{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "5d3e2022",
   "metadata": {},
   "source": [
    "# Conditional Playback"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d75d2214",
   "metadata": {},
   "source": [
    "In this tutorial we show how our Cluster Feedback capability (see section [Feedback](https://docs.qblox.com/en/main/cluster/feedback.html)) can be used to send pulses dependent on the measurement outcome. Concretely, this tutorial will show how to perform active reset, which means sending a $\\pi$-pulse if (and only if) the qubit state equals $\\left|1\\right\\rangle$, to flip the qubit back to the $\\left|0\\right\\rangle$ state.\n",
    "\n",
    "This tutorial should be ran on a Cluster with at least two modules. A QRM or QRM-RF module is used to emulate qubit readout. For this tutorial we connect $\\text{O}^{1}$ and $\\text{O}^{2}$ to $\\text{I}^{1}$ and $\\text{I}^{2}$ of the QRM. Depending on the result acquired by this QRM, a second module (called QCM in this tutorial) is used to conditionally generate a $\\pi$-pulse. The output of this QCM can be visualized on an oscilloscope to verify the behavior of the system.\n",
    "\n",
    "To display the behavior of the QRM, its marker 1 should be used to trigger an oscilloscope. Marker 2 and marker 4 need to be connected to the oscilloscope when running the section `Active reset`.\n",
    "\n",
    "The tutorial will go through the following steps:\n",
    "- Calibrate the time of flight (TOF) from QRM output to QRM input.\n",
    "- Set up the thresholding to separate the $\\left|0\\right\\rangle$ and $\\left|1\\right\\rangle$ state.\n",
    "- Sending the qubit state through the feedback infrastructure.\n",
    "- Performing conditional pulses depending on the qubit state.\n",
    "\n",
    "To synchronize the modules, we use the SYNQ technology."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d267d356",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "First, we are going to import the required packages and connect to the instrument."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "851e21d2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:53.296175Z",
     "iopub.status.busy": "2025-05-07T16:50:53.295592Z",
     "iopub.status.idle": "2025-05-07T16:50:53.908635Z",
     "shell.execute_reply": "2025-05-07T16:50:53.907978Z"
    }
   },
   "outputs": [],
   "source": [
    "from __future__ import annotations\n",
    "\n",
    "from typing import TYPE_CHECKING, Callable\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from matplotlib import colors\n",
    "from qcodes.instrument import find_or_create_instrument\n",
    "\n",
    "from qblox_instruments import Cluster, ClusterType\n",
    "\n",
    "if TYPE_CHECKING:\n",
    "    from qblox_instruments.qcodes_drivers.module import Module"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4ae9fdc6",
   "metadata": {},
   "source": [
    "### Scan For Clusters\n",
    "\n",
    "We scan for the available devices connected via ethernet using the Plug & Play functionality of the Qblox Instruments package (see [Plug & Play](https://docs.qblox.com/en/main/api_reference/tools.html#api-pnp) for more info)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3690195d",
   "metadata": {},
   "source": [
    "`!qblox-pnp list`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4507c5fa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:53.911839Z",
     "iopub.status.busy": "2025-05-07T16:50:53.911681Z",
     "iopub.status.idle": "2025-05-07T16:50:53.914194Z",
     "shell.execute_reply": "2025-05-07T16:50:53.913753Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster_ip = \"10.10.200.42\"\n",
    "cluster_name = \"cluster0\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e5a8b623",
   "metadata": {},
   "source": [
    "### Connect to Cluster\n",
    "\n",
    "We now make a connection with the Cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "25456317",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:53.915919Z",
     "iopub.status.busy": "2025-05-07T16:50:53.915652Z",
     "iopub.status.idle": "2025-05-07T16:50:54.733130Z",
     "shell.execute_reply": "2025-05-07T16:50:54.732428Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster = find_or_create_instrument(\n",
    "    Cluster,\n",
    "    recreate=True,\n",
    "    name=cluster_name,\n",
    "    identifier=cluster_ip,\n",
    "    dummy_cfg=(\n",
    "        {\n",
    "            2: ClusterType.CLUSTER_QCM,\n",
    "            4: ClusterType.CLUSTER_QRM,\n",
    "            6: ClusterType.CLUSTER_QCM_RF,\n",
    "            8: ClusterType.CLUSTER_QRM_RF,\n",
    "        }\n",
    "        if cluster_ip is None\n",
    "        else None\n",
    "    ),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31176836",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "#### Get connected modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "da4dd1ac",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:54.735193Z",
     "iopub.status.busy": "2025-05-07T16:50:54.735034Z",
     "iopub.status.idle": "2025-05-07T16:50:54.738615Z",
     "shell.execute_reply": "2025-05-07T16:50:54.738111Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_connected_modules(cluster: Cluster, filter_fn: Callable | None = None) -> dict[int, Module]:\n",
    "    def checked_filter_fn(mod: ClusterType) -> bool:\n",
    "        if filter_fn is not None:\n",
    "            return filter_fn(mod)\n",
    "        return True\n",
    "\n",
    "    return {\n",
    "        mod.slot_idx: mod for mod in cluster.modules if mod.present() and checked_filter_fn(mod)\n",
    "    }"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "45547ed5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:54.740807Z",
     "iopub.status.busy": "2025-05-07T16:50:54.740660Z",
     "iopub.status.idle": "2025-05-07T16:50:54.761588Z",
     "shell.execute_reply": "2025-05-07T16:50:54.761080Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{4: <Module: cluster0_module4 of Cluster: cluster0>}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# QRM baseband modules\n",
    "readout_modules = get_connected_modules(cluster, lambda mod: mod.is_qrm_type and not mod.is_rf_type)\n",
    "readout_modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "30bdc105",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:54.763303Z",
     "iopub.status.busy": "2025-05-07T16:50:54.763158Z",
     "iopub.status.idle": "2025-05-07T16:50:54.765659Z",
     "shell.execute_reply": "2025-05-07T16:50:54.765147Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module = readout_modules[4]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "07bec500",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:54.767362Z",
     "iopub.status.busy": "2025-05-07T16:50:54.767073Z",
     "iopub.status.idle": "2025-05-07T16:50:54.786690Z",
     "shell.execute_reply": "2025-05-07T16:50:54.785987Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{2: <Module: cluster0_module2 of Cluster: cluster0>,\n",
       " 10: <Module: cluster0_module10 of Cluster: cluster0>}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# QCM baseband modules\n",
    "control_modules = get_connected_modules(\n",
    "    cluster, lambda mod: not mod.is_qrm_type and not mod.is_rf_type\n",
    ")\n",
    "control_modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "02f25076",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:54.788940Z",
     "iopub.status.busy": "2025-05-07T16:50:54.788666Z",
     "iopub.status.idle": "2025-05-07T16:50:54.792078Z",
     "shell.execute_reply": "2025-05-07T16:50:54.791382Z"
    },
    "lines_to_next_cell": 0
   },
   "outputs": [],
   "source": [
    "control_module = control_modules[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "551c5d8c",
   "metadata": {},
   "source": [
    "## Sequencer configuration"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "69b4e248",
   "metadata": {},
   "source": [
    "Define all waveforms necessary for this tutorial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "05cff474",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:54.794459Z",
     "iopub.status.busy": "2025-05-07T16:50:54.794176Z",
     "iopub.status.idle": "2025-05-07T16:50:54.801482Z",
     "shell.execute_reply": "2025-05-07T16:50:54.800826Z"
    }
   },
   "outputs": [],
   "source": [
    "waveform_length = 120\n",
    "t = np.arange(-80, 81, 1)\n",
    "sigma = 20\n",
    "# waveforms for readout pulses\n",
    "waveforms = {\n",
    "    \"zero\": {\"data\": [0.0] * 1024, \"index\": 0},\n",
    "    \"one\": {\"data\": [1.0] * 1024, \"index\": 1},\n",
    "    \"state0_I\": {\n",
    "        \"data\": [0.001] * waveform_length,\n",
    "        \"index\": 2,\n",
    "    },  # I waveform emulating a qubit in the 0 state\n",
    "    \"state0_Q\": {\n",
    "        \"data\": [0.001] * waveform_length,\n",
    "        \"index\": 3,\n",
    "    },  # Q waveform emulating a qubit in the 0 state\n",
    "    \"state1_I\": {\n",
    "        \"data\": [0.001] * waveform_length,\n",
    "        \"index\": 4,\n",
    "    },  # I waveform emulating a qubit in the 1 state\n",
    "    \"state1_Q\": {\n",
    "        \"data\": [0.003] * waveform_length,\n",
    "        \"index\": 5,\n",
    "    },  # Q waveform emulating a qubit in the 1 state\n",
    "    \"gauss\": {\"data\": list(np.exp(-(0.5 * t**2 / sigma**2))), \"index\": 6},\n",
    "    \"empty\": {\"data\": list(0.0 * t), \"index\": 7},\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4e200ee8",
   "metadata": {},
   "source": [
    "Specify acquisitions that are used in the tutorial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "7c464de7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:54.803678Z",
     "iopub.status.busy": "2025-05-07T16:50:54.803406Z",
     "iopub.status.idle": "2025-05-07T16:50:54.807378Z",
     "shell.execute_reply": "2025-05-07T16:50:54.806701Z"
    }
   },
   "outputs": [],
   "source": [
    "acquisitions = {\n",
    "    \"state0\": {\"index\": 0, \"num_bins\": 1024},\n",
    "    \"state1\": {\"index\": 1, \"num_bins\": 1024},\n",
    "    \"single\": {\"index\": 2, \"num_bins\": 1},\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0db52097",
   "metadata": {},
   "source": [
    "Set up sequencer parameters for both QRM and QCM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a3c28af8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:54.809665Z",
     "iopub.status.busy": "2025-05-07T16:50:54.809405Z",
     "iopub.status.idle": "2025-05-07T16:50:54.882585Z",
     "shell.execute_reply": "2025-05-07T16:50:54.881685Z"
    }
   },
   "outputs": [],
   "source": [
    "integration_length = 120\n",
    "readout_module.sequencer0.integration_length_acq(integration_length)\n",
    "readout_module.sequencer0.sync_en(True)\n",
    "readout_module.sequencer0.nco_freq(50e6)\n",
    "readout_module.sequencer0.mod_en_awg(True)\n",
    "readout_module.sequencer0.demod_en_acq(True)\n",
    "\n",
    "control_module.sequencer1.sync_en(False)  # We will turn on the sync enable of the QCM later\n",
    "control_module.sequencer1.nco_freq(50e6)\n",
    "control_module.sequencer1.mod_en_awg(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc407d21",
   "metadata": {},
   "source": [
    "## Calibrate TOF"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "17255879",
   "metadata": {},
   "source": [
    "To ensure proper measurements, we must calibrate the time-of-flight (TOF). This is the time it takes for a signal to travel from the output to the input of the module. To do so, we first play an excitation pulse and acquire it back into"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d7ea3f35",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:54.885372Z",
     "iopub.status.busy": "2025-05-07T16:50:54.884995Z",
     "iopub.status.idle": "2025-05-07T16:50:54.889653Z",
     "shell.execute_reply": "2025-05-07T16:50:54.888797Z"
    }
   },
   "outputs": [],
   "source": [
    "prog = \"\"\"\n",
    "play    1, 0, 4     # start readout pulse\n",
    "acquire 2, 0, 16384 # start the 'single' acquisition sequence and wait for the length of the scope acquisition window\n",
    "stop\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f67e4354",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:54.892715Z",
     "iopub.status.busy": "2025-05-07T16:50:54.891986Z",
     "iopub.status.idle": "2025-05-07T16:50:54.982783Z",
     "shell.execute_reply": "2025-05-07T16:50:54.981831Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.sequence(\n",
    "    {\"waveforms\": waveforms, \"program\": prog, \"acquisitions\": acquisitions, \"weights\": {}}\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "249c0a64",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:54.985564Z",
     "iopub.status.busy": "2025-05-07T16:50:54.985161Z",
     "iopub.status.idle": "2025-05-07T16:50:55.006376Z",
     "shell.execute_reply": "2025-05-07T16:50:55.005247Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, State: STOPPED, Info Flags: FORCED_STOP, ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n"
     ]
    }
   ],
   "source": [
    "# Arm and start sequencer.\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for the sequencer and acquisition to finish with a timeout period of one minute.\n",
    "readout_module.get_acquisition_status(0)\n",
    "readout_module.store_scope_acquisition(0, \"single\")\n",
    "# Print status of sequencer.\n",
    "print(readout_module.get_sequencer_status(0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "485b1c39",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.009201Z",
     "iopub.status.busy": "2025-05-07T16:50:55.008828Z",
     "iopub.status.idle": "2025-05-07T16:50:55.090707Z",
     "shell.execute_reply": "2025-05-07T16:50:55.089869Z"
    }
   },
   "outputs": [],
   "source": [
    "p0 = np.array(readout_module.get_acquisitions(0)[\"single\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"])\n",
    "p1 = np.array(readout_module.get_acquisitions(0)[\"single\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"])\n",
    "\n",
    "# Determine when the signal crosses half-max for the first time (in ns)\n",
    "t_halfmax = np.where(np.abs(p0) > np.max(p0) / 2)[0][0] if np.any(p0) else 16\n",
    "\n",
    "# The time it takes for a sine wave to reach its half-max value is (in ns)\n",
    "correction = 1 / readout_module.sequencer0.nco_freq() * 1e9 / 12\n",
    "\n",
    "tof_measured = t_halfmax - correction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "8773ac3b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.093474Z",
     "iopub.status.busy": "2025-05-07T16:50:55.093045Z",
     "iopub.status.idle": "2025-05-07T16:50:55.420095Z",
     "shell.execute_reply": "2025-05-07T16:50:55.419509Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x621 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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A8Y6vo7B6VUNq2PyMSQdl08SmXdY8LGP7FotLxp6J1SijyIea1yhylEHkmmDYrbgrhm7jlWigsm7GxuctPu2TrX+9qYcJ7WnQfnrXDKiewQZ49nPvzsS6a1K5OcakmU5XcxtpWbN5oW2iy6URBltXWyveNmWykFttVBJIft2o+1l+zTLetOZx1r8NcERFfq5xhI3BYDAYCsAG2xhEV1srbl9ysu9rZdPEaxteQv765ZWDpon89ZfBLBWtPxNsUW8Zk/6vpTQNcya1ofCL7wL9ewAAw595T7UxmWANG8UoKvxqpXUgP4zB986q5pagQtjV1oqjDp3g+1pK0/CWtatR+N4Ki+tjD6CwehWA5NPBgpwDQLWiWn5to3XQjsI0orumSNbc/fzFdwFbWR7+9NlV+2kkuJ8kWbv7v6wD/bsxsGSmxa0BzgEAaMn4Z8O7zoHNfwNQMTiA5A02iqwVVq+C8fQfAAD5b11TtZ8Y3A9zeChBbv6viZ5r4Agbg8FgMBSADbYxiv9z9Gzf4ylNw+z9fVY7fy+McsXLWy4nNgi6q60Vnz95Yd1xXQNWLjkZU4d2I//VKzy8DMuYtPkmbRS9f+5039dSmoa5pX0o/vRbddyQtmcpJdyNMZOybsejDqkoySlNw49POhwtN19pDeC1mCB//WUw+roTj8h0tbXiewHOAVdRXb0KxtNrAACFW75gKdGZrNUhD8ntaVdbKz57vH8TGGc//WWtnCgvh9vZR0wVciv98j/ruCGTs/5MWNb6BvwNG8c5UPzvbwMASvf91OMcSNbQ7WprxX+ec2Igr7mlfTWOKGvNjIH+yryzBLldc/LRdcfDnmsuOMLGYDAYjBhgg22Mone/pXCldc315GuwlIeOtxwD6DVbq6eQOvwtrhKdZHTh+KlWdOUth7ThRPv3ry8+HssWzYOxdWP94G6jDAxYkRqnC11SmDK+GQBwXMck91hK06x12/26xyiqcHMjkwk3NXD2dPlx8y2urc3YcuV5+HBb2dcAN7Ztcg22JBX8c+fNcH+vlbWpQ7v9lei+7oZEJo85zNrHWe2VphSOEm3tp4+s7bdkDf27YRaLiXE7rMWStZOmVhoBhckaHGMycYPNqp370PzK3lY5B5zqO9Ns6H4uOcJOqUW9rHXsft3fEdX9SkPSvd8+xXqWHXlIO97WaaWUfvNdJ4ifa/Y8PY6wMRgMBiMO2GAbo3CU++ltrfiXdxwDADh3/gwsWzQPekcXsld/vXKynkLuupXQO7oaUiOz3eY2f/IEzJ9sGYiFsqXM6DPmArVpT3oK+luOs353utAlzO3S4+Yha+c4/fHj77HWLYBb6oijACS7ZoZp4g1biV5kK4N78gVMG99i8fIxwPXpcxqiqPba0ZhDWnK47h3HAgA+OG9GRVENMiYboOD37B8EAJw5awqWzLEaZKw47a3C/dQXLHKPm3t3Js7t8rfPR6udgvjQx86ucKtNmtRTSM0+0uKV4H4Ol0rYM2wZEpceZ3U3PKQ5F+4caMB+brfXbNr4FlfW3j93emXNwu6DBLk5Ru78ye1YcAjxuTbNyoTgGjYGg8FgxAEbbGMUjhLdOa4ZC2yjqD9fiRZkzviA/UsWrfduQXbpMgCNabjgKF1TxjWjY1xzFV+9owvppZdWTraNydSMuZUudAnWsTkG25RxLZg63onKaC631KLT6rjpjhKd4JrtHMyjbEdcjjlsIgBgqFRGf74IvaMLuetu9/DSXQNcb0DDBcc50Nna7Cqqe/OWwi9SovWGyFplP4+Y2AYAGC5aUapAWZs6023c0ghuU8e1YNr4lqrXLFl7Rx03vQEGm+MYyOg6jjxkAgDLOTCV6hxIUtY8z7W32LLWX7Cea3pHF7JX3ljFq5GOKPc+GNeMTvu55uyx3tGF9IfqZU3vsg02jrAxGAwGIwbYYBujcIyiztaK8tDrqUsxB/YBALS2iW47cwANUfC9SnRnq8Wtb/+w+3rqqLdbXI45ufHG5L6KMemkRzprCQBahxWlyZx/ucvNVQb37IBZLifCyxvFam/Koi2XqeKWXboMmNQBAGi65beeNUu+SYUra+Oa3f30GuCBSnQjImz2fk4d34wpNUo0MLKy5nCbUsXNI2uHWjVumY98pl7Wdr+RWGqwEyk6rLXJfXaUDBM7B/Ni50BD7s/Ks8NvzdLvWGL90trmv597koywWdw6Wiv72euVtSN9ZM1p2sIRNgaDwWDEABtsYxS9XqPIR3kwBy2DDS3jq97XiBS6isHmb0zCNib1aYdXGZNJz2IzTNNVVi2FsKWKLwCYdi2dvuC4ytwuOxoD00ys42Hf/ooyaPGr31MMW23NUzPmuocaGVmYMq7FNXK9vMKV6OQipk7a4VSPc6BK1uz0Wr1rdrWsJWx8DBVL2G2nHU713KPbfe7RlFfWnGHo+WHAHiuhGl7DI5tK4dCWJpubxznQakUrm1c+3FAj19m7KT5RLADus0ObMLlmPxsQaR6oRJorz46KMen3XOM5bAwGg8FQATbYxiiq0nNsRXXnUB4FJwLkKDatNQZbQyJsnpTI1qYqvkDFKNJspdDllrBCuGsoj6Jdn9Mxrsk3IuO3blomA7RPSpSbVxkEUGdMmoZRUeC93BpYw+aVtd3DBQyXStYJtlGkTTykoUYR4I3I+EdMHaNIC3JcJLWf9r41pVOY0JR197PXR9aq9rO5FWiyzk1qTyvOAevedO4Dx/g1TRMYsmRN9zoHGphO3TmuYhT154sYLFqyFrafSTbf8XvmVmU1+HDTxvMcNgaDwWDEBxtsYxTbPXVFE5tzyNh1J059SriimnyEzVvr0eeTrolaY9LmVlr3hDu4Nwlek5tzyKZSvilXgcak7Sk3XnlBOS+gsj7OejkKoWtMeqItXm6uAb6zD+XebYlwc4yiztZmTGjKImePH3DSXMMMcGPLy4nsp2malTqx8S31awbAdIzJcf7cyi88mQi3Ho/TQtM0X+dA0Lo5zoHypvXKeQGVlEhH1lxu9j5jeNBtPOJdN/fZsbM3kTUDvNHcZrTlMmhOp6qOmyGOKOPVvyXGrRKZbPI4B+plDd41s58byA/DLOQT4cVgMBiMAx9ssI1ReKMeuqbVRbKCjSJbsXltQyKKTdkwXKPRW8NWHf3zV1TNHdsBAKX/ud0dJKwS3vo1hx9Qq0TXr1th9SqY3ZsBAMNf+IhyXkBl39yUyJpokZvimkoBuSb3faU/3WP9Ui65g76Vc/OkqWmaVpfm6joHavaz/Le/AgCMl/6ayH7u9ERMvRGZNweGUXI6HQakBjuyX/rtHcnImqfhiMPPOi6O/hVWrwJsbsP/uDSR/fSmRAKWsevl7N4DmuY2AgKA0p/vs34pFhJZMy+HzhpZc9ctaD9fftb6d90TiXAzTbMqwuY8Q/YMFzBkR//g5yTz/M5pkQwGg8GICjbYxii8nmgA9bViARG28ot/AWApOEkoNm8ODsMwTWiwmhpMbM4hbbfPd6N/Pl5yo68b5ScerFzIqMzzUgVvMxTr33olutaYNPq6a+aMmcp5AdXpVl6OrhLteO9b26DZ7cONvm7kv1Y/rDdpbrU1kxVu1fvpDF9OipvT1OOQFitiekhLDilNgwmvrNU7B4y+bpQfvach3BzDm5IS2ShZ80aKvNycqKBzD6B1fLWs3fTZykUSkrX6e7R63dyIaa2s/aJ+CLlKbnvzBeTtFv4drc1oz3kizQPB0T8tlapE3PaxwcZgMBiMaGCDbQzCap4RokQHGEXFn37Lc6HkjKLDWpuQ1nU7+lfDzceYtAbP1g8SNrZtUsitNsIW3AjCWTfRnDGVcNPUWgO4Ba1ZA7j1BqZrViv4VUZRwCBhldy8DUcAIKXrOCwg0lx1HzRA1mq5iZqOjJSs1Ta4qY2w1e1nwty8UaxaR9T22mdHg2XNWbO2XAbNmbSd5lrjVAmINGt2p0hz/x5lfBgMBoNxcIENtjGInYN5lAxL4XQU1M5ao8jxktcZRckqNrUecgD1dWwDlWiRg8DBs9PnqOdWE/VwUujMUgkYts5xlC7RXCqV6K2LetSkRPrUYjWC21CxMmTZkbFg50BjuTk1V1M9M87quveNlKzVcHP200kNNotFqxMkKkZ4o2QtOCXSljXHAPc8OxrBraopUFC3VJ+U5UZw884idFBnhPtEmgFPp0iOsDEYDAYjIthgG4PwzuzKpqyi/LqUSJ/IQmOU6OooFoD6CJsft44uZD7ymSpezvwnZdxqjMlDW5vcFLq+/UOV+hjAVbrcuVSOgq9pynkBhJRIn9qduplZmq6cm6Pc51I6JjRlq7i5NWwD9Yqq3tGF3Odvq1wogf3s2V8va3URmSBZu/CqhnKb5GkM1Ld/eERlzY2wjavpErmv2jngbZ7RCFlz5GlScw45u9lIXfTPJ9Ksd3Qhd40n/TaB/ay9P73cRJkDgCfCxp0iGQwGgxERbLCNQYi8vXXKQ2uN0nXtdyoXaoBR5OUZ1qQi/c4PWcenzKya56WOW7USrWsaOjwKoauoZnPQMln3fdmly5D5+D9ZHM++QDmvkmFgx6B/mprb1CCg22F26TLobz0FAJC75hbl3LyKqlPPVNeNMaCJTOb8T7m/N//kyQT2s7qxB+CjRAdwSy8+z/rl0KkJyVo1N29joO37ByuNPfxk7aNXWxzfc6FyXsWygV1DVrdCv5RI0zQD61+zS5dBP/pEAEDu2u+oX7N9Ps+1mvTboC6RmfMvd39v/tnTyrnVRiWB+miu61Sp4QaexcZgMBiMmGCDbQzCz9sbFMWqVR6y530KSKUBAM0/WpuYouoX9XA8+4GpQy3jrF9MU3lUoZpbvYK/ff9QoIccAPTDulxuqvHmwDBMWEr9IS05AKhqn98bxq3dGjiObE45t9r6Ne/vdRHT2tb5mlaJHtW2rleAV3ZZctScSbnHgmr/6mXN+lszjURkrbvfGnKue1Ivp4yvRCbFsjbNJqmcFt6w9zOlaZjUbMmLcz8UygZ2DxeCxw3AmrUHoMrIVAW/Z4d3zQBUUlxro1i67na01GsNJgXwe+YGpUQG1bCBI2wMBoPBiAg22MYg/rZjDwCgLVdRmuoGuQoUQkd5dQ0khdi821JamjIV0aobORDErdniYw7th2qYponX9zndICtGV1WtmE8qmANnrZLg5uxZey7jKn+apuHQFmvdnuvbJVSi4ezjoHpuL765BwAwwSNrgVEsH1nTEtrTVc9swP2bewAAX1zzDFY9swFAfft8M0iJdvYzgTX77l9ewt58EQDwrp894HKrmncW4FABkOh+Ok6T9lzGTYHMpVOu8VYV/fO7D5qTW7eXdloRqLZcxj0WmBIpukcT4FY72N7Lbf0bu9HdP1DXRMblZUfYyhueS2xGHIPBYDAObLDBNsaw6pkN+Opj6wAAq196rU5RDRswC3gU6wSV6H9d82wdt5d27EX3zt2APUC2LiKToKL6nb+8hOGSNQfujDvu9yjRlgf/se438OaON20ejVWif/y81fRl93ABM2+9C6ue2YBVz2xAt61Qf+iuR/Dc5tesk333MxlFddUzG3DdmmcAAL/b3FO3nz37B7Ft737