{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "intro",
   "metadata": {},
   "source": [
    "# ``Dynamics`` Protocol\n",
    "\n",
    "This tutorial systematically introduces the **Dynamics** programming protocol in BrainState, which defines the standard interface for implementing temporal evolution of neural systems.\n",
    "\n",
    "## Learning Objectives\n",
    "\n",
    "You will learn:\n",
    "\n",
    "- 🧠 **What is Dynamics** - The design philosophy and element-wise computation principle\n",
    "- ⚙️ **Basic structure** - How to implement the `update()` function\n",
    "- 🔄 **Before/After updates** - Flexible control flow mechanisms\n",
    "- 📐 **Size inference** - Input/output dimension management\n",
    "- ⏱️ **Delay support** - Temporal dynamics with delay mechanisms\n",
    "- 🌍 **Ecosystem integration** - Usage across brainpy.state, brainmass, and braincell\n",
    "\n",
    "## Why Dynamics Protocol?\n",
    "\n",
    "The Dynamics protocol provides:\n",
    "- 🎯 **Unified interface** - Consistent API across the ecosystem\n",
    "- 🧩 **Composability** - Easy integration with other modules\n",
    "- 🔬 **Biological fidelity** - Element-wise dynamics matching neural behavior\n",
    "- 🚀 **Performance** - Efficient JAX compilation and state management"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "2fb1495702e12179",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:48:58.344008Z",
     "start_time": "2025-10-11T09:48:56.707657Z"
    }
   },
   "outputs": [],
   "source": [
    "import brainunit as u\n",
    "import jax.numpy as jnp\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import brainstate\n",
    "\n",
    "# Set simulation time step\n",
    "brainstate.environ.set(dt=0.1 * u.ms)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e6a846f6127af4c",
   "metadata": {},
   "source": [
    "## Part 1: What is Dynamics?\n",
    "\n",
    "### Core Concept\n",
    "\n",
    "`Dynamics` is a module that defines how **state variables evolve over time** in neural or other dynamical systems. All Dynamics models follow the **element-wise computation principle**: state updates only affect local variables and do not include cross-unit interactions.\n",
    "\n",
    "### Element-Wise Principle\n",
    "\n",
    "Consider the **Leaky Integrate-and-Fire (LIF)** neuron model:\n",
    "\n",
    "$$\n",
    "\\tau \\frac{dV}{dt} = -(V - V_{rest}) + R I\n",
    "$$\n",
    "\n",
    "Each neuron's voltage $V$ evolves **independently** based only on its own state and input current $I$. This is element-wise dynamics.\n",
    "\n",
    "### What Dynamics is NOT\n",
    "\n",
    "Dynamics does **NOT** include:\n",
    "- Synaptic connections between neurons\n",
    "- Network connectivity\n",
    "- Inter-neuron interactions\n",
    "\n",
    "These are handled by separate modules like `Linear`, `Sparse`, or `Convolution` connection operators.\n",
    "\n",
    "### Architecture Overview\n",
    "\n",
    "```\n",
    "Input (External Drive)\n",
    "    ↓\n",
    "[Connection Modules]  ← (Linear, Conv, Sparse)\n",
    "    ↓\n",
    "[Dynamics Modules]    ← (LIF, HH, Izhikevich)\n",
    "    ↓\n",
    "Output (Spikes/Voltages)\n",
    "```\n",
    "\n",
    "See [BrainScale documentation](https://brainscale.readthedocs.io) for visual reference.\n",
    "\n",
    "![](https://brainscale.readthedocs.io/_images/model-dynamics-supported.png)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce89f37e1374b0a4",
   "metadata": {},
   "source": [
    "### Example: Simple Exponential Decay\n",
    "\n",
    "Let's implement a simple dynamics model that demonstrates the element-wise principle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "dbf2b2094c7a8b5f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:48:58.532641Z",
     "start_time": "2025-10-11T09:48:58.348559Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Dynamics module: ExponentialDecay(\n",
      "  in_size=(5,),\n",
      "  out_size=(5,),\n",
      "  v=State(\n",
      "    value=ShapedArray(float32[5])\n",
      "  ),\n",
      "  tau=5. * msecond\n",
      ")\n",
      "Input size:  (5,)\n",
      "Output size: (5,)\n",
      "Variable shape (varshape): (5,)\n",
      "\n",
      "Initial state: [0. 0. 0. 0. 0.]\n",
      "\n",
      "After one step with input [ 1.   0.5  0.  -0.5 -1. ]:\n",
      "Output: [ 1.   0.5  0.  -0.5 -1. ]\n"
     ]
    }
   ],
   "source": [
    "class ExponentialDecay(brainstate.nn.Dynamics):\n",
    "    \"\"\"Simple exponential decay dynamics: τ dv/dt = -v\"\"\"\n",
    "\n",
    "    def __init__(self, size, tau=10.0 * u.ms):\n",
    "        super().__init__(in_size=size)\n",
    "\n",
    "        # State variable\n",
    "        self.v = brainstate.State(jnp.zeros(size))\n",
    "\n",
    "        # Parameter (constant, not a State)\n",
    "        self.tau = tau\n",
    "\n",
    "    def update(self, inp):\n",
    "        \"\"\"Element-wise update: each element evolves independently\"\"\"\n",
    "        # Exponential Euler integration\n",
    "        dt = brainstate.environ.get_dt()\n",
    "        alpha = jnp.exp(-dt / self.tau)\n",
    "\n",
    "        # Update state (element-wise operation)\n",
    "        self.v.value = self.v.value * alpha + inp\n",
    "\n",
    "        # Return current state\n",
    "        return self.v.value\n",
    "\n",
    "\n",
    "# Create dynamics module with 5 independent elements\n",
    "dynamics = ExponentialDecay(size=(5,), tau=5.0 * u.ms)\n",
    "\n",
    "print(f\"Dynamics module: {dynamics}\")\n",
    "print(f\"Input size:  {dynamics.in_size}\")\n",
    "print(f\"Output size: {dynamics.out_size}\")\n",
    "print(f\"Variable shape (varshape): {dynamics.varshape}\")\n",
    "print(f\"\\nInitial state: {dynamics.v.value}\")\n",
    "\n",
    "# Apply input to all 5 elements\n",
    "inp = jnp.array([1.0, 0.5, 0.0, -0.5, -1.0])\n",
    "output = dynamics(inp)\n",
    "print(f\"\\nAfter one step with input {inp}:\")\n",
    "print(f\"Output: {output}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50688b07f04b9e4e",
   "metadata": {},
   "source": [
    "### Visualizing Element-Wise Dynamics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "dc73792114f18aa2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:48:58.861687Z",
     "start_time": "2025-10-11T09:48:58.539647Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAA+kAAAIjCAYAAAB/OVoZAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjYsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvq6yFwwAAAAlwSFlzAAAPYQAAD2EBqD+naQABAABJREFUeJzs3QV4U9f7B/BvmzZ1AYoXKO7u7g7DZdhwGT6F/Sc/GHPGGMOGbwx3h6HD3d0pXrSllGryf96TpmtLYU0t0u/neS5t0pubc5ObS977nvMeO71erwcRERERERERmZ29uRtARERERERERAYM0omIiIiIiIgsBIN0IiIiIiIiIgvBIJ2IiIiIiIjIQjBIJyIiIiIiIrIQDNKJiIiIiIiILASDdCIiIiIiIiILwSCdiIiIiIiIyEIwSCciIiIiIiKyEAzSiYgsiJ2dHf73v/+ZuxlWadeuXer1k59k+erUqaOWpODnJP3ie09E6QGDdCKiVDZv3jz1xfJNy8GDB2GL7t27p75Mnzx58j/XXbp0qXotVq1a9drfSpcurf62c+fO1/6WO3duVKtWDeaSXt/bxDp//rw6Bm7evJnmzy3PGfu9cHR0hI+PjzpePvvsM/j7+8MW9OzZM85+uru7I1++fGjfvj1WrFgBnU5n7iYSEZGJHEx9ABERJc3YsWORN2/e1+4vUKAAbDVIHzNmDPz8/FCmTJm3rlujRg31c+/evWjTpk3M/UFBQTh79iwcHBywb98+1K1bN+Zvt2/fVkvnzp3V7Vq1auHVq1fQarVIa+ntvTUlSJdjQDLmchzE9vfff6dJG9599100a9ZMBavPnj3DkSNHMHHiRPz666+YPXt2zPFjzZycnDBr1iz1u3wGbt26hXXr1qlAXV77NWvWwNPTE7ZA9k/OB0REtoxnOSKiNNK0aVNUqFDB3M2wSDly5FBBrgTpsR04cAB6vR4dOnR47W/G28YA397eHs7OzjAHvremS6uLKeXKlUO3bt3i3CdBbKNGjfDee++haNGiqreGNZOgNf4+jhs3Dt9//z1Gjx6Nfv36YcmSJbAF5vqMExGlJXZ3JyKycHfv3kXv3r2RNWtWlTErXrw45syZk+B4bOk2LpnLnDlzwsPDQ2XSAgMDERYWhhEjRiBLliyqO2yvXr3UffH99ddfKF++PFxcXJAxY0aVZZRsdWySmStRooTKkkpm29XVVT3fjz/+GKc9FStWVL/Lcxm74kr38DeRYPvEiRMqU2Yk2XPZXwmCpet47K678jfZZvXq1d84Jv3KlSto164dsmXLpr7c+/r6qn2S18TU/U6Or776Sl1E2L59e5z7+/fvr4LVU6dOxdkHCaikS7a0283NDe+8806C7Vm2bFlMu6UrtwRqcrzE7w4t77nc37p1a/V75syZ8dFHHyEqKirOuvL6SpZZXnN5veSYGzBggMpAxyZZ8RYtWqgLJZUqVVLrShfrP//8M2Ydea/l4oqQ48R4DBjfn/hj0sPDw/Hll1+q/fHy8lL7XbNmzQSHOSRXnjx5VPvkOWMft+L58+fqs5IrVy71eZPeED/88MNr3cbltmTjS5YsqfZfXtMmTZrg6NGjMevMnTsX9erVU5872VaxYsUwbdq0ONuRCwXy3kVERLzWTrmQULhw4STv56hRo9Q25Di5fPmyyc8n79eQIUOwevVq9Zk3nn82b9782kWP999/Xz1WjsVMmTKp9z7+MAfj8BA5boYNG6ZeM29vb3WMyXshr32PHj2QIUMGtXzyySfqIt1/jUmXY7tPnz7qYp+0US74DRo0SG1TyL7KebFgwYLqvZL2yflm69atSX5tiYhSEzPpRERpRALDx48fv/aFU74wvsnDhw9RpUqVmC/L8qV206ZN6gupdAWXYCK27777Tn1Jli/nV69exW+//abG4kqAKIGWfLmVYFe+LMsXWQmKjL755ht88cUX6NixI/r27YtHjx6px0s3cgme5cu0kWxLApK2bduq9ZcvX45PP/1UBSwSUEt2UrqAy/YlEJVgS7xt/Lh8aZ4/fz4OHToUE7xJIC6PkUVeP+n6XqpUqZi/FSlS5I2vn3xBb9y4sboYMXToUBXwypf59evXq2BAAkFT9zup7+3nn3+uuh/L+3bmzBl1AWXLli2YOXMmvv7669cyudImeby8pgEBASpwbtCggRrfL++vkPdQLoDIxRB53+VYkaBRXpf47ZZgXF6LypUrY/z48di2bRt+/vln5M+fXwUzRhIsGbcrQdSNGzcwefJktT3ZrhxLRnJ8yUUg2ScJ/OTCkVwQkCBbAjl5/WQbkyZNUhcc5JgQxp/xyfEsXbale7pkfl+8eKG6o0u7Dx8+/J9DJkxVtWpVtf+xA7WQkBDUrl1bHSfyWkjNg/3796ts9P3799X7YCT7La+VHO9y3ERGRmLPnj3q82XsVSEBubwWcpFFst1yDEgwKwH+4MGD1Trdu3dXFzfkeJALH0YPHjzAjh071AWe5JDty9AC2c9ChQqZ/HwSUK9cuVK1W45beT/lwpeM6Tce3zKEQF4nubglF8IkOJd9l8+xXMyTC3mxGT+PEjjL6zVjxgx1vMo25DX/9ttvsXHjRvz000/q4oAE7m8bViMXiuQzLecaOSfI+yfnJHk/5SKYnPfkMyLvk6wrx5pcTDl+/DgaNmyYrNeXiChV6ImIKFXNnTtXUkEJLk5OTnHWlfu++uqrmNt9+vTRZ8+eXf/48eM463Xu3Fnv5eWlDwkJUbd37typHluiRAl9eHh4zHrvvvuu3s7OTt+0adM4j69atao+T548Mbdv3ryp12g0+m+++SbOemfOnNE7ODjEub927drquf7888+Y+8LCwvTZsmXTt2vXLua+I0eOqPVk/xPj3Llzav2vv/5a3Y6IiNC7ubnp//jjD3U7a9as+ilTpqjfg4KCVHv79esX83jjayA/xYkTJ9TtZcuWvfE5Tdnv5L63sk2tVqvv27ev/tmzZ/qcOXPqK1SooPYz/j7I32QfjZYuXaru//XXX9VteY+zZMmi3u9Xr17FrLd+/Xq13pdffhlz33vvvafuGzt2bJz2lC1bVl++fPmY23v27FHrLViwIM56mzdvfu1+OXbkvt27d8fcFxAQoPb5ww8/jLlPXvvY70lschzJYhQZGamOo9jkdZL3vXfv3m/9nCTkxo0bar2ffvrpjeu0atVKrRMYGKhuy7Enx9zly5fjrDdq1Ch1nPj7+6vbO3bsUI8bNmzYa9vU6XQxvxs/n7E1btxYny9fvpjbUVFRel9fX32nTp3irDdhwgT12b1+/fpb91PeX2nzmxg/ByNHjjT5+eRxcsxevXo15r5Tp06p+3/77be37ueBAwdeO08YPy/yGsR+neR8JM89cODAOMeDtDP2MZLQe9+jRw+9vb29Ot/EZ3yO0qVL65s3b/7G14iIyNKwuzsRURqZMmWKymbFXiQr/ibyfVSqM7ds2VL9Lpla4yLZRcneSiYoNsk4xc52SuZUHivd5WOT+6X7tGT/hGTKJLsn2eTYzyPZLukiGr/LsXSZjj0GVrJVkqG6fv16kl8fybBKZs441ly6gL98+TIm+y4/JZtrHKsu2WHjePSEGDPlkjGUjFpCTN3v5Ly3khGUzKFki+X9k+f5448/EiyCJe+jZC2NJGOdPXt2lV0UkgWUDLtkN2OP0W3evLnKJG7YsOG1bQ4cODDObendEPv9ki7R8ppJZjH2ayGZcXm/478W0nXb2ENCSC8P6e6c1GNAo9HEjFOX9+Tp06fq+JSsdPzjPKXIfgnJ2htfA9kn6Wod+zWQXgxyvO3evVutJ59L6emQUJZb7jcy9nqI3dtCMvXyGhmHXEgvl65du2Lt2rUx7RALFixQx3xCBQmTs4+mPp/su/Q4MJKeLFKELvb7HHs/pWv5kydP1DAByY4n9N5JL4TYr5PxPCX3xz4e5L1/2/Ekx4l0xZdzZEI1IYzPIe04d+6cGv5CRGQN2N2diCiNSBBrSnEx6XYtXTilK6gsCZFALTbpKppQoCrja+PfL19wJVCQwFi+vMqXZAlMExI78BfSpTX2l2whgc3p06f/c7+Cg4PVEvvLuAR4sj0JEiQQkrZJQC5jeY0V0uVv0vVaGIP1twXpEmx88MEHmDBhggpAJPiSbsdyccH4upi638l9bz/++GMsXrxYdd+WLr0S6CYkfnvktZHXwTjGV8YAi4TGK0uQHr/InnHMdPz3K/ZYc3kt5HiQ1zwpx1pC2zSVXLSQbvgXL16MM2Y6uYHqmxiPQ+MFEXkN5BiO/1rFfw2uXbumxj9L/YK3keNUAnm5qBT/QpG81sbjUC7KyLh3mYJQfr906RKOHTuG6dOnp/g+mvp8iXmfpY6EdCeXMfjS1Tz2OPL49R9MPU+97XiSc6R0XZcLYG8jQ29atWqluvvLujJUR7r9G4fOEBFZGgbpREQWylioSoJKGfObkPhfMiXgTcib7jd+mZbnkkBQsr8JrWvMxiV2e28jY6Iloxy7iJcx+JSgW8btyrht43h0I/ldglwJAiQIlSBJipW9jQR8Mk5apqCScbkyRlqCCRkHKxcaTN3v5JKsoDGbJ/uYVt70fsUmr4UE6HJBIyHxA9fkHAMJkeJ98l5JcTt5n6Ut8hzyfklQnBqkxoE8j3F6MnkNpCeBFCxLiAR5iSVtrl+/vrpoIheKJACVngLSG+KXX36JU4hOLtZIjwV5DSRolp+yrvTwSIl9jD8doCnPl5j3WcaYS4AuNTJkrL8E1/K5kjHqCc3Tbsp5KqnHU2xSH0HeD+N5QHqzyHsgFyVknDoRkaVhkE5EZKEkKJLsl3SzlS6nqUm6s8qXYclYmhKIvE38TLuRBAWxM+Cxu8rGni9dgvTYhfEkqJDKzVIdXIrLydzXiSHF7GSR4m1SmEqqwcuXc5miKjX2+00kWJEgVAJC2S/JpEs3dim+F1/8brnSRinUZrwoIxc2hGRApXp4bHKf8e+mkNdCCsrJ6xP7PUmNYyAhUuhLLrrIEITYj0tu4bQ3key2BG6xh23IayCZ5//6vMl6MoxCuuS/KZsuF5ukaKF0K4+dOX7TEAr5XEjPDylQt3DhQjV0QTLWySXFGOX1jF8gLSWfT947uZAoF8WMQkNDVU+g1D5HyufJeCHibeR9koKIssh7LIG7FJRjkE5Elohj0omILJRklaSKsox/TehLqHT1TCkSKMrzSYY7fuZKbssYU1PJFFoi/hd1CcQkCDIuxinUhHQZl67Zks2VjHnsTLoE6DLntYz/lrHqb+vqLqQbrHHMvZEE6zIm1zj9XGrs95tINlUuEsjQBanoLvsmldXjV4UXUn079nhhCYIkmJJK4sbXSTLAcrEh9lR60iPgwoULKuAylWRR5YKQtC0+eR2TEnC96Rh4WxY19vsgF2MkmE5pMlxALphI9liy9rFfA3k+CcDjk30wHk/yuZR2xu4RYmRsf0L7I12/JeOcEKlqL8H08OHDVY+L+POeJ4XMky6Z406dOr02hCIln0/2Nf7nR2ZIiD/FX0qTz7L0vJALIrGnvjMytin+51h6yEjPgoSmoSQisgTMpBMRpREJoGSsbXwSrL2p27Z8yZbMmxRWkmmppJuqZO+kGJNkPeX3lCCZQcksy1RT0vVcvvhKFl+m4JJxqzK1kcyrbeo2pWCTBJKyLQnYZD/eNr5YgiaZUkymspKgXLLn8V8rY7buv4J0mU5Kpq2T+ZolSy4BlmQVjRc/UnK//+u9lcBZpnmTwFCKXAmZvkumFZPibzK/ffysn+yfZP1kajWZ+kuCCjkGjGPlZUyx/F0KkUnAZZyCTeYwHzlyJEwl25Fpx6R7uUz1JnNmy/NIVl8Kqsm2JfNvCtk/eb2lrRKgyntqnDc8PpkOTLLobdq0URcZ5D2QY0eO+dg1DEwlnxXpzi09GSTQlunCjIXf5HiIPWREAnbJfEtbjNPJyQUhGZogF0rkGJE5xmXedxnTLNORyesjY5xl+3Lcyt/kuJPXT45neb/ldZV9kCn3ZN/lgkt8xnnW5bWWz40pF1rk2JZ9NGaw5SKE7IeMr5f2JFTTIjnPF5+8XvJaSjd3eb/kQoecn942vWRKkR4pciFCjl/5vEoBSnl9Zb+kR47sm7RJpoOT91M+WxLQy/sp7xMRkUUyd3l5IiJb97ZpuuJPUZbQ1FIPHz7UDx48WJ8rVy69o6Ojmuqsfv36+hkzZrw2dVf86caMzx1/eiJ5Drn/0aNHce5fsWKFvkaNGmpKJ1mKFCminvvSpUsx68iUSMWLF09wKqjY07qJNWvW6IsVK6amM0vsdGyjR49W61arVu21v61cuVL9zcPDQ03RFFv8KdhkKimZuit//vx6Z2dnfcaMGfV169bVb9u27bXtJma/k/reSjsrVqyoppN6/vx5nMfLlGqy3pIlS+Lsw6JFi9TrINOsubi4qOmjbt269drzy+NkKjWZ+kz2r2vXrvo7d+4kaoou4zEQnxxXMjWbPK+8ziVLltR/8skn+nv37sWsI+9zQlNaxZ9WTcycOVNNOSZTmMV+f+KvK9Nlffvtt2rbsj+yXzKlXELHlSlTsBkXOQblNapcubJ6bRN6PcWLFy/U3wsUKKCmH/Px8VHH4vjx4+NMbyjvq0zvJseKrJc5c2Y11eGxY8di1lm7dq2+VKlS6vjz8/PT//DDD/o5c+ao9kj74jNOtde/f399Yhmn2DMurq6u6rlkOsTly5erKdfe5L+eT/4mn4P45P2Q5409VV6vXr3Ua+Xu7q6mWLt48eJr65l6Pkro2E3ovZf3UqZik/dAjh053qTdxin9xo0bp69UqZLe29tbHdfynsn0irHfTyIiS2In/5j7QgERERFBjbeXzKdkAU3NWpP1k8Jm0ptDZjiIPb2drTwfERElDsekExEREVkA6Q4vwyP+ayiHtT4fERElDsekExEREZnR4sWL1fjxDRs2qLH/plTFt4bnIyIi0zBIJyIiIjIjKfwnFcf79OmjCgna2vMREZFpOCadiIiIiIiIyEJwTDoRERERERGRhWCQTkRERERERGQh0t2YdJ1Oh3v37sHDw4OFUoiIiIiIiCjVySjzFy9eIEeOHLC3f3uuPN0F6RKg58qVy9zNICIiIiIionTm9u3b8PX1fes66S5Ilwy68cXx9PSEpWf9Hz16hMyZM//n1RYis4iKgu74cTx//hzederA3tHR3C0ieiOeU8la8Fgla8FjlayFzgKO1aCgIJUsNsajb5PugnRjF3cJ0K0hSA8NDVXt5ImPLFJ4OPS7d8Ph5Uu4Nm8Oe2dnc7eI6I14TiVrwWOVrAWPVbIWOgs6VhMz5JqfJiIiIiIiIiILwSCdiIiIiIiIyEIwSCciIiIiIiKyEOluTDoREREREVFiRUVFISIiwtzNoGSOSZf3UMalp+aYdEdHR2g0mmRvh0E6ERERERFRAoKDg3Hnzh01xzVZL71erwJ1mac8MYXbkkq2LdOrubu7J2s7DNKJiIiIiIgSyKBLgO7q6qqm7krN4I5SP0iPjIyEg4NDqr2P8hwyzZscMwULFkxWRp1BOhElnYMD9O++i1dPnsDVgacTIiIish3SPVoCLwnQXVxczN0csvAgXcixcvPmTXXsMEgnIvOQMT2FCiEqIMDwOxEREZGNYQad0vpY4bdqIiIiIiIiIgvBIJ2Iki4qCjh5Eg5nzxp+JyIiIiKiZGGQTkRJFxUFuzVr4Lx5M4N0IiIiIivqlr169WpzN4PegEE6ERERERGRjejZs6cKwuMvTZo0gTXy8/PDxIkT/3M9mQN98ODByJQpk5oCrV27dnj48CGsEYN0IiIiIiIiGyIB+f379+MsixYtgi0bOXIk1q1bh2XLluGff/7BvXv30LZtW1gjBulERERERESJmMYrJDzSLIs8tymcnJyQLVu2OEuGDBneuP7t27fRsWNHeHt7I2PGjGjVqpWaSix2dr5169b49ttvkTVrVrXe2LFj1bRmH3/8sXqMr68v5s6dm6Ttjh8/HtmzZ1dZ8MGDB6spzESdOnVw69YtFYAbewQkJDAwELNnz8aECRNQr149lC9fXrVl//79OHjwIKyNWadg2717N3766SccO3ZMXd1ZtWqVepPeZteuXfjggw9w7tw55MqVC59//rl6c4mIiIiIiFLLq4goFPtyi1me+/zYxnDVpk7oJgFx48aNUbVqVezZs0fNJT5u3DiVjT99+jS0Wq1ab8eOHSoQlxhu37596NOnjwqCa9WqhUOHDmHJkiUYMGAAGjZsqNZL7HZ37typAnT5efXqVXTq1AllypRBv379sHLlSpQuXRr9+/dXt99E4kl5vgYNGsTcV6RIEeTOnRsHDhxA5cqVYU3Mmkl/+fKletGnTJmSqPVv3LiB5s2bo27dujh58iRGjBiBvn37YssW83xYiIiIiIiILM369evVuOzYi2TBEyLBtU6nw6xZs1CyZEkULVpUZaH9/f1VgtRIMuGTJk1C4cKF0bt3b/UzJCQEn332GQoWLIjRo0erwHvv3r0mbVcy/JMnT1ZBdYsWLVS8t3379pjn1Gg08PDwiOkRkJAHDx6o55aMfWyS9Ze/WRuzZtKbNm2qlsSaPn068ubNi59//lndljdaDoJffvlFXaUhorQXEaVDQHA48pjYDYuIiIjImrg4alRG21zPbQpJak6bNi3OfRLwJuTUqVMqgy2BcPxCbNeuXYu5Xbx4cdjb28cJgEuUKBFzW4Jp6a4eEBBg8nblsUbZs2fHmTNnkJ6ZNUg3lXRViN2FQUhwLhn1NwkLC1OLUVBQkPopV3VksWTSPhl/YuntpHTM3h5Tfcpiw/0HKLf2Ar5pVxr29gmPFSIyN55TyVrwWCVrYevHqnH/jEtSguWUZMq4dDc3N+TPn/+t2zDu14sXL9QY7r/++uu19TNnzhzzGEdHxziPl/Hh0oU9/n1RUVHJ2m7s194o9nuQELlgEB4ejmfPnsXJpkt1d/mbcRuxf6YGYzsTijVN+ZxYVZAuXRWML7KR3JbA+9WrV3BxcXntMd999x3GjBnz2v2PHj1SV3EsmbyRUgRB3ujYV62ILMkhp8y4ktkJV07cx4vQMPxfQz9oGKiTBeI5lawFj1WyFrZ+rMoYZ9lHKY4mi7UwBoj/1WYJpmUdGf+9dOlSlWn39PR8bT1ZJ6FtGgPS+M9jXC+ltuvo6Kjei7ftjwyhlvX+/vvvmIruly5dUl3rK1WqpB4v+yveVHwuJRj36cmTJ6o9sclFC5sM0pNCxkZIoTkjCeil4JxcvUnoYLEk8gbLQSRttcUTH9kGe4d/K3RuvPAU9o5O+LlDKThqeMySZeE5lawFj1WyFrZ+rEpCTwIryRbLYi3kvZCg9PHjx3Hul33w8fGJuS1dzOW+7t27q6ro7du3V8lNKfomFdWlaNsnn3yibss2ZYn9Ohirrcd/bYzrpdR28+bNqwrVdenSRVWtj70PRtLNXsbJy3aNcd6wYcNU0brq1avHrBc/cE5p0mbZH2mPs7NznL/Fv/3W7cCKSKGA+BPSy215ExLKogt5I2WJz3hAWDo5QK2lrZQO6XTIducaCj4KRPH6lbHh3EOsP30fkVF6THq3LLQOPG7JsvCcStaCxypZC1s+VmWfjAFjamZfU8PmzZuRI0eOOPdJobeLFy/G3Dbul3SNl4rtn376Kdq1a6cuTOTMmRP169eHl5dXnH2P/zok9Nokd7t20b8bf8pUb1I1vkCBAmoY85u6q0+cOFFdeJCLArKeDIueOnWq2o48Jv52U4Nx3xP6TJjyGbHTp2anfBPIzvzXFGzyBm/cuDFOIQG5ovL06VN1ICaGZNLloJCuOdaQSZfCC1myZLHJEx/ZgPBwLGkzEPcDQ1Fk0rdwdHHBoL+OIzxKhwZFs2BK13JwcjDf2C2i2HhOJWvBY5Wsha0fq5JJl9mlJJNrShaULI8+uvu8ZLpTM0h/2zFjShxq1k9TcHCwmkpNFiE7JL/L2AFjV/UePXrErD9w4EBcv35ddWOQq0ByZUTGOcjk9kRkHlHRNTAc7O1Rv2hWzHyvApwc7LHtQgD6/XkMoRGG8T9ERERERPTfzBqkHz16FGXLllWLkLHj8vuXX36pbt+/fz8mYBdyRWLDhg3YunWrKg4gU7HJvHucfo3IfHTRnXG0GsNVydqFMmNuz4qq+unuy4/Qe94RhIRbT7EVIiIiIiJzMuuY9Dp16ry1BP68efMSfMyJEydSuWVEZGqQLpl0o2oFfPBH70roNfcw9l97gp5zjmBOr4pwd7KqMhhERERERGnO9gaPEFGaitJFB+nRmXSjSnkz4s8+leHh5IDDN5+i++xDCHwVYaZWEhERERFZBwbpRJQs0TF6glOulc+TAQv6VYaXiyNO+D9Hl5kH8fRleNo3koiIiIjISjBIJ6IU6u6ecKXMUr7eWNy/CnzctTh3Lwidfj+AgKDQNG4lEREREZF1YJBOREmn0WBH4Wr4u2BVOGgd37ha0eyeWNy/KrJ5OuNKQDA6/H4Ad56FpGlTiYiIiIisAYN0Iko6jQbnsuTF+az54Kh9e1G4AlncsWxgVeTK6IJbT0LQcfoB3Hj8Ms2aSkRERERkDRikE1GyREQZC8f99+kkV0ZXLB1QFfkyu+FeYCg6TD+ASw9epEEriYiIiIisA4N0Iko6nQ6+j24j79O7cMCbp1OMLbuXiwrUi2TzwOPgMHSecQBn7gSmelOJiIiIyMDOzg6rV682dzPoDRikE1GS6SMi0PzsTrQ6vwuOel2iH+fj7qSKyZXO5Y1nIRGq6vvRm09Tta1ERERE6UHPnj1VEB5/adKkCayRn58fJk6c+J/rzZgxA3Xq1IGnp6fa3+fPn8NaMUgnomTPkS4c482T/l+8XbX4q08lNZ/6i7BIdJ99GHuvPE6FVhIRERGlLxKQ379/P86yaNEi2LKQkBC135999hmsHYN0IkqyyFhBemLGpMfn4eyIP3pVQq1CmfEqIgq95x3B5rMPUriVRERERClApp0Nf2meJXrK28RycnJCtmzZ4iwZMmR44/q3b99Gx44