qnUekxtUyPFy7xxELu2AzOf3hXBPRxcc7z8F7lY1hdiDpBj0PrwGex5eLc1uExERVSgaTT6NjIxgZWUFsZiL6BIRUcUi1jeGzahfUWPaUWiZ1RDisseXEL6gORL9VkH173SRmsbm2NdrLMa6dBDqpWfJ8dXZPZga5AupnJ/hEhER/ZdGs8SWLVviyZMnSEtL02SzREREpcawcQ84LrkFk3YjhJhKLkPc7ml49n1XZMY+BgDoSLQwr1UfbOs2Eqa6uftd7w27ht6H1+BeQnSp952IiKg802jyOWHCBCgUCnz77beFbrFCRERUXkkMTWH7xVbYffkXJCY2Qjz9QRDC5zVFUsAG4edct5oNcaL/FLS0dhTqPUqOQ9+/12JX6CX+PCQiIvqXxrdaCQgIwKRJk2Bvb4927drB3NwcIpHojfUnTZqkydNXCVxwiIio9ChSXiJ2+2SkXPLNEzdw6Qabz3+Dtrk9AECuVGDFtZNYd/t0nnoDnJrg+7aeMNLWLaUeExERlU8aTT5TU1PxxRdf4Pr1629NOF937949TZ2+ymDySURU+lIu+SLGexKUqfFCTKxfDdYf/wLjth8LP/cCnz3Al0G+SMjInYJS28QSGzoPg4uFXan3m4iIqLzQ6HK0q1atwvXr1wEAVlZWsLOzg7a2tiZPQUREVCaMWw2GvnNHxPwxDmnXDwMAlOnJiN48CqnXDsB65K/QMrGGh319+A2YgklnfHAxJnvrlievXqL/kfVY0KovPqnfWu1f0BIREVUmGn3z2blzZ8TExGDZsmUYNGiQppql/+CbTyKisqNSqfDqnDfidk6FMv2VEJcYW8F61K8wbp798y9LqcDPN/yx+mYgVMj9Udu/thu+b+sJYx29Uu87ERFRWdLogkMJCQlwdHRk4klERJWWSCRCtfYj4bjkJgwadRXiipQ4vFjzIaI3j4IiLQlaYgm+btYdu3p8Bit9I6HeoSe30PvwWtxNeF4W3SciIiozGk0+ra2tIZFINNkkERFRuaRt4YAa04/D6uPVEOnoC/FX57YjfF4TpN05CQDoYFcPfv2/RFtbJ6HOk1cv0e/v9dj5gKvhEhFR1aHR5LNHjx54/PgxQkJCNNms2p48eYLp06fDw8MDbm5u6N69O37++ed32nc0JiYGCxYswPvvv4/GjRvDw8MDixcvRkJCglrHZ2VlYciQIahfvz4uXrxY5PMTEVH5JxKLYdZtIhwXXYNenfeEeFbCM0St6Jm9QFFGGqwNjLG7x2hMbdoVImTP98xQZGFG8H5MCfoTafKMsroEIiKiUqPR5HP8+PFwcHDA+PHjcfz48XdK+t7VrVu34OnpicOHD8PKygqdO3eGVCrFhg0b4OXlhZSUFLXbioiIwAcffAAfHx/o6enBw8MDEokEO3bswMCBA/HixYtC21izZg1u3LhRjCsiIqKKQsfWGTVnn4Hlh0sBSe5Ce8kBvyJ8fjOkPwyGRCzGdPf3sbP7Z7DQMxTq/PX4BvocXov7idFl0XUiIqJSo9EFh7755hskJCTg7NmzEIlEEIlEMDY2hr6+foH1RSIRAgMDi31euVyOHj16ICoqCsuXLxfmnMpkMnz11VcICAjA0KFDsXDhQrXaGzp0KK5du4bJkycL+5AqFAosWrQIPj4+6NixIzZv3vzG4y9fvowRI0ZAqVQCALy9vdG6deviXeRruOAQEVH5lRFxEy82jUTms9u5QZEYZr2mw2LQQoi1dREtfYWJp3fhYsxToYqeRBtL2wzAkHotSr/TREREpUCjyWeDBg2KdnKRSCP7fB44cAAzZsxAu3bt8Pvvv+cpS0xMRJcuXSCXyxEcHAwTE5O3tnX58mV8/PHHcHJywpEjRyAW574clsvl6N69O54/f44jR46gbt26+Y5PTk7GgAEDIBKJIJFIEBkZyeSTiKiKUcozkHBwERKO/AColEJcx74xbL/YBj3HpshSKrDi+kmsvXU6z7GD6zbH0jYDoK+lU8q9JiIiKlka3efzu+++02Rzast5e9q9e/d8ZWZmZmjdujUCAwNx9uxZ9O7dW622unXrlifxBABtbW107doV27dvR0BAQIHJ57x58xATE4M//vgDS5cufddLIiKiCkysrQvLD5fCsGlfRG8eBXnMIwBA5rPbiFj0HiwGLoB5768xs3lPtLKpjS+D/kRihhQA4PvoKm6+fIYNHsNRz9S6LC+DiIhIozSafJbVFiuhoaEAgPr16xdYXq9ePQQGBuLBgweFJp+FtZWTcD548CBf2Z49e+Dn54cxY8agVatWavefiIgqJ/26beC46Bpe+s5Ckv+67KBCjvh9c5F28whsv9iGLvb14dd/Ciac2Y0rseEAgAdJMeh9eA2Wt/XEB3Xcy/AKiIiINEejCw6VlZiYGACAjY1NgeVWVlYAgNjYWI21FRcXlyf+5MkTLFu2DC4uLpgyZYp6HSciokpPrGsI609Wo8bXftAytxfiskfnET7PHUkBG1DdsBr29BqDca4dhfL0LDm+DPoTX5/bh/QseVl0nYiISKM0+uazrKSnpwMA9PT0CizPiUul0hJpSy6XY9q0aVCpVFixYgW0tbULPPZtfHx84Ovrq1bdsLCwIrdPRERly9ClGxwX30TsjilIOb8TAKDKlCLWeyJSbxyG7WdbMLdlb7S2qYWp/+xBcmb2z6PdoZdxIy4SGz2Gw6maVVleAhERUbG8c/LZsGHDYp9cJBLh7t27xW5HIpEIK8u+jTprK0kkErXO+fr5Vq5ciZCQECxcuBBOTk5vOerN4uLiymx/VCIiKh0SQ1NUH+sNo2b9EfPHBChT4wEA0lvH8XSOG2xGrsP7rQbDb8AUjAvchRsvIwEA9xKj0evQGvzQ7gMMcGpSlpdARET0zt45+dTgIrnFZmhoiKSkJGRkFLxJt0wmAwAYGBio1RaAQtvKqRccHIytW7fCw8MDQ4cOLXLfc1hZWcHFxUWtumFhYUI/iIio4jFu+SH067VDzNYxSLt5FACgTEvAi/VDkXrtEKp/sgb7e4/FsivHsOXuOQBAWlYmJp7ZjQvRj7GgVV/oaRX9KxsiIqKy9M7Jp7e3d5GP8fPzw65duwBkJ68tW7Z819PnYW1tjaSkJMTFxaF69er5ynPmelpbF75qoLW1NUJCQt44P/S/bS1btgwqlQpyuRzTp0/PU/fFixcAgA0bNmDPnj3o3r17gSvyAoCXlxe8vLwK7R+Qu9UKERFVXFqm1WE39RCSz2xB3O5pUGWkAQBSLuxG+oMg2Hz+Gxa27ofWtrUx7exevMrM/qXj9gcXcePlM2zwGAZHY4uyvAQiIqIieefksyiruSYlJWHRokU4duwYVCoV9PX1MX36dAwfPvxdT59H/fr1ERoaiocPH8LNzS1f+aNHj4R66rQVGBgoHFNYWzlzP8+ePfvGNoODgwEAjo6Ob0w+iYio6hGJRDDt/AUMGnVF9OZRkD3MfsuZlRiFqBU9Ua3rBPQY/D0a9Z+M8YG7cCs+CgBwOz4KvQ6twaoOg9HdoVFZXgIREZHaSny121OnTqFv375C4tmyZUscOnRIY4knAHTu3BkAcOLEiXxliYmJuHjxInR1ddGmTRu12zp58mS+T4vlcjn8/f3z1AsICMCDBw8K/K9BgwYAst8SP3jwAJMnT37HKyQiospMx9oJNWcFwnLwcoi0dIR4sv96hC9oDuvYR/irz3iMbJD7c+xVpgyf+XtjyeWjkCsVZdFtIiKiIimx5DM5ORnTpk3D5MmT8fLlS+jp6WHu3LnYvn07atasqdFzdevWDTVq1MDp06fh4+MjxGUyGebMmQOpVIrBgwfD3NxcKJPL5QgLC0NYWBjk8twl7N3d3eHm5obQ0FCsWrVKSEAVCgWWLl2KFy9ewMPDA87Ozhq9BiIiqtpEYgnMe38NhwUXoVMz9yseeXQoIpd2QMrBxVjSsjfWdvKCwWsJ6oY7QRhyfDOipa/KottERERqE6lKYOUgf39/LFiwAPHx8cLbzmXLlmk86Xzd5cuXMXr0aMhkMri4uMDe3h7Xr19HbGwsXF1d4e3tLSwSBADPnj1D165dhf7a2+fuvRYWFobhw4cjMTERTk5OqFevHu7du4eIiAjY29tj9+7das0fHTBgAO7fvw9vb2+0bt1aY9eaM+fTxcUF+/fv11i7RERUPijlGYj/ayESj/0IvPZjWrdWc1Qf440IA3OMDdyJB0kxQpmlnhHWdvJCe7u6ZdFlIiKiQmn0zeerV6/w9ddfY9KkSSX+tvO/WrZsiT179qBHjx54/vw5Tp8+DWNjY0yaNAl//PFHnsSzMHXq1MG+ffvg6emJlJQUBAYGQiQSYcSIEfD19VUr8SQiInpXYm1dWA3+DjVnnYa2Ve4WXhlPryJ8QXNYXNmDQ73H44M67kLZS1kqhvr9hl9u+EOpKnz7MSIiotKmsTefgYGBmD9/Pl6+fFlqbzurKr75JCKqOpSyVMTtnobkM1vyxA1c34fNZ1vgG/cc8y8eQoYiSyjrXMMZqzsOgbme+r94JSIiKmnFfvOZkpKCGTNmYMKECYiLi4Oenh7mzJlTKm87iYiIKjuxnhFsPt0Iu6kHITHJ/fJGeuckwuc1Rf+kJzjYZzwcjXPXNTgdFYoeB1fjamx4WXSZiIioQMVKPs+cOYM+ffrg0KFDUKlUaNGiBQ4ePIhPPvlEU/0jIiIiAEZN+8JxyS0YuvcXYsq0RLz4dRgs9szA310+Ro/Xtl15IU3GB0c3YkvI2XyrtxMREZWFd/7sdtasWThw4ABUKhXEYjGGDRuGESNGQCQSFakdvh0tOn52S0RUdalUKrz6Zytid30FlSxViGuZ28Pm89+wU6WLpVeOQfHavM/ejq5Y0f5DmOjolUWXiYiIABQj+WzQoEGRE818JxeJcPfu3WK1URUx+SQioszYx4jZ8inSQ8/miZt2/xLhHcdg/Ln9ebZfqWVsgU1dhqORuV1pd5WIiAhAMT+7ValUxfpPqeRqfERERO9Cx9oJ9jMDYPnRd4BEW4gnnfgFVus/whH3TuhoV0+IP02JR7+/18Mn9HJZdJeIiOjd33xGRUVppAM1atTQSDtVCd98EhHR62ThNxC9aQQyo0JygxJtmA9cAG+7Zvj51mmokPvjfnDd5ljaZgD0tXTKoLdERFRVaWyrFSo9TD6JiOi/