{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "aadaacc9",
   "metadata": {},
   "source": [
    "# Your First Hodgkin–Huxley Neuron\n",
    "\n",
    "This example builds a single Hodgkin–Huxley (HH) neuron, injects a constant current, and plots the resulting membrane-potential trace and spikes. It is the simplest end-to-end workflow in `braincell`: define a cell, initialize its state, step it through time, and read out `V` and `spike`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "07d67536",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-25T10:04:15.357023Z",
     "iopub.status.busy": "2026-05-25T10:04:15.356845Z",
     "iopub.status.idle": "2026-05-25T10:04:17.081295Z",
     "shell.execute_reply": "2026-05-25T10:04:17.080385Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "An NVIDIA GPU may be present on this machine, but a CUDA-enabled jaxlib is not installed. Falling back to cpu.\n"
     ]
    }
   ],
   "source": [
    "import brainstate\n",
    "import brainunit as u\n",
    "import matplotlib.pyplot as plt\n",
    "import braincell"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5fef1011",
   "metadata": {},
   "source": [
    "## Define the neuron\n",
    "\n",
    "A `SingleCompartment` subclass holds ion channels grouped by ion. Here we use the classic HH sodium and potassium channels plus a passive leak. `V_th` only sets the threshold used to emit `spike` events for plotting; it does not alter the dynamics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b091c8b0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-25T10:04:17.083966Z",
     "iopub.status.busy": "2026-05-25T10:04:17.083626Z",
     "iopub.status.idle": "2026-05-25T10:04:17.089288Z",
     "shell.execute_reply": "2026-05-25T10:04:17.087681Z"
    }
   },
   "outputs": [],
   "source": [
    "class HH(braincell.SingleCompartment):\n",
    "    def __init__(self, size, solver='exp_euler'):\n",
    "        super().__init__(size, V_th=20. * u.mV, solver=solver)\n",
    "        self.na = braincell.ion.SodiumFixed(size, E=50. * u.mV)\n",
    "        self.na.add(INa=braincell.channel.Na_HH1952(size))\n",
    "        self.k = braincell.ion.PotassiumFixed(size, E=-77. * u.mV)\n",
    "        self.k.add(IK=braincell.channel.K_HH1952(size))\n",
    "        self.IL = braincell.channel.IL(size, E=-54.387 * u.mV,\n",
    "                                       g_max=0.03 * (u.mS / u.cm ** 2))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9eb5f09",
   "metadata": {},
   "source": [
    "## Run the simulation\n",
    "\n",
    "We inject a constant current **density** of `5 uA/cm^2`. `update` advances the cell one `dt`; we record both the membrane potential and the spike flag at each step with `brainstate.transform.for_loop`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2d617687",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-25T10:04:17.091507Z",
     "iopub.status.busy": "2026-05-25T10:04:17.091231Z",
     "iopub.status.idle": "2026-05-25T10:04:20.712955Z",
     "shell.execute_reply": "2026-05-25T10:04:20.712041Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "number of spikes: 8\n"
     ]
    }
   ],
   "source": [
    "neuron = HH(1)\n",
    "neuron.init_state()\n",
    "\n",
    "I = 5. * u.uA / u.cm ** 2\n",
    "\n",
    "def step(t):\n",
    "    with brainstate.environ.context(t=t):\n",
    "        neuron.update(I)\n",
    "    return neuron.V.value, neuron.spike.value\n",
    "\n",
    "with brainstate.environ.context(dt=0.01 * u.ms):\n",
    "    times = u.math.arange(0. * u.ms, 100. * u.ms, brainstate.environ.get_dt())\n",
    "    vs, spikes = brainstate.transform.for_loop(step, times)\n",
    "\n",
    "print('number of spikes:', int(u.math.sum(spikes)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e8efa43",
   "metadata": {},
   "source": [
    "## Plot the membrane potential\n",
    "\n",
    "The trace shows the characteristic train of action potentials driven by the constant input."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "be8c5172",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2026-05-25T10:04:20.715430Z",
     "iopub.status.busy": "2026-05-25T10:04:20.714831Z",
     "iopub.status.idle": "2026-05-25T10:04:20.852623Z",
     "shell.execute_reply": "2026-05-25T10:04:20.851674Z"
    }
   },
   "outputs": [
    {
     "data": {
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/7RmGwU033YTDhw/j119/bVMS5IhTp05hypQp7Z5z9uxZdOvWrY0R3bNnT9vPW9LRPahUKvHyyy/j4YcfRmJiIi666CJMnDgRt99+O5KSkjqUmWVZvP3223j//feRm5tr5xzGxsa2OV/s/3unTp2CVCoVfRyxs/8/qampdo4RwP/fPHLkiNNSpdb/N1tfA4C/DmLfgwTRGSDHgiCIDnE2hpRraoC1ZiNeffVVDBgwwOG51rppZ1HF1tFrKx1NNnKFjuR3hkQicXiOM1ndfR9HsCyLhIQEp43OrY0aMa5Teno6Kisr2z1HyN9v/fr1KCoqwooVK7BixYo2P1++fLmdY7FmzRqPJik5u/6OjrvzN2mPu+66C7/88guWL19ui1z7A1fuwQcffBCTJk3CDz/8gN9//x1PP/00Fi1ahPXr12PgwIHtvv6LL76Ip59+GnfccQeee+45xMTEQCqV4sEHH3SYlRTz/4QYCNUzjo6zLIu+ffvijTfecPg7rR3ZznYNCMKbkGNBEITHWNP80dHRDjMkLdHpdA6XQLlalhQfH4/w8HAcO3aszc+OHj0KqVTa5sHuLjqdzmG5grslVBkZGQCaMzwtaf15cnJy8Mcff2DYsGGiOA0dwXEczpw506FhaY04t/4bOromy5cvR0JCAhYvXtzmZ6tWrcL333+PpUuXQq1W4+DBg8jLy8OECRNs58THxyM6OhoHDx504xP5jkcffRTLli3DW2+9ZVey1BE5OTkdfraMjAzs378fLMvaZS2OHj1q+7k75OTk4OGHH8bDDz+MEydOYMCAAXj99dfxv//9D4BzB/Lbb7/FyJEj8cknn9gdr66udnt0sZASppycHLAsi8OHDzsNYgCO9YzJZEJRUZFbMraWYd++fRg1apRH5VctEet1CMLfUI8FQRAeM2jQIOTk5OC1115DbW1tm5+3HO2ak5MDvV6P/fv3244VFRU5HbnaGplMhrFjx+LHH3+0G8dYUlKCL7/8Epdccgmio6Pd/zAtyMnJwdGjR+3k37dvX5sRuq6SnJyMAQMG4PPPP7ebzLVu3TocPnzY7twbbrgBDMPgueeea/M6FovFow29jkbtLlmyBGVlZRg/fny7vxsdHY24uDj8/fffdsdb92Y0NDRg1apVmDhxIq677ro2X3PmzEFNTQ1++uknAHy2IjEx0a7UzzqJ6eeff3a4db4zRHxfffVVvPbaa/jPf/7TZkJTR0yZMgX79u1zeO9bP9uVV16J4uJiuwlmFosF7777LiIjIzFixAhB71lfX4/Gxka7Yzk5OYiKirIblRoREeHwHpPJZG2u+8qVK1FQUCBIjpZERES4PKlu8uTJkEqlWLhwYZsMSUu5cnJy2tyjH374odOMhRBuuOEGFBQU4KOPPmrzs4aGBrupUq5i3ZtBm7eJQIcyFgRBeIxUKsXHH3+MK664Ar1798aMGTOQmpqKgoICbNiwAdHR0fj5558BADfddBMef/xxXHPNNXjggQdQX1+PJUuW4LzzznPY/OmI559/HuvWrcMll1yC++67D2FhYfjggw9gNBrxyiuviPa57rjjDrzxxhsYN24cZs6cidLSUixduhS9e/du0yDuKosWLcKECRNwySWX4I477kBlZSXeffdd9O7d284pGzFiBGbNmoVFixZh7969GDt2LORyOU6cOIGVK1fi7bffxnXXXeeWDBkZGbjxxhvRt29fqFQqbN68GStWrMCAAQMwa9asDn//zjvvxEsvvYQ777wTgwcPxt9//43jx4/bnfPTTz+hpqYGV111lcPXuOiiixAfH4/ly5fjxhtvxOrVq3HFFVe0idy++OKLWLt2LUaMGGEb7VlUVISVK1di8+bNft1S/P333+Oxxx5Dt27d0LNnT1u038qYMWPaHd/76KOP4ttvv8X111+PO+64A4MGDUJlZSV++uknLF26FP3798fdd9+NDz74ANOnT8euXbuQmZmJb7/9Flu2bMFbb72FqKgoQTIfP34co0aNwg033IBevXohLCwM33//PUpKSuwWAA4aNAhLlizB888/j65duyIhIQGXX345Jk6ciIULF2LGjBm4+OKLceDAASxfvtxukIJQBg0ahK+//hrz5s3DBRdcgMjISKeb17t27YqnnnoKzz33HC699FJce+21UCqV2LlzJ1JSUrBo0SIA/D16zz33YMqUKRgzZgz27duH33//XZSFkLfddhu++eYb3HPPPdiwYQOGDRsGhmFw9OhRfPPNN7Z9MkKvAcCP373pppsgl8sxadIkp4v6CKLT4o9RVARBCMM6EtHRyE2O48ciOho3O2HCBIfnW0dBujputvV5zkaO7tmzh7v22mu52NhYTqlUchkZGdwNN9zA/fnnn3bnrV27luvTpw+nUCi47t27c//73/+cjpudPXu2Q9l2797NjRs3jouMjOTCw8O5kSNHclu3brU7x9l1s36uDRs2tPv5OY7j/ve//3HZ2dmcQqHgBgwYwP3+++9Ox806GuEJB2Mvv/vuO65nz56cUqnkevXqxa1atcrpGN4PP/yQGzRoEKdWq7moqCiub9++3GOPPcYVFhbazmnvb+2IO++8k+vVqxcXFRXFyeVyrmvXrtzjjz9uG13aEfX19dzMmTM5jUbDRUVFcTfccANXWlpq91knTZrEqVQqrq6uzunrTJ8+nZPL5dyZM2e4sLAw7ptvvnF43tmzZ7nbb7+di4+P55RKJZednc3Nnj3bNsbU2d/Zek+VlZXZHZ82bRoXERHh0mdtD+vrO/ty5f6qqKjg5syZw6WmpnIKhYJLS0vjpk2bxpWXl9vOKSkp4WbMmMHFxcVxCoWC69u3b5v/e67eg+Xl5dzs2bO5Hj16cBEREZxGo+GGDBnS5toXFxdzEyZM4KKiojgAttGzjY2N3MMPP8wlJydzarWaGzZsGLdt27Y2o5mF6I7a2lpu6tSpnFarbTN22RmffvopN3DgQE6pVHI6nY4bMWKEbaQxx3EcwzDc448/zsXFxXHh4eHcuHHjuJMnTzodN+tItzrSq1ZMJhP38ssvc71797bJMGjQIO7ZZ5+1G9nsTIe1loPjOO65557jUlNTOalUSqNniYBFwnGdIJdMEARBhCzffPMNbrnlFpSXl9uN4SUIgiACC+qxIAiCIPyKVqvFO++8Q04FQRBEgEMZC4IgCIIgCIIgPIYyFgRBEARBEARBeAw5FgRBEARBEARBeAw5FgRBEARBEARBeAztsWgFy7IoLCxEVFQUbcIkCIIgCIIgQhqO41BTU4OUlBRIpe3nJMixaEVhYSHS09P9LQZBEARBEARBdBry8/ORlpbW7jnkWLTCusU0Pz8f0dHRfpaGIAiCIAiCIPyHwWBAenq6zUZuD3IsWmEtf4qOjibHgiAIgiAIgiAAl1oEqHmbIAiCIAiCIAiPIceCIAiCIAiCIAiPIceCIAiCIAiCIAiPIceCIAiCIAiCIAiPIceCIAiCIAiCIAiPIceCIIhOAcdxKDE0+luMoKXeZEF5rdHfYgQt5bVGmCysv8UIWs5V1YNlOX+LEZRwHIdiPeleb1FnDC3dS44FQQigss6E3XlV/hYjKPls6xkMefFP/Li3wN+iBCWzvtiF4a9swNmKOn+LEnTUNJpx+Wt/YdK7m8GQ8Ss6209X4JKXN+CZnw/5W5Sg5N31J3HRoj+x5kCRv0UJSu74bCcue/UvnKuq97coPoEcC4IQwGPf7sO172/F1pPl/hYl6Fh/tBQA8OmWM/4VJAixMCw2nShHvYnBd7vJcRObAwV6GBotOFZSgx2nK/wtTtCx9RR/Tf+77SwazYyfpQk+/jhSAgD477Yz/hUkCDFaGOzIrUSt0YIf9xb6WxyfQI4FQQjgjyO88RsqCsKXnKtqAADsP1eNyjqTn6UJLopalDmsP1riR0mCk4KmexcA/j5BQQexaZll23aKHDexseqH3WerUW+y+Fma4CK/slk3/HkkNHQvORYE4SI1jWbbv/8+UeZHSYKTqnremeA4YA+Vm4mK9doCwJGiGtQZyXgQk9Ka5vrpHblk+IpNVX2z7t11lnSD2Bga+OtrYlj8e4aur5hUt9C9BwsMIZFxC1jH4qWXXoJEIsGDDz5oO9bY2IjZs2cjNjYWkZGRmDJlCkpKQsNDJLxPWQvjoUjfiFJqNBaVOqMFqVo1ADIexKa2yZFIj1GDYTnsO1ftX4GCDGuUNzs+AgfO6UPCePAldUYLYiIUUMtl1OMmMiYLC6OFRZeYcADAvvxq/woUZFh1b5pODRPD4lCh3s8SeZ+AdCx27tyJDz74AP369bM7/tBDD+Hnn3/GypUrsXHjRhQWFuLaa6/1k5REsFFn5I2FNB1v/O47F/wKwlcYLQzMDIeBXbSIUMjIsRAZ6717abd4AMCevGo/ShN81Jv463tRdiwsLIdjxTV+lii4qDNaoFHLMSBdi7351dQgLyJWw3dwpg4yqQT7C+i5JiZW3Tv8PF737j5b7UdpfIMgx+LIkSNYsGABLr/8cuTk5CA5ORn9+vXDtGnT8OWXX8Jo9P44rdraWtxyyy346KOPoNPpbMf1ej0++eQTvPHGG7j88ssxaNAgLFu2DFu3bsX27du9LhcR/FijkkOzYwFQZEdMrMo3Wi1Hz+RoHCkygOPIeBALa+nTBZk6SCTA4SKDnyUKLuqb7t8LMvlnEl1fcak1WhChlKFPajTqTQzyKkNjuo4vqG3kdUN8pBLnJUbhIDkWomLVvUOyYgAAR0JAN7jkWOzevRujR4/GwIEDsXnzZgwZMgQPPvggnnvuOdx6663gOA5PPfUUUlJS8PLLL3vVwZg9ezYmTJiA0aNH2x3ftWsXzGaz3fEePXqgS5cu2LZtm9PXMxqNMBgMdl8E4QhrVLJ/uhZhUgmOUlRSNKzKN1IZhh7JUTA0WlBMpWaiUWeyGg8qdIkJp4i6yFiv7+AM3ngIhXIHX1JntCBCEYbuSdEAgKMhYJz5CkNT72CkMgx9U6NRpG8MqZ0L3saaEUrRqpGiUYWE3RDmyklTpkzBI488gm+//RZardbpedu2bcPbb7+N119/Hf/5z3/EktHGihUrsHv3buzcubPNz4qLi6FQKNrIl5iYiOLiYqevuWjRIjz77LNii0oEIVbHQqOWIzMuAidLg19B+IraFo5FelOt79HiGiRr1P4UK2iwOm4RShl6JEVh3eESNJoZqOQyP0sWHNSbGCjCpEjTqaENl+NQIRm+YlJnZPigQ1IUAOBIcQ2u6JvsZ6mCA2s/kFohszluJ0pqERep9KdYQYP12cY7xlHYcrICZoaFXBaQnQgu4dInO378OGbPnt2uUwEAQ4cOxYoVK/Doo4+KIZsd+fn5mDt3LpYvXw6VSiXa6z755JPQ6/W2r/z8fNFemwgurFHJcIUM3RIikVdZT02aImG9jiq51GY8UFRdPKxOsdV4YDngZGmtn6UKHviIugwSiQQ9kqJwoqSWSvlEgmU5mBgWKoUMXRMiIZUAx4rJcRMLS1O/ilwmRdeESACgoJmIGC3Nz7buSdEwMSzOlAf3klKXHAu5XI733nsP1dXVLr2oXC73RCaH7Nq1C6WlpTj//PMRFhaGsLAwbNy4Ee+88w7CwsKQmJgIk8nURsaSkhIkJSU5fV2lUono6Gi7L4JwREOTcRauCEO3xCiwHHC6LLgVhK+wPtzCpFJ0b3IsqNxBPJgWxkNP6/Ulx000WmZ/cuIjUWu02E2RI9zHZvhKJVDJZciKi6B7V0QsDH99ZVIJutkcCwo6iEVLx61lxi2YcTkXY+2hmDp1KtavX+9NmRwyatQoHDhwAHv37rV9DR48GLfccovt33K5HH/++aftd44dO4a8vDwMHTrU5/J2VowWBj/vK6Q59m7QMuprVcAnKLIjCtaHW5hMgmiVHInRSpwO8qiOLzFbr69UYotKni4j40EsLCyHMJkEAJAdz1/fUxR0EAULywIAZFLeXOmaEIn8ynqYLKw/xQoarNdXLpMgWaNChEKGE+RYiAbTwnELFd3rsmNRXFyMpUuXoqioCGPGjEFWVhaee+45n5UORUVFoU+fPnZfERERiI2NRZ8+faDRaDBz5kzMmzcPGzZswK5duzBjxgwMHToUF110kU9kDAQ+23IG93+1By/9etTfogQcFoZXwAqZFN0SmxyLkuBWEL6CaZGxAICsuAjkltdROYlIMDbjTIL0mHBIJEAuOW6iwbAc5E33bk58BADgVJAbD76iOZvJO25ZcZFgOdBkKJGw6l6ZVAqJhDd+ybEQj5b3b2YcrxuCXfe67Fio1Wrcfvvt2LBhA06cOIHbbrsNn3zyCbKysjB+/HisXLkSZrO54xfyIm+++SYmTpyIKVOmYPjw4UhKSsKqVav8KlNnY+spfivs+qOlfpYk8DCzzVH1zFheQZypCG4F4SusUbNm4yECNY0WVNSZ2vs1wkVapuNVchlSteqgf7j5EgvLQdZ07+bEW6OSdH3FwBbxtWaEQsQ48xUts5kA0DUhCmU1Rujr/WvPBQuWFkGdSGUYEqKU1GPhiOzsbCxcuBC5ubn49ddfERsbi+nTpyM1NVVs+drlr7/+wltvvWX7XqVSYfHixaisrERdXR1WrVrVbn9FKHK2yRAu1DdQ47FAmBbGr0ouQ1K0iqJmItGyzhfgHQsAQa+AfUVzVLL5+p6pqANLi8ZEgWnhWKRo1VCGSSljIRIteywA2KK+pBvEobVuyG7KuOVS0EwUHGXjTwd5Nt6jeVcSiQRhYWGQSCTgOM7vGQuifTiOs+0G4DhK1QvF0kpBdIkJx9kKcizEwNIiGwTAlhGiPgtxaFtOEoFGM4uSGtoVIgYWlrXduzKppMl4IP0qBi1LdYDmoAMZvuLQsscC4J9rQHMQkvCMlv2DQHM2vjKIs/FuORb5+flYuHAhsrOzMWbMGBQWFuKjjz5CUVGR2PIRIqJvMKPRzELRND85v7LBzxIFFpZWKfkuseHQN5gpZSwCjiLqAEUlxcLaH9T6+lI5iThYGM5m+AJ81PdcVYNt1CThPuame9dqmMVFKhCpDEMulZqJQmvHLSOWdyzyKGgmCs6ebcGse112LEwmE1asWIGxY8ciKysLH330EaZOnYrjx49j/fr1uOWWW0TdL0GIj3X8Yb80DQCgWE+OhRCYVin5DGtkpzJ4FYSvaO6xaMoGxVKDsZi0zraFwsPNl1hYzpYNAoB0XTg4DiispoyQp7Q2zCQSia2Uj/AcS6sei4wYXjecpTJfUTA7yBYDwa17Xdq8DQBJSUmor6/HxIkT8fPPP2PcuHGQSoN3c2AwYmjkI+vdk6Lw79kqFBnooSeElk1YAG/8AsDZinr0S9P6S6ygoPXDTRlGDcZiwrBt0/EAZYTEomWPBQDb9vj8ynrbtSbco3WPBcDfvwcK9GgwMVAraHu8J1haOW6acDk0ajllLESCYUMvW+yyY/F///d/uO222xAfH+9NeQgvUtPI766w7mAo1pNjIYRm49eaMuYVBDVwe44tKilrNh4yYsOxL18PjuMgkUic/SrhAjbjoek6pmrVkEklVA4pEhaGtdWoA82OBekGz2ldqgM09wGcq6pHt8Qov8gVLNiGkrTSvZSJFwcLw2czrc8wW9ChKnh1r8sph3nz5rVxKmpra2EwGOy+iM6L1bGIi1JCFy5HETkWgrC0Mn4zqMlNNFo3FwNAmjYctUYL9A3Uw+IpFoaFVAJIm65vmEyKpGgVzlWT4SsGfMaireGbX0XX11Na91gAQJpODQA4F8TGma8wtwqYAfz9W2Iw0uRIEWidzVTJZYiPUuJcEOsGwbVMubm5mDBhAiIiIqDRaKDT6aDT6aDVaqHT6bwhIyEStU3btqNUciRGq1BCpVCCYFoZv9pwOaJUYTQZSgSYVj0WQLPxQFF1z2FYzu7aAvz1pWsrDq17LFK1akgkfCkU4RmteyyA5qhvMBtnvsLR9bU1cNP96zHmVroB4HVvMDvFLpdCWbn11lvBcRw+/fRTJCYmUolCAFHT1GMRqQxDXKQS+/Kr/StQgGGLnLVoIkzXhQe1gvAVrcfNAvbGQ9+mgQOEe1haRc0AIE0Xjh25lTA0mhGtkvtJsuCgdVRSESZFMu25EQWH2Uxr0IF0r8c0L89s4Vg0NXDnVdTjPCo18wiGZR3q3j151Wg0M1DJg69HSLBjsW/fPuzatQvdu3f3hjyEF6ltKoWKVoUhJkKBGqMFRgsDZVjw3djewFFkJ0WrxrGSmjaGBSGM1gvyACp3EBOG5eycNgBIj+Gvb0FVA6KTybFwF47j2mQsAN4xPlpc4yepgofWmWIASNbwGSHKWHhO6+ZioMVgEnKMPcbCcAiT2WeL01s827o29bwGE4JLoS644ALk5+d7QxbCy9Q0lUJFqsIQG6kAgKBe0iI2VuOhZZYuTacGw3IopUVjHuE4KknlDmJhbSBsifX6UrmOZzgKOAC8Y6FvMFOPkIfYpvG1MM6sGSEKOniOox6LVC1v+BZW0/X1FMZhKVRwP9sEZyw+/vhj3HPPPSgoKECfPn0gl9tHuvr16yeacIS4WJu3I5VhiI3gHYuKWhOSNWp/ihUwWJi2Kc0ULb+7paCqga6jBzjqsUiIUkIhk5LxIAIWlrVrLgYoIyQWzaUk9te3S4uRs5pUKuVzl9ajqK2k6cJxsoy2m3uKI8c4SaOCVMI/1wjPcNZjAQSv7hXsWJSVleHUqVOYMWOG7ZhEIrGNhGQYmiLQWbGWQkUowhAToQQAVFDGwmUclTukannjoaC6AYP9IVSQ4KjHQiqVIDXIm9x8hbNSHSB4H26+wnnGwjp8oB59yLFwG2fXN02nxj9nKlFntCBCKdiUIZpw1GMhb5oaV0AZC49hWNZujDrQcuQsZSwAAHfccQcGDhyIr776ipq3A4xGCwOVXAqpVNKiFMroZ6kCB75O3T4qactYkAL2CEc9FgBvPOw6W0W7LDzEUQ9QYpQSYVJJ0D7cfIWjMj6A374NkG7wFGfXt2XUt3sSNRi7i6MeC4DvHwzmJW6+gi9DdWw3BGtQR7BjcfbsWfz000/o2rWrN+QhvIjJwtoatVuWQhGu4ahOPVVHtahi0J7xsOlEOarqzYhpumcJ4VgYzi4iCfC7LJK1VKfuKc4i6slNderkWHhG8wK3VqV8LabGkWPhPo56LAD+2fbv2Srabu4hjnoslGEyJEYrg1b3Cm7evvzyy7Fv3z5vyEJ4GaOFhTKM/5PHRlIplFAsDsbGxUXwfQCF1dS87QnOombB3uTmK5xNLePHJdO19QRLqzHUVhKjlJBKKOjgKWanPRbNpWaE+zAOylCB5gZucow9w9Gob4B/thUEqe4VnLGYNGkSHnroIRw4cAB9+/Zt07x91VVXiSYcIS5GCwNFk2Nhjf5WUsbCZRiWa9OgKZVKkKxVUZObhzhrgG1Z7tAvTetrsYIGM8tCLm0bR0rTqbH1VAX09WZowmnkrDtYbBkL++tr3W5OQQfPcNrDYp1qRrrXI5xli1tm44NxJKqvsLAsImRtMz7pTWW+wZgREuxY3HPPPQCAhQsXtvkZNW93bozm5oxFtCoMcpmEMhYCcBZ5SNWqceCc3g8SBQ/t9VgANJ3EUxiWgyrM0b3b3AdAjoV7MA6aX62