d4e3tjYwZM6JVq1a4efNmnOx869at8e233yJr1qxqvbFjxyIyMhIff/yxeoyvry/mzp2bpO2OHz8e2bNnR6ZMmTB48GBERESov0tm/NatWxg5cmRMj4A3GTFiBEaNGoUqVarA2r29HDMR0VuER/3bxd3xDfOk/xcXrQYze5TH8EUnsfncA7y/4Bh+bF8a7cv7pmBLiYiIiJIpIgT4Nod5nvuze4DWLVU2LQFx48aNUbVqVezZswcODg4YN26cykqfPn0aWq1Wrbdjxw4ViO/evRv79u1Dnz59sH//ftSqVQuHDh3CkiVLMGDAADRs2FCtl9jt7ty5UwXo8vPq1avo1KkTypQpg379+mHlypUoXbo0+vfvr26nF8ykE1GSRUZXdk9qJt3IyUGDyV3KokN5X0hy/qNlpzB3340UaiURERFR+rJ+/Xq4u7vHWSQLnhAJrnU6HWbNmoWSJUuiaNGiKiPu7++PXbt2xawnmfBJkyahcOHC6N27t/opXcyle3nBggUxevRoFXjv3bvXpO1Khn/y5MkoUqQIWrRogebNm2P79u0xz6nRaODh4RHTIyA9YCadiJIsMlYmXZPETHrsIP+HdqVUF/g5+25gzLrzCHoViWH1C7y1axMRERFRmnB0NWS0zfXcJqhbty6mTZsW5z4JeBNy6tQplcGWQDi20NBQXLt2LeZ28eLFYW//b1JGur2XKFEi5rYE09JdPSAgwOTtymONsmfPjjNnziA9Y5BOREkWET0mXZNCQbS9vR2+aFEUXi6O+GXbZbUEhUbg8+ZFGagTERGRecl3kVTqcp7S3NzcUKBAgUStGxwcjPLly2PBggWv/S1z5swxvzs6Osb5m3w3S+g+yZ4nd7u66G2kVwzSiSjJImGHnfkqwNnBHoNjXQFNDjkxD29QEJ4uDiqbPnvvDQS9isB3bUsmq0s9EREREb2uXLlyqmt6lixZ1PRllrZdrVaLqKgopCf8xktESRYBO5zKURgXchWRPk4puu1e1fPi5w6lIb3olx27g6GLTiAsMn2doImIiIiSIiwsDA8ePIizPH6c8FS3Xbt2hY+Pj6q8LgXebty4ocaMDxs2DHfu3ElyG1Jqu35+fqpY3d27d9+4D0L28eTJk6qLvZAu83L76dOnsDYM0okoySKiC8dpTJwjPbHalffF1K7lodXYY9PZB+j7x1G8DItMleciIiIishWbN29WY7tjLzVq1EhwXVdXVxUE586dG23btlUF3qRyu4wdT04GPKW2O3bsWDVtW/78+eN0k49v+vTpKFu2bEwVeKk6L7fXrl0La2On15s46Z6VCwoKgpeXFwIDA1O0O0dqkLEYUnhBuojELtJAZCnO+D/DoO9WIaOrA1b/0AX2DqkzgmbvlcfoP/8oQsKjUCaXN+b2rIgMboZpO4gSi+dUshY8Vsla2PqxKsGkZH/z5s0LZ2dnczeHkkFCXpnTXaaBS806R287ZkyJQ23v00REaSYyPBztz2xDq5NbgcjUy3DXKOiDBX0rw9vVESdvP0eH3w/g3vNXqfZ8RERERETmwiCdiJI9T7p9GlReL5s7A5YPrIrsXs64GhCM9tP2q59ERERERLaEQToRJVlE9DzpyZwiPdEKZPHA8kHVkC+zG+4FhqLD9P0qs05EREREZCsYpBNRCgTpaTeHeU5vFywfWA2lfb3wLCQCXWYexJ4rj9Ls+YmIiIiIUhODdCJKge7uafu8Gd20WNCvCmoU8FHF5HrPO4L1p++lbSOIiIiIiFIBg3QiSrJIfXQmPa2jdADuTg6Y3bMCmpfMrqaCk3nU5x+4mebtICIiIiJKSQzSiSjZ86SbIUZXnBw0mPRuWXStnBsymeQXa87hl62X1TQbRERERETWiEE6ESVZuN4Oe/zK4mzRioBGY5Y2aOztMK51CQyrX1Dd/nX7FXy26iwio8fLExERERFZEwbpRJRkkbDHMd9iuFawlNmCdGFnZ4cPGhbC161LQGrYLTrsj0ELjiM0IspsbSIiIiIiSgoG6USUZBE6Q7baUWMZp5LuVfJgWtdy0DrYY+v5h+g66xCeh4Sbu1lEREREFkUSHKtXrzZ3M+gNLOObNRFZpciIKGR98Rg+gY+B6IDd3JqUyI6/+lSGp7MDjt16hg7TD+De81fmbhYRERFRmujZs6cKwuMvTZo0gTXy8/PDxIkT37rO06dPMXToUBQuXBguLi7InTs3hg0bhsDAQFgjBulElGRR4eF499QW1NmzFoiMhKWolDcjlg2shmyezrgSEIy2U/fj0oMX5m4WERERUZqQgPz+/ftxlkWLFsFW3bt3Ty3jx4/H2bNnMW/ePGzevBl9+vSBNWKQTkQpUN3dTOXd36JwNg+seL8aCmRxx4OgUHSYvh+Hbzw1d7OIiIjISsnsMSERIWZZTJ25xsnJCdmyZYuzZMiQ4Y3r3759Gx07doS3tzcyZsyIVq1a4ebNm3Gy861bt8a3336LrFmzqvXGjh2LyMhIfPzxx+oxvr6+mDt3bpK2K8F19uzZkSlTJgwePBgRERHq73Xq1MGtW7cwcuTImB4BCSlRogRWrFiBli1bIn/+/KhXrx6++eYbrFu3TrXR2jiYuwFEZL2MFdTtLfRyX05vFywfWBV9/jiqur53m30IkzqXRZMS2czdNCIiIrIyryJfofLCymZ57kNdDsHV0TVVti0BcePGjVG1alXs2bMHDg4OGDdunMrGnz59GlqtVq23Y8cOFYjv3r0b+/btU1nq/fv3o1atWjh06BCWLFmCAQMGoGHDhmq9xG53586dKkCXn1evXkWnTp1QpkwZ9OvXDytXrkTp0qXRv39/ddsU0tXd09NTPa+1Tc9roV+ticgaROgsN5Nu5O2qxYK+ldGgaFaER+owaMEx/Hng3yu4RERERLZm/fr1cHd3j7NIFjwhElzrdDrMmjULJUuWRNGiRVVG3N/fH7t27YpZTzLhkyZNUuO+e/furX6GhITgs88+Q8GCBTF69GgVeO/du9ek7UqGf/LkyShSpAhatGiB5s2bY/v27THPqdFo4OHhEdMjIDEeP36Mr7/+WgX31oiZdCJKViZdTiL2lhujK86OGkzvVg5frDmnpmf7cs053H32Cp82KQJ7S288ERERWQQXBxeV0TbXc5uibt26mDZtWpz7JOBNyKlTp1QGWwLh2EJDQ3Ht2rWY28WLF4d9rO6T0u1dupkbSTAt3dUDAgJM3q481ih79uw4c+YMkiooKEgF+sWKFcP//vc/WCMG6USUZJE6fXSQbvmBroPGHt+2KQHfDC74acsl/L77Ou4FhmJ8h1JwcjDfHO9ERERkHWQ8dGp1OU9pbm5uKFCgQKLWDQ4ORvny5bFgwYLX/pY5c+aY3x0dHV97PRK6T7Lnyd2uLomzBr148UJ1p5cLA6tWrXpt29aCQToRJVlEpB7OVpBJj33SH1y3ALJ7OeOT5aex7tQ9BASFYkb3CvBytc6TOBEREVFylCtXTnVNz5IlixrDbWnb1Wq1iIqKSlQGXcbAS9G8tWvXwtlZvqVaJ45JJ6IkCwdwMHdJ3C5ZQfo4wVq0LeeLeb0qwd3JAYduPEX76ftxl3OpExERkY0ICwvDgwcP4iwyTjshXbt2hY+Pj6q8LgXebty4ocaMyzzjd+7cSXIbUmq7fn5+qljd3bt337gPEqA3atQIL1++xOzZs9Vt434nJsC3NAzSiSjJImCPg7lL4W7pilYVpIsaBX2wdEBVZPV0UnOpt5myD+fuBZq7WURERETJJnOEy9ju2EuNGjUSXNfV1VUFwblz50bbtm1VgTep3C5jx5OTAU+p7Y4dO1ZN2yZTq8XuJh/b8ePHVYV5Gcsu3fxj77dMA2dt7PTWVo8+meSqipeXV0xJfksmYzGk8IJ0EYldpIHIUny49BRWHL+DwTVy4sNmpazyOL33/BV6zj2Myw+D4abVYFq38qhVKOH/AMi68ZxK1oLHKlkLWz9WJZiU7G/evHmtuus0QU3BJvOly3Rsb5prPbWPGVPiUNv7NBFRmomIjEKml8/hEfRMzn6wRjm8XbBsYDVUzZcJL8Oj0HveESw9an1XXImIiIjINjBIJ6Ik00eEo/uJDSi7cSkQEQFr5eXiiHm9K6J1mRyqYr0Ulfv570vqqisRERERUVpikE5ESRYRZQhiraW6+9vINGwTOpbBkLqG6Up+23EVI5acRFik9RUbISIiIiLrxSCdiJIsMsowh6XGCuZJTwx7ezt81LgwfmxXCg72dlhz8h66zzqMZy+ljj0RERERUepjkE5ESSZdw4WNxOgxOlbMpaZo83BywOGbT9Fu2n7cfPzS3M0iIiIionSAQToRJVl4pCGTbm9rUXr0FG3LB1VDTm8XXH/8Em2n7cexW0/N3SwiIiIisnEM0okoyaKiM+k2OOuKUjibB1a9Xw0lc3rh6ctwvDvzEDacvm/uZhERERGRDbPRr9ZElJZj0m0xk26UxdMZSwZUQYOiWVXPgcELj2Parmus/E5EREREqYJBOhElWZjeDsdyFsXzUmUBjQa2ylXrgN+7l0ev6n7q9g+bL+LTFadjuvsTEREREaUUBulElGThsMOevOXwrFpNmw7ShcbeDl+1LI4x7xRXU84tPXoHPeYcwvMQVn4nIiIi62JnZ4fVq1ebuxn0BgzSiSjZ86TLdGXpxXvV/DD7vYpwd3LAwetP0Wbqftxg5XciIiKyED179lRBePylSZMmsEZ+fn6YOHHif643YMAA5M+fHy4uLsicOTNatWqFixcvwhoxSCeiJIuIjIJnaDCcX74A0tEY7bpFsmD5oKqq8rsE6K2n7MOBa0/M3SwiIiIiRQLy+/fvx1kWLVoEW1a+fHnMnTsXFy5cwJYtW1T9oEaNGiEqKgrWhkE6ESVdeAR6H10Dv4XzgIgIpCdFsnli9eDqKJPLG4GvItB99iEsPXLb3M0iIiKiVCJBny4kxCyLqQVrnZyckC1btjhLhgwZ3rj+7du30bFjR3h7eyNjxowqC33z5s042fnWrVvj22+/RdasWdV6Y8eORWRkJD7++GP1GF9fXxUkJ2W748ePR/bs2ZEpUyYMHjwYEdHfK+vUqYNbt25h5MiRMT0C3qR///6oVauWyryXK1cO48aNU88f+/mshYO5G0BE1itSF13dPR11d48ts4cTFvevgo+WncL60/fxyYrTuPY4GJ82LpJuXxMiIiJbpX/1CpfKlTfLcxc+fgx2rq6psm0JiBs3boyqVatiz549cHBwUAGuZONPnz4NrVar1tuxY4cKxHfv3o19+/ahT58+2L9/vwqMDx06hCVLlqgu5w0bNlTrJXa7O3fuVAG6/Lx69So6deqEMmXKoF+/fli5ciVKly6tAnC5nVgvX75UFwzy5s2LXLlywdowk05EyR6TbstTsP0XZ0cNJnUui2H1Cqjbv/9zHYMWHENIeKS5m0ZERETp1Pr16+Hu7h5nkSx4QiS41ul0mDVrFkqWLImiRYuqANff3x+7du2KWU8y4ZMmTULhwoXRu3dv9TMkJASfffYZChYsiNGjR6vAe+/evSZtVzL8kydPRpEiRdCiRQs0b94c27dvj3lOjUYDDw+PmB4BbzN16tSY/d20aRO2bt0aczHAmjCTTkTJz6Sn3xhdkaz5B40KI19md3yy/DS2nHuIDtMPYGaPCsjh7WLu5hEREVEKsHNxURltcz23KerWrYtp06bFuU8C3oScOnVKZbAlEI4tNDQU165di7ldvHhx2Nv/m+OVbu8lSpSIuS3BtHRXDwgIMHm78lij7Nmz48yZM0iKrl27qky+jMGXLvTS1V6y/tL935owSCeiJItkJj2O1mVzwjeDC/rPP4Zz94LwzuR9mNmjPMrmfvMYMCIiIrIOakx0KnU5T2lubm4oUMDQy++/BAcHq6JrCxYseO1vUiXdyNHR8bXXI6H7JHue3O3qordhKi8vL7VIZr9KlSoqS79q1Sp07twZ1oRBOhElWQQz6a+p4JcRawZXR78/j+LigxfoNOMgfmxXSgXwRERERJZGiqxJ1/QsWbLA09PT4rar1WqTVKFdiu3JEhYWBmvDMelElCRROjnxGX5nJj2uXBldsXxQNTQomhXhkTqMWHISP26+CJ0u/UxTR0REROYjgemDBw/iLI8fP35jF3EfHx9VeV0KvN24cUONGR82bBju3LmT5Dak1Hb9/PxUsbq7d+++cR+uX7+O7777DseOHVNj3qWgXYcOHdSc6c2aNYO1YZBOREkSEaWDzs4ep7IXQkSZMjIw29xNsijuTg6Y0b08BtXJr25P3XUNA/46hpdhLChHREREqWvz5s1qbHfspUaNGgmu6+rqqoLg3Llzo23btqrAm1Rul7HjycmAp9R2x44dq6ZRy58/f5xu8rE5OzurCwESkEs3f6kQL2PhJViXTL61sdObOumelQsKClLjFAIDA1O0O0dqkLEYUnhBDqzYRRqILMGL0AiU/N/f6vddQ8oid45sPE7fYNWJO/h0xRmVVS+SzQOz3qsA3wzWMabNlvCcStaCxypZC1s/ViWYlOyvTOMlQSBZL71er+Z0l2ng3jbXemoeM6bEobb3aSKiNC0aJxw4KP2t2pT1VfOp+7g7qXHqrSbvw9GbT83dLCIiIiKyQAzSiSjpReP0erhGhMLhVYj6nd6sXO4MWDukOopl98STl+F4d+ZBLDnib+5mEREREZGFYZBOREnOpDvqIjHo8Eq4yzycERHmbpLFkznTlw+qiqYlsiEiSq+6wP9v7Tk1vp+IiIiISDBIJ6LkzZHOru4mcdU6YEqXcvigYSF1e97+m+gx+zCevgw3d9OIiIiIyAIwSCeiJAmPzv4yRjedXNgYVr8gfu9eHm5aDQ5cf4J3Ju/FhftB5m4aEREREZkZg3QiSpJIGZPOOdKTpXHxbFj5fnXkzuiKO89eoe3U/dh05r65m0VEREREZsQgnYiS1d1dw1R6shTO5qEKytUo4INXEVEYtOA4Jmy9DJ2OhfiIiIiI0iMG6USUJMZiZ8ykJ5+3qxbzelVE7+p51e1J269gwF/HEBwWae6mEREREVEaY5BOREkSGZ3pZSI9ZTho7PFly2L4qX0paDX22Hr+IdpM2Ycbj1+au2lERERElIYYpBNRkkRE6qCzs8cN34KIKF5cqqGZu0k2oUOFXFg8oAqyeDjhSkCwKii34+JDczeLiIiIbIidnR1Wr15t7mbQG/BbNRElSYROjyh7DQ6XqYWwpk0BBwdzN8lmlMudAeuH1kD5PBnwIjQSff44qrrAc5w6ERER/ZeePXuqIDz+0qRJE1gjPz8/TJw4MdHr6/V6NG3a1KovRDBIJ6IkiYwek+6o4WkkNWTxdMaiflXQrUpu6PVQxeRknPqL0AhzN42IiIgsnATk9+/fj7MsWrQI6cHEiRNVgG7N+O2aiJIkQqq76/Vw0UUC4eHqd0pZWgd7jGtdEj+0KxkzTr31lH249ijY3E0jIiJKdyRDGxEWZZZFntsUTk5OyJYtW5wlQ4YMb1z/9u3b6NixI7y9vZExY0a0atUKN2/ejJOdb926Nb799ltkzZpVrTd27FhERkbi448/Vo/x9fXF3Llzk7Td8ePHI3v27MiUKRMGDx6MiAhDUqJOnTq4desWRo4cGdMj4G1OnjyJn3/+GXPmzIE1M3v/1ClTpuCnn37CgwcPULp0afz222+oVKnSW6+MTJs2Df7+/vDx8UH79u3x3XffwdnZOU3bTZTeSXV3R10k2v89H+7+GYBx4wCNxtzNskmdKuZG4WyeGDj/GK49eonWk/dhQqcyaFgsq7mbRkRElG5EhuswY/g/Znnu/r/WhqNT6nzPkoC4cePGqFq1Kvbs2QMHBweMGzdOZeNPnz4NrVar1tuxY4cKxHfv3o19+/ahT58+2L9/P2rVqoVDhw5hyZIlGDBgABo2bKjWS+x2d+7cqQJ0+Xn16lV06tQJZcqUQb9+/bBy5UoVI/bv31/dfpuQkBB06dJFxZdyUcKamTWTLm/kBx98gK+++grHjx9Xb4C8kQEBAQmuv3DhQowaNUqtf+HCBcyePVtt47PPPkvzthOld5G66CnYWN49TZTJ5Y11Q2ugkl9GvAiLRL8/j+IXzqdORERECVi/fj3c3d3jLJIFT4jEUzqdDrNmzULJkiVRtGhRlRGXpOiuXbti1pNM+KRJk1C4cGH07t1b/ZTAWGKxggULYvTo0Srw3rt3r0nblQz/5MmTUaRIEbRo0QLNmzfH9u3bY55To9HAw8MjpkfAm0i2vVq1aipbb+3MmkmfMGGCuiLSq1cvdXv69OnYsGGD6p4gwXh8cqWmevXq6gqJsYjAu+++q67cEJEZurvLmHREwT74AaA3BO2UejJ7OGFBv8r4ZsMFzNt/E79uv4IzdwPxS8cy8HJ1NHfziIiIbJqD1l5ltM313KaoW7eu6n0cmwS8CTl16pTKYEsgHFtoaCiuXbsWc7t48eKwjzWbj3R7L1GiRMxtCaalu7ox4WrKduWxRtmzZ8eZM2dM2t+1a9eqTP+JEydgC8wWpIeHh+PYsWPqiouRvOkNGjTAgQMHEnyMXBn566+/cPjwYdUl/vr169i4cSO6d+/+xucJCwtTi1FQUJD6KVd1ZLFk0j4Zf2Lp7aT0KSIySv0sFXoUrhcvQ7c0FLoOMwFnL3M3zaZp7IAvWxRFiRye+L/VZ7HjYgBaTt6DqV3KoVgOT3M3z6LxnErWgscqWQtbP1aN+2dckhIspyRTxqW7ubkhf/78b92Gcb9evHiB8uXLqzgrvsyZM8c8xtHRMc7jZXy4dGGPf19UVFSythv7tTeK/R4kRDLvEvjL2PfY2rVrh5o1a6qu9MbHmzq+3xTGdiYUa5ryOTFbkP748WP1BsoVmNjk9sWLFxN8jGTQ5XE1atRQOy+FCgYOHPjW7u4yXn3MmDGv3f/o0SN1FceSyRsZGBio9jX2VSsiS/As0HDByyXKUMTM/urfiJxeC88b/YZInyJmbp3tq+HriJkdC2PU+mvwf/oK7abtx6f186BZsUzmbprF4jmVrAWPVbIWtn6syphq2UeJOWSxFsYA8b/aLLGYrCPjv5cuXaoy7Z6er1/wl3US2qYxII3/PMb1Umq7jo6O6r142/589NFHqghdbOXKlVMF6aT7vDxe9lekZuV34z49efJEtTs2uWhhNYXjTCFjF2QsxdSpU1G5cmXVfWL48OH4+uuv8cUXXyT4GMnUy7j32Jn0XLlyqas3CR0slkTeYDmIpK22eOIj6+bk8lL91NhFX5W0c4BDkD8yre4MffMJQOnOZm6h7cuSBdiQPydGLj2FXZceYezfN3EtUIfPmxeBkwOL+MXHcypZCx6rZC1s/ViVhJ4EVpItlsVayHshQakkN2OTfZDC20bSxVzuk17JMgxZCnJLclOKvklFdSna9sknn6jbsk1ZYr8Oxmrr8V8b43optd28efOqQnWSsJWq9bH3wUi2JUt8MjxaxssbxQ+cU5q0WfZHuv3HL2xuSqFzsx1t8uLKgfHw4cM498vtNxUEkEBc3uy+ffuq21KA4OXLl6ra3//93/8leHKQN1KW+IwHhKWTA9Ra2krpS/SQdGhg6Lqjb/oj7K5tht3VrbBbMwi4exRo8h3g8Prnj1JOBjcnzHmvIibtuKLGqC845I9z94IwrVs5ZPdyMXfzLA7PqWQteKyStbDlY1X2yRgwWtu825s3b0aOHDni3CeF3mL3WDbul3SNl4rtn376qeoeLhcmcubMifr168PLyyvOvsd/HRJ6bZK7Xbvo340/Zao3qRpfoEABNYzZlO7qxrbIY+JvNzUYny+hz4QpnxGzBelS+U/GKMj4AZkbz3g1Tm4PGTIkwcdI9cD4O2csMpCaYwuI6HWRUTro7OwRlVULhGsAj6xAl6XA7h+BXd8DR2cD908CHf8EvF6/skkpRyrsj2hQCKV9vTF88QmcvP0cLSbtxW9dyqJa/tevNhMREZHtmjdvnlreJn7sJEnSP/74463bjC92hXaj2HOgJ3W7EydOjHO7SpUqqgidqaw5PjTrJS/phj5z5kz1xsmUaoMGDVKZcWO19x49esQpLNeyZUtVpXDx4sW4ceMGtm7dqrLrcn/sioBElDbV3aPsNYgo6QkUdwScXCVaBOqMArouA5y9gbvHgN9rAddfP4lTyqtbJAvWD62JYtk98eRlOLrNOoTp/1yz6v+kiIiIiNIbsw6ukInqpYDbl19+iQcPHqjiAtI1w1hMTubQi505//zzz1X3Afl59+5dNf5FAvRvvvnGjHtBlL7nSXfURxju0Gj//WPBhsCAf4Al3YEHp4H5bYB6nwPVRxoCeUo1uTO5YsWgavh89VmsOH4H32+6iGO3nmF8h9LwcuE0bURERESWzk6fzlIsUjhOxkBIJUprKBwn8wxmyZLFJsf5kHX7duMFzNh9HSc8P0KG8HvQ9f4b9rkrx10p4hWw8SPgRPTUGwUbA22mA64Jz9NJKUdO7QsP+2PM2vMIj9IhV0YXTOtaHiVypt8p8nhOJWvBY5Wsha0fq1I4TnrvSuEyU4p+keXRR1eLl8JuqTkm/W3HjClxqO19mogoTURE6eAYFQHXbQ+BXaFAVAInPEcXoNUU4J3fAI0TcGUL8HttQzd4SlXyH1DXynlUVt03gwtuP32FttP2Y9Fhf3Z/JyIiIrJgDNKJKEkio8u72yPq9e7u8ZXrAfTdBmTICwT6A3OaAIdnymXNNGpt+lXS1wsbhtZE/SJZEB6pw+iVZ/DhslMICbee+V6JiIiI0hMG6USUrDHp9nrDT2j+Y7xz9lKGcepFWgBR4YZu8Cv6AGEv0qC16ZuXqyNm9qiAT5sUgb0dsPL4XbSZsh/XHgWbu2lEREREFA+DdCJKcnV3YaePzqQ7vCWTbuTsBXT6C2j0DWDvAJxdAcyoCwRcSOXWkkzTNqhOfizoWwU+7k649PAF3vltL9afvmfuphERERFRLAzSiSjJY9IBfeK6u8cmxTqqDQF6bgQ8cgBPrgAz6wGnFqdqe8mgav5M2DisBirnzYiX4VEYsvAEvlpzFmGR0e8jEREREZkVg3QiSvKYdAdjgC6kMJwppBL8wD1AvrpARAiwagCwdqihIjylqiyezljQtzIG1s6vbv9x4BbaTzuAW09emrtpREREROkeg3QiSnImXYtYxcf+a0x6Qtx8gG4rgDqjJcUOHP8TmFkfeHQ5RdtKr3PQ2GNU0yKY27MivF0dceZuIFpM2otNZ+6bu2lEREREyXbz5k01283JkyfV7X/++UdNFfj8+fNkbdfPzw8TJ05EamKQTkRJEqnTQ2OnAzJqDIvWJWkbstcAdUYBPVYDblmAgHPAjDrAqSUp3WRKQN0iWbBxWE2Uz5MBL8IiMWjBcfxv7Tl2fyciIrJSPXv2ROvWrdP8eefNmwdvb29YqqpVq+LevXtqrnJLxyCdiJKcSdfY64BSjtCX0gKOJnZ3jy9fHWDgXiBvLSDiJbCqP7BmCBAeklJNpjfI4e2Cxf2rYEDtfOr2vP03Vfd3/yd87YmIiMg2aLVaZMuWTWXXLR2DdCJKfnd3KRqXEic8j6xA99X/dn8/MR+YJd3fLyV/2/RWjhp7jG5aFHN6Vojp/t580h52fyciIoovPPzNS2Rk4teNiEjcuslUp04dDBs2DJ988gkyZsyoAtX//e9/cdaRwHXatGlo2rQpXFxckC9fPixfvjzm77t27VLrxO4qLt3I5T7pVi5/79WrFwIDA9V9ssR/DqNr166hVatWyJo1K9zd3VGxYkVs27bttS7lX3/9Nd599124ubkhZ86cmDJlikltji+h7u579+5FzZo11eNz5cqlXqeXL/+t0RMQEICWLVuqv+fNmxcLFixAWnBIk2chIpssHKe1M/xHpE/KePT/6v6euyqwoi8QcN7Q/b35BKDMuyn3PJSgekWyqu7vQxYex3H/56r7e89qfhjdrAicHDTmbh4REZH5ffvtm/9WsCDQteu/t3/66fVg3MjPT/qm/3tbxjmHJNCL7Q3Brin++OMPfPDBBzh06BAOHDigusRXr14dDRs2jFnniy++wPfff49ff/0V8+fPR+fOnXHmzBkULVr0P7dfrVo1NU77yy+/xKVLhuSKBOAJCQ4ORrNmzfDNN9/AyckJf/75pwqE5XG5c+eOWe+nn37CZ599hjFjxmDLli0YPnw4ChUqlGJtlosFTZo0wbhx4zBnzhw8evQIQ4YMUcvcuXPVOvI6SRf5nTt3wtHRUQXxErinNmbSiShJInR6uESFArvDgH9CUuRKbxz5akd3f69tqP6+eiCwejAQzgrkqU26vy8ZUDVO9/e2U/fjxmO+9kRERNaoVKlS+Oqrr1CwYEH06NEDFSpUwPbt2+Os06FDB/Tt21cFwpLFlnV+++23RHcll7Hekt2WTL0sbwrSS5cujQEDBqBEiRKqPfJc+fPnx9q1a+OsV716dYwaNUq1Z+jQoWjfvj1++eWXFGvzd999h65du2LEiBGqHXKhYdKkSeqiQWhoKC5fvoxNmzZh5syZqFKlCsqXL4/Zs2fj1avUn4mImXQiSpJI1d09AtDpAV0qXe9T3d9XAXt+BnZ9B5z8C7hzGGg/F8hWInWek+J0f6+SNxM+WHoS5+4FocWkPRjXpgTalPU1d/OIiIjM57PP3vw3+3jfiT7++M3rxh8qOGIEUjNIjy179uyvZYSlsFr828bK6ClJMunSFX7Dhg24f/8+IiMjVeDr7+//n+2ZGK+qenLafOrUKZw+fTpOF3a9Xg+dTocbN26oIN3BwUEF50ZFihRJk+J4DNKJKMnd3d2MY9Kli3pqkW3X/sTQ/X1lP+DxZWBmPaDxN0DFvikzFp7eWv190/BaGL74BA7deIqRS05h75UnGNuqONyc+F8IERGlQ1qt+dc1kXTVjk0y3hKMJpaM5TYGsUYRb+rG/x8++ugjbN26FePHj0eBAgXUeG/JkoendK/MRFwskIy+dGGPT7rdS5BuLuzuTkRJLhznGD0mHXZpcCrJWxMYuA8o2BiICgM2fgQs6Qa8epb6z53OZfNyxsJ+VTCyQSHY2wErjt9By8l7cf5ekLmbRkRERCnk4MGDr902ju3OnDmz+imZb6P4GWvp8h4V9d9TuO7bt0+N9W7Tpg1KliypusZL8TlT2mPKOm9Srlw5nD9/Xl0oiL/IvkjWXLL8x44di3mMjJtP7jzricEgnYiSJEKng2N0Jl1vl0YFxdwyAV2WAI2/A+wdgYvrgek1Af+4J2hKeRp7OwxvUFAF61k9nXD90Uu0nroP8w/cjHNVnYiIiKzTsmXLVAE1ySDL+PXDhw+rImpCAlepfi7d1K9cuaK6qv/888+vVWSX7LSMdX/8+DFCEiqCp2rrFcTKlStVkC9dzrt06ZJgVn/fvn348ccfVXuksru0T4rHJbbN/+XTTz/F/v371frSFtmvNWvWxDy+cOHCqrCcZNul4J4E6zL+XTL/qY1BOhElvbq7jEkXaRWkq+eyA6q+D/TdCmTMBwTeBuY2A3aPB3T/ffWWkqdKvkyq+3u9IlkQHqnDF2vOYdBfxxEYkrQub0RERGQZpIr64sWL1fh1KZ62aNEiFCtWLKa7vNy+ePGi+vsPP/ygqqLHJoXXBg4ciE6dOqnMuwTYCZkwYQIyZMig1peq7o0bN1ZZ7fg+/PBDHD16FGXLllXPJY+TdRPb5v8ij5Fp2STAl2nY5HmkOn2OHDli1pEq73K7du3aaNu2Lfr3748sWbIgtdnp01kKJCgoSFUelDn8PD09YcnkipIUdJADwTgOhMhSVBi3DZVf7MKUQz8hyj0H7JZfgL2zc9o2IuwFsP4D4MxSw+28tYA2MwDP7GnbjnRI/uuYs+8mvt90ARFReuTwcsbEzmVRKW9GWCqeU8la8Fgla2Hrx6pU+JYCYjI/tnNaf8dJYzJGfdWqVWjdujUsgZ+fn6q6LktKtFm+t0jXdSkEJ48zxzFjShxqe58mIkoTkaq7ewTgbQ9dZjfzFHBz8gDazgBaTwMcXYEbu4Hp1YFLm9K+LemM/AfXp0ZerBhUDX6ZXHEvMBSdZxzAhK2XVeV/IiIiIkoaBulElCQRkTo4OOiBMlroauSVflDmaYhcHCjTBej/D5CtJBDyBFjUGdjwERCR+vNYpnelfL2xflhNtC/vq2bjm7T9CjrNOIjbTxMeh0ZEREREb8f5c4goSSJ0MiY9unCcxkwBemyZCwF9twPbxwIHJgNHZgI39wLtZwNZi5u7dTbN3ckB4zuURq1CmfF/K8/g2K1naDZpD75tUxItS/87rouIiIgsk6WNgL6ZQLV3S29zSmImnYiSRLo0x1R316TevJ4mcXAyzJ/ebQXglgV4dAGYURc4NEPO5OZunc17p3QObBxeE+Vye+NFaCSGLjqBj5adwsuw6Kn6iIiIiOg/MUgnIpPpdHrVtdk5KhTYFwaHjZeB8HBYjAINgEH7gYKNDHOqb/rY0AX+5WNzt8zm5croiqUDqmJYvQJqTvXlx+6gxW97cfpO6s8pSkRElBpsOWNLlnmssLs7ESVpjnShMukResNiadwzA12WAod+B7Z+AVzeDEyrBrSZDuSvZ+7W2TQHjT0+aFQY1Qv4YOSSk7jx+CXaTt2PDxoVwoBa+dWc60RERJZOph2TQqmPHj1SU4qlZlVwSl36NKjuLs8hx4psX46d5GCQTkQmkym3hJNdZNrPk24KOQlXGQj41QBW9AEeXQTmtwGqvA/U/wpwtO3pVMytcvSc6qNXncbGMw/w4+ZL2HXpEX7pVAY5vV3M3TwiIqK30mg08PX1xZ07dxI1Rposl16vV1MGylSBqXmxRbYtx4wcO8nBIJ2ITGacYitmTLqlBulG2UoA/XYCf38OHJ0NHJwKXP8HaDeTReVSmZerI6Z0KYdlx+5gzNpzOHzjKZpM3I1xrUugVZmc5m4eERHRW7m7u6NgwYKIiIgwd1MoGSRAf/LkCTJlyqQC9dQiGfTkBuiCQToRJTmTrpV50kUqnuxSjNYVaDHBME59zWAg4Bwwow7Q4H9A5UHWsQ9WSq4qd6yQC5XzZsSIJSdxwv85hi8+iZ0XAzC2dQl4OlvA7ABERERvIEFXSgReZN4g3dHREc7OzqkapKcUy28hEVmcyOgx6U52Osvu7p6Qwk2A9w8AhZoAUeHAls+Av9oAQffM3TKblyeTG5YNqIrh9QuqonKrT95D04l7VHadiIiIiAwYpBORySIi445Jt/ju7vG5ZwHeXQy0+AVwcAGu7zIUlTu/xtwtSxdF5UY2LIRlA6shd0ZX3H3+Cp1nHMBPWy4iInoYBREREVF6xiCdiJJc3V1rHwl42EPn420o0mZNpL0VegMD9wDZywCvngFLewCr3wfCXpi7dTavfJ4Mak719uV91XR+U3ZeUxXgrwbwtSciIqL0jUE6EZks0ljd3UEHlNciokU1qZQBq+RTEOizFaj5oUTuwMkFhqz6rf3mbpnNc3dywPgOpVVhOS8XR5y5G4jmk/Zi7r4b0EnkTkRERJQOMUgnIpMZuyVrEaV+6jVaWDUHLVD/S6DXRsA7N/DcH5jbDPj7CyAyzNyts3nNS2XHlhG1UKtQZoRF6jBm3Xn0mHMY9wNfmbtpRERERGmOQToRmSxSF2+edI2VZtHjy1MNGLgPKNtNLj0A+ycBM+oCD86Yu2U2L5uXM/7oVRFftyoOZ0d77L36GI1/2Y01J++au2lEREREaYpBOhElOZPuJNXRD4ZBu2I3YCvzhzp7Aq2mAJ0XAq4+0VO11QX2TAB0hp4DlHpTtXWv6ocNw2qitK8XgkIj1VRtQxYex/OQcHM3j4iIiChNMEgnomR0d48AQvXAy3BAb2NjiIs0B94/CBRuDugigO1jDF3gn143d8tsXv7M7lg+qBpGNCgIjb0d1p++j8YTd+Ofy4/M3TQiIiKiVMcgnYiSXDjOIXpMOuxt9FTinhnovABoNRXQegC3DwLTagBH59reRQkL46ixx4gGhbByUDXky+yGh0FheG/OYfzfqjN4GRY9zIKIiIjIBtnoN2siSk2R0VOwOUkmXVjbPOmmTtVWtiswaB+QpzoQ8RJYPwJY0AEIumfu1tm80rm8sWFoTfSs5qduLzjkj6a/7sGh60/M3TQiIiKiVMEgnYhMFhGTSY+0/SDdKEMe4L31QKNxgMYJuLoVmFoFOLWEWfVU5qLV4H/vFMfCvpWR09sF/k9D0HnmQYxbfx6hEawTQERERLaFQToRJWNMuiFI19ungyDd2K2/2lBgwG4gRzkgNBBY1R9Y0g0IDjB362xetQI+2DyiJjpVyKWui8zaewPNJ+3BydvPzd00IiIiohTDIJ2IkjEm3ZhJT2enkixFgD5bgXqfA/aOwMX1hqz6udXmbpnN83B2xA/tS2FOzwrI4uGEa49eot20/Ri/5RLCIw0Xj4iIiIisWTr7Zk1EKZlJd5Qx6a720GXKZBi7nZ5oHIBaHwP9dwJZSwAhT4Bl7wHLewMhT83dOptXr0hW/D2yFlqVyYEonR6Td15Fqyn7cP5ekLmbRkRERJQsDNKJyGSRuuhMuiYKqKTFq24dAUdHpEvZSgL9dhoCdhmbf3aFIat+aZO5W2bzvF21+LVzWUztWg4Z3bS4cD8I70zei1+3XYm5kERERERkbRikE5HJIo2ZdH10dXd7LdI1B62h63vfrYBPYSD4IbCoM7CyP7PqaaBZyezYMqIWGhfPqi4g/bLtMlpNZladiIiIrBODdCIyWXj0mHRNdJCu16TTLHp8OcsbispVG2YYp396iSGrfnGDuVtm8zJ7OGF6t/L4tXMZeLs64nx0Vn3itsscq05ERERWhUE6ESUpk24PHTRRUcDhcDgvWA5ERGfV0ztHZ6DR14bCcj6FDFn1xV2AFX2ZVU9ldnZ2aFUmJ7aOrB2TVZ+47Yoaq37uXqC5m0dERESUKAzSichkEvw4Giu7h+hg/yyQc4XH51sBGLAHqD7CkFU/swyYUgm4sM7cLUs3WfVJ75ZFBldHNVZdur9LwM6x6kRERGTpGKQTkckk0HGSyu5GUjCNEs6qNxwD9NkGZC4CvHxkmFNdKsC/fGLu1tl8Vv2d0jnwd6ys+qQdV9F70UWcvcusOhEREVkuBulElKR50mMy6elxnnRT+ZYH+v8D1Pjg3wrwklU/u5I9ENI4q37l8Su0mXYAP2y+iNCIKHM3j4iIiOg1/GZNREnKpGujg3S9BJ3pbY70pGbVG3wF9JWselEg5DGwvJchs/7igblbly6y6puH10T9ghnUvOrTdl1Ds0l7cPQm6wQQERGRZWGQTkQmi5BMul10Jt2eXd1NkrMcMOAfoPangL0DcHE9MLkScHw+s+ppkFX/pnk+TOtaVv1+/dFLdPj9AP639hxehsXqGUJERERkRgzSichkkTrJpEePSed4dNM5OAF1PzN0gc9eBggLBNYOAea3AZ7dMnfrbF7j4tmwbWRttC/vq66LzNt/E40n7sbeK4/N3TQiIiIiBulElLRMurG7O9y00Hl6sst7UmQrAfTdDjQcCzg4A9d3AlOrAgenAzpWIU9NXq6OGN+hNP7oXQk5vV1w59krdJt9CJ8uP43AV5xOkIiIiMyHQToRJWmedBWka+yAulkR0r8/4Oho7mZZJ40DUH04MGg/kKc6EPES2PwpMLcJ8OiyuVtn82oXyowtI2uhR9U86vaSo7fRcMI/2HyWdQKIiIjIPBikE1GSCsfFVHfXaM3dHNuQKT/w3nqg+c+A1h24fQiYXh3Y9QMQGW7u1tk0dycHjG1VAksHVEVeHzcEvAjDwL+OYeD8Y3gYFGru5hEREVE6wyCdiEwWodNDaxfdJZhBesqxtwcq9gXePwgUbAREhQO7vgV+rwXcPmzu1tm8SnkzYtPwmhhcNz8c7O2w+dwDNJjwDxYe8odOx6J+RERElDYYpBNRkrq7q0x6lB7Y/wQu8+cDERzHm2K8cwFdlgLtZgOuPsCjC8DsRsCGj4DQIHO3zqY5O2rwceMiWDe0Bkr7euFFaCQ+W3UGnWcexLVHweZuHhEREaUDDNKJyGSRUXo4Gbu7B0VC8/Ahpw9LaVKIr2R7YMgRoExXmZEeODITmFoFuLTJ3K2zeUWze2Ll+9XxRYticHHU4PCNp2j66x5M2XlVDfcgIiIiSi0M0okoSd3dY8akcwq21OWaEWg9FeixBsiQFwi6CyzqDCx9D3jx0Nyts2kaezv0qZEXf4+shVqFMiM8UoeftlxCy9/24oT/M3M3j4iIiGwUg3QiMllEZKx50u0dzN2c9CFfHUMF+OojDBdGzq8GplQEjs3jdG2pLFdGV/zRqyImdiqDDK6OuPjgBdpO248v15xFUCiHeRAREVHKYpBORCaL1OmgtYv8t9gZpQ2tK9BwDNB/J5C9DBAaCKwbDsxtCgRcMHfrbJqdnR1al82J7R/WQbtyvmp0x58Hbqnp2jaduQ89h3sQERFRCuG3ayIyWURU7O7uzKSnueylgb7bgSbfR0/XdhCYXgPYPhaIeGXu1tm0jG5a/NyxNBb2rayma3sYFIZBC46j359Hcfc5X3siIiJKPgbpRJS0THpMd3eeRsxC4wBUGQQMPgQUbg7oIoE9PxsKy13bYe7W2bxqBXzUdG3D6hWAo8YO2y4EqKz6rD3X1ewHREREREnFb9dEZLKISD20iDLccHGG3sXF3E1Kv7x8gXcXAp0WAB45gGc3gfltgBV9geAAc7fO5qdr+6BRYWwcVhMV/TIgJDwK4zZcQOup+3D6znNzN4+IiIisFIN0IjJZhDGTrrED2lfCy8GDAa3W3M1K34q2AIYcBioPAuzsgTPLgMkVgKNzWVgulRXM6oEl/avi+7Yl4ensgLN3g9Bqyj4WliMiIqIkYZBOREmaJ93RWDhO42Tu5pCRkwfQ9HvDeHUZty6F5daPAOY0Au6fNnfrbJq9vR06V8qtCsu1KpMjprBc/Z//wZqTd1lYjoiIiBKNQToRmUzG3GqNheM0juZuDsWXsxzQd0d0YTkP4M4RYEZtYPNoIOyFuVtn0zJ7OOHXzmWxoG9l5PNxw6MXYRi++CS6zz6M64+Czd08IiIisgIM0onIZBG66OruUXpg23m4LFkCRLBbr0UWlpMu8MXbAHodcHAqMLkicG4VVKqXUk11KSw3oiY+aFgIWgd77L36GE0m7sGErZcRGhFdz4GIiIgoAQzSichkEVE6OBmruwe8gOb2bQZ9lsozB9BhHtBtBZAhL/DiPrCsJ/BXO+DJNXO3zqY5OWgwrH5BbB1ZC7ULZUZ4lA6Ttl9B44m78c/lR+ZuHhEREVkoBulElLQx6cbu7vYaczeHEqNAA+D9g0DtUYBGC1zbDkytCuz6HogINXfrbFqeTG6Y16sipnQph6yeTrj1JATvzTmM9xccwz3OrU5ERETxMEgnoiRl0rXGwnEM0q2HozNQd7QhWM9XF4gKA3Z9Z5hb/fLf5m6dTbOzs0PzUtmx7YPa6F09L+ztgI1nHqjCctN2XUN4JCvwExERkQGDdCIyWaRxTLqwY5BudTLlB7qvAtrPATyyA89uAAs7AIu6AM9umbt1Ns3D2RFftiyG9UNrokKeDHgVEYUfNl9E0193Y//Vx+ZuHhEREVkABulEZBKdTo8ond4wT7pgJt062dkBJdoBQ44A1YYC9g7ApQ3AlErAPz+xC3wqK5bDE0sHVMX4DqWRyU2La49eosusQxi66AQeBPK1JyIiSs8YpBORSSJ0hm65MVOwMUi3/rnVG40DBu4F/GoCkaHAznGGLvBXtpq7dTY/t3r78r7Y8VEd9KiaR3WBX3fqHur/vAuz9lxXw0qIiIgo/TF7kD5lyhT4+fnB2dkZlStXxuHDh9+6/vPnzzF48GBkz54dTk5OKFSoEDZu3Jhm7SVK76RonDCOSdc7aqF3cDBzqyjZshQF3lsHtJsNuGczdIFf0B5Y3JVd4FOZl4sjxrYqgbVDaqBsbm+8DI/CuA0X0OzXPewCT0RElA6ZNUhfsmQJPvjgA3z11Vc4fvw4SpcujcaNGyMgICDB9cPDw9GwYUPcvHkTy5cvx6VLlzBz5kzkzJkzzdtOlN6DdDUmXWMHDOqClyNGAFqtuZtGKdEFvmR7Qxf4qkMM9QYurjd0gVdV4FmJPDWVyOmFFQOr4cd2pZDRTYsrAcGqC7xUgb/LKvBERETphlmD9AkTJqBfv37o1asXihUrhunTp8PV1RVz5sxJcH25/+nTp1i9ejWqV6+uMvC1a9dWwT0RpXV3d8OY9FfQ4+yzs4jSRZm5ZZRinD2Bxt8YusDnqWHoAi9V4CVYv7AO0Bsu1FDqdIHvWDEXdnxYO6YLvKEK/C78tv0KQiP4OSMiIrJ1ZuujKlnxY8eOYfTo0TH32dvbo0GDBjhw4ECCj1m7di2qVq2quruvWbMGmTNnRpcuXfDpp59Co0l4XGxYWJhajIKCgtRPnU6nFksm7dPr9RbfTkpfwqODBC0MP3/0X4+VDw+gyJUiGFVpFMpmKWvmFlKKyVwE6LEWOL8adls/h91zf2BJN+jz1oG+yfdA5sKwJtZ0TvV0dsD/WhZDpwq++N+68zhy8xl+3noZy47dxufNi6J+kSxqWjeyTdZ0rFL6xmOVrIXOAo5VU57bbEH648ePERUVhaxZs8a5X25fvHgxwcdcv34dO3bsQNeuXdU49KtXr+L9999HRESE6jKfkO+++w5jxox57f5Hjx4hNNSyK+jKGxkYGKgOKLmAQWQJHgQaLnpp7SIAnR45Nh1H89Dn2Fz5Anpu6Yl62euhX6F+8HH2MXdTKaVkrg67DhvgduJ3uJ2cDbsbu4DfayCkRHcEVxgCvdYd1sAaz6mZNMCkVnmx9ZI3fttzB/5PX6H//OOo6ueJkbVzIXcGZ3M3kVKBNR6rlD7xWCVrobOAY/XFixeJXtfB2l7cLFmyYMaMGSpzXr58edy9exc//fTTG4N0ydTLuPfYmfRcuXKpLLynpycsfX8lUyJt5YmPLEWw/ct/M+l6IMvDl4gKDUNR7yI49+IydtzfgQOPDqBvib7oXqw7nDRO5m4ypZSc30FfrT/w9//B7vImuJ2eC9drG6Cv/xVQujNgZ9nnKWs+p3bLmhVtKhfAlF3XMHvvDRy4GYSjt8+jVzU/DK6bX82/TrbDmo9VSl94rJK10FnAsSqF0i0+SPfx8VGB9sOHD+PcL7ezZcuW4GOkorujo2Ocru1FixbFgwcPVPd5bQKFq6QCvCzxyZtjDScTOZispa2UPuiihyOrTDqAKL2h686AUv2ROUNOfH/oe5x8dBK/nfwNq66uwscVP0bdXHXZNddW+OQHuiwGrmwDNn8KuydXYbd2MHBsDtDkByBXRVgyaz6nerhoMappUXSqmBtj153DzkuPMGPPDaw8cQ+fNCmM9uV81Zh2sg3WfKxS+sJjlayFnZmPVVOe12yfJgmoJRO+ffv2OFc45LaMO0+IFIuTLu6x+/NfvnxZBe8JBehElPKMczcb50mPjA7SJWNePFNx/Nn0T3xX8ztkccmCO8F3MHzncAzYOgDXn183a7sphRVsAAw6ADQcC0h397vHgNkNgJX9gaB75m6dTcvr44a5vSphbs+KyOfjhsfBYfhk+Wm0mrIPx249NXfziIiIKJmSFKTLXOWzZs1SXcml2rqQKdSk67kppBu6TKH2xx9/4MKFCxg0aBBevnypqr2LHj16xCksJ3+X5xs+fLgKzjds2IBvv/1WFZIjIjNMwaYy6YYCcsZu7XKVskW+FljXZh36luwLR3tHHLh/AG3XtsV3h75DYFigGVtPKcpBC1QfDgw9DpTpJu8+cHoJ8Ft5YPdPnLItldUtkgWbR9TC/zUrCg8nB5y5G4h20w5g+OITuB/I156IiCjdBOmnT59GoUKF8MMPP2D8+PEqYBcrV66ME1AnRqdOndQ2vvzyS5QpUwYnT57E5s2bY4rJ+fv74/79+zHry1jyLVu24MiRIyhVqhSGDRumAvZRo0aZuhtElMxMumO8TLqzJu44G1dHVwwvNxxrWq1BnVx1VDC/8OJCNF/VHAsvLESEztBdnmyAR1ag9RSg3w4gV2UgIgTYMc4wZdu51ZyyLRVpHezRr1Y+7PioDjpXzKWmul9z8h7qjf8HkzhlGxERkVWy00uJOxPIFGnlypXDjz/+CA8PD5w6dQr58uXD/v371XRoN2/ehCWTwnFeXl6qup81FI4LCAhQxfI4zocsxYFrT9Bl5n7ccO4maXTMOe+F0KgwNPp9FwpkLfbmx907gB+P/Iirz6+q2/m88uGTip+ges7qadh6SnXyX8rZFcDWL4Gg6N5VMtd60++BbCXN2rT0cE49cycQY9adw9Fbz9TtnN4uGNW0CFqUys66EFYkPRyrZBt4rJK10FnAsWpKHGpyCyWLPWDAgNfuz5kzpyrgRkS2LVKng2P0HOnqdnR3d6392+tCVM1RFctaLsPnlT+Ht5M3rgdex8BtA/H+tvdxI/BGqreb0ogEgiXbA0OOALVHAQ7OwK29wPSawJohwIu4xUIpZZX09cKygVUx6d2yyO7ljLvPX2HoohNoP/0ATt429HwjIiIiy2ZykC6V0uUqQHwyRlxK2hOR7Y9J18LQVV2vscPkVj6Y1iYrnF3/u2eKg70DOhXphA1tN6jp2RzsHLDn7h60XdMWPxz+gePVbYnWDag72hCsF28rRwtwYj7wWzlg93iOV09FkjF/p3QO7PiwDj5oWAgujhocu/UMrafsw8glJzlenYiIyNaC9HfeeQdjx45FREREzJcBGTv+6aefol27dqnRRiKysDHpxvHochbQS/AVq3BcYnhqPVVX91WtVqG2b21E6iPx14W/1Hj1BRcWcLy6LfHODXSYC/T+G8hZHggPBnZ8DUyuCJxZzvHqqchFq8Gw+gWx86M6aFfOV9236sRd1B2/CxO2XkZIuOFzTERERFYepP/8888IDg5W/flfvXqF2rVro0CBAmp8+jfffJM6rSQiixGhMumGL/ehGoeY+00J0o38vPwwuf5k/N7gdxTwLqAy6d8f/l5l1nf474CJJTPIkuWuDPTZBrSdCXjmBAJvAyv6ALMbArePmLt1Ni2blzN+7lgaa4dUR0W/DAiN0KmichKsrzh2BzodP2dERERWXTjOaO/evarSuwTsUkhOCspZAxaOI0qeNSfv4qclf2Ov0wg8dnDF9/cd1f0/TLgCjZPpgbpRpC4Sq66uwuQTk/E01DC1Y8VsFfFRhY9QLNObC9KRFQoPAQ5MBvb+YqgEL0q0Bxp8Zci8pxKeU6Xjgh6bzj7Ad5su4PZTQ7f3Ejk98X/NiqFq/kzmbh5F47FK1oLHKlkLnQUcq6bEoUkO0q0Vg3Si5Fl+7A6mLd+I7U4f446TF9YeClVjzfsuvA5757jTsCVFcHgw5pydgz/O/YFwXTjsYIeW+VtiWNlhyOpmmJ6RbETQfcNUbScXGMasS2+MKoOAmh8Azl4p/nQ8p/5Lpmabu+8mpuy8iuAwQ8+YBkWzqkrwBbK4m7t56R6PVbIWPFbJWugs4Fg1JQ79t69qIsl49LeROc+JyHZFqjHphoruYaqLeyg0dpoU27671h3Dyg1D+0Lt8evxX7HxxkasvbYWW29txXvF30Ov4r3UHOxkAzyzG+ZXr9QP+Ptz4OYeYN9EQ4E5qQxfoRegMfTUoJTl7KjBoDr50aGCL37ddgULD/tj24WH2HkpAF0r58bw+gWRyT3pPWOIiIgo6UzOpJctWzbObSkgd+PGDTg4OCB//vw4fvw4LBkz6UTJM//gLSxbswZrnb7AeY+c2LXnMVwdXNHjr4spkkmP78yjM/jp6E84EXBC3c7knAnvl3kfbQu2VRl8shHyX9HlLcDWL4DHlw33ZcwPNBwLFGlumNotmXhOfbOrAcH4ftNFFagLdycHvF83P3pXz6sCekpbPFbJWvBYJWuhs/V50k+cOBFnOXv2LO7fv4/69etj5MiRyWk3EVmBiMh/q7uHOxiC5JTMpMdXMnNJ/NHkD/xc+2fk8siFJ6FP8PXBr9FubTvsur2LxeVshQThhZsAgw4AzScAbpmBp9eAJV2Buc2AO8fM3UKbJl3cZ71XAQv7VVZj1KUL/I+bL6H+z/9g1QkWlyMiIkpLKXIZQa4EjBkzBl988UVKbI6ILFikTgetXdzq7qkZpBunemzk1whrWq3BqEqj4O3kjeuB1zF0x1D03tIb5x6fS9XnpzQkx1TFPsCwE0CtjwEHF8B/PzCrHrC8N/D0hrlbaNOq5ffB2sE1MKFjaWT3csbd568wcskptJy8F3uvPDZ384iIiNKFFMv1S9peFiJKP1OwhUd3N3ewS5tu544aR3Qt2hUb2m5A7xK9obXX4ujDo+i8oTM+2f0J7gbfTZN2UBpw8gDqfQ4MPQaU7iKXaoCzKwzzq28aBbx8Yu4W2ix7ezu0Leer5lf/uHFh1fX93L0gdJt9CD3mHMb5e0HmbiIREZFNM/mb9aRJk+Lclq6m0t19/vz5aNq0aUq2jYgsUKQK0iPU76H2hgy6JvpnWvHUemJk+ZHoXLgzJp+cjHXX1mHTjU3YdmsbOhfpjP4l+8Pb2TtN20SpxCsn0Gaaoer7tq+AazuAQ9MMFeGrDweqvA9oWUgwNchY9MF1C6BzxVz4bcdVLDh0C7svP8KeK4/QpmxOfNioMHJ6u5i7mURERDbH5MJxefPmjXNbBt5nzpwZ9erVw+jRo+Hh4QFLxsJxRMnz89+XcG3XX5iqnYS1uUvjK/0TlMtYDjPfmQd7jXkKTF14cgETjk3AwfsH1W13R3f0KdlHZd1dpLs02Q4J0rd+BTw4bbjtkR2oMxoo09XQVf4teE5NnltPXuKnLZew/vR9dVvrYI9e1fzwfp0C8HJlFf6UxGOVrAWPVbIWOlufgk0quRNR+hUepYvp7h6m0SAS9nBwdk2R6ttJVTRTUcxoOAP77+3HxOMTcfHpRTV928ILC1Ul+NYFWrMSvK3IXw/IWwc4uxzY/jUQ6A+sGwYcnArU/woo3NSsx6Ity5PJDZO7lEO/ms/x3aYLOHj9KX7ffR2Lj9zG4Lr50aOqHyvBExERpQBe8iIik7u7O0YXjguL7uYuY8PNTYrLVc9ZHUtaLMH3Nb9HTvecePTqEcYcGIM2a9pg+63trARvK+QKeKmOwNCjQKNvAJcMwKOLwOJ3gblNAX9DjwpKHaVzeWNRvyqY27MiCmV1R+CrCHy78SLqjt+FJUf8ERmlM3cTiYiIrFqiUktt27ZN9AZXrlyZnPYQkYWTL+BO0WPSw3R61DsWhDIZ/YG6kYDW/MG6vZ09mudrjoZ5GmLppaX4/fTvuBl0EyN2jUCpzKUwstxIVMhWwdzNpJTg4ARUGwKU7Qbs/QU4NB3wPwDMaQwUagrU/wLIWtzcrbRJclGsbpEsqFUoM1Yev4Nftl7GvcBQfLriDGbuuYGPGhVG4+JZ1XpERESUCpl06Tuf2IWIbFuETh8zT3qEnT0K+79C7htPZbAPLIlWo0W3Yt2wqe0mDCg1QI1NP/3oNHpt6YVB2wapLvFkI1y8gYZjgKHHgXLvATIl4OVNwLTqwKqBwLNb5m6hzdLY26FDhVzY8VEdfN68KLxdHXE1IBgD/zqGttP24+B1VuEnIiJKlUz63LlzTd4wEdmmiEgdPKKD9FA7O2jTYJ705HDXumNI2SHoVLgTpp+ajpVXVmLv3b1qaerXVP0tt2duczeTUqoS/DuTgGpDgR3jgPOrgVOLDFO3VegD1Bhp7hbaLBmL3rdmPnSsmAsz/rmO2Xtv4IT/c3SecRC1C2XGJ00Ko3gOXsgnIiJKDI5JJyKTRMbKpIdF92S15CDdKLNrZnxR9Qusab0GTfMapovcdHMTWq1uhbEHxiIgJMDcTaSU4lMQ6PgH0G8HkK8OEBWupm2z+60c3I/8BoRxnu/U4unsiI8aF8Y/H9dBtyq54WBvh38uP0LzSXsxdNEJXH8UbO4mEhER2WaQvnz5cnTs2BFVqlRBuXLl4ixEZNsipLq7nWFMejisJ0g3kqz5j7V+xLKWy1AzZ01E6iOx7PIyNFvZTE3jFhgWaO4mUkrJWR7osQbovhrIURZ24cFwPzYZdpPKAvsmARGvzN1Cm5XF0xnjWpfEtg9qo2XpHOq+dafuoeEvuzFqxWnce87XnoiIKMWC9EmTJqFXr17ImjUrTpw4gUqVKiFTpky4fv06mjY1ZKeIyLaru2sRpX4Piy4KpYmu8m5NimQsgqkNpmJek3kom6UswqLCMPfsXDRd0RS/n/odLyNemruJlFLy1wX67YSu/TxEeueD3aunwNYvgF/LAEdmAZHGy02U0vx83PDbu2WxYVgN1CuSBVE6vZqyrc74Xfh6/Xk8CQ4zdxOJiIisP0ifOnUqZsyYgd9++w1arRaffPIJtm7dimHDhqmJ2YnItkXqZJ706Oru0FtdJj2+8lnL448mf2BK/SkolKEQXkS8wOSTk1Ww/se5PxAaGWruJlJKkAtKxVrhccd10LWaCnjlBoIfABs+BCZXAE4uAnSGi0+U8mQ8+pyeFbF8YFVUypsR4ZE6NW691o87MeHvSwgKNZxTiIiIKAlBur+/P6pVq6Z+d3FxwYsXL9Tv3bt3x6JFi1K+hURkUcJlnnRj4bjoIN3BLlE1KC2WTBNVy7eW6gIvXeHzeObBs7BnGH90PJqvbI4lF5cgIopBhE2wdwBKv2uYY73ZeMA9K/D8FrB6IDCtGnB+DaA3HNeU8ir4ZcSS/lXwZ+9KKJnTCy/DozBpx1UVrE/bdQ0h4YZzCxERUXpmcpCeLVs2PH36VP2eO3duHDx4UP1+48YN6PnFhihdzJOujQ7SX2mAec0y41LPdwBHR1g7mWNdisqtbrUaY6uNRXa37Ah4FYBxh8ah5eqWWH11NSJ1DCJsZo71Sv2AYSeBBmMAZ2/g0UVgaQ9gRm3g8hYG66l5UaxQZqwdUh3Tu5VDgSzueB4SgR82X1TBumTYQyPYq4GIiNIvk4P0evXqYe3atep3GZs+cuRINGzYEJ06dUKbNm1So41EZGFj0h3tjFOw6fHKyR4aN09Dd2Ib4WDvgDYF22B9m/X4rPJn8HHxwd3gu/hi3xdos6YNNt/YDJ3esuaFpyTSugI1RgAjTgO1PgG07sD9U8DCjsDshsC1HQzWUzFYb1IiO7aMqIWfO5RG7oyueBwcrsaq1/5pJ+YfvKW6xRMREaU3dnoT0986nU4tDg6G7q2LFy/G/v37UbBgQQwYMECNU7dkQUFB8PLyUuPnPT09YcnkdQ4ICECWLFlgb8/Z8sgytJm6D33uj0ELzSF0KFIOF8Me49ty36J58eY2e5y+inylurzPPjsbz8Oeq/sKeBfA4DKDUS93PZWBJ8uXqHPqyyfAvonA4ZlAZHQF8jzVgbr/B/hVT9P2pseZI1Ycu4NJ26/gXqChFkRObxcMq18Abcv5wlGTfj5n/P+frAWPVbIWOgs4Vk2JQ00O0q0dg3Si5Gn5214MDfgSjTTH0LpAaeQ45o8+hXqjbJ9RsLfwi3TJFRwejPkX5mP+ufmqwJyxSvz7pd9HnVx1VGaQbOSc+uIhsPcX4OgcICq6ArnMuV73cyBXxTRpb3oVFhmFJUduY/KOqwh4YXjt82RyxYgGBfFO6ZzQ2Nv+54z//5O14LFK1kJnAceqKXGoyS0sUKAA/ve//+Hy5cvJaSMRWfM86dFj0iN0kShxIwQZz12Tsx9snbvWHYNKD8KmdpswoNQAuDm64eLTixi2cxg6b+iM3Xd2szaHrfDICjT9Hhh2AqjQB7B3BK7vAmY3ABZ0AO4eN3cLbZaTgwY9qvph9yd18XnzosjopsWtJyEYueQUGv7yD9acvKumciMiIrJVJgfpgwcPxoYNG1C0aFFUrFgRv/76Kx48eJA6rSMiiwzSY6q76yNtorq7qbycvDCk7BBsbrsZfUr0gYuDC84/OY/B2wej28Zu2H93P4N1W+GVE2gxARh6DCjbHZDpBq/8DcysCyzsxGA9FTk7atC3Zj7s+aQuPm5cGF4ujrj+6CWGLz6JxhN3Y+2pewzWiYjIJpkcpEuhuCNHjuDChQto1qwZpkyZgly5cqFRo0b4888/U6eVRGQxInV6aO0M05GFRwfp1jxPenJ4O3tjRPkR2NR2E3oW7wlnjTNOPz6NAdsGoMemHth/j8G6zciQB2g1GRhyBCjdBZA6BJc3RwfrnYF7J8zdQpvl5uSAwXULYO+ndfFhw0LwdHbA1YBgDFt0Ak0m7sb60/egY7BOREQ2JMkd8gsVKoQxY8aobu979uzBo0ePVLV3IkoH1d2NmXRd+g7SjTK5ZMKHFT5U3eC7Fe0Grb0WJx+dxICtA9B9U3dm1m1JpvxAm2nAkKOG+dZVsL4JmFEHWPQucO+kuVtoszycHTG0fkHsHVUPH0QH61cCgjFk4Qk0/XUPNp65z2CdiIhsQrJGzR8+fBgjRoxQU69JsN6hQ4eUaxkRWWx3dydEQmYxjtQb5jLW2KfvIN1Ipmr7tNKnMcG6k8YJpx6dUpn1bpu6Yd/dfQzWbSpYnw4MPgKU6mwI1i9tNMyxvqiLYRo3ShWezo4YVr8g9nxaTxWT83B2wKWHL/D+guMqWJfMOrvBExFRugrSJRj/6quvVCa9evXqqtv7Dz/8gIcPH6rp2IgofYxJD4tVyTy9Z9Ljy+KaxRCst/03WD/96DQGbhuoxqzvvbuXwbqt8CkAtP0dGHwYKNUpOljfAPxey9AN/u4xc7fQZskY9RENCmHvp/UwvH5BeDgZgnXJrMuYdRaYIyKidBOkFylSBJs3b1YF5O7cuYMtW7agR48ecHd3T50WEpHFdXfXIoJBeiJkds2sgvXN7TajR7EeMWPWB20bhK4bu+Kf2/8wWLcVPgWBtjMMwXrJjv92g59ZD/irHXD7sLlbaNPB+siGhmBdMuvGMetSYK7hhH+w8vgdREbZ/uwTRERkO0yeJ/3KlSsoWLAgrBXnSSdKniJfbMJO+/dh5xCIhrlywDvUDsvrLkfmAgVgr2Gw/jaPXz3GvLPzsOTSEoRGhar7imYsiv6l+qNe7nqwl8CObOOc+uQasOdn4NRiIHpYiJpnvdYngF/11H3udC4oNAJ/7r+JWXtv4HmIocilXyZXVXyuddmccNRY/ueM//+TteCxStZCZ+vzpFtzgE5EKZxJt7NDpKc79F5e6nf67zHrH1X8SGXWe5XopaZuu/D0AkbuGol2a9th041NiNJFB3Rk/WPWW081TN1Wrgdg72CYZ31eM2Buc+D6PwB7UaTamPUh9QqqzPonTQojg6sjbj4JwcfLT6Pez7uw8JA/wiL5OSMiIsvFS15ElGjS8UamYJMx6aHRQblWozV3s6yyGvwH5T/A3+3+Vll0d0d3XH1+FZ/s/gSt17TGmqtrEBldOZ+sXMa8wDu/AcNOABV6A/aOwK29wJ/vALMbAZe3MFhPJe5ODni/jkzdVg+jmxZBJjctbj99hc9WnUHtH3dh7r4beBXOYJ2IiCwPg3QiSrSIKEMwIdXdw+ztYK/To9rZYGh37QKi+GU3KfOsDy07FFvab8HgMoPh5eSFm0E38fm+z9FiVQssv7wc4VHh5m4mpQTv3ECLX4Dhp4BK/QGNE3DnMLCwo6HI3LnV0hfP3K202XnWB9TOjz2f1sUXLYohq6cTHgSFYsy686j54w5M/+cagsN4UYyIiCwHg3QiSrRIFUQYMunS3V2C9FKXg6E9epRBejJ4aj0xsPRAbGm3BSPKjUBG54y4G3wXYw6MQdOVTTH//HyERISYu5mUErxyAs1+AkacBqoNBRzdgAengWXvAVOrGMawRzFgTA2uWgf0qZEX/3xcF+Nal4BvBhc8Dg7H95suovr3OzBx22UERo9hJyIissogPTw8HJcuXUJkJL9MEKWnTLoDomBvp4+p7s450lOOm6Mb+pTso6Zu+6TiJ2oqt4CQAPx45Ec0WdEEM07PQFB4kLmbSSnBIxvQaBww8ixQ+1PA2Qt4fAlYNQCYXB44OheIDDN3K22Ss6MG3arkwc6P6mB8h9LI5+OGwFcRmLjtCqr/sEMF7Y9e8LUnIiIrCtJDQkLQp08fuLq6onjx4vD391f3Dx06FN9//31qtJGILIRMY6SF4cKcMUh3kIJYlKJcHV3RvVh3Fax/VfUr+Lr74lnYM/x24jc0Xt4Yvx7/FU9ePTF3MykluGYE6n4GjDgL1P8KcPUBnt0E1o8Afi0N7J8MhAWbu5U2Saq8ty/vi60f1MZv75ZFkWweqtu7dH+XYP2L1Wdx+yl7sBARkRUE6aNHj8apU6ewa9cuODs7x9zfoEEDLFmyJKXbR0QWxFg0TsRk0jlHeqqRonztC7XHujbr8H3N71HAuwCCI4Ix68wslVn//vD3uB9839zNpJTg7AnU/AAYcQZo8j3gkQN4cR/4+/+AiSWAnd8BIU/N3UqbpLG3Q8vSObBxWE3M7FEBZXJ5IzxSh/kHb6HO+F34YMlJXH74wtzNJCKidMTkIH316tWYPHkyatSoAbtYUy5JVv3atWsp3T4isiDyxVWmXxNh0XN6M5Oe+uQ1bp6vOVa8swK/1v0VJTKVUPOsL7iwAM1WNsP/7f0/XHvO869N0LoCVQYBw08CLScBGfMDr54B/3wP/FIC2PwZEHjX3K20Sfb2dmhYLCtWvV8NC/tVRs2CPojS6bHyxF00+mU3+v15FCf8n5m7mURElA6YHKQ/evRITQIf38uXL+ME7URkm5l0Y3f3UAdH9ZOZ9LRjb2ePernrYWHzhZjRcAYqZ6+MSH0k1l5bq6ZuG7ZjGE49OmXuZlJKcHACyr8HDDkCdJgHZCsFRLwEDk4xdINfMwR4fNXcrbRJ8l2mWn4fzO9TGWuHVEfTEtkgX2+2nn+INlP3o8vMg9h9+ZGakpKIiMgigvQKFSpgw4YNMbeNgfmsWbNQtWrVlG0dEVnemHQ7Q5AeHp1BZyY97cl5t2qOqpjVaBYWNV+EBrkbwA522Hl7J7pt7IZem3th7929DCJsgRRmLN4GGLAb6LYCyFMD0EUAJ+YDkysAS7oDd4+Zu5U2q5SvN6Z1K4+tI2ur8esO9nbYf+0Jesw5jBa/7cXaU/fUeZGIiCglmfzt+ttvv0XTpk1x/vx5Vdn9119/Vb/v378f//zzT4o2jogsr7q7cUx6qEaDSI0dTrSrilJ+78HV0ZBZp7RVwqcEfqn7C64HXse8s/Ow7vo6HH14VC2FMxRG7xK90civES+mWDu5IF6ggWG5fRjYMwG4vAm4sNaw+NUEqo8ACtQ3rEspqkAWd1UJfmTDQpi15zoWH76Nc/eCMGzRCYzP6Ip+NfOiQ4VcqnI8ERFRmmfSZSz6yZMnVYBesmRJ/P3336r7+4EDB1C+fPlkN4iILHue9Jgx6RL02dkhwicDdD4+DAzMLJ9XPoytPlZVhO9RrAdcHFxw6dklfLrnU7RY1UKNX+dc6zYiVyWgy2Jg0AGgdBdAPos39wAL2gHTawCnlwJRnO87NeT0dsFXLYtj/6h6GNmgEDK4OsL/aQi+WHNOzbX+2/YreB4Sbu5mEhGRlbPTp7P+kEFBQfDy8kJgYCA8PT1hyXQ6HQICAtRFEHv7JE9pT5Rijt16im+m/4GVTv/DT9lz409noGfxnujq25XHqYUJDAvEoouL1PI01FAV3MvJC50Ld8a7Rd5FJpdMSG9s9pwaeAc4MBU4Ns8wbl145QaqDgbKdQe0buZuoc16FR6FpUdvY+ae67jz7JW6z1WrQeeKudG7hh98M7gmabs2e6ySzeGxStZCZwHHqilxqMkt1Gg0agfje/LkifobEdl2d3fjmPQwew3sdXrkO+EP7f79QFSUuZtHsUhAPrD0QGxptwVfVPkCuTxyqcD999O/o/GKxvj6wNfwD/I3dzMpJXj5Ak2+BUaeBep9bphrPdAf2Pwp8EtxYMc4IPj1/7cp+Vy0GrxXzQ+7PqqDXzuXUXOth4RHYc6+G6j90y4MX3wCZ+8GmruZRERkZUwO0t+UeA8LC4NWq02JNhGRhYqMPSbd3l4F6bmPX2eQbsGcHZzRsXBHrGu9Dj/X/llN3xYWFYall5eqbvAf7PqAFeFthWtGoNbHhmC9+QQgQ17D9G27fzJM37Z2KPDosrlbaZMcNPZoVSYnNg2viXm9KqJ6gUxq+rY1J++pAnNdZx3EP6wIT0REiZToSkKTJk2KqSosldzd3d1j/hYVFYXdu3ejSJEiid0cEVmhiNhj0mUMuh5wsGNBMmugsdeoAnIN8zRUReXmnp2LPXf3YOutrWopk7mMGrpQJ1cdtS5ZMUcXoGIfoHxP4OJ6YN8k4O5R4PifhqVQU6DaUCBPNdaSSGHyHalO4SxqkQy6dINff/o+9l19ohbJtPermQ8tS+eA1oFdg4mIKGGJ/nb9yy+/qJ9yFXj69OlxurZLBt3Pz0/dT0S2KyJSB0cYMuZhMp4nilOwWWMQUTFbRbVceXYFf5z7AxtubMDJRycxYtcI1S2+e7HuaJW/FVwdkzaeliyEXGwp1goo+g5w+xCw/zfg4gZDVXhZcpQDqg8DirQENPwcp7QSOb3wa+ey+LhxYczddxOLD/vj4oMX+HDZKfy05ZLqJt+lUm54uXJmDCIiSmbhuLp162LlypXIkCEDrBELxxEl3cYz97F50W+YpJ2CAXkL4XBkCBadLAlfJ1+4jhsHe2dnczeRkiAgJEAVmFt6aSmCwoNixrR3LNQRXYp2gY+LD2wBz6kAHl8FDkwGTi0CIkMN93nnBioPBMp2B5wt+/9FaxYYEoEFh29h3r6bCHgRFlNkrmOFXOhV3Q95Mv1b4I/HKlkLHqtkLXS2Xjhu586dVhugE1HyRETpYgrHhcLQTZaZdOuXxTULhpcbjq3tt2J0pdHwdfdVReZmnpmJRssb4Yt9X+DyM45ltgk+BYCWE4ERZ4HaowDXTMBzf2DLZ8CEYsCW/zPcphQnGfP36xTAnk/rqjnXjUXm5u2/iTrjd2HA/KM4evMpx60TEVHiu7vHdufOHaxduxb+/v4ID487H+iECRNSqm1EZIGF47TRhePCo4eycvyy7ZDu7ZI571S4E3be3ol55+aponKrr65WS+XsldUc7DVy1oC9HTMmVs09M1B3NFBjBHB6CXBgCvD4siHLfnAaUOwdoOoQwLeCuVtqc5wcNGhf3hftyuVU49Rn7b2OXZceYcu5h2opncsbfav7oWwWfsaIiNIrk4P07du345133kG+fPlw8eJFlChRAjdv3lRXfsuVK5c6rSQiixCpkzHpxky6IdvDwnG2Ry68NMjTQC0nA05i/vn52Oa/DYfuH1KLn6efGrfeMn9LuDi4mLu5lNwic1JgrmwP4Np2Q5B+fRdwbpVhyVUZqPI+UKQFx62nQn2IGgV91HLl4QvM3nsDK0/cxanbzzF08Ulk89CiZ/WXeLdSHo5bJyJKZ0wek16pUiU0bdoUY8aMgYeHB06dOqX69nft2hVNmjTBoEGDYMk4Jp0o6eYfvAX/dd/j/xwXolm+grgTFYq/yvyEbMgGn5IlYe/AL/G26l7wPSy8sBArrqxAcERwzLj1DoU6oHPhzsjqlhWWjufURHpwFjg4FTi9FNAZZnOAVy6gUj+gXA/AhUPeUsvj4DD8dfAW5h+4hScvw2PGrUvmvWc1P+TL/O/MOkSWgOdVshY6CzhWTYlDTQ7SJTA/efIk8ufPr8am7927F8WLF1fBeqtWrVRW3ZIxSCdKurn7buDRxm/xieNS1M9XAAH6cCxuthiZojLxOE0nXka8VF3fJbt+N/huTG+Khn4N0a1oN5TKXAqWiudUE714AByZBRydA4Q8MdwnFf/LdDEUmvMpaO4W2qxXYRH4a+8lLD/zFJcevIi5v16RLOhdPa+ah10y8UTmxvMqWQudrReOc3NzixmHnj17dly7di3mb48fP05Ke4nIisakO0UXjguL7u6u1WjN3CpKS26ObuhatCs2tNmAiXUmolyWcojUR2LTjU3ourErum7oio3XNyLCmIEl6+WRDaj3OTDyHPDOb0CW4kBEiCFwn1wB+Ks9cHW7zM1q7pbaHCdHDVoW98HGodWxsG9lNCiaRU1pv+NiALrNPoTGE3dj0WF/vAo3TIlJRES2xeS+qVWqVFHZ86JFi6JZs2b48MMPcebMGTUtm/yNiGxXRKwx6WH6KNjr9PA4chqOYY5A06YAr6Knq3Hr9fPUV8u5J+dUV3gJ1E8/Po3Te07j56M/o2PhjuhQuAMyOmc0d3MpuePWpZu7TNF2YzdwaDpwaRNwdath8SkMVO4PlOoMOLE7dkqSbHm1Aj5qufn4paoEv+zobVx+GIzRK8/gh80X0blibnSvmgc5vVkfgojIVpjc3f369esIDg5GqVKl8PLlSxWk79+/HwULFlSV3fPkyQNLxu7uREk3afsVuO78An0cNqF03tzQROqw91oz6MP1nCed8PjVYyy7vEzNty6/C629Fs3yNVPZ9yIZi5i1fTynpqAn14DDM4ET84FwQ40COHkBZbsBlfoCGfOZu4VW7W3HalBoBJYeua0C9jvPXqn77O2AxsWzqXHrlfJmZFd4SjM8r5K10Nn6mHRrxyCdKOl+/vsSfHb/H9512IryeXPDIVKHAzdaIjI0kkE6xYiIisDmm5ux4MIClWU3kq7x7xZ9F/Vz14ejfdpXq+Y5NRWEBgInFgCHZwDPbkTfaQcUagxUHgDkqyvpYDM30vok5liN0umx/cJD/HHgpprKzUjmX+9V3Q+tyuSEsyOnyKTUxfMqWQudrY9Jl6nXnjz59z8Do+fPn6u/EZHtioieJz1U0jbROAUbxeeocVTTsy1qvgjzm85HE78m6jg5HnAcH//zMZosb4Lpp6bHZNvJijl7AVXfB4YeB7osA/LXB6RexeXNwPw2wJRKhox7WHS2nVKMxt4OjYpnw4K+VbBlRC10qZwbzo72uPjgBT5dcQZVvtuO7zddxJ1nIeZuKhERmcjkIF2qt0dFvV6oJCwsDHfvGir9EpFtiozSQWsXifDozJgd7GBvxyvnlDDpclsmSxn8VPsnbG63GQNKDVDj0wNeBWDKySlouLwhRu0ZhdOPTpu7qZRckpUo1AjovhIYchSo1B/QugOPLwMbPwImFAU2fgI8vmLultqkwtk88G2bkjg4uj4+a1ZEjU9/HhKB6f9cQ60fd6Lfn0ex58ojpLPOk0REVivRKbC1a9fG/L5lyxaVqjeSoH379u3w8/NL+RYSkcWI1EkmPQKh0UG6k8aJYx8pUWQe9SFlh6B/qf74+9bfWHRxkQrON1zfoJYSmUqgc5HOaOzXGM4OHDZh1WRqtmY/AfW+AE4uNHSFfypj2H83LPnqABX7AYWaABr2xElJ3q5a9K+VH31q5MO2Cw/VfOt7rz7G1vMP1ZIvsxu6V8mDduV94emc9kNOiIgocRI9Jt3Yd1++kMd/iKOjowrQf/75Z7Ro0QKWjGPSiZLu/1adQc3jI1HQ+QRa++ZAJo0Hdl5pqIpIckw6merc43NYeNFQFd44ZZuXkxfaFmirqsLn8siVos/Hc6qZ6HTA9R3A4VmGbvDR0zfCKxdQoRdQ7j3AzcfcrbQoKXmsXg14oYL1FcfvIjjMMDuHq1aDtuVyokdVPxTK6pFCrab0iOdVshY6Wy8clzdvXhw5cgQ+Ptb5HyqDdKKk+2T5KTQ5NQzZXM6hU87syKH1weaLtRikU7I8DX2KlVdWqqrw91/ejxlKUSNnDZVdr56jupryLbl4TrUAz24CR+cAx+cDr54a7tNogeJtgYp9Ad8KLDSXSseqBOirjt/BHwdu4WrAvzUCpBq8ZNelOrzWgZ8LMg3Pq2QtdBZwrLK6+1swSCdKug+WnESbs4Ph7noZPXJkQ243X6wrN0UVk8xUtizsHdh1lZIuSheF3Xd2Y8mlJdh3b1/M/Tndc6JT4U5oXaA1MjhnSPL2eU61IBGvgHOrDF3h75349/5sJYEKfYCSHdL1nOupeazK174D15/gz/23sPXCQ1UlXvi4O6FzxVx4t3JuzrlOicbzKlkLna1Wdz9w4ADWr18f574///xTZdZlZ/v376+KxxGR7YqQMel2kTFj0rWOzoCfH6Jy5TIUjiJKBsmW181dF9MbTsf6NuvRo1gPeGg9cDf4LiYcm4AGyxpg9J7ROBlwkgWwrJ2jC1CmC9B/F9B3B1D6XUDjBDw4A6wfEV1o7mMg4IK5W2pzZNhitfw+mN69PPZ+WhfD6hdEZg8nPA4Ow+SdV1Hzhx2q0Nw/lx9BFx3AExFR2kr0t+qxY8fi3Ll/57s9c+YM+vTpgwYNGmDUqFFYt24dvvvuu9RqJxFZSnV3/Fvd3VnD7u2UOvJ45sHHFT/G9g7bMbbaWBTNWBThunCsv74e3Td1R7t17bD44mIEh3NqL6vnWx5oMx348CLQaByQMR8QFmTIsk+tAsxtBpxZDkSGm7ulNie7lws+aFgI+0fVw9Su5VA1XyZIXC5F5t6bcxh1f96FGbuv4elLvvZERGkp0d3ds2fPrgLxChUqqNv/93//h3/++Qd79+5Vt5ctW4avvvoK58+fhyVjd3eipOv7x1GMvNYbd9wD8FHWzCifqQzm+AzGs2fPkKFBA9g7slowpQ75r+rck3OqK/zmG5sRGhWq7ndxcEHzfM3RsVBHFM1U9K3b4DnVigrN3dgFHJkNXNoE6KOnfXXLDJTpCpTvCWTMC1tmzmNVxqsvOHQLy4/dwYtQQ6E5rcYeTUtmQ5dKudUYds7qQUY8r5K10FnAsWpKHJroAaTyJTxr1qwxtyVAb9q0acztihUr4vbt20ltMxFZgYgoHRwRibDok5urvRPsNm2C08uXQN26MtWDuZtINkqCghI+JdTyUYWPsO7aOiy9vBQ3Am9g+eXlainlUwrtC7VX07i5Orqau8mUVHJ+yV/PsATeBY7/CRz/A3hxH9g30bDkqwtU6A0UbgpoeN5JSQWyuOOrlsXxcePCWHfqHhYc8sfpO4FYc/KeWuTvEqy3K+cLL1e+9kREqSHRlxEkQL9x44b6PTw8HMePH0eVKlVi/v7ixQs1FRsR2a5InaG7e1h0EkXmSSdKazJNW7di3bCm1RrMaTwHTfyawMHeAacfn8aX+79E/WX1Me7gOFx6esncTaXk8soJ1B0NjDgDdPoLyF9f1f7H9Z3A0u7AL8WB7V8Dz/3N3VKb46p1QKeKubF2SA2sG1ID71bKpaZuk0z72PXnUenbbfhw6Skcu/WMNSKIiMwVpDdr1kyNPd+zZw9Gjx4NV1dX1KxZM+bvp0+fRv78+ZPUiClTpqh51p2dnVG5cmUcPnw4UY9bvHixyq60bt06Sc9LRKaJiNLD0U6CdMOpg0E6mZOc/ytmq4ifav+Ere23Yni54fB190VwRLDqFt9+XXt03dAVq66sQkhEiLmbS8kh2fKiLYHuK4HhJ4EaHwBuWYDgh8Ce8cDEUsBf7YEL64GoCHO31uaU9PXCd21L4dBn9fF16xIoks0DYZE6rDh+B+2m7UfTX/dg3r4bCAzha09ElKZB+tdffw0HBwfUrl0bM2fOVItWq435+5w5c9CoUSOTG7BkyRJ88MEHajy7ZOdLly6Nxo0bqzEDb3Pz5k189NFHcS4UEFFaFI6LiKnuziCdLIWPiw/6luyLDW03YEbDGWiYpyEc7OJm17899C2uBV0zd1MpuTL4AQ2+AkaeAzrMA/LWlqoFwNWtwJKuhuz6tjHAU0PvP0o5Hs6Oak71TcNrYuX71dC+vC+cHOxx8cEL/G+dIbsuU3UevvGU2XUiomQweZ50Geju7u4OjUYT5/6nT5+q+2MH7okhmXMZzz558uSYQf25cuXC0KFDVeY+IVFRUahVqxZ69+6tMvvPnz/H6tWrE/V8LBxHlHTvTN6L+Y86YEEGR0zL4IV387XDqE3heHHLH27TpsLBwj9TlL48fvUYa66uUePV7wTfibm/eKbiaFeoHZr6NYW7Nv3OxW1TnlwzjFs/uRB4+ejf+yWAL/8eUKQF4GA9FxWt6f//wFcRWHPyLhYe8lfBulH+zG54t1JutC3ni4xupn03JOthTccqpW86CzhWTYlDTQ7SU5KMbZdu88uXL4/TZf29995TgfeaNWsSfJxk3aV7/apVq9CzZ8+3Bukyd3vs+dvlxZGLAFIIzxqC9EePHiFz5sw88ZFFaDZpL1Y9a4dpGV0x19sTPQp0xoBRmxF24QKe5s0Hr9at4NW+PZwKFjR3U4li6PQ6HHlwBMsuL8PO2zsRqY+MmUJQxrO3LdhWFZ1jxWobEBWuKsLbSbG56zthJxl2ybO7ZgJKdYa+XA/ApxAsnTX+/y9fJ6XA3OIjt7Hu9H2EhBuq8ms1dmhULBs6VvRFtXyZYG/Pz5ktscZjldInnQUcqxKHZsiQIWWru6eGx48fq6x47KrxQm5fvHgxwcfIlG+zZ8/GyZMnE/UcMnf7mDFjXrtf3qTQUMMUPpZ8MMmbKP/x8cRHliA0PMJQ3T06mIkKi0LEs+fqd11QEJ7N/0stmqJF4dS8ObT16sLOlVW2yfzyavLio8IfoVOmTjgUfAib723G7Ze3sfraarXkccuDpr5N0SBHA3hpvczdXEoOn6pAo6rQBN2By8XlcLm4ApqQAODgFNgdnILwbOXwqkh7hOZvAr2jGyyRtf7/n90JGFkjK/pX8sHWS0+x5uxjXHgYgvVn7qslu6cWLYv7oHmxTMjqwey6LbDWY5XSH50FHKtSaD2xzBqkJ2XHunfvrsbD+/j4JOoxUuROxrzHz6TLVRRryKRLZodXJ8lS2OEsHOx0MUG6t7cPQnLmRHhICLzfew+R9+4heNcuRF24gJALF/BqyhR4NmsGr3Zt4Vy6NDOVZBHn1PLFymOw3WCcfHQSK6+sxN+3/satl7cw/dJ0zL4yG3Vz1UXrAq1RJVsVaOzjDu0iK5IlC1CgHNBsLHRXtsLuxJ/Alb+hfXBcLZ77vwWKt4W+bDcgZwWpRAhLYQv///f3zY7+9YFz9wKx5MgdrDl1D/eDwjHjwD3MOngPNQtmRscKvqhfJAu0Dta5j2QbxyqlDzoLOFalSLpVBOkSaMvY9ocPH8a5X25ny5bttfWvXbumCsa1bNkyzgsupKjdpUuXXqsw7+TkpJb45M2xhpOJHEzW0lZKB6KrJodFd1d0cXJDuEaDcK0WWevVhXuVKoh8/BiBa9bg+fIVCL9xA4ErVqhFmz8/vNu2hVerd+CQyItsRKl5Ti2frbxaRlUehU03NmHFlRU4/+S8CtplyeaWDa3yt1IBu6+Hr7mbTkllrwWKNjcsQfeBUwuBE3/B7ul14MSfhuA9cxGgbHegdGfAzTLOT7by/39J3wxq+bxFMWw++wCLj/jj4PWn+OfyI7VkctOiTdmc6FQxFwpm9TB3cykdH6tk++zMfKya8rxmHZNuLBxXqVIl/PbbbzFBd+7cuTFkyJDXCsdJ9/SrV6/Gue/zzz9XGfZff/0VhQoV+s/CdSwcR5R09b9Zg+0RPfBBFh9sdXPFZ5U/Q4UBvyPy4UPkWbYUriVLxqwrp5ZXx4/j+bLlCNq8GXrj8BKNBu516sC7bRu416oFO0dH8+0QpSuJOadeeHIBq66uwobrGxAUHhRzf+VsldG6YGs0yN0Azg6JvxJOFkq++tzaBxyfD5xfA0S+Mtxv7wgUbgKU6QYUaABozJPLsPX//28+fomlR29j+bE7CHjxb92g0rm8VXa9Zekc8HTm/w3WwNaPVbIdOgs4Vq2mcJxxCjYpFPf777+rYH3ixIlYunSpGpMuY9N79OiBnDlzqrHlCfmvwnHxMUgnSrr6Y5dju64P3s+aGXtcXTC28lco2/Yr6EJCkGPr33B+Q8G4qOBgBG3ciMAVK/Hq1KmY+zWZMsGrVSsVsDsVKJCGe0LpkSnn1LCoMOz036kC9gP3DkAfXYDMw9EDzfI1Uxn2Ej4lOITDFoQGAmeWAyfmA/dO/Hu/e1ZDZl0C9sxpW2wuvfz/L9N6SjZdis3tvBiASJ3hcybTujUtkQ0dKuRCVRabs2jp5Vgl66ezgGPVlDjU7GPSO3XqpIq4ffnll3jw4AHKlCmDzZs3xxST8/f354eeyELY6QwZjzA7w2fSWe8At0cBKitl/5ZxNhp3d2To2FEtYVev4vnKVapLfNSTJ3g6Z45anEuXgnebtvBs1hQaC7+ARrbPSeOEJnmbqOVe8D2subZGTed2N/gullxaopb8XvnRqkArtMjXApldM5u7yZRUzl5AxT6G5cFZwzRupxcDwQ+Bfb8aFt+KQJmuQIm2hvUpRTho7FG/aFa1PA4Ow+oTd1WG/fLDYKw+eU8tOb1d1HzssuTKyEKkRJQ+mD2TntaYSSdKukZfzMPfmuHoliM7Tjk5YlK5cShRt4/6W4ZLl+CQKVOit6WPiEDwnj14vmKlKjaHKMN0PXZaLTwa1IdXmzZwq1YNdhoW7iLLOKfKVG6HHxxWwfq2W9sQGmUYwqGx06B6zuoqu14nVx1oNaxabfUiw4ErW4ATC1SxOegN5yc4uABFWwJlugB5awGpVFgwPf//b5zKTYL1tafu4UWoYcpEUSVfRrQvn0tl2d2czJ5nonR+rJJ10VnAsWpV3d3TGoN0oqRr+n8zsMnxY7T3zYlLjhr8XvJrFGzUV9V9z3jbHxoXlyRtVxWbW7sOgatWIezKlZj7HbJkUYXmvFq3hlO8opBE5jynvgh/gb9v/q0y7CcC/u0i7an1RLO8zVSxuWKZirE7vC148RA4vQQ4uQB4FGt6WM+cQKlOhoDdJ+GhPknF//8NQiOisOXcAyw7egf7rj1WpQSEq1aDJiWyqex6lbzsDm9OPFbJWugs4FhlkP4WDNKJkkZOFc0/m4qNTp/hnVy+uOFgj3mFxiB3y/74//bOA0yus7rfv+llZ3vvu+q9y7Il25JtudtgAoY4oeYfUmmBEErAhoRO6KY6AUIxGAgY927Lli1bvfey2t777E6f/3O+O3eKdrWSVitN2d/r5zz3zr2zO1fS5zvzzjnf+WCxoPDUqQlL3s/3NTwHD2LgTw9j8NFHERwYiJ6zL1mC3LvejJxbb4U5P38K/kRkunGp7qkNAw145MQjKjpGYquVSDn8nTPvxO0zbled4kmaIx+XWnZqsr7/D9pcdh0ph196j1YO77j4+xPf/8fS0j+KP+1sxv/tbMGpbnf0uJTD/8WKSrx1RRXqilJz3ftMhmOVpAuhFBirlPQJoKQTMjn8wRDu/sz38LDtXtxcU41WkwEP1tyLsrv/EQanEwVHj160pMcT8vlUGbwI+/DLL0fL4eULgewN61V23XXNNao8npBUuKcGQ0G80f4GHj7+MF5ofEE1nxMMMODK8iuVsN9QcwOcFs6rTXv8HuDok8Du3wDHn4uVw5tswNxbtez6zOsB0+Q6lPP9/+zIx9adjX34w44WPCbl8N5YOfzK2nwl7HcsrkCuk93hLwccqyRdCKXAWKWkTwAlnZDJMeoL4t33fRu/t/0H1tfWoNcI/L7031H4zg/AkJOLgoMHplTSx5TDP/qYajbnPRwrNzXl5SHn9ttVht2+iJ22SercU4d9w2qtdcmu7+jYET3uNDtxY+2NeNPMN2FV2SoYI00YSZqXw+/7PbDnN0DH/thxZxGw+G1aSXzFclmg97x/Jd//z78c/pmDHWopt83HuhBpDg+ryYiNC0rwluVVWD+nGFYz/w4vFRyrJF0IpcBYpaRPACWdkMkx6PHjH//jG/i19cu4qq4Gwwbgz7mfQvbffgjGwiLk79l9ySQ9Hs+RIxj48yMYePQRBLu6o8et9fVqObfcO++ApbLykl8HST+SdU9tGmrCYycfw6MnHlX7OqXOUlUKf+eMOzErn0sQZgRtezVZF2l3d8WOF80Flr4DWPx2IK/6nL+G7/8XTsegB3/e3YL/29GCIx1D0eMFWVa8aWkF3rK8Ekuqcvll7hTDsUrShVAKjFVK+gRQ0gmZHL1uHz76xa/h59avY3ldDQIG4HHnv8H/b/fBPH8+qh/5M4zmy9dtNxwIwL3ldZVdH3ruOYQ9WqdtwblqFXLedCdybr4Zplwul0RS454qb7e7u3ar7vDSdG7IHxOJeQXz1FJu0nSOy7llAMEAcOIFbSm3w48DAf3+ZADqrtbWX5//JsCek5JjNZ2R/88Otg3iTztb1BJusrSbzsziLCXrb15WyeXcpgiOVZIuhFJgrFLSJ4CSTsjksxT3fuUr+IH1W1hWX6OOPWX6KAa/8DVY1q3FjAceSNo4DQ4PY+jpZzDwyCMY2bpVa/AkNziLBa4NG5Swu9avh5Hz16c1qXRPlfnqLze/rLLrr7S8gkBIm1cr5e8yf12EnfPXMwTPIHDoEWDPb4GGV2LHzXZgzi1aOfysjYDZmpJjNZ0JBEPYfLwbf9zZgmcOtsPjD0XPrarNx13LK3H74nLkZ/G9YbJwrJJ0IZQCY/VCPJSLTBJCzrtxnAUBeONKBU0en9oaHMkVCZPLhby3/oUKf1sbBh9/XJXEy3JuQ88+q8KYk4OcW25R5fCOlSth4IcJkkRsJpuamy7R7+nH0w1P49GTj2JP1x681vqaCofZodZdF2G/quIqWIxshJWWSLZ8+Tu16G8C9v0O2PMQ0H0EOPiwFtIRfuFbtHL46jXJvuKMwWwyYsPcEhVDHj+ePtCBh3e1qOXctp/uU/H5Rw9g/RyZv16JG+aXwG4xJfuyCSGEmfRUJhW+8SFEp6Hbje9+8z/wWftPcG1tlTr2XN//w/B3vgvLddeh6ic/vqzl7uc9f/2RRzD46GMIdHZGj5vLy5F7+23IueMO2ObO5RzFaUI63FObBrX56xKNQ43R4/m2fNxUd5MS9qXFSzlm0x356NW+F9j7O2DfH4Dh9ti53BqEF78N3RU3oHDe2pQdq+lM+4AHj+5pxcO7W3CgdTB63GUzq/XX37ysAmtnFsHE9dcz4r5KSKqMVZa7TwAlnZDJcbxzCA985/P4F/tPcWNNJcxGM546/TYYv/0tmBctQu5TT12WxnGTIRwMYmTbNpVdH3rmGYTcsTV2rbNmIveOO5Fzx+2wVmlfPpDMJJ3uqfLWvL97Px4/9TiePPUkej290XOVrko1d12azs3Mm5nU6yRTQCgInHpZazZ38BHAF+tVEC5dBIN0iF/0ViBPm2ZEppajHUMqu/7n3a1qLXadIpcNdywpV8K+rDqPX4xlwH2VTG9CKTBWKekTQEknZHIcahvEg/d/Fn/r+BXuqK6Ay+LCH/dfD/NPfgzz8uXIffTRlJX0eEIeD4Y3vYzBxx5T67CH/f7oOceyZSq7nnPLzTAXFSX1OsnUk673VJmv/kbbG3j85ON4vvF5jARGoufm5M/BrfW3qhB5J2mOfxQ48iTCex8Cjj8PQyh2f0LNVZqsS1l8Fu9PU00oFFbl79Ih/vF9begfif3d1xQ4laxLzCrJTup1phrpel8l049QCoxVSvoEUNIJmRx7m/vx5x/+O97ufAhvqypHgb0AD762HNZf/wqW1Vcg509/TAtJjyc4OKjmqw889hhGXn8j2nAORiOyrrxSrcGefeNGmFL8XkGmzz11NDCKTU2blLBvbt0cbTgnSBm8yPrNdTejyEGJS/ex2tV4FMXdW2Dc/39Aw2bJq2snDSZg5nXA4ruBubedtUM8mTy+gDSc61LZ9WcPdmDEF4yeW1Cegzctq1BZ9qp8NnbMhPsqmR6EUmCsUtIngJJOyOTYcboPz/3kk7jV9Uf8dUUZKrIq8N9P1cD+8J9gWbsWOb/7XdpJejz+jk4MPfUkBh59DJ79+6PHpUN81jXXIOf225B93XUwOvmhLF3JtHvqgHcAz55+VpXDb2vfhnBE4qRD/Oqy1aokXjrE59q4DGHaj9XBVmD/H7WS+LbdiR3iZ9+oZdhn3wxYeX+aakZ8ATx3qBOP7G7BS0e6EAjFPjavqMnDnUsrVIf4kpz0ff+7GDLtvkoyl1AKjFVK+gRQ0gmZHG+c7MGr//NvuCb7UfxNeSnqc+vxvYdccD77DKzr1yP7179Oa0mPx3f6NAaffFJ1ifceOx49bnA4lKiLsIu4c0m39CKT76mdI51q7XUR9r3de6PHpXfEuop1Krt+XfV1cFldSb1OMgVjtfs4sP8PmrD3xO5PsGQB824DFv4FMOsGwGy77Ned6fS5fXhyfzse29uKLSd7YsVXBuDKGYVK2G9ZWDatlnTL5PsqySxCKTBWKekTQEknZHK8erwbu37+USzLfhr/WFaCeQXz8NX/8SN782ZYN25E9s9/njGSHo/n6FEMPv4EBp94Av6mpuhxo8uF7BtuQPatt8C1di0MFPaUZ7rcU5uGmvDUqafwxKkncLw/JnFWoxXXVF2DW+pvwbWV13IN9nQfq6pD/D7gwB8BKYnvj60GAKmemH8nsOgtQP16wMTl+6aazkGPmrsuXeJ3NvZHj5uNBlw9uwh3LKnAjQtKkevI7L/76XJfJelPKAXGKiV9AijphEyOl4504sgvP4JZOS/gI6XFav7r577Vgdxdu2C79Va4HnggIyVdR26VUgY/+NjjGHzqKQQ6OqLnjLm5yN54A3JuvQ1Za65QJfIk9ZiO99TjfcfxVMNTah32hsGG6HFZg3191XrcUncLrq66Wq3bTtJ4rMpHuZYdmqwf+BMw1BY75yjQhF0aztVdA5hSa6nMTKCpdyQq7PFLullNRlw7pwi3LynHxvmlyLZn3nvDdLyvkvQklAJjlZI+AZR0QiaHNM9pfvCDKM19BZ8oKcKasjX4t/84DHNLC7LuuxfF73wnjNNETsOhEEZ37cLgE09i8JmnEezqjp4z5eUh+6abkHPrLXCuXg1Diq0dP52ZzvdUeas/0ndEZdhF2luGW6LnnGYnNlRvUOuwX11JYU/7sRoKAY1bNGE/+GdgJHZ/grMQmP+miLBfDRhNU37t050TXcN4fG+biiMdseX0rGYjNswpjgp7li0z3hum832VpBehFBirlPQJoKQTMjme3NeG3of+Gc6813FvcSGuqbwGH/r46wiPjiLnwV+jfNmyaTlO1Rrs23dg8MknMPT0Mwj29UXPmfLzkX3jjci++SZkrVlDYU8yvKdqyNv+gZ4DStifPv002t3t0XNZliyVYZc57Osq11HY032sBgPA6c1adl3WYB/tjZ3LKo4I+11A7ToK+yVag11kXeawn+hyR4/bRNjnFuO2xeW4YX4pXGks7LyvknQhlAJjlZI+AZR0QibHI3ta4f393yOQvxNfKirATdUb8bf/9JQ6l/vwn1A2Z860H6fhQAAjW7eqpnNDzz6HYH9/Yob9xo3IvvkWlsQnCd5TxxIKh7C3ay+eOf2MajzXMdKRIOwqw157E9ZWrIVdOomT9B2rIuwNL2vCfuhRYLQvUdjn3RER9qtZEn8pKlmiwt6GU93uhAz7esmwK2EvSbuSeN5XSboQSoGxSkmfAEo6IZPjjzubYfzT+zGQvw//VZiPt5TdjHs+9Bisfj+y/+d/UHTN1TAyUxwl7PfDvXUrhp56GkPPPZeYYc/Lg0vmsN98s5ZhZ9O5ywLvqZMXdimJlwz7xtqNqiSeTefSfKwG/cCpTZqwH348UdjVHPY7gAV3AfXXsuncFCMfuw+2DeLJfe14Yl8bTsYLe2QOu55hT4emc7yvknQhlAJjlZI+AZR0QibH77Y1wfXI36Cp8DDuz8/DOwtvxZs+9giK+nphf9e7kPXFL2Z047gpybCLsD/7bIKwG3NykH3dBmSLsK9bB6ON5cWXCt5TL1zYpeHcc43PJZTE20121SV+Y81GrK9erzLuJI3HqhL2l7X564cfA0Z6YufseVqGfcGbgBkbuKzbFCMfwQ+3D6npZNJ4Lr4k3mIyYN2sIty6qAw3LihDQYou68b7KkkXQikwVinpE0BJJ2Ry/Or10yh7/D04WHQSD+Tl4u9ybsPGT/4ZxcNDsN9zD5xf+AIl/XyFfds2DD7zjFYS3x1r6mR0OuHasB7ZN90M17XXqMdk6uA9dXLIx4T93fvx7OlnVZY9vumcLOu2tnKtEnYpjc+Vpb9I+o5VfQ67CLuUxLu7Yues2cCcmzVhn7URsPLLman+/+xox7DKrksc6xyOnjMZDVhTX6CE/eaFZSjJSZ33Wt5XSboQSoGxSkmfAEo6IZPj56+ewoyn3oU3ipvwi9wcfMRxO9Z+9mGUeL2wve2tlPRJNp1TXeJF2J95FoH2WLbSYLfDdc3VyN64Ea4NG2DKpfxcLLynXjzykeFQ7yE8d/o5JeynB09Hz5kNZqwuW61K4q+vuR5FjqKkXms6kxJjNRQETr8GHHpEE/b4Zd3MDmDWDcCCN2vibuf9aao53jmEp/a348n97QnLuhkMwMqafNwSEfbqguR+mZsSY5WQNBmrlPQJoKQTMjn++5WTWPTsX+G54nY8lJONTxlvx/IvPIzScAjWN72Jkj4Fy7p59u3ThP3pZ+Bvbo6dNJvV3HXVKf6G62EuLk7mpaYtvKdOLfLx4Vj/MZVhf77xeRzrOxY9Z4ABy0qW4YaaG5S0V7oqk3qt6UbKjVVZ1q1leyTD/gjQ3xg7Z7QAM9Zra7HPvQ1wlSTzSjOSxp4RPHWgTQn7rsZYQ1JhYUUObllYhpsXlWF2iQsGsfjpPFYJSeGxSkmfAEo6IZPjhy+dwBUvvAN/KunBn7Nd+HzgNsz/2p9RZjbDImuCU9KnDLktew8dUg3nZA6799jx2EmDAY7ly1WGXbrFW6urk3mpaQXvqZcWyaqLrD9/+nns7d6bcG5+wXyVXZeYnTf7sotEupHSY1U+Nrbv1ZZ0E2HvPhp30gDUXKnNY5fmc/l1SbzQzKRtYBRPRzLs2xp6EYr7FD+jKAs3ibAvLMXSqjwYjYbpPVYJSbGxSkmfAEo6IZPje88fw4ZNb8MvS4fwpCsLX3Xfhvrv/BnlTgfMN9xASb+EeE+d0oT9uefg2ZMoP7Z585B9ww3I3niD2qf8nB3eUy8f0mjuhcYXlLRv79iuGtHpVGdX4/rq63FD7Q1YUrQEJq7Pnd5jteuIVg4vTedadyWeK12sybpIe+lCrVabTBk9w148f6gTTx1ox+Zj3fAFY/+fleXYcdPCUty0oAxrZhTAYro04yitxiqZ1oRSYKxS0ieAkk7I5PjmM0dw2+a34gdlo3gxy4lv9d6Myh89horcHJiuvZaSfpnwt7dj6PnnVdM5aUCHYDB6zlJRoZZ2y75hI5wrV8DAJfES4D01OfR6erGpaZOS9tdaX4Mv5IueK7AX4Lrq61SGfU35GthM7B6e1mN1oFlb0k2kXeazh2P3J+TVarI+7zag+kquxT7FDHn8eOlIF54+0I4XD3fC7Yv93efYzbhuXokS9vVzi+GyTd3ffdqOVTLtCKXAWKWkTwAlnZDJ8dWnDuPu196Mr5YH8ZrTgR+03Yiinz2BwjVXwHTPPcjfuBFGS+qv6ZpJBPr6MLxpE4affx7Dr2xG2OOJnpNGc67rroPrhuvhWrsWxix2YuY9NfmM+EfwauurKsP+ctPLGPIPJazFvq5ynZL2a6uundad4jNirLp7gKNPAoceA06+CAQ8iWuxz7kFmHc7MPN6wMqVLKYSbyCIV49349mDHSq6h30Ja7GvnVWohH3jghKUZF/cl+sZMVbJtCCUAmOVkj4BlHRCJscXHz+I92y9E/9eYcROux0PnLoOub99Fnl/9Vcw/N37OU6TTGh0FO4tWzD03PMYfuEFBPtjzYUMViuyrroKruuvh+u6DbCUTM/GTrynphb+kB/b2repDPuLjS+ic7Qzes5kMGFF6Qol7BJV2VWYTmTcWPW5gRMvaFn2o08Bo32JneJnXqc1nZNO8Ww8N6UEQ2HsburDMwc6VJa9oWckek5mHyyrzsPG+aW4cUHppBrPZdxYJRlLKAXGKiV9AijphEyOzz1yAP+04zZ8uNKG/TYbfn7oGjgffhEF738/wn/9VxynKbYWuyztJsI+9MIL8Dc1JZy3L1mC7OuvU9Jumz19mnjxnpq6yEeRgz0H8ULTC3ix6cWETvHC7PzZ2FC1QQn7wqKFMBoy+98vo8eqrMXeuAU48oQ2jz2+U7w0nqtaDcy9VZP24rmcxz7F/58d7xzGMwc7VOxpSuwUX1PgjAr76rp8mM9jHntGj1WSUYRSYKxS0ieAkk7I5PjMw/vwsV234G+qXDhuteKXu66E7clXUPLudyF0000oXL4cRs6BTjnkFu87fhxDz7+ghN2zN7HxnKWqSpXFZ1+3Ac5Vq1TWPVPhPTV9aBpqwktNLylh39mxE8G4uc2y/rqUw4u0X1lxJRySic0wps1YlY+gHfuBw09o0t62O/F8fr0m6yLt0jXexClVU0n7gAfPH+7Acwc78OqJHvgCscZzuQ4LrptbjBvml6p57Dl2y/QeqyTtCaXAWKWkTwAlnZDJ8Yk/7MW9+zbi7uoCNFks+M2WFTC9+AZqF8xHaOZMNo5LE/ydnRh+8SVVEi/l8WFfbK6i0eVC1tVXK2HPuvZamPPzkUnwnpqeDHgH8HLzy0raZT672++OnpNGc9JwbkP1BqyvWo8SZ2aUSk/bsTrYqpXDH3kSOLkJCHpj5+y5wKwbtbnss24AnAXJvNKMw+0N4JVj3XjuUAdeONyJXnfsvcFsNOCK+gIl7DfMK0FdUazHybQdqyTtCKXAWKWkTwAlnZDJ8dHf7cZXDlyPW2tK0Wk246EXFsHw+i7ULVuKYHU1JT0NCY2MwP3aaxh68UUMv7QJwZ6e2EmjUVuP/boNKtNunTEj7cvieU9Nf/xBP7Z1bFPd4jc1b0LLcEvC+QWFC1SWXYRd9tO1LJ5jVbqfDWsN50TYjz4NjHTHzhlMWmZd5rCLtBfNYVn8FM9j39nYp5rOPX+oAye6Yl+MCTOLs6LCvrw6F7093dN7rJK0IJQC91VK+gRQ0gmZHB9+cAe+c/R6XF1TiQGTCb9/bDbCew+ifvUqBMrKKOlpTjgUgmffPk3YX3wJ3iNHxpbFr18P14YNcF6xGkZb+i2VxXtqBs6v7T+uMuwvNb+EfV37EEbsI02hvVAJu8RVFVchy5I+KxxwrJ5BKAg0b9ey7BKdBxPP59cBc24F5twE1K4DzOl3f0plGrrd0Qz71lO9CITCCWXxa2pcuHVpjVrmLc+ZuVOmSHoTSoH7KiV9AijphEyOD/1yC7574hasrq2Cx2jEH35fjdCxk5ixbi38BQWU9AzD39KCIVne7cWXMPLGGwll8QaHQ+sWv2G9EndLaSnSAd5TM5ue0R5sbtmsMuyyHnt8WbzZaMbq0tVRaa/JqUEqw7F6DvpOA8ee0bLsDa8Awdj9CfJljHSLn30TMPtGIKcimVeacQyM+vHKsS48f6gTLx7pRP+IP3rOaABW1OQrWb9+XgnmlWWnfQUWyRxCKXBfpaRPACWdkMnxwZ9vwncb3oSlddUIGwz4w/8WI9TSipkb1sOXnU1Jz/Sy+Ndf1+ayb9qEQGdsqSzBNn8+XOuvhevaa+FYsgSGFG0gyHvq9CqL39G5Q5XFy3z2xqH4DuJAbU4trqm8BtdUXYNVpatgNaVW9o9j9ULL4l/S1mQ/9iww3JF4vmwxMFvK4m8GKlcCRlOyrjQjy+K3N/Tg8Z2n8UazG0fahxLOV+TasUGEfW6JWpvdaU3N9wYyPQilwH2Vkj4BlHRCJscH/vtZfLP5bVhZr2Wg/vDDLIT6+jHrxhvhtdso6dMEecvwHj6M4ZdeUvPYR6VbfNzbiDE3F65165S0Z11zDcwFqdPciffU6UvDQIPKsL/S/Ap2dOxAIByInpPu8NJ8TqRdsuxlWWVINhyrkyQUAtr3AEefAY49DbTslLtW7LyjAJi1Ucuwz7wByCpM5tVmBPFjtW3QixcPd6p49UQ3PP5Yt3ir2Yg19QW4bm4JNswtRn1RFrPsZNrdVwcp6WeHkk7I5Pjgjx/HFzv+Gutqq9Xj3/2XAfD5MPv221T5OyV9ehLo7cXwyy/D/fIrGH71VYQGBmInDQbYFy+G65prlLTbFy6EwZS8LBbvqUQY9g3j9bbX8UrLK0rau0a7Es7PypulhP3qyquxvGQ5LElY9otjdYoY7gKOP6cJ+/EXAO9A4prsklkXYZeu8RXLVcNMMjVj1eMPYsuJHjWPXcrim/tGE36uttCJDXOKVab9qhmFsFtY4UAy/746SEk/O5R0QibHB77/J3yu929wXU0VzEHgwa8FVAZ19re/hQG/H/m33gqjhWvYTmfCgYDKrA9vehnDr7wM78FDCedNeXlqiTfXNVcja906mIuKLuv18Z5KzkQ+Ah3uPayEXcri93btTWg+5zQ7cWX5lbi66mol7pcry86xegkI+oGmN7SSeBF3WZ89HmeRtrSbCLvMac+6vPendOV8xqr8f3aiaxgvHelSwi7N5/zB2P9nNrMRV80sxPo5xSqYZSeZel+lpE8AJZ2QyfGh7z2Efxv4R9xaXYkirw0/+KbWlGnO3j3o6u3lOCVj8Hd0wr35FSXtstRbaHg44bxk1rOuufqyzWXnPZWci35Pv2o6J+uxSxO6Xk9vwvmZuTNVhn1d5TqsKF2h1mm/FHCsXqY12VWW/RngxEuAL34+tUHLrEtpvIRk3E2cTz1VY3XYG8Brx7vx4pEubDrSidYBT8L56gIHNswpUcIu8p5l4989yYz7KiV9AijphEyOD337l/iw+yO4q6oCM0Zc+Mp3+mGw2TBn106OU3JOwn4/RvfswbCUxW9+ZUyW3ZiTg6wrr0TW1evguvpqWCqmviMz76nkQgiFQzjUewibmzcrYd/bvVcd07Gb7FhVtkpJ+9qKtajLqZuy7B/HarKy7M9oZfEd+xLP23OBGddFpP0GdoyfwrEqGnK0YxibjnZi09EubDvVB18w9v+ZxWTA6roCJezXzilmx3iS1vdVSvoEUNIJmRwf/sb/4O+9n8A7KsuxbDAfn/5+F0z5+Zj1u4fQ3d2NosWLYUzRrt4k9Qh0dWF486twv/IK3K++imD8XHZpMjRjRlTYnatXw+hwXPRr8p5KLoYB7wC2tG1R0i7Z9jPnsle6KpWsr6tYpxrRuayuSb8Wx2qSGWwDTrygZdpl6+lPPF88X5N1KYuXddktF39/Slemeqy6vQG8frJHCbuUxzf2jiScL8624ZrZRUra180qQpHr0lSzkMwjlAL3VUr6BFDSCZkcH/naD/Ge4L14d0UZruktxgd/3AZLZSVmXr0ObrebjePIpAkHg/Ds26dJ++bNWsd46dIcwWC1wrlqJbLWXa3E3TZnzqQyKbynkqlCPjod6z+G11pew+bWzdjZsRP+UGy9aJPBhCXFS3BVxVVK3BcWLlRrtZ8vHKspRCiodYkXYZdo2ZHYMV6mPNSujUj79UDJAtU0c7pwqcdqQ7dbCbuENKIb9QcTzi+qzMG1s4txzexirKzNV13kCUnV+yolfQIo6YRMjo9+5bu4G1/A35WX4taOMrzvp81KluqXL6OkkylFsuruLa/D/epmJe6BtraE86aiImStvUot9ea86ipYSkrO6/fynkouFSP+EWzv2I5XW15V89lPD55OOJ9tzVYN6HRpl6z7RHCspjAjvdq67CeeB068CAy2JJ53lWmyLln2GRsA1/ndn9KVyzlWvYEgdjT0YdOxLrx8tBuH2gYTzjutJlw5oxBXzyrCtXOKMLPYxdJ4klL3VUr6BFDSCZkcH/vSf+FNpq/jA2UluLu5Cnf/sgGOZctQO3cOJZ1cMuQtynfqlMqwyxJvI1u3ITyauJSPfFmUtXat6hgvGfezlcbznkouFy3DLdjSukWVxctyb0MJTcmA2pxaTdrLr8Lq8tXIsSZ+HuFYTRPkI3TXEa0kXqS94VUgkHh/QumiiLBLafzajCuNT+ZY7RzyYPOxbrx8tAuvHOtGj9uXcL4sx46rZxep8ngR90KWxk9rQilwX6WkTwAlnZDJ8fEvfAkbrd/Fv5YW4z2nqnH7b08ha91aVFdVUdLJZSPk82F01241j13Cc/Cg9kE5gsFigWPFCmRddZXKtsevzc57KkkGwVAQB3oOKGEXcd/TtQfBcKxk12gwYlHhIlxZcaUS92XFy1S5PMdqGuL3AI1bgJMvaln29r2J56U0vubKmLSXLUn7tdlT5b4aCoVxqH1QSbsI+9aGXvgCsWlTwoLyHCXsMpddmtE5rFybfToRSoGxSkmfAEo6IZPjE//xeaxz/hj/XlyIfzpaiw3/dwLZN92Iyvx8SjpJGoG+Poxs2aKy7O7XtowpjVdd49esUcLuWHMl+hx2lJaW8p5KkoZk1be1b1MZdpH2hsGGhPMOswMrS1ZiYfZCbJy9EXMK5iiRJ2nIcBdwapMm7CfHKY135AP112pl8RL59Wk3nz1VP6t6/EFsa+hVwi5xZmm81WRUc9ivjkj74spcmIzp9XdP0m+sUtIngJJOyOT41Of+HSuyf4b/KCrEx/bXYs2jJ5D7lrtQbrVS0knqlMY3NMC9ZYtal33kja0IDSWWGRtLS+Fauxauq66E88orz3s+OyGXirbhNk3Y27bgjbY3xqzNXmAvwBVlV6gsu3SNr8quStq1kotAPm53H4tl2Rs2n7E2O4DcGmDGek3Y69cDrmKkOunyWbVryIvXTnTj1ePdKtt+5trsOXazWpNdhH3tzELOZ89AUmGsUtIngJJOyOT4zL2fwLy8X+Orhfn4zM5aLHn6BAr++q9QEghQ0klKEg4E4DlwICLtWzCycycQCCQ8xzpzprY+u0j76tUw5eYm7XoJkXXYj/VpXeNfaXwF+/r2wRNMlAlpOqcLu8h7oaMwaddLLoJgAGjdqTWhk2jaCsStEKCQTvEi65Jtr1unrdeeYqTjZ1VRn4aeEWw+3o1Xj3UreR/0JL43lObYsHZmUVTcK/Myq5fAdCSUAmOVkj4BlHRCJsd9n/0XVBf8Ad8pyMMXXq/BnBdPougf/h6FS5agv78feXfeCaPFkuzLJOSsBIaH0fbCC7AcPozR19+A59ChhPnsMjfUvmABsq5cA+eaK+FcuQJGpzOZl0ymKfr7f35hPvb17MMb7W+oLPu+rn0IhBNlYlbeLCXsq8tWY1XpKuTaUk/kyHngcwOnI/PZT24COvYlnpcpDxXLNWGXqL4SsCb//pQJn1WDoTD2twwoaRdh397QB+8Z89lrC51K2iXLLuLO9dnTj1AKjFVK+gRQ0gm5cOQ28R+f+SCKix/BD/Nz8fVN1ah97RRKPv6vyH/f+zhOSVpw5j1VzWffug0jb7yulnyTLvIJSBO6xYuj0u5YthRGGz+YkeS9/7v9buzo2KGEXeJI35GEnzPAgPmF87GmbA2uKL8CK0pWwGlJvsiRSeDuBhpeAU69rEl774nE8yYrULUaqLsGqL9G2zdf/vtTJn5WlfnsOxv71LrsUh6/p3lAiXw8c0pduGqGCHsRrpxRgDynNWnXS9JnrFLSJ4CSTsiFEwiG8PV7/wm2kifxs7wcfOeZCpTvaETZ5+5D7tvfznFK0oJz3VP97e1wv/66msvufuN1BFoTm9AZbDY4li9H1por4FyzBo5Fi2Cw8oMZSd77f5+nT63PLsK+tX0rTg0kftFkNpixsGihyrJLSOd4SnuaMtAMnBJp36RJ+1Br4nmzHaheowl73bVA5QrAdOmr26bDZ9Uhj181oXv1eA9eO9EzpgmdTF2fX5ajMuySaV9dX4AcOysLU41QCoxVSvoEUNIJmdy3yvd/7u/hL30OD+Zm44ePlKLwQAsqvvZVZF9xBbq7u1E0fz6MkaWuCEn3e6q8NfqbmxOkPdjVnfAcg90O54rlcF5xhQpKO0n2+3/nSKeS9a1tW5W4t7oTRc5sNGNx0eIEabeL3JH0Qj66957Usuwq2/4K4O5MfI4lS1vure5qLdteseySSPt0/Kza6/bhjZM92CJxogfHOocTzkuT+EWVubhyRqHKsq+qo7SnAqEUGKuU9AmgpBMyuW+Rf/aFv0Vv6cv4vxwX/vv3hcg53oGq73wbrtdeY+M4khZczD1VdY4/dSoq7SNbtyLY15fwHIPDAedyXdpXU9pJ0t//W4ZblLBLtl3kvd3dnnDeYrQoaV9VtkrNZ19avJSZ9nREPsp3HYmVx0vn+NHecaR9TZy0L58SaednVaBzyIPXT/YqYd9yols1pYuH0p4ahFJgrFLSJ4CSTsiF0+f24aEv/w1Ol7+Gx1xZ+N9f5sLR3IOaBx6A87lnKekkLZjKe6qS9uPH4d4qwr5tfGm32+FYtgzO1atU53jHUs5pJ8l7/5cx2zzcrNZoF2Hf1rYNnaOdZy2PF2lfXrKc0p6OhEJA50FN1kXcT782jrQ7tfJ46Rpfe7VWHj+JOe38rDqWtoFRvHGyF6+f7FExnrQvrMjFFfUFWFNfoLac037pCaXAWKWkTwAlnZALp3PQg8e+9h7sr9iOZ7Oc+NVPHLD2DKHuwQdh//PDlHSSFlzKe2o4FILvxAlN2iXTvn07gr2JH4olq+5YskRl2aPSzu7xJEnv//Lxr3GoEdvbt6tMu8SZmXaTwYQFhQuUsK8sXYllJcvYPT5dpb3rUEzaG14dK+0y7UGaz9WuBWrXafvn0T2en1UvXtplTvvc0myVaRdhl2D3+KknFcYqJX0CKOmEXDgt/aN44b/eidcr9+BlpwO/+Y4JphEvZjz8MKy/eZCSTtKCy3lPVZn2Eycwsm2bCve2bWPmtMNshmPhQjhWrYRz1So4V6zgOu0kae//MmalPF4y7SLs0kVeHp/ZPX5O/hwl7BIrSlegyFF0Wa6PTLW0H9ak/fSrWri7Ep9jtGjZdV3aq68Yd512fladnLRvPdWLNyRO9uBEl3vMc2aVuLC6Tsu0SyM6rtN+8aTCWKWkTwAlnZAL53SPG69/66/wbNVBvGG34aGvhWAIhTHr2Wdh/u8HKOkkLUjmPVVJe0NDRNq3q22gPTFrKekU29y5cK5cqZXIr1wJc3HxZb1Okhqkyvt/63CrknU9GgYbxjynLqcuKuyy5FulqxIGSQ2S9EFUoPtYRNhf07aDLWPXaS9dqAl7zVWavLtKUmaspjNdQ96ItPeo7eH2oTHPEUmXDLuIu2xnFmfx/7MLJBXGKiV9AijphFw4xzuHsfd778Afq47hsNGKX34jqI7Pee01GL/zbUo6SQtS7Z7qb2lRZfEqtm1XEn8mltoaOFdIpn0lHCtWwFpXxw9m04BUG6s63aPdCdJ+tO/omOeUOEuUrOvSPjt/NowieCR9EDXoP62VxYu0N76mdZM/k4KZCNdchcG8hchedDOMhTO02m1y0X2AZMk3CZH2/a2DY9ZpL8yyYlVdvpJ2iQUVObCY+P9Zqt9XKekTQEkn5MI53D6I499/G/63+jTa/BY88D1N0uft3gV8+cuUdJIWpPo9NdDVhZEdOzCyfYfKtHuPHtU+LMdhKixUZfGOlSvgXLkK9nlzYbCwS3CmkepjVWfAO4CdHTuxs1OLg90HEQgHEp6Tbc1WDej0WFS0CDYT59umHUPtEWHfom07DojNJz7HVaot+yaZdtmWLgZM5mRdccbg9gaws7EP2071YmtDL3Y19sMbCCU8x2ExYXlNXlTaZT/Lxr/7VLuvUtIngJJOyIWzr3kAbT9+C+6vacXosBnf/XFQNbyau20rQs8+i/7+fuS99a0wUhZICpNu99Tg4CBGd+/WpH3nDnj27kPY5xuz7JtqRrdyBRzLV8CxbClM2dlJu2YyPceqzmhgFPu69mFH5w7s6tiF3V271bEzl32TZnSSZRdpl2Z0+fb8pF0zmSSjfUDTVoQbNsN/cjMsXfthCPrGLvtWvVqTdukkX7UKsPH+dLF4A0HsbxnAtgZN3Lef7sPAqD/hOSajAQvKc7CyVsu2S9a9NGd6J1JCKXBfpaRPACWdkAtHvsEdfODN+HJtF2w9Jnz1Z0E1V3b2Ky9znJK0Id3Hasjng2f/fpVtH92xEyM7dyI0ODj+vPYVy5W0y9ZcUcES+TQj3ceqTiAUwJHeIyrLvqtzlwopmT+T+tx6TdiLlylpl3nuHLNpNlYLcmBs26Nl2htfB5peBzwD489rr5Zs+5WauOdVJ+vSM4ZQKIzjXcOqNH67KpPvUw1/z6Qq34FVtflYKdJem485pdlK5qcLoRS4r1LSJ4CSTsiFIzd+/0/vwKfr+1HaYsTnfx1Uc2NnPvUkxylJGzJtrOrLvo3s3IXRnZJt3wV/U9OY55lLSuBYvjwi7sthnzdPLQdHUpdMG6sJa7UPNWNX1y5VJi/SfnJg7FznPFueEvalJUuVvC8sXAi7LBFG0mes6h3klbRvAZreAPobx/6CnEqtc7yIu2zLpESeVXkXS2v/qMqw72jQMu2H2gZxxrR2ZNvMWF6bjxU1eSrjvqw6D9n2zP27D6XAfZWSPgGUdEIunNeOd8Pyi1vxofoRzDkBfPIPIdgXLkT9H36PUF8furq6UDxrFowmU7IvlZBpfU/1d3ZiVKR9l2Tad8Fz6BAQSJwjbLDZYF+8CM7lmrQ7li2DuaAgaddMpudY1en39KuyeBH23Z27caDnALxBb8JzzEYz5hfMx9LipUrcReDLssqSds1kkmN1sE3LsDe+oW3b9gJhrcdNFLNDW/pNibuUyF8BZBVe0j/DdGDYG8Cuxj5sb+jDjtN9at/tC467XrsIux41Bc6MqWoJpcB9lZI+AZR0Qi6cTUe7kPurm/C+GX6sORjGhx8JwXnFFaj97wcQ/uIX2TiOpAXT8Z4aGh3F6L59GN21G6O7RN53IThwRgmqTB2tqVHz2UXYncuWwTZnDgxmNh1KFtNxrOr4g34c6j2khF2X9/FK5KWLvEi7nnEXibeaWCGSVmPV5wZadmjS3rxVzXGHp3/s8wpmasIu89urVgMlCwAjkwIXQyAYUku9iayLtO9o7ENT79gS+SKXFcuq87GiNg/Lq/OxtDoXTmt6vjeEUuC+eiEemp5/y4SQy4o/EIIFAQQMBth92vd6xqysZF8WIeQcGB0OZF1xhYroeu2nGpSsj+zaqeRdSub9jY0qBh95VD3P4HTCsWiRknYl70uXwlzIbBa59FhMFiwpXqLi3Xi3GrOt7lYl63s692BP1x619FvnSCeePf2siviGdPrPiryXOkszJguYkVizgPprtdBL5HuOa6XxKrYC3UeA3hNa7Hkw8nMuoGK5lm2XTLs0pMsqSuofJd0wm4xYVJmr4l1X1aljnYMe1YNISfvpPuxvGUT3sA/PHepQIcgc9nll2VhRk686yMu2tjBzsu2pBCWdEHJOAqEQwgYpmTXDEWneSkknJP2QD1K2GfUq8t76F+qYZNZH9+7F6O49qpv86J49CA0PY2TrVhU6lqoqJesqli3l3HZy2cZspatSxR0z7lDHRvwjqixehF0X9z5vn/a4a0/0Z0scJVFplxCJd0g5NUlNJLtZPEeLFe+KdZFv3q4Ju2Tbm3cAviGg4RUtdApmaFn2ylWatJcuAsy8P10IJTl23LKoXEWsi/ygyrbLsm8i8G0DHhxoHVTxy9dPq+cVZEm2XTLteVhWk4el1XnIyeC57ZcLSjoh5Jz4g2GEDf6IpDOTTkgmYcrNheuaa1QkNKQTYY9Iu+/ESfibm1UMPv64ep4Iun3BAjiWLoF9yRIl75bKSmZUyCXHaXFiddlqFYJk25uGmpSg7+3aG8u2j3biucbnVAgmgwlz8udgcdFiLC5ejCVFS1CXWwejdB0nqYkjH5h9oxZCKAh0HYmUx28DmrdFsu0ntdj7kPY8kw2oWBaR9pWawOdWaxOvyXlhM5uic9N12gZGsfO0Juwi7yLxvW4fXjjcqUKQv+JZxS5N3Gu0hnRzSl0qe0/OH0o6IeS8MukhY0jtO31ykw1S0gnJUAxGI2yzZ6vIv/tudSw4NASPzG3fI9n2PWob7O/XJH737ujPmgoK4Fi8GPalS+BYshSOxYvUlwCEXErki6GanBoVd868Ux2T9dkP9hxU0q6Le9dol5rvLvG7o79Tz8u2ZGNh0UIl7pJtl22hg1M7UhaZi166QIuV743Ltu8AWrZr0i6Zd5nbrpfN62SVaFl2aUwn8i4l8468pP1R0pHyXAduXyIRy7YfbB3E7qZ+lW3f1aTNbT/WOazi9zua1fMcFhMWV+UqYdejPNfOL3UngJJOCDmvTDpUuTuQ5dcl3ZnsyyKEXCZM2dnIWrtWhZ65lDns0TL5vXvhOXwYwd5eDG/apEJHlmtU2fbFS5S02+bNg9FmS+KfhkwHpKx9ZelKFfqYbXe3Y2/3Xuzr2od93fuUxA/5h/B62+sqdCqyKrCoaJESdtlKmbxk70kqZ9s3aiFIT+yeE4nS3rEfcHcCR57QQqdwdkTcV2ryXrqYZfIXmG2XbLnE+9Zpx7qHvdgdEXaR9z1NA6q7vCznK6FTnG2LCvvSqjwl8bkOlsnrUNIJIefEHwwhaNSW6sjya996MpNOyPRFsh/W2loVuXdqmcuQ1wvvoUOauO/dp7Yi8r6GBhUDf35E+2GLBfa5c9UycA4R9yWLYa2vh4FLOJJLPGbLXeUqbq67WR3zh/w43ndcCbtk22V7auCUalQn8czpZ9TzpBx+Zt7MqLQvKlyEWfmzVLM6koJIdrZolhZL/1I75h8F2vZo3eT16GsAeo5psec32vNkhQBZq71Csu0SKzWRn2arLFwMRS4bNi4oVSEEQ2Gc6BpWwq5Je7/qLN815MWzBztU6MwoylJz2pdU5artgvIc2C3T872Bkk4IOScBNSddL3ePk3SjEeFVq+CXJZ34BkbItEay41o3+GXRY4G+PnhE2vftx+i+vfDs3YegHNu/X0X/b36r/azTCfvChbAvXgzHIm0rjepYCkkuJSLZ8wvnq3j73LerY8O+YZVhF2Hf371fbTtGOnCs75iKPx77o3qe1WjFvIJ5qlReF3fOb09hLA6g5kotdNzdQMvOiLRv17ZSOq9L/LbI86zZ2vx2KY8XaZdtXg3nt58n0hF+Tmm2irevqlbHRn1BHGgd0Mrkm/qxt7lflcmf7Har+NOuFvU8s9GAuWXZStiXVuVicWUeZpe6YJkG89sp6YSQc+IPBBGMSLojIukmlwuQdZRvvx3ezk5tnxBC4jDn58O1fr2KaJl8Sys8+7Rsu5rnfvAgQiMjGNm2TYWOzGW3L1qkZdzVdjHMJSUUd3JJcVlduKL8ChU6stybCLsu7dJZfsg3pErnJXSyLFlqvXaR9oWFC1VUZfPLppRFlm2bc5MWepl83ylN3Ft3aaIu2ffxusk7CzVZj8YKIEebp03OjcNqwqq6AhU60oBuT3M/9jYNaNvmfrUEnN5N/sFIewGb2YiFFTlYUqVl3CVmFLlgNGbW/2cp8an6+9//Pr7+9a+jvb0dS5cuxfe+9z1cEVnT9UweeOAB/OIXv8D+/fvV45UrV+JLX/rSWZ9PCLl4QkE/VL84gOukE0Iurky+qlJFzq23qmPhYBDeEyfg2bcfngOScd8Pr8xvHxiA+9VXVeiYiorgkIy7hIj7woWwlJYk8U9EpgMlzhJcX3O9Cv3Lpsahxqi4i7Qf6jkEt9+N7R3bVehkW7PVnHZd2iXzLnPeKe4piPybyFJuEovfph0LBrTu8UrcI1n3joPASA9w/DktdFxlcdK+DChfBmRrJd/k3MhSbtfNLVGh/3/WOuBR5fEi7fuaB1QMeQPYqZaE64dOltWk1nz/9l8uU83tMoGkS/pDDz2Ej370o/jRj36ENWvW4Nvf/jZuvvlmHDlyBCUlY994X3rpJdxzzz1Yu3Yt7HY7vvrVr+Kmm27CgQMHUFlZmZQ/AyGZTijggzfygcIev066fOvsdsMwMqLtE0LIBSJz0e1z5qhAZO32sM8Hz9FjqiR+dL9k3PfDe/w4gt3dYxrTmYuLo8JuX7hAE/dxPj8QMlWIYNfm1Kq4fcbt6lggFMDJgZM40H1ASbtsj/QdURn3N9reUKGTZ8tTGXeRdz1kHXiKewpiMgOlC7XQ124PeLVGdJJtV7Eb6DwEDLcDR5/UQie7XJN2EXaK+wVhMBhQmedQcdtirUohFAqjoceNfS0DqiHdvpZ+tQyc2xfEjtN9yHdmTtM/Q1i+pkgiIuarV6/G/fffrx6HQiFUV1fjgx/8ID75yU+e8+eDwSDy8/PVz7/73e8+5/MHBweRm5uLgYEB5OTkIJWRv4vOzk71ZYWR831JEvnBE9tQd+BN+ERJEX52vwFZQ37UP/wn2GfMQODz/4me9gHY//M/kFOeyw8ZJGXhPTW9CXk8KsM+uv8APAcOKIGXDDxC2lSceEzFRXAsiEm7rOduLitLm/sTx2pm4A/6cbz/uCbtEXE/1n9MCf2Z5NpylbjL/HiVeS9Ij1J5jtUIvhGgfZ+WbRdpb9sNdB8FwmPvT0rcRdbLl2oh8i7HUvzfOlUJhsI43jms5P3mhWUpPVYvxEOTmkn3+XzYsWMHPvWpT0WPyV/axo0bsWXLlvP6HSMjI/D7/SgoiM1piMcr3Wa93oS/HP0fSiKVkeuT71BS/TpJ5hPye6OZdKtX6/IOh0ONzaZDvehqHMaO+96ANceBoupsFNe4tG21CzlFDhgybJ4QSU94T01zrFbYlixRoSNz2b1HjsCji/vBg/CdPIlg19iMu6zhblswH/b5C2CfP1/tW6qrU1KCOFYzA5PBhLn5c1X8xSytSsQX9ClRl+Z0UiIva7Yf7T+KAe/AmKXgZA33uQVzVYM6JfAF81GXUweTrBWeInCsRjDbgarVWuj4hjVxb9sDg0i7zG/vOgLDUBsgEZdxD2cVA2VLlLSHRdzLlrI53Xkif0OzS7JUTDQOU2GsXshrJ1XSu7u7VSa8tDSx7EMeHz58+Lx+xyc+8QlUVFQosR+PL3/5y/j85z8/5nhXVxc8Hg9SGfmHlG9aZEBN628nSdIZHR6Ax2CAIRSGxafdYHpHR2Hs7MRwX+z/I487gObDfSp0zFYj8srtyCuzR7fZxTYYTXzjIZcX3lMzFJnqVlkJ0803QTplOEdHETx5EoEjRxE8dhTBo8cQbGhQa7iPbH5VRZSsLJhnzYJp9myY5syGedZsGGtqYDAnV4I4VjObYhRjfd56FZipLQXXMNyAYwPHcHTwKI4NHsOp4VNqDfcz57jbTXbUu+oxK2eWFtmzUJddp7rNJwOO1XNgnwnUS2hf0hj8bpi7D8HSfRCWroMwdx+Aue8EDO4u4MTzKvRPRyFrDvxF8xAoWgh/0XwEihYgkFcPGJM+WzktCaXAWB0aGjrv56b1v/JXvvIV/Pa3v1Xz1GV++nhIll7mvMdn0qWcvri4OC3K3eUbfrlW3vhIMrFZjPAZDNH56EJJbS2MBgPa/dqMmTs+uATWHCe6GofQ1TSM7qYh9DQPI+ALofv0iAodk9mAgooslW0vqnKpKKxywWJLnewAyTx4T51G1NYC110XfajWcD96FN4DB+E5dAjeQwfhPXoMYbcbgT17VOgYbDbY5syGbd482ObPh122c+aoZeIuFxyr049KVGId1kUfi7jLmu2Sadcz7jLHfTQwikMDh1TomA1mzMiboTL2knWXkH1pWnep4VidBJX1AG6LPgz7RxHuPKhl3Nv3aqXynYdg9A3C1rpVRfS5krEvWQiUL0ZYMu+li4HSBYDl8t2f0pVQCozVs/lqykl6UVERTCYTOjpii9gL8ris7OxzCoT/+q//UpL+3HPPYUlc6duZ2OTN1mYbc1z+cdLhZiKDKV2ulWQwQR88RgMcuqSbzTDJjcbrgz9S/p5b7FBz0kvrcmM/Fgyhv30EnaeH0N08hO6IvPs8QVUiLxHFAOSVOFFUrUl7UVW22nfmWFOyHJWkJ7ynTk+MDgfMS5cia+nS6LGw3w/vyZPwHDykyuQlvIcOqRJ61Wl+n7aKjEK60tfVaWXy8+fBPk/K5ufBXFR0ya6ZY3V6YzPaMK9wnoq3zH6LOhYMBVVXeV3aJQ73Hlal8kf7jqp49OSj0d9R5arShL1AK7mX/bKsqe/NwLF6kdiygOrVWugEfEDXYUBJ+15t274PBimhb92hIvqvaDAChbOBssVxsQRwFSfpD5S6GJI8Vi/kdZMq6VarVS2h9vzzz+Ouu+6Kfsshjz/wgQ+c9ee+9rWv4Ytf/CKefvpprFq16jJeMSHTlKDW3d0R19ldbnQjw/5oU3dHzthSO5PJiMJKlwpA68wZDoUx2DOqBF2Evbt5GF1NQxgZ8KG/Y0TF8e2d0d/hyLaMybjnlzphNPHDACFk8hgsFtjnzlWBt2ifQcKhEPyNjfAcPqzJ++FDKvMuc9x9p06pwBNPJCwJJ5l2+7y5sIm4z5urZN5gTutCRZKiyFz0+tx6FbfN0DKxUrrb7m7XMu29R6Li3uZuQ/Nws4rnGmPLhOVYcxLEXbYzc2fCYrIk8U9GxmC2AuUyR30JsDxyTOYz954E2vdExH2fJu9SKi/LxEns/0PiknBlizRpL41sC2cBKdTTgJydpL+LSCn6e97zHiXbsta5LMHmdrvxvve9T52Xju2ytJrMLRdkybV7770XDz74IOrq6tTa6oLL5VJBCLkERJZgiy2/ppVVuQe0poxmi0EJ+fkgTeRyi50qZq2MLZM0MuiLZdubNYEXYR8d8qPpYK8KHZPZqMrlRdiLKmPybs/ihwxCyOQxGI1KsiVybrklejwgfWxE3A9JHIT38BH4ZJ57dzfcmzeriP4OqeCbLeXyc2GfI/KufRFgyo1VGREyVcgX5uWuchX6Ou5Cv6dflceLuMtWxP1k/0kM+gaxtX2rivhy+fq8+miTuzkFczAnfw6KHJeuUoRMAsnCFs3SYtFbY8eHOiLCviey3Qf0nNCWhDvenriWu9kBlMyPyLuUyy/SyuXtvD+lGkmX9He84x2qiZuItwj3smXL8NRTT0WbyTU2NiaUBvzwhz9UXeHf9ra3Jfye++67D5/73Ocu+/UTMi0I6Zl0LW1ukjXSRdIH/egunImsfKv25nERSFl7zYJCFTp+XxC9rW4t4x6R956WYVVir+a+NyY24HDl2zRhl+x9ZJtX4mDWnRByUcha7C6Ja65J7Cx/7Jgm7kcOwyvbo0cRlnL5/ftVDMT/jvJyJes2yd5L5n3uXFhVk7qkfxQjGUiePQ9ryteo0JHO8rKWuwi7yLvaRtZyP9Z3TMVjeCz6/EJ7YTTjPjt/thL3GbkzmHVPNWTddYnZcU20vcOAzHMXYZc13dX2IOB3R5aJ25n4O3JrNHHX14QXeS+Ywaz7dF4n/XLDddIJuXC+95Mfo8P3FbS2OfHx/wvBsXQp6h76LQ5ubsWLvzqMstkuvOVfVl2WcaqXy6tsu0h7ZDvUM/5qDdGse6VEROArtbnuZHrBeyq51Ei5vO/0aXiPHNXE/chRtba7v7V13OerrPusWaoxnW3unKjEG/PyOFbJZUEvl4/Pusvc9sbBRoQxVhH0rLsIu8Ts3NnID+ZjfvV81WeKpDBSLt93KjK/fb8m7x0HgIGm8Z+vZ90l0y7N6nSBz0rPCotQCnwGSJt10gkhaULQq3V398bmpMeXu9uzL9+tJL5cfubyWLm8dzSghF0y7d0tmrz3tLoROEvWXea6K2GvcKEgIvAi8xYrP2QQQiZfLm+rr1eRc8vN0ePBwUHVXd5z+Ii2rvuRIyoLHx4d1dZ3P3Ag4ffIXHdDXR2wcCHsIvASs2aqBniEXKpy+Q3VG6LHR/wjaj13EXfJsIu4y1aWhdOz7o/j8YS57pJtn503O5p1n5U3Cy4rp6KmDCKmhTO1WKg1I1SM9mlZ9o44cZfHgdHxs+5ZJTFhL1mgSXzxPMDC+9NUQkknhJwTQ9Cf0N09Kul9HhiDfjgdYfk6PqnXaHOYUTE7T8WZWfeeZndM3FuGMdA9qua6n7mmu7RKzS1yRIVdZeArXMgtdZz3nHtCCDkTU04OnKtWqdBRTeqamjRhP3pMk/ejR+BvbFJz3dHdjb7t2xM7zNfUaMvDzY6I+5zZLJknlwSnxYmlxUtVnJl11zvJ69Ew2KDmuu/o2KEinoqsCiXtIuyz8mcpiZfGd1YTq9lSBkc+ULdOC51QEOg9pUm7lM0rcT+gZeLdncBJiRdjz5cO81IeL5l3ybqr7QLtmIn3p8nAvzVCyDkxypx0kwE5Z0j6SO8IVu56EOVuF3D3N6SdO1KJ+Kz7jOWxpUhkTntvm1sJe2+LGz2tmryLuA90jao4ubsr+nyj2YD80oi0V8rWhYLyLOQU2tVrEELIpJrU1daqwE03Jcx1Hz1yFN07dsDa3g7fsWMqCx/s61Ol9BJDzz6X0KXeOnOm1qxOxSwl8ZaKcvUahFyKrPv66vXREuLmtmYM24ZxYuBENOMu0TnaiVZ3q4pNzZuiv8dkMKE2pzZB3GW/OrtadbAnKYD8O+hN6hZqq19E57rL0nAq4x6Rd5H40V6g57gWh2LLAMJkA4rnaMKui7tk3XOrL7qXUaZDSSeEnBNDpHGcPdI4Lirp/ZHu7tb0utFabCaU1uWoiEc6zIuwi7j3iri3ytatpF4kXuLYttjz5c8tsq6iIpZ9lwZ2XNudEDIZjE4nHEuXwFZeljB3MtDdrZXMHz2qZd5le+KEKpmXee8SZ/4eq8x310PkfdYsmMumfp1sMr2RrLgs67agaEHCcX39dhH2E/0ncLz/eLRkXhrYSTxz+pnY7zFaMSNvBmbmzdQEPm+W2q90VcIomVqSfGwuoGqVFjpSSTncCXSKsB/S5F3EXWTePxLrOB+PTIMQWVfiPj+2n12uqoYIJZ0Qch5ISbt3vHL3wYik2zLjzVOayTlzClA9ryChZH6o16NkXcu4a+Le1+FGwBdC5+khFfFY7KaovOcrgdf2Ke+EkMliLipSkbV2bWLJfEuLmt+uxF22x4/De/Kkysh79u5VEY/R5YJt5kxYI9JumzVbzXc3l5by/kSmlFxbLlaXrVYRXzLfOdKp5rsf7zuutiLupwZOwRP0qI7zEvE4zA5VIi/SLt3l1TZvBuU9VZD7ht5hfub1iY3q+hs0ae86pAl852Gg+yjgGwZatmsRjy0XKJkHFM8FiudH9kXey6advFPSCSHnlUn3qCXYYpIeCoYwOqgdyORma1LOnlPkUFG3JNbRVP78UhYvwi6l85rEuzHQMQK/J4iOU4MqzszgR6W9TATeqeQ9u4Bl84SQSZbMV1eryL4+9uE47PdrXeZF2I8d17bHj6u13UPDwxjds0fFuPI+ayZsM0XeZ2qZ9/JyyjuZMmQslWaVqri68uro8WAoiNbhVpVt10Oy7yLvo4FRHOw5qCIeu8kek3fJwOfOjGbeWTafAkgVkMxJl5h/R+x40K+t4x4Vd8m8HwZ6TwLeAaDpDS3ikXXci3V5j2yL5gK5VRkr75R0Qsg5MYb8kXL3yOOsLDV/Wyqc5N5osmbmDXIiZO31fBHtsizMjDseDITQ3zmCvrYRVTLfK9u2iLx7g+hsGFQRj5TN58dJu+yrOe9Fdq7xTgi5YGSeul7mjltix8M+H7wNDfBFpF1l3k+cVEJ/VnmXsvkZM2CbOQNWkXfZzpihvhhgwzoyVYhUV+dUq7iu5rro8UAogKahJiXsKga0rZ55P9R7SEU8UjZfl1unsu66vMu+zIPnGu8pgPwbSIZcIr7LfMCrzWkXce86rIUu756zyLuUzRfNiYn7yvdojfAyAN5dCSHn1zhOMulxS7Dpy69JdphZlsR12aUjvARWxpaIC0rmvWNUy7pHMu997W4l9FI2P94ycdKwLq/EifwyiazoNq/MmdHVC4SQS4PBalVLuknEE5X3EyfgPX5CzXX3nTgOb8NprWx+/34VCb9LGtbV1WlN60TaZ87QtvX1MNrtl/lPRjIVs9GssuUSG2s3Jsh781CzkvaT/SdV5l3EXea5e4PeaOf5eKRhnTSnk9+lC7xs63LquFRcKmC2xZZ2i0fkvfsY0H0E6DoSEfgjmtBL2Xz8MnEi6RkCJZ0Qck5M0Uy63jjOCXd/TNLJuZEl3PTGcvFI2fxgt0eJu0i72raNqH2Rd1VO3+oGEOs2L0iJvGTepeu82pY5kVeapdZ/55cmhJApkXcpm29qiki7yPtJbXvyJMIej5aJP3YMCV8vGgywVFRo0l4fJ+8zZsCUn8/7E5kyeZdsucQNNTckls27W5W4i7DrWXeRebffrZaLk3ixKW75MAAlzhIl7PoXAipy6tVxjtkUkPeyRVrEI2XzkmVX0n4UGGzJmCy6QEknhJwTU1iTdEdcd3f3gA9hgxHeutkIzMnjUhqTRMrZ80pFsJ0Aisc0rOvrkNJ5EXhN3EXgPW6/OifReKA34ffZnGZN2CXzHvm98jinmGu9E0ImUTYvpe4zZgA33pjYsK61Db6TWubdd+pkVOCDAwOqmZ2E++VXEn6fKTdXK5Wvr4dtRr22X1cPa3WVei1CpqRsPrtahb5MnN6wrmOkQ4m7SLuedReZ7/H0qGZ2Eq+3vZ7w+5xmZ6K459arzHtNTg1ssrwYSW7ZfLHMUZ+LTISSTgg5/3L3yJx0k0h6oxdhowmD698Ezw15yOHcxEvWsK52YWHCudEhX0za1XYE/R1uDPZ44B0JoP3koIp4jPL7ih3RLwS0zLtk4p2wu5h9J4RcYMO6qkoVrmuvTTgX6O2NZNtPaRIv2xMn4G9rUwI/umuXigTMZq0BXn09rPV1sKmtFsy+k6lAxlBZVpmKtRWxFRL0peJ0cVcxeAoNAw1qLvxIYAQHeg6oiEe6yldkVWjZ/Jy6BIEvchRxzJKLhp+qCSHnJixZ88TGcfqc9Kw8a3KvbRriyLaqqJidl3A84Auiv3NUm+uuZ+A7RtSxgDeojkmciWTfdXmXOfD6fm6Jg3PfCSEXhLmgQIVzdWzZLSE0Oqoa1PlOnVLl8r6Tp+A9dRK+Uw1qrXc5LnEmxtxc2GTuuy7usi9RW8O572TKlopbVrJMRTz+oF+Jui7uusSLwMta783DzSo2t2xO+LksS5ZqUifCLqH2c7WtnCPkfKCkE0LOScig2Xn8Emzufm2OtDOX5V6pgtlqQlGVS0U8UuYnPQSUsEvmPSLrsi8l85J9H2/JOMFVYNPEvSQm7rKfXWRn+Twh5LwxOhywz5unIh4pnQ90dGjyrkS9ISrskn0PSfZ9nK7zMvfdXF4GW12cuNfVqq3MiWfneXKxSCd41Vwub8aY91QpkVfCLnPcBxqi+y3DLWru+3hLxgnFjmIl7DXZNVGBr82tRbWrmp3nSQK8gxFCzgMfTMEwLMH4THozjEE/Kn/9bZizwsAXvgAwq5GSSNmdK9+uonpewZjsu6z3rkrmO0fUUnG6xIu8D/d6VTQf7htTPi+irrLuxTF5l62rwK7OE0LI+ZTOW8rLVWStTSxDDnk80ey7ioYGrQv9qQaEBgcRaG1T4X7ttcRfKp3nq6pgra3Vor4uum8uK1OvScjFvKdKSbvE6rLEihFf0Ke6zkvm/fTgaSXwajvYgF5PL7pGu1Rsa982bvm8CHttdq2Sd5n3LvvlrnLVKI9ML/gvTgg5J2H4o8uv6ZI+oi/BZjer8yR9s++FlS4VZzI67FPZdimXVwLfKfI+qrYBfwgDnbI/itPoGbMMnazxnqsy8I6ErSvPpubbE0LIuZBydvvcuSrOzGQG+/u1rLtIuxL3U5rQnz6NsNd71vJ5g80Ga001LDURgVdRowl8aSkFnlwUVpN13Oy7Pve9cbBRCbuIe3zI3He9fP5VvJrwcyLoVa4qJe2SgdflXbYyx54Cn5nwX5UQck5CCERL3eUDTghGjA75IR9lLHYTfH5KeibicFnhmGVF+azEue/SeV56EqiSeRH4jojAd45isHsUwUAo2tDuTJTAFzuQK03sIuIu+xLMwBNCzjeTac7PV+FcsXz88nkRd5WFj2zlcXOzEnjvseMqJhT4GhH3GrWVx5byMhhM7NFBLm7u++LixSrGK5/Xs+56NA41qjnxsu67vnTcmegCL93s4yVetpKBtxhZQp+uUNIJIRMSDIUBoz+hadzIoPbAaDLAbDHCR0efVkgmXC+fr0qcXqrWfR/q9WKgS8Rdz8Br26Fujybwai14Wfs9ERlP0s1ehF0XeT1yCh0wWZjhIoRcQPn8VVclnAsHAvC3tsJ3ujGadfc1noa/4TR8LS0TCny0hF5Je43Wjb62BpbqGliqKmG0sokqufjy+VVlqxLOhcIhtTRcVNwHG3F6SNtKWb0v5IsJfEvi7zUZTCjPKlfSri9Lp2Q+uwZV2VWwmzlFMZWhpBNCJsQfDCFsCJzRNC7S2T3XxmVGyJh133WxxoKJBV7mwksGXm27RxEKhM/agR4GwJVv0363LE0n4h4Regmbk9kCQsjESDM5lSGvqQGuuXqswLe0wNfYpIl7o4h8I3yNjfA3NSHs95+1hF5vYmeVDHy1ZOKrta2IfE0NTNnZl+8PSTIKmauuLx23pnzNGIHvcHeojLvKug82Jex7gp5oCf14lDhLlLTrmXi1n63t59ny+PkuyVDSCSETEgiFETYG4fCExyy/5sy1AnFz1QmZtMCHwhju82BQhD0Sst8f2fq9wWgTu5Yj/WN+ty3LnCjvao15u3osGX+W0RNCzinwkTnqwBkCHwwi0N6uhF3LvjfB39QYEfpGtYSc3sRu5PXXx/xuU25uJPtepTLvalslIl+lNbJjGT2ZpMBLSbvEeALfNdKlyuXjQxd4WUJOMvQSOzp2jPndLosrKuwi8bKvHruqUeYqYxn9ZYCSTgiZkIDKpAcTyt0H+33RTDo6k3t9JDMQiZaSdokzS+hlvp70QNDEfQQD3XEy3z2K0UEfvO4AOt1D6Dw9NO7vzi60K2k3O4HSag9yi52axBdJFt7MjAEh5KyIRFsqK1WMKaGXJnbd3fA1acKuMvBNzdq2uRnBnh4EBwYQ3LcPnn37xv5yiwWWinJYqyTzXqVl4CtF5qtUeb0IPiGTEfjSrFIVZ5bQy5hVTeyGtJL5eImXrLuI+7B/GId7D6sY73dLGX28vFe6KlXIfr4tn++pUwAlnRAyIb4x5e7OaCbdkW9HOGcWAoODYkLJvVCSscibvTPHqqJ85tgPrJJll4Z1SuK7tcy7EnnZ79HK6PXsvHBqR+Jycla7ScvAFzrUsnLqy4LIVh5brMxyEUImaGJXXKzCuWLFmPPBYTf8Lc2Rsvlm+JpE5Jvgb26Gr7UV8PvhP92oYjyM2dmasIu4V0lUaiIv+xUVqgM+IRc6ZvPseSqWFC8Zc94T8Kj13nVxl32ReRXDzaqRnRyTeKP9jTE/7zA7osIuIq8LfGV2pXrstDgv0580vaGkE0ImJBAMI2gIRZdgU43j9DnpBU7gpr+Gp7MTOWbeTkhysNjOvoyclNFLDwVN4kfQ1tCDoMeIoR6ReI9qgujzBNHdNKxiPBw5VuRIJr7Qjmwpo1f7DpWdzy6ws6EdIeSsmFxZMI2zjFy0jF460Tc3awLfLGX0st+kGtlJhj40NATvwUMqxv39xUWawEumX8S9skJl4NW+lNKzoR25QKSh3My8mSrORMroe0Z7tLnukSx8VOKHm1WJ/WhgFMf7j6sYD5nvHhX3OIGvcFWoteLZ0E6Dn6oJIeeU9JAqdzeNmZOelWdL8tURMjGq1L1Ak+nyWbkomGlCSUkJjJHKD78vqLrOS8ZdZd6jGXgPhrpHlcBLOb1Ex6nBsS9gALJyrMiOZN+zdYGX16TEE0LOVUZfUaECV1wx5nxoZERrZicS39wCf3MTfGqribycD3Z1Y1Ri9+5xXsCg1n7XSvUr1NYq+/KalZUwl5ezKz25IKTUvdhZrGJ5SeLyh4Jk2VuHW7VM+1CLEndd4lvdrarMvt/br+JAz4FxX6PQXqjEXUm7qyJhX8rsJVM/HaCkE0ImxB8KIWgMweHTRMOkJD1uTjohaYyUshdUZKk4E5m35x0JRLLumsAPiczLY5H4nlEEfCH1/4NE+8mBcV9DGiyKrKtMvIqIxEdEXioBCCHkTIxOJ2yzZ6s4EzUXvr8f/pZWTdpbmmNCL8dkSTmPRzW8kxjdsWN8iS8u1iQ+8mWBLvP6Y6NjeggRmRpsJhvqc+tVjMeQbygm8XoMtSiBl323363WjO/x9GBv995xf0eBvUBl3OPFXUReGujJ62ZKUztKOiHknJn0gJS7xy/B1hDJpDsMwJe+hKzhYeBznwM4N45k2Lw9e5ZFRXFN9rgfkj3D/oiwa9l4vYx+qFeLgDeIkQGfinEz8VJamGWBq8CWkH2PbgvssLssbMJDCBk7Fz4/X4Vj0cLxJb6nR60LL8KuBD6yTZD4zk4Vo7t2jfs6pvz8mMBXlKutZOAtFSLy5TCwsR25ALKt2ZhbMFfFeGN20DeYIPGtw63aY7e2LxLf6+lVsb9n/5jf8eLbX1TrzWcClHRCyDnXSQ8aw3BGJD3kcKnsopCVZ4XB74choD0mZLp9SHZkW1WU1uWML/FuvxJ3Fb16Bj722DcaUM+RONuceCmXF1mXdeJ1gZdl5bILbHBFjpstzMYTQs6Q+KIiFY4lS8aX+N7eiMS3xmS+NbYfGh5GsK9PhefA+KXJBocDhqIieGVteF3gyytgUSJfrpaYY0k9Od8xm2vLVTG/cP5ZJb7N3aYEvm04snW3KYGXufJSKp8pUNIJIeeU9PhMus+sNecyW4ywOngLIWRCiXdZVZTUjpV4wTuqldMPRzLvurzrIRn4oD+E/o4RFWfDkW3RRF4kPl+2NiXyKkOfb1ed8Q1cK54QEi/xhYUqHIsXj/uc4OBgRNrbYvLeFtm2tqr58LJGfLipCSMSZ3ktaW5nKRN5lyjTRL4sti9fJBi4Qgy5AImfV3DGWq0ZCD9hE0ImJBAKw28IR9dJ9xi1ubvOPJu6YYaTe3mEpDU2hxm2KheKqsZ2phdE0If7Rdi9UZFX2z6vJvd9HjUvXtaRlxhvnXi9gZ40eozKe74tlo2PPGZZPSEkHlNOjgr7vPGFKOTzqRL6rkOH4BodVXPf/W1tCIjUt2khJfUi8xLjrhOvrxVfUgJzeVlM3kvLtG2ZbMtV2T3vT2Q6QUknhEyIX9ZwlYygV9NxD7QmMlm5LF8j5FIjpe65xU4V46Ga27kDmrz3RWS+T8/Ma/vS1E6WotOz88D4De5MZiOyRN51mc/TZV4TeZF8h4g8M/KEEPnyz2qFtbYWFocDuXGrZiSU1Pf1qUx8oF2kPSLxsi8iL03tOju1teIj8+VHz/JaspScEvYyEfdSWEolCx95LB3sKfIkw6CkE0ImJOj3wWs0RMvdRwMi5z4uv0ZIqjS3c1lUjNfcTggFQ2o9+JjAR7Z9sa2cDwZCGOwaVXE2jGaDkniVlZetZOH1x/naVr7AM5pYukrIdEeV1BcUqMA4ze2EcCCgRF2EXRN42bbD396GgGw7OtR68WGfD/7GRhWYSOQlI69LvNqWaln5slIl+VLebzBTf0jqw1FKCJmQkN8Dr4iALul+uW34uPwaIWmCCLNW0i6rL4zfiVkE3d0v0u5V5fVK5OVxr0c73q+JfCgQjqwlLxn5s2CAmgOfKPMRgdcf59lgtfMjCCHTHRHm6FrxZ0HK6gMdHZrAt3cg0BER+Q5ZXq5DbYPdPZrIqzXlm8+akYfRqDXUU/JeAkuJJu+W0hLtWImIfYlayYaQZMJ3SELIuTPpUu6uS7pXKyVTki5z0mtrERwaUvuEkPRESt1zihwqzkZQMvIDvmgGXpd3EXrZ10NK6/Vl53CWOfKCrA+fKO7WSCZeOybry8u+XBshZJqX1VdXqzgbIuiBri6VeVcy39EZ2UYed4rcd8qNLLrsHPZN8JpZWRFpL9EEXmResvRK7OVxidbwjp3rySWCkk4ImZBQwAMvYpI+Evl6Wj5QS7MXvPe9GO3sRLbsE0IyFpNJWwpO4mwZ+XAojNFhf1Ti9ey8LvTq2IBPLT3n9wbP2bVe71zvzNXl3RqT+JyY1DtzLCyxJ2QaI7JsqaxUcTbCIug9PUrWA52SgdfEXbL0Kisf2Q+53Sp8J0+qmAiTlPMrmS/W5L04IvAlxbH9wgKW2JMLhiOGEDIhoYAPgaABxkgb9xF3UG1Z7k4IORNpKifyLIHasz/P5wloWfm4DLwm8LL1RfdDwXC0c31P8/AELywyLwKvSbyehZfHzrjHspUvGwgh0w+DyaREWgJYdNbnBYfdkWx7hzZfXpf5zojQd3Ui0NWtGt7JWvMS3kOHzv7CRiNMhQWwiLQXF2virrYi8nEhmXkmPEgESjohZEJCfi8M/lgp+8igX23ZOI4QMllkPrpEXun4Xev1ztAetz8i8DFxF7nXZF7LystceZXBH/Sp6G6aQOYB1WRPZeF1gVf7usjLFwzavpTjs1M0IdMPkysLJlc9bDPqz/qccCiEYH9/tHReybySeBH4rtjxnh5VYq8vQ3fO187PTxR3FUVRidePcc585kNJJ4ScM5OOiKT7s3JViaogH2Lh8wHf+hayhoeBf/93wC5lsIQQcvGIIDtcVhVFVWd/nsyB9wz7x0h8VObV/Hjtsf5cid5W94Svb7YaYwIfqQ7Qs/LRxzk2OHIszM4TMs0wSAM6vXP9WdaR10vsJdOu5st3xgm8bLu6Y4+7u4FAQC1ZJ+E9enTi13c6NXkvisi7Enhta9JlXs4V5DM7n6ZQ0gkhExPwRDPpvhwpEQMsdpPWmdnng2FkBIbRsy/ZRAghlxJjXIl9McZfhk6QbLtk5iXzrkt8/H78MfkyMuALnbuTfQR7lsyb165Byu7Vvmwj1+XQty7OnSdkupXY69lv+4IF587MK2kXgY9Ed0Tku/Vj3QiPjKjwn25UcV7Z+aJCTd4LI0Kf8LgQpsJC9YUD586nDvyXIIRMSCjghyGg7fuyi9SW89EJIemGzJcXgZYorHRN+FyZMz86JOLui4q7ysYrqfepc/JY5sqr7Lzbr+Jc2Xk1d95l0UReF3q1tSQ8trvMark7Qsg0zMzPnTvhc6WpXVTglcRHtiLy3VpZvXqsl9pHsvM4dvwcF2HQhL5QBL5QE/j4fZH5gkK1VULPzvaXFEo6IWRiAl6YVSY9DJ+zMNbZnRBCMnzOfG7x2efMR7PzI/6YyCuZ92FkSJsfL1v9sWfIh3AY0UZ45xR6uQ7HsZjER75gUFn5bIvaKqlXxy2wOsycQ0/INEDmo1sl6uomfF4sO9+NYI8u8j2ayMtjkXnpdt/To0ryIc+PNMLDsWPnvo7cXO2LhcJIJr6wILIVmdeO6+eMLhfvTxcIJZ0QMiHhoBemyPJrPnuB2jKTTgghkex8ZN584dlXflLo8+FF5KMCH7c/GvdYz9DLUnUS/R3nvhajSa8UiAm9PbKvmuWd8ZiN8QiZRtl5zJnwuWrufF+fJu1K4mUbt6/LvGxF4gMBhAYG4JM4derc12KxKFk3FeTDXBAR+oLYY+l+L9epMvUF+TA6J/6CdDpASSeETEjQ74E1kkn327S1kSnphBAy+bnz5yIYCKKlsR1Zthx43AFN3lUGPi5LL8eGtWN+T1AtV6cvZXc+mC1GJe3qS4b4bUTilfCrrXZOepFQ6gnJ4LnzkQZ05yq3Vxn6gQGtIV63ZOFF4HsR6BGh70WgV2S+Nyr1Up4f9vsRaG9XcT53KIPdHpF2yc4XwJyv7YvAm9R+Psz5+dr5ggJVXZBp9ydKOiFkQgLBUdgjmXSvORsIcvk1Qgi51Bl6q9OE/JIsGI3nbjQX8AejEh+V+YjES5n9yJB0tNcz9n4E/SEE/CEM93pVnA9GswGOLAvsury7zth3ReRe7WvBrveEZGiGXuau5+fDNnPmOZ8f8ng0oe/pjQp9sC/yOK7cPiBz53t6EPb5EPZ44G9tVXFe1ySZ+oIC1P/pj5HKgfSHkk4IOaekOyKf4XzGLCXpavk1wWBAuLwcwaEhtU8IIeTyY7aYkF0gce5lMGX9eeler2R+WObK+7U585GsvJad16Ref450updGdtI0T+J8sTnNqvN9orxbY/tnnLM5LarigBCSORjtdhgrKmCpqDiv+1PIPaIkXiutl6Z3uuBH5F6OKamXY31K6FWmvqMDJtfETUHTCUo6IWRC/CEPHD6ty7An7FDbaCZd1t78u7/DaGcnsrkOJyGEpDxSEhprjKfd08+F3xdMkPiEfX3rjhyP7CMMeEcCKga6znOZTkNM7B26xEdEPir14xwzmZmxJyRT7k8mV5YKVFef18+ERkc1ae/vz6iO85R0QsiEBAJaubtouieoiTjnpBNCyPTBYjXBcp6ZekGa3nlH4qRdMvPuSOZel/x4qR/2qwZ5SuzdARUDnaPnf302U1TcleSfKfRZZth0sXdqW+mGz6w9IemP0eGAsbISlspzdO9MMyjphJAJCYQlkw4EzA4Ew1q2IksvdyeEEELOwBjX9T7/PH8mGAwpOVcS7xaZD2hSr9agl+Oyr5/Xwuv2q2XtpHxfYqjXc/4XKVl7h5a1VwKfFbfvjEi9PNZL9tU5s/oZI+faE0IuMZR0QsiEBEJeZPsArzVPPZYPLGarSTvp9wP33w+nzEn/xCcAGzPshBBCLhxpMhfrfp91Xj8j69R7R8eKu5L5yGO9DF/K7tXzRvyqG358OT7Otxw/gtVuUhKvC7zMpReBt8dvI6KvtvI8p4Ud8gkh5w0lnRAyIcGwD3ZfGD59+bX4zu7hMAz9/TC63WqfEEIIuZxd8PUs94UQDIQ0aU8Qe5F5kXYReSm5j5xTIq+JvyrJlyaqnqCKoZ4Lv15d2kXs7XH70a1k6/V9h76v9RCQnyeETA8o6YSQCQmEvarc3WvV10hnqTshhJD0RRrNne+a9fGEpCQ/kn3XBV7bxu27Y1KvH5eQLwYk86/PyQcuLHuvl+crYXfEiX28yDtimXs5blVbTfzNFiOz+ISkEZR0QsiEBEJ+2L2AN1uXdJa0E0IImX7IXHSHrA2ffeFfVgekQ36CuMcE3nPmMf15oxHB94cSy/Mnde2GmOBHZV+y9SZYVdbeFJV8/TnalwHa1mozMZNPyGWEkk4ImZBQ2Kcy6cORTLozvtydEEIIIedEerm4JPIv/D004A9GBV1K7vUsvuyr46MB+HTBjzsmou8bDaoMfigY1ta9H5Is/iQwyFx8EXZTTOAdZjXPPgg/cguG1bx7JfQi/PaY6EefS9En5LyhpBNCJsQPv1buHpmT7qKkE0IIIZcNs8UEc65pUpVs4XBYdb5PFPp4iZf9oCb5sh2NfAHgCUaz+aFAWGXy5bkSw/CO80p95y/6dsnax0l85LG2H5H86H7kvL7vMKnpCizdJ5kOJZ0Qcu7Gcf74OemUdEIIISQdEJnVxNgM1/muhzdOJl8y8rroa2IfyeqP+NHXPQCL0aa65qvjHjkX2Y+EZPLjRR9944n++Zfuj5F5uwkWXeRtcjzyWH+eXcv6R78kkMfM7JMUhpJOCJkQgyyzBsmka0uwOfPi5uIZDAgXFyNkt6t9QgghhGRgJt9iGrfRXigUQmenDSUlJTAajWfN5su8etUVP07wNZnXhF725bhfHdeepx0Lwq+f82pL54nw6535LxYR9ajgx23jpV7bxu3btG30fOR3SM8CQqYKSjohZEIMvgDCMMBnzRmbSbdYgH/6J4x0dsIl+4QQQgghZ2TzZU6+xIV21I9H5tar0v1Ipl5t4/cjgi9Sry2Tp53THkdEP7J8nvwuQX6fkv8B30X/OU0Woyb6tjjpt+nbsVKvP08/px2PPTZR+qc1lHRCyIQY/QH4LVkIG7XbhZNLsBFCCCHkMiOl6frcdUyydH9MZt+ji/tYwZfjCee8McmP/pw3Mmdfpgf6QxiVmGxzvjMwmg1a1j5O4qOhZ/THOxcN7bzZZow+V34n5/OnB5R0QsiEGKWrrLVA7TuyLfxmlxBCCCGY7pl9nWAgFJV5LdMfk30tU69/ARB5LOe8sf3oz6jHQfX7BJF/T2Bqyvp1jEYDzOMIvfxdRIVf37cZleibrcbo8ejPRp+jHTNb2MxvqqGkE0ImxCANYyKd3bPO7Owu89V//GM4h4aAj34UsLGpHCGEEEKmD9Jt3uQywu6amml/waAm/XopvravyXzsS4Ag/L6450Sy/LHHic+RLL8QCoVjzfumEoO2zKBFhD5e+uP3rUbty5E4yVdfAMQ9R9tqz9O/DJDnTMf5/pR0QsiEmP2hs3d2D4dh6OqC0e1W+4QQQgghZPJIxaIpywh71tT1+gmJ+Ps0+Q9ExF3P/AfkeNyXAOqYN+6YOh85HvfFQEAiIv/S0E899ganrNw/HinT14Q9JvfSzFAXev0LgnV3z1bz+jOBzPhTEEIuGUZfOLpGehbnoxNCCCGEpBWSibY5JKZW/SQzr4u7tg0liHy82KsvA3yayMe2oehzoj/nC0WfI/KvXicQhjegLQE4EVe/fQ4yBUo6IWRCTP4wfFZ9+TWWsxNCCCGEEG2Ou7b2/NQrZVga/AVE2CNyryIm9dqxeMkPqbnxmQIlnRAyIWZ/fCadkk4IIYQQQi5Dgz+LNKUzwY7pt8xv5nzdQAi5dJKuz0lnJp0QQgghhJBLCiWdEDIhZh84J50QQgghhJDLBMvdCSETYvIbMTt/zB0AABGgSURBVJqbM34m3WBAOC8PIZNJ7RNCCCGEEEIuDko6IWTCrp3mYDZgkKKbMBzZZ2TSLRbgwx/GSGcnXLJPCCGEEEIIuShY7k4IOSv+UAimkFbqbjX7VRdPQgghhBBCyKWDkk4IOSuBQBAGaJJusweTfTmEEEIIIYRkPJR0QshZ8fu8UUl3ZI2TRff7gZ/8BI5f/lLbJ4QQQgghhFwUnJNOCDkrfq8HMGiS7swZZ855OAxDWxtMbrfaJ4QQQgghhFwczKQTQs7KqH8IYZMm6a4CZ7IvhxBCCCGEkIyHkk4IOSue0SEEzXlqP6coO9mXQwghhBBCSMZDSSeEnJUR9wD8Vi2TnlusrZVOCCGEEEIIyXBJ//73v4+6ujrY7XasWbMGW7dunfD5v//97zFv3jz1/MWLF+OJJ564bNdKyHTCM9ADb0TSs0u1LSGEEEIIISSDJf2hhx7CRz/6Udx3333YuXMnli5diptvvhmdnZ3jPv+1117DPffcg//3//4fdu3ahbvuukvF/v37L/u1E5LpjPb1wm/VytxdRVnJvhxCCCGEEEIynqR3d//mN7+J97///Xjf+96nHv/oRz/C448/jp/+9Kf45Cc/Oeb53/nOd3DLLbfg4x//uHr8n//5n3j22Wdx//33q5/NFF74zS/Quu84gsEATCYzDOOsfkXIpcbX5wZQD0MoAHvWON3dpcG704lwKHTZr40QQgghhJBMJKmS7vP5sGPHDnzqU5+KHjMajdi4cSO2bNky7s/Iccm8xyOZ94cffnjc53u9XhU6g4ODahsKhVSkKg0vHMWo6fpkXwYhCnNgAGH5L3TGMmtmM0If+xiGu7rgMJvlf6xkXSIh50Tu+eFwOKXv/YQIHKskXeBYJelCKAXG6oW8dlIlvbu7G8FgEKWlpQnH5fHhw4fH/Zn29vZxny/Hx+PLX/4yPv/5z4853tXVBY/Hg1TF4AzA3n8i2ZdBiOTKYSw4hc7Oa856wxkYGFA3PvmSjZBUhWOVpAscqyRd4Fgl6UIoBcbq0NBQ+pS7X2okSx+feZdMenV1NYqLi5GTk7rdqt/zrS+pwSRfJsi18sZHUhUZpwaDgeOUpDwcqyRd4Fgl6QLHKkkXQikwVqXpeVpIelFREUwmEzo6OhKOy+OysrJxf0aOX8jzbTabijORf5x0uJnIYEqXayXTEL8f+OUv4RwagvEf/gFGKXknJIXhPZWkCxyrJF3gWCXpgiHJY/VCXjep/zdZrVasXLkSzz//fMK3HPL4qquuGvdn5Hj88wVpHHe25xNCLiHhMAynT8PU1KT2CSGEEEIIIRdH0tNeUor+nve8B6tWrcIVV1yBb3/723C73dFu7+9+97tRWVmp5pYLH/7wh7F+/Xp84xvfwO23347f/va32L59O37yk58k+U9CCCGEEEIIIYSkuaS/4x3vUPOu7733XtX8bdmyZXjqqaeizeEaGxsTSgPWrl2LBx98EJ/5zGfw6U9/GrNnz1ad3RctWpTEPwUhhBBCCCGEEJIBki584AMfUDEeL7300phjd999twpCCCGEEEIIISSTYIcHQgghhBBCCCEkRaCkE0IIIYQQQgghKQIlnRByUYQtFoS59BohhBBCCCFTAj9ZE0Imj9UKfPrTcHd2Ikv2CSGEEEIIIRcFM+mEEEIIIYQQQkiKQEknhBBCCCGEEEJSBEo6IWTyBALAr38N+//9n7ZPCCGEEEIIuSg4J50QMnlCIRiOH4fZ7Vb7hBBCCCGEkIuDmXRCCCGEEEIIISRFoKQTQgghhBBCCCEpAiWdEEIIIYQQQghJESjphBBCCCGEEEJIikBJJ4QQQgghhBBCUoRp1909HA6r7eDgIFKdUCiEoaEh2O12GI38PoWkID4fwl4v3F4vAoODMPp8yb4iQs4K76kkXeBYJekCxypJF0IpMFZ1/9R9dCIM4fN5VgbR3NyM6urqZF8GIYQQQgghhJBpRlNTE6qqqiZ8zrSTdPkWpbW1FdnZ2TAYDEhl5NsW+UJB/iFzcnKSfTmEjAvHKUkXOFZJusCxStIFjlWSLgymwFgV7ZZsfkVFxTmz+dOu3F3+Qs71zUWqIQOJNz6S6nCcknSBY5WkCxyrJF3gWCXpQk6Sx2pubu55PY+TRwghhBBCCCGEkBSBkk4IIYQQQgghhKQIlPQUxmaz4b777lNbQlIVjlOSLnCsknSBY5WkCxyrJF2wpdlYnXaN4wghhBBCCCGEkFSFmXRCCCGEEEIIISRFoKQTQgghhBBCCCEpAiWdEEIIIYQQQghJESjphBBCCCGEEEJIikBJT1G+//3vo66uDna7HWvWrMHWrVuTfUmEJPDlL38Zq1evRnZ2NkpKSnDXXXfhyJEjyb4sQibkK1/5CgwGAz7ykY8k+1IIGZeWlha8853vRGFhIRwOBxYvXozt27cn+7IIiRIMBvHZz34W9fX1aozOnDkT//mf/wn2oibJ5uWXX8add96JiooK9V7/8MMPJ5yXMXrvvfeivLxcjd2NGzfi2LFjSEUo6SnIQw89hI9+9KNqmYCdO3di6dKluPnmm9HZ2ZnsSyMkyqZNm/DP//zPeP311/Hss8/C7/fjpptugtvtTvalETIu27Ztw49//GMsWbIk2ZdCyLj09fVh3bp1sFgsePLJJ3Hw4EF84xvfQH5+frIvjZAoX/3qV/HDH/4Q999/Pw4dOqQef+1rX8P3vve9ZF8amea43W7lTZLsHA8Zp9/97nfxox/9CG+88QaysrKUY3k8HqQaXIItBZHMuWQo5eYnhEIhVFdX44Mf/CA++clPJvvyCBmXrq4ulVEXeb/22muTfTmEJDA8PIwVK1bgBz/4Ab7whS9g2bJl+Pa3v53syyIkAXmPf/XVV/HKK68k+1IIOSt33HEHSktL8T//8z/RY29961tVZvJXv/pVUq+NEB3JpP/pT39SlZ6CKK9k2D/2sY/hX//1X9WxgYEBNZZ//vOf4y//8i+RSjCTnmL4fD7s2LFDlV/oGI1G9XjLli1JvTZCJkJudEJBQUGyL4WQMUjVx+23355wbyUk1XjkkUewatUq3H333epLz+XLl+OBBx5I9mURksDatWvx/PPP4+jRo+rxnj17sHnzZtx6663JvjRCzsqpU6fQ3t6e8DkgNzdXJUdT0bHMyb4Akkh3d7ea6yPf6sQjjw8fPpy06yJkIqTaQ+b4SpnmokWLkn05hCTw29/+Vk0dknJ3QlKZkydPqjJimfL26U9/Wo3ZD33oQ7BarXjPe96T7MsjJFrxMTg4iHnz5sFkMqnPrV/84hfx13/918m+NELOigi6MJ5j6edSCUo6IWRKspT79+9X36QTkko0NTXhwx/+sOqbII04CUn1Lzwlk/6lL31JPZZMutxbZf4kJZ2kCr/73e/w61//Gg8++CAWLlyI3bt3qy/qpZSY45SQqYHl7ilGUVGR+layo6Mj4bg8LisrS9p1EXI2PvCBD+Cxxx7Diy++iKqqqmRfDiEJyPQhabop89HNZrMK6ZsgjWNkXzJAhKQK0nF4wYIFCcfmz5+PxsbGpF0TIWfy8Y9/XGXTZQ6vrD7wrne9C//yL/+iVn0hJFUpi3hUujgWJT3FkJK2lStXqrk+8d+sy+OrrroqqddGSDzSgEMEXZpyvPDCC2opFkJSjRtuuAH79u1TmR49JFMpZZmyL1+KEpIqyJShM5eylHm/tbW1SbsmQs5kZGRE9UuKR+6l8nmVkFSlvr5eyXi8Y8m0DenynoqOxXL3FETmokm5kHyQvOKKK1QHYllS4H3ve1+yL42QhBJ3KXX785//rNZK1+fzSBMO6fBKSCogY/PMPgmy5IqsQc3+CSTVkGykNOWScve3v/3t2Lp1K37yk5+oICRVkHWoZQ56TU2NKnfftWsXvvnNb+Jv/uZvkn1pZJozPDyM48ePJzSLky/kpamxjFeZliErvMyePVtJ+2c/+1k1TUPvAJ9KcAm2FEWWX/v617+uxEeWCpLSTOk+SEgqLW0xHj/72c/w3ve+97JfDyHny4YNG7gEG0lZZPrQpz71KRw7dkx9iJQv7t///vcn+7IIiTI0NKTkRirpZDqRSM4999yDe++9V1WEEpIsXnrpJVx33XVjjkvyU5ZZE+2977771Bef/f39uPrqq9XSrHPmzEGqQUknhBBCCCGEEEJSBM5JJ4QQQgghhBBCUgRKOiGEEEIIIYQQkiJQ0gkhhBBCCCGEkBSBkk4IIYQQQgghhKQIlHRCCCGEEEIIISRFoKQTQgghhBBCCCEpAiWdEEIIIYQQQghJESjphBBCCCGEEEJIikBJJ4QQQjKA9773vbjrrruS9vrvete78KUvfemS/f6DBw+iqqoKbrf7kr0GIYQQkgoYwuFwONkXQQghhJCzYzAYJjx/33334V/+5V8gb+l5eXm43OzZswfXX389Tp8+DZfLdcle521vexuWLl2Kz372s5fsNQghhJBkQ0knhBBCUpz29vbo/kMPPYR7770XR44ciR4TMb6Ucnwu/vZv/xZmsxk/+tGPLunrPP7443j/+9+PxsZG9XqEEEJIJsJyd0IIISTFKSsri0Zubq7KrMcfE0E/s9x9w4YN+OAHP4iPfOQjyM/PR2lpKR544AFVLv6+970P2dnZmDVrFp588smE19q/fz9uvfVW9TvlZ6SMvbu7+6zXFgwG8Yc//AF33nlnwvG6ujp84QtfwLvf/W71u2pra/HII4+gq6sLb37zm9WxJUuWYPv27dGfkUy8/B653qysLCxcuBBPPPFE9PyNN96I3t5ebNq0aYr+ZgkhhJDUg5JOCCGEZCj/+7//i6KiImzdulUJ+z/+4z/i7rvvxtq1a7Fz507cdNNNSsJHRkbU8/v7+1XZ+vLly5U8P/XUU+jo6MDb3/72s77G3r17MTAwgFWrVo05961vfQvr1q3Drl27cPvtt6vXEml/5zvfqV5/5syZ6rFe1PfP//zP8Hq9ePnll7Fv3z589atfTagQsFqtWLZsGV555ZVL8vdFCCGEpAKUdEIIISRDkfnbn/nMZzB79mx86lOfgt1uV9IuJeNyTMrme3p6lGgL999/vxJ0aQA3b948tf/Tn/4UL774Io4ePTrua0j222QyoaSkZMy52267DX//938ffa3BwUGsXr1afVEwZ84cfOITn8ChQ4fUFwGClLGL1C9evBgzZszAHXfcgWuvvTbhd1ZUVKjXJIQQQjIVSjohhBCSoUg5uY6IdGFhoRJgHSlnFzo7O6MN4ETI9TnuEiLrwokTJ8Z9jdHRUdhstnGb28W/vv5aE73+hz70IVUiL6IuzfD0Lw/icTgc0cw/IYQQkolQ0gkhhJAMxWKxJDwWkY4/pot1KBRS2+HhYTUnfPfu3Qlx7NixMRltHcnMizT7fL4JX19/rYleXxrQnTx5UpXFS7m7lNB/73vfS/idMie9uLh4En8bhBBCSHpASSeEEEKIYsWKFThw4IBq+iZN5eJDGrmNh8wR19cxnwqqq6vxD//wD/jjH/+Ij33sY6rZ3ZmN7aQMnxBCCMlUKOmEEEIIiTZuk0z1Pffcg23btqkS96efflp1g5cu7uMhWW2R+82bN1/060snenm9U6dOqcZyUno/f/786PmGhga0tLRg48aNF/1ahBBCSKpCSSeEEEJItCnbq6++qoRcOr/L/HER57y8PBiNZ//IIGXqv/71ry/69eV15YsCEfNbbrlFNZf7wQ9+ED3/m9/8Rl2XLOdGCCGEZCqGsL7uCSGEEELIJJDmcXPnzsVDDz2Eq6666pK8hsx5ly7xDz74oGosRwghhGQqzKQTQggh5KKQjuu/+MUv0N3dfcleQ5Zn+/SnP01BJ4QQkvEwk04IIYQQQgghhKQIzKQTQgghhBBCCCEpAiWdEEIIIYQQQghJESjphBBCCCGEEEJIikBJJ4QQQgghhBBCUgRKOiGEEEIIIYQQkiJQ0gkhhBBCCCGEkBSBkk4IIYQQQgghhKQIlHRCCCGEEEIIISRFoKQTQgghhBBCCCFIDf4/dsSKfxY2pPIAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✅ Each element decays independently (element-wise dynamics)\n",
      "✅ No interaction between elements (pure dynamics, no connectivity)\n"
     ]
    }
   ],
   "source": [
    "# Reset dynamics\n",
    "dynamics.v.value = jnp.zeros(5)\n",
    "\n",
    "# Simulate with step input\n",
    "n_steps = 100\n",
    "history = []\n",
    "\n",
    "for i in range(n_steps):\n",
    "    # Step input at t=20ms\n",
    "    if i == 20:\n",
    "        inp = jnp.array([1.0, 0.8, 0.6, 0.4, 0.2])\n",
    "    else:\n",
    "        inp = jnp.zeros(5)\n",
    "\n",
    "    output = dynamics(inp)\n",
    "    history.append(output)\n",
    "\n",
    "history = jnp.array(history)\n",
    "times = jnp.arange(n_steps) * brainstate.environ.get_dt()\n",
    "\n",
    "# Plot\n",
    "plt.figure(figsize=(12, 6))\n",
    "for i in range(5):\n",
    "    plt.plot(times.to_decimal(u.ms), history[:, i], label=f'Element {i}')\n",
    "\n",
    "plt.axvline(20 * 0.1, color='red', linestyle='--', alpha=0.5, label='Input applied')\n",
    "plt.xlabel('Time (ms)')\n",
    "plt.ylabel('State value')\n",
    "plt.title('Element-Wise Exponential Decay Dynamics')\n",
    "plt.legend()\n",
    "plt.grid(alpha=0.3)\n",
    "plt.show()\n",
    "\n",
    "print(\"✅ Each element decays independently (element-wise dynamics)\")\n",
    "print(\"✅ No interaction between elements (pure dynamics, no connectivity)\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ed3564a7e53d03f",
   "metadata": {},
   "source": [
    "## Part 2: Basic Dynamics Structure\n",
    "\n",
    "### The Core: `update()` Function\n",
    "\n",
    "Every Dynamics module must implement the `update()` method, which defines how state variables evolve in time:\n",
    "\n",
    "```python\n",
    "class MyDynamics(brainstate.nn.Dynamics):\n",
    "    def __init__(self, in_size):\n",
    "        super().__init__(in_size=in_size)\n",
    "        # Define state variables with brainstate.State\n",
    "        self.state_var = brainstate.State(initial_value)\n",
    "        # Define parameters as regular Python variables (constants)\n",
    "        self.param = value\n",
    "    \n",
    "    def update(self, inp):\n",
    "        # 1. Compute state evolution\n",
    "        # 2. Update internal states\n",
    "        # 3. Return output\n",
    "        return output\n",
    "```\n",
    "\n",
    "### Key Points\n",
    "\n",
    "- **Input**: External drive (current, synaptic input, etc.)\n",
    "- **Output**: Observable quantity (voltage, firing rate, spikes, etc.)\n",
    "- **States**: Dynamic variables that change over time (`brainstate.State`)\n",
    "- **Parameters**: Constants that don't change during simulation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea0b243d62489fdd",
   "metadata": {},
   "source": [
    "### Example: Leaky Integrate-and-Fire Neuron"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e5f4d9d5f3445900",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:48:58.978533Z",
     "start_time": "2025-10-11T09:48:58.873919Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "LIF Neuron Population:\n",
      "  Size: (3,)\n",
      "  Initial V: ArrayImpl([-65., -65., -65.], dtype=float32) * mvolt\n",
      "  Threshold: -50.0 * mvolt\n",
      "  Time constant: 10.0 * msecond\n"
     ]
    }
   ],
   "source": [
    "class SimpleLIF(brainstate.nn.Dynamics):\n",
    "    \"\"\"Leaky Integrate-and-Fire neuron dynamics.\n",
    "    \n",
    "    Equation: τ dV/dt = -(V - V_rest) + R*I\n",
    "    Spike when V >= V_th, then reset to V_reset\n",
    "    \"\"\"\n",
    "\n",
    "    def __init__(self, size, tau=10.0 * u.ms, V_rest=-65.0 * u.mV,\n",
    "                 V_th=-50.0 * u.mV, V_reset=-65.0 * u.mV, R=1.0 * u.ohm):\n",
    "        super().__init__(in_size=size)\n",
    "\n",
    "        # State variables (dynamic)\n",
    "        self.V = brainstate.State(jnp.ones(size) * V_rest)\n",
    "        self.spike = brainstate.State(jnp.zeros(size, dtype=bool))\n",
    "\n",
    "        # Parameters (constants)\n",
    "        self.tau = tau\n",
    "        self.V_rest = V_rest\n",
    "        self.V_th = V_th\n",
    "        self.V_reset = V_reset\n",
    "        self.R = R\n",
    "\n",
    "    def update(self, I):\n",
    "        \"\"\"Update membrane potential and detect spikes.\n",
    "        \n",
    "        Args:\n",
    "            I: Input current\n",
    "            \n",
    "        Returns:\n",
    "            Spike events (boolean array)\n",
    "        \"\"\"\n",
    "        # Exponential Euler integration for V\n",
    "        dt = brainstate.environ.get_dt()\n",
    "        alpha = jnp.exp(-dt / self.tau)\n",
    "\n",
    "        # Update voltage\n",
