{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BnoPtme4om-8",
        "outputId": "4db8efdc-e9ca-421b-8109-6cff01e6b9dc"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m9.2/9.2 MB\u001b[0m \u001b[31m76.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m40.1/40.1 MB\u001b[0m \u001b[31m18.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m63.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m300.4/300.4 kB\u001b[0m \u001b[31m21.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m45.2/45.2 kB\u001b[0m \u001b[31m3.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m168.7/168.7 kB\u001b[0m \u001b[31m11.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m115.0/115.0 kB\u001b[0m \u001b[31m9.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m51.1/51.1 kB\u001b[0m \u001b[31m3.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m203.1/203.1 kB\u001b[0m \u001b[31m12.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m51.5/51.5 kB\u001b[0m \u001b[31m3.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m48.1/48.1 MB\u001b[0m \u001b[31m16.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ],
      "source": [
        "!pip install -q pycbc lalsuite gwpy gwosc astropy"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "from pycbc.waveform import get_td_waveform\n",
        "import pycbc.waveform\n",
        "from pycbc.filter import match\n",
        "from pycbc.psd import aLIGOZeroDetHighPower\n",
        "from pycbc.psd import interpolate, inverse_spectrum_truncation"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hJ9Y2R4zoxc8",
        "outputId": "71c370e7-0dbe-477b-cf50-dd21093eadf5"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/lib/python3.12/importlib/__init__.py:90: UserWarning: Wswiglal-redir-stdio:\n",
            "\n",
            "SWIGLAL standard output/error redirection is enabled in IPython.\n",
            "This may lead to performance penalties. To disable locally, use:\n",
            "\n",
            "with lal.no_swig_redirect_standard_output_error():\n",
            "    ...\n",
            "\n",
            "To disable globally, use:\n",
            "\n",
            "lal.swig_redirect_standard_output_error(False)\n",
            "\n",
            "Note however that this will likely lead to error messages from\n",
            "LAL functions being either misdirected or lost when called from\n",
            "Jupyter notebooks.\n",
            "\n",
            "To suppress this warning, use:\n",
            "\n",
            "import warnings\n",
            "warnings.filterwarnings(\"ignore\", \"Wswiglal-redir-stdio\")\n",
            "import lal\n",
            "\n",
            "  return _bootstrap._gcd_import(name[level:], package, level)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "mass1 = 20.0  # m1\n",
        "mass2 = 20.0  # m2\n",
        "f_lower = 20.0  # starting frequency in Hz\n",
        "delta_t = 1.0 / 4096\n",
        "\n",
        "# to generate waveforms using the pycbc package, use the following function:\n",
        "\n",
        "hp, hc = pycbc.waveform.get_td_waveform(\n",
        "    approximant=\"TaylorT4\",\n",
        "    mass1=mass1,\n",
        "    mass2=mass2,\n",
        "    f_lower=f_lower,\n",
        "    delta_t=delta_t\n",
        ")\n",
        "\n",
        "plt.plot(hp.sample_times, hp)"
      ],
      "metadata": {
        "id": "xra9gATYpBTE",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 462
        },
        "outputId": "d842890b-c22f-4006-843e-5ffc4b457af0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[<matplotlib.lines.Line2D at 0x7b77f7853fe0>]"
            ]
          },
          "metadata": {},
          "execution_count": 2
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAiIAAAGsCAYAAADg5swfAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjAsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvlHJYcgAAAAlwSFlzAAAPYQAAD2EBqD+naQAAwg9JREFUeJztfXmcZVV17jrn3lu3qnpuuqFpaZpJJplBWnAApaMYX4RnoonPBDAEY4IxCcYn/RLhoSaNwWhefATNAJhERYkieXEgRhA1MgsyKEMjQzM1Q9NVPVXVHc7749599tprr7X3vt1dfW93re/3619XnbPPPvvcqrr7u9/61lpZURQFKBQKhUKhUPQBeb8XoFAoFAqFYuZCiYhCoVAoFIq+QYmIQqFQKBSKvkGJiEKhUCgUir5BiYhCoVAoFIq+QYmIQqFQKBSKvkGJiEKhUCgUir5BiYhCoVAoFIq+QYmIQqFQKBSKvkGJiEKhUCgUir5hlyEiP/jBD+BXfuVXYOnSpZBlGXzjG9/o+/3WrVsH55xzDixduhRGR0fh9NNPh0ceeWRa16VQKBQKxe6EXYaIbN68GY4++mi4/PLLB+J+RVHAmWeeCb/4xS/g+uuvh7vvvhuWL18OK1euhM2bN++UNSoUCoVCsasj2xWb3mVZBtdddx2ceeaZ5bHJyUn40z/9U/jyl78MGzZsgCOOOAI++clPwqmnnjot93v44YfhkEMOgfvvvx9e9apXAQBAu92GJUuWwF/8xV/A7/zO72z3fRUKhUKh2N2xyygiMXzgAx+AW265Ba655hq499574Z3vfOe0hkomJycBAGB4eLg8luc51Ot1+NGPfjQt91QoFAqFYnfDbkFEnnzySbjqqqvg2muvhde//vVw4IEHwp/8yZ/A6173Orjqqqum5Z6HHnoo7LvvvrBq1Sp4+eWXYWpqCj75yU/CU089Bc8+++y03FOhUCgUit0NuwURue+++6DVasHBBx8Ms2fPLv/dfPPN8OijjwIAwIMPPghZlgX/XXjhhcn3rNVq8PWvfx0efvhhWLhwIYyOjsJNN90Eb33rWyHPd4uXVaFQKBSKaUe13wvYEdi0aRNUKhW46667oFKpOOdmz54NAAAHHHAA/PznPw/Os8cee/R03+OPPx7uueceGBsbg6mpKVi8eDGsWLECTjjhhN4eQKFQKBSKGYrdgogce+yx0Gq14Pnnn4fXv/717JihoSE49NBDp+X+8+bNAwCARx55BO688074+Mc/Pi33USgUCoVid8MuQ0Q2bdoEa9asKb9/7LHH4J577oGFCxfCwQcfDO95z3vgrLPOgr/6q7+CY489Fl544QX43ve+B0cddRS87W1v26H323fffQEA4Nprr4XFixfDvvvuC/fddx/84R/+IZx55pnw5je/efsfWKFQKBSKGYBdJn33+9//PrzxjW/0jp999tlw9dVXQ6PRgE984hPwT//0T/D000/DokWL4DWveQ1ccsklcOSRR+7w+wEA/M3f/A1cdtllsG7dOth7773hrLPOgo9+9KMwNDTU8/0UCoVCoZiJ2GWIiEKhUCgUit0Pmt6hUCgUCoWib1AiolAoFAqFom8YaLNqu92GZ555BubMmQNZlvV7OQqFQqFQKBJQFAVs3LgRli5dGq2tNdBE5JlnnoFly5b1exkKhUKhUCi2AWvXroV99tknOGagicicOXMAoPMgc+fO7fNqFAqFQqFQpGB8fByWLVtW7uMhDDQRMeGYuXPnKhFRKBQKhWIXQ4qtQs2qCoVCoVAo+gYlIgqFQqFQKPqGaSUiV1xxBRx11FFlaOWkk06Cb3/729N5S4VCoVAoFLsQppWI7LPPPnDppZfCXXfdBXfeeSe86U1vgjPOOAMeeOCB6bytQqFQKBSKXQQ7vcT7woUL4bLLLoNzzz03OnZ8fBzmzZsHY2NjalZVKBQKhWIXQS/7907Lmmm1WnDttdfC5s2b4aSTTmLHTE5OwuTkZPn9+Pj4zlqeQqFQKBSKPmDazar33XcfzJ49G+r1Orz//e+H6667Dg4//HB27OrVq2HevHnlPy1mplAoFArF7o1pD81MTU3Bk08+CWNjY/Cv//qv8A//8A9w8803s2SEU0SWLVumoRmFQqFQKHYh9BKa2ekekZUrV8KBBx4In//856Nj1SOiUCgUCsWuh172751eR6Tdbjuqh0KhUCgUipmLaTWrrlq1Ct761rfCvvvuCxs3boQvfelL8P3vfx9uuOGG6bytQqFQKBSKXQTTSkSef/55OOuss+DZZ5+FefPmwVFHHQU33HAD/NIv/dJ03lahUCgUCsUugmklIv/4j/84ndMrFAqFQqHYBtz1xMvws2fG4DdfszypMd10YqC77yoUCoVCodjx+NUrfgwAAK9YMAJvOnSvvq5Fm94pFAqFQjFDseb5Tf1eghIRhUKhUChmKto7tYAHDyUiCoVCoVDMULQGgIkoEVEoFAqFYoZiJ9c0ZaFERKFQKBSKGYpWu98rUCKiUCgUCsWMRVsVEYVCoVAoFP2ChmYUCoVCoVD0DS0lIgqFQqFQKPoF9YgoFAqFQqGY0VAiolAoFAqFom9QIqJQKBQKhaJvUCKiUCgUCsUMRQFqVlUoFAqFQjGDoUREoVAoFApF36BERKFQKBQKRd+gREShUCgUipmK/ltElIgoFAqFQjET8OM1L8In/v1nMNls9XspDqr9XoBCoVAoFIrpx//4h9sAAGDPufU+r8SFKiIKhUKhUMwgPPbiln4vwYESEYVCoVAoFH2DEhGFQqFQKGYUCuar/kGJiEKhUCgUMwjFILAPBCUiCoVCoVAo+gYlIgqFQqFQzCDkedbvJThQIqJQKBQKxQxCFRGRYgDiNEpEFAqFQqGYQcgzVUQUCoVCoVD0CZiHZANASpSIKBQKhUKh6BuUiCgUCoVCsZviurufglsefck5NgC2EAfaa0ahUCgUit0QDz43Dn/8lZ8CAMDjl76NHaNmVYVCoVAoFNOCp1/eyh4fBPKBoUREoVAoFIrdENiH2m4PVll3DCUiCoVCoVDshsjAMpGJZquPKwlDiYhCoVAoFLshCqR9TDba9jiSRAYhSqNERKFQKBSK3RCNlmUZLcQ42oPAPhCUiCgUCoVCsRuiiYlIGxORfqxGhhIRhUKhUCh2Q2AVpInNqqqIKBQKhUKhmA78611PwUe/cT+024VDOFqtwQ3NaEEzhUKhUCh2E/zJtZ0CZq975SLHiNpoW7MqDs0MAiVRRUShUCgUit0MG7ZMOVkzrkdkEOiHhRIRhUKhUCh2A+BQTJ5lgEQQh4gMGA9RIqJQKBQKxe6ACVQrJM8yJ+yiiohCoVAoFIppxUTDVk+tVjJHIWkK6buDwEmmlYisXr0aXv3qV8OcOXNgzz33hDPPPBMeeuih6bylQqFQKBQzBkVRlGoHVTrwty3HrDoA7ANhWonIzTffDOeffz7ceuut8N3vfhcajQa8+c1vhs2bN0/nbRUKhUKh2O1RFAW883O3wFv++gfQaLUdpaPVLhyzKi5uNmh1RKY1ffc73/mO8/3VV18Ne+65J9x1113whje8YTpvrVAoFArFbo0tUy2484mXAQDgiZc2w9yRWnmu1S48YmKATayDgJ1aR2RsbAwAABYuXMien5ychMnJyfL78fHxnbIuhUKhUCh2NWzY2ii/brVpKKZwvncqqw5E9RCLnWZWbbfb8Ed/9Efw2te+Fo444gh2zOrVq2HevHnlv2XLlu2s5SkUCoVCsUuh0bTSxpappuP9aBWF+72QvjsIpGSnEZHzzz8f7r//frjmmmvEMatWrYKxsbHy39q1a3fW8hQKhUKh2KWAVQ6qgHQ8IvxYfDyDbPoWmIidEpr5wAc+AP/+7/8OP/jBD2CfffYRx9XrdajX6ztjSQqFQqFQ7FIY29KAz974CLzjuH3g8KVzoYnMHo2Wr4BUkdTQbNmxA+ZVnV5FpCgK+MAHPgDXXXcd3HjjjbD//vtP5+0UCoVCodhtccn/ewD+4UePwRmX/wgA3EwYThHBZtW2Qz4Gi4lMqyJy/vnnw5e+9CW4/vrrYc6cOfDcc88BAMC8efNgZGRkOm+tUCgUCsVuhVt/8RIAdNQPADfc0mi3PSJSzV3PiAEmJVn/IzPTq4hcccUVMDY2Bqeeeirsvffe5b+vfOUr03lbhUKhUCh2O9Sq7paNwy0tGpopiCIywCXep1URGbSiKQqFQqFQ7CrYPNmEoWoOtUqHgOREvsCKSLPddolIq4AC7fAtocT7IEB7zSgUCoVCMWAYn2jA8Z/4Lpx5+X+JY7BHpEkLmBWFIwZgkjJoIoESEYVCoVAoBgx3PLYeJhpteOCZ8TKsQu0cDZQ10yElsnm1LZKSHbrsbYISEYVCoVAoBgx5bmnHxslm5wvCRFoBRaQoKPmw5watxLsSEYVCoVAo+oxnx7bC2BZbsn1iqlV+PdWtoEoVkaajiLQ91QOLHdgjgjNoZlRlVYVCoVAoFD5e2jQJJ62+EV77yRvLY1MoIwZ/jdEk5MINxYAYmik0NKNQKBQKhcLgp09tAACATZPNMiW3gcIupSJCs2ZabuilTZQOqdeMZs0oFAqFQqEoMdW0zGDjRMcPgmuENBIUkTYxp1Kloy2oI4MAJSIKhUKhUOwk/PzZcXj9X94IX7vrqfIYJhqTXfUDk4ypJk9EqCfE+b5duEXMBEVkEFJ5lYgoFAqFQrGT8GffuB/Wrt8KH7r2p+UxbDo1pKPJkBOqZBQkK8bziAD+XuuIKBQKhUIx4/Hy5invWAOFZqZanWwZp49Ml5RgVaNgSriHFJKWVEdkWx5iB0OJiEKhUCgU04Dzv/QTePv//RFsmWqWxyaZMAvOiplo+KEZQ0BoN12feNjzBc2icebD49KfZ7qgREShUCgUih2MRqsN37z3Wbj3qTG48/GXy+OV3G9322RSdfGxZklE3CwYSkywvuGHZvDXA8A+EJSIKBQKhUKxHXhx0yTc/PALjvcCh2Bw6ixHRLhUXVojBMCvC0J7yTiKCLjnW05Yxx3XbygRUSgUCoViO/A///VeOPvK2+E79z9XHhvbiqqkNmyVVIaHuMXLSrOqH5qhxIJmxdDMmIKEauw5LWimUCgUCsUuCawsGNz44PMAAPCVO9eWx7AXBBMNPjTjqx9YETFf0ywY3zNivy8SzaqDACUiCoVCoVAk4K//82E45pL/gEfWbWTPY4rh1AZp2K85DoDHGlWjyRzDaLfBIxo4zNJuyx4RNzTTfygRUSgUCoUiAX/9n4/AxskmXHbDQ+x5vNnjImSTiFTgjd+ESxqMMZXziGCiQ3vLeFkyTIEzfM5exz7KToUSEYVCoVAoED76jfvhvVfd7qgSKcAbPDagTiKPCGcgbTB+EFzkjAsHtSJ1Q9oFOKxH6r47CKj2ewEKhUKhUAwKNk824Z9vfQIAAO59egyO23dBcDwXNgGwhck6X/OKSLNdQLUiKCItn7DQFNy2QzR8cyq+l+MRcfhV/0mJKiIKhUKhmHG4Z+0GeMNf3gTX3/O0c/zZsYny682TTXoZAJA+MNjLgTZ73MjO6RWD9v1mQP1wQjPdr6nhlJZtpxVT3Uqs4IzljvcLSkQUCoVCsdti82QTJpst7/gl/+8BeHL9FvjDa+5xjuNUW0xEpG64bmqudXFMMb1iAFz9odVVPTBpaTFmVXOMhnVoSq5XZwTfS2h6NwhQIqJQKBSK3RLjEw1Y+emb4R1/+2Ov0dvz45PsNS4RsV9jMoEJh0My0C0aTb82CADxkbT9ZnZW/bBzGSXE7S0DfmiGVFalHhLua1VEFAqFQqHYTnz/oefhPx54zjt+79oxeHZsAh54Zhxe3OQ2m5NqaUygVNvNQo8YxEOc1NwpplQ7gKtGcN4P57zxg7C9ZlzDqWdWRREgTiGxX9vjWllVoVAoFIrtwKbJJpxz1R3wvn++C55D/g4AcJrNjW11iQiXiQIAThgHkwx8HF+Lj0vhG+wBmWLGcIXH8DGWnDBN7qhnRC7x3n/ygaFERKFQKBQDjclmC864/L/gt6++w9tEX9xoQyyPv7TZOTc+gYmIazzlKpwCuIoIV3odgBQra2LCwRtUcRZwg1FKHCLCkZPSI2LnaROPSItWWiUFzVpELTEYBE6iREShUCgUfcdEowWX37QGHn1hk3fugWfG4adrN8CNDz4Pz290vR