{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3e168cd5",
   "metadata": {
    "tags": []
   },
   "source": [
    "Multiplexed sequencing\n",
    "======================\n",
    "\n",
    "The Cluster QRM/QCM supports six sequencers. The output of each sequencer is multiplexed, accumulated and connected to the output ports of the instrument.\n",
    "\n",
    "- In the first part of the tutorial we will demonstrate how to connect multiple sequencers to a single pair of output ports.\n",
    "- In the second part of the tutorial we will demonstrate frequency multiplexing by assigning different unique modulation frequencies (frequency of the carrier) to the sequencers. We will then show how to acquire, demodulate, and integrate the received frequency multiplexed waveforms.\n",
    "- In the third part of the tutorial we will demonstrate \\\"real mode\\\", where we will output real signals on each individual output port of the instrument.\n",
    "\n",
    "We will show this by using a [QRM](https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/cluster/qrm.html) and 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 (using the same sequencers)."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac4b6b87",
   "metadata": {
    "tags": []
   },
   "source": [
    "Setup\n",
    "-----\n",
    "\n",
    "First, we are going to import the required packages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "cdf8fac0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:57:59.763959Z",
     "iopub.status.busy": "2024-07-23T09:57:59.763771Z",
     "iopub.status.idle": "2024-07-23T09:58:00.597434Z",
     "shell.execute_reply": "2024-07-23T09:58:00.596452Z"
    }
   },
   "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",
    "from scipy.fft import rfft, rfftfreq\n",
    "\n",
    "from qblox_instruments import Cluster, ClusterType\n",
    "\n",
    "if TYPE_CHECKING:\n",
    "    from qblox_instruments.qcodes_drivers.module import QcmQrm"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3b52345f",
   "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://qblox-qblox-instruments.readthedocs-hosted.com/en/main/api_reference/tools.html#api-pnp) for more info)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "d6ca1b17",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:00.600879Z",
     "iopub.status.busy": "2024-07-23T09:58:00.600590Z",
     "iopub.status.idle": "2024-07-23T09:58:02.574134Z",
     "shell.execute_reply": "2024-07-23T09:58:02.570131Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "No devices found\r\n"
     ]
    }
   ],
   "source": [
    "!qblox-pnp list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "c5de95e2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:02.582109Z",
     "iopub.status.busy": "2024-07-23T09:58:02.581919Z",
     "iopub.status.idle": "2024-07-23T09:58:02.585320Z",
     "shell.execute_reply": "2024-07-23T09:58:02.584661Z"
    }
   },
   "outputs": [],
   "source": [
    "cluster_ip = \"10.10.200.42\"\n",
    "cluster_name = \"cluster0\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87a782bd",
   "metadata": {},
   "source": [
    "### Connect to Cluster\n",
    "\n",
    "We now make a connection with the Cluster."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "227adb61",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:02.587537Z",
     "iopub.status.busy": "2024-07-23T09:58:02.587355Z",
     "iopub.status.idle": "2024-07-23T09:58:03.316229Z",
     "shell.execute_reply": "2024-07-23T09:58:03.315496Z"
    },
    "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",
    "        }\n",
    "        if cluster_ip is None\n",
    "        else None\n",
    "    ),\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1ba35abd",
   "metadata": {
    "lines_to_next_cell": 2
   },
   "source": [
    "#### Get connected modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "315e66a0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:03.318944Z",
     "iopub.status.busy": "2024-07-23T09:58:03.318763Z",
     "iopub.status.idle": "2024-07-23T09:58:03.322537Z",
     "shell.execute_reply": "2024-07-23T09:58:03.321888Z"
    }
   },
   "outputs": [],
   "source": [
    "def get_connected_modules(cluster: Cluster, filter_fn: Callable | None = None) -> dict[int, QcmQrm]:\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": 6,
   "id": "7202dbd2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:03.324762Z",
     "iopub.status.busy": "2024-07-23T09:58:03.324595Z",
     "iopub.status.idle": "2024-07-23T09:58:03.350652Z",
     "shell.execute_reply": "2024-07-23T09:58:03.350047Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{4: <Module: cluster0_module4 of Cluster: cluster0>}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# QRM baseband modules\n",
    "modules = get_connected_modules(cluster, lambda mod: mod.is_qrm_type and not mod.is_rf_type)\n",
    "modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e1462755",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:03.352807Z",
     "iopub.status.busy": "2024-07-23T09:58:03.352639Z",
     "iopub.status.idle": "2024-07-23T09:58:03.355348Z",
     "shell.execute_reply": "2024-07-23T09:58:03.354807Z"
    },
    "lines_to_next_cell": 0
   },
   "outputs": [],
   "source": [
    "readout_module = modules[4]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e61b4894",
   "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": 8,
   "id": "3a52ca40",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:03.357506Z",
     "iopub.status.busy": "2024-07-23T09:58:03.357340Z",
     "iopub.status.idle": "2024-07-23T09:58:06.655935Z",
     "shell.execute_reply": "2024-07-23T09:58:06.652643Z"
    }
   },
   "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": "markdown",
   "id": "92181049",
   "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": "caddee14",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:06.664207Z",
     "iopub.status.busy": "2024-07-23T09:58:06.664002Z",
     "iopub.status.idle": "2024-07-23T09:58:06.668871Z",
     "shell.execute_reply": "2024-07-23T09:58:06.668203Z"
    }
   },
   "outputs": [],
   "source": [
    "# Waveforms\n",
    "waveform_len = 1000\n",
    "waveforms = {\n",
    "    \"gaussian\": {\n",
    "        \"data\": scipy.signal.windows.gaussian(waveform_len, std=0.133 * waveform_len).tolist(),\n",
    "        \"index\": 0,\n",
    "    },\n",
    "    \"sine\": {\n",
    "        \"data\": [math.sin((2 * math.pi / waveform_len) * i) for i in range(0, waveform_len)],\n",
    "        \"index\": 1,\n",
    "    },\n",
    "    \"sawtooth\": {\n",
    "        \"data\": [(1.0 / waveform_len) * i for i in range(0, waveform_len)],\n",
    "        \"index\": 2,\n",
    "    },\n",
    "    \"block\": {\"data\": [1.0 for i in range(0, waveform_len)], \"index\": 3},\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e43297b2",
   "metadata": {},
   "source": [
    "Let's plot the waveforms to see what we have created."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "74eaea58",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:06.671093Z",
     "iopub.status.busy": "2024-07-23T09:58:06.670929Z",
     "iopub.status.idle": "2024-07-23T09:58:06.907862Z",
     "shell.execute_reply": "2024-07-23T09:58:06.907203Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x621.118 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, figsize=(10, 10 / 1.61))\n",
    "\n",
    "for wf, d in waveforms.items():\n",
    "    ax.plot(time[: len(d[\"data\"])], d[\"data\"], \".-\", linewidth=0.5, label=wf)\n",
    "\n",
    "ax.legend(loc=4)\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": "85f590b2",
   "metadata": {},
   "source": [
    "Specify the acquisitions\n",
    "--------------------\n",
    "\n",
    "We will only use a single bin in this tutorial, so we can keep it simple"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a1444db9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:06.910245Z",
     "iopub.status.busy": "2024-07-23T09:58:06.910042Z",
     "iopub.status.idle": "2024-07-23T09:58:06.913281Z",
     "shell.execute_reply": "2024-07-23T09:58:06.912588Z"
    }
   },
   "outputs": [],
   "source": [
    "# Acquisitions\n",
    "acquisitions = {\"scope\": {\"num_bins\": 1, \"index\": 0}}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8be8a96b",
   "metadata": {},
   "source": [
    "Create Q1ASM program and upload the sequence\n",
    "--------------------\n",
    "\n",
    "Now that we have the waveform and acquisition specifications for the sequence, we need a simple Q1ASM program that sequences the waveforms and triggers the acquisitions. In this case we will play a gaussian and a sinusoid wave for path 0 and 1 respectively per sequencer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "8d4bf361",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:06.915601Z",
     "iopub.status.busy": "2024-07-23T09:58:06.915395Z",
     "iopub.status.idle": "2024-07-23T09:58:07.672498Z",
     "shell.execute_reply": "2024-07-23T09:58:07.669128Z"
    }
   },
   "outputs": [],
   "source": [
    "# Number of sequencers per instrument\n",
    "num_seq = 6\n",
    "\n",
    "# Program\n",
    "program = \"\"\"\n",
    "wait_sync 4\n",
    "play      0,1,4\n",
    "wait      140\n",
    "acquire   0,0,16380\n",
    "stop\n",
    "\"\"\"\n",
    "\n",
    "# Write sequence to file.\n",
    "with open(\"sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(\n",
    "        {\n",
    "            \"waveforms\": waveforms,\n",
    "            \"weights\": waveforms,\n",
    "            \"acquisitions\": acquisitions,\n",
    "            \"program\": program,\n",
    "        },\n",
    "        file,\n",
    "        indent=4,\n",
    "    )\n",
    "    file.close()\n",
    "\n",
    "# Program sequencers.\n",
    "for sequencer in readout_module.sequencers:\n",
    "    sequencer.sequence(\"sequence.json\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4bf796d",
   "metadata": {},
   "source": [
    "Multiplexed sequencer output control\n",
    "------------------------------------\n",
    "Each sequencer has two output paths. The output paths of each sequencer are physically connected to the instrument's outputs. It is possible to map any sequencer output path to any output port by using the sequencer's channel map.\n",
    "\n",
    "We can do so by calling `sequencerX.connect_outY(Z)` where `X`, `Y` and `Z` represents sequencer ID $\\in[0,..,5]$, output port number, and `Z`$\\in \\{$`\"off\"`, `\"I\"`, `\"Q\"`$\\}$.\n",
    "\n",