    "        V_inf = self.V_rest + self.R * I  # Steady state\n",
    "        self.V.value = self.V.value * alpha + V_inf * (1 - alpha)\n",
    "\n",
    "        # Spike detection\n",
    "        self.spike.value = self.V.value >= self.V_th\n",
    "\n",
    "        # Reset voltage for spiking neurons\n",
    "        self.V.value = u.math.where(self.spike.value, self.V_reset, self.V.value)\n",
    "\n",
    "        return self.spike.value\n",
    "\n",
    "\n",
    "# Create a population of 3 LIF neurons\n",
    "lif = SimpleLIF(size=(3,))\n",
    "\n",
    "print(\"LIF Neuron Population:\")\n",
    "print(f\"  Size: {lif.in_size}\")\n",
    "print(f\"  Initial V: {lif.V.value}\")\n",
    "print(f\"  Threshold: {lif.V_th}\")\n",
    "print(f\"  Time constant: {lif.tau}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ed43aebeadf0eab6",
   "metadata": {},
   "source": [
    "### Simulating the LIF Dynamics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f1bc101789484373",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:48:59.888973Z",
     "start_time": "2025-10-11T09:48:58.987600Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1400x800 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Neuron 0: 7 spikes, rate = 70.00 * becquerel2\n",
      "Neuron 1: 14 spikes, rate = 140.00 * becquerel2\n",
      "Neuron 2: 20 spikes, rate = 200.00 * becquerel2\n",
      "\n",
      "✅ Each neuron evolves independently (element-wise)\n",
      "✅ Different inputs lead to different firing rates\n"
     ]
    }
   ],
   "source": [
    "# Reset neuron states\n",
    "lif.V.value = jnp.ones(3) * lif.V_rest\n",
    "lif.spike.value = jnp.zeros(3, dtype=bool)\n",
    "\n",
    "# Simulation parameters\n",
    "duration = 100 * u.ms\n",
    "n_steps = int(duration / brainstate.environ.get_dt())\n",
    "times = jnp.arange(n_steps) * brainstate.environ.get_dt()\n",
    "\n",
    "# Different input currents for each neuron\n",
    "I_inputs = jnp.array([20.0, 30.0, 40.0]) * u.mA\n",
    "\n",
    "\n",
    "def step_run(t):\n",
    "    with brainstate.environ.context(t=t):\n",
    "        spikes = lif(I_inputs)\n",
    "        return lif.V.value, spikes\n",
    "\n",
    "\n",
    "# Run simulation\n",
    "V_history, spike_history = brainstate.transform.for_loop(step_run, times)\n",
    "\n",
    "# Visualization\n",
    "fig, axes = plt.subplots(2, 1, figsize=(14, 8), sharex=True)\n",
    "\n",
    "# Membrane potentials\n",
    "for i in range(3):\n",
    "    axes[0].plot(times.to_decimal(u.ms), V_history[:, i].to_decimal(u.mV),\n",
    "                 label=f'Neuron {i} (I={I_inputs[i]})', linewidth=1.5)\n",
    "\n",
    "axes[0].axhline(lif.V_th.to_decimal(u.mV), color='red', linestyle='--',\n",
    "                alpha=0.5, label='Threshold')\n",
    "axes[0].set_ylabel('Membrane Potential (mV)')\n",
    "axes[0].set_title('LIF Dynamics: Element-Wise Computation', fontweight='bold')\n",
    "axes[0].legend()\n",
    "axes[0].grid(alpha=0.3)\n",
    "\n",
    "# Spike rasters\n",
    "for i in range(3):\n",
    "    spike_times = times[spike_history[:, i]]\n",
    "    if len(spike_times) > 0:\n",
    "        axes[1].eventplot([spike_times.to_decimal(u.ms)], lineoffsets=[i],\n",
    "                          colors=[f'C{i}'], linewidths=2)\n",
    "\n",
    "axes[1].set_ylabel('Neuron Index')\n",
    "axes[1].set_xlabel('Time (ms)')\n",
    "axes[1].set_yticks(range(3))\n",
    "axes[1].set_ylim([-0.5, 2.5])\n",
    "axes[1].grid(alpha=0.3)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show()\n",
    "\n",
    "# Statistics\n",
    "for i in range(3):\n",
    "    n_spikes = jnp.sum(spike_history[:, i])\n",
    "    rate = n_spikes / duration * 1000 * u.Hz\n",
    "    print(f\"Neuron {i}: {n_spikes} spikes, rate = {rate:.2f}\")\n",
    "\n",
    "print(\"\\n✅ Each neuron evolves independently (element-wise)\")\n",
    "print(\"✅ Different inputs lead to different firing rates\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d233fec548fc9eea",
   "metadata": {},
   "source": [
    "## Part 3: Before/After Update Mechanism\n",
    "\n",
    "Dynamics supports flexible control flow through **before-update** and **after-update** hooks. These allow you to insert custom logic at specific points in the update cycle.\n",
    "\n",
    "### Basic Usage\n",
    "\n",
    "```python\n",
    "# Add functions to execute before/after update\n",
    "dynamics.add_before_update(key, function)\n",
    "dynamics.add_after_update(key, function)\n",
    "```\n",
    "\n",
    "### Default Behavior\n",
    "\n",
    "- **before_update**: Does NOT receive `update()` input parameters\n",
    "- **after_update**: DOES receive `update()` return value\n",
    "\n",
    "```python\n",
    "# Execution flow:\n",
    "for fn in before_updates:\n",
    "    fn()  # No parameters\n",
    "\n",
    "output = dynamics.update(inp)  # Main update\n",
    "\n",
    "for fn in after_updates:\n",
    "    fn(output)  # Receives output\n",
    "```\n",
    "\n",
    "### Custom Control\n",
    "\n",
    "You can modify this behavior using decorators:\n",
    "\n",
    "- `brainstate.nn.receive_update_input(fn)`: Make before_update receive input\n",
    "- `brainstate.nn.not_receive_update_output(fn)`: Make after_update NOT receive output"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a279fb222572705d",
   "metadata": {},
   "source": [
    "### Example: Monitoring with Before/After Updates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3d88f6cf3011e7f6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:02.197336Z",
     "start_time": "2025-10-11T09:49:01.947513Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running simulation with after-update monitoring...\n",
      "\n",
      "Step 1:\n",
      "  Spikes: [False False]\n",
      "  Total spikes so far: [0 0]\n",
      "\n",
      "Step 2:\n",
      "  Spikes: [False False]\n",
      "  Total spikes so far: [0 0]\n",
      "\n",
      "Step 3:\n",
      "  Spikes: [False False]\n",
      "  Total spikes so far: [0 0]\n",
      "\n",
      "Step 4:\n",
      "  Spikes: [False False]\n",
      "  Total spikes so far: [0 0]\n",
      "\n",
      "Step 5:\n",
      "  Spikes: [False False]\n",
      "  Total spikes so far: [0 0]\n",
      "\n",
      "Final statistics:\n",
      "  Min V: ArrayImpl([-65., -65.], dtype=float32) * mvolt\n",
      "  Max V: ArrayImpl([-65., -65.], dtype=float32) * mvolt\n",
      "  Total spikes: [0 0]\n",
      "\n",
      "✅ After-update hooks receive the output\n",
      "✅ Useful for monitoring, logging, and statistics\n"
     ]
    }
   ],
   "source": [
    "class MonitoredLIF(brainstate.nn.Dynamics):\n",
    "    \"\"\"LIF with monitoring hooks.\"\"\"\n",
    "\n",
    "    def __init__(self, size):\n",
    "        super().__init__(in_size=size)\n",
    "\n",
    "        # States\n",
    "        self.V = brainstate.State(jnp.ones(size) * -65.0 * u.mV)\n",
    "        self.spike = brainstate.State(jnp.zeros(size, dtype=bool))\n",
    "\n",
    "        # Monitoring statistics\n",
    "        self.min_V = brainstate.State(jnp.ones(size) * jnp.inf * u.mV)\n",
    "        self.max_V = brainstate.State(jnp.ones(size) * -jnp.inf * u.mV)\n",
    "        self.total_spikes = brainstate.State(jnp.zeros(size, dtype=int))\n",
    "\n",
    "        # Parameters\n",
    "        self.tau = 10.0 * u.ms\n",
    "        self.V_rest = -65.0 * u.mV\n",
    "        self.V_th = -50.0 * u.mV\n",
    "        self.V_reset = -65.0 * u.mV\n",
    "\n",
    "    def update(self, I):\n",
    "        # Update voltage\n",
    "        dt = brainstate.environ.get_dt()\n",
    "        alpha = jnp.exp(-dt / self.tau)\n",
    "        V_inf = self.V_rest + I * 1.0 * u.ohm\n",
    "        self.V.value = self.V.value * alpha + V_inf * (1 - alpha)\n",
    "\n",
    "        # Detect spikes\n",
    "        self.spike.value = self.V.value >= self.V_th\n",
    "        self.V.value = u.math.where(self.spike.value, self.V_reset, self.V.value)\n",
    "        return self.spike.value\n",
    "\n",
    "\n",
    "# Create neuron\n",
    "neuron = MonitoredLIF(size=(2,))\n",
    "\n",
    "\n",
    "# Define monitoring functions\n",
    "def before_check():\n",
    "    \"\"\"Check state before update (no parameters).\"\"\"\n",
    "    print(f\"  [Before] V = {neuron.V.value}\")\n",
    "\n",
    "\n",
    "def after_statistics(spikes):\n",
    "    \"\"\"Update statistics after update (receives output).\"\"\"\n",
    "    # Update min/max voltage\n",
    "    neuron.min_V.value = u.math.minimum(neuron.min_V.value, neuron.V.value)\n",
    "    neuron.max_V.value = u.math.maximum(neuron.max_V.value, neuron.V.value)\n",
    "    # Count spikes\n",
    "    neuron.total_spikes.value += spikes\n",
    "\n",
    "\n",
    "def after_log(spikes):\n",
    "    \"\"\"Log output after update (receives output).\"\"\"\n",
    "    if jnp.any(spikes):\n",
    "        print(f\"  [After] Spike detected! Neurons: {jnp.where(spikes)[0]}\")\n",
    "\n",
    "\n",
    "# Add hooks (only for demonstration, normally not called every step)\n",
    "neuron.add_after_update('statistics', after_statistics)\n",
    "\n",
    "print(\"Running simulation with after-update monitoring...\\n\")\n",
    "\n",
    "# Simulate for a few steps\n",
    "for i in range(5):\n",
    "    print(f\"Step {i + 1}:\")\n",
    "    I = jnp.array([3.0, 4.0]) * u.nA\n",
    "    spikes = neuron(I)\n",
    "    print(f\"  Spikes: {spikes}\")\n",
    "    print(f\"  Total spikes so far: {neuron.total_spikes.value}\\n\")\n",
    "\n",
    "print(\"Final statistics:\")\n",
    "print(f\"  Min V: {neuron.min_V.value}\")\n",
    "print(f\"  Max V: {neuron.max_V.value}\")\n",
    "print(f\"  Total spikes: {neuron.total_spikes.value}\")\n",
    "\n",
    "print(\"\\n\"\n",
    "      \"✅ After-update hooks receive the output\")\n",
    "print(\"✅ Useful for monitoring, logging, and statistics\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "52fbcd7eebdbd64",
   "metadata": {},
   "source": [
    "### Example: Custom Input/Output Control"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "177f8088a19c0e20",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:02.360505Z",
     "start_time": "2025-10-11T09:49:02.207279Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Running with custom input/output control:\n",
      "\n",
      "Step 1:\n",
      "  [Before with input] Received I = ArrayImpl([3.5], dtype=float32) * namp\n",
      "  [After without output] Current V = -65.0 * mvolt\n",
      "\n",
      "Step 2:\n",
      "  [Before with input] Received I = ArrayImpl([3.5], dtype=float32) * namp\n",
      "  [After without output] Current V = -65.0 * mvolt\n",
      "\n",
      "Step 3:\n",
      "  [Before with input] Received I = ArrayImpl([3.5], dtype=float32) * namp\n",
      "  [After without output] Current V = -65.0 * mvolt\n",
      "\n",
      "✅ receive_update_input: before-update receives input\n",
      "✅ not_receive_update_output: after-update doesn't receive output\n"
     ]
    }
   ],
   "source": [
    "# Create a new neuron for this example\n",
    "neuron2 = MonitoredLIF(size=(1,))\n",
    "\n",
    "\n",
    "# Before-update that RECEIVES input\n",
    "@brainstate.nn.receive_update_input\n",
    "class InputLogger:\n",
    "    def __call__(self, I):\n",
    "        print(f\"  [Before with input] Received I = {I}\")\n",
    "\n",
    "\n",
    "# After-update that DOES NOT receive output\n",
    "@brainstate.nn.not_receive_update_output\n",
    "class StateLogger:\n",
    "    def __init__(self, neuron):\n",
    "        self.neuron = neuron\n",
    "\n",
    "    def __call__(self):\n",
    "        print(f\"  [After without output] Current V = {self.neuron.V.value[0]}\")\n",
    "\n",
    "\n",
    "# Add custom hooks\n",
    "neuron2.add_before_update('input_log', InputLogger())\n",
    "neuron2.add_after_update('state_log', StateLogger(neuron2))\n",
    "\n",
    "print(\"Running with custom input/output control:\\n\")\n",
    "for i in range(3):\n",
    "    print(f\"Step {i + 1}:\")\n",
    "    neuron2(jnp.array([3.5]) * u.nA)\n",
    "    print()\n",
    "\n",
    "print(\"✅ receive_update_input: before-update receives input\")\n",
    "print(\"✅ not_receive_update_output: after-update doesn't receive output\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3074c73826d2d20",
   "metadata": {},
   "source": [
    "## Part 4: Input/Output Size Definition\n",
    "\n",
    "### Size Management\n",
    "\n",
    "Dynamics modules use `in_size` to define the geometry of the neuron population:\n",
    "\n",
    "```python\n",
    "# 1D population\n",
    "dynamics = MyDynamics(in_size=10)  # or in_size=(10,)\n",
    "\n",
    "# 2D population\n",
    "dynamics = MyDynamics(in_size=(10, 20))\n",
    "\n",
    "# 3D population\n",
    "dynamics = MyDynamics(in_size=(10, 20, 5))\n",
    "```\n",
    "\n",
    "### Key Attributes\n",
    "\n",
    "- **`in_size`**: Input shape (tuple)\n",
    "- **`out_size`**: Output shape (default: same as `in_size`)\n",
    "- **`varshape`**: Alias for `in_size` (variable shape)\n",
    "\n",
    "### Size Consistency\n",
    "\n",
    "This design ensures consistency with the `Module` class and enables seamless integration into larger network architectures."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "add245a0ccac9a40",
   "metadata": {},
   "source": [
    "### Example: Multi-Dimensional Populations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "891faca8c41b39da",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:02.941254Z",
     "start_time": "2025-10-11T09:49:02.367511Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1D Population:\n",
      "  in_size:  (10,)\n",
      "  out_size: (10,)\n",
      "  varshape: (10,)\n",
      "  V shape:  (10,)\n",
      "\n",
      "2D Population (8x8 grid):\n",
      "  in_size:  (8, 8)\n",
      "  out_size: (8, 8)\n",
      "  varshape: (8, 8)\n",
      "  V shape:  (8, 8)\n",
      "\n",
      "3D Population (4x4x4 volume):\n",
      "  in_size:  (4, 4, 4)\n",
      "  out_size: (4, 4, 4)\n",
      "  varshape: (4, 4, 4)\n",
      "  V shape:  (4, 4, 4)\n",
      "\n",
      "Applied 2D input with shape (8, 8)\n",
      "Got 2D output with shape (8, 8)\n",
      "Number of spikes: 0\n",
      "\n",
      "✅ Dynamics supports arbitrary dimensional populations\n",
      "✅ in_size defines the geometry of the population\n",
      "✅ Element-wise operations preserve dimensionality\n"
     ]
    }
   ],
   "source": [
    "# 1D population (line of neurons)\n",
    "pop_1d = SimpleLIF(size=10)\n",
    "print(\"1D Population:\")\n",
    "print(f\"  in_size:  {pop_1d.in_size}\")\n",
    "print(f\"  out_size: {pop_1d.out_size}\")\n",
    "print(f\"  varshape: {pop_1d.varshape}\")\n",
    "print(f\"  V shape:  {pop_1d.V.value.shape}\\n\")\n",
    "\n",
    "# 2D population (grid of neurons)\n",
    "pop_2d = SimpleLIF(size=(8, 8))\n",
    "print(\"2D Population (8x8 grid):\")\n",
    "print(f\"  in_size:  {pop_2d.in_size}\")\n",
    "print(f\"  out_size: {pop_2d.out_size}\")\n",
    "print(f\"  varshape: {pop_2d.varshape}\")\n",
    "print(f\"  V shape:  {pop_2d.V.value.shape}\\n\")\n",
    "\n",
    "# 3D population (volume of neurons)\n",
    "pop_3d = SimpleLIF(size=(4, 4, 4))\n",
    "print(\"3D Population (4x4x4 volume):\")\n",
    "print(f\"  in_size:  {pop_3d.in_size}\")\n",
    "print(f\"  out_size: {pop_3d.out_size}\")\n",
    "print(f\"  varshape: {pop_3d.varshape}\")\n",
    "print(f\"  V shape:  {pop_3d.V.value.shape}\\n\")\n",
    "\n",
    "# Demonstrate element-wise operation with 2D input\n",
    "I_2d = brainstate.random.randn(8, 8) * u.nA\n",
    "spikes_2d = pop_2d(I_2d)\n",
    "\n",
    "print(f\"Applied 2D input with shape {I_2d.shape}\")\n",
    "print(f\"Got 2D output with shape {spikes_2d.shape}\")\n",
    "print(f\"Number of spikes: {jnp.sum(spikes_2d)}\")\n",
    "\n",
    "print(\"\\n✅ Dynamics supports arbitrary dimensional populations\")\n",
    "print(\"✅ in_size defines the geometry of the population\")\n",
    "print(\"✅ Element-wise operations preserve dimensionality\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "37c786a93c8b6658",
   "metadata": {},
   "source": [
    "## Part 5: Delay Support Mechanism\n",
    "\n",
    "Dynamics naturally supports **temporal delays** through the after-update mechanism, which is crucial for neural dynamics modeling.\n",
    "\n",
    "### Two Types of Delays\n",
    "\n",
    "#### 1. Output Delay\n",
    "\n",
    "Delay the output of `update()` for downstream modules:\n",
    "\n",
    "```python\n",
    "# Create delayed output reference\n",
    "delayed_output = dynamics.output_delay(5.0 * u.ms)\n",
    "\n",
    "# Access delayed value\n",
    "value = delayed_output()\n",
    "```\n",
    "\n",
    "#### 2. State Delay (Prefetch Delay)\n",
    "\n",
    "Delay a specific state variable:\n",
    "\n",
    "```python\n",
    "# Prefetch delayed state (before init_state is called)\n",
    "delayed_V = dynamics.prefetch_delay('V', delay_time=5.0 * u.ms)\n",
    "\n",
    "# Access delayed voltage\n",
    "v_delayed = delayed_V()\n",
    "```\n",
    "\n",
    "### Automatic Synchronization\n",
    "\n",
    "After each `update()`, the delay buffer is automatically updated through the after-update hook. No manual management required!\n",