0bUE+XjRMu2Rh3zjVAAt7QsUfEKUrmEBFeaXCa1zmEA5GVFqd0gH+MCauEQzMAbvddv+CZO7Z7HPoPJSIKhUKh2CnYNNmE58cn2HNfvO1JuOyGh+C3r77DO7dhiw2rvLjJJSK4uRwOxZj7GWClA8BVAjBpmEChFqlMO1f3A0Auyy6l+xpSwvWB4a53zalcaAZ9D3zIB0D2x/QLSkQUCoVCsVPw3qtuhzdcdhM8+dIW79y37nsWAACeYM5hpWMTUT0wSdlE6n40BPMoBVY+nNCMo4jwSgnn5QBwQyEtgawY70jB+UGY8uzuMT9843lE0DO6YRsNzSgUCoViN8SPH30RXv+XN8KPHnnROzfZbMEdj78ME402fP/h573zIQOlQ0QmZdWDFiBziETDrSWCt2mXiAiKiOARaUm+EIZcUNWCy5pps+pH91ywbggw3/vz0rk1a0ahUCgUuwyeeGkznHXl7fCDh19gz59z5R2wdv1W+IMv/8Q7h0Mokw1fnXA+vZOMFkxEqA8Eb/647geASx7w1wCynwOPm2rxJIPrDQPgZsfg46ZwGU3UaTDHOUWkVdYbseNaRcFk0chEpUXGDhKUiCgUCoUCAACeH5+AVV+/Fx4W2tz/3Q9+AT94+AU475/uZM+bDf3lLb4xdAwde3nLlHce742bPa9HA30dUD08ssGHWbzrhHCMlCnjKCJY+cAm1khKLoCQNSPUDKHH2m2aJeMrJJJHxFnGAHASJSIKhUIxQ/DAM2Ow+ts/F3uoXPL/fgZfvn0tvP9f7mLP3/qLlwDA3/BTsMExlfol1/GmT1WPrVMy2ZCIA/0+eJ2Q4YIJh9tZlw/NSOO5EAyAVVBYIuJ4TExdEHDG0awZv44ION+X15KeNP2Gdt9VKBSK3QT/fOsTMHe4Cmcc8wr2/G/+w23w8pYG1Cs5XPDmQ7zzJuTyixc2e+cA3NobRVFAlvG1ODhgRWSi4RORregYPY/JgUc2HENqSzyHzaZFUYg1QrDJdCqhRohkVuWzXggRaXGkgw/N0GiK5wHpqdfMINAPC1VEFAqFYhfAXU+sh1Vfvw9e3uyHNQAAHnxuHD76jfvhD6+5x9n0MUzI5KaHeI9HpRImFnj/6lUVwWmxnCKCzaReiEWoZAoQVkSk0AzNoJlsxhURx5Ta4omLW74d0Ndtbw4Aq0zwxlZ8vU8eaGVVzyNCrnFTffHX/SclSkQUCoWiz3j8xc3w3qtuh5sFEygAwLlfuBO+fPuT8Nkb17DnsYrx5Ho/BdZJ2RQE+UaEXOANe+sUNYb65MI5j3wYWxlFRDKMAlizJ3dOUjbo95MBwuKUby94wsGFT+jXjXa73NgdpUQwq7ZL0sGEcWgfGXKtF5ppE4IBhRN3kVSQ/tMQJSIKhUKxXYhtwL94YRO87W9+CF/48ePimP/zvUfgpodegA999R5xzIaumvHjR/3UWACA9UgpWccUDcMG0aEK/9bfELJEDHDIZAshE7RgWKMlEwZKYgBIhguZuxEKzSQqHVIdEABZyZBCNhIRKQpLNrgxNBuITd9liAztIwPAlHQvimD3Xam3ziBAiYhCoVAwGJ9owG2/eCkoXX/3Z+vg8ItugMtv4lUKAICr/utxeOCZcbj43x4Qx/xoTYdc0A6xBs1WWKkAACdkQzNLANy+K1JYBVs+OEMrJiJbSWYLJWRU9cDkglNEJgOEQmoyB7BjQjMuaZBUEHzckooWJQjM8aYw1tyWL+fujqO/hrSpHdcET/KIuPOwh3cqlIgoFIoZh2tufxJufHBdcMyHr/0p/Prf3QrX3/OMOObvf/gLaLULuOyGh8Qxv3jR9k6hn4gNsELBjXkJkYyhKv+2vR4pHhsZEoFVCClrBpstOTIzgTZz6vOgtUH80I18bVEUYjotgKtYhMyqocwY/GyNpvsaNyTPh1ApFQCl1AoqB63xwY1le8h070NJhkdiGA+I/70dLxGOAeAhSkQUCsWugfWbp8SN3OC6u5+C3/i7W+Cpl32PhMHPnx2HC79+H/z21XeKjdCKooAbHugQlS/d9qQ415rn/QZtFPiT6HqmfgYdQ0MeAG7DNo4gALilz2kZdABXheDmaLTazjpoLQ9KFjwiQkgAPR+qcopDQtxcuFBYL+m7eF632VyaIuIcl5QPwYCa4hHhMmQMAXHDNb7HoyDz0d4z7cLvzjuoUCKiUCj6hla7gOvveRrWMuZKjG/e+ywc9/Hvwqe/+3Bw3F9860G49Rfr4dJvPyiOuWfthvLrh9fxRAL7HUIlsPEbveQV2YALeQkZL7hZG0eO8KZOa2wYuETDnwMrFKzaQcgBVU0oAYiZVUOKSIMQAXot/d4JzTRkIuL5UpoCqfDqeeANGx0XKqjiOWSCEh9rlRJ/rBdmIYoMzZIpOgPReVKtVjKrDgBBUSKiUCiS0WoX8IsXNkXfvJ7esBXe+bkfw3V3PxUc9427n4Y/vOYeOPcLfsdVDGP0/L8BL0aj1YYXui3in3p5qzjuJdS99YWNfCdYbOycasnPijew8a2CUoE2dI4AFEXhhFI4ouESEV7FwUQipohMNNreZkzNpnTDp0QlpohQUhAyi/pZLLKy4XlEAo3t8PdSx9zO93z6rtOsTiAvXriFUTnKwmUJoRkzxPd/EEWEKVjmkReh14wzD3t050KJiEKhgG/d9yxcftOaqLP+/964Bt70VzfD3//wF8Fxf/+DX8Adj78Mf/yVnwbH3fRQp/nZw+s2sUWuDJ4dt8RCWiNWHkJEaf1mO+4lQaHAc41v5Td+ALL5CyGTLRElYrLpFqviiAZWFyYabda8ionGZiYrxTOPkg2dvv6UDESJRixrRujVAuATCL+gmUwIHKWFeD+SFZEWf07qHYO/9xQRJrQihnG603OhmZD/gzvmKSQFqUUyAMqHBCUiCsUuhh88/AJ8/yG/eynF7Y+thyMuvgE+f/OjwXGbJ5vwwS/fDZfd8FB03s/e+AgAdEIgIfzs2fHyay5V0wBncnAppwZ4k5OIAVYxJC+GN07IUtmw1R4fE+431Ww7GyqnQgC4IY5YJgpAXBEBcE2jBvh15rJiJgKejc41YSJC1xm7PqRy0HolIXMqgNznhd6Hej8cRSRB3QCQCQvdyCVFJJQ1wxUlk+5DU3q9GiQ0fZfUEaHEREy8GgB+okREoZgmrF2/Bb5137NRgyUAwMf//Wfwtr/5ITwf2IwBOoWvzrrydjjnqjvg6Q1y+AGgE8bYNNmE1QG/BADAQ+s2lm+UDz7HNzszoG/gEvDmYMIlHDZgUiCoEwDuBs41TKPXS5VF6fWSioGvH9vaYBWWLcTMySkZzVbb2YA5kkGVCk4ZovfixuDQCjWDcvfxiYa8iXPnJwM1O7jrQ+m59HvqIXFUCqqmCJkxnbFt9usWmV8iItJx/L10vM1c6xERpoqqDc244+jvYBFRRGjKr6QShjxQOwtKRBQzHj9+9EW44/H1SWM//d2H4dc/f4vjM+BQFAWc9093wu9/8Sdw3d1PB8eObW3AP/7oMXjgmXG49q6wp+KnT22wXyPTJYdnEFEJhT0w+Xl2TCY39BNviGC9iF6f5wUfBoCrNkhEpNUunFAD19kVwDWCbp5qiW+8OOxCM0MMMGFotQtvEzb3cK5hSA3NgOGID1WMuHulkBV8jFNE/LoeYcWDkpm4IhL2faSaSgEYRQSn3pLfO8f7Qa5rCqSCjmsJ/pFQOMeWZwf3OENQOAOrO4dLKPD/na+ZqqzEA0JDMV53XtGsyh7eqZhWIvKDH/wAfuVXfgWWLl0KWZbBN77xjem8nWI3xh2Pr4f/99Nnkhzedz/5Mrz20hvhn295PDr20Rc2wXv+4TZ499/dGlUjxica8DffewRue2w9/GuEMGzY0ijVhf/8ebheBc4YiWWPPDtm1/h0wJAJ4BKHZwLqyfNIsVg3LhOsl0gYQwpZFEXhqCDSOHpO8mvQkIeUeZJCHgDcDXXzJE/Q6KbNFeDaQkgFF3bZMhmfJ00RCasZdB4ugyeW5RJTRGJEI56Sa8+3C1qkjBIRqojwykbnHO/p8M4JfWM61/lEgB73iEjLkAv3nlxBMlERKfx7WrOrO6dvVnWzbQpwK6t2vpbXP0iYViKyefNmOProo+Hyyy+fztsopgnrN08lVXQE6LwJ/5//fATueuLlpPFfu+spOPLiG+DffioXizIYn2jAb/7DbfAHX74bbum2IQ/h/3zvEXh6w1a4KFDJ0uAnT7wMRdF5w4mt/cFnbdji8Zf47qQGOGwiyf/c2Fi45Vl0HpMSiqIo4HlEKkJhDzwuFNJ4kahAUhrpZDMejjBrxH4Padw4CXlIKgYNX2yreRTAJwd07s464koGXSs3hhKPFCIS714bv0/MAxJTTPysmFjWjExk/EwYGmKR1YyQ0iEpIpLfg84R6ljbLBvZOYdZ0tFkVBIARDrQHHyJd+ZaJhTjZs3Q0Ayw2O0Vkbe+9a3wiU98Av77f//v03mbGYlmqw03P/xCdJMzeGnTJHzgSz+Br96xNmn8PWs3wGtWfw9+7XO3JKkQV/7oMfjMfz4M53/xJ0njV113H2ycbMLqb/08vpYnN5RvYnc+Hic6P+8aJYtCriBp8ChqFBYlAShswTUVw3g6kTAAuGoFVR0onk9UGjZONp03/tBYbMykm74zJyEK0li6aXIhC4AOCcBvnFRhwONC8xtsJRtnCsngCAZAIjkg8/OqSbwx3NYpsuGzRtQ4oYmaVSNZM3T9sUyWXkMzIQ8JVU/oB6BmquohbPSdOeVxEuEIqSgcYcDfx/rH4DFc+i6tzErfVinx8IkJMauqRyQNk5OTMD4+7vwbBGyZasKTL4U3HoxGqw1XfP9RuOnBeGaDwepv/Rxee+mN8OBzac/8mf98GM6+8vZgkyyML9zyBPz7vc/C//zavUG/gMF37n8OppptuGfthuimCwBwR1dNeG58Ap6LhDiarXb5JvXs2ERSTQqDUMVMA7xRhTwPAK6RMkZEMEnAKaAccJhnXYSIYJKwIZDtAeBu/mNb5bE0syRERHB4IpSqSkmdREToOKnuBV0Tl3LauT6RiEzFQyUAbvbIptTQzBSndsTJClVEqMrA3Yubx0ulJWPa7UJs8GZAvRW9KiKxlNtQfQ/ufo1E82jnvEwimkLYpigKkcC0Alk5qR4RSeXgMmTakiLCkZbk0IwbevHMqQBJvWYGAQNFRFavXg3z5s0r/y1btqzfSwIAgLOvvB1O/dRNSSmTAADX3/MMfPI7D8Lv/vNdwQ3AYKLRgs//4Bfw9IatwQ6dGF//SccAecMD65IUiJ+jdMqUstSYED32YjgMAQDwlONzCG/oNEwgfWI2wIpCqFAVQOe1xBvXMxvCJABnUDwfyO4AcNct+RQMcFrqxslm8E0AF8LaEPl9wc+2IRBGoWpA6PcQjx0XwiMA/qYqFfCi46SQC/VnSOoEJTKSckI39JQKpClkRVobPcZlqlBVIBZS6YzxyQoNc0zENn1mDqoyxOqETLXce3ipsRGDaaxoWSOgiNDnDRlSJZJC/+SkMA2doy2Mk2qPpGTT2LLv7pr4Bne8SsJ6RJzQi29eddN7BUVkAPjJQBGRVatWwdjYWPlv7dq0MMJ04oWNk3DH4y9DuwD42k/C2Q8GP3myow5Mtdpw/9Nj0fEPoZTJFJJAzYAhg6EBJhMpxOI5tPmnKCJ4PTHDJd3wX4wQAKwoUJ8CBT0vpXpy50P+CADXTLl+y1SQAFJlQVIFAFxlYctUK9hWHm+uYZUjnYjgsZsmm6IviBIH6ZnoOKm+Bn1OyThKFRCuFws3bmuD76eCNxepxkmKWZWulwupxHwSAD7p4ciKZ/yMGkt7n6PXTBZ6T7q50/mo6oGLj4UKjNHzdF4xM4aqLIL3ozNnnHyI5dm9lFz/Ws6U2hnT+b8ouLF2HK2aaubyQzHueW5eigHgIYNFROr1OsydO9f5129gZeDRBJIAALAG9a9IIRa4O2fKpj8+0XT+WJ6IGCcBaFnrOHFx0i8jRGei0XJUjdjm/wIhC1Lrc4OXNtvxUupmOTd5tpgihZWN2Nj1aB1TzbYYIgDwwxaSegDgb+hB78dEmnpC1YBeSIusYKSNSzWN0o1OUkS8cYmKSEoarET66LUcOZiKVCYFYJSMbajvwc5D7h0rEMbNQZ+dbv6hxnMAHFHZdiLjkRhKWkL+DkIwuKZxdH2+z4T3grSY8ApdR0rTu2hoJiF9l37w8Twibd/gSgucDSoGiogMIh5H3pCY38AA100IVYs0eHGj3Qxf3BTvMEo329hG3mi1nQ08pio0W23n07+UVinNF8rQAODWH17PuBOOCCsRlATFVA78umwIeC4A/M08RARoiCNEBChJCfk0MGmRNmQA/9N6qLqpZwYVFAfPEyFs4qn3phud5BGhn7xlj0iKMTTsgyjHRfqqAPgKA0tWIps7dy8uxOMTmrAawd0nRjTo5h/qZMudjyki9LxTiMwLxVDlAIdxwvOa71Orp4bOdVJk+fliTe+c9F1DLsSsmRgR4RUR2o+GEo8C/HkpBoGfVKdz8k2bNsGaNbZJ1WOPPQb33HMPLFy4EPbdd9/pvPUOAw4bvLylARONFgzXKsFr8EYb8x0AuBtxq13A+i1TsGh2PWl+APeTOgdKDGKKyPrNU84vZ8wPQYlQNBxC5osRF7wxN1oFbJlqwaw6/6tLzYchAtBstYlRNExaPE9DgAhQMhHKRqHnpI12iqTFbmm0oN0uIM8zbyztvhpSb3zikKaISASDKhtcWAMgXenwlZO0cEosswRAJlOUVHDPEKs8CuArFbyyElY7AOKkxwurtNre7wZVAfzaHRFFpGfFQ1Yk6JpDFVHp3JInA39fq/iG1JBHxJmfSe0dyjM54yXBI1IUfHiF846YH5NLTjiPCNdbJqSIgID+M5FpVUTuvPNOOPbYY+HYY48FAIALLrgAjj32WLjoooum87Y7FPTTeixMsXmy6XyyS1JEyEYeuwetVBlTROgzxBQIqoCE+nYA+MQjRizoJ/BYCjINAYSIDvUjpJo0zX1CplJqwgytmyoiIY8IfT7JK0HnKAp5I6WELExEKMHgVQKPYAhzpmSTAPSgiCSGcMwzZpl8X0MoKt0NutEq2J+5ubZe7bxFcs9q1pUH7pfiETFjRocq3Xl695oYooI5qW8+JUSDrDdKNKKKx7ZfH/Js0Gv9WiE8wenlfttTyl1SSrjiZb7PBLyxZoxfJZUQEfDrj/i+Evm5BgnTSkROPfXU0smL/1199dXTedsdCrppv7ApTCyo2hCrC8HdI6YoUOIRN3CSLJVAZgSAv8FGiYVHFNIzPzrfh8f34rfoxaTJ1n0QNjlubokwAABs7N53qLuRpfhJhmvdTY8xWQLY120EKXLSvOZnMrurHEnPVRQFbJpKG2vIzdzhanedgiLSfZ0WjNYAIEREOseHKuY1EhSR7gYyp1xfWMVYMDrU/V4Og8wfqdn5A+GS+d1nCBGIOcPd5wyMmVWSDFlZMa9/iNAYsuIrBua8VQo9M2n3e/M76WWqdDcq8/slmVENifP6wxAy5JtVqWIih2Y8oykOzZCOuJ7KECEO+FnsuRBJaXePAzkuhFsEj0q7KOQOvo564od8OteCd22w+y74ZIbDIIRm1CMSAd3EY4ZGSgpS0ndfIqGVkEeAOx+7Bz0fChMAWGJgPllKWQ8GhriYDSV1fK2Sde8nj2+3i3L8nMhGCWBTgc0GEnptzEY1u14t31xDhMEUp1o4a8h5jtA69pxTj85rNh4TjouVHZ89XC03JFowy8CoN4sj998y1SrfiMzYGMFYFBlnlA3zOsVCM3NHqs73FIYEzOkSII4UmGcBCBMgk6Fifj+kcUYBmTscJyJm/SGPyOzhAMnoZo8YIkI/8Xfu1TlmiAZVN8ymPjJkSaoU3oiTmbTz9DUxm3lJZIR0XUO4QwbUUIVUXGWUK9Jl5g1mzWxD6Idm/ZjvJY8IN49kbMVT8EXOfEWkTUIvReEGWTjPCIcB4CFKRGIw2SbmU0Rs0zebvHlTiZEKAOtNMG/cMaJgNkCzccUUDvNJfsnc4aTx5vze3fGx0IkhHnvN626kAaKAxy+ZN+x8z46dapZ/TOX4wHrKtczpjJU2QQC7KQzX8vLNVaorURRF+VyGXISqthrZew+zGQtEoChsTxTz85eIlnnjr1ftercI6snm8nckfH8zLsvs/SUFwzz/oln14JyGsOwxK0xYzOZpNvuYcjInQArweowiwo0zZGX2cA2qXfLJVyHtHJvXVU44kmQ2vDn17roCSkapmjAqjanXMVrnlQg8j/m5e2GR7lqGKnn5XFIBstEaP4cZbzxwfmjDVUykNRgyJIUszPycCmE+zOC5O51nnals+IUhbRIRcAqfbYOR1W9u5/5fHpfSelkywakf7v/m69h8bPdd8OcdRMxIIvLIuo3w59/8GXz+5kejYw3xWL5wFADihkazib9i/kjn+0gxKwC7sZprQqEHALvZLp1viEWEuBhi0R0fI0clEemuZ9NkM5jJYz797z13xLmfuB4zfl73eQPjzVqGqjks6G6UoZCI2Vj3nJuuRNSrFZg1FJP92+Uf8p5dghYiXEamnz9qyEU8I2RBZOwk8i2YT8bSazFF7y8QFrMxjtQqltxEslJiSofxrSyYJW++nedJUzqmiCJC02bL9ZXhFJlQmbUNV/PS/8Fl15hrQ0SEhlRY1aTpjqGbd2cMUTsSfCTUBGs22VolgxqzmeMxhijQSqve+cj1nq+j+329WnHG0/PD5jza2S0J8tdOs3nwvek98LV+aEROo8XzpJtS2+xxOVWXqznik5aiVEncY/QtuCDz0VAMLWgmlngfgNjMjCQiz4xNwN//8DG4/p5ww7WisGGBfRZ0Ns24ItIlFd3xAGGiUBRFuXkaYpGqiCQrHGb+7sa/eaoVJEfl/F0FonNN3DuxV3d8rFJqSVxKhSOU2to5N3e4VsbZQ0qEWXsZkgiMNRvkcC0vP41Kc+PnX9xVoiRlpiiKcjNJVTncsWFz51DVkoZYaqzxQsjjLLkxn3QlglHOORqe0zy72cRpwa5yXBnaCCsdlIjExs0r55MNpkPVvPxkzhElcw8TUqFVRvFcs+r8xo2PJY0RCACArzb4xcc656uVvAx5RhUL6XzNJwrceSnF1pAJqShZed5RIVySE1Io8Nz4nJmXKiLm9QCwpCYUCpLUElkp4Y/T/b0TmqHHTEVUdIzxmHTCMO6EBYQLmPmVVjU0M1Awn042BjZAgM6bkflj22dBRxGJERFDOhaMDpV/sKFr8D2WlopIWvhnKVIsQigVEUQsguGQCSPBD5V/xCnhEDP/VLMtxvsB7GtkFJEQkSr9IcPVMmU3uJbSm2FUi4AiYj4d1+KKiCEoo0OVckOUSAveKOMqhx1rNtDYvDg0IxFEswmnk5u83ASiBCNqQnVDLlGPSHdcq12wVV0tEUkjLNazIW/6Q5WwIkLVjqBKYcZwayfeDrp54+tGA6rJVElWeI+I+URfzbEiQkMrrofDPx8OvXihG+G8JRP2fFFYf4RVTPzNf5hZG/eacYSCKjFNcj8AmaQEs2YM6UlUStoCQSmKgq3OSnlWmb5bRMYRctIpaIbuB9prZqBhNpJYCMFskFlmwxqxAlnmmjnD1XJjSU0hNRt5jOxsIgpKPAumS45mDZWfGsJdVhvdZ6iVb8RB4mIUkblIQemBuITWb30clXItKYqI8XGECnlNlopIJbqxmxDIrHq1/HQrhUUwuTDGSZkIWEXCzJsy1mxsUUVk1IZRuE9Eltz0orJEwk1EmWi2C3Zztd4Pm+nBZZ6UpMAoIgyxKYoiyXOSoogUhV1vChGZbUhGk9kwidqRNA9rVg17REqCVc3F0IwlCjzh8UMzEcXDUxW655nQCx5rFRPk2fDUGN8/AmAzcqgi0iFgLqmwxMduczTl1nhSws3t+FCPWNBMyJrBVV8NJN8IX0U1TGJouq5