fxh4uEuDW3T+A5feudf82AVx271p09w+4+/nyzr3o3rELKFmGU9194Ozn0ADM2u6HMbld8cDj7t+GWeHmKPthspak4eHI2i6PrAHAIbbB9lzf7kqKq4hbAs+OG//8PADg7pe3VmTNXrO+/UN4bc++ynOtwffolr3WNTN6Jey57o3dAIAnenbgiFvurGsi48B4/VUAQOkee+bfb36knB+DwWAwDmywwTaG4CiqTnzIq6g6SvRAsYSXd+71bVLhIAmFUKREP92zEwCw7s3deOstP6u8qTatyVG4igWYxYJSblf97gn3b68S3WtHYn70/Cv49K9+Z/HwSwVLKLLQ3T+AW578m4ebieX3PIbl9z7mHjMB/PnlTYHckIABLpK1ezfZQ6cNE7Nuuws7duywuAmiHiqV6I27+mHUpKaWTRObdvXjLz0Wlxd37MVx3/5p5YRaWWuupN8iPwRVsLhVH3O4OVG/H697BZffZcuaKIql2Cjq7h/At5+qlrXL7l2Lm9euxwY7vfRjd/8RL2zZFsgtCaNIJGu/3bjNPTb7O7/Cnl3Ws8TXcZFgNPeRLb0AgM8//LTlTOkfwG1/qaxla9EjQ7XzJZ2B44A1SuVrVyrlx2AwGIwDH2ywjSGIFNWfv/Cqe+zI763G4B7L++sXYXMVCif1KUFua7e9gZufWF/5aFuxMXPN0NLp6ovYNSgAgKEBxdyqjzncfruxkqLkcBvOtaAObkRGrTK4cVc/aqviDKCOb2vR9t6LImwN2s/P3F9t/O61lWhhSqRCBX/upLaq2jDAqslqzaTxtbXr3GOtBVvWmlqsAcZeNDW73RiVc6s55nDzlbWsQNYUOwf8ZK1smvj8Q39x/zYBPLVps82jMc4ekax96r7qaOU+57k2wo6ox7a9UXWPjrPvTyNT3UTGf+afuogug8FgMA4OsME2hiBSVL1KhWECJUHqUBKe6CBuJqqNj/ElS1EtNbWiFlomC9jKTiOUaBOoUmDbbKVrX7qpnlsCRpHDrba3hA5ArznYZq+bX9phEoqqeD+rFdDxTnTBLyLTqj7619XWim+ffUIVr5VLTsb+YqlG1qz9LDnRNA80TasYRgr3tKutFZ85/i2+3Lyr5nDbl65vFOMY5aqjuUGyVms+jCtWzyKsQovDTd2aRZE1X0dUS+McURqq79Fx9n6ipi7Yf+Yf/7fLYDAYDDnw/xxjCF1trbh9ycnu37oGj6JaUSo003AVQt/UIUchVKyo3uqjRJ8y/bBqxcY2inQ/5R5IpOapq60Vn377Al9uXlXKUbrGTZhYd42k6oq62lrx7tlTq7jd/t5TcPuSU1xuGoC3t1uKva+i2qw++hcka9Z+Viugzrr5ppImtG4fmj/T/f3VK/4eyxbNq1P8HV5BHSqTSqE7edqhAIC3dkzElivPc7n5y9qk+gsksJ+AtafvqpG1r77zbXX7Ob7kX2MKJJPiSpY108Q4m5vQcdEAR9TJ0w/D95ac4h5rL1u8UjVrpnd0If3+iz0HUsh9/lZl/BgMBoNxcIANtjGGZYvmYVa7FZ365YfOCFBU8+7vjSzO/9CCeiW6q60VKz2KzQRbUc2Mb/e9hpaQsnqSrUQf1zHJVaK72lrx+VOOds9pt6NYrRMn11/Aw8tU3Np/1gTr2p845giX27JF83DdO44FAJw7fwamaCUAjTWKli2ah7kTrc/72bmnu2vmVa6bjCJyhoBbQrV/+4vWZ47PZjC93fqMWm4T7P0MkrUknAMAsL9gcZveNg5dba0uN6+stdn3QWsDnQMAMMteq4ttWfvnUxbi9iUnVzkHjmlN2Twak+IKWLI2036u3fX3Z/jK2ngjD92OU/pH2JJx9nzr3fWOqK62Vly6aB6a7QHf3zv9KJtX/T2QPvEsAID+luOsmX8f+IQyfgwGg8E4OMAG2xjEkN3t8IhJlnJQq9i0le3oWipl1erUQEsgrQkA9hXqlWgA+IdF89But+r+2snzqjjUc0tGIdxXsLoFzphQUaIB4IKjZgMAJjZlsXyBFX0Q1YmhXHa7XCrjlrfW7ZjDJlVxm27/XvYMM/arK3LT1BSnawLAUMnidsTEyucuWzQP7zp8CgDgayfM8/DwGRORUO3fPrtt/nhPC3iH28QmK632hhNtWQuYy5VUV1JH1sZnq7l5Ze1yV9YEUaxCHmaxmAi3YzoqsrZs0Tx8+Yy3AgDOmTMNh8L+TFHTkQTGW7jPtYmVz122aB7eY0cFv/L2OdZBXQea6mv/XGeP4v1cOn8GAMtYcxxRDpwRBKIaU6Stc7SW8YnM/GMwGAzGgQ822MYgvIaRg2WL5uH9cy1l4JpjZ1kHW8ZbtTq1SMooClCigcrMuOaCoN7Jw029El2/Zt6/C2XDbVLhW7vjaYiSlDFZy21c1mrKsr9QqswTE6WpJaBEu9xq9vTQFssR0Fy0Z9s1t9Y39vBwU21MVtYsXfdauy1rLQWLm+9+IrloUWXNqrmNy1h/Fw0DrSWBgl/VfKcxsjZ9vLUWZcMUz9VLIJ3a5Zb353ZoqyNrlToxv+dapfZPLbd+m1d7U7bKEQUA42yuxX17bW4++5my5aBcUsqLwWAwGAcP2GAbYygbBgaL/sZHh6PYuIpqQGTB9UQ3Tol2uJZsxSY4wpZMw4UgZdAxigaKpYoS6qeoeqOVSSnRtQq+zXV/oRg8bBzJRSVN0ww2dG2uxX2Cgd5AJZW0QUauxa1GiQ64DxKL/gUa4NbfA4UQWUuo+Q5QuQ/acrX76chaSTikPam6v5JhuBG2WucA9dmRnLPHXjMfWXOeH8V9eyxufmtmR9jMktpoKYPBYDAOHrDBNsbg1McAwQp+aX+whxxIrgudSIl2FBuXW0iammqFMMwoAoDyflshDIj+JR6RCTIm84WKEtqg2ViAlaLmNLMJikyW9++xDjR6PwMMcKCybu5+BkXYko401xm5tuIOoBxyHyQVBe8PkjU7+rc/nx8RWdtfqBgzQc6BUth+JnR/9gsyB8bXPnMFKZFgg43BYDAYEcEG2xiDo9yndQ25mhQ0R3kwHO99mDKoOk1NoES73PY7UY9Gp0T6c2tOp9yGLeUQQzcxboHRv5r9DOCWVNTD4QUArVl/Q9fYL46wJV2T6KdEj8s43OyoZIONoiBuzemU29yjLEg7BJJrvhNmTJYHBty5YY2M5jp1nBldRy5d/Vyr3c+GOweEEbaae5RTIhkMBoORANhgG2PwGh61dRyuB39/cPpc1fHEoljBUQ9Rah/gMT4Sq3mq5qZpWoWbrUQH1dc12vhweLn7lE4DOZ8ZcY4Cmx+GWVKnFHqjMXWt32sU1aCoZHIRGet7Osp8FTfnPnBSfkMiMqrvgyBulqw592i/mFvDZc1ZM5tXQMOiShrpAEyFA6BFz47a/Wy0Q6U/Xwjk5t6jg4L7gCNsDAaDwYiJA9Zg27NnD6655hosXLgQU6ZMQWdnJzo7O3HkkUfi8ssvR19fn/D9pVIJX/rSlzB37lz3vZ2dnejq6sLpp5+ONWvWNOaL1ICSCuYqD2Ge6AYZRRY3+9gAMerR0BQ6+5it6AUqhElFsgLT1Ky/dU+HSFETGQBKjQ9RExmHq041wBuU4gpU0vs0wfB463hjm44A9Hu08c13LF5hsla1lkMDCnkF17+6+xn6XEu2+21t3R/gWUdRoxauYWMwGAxGTByQBlu5XMZZZ52F1tZWrFmzBj09Pejt7UVvby/Wrl2LBQsW4NRTT8Xg4GDgNb7xjW/gmWeewWOPPea+t7e3F9u2bcPXvvY1XHzxxXj11Vcb+K0sCD3RtvKgOcpxoCc6oQgbISVSdxTQkMhCYimRvil0jrJqG2whETaV3AzTdCMyQTVsTfmQboeZrOvFV2l8CJVoR8EfEEexEk87FBjg+pB4PxudfuvlpoU4B5IwJr0Ni2qND4dXdtgywgKbyOSarLb6irkJnx25eseFL5Kq+3MibCJZG7SNV98aNvv+URj9ZjAYDMbBhQPSYFu9ejVmzZqFFStWYPLkyVWe4vb2dlx11VVYsmQJVq5cGXiNBx54ANdddx0OPfTQquOapuGkk07CRRddhN/+9reJfYcgUBp7pB1FteERNtvwEKQO6cNEbg3uKpgyytCdtv4NVKIHqprI+CvR44vOuIEARRVIRFmldGJMDTfeyAXCFHxL1lJDYgU/sSYyYY4L04Q+LFDwvdxURkxFjT3sv8eJxg3Aev4lYeiK06kdWbONyUbLmlPDJnD2uPeBn6xxSiSDwWAwYuKANNjWrVuHM888U3jO4sWLsW7dusDXr776ahxzzDGBr0+bNi00rTIJOMX5oihWaijEez8CXSKdYxnXmAxpA688+he8buMyaYy3FVUAwc1aEuDmrJmuaWiuabaQSenIpXRXiQ6MYsGrrKozwoVppJka58CIpUQGNx3JDNuRybCaxAbXcraW89Ccxh4NTIkUNfbIpnSkdc11DghlLUFjUvTsSDsGW4NlrZ+QTp0WRXO56QiDwWAwYuKANNi6u7sxZcoU4TlTp07F1q1bA19/3/veh2w2K/yM4447LjLHqKCkRGbzjvc+3CgybcVRCbe8KIWuWokO7fTWyJTIbKaiqGZzVophg7h50w79aobGZTNoK4VH2JKYX9cfMLMLqKxjdjhE1jyGh1JZI0T/sqKoRw03lQhLiXRlTdeBphbfayQqaz77qWkaxmczruMiMI0UaHg014nOZ0OikonJGuk+sJ9rgggb17AxGAwGIyoOSIOtXC4jVdPyvhbpdBqlCDUFpVIJf/7zn/HAAw+ERvHy+Tz6+/urfuJiv7CuyDHYQgZnO8fLZSA/7HtOFFC85Lm82EueVB2Ks25OZMiLcdm0JxWswYqqwHvvcivSuSWSpibcT1oUC4ahVNbcToyCJhUOt7AukSr30zBNN83Vl5tH1gKbyACJRnP9nh0Wt4oxGXh/el9TmFJNqX91ZS0kcwCGAQwPKeMWNLsOqMhatuDU/gU3HeGUSAaDwWBExQFpsKnGLbfc4naJbG1txRlnnIEbb7wREydOFL7vxhtvRHt7u/szffr02FwcpWucQLFpyocoXR6vfqM8+HUNNEKGU6tUVEuGgaFSOZCbFVlwUsEEimpzY2t3AFuJdoxJoRLd2IiMI3/NBbESnbisCdLUmkIcF5UW9ep4DRZLcGI7QcbH+JA6MSCh/XQjRf4R5Gpu4em3alMiw+tfXVkLWjevrCXQLdW3hs25D0SNgTglksFgMBgxcVAYbC+//DJmz56NDRs2RHr/VVdd5XaJ3LdvHx577DH8y7/8C9auXSt837XXXou9e/e6P9u2bYv0+V6IU8EsxWBi3vJ8m8WC7zW0VKqi3CiseRLVejiNPXJli1NQw5MkFNX9gmYLgBNZsKMemgajr9ufm1P716DaHYtbGp1Du6zP1QOiMRi5uqJJjqyVCLKWxMiBAFnLlovIGJaCHChrCdRyOrx0TUNLUDS3ODIGuChS5HBzZS1Y1EYsmjspb32eWfSPVGm6DjS3KucmWrfxuTQ000Cz8/zw7RLJETYGg8FgxMNBYbDNnz8fmzdvxrx582JfK5vN4vjjj8dNN92EG264QXhuLpdDW1tb1U9cCJtnZDO46NU/YtGeLQCA/A2fQmH1Kt/rJKKshqQO/cPmh92/By94qz+3BjdbACxF9b09fwUAmNtewcCSmWJuDUoFA4APvvQQLt38CACgdPd/Be6nqyg2iFtrNo2LXv0j3rrnNQBA/iuXBctao6N/mTSWeWXtwwt9uVVSIhWumRsBD6hJzGTclEjTNAOdA0gimiuoMQWAc1/2yNqv/1/wfiaQSiri1pJJ4+PU51qDI5PWfubdv839e+sv4Bhs5bLS2joGg8FgHDw4IA02Sn1aqVRCOu2vuFBw7LHH4vnnn4/8/qgQKar6mz349l9/CFdNNA3kr7/MXylsSU5Z9eM2cd+b+Opz/105YPhzSybdSpx22DmwE5e8+odwbglEsfoF3Iy+bnz699+u3KSmGbifSSjRDje/VDC88bq0rDUqIjOh/038+/M/rxwI2M8kmlRQIqZLtj8DADC3vBToHGj0fSAlaw1+dphvvI5bRvC51i+sG07j4lfXuH8PLl1Qt5+a9/8ZnsXGYDAYjAg4IA22rq4u9Pb2Cs/p6enBjBkzfF97/vnncckllwjfr+s6dL3xyydqHGBs3YgUahRPowxj26a6c910rAY10Gh74zUaNyeyMDwEs1xWwyuk2ULn7h7oBG5Jeu/91szYuhG6aYTyAlBRVBuUdigla4oNXdGwcQBoJ8paEg1RwiKmhw3sxEVbHvXwEhuTjYqAS8laawLPjhBuo+G55hdha9/7Br687pceXj77mfZ8J06LZDAYDEYEHJAG28KFC/HQQw8Jz3nooYewcOFC39cmTpyIJ554Quh1f+GFF3DEEUfE4hkFIoVQnzEX5do0LD0FffqcunNVD8+uauzhwy03cz7KCOfmKtEAMDSghFuYEl3umg2j9qDfujU4UqTPmAtDq7lFQ/azUQ1RZGRNtfExWKxEKfw6MeZm0WQtiYYo+4vBHSIBoGPX61LOgWQMj5iylkRKZMh9IP1cU8StbBgYKArS0PsIzgGvwcaNRxgMBoMRAQekwXbuueeiu7sbK1aswM6dO6sMr/7+ftx666245557sHz5ct/3d3V1YfLkybj55puRz+erXjNNExs3bsTVV1+NK6+8MtHv4QehYtPRhZtO+7TnQAq561ZC7+iqv5DjiVYU9ahq7JHzSR2aPgvfnnt2OLdsDrBHMqhSusJSItOdM3D/lGNDuSVZi+WrRHd04bfnXVtRBzU9cD8TTVMLkLWvn06TNU1xfV1oY4/ps3Db3HeHckuiIUqYc8DsOoLkHKjM1UsitS+erDU6mqt3dOEbZ3zGc0DwXFNc++dEcgH/e7T5cIJzIOWRUY6wMRgMBiMCDkiDLZVK4cEHH8TQ0BBOP/10TJ061W3Lf8IJJ2D9+vV49NFH0dpqdRRbs2YN5syZ485J0zQNP//5z/HSSy9h/vz57ns7Ozsxbdo0XHDBBfjsZz+LD37wgw3/bmHGx9qjz3J/b/nlOmSXLvM9T3WEzWnskdY15Hxm4LVm0nj0sLcAAIyuOWi9d4svN03TlM+gCqsrGp/NYOM4a9B66l0fDuSGJDoxCprIAMCmd5yH9e2WYtr0b/8VuJ9IJBVMzO0Jr6z9z4vBsqZ43cIae7Rk0nj0UFvWps8N3k+oN8LD7s/MlBn4XYcnsh9kfCQYYQvaz1eIstboaC4ArD16sfs76bmmSNaczrdBDYtau2bhu3PeVTngs59aKgXYcsrDsxkMBoMRBdG7boxytLe346abbsJNN90Ueu4ZZ5yBTZuqU5KmTJmCVasCOvKNIMKMj8lape7LNz3NRsWDr1ZRbctlfZXolK5jAixu5YmH+nvHXW7jYO7fq16JFjSCaLbHDaRmzQ/kNhKK6rhsGmnDisloncFz/JJpA2+tiW/TEQCTiLKmOiUybD91TcMEWMZmaeJhQllDyzhg1xvK9pQia8+O7wT61iF9zoXIXfU1ccS0gc13xmUzFVmb4l/fCyTVXVPsHJisS8qaKkdUyJppmoa/TjkS2PQ7FGcuwISVv/eXt1Taiq5xSiSDwWAwIuCAjLAdyAjzkk/SLYWrnEpDy/ifA8DjwVes2ATU7gDABM1WojM54bWURz1C1mxcNuMabN66piBeKBYCZ9xJcwtZt3GZDJrK1jmagBsSbbUuNthK6aw1AysAqg3dMF5V3LJNwmspj/5RZM2eWacf/pZgYzLR5jvBkWbnPtByzcEXSqLpSMi6TbSdPYYufq5pilO9+/O200IgaxNt50BR5BzgWWwMBoPBiAE22MYQimUD+bJlkAV5fCeYtlGUFShcUD+HjaJEOxG2QkasRFfqUFQZk7b3PmDNxmfTaHaNIsG6OUN5gYY1RBmXTaOlbNdRCpRo1yhSpKhSZM1RokMNcMXGZNh+AkC7fR8Uw2RNefQvTNYy7n6KDPAkmu/0C5qOANWRZorjQtWa5UtlFA1H1vwdFxM16/VimAHe4P0EKs81oayxwcZgMBiMGGCDbQxhn6exR1AXugmOYpOub0FdBcVpTWGpQwDQblrnFMIUfNXGZGiaWgbNthJtChRCLZMFMtmGchufo0XYlNckepvIBHBroyiqQCWaq7jBzTifhiO13PIh94Hq6F8Yt3HZtLufZk6wbkk23xHImhthE8laQjWJgHUv+qEd1jnFTMhzTfF+UiJsjqwVBLLmzGIzeQ4bg8FgMCKADbYxBCcak03pyPo09gC8RhHNE92o2h0AaLOjHvm02GBTHvXIV5pU+MEbWRhuNLewuqJMBi1O1KNZkBKpOBXMWbNcSkcm5f+YcKK5+UanuBKcA232fRAma+qjf+F1Ys5+ihwXiTTfCYvmZtIVWROl3zrPDsVdP5vTKaQDUmvbXQOcmOLaQEeUK2scYWMwGAxGQmCDbQxhf5FgFNn1FGGGh1PrYWx/rX5obwRQDLbxtmITyk2xohq2brlUCi1lh1tIRKbBHSzH6SYypqWsiuqKXKNof7+S/ez3NJEJQpsd9cinqNHcxjkHqLKmOvoXxq05nSI7Bxpt6I7TgbQ9PFuUGpxYBFxoFNGcPaq5haWRAsB4g/DscAw2bjrCYDAYjAhgg20MgVInRlIeAJTWPwEAMF54CgNLZqKwOl5HTBluQ0RFtbzheTXGZAg3TdPQ6nALMz6yFnfj9Vdj86JwG296FDxB1KP0yN32L8WG7ec4mxt1P82+bQ3ZTwAY58oaLSWyvGldw2RtnGEZbEOpEGPSkbXuzbF5maYZ2onRiRQBEEfY3IYogyj3vBabG8kANxwjl5YSafZ1N8wRNc50nh2C/XRmsXGEjcFgMBgRwAbbGAKlAL7VDDc8jL5ulO5a6TlgIH/9ZbEUHAq3FluJHtQF3SsBGD1bAAClX/+XGuODxM1SCAdTwecUVq+CuXUjAGD4CxfE5kVp7OEYHgY0V4GvhdHXjfzXr/YcULGfTtQjuE5sHNHILT/3mEXr5Wcbtp+tVFmzjaHSb+9oPLcwWbO5DX/+w7F5DRZLMExrLHZg0xGbVxkazHQwt9KDd1Wu+/7ZCtYs3ChqdZwDYbL27J8BAMbG55XsJyXCNq7sGODhETaew8ZgMBiMKGCDbQyB5O0tO4qqwGDbuhGwU58qB8swtm3yf4Mibq02twERt75ulJ98yHNAofEh4ObU7uzX/LkZfd3IX7+8csA0lfEScasY4BmUDNOf29aNgNH4/aQYuUZfN4o//47nQGP3M1TW1j7QeG4lh5vAAE9I1jRYQ+z9UIn8ZVGolScvt69d4TmgYM1CBrQDnmdHmKz9961qucnImoCb5kTYOCWSwWAwGBHABtsYQiXdKjjqQVEe9BlzAa1m6/WUeCCtAm5OJ8b9IqVr60bArDFM4hofBG5O5779ARGZRIwiQmOPFo/3fqDo753XZ8wFaps1KNtPkaLqGOBh+6l23dxOjCJZs42iRssaiZvjHND9z0nGAC/ZvDK+g+0tXpU0UseIagy38Bo2SnQ+CVmjRNicdduvCaK53HSEwWAwGDHABtsYAkWxoSgPekcXspd/yXMghdx1K4OHviri1uQo0VqwMmsZkzUKZVzjg8TNMib3BSjRiRhFBF6ZosVrKBWsROsdXchdd7vngB57PytNRwSyZq+ZUNaScA4Qoh5NtnNgXyi3hGSNxK2BspYPlzW9MAwAGExlXcOzIdxChscDY0PWgpw9ANhgYzAYDEYssME2htDdbw3Q1eHvIQc8ymBI7U7mvRdZv6QzaL13C7JLl8Xi9uagpewVy/6pVACQs42P/hBjMr3kY54D8Y1JZ5ZSkBJqmmaFmxmgRDtGkaPga5oyIzetae7e1nEbHgJgGWz7AyJsAKz9s7k0fX117P2syFownKikSNb0ji5kP3O950D8/dwxYMlagSBrQUaRwy39/k8o42aYJvbbkSzHQKpFlawF3AcVA1y9rKU0CGRtEIDVPGNfkMGWgHOAJmvWPRwqa1fe4DkQX9besGWtGJAiClScPf2iZ26K57AxGAwGIzrYYBsjWPXMBty0dj0A4Jd/24JVz2zwPc9VHgSKqnWi3ba7VIR26NTY3P64tQ8A8LnfPxXILWtz2wsxt/TJ7wYA6G95W2xjcuVfX0LRrv065Yf3+nMrFqDDOmdvQIQNsIyi9HsuBABkPnp1bKPoly9uAQD0Dgxj5q13+XOzlejBdNY1BoKg26ManNbmUbHqmQ34+uMvAADufDFY1hzDI2w/M+//uE1Qj72fq57ZgMd7dgAArrj/cYGsFUjc0iefbVGbd2xsbt/9y0vu72//r//151YqImWn7YnuUUvWLgAAZC76x9iydtffrG6O2/oHBbLmOAcyQlnLLl0GTDscAND01Z/H3k+SrDnPtVBZu9j9veWeV+PL2utvAgCuvP+JYFkj3AcaR9gYDAaDEQNssI0BdPcPYPm9a+FU25gALrt3ra+nPFO0PML7tDRKAq9w1Uyv/HBsbg5E3LI2t72a/9BvFzY3rak5tuf+0/c97v5tmAHcbKMIAPYGRNgcaJMOtf7NhLQXJ3D71pMveriZvtzMvKVEDwvS1Fw4RriteEflRZW1rB3NHdAzKJTLgdd0Zc0woE3qiM3NAUXW9oQo+I6sIdcUW9Y++7sn3L8psrYH4ii4NuEQ618Fsvadv/zNwy1A1twIWzYwwuZAb22zuMVwDkjJWrFS/5ovEWQNgD7x0NjcHFCeuULnQIYNNgaDwWBEBxtsYwAbd/W7LbkdlE0Tm3b1152bLVaaVLy8c2/wRasMtugKvgy3tK3Y9BSD07KAitJlepTb6Nyqj/lxc9IOS5qOdbv20bjFWDOHW23PR991cyJsqSy27BEPA1bBTWY/M3bN01A6i5d3EGWtEN05ICVr9uf0lEzxfiowcivcqo+JZK0MDf1l/66ftdxMBdxkZG0olcVre/aJL9poWbOfHcOpLDaInmtNjX+uOXWm20Wyxl0iGQwGgxEDbLCNAcyd1Aa9pjlCStMwZ1Jb3bmbe63UxMFUDsfc/uvANB4tnQbSdl1FDMVGhltp0FJmNg6Wg9OyACWRogq36mO+3DyK6s//9pqYm2N8xDTY5k5qq6tE9OP26AZrQPdwKotlv/1zMC9F3KLI2pCexVt/8BvBmjW5vzZM1oaIsqbIAJeVtcF0Dn/buVdoTDZc1ja+6nL71H3B6aaAGkNXZj9f2f6GxS0VImvpjNsUJY6hK8OtOGDt4SaRrHFKJIPBYDBigA22MYCutlbcvuRkV+nSAaxccjK62lqrzuvuH8C6rT0ArKhHYFqWg1x8pcvh5kDXtEBuhq1ED6WygWlZAKA1tQCIr0R3tbXiuncc6/6dCuDWu3OnywsIThmzuKmJenS1teL8I2cJuXX3D+CXz77kchOlZQHwGB/Ro1h1sqYFy9rzW7db3EJkTdO0itHWIFkrD1mG0bCeEe+nIqOoq60V1556jPt3kKx50w7v3rCtIcZkV1sr/v4tM4XcuvsH8KvnLFkbTmXIshZn3WRk7bmtrwOwGqKEy5o6bg5EslYasiLfg4LnmjOHzeQIG4PBYDAigA22MYJli+bhHdOt+p9vvOsELFs0r+6cjbv63W5qw/b8qaA0HkBdet+yRfOQtr3Ray9eEsjNmY01aBtGgdwUKdEAcPbsaQCAKa3N2HLleb7cut/cUcWrUdyOPWwSAOCcI6b5crP2M1/FTbifTWq4LVs0D6d0HQYA+KZA1py5ekMEbqqMj0veOtf9/alL3hvIzZlfN5jOibkpWjMAePfhVvOe6W0tgbL2hu0cGKQ4BxTK2sJDJwIA3j+3K1jWqPcn1D47TrZl7VvvPjH0uTbUwOeaV9ae/GSwrDnPNeF9wBE2BoPBYMQAG2xjCKZdidLV1uL7+txJbRVFNWUpqkFpPACUGR9lw0DJrveYPdG/CcHcthZkTatZwLCt2ARxU1XDBgBDdhvtyS25Ou+4g+k5vYoXiZsCJdrhdsTE8b7c5k5qQ6trgIvXDIAyowiAW/MUtGZeWRsicNOydoQtJjdvK/8jJvp/1ty2ZmRsWQvj5kZzY0ZMAWDQkbXmpsB1e912DgxRnAOKorlebkdMbAuUtcp+Ep4dCg1d97k2Pvy5RpE1Vdy8rfyPmBTwXJswDs3OUO+0gBsbbAwGg8GIATbYxhCG7O5ozRn/bmRdba14yzhLMRhKZQNTjBy46X0xFZshT9e25rR/B8hpuYqoDaazgSljAJQqg2FrBgCH6pbCOOhRBgO5KYx6UPbzAzMPcblpCNlPpdwsBT9oP7vaWrFgnLVeFFlTVZc45Jlj1ZwJkLVMpfZoMBUia541M01xE5BQbkVnP4O7oHZlLW5DabpzQMl+OtwE+/mBGZasDaUyZFlTYUw63FoE98GRMrKmiJvDCwCa0/7cvM+1oVQuWNa46QiDwWAwYiCk5zVjNGGwKFaiAeAQ3YABS+m6fckpvmk8LhTUsAE1ik2A0uWNlg3rGbyw/IM48tAJvue6imqpBLNUshqkRARlzRxuw6kM5k9uw4MfPTvU8FAS9SBwW9jWhCIsBf/SRfMasp9AuIIPVGRtMJXF9845WchNyzXDhALngM1L1zRkdH9/k/MZBjQU9DRN1kwTKBaAbC46N8cAF8jrZN3EMKojRaPBOQAAR7flLFlLZXHxsXNostYA5wAAHJo27ecaXdbicnN4aQCyqQBZ89xrQ6kM1gfImjOHzSxyhI3BYDAY8mCDbQyBokQ7yupQKofWLG0GVfwIm6XY5FJ6XWc1F7ZRNJDKApqGSc2C2VJNntSo/BCQjj7ribJmcNcsi4yuBxtraGzUA/DuZxap2jaEtdwURUwBjxItUPC9M+KCoiMuFK2b18jVQmRt0Ja1iU0iWfO0gR8ejGewEQxwb0fSwyeMwx8/fk54FEuJrNEdF4OpHNIBxnAS3AaL4cak6Rkg35oVz69T9lyzeTURZG1YT8PU9ODnGqdEMhgMBiMGOCVyDMFRooXKsUex8Ua+/KDK+KB4790olt0EQshNURt4i1v4mnk79w2GrFkSkQXhfg5VuIXtZxIRGbKsCYYZA+oU/IqsESKmdtqhkJuiNvCy3JxUTZFzQFUaKZWba0yms66B1xhuzn0g4lZxDoRxUzVbT+a5NmQ/1wKfH2lOiWQwGAxGdLDBNoYg44keSmXdRgOBUJTeR0nt8ypcAITcqtvAx2s84q6ZKK3SiWKls1U1Ur7clKZEhnPz7mcoN6URGUL0z40uZEINNnU1bIT9rHUOhMqaWsdFC4GbdX82xsilcqtEcwn7mYisESJsqXDngLr9pEdMQ2WNI2wMBoPBiAE22MYQSAqEJ4WuYRE2CYUrT4mwAeoaB7ipfbSox2BYZCGJ2h1RZMGzn+HRv/izzuq4EWRtMJ0LXTdlETZSap/1GfmwqEdS3EiylguPYilNvyXImmtM0vczLjfTNIkOH6fOtIHRXAmnRais8Rw2BoPBYMQAG2xjBCXDQMmwutgFpamZxSJgK9pDEp5oVWmHFGWwkHE80SFKl1PHpkjpEqf2edKtGhn1IHCrjiw0xigqliuyFthEplbWGmR8yKT2ubJGTe9TxY0QzR1OZcKNIqU1iclEseJyK5QNd4RE4HOtXLYawjjcGr2fomeH/RkFJ/02gJvGETYGg8FgxAAbbGME1S2mA5RVT/ogRbFRXcNGMTwKGSsKRFXwldU8kZotZFEoGyh75i8F8VLauY8QxRpuYA1bVev8IG6ezyA5B1zjY1gJN4rh4chaaGqwomiuTEfSwXQW+bIBQzRKQGHXT9m0ZWpqcCPGNNTKWth+qpqtR4kym0M1z7Wg+4ANNgaDwWDEABtsYwReb3xTgALhKIOGpqOgp8k1bKra+lNSmopEJbqiEMatYZNLtwLE0T+XV7kcu0W3DLfBBtYkeg3DMFkzNQ15Pd2wFDoZWSu5zoHR03zHm3ZocROsmzveomhFmRLmVhVho6Ysx+76SRjT4JHn4VSmcY4LqeeakxIZsJ88h43BYDAYMcAG2xiB4+0Vtpi2FZRSJgdoGllRja900SMLxSxNiVY2I06iPb0zOFvcwdLTBl5ZKimlC10ju34SZM1rgGtaA9Nv6dFcR9ZC6xKdiExD6us8Iwcgrq/TmhTKmszIAYmun6p4tWTCZa2UycHU9AZ2JKXfn6Vss/0ecYTN5Agbg8FgMCKADbYxAhlFtRymPDhQ3U2NUOthZOVq2Bqh4HsVQus9AgU/axnDjePmaSJDTe1rRBqp/RllogGuKTfAw9NI6bKmug28gNtQdURGuKce50CjRw6EG7mNq/urGEVy6dTqOpISorkh3LiGjcFgMBhxwAbbGIFMek45R4ssqGpqQFLwh6qNyUZ1Y5QZTl0icKsaOdDALnSULpGaKiWaMD7CkTUjS6wTU82NoOA33nFBaJ3v3qMEWdN1IJNtGLeqeklqFKsRI0Ec50BYnZjDTdFzbVjCmHSfa4ERNvsaYfcJg8FgMBg+YINtjICWduhEFmiKjTJPNKkTY7WiSlcIG1fDZhC5NapJhWma1WMaiBE2ZVEsiqw5axbmHLBlshHpt7Wy1vCRA6ToX+OMSdM0Q7mZ5TJQyAMgdmJ0eBXiNpGhZw7I3p/qHBfh+2nmQqJ/HGFjMBgMRgywwTZGINPQwKQq0aprPQiRIio35YOWhQphjaHbgFqxYtlA2RS3zkchD9jnOHP1TEFXwUbOn4pq5Dairb8TzSXLmmvoxnMOyKT3mQ2Mgntb5wdy8+n62RBZkxgJEmoUOVDk7JF5roXeB9x0hMFgMBgxwAbbGIGjPLQQalDMXIv9nsYo0YMSKXRUbupq2MLXrdbQpaZrxuHmjZYFcvMonEOpDMqmiSJx5IBI2Q7nRo96gBrFUtXBktDW35Vnhxs1ha4R6X2ugm/fBw1ovuPdm8AIW00nRgDIizpTKnKoDJJSXJ0olrOfxA6zDez6Gfbs0LjpCIPBYDBigA22MYKKMhiuPDhd76iNAxoyr8hRnpoaW8NGWTezRsFvRJMKh5cGIJcKUKIdXqk0SrrFX6Tgu7wMI1bqFWU/a42ihqepEaIejtHf+KHe4Yaus1ehxocS50B463z32ZFrgqlZ5whlTdHIAW+XyEC43OSMXFXjLZoC7k/rM6qfuTyHjcFgMBhJgA22MQKZ5hmOMti41tz0FDotTLGp4aZK6aJwa6Qx6SqDotb5dmofmlvgnEHtKhjHmKQ0HXENj2aaEq0uhY4e9QhVolVzk4iwoanVfk/yhq6XV5CseQ2PlH2O8D5QNN6CkkaKGmdPw55rlHTNoernGs9hYzAYDEYSYINtjECmPb1sZKGR84r0ZiI3RYOzZdL7dFfBb1zUg8JLyzW7ayvsFKlo5MAgJcLm4eZ9TyCUpanR64ocWWtYR1JKfZ3jVCFyU5GuSRo34Hl2OOcJDSOnU2pMboOERi0jFjGlOHvsz9DDHBccYWMwGAxGDLDBNkYgp6ja3ntqal8jWobXGUWNGrRMT++jrpuKuiKptMOmFvc8kTGpauQArXW+df2Us2bkRhCNU6JT1AibstRgifuAauiqiLBRxg14UlydfRetm6brloOgEdwknx2NrJekOnu4ho3BYDAYccAG2xgBrbGHo6hKpvapUqIJXnLHKAqPLFgKUNx25mHrZpqm+/2pEZmKQhg9+kfZT29kwYnENaJ+R6ZzX4rqHBiBNvBUWYMiWQttnV8sunO4Ui3jADQmlZQ0bqBK1lJV7wuEynRNQut8qqw1NGJacx+EpkTyHDYGg8FgRAAbbGMElPoYR3lIO8pgg1pzy3THS7fIKV1xuBUNA4bTOj+IW75iQKSJ9Viq64oCURX1sM6jzhRTE2ELT+1L2WtWKBsoEztYxoGMMenKWgOMIlLrfI+Bn2pguqbMuAErmhseYQPUrNsgpYbN3c9KSmRjx1tQuIU81zKcEslgMBiM6GCDbYxApobNUR6AkNbcitvAU2adZZqJdWIKati8inrgunmun25gkwqpGjZqXRGgaOQAvbGHV9aEKXSq0tRI6ZoWt4zNrRFph7TW+bas6TpyxAYaKjq5UurEnCiz1tTsnhduTDZVvTcKaI4o6/ppO4plgjhyoAHOAZNqsHHTEQaDwWDEwAFrsO3ZswfXXHMNFi5ciClTpqCzsxOdnZ048sgjcfnll6Ovry/0/VdccQUOP/xw972dnZ3o6urCO9/5Tjz22GMN+iYWZGrYMnaEDRA3qWhoG3hXsRkfyguA0tQ+DUA25S/qrmGTziDXlLO5NSLqQVizoUrUw02JJM+gip56KCVrrRVZE0aylDkH6OvmcAuNmCps7EFqnd/UgpasFXFpSMR0FEfYojqiSCMHymUrDTUmN9pzzZK1wP3kGjYGg8FgxMABabCVy2WcddZZaG1txZo1a9DT04Pe3l709vZi7dq1WLBgAU499VQMDgZHb66++mpkMhmsX7/efW9vby+2bt2KL3/5y/joRz+Knp6ehn0nUg2bJ03Nac0trENR3AaeEi3KttCaVKioYfOuWWDrfK8SnaYZRWqiHoSopGdMg6tENyRdk6Ko2nV/uRbkbGNYZHy4SrRpAsVCZG4y65Z1a54akUZKaJ3v7KcnxbUhEVOJlGXN2+CmAY4LmS6RqeZW6M5zTdjBUs3IgWGJkQO5kPRbjbtEMhgMBiMGDkiDbfXq1Zg1axZWrFiByZMnVylQ7e3tuOqqq7BkyRKsXLky8Br3338//v3f/x2tra1Vx3Vdxzve8Q5ccMEF+PWvf53Yd6iFo3SKBsz6NqkQKTaK2sDLRNhy48aH8wKURrFoa0ZsnQ9VUQ+JgcEeJZoakVGxnxQDHE0t7rqJZ8RV2sAnHpl0nAPjnGgutYNljPRbidb53ogptcFNvI6k9OYZoD47oCbNlRTFch0XRGPSO3JASWpw+Lpl7WhuYPotp0QyGAwGIwYOSINt3bp1OPPMM4XnLF68GOvWrQt8/ZprrkFzc3Pg69OnT8e2bdsic5QFqXanf5f1b36IVPOkqg18aCfGctmNqjTn94XyAtR0YqQ1Dai0zne74xFrnuJFPQj76YnIUJVoNSMH6JEFrYnILZOtOAdUDPUOUPDNUsmVtZah/eG8oGa8hUx7epgmJu97E0Bjm44Iue20U8TLZel6SRWRSZW1nOrGW4idA6ZhuPdZy/D+qvfUgSNsDAaDwYiBA9Jg6+7uxpQpU4TnTJ06FVu3bg18/eqrrxa+f/369ZgzZ04kflEQ1omxsHoVjOfWAgDyX7sSF27+Q9X7AqGyDXwAt+Jd33N/77jsNFz06h8bMnKA0r3SVaINA5P6dwAgdBVUEPUgcdvZa/1rlMkpdK6hq8KYFEQWjP7d1ucMD3qiHmFKdDwF3zTN0IYoxV9VouaHfOodDZM1Snv60sOrAQBm71Ys/fxZuOjVPzamTiyEW2H1KhR/9i2L4z0/wZnP3QegMdHcQZIjypa1oUFP2nJYXaKVUq0m+hcga3d5ZO3yM8T7yTVsDAaDwYiBA9JgK5fLSKUEKTYA0uk0ShFn4vzmN7/B/fffj6VLlwrPy+fz6O/vr/qJClF6jtHXjfz1yysHTBMr/nw7pg7uCq8Vi6lElwwDJSO4db7R1438TZ+tfJ5p4JZnfoRJ/W+KW3M7ClfCKU2lNVZaq9mzBe/9pzPkFPwEuRVWr0Lxzu9YHH/zQ5z23L0ARkdDlMLqVTD/9rT1MddfhvM3PkLiFteYDBvTUCdrhiVrh+3fiZJg5IDK5hlByr3R143inbdWPtO+D5p39YovnHDTEffZ4d6LJv7P/95MenYolTXBfWC88JT1MTdejo+8Ysla0s810zTdGramIFn72hWVz7P385B9O3zHW2icEslgMBiMGDggDbaksHv3blx88cW4+uqrcffdd2PixInC82+88Ua0t7e7P9OnT4/82W5dkZ/StXWj1enRg5RpYPbAG4k3NQhrne/HLW1zG6Y0DojRVTCsFsvo60bx57e5fztKV+tucQdRpXViIiXamexlmjjv7pssJZrYQENJ1MNvP32cA5//43dtbsmma3plzddxIZC1pDtYhjXPMLZu9BhFFW6Td3YLr6uiTkwUzfVbM5367FBYwya+D2yYJv7vn1ZKyVrU+8D7bJKWNT9uPIeNwWAwGDFwUBhsL7/8MmbPno0NGzZEer9pmrjzzjtx7LHHYuLEifjrX/+KY445JvR91157Lfbu3ev+xKl5GxIo0fqMuUBNK/GypmNz62GJ1+94DQg/T7Q+Yy6gVXMrEbipGDkQVicWqETvCtknlZ0YiUauTjE8vNwSSnEVOweSrf3zjmnI+UTQRbIm7GCpQtZCImwWt+rukSVNx6bWQ8UXVhrNpT07DOqzQ+l9ICdrSTdr8X53vz0VPtf87lG3ho0jbAwGg8GQx0FhsM2fPx+bN2/GvHnzpN+7bds2LF68GLfffjvuu+8+fPOb30R7ezvpvblcDm1tbVU/USHykusdXchdd7vngI7vvfuz6GmZlHj9jqOcNAW0M9c7upC99IueAyl87m2fCOdWNXIgWuORsDqxQCW6pUN43aSjHiIlOnQ/VdawEbmVidziKvhDIWMa9I4uZJdXy9o/v/2T6GmZJDYmnRESQIz7IETWOrqQPvv/uH+begpXLfoEtubEUXqlNWzCZ4e9npqOh//PF601o9a/xonmCpwDcRxRcQ1d57unNA0ZnxmOekcXspf9q+dACv/0touDn2tOSmSpGGsOIYPBYDAOThyQBhulPq1UKiEt6oIH4Mknn8Rpp52Gj3zkI3jooYdw1FFHqaQphbABs9mlywB77lTz99dg7XHvs95HbFEfVekSKVwO0u84x/plcgda792C/5l3lsUt4a6CYWumd3Qh/e6PuH87SvRruRCDXGXnPr+oh48S/ehHV9iGR+NGDvhGZHycAz9a8jkSN8Qc6k1pAZ9+xxLrl0mWrK2eb8macFSDV9YiR//C6yVTb1kEANBPehe2/ugZ3HH4acFt4B0o7GAZxC27dBn0E6yuurn/72t49e/Or3pfEJSMHBB0ifSTtR+c/f+RjMm4zzXKfrqyNvGwKlnzcw64c9gAoBxynzAYDAaDUYMD0mDr6upCb6+4mL+npwczZswIfH3Pnj340Ic+hDvuuAPLly8PHrzcIJDmFdntzPVph3u6CibbOECU2ufAtBV0vW0i9I4u0iwlTdMqkY+4SpdgzfQFthJ98tnYfsdzthLdgM59IdyyS5dBf9tpAIDc576OrWd8uOp9gcg2NYQbMlnrnB8+hqfe/n7rfQk7Bygz2CqyNgF6RxdaCPeBig6WlFEIDrfU1FnITrGePeQoVsJjGjTbOaAdOtU1UhrafCeAW3bpMrdFf/P/exRPvP19Ve8L5RbT2UPZT73dfq6J5jimPNfhxiMMBoPBkMQBabAtXLgQDz30kPCchx56CAsXLgx8/etf/zouvPBCvOMd71BNTxqmaYY2NTC99TfZJlfRIHfui6zYEAYZF4ZdXta5RG5xo3+EVuso5AFYSnRuKlGJVhD1oHBzXATaYVPpg7OVRD3Eyqppmr7OgaQVfIpzoE7WqMPQ494HbqSIdh+0kHnFc1qQuRXzLjfyCImY92fZMFAoWzVqgc81r6xNPZzc1j9uR9KwFFcAdbImdA54I2zceITBYDAYkjggDbZzzz0X3d3dWLFiBXbu3FlVM9Df349bb70V99xzD5YvXx54jaeffhrvfe97G0E3FHlPCk2gx9c2PABAy+YaNvzWUaKFg2/ztUo0kZtrfESrYasYkwQFP1cxcodKZfHIAaWz6wTrZu+p5lHwk261XjYMFO1GD4EKvq1A13GjKvgR140yu869D+yojDsMnVzLGVXWCBEZDzfnOxQNQzhyQMmQdolokZbNVe6DpA1wj7wEPj9KJbfxiJZrqjw7GrWfIiPXkeNctXNA2HQEYIONwWAwGNI4IA22VCqFBx98EENDQzj99NMxdepUdHZ2orOzEyeccALWr1+PRx99FK2tVs3XmjVrMGfOnKo5abt27cJ5553nvs/v56Mf/WhDvk9Y63wAFcMDqPLgJ+0lJ6Vq2tw0V4kmDr+NqeDLGJNeIxcAeeRAVFC4VTz4uSpjUgRV+wkIIlneGrQq50CykUmKEm06spbJWedSBy03IF3TWTctk6vad+HAcSU1bHLRIvKzI3ZUsnJ9vw6zVbwAINO4+2CYZIA7zw4nc8CONPvdB56upianRDIYDAZDEuKuG2MY7e3tuOmmm3DTTTeFnnvGGWdg06ZNVccef/zxpKhJw1FOgjqWAZ4olq4D6TSpTgxAbOODFPWojbARuWlNLdYksgYYk940Uue9gQaLs2bFAsxyGVrIkHY13Ihph3HbmROUaLNKic42LMWVFDHNVyKmADyph+Hc4siaaHadC08017u2g8USxucy/u/x1GKZphmplpbCzcx7I82Nic47e5JL6dADvpdZ6xxoVPptyEBv69r+suZngGuaBqTTVsSQW/szGAwGQxIHZITtQAOtFqui3Gua5lGikx1+K+oo6MCsibCRuTWihs1jTGZSOtK6pTgKG6I4RhFQHQFQzM2N/uUaGTENV6K9iqqmaUJFtQq2wR67hk3UdCQg6pH