{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2da5d7ea",
   "metadata": {
    "lines_to_next_cell": 0,
    "tags": []
   },
   "source": [
    "Scope acquisition\n",
    "=================\n",
    "\n",
    "\n",
    "The QRM/QRM-RF instruments have high speed analog to digital capability for performing measurements.\n",
    "In this tutorial we will demonstrate the sequencer based scope acquisition procedure allowing you to inspect and process the raw input\n",
    "of the QRM/QRM-RF. We will also have a look at how to average multiple scope acquisitions in hardware (see section [Acquisition](https://docs.qblox.com/en/main/cluster/q1_sequence_processor.html#acquisitions))."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "363ada53",
   "metadata": {
    "tags": [
     "intro"
    ]
   },
   "source": [
    "We will show this by using a QRM and directly connecting outputs $\\text{O}^{[1-2]}$ to inputs $\\text{I}^{[1-2]}$ respectively. We will then use the QRM's sequencers to sequence waveforms on\n",
    "the outputs and simultaneously acquire the resulting waveforms on the inputs. As this tutorial uses waveform generation and acquisition, it will cover usage of `waveforms` and `acquisitions` in the sequence."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ccbaf7c0",
   "metadata": {},
   "source": [
    "As with all operations with QxM instruments, the devices will be controlled by preparing and uploading sequences onto the Q1 processors.\n",
    "For more info on the features, programming and operation of Q1 sequence processor please view [Q1 Sequencer](https://docs.qblox.com/en/main/cluster/q1_sequence_processor.html)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "edde6b4f",
   "metadata": {
    "tags": []
   },
   "source": [
    "Setup\n",
    "-----\n",
    "\n",
    "First, we are going to import the required packages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "74130aa4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:20.832181Z",
     "iopub.status.busy": "2025-05-07T16:53:20.831768Z",
     "iopub.status.idle": "2025-05-07T16:53:21.701364Z",
     "shell.execute_reply": "2025-05-07T16:53:21.700633Z"
    },
    "tags": [
     "imports"
    ]
   },
   "outputs": [],
   "source": [
    "from __future__ import annotations\n",
    "\n",
    "import json\n",
    "import math\n",
    "from typing import TYPE_CHECKING, Callable\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import scipy.signal\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": "6aa07c2c",
   "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": "80b72d45",
   "metadata": {},
   "source": [
    "`!qblox-pnp list`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f940b951",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:21.704648Z",
     "iopub.status.busy": "2025-05-07T16:53:21.704476Z",
     "iopub.status.idle": "2025-05-07T16:53:21.707203Z",
     "shell.execute_reply": "2025-05-07T16:53:21.706743Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster_ip = \"10.10.200.42\"\n",
    "cluster_name = \"cluster0\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "106580cf",
   "metadata": {},
   "source": [
    "### Connect to Cluster\n",
    "\n",
    "We now make a connection with the Cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "1ea88baf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:21.708948Z",
     "iopub.status.busy": "2025-05-07T16:53:21.708683Z",
     "iopub.status.idle": "2025-05-07T16:53:22.557658Z",
     "shell.execute_reply": "2025-05-07T16:53:22.556562Z"
    },
    "lines_to_next_cell": 2
   },
   "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",
    "            10: ClusterType.CLUSTER_QTM,\n",
    "        }\n",
    "        if cluster_ip is None\n",
    "        else None\n",
    "    ),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b609fd80",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "#### Get connected modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f1dc15c8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:22.561458Z",
     "iopub.status.busy": "2025-05-07T16:53:22.561175Z",
     "iopub.status.idle": "2025-05-07T16:53:22.565934Z",
     "shell.execute_reply": "2025-05-07T16:53:22.565167Z"
    }
   },
   "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": "783b6613",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:22.569115Z",
     "iopub.status.busy": "2025-05-07T16:53:22.568650Z",
     "iopub.status.idle": "2025-05-07T16:53:22.587277Z",
     "shell.execute_reply": "2025-05-07T16:53:22.586505Z"
    },
    "tags": [
     "module_select"
    ]
   },
   "outputs": [],
   "source": [
    "# QRM baseband modules\n",
    "modules = get_connected_modules(cluster, lambda mod: mod.is_qrm_type and not mod.is_rf_type)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "9563ae78",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:22.590286Z",
     "iopub.status.busy": "2025-05-07T16:53:22.590038Z",
     "iopub.status.idle": "2025-05-07T16:53:22.593628Z",
     "shell.execute_reply": "2025-05-07T16:53:22.592862Z"
    }
   },
   "outputs": [],
   "source": [
    "# This uses the module of the correct type with the lowest slot index\n",
    "module = list(modules.values())[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cc8edad0",
   "metadata": {},
   "source": [
    "### Reset the Cluster\n",
    "\n",
    "We reset the Cluster to enter a well-defined state. Note that resetting will clear all stored parameters, so resetting between experiments is usually not desirable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "064b5979",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:22.596607Z",
     "iopub.status.busy": "2025-05-07T16:53:22.596453Z",
     "iopub.status.idle": "2025-05-07T16:53:25.142522Z",
     "shell.execute_reply": "2025-05-07T16:53:25.141266Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, Flags: NONE, Slot flags: NONE\n"
     ]
    }
   ],
   "source": [
    "cluster.reset()\n",
    "print(cluster.get_system_status())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "b28063db",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.145766Z",
     "iopub.status.busy": "2025-05-07T16:53:25.145563Z",
     "iopub.status.idle": "2025-05-07T16:53:25.149364Z",
     "shell.execute_reply": "2025-05-07T16:53:25.148560Z"
    }
   },
   "outputs": [],
   "source": [
    "readout_module = module"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ddeeebc5",
   "metadata": {},
   "source": [
    "Generate waveforms <a id='gen_wf'></a>\n",
    "------------------\n",
    "\n",
    "Next, we need to create the gaussian and block waveforms for the sequence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "83c2de31",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.152160Z",
     "iopub.status.busy": "2025-05-07T16:53:25.151979Z",
     "iopub.status.idle": "2025-05-07T16:53:25.157050Z",
     "shell.execute_reply": "2025-05-07T16:53:25.156237Z"
    }
   },
   "outputs": [],
   "source": [
    "# Waveform parameters\n",
    "waveform_length = 120  # nanoseconds\n",
    "\n",
    "# Waveform dictionary (data will hold the samples and index will be used to select the waveforms in the instrument).\n",
    "waveforms = {\n",
    "    \"gaussian\": {\n",
    "        \"data\": scipy.signal.windows.gaussian(waveform_length, std=0.12 * waveform_length).tolist(),\n",
    "        \"index\": 0,\n",
    "    },\n",
    "    \"sine\": {\n",
    "        \"data\": [math.sin((2 * math.pi / waveform_length) * i) for i in range(0, waveform_length)],\n",
    "        \"index\": 1,\n",
    "    },\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd457293",
   "metadata": {},
   "source": [
    "Let's plot the waveforms to see what we have created."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "10fb1161",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.160235Z",
     "iopub.status.busy": "2025-05-07T16:53:25.159581Z",
     "iopub.status.idle": "2025-05-07T16:53:25.475126Z",
     "shell.execute_reply": "2025-05-07T16:53:25.474504Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x621 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "time = np.arange(0, max(map(lambda d: len(d[\"data\"]), waveforms.values())), 1)\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "\n",
    "for wf, d in waveforms.items():\n",
    "    ax.plot(time[: len(d[\"data\"])], d[\"data\"], label=wf)\n",
    "\n",
    "ax.legend()\n",
    "ax.grid(alpha=1 / 10)\n",
    "ax.set_ylabel(\"Waveform primitive amplitude\")\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "\n",
    "plt.draw()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "96e20d83",
   "metadata": {},
   "source": [
    "Specify acquisitions\n",
    "--------------------\n",
    "\n",
    "We also need to specify the acquisitions so that the instrument can allocate the required memory for it's acquisition list. In this case we will create 5 acquisition specifications that\n",
    "each create a single bin. However, we will not be using the bins in this tutorial."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "74482714",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.476749Z",
     "iopub.status.busy": "2025-05-07T16:53:25.476585Z",
     "iopub.status.idle": "2025-05-07T16:53:25.480056Z",
     "shell.execute_reply": "2025-05-07T16:53:25.479540Z"
    }
   },
   "outputs": [],
   "source": [
    "# Acquisitions\n",
    "acquisitions = {\n",
    "    \"single\": {\"num_bins\": 1, \"index\": 0},\n",
    "    \"multiple_0\": {\"num_bins\": 1, \"index\": 1},\n",
    "    \"multiple_1\": {\"num_bins\": 1, \"index\": 2},\n",
    "    \"multiple_2\": {\"num_bins\": 1, \"index\": 3},\n",
    "    \"avg\": {\"num_bins\": 1, \"index\": 4},\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7de4ca27",
   "metadata": {},
   "source": [
    "Create Q1ASM program\n",
    "--------------------\n",
    "\n",
    "Now that we have the waveforms and acquisitions specification for the sequence, we need a simple Q1ASM program that sequences and acquires the waveforms.\n",
    "For a reference of available commands with Q1ASM please visit [Q1 Sequencer](https://docs.qblox.com/en/main/cluster/q1_sequence_processor.html). Note how the Q1ASM references the JSON structures stored in the JSON file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "0706c696",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.481534Z",
     "iopub.status.busy": "2025-05-07T16:53:25.481227Z",
     "iopub.status.idle": "2025-05-07T16:53:25.484080Z",
     "shell.execute_reply": "2025-05-07T16:53:25.483512Z"
    }
   },
   "outputs": [],
   "source": [
    "# Sequence program.\n",
    "seq_prog = \"\"\"\n",
    "play    0,1,4     #Play waveforms and wait 4ns. Parameters: waveform index (from dict) on path 0, waveform index (from dict) on path 1, wait (in ns)\n",
    "acquire 0,0,16380 #Acquire waveforms and wait remaining duration of scope acquisition. Parameters: acquisition index (from dict), data bin, Duration of acq (in ns)\n",
    "stop              #Stop.\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cff53ff1",
   "metadata": {},
   "source": [
    "Create and Upload sequence\n",
    "--------------------------\n",
    "\n",
    "Now that we have the waveform and acquisition specifications and Q1ASM program, we can combine them in a sequence stored in a JSON file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "aa65a647",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.485652Z",
     "iopub.status.busy": "2025-05-07T16:53:25.485263Z",
     "iopub.status.idle": "2025-05-07T16:53:25.513084Z",
     "shell.execute_reply": "2025-05-07T16:53:25.512283Z"
    }
   },
   "outputs": [],
   "source": [
    "# Add sequence to single dictionary and write to JSON file.\n",
    "sequence = {\n",
    "    \"waveforms\": waveforms,\n",
    "    \"weights\": {},\n",
    "    \"acquisitions\": acquisitions,\n",
    "    \"program\": seq_prog,\n",
    "}\n",
    "with open(\"sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(sequence, file, indent=4)\n",
    "    file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac423ab9",
   "metadata": {},
   "source": [
    "Let's write the JSON file to the instruments. We will use sequencer 0, which will drive outputs $\\text{O}^{[1-2]}$ and acquire on inputs $\\text{I}^{[1-2]}$."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f4863d0f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.514601Z",