f8h1YDEBkZoYTkclmMD5mNrXZQ9Xyk22qIjI3lYigNEvzBh8lIuVGbhWRlFDL7Hq1fJMOEhEzHqkQoXBLmakyUivfZFJUC0NcQlkwOHxSKiIpYaLu3FOtNrsJAtiNcLiW29RVsd9JZ95ZQ5WSBMjhls4ceWbDDlJK7oRDhiJKS3dsPYE4mQ3PEKGiEIpyMRuzVFl1khCMmNIxL5KZYsbNRsXpQo3jQqEZrEaEQj1GSahV8tKA7pU6R+bIWSG1o0s8QmM41YS+55gNPzQPzXiRSEY1z6BWlUIz3bXEzKY1X9EAQB4P6Xp6HiseiJTUGTNsqV5w57r3yTOceuyqHpU8KzPfzL1KssEQEUOqzLlQvQ3Z/CoTDgDGU1IwWTNMJg2nflCS0TnGlYFH89ADAgaAh8xMImKNY4Uo8wJYUoE35FhGiFVEatFPzgAuSTCf+ELhBHyNE2oJbvyt8h6zIrUYACzRmTNcTVNEuq/TrHoVZnczCKT1tNpFeW9jKA2pFqUiUq3YtYfqd0y4ZlWAeN2JerVSbhTSz3dTGZqplp+wJBMmJhcjEQPotng06hF/Ax47F9XL4MqZuypLLDTjpr6K45CaYFLAQyRoZKhSfjJlyQMJ4Uw2/c0cKw1zQ6mySDkwm16o+dusBEWk9H8E1m4UEQC50JaZJyUMJCkitUoOtTxcJ8Sm5wqhG+G8IQQjZdYLPe8SkZaTpWK/HmauL9WWqq/mmNermudQzV01poUImHeubV8Tex+epIQUEfM6phhN8fd+aIavLUK5Qjt1XDviEYHBzpTBmJFEZNaQfYMM+hOQWjE7gVTga7CnIVj3YsKqD3bTSiM7e8yul2/gIUPsJkSozJtIKLyxET03Vo/E+ScxcakEx3OmTylsAIDIQi1PMquaDW/ucK2UaqXX01FbIoShTPus259TLN3USbONhDvqNUsuJHKM5w35G/DxkaFK+TpwVVgdRaRaca71xpLQR6zuR71aKX/fJphqrWa+oUoO9Zohd7JfA4dwQn1P5gSIiBlXq+Tlpuc3kLNzm9o1IYJk/s4nQ96OOl67O87MPSqETJx7lSEengTUKqHQjEs0pIJl5vfQL4jmKiZ+9VM3dOPUCUFfm9cdh1+ov4SrglrJM6h2f5dbpQ+k7Z0z85p7VitZGdJpEQLD+VUMgTBp0FKBsrKnjRfCcv/Hz8F16uV9I/6c9P4F+F173VCNm74rQbNm+oQ8z8p4bEpRqjnDVSub96CIWPk8nm46u161hskA2cEFvmbXq2W2R0pTszn1avRTb2e9aP6IibPzDNY/MRLxLpgMijyz0n27kDdf4xkYRqpFaC2TpackR6QrrIgMV61yIZEcc8/hoUq5YceViwTfRcOOtUpLfN6YIjKF1BPzZssrImhcTVYlcCbQ7MTslaGqDX9wWSdmPUN4jcyctKBZ55g7n9k0q3lWzhXyWgxVMlERMXNlGdq0E6qmNkJhF1TxlHpJUjJrzKYn+TvM99VKKDSTqIgIWTNlaIYxo+I1cooH3ujN7wRnEOXujZ+tStSe0iOC6qfQkEkVhW3Mpk8VEdx8zvwIqVpClSyuOV1nfFs4zvea4ZQWyg240IxXSZX7Xhb8BwozkogA2DfTUMjBqhW1JKMkgPVezBnGxCKuJsxGJCG46SMiNGe4WsZ7U0Its+rVaKgAwG6aI0P2E63UCK0zl/VPjJRlysO1HkZqFadUubj5ImJhPkkFi5Shzdp8ChVJEfJcxEMdtv7EsLCB0WfpFEpL85PUE+a1HpEURQQTkXjYY6gaDo800ZtoWc+D2XjdOfNyTjZFttXbGvFm7vVR4chPwEvSWRu/YZsx2EcS8n+Y37OiYMIuhkjX8lKF9UujU0XENyvGUnwbSBGhmzWdI1aQbFQiGhGikmI4xXVOODMr5z9hDanEB1LBoRnvXG6JCCEppVmVCadQwtQm13ApxJ3vO/9zng4v5NJmyr4XfLiHC+F4oRlyvv9aRxpmLhFJSOE1IQ2sJITUCgBELIatWhHa9DcyRCSkuuDy6HWUchkkIpOWiNiKnAEigshC+Yk+YTz2REjEAo+toZoHYnGsHuZuttpOrYLY6znRxCSn4hyjwEbRkSFe0i/HcqGJBD/JcC0t3NITaUFKCzevq4jIc3KhD3w9t04ccuHNnpYElc8eCKfUaxVkMOU3c1eFke8ZDGGYdVVipKardgTCLlw2i0dEyhLvFXSd+8m2LPEueERwQTOuOmlnjKtoxAua8eoOV3QMf8+FZsw5x1TKGFJpLRA8T7WSl+GXBslkqeLQDHOukrlERFJE8H3N60g9H+Y9yx53XgY5a0ZUNcA7xjXHi3Xf7XhT8fc+oeUwAJGZmUtEzJtpyCOykTFtbp4KZ9qYTXJ0CNemSPChDLtGUukeJswwUqtAlmU2jVPIyuisyXzismsKKRzmGUaGKuWbltSRFZcoH65hBSWsQpiNdDii6DgbdTVMRHDqJ85CkT0iluQMBzwKAMQoGlsH8rXUeyAX9WpMlUkjF3TekPfEGFCHIr4Th4jUUcO4gC8CKyLcRo5rmJTPHlIxcO0P8tpPIvJQC9yzwagdEqmpVTKoJ8yFs37oOEddMQRBuB8mNE5DOLRTGQXU6zWDCRYTmmmj7Iwya8Zbh6tK0Doh1lDKm1X9Eu5+6KWW2xAKV+K9DKsx12JDKiUUHUVEVkt8RcT+PeOxDhGpuspHm5CXWB0RrhmeT054E2xBft0kwuJkyZBQTAFpJCPFRzLdmLFEZHbXcJdSH6Pjxei8SbQLeaMAsBvqSK2CMm1CaoXtTYNLJ3Nv8ACY6FTL+wDIRKHZatuGWAlZHJ25/PBJzA8B0A3llMRIUERQ2KfzHDHiYjd1q4iEXxuAzoaUrEYgz0VKuKWe+JoMVytBfwYe2yEMvZOLmEcEKwRRj0iCT6OSZ+U6pTmxP2WoKnsspjAJS1BEMGGhfx9cOCiswuRi4a+pRHUFKwCxsAtW/6RQ0KjjI7Fj3CwenkRwmSWOIoF2KHMfqcOtbEbthl5Q9VP8gclP38Vkqvv7U7HKBdf0jiMxZp6OR8QlG4ZQdBQRQyra3jlKRKSsGc7LYoiCOVej4Zzu8YwaYhmC4ZGJxNAMTdXljlFzalEUA0EyUjBjiUjprQiEHIykP6tuvRj4OEVRFDasMYR6d4SyPKasWoHvIYWA8Pz4f/FTv6cShDd+/AyuwsHPj+cZrualR0RUOFA4BAAQWYiMR/J9jAAMVXPI8yyYiQFA/CfJighWTyRyYclTOTYhjBP1qWCPSJS0IPUk8Bq7ptZAGAKNy7IsKfxRj/k1HIIR94g4XhJqMHWIF7/hd47ZOH+s8FctFpopVZiKqPywcwVCGia7w+m1gsytUmZNsyRPfK8Z7MeQQi9erRJaR6RcJ5+KTM9zZlVMlNzzfmimIBt9lfF6mDW7qgc4/1cYsyotdlYaT5nQDFVLSvJCKq6WBKVURMBBq+BIB690bEuRM7/AWVr6roZm+gi7IcdJwshQBfI8i3Zo7dQ36HydqohgP0YVvVlJBMls/OaPPebhwJtPx1MSzjxptOwvM/ZlxBqc1SqdTyRRYoHUFvwcSaGZ2NyoKVzn/4gigkq8l3MnqBHRZ2zgjdO+6XNF5yZxGEdIJ7Vr8EMz3LM1W21U3jq8yeM5pVAFgM16GSpf20QFI2CAxcQxGD7CtT+ENeLwzVAloMIwc/l9W9BcASJSqh1V7Mso2DEuQeDDKk5YCRMRtKOJvWZadrM2RMxNj0VziCXcXSJBzZW0Tgg+BoBDM4wZ1an3wXlEmLm758usGeQD8T0iOGum7fxfrcSLnXGKiPlZ0Hoh1OBqztepUpKQqttq82XfU0rB06wYv8CZekQGHikhiomGu2mWxEJSK9BcbjfTND8GgHXFSyrKVvQpPuU5LHHJHTIljm+4z2BDM/xmTonRcERxwWoLQDqRGkZ1NkRFxPOfhFUDXEckSloYQiQbRQ25sIQBIOyTSAkP8b4PhgigDSaWYcNv8v448/zmTbgufLr35izNqmlqTLAse6AaKp7LeCRCKgYOlfgqhh0T8rjguSTC4oxJUU0YsoI9KxLhMaSjirJSppw57NfWAxIOveB7A1jfxohDFjDZ6ZKJqk90HL9GxSdKXDl2mpWCM2NahFDwPpDO/3lmzaqlwZTUEWkRssGZaqkiQnvK1Aipwes2c7NmVSY04xcvkzJpKPGw5wsYDJKRghlLRFLqaWylRCSShWHGD1VyqFby0hgaKoJm7l8vN+awikLJUYxYSOPlkuOd8ZVuqlysERolFjFPCTWrxjJhOCOs6OMgYZ/klNwks6pPAqZQlo471t9gpbkdRQSFccJ9YeQQBYC70XUMngHvB1KRglkzJtW25qpNdGy7XTjhj+BGjtJ3pTAJvjZUDZXb8JtM/B1v6lIWyxRWOszrvM1hHkx8BAWmvF9ebmZcaKYmKCZ4/JCTvouJAH5uPnRlfCcjjCoBgNJ3h3yygO/BhmbQ684pIrR8fOdY2xlXZa5tcv4Rom5UEfkRe80QHwg2v/qN8viQTZlNQ7wzNXTvdkmOOuc4PwhX+Aw3DTRok9BLUbhZM5yvhMMg+EhmLBGJhSgA0Kf9IUISYkWvum/WNn03oIg0JWIRJgojhLhIISZv448U+cJG1SzLELEIzz+SSEQouRuphX8OuB9MjADgku2d/8PkwoZQ4mEfzlQqjcevOS60FA6NWMJQFLzSgFOIS99HICW30jXwBVNjmYyUoMmz+yYs+R3w99GaHthjIYzDzeywaiPdF9+THceaVfkNmYZmpNoejiFYUDuGsFKD7ocb7GGSgF+HBjJdSv4Xm+KasaGZJgrdlGRH6CWDiQg2xdraG5XSmInnMCqDISqSImJLseO5rTpJ58Nrr9Dwi+MRkRSJ3Evf9XrNdJdiiEIlyyCnRKQonGuo3wQfx+9PZYinKErfCvaT8B4ReoxRSbz0Xf66GAZBNZm5RCShEJiniETqgtCMll4UkZJYRPqpUHIUew76DLGurZ7CkZjVMpKscPChpdj8w9V4AbQyzEEVETE045OcmFEUpxHL66BeFTnkwZlg8XFp3pAiMok8KmZuAD41FhtgbXaNvM4hQvLo/fG6Qxu0OycOSYSJjUQuOYJBr8fzh/wfOFSCW8jj8Ea7XThZFKLK4HhXus9INnezEdQxIWP8HQ55CoSTuNDMFCY7RjHxysTb3wWOaDjVW0nxMDyWS+/FagJVGvA8HMlxM2N4lYLznjiKSI9ZM3g+6wWB8jXsfM8rJW3i+3CICPGZcCm9RcE3zOOzZuz3fGn4AWAZCZixRCQWogDgNtnwJl6m7g5R4pLiEemqKEaxEMM/rgIRCzFJnowtwnNvJeuJeUQosSh9HKnEJZIJg9UFHObgxk8SRcQqAeG1YxIQTZ3tem3MGxi7uSNyYdaOn4Wdt7sZmzfhENFy0ndZ3wchQoHXYZJRRGKZKwBYEeEJQa9zxjwWdD6pXgfe8AH8DXsq4sfAz4SJD74H/bpWyUqClhaaQZs3+rqGDa1YEWFCM1LGi1tZ1VdEcJ0Rv3Kq3YQ5ouFs0qTCKf7aqHW4FohT0Iy7FikmNaJsYLVHrp6Kwi/de5n/KxXZPyLVEckd8tJ2zg2VRKuzds7Eil9a27PGhk7M68cZSqXQDGdWpb1mKO1IC830HzOWiCTV0/A25fCm6YUdIn4PfM0wUV1ixCLVI7KVhItiz40VCDw+pVIqXlesjggNd6XUEcnzLBhu8RSRSBM3bFYdjphVcaXSzty5uG5KzlJMoMPdUFhQ6eAKmjHjSmNpiiKDwz3ISyJ1t/WzZuQQiZPmG0nfLcvLC6EUAKJiBEIuOfo0Gw7N8GPwxo9JjRMucYiILRcvm1Xta9EQCY1gVkU+iJKItN2fUQN7QEz4hlkv3sw9JQh1qw0RjWrFD5EUhVWIbNaMH9apVmx3YMd/gnwWNMMllBnDKS2cIpJnrrpBa4LQxnZcOrD1lfAExYZbgFVEWu3CeR3MsdTQjG9WlTsCGyQpIgPARGYsEUnp60IzQmJpm8anMULCJlPNtvcLUl5DiEU8ndVVXUqvS8Rk2WsBMfoMkqpDC5RFFZSmS3Siz9t0fwYhLwclUb2ZVWMeEVdlCI2nikhpsAyFW4iixIdx7Nie7h8wq3IdcAFklcBXRPiN16Qylqm0ZFy77Xo/St9Ck97XbrB5nonmV0qUhoT53MqqFedaes+hSu58MnYMpOj1wQQpVJOEq/iKv+70UuHMqmjN3fM0tbaBfBS0/gX+uppbAkb74jQd5cFNk8VrwuvkKpKa94A2CjE0kNoSKvHudNEtr7Ukil6bkjXDzSlVSXWISOYSjlL5IB4R8xi49LvrEbGhHC800/bJAmcy5euI+IRFasw36JjxRETaeABkkhBTB8zcjqlR+FRuapV4ZEccz4daYgXHkp+BridGXFD6KR4/ISo0bWdcaoqt2QBD1VInkN8B/5+SkVN+imsXXmlrOhavn1c5eI8InzXjPl9ImcFjw7VBevCoMHVMuLGS7yRUWAz/LyknZk5bDVXwfhCTrNT0zqyvJszn+i3Cvg5DjjjygzflHG3MoR44nAKDPSRZZs2qk869umQmt2EVfByAZqWk+Uyw2oEVjU4tEia8w6gP5jzeALlaIHzjOkYxwaqHCbE411LiYH8OQY9IZskAPmcJASEiGVcgzVc++ONutpZVXex9cGjG83VwKb2scsJn3IS+56BZM31ELFsDwFcHYnUsthCS4JoaBYVAIjtRz0daqIWGTmIhCD+rJTx+Yqq310h83khNDlobJGQSLRWRxJ4w2KwKIPk+iCJSNQRNDqGYOUNpsb56Eg894SyflDBKqD6J5K0QC4ZRckM28bLhHRnnEQwhu8ZTRMwzd59B9JKg58DjxC69ARUDh1Pw/45HBKkU+H5hQyujdrTovZgxJmSCPCT0NXC8KKHQDFIHcPdkt5CX78XofO2HiKhXA8AlItYEilWNgGJTwaXau4oIo3rw/WQkdcOvyErVjZIwMXVESkUkQl6wuoIJQhmGQQoGNsKasTWHnIADPhXX78i7TUSk/zxk5hKRWIii0Wrbjpdd0mLVAWETn3IVEWxqjPpKiELAbYYAzEYe3WzdTRGXHOdqVUhEZKrVZpUCjxglEpEU/0RnnXT98vwTDXfTsmXQ/XXj6qPDVdcImxLuCCk5k+TTeS/qxXAgjMJlzXBjpfuHs2YqjqcjtIEDYKVDUDBoCIeuEZEip96IR2zIfYVQj0cMBFMnroYqNcdreKTGN6JOCQSCS7s14zji46kvzOuFQzNmA6Pz4w61bGiGOQ/gl0o3Y6qMWlSSqhx5SMo0WjvOSf8labZY8eDqjDjKhvGIlARI9oi4/hFKREAM2/ipuDZEJGXa1Ah5sUTC+k3MfFnWuX95nHpT2pic8GE3c62niLTjikiKRWQQMOOJiOh9QG+ww14GSdqnffw1t7k1WrhtfZoPxVcUzCfoNIXDbNJSrQqqcOAqi/zmT3w0sdCMp3DIiki7XZRvyMPk030sA8Udy6wbvdFTo2jQf1KGfUIhol58LQJRJGOLorAEo+amlcpEhBCySB2RzjX82ElCMMRS6wIJEhWMqhuSCNUHwf97xCaVAGFFhElzxd9bUsPU9qDrKolIC41x5XmOHE013U/Z1nvBh2bwayUVLOOMupZcWcUBz41JDecBAUA1OwIl0/Fr4p73FRmxzggp485m6xACxSkYbI8aYkqlZdzNkjgvC5d6686FC5d15qlkbljIJy3YyGtJJkcoOI8I/SxJM6HSQjP9x4wlItHske7xPLO/eDGSQEMzna+7ighzH1pOHcBucNGsGRIKkT0WvOLSORfaRO1GYlJKOSIiKShirxyySafU2MDjQ2TQ39TjZAGvIUxyyOaeVBukd0VEKjXfaKF6E9VKx7zZ/bl4pAH5PvCcKWZZqbstfX5xo5eIQ8zUKhhHjXISIxgSMQim05bhoPBcsWqneKxTLRTNK5lV8Xo6/5tNGoctrIqDxzo1PHCKr1kLY66toponAL5iYdfKhHfMOnB6LyEEZgM37xlNQiY4pQF/jdOP/doeuQ2/eBk1skckZGSVipNhkzJtiCcZXDlFJM8yyFAxNY60FISc4NfNgKs3wnlEuEZ7MaT0o5luzFwigmLsHGvEG6z5RUrtozKKVISRAFEwZMeUUwfARbjC4R9fQYmMR2/QmbCB4Wcw82dZZsMFSZ/+7R8pV66bVmKVTI94bm7+kGrhhyTksSbdMzY3ViPwenhTKd3cE0gLMdhSTwW+1nTAlQiGpHLE+rg4a42YUMV7e6EUfj7qJZGMo9KzxLJmpH4zZkOuB9N3+TAPflaq1ISMqGYjZBvaefP4pIeGnVjFAykOZcEyhszg8/hZDWnphBKsR6SBNluzX3GhG5zZAgBeHRKuzolDpJCyQY2wHNlocGSjrCPihlmc9F1P3egcN0XE8L2MkiEpIrS5neMRKQkN7jVjQyVVTFrQMxiYe5pDtHhZ5xjjEYmk8w4qZiwRMfUrACKf9BlSEauRMeIoIrKvhCM70RRhspGndqQ1JAoTC24TpQoHAPLGBFQIuh5pTZJCwxI11Nm3khOiFqwjQtSigMJhCJoznqyliUJoSZkwwjrCmTBhYoY3Qa9QmZThQlQntmw8qb0iqTeUOMQKkA2RNYqKSI/zSV4Sz6zKkAf3E2mg+y4KY5ixnXF446RKhlFXCm+e0kfCmEglrwkXtjAbeKm+cOupCv4ORATy3Kpp1BBqCATNbMFzOYZSokyY62kFVC70wpV4r+Z2blvQzJIcP/xiz4UUEck/gsNILaJklJktXWJh9vgyO4Y8e0lQ2iT7BjXca5e/f74xtYb9P6VnxhIWqlwU4Ge80PTdJEUkOmL6MWOJyDAqY8z5RKjyANBDH5UhhogE1Qe8GcobHD5ON3Ip7ZQjFtiwKs6Pxwc2XVqgDIdygqGfhBoXZail6r+eKT6OIMlp+D9fiaBRPwn+P9ZIDv8frA3ikQueiBhPhTuvFEYxc/Jhj85azabrhlxC3W1Dz2SJQ8WZV1ROIqGUVPOrRGw4YyhAt8FcSR7k8I0zVzCkwt2PhG8YEkXVDi40Y1WTzrlg5dScz86hhKdKxuCMGPe8u9mW96A9X4zJs3s9rb3CEQbHrFr6JHD6rh9+oTVQUrJmsN/Dy3SpuBk+eJ05UkTwhu7VEQmFZlCYqoXmsQTDhlewd4f6RrgS75yBtUViMylRlwGIzMxcIuI0dAv4N1xlIEwSaIl3gDCx4MhOvM4HNasiBYLdzGWVJrQm5xkCISlboKzznDHTJ61WmxRq4UhUgo8jpPxQP0nnPvxacAgrJdzRS0Exug5pg6fkJjSvtykLNS4A7AZVJybc1IJhITNoaFwywRAKqckEyCUGTvEwnDJckTvZGgOpV0eEIRBGNWGrppLXIlTiPURoPLLCNM9zeslEqqIC2E/f5jguOIb/p83lOnP4Rk5cUA2v1T+feSTHWR9b0MyQDesRCVddpSTFN6tSZQLAbUqXZ5Yw4ZANgP1Zl6SGeDyw7wP7U1hFBBlYq0xoxlzbyaQBB5xHhPksuktgxhIRgHB1Vao8AOAwS1it4DwiKUZP/LVYt4NUGnX6r7DP4W+4oVAB9YgAoJoZicQlFF6i5Cu8SfuKkTVzxhWRYE0OZmOXUmfx5pqTEFHKusOZMLxZVQrN4GwZufGcG0aRQjg45FQSrApP9HyvhkSCJOIgKzwA9k082XMSyMLB9+c29M790tN3a0zHW8lkyvk/wqqJRFbk0AzbB8Yxo3bncBQHXhGhigZda0lUpKwaGpqpECJDCUOFT991qqB6Bc3s2um1vCG1ex2qFBtremfOOb4SRGzwhj9EiFLZDK9qyY758VUyq6zg4mU45GJ9I4iItHxywldbdQ55ikgKBkAQmdlEJOR9oBVGAeKhmS2MR6SswJnglwCwm0a0V0utNwXC+eQfHN8WnyEUauEVFyoT2hTUNPOpTKL4kAiviHBhK0roAGTigvvd2HVsvyLSeYMDMpYPm9FwC16Pp54IGT5SCi2eSzTLEt9JrLCYn74bXmOsuFiqEkM3Up4YZM7fjVxrRCY/NMU3GA4ps13cDda9lzvGUU3K1yDgI0GEplQc8HojISBc3h3/b0M3dsPPMj8FFxtzAThFxW7wZdgGbZpNJ3TDqymcv4StP5IQtqEFzcy5UhHJXdLjFnzLnTn8su1WQckRoWm3AcyP1fxu4SqqVWwiRrVTyteI/J5yRlTqEUnCAMRmZjYRMRtmYmgmVgXUqgPWCBtSE8JqhT++3bYbObcuzoPAhlqSfBZp4aXQM9Bn5tJxg4pI0yVdsbVMkvF4TXR+3PDOQFoLr0YI5KKFCqWRzT1oQI2NZciQpA7IJd7pnG6oAv8vEgyinISayuH/Y+ZSKUwi1geR7hsICcmhEmkueeNvkHWxqbk0+4YhPlJoJpTiy5lRpxCRoP6Nztd86MTLejFmU48M2A2fO0+byNHwC9frpiQFbbeoFyUbITUlnKKLyA/yaeD/ccpsh3D4iggt2R5L38WVVfMM7L1xaAaRE1pZ1Zkzx8fc31Mu23NXyZKhUCICfGgmHDaJGEnxphxQE7gsm2AvFUQ0eB+KrFi42SHmU3dA4Riy44Ohlh4UF7zx2doddix1hZfl3VmzKrd2lxSFqqVyhEv0iDBqRGmEDZAt2qnXUzlY78n2kyFbFp3MKYRbKihuL5llxR4yEa+GRGzMs3uhFKHpXcxzIqXBsooISbltko1mimz8KWZVtmtuy/2kHFqT761AY0QSwYdeagzhwb1oADCZoUSCV288okHVB8Fj4tUCwSXemWJobvouJTH2WmqiDSkieeaSCjpnhokC8nbg+dwmdohwCEoJzpopQzPYD8I0yMsR6aDmX/o6mWsptkURGQTqMrOJSCgtlfM+oPFcERhDaLBHJOiv2EYjKZ43dk3I68LWEZnyN/+6oHDg+bGyYEM5ZPPvblq4poLZJNuF/0fEGkpDtUGIEoBL7FPSNdHwN3bRI8KoEaVXRQg54HVIvWYm0KZt3oREs2ooNCOQIa/2BlUbGv6cInEQVBaxoFms7gcJ4cjGUZdg1IX1pYRwaBVTLMuHanuwZlWSyZLiEaH1MQB8gsD13CmVle69yhLujELDNaTrfO1ugNZnQhQRSdHwsmooUSGhGXq+xREGV/EwrwMNo7g9biSCk0NFSKvl0nfbzLl22w1B4bRbXLJdDtnY4zhrpgzNFK66Y+Y2U+BGe9T86zwreRaMlEqqFAMQmZnhRCSwwfIZMJ2vO8W6/J8epw6EMm24TTyYZYMMlpg991oXpBzPKCLlM7Dm04DikmBu5TY+vLnLqgV+fWQSNRkgLnR8L6897TCMx3rkwnzSrySQCzYThlckKBEIjhX8HC3ilTE+ELwhR3vNxLwaiZVQpfloKu22hno4QkWVDizLh9JuOQXCz2Tx109TZtnMGu9esjF2qCQJDOlBGxxbeVUI78QUDVoZ1VNumIJleJxVJ2zIg9YYwV4RXNyR677rlV1nCqF5HX8rTPouqhdi03TbVhHJ3OZ8bFdeklJr/h5bhUt0zFs1bnpXK8kMoDAOGkuyZvBrzFWmLcdskyLSfyYys4lIIC01FJrB551rOPISyPIIZZw0235lUk7dAMDhn7TQiRRWAMCFvvzxrCISDFtQBUAO4+B7l+N7TN+ligi+l18bhFtLuiJiK+AmKBe9hFsE9YSSi/C8fCYOHTvBEcNY5lAkG0bsDRPxfpjNh3bzTSVA1LMRqiNCwzd0PrHBnxOakciKrIhwRc88pSFnwjcREoDnwdlAbMM6QhQaRNHw1RtKNFyi4vWDoYqJV+I99+ZuoefAfWFosTUnRZeEjDBJob1mKHnA51ySgsI5eWab1bXd6qeY1HAhG+x5wffme80gP0kOZY0gbMI1wGQOPwOGekR2QYx0u+qGQg6YfOAKn3TTb7WL8s2DrUoaIDuc0ZO7h8nkwfMDyB6Eoih6NsSyoRZBhXCa0nFZNlLFT7TxhTq+siQnQOyCighZC2dWlRQRnlzwZIv2bnHXIBERbmz6GmJhDycEwXxi5xQRUcGgioNAHMpsGKQmOD6MQNYMDnt6JlmhJ41RFvwCaf49zTm8qSRVTQ2QGi4DRyzfzphIh4iy4vaRcUMzVDVptfEnbb6yKjWb0lojNHRDK6c2UFYLd55unDR9FxMuL/TStmEPHLa1qb/+tVb1sCEhTxHBtTxoiXdMUjJLUtoOsbH3KpvYYRNr4RY6w94RJ2uGS99l/CQ5Wgslds6amdAMdywVGprpM0zYhCUJjFoRKoKGNy9MFEJdWjnVxTVY8p/iPSIi3ANvfHzWjL8mbjOXsmDwJsRXKOU9IsMSkUowlEpKRFEUVhHhlAshC2U4wfzJG1v5dXDeE9HLwXpPegjNxEq8V+2Ga96k8bw03RlANqHanjgucYj1pJF8GFLRtYJ4hdIrq3bWS8kD1x/GbOj4vqEqpCGzatCIShrjcWEX8xxmwxlKCM3QOiG0/DpHwryCZrSOCKrMitdKz9usGlm1wP9T46jTL4aoMX5YyCVJOH03LWsGn7MkoUAhkjxHPWqQ58NTRFDIBpMsTK65Kqh5Bk6fG77pXXctKDRjwzD274eGZvC9cYffXqFEpM8w/WbC5df5TZ9eg7/Hm0W4W6xPLLIsEz+ZG/JT99YUHg/gZs1I2SFY1eHDGzL5cuc3ZE0IL1TdXzvRzMmUeJfSW6dabac7rV07rxbReibO2B4UEYngcMZWqfZFChnqJWsmWPwMvQ7UV4HHSSoLze5JTd+lY6UQDoBQnZSGhMh9aYYKG5pp+s9bhoQ4klGSJN+TkdIjRvKtOKGZchMOEBpiUqR1QpzS9RU//dV5JhI6MUpSkyoeXnddQhY8HwdVTHzVxqzdIxNkg/XntiSJkhhclZSu2SUiUB7DIY0qUUtcP4qdzzxfTk2sQmjGUTm6ay4Ku+mbtXaa2fnqSYOQM/xcNMwkHduVMKOJSKhSKqdWACAVRSp6RY2kCTU4PM+HsPFzvWlSxtdQkyoAbFalGy4iFqwiwhMFnP4JgMytnloQIVLCeM6sGspWYWuDCKbS4Z5CKEzmEV1zkATwa3BIS7SRHbNeQZWoM+RwylFE/PvLJlTX2BotaEY2X/HeEb8GzcLBJlQcwhErnQbMqtJz+EoGQzKoWTWgZJhwC+3v0vnaDSmxY5ruPPReOIyDu9s2WrbUeENSRMqsGXreJQPYDOtcT1QLs3F6lUxbPGEo0GZeE9QU2sWYm9cp486oJTh9F2/WOT3nhGw6Y3ClVFpfBGfT4FLuOCyUOfO4IRcnjJPZFF5swrW9alzSSgkVfuZeMAjUZUYTkSS1Yihnr6FF0Dj53hkfMKt6G7PUfE0gR2IohAk/4DX68/OhFukZygJiROHoRVnofC8YNDnVIvLaZJm7+UmN70JhHz8dliFEwjomOYITrYAaJxd81gxPhmiJdwCpOiiniPAqi1wxNayIZFkWzGApM0HQGy5rHCVeEgC7+bWRpB4q8U6VDnx/rB5Iag2nmnh1RJocOXJ9GXwdETc0w2a80BLvZKPOu5sh/nlyWSv4f+rhMNkctM4ILrOOr6dkyCc6vuKCP+XjImK0YZ5f0CzzCJBVPfzNGPs98DlcF4x2x3V8JSgdGHs+LOGw5d1dr4mbNYMVF1q8DJdpr2R+V2Qc2qGKCP4doXVSegFXimJnY0YTkdGQkZQpNoa/9xWRNjs+pa+Lr7qEFQX/HnyYoPQrkPFSwbEJpKDgtDExrZXxk+DvUzwfzvxCeiu3qUvF0jrdf+3aZUXEf22kYl49+T5CWTNJ/WN6ybBJV3A4MsRl4vTa3dbPhmFIEDMnzZpxCEsgNINfVzMOj6ehEk7pcEIzrCJC1Q6rMHhzGZWCJT7u/fjS7HH1pcx4MWZV0/TOhGaIWsH1LKEkrFRe2nQOGpohigkhMlwVUwDfPIkVEVqki9bHoEZanDosqx458nq0nXM5IRuYdFKVBSsRjonVSeu1RAnXC+GyadzQDC6YlpfrsaqKm0psrqcpvbgYmkEok2ZXwE4hIpdffjnst99+MDw8DCtWrIDbb799Z9w2ipSGdL16RKSwSWpBM4AQUehx4zfm1iF+TZK5lSookiKCw1H8eGmDTFNEOHOrVS34DTCV5LCpvoKyxKkRNkQkhXzioZlwbZD4GuQS74EwTkwRqfj3b7bapbmPZqV4tUkYHwZHWigRwdfwiogc6qEeCfGeTGiG82RIZlXcLyfFrErDN2Yevr4HIVCBmiWUJDSFtQAgouF1x+UVET80Q4hESXZcciaGdpg6JDVkwOz8/rhro5kxOOOGpu+6HhF3zbiKKTarOopInjmkCSsieHNvMQpHu42UD1K9tUzfzbPyg1GnZgg4r08beUQquVU2aG8f/HrQDCAAtyrrrohpJyJf+cpX4IILLoCLL74YfvKTn8DRRx8Nb3nLW+D555+f7ltHEWpvH1UrRM9BmpHUvUYgL1M82amT8XIGhxSaCYcrfA8HT6a40AmeP1URiabYOtVP7Rs+/kPkamJ0vo95RBIUhoA/Y6rZdpzqwTTbFhnLZij1sAZBleE8Ilx4gTXW1uxa6TN15qx413BjuZ44HMHgMnaclFuyyeJmZJaI2PEeMeCUDob8hNJu2VRgIeySUkdkilFNqJrBp966hKZB1I4qWQt+ZqleCQ2t2NCMew+/e69LCMrzuTs/F5qhRbpoyCFU0Mx2DaYekZh/BMpzjskT1/koXMKBiYWUnePUMWHSdDvzgzd/1SFGVj2hoZksUOQMv/9Vsm0nIgMQmZl+IvLpT38azjvvPHjve98Lhx9+OHzuc5+D0dFRuPLKK6f71lGMdjeALRxJYNJ3AWQVhba3j40HkEMtIz182u58bzZ+fvPqPXSSpqBIxEUqCS8pIpLKwXe9tfdywgwxRURSl3pQRLiy+gDCRswUKaNjOVVmx4Rx/PAINy81lgKESQOeUzKhcioLR4Ko0gHAk4cQqaKKCDYS8lVM/bXRiqj402woA2eKkBrudZM768pkhSvfbv0v/DxU7ciyzA+NkLRRz2xaEgWjuriKRgNt6gC+T4WSCb/7rq80mPPUf+IVNGOu5VJ0qYmTq5KKPSlZZjJVoDzHlYXH3o4KymzB5tOO6dWfJ0Mej44fxA2v4PXirBnHwCp4RGx1WIDt4CEDgWklIlNTU3DXXXfBypUr7Q3zHFauXAm33HKLN35ychLGx8edf9OJUt0IKCKjAhHxzKrdNyDJI0I3FnyPYS9rJrx5isQlmVjwxEVSFcrKqoJBVyIWqeuRFRE5NEPXH1VEkmqD9K6I4LmkZ3Sqx6I1BzNhmm4/o9QwDm4/wGXuOKQppLIw5AJ/GqxW8vINPBRKwV+7HpGAlyTgEXHHtZwxNY5Qcem7Th0R10CK1xiqSSIXPcPKiuQRsWOo0pBSTp6qGTQ1F89nrhWzfErFRCAqgplV9IB4yo7v86CbP03f9QuaWR+NLUDnKjE0xIL/p+m72GCKX0+ngmrGZ9PkmZvxggkK6ykh5MKQB6xaOc35Mvf58DFcvA2/PnjMtmC3L/H+4osvQqvVgr322ss5vtdee8Fzzz3njV+9ejXMmzev/Lds2bLpXF7Qv7FFUDiGhUZ5E1P8JmtIwlSr7XzKAeBDD/ie261YiAXEwp4ST9UZkrIzjOLCP7O0nrr4vMLrg9aDe1GkKCKxjrpciXc528eOxW+KTriDGVtFb7zummX1pF24qXiplVXx12xoBj0bq15UKt48Uv2XVKUjZEKtO4qIu3k6a2TmM78fNEyCx3NZLJxaY865xleyaYeMqByJEsgK3tikUvGhDr3Ua0LDOwCyYlEWHDPPRH0Y9Hy54buf5L3uvORnIFVPtWbXvLy/tzaqiDDVU0tFpPvjrXLn2gwZQOZQQzRydL/ymgpRRLi5BFOqWBK+sFk2Trq6IfoZlKoKJhmGY9B+QO3S5Lp9isiMCM30glWrVsHY2Fj5b+3atdN6P6N2bCGf9NvtonxzTc6aKY2h/CbbGUM22kj4Jz0dV1IU/I0OQPaUTEqhH9PELjFlWUzfZcqqd9YnrF9KD2ZSZ0VSJ9RMCTW9k0IdHgFkTMWccpFlGavMhFQObyyb5ePPyYVR8LwsaYpkzXDN8QDCKcGhUAoe5yodnXWwBc0C5lcuLZfb0INmVdb4Ss2q8voxWSlrdwgqBL6PVHqdy5oxSk7pkSFz4PltqXieKFgPR3cOSjREw2ju/E8VD9nnYa53PSYt5BGpeqEZc61VEahHpMUqIu51nvHUq3nSec0wSalkLnlxsnNYwgFu6XfG9+GUeMeGXUbZoGXv8fPQVN1sOxWRQUB1OidftGgRVCoVWLdunXN83bp1sGTJEm98vV6Her0+nUtyIG74aNMSPSLUSDrFkwT8hrx1qgWz6/YlnxA2OKksvLjxx+qI9Bia8RSOMp248yZrXNxcLxi8Pjn7JE0RkTwu9VoFNk422ZCIb+Q1SkBCaEZ8HWVCt3mq5axb9uXksLXRYhURsQlgw/6+pHbfNePyzK3KyFV35Tb5EGHB48zzw0STVU+MsgIghGbMa+qoMb4iwmbXUI8Ik5YbLFQWICxYNTG/51wZeMnbURSdDaJaycSMGAA/pEEVEbbXjFSjg8wB4JMVqctvqTrQ8I+giFgzKvGAtN355fRd93wDeUQsGaMkyJIAv/4JIhukYiunSuDwiAml4PLojjGWzaYBpx+M40PB2TQ4NMN4TRxSyhCKMuTEkBOq/HR8JLDNGABBZHoVkaGhITj++OPhe9/7Xnms3W7D9773PTjppJOm89ZJsIpI04nHu6XRpawZwfxIiEue8yXbm612+WlCUjikWiW+p0RQaXo0q3KmTPw99h8AyAqKmL7bqyISybJxlQieLFhFJB4Ww/6ImD+jc62/bmlsnVVxePWEzXAJhGakcA+up8LP6d8/dG9JEQmVbsfzG2UFj+OquuINP1ScrfQ/dOd1CYa7EeN52dCM56VgwjwJabd4HK2a6owp105IBhvicTdxz6xK1AY8H9d0rvO/+1p7oRNyvZTdY0NMETJBVA+8mVKPiPVAmLXZuSnBwRu+1/QOZ7SgUBFVFhySgs6ZuiRtHJrJUG+agi90hg3PtIaJOY7DaOY5K7klFLbnDTh+Guf1MQQGttMjMgCxmWlVRAAALrjgAjj77LPhhBNOgBNPPBH++q//GjZv3gzvfe97p/vWUZgNvV10/vDNZmE29KFq7uVnR+uIkI0QoLMxTzTa7id49EafHJoRQhV1QeGI1TYRe7t4vhh7/USz5W1WEpGSa3cIoaKEMuzO/Mym7qtLRhGxaymKgq+W2l1HQX4fuJRUad3Sa8iZQOW6KjlMNdtR7wmXCcN1/8X34EgLH8JBpCGwTnwev5Fz9U54Ncb13QAIZlVGtbFGTF8R4CqrhvwrNBWWVU0CahLtqTMCFY9kmE/mHULvhkyo98KEeLIsKzdimzXjPhtVM+g8AL5iUSs3e/Lc9DypVUJDO14vGY9MUA+KT3RoSiutYYILeVkCQwlUbskGCRflmWtWldbq9ZpBSoRDOJCCEs2myVDWDCI0NbSvcGZV8wxZ5tcRweZac49dPDIz/UTk13/91+GFF16Aiy66CJ577jk45phj4Dvf+Y5nYO0HsP9jYqoNVJqnGTP4GskvQYuHmWtehoZDXvD1vWedJCockqeE1OIwf4hSeKMjU3c26ImpFswdrpH18J/+6WvUu0dEUDkYj0svikijZT+Z1KWwSLPtbfRS2I1VRFKIgFj5tgIboRmdN0RuaBglVN006ucoN3B3nXSs5E8JzymrMUXBN2GUPCIh7wcexzW9s1kzPqkJ1f8o+8igjYX6P2jIBDeXLP0fJQHIu8+OQjxe2MQlTzZsgu4jECxfsTBEww0ZeNeLHhBeMfGITNs9j0M7dG5a0AxXdaXnOB8IVUucgmaFr4hI6bilKZQQlDJNF/WgceqRUIKCvCN2TVhBa5f3DFdWbZdz4ufc/qyZ/sPfNacBH/jAB+CJJ56AyclJuO2222DFihU747ZR1Cp5+Qe1pdEsj5uusdSoChBvescpIlzhNLyJZ+SXSAptbJUUi0j/FYm4ALgbo/RpPssydk1SHRGbZeOGOERFhAkHNFq2YJms6ITTZjtr8xURTGDweEO48HzOuhOylcQOw4lmVfw9m+qbGpoRyCGf4cL4OZDpUgzNkPvHiEhMDaKf9DtN0eT5qMGUG+OEeQLZNd5cEb8JTYfFJerLDBwuzEM2eDOmVETQM3gbsZDFQ+uVAHB1QHgyY4iXV0eEVEalDddw1gtAKPRDPSKZMw53tvUycmivmYhHxC9o1kbnoDzXph4RRhHB6btOKXcUaikK4R40ZIMqq+LKrQY2Q8aSo7J2ClJUxO67aMw2YQCYyE4hIoMMroqpVFUVH5PUChpmwddsZTfONOICgD0ZfKiCVtiUzKdiLQ5hY5SewYZm5Pm5zI+U7sH465QCbpKhlFNEpAZ5neyWEAmIe1WkFGh2XsasChAL4/ikARO+2Fp5PwkmNzY8RTfLWGhmsmVfV6wQpPSQwV9HFRbqESlVIN8j0WhZOZyrrOqFOQLpwmwDPS4cYjZ3bgwhSFRux6TFkEFDEqQaH7SgGV6/VznVM6u650vFhFZGJYoJ7esihzuoIuKGdtwS73xYB3ffpd4UtsR7955G9XQyYNp+JVepa65Nk+ULpwG4NXa4tF6nsmrb1jDBTR5dYyo4z+dk0hAvDa7IuquHZmY8EeE2WKnPDD4meUSoOoDv4W60AdVFNJ/yBElskidsirgWB1+MS35uPlOFD/0AEBWoyY/nFBFMMnyTqPl074cuUtQTHGqhalQ5PsGAascmKCJs07mwsTW2BpY0MKEMAOlTvW8E5ZvK8eukIRKbMZOzRllzbxxyCW34DhFhFIrJcn1+CMTp0ktUAbduCiE1oZokHBFBKgQ1mtJMFTyvT3xcAgDQIU4trAoJtUaazPNXySdrWgbeUxba7hw0a8YPvRAyFPF54M0WAGXNIOWzQtQWGn7BtXtoyMev14G6+uZu1VVq+sTEB8+HFRE31FK+zOXrQuuIcKEZnL7rFi+zfhAamskQyaBkj+vQuy0YAEFEiQjXgXerUN8DIOQRCYVzeiM7sQ6/UmimgYxfnfEBYsGkqkq1ODpz+CEpqZppFYW8JjhPRIInBmeUSGRhW02ikhcGr20iRbnoIXuHD83ElBa7cYca2XXm6qzBkBsaRgnWEWHIAJ6LM4zi7yfJJi6FcErlJFXpcD4J+wSM9prhKqty83H1RvxwCkcerLrCjyPqSlCBoSGLznHsTWi03Cw1qaEcW0eEZs0QLwrNmrFEg4ZHCFEhoRVquqUFzUoyQbNuUDikQTZYfO+icMlBadQs/MJhTm2OAlVQlUIzhojgrBYmfbfd5kNAAPb3gJpVcdaMe9yQDpQGjFUVQhDzzK8jgu/fmcslR71iELJmZjwR4RQOSXkAkJvehcI5Nvzjb4YsERnyNzh8j3CoJe75ALDhH9ffwM+P5+CKd4WJjh/6kZve4U1SnpsnAIJqURpOUwkXp0aECVQKyQkXFJPGduZqtOynYq5sO4C/yfuKjJ9hw4VHcqSWlUqHsE4plEKJlTcOKQsho6xIgBI8Imw6LWNEtaqOG+ZwCAarrsjkxzerch4ROgapGWiTN/fD85RkpumuuRoiRUJ2Di1YZpSOClU8xO66LtGpUEXEvF6kVkgVKSYtsxHTgmYtt7FljTbMaxeuR4P0b3HTfruKSOGnC9s6Hzht1lUnsK8Eqw/YaFpBxAUXOnPrlEB5bzNNw1E27LN1jsl1RAzyrJPCi0HJyqBjxhOREU4R2Qa1IrSJhz0i8qYv93bhN3I8JnaPoOejx/ASSxaYZ4grIpzCwagWAZOoWOIdkwUhjIPXZubD0rGfvdOLImLmTQjNENKASVGs5oh4f8anIY2VPRiUELhETPSSkHunhlxiJtnQ+vAnV+th8ceJHpGAuoJDS5xyEjK+liSDjOHUjEarXY4DsCShPB9QRDCZKQqrrFTpHNSrQkI3UpoxJSr+efeTfYvMjxUTusHiUvi4zQEOKZvzZV2O3G2m12i1rSoRMauW6gxVRCqWoJg/m5zcB5dnrzDz5LhnTWHVBxzKMT/jnAnN5Dmg0IwlPRi4Q2/5WvUQqum/HqJExIZmmNRaLjQjkYReDa5J49EGhOV5uq48txuSQ3ZKM6kcakklLjxZkM2tXC2RWIGyyYSxsbklRaRnL4wJdaCNQMxESVBmQqGZmELkrCESchHJAONR4RSRzlh3rRIh8Op59BiaiXlJpPVZ86tRjPyNGI8Lh0oE8iCEqxotd3MMlZVn1RXP3+GrGTizBneeNRuQXPWUI1iFpyrg+1FDqFU83NCK3yuG92qUqk2k140J8bTabeR9MGqMfb6ms/bc+aTfaLfZpncALtmNFTQriQK6H86OaaGsGZymi183qbldJ2umM7bddiu0ep12UYaN+blkCYpI1h2H0UuoZgAiM0pEOM+HJQkBtaLhdkct/RIhjwijDvChGT+UgzcjPhRiiAUXaklUOEKhlh2goERDHAm9Y/D4pGwV1iMi/6yoIoJJBlUEuN402+RVEcmFS4aGGL8MNbZylUi558JjPRMqUURE5WQbQykSWRI9JxX+WXyDKX/f0Hy08BmXcos/BU81245plVdXXOMw7yOhYwRFJBDeMZtVuWZsnEWhEewzkQuWFc5xsekdUVT8NFqXTJhiYOatkmbGYGLHeURaaO2eD6TlekSwCoD/ztwUWqagWenhoLVH0DUofIQNpOa1zwlBcbNmfA8KVjFwaMZm0uBQEJmTsIycUUSq22Ma6QN2rdVOA0aGOjXdevWIALi/7EkekV4VEaEAGk2XxffoVeFIMZ/iOXpXUDpjsKIjb9LxLBgAwX8ipQY75enb7rpDryNDAqgkyvWmidcG6d3YKoVw3HkTSQOTQit31SVm1YgyERs3STb71JBLLAOo7DVDxsmpufym3/nfVzHoONzRl2s0R8Mu+H6WRFAlgQnfYCKS8+c7c3TVDEERwT4TWuej9MaQgmM1pCDg9VpFhV8DJTLNllUt8HEn/GJIDBP2cdbeVT3wZk2zXHJCEMx1ZREyRhHB2S64663bn6ZzPe1P4yoi5S0do3WGSBBOKaal7GmacWcdfh0RziNCs2Z6sYgUAxCcUSLS3bi2sFkzfuFZMTV1Gz0iXObGCKO6mI2xSjIIynUxJsuQh4NTaaR0XOkZpE2vc09XoQmHF2Riwa2Fq5sirR2/vmYNodAM3dhTwk+4EqioiBBy0UQysBhGiZALZ2xJWtrOce/+TDZQrMCcGMLxQi68GjNEslxS54sTIKN0dO5LyYM4H1NW3j5rdy6P1GTlPXG9FPwpeIhszg3uflU7D8764E2vNjQTKjlvNk/8OuES7LiBniEYmCjg/2l3XLHXDMnk8M9bMoHvz4VfaNM7HPbBiofZ0LF/xSot7n3x+42Tvut02LXn6bkq6rKLPR805dfJmsEhm6ZPaKT0XScM0/0Rmt8hp8Q7IjcYXPfdXsyqGpoZAHDqw5aAWlGt5OUbBauicCm/JgsmsWia2Uxxk7lQejCAUOQrRVVgQgXBcEgi+aKKCN4A5SZ5vfk4uDBHqPtxuZZSmWEUBrruEAkgioiTDRLJhOllrBTSwmuw83bJgLApp3hEfE8HP6dslE2bL1YgrXwWUbFxVQxfESHEwHyqxwoFCc2UcwnG3E5oxpIHHCoTPSKsAsMrFe4YPjRD/RfmfviTcg0rEiazI7MqgFiwjBCVRukBIWShNMwW7nlKZNquz4Ntekc2eVy0rMFsvuZrSjbw/1gRwUXF3NBMXp6n5yo5qbiKCAR3Hxoast4Vfv48R1VUkc/FV0Ss0oKNuRhZ5veaoeGbQceutdppQBmawRtsqYjwLw+tqRHqpAsgKSIBtQIdM9eE1Ao8D1+LQ1ZEXGIhb9C2aJr/iTrFUyK1pwewz9vE4ROhwR9eH+c/oWt3qqX2oohENld8ryRTKVU5nIJtiaEZ5udSbspk3liqLVZk5N4/JEQijIsqGL2OoyGcRM+JZ1YNmGQNUjwbnWtQuCSyrk66NZ9ZE1MqAFzVxPaI8c/Tqqlc+u5US1gHIRq0gy/teeNVZiVhBa8yK/J5NBHp5ku8UyOsfR1LxQi9Z1jVw/79lySmJCnuOd6sCt3/OSKSu0RE8JWY0JZvYrXhHzdrpntPRDCcEu8kDJNnvrpRIb+bXK8ZRjQXoYrIAMBsglvQphZSKwD8sEaoky5AuFYJt+njfHkzTqohQu+Bi2AF64j0aD41hIANRwUNpW3n/+GaX80Ub3ATJfGS11IqEYlhKFp3ROoazK07RAKoeiKVjsdrLsmQCQGQ2gh4vb4i0gtxCpMbrMikZrnEzKqiIkKUgjKNNjW7JqqI+CEQAE6h8Ddk498IZc3QtUljsJJBsz3o/bDa0Rnjb7RNFJrhwy5FNzXXPD+aw1FE5Owdv4S7q4jQtVrVojPOFBajZlbs8+DDK+a8fa1ojRKsCOO/EbM2TOZLgkCyoDoGUNes6hU0Y9QSp/5HgcgCybThGtY5x5EaU5AS8tRngj0uTXSMvl9yiggVQHpJ3x0EKBEJhE24TQ3ADyXgT+Zsn5aAH4MjO7jJXEl2ImvyFQgcCpE/zTtEJBQOGXKfuUN0Qj4XuvmHDZfm74YqQLz518yN1JmUUA7xfQTriDTjpIVWQMV1UvzsFjKv0BMGIOQRkddLDaOxNF/8Jr6t9UFkEyofHpsi9/YrtaZ5SaQ6JzgEgq8LmV/NPUMFxvD3U612QDXxQyr0ObG/A2ezuF4TrJr498LzNdFmzSkiTVzYywn/uIoGDQHVyD2oqVYqLGbTd21ohnbXxV/ja/2MmjbrobGqhx+aoeeoJ4WqHnhMu3DPYRXKEjF3DeVxKa2XGFBxZdXMUz+wgdUPzdhndX83OUWEGusHHUpEuqEZ3qyatumb8VwnXYBwHZFkYhHxiIwQYhHyZEhrSvGUlOEo5AAPVihNUDiyLEMVUBPIQo9rt0XN4qTOV3JkskUNwj2ZSpN8H2Ys75VwxpLiZ3Gfhn3zp+bnXk2oMcIkVVaVFBbaQya5sqqY6VI4GQtsEbKoR8TOJWfW2E/jYmaNY0S163a8Jkg1sf4PPzQDYPqjuBs5XYvpsIvnoN1zacEzPFeTIUT4mbAPpEqICk7BrTGqBucRwRk1YY8ICr8Q74b5XTSPjImITY3tnMPhELf7bjk9KlzmKiJuiXc7nlNKcDdpLmvGqDdmrDnmhV3I95jUGFDVJAQt8T4ACGW0pIZmQuXIY/cQrxlyiUVoYwYAGO0SqokyXGSzbOgbJl6TmRfLoEFPCdmgAcKbdLn+gCKC5/fIHRfqqsprZ0kRGR9KU+7NKOoqIqEMm1TCwK4hWMHWJThStpFVTjrZGqH7240+/BqIno7tHZeaXRNJucVqkdTJtybcU1REmm3Ru4JJhlkbzayxIZE28nZk7DyOMZYJzZjXgAsV2cZxNn12iFFEvPRbUhnVPI+UFWPOU48ILpiGzZh2fbJHxFFLmJTV0iPSsK9xWeyN+Ec8RYTNgOnM6xYcI112S8LRna/0iLghFLNMQ/44wgHgKh0NRv3gzKrl85Pflwz8dN2esmaSR04flIj0WOODu8YUHosSF+ce8uaC5/I9IuF7GGXHqjSJPhe0tlAoh27mAIKRUwhbiAoQ8XFYs2o8NOOuPWWzlo2/nkckmKJMFZEUEywhQwmG2ZBx1ydOQkYKus9Uq22fK+H+Ug+ZOiEsUsaOXyBNUFgq7rMkE5aYZ6NZOJ6YUH8YsTgam8lC7lflxzjVY5k+MvTTK+4+22zJJAKgs7lNBXroNJp8CjCtrEoNr1lmy6ljMlPWCaGKCc2aQZsvG15B9/f61CACYBTVqnMtDb/4agn2iOAxrZZLNgAks6qgiBCFpfSwZPS4HU8NqOaens8El31v2/VTtYOSjDyjnWZ6IyKDgBlPRNjuu2bTF0Iz20oSuKZ3MbLjf4oPj9/SaHbGB0IVADi8wWzmgcwfzvPBhaOopySkFuDxW0siJRMXSgBiHh3a+K4sfZ9AGELKgWzIjYdbguoJ8bRMBklLYngEvZFPNtti3x98LGpCFbwfUsZO1HOS4OnoPAvvJZHIw2TAGIpDLgC4DLzsN4l5VzARkVSTKRya8V6HcGgmy9wOvVbNwIqI3dBs5o2vSHhN8RjlAdcCMYQAGyuxIlmGdlBWDBde4WqFlGoM+vlMBMiG+dvk5i1JChcqounCSC3BZlVOEaFF0BrkuCEdXDM87AniMmSwmddES1L6yLAekV56zQyAJDLjiQhb9TSicNBNM7bJhutkCBtzzSUvoTolAJZQlaGZROKylWzOQxW/giiA3QS3EmIkKxy8eVZMP67S9RiiJhOA0k8SWTutO9JLT51gWMRTOQKKiOARSZo3SREJz1ur2IqUk81WqV6woZkKnTPiOyFqQp0SAqqcxEIuVOmQ5hOMluUzl6qAG07han941VAl/0fArIrHSGuqIrLSJJs3XRMOzUjhG6nWiKM4hLJmyjogTHYOp94w92gEUnC50AuASwy8jBw0bqJURNDPjBQtw68f9YhwtUlw2ANAqiOSu5VSzXy0jkiLP+5WaIXuMTc042XNMH4QPjU37hHpLTTTfyYy44kIp4ikqhUmvGLCIaMRBcWplJrqQ/FCFWHissXLsgmTI2tulU2ZeHyywiGZPiMekXJ8ILREm96FDKX4nnTtbDE5gQSEFJFJqoiE0mwTPD9ShgufQsyTIbpep55Kox3J2ukqDi2X3Hh1RCp2PnedxIRK0mijikiPXhKJPOD7xtJyJ0tSwxdHw4XPpHVhAkE/kds1+WoHVV+w18RsXvS1ckgCF5rhysQzJl2z+XJkwcm8IQXPOl/b8Ittmudu/LjGEpfVw92bIyIVjmx0z+E91ys0RgmC02QvEJrpVjSl85XXlF4Q97mpd8TMY15HvM6ckpbcNsgzyDOfVHgeETazRkMzuxTohl8UhfWIJBCLzv+dcMisul8SHsAqKK22jVVvLTfPRMUi4vkwJGiLt9EJCgTxfBgCI1du5YmF+BoNuRukeQ6JrHkelKY8v9k8TTZEamozVURCfYFiBcI660gnRFJoJlQnxfeIxMeGPC14Y5bIhTOOmkZJnQ5JEYk1qYuVlo/WESGKzZRIHqx8LhU9w6ZNqQgZ/h7XEQn2oxGyb2qMIlLzFBG7icc9K1LBMu68r2YAuEqt48VA4RtOmcH3oOm9tURFBNdcoQ3zAOzfn7t2PvzinnPDNjZFF2Wk5C55aBe+f4Sr9YHnK82qJJvGCc0YcoIM01lmyUyzbefg0nDjHhFeSUmFhmYGALReB67mF/N8mD/gzZNpiggAwEQ31BI1uJqNf8olCqP11NBMbx6UGFGg46PEpeq+rj2vZ8p8spcVETM+5M3ozOGSnJAHqJdiYub3oyRESWZVN5zEkguicqSQIS8bJ5D2PNlo95a1IykipIeMnOaLNgG0uW5/ITU31CNt1lOhe3bHmAqisbmwIiIpOo1mIY6xhlZUPyMQdpHWgxURmvGCxzfbbc/fQcfi0gXsHI4PJezzoIXFpDomVUaFMMewUXaC8YFI4ZfO1+7vEC397pzL3LVSsyr+X0rfpWElz6yauWpMuc7M945g9cSA76zrh2ZoQbOe0neTR04flIggRQSrIQBxdWBrSRI6isgo0yQPoPMHbX4xbKaNUVEiPhRDdgwRqQmqCwnNWOISVmm2UmIhPAMtgBZXOLrEopk6P+9BYSvVoo1potGyxcwEPww1f4ZCKH7WTCg0Y49NNjEhSiEXAZ+KkOobDPmQbJzYWEltwMdi3X977ZYL0FVjpPlQKKDdljdzP303omIENnS6Nsnb4ZhVxSydcDgEf98IqB2uoZVXe7huwFzoRTLOYl+Fo4gwXX4dMsOcxxl01TLzxao6ZXddpo4J7aBrQCtLuyEh93eeM+HSjJoqQ0RoOIUzsnqkp0xvducqFZGMkIvcb25nxlHS0Un1dg7xdUSYgmbb4xEZBCgRwWpFo13+4ueZ/2ZEr6GbuLQp02va7aIMoUjkhZo3Y8TFzLPFIy6R0E+p0BgyFVcsiqIoSZi4frKhx1KipdAP54nJ86x8U51otoNKBIAfQgkVrBMrqwZCKGbdoTVL4aTt6aiL11v6OQLhIbyZhjwiXpZLjwqGpDqU904lLILCQkM41v8hk4fYhg5gUl358JLTuyVWayTgI8HeDU6pwPOkEBps9uR72tjzXGVVANeozykeOLzjqhqu0ojP246zvJnYLUHPrI/UCmEVkYZLAvA5KcsFwP5t0wZ27ZAiQlUUErKhNUnw/alKUh5nfB28WdUd5ysiYUNrjJNoaGYAgDeYrY0WbJ7sbvhDVTYtFcCvYppCRHCmzUSzVf7wJWJRFjQjCkdq1kyMWNDKp7FnMKpCu+i80W6JeFZKBYXUNUkx9ALEPSh15CmJhWZ6KfHei8m2klsJebKJlJlAaAbA3YxTysyHQz5UPeE3eWdsMxaasSGXUKE7ufuuO65ayR1zXyzkYtcYHmdCPbYJnTuOC3FQguF8Um61A34TRhEJEAiJlBnSMdXke8Tg75uOmkHDN93NrWkzWmoM0cD+DkxUsBHT/C1XiR/BCc0EDK9bGSLielB8MoELmtE+NQBWeSgLMwY9Ipwi4qolnCJS1hExWTMFOGZVPEYK9dBeOB5BYQuXgXNfA0kliakdGfhkgyNuMvrPRGY8EankNpugQ0Q6v8CS8RTA71wbC80AuButuUeWyeEEyZMxK6JAmDoipW9FIjqe4TbNw9FZUzs5NDOZoEJ0xptPQGbzlZUIfLxDRBKNucRUmpI1E9rYO8ctcZlIIBdm7lSzalEU4ZofSD0piiIxLVhWJQD4mhncWOzBKIpCVAHwMYcE0Xoj26iccJ/W6XNIWTNZljmm27KOSCikEsnmwSqEb45FagezAXeeA6kvsRBPuxBCM4hEMEQFf2/+NunrZ76farXYFvQ0ewU/C5f5UmMyX2hTPDqPUWz58IvsH6EhkwohnPiYeU6siFBlh14j3Ydthkc8IrSQmgGuzVIeS1BEYmZV6QP1IGHGExEAXHCsCZsmwyEQAN/PsKUkL/HQzESjZYlLrSI2Jxr2iEjTWSsFTUO2RIEnLmY9RtqNEYVaxf5BTDRaPYRyOn98WxKJDi3xLody7MYWq5mCyYKTFZVSWTVQTMxdR1gRqVZsW3FnzQE/SVF0NrU0E6z1feDjGE5oJmDCxXNKpdHxOgFIJk6gNknHI8KPy7IMZcS0xDBTMmFBWR2TAsFwxgUyYmLpsO79MFmhKg0OzfAEivV/CMqKtGZsZhVDSSS0QrN3bOgFeUAYsmPO43L2+Jk4wyk2q/Jl3DNyLSYx7n1xgS+/oFnWXVuGiBMxnmaWKFCyQDNebPouJSjgXIcNqFYlKcq1dOYAB3nmqxe8R4RTUkAcE+vEq6GZAQH2S5jQzOyQIkI2zc0lSZCvwaGZmJG0MxfvQ5EUEUpESuIi+SbQm/vWRisamsEdgSfQ+FhjQJoFI4da7PqLwm6+Um0Q3D/GllaXQjOWtEy12uWnu3B581ZXYZBDGJ3jSBGJFHnDGS4pdUTMOsJVUHG4pe0dl54t2UtSxtP9T2KUEEwJno7OMRvuCaYYJ4RAxFAPrV/CKSIMEcHkwPphZHVFzIhhUnz9sItVKmLF0zrraTlz23ns5sml5zppwqLy4oZWPEXEGOyFrBp6fY0xowJYwsCl/nYyblwjKB5bkqRA+CUlawZ/PSmoG602lO8NovIhZscQ4oLuQYkDDfvg4xzpoB9W/ToiYbIS9YiET+8UKBEBd9PfnBBmKY2hk5QkhBQRG/7ZElETOuPNmtrOPWK1TbZ0zaQxlaZTmr3ztUMshKwcAFcJitcdMW80XcWlkaigdDcWw9LFTb2GN/UYAcBhHLtZs6EZ5IVptIqot8XxqkRICw5XhdJ3aTl2S8oC5AKl5GYZb7R2SItQKAuAhlEsaaASr0dEhPAHvg8mN0HVBisnzHPjNUaJAVYFIs8bC82EjKg8oQnMI1RNNdc0Wzbs4hU0K+tYSJVTDVEprIemSje0znjztyylCG9lQi/4ay600ylX3vm6rI7KeURafLG0kmxw/pKKSw54j4islkh+D9zNlzbgs6X2eYJiCBAbmvHCJuZ/Sih8ZYM3ovpKIv1rx88tqe6DBCUigDbxqWaSR2T2cOecCeP0lDUz1UJ1R+KqC/WhyObWzvGi6PwRxtJlHYVjqh0NtQC4YYuJRviZMSnohHJiPg77+kxGyAKAq4jEy+XjMI79FMVv1q4aEU07Rpt7zKuCPRqhsbgKaic9OcUjYscNM6QBXx/LmnFJg0wucsesG+5f4xCMUsEIhHBihKU7buNE01u3d8+AQgFAU2r5Tr6uUsOPwTVCxHBIFd1LCN/gYlmx8vXNllQ5FYVumKZzADbFtlQ0BPKFs2I4ZYILveDzfOM6+0GFS9+tkntzfXQmCQkAsKpKUBEh5yhBCZ2jnhN7n+51pFdMJcu8Gh+0Lw2+J99Hxr3eH8N4RNA9Y2bVYgBiM0pEAGWcoKyZ2QG/hwnbGCJirgmqKN1rNk81LakIEZfuOY/sCIoF3rC3TiFlR9gU8TVbE0ItAG4mTGyDxptCx9za+YMVFRFUiXWrQxbC6sIEGi+GoRBpKQlRlW/WR9cdK8TGZ+/EiEicPDmkJSVrJmAC5e4fzq7BpCGs8mDiMBVSWTDBCJaX90kQT2w6145PNNC6ZT9GSK3BXhLJ1JpkVmVqhHhhF/SJWVZy/HVLJGKqaUMvLknorgWl90qm2AlG0eiMd0MzuCkbHm9+7z1FxXg5iL8Cf91iDKL4PF/QzCUpeNmhsI0lFSbcSBUR5IUhCkeo9ggeR9WHSs4RBz40k2eMgTUSdjHz4R9tngFgjSTqEQme3TlQIgJuyKHcwAOKyBykiGDzY8isOtdcM9FEGS2he9QAoENc2u0iWlm1WsnLN70taMNNUTg2TzVRXZM4OZpopnlKcNn2rRHPClaMYpt/Z+1m7nY0a8lRRAKl48268YYde05eEZGIQHdsA6fvhj0zbl8YmTS4pl3h/iicJdXoALBpsHidIrnprtM1oYa9HylKR6jLLb7WKCJcOAorO5JCgecPdc3lSqrLtUYC4RtGNQn1tYnVEXGqoqJ5cJn4MvXWC81kzhzUA2SIylYmtILXwIVe8PxYhTRwS7zL4ZfSX8JmzfgEq5eqq7RBHyYiZsqSvJhQSyYQDtGA6ns8bGiGjM390AxnROU8Ipgg0mtioZkBEESUiADg0EwryaxqzrXahZOOG/JXmGs2TqYpInMQcZlAscsUopBqiDX32DzZTCMuRllIJgtIiYjWBfFJjrRJO+MbrQQ/jNlY4yEid92W5MS8Kh2PiOz7wGM7YYyYCZZTT2RFJGYCBSCZKyFFpMZsqIIyxSki8fTdOGGZbKWN29hVROqMwsVVMeXNqj5hCaYCC36TGgoLRKu9Nq0RVa5HgiqrJvg38BhuDpoVM0SIhr/WmOLhKibSeS684jTda3FZM4TkMEZWLvwi+UDwOfN7RY2nrkekq4iQ3ykuPRnP4RlQmXALrV9igDvyGsSMqOY6fIj2rNkFLCJKRADcjJNNZlMLmlUrJePcNNGMVj0FAJhd7ygcGyeatupp4B6YuKTUHQFwVYUUQ6y5x2ZEjkKZP64iEk4nxuvpbOiJ6bsorBQKjw2jbJVY1hJWRLYGNnUDlwSEQ0rDiOTEOhhz86b4SVJqfrjpw2H1wvFzcEZQx6cRITdV+8ncSOzcZp/ccK9H5cSELmMVYqU0WAC84bZKqd0P8yByZkJQCbVGpLBLsy2