0EGhKzZOXm3WPEhqieMdbeNKeVXNzati0bBO56YgraxHvgbDB9gAq91cmC03XK2mHie9n9Ahb4H46aZEcYWMwGAyGJNhgGwOQrY8BPLU7Id7c2LOxJCNFUtxi17BJKF21xiQlJRLxRw6Q6us8SnTiNYmCIct+vIAGGkUkbtX3gazxkWS6Zn19HcFx4TXYkuTmOi7oaYexo7mU/ayJYpGj8414rtXV5obsp2cWG4PBYDAYMmCDbQxApgNdw2t3ZJqO1BhFydewUdat0h3Pe64wwpZKVbzlMbvQibh5I2zkLpGqopLCSFHe5eU9N3mjSKIWy74PqF0FG9nWH+49SoiwZTJu/VOSzgFvtEi2sUeisuaJ/AESDYtUpd8S6iUdwzV0hIT9zDDZYGMwGAyGJNhgGwMgRWNqjSJqZCG2l5yuRNcqXeHcVM1hoyiqkoZujGYQpmnS9tTTap3cJVJRDRsp8ucYRbJNZBrgHNBq7gNKvWQ8bhJOFZkIGxDLmDRNk8bN8/wgt85vQIdZb+QPoBvgsZ9rNrcmUX1qvva5Jk4N1pwIG6dEMhgMBkMSbLCNAZDqnerqKYh1RY2YjRUUYSNyMzatg9HXLc1NqoYtQpMKIFrUw9uBUjh/yidNLV82YAhGDjQkshBkFJFTXBuZfuukuNIMXWNjNFmTcqrIOi5i7GmhbMCRlsC5erUzHG1ewyHjLdRFJQlRrNoIW4NGDlCbyAAVgzhwP52oPDcdYTAYDIYk2GAbA3CUhxZh1CNeDZvxxuvRjCJChK3WmKRyM3teAwAUf3U7BpbMRGH1KilutHWLNiPOtJUvY/trUpxqrx2o4JeKgK0se+dPASHpmo6iOjQQ0/BQPwi9EZ37AtNvQ5wDpr2Pxbu+F1HWJNL76sZbhNwHjqz1bJHiVHvtwHWrneHokUnReAu3rf/A/ngOFcooBMl06rjPNVITGVuO65xkQdxcg41TIhkMBoMhBzbYRgCF//2x1PlDEh0FIVnDVnruMQCA8benoymqhM59gRE2ATejrxvlv/7Rc8BA/vrLpJQvmXWrm6UkMD4Kq1cBNo/hzy2NsGbWtdN68JiG6llnTVXrK1q34sP/Y/1SKsbcT/nW+WFGkatEv9kTUYmmpGvaRlFNnZhoPy1Ze9RzQF7WSG39A9L7RCmRhdWrgDd7AADD/98HpffTubauacjoAbJWM8PRe7+I1q348Gr7l3wsI5c2i1CuXjL2c02mUQu1ltNOiTQNjrAxGAwGQw5ssI0A8v9xVTRlkBApqk1TC1NUS79a6TkQwSgiKF1BaU1Cbls3AqhJxzLKMLZt8j3fD4OUNLW6tCax8WH0dSN//fLKATOCci9RWwcAyOaQ0nVkbeNOxK3wzX/yHIi+n0Ijt7YRBLFLpKtEv/iXxKJYgfspcg4okDWZtv7U9D4VsublFTTDrXaGY1r3jLcIWDejrxuFb/2z50AUWaPPh6urEwtx9qh6rpHu0SxN1jSOsDEYDAYjIthgGwkYhpwyKDPEVUKJNrZudNPuKgclFVWJ1ty1XQVFERl9xlygVsHUU9Cnz6FzI9X+BRkfAUr01o2AYdQcjKjck7pX5lxF2/XgJ8pNohFEg50DpAHQERrcKJE1iYhMXdORIKNIxX6Sxg1Uz3D0cgs02BRwc/Zk73AB3f0D/icVq1O9KW39lTzXJDIHyLWcXMPGYDAYjIhgg20koOuRlEGRYlM7T4zSVdBSVGtEQFJR3TWYD/2coEYQotodvaMLqXd+qIpX7rqV0Du6yNy8CmE4t+pU0iAFX58x14pEVB2MptxrQLCiWmOAA+F7qoabde3+PEHWJFrnq1Cidw1ZnyuUtdp0TQI3vaMLqTOXeg7Iy9qAzWkPSdZoxodaWdME+1ltFDWK26Nb3wAAPLRlO2beehdWPbOhnltNGimlxlTFcy3aPMKQFFcnWscGG4PBYDAkwQbbCCD3z7dIKYN/3tYHAHhgc0+gYlM7T4xSJ6Z3dCH7D//iOSCnqK56ZgMe3LIdAPCFh5/25wW/OjFafV36uL+zaB1/Jlrv3YLs0mUkXgDw/Wc2IF+2IgCn/ujeQG6B9VgB3PSOLuSuux2WuQVA06WV+7v+tgUA0DcwHKyo1owbAMLXrcLNOSBvePxpqyVrD2/pDZa1gAjbULEU2FUwrhK96pkNeGhLL4AQWau9D2xuPfsGg41jAOlF77AonXCWtKz94JkNbnOO0358Xyg3Z08dWXvhzT2+3Or2M4qsvbgFAPDmYLCs1c5wBJKXte7+Afx6w1b3b8M0cdm9a+vXobZhEfm59n8jcwOA3UPhjqhKt1R7DltYB0tOiWQwGAxGRLDBNgLIvv/j5HO7+wfw242VtLEgxcasjRTZykOhbOC1PfsCr58++wLrl9Y2KUW1u38Ay+9dW/l8wF/hAurqiqhKtKN06+PapZSt7v4BfOrex9y/DTOYW1AK3d/e3BvILbt0GVKnvsf6/dNfkVLuu/sH8PXHX/BwEyuq3gibU1f02t79gdfPLl0GjJ8AAGj63u+lua1+ma5E1zoHTACv7O73vXYcJTqKrDlG0aPbrCjO82/sDjZYPN8liqxdRpS12nXbtMu6L3+87pVAbtmly5A6+Wzr9ytukN7P/3h8vYdbwH7WGOAALZU0u3QZ0Npmnb/yISluG3f111YNomya2LSrRn4iOAeA6M81gO6Iqnuu2fdB78CQ7/47c9hMnsPGYDAYDEmwwTbKIavYOIbHL23POgDM/s6vApUON4JjGlKK6sZd/XXzwHx5wZvWZHFzojjr39wjVKKd72J6OyaSuVUfC+JWq3Q559yxPliJBgCtbaL1rzNbTIIbZT9r29OvemYDNtjnXLj6j8FKJCpDoHXbcEuKm5N++/MXX3Vfm//d1YHcoirRMrLmTSXt7h/Ad576m/tSoMHi+S5VzV7I3KqP+a6ZaVaN3ujuH8CDr/bQuCUtazVOCwBI2bVs20QOFQBac0sVRyrmTmpDbQuUlKZhzqQ2ITevc2Dz7mBHlPtdJJ9rMs6B2rb+f9hqRYD/tmOv/7PDibCVOcLGYDAYDDmwwTbKQVVsvIZHd/8ArnjgCfclodff8apLKqpzJ7VBr2nU4MvLc23N5nYbUYmOx636mK8yWC679SSareD/bjNRiY5oTMrup8OLHGECPOuW9389LrdiJe2wu38Al9/3uPuSSNaiKtEysuat5dy4qx81bTGCDT3HcRFhzSiyVj3rrInuiAHc/UxO1qpr2FY9swHr39wDALj4N48KnQPOGBHZe7SrrRWndh1WxWvlkpPR1dbqz82WnTtf3Oy+NO+7/xPMLeI9EMk5YD/XbnnyRfcl32cHp0QyGAwGIyLYYBvl6GprxUnTDnX/DlJsvN0OZZQOV4kulWBKFMN3tbXi9iUnu3/rGvwVLqAqFUxOiXaiHnJKV1dbK2444zj371BlEABy0ZToKIrqJ46p1G2FcsvJ7SdQqUWSjRZ1tbXiHdPDlWhvIwgpbs7g7Ai86LJWUfDJxpR9flRuN575tqrrU2SNbEzBc49G4HbxseGy5p3hKOsc0CIakwAwo30cAOAzb5uPLVeeh2WL5tWdY9Y4oj59H80RVXmuFS3HDBFRHFHucy0s0mqnREKCD4PBYDAYABtsYwIz2i0F64q3LwhUbLwRNimlw1O34kZOiFi2aB46Wq3333vBYn9eqE6hk1Gi3XRNSUUVAD44fwYAoC2bCV8zAMjkpJToqAo+AJw47RAAwDumHxasqDprZvMi7ydQ2dMISvRMW4n+1HHzQtdNy8rJmqPcyzoHAAlZ89RydrW14t9Oe2sVryBDL2rEFADOtWWtNZMKNzwAIJ1BV1srLjx6NolbnP08carl7BHJGmqjkhLOgTj3wbBtuBx92ET/7w14Ur0lnQOeZj0yUTYZ54Dsc82Zw2ZyhI3BYDAYkmCDbQzA6UC3kKDYIJPzUToEyqCnM1wUhbBou5UdRd8XHk90V1srvkRUouMoqs6ajc9lAtfMVc5TKWjpNLraWvFRohIdJ7LgcJve1hq8nx4D3NlPRx/UIIgwAZ7IZLJKtJebA6GseWqkZJ0DAFHWaurrPnr0EQCAprQebLAAkSOmQGU/x2WDZc27Zs6ss3fOmgIAOGnaIUJumoL9FMqap+4vsnNAMgoOVNatiTIIXZabV9Yk123ZonnotJ0Dv/1IsHOg9rn2ldNDovo8h43BYDAYEcEG2xgARbGpncO2bNE8TB1npaD9+sPvDFYG02l3PpBs6iGZW4ASnUuJlehYiqrNK5eiKYMOHCX6xKliJTpWZEFizZzPWbZoHj60YCYA4NpTjwnmBU8kK4Yx2SRYt9pGEMsWzcNMOwr8P+edIVizeM4BWQUfsGQMAEqGGWywwCtryRseDhxuQkMPiOW4cFrMC2XNNp61CM6BqOm3gPyzQ8Y5oKXTgC3DUZwqFOdAbVv/ixZaz7W0rvk/O5yUSI6wMRgMBkMSbLCNATjzxITGh8+g5XFZy6PbnsuKPyCi8WGaZiRl1Tm3aJiYNr4l+H0Je+9rDUnv+a0hSnScCJuzn5Q183Kb3JwLfx/g2c+kjI/6QcutGUvW2gSypqVSbpRBVsGnylqtMemcWzJMlI3a6kkPYqTfUu5Pt8bUR9aGQ+YRuhHTCFFJ0n56ovOAZYBfcOQsAMA/nXSU0DmgIgou41QhOwc874m2pxLPNXsNcumKc8D3uZbhLpEMBoPBiAY22MYASIpqMVghzIcohFHrd0qG6daUBHEzTbNulpJzrmGaKNVW6nuRsPfe2+3QAXXNVETYxIpqMLcwBd+p/Uss6lGoVvBluEVV8CmyBsCzbvXGrWNYqeQFSEbYIqxZrIgpwfAwawwPAJjc4tyraTE3BVFw2n7WO6JEzgHAO6ohuqHrREFrUTWmocY5AFQMviq4c9i46QiDwWAw5MAG2xiAlJfck3aWcxTCMAUhYv2OV9EM5FYsuL/WRj2AAMXGOT9pJVrJmiUU/fOJsDncRGsGIPF0zdo6Me/54cZkNAWfImu1s86AypqFcUva8PCL5joGu9CQBNTsJyE6753DJn0fJHSPViKmnns0RXQORBw5UDIM15EUyM3zfbVc/XPNj5vGbf0ZDAaDERFssI0BSKXneCMyVMXGUYYklS7vdQOjRd5rSirRXkXVNAWROAE3mfQ5gL5mcRR80n7WpKnJcIs6t8t7bWlZoxqTERV8kqzVzDoDgLSuu0OghesWwwB3vrNsvaS0kZvUfhbrU1zpz46m6muo5lYTnfeen1Q0N09xRHnve3sNMnrlv9N8yccIZ4ONwWAwGBEhzncJgGmaePPNN9HT04P+/oB2z7UflE5jypQpmDp1KnK5XPgbGC7C0nMAjwc/okJoInrUI5fS3c53dbyqWudbKUy6piGj6ygahjjq4ShchmF1VnNqQCS4jTZl0Htt4X76pKnJKvhJN0SpjhbpJG5RO1hSZK3q+9as20CxJE5zdQxje26XJjK+ArjJ1v1Jy1rS+5mNkK7ppN8mnK45Es81oNq5VMXL+b667jZt0jQNTekUhktlf27uHDbuEslgMBgMOUgZbC+88AJuvvlm3HnnnSgUCtJRD8D6T+3kk0/Gtddei/e+973S7z8YIRX1iFDD5nrJZaMeMpEiTztz5z3Fgthgq2sDL2OwydTuRKhhS7x2R2CAh+5n0q3WBbV/lHosE0hE1txaJU2rRDNgKd0DxZIwvc9rfKKQB5oFzXBquclEczP16bfhKa4xjKK4EdMG1HKONqeKk6Ka1jWk9QCnimfNvM+1XErHcKnsv6c8h43BYDAYEUFOiXz55Zdx8sknY8OGDfjxj3+MjRs3Yu/evTAMg/RTKBTQ3d2NRx55BLNmzcIHPvAB/OIXv0jyux0woHQVdLvQVdWh2FGPEIWwUpwfzRMtqwx63yNUVj0ef1llVap2Jye/Zg1rUhGBm9tqPamoRxwlOqKCL1uTWOscCOUWY26XVIrrKIyY+nWYla1hi2VMEkZI+DoHiLWcst01KU2B/O6BKm6CGjaj5zUpPgwGg8FgkCNsn/nMZzB37lw88sgjyGZD2sT7fVA6jalTp2Lq1Kk47bTTkE6n8alPfQrnn39+cIoTA4Bs++sINU8JKtF+6XMALYVO03XLK10qJqPg+0WKEm5oAEi2gY/CTUUKHUHWNJ+Oh2ENNKLWY8VyDqTCo0Xu3K5yGWYhD5knkkyKa6z9TKqxh1+HWclazqRHSETiFrNekjZ2o7nqsMhgK29aZ/37yN1SfBgMBoPBIEfY/vKXv+CjH/1oJGPNDx/72Mewd+9ebN68Wcn1DlSQZ52pSB2SVLpURNiSUlYTr91pVGOPOHO7GpimRu7cF7MjaSTnQJpYXxfRCI97fxbKhjC9vFHpt4hwH0Tdz5JhEMc02NeNMkKiwfsJBHf+NPq6UX703rrLGH2vS3FjMBgMxsEJksE2MDCAwcFBvO1tb1P2wUcffTR0XcfOnTuVXfNABHX+lJ8H362R8etY5kGSUY8gJVq6Q17EtCZZY9JZs/BBy8mmqbl74RfFCtvPyLPOCO3MEa8RBJKMsPlETKu4JZTe5+yHLDfHkARCUoMVzGFrFsxTE+1naC1nxFmJpJEgEA+3T8qpQklxNfND1mcQHVHG1o2Aj1FuvP6KFDcGg8FgHJwgpUS2trZiz549yOfl016C0NnZib1796KlhV7cfzDCq8gFdSwDIO5Cl/ActjhKdPgMqngjB6LWYjncWgKaDsSJsMmMafCbw0at3ZGNmJLamXuvG0OJTjTClq3uQks2dO2ugtLcnLb+EaO5gPX9AodUj0TENOFaTkonRgDxRkg0pF6yNprrz02fMddqhlNjtOnTjpDixmAwGIyDE+SUyP/8z/9ER0cHLrzwQjz++ONKPpyNtXBUz5/y3y6zXK7M9okwtyt2hI3Q2KNOsZGsr0uyIYpfZCGUm4IIm7Am0Wfd6PsZP+oR2M7cMCrD0OMo0XaEQpYbpbYusqzFTQ2W5JbRdbdWTmRMRjVyq7glVcsZ8/7MpnToQSNBfAahA/LpmmbE/RTXmAZkDgSsm97RhfQ5F9ZdR++YJsWNwWAwGAcnyAbblVdeie985ztYv349Tj31VLz97W/HT37yExSL3KI4STj/8Wd0HanAFtOegcGR2vonV+sRqNjIRmQSaRxQr6h6By0L182j3Cc61HsEOjGK25l7h1N7WtQT57BFjUzGqSsiy1rM9D7ZaK6maZWoKcU5kE9ogLyCWs5E6l8dxwCiz2GzuCXn7JGpzU2fcBYAQD/qeCk+DAaDwWCQDbZcLodLL70Uzz//PB588EFMnz4dF198MaZPn44vfelL6O3tTZLnQQvHaPDWu9TBq5D4teZOSMEfKlkDYKOkDiVtfJDqUAKMScq6VdWuJNKsJXjWGXUOW6KdGAO4jaSsud0Oo4yQAKLP7XLvUUK3wwj1da58mqY1QF4CcWs5w9JI3Yh+RFkjRZmBiM13kkunDmw6Yj+nfe9Rm4/W3CrFh8FgMBgMssHmxZlnnonVq1dj06ZNuOiii/Dtb38bM2fOxEUXXYSnnnpKNceDGlJzsVIpqz25DWoNW5JRjzCjKEyJ1mKmNdHSNf1rnoTrVjVoOZoxKTLCK/On6gcth+5n1MiCjKzpOuAnayNpTAbsJzX6Fzm9T6ImMVDWEpoRF7eWcyRnOFZd0zMIXbphUaLOnoC2/n7rFiONmsFgMBgHNyIZbA5mzZqF//iP/8C2bdtw66234tlnn8VJJ52EE088Ef/93//N6ZIKQDI8ghp7jII5bIERtoTnnUkphFGif+mM1UQAyRqTkVIiG1SL5TecmjqHLdH024jR3NjpfZSap7r6OkFExkGMAfJDEs+POF0/k26d75U1sgEeM51aNFcvtK2/T2QyzngGBoPBYBzciGWwOWhpacHy5cuxbt06/P73v8eUKVPwsY99DDNnzsRXvvIVvPHGGyo+5qAEpWW4GRIpCm3N3YAIW9S6oiTnsPkZRQBog5Y1LVluft3xqE1HkqzF8mkCAURo7DECNWyhHUkjpveR0pZj1NdpmhapztQwTRTKhJEDfnPYCPcAgMak38ZMp04y+iflHIjoEGAwGAwGQ4nB5sU73/lO3H333di0aRMuvPBCfPOb38SMGTNw8cUX4/nnn1f9cQc8XG+vZLdD6z1yqWCJ1GLlIyg2HkT1SsulqcVdNzq3soJZZ2GDlhthSGqZCKl9iLGfMRR8qjGZbHpfyIw4qqxJ7Cl1TIP/DMfKPUAZ6i397JBIv43dsCiJ59qw3eVUYj85wsZgMBiMqFBusDk4/PDDcfPNN+OVV17BySefjB//+Mc4/fTTk/q4AxYkwyPMe5/UHDYZoyioOJ/MTb3SZcZoBOF9n0x0wRvlkZ2rRx603KA0NS8Sj5iS6ors/YzKLcHav4pTpba+jppKKh81pQ6n9ttT53wTQFE4QD5mynKUVG/qc60R6dRBKZF+3GIMQGcwGAzGwY3EDLa+vj7827/9G4488kj84Q9/wJIlS/DrX/86qY87YJEnKDaB3fFk57AloHSZQRE22fS+RFOuokWLohi6FCW6av5UhBlxDWkiE7ETY5Ky5u5DQPSP6hyQrUl005YjzCNM0ph0rqlrGtJ6wKwzw6jMcIwia0mmHQYNQpeNmMqmuEqkkUplDjjnesYVMBgMBoNBQTr8FDn85S9/wS233IJf/OIXaGpqwic/+UlcccUVmDNnjuqPOihASokM6o5Hbc3diFqsuBGZBnXHA8SNA7zQsjmYkIyw2bxSmvysM2fQsgliV8Ficimuo7GGLWw/qc6ByE0qEpxHGKVWzLtmWsBw6uC5epXvki8ZQPWjpY5Xo+o4ve9JuiGKcORAYIQtOHMgasotg8FgMBhKDLZSqYS77roL3/72t/HEE0/giCOOwM0334yLL74Y48ePV/ERBxRMUYpRDRLvdoikm1SMrNJFS1NrfNSDUpNonVjh5gxaHi6Vhcakq3iXSjBLpapRDxRuDanFGo37maBzIMz4oEQmTUluUinLNdw0TUM2paNQNojOgQJM0ww2DGtAaZ2vKv12JCLNwggbG2wMBoPBkESslMgdO3bghhtuwKxZs3DhhReira0N//u//4uXX34ZV1555agz1vbs2YNrrrkGCxcuxJQpU9DZ2YnOzk4ceeSRuPzyy9HX10e6ztq1azFz5kwMDAxEIyKRciVTwxbovU9oYHCcTozU6F+S6X2xFcIINWxSs840rWr+VBU36ow4iSibVC1W1EYQEdbMe13SsPEGc6PN7Wp8d02pqGTNXD3v+4RDvb1RfZnnWiPGNDQi0tzkP4fNv62/40gJ2WsGg8FgMGoQyWB79tlncckll2D69Om48cYb8cEPfhAvvvgi7r//fixZsoTsZW0kyuUyzjrrLLS2tmLNmjXo6elBb28vent7sXbtWixYsACnnnoqBgcHhdf54x//iAsuuAC7d++OPmdOwsPqtgwXzQQK896PgqhH4By2MGMyZgdL0boFKoSixgEeaDFq2KhppLX3EklZ9dZwRVHwKbVYMevEEp3DlvEfnE3mFlHBp8ztqqvHSrC7Zpy5emRuEQfIN2RMQ5Lpt4Fz9QTPtZrvwWAwGAwGFWSDzTAM/OpXv8Lpp5+Ot73tbVizZg1uuOEGvP766/jOd76DBQsWJMkzNlavXo1Zs2ZhxYoVmDx5cpVy0t7ejquuugpLlizBypUrA6/x5z//GR/72Mdw9913Y9KkSZG5yDQ1kOp2GFBPkVRxvlzjgKhRLPl0TdM0aY0DgqIesm39I9SwiQ1w/7RDgDgjLp12oyWRFPwItVhkWUuyrX/ciGnMGrYkUyITi7C5slZfpEaaxeYdIK+aW1AzpYRTvd2IqcjQddr6y8haJqgQkMFgMBgMMcgG27e+9S2cf/75SKfTWL16NTZt2oTPfe5zaG9vT5KfMqxbtw5nnnmm8JzFixdj3bp1ga9ns1ncd999WLRoUTwySUVkBLOxhHO7GtDOPG6ampRR5FF+SfV1UWeKRWgiEMfIBZKdrafC8CgZJkqiGs1E2/qLuSWxn6ZpxozIJGfoOtdszsjX/QGVtOXQod5JRZoDmimRn2sxI2zCQeghMxz9jFyvI4XBYDAYDBmQ//e49NJLce6552L27NnKPlymSD0uuru7ccwxxwjPmTp1KrZu3Rr4+vHHH6+Ei5mnK9FOpEjUsSyoO17tLKVswDUqimoCs84C2pnLz2GTVwbDuIXW/iXRdERqoLdP1INs6OZgDu5XH/UIqRMDLGU1nQ1QdhNNvw2INFNT6CI4B0qGCcdkEHcVjFdfF2UeoVSKq0+6ntR9MDwUiVucVG/AGiIf2MCnISMHAvYz6LmWbQLy+6X4MBgMBoNBirANDAygq6sLb7zxhrIP3rFjB9rb2/HXv/5V2TVFKJfLSIkUFwDpdBqlUknZZ+bzefT391f9AABKyUQ9gpQHIKS5R1wlmlAjE7tJRQRlUIPVCt8P1qyzsDQ1Wo2MXFv/8FRNM8CQ9L6PXvuXTNSjLlLklTXBusVOv41SXyc7tyvRuXoRZ/4ltJ9Bkb8qbqEdLOVnJUoZRQLnAGUeoXT9q4LMgaDnrd86MxgMBoMRBpLB1tLSAsMw8MQTTyj74BdeeAEDAwMYN26csmuONtx4441ob293f6ZPn269IBFhi9MdzxtRIzUOyA+LU4yicAsaGEztjucouBEV1cAIbqkE2Kl79fVYkumakSIL8mmHgLeuSH3DhTjDxtO6jpS91qQ28Ek2HYkcMXVkTX4/AcGohqpZZ/6yFuYciGLoxnl2AMQaNiA550DAfeB1wiQhaySnSljTkSBe3HiEwWAwGBFAMtg0TcMxxxyD1atXSyn0Ivz6179Gc3MzjjjiCCXXk8XLL7+M2bNnY8OGDYl9xrXXXou9e/e6P9u2bQMg58EntQx3PNE1kQXdnqUEhHiivUpHsUDmpkKJDjU8orTOpyiD3k6ADZzbFSeNFKDVFQExuwpGrK+jrJsrB+UyTIlodhwFvzJCQr3h4dyfGV2HHjic2nO9UZZ+awZEJQF6vWQkY1JiFELts0PTNJqsOQZ4VFmjRHMD2voH8uIIG4PBYDAigNx05Jvf/CbWrl2LCy64AE8//TQMieHPXrz++uv44he/iFtuuQX/8R//EZqmmBTmz5+PzZs3Y968eYl9Ri6XQ1tbW9UPgGiDlim1HlFT6LIx28BHiLDlKLyQXOv8KuUybqv1CA1RKMakMCUyiaYjMVLByNy8cpDUnkacRxhlP6Xq/kRz9ZIwimTSqVXImszMP8mRA4HchM+1eLJGGm4fGDH15+W3zgwGg8FghIHcdOSEE07Avffei+uvvx7HH388NE3DpEmTMG7cOFLjkGKxiB07dqBQKGD69Om47bbbcPnll8ciLwNKfVqpVEK6AV28VLf1N/buDLyupUAUxdGFTNbDbRgaaJ0/G5OmlnC6VToDrabOLUzpqpwYnRtlZpew6UhoDZt8S3OKEh3UidHLTbhuHjkw88PQWmgp0VJNR0ZZxNS7n7XPSrKsZeRTg4eK0R0q3vdRZU35yIE9znOt/ro050Dl/pGSNUr0b9ia12nu2y3Hi1v7MxgMBiMCpKyTs846C2eddRZef/11bNu2DT09Pdi3bx/tg9JpdHZ2Ytq0aZgzZ05DDCMvurq60NvbKzynp6cHM2bMSJ6MhMEWNk+ssHoVyr/7BQCg+MOvQZ8+B9mly9zXSalDTmvu/DBZ6aK2M0femldk9O+uCufKN4JQXPfnfM90GkZfN/SOrgo3SWMyqVln5sC+em7EuiItoRo2c6+toEZUojVdtxwExQLZ+CC3zh8eAAAY+3bDe5Y7ODuBBjekiKnzPfVUdFlLaj/tqJg5WC9rOWK9ZBLpt4XVq1B64E4AQPFH/wF9xrzq5xrh+aGlUlZEs1RUaoQXVv/AncM2dMnfIXfd7S63MKcFR9gYDAaDEQWRrKZp06Zh2rRpqrkkioULF+InP/kJrrjiisBzHnroISxcuDB5MoqaVBh93chfv7xywDSRv/4ypE8521W8pIyP/DBZsSkahtvOXKjY2Arm0CdP9VdsqI0gFNfHFO/7mX3yEAaWzPTlRmmdL82NoESXn3oEAGA891gdN2oNWxKRycLqVSivudv6/fYvQ+uYXqVEU5u1INdkGWzEdaPJ2irAjsgMf/o9ML/op0Qb4lEiMRrciCKmxfv+2/plaCCGrEUwigj3gStrz/45MjfVxqTS51quyTbYJIxwQaTZ4naZ54BRxS10rh7XsDEYDAYjAsg1bGMd5557Lrq7u7FixQrs3LmzqnlKf38/br31Vtxzzz1Yvny54CpqoMoTbWzd6HY6rBwsw9i2yf2TlKYG+RoZr0LS7BMtDVJsjL5uABXDo2yGDFpOwHtv9HWjsPJLgdyoaxatSYV4rp7R143S734eyi2J+rooSrTDKxI34rrRZM3LzX/NAGK6pkID3OjrRuH7X/EciChrcbg1StYi3Adxn2uh3DLRU4P9atjCuDm8SoaJst9zjSNsDAaDwYiAg8ZgS6VSePDBBzE0NITTTz8dU6dORWdnJzo7O3HCCSdg/fr1ePTRR9Ha2goAWLNmDebMmVOZnVaDww47DNls1ve1UChK79NnzAVq54zpKejT57h/hnp8HUg2DvBeL+sTXaAqNmHcYjUdCVJUt24EzGBu1DVLohGExa2mE6vPuoXWFeXk9jOMm0olWnZAdVxZ8xrHovQ+1YaHy02FrCXhuCDKGt1x0bjnWlLRv5JhoGyvSRRuYfMIeQ4bg8FgMKLgoDHYAKC9vR033XQT1q9fj+3bt6O3txe9vb146aWXsHLlSnR2drrnnnHGGdi0aVOls2MNnnzySbS0tETiEaWtv19ERu/oQu662ysHNB2561ZGqpGJGmELmnUWqtikZGcp5ckjJcLmKOkz5gJaMLeRbIhicatZT591o6aSqjImZZRoarRINsIWVdayVFmLMGg5bK6eMllLIPoXLmvU+yDerMQ6XhLPNaoxGSWaG8Qt+9mveQ6kqriFOqI4wsZgMBiMCDioDLZRA4UNNLJLl0GbY9XdNX3ph1U1Rd73qTY+QpXBji5kP/tVz4FqxSal6+4AXJHx4daJGYY17FoRt8wFnlrGAKWLqkSrbOuvd3QhdeLi2Ny0GOmaUZVo2WiRbIRNtGa5f/qW50D1mlHndrkd/EpFmGGGgAS3zIc/HchNdh6hUueAKllLINKcXboM2txjrHP+7b8iP9dkm+9UDUIPqEvMvHOpfUITWu/dUsXNO0De77nGETYGg8FgRAEbbCMBxR0PNTvlSuuobwRTaRtOVAgVKdEAkDnTVmyamusUG4A4mDfCLCVKs4XUcacBAPQ5R9dxo65ZFKMoLCID2JEPAOn3fbyOW1Jph95rCpXomdbcwqYbfxbdOSCZ5kqRtfS7znd/b7nn1XpZcyKTAkOsqoMf8R6lcEsd93cAAH3esfWyNsIz4pTKmuIREpXnWlfda0nNI3SMrIyuI1UbtbXhDvRubq1yWDgQNgbiCBuDwWAwIoANthFApJTIdPBWubPORLOUiB0PpdPUCDO7tOZxvoqN7FDvKOmagXC4Te6s4zbSrdad6+mzFgRyCzUmJdMOq7iJhhkb1jl6x/S6l5JqiEIbsmwr5E3NSHVG5BbBOVC5P8O5aYcokDVFNYkuSLJGjLBFSSUVjRwIGIQOSIwFifhcEz1vRQO9gZDnGkfYGAwGgxEBbLCNBKJE2ETKqkixScj4kBlk7DcAGiDOUnLmdgFKIzIutxhrlkQjCO/1/GY20euK1DaCcEGQtdBobgIRNvdaAYOJSTPi0mnAXl+q8SHluPDhRjc8komwOXPY/GWN2LBIcqh32TBQNMR1pgBc4zSOI0o61Zs0V0/8XBPVmWoB72EwGAwGQwQ22EYAZlFxREbg8SV7ySMW51MMjzBPdGj9jmQzCCmjKMaaRWlSUWkiI/LgOwphHEVVLrJAVqIFe0o1JiNH2AjRmKDBxOTUYEnjI66R60Ry8qWyuKlOlG6ptqw1U7j5GBJJOXu8exDXOZCYI0pkgDuGZBTnAEfYGAwGgxEBkQZn12LHjh1Yu3YttmzZgjfffBNNTU244oor0NbWhjvvvBNTp07FqaeeipQoSnQwIU9T8MuGgZIR3GLagVtToSIiQ1VsJDzRQV5l6hBoLZODCbXpmiJF1VmzQtmAYZrQAwctNz7CllSzBaoSLZK1xGrYSLJGTFOjcBseJBuTThQlagqdw8uENSA8GySzCdQkAqrSqaM5e8jcfAwjUv1rDG5RDUnve33b+nMNG4PBYDAiILbBdvPNN+MrX/kK9u3bh/Hjx6OtrQ09PT1YtGgRzjnnHHz3u9/Fn/70J5xxxhn4zW9+g3HjxqngPbZBLYD3/IcvrpFR5yVPRLEJSomUnSmmMiJDUFQBSyFvzvjfJrJGEZUbJeqheqh3VXe8mNHcRnckBcIjbDLGhynDjWBMUoxch1uQwRarJrFRKa6S92dK05AOaOxB5UZ+dpCbjoRHmd102YAIm9BJxhE2BoPBYERArJTI++67D9dccw0+/elP480338TevXuxdu1amKbppvf84Q9/wMMPP4wnn3wSt912mxLSYx3UlEiKJ9osldx29yq85ErTDovBqX0AvX4n6iyluIpqKDeP4UGeEWcrv6IukSOZdpjWg5XoalmLbkzGmfkXiCJNiVad5kpriBJcX+c10ISpwYpnnbkQ3KPSskZsiEJ6dpTLQKkYyC2p2r9hUhOZGM4BjrAxGAwGIwJiGWxf//rXceaZZ+LGG2/E5MmTAcB3sO0ZZ5yB8847Dz//+c/jfNyBA8kW00JPtFdJEnrJG99qPSwlslLDRkzvS6CGzU8ZTOuamwZJagOvcEYc4IkWxYliSXYVlFLuvdf3fiS1SUUCETZqmhol/RagOwdIERkBN13T3MHewoYozpqVSpbhTICcrMWIzjvvTaJhEWKm30oaulIdScOajvg8O3gOG4PBYDCiIJbBtmHDBpxyyimkcxcsWIBt27bF+bgDBrKRBUrLcAC+HnzZYcZqW62L64qoNWzSjSBk6ut8lEFN02jr5l3vJDoeKlBUlUaxvNfy63iY0KBlqU6MKmrYAGnjgxSRidIGvpYXIG+ER7xHRzLFteo7jjJusZqOcISNwWAwGBEQy2Dr7u5GR0cH6dxx48Zh9+7dcT7uwAFV4aLUxziKZSpltSWvwUgOMzaJEbbQocERFfyoaYdV3IQpkfIz4vIyNU8Kun6qjCy4Uad0Op6sjUCEze3GSKz9G5EmFVTnQALdNUURU9UprqR7QNFzLZH0W/J++jQd4Qgbg8FgMCIgdlt/XVQ07oFfquRBC4Wpfcq642WSSGsK4SY9U0y9ohpqTCY0Iy5qExly2mGic/VCFNWwJhWyHUlloh4xZU02/dY1PmK0gafUimnpNGAbLhRjckRmnalMv1UwV6+Km+Qg9Fj1kiJHFEfYGAwGgxEBsQy2dDqNYrFIOrdUKnFbfxvUobxuy3DBzC5V86ec95e3vwajrzuUm0yELaxLZFgNG5Lwkoela5LndlkGm/H6FjluCQ9CT2SuXoiRS25S4chazxZlskbuSBrCzbTHaJhv9ITy8l5P2NZfUX2djKFLbZ2vZA5bAum3osif973U55rsIHRRdD7U2SO6DwKMPAaDwWAwRIhlsM2aNQuvv/466dy+vj7MnDkzzscdMDD371WnqCqKsJX/9jQAwHjyIQwsmYnC6lVibkrmsBGjRXakwNzZKz7P4dagJhWF1auAwf0AgKFLzwhdM8M0UShT2oYH1zx5FVXKoGVzfz9N1ho46ywZWaPVS4o6MRZWr4Lx9BrrvG/+YygvIH6DG+97Q9M10xkAQHn7FjIvQBzNVSFrrnNg3x655xohZTl2TaJtIBkKHVFhkeacwBHFc9gYDAaDEQWxDLajjjoKv/nNb1AK6VpmmibuvfdeHH300XE+7sDB3l3KjaI4hofR143SfT/zHDCQv/4yoYIzVFSo4AsU1cLqVSg/eq/1+39+UbkSHVUhNPq6kb9+ueeC4WtWKHuVaMKg5ZCRAwVBdKH0h99av+zdSZO1Bhm5SckaeQ5bgKzV76cZyst7Pcq6BUfBwx0XhdWrgH6rBnj4U+8m76doTIOXm38Nm/WdDNNEyQg22Er2/Yndb44qWQOA8ot/AQAYf1mjjFtlXEmEaC7XsDEYDAYjAmIZbF/60pfwyiuv4J3vfCd+9atf4a9//Su2bNkCANi+fTtefPFFPPDAAzj33HPxwgsv4Etf+pIKzgcGCIqqEw0Qpuc4hkdIrYfIe29s3QjUetCNMoxtmwLfoyQlMiSFLrISLeMlD025CuC2daMb+ascpK2ZiJs1fyp4rp5XFkTrVvjeCs+BcFlTaeSOhKyJ5okBBFmLsJ8A7R6l1v6pdA54Dbbu/gHfc0zDEM86I8wjNPq6UVjpea5LyJow8qegJtHo60bp3p9IcXtz0JLxoijVkugc8G3rzxE2BoPBYERALIPtmGOOwf3334+9e/fi/PPPx/HHH4/TTjsNAHDppZdi4cKFOOecc7B582bcd999OOaYY5SQPmBAVFSHSqVApSu0Ox7Be6/PmAvUNoXRU9Cnzwl8z66hfOh1qWlNQWlqUZXogaJl8OwdLgSeE2bohq2bPmMuUBu5CFkz77X69g/5n1QQzzrLeuoZhcaHGc2Y3F8oBstaWCoYQYlOStbMkBo2UZqay0tyP72caIZutPq6KPfBT1/YbF/TwMxb78KqZzbUn+SddebX4IZisEWRNduQ2ZcXyJqCmkRZ58CqZzbge0+/DAD4wbMb/NcMIAxpFzw7OMLGYDAYjAiI3SXyrLPOwnPPPYddu3bh6aefxsMPP4xHHnkEjzzyCJ566ins3LkT69atw+LFi1XwPbAQohA+sNmqD3yub3eg0kWtjxEq0R1dyFxwZRWv3HUroXd0+Z6/6pkN+M3GbQCAL/3x2WDFJmzAbAi3KEr0qmc2uF7yc+78fTC3mClXekcXctfdXjmg6cI1A4AfP/+K+/us234VoER7Gjf4KISapoVzi7BuD2/ZDgB4/PUdBFmLrkQnJ2vxUlzd/XSMSU0L3U/AMnABoD8f7ByI2+BGdj+7+wfwpT8+6/5tmCYuu3dtvXHklTUfbt6h3kFR0yiytuY1qxb1T9v64j/XBNFcGedAd/8Alt+7Fo55ZwL+awZ6MyWew8ZgMBgMVYhtsDmYMGEC3vrWt+L00093f4477jhMnDhR1UccWAhRVLv7B/DD5yqe4GClK3gANECv9Uif/gHrOlNnofXeLcguXRbIa/m9a92/xYpNvMiCrBJdy80wg7mpaKCRXboM+lHHAwBy//e7gWvmcLv2kac93Pz3M2z+FBA+H0vv6ELu87d5DoTL2s/Wbw7lRk0FGwlZIxvgAgU/u3QZMud9yuJ47jLhfgKWMbnV5vKhux4JNCapHQ9VOQc27upHbclZ2TSxaVe/Py9dd0cG1CIsaqp3dCF3zbc9B8Jl7ZcvbnH/jiprYc4eh1vmwqtI3Kw1q140vzWr4hbBAOc5bAwGg8GIAmUGG0MOLXc+I1QIN+7qR22Zv68CQZxXFD4by35/OiOMKkgpNmG1OymiEv2xz1nU3vN/QteMyo3apCK0bXhrm/3vOOF5VCU6zJD0chMpq5nzLnN/b/7vv6qVtbjdDhOQtbD6OtfIDRs5MOkw619nvl4A5JwDIfVYVOfAW08BAOSuuUW4n3MntdU92FOahjmT2mp4VfYzaE4mSdY+VKmva/n5s42RNfvZMSBK4QWQPuNcAIDWOV3oHJg7qQ16zRr4rhngqZfkCBuDwWAwGgM22EYIWvsk4etzJ7WhVoXyUyCoc9jCFBtXmQyZ2yWl2BBTh3r2DQq56ZM77A/yjwJUc6s+Fq50iddt/Ru7hdyoA6qp3ML2E7AaSQDAa3v3B56j6brbBl5XLWshRtFgUVBziZGVtddDZI06QF7OcRFSX2fL2os79ojXrbXd+rdF7BzoamvFFce/xf07pWlYueRkdLW1Vp0XltoH0GQN6bSbFqlNOETIjSxrIZkD//PSawAsh0pgjZ73/XpK6BzoamvF7UtOdrnpgO+aAZT7wJG1gfr9TGdQtwAMBoPBYIRArAHb+N3vfofu7vAZNmHo6urCu9/97tjXOSAQohB2tbXiA/Nm4NcbtgIIVrrCPNG1is3tS07GskXz6k90lLaQAbOOYvMP9zwGANA1gWITEvV4rLsPAPBkz44QbjQFv6utFd9+94m44oEnAAjWDOGG0RZbQb39mQ34wbMbA7k5TUvCBvN2tbXin048Gjc9vl7MLcSQXPXMBry+z2pYcu4vH8btS07xXzPAMiZLRZKsnT17Ku7f3EPjFrBmd/1tCwAr2jRSsha0bo91vwEA+Mv2nUJulUHLNGPSa7QFGZNh98HmPfsAAKue3Yj/99ymcG6EAdVnzOzEt5/6G446ZALuv/BdvmsWVve36pkN2G43x/nALx4KlDVN06w9HR4i3aNnHT4FD75q1UxGea519w/gmof/4v7tpFWefcS0+usQnx0AsGzRPPxk/Wasea0XNy8+Pvi+ComwPfH6mwCAx7rfrJM1d61AG+TNYDAYDAZANNg+/elPY/PmzXXHNU0TD+/1nAcAs2fPxsaNGyUpHpgIU/AB4KhDJ+DXG7biQ/Nn4JazTxQaHn5KtIxi49SZUXgtWzQPX3tsPTbu7sd/n3s6PnzU4f4nCjz43f0D+P4zFVkQKl3OdyNw+/CRh7sG2+Yr/h4z2gOiEYJU0u7+Afxpax+Nm/PdiuHczjp8Cm56fD2OmDgOay46x1+JFnTHC0rD8+UFSxE3B/aFGh8AMG9yO+7f3IOPHj0bX33n26QjC939A/jcg095uIlkjWYUARKyJjDAu/sHcPtfKxEYkoJPMHK/e85JuMzeD5FzQFRf190/gD/YTThCuWXosuakpR7W2uTPicBLRtaQbQKGh0jG5JyJbXjw1e34xMIjcP2Zx4mfaz73gSi9uE7WXANczkCaOr4l8DVRZLK7fwD/9VzIcy3bBDbYGAwGgyEDUkrkpk2bYBhG3Y9pmrjtttt8X3N+nnnmGZx88slYunQpXnrppaS/z9gBQVl1aiDmTGoLVroE84rIdVOAlCcaAAy7EiWQF8SRBXItC7xRrHBujqKa0fVAY800TaGyKsMNElEPp1bvkJZgJTpszchpeB5uFEPXWbd5IlkTpPbJyRotwuaAImuiiIyUrDn7STCKPnr0bPf3Fz91rm9ExjRNoFhQwk1K1iizzhTKGjXNFajI2oJD2kNlzY+bVKqs5HONNsMx3nNNywWnoDIYDAaD4YfEa9iOPfZY/PrXv8a9996LH/zgB0l/3NiBhNIlVB4Enmg5xaaiRFOipnlXIRSIkMATTW6MAJDrxMi8ipUW7EEKIaXOBvDMcaNEPShDlgWGpNR+Am5EhmLoyslaXCVaTtZkhrT7RdikZM3hRpE1T0Oa2RPH+58UMusskqxRDHBb1qIOj5eWNal71L4PKLLmw81JlfXyCoxuevZTlazFfq5luPEIg8FgMOTQkKYjkydPxpIlS/Czn/2sER83JiATLRIp+CIvuYxiU/X+omCmlA0nWhRVselqa8XnT1koxY1keFB4eZXKAIXw3PkzSNxkFFWZIct+RlHtfopqugCP8aJIiXZlLaYSLStr7n0gdA4Ep7jKyJpMRMbZz5SmIV07i6yWFxAoax9aMJPITT4lMpcKXjM3UhewZlKy5t6j4dwo92hY3d+yRfPQmrEy+h+56OzAejNXVk3TqucMQV6CW9Bz7R9POtr9228/RQ2FGAwGg8HwQ8O6RC5YsAAvvvhioz5u9EN1hC1ACfAqNmsEik2V8iHhwY9qTALA+UfOAgBMbs5hy5XniZtnqOTlVXgD2re/Y7rVmXLxrClCbtSmI4DcfgYpdcsWzcPiWVMAADee+bbgNQOkjA+Kgi+KsDnc2nNWZ8oHP/ruxspayH3wYVvWJjVlxfvpGB6qDHDnOprmdu2sxWkzLFk7c2anmJtESqQT/RNGcwUGOGDt5ztndQIAvvbOt4fImhP9k4iCC7mJG9wAQHPGev+kZkGKoVdWZVJJRfdByJiGv3+LZYB3tDb576egKyeDwWAwGH5omMF26KGHYvfu3Y36uFEPSo0MSSEM6SoIVBSbiSLFxmO4KDM+iK3WTYTUJ2UklEFCVNJr5AbNn3KiOROas2JuEaIewjUj7Kezjy0Zcc8gGQVfStaESrTFaUKTYI6ZRx6UpWuGOAfIspajG7kyvISyZstqe1OIrEmk31Jq2MIMcACY2ESTNUgYuqToH2UeYchQb+v9Scga7bmmaZr/fnJKJIPBYDAkEctg03Ud5bAhuTaClJWDFooUGzciI/DaUhQbTdcrRluIYmOYJooGPcIWNvw2dJixYsMjbNi4l5tQGQTIXQW916JEioT7SRhmXMWNZEzS6+sosiYaOK5pmkfWxNyoshYWkckReAFwlXCK06KSqklR7gWGB3U/I9RyUgxwUYoelZum2tBVdB9U2uiDFM2VSVuOOqSdUyIZDAaDIYtYBtv06dOxfft20rlvvPEGpk+fHufjDiyo9uCrUAiJik3BY6RTmo4EKV05