     "iopub.status.busy": "2025-05-07T16:53:25.514453Z",
     "iopub.status.idle": "2025-05-07T16:53:25.565270Z",
     "shell.execute_reply": "2025-05-07T16:53:25.564395Z"
    }
   },
   "outputs": [],
   "source": [
    "# Upload sequence.\n",
    "readout_module.sequencer0.sequence(\"sequence.json\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b4209d07",
   "metadata": {},
   "source": [
    "Connect sequencer\n",
    "-----------------\n",
    "\n",
    "First we disable all sequencer connections and then map sequencer to specific outputs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d5a2ee1e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.567475Z",
     "iopub.status.busy": "2025-05-07T16:53:25.567040Z",
     "iopub.status.idle": "2025-05-07T16:53:25.599419Z",
     "shell.execute_reply": "2025-05-07T16:53:25.598560Z"
    },
    "lines_to_next_cell": 0
   },
   "outputs": [],
   "source": [
    "readout_module.disconnect_outputs()\n",
    "readout_module.disconnect_inputs()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "572b17b9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.601868Z",
     "iopub.status.busy": "2025-05-07T16:53:25.601581Z",
     "iopub.status.idle": "2025-05-07T16:53:25.614986Z",
     "shell.execute_reply": "2025-05-07T16:53:25.614032Z"
    },
    "tags": [
     "connect"
    ]
   },
   "outputs": [],
   "source": [
    "module.sequencer0.connect_sequencer(\"io0_1\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7e1c0224",
   "metadata": {},
   "source": [
    "Play sequence\n",
    "-------------\n",
    "\n",
    "The sequence has been uploaded to the instrument. Now we need to configure the sequencers to trigger the acquisition with the `acquire` instruction."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "b8820627",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.617672Z",
     "iopub.status.busy": "2025-05-07T16:53:25.617370Z",
     "iopub.status.idle": "2025-05-07T16:53:25.635343Z",
     "shell.execute_reply": "2025-05-07T16:53:25.634504Z"
    },
    "lines_to_next_cell": 2
   },
   "outputs": [],
   "source": [
    "# Configure the sequencer to trigger the scope acquisition.\n",
    "readout_module.scope_acq_sequencer_select(0)\n",
    "readout_module.scope_acq_trigger_mode_path0(\"sequencer\")\n",
    "readout_module.scope_acq_trigger_mode_path1(\"sequencer\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "24e8f676",
   "metadata": {},
   "source": [
    "Now let's start the sequence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "45d85f39",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.637852Z",
     "iopub.status.busy": "2025-05-07T16:53:25.637565Z",
     "iopub.status.idle": "2025-05-07T16:53:25.650309Z",
     "shell.execute_reply": "2025-05-07T16:53:25.649539Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status:\n",
      "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": [
    "# Arm and start sequencer.\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Print status of sequencer.\n",
    "print(\"Status:\")\n",
    "print(readout_module.get_sequencer_status(0))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "279ae244",
   "metadata": {},
   "source": [
    "Retrieve acquisition\n",
    "--------------------\n",
    "\n",
    "The waveforms have now been sequenced on the outputs and acquired on the inputs. Lets make sure that the sequencer has finished it's acquisition and then retrieve the\n",
    "resulting data. The acquisition data is stored in a temporary memory in the instrument's FPGA. We need to first move the data from this memory into the into the\n",
    "instrument's acquisition list. From there we can retrieve it from the instrument."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "9fccf115",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.652845Z",
     "iopub.status.busy": "2025-05-07T16:53:25.652277Z",
     "iopub.status.idle": "2025-05-07T16:53:25.686702Z",
     "shell.execute_reply": "2025-05-07T16:53:25.685838Z"
    }
   },
   "outputs": [],
   "source": [
    "# Wait for the acquisition to finish with a timeout period of one minute.\n",
    "readout_module.get_acquisition_status(0)\n",
    "\n",
    "# Move acquisition data from temporary memory to acquisition list.\n",
    "readout_module.store_scope_acquisition(0, \"single\")\n",
    "\n",
    "# Get acquisition list from instrument.\n",
    "single_acq = readout_module.get_acquisitions(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0eb7d517",
   "metadata": {},
   "source": [
    "Let's plot the result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "da3c090b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.689124Z",
     "iopub.status.busy": "2025-05-07T16:53:25.688836Z",
     "iopub.status.idle": "2025-05-07T16:53:25.814687Z",
     "shell.execute_reply": "2025-05-07T16:53:25.814101Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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G3lj4OwCfXH4+5yZUtzhR8VVxOflmUHeqhrpYnLafYd8vRNupiohUbCrYRKTMc7/9f/h+mQwhoYS99R22pAZWRyqXHB174hr8KAD5z92OPy3V2kAW+GVbOnd+vwCAEV1ac3XzehYnOn0NYqP4csAF2AyDT1Zt4u3f1lkdSURESpEKNhEp0zw/fon7k1cACH3mY+ytz7M4UfnmGvYctpYd4XAmeY9di+lxWx0paNIP53LlxNl4/H6uapbM013PtjrSGbuofgKv9ijcJH74T4uZnbrb4kQiIlJaVLCJSJnlW7+C/GduAcA1+FHttVYCDKeTsJfGQZVo/KsXUvDmw1ZHCgq/aTL4u3nsy82nVVxVPr78fGyGYXWsgDzYoTnXt6iPzzQZ9PVstmUctjqSiIiUAhVsIlIm+Q/tJ294P8jPw97pElz3/NPqSBWGrXY9wp4fDYDn8//g+eFzixOVvreXrOXHLWmEOux83r8b4WVsr7UzYRgG7/fuRNv4auzPLaDf+JnketSERESkolHBJiJljunxkP/oVZi7t2EkNSDspc8x7HarY1UojguuwHXrEwDkP3dbhd6fLWXvIR6Z8RsAr/c8h2Y1YqwNVILCnA4mDbqQGuGhrNhzkNumzFcTEhGRCkYFm4iUOQX//T98S2ZBeBXC3vwWI6qq1ZEqJNew57B36An5ueQ9NAAzO9PqSCUu3+vlum9+ocDnp1fDRO5q19TqSCWuTnQVJgy8AIfN4PPft/L6kQ6YIiJSMahgE5EyxfvbHDyjXwcg9LlPsTdobnGiisuw2wl9cRxGfBLm9o3kjxhc4WZnnpi1jNV7D1EjPJSP+nTGKOfPrZ1I17rxvHVxewAem7mUHzfvsjiRiIiUFBVsIlJmmIezyB8xGEwTZ79bcfYYYHWkCs8WW4Ow1yaA04V31jd4xr5ldaQSM2NrGm8uWgPAR5d3pmaVMIsTla672jVlSOtG+E2TaybNYdPBLKsjiYhICVDBJiJlRsEbD2KmpWIkJBPy0L+sjlNp2Fu0J+QfbwJQMPJxfJvXWJwocLkeL0OnFu63dmfbJvRplGRxotJnGAbvXNaRjrVrkJHv5sZv5+KvYDOmIiKVkQo2ESkTvHMm4/nmQzAMQp/7FKNKlNWRKhXnoGHYO10K7gLyn7oR0+OxOlJAnp+7ki0Z2dSODOeVI/uVVQYhDjvjB15AFZeDhbv28dGKjVZHEhGRAKlgExHL+Q/uI/+52wBw3vgQjnZdLU5U+RiGQeiIDyGqKv61y3B/8ILVkc7Yqj0HeW1BYdfL/17akagQl8WJgisxKoJnu7YB4NGZS9mfm29xIhERCYQKNhGxlGmaFLw4DPPgXmwNmhNy1/NWR6q0bHEJhD7xLgDuD/+JL2WxxYlOn8/vZ+j3v+IzTQY0rUvfJnWsjmSJe889i5ZxVTmYV8DjM5daHUdERAKggk1ELOWd9Q3eGRPB4SD0hc8wQkKtjlSpOS+5Gsel14LPR/5TN2Hm5Vod6bS8u3Q9i3btJyrEyX+OdE2sjJx2G+9c2hGAD1ZsZOHOvRYnEhGRM6WCTUQsY+YepuDV+wBwDX4Ue9M2FicSgNDH3saokYA/dT0FIx+3Ok6x7cjM4fFZhbNJL3dvR+2oCIsTWev8OjUZ3KohAMN+WIjX77c4kYiInAkVbCJimYL/PYO5ZydG7Xq4bv0/q+PIEUZ0LKHPfASA5/P/4F00w+JEp2aaJvf8uJDDbi+dEuO4o20TqyOVCa/0aEdMqIsVew7y7tL1VscREZEzoIJNRCzh27AKz7i3AAh99G2M0Iq9R1Z54+h0Cc5BwwAKN9TOzrA20CmMS9nCdxt24LTZGNXrPGwVdIPs0xUXEcZLF7YF4MnZy0g/XL6WuIqIiAo2EbGA6feT/887wefD0WMgji69rI4kxxEy/DWMpAaYe3aS/+r9Vsc5od3Zudz74yIAnu7SmhZxVS1OVLbc3qYx59SqRlaBh3/8/JvVcURE5DSpYBORoPN88xH+VQsgvAohD79ldRw5ASMsgrDnRoPNhnfKaDwzvrY60t+YpsmdPyzgUL6btvHVeLRTS6sjlTl2m413LzsPAxibsoXZqbutjiQiIqdBBZuIBJX/4D4K/v0IACHDnsNWM9HiRHIy9rM74Rr8KAAFL9yB/8AeixMda+yflkJ+csX5OO36WDuecxKqc2e7wuf67pq2ELfPZ3EiEREpLn2yiUjQHN1zjaxD2Bq3xnnNvVZHkmJw3fkMtsatMTP2k//c7ZimaXUkoHAp5H1/WgrZUkshT+qfF7SlRngoa/dn8taiNVbHERGRYlLBJiJB45kw6siea05Cn/4Aw+GwOpIUg+F0Efr8aHC68P0yGe/3Y62OhGma3PG9lkKejqphIbzW4xwAnp27ku2Zhy1OJCIixaGCTUSCwrcphYI3hgMQcu9L2JufY3EiOR32xq1w3TECgII3HsTMOmRpnknrtzN5o5ZCnq6bWjWgS1JNcj1ehk9fYnUcEREpBn3CiUipM/NyyX/0aijIx97pUpw3DLc6kpwB103/wFbvLMxD+ygY+YRlOTw+P4/NLNwg+5HzWmgp5GkwDIP/XtYRu2Hw9bpt/LBpp9WRRETkFFSwiUipK3hjOP4tazCqxxP6/KcYNv3qKY8Mp4uQJ94FwDNxFL7ViyzJ8cGKDWw8mEWN8FAe6dTCkgzlWcu4qjzQoRkA90xbRJ7Ha3EiERE5GV01iUip8kwfj2fie2AYhD7/GbbYOKsjSQAc53TDcfnNYJrk//NOTG9wL/azCzw888sKoLDRSFSIK6jjVxQjupxNYmQ4WzKyeXH+KqvjiIjISahgE5FSY2ZnFm6QDbgGP4qjY0+LE0lJCHngNYiqin/9Cjxfvh3Usd9YmMLenHwaVI1kaNvGQR27IokMcfKfSzoA8MqvKazbn2FtIBEROSEVbCJSatyjX4PMg9jqnYVr2HNWx5ESYoutQcj9rwBQ8M5T+PfuCsq46YdzeX3h7wC8eGFbXHZ7UMatqPo1qUPvhol4/H6G/bCwzGzXICIix1LBJiKlwr8/HfeYNwFw3fsihtNpcSIpSc5+t2JrdR7kHqbg9eA0kXlu7kpyPF7OTajOoLOSgzJmRWYYBiMv6UCYw87sbemMTdlidSQRETkOFWwiUircH7wA+bnYWnbAcUFfq+NICTNsNkKfeBdsNrzTx+NdMqtUx1t/IJP3lm0A4NXu7TAMo1THqyzqVY3k6S6tAXhw+hIO5RVYnEhERP5KBZuIlDj/zi14Jo4CIOS+l3VxXUHZm7TGOWgYAAWv3leqDUienrMcn2nSu2EiFyTXKrVxKqMHOzanWfUY9uXm8/ispVbHERGRv1DBJiIlruDdp8Hrxd7pEhznXGB1HClFIcOeg+hY/JtSior0krZufwbj16QChc+uScly2e28e1lHAN5fvpGth7ItTiQiIn+mgk1ESpRv/Uq8P4wDIOTelyxOI6XNiI4l5K4XgCMNSA7tL/ExXvk1BRO4onESrWrGlvj5BbrWjeeiegn4TZORv621Oo6IiPyJCjYRKVEF//0/ME0cl1yDvWkbq+NIEDgHDsXWuDVkHcL9zlMleu5tGYcZk7IZgMc7tSzRc8uxhh/ZTPuD5RvJKnBbnEZERI5SwSYiJcb722x8c6eCw0HIXc9bHUeCxLDbCXnkPwB4vn4P3/oVJXbu1xem4PWbdE+uRcdEbbpemi5pUJum1aLJdnv4eOUmq+OIiMgRKthEpESY7gIKjmyS7RwwFFudhhYnkmBytOuK4+Krwe+n4JX7SmRPrz2H8/hgxUYAnuis2bXSZjMMHmhfOMv278Vr8Pn9FicSERGo4AVbRkYGjzzyCC1btqRWrVrEx8cTHx9Ps2bNGDZsGHv27Dmj865Zs4ZGjRqVcFqR8s390Uv4U9djVI8n5J5/Wh1HLBAy/DUIDcO3fC7e2d8FfL63Fq8h3+ujQ+3qdFdnyKC4sVUDYsNC2JpxmO827LA6joiIUIELNp/PR48ePYiIiGD27NmkpaWRnp5Oeno6CxYsoGnTpnTu3Jnc3NzTOm9WVhaDBg1iyxZtMCpylG/LWtwfvghAyCP/wYiMsTaQWMIWn4TrugcAcI96JqBZtoz8Av772zoAnujcSltDBEm408GdbZsA8OaiNRanERERqMAF26RJk0hOTmbEiBFUq1btmA/76Oho7r//fnr16sWoUcVvQ22aJrfccgs33ngjkZGRpRFbpNwx/X4KXhgKXg/2rn1w9LzS6khiIdeND0FEJP71K/DO+uaMz/Pf39aR7fbQokYMfRollVxAOaW7z2mK02Zj7o49LN1d8l0/RUTk9FTYgm316tVceOGFJz2mZ8+erF69utjnfP311/F4PDzyyCOBxhOpMDzffIhv+TwIiyD0sf9qJqSSM2Kq4br2fgDc/xuBeQbPQR12e3hrceHszuOdW2HTf1NBlRAZztXNkgHNsomIlAUVtmDbuXMntWqd/JmHhIQEtm/fXqzzzZo1iw8++IDRo0djs1XYPzaR0+Lft5uCNx8GIOTuF7DVqmNxIikLXDc+CFWi8G9cjXfG16f9/n8t/J39uQU0rBrJVUcKBwmuB460+P9yzVZ2ZeVYnEZEpHKrsJWHz+fDbref9BiHw4HX6z3luXbu3MngwYP54osviImJKXaGgoICsrKyjvkSqUgK3vwHHM7E1uwcnNfca3UcKSOMqKq4rh8OHHmW7TRm2fbm5PHawhQAXrigLQ7dILNEu1rV6VqnJl6/yQvzVlkdR0SkUtMn4Sm43W4GDRrEiBEjaNPm9DYBfumll4iOji76SkrScxhScfg2rML7wzgwDEKfHIVxihskUrm4rn8AqkTj3/w73unji/2+5+au5LDby7kJ1Rmk2TVLPdet8DPvveUbSNl7yOI0IiKVV6Up2NavX0/9+vXZsGHDab1v+PDhtGjRgiFDhpz2mI8//jiZmZlFXzt2qEWyVBzuUc8A4LjoKuxntbU2jJQ5RmRMYQMSjsyy+XynfM/Gg1mMWrYegFe7t9OzaxbrVjeegU3r4jdNhk9fXCJ764mIyOmrNAVbkyZN2LJlC40bNy72e0aPHs2CBQsYOXLkGY0ZEhJCVFTUMV8iFYFv7TK8MyeBYeC6Y4TVcaSMcl13P0RVxb91Hd6fvjzl8U/MWorXb9KrYSIXaN+1MuHVHufgstv4eetupm7aaXUcEZFKqcIWbMV5Ps3r9eJwOI772sqVK3n88ceZMGECoaGhpRFRpNwq+N8zADguuw57/bOsDSNlllElCtdN/wCgYNSzmCf5nbxo1z4mrN2GAbzcvV2QEsqp1K8ayfAjDUgemr4EdzFmSkVEpGRV2IItMTGR9PT0kx6TlpZGnTrH72r3zjvvkJOTQ6dOnYiPj//bV2ZmJvHx8Xz22WelEV+kzPL9vgTfL5PBZiNk6NNWx5EyznXNvRgx1TC3bcA77fPjHmOaJo/M+A2Am1s1pGVc1WBGlFN4onMr4iJC2XAwi3eObGYuIiLBU2ELtpYtWzJjxoyTHjNjxgxatmx53NdGjRpFRkYG6enpx/2Kjo4mPT2dG2+8sTTii5RZBe8UFmmO3jdiq1v8JcZSORkRkThvPDLL9t5zx51lm7ppJ79s30Oow17U6ELKjqgQF/+8oPA51WfnrmR/br7FiUREKpcKW7D169ePnTt3MmLECA4cOHDMw9JZWVmMHDmSqVOnMnToUAtTipQvvhW/4vt1Gtjtml2TYnNdcw9GTHXMHZvwfj/mmNdM0+T5uSsBuPfcs0iKjrAiopzCLa0b0rpmVTLy3Tzzywqr44iIVCoVtmCz2+38/PPP5OXl0a1bNxISEoqWM7Zv356UlBTmzZtHREThxcHs2bNp2LBhsfdKq127dmnGFymTCv5X2GDEecUt2BLrW5xGygsjvAquwY8AUPD+85geT9Frc7fvYXHafkLsNv7RsblVEeUU7DYbb17UHoD3lm3QZtoiIkFkmOrTGzRZWVlER0eTmZmpjpFS7niXzSXv1q7gcBLx7QZsCclWR5JyxMzLIadPfcyDewl5+gNc/W8FoM8XPzN1007uaNuY//XqZHFKOZUun37PvB17+UfH5rzW81yr44iIlGvFrQ0q7AybiJQs99HZtb5DVKzJaTPCInANfhQA9wcvYHrcrNmXwdRNOzGAhzq2sDagFMtjnQqf+/7fsvUcyiuwOI2ISOWggk1ETsn72xx8S2aBw4nr1iesjiPllPPKOzGqx2OmpeKZ/CmvL0wBoH/TujSK1aqD8qBXw0Ra1IjhsNvLu0vXWx1HRKRSUMEmIqfkHvUMAM7+t2GrdfytMEROxQgLx3XLYwDkvfc8X67cAMAj52l2rbwwDINHj8yyvbV4DXmek+93KiIigVPBJiIn5f1tNr7fZoPThWvI41bHkXLOOWAoRvVa2Pbs4Jotc+iSVJMOtWtYHUtOw9XN6lE3OoJ9ufl8smqT1XFERCo8FWwickKmaeJ+98iza/1vwxafZHEiKe+M0DD8Nxd2jPzHusk8em4jixPJ6XLabfzjyDOHry1Iwev3W5xIRKRiU8EmIifk+202vmW/aHZNStSHdbqwK6wqiXmH6LlqmtVx5AwMObsR1cND2JpxmAlrU62OIyJSoalgE5HjOmZ2bcBQbDUTLU4kFUG+18vryzfzepM+AHg+egmzIN/iVHK6wp0O7ju3GQAv/7oa7RAkIlJ6VLCJyHH5Fs/Et3wuuEJwDXnM6jhSQYxcso607FxmtrwEaiZh7kvDM/E9q2PJGbj7nKZEOB2s3HOIqZt2Wh1HRKTCUsEmIn9jmuYf+64NGIotrrbFiaQiOJhXwIvzVwHwdI/2hNz2fwC4P34JMz/PymhyBmLDQrj7nKYAPDV7OX7NsomIlAoVbCLyN75FM/CtmF84u3aLZtekZLw4fxUZ+W5axlXlxpYNcPa9BaNWXcz96Xgm/M/qeHIGHjmvBVEhTlbsOcjEtdusjiMiUiGpYBORY5imScHR2bWBd2CLS7A4kVQE2zIOM3LJWgBe6d4Ou82G4XThuu1JANwfv4yZl2NlRDkD1cJDebBDcwCenrNcHSNFREqBCjYROYZv4XT8K3+FkFDNrkmJeWrOctw+PxfWjefSBn8ssXVefjNG7XqYB/fiGf+uhQnlTA3v0IxqYSGsO5DJmNWbrY4jIlLhqGATkSKmaVJwtDPklXdiq1HL4kRSEaxIP1B0If9qj3MwDKPoNcPpJOT2pwBwf/IqZu5hSzLKmYsKcfFop5YAPPvLStw+n8WJREQqFhVsIlLEt+An/KsXFs6uDX7U6jhSQTw6cykmcHWzZM5JqP631x29b8RIaoB5aB/uL/8b/IASsLvPaUp8lTBSMw/zwfKNVscREalQVLCJCPCXZ9euHIaterzFiaQimLl1Nz9tScNps/HPC9oe9xjD4SDk9qcB8Ix+DTMnO5gRpQSEOx08eX4rAF6Yt5Jcj9fiRCIiFYcKNhEBwDd/Gv7ViyA0DNctml2TkvHyr6sBGNq2MQ1io054nOOy6zDqNMLMOID7i5HBiicl6PY2jakbHcHuw3m889s6q+OIiFQYKthEpHB2bdQzADgH3YWtWk1rA0mFsGrPQaZvTcNmGDx0pJPgiRgOByF3FM7wuke/jnk4KxgRpQS57HZGdDkbgDcW/U6BV8+yiYiUBBVsIlLYGTJlceHs2s0PWx1HKoh/LfodgIFN61KvauQpj3dccg22ek0h6xDuz/9T2vGkFFzfsj6JkeGkH85Tx0gRkRKigk1EcH/4InBk3zXNrkkJSMvOZVzKVgAe6njy2bWjDLsd19Ajs2yfvYGZnVFa8aSUuOx2HujQDIDXF/6O3zQtTiQiUv6pYBOp5Lwr5uNbOgccTlw3PmR1HKkg3l6yFo/fz/lJcXSoXaPY73NcNAhb/WaQnYF73L9LMaGUltvbNCY6xMm6A5lM2bjD6jgiIuWeCjaRSq5odu2KwdhqJlqcRiqCHLeH/y1bDxR/du0ow27HdfRZtjFval+2cigqxMWd7ZoA8NqCFIvTiIiUfyrYRCox3/oV+OZ9DzYbrpsfsTqOVBAfr9zEoXw3DatGcnmjpNN+v6PnlRhJDeFwJp4po0shoZS2+85thtNmY96OvSzYudfqOCIi5ZoKNpFKzP3RSwA4Lr4aW52GFqeRisDn9/PmojUADO/QHLvt9D9mDJsN1zX3AuD5/D+Yfn+JZpTSlxAZzo0tGwCaZRMRCZQKNpFKyr9tA97p4wFw3fKYxWmkovhm/Xa2ZGQTGxbC4NZnfhPAecVgiIjEn7oe38LpJRdQguYf5xUuh/1m/XY2HMi0OI2ISPmlgk2kkir4+GUwTexdL8feuJXVcaQCME2T1xYWzqYMa9uEcKfjjM9lVInC2XcIgJqPlFNnVY/h8kZJmMAbC3+3Oo6ISLmlgk2kEvLv3o536mcAhNz6hMVppKKYsnEni3btJ8xh555zmwZ8Ptc194Jh4Jv/A/7U9SWQUILt4fNaAPDpqk2kZedanEZEpHxSwSZSCbnHvgVeL/b23bG36mh1HKkAfH4/T8xaCsAD7ZsRXyU84HPakhpg79IHAPcXIwM+nwTf+UlxdE6Mo8Dn5/m5K62OIyJSLqlgE6lkzLxcPN99DIDrBu27JiVjbMoWUvZlUDXUxSOdWpTYeV3X3geA57tPtJF2OWQYBi91bwfA+8s3sPFglsWJRETKnxIv2Px+P6ZplvRpRaSEeH4YB9kZGIn1sXe+1Oo4UgEUeH08PWc5AI91aklMaEiJndveoQe2Bs0hLwfPNx+V2HkleLrUqUmvhon4TJOnZy+3Oo6ISLkTcMGWmZnJ448/Trt27ahWrRpOp5Pw8HCWLVsGQJs2bejevTs//fRTwGFFJDCmaeL56r8AuAYNwziDlusifzVq2Xq2ZeaQEBnOPeeeVaLnNgwD55FZNvcXIzF9vhI9vwTHixe2BeCLNVtZnn7A4jQiIuVLQFdrGRkZNG/enHfffZdOnTrx5JNP8tprr1FQUEB6ejoAzz//PIZh0KdPH+bNm1cioUXkzPhXLsC/fgWEhBZ14BMJRHaBhxfmrQJgRJfWAXWGPBFnrxsgOhYzLRXvnO9K/PxS+lrXjOW65vUBeHzmUovTiIiULwEVbCNGjCAvL4/169czcuRIhg8fztVXX33MMX369GH69Om0aNGCt956K5DhRCRA7iOza45Lr8WIjrU4jVQEby76nX25+TSKjeKW1o1KZQwjLBzXwDsAcH/6WqmMIaXvuW5n47AZ/LgljVmpu62OIyJSbgRUsM2ZM4frrruOmjVrnnwQm41evXqxdKnuqolYxX9gzx8bZV91t8VppCLYn5vP60f213rhgjY47aW3xNZ5zb3gdOFftQDvivmlNo6UngaxUQxt0wSAx2ct1fPuIiLFFNCn66ZNm6hbt26xjq1evXrRMkkRCT7PpA/A68HWsgP2Zu2sjiMVwFuL1pDt9tAmPpYrz0ou1bFsNWrh7H0jAB7NspVbT57finCng0W79vPthu1WxxERKRcCKthyc3MJDy/eXjtOpxO32x3IcCJyhkyvF8/EUYBm16RkZBd4+O/SdQA8eX5rbIZR6mM6b/oHAN7Z3+Lbuq7Ux5OSVysynPuPNKZ5bu5KzbKJiBRDwOtXivvLVr+URazjnTsFM30HRkx1HBcNsjqOVADvLV9PRr6bJtWi6NekTlDGtNdriqPbFQB4PnsjKGNKyXuwY3PCnQ6Wpx/kxy27rI4jIlLmBVSwxcbGkpGRUaxjs7OzqVq1aiDDicgZ8nxZ2GzE2f82jJBQi9NIeVfg9fGvRWsAeOS8lkGZXTvKOfgRADxTRuPfr2X25VH18FDubFv4LNuL81ZbnEZEpOwLqGBr2LAha9asKdaxGzZsoEGDBoEMJyJnwLcpBd+in8Fmw3nlHVbHkQpgbMoW0rJzSYgM5/oW9YM6tuPszthanQceN57P/xPUsaXkPNihGS67jbk79jB3+x6r44iIlGkBFWz9+/fnq6++Ytq0aSc9bsmSJXz++ecMHDgwkOFE5Ay4x/wLAEf3AdgSkq0NI+Wez+/n1QWFsyIPdmhGiMMe9Ayumx8GwD3+Xcyc7KCPL4GrHRXB4FYNAXhp/iqL04iIlG2GGcDDZR6Ph0suuYQ5c+Zw1llnUb9+fZxOJ5MmTeKCCy6gevXq7NixgyVLlnD++eczffp0nE5nSeYvV7KysoiOjiYzM5OoqCir40gl4N+3m5xedcHrIfzTBdhbdbQ6kpRzX6/bxsAJs4gJdbH93kFEhgT/d7rp85EzsBnmtg2E/ONNXNc/EPQMErjNB7No/O4k/KbJstsup018NasjiYgEVXFrg4Bm2JxOJzNnzmTChAn07NkTm83GwYMH6datG6Zpkp+fT/v27fnyyy+ZPXt2pS7WRKzg+fLtwlb+rTupWJOAmabJy78Wzq7d3a6pJcUagGG347rxIQDcY9/C9HotySGBaRAbxTXN6gHw0nw9yyYiciIBzbDJ6dEMmwSTmZfD4UuTIOsQoW98jbN7f6sjSTk3K3U33cf8SKjDzrZ7ryQuIsyyLGZ+HjmXJWFmHCD09Yk4ewywLIucuZS9h2j53rcYwNph/WlSLdrqSCIiQROUGTYRKbs8330CWYcwkhoUtUIXOVOmafL83JUA3Hp2I0uLNQAjNAznwMImOp5x/7Y0i5y5FnFV6ds4CRN45VfNsomIHI8KNpEKyPT5cI99EwDX9cMx7MFvDCEVy49bdjFrWzouu42HO7awOg4AzkHDwG7Ht+wXfOtXWB1HztATnVsB8NnqzWw9pCYyIiJ/pYJNpALyzvkOc8dmiKqK84rBVseRcs7n9/PIjKUA3HPOWdSNqWJxokK2mok4elwJgFst/sut9rVrcFG9BLx+k5c0yyYi8jeO4hzUtWtXUlNTAx6sfv36zJ49O+DziMjJeT57AwDXoGEYYREWp5HybszqLazee4joECdPdG5pdZxjuK67H+9PX+L9YRz++17BFlvD6khyBkZ0bc30rWl8vHIjT3RuSXJMpNWRRETKjGIVbIMHD2bHjh3HfM80TZ577jkuu+wy2rdvf9z3mabJypUrmTp1KhdddJH2YRMJAt+qhfhWzAenC+fV91gdR8q5fK+Xp+YsBwqXrlULD7U40bFsrTpia34u/t+X4Jk4ipDbn7Q6kpyBzkk16VmvFj9v3c1L81czqncnqyOJiJQZAXWJtNlsvP3229x1110nPW7MmDHccccdLF++nMaNG5/pcOWeukRKMOQ9di3eH7/AcfnNhD33idVxpJx7bUEKj8z4jcTIcDbcNYAwZ7Hu8wWV5/ux5P/fDRjVaxHxfSqG02V1JDkD87bvocvoH3DYDDbdNbDMLL0VESktZapL5A033ECdOnV47bXXgjGcSKXl37sL74wJANpMWAJ2MK+AF+evAuD5C9qUyWINwHHRIIzq8Zj7d+P9eYLVceQMnV+nJj2Sax15lm2V1XFERMqMoDUdufjii5k5c2awhhOplDxfvQNeL/a2XbE3OdvqOFLOvTh/FRn5blrGVeXGlg2sjnNChtOF88phgJqPlHcjup4NwEcrNrE987C1YUREyoigFWy1atViz549wRpOpNIx8/PwTBwFgPO6+y1OI+XdzqwcRi5ZC8Ar3dtht5XtpsLOK+8Apwv/6kX4Vi6wOo6coS51anJh3Xg8fj8vzVfHSBERCGLBVqVKFfLy8oI1nEil4/lhHGbGAYxadXFc0NfqOFLOvb4wBbfPT5ekmlzaoLbVcU7JVq0mzl43AOAereX35dnRWbYPV2zULJuICAEWbJGRkWRnF2+Ty5ycHCIj1aZXpDSYponn838D4LrmHm2ULQHZl5PPe8s2APDk+a0wDMPiRMXjvOkfAHhnfYN/2waL08iZ6lY3nguOzLL9c56eZRMRCahga9iwIZs3by7WsVu2bKF+/fqBDCciJ+BbOgf/xtUQGo6z361Wx5Fy7t+L15Dn9XFOrWpcVD/B6jjFZq9/FvaufcA0cR/Zi1DKp+e6tQHgo5Ub2Xwwy+I0IiLWCqhgu/jiixk3bhwbN2486XEbNmxg7NixXHLJJYEMJyIn4BlXOLvmvPxmjKiqFqeR8iwz383bvxU+u/ZE5/Izu3aU6+ZHAPBM/hT/AT03XV51qVO4FNfrN3nmlxVWxxERsVRA+7Dl5OTQrl07UlNT6d27N3Xr1qVKlT/2TTl8+DCpqal8//33JCcns3TpUiIiIkokeHmkfdikNPh3bSXn8gZgmoRPXIO9/llWR5Jy7OX5q3h81jLOqh5Nyh39sJWzgs00TXJvPg//6kW4bnuSkLuftzqSnKGlu/dzzodTMIDVd/SleQ3djBKRiiUo+7BFRESwatUqXnrpJXw+HzNnzuSzzz4r+po5cyZ+v5+XXnqJlStXVupiTaS0uL94G0wT+3kXq1iTgOR6vPxr0RoAHu/UqtwVawCGYeC66WEA3F/9FzNXTSvKq3a1qjOgaV1M4Ok5K6yOIyJimYBm2OT0aIZNSpqZl8vhS2pDdgZh/5mKo0svqyNJOfb2krXc++MikqOrsOGuATjtZbuV/4mYPh85/Zti7thEyMP/xnXdfVZHkjP0+75DtBz1LSbw2619aFerutWRRERKTFBm2ETEWt4fv4DsDIzE+tg7X2p1HCnH3D4fry5IAeDRTi3KbbEGYNjtuG58CAD3mH9her0WJ5Iz1bxGVa5vUdiw7MnZyy1OIyJijfL7iSxSyZmmifur/wLguvJOjDK+sbGUbWNXb2FHVg7xVcIY3Lqh1XEC5rz8ZoyqNTB3b8M7fbzVcSQAz3Q9G4fNYNrmXczbrkYyIlL56ApPpJzy/74E/9pl4ArBccUtVseRcizP42XEkU58D3VoTqjDYW2gEmCEhuG85l4APEdubEj51CA2iiGtGwHwxKxl6EkOEalsAvpU/vDDD9m2bVuxj69bty633qo9okRKgnv8uwA4LroKW1U91yFn7q3Fa9iRlUOdqAjuPqep1XFKjLP/bbjfexbfivn4U9djS25idSQ5Q091ac3o1ZuZu2MP32/aSe9GSVZHEhEJmoAKtrFjx7J169YTvu71etm1axeGYZCYmEiDBg1UsImUADPzYOHza4DrqrssTiPl2d6cPF6avxqAFy9sS5iz/M+uHWWrUQt758vw/TIFz7cfEXL/K1ZHkjOUGBXBveeexWsLUnh81jIubVAbu5aBi0glEdBvu5kzZ7J169YTfu3YsYPNmzfTrVs3unTpwsyZM0sq9yllZGTwyCOP0LJlS2rVqkV8fDzx8fE0a9aMYcOGsWfPydfBZ2RkcM8991CvXr2i98bHx5OYmEj37t359ddfg/STiPyd57tPoCAfW9M22Fp2sDqOlGMj5qwg2+3hnFrVuPZIc4eKxNl3CFC4kbbp8VicRgLxWKeWxIS6WL33EGNTtlgdR0QkaEr99lS9evWYNGkS3377LePGjSvt4QDw+Xz06NGDiIgIZs+eTVpaGunp6aSnp7NgwQKaNm1K586dyc3NPeE5hg8fjtPpJCUlpei96enpbN++neeee47rr7+etLS0oPw8In9m+v1FyyGdg4ZhlMO9sqRsWLMvg/eXbwDgjZ7nlst9107F0aUPRmwc5oE9+H6dZnUcCUBsWAiPd2oJwFOzl5Ov7p8iUkkEZT1BdHQ0l19+OR9//HEwhmPSpEkkJyczYsQIqlWrdswFbXR0NPfffz+9evVi1KhRJzzHtGnTePHFF/+22bfNZuP888/nmmuu4dtvvy21n0HkRHyLfsbcsQmqROG87Dqr40g59siM3/CZJv2a1KFr3Xir45QKw+nE0ftGADzffmRxGgnUveeeRe3IcLZn5fDu0vVWxxERCYqgLQBv1KgRK1euDMpYq1ev5sILLzzpMT179mT16tUnfP2RRx4hLCzshK8nJSWxY8eOM84ocqY8R2fXLh+MERZxiqNFjm/G1jSmbtqJw2bwSvd2VscpVc6+hV1UvXOn4D+gtvDlWZjTwbNdzwbghXmryMx3WxtIRCQIglawVatWjYMHDwZlrJ07d1KrVq2THpOQkMD27dtP+Prw4cNP+v6UlBQaNiz/exVJ+eJP34F3zncAOK+80+I0Ul75/H7+8fNvAAxr15TG1aItTlS67A2aFz7r6fXinTrG6jgSoJtbN6RptWgO5hXw2pHN3kVEKrKgFWxut5vQ0NCgjOXz+bDb7Sc9xuFw4D3D9e/fffcd06ZNo3///ic9rqCggKysrGO+RALhmfge+P3Yz70Qe/2zrI4j5dTHKzexYs9BokOcPN2ltdVxgqKo+ci3H2kfr3LOYbPxUve2APxr0e/szj7x8+giIhVB0Aq2HTt2UL9++e5AdujQIQYPHszw4cP55ptvqFq16kmPf+mll4iOji76SkrSvjFy5kyPG883HwCFzUZEzkRGfgFPzFoGwDNdz6Z6eHBupFnNeck1EBqGf8sa/CmLrY4jAerbuA7nJdYgz+vjubnBedxCRMQqQSnYDhw4wLhx4zj//PODMdzfrF+/nvr167Nhw4Yzer9pmnzxxRe0bt2aqlWrsmzZMlq1anXK9z3++ONkZmYWfemZNwmEd9Y3mPvTMarH47ign9VxpJx6fu4q9uXm07RaNHefU3lmaY0qUTh6DgLA882HFqeRQBmGwcsXFj57+f7yDWw4kGlxIhGR0hPQDqk//fQTO3fuPOHrhw8fZvv27YwePRrDMHjuuecCGe6MNWnShC1bzmzPlh07djB48GBM0+SHH36gefPmxX5vSEgIISEhZzSuyF95vnoHAOeAoRhOp8VppDxatz+D/yxZA8BbF7fHaa9cGw87+w7BO2U0nh+/IOShf2GEV7E6kgSga914+jRKZMrGnfzf7GWMH3jyZmMiIuVVQAXb3XffzebNm0/4emRkJMnJyVxzzTU89dRTVK9ePZDhiq04z6d5vV4cjpP/+IsXL+bqq6/m8ccf5/bbb9d+V2IZ3+Y1+JbOAbsd54DbrY4j5dSD05fg9Zv0aZTIJQ1qWx0n6OztumLUaYS5fSOeaZ/j0t+lcu/FC9sxdeNOJqzdxuJd+2hfu4bVkURESlxAt1c3btyI3+8/4VdmZiYrV67kP//5DzVqBO+XaGJiIunp6Sc9Ji0tjTp16pzw9YyMDAYMGMBnn33G0KFDVayJpY628nd0uwJbzUSL00h59P2mnfyweRdOm41/XdTe6jiWMAwD15Huqp6v3lHzkQqgZVxVbmrVAIDHZi7Vv1MRqZAq5HqYli1bMmPGjJMeM2PGDFq2bHnC19944w2uu+46y567EznKzD2MZ8qnADgH3WVxGimP3D4fw38qbLTxQIdmNIqNsjiRdZxXDIaQUPzrV+BftdDqOFICnu3aBpfdxqxt6fy0Jc3qOCIiJa5CFmz9+vVj586djBgxggMHDhxzxy0rK4uRI0cydepUhg4desJzLF26lN69ewcjrshJeX4YBznZGHUaYW/f3eo4Ug6NXLKWDQezqBkRypPnn7phUkVmRMfiuPRaANzj37E4jZSEujFVuOdIA51HZ/6GX7NsIlLBBFSwvfjii2zcuLFYx27YsIEXX3wxkOGKzW638/PPP5OXl0e3bt1ISEggPj6e+Ph42rdvT0pKCvPmzSMiIgKA2bNn07Bhw2P2STt48CBXXnll0fuO93X99dcH5eeRyss0TTxf/hcA16BhGLYKeY9FStGew3lFbc9furAdUSEuixNZz3Vkptr701f4D+6zOI2UhCc6tyQqxMnKPYf4POXMmoyJiJRVhhnAgm+bzcbbb7/NXXedepnWq6++yj//+U8yMytv692srCyio6PJzMwkKqryLkmS4vOt+JXcWzpDaBhVftyFEXXyvf9E/uq2KfP5cMVGzqlVjUVD+mDT87gA5NzQHv/vS3Dd9zIhtzxqdRwpAS/OW8X/zV5GQmQ4a+7oR3Sobk6ISNlW3NogaLfrU1NTqVevXrCGE6kQ3BOONBu55BoVa3Lalu7ez0crCldB/OeSDirW/sR1VeGNRs+E/2H6fBankZIwvEMzGlaNJC07l8dmLrU6johIiQlKwbZt2zbGjh1Ljx49gjGcSIXgP7gP709fAX8s4RIpLtM0uf/HxZjA9S3qc15inNWRyhTHxVdDVFXMtFR8v06zOo6UgDCng/d6dwLgf8vWM2/7HosTiYiUjNPah23jxo2MGTPmmCYekydPPmEL/dzcXHbs2MGUKVOIi4vj6aefDiytSCXi+e5j8LixNTsHe/NzrI4j5cwXv29l/s69hDsdvNy9ndVxyhwjNAxn3yF4PnsD91fv4OiiJlMVwYXJtbj17EZ8uGIjt0/9lRW3X0GIw251LBGRgJxWwbZ69Wo+++yzYwq2xYsXs27duuMeHxERQXJyMk8++ST3338/4eHhgaUVqSRMnw/PhP8BfyzdEimuHLeHh2f8BhQ2Y0iMirA4UdnkuvJOPJ+9gW/+D/h3bsGWWN/qSFICXutxDlM27mDdgUxemr+KZ7q1sTqSiEhAgtZ0RNR0RIrPO/d78u7rDVFVqTJtJ0aYbnZI8T09eznPz1tJcnQV1tzZjzDnad2bq1Ry774U368/4hr8CCH3v2J1HCkhX63ZytVfz8Fps7H89stpXkPPAItI2ROUpiNRUVFER0cHcgoROY6jzUaclw9WsSanJTUjm9cWpgDwxkXnqlg7haPPh3q++QizIN/iNFJSBp2VTJ9GiXj8foZOXaC92USkXAuoYNu1a5f2IhMpYf60VHxzpwLgGnSnxWmkvHl4xm/ke31cWDee/k3qWB2nzLN36Y0Rn4SZsR/vzxOsjiMlxDAM3rn0PKq4HPy6cy//W7re6kgiImcsoILt6MbTIlJyPBNGgWli73gRtrqNrY4j5cjs1N1MWLsNm2Hw1sXtMdTG/5QMux3nwDsAcH/1jsVppCQlRUfw0oWFDXcem7mUnVk5FicSETkzxS7Y9u7dy7x588jKyirNPCKVmukuwPPNhwA4Bw2zOI2UJ16/n/t/WgzAnW2b0KpmrMWJyg9nv1vB4cS/agG+dcutjiMlaFi7JnSsXYNst4e7py0kgMf2RUQsU+yHG1q0aMGBAwc4//zzmTNnDgA33XQTqampxR4sOTmZ0aNHn3ZIkcrCO2Mi5qF9GHG1cXS93Oo4Uo58sHwDq/Yeomqoi+e6nW11nHLFVj0eR4+BeH/8As/4d7E/9Z7VkaSE2G02PujTiTbvT+a7DTuYuG4bV56VbHUsEZHTUuyCLSYmhv379xMTE1P0vQYNGmC3F39/k+Tk5NPJJlLpeI4syXIOvAPDoWYRUjyH8gp4cnbhzNBz3dpQLTzU4kTlj/OquwoLtu/HEvLAqxiRMVZHkhLSvEZVHuvUkufnreTeHxfRI7kWVcNCrI4lIlJsxW7r7/V62b17N4mJiXou4gyprb+cjG9TCrmDWoLDQcT327HVqGV1JCkn7v9xEf9ZspbmNWJYcfsVOGwBPZ5cKZmmSe5VrfBvSiHk4X/juu4+qyNJCcr3ejn7/e9YfyCL285uxPt9OlsdSUSk5Nv6OxwOkpKSVKyJlJKjz645ul6hYk2KbdnuA/z3t3UA/Pvi9irWzpBhGDiPtvgf/46edapgQh0O3u9dWKR9sGIjc7alW5xIRKT49MkuUgaY7gI8Uwqf73T2u9XiNFJe7M7Ope9XM/CZJgOb1qVHvQSrI5Vrzt43QHgV/Knr8S2ZZXUcKWFd6tTkjraFnXdvn/or+V6vxYlERIonaAXbt99+S9OmTYM1nEi54p31DWQexIirjb3TJVbHkXIgz+Ol3/iZ7MzOpWm1aD7o08nqSOWeERGJs89NAHi+/K/FaaQ0vNL9HGpVCWPjwSyen7vK6jgiIsUStIJt+fLlHD58OFjDiZQrRa38+w7BOI1GPlI5mabJkMnzWZy2n9iwECZf3YOYUDVRKAlHt9PwzvkW/940i9NISYsOdfH2pR0BeHXBalbtOWhxIhGRUyt2web3+8/oKy8vjyVLlvDxxx9z/vnnl+bPIlIu+XdtxbdwOhgGzn5DrI4j5cAL81bxxZqtOGwGEwdeQMNYNTEqKfaGLbCf3Rl8PjzffmR1HCkFA5rWpX+TOnj9JrdP/RWf3291JBGRkypWwdagQQOcTucZfVWpUoWOHTsSHR3Nq6++Wto/j0i54/n2YwDs7XtgS0i2NoyUeRPXpvL0nMIW/u9edh4XJKtBTUlzXnknAJ6v38f0+SxOI6Xh7Us7EhXiZHHa/qKmPSIiZVWxNnr63//+R1ramS0NCQ0NpV69erRr1+609mwTqQxMnw/Pd4UFm7P/bRankbJud3Yut039FYAH2jfjtjaNLU5UMTl6Xgmv3Y+Zvh3fr9NwdOltdSQpYQmR4bzSvR3DfljIE7OW0bdxHerGVLE6lojIcRWrYLvoootKO4dIpeRb8BPmnp0QHYvjwn5Wx5Ey7p4fF5GR76ZdrWq81vMcq+NUWEZIKM4+N+MZ+ybuCaNUsFVQQ9s2YWzKFubt2MuwHxYw9Zqe2rpIRMoktfUXsZBn0gcAOPvchOFS0wg5sYlrU/l63TYcNoMP+3TWfmulzDlwKAC+eVPxp++wOI2UBpth8F7vTrjsNn7YvIt3lmpppIiUTfrEF7GI/8AevL98B2jvNTm5g3kF3D1tIQCPdWpJ65qxFieq+Oz1mmI/5wLw+4u6uErFc1b1GF7p3g6Ah6YvYaW6RopIGVTiBdufO0SKyIl5p4wGrxdbyw7YG7awOo6UYQ9OX8yenHzOqh7Nk+e3tjpOpeEceAdQOBNuapPlCuv+9s3o3TCRAp+fa76eQ47bY3UkEZFjBFyw7du3j3vvvZdWrVoRGRl5TIfIyMhIWrVqxb333svevXtLIq9IhWD6/bgnjgLA2U/NRuTEfty8i09XbcYAPuzTmRCHmjcFi6N7f4yY6ph7d+GdO9XqOFJKDMPg48vPJyEynHUHMrn/p8VWRxIROUaxmo6cyN69e2nWrBmGYXDzzTeTnJxMZGRk0evZ2dmkpqYyevRovvjiC37//Xfi4uICDi1S3vkW/Yy5YzNUicZ52bVWx5Ey6mBeAXd8X9gV8r72Z3Feon5/BpPhCsHR9xY8n76GZ+IonBf2tTqSlJIaEaGM6duFHmN+5MMVG7moXgJXN69ndSwRESDAgu3pp58GYN26dVSrVu2Exz322GOcddZZjBgxgnfffTeQIUUqBM9X7wBHmo2ERVicRsqiPI+Xy7+cwbbMHJKjq/DCBW2tjlQpuQYMxfPpa/h+nYY/LVV7JVZgFybX4v/Ob8UL81Yx9PtfaVermjalF5EyIaAlkb/++ivXXnvtSYs1gOrVq3Pttdcyb968QIYTqRD86Tvw/jIZ+GODXpE/8/r9XDNpDr/u3EtMqIvJV/egistpdaxKyVanIfYOPcE08Xz3idVxpJSN6Ho2nRPjyCrwcMm46aRl51odSUQksIJt8+bN1K1bt1jH1qlTh61btwYynEiF4Pn6ffD7sbfrhr1BM6vjSBljmiZ3/7CQ7zbsIMRu47uretAirqrVsSo1Z99bAPBMGY2phloVmsNmY8KVF9CgaiRbMrK5eNxPHMjNtzqWiFRyARVseXl5hIWFFevYsLAw8vLyAhlOpNwzPZ4/9l4bNMziNFIWPTd3Je8t34DNMPi8fze61KlpdaRKz3FBP4iIxNy1Fd9yrRSp6OKrhPPz9ReTEBnO7/syuOyLn8kuUOdIEbFOQAVbVFQUhw4dKqksIhWed/a3mPt3Y1SriaN7f6vjSBnz4fINPPPLCgD+e2kH+jct3goGKV1GWDjOi64CwDv5U4vTSDAkx0Qy/bqLqRYWwpK0/fT9agb52tpBRCwSUMFWt25ddu7cWVJZRCo8z4TCpjvO/rdhOF0Wp5GyZHbqbu78YQEAT57fijvbNbU4kfyZ4/KbAfD8PB4zT881VQbNasQw