lJkyxO+bi0S/n/PE9eq2RUT/BZhw5zwSMtKEeEMzW2z0+BhO1SxLu6tERFRFFXurFSIiIip7Yh09WA1dAftvTkLLPHcxP9mjYNis/wCHrczRwspBiN9LjEafw2twLPxOWXSXiIiqICafRERElYhBoy5wXHwDxm2GCzGVLBUZO6dg7eNTmOTkJsRT5Bn4ImAHFl8+CrlSURbdJSKiKoTJJxERUSUjMTRF9bHeqD5hN8SGZkJceu0gPtr/NbztHWGkrSvEN94JgtfxzYh5bXVcIiIiTWPySUREVEkZtxoMxyU3YeDSVYgpkqNhv3MSDsuewdUoNzG9GPMUPQ+txvnox2XRVSIiqgKYfBIREVVi2mY1UGPacVgN+xkirdy3naqz27D+6jaMrVZNiMWlp8Lr+Basv30GXI+QiIg0jcknERFRJScSi2HWfQocFl6Cbs0mQjwrOhRDjizEH6pk6EEEAFColFh25RhGB2xHckZ6WXWZiIgqISafREREVYSuvStqzj8Ps95fA6LsZBOKLNQM2oTD4f5wFyuFun4Rd9H78FqExD8vo94SEVFl887Jp6enJ3755Rdcv36dn+YQERFVEGJtXVgNXg77Gf7QssjdekXy9CpWBm/EVFkc8O/P9fCUePQ/sh5/PrxSVt0lIqJKRKR6x8yxRYsWSE1NhUgkQrVq1dC+fXt06NABHTp0gLm5uab7Sa/x9PRESEgIXFxcsH///rLuDhERVVAKaTJid0xBSvCOPPHoOu0w3sYdydr6QsyrXgssfm8A9LW0S7ubRERUSbxz8qlQKHDt2jWcPn0aQUFBePjwIUQiEUQiEVxdXdGpUyd06NABbm5uhTdGRcLkk4iINCnlki9i/pgAZVqiEFMYWeE75+4IMLYTYq7mdtjYZTgcjS3KoptERFTBvXPy+V8xMTE4ffo0zpw5gwsXLkAqlUIkEsHc3BwdOnRAx44d0b59e5iYmGjidFUak08iItI0eWIUYrZ8CmmIf5742TodsaR6M2RKst94mujoYVWHweju0KgsuklERBWYxpLP18nlcly5cgVnzpxBUFAQHj9+DJFIBLFYDDc3N3Tu3BkdO3ZEw4YNNX3qKoHJJxERlQSVUomkU2vx0ncmVFkZQjzJzB7f1O6CR8Y2Qmxi4874utn70BJLyqKrRERUAZVI8vlfz549ExLRS5cuIT09HSKRCFZWVggKCirp01c6TD6JiKgkZUSF4MWGj5EZeUuIqcRa2ObUETvt3KEUZa9X2NbWCes6D4WVvnFZdZWIiCqQUkk+X5eZmYmLFy/izJkz+Oeff+Dn51eap68UmHwSEVFJU8ozEL9vHhL9Vgqr3wLAA4s6WFC3G2L1sqfR2BiYYJPHcDS3diyrrhIRUQVR6sknFR+TTyIiKi3SuwGI3vIpshKeCbEMbQP8WLcLAqyzp89oicSY36oPPm3YFqKc/UOJiIj+4533+SQiIqLKz6BRFzguvgGjVh8JMV25FHPv/Y05947AMEuGLJUS8y8exqQgH0jlmWXYWyIiKs+YfBIREdFbSQzNUH38btiO+QNi/dxV67vG3sXvV73hlhQJADj4+Cb6/b0Oj5PjyqqrRERUjjH5JCIiokKJRCKYtP0YjouuQ9+5vRC3kiVj5c0/MfpxELSUCjxIikHvw2tx9OmdMuwtERGVR0w+iYiISG3aVrVgPzMAlh8uBSRaAAAxVBgWeRHrru+AQ1o8UuUZGBO4A0suH0WWUlHGPSYiovJCY8nnkiVLkJKSoqnmiIiIqJwSiSUw7zsTDnPPQdvWWYjXS43Fxmve6B91HVCpsOFOEIb6/Ya4dP77gIiINJh87tixAz179sS+ffs01SQRERGVY3q1W8Dx2yuo5jFWiOkqszD10SksvbMfZplpOB/9GD0PrcGVmPAy7CkREZUHGks+XV1dER8fj7lz52LIkCG4c4dzPYiIiCo7sa4hbEauh93Ug5AYWwnxNgmPsfnKNrSOD0OM9BU+PLYRv909B+7wRkRUdWks+dyzZw8WLVoEU1NT3Lx5E4MHD8b8+fORmJioqVMQERFROWXUtC8cl9yEoVsvIWYul+K7O/sx5eFJSLIysODiYUw644M0eUYZ9pSIiMqKxpJPkUiEwYMHw8/PD0OHDoVIJMKePXvQs2dP7Nq1i7/pJCIiquS0qtnA7qvDsP5kLUTaekJ84PMb2HDNG3VTYnDwSfZ2LI+SYsuwp0REVBY0vtqtiYkJFixYgH379sHd3R3JyclYvHgxPvjgA1y7dk3TpyMiIqJyRCQSwbTreDh8ewW6Dk2FuKM0Aeuu78CQiIt4mBiDPofX4sjT22XXUSIiKnUlttVKgwYNsGvXLixfvhwWFha4e/cuhg8fjhkzZuDly5cldVoiIiIqB3TtGqLmvGCY9ZoOiEQAAG2VEmOfBGHFLV8YpL7E2MCdWHzpCLdjISKqIkp8n8+BAwfCz88Po0aNgkQiwaFDh9CzZ09s27YNCgV/2BAREVVWYm1dWA35HvbfnISWWQ0h7p4UgS1Xt6FT7H1sDPmH27EQEVURIlUpTsYMDQ3FV199hbCwMIhEItSqVQudOnVCo0aN0KhRI9SpUweif387Sm/m6emJkJAQuLi4YP/+/WXdHSIiokIpUhMQ88d4pF7emyd+3MYFa+t2hYmJFTZ6DEdza8cy6iEREZW0Ekk+ZTIZnjx5grCwMDx+/Fj434iICGRmZgKAsADR68mmnp4e6tevDx8fH013qVJh8klERBWRSqXCq3PeiN0xBSpZqhB/rlcN3zXog1AzByxs1RcjGrzHX0YTEVVCWppq6NWrV1ixYgXOnj2L6OjoPKvb/je/tbKygpOTExwdHfHy5Uvcu3cPL168QHp6Om7evKmpLhEREVE5IhKJUK39SOg7t0f0ppGQPToPALCTJWPVjd3Y4dgG8xRyXIuLwPK2g6CvpVPGPSYiIk3SWPI5e/Zs+Pv7C4mmjo4OHB0dUbt2bdSuXRtOTk5wcnJC7dq1YWRklO/4xMRE3L17F3fv3tVUl4iIiKgc0rGug5qzTiPh8DLEH1oCKBWQQIWR4cFokfgUy2SvMCAxGps8PkYtE4uy7i4REWmIxj67bdGiBdLS0vD555/jww8/hKOjIz+ZKSH87JaIiCqL9EfnEb1xBORxj4VYmkQHq+t2xaWazbG601B0rdmgDHtIRESaorHVbk1MTGBiYoLp06ejVq1aTDyJiIioUPp128Bx0TWYtB8pxAwVmZj14Bgm39yLicc2YMX1k1AolWXYSyIi0gSNfXYbEBCAtLQ0TTVHREREVYRY3xi2o3+HoVtPxGwbD6U0CQDQJe4+XF5F4bu0ONyIi8SaTl4w0zUo284SEdE701jyCQCGhoaabK7Injx5gnXr1uHq1auIj4+Hra0tevXqhTFjxhS5bzExMVi/fj2Cg4MRHR0NS0tLdOnSBRMnToS5uXm++pmZmdi2bRsOHz6Mp0+fCiv3fvTRRxgwYICmLpGIiKjSMm41GHp12iB600ikPzgDALDJSMHKmz7YlfgU/RKjsaHbSLha1CikJSIiKo9KdZ/PknTr1i2MHDkSUqkUTZo0ga2tLa5du4a4uDg4Oztj165dMDY2VqutiIgIDBs2TDi2du3auHv3LiIjI2FjY4M///wT1atXF+rL5XKMHj0aFy5cgLGxMZo1a4asrCxcvXoVMpkMffv2xYoVKzT2KTLnfBIRUWWmUiqQeOwnvNw3D1BmCfH7xrb40WUAJnf9DIPrtSjDHhIR0bvQ2JzPsiSXyzF16lRIpVIsX74cvr6+WL16NU6dOoUuXbogNDQUP/30k9rtzZgxA3FxcZg8eTIOHz6M1atXw8/PD15eXoiJicH8+fPz1N+8eTMuXLgAV1dXnDx5Eps2bcLvv/+Oo0ePwtbWFn///TeOHz+u6csmIiKqlERiCcz7fAOH+cHQtnUW4g1SorH20u84uWc+Zp7bjwxF1ltaISKi8qZSJJ9HjhxBVFQU2rVrh0GDBglxPT09LFu2DAYGBti7dy9evXpVaFuXL1/GtWvX4OTkhAkTJghxiUSCuXPnws7ODkFBQXj06JFQduDAAQDAnDlzYGZmJsRr1KiBjz/+GAAQFBRU3MskIiKqUvRqNYfjt1dQrfMXQkxfKcfXoX6o+9dsfPLXSjxPTSq7DhIRUZFUiuQzMDAQANC9e/d8ZWZmZmjdujXkcjnOnj2rdlvdunWDWJx3eLS1tdG1a1cA2Qss5Th48CAOHDgAd3f3fO0p/12dT1tbW82rISIiohxiXUPYjNoAu8n7AMPcNRc6vnyIqSeW4uutX+Hs80dvaYGIiMqLSpF8hoaGAgDq169fYHm9evUAAA8ePCh2W3Xr1s3Xlr6+Pho2bJhvTuf169fxxx9/QCwWY+DAgYWem4iIiApm1HwgnJbchF6jrkLMMjMVC6564/T6j/Hr9ZOoJMtYEBFVWpUi+YyJiQEA2NjYFFhuZWUFAIiNjdVYW3FxcQWWp6WlYcqUKejXrx+8vLygUCiwYsUKNGvWrNBzExER0Ztpmdmh5vTjsBr6E5SS3C+KBj+7DIffRmDWXz8iVZ5Rhj0kIqK30ehWK2UlPT0dQPYcz4LkxKVSaYm39ezZM/j5+Ql/FolECA0NRY8ePaCl9ebh9vHxga+vb6H9A4CwsDC16hEREVU2IrEYZj2mwqChB56sGwJxzEMAQL3UWNT8ex5+fHoZH3+6FvXMCv4lMhERlZ1KkXxKJBJhbuXbqPM5jkQiUeucbzqfvb09Ll68CIlEgsuXL2PZsmXYsGEDoqKisGLFije2FxcXh5CQELXOTUREVNXpOjSB8+LreLbzK8jObAYA6CmzMPzWflxYegePP9uIHo06lnEviYjodZUi+TQ0NERSUhIyMgr+1EYmkwEADAwM1GoLQKFt5dR70/EA0KVLF9SpUwf9+/fH4cOHMXbsWGH+6X9ZWVnBxcWl0P4B2W8+c/pBRERUVYl19OHw6Qa8atIH4ZtHQjc9GQDQ+mUo4lf1xW89Z2LUwJmQiCvFLCMiogqvUiSf1tbWSEpKQlxcHKpXr56vPGeup7W1tVpthYSEvHF+aFHaAgBHR0e4u7vj/PnzCAkJeWPy6eXlBS8vL7Xa9PT05FtSIiKif5k064eG393FnbWDYfDoHADAIjMNHQ7Nw/YHp