kaNU4U0F16p7gzPBN0qggoYyQx1gzbo56LADKWHgKw3Btgg5As+NWEISOm+BSKJZlnX6RU9G5MbbosZBIJNCoFdA3kGPhKo56LABeAdcYLTSv3gOcGQ/WEb6Fenq4eQK/pKntvZvc1ERYRNfXbSxOIuoArxvKa01oNNOz0V2clUnKZVIkRClRqKeMkCc0LyBslS3WUlBHDCwsB7kD3WB9tgWj7hXsWBCBi9HCQClv/pNrw+Woridj2FUsLOvQOKNlQp7jzHhIaKpTL6JyEo9w1EAIACkaunc9pXkHS3uOG92/7uKsTBLgjbMiunc9wtGob6A5Y0G6wTOcVTpYJ0MF4/V1ybFYsWKFyy+Yn5+PLVu2uC0Q4T1MLZq3AUCrlqOaouwuwzfAOkhpkgL2GGfGQ5hMisRoFWUsPITfY+HAMLM+3MjwdRtnPRYA6QYxcFYmCfDGWVmtESYL62uxggZbD0urcd4RyjBow+U4R/euR1gYxwFJWzY+CINmLjkWS5YsQc+ePfHKK6/gyJEjbX6u1+uxZs0aTJ06Feeffz4qKipEF3TRokW44IILEBUVhYSEBEyePBnHjh2zO6exsRGzZ89GbGwsIiMjMWXKFJSUlIguS6DSshQKsGYsTOA4zo9SBQ5mJ6VQLWslCfdoz3hI1lADrKc4mmgGNGcsKOrrPrbN0I56LDSkGzzFWZkkwBtnHAeUGEg/uIuZYSGV8INIWpOqVVMplIc4C0imhHop1MaNG/Hyyy9j3bp16NOnD6Kjo9GtWzf07dsXaWlpiI2NxR133IEuXbrg4MGDXpkMtXHjRsyePRvbt2/HunXrYDabMXbsWNTVNTfGPfTQQ/j555+xcuVKbNy4EYWFhbj22mtFlyVQMVpY21QoANCoFTAzHOpNVP/rCvyCPMeGLxCckQdf4SxqBvD7AMprjTBa6D51F8ZJj4VaIYM2XE4ZCw/oqMcCoIyFJzgrkwSadS+VmrmPo8WvVlK1ahQbGm36mRCOxUkZarQ6DOEKWVDeuy5Phbrqqqtw1VVXoby8HJs3b8bZs2fR0NCAuLg4DBw4EAMHDoTUgVcmFr/99pvd95999hkSEhKwa9cuDB8+HHq9Hp988gm+/PJLXH755QCAZcuWoWfPnti+fTsuuugir8kWCFgYFgzL2ZdCNU2BqW4wI0IpeEBYyOFMQSQ1PdyKgzDy4CssrPOoWUrT9S3RG9ElNtzXogUFzup8gaY6dbp33aa9HgtrKRT1CLlPez0WtutL96/bOHuuAXw2nmE5lBgabU4yIQxn/W0SiaQpGx98965gazIuLg6TJ0/2gijC0Ov58Z4xMTEAgF27dsFsNmP06NG2c3r06IEuXbpg27ZtTh0Lo9EIo9Fo+95gMHhRav9hbKpBbVkKpbM6FvUmm4ImnOOsnCRcEQaNWh6UkQdfwTjpAQDsJ0ORY+Eezh5uAO+4/X2iBizLOXTsiPaxOFngBjRHJalHyH3aLZOkkage4+y5BtiX65BjIRyO43jHzUG2GOAzmrvOVoHjOEgcZOsDlYCcCsWyLB588EEMGzYMffr0AQAUFxdDoVBAq9XanZuYmIji4mKnr7Vo0SJoNBrbV3p6ujdF9xs2x6LFVChNOL8kT0+ToVyCYdouyLOSrFGhmOp83cbspFQHaJ6eQVFJ9zGzrHPHTauCmeFQXmd0+HOifWxlfA50g0QiQYpWTYavB7TXY2HNZlJGyH2cjVEHWgx3oOvrFkw7gx0A3m6oNzEwNFh8KZbXCUjHYvbs2Th48KCgaVXOePLJJ6HX621f+fn5IkjY+TDZMhb2U6EA0GQoF2mvnCRJo0KRvpEa4d2E6aBUB6CHm7uwLAeOA2ROHDfbPHW6vm7RnuEL8FHJwuoG0g1u0l6PRVykEnKZhIIOHtBej0Uw71rwBR3phmDd0xRwjsWcOXPwyy+/YMOGDUhLS7MdT0pKgslkQnV1td35JSUlSEpKcvp6SqUS0dHRdl/BiLXxtfVUKACoqqclea5gYdl2FIQKJguLKsr+uEW715YyFh7RseFL19cTmHaatwEgVatCo5l0g7s0379tzRWpVMKPoyan2G3a67Gg5njPYEJU9waMY8FxHObMmYPvv/8e69evR1ZWlt3PBw0aBLlcjj///NN27NixY8jLy8PQoUN9LW6nw1oKpbDLWPClULQkzzXazVhEU2THE5yN5AOAuIimqCQZD27RkeFLGSHPMDPOm7cBWkLoKUw743wB/vqS3nWf9nosaEGpZ7Q3ihoIXt0bMKOAZs+ejS+//BI//vgjoqKibH0TGo0GarUaGo0GM2fOxLx58xATE4Po6Gjcf//9GDp0aMhPhAIAo9lBKVRTxkJPpVAdYi0ncZ4ybppcZGhE7xSNL0ULCswMB7kT5SuVSpCkUdFIVDextDO1CCDD11M6dNxajJztk0q6QSgdlpNoVfjnTCUaTAzUCpnDcwjntNdjESaTIiFKhSLqH3QLSztlfEDwbt92ybGYN2+eyy/4xhtvuC1MeyxZsgQAcNlll9kdX7ZsGaZPnw4AePPNNyGVSjFlyhQYjUaMGzcO77//vlfkCTSaS6EcjJulUqgOMXdgnCVRytgj2uuxAPjIzvGSGh9KFDw0R80cO8WJGiUkErp33aW9cahA8BoPvqIj46xlH0B2fKTP5AoW2uuxAHjHjZbkuQfTThkf0PLeDS7d65JjsWfPHpdezJvjslxpfFOpVFi8eDEWL17sNTkCleapUM0RnUhlGGRSCZVCuUDH5STWXRbBpSB8RXt1vgA//eWfXIpKukNHEV9lmAxxkcqgayD0FR3phpQgNR58RUfGWXOdeiM5Fm5gabXfqjXJGhX25lfDzLBOnWfCMe0tzwSACCU/qj7Ygg4uORYbNmzwthyEl3E0FUoikUCrlpNj4QK2qKSThxtlLDyDaafOF2hRTqJvQA4ZD4LoyPAFeMeN6qjdoyPHzaobaOSse9j2WHRYp07X1x0sLItwqfNgTbJGDY7jy3zTdLRHSAgd9VgAvOMWbHYDuZ8hgqNSKADQhMtR3UClUB3R0cMtSiVHpDKMMhZuYmlnQR5A8+o9oaMeC4A3HkprGmFpakQmXKe9cagAoJLLEBuhCDrjwVd0PLKTgjqewDAdlEJRNt5tXNG9KVo1ivWNYNngGUftVvP2v//+i2+++QZ5eXkwmeyN0lWrVokiGCEuRgcZCwDQhSuQX1nvD5ECClcUBL/LgqJm7mBhOKjl7Ru+QPDN+/YFHS1pAvg6apYDSmqMSKUNu4IwM+2X6gC88VBEEXW3cGVPCEAZC3fpqAy1WfeSYyEUl3SvRgUTw6KizoT4KKWvRPMqgjMWK1aswMUXX4wjR47g+++/h9lsxqFDh7B+/XpoNDTxorPSPBXKPuWpVctR3WCm5U0d0FGdL9Cc0qRrKRymo4cbNcC6jdXwdTZ1C2jRB0DXVzCulJola1QoqTHaziVcp6OMkC5cDmWYlAxfN2lvjDrQXMpXTEEdwXTkFAPNjnEwBSUFOxYvvvgi3nzzTfz8889QKBR4++23cfToUdxwww3o0qWLN2QkRKC9UiiThUWjmUog2sOVWsmkaBXqTQxqjBZfiRU0tDdLHWhp+JLxIBSXDF+r40bGmWCap0K1bzwwLIfSGrq+QrEwvOHrbDiMRCKhjJAHWBjny0mBllPN6N4Viqs9FkBwXV/BjsWpU6cwYcIEAIBCoUBdXR0kEgkeeughfPjhh6ILSIhD81Qo+z+5bUke9Vm0S0fTHQCqRfUEpoMeC224HCq5lEqh3MDVHguAMkLu0FFEHWhpPND1FUpHo6iB4GyA9RUdjZtNiFJBJpUEVUTdVwjRvcF0fQU7FjqdDjU1/Dz51NRUHDx4EABQXV2N+nqq1e+sNPdYtCqFatplUVVHk6Haw2o8yNtNGdNYSXcxM1y7UR2JRNK0YZeurVBcqfO1jewkw1cwFlfKJLXBuWHXF5hZrl29C/DGWa3RAkMjPceE0lGPhUwqQUKUkgJmbiBI9wbR9RXsWAwfPhzr1q0DAFx//fWYO3cu7rrrLtx8880YNWqU6AIS4uCseZuW5LmGxcUmLIBqUd3BpaikVoWi6gbqYRGIK3W+1qgklUIJh2E6zmam2owH0g1C6WgUNdDSMab7Vygd9VgA/LONdINwXNG9SUGYzRQ8Feq9995DYyN/gz311FOQy+XYunUrpkyZgv/7v/8TXUBCHKw9Foo2joW1FIoiPe3hUo8FjT10Gwvbfp0vwEclt5gqYGi0QKOW+0iywMeVe1cmlSCRopJuYWZdqaOmjIW7WDoYhwrYT43rnhTlC7GCAo7jwLBcu/1BAH999+RXw2Rh29gQhHMsLgQd+AWlwTWOWrBjERMTY/u3VCrFE088IapAhHdobyoUAFqS1wGuRB6ox8J9+IxF+w8s2y4LfQM5FgJwpc4X4Mt1zlbU+UKkoMKVHouEKCWkEspYuIOr2UyAMhZCcaVUB+CfbdYleekxtCTPVay61xXHLZjKUF1yPQ0Gg92/2/siOift7bEAgCoqhWoXV4wHjZpvMA6myIMv4DgOZsaFqJmWJkO5gxDjobzWZMtuEq5hmwrVzvUNk0mRGK2ijIUbuNJjkRKEDbC+wJWAGdBi5KyB7l8hCNG9wTSO2qWMhU6nQ1FRERISEqDVah2OfeM4DhKJBAxDD6XOiG3cbOupUNRj4RLNS7DabzBO1qgpYyEQqy51pc4XoCV5QnHVeLDOUy/WNyIjNsLrcgULth6LDqOSKuTRMlLBMCzb8bWlkahu4cq0Q4CWELqLEN1rHUdtLesLZFxyLNavX28rgdqwYYNXBSK8g6kpY6FoVauqi7BmLKgUqj1sC/I6qPVNilbhUKHeFyIFDa6W6qRQxsItXKnzBeznqZNj4TpCjIfdedUwWpg2JamEcyxM+6OoASBaJUekMowyFgJhXFieCbRckke6Vwiu7BAC7HVvyDgWI0aMsP07KysL6enpbbIWHMchPz9fXOkI0TBa+ObY1oZxhEIGuUxCGYsOcNV4SNaosO10BeqMFkQoBbcwhSRC0sUAZSyEYi3ja6+5GAjOeeq+wFXjgTJC7uFKjwVAuyzcweJCiS/QstSMrq8QzIyLPRZ227d13hbL6whu78/KykJZWVmb45WVlcjKyhJFKEJ8jE6mOUgkEmjUCmre7gAL45oCplpU4bhSZgYAUSo5opRhlLEQiCt7FoDgnKfuC4QEHQAq1xFKR3sWrCRr1SikcdSCcFU3xEcpaUmeG7gaNLMNJgkS3SDYsbD2UrSmtrYWKpVKFKEI8TGamTaN21Z04XJq3u4AW4Nmh2MPKWUsFMaFcZ1WkrUqergJxPV0PNVRu4OrQQe6vu5hYVmXdEOKRgWjhaWyXgG46hRbx1FT0EEYLgcdtM3jkoMBl2s15s2bB4CPcD/99NMID28eOcYwDHbs2IEBAwaILiAhDkYL67SuVxeuwKmyWh9LFFi4apzR9m3huNpjAfDG2fbTFU4DHERbLC5mhGIjFFDIaKqZUBjBGaHgMB58BcN0PIoasHfcYpp6B4n2cXXwAMBn4/Or6N4Vgqt2Q6J1HHWQZCxcdiz27NkDgM9YHDhwAApF839chUKB/v3745FHHhFfQkIUjBa2zUQoK9pwOaobzGSstYO1VtLVcgfavu06rqaLAd44M1pYVNaZEBup9LZoQYGtjroD40EqlSBJo6KIukAsLmbcmpe4BYfx4CtcL4VqLuXrk6rxtlhBgVlIUEdLS/KEYnHRbgiTSZEQFTzZeJcdC+s0qBkzZuDtt99GdHS014QixMdkaa8USgGG5WijcTu4nrGgOnWhuLIZ2kpyi4wQORau4cqeBSvJGhWOFtd4W6SgwqYbOgjKxEYooAiTBtUiLF/gavM27bIQjqCgDi3JE4zFxWmSAO8YnwuSjJBgt3PZsmXkVAQg7ZVC0S6LjnG1xyImnC8noR4L13G1DhVo2QAbHArYF7jqFAP85CJ9gxn1Jou3xQoaLCwLqYTP+LSHVCqhyUVuYGZYQRkLao53HWtQp6MFhACV+bqDIN2rUaO81mhbDRDICHYs6urq8PTTT+Piiy9G165dkZ2dbffVGVi8eDEyMzOhUqkwZMgQ/PPPP/4Wye84mwoFANqm7ds0Gco5ru4CkEolSNRQk5sQGAHpeNsuC7q+LiMsI0TGmVAYtuM9C1aSNSoUkFMsCIblXIr4UsZCODbD18XmeICurxCEBs2sGaFAR/Cg/TvvvBMbN27EbbfdhuTk5E5Xk//1119j3rx5WLp0KYYMGYK33noL48aNw7Fjx5CQkOBv8fxGR1OhANBkqHYQYvwmR6txopTKSVzFIiAdT7sshCMkatZynnrXhEivyhUsmBnXSnUA3vjdfroStUYLImnPjUu42mOhVsigDZcHTQOsLxDSY0FlvsJxdWIc0GIyVHVDwJeaCdZsv/76K1avXo1hw4Z5Qx6PeeONN3DXXXdhxowZAIClS5di9erV+PTTT/HEE0/4WTr/wZdCUcbCXYTUSiZpVPjnTCUaTAzUCtqw2xFu9ViQ8eAyQoyHYJun7gsYFw1foEWDcXUDuiVGeVOsoMHVHguA1w8UdHAdYYMzrLqXrq+ruFpCDbTMCAW+7hVcCqXT6RATE+MNWTzGZDJh165dGD16tO2YVCrF6NGjsW3bNj9K5l84jutg3CxlLDrC1VIooOV0ElLArmAREFFXK2TQhcvp2gqAsY2bFTCyk66vy7i6ZwFoNs5oMpRrcBzncsYC4I2zEkMjWJaW5LmCrcfChfs3LlKJMKkkKAxfX+FOtjgYdK9gx+K5557D/PnzUV9f7w15PKK8vBwMwyAxMdHueGJiIoqLix3+jtFohMFgsPsKNqybjZ2Pm+UzFrRYyDlCaiVTqQ9AEELKzICmqCRF1F3G1XGoQItdC3R9XYaPqLv2KLX1AVDU1yWEGGYAH9QxMxzKa43eFCtoEHJ9ZVIJEqNp+IAQhNgNwZQtFlwK9frrr+PUqVNITExEZmYm5HL78aS7d+8WTThfsGjRIjz77LP+FsOrGC0MAHTYY6GnjIVTbMavgHIdmlzkGq4ucLOSolXheEmNoBKJUEaI8aBRy6GWy4IiauYrhETUmycX0fV1BSGlJID9rpCEaJXX5AoWhJRJAnyZ79mKzhdU7qwI6bGIi1RCLpMERTZesGMxefJkL4ghDnFxcZDJZCgpKbE7XlJSgqSkJIe/8+STT9q2igOAwWBAenq6V+X0Ncam8WXOx81SxqIjmiMPrjcYU2THNZonk7huPFhYPiqZSMZDhwiJmkkkEiRrKSopBKE9AACVQrmK0IxFSoselgHpWm+JFTQIKZME+GfbrrNVMFoYp/YE0YyQbLG0KSMUDNl4wY7FggULvCGHKCgUCgwaNAh//vmnzQFiWRZ//vkn5syZ4/B3lEollMrgXrRldSycjZtVhEkRoZBRj0U7COmxSNHS2EMhmAUYvoB91Jcci44REjUD+HKdPXlV4Diu003964xYGM7lHotoVRgiFDLSDS4ixCkGyHETihDDF2gOmpUajAE/ucgXMAICkgCve4NhoqRbe9mrq6vx8ccf48knn0RlZSUAvgSqoKBAVOHcYd68efjoo4/w+eef48iRI7j33ntRV1dnmxIVihjN7ZdCAXzWgqZCOceaMnalyU0XLocyTBoUkQdfILTHIoUWNQlCeDmJCnUmBoZGWpLnChaWddlpk0gkSNGqg6KO2he44xQD1MPiKhZW2PWlMl9hCHaMtSpU1ZvRYGK8KZbXEZyx2L9/P0aPHg2NRoMzZ87grrvuQkxMDFatWoW8vDz897//9YacLnPjjTeirKwM8+fPR3FxMQYMGIDffvutTUN3KNFRxgLgt29TxsI5zSNROzbObMYDRSVdQkg2CKBSM6EIb4Btzrhp1PIOziYsDOey0wbw1/ef3ArKCLkAI9AwS9Tw1QekG1xD6PW16t7iIFji5gtsjrHLGaFm3ZsdH7h7hARnLObNm4fp06fjxIkTUKmayxCuvPJK/P3336IK5y5z5szB2bNnYTQasWPHDgwZMsTfIvkVq2OhkjuvidSFK6CnjIVTrApCLkABU1TSNYTsCAFonrpQLIIzQsEzncQXWFjXS6EA/vo2mlnKELuAWaBuUIbJEBeppOEDLmIR2mPRpHtpe7xr2LLFrpZCaYMjaCbYsdi5cydmzZrV5nhqaqrTka6Ef7GWQqk6yFjUGC0wNxnQhD1Cjd9kjRo1RgsMjWQ8dIRZoNOWGK2CRBL4ytdXCMm2AcE1T90XWBjWZacNaI5KknHWMYyA5ZlWUrQU1HEVoaVQqVoqhRKC8Gx8cFxfwY6FUql0uOvh+PHjiI+PF0UoQlwarVOhOshYALR92xlCFQTtA3AdRqDTpgiTUlRSAELrfCljIQw+YyGkFCo4opK+QOg4VIDPFpfWNNqyzIRzhDZvx0YooKD+QZexCOjNBIKnzFewY3HVVVdh4cKFMJt5A1QikSAvLw+PP/44pkyZIrqAhOe40rxt3WVRTX0WDhHSvA3QBmMhCN1jAfDGLxm+rmHNCLneQEj3rhAsAveppGhoapyrCC3VAXjdy3JASQ0tyesIoddXKpUgRaMK+Ii6r7AwvG5wtZcqWCZKCnYsXn/9ddTW1iIhIQENDQ0YMWIEunbtiqioKLzwwgvekJHwkI72WACAhnZZtIvwWlSK+rqKWcDyQSvJGjVFJV1EaLYtUhmGKFUY3bsuYmFYlwMOQHM2k6K+HSM04gvY77Ig2sdWhiro+qqpjM9FhAYdgmWipOCpUBqNBuvWrcOWLVuwb98+1NbW4vzzz8fo0aO9IR8hAs3N286N4pgIPmNRWUcZC0cIfcBRVNJ13IpKalW2qKS17pdwjHUztJAJRCkammrmKvz1FRZRB0g3uEKzUyz8+tIui44R2jsI8I7F1lMVMDSaEa2iqXHtYWZYl3sHgeCZKCk4Y/Hf//4XRqMRw4YNw3333YfHHnsMo0ePhslk8vuoWcIxjbZSKOcZi9gIfkwfORaOEZrSTKaopMsIrfMFaF69ECwsK+jaArBt3+Y4zktSBQ8WhhNUxqdWyKALl1M5iQtQxsK7WASWSQLUwC0EfnmmMDM7GCZKCnYsZsyYAb1e3+Z4TU1NSC+h68zYSqHayVjERvKlUOW1VJfqCKEpzWiVHFHKsICPPPgCdx5uNseNopIdYmE4l8cdWknWqGG0sBRocAG3HDeNmoIOLmB2o/8qmRZouoz1+grZw0KOheswrLCgA9A8UbImgCdKCnYsnC31OXfuHDQajShCEeJitHTcvB0fyWcsKsixcIjQlCbQHPUl2kfoZmighfFAD7cOMTPCDd+UIJlO4m1YlgPLCSvjA/ioeomh0TYRjXCMbbmjAN2QEKWEVEKGrysIXZ4JNDcYF1TR9e0IsxtBh2DYZeFyj8XAgQMhkfClIKNGjUJYWPOvMgyD3NxcjB8/3itCEp7RaHZhQV5EU8aCIpQOcS+lqcb207RhtyOENhcDwaF8fQXDcoJq1IEWk6GqG9AnlQJGznCnjA/gjTMLy6G81ojEaFXHvxCiCN1xA/D9AonRFNRxBaHTDoFm3VtAGbcO4cskhdsNAK97z0uM8oZYXsdlx2Ly5MkAgL1792LcuHGIjGxeN65QKJCZmUnjZjsprmQs5DIptOFylNOIPocwLCdI+QK8AjZaWFTVmxHT5LgRbXGnjjohSgWZVEJRSRcwu3PvUsbCJZq3mrtvPJBj4Ryhyx2tJGtUyKus94ZIQYU71zeFSqFcht9xI7zSAQhs3euyY7FgwQIAQGZmJm688UaoVKQMAwWjueNxswAQF6lEBWUsHGJmWY+MB3IsnGN2YyqUTCpBYpQyoJWvr7C4UQpFuyxcQ+jyQSstR84O7CK6WEFDc5mk8Pt3d141jBamw+deKGNxIyOkkssQF6kgx8IFLAwrXDcEQZmv4HGz06ZNAwDs2rULR44cAQD07t0bAwcOFFcyQjRcGTcL8Fs1j5fU+EKkgIMvhRLahGU1HqicpD0YN/ZYALzxcLaizhsiBRXuNW/THhZXaI74Cm/QBGjkbEdYM0JCyiSB5oxbsb4RGbERossVLJjdGDcL0C4LV7GwXLuVIo4IhsEkgh2L0tJS3HTTTfjrr7+g1WoBANXV1Rg5ciRWrFiB+Ph4sWUkPMTowrhZgM9Y7Mit5BuVBSqaYMfsTuRBS9NJXMGdjAXAG7+7zlZRVLIDLCwr2DBTyWWIiVCQ4dsB7kw0A1oGHUg3tIc7O26Altlicizag3HTMU7RqHGwQE+2QgdYWBYRMmHPpmiVHJEBPlFS8B1x//33o6amBocOHUJlZSUqKytx8OBBGAwGPPDAA96QkfAQa8ZC0YHnHNc0craKyqHawNdKuhf1pXKS9rG4mbGwOm7F5Li1izv3LsDfv2T4to87C8YAIEmjgkRCGYuOcGczNNByuANd3/Yws+45xilaNb+g1ED6oT34/Vfu6d5AzhYL/sS//fYb3n//ffTs2dN2rFevXli8eDF+/fVXUYUjxMFoYSCXSTqMWsY2jZwtryXHojXuzqMGqJykI6xRSXfLdcj4bR8LI7x5G+DvXxqJ2j7ulkLJZVIkRCkDutzBF7gzDhWgXRau4m5GKIUWwLqEmeEEj6kH+DLfQn1DwC4oFexYsCwLubztGne5XA62yfslOhdGCwuVC6UitCTPOe6kfK0bdilq1j4W26x694wHaiJsHwsrvIwP4I0HC8uhjCbFOcXiZsQXsC7Jo3u3Pcxu7LgBWtSp0/VtF3cm8gFAmq5pl0U1Td5qD8aNPRYA3yPUaOYnSgYigh2Lyy+/HHPnzkVhYaHtWEFBAR566CGMGjVKVOEIcWg0M+1u3bYSZ12SV0eGRGvcad4G+JQxRXXax9069eaHGxkP7eHOLHWgecMuGQ/OaZ4KJfz6pmhVKK81wmShgJwz3NUN8ZFKKMOkpBs6wMxwkEklgvcsNY+cpWdbe3isewN0CaHgT/zee+/BYDAgMzMTOTk5yMnJQVZWFgwGA959911vyEh4iNHCutTcau2xqKBSqDZYWFZwqQ7AK4hiQ6PtAUm0xd2opNWxOFdFhm97uLN5GwDSY8IBAOcC9OHmC5pLSdzLWHBUp94ujJs9LBKJBKk6NfJpl0W7uDMOFWixfZsct3ZxZ/M20Kx78wP02SZ4KlR6ejp2796NP/74A0ePHgUA9OzZE6NHjxZdOEIcjGbWpZFncdRj4RQLywmu8wV4BcGwHIr0jTZlQdhjnUwi9PJq1HJEKcPI8O0Ad5u3rY4bGWfOaR484F6DJsCX65BucIzZA8ctXReO7acrwHGc4Ih8qGBxo3cQ4EfTK8KkARtR9xXuZiwCPWgm2LEA+GjAmDFjMGbMGLHlIbxAo4VBuKLjP3Vz8zaVQrXG3VIom3FWVU/GgxMsLAu5THg63haVDFDl6yssrHsNhOk6ylh0hLsL3IDmcgdqMHaOrRTKTd1rtLAoqzUiIYoW+jqCf64JN3wlEglStdQj1B4cx7ntuAV6ttitAcR//vknJk6caCuFmjhxIv744w+xZbNx5swZzJw5E1lZWVCr1cjJycGCBQtgMtlH1vfv349LL70UKpUK6enpeOWVV7wmUyDRaGZcylhEKGRQhknJsXCAu/O608g46xCzm1EdgL++RdVUatYeFkb4HgsA0IbLEaGQ0b3bDtZSKHeubzKVk3SIu2WSAOleV7AGddzB6lgE6uQib9Ncxif8+sZHKqGQSQM2Wyz4f+v777+P8ePHIyoqCnPnzsXcuXMRHR2NK6+8EosXL/aGjDh69ChYlsUHH3yAQ4cO4c0338TSpUvxn//8x3aOwWDA2LFjkZGRgV27duHVV1/FM888gw8//NArMgUS9SYGEcqOeywkEgkSo1UoMZBj0Rp3Iw/NKU16uDmDYd3LBgFAeowaFpZDCU0ucgjLcmA59wwziUSCNF04ZYTaoTmi7kbztoZ2LXQE4+bmbYDXDQDp3vbwJKiTolWhzsTA0GARWargwOKBUyyV8tn4QL13BZdCvfjii3jzzTcxZ84c27EHHngAw4YNw4svvojZs2eLKiAAjB8/HuPHj7d9n52djWPHjmHJkiV47bXXAADLly+HyWTCp59+CoVCgd69e2Pv3r144403cPfdd4suU6DAcRwaTAzUctf+1InRSpwqq/OyVIEFx3FgWM7NqFnTwy1AIw++wJ2t5lasUcn8ynpbaQnRjNnN5YNW0mPU2Hi8DIybPUbBji2i7sa1iWuKSlKdunPc3XED2OsGwjEWN5uLgeYG7vyqemjCNWKKFRRY3NzBYiVNp8a/Z6oCskdI8P/W6upqOyPfytixY6HX60URyhX0ej1iYmJs32/btg3Dhw+HQqGwHRs3bhyOHTuGqqoqn8nV2TAxLCwsh3CFa2vlE6NVqKwzwWhhvCxZ4OCJgohSyaENlwds5MEXuNtcDADplBFqF3cXjFlJ04XDzHAoraE+AEdYR8UqXCg1bY1UKkGaTo18unedYnZzASFA2WJX4Jdnuqd7u9j6AMhxc4TZ4t6OECtpunA0mBlU1AXeMB3Bd9RVV12F77//vs3xH3/8ERMnThRFqI44efIk3n33XcyaNct2rLi4GImJiXbnWb8vLi52+lpGoxEGg8HuK5hoMPEOgiulUACQFM2n50upHMqGJ8YDwD/gSPk6x2RhoXDz4dZcR03X1xHWe9eVHitHNE+GIuPMER7rhphw5FfWU526E0wM//xy5/rGRiiglstIN7SDu9MOgeYG4zzKCDnExFh1r2u2V2uspXyBmHET/L+1V69eeOGFFzBhwgQ8//zzeP755zFx4kS88MIL6NOnD9555x3bV0c88cQTkEgk7X5ZR9paKSgowPjx43H99dfjrrvuEip+GxYtWgSNRmP7Sk9P9/g1OxP1TY6Fq6VQSU11vzRbvRmjp8aZNhzFhkZahOUEk8W1cciOSIshw7c9bIYvOW5ewWb4uh31bZpcRD1CDvHEceN7hAK3Tt0XeBLUsWYsSPc6xvOAZOAOHxDcY/HJJ59Ap9Ph8OHDOHz4sO24VqvFJ598YvteIpHggQceaPe1Hn74YUyfPr3dc7Kzs23/LiwsxMiRI3HxxRe3acpOSkpCSUmJ3THr90lJSU5f/8knn8S8efNs3xsMhqByLqyOhZBSKAAoJsfChqcKIj1GDZbjmzQzYiPEFC0oMFoYqOTuRXWiVXJo1HIyfJ1gFCHbBgTmw80XWHWD3F3doGtehJUQTSNRW+OpY5weE47NJ8rBshyk1CPUBpOFhSLCvWtr3W5OGQvHGD29dwNY9wp2LHJzc0V78/j4eMTHx7t0bkFBAUaOHIlBgwZh2bJlkLZq5ho6dCieeuopmM1myOVyAMC6devQvXt36HQ6p6+rVCqhVCrd/xCdnHoTP7Eh3MVSKJtjQbPVbYgZeSDHoi0mCwuNWu7271NU0jnWdLzbTjE1wLaLrdTMw6hvXmU9BmXEdHB26GG7f93OuKlhYvhdFonkuLXBaHFtFL0jmnuESDc4Qiy7IRCvr3uf2McUFBTgsssuQ5cuXfDaa6+hrKwMxcXFdr0TU6dOhUKhwMyZM3Ho0CF8/fXXePvtt+2yEaGILWPhYkTY2mNBpVDNWBvZ3a2VDPQtmt7GxLBuK1+AN36L9A0w0y6LNjRHfN27dzXhckSpaLu5MzzNCKVTOUm7mCz8ngV3sw20Pb59TBbPdG+XmHCcq2wAy1KPUGs8DerERSqgkksDUve6tXnb16xbtw4nT57EyZMnkZaWZvcza9ObRqPB2rVrMXv2bAwaNAhxcXGYP39+SI+aBZqbt13ZvA0ACdF89qaYmrdteNxjEcC1kr7A6OHDLU3Hl5oV6xtpu3krPDV8Af7+PVdNhpkjrFOLPHUsqJzEMUYPegAA++3xgzNFEiqIMDHu97cB/P1rYspQWmO09WcSPJ6W8Vn3CAXiqPqAyFhMnz4dHMc5/GpJv379sGnTJjQ2NuLcuXN4/PHH/SRx58GWsXCxFEoll0EXLkcJlULZECMdD1DUzBmeNBACdH3bw9OpUABf61tI280d4mm5g0YtR7QqjO5dJ3gedKDhA85gWQ5mhvM4YwGQY+wIT3UD0FTmWx14GaGAcCwI96mz9li42LwN8H0WJTS33obR3GScyd377xKhDENMhIIyFg7gOM7zUqgYygg5Q5yHWzgYlqOBDg7wdCoUAHSJDSfHwgmelurQuGTneDoOFaAlhO3hyahkK+m6cJgsfI9QIEGORZDTIHDcLMA7FsX6Rpqt3oSnGQuAGoydYWE5cBygEOHhRlHJtojxcKPJUM4Rw3FL14WjiMZRO4QfRe2+btCGyxGpDKNSPgd4OrUIoIxFe4iRLQ7U/ky3PvGmTZtw6623YujQoSgoKAAAfPHFF9i8ebOowhGeI3TcLACkaPnZ6pUBuPHRG4iV0iypaaSN5q3wtA4VaBGVJMO3DaKUQsVQVNIZYuiGLjHh4DigoJru39Z4ms207rKgjEVbRHGKrXuEAszw9QViOG6Bmo0X/Im/++47jBs3Dmq1Gnv27IHRyKdo9Ho9XnzxRdEFJDyjwY1SKDLU7PF0KhTARyU5Diiga2qHGA+3CGUYYiMUZPg6QJyHG+kDZ9jKSdycugWQ49YenvZfAXxGs7C6AUyA1al7m+bnmvvXN0olhy5cTveuA8TKZgLA2YrAur6CP/Hzzz+PpUuX4qOPPrLtiwCAYcOGYffu3aIKR3hOjZF3LCJVrpdCBWr6zVuIkrGwGg9knNnRXOfrofEQE07peAeIMRWKdlk4R5TrS+UkTvG0xwLgM0IWlkORnnRvS8R4rgH89aV7ty2ejpsF+P4rIAQci2PHjmH48OFtjms0GlRXV4shEyEihgbesYhWub6AjGar2yNWuQNAxllrxHy4ldYY0WimUrOWiJkRIuOhLaQbvIunpVBAc8aN7l97xDB8AT6oU2Ig3dsaMcp8NWo5tOFy5FXWiSWWTxD8iZOSknDy5Mk2xzdv3ozs7GxRhCLEw9BohkwqcasUijIWPJ7usQD4kZ0AGQ+tEaNUB2i+vnTP2tPcY+F+qQ7AGw9077bFZGEhlQAyNxe4AUCKVgWJhOrUHcE3b3sedACAcxQos8M27dBD3dAlQPsAvI1YQbOM2Ijgz1jcddddmDt3Lnbs2AGJRILCwkIsX74cjzzyCO69915vyEh4QE2jGVGqMEgkrj/44iOVUIYF5sZHbyCGgkjVqcl4cIBYypeybI4RKypJGSHHiBFRV4bJkBytooi6A8TosaBSM8eIpRtspZL0bLNDNMeiSffWN/XLBgKCN28/8cQTYFkWo0aNQn19PYYPHw6lUolHHnkE999/vzdkJDzA0GARVAYFtJikQYoCQHOTmycPOGWYDElkPLRBTMMXIOOhNWKk4wH7jFDXhCiP5QoWjGYWKrlnEV+AzwgdLTKIIFHwIMaOG4AMX2eIWYYKUDa+NWL1D2bENj/beiRFeyyXLxD8iSUSCZ566ilUVlbi4MGD2L59O8rKyvDcc895Qz7CQwyNZkSrBfuPSNOFo6CqgXZZwL2RvY5IjwmniHormveseHhtqcHYIdYMg7vLHa2Q4+aYejODcBEci4yYcBgaLdDXm0WQKjhobCrV8VQ3qBUyxEUq6d5thW0qlIdBB5tuCLByHW9jfbZ5GniwXt9AKody+45SKBTo1asXLrzwQkRGRoopEyEiNY0WRCmFZSwAvuHNaGFRVhNYGx+9QbNjIdxBa0m6Lhz6BjP0DWQ8WGkw8+ldtYdOW7JWBZlUQsZDK8R0igEqNWtNo4mBysNrC7SI+lJU3Ya19EOc60u7LFrTYGpy3Ej3eoV6szh2Q2ZcBIDActwEf+K6ujq89NJL+PPPP1FaWgqWtd8Wevr0adGEIzyDZTnUeJCxAPjxqAnRKrFFCyhsUXUPFXDLlLEmVeOxXMGA9eHmqeErl0mRrFHRON9WWO/dcLlnDzfKWDim3myBRi08cNOalmMl+5BuAAA0WA0zETJC6THh2J1XjXqTxWNDL1iod2PHlSPkMilStWrSDa1oFCmok9Gke89UBM5kKMH/w+68805s3LgRt912G5KTkwU1BRO+pc5kAcvxS2yE0mxI1GFQhk5s0QKK5siDp1Hf5jp1Mh54xHq4Afw9u/+cHhzHkV5qwmqceRyV1PBRSSo1s6fBxCIpWhzDFyDHrSUNIhlmgP3kovMSqUcIEE83APz13ZNXRbq3BfUmBhKJ5z0W8VFKqOWygNINgh2LX3/9FatXr8awYcO8IQ8hIoZG4TssrGQ1pd9yywLHS/YWDSYL5DIJ5GLVogaQgvA21oebGA2w6bpwbD1Vgep6M3QRCo9fLxioNzEIk0o8btAMk0mRoqXhA61pMFmgFiECnkG6oQ31tkyx59fX2oOVV1FPjkUTdUZxSnUA3jHefLIcFXUmxEUqPX69YKDezEAtl3nsaEkkEnSJCQ/uHgudToeYmBhvyEKITGWtCQAQGyncyMqM5R2LU+XkWNSbGI8bCAGqU3eEWP0rQHM5CRlnzTSYLaJEJAHeODtHAx1scBzXZDx45rQBQEyEAhEKGWWEWiBWfxDQQvdSD4uNBpGzxQDp3pY0mCyiXFuAnwxVUN0AM8N2fHInQLBGfO655zB//nzU19MN1Nkpr+Mbr2PdiN6qFTKkatWUsQD/gBPD8I2PVEIRJiXl2wIxjQfrYkcyHprh711xHm5dYsJRa7SgiiYXAeCXO3KcOE6xRCJBekw4zgbYhl1vYp1oJk5Qh7Zvt6ZepIl8AI2cdUSDmREtqJMRGw6G5VAQID2EgjXi66+/jlOnTiExMRGZmZmQy+3LbHbv3i2acIRnWDMWMW6WhWTFRWDXWaqbbBDJOJNKJUin/SB2iGk8UNSsLQ0iOcVAy4xbvds6JZgQa5yklS4x4fjzaCnMDOtx2WUwUC/S0AwASNaoEUY9QnaI1TsItNi1EEDlOt6m3sR4PDTDSpemCpKzlfW2KVGdGcGfevLkyV4Qg/AGFdaMhZs1j9nxEdh8shzFhkYka9RiihZQ1JuFLxl0RnpMOLaerADLcpBKQ9dZs2Jt3hbDeKBSs7Y0mMV3LPIq69E/XSvKawYyDSIaZkBzVLKoutFW1hfKiDnYQSaVIFVHI2db0iBiGapVN5wlx81Gg4lBVLQ4doOtB6uiDkC8KK/pTQTfUQsWLPCGHIQXqKhr6rHwIGMB8A3coexYNJgYJIk0crdLTDj+YspQWmNEkia0x/gC4pZCxUYoEE516nbUmxjRminTqdTMDjFLSQD7jBs5FuJOLQL46/vvGcrAW6k3WSCRACoReoQ0ajk0ajlli1vAZyzEuXczYyMgk0oCpgyV8q1BTIUHzdtAs2NxOsQbuGuNFkQoRYr66qiJsCW2cpIwzxWwRCJBui6crm0LxCrjA6iOujV1Rj6iLppuoFI+O8Qc7ADwu5kazIwt4BbqWIeSiOVkdYkJJ93QBMdxoureNJ0aR58bjwdGdRPl9byNYMeCYRi89tpruPDCC5GUlISYmBi7L29jNBoxYMAASCQS7N271+5n+/fvx6WXXgqVSoX09HS88sorXpenM1NZZ4JCJkWkmw++nHh+o/rpEG7gNloYNJpZUZZgAS2MB6pFBQAYGs2IUoWJVhaWHhOOgqoGMCxNLmJYDrVGC6JU4hhmMbaMEJWTAPy9C8CtBaSO6GIrJwldfduSmqbrK9b9Sz1Y9tSJGDAD+Kl8xYZGW99cKGO0sDAxLKJFshukUs/H3fsSwZI+++yzeOONN3DjjTdCr9dj3rx5uPbaayGVSvHMM894QUR7HnvsMaSkpLQ5bjAYMHbsWGRkZGDXrl149dVX8cwzz+DDDz/0ukydldKaRsRHKd2OSKRo1VDIpMgtrxVZssDB0OD+LhBHWKeTUFSdx9AgXv8KwF9fC8uhSE/Gr9UwE8spts5TJ8OMp8aDPUGOSNOFQyKhjJAVq+4VL6jTpHvp+gIA9A1m0a4twDtuHAcUVJPuNTQ0BR1EcooDDcGOxfLly/HRRx/h4YcfRlhYGG6++WZ8/PHHmD9/PrZv3+4NGW38+uuvWLt2LV577TWHcplMJnz66afo3bs3brrpJjzwwAN44403vCpTZ6awuhHJHtTxy6QSZMaF41QIZywMIhtnVO5gj6FR/IcbQA3cgPhOMcAbv4XVDbAEyDx1b2IzHkS6fxVhUqRo1KQbmjB4KWNBjgWPodEiquHbhbLxNpqzmeLp3kBCsGNRXFyMvn37AgAiIyOh1+sBABMnTsTq1avFla4FJSUluOuuu/DFF18gPLxtY9u2bdswfPhwKBTN/QTjxo3DsWPHUFVV5TW5OiuNZgaVdSakaD1rus6Jj8S5qvqQTW/qG8Qtd4hWyaENl+McGb4AeONMrGsLtOhhIePBKw+3LjHhTRmhRtFeM1CxXV8RjbP0GDUZZk3oG8xQyaVQitB/BbTUDaR7Ae9kLAAKmgGAXuRsW6Ah2LFIS0tDUVERACAnJwdr164FAOzcuRNKpXdWuXMch+nTp+Oee+7B4MGDHZ5TXFyMxMREu2PW74uLi52+ttFohMFgsPsKBqwP/mStZ5OHcuIjwXIIqHXyYtKc0hRXAZPy5f9f81EzMUuhqDneil7kiDpApXwtsWWERDbODI0WVNdTg7GhwSyqbtCGyxGlDCPdCz7waLKI1zsIkGPRkuagAzkWLnHNNdfgzz//BADcf//9ePrpp9GtWzfcfvvtuOOOOwS91hNPPAGJRNLu19GjR/Huu++ipqYGTz75pFBxO2TRokXQaDS2r/T0dNHfwx8UNtU5pnqasUjgJ0OdKgvNPgtDo/iRh3RdOEpqGmG0hGYWyEq9iQHDcl4xfOnh5p06XyonaUbsUh0AyGhahEX3b1Opjoi6QSKRIC2GpsYB4pfxAUCyRoUwqYTuXbS8vqHZYyH4U7/00ku2f994443IyMjA1q1b0a1bN0yaNEnQaz388MOYPn16u+dkZ2dj/fr12LZtW5uMyODBg3HLLbfg888/R1JSEkpKSux+bv0+KSnJ6es/+eSTmDdvnu17g8EQFM6F1bHwdP+EdTLUqdIQdSy8EvVtanKrakB20/UNRfReyAaFK8IQF6kgwxfeylhQOYkVb2QzW/Zg9UvTiva6gYihwWy7HmLRJUaNdYcNIb/d3KobxAyYhcmkSNVRKR/QHJAM1YyFIMfCbDZj1qxZePrpp5GVlQUAuOiii3DRRRe59ebx8fGIj+94i+A777yD559/3vZ9YWEhxo0bh6+//hpDhgwBAAwdOhRPPfUUzGYz5HL+j7lu3Tp0794dOp3O6WsrlUqvlXD5kzMVfMN1hoeLlqy7LEI1Y1HVNPNc1IxFi6g6ORbiR3XSY8KRR4avV9Lx1jp1ikry968iTAqVSEuwAConscJxHPQNZvQSeapOui4cLIeQ327urVIdWkLI442AZCAhyGWXy+X47rvvvCWLU7p06YI+ffrYvs477zwAfI9HWloaAGDq1KlQKBSYOXMmDh06hK+//hpvv/22XTYilDhdVgeJxHPHIkolR2K0MmQnQ5XVGgEACdHiOZ/NS/JC2/i1LnAUazO0lXRdOMprjbble6GKdRFYbIR7CzIdoVbIEBeppHISAOW1JsSLfO/SZB2eOhMDo4VFbITI1zeWHDcAqKzjDV9tuPiORYOZQXltaPcIlTfZDe4uJw50BOcCJ0+ejB9++MELoniGRqPB2rVrkZubi0GDBuHhhx/G/Pnzcffdd/tbNL9wuqwOaTq1KBM1cuIjcbqsFhwXekvHymqMkEog6gOO6tR5ymr5AQPxUd4xzkLd+C2r4R9u4l9fdcjfuwBvPMSJbDjowuWIpAZjr927zUGd0L6+VsPXW7o31O/f0qb7V2zHOFAQnGfs1q0bFi5ciC1btmDQoEGIiIiw+/kDDzwgmnDOyMzMdGjk9uvXD5s2bfL6+3d2GJZDbkUdhmbHivJ6OfGR2HqqAiUGI5I82IsRiJTVGBEToYRMpM3QAL94kBZhedF4aLEI67zEKFFfO5AorzVBLZeJul0X4EvNdudVo95kQbgiNJsTOY5Dea0RvZKjRX1dWkLIY9UNCaLrBjJ8AW8GHZqDZoMynJegBztlNUbowuVQhIVmH4/gp8Inn3wCrVaLXbt2YdeuXXY/k0gkPnEsiPbJr6yHycIiOz6i45NdICe+uc8i5ByLWqPoypcWYfHYHm5il0KR8QCAv75i37uA/RLC7kmh6bjpG8wwM5zXru/aw8Uh3WDsLcM3TUfbtwFvBnV43RCq4+mtlHtJ9wYKgh2L3Nxcb8hBiMjBQn5pYe8UjSivl5PQNBmqrBbDusaJ8pqBQlmNEYMzxXHQWpKmU+NIUXDsTHEXr5c7hHgDd1mN0eMeK0e0XEIYqo6FtZRE7P4ggO8DYDl+sp91/GyoUVbjnTJJlVyGxGglORZeKPEFqIfFSlmNEf3SxbG/AhGPwiEcx4Vk3X1n50AB71j0SxPJsQjRkbP6BjPqTYzo6XigeRGWvt4s+msHCqU1RkQpw0SdqgPQPHUAMDMsKuuMomeDAMoIAUCxXvyhDlYo6ttco+6NqG+6LjzkB2eU1jSKXuIL8FOmdOHykHbcGkwMaowWr+jeQMEtx+KTTz5Bnz59oFKpoFKp0KdPH3z88cdiy0a4ycECPdRymc0h8JSkaBXCFbKQmwxlnczSReRZ6gBtiAb4iGyKhwscHREmkyJFq8a5EL62RdWNYLnm0g8xoe3bzZ/dmr0Rkwxy3Gx7mJKixS+97RITjso6E2qNFtFfO1A4V9XgFd0AIOR7hAqs966HO8QCGcGOxfz58zF37lxMmjQJK1euxMqVKzFp0iQ89NBDmD9/vjdkJARgYVjsP6dH75Ro0aIRUqkE2fERIbfL4mylOLtAHBHqk6EYlsO5qgbRF2BZsT7cQjWjajN8vXB9kzVqhEklIXvvArA5rVYnS0xCXTcAwNnKesRFKkUfPAAAaSF+fRtMDEprjF4JmAG8zik2NKLRHJrjvq33lTfshkBB8P/aJUuW4KOPPsLNN99sO3bVVVehX79+uP/++7Fw4UJRBSSEcajQgJpGCy4SaSKUlZz4SBwsKESt0YJILyj7zshZr2YsmpfkhSJF+gZYWM6LDzc1Np8sR2WdCbEhmJK2Pty8YfjKpBKk6tQh3cNi/eypWvHv3xStGlJJaJdC5VfWe0836Jp1b0+Rp3oFAlan2FvX12pQn6uqR9eE0OvBsj7TM7x0fQMBwRkLs9mMwYMHtzk+aNAgWCyhm1rsLGw9VQEAuDhHfMcCAHJDqByKSqG8h1X5dvGC4QtQH0Dz9aWMkDfIa4qoqxXi9gcB/NS4pGiVraQi1KgzWlBea/LqvQuEbsYi34vZNgBIC/EFsHmV3ssWBwqCHYvbbrsNS5YsaXP8ww8/xC233CKKUIT7bD1VDkWYFOeLPEPa1sAdQuVQJ8tqoVHLESPi5mIr8ZFKqORS5IVo1Nfar5MZ552pN6G+3fxkaS1kUonXHm5pOn7DrnW7dyjBcRxOltaia4L3JjYla9Uo0jd67fU7M7nl1hJUL+mGEHcsTjYNYcn00vW1jqQvDtH793RZLRQyKZJDbDR/S1yqaZk3b57t3xKJBB9//DHWrl2Liy66CACwY8cO5OXl4fbbb/eOlIRL6BvM2H66AkNz4kSftJOT0LzLIhRgWQ5HigwYkK6FRCLu5AyA/3+UpgvHuRB9uFlH7XqrFCHUo5JHi2uQEx8BZZj4EXXAfsOuN0audmbOVTWg1mhBjyTvldEkaVTYdbYKJgsbcku2Dtt0g3fKaBKjVVDIpCEbdDhaVAMA6OEl3ZvS1LQcqo7xkaIadEuMRFiI7qABXHQs9uzZY/f9oEGDAACnTp0CAMTFxSEuLg6HDh0SWTxCCH8eKYGZ4TChb5Lor50ZGwGJJHQcizMVdag3MaJv1m1Jl5hwbD5RDpblIBV57F9n50iRATERCq+M8gVCOypZa7Qgr7Iek/qneO09Wm43P79LaG3YPVbMG2be3OGR3DQNqcTQGHIlFd4OOlh7hEK1TPJwkQGpWjU0arlXXr85YxF6jltVnQnFhkZc0i209n21xiXHYsOGDd6WgxCBNQeKIJNKMKaX+I6FSi5Dmk6NU6Wh0WNh3QXSK8V7jkW6Tg0Tw6KkphHJITSajmE5HCuu8Vo2CAB04XJEKGQhaTxYDbMeXjR8QzkjdKjQ+9c3Wdsc9Q1FxyJCIfPKKF8r6THh2HG6AhzHeU0HdUYazQxOldVieLd4r71HtCoM4QpZSGYsDnvZKQ4UQjdXE2SUGBqx4VgZLuka55WeAIDvs8gtrwPDBn/D5vbTlQCACzJjvPYezVH10IrsHC40oN7EYGAXrdfeQyLh+wtCsTl+5xn+3h0kcp9VS6xGXyg6bjvPVEIZJkXvFO9t1rXWZxeFWNTXZGGxN78a/dO1Xs3ipuvUMFpYlDUt4gsV9p/Tw8xwovdgtkQikSBZowpJx8Kqeweka/0riJ8RPDe0sbER7777LjZs2IDS0lKwLGv38927d4smHOE6X+/MB8NymDqki9feIyc+En8dK8O5qnqvNdZ1FrafrkCaTu3VaGHLyUUXZnnPgelsbD/NTy4TeyRya9JjwrH+aCksDBtS9a7/5FZCLpN49eGmDZcjUhkWck6xhWGxO68KA9K1Xu19SLI5FqFlnO0/V41GM+t13dClxVS+BC8s4eus/JPL615vP2+SNWrsyasKuYzQjtOVUMtl6JfmvaBDICDYsZg5cybWrl2L6667DhdeeGFI3TSdFTPD4qt/8pAYrcSoHgleex/rZKjTZXVB7Vicq6pHbnkdrh+U5tX3CdVyku2nKxAmlXg1og4AqVo1GJZDSY0RqV7Y8N0ZMVlY/HumCv3StKIPcGiJRCJBqlYdchH1feeqUW9ivG6YWRtgQ22yjq+CDilN+qCguhGDMrz6Vp2KracqoAyTet3wTdaosNnEoMZoQbTKO70cnY1GM4PdeVW4MCsG8hAKZDlCsGPxyy+/YM2aNRg2bJg35CHc4PvdBSjSN+LRcd29GpnNiW+eDDXSiw6Mv/n1QDEAYEyvRK++T1rToqZzITSdpM5oweaT5RiUoUO4wruLFq3ORFF1Q8g4FltPlaPWaMGont7//5msVWHrqdCqU197qAQAMKqnd3VDfJQSMqkk5By3dYdLEKUMQ/907xq+KdqmjFAI7QqprjdhR24lLjsv3mvT4qwktxg5GyqOxeYT5TBaWFwa4o3bgBs9FqmpqYiKCr1tip0VC8PivQ0noVHLcftQ74ZechJCY5fFLweKEKkMw/DzvNfgBgBRKjmilGEhZTxsOFYKo4XFhH7JXn+v5CbjIZQWjf3eZPiO6y3+AIfWpGjVMFnYkNllwXEc1h4uQVK0Cv1SvWv4yqQSJEQpQ6oU6lxVPfad02N0r0SvG74p2tAbifrHkVIwLIdxfbyvG5KaMm6FIaR71xwoAgBc0cf7z7bOjmDH4vXXX8fjjz+Os2fPekMeQiArd51DXmU9Zl6ShSgvRwZiIxTQqOVBPRnqUKEe+/KrMa53kldLSaykhNgirO93F0Ai8Z3hC4SO8dBgYrB6fyG6J0bZyha9SUpTVDJUjIddZ6uQW16H8X2SfDIeOinEGmB/3FsIALiyr/cNs4QoFWRSSUgFHb7bdQ5ymQSjvZxtA5qDOqFSyldrtGDt4RL0TdWE3BQ3Rwh2LAYPHozGxkZkZ2cjKioKMTExdl+E79A3mPHq78cQF6nEjGGZXn8/iUSCnPgInAzijMVnW84AAKZfnOmT90vWqlBY3QCOC/5JW3kV9Vh/rBSjeiQi0QcNk7ZFTSFiPPy8rxCGRotXBzi0xOq4FVaHhvGwfEceAPju+mrUKK81wmRhOz45wLEwLP63/SySolW4rLt3M8UAnxFKjFKGTLb4ZGkNtp2uwBV9kr02NbIl1lKowhBxLFbtPodaowU3X+gb3dDZEVzkfPPNN6OgoAAvvvgiEhMTQ6a2tjPy9h8nUFlnwmvX9/d6tsJKdnwkdudVo7reBG249xWUL8mrqMcPewswOEOHvj6a6pCi5cceVtaZEBvkG4w/3ZILjvOd0xYfpUSYVIKCEDB8GZbDR5tOI1whwzXnp/rkPZNDqNwhv7Iev+wvxIVZMTgv0TelwEkaFTguNJbkrT5QhCJ9Ix4Ze57PGl9TtGrklgdv9r0lH/2dCwC4zcvl0laSo63DB4JfN1gYFp9tOYNoVRgmD/TeUtJAQrBjsXXrVmzbtg39+/f3hjyEixws0OPzbWfQP12Lawf6xpAAgGxbA3cdBmUEl2Pxyu9HYWY4PDy2u8/es7mcpDGoHYu8inos33EW/dM0GNbVuxNfrMikEiRGq0IiKvnj3gKcKK3F7JE5PmuWtDXHh8D1fXf9CZgZDnNHdfPZe9oaYIPcsTBZWLy+9jiilGGYOsR3I5qStWr8e7YKjWbGJ2Wv/uJkaS1W7srHhVkxGOzlSXxWotWhsyRv5a5zOF1ehwdGdfP6QJJAQXBooEePHmho8M+DZPXq1RgyZAjUajV0Oh0mT55s9/O8vDxMmDAB4eHhSEhIwKOPPgqLxeIXWb2JycLikZX7IAHwwuQ+Pqn3tdI8cja4yqH+OlaKX/YXYVSPBAzN8Y3hC7QoJwly42zRr0dgZjg8cUVPn2Y5U7TBX6de08iXREapwnD3pTk+e99EDe8IB3u5w568KqzcdQ4XZcfgYh/qhlDJCH2+9QzyKutxz2U5PinTsZISArtCOI7DC6sPg+WAx8f38JnulUgkIdEjpG8w4411xxEXqcDdw7P9LU6nQbBj8dJLL+Hhhx/GX3/9hYqKChgMBrsvb/Hdd9/htttuw4wZM7Bv3z5s2bIFU6dOtf2cYRhMmDABJpMJW7duxeeff47PPvsM8+fP95pM/uLd9SdwtLgGcy7vij5enk7SmpwWGYtgobrehCe+O4BIZRgWTu7j0/cOBePh532F+PVgMa7ok+RTpw3gHbfKOhMaTIxP39eXvPTrURTpG/HEFT2gCffdaEdlmAzxUcqgvneNFgZPrjqAMKkEz13dx6dOsbUBNpiNs1NltXht7TFkxobjjmFZPn3vFG3w92Ct2l2ADcfKcM3AVK/vDWpNikaNoiDvH3z250MoqzHisXE9EKmkbIUVwVdi/PjxAIBRo0bZHbfOMmcY8R/gFosFc+fOxauvvoqZM2fajvfq1cv277Vr1+Lw4cP4448/kJiYiAEDBuC5557D448/jmeeeQYKRXCU7ezLr8b7f51C75RozB7Z1efv3yUmAjKpJGgyFmaGxZwv96DY0IhXruvn830HqUE+uSivoh5P/3gQMREKPOdjpw1odtyK9A3I9sGkJF/zy/5CLN+Rh4uyY3DzBb5vHEzRqFAUxD0sC38+jKPFNXho9Hno5qPeCivBPnygwcRg7oo9MDEsXru+P9QK35YjBXuD8cnSWjzz0yHERSqxYFKvjn9BZFK0Kmw+ycDQYPFpwMNX/Li3AKt2F2Bk93hcP9i7y3QDDcGOxYYNG7whR7vs3r0bBQUFkEqlGDhwIIqLizFgwAC8+uqr6NOHN1a2bduGvn37IjGxeZTauHHjcO+99+LQoUMYOHCgz+UWG329GbO/3A2ZVILXb+jvl+2OijApusSE43QQNL1xHIcFPx3C5pPluGVIF9wwON3nMljLSYJx7GFNoxkzP98JfYMZn06/AHF+6CFJ1Tb3sASbY3G40IBHV+5HfJQSb9800KclkVZStGrsL9DDzLBBt232q3/ysHxHHi7pGofZI31XYmYlmIcPcByHR7/dh4MFBjwwqhsGZ/p+omTzVLPg0736BjPu/u+/qDcz+OC2QX4ZtGLLxusbgs6x2Jdfjce+3Y/EaCVentKPhhi1QrBjMWLECG/I0S6nT58GADzzzDN44403kJmZiddffx2XXXYZjh8/jpiYGBQXF9s5FQBs3xcXFzt9baPRCKPRaPvem+VcnsCyHOZ9sxfnqhqw6Nq+6JEU7TdZsuMi8PeJMlgY1qubvr0Jx3F45qdD+LLJcHjmqt5+kUMZJkNcpDLoopJ1RgtmfvYvTpTW4j9X9sDI7v7Z1N7y4RZMnCytxe2f7oCFZbHklvN9Mr7XEckatW1yUZoueBqMf9lfiKe+P4A0nRrv3DzQL3pOJuXr1IPN8OU4Ds/+fBi/7C/CFX2S8KAPG+JbkmzrsQiu61vTaMa0T//B6fI6zJ/YCxd39c8m6NQWjlvPZP/ZK2JzvKQGd3y2EwDw0e2DkeAn3duZcUtbbtq0CbfeeisuvvhiFBQUAAC++OILbN68WdDrPPHEE5BIJO1+HT16FCzLz/F+6qmnMGXKFAwaNAjLli2DRCLBypUr3fkINhYtWgSNRmP7Sk/3fdTaFT74+zT+PFqKa89PxU0X+FfG7PgImBkO+VWBqZDNDIv/fH8An287i6HZsfjo9sF+jbamalVBtQugzmjBjM924p8zlZh5SRbuutR/TW22OvUgur4nS2txy8fbUV1vxuKp5/sl2mslpUVGKFhYvb8ID67Yi7hIJZbfOcSnDcWtSdGog8rw5TgOC385jM+2nsFF2TF4/Yb+fsm0AUBMhALKMGlQ3buGRjPu+Gwn9uZX477Lcnyy38oZVt0bTKVmx0tqMPWj7TA0mvH+LeejX5rW3yJ1SgRbU9999x3GjRsHtVqN3bt326L9er0eL774oqDXevjhh3HkyJF2v7Kzs5GczG/ibNlToVQqkZ2djbw8fmlRUlISSkpK7F7f+n1SkvMtv08++ST0er3tKz8/X9Bn8AXbT1fg1d+P4rzESDw/2bcNhI4I5MlQ+gYzZizbia/+ycel3eLw6fQLfF7b25pkjRqlNY0wM4G/CKtI34Drl27DP7mVmDEsE/83wbdToFqTGmTlDjtOV2DKkq0orzXhrZsGYKwPNpi3R0qQjZz9ZHMu5ny1G7oIBZbfOQQZsRF+lSdFq0JVvTkohg80mhk8sGIvlm05gwuzYvDp9Av8Op5TIpEgRasOGt1QUN2A65dsw84zVbjr0iw8Oq67X3VvsJWabTlZjilLttoCOqN8sME8UBH8v/r555/H0qVLcfvtt2PFihW248OGDcPzzz8v6LXi4+MRH9/xls1BgwZBqVTi2LFjuOSSSwAAZrMZZ86cQUYGP/d66NCheOGFF1BaWoqEBL7sYt26dYiOjrZzSFqjVCqhVHbe/QGlNY24/6s9UMtlWHLroE4xJznb5ljUYVRPPwsjgEOFetz/5R6cLq/D1CFd8OxVvTtFXXiKVg02CMpJ9p+rxl3//RclBiMeHnMe5lze1e9OsEYth1ouC4pSqJX/5uOp7w9CLpNg2fQLMPw8728o7ohkTXBkLIwWBs//cgRfbD+LnPgIfDbjwk6xOyK5xTjqnADuESqrMeKe/+3CrrNVGNc7EW/eOKBTPMuSNSrsP6f3txgeszuvCvd8sQulNUY8cUUPzBqe7XfdGyzDBziOw4qd+Xj6h4NQK2T4bMaFuKSbf8rLAgXB/7OPHTuG4cOHtzmu0WhQXV0thkxtiI6Oxj333IMFCxYgPT0dGRkZePXVVwEA119/PQBg7Nix6NWrF2677Ta88sorKC4uxv/93/9h9uzZndpxaA8Lw+KBr/agrMaId28e2GkeLNYleafLAyNjwXEcPt96Bi+uOQoOHOZP7IUZwzL9rnitpLQYKxmIjgXHcfh0yxm89OsRSCQSvH3TAFw9wHdLG9uDj0oG9jz1BhODp388iG93nUOyRoWPpw1G7xTfjpl2RjBkhPIr6zHny93Yd06Pi7JjsPRW/zS7OqJl1Lez6H+hbD5Rjge/3ovyWiNmDc/G4+N7+K38qTUpWjW2nqqAodHss8WSYsJxHD7elIuXfzsKmVSCd28eiEn9O8f2Z7VCBl24PKCDDrVGC57+4SC+31OANJ0ay6Zf4PPpcIGIYMciKSkJJ0+eRGZmpt3xzZs3Izvbe7XUr776KsLCwnDbbbehoaEBQ4YMwfr166HT8bOZZTIZfvnlF9x7770YOnQoIiIiMG3aNCxcuNBrMnmbN9Ydx/bTlZg2NKPTKAsAiI1QQKOW42Rp53csivQNeOr7g1h/tBRdYsLx7s0D0T9d62+x7AjklHFlnQmPfbsffxwpQWZsON6ber7Pd6t0RIpWjV1nq2wjsQOJQ4V6PPT1XhwvqcVl3ePxxg0D/Frz35q4SCXkMknAlkLxTdoHoW8wY/bIHDw0+rxONZDCtsQtAI0zM8PirT+O4/2/TiFCEYZ3bh6IqzrRcwxovr6F1Q2ITgosx6K81ognvtuPP46UIjs+Aounnt/pmqSTNeqAzRYfLNDj/q/2ILe8DqN6JOC16/tD14l0b2dGsGNx1113Ye7cufj0008hkUhQWFiIbdu24ZFHHsHTTz/tDRkBAHK5HK+99hpee+01p+dkZGRgzZo1XpPBl6w/WoL3/zqF/ula/GdC56o3kkgk6J4YhSNFBrAs12miTy1hWQ5f7czDS2uOosZowTUDU7Hw6t6I6oRRqUAsJ+E4DqsPFGHBj4dQUWfC1QNS8MI1fTvlkqBkjQr1psCap26ysFi84SQWbzgJDsCj47rj3hE5ne7/mrRpclGgjUQtrzVi/o8HseZAMWIiFFg2/QKM7OGfyWXtYQ06BNo46oMFejz67X4cKTKgb6oG700d6Pd+FUck25bkNfp10qIQOI7DT/sK8cxPh1BVb8bkJt0b0Ql1b4pWjePHasCwHGSdTHc5w2hh8N76k1jy1ylIJMDTE3vhjk5U4RAICL4Tn3jiCbAsi1GjRqG+vh7Dhw+HUqnEI488gvvvv98bMoYc+ZX1eOjrfdCo5Vg8dSCUYf5tLnZEn1QN/jlTibOV9ciK61wPjNNltXhy1QHsyK1EskaFt28egMt7dN5Gq0ArJyk1NOL/fjiItYdLoAuX460bB+DqASmdVvGmaANrnvrBAj0eWbkPR4tr0CMpCq9d37/TZYFakqxR43hJjb/FcAmO4/DL/iIs+OkQKutMuLJvEhZe3ccvO1ZcIdCymY1mBm//eQIf/n0aEgD3X94Vcy7v2imfYYC9bggESg2NeOqHg1h3uASxEQosnno+ruyb1Il1rwoWlkNZjRFJms4/lnV3XhUe+3Y/TpbWomdyNF69rl+n1r2dFcGOhUQiwVNPPYVHH30UJ0+eRG1tLXr16oXIyMCs/+xsGC0MZn+5G/oGM5ZNv6DT1tz3TeOjOwcK9J3GsahpNOPd9SexbEsuzAyHWy/qgsfH9+iUWYqWBEo5iYVh8eU/eXjt92MwNFowoV8ynr2qd6c1yqxYmwg7+zx1fb0Zr687hv9tPwupRIK5o7ph9siuUIR1ntIcR6Rq1fgntxL1JkunaMh1hnUT8eaT5YiJUOC9qQMxsV/nKs1pTbQqDBGKwBg+8PfxMjzz0yGcLq9Dn9RovDKlP3qldN7/b0DglJqZGRZfbDuLN9cdR43Rgkn9U/DMpF6I7ey6t0XGrTM7FtX1Jryx7ji+2H4WcqkUj47rjruHZ3eK4S6BiNtPAYVC0e60JcI9nv/lCPaf02P2yJxOmZq30rfJiz9YoPd73SzLcvh21zm88vtRlNea0DdVg2eu6oVBGf6b7y8EaznJuU68F2TbqQo8+/MhHC2uQVK0Cq9e3x/j/Dzq1FWao5Kd03hgWQ4rd+Xj5d+OobLOhMEZOiy8uk+nN8qstCzl65rQ+QJMdUYL3ll/Ap9u5gMONwxOw+Pje3R6owzgA3npMeE4W1Hvb1GckldRj+dWH8a6wyVQyaV4fHwP3HVpVqfqVXFGcgBkhLaeKsczPx3C8ZJapGrVeP2G/n4fM+0q6U2B0bzKOgzK0PlZmrYwLIev/snD62uPoarejMEZOrw0pS+6JlCDtie47FjccccdLp336aefui1MqFNqaMSPewswNDsWD40+z9/itEtWXCTCFTLsy6/2qxzbT1fgxTW8MxYXqcDLU/ri+kHpna4WvSMyYyOw80xlp+tZKahuwItrjmD1/iIoZFLMGdkV943M6dSR6dZYFzUVdELHbXdeFZ79+TD25VcjLlKJN27oj2sGpnba0gZHtCzX6UyOBcty+GFvAV757RiKDY3okxqNhVf3wfldOp+B0x45CZFYc6AIDSbG7zt3WlJvsuD9Dafw4abTMFlYTOyXjCev7Gkr7QwEIpVhiFaF4VwndCwKqhuwaM0R/LK/CIowKR4Y1Q33jsjpVPdAR+Qk8NUMp0rr/CxJW/7JrcQzPx3C4SIDEqKUnb6kN5Bw2Tr47LPPkJGRgYEDB4LjOG/KFLIkRKuw+oFLoZRLO320RyaVYFCGDjtyK9FoZqCS+1bZHSzQ45Xfj+Hv42UIk0pw5yVZeGB0t4AcGQgAXRMiselEOQqqGzrF/PzqehOW/HUKn209A6OFxZheifi/CT07ZQNmR6TrwhEmleBUJ1roeKqsFq/+dgy/HSqGrOn+nTu6W6cv23NERix/v+aW13WK3RoAX5bz0q9HcbjIAI1ajucn98HNF3YJmAbSluTER4Lj+OvbGbJYZobFN//m4+0/TqC0xogeSVF45qreuCg71t+iuUV2fCROdaIJh1V1Jrz/10l8vu0sTE269+kJvdAl1v/PBaFkxkZAKkGn0r0nS2vx+tpj+PVgMRQyKe69LAezR3btlINHAhWXr+S9996Lr776Crm5uZgxYwZuvfVWxMQERqlJINEZjEpXGdY1DptOlOPfM1U+WxhzuqwWr687jtX7iyCRAJMHpOChMecFpMHbkm5NqdcTpTV+vQcaTAyWbc3F0r9OwdBoQY+kKDx5ZU+M6CQGozsowqTIiovoFA3GpTWNePuPE1ixMx8My2Fc70Q8Oq5Hp4r0C6V701z3Y53g+h4s0OPl345i04lyKMKkmDUiG/eN6BoQTfvOyGnaG3SqrNavjgXLclhzsAivrz2O3PI6xEUq8NzVvXHzhV06fSCsPbonRmFvfjXKa41+7Rez6t4lf51CTaMFvVOi8cQVPXBpt8DVvSq5DOkx4Z3CsSjSN+DtP07gm3/zwXLA2F6J+M+VPZHZSXpEgwmXHYvFixfjjTfewKpVq/Dpp5/iySefxIQJEzBz5kyMHTuW0kchyCVdeWdi08kyrzsWp8tq8f5fp/D9ngIwLIdRPRLwyLjunboZVwjdEnnD8mRprV8mWJksLL7ddQ5v/3kcJQYj0nRqPHt1b1zdP7VTlWa5y3lJUVhzoMhvDcZVdSZ8vPk0lm05g3oTg8EZOjx5ZY+A6QNqj/goJbThchwr9p9jcbykBu/8eQKrDxQBAK49PxUPj+0eUGU5zrAuxvPX3iCO47D5ZDle+e0YDhToEakMw0Ojz8Odl2Z1yhGnQrHq3uMlNX5xLIwWBt/uOod3/zyJYkMj0mPUeH5yH0zqlxIUujcnPhKbT5TDwrB+cUCr6kxYurE5+z4kKwaPX9Ej4EoiAwlBWkGpVOLmm2/GzTffjLNnz+Kzzz7DfffdB4vFgkOHDtFkqBCjV3I0kqJVWL2/CI+P88421SNFBizecBKrDxSB44AhWTF4ZFx3XJAZ+AZZS7o1RayPFvnWOGs0M1i56xyW/nUKBdUNiI1Q4JlJvXDzkC6ddkSkO3RPjMLq/UU4WVqLfmlan71vRa0RH23KxX+38Q5F14RIPDauO8b0SgyaYIx1r83hQoPPlxAeK67BO+tPYE2TfrisezweG9ejU5QMiUVOfCSkEuBoscGn78txHP46VoZ31p/AnrxqKGRS3DEsC7NH5gRE47urdE/iM27Hi2twcY5vMu8Ar3u/+TcfS/46hSJ9I2KadO/UIRmdfhKcELolRGL90VLkltf5dGt1WY0RH286jS+2n0W9iUHP5Gg8Pr47RpwXHzS6t7PidrhBKpVCIpGA4zgwDCOmTESAIJVKcPWAFHzw92nsPFOJISLV2HIchx25lfh402n8caQUADDivHjMubxr0DkUVrThCmTGhmNXXpVP3q/BxODLf/Lw4d+nUGIwIiZCgcfGd8ftQzODsta0R5PxsP+c3ieORWlNIz7elIsvtp1Fg5nBeYmRuP/ybriyb3JA1vl3RI+kKOzIrUReZb1PyhIPFerx/oZTtgzFyO7xeGBUNwwMwiikWiFD96Ro7Mmr9onjxrIc1h4uwXsbTuBggQEKmRRTh3TBfZfldNrx555gXYy3v0Dvk/drMDH46p88LN14CqU1RsRGKPDkFT1w60UZQZEBak3/dC0AYE9etU8ciyJ9Az7YeBpf/ZMHo4XFeYmRmHN5N0zsmxwUGaBAQNBdbDQabaVQmzdvxsSJE/Hee+9h/PjxkEqDx8MmXOe6QWn44O/T+HhzrseORaOZwY97C7BsyxkcbSqrGN87CbNHdkXftOBfUjMoIwbf7T6Hshoj4qO8ExEsrWnE/7bnYfn2s6ioMyE+Son/m9ATU4d0CahJT0IZ3OSQ7jxTiVsvyvDa+xwtNuCTTbn4cW8hTAyLHklReGBUN4zvnRTUD7XBmTH4fNtZ7Mit9JpjwbIcNh4vw0ebTmPrqQoAwOU9EvDAqG4Y0GS8BCvnd9Fi+Y48FFQ3eM24bzQz+GFPAT7dkovjJbVQhkkxY1gm7h6ejWRN4JeUOSM+SonsOH4qnzcprWnEF9vOYvmOPFS20L23DMkIqElPQrGWHO3Oq8INF6R77X0OFxqwbEsufthbADPDoU9qNOaM7IaxvRKDWvd2Rly2JO677z6sWLEC6enpuOOOO/DVV18hLs53aUOic9ItMQrjeyfht0PF2H66wq3JIIcK9fhuVwG+33MOVfVmRCrDMP3iTEy7OLPTLN/zBYMzdfhu9zlsO10h+m6QgwV6fLolFz/vK4SZ4ZCmU2Ph6N64YXC6zyd6+YOYCAW6J0Zhx+lK0aO+LMvh7xNl+GRzLjadKAcAXJCpw52XZmNMz9B4qA3J5h237acrcMNgcY2HBhMfcPh4cy5OltZC1pQpvevS7JDZijsoQ4flO/Kw43Ql0gaJ61iUGKwG71lU1ZsRpQzDrOHZuPPSbK8FODobF2bFYMXOfBRWN9jGJ4vF4UIDPtmci5/28QZvl5hwzB3VDTdeEBq6N0mjQqpWje2nK0TXvQzL4c8jJVi25Qy2neaDDYMzdJg9sisu604lT/7CZcdi6dKl6NKlC7Kzs7Fx40Zs3LjR4XmrVq0STTgiMHj8ih7YeLwMD329FyvvGepSRO1MeR3WHi7Gqt0FtuxEdlwE5o7qhimD0gJy7KanXN4jARIJ8NvBIlEcizqjBasPFOGbnfn49yxfYnVhVgzuGJaFMb0Sg7Ikpz0u7hqLZVvO4FChQRSDtNTQiJW7zuGbf/NxtqIeMqkEk/qnYOYlWUEfQW9NQpQK5yVGYuOxMpgZVpSNtUeKDPjqnzx8v6cANY0WRCnDcPfwbEy/OFN046+zM+K8eEglwG+HijFlUJrHr8ewfEP2Nzvz8fuhYlhYDhmxvMF73eD0oCyHbI9hXeOwYmc+1h0uwbSLMz1+vXqTBb/sL8LXO/Oxy6p7M2Mw89IsjO4Zerr38h4J+GL7WRwrqbGVnnlCsb4R3+0+h6935iOvsh5hUgkmD0jBjGFZttIrwn+4rD1uv/128v4Ih2TFRWDRtX3x0Dd7MXnxFjw6rjuu7Jtscw5YlkOxoRH78qux62wV/jpeZptwEqUKw9QhXXDdoDQMTNeG9D2WGK3CBZkx+PNIKSrrTIiJUAh+DY7jsDuvGiv/zcfP+wpRZ2KgDJPi2oGpmDEsKyRKypxxVf8ULNtyBt/uOue2Y2G0MPj7eDm++Tcf64+WgmE5xEUqcc+IHNw2NCMophC5y1X9U/Da2uP461gZxvRyb7JZZZ0Jvx4swsp/z2Fv0/LN7olRuHlMesgGHAAgNlKJi7JjsfF4mdu6AeC3ZH+7Kx/f7jpn20R/cU4sZgzLwuU9EkLO4LUyqmcCwhUyrNp9DrcPzXDrOcSyHPbkV+PbXefw875C1BotUMmluPb8VEy/ONOnQyM6G1f2TcYX28/i+z0FePIK9xwLo4XBhqOl+HpnPjYeLwPLAbERCswZ2RW3Dc1AYrRKZKkJd5FwtO3ODoPBAI1GA71ej+jo4Jks4gvWHCjCf74/gOp6MwAgLlKJMKkElXUmmBjWdl58lBKjeyZgdM9EDOsaFxLpYFf5eV8h7v9qD+68JAv/N7GXS7/DP9CqsOZAMX49UGQzGPqmanDDBem4qn8KNOrQNMhawnEcrnh7E85U1OGvR0YiSePag8hkYbHlZDl+3l+IdYdKUGO0QCIBhneLx80XpmNUz0RRIvSBTmF1A0a8ugE9kqLx4+xhLpeA6evNWHekBD/vK8Tmk+VgWA4quRST+qXg5iFdQj7gYGX1/iLM/nI3Zg3PxpNX9nT5985W1GHNgWKsOVCEA00NyskaFa4blIbrB6UH5OI1b/DkqgP46p88LJtxAUZ2T3DpdziOw978aqzeX4Q1LXRvn9Ro3HhBF9K9TTAsh7FvbkSJwYiNj17m8lSxRjODTSfKseZAEf44zOteqQQY2T0BN1yQjst7JJDu9RFCbGNyLFpBjoVn6BvM+GlfIXbmVuJcVT2YpqhCqlaNPqnROL+Ljh+fGKKRsY5gWQ5XL96Cg4V6vHXjAFw9INXhecX6Rmw9VY7NJ8qx6WQ5ymqMAIA0nRoT+ibj6gGpQTVyUyzWHy3BHZ/9iwszY/DJ9MEOI+Acx+FsRT02nSzHxmNl2HaqHHUmfvJd31QNJvZLxsT+KSGdnXDGc78cxiebczFreDYeH+94BLWZYXGkyIC/j5fhr2Nl2JNfDYblECaV4NJucZjUPwVjeiWGbHbCGSzLYeK7m3G02IAPbxuM0U6yQvUmC/7JrcTmE+XYfLLcVmoapQzDmF6JmDQgBcO7xYdsdsIZRfoGjHztL0Sr5Phm1lCni9PKa43YcrIcfx8vx6YTZShtqXv7JWNSv5SQ6f0RwpoDRbhv+W4M6xqLD28b7HACFsdxOF1exz/XTpTb6d5+aRpc2TcZ1wxMpeyEHyDHwgPIsSD8zdmKOly3dBvKaowYlKHDoAwdVHIZqutNyK+sx6FCg+1hBgDnJUZiZI8ETOibjL6