    "For most common sequencer configurations, the convenience function `sequencerX.connect_sequencer(config)` can be used to easily set the channel map. Some examples:\n",
    "\n",
    "Multiplexed sequencers on a QRM baseband\n",
    "```python\n",
    "instrument.disconnect_inputs()\n",
    "instrument.disconnect_outputs()\n",
    "for seq in instrument.sequencers:\n",
    "    seq.connect_sequencer(\"io0_1\")\n",
    "```\n",
    "\n",
    "Multiplexed sequencers on a QRM-RF\n",
    "```python\n",
    "instrument.disconnect_inputs()\n",
    "instrument.disconnect_outputs()\n",
    "for seq in instrument.sequencers:\n",
    "    seq.connect_sequencer(\"io0\")\n",
    "```\n",
    "\n",
    "Sequencers 1:1 on a QCM baseband\n",
    "```python\n",
    "instrument.disconnect_outputs()\n",
    "for idx in range(4):\n",
    "    instrument[f\"sequencer{idx}\"].connect_sequencer(f\"out{idx}\")\n",
    "```\n",
    "\n",
    "Sequencers 1:1 on a QCM-RF\n",
    "```python\n",
    "instrument.disconnect_outputs()\n",
    "for idx in range(2):\n",
    "    instrument[f\"sequencer{idx}\"].connect_sequencer(f\"out{idx}\")\n",
    "```\n",
    "\n",
    "For the sake of this tutorial we will map the <span style=\"color:#ed1c24\">in-phase path</span> of each sequencer to the ports with the even output port numbers (indexed from 0) and the <span style=\"color:#37b5b9\">quadrature path</span> of each sequencer to the ports with the odd output port numbers.\n",
    "<!---\n",
    ", like is shown in the figure below. Note that this figure is for the [QCM](https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/cluster/qcm.html), so it has 4 outputs.\n",
    "\n",
    "<img src=\"https://qblox-qblox-instruments.readthedocs-hosted.com/en/main/cluster/figures/QBLOX_MULTIPLEXING_DIAGRAM.svg\" alt=\"drawing\" width=\"1000\"/>\n",
    "-->"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f5bd4965",
   "metadata": {},
   "source": [
    "Now lets configure the first sequencer to output its <span style=\"color:#ed1c24\">in-phase</span> and <span style=\"color:#37b5b9\">quadrature</span> paths on $\\text{O}^{1}$ and $\\text{O}^{2}$ respectively. We will scale the amplitude of the signal such that we are able the show what happens when other sequencers are added and eventually output overflow occurs.\n",
    "\n",
    "We will also configure the channel map so that inputs $\\text{I}^{[1-2]}$ of the QRM are mapped to the <span style=\"color:#ed1c24\">in-phase</span> and <span style=\"color:#37b5b9\">quadrature</span> input paths of the same sequencer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "14bd58dd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:07.680278Z",
     "iopub.status.busy": "2024-07-23T09:58:07.680103Z",
     "iopub.status.idle": "2024-07-23T09:58:08.018513Z",
     "shell.execute_reply": "2024-07-23T09:58:08.017866Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "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\")\n",
    "\n",
    "# Configure sequencer\n",
    "readout_module.sequencer0.sync_en(True)\n",
    "readout_module.sequencer0.gain_awg_path0(\n",
    "    1.1 / num_seq\n",
    ")  # The output range is 1.0 to -1.0, but we want to show what happens when the signals go out of range.\n",
    "readout_module.sequencer0.gain_awg_path1(1.1 / num_seq)\n",
    "\n",
    "readout_module.disconnect_outputs()\n",
    "readout_module.disconnect_inputs()\n",
    "\n",
    "# connect output paths of the sequencer\n",
    "readout_module.sequencer0.connect_out0(\"I\")\n",
    "readout_module.sequencer0.connect_out1(\"Q\")\n",
    "\n",
    "# connect input paths of the same sequencer.\n",
    "readout_module.sequencer0.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer0.connect_acq_Q(\"in1\")\n",
    "\n",
    "# Start the sequence\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for the sequencer to stop\n",
    "readout_module.get_acquisition_status(0)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "# Plot the results\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len])\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][0:waveform_len])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bfd6f5c0",
   "metadata": {},
   "source": [
    "Let's add the second sequencer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "9976f452",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:08.021035Z",
     "iopub.status.busy": "2024-07-23T09:58:08.020844Z",
     "iopub.status.idle": "2024-07-23T09:58:08.259754Z",
     "shell.execute_reply": "2024-07-23T09:58:08.259040Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Configure the sequencer\n",
    "readout_module.sequencer1.sync_en(True)\n",
    "readout_module.sequencer1.gain_awg_path0(1.1 / num_seq)\n",
    "readout_module.sequencer1.gain_awg_path1(1.1 / num_seq)\n",
    "\n",
    "readout_module.sequencer1.connect_out0(\"I\")\n",
    "readout_module.sequencer1.connect_out1(\"Q\")\n",
    "\n",
    "# connect input paths of the same sequencer.\n",
    "readout_module.sequencer1.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer1.connect_acq_Q(\"in1\")\n",
    "\n",
    "# Start the sequencers\n",
    "for seq in range(0, 2):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop\n",
    "for seq in range(0, 2):\n",
    "    readout_module.get_acquisition_status(seq)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "# Plot the results\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len])\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][0:waveform_len])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2b07f034",
   "metadata": {},
   "source": [
    "Let's add the third sequencer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5f1abab4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:08.262176Z",
     "iopub.status.busy": "2024-07-23T09:58:08.261972Z",
     "iopub.status.idle": "2024-07-23T09:58:08.530086Z",
     "shell.execute_reply": "2024-07-23T09:58:08.529409Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Configure the sequencer\n",
    "readout_module.sequencer2.sync_en(True)\n",
    "readout_module.sequencer2.gain_awg_path0(1.1 / num_seq)\n",
    "readout_module.sequencer2.gain_awg_path1(1.1 / num_seq)\n",
    "\n",
    "readout_module.sequencer2.connect_out0(\"I\")\n",
    "readout_module.sequencer2.connect_out1(\"Q\")\n",
    "\n",
    "# connect input paths of the same sequencer.\n",
    "readout_module.sequencer2.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer2.connect_acq_Q(\"in1\")\n",
    "\n",
    "# Start the sequencers\n",
    "for seq in range(0, 3):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop\n",
    "for seq in range(0, 3):\n",
    "    readout_module.get_acquisition_status(seq)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "# Plot the results\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len])\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][0:waveform_len])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7755a82b",
   "metadata": {},
   "source": [
    "Let's add the fourth sequencer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "09aa6955",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:08.532492Z",
     "iopub.status.busy": "2024-07-23T09:58:08.532290Z",
     "iopub.status.idle": "2024-07-23T09:58:08.796633Z",
     "shell.execute_reply": "2024-07-23T09:58:08.796005Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Configure the sequencer\n",
    "readout_module.sequencer3.sync_en(True)\n",
    "readout_module.sequencer3.gain_awg_path0(1.1 / num_seq)\n",
    "readout_module.sequencer3.gain_awg_path1(1.1 / num_seq)\n",
    "\n",
    "readout_module.sequencer3.connect_out0(\"I\")\n",
    "readout_module.sequencer3.connect_out1(\"Q\")\n",
    "\n",
    "# connect input paths of the same sequencer.\n",
    "readout_module.sequencer3.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer3.connect_acq_Q(\"in1\")\n",
    "\n",
    "# Start the sequencers\n",
    "for seq in range(0, 4):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop\n",
    "for seq in range(0, 4):\n",
    "    readout_module.get_acquisition_status(seq)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "# Plot the results\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len])\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][0:waveform_len])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9579ebf7",
   "metadata": {},
   "source": [
    "Let's add the fifth sequencer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d5caafce",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:08.799065Z",
     "iopub.status.busy": "2024-07-23T09:58:08.798884Z",
     "iopub.status.idle": "2024-07-23T09:58:09.070387Z",
     "shell.execute_reply": "2024-07-23T09:58:09.069752Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Configure the sequencer\n",
    "readout_module.sequencer4.sync_en(True)\n",
    "readout_module.sequencer4.gain_awg_path0(1.1 / num_seq)\n",
    "readout_module.sequencer4.gain_awg_path1(1.1 / num_seq)\n",
    "\n",
    "readout_module.sequencer4.connect_out0(\"I\")\n",
    "readout_module.sequencer4.connect_out1(\"Q\")\n",
    "\n",
    "# connect input paths of the same sequencer.\n",
    "readout_module.sequencer4.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer4.connect_acq_Q(\"in1\")\n",
    "\n",
    "# Start the sequencers\n",
    "for seq in range(0, 5):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop\n",
    "for seq in range(0, 5):\n",
    "    readout_module.get_acquisition_status(seq)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "# Plot the results\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len])\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][0:waveform_len])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2114e1d2",
   "metadata": {},
   "source": [
    "Let's add the sixth sequencer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b061e1e1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:09.072747Z",
     "iopub.status.busy": "2024-07-23T09:58:09.072566Z",
     "iopub.status.idle": "2024-07-23T09:58:09.347278Z",