    "\n",
    "### Use Cases\n",
    "\n",
    "- Axonal delays\n",
    "- Synaptic delays\n",
    "- Feedback connections\n",
    "- Time-delayed systems"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d03b5f1de8cccead",
   "metadata": {},
   "source": [
    "### Example: Output Delay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "be45b27be04b3d4e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:04.319908Z",
     "start_time": "2025-10-11T09:49:02.947260Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Simulating with output delays...\n",
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✅ Output delay shifts spikes in time\n",
      "✅ Multiple delays can coexist\n",
      "✅ Delays are automatically managed\n"
     ]
    }
   ],
   "source": [
    "# Create neuron\n",
    "neuron = SimpleLIF(size=(1,))\n",
    "\n",
    "# Create delayed output references\n",
    "output_now = neuron  # No delay\n",
    "output_delayed_2ms = neuron.output_delay(2.0 * u.ms)\n",
    "output_delayed_5ms = neuron.output_delay(5.0 * u.ms)\n",
    "\n",
    "brainstate.nn.init_all_states(neuron)\n",
    "print(\"Simulating with output delays...\\n\")\n",
    "\n",
    "# Simulate\n",
    "n_steps = 200\n",
    "history_now = []\n",
    "history_2ms = []\n",
    "history_5ms = []\n",
    "\n",
    "for i in range(n_steps):\n",
    "    t = i * brainstate.environ.get_dt()\n",
    "    with brainstate.environ.context(t=t, i=i):\n",
    "        # Update neuron (immediate output)\n",
    "        spike_now = neuron(30.0 * u.mA)\n",
    "\n",
    "        # Access delayed outputs\n",
    "        spike_2ms = output_delayed_2ms()\n",
    "        spike_5ms = output_delayed_5ms()\n",
    "\n",
    "        history_now.append(spike_now[0])\n",
    "        history_2ms.append(spike_2ms[0])\n",
    "        history_5ms.append(spike_5ms[0])\n",
    "\n",
    "history_now = jnp.where(jnp.array(history_now))[0]\n",
    "history_2ms = jnp.where(jnp.array(history_2ms))[0]\n",
    "history_5ms = jnp.where(jnp.array(history_5ms))[0]\n",
    "times = jnp.arange(n_steps) * brainstate.environ.get_dt()\n",
    "\n",
    "# Visualize\n",
    "plt.figure(figsize=(14, 6))\n",
    "\n",
    "# Find spike times\n",
    "spikes_now = times[history_now]\n",
    "spikes_2ms = times[history_2ms]\n",
    "spikes_5ms = times[history_5ms]\n",
    "\n",
    "if len(spikes_now) > 0:\n",
    "    plt.eventplot(\n",
    "        [spikes_now.to_decimal(u.ms)],\n",
    "        lineoffsets=[0],\n",
    "        colors='blue',\n",
    "        linewidths=2,\n",
    "        label='No delay'\n",
    "    )\n",
    "if len(spikes_2ms) > 0:\n",
    "    plt.eventplot(\n",
    "        [spikes_2ms.to_decimal(u.ms)],\n",
    "        lineoffsets=[1],\n",
    "        colors='orange',\n",
    "        linewidths=2,\n",
    "        label='2ms delay'\n",
    "    )\n",
    "if len(spikes_5ms) > 0:\n",
    "    plt.eventplot(\n",
    "        [spikes_5ms.to_decimal(u.ms)],\n",
    "        lineoffsets=[2],\n",
    "        colors='red',\n",
    "        linewidths=2,\n",
    "        label='5ms delay'\n",
    "    )\n",
    "\n",
    "plt.yticks([0, 1, 2], ['Now', '2ms', '5ms'])\n",
    "plt.xlabel('Time (ms)')\n",
    "plt.ylabel('Delay')\n",
    "plt.title('Output Delay Mechanism', fontweight='bold')\n",
    "plt.legend()\n",
    "plt.grid(alpha=0.3)\n",
    "plt.show()\n",
    "\n",
    "print(\"✅ Output delay shifts spikes in time\")\n",
    "print(\"✅ Multiple delays can coexist\")\n",
    "print(\"✅ Delays are automatically managed\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e73f875251734a6",
   "metadata": {},
   "source": [
    "### Example: State Delay (Prefetch Delay)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9678f9b8a392febb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:05.305541Z",
     "start_time": "2025-10-11T09:49:04.466890Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1400x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "✅ prefetch_delay accesses delayed state variables\n",
      "✅ Delayed feedback creates oscillatory dynamics\n",
      "✅ Delay buffer is automatically synchronized after update()\n"
     ]
    }
   ],
   "source": [
    "class DelayedFeedbackLIF(brainstate.nn.Dynamics):\n",
    "    \"\"\"LIF with delayed self-feedback.\"\"\"\n",
    "\n",
    "    def __init__(self, size, feedback_delay=3.0 * u.ms, feedback_strength=0.5):\n",
    "        super().__init__(in_size=size)\n",
    "\n",
    "        # Create delayed voltage reference\n",
    "        self.V_delayed = self.prefetch_delay('V', feedback_delay)\n",
    "\n",
    "        # Parameters\n",
    "        self.tau = 10.0 * u.ms\n",
    "        self.V_rest = -65.0 * u.mV\n",
    "        self.V_th = -50.0 * u.mV\n",
    "        self.V_reset = -65.0 * u.mV\n",
    "        self.feedback_strength = feedback_strength\n",
    "\n",
    "    def init_state(self, *args, **kwargs):\n",
    "        self.V = brainstate.State(jnp.ones(self.varshape) * -65.0 * u.mV)\n",
    "        self.spike = brainstate.State(jnp.zeros(self.varshape, dtype=bool))\n",
    "\n",
    "    def update(self, I):\n",
    "        # Get delayed voltage for feedback\n",
    "        V_delayed = self.V_delayed()\n",
    "\n",
    "        # Add delayed feedback to input\n",
    "        feedback_current = (V_delayed - self.V_rest) * self.feedback_strength / (1.0 * u.ohm)\n",
    "        I_total = I + feedback_current\n",
    "\n",
    "        # Update voltage\n",
    "        dt = brainstate.environ.get_dt()\n",
    "        alpha = jnp.exp(-dt / self.tau)\n",
    "        V_inf = self.V_rest + I_total * 1.0 * u.ohm\n",
    "        self.V.value = self.V.value * alpha + V_inf * (1 - alpha)\n",
    "\n",
    "        # Spike\n",
    "        self.spike.value = self.V.value >= self.V_th\n",
    "        self.V.value = u.math.where(self.spike.value, self.V_reset, self.V.value)\n",
    "\n",
    "        return self.spike.value\n",
    "\n",
    "\n",
    "# Create neurons: one with feedback, one without\n",
    "neuron_no_fb = SimpleLIF(size=(1,))\n",
    "neuron_fb = DelayedFeedbackLIF(size=(1,), feedback_delay=3.0 * u.ms, feedback_strength=0.3)\n",
    "\n",
    "brainstate.nn.init_all_states(neuron_no_fb)\n",
    "brainstate.nn.init_all_states(neuron_fb)\n",
    "\n",
    "# Simulate both\n",
    "n_steps = 150\n",
    "V_no_fb = []\n",
    "V_fb = []\n",
    "\n",
    "for i in range(n_steps):\n",
    "    t = i * brainstate.environ.get_dt()\n",
    "    with brainstate.environ.context(t=t, i=i):\n",
    "        neuron_no_fb(28.0 * u.mA)\n",
    "        neuron_fb(28.0 * u.mA)\n",
    "        V_no_fb.append(neuron_no_fb.V.value[0])\n",
    "        V_fb.append(neuron_fb.V.value[0])\n",
    "\n",
    "V_no_fb = u.math.array(V_no_fb)\n",
    "V_fb = u.math.array(V_fb)\n",
    "times = jnp.arange(n_steps) * brainstate.environ.get_dt()\n",
    "\n",
    "# Plot\n",
    "plt.figure(figsize=(14, 6))\n",
    "plt.plot(\n",
    "    times.to_decimal(u.ms),\n",
    "    V_no_fb.to_decimal(u.mV),\n",
    "    label='No feedback',\n",
    "    linewidth=1.5,\n",
    "    alpha=0.8\n",
    ")\n",
    "plt.plot(\n",
    "    times.to_decimal(u.ms),\n",
    "    V_fb.to_decimal(u.mV),\n",
    "    label='With delayed feedback (3ms)',\n",
    "    linewidth=1.5,\n",
    "    alpha=0.8\n",
    ")\n",
    "plt.axhline(-50, color='red', linestyle='--', alpha=0.5, label='Threshold')\n",
    "plt.xlabel('Time (ms)')\n",
    "plt.ylabel('Membrane Potential (mV)')\n",
    "plt.title('State Delay: Delayed Self-Feedback', fontweight='bold')\n",
    "plt.legend()\n",
    "plt.grid(alpha=0.3)\n",
    "plt.show()\n",
    "\n",
    "print(\"✅ prefetch_delay accesses delayed state variables\")\n",
    "print(\"✅ Delayed feedback creates oscillatory dynamics\")\n",
    "print(\"✅ Delay buffer is automatically synchronized after update()\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "428bb19dcc3fef2a",
   "metadata": {},
   "source": [
    "## Part 6: Ecosystem Integration\n",
    "\n",
    "The Dynamics protocol is the foundation of the BrainPy ecosystem, providing a unified interface across multiple systems:\n",
    "\n",
    "### **brainpy.state** - General Dynamical Systems\n",
    "\n",
    "Implements common neuron models (LIF, HH, Izhikevich) and synapse models (Exponential, Alpha, NMDA)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f71f7681d67df776",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:07.764615Z",
     "start_time": "2025-10-11T09:49:05.478944Z"
    }
   },
   "outputs": [],
   "source": [
    "import brainpy\n",
    "\n",
    "# All follow the Dynamics protocol\n",
    "lif = brainpy.state.LIF(100)\n",
    "hh = brainpy.state.ALIF(50)\n",
    "syn = brainpy.state.Expon(100, tau=5.0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9c76960c989ed0",
   "metadata": {},
   "source": [
    "\n",
    "### **brainmass** - Neural Mass Models\n",
    "\n",
    "Large-scale brain modeling with population dynamics."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "96a54b90cb598ad4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:07.987082Z",
     "start_time": "2025-10-11T09:49:07.904940Z"
    }
   },
   "outputs": [],
   "source": [
    "import brainmass\n",
    "wilson_cowan = brainmass.WilsonCowanModel((10, 10))\n",
    "jansen_rit = brainmass.JansenRitModel(5)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6675fa2f4fd1053c",
   "metadata": {},
   "source": [
    "\n",
    "### **braincell** - Detailed Neuron Models\n",
    "\n",
    "Multi-compartment neurons with dendritic dynamics.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "99857cf9aee9eeb5",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:08.045826Z",
     "start_time": "2025-10-11T09:49:07.991826Z"
    }
   },
   "outputs": [],
   "source": [
    "import braincell\n",
    "ca = braincell.channel.ICaT_HM1992(10)\n",
    "na = braincell.ion.Sodium(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fb93666039c8aa0",
   "metadata": {},
   "source": [
    "\n",
    "### Unified Benefits\n",
    "\n",
    "✅ **Same API** - All use `update()`, before/after updates, delays\n",
    "✅ **Composable** - Mix and match across systems\n",
    "✅ **Consistent** - Learn once, use everywhere\n",
    "✅ **Scalable** - From single neurons to whole brain models"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e3b8afd2f8f451d",
   "metadata": {},
   "source": [
    "## Summary\n",
    "\n",
    "### Key Takeaways\n",
    "\n",
    "#### 1. **Dynamics Concept**\n",
    "- Defines **element-wise** temporal evolution of state variables\n",
    "- Does NOT include inter-neuron connectivity\n",
    "- Foundation for all dynamical systems in the ecosystem\n",
    "\n",
    "#### 2. **Basic Structure**\n",
    "- Implement `update(inp)` to define state evolution\n",
    "- Use `brainstate.State` for dynamic variables\n",
    "- Use regular Python variables for constants\n",
    "\n",
    "#### 3. **Before/After Updates**\n",
    "- `add_before_update(key, fn)` - Execute before `update()`\n",
    "- `add_after_update(key, fn)` - Execute after `update()`\n",
    "- Control parameter passing with decorators\n",
    "\n",
    "#### 4. **Size Management**\n",
    "- `in_size` defines population geometry\n",
    "- `out_size` typically matches `in_size`\n",
    "- `varshape` is an alias for `in_size`\n",
    "\n",
    "#### 5. **Delay Support**\n",
    "- `output_delay(time)` - Delay the output\n",
    "- `prefetch_delay(state, time)` - Delay a specific state\n",
    "- Automatic synchronization through after-updates\n",
    "\n",
    "#### 6. **Ecosystem Integration**\n",
    "- Unified interface across brainpy.state, brainmass, braincell\n",
    "- Composable and interoperable\n",
    "- Learn once, use everywhere\n",
    "\n",
    "### Best Practices\n",
    "\n",
    "✅ **Always call `super().__init__(in_size=size)`** in `__init__`  \n",
    "✅ **Use `brainstate.State` for variables that change** during simulation  \n",
    "✅ **Use regular variables for constants** (parameters, time constants)  \n",
    "✅ **Return meaningful outputs** from `update()` (spikes, voltages, etc.)  \n",
    "✅ **Use delays through the protocol** rather than manual buffering  \n",
    "✅ **Leverage before/after updates** for monitoring and statistics\n",
    "\n",
    "### Protocol Summary\n",
    "\n",
    "```python\n",
    "class MyDynamics(brainstate.nn.Dynamics):\n",
    "    def __init__(self, in_size, **params):\n",
    "        super().__init__(in_size=in_size)\n",
    "        \n",
    "        # States (dynamic variables)\n",
    "        self.state = brainstate.State(initial_value)\n",
    "        \n",
    "        # Parameters (constants)\n",
    "        self.param = value\n",
    "        \n",
    "        # Optional: prefetch delays\n",
    "        self.state_delayed = self.prefetch_delay('state', delay_time)\n",
    "        \n",
    "    def update(self, inp):\n",
    "        # 1. Compute new state values\n",
    "        # 2. Update self.state.value\n",
    "        # 3. Return output\n",
    "        return output\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23a45d683608e7df",
   "metadata": {},
   "source": [
    "## Exercise: Implement Your Own Dynamics\n",
    "\n",
    "### Task\n",
    "\n",
    "Implement a simplified **Izhikevich neuron** model:\n",
    "\n",
    "$$\n",
    "\\frac{dv}{dt} = 0.04v^2 + 5v + 140 - u + I\n",
    "$$\n",
    "$$\n",
    "\\frac{du}{dt} = a(bv - u)\n",
    "$$\n",
    "\n",
    "When $v \\geq 30$: spike, then $v \\leftarrow c$, $u \\leftarrow u + d$\n",
    "\n",
    "### Requirements\n",
    "\n",
    "1. Inherit from `brainstate.nn.Dynamics`\n",
    "2. Define states `v` and `u`\n",
    "3. Define parameters `a`, `b`, `c`, `d`\n",
    "4. Implement `update(I)` with Euler integration\n",
    "5. Return spike events\n",
    "\n",
    "### Starter Code"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "3374b2b0ee91439f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-10-11T09:49:08.055213Z",
     "start_time": "2025-10-11T09:49:08.051770Z"
    }
   },
   "outputs": [],
   "source": [
    "class Izhikevich(brainstate.nn.Dynamics):\n",
    "    \"\"\"Izhikevich neuron model.\"\"\"\n",
    "\n",
    "    def __init__(self, size, a=0.02, b=0.2, c=-65.0, d=8.0):\n",
    "        # TODO: Initialize parent class\n",
    "        # TODO: Create states v and u\n",
    "        # TODO: Store parameters a, b, c, d\n",
    "        pass\n",
    "\n",
    "    def update(self, I):\n",
    "        # TODO: Implement Euler integration\n",
    "        # TODO: Detect spikes (v >= 30)\n",
    "        # TODO: Reset v and u when spike occurs\n",
    "        # TODO: Return spike events\n",
    "        pass\n",
    "\n",
    "# Test your implementation\n",
    "# izh = Izhikevich(size=1)\n",
    "# for i in range(100):\n",
    "#     spike = izh(jnp.array([10.0]))\n",
    "#     if spike[0]:\n",
    "#         print(f\"Spike at step {i}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9e0adebf175d9a1",
   "metadata": {},
   "source": [
    "### Solution Hints\n",
    "\n",
    "<details>\n",
    "<summary>Click to show hints</summary>\n",
    "\n",
    "1. **Initialization**:\n",
    "   ```python\n",
    "   super().__init__(in_size=size)\n",
    "   self.v = brainstate.State(jnp.ones(size) * -65.0)\n",
    "   self.u = brainstate.State(jnp.ones(size) * b * -65.0)\n",
    "   ```\n",
    "\n",
    "2. **Euler integration**:\n",
    "   ```python\n",
    "   dt = brainstate.environ.get_dt().to_decimal(u.ms)\n",
    "   dv = (0.04 * v**2 + 5*v + 140 - u + I) * dt\n",
    "   du = a * (b*v - u) * dt\n",
    "   ```\n",
    "\n",
    "3. **Spike detection and reset**:\n",
    "   ```python\n",
    "   spike = v >= 30\n",
    "   v = jnp.where(spike, c, v)\n",
    "   u = jnp.where(spike, u + d, u)\n",
    "   ```\n",
    "\n",
    "</details>\n",
    "\n",
    "### Further Exploration\n",
    "\n",
    "- Add delayed self-feedback using `prefetch_delay`\n",
    "- Add monitoring using before/after updates\n",
    "- Implement different Izhikevich neuron types (RS, IB, CH, FS)\n",
    "- Combine with synaptic models from brainpy.state"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "resources",
   "metadata": {},
   "source": [
    "## Additional Resources\n",
    "\n",
    "### Documentation\n",
    "- [BrainState API Reference](https://brainstate.readthedocs.io/)\n",
    "- [BrainPy Documentation](https://brainpy.readthedocs.io/)\n",
    "- [BrainScale Documentation](https://brainscale.readthedocs.io/)\n",
    "\n",
    "### Related Tutorials\n",
    "- `06_delay_basics.ipynb` - Detailed delay mechanisms\n",
    "- `01_module_basics.ipynb` - Module system fundamentals\n",
    "- `02_state_management.ipynb` - State management in depth\n",
    "\n",
    "### Papers\n",
    "- Izhikevich, E. M. (2003). Simple model of spiking neurons. IEEE Transactions on neural networks.\n",
    "- Brette, R., & Gerstner, W. (2005). Adaptive exponential integrate-and-fire model.\n",
    "- Gerstner, W., et al. (2014). Neuronal Dynamics: From Single Neurons to Networks and Models of Cognition."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Ecosystem-py",
   "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": "3.11.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