7dqLiHQ5mbUtneu/mYtpmlbHEpFKKKCCrVevXkyePFmbZIsUgz91Pb7FM8FmwzlgqNVxpAzZdDCLgRNn4/WbXNOsHs91a2N1JPkLe5vzMRLrQ0423lmTrI4jQXJOQnUmX90Dl93G1+u28a9Fv1sdSUQqoYAKtkceeQSHw8Fjjz1WUnlEKiz3hP8BYD+/N7ZadSxOI2VFRn4Bl385g4N5BbRPqM5Hl3fGMAyrY8lfGIaBs89NAHi0LLJS6VY3nrcubg/AYzOXsmDnXosTiUhlY5gBzO8//fTTzJ8/n9mzZ1O3bl3OO+887Hb7cY9dv349v/32G9dff/0x369Tpw4vvPDCmUYoV7KysoiOjiYzM5OoKO3tUpmY+XkcvqQ2ZB0ibOT3OM6/zOpIUgZ4/X56f/EzP21JIzEynMVD+lArMtzqWHIC/l1byelTHwyDiB+2Y6uZaHUkCRLTNLl20hy+XJNKUlQEy2+7nGrhoVbHEpFyrri1QUAbZ2/fvh2/30/Xrl0BSEtLO+Gx4eHhdO3alR07dhzz/RMVeCIViXfGRMg6hFGrLvbzLrY6jpQRD05fwk9b0gh3Ovju6h4q1so4W+162Nt2xbfsFzxTxxAyRKtLKgvDMHivdyeWpR9k48EsbvpuHpOv7oFNs+EiEgQBFWyffPJJCcUQqdg8E98DjjQb0U0KAf6zeA0jl6wFYEzfLrSJr2ZxIikO5+U341v2C94pn+K65VEtX61EokJcjB94AR0/nsr3m3by6q+reaxzK6tjiUglENAzbCJyar6t6/Atn1vYbOTIBrxSuX27fjsP/LQYgJe7t1P7/nLE0fNKCA3Dv3Ud/pTFVseRIGtdM5b/XNwBgCdnL+frddssTiQilYEKNpFS5vn6fQAcXfpgi6ttcRqx2m9p+7num18wgaFtGvPIeS2sjiSnwagShaP7AEDNRyqr29o0YnCrhvhMk0ETZ/Ppyk1WRxKRCk4Fm0gpMt0FeKcUXtQ5B9xucRqx2raMw/T58mdyPV4ubVCb/17WUUvqyiHn5YMB8PwwFjP3sLVhJOgMw+CDPp0Y0roRftNk8OR5vH1kebOISGkI6Bm2o1auXElKSgppaWnk5eWd8Lg6deowePDgkhhSpFzwzpyEmXEAo2Yi9k6XWh1HLJSRX0CvL35mT04+reKq8uWAbjhsumdWHtnbd8eo0whz+0Y8Uz7DddUwqyNJkNltNt7v04moECdvLV7DvT8uIrPAzROdW+kmjIiUuIAKtsOHDzNgwABmzJiBaZrExsYSFhZ2wuMbNGiggk0qFc+kwuWQzr5DMBwlcn9EyqHsAg+Xff4za/ZnkBAZztRrehIV4rI6lpwhw2bDdfU9FLx2P54v38Y56E5dpFdCNsPgXxedS3SIk2fnruTJ2cvJKvDwcvd2+u9BREpUQFeQTzzxBDNnzuTdd9/lxhtvPGmxJlLZ+Ldvwrd4JhgGzr5DrI4jFslxe+j1xXQW7tpH1VAXP1zTk8SoCKtjSYCcVwym4L//h3/LGnyLZ+Lo0MPqSGIBwzB4plsbokNdPDh9Ca8uSMHrN3m95zkq2kSkxAS0Huenn35i8ODBDB06VMWayF94Jn0AgL3TpdgS1AWwMsr1eLn8yxnM27GX6BAn06+/mFY1Y62OJSXAqBKFs89NAHi+GGlxGrHa8A7NeeeyjgD8a9HvPPDTYkzTtDiViFQUARVsW7ZsoUULdTgT+SvT48bz3ceAmo1UVvleL/3Hz2TWtnQiXU5+vO5i2tWqbnUsKUHOq+8BwPvLZPxpqdaGEcsNa9eU93p1AuA/S9Zyz7RF+FW0iUgJCKhg83q92LUJsMjfeOdMxjy4F6N6PI4ufayOI0GWme+m71cz+WlLGhFOB99f05MOtWtYHUtKmL3+Wdg79AS/H/dX71gdR8qA29s25sM+nTGAd5auY9j3C/D6/VbHEpFyLqCCLS4ujl27dpVUFpEKw/PVf4EjzUacTovTSDCtP5BJh4+n8NOWNMIcdiZf3YPz69S0OpaUEtc19wKFS6DNvFyL00hZMOTsRnxyxfkYwHvLN9D7i585lFdgdSwRKccCKtguvvhipk6dis/nK6k8IuWeb/MafEtmgc2Gc+AdVseRIPp+007afzSF9QeySIwMZ+7Nl3Fhci2rY0kpsnfpjZGQDFmH8Ez73Oo4Ukbc1Koh4wdeQLjTwU9b0mj/0RTW7MuwOpaIlFMBFWyvv/46fr+f3r17M23aNNatW8f27dtP+JWVlVVSuUXKLM/4wqVRjm5XYKtVx+I0EgymafLy/FX0+eJnsgo8nJ8Ux2+3Xq5n1ioBw27HddVdQGHzETWakKMGnpXM/Jsvo250BJsOZdPh4yl8t2G71bFEpBwyzAA/XT7//HNuvPHGYn1IxcXFsXv37kCGK9eysrKIjo4mMzOTqKgoq+NIKTBzsjl8SW3IySbs3ek4Ova0OpKUMq/fzx1TF/DRyo0ADG3TmJGXdsCl53srDTPzIIcvTYT8PMI/no/97E5WR5IyZF9OPld9PZvZ29IBePOic3mgQ3OLU4lIWVDc2iCgfdjGjRvHjTfeSOfOnbnuuutITEw8aXv/mjX1HIdUbJ6pn0FONrbkJti1L1OFl+vxcvXXs5mycSc2w2DkJR2465ymVseSIDOiY3FcdBXeyZ/imfyJCjY5Ro2IUH667mKGT1/Mf39bx/DpS/D4TR4+T122RaR4Appha9u2LeHh4cydO1cbRBaDZtgqNtM0yb2yBf4tawh5+N+4rrvP6khSivbn5nP5lzNYuGsfoQ47X/TvRt8mWgJbWXmXzCJvaHeoEkWV6ekYodqbVI5lmibP/rKCZ+euBOCfF7TlifNbWZxKRKxU3NogoGfY1q9fz2WXXaZiTQTwLZ2Df8saCIvAefnNVseRUrT1UDbnf/o9C3fto2qoi5+vv1jFWiVnb9cNo1ZdOJyFd/a3VseRMsgwDJ7p1obnu7UB4P9mL+O5X1ZYG0pEyoWACra8vDxiYmJKKIpI+eb58kgr/143YERGW5xGSoPb5+OVX1fT8r1vWX8gi6SoCObd3IvOSVruXdkZNhvO3jcC4Jn8qcVppCx7sktrXrqwLQAjflnBozN+w61u2yJyEgEVbDExMRw6dKiksoiUW/69u/DOmgSA8+q7LU4jpeHnLWm0eu9bHpu5lByPl06Jcfw6uBfNasRYHU3KCGefmwDwLfwJ/940i9NIWfZY51a83vMcAF5dkMLZ73/HjK36b0ZEji+ggu38889n2bJlJZVFpNzyTHwPfD7sbbpgb9TS6jhSgvbn5nP117O5aNxPrD+QRVxEKJ9cfj5zb76MxKgIq+NJGWKr2whb607g9+P9YazVcaSMe6hjC8b260qN8FDW7s+k59ifuGribHZm5VgdTUTKmIAKtjfeeIOFCxfy8ccfl1QekXLHPJyF56vCvdc0u1axzErdTev3v+OrNanYDIP7zj2L9cP6c3Prhtj07K4cx9HnVz2TP9WebHJK17Woz4a7+nPPOU2xGQbj16bS9N1J/Gvh7/j8fqvjiUgZEVCXyJtuuonFixezceNGYmNjqVu3LuHh4Sc8Pjk5mdGjR5/pcOWeukRWTAX/fRL3B//EltyE8PEpGI6AdsuQMsDr9/PsLyv457xVmEDTatGM7deVtrWqWR1NyjgzO4PDPePBXUD42N+wN2tndSQpJ1akH+CeaYuYv3MvAOcmVOeD3p1oVTPW4mQiUlqCsg9b/fr1sdvtnHfeecU6vm7duoEMJ1Lm+Pem4R7zLwBc976kYq2cM02TZekHuPfHRSzYuQ+A285uxFsXtyfC5bQ4nZQHRmQMjgv64f3pSzyTP1XBJsV2dnw1frn5Mj5cvpGHZyxhSdp+2n04mUfPa8mTXVoRqs8XkUoroBk2OT2aYat48p8fiufr97G17kT4x/O0xUU5dSA3n3G/b+XDFRtYuaewkVJ0iJP3enfiqmb1LE4n5Y133g/k3dsLI6YaET+lYThdVkeSciYtO5d7pi1k0vrtADSoGsnL3dsxsGldfc6IVCDFrQ1UsAWRCraKxbdlLbmDWoDfT/jH87Gf3cnqSHKaVqQf4LUFvzNhXSpuX+HzIiF2GwOa1uXFC9uSHBNpcUIpj0yvl5zLkjD3pxP6r0k4L+xndSQpp75et417pi1k9+E8ADolxvFGz3PomBhncTIRKQlBWRIpUpm5Rz4Ofj+OC/upWCtHTNNk7vY9vPzran7YvKvo+2fXjOXWsxtxXYv6xIaFWJhQyjvD4cDR6wY8o1/H881HKtjkjA1oWpeL6yfw+oIUXlv4O7/u3Mt5n3zPoLOSebRTC9rVqm51RBEJAs2wBZFm2CoO7/J55A3pAnY74eNTsNdranUkKYZZqbt5cvZyfj3yUL/NMLjqrGT+cV5zXfhIifJtXUfugLPAZiNiylZstepYHUnKuV1ZOTw9ZwUfr9zI0Qu38xJrcN+5ZzGwaTJOe0CNv0XEAkFdErl06VLmzZtHamoqmZmZJzyubt26jBgxItDhiiUjI4MXX3yRH374gf379xe1V46NjaVbt24888wz1KxZ86TnWLp0Kc8++ywpKSnk5uYCYLfbqV27NkOHDuWWW27BbrcXO5MKtuLx703DO2MiRlgEjgv7YUSXfIcs0zQxt2/Et3oR/h2bsCU3xd6iPUZi/WOeDzBNE7Iz8O/dBXk5mHk5kJdDwfvP4/99Cc6BQwl9clSJ55OStW5/Bo/MWMrkjTuAwmWPt7RuxD86NqdBrP4uSunIHdod35JZuG57kpC7n7c6jlQQq/Yc5NUFKXy1JhXPkdb/taqEMaxdU4a2aUzNKmEWJxQrmKYJ7oI/rlXc+RixcRiRMWd2Pq8XM2M/5OVg1Kpb4k3VTI8b/4aV+FYvwpeyCP/vSzBNE3uDFtgatsDWoDm2pIbg9RRde5n5uRiRMdhq1yvM5PpjNczR6zUz4wBG9XiM8ConHnfbBoywCGy1rX9GPSgFm9/vZ/DgwYwdO5bIyEhq1qzJpk2baNq0KbGxsXi9XpYvX47H4+Gcc86hSZMmQWnr7/P5aN++PVdccQX33HMPsbGxRRfhmZmZfPLJJ4wcOZJVq1adcBuCpUuXMmjQIN5++2169OhBSEhI0c+8ceNGHn30URo2bMjrr79e7FxlpWAzvV782zZgpqXiT9uKf9dWzF1bMTP2YyTWP+Yvi5mxv7CoSVlc+Bdq9zaM6GqFvwRi4zCq1sBwnmL5mOnHLMg7puChSjT2Fu2xt+iAvUV7CK+Cd+5UPN98iG/+D3B0/xmHA3vHi3FefDX2tl3wb1yNL2URvpTF+Ncvx6hRG3v77jjO7Y69bVeoEoW5fVPhMasX4d+4CgwDwiIwwiIgLAJz/258KYsh69Dfohox1bG1aI/hdOHftRV/2lY4nHX8nys0nIjvNmGrUSvAfyNSGkzTZHtmDq8uSGHUsvX4TBO7YTCsXROe6NyKWpEn3oJEpCR4po8n/5GrMKrHE/H9dgynOo1KyUk/nMuoZRv437L1pB95xs1lt3F1s3rce+5ZnJugVQPlkXfpL5iH9mFv2AIjsUFRoWR63Ph+X4Jv8Ux8y37BPLgXMz/n2Gur4+3dVyUaW+16hcVJZMwxx5sFefDnMsA0ITcb/8G9kHnwj+87XdiSmxZdG+IuKLx2PHoNmZuNLb4ORkLhOLb4JMzMg0XXUWZaKuZfr7l83uPnPQ1GjQSMmGqYGQcwD+0Fr/eP1xKSsTVsgb1BCwgNx7/5d/ybU/BvWw9eL86b/kHo8NcCGr8kBKVgGzVqFMOGDeO9995jyJAhpKWlUadOHaZMmUKvXr0AOHjwIEOGDCEnJ4cff/wRm630p+wnTJjA559/zsSJE094zH333Ue9evUYPnz4cV/v06cPd9xxB5dffvlxX8/JyaFZs2YsXrz4lDN1R5WVgs1/YA85PeMtG/+4wiIKf9kcYWvdCfJy8G9YWfxz2GwQHgmHTzzLewxXCLambbElN8G/ZQ3+9SvA4z7uoUZMNQiPLCr6jPAqOPvdhvOya4ufT0qV1+9n/o69/LpzL4vT9rNo176iB/UB+jZO4pUe59CkWrSFKaUyMT0ecnrVKWw+8upXOC8aZHUkqYDcPh8T1m5j5JK1LNy1r+j7TatFkxQVQVxEKHERocRHhNGnURLNasRYF1ZOyvPtx+Q/M+SPb7hCsNU7CyM6Ft/qRcdcJ52UK6Tw60Q3nIvLMMDpKpy5Kw3RsUU37u3N24PTiX9TCv5NKfi2/I6Zlgqu0D+uvULDMTP249+1FfJzj3/O0DDIzzv+a0dVicLZ91ZC//GvEv+RTldQmo58+umn9O3bl9tuuw3guK1mY2NjGTduHLVr1+a9997jzjvvDGTIYlm9ejUXXnjhSY/p2bMn33zzzRmfIyIignbt2rF+/fpiF2xlhREbh1G9FkZsXOG0ckIytoR6GDHV8O/YVPiXZXMK/u0bISwCe/P2RbNhtuQmmNkZmAf34j+4F/PQPvB6Tj1maHjRXzbCIjD3pRXNlJnbNxZOuVerifPym3H2HYItuQlQ+ByI96cv8f74Jf7UddjqNyvM0bID9qZt8e/agm/JLLxLZmJu21BYrB0pxOwtO2A/qx04nEV3lMy8HIwjs3u2Ri2PabdtugsKp+d/XwKmeeTPph62hGSMMM3GlEV+02Te9j18uSaV8WtT2Zebf8zrdsPgvMQaPN+tDRckayZUgstwOnH2uw33By/gGf+uCjYpFS67neta1Oe6FvVZkrafkUvW8sXvW1l3IJN1B469gfnozKX0rFeL+85tRq+GtbEH4Sa6FI/n54nkP3fkerpuY8w9OyE/t/Bm8hFG1RrYz70Q+zkXYktqgBEaccwKIiMsAkLD/5iVy8vFn5b6x0xYTvaxx4aEYfz1v4HwKoWrp2LjMKKrgWFg7t6Gf/Pv+Dal4N+yBiMkFKN2/T9m7sIjC485OqOWvgMjOvaP66ja9TCq1igsAI+y2QuXLv61duh40Sn/rEzTxDy0r2jmrihv1RoYrhD8h/b/MaO2KQWzIA97g+bYjqwgM2omlrvtMQKaYatZsyZ33303Tz/9NAC7du0iKSnpmBm2owYPHsyWLVv45ZdfAktcDLfeeiu9evVi4MCBJzzmt99+47HHHuPnn38+7usxMTFkZGScdJx77rmHjh07csMNNxQrV1mZYSsu0+MBu/3vf5lLepzMg/h3b8PWoMVJlwyZXu9J11D79+zEzDiArf5Z2veoAjNNk8Vp+/ni962MX5vKruw/7rJVCwuhe3ItOtSuToeEGrStVY1wp5rhinX86TvI6Z1cuP3H12vVoEiCYm9OHsvSD7Avp4C9uXnszcnn930Z/LB5F/4jl331Yqpwe5vG9G1ch7OqR5e7C9iKxLtwOnn39QGPG2e/Wwl5+n0wzcJHVzal4D+4F3vLDtgaNC/1azIJrqDMsO3bt49q1aoV69h69eoxZcqUQIYrNp/Pd8pmIA6HA++f1rqeiVOdo6CggIKCP6aRs7ICnJoOsmA9b2FEx2IvRmORUz3waquZCDUTSyqWlCEen58Vew4ycV0qX/6eSmrm4aLXokOc9G9Sl2ua16N7ci11SpMyxRafhKNLH7xzvsMz4X/YH37L6khSCcRFhHFpg79/HqZmZPPO0vV8sHwDWzMO88SsZTwxaxn1YyLp0yiRPo2SOC+xBlVcet4yWHwrF5A3vB943DguGkTIk6MKi2fDwEisjy2xvtURpQwI2q3n2NhYDh36e5OHiuyll17i2WeftTqGSLni9fvZfCibFekHWZS2j8W79rM0/QD5Xl/RMRFOB1c0TuKa5vW4pH5tQhzF79YqEmzOQcMKC7bJnxJyz4taYi2WSY6J5NUe5/BM17P5PGULE9dtY2bqbrZkZPOfJWv5z5K12AyDZtWj6VC7Bh0SatA5KU4zcKXEt3kNuff2gvxc7J0uJfSfYzBOo/u4VB4BFWyxsbHHnTU63ipLK/+ir1+/nssuu4xp06bRuHHjMzrHyy+/zK+//sp3331X7Pc8/vjjPPjgg0X/nJWVRVJS0hmNL1KR+E2T9MN5pGYcZmtGNlszDrPuQCYp+w6xdn8mbt/fO0fFhLronlyLa5rVo3ejRC11lHLDft7FGIn1MXduwfvjFzj7DTn1m0RKUbjTwa1tGnNrm8Ycdnv4eWsaUzbu5KctaezIyiFlXwYp+zL4cMVGAGpGhHJh3Vp0T65Fp6QaxIS4iHA5iHA6taohAAX/fgSyM7Cf3Zmw1yfqcQ45oYCueGrXrs2GDRuK/rl69cIWssebScvIyCh6PdiaNGnCli1bAjrHY489dtrvCQkJKdoOQKSyMk2T1IzDhbNlaftZtGs/y9MPkPenGbO/Cnc6aF4jhnNrVS98Hq12DRrFRmHTHV4phwybDefAO3D/+1Hc499VwSZlShWXk35N6tKvSV0AdmfnsihtH4t27Wfhrn0s3LWPPTn5fLFmK1+s2fq397vsNmpVCaNeTCT1YqqQHF2FxtWiOLdWdepXjdTM3An4tqzFN3cqGAahz36imXc5qYAKtiuuuIKRI0fywAMP0Lp1a0JCQmjQoAHTpk37WyOOH3/8kaZNg/OwdXGeT/N6vTgC3ASwJM4hUhaZpkm+10eOx0uux0uOx0uOu/D/hzsdxEWEUiM8lDCnA5/fz5r9mSzaVViQLUs/wKE8Nzkez5H3+4oecv8zm2GQGBlOvZgq1IuJpFFsFC3iYmhRoyrJMVVUnEmF4uw7BPc7T+Ff8xu+9SuwNznb6kgix1UrMvyYAq7A62Phrn3MSt3NzNR0Vu09yGG3F9+R3+tun59tmTlsy8xh9rZjz1U9PIT2CTVon1CdJtWiioq6GuGhlb6Q84wpbCnvuKAvtjoNLU4jZV1A1cb999/PpEmTaNu2LbfccgsffPABTz/9NDfffDPbtm3j3HPPxe/3M3fuXJYvX8706dNLKvdJJSYmkp6eftJjju4ZdyIxMTEcPnyYKlWOv1N6cc5RGRzIzScyxIlLa65Pym+aHMwrwOc3qRYeguM0uzzlebzszclnX25+Uev6CKfjyJIUB6EOOwYn//DL8XjZm5PHvtw/uobtzclnb27+ke/nk5HvPmmR9VeRLid+0yTHc/IbJE6bjdY1qxY9E3FuQjUaVI3SUhqpNGxVq+O4oC/e6ePxTP5UBZuUGyEOO93qxtOtbjzPdCv8nmmaePx+ctxest0edmblFi1v35pxmJR9h1ix5yD7cwv4ftNOvt+085hzRjgdJEaFExceVnQDsFpYCA7byT/HXHY7daIjim70xVcJw2YY+Px+cj0+cjweTBOqh4eW6ueLaZrsy83HZbcRHeI67eLTf2APnqmfAeC88aHSiFimef1+DuQWUCMiVDdniymggq169eosWLCAKVOmFG2IfeONNxIfH8+7777LzJkzsdvtNGzYkHfeeYcOHTqUSOhTadmyJWPGjOGee+454TEzZsygZcuWJz3HjBkz6Nu373Ffz8nJYenSpTRp0iTgvMHmN03u/3ER4U7HMRf9IXY7eX+ZVQlz2As33TzyS9U0TZbsPlA0m7IjKweHzSicHalRlRY1YmhQNZIqLmfRuV12G2nZeWzNyCY1s/CXea7HW/h60TF2Dvy5kMjNx2mzHRk79MjGn2HUCP/jn6uHhxYWMrlHCo+cPAp8/j+9J4yqoS7Sc/KOfIhkk5pxmJwjs0RHxw93Oo75hWFiUuD1F80Q5bi9uH3+v/15Hf2wyjnyZ/XX5658fj8H891FRdLRAsgAqoWHEBceRmyYiwLf0fN4yPX48PqPPY/b5z9lQVSaQuw2Io78+wx32slxe9mTk4/H7yfbXbgHXxWXg3NrVad97eq0T6hBrSphx/z7rRoaosYgUuk5L78Z7/TxeL8fi3n/q0HrxCtS0gzDwGW34wqzUzUshDrRVeiUFHfMMQVeHyv3HGRR2n5+S9vPliMFXVp2LjkeL+sPZLH+QGDds112GwZQcJznnquGugqvFcJC8ZrHfl6H2O0kR1c5UvhVoXZkBJkF7qIbmHtz8vGb5jGffQDbM3PYmnGY1MzDRY2wiq5VIkKJDQ0pukb443rBecy1gwE0mvgWbdwFpNVpzocHQqg6f1XRdUtcRCg+v3nMjdVD+e6//XzJMVXokFCd1jVj//b5muvxsj3zMFkFnqKfOcftJSP/Tz9jbj6H8tzEHPlzOnptFRPqIsLppMqRvA6bjf25+UXXWvty8wk9cm149JoszOkoPObI9dv+3Hy8/mNv+mbku4uK+h1ZOfhMk5hQ1zGPPlQLC/nTzeQ89ucWcNjtKSrGcz0+wpz2Y/6sqoeFHPPnHO60k1ngKTrH3pzC68lzEqrRPqEGsWHl81GlgPZhK6t8Ph8dO3akV69e3HfffcTGxhbd/cjKyuLTTz/l3//+NytXriQiIuK451i+fDkDBgzg7bffpmfPnkXPovn9frZs2cLDDz9M/fr1eeONN4qdq6zsw5bj9lDl1bGWjS9nxmW3ERdeWKgCxxTW+Sd5HuyoUIedmn8qvv9c2NY45hf1Hx804Ud+Wf+VaZpkFXjYm5uPz++nUWyUNmAVOQXT6yXn0kTMA3sIe+s7HN0utzqSSNAVeH1sz8ohLTv3mIvqA3kFp1zZkefxkZp5mNQ/XfT/mUFhMVmcFSKBMoAzGSXU52bN9w9R3X2YmzsMY1Ji+4ByuOw2zq4ZS93oKuzIymFrRjZ7cvIDOmdF1rBqJB1q1+DyRklc3bye1XGCsw9bWWW32/n555/55z//Sbdu3Thw4EBR58qYmBi6devGvHnzioq12bNnc9ttt7Fs2bKiP6w2bdrw9ddfM2LECO69915ycws357XZbNSuXZvbb7+dW2+91ZofMECGYfDk+a2K7rgcvftS4PURVjTrZCfc6SDP42Nvbj77jvxSdfv8tImvRvuE6nRIqE67WtXJLHCTsu8QKXszSNl3iB1ZuYWzU+4/iolaVcJJjvnjblaky3nMs1EFPj/VwkKKiogaEaF4/WbRna4/39k5emdoX05+0fNUcRFhxIWH4rLb2P+nmboDeQXERYRSLyay6G5aVMixY+d5fZh/+bXrstmPuUvmstuK7vAcfZ/TbvvbDOWfZ/YNDGLDQqgRHkJcRBjVw0OwGcaRmcTCn+NgnptQh/2Y8/x1GYfDMKgeHkpUiLPMrPk3DIPoUBfRoepoJVJchsOB47Lr8Yz5F57Jn6pgk0opxGGnUWwUjWIDu3Ht8flJyy68Nvvz4wEmcDCvoGjlzf68Apy2Yz+vcz3eouWbWzOy2X0478iM3B9LNB0245jrJJ/fPGY5ZlJUBD7Tf8zm5AfzCo6Z0Tr2/xdeP3RfPoXq7sMciIkn8fLrGO5ycSivcOZrX24+ew7nYbcZ1DySJS48lKphIfx5tajPbxY9O34gr4DFaftZnLb/mD+fSJeTqqGuwhVPR37uqBBn4XmPXGfFhLgKZxb/9HhEZoHnmMwev0n1ouuzwmuZAp/vT9dk+eR6vNT4003g6uEhuP5yLRPhdBZdA9aLiaR6eAi/78tg0a7CBjeL0/aT6/FSs0rhODXCQ6keHkLkn/KHOx3kuL3HPMpx4Oif+ZE/71yPl6gQ5zHLbbPdHhan7WfjwSw2Hcpm06Fswp2OMlGwFVeFnGErq8rKDJuIiFjDt2EVuVe3BqeLKtN3Y0THWh1JRILE9PvJGXAW5rYNhDz8Fq7r7g/sfKbJlkPZLE7bz+7DedSNjii8QR1Thaqhp/9sXUV3MK+AxUf2d+1YuwYXN6htdaTKPcMmIiJSFtkbt8LW5Gz861fg+fELXFfdZXUkEQkS39ypmNs2QJVonH0D397DMAwaxEbRIMDZysoiNiyESxskcmmDRKujnDY9dCIiIhJEzstvBsAz+VOLk4hIMLk/K+x74LryDoyISIvTSHmigk1ERCSIHJddBw4H/pTF+LastTqOiASBb/MafEvngN2O85p7rY4j5YwKNhERkSCyxcZh73QZAF7NsolUCp5vPgTA0aUPtprlb0meWEsFm4iISJAVLYuc+hmm79TbcohI+WV63HinjAbA2f82i9NIeaSCTUREJMgcXftAVFXMfWn4Fs+wOo6IlCLv7O8wM/Zj1EjA3ulSq+NIOaSCTUREJMgMVwjOS68F/lgqJSIVk+ebDwBwXjEYw6EG7XL6SuS/Go/Hw7p160hNTWXfvn2EhoYycOBAQkJCmD9/PomJidStW7ckhhIREakQnANux/PVO3hnTsJ/cC+22DirI4lICfOnbcO34CeAEmnlL5VTwDNsX331FY0aNeLss8+mb9++3Hbbbdx4443MmTMHgNtvv5369etz00034fV6Aw4sIiJSEdibnI2tRXvwevB8+7HVcUSkFHi++xhME3v77tiSGlgdR8qpgAq2RYsWce2119KpUycWL17MgQMH2LZtG6ZpFhVny5cv58MPP+SLL75g1KhRJRJaRESkInANvAMAz9fvYfr9FqcRkZJk+nx4vv0IAGc/NRuRMxdQwfb888/Trl07xo0bR7t27ahatSo227GnDAkJYfDgwfTv35/PPvssoLAiIiIVieOSq6FKFObOLWo+IlLB+Bb9jJm+A6Kq4uje3+o4Uo4FVLCtXbuWnj17FuvY1q1bs3Xr1kCGExERqVCMsAicvW8CwDNBq1BEKhLPpCPNRnrdgBESanEaKc8CKti2bdtGrVq1inVsZGQk+/fvD2Q4ERGRCsd5ZeGySO/sb/Dv221xGhEpCf6De/HO/hbQ3msSuIAKNr/fj91uL95ANu0gICIi8lf2hi2wte4Ef3reRUTKN++Uz8Drwdb8XOyNW1kdR8q5gKoom82Gz+cr1rE+nw/DMAIZTkREpEL6o/nI+5jF/FwVkbLJNM2i/RU1uyYlIaCCLSkpibS0tGIdu2/fPpKSkgIZTkREpEJyXDQIoqpi7v5jzyYRKZ/8Kxfg37oWQsNxXnKN1XGkAgioYGvatCk///wzpmme8tjZs2fTpEmTQIYTERGpkIzQMJx9jjQfmajmIyLlmfubwmYjjouvwqgSZXEaqQgCKtgef/xxli5dyvXXX8/SpUs5ePBg0f5rfr+f3Nxc1q9fz7333suvv/7KE088USKhRUREKhrnkWWR3l8m499bvNUrIlK2mIez8P74JaDlkFJyAirYunbtykcffcSsWbNo3749NWrUoH79+gD07duXyMhImjVrxldffcUHH3xA165dSyS0iIhIRWOvf1Zh8xG/H89U7VsqUh55fvwC8nOx1WuKvXUnq+NIBeEI9ASDBw/mmmuuYd26daSmppKZmVn0WmRkJPXq1aNp06aEhYUFOpSIiEiF5uw7hIKVv+L59iNcgx9Rsy6Rcqao2Ui/2/T3V0qMYRbnATQpEVlZWURHR5OZmUlUlNY0i4jIscycbA5fVAvycgj7eB6OsztbHUlEism3YRW5V7cGh4OIH3dhi42zOpKUccWtDbQ5moiISBlhRETiuPgq4I879SJSPhz9O+vo1lfFmpSogAq2Bx98kH/84x/s2rWrpPKIiIhUas6+QwDw/vQVZk62xWlEpDjMgvyiZ0/VbERKWsD7sH344YfUr1+fW2+9lXXr1pVULhERkUrJfnZnjDqNIC8H7/TxVscRkWLwzvoGsg5hxCdh73iR1XGkggmoYBs+fDjbt2/n+eefZ9q0aTRv3pz+/fuzcOHCksonIiJSqRiGUTTL5vn2I4vTiEhxeCYV7r3m7DsEw263OI1UNAE/wxYZGckjjzzC1q1bGTVqFGvXrqVz585ccMEF/PDDDyWRUUREpFJx9rkJbDZ8K+bjT11vdRwROQn/zi34Fs8Aw8B5xS1Wx5EKqMSajrhcLm677TbWrFnD+PHjyc/Pp3fv3rRq1Ypx48bh8/lKaigREZEKzRaXgL3zZQB4vv3Y4jQicjJHZ8LtHS/CllDX4jRSEZV4l0ibzcaAAQNYuHAhM2fOJCEhgRtuuIFGjRoxZsyYkh5ORESkQipaFjnlU0yv1+I0InI8ptdbdFNFzUaktJRqW/8LLriAr776isGDB5Oamsp9991XmsOJiIhUGI6ufTCq1sDcn4537lSr44jIcfgW/Ii5Lw0jpjqObldYHUcqqFIr2LZs2cLw4cNJSkpi7Nix3HDDDcyZM6e0hhMREalQDKcLx+U3A+CZ8K7FaUTkeI42G3H0uQnDFWJxGqmoSrxgmzNnDv3796dx48aMHTuW+++/n9TUVEaPHk3Lli1LejgREZEKy3XlnWAY+H79Ef/2TVbHEZE/8e9Px/vLZACc/W61OI1UZCVSsLndbj755BPatGlD9+7d2bx5M++99x7bt2/nueeeo1atWiUxjIiISKViS2qAvdOlALjHa5ZNpCzxTP4UfD5src7D3qCZ1XGkAguoYNu7dy/PPPMMSUlJDBkyhKSkJKZPn86qVasYMmQIoaGhJZVTRESkUnJdfTdQ2InOzMu1OI2IAJimieebDwFwqdmIlDJHIG/u27cvKSkp3HLLLdx33300bNiwpHKJiIgIYO90KUZCMmZaKp5pn+Pqr6VXIlbzLZuLuX0jhFfBcfFVVseRCi6ggu2rr74iOjqaqKioksojIiIif2LY7TgHDcP970fxfPVfnP2GYBiG1bFEKrWjzUacl16LEV7F4jRS0QW0JDIpKUnFmoiISClz9h0CrhD865bjX7XQ6jgilZqZnYH35/GAmo1IcBS7YPP5fOzcubM0s4iIiMhx2KpWx3HJNQC4x79jcRqRys0z5TMoyMfWsAW2Fu2tjiOVQLGXRDZp0oStW7dy2WWXMWXKFACefvppUlNTiz1YcnIyzz333GmHFBERqexcV9+Nd/KneH/6Cv+Db2CLjbM6kkilY5omniMdW51X3qnlyRIUxS7YsrOzMU2TnJycou/t2LGDHTt2FH8wR0CPzImIiFRa9ubnYmt+Lv7fl+CZ9CEhtz5udSSRSse39Bf8W9dCWATO3jdaHUcqiWJXUCkpKaxbt46zzz676Hsff/xxaWQSERGR43BddTf5IwbjmTgK1y2PYthKZDtVESmmotm1XtdjVFEfBwmOYv+mr1GjBl26dCEyMrI084iIiMgJOC6+CqpEY+7ehm/JLKvjiFQq/gN78M78GgDnoGEWp5HKRLfmREREygkjNAznZdcBhRtpi0jweL75ELwebC07Ym9yttVxpBIJqGB78cUX2bhxY7GO3bBhAy+++GIgw4mIiFR6zr5DAPDOmIiZdcjiNCKVg+nz4ZkwCgCXZtckyAIq2J588kmmT59erGO/+eYbXnnllUCGExERqfRszdpha9QS3AV4pn1hdRyRSsE3/wfM9O0QHVu4NFkkiIK2JDI1NZV69eoFazgREZEKyTCMolk2LYsUCQ730WYjV9yCERJqcRqpbIJSsG3bto2xY8fSo0ePYAwnIiJSoTkuux4cTvxrfsO3YZXVcUQqNP+urfjm/wCAa+AdFqeRyui0NkbbuHEjY8aMwTTNou9NnjyZ9PT04x6fm5vLjh07mDJlCnFxcTz99NOBpRURERFssTVwdLsC74yJeL77GPs/3rQ6kkiF5Zn4Hpgm9o4XYavbyOo4UgmdVsG2evVqPvvss2MKtsWLF7Nu3brjHh8REUFycjJPPvkk999/P+Hh4YGlFREREQCc/W7FO2Mi3qmfYd7/CobTZXUkkQrHdBcUdodErfzFOob55+rrNNlsNt5++23uuuuuksxUYWVlZREdHU1mZiZRUdpsUUREzpzp85HTqy7m3l2Evjoe50VXWh1JpMLx/PA5+U9chxFXm4ipqRiO05rrEDmp4tYGAT3DFhUVRXR0dCCnEBERkTNg2O04L78ZUPMRkdLiOdpsZMDtKtbEMgEVbLt27eL6668vqSwiIiJyGpxX3AKAb8GP+PfstDiNSMXi25SCb/lcsNtx9r/N6jhSiQVUsEVERJRUDhERETlNtjoNsbfrBn4/nq/esTqOSIXimfA/ABzd+mKLq21xGqnMgrYPm4iIiJQ853X3A+CeOAozL9fiNCIVg5l7GM+U0YCajYj1Ai7Y9u3bx3333UebNm2oWrUqdrv9hF+NGqkVqoiISElydLsCI7E+ZB4susAUkcB4fhgHOdkYdRphb9/d6jhSyQVUsO3du5ezzjqLMWPG0KVLF+6++25M0+Tuu+/mvffe45133mHAgAHYbDaGDRvG22+/XVK5RUREhMLmI65r7wPAM+4tTL/f4kQi5ZtpmkXNRlxX3olh04I0sVZAbf3vuOMOJkyYwNq1a4mLi2PXrl0kJSUxZcoUevXqVXTc6NGjue+++1izZg0JCQklErw8Ult/EREpDWZONocvTYTDWYT9ZyqOLr1O/SYROS7fqoXk3nwehIRS5cddGNGxVkeSCioobf1//fVXrrvuOuLi4k563E033URSUhKvvvpqIMOJiIjIcRgRkTj7FXaxc4990+I0IuWb+8jsmuPiq1WsSZkQUMG2ZcsWkpOTi3XsRRddxLRp0wIZTkRERE7Ade29YLPhW/Qzvo2rrY4jUi6ZGQfw/vQlAC41G5EyIqCCLS8vj7CwsGIdGx8fz86d2iNGRESkNNgSknF0HwCAZ9y/LU4jUj55vvsE3AXYmrbB1qK91XFEgAALNofDgcfjKdaxERER5OXlBTKciIiInITr+uEAeL4fg//gXovTiJQvpt+P+8jea85BwzAMw+JEIoUCKthq1qzJoUOHiv7Z4XAA4PV6/3as1+vFbrcHMpyIiIichK31eYWzAu4CPOP/Z3UckXLFt3gG5o5NUCUK52XXWR1HpEhABVvTpk2ZO3du0T/HxcUREhJy3KWPRztIioiISOkwDAPXdQ8A4Jn0PqbPZ20gkXLkaCt/Z++bMMIiLE4j8oeACrbBgwcza9YsHnroIXbt2oVhGHTr1o2RI0eyZcuWouNWrlzJp59+ygUXXBBoXhERETkJR48BEB2LuWcnvgU/WR1HpFzw792Fd853ADgH3WlxGpFjBVSwXX/99Tz11FO8//77XHnllQC89dZbFBQU0KhRI2JjY4mJiaFt27bUrFmTF198sURCn0peXh4vvfQSbdq0ISEhgfj4eOLj42ncuDHXX389mzdvPuU5CgoKeOqpp2jYsGHR++Pj40lISKBjx45MmTIlCD+JiIjI6TFcITj73ASAZ9IHFqcRKR88X78PPh/2tl2xN2hudRyRYzgCPcGzzz7L//3f/5GbmwsULpNcu3Yt06ZNY+vWrdjtdho2bMjFF18ctGfYrr32WmrVqsWUKVNISEgoemg0JyeHiRMncuGFF7Jw4cKTbuL98ssvs3HjRhYvXkxs7B97cJimSUpKCoMGDSIxMZGzzz67tH8cERGR0+LsdyuesW/h/eU7/Af2YKtW0+pIImWW6fEUFmwUNhsRKWsM0zRNq0OUpN9++40777yTxYsXY7MdfwLxX//6F9u2bePf/z5x2+MOHTowevRomjRpctzXR40axZYtW3jllVeKna24u5mLiIgEKuemjvhXLyJk+Gu4bvqH1XFEyizPzxPJf/hKjNg4IqbtwHC6rI4klURxa4OAlkSWRatXr+aCCy44YbEG0LNnT1avPvmmotdffz0NGjQ44etJSUns2LHjjHOKiIiUJme/24DCZZEV7N6sSIkqajbS71YVa1ImBa1g27BhQ1CeYdu5cye1atU66TEJCQls3779pMfcd999RdsUHE9KSgoNGzY8o4wiIiKlzXnJ1RAWgT91Pb4V862OI1Im+bdtwLd4BhgGzoFDrY4jclxBK9i+/fZbXn311VIfx+fznfJZOYfDcdy94opr4cKFjBw5ksGDB5/0uIKCArKyso75EhERCQYjIhLnxVcDaj4iciLuCaMAsJ/fC1tCsrVhRE4gaAXb7Nmzady48Rm9d8yYMcTExJz0a8yYMSWc+O/y8vJ4+OGH6d+/P5999hn169c/6fEvvfQS0dHRRV/ah05ERILJ2b9wWaR3+leY2ZkWpxEpW0x3Ad4pnwLgGniHxWlETqxYXSKffvppUlNTz2iAgoICfv/9d9auXcukSZPO6Bw33HADN9xwwxm9NzMzk3bt2vHBBx8EtA/cTz/9xL333kuHDh1Yvnw58fHxp3zP448/zoMPPlj0z1lZWSraREQkaGytOmKr3wz/ljV4fvwC15W6KBU5yjtzEmbGAYy42tg7X2Z1HJETKlbBtn379jNusBEaGkrXrl356KOPaN++/RmdIxDR0dFs2rTpjN9/6NAh7rzzTjZs2MBHH31E586di/3ekJAQQkJCznhsERGRQBiGgbP/bRS88SCeSR+oYBP5E8+kI638+92KcZK+BSJWK9Z/nZ988kkpxyg5xXk+zev1nrShyFEbN26kb9++XHvttYwbNy5o+8iJiIiUFEfvGyn496P41/yGb81S7M3aWR1JxHL+7ZvwLZ5Z2Gyk7xCr44icVIVr65+YmEh6evpJj0lLS6NOnTonPcbj8dC/f39GjBjBU089pWJNRETKJVvV6jguGgSA+8u3LU4jUjYcbcRj73QptoS6FqcRObkKV7C1bNmSWbNm4ff7T3jMjBkzaNmy5UnPM3r0aJo1a8bVV19d0hFFRESCynXNvQB4p32O/+A+i9OIWMv0ePBM/gQA54DbrQ0jUgwVrmBr164ddevWZdiwYezateuYzUJzc3MZM2YMb775Jo8++uhJz7N06VJ69+5d2nFFRERKna1lB2zNzgF3gVr8S6Xn/WUy5oE9GNXjcXTpY3UckVMqkYJtzZo1jBw5koceeoibbrqJoUOHsnfvXgBee+01PvvsM7Kzs0tiqGIZN24cycnJ9O7dm4SEBOLj44mPj6d169Z8//33zJo1i4SEhKLj169fT/369dmwYUPR9w4ePMjw4cOL3nu8r65duwbtZxIRETlThmEUzbJ5JryLGcBepCLlnefr9wBwXnELhtNpcRqRUzPMP09BnYF77rmHUaNGUaVKFerUqUN4eDiLFy9m8uTJ9OrVi+uvv56vvvqKpk2bMmPGDOLi4koqe7mTlZVFdHQ0mZmZREVFWR1HREQqEbMgn5xLkzAz9hP62gScPQdaHUkk6PxpqeT0qQ+mScTkzdgST76nrkhpKm5tENAM25gxY3jnnXd4++232bdvHytXrmT8+PHHLEMcO3Ysa9euZffu3bz11luBDCciIiJnyAgJxTnw/9u77/Aoqv1/4O/ZmkJIDC2VkNAUCPWHooIQ5CIaDR2kigoIcqnSLSCIgJQgSBMQwVA0oIigeBWCoN4vAgrSCT2FDTUJKdvP74/oXmKSzYaU2d28X8+T5zFzzsy+57hM9rMzc2Y4AMC0dZnMaYjkYfpqHSAElI91YrFGLqNUBdvHH3+MmJgYvPbaa7Zp8iVJKtCvXr166N27N77++uvSvBwRERGVgrr3SECphOXoT7Cc/1PuOEQVShgNMH39CQDYvrwgcgWlKtgSExPRokULh/qGh4cjNTW1NC9HREREpaCoFQJVVHcAgIlT/FMlY9q2GuJmKqSawVB16Cp3HCKHlapgS0tLQ/Xq1R3q6+XlhczMzNK8HBEREZWS+u/JR76Ng8i4I3MaooohcrNhXDcHAKAZ9jYktUbmRESOK/UskYVdAlmafkRERFR+lC3bQVG/KaDPhWnHOrnjEFUI45ZlEHduQAqJgLrrK3LHISqRUhVsGo0Ger3eob5GoxEaDb/NICIikpMkSdD0HwsAMG5ZCmEyypyIqHyJe+kwbvgAAKB9bSan8ieXU6qCLSIiAklJSQ71vX79OsLDw0vzckRERFQGVM8NgFQ9ACItGeY9W+WOQ1SujJ8tBjLvQhHRCKpn+8sdh6jESlWwtWzZEvHx8cjOzrbbz2QyYfv27WjVqlVpXo6IiIjKgKTRQt3vr7Nsny1EKR/JSuS0rHduwrgpFgCgGTkLklIpcyKiklOVZuU5c+agUaNGaNasGUaOHInw8HCYTCZIkoTjx48DAJKSkvDxxx9Dp9Nh9uzZZRKaiIiISkfTewSM6+bAmngCll+/h+rJLnJHIipzxk/nAzlZUDzSEqqne8gdh+iBSKKUX6udOXMGU6dOxU8//VToLJA+Pj546qmnMH/+fDRq1Kg0L+XyHH2aORERUUXQL5wA06ZYKFtHwevjfXLHISpT1hupyI6pCxj08Fz2LVRtn5U7ElE+jtYGpS7Y7peeno6MjAzb7z4+PvD39y+rzbs8FmxERORMrNev5X2gNZvhtekIlI146wK5D/2SyTBtWABl8yfh+clBzlhOTsfR2qDU0/rfz8/PD2FhYbYfFmtERETOSxFYG6pnXgQAGDcskDkNUdkRuTkwfbUWAKAZMoXFGrm0Mi3YiIiIyLVoBk0EAJh/jIc1+ZLMaYjKhum7zUDmXUjB4VC2fU7uOESlUqqCrSRXUx4+fBiHDx8uzcsRERFRGVM2bAblE88AViuMcbFyxyEqNSEETJ9/BADQ9BnFmSHJ5ZWoYLt9+zZGjx6NJk2awNPTEyqVCqGhoYiOjsaBAwcKXefOnTsYNmwY2rRpg/Xr15dJaCIiIio7msGTAACmr9fBeueGzGmISsfyx8+wnj8OeHhC3fVlueMQlZrD0/rfunULTZo0gdlsxpAhQ1C3bl1oNBqkpqZi586diIqKQnx8PHr0+N+UqevXr8fkyZNhsViwatUqDB06tFx2goiIiB6c8tGOUDRuDeupwzDFxUI7Zq7ckYgemGnrMgCA+rmBkHw5nwK5PodniRw5ciTi4+Nx+vRp1KxZM1+bEAI9evTAoUOHkJqailOnTmHEiBH45ZdfMGjQICxcuBA1atQolx1wJZwlkoiInJV5/07kju8KeFVBlW+v8oMuuSRrWjKyo+sAFgu8vvgTyvqRckciKlKZzxL5888/o3///gWKNQCQJAljx46FTqdDv3790Lx5c9y6dQv79u3Dhg0bWKwRERE5OWX7F6Bo0AzIyYJx84dyxyF6IKZtqwCLBcpW7VmskdtwuGBLTExEeHh4ke1hYWEAgJ07d+Ldd9/F8ePH0aFDh1IHJCIiovInSRI0Q98CABg3fwhxL6OYNYicizAaYNr+MQBA/eJomdMQlR2HCzaj0QitVltku0ajAQB8+umnmD59uu13IiIicg2qp3tAEf4IkJUB4xfL5Y5DVCLm/3wBcfcmpFohUHXoKnccojJT5s9h8/b2LutNEhERUQWQFApohr4JADDFLYbIyZI5EZFjhBAwblkKAFD3HglJ5fC8ekROjw/OJiIiIhtV576QQutBpN/Oux+IyAVYfj8I6+kjgNYD6u7D5I5DVKZYsBEREZGNpFJB++p0AIBx40IIfa7MiYiKZ9y4AACgfmEIFP6c7I7cS4kKNkmSyqQPEREROS/VcwMhBYZB3E6D6etP5I5DZJfl0hlYDuwCJAmagRPkjkNU5hx+DptCoYCfnx+qVKlSaLvZbIZOp0O1atXg6elZaJ969eph3759D57WxfE5bERE5CqMWz+CYf5oSLXrw/urs5AUvCiHnJN+1jCYvloLVcfu8Fz0pdxxiBzmaG3g8B2Zn3zyCa5evVqqULVr1y7V+kRERFQx1DFDYFjxNsS1RFgO7oaq/QtyRyIqwHpLB9OujQAAzaCJMqchKh8OF2xDhgwpxxhERETkTCSvKlD3GAbThgUwboplwUZOyfT5R4DJCEXTx6Fs/oTccYjKBa9vICIiokJpXhwNKJWwHE6A5dwxueMQ5SNys2H8YgUAQDOYZ9fIfbFgIyIiokIpAkKheroXAMC4aYm8YYj+wfT1eiDzLqTQenxQNrk1FmxERERUJM3A8QAA854tsN7SyZyGKI+wWGCMWwwA0AycAEmplDkRUflhwUZERERFUkY+BkXTxwGTEaa/Lj8jkpt535cQKZch+VWD+oWX5I5DVK5YsBEREZFdf59lM8Wv5IO0SXZCCBg3/PWg7D6jIHl6yZyIqHyxYCMiIiK7VFHd8x6knX4Lpm83yR2HKjnLHz/DeuowoPWAuu8oueMQlTsWbERERGSXpFLlzRgJwBS3GMJqlTkRVWamjQsBAOrnX4LCv6bMaYjKHws2IiIiKpa6+1Cgii+sl8/AvO8rueNQJWW5fBbmn3YCkmS7VJfI3bFgIyIiomJJPr7Q9BsDADCufQ9CCJkTUWVk+mtmSFX7GCjqNJQ5DVHFYMFGREREDtH0Hwt4VYH13DFYDuySOw5VMtbbaTDt2ggAUL80SeY0RBWHBRsRERE5RPKrBk2f1wEABp5lowpm2voRYDRAEdkGymZPyB2HqMKwYCMiIiKHqQe9AXh4wnryN1j+7we541AlIXKzYYzPew6gZvBESJIkcyKiisOCjYiIiBym8K8Jdc/XAADGNbN5lo0qhGnnp0DGHUihdaGK6iZ3HKIKxYKNiIiISkQzeCKg1sDyx8+wHD0gdxxycyI3G8Z17wMANAPGQ1IqZU5EVLFYsBEREVGJKGoGQ93tVQB5Z9mIypPxs8UQN1MhBdXJe7wEUSXDgo2IiIhKTDNkCqBSwfLbXpiP/SJ3HHJT1pvXYfx0PgBAO2YeJI1W5kREFY8FGxEREZWYIigM6piXAQDG5W/xXjYqF8ZVM4DcbCgiH4Oqcx+54xDJggUbERERPRDN0Lfy7mU7sh+WQ3vljkNuxnLhJEw71gEAPCYs5syQVGmxYCMiIqIHogisDXWvEQAAw/I3eZaNypQhdhJgtULVqReUzfncNaq8WLARERHRA9O8Oh3w8Mp7LttP38gdh9yE+b//geXXPYBKDe2YeXLHIZIVCzYiIiJ6YIpqtaDpNwYAYFjxNoTVKnMicnXCYoEhdiIAQN3331CE1pU5EZG8WLARERFRqWhemgRUqQpr4p8w/+cLueOQizPv3Q5r4gnAxw/aYW/JHYdIdizYiIiIqFQkX39oBuWdETGsmgFhNsuciFyVEOK+h2SPg+TrL3MiIvmxYCMiIqJS0wwYB8mvOsTV8zDv2ih3HHJRlp+/g/X8ccDTG5oXR8sdh8gpsGAjIiKiUpO8faB5eSoAwLD6XQijQeZE5GqEEDCsmwMAUPceybNrRH9hwUZERERlQt3ndUg1giB012D6co3cccjFWI4egPX4r4BGC83ACXLHIXIaLNiIiIioTEgennkP0wZgXDcHIjdH5kTkSoyf5N27pu76ChQ1AmVOQ+Q8WLARERFRmVF3fxVSUB2IWzoYP/9I7jjkIiynjsDy3/8ASmXerKNEZMOCjYiIiMqMpNZA+9pMAIDx0/kQ9zLkDUQuwfjJXACAqkt/KILDZU5D5FxYsBEREVGZUkUPhCL8YSDjDoybYuWOQ07OcvE0zPu+BADbxDVE9D8s2IiIiKhMSUolNCNnAQCMcYsh0m/LnIicmXH1TACAqmN3KOs2kjcMkRNiwUZERERlTvV0TygaNgey78Hw6Xy545CTMv9+EOYf4gGFApq/LqUlovxYsBEREVGZkxQKaEe9BwAwbV0Ga1qyzInI2QirFYaF4wAA6u5DoWzQVN5ARE6KBRsRERGVC2Xb56Bs0RYw6GFYynuTKD/zro2wnvkdqFIVmtdnyx2HyGmxYCMiIqJyIUkStBOXAJIE87ebYDn2q9yRyEmInCwYlk0DAGiHvQ2Ff02ZExE5LxZsREREVG6UjVpB3fUVAIB+wVgIq1XmROQMjOvnQdzSQQqtC/WLo+WOQ+TU3LZgy83Nxdy5c9GiRQsEBQUhICAAAQEBaNCgAQYMGICLFy8+8LZ1Oh0aN24MnU5XhomJiIjck+bfcwBvH1hPH4F510a545DMrKlXYdy4EACgHb8QkkYrcyIi5+a2BVu/fv1w7do17Nq1CykpKdDpdNDpdPjjjz/wzDPPICoqCqmpqSXerslkQt++fZGYmAi9Xl8OyYmIiNyLolotaIe9DQAwLJsGkX1P5kQkJ8OHUwCjAcrWUVB16Cp3HCKn55YF25EjR5CcnIzly5cjODgYkiTZ2ry9vTF48GCMGzcO8+eXfJrhqVOn4pFHHkGjRnxOCBERkaPU/cZACq0HcUsH47r35Y5DMjEf+wXm/3wOSBK0b8Tm+4xGRIVzy4LtxIkT6NChAxSKonevU6dOOHHiRIm2+8UXX+DAgQNYsmRJKRMSERFVLpJGC483FgPIe5i2NenBb00g1ySsVhgWjAPw1zT+DZvJG4jIRbhlwZacnIzAwEC7fYKCgnDt2jWHt3n69GlMmjQJ8fHx8PDwKG1EIiKiSkf51PNQPt4ZMBlhiJ0odxyqYObdcbCePgJ4+3Aaf6IScMuCzWKxQKlU2u2jUqlgNpsd2l5mZiZ69eqFlStXok6dOg7nMBgMyMzMzPdDRERUWUl/XQYHpRLmhB0w/9+PckeiCnL/NP6aoW9BUa2WzImIXIfLFGxxcXHw8/Oz+xMXF1fmryuEwMsvv4zevXvjueeeK9G6c+fOha+vr+0nNDS0zPMRERG5EmXdRlD3fh0AYFg4DsLBL0/JtRk//QDiZiqkkAho+o+VOw6RS3GZgm3gwIFIT0+3+zNw4MBC183IyEC9evWwf//+Er/uwoULkZWVhXfeeafE606bNg0ZGRm2n6SkpBJvg4iIyN1oR8wEfP1hvXgKpu2r5Y5D5cx6/RqMGxcAALTjFnAaf6ISUskdoCL4+vriwoULJV4vISEBK1aswOHDh4u9xLIwWq0WWi0PSkRERPeTfP2hfX02DHNHwbDyHai79IPk6y93LConhqVTAYMeylbtoerYXe44RC7HZc6wlYQj96eZzWaoVEXXq8nJyRg8eDC2bt2K6tWrl3VEIiKiSk3dYzgU9ZoAGXdgWDVT7jhUTizHfoV5z5a8afwnchp/ogfhlgVbSEgIdDqd3T6pqamoXbt2ke0bNmxARkYGunbtioCAgAI/J06cQOvWrfH++3yWDBERUUlJKhW0E5cAAEzxK2C5eEreQFTmhNEA/exhAAB111egfLiFzImIXJNbFmyRkZFISEiA1Wotss/evXsRGRlZZPubb76JzMxM6HS6Qn9CQ0ORmJiI6dOnl8cuEBERuT3VY09DFdUNsFhgWDAOQgi5I1EZMq6dA+ul05D8a0I77gO54xC5LLcs2Fq1aoWwsDCMHDkSKSkp+f4A5OTkIC4uDrGxsZgyZYqMKYmIiEg7fiGg1sBy6EeY930ldxwqI5bzf8K4fi4AQDt1Oe9RJCoFtyzYAGDz5s2oU6cOoqOjERQUZLuUsVmzZvj222+RkJCAoKAgW/9z584hIiIC58+fd2j7NWrUgFqtLq/4RERElYIitC40L00G8Nc0/7nZMiei0hJmM/TvvgqYzVB17A5Vp55yRyJyaZLg9QcVJjMzE76+vsjIyEDVqlXljkNEROQURG4Osns2grh+FZpXp0P77zlyR6JSMG5YAMOSyYCPH7y3n4aiRqDckYickqO1gdueYSMiIiLXIHl6QTtpCYC8D/vWq45d7ULOx3o1EYaVec+u9XhjMYs1ojLAgo2IiIhkp+rQFconugBmE/QfjOEEJC5ICAH9e8Pznrn2WCeoYobIHYnILbBgIyIiItlJkgSPyUvzJiD59XuYE3bIHYlKyLzrM1iO7Ac8POHx9sd85hpRGWHBRkRERE5BEVYfmpcmAUDeNP+5OTInIkeJjDswLH4DAKAZPgOK4HCZExG5DxZsRERE5DQ0r0yHFFAbQncNhkXj5Y5DDjIsnQqRfguKuo2hGThB7jhEboUFGxERETkNydMLHjPWApIE0/aPYfp6vdyRqBiWY7/C9OUaAIB2+kpIfOwRUZliwUZERERORdXmX9CMnAUA0M99HZazf8iciIoiTCbo3x8BAFB1fRmqlu1kTkTkfliwERERkdPRvDodyqeeBwx65E7sCZFxR+5IVAjTlqWwJp4AfP2hHfuB3HGI3BILNiIiInI6kkIBz9kbIYVEQKRcRu6bAyGsVrlj0X2sqVdhWDUDAKAd+wEUD1WXORGRe2LBRkRERE5JqvoQPBduB7QesPzyHYxr3pM7Ev1FWCzQvz0YyM2GsvmTUHd9We5IRG6LBRsRERE5LWXD5vCYvgoAYFw7G9Yr52RORABg3LAAlt8PAF5V4DFrAyQFP1ISlRf+6yIiIiKnpo55Ccp20YDZDP2CcRBCyB2pUrOcPgrjyrcBAB6Tl0IRWlfmRETujQUbEREROT2PN2IBlRqWX/fAcnC33HEqLZGbjdzp/QGzGaqne0IVM0TuSERujwUbEREROT1FWH1oBuY9SFu/cDyE0SBzosrJsOgNiKvnIdUMhsfbH0OSJLkjEbk9FmxERETkEjRD34JUPQAi6QKMm5bIHafSMe/fCdP21QCQd9+ar7/MiYgqBxZsRERE5BIkbx/bs76Ma2bDeiNV5kSVh/VGCvTvvgIAUA+eCNVjT8uciKjyYMFGRERELkP13AAoItsAudkwLJ0qd5xKQVgs0E8fAJF+G4qHW0A7io9XIKpILNiIiIjIZUgKBTymLAUkCebdn8G8f6fckdyecd37sBz9CfCqAs95n0PSaOWORFSpsGAjIiIil6Js3BrqPqMAALnTXoTl+H9lTuS+zH/8DOPqmQAAj2kroAirL28gokqIBRsRERG5HO3E2Lxns+lzkTP2eVgunZE7ktsRGXegn94fsFqhih4E9fOD5I5EVCmxYCMiIiKXI6lU8Jz/ORSRjwEZd5A7qgusN1LkjuU2hBDQzxoKoUuCFFoPHtOWyx2JqNJiwUZEREQuSfL0hueHu6Co0xBCdw25o7pA3EuXO5ZbMH4yF+Z9XwEqNTznbYXk7SN3JKJKiwUbERERuSzFQ9XhuXwPpOqBsF44idw3ekCYTHLHcmmmvV/C+NGbAADtlGVQNmolcyKiyo0FGxEREbk0RVAdeH70HeBVBZbDCTDM/zeEEHLHckmWs39A/1bevWrqF0dD0+s1mRMREQs2IiIicnnKhs3gOXcLIEkwbf8Ypi3L5I7kcqw3ryN3XAygz4Hy8c7QvrFY7khEBBZsRERE5CZUTz0P7bgFAADDovEw/7JH5kSuQ+hzkTuhG0RaMhThD8Nz/ueQVCq5YxERWLARERGRG1EPmgBV15cBqxW5U/vCcvG03JGcnjCZoJ/WD9aTvwG+/vBc8g0kHz+5YxHRX1iwERERkduQJAke01dC2aIdkJWJ3LHPw5p8Se5YTkuYzdBP7w/z/q8BjRaeC7dDUbue3LGI6D4s2IiIiMitSBotPBZuhxQSAZFyGTmD28By/L9yx3I6wmKB/p2XYP5xG6DWwHPRV1D9vw5yxyKif2DBRkRERG5H4V8DXusOQvFIS4i7N5EzPAqm7z+XO5bTEFYr9LOGwvzdZkClgucH8VC1fVbuWERUCBZsRERE5JYUNYPgte4AVO1jAKMB+qkvwrDu/Uo/5b8w6POKtZ2fAkolPOZuhapDjNyxiKgILNiIiIjIbUme3vBY9CXUA8YDAIwfvQnDgnGVtmiznDqCnH4tYf56PaBQwGP2Z1B36il3LCKygwUbERERuTVJqYTHxMXQTlsOADBtWQrjqpnyhqpgwmSCYdVM5LzUBtbLZyBVD4Dnkm+gfraf3NGIqBh8wAYRERFVCpo+rwNWKwzzR8P48SxIPn7QDBwvd6xyZ029gtyJvWA9cxQAoOrcBx7TVkDyqyZzMiJyBAs2IiIiqjQ0L/4bIisDxuVvwbBoAqQqvlB3e0XuWOXGmnQROcM7QuiuAVUfgse0FVB3eVHuWERUAizYiIiIqFLRvDodIvMuTJ8tgn72MMC7KtT/6iV3rDJnvZqInOFREDdSoKjTEJ6rfoSiVojcsYiohHgPGxEREVUqkiRBO34B1N1eBaxW6Kf0gX7RGxAGvdzRyoz1yjnkDG2fV6yFPwLPNftZrBG5KBZsREREVOlIkgTtW6uh7jUCEAKmuMXI6dcSllNH5I5WapaLp/OKtVvXoajXBJ5r90NRPUDuWET0gFiwERERUaUkKZXweHMlPJfuglQ9ANbLZ5DzUhsYVs2EMJvljldiQggYv1qHnJfaQNxOg6J+U3iu3geFf025oxFRKbBgIyIiokpN1S4a3vEnoercB7BYYFz9LnJHPQORflvuaA6z3tIhd1wMDLOGAtn3oGzRFl4f74PCv4bc0YiolFiwERERUaUn+VWD5/zP4fH+ZsCrCiy/7UP2wNawJJ6QO1qxTD9sQ07vJrAc2AWoNdCMnQ/PNfs5bT+Rm2DBRkRERPQX9bP94LXhv5BCIiBSLiPnpcdh+nG73LEKZb15HbkTe0E/uTdE+m0oGjaH16Yj0A6ZDEmplDseEZURFmxERERE91HWawLvuMNQPtYJyM2GflIv5M58BeaD30Loc+WOl3ev2pdrkd3jEZj3bgeUSmiGvgmvzw5BWT9S7nhEVMYkIYSQO0RlkZmZCV9fX2RkZKBq1apyxyEiIiI7hNkMw5LJMG2K/d9CDy+oHusEVcfuUD03EJKq4h5pK+6lw3LyNxg/mQvLkf0AAMUjreAxYx2UDZtVWA4iKhuO1gYs2CoQCzYiIiLXYz6yH+b/fAHzgW8g0pJtyxUPt4DHO2uhfKRlubyu0OfC/P1WmI/sh/XkIVivnPtfo4cntK+/B3W/MRVaNBJR2WHB5oRYsBEREbkuIQSs54/DvH8njJuXAJl3AaUS6oEToH1tJiRPr7J5nXsZMMavhGnzEojbafnapJAIKFu0g3b4O1CERJTJ6xGRPFiwOSEWbERERO7BejsNhg/GwvyfzwHkFVKqjj0geXpD8vQGPKtAUTMYykc7QvKqUnD91Csw/7gN1hupf/XPW8+algTT9tVAVmbedgNqQ/38YCibPg5F49acpp/IjbBgc0Is2IiIiNyL+advoJ/7er5LJfNRa6BsHQVVu+ehbNEWliP7Yfp+K6wnDtndriKiETQvT4XqmRchqdXlkJyI5MaCzQmxYCMiInI/IisTpq/WwnozFcjNhsjNBnKzYUk8DpF0sfCVJAnK1lFQPNIK0OfY1oEkQf3sACifeh6SgpN5E7kzR2sD3qVKREREVApSlarQDJpQYLkQAtYr52A58A3MB3bBcvIQlI3+H1Sd+0LVqRcUNQJlSEtEroZn2CoQz7ARERERERHgeG3Ac+1EREREREROigUbERERERGRk2LBRkRERERE5KRYsBERERERETkpFmxEREREREROigUbERERERGRk2LBRkRERERE5KRYsBERERERETkpFmxEREREREROigUbERERERGRk2LBRkRERERE5KTcsmDLzc3F3Llz0aJFCwQFBSEgIAABAQFo0KABBgwYgIsXLxa7DavViuXLl6NJkyYIDAy0bSMgIADh4eEYNWoU7t69WwF7Q0RERERElZVbFmz9+vXDtWvXsGvXLqSkpECn00Gn0+GPP/7AM888g6ioKKSmptrdRlxcHL744gt89913uH79um0bOp0Op06dgqenJ0aPHl1Be0RERERERJWRJIQQcocoS0eOHMGIESPw22+/QaEovB5dvHgxrl69ig8//LDI7XTu3BkzZ87EE088UWi72WxGYGAgbty4AUmSHMqWmZkJX19fZGRkoGrVqg6tQ0RERERE7sfR2sDtzrCdOHECHTp0KLJYA4BOnTrhxIkTdrdz5coV1K1bt8h2lUqFnj17wmw2P3BWIiIiIiIie1RyByhrycnJCAwMtNsnKCgI165ds9vHaDRCq9Xa7bNq1aoS5yMiIiIiInKU2xVsFosFSqXSbh+VSuXQmbHTp0/jww8/xLFjx5CRkQEAUCgUCAwMRI8ePTBhwgR4enoWub7BYIDBYLD9npmZ6eBeEBERERERucglkXFxcfDz87P7ExcXV+avO2vWLEyePBknT560TTiSnJyMHTt2IDExERMmTLC7/ty5c+Hr62v7CQ0NLfOMRERERETkvtxu0pGZM2fCz88P48aNAwBkZGSgVatWWLt2LTp06AAASE9PR/PmzXHlypUit1OnTh2sX78eUVFRhbbr9XrUrl0bycnJ0Gg0hfYp7AxbaGgoJx0hIiIiIqrkHJ10xO0uifwnX19fXLhw4YHWffjhh4ts8/DwQJ06dXD16lXUr1+/0D5arTbffXB/18a8NJKIiIiIqHL7uyYo7vyZ2xVsjtyfZjaboVIVv+v27k8DAC8vL2RnZzuc7d69ewDASyOJiIiIiAhAXo3g6+tbZLvbFWwhISE4efKk3T6pqamoXbu23T7e3t7Q6/V2++Tm5sLLy8vhbEFBQUhKSoKPj4/Dz24rL39fnpmUlMTLM8sJx7h8cXzLH8e4fHF8yx/HuPxxjMsXx7f8yTnGQgjcu3cPQUFBdvu5XcEWGRmJZcuWwWq1Fvkstr179yIyMtLudiIiIpCYmIiAgIBC241GIy5fvoywsDCHsykUCoSEhDjcvyJUrVqVB4ByxjEuXxzf8scxLl8c3/LHMS5/HOPyxfEtf3KNsb0za39ziVkiS6JVq1YICwvDyJEjkZKSku+a0JycHMTFxSE2NhZTpkyxu50RI0Zg0qRJSExMLHBdaXp6OsaPH4/o6Ohin9VGRERERET0oNzuDBsAbN68GbGxsYiOjkZaWpqt4PLx8UHr1q2RkJCQ79TjuXPn8Oyzz2LPnj1o0KABACA6OhpZWVno168fUlNTYbVabf19fHzQo0cPzJs3r2J3jIiIiIiIKhW3LNg8PDwwbdo0TJs2zaH+DRs2xKVLlwos79u3L/r27VvW8ZyCVqvFjBkzeIawHHGMyxfHt/xxjMsXx7f8cYzLH8e4fHF8y58rjLHbPYeNiIiIiIjIXbjdPWxERERERETuggUbERERERGRk2LBRkRERERE5KRYsBERERERETkpFmyVSHp6OiZPnozIyEgEBgYiICAAAQEBaNSoEUaOHIm0tDS5I7qEuLg4NG/ePN8YBgYGolGjRli8eDHMZnO+/nv37kWnTp1Qp04dW//Q0FC0a9cOX375ZYHn/FHRLBYLevTogfj4+HzLOcYls3fvXrRt2xbBwcG28fp7zGJiYnD69Ol8/RMTE9G/f3/Ur1/f1jcoKAgtW7bE/PnzYTAYZNoT55WWloZhw4YhPDw83xiHh4djwIABSEpKytefx2fHZGVlITo6GmvWrMm3/OjRo4iJiUFERIRt7IKDg/Hoo49i7dq1sFgsBbbF93XhChvj9PR0/Pvf/y7wfg4JCUHHjh3x66+/FthObm4u5s6dixYtWiAoKMi2ToMGDTBgwABcvHixInfLqRT1Pi7M6dOnUb9+/QLLOb5FK2x8DQYD3nvvPTRs2DDfezggIAD16tXDW2+9Bb1en287Qghs27YNbdu2Re3atW39w8LC8K9//Qv79++vuJ0SVCmYzWbRsmVLMXPmTHHr1i1htVptbenp6WLJkiWibt26Ijs7W8aUzi8hIUE0btxYnDt3rkCbTqcTL7zwgli6dKlt2VdffSUiIyPFwYMHhdFotC03mUzi6NGjom3btmLZsmUVkt0dTJ8+XWg0GrF+/XrbMo5xyZw/f16EhYWJ//u//8t3HBAi7zjx+eefi/r16wu9Xi+EECIpKUmEhoaKTZs25Ts+WK1Wce3aNTFs2DDRs2fPCt0HV9C5c2cxe/ZskZubm2+5yWQS69atE61btxYWi0UIweOzozIyMkTbtm1FWFiYiI2NtS0/cuSICA8PF7t377a9b4UQwmKxiLNnz4quXbuKN954I9+2+L4uXFFjPGTIEDFu3DiRlZWVr7/FYhEHDx4UderUESkpKfnaunbtKkaMGCGSk5PzvaezsrLEhg0bRGhoaIF1KoOixriovo0aNRIKhaJAG8e3cEWN77vvvit69eolbt68WWCdO3fuiP79+4s333wz3/LY2FjRvn17cezYMWE2m23LDQaD2L9/v2jcuLHYuXNnue3L/ViwVRLx8fGiR48edvuMHj1aLF68uIISuabJkyeLVatWFdl+9uxZ8eijj9p+b9y4sTh+/HiR/ZOTk0VQUFC+AwEVbseOHaJ58+Zi+PDh+Qo2jnHJzJkzR8yZM8dun44dO4qjR48KIYQYNWpUvi8h/slisYhmzZqJ33//vUxzurL09HRRu3btAgXx/Z588klx+vRpIQSPz47IyckRjz32mHj33XfFjBkz8n0Qi46OtvuhKSsrS9SuXVvodDrbMr6vC7I3xgEBASInJ6fIdadOnSpWrFhh+/3w4cOiVatWti8lCrNo0SIxZsyYMsnuKuyN8T9ZrVbRo0cPMXfuXOHr65uvjeNbOHvjW79+fbsF7LVr10RkZKTtd5PJJAIDA8X169eLXOfo0aOiWbNmZRG9WLwkspI4ceIEoqKi7Pbp1KkTTpw4UUGJXNPjjz+Of/3rX0W2h4aG2i51MplMuHXrFpo2bVpk/+DgYNSqVQspKSllntWdJCYmYuzYsdi2bRs8PT1tyznGJXflyhXUrVvXbp9u3bpBocj781DcsUOhUKBjx448dtznxo0bCAwMhCRJRfYJCQmxHSt4fC6eEAITJkzAO++8U6CtuPHz9vZGq1atcO7cOYfXqYzva3tjPHny5HzH3n+6/28fkDe+HTp0sB1HClMZ39P2xvifFi5cCJPJhMmTJxdo4/gWzt74pqWlITAwsMh1g4OD8dhjj9l+T0pKsl1qWpSWLVvi+vXrBW6FKQ8s2CqJ5ORku29UAAgKCsK1a9cqKJFr6tatGyIiIopsP3nyJOrVqwcA0Ol0qFGjRrHb5Ljbl52djZ49e2Lp0qUFCg2OcckZjUZotVq7fUaPHo3mzZsD4LHjQYSHh+POnTuwWq1F9klKSrIdSzjGxfPy8kKfPn0KbcvIyECVKlXsrv/P8eOYF2RvjMePH2933fv/9gEc36LYG+P7JSQkYO3atdi4cWOhRRnHt3D2xleSJLtfoikUinz3vDkyxgBQo0YN6HS6koctIRZslYTFYoFSqbTbR6VSVci3BO4qJSUFr732GsaMGQPAsTEHOO72CCEwfPhwREdHIyYmpkA7x/jBpKenY/To0WjRokW+G68bN26M4cOHIzU11daXx46SU6lUePTRR/Hmm2/i7t27+Sa9MRgM+Oyzz3DlyhVbwcYxLn//HD+OednZuXMn9uzZg+7du9uWcXwfXHJyMoYMGYKtW7fCz8+v0D4c3wfzyy+/oFu3bqhbt26+yYkee+wxrFy5ssTHCKDixllV7q9A5OaEENiwYQMmTZqEt956C7169ZI7ktv46KOPcP36dWzYsEHuKG5l3rx5WLBgAebPnw8vLy8Aee/jjIwMbNiwAV26dMHvv/8OlYp/Ih7UW2+9hTZt2mDevHnw9/eHWq2GEAK3bt2CWq3Gvn377F7OROTs7t69i/Hjx+PgwYPYsWMHHnroIbkjuTyj0YjevXtjxowZaNGihdxx3Epubi5iY2Mxb9481K9f31aMWSwWXLx4EePGjUNmZiamTJkic9LC8a9FJXXu3DlERETg/PnzckdxaefPn0fnzp2xevVqfP/99xg7dqzd/qNGjcKoUaMqKJ1r++WXX7Bo0SJs2bKlRIUDx7h4ffv2xQsvvGAr1oC8y0X8/PwwduxYhISE4MCBA4WuGxcXxw8Sxbh58yZiYmKwZs0aZGVl4fbt29DpdEhLS0NmZiY+++wzzJs3D0ajsdD1eXwunXnz5hV6Rt4evq8dJ4TA1q1b0axZMzz00EP4/fff7d5HDORdtlqvXr2KnQbdBY0fPx5NmjTBK6+8UqL1OL7FMxqNWLBgAR5++OF8Z86USiUaNGiA9evXY8WKFXa3ERMTg3nz5pV31ELx69NKqmHDhrh06ZLcMVyWxWLBnDlzsHbtWsyaNQuDBw926Nvy5cuXV0A616fT6dC/f39s3rwZtWrVKtG6HOPiPfzww3bbmzRpgosXL6Jjx44F2gYOHIiBAweWVzS3sHXrVnTt2hW9e/cu0Obt7Y3evXvj0KFDiI+Px4ABAwr04fG5dKZOnVridfi+dkxSUhKGDBkCIQS+++47NG7c2KH1fH19ceHChXJO59o2btyI//73v4U+0644HN/iabVa1KlTp8j2WrVqwWAwwGAwFHmf986dO8spXfF4hq2ScOQaW7PZzEugHJCVlYXu3bvj2LFj+PPPPzFkyJBCizVHr2vmuOdnNpvRt29fjB8/Hk8++aTdvhzjB2Nvtjcg78bt7OxsADx2PIizZ88We8YhMjIShw8fBsAxrgj/HD+Oecn99ttveOqpp9C3b1/s3bvXbrHG8S2Z48ePY9q0adi2bRs8PDyK7c/xLTkPDw+7k4783Sc3NxeA832+4P/JSiIkJKTYWWxSU1NRu3btCkrkuiZOnIiQkBAsX77c7j/+gIAA3Lp1q9jtcdzz++WXX3D06FGcPXu20EsPMjIyoNFosG3bNuzYsYNjXELe3t7Q6/V2++Tm5iIoKAjA/44d1atXL7J/amqqbVZJgkN/vCVJsn0Y4PG5dPz8/JCVlWV3psh/jh/f1yWTnp6OHj16YOvWrWjbtm2x/UNCQnDy5Em7ffie/p8VK1YgOzsbTzzxRKHtGRkZCAgIwIIFCzBo0CCO7wNQqVQQQtj93KbX620FsyPHZSDvEnh7U/+XFZ5hqyQiIyOxd+9eu3327t2LyMjICkrkmhITE7Fnzx4sWrSo2G9qVCoVatSogWPHjhXZJzU1FWlpaQgODi7jpK6rffv2yMrKQlpaGnQ6XYGfvn37YsOGDdi1axfH+AFEREQgMTHRbp8zZ87YZjAs7thhtVqRkJDAY8d9IiIicPr0abt9Tp8+jfDwcAA8PpdWceOXnZ2No0ePomHDhg6vw/d1fosWLUL//v0dKtaAvPFNSEiw+2gLvqf/Z/Xq1UhPTy/0b55Op4Ovry90Oh0GDRoEgOP7IAIDA5GcnFxk++3bt6FWq/MVbNevX8f169eLXOePP/5AQEBAhZxhY8FWSXTr1g3JycmYMWMGbt++nW+a6czMTCxbtgy7d+/G8OHDZUzp/P744w9ERUUVe0nZ3+bMmYNBgwbh559/hslksi23WCw4duwY+vbti6lTpzo0dSwVjmNcMv3798f69euxf//+An/sTSYT1q9fj8TERLRr1w5A3v1AixYtwqZNm5CTk2PrK4RASkoKRowYgYiICE7YcJ8BAwZgy5Yt+P7772GxWPK1WSwW7NmzB3Fxcejfvz8AHp9La9asWRg3bhx2794Ng8FgW261WnHhwgUMHDgQvXr1ync/LN/XJXP06FFER0c73L9Vq1YICwvDyJEjkZKSku89nZOTg7i4OMTGxjrtjHzOjuNbciNHjsTrr7+OlJSUAm06nQ7Dhw/H0KFDbctUKhWmTJmCvn374vjx4/mO5SaTCQcPHsSgQYPw3nvvVUh+XhJZSSiVSvz444+YM2cO2rdvn+9DgZ+fH9q3b4+ff/4Z3t7eMid1brdv30Z8fDy+++67Ivuo1WocOnQIQUFBiImJQZUqVTBz5kwkJibaPkyo1WqEhYVh/Pjx6NGjR0XFdwu+vr75Ln3iGJdMYGAg4uPjMX36dAwaNChfkavVavH4449j9+7dtpuug4ODsW/fPrz99tuYOXMm7t27ByDvkr5atWrhxRdfxNKlS2XZF2dVvXp1fP3115g6dSqGDh2ab4xVKhUaN26Mr776yvZQVh6fS6Zq1arw8fGx/d6iRQt8+eWXmDFjBkaPHm0rwBQKBYKDgzFs2DC8+uqr+bbB97V9/xzjO3fuoFevXna/+Hr66aexadMm2++bN29GbGwsoqOjkZaWZntP+/j4oHXr1khISLBdel0Z/XOM7SnsChGOr33/HN/XXnsNANClSxfcvn3b9oXl3zMkDxkypMAD4kePHo2goCC8/vrruHr1qu0ydq1Wi/r162PZsmWIioqqkP2RxP1lORERERERETkNXhJJRERERETkpFiwEREREREROSkWbERERERERE6KBRsREREREZGTYsFGRERERETkpFiwEREREREROSkWbERERERERE6KBRsREREREZGTYsFGRERERETkpFiwERERuRiTyQS9Xi9rBiEEsrKyZM1ARFQZsGAjIiKns2nTJkiSVOKf999/37aNl19+GVqtFt9++62Me1K2NmzYgMaNG8PLyws9e/aUNcuaNWvg4+ODsLAwjB8/HgaDQdY8RETuSiV3ACIion/q2LEjPvroIwgh8i2/efMmZs2ahTFjxqB+/foF1uvcubPtv3/66ScYjUYcOXIEzz33XLlnLm+zZ8/GO++8g0GDBmHMmDHo2LGjrHlefPFFVKlSBX/++SeWLVuG33//Hfv374ckSbLmIiJyN5L4519DIiIiJ3XhwgXUr18fCQkJ6NChg92+s2bNwvbt27F69Wq0adOmYgKWk4yMDISGhuK9997DmDFj5I5TwPHjx9GiRQvs3bsXUVFRcschInIrvCSSiIjc0jvvvIPjx4+7fLEGAN988w1UKhWGDRsmd5RCNWvWDF26dMGmTZvkjkJE5HZYsBERETm5pKQkNGnSBJ6ennJHKVKrVq2QnJwsdwwiIrfDgo2IiNzSjz/+iLp168JqtRZoq1evHr7//nts3LgRzZo1g4eHByRJQrVq1dCtWzdcuHABALBnzx488cQT8PHxgSRJ8PX1RevWrbF169YiX1cIgR07dqBDhw4ICQmxTYiiVqvRoEED9OrVC2fOnCnRvqSmpqJGjRpFtv/www+IiIiA1WrF7t27ERMTg4CAACiVSmi1WjzyyCMYMGAALl++XOQ2Nm3ahGbNmsHT07PAZC61atVC//79kZqaWuT6NWrUsNtOREQPhpOOEBGRW0pOTsalS5dgtVqhUOT/fvLixYt4//33ceLECfTv3x+DBg2CRqPBtWvX8Omnn6J9+/ZYtWoVunfvjpiYGHTp0gUPPfQQ0tPT8e2336Jfv34wm80YOHBggdedNWsWZs6cifbt2+Oll15CrVq1oFAoYDKZkJKSgm+++QbNmjXD3r170a5dO4f25d69e6hSpUqR7SkpKbh8+TKmTZuG2NhYdOnSBS+//DJq1qwJq9WK5ORkbNu2DY0aNcKRI0fQuHHjfOv/9NNPGDhwILp3745BgwbBw8PD1iaEwNmzZ7Ft2zb069cPP/30U6EZfHx8kJmZ6dD+EBGR41iwERFRpXTixAmcOXMGtWrVyrd86NChaNSoEbp164Z169ZhyJAh+dqnT5+O9u3bY+HChQUKttTUVMybNw8TJ07EBx98UOiMie+//z46deqEiRMn4tChQw7ndWT2xd27d+PSpUsICQkp0DZnzhy0bt0aU6ZMwa5du/K1xcXFoWnTpti+fXuRr9OxY0f06tULKSkpCA4OfqB8RERUcrwkkoiIKqW/z37908MPP4zWrVujWrVqGDx4cIF2pVKJAQMG4NSpUwUutzx06BD0ej0mTZpUZAGj0WgwZswY/Pbbb0hPTy+TffnbRx99VGixBgBeXl4YOXIk9u/fX+BxCUlJSWjQoIHdois6OhqTJ09G1apVyzQzERHZx4KNiIgqpfDw8CLbQkJCUKdOnQKXUt7fbjabcfPmzXzLr1y5Am9vb9SsWdPua0dERAAArl69WsLU9j3++ON228PCwpCdnY1bt27lW+7v719s8ejh4YH58+fDx8entDGJiKgEeEkkERFVSl5eXkW2eXp6FtsOALm5ufmWZ2RkoEqVKsXOlmgwGACgQMFXWkql0m7738VWRkZGvklM2rVrh9GjR2PTpk1o06YNtFptvvX8/f3tjgcREZUfFmxERERlKC0tDaGhoQ71vX9yDzkNHToU+/btK3QSlb81aNAAixYtwvPPP1+ByYiIiAUbERFRGfL398eGDRuK7efh4eE0D/VWq9WIj4/H5cuXcfHiRej1elubEAIZGRnYtGkTevfujXPnzqF27doypiUiqlxYsBEREZWRv5/X5qpnocLDw4u8t6979+7w9/fHDz/8gFdffbWCkxERVV6cdISIiKiMhIeH4/bt28jJybHb7/r16wgLC8OlS5cqKJl9K1eutPtQbQDw9vaGv78/dDpdBaUiIiKABRsREVGZefTRR6HVarF8+XK7/VavXo0bN24gICCggpLZt3DhQnz44Yd2+9y9exe3bt0q8rEBRERUPnhJJBERURkJCQnBlClTMHnyZCQkJNie56ZQKGCxWJCRkYFDhw7h22+/xfTp0x2eeVGlUhWYkbIs9enTBwsXLsTNmzfRvHlz2yyYQN49bPfu3cP27dvh7e2NZ599ttBtmEwmqFT8WEFEVNZ4ZCUiIpdRrVo1BAUFITAwsNi+wcHBCA8PL/RZanXr1kVwcHCR64aFhdktPgICAlCzZk34+fkVaJs5cyaaNm2KpUuXYu3atUhNTQUAKBQK1KhRAw0aNMD69evx0ksvFbsP97/eb7/9VmR7UFBQkft6v5o1a6JmzZrw9/fPt/zdd98FAGzZsgWff/45LBZLvvaHHnoITZs2xZ49e4p8xtyNGzcc+v9CREQlIwkhhNwhiIiIqGgrV67EwoULceHCBUiSJHecQr3yyivIycnB1q1b5Y5CRORWeA8bERGRk4uKisLly5fx448/yh2lUHfv3sUXX3yBjh07yh2FiMjt8AwbERGRC+jTpw/27NmD2bNno02bNmjSpAm8vb1ly2O1WnHq1CmcOXMGb7/9Nu7du4dLly45zcPAiYjcBc+wERERuYD169ejX79+GDduHNq0aYPevXvLmmfNmjVo2rQp+vbti2rVquHnn39msUZEVA54ho2IiMiFZGdn49y5c6hatSrq1asnW47MzEz8+eefaNiwIWrUqCFbDiIid8eCjYiIiIiIyEnxkkgiIiIiIiInxYKNiIiIiIjISbFgIyIiIiIiclIs2IiIiIiIiJwUCzYiIiIiIiInxYKNiIiIiIjISbFgIyIiIiIiclIs2IiIiIiIiJzU/wfjympXQkTxCQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 1000x621 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot acquired signal on both inputs.\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "ax.plot(single_acq[\"single\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][130:290])\n",