pGorudoDV+E2IUmJivxSk6tRgWBbFeiNOldVi/7lqVDVl3WRSCc7vosVl3RMwsV9ywG949zYNJgY3fbQd+/Kr0TslGqN6JEAXoUCDmUFBVQOOFdfgYKEejWY+gxmhkOHirnG4vEcCxvdOgs7NEp9Q4VRZLaYs2Qp9gxmXd0/A+Rk6RChkqKo3I7+qHocLDThRWguG5R/rcZFKjDgvHhP6JWFY17ig2k3jDX7aV4i5K/ZALZdhQt9kdE+KgkQiQVmNEWcr6rD/nB4F1Q2287slNOvefmmkezviqe8PYPmOPCRrVJjYLxnJGjUsLIsSgxHHS2pwqNCAyjoTAF73DkjXYnzvJIzvk4T0GMqs+RNyLDyAHAuiM1BiaMTLvx3FmgNFNiMMAOQyCbonRaFPigYXZMbgkm5xFL0RCMdxWL4jD4s3nERRU+mCFUWYFL2So9E/TYOhObEYmhNHpQwCqTdZ8Mpvx/DNv/moN9nvOIpShWFAuhb907S4uGssBmfEBNUyMF9wtqIOC38+jPXHStH66Z2qVaNXSjQubNINPZoMY8J1Np8oxwtrjuBIkf1CQqkE6JoQib6pWlyYpcOl3eJDboiAp3Ach8+2nsHiDadQXmu0+5kyTIpeKdG8bsiJxUU5sYimrGWngRwLDyDHguhMmBkWhdUNaDSz0IXLEROhQBjVlIoCy3I4W1mP8lojpBK+eT4xWkU1uyJhtDA4VVqHWqMFijApUrQqxEUoqQxSJAyNZpwqrYXRwkIbLkdStAracMr4iEWxvhEF1fWwMBzio5RI1qiDet+EL2FZvuSpqt4EqYSfKpesUdGzrRNDjoUHkGNBEARBEARBEDxCbGNyDwmCIAiCIAiC8BhyLAiCIAiCIAiC8JiAcSyOHz+Oq6++GnFxcYiOjsYll1yCDRs22J2Tl5eHCRMmIDw8HAkJCXj00UdhsVj8JDFBEARBEARBhA4B41hMnDgRFosF69evx65du9C/f39MnDgRxcXFAACGYTBhwgSYTCZs3boVn3/+OT777DPMnz/fz5ITBEEQBEEQRPATEM3b5eXliI+Px99//41LL70UAFBTU4Po6GisW7cOo0ePxq+//oqJEyeisLAQiYn84qClS5fi8ccfR1lZGRQK16ZlUPM2QRAEQRAEQfAEXfN2bGwsunfvjv/+97+oq6uDxWLBBx98gISEBAwaNAgAsG3bNvTt29fmVADAuHHjYDAYcOjQIaevbTQaYTAY7L4IgiAIgiAIghBG253qnRCJRII//vgDkydPRlRUFKRSKRISEvDbb79Bp9MBAIqLi+2cCgC2763lUo5YtGgRnn322TbHycEgCIIgCIIgQh2rTexKkZNfHYsnnngCL7/8crvnHDlyBN27d8fs2bORkJCATZs2Qa1W4+OPP8akSZOwc+dOJCcnuy3Dk08+iXnz5tm+LygoQK9evZCenu72axIEQRAEQRBEMFFTUwONRtPuOX7tsSgrK0NFRUW752RnZ2PTpk0YO3Ysqqqq7Gq7unXrhpkzZ+KJJ57A/Pnz8dNPP2Hv3r22n+fm5iI7Oxu7d+/GwIEDXZKJZVkUFhYiKioKEonvN8QaDAakp6cjPz+fejxCFLoHCIDuA4LuAYLuAYLH3/cBx3GoqalBSkoKpNL2uyj8mrGIj49HfHx8h+fV19cDQJsPI5VKwbIsAGDo0KF44YUXUFpaioSEBADAunXrEB0djV69erksk1QqRVpamsvne4vo6GhSIiEO3QMEQPcBQfcAQfcAwePP+6CjTIWVgGjeHjp0KHQ6HaZNm4Z9+/bh+PHjePTRR5Gbm4sJEyYAAMaOHYtevXrhtttuw759+/D777/j//7v/zB79mwolUo/fwKCIAiCIAiCCG4CwrGIi4vDb7/9htraWlx++eUYPHgwNm/ejB9//BH9+/cHAMhkMvzyyy+QyWQYOnQobr31Vtx+++1YuHChn6UnCIIgCIIgiOAnIKZCAcDgwYPx+++/t3tORkYG1qxZ4yOJvINSqcSCBQsoyxLC0D1AAHQfEHQPEHQPEDyBdB8ExII8giAIgiAIgiA6NwFRCkUQBEEQBEEQROeGHAuCIAiCIAiCIDyGHAuCIAiCIAiCIDyGHItOxOLFi5GZmQmVSoUhQ4bgn3/+8bdIhJdYtGgRLrjgAkRFRSEhIQGTJ0/GsWPH7M5pbGzE7NmzERsbi8jISEyZMgUlJSV+kpjwBS+99BIkEgkefPBB2zG6D4KfgoIC3HrrrYiNjYVarUbfvn3x77//2n7OcRzmz5+P5ORkqNVqjB49GidOnPCjxITYMAyDp59+GllZWVCr1cjJycFzzz2Hlm2wdB8EF3///TcmTZqElJQUSCQS/PDDD3Y/d+XvXVlZiVtuuQXR0dHQarWYOXMmamtrffgp2kKORSfh66+/xrx587BgwQLs3r0b/fv3x7hx41BaWupv0QgvsHHjRsyePRvbt2/HunXrYDabMXbsWNTV1dnOeeihh/Dzzz9j5cqV2LhxIwoLC3Httdf6UWrCm+zcuRMffPAB+vXrZ3ec7oPgpqqqCsOGDYNcLsevv/6Kw4cP4/XXX4dOp7Od88orr+Cdd97B0qVLsWPHDkRERGDcuHFobGz0o+SEmLz88stYsmQJ3nvvPRw5cgQvv/wyXnnlFbz77ru2c+g+CC7q6urQv39/LF682OHPXfl733LLLTh06BDWrVuHX375BX///TfuvvtuX30Ex3BEp+DCCy/kZs+ebfueYRguJSWFW7RokR+lInxFaWkpB4DbuHEjx3EcV11dzcnlcm7lypW2c44cOcIB4LZt2+YvMQkvUVNTw3Xr1o1bt24dN2LECG7u3Lkcx9F9EAo8/vjj3CWXXOL05yzLcklJSdyrr75qO1ZdXc0plUruq6++8oWIhA+YMGECd8cdd9gdu/baa7lbbrmF4zi6D4IdANz3339v+96Vv/fhw4c5ANzOnTtt5/z666+cRCLhCgoKfCZ7ayhj0QkwmUzYtWsXRo8ebTsmlUoxevRobNu2zY+SEb5Cr9cDAGJiYgAAu3btgtlstrsnevTogS5dutA9EYTMnj0bEyZMsPt7A3QfhAI//fQTBg8ejOuvvx4JCQkYOHAgPvroI9vPc3NzUVxcbHcPaDQaDBkyhO6BIOLiiy/Gn3/+iePHjwMA9u3bh82bN+OKK64AQPdBqOHK33vbtm3QarUYPHiw7ZzRo0dDKpVix44dPpfZSsAsyAtmysvLwTAMEhMT7Y4nJibi6NGjfpKK8BUsy+LBBx/EsGHD0KdPHwBAcXExFAoFtFqt3bmJiYkoLi72g5SEt1ixYgV2796NnTt3tvkZ3QfBz+nTp7FkyRLMmzcP//nPf7Bz50488MADUCgUmDZtmu3v7Oj5QPdA8PDEE0/AYDCgR48ekMlkYBgGL7zwAm655RYAoPsgxHDl711cXIyEhAS7n4eFhSEmJsav9wQ5FgThZ2bPno2DBw9i8+bN/haF8DH5+fmYO3cu1q1bB5VK5W9xCD/AsiwGDx6MF198EQAwcOBAHDx4EEuXLsW0adP8LB3hK7755hv8f3v3HttU+cdx/DNWNi5VtlhonbgxYLABAzqmpjYxBmQBZUETMS7QwZJxc4AjBLwC/yDqP5qIMUYSUONAEgNR8MIfrKKQCIxtbFwyCJc2MTCUZQzZwsL6/P4wnB/9bSL+Dl2xvF/JSdrnOe336TlP0n5yes6pqqrSli1bNHbsWNXX16uyslIZGRnMA/yr8Feou4DL5VJycnK3K700NzfL4/HEaVToDUuWLNGuXbsUDAY1dOhQq93j8aizs1Otra1R6zMnEsvhw4d18eJFFRQUyOFwyOFwaO/evfrggw/kcDjkdruZBwnuwQcf1JgxY6La8vLyFA6HJcnaz3w/JLaVK1fq1Vdf1Ysvvqj8/HwFAgEtX75cb7/9tiTmwb3mdva3x+PpdoGf69evq6WlJa5zgmBxF0hJSdGkSZO0Z88eqy0SiWjPnj3y+XxxHBlixRijJUuWaMeOHaqurlZ2dnZU/6RJk9S3b9+oOdHU1KRwOMycSCBTpkxRY2Oj6uvrraWwsFCzZ8+2HjMPEpvf7+92qemTJ08qKytLkpSdnS2PxxM1B9ra2nTgwAHmQAJpb29Xnz7RP8mSk5MViUQkMQ/uNbezv30+n1pbW3X48GFrnerqakUiET322GO9PmZL3E4bR5Qvv/zSpKammk8//dQcP37cLFiwwKSlpZkLFy7Ee2iIgcWLF5tBgwaZH3/80Zw/f95a2tvbrXUWLVpkMjMzTXV1tampqTE+n8/4fL44jhq94earQhnDPEh0Bw8eNA6Hw7z11lvm1KlTpqqqygwYMMB88cUX1jrvvPOOSUtLM19//bVpaGgwM2fONNnZ2aajoyOOI8edNHfuXPPQQw+ZXbt2mbNnz5rt27cbl8tlVq1aZa3DPEgsV65cMXV1daaurs5IMu+9956pq6szoVDIGHN7+3vatGnG6/WaAwcOmH379pmcnBxTUlISr49kjDGGYHEX2bBhg8nMzDQpKSnm0UcfNb/88ku8h4QYkdTjsnnzZmudjo4O89JLL5n09HQzYMAA89xzz5nz58/Hb9DoFf8bLJgHiW/nzp1m3LhxJjU11eTm5ppPPvkkqj8SiZjVq1cbt9ttUlNTzZQpU0xTU1OcRotYaGtrMy+//LLJzMw0/fr1M8OHDzdvvPGGuXbtmrUO8yCxBIPBHn8HzJ071xhze/v70qVLpqSkxDidTnP//febsrIyc+XKlTh8mv9KMuam2zoCAAAAwP+BcywAAAAA2EawAAAAAGAbwQIAAACAbQQLAAAAALYRLAAAAADYRrAAAAAAYBvBAgAAAIBtBAsAAAAAthEsAAAAANhGsAAA/CPz5s3Ts88+G7f6gUBA69evj9n7Hz9+XEOHDtXVq1djVgMAElGSMcbEexAAgLtDUlLSLfvXrl2r5cuXyxijtLS03hnUTY4cOaLJkycrFArJ6XTGrM7zzz+vCRMmaPXq1TGrAQCJhmABALBcuHDBerxt2zatWbNGTU1NVpvT6YzpD/q/U15eLofDoY8//jimdb799lvNnz9f4XBYDocjprUAIFHwVygAgMXj8VjLoEGDlJSUFNXmdDq7/RXqySef1NKlS1VZWan09HS53W5t3LhRV69eVVlZme677z6NHDlS33//fVSto0ePavr06XI6nXK73QoEAvr999//cmxdXV366quvVFxcHNU+bNgwrVu3TqWlpXI6ncrKytI333yj3377TTNnzpTT6dT48eNVU1NjvSYUCqm4uFjp6ekaOHCgxo4dq++++87qnzp1qlpaWrR3716bWxQA7h0ECwCAbZ999plcLpcOHjyopUuXavHixZo1a5Yef/xx1dbWqqioSIFAQO3t7ZKk1tZWTZ48WV6vVzU1Nfrhhx/U3NysF1544S9rNDQ06PLlyyosLOzW9/7778vv96uurk7PPPOMAoGASktLNWfOHNXW1mrEiBEqLS3VjYP0FRUVunbtmn766Sc1Njbq3XffjToSk5KSookTJ+rnn3++w1sKABIXwQIAYNuECRP05ptvKicnR6+99pr69esnl8ul+fPnKycnR2vWrNGlS5fU0NAgSfrwww/l9Xq1fv165ebmyuv1atOmTQoGgzp58mSPNUKhkJKTkzVkyJBufU8//bQWLlxo1Wpra9MjjzyiWbNmadSoUXrllVd04sQJNTc3S5LC4bD8fr/y8/M1fPhwzZgxQ0888UTUe2ZkZCgUCt3hLQUAiYtgAQCwbfz48dbj5ORkPfDAA8rPz7fa3G63JOnixYuS/jwJOxgMWudsOJ1O5ebmSpJOnz7dY42Ojg6lpqb2eIL5zfVv1LpV/WXLlmndunXy+/1au3atFXhu1r9/f+sICwDg7xEsAAC29e3bN+p5UlJSVNuNMBCJRCRJf/zxh4qLi1VfXx+1nDp1qtuRgxtcLpfa29vV2dl5y/o3at2qfnl5uc6cOaNAIKDGxkYVFhZqw4YNUe/Z0tKiwYMH394GAAAQLAAAva+goEDHjh3TsGHDNHLkyKhl4MCBPb5m4sSJkv68z8Sd8PDDD2vRokXavn27VqxYoY0bN0b1Hz16VF6v947UAoB7AcECANDrKioq1NLSopKSEh06dEinT5/W7t27VVZWpq6urh5fM3jwYBUUFGjfvn2261dWVmr37t06e/asamtrFQwGlZeXZ/WfO3dOv/76q5566inbtQDgXkGwAAD0uoyMDO3fv19dXV0qKipSfn6+KisrlZaWpj59/vqrqby8XFVVVbbrd3V1qaKiQnl5eZo2bZpGjRqljz76yOrfunWrioqKlJWVZbsWANwruEEeAOBfo6OjQ6NHj9a2bdvk8/liUqOzs1M5OTnasmWL/H5/TGoAQCLiiAUA4F+jf//++vzzz295Iz27wuGwXn/9dUIFAPxDHLEAAAAAYBtHLAAAAADYRrAAAAAAYBvBAgAAAIBtBAsAAAAAthEsAAAAANhGsAAAAABgG8ECAAAAgG0ECwAAAAC2ESwAAAAA2PYftvYwj6GColsAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 800x300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(8, 3))\n",
    "plt.plot(times / u.ms, u.math.squeeze(vs) / u.mV, linewidth=1.2)\n",
    "plt.xlabel('Time (ms)')\n",
    "plt.ylabel('Membrane potential (mV)')\n",
    "plt.title('HH neuron under 5 uA/cm^2 constant current')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.13.11"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