PcZvN8WqGeX7zwQlfB+Cm70qkiCoWfmiGEhW6IZIQiaCocAXNKjh0xNYRIWtjjKxcsbMKUTe4uieUpJQ+J+RNM5fR18S8hH4IhicXXNaMTd/1VRU2a4YqIsx8znUZOIpIPH23/5KIEhGwGxhWREKkIsuychMf29ooiUXI4IrDOWWWTYi4dMdPNdswtnWqs85A3REAG7bp+FDiioVZ78aJZrRuB4B9c9461U4y6OKQlzW3hj0uHTIY7mbcmdsPn0gKE1ZmzJtNipKzebJVbjqxrsFpZlUUxomkHGNfS0qRskbLhu/keiomNGNTnjnS4Bpgw+TKbPabJpFXI1pePi00k0JYTGiGm8tVROTntc+QZnxNK2gmmF5xiCcavsGKFDG0krAKruGB74NLwItEI5Y10yX6fil6Qwik+aki4hONFmqYx9VBsWoMQzaYEu++kZUhIkIGDCYvElko/R2CSsEpIl6Nj5BHhAvtJFVWdRUQ5/tYaCZ4dudAiQgAzB2xpMJmp8ibIADAnO75Z8cm7LHheKbNxokGbEkwt2JFZt34ZHe8vHniNW2cwGQnLfsnKfMHmXpjWTMA9s1802SjfGOWCMAsZADekpC5NMyoLTGPyNZG3NiK1/3ylinvfv5Y/JpEQjNMHRGRNHTXPB7ICsHjOmMb4jgAV5UIldDHm6V5vWKhmfGteJ0xj0g85LJlqlnGrusVeVz5zCHy0wqneJsNMJSBk2QgRZkqUrYRHiOFi2yBNVxZlQ87YRLhGkk753FHYaleCVcHBH9vz/OKR7kGoU7JBEMKbK8ZWz6erazKZNyUIbCWrHqEzKqUwJRZSsbEylxD180RDgCGoGS+ImK+9fwgue8nyTJZfcHzOZ4Qks67KzTAUyICAPNGOmGTsa2N8s0oSkS6ZtJnNmwFgM5mJ20qAK5Z1dwjFHqo5Fn5Cd+Qnbnde4r36D7HOCJUIaIwB4VmNiV4Y0wzt60NG8IK+WLMJrd+c8M75q0FkSLz6TrkocHprTZrKUxysBdG+oQPYDerDV0ikmeh2iBWEdkcCdHVESFKDc1sQGSII1p4c3l5S+d1i/XnmcShMo6IoGcd39ro3js851h33FA1Z9/4htDvjg1/MMTKEAxMbAJpvlYRCRCqZgEhIzGdq5pn3qf/IU6lkDwiLbmkfBWNiZKVNg7N8GO2CEQRqxOlGVVQRMTzJVExigclKq7i4afvuqEbzlSKO95yoaUJhgRVAvf1PSL+PaVy7Vw4xzeaCkSkNLGCO57xiHCN+MzcKU3vYp6QDHzzahADIIkoEQGXiJg31Pkj4U3fqAnPdEnCnAhJwB4Rc495qffokp05kfGGqDw3PlFWCAyRl1nIh2LehEOqjtm0Jhut0iQYGm+UgRc2dhSdejVnjYwAlgC1C4AXN00562PnRsXBYqEuM3ejVZQqR4hwWUXEbMJyA0Rsmt0cCSmNohDglqkw8TMb6/rNnfUO1/gNvlrJyzdOQ1pE0oBCQ2ULgEhX4bGt9jXgYDbADYYEScSq3OzTQjh4XCicEgrNcIoIR1jMpm4IcGo2D1UpuBLvaWXgeRKBS7xLaoZRVz1zLRovmVEt0ZBCL10iIRAVSgjo6+HVEUG/vzWk2LB1RIwRlqtBQokDDtuQhnh4SVKVVNpEj1uH/T7vzpsempHIjB9ySQvN0NBLRkI6XtbM4PMQJSIAAPNHhgCAEJHRGLFwScLcwIYM4IZBjJw8N0ZEeryHIQVPvdwZX6tkogcBzz++1SoiIUJlNv/xiWb5RxsiOubehoiESAs2AK8bn3DWF5o7JTSDw1zPjaXM3XlOQ1qCGTZVqwgY8icREaPwbNgyVYaqpHRsq4iEiQAea9YrGa2xeTNUch9vKIaMSa/BEHp+AJmIUOIAEDa1mpDUUCVnY9xc1oz/HDhUElBEKKkJhG9Sao20C7uBhsYYciTWI2kW0ewbsSoqes3smEh4x9t0w6Gb0oza9MkCACYqvqLipu/6JejN1yY8x5WHN+c4j4i9D5qTZNvUBPLAhXoMzHSpZlUuE0Yamwmpvuw4h4jQ713yoaGZXQSlIrKlUb7xG3IigaoVMVIxB3lEzJt2lIh0N/mnE+9hzj/18pbO98O1YOdFsyaz8eNjHMxm9PxGO352goKybmNcNcIGYEMWgv4WpDDZdGh+fI7DXOPxuc1zvrgxrDAA2E3LKBcAcR/M811iBiAXnKPzpqwhGppJrI+Ca6lYIhQhTMZQHRlnfve58AcAJrs21MPBV0TCqcBJHpEuGR8OqCuTTblwG16r+Z2klVxxiMUoaHL6Lt9HBsBuxlJopsISEckjImXVUJ8GJTLd64U6JDVKVBilAXff5ZSNci4mxELn6pyjrwN457zuuwEPhhRuor+6QUWESckF8JUKLmuGK/vOKR5OKCan6bthIqJZMwMCQ0Re2DRZ/tHNiygixl9RkoRIaGYOMmOaN/dYaGZb75FKXGYRw+1QNQ9++jfrfbqruMwaqgTZ9lziowmpEHj9hhil1Fnp+GHCNUoALGFaV4bS5LUY5emFTXGTsNmMXtpsM5uk18QSkYnyWm4zxvO+HAm3OGMjpIULzcgpz4YITXbHhQnThohyYurZmHGS52ZkqJI0joZ6Qj6SRitNETF+mLAiEu9HAwClh0rykQDYZpmhnjWS+jIUCc3gTsZS1gstox4lGp7qYlVJ7vpQenCVkAIAN9zhG2MD4RImbJNyzvy8aMXZUOdaM510DWdWpb4ROWuGKefOEBkvNAMuMcnAN6+G0H8aokQEAOwGaz59ZpndFCXMH+0oJk+81FUfEv0e7aLj4QCIE4teQzNWEUkMF5VEJG288c2s7c4f88XMI+sJbf4AiCx0s4RCqoV51nVInQmlQ5u5nktQRMw6n+u+LikpyuZ3JzSvIVbPJzyf2YCtIhIfW/o0IqGZiUarlKcl9cb8bmCCxY7r3uulLmkbEUKBo4TYcJs9gH2tDQGLVYlN8YgUhQ31cMqJeTaj1gTL3geyfjDJMATBL82OyQq/9rSCZuHQTGdM5ozx1JncJRpiiXYxa4YQDRq6oaEZxoxqlCMAVy2SSBOAv4G7qb38M3LnSkVEMPHy13TOcTVAABhza84TDgDw1Oo850I7vnKSATGrEm9JRzGRn3sQoUQEfPVj3kgtmnu9aLYbupk3Et5kR2qV8o3RSJFRRaS7IZo/5HhoxtYeSRlvNn6zgcWIhfHNmM0xRizM65riEQGwm18KWTCk6dkNnbF5Fi72RtWWkDpjM6LiIaWSMJQG2zgZMqGZcAG8riqzMUWVcbN8JCXJbLgvbcKZOGFC8OLGsCJiPC7GYCzWiRmi46T7GmITDvXQTBfaOA7AJU8btljTr782l8jFapJsFTJwssw2AZTCLnlu0znLMSIRkU2vNRo2Yd6vqAdE6jVjyICUqiqFZkJ1QvD9OLMs9Y/Q6z31gjG60vvwzxBSRORwCvc1AFYzwD0uKSKcopHzc8hZM35oJ+wRcdN3tcT7LoI59arDKGMZMwAAi2bXne8Xzx4Ojs+yDBaTa+ZGyMsedHzMrFp31x1TXOhzxogCNfBGiQiZf3Y9Rozo+DhZMNJujDwaEmA+YYbntmE0/D0Ho4hsTKgNg4vgAYSr984mpCU073DiJj+bhJyyTFYczOsVm9M8w4vdOaXQjJnvpUi4a8TzxoTVHUlVMGPM5mPCVhxZHam5RI7PrOl6GtpFsBaNzcDpKiKBSq6mYjItVobvVRIRIXxTPj+7FpdISHNsFlLaveslVSaSlcORKWp8pcf8ME/AIxJQRELGU6Nu+JkxcRVFMqtyxEWqI8KTFucQW0eE9qTphGIy9xqSzhtCMQDBGSUi0PnBLp5jN/295oZJBYBPRBbNCZtbO2PsNXOHq8G6IwDgrAnAJyYUVAGJKSL0GWIKzTxi4E0NzdjxaR4Rg1DmEiVx0VRoMnewlxBZZ+h1pBtqyNdC+/4Ea7yQNaQ0VDSkTArNmLo1OCwjmZnN/cycsvfD+k469w4rLLH2Bmac2WBFRYRsqlJ2mLl+PJARY14vO0YO8wDYT5AhL4khpiGyInpE0PexgmbmZ8kZbI1SINVtMedtaf4Ke948r9RJ2JwPZe7Q56Jm1CpJc6XqTVAtCXpEQt4SwauREs5JJCjUOIrHeqEZjnSwdUTccX5dERqq8YunDRqUiHSxdP5I+fXe8+JEZA8SmqGbOgesiOyZQHYoEaHfU9BwUWx8r89AicEes8Lki5KDXsmC8eFwoGrPvMBYbu6wRySdQNHXJNRkkBawC1e9JfP2QFpERaSePidVa2KKiIHkEaEbsqiIDKWNo5umXLvFHccpJ3RtoVojGBz5MePM5swRuCEyRkrfDa2JboQsKSL9aSQvip1D3vy5dVIy4Z0nZKLuKCIymQCQ63cAcPVOMvGc6/fg7yF5WzrXCMqHVEeEbPgVhkhkZXgnHoZJOUbNq9QjQkM1FLt1aObP//zP4eSTT4bR0VGYP3/+dN1mhwETkSXzRgIjO6CbfIqK4qouvREXAIA9I8RiCSFQsfGjQ1XnjTpGXCiRoESGgqZAL4rMv4AQmwUBRaRezZ037NTicCnj6cYeCnFRshSal26WvZGLeBjHQFIR6GsQypCia5XMqvQZYqnL0nXS9SIRIZveqFDhl75u3DMbj4hBKAPHIMukOijuW35IEZHm5vwelPTQ52d9LZQIBMy17DqE6rLS/KEMIQCXGIUMpwCMYhJSNgIekZCSYlNxAx4RqQaI4B3hQjYZo1jg/+1xPkOGKie0Tog/v5/eG8qcGQAeMn1EZGpqCt75znfC7/3e703XLXYoli0YLb/ef9FoYGQHe8wacn6x9180K3oNJh9pxKU3xWJ0qOpsYDEiAuCSCaqoUNQquRM+ia2HbsqLI/PT9YYUkSzLnPBMzNdDz4dIFPXiBBURMm9oHVQ9CBEcGqYKEyfqDRI2ZbIphkJrNBQkkRtKMIaTlY404iC1EKCbnhS6osSDNat6iog/Js8z5+99uMqHtei6OCJCXwtfSSAeAIb0eGpGwGBbjqlRokFVlTAhCpWR5877ZAMThvDzeH1vQpkxIY8I9pYI5EaqCIvH0HOyIsKHeThyw5EWj5xwxzzFgyErSAOh6b2DiGkjIpdccgn88R//MRx55JHTdYsditccsLD8+rh9F0THZ1kGB+05u/w+9okcAODQJXPKrw/ea05gZAf7LHAJUaz/DQDAEkRw9k5RdnC4aE6cHGHlKEZE9pzbm8cFKzLVPIumUC9ECkrs9V9MiN+CAMnxN3Z5bnrfkIpDwzgLA6EtuoaQX4YSJem1yPPMUU9CmV6ppIkqFtLPjI7b7tAM3fAj3hQDThHxyQo/F94spfvtCOLTyb6xxzjS44VmmHCSRzQEj4hBlOx4RCamiMjf+zVLwiQGr1Uq7sbNyxVRo9+HPCJixotQ7l7sQcMUGGOzYZLDNfIYms4LmUtMPAyAJDJQHpHJyUkYHx93/u0svP6Vi+GPVr4SPn7Gq+CVCSQBAOCCXzoY5o3U4E9/+bCk8cctXwBD1RzyDOC1By6Kjh+uVeDAxR2l5cT9F0ZGd7DPAksUMFGScOBiO+aAxXFVZ9nCUfZrDsO1iqOyxBQaTET2nj8cTTvDITQalvLmRiRoznBVrNgJ4HtfQiGrKlGJQl6V2XX3viHFp7dQEvXihNdgkNKHKHZ/Ok4y9tLQSSpxEIuzkY1LykBKCR3RY5LhGP/sOHMoQJpCRJ895CPhxgP4GTAc4aFEIRaaoUSFbqpedk9EMfGux2ZVz8gaDtW4mTEhT0e636NaZs3I14jkJTFkU5aEJ0RBmiOljggNtWSQ0GsmyEP6z0TiH7F3IlavXg2XXHJJX+5dyTP4o5UH93TNm1+1BFYetld0wzTYc84wfO39J8PWRguO3Gde0jUfO+MI+NzNj8L/fMuhSePfdcIyuOmhF+CtRywJVho1OHrZfLj2rqdgpFZJUmn228OSj1cmEB385kQVHgpsEt4rRZ1B45fOD4/H6kxMyVk4awiGKnmZsRAjUPNGa2WWREgRybIMFs0aKhslhsbS8EovnpawT8X+TvSSDZSsiEhhIWrUTSUO26mIYJKRZzyxSQ0bOSpFomeGSxdOeUa8EbMl5yMkozMmHHrxwzsRDwn1pUR8KyETbijzBYAzpKZd21vVVUHFwIoIo1CEruEqq3pzloqIM5TNkMlIGMYcowqLT0zoeRCxy5lVL7zwwvKFkf49+OCD27yYVatWwdjYWPlv7dq12zzXzkIqCTE4cp95yeoGAMBrD1oE/3zuimTi8tYj94Y7/nQl/J/fODZp/DtP2Ac+/JZD4O/OOj5oXjR494p9YfGcOrz7xGWeuZTDrx2/DwAAnHTAHtEKf9ins+8ecZ+Oo85ESM5eTsgqXvMFb9Lx7CN7vpexIUVkwajrQQqRC0xacOE8Dlg96YXcSD2FqFE2lbBIYcbU0IyXBZVAbGYJXZSpIiKldmNTa6wyLEBn86GbOYBPYmIqTUo4iTPYxnwkoV45adeHvS6hLJ1qJXc2x5hhN6RscIXS7Lm4WtKL+dV8L6XkinVHMuYYQ3K4miPcMUfxyP2S7p6HJCCJDAAP6U0R+dCHPgTnnHNOcMwBBxywzYup1+tQr8cNloowYpshRr1agfPfeFDy+AMXz4Y7/nRl8vjff+NBsM+CUXj9wfFQVJ5ncPGvHA5f/8nT8P5TDoyOP/WQxfDp7z4Mc4arcMQrwkRt6bxhGK7lMNFoJyk/WOqO+U/2XTgKP127AQDihAibZEMqTp5nsGh2vawyG0r3xudiXaMXO7Vs5LELZ6FQVr0qkkg6h2SAHalVoFbJyoJykhpESYD02tNqyFIXY1xTRSJTdFOX5uqkP2/tXsOTPaymSHVaMFkZqubsa4vTwDnSk5KWTJ+LbvYx06x3fYzIRBQW//qKXCwtpHrsoIwao5aYAmFGGQgqIoa8CB4RuYqqT6RSMmT4OiI0hMOZV93xg25W7YmILF68GBYvXjxda1HshhiuVeBdr16WPP69r90f3vva/ZPGvmrpPLju90+G+SNDUTUnyzL42NuPgK/95Ck47w1xsnzWScvhL771IJxxzNJgB2MAN2PqFQvCBmFsJt434rHBb157BcjlUuSVidWnwZlb1EyMgQlLqAHkvJEaVPOsLJolhWayLIMFo0NlpViJMBlFxxTqEokIOZ6SDpyqwkjqCvYCxUrjAwSKrKE1bes8KbVP8Jh6Nfd+jz1VJeI78c+TUE5UEfFDPVuF8vCVQIZOqNjZtlZdreaWJFfIce4aSiKs8dU5zIZmpKZ3XNYM7xuJFTBzz9NQDsUgdN+dNo/Ik08+CevXr4cnn3wSWq0W3HPPPQAAcNBBB8Hs2XFvgUKRgqP2mZ889l2vXpZMin7ndQfA8csXwOF7x0NiZ5+0HB59fhOccvBitvAVxmmH7QXX3LEWjl42PxiaAQA4dt/5ZSdlqUsvgEsamEiAA+y9WRIgLamVhvM8g/mjtbIUfCgteuEsS0QkQ22WZbBwdMg2hkwkIlIWFPbEpBY9i5XIB/DbKXDXSuQYEx+p7ooTmknwmbCF2oYqwfNxxaM3RYQaiD0PSSDLxvOEBJSNUEZNKC04VHW1IhARMU1X8I6kVFGVFJEsy7z7sam5GecBkUMxGYTLvPefhkwjEbnooovgC1/4Qvn9scd2PAs33XQTnHrqqdN1W4VihyDPMzh+eZqXZ4/Zdbj8Pccljf2lw/eCb5z/WlgWUU4AAD7wpoPgqZe3wu9GFJxKnsFJB+wBt/ziJXjXCWGitR9Sb0K1b3C2E31zDGHRLFllwSRlwSxZZVkwyxIRWhTPgIaEJIUFkz0ptZiGjSSPCD4umnJJaEa6X/n1tioiCZk3jiKS4DOhRCGumOw4IhOvQZKxX9Pvg8XJhHAKQKduyQT4XYKpr6Q0q6ZmzTDjDQHi1I+U0AwNvdACZ5xiAmQ8FkEGQBCZPiJy9dVXw9VXXz1d0ysUuyyOWTY/adyhS+bCN85/bdLYy99zHNz71AZ4wyvDodM3HronvGrpXNhvj1mwPGAIrlcrcMQr5sL9T4/DKYeE51w6f6RURELmbfzJ/hXzZSLmFs3jiYgfNuA3dHy91GSSho0k5QSTD8kLgwmEFFZyiIjYw8feK0YyAHjFw/GiMIqaNwc10UY8JDGza6ykPB4v9dIxCDa9CzTLc0gK2eRx0bSKQGboyybVHomWfmeyZjgTatwPwpV4Z0q6k+/p+NYgsA+EgaojolAotg0LZw3BqYfsGc3iml2vwjc/+Hq4/D3HRb0vf/3rx8Ilb38VvC+iyJz7uo6n5wMR0/Nhe88tvw5VdcXLkozXsbUb7IEUGtoyAQOHdqRCc05oRkxTRnVaJCKSEJoZjagm1Yrb4oAjT8OOIsKFZiIeEM+MGlZhfLNqerpwrKBZLeQRCdQnCZlVK4LJtRJSRGLZMQy56BzHa/LDNZ2xqXVE/FAM7T1D64h4dUUI+u0TGag6IgqFYnBw0J6zk4rinXHMK+B1By0KVooF6BiAH31hE7zlVUui89322Ho4bt/5QcJhTK2hujB4TaFx+NO55HOZkxCawcXQxFL7Q3GyMurMw48ZrtlaN9x68BxcuIkSCWrS7TVrxjOrRq53FJGIsRWTFk/1CJlLA+m7NcF3IikieG6uPDuAq4jgLBh83KyD+rm49F2ujgglFhmEK63Spned+VziURT97dCrREShUGw3YuX7AToZPVf85vHRce88YR+YP1qDY/edHxz3p798GFz8bw/AH618pThm2UIbAgrVpml0N3QAuaDZooTu2fh1kEgGTl2WehONJJGVKoxPdArpcYrICKmh4p2PpC3HPCIe0YgqIoRcBLrxUtUDzxUqWhaqMUKrt7rZMbxfpSKEfTx1pQy38PPnDLnhG+Q5h9g6In6ohVFE8HggZtkBzOVVIqJQKAYKtUoOv3zk3tFxZ5+8H5x57Cui5e8/cvqhcP8zY7DysL3Ece847hXwF996MJhJhImMNA6nR0tZUZisSKnRWOGQlJURR/EI+0i4Gio0XEPJiinIZky8lOxQokEbD/qhHrkIGyU91FhaD4VfAmEbTBhCRdMc4yomIuhWWEHx03dtTRJuTM4oInwYxicnnvEU3FBPntMmiZm3Dm4OjH47RpSIKBSKXRYpzSZ/79R4cbzffM1ymGi04W1HyQTo0CVzYaiSw3Ath0OW8EXxUtKjcbhISjt2TLZCaAYrJbOZdOKRSGiGKiJcds5wtQKNVpOdgxINP6XYzfyhCgAmBl5NEqJQ4E/0oWZ9IY8IXm+euaRB6riL65mEapJw/WOkNOBSEfGKkDGhGVKsjEsTzsBXRJw5MjPKv69BxyPSP6VEiYhCoZjxGB2qwgdPk0M8AB0C8d0L3gB5lokEaMGsIXjDwYvh7idfhjcI1YSdonKCGReHfqRWCtjQynlEMHGgagWAT0Q4P069Vin7KFGikWUZ1Ks5THaLz40QRQUrHpwp12kiSBURtJt6XYOJWoIJVMgj4tQtocoJHucoIoJSQguXcRVUMTlgwkB4DkMOvNBMThvmMUbXjCgkbFYNGq6KiEKhUOy6WL5HvEP1P559ArTahVjQbM5wDd594r5w95Mvwy8dzoeLcD8kKc26jTIdOI8I9rRwikmoSJ4BJgGcqlLNM5g0awg0/ON8N3WHiMh+EhpComQDKy9UUcA/A0xEqHEWe0GkImg1wTsCwCsVroKC7+WTiQpzfef+OR+aQccqlHjktLIq3+sGo9/ZvEpEFAqFYgeiVskh1j9y9TuODJ4/eM858KvH7QOVHOCgxXzm0lH7zIPbHlsv9gFyO07HG1RywBs214OnjTYwmmbsekB80oPnpoqJq4jI5zrn5ToibtE0npQAyIQjl0I2tCZJxagceDyvrHAZNuZLLuSTRwhLrCleJ2smEprpsyaiREShUCgGDHmewV+96+jgmPPecAA8vWFr2eGaAtdQCRWQC6EmhCwMqpUMoMGfxySAV0TkWimYDES7AtdkRaQuqCChSq5SdoxLUOy1OLMFExecCcSVeOd62njVVklYJWfGcQXLQnVFUmvw7EwoEVEoFIpdEHvOGYa/fY+cDl3JM1j9jiPh3qfG4DQhY+h1By2CH615EU5YvoA930SSB+shqeawUTiP+/Fwqg0OJ9GMmpBHJEQ26hWqyvAqSCjcMyQpIoL/oyYpH4K51RY085+Jvoad0Iw/Dw3rSBk65nt3DvDQ79CMVlZVKBSK3RTvPnFfWP2OIz1VweB//fJh8ObD9xJDRVJYyKDVlncwbKA1hlbp/HCgnLxnVg0QES88JKggnnqDiEktQRHBqolkYnUKpjFEgQvj0JBPnvMGWNfzQRUSP6vGmVMVEYVCoVAMCg5fOhf+7qwTxPOrfvkweGnzlNh4ca+5w/DylgZ7LtZuAKcfjxKPCCYpNKzjd6PFpIAqCrzplRIzrMjUnDRfPmSTC/cUxzMVWjmlI1pHhBlHq6/SuiEZDe+w6bveoZ0KVUQUCoVCwWL/RbPga793MrxZKMv/sTOOgEWzh+BT7wz7WRYy3ZZxoTbajRnXTunlA3yIpGAVxK8S22vWjGBKFaq1cl2AHdLChGvMdbHsGq7omdv0zu/WS9Fvs6oSEYVCoVBsE07cfyHc+We/JBpmzz5pOQAAvO8NflE5TDbmjbhZPTjtdkd9WpeMq51zuAEf7+2QlA+poJo0ng+v+OEaM5b3iNgxfol3n5iEsmwA+q+IaGhGoVAoFNOCi3/lVfC+Uw5ks3b2W2RrsuyzQM7qae+gXdKtIyJXlRWVD6nvjEQ4BANsOGsmHJoxpz3ikeMxrgSSZ27TO/WIKBQKhWLGIM8zMXV4/0Wz4MpzToB6tSIWfwMA2C+hiFwKQum7riISVzikrJmqELLhxvAeEbsmE2KJjaPhm44CYs+b8vH4ewqtrKpQKBSKGYk3HSo3IvzLXz0KvnT7k0m9glLgZM2QTrzYI4JL2UuKiFMvRCAcNUE14WqOmLm5eiNOmi/jEWFLugMmHilmVfWIKBQKhULh4F2vXgbfOP+1TgjH4I9XHgwAIGbzcBh2Cp/JisiIUCANpwa7iggKwQj9bNzQjOm+C+iYH67hMmm4XjO0pHtO03nBTeGlKcIAqogoFAqFQtET/uBNB8GKAxbCsfvO987NrldhU7dRHwZWOlptt64J9ohgwiH1w6kIiggmIjWh1ogJzWBCYBQTpyAaU2/EHAuZVblKq9HQjKbvKhQKhUKRjjzP4DUH7OH1oQEAuOq9r4ble4zCl35nhXMcb8ZTTXfnrQsN+pzqr0gpGRZUE0xEHLJS9VWNnFE/KhVO/QD/WhKu8cyoHlEh5yk0a0ahUCgUih2DV++3EG7+8BuDY17/ykXO925fHEsyZgtEBI9po+qyQ071VSkTxz9mVJKa4xvhTK3gHctZsyrxiOCmd1yJd216p1AoFArF9OPL570GvnP/s/DOE9y6J5iIYBUEEw6sKmBSgvvxOKEZKXzT7YcTS+k1ZCLWfdevG+IqJLSgGecR6TeUiCgUCoViRuCkA/eAkw7cwzt+2N5zy6+xCjILhWlwWx2uKBhASBHxwzdul9/cu8bcjpZr7/yP1+KGebLMVT0yoB4RLmuGfZydBiUiCoVCoZjROOIV8+Avf+0oOHCxm6ET65cD4JKCIcHcyhlauXolmLCYQm5cSm9MEclJqMb1kPjPoFkzCoVCoVD0Ge86YRl7fM85dXh+4yQcvc889jze192uwXyRNKOaDHGZNIglGJUCF0njysPTrBhKNDoeEnc8Rb/riCgRUSgUCoVCwOXvOQ7uf3oMVh4mF18zkKqscsXUcCZNqYigmIohB1wX31hBM8esCnzmDYYqIgqFQqFQDChevd9CePV+C8Xzhy+1/hKnqy/a7zGZMGZVLjSTM4oIN84N1/g+kox8T0M1FP32iGgdEYVCoVAoesQXf2cFvOVVe8EFv3RIeQwTkVbL7u4xjwhHBMwhPpMGnGOUaLjpu+682vROoVAoFIrdAK89aBG89iC3HglWKppCfRFLRMK1PYxZFYdrpDRf6gGhzfMwWI9In4MzqogoFAqFQrGD8IaDFwMAwC8fuXd5DPtBOEWES6k1R6pM11/aRM8PvfgqSvn9AKbNqCKiUCgUCsUOwmfffSy8uGkSDlw8uzw2jDJoZnWLpFWZkAuGOVZ1aoSYY5jEcL1m7DwZaPquQqFQKBQzBvNGajBvpOYcG0VF0uYMd86FUm47Azr/VSsu6QDwu/TS0AwtYIaJBp++Kz3NzoESEYVCoVAophGv3m8BLN9jFA7eaw5blTWoiKAwjBSuoZ6QUJO7QfSIKBFRKBQKhWIaMTpUhZs//EaxcNhUs+0dM2TCDc1wx0hBs5ym78ZDM/2GmlUVCoVCodgJ4EypAACNlk9EWD8ImKwZN5OGpusGK60OYGhGiYhCoVAoFH3AGccsBQCA9596oHeurKzKKCK13CUaoboinkeE2fXVrKpQKBQKxQzEp991DPzp2w6DPecMe+dMuIZ21gUAqFTcUEyoyV1KQbN+95pRRUShUCgUij6gkmcsCQGQwzgAbpGzWp4zBc1IwTNwz1NoaEahUCgUCgUAABy6ZA4AABy+91zvnPWIWDJRrbjEg6bzUtqhZlWFQqFQKBQiLv3Vo+DMY5bCZ37jGP9kWVvEsokaISJVpq4IxiAqIuoRUSgUCoViQHDMsvnw179xbHAMzqSp5rmjclTyPNz0bgAlEVVEFAqFQqHYBVAWNCOhmcwJzVCzKlVE/Hn7XdBMiYhCoVAoFAMM07130ew6ALgekVol99N3cQl4Qjy4yq79Ds0oEVEoFAqFYoBx8dsPhxOWL4A/eNNBAOATkSyQJUOJB5eNo3VEFAqFQqFQiHjPiuXwnhXL2XPVSgbttqUSOa2sSokIM8duW0fk8ccfh3PPPRf2339/GBkZgQMPPBAuvvhimJqamq5bKhQKhUKx2wN7Ojp1ROReM5WMKiLcfP3FtCkiDz74ILTbbfj85z8PBx10ENx///1w3nnnwebNm+FTn/rUdN1WoVAoFIrdGo2WpQ71ag7Ntu1Vk9GCZp4iMnhZM9NGRE4//XQ4/fTTy+8POOAAeOihh+CKK65QIqJQKBQKxTZi7rDdummJ9wzczJgK6TXDKiIzqY7I2NgYLFy4UDw/OTkJk5OT5ffj4+M7Y1kKhUKhUOwyOO2wveCNhyyGo/aZDwDAlHR3K622EdPg9ZD+MpGdRkTWrFkDn/3sZ4NqyOrVq+GSSy7ZWUtSKBQKhWKXQ62Sw1XvPbH83q2kSr5PyZrZ1dJ3L7zwQsiyLPjvwQcfdK55+umn4fTTT4d3vvOdcN5554lzr1q1CsbGxsp/a9eu7f2JFAqFQqGYQaCeEGpWjRGNXc6s+qEPfQjOOeec4JgDDjig/PqZZ56BN77xjXDyySfD3/3d3wWvq9frUK/Xe12SQqFQKBQzFlj0qFdz0gQPAGX37h4ekcWLF8PixYuTxj799NPwxje+EY4//ni46qqrIM+1fppCoVAoFDsSmHgMVXLPM4LBZc30u8T7tHlEnn76aTj11FNh+fLl8KlPfQpeeOGF8tySJUum67YKhUKhUMwoYB/IyFDFDc3kmVOwjFNE+o1pIyLf/e53Yc2aNbBmzRrYZ599nHP9ruKmUCgUCsXuhFVvPRQefWETnHzgInhy/ebyeJ67HhHMQ/KsE7bp95Y8bbGSc845B4qiYP8pFAqFQqHYcfjdUw6Ev/y1o2GomgOmG6HKqiZs0+9tWU0bCoVCoVDsRshpaEbwgBhS0m+PiBIRhUKhUCh2I+COu52CZvacE6ZRRUShUCgUCsWORic808FwrSJaImjYpl9QIqJQKBQKxW6E4Wql/LqaZ2LgJR8MHqJERKFQKBSK3Qn1GtnaC/ZLNasqFAqFQqHY8ahXKzC73qnOsWTesKyIdCWRfptVd2r3XYVCoVAoFNOLSp7BN85/LTRabVg0uy56RExopt+KiBIRhUKhUCh2Mxy05+zya8wzMOkoQzM7aU0SNDSjUCgUCsVuDEnxsOm7WkdEoVAoFArFNEHK0tWsGYVCoVAoFNOOqsA4NDSjUCgUCoVi2pEjSQRnyAyKWVWJiEKhUCgUuzHE0EyplKhHRKFQKBQKxTQhg0hoRhURhUKhUCgU0wWsiLjpu91jO3c5HpSIKBQKhUKxG+P45QvY44+/tAUAAH776jt25nI8aEEzhUKhUCh2Y6z65cNg8Zw6/Lej9oZ/ufVJ73yrrSXeFQqFQqFQTBNm16vwRysPFs/3u5yIhmYUCoVCoZghyKUUmj5CiYhCoVAoFDMElQHc9QdwSQqFQqFQKKYDmSoiCoVCoVAo+oXBoyFKRBQKhUKhUPQRSkQUCoVCoZjB6He4RomIQqFQKBSKvkGJiEKhUCgUir5BiYhCoVAoFIq+QYmIQqFQKBSKvkGJiEKhUCgUir5BiYhCoVAoFDMEXHu7ftcWUSKiUCgUCsUMwauWzvUP9pmJaPddhUKhUChmCH7lqKUw0WjBcfsugF/6zA/6vRwAUCKiUCgUCsWMQZ5n8Ouv3rffy3CgoRmFQqFQKBR9gxIRhUKhUCgUfYMSEYVCoVAoFH2DEhGFQqFQKGYwNH1XoVAoFArFjIUSEYVCoVAoFH2DEhGFQqFQKBR9gxIRhUKhUCgUfYMSEYVCoVAoFH2DEhGFQqFQKGYwsqy/eTNKRBQKhUKhUPQNSkQUCoVCoVD0DdNKRN7+9rfDvvvuC8PDw7D33nvDb/3Wb8EzzzwznbdUKBQKhUKxC2Faicgb3/hG+OpXvwoPPfQQfO1rX4NHH30Ufu3Xfm06b6lQKBQKhaIH5H0urVqdzsn/+I//uPx6+fLlcOGFF8KZZ54JjUYDarXadN5aoVAoFApFAvptVp1WIoKxfv16+OIXvwgnn3yySEImJydhcnKy/H58fHxnLU+hUCgUihmJfisi025W/chHPgKzZs2CPfbYA5588km4/vrrxbGrV6+GefPmlf+WLVs23ctTKBQKhWJGoyj6e/+eiciFF14IWZYF/z344IPl+A9/+MNw9913w3/8x39ApVKBs846CwrhqVetWgVjY2Plv7Vr1277kykUCoVCoYiizzyk99DMhz70ITjnnHOCYw444IDy60WLFsGiRYvg4IMPhsMOOwyWLVsGt956K5x00knedfV6Her1eq9LUigUCoVCsY2QxIGdhZ6JyOLFi2Hx4sXbdLN2uw0A4PhAFAqFQqFQzFxMm1n1tttugzvuuANe97rXwYIFC+DRRx+Fj370o3DggQeyaohCoVAoFIqdj36HZqbNrDo6Ogpf//rX4bTTToNDDjkEzj33XDjqqKPg5ptv1vCLQqFQKBQDgn6bVadNETnyyCPhxhtvnK7pFQqFQqFQ7AD02yOivWYUCoVCoZiBOGDxLAAAWHn4Xn1dx04raKZQKBQKhWJwcM15r4EbHngO/vtx+/R1HUpEFAqFQqGYgdhz7jD81kn79XsZGppRKBQKhULRPygRUSgUCoVC0TcoEVEoFAqFQtE3KBFRKBQKhULRNygRUSgUCoVC0TcoEVEoFAqFQtE3KBFRKBQKhULRNygRUSgUCoVC0TcoEVEoFAqFQtE3KBFRKBQKhULRNygRUSgUCoVC0TcoEVEoFAqFQtE3KBFRKBQKhULRNwx0992iKAAAYHx8vM8rUSgUCoVCkQqzb5t9PISBJiIbN24EAIBly5b1eSUKhUKhUCh6xcaNG2HevHnBMVmRQlf6hHa7Dc888wzMmTMHsiyb1nuNj4/DsmXLYO3atTB37txpvdcgQp9fn3+mPv9MfnYAfX59/ul5/qIoYOPGjbB06VLI87ALZKAVkTzPYZ999tmp95w7d+6M/GU00OfX55+pzz+Tnx1An1+ff8c/f0wJMVCzqkKhUCgUir5BiYhCoVAoFIq+QYlIF/V6HS6++GKo1+v9XkpfoM+vzz9Tn38mPzuAPr8+f/+ff6DNqgqFQqFQKHZvqCKiUCgUCoWib1AiolAoFAqFom9QIqJQKBQKhaJvUCKiUCgUCoWib5hRROTP//zP4eSTT4bR0VGYP39+0jVZlrH/LrvssnLMfvvt552/9NJLp+kptg3b8uznnHOO91ynn366M2b9+vXwnve8B+bOnQvz58+Hc889FzZt2jQNT7B96PX5G40GfOQjH4EjjzwSZs2aBUuXLoWzzjoLnnnmGWfcrvCzB9i2n39RFHDRRRfB3nvvDSMjI7By5Up45JFHnDG7ys+/13U+/vjj4t/+tddeW47jzl9zzTU745F6wrb8nE499VTv2d7//vc7Y5588kl429veBqOjo7DnnnvChz/8YWg2m9P5KD2j12dfv349/MEf/AEccsghMDIyAvvuuy988IMfhLGxMWfcoP7sL7/8cthvv/1geHgYVqxYAbfffntw/LXXXguHHnooDA8Pw5FHHgnf+ta3nPMp7wPbjWIG4aKLLio+/elPFxdccEExb968pGueffZZ59+VV15ZZFlWPProo+WY5cuXFx/72MeccZs2bZqmp9g2bMuzn3322cXpp5/uPNf69eudMaeffnpx9NFHF7feemvxwx/+sDjooIOKd7/73dPwBNuHXp9/w4YNxcqVK4uvfOUrxYMPPljccsstxYknnlgcf/zxzrhd4WdfFNv287/00kuLefPmFd/4xjeKn/70p8Xb3/72Yv/99y+2bt1ajtlVfv69rrPZbHp/+5dcckkxe/bsYuPGjeU4ACiuuuoqZxx+fQYF2/JzOuWUU4rzzjvPebaxsbHyfLPZLI444ohi5cqVxd13311861vfKhYtWlSsWrVquh+nJ/T67Pfdd1/xjne8o/i3f/u3Ys2aNcX3vve94pWvfGXxq7/6q864QfzZX3PNNcXQ0FBx5ZVXFg888EBx3nnnFfPnzy/WrVvHjv+v//qvolKpFH/5l39Z/OxnPyv+7M/+rKjVasV9991Xjkl5H9hezCgiYnDVVVclvxlTnHHGGcWb3vQm59jy5cuLz3zmM9u/sJ2AXp797LPPLs444wzx/M9+9rMCAIo77rijPPbtb3+7yLKsePrpp7dzpdOD7fnZ33777QUAFE888UR5bFf62RdF+vO32+1iyZIlxWWXXVYe27BhQ1Gv14svf/nLRVHsOj//HbXOY445pvjt3/5t5xgAFNddd92OWuq0YFuf/5RTTin+8A//UDz/rW99q8jzvHjuuefKY1dccUUxd+7cYnJycoesfXuxo372X/3qV4uhoaGi0WiUxwbxZ3/iiScW559/fvl9q9Uqli5dWqxevZod/653vat429ve5hxbsWJF8bu/+7tFUaS9D+wIzKjQzPZi3bp18M1vfhPOPfdc79yll14Ke+yxBxx77LFw2WWXDZw8ua34/ve/D3vuuScccsgh8Hu/93vw0ksvleduueUWmD9/PpxwwgnlsZUrV0Ke53Dbbbf1Y7nTirGxMciyzAtt7I4/+8ceewyee+45WLlyZXls3rx5sGLFCrjlllsAYNf5+e+Idd51111wzz33sH/7559/PixatAhOPPFEuPLKK5Panu9MbM/zf/GLX4RFixbBEUccAatWrYItW7Y48x555JGw1157lcfe8pa3wPj4ODzwwAM7/kG2ATvqd3RsbAzmzp0L1arbnm2QfvZTU1Nw1113OX+zeZ7DypUry79ZiltuucUZD9D5GZrxKe8DOwID3fRu0PCFL3wB5syZA+94xzuc4x/84AfhuOOOg4ULF8KPf/xjWLVqFTz77LPw6U9/uk8r3TE4/fTT4R3veAfsv//+8Oijj8L/+l//C9761rfCLbfcApVKBZ577jnYc889nWuq1SosXLgQnnvuuT6tenowMTEBH/nIR+Dd73630xhqd/3Zm58f3mTM9+bcrvLz3xHr/Md//Ec47LDD4OSTT3aOf+xjH4M3velNMDo6Cv/xH/8Bv//7vw+bNm2CD37wgzts/duLbX3+//E//gcsX74cli5dCvfeey985CMfgYceegi+/vWvl/Nyvx/m3CBgR/zsX3zxRfj4xz8O73vf+5zjg/azf/HFF6HVarE/kwcffJC9RvoZ4r9xc0wasyOwyxORCy+8ED75yU8Gx/z85z+HQw89dLvvdeWVV8J73vMeGB4edo5fcMEF5ddHHXUUDA0Nwe/+7u/C6tWrp7Vs7nQ/+2/8xm+UXx955JFw1FFHwYEHHgjf//734bTTTtumOXckdtbPvtFowLve9S4oigKuuOIK51y/fvYAO/d3fxCR+vzbi61bt8KXvvQl+OhHP+qdw8eOPfZY2Lx5M1x22WU7ZTOa7ufHG++RRx4Je++9N5x22mnw6KOPwoEHHrjN8+4I7Kyf/fj4OLztbW+Dww8/HP73//7fzrl+/ux3N+zyRORDH/oQnHPOOcExBxxwwHbf54c//CE89NBD8JWvfCU6dsWKFdBsNuHxxx+HQw45ZLvvLWFnPTuea9GiRbBmzRo47bTTYMmSJfD88887Y5rNJqxfvx6WLFmyw+4rYWc8vyEhTzzxBNx4443RNtk762cPML3Pb35+69atg7333rs8vm7dOjjmmGPKMbvCz3971/mv//qvsGXLFjjrrLOiY1esWAEf//jHYXJyctqJ6M56foMVK1YAAMCaNWvgwAMPhCVLlngZGevWrQMAmPaf/8549o0bN8Lpp58Oc+bMgeuuuw5qtVpw/M782XNYtGgRVCqV8mdgsG7dOvFZlyxZEhyf8j6wQ7DD3Ca7ELbFsHj22Wd7GRMS/uVf/qXI89zLMBkEbI9Zc+3atUWWZcX1119fFIU1gt15553lmBtuuGHgzIoYvTz/1NRUceaZZxavetWriueffz7pmkH+2RdF72bVT33qU+WxsbEx1qw66D//7V3nKaec4mVMSPjEJz5RLFiwYJvXOh3YUT+nH/3oRwUAFD/96U+LorBmVZyR8fnPf76YO3duMTExseMeYDuwrc8+NjZWvOY1rylOOeWUYvPmzUn3GoSf/Yknnlh84AMfKL9vtVrFK17xiqBZ9b/9t//mHDvppJM8s2rofWBHYEYRkSeeeKK4++67yzS8u+++u7j77ruddLxDDjmk+PrXv+5cNzY2VoyOjhZXXHGFN+ePf/zj4jOf+Uxxzz33FI8++mjxL//yL8XixYuLs846a9qfpxf0+uwbN24s/uRP/qS45ZZbiscee6z4z//8z+K4444rXvnKVzpvMqeffnpx7LHHFrfddlvxox/9qHjlK185kOmbvT7/1NRU8fa3v73YZ599invuucdJ0TMZAbvKz74otu13/9JLLy3mz59fXH/99cW9995bnHHGGWz67q7w84+t86mnnioOOeSQ4rbbbnOue+SRR4osy4pvf/vb3pz/9m//Vvz93/99cd999xWPPPJI8bd/+7fF6OhocdFFF0378/SKXp9/zZo1xcc+9rHizjvvLB577LHi+uuvLw444IDiDW94Q3mNSd9985vfXNxzzz3Fd77znWLx4sUDmb7by7OPjY0VK1asKI488shizZo1zt9+s9ksimJwf/bXXHNNUa/Xi6uvvrr42c9+Vrzvfe8r5s+fX2Y2/dZv/VZx4YUXluP/67/+q6hWq8WnPvWp4uc//3lx8cUXs+m7sfeB7cWMIiJnn312AQDev5tuuqkcA93ccIzPf/7zxcjISLFhwwZvzrvuuqtYsWJFMW/evGJ4eLg47LDDir/4i78YmE8EBr0++5YtW4o3v/nNxeLFi4tarVYsX768OO+885xUvaIoipdeeql497vfXcyePbuYO3du8d73vtfZ3AYFvT7/Y489xo7H1+wqP/ui2Lbf/Xa7XXz0ox8t9tprr6JerxennXZa8dBDDznz7io//9g6zc8bvx5FURSrVq0qli1bVrRaLW/Ob3/728UxxxxTzJ49u5g1a1Zx9NFHF5/73OfYsf1Gr8//5JNPFm94wxuKhQsXFvV6vTjooIOKD3/4w04dkaIoiscff7x461vfWoyMjBSLFi0qPvShDzkproOAXp/9pptuEv/2H3vssaIoBvtn/9nPfrbYd999i6GhoeLEE08sbr311vLcKaecUpx99tnO+K9+9avFwQcfXAwNDRWvetWrim9+85vO+ZT3ge1FVhQDlmumUCgUCoVixkDriCgUCoVCoegblIgoFAqFQqHoG5SIKBQKhUKh6BuUiCgUCoVCoegblIgoFAqFQqHoG5SIKBQKhUKh6BuUiCgUCoVCoegblIgoFAqFQqHoG5SIKBQKhUKh6BuUiCgUCoVCoegblIgoFAqFQqHoG5SIKBQKhUKh6Bv+PxW6hKtxrNxyAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Exercise 1\n",