     "shell.execute_reply": "2024-07-23T09:58:09.346602Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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yNhnTWD+66uCaeqEJ0OMiGHHfwWnF0iBtyCzimneWH7L7Zq/kSJ4f34eUmGATk0lDV+Xx8upPO5n+Szp7C42Rb1HBAdwyogMTh6RWr/UnIiIijY9Ktzqk0k2kEfD5jI0RKovg0xsP3ZUz9SQY956xppaIWUqyYPs8+P5hKMk0ztkDIXkQnP8ahGnR9YakoMzFzR+s4ucdedW7hsaEOPjHmK6c2zsRyx+t/SjyPzILK7jh/ZXVo94ABqRG8fqkAZpyKiIi0kipdKtDKt1EGjC/H9KXwcZPYcmLh17X5RwY/YSxML5IQ+GugC1z4NObjV1tAaLawEl3GJs62PQm3EyVbi8v/biD6b+kkV1s7AR8Sqc4/n1BT2JDnRqdJEfN4/Ux/Zd0/v3VZkqqPPRJieSJC3vSPl5TzUVERBoblW51SKWbSAP242Pw46OHngttATctM3blFGmoijJgwyfwwyPGTrNg7HaaMgSG/92YAh3W8o9305V68dAXG3lj4S4AQhw2Zlw3RBskSJ3amFnM+FcXU1zpwW61cNvIDozpmUhqbIjZ0URERKSGVLrVIZVuIg3QrgXwzb2wb/XBc13Pg05nQqsBENPOrGQitZO7FX55HVa8Dd6qQ6874TY47QEzUjU76/cW8c/PNrB8j7HpypieLbl1RAc6JGgUktS9nbml/OvLTczbnFN97qJ+rZgwuDW9kiPNCyYiIiI1otKtDql0E2lAKgpg1fvww78Ojg7qeIYxjTS8FVit5uYTOVoZK2Dl27BhNlQVHzx/1tPQ53KwO8xK1qStTi/k4S82VpdtANcOa8vfRncxMZU0B36/n/eW7GH6snQ27jv4d/62kR24bWRHE5OJiIjIkah0q0Mq3UQagC1fwbqZxtptPo9xLq4z9JsMvcZrN1JpOioKYNMXsPlL2PqVca7tcLhsptZ7q0PrMop46aftzFmXVX3u1M7xPHBON5KjtSupHF/LduXzxsKdzN2QDUCnhDAeOLcbg9vGmJxMREREDkelWx1S6SZiIo8LNn8OH197sGwLS4ShN0P/yRAQZG4+kfriqYLFL8D8p4wNFwIjjLXeBl1ndrJGL7ekirOeW0BOiTGdt3OLMJ68qBfdEsO1K6mY6om5m3nxhx3VxxMGpzBpSKqmOYuIiDQwKt3qkEo3EZMUpsPUCyBvy8FzqSfBmGcgtoN5uUSOp81zYNZk8FQax0FR0OMio4CzB0JAoLn5GhGfz8+DX2zk7UW7q89dc1Ibrju5HbGhTvOCifzG9pxSbnx/BVuzSwGIDXUy47rBtIsLNTmZiIiI/EqlWx1S6SZynLkr4fuHjIXlXaVGydD9Qjj9IY1sk+apPB/mPWD8nfityBS4/mcI1O+mP+Pz+Xn62628s3g3JZXGiNmWEYG8cnk/eraKNDecyGFkFlbw5NwtzF69F9+BV+mD20Zz9YltObFDLIEBNnMDioiINHMq3eqQSjeR42j9R8Z0upwNxnGLHnDJdIhoZW4uEbP5fLDqXcj4BdbOPLjTaVA0nHIPDLwGNDXyd1amFfDyjzv4ZqOxVpbVAv8a24PxA5I1lVQavIyCcv7y4Rp+2Z1fXb51Twrn4xtOwGHXxkEiIiJmUelWh1S6iRwHRRmw+L+w5EXjODASzvsvdBqtIkHkf5VkGQX13L8dPNf1XOh6HnQbq78zB2zPKWX0fxbg8voAY1fIi/snkxipEbPSuGQWVvDq/J3VU6OjQxzcfUZnLh6QbG4wERGRZkqlWx1S6SZSTzxVsPJdyFwNa6aB33hjzJCb4ITbIDTOzHQiDZvfD7NvNP7u/NbZ/4F+V5gSqaFweXw89tVm3vx5F2BslPCvsT3o1zrK5GQix+bDX9K566O11cdvXtGfYR3isNs06k1EROR4UulWh1S6idSTT6fAqqkHj2M7woCrtTujSG34fDBzImz6/OC5AdfAyX9tdsW1z+fn0zV7eXPhbtbtLQIg2GFj7m3DSI4ONjmdyLHz+fw8MmcTry/cVX0uNtTJxzcMJSVGf8ZFRESOF5VudUilm0gdK9sPX/8V1s00jhP7wsBrofcl5uYSacy8bnjphIO7/Ua3hZPvhu4XgM1ubrbjwOP18cDnG3lvyR7AWLvtpuHtGdu3FW1iQ0xOJ1K3yqo8jHl+IbvyygBoHRPM30Z34fSuCVqrUERE5DhQ6VaHVLqJ1JHKItjytbEzaVG6cW7kA3DibabGEmkyCtNg7QxY9AJUFhrnek+A8140NVZ9W7+3iNtmrGZ7TikAo7olMHFIKie0jzU5mUj9qXB52ZxVzBVv/UJRhRuAG09px52nd8JqVfEmIiJSn1S61SGVbiJ1IGcTzLgc9m8zjgMjYcLH0KqfqbFEmqT9O+Cnx2HtdOM4IgVG3Ac9LzI3Vx2rdHv57w/beWX+Tqo8PqKCA7j/7G6c1yfJ7Ggix82uvDLeXLirepRnm9gQnh3Xm17JkeYGExERacJUutUhlW4ix6A4E76+GzZ+evBcUn847UFIPcG8XCLNwbf3w8/PHjyOTIGT/tIkNlrw+fzc9MFK5qzLAuDUzvE8c3FvIoIDTE4mYo53F+/m8a+3UFrlIcRh469ndubSgSnaZEFERKQeqHSrQyrdRI6C3w9z/w5LXwa/FyxW6HgmjH4cIlqZnU6kefD5IHMlLH8LVv9m05Ixz0LfSWBtnG/GP129l4e+2EheqYsAm4WnL+7NmJ4ttZaVNHsllW6un7qCn7fvB+DCfq144sKe+rshIiJSx1S61SGVbiK15K4wRreteNs4ThkKZ/4bWvY0NZZIs5a3HeY9AJs+M47bngLjpoIzzNRYtVFY7uL577fzxoGdG0Oddv41tjvn9tZ0UpFfub0+3l+yh4e+3ITX52douxjuPrMzPVtFmh1NRESkyVDpVodUuonUQvE+mHoB5Gwwjs/9L/S5zNxMImLwemDhM8aXuwyCoqH/lXDqvdDAR8LM3ZDF3z9ZT15pFQCTT0jlnjO74LA3ztF6IvXt/aV7uHf2en59ld8iPJArT0zl2mHtzA0mIiLSBKh0q0Mq3URqwOuG+U/AstegIh9C4uHcF6DjKLOTicj/ylwFH1wCJfuM48E3wpCbIKLhjRjz+fzc/9mG6kXi28eH8vezujC8U7zJyUQavvT8ch78YiPfbswGwGqBqVcNYqh29hURETkmKt3qkEo3kSPY8pVRuO1dYRzHdoTLZkFUa3Nzicgf87jgl9dh7j3GsT0QRj0CPS6EwAhzsx2wYFsury/YxU9bc7Fa4LqT23HriA4EBtjMjibSaPh8flZnFPLg5xtZnV4IwLm9E3n8wp447fq7JCIicjRUutUhlW4ih+F1G2/Yt8yBXfONc44wGPMMdBsLNru5+USkZlZNNf4uZ64yjp0RcNlMSBlkWiS/38+7i/fwz883VE+Ne/KiXlzYT5uwiBytkko3d3+0jq/W78Pnh/6to3jyol6kxoaYHU1ERKTRUelWh1S6iRzG/Cfh+4cOHg+4Gk68XTuTijRGPi8ses7Y/KRgNzhCjb/Tw/8GdudxjVJW5eHW6av4blMOAOf3SeKqk9rQLbFhjL4TaewWbc/j2vdWUFrlIcBm4coT2vB/ozpht2l9RBERkZpS6VaHVLqJ/IbPZ+x+OPtGYyF2gBH3wYl3NPiF2EXkCFxl8P7FsGehcXzSnTDiH8ft6VfsKeC+T9ezIbMYh93K/53eiatPaoNF/7aI1Kn0/HL+Pns987fmAjCySzzPX9KXIIemm4qIiNSESrc6pNJN5ACfF+bcCcvfNI6TB8OVX6tsE2lKfF5jxNuXdxjHfS43ivXQ+tu4IKekkvlb87hr1hp8fogMDuCtKwbQJyWq3p5TRGDOun3cPmM1VR4ffVIieWPSAKJDHGbHEhERafBUutUhlW4iGJslfDoFyvcDFjjxNjjhVgjSm2KRJsfvh1mTYcMnxnFUG7joLUjsU+dP9e3GbG6YugKPz3gpMqpbAg+c050WEYF1/lwi8nvLd+dz1TvLKapw0zYuhHcmDyQ5OtjsWCIiIg2aSrc6pNJNmjVXmbHQ+rf3g6fCWGT9jEehz2VmJxOR+uTzwvbvjNGthWnGuRH3w0l31NlTrEwr4NLXllDp9gFwUodY3pg0AIdda0uJHE/bskuY9OYyMosqcditjOwSz0Pndicm9Piu6SgiItJYqHSrQyrdpNny+eDdc2D3AuO4/WlwyQdgCzA3l4gcPyVZ8M0/YN2HxvEJtx3zBguVbi8zV2Tw9DdbKCh3M7xTHC9f3g+nXetJiZglq6iSK95axuasEgDG9GzJC5f2NTmViIhIw6TSrQ6pdJNmqTAdfnwUVr8PVjuccg8MvhEcmnIi0iz98Cj89Jhxue0pcMkMCKj9FNB1GUVc8+5ysoorAejVKoIPrh1MsMNeh2FF5Gi4vT5mr9rLXR+txe+HUzvH88A53TTdVERE5H+odKtDKt2kWfG6YccPMPsGKM8zzo15FvpPNjWWiDQAGz8z/m1wlUJQNAy7E4ZMqfHdy6o8jH5uAXv2l5MUGcSVJ7Zh/IBkQpwq3EQakhe+38aT32wFID7MyVMX9+LE9rHaSVhEROQAlW51SKWbNBvuCnh7DOxdbhwn9IDTH4R2p5qbS0Qajl3z4cNJUJFvHA++EU68/U93N/X5/Hy+NpOnvtlKWn45iRGBfHXbMCKCNFVdpKHakVvKjVNXsiXbmG56ft8kHjy3O6EqyUVERFS61SWVbtIsbJgNPz4GuZvAYoO+l8NpD0JghNnJRKSh8bphwVPGFHSAyNZwwyJwhv7upn6/n9tnrGb26kwAYkOdvHJ5X/q1jj6eiUXkKBRVuHn2u628u3gPXp+fEIeNe8d05ZKBKWZHExERMZVKtzqk0k2avM1fwvRLDxxY4PKPNbpNRP6c3w+bPoev74bivca57hfCeS+B3UFplYcn527hw+XplLu82K0WbhvZgStPbKP120QamUXb87h39np25pUB8NC53ZgwuLWmm4qISLOl0q0OqXSTJstTBV/cDmtngM9j7E464h/QspfZyUSksdj2Lbx/4cHjbufjHvEAF05LY01GEQBWCzx6fg/GDdDoGJHGyu/38+AXG3nr590AnNWzJY+M7aFp4iIi0iypdKtDKt2kSfJ64LObYM0HxnHHM+Hid8HuMDeXiDQ+m+fAps+q/z2ptAZzTsX9ZAe25eHzutM/NYqWEUEmhxSRY+X3+3l1/k6emLsFj89Py4hAnriwFyd2iDU7moiIyHGl0q0OqXSTJidnE8y+ETJXgsUK4z+ATmeYnUpEGrn8tV+T+8nddPLvYoevJbtHvcWIE4aYHUtE6tjq9EJum76K3fvLsVktPHVRL87rk2R2LBERkeOmNj2R9ThlEhGzucrgq7/CyycZhZszAi54Q4WbiBwTv9/PC99vY/QXAVxacRc5lhjaWfcx4oexsPi/4POaHVFE6lDv5Ei+unUYY/sk4fX5uW3Gam6atpLvN2ebHU1ERKTBUekm0hxUFsF7Y2Hpy+BzQ8czYMoS6H6+2clEpBErrnTz2FebefKbrWQVV2IPj8cz6StoczJ4KmDuPfDWmbB3pdlRRaQOBTlsPHVRL64YmgrAF2v3ceXby/ly7T5zg4mIiDQwja50e/HFF0lNTSUwMJBBgwaxbNmyGt1v+vTpWCwWzjvvvPoNKNLQeKpg5hWQvhQCI2DCR3DpDAhPNDuZiDRin63JZPAj83hl/k4AbjilHfP+cgqJqZ1g4qcw5llwhBr/9rw23Bj1JiJNhtVq4f6zu/Kf8b3p2tKYWnPnzDVMX5ZmcjIREZGGo1GVbjNmzOCOO+7g/vvvZ+XKlfTq1YtRo0aRk5Pzp/fbvXs3d955JyeddNJxSirSQGyfB093hR3fQ0AwTPwM2o80O5WINHJvLtzFLR+sotzlJTrEwZTh7bhrVCdCnXbjBhYL9J8MNy6BHhcZ5+beA4tfNC+0iNQ5i8XCub2T+OymExjWMY4Kt5e7P17H1CV7zI4mIiLSIDSqjRQGDRrEgAEDeOGFFwDw+XwkJydz8803c/fddx/2Pl6vl2HDhnHllVeyYMECCgsLmT17do2fUxspSKOVtQ7ePANcpRDWEs55HjqcZnYqEWnk3li4i4e+2AjA1Se24Z7RXbBZLX98B78ffngE5j9uHCf1g9FPGP8VkSbD6/Pz9LdbePGHHVgtxujXKcPbE+ywmx1NRESkTjXJjRRcLhcrVqxg5MiDo3SsVisjR45k8eLFf3i/Bx98kPj4eK666qoaPU9VVRXFxcWHfIk0KtkbYPYUeP00o3BLPQluXavCTUSOSUmlm7/OWltduN00vD1/P+sIhRsYo96G/w1O+ZtxvHcFzLgcKgrrN7CIHFc2q4U7T+/EpYNS8PnhxR92MOzxH3lv8W58vkbzGb+IiEidajSlW15eHl6vl4SEhEPOJyQkkJWVddj7LFy4kDfeeIPXXnutxs/z6KOPEhERUf2VnJx8TLlFjquivfDO2bB6qrGIeasBMO49sDvMTiYijdiGzCLOeeFnZixPx2KB20Z24C+nd8RiOULh9iuLBU75K9yyCiJSoHgvvDAANn5av8FF5LiyWCw8MrYHL0/oS0p0MHmlVfzj0w08eKCsFxERaW4aTelWWyUlJVx++eW89tprxMbG1vh+99xzD0VFRdVf6enp9ZhSpA7lbTd2KC3fD8GxcNbTxmLmQVFmJxORRsrv9zNtaRpj/7uIXXllJEYEMv2awdw2shaF229Ft4WL34HQFlCWAx9dA5mr6zy3iJjrjO4t+e6Ok7n3rC4AvL1oN5e9voSduaUmJxMRETm+Gs0iC7GxsdhsNrKzsw85n52dTYsWLX53+x07drB7927OPvvs6nM+nw8Au93Oli1baNeu3e/u53Q6cTqddZxepJ5t+Qo+vhaqio312674EmJ+/+dbRKSmftiSw72frGdvYQUAwzvF8fTFvYkKOcaRs0l94fb1MP1S2PYNvD4STvoLnHK3MSJORJoEh93K1Se1xe+HR77axM/b9zPxzWW8cnk/uiVGmB1PRETkuGg0I90cDgf9+vVj3rx51ed8Ph/z5s1jyJAhv7t9586dWbduHatXr67+Oueccxg+fDirV6/WtFFpOuY/CR+MNwq3lCFw7U8q3ETkmOSVVnHb9NXsLazAbrVw95mdeWPSgGMv3H5lC4Cxr0C7U8Hnhp8eg0+uA4+rbh5fRBqMa4a1Zf7/Dad1TDAZBRWc9dxC7p29jka0l5uIiMhRazQj3QDuuOMOJk2aRP/+/Rk4cCDPPvssZWVlTJ48GYCJEyeSlJTEo48+SmBgIN27dz/k/pGRkQC/Oy/SKBXshiUvw9KXjOOB18Lp/9L6bSJyTBZuy+OBzzdQVOGmQ3won0w5gVBnPbxcCI6Gyz+Ble/B57fC2hlQkmWsQxmoUTAiTUlydDBvTx7Iw19s5IctOUxdkgbAnad3IjJYr1tERKTpalSl27hx48jNzeW+++4jKyuL3r178/XXX1dvrpCWlobV2mgG74kcvZzN8PoIY3dSgJEPwIm3mRpJRBo3j9fHw19u4u1FuwGICArgmXG966dw+62+l0N4S/hwEuz6Cd48A8a/b6z/JiJNRpvYEN64YgBvLtzFg19sZOqSNL5en8XjF/bk1M4JR34AERGRRsji19juP1VcXExERARFRUWEh4ebHUeaO58PFv0HFj4LlYUQ3Q6G/w16XGh2MhFpxEqrPNw0bSU/bskFYOKQ1txxWsfjOwIlczVMuxhKsyEoGibPgfgux+/5ReS4+XFLDg9/uYntOaVYLfDAud2ZMCjl6DZoEREROc5q0xOpdDsClW7SoMx/Er5/yLgc3gqu/RFC40yNJCKN23cbs3n4y43s3l9OYICVZ8f14Yzuv9+g6LgozoQPLoF9q40ppr0nQP/JENvBnDwiUm+qPF7u/WQ9M1dkAHBKpzgePb8HLSOCTE4mIiLy51S61SGVbtJgrJkOs28Av8/Y6e+EW7XukYgcNb/fz+sLdvGvOZsAiAtz8trE/vROjjQ3WHk+vHce7FtjHFvtcOGb0PVcU2OJSN3z+/28On8nT327FZfHR0RQAM9f0odhHfWBooiINFwq3eqQSjcxnacKvr4blr9pHPebDGOeAU3BEJGjtLewgrs/WsuCbXkAXD64NX89s3P9r99WUz4vbP8OFr9orPNmtcO4qdDpTLOTiUg92J5Tyh0frmZtRhFWC/zfqM5cf3JbTTcVEZEGSaVbHVLpJqby++GT62HtdON46C3GpgnaMEREjoLH6+P577fz2oKdlLu8OO1W7j6zM1cMTW2Yb259Xvj4Wlg/C2wOGP8BdBhpdioRqQdVHi/3f7qB6b+kAzC6RwueuLAXIQ3lwwAREZEDVLrVIZVuYppd8+G7B2DvcrDYYPw06HSG2alEpJEqqXRzx4dr+HZjNgD9W0fx+IU9aRsXanKyI/B6YNZk2PQZ2APh0hnQ9hSzU4lIPZm2NI37P1uP2+unY0Ior1zenzaxIWbHEhERqabSrQ6pdBNT/PIGfHmHcTkgGM56Cnpfam4mEWm0NmQWce27K9hbWIHDbuXxC3pybu/Ehjm67XA8LvhwImz9yvg38eL3NOJNpAlbsaeAG6auIKekijCnnSmntufqE9tgt2mkv4iImK82PZF+c4k0NDmb4dv7jMt9JsCta1S4ichR+2rdPsa/uoS9hRWkRAcz7epBnNcnqfEUbgB2B1z8DrQfCe5ymHYRLHrBmIIvIk1Ov9ZRfHHzifRvHUVJlYfHvtrMDe+vpNzlMTuaiIhIrWik2xFopJscN34//PAvmP+EcdyiJ1z7I1htpsYSkcbJ4/Xx+NwtvDp/JwADU6N5/Yr+hAcGmJzsGHiqjFHAq6Yax70vMzaWsTvNzSUi9cLr8/PRigzu/XQ9Lo+PlOhgXprQl26J2r1dRETMo+mldUilmxwXZXnw3T9h1XvGcWJfOPdFSOhqaiwRaZy+2ZDFnTPXUFxpjAqZMrwdt4zogNPeBEp8vx+Wvgxz/wZ+H7QaaOxsGpZgdjIRqSfLduVz2/RVZBZVEua088YVAxjYJtrsWCIi0kypdKtDKt2k3rnK4fWRkLPBOD79XzD0JnMziUijVFLp5qMVGTz05Sa8Pj/BDhsPndudC/q1Mjta3ds+z9hgobIIwpPgkunQsqfZqUSknhRVuLnmneUs252P027l3rO6MH5gCgFa501ERI4zlW51SKWb1CtPFXx8LWycDSHxcNHbkHqC2alEpBHaX1rFxa8sZkduGQA9W0Uw6/qhOOxN+A1p3nb4YDzs3wZhLeG6+RAab3YqEaknFS4vU6at5PvNOQCc2jmelyf0a9r/zomISIOjjRREGoPyfHhvrFG4WWxwwesq3ETkqGzPKeWil43CzW61MKpbAi9e2rfpvxGNbQ9XfwexnaBkHzzbA35+zuxUIlJPghw2Xr28Hw+c043AACvfb87hopcXsS6jyOxoIiIih6WRbkegkW5SLwp2w9QLjdEZznBjV752p5qdSkQaofwyF6P/s4Cs4koSIwJ57+pBtIsLNTvW8ZWzCd47H0oyjeMJHxk7nYpIk/XjlhxufH8l5S4vYU47r07sz+C20Y1rZ2YREWmUNL20Dql0kzqXuQrevxjKcox1iC6bCQndzE4lIo2M3+/nzZ938+IP28kvc9E2LoQPrxtCbGgz3cnT64HPb4HV74PNCSf9BU6+C/QGXKTJyi2p4qZpK1m6Kx+AEZ3jef7SPgQ77CYnExGRpkzTS0Uaqm3fwVtnGYVbQndjWpQKNxGppYIyF4/M2cRDX2wkv8xFZHAA/72sb/Mt3ABsdhj9JLQbAd4q+PER+PlZY7dTEWmS4sKcvD6pPxf2a4XDZmXe5hzOe/Fnfticg8YViIhIQ6CRbkegkW5SZ/bvgP8OBq8L2pwM46ZCoP5MiUjtpO0v5/yXFpFXWgXAHad1ZPIJqYQFBpicrIHw+2HR8/DtP4zj1JOMEcUBQebmEpF6tSqtgCvf/oWCcjcAJ7SP4ZlxvYkPCzQ5mYiINDUa6SbSkPj9sOkLeO3UA4XbMLhslgo3EamVKo+Xp7/dysWvLCavtIo2sSH8Z3xvbhnRQYXbb1ksMPRmGHE/BATD7gUw7yGzU4lIPeuTEsUPd57CdSe3xWm38vP2/Zz3ws/kllSZHU1ERJoxjXQ7Ao10k2O26AX45u/GZasdblgMcR3NzSQijcr+0iqun7qCX3YXAJAUGcTHNw4lIVwjOP7U1rkw7WLjcq9LYMwzGvEm0gzszC3lqneWsyuvjEFtonn+0j4a8SYiInVGI91EGoKcTfB8v4OFW1J/uPAtFW4iUitbs0s4778/88vuAsKcdp68qBdf33aSCrea6DgKhv8dLFZY84Gxa3RlsdmpRKSetY0L5bWJ/QgKsLF0Vz6nPPEjb/+8i0q31+xoIiLSzGik2xFopJsclcpiYzrp/m3Gcb/JxggL7aInIjVUUunmP99t44NlaZS5vKREB/PmFf1pHx9mdrTGZ9cCmH4pVBVDy14w4WMIiTU7lYjUs1VpBfzz842sSS8EIDbUwTtXDqRbYoS5wUREpFGrTU+k0u0IVLpJrZXnw9TzIXMVhLWEK7+GqFSzU4lII5JXWsUVby1j/V5jVNbANtG8PKEf0SEOk5M1YvvWwHvnQ3kexHSAyz+ByGSzU4lIPfP5/ExduoeXf9xBZlElqTHBvH/NYJIiNdVcRESOjkq3OqTSTWrF44L3xsKehRAcY4ymSOxtdioRaUS255Qw+e1fSM+vICbEwb8v6MnwzvHYrBope8zytsN750FROoQnweWzNeVfpJkoLHdx1nML2VtYgcNmZXSPFtx1RmcSVb6JiEgtaU03ETO4K2HmJKNwc4TBpM9VuIlIrXy3MZvz/7uI9PwKUqKDmXn9EEZ2TVDhVldi2xujj2M7QvFeeOsMY/1NEWnyIoONqaWD20bj8vqYvTqTsf/9mU37tM6jiIjUH410OwKNdJMaqSw21gvavQBsTrhkGrQfaXYqEWkk0vaX8/CXG/lmYzYA/VpH8erl/YgJdZqcrIkq2w/vX2AsA9CyN1zzPVhtZqcSkePA7/ezJqOIu2atYWt2KaFOO69c3o8T2mudRxERqRmNdBM5nsry4J2zjcLNEQYTPlLhJiI19svufM59cSHfbMzGaoFrh7Xl/asHqXCrTyExcMkMCIyAfavh0ylQWWR2KhE5DiwWC72TI5l53VAGtYmmtMrDpDeX8fJPO7S7qYiI1DmNdDsCjXSTP1WUAe+eZ+xSGhxjFG6JfcxOJSKNQHp+OTOXp/PyTztxeX30bBXBUxf1okOCdic9btZMh0+uMy6HJ8GFb0HKIHMzichxU+Xx8pcP1/DF2n0AtIwI5JGxPRjeOd7kZCIi0pBpI4U6pNJN/lDednj3XCjOgPBWxk54WpBbRGrgy7X7uGvWGspcxqiK07sm8J/xfQhyaIrjcbf7Z2OkW8EuY+Tb1fMgtoPZqUTkOPH5/MxamcGz324ls6gSp93K1KsH0b91FBaL1tMUEZHfU+lWh1S6yWGVZMNrpxqFW0x7Ywe8yGSzU4lIA+f3+7nn43VM/yUdgD4pkVw6MIXz+7bSZglmcpUZH6Jk/GIsEzD6Ceh9idmpROQ4qnR7mfTmMpbuygegV3Ik70weQGSww+RkIiLS0GhNN5H6tOUreGPkwcJt8tcq3ETkiFbsyeead1cw/Zd0bFYLU4a3Y+Z1Q7iof7IKN7M5QmD8NGg1EFwlMPt6+OYfoM8lRZqNwAAbT17Ui+ToIADWpBdy3os/M3N5usnJRESkMdNItyPQSDc5xMZPYeYV4PdBWCJM+hxi25udSkQasEq3lzcW7uKJuVuqzz10XncuH9zaxFRyWD4vzH8CfnzUOB75AJx4m6mRROT425JVwqWvLWF/mQuASUNaM+XU9sSHBZqcTEREGgJNL61DKt2kWuYqeGMUeKug16Vw1pPG6AgRkT+wM7eUS15bQnZxFWBMV7qwbxITBrfWWkEN2eIXYe7fjMvnPA99Lgf9/xJpVoor3by+YBfPzdsGQFignU9uHEr7eG12IyLS3Kl0q0Mq3QSAsjx49RQoSoeOZxjTkKxa8FxE/tjO3FKuemc5u/LKaBkRyJTh7Zmg0W2Nx9y/w+IXjMsdz4BxU8EWYG4mETnu5m7I4qlvtrA1u5T4MCd3nNaRi/snY9WyACIizZZKtzqk0k3I227sbJe+BKLbwbU/GDvciYgcRmmVh+fnbeOtRbtxeXwkRQYxe8oJxIU5zY4mteHzwQ8Pw6IXjBHOA6+DUY+AzW52MhE5znJKKjnruYXklhijls/tncitIzrQNi7U5GQiImIGlW51SKVbM+b3w4Kn4MfHwOcGRyhc/R3EdzE7mYg0UJv2FXP1O8vZW1gBwEkdYvn3BT1JjAwyOZkctU2fw4wJxuUWPeCKL/XBi0gzlF1cyftL03j++23Ve6z8fXQXrhnW1txgIiJy3Kl0q0Mq3Zopvx++uffg1KL2I+H0h1W4ichh7cgt5T/fbeOr9ftwe/20igriwXO7MbxTvNZuawpWvA3f3g+VhdD7Mjjvv2YnEhGTfLE2kxe+387mrBIAJp+Qyl/P6ExggJYdERFpLlS61SGVbs2Qqxw+uxnWzzKOz3oK+l+lRbRF5LAq3V7GPL+Q7TmlAHRtGc4H1w4mIkjrfzUpexbDW2cCfjjpTjj1Xv1eEGnGnpy7hRd+2A5A/9ZR/PXMzvRvHaUPWkREmgGVbnVIpVszU5oL742F7HVgsRk7lPa/0uxUItJAfbQig/s/20BplYcAm4V7zuzCRf1bERaowq1J+vk5+PYfxuXTHjJGvYXEmJtJREzz/eZsbnx/JZVuH2Cs9fbsuN4q3kREmjiVbnVIpVsz4vPBtItg+3cQEgcXvQ2pJ5qdSkQaoPlbc/lgWRpfrc8CICzQzouX9mVYxziTk0m9W/A0zHvgwIEFLv0QOp5uaiQRMc+iHXk8Omcz6/YWAdApIYw7Tu/IqG4tTE4mIiL1RaVbHVLp1ows/i/MvQfsgXDtj1q/TUR+Jz2/nMfnbuHzNZnV5yYMTuG+Md1w2K0mJpPjxu+HmVfAxtnGcXgrmLIEnGFmphIRk725cBcPfrERMGaeXzIwhUsHptA9SRuviIg0NSrd6pBKt2YiY7mxVo/XZazhNuBqsxOJSANSVuXh243Z3P/ZBooq3FgsMH5AMiO7JDC8UzxWq6YSNSt+P5Tnw2vDoXAPpAyBS2doV1ORZm5LVgmvzN/Bxyv3AmC1wI2ntOf20zpi0+8JEZEmQ6VbHVLp1gzsmg8fXAKuUug0GsZP0+LYIlKtsNzFmOcXklFQAUDPVhE8MraHRi8IZKww1gGtKoJu58NFb5mdSERM5vf7+XFLLjNXpDNnnbEEwUkdYnlufB+iQhwmpxMRkbqg0q0OqXRr4jZ/CTMng7cK2gwzCjdNERIRjDdOn63J5Im5W6oLt0sGpnDvWV0IcdpNTicNRsZyeON08HshtiOc/Ry0HmJ2KhFpAD5bk8lfZ62lwu2lVVQQr1zej26J+sBGRKSxU+lWh1S6NWGrp8GnNxlvlDqPgQvegIBAs1OJSANQUObino/X8fWGrOpzs64fQv/UaBNTSYO18Fn47n7jckgc3LgEQmJNjSQiDcOmfcVc994K0vLLCXbY+Oc53RjWIY4WEXrNKSLSWB2X0s3lcrFr1y7atWuH3d50P/FX6dZE/fIGfHmHcbn3ZcbIBFvT/XMsIjXj8/l5f+ke/jNvG3mlLgJsFs7s3pIRXeI5t3eS2fGkIcvZDNMuNtZ4Sx5k7GoaFGl2KhFpAArLXVw/dQVLduYDxlpvfzm9E1ed2IbAAJvJ6UREpLbqtXQrLy/n5ptv5p133gFg69attG3blptvvpmkpCTuvvvuo0/eAKl0a4I2fQEfXg5+HwyeAqc/DFbtOijSnPl8fhZsz+PNhbv4aWsuAO3jQ3nyol70To40N5w0Hlnr4e3RUFlkFG8TP9MIahEBjA15rp+6ggXb8qrPxYY6eO+qQXRpqfcYIiKNSW16olo3Dffccw9r1qzhxx9/JDDw4AvJkSNHMmPGjNqnFTmevnsAZlxmFG59JsCof6lwE2nmtmWXMPq5BUx6cxk/bc3Fabdy/9ldmXPLSSrcpHZadIcrvjR2MU1fanzAU1FgdioRaQBCnHbeu2oQux4dzWPn9yApMoi8UhfnvfgzT87dQn6Zy+yIIiJSD2o90q1169bMmDGDwYMHExYWxpo1a2jbti3bt2+nb9++FBcX11dWU2ikWxOy9FX46v+MywOugVGPgF27SIk0VwVlLqYtS+O1BTspLHcTFmjnrB4tmTQ0VaMO5Njs+MGYaup1QWQKXPg2tOpndioRaUDyy1yc9dwC9hVVAtAuLoRbR3bkzO4tCLDpA2ERkYasXke65ebmEh8f/7vzZWVlWCyW2j5crb344oukpqYSGBjIoEGDWLZs2R/e9rXXXuOkk04iKiqKqKgoRo4c+ae3lybK54MFTx8s3EbcD2c9qcJNpBnbX1rFxa8s5om5Wygsd9O5RRg/3nkKj13QU4WbHLt2w+GqbyCyNRSmwZujYPlbZqcSkQYkOsTBrBuGcvOp7YkJcbAjt4xbPljFDVNX4Pb6zI4nIiJ1pNalW//+/fnyyy+rj38t2l5//XWGDBlSd8kOY8aMGdxxxx3cf//9rFy5kl69ejFq1ChycnIOe/sff/yRSy65hB9++IHFixeTnJzM6aefzt69e+s1pzQg7kqYej7Me8A4HnITnHi7uZlExDR+v5/py9IY/uSPbMspJTI4gDtO68gH1wwmJtRpdjxpShL7wHXzocvZ4HMbm/ekLTE7lYg0IEmRQfzl9E7MufUkrhvWFqfdynebcjj7+YXM25TNUe53JyIiDUitp5cuXLiQM888kwkTJvD2229z3XXXsXHjRhYtWsRPP/1Ev371N31i0KBBDBgwgBdeeAEAn89HcnIyN998c402cPB6vURFRfHCCy8wceLEw96mqqqKqqqq6uPi4mKSk5M1vbQxclfAp1Ng/UcQEAKjHoZ+k+E4jMgUkYbnmw1ZvPTTDlalFQLQuUUYL1zal/bxoeYGk6bN74dProe1042pplfOhfBEs1OJSAP0w5YcbvlgFSWVHsD4PXXfmK4MbR9rcjIREfmtep1eeuKJJ7J69Wo8Hg89evTgm2++IT4+nsWLF9dr4eZyuVixYgUjR46sPme1Whk5ciSLFy+u0WOUl5fjdruJjo7+w9s8+uijREREVH8lJycfc3YxQWURvHaqUbhZbDB+KvS/UoWbSDOTV1rF5LeW0faeL7n2vRWsSivEaoH/G9WJObecpMJN6p/FAqMfh6hUY6rp22OgJMvsVCLSAA3vFM+Cu4Zz/cntCAywsjmrhEtfX8qdM9fw5dp9ZscTEZGjUOuRbmbJzMwkKSmJRYsWHTKN9a677uKnn35i6dKlR3yMG2+8kblz57Jhw4ZDdl79LY10ayJm3wir34eQeDjvv9DhNLMTichxtjajkOvfW0HmgUWqAS7o24o7Tu9IUmSQicmkWSpMg7fOgqI0iO1o7HIa+vs1ckVEAIrK3Vz2xhLW7zU2qbNaYOpVgzTqTUSkAajNSDd7TR+wphpqMfXYY48xffp0fvzxxz8s3ACcTidOp9b1abR8Xpj7N6NwwwIXvwut63etQRFpeDZkFjH+1SWUu7wkRwdxTq9EEsIDuWxQa2xWjXgVE0SmwKTPjJFueVvh7bPgwregRXezk4lIAxQRHMBj5/fkkteWUFLpweeHy95Yylk9WvLI+T0IDwwwO6KIiNRAjUq3yMjIGu9M6vV6jynQH4mNjcVms5GdnX3I+ezsbFq0aPGn933yySd57LHH+O677+jZs2e95JMGwFMFM6+ALXOM41GPqHATaWbS9pfz4fJ03l+6h3KXlyFtY3hlYj+9OZGGIbrNocXba8Phkg+g/cgj31dEmp3uSREsv3ckPh/c/MEqvtuUzRdr97Fox35O75rAlOHtSY4ONjumiIj8iRqVbj/88EP15d27d3P33XdzxRVXVE/zXLx4Me+88w6PPvpo/aQEHA4H/fr1Y968eZx33nmAsZHCvHnzuOmmm/7wfo8//jj/+te/mDt3Lv3796+3fNIAfH2PUbjZnDD2Zeh+vtmJROQ4SdtfzvVTV7Bx38GR2Z1bhPHy5SrcpIGJaQfX/mBs9LP9O5g+Aa6ZBwndzE4mIg2Q024D4PVJ/VmdXsiU91eyt7CC6b+k88mqvTxwTjfO7Z1EkMNmclIRETmcWq/pNmLECK6++mouueSSQ85PmzaNV199lR9//LEu8x1ixowZTJo0iVdeeYWBAwfy7LPP8uGHH7J582YSEhKYOHEiSUlJ1eXfv//9b+677z6mTZvGCSecUP04oaGhhIbWbPHs2szVFZNUFBpvXjZ/YRxfOhM6nm5qJBE5PnbllfHwFxuZtzkHAJvVwtB2MVwyMIWRXRJw2Gu9X5DI8eFxwbSLYecP0GoATP4abDX6LFREmjGXx8fy3fk89/02luzMByAs0M4Ll/bl5I5xJqcTEWkeatMT1bp0Cw4OZs2aNXTo0OGQ81u3bqV3796Ul5fXPnEtvPDCCzzxxBNkZWXRu3dvnnvuOQYNGgTAKaecQmpqKm+//TYAqamp7Nmz53ePcf/99/PPf/6zRs+n0q0R+HQKrJoKFiuMuB9OvM3sRCJSz1weH5+u3ssz326t3ighIdzJJzeeQKI2SZDGomgvvDgIXCUQ19lYhzSuk9mpRKQR8Pn8vPTTDqYu2cO+okrsVgsTh6Ry68gORARphLeISH2q19KtU6dOnHvuuTz++OOHnL/rrrv49NNP2bJlS+0TN2Aq3Rownw/WTINPbwL8MOkLaHOS2alEpJ5Vebxc994KftySC0BsqJMrhrZmTM9EUmNDTE4nUkubPjd+j1UWQlhLuGyWNlcQkRpzeXz836w1fLo6E4CYEAfDOsZx06ntaRdXs5k9IiJSO/Vaus2ZM4cLLriA9u3bV48wW7ZsGdu2beOjjz5i9OjRR5+8AVLp1oDNuQuWvWJc7nUpjH3J3DwiUq/Kqjy8s3g3by7cRV6pi8AAK9cOa8fEIa2JDdWu09KIleUZmyvkbgJrAIx/HzqOMjuViDQSfr+fBdvyuP+zDezKKwMgKjiAxy/sxcgu8TXeEE9ERGqmXks3gPT0dF566SU2b94MQJcuXbj++utJTk4+usQNmEq3Bmrle/DZgQ00ht8LJ9wCdr3pFmlqisrdpOWX8/3mHF6dv4Myl7FDdnyYk6cv7s2JHWJNTihSR0pz4dMbYds3EJUKU34Bu8PsVCLSiFS6vfy4JZfn5m2r3ljozO4tePzCnoRpUyERkTpT76Vbc6LSrQFK/wXeHg1eF5xyD5xyt9mJRKQe5JZUcf5LP5OeX1F9rm1sCDed2p6zeyUSYNMmCdLEuMrguT5Qmg19J8IZ/wZHsNmpRKSRKavy8Pz323lj4U7cXj8Ou5WgABundU3g3xf0xGbVyDcRkWNRr6Xb/Pnz//T6YcOG1ebhGjyVbg1MUQa8NgJKs6DzGLj4PbDqjbdIU+H3+5m7IZtnv9vK5qyS6vNhgXbuPasLF/dP1jQZadpWfwCzrzcudxgFl0zX7zkROSor0wq4Y8Zqdu8/uNFdv9ZRXDE0lbN7JZqYTESkcavX0s16mBd+v30D5PV6a/NwDZ5KtwZk8X/hu/uNEW5xXeDqb8EZZnYqEakj+0uruGHqSpbtzq8+lxQZxNuTB9AuLhSrPpmX5mLbtzBjAngqocs5MPKfENPO7FQi0gi5vT4W7djPL7vyeemnHXh9xlu/Ud0SuHRQa07uGGdyQhGRxqdeS7eioqJDjt1uN6tWreIf//gH//rXvxgxYkTtEzdgKt0aiLSl8NYZ4PdBUj+44HWIbmt2KhGpA0Xlbj5elcGbP+8iPb+CoAAbV53YhvEDk0kID9Q0Ummefrt2aXgSXL8QgqPNzSQijdruvDKm/5LOK/N38Os7wI4JofRqFcm9Y7oSEaR130REasKUNd1++ukn7rjjDlasWFEXD9dgqHRrALLWw3tjoSwHeo6H818xO5GI1AGfz8+7i3fz+NwtlB/YICExIpB3rxpE+/hQk9OJNAAZK+DjayB/B7Q+ES6drhHeInLM1qQXMnXJHmauyKg+1z4+lP+M702YM4CUGK0lKSLyZ0wp3TZv3kz//v0pLS2ti4drMFS6maxgD7x2KpTnQUIPuOILCIo0O5WIHINVaQV8sCyNNelFbMk21m3r3CKMSwelMLZPknZYE/mtrPXw5ihwlUJiX5jwkUa8icgx8/v9zFqRwfLdBczdmEVhubv6uv8b1YkbT2mnNVRFRP5AvZZua9euPeTY7/ezb98+HnvsMTweDwsXLqx94gZMpZuJFv8XFjwJ5fuhRQ+YpMJNpLHKLali7oYsftqay7cbs6vPBzts3HNmZy4b1Fprton8kb0rYOqFUJEPwbFw8l0w6DqzU4lIE7GvqIKr31nOhszi6nNtYkOYMrw95/dJ0u9nEZH/Ue8bKVgsFv73boMHD+bNN9+kc+fOtU/cgKl0M8namfDx1cblqDbGCLeIVuZmEpFa21tYwWvzd/Lh8vTqKaRWC5zTK5F+qdGc2jmepMggk1OKNAK5W2DaxVCw2zie/DW0HmJqJBFpOjxeH0UVbj5bk8lT32yltMoDwOC20VzcP5lTO8cTGewwOaWISMNQr6Xbnj17Djm2Wq3ExcURGBhY+6SNgEo3E2z7FmZcDp4KGHoLjLgfbHazU4lILfj9fr5en8XdH6+jqMKYstI9KZyh7WK5qF8rOiRoXSqRWvN6jM0V1nwALXrCVd9CQNN8/SUi5imr8vDO4t088+1W3F7jrWJiRCD/PKcbQ9rFaBkIEWn26rV0e/fddxk3bhxOp/OQ8y6Xi+nTpzNx4sTaJ27AVLodZ1nr4bXh4HVBxzNg/DSw2sxOJSI1VO7ysCqtkOfmbWPprnwAeraK4C+nd2JYh1itDyNyrEpz4YV+UFkE3cbCBW+CVTv8ikjdW7gtj5d/2sHKtILq0eoAp3VN4LHzexAT6vyTe4uINF31WrrZbDb27dtHfHz8Ief3799PfHw8Xq/3D+7ZOKl0O45yt8DMKyBnI7QfCeM/ALuGsYs0BtnFlczblMNT32xhf5kLgMAAK1ef2JabR7THaVd5LlJndv4EUy8AnxsGXgej/gU2jTwRkfpRXOnmxe+3M3v1XrKLqwCID3Pyt9FdGNElXiPfRKTZqfc13bKzs4mLizvk/Jo1axg+fDj5+fm1T9yAqXQ7TjJWwFtngrcKgmPghsUQlmB2KhH5EwVlLnJLq/jbx+tYvqeg+nxMiIPBbWO4+8zOJEcHm5hQpAn77dqncZ3hii8hJNbcTCLS5K3fW8RtM1azPacUgIRwJ8+O68OA1CjsNo26FZHmoTY9UY0XyurTpw8WiwWLxcKIESOw2w/e1ev1smvXLs4444yjTy3N19a58NktRuGWehKc/R8VbiIN2IbMIj78JZ13l+zh149tLBbomRTBGd1bctWJbXDY9cJbpF71vAj8Xpj7N8jdbPz3/FfNTiUiTVz3pAg+u+kE/vvDDj5ZtZe9hRVc8toSYkOdXD64NR0TQmkXH0r7uFDteioiQi1Guj3wwAPV//3LX/5CaGho9XUOh4PU1FQuuOACHI6mNR1QI93q2Zrp8Ml1xuXQFnDjYgiONjeTiBxWbkkVr/y0g9cX7jrkfNvYEN65cqBGtYmYIWMFvD4C8ENSfxj3HoQnmp1KRJqBonI3f5m5hp+351HhPnSJoYRwJzee0p7LBqVoBJyINDn1Or30nXfeYdy4cU12t9L/pdKtHrkr4Pn+UJwBbYfDmGcguo3ZqUTkN1weHz9tzeWjFRl8vSGr+vzILvFcPiSVbonhhDrtBAZozTYR0yx8Fn74l7EJUdvhcPknxvBTEZHjwO318dGKDBbv3E9afjmb95VUl3A9W0Vw35iu9Gsdpc2URKTJqNfSrblR6VZPCtNg2njI2QDhreDmFRDQPIpckcYgq6iS6b+kMWtFBhkFFYDxHj4lOpgbT2nHuAEpJicUkUPkboVXhoGnAnqON5Zq0O9VETFBlcfLzOUZPP71ZoorPQAkRwcxaUgqvZIj6dkqQhssiUijVuelW3R0NFu3biU2NpaoqD//lEIbKcgR+bzw1mhIX2JsmnDR29BmmNmpRJo9t9fHXbPWMmfdPqo8vurzcWFOzujWgsuHtKZjQpiJCUXkT63+AD6dYqz1NvhGOONRsxOJSDOWU1zJU99s5eNVGbi9B99yntWjJS9e1tfEZCIix6bOS7d33nmH8ePH43Q6efvtt/+0dJs0aVLtEzdgKt3qWMEe4w3B7gXgCIMbFkJUqtmpRJqt4ko327JLeXfxbr5an4XrN2Vbh/hQrj6pDef0SiLIoU+kRRqFTV/AjMvAYjV2NG091OxEItLMlVV5eG/JHl75aQcF5W4AAmwWLuqfzJUnpNIuLlRTT0WkUdH00jqk0q0Oed3GYs/71oDNAee9BD0uNDuVSLO0Yk8+X6zdxwfL0qh0HyzabFYLp3dNoFVUEFOGtycyuGltjiPSLHx0NaybCfYgYzR5J+0uLyINw6NfbeKVn3Yecq5XciSXD27NgNQoWseEmJRMRKTm6rx0Ky4urvGTN7ViSqVbHfH5YM5fYPmbEBQFV8+DmHZmpxJpNnw+Pzvzyih3eXjr5918smpv9XWhTjvdEsO5dlhberaKJC7MaWJSETlmVaXw4UTYMc8Y8XbW09B/stmpRERweXzMXJFevVHToh37q0fZO2xWLh7Qiv6tozmrZ0sCtOupiDRQdV66Wa3WIw759fv9WCwWvF7vn96usVHpVke+/hsseRGwGJ+6dzvP5EAiTV+Vx8v8rXnszivjlfk7ySutqr7OaoGzeyVybu9EhneK17QOkabG64bPb4PVU43j0x+GoTebGklE5H9lF1fy5NwtLN2VT1p+efV5p91K+/hQ/j66C31bR2mXdBFpUOq8dPvpp59q/OQnn3xyjW/bGKh0qwObv4TplxqXx74KvcaZm0ekifL7/bi9fiwW2JJVwoNfbGTZroOb2wQGWPH5oE9KJPeM7kLv5EjzwopI/fP74YdHYP7jxoi3y2dD26b1Ok1Emga/38+Hy9NZtquAH7fksL/MVX1diMPGnaM6kRQZxMmd4rTzqYiYTmu61SGVbseoeoQbMOBqOOspc/OINFF+v5+/fLiGj38zbfRXIQ4blw1uzZ2ndyLAZtGoNpHm5pMbYM00sDnh/Feg21izE4mI/KFKt5et2SW88tNOvly373fXJ0UG0TslkusOLIshInK81XvpVlBQwBtvvMGmTZsA6Nq1K5MnTyY6OvroEjdgKt2OweY5MP0SwGKsJTPqEQgIMjuVSJORWVjB8j0FFJW7WLGngNmrMw+5PjzQziPn92BMz0STEopIg+Aqh4+ugi1zIDACbl0LQZFmpxIROSKvz88dH67m0/95jfOrsX2SOKd3In1ToogICjjO6USkuarX0m3+/PmcffbZRERE0L9/fwBWrFhBYWEhn3/+OcOGDTv65A2QSrejlL4M3jsfXCUw9BY4/SGzE4k0epVuL1+u3ccnq/aSW1LF9txSvL5D/wk/pVMcg9rEMG5AMtEh2nlURA7weeGloZC7GcJawjnPQ4fTzE4lInJEfr+fkioPafvLeW/xHjokhLIxs5hPVu/l13eykcEBnNGtBf1Tozm7V0sctiOvSS4icrTqtXTr0aMHQ4YM4aWXXsJmM+bTe71ebrzxRhYtWsS6deuOPnkDpNLtKKQtgakXGoVb6klw2SwICDQ7lUijlFFQzrSlaWQWVvD95hyKKz2HXN+5RRhtYkMICrDRt3UUlwxMwWbVi0wROYz1H8GsK43LNifctAyiUk2NJCJytFbsKeCZb7eyaV/xIWvAAbSNC2FYhzhaxwRzbu8kAgOsBDvsJiUVkaamXku3oKAgVq9eTadOnQ45v2XLFnr37k1FRUXtEzdgKt1qwe+Hr++GZa+C32cUbpfOAEeI2clEGrwKl5d1e4tIjQnmy3X7KKn0sDmrmG83ZuP2HvxnOikyiAv7tSIm1EHLiCBGdtHOoyJSQ34/rHzX+F3tLocOp8O498GuUbEi0ni5PD4+WpnB1uwSPl2dSf7/FHAANquFK09I5aQOcQxtF4PdZjUhqYg0FbXpiWpd9/ft25dNmzb9rnTbtGkTvXr1qu3DSVOy+EVY+rJxudtYOPe/4Ag2N5NII1Dp9jL+1cWsySg67PWD2kQztF0svVMiOal9LFaNZBORo2GxQL9J0GoAvHISbPsG3hsLE2ZpzVURabQcdiuXDEwB4O+ju5BVXMm7i/ewaV8x6/YWUVjuxuvz89qCXby2YBetY4LplxJF65gQTu+WQJeWGlghIvWn1iPdZsyYwV133cXNN9/M4MGDAViyZAkvvvgijz32GF26dKm+bc+ePes2rQk00q2GVk2Fz242RriNfhIGXmN2IpEGK7Owgp+357Ehs5jSKg8bMovZtK+4+vrEiEBO6hBHYmQQI7rE0z0pwsS0ItIkbf0GProaqoqg67lw3sv6oExEmhyXx0dBuYsft+Qwe1Um6zOLKPmfpTqGdYzjjG4tGNklnvhwLYkjIkdWr9NLrdY/H4prsVjw+/1YLBa8Xm9tHrpBUulWA+s/hlmTjcv9roAxzxqfposIheUuluzcz9bsUlbsKWBLVglZxZW/u12Iw8Yj5/fA7fVzRvcWhDq17oiI1LNdC+C988DngdhOcPW3xu6mIiJNVEmlm/lb89iTX8ba9CK+25SN58CmVBYLxIU6iQ930jo6hHZxIQxuG0NqbAiJkRoNLCIH1WvptmfPnhrftnXr1rV56AZJpdsRpC2Bd84BbxUMuNoY5abCTZopv99PcaWHcpeH57/fzp79ZSzdmV/9Yu5XVgv0bBXJgNQoQpx2rBYL4wcmEx+mT1dF5DjbPg9m3wCl2dBzHJz3ElhtZqcSETku9uwv4/2lafy0JZct2SWHvY3VAkPaxdA6JoRzeiXSv3WU1oQTaebqtXRrblS6/Yn9O+D1EVBRAJ3HwMXv6oW6NCsVLi8LtuWSXVxJWn45c9Zlsbfw95vJdEwIpUdSJF0Tw+mTEkn7+FDCAwNMSCwichi75sM7ZxuXI1vDpM8hqvF/cCoiUlMer4/523IJsFnJL3ORW1LFwu15bM8pJaPg0Nd2gQFW2sWFcm7vRC4fnEqQQ+9/RJqbei/dMjMzWbhwITk5Ofh8vkOuu+WWW2r7cA2aSrc/kLcN3r8ICnZBUj+Y9IXWgpEmbc/+MrbnlBIRFMCKPQUs2bmfpbvyKXcdfhp9q6ggrjyhDSe0j6VTi7DjnFZEpJYWPA3zHjAudzkbxk01N4+ISAOxNqOQNRlFrEkv5NuN2RRVuA+5PjDASmyok5FdErhkYIpe94k0A/Vaur399ttcd911OBwOYmJisPxmKqHFYmHnzp1Hl7qBUul2GOnLjE/EPZXGJ+JXz4PQOLNTiRwTv9/Pij0FtIsLpaTSw+qMQqYt3YPVYsFpt/Lj1lwO969lmNPO0PYxhDjsnNY1gT4pUaxOL2BI21gigjWaTUQakewN8PJJ4PdCm5Ph/NcgLMHsVCIiDYbX5yctv5wlO/fzn++2HXad3vbxoZzWNYGWEYEEBtiICAqgfXwo7eJCTUgsIvWhXku35ORkrr/+eu65554jbqrQFKh0+x+eKuMFed4WaH0inP8KRLQyO5VIrRWVu1mZVsCajEK+Xp/F5qzDr+PxWx0TQskpqcICdEuMIMhh474xXUmO1ihPEWkiFjwF3z9s7EbeeQyMf9/sRCIiDVJJpZsVewpoFRVEWn45H/6SwbebsvH6Dv/2OjDASquoYCYNTSUpMpAQhx27zULflKhDBrKISMNXr6VbTEwMy5Yto127dscUsrFQ6fY/5vwfLHsVQuLhpmUQFGV2IpFD5JRUEhEUgM1iwWqxsGt/Gbvzyiit8rBwWx7r9hZRVOFmf5kLl8d32Mdw2Ky0jQthaLtYUqKDsFgs9E+NoltiBD6fH4sFvTgSkaZr3xp47VRjV9NzX4Q+E8xOJCLSKBSWu5i/LY8v1mTi80OVx8v+Uhcb9xX/4X2GtI3h1M7xDO8cT3p+Of1So1ibXkTXxHCiQxzHMb2I1FS9lm533XUX0dHR3H333ccUsrFQ6fYbq6bCp1OMy+M/gM6jzc0jApRWeSir8rCvqJKftuTyn3lb+YMPGH8nJsRBbKiTIe1i+GV3Pled2IZBbWOIDnZoUVwRad5+eBR+egwsVrh0JnQYaXYiEZFGa0duKXsLKvh0dSar0wsIDLCRX+ZiX9Hvp6c67FZcHh/BDhudW4QRGexgYJtozu2diNfnx++H+HAndqsVm1UfAouYoV5LN6/Xy5gxY6ioqKBHjx4EBBy6ZtHTTz9d+8QNmEo3wOeDDR/DpzeBpwKG3wsn/5/ZqaQZ8fr85JVWsTmrhD37y8gpruKTVXsB2FdUccSSrUV4IPHhToa0jWFAajRRIQ48Xh/9U6P1YkVE5HB8PuODtjXTIDgWLvvQ2DhJRETqzLqMIj5amcHKtALWZhTV6r7RIQ5O6RhHZLCDKcPbERpox2m3UVblIcRpr6fEIgL1XLo9/PDD3HfffXTq1ImEhITfbaTw/fffH13qBkqlG0bZtuo943LKULjiC7BqFJAcG7/fz+asEspdHpbvLqBf6yh25paxPbcUgNhQB0UVbrZml7J+b9FhPwn8rRbhgaREBzOsYywr0wpJCHcytF0sMaEOhraLPR7fkohI0+KuhFeGGeu4Aox6FIbcaG4mEZEmyO/3U1LlwWax8M3GLPq3jmZNRiFen5+CMhdfrN3HyrQCrAfee3sO84mzxQKdEsLYnFXCSR1i6Z4UwYDUKCKCHLSPD8VmtRBot2K3Nf112UXqW72WblFRUTzzzDNcccUVx5Kx0Wj2pdtvp5T2ngAj/6mdSuWw0vPLsVotrMsopKDczWldEygoc1FY4WbB1ly25ZSyOr2QtnEh9G8dzYo9BSzcnler54gICsBpt5JXWkXv5EhSY0K4oF8rTmivUk1EpF7kbYOProZ9q8ERBretheBos1OJiDQ7JZXu6hka+WUuHp2zmYXb8yiqcNf4MaKCA2gVFUynFmG4vT4Kyt1EBAVQUObiskEptIwMIjbUwYo9BZzWNYFgh0bMiRxOvZZuLVq0YMGCBXTo0OGYQjYWzbp0m/egsYsZwAm3wmkPmptH6pXf78ft9VPh9hIRZEwbr3B5WZ9ZRGJkED9vz+OUTnFEBjnIKqqk0uMls7CClXsK2LW/nK/W7Tvsp25HEh5op7jSA4DNauHSgSkEBlhZuisfvx/G9GxJ65hgTukUT2CADb/fT7nLq2HzIiLHi89njHjLXgftToWzn4PIZLNTiYgIxmYNe/aXU1rlYfGO/fRNiWLxzv1kFlbw09Zc3F4fheU1L+Z+Kz7MySmd4ujaMpz0ggq8Pj+ndo4nOsRBlcdHRFAAcWFObFYLPr+f8MCAIz+oSBNQr6Xbo48+yr59+3juueeOKWRj0WxLt4wV8PoIwA8n3Qmn3AM2lRyNkdfnZ/nufDq3CKfc7SEmxElhhQufD9ILytmVW8abP+9iz/5yKtxe7FYLHRLC8Pp87M4rx+U9uMNngM2C58ACrn/EYoEAm/WQnUHjw5w4A6zceEp7XB4fazOKiA11cFH/VrSPD8Pr8/PRygzaxYXSr7V2xBURaXC2z4P3LwK/F+K7wnXzwaY3VyIiDZ3f72dnXhkhDjtbskvYW1DBxyszcPv8dG0Zjs0KafkVbMkqprjCQ4XbW6vHt1ionvYaeWBWyqShqXRLjKBf6yiyiiuJCXXgtFtx2g8uUZRXWkVQgE0fpEujVK+l29ixY/n++++JiYmhW7duv9tI4eOPP6594gasWZZuy9+CuX8Ddzn0HAfnv2p2oiZrY2Yxm7OKGd4pHp/fz7acUqYtTWPS0FRKqzzYrRbS88sZ1DaG7OJKQp12HpmziVCnnSqPD5fHh91moajCTauoIMpdXnx+2FtQTlJUMPsKK9iWU3rIc4YF2ik5MLKsNmJCHOwvcwEQGGAlMMBGbKiTHkkRBDts9GoVSdfE8Orn2FdUSbfEcPLLXLSOCTn2H5aIiJgreyO8czaUH1ga4JR74JTmsZu9iEhzUOHykl/uIjzQzsq0QtbvLeKLtfuIC3PSuUUYOcWVfLomE4fNSnSIg3KXt1bTW1Oig8ksrCDEaaeowo3daqF9fCgD20TTMSEMp91Ky4ggLBZweXzklVbRJyUSn98o9FxeHy0jgli+O5+uieGEaWSdmKReS7fJkyf/6fVvvfVWbR6uwWt2pVvedvjvYPC5IXkwjJ8GITHH/LDFlW42ZhYzMDUar99PQB0s4On1+dlbUEF8uJPFO/fTPTGCLVkltI8PZfHOPIIddoZ3isdhtx7YXtvP+sxitmaXMKZnS/JKXDgDrMxZt4/wwADW7S0iITyQL9ZmclKHOFrHBNMxIYyMgnIigx3szC2lrMrDKZ3iCXXa+X5zDkt27qd9fCiFFW7CAu1kFVWSW1JF5xbhdG4Zxg+bcwh12qvLqszCCqo8PiKDAyir8rA1u/QI32X9iglx0DommOToYPLLXHh9fi4ZmEJRhRuP18fewgquOrEtfvwkhAWye38ZYYEBxIY6DtlERUREmom1M+Hjq43LFitMWQaxzWPJERERgX1FFYQFBhB6YIRaTnElXr+fsioPewsrWZ1WyMLtuezKKyOv1IXDfugMmLrisFuJC3US4rRR6fbRqUUYfVIicXuMeqN1TDBdWoaTXVxJdIiDjIIKwgPtlFR56NUqkoRwJxaLBf+BgQ+788ronhRBYmQQAB6vD4vFUr2Onshv1WvpZrYXX3yRJ554gqysLHr16sXzzz/PwIED//D2M2fO5B//+Ae7d++mQ4cO/Pvf/2b06NE1fr6mVrq5vT6em7eNIe1imL1qLxVuH0PbxdC1ZTjrNm5k+Lq7SCpdx2JrP2Z1eprU2BA2ZBZTWuWhb+so1mYU0jIiCLfXR4jDxq795TjtVvYWVBDqtOPx+bDbrJzQLpYWEU6sFguLd+znhy05FBxYS8BigXZxoVS4vKTGBhMT4sTj87Exs5iIoAAq3F6SIoPw+PzsL3WRFBVETnElpVUe8kqN8sputeD1+w9Zn8Bi4XfTHq0WaBkRRHGl+6hGd5kpLNBe/QlSbkkVATYLbq/xDQ5uG02b2FDiwpxUebzsyCkjt7SKM7q1IMRpIzEiiMyiCqrcPlbsKeDKE9uQFBVEZFAAm/YV0zIyiIQD6y+oPBMRkVpJWwKzroTivdD2FBj7KoQlmJ1KREQaELfXR1ZRJUmRQbi8Poor3WzaV0JSZCA5xVWkxobg9fnZkFnE+0vTKKvyYLFYKCx3UeHyUlrlISkqmC1ZxYQ4j26mzp8JddppFRVEhdtYEw+M95OxoU6CAmzkllRVHwc7bPROjsTr89MqKhiH3cqSnfvZtK+YuDAnKdHBxIU52ZZdisNuJT2/nPhwJ6HOAMIC7UQFOwgNtNMyIpAqt5fOLcOp8vhIzy/H7TUKw282ZDO2TxI9W0WwLacUh81KaZWHYIcNZ4CNRdvz8Pj89E6OpKTSw8LteZRXeUiMDCItv5yzeyWSVVRJWKCd4ko3qTEhpOeXExYYQPekcEKcdl76cQfRIQ5O6hBLUICN6BAHVosF64FicX9pFWv3FpEcFUyl20uo084PW3JIjgpmUNtoQhx20vLLSQgPJMhhTBX2HNiQo7jSTaXbS6uo4Or1wZuyJlu6zZgxg4kTJ/Lyyy8zaNAgnn32WWbOnMmWLVuIj4//3e0XLVrEsGHDePTRRxkzZgzTpk3j3//+NytXrqR79+41es6mVrrNX/YLOz57gv3+cAZYtxBrKaLIH0I5Tk6wbiDI4qLM72SM6xF2+VuaHbfGDvcJitUCNV3XPzI4AJ/PT3Glh16tItiQWVy9KUBQgI0qjzFt02GzYrUaa0p7/X5aRQURF+qkR6sI/H5oGRFIVIiDVQeGY3dqEUZMqIO4UCdBDhvRwQ4iggMoKnezfE8BLo+Pu87oRKXbx579ZSzesZ9LB6WwI7eMXskROO3GxgEr0wppExvC3oIKEiMDiQl11vWPUEREpOb2rYXXhoPPA+FJcP1C7WoqIiJ1zufzY7Va8Pr8rMko5N1FuxnbtxWF5S6igh2AUfB9tymb4koPEUHG+7pvN2ZTWOEmKthBpdtLm9gQylweHDYrW7JLDhms4bBbiQ9zklFQYdJ3eVBkcMBRb3zxRw43OAWMgSxBATa6J0VQ7vKwJbuESvfhRyVaD6zbXeXxEWCzEB8WiDPAyv5S1++mGEcEBRAVHEBeqQurBRLCAwmwWRnVrQW3jmwao+PrvXSbNWsWH374IWlpabhcrkOuW7lyZW0frsYGDRrEgAEDeOGFFwDw+XwkJydz8803c/fdv19TZNy4cZSVlfHFF19Unxs8eDC9e/fm5ZdfrtFzNrXSbceCGbSbd+0fXr/C34l/+q/l4jNHsrewkvSCcnq1iqC4wsNPW3MZ2CYau81C2IFPG5KigigsdxMf5qTM5aXK42V/qYv0/HLWZBRSUObm7F6JtIsPITLIwexVezmndyKBATYSIwLZvb+cygOLdbaJC6G4wk1plYeftuRS4fbSMiIQh93K0HaxRAQFEB/mxGq1UOU2Pi3pmhhO2v5y2sSGsCW7hDYxISzdtZ92caG0jw8lt6SKtPxynHYbQQ4bNqsFm8XCqvQCEiODWLpzP5cOak10iPEPdmG5i4igAIorPIQ4bezILTsw2syD3WYlKTIIv99PlceHxcIhi4GKiIg0K2lL4JProGA3dD0XLnhTmy6JiEiD4Pb6cHt9BDt+/3up0u0lo6CCvYUV+P1++iRHEREcwIbMIlwH1s2OCA7A74fCcjd79pexJ7+c4AAb6QXGTrF9U6LokxJFQZmLtPxysooraRsbgs8PTruVdXuLCHLYKKvyUFjuZmdeKcUVHlpEBJJTXInDbiU5Kphd+8vYmVt2SD671YLdZiHUaSxJVOH20jYuhMigAHbklhFgszKkXQw2C+zJLye7qJLMokrax4diAYKddnbklJISHUyF28uuvLLf/Qz+iNVilJBOu42iCje9WkVQVOFm94HRgH8kxGEjMMBWvazS4YwfkMxjF/SscZaGrF5Lt+eee46///3vXHHFFbz66qtMnjyZHTt28MsvvzBlyhT+9a9/HVP4P+JyuQgODmbWrFmcd9551ecnTZpEYWEhn3766e/uk5KSwh133MFtt91Wfe7+++9n9uzZrFmz5rDPU1VVRVVVVfVxcXExycnJTaZ0I2s9rJuJK38PtrhO2JL7Q/l+qCqBmHZ4U0+h0uOrk11kPF4fFW6vFrgUERFpqjJWwBunGbuatjsVLp2p4k1ERKSGqjxetmWX0rVlOPuKK8ksrKBLy/DqNfNqwn9g2aWoAwNJ/ld6fjlz1u2jR1IEA9tE4/b6ySutoqTSw579ZezMKyMlOpgAm4URXRIIsFnx+41ZYOGBdiwWCzkllVS6fESHOpi5PJ2QAxv7BQfYOLtXIg67sWZ7uctDen4FBeUu4sKc+Hx+sour8Pr9tIwIpGNCWJ383MxWm9Kt1q+K/vvf//Lqq69yySWX8Pbbb3PXXXfRtm1b7rvvPvLz84869JHk5eXh9XpJSDh0zZCEhAQ2b9582PtkZWUd9vZZWVl/+DyPPvooDzzwwLEHbqhadIcW3Tn8X0ewASF1sMkBgN1mJayOHktEREQaoFb94OJ34eNrYcf3sPIdGHCV2alEREQaBafdmN4JkBQZRNKBjRxqw2Kx/GHhBpAcHcx1J7erPrbbjHMAXRMPXxhZLJZD1maLDwusvjz5hDZ/+FzBDjudWhxarHVoIkXb0ap1I5KWlsbQoUMBCAoKoqSkBIDLL7+cDz74oG7TmeCee+6hqKio+is9Pd3sSCIiIiINV5cxMPKfxuUv74DPbgFP1Z/eRURERKQ5qHXp1qJFi+oRbSkpKSxZsgSAXbt2UZ97MsTGxmKz2cjOzj7kfHZ2Ni1atPjDrLW5PYDT6SQ8PPyQLxERERH5E/2vhNYnGJdXvgMLnzE3j4iIiEgDUOvS7dRTT+Wzzz4DYPLkydx+++2cdtppjBs3jrFjx9Z5wF85HA769evHvHnzqs/5fD7mzZvHkCFDDnufIUOGHHJ7gG+//fYPby8iIiIiR8Fmh0mfw6hHjOMFT8G2b83NJCIiIuYrz4eZV0D+LrOTmKLWGyn4fD58Ph92u7Ec3PTp01m0aBEdOnTguuuuw+H447nEx2rGjBlMmjSJV155hYEDB/Lss8/y4YcfsnnzZhISEpg4cSJJSUk8+uijACxatIiTTz6Zxx57jLPOOovp06fzyCOPsHLlSrp3716j52xqu5eKiIiI1Bu/Hz68HDZ9DhYbjH4cBlxtdioRERExQ952mDoWCtOg1UC46huwWMxOdczqdSMFq9WK1XpwgNz48eMZP3587VMehXHjxpGbm8t9991HVlYWvXv35uuvv67eLCEtLe2QbEOHDmXatGnce++9/O1vf6NDhw7Mnj27xoWbiIiIiNSCxQIXvAlf3Aar34cv/wI2B/SdaHYyEREROZ58Xvj4aqNwi0qFMc80icKttmo90q250Ug3ERERkVry+2Heg7DwabAHwuWzobWW9xAREWkWyvLg63tg3YfgDIcpyyC8pdmp6kxteqJar+kmIiIiIvKnLBY49R/Q4XTwVMK758L6j81OJSIiIvXNUwVTLzAKNzDWe21ChVttqXQTERERkbpntcJFb0On0eCtglmTYdX7ZqcSERGR+vTNvbBvNQRFwZVzoe/lZicylUo3EREREakfjhAYNxUGXmscf3kH7FtjbiYRERGpHxs+gWWvGpfHvgIpg83N0wAcVenm8Xj47rvveOWVVygpKQEgMzOT0tLSOg0nIiIiIo2c1QZn/PvgVNN3zoG9K8xOJSIiInVp/w749Gbj8gm3QsdR5uZpIGpduu3Zs4cePXpw7rnnMmXKFHJzcwH497//zZ133lnnAUVERESkkbNa4fxXodUAqCyE6ROMRZZFRESk8cveCFPPB1cJJA821nUV4ChKt1tvvZX+/ftTUFBAUFBQ9fmxY8cyb968Og0nIiIiIk1EUBRc/gnEdICSTJg2DsrzzU4lIiIix2LfWnjrDCjYDZEpcOGbYAswO1WDUevSbcGCBdx77704HI5DzqemprJ37946CyYiIiIiTYwzDC5+FwIjYe9yY3czV7nZqURERORo5GyC986DyiJjNPs1P0JEktmpGpRal24+nw+v1/u78xkZGYSFhdVJKBERERFpohK6wpVfQ1A0ZK6EmZOgstjsVCIiIlIbeduNdVrL90PL3jDhIwiJMTtVg1Pr0u3000/n2WefrT62WCyUlpZy//33M3r06LrMJiIiIiJNUXwXY1dTmxO2fQPvngtet9mpREREpCbyd8E7Z0NZDiR0N5aPCIwwO1WDZPH7/f7a3CEjI4NRo0bh9/vZtm0b/fv3Z9u2bcTGxjJ//nzi4+PrK6spiouLiYiIoKioiPDwcLPjiIiIiDQdGSuMhZcrC2HY/8Gp95qdSERERP5MUQa8dSYUpkFsJ7jiSwiNMzvVcVWbnqjWpRuAx+Nh+vTprF27ltLSUvr27ctll112yMYKTYVKNxEREZF6tP4jmHWlcfnMJ2DQtebmERERkcPL2w7TLoL8nRDdFq6YA+EtzU513NWmJ7LX9sErKysJDAxkwoQJRx1QRERERASA7hcYO5/9/Cx89X/g98Hg681OJSIiIr+1fwe8dipUFRm7lE78rFkWbrVV6zXd4uPjmTRpEt9++y0+n68+MomIiIhIczLyn3Di7cblr/8K8580NY6IiIj8hs8LX9xuFG6JfeGq7yAy2exUjUKtS7d33nmH8vJyzj33XJKSkrjttttYvnx5fWQTERERkebAYoER98Owu4zj7x8ypp2KiIiIuQrT4ZVhsOsnsAfChW9AWILZqRqNWpduY8eOZebMmWRnZ/PII4+wceNGBg8eTMeOHXnwwQfrI6OIiIiINHUWC5z694Mj3mZPgZ8eB82sEBERMYe7EmZOguz1xu6k575orOUmNXZUGyn8r40bN3LZZZexdu1avF5vXeRqMLSRgoiIiMhx5PXA9Etg2zfG8fB74eT/MzeTiIhIc1OwB6aNg9xNRuF23QKIam12qgahNj1RrUe6/aqyspIPP/yQ8847j759+5Kfn8///Z9eEImIiIjIMbDZ4dIP4Yx/G8c/PgJLX4Vj/5xYREREasLvh0+nGIVbSBxc/J4Kt6NU691L586dy7Rp05g9ezZ2u50LL7yQb775hmHDhtVHPhERERFpbiwWYwfTvK2w/A1jV9OAQOg70exkIiIiTZu7Er67H3YvAHsQXPUtRLcxO1WjVevSbezYsYwZM4Z3332X0aNHExAQUB+5RERERKS5O+spCIqCBU/C1/eANQB6jgPrUU/WEBERkT/z2c2w7kPj8sh/qnA7RrUu3bKzswkLC6uPLCIiIiIiB1ksMPxvkLYY9vwMs6+HvC3GmwARERGpWyvfMwo3ixUufhe6nG12okavRh8TFhcXV1/2+/0UFxf/4ZeIiIiISJ2x2uCS6TDswNrBC5+FFW+Dr2lt3iUiImKakmyYfSN8dpNxfNJfVLjVkRqNdIuKimLfvn3Ex8cTGRmJxWL53W38fj8Wi6XJ7V4qIiIiIiYLDIdT74XiTFj9Pnx+K+yaD+e/ZpRyIiIicnQqi+Dts2D/NuP4hFvhlHvMzdSE1Kh0+/7774mOjgbghx9+qNdAIiIiIiKHNeZZiOsM8x6E9R+BIxTO/o8xDVVERERqx+eDT643CrfwJLjoHUgeYHaqJqVGpdvJJ59cfblNmzYkJyf/brSb3+8nPT29btOJiIiIiPzK7oATboHIZJh1Jax8ByKS4eT/MzuZiIhI4+L3w/cPwZY5YHPCuPcgqZ/ZqZqcWm/91KZNG3Jzc393Pj8/nzZttKuFiIiIiNSzbmPhrKeNywueMqadioiISM19fissPPC79KynVLjVk1qXbr+u3fa/SktLCQwMrJNQIiIiIiJ/qt8VkDwYPBUw92/GJ/YiIiJyZNvnGaPFLTYY/ST0vdzsRE1WjaaXAtxxxx0AWCwW/vGPfxAcHFx9ndfrZenSpfTu3bvOA4qIiIiI/I7FAqc/DG+Ogg2fQHQ7GPEPs1OJiIg0bMX7YM6dxuVB18HAa8zN08TVuHRbtWoVYIx0W7duHQ6Ho/o6h8NBr169uPPOO+s+oYiIiIjI4SQPgLOfhc9uhgVPgiMYht4CtgCzk4mIiDQ8+Tvh3fOgcI+xccLJfzU7UZNn8ftrNxZ/8uTJ/Oc//yE8PLy+MjUoxcXFREREUFRU1Gy+ZxEREZFG5YdH4afHjMspQ2HS52Cr8WfLIiIiTd+mL4x13MrzIKoNTJwNUalmp2qUatMT1XpNt7feekvlk4iIiIg0HKfcbSwC7QiDtEWw6Dmt8SYiIvKrle/CjMuMwq1FD7hyrgq34+SoPgJcvnw5H374IWlpabhcrkOu+/jjj+skmIiIiIhIjVgsMOBqsNqNT/HnPQCbv4RLPoDQeLPTiYiImGf9R/DZLcblAVfDqEfA7jQ3UzNS65Fu06dPZ+jQoWzatIlPPvkEt9vNhg0b+P7774mIiKiPjCIiIiIiR9ZnorGmW0Aw7F0Ob50JFQVmpxIRETFH+i/w8bWA39j1e/STKtyOs1qXbo888gjPPPMMn3/+OQ6Hg//85z9s3ryZiy++mJSUlPrIKCIiIiJyZFYrnP4QXL8QIpJh/3aYPQV8XrOTiYiIHF9Fe+GT68DngS7nwFlPGyPD5biqdem2Y8cOzjrrLMDYtbSsrAyLxcLtt9/Oq6++WucBRURERERqJaYdjHsPbA7Y8iXMnATuCrNTiYiIHB+7F8Lz/SB/B4QlwjnPg9VmdqpmqdalW1RUFCUlJQAkJSWxfv16AAoLCykvL6/bdCIiIiIiRyOxD1zwulG8bfoc3hurqaYiItL0VRbBx9eBpwJaDYAJH0FQpNmpmq1al27Dhg3j22+/BeCiiy7i1ltv5ZprruGSSy5hxIgRdR5QREREROSodD0XJnwMzghIWwxvngFFGWanEhERqR9VJfD+xVCcYexOevlsSOhqdqpmzeL3124/9fz8fCorK0lMTMTn8/H444+zaNEiOnTowL333ktUVFR9ZTVFcXExERERFBUVER4ebnYcEREREamt7A0w9QIo2WdMs7nyK+PNiIiISFNRUQDTxkH6UuPDpkmfQWJvs1M1SbXpiWpdujU3Kt1EREREmoDCdKN4y9sCyYNh8hytbyMiIk3D9u9g1lVQWQiBEcYIt6S+ZqdqsmrTE9lr+oA1pWJKRERERBqcyGS4bCa8NBTSl8BHV8G5/wVHsNnJREREjl55PnxyvVG4xXaC81/VCLcGpEalW2RkJJYjbC3r9/uxWCx4vdqSXUREREQaoKjWxg5uH18DGz4BLHDhm3CE17kiIiINkt8Pc+6EslyjcLt+AdidZqeS36hR6fbDDz/Udw4RERERkfrX/XwIjoGp58OGj43dTUc9AiExZicTERGpOXclfPsPWP8RWO3Gh0oq3BqcGpVuJ598cn3nEBERERE5PtqebBRtX90Fa6dDYRpc8YXWeBMRkcYhcxV8fC3kbTWORz8JKYPMzSSHZT2aOy1YsIAJEyYwdOhQ9u7dC8B7773HwoUL6zSciIiIiEi9GHQdXDkXHKGQtggWPm12IhERkSMryYL3zjcKt9AEGP8B9J9sdir5A7Uu3T766CNGjRpFUFAQK1eupKqqCoCioiIeeeSROg8oIiIiIlIvUgbDGY8al79/GFa+Z24eERGRP1NZBB9dDRX50KIH3LgEOo82O5X8iVqXbg8//DAvv/wyr732GgEBAdXnTzjhBFauXFmn4URERERE6lXfiXDi7cblL+8wpuyIiIg0NJVF8OYZsHsB2INg7CsQHG12KjmCWpduW7ZsYdiwYb87HxERQWFhYV1kEhERERE5fkbcD53OAq8L3j0PNn1u7AgnIiLSELgr4MNJkLMRQlvA5DmQ0M3sVFIDtS7dWrRowfbt2393fuHChbRt27ZOQomIiIiIHDcWC5z3IiT1h8pCmDHB+PJ5zU4mIiLNnbsS3r8Idv4AAcFw6QxI6mt2KqmhWpdu11xzDbfeeitLly7FYrGQmZnJ+++/z5133skNN9xQHxkByM/P57LLLiM8PJzIyEiuuuoqSktL//T2N998M506dSIoKIiUlBRuueUWioqK6i2jiIiIiDRSQVHGyIETbwebEzZ/Ad8/ZHYqERFpzor3wSfXGlNKHWFw2UxI7G12KqkFe23vcPfdd+Pz+RgxYgTl5eUMGzYMp9PJnXfeyc0331wfGQG47LLL2LdvH99++y1ut5vJkydz7bXXMm3atMPePjMzk8zMTJ588km6du3Knj17uP7668nMzGTWrFn1llNEREREGim7E0b+ExK6w0dXwcJnjMs9LjQ7mYiINDf71sBbo8FVChYbjJ8KqSeanUpqyeL3H92CFS6Xi+3bt1NaWkrXrl0JDQ2loqKCoKCgus7Ipk2b6Nq1K7/88gv9+/cH4Ouvv2b06NFkZGSQmJhYo8eZOXMmEyZMoKysDLv98H1jVVVV9Y6sAMXFxSQnJ1NUVER4ePixfzMiIiIi0vDN/TssfsG43GEUjHvPKOVERETqW2kuvHEaFOwydikd8U/oMNLsVHJAcXExERERNeqJaj299FcOh4OuXbsycOBAAgICePrpp2nTps3RPtyfWrx4MZGRkdWFG8DIkSOxWq0sXbq0xo/z6w/kjwo3gEcffZSIiIjqr+Tk5GPKLiIiIiKN0MgHjJ1NrXbYNhe+f9jsRCIi0hyU5sBbZxiFW0QKTPxMhVsjVuPSraqqinvuuYf+/fszdOhQZs+eDcBbb71FmzZteOaZZ7j99tvrJWRWVhbx8fGHnLPb7URHR5OVlVWjx8jLy+Ohhx7i2muv/dPb3XPPPRQVFVV/paenH3VuEREREWmkbHY453m46B3jeNFzMG2csYOciIhIffC64eNrYP92CG8Fl38MwdFmp5JjUOPS7b777uOll14iNTWV3bt3c9FFF3HttdfyzDPP8PTTT7N7927++te/1urJ7777biwWy59+bd68udbf1P8qLi7mrLPOomvXrvzzn//809s6nU7Cw8MP+RIRERGRZqrLGDjlb2ANgK1fw8/PmZ1IRESaotwt8OIg2PmjsUvphI8gtoPZqeQY1XgjhZkzZ/Luu+9yzjnnsH79enr27InH42HNmjVYLJajevK//OUvXHHFFX96m7Zt29KiRQtycnIOOe/xeMjPz6dFixZ/ev+SkhLOOOMMwsLC+OSTTwgICDiqrCIiIiLSTJ3yV4htD7OuhB8fMXaRu/AtCI0zO5mIiDQFZXkwYwLk74DgWDj3BYjvbHYqqQM1Lt0yMjLo168fAN27d8fpdHL77bcfdeEGEBcXR1zckV+sDBkyhMLCQlasWFGd4fvvv8fn8zFo0KA/vF9xcTGjRo3C6XTy2WefERgYeNRZRURERKQZ63Y+rPsItnxplG4//AvOftbsVCIi0tht+sL4UMdbBWGJcN18fajThNR4eqnX68XhcFQf2+12QkND6yXU/+rSpQv/396dh1dRHmwYv08SEtYkrAkom0LBBRGMKIJLAVm17luRCm5VQQX9rEvr0varuHxa61JR61pRXKmKiqIgiEV2RBGCRQUEI0IgAQIkJPP9MRpMRQl6yGS5f9eVy8ycOTPPAV8lD+/M279/fy644AJmzZrFe++9x4gRIzjzzDNLVy5dtWoVHTt2ZNasWUBYuPXt25fNmzfz8MMPk5+fT05ODjk5ORQXF1dIbkmSJFUTsRic8SQc/7dwe94T8MmkaDNJkqq2rfkwYVRYuGUeBGc9beFWzZR7plsQBAwdOpSUlHCp9K1bt3LRRRdRr169Mse9+OKL8U34jbFjxzJixAh69+5NQkICp5xyCnffveOZGkVFRWRnZ1NQUADAvHnzSlc2bdeuXZlzffbZZ7Rp02aP5JQkSVI1lZAAhwwNy7YlE2DsqdBvNHS/JOpkkqSqZmt+uGjC5jXQuB2c/zYkJe/6fapSYkEQBOU5cNiwYeU64aOPPvqzAlU2+fn5pKWlkZeX56IKkiRJgsICmHQ9zP5HuN1jJPzyOkhKiTSWJKmK2F4I/zwRlr8Hickw+HnY5+ioU6mcdqcnKnfpVlNZukmSJOl7ggDeugneuyvcPugMOOmB8DZUSZJ+SP6X8NJwWPY2pKTCkPGwd1bUqbQbdqcnKvcz3SRJkiR9IxaDY/8Ipz0OsURY+Ay8+39hGSdJ0s6sWQIP9QoLt8TkcCVsC7dqzdJNkiRJ+qkOOBF63xB+P/l/YdINkcaRJFVSq+bCowNg42po0iFcpbR9n6hTaQ8r90IKkiRJknaix+VQqy68fhX8+24ISuDIK6Fuo6iTSZIqg01fw9jTYUsutOgKZ7/g/yNqCGe6SZIkST9HLAaHXRiubAow4174Rx8o3BxpLElSJbB5HbxwHhSshWYHwDkvW7jVIJZukiRJUjz0vwV6XR8+pyd3GUwYBcVFUaeSJEVl8zp48Bj4bCokpsDJD0BKg6hTqQJZukmSJEnxUKsOHPU/8OtngFi4uMJTp1u8SVJNEwQwfyw8eDTkrYD01nDu65DZKepkqmCWbpIkSVI87dsLznwKatWDZZNhwkgoKYk6lSSpoiyZAC9dAnkrIal2+P+EvQ6JOpUiYOkmSZIkxVvHgXDqI0AM5j8JL5wL27dFnUqStKdt+hre+H34fZsj4aL3IPPAaDMpMpZukiRJ0p7QoT+c8g9IqAWLxsPYU2FrftSpJEl7yvrl4TPcNiyH1L3Cxw00aRd1KkXI0k2SJEnaUzqdCoOfg+T68Nk0eGwgbPwq6lSSpHjLXw1Pnwn5X0DjdjDkX5BcL+pUipilmyRJkrQn7ftLGPoq1GsKOR/Cw8fCumVRp5IkxcvyGXDf4bDmY6ifCb95GZr+IupUqgQs3SRJkqQ9rcXBcN6b0LBteNvRw8fC5+9FnUqS9HMtfSNcqXpbHrToCkMnQNpeUadSJWHpJkmSJFWERvuExVvzg6FgHTzxK8ieGHUqSdJPNe+f3xRu+dC6Jwx7DZq0jzqVKhFLN0mSJKmi1G8Gw16H/U+Eku3w/DD4Ym7UqSRJuyt/9Y5VSrPOg7Ofh1p1os2kSsfSTZIkSapIyXXDVU3b9YGignCWxBdzok4lSSqPjV/BW3+EB47acUvpwNst3LRTlm6SJElSRUusBac9Ds07Q8Ha8BlvH4yLOpUk6cds2QCPHwfT74TNX0PT/cK/RElIjDqZKilLN0mSJCkKKfXhNy/BgadAUAIvXwqfvBV1KknSzmzZAE+dAWuXQupecNKD8Nup0HjfqJOpErN0kyRJkqJSpyGc/A/Y71dQXAhPnQbT/wpBEHUySdK3iovg6TNh5ftQOw3Oeho6nwFJKVEnUyVn6SZJkiRFKSEhvD2py5BwxttbN8GjA2HNkqiTSZKCIFwwYcUMSEmFoa+GjwaQysHSTZIkSYpaUgr86h447q+QVBtW/BuePAUKcqNOJkk119Y8GH8RzHog3D7hXsjsFG0mVSmWbpIkSVJlEItB1rlw6TxotC/kfwFjT4P8L6NOJkk1z5b18I9jYeE4iCXA8X+D/U+IOpWqGEs3SZIkqTJJ2wtOfyJ8btCqOfBIP4s3SapIOR/Bk6fC2mxo0ALOmQCHDI06laogSzdJkiSpssk8EC6YAg3bwIbl8M8TYfO6qFNJUvX39VJ4+NjwLz2S68PgZ6FNj6hTqYqydJMkSZIqo8b7wm9eDmdZfL0Enjw5fL6QJCn+Soph+l3wj95QVAAtD4eLpvsMN/0slm6SJElSZdWwNfzmJajbGL5cAA/3g49fijqVJFU/026Ht26EbflQpyGc+gg0aht1KlVxlm6SJElSZdb0FzBkPNROh68Xw7O/gdkPR51KkqqHzevgsePgndHhdrffwsUzwudrSj+TpZskSZJU2TXvDCPmwKHnh9uvXgHjL4bthdHmkqSqLAjg1VHw+buQkARHXgkDb4PU5lEnUzWRFHUASZIkSeVQvykM/L/wtqd374APnoLCTXDSA5BcN+p0klS1rJoHT50Om78GYjBsIrQ8NOpUqmac6SZJkiRVFbEY9PoD/Po5SEyGxS/DA0dC/uqok0lS1VFSDK9c9k3hBvS5ycJNe4SlmyRJklTVtO8Dv34WGjSHdf+Bp8+Er5dGnUqSKr9Vc+GhX0LOh5DcAK5YAj1HRp1K1ZSlmyRJklQV7ftLGPpq+EPjlx/AfYfC+/dHnUqSKqfCAvj3vfDY8eF/MxOT4bi/+vw27VGWbpIkSVJV1XhfGPwctDky3J54Tfi8tyCINpckVSbbC2HsafDm76FoM7Q9OpzhdtBpUSdTNWfpJkmSJFVlrbvDOa/AEZeF22//CV67yuJNkgDWLIHHj4fl08OZwcf9FQY/D/UaR51MNYClmyRJklTVxWLQ988w6E4gBrMfCmd15H0RdTJJik7h5vC/hSvfh6TacNqjkHUuJCVHnUw1hKWbJEmSVF0ceh4cfxfEEuE/k+CFC5zxJqlm+vw9eHQA5K2AtJZw6Vxof2zUqVTDWLpJkiRJ1ckhQ+Hi98JZHSv+DXcfDJ+8FXUqSao4/3kLnjghXDAhlhDOAk7bO+pUqoEs3SRJkqTqptl+cNhvw+/Xfw7PnQM5H0YaSZIqxPJ/w7izoaQIOgyEC6fCL/pGnUo1lKWbJEmSVB0dcx30uQkSU6BwE4zpCa9c7u2mkqqn4iJ47Xfw2HGwfQu0OxZOexyaHxR1MtVglm6SJElSdVSrNvQcBcNnQsaB4b65j8HilyONJUlxV7wdnv0NzHoAgmLY/wQ4/QkXTFDkLN0kSZKk6qxR2/AZb91HhNvP/gZevBBKSqLNJUnx8s5oyH4tfJblmU+HhVty3ahTSZZukiRJUo1w9NXQ5sjw+4XPwPv3RZtHkn6ubZtgxt/h3f8Lt0+4DzoOjDaT9B1JUQeQJEmSVAFqp8LQCTDrIXjtf+DNP8DaT+CIS6FJ+6jTSVL5bdsEr14JH70QLpgA4WzeTqdGm0v6L850kyRJkmqSQ8+Hbt+sbDrvcbj/CPh0arSZJGl3TLsdFo4LC7e6TaDHSDj2z1Gnkr7H0k2SJEmqSWIxGHgbDH0NWveE4kJ45mzI+SjqZJL044IAFr8CM8eE26c+Ar9bBsf+ERKsN1T5+G+lJEmSVBO16QFnvwCte8C2fHjwGHhpOGzZEHUySfq+4iIY/9vwLwm2bw3/0uCAk6NOJf2oKlO65ebmMnjwYFJTU0lPT+e8885j06ZN5XpvEAQMGDCAWCzGv/71rz0bVJIkSaoqatWGM8dCs/3D27TmPwlv/D7qVJJU1tZ8eGZIuAhMLBF6XA5n/DOcuStVYlWmdBs8eDCLFi1i0qRJTJgwgWnTpnHhhReW67133XUXMQejJEmS9H11GsIFU6Df6HB7wZNwVyf4/L1oc0lSEMCM++COjrD0dUj65i8Kjv0T1G0UdTppl6pE6bZ48WImTpzIP/7xDw477DB69uzJPffcw7hx41i9evWPvnfBggXccccdPPLIIxWUVpIkSapiatWG7pfA0deE2xtWwFOnw/v3Q9GWaLNJqrkmXgNvXAdFm6HJL2DIeOgwIOpUUrlVidJtxowZpKenk5WVVbqvT58+JCQkMHPmzB98X0FBAb/+9a+57777yMzMLNe1tm3bRn5+fpkvSZIkqUb45bVwxeLwWUmFm8IfeJ84AbasjzqZpJqkpASm3v7Nggkx6H8rDJ8FrY+IOpm0W6pE6ZaTk0OzZs3K7EtKSqJRo0bk5OT84PtGjRrFEUccwQknnFDua40ePZq0tLTSr5YtW/7k3JIkSVKVk9oiXGBh4P9B7TRYORMeHQQbv4o6maSaYNPX8NRpMOV/w+0+N8LhF/n8NlVJkZZu11xzDbFY7Ee/lixZ8pPO/fLLLzN58mTuuuuu3XrftddeS15eXunXypUrf9L1JUmSpCqrVm3odgEMex3qZ8CaRfDkyVCQG3UySdVVEMDMB+CervCft8Lntw26E3qMjDqZ9JMlRXnxK6+8kqFDh/7oMfvssw+ZmZmsWbOmzP7t27eTm5v7g7eNTp48mWXLlpGenl5m/ymnnMKRRx7JO++8s9P3paSkkJKSUt6PIEmSJFVfGQfAuRPh4b7w1UdwW1vIOi+cBZdQJW6akVQVbFkPb/8J5nzzLPbMg+CkByBj/2hzST9TLAiCIOoQu7J48WL2339/5syZwyGHHALAm2++Sf/+/fniiy9o0aLF996Tk5PD2rVry+zr1KkTf/vb3zj++ONp27Ztua6dn59PWloaeXl5pKam/vwPI0mSJFU1K2fDc+dA/qpwu9PpMOib208l6ef4bBo8fx5s/maizbF/gu6XWuyr0tqdnqhKlG4AAwYM4KuvvmLMmDEUFRUxbNgwsrKyeOqppwBYtWoVvXv35oknnqBbt247PUcsFmP8+PGceOKJ5b6upZskSZJEeOvXB0/Dvy4BAkhvDSeNgZaHQUJi1OkkVTWFm+HpM8PSDaBJB+h3M7TvE20uaRd2pyeqMtXx2LFj6dixI71792bgwIH07NmTBx98sPT1oqIisrOzKSgoiDClJEmSVE3FYnDwr2Hoq2HhtmE5PDoAHuoF2zZGnU5SVRIE8NYfw8ItMRkOGQoXvmPhpmqnysx0i4oz3SRJkqT/UpALE6+Bhc+E2weeAqc87OqCknZt3TIYNxi+Xhxun/UMdOgfbSZpN1TLmW6SJEmSKom6jeDkB+HcNyCWCB+9AG/8Ppy9Ikk7s30bTP8rPHZcWLgl1IIjLrNwU7Vm6SZJkiTpp2l1OPzq7vD79++DZ86GDSuizSSpcnr1CnjrJti4Ghq3g1GLoO+fo04l7VGWbpIkSZJ+ui5nw6/uDWetLJkA9x4Ki8ZDSUnUySRVBp+9C3d3hflPAjHodT1cMBkaZESdTNrjLN0kSZIk/Txdh8D5b0Gr7rB9Kzw3FO7cD76YE3UySVHZXgjv/Q2ePBlyl4W3ovf7Cxz1P1A7Lep0UoWwdJMkSZL087U4GM6ZAFnnhtubcuCRfvD2n8KFFyTVLC+PgEk3QHEhdDwOfvcpdB8edSqpQlm6SZIkSYqPxCQ47q/wu8+gYVso2Q7v3hGuVFi8Pep0kirC1jyY/L/h6saxBDj+b3D6E1AnPepkUoWzdJMkSZIUX3UbwbkTocflQAxW/BueOg3yVkWdTNKeVLg5XJ102u3h9pFXwiFDISEx0lhSVCzdJEmSJMVfg0w49k9wxpOQmALLJsOYHrDktaiTSYq39cth6u3w4DGQsxDqNoET74djros6mRSpWBAEQdQhKrP8/HzS0tLIy8sjNTU16jiSJElS1fP1UnjxAvhyQbjdYRAcfRW06BJpLElx8NUieHQgbN0QbqekwuDnodVhkcaS9pTd6Ymc6SZJkiRpz2r6CzhvEnQfEW5nvwoP94WFz0abS9JPV1ISzlx9bFBYuGV0Cp/fNvJDCzfpG0lRB5AkSZJUAyQlQ7+/QJch4Yqm2a/C+Itg89fQ6XSo3zTqhJLKK381PHVGeCspQIuuMORFqNMw2lxSJeNMN0mSJEkVp1nH8Dlv+/0KgmJ44zr4W2eY98+ok0naleKicEXiB44OC7fkBuEM1mGvW7hJO+FMN0mSJEkVKyEBTrgXkmrDZ9NgUw68PALqNYEOA6JOJ2lnNqyAF38brkYM0LgdnP0iNGwdbS6pEnMhhV1wIQVJkiRpDyopgVevgLmPhtt7ZUG3C+CgMyAWizabJNi+Dab/Fd67G4o2h7PbBtwCnU6DpJSo00kVbnd6Ime6SZIkSYpOQgIMuBU2fglLJ8KqOTB+DiwaH/5Qf8BJkJAYdUqpZspfDc8MCcclQMvD4cS/Q+N9o80lVRGWbpIkSZKilZQCv34GNubAnEdg6q1hAbd0IqyeHy7AIKliLZ8Bz/4GNq+B2mkw6E444OSwKJdULpZukiRJkiqHBpnwy+tg724wcwz8ZxLMuDcs5X75B3/YlyrC1jx4985w7JVsh2YHwJlPQqN9ok4mVTn+X0uSJElS5dK+D5z9PPS5Kdx+9w548XzI/TTSWFK1VlIS3tZ93+Hw3l1h4XbgKXD+JAs36SdyppskSZKkyqnnKKjXFF65HD56Ifw6fDj0udEHuEvxNPthmPIXKFgXbjfaB/rfAu37uqCJ9DO4eukuuHqpJEmSFLHPp8OU0bB8ergdS4Ref4Ajr4g2l1TVfT4d3r8flkwIt1PS4PCLocflkFw32mxSJbU7PZGl2y5YukmSJEmVxPyxMPFa2JYXbh90Jhz9O1dSlHbXto3w4fPw6pUQFIf7ul0I/W6GxFrRZpMqOUu3OLJ0kyRJkiqRIICpt8E7N4fbKWnQ7Xw44CTI7BRtNqkqWPsJPP4r2Lg63N4rC7KGhSV2ok+gknbF0i2OLN0kSZKkSmjF+/DGdbBqbrhdOx0umQGpLSKNJVVqaz+Bx46DTTmQujcc/Gs4+mrLNmk37E5P5OqlkiRJkqqeVofDb16Go34HicmwdQM8eAzMeSScDVe8PeqEUuWxfAa8cws8fGxYuDU7AH47FXr93sJN2oOc6bYLznSTJEmSKrmvs8MyYWvejn3prWDoq+E/pZpqax7MuA+m3rpjX/POcPZ4qNc4ulxSFeZMN0mSJEk1R9MOcOk8OPJ/duzbsAKePBVWzo4ulxSVIID3x8Dt7XYUbm2Pgl/dC+dPtnCTKogz3XbBmW6SJElSFbLwWVi7FGY9uGPmW9a50Ot6qNso2mxSRVi9IFyVdNWccLtuE+h+CfS8AmKxSKNJ1YELKcSRpZskSZJUBeWvhsn/CwvGhtvJ9eGgM+CYa6B+s2izSXvCxhyYdjvMeRSCYqhVNyybD7/Ysk2KI0u3OLJ0kyRJkqqwT6fCm7+HnA/D7ToN4Zhr4ZChkJQSaTQpLr5cCHMfgw+ehqKCcN/+J8KA26BBRpTJpGrJ0i2OLN0kSZKkKq6kBD6fBm/+YUf5lt4KjrgMGrYJV0JNaRBpRGm3LZsMb/8ZVs/bsW/vQ6H3jdD2yOhySdWcpVscWbpJkiRJ1URxEcz/J7xzK2zK2bE/8yA45xWokx5ZNKncvpgLHzy14zbShFqw33Hh7M22R3srqbSHWbrFkaWbJEmSVM0UFoQLLcx/EtZ9Eu5r3A5O+Du0OizabNIP2ZgDC5+Bt/4Ylm0A+/0KBt0J9ZtGm02qQSzd4sjSTZIkSarGcj6EJ0/9ZuZbDNr0hM5nQZfBUSeTIAjCom3ZZFg0HooLw/0tusL+J8Dhl0BScrQZpRrG0i2OLN0kSZKkaq4gF964LnwQ/bdS94bW3aHnFZCxf3TZVDMFASx7G+Y9AR+/tGN/iy7hKrzdfgsJCdHlk2owS7c4snSTJEmSaojVC+CDcTDz/rL72/WBUx72mW/a84IAVrwPcx6GD5/bsf/gs6HzGdDmSJ/ZJkXM0i2OLN0kSZKkGmbVXPhqEXwyCZZMgKAE6jSCjgPh6KvDlU+leNqaF85q+/B5+HLBjv1tjoSuv4GDTo8smqSyLN3iyNJNkiRJqsG+/AAePz4sRQBq1YMel0H34ZBcv3LPOgqC+Of773MWbg5LyZQGZY8rKYGtG6Buo++//4s50PQX4ftq1dvxTLKVs2DLemjfd8c1SkpgWz58vQT27gZbcqFu4/C17+YoyIVadcIvgKIt4fmT6+04ZmserJgJX8yC1j1g76zv5/6uRePDz3fw4PBay2fAp+9A1yGQtnf4WfJXQ2oLyFsJW/OhYC1kHAib14ZZCjeHz2FLSISUVNi+FdZ8HB7zxezw9fn/hK+XwvYt4XVr1YM2PSDrXOgwoDy/K5IqkKVbHFm6SZIkSTVc3ir4z1uwYCysnLljf2Iy9Lo+LFoat4dtG2H9Z2G50qZnWOok1w/LpNxlsGUDFG6Cek3D4wByP4OOg8IFHfbOCs+5fRts/hqa7ReWOkEAG78MC6J9jgmLqXlPhO9JbxUWQm2PguKi8P3r/gMF6yD7dUhvDU3aQ9pe0KB5WHgVboavF0Px9vB8iUlhzoJ1sGoexBJgw3LIOCCc8ddoX9j3l2Hu9+8P/9mobfh5V84Kr9/5rDBz4WaonxH+Oq37BJp0CEupxFphaVVSFBZP36qfCb/oC5u+hqUTgSAs1Wqnh6XZ+s/Dfd+VmBJmTG+549crdxkkN4C9uobbX34Qllh1GkLR1nB1z/Wf/9dvbAz27QUN24S/pssmh78OyXXD35eSoh/4FyIGaS0hBmxYEX6ft3LHywm1fuS9P6LRPtDtQjjwVFcjlSoxS7c4snSTJEmSBISzrha/BJP/Nyy2VPXUz4SWh4YFYMHa+J67bmMgVva8scRvisEtP/y+TqdDp1PDW0mT68Y3k6S4252eKKmCMkmSJElS1ZaQAAecBB2Ph9xP4V8Xw6o54WsN20KTX4Sz0zavhcWvwLa8He+t1wwatg6fDbd5DTRuF97uuGYJ5H0zWyqxVjjDq1YdSKodnrtuY6hVN3xtY0547rqNwtlZHQZCQlJ46+WquWGG7VvCGVOb1oSzvFbPh9S9wtsbYzHIPCi8Rr0mkJQCaxaH+fJXh7O9OgwIZ+rVToWvs6H5QbB+OSx9Axa/DE07hFnrN4PCgvC4xu1g3bJw5llyvTBj7TRo1xtyPgrPu+4T2PvQb67dFN77WzgDLyExPL5OOjQ/GJp2DD9PUkp4W2aTX4Qz+P7zNrxzczijLpYQnmPV3HA2XuZB0CAznP0XlITlVcPWULId8r4IZ/sVboQWXcve7rpmMcx/Mvy1Tq4LGZ3CW123b4OchVC3STi7MPdTaLxvmKPTaeGtrF99FM6c2+uQcFbfvr3CY4IAlv87nIH47e9bcn0gCFchXf95uPro+s+hZbfw9yltrz39b66kiDjTbRec6SZJkiRpp7ZtCm/hbN8nLLi+q6Q4vP3y0ylh0bbP0Ts/RxDApq/CWzJ39fy1IAi/EhLik3937YlnxFWl60sSznSTJEmSpD0vpT4cdNrOX0tIDGdvHXDSj58jFgtnaZVHLBZt6RR14RX19SVpN0X0VySSJEmSJElS9WXpJkmSJEmSJMWZpZskSZIkSZIUZ5ZukiRJkiRJUpxZukmSJEmSJElxVmVKt9zcXAYPHkxqairp6emcd955bNq0aZfvmzFjBr169aJevXqkpqZy1FFHsWXLlgpILEmSJEmSpJqqypRugwcPZtGiRUyaNIkJEyYwbdo0Lrzwwh99z4wZM+jfvz99+/Zl1qxZzJ49mxEjRpCQUGU+tiRJkiRJkqqgWBAEQdQhdmXx4sXsv//+zJ49m6ysLAAmTpzIwIED+eKLL2jRosVO33f44Ydz7LHH8uc//7nc19q2bRvbtm0r3c7Pz6dly5bk5eWRmpr68z6IJEmSJEmSqqz8/HzS0tLK1RNViSlfM2bMID09vbRwA+jTpw8JCQnMnDlzp+9Zs2YNM2fOpFmzZhxxxBFkZGRw9NFHM3369B+91ujRo0lLSyv9atmyZVw/iyRJkiRJkqq/KlG65eTk0KxZszL7kpKSaNSoETk5OTt9z6effgrATTfdxAUXXMDEiRPp2rUrvXv35pNPPvnBa1177bXk5eWVfq1cuTJ+H0SSJEmSJEk1QqSl2zXXXEMsFvvRryVLlvykc5eUlADw29/+lmHDhtGlSxf++te/0qFDBx555JEffF9KSgqpqallviRJkiRJkqTdkRTlxa+88kqGDh36o8fss88+ZGZmsmbNmjL7t2/fTm5uLpmZmTt9X/PmzQHYf//9y+zfb7/9WLFixU8PLUmSJEmSJO1CpKVb06ZNadq06S6P6969Oxs2bGDu3LkccsghAEyePJmSkhIOO+ywnb6nTZs2tGjRguzs7DL7ly5dyoABA35+eEmSJEmSJOkHRFq6ldd+++1H//79ueCCCxgzZgxFRUWMGDGCM888s3Tl0lWrVtG7d2+eeOIJunXrRiwW46qrruLGG2+kc+fOHHzwwTz++OMsWbKE559/vtzX/nZx1/z8/D3y2SRJkiRJklQ1fNsPfdsX/ZgqUboBjB07lhEjRtC7d28SEhI45ZRTuPvuu0tfLyoqIjs7m4KCgtJ9I0eOZOvWrYwaNYrc3Fw6d+7MpEmT2Hfffct93Y0bNwK4iqkkSZIkSZKAsC9KS0v70WNiQXmquRqspKSE1atX06BBA2KxWNRx4iI/P5+WLVuycuVKF4qQfgbHkhQ/jicpPhxLUvw4nqT4qU7jKQgCNm7cSIsWLUhI+PH1SavMTLeoJCQksPfee0cdY49wdVYpPhxLUvw4nqT4cCxJ8eN4kuKnuoynXc1w+9aPV3KSJEmSJEmSdpulmyRJkiRJkhRnlm41UEpKCjfeeCMpKSlRR5GqNMeSFD+OJyk+HEtS/DiepPipqePJhRQkSZIkSZKkOHOmmyRJkiRJkhRnlm6SJEmSJElSnFm6SZIkSZIkSXFm6SZJkiRJkiTFmaVbDXPffffRpk0bateuzWGHHcasWbOijiRVKqNHj+bQQw+lQYMGNGvWjBNPPJHs7Owyx2zdupXhw4fTuHFj6tevzymnnMJXX31V5pgVK1YwaNAg6tatS7NmzbjqqqvYvn17RX4UqVK55ZZbiMVijBw5snSfY0kqv1WrVnH22WfTuHFj6tSpQ6dOnZgzZ07p60EQcMMNN9C8eXPq1KlDnz59+OSTT8qcIzc3l8GDB5Oamkp6ejrnnXcemzZtquiPIkWquLiY66+/nrZt21KnTh323Xdf/vznP/Pd9QUdT9LOTZs2jeOPP54WLVoQi8X417/+Veb1eI2dhQsXcuSRR1K7dm1atmzJbbfdtqc/2h5j6VaDPPPMM1xxxRXceOONzJs3j86dO9OvXz/WrFkTdTSp0pg6dSrDhw/n/fffZ9KkSRQVFdG3b182b95cesyoUaN45ZVXeO6555g6dSqrV6/m5JNPLn29uLiYQYMGUVhYyL///W8ef/xxHnvsMW644YYoPpIUudmzZ/PAAw9w0EEHldnvWJLKZ/369fTo0YNatWrx+uuv8/HHH3PHHXfQsGHD0mNuu+027r77bsaMGcPMmTOpV68e/fr1Y+vWraXHDB48mEWLFjFp0iQmTJjAtGnTuPDCC6P4SFJkbr31Vu6//37uvfdeFi9ezK233sptt93GPffcU3qM40nauc2bN9O5c2fuu+++nb4ej7GTn59P3759ad26NXPnzuX222/npptu4sEHH9zjn2+PCFRjdOvWLRg+fHjpdnFxcdCiRYtg9OjREaaSKrc1a9YEQDB16tQgCIJgw4YNQa1atYLnnnuu9JjFixcHQDBjxowgCILgtddeCxISEoKcnJzSY+6///4gNTU12LZtW8V+ACliGzduDNq3bx9MmjQpOProo4PLL788CALHkrQ7rr766qBnz54/+HpJSUmQmZkZ3H777aX7NmzYEKSkpARPP/10EARB8PHHHwdAMHv27NJjXn/99SAWiwWrVq3ac+GlSmbQoEHBueeeW2bfySefHAwePDgIAseTVF5AMH78+NLteI2dv//970HDhg3L/Fnv6quvDjp06LCHP9Ge4Uy3GqKwsJC5c+fSp0+f0n0JCQn06dOHGTNmRJhMqtzy8vIAaNSoEQBz586lqKiozFjq2LEjrVq1Kh1LM2bMoFOnTmRkZJQe069fP/Lz81m0aFEFppeiN3z4cAYNGlRmzIBjSdodL7/8MllZWZx22mk0a9aMLl268NBDD5W+/tlnn5GTk1NmPKWlpXHYYYeVGU/p6elkZWWVHtOnTx8SEhKYOXNmxX0YKWJHHHEEb7/9NkuXLgXggw8+YPr06QwYMABwPEk/VbzGzowZMzjqqKNITk4uPaZfv35kZ2ezfv36Cvo08ZMUdQBVjLVr11JcXFzmBxeAjIwMlixZElEqqXIrKSlh5MiR9OjRgwMPPBCAnJwckpOTSU9PL3NsRkYGOTk5pcfsbKx9+5pUU4wbN4558+Yxe/bs773mWJLK79NPP+X+++/niiuu4LrrrmP27NlcdtllJCcnc84555SOh52Nl++Op2bNmpV5PSkpiUaNGjmeVKNcc8015Ofn07FjRxITEykuLuYvf/kLgwcPBnA8ST9RvMZOTk4Obdu2/d45vn3tu49WqAos3STpBwwfPpyPPvqI6dOnRx1FqnJWrlzJ5ZdfzqRJk6hdu3bUcaQqraSkhKysLG6++WYAunTpwkcffcSYMWM455xzIk4nVS3PPvssY8eO5amnnuKAAw5gwYIFjBw5khYtWjieJMWdt5fWEE2aNCExMfF7q8J99dVXZGZmRpRKqrxGjBjBhAkTmDJlCnvvvXfp/szMTAoLC9mwYUOZ4787ljIzM3c61r59TaoJ5s6dy5o1a+jatStJSUkkJSUxdepU7r77bpKSksjIyHAsSeXUvHlz9t9//zL79ttvP1asWAHsGA8/9ue8zMzM7y2etX37dnJzcx1PqlGuuuoqrrnmGs4880w6derEkCFDGDVqFKNHjwYcT9JPFa+xU93+/GfpVkMkJydzyCGH8Pbbb5fuKykp4e2336Z79+4RJpMqlyAIGDFiBOPHj2fy5Mnfm9p8yCGHUKtWrTJjKTs7mxUrVpSOpe7du/Phhx+W+R/KpEmTSE1N/d4PTVJ11bt3bz788EMWLFhQ+pWVlcXgwYNLv3csSeXTo0cPsrOzy+xbunQprVu3BqBt27ZkZmaWGU/5+fnMnDmzzHjasGEDc+fOLT1m8uTJlJSUcNhhh1XAp5Aqh4KCAhISyv4YnJiYSElJCeB4kn6qeI2d7t27M23aNIqKikqPmTRpEh06dKhyt5YCrl5ak4wbNy5ISUkJHnvsseDjjz8OLrzwwiA9Pb3MqnBSTXfxxRcHaWlpwTvvvBN8+eWXpV8FBQWlx1x00UVBq1atgsmTJwdz5swJunfvHnTv3r309e3btwcHHnhg0Ldv32DBggXBxIkTg6ZNmwbXXnttFB9JqjS+u3ppEDiWpPKaNWtWkJSUFPzlL38JPvnkk2Ds2LFB3bp1gyeffLL0mFtuuSVIT08PXnrppWDhwoXBCSecELRt2zbYsmVL6TH9+/cPunTpEsycOTOYPn160L59++Css86K4iNJkTnnnHOCvfbaK5gwYULw2WefBS+++GLQpEmT4He/+13pMY4naec2btwYzJ8/P5g/f34ABHfeeWcwf/78YPny5UEQxGfsbNiwIcjIyAiGDBkSfPTRR8G4ceOCunXrBg888ECFf954sHSrYe65556gVatWQXJyctCtW7fg/fffjzqSVKkAO/169NFHS4/ZsmVLcMkllwQNGzYM6tatG5x00knBl19+WeY8n3/+eTBgwICgTp06QZMmTYIrr7wyKCoqquBPI1Uu/126OZak8nvllVeCAw88MEhJSQk6duwYPPjgg2VeLykpCa6//vogIyMjSElJCXr37h1kZ2eXOWbdunXBWWedFdSvXz9ITU0Nhg0bFmzcuLEiP4YUufz8/ODyyy8PWrVqFdSuXTvYZ599gt///vfBtm3bSo9xPEk7N2XKlJ3+rHTOOecEQRC/sfPBBx8EPXv2DFJSUoK99toruOWWWyrqI8ZdLAiCIJo5dpIkSZIkSVL15DPdJEmSJEmSpDizdJMkSZIkSZLizNJNkiRJkiRJijNLN0mSJEmSJCnOLN0kSZIkSZKkOLN0kyRJkiRJkuLM0k2SJEmSJEmKM0s3SZIkSZIkKc4s3SRJkqqRoUOHcuKJJ0Z2/SFDhnDzzTfH5VyFhYW0adOGOXPmxOV8kiRJFSkWBEEQdQhJkiTtWiwW+9HXb7zxRkaNGkUQBKSnp1dMqO/44IMP6NWrF8uXL6d+/fpxOee9997L+PHjefvtt+NyPkmSpIpi6SZJklRF5OTklH7/zDPPcMMNN5CdnV26r379+nEru36K888/n6SkJMaMGRO3c65fv57MzEzmzZvHAQccELfzSpIk7WneXipJklRFZGZmln6lpaURi8XK7Ktfv/73bi895phjuPTSSxk5ciQNGzYkIyODhx56iM2bNzNs2DAaNGhAu3bteP3118tc66OPPmLAgAHUr1+fjIwMhgwZwtq1a38wW3FxMc8//zzHH398mf1t2rTh5ptv5txzz6VBgwa0atWKBx98sPT1wsJCRowYQfPmzalduzatW7dm9OjRpa83bNiQHj16MG7cuJ/5qydJklSxLN0kSZKquccff5wmTZowa9YsLr30Ui6++GJOO+00jjjiCObNm0ffvn0ZMmQIBQUFAGzYsIFevXrRpUsX5syZw8SJE/nqq684/fTTf/AaCxcuJC8vj6ysrO+9dscdd5CVlcX8+fO55JJLuPjii0tn6N199928/PLLPPvss2RnZzN27FjatGlT5v3dunXj3Xffjd8viCRJUgWwdJMkSarmOnfuzB/+8Afat2/PtddeS+3atWnSpAkXXHAB7du354YbbmDdunUsXLgQCJ+j1qVLF26++WY6duxIly5deOSRR5gyZQpLly7d6TWWL19OYmIizZo1+95rAwcO5JJLLqFdu3ZcffXVNGnShClTpgCwYsUK2rdvT8+ePWndujU9e/bkrLPOKvP+Fi1asHz58jj/qkiSJO1Zlm6SJEnV3EEHHVT6fWJiIo0bN6ZTp06l+zIyMgBYs2YNEC6IMGXKlNJnxNWvX5+OHTsCsGzZsp1eY8uWLaSkpOx0sYfvXv/bW2K/vdbQoUNZsGABHTp04LLLLuPNN9/83vvr1KlTOgtPkiSpqkiKOoAkSZL2rFq1apXZjsViZfZ9W5SVlJQAsGnTJo4//nhuvfXW752refPmO71GkyZNKCgooLCwkOTk5F1e/9trde3alc8++4zXX3+dt956i9NPP50+ffrw/PPPlx6fm5tL06ZNy/txJUmSKgVLN0mSJJXRtWtXXnjhBdq0aUNSUvn+uHjwwQcD8PHHH5d+X16pqamcccYZnHHGGZx66qn079+f3NxcGjVqBISLOnTp0mW3zilJkhQ1by+VJElSGcOHDyc3N5ezzjqL2bNns2zZMt544w2GDRtGcXHxTt/TtGlTunbtyvTp03frWnfeeSdPP/00S5YsYenSpTz33HNkZmaSnp5eesy7775L3759f85HkiRJqnCWbpIkSSqjRYsWvPfeexQXF9O3b186derEyJEjSU9PJyHhh//4eP755zN27NjdulaDBg247bbbyMrK4tBDD+Xzzz/ntddeK73OjBkzyMvL49RTT/1Zn0mSJKmixYIgCKIOIUmSpKpvy5YtdOjQgWeeeYbu3bvH5ZxnnHEGnTt35rrrrovL+SRJkiqKM90kSZIUF3Xq1OGJJ55g7dq1cTlfYWEhnTp1YtSoUXE5nyRJUkVyppskSZIkSZIUZ850kyRJkiRJkuLM0k2SJEmSJEmKM0s3SZIkSZIkKc4s3SRJkiRJkqQ4s3STJEmSJEmS4szSTZIkSZIkSYozSzdJkiRJkiQpzizdJEmSJEmSpDizdJMkSZIkSZLi7P8BHFrMZWPav8YAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Configure the sequencer\n",
    "readout_module.sequencer5.sync_en(True)\n",
    "readout_module.sequencer5.gain_awg_path0(1.1 / num_seq)\n",
    "readout_module.sequencer5.gain_awg_path1(1.1 / num_seq)\n",
    "\n",
    "readout_module.sequencer5.connect_out0(\"I\")\n",
    "readout_module.sequencer5.connect_out1(\"Q\")\n",
    "\n",
    "# connect input paths of the same sequencer.\n",
    "readout_module.sequencer5.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer5.connect_acq_Q(\"in1\")\n",
    "\n",
    "# Start the sequencers\n",
    "for seq in range(0, 6):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop\n",
    "for seq in range(0, 6):\n",
    "    readout_module.get_acquisition_status(seq)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "# Plot the results\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len])\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][0:waveform_len])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e914b775",