WcNDJsIm4EUZTk1WVB0FX1HEVGY/82HOEokGGqq4OeseZoRTjQ/vdUhKdIAR7t1PUfMJmW6H7po1yAB3028V1bBBUMPmoGLoUu9RCedAbFlzHD40I1zdfUCLsAXuJ6dEMhgMBkMSsQy2BQsW4OGHHyad++CDD2L+/PlxPu6AguoaGZHxQVVsqO3zh4lKdNiAWee9ZdNEyRBEZGRqdyidGEdIGSQ1NAipxQIqSni4Mek0gpAxdCnGh4ibWuMjT3UOhKybs+aGaaJUO3/AC8VNZKSM3DCjSCbCRoiYmoVwWZN2XCiqYZNyqoSsG/U+ME3TXbegPa0e0xDgiPJEc/2cAyLjncFgMBgMP8Qy2K699lo8+eSTuOSSS7B+/Xr09/dXzWDr7+/H888/j09+8pN46qmn8C//8i+qeI99kJRoSmtuiQgbVSEM8ZJ7jZhMQHc8s1wGSiUA4XVFQFgdCj21T5WRS14zRxmUqSsSNjQIN4qSSKGT4UZR8Kmph2Gy5v2OgbJmGMJZZ15eFjdBCl0kI7cx0VxEaHBDqWFTImsRUoNjP9eIKdXUCH3JMN3Zc4HGZNWYhojOAa5hYzAYDIYkQirJxTjttNPwX//1X7j22mvxox/9yPcc0zRx2GGHYdWqVfi7v/u7OB93QEFK6RJ6ycMbQdDrseSU6FxKD65N9F4j0BNdUXTzpTLGZf276NXOUhLVQ5JSwQiNPahrpimuj1FZ8yRlfEjMOhNGiyRT6MK4eeeJBe67d65eUA1bjXMgUNYkOpKS9lOlrEnUiVH2E4QmMuT021wEQ1fYdCScGzmlmhihJ2UOEJ5rtY6oTO339AzONvpeB2YLum8yGAwGg4GYBhsAXHzxxfjIRz6Cl19+GVu2bMHevXvd19rb2zFr1izMnz8fzc3NcT/qwILq7niiBhppmidayzbBBEGJJs1g81wjQFlN6TrSuoaSYYobB9TOUgpoxQ/IdseLv2aqIwuiWWcOyA00ZMYhyLSBF6ybE22iGLomgRvJAK+SNX9uuqYho+soGoaYm3MflYowy2VogvWg1LBRZE06/VamIQphDptwPyXTb6XSNRU91yjcKLLmvU4Qt6pnY8BzKFcTzR2PaueA2bPV/X3gQwuQW/F9ZJcuE3JjMBgMxsGN2AYbADQ3N+Otb30r3vrWt6q43MEBRZ3ewmp3AJnmHjSFkKJwuR5yXYeWDhazpnQK+wslWkokYH1fgcFGSSMN6/IG0NdMpumITCdGijFJTaFT3bmPFJFRZOiqmnXmXKNYMITcqgzlQh5obgk81xv9C+Qmk+KqqBYLkDPAlXawVNV8R0bWqM13iI6obEqHHpY5kM0FRnxFzgGjrxvlZx/1HDCR/8pypE85G3pHl/h7MBgMBuOgRcPmsDGqQZoJRGkEoVAhBLERBCmyQFAGydyqZimF1dfJzWGLxcvLTXHLcCUpkVKDltXImnT7/NCmIxKGh2DWGeCJ/gllzWuw0YxJUjRXRQ2b6vRbwhw26aYjEo4oyhw2saxJNt8hOgdI4yNCGocEdUs1tm6sP9k0UPjZLcLrMRgMBuPgBhtsIwXVLaYV1LBpxCYVeYKiahIVm0rjAOrcLqrSFU8ZlG62oHr+lJLIQgRuMQ1dcpdIyXpJUoQtzDlAmUeYTgP2eWHOAcfwE7b1d2adNbB5hvdawoYoEnPYwg1wGjfTNGmGkUpDl1j7p2IGWx23mntUnzEX8PEpFO/4BkrrnwJgReFKTz2C0vqnUHrqERh93VXnOq87x2v/ZljgdalgNKzFaOBAxVjiqhIHyvc+UL5HLWKnRBqCduy10AO6vB2MkJrbRYkuKKhhq6TQqagrEs9gcyDVOKBYCDcmSfV1dCM3vO5PftBy7DbwkgZ4WGTBNE0U3DTXcAVfzYw4mhJNcQ5UZI2mRIfWimVyQHmQzI0WxQqvYaO3zm9c+i1V1qgpriXDhNM3MW6zFno0Vy7CFmcGm4Mg54De0YXMBZ8Fnv929RtMA0MXnYjUSe9G+YnfA6bnO2kaMh/7R6Tf/WGUfv8LFO/4hvW6piF1oud8+7zsR6/yTa80+rqtCF/zOGBov2U8AnXH9I6uunNr/3XOq722zPudzw56T+1x6nloHle3Ts76mT2vAgBSx54i5Cn7/YK4et9ffu4xazunHi78jKA1k/3XuX7+RzejcMvn69bC79yg7yWSIco6lV98GoVvfx4wDEDXkbvudqRPOZskM1Ff95NvynuDZIcikyI5iLp2UdbBkbUgOffjWXrsAeSvX27tUYCcyMhe0NrXfu+w55SsPFTJmmJ5j/J9Kd+j9OKzgevhRSyD7YgjjsCWLVvI5x9++OHYtGlTnI88cKBKiSbNYSOmDhE7valqy+29Bq1xQD+hIYqqobzObCxD3JkyQhSL0vVTbfQvbBB6RTmkKPgUWVNl6Eo1HVHpHBgepKfQCYfH09MOnXmE6SDHVhRZU5VOTX12SM3VUzR6g5o5QE31pqQsCxxkgLiRTPYjnwH+77frjgMmyo8/4HPYRPGOm1G84+a641Xnu+d9HZmLqpWUKiXUC02zmjl5/q4yAoNANSJFcD476D0+BinpPOL6pU46O/g9st9P05A64Z0oP/mw+52q3v/jrwMwaZ+hCpoG/a2nwXjmD6FrUflev6uTByHHKHJgGMh/+VLkNY0mM7Fe11C37jLXrl2vMJnUNKROfBfKTzxYMfguuRYoFoRrV/zdz1H6yTcI98Ni+9o+38l53+O/q/rOvnLu+xmetQqSExnUPlt8vnetIUO6D2SeMaHyTnSO0b4whLIm+B5DYU5kG7EMtpUrV+L1118PfL1UKuFPf/oT7rzzTixfvhzvf//743zcgQViATzQwDls5AgbZSgvLcImO++MnNZEGcpLaOwBWHvRFNQ4RSLqIWfoKmg6Qmy2QGlnbpomKZorG/VQkqZGUO6916A09zAbyK1K1kplpLNBBluEaG6j0g6JA+SrOjFSjHAFXSKp0T+Z6DxZ1ny46R3ThO+NDwllq1ahqjUCBe8jGZGUzw56j49BSjqPCOF7ZL+faaL8xEPh76d8hiqYZrWxFnKulLMg7PXQPTHD9596LeHrIQq0rOyEyaRp2gZT5e/iqn8PvJa0jD3+ezo3G/R7RsLYoMDPWLOPx5L7iPc76RqxuEmuX4TvEctgW7x4ceg5y5Ytw/ve9z4sW7YM11xzTZyPk8KePXvw7//+77jvvvuwY8cOS+EEMGnSJJx++un4t3/7N3R0dAiv8fTTT+NLX/oS1q9fj8HBQQBAKpXCtGnTsHz5cnzyk59ESqQQCaBiJpBZKgG2kiFUCGXnsCnwRJMjbNT6HTf6R2w6osjIBazvG2SwqZ7DZirsjkftKui9TjZIiS6VrBQDKBoCTY6wqel2CMjLWmh9nbIU18qaD5fKaA2YERdlDpsw+qcwxZUsazavtK4hFTQInfhcc9YtnJsja/HrX12ZCIuwUecRapJeWQaDwWAclGhIUdl5552H2bNn46abbmrEx6FcLuOss85Ca2sr1qxZg56eHvT29qK3txdr167FggULcOqpp7pGmB+efvppnH/++fjUpz6Fv/3tb+77t23bhjvuuAO//e1v8fnPfz46SeLAYADIBKVIeQ0rQov6sNodas2TTF2RqjQ1jejBl5k/JTKKvGsuXDeZRhAS6X0quuOB2ESGNgjdcw0CN6oSraKtP2XYOCAhaxmagu/IBSnSLJA1Zx5hKDdPBNwM8l463ChRcIVz2KiyJmWAA2pGDqgcIUGYkyjDLfeF2wCNa7sZDAaDIUbD/qc488wzcf/99zfks1avXo1Zs2ZhxYoVmDx5cpUS2t7ejquuugpLlizBypUrA6+xYsUK3HLLLViyZAlyuYpCo+s65s+fj5/+9Kf45S9/ib6+vkgcZQrgA5Vo7zVUzu0i1qGIOzHaimqIJ1p1N0apYeMCZVDTNBI3V9k1DCsyEJebwjQ1eoSNMFePKGv0IdC0uiK5cQOKZE3S0CVF2BTcB66RYBhWxJPATVWkuZH3J1XWyE1klNbmEpuOENct+4FPoPW+15D5+D8Buv25mo7Mx/8JzXc8WX3cgaYjdfLZVeenTj6bDb9a1K7TQQ/NjugyQnFQy44GHBANAg+U71GBksHZFHR2dgrr3VRi3bp1OPPMM4XnLF68GHfffXfka7S2tuJtb3sbXn755dDUSl+EpR0S0q1cBSSdhibwWEunqalUVBXWFVG40Tz44V0iHW7DpTJ5RhwKw0B6XOCpJGWV0gZeup05LcVVuGaOvGay0AQPQeUpkZQ0NYKR6+VG7WCpRMEncsulUtiPkrj2z2v0FfNAJnhIOKUeSyb9lu4ciG+Au7KWzgifaznJZ4cSA7xITYmkRZoBq3Nk09X/geyFV8HYtgn69Dlup7L00ce7x9HUCgwPuK8bfd1V5xt93Sj87BYUf/JNwPD5XE1H5qLPAZkciv/vRruLmnUs/S67yN55r+c4hgfcz0ZTa/V5nmunTrKbLQjeX3r8warPDnpPLRfqed7PrF0nNLXC7NmC0pMPo7T6+4E8Zb+fkKvn/ekPXYr0CWdBmzor8DOC1lz2X791yV54FQBUyVLQuXXfy4cjaZ2g2b0YTEBPIf3ej6F0z09C9zWMmxR3TUfmki8gfdK7SN87SHbCZDLwe0ddO4l7s/b19IcuBaD5yrnwe+gp5K5baXXwrJETyr+19zfp3gp4ToU+e2rOq/pswfeIKu/ke81H1sLekzrhTGDdQ8FrYqNhBltzczOGh8PTxlSgu7sbxxxzjPCcqVOnYuvWrYGv7927F+PGBSvflGsIQUw7jDv4FvDU7lAVG4VNR0JTIh3Fhmp8hEVkKPOnnIgMMeoh5Oa9RiEPtATLDKmDpVQNG6E9PdCw9vQAvXZHUxmRIc7GIg9aJhq6lUhzfG4kw8g7QD4/DE0kaxRDl+AcyFFljdjgRsoAj9g6vw7UZ4f9HZU2uAnj5oHe0eXb7pp6vNbwq1UUvIZg9vxPCY1D7/FayBiRde99+xl1n+33Hj8u1POE63T08ci8+3wYl/5L4Htkv5+Iq9/ah32GCojWRfR9qc4CmXUCUL02n7k+dF8p34PKPVAWJWWHIpN+3zvO2lG/T9DrfnJOvbeiyKLf/R3EM8igoT576u6pgM9WJe+B35n43BS9x2xuA1a1h78v9AxF2LFjB6ZOndqQzyqXy6HNQNLpNEohaUVhCLtGPp9HPl9REvr7+93fVRTAU1rAA/S2/rJNRyjtzJUoqh5uSqJ/5KhH+Lq5g5bLZZiFvN9M3HpuBAWf0olR1Rw2WoqrnFEUHsVS15GUWsMmnRqssr5OgYKvpVJAOm2lQwruUdM0lc1hkzWKVNyfZFkjzpfUJJ8dtEgz1XGhsE07EUEGHuUcynvjvt/P0KQapHE4y7xHhfEcdQ9UQeb6UddWZj1Er0X5jLjcqeeIzqf8rYp3lHVQKa9UxN3PONdvxPMrzucGvsdjGwjfI0ssKh5//HHMmTOnUR83KnDjjTeivb3d/Zk+fXrlRZVph4rqKWSbjjSy1oMakaFF/4iRSYX1O6ZpShmT1E6MwuYTKuv+JNMOVdXXJXEfhCnRKucRkud2UbsKEkZvVM3Vo0SaVcxhU3h/qpa1ROrrEoiwMRgMBoMRhMQNtv379+MrX/kKHnzwQXz2s59N+uN88fLLL2P27NnYsGFD5Gt89atfxQc+8AGp91x77bXYu3ev+7Nt2zb3NWojCKVKNFUZJKYOkVLBqM0WwriRu9ARamRUpzUR6rGKRkWJJs06I44cKAiMD3qEjdB0hGjk0puOUCNshBRX4n5SI5NUBZ80t0uxrFH2lDzDUSL91rCHegdCNo2UYEiSHSrUmkSFEVNlzZQYDAaDwSAgVkrk6aefjldffTXw9f3792Pv3r3IZrP44he/iKVLl8b5uMiYP38+Nm/eHOsaX/jCF6Tfk8vlqjpMVkFBIwjZ+hhVSrTKVDA3shA2ckA2IqNibhc1IpPJWZOUBIZu1cDgIGVVctaZxa0cbGgROzHS1ow2MJgcKZKVNYX7SU7vI9+jhAHQqtM1BXvqvZeyAetmGgZQKoZy88rWcKmMcQFDvamjEEj7STbAafWv1Pl1pLl6RWJtbppYm8tgMBgMBgGxDLaLL75Y2HSjra0Ns2bNwoknntiw+jWAVp9WKpWQDhiGTEWsaxSGYZpmYMt+qTS10Loi1W3gCbUexAGz8mlNKpqOyBkfKtrAVxlsQetGnKuXrRm03Ba0xJ5ZZyJZkxo2rmg/6YOW6SMHqFGs0IYoCmvYqLJG7mBJkDXnGhldhx44V68ia5Q5bIBjsAV0pqRGwAn7qbwmUfLZIawxlY2YErpEMhgMBoMRhlgWyyc/+UlVPJSiq6sLvb29wnN6enowY8aMwNcnTJiA/fv3CztFhl1DCGeWUkBrbqkW8IpT+9QYRUmlHSpoHKDc+LAibKKIDGU4NXX+lKZpyKV05MsGbW6XaVrRlEzW9zyZYePkqIeypiMSjSAUdYkEMSJDSlsm17ARO1ja0VyTEM0l8QKE65bSdWR0HUVDLGvuNUpFmOVyYDt+ucwBRTWJss8OJW39iVkNDAaDwWAQ0LAukY3EwoUL8ZOf/ARXXHFF4DkPPfQQFi5cKLzGQw89hA9+8IO+rw8MDODpp5/G/PnzoxMtDAcabCRFldr+WnWtByV1SHXTEXING701dyObGpBa+rtz9TLCWWcOtzCDrUoRzw8HGmxyjT3U1LApbToiex9Qo38KugoqlzWJCBul7g+6bnWeDOFWLBjC9L4qQ76QB5pbhNyUyJrCCLj3Oo2UNQDo7h/Axl39GJdJY3+xVPfv3Elt6GprDTzPeT3serXnRUHttcOu6Zyv8rODvi+Fy2Pb3gAAnDL9MN9zVXxG0Hlhaye7VrXnU94fdg51f5NY86gyRdkzAL7viXqPhXEZl0nj1T37q7533P2Nul5hPKM8a8KuJyODUWVSdB1nv4OeqWHfV+aeou6XimdgLINtcHAQLS3+/zGrOD8qzj33XHz1q1/FihUr8NnPfhaTJk1yoxr9/f340Y9+hHvuuQfPPfdc4DW+/OUv40Mf+hDS6TQWL17s1qIZhoHNmzfjn//5n3HeeedFG5ptw8wPQ2sd7/uaUiXa9fbS2l+HzzpT14mRHpGRawRBMYzCW9Srq8dS2YkRsL9fviiOLnjndhWGoaHN/2MpTWRUN7iRjrDFHzlAnl9HnNslc48q4+bWioXXsFGjkkERXwe5tI59hZA99X6/YrjBpnIQOtWhEuocoAwbJ8yuk+H2o+c24spHnoMh6PaqAXj34VPx+y09MHxO0wD844lH4cNHzsIv/rYF33jihdDzHGXy8AnjhAqN91+/a3uvKTpf5WcHfd8wLl9//AV4l+Wfas71XkvXNNy+5GScfcQ03PLki+TP8Hv/xl39eOjVHtz453Xw3t1RvkfQenjlw+/9r+7Zj4e3bMf3n90QeA51f0XfM86aR5GpoO9de10NgCm4lzQA7zp8Kn7/ag/87sSwdQi7R88O2Z8o8i7i5r3HZHjKvi5az2tPWYjFs6fGktug7xvGwdnvMIj4i7jVGnTe+9s596oTj8QDr7yO5feuhWGawn3v27WbwDamwdbV1YXbbrsNF154Yei5d9xxB66++mrs2LEjzkeSkEql8OCDD+KGG27A6aefjp07d7rtzydMmIDTTz8djz76KFpbLWt3zZo1+Id/+Af89a9/RVubpdQuWrQI//M//4MVK1bgyiuvxODgIABA13VMmzYNl156KZYtWxaNYCYDGEVSkwrSEFfFs85UNh2hpjWRu+OpaFKhukW9o0RT9lNBExnvdYQpkZpm7WkhH9+YJCqq5EHoxEHLaufqSTb2aOjMP8lIs2DdpCJ/IfcnQJS1dNqK1hmG5YgK46ZkEDqxJpFcX0dvvqNqgPwVDzwBMyS90gTwwKs9wtdvfuIF3PzEC6HXoZwng5H47KBryX6G6FzDNHHpPY+515X9DOf9mgZfxVfl96iVD8r7Ve1b0DoFQaWsyHxvM+A93td/F+MeC7tHZfdH9rOp16M8S2ReF63nvz+2Dv/+2Dqpa0Xd91oOFFkMei+FmwbgzJmdeOS13rrP8p7rNRyF3294iMQ3lsG2Z88e7Nmzh3Tuhg0bXAOpEWhvb8dNN92Em266KfTcM844A5s2bao7vmjRIvzmN79RTy7bBAwXaWlNIk+0YyA0eDbWyDYdCeZmmqbb5l6YDqbYS05KU1McYZMywgt5EjfhIHRJwyO8rohmgJOajijeT+ocNsp9oFzWCE4VmbRDknNA5h4dHhSnBpcodX9yz7VC2YBhmsENViS7pZJSSWPs54+e21i5HlWzYDQccbfGxMGxvwfBV2QwqmACePg1cZ8M5zyVaNjg7DVr1mDu3LmN+rhRDUoRvNQQV2IUqxw2S0nlbCzJpiOhqWDZ8KhH1cBghRE26jBjUtMRguERpgxWcVNghCcyV09Vg5sEajnDo3/hBrjhcQ6MSH2dcD/VGeBebqENNCRmxFGif1Qj1+ImiP6pnMNWpGUOBKV6d/cP4DP3PyF8L4PBYDAYtZCOsBm2wu+kGBqG4R6rxeDgILZt24bbbrsNjz32GO6///4YVA8gEIwPlfUx3ihdvlRGOmCWknSamsLUIRWKqvcagcOpDQMoFqw/VHXuI6wbqVGLq6iGp6k5hh+1kQwlhU5Jal/NoOV0UPMUlU1HJBuihK2ZG2ETzjqTlLVQbuq6a8rUmFIibOR1yzaR5xHS9pM26wyw1q05E/DfGfW51oBmSht39Qvfx2AwGAyGH6QMth/+8Ie45JJLqorUr7rqKlx11VXC902YMAG33XYb3vWud0VjeaCBMGSW1DKcOoetZvhta8AsJZVpakkNM6akkQLVs8qqeXnmT6nu3CdUoilGLm3NvNchD4GOG/WQbCIDiJ0DmsqmI9TZWNQ1IzhUvLIWGMmSkTUyN5kaNtFAb5rhIceNvm4qho1ndN2tERBy89yfpNmXCgzdoGeH08HMD999z0lYcEg7WjNpDBRLaLWL7r/5xIsomyZ0AJ876Sh8+C2zfF93QD0vCrzXplxTB/Cu2VPx4KvblXy237Won6EDuHTRPGga8P1nNvqe60hG7SvUzwh6v/c6XzhlIQqG4btvMmtVez7l/RqAdwvOoe5v2Pf0Xi9szePKVND39nL0e4/fZ8reO6LrbtmzHw+/tt393nH3N+p6hfGM8qwJul4upePGx9YF1m0GcRGti2ivvO+r3e9a/rX/Bn1f0WeEIajZiQarp4CouRQFUgbbOeecgx/+8IcwTROmaeKSSy7BRz/6UZx11lm+57e2tmLWrFlYsGCBcJ7ZwQZKEbzUvKIQZTCt60jrGkqGGdIGXq7piLhzn+KmI44xKYx6WIZkVjDrjDp/SoqbRNMRSn1M2H5KcXOiHnGbjlCHjROdA9SunzJpatT9JKdEEowiDZbhIOQlwY0azRV2iaR0OyQ6e+S4NdnzCMNr2FQMQtc0DU3pFIZKZWG6ZpVxVcgHRoml6uvITUeqeXW1teKYjol4vub8lKbhffOm17V9Pn7aobjqhCOxaVc/5vi0hfa+7igjlPO27NkPaMCs9nGBCo3fv95r+3120Pnd/QPKPtt7LdFxEfd/ecexvufOmdSGB155HZfdu7ZKkbvqhCPJn+H3fkdx9HII2rewzwg6X/R+Z81P7jpM+BnU/Q37nrJrHkemRHIBwPecoM+k3mNhXJz3nX/U4e73jru/MutVe4+JeEZ51oiu96m3LVCyf2Hf1+86tfstQtD3FX1GmGHrcLjlyRfdc1KahpV2J9WgdXlj12687wYhXQCSBltHRwc+/vGPu39fcsklOOmkk/CJT3xC5jIMQhG8jBJNVbr2F0ohbeDt65SKMA0jcBYYqakBccAsuU6MkkYqo6gS509Z3Iht4BWluKqsYaOkg5GajhC5pXUdKU1D2TSF6+Ya8uWycNAyZX4dtZbT+X4q5rB59zN0ELqmhcoadX4daeafRARcxjkQKmsjcB/kbINNmK5ZOyMu4DuTBmcryBw4vH1clcHm/IcepGB0tbUKlY+w1/3OO37aoaHnUzASnx30mVQuYecuWzTPVa5qFT/KZ4jer/p7+J3v9/7aNY+yb7Wgfk+Vnyk6T7SelHPi3GOi16k8VX520D2m+nv6na96/2Tfp2JtRZ8RZtgCwH8sPt73nCBu/ePDM12AmF0iv/zlL2Px4sVxLnFQwo3IEFKHRIqNsXdn6HUc5FIp7EdJ3Jrbq/AW8kBTcwA3CSVaVat1kqJKaFDhGJKpDMw3XofW0RWfm2OUigxwmfoY0hw2veq6QSAZHxKGLrW+brBYEiv4tbIWMLeLFM0dsmbOmPv2CnmRZ8QRWueTUpYLlXsgbNaZ7Pw6SoSN1qhFXQ0bpS6RNlePFs0FiNG/dMYymk3TnkfY7nsa6T4gZg7kBEbukOfYvRcsxsKuTiklg5E8ZJVq1e8fKzhYvieD4QVF7pO4N2J1ibzuuuswb948VVwOHlCaVIQYH4XVq1D+/S8BAMUffhWF1auEH0lSbLxKSMyZYonNYYtZH1O85yf2L3kMLJkpXDelaWoSjSDM/f0w+rqFnylbw0aKyIi49e+y/s2HzwshGR9VaWrhRniQEl1YvQp4c7v1ef/fB8T7maJGsRR1/XSjuSll++mm98WMYjnpu+bgPnXcKLWclI6ke21ZI8ymocz9c+cRAvHXbciax2ns2yPkJboHvAbbaTPZWGMwGAxGOBrW1p/hQTY8wiZSHoy+buSvX145YJrIX3+ZUPEipR46nugQbnmKsjo8YHGlKjYK64qCFC6jrxuF767wHDCE60ZP11SjRJf/8geL1l//qMyYBCHCFhaRKaxehfIff2v9/r1/C3UOkJRoZ9Aygg0j05NW6cet/j4Q72eObIBLyJrA8Cjdf6f1y+B+8n6SU1xFtZwEx0X5qUcAAMazf1Yna4SB42H3gSVr/2v9vjJc1hJ5fgjuA+zqs8698r2R93OwWBJzZTAYDAajBuSUyBUrVuDPf/4zPvKRj+DSSy8FALz44ovo7e0lf1hnZyeOPPJIeZYHGKQUQj+DbetGoHaUglGGsW0T9IAUP0p6n+uJzg8HeslLhuF2ywlSCAurVwF7rHTN4U+/B+YXb0d26TLfc2tnxAW1ga8MMyZEsYIMtq0bAZO+bvR0TXrTEZExWXrwl54DlvGRPuVsX27U2Vhu1CMityDnQBAvgD48O2zQcskw3a5KKu4D5xpFw0DZMJAKahaiYBC60deNwve/4jkg3k+yMUmJNIfdB33dKP3u5xLcwg3wKm6kekk1siYToTf3Ba+baZrCPQ1yDgSumWAkSOjzhMFgMBiMGpANthtvvBGlUglvvvmma7CdddZZ6OvrI39YR0cHtm/fLs/yQEOOMEtJMPxWnzHXik54lVU9BX36nMDrSXmi88OBSnTY/Kmoio1z7cAZcRlCGmlIpEifMRfQ9GqjTbBusumalHbmgQr+1o1AbctXkTEpWfNEarXuI2tRnANSw7OHBwON8OrW+fXrJnsfVA1aLhtoCXIOSMz8C2rUIuscINewSdRLBt0HsrJGr68jOKIE0b84jiiSc0DArWgYbjtmFfeBt2FR7SgBjrAxGAwGQxZkg+273/0uHnvsMSxdutQ99tJLL2HPnj3kD5swYYIMtwMWWoauEPql5+gdXchddzvyX/4H+4I6ctetDFRqALl6LKs1d5ASXVFafL3kkooNuQ28xygKmqUUFvXQO7qQufCzKP70W/aBlHDdpFPBKG39hcakVq1Ii4yPBAaO+8paBOcAOSJjy1qQEu39bn4Kvt7Rhdznb0P+xk+7vET76V37fKmMltBBy9GbyETdT3rXT8LMP8XcyDP/InJL0hGl5ZqEz7XhEEeULDevrBXKRtVzbogjbAwGg8GQBLmGbdmyZVi1ahXe9773ucfa29sxc+ZM8k97u393roMOCgrgs0uXQTviKOucL/8wMOXQAbkeK8T4cHilNM03fdFVbKoOBis2zow477X9UDVLqVjwPYdSu5N62xnW9WYfidZ7twjXjbpmlKYjYfupd3Qhdfw7PQcUGZOE+jpRCp3jHKgcCHcOyEc9ApwD9ndL61pg+mLmPRe4v7f8eqNwP9O6Bl0Ll7Wq8RYBex9W76R3dCF9/qc9B0KMSdmRAzE6MeodXUid6OnuS5S10PRbQg2bqCYxiqxJP9dIzoEAbp+/1XOAtma11waAoRJH2BgMBoMhB246MhJwFfx4s5Q029urdU4P/UhRTUX1ieIambCGI3pHF3L/9C3PAbFiAxDnndXOUvKBzBwlfdJhQk6AxJpRRg4QWobr048AAKQ/eEmoMSlqG159YnwFP7t0GbSu2QCApq/+PNQ5QK39CzN0SR0FnffqOvRps8SfZw9aDuOmEWSNcn+m33aaRW3esWTnALVeUhxhC+emz5hrcXzfx8mypqIjadg9ml26DJp9HzTdeKcyWQurS/SOjwgawZB590fc31v+9xUht6w31bvGmBwqcoSNwWAwGHJomMHW09ODn/zkJ436uFENUmtuykygotM6X9G8Inja8IfUFYmiWOl3f9j9veWeV9UoXZms+2uQ8eEoqsLZWBLzp1Qq0aR5Yja31OELQo1Jal2RFhLF8nITrpv9OfqUGcLP816H3F0zJOpBG7KcC511Bng6WMYcOUDi5syuO6RT2X5Sun5SZM3hps+SkDUFA8cpjososhY3MkmZq+e+N51GaupM8edpmq/Dp2wYKIRFnhkMBoPBqEHDDLaf//zn+PSnPx1+4sEAQmtuGYUQhGHG0vVYChRV5JqQIkT/SFEPwiwl2lBeW4lWNZQXnkhRzLb+FeODwE2ygyVlCLQwMunIKmnQMq2GLczQrTRDESjREgY4QJS1dBqw1zew5ok0ZNmWNcqaEWfEaRJt/UnOHsp9kCIak6SZfwRjUuY+oDoHqBE2Rc4eLzevrHH9GoPBYDCioGEG21NPPYXDDz+8UR83qkFrzS2ukQE8Hl8ZhTDEuxvWPp+SpiajcAHqZimpNoqka7FUGeASxiS51TrFmBTJmhMtInDLERX8sKgHbUA73SgC1DkuKoZHg6O5pI6khHs0grMn3ABXE82VkzXJ2r+Q2lzK85Yqa27asuf5wemQDAaDwYgCUpfIH/zgB9i6dWukD8jn81i/fj3uv/9+fP/73490jQMOaTu9L0AZNE0ztG04gErKlcJoEbXpiIiXjMLl5Rba3CPXBHP/3uD6OpmaJ8k1C+pMCcBTkyiKelC4SURkiE0qSPV1ErV/rnwIQG1SERpho9wDEvsJSBjhuSZr5EBIREZogBflZa1oGDBM022OUgunsYdo5h9psH0CsqaF1OaGDUJ3IRHNlU5bjrOfkrLmFwXnlv4MBoPBiAKSwfbTn/4UW7ZsifQBTU1NOPzww3HnnXfi/PPPj3SNAw4hXnLvTCBlKXSKPPhhLcNleQEyA6rFkSyS4ZGnK6re71jbmtuLuIPQKx8SwZiMWfNEGYRumqZU9K9iFNGU6FhNR9z9DDckAbmaJ8rIAVKkiMCtduRAc9DIAUKETaaGLQlZEz3XHAQZ4dKyRmlY5OUWEjFVVf/qvZY3MskdIhkMBoMRBSSD7ZFHHkmax0GF0AJ4T2QiSIEwSyV3JpBMhC00ipVRqERLRtioXvLAqAeloYGnSQWVF2CtW6AhKNF0hFTzRIliUTsxOnsQYuQKuXnGKKiNyDQ2xdV7LXrHQ3F9nWqHisMt0GAjzPwjcUsgilVJpxbvp5BbqejOh6MYurL3QZxnh0z9K+DfXXOQUyIZDAaDEQHc1n8kEKLge/+DzwYZRl6liKDg01vU01IiR0KJDlPwKQ0NTIkIm7c1t3hGHCUlMqkaNmLaYUgaKSCITHq/l0LnALnpCGE/6dFcQpdIeB0XYuODJGuENaPOiCPVvyqOTDYRG6KEz9WrvD/wueb9XkpTImnOAVLdH+F5W8WtzBE2BoPBYMQDG2wjAGqzhWxKD6xlqVLYVHaJDJvDVg5XbKJ27ovb6U2qIQpBiQ5qzV0HiZRIVd3xqLOxqLIWNAi97r2e8QqB3MgdD2ncKM4B5dFcYldBVVEs74w48cgBQoRNpiZRoayFdYl0vldGFzzXCnLPNeo8wrBmSlIRcHK9ZH23VI6wMRgMBiMK2GAbCWRtpVdFal86A01koNggR7FCUq5ojSCiKTZ04yO+0qU0+ueJFJmm6XuK6u545LoiYk0irZ253KyzuPPrKAOg3fcqrmFDWNoyYW6XTCdGgLZubmS4VIIZsPcysqayhs2NSsYxciVlTbq+boTTb7npCIPBYDCigFTDFobXX38dTzzxBF599VXs3bvXPd7e3o7DDz8cJ554IqZNm6biow4MZKipfQo7llGL88MiCzKpfcrb+oe0WifM7XLWTSYiszdfFK5bVXplseCroKuOyKgyPOTq/hRHTDMhqcGKZ50B9CYVWkgNGyWFTpablHPA4dbcUncKJZXUkTWZ5juqImykrp/UNXOjufG6RKpOWfZeq6qtP6dEMhgMBiMCYhtsX/ziF3HzzTcjn89j0qRJGD9+vPvavn37sGvXLuRyOfzzP/8zvvzlL8f9uAMCWi6+J1qmQQVA78QY2nSkJNGeXnnTkZDGATLd8VSuW60S7WOwqW7WQlVUwwwPqbo/yWYLoSmRIU0qVM86A+hNKkzDipSab/T4vq56rp73WkJj0vs9C8MBBhshMikR/ctRZY3YTIlm5BLvT8kGN7FqEgt0I9e6FjcdYTAYDIYaxEqJ/NWvfoUbbrgB1157Lfbu3YsdO3bg1VdfdX927NiB/v5+XHvttbjhhhvwq1/9ShXvsQ0V6TkRlcHGNB2R9JJTo3+m9bq5Y7vvy5TW3IkYk566Lj9D1ztXjxTJojSR8SiqQWmY3muZA/0w+rrrXk5iEDp1cLYja0b35gBuFCVa/X1QWL0KxtNrLA7f/EcUVq+qO4fkVJGIYgE054CWTgN2qmD59Vd9z6EZH/Ton3T96/69vvs5Grp+Gtu3xucWQ9Y4wsZgMBiMKIhlsN16661YvHgx/vVf/7UqsubFuHHj8K//+q9YvHgxbr311jgfd8DA9fYO7o+vqCpPO7QVm+5XQ7gR6sQkhxmHKdHlP91j/f69Fb5KdBLGB2XdNF0H0hkAgOGjRJcME4ZtVAWOaZCcP+Vcx0T1fKu6z/7j/1q/9O/GwJKZdetGi+bKp5EC4RGZ8sZ11r9//N/I3CAb9QjhZvR1I3/98soB00T++svq7gXKfSBbw0Y1Jp2290MfO6FuzUzTlJspJiFrZdNESSRrf/qt9cvuHb77KdWwSPEg9PL6pwAAxjN/in4fOJFmyei8NzWYI2wMBoPBiIJYBtumTZtw0kknkc496aSTsGnTpjgfd8Cg6Cg2QwPRFdWoaWohUQ/j5WcBAOXH7hMrXaI6FInW+UC4okpVot3IgoCbtEJIWLfC6lXW/CgAQ584OXDNAHWzzmrndvnB6OtG4T//1XPAqFs3mSYy9DTS8Nb5Rl83yg//j5gbJbVPYq4eEN6kwti60Z1vWDlYhrGt+tk1EtGi+vugfs1Khgkn3hpkGJmG4cqr7Iw4kaFb+N6XPAfquVHuTyRQ92f0daP02x+RuCUeYeOmIwwGg8GIgFgGW09PDw477DDSuYcccgi2b/dPZTvYUFj5b5U/IisP0YrzQxWbB39J46aodT5AUFSJSjRtmLFcRCZs3ShKtPe9gcaHty6PsG5eZTyoVszYutFNI60crF43qSYyMQYG+3OrSeWs5UaQNekh7SH7qc+YC9SON9BT0KfPqTqkuusnEG7oUu4D73spc/UotWI5wjxCiqzJ3J8qU1wpsrZzyPrcgsihpaD5ziCnRDIYDAYjAmIZbOl0GsVikfZBATOeDkoYYuXBiSwMFkvo7h/wvYRscb4yxWbQUmxE9Ukyw6m93IIUVaoSvT9vKUP9wwKZHAFj0jvrrGffoO91TG/NIGHWmaZp7mDvOMaHY+wNFcsEWVNXk6jPmOvWYgVx2zlofa6wFk62vi5dPxurikJHF3LX3V7hpmnIXbcSekdX1Xn7C5aM7R0u1F4iMrcwWaPsZ5VzICilumrWWTi3lK4jrYuHesvImvC5JvnsoERzw2Rt1TMb8MPnrPv11qdewqpnNoi5xRhXwimRDAaDwYiCWFbUIYccgr6+PlVcDh7oYkX195utznR/7d2Fmbfe5a9ARPX2Cgw2imLz0/WbAQDfeuLFQMVG1igKmz9FUaJXPbMBG3f3AwD+z91/CFa6JLtrhq0bRVG94/lXAFg1QIH76YliUeZPebkFGTR6Rxdy136nilftuj2w+XUAwPNv7CZxo4DSVVDv6EJ66aWB3FY9swH//YJVD/iNx18QyFq0Bjcix0V26TJkzvsUACB97jJkly6ren3VMxuw+f9v78zjoyqv//+5s2chgSBkIRBkVRERKVZarUitWmi1WJda0dpiXdqvu62iti5fv1Vb/dFWrXWhrRat1oW6YW2LaK1rVVTcIIAISUhAAplkksx27++Pu8ydmbs8d5s7hPN+vXiR3Llz5+R5zr1zznPOc87uPgDAqSteNNA1d6NFyn2gHAgUzac85gEO2NY3oC2XPJ+BABBiKxTMJNsVqj3KBrr2XpeBrtlNcTXRtfCiSzVla4sncM7K15Q0UgHAuStf03YoXXDAKSWSIAiCsIMjh+3QQw/FO++845Ysew3Rn/wm90uBYdMWT+D+93PRGV4QtA0Iy2lqklNktBJd34yQZKgWymbFsPGiIEpk4WKEz7wcABA69jt5RrQsmwwvGBhdLo+bmRHdFk/gmpdy94jufFrcJwawjVv42+cqP1c8+N+icfvDu62mslkvZ24e9QCA0OFfF6874QBUrdysyGZH1yxHms2aQNeJqd5cQbTTkq5Zbb3BEJmMLFwMbuI0AEDs+j8VOZN/XrtRkUvXKVL1+7O6OGAkW/jEXGpw5cNrinRNjmKJ8unoms0ejmZFR0LzFoo/jGrK07XW7rhSEEgmKwjY0B0vuobV4jta7S0owkYQBEHYwZHDds4552DVqlX4+OOP3ZJnryDyze8pK8gVf3olz7Bp7Y6jsEi7lgFh1Yhm7T8VPuIb4nXHTbFt2FgtiMJawTIgGdEI5kcFLMlm1ZlkGLfIwsXgpswQz792WdF8FmbAas6nxTED2CJZHMcpzmmgpi7vNVZdczuNVJFNmgMuEs2LxNjRNavRv/Z4v25aHoCc41zQ889L2VjvUa6qRvyhKr8yb1s8gatfNF8cECxWrwSAkOTYfdbTpy9XKARIfwNXOzLvNau6xp52KH5eIpU2nE9F14LBPF2bXFeDQIHTGuQ4TKqrKb6ITWfys54+RTYq608QBEHYwZHD9qUvfQlnnnkmjjnmGDzwwANobW3Fpk2bNP/t2LEDAPDpp5/mHe/u7nblD9njiMhG9Ii8w5PralC45q1pQNhMHTLaPwJAMS65cNi+YWMzwtbZN2Asm07/OiuyWXWMstL+tC6d9DKZgGxEV1RryJZ/rvF8sjtsQenCWwyM6LxraoybJV2zGCmKJ42NaMWRSTqYT4v7615vF59Dr7Xv0I9AQb+pt5eyySXzuxLGusbpjBvr4oDVSozL1qxHZ0J8zzce+Zd+eirgnq4xyvbEJ58BECNsRvOpPCcLxqy5pgr3zJ+j/B7ggLvnz0FzTVXxNSw+c9/u+BwAsPqzTkW2fkqJJAiCIGzgyGHbb7/9cP/996O9vR1nnXUW9ttvP0yePFnz3w033ABBEDBp0iTl2KRJk3DAAQe49bfsUSgGoYYB8Y3JOUcpyHGaBoTVzfmPfbwZgEmqFAAuWiFeP2XfsLEq28tbxH2Qa7oM9uwBihGnNWZq2fTGDEBeOpgZy9asx8MfbQYA3Gq0jwoAYuK4FRqqzTVVuOTQaaayWXUkl61Zj83SPqqTH9ffR6W+ZmFT7+aaKpwwdZzrsj29fgsAYNdgynNds1JVkDUFFEBOPzR07W5WXbMgG/OePbVsms5k/qmaTpGFyJ+lFFAY69rxUxh0zULaYVs8gZ++8JZKNv35VHpfFowZACyeOQVfbNoHAHDnsYdh8cwpmp9nxQFviyewXNrvq5Ztt1GRGoIgCILQgW3HuQ6rV6/G9u3bHQnA2hZgyKFjdAHA/vsMx9OtbTh5//H4f1+bbbzay2jYXPqv/yq/y8bDsRPHFF9bvt5g8Sr/4plTcNfb6/B25078/utzdA0bq7Ld9fY6JtkUI05jzL43YxLOfvZVAMCas7+J6fV1RecImQwgpSSZGYR6+6g0xwwqgzBZPG7z9m3EbW98iCl1NVi16FjHjmSREW0imxIZ0xi3A0cNx9/WbcG3pozF7ccdZhJZYJPt2n+/m5PNSNd0nCJA1LU73/4Eazq7cc/8L5nrGkP0zygtT0/X8qp3SpwxfSJ+KOna2nNPwP77DC86R+D5XG89E9ks65rBYs+lX5yGW1//EACDU8Qwn0YpoFZ1bdqo4Xhy/RZ8e79x+PUxX9R+v4W0Q6OIou5zTUPXAChjP0ZLpkLZGJ5rerq2ixw2giAIwgaOHLb9998f+++/v1uy7FVw0RgEFK9EA7liDZNGDNM2agBLRrQlw8ZgJRrIGTa6csHaHhkrRnTOydUYM9W+nwkjhhW9DiDnFDHIZtlQNTAI5T1Joypj+uNmccysyKbomoFsk+pqdGWzUu3Qiq7lHA+daobSdVh0jSUiM7muBgGIDq6MblqvTgodkL/HbKKerql7nZnIZl3XtKO5ADBvfCNuff1DTB5RgxfO0FkcsJDaJ6eAquXTHTOA6T4w1jWPZJOfHZk0BJ4HV1DZlamvnoUIm5wCqp7VIGOBF4IgCIIohJqj+YVBhI3NeGBPHbKy70Zvf4wV2azskWFO40KuEqCWM2m5ObVJ1MPSnj3AcD6THhiDbsnGNJ8WUlytzKeRXMyyWVi4aK6pwuVzDsyTSzedkWHMOABhvf6SFnqdWZ1PTic1WC3bqCr9xQErlRgtpafCOPWQpRG6FV2zkgqd95w0WCRzq4F8c00VLjo0l+4vy5Yu7NlIEARBEAyQw+YXDCv4TMYDQyqYpT1eKkNVKGyiDW8Mm6u/PINNNobV+1CAQ0jHiFaMyFBIrGhnItc98+cohRI4mBiqOmlqatl0HUnA8pipZTMzolnGjc0pYtO1O487TPmddT61dI1p4cJiJcZv79cCAKivimHzBSfpplqyOEWxUFC3LL4SlWTodWZV12CQGmxpQYVxzBbPnIKjxjcAAH457wv66alq2ZzqmgXZKsPi9V4841h92dQOoN1xs5C2DAALpf2hzcMqFV2joiMEQRCEHchh8wmjlWi5b4+RgS/YMGyGx8SeUv88/Rh9Q1UunsHzyn4vNW6nDgHAd6btCwCoiYQNjWijdE25DxOTI8ko1+KZU3DdkQcDABZMbjYxVPXT1AYZnFyrY7Z45hR8fdIYAMANR840lE3RNY39WF7M57mHTFV+fnvxN02dIgC5/V4qmBYH0hbbW6iuZZRqqdxXWmPGIpfKyWXpdbZ45hTcMPdgAMDXJ40x1jWDvX+WFnssVCQdEROd9aqISRY9g66xPNdY5xMAKsOiTHUV+u/hQiGlwb3hokpQ/yvRavGdCkmuAMcpujZg0rKBIAiCILRw7LC98sorOPHEEzF58mRUVVUhGAzq/psyxcAI2dswWonOups6JCMbNrLjpokbK9FW+09J18oKgqERnSs6YtfxsGbcA0BjVSUAFKWsFclmEJFJsqSCWdgnJiMb0RUmERzDaK7LEVNA7P0mG74jKgx0TX09x86HxcbZZoaznH5rUy6rDaABC7qm03IAYFwcUJxc9j5s8nya99ZzqGs27oMoY/86x6nBFttbVEjXUjtpFGEjCIIg7OCo6MiqVavwta99DePHj8cpp5yC5uZmVFRU6J7f3Nys+5rXDAwM4Ne//jX++te/oqurC7y0l6CmpgazZ8/GDTfcgIkTJzJda/369Tj++OPx5JNPYurUqeZv0IBprwdLeo4FwybG0GhZbfgKyQFwBc15cyvRDNE/i1EPOaKii0EFOqb9MRb7KOXJZmYMKg54cQGNXGTBYH3ERh82qw2qjaK5RuNmdT5l2ZJZ3li2cATgOEAQIKQGwaE272WmqIfFiIzSbDxrvJeIc8m4t7I4EFV0zWSfE0uEjWGxxwtdY3KKjHTNQqq3ZdmiMWCw37ETzhxhUxw20UlLZ3lkCivyEARBEAQDjhy26667DgceeCDefPNNxGLsX/5+cNppp6GxsRHPPPMMmpqalDSlRCKBxx9/HEcddRRef/11NDU1GV7no48+woIFCzAwMICBAeMGt4YYRIuYilTIxoMFw0Z2GIwMG47jRIcmlXS8D4XVsJEN8gwvIMPzunvQSrlPTJGNYcwAGKZrWjIGbTiTTIYq4GA+2QvcqGXrSabNdS0aE1tIFMgmCIKn0dzBTBaCIOinKzKMmdGihR1dY3bAjSJsFlJcPZWtRM8OQO2Emy9cCKrPkBEEgS2l2uLChZwSOZAW5RrQSDEnCIIgCBYcpUR+8sknOPHEE8veWXvrrbfQ1taGO++8E2PGjMkz0qqqqnDmmWfi4osvxi233