    "ax.plot(single_acq[\"single\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][130:290])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35655dd7",
   "metadata": {},
   "source": [
    "Retrieve multiple acquisitions\n",
    "------------------------------\n",
    "\n",
    "We can also run the sequence multiple times consecutively and store the acquisition data in the instrument's acquisition list before retrieving them all in\n",
    "one go. To demonstrate this we will run the same sequence three times and vary the output gain for each run to create a clear distinction between the acquisitions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "3bd51f43",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.816590Z",
     "iopub.status.busy": "2025-05-07T16:53:25.816286Z",
     "iopub.status.idle": "2025-05-07T16:53:25.987621Z",
     "shell.execute_reply": "2025-05-07T16:53:25.986578Z"
    }
   },
   "outputs": [],
   "source": [
    "# First run\n",
    "readout_module.sequencer0.gain_awg_path0(0.33)\n",
    "readout_module.sequencer0.gain_awg_path1(0.33)\n",
    "\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "readout_module.get_acquisition_status(0)\n",
    "\n",
    "readout_module.store_scope_acquisition(0, \"multiple_0\")\n",
    "\n",
    "# Second run\n",
    "readout_module.sequencer0.gain_awg_path0(0.66)\n",
    "readout_module.sequencer0.gain_awg_path1(0.66)\n",
    "\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "readout_module.get_acquisition_status(0)\n",
    "\n",
    "readout_module.store_scope_acquisition(0, \"multiple_1\")\n",
    "\n",
    "# Third run\n",
    "readout_module.sequencer0.gain_awg_path0(1)\n",
    "readout_module.sequencer0.gain_awg_path1(1)\n",
    "\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "readout_module.get_acquisition_status(0)\n",
    "\n",
    "readout_module.store_scope_acquisition(0, \"multiple_2\")\n",
    "\n",
    "# Get acquisition list from instrument.\n",
    "multiple_acq = readout_module.get_acquisitions(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc713c16",
   "metadata": {},
   "source": [
    "Let's plot the result again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "68edf29e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:25.990230Z",
     "iopub.status.busy": "2025-05-07T16:53:25.989835Z",
     "iopub.status.idle": "2025-05-07T16:53:26.129771Z",
     "shell.execute_reply": "2025-05-07T16:53:26.129179Z"
    },
    "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": [
    "# Plot acquired signals (add acquisition index to separate acquisitions in plot).\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "for acq_idx in range(0, 3):\n",
    "    ax.plot(\n",
    "        np.array(\n",
    "            multiple_acq[f\"multiple_{acq_idx}\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][130:290]\n",
    "        )\n",
    "        + acq_idx\n",
    "    )\n",
    "    ax.plot(\n",
    "        np.array(\n",
    "            multiple_acq[f\"multiple_{acq_idx}\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][130:290]\n",
    "        )\n",
    "        + acq_idx\n",
    "    )\n",
    "    ax.set_xlabel(\"Time (ns)\")\n",
    "    ax.set_ylabel(\"Relative amplitude\")\n",
    "    plt.gca().set_prop_cycle(None)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b543eb4f",
   "metadata": {},
   "source": [
    "### No Demodulation on Scope Acquisition\n",
    "\n",
    "The scope acquisition is carried out before the incoming signal is demodulated. As a result, the acquired signal needs to be demodulated in software in order to retrieve the original waveform for a non-zero NCO frequency."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1585defd",
   "metadata": {},
   "source": [
    "Hardware-based averaging\n",
    "------------------------\n",
    "\n",
    "We can also use hardware in the instrument itself to automatically accumulate acquisition data on-the-fly. This can be used to do averaging, by dividing the final\n",
    "accumulated result by the number of accumulations. To use this feature, we first need to modify the Q1ASM program to run the sequence multiple consecutive times."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "b72268c8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:26.131603Z",
     "iopub.status.busy": "2025-05-07T16:53:26.131445Z",
     "iopub.status.idle": "2025-05-07T16:53:26.134048Z",
     "shell.execute_reply": "2025-05-07T16:53:26.133544Z"
    }
   },
   "outputs": [],
   "source": [
    "# Sequence program.\n",
    "seq_prog = \"\"\"\n",
    "      move    1000,R0   #Loop iterator.\n",
    "\n",
    "loop: reset_ph\n",
    "      play    0,1,4     #Play waveforms and wait 4ns.\n",
    "      acquire 4,0,16380 #Acquire waveforms and wait remaining duration of scope acquisition.\n",
    "      loop    R0,@loop  #Run until number of iterations is done.\n",
    "\n",
    "      stop              #Stop.\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "316b1042",
   "metadata": {},
   "source": [
    "Next, we need to program, configure and start the sequencer with the updated Q1ASM program. This time we will also configure the sequencer to run in averaging mode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c4aea1c1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:26.135589Z",
     "iopub.status.busy": "2025-05-07T16:53:26.135434Z",
     "iopub.status.idle": "2025-05-07T16:53:26.234760Z",
     "shell.execute_reply": "2025-05-07T16:53:26.233732Z"
    }
   },
   "outputs": [],
   "source": [
    "# Add sequence to single dictionary and write to JSON file.\n",
    "sequence = {\n",
    "    \"waveforms\": waveforms,\n",
    "    \"weights\": {},\n",
    "    \"acquisitions\": acquisitions,\n",
    "    \"program\": seq_prog,\n",
    "}\n",
    "with open(\"avg_sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(sequence, file, indent=4)\n",
    "    file.close()\n",
    "\n",
    "# Upload sequence.\n",
    "readout_module.sequencer0.sequence(\"avg_sequence.json\")\n",
    "\n",
    "# Enable hardware averaging\n",
    "readout_module.scope_acq_avg_mode_en_path0(True)\n",
    "readout_module.scope_acq_avg_mode_en_path1(True)\n",
    "\n",
    "# Arm and start sequencer.\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequence and acquisitions to finish.\n",
    "readout_module.get_acquisition_status(0)\n",
    "\n",
    "# Move accumulated result from temporary memory to the instrument's acquisition list.\n",
    "readout_module.store_scope_acquisition(0, \"avg\")\n",
    "\n",
    "# Get acquisition list from instrument.\n",
    "avg_acq = readout_module.get_acquisitions(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ca36d65a",
   "metadata": {},
   "source": [
    "The sequence has now run and accumulated a 1000 times. Time to finish the averaging process and print the result."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "16e24470",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:26.237572Z",
     "iopub.status.busy": "2025-05-07T16:53:26.237075Z",
     "iopub.status.idle": "2025-05-07T16:53:26.380264Z",
     "shell.execute_reply": "2025-05-07T16:53:26.379513Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x621 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot results.\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "ax.plot(np.array(avg_acq[\"avg\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][130:290]))\n",
    "ax.plot(np.array(avg_acq[\"avg\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][130:290]))\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35f1d1fa",
   "metadata": {},
   "source": [
    "Note that the accumulated acquisitions have already been averaged when the data is returned. The instrument keeps track of the number of accumulations and divides the result upon returning the data. The number of accumulations is also available for review."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "e40ca6c5",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:26.381975Z",
     "iopub.status.busy": "2025-05-07T16:53:26.381822Z",
     "iopub.status.idle": "2025-05-07T16:53:26.385436Z",
     "shell.execute_reply": "2025-05-07T16:53:26.384903Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "569\n",
      "569\n"
     ]
    }
   ],
   "source": [
    "# Print number of averages\n",
    "print(avg_acq[\"avg\"][\"acquisition\"][\"scope\"][\"path0\"][\"avg_cnt\"])\n",
    "print(avg_acq[\"avg\"][\"acquisition\"][\"scope\"][\"path1\"][\"avg_cnt\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "04c88d32",
   "metadata": {},
   "source": [
    "To show that the hardware averaging worked, let's compare and zoom in on the data from the very first acquisition in this tutorial and the very last."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "96f480c6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:26.387106Z",
     "iopub.status.busy": "2025-05-07T16:53:26.386955Z",
     "iopub.status.idle": "2025-05-07T16:53:26.485312Z",
     "shell.execute_reply": "2025-05-07T16:53:26.484734Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x621 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot results\n",
    "fig, ax = plt.subplots(1, 1)\n",
    "ax.plot(np.array(single_acq[\"single\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][1000:2000]))\n",
    "ax.plot(np.array(avg_acq[\"avg\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][1000:2000]))\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ecfbc20",
   "metadata": {},
   "source": [
    "Stop\n",
    "----\n",
    "\n",
    "Finally, let's stop the sequencers if they haven't already and close the instrument connection. One can also display a detailed snapshot containing the instrument parameters before\n",
    "closing the connection by uncommenting the corresponding lines."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "b80330f0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2025-05-07T16:53:26.487055Z",
     "iopub.status.busy": "2025-05-07T16:53:26.486902Z",
     "iopub.status.idle": "2025-05-07T16:53:32.585213Z",
     "shell.execute_reply": "2025-05-07T16:53:32.583732Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, State: STOPPED, Info Flags: FORCED_STOP, ACQ_SCOPE_DONE_PATH_0, ACQ_SCOPE_OVERWRITTEN_PATH_0, ACQ_SCOPE_DONE_PATH_1, ACQ_SCOPE_OVERWRITTEN_PATH_1, ACQ_BINNING_DONE, Warning Flags: NONE, Error Flags: NONE, Log: []\n",
      "Status: OKAY, State: STOPPED, Info Flags: FORCED_STOP, Warning Flags: NONE, Error Flags: NONE, Log: []\n",
      "\n",
      "Snapshot:\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4:\n",
      "\tparameter                    value\n",
      "--------------------------------------------------------------------------------\n",