        "\n",
        "We will see how the overlap between waveforms changes when we introduce orbital eccentricity.\n",
        "Use the same function above to generate an eccentric waveform with the same masses but eccentricity = 0.05. The waveform approximant is changed to \"EccentricTD\". Plot the plus polarization of the two waveforms in the same plot to see if you can see visual differences"
      ],
      "metadata": {
        "id": "_Dzy3PzDpwCz"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Exercise 2\n",
        "\n",
        "Now we will see how the magnitude of overlap changes as we change the eccentricity. Overlap is defined as the normalized match.\n",
        "\n",
        "$$\\text{Overlap} = \\frac{\\langle h_1 | h_2 \\rangle}{\\sqrt{\\langle h_1 | h_1 \\rangle \\langle h_2 | h_2 \\rangle}}$$\n",
        "\n",
        "$$\n",
        "\\langle h_1 | h_2 \\rangle = 4 \\, \\text{Re} \\int_{f_{\\text{low}}}^{f_{\\text{high}}} \\frac{h_1(f) h_2^*(f)}{S_n(f)} \\, df\n",
        "$$"
      ],
      "metadata": {
        "id": "S-NpSk_Kqel9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# to find overlap using built in function, first convert both your waveforms to frequency series:\n",
        "\n",
        "max_len = max(len(hp_circular_td), len(hp_eccentric_td))\n",
        "\n",
        "hp_circular_td.resize(max_len)\n",
        "hp_eccentric_td.resize(max_len)\n",
        "\n",
        "# convert to Frequency Domain using the built-in method\n",
        "hp_circular_fd = hp_circular_td.to_frequencyseries()\n",
        "hp_eccentric_fd = hp_eccentric_td.to_frequencyseries()"
      ],
      "metadata": {
        "id": "M6pkGmtNqp58"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# to find overlap, generate PSD.\n",
        "\n",
        "f_len = len(hp_circular_fd)\n",
        "delta_f = hp_circular_fd.delta_f\n",
        "\n",
        "# Generate a raw PSD that covers up to the Nyquist frequency of our data\n",
        "psd = aLIGOZeroDetHighPower(f_len, delta_f, f_lower)\n",
        "\n",
        "# interpolate the PSD to ensure every frequency bin aligns perfectly\n",
        "psd = interpolate(psd, delta_f)\n",
        "overlap_score, max_phase_shift = match(\n",
        "    hp_circular_fd,\n",
        "    hp_eccentric_fd,\n",
        "    psd=psd,\n",
        "    low_frequency_cutoff=f_lower\n",
        ")\n",
        "\n",
        "print(\"-\" * 40)\n",
        "print(f\"Calculated Overlap (Match): {overlap_score:.4f}\")\n",
        "print(\"-\" * 40)"
      ],
      "metadata": {
        "id": "an--8tu8uRYq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Homework 1\n",
        "\n",
        "**Plot the overlap vs. eccentricity as you vary eccenntrcity from 0 to 0.2. Repeat for a 40Msun - 20Msun system.**"
      ],
      "metadata": {
        "id": "K7FZMNiCzRoY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from gwosc import datasets\n",
        "from gwpy.timeseries import TimeSeries"
      ],
      "metadata": {
        "id": "kV2bpJqluvHF"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Exercise 3\n",
        "\n",
        "For the loudest event that we have detected so far, we will plot the raw time series, whitened time series, and Q transform.\n",
        "\n",
        "## Part 2: Time-Frequency Analysis via the Q-Transform\n",
        "\n",
        "While matched filtering (calculating the overlap) is excellent when we have an exact analytical model for a signal, it can fail if the signal has unmodeled physics (like high eccentricity). To visualize a raw, model-independent representation of transient signals, we map data into the **Time-Frequency (TF) plane** using a **Constant-Q Transform (Q-transform)**.\n",
        "\n",
        "### Q-Transform\n",
        "\n",
        "The Q-transform is a variation of the Short-Time Fourier Transform (STFT), but with a crucial modification: instead of maintaining a fixed frequency window, the filter width scales dynamically with frequency to maintain a constant **Quality Factor ($Q$)**.\n",
        "\n",
        "The Quality Factor is defined as the ratio of a central frequency $f_0$ to its bandwidth $\\delta f$:\n",
        "\n",
        "$$Q = \\frac{f_0}{\\delta f}$$\n",
        "\n",
        "The Q-transform of a continuous time-series $x(t)$ is computed by projecting the data onto a family of complex, windowed sinusoids (often using a Gaussian/Morlet window) denoted as $\\Psi(t; f_0, Q)$:\n",
        "\n",
        "$$X(t_0, f_0, Q) = \\int_{-\\infty}^{\\infty} x(t) \\Psi^*(t - t_0; f_0, Q) \\, dt$$\n",
        "\n",
        "Where the base wavelet is mathematically expressed in the frequency domain as:\n",
        "\n",
        "$$\\tilde{\\Psi}(f; f_0, Q) = \\exp \\left[ - \\frac{Q^2}{2} \\left( \\frac{f - f_0}{f_0} \\right)^2 \\right]$$\n",
        "\n",
        "### The Heisenberg Uncertainty Principle in Data Analysis\n",
        "\n",
        "A central takeaway for this exercise is understanding the trade-off governed by the Gabor-Heisenberg limit:\n",
        "\n",
        "$$\\Delta t \\cdot \\Delta f \\ge \\frac{1}{4\\pi}$$\n",
        "\n",
        "* **Low $Q$ values:** Provide excellent **time resolution** ($\\Delta t$ is small) but poor frequency resolution ($\\Delta f$ is large). The track will look like sharp vertical lines or bursts.\n",
        "* **High $Q$ values:** Provide excellent **frequency resolution** ($\\Delta f$ is small) but poor time resolution ($\\Delta t$ is large). The track will appear smeared horizontally out in time.\n",
        "\n",
        "### Real-World Event Focus: GW250114\n",
        "\n",
        "On January 14, 2025, the LIGO Hanford and Livingston detectors recorded **GW250114**—the loudest binary black hole coalescence detected to date. With component masses around $33.6 \\, M_\\odot$ and $32.2 \\, M_\\odot$, it is a much cleaner counterpart to the historic GW150914 event.\n",
        "\n",
        "Because of its exceptionally high Signal-to-Noise Ratio (SNR $\\sim 76$), computing its Q-transform reveals a spectacular, sharp \"chirp\" profile slicing right through the background noise.\n",
        "\n",
        "**Task:** 1. Look at the resulting time-frequency track.\n",
        "2. Experiment by changing the `qrange=(low, high)` parameter in the `q_transform` function to see how low and high $Q$ values visually manifest the uncertainty principle."
      ],
      "metadata": {
        "id": "_RfVTWHzwVHH"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "event = 'GW250114_082203'  # for the loudest event that had\n",
        "gps = datasets.event_gps(event)\n",
        "\n",
        "strain_ts = TimeSeries.fetch_open_data(\n",
        "    'L1',     # IFO\n",
        "    gps-128,  # start gps\n",
        "    gps+128,  # end gps\n",
        "    #sample_rate=4096\n",
        "    )"
      ],
      "metadata": {
        "id": "gctc_Zmzu7lh"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Plot a short time-domain segment\n",
        "plot = strain_ts.crop(gps-5,gps+5).plot()\n",
        "ax= plot.gca()\n",
        "ax.set(title='LIGO Livingston Strain Data', epoch=gps)\n",
        "ax.set(xlim=(gps-1, gps+1))\n",
        "plot.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 374
        },
        "id": "y2JjYYB6vrqD",
        "outputId": "35360960-d181-449f-b0d2-8816f9335436"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Plot size 1200x400 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#create psd using built in welch method:\n",
        "\n",
        "fftlength = 4 # seconds\n",
        "overlap   = 2 # seconds\n",
        "welch_asd_fs = strain_ts.asd(fftlength, overlap, method=\"welch\")"
      ],
      "metadata": {
        "id": "EvTrMm8mv4SE"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# whiten the strain using built in method\n",
        "#BONUS exercise: manually whiten the way we learned in class to see if the two match\n",
        "\n",
        "whitened = strain_ts.whiten(asd= add your asd here,fftlength=4)\n",
        "\n",
        "plot = whitened.plot()\n",
        "ax = plot.gca()\n",
        "ax.set(title='Whitened Strain Data', ylabel=\"Whiten data\", epoch=gps) # Notice the epoch argument\n",
        "ax.set(xlim=(gps-0.5, gps+0.5))\n",
        "plot.show()"
      ],
      "metadata": {
        "id": "tVfI_F0KwFC4"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from gwpy.segments import Segment"
      ],
      "metadata": {
        "id": "5i24EmSGx2Ka"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Qtr = strain_ts.q_transform(qrange=(4, 20),outseg=Segment(gps-0.75, gps+0.25), logf=True, frange=(10,1000), tres=.001, gps=gps, search=.5)\n",
        "\n",
        "plot = Qtr.abs().plot(norm=\"log\")\n",
        "\n",
        "ax = plot.gca()\n",
        "ax.set(title=f'Q-transform of the Livingston Strain around {event}', xlim=(gps-.75,gps+.25),yscale=\"log\",ylim=(10,1000))\n",
        "\n",
        "ax.colorbar(cmap='viridis', clim=(2, 100),norm=\"log\", label=\"Normalized Energy\")\n",
        "plot.show()"
      ],
      "metadata": {
        "id": "jJzJylkSzNK6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "P6m7CR7mzkH0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Homework 2\n",
        "\n",
        "Repeat the same exercise for GW231123. Play around with qrange=(low, high) to get an optimized q-transform plot that we see in LVK papwrs"
      ],
      "metadata": {
        "id": "7ynZtp3q0STu"
      }
    }
  ]
}