GJ4nXXr1uHrX/86fv/732O//fZzJpRRtChrISJjx+gyi2TprJJneB5ZqTiEnmEjCILlFXz1tYyjf86iHnb2x7COmVF1TWt7nqzLZhqZdKlKpCdRD53+dWmeV0qi6+oazwOZdN51WOUCgJRBlM1pBNxO+q3l+9MgmutW1U8Z1sikIpvN/ZKeRv90FsnUeqDnhOc912ykeqezvOK4EQRBEIRVHDlsO3fuxKhRo9ySxTPWrl2LuXPnIqBXghvA0UcfjbVr1xpeJxAI4KGHHsKxxx7rWCanK9F29sg4XSVXv09XtkxaaaDFHGFTXctQNpXBVVhV0NJeLCtj5sL+GKWIDEsqmAd7d3IRGXsFNAQbUQ+r6ZqF48aka+peZ4yRSfUiiKGjK1/P5n5JO+m3UZaUZcB5xNROOnWp9v55qWth7bYgTLqmKorD6uhWqK41kMko+9cqwgZzQxAEQRAaOEqJrKioQG9vr1uyeEZbWxsaGxsNz2lqasKWLVsMz5k8eTImT57sjlAMBj7LfixbqUNme2R0Kh6qDUndfUVqQ43RsAkFAggFOGR4wXAFv6iqoMoYZtofk7ae2se6r4iTxsxxKphf+4pcjv7JhVDspmvm9dXTm1MLvc60rjWYyaJGz59SN1rOZsEFixcVfFtQKeP0W+d7/6yVzgdyzyLTSDODrkX0nmtqx91ihE3+jH4pJbIiGISDZHqCIAhiL8SRwzZ16lR89NFHbsniGdlsFkEj5wdAKBRCxuU9BslkEslk7os+Ho/nXnS6H8uGYWMlwiZoyCa/LxwIIGjW6wywHF3I8Blj2dTXSw5qO2y+p1s5NFTLMerhZD8W476iQucjF5UM6Pc6k+Vi6HWmfJ5UwdKsIEpRo+WKSuVXr/ZilW5Poofptw5l83J/nd4+U7a+eqr3hA0qn6rgOA6xUBCDmSwG0lklJVLe20YQBEEQrDhKibz00kvx8MMP4+WXX3ZLHmaWL1+O4cOHG/5bvnx5yeVSc9NNN6G2tlb5N3bsWOW13Eq0wzQ1L4pU6OyRsVpmnaX/lCXZVIaSkdGli4Mqkaz7ioTB4rVzln5idvbXsUYWWKIehgU0nOzHshths9CDDZGYJV1ToqZG+7EM2lt4FSlidYocV5i1sXDBXtbfQDYLacueRP90dI2p35/N55q6UqSSEmn0OQRBEAShgaOlvkWLFiGbzeKrX/0qZs6ciX333ReVlZW657e0tODaa6918pF5n71o0SJb7+3p6cGsWbNw3333Ye7cua7Io8WSJUtw6aWXKr/H4/Gc0+Y0ImMn6sFYTS1XCELbiHa7PD3AZnQpVQWTg7aMrlwqmA0jmtUYNHSKDMbNYj8xtWyli8hYl8200IJJ1MOwybKNMZNli5tVsJQbLfM8hFQSahOdpU+inQUVVqeIqYcjSx82L6N/jvf+2Uj1Zi2IUiAb0/1p87lWEQ5h12AKA5ms0o+NImwEQRCEVRx9c+zYsQO//vWvkclksGXLFmSzWcM+bG6nHNqltrYWGzZs8PxzotEoolFtg01vAzyQcw7c7HUGsJeo13M+mPaJ2SgBD1iseJgcLKpCZ8kYtLTvz1pZf6cVLD3d82Szcp+j6ppmssWk54VO+i3TPk6riwNWCskM9tuLsJWg15lhhI2pD5sHiwMGzzW254eHuhYxLjriZg82RbZgbuFCjrBVksNGEARBWMTRN8dll12G1tZW/OMf/8DRRx/tlkyuw7I/LZPJIMS4D8YVfOqNpb6+LjqNeb1aIQcsVDyMRA3313kVYTPr2+W4/5QNgzDn5JoVkXGoaw6iuXZbSHgll/qaTNUYNRote70XK5nlmXTN6T4xW5Fms4bjOrJ51VcvTzabiypePtfkipADmUwuwmayn5ogCIIgCnG0h+3555/HD37wg7J21gCgubkZnZ2dhud0dHRg3LhxJZIIuqvkzL3O5Pd50BtLjnqUdCXaYcVDpr1YDsqZCxB7g+miU1kTyBm5LPvE7KSC2Y16ZHle+ZsMe53JJc29jP4NWt8vacfxAHJplk5bDjAtqNiYT8C4R5xrffU8aCGh38NRAM/yXLOha8zN7U3alXjxXKtQ6ZocYesvk0wTgiAIYs/BkcO2Y8cO98rce8j06dOxevVq8AYG96pVqzB9+vSSycTp7PVgKp2fyQDS3+JJREbH6JLf58VKtFs94rxKUwOMS/s77qvnZf8p3WILub+Hqf+Up3ue7DtFdiNsptE/nXvU631/6s/QQmkhYddhS3tbYVaUreC5phprpr56HlUkFT/HxnPNxpgBufYWA5ksVn26DQDwZsfnlq5BEARBEI4ctlAoZOgElQuzZs1CS0sLzj//fLS3t+c1Xe7v78fy5cuxdOlSXHHFFaUTyiTtEDAouGCj/xRgYZVcNrpsRD0cp6l5mEJnpxBERKP/lqFcyeIqkZYMfA8ipmZjZiibTV2TU8GYI2wOishYGTNAVXzHYaNltyMy6h5gTA3kHbZp8KTCrDwXBrrG9lyz03CcMTVYt+iI+881+T5oj/fjkY8+LXq9PZ6wdD2CIAhi78SRwzZhwgTTZtPlwkMPPYTx48djwYIFaGpqQkNDAxoaGjBjxgysXLkSq1evRlNTk3L+unXrMGHCBKxfv17zeiNGjDCsiGmG2Qb4UIBDSK/XWdKeYeO0+a2naWpWK+TZiXrYiLAFOE4xpJmM6FQyb0EAyDkfhkVknOzdMYss6EU9pL8nyDHoGscx9zoDLBT2cBRhs5emZjWFrlR7OeUecYDJnMrXTKfElNUSyGa1D5teBDwSDCBg1leP44BQ2LJsdhcHLD3XLC4OyCmRW+J9EDRe37ir19L1CIIgiL0TR1U2zjnnHPzmN7/BjTfeaFgdshyIxWJYsmQJlixZwnT+1KlTsWnTJt3XV6xY4UwgN9JzwhFwOoa2Fm4VHfFiJZrZ6HIS9bBRCEK+ZirLG6Zc5TmoqWTeZ1hyPjzojeVKsYWotV5nSll/s/06TvYk2nDA1bLZrcZorW+XddksN/WO5Z69XjVCZy8K5J+usTaQ96PATU00Ag4octomjhhm6XoEQRDE3okjh+2YY47BU089hUMOOQQ//vGPMX78eMOoU319PaZNm+bkI4cOJivRbIaqtdXeKGMftlxEpnQRtpI0WrZRJRKQxy1tnEKXZ0QPWnfYHETYWA1Vvb56TMa9V3sS5QI3dqIeNvqJqa/JXPFQL5prFDF1IFuPSY+4oqbeaofNQsPxkjZCt+JI2qwwy9xf0oYDbve5Ju9hiwYD+FLzaLzStj3v9TE1VZauRxAEQeydOHLYjj76aGzfLn4BXXjhhabn19fXY9u2bU4+csjgR9ohu9Fl0hvLg8gCa/NbTs/oYuk/ZaNKJMA4bqFwrtFychCcauGcySD00Ih2I+rhma65UdbfYpqa1eqazu4Du4sqBgVuQiEgGASyWVHXSiCb055/bH31rN8DlmQzcyY93MM2mMmicZj4XD1/1lTcZekqBEEQxN6OI4dt3bp12L17N/P5w4cPd/JxQwu9KpFW0q28Sjt0EGGz05zaimxO9rApxRasFqlgkI3jONNGy7pVPwFn/adM+nY524vloZMLla45KOtfjveB54sqkRgwkLDZ3N5++q15FMuBk2ujsqb6mk4LFukWQ8mTzV6EbSCTRW8yDQA4uL7O0jUIgiAIwpHDVltbi9raWrdk2asw24tlWKDCZolpy4ZNQcVDK5X7rFSgU1/TaRU6L51JpoILg/15zkeG55HhTfpPqXudWXAmZR3hBQEZXkA4qNNo2Szq4ed8uhBhs+sU2Tbwy2RRRRhI5OkaLwhK/zav0m8zvIAMz+sWqXFUxdVmrzPWvZx6xXfYHHB7Ka5y0ZGBTBa9KXE/Z3WEvaAKQRAEQQAOq0QSDnAS9bBpRFuuxFii6njqa9ruwyZXYgzpq7T9PTKMBqGGsare9+ZV/ylT2Uzm07iht7PIAnNhDxtl/e2muFpub2GnImmpFlUs6prA80AmbVm2/H6E5gVR7OyX9PrZobvY46FsckrkQDqDeFJclBlGDhtBEARhkZI4bAMDA7j//vtx9dVXl+Lj9gx0SnOXhVOks0+MKfrncJXccR82BufDbpEKO46uei+S6331WB022VC1oWuOi44wFrixldrncfSPc7CHza5sVp1JtWxsffVUiwNWep2x6pryXLMfzfVq/6teoSeW/a+CjX1/gLpaaha9KdFRHhZ1lNhCEARB7IV46rB9+OGHuPDCC9HU1IQf/OAH2LBhg5cft0dRVJpbItezyzxSVErHQ/0+X1fJTaprMu3HKqGjK7+HqddZIGCp15m6R5yRo6una172OnOthYRBxNSprrH2FHOUfuuDrgU4DqGAzn5Gm4sDoUAAQWmPpGFBFNmhyWQgqFo6MEVzHVb9dFp8h0XX7FaJzEuJDFOEjSAIgrCG6w7b4OAgHnjgARx++OE46KCD8NBDD+Gcc87Bxo0b8cgjj7j9cXsu6i/+tD0j2r6halbOXCq17qRyn8eGqq2iIw6dD/MV/OLqmlbT56z0nwIYIzKFZeCtyObQyR1Ie1jgpkQprrZaDjjcw2bYQgLQdHTVcunpkd3FAbVsTOm3gPXnmtd99VxIQ7dcJVIlm1x0hFIiCYIgCKu4lpvx0Ucf4Z577sEDDzyA3bt3g+M4XH311bjqqqsQi1n7ktsrCIUAjgMEIa8MvJeV+5jTrfSiHlb6FXnlFLnR/NajNDUt58NKoRarcsnX7U2Z9O0KhXItB1JJpQy8pfn0quiI7OTa2FfkVNeYDXwb6X12ep0BuSgPayppXoTNyr4/G4sDsVAQiXSGLf0WEO+3CrHPmLXKmhbvT8aIqW7xHS/7sEl72HYPppCW0pGrKSWSIAiCsIijCFsymcTy5ctxxBFHYPr06bj33ntx0kkn4cknn4QgCDjssMPIWdOB4zjNlCvZYTHcJyYbDx6Upxc/XI4s6JRaZ2rq7Y0zaba/jqkMvNc9xVTjZqVkuFVjkFU2peWA6rPU7/FiPln3sJmmuDL07fIq0mzWh42pTYNVR9fqoorFiKnTxQHAJP02FFIid1rpmr5G2MxaDnjRh00ai+2J3DOBImwEQRCEVWwt9X3yySdKNK27uxtTp07F0qVL8b3vfQ+1tbVob293W86hSSQGDA7kGatepuc43euRtLJKXuL9dUmWcuY+yOalMQhY7I812G9Z1zzvdabTQsLTiIyDiKkgCOXRh82urjlYHLAUoc/0Wd4vaVvX5KIjNltIJDPmzw47je2BXErk9n7xMyvDIQT1WiIQBEEQhA7MDlsqlcJjjz2Gu+++G//5z38QCASwcOFCnH/++TjqqKO8lHHIwkViEADrq+Q2jS7Z4ErzPHhBQMCTRsuliWKpS62zGNGCIDiO/jGnXGmUWvdiPtXXZXGM7Oia7V5nDqodAmxGtNcLF1qpwWmeF8fRI9mU9L6MyT5Tg6IjXsilvq65rkUh9PfZXoiym0Zq1kBet+UASxTcoa7Flf1rlA5JEARBWIf52+Oggw5Ca2srotEorr32Wvzwhz9EY2Ojl7INfZSUSFWVSA/3sBX2UqoIa0+/btqhlV5nHjWn5jT2sKVUqW2645bJAIJoapc0wsYwZnbn06lsXvY6k/fupLLGiwNmuuZt8R3GCJtG8Qwj2ez2OlNfkzWV1GqBG6UBtIeLA5rpmh7qWt5zLZtFTK+YipNG6PJ7LKahFz5jKR2SIAiCsANzbsY3v/lNxGIxDA4OYvny5XjkkUewa9cuL2Ub8mhVoWMz8O0ZD8yNlmPF1Q7V7/Ei5cpJQRT1e3T3/tksZw5YiCxoVNf0sv+U+rqmlT81IpPW+ok5WxzQxaR0vvFeToeFPWzseWLTNXu9zgD2yKRdXcs5ud7sYQNgO13Trq6p58EoMqks1GSzmi0HmGSzWSVSZliUHDaCIAjCOswO269+9St0dHTgt7/9LWKxGC699FI0Nzfj7LPPxjvvvOOljEMXjWiRl8ZDKMApkQ7DwgGywZRJQ1Cdx2TgJ3rF//t7LcnG7hTpp4IBUPqSFcmlMh757u22ZGNu6m1zXxEG+8F3tVmSzXKjZavO5O7Pxf8L2iiYob7mgFFBFEXXtPt2Gcom6ZiQiFuTzYXCHtFgQL/KooPFgVxKpLOy/no4WRyw3A7BYll/u7qmvueN21uonFSrsim6Zu25VuSwUYSNIAiCsIGl3c+1tbX4n//5H7z//vt45ZVXcPLJJ+Ohhx7C7Nmz8cUvfhEPPPAABgcHzS9EiGhE2Jg2wNs0bDiOYzO68hotsxuEqRXLIGxpFc+98jSkVixjls1RuhVD/6n0039Sfu7/xr6WZGM1VLWqa8rzabQ/JvPq8wAAfv17SMxv8WbcpGislX1FqRXLkHnmzwCA9F9+Y0kudaNlY12ryP1swYhOrVgGYfM68dyrTrc1Zsz7xOw6RRwHfmcns1zq6zLrmt0IW3LA8uKAk2qMXuoax3FsshW2HJB/9FDXClMiayjCRhAEQdjAdrmqOXPm4E9/+hM6OjqwdOlS9Pf346yzzkJzczN+/vOfW+7xszfCGUQ99Az81IplyDz3FwBAevn/s2Q8AIxGl45hY2R08V1tSN54Tu6AwCN547nMRqHVdKu81D6TPSh8VxtSv7lSdcCebOwVD9kNVb6rDRmVM+mZbBYjbLn5lEpsCIIluZhli5Re1+R7i3mfmMVoTPqZ+yW5BPQvGG/PAWcscKO1X9JItpIsDlgsiOKGrrFUS9VtOZDVf+Y61TWKsBEEQRBu4Li+8PDhw3HhhRdi7dq1ePnllzF//nw89NBDEAQBN9xwAx599FFkVKlOhAolWsTmfJTKiNYzbIxK5/NbWgG+IGLBZ8Fv3cAkF3u6lfXVe35LKyDYl81yYQ+tYgs6KZGibELBQeuyOUnX1Oon5nQ+1bIZ6lowCIREI1bQ6F/nha5ZjRRZibDxXW1I3X616oBFB5y1RL2RA66nay4tDpjul7RYEKVUugbAciqpW7omQw4bQRAEYQdXG8J8+ctfxgMPPKBE3Xp7e3Hqqadi3LhxuP7669HR0eHmx+3xGO3H0jK63DBsciXqTZoGWzRsAuMmA4X9hQJBBMZOYpLLlZRIHUM1MG4ywNmXjXXM7JT1F2UriEbbkI157x9jtMjpfKqv63YFS8e6xugUafUj9HpxgLUgip10TaeLA5YLAzGOm5u6ZuceNXp+uPVck6GiIwRBEIQdPOngOWLECFx00UX48MMP8dJLL2HevHm4+eabcdBBB3nxcXsu4eJokWxEaqXnlNKILqxCp+51plUdL1DfjOg1d+fJFb3mbgTqmy3JleEFZAudUrVcdpyi+maEz7jMsWymhqpGdc1ciqv2rRaob0bw8AXey2bVAa9vRvSae3IHuIAluYBcOhiz8yHNKS8ISqsGfdns61rUgSNp5hQ5XRyw7uSyRSVzstlfHLCaGsxakdQNXbNefEeUTfBY19T76wCKsBEEQRD28MRhU3PEEUdg+fLlaG9vxz//+U+vP27PwmLhADcMG7tRD5ZeZ+H5i5SfKx9di8jCxZblAkxWyTV617HsKwodOg8AwI2dhKqVm23JZtXxYJUtsO9+AIDg107xTDYlvc9Cb6zIwsXgph4snvPzey3JZUm2Al1TR770SueHv3Gm8nPlX9+zNWZZQUDG4uKA2ZgF6psRPv1i1QF7DjhrBNyKrgXqmxE84huOZWMuOpKXTs2ga/sdLJ7jpa4VpFSrU4l1n2tqXXvkXcuyqfexUdERgiAIwg6eO2wydXV1mDlzZqk+bo/ATuGAyMLF4CYdKJ5z3R9tGzase57kfUUsDYPVq/2BsRMtyaWOKDIVqUglIUjpXSzFFuS/g6sbbcnBVV+Xuf/UoKpKpMHqfe4k8fxgyxTPZDMsiGLQcoDjxXO4hrGW5FLLZlrco8D5YNK1wX7lRysR5sJrGqZFqnRN+ViGMQt9YS4AgBs/1bIDbjXF1WpZfyeLA3KUmLkwkFVdk+4VO7oWtXgfaOmabu/LQfVzzZquAfmVIinCRhAEQdihZA4boYFG4QAlJVKnnxgAcJJRwjXaMGxYi3sUGIRMvc5kwyYQUApJsMJaBj6vqa5kSBsVz1CQHTZ1GXlGmMv6G/btMnDY5HGLeSib3T5simyVlmWTrzuQNi46pKdrAY5DKKBdbVaRi+OAcMSSXFHmvl2SXKp+hGxl/UXZAnX1th1wt/eJ5U5ysDjA6kzalE0pOmPjHrXcW69A1zgA4cJ080K5OM5Ww3F1hI0cNoIgCMIO5LD5iNW9HjKCA+fDrkHI0usMKoPLTlsHJtk0esRZczy8GzP7fbu8n0+7uubE0WVPiZSubUfXYpWWdS0YCCiOoOHiQLR4cYClT6ITB9xyA3mLuqZEJj2UTbP6bZnoWmGhJ2vPtZij5xpARUcIgiAIe5DD5icaez2sGDa2VqJtOh9me1DEc+0bXOprG6Y1hcJK4QQhye6wlcbxsBn1KMF82o6w+aBrllJcHeuawV6xiMbigMeysfQTy5PNwv46p7IpY2bacNz6fknxwjnHyCpKuqZFZ5IlZVlZ7LGpaxRhIwiCIJxCDpufaOwrYjIgZKPLwSq5aVGDmH7UQ5ek/cgCwFa9j+O4osIjpXKKzPtP5VfWFN9jnhLpzMBnnE+tiqQW9tc50TXmBtXSZ5lV/RQv6lDXGFLouFBIqcoqlFjXWB1wq/vEnMhmueG41UjzoAuLKqaObv4iWa6KqzeLPQBQEVLvYQsZnEkQBEEQ2pDD5iNGfdiY9jw5MPAtRz0Y9ok5XYlm3ocS1ja6vDIGLZcMt5ymVsIUOgsRNkEQHOma1T1PRWlqRk6unNrnMMLmJDVYV7YSprjajZjaks3iPjHLulaCPWx6zzVDXXMgFwBUhNVVIq3ttyQIgiAIgBw2f7HYGwuAWPwgkxZ/KUUKXUGVSEPHQzLQnKapWd2/43X0Ty2XUNh4WE1BZU1W2Uq6J1EaM3VfPf2qnzm9tCObXB3PqqNr1rtOPLcE6bcq2SzpmqMiMrmIqaGu7QGLA7JsGZ5HhheMZUunlKbedqK5SpVIk3TNwtRgS+nUNqO5lBJJEARBOIUcNh9RHI+0mG7FCwLSvEmamsoZcJSm5kVkwWmEzWLLAVk2S2mkDpwiXhAUw1MLrVLrLHv/3EnXZHRyJV1j6aun1jVPFwcKdc3CXiy7umY10mwnwuZkzEx1zWbPP3f2sDHOZ1ou1MLQpqFEuqYbYTO8PwdtywUUpERGKSWSIAiCsA45bH5S2MSVoWGwMOjMsGHuV1QYWbDgeNhdiZYjKuzpfaXZV6Te32I4birjXukRx5JK6iD6xzpmeuXMAYNorixXKAQubD0yoJT19yJiKqe4VlhvN6C+NnuxlgJdY9gn5sQpMpWtoLJmnmxMkWbr48a6h00pOqKha3r3gZM2DYD1iKniTJawwE0owBmnuhMEQRCEDuSw+YnO6j3AsBIdjoDT6RtkhNV9KPzmT8B3tXle0MCKbAKkKpFdW/PON97zZN+ZZO3bpUTYeB58++Z82VicD0/3FWnv+wP0+0852b9mSTbp+iXVNdaITDi/4qGlCJsDpwgwdj4UXctkIGQylmUrxR62Ql0LBTgE9XTNYUsQ5n2m0nzym9fl6ZphD0enVSKlPWzDImFbfxtBEARBkMPmI3J6Dt+9I894MGoYXCpDlf9sPQAg89xDSMxvQcOqh/Per4VbK9FGsqVWLIPw6cfiedecgdSKZZYqvdkZt2AgoDg1RrKln39E+bn/hEl5spVL6fxCXTPqP1WK+QRE4xkora6xls8X5CqRnQWLAywOuI3FgQDHMemauuUA377Jsmye9mGTnEl+Z1eRrunhpPKtFdn4zyRde/5hJOa3oN6KrtnewyamQdZQDzaCIAjCJuSw+Ujmvy8AAIQt65GY3wI89UcAojFpakQ7NGyM9qHwXW3Ivva86gCPGX+6Bk393Z6WWjfr88R3tSF54zm5A4KA5I3nIta9Le/9WrjWt0tn3PiuNiRv/rHqAI/kjedieHwHAJOqnyVo01Coa4Fn/pj3fiO5vFwc0NK1mff/jEHXvK8SmVqxDMLGD8Xzfv490QH3eE8iq2zplQ8qP/efuD+zbG4sDpjtYcu+9ZL4WZs+QmJ+C4LP/MlULqdRLBYHnO9qQ/aV51QHeBzM8lxzWiVSujYHoC2esHUNgiAIYu+GHDaf4LvakF6+VHWAR9X/u4jdKbJr2Mh7nowMmy2tSsU2mQDPY0Jiu2EUS3GK1A2HrcgmpzXpyMZvaQX4AseEz2L452L0w0ujy2zc9GRr2NVhKJtYztx+UQOW3nVaula79BJTXZNL53sZ9TDSNaY2DR7Jprc4UNndCcC7vnpq2fScD76rDclfnKc6IC4OjIhvz3u/JvKc2tI1hmdHVxvSf/ltnmx1v7lU1DUPS+d7qmsO5/PDz3cDADb3JNBy+2O4/71WW9chCIIg9l7IYfMJ0XjIN/A5Puu58cCyDyUwbrK4+V8tbyCATVWjfd1XFBg3WWlknDsYxJZhDeL7Gfaw2Y7+mYybnmzrK/cR3+9R6XyW+TTUNY/6/QFsRrSRrrFEJe3sEwPMG47rOeB1OxkWB1yKFuk6kzqyNe2WIs16BYt4XimeYisl0qmuedic2qmueTWfbfEEnly3Jfd5goALnn/T8nUIgiCIvRty2HxCNB7yh18IBNkNVS8Nm/pmhBacoToQxKpTf4aOyjpfox6B+mZEr7kHkIqOgOMQveZudFTW5b1fE48Nwpxs8oEAotfcjc3R4QAMIjIlKGdupGtels6vsKlr/zrlGnNd83o+dRzwdRWjAAB9qbS5bF7dByayebY44FDXMjyvmxLodEHFzAEHJF37xvdUB3LPNZaIqR3ZWrvjKGzOwBv11yMIgiAIDchh84lAfTMiF96kOhDElvN/WTKnyKzBbGjOMaJY+x+CqpWbsfqg4wBA6ROniUvOpNEemcjCxQgd9x0AQPjMyxFZuBg9gykAxka0e7Lp//2RhYuBxvHi+b96DKFv/UDpd2ZaOj8YdFQ6X+zbpS1boL4ZkYtuVh0IYuO5N6Ojsg5pAyO6FFEPoFjXXjjo6wBKo2umDjiXWxz475nX4/k+8fdzV76GZWvW+yubciCAwJLfKQsXOweSxnLZlE1Ov83wArJGuvaj/1UdCOJvC69AR2WdkhKoOW6l0rUvHSuKNfVgy881O7JNrqtBYf2oAFWKJAiCICxCDpuPhE/4gfJz5dMb0X7UqQDAZETb34vF1ktJSTWLxPDHjn7c+dYnAIA/vbdB11B13MyYYY8MAHDDxTRDLhzBsjXr8XbnTgDGRrRTR5d13ALVNeLnVFbnOZ66RrTjPYlsfbsiBbq2bNzhAICNu3p1jehc1MNZrzOzPmyFunbX26Ku/eHdVoP5dLa/TtY188WB0wAAg6dcgK/1Nec+H6K+ad2ngoN9YqJs5tGiyMLF4FqmAABiv3hImU8AmHb337TnU91XL2S9gbN60cFItvDxUhQrEED8kY9wFiYrr/GCoD1ubi2omD07FF2LluS51lxThXvmfwlByUkLchxuP/ZQy9chCIIg9m7IYfMRTmUIB4aPxDOt4v4YQyO6BHvY1NdP9ydwzsrXlLQeI0PV8Sq5JNvGXb2G1dTkcevt6cE5K19TjrPI5nlPMdmBGBzAfe/m5s/MiHZant5UNtX1twVi+J1kqALmRrTTaO7O/kHj+bSja27trzMz8EeIaYa7MkJRKltWELChO178JgcpdICFe7S6FgCwUwjikn/m9kXpzqdLY2Ymm/Jc43m0IlaUEqg1bo7vA9YG8jH7umb3Plg8cwo2X3ASVi86FpsvOAnfmzHZ/E0EQRAEoYIcNj+J5qopdnz+ubLaC3i/Et09kDQuMS0ZXan+PmZD1ek+lLXbdwEAnlq/VT91SnX9nnicXTaHBqFMe2+/4euysbpzVzcu/geDEe1wPoOBAELS6v2nu3r1T1Tp2qed2y0Z0XZl++cmsULmZ3GDVDjAnq6VeHGgjssWpbIFOQ6T6mqKZXPQCF2Nqa5J1+/cuRN8wYQaOkU2I6ahQED5wthkpGuq60+qCqMwAVBz3FwqCrSzn+25lu5PWHfAbVa/BcRI29zxjWiuqbJ9DYIgCGLvZUg6bAMDA7jpppswc+ZMNDU1oaGhAQ0NDZgyZQpOP/10bNy40fQayWQSP/vZzzBp0iTl/Q0NDWhqasJhhx2GZ555xrGcXCCgGNKbO3ewGdEODZu/b2oHIBqDRka0vJoczaSYDVWkxKIGdgzVtngCKwqqqemteMsG53BkmGQTBMFR365la9bjlTaxZPpFz7+h73gAikHYtbObzYh2uHq/bM16ZCTD87A/Pas/n4GAojMTKoKMRrT91L62eAK3vLZW+d14Pm3omsMqkeyLA+L1q/k07pk/Rzkc4DjcPX+OtgHuwNG1o2uNYa5on5TmuDl0wJetWQ85EfKLf3xGX7ZwRNn71xTm8J1p++bJpTVugoNnBwD8Q1oc2GKyOCA/OyLpQXYH3KXFHoIgCIKwy5B02E477TRs2bIFzzzzDNrb29HZ2YnOzk6sWbMGxx57LI466ih0dHQYXuPmm29Ga2sr3nzzTeX9nZ2daG9vx7333ovLL78c7777rnNhJSNgX1Yj2oHx0BZP4KZX3ld+NzKiZWMwmBzAPfPnKLIFAE8MVa1qaror3tL1K1mN6ExaKYNu1TFqiyfY0y6Rm5eGMDw3ogtl4wUT2aQ5bQgBJ+8/Pk8uzXFzOJ8sDisAW7omOCy1zrw4IF1fSA5g8cwpCEuT+upZX8fimVOK5cpmgXTKlmyWdU0atxHI4qovH6Qc13WKHD47WHWN47icIz3Yj4PrxWIox05owuYLTtIcN6f3AevigHz9QGqQ/bnmcJGMIAiCIJwy5By2t956C21tbbjzzjsxZswY0XiQqKqqwplnnomLL74Yt9xyi+F1Vq5cieuvvx51dXV5xzmOw/Tp03HJJZfgL3/5i2N5ZaOrPgScfMB45biZ0eW1ES3LJQz2Y/HMKThiXD0A4LavzdY2uOAsFWxyXQ2bw6ohm5kRrRhcgOVxE8eMMXUKUAzV4RaNaPvzaUE2+TOSAziofgQAYP7EMbpGtJPon1Z1PNb5/PLY0QCApcccqqtrcFB0xNLigOx4DPQjy/NISzfQhOEaUT9AiTLbkc26rsn7JftxzIQxAIDmYZX6TpEDx8OqbOo57U9nAAD7Dh+mmxLoRNfsPNdg5blGETaCIAjCZ4acw7Z27VrMnTsXgcI+RSqOPvporF27Vvd1ADj99NMxceJE3dfHjh2LrVu32pZTQWXYHDTa3Ih2sgHeihGtNu4FQYBsqxnuwXBQbKG5pgrnHJL7e3WjPgWyqY3oiSO0jWjFKeI4IBK1JJc4Zoxpesg3VJmMaAeFPazKpta1gbRYnGHCCH0j2knUo7mmCrd+dXaeXCzzyaprThxda4sDUoRtsD+voEVFWKdNg4PFAdu6lhxQnKKRlVF9p8hxeXrruobBfqVKqN6YAXCka5aea7JcqSSEbFbRtTHDGJ5r5LARBEEQPjHkHLa2tjY0NjYantPU1IQtW7YYnnPhhRciZFD6+oMPPsCkSZNsyaiGUxmrshE9sa7GMyN66ddyJaWNjGhlJVoQgFQSAxnRIKzwsJnxgkljAQD7jazRd3CAnOMxUGBE6zYMlscslhdxZUEsy51LneJgkDoF5OZlcAADLEa0g9Q+WTaZAGcsG6dpROvruNMiFWer5u/j876lO5/FuibJ5lEj9OaaKvxwJuPigCxbciCvPYGproXC4AyaMevJZUnX8uZTvj8NyvU72MdpV9cEta4ZyOa0dD7r4kCeLicHlHGrNHAmKcJGEARB+M2Qc9iy2SyCJoZSKBRCRvqitsPrr7+O22+/HWeddZbheclkEvF4PO9fESrng8VQdWo8qA3VteeeoO8Uqa/PaHSpHSM7yH93OBg0jK4o0ahCI1rH+XDiFAFiWe7zDpkKADj74Cn6YwaAq7BmqDpthbB45hQc0iCm7d49f46hbHkRNgYH3GkZeHVEZWSlgU4U6JocLWJx2OwWHfnGZLbFAbXjIS8OhAMBBPUi+A5L+qt1bfHBk411LZqL/smLPSzPDif3wcFSKu19C75somvFCxcsumb/PsiVyjdaHFA/m4TBAbZ7lPawEQRBED6zRzhsy5cvx/Dhww3/LV++3HM5BgYG8JOf/AQLFy7En//8Z0yYMMHw/Jtuugm1tbXKv7Fjxxadw6n2oVgyVF3opVQX008P5MJhQDJi1ClXRmlNTsuZy9eWP0sXjf0xkWCgKGVLwYUV8tFVoqEXLMy90pGtVPMJAMOleawMhw3P49TRIgsGvt0KlqFAACFpvAYM5rRQ1xRn0ij657C6JuvigDpdkyW1z42S/rKuhQzSugFoRv+MxsxpPzEAqI1GAACVRp8DnQgbS0qk7fnMyWO0OKCuzAu1o8sQYaOUSIIgCMIv9giHbdGiRdi9e7fhv0WLFmm+t6enB5MmTcKLL77oSIZ//OMfOPjgg9HV1YU1a9Zg7ty5pu9ZsmQJenp6lH+ae97yjC45Pcc7Q5XjOMVYHTCLMqoKLlhJU7MdkZGMrgHGpt55hqqHkQUgZwibjZm6qiBT2qELRrQyn2aOrizbQD+TU+QkhS4nm3j9ftOGxsW6pncfCILgXNcYFwfyHI8SOeCVrLqmETFlSe0rxX2guYeNISXSrqMbDrItDqhlEwb70c8SaaaUSIIgCMJnjJdJhwC1tbXYsGGD7ffv2rUL5513HtavX48//OEP+PKXv8z83mg0imjUuMhFntEVYVgld8noGshkmRwjoS8uOh9pY2fSSTlzGdnYtGJwmckFwFFhj5xsbM6k1r4iIyPaXQPfZD7VsoW8T78FRMeoN5U2ndN8XTORLZWEXC3Crmz25tN7xwNQO0VmskmfMaBOifQu/RawrmuldHQrQiH0ptKmiwNctEKsEqqWTe+5xvOivgGUEkkQBEH4xh4RYbMCy/60TCZjWFBEB+X9lAAAZyhJREFUprW1FV/+8pdx4IEH4q233rLkrDGjihaxpNC5YhCGrKUeMhmrDsqZ5+RiNQa1ImwMe1BcGDPZMNaXrbgSo+cGvhIxNTHwK6zJ5jRNzZJsmgU0TAp7OJCNNSqZqxKp2otl5IC7sN+J9f5UV4ksRQRcfX2z+8BqlchcKqm9/a+AjQUflnFLqp5rFGEjCIIgfGLIRdiam5vxwQcfGJ7T0dGBcePGGZ6TTqexcOFCXHvttTj11FPdFDGPPAM/aJwKBsBdI9rM+ZBWorP9fUhlxcbTXpQzV+SSrj2YyYIXBP09aYoxOID+VNpQLsBtp4gt7RCDbA64OxFTawY+BvsxEGTfk+hGSiRThA1Aur8PGalNg2kRmUAACBnv2zOTy9VFCzivrCle37pTZGmPaYULsllJ15R1jalgkQu6xhD9EwDwquea7jM36fy5RhAEQRBOGXIRtunTp2P16tXgeV73nFWrVmH69OmG13nggQdwwAEHeOqsAdAxCL01oq2mgyX7E8ohL8qZ566dM5oGDWRTO17JgX5judSyuZCm1m8lwmYlsuBKuibjHjZVZIEtldS+gW9V11L9fcohU12LVVpu01AoVzLLFzWEVqPoWiaNwWTSWC61bKVIO1RXiWQp61/C+yCvWIuVAjcuLFywRthYdE3Z9xcKgWPIyiAIgiAILxhyDtusWbPQ0tKC888/H+3t7WKBAon+/n4sX74cS5cuxRVXXGF4nbfffhsLFizwWty8lCuWVXI39qEohg3jKnkqoTJsdFeipdQhJ5E/1d9taHSp/vZUnyibl4VaAAsRtgqNPWyliiwwOpMoURl49fVZ9zylErnFgZiJEe3GPQAYLw6o2wYkpfvA82gu4/2ZV7CoVE6R1QibumCR55kDbAVu5OdASr0QpSebCwtkBEEQBOGUIeewAcBDDz2E8ePHY8GCBWhqakJDQwMaGhowY8YMrFy5EqtXr0ZTU5Ny/rp16zBhwgSsX79eOdbd3Y1LLrlEea/Wv6985SvOhdUqUuFRg1kZ9nQw8TPSA6JhEzUone+GMZhXBt4owhYKKalwaWmVvFz27uRViUybG6puOkVW2iEw9WFzoVgLe9RDNqJz86kbPXOlemXu7zYcN9WeqrRk4Hu/X5Lt/tSO5pbHXs685xrL3lwX2iFY3cMmL0QZtQShptkEQRBEOTAkczxisRiWLFmCJUuWMJ0/depUbNq0Ke/Yww8/7IVoRWg2v/W44qHVAhqiYVPnefVKQIyUxZNpthS6vp6cgc/gFLlTHY99z5OVPWyuOEVWqkSaGPiCILjsfLDJlulPAIh63gohGAggHAggzfOG9wHHcaIzOTiAjJR+qxf5A1QOeAnuT6h6ODKV9Zcc3VKk3+Y1kK+wsDe3RHvYAFnXqjxf7CEIgiAIpwzJCNsehSqtyawnkFtGtNV9RdkBObLgbbqV+jNYq/dlSryHzVI5cwt72Eoyn8riwIB51MOl6nhW0/sy/ea65t7igLX0voyFaG5pS+cPWKv6WZKWA+x7c91oCSLKxhhplj5D1jXDdGoXFlQIgiAIwinksPmMVhl4XQNC7geEEu1DieY7RYYr5C6UMxdls+pMmssmlLDUen6xBfY9bK7Mp5mTW6FlRHtbHY95D1uU3QHPRbHsF0MBLDgfkmzKwoXHffUsN7ZnLVhUwpYg+anBJntzXWgJopaN1dHNDsq6ZnR/SrJRhI0gCILwEXLY/EYd9TDtCeS8/xSgMlQZ96HwFiJsiNjvoyTKZs0gZIn+uesUmRiDslOUzSItGXveG/jWStQLg/3mbRpkuYJBcGF7pfPVsrHuK1J0jSUt2KVoLuu4sRj4woDztEP1/SkwVrBMSos5TLpWknTN3HzKf4HeuLnREgRQRSZZ55PBAXdjjylBEARBOIUcNp9RR9jk8uKmvc4c9J8CrK+S83LUoyRGtLUIGz9oLpsrhT2k62cFAemsfssIddSHZzHw3ahgaXEPm+wUibLpGKsuVcezWqJeHjPjvVjuRHMrGRcucuNWovRb6fpZQUDaoD2JWteyA+y6VsrUYHnMxPd61xIEsL6Hzcp8UtERgiAIwk/IYfObmOwU5Yxo0yau0Qrb/acAdgO/yCli6Q/n2IhmTO+TI5MsRpcrvc5ULQeMUtVCYdGhRukM/EpWJ1dxinIRDd2iIy70YAPY09TU0T/xfUbpt1IUy639kqz966Rx87rATX57C4NxU1WwRImcD9Z9f4UR0wDHIRzQ+bpxIfIHWN/Dpswni5NLe9gIgiAIHyGHzWfUhQMAY8PGrcIeOQOftdKbbNh4vxJtNcImj4nXTlE0GITsIptXFcwVkgFKZ+CbF2rJ7XkCjMuZu1XYg1m2ikKHzfs0NasVLIXB0hREydM1g3tUqWCp+lzvW0hY7/knvk+/TYMbJf0B9oWLnK6x70mkCBtBEAThJ+Sw+Y0Fw8a9lWjGPWzRfGOQpZqaewY+W/NbDDIUHXHB6OI4TinnzlpVEAzpfaVsGKyla3q4UQI+TzZmXZP3/XmffsseLRI/h1MibAz9xByMG8dxzPeoomtJCxG2CvtRU8sFUZLmY+b+4gDbfcAxPNeorD9BEARRDpDD5jOK0ZlicIpc2lek7GFjdDy4JEs1NZcLQTAahJxUYc7rcuZAzolgdT44Jfqnk3aYTgNZ8VqlaBjMWYj8ubWHjbWsf7Gumae4ulYlktUpKqWuWbwPAibOh2t99RjvAa4w8meUdljiIjLy53AWUr0pwkYQBEH4CTlsfiMbqoMDgCCUKO2QcSVa+pwAyyq522X9rRpdHkc9RNmsOh8m6Zqulc63lkYaSA2CE/gSpR0y7mGLFkSxWMrTuzSfzE6RhXTN0t+jsjOpVzq/tC1BCqNYbA64W+nUHiz20B42giAIwkfIYfMZOT2J47MIC9mSlJi22pjX1BiEi4aqxYIogZS5bO41WrbWDiFo4ugKeQ6b/XYI8vUHM1ml0qgWagcnlk2XKGLK6IAXzKdxzz+p8mCJ5lMeA0XXPE5xzZON8R6NZkzK+g/mqjW6Uzqf8dmRSSPEZ5iea85TXK2Nmdn9mSebw3YlBEEQBOEEctj8RmWkVGRTTM2pHUcWLFZ6C7IY0Sl3GsxaLQPPIpvrUQ9Tg1D8nBifNpZNcSRjzqp+qhyvQSPZCnSNJSrpVuU+Vgc8yOAUuT+frPeBhaqCJSrWIstWkU0ZyuZeXz1VywHG9hYVjIsDpd7DFizhYg9BEARBOIEcNr8JR5Qy8BWZVIn2x7A2WpadIoY0NbfTDhkNVUtGV4kd3cqMiRHtsnEPGI8bFwwCkagoWzbFln7rcJ8Yc8sBaW5CDE6Rayl0zPuxKiXZ2HXNrcik6T5T6XMqsylwECt/auKFrhnJFokC0iJEhYmuuZ1+a743V3qupcWoJMu+YafPNYIgCIJwAjlsPsNxnGKomBnRpd4foxiqaTndqpTOJFsUSzGiWYyuEjm6nBL1SCLIcQjrGdEuzWcoEFBaQbBGsswWB9yv+sk2ZoquMe1hc+pMWuvDFmS4D1zf+8cYLYplU6gIh/RL57uka+qWA0b3gfq5ViHJpouUcu1WRVLWMQszLERRhI0gCIIoB8hhKwM4ldHFVGLarbL+jHs9wmk/9rCxRbHCGXMD3+3KfayFICqyabY9iS6s3rM2DZbnp4I3SYn8vFP8IWvyt5rJxdhyoEjXjJyi3l3i/+p9WXZkY92PJe0zjTDcB7nIZGnvUdaIqdN7IK+9BeOCT6kibKxtGnK6VjoHnCAIgiCcQA5bOaA2uliqHZaq/5T0OWGG1CH1fiwnsO8TyzeidcuZZ7NAWkxN5OO7nMlm0Yhm3ZOIbBZ8V5sz2VirMeZF2LR1LbViGdIP/RoAkFn5IFIrltmXi3UvVqGuGcjGv/86ACB58/84k421SmSBbHrj5lbpfMB6jzgzXXMztY/1PsilBidLk0bKKpf0OdH0IHtlXkqJJAiCIHyEHLYyQClSYbYS3d0l/p81MeJMsJo6FMmmETApA8/Hd4uyDSQcyZarQsdqRMv7xLRlSz9+t/LzwHcPcWTgM6fQKQ64saGaeelJAIDQsRmJ+S3OZGMct/yITLGBz3e1IXnjOYBSbVJA8sZzbTuUVh1JRdc0nA9FNhnBmWxWKx5GzCIyqtL5Qk+3LZlkWO9R1iiW7HgI2YzjxQHW+0COTJqlRAo73XquMUaZVam0UT5jmBrs1nONIAiCIJxADls5oDKi9VbJUyuWIf3I7wAAmaf+5E5kIZ0RowI6qFeVjYyu1IplED55BwCQvPFch7JZjWLpG9F8VxuSt1ygOsA7cz6YDXzZAdevjsd3tSH9yJ3uyca49w+qcdOK5vJbWgG+oPofnwW/dYMjuQYzWWu6puF8uC+bNQc8V4lRZ3HgiXuUn/tPme7aPcokW8Y4Op/+99MAAGHrRseLA6z3ARjSNVMrliH96O8BAJm/LXNp0YItwibKpn0fyLK59VwjCIIgCCeQw1YGcOrN+UZRD0gGr8PIgmygCABSRqW5VYaNXvTP7agHexn4nFMEaBvRXhn4bhjR/JZWVRTLBdmY9+/kCtxoLQ4Exk1WqpbmDgYRGDvJkVwAe8uBmE5qsPuyMRa4ieYi4OL7dO6DWy9RHXC6OMCYGpxXsEh/cSDz6F3uyWYxkqXXQsL155okV5rnkSm879VyhcNASGxtUJHRvg/cfq4RBEEQhBPIYSsHTNKa3HY81AaKkYHPBQLKnrRKnT1PfjtFlVLRkZiGbIFxkwHOfeeDvRBEUteIFmUrqOjnQDb28vmqqoJaY1bfjOg19wByLUAugOg1dyNQ32xLLvXfbyRbsa5pOJOKbPIBZ7Kx7xPLRYo4iJUSC3H9HlXmk002o3Rq7xYHWIvv6CxEuf3sUD/XTKN/atm8n0+CIAiCcAI5bGUAZxKRcTuyEA4EEJCcBdb0oVg2XZqIDOveHVkuPo2KUFCznHmgvhmRxUvy5HLD+WAt1iKOmbYRHahvRvCohe7Jxtg0WHEmDcr6RxYuRuCgLwIAolfejsjCxbZkAoBwMIBQQNY19nHTcz7CJ3xf+bniwbccyca+Tyxn3Mf0dM31xQFre9gqDVKW3V4cYL0POJMCN24/O9SLNsyy6S1cuCwbQRAEQTiBHLZyQLUSrekUFUYWHEY9OI6znNYk7vXQk+1u1QGXHA8LzamNChoED/0qAIBrbEHVys2ODHyrRSqM0tQAIDhhf/H/oxY6ls1yuqZJRVJI4x9obLEtU042qyXqk/oVD+VqpACCLVMcymVnzHScovpmhM+8XHXA6eIAq2zGkSJZtuBXvumabMx7xUz25rr9XAtYaDkAE0fX7ecaQRAEQTiBHLYygKXSW2ThYnD7zQQARH92jyPjHrCb1qQT9Zi/SPm58q/vu+MUMe7dMausif4+8fyR9Y6NLcul8w0KGgCAIMkWHD/VBdkYox6MTdox0CdduNqRXAB7jzgWXZPHDKrGzHZh1jWGVggAEJp1pHj+uCnOHXCL6bdmPRwD46cCAIJfO8W1xQEr7S0Mn2tTZgAAYtctc/5cY61gyfJc+/rpys+Vj651LBtBEARB2IUctnIgZl44AAC4jFhgI9A03vFHsu55yhld+mlqihGNnGFol1xzasaoB59GZbA4Ra1QNq7SBceDtaogs1MklQp3QTZW5yN/z5NBqXVPxs2Cruk5H7KuVVSJ+95ckcvCfAb1P1OQnNzAqEbHDrjVPYmmuiYvDkzY38WFCwvtLQycSU5qzcG58FxjLSSjjprq9nBUP9ccRnMJgiAIwgnksJUDjKvkQqIXgEtGNGNDY0EVLdKVTY7GxCrAaRRksCSXZKgmszyyRpXeVGXgh3P65eIFRbYqR3IBFqoKVsjzqb3vT5HNTafI6h42sybtrjpsbD3iBCW9T79/nbtjlptP45YD4pgFIKDGSL1lA7+E96cSKTIp6+/VuBnKFlPJZtRfUrpHOReiuVZ7JRr2r+vvVc51+lwjCIIgCCeQw1YGsBrRimNUOczxZyp9u0wMGz4SM5VNMQZdTJ8D2MvAD+fS+udJUaySRthUFSwNo1huph3Ke54sGao6kQVBUOmai86HSbSIj6giWXq65uKYyQVheEFA2mBxQB4zABgu6I+vq/cB4/3JMp8A3E1xtRgFj2XTTM6kO7rGtr9O1rUKgz2wynxWOX/eEgRBEIQTyGErBxj2UwD+RGSyksNWkU1pljMH4G5kIa/Sm0EZ+GAQ2VAEAFAr6J/nSxSLcT7homzMBVEq1FUidWRLp5SiI+5EPdjS+6zompuRP8B43LhwGHxAlKcGBg7bgJuyWYuY+vLscKG9BQCX55Rt4SIbiUqypTRbggCAIEfYXJCLIAiCIJxADlsZwFI4QEingZTYc8zVNDUzIzosGtE1QkaznDmQM2zckCsYCCAi7RNidSZrDKIeuT1PbjoerFEPtsiCH/vrxvTvRE1Pl/Y5qr07qHAjlZQtIiPrWq2QNdA198YsEgzI3eZMC6LIulYrGERzvYgUMTaQNyrrD7gbxbJ+HxgUkUmnAGlvbikd3YwUYZve2wZsb9c+ycWIKUEQBEE4gRy2ckAybJoT3ajepWNEDyZyP7sSkWEzojOSoXpgvB18V5vmOTlj0J3UIVbnIxsUDcfmxA7dc1yNelgs61+VGcA+fZ/rn6ikqbm5v85kzD54EwAwp3sD9lv8BaRWLCs6R5nPaAycUWSEVTbGxYG0pGvT4m26uuamA85xHHOxloy8cGEUYXM1Ysq4h01Jvx3EyF79+wAu7hOzeh8093ejejfL4oCbxXdMnMnOLQCA729cjcT8FsP7gFIiCYIgCL8hh60MyH7wBgDgi7s2ouWsg42N6FAYXDji+DOZe2N1iYbN6Rte0DVs3ExpAticj9SKZYj1dgMALn1kibZccHl/DGO6VXrVEwCAiMDjtKuO0ZdN3l/n5r4ig/nku9qQefIPyu+cwCN547lFzpGbcgHsZf0DDLomDLq3J1Etm/niQBgA0GjgFOVS6NzbY2rq5K7+m3g+n8FJVx6tr2tywSIXnA/W+yCz9nUAwOxdm9B85gzt+ZTkcm1xgMEB57vaEFn7muqA9n2gFB2hCBtBEAThM+Sw+Qzf1YbMivuU3zkd48FNxwNga8zLd7WhgsGwcbPYglo2PaOL72pD8sZzlHS2gCBoG1yAJ/tjjCILfFcbUksvU37Xc4oAl9PUGKIe/JZWoLAaIp8Fv3VD/jEXC44A7M6kFV1zTzbzioepFctQtbsTAPCjv16j6xR5shfL5P5MLb1c+d1I17zYZ2p2H2SeuDcnm958uhj5U8tmOG5bWsHB/D6gCBtBEARRLpDD5jPMRrTrUSwGI5rRsHHfwDd2PvgtrUBhVT8tueCuQahevdcrA29FNk+cSYOoR2DcZIAruOUDQQTGTso75GZqnyibeVl/Zl3zanFARzYriwNeVEt1S9e8ug/0sPpcc31xwMCZDIybDAEFeyS17oMEFR0hCIIgygNy2HyG3YiWUppcMlRZ9npYNWzcWok2S1MLjJsMFDZN1pALgKsGIUsZeFbZXC+2wNAbK1DfDO7sa3IyBIKIXnN3cSNlVXNqN2BZHGDWNcUpckc2sz1slhxwFxcu1MWHkllt2Zh1LZMBkoMAXN5fZ/bs8GFxgGVPYqC+GV2Hn5Anl+Z9oOx/pQgbQRAE4S/ksPlMoL4Z6R9cozpgYkS75RSZRLFk2doYDBu3UyLNysAH6psRveYeJR4jcJz2mMFdg5ClDHyxbAHj+QTcaerNWKglddzpAIAkF0Ts6U2ILFxcdI7baWosZf0D9c1o/zK7Ee1aRMZkf52VxYGy1bUBdwsWsT470mf/THXA+Nnh1j4x1v2SXQceAQBYP3oSqlZu1r4P5IUoirARBEEQPkMOWxmQOPY0AECaC6Dy2U+1jQfX09TYDJv2A78CAPh09ERdw8YrI9rIIIwsXIw1B8wFAKw55gfaciFXQMONaBFrGfjIwsX4rKYBALDl8t/rOEWSXOEIuHDYsWysfdgGpHLmUSGL8KgGzXNc1zXGiodt00Qj+tN6fV3zLF3TxcUBN+6DcDCAoNTawEzXtlaPBgC0X3mvoQOOUAhwpWAR27Oj75jvAgCygO5zDS5WcRVlY6sS2R8W7wOEwppzCajGjSJsBEEQhM+Qw1YG9EtGdFjgERgxSvMc1zfnMza/TUiyIRDUN2x8ciZ3VtUBAEIBg+bULo4bx3HM/bF2R8TPi1TENF/3rIiMiaE6EKnM/SLv0SnEo8IerLomBEKmuuZWRIalfH5k4WK8dtCxAIAP556uuzjgpq4B7Pfo7qisazqLEqox0+tvZ00utvmUFweCAAK1IzXP8Swl0mThIiG1kKhMDRicRBE2giAIojwgh60M6A9VKD93dHXqnOSuEc3af6pPki2aTKAtntA8R3C5/DXrKvmuYBQAwPXrOB7wzpk0k60nJBqEgz27tU9w3bhnjLAhgP6gGGURdMbN9aqfjGlqCWnMIoP6uuZVRKbf5D7ojNUCALI6BUAAf/ZjAUBcug8Ge3aVRC7We6A/mFusKNVzjaUiKZB7rkWS/QbPNdrDRhAEQZQH5LCVAX9dtxV9ktH1lbsexbI164vO8czoMjGi39ydAgAE+3vRcvtjmrIplftcLzqib3QtW7Me7/eJr6/99DPtMeP53P6dElahW7ZmPXYHxPm849//Lcl8VjIa0QPpDPokx6izS7uZseBDWX8AeLMnCQAIDPTp6pof98GyNevxfkKU/X1fdE1ftvvWrMduyTG6bfXrJR4z4/l8dN1niEu6Nvf3Os81H8r6A8Dru8TIWngwYfBcoyqRBEEQRHlADpvPtMUT+OWra9Er7amoSg/g3JWvFa/6DribCpbrP6Vv2LTFE3i6YzcAYFhmELwgaMrmVWTh4x09mqvfbfEEzln5GvrCMUU2zTFLDiilxUsV9ZBlk+ezWm8+3Y4sSHJleAGf7tKPOD728WfolYzokx542tgBL2FZ/7Z4As929AAw1rVSR5oL57OUumZ2j7bFEzh35avKfaCray4/OyoZ2luIz7UPlMUBveea66nBDFHJtngCT24Vo5HVmUHwPG/8XKM+bARBEITPkMPmM63dcfCAYtgMSw8gKwjY0B3PO8+rQhBdiQHdlKDW7jjiUupQZTaFIJ/VlM1tg1C+/p8/2Ki5+t3aHQcvCIrjYTZm4DggWgE3CAbEPUBbevo0Xy+UrTo9WJL5fOTDT5WfJ/3ucU1HrC2ewK2vf4BexcDvL4kDzq5rOQecE3jtcfNon9jHn+/WlC03n6L+1Piga1sNxowXoJKtNLpWoWpv8elu7cWBwudadUZbNrcXB+Q9iZ19+qmOrd1x5R4IC1lE+UxJdI0gCIIg7EIOm89MrqsBBygGRE1mAEGOw6S6mrzz3O519uJn4p6ST3bGdVOCJtfVKKv3gGhIa8rmotHVFk/gH5s6lN+1Ii2T62oQ4Dgl6qE3Zup+YlxhaXYbLFuzHh9/LkaBznjyZd0xC3BQxk13PuX0ORdK+rfFE/if599QfucFaDpird1xCMgZ+HqOrtsO+EvMupZzdKoySUNdcysis26n+Lc/8tFmTdlkXYsr0dzS6dqHO3YDAL731H8MdU2Wrdrk/nRrzB5WLQ5M/t0TurKJzzVZ13Rkc9kpeukzMc33o897DHVN3i8JANV6cyoX5aEIG0EQBOEzQ9JhGxgYwE033YSZM2eiqakJDQ0NaGhowJQpU3D66adj48aNptcQBAF33HEHpk2bhsbGRuUaTU1NOPTQQ/HEE0+4ImtzTRUWHThBiWTVZJK4e/4cNNcUGPIuGtFt8QR+8+ZHyu966WfNNVWYPmY0BgNimtHwzKCmbG46k7JToabQqWiuqcI98+coYzYsrSOXy47kOStfy10b2k5Rc00V/vfIQ3Ky6YyZm8Uz5CiQGi1HTDai1VGPUjjgv2bUtWljGpCRmi0Pz+rcBy7L9tyGNkPZZF3rLVNdu+4rBysFNGoyA8a65tKz48d/N18ckJ9rcqS5NqtzH7joTLbFE/gto64d0jQaCan4znCdZ67bkUmCIAiCsEvI/JQ9j9NOOw2NjY145pln0NTUpJSyTiQSePzxx3HUUUfh9ddfR1NTk+41Hn30UTz00EN47rnnMG7cOOW4IAj46KOPcPLJJ6OxsRFz5sxxLO9B9XWKEX37Eftj9MwpRee4aTzIqVRqZAO/0GjZpyKG3nAFYslevHLy4WgqkE0QBFedSdmpUIun5VQsnjkFv/+LWKJ+fETAIVpj5qJcRk5R4Zh9fdIY3CnN58nj6lDn8XzKUSC1fFpj1lxThe9M2xe9b4oGfq2eA+6iEW1F10ZVVaA3FMOIdD/eOPUraJpeoGvpFJBJA3DvPtBbHFDLtnjmFPzhEfHzJkQEzC4jXTtmwhj8QdK1U8fvg5EleXawyTajIfdc++0RB5TmuVZwTE+2+uoY+kIxVGVT+PdJGs+1bBYY7Bd/oZRIgiAIwmeGXITtrbfeQltbG+68806MGTMmr+9QVVUVzjzzTFx88cW45ZZbDK/z/PPP49JLL81z1gCxF9e0adNw2WWX4bHHHnNF5r5UWkkdGs6nNM9x04iWU6nUaKYEAehNZZTowmhOo/hBKglkxQ3+bhhdzTVVOGvGpDy5tJyKLM/jc6kSY0g2lgvxwClSoztmydx8xpL9hrK5YQzKUSCZAAftaAaA6aNHKNG/n82agMUaRrSbERkrutaXyijjVq+la/2qeXYhlVReHDCTTRAEbIcYjQmXma71pdJK+m1FykTXfLgPZNlMn2s+6prmc20gF5WjoiMEQRCE3ww5h23t2rWYO3cuAgb7SI4++misXbvW8DqLFi3CvHnzdF8fM2YMunTKolulN5UrtS70xbVPctGIbq6pwm1Hz1Z+13OKANEglPfIaDVaFtRGtF7jXot8Y/JYAMC0fYZj8wUnaToVfakM4pLBxQ0kxBXxQtkko8stR/Ke+XMUA5+DvlPUm0orTpFurzOX+4ktnjkFB+wzHADwp+MP13bEkG9ED0sPasvmovNhRdd6U+ncfWCka5EouHDYFdnOPWSqqWwDmazSV4/r7xVL+OvI5quu6Tw73OyrZ2VxoC+dW+wxfa65NG6/+uoXlN/NdE1O19R+rknHgkEgEnUsG0EQBEE4Ycg5bG1tbWhsbDQ8p6mpCVu2bDE856ijjkJdXZ3h5xxyyCG2ZCxE7RQJCROjyyUD//xZ+yk/v3fO8foGfiqdM7q0ZJMjDrEKcMGgK7INi4jGeCDAaRpbgBRZUBUOgJZjpCoE4QaLZ07BD6VxOmfmFMMxU4q16M2nyz27AGBkhWhYxoL6mc6iES3Jptdw3OUiFefNyjlF759zgu649amMaC1H14s9RcdPERcHJo0YZrA4kIuYAsiP9BUecyl9bvHMKThPciYXHzzZYMxyiz168+l2X73FM6fgoNHDAQDLvvFlw8UBo/kUj7s7p2oH/MPzvmWoa31Gsin3wLC8LA2CIAiC8IMh57Bls1kETRyHUCiEjEmDYT14nsf777+Pe++9F9/61rcMz00mk4jH43n/tBAjC5JBqLHaC8B1IzoaCiIsRSFrIhHd8/KiHhqr5ErBkUr30oaGRUSHozeZ1j2nL51BKhjGYCCsL5sHZbmbhon75opy6VT0JnNOkVakCEAuhc4lZxIAhkXFsehN6Y9bb9J4PgH3o3/RYBAhKVetJqofGetTNfWGlmwuV68EcosDAHQXB3qTaQwGwkhz4nNFa+HC7TEDVLpmQK/KmdSNYnng6I6sEOcpavCs7UtlVAsXZs81d54fleGQkrJZE9HXtbysBq0Im/Jco/1rBEEQhP/sEQ7b8uXLMXz4cMN/y5cv9+zzn3jiCaVKZHV1NWbMmIEf/ehHmDBhguH7brrpJtTW1ir/xo4dq3meOj1HN8KmGIQuOkYMBr56r4dmtMhlR5JVLtmZ6zeITLpdzhzIGfi9SX2Hvy+tTu3zPk1NplpydPuM5jOdVlJJNccsmwUGB8RfXJKN47jcuJnMqeJ8lCjCxnQPpDMAx6Evou8YKbrm4n4nWba+lIGupTLm6bf9/jw7TKPzcN/R5ThOuQ+Mn2uqKLiWrnnwvCUIgiAIu+wRDtuiRYuwe/duw3+LFi3SfG9PTw8mTZqEF1980fbnn3jiiejs7ERnZyfi8Tg++ugj/PnPf8bjjz9u+L4lS5agp6dH+bd161bN89ROkaahmskoRrSrxqqJYZPheQxmsoYGoRdRLBbjXnZK+qNSFEIruuCFgc/oeMTDuYip1p4nuJymZkU2xQHXMvDVxRY8cXS1ZeMFAQlVuqZmtMhLB9zAKcotDki6ZrBw4aoDHjZ3PNR7EpGIi1VbC/FJ1/JSXLWiWJkMkBT3UZbyHhUEQXzmGkXB5WMUYSMIgiDKgCFZ1l9NbW0tNmzY4Nr1QqEQ9t9/fyxbtgwLFizAt7/9bd1zo9EoolHzDeu9qTSqjQxVlRHtpgFRE40ASCCuY0TLhqrc1NswsuCBwZXK8khls4hopF31pUUDeyAiprEZRdhcdSajDEZ04Z6ngURR5MWTaBGTEZ1B2ijFVZ5Pl4stmEVk+qX5NNqP5eXiQH86gyzPI6hRrKgvLco8EK0E+vR0zf0UOrbon6p4hhwdrchPpfQivc/MAQdEuYcZRLGgrrhZQtkGMlnwgmC4h025P6lCJEEQBFEG7BERNiuw7E/LZDIIhZz5qi0tLejo6EA6rW+wsJJX1MBgfwxCISCsv9/MKmYGvny8P8IQWfDAUAX0jS45wpaUImyGBVFKHcVKiXue+IDBnicf0zV7jVLoVPvE3Cy2YDZu8nz2hQ0iMp7oWu45oJd6KI/nYFRaHCh59M/YAU+Eco51yaLgUfPIZJ+qJYjhPRAKg3PzuWYim6JrRlUiPRgzgiAIgrDLkHPYmpub0dnZaXhOR0dHUX81Nd3d3TjmmGNMPyvsQmlxwHwDvLoCnbtGtHFxD9mAzcSMoljuFx0JBQKIhURnR9eZlIzoVKxakq1EBj5LZCEp7nlKKeOmn3roZtERlj1svcmMEjHVXBzwYMwAc2dSNq6TUXk+S+MURYNBBKV7Sm/c5OPyfBqOmwfRP6M9bL3JNAQukJOtjJxJ5jYNLuuaXGwkntTu/Sbfu6mo/nNNceIowkYQBEGUAUPOYZs+fTpWr14NXmvfkMSqVaswffp03ddramrw7rvvGkbqtm3bhurqalectj51L6VSGtEmKVfy8bRkhJYqJRIw31skp6llZAPZaAXfk8iCcZoaAGRjBrJ5GvVgS6Ezms9S65rsFGVkB9YoTc3FMeM4zvp9UKIqkUzFMwrug5IVa2Gp5JpK5xYHDErnl1zXpPTblKRrhmNGETaCIAiiDBhyDtusWbPQ0tKC888/H+3t7Xmb8Pv7+7F8+XIsXboUV1xxhe41QqEQjj32WFx++eXo7S3+Mm9vb8c555yDCy64wLG8ygZ4lWFTWDjA86iHbhRLcjxko6WURpdJJEuJ/lUaRGQG3WucXSQXQwXLbKW2oysIgn9RD3XRkUwaQiqZf4IHTq4om7Hzocyn0eKABymuomxmKXTi8ayBbJ7Op2E0V3yN13EmBZ7P7YH1obCHYYTNo7RD8/mUxkxZUDFonE0RNoIgCKIMGHIOGwA89NBDGD9+PBYsWICmpialJP+MGTOwcuVKrF69Gk1NTcr569atw4QJE7B+/Xrl2B133IFgMIiDDz5YeX9DQwMaGxtx7LHH4phjjnHFYSvcAA91WXXlJHd7FcnIPbH0io7Iq/dCVY34f4lSwQDz4h7ycV4ak1JFi9RparxWRT6VbIIsW6GjOzgASO/1SjYtsjyPgUw2r+F4kTPpQaRILZue86HMp0GkyK/FgSJdK1mBG1GuRFpf1+RokSxbkfMx2K/8WMpo7mAmi6wgKHvYkE7pLw74Np+l1zWCIAiCsMOQrBIZi8WwZMkSLFmyhOn8qVOnYtOmTXnHamtrcdttt+G2227zQkQF2ahIhKIAxwGCAKG/F5yq0ptXTVzNI2yS4W/gFCnOpMsr0dVh2fkwTqFTnFijPU8e7BMDgEQqk1cgRUYZT3lMdJwiAEDMvDmyVdnMolg8FxDHZCAhRk3rRuVO8jzF1Ww+jaIeXqXQmY2bvHBhoGseFrgBDHRNen5wOs6kkhbMcUCsAm5hPp9y1U9VQZREL7iIukCKX/NZ8FwziLBRHzaCIAiiHBiSEbY9CdkYrIpGcsZeoYHvWZoa20o0V60fYeN3dok/ZI0rc1qWzXTPk/R5LNE/Fw3CynAIAZMiFXIqVqCqVpKjwCCUU9QqqsBplJG3i3kaqXg8FOCUcuV6Br4wkADf1eaebG7M564d4v8uVGbNk42xWiony1aiaG4sFFR0zWw/lnKPFsqmcsA9qfpp8uyIRqM5R7HgPvD8uca62KO1h61b0rWMu7pGEARBEHYgh81nZKOiOhLOGYSFxuqAP0a0fDwoGYOFjXlTK5Yh+9JT4s93X4/UimXuyca4DyWoZ6giN458f1/Ra3bhOI4hkiXLZhL1CIV9mc/qSDjnGBWMW+btFwEA/FsvIjG/xbU5ZXWKAlXaaaSpFcuQffXv4s93Xu2qrlVHjKO5igNeLTngWs6kNI6Cy7pmtvdPdpiC1dqLA0o0N1haXZPHclgkpO/oevVcM9U1eUFFO8KWWrEM2df/If58+xJXdY0gCIIg7EAOm8/IkYVhaoetwOjKvPUSAID/7wslNaKViMww0RhENgskB0VZutqQvPGc3MmCgOSN57pmeLGu4Id0jOjUimVA724AwOC5R3vkTBbLJhdbAFTjVmAQZp77i/hD725P5lNvD1uermlEF/iuNmRX/y33Bp53bU5Zo3+y44FErvhOyXTNZHEgpMhWqGv3KeM4cM5R3uiaxriJuibLlltUUZP++8PiD/Fuj54dem0aVIsDOns5PX+umUWa5fkcSIjFWeC9rhEEQRCEHchh85mcYRPS3PPEd7Uh+9KTuTe4aESbFR2RZYtU1Yh7YKCKWm1pBQpbJ/BZ8Fs3OJYLYN+HEqoZLh5I5I9ZvtHl3pgBxgZhv6pARGRYsTPJd7Uh9adbcm9wcT7lyF+a55HMZIteV+uaVgodv6VVKYaSO+jOnJo3My5wcgVBSR31XNdYFwd05jN547kquVzWtah+9K8/nYE8W+EaWbZ8Bzx9/y89kU0es/50BlmNFir5C1HFBVG8fK6ZRpqT8nyq9qdJkVGvdY0gCIIg7EAOm8/0KqlD2hE2T41oxqIjw2LRov11gXGTgcL9V4EgAmMnOZaLRTbZgI3Ihmqh4+GpM6nvfCj7nQBEJGcyz8Df0goI3shWrSpSoTVuZtHcwLjJxRd1aU5Z5zNaVa3olex8eK5rjIsDynyWUNeqDSJZslwcgLCWM+mpA54rvqMV0c1bHCjxcy3XONt4319FZTUQDIqyJUrzXCMIgiAIO5DD5jNaK9Fqg7AkRrRJWf9h0eL9dYH6ZkSvuTtPpug1dyNQ3+xYLhbZlKIGNSNEuQodD84fZ1I2rKsjYXDVxSmRomwFxR9cki0UCKAiJBqgWuPWp05T06h4GKhvBjdOJYeLc2rWaFkx8KORosqfgfpmRJfc5YlcomxsEZlo7XAA+U6Rv7omFSyKhJT9dSh8dnika9FgEKGAfkGUPtVCFEr9XGPcX1cdVe3llBcH6psRveKOPJnc1DWCIAiCsAM5bD6TnxJZXHQkUN8Mrml87g1uGtGMqUPV4ZBmQZTw105Rfq584mNEFi52LBOrbLKjWzFcdNjUBVEC9c0If/ei3MmuG/j6zodiqEbDmqXWA/XNCB4+3zvZ5BS6tH7UI68QRGFJc8n5iFy+FFUrN7s2p6zzmbdwoZItNPd45efKpze6q2smRUfkhYtKPV37zv/kTvZD1/QipvXNCM45xhPZxIIojAsXGvslA/XN4Mbs64lsrAVu9GQLyfdnKIzKZz91VdcIgiAIwg5Dsg/bnkSe0aVXZloyDqNX3onQ3OM9iCxkIAhCUdnvXpXzAaWoQU42oXu7+ENFFYItGivmrshmvEpeWSsZ0XLDcal/XXC/mUgDCOx/CCqWPunqCrmhoap2cqurABQ7RYF9GpEFEDr++4j+6AZXZasOh7EdgzoGfrERXVTBUiqdHzrsmJKNmShbfgqdgHznQ5aLG74Pgk0trsklfqZJAQ1pLCtq68QDhbo2ZYaoawceiopbH/dk3Po0Whmo5xOVYjP0wvnk6uoBAKETf4joOT93XbZdgykGZ1K/3xkARK+4HaGjvlWy6Hzh4oBQIJuwS3yucSPrEWwY64pMBEEQBOEEirD5TN5qr0YhCEEQFAMi9OXjXDW45KIjvCCg3zAiEwZCEfHcjs052WQjesSoovc6xcjAT2d5JLPivqFqKU0NALKbP8nJ1i32hwvsu7/r6UxG0aI8J1dyividnXnFFGRHN3jQYR7Ipr8fKy+aK+ka/+k6RTYhnQbiuwC4P6fyfKayPFJZrYIoKudDI4WuJLqmYeCrdW2Yjq7x0nwGJhzg+nxWG8iWt/9VfnZ8rq1roRlfKu19kFTpmk67EmVx4EvuPtdkuZJZHumsVkEUlWwaFSzlHmxc3WjXZCIIgiAIJ5DD5jPq1V7ZsMluWZ8zugYS4mo+3DcgqsIhyDE1oyIV4178K/g1LwMAkrderJTflg1VLwybnBGtVWwhJ2vFc39Wfh44fXZONqmhtxxh8EQ2I4ctEkb2zVXiwa62vLLlJRk3k31F/IYPAQDZV59TZBN6doonBgLg5GiSW3JFVQVRTCIyCIrnCts+U1731GEzcHLzdO3vy5Wf1bqmLA54MZ8GBW5yEbYQsm++IMqy7bM8XVOiRSNKrGvp4hYS/GbV4sDggFKZ0avFAT3Z8loOhCRd61Drmjxm7usaQRAEQdiBHDafUa9E8xvWAgD4V5/PGdFy2mGsAqiocvWzxSbQxhUPm/q7MebOy3MHVX2JvDWijRwPUdaW5G5kfnGeSrZcaXChJM6kVmRBkm1wN1L33ph7QVW2XDYIAx4a0Vr7seSxbOjvRub5vxTJlm0V9Y+rHQlOqp7nFqFAADG5IIrBnI598RHw7/4HQP7igF/RXCZd83lxYNzgbqSW/SL3Al/q+0B/UaU6EgK/SVocePmZ3HNNmk+EI7l0a5cIBwOIBgOSbIwLUbddoqFrFGEjCIIgygNy2HxGXomuT+xE5rmHci/IRvSGDwCIxkPhHjM3UBwjTecjjYl9XeB0ytArho0nxqAY9dByPOT9PAcOfq5bUl2Jeoz0wIg2ciYl2fbt7dQt358z8N0fN5Yy8E27OrRLqre+L8rlUWTBqNlyX1pcHGjyY3GAwSky1jUvnSKD+0A6NqFPW9eyW1q9lY0hNbg+sROZfz6qkqtgcWDEKG+fazqyGS1EKRFwirARBEEQZQI5bD4jO0qju9u0jWjZYfPA8QByPYsKDZssz2Mgk8XG6noIOn2JcpEi9w2bapVcQsG4yGO2Y2Szbs+kUkQ9NPtPSbL1N47XlI0b1aQ0hPZiTg2jf9IcZ8ZM0CxFz0XFwhWeO2xGiwN6TlEJHDajfmKGuiYtDngxn9UMzmRf/Xht2epGA+mUKJuHzqRRZHJ0d7v2c22jvBDl9eKAtmxMC1HksBEEQRBlAjlsPqNUfxs7SdOIRlg0PLzaAC+vRBc2mZUNro7KOoSu+n2ebHL5bS9Th2SDK8MLSBYUqZBlS4xoQPSae3K9pjguJ9tOL41o88Ie2VFjRNlkAgFEr7kbXFgs3oJoLNeM3EWM92OJ4xZqGIvIZbepZBNLqssRJM+MaB3Z2BYHvDOiZaeoP51BtsBhlKNY/Ua61l2CfWIGqX28nq5J+7NQXaM446WSTT4mNE/UXhyQihh59Vyr0ckcyPI8+tMZY12Ti8hQ0RGCIAiiTCCHzWdkgyLSOA7RK4sbtiIjGmVe7HcC9Fei5d9DAQ4VJ56N2P9bIb4wqknpSyR4mDokO0VA8R4Z2cmtjoQQWbgY4dMvEWU99juILFwMgefzSnO7DWvRkcjCxQgc+EUAQPSnvxVlkx1Jr1JcGfawVUfCiHz3InH/EICKP/xblM3DFFe1bIXjlkirFwfuMlkc8K7oCFAcZcsbMy1dy2Yh7P5clM3T9Fv96J98H3D7HQIAiC65C5GFi3OFd0r87ABy92ikcRwiF/8y94L8XBOykmzeRtjiBroWXFJ6XSMIgiAIO5DD5jN5BuEp5wM1Yl+x2B3PSUa0d3tQAP3GvHklwzkOwf1mii/s2g5BikJ4adgEAwFUhrUjMrleZ6JRFphwgChP727x/55usVeWR7KxFB2Rzwk0TxBfSA6KsnV750gCxil0uUqMIXAcB04upS7Pp8d7d/TGTf49yHGoOPGHiP3mafGFEaNyiwMe6lo0GEQoIDrPheOWV8UVWrq2Uxw/jgM3fB/XZTNywPMqawIIjp0ovpASq8p6uX8NMCvrn2vTEDn9YkAqYlPxwGv5iwNeO5M6mQNBjkPlt9W6Nrp4IYoibARBEESZQA6bzxQZhE3jAQBcOgmgBEaXjoFfKBc3skFMB8tkFGPLe9m0HTZFNslglHs4Cdvb8uRCzYhcCqKbcjEUHVHGbfQYAAC/o0P8v2Tzqb+/TnbqAqNE2YTt7eL/HkcW9MZNKQEflRYHpn1BfGH35xCkPVheysZxnGmkWY74FumaHMWqHQkuFILbGKffqnrXQaVr8nzKqX0eLQ6wRNiGRcPggkFwkq5x0kKK14U9dHVN3aA9T9d2QEinxL6XuynCRhAEQZQX5LD5TLFBOBYAwHduBeC9U1QTjeTJochVYNxz4bASFRK2t0sNvT028PVWyeWUSCkCV2yoelchMk8uA6dITrMLjGoSZSowoj132LT2PKXzHV153ErmsOkuDhTM54hRQCQKCIKoazyv9Igrua4VLlzoOEVeRUxZ++oBQGC05EzKvc487MGWJ5vBHjZlTiVHV+nD5lP6bV4PNhTrmpd9LwmCIAjCLuSw+Ugqm0UqK6ajKQZhwzgAgNBVGodNdiwKi44oKZGq/T2cOiLT1wNkxHNKv0qeH1mQox7o6YYwOOBphUggN1daRSqKDELZKdpR4Ex6ZURL86UUs5EQBKHYMSp0PjyOLNTozGfR4gDHgVMtXAg93bmCKB6kHQI5XSvaw1YYlSzUtW7vWjQA+RUs+YJqi+rG2UDOKVIccA/bRwD6++vkIjLqc+SFqMLnmhcVZgELmQOFuib3h4vGXO97SRAEQRB2IYfNR9TGoWKsNsjGwxYAJVwl11mJTmd5tMXFMvQBlYEvdEuGTWU1uFiFL7LJxiCqaxXjStje7mmZdfFz9YtUdA+IqawDaWkPXYkjMvK+vsKoRzKbRYYXDX7FiC6IsJUqXbOoImlB5A8AAtJ9IHRuyRnRw4aDC4fhBboGfrpg4aJI1+Qx80rXcn9vf1q7IEpx9C8/NbjU0b/855rPEbak9pipixoputa1Na/ipxdFgQiCIAjCDuSw+Ygc8QgHOHQlxDQcZSW6c6tU7bA0hs3GXXHFMQOA5zeKRvw7nd1ouf0xLFuzPm8Fn/e4GIpatkLno7OvHwCU6BbHcXnGqtcRNr0iFcvWrMem3X0AgO+seBHL1qzPOUU7OsQ0Up8KQaiN6F2SU6nM5452CJkM0NMtHi952qG8OJBVdFAr6uHlniK9vWKdvbKuic6uvq55M58VoSACkuNQOG67B8V57JecyoDq/iyJrukULJLnM8ABOxKDBbIVOJM+7WHL8Hyxrm3bQhUiCYIgiLKEHDYf+dP7GwAAaV7IOUWNYkok37UViO/KVTv0KBVsTadopL/4WZciQ1s8gQc/2KScwwsCzl35GnprRCOG39FeEsNGNvDf6dypGFfL1qzHgx98CgBY+sZHWLZmPYACY9VjQ5XjOFRJaYWt3XEAQFs8gXNWvqacwwvAuStfQ0ekRjyQSoppdJ5X/RTHrHsgleeA3yeNEwBMuPMJ0ZmUUlz5rjZljxg4DlztSE9l27S7N0+25zaIiwPvdu1SdDCgSg1WdM2je0At21vbPs/Ttb98tBkAcNvrHxrrmkdRLI7jNJ3JZWvWY2tcdCYXPrZafHZI+yWRSkLYvdP76HxU1rVk3nz+8b1WAOI9MP6Ox6XFHpUDPpAABvsl2bxaHBDHzLKueexIEgRBEIQdyGHzibZ4Atf/+13ld9kp6qoSjWWhqw38zk7xxdo6T1LB2uIJ3C85jWoZXt26HULBuVlBwLYKseVAnqHqkTEIAO1SJO13b69Dy+2P4Vevrs1zigSITlFbPKHsr+O72sB7nBK5bM169EhRhaMffB7L1qxHa3e8aI9RVhCwoS+pOBr89va8Pmxe8GyrGMHoTaXzHPCrX3xHOUee585KaT53dOTms7YOnFSC3W3e3ib2K3u1bUeebH9eu7FItt214vjwqpRIr/Y7AUBnnxjh/s2bH9vTNQ/vg8qQOB8bd/UC0F8caB9IKwsBwva2XB82jxYHZF2LF+jatRrPtc+rRypyKSmukShQNcwT2d7ZJi5AvLJ1O7uudW0F73FGA0EQBEHYgRw2H3jgvQ2SgZ9/PCsIaA1UAYEAkEmDb10LAOAqqpS9H27S2h3XdMw4AIW7N4Ich1HjxT5PQlcb+K2io8fFKl2XCxCN0v9s6VJ+5wUBV77wtrZT1B3PRT262pQKm1zAfcdDz1iuDocQKBi0IMdhUl1NrvCIKlok8FlPZLty9Vsq2XIOuJaubeCkuUunwH/6sfhzrNITXWuLJ3Dfu62asmnpYHtFHQAxNVjWNXioa6+378iTjVnXpLHyysldtmY9OqW0wm88/C/jxYHueC5ds/1TQOoVh2xxNVOntMUTWLL6beV3M13bFKkFIC0OfC4uRHEjRnmyT8yZrkkOXSTmulwEQRAEYRdy2Hzgon+8iepwSNMpmjSqTkltSj/1JwCiIZGY34LUimWuyjG5rkbTyZgzdjT236c279jd8+dgtOSw8e2fIn3/rQCAzD//6rpcgLYzyaNYYQudoux7r0BY/x4AYPCGH7oum56xnEhncM3hM/Lkunv+HDTXVCmypf72B0B678Ci2R7Jln/MyAGfWL+PEklIP30/AO90zeriQMOkKQAAfusGpP/8/wAAmX88Ur66dv3ZrstWtDgAlsUB0ZlM/+0Pymv93znYd11r2Xei2Dw7m0V2g7gQhWhFWSxEKbq2pRWZFfcCADIr7vVE1wiCIAjCDuSw+QAvGfjfmNysHMsz8KX9HtnXnle9iUfyxnNdNXCaa6pw29GzNWUIBUTV+OW8Wdh8wUlYPHOKUkADyQFANokEwXW5ANGZ1DKubvnqF5TfA3lOkVSF7pM1uTcI7o+Z6OTmSyYby3OaxZS9iSOqlTEDcr3Ysi88kXuTB/OpJ9ucsaNx2rR9844VOpPZ/6wsgWz5x2TZDhw9oki2xolTxQOD/fBL126eN6tIrlLqmtHiwOVfPFBTNjn6l335mdybSqxrJ+7XUizbiBplISqz8kEAgLClteQLUdNGDS+SLV/XJDzSNYIgCIKwAzlsPhCQDPzGajHF63vTJ+Yb+FKZ6SL4bC49zCUuPPQABCXj5rWz5isydEpVK4+dOAbNNWIZc666BghHSyJXc00VLjr0AOV32bj60Rf2U46tPeeE3JjVNxddwwvZmmuqcM/8OYqBzwGKsdzVJ6auTRxRo4wZkCu3XirZZAJcTrbxw8W9Qt+aMjZP10op253HHab8rnYygpLhf9NRhyiycdU1Yi8sj+WSZTvnkClFssljBADrzl9Ycl0zWhyY1STuCZs+aoRv86mna2Ml3T9t2vh82eSFqLdfUsnlzULUHcfq6Jrkyd0yzx9dIwiCIAg7kMPmA7855lA011QpTtGc5tF5Br4Q3639xkAQgbGTXJUlwHFokBxHeT9JhueVctwN1bkea6kVy4B0siRyAcD3Z4jXrImGFeOqSyoOEQsF89I2M2oj0GPZFs+cgssPmwYAOHn/8YpBKrdmqK/K70una0R7JNtR4xsAADcfNSvngEvj9oWmffJ0DYneksl23qz9lObZ//juMYps26TiMsepFgdSK5YBycGSyAUA3502AQAwZlilomvymI2IRTCxrkY5t1S6ZrQ4IMu23z61efOp7MHyWDbAXNcObRqVJ1upHF0AOP8L+ymVXF9YdKwiW0evKNtxE5t90zWCIAiCsAo5bD5wpuSIbJMMm8ZhOQOf72pD9o1/Fr8pEET0mrv1jR4HyE6Z7EDuSAxCgLgyPbIiqsiVvPGcksolRyDjyTRGV8XyZGyoqlAcTL6rDalf/6Sksu23z3BRNlWp9S7Jya2vyl+t5zd8UFLZ9q0Vo2nJLK8ck50ieUwBSdfe+XdJZRszLL9wSDrLY7s0bk3Sa37omnwPxJNpxZDXG7NS6trimVPwv3NnAgCOndBU5BSpF1T4rjZkpL2IpZAN0NY15R6tzl+4KOVCFJDTJ5lUNosd/f7rGkEQBEFYJeS3AHszitGlisjwW1qVwhRqYjf9BeFjTvZEDvnzZXlkg2t0VQxBaS8bv6UV4Pmi93op18jKKEIBDhleQFffIMbWVmkbqj7I1lidP2aAdoSN72pD+uE78t/MBVBx/2sIHTgbXtBY4IADucWBonHzQdc+/rxHcYa6EgMQAIQCHPapjOXkKvF8yuPSm0ojkUqjKhLOLaj4rGsHSIsDu1UNqtULF3myCT7dBypd03yu+bAQVV8VQ2t3XFlIkeUKBwK5hSgf5pMgCIIgrEIRNp8QBEExINQr+IFxk8Wy/moCQQRnzIFXNBQ4H1pOkR9yBThOMfpkA19r9d4P2WRDVZYL0HHYtIxogQcGE/CKBkU2lRGdKHY+/Bm3yjzZtqmMe3m/lh9yDYuEUSH1Oys08P3WtQYNXSs/2Yp1jXVxILJwsaeyyfJ09Irj1zQsF533Y8wIgiAIwirksPnEzoEk0tLKbn11LoUuUN+M6DX3AHIPsRKk5igRtkSBw6ZyPPyQCwAah+Ub+OUim+x4bE8MIiPNo1ZKpJ5B6OXemEJnMsvn0g7zHDY/xm2YnhGtWrTwQS6O44oWLrQibP7oWk4uQXJ6NBcufJRN1rXBTAa7B1PFsvnhTBZkDnRI//utawRBEARhFUqJ9AnZiBhZEUWkoOluZOFihL50LPitGxAYO8lz46EowqZTPKPUcgHFBqFWZMEP2fapjCLAceAFAdsTg2gaVpmLsGkY0ckbzwX4bEmdSXmsdvQPghcEBDgOoyrz99eVXNfkiGmv7BTJ+8T817WG6gp8urtP0X9ZNr91Tf78ZJbH7sEURlRENRcu/JCtUNfkSqnRYAC10Yhynh/3gfz86ipcHKjO39vmh64RBEEQhBXIYfMJrdV7NYH65pIZDiwpkX7IBagdtnxnstBQLbVswUAA9VUxbOsbwLa+foyuiuUqa/psRKvT1ARBUMZOvSdRTSnHrXDPk1y1r7BARKnlAjT2cmqkLPshWywUwvBYBLsHU9jWN4CaaFiJmPp9jxbqmjryxxW0JPB7IUormitTal0jCIIgCCuQw+YDGZ43dIpKTVFKpE6VNz8o3PNUTuPWWF0pOWwDGDNMrKwZ4DjsU1ncq84PI3owk0U8mc7bJ+Y3hfuxOvq0ox5+wJIS6ReN1RXYPZhCZ98A9qmMIisI4ICiiGmpKdQ1s/uzlPdBfcFzLadr/s8nQRAEQViB9rD5wHYpKgNor96XGt0IWxkY+KwpkX6gyNY7oOxf26cyqhnFKiWV4ZDS72xbX78qUlQOY6ZddKQcZGsoSKErp4ULdfEdeT73qYwhHCxPXSuHZ4c8b1195tFcgiAIgihnyGHzgW2JwfIyVCUZEukM+lLmq+SlRDflqgwMQrUzKRuFhfv+/EKdSlpOiwOyXLsHUxjMZAzT1EqNuqrgQDpXPKMc7lFlr1hioKzuTyBf18rRye1KiHs4yymaSxAEQRBWIIfNB7oS/WVldFVHwqgKi9mxnWVmdKkjMrsHU0hliytr+oVaNr2m2X6h3o+l1YPNL4bHIohKUaHOvoGcEV1ODltfzimKhYJ5xTP8Qr1w0aWzV9Iv1LpWThG20dK9mOZ57BpIltXiAEEQBEFYgRw2H+jsHdStjucXskG4aVcv4lKD3nIwuhpVaU3tksE1PBZBLOT/9ku5RP22vn7NHmx+onYmyyklUl0+f2u8XynUUg6y5TkeqkhuYfEMP1Cn35bTggpQoGtlJFs0FMSImOhsb+7pwy4pYto0zH/ZCIIgCMIK5LD5QGeiX5USWR6rvbKx+t72XQDEyIK8N8VP6qsqwAHICgI+3LEbQHk4kkB+KljZOWyqfmfllH4L5Iz5d7u6IQAIBTjs43PxDCA/JVKOxjSWiXGvlq2covNA/sKFXisEv5DlWNPZDQCIBALolRakCIIgCGJPYcg6bAMDA7jpppswc+ZMNDU1oaGhAQ0NDZgyZQpOP/10bNy40fa1Ozs7MW3aNHR2dtp7f2JQSQUrF+TeYe9Khk1tNKxEtPwkHAwoxvyarp0AyscYVPegKteUyG295ZV+C+TG7Z1t4nyOiEUVB8lPZGc7leXxRvsOAEBtxP9FCyB/v+SmXb0AgFhB/0a/KNeUSCA3pw9+ID7vUzyP8Xc8jmVr1vspFkEQBEFYYsg6bKeddhq2bNmCZ555Bu3t7ejs7ERnZyfWrFmDY489FkcddRQ6OjosXzedTuPUU09Fa2srBgcHbcm26tMO9KUyAIB5y/9eFsaDbGA9v6kNgLhRv+X2x8pCtpEVYpn8FzeLDnJNmRnRHX39WPd5DwAg7HOFSBnZKfpwx260x/t8liYfWdeead0KQGzsXQ66pk6h+9XrHwIAnt/U4btcQG4+N+/uw9/WbwEA3Pif98pKtg937EZHPAEAECD4KZKCrGsvftalHOMFAeeufA1tkqwEQRAEUe6Uh3XpMm+99Rba2tpw5513YsyYMXl7UKqqqnDmmWfi4osvxi233GL52ldeeSX2339/HHDAAbbla4vnogm8gLIwHuRo2s6BlHKsHAybZWvW45OdojP0RsfnAICnW7eWhaH63EbRuc3wAt7cJsp22b/+WxayydHINV3dSPKi8fyVB54rC9nkaNrnA0nlWDnoGiBGltUIKI/7U46ODmSyyrFykU2ta2nJTzv8/vLQNb2oclYQsKE7XmJpCIIgCMIeQ9JhW7t2LebOnYuAQbTj6KOPxtq1ay1d969//Sv+/e9/49e//rVDCfPx23hoiyfwlLRqX4ifsrXFEzhn5WtFx8vBUG2LJ/Cj594oOl4usv3mzY+KjpfD4kBbPIGnpchaIX7fB8vWrMfmnuKx8VsuAHjik880j/stWznrGgBs6dGOLgc5DpPqakosDUEQBEHYY0g6bG1tbWhsbDQ8p6mpCVu2aDspWnz00Uf4yU9+gkcffRSxmLv7lPw2Hlq747oJTH7K1todBy9oS+a3oVr+smm/Vg6ylaOu6S0OAP7fn23xBM4tU9nKWdfa4gmsWFf8jA9yHO6ePwfNNVU+SEUQBEEQ1vG/NroHZLNZBE025IdCIWQyGabrxeNxnHTSSbjrrrswfvx4ZjmSySSSyVzaVzxebLyUg/Ewua4GAY4rckD8lk1PLsB/Q5Vks0e56pqeAx7g4Pv9Wc6ylbOu6S0O/OVbX8HJ0/YtuTwEQRAEYZc9JsK2fPlyDB8+3PDf8uXLXf9cQRDw/e9/HyeffDLmz59v6b033XQTamtrlX9jx45VXgsAuPywadh8wUlYPHOKy1Jbo7mmCvfMn4OgtNevXGQrlEvGb+MeINnsUq66JjseagIAXj9rge/3ZznLVs66pjVuQY7DnLGjfZKIIAiCIOzBCYJOXtcezHXXXYfhw4fj4osvBgD09PRg1qxZuO+++zB37lwAwO7du3HwwQdj8+bNhtf61a9+hX/9619YuXJlXtTu4IMPxt/+9jfDiJtWhG3s2LF45v11mNEypuxSctriCWzojmNSXU1ZySbLVRUOIZHOlJV8JJs9ylHXlq1Zj3NXvoasICgOh98OkUw5ywaUr66V47glEglUV1cDAPr6+lBV5f84EQRBEP4Qj8dRW1uLnp4e1NToZ6UMyZTIQmpra7FhwwbL71u9ejV+97vf4b///a9piqUW0WgU0Wi06PgRLQ2oKQNjppDmmqqyMLIKKVe5AJLNLuUo2+KZU3DsxDFl50gC5S0bUJ7zCZT/uBEEQRAEC0PSYWPZn5bJZBAK6f/5bW1tOPPMM/HYY49hn332cVtEgiDKkHJ1PIDylq2coXEjCIIg9nSGpMPW3NyMDz74wPCcjo4OjBs3Tvf1+++/Hz09PTjhhBM0X9+xYwdmz56NSy65BFdddZUjeQmCIAiCIAiCILQYkg7b9OnTcfvtt4Pned1ebKtWrcL06dN1r3H11Vfj6quv1n19/PjxePfddzF8+HCn4hIEQRAEQRAEQWiyx1SJtMKsWbPQ0tKC888/H+3t7VDXVenv78fy5cuxdOlSXHHFFT5KSRAEQRAEQRAEYcyQdNgA4KGHHsL48eOxYMECNDU1oaGhAQ0NDZgxYwZWrlyJ1atXo6mpSTl/3bp1mDBhAtavX890/VGjRiEcDnslPkEQBEEQBEEQxNAs61+usJbuJAiCIIYmVNafIAiCkGH1DYZshI0gCIIgCIIgCGJPhxw2giAIgiAIgiCIMoUcNoIgCIIgCIIgiDKFHDaCIAiCIAiCIIgyhRw2giAIgiAIgiCIMoUcNoIgCIIgCIIgiDKFHDaCIAiCIAiCIIgyhRw2giAIgiAIgiCIMoUcNoIgCIIgCIIgiDKFHDaCIAiCIAiCIIgyhRw2giAIgiAIgiCIMiXktwB7E4IgAADi8bjPkhAEQRB+kEgklJ/j8Tiy2ayP0hAEQRB+IvsEso+gBzlsJaS3txcAMHbsWJ8lIQiCIPymqanJbxEIgiCIMqC3txe1tbW6r3OCmUtHuAbP8+jo6MCwYcPAcZzf4jgiHo9j7Nix2Lp1K2pqavwWZ6+E5sB/aA78h+bAf2gO/IfmwH9oDvxlTx1/QRDQ29uLpqYmBAL6O9UowlZCAoEAmpub/RbDVWpqavaoG2MoQnPgPzQH/kNz4D80B/5Dc+A/NAf+sieOv1FkTYaKjhAEQRAEQRAEQZQp5LARBEEQBEEQBEGUKeSwEbaIRqO49tprEY1G/RZlr4XmwH9oDvyH5sB/aA78h+bAf2gO/GWojz8VHSEIgiAIgiAIgihTKMJGEARBEARBEARRppDDRhAEQRAEQRAEUaaQw0YQBEEQBEEQBFGmkMNGEARBEARBEARRppDDtpfR19eHBQsW4N577807/vbbb+P444/HhAkT0NDQgIaGBowZMwaHHnoo7rvvPmSz2aJrtba24rvf/S4mT56svKepqQmHHHIIbrnlFiSTyaL3bNu2Deeeey72339/NDY2oqGhAY2NjTjooINw5ZVXIh6Pe/a3lwtuzcG1116L2tpa5Vytf1/5ylfy3iMIAh577DEcfvjhGDdunHJeS0sLvva1r+HFF1/0+s8vK/TmAgBee+01tLS0IJFI5B3PZDK45557MHv2bIwZM0YZwwkTJuCEE07Au+++W3QtGnd9rM5Bf38/qqurDfW+oaEBTz31VN616NmTj9a47969G//zP/+DfffdN28sm5ubMW/ePLz66qtF1xkYGMBNN92EmTNnoqmpSXnPlClTcPrpp2Pjxo1F77FzDw1V3JiH1tZWVFRUGN4PjY2NePvtt4veZ/U7fKihNf6ZTAbXX3993rjI43/kkUdqPq/pe8E+bszBXvG9IBB7DT09PcLhhx8utLS0CEuXLlWOv/XWW8K+++4rPPvss8Lg4KByPJvNCp988olwwgknCJdddlnetbZu3SqMHTtWePDBB4VEIqEc53le2LJli/DDH/5Q+Pa3v533nt7eXmHChAnC7bffLsTj8bz3bN++XbjmmmuE2bNnC9ls1uW/vHxwcw4uuugi4Y9//KOlz1+6dKlw5JFHCu+++66QyWSU48lkUnjxxReFadOmCU899ZStv21PQ28uBEEQXnrpJWHcuHHCsGHDhF27duW9dtFFFwknnnii0NramqerAwMDwlNPPSWMHz9eWLNmTd57aNy1sTMHu3btElpaWix9Dj178tEb97POOku4+OKLhb6+vrzzs9ms8PLLLwvjx48X2tvb81474YQThPPOO09oa2sTeJ5Xjvf19Qn333+/MHbs2KL32LmHhiJuzcOaNWuEI4880tJn2/kOH2rojf8tt9winHDCCcL27dvzzud5XnjttdeElpYWYdOmTXmv0feCPdyag73he4Ectr2E/v5+4Ytf/KJw/fXXC9dee23ejbFgwQLDh0JfX58wbtw4obOzUzn24x//WPjtb3+r+55sNivMmDFDeOedd5Rjv/rVr4RLL73UUM5vfvObwhNPPMHwF+15uD0HVh22dDotNDY2Ctu2bdM95+233xZmzJjBfM09FaO5+M9//iOMHTtWeOedd4SWlpY8Z6Gjo0NoaWkR+vv7da/9+OOPC8cff7zyO427NnbnwM4X897+7FFjNO4NDQ2Gun3llVcKv/vd75Tf//vf/wqzZs0yNGhuu+024cILL1R+t3MPDUXcnAc7Dpud7/ChhNH4z5s3T/jvf/+r+95rrrkmb+zoe8Eebs7B3vC9QCmRewmCIODSSy/Fz3/+86LX1q5di6OOOkr3vVVVVZg1axbWrVvH/J5AIIB58+Zh7dq1zO8BgKOPPjrvPUMJt+fAKlu3blVSlvQ45JBDsG3bNmQyGdufsydgNBeRSATPPfccZs6cWfTaJ598gi984QuoqKjQvfZXv/rVPB2mcdfG7hzYYW9/9qgxGvef/vSnhro9duxYbN26Vfl97dq1mDt3LgIBfVOicFzt3ENDETfnwQ52vsOHEkbjf8kll+Cggw7Sfe+YMWPQ1dWl/E7fC/Zwcw7ssKd9L5DDtpdQWVmJU045RfO1np4eVFdXG76/qakJW7ZsUX5va2tDY2Oj5+8ZSrg9B1ZhGX8AGDVqFDo7O21/zp6A0VzMnj0b06ZN03yNZQxra2vR3d1t6T3A3jHuauzOgR329mePGqNxv+SSSwzf+8EHH2DSpEnK7159DxTeQ0MRN+fBDnv7PWE0/t/4xjcQiUR039vW1oZDDjkk73f6XrCOm3Nghz3tHiCHjWAiFArlrfJks1kEg0HP30Pk0BqbF198ESeccAImT56M+vr6vEIld955p+Xx1/scQoR1DO28h8adnf7+fvzsZz/DIYccgjFjxii6P2XKFHznO9/BJ598knc+PXuc89RTT+Hvf/87Fi5cqBzz6nuA0EdrHgBgx44dSlRCXfzlgAMOwNlnn422tra88+mesE4mk8Err7yC559/Pi8yQ98LpUNvDoCh/70Q8lsAgiDsMXXqVDz66KO48sorMXv2bAwfPhwcxyGbzWLz5s24+OKLEY/HsWTJEr9FJQjXiMViGDt2LARBwBNPPIGmpiZlJTaRSODZZ5/Fcccdh3fffRfDhw/3V9ghwK5du3DJJZfg5Zdfxt/+9jeMGDHCb5H2SozmYfTo0QgGg2hubsbKlSvR0NCAUEg073p6erB8+XJ8/etfxzvvvINwOOzXn7BH8pvf/AY33XQTAHEOeJ7Hc889R/dBCWGZg73he4EibEQRN998M44//nhL71m+fLnl/SYvvvgiJk2aVF5lU8sEljk4//zz8cILL+CYY47BiBEjwHEcACAYDGLixIn44x//iLvuusvwGscffzxuvvlm1+TeG5k5cyYefPBBS++hcbdPLBbD22+/jRtvvBHjx4/PS5upqqrCKaecgm9+85t4/PHHda9Bzx5zBEHAww8/jBkzZmDEiBF45513DPeUAKJzMGnSJMvlyO3cQ3sLLPPQ1NSE999/H5dddhmam5sVZw0QU/F+/OMfY/z48fj3v/+t+zl2vsP3Bi666CJ0dnais7MTvb29ePXVV3H11VfjtddeM3wffS+4B8sc7A3fCxRhI4q48sorLb9n0aJFWLRokaX3zJ07Fxs2bLD8WXsDduagkH322QepVAqDg4OIxWKa5xT2JCGss2bNGsvvoXH3lv3331+z/5cMPXuM2bp1K8466ywIgoDnnnuOeT9hbW2trXG1cw/tDdidBy3ke+KrX/2q5ut2vsP3NiKRCGbPno1f/vKX+L//+z8888wzuufS94I3WJmDQvb07wWKsBFMZDKZvFU7lrxeN95D5LAzNrFYDIODgwDYc7FpDvSxk89O4156Kisr0d/fr/xOzx523nzzTXzlK1/BqaeeilWrVhk6CV59DxDW5oEFuifcY8aMGXj//feV3+l7ofQUzgELe/o9QA4bgeHDh6Ovr8/wnI6ODowbN075vbm52bRykRvv2VuwMwdXXHEFksmk4XuSyaQSXWMZf0DcvG5UanhvhmUM4/E46urqLL0HoHFn5Y033sBDDz1keM7AwEBeiW169rCxe/dunHjiifjzn/+Mc845R0mz1sOr74HCe2hvw+o8PP3001i1apXhOXRPsPH+++/jBz/4geE5gUAgr5UFfS+4i5052Bu+F8hhIzB9+nTDh30ikcDbb7+NqVOnMr+H53msXr0a06dPZ34PAKxatSrvPXsLdubg1Vdfxfr163Xfs2vXLoRCoTyHbdu2bdi2bZvue9asWZO3YZ3IZ7/99sNbb72Vt0pXSKEO07i7S19fn+E+BABYv349JkyYoPxOzx42brvtNnz3u9/F4YcfznT+9OnTsXr1avA8r3tO4bjauYf2NqzOw/bt27Fy5UrDc6zeE1rf4XsDI0aMwBtvvAFBEHTP+fDDDzFx4kTld/pecBc7c7A3fC+Qw0bghhtuwMUXX4xnn302L2LD8zw2bNiARYsW4aSTTkJ9fb3y2pVXXonbbrsNDz74YN5DShAEtLe347zzzsOECRPyNjGfd955eOqpp3D77bejt7c37z07d+7Ez3/+c3R0dOCEE07w+C8uP+zMwcKFC3HllVeio6Oj6HpdXV0499xzcfbZZyvHQqEQrrjiCpx66ql47733kM1mldfS6TRefvllnHHGGbjxxhs9+iv3fBoaGnDiiSfi9NNPx4YNG/IM1WQyiWeeeQaXXnoprrvuOuU4jbu7zJ49G2vWrMETTzxR5Chks1msXLkSK1aswIknnqgcp2cPG2+//TYWLFjAfP6sWbPQ0tKC888/H+3t7XkGVn9/P5YvX46lS5fiiiuuUI7buYf2NqzOw9FHH41HH30UL730UpGRm06n8cADD2DdunX4yle+ohy38x2+N9Dc3IyRI0fi1ltvLcpgEQQBra2tuOSSS3DBBRcox+l7wV3szMHe8L2wd7ntBACgpqYGw4YNU36fOXMmnnjiCVx77bW44IILlId3IBDAmDFj8MMf/hCLFy/Ou8aYMWPwwgsv4Gc/+xmuu+46Rdk5jkN9fT2+853v4Le//W3ee6qqqvDKK6/g2muvxezZs9HT0wNBEMBxHEaOHIkFCxZg1apVeWHuoYobc3DRRRchk8lg3rx5ylgC4hyMGDECZ511Fi6++OK891xwwQVoamrCj370I3z22WdK/nY0GsXkyZNx++23F/U2GeoUzoWa0aNHFzXv/NWvfoVly5bhtNNOQ3t7u/LlUFlZiQMPPBBPPPFEkZFD426MlTmoqanBk08+iauuugoXXXQR0um08lo4HMaMGTPw5JNPYuTIkcpxevZoUzju3d3dOOmkkwx7E331q1/Nq3730EMPYenSpViwYAG6urqU59CwYcMwe/ZsrF69Gk1NTXnXsHMPDWWczkNLSwsefPBBXHvttVi3bl2e8R+LxTBnzhw8++yziEajynE73+FDFfX4cxyHRx55BNdccw2mTp2q7AEHxO/jxsZGXHbZZUVGPH0vOMPpHOwN3wucYBRzJAiCIAiCIAiCIHyjPNxGgiAIgiAIgiAIoghy2AiCIAiCIAiCIMoUctgIgiAIgiAIgiDKFHLYCIIgCIIgCIIgyhRy2AiCIAiCIAiCIMoUctgIgiAIgiAIgiDKFHLYCIIgCIIgCIIgyhRy2AiCIAiCIAiCIMoUctgIgiAIgiAIgiDKFHLYCIIgCGIPI51OY3Bw0FcZBEFAX1+frzIQBEHsDZDDRhAEQZQdDz74IDiOs/zvF7/4hXKN73//+4hGo1i5cqWPf4m73H///Zg2bRoqKyvx7W9/21dZ7r33XgwbNgwtLS245JJLkEwmfZWHIAhiqBLyWwCCIAiCKGTevHm44447IAhC3vEdO3bghhtuwIUXXojJkycXve+YY45Rfn7ppZeQSqXw1ltvYf78+Z7L7DX/+7//i5///Oc444wzcOGFF2LevHm+yvOd73wH1dXVeP/993H77bfjnXfewYsvvgiO43yViyAIYqjBCYXfhgRBEARRpmzYsAGTJ0/G6tWrMXfuXMNzb7jhBjz++OO4++67cdhhh5VGQI/o6enB2LFjceONN+LCCy/0W5wi3nvvPcycOROrVq3CUUcd5bc4BEEQQwpKiSQIgiCGJD//+c/x3nvv7fHOGgA8/fTTCIVC+OEPf+i3KJrMmDEDxx13HB588EG/RSEIghhykMNGEARBEGXO1q1bceCBB6KiosJvUXSZNWsW2tra/BaDIAhiyEEOG0EQBDEk+de//oWJEyeC5/mi1yZNmoTnn38eDzzwAGbMmIFYLAaO4zBy5Eh861vfwoYNGwAAf//73/GlL30Jw4YNA8dxqK2txezZs/Hwww/rfq4gCPjb3/6GuXPnorm5WSmIEg6HMWXKFJx00kn4+OOPLf0tHR0dGDVqlO7r//znPzFhwgTwPI9nn30Wxx9/PBoaGhAMBhGNRrH//vvj9NNPx6effqp7jQcffBAzZsxARUVFUTGX+vp6fPe730VHR4fu+0eNGmX4OkEQBGEPKjpCEARBDEna2tqwadMm8DyPQCB/fXLjxo34xS9+gbVr1+K73/0uzjjjDEQiEWzZsgV/+tOfcOSRR+L3v/89Fi5ciOOPPx7HHXccRowYgd27d2PlypU47bTTkMlksGjRoqLPveGGG3DdddfhyCOPxPe+9z3U19cjEAggnU6jvb0dTz/9NGbMmIFVq1bhiCOOYPpbent7UV1drft6e3s7Pv30UyxZsgRLly7Fcccdh+9///sYPXo0eJ5HW1sbHnvsMRxwwAF46623MG3atLz3v/TSS1i0aBEWLlyIM844A7FYTHlNEAR88skneOyxx3DaaafhpZde0pRh2LBhiMfjTH8PQRAEwQ45bARBEMReydq1a/Hxxx+jvr4+7/jZZ5+NAw44AN/61rewbNkynHXWWXmvX3XVVTjyyCNx6623FjlsHR0duPnmm3H55Zfjl7/8pWbFxF/84hc4+uijcfnll+ONN95glpel+uKzzz6LTZs2obm5uei1//u//8Ps2bNxxRVX4Jlnnsl7bfny5TjooIPw+OOP637OvHnzcNJJJ6G9vR1jxoyxJR9BEARhHUqJJAiCIPZK5OhXIfvttx9mz56NkSNH4swzzyx6PRgM4vTTT8eHH35YlG75xhtvYHBwED/5yU90HZhIJIILL7wQb775Jnbv3u3K3yJzxx13aDprAFBZWYnzzz8fL774YlG7hK1bt2LKlCmGTteCBQvw05/+FDU1Na7KTBAEQRhDDhtBEASxV7Lvvvvqvtbc3Izx48cXpVKqX89kMtixY0fe8c2bN6OqqgqjR482/OwJEyYAAD777DOLUhszZ84cw9dbWlqQSCTw+eef5x2vq6szdR5jsRhuueUWDBs2zKmYBEEQhAUoJZIgCILYK6msrNR9raKiwvR1ABgYGMg73tPTg+rqatNqiclkEgCKHD6nBINBw9dlZ6unpyeviMkRRxyBCy64AA8++CAOO+wwRKPRvPfV1dUZjgdBEAThHeSwEQRBEISLdHV1YezYsUznqot7+MnZZ5+NF154QbOIisyUKVNw22234Rvf+EYJJSMIgiDIYSMIgiAIF6mrq8P9999vel4sFiubpt7hcBiPPvooPv30U2zcuBGDg4PKa4IgoKenBw8++CBOPvlkrFu3DuPGjfNRWoIgiL0LctgIgiAIwiXkfm17ahRq33331d3bt3DhQtTV1eGf//wnFi9eXGLJCIIg9l6o6AhBEARBuMS+++6LnTt3or+/3/C8bdu2oaWlBZs2bSqRZMbcddddhk21AaCqqgp1dXXo7OwskVQEQRAEQA4bQRAEQbjGoYceimg0ijvvvNPwvLvvvhvbt29HQ0NDiSQz5tZbb8VvfvMbw3N27dqFzz//XLdtAEEQBOENlBJJEARBEC7R3NyMK664Aj/96U+xevVqpZ9bIBBANptFT08P3njjDaxcuRJXXXUVc+XFUChUVJHSTU455RTceuut2LFjBw4++GClCiYg7mHr7e3F448/jqqqKnz961/XvEY6nUYoRGYFQRCE29CTlSAIgthjGDlyJJqamtDY2Gh67pgxY7Dvvvtq9lKbOHEixowZo/velpYWQ+ejoaEBo0ePxvDhw4teu+6663DQQQfht7/9Le677z50dHQAAAKBAEaNGoUpU6bgj3/8I773ve+Z/g3qz3vzzTd1X29qatL9W9WMHj0ao0ePRl1dXd7x66+/HgDwl7/8BY888giy2Wze6yNGjMBBBx2Ev//977o95rZv3840LwRBEIQ1OEEQBL+FIAiCIAhCn7vuugu33norNmzYAI7j/BZHkx/84Afo7+/Hww8/7LcoBEEQQwraw0YQBEEQZc5RRx2FTz/9FP/617/8FkWTXbt24a9//SvmzZvntygEQRBDDoqwEQRBEMQewCmnnIK///3v+N///V8cdthhOPDAA1FVVeWbPDzP48MPP8THH3+Mn/3sZ+jt7cWmTZvKphk4QRDEUIEibARBEASxB/DHP/4Rp512Gi6++GIcdthhOPnkk32V595778VBBx2EU089FSNHjsR//vMfctYIgiA8gCJsBEEQBLEHkUgksG7dOtTU1GDSpEm+yRGPx/H+++9j6tSpGDVqlG9yEARBDHXIYSMIgiAIgiAIgihTKCWSIAiCIAiCIAiiTCGHjSAIgiAIgiAIokwhh40gCIIgCIIgCKJMIYeNIAiCIAiCIAiiTCGHjSAIgiAIgiAIokwhh40gCIIgCIIgCKJMIYeNIAiCIAiCIAiiTCGHjSAIgiAIgiAIokz5/1vERkep5Fh3AAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 1000x621 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "r = readout_module.get_acquisitions(0)[\"single\"][\"acquisition\"][\"scope\"]\n",
    "plt.plot(r[\"path0\"][\"data\"], \".-\")\n",
    "plt.plot(r[\"path1\"][\"data\"], \".-\")\n",
    "plt.axvline(tof_measured, c=\"k\")\n",
    "plt.xlim(\n",
    "    tof_measured - 10 / readout_module.sequencer0.nco_freq() * 1e9,\n",
    "    tof_measured + 10 / readout_module.sequencer0.nco_freq() * 1e9,\n",
    ")\n",
    "plt.ylabel(\"Amplitude (V)\")\n",
    "plt.xlabel(\"Time (ns)\")\n",
    "plt.show()\n",
    "\n",
    "plt.plot(r[\"path0\"][\"data\"], \".-\")\n",
    "plt.plot(r[\"path1\"][\"data\"], \".-\")\n",
    "plt.axvline(1024 + tof_measured, c=\"k\")\n",
    "plt.xlim(\n",
    "    1024 + tof_measured - 10 / readout_module.sequencer0.nco_freq() * 1e9,\n",
    "    1024 + tof_measured + 10 / readout_module.sequencer0.nco_freq() * 1e9,\n",
    ")\n",
    "plt.ylabel(\"Amplitude (V)\")\n",
    "plt.xlabel(\"Time (ns)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "5b006317",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.421594Z",
     "iopub.status.busy": "2025-05-07T16:50:55.421440Z",
     "iopub.status.idle": "2025-05-07T16:50:55.424506Z",
     "shell.execute_reply": "2025-05-07T16:50:55.424006Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Measured TOF: 149.33333333333334\n",
      "Rounded TOF:  149\n"
     ]
    }
   ],
   "source": [
    "tof = int(tof_measured)  # time of flight must be an integer\n",
    "print(\"Measured TOF:\", tof_measured)\n",
    "print(\"Rounded TOF: \", tof)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "98eb1666",
   "metadata": {},
   "source": [
    "## Measure qubit histogram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7d0dc832",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.425834Z",
     "iopub.status.busy": "2025-05-07T16:50:55.425689Z",
     "iopub.status.idle": "2025-05-07T16:50:55.428158Z",
     "shell.execute_reply": "2025-05-07T16:50:55.427694Z"
    }
   },
   "outputs": [],
   "source": [
    "prog = f\"\"\"\n",
    "    move 0, R0\n",
    "    start: set_mrk 1\n",
    "    play 2, 3, {tof}\n",
    "    acquire 0, R0, 120\n",
    "    play 4, 5, {tof}\n",
    "    acquire 1, R0, 120\n",
    "    add R0, 1, R0\n",
    "    wait 4000\n",
    "    jlt R0, 1024, @start\n",
    "    set_mrk 0\n",
    "    upd_param 4\n",
    "    stop\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "94095dae",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.429511Z",
     "iopub.status.busy": "2025-05-07T16:50:55.429356Z",
     "iopub.status.idle": "2025-05-07T16:50:55.512290Z",
     "shell.execute_reply": "2025-05-07T16:50:55.511772Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.sequence(\n",
    "    {\"waveforms\": waveforms, \"program\": prog, \"acquisitions\": acquisitions, \"weights\": {}}\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "2aa8f314",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.513945Z",
     "iopub.status.busy": "2025-05-07T16:50:55.513793Z",
     "iopub.status.idle": "2025-05-07T16:50:55.547122Z",
     "shell.execute_reply": "2025-05-07T16:50:55.546593Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, State: STOPPED, Info Flags: ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n"
     ]
    }
   ],
   "source": [
    "readout_module.sequencer0.arm_sequencer()\n",
    "readout_module.sequencer0.start_sequencer()\n",
    "print(readout_module.sequencer0.get_sequencer_status(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "feddde92",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.548545Z",
     "iopub.status.busy": "2025-05-07T16:50:55.548397Z",
     "iopub.status.idle": "2025-05-07T16:50:55.563960Z",
     "shell.execute_reply": "2025-05-07T16:50:55.563494Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.get_acquisition_status(1)\n",
    "data = readout_module.sequencer0.get_acquisitions()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "c1e92091",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.565538Z",
     "iopub.status.busy": "2025-05-07T16:50:55.565378Z",
     "iopub.status.idle": "2025-05-07T16:50:55.568822Z",
     "shell.execute_reply": "2025-05-07T16:50:55.568347Z"
    }
   },
   "outputs": [],
   "source": [
    "state0 = np.array(data[\"state0\"][\"acquisition\"][\"bins\"][\"integration\"][\"path0\"]) + 1j * np.array(\n",
    "    data[\"state0\"][\"acquisition\"][\"bins\"][\"integration\"][\"path1\"]\n",
    ")\n",
    "state1 = np.array(data[\"state1\"][\"acquisition\"][\"bins\"][\"integration\"][\"path0\"]) + 1j * np.array(\n",
    "    data[\"state1\"][\"acquisition\"][\"bins\"][\"integration\"][\"path1\"]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e3bdaa9",
   "metadata": {},
   "source": [
    "Given this data, we can now determine the rotation and thresholding values to discriminate the $\\left|0\\right\\rangle$ state from the $\\left|1\\right\\rangle$ state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "dea07e6b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.570313Z",
     "iopub.status.busy": "2025-05-07T16:50:55.570059Z",
     "iopub.status.idle": "2025-05-07T16:50:55.572968Z",
     "shell.execute_reply": "2025-05-07T16:50:55.572502Z"
    }
   },
   "outputs": [],
   "source": [
    "rotation = np.mod(-np.angle(np.mean(state1) - np.mean(state0)), 2 * np.pi)\n",
    "threshold = (np.exp(1j * rotation) * (np.mean(state1) + np.mean(state0))).real / 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "aeccd815",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.574510Z",
     "iopub.status.busy": "2025-05-07T16:50:55.574246Z",
     "iopub.status.idle": "2025-05-07T16:50:55.735340Z",
     "shell.execute_reply": "2025-05-07T16:50:55.734761Z"
    },
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x621 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "scaling = 1000 / integration_length\n",
    "maxr = max(np.max(np.abs(state0)), np.max(np.abs(state1))) * scaling\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "cmap_blue = colors.LinearSegmentedColormap.from_list(\"qblox\", [\"#00839F00\", \"#00839FFF\"])\n",
    "cmap_red = colors.LinearSegmentedColormap.from_list(\"qblox_red\", [\"#F2300000\", \"#F23000FF\"])\n",
    "ax.hexbin(state0.real * scaling, state0.imag * scaling, cmap=cmap_blue)\n",
    "ax.hexbin(state1.real * scaling, state1.imag * scaling, cmap=cmap_red)\n",
    "\n",
    "if not np.isnan(threshold):\n",
    "    ax.set_xlim(-maxr, maxr)\n",
    "    ax.set_ylim(-maxr, maxr)\n",
    "ax.plot(\n",
    "    ((1j * np.linspace(-maxr, maxr, 100) + threshold) * np.exp(-1j * rotation)).real * scaling,\n",
    "    ((1j * np.linspace(-maxr, maxr, 100) + threshold) * np.exp(-1j * rotation)).imag * scaling,\n",
    "    \"k\",\n",
    ")\n",
    "ax.set_xlabel(\"I (mV)\")\n",
    "ax.set_ylabel(\"Q (mV)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "0cd1e80d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.736829Z",
     "iopub.status.busy": "2025-05-07T16:50:55.736679Z",
     "iopub.status.idle": "2025-05-07T16:50:55.757193Z",
     "shell.execute_reply": "2025-05-07T16:50:55.756696Z"
    }
   },
   "outputs": [],
   "source": [
    "if not np.isnan(threshold):\n",
    "    readout_module.sequencer0.thresholded_acq_threshold(threshold)\n",
    "    readout_module.sequencer0.thresholded_acq_rotation(rotation * 360 / (2 * np.pi))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b64697c",
   "metadata": {},
   "source": [
    "Now that the rotation and thresholding values are programmed into the QRM module, the module will automatically assign a qubit state to every acquisition. By running the same sequence as before, we can check the the module is assigning the correct state to the qubit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "8af52f49",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.758869Z",
     "iopub.status.busy": "2025-05-07T16:50:55.758723Z",
     "iopub.status.idle": "2025-05-07T16:50:55.794510Z",
     "shell.execute_reply": "2025-05-07T16:50:55.793932Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, State: STOPPED, Info Flags: ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n"
     ]
    }
   ],
   "source": [
    "readout_module.sequencer0.delete_acquisition_data(all=True)\n",
    "readout_module.sequencer0.arm_sequencer()\n",
    "readout_module.sequencer0.start_sequencer()\n",
    "print(readout_module.sequencer0.get_sequencer_status(1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "94d399b0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.795909Z",
     "iopub.status.busy": "2025-05-07T16:50:55.795765Z",
     "iopub.status.idle": "2025-05-07T16:50:55.811860Z",
     "shell.execute_reply": "2025-05-07T16:50:55.811345Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.get_acquisition_status(1)\n",
    "data = readout_module.sequencer0.get_acquisitions()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c82c147e",
   "metadata": {},
   "source": [
    "To check that the assignments are made correctly, we calculate the confusion matrix."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "33585051",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.813471Z",
     "iopub.status.busy": "2025-05-07T16:50:55.813319Z",
     "iopub.status.idle": "2025-05-07T16:50:55.816906Z",
     "shell.execute_reply": "2025-05-07T16:50:55.816413Z"
    }
   },
   "outputs": [],
   "source": [
    "confusion_matrix = [\n",
    "    [\n",
    "        np.sum(np.array(data[\"state0\"][\"acquisition\"][\"bins\"][\"threshold\"]) == 0),\n",
    "        np.sum(np.array(data[\"state0\"][\"acquisition\"][\"bins\"][\"threshold\"]) == 1),\n",
    "    ],\n",
    "    [\n",
    "        np.sum(np.array(data[\"state1\"][\"acquisition\"][\"bins\"][\"threshold\"]) == 0),\n",
    "        np.sum(np.array(data[\"state1\"][\"acquisition\"][\"bins\"][\"threshold\"]) == 1),\n",
    "    ],\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "c358694c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.818332Z",
     "iopub.status.busy": "2025-05-07T16:50:55.818186Z",
     "iopub.status.idle": "2025-05-07T16:50:55.876736Z",
     "shell.execute_reply": "2025-05-07T16:50:55.876140Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 621x621 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "p = plt.matshow(confusion_matrix, cmap=\"Blues\", vmin=0, vmax=1024)\n",
    "ax = plt.gca()\n",
    "for i in [0, 1]:\n",
    "    for j in [0, 1]:\n",
    "        ax.annotate(\n",
    "            confusion_matrix[i][j],\n",
    "            xy=(j, i),\n",
    "            horizontalalignment=\"center\",\n",
    "            verticalalignment=\"center\",\n",
    "            color=p.cmap(1024 - confusion_matrix[i][j]),\n",
    "        )\n",
    "plt.xlabel(\"Assigned state\")\n",
    "plt.ylabel(\"Qubit state\")\n",
    "plt.xticks([0, 1], [\"|0>\", \"|1>\"])\n",
    "plt.yticks([0, 1], [\"|0>\", \"|1>\"])\n",
    "ax.xaxis.set_ticks_position(\"bottom\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "783122d8",
   "metadata": {},
   "source": [
    "## Sending results on the trigger network"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fb2039e",
   "metadata": {},
   "source": [
    "Now that the module can correctly identify the qubit state, we want to send this result to all other modules in the Cluster. Hence we must enable this functionality and specify an address used for sending these triggers. In this tutorial, we will only use address 1. Note that only one trigger can be sent simultaneously, even if the address is different."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "246f0190",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.878280Z",