      "connected                     :\tTrue \n",
      "in0_gain                      :\t-6 (dB)\n",
      "in0_offset                    :\t0 (V)\n",
      "in1_gain                      :\t-6 (dB)\n",
      "in1_offset                    :\t0 (V)\n",
      "marker0_exp0_config           :\tbypassed \n",
      "marker0_exp1_config           :\tbypassed \n",
      "marker0_exp2_config           :\tbypassed \n",
      "marker0_exp3_config           :\tbypassed \n",
      "marker0_fir_config            :\tbypassed \n",
      "marker0_inv_en                :\tFalse \n",
      "marker1_exp0_config           :\tbypassed \n",
      "marker1_exp1_config           :\tbypassed \n",
      "marker1_exp2_config           :\tbypassed \n",
      "marker1_exp3_config           :\tbypassed \n",
      "marker1_fir_config            :\tbypassed \n",
      "marker1_inv_en                :\tFalse \n",
      "marker2_exp0_config           :\tbypassed \n",
      "marker2_exp1_config           :\tbypassed \n",
      "marker2_exp2_config           :\tbypassed \n",
      "marker2_exp3_config           :\tbypassed \n",
      "marker2_fir_config            :\tbypassed \n",
      "marker2_inv_en                :\tFalse \n",
      "marker3_exp0_config           :\tbypassed \n",
      "marker3_exp1_config           :\tbypassed \n",
      "marker3_exp2_config           :\tbypassed \n",
      "marker3_exp3_config           :\tbypassed \n",
      "marker3_fir_config            :\tbypassed \n",
      "marker3_inv_en                :\tFalse \n",
      "out0_exp0_config              :\tbypassed \n",
      "out0_exp1_config              :\tbypassed \n",
      "out0_exp2_config              :\tbypassed \n",
      "out0_exp3_config              :\tbypassed \n",
      "out0_fir_config               :\tbypassed \n",
      "out0_latency                  :\t0 (s)\n",
      "out0_offset                   :\t0 (V)\n",
      "out1_exp0_config              :\tbypassed \n",
      "out1_exp1_config              :\tbypassed \n",
      "out1_exp2_config              :\tbypassed \n",
      "out1_exp3_config              :\tbypassed \n",
      "out1_fir_config               :\tbypassed \n",
      "out1_latency                  :\t0 (s)\n",
      "out1_offset                   :\t0 (V)\n",
      "present                       :\tTrue \n",
      "scope_acq_avg_mode_en_path0   :\tTrue \n",
      "scope_acq_avg_mode_en_path1   :\tTrue \n",
      "scope_acq_sequencer_select    :\t0 \n",
      "scope_acq_trigger_level_path0 :\t0 \n",
      "scope_acq_trigger_level_path1 :\t0 \n",
      "scope_acq_trigger_mode_path0  :\tsequencer \n",
      "scope_acq_trigger_mode_path1  :\tsequencer \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer0:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq_I                    :\tin0 \n",
      "connect_acq_Q                    :\tin1 \n",
      "connect_out0                     :\tI \n",
      "connect_out1                     :\tQ \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "demod_en_acq                     :\tFalse \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_freq_cal_type_default        :\toff (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "thresholded_acq_marker_address   :\t1 \n",
      "thresholded_acq_marker_en        :\tFalse \n",
      "thresholded_acq_marker_invert    :\tFalse \n",
      "thresholded_acq_rotation         :\t0 (Degrees)\n",
      "thresholded_acq_threshold        :\t0 \n",
      "thresholded_acq_trigger_address  :\t1 \n",
      "thresholded_acq_trigger_en       :\tFalse \n",
      "thresholded_acq_trigger_invert   :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "ttl_acq_auto_bin_incr_en         :\tFalse \n",
      "ttl_acq_input_select             :\t0 \n",
      "ttl_acq_threshold                :\t0 \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer1:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq_I                    :\toff \n",
      "connect_acq_Q                    :\toff \n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "demod_en_acq                     :\tFalse \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_freq_cal_type_default        :\toff (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "thresholded_acq_marker_address   :\t1 \n",
      "thresholded_acq_marker_en        :\tFalse \n",
      "thresholded_acq_marker_invert    :\tFalse \n",
      "thresholded_acq_rotation         :\t0 (Degrees)\n",
      "thresholded_acq_threshold        :\t0 \n",
      "thresholded_acq_trigger_address  :\t1 \n",
      "thresholded_acq_trigger_en       :\tFalse \n",
      "thresholded_acq_trigger_invert   :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "ttl_acq_auto_bin_incr_en         :\tFalse \n",
      "ttl_acq_input_select             :\t0 \n",
      "ttl_acq_threshold                :\t0 \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer2:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq_I                    :\toff \n",
      "connect_acq_Q                    :\toff \n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "demod_en_acq                     :\tFalse \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_freq_cal_type_default        :\toff (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "thresholded_acq_marker_address   :\t1 \n",
      "thresholded_acq_marker_en        :\tFalse \n",
      "thresholded_acq_marker_invert    :\tFalse \n",
      "thresholded_acq_rotation         :\t0 (Degrees)\n",
      "thresholded_acq_threshold        :\t0 \n",
      "thresholded_acq_trigger_address  :\t1 \n",
      "thresholded_acq_trigger_en       :\tFalse \n",
      "thresholded_acq_trigger_invert   :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "ttl_acq_auto_bin_incr_en         :\tFalse \n",
      "ttl_acq_input_select             :\t0 \n",
      "ttl_acq_threshold                :\t0 \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer3:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq_I                    :\toff \n",
      "connect_acq_Q                    :\toff \n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "demod_en_acq                     :\tFalse \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_freq_cal_type_default        :\toff (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "thresholded_acq_marker_address   :\t1 \n",
      "thresholded_acq_marker_en        :\tFalse \n",
      "thresholded_acq_marker_invert    :\tFalse \n",
      "thresholded_acq_rotation         :\t0 (Degrees)\n",
      "thresholded_acq_threshold        :\t0 \n",
      "thresholded_acq_trigger_address  :\t1 \n",
      "thresholded_acq_trigger_en       :\tFalse \n",
      "thresholded_acq_trigger_invert   :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "ttl_acq_auto_bin_incr_en         :\tFalse \n",
      "ttl_acq_input_select             :\t0 \n",
      "ttl_acq_threshold                :\t0 \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer4:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq_I                    :\toff \n",
      "connect_acq_Q                    :\toff \n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "demod_en_acq                     :\tFalse \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_freq_cal_type_default        :\toff (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "thresholded_acq_marker_address   :\t1 \n",
      "thresholded_acq_marker_en        :\tFalse \n",
      "thresholded_acq_marker_invert    :\tFalse \n",
      "thresholded_acq_rotation         :\t0 (Degrees)\n",
      "thresholded_acq_threshold        :\t0 \n",
      "thresholded_acq_trigger_address  :\t1 \n",
      "thresholded_acq_trigger_en       :\tFalse \n",
      "thresholded_acq_trigger_invert   :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "ttl_acq_auto_bin_incr_en         :\tFalse \n",
      "ttl_acq_input_select             :\t0 \n",
      "ttl_acq_threshold                :\t0 \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4_sequencer5:\n",
      "\tparameter                       value\n",
      "--------------------------------------------------------------------------------\n",
      "connect_acq_I                    :\toff \n",
      "connect_acq_Q                    :\toff \n",
      "connect_out0                     :\toff \n",
      "connect_out1                     :\toff \n",
      "cont_mode_en_awg_path0           :\tFalse \n",
      "cont_mode_en_awg_path1           :\tFalse \n",
      "cont_mode_waveform_idx_awg_path0 :\t0 \n",
      "cont_mode_waveform_idx_awg_path1 :\t0 \n",
      "demod_en_acq                     :\tFalse \n",
      "gain_awg_path0                   :\t1 \n",
      "gain_awg_path1                   :\t1 \n",
      "integration_length_acq           :\t1024 \n",
      "marker_ovr_en                    :\tFalse \n",
      "marker_ovr_value                 :\t0 \n",
      "mixer_corr_gain_ratio            :\t1 \n",
      "mixer_corr_phase_offset_degree   :\t-0 \n",
      "mod_en_awg                       :\tFalse \n",
      "nco_freq                         :\t0 (Hz)\n",
      "nco_freq_cal_type_default        :\toff (Hz)\n",
      "nco_phase_offs                   :\t0 (Degrees)\n",
      "nco_prop_delay_comp              :\t0 (ns)\n",
      "nco_prop_delay_comp_en           :\tFalse (ns)\n",
      "offset_awg_path0                 :\t0 \n",
      "offset_awg_path1                 :\t0 \n",
      "sync_en                          :\tFalse \n",
      "thresholded_acq_marker_address   :\t1 \n",
      "thresholded_acq_marker_en        :\tFalse \n",
      "thresholded_acq_marker_invert    :\tFalse \n",
      "thresholded_acq_rotation         :\t0 (Degrees)\n",
      "thresholded_acq_threshold        :\t0 \n",
      "thresholded_acq_trigger_address  :\t1 \n",
      "thresholded_acq_trigger_en       :\tFalse \n",
      "thresholded_acq_trigger_invert   :\tFalse \n",
      "trigger10_count_threshold        :\t1 \n",
      "trigger10_threshold_invert       :\tFalse \n",
      "trigger11_count_threshold        :\t1 \n",
      "trigger11_threshold_invert       :\tFalse \n",
      "trigger12_count_threshold        :\t1 \n",
      "trigger12_threshold_invert       :\tFalse \n",
      "trigger13_count_threshold        :\t1 \n",
      "trigger13_threshold_invert       :\tFalse \n",
      "trigger14_count_threshold        :\t1 \n",
      "trigger14_threshold_invert       :\tFalse \n",
      "trigger15_count_threshold        :\t1 \n",
      "trigger15_threshold_invert       :\tFalse \n",
      "trigger1_count_threshold         :\t1 \n",
      "trigger1_threshold_invert        :\tFalse \n",
      "trigger2_count_threshold         :\t1 \n",
      "trigger2_threshold_invert        :\tFalse \n",
      "trigger3_count_threshold         :\t1 \n",
      "trigger3_threshold_invert        :\tFalse \n",
      "trigger4_count_threshold         :\t1 \n",
      "trigger4_threshold_invert        :\tFalse \n",
      "trigger5_count_threshold         :\t1 \n",
      "trigger5_threshold_invert        :\tFalse \n",
      "trigger6_count_threshold         :\t1 \n",
      "trigger6_threshold_invert        :\tFalse \n",
      "trigger7_count_threshold         :\t1 \n",
      "trigger7_threshold_invert        :\tFalse \n",
      "trigger8_count_threshold         :\t1 \n",
      "trigger8_threshold_invert        :\tFalse \n",
      "trigger9_count_threshold         :\t1 \n",
      "trigger9_threshold_invert        :\tFalse \n",
      "ttl_acq_auto_bin_incr_en         :\tFalse \n",
      "ttl_acq_input_select             :\t0 \n",
      "ttl_acq_threshold                :\t0 \n",
      "upsample_rate_awg_path0          :\t0 \n",
      "upsample_rate_awg_path1          :\t0 \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Status: OKAY, Flags: NONE, Slot flags: NONE\n"
     ]
    }
   ],
   "source": [
    "# Stop both sequencers.\n",
    "module.stop_sequencer()\n",
    "\n",
    "# Print status of both sequencers (should now say it is stopped).\n",
    "print(module.get_sequencer_status(0))\n",
    "print(module.get_sequencer_status(1))\n",
    "print()\n",
    "\n",
    "# Print an overview of the instrument parameters.\n",
    "print(\"Snapshot:\")\n",
    "module.print_readable_snapshot(update=True)\n",
    "\n",
    "# Reset the cluster\n",
    "cluster.reset()\n",
    "print(cluster.get_system_status())"
   ]
  }
 ],
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