9Fvkg8sjM0LaYWIiEpapfhVYM7KtA8fPiywPGdPzjetYFtQW6/v4/m2tuLj47F48WLMmjXrjW3q6OgAAORyeaHnJyIioqLTMrVFk9mnIR60GHJx7hSatg/8cX12Y9y6E/CWo4mIqDRUiuSzc+fOAIATJ07kK0tMTMTFixehq6uLNm3aqN3WyZP5l2yXy+Xw9/fPU09PTw++vr7Yv38/bt++na+9pKQk3Lx5EwDQuHFjdS+JiIiIikgkFqPugNmoMS8YL01rCHGHlGiIVvbCqd0zuB0LEVEZqhTJZ7du3VCjRg2cPn0aPj4+Qlwmk2HOnDmQSqUYPHgwzM1zP7mRy+UICwtDWFhYnjeS7u7ucHNzQ2hoKFatWiX8kFIoFFi6dClevHgBDw8PODs7A8ie45mzh+ecOXPybMGSkJCAadOmISkpCR07dkSDBg1KchiIiIgIgGntFmj9/X08cx8kxHSVWXDwWwH/Ba0hTXxehr0jIqq6RKpK8ivAy5cvY/To0ZDJZHBxcYG9vT2uX7+O2NhYuLq6wtvbO89iQM+ePUPXrtkbVfv7+8Pe3l4oCwsLw/Dhw5GYmAgnJyfUq1cP9+7dQ0REBOzt7bF79+48cz5TU1MxatQo3L59GwYGBmjWrBlUKhVu3bqFlJQUuLi44LfffoOZmZlGrjVnzqeLiwv279+vkTaJiIgqo8uBv0G1+yuYZqYJsVe6xrD+/Dc4tPqgDHtGRFT1VIo3nwDQsmVL7NmzBz169MDz589x+vRpGBsbY9KkSfjjjz/euDptQerUqYN9+/bB09MTKSkpCAwMhEgkwogRI+Dr65tvsSEjIyPs2rUL06ZNQ82aNXH58mVcu3YNDg4OmDFjBnx8fDSWeBIREZH6Wnp8Drtvr+KebSMhZpKRAtn6wbix6TMoM7l6PBFRaak0bz6rEr75JCIiKhpZlhy+v49Hs/Pe0FEphHiqpRMafbkfejW5LgMRUUmrNG8+iYiIiN5ET0sbI8ZsQdhobzwxtBLiRi8f4/HClojxW8XFiIiIShiTTyIiIqoyBrTzQvW5Z+FXK3cFfC2FHMm7p+Hhjz2R9argfb6JiKj4mHwSERFRleJWvS6Gz/TDjk6TkaBtkFtw9xRCZ7si7dbxsuscEVElxuSTiIiIqhxzPUMsGLkSF0ZsxgVzJyGulRqPqJV9ELPjSy5GRESkYUw+iYiIqEqSiMWY2sELVlP2Y6NzD2SKJEJZ8qm1ePJtK2Q8u1OGPSQiqlyYfBIREVGV1qtWY4yfsA3LOn2Jx4aWQlwRFYKnC1sh8dQ6LkZERKQBTD6JiIioyqtrao1Nw5fg4MDvsK9GMyEuyspA3I4peL6qPxcjIiIqJiafRERERACMtHWxvtunMBnyI2Y1/jDPYkRpN4/i6dymXIyIiKgYmHwSERER/UskEmGiW2dMHboE09pOyLMYkfJVDKJW9kHszq+4GBER0Ttg8klERET0Hx3s6uHPj2Zid6fJWF23a57FiJJOrkbEove4GBERUREx+SQiIiIqgL2RGfb3GQ+dTl9gXPNPEPbaYkSZz24j4tvWXIyIiKgImHwSERERvYG+ljZ+av8hxnb7Al82H4V9NZoLZSq5jIsREREVAZNPIiIiorcQiUT4pMF72N13Iva6DcSMAhYjCudiREREhWLySURERKSG5tYOONZvMsQNu2B0i1E4/9piRAphMaKpXIyIiOgNmHwSERERqcnawBg+PUfjw6bdMcfVE7/U7YoMsZZQnnRyDRcjIiJ6AyafREREREWgLZZgYet+WNNpKPwcWmN8swIWI1rYiosRERH9B5NPIiIioncwqE5THOo7ASpbZ0xo9knexYiyMrIXI/q5HxcjIiL6F5NPIiIionfUyLw6jvSbhA4OLlhXt0v+xYhuHUP43CZIu3WsDHtJRFQ+MPkkIiIiKgZTXQNs6zYSU5t2xWXz2gUsRhSLqJV9uRgREVV5TD6JiIiIikksEmO6+/vY2nUEFIbmb1mMqDUXIyKiKovJJxEREZGGvO/QCEf6TUJ9M1scrNGsgMWI7mQvRnRyLRcjIqIqh8knERERkQY5VbPCob4T0K+WG54aWmJCs0+w97+LEe38ElEr+yArOaYMe0pEVLqYfBIRERFpmKG2LtZ3Hoq5LXpDIdHG+gIWI5Le9kP43CZIvXGkDHtKRFR6mHwSERERlQCRSIRxjTtid/fPYa5riMvmtfF5i08RbFFHqKNIicPzVf0Rs30ylJnpZdhbIqKSx+STiIiIqAS1s6uLY/0no4mlPZJ1DDDXZRBW1euGzNcWI0r2X4+Iha2QEXGzDHtKRFSymHwSERERlbAaRqbY12sshtRrDohEOGTnjjHNRiDM0Fqok/n8LiIWvYdEv1VQKZVl2FsiopLB5JOIiIioFOhpaWNFuw+xvM0gaIsliDC0wIRmw+Fr30Koo8rKRNzuaYha2RtZSS/KsLdERJrH5JOIiIiolIhEInzcoDX29hoLGwMTyMVa2FDHA9PdPkKynolQT3rnJJ7ObYLU64fKsLdERJrF5JOIiIiolDW3dsDx/pPR2qY2AOCaWS2MbPYJLlrVF+ooU+Px/JdBiPljApQZ0rLqKhGRxjD5JCIiIioDVvrG8Ok5GqMbtQMAvNI2wKyG/bCyXncotHSFesmBGxGxsCVkT6+VVVeJiDSCyScRERFRGdEWS7CwdT+s7jgEehJtQCTC33ZN8Jn7cESbOwr1Ml/cR8Titkg4+iMXIyKiCovJJxEREVEZ86zjjkN9x8PR2BwAEGlggREuH+BYnU6ASJRdSSHHS9+ZePZjd8gTnpVhb4mI3g2TTyIiIqJyoJG5HY70mwSPGtnzPrPEEvxo3wqzmw6D3Dh3S5b0e4EIn9cUKZf2lFVXiYjeCZNPIiIionLCVNcAf7w/ElObdhViF0zs8GHjwYis016IKdMS8WK9F6J/+xzK9JSy6CoRUZEx+SQiIiIqR8QiMaa7v4+tXUfAWDt74aEUbX2MrPEe9rcaCegaCXVf/bMN4QuaI/3RhbLqLhGR2ph8EhEREZVD7zs0wpF+k1Hf1CY7IBJhrb41pr03BkoHd6GePDYMkcs6Iv7gYqgUWWXUWyKiwjH5JCIiIiqnnKpZ4lDfCehXy02IXYcE/Z3ex4v2nwOif/8pp1Qg/q+FiPzOA/K4J2XUWyKit2PySURERFSOGWrrYn3noZjXsjck/yabUpUKwyXm+LvfIkgsc7dkkT0KRvg8d7wK3gGVSlVWXSYiKhCTTyIiIqJyTiQSYaxrR+zq8Tks9AyF+MrkZMxsNwFaLQcLMaUsBdGbRiJ6w3Ao0pLKoLdERAVj8klERERUQbSrXgfH+k1GU8uaQux80kt4mrsgxWslxPrVhHjKxT8RPq8ppPfPlEVXiYjyYfJJREREVIHYGZliX++xGObcSoi9lKXCMzoGwZ9shJ5z7pYsWQmRePZ9V8T5zoIqK7MsuktEJBCpKtGEgCdPnmDdunW4evUq4uPjYWtri169emHMmDEwNDQsvIHXxMTEYP369QgODkZ0dDQsLS3RpUsXTJw4Eebm5vnqZ2VlwcfHBwcPHkRYWBgyMzNha2uLTp06YcyYMbCxsdHUZcLT0xMhISFwcXHB/v37NdYuERERVSy7Qi9h7vmDyFQqhNhAx8aY++oJXh1eDLy2+q2uYzNUH7sdOnYNyqKrRESVJ/m8desWRo4cCalUiiZNmsDW1hbXrl1DXFwcnJ2dsWvXLhgbG6vVVkREBIYNGyYcW7t2bdy9exeRkZGwsbHBn3/+ierVqwv1MzMzMXr0aFy8eBH6+vpo3LgxDA0NcefOHcTFxcHMzAx//PEH6tevr5FrZfJJREREOa7HRWJMwA68kCYLsfqmNthUtzHEOydDHh0qxEU6+rAa8iOqdRkHkUhUFt0loiqsUnx2K5fLMXXqVEilUixfvhy+vr5YvXo1Tp06hS5duiA0NBQ//fST2u3NmDEDcXFxmDx5Mg4fPozVq1fDz88PXl5eiImJwfz58/PU37JlCy5evAhnZ2ccOXIE27dvx4YNG+Dv7w9PT08kJiZi+vTpmr5sIiIiIrhb1cSx/pPR1tZJiD1IikG/W2cRNno7qnUeI8RVmemI3T4Jz3/uh6zkmLLoLhFVYZUi+Txy5AiioqLQrl07DBo0SIjr6elh2bJlMDAwwN69e/Hq1atC27p8+TKuXbsGJycnTJgwQYhLJBLMnTsXdnZ2CAoKwqNHj4SyvXv3AgAWLFiAGjVqCHFdXV18++23qFatGkJDQ3H//n1NXC4RERFRHpb6RtjV43OMde0oxF5lyjDqn73wdhsE28n7ITG2FMrSbh1D+NwmSL1+uCy6S0RVVKVIPgMDAwEA3bt3z1dmZmaG1q1bQy6X4+zZs2q31a1bN4jFeYdHW1sbXbt2BQAEBAQAAGQyGWrUqIE6derAzc0N/6WjowN7e3sA2fNIiYiIiEqClliCeS17Y0PnYTDQ0hHiv9wMwIT4eJjOuwBDt15CXJESh+e/DETMtvFQZqSVRZeJqIqpFMlnaGj2XIY3zamsV68eAODBgwfFbqtu3bp52tLT08P27dtx9OhR6Ojo5KufmpqKsLAwAMgzT5SIiIioJPSt7Ya/+02Ek0num87TUaHod2YPEkdsgPUnayHS1hPKkk9vQviCFpA9uVIW3SWiKqRSJJ85bxTftKKslZUVACA2NlZjbcXFxanVt7Vr10Imk6Fu3bpwdnZW6xgiIiKi4nA2tcGRfpPQ08FFiEWkJmDA0Q045dgKDt9ega6ju1Amjw5FxJJ2iD/8HVSvrZxLRKRJWmXdAU1IT08HkP0WsiA5calUWqptHTx4ENu2bYNYLMbs2bPfWtfHxwe+vr6FtglAeJNKRERE9CbGOnrY3OVjrLt9Bj9c84NSpUKGIgtT/9mD6w3ew/zZQXh1cDESj/0IqFSAIgvx++ZCevs4bL/4A9pWtcr6EoiokqkUyadEIoFSqSy0njq7ykgkErXOWdj5fH19sWDBAqhUKkyfPh3t2rV7a/24uDiEhISodW4iIiIidYhEIkxy64wmljUw4fRuJGZk//L8j/sXcDv+OTb2mQl7t56I3jQSWQmRAID00LMIn9cU1p+shnHbT7glCxFpTKVIPg0NDZGUlISMjIwCy2UyGQDAwMBArbYAFNpWTr3/UiqVWLlyJTZv3gwA+PrrrzF69OhCz2tlZQUXF5dC6wHZbz5z+kFERERUmA529XCs/2SMDdyJmy+fAQCuxUWg16E1+NVjGFotvoHY7RORcsEHAKCUpSB686dIvf43bEb9ComRRVl2n4gqiUqRfFpbWyMpKQlxcXEFLuqTM9fT2tparbZCQkLeOD/0bW1JpVJMmzYNAQEB0NbWxpIlSzBw4EC1rsHLywteXl5q1fX09ORbUiIiIioSeyMz7Os1FvMuHsLu0MsAgJeyVHgd34I5LXrhi7E7YOjWG7HbJ0OZngwASL2yD+mPgmE7+ncYuubfVYCIqCgqxYJDOSvTPnz4sMDynD0537SCbUFtvb6PpzptJSQkYPjw4QgICICpqSm2bt2qduJJREREVBr0tLTxY7sP8H1bT+iIs6caKVRKLLp8BBPP7Iak5YdwXHID+g06C8cokl4gakUvxO6cCmVmehn1nIgqg0qRfHbu3BkAcOLEiXxliYmJuHjxInR1ddGmTRu12zp58mS+OaJyuRz+/v556gFAWloaPv30U9y9excODg74888/0bJly3e7GCIiIqISNrx+K+zrPQ52htWE2KEnt9D/7/WI1NKH/TcnYTnkB4he2y806eQaRCxsBVn49bLoMhFVApUi+ezWrRtq1KiB06dPw8fHR4jLZDLMmTMHUqkUgwcPhrm5uVAml8sRFhaGsLAwyOVyIe7u7g43NzeEhoZi1apVQgKqUCiwdOlSvHjxAh4eHnm2TVmyZAnu378Pa2tr7Ny5E7Vq1Sr5iyYiIiIqBnermjjWfzLaVa8jxB4kxaDP4bU4EXkP5r2mwWHBRejYuwrlmc/vImJRGyT8/T23ZCGiIhOp1FkCtgK4fPkyRo8eDZlMBhcXF9jb2+P69euIjY2Fq6srvL298ywS9OzZM3Tt2hUA4O/vD3t7e6EsLCwMw4cPR2JiIpycnFCvXj3cu3cPERERsLe3x+7du4U5n48fP0afPn2gVCrh4uICJyenN/Zx1KhRcHV1fWO5unLmfLq4uGD//v3Fbo+IiIiqriylAj9cO4H1t8/kiU9288B09/chyspE/L65SPT7OU+5vnMH2H6xjVuyEJHaKk3yCQChoaFYu3YtLl26BKlUCnt7e/Tq1QuffvopjIyM8tR9W/IJAFFRUVi7di3++ecfJCcno3r16ujUqRPGjRsHC4vcFd+2bduG7777Tq3+rVu3Dt26dSvmVTL5JCIiIs07+vQOvvrHF2lZmUKso109rO3kBXM9Q0jv+iN686fISowSysV6xtyShYjUVqmSz6qCyScRERGVhEdJsRgdsB2PkuOEWA1DU2z0GI6mVjWhSEtErPdEpFz8M89xRi0+4JYsRFSoSjHnk4iIiIiKr66pNf7uNwl9azUWYlFpSfA8ugE7HlyE2MAU1cfvgu3Y7RDr5y5WlHplH57ObYK0O/kXfyQiysHkk4iIiIgERtq6+LXzMMxv2QcSUfY/FTOVCswM/gvTzu5FepYcJm2GvXFLlpjtk6HMkJZR74moPGPySURERER5iEQijHHtAJ+eo2Gpl7tuhu+jqxh4ZD3CU+KhbeHw75YsP+bZkiXZfz3CFzSH7PHlsug6EZVjTD6JiIiIqEBtbJ1wfMAUtLB2FGIhCS/Q+9Ba+Efeh0gshnmv//27JUvup7ry6FBELGmHl399C1WWvKCmiagKYvJJRERERG9ka2AC355f4LOGbYVYcmY6Rp36Ayuun4RCqYRuTTc4LLgIs95fAzmr3ioVSDi4CBFL2yPz+f0y6j0RlSdMPomIiIjorXQkWlj0Xn+s7eQFfS1tAIAKKqy64Y+Rp7YhMUMKsbYurAYvh/3MQGhZ1hKOzXhyBeELmiPx5BqolMoyugIiKg+YfBIRERGRWgY6NcXhvhNR28RSiJ2OCkXvQ2tw+2X2/p8G9Tug1uIbMOn4mVBHJZchbudURP3UE/KEZ6XebyIqH5h8EhEREZHaGpjZ4ki/Sejh0EiIRaYmYuDRX+ETmr3IkFjfGLafbYbdl39BYmIt1JOG+CN8bhO8Or8L3GqeqOph8klERERERWKio4ctXT7BrOY9If53jmeGIgvTz+3D1+f2QfbvIkNG7v3huOQWDJsNEI5VSpMQvfETvPh1KBSpCWXSfyIqG0w+iYiIiKjIRCIRJrp1xq7un8Nc11CI7w69DM+jG/AsNREAoGViBbvJ+2Dz+W8Q6xkL9VIv7cHTuW5Iu3W81PtORGWDyScRERERvbP2dnVxvP9kuFvVFGK34qPQ89AanI4KBZCdqFbrMAqOi29Av35HoZ4i6QWiVvZBjPdEKDPSSr3vRFS6mHwSERERUbHYGZlib6+xGNngPSGWlCHFJye24ucbp6BUZa9yq21VC/Yz/GE55EeItHSEuskBGxA+zx3pD8+Vet+JqPQw+SQiIiKiYtOVaGFpm4FY1eEj6Eq0AGRvx/LT9VMYefIPJMqy32yKxGKY9/ofHBZehm7NJsLx8tgwRC7rhDjfmVBmysrkGoioZDH5JCIiIiKN+bBucxzuOwGOxuZCLDDqAXoeWoMbcZFCTNfeFQ4LLsC832xA9O8/SVUqJB79ERHftoLs6bXS7joRlTAmn0RERESkUY3M7XC032R0r9lQiEWlJcHz6AbsuH9R2GZFpKUDyw8Wo+bcs9C2dRbqZkaFIGJxG8QfXAzVvyvnElHFx+STiIiIiDSumq4+tnTNux1LplKBmef/wtR/fJGelSnU1a/TGo7fXoXp+1NyG1BkIf6vhYhY2h4ZUXdLu/tEVAKYfBIRERFRiRCLxJjo1hk+PUbDSt9IiO8Lu46+h9fhcXJcbl1dA1gP/xn2M05By8JRiGc8uYKIBS2QePxnqJSKUu0/EWkWk08iIiIiKlFtq9fBsf5T0MqmlhB7kBSD3ofX4ujTO3nqGjT0gOOSGzDp+JkQU2VlIM5nOp4t74rM2Mel1W0i0jAmn0RERERU4mwNTPBnzy8w1qWDEEuVZ2BM4A4svnQE8tfeakr0TWD72WbYTT0ISTVbIZ4e+g/C5zVFUuBGYd4oEVUcTD6JiIiIqFRoiyWY16oPNnl8DCNtXSG+MeQfDDm+GdHSV3nqGzXti1pLb8G41WAhpspIQ+wfExD1U2/IE6NKre9EVHxMPomIiIioVPWu5Yqj/SahgVnuW81LMU/R69BqBL8Iy1NXYmSB6hN2o/r4XRAb5m7fIr1zAuFz3PDqnDffghJVEEw+iYiIiKjUOVWzwuG+E/BhnWZCLC49FV5+W7Du1ul8CaVx6yGotfQWDJv0FmJKaRKiN3+K578MRFbSi1LrOxG9GyafRERERFQm9LV08HOHj7C87SDoiCUAAKVKhe+uHsfogO1IzkjPU1/LtDrsph6CzWebIdYzFuJpN/7G0zmN8Sp4B9+CEpVjTD6JiIiIqMyIRCJ8XL81/uozHvZGpkLcL+Iueh9ei5D45/nqV+v4GRyX3oKBSzchrkxLRPSmkXi+2hNZSdGl1X0iKgImn0RERERU5ppY2uNY/ynwqFFfiIWnxKP/kfXwCb2cr762hQNqTD8O61G/QqSXu4do2vVD2W9Bz+/iW1CicobJJxERERGVC2a6Bvjj/ZH42v19iCACAGQosjD93D787589SM/KzFNfJBLBtPMY1FpyCwaNugpxZVoCojd+ghdrP0RWckypXgMRvRmTTyIiIiIqN8QiMb5s2hW7enwGc11DIe776Cr6Hl6HR0mx+Y7RtnREja/9YD1iHUSvHZN69UD2W9ALPnwLSlQOMPkkIiIionKng109HB8wBS2tHYXYg6QY9Dm8Fgcf38xXXyQSwbTLONRacgv6DbsIcWVqPKI3DMeLdYOR9Sp/4kpEpYfJJxERERGVS3aG1eDbawzGunYUYmlZmZh4Zjdmnz+ADEVWvmO0rWrB/ms/WH+yNu9b0Cv7ET6nMVIu7SmVvhNRfkw+iYiIiKjc0hZLMK9lb/zW5RNU09ET4t73L2DQkV8RnhKf7xiRWAzTruNRa8lN6DfoLMQVKS/xYr0Xnq8bwregRGWAyScRERERlXs9HF1wrP8UNLG0F2K34qPQ69AaHA8PKfAYbavasP/mJKw+Xg2RjoEQT728F09nu3JFXKJSxuSTiIiIiCoEB2Nz7O89DiMbtBFirzJlGB2wHYsu/Q25UpHvGJFYDLNuE+G45Ab06+d+vqtMjUf0xk/w/JeBkCdGlUr/iao6Jp9EREREVGHoSrSwtM0ArO80FIZaOkJ8U8hZfHh0I56nJhV4nI51HdjP8M9+C/raXNC0G38jfHZjJJ/5jW9BiUoYk08iIiIiqnD6OzXB0f6T0cDMVohdjYtAj0OrcToqtMBjct6C1lpyCwYur+0Lmp6MmK1jELWiB+RxT0q870RVFZNPIiIiIqqQ6lSzwuG+EzCkXgshlpghxScntuLHayegUCoLPE7bqhZqTPeDzaebINavJsSlIf54OrcJEk+uheoNxxLRu2PySUREREQVlr6WDn5q/yFWtv8QehJtAIAKKvxyMwBD/bYgVppS4HEikQjVOn0Ox2W3Ydi0rxBXZaQhbueXeLbcA5nRBb9BJaJ3w+STiIiIiCq8wfVa4HDfiahTzUqIBUc/Rs9DqxH8IuyNx2mb1YDdlwdgO24HxEYWQjw99CzC5zZFwtEfoSpgP1EiKjomn0RERERUKTQ0t8WRfpMwoHYTIRabngIvvy1YfTMASlXBn9KKRCKYvDcUtZbdgVGrj4S4KisDL31nImJxW2RE3i7x/hNVdkw+iYiIiKjSMNLWxdpOXljWZiB0xBIAgFKlwg/XTuDjE1sRl17wZ7gAoGViDbsJPqg+eS8k1XIXMsp4ehXhC1vi5V/fQpWVWeLXQFRZMfkkIiIiokpFJBJhRIP3cKDPeDgYmQvxoOcP0ePgapx9/uitxxs3H4Ray+7ApP3I3KBCjoSDixA+vznSHwaXVNeJKjUmn0RERERUKblZ2uNY/8no7egqxGLTUzDU7zesuH7yjavhAoDE0Ay2o39Hjf8dgZZ5TSGe+fwuIpd1RIz3JCjSX5Vo/4kqm0qVfD558gTTp0+Hh4cH3Nzc0L17d/z8889IS0srclsxMTFYsGAB3n//fTRu3BgeHh5YvHgxEhIS1Dr+ypUraNiwIbZt21bkcxMRERGRZlTT1cdGj+FY+t4A4TNcFVRYdcMfQ/w240Va8luPN3TrCcelt1Cty/jcoEqF5IBfET7bFanXDpZk94kqlUqTfN66dQuenp44fPgwrKys0LlzZ0ilUmzYsAFeXl5ISXnz9/3/FRERgQ8++AA+Pj7Q09ODh4cHJBIJduzYgYEDB+LFixdvPf7JkyeYOnUqlNwfioiIiKjMiUQijGzYBof6TkBtE0shfiH6CXocXI2AZw/eerxE3wQ2I9ai5pwg6Ng1EuJZiVF4vtoTz9d+hKykt//7kIgqSfIpl8sxdepUSKVSLF++HL6+vli9ejVOnTqFLl26IDQ0FD/99JPa7c2YMQNxcXGYPHkyDh8+jNWrV8PPzw9eXl6IiYnB/Pnz33js+fPn8fHHHyMuLk4Tl0ZEREREGuJqUQPH+k/GQKemQiwhIw0jTm7F0svHIFcq3nq8fr12cPj2CiwGLYRIS0eIp17Zj6ezXJB0ehNUfPlA9EaVIvk8cuQIoqKi0K5dOwwaNEiI6+npYdmyZTAwMMDevXvx6lXh3+VfvnwZ165dg5OTEyZMmCDEJRIJ5s6dCzs7OwQFBeHRo7wT1WNiYjBv3jx89tlnSEpKgp2dneYukIiIiIg0wkhbF2s6DsGKdh9AT6ItxH+9cwYfHN2IZ6mJbz1erK0LiwHz4LDoGvSd2wtxZXoyYreNx7PlXZD5/H6J9Z+oIqsUyWdgYCAAoHv37vnKzMzM0Lp1a8jlcpw9e1bttrp16waxOO/waGtro2vXrgCAgICAPGU///wzfH19Ubt2bWzfvh2tW7d+p2shIiIiopIlEong5dwSR/pNgrOptRC/FheBHgd/wfHwkELb0LVrCPuZgbAeuR5ifRMhnh76D8LnuyP+4BJuy0L0H5Ui+QwNDQUA1K9fv8DyevXqAQAePHj79/zqtFW3bt0C26pduzaWLFmCQ4cOoVmzZup1nIiIiIjKTH0zGxzpNwle9VoIseRMGUYHbMf8C4eQoch66/EisRimHmNRa1kIjJrnfn2nyspE/F8LEL6gBdIfnS+x/hNVNFpl3QFNiImJAQDY2NgUWG5lZQUAiI2N1Vhb/53TOXbsWPU6+wY+Pj7w9fVVq25YWFixzkVERERE2fS1dLCi/YdoW70OZgX/hbR/31b+fi8Yl2PDsb7z0DyLFBVEy8wOdpP3IvXqAcRsnwxF0nMAQGZUCCKXdkA1j3Gw/GgZJK+9ISWqiipF8pmeng4ge45nQXLiUqm0VNsqiri4OISEFP6JBxERERFpnmcddzS1tMe407twNyF75drb8VHodWgNfmjrif5OTQptw6j5QOg39MDLvbORHLAhO/jvtiyp1w7AethKGLX8CCKRqCQvhajcqhTJp0QiUWtbE5VKpVZb6tD0NipWVlZwcXFRq25YWBhkMplGz09ERERU1TlVs8KhPhOw+PIR/HH/AgAgVZ6BCWd249yLMCxs3Q/6WtpvbUNiUA02I9bBpM0wxGwdi8zn9wAAiqQXeLF+KAxct8J6xFroWNcp8eshKm8qRfJpaGiIpKQkZGRkFFiek6gZGBio1RaAQtvKqacpXl5e8PLyUquup6cn35ISERERlQA9LW0sbTMQbarXwddn9yJFnv1vwp2hl3A1LgLrOg1FfbOCp2e9LntblqtIPPoDEg5/B1VWdjvSOycQPrsxzPvNhlnvryHW1i3R6yEqTyrFgkPW1tmrlL1pb82cuZ459dRp603zQ4vSFhERERFVTH1rNcbxAVPQxNJeiN1PjEbvw2vgff+CWl/U5WzL4rj0Fgxc3xfiqqyM7AWJ5jWF9G7AW1ogqlwqRfKZszLtw4cPCyzP2ZPzTSvYFtTWf/fxfJe2iIiIiKjicjS2wF+9x2GMS+5+nhmKLMw+fwCjA7YjQZamVjs6NnVRY9oxVB+/CxLT6kJcHh2KZz+8jxcbP0FWcozG+09U3lSK5LNz584AgBMnTuQrS0xMxMWLF6Grq4s2bdqo3dbJkyfz/UZLLpfD398/Tz0iIiIiqrx0JFqY36ovvN//FJZ6RkLcL+Iu3j/4C849L/iFxX+JRCIYtx6CWstCYNptEiDK/Wd4yvldeDqzIZICfoVKqdD4NRCVF5Ui+ezWrRtq1KiB06dPw8fHR4jLZDLMmTMHUqkUgwcPhrm5uVAml8sRFhaGsLAwyOVyIe7u7g43NzeEhoZi1apVQgKqUCiwdOlSvHjxAh4eHnB2di69CyQiIiKiMtXFvj5ODvwSnWrk/hswRvoKXn6/YdmVY5CrmTRKDKrB+uNf4LDgAnRrtxTiyvRkxHpPQsTidpA9vabx/hOVByKVOh+sVwCXL1/G6NGjIZPJ4OLiAnt7e1y/fh2xsbFwdXWFt7d3nkWCnj17hq5duwIA/P39YW+f+z1/WFgYhg8fjsTERDg5OaFevXq4d+8eIiIiYG9vj927dxc653PmzJn466+/MGvWLIwaNUqj15qz4JCLiwv279+v0baJiIiI6M2UKiV+vxuMZVeOIfO1hLOJpT3WdvIqdE/Q16mUCiQHbsLLvXOgTE/OLRCJYdptIiw8F3FvUKpUKsWbTwBo2bIl9uzZgx49euD58+c4ffo0jI2NMWnSJPzxxx9FWp22Tp062LdvHzw9PZGSkoLAwECIRCKMGDECvr6+XGyIiIiIqIoSi8QY7dIeh/pOQJ1qVkL85stn6HlwNfY8vKrWYkQAIBJLYNp1PGp9dxfG7w3NLVApkXRyDZ7OaoSUi3+q3R5ReVdp3nxWJXzzSURERFT2pPJMLLz0N3aFXsoTH+DUBN+1GQQTHb2itXfXHzHekyCPDs0T12/QGdbDV0G3ZuNi95moLFWaN59ERERERKXJQFsHP7TzxEaP4aimoy/EDz6+iR4Hf8HV2PCitdeoKxwX34DFoG8h0srd/zP9/mmEL2iO2B1fQpGWqLH+E5U2Jp9ERERERMXQp1ZjnBzwJVrb1BZikamJ8Dy6Eatu+EOhVKrdVvbeoHPhuOw2DJv0yS1QKpB0ai2ezmyApNObuSouVUhMPomIiIiIisnOyBS+Pb/A1+7vQ/LvNioKlRIrrp/E4OObEJWaVKT2dKzroMZXh2D31WFo29QV4oqUl4jdNg4Ri9og/dEFTV4CUYlj8klEREREpAESsRhfNu2K/b3HoqaRmRC/GPMU3Q+uwt9Pbxe5TaMmveG45BYsP1wGkW7uApoZT68ickk7RG/+FFlJ0RrpP1FJY/JJRERERKRBza0d4TfgSwx0airEkjNlGBe4E1+f24c0eUaR2hNr68K87wzUWn4Pxu955Sl7dc4bT2c1ROLxn6HKkr+hBaLygcknEREREZGGmejoYU3HIVjV4SMYaukI8d2hl9H94GpciSnaYkQAoG1WA9XH7YT9rEDo1HQT4sr0V4jzmY7w+e5ICzmlkf4TlQQmn0REREREJUAkEuHDus1xfMAUNLG0F+LhKfHwPLYBy68eR6Yiq8jtGtTvCMeFl2H98RqIDUyFeObze4j6sQeer/kQ8rinGrgCIs1i8klEREREVIJqm1jiQJ/xmOLmAbFIBABQqlRYe+s0+v69DvcTiz5nUyTRgmm3Caj9/QNU6/wF8G+7AJB69S88ndUIcXtmQ5H+SmPXQVRcTD6JiIiIiEqYtliCb5r3wF+9x6OWsYUQv5vwAr0PrcGG20FF2pIlh8TYEjajNsBhwUXo1W0jxFVZGUg88j2efuOMpIANUL3DG1YiTWPySURERERUSppbO+DEgC8xosF7QixTqcCSK0cx+PhmRKQkvFO7erWao+bsINh+sRUS0+pCXJESh1jviQif5460W8egUqmKfQ1E74rJJxERERFRKTLQ1sGyNgOx/f1PYaNvLMQvxjzB+wdWwSf08jsliSKxGCbtRqD29w9gPmA+RDoGQlnm87uIWtkXUSt6IiOy6Fu+EGkCk08iIiIiojLgYV8fpwZORb9auSvXpmVlYvq5ffjc3xsv01PfqV2xriEsBy1Are/vw6TDqDzzQaUhpxA+vxlito7l/qBU6ph8EhERERGVETM9Q/zqMQxrO3mhmo6eED8ReQ9dD/wMv/CQd25b26wGbD//DQ4Lr0C/YZfcApUSyWe24MnM+og/tAzKDGlxLoFIbUw+iYiIiIjK2ECnpjg18Ct0sqsnxOJlafg8YDv+988epGTK3rltPcemsP/mBOy+PABt2/pCXCVLRfz+eXg6qyFendsO1TsseERUFEw+iYiIiIjKgeqG1bCj+2dY8t4A6Em0hbjvo6t4/+AqBL8Ie+e2RSIRjNz7odaSm9n7gxrlrriblfAM0ZtHIWLRe5DeP1OsayB6GyafRERERETlhEgkwqiGbXBiwBQ0tawpxJ+lJmHI8S1YdOlvyLLk796+lva/+4OGwqzXdIi0dISyjKdX8Wx5Fzz7qTdkT68V6zqICsLkk4iIiIionHGqZoUDfcZhuvv70BJl/5NdBRU2hZxF78NrcOvls2K1LzE0hdWQ71Hru7swavVRnjLpbT9ELGyJ5+uGIPP5/WKdh+h1TD6JiIiIiMohLbEEU5t2xcG+E1C3mpUQD02KRd+/12Hp5WNIL8ZbUADQtqoNuwk+qDnnH+jVa5enLPXyXjyd0xjRv42GPD6iWOchAph8EhERERGVa00s7XGs/xSMbpSbHCpVKvx65wzeP7AK56MfF/sc+vXaoubsM7D76jB0azbJLVAp8eqfrXg6oz5id36FrFexxT4XVV1MPomIiIiIyjl9LW0sbN0Pvj2/gKNx7mJBT1Pi8dGxTZgZ/BdeFWNFXODfRYma9IbDt1dQffwuaNvkrryryspE0snVePJ1XbzcNx+KtKRinYuqJiafREREREQVRNvqdXBq4JcY59oRYpFIiO94cBFd/lqJU5H3in0OkVgM49ZDUGvpbdh8uhFa5vZCmSojDQmHl+LJN3WRcOQH7hFKRcLkk4iIiIioAtHX0sHclr1xuO9ENDCzFeLR0lcYdeoPTDyzG/Gy1GKfR6SljWqdRqPW8gewGvoTJMaWQpkyLREv98zCk2/qIcn/V6iyMot9Pqr8mHwSEREREVVATSztcbTfJHzt/j50xBIhfvDxTXTevxJ/hd2ASqUq9nnEOnow6zEVtX94BItBCyHWMxbKFMnRiN0+CU9mNkTS6U1QyjOKfT6qvJh8EhERERFVUDoSLXzZtCuOD5iC5lYOQjwxQ4rJQT4YdeoPPE9N0si5xPrGsBgwD7V/fASzntMg0tYTyrJePkXstvF4+k09JJ5cw89xqUBMPomIiIiIKjhnUxvs7z0O37buB30tbSHu/+w+uhz4GdvvX4BSpdTIuSTGlrDy+gG1fghFtc5jAImWUJaVGIW4nVPxZLpT9pzQ9BSNnJMqB5FKE+/iqVR5enoiJCQELi4u2L9/f1l3h4iIiIjKkciUBMwI/gtBzx/mibe2qY0f23nC6bU9QzVBHvcECUd/xKt/tuab+yk2NIPZ+1Ng2m0SJEbmGj0vVTxMPisgJp9ERERE9DYqlQp7H13Dwkt/IzkzXYjrSrQwzf19jHFpD63X5olqgjwxConHfkLy6U1QvXZOABDrGaNal/Ew6/kVtEysNXpeqjiYfFZATD6JiIiISB2x0hTMu3gIR57ezhNvbFEDP7T1RGPLGho/Z9arWCSd+AVJp9ZBKcv72a1IRx/VOn0Bs97ToW2m+XNT+cbkswJi8klERERERXH06R3MvXAQsa/NwRRBhOH1W+GbZt1hrmeo8XMq0hKRdGotEk/8AmVaYp4ykZYOTNqPgnmfb6BtVVvj56byiclnBcTkk4iIiIiKKilDisWXj+LPh1fyxKvp6GG6e3d80qC1xj/FBQBlegqSAjcg8fhKKF7F5i0UiWHUfBDMuk+BXr12EIlEGj8/lR9MPisgJp9ERERE9K7OPn+EuRcO4lFyXJ54fVMbLHqvP9pVr1Mi51VmSJEc9DsSj/6ArMSofOW6js1g1n0yjFoNgVhbt0T6QGWLyWcFxOSTiIiIiIpDrlRg271grLx+CinyjDxlfWs1xtyWvWFvZFYi51bKM/DqnDcSj/wAedzjfOUSExtU8xgLU4+x0DK1LZE+UNlg8lkBMfkkIiIiIk2IS0/B8qt++T7F1ZNoY6JbJ4xz7ZRn31BNUikVSLvxNxJPrkH6vcD8FSTaMG49JPuT3FrNS6QPVLqYfFZATD6JiIiISJOux0Vi/sVDuB4XmSdub2SKeS37oLeja4nOx8yIvIXEk2uQcn4XVHJZvnK9eu1g9v5kGDUfBJFEq8T6QSWLyWcFxOSTiIiIiDRNqVJi36PrWHb1GOLSU/OUtateB9+27ocGZiX7Gawi5SWSTm9Gkv96KJKe5yvXMq8J064TUK3TaEiMzEu0L6R5TD4rICafRERERFRSUjJlWHUzAL+FnEWWSinEJSIxRjZ4D/9z7wZTXYMS7YMqS46UK/uQdHINZGEX8pWLdPRh1HwQTNqNgEGjLhCVwCq9pHlMPisgJp9EREREVNIeJcViwaW/cSYqNE/cXNcQM5r3gFe9FpCIxSXej/THl5B0YjVSLu8BFFn5yrXM7WHcZjiqtRsBHbsGJd4fendMPisgJp9EREREVBpUKhVORd7Dwkt/IzwlIU9ZY4samN+qD9rYOpVKX7ISnyMpYAOST2+CIiWuwDp6Tq1h0v4TGLcaws9yyyEmnxUQk08iIiIiKk2yLDm23D2LX24GID1LnqespbUjJrp1Rhf7+hCLSv5NqFKegbSbR/Dq7B9Iu3UMUCry1RFp6cCwaT+YtB8BQ9ceEJXQir1UNEw+KyAmn0RERERUFp6nJWPZlWM48PhGvrL6pjaY4NYZ/Wu7QbuU5mBmvYpFyvndeHX2D2RE3iywjsTEGsZthqFa+5HQrelWKv2iglWq5PPJkydYt24drl69ivj4eNja2qJXr14YM2YMDA0Ni9RWTEwM1q9fj+DgYERHR8PS0hJdunTBxIkTYW5e8Cv827dvY/369bhz5w5evXqFmjVrYsCAARg1ahS0tTX32xYmn0RERERUli7FPMX3V/1wMeZJvjJ7I1OMdekIL+cW0NfSKbU+ZUTcRPI5b6Sc3wXFq9gC6+g6NIVR84EwbNIbug7uEJXCnFXKVWmSz1u3bmHkyJGQSqVo0qQJbG1tce3aNcTFxcHZ2Rm7du2CsbGxWm1FRERg2LBhwrG1a9fG3bt3ERkZCRsbG/z555+oXr16nmP8/f0xZcoUKJVKtGjRAiYmJrh8+TKSk5PRpk0bbN68WWMJKJNPIiIiIioPrsaGY/3tM/CLuJuvzFzXEJ83aouRDduU+Oq4r1NlyZF2xw+vznoj7cZhqLIyC6wnqWYLQ7eeMHTrDQOXbpAYVCu1PlZVlSL5lMvl6NGjB6KiorB8+XIMGjQIACCTyfDVV18hICAAQ4cOxcKFC9Vqb+jQobh27RomT56MSZMmAQAUCgUWLVoEHx8fdOzYEZs3bxbqJyUloUuXLsjMzMSmTZvQtm1bIT5mzBjcvHkT06dPxxdffKGR62XySURERETlSWhSDH69fQZ/hd3Isz0LABhq6WB4/VYY7dIBdoalm+ApUhOQcvFPvDrnDdnjS2+uKNGCvnMHGLr1gmGT3tCp3gAikeidz6tSZEGVlQGFNAnKtESIDc0gMTCFSEsXIonWO7db0VWK5PPAgQOYMWMG2rVrh99//z1PWWJiIrp06QK5XI7g4GCYmJi8ta3Lly/j448/hpOTE44cOQLxa6/i5XI5unfvjufPn+PIkSOoW7cuAGDt2rVYs2YNBg8ejMWLF+dpLywsDL1794aVlRWCgoLytPeumHwSERERUXkUlZqEzSH/YGfopXwLE2mLJfCs444JjTuhTjWrUu9bxvN7SLt2EKk3j0L26DzwnyT5ddpWtWHg1gtGTXpDv0FniHX01T6PMiMNqdcPI/Hoj8iIuCHEdR2awqz31zBy7wexbtGmBFYWleIj58DAQABA9+7d85WZmZmhdevWkMvlOHv2rNptdevWLV+iqK2tja5duwIAAgIChPjp06ffeP46derA2dkZcXFxuH37tnoXRERERERUAdUwMsXC1v1w6aOZ+F/Tbnk+t5UrFfjz4RV03r8SXwRsx424yFLtm65dQ5j3nQmHOUGosyYatuN2wLjNMIiNLPLVlcc9QbL/ekSt7IuwSVaIWtkXL/9aiJSLfyIj8haUmbICz6HMSEOcz9eI3jA8T+IJABkRNxC9YTji/vwGyoy0krjEcq9SvPMNDc3e+LZ+/foFlterVw+BgYF48OABevfuXay2ct52PnjwQIg9fPiw0POHhobiwYMHaNKkyVvPT0RERERU0ZnpGeJ/7t0wzrUjdoVewsY7/+CFNBkAoIIKx8JDcCw8BO2q18FXTbvivVLaKzSHxMgCJu8Nhcl7Q6FSKiB7fAlpN48i7dYxZIRfz1NXlZmOtFvHsrd1ySESQ9uqNnTsGmb/V70BdGydkfHiPpIDN7713MkBG6BfvyOMW3xQ5T7BrRRXGxMTAwCwsbEpsNzKKvu1fmxswatevUtbcXHZG9smJSVBJpNBLBbD2tq62OcnIiIiIqosDLR1MNqlPUY0eA8HH9/E+ttn8DA599/E516E4Xz0Y+zvNQ4tbBzLpI8isQT6ddtAv24bWH6wGFmJz5F2KzsRTQs5BZUsNf9BKiXksWGQx4Yh7cbfRT5n4tEfYdS0L5PPiig9PR0AoKenV2B5TlwqlWq8rcLqq3t+Hx8f+Pr6Fto/IHseKRERERFRRaEj0cJH9Zrjg7ruOBlxD+tun8G1uAgAgFKlQmRqYpkln/+lZWaHap1Go1qn0VDKMyB7eBbSB/8g8/k9ZL64j8wXDwCFvPCG3iIj/DoU0qQqN/ezUiSfEokESuWbJwznUGdtJYlEvQ1xc85XlAWE3nb+uLg4hISEqN0WEREREVFFIxaJ0cPRBT0cXcq6K2oRa+vCoFFXGDTqWmjdjGd3ED5X/Sl2SmkSYFajGL2reCpF8mloaIikpCRkZGQUWC6TZU8INjAofH8hQ8Ps3z4U1lZOvcLqq3t+KysruLio95fw2bNnMDAwQO3atdWqT0REREREJUtsaFa0+gamJdORcqxSJJ/W1tZISkpCXFwcqlevnq88Z67lm+Zk/retkJCQN87P/G9bRkZGMDIyQmpqKuLj42FhkX+1LHXO7+XlBS8vr0L7R0RERERE5Y/EwBS6Dk3zrXJbEF1Hd0iqYPJZKbZayVllNmfV2f969OhRnnrqtJVzjDptOTs7a+z8RERERERU8Yi0dGHW+2u16pr1/hoiLd0S7lH5UymSz86dOwMATpw4ka8sMTERFy9ehK6uLtq0aaN2WydPnsw3R1Mul8Pf3z9PvcLOHxYWhtDQUFhaWsLV1VWNqyEiIiIioopGJNGCkXs/VPMY+9Z61bqMq5Ir3QKVJPns1q0batSogdOnT8PHx0eIy2QyzJkzB1KpFIMHD4a5ublQJpfLERYWhrCwMMjluatVubu7w83NDaGhoVi1apWQgCoUCixduhQvXryAh4eH8LYTADw9PWFkZARfX18EBgYK8aSkJMyePRsAMHr0aGhpVb0bjIiIiIioqhDrGsLK60fYjt8FXYemecp0HZrCdvwuWA35ocqtcptDpFJnCdgK4PLlyxg9ejRkMhlcXFxgb2+P69evIzY2Fq6urvD29hYWBwKyF+3p2jV71Sp/f3/Y29sLZWFhYRg+fDgSExPh5OSEevXq4d69e4iIiIC9vT12796db/7mkSNHMH36dKhUKjRr1gzm5ua4fPkykpKS4OHhgbVr1zL5JCIiIiKqAlSKLKiyMqCQJkEpTYLYwBQSA1OItHSr5BvPHJUm+QSA0NBQrF27FpcuXYJUKoW9vT169eqFTz/9FEZGRnnqvi35BICoqCisXbsW//zzD5KTk1G9enV06tQJ48aNK3BRIQC4cuUKNm7ciBs3biArKws1a9aEp6cnhg0bBh0dnZK5aCIiIiIiogqgUiWfREREREREVD5VijmfREREREREVL4x+SQiIiIiIqISx+STiIiIiIiIShyTTyIiIiIiIipxVXed3ypo2rRpePLkSVl3g4iIiIiIyonatWvjp59+KpVzMfmsQq5evYoXL16UdTeIiIiIiKicSEhIKLVzMfmsQqRSKQBAT08PderUKePeVB5hYWGQyWQcVw3juJYMjmvJ4LiWDI5ryeC4lgyOa8nh2JaMnHHNyRFKA5PPKsTe3h7JycmoU6cO9u/fX9bdqTQ8PT0REhLCcdUwjmvJ4LiWDI5ryeC4lgyOa8nguJYcjm3JyBlXe3v7UjsnFxwiIiIiIiKiEsfkk4iIiIiIiEock08iIiIiIiIqcUw+iYiIiIiIqMQx+SQiIiIiIqISx+STiIiIiIiIShyTTyIiIiIiIipxTD6JiIiIiIioxDH5JCIiIiIiohLH5JOIiIiIiIhKnFZZd4BKz+DBgxEXFwcrK6uy7kqlwnEtGRzXksFxLRkc15LBcS0ZHNeSwXEtORzbklEW4ypSqVSqUjsbERERERERVUn87JaIiIiIiIhKHJNPIiIiIiIiKnFMPomIiIiIiKjEccGhCubgwYPYu3cv7t+/j/T0dFhYWKBNmzYYM2YMnJyc8tSdMWMGDhw48Ma2hg8fjvnz5+eJJScnY8uWLTh58iSeP38OExMTtG/fHhMnTkTNmjVL4pLKBaVSiT///BN79+5FWFgYRCIR6tSpg4EDB8LLywtaWvn/qhw9ehTe3t54/PgxFAoFGjRogBEjRqBHjx4FnkMmk8Hb2xuHDx9GZGQk9PX10bJlS4wfPx4NGzYs6UssE0UdV96z72bKlCnw8/PDd999B09Pz3zlwcHB2Lx5M+7fvw+ZTAYnJyd4eXnhww8/hEgkylc/KysL+/btw59//omnT59CS0sLjRs3xhdffIH33nuvNC6pXHjbuK5evRrr1q1747GdO3fGxo0b88Sq4jMAAC5cuICRI0e+sdzAwADXr1/PE+PztXBFHVc+X9WXkJCATZs2ITAwEM+fP4eenh7c3NwwZswYtG7dOl99PmPVU5Rx5TO2cF26dEFUVFSh9Vq1aoXt27cLfy7r+5XJZwWhUqkwffp0/P3339DW1oarqyvMzc1x//59/PXXXzh+/Dh+/fVXtGnTRjgmJCQEANCnTx+Ixflfcru5ueX5c2JiIoYPH46wsDA4ODigc+fOePLkCf766y+cPHkSO3bsqJR/eQFg5syZOHjwIPT09NCsWTNoa2vj2rVrWLx4Mfz8/PDbb79BR0dHqP/DDz/gt99+g4GBAVq3bo3MzExcunQJU6ZMwYQJE/Dll1/maV8mk2H06NG4fPkyrK2t0bFjR7x48QJ+fn4ICAjAr7/+ig4dOpT2ZZe4oo4r79mi27NnD/z8/N5YvnPnTixatAja2tpo3bo1tLW1ceHCBcydOxdXrlzB999/n6e+UqnEN998gyNHjqBatWpo27YtkpKSEBwcjHPnzmHx4sX46KOPSvqyylxh45pzr3p4eMDIyChfeaNGjfL8uao+A4DcsWrcuDFq1aqVr1xXVzfPn/l8VU9Rx5XPV/WEhYVh5MiRiIuLQ40aNdCpUyc8e/YMZ8+exblz57B27Vp069ZNqM9nrHqKOq58xhauW7duSEhIKLBMqVTi+PHjUCgUcHV1FeLl4n5VUYVw4MABlbOzs6p9+/aqBw8eCPGsrCzVypUrVc7Ozqq2bduq0tLSVCqVSiWVSlUNGzZUtWvXTu1zTJs2TeXs7KyaM2eOKisrS4j/+uuvKmdnZ1Xfvn1VCoVCcxdVTuSMrYeHhyoqKkqIJyQkqAYMGKBydnZWbd68WYifO3euwPr37t1TtW7dWuXs7Ky6ceNGnnPk/H80evRoVXp6ep5z169fX9WmTRtVSkpKCV5l6SvquPKeLbrHjx+rmjZtqnJ2dlY5Ozur9u3bl6c8LCxM1aBBA1WLFi1U9+7dE+JRUVGqbt26qZydnVVHjhzJc4yvr6/K2dlZNWjQIFVSUpIQDw4OVjVu3FjVuHHjPP9/VkaFjatKpVK1a9dO1bBhQ5VUKlWrzar4DMjx1VdfqZydnVVBQUGF1uXzVX1FGVc+X9Ujl8tV/fr1Uzk7O6uWLVuW57r37NmjcnZ2VjVv3lyVkZGhUqn4jFVXUcdVpeIztrhyxmPkyJHCeJeX+5VzPiuIvXv3AgCmTZsGZ2dnIS6RSDB16lTUq1cPL1++RHBwMADg/v37+X7b8TaRkZHCbzVmzZoFiUQilI0bNw5NmzZFaGgo/vnnHw1eVfnw119/AQC++uor2NnZCXEzMzOMGTMGABAUFCTEN2zYUGD9Bg0aYOrUqQCA33//XYinpaVh+/btkEgkWLRoEfT09ISyAQMGoHfv3oiPj8fBgwc1f3FlqKjjynu2aDIzMzFt2jSIxeJ8vwHOsXnzZiiVSnz++edo0KCBELezsxM+r3v9XgUgfMY0d+5cVKtWTYi3adMGI0eOREZGBnbs2KHpyyk31BnX2NhYxMXFoU6dOtDX1y+0zar6DMiR8wZDnb/bfL6qryjjyuerek6ePIkHDx6gZcuW+a77ww8/RIcOHWBiYoK7d+8C4DNWXUUdVz5ji+fcuXPYuHEjzM3N8dNPPwnjXV7uVyafFYSJiQnq1KmD5s2b5ysTiUSoXbs2gOy/sEDRfigB2UmAUqlE+/btYWhomK+8Z8+eAICAgIB36n95tmnTJhw+fDjP5x45lEolAEBbWxsAkJqaiitXrkBbWxtdunTJV7979+4QiUTCeALAlStXkJaWhsaNG6N69er5jskZ28DAQI1dU3lQlHEFeM8W1c8//4yQkBDMnz+/wPsKAE6fPg0g+778r7Zt28LExAS3b9/Gy5cvAQCPHj1CZGQkrKys0KxZs3zHVNZ79XXqjGtR79Wq+gwAsp+Z4eHhqFGjBszMzAqty+ereooyrgCfr+o6duwYAGD06NEFlm/ZsgUBAQFo2rQpAD5j1VXUceUz9t1lZmbi22+/hUqlwrx582BhYSGUlZf7lXM+K4i3TbpWKBTCX9Scv3Q5f5ZIJJg2bRquXbuG+Ph41KxZE/3798eoUaPyzAcJDQ0FANSvX7/Ac9StWxcA8ODBg+JfTDmjo6OT521yjrCwMKxZswYAhMVGwsLCoFAoULNmzQJ/IJubm8PS0hJxcXGIiIhArVq1hDGramNblHEFeM8WRXBwMLZu3Yo+ffpgwIABBc5NfPnyJRISEqCrqyv8cup1EokETk5OuHHjBh48eABLS0u1xlQkEiE8PBwZGRn55pRVdOqMK5B7r5qYmGDevHm4cOECoqOjYWtrix49emDs2LEwNjYW6lfVZwAA3Lt3DyqVCo6Ojli/fj2OHTuGiIgIGBkZoW3btpgwYYJwf/L5qr6ijCvA56u67ty5AwBo2rQpkpKScPToUdy/fx9aWlpo0aIFevToIbxF4jNWfUUZV4DP2OL47bffEB4ejrZt26J3795CvDzdr0w+K4Fdu3YhKioKZmZmwqpTOX9xV61aBTs7O7i4uODly5cICQnBypUrERAQgK1bt8LAwAAAEBMTAwCwsbEp8BxWVlYAgLi4uJK+nDI3Y8YMhIWF4c6dO9DX18esWbPQp08fAIWPE5A9VnFxcYiLi0OtWrWEt9HW1tYF1s+J5/ymqbJ627gCvGfVlZCQgG+++Qa2trZYuHDhG+vljI+VlVWBq9fllAG5Y5RzzJvuVV1dXZiYmCA5ORnx8fF5Pous6NQdVyD3Xt22bRvMzc3h7u4OW1tb3LlzB5s3b8bJkyexfft2YRyr8jMgZ6yCg4Nx9epVtGzZEtWrV0dISAgOHTqEU6dOYcOGDWjdujWfr0VQlHF9vT6fr2+WmZmJqKgo6OrqIiQkBNOmTUNiYqJQvnPnTri4uGDDhg2wtrbmM1ZNRR1XgM/Yd5WSkoItW7YAAP73v//lKStP9ys/u63gzp8/jx9++AFA9nxQfX19ZGRkICwsDED2vBl/f3+sXbsWPj4+OHjwIOrWrYsbN25g+fLlQjvp6ekAkOc7+dflxKVSaUleTplLTU3FgQMHcPv2bahUKohEIkRERCAtLQ1A7vW/bQ5Czm9+cuoWdkxOfaVSKfz/UNkUNq68Z9U3e/ZsxMfH44cffoCJickb6+WMjzr3anHu78pC3XEFIMxLGjp0KM6cOYP169dj+/btOH78OFq0aIGnT59i1qxZQv2q/AzI+Udks2bN4O/vj99++03YamH48OGQSqWYOnUqUlNT+XwtgqKMK5+v6klNTQWQfa9MmjQJDRo0wL59+3Dt2jX4+PigcePGCAkJwYQJE/LcT3zGvl1RxxXgM/Zd7d69G6mpqejcuTMaN26cp6w83a9MPiuwwMBAjBs3DpmZmRg2bJiw1LGuri7Onz+PI0eOYNy4cXmWVHdychKWUd63b5/wUHj9c4e3yXkwVFY6Ojo4e/Ysrl27hj/++AMODg7YuXMnxowZA5VKpfY4Ablj9S7HVDaFjSvvWfXs3LkTgYGB+Pzzz9GqVau31i1oK4U3UalUAKruvVqUcQWAI0eO4NChQ1iwYEGerYJsbGywYsUK6Ovr4+zZs8I/+KvquALA0qVLcfz4cWzevFn4rTqQ/UyYM2cOGjZsiISEBBw6dIjP1yIoyrjy+aqezMxMAIBcLoeDgwO2bNkCV1dXGBoawt3dHVu3boWlpSVu374Nf39/PmPVVNRxBfiMfRcKhULYy3PChAn5ysvT/crks4Lavn07Jk6cCJlMhk8++STfxtAmJibCN+7/5erqCltbW2RlZeHevXsAIMyvkclkBR6TEy9oHk5loqOjAysrKxgaGuK9997D1q1bYWVlhStXruDMmTOFjhOQ/RYPgPD5UmHH5NQXi8VqrepWERU2rgDv2cI8fPgQ33//PVxcXPLtc1iQkrhXCzqmoivquAKAkZER6tevX+CnS9WrVxdWyb19+zaAqv0M0NHRQe3atQvcp08ikaBz584AsseKz1f1FWVcAT5f1fH6/TF8+HBoaeWdmWZsbIz+/fsDyP7qjM9Y9RR1XAE+Y9/FpUuXEBsbi7p166JJkyb5ysvT/co5nxVMVlYWFi1ahD///BMikQjTpk0Ttq0oiurVqyM6Olp4TZ4zr+NN8zcK+56+sjIzM0OnTp2wd+9e3LlzBx4eHgDePs/lv2NV2NjmfFNvYWFRpN9MVWT/Hdecfyi9TVW/Z1esWIGMjAzo6enl+dwIyP0Ez9fXF8HBwWjZsiV69OgB4O1zXIp6r8pkMiQnJ0MsFud521KRFXVchwwZUmibOQu/qXuvVsVnQI6csUpPTy90nAA+X9X1+riqW78qP1+B7IRHR0cHmZmZsLe3L7BOTjwhIUEYIz5j366o46oOPmPzO378OAAIifx/laf7lclnBSKTyTBx4kScPXsWenp6+P7774Vljl935coV7NmzB9bW1pg2bVqBbb148QJA7l/gnJWsHj16VGD9nHhBq5dWZJmZmVixYgWio6Px448/FrhSV84nH1lZWahbty60tLQQGRlZ4MpeCQkJiI+Ph76+PhwcHACoP7ZvWk2sIirquPKeLVzOD9mrV6/i6tWrBda5fv06rl+/Di0tLQwZMgQ2NjaIiYlBZGQkatasmaeuQqHA48ePAeSOkbpj6ujoWGlWYSzquDZv3hy//fYbxGIxli5dWmD9d71XK9MzAMh+DixZsgTx8fFYtGhRniX/c7w+Vny+qqeo48rnq3okEgnq1auHkJAQIVn5r5x/uFtYWMDU1JTPWDUUdVwfPXrEZ+w7yPmK7PUVbl9Xnu7Xypn+V0IKhUJIPM3NzbF9+/YCE08g+7vrAwcOYPv27UhJSclXnrNktZ2dHerVqwcA6NixI8RiMYKCggp8vZ6z5UDOm7/KQkdHB8ePH4efn1+B+xRlZmYiODgYANC4cWPo6urivffeQ2ZmZoH1/fz8oFKp0LFjR+Fb+ebNm8PIyAg3btwo8MGb89uqyjS2RR1X3rOF2759Ox48eFDgf127dgUAfPfdd3jw4IGwcEjOG+UTJ07ka+/cuXNISUmBi4uL8FtOR0dH1K5dG8+fPxc+Z3pdZbxXizquenp62L9/P/bu3YunT5/ma+/p06e4ceMGDAwM0LJlSwBV8xkA5M71PnXqlDCX63WZmZk4evQogOy/z3y+qqeo48rnq/pynpmHDh3KV6ZSqRAUFAQAwtxwPmPVU5Rx5TO26GJjY/HixQtYWVnlSypfV17uVyafFcSvv/6Ks2fPwsDAAN7e3nBzc3tj3RYtWsDZ2Rnp6emYNWtWnhWoHj58iJkzZwIAJk2aJHxPb2Njgx49eiAhIQELFiyAXC4Xjtm4cSNu3LiB+vXrq/V5ZEUzbNgwAMCyZcsQHh4uxKVSKebOnYunT5/C2dlZuPYRI0YAAJYvX56n/v379/HLL78AQJ5PoXV1deHl5QW5XI5Zs2YJq4gB2Q/i48ePw8LCAh9++GGJXWNZKMq48p4tGcOGDYOWlhZ+/fVX3Lp1S4g/f/4cixcvBgCMGzcuzzE59/fcuXMRHx8vxM+fPw9vb2/o6Ohg1KhRJd/5csre3h6dOnUCAMycOTPPZ2LR0dGYMmUKFAoFPv30U2E+XlV9BgC5z4GffvoJ9+/fF+IymQyzZ89GeHg4WrVqhTZt2gDg81VdRRlXPl/V5+XlBRMTEwQHB2PDhg3CwisqlQqrV6/GnTt34OjoKPxjm89Y9RRlXPmMLbqce++/K9z+V3m5X0WqnDuAyq3k5GR07twZUqkUtWrVeuvNNWDAAHTo0AGPHj3CiBEjEB8fDwsLCzRp0gTp6em4cuUK5HI5RowYgTlz5uQ5Ni4uDkOHDkVkZCRq1KgBV1dXPHnyBKGhoTA1NcXOnTvfuGBBRSaXyzF58mQEBgZCW1sbzZs3h66uLm7fvo2EhATUrFkTW7duzfPbpG+//Ra7du0SflOvUChw8eJFyOXyAufhpqen45NPPsHt27dhYWGBFi1aIDo6Gjdv3oSuri42b94s7MdWWRR1XHnPvrsJEybA398f3333HTw9PfOUbdmyBT/++CO0tLTQqlUr6Orq4uLFi5BKpfDy8sK3336bp75SqcSECRMQGBgIIyMjtG7dGikpKbhy5QpUKhV+/PFH9OvXrzQvr8y8aVxjY2PxySef4OnTpzA2Noa7uzuA7AUfZDIZevTogZUrV+ZZWKMqPgOA7M/qv/zyS5w6dQpaWlpwd3eHmZkZrl27hpcvX8LJyQne3t555gvx+Vq4oo4rn6/qCwoKwuTJkyGTyeDo6AhnZ2eEhoYiPDwcpqam2Lx5c54XAHzGqqco48pnbNFs27YN3333HYYMGYJFixa9tW55uF+ZfFYAJ0+exKRJk9SqO2vWLOE3EHFxcdi4cSNOnz6N6Oho6Ovrw9XVFR9//LHwOdl/JSQkYP369QgICEBsbCysra3RunVrTJgw4a2v8is6pVIJX19f7Nu3Dw8fPoRSqYSDgwO6d++OTz/9FMbGxnnqq1Qq7N+/H7t378ajR4+gq6uLevXq4dNPP33j2EqlUmzevBlHjx7F8+fPYWZmhqZNm2LChAlo0KBBaVxmqSvquPKefTdvSz4BwN/fH9u2bUNISAhEIhFq166N4cOHY8CAAQUuviCXy7Fjxw7s378f4eHhMDIyQqNGjTBu3Di0aNGiNC6pXHjbuKampmLLli04ceIEIiMjoa2tjfr16+Ojjz7CoEGDClylsSo+A4Ds5+XevXuxd+9ehIaGQqFQoGbNmujVqxc+++yzfKsk8vmqnqKOK5+v6gsPD8eGDRsQHByM+Ph4WFpaokOHDhg7dmyBi+bwGaueoowrn7Hq+/nnn7FhwwZ88cUXmD59eqH1y/p+ZfJJREREREREJY5zPomIiIiIiKjEMfkkIiIiIiKiEsfkk4iIiIiIiEock08iIiIiIiIqcUw+iYiIiIiIqMQx+SQiIiIiIqISx+STiIiIiIiIShyTTyIiIiIiIipxWmXdASIiIso1a9Ys7N+//52OdXNzw549ewqtl5WVhffeew/29vY4cODAW+s+e/YMXbt2BQB4e3ujdevWb6x74MABzJo1C0qlEu7u7tiyZQuMjIyKdA1ERFR5MfkkIiIqR549ewZLS8t8calUCqlUCgAFlgNAq1at1DrHtWvXkJKSgk6dOr17R//j9cSzVatW2LBhAwwNDTXWPhERVXxMPomIiMqR7du3FxifN28efH19Ub16dZw+fbpY5zhz5gwAoGPHjsVqJ8fBgweFxLNt27ZYv3499PX1NdI2ERFVHpzzSUREVAGEhIQAABo1alTstoKCgmBqaoqmTZsWu61Dhw5h5syZUCqV6NixIzZs2MDEk4iICsTkk4iIqJzLysrCw4cPARQ/+YyOjkZoaCjatWsHiURSrLZeTzy7dOmCdevWQVdXt1htEhFR5cXkk4iIqJx79OgRMjMzARQ/+dTUJ7eHDx/GzJkzoVAo0KNHD6xevRo6OjrFapOIiCo3Jp9ERETlXM4ntwDg4uJSrLbOnDkDkUiEDh06vHMbf//9N2bMmAGFQoG+ffvi559/hra2drH6RURElR+TTyIionLu3r17AAALCwvY2Ni8czuZmZk4f/48XF1dYWFh8U5tHDlyBN988w0UCgV0dHQwY8aMYn++S0REVQOTTyIionIu581nw4YNi9XO1atXIZVK33mLlaNHj+Lrr7+GQqGAWCxGZmYmZs+eDZVKVax+ERFR1cDkk4iIqBxTKpW4f/8+AM18cgu8+3xPHx8fKBQKjBw5EosWLQIA/PPPP/j999+L1S8iIqoamHwSERGVY0+ePIFUKgWgmcWGzM3N0bhx43du4/PPP8fsQZNW7gAAAjxJREFU2bPx0UcfoWvXrgCAn3/+Gbdu3SpW34iIqPJj8klERFSO5cz3BIr35jMyMhKPHz9G+/btIRa/24//zz77DN98843w5yVLlsDS0hJyuRzTpk1DamrqO/ePiIgqPyafRERE5VjOfE9jY2PY29u/cztBQUEA8M7zPQGgc+fOef5sbm6OJUuWAAAiIiKwYMGCd26biIgqPyafRERE5djdu3cBZC82JBKJ3rmdoKAgiMVitG/fXlNdAwB4eHhgyJAhALK3YNm3b59G2yciosqDyScREVE5ponFhjIyMnDx4kU0adIEpqamGupZrpkzZ6JWrVoAsj/Fffz4scbPQUREFR+TTyIionLq2bNnSEpKAlC8bVYuXryI9PT0d17ltjAGBgb44YcfoKWlBalUiv/973/IzMwskXMREVHFxeSTiIionMr55BYo3ptPTcz3LEyTJk0wbtw4ANmLJP3www8ldi4iIqqYmHwSERGVUznJp76+PpycnN65naCgIFhZWRV7q5bCjB8/Hm5ubgCA7du3w9/fv0TPR0REFYtIpVKpyroTREREREREVLnxzScRERERERGVOCafREREREREVOKYfBIREREREVGJY/JJREREREREJY7JJxEREREREZU4Jp9ERERERERU4ph8EhERERERUYlj8klEREREREQljsknERERERERlTgmn0RERERERFTimHwSERERERFRiWPySURERERERCWOyScRERERERGVOCafREREREREVOL+D6uo5UhN+NOJAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "plt.title(\"Surface tension of water\")\n",
    "sns.lineplot(data=literature, x=\"Temperature (K)\", y=\"Surf. Tension (l, N/m)\", label=\"NIST\")\n",
    "sns.lineplot(data=dft_data, x=\"Temperature (K)\", y=\"Surf. Tension (l, N/m)\", label=\"PC-SAFT (2B)\")\n",
    "sns.scatterplot(x=[cp.temperature / KELVIN], y=[0.0], clip_on=False, color=colors[1], label=\"PC-SAFT (2B), critical point\")\n",
    "plt.ylabel(r\"$\\gamma$ / Nm$^{-1}$\")\n",
    "plt.xlabel(r\"$T$ / K\")\n",
    "\n",
    "plt.xlim(250, 700)\n",
    "plt.ylim(0.0, 0.08)\n",
    "sns.despine(offset=10)\n",
    "plt.legend(frameon=False);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35af1b14",
   "metadata": {},
   "source": [
    "## Concluding remkars\n",
    "\n",
    "Hopefully you found this example helpful. If you have comments, critique or feedback, please let us know and consider [opening an issue on github](https://github.com/feos-org/feos/issues)."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}