     "iopub.status.busy": "2025-05-07T16:50:55.878129Z",
     "iopub.status.idle": "2025-05-07T16:50:55.898902Z",
     "shell.execute_reply": "2025-05-07T16:50:55.898414Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.thresholded_acq_trigger_address(1)\n",
    "readout_module.sequencer0.thresholded_acq_trigger_en(True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e2a7784f",
   "metadata": {},
   "source": [
    "To verify that the correct triggers are being sent, we can use the trigger monitor. This monitor can be reset with the following command:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "8f5b15ab",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.900524Z",
     "iopub.status.busy": "2025-05-07T16:50:55.900364Z",
     "iopub.status.idle": "2025-05-07T16:50:55.903213Z",
     "shell.execute_reply": "2025-05-07T16:50:55.902686Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster.reset_trigger_monitor_count(address=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7104fb49",
   "metadata": {},
   "source": [
    "Such that the monitor reports both a total trigger count of 0 and no latest trigger (also represented by the value 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "321d09bf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.904636Z",
     "iopub.status.busy": "2025-05-07T16:50:55.904489Z",
     "iopub.status.idle": "2025-05-07T16:50:55.909213Z",
     "shell.execute_reply": "2025-05-07T16:50:55.908718Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0, 0)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster.trigger1_monitor_count(), cluster.trigger_monitor_latest()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2472b9c",
   "metadata": {},
   "source": [
    "Now, to verify the Cluster is configured correctly, let us run the above program one more time:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "7371f180",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.910728Z",
     "iopub.status.busy": "2025-05-07T16:50:55.910580Z",
     "iopub.status.idle": "2025-05-07T16:50:55.959859Z",
     "shell.execute_reply": "2025-05-07T16:50:55.959297Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.delete_acquisition_data(all=True)\n",
    "readout_module.sequencer0.arm_sequencer()\n",
    "readout_module.sequencer0.start_sequencer()\n",
    "readout_module.sequencer0.get_sequencer_status(1)\n",
    "readout_module.sequencer0.get_acquisition_status(1)\n",
    "data = readout_module.sequencer0.get_acquisitions()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a64e0ad",
   "metadata": {},
   "source": [
    "The number of triggers received by the monitor should be equal to the number of measurements that have been classified as the $\\left|1\\right\\rangle$ state."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "7d656714",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.961538Z",
     "iopub.status.busy": "2025-05-07T16:50:55.961378Z",
     "iopub.status.idle": "2025-05-07T16:50:55.965545Z",
     "shell.execute_reply": "2025-05-07T16:50:55.965019Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Acquisition: 1024\n",
      "Monitor:     1024\n"
     ]
    }
   ],
   "source": [
    "print(\n",
    "    \"Acquisition:\",\n",
    "    np.sum(np.array(data[\"state0\"][\"acquisition\"][\"bins\"][\"threshold\"]) == 1)\n",
    "    + np.sum(np.array(data[\"state1\"][\"acquisition\"][\"bins\"][\"threshold\"]) == 1),\n",
    ")\n",
    "print(\"Monitor:    \", cluster.trigger1_monitor_count())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d62fbee7",
   "metadata": {},
   "source": [
    "The most recent trigger that has been received should now be equal to 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "8f1ae113",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.967289Z",
     "iopub.status.busy": "2025-05-07T16:50:55.967009Z",
     "iopub.status.idle": "2025-05-07T16:50:55.970925Z",
     "shell.execute_reply": "2025-05-07T16:50:55.970410Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cluster.trigger_monitor_latest()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c007105",
   "metadata": {},
   "source": [
    "Besides investigating the sent triggers using this monitor, it can be convenient to visualize the triggers on an oscilloscope as they are being sent. In order the enable sending the trigger on marker 4, use the following commands. Enabling triggers on the marker outputs can also be used to control external equipment based on the measurement results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "c3f97236",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.972755Z",
     "iopub.status.busy": "2025-05-07T16:50:55.972607Z",
     "iopub.status.idle": "2025-05-07T16:50:55.993680Z",
     "shell.execute_reply": "2025-05-07T16:50:55.992782Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.thresholded_acq_marker_en(True)\n",
    "readout_module.sequencer0.thresholded_acq_marker_address(8)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2eb19b9",
   "metadata": {},
   "source": [
    "Now connect your marker output 4 to the oscilloscope and run the following cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "2253c5a2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:55.996275Z",
     "iopub.status.busy": "2025-05-07T16:50:55.995893Z",
     "iopub.status.idle": "2025-05-07T16:50:56.004667Z",
     "shell.execute_reply": "2025-05-07T16:50:56.003804Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.sequencer0.arm_sequencer()\n",
    "readout_module.sequencer0.start_sequencer()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "946dc02c",
   "metadata": {},
   "source": [
    "The following image can be obtained on the oscilloscope (C1 (yellow) is the marker 1 output whereas C3(blue) is marker 4 output:"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "127f5fae",
   "metadata": {},
   "source": [
    "![SDS6204A_PNG_5 (2).png](figures/9d786b40-430b-47ab-9721-94f3e25fd196.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84a62d64",
   "metadata": {},
   "source": [
    "## Active reset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "67b2c9d7",
   "metadata": {},
   "source": [
    "As the final part of this tutorial, we will show how the triggers we have been generating above, can be used to affect the behavior of other sequencers in the Cluster. We will show this capability using a active reset protocol as an example. Basically, in order to perform active reset on a qubit, we must first measure the qubit state, and if the state equals $\\left|1\\right\\rangle$, we must play a $\\pi$-pulse to flip the qubit back to the $\\left|0\\right\\rangle$ state."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "82f7eb7c",
   "metadata": {},
   "source": [
    "In a real qubit setup, the QRM would play identical readout pulses and the actual qubit state would influence the acquisition result. For this tutorial, in lieu of a qubit, we determine the qubit state results in advance for the QRM, and play a different waveform depending on this pre-determined state. To still properly demonstrate the feedback capability, we ensure that the QCM is not aware of the pre-determined choices in advance, as it can figure out from the acquisitions results whether it should play a $\\pi$-pulse."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4571c145",
   "metadata": {},
   "source": [
    "Generate 100 random qubit states:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "fc5bcdc1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:56.007896Z",
     "iopub.status.busy": "2025-05-07T16:50:56.007147Z",
     "iopub.status.idle": "2025-05-07T16:50:56.014385Z",
     "shell.execute_reply": "2025-05-07T16:50:56.013552Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1,\n",
       "       0, 1, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0,\n",
       "       0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1,\n",
       "       0, 0, 0, 1, 0, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 1, 1,\n",
       "       0, 1, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "length = 100\n",
    "states = np.random.choice(2, length)\n",
    "states"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a7894400",
   "metadata": {},
   "source": [
    "For the QRM program, this means playing waveforms `'state0_I'` and `'state0_Q'` if the qubit state has to appear as $\\left|0\\right\\rangle$ while playing waveforms `'state1_I'` and `'state1_Q'` if the qubit state has to appear as $\\left|1\\right\\rangle$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "69d3d8f4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:56.016815Z",
     "iopub.status.busy": "2025-05-07T16:50:56.016443Z",
     "iopub.status.idle": "2025-05-07T16:50:56.021809Z",
     "shell.execute_reply": "2025-05-07T16:50:56.020944Z"
    }
   },
   "outputs": [],
   "source": [
    "qrm_prog = \"\"\"\n",
    "wait_sync 4\n",
    "set_mrk 1\n",
    "upd_param 1000\n",
    "move 0, R0\n",
    "\"\"\"\n",
    "for s in states:\n",
    "    if s == 1:\n",
    "        qrm_prog += f\"\"\"set_mrk 3\n",
    "        play 4, 5, {tof}\n",
    "        set_mrk 1\"\"\"\n",
    "    else:\n",
    "        qrm_prog += f\"play 2, 3, {tof}\"\n",
    "    qrm_prog += \"\"\"\n",
    "    acquire 0, R0, 120\n",
    "    wait 1000\n",
    "    \"\"\"\n",
    "qrm_prog += \"\"\"set_mrk 0\n",
    "upd_param 1000\n",
    "stop\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3258faca",
   "metadata": {},
   "source": [
    "So, in order to achieve feedback from the QRM module, we only had to set the thresholding and trigger parameters without any changes to the Q1ASM program. On the receiving side, for the QCM, the feedback is controlled via Q1ASM, however. Let's build up the program step by step."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "276da7ef",
   "metadata": {},
   "source": [
    "First, we need to tell the module to listen for triggers on address 1 with:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "654773f3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:56.024494Z",
     "iopub.status.busy": "2025-05-07T16:50:56.023878Z",
     "iopub.status.idle": "2025-05-07T16:50:56.027954Z",
     "shell.execute_reply": "2025-05-07T16:50:56.027093Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog = \"set_latch_en 1, 4     # Enabling listening to triggers on address 1\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0e1e3336",
   "metadata": {},
   "source": [
    "We can then sync with the other module and program our loop:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "b2634f7d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:56.030673Z",
     "iopub.status.busy": "2025-05-07T16:50:56.030012Z",
     "iopub.status.idle": "2025-05-07T16:50:56.034538Z",
     "shell.execute_reply": "2025-05-07T16:50:56.033731Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog += f\"\"\"\n",
    "wait_sync 4\n",
    "wait 1000\n",
    "move {len(states)}, R0\n",
    "s:\n",
    "\"\"\"\n",
    "# Here we need to write the code to receive and react to triggers\n",
    "# Therefore, we store then end of the program in a separate variable for now\n",
    "qcm_prog_tail = \"\"\"\n",
    "loop R0, @s\n",
    "stop\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e96ace5b",
   "metadata": {},
   "source": [
    "For every iteration of our loop, we first need to clear any received triggers and then wait for any new trigger to come in:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "500e0a62",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:56.036963Z",
     "iopub.status.busy": "2025-05-07T16:50:56.036599Z",
     "iopub.status.idle": "2025-05-07T16:50:56.040524Z",
     "shell.execute_reply": "2025-05-07T16:50:56.039684Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog += f\"\"\"\n",
    "latch_rst {tof + 120}   # Deletes all previously received triggers\n",
    "wait      300         # gives the acquisition result time to be received by the QCM\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "286db37b",
   "metadata": {},
   "source": [
    "Next, we program a conditional play instruction. In order to mark a `play`, `acquire`, `acquire_weighed` or `wait` instruction as conditional, we open a conditionality block using the `set_cond <enable> <address_mask> <operator> <else_wait>` instruction.\n",
    "\n",
    "The `<enable>` argument sets whether subsequent real-time pipeline instructions are conditional or not. In case a conditional instruction is skipped, the `<else_wait>` argument determines how long the real-time pipeline will stall (minimum is 4 ns).\n",
    "\n",
    "The `<address_mask>` and `<operator>` determine the conditionality, if the condition evaluates to `True` the instruction es executed, otherwise the instruction will be skipped (equivalent to a `wait <else_wait>` instruction).\n",
    "\n",
    "When only listening to a single trigger address, the `<address mask>` should be made equal to `2**(address-1)` and the `<operator>` should be `0` for `OR` or `2` for `AND` (both having the same effect for a single input, feedback based on multiple trigger addresses is not covered in this tutorial). To invert the conditional, `<operator>` `1` for `NOR` or `3` for `NAND` can be used.\n",
    "\n",
    "For active reset, we can enable the conditional with:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "d999e565",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:56.043343Z",
     "iopub.status.busy": "2025-05-07T16:50:56.042728Z",
     "iopub.status.idle": "2025-05-07T16:50:56.046634Z",
     "shell.execute_reply": "2025-05-07T16:50:56.045803Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog += \"\"\"\n",
    "set_cond 1, 1, 0, 700 # Enable conditional commands\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d59dab9",
   "metadata": {},
   "source": [
    "Next we can invoke our play command as usual:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "48ba140b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:56.049439Z",
     "iopub.status.busy": "2025-05-07T16:50:56.048806Z",
     "iopub.status.idle": "2025-05-07T16:50:56.052797Z",
     "shell.execute_reply": "2025-05-07T16:50:56.051956Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog += \"play 6, 7, 700\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "af23a375",
   "metadata": {},
   "source": [
    "Finally, do not forget to disable the conditional commands again (after the first `0`, the parameters do not matter):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "c396f391",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:56.055592Z",
     "iopub.status.busy": "2025-05-07T16:50:56.054822Z",
     "iopub.status.idle": "2025-05-07T16:50:56.058918Z",
     "shell.execute_reply": "2025-05-07T16:50:56.058079Z"
    }
   },
   "outputs": [],
   "source": [
    "qcm_prog += (\n",
    "    \"\"\"\n",
    "set_cond 0, 1, 0, 700 # Disable conditional commands again\n",
    "\"\"\"\n",
    "    + qcm_prog_tail\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eea94bb8",
   "metadata": {},
   "source": [
    "In summary, the complete QCM program is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "a751fde4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:56.061551Z",
     "iopub.status.busy": "2025-05-07T16:50:56.060924Z",
     "iopub.status.idle": "2025-05-07T16:50:56.065230Z",
     "shell.execute_reply": "2025-05-07T16:50:56.064437Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "set_latch_en 1, 4     # Enabling listening to triggers on address 1\n",
      "wait_sync 4\n",
      "wait 1000\n",
      "move 100, R0\n",
      "s:\n",
      "\n",
      "latch_rst 269   # Deletes all previously received triggers\n",
      "wait      300         # gives the acquisition result time to be received by the QCM\n",
      "\n",
      "set_cond 1, 1, 0, 700 # Enable conditional commands\n",
      "play 6, 7, 700\n",
      "set_cond 0, 1, 0, 700 # Disable conditional commands again\n",
      "\n",
      "loop R0, @s\n",
      "stop\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(qcm_prog)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "4f7596bb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:56.067492Z",
     "iopub.status.busy": "2025-05-07T16:50:56.066901Z",
     "iopub.status.idle": "2025-05-07T16:50:56.244521Z",
     "shell.execute_reply": "2025-05-07T16:50:56.243560Z"
    }
   },
   "outputs": [],
   "source": [
    "control_module.sequencer1.sync_en(True)  # We did not enable the sync on the QCM sequencer yet\n",
    "\n",
    "readout_module.sequencer0.sequence(\n",
    "    {\"waveforms\": waveforms, \"program\": qrm_prog, \"acquisitions\": acquisitions, \"weights\": {}}\n",
    ")\n",
    "readout_module.sequencer0.arm_sequencer()\n",
    "\n",
    "control_module.sequencer1.sequence(\n",
    "    {\"waveforms\": waveforms, \"program\": qcm_prog, \"acquisitions\": acquisitions, \"weights\": {}}\n",
    ")\n",
    "control_module.sequencer1.arm_sequencer()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c7bfb8e0",
   "metadata": {},
   "source": [
    "We are all set to witness the conditional playback! Please make sure that you have connected the QCM output 0 to the oscilloscope along with the marker 1 of QRM as trigger and marker 4."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "b3abd5dd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:56.247133Z",
     "iopub.status.busy": "2025-05-07T16:50:56.246743Z",
     "iopub.status.idle": "2025-05-07T16:50:56.256257Z",
     "shell.execute_reply": "2025-05-07T16:50:56.255374Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module.start_sequencer()\n",
    "control_module.start_sequencer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "92c789a3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:56.258972Z",
     "iopub.status.busy": "2025-05-07T16:50:56.258589Z",
     "iopub.status.idle": "2025-05-07T16:50:56.269555Z",
     "shell.execute_reply": "2025-05-07T16:50:56.268664Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "QRM:\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, State: STOPPED, Info Flags: ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n",
      "QCM:\n",
      "Status: OKAY, State: STOPPED, Info Flags: NONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n"
     ]
    }
   ],
   "source": [
    "print(\"QRM:\")\n",
    "print(readout_module.get_sequencer_status(0))\n",
    "print(\"QCM:\")\n",
    "print(control_module.get_sequencer_status(0))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0907c7e3",
   "metadata": {},
   "source": [
    "On the oscilloscope, you should see an image as below (CH1 (yellow) : Marker 1, CH2 (pink): Marker 2, CH3(blue) : QCM Output 0, CH4(green) : Marker 4). Marker 2 activation corresponds to a state 1 signal by QRM which is confirmed by the Marker 4"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0510a4cd",
   "metadata": {},
   "source": [
    "![image.png](figures/5a08cf99-6cfa-49a0-94c7-accea41f8c21.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62934e36",
   "metadata": {},
   "source": [
    "## Stop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "276da1d8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:50:56.272441Z",
     "iopub.status.busy": "2025-05-07T16:50:56.271771Z",
     "iopub.status.idle": "2025-05-07T16:50:58.847116Z",
     "shell.execute_reply": "2025-05-07T16:50:58.846052Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "QCM :\n",
      "Status: OKAY, State: STOPPED, Info Flags: NONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n",
      "\n",
      "QRM :\n",
      "Status: OKAY, State: STOPPED, Info Flags: FORCED_STOP, ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_BINNING_DONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, Flags: NONE, Slot flags: NONE\n"
     ]
    }
   ],
   "source": [
    "# Stop sequencers.\n",
    "control_module.stop_sequencer()\n",
    "readout_module.stop_sequencer()\n",
    "\n",
    "# Print status of sequencers.\n",
    "print(\"QCM :\")\n",
    "print(control_module.get_sequencer_status(0))\n",
    "print()\n",
    "\n",
    "print(\"QRM :\")\n",
    "print(readout_module.get_sequencer_status(0))\n",
    "print()\n",
    "\n",
    "# Reset the cluster\n",
    "cluster.reset()\n",
    "print(cluster.get_system_status())"
   ]
  }
 ],
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