   "metadata": {},
   "source": [
    "Note that now the outputs overflow and the output signal is clipped as intended. Also note that the output range of a QRM is 1 Vpp, while it's input range is 2 Vpp. This causes the signal in the figure to be clipped at 0.5 and -0.5."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c4ad566d",
   "metadata": {},
   "source": [
    "Frequency multiplexing\n",
    "----------------------\n",
    "Next, we will show frequency multiplexing. We will connect the outputs of various sequencers to a single output port pair, modulate their waveforms on unique carrier frequencies and in turn acquire, demodulate and integrate the results fed back into the inputs to validate the acquired signals. In this case, for simplicity, we will modulate a square wave pulse on each sequencer and we will play with the output gain. In order to visualize the frequency multiplexing, we will preform an FFT over the acquired scope acquisitions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "0d20b590",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:09.349675Z",
     "iopub.status.busy": "2024-07-23T09:58:09.349471Z",
     "iopub.status.idle": "2024-07-23T09:58:12.637709Z",
     "shell.execute_reply": "2024-07-23T09:58:12.636894Z"
    }
   },
   "outputs": [],
   "source": [
    "# Reset\n",
    "if cluster:\n",
    "    cluster.reset()\n",
    "else:\n",
    "    readout_module.reset()\n",
    "# Program\n",
    "program = \"\"\"\n",
    "      wait_sync 4\n",
    "loop: play      3,3,4\n",
    "      wait      140\n",
    "      acquire   0,0,16380\n",
    "      stop\n",
    "\"\"\"\n",
    "\n",
    "# Write sequence to file\n",
    "with open(\"sequence.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(\n",
    "        {\n",
    "            \"waveforms\": waveforms,\n",
    "            \"weights\": waveforms,\n",
    "            \"acquisitions\": acquisitions,\n",
    "            \"program\": program,\n",
    "        },\n",
    "        file,\n",
    "        indent=4,\n",
    "    )\n",
    "    file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "594d7db7",
   "metadata": {},
   "source": [
    "Lets start with a single sequencer with an AWG gain of 1.0 (only on path 0 to create a \"real\" pulse). Let's modulate it's output with a carrier frequency of 20MHz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5b52ac3c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:12.640501Z",
     "iopub.status.busy": "2024-07-23T09:58:12.640293Z",
     "iopub.status.idle": "2024-07-23T09:58:12.923431Z",
     "shell.execute_reply": "2024-07-23T09:58:12.920115Z"
    }
   },
   "outputs": [],
   "source": [
    "# Program sequencer\n",
    "readout_module.sequencer0.sequence(\"sequence.json\")\n",
    "\n",
    "readout_module.disconnect_outputs()\n",
    "readout_module.disconnect_inputs()\n",
    "\n",
    "# connect output paths of the sequencer\n",
    "readout_module.sequencer0.connect_out0(\"I\")\n",
    "readout_module.sequencer0.connect_out1(\"Q\")\n",
    "\n",
    "# connect input paths of the same sequencer.\n",
    "readout_module.sequencer0.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer0.connect_acq_Q(\"in1\")\n",
    "\n",
    "# Configure sequencer\n",
    "readout_module.sequencer0.sync_en(True)\n",
    "readout_module.sequencer0.gain_awg_path0(1.0)\n",
    "readout_module.sequencer0.gain_awg_path1(0.0)\n",
    "readout_module.sequencer0.nco_freq(20e6)\n",
    "readout_module.sequencer0.mod_en_awg(True)\n",
    "readout_module.sequencer0.demod_en_acq(True)\n",
    "readout_module.sequencer0.integration_length_acq(waveform_len)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "1b7d9004",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:12.932021Z",
     "iopub.status.busy": "2024-07-23T09:58:12.931846Z",
     "iopub.status.idle": "2024-07-23T09:58:12.970561Z",
     "shell.execute_reply": "2024-07-23T09:58:12.969586Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "# Start the sequencer\n",
    "readout_module.arm_sequencer(0)\n",
    "readout_module.start_sequencer(0)\n",
    "\n",
    "# Wait for the sequencer to stop\n",
    "readout_module.get_acquisition_status(0)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c2f860c",
   "metadata": {},
   "source": [
    "Now lets have a look at the FFT of the scope acquisition to verify the presence of one tone at 20MHz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "13d03d72",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:12.974075Z",
     "iopub.status.busy": "2024-07-23T09:58:12.973820Z",
     "iopub.status.idle": "2024-07-23T09:58:13.095069Z",
     "shell.execute_reply": "2024-07-23T09:58:13.094411Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the FFT\n",
    "fig, bx = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "yf = abs(rfft(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len]))\n",
    "xf = rfftfreq(1000, 1 / 1e3)\n",
    "norm_fact = readout_module.sequencer0.gain_awg_path0() / 2 / np.max(yf)\n",
    "bx.plot(xf[0:100], yf[0:100] * norm_fact)\n",
    "bx.set_xlabel(\"Frequency (MHz)\")\n",
    "bx.set_ylabel(\"Amplitude\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dbe5d1eb",
   "metadata": {},
   "source": [
    "Now let's have a look at the hardware demodulated and integrated results and check if it matches our expectations. Don't forget that we need to divide the integration results by the integration length. In this case, the integration length is the same as the waveform length."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "ffd37c21",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:13.097457Z",
     "iopub.status.busy": "2024-07-23T09:58:13.097278Z",
     "iopub.status.idle": "2024-07-23T09:58:13.101315Z",
     "shell.execute_reply": "2024-07-23T09:58:13.100665Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Integration results:\n",
      "I = 0.5561592574499267\n",
      "Q = 0.04270835368832438\n",
      "R = sqrt(I^2 + Q^2) = 0.5577966682600577\n"
     ]
    }
   ],
   "source": [
    "bins = acq[\"scope\"][\"acquisition\"][\"bins\"]\n",
    "I_data = bins[\"integration\"][\"path0\"][0] / waveform_len\n",
    "Q_data = bins[\"integration\"][\"path1\"][0] / waveform_len\n",
    "print(\"Integration results:\")\n",
    "print(f\"I = {I_data}\")\n",
    "print(f\"Q = {Q_data}\")\n",
    "print(f\"R = sqrt(I^2 + Q^2) = {math.sqrt(I_data**2 + Q_data**2)}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ef404ffa",
   "metadata": {},
   "source": [
    "The pulse acquired at the inputs is automatically demodulated at 20MHz, but due to phase rotation caused by output-to-input latency the result is not purely real. However the amplitude of the IQ vector is 0.5 as expected because: 1Vpp output range / 2Vpp input range = 0.5.\n",
    "\n",
    "Now lets increase the number of sequencers to three, each with a slightly different AWG gain. We will modulate the signals of sequencer 0 to 2 with a carrier frequencies at 20MHz, 30MHz and 40MHz respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "dc876861",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:13.103479Z",
     "iopub.status.busy": "2024-07-23T09:58:13.103311Z",
     "iopub.status.idle": "2024-07-23T09:58:13.807079Z",
     "shell.execute_reply": "2024-07-23T09:58:13.803571Z"
    }
   },
   "outputs": [],
   "source": [
    "num_seq = 3\n",
    "for seq in range(0, num_seq):\n",
    "    # Program sequencers\n",
    "    readout_module.sequencers[seq].sequence(\"sequence.json\")\n",
    "\n",
    "    # Configure the channel map\n",
    "    readout_module.sequencers[seq].connect_out0(\"I\")\n",
    "    readout_module.sequencers[seq].connect_out1(\"Q\")\n",
    "\n",
    "    # Connect input paths of the same sequencer.\n",
    "    readout_module.sequencers[seq].connect_acq_I(\"in0\")\n",
    "    readout_module.sequencers[seq].connect_acq_Q(\"in1\")\n",
    "\n",
    "    # Configure the sequencers\n",
    "    readout_module.sequencers[seq].sync_en(True)\n",
    "    readout_module.sequencers[seq].mod_en_awg(True)\n",
    "    readout_module.sequencers[seq].demod_en_acq(True)\n",
    "    readout_module.sequencers[seq].integration_length_acq(waveform_len)\n",
    "\n",
    "# Set the gains\n",
    "readout_module.sequencer0.gain_awg_path0(0.5)\n",
    "readout_module.sequencer0.gain_awg_path1(0.0)\n",
    "readout_module.sequencer1.gain_awg_path0(0.25)\n",
    "readout_module.sequencer1.gain_awg_path1(0.0)\n",
    "readout_module.sequencer2.gain_awg_path0(0.125)\n",
    "readout_module.sequencer2.gain_awg_path1(0.0)\n",
    "\n",
    "# Set the frequencies\n",
    "readout_module.sequencer0.nco_freq(20e6)\n",
    "readout_module.sequencer1.nco_freq(30e6)\n",
    "readout_module.sequencer2.nco_freq(40e6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "7129d6fb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:13.818730Z",
     "iopub.status.busy": "2024-07-23T09:58:13.817705Z",
     "iopub.status.idle": "2024-07-23T09:58:13.898204Z",
     "shell.execute_reply": "2024-07-23T09:58:13.895057Z"
    }
   },
   "outputs": [],
   "source": [
    "# Start the sequencers\n",
    "for seq in range(0, 3):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop\n",
    "for seq in range(0, 3):\n",
    "    readout_module.get_acquisition_status(seq)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b30ddf22",
   "metadata": {},
   "source": [
    "Now lets have a look at the FFT of the scope acquisition to verify the presence of three tones at 20MHz, 30Mhz and 40MHz."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "8f53c3a6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:13.909658Z",
     "iopub.status.busy": "2024-07-23T09:58:13.908747Z",
     "iopub.status.idle": "2024-07-23T09:58:14.039880Z",
     "shell.execute_reply": "2024-07-23T09:58:14.039159Z"
    }
   },
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the FFT\n",
    "fig, bx = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "yf = abs(rfft(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len]))\n",
    "xf = rfftfreq(1000, 1 / 1e3)\n",
    "bx.plot(xf[0:100], yf[0:100] * norm_fact)\n",
    "bx.set_xlabel(\"Frequency (MHz)\")\n",
    "bx.set_ylabel(\"Amplitude\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0a6d82f",
   "metadata": {},
   "source": [
    "Now let's check if the hardware demodulated and integrated results match our expectations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "454b3187",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:14.042306Z",
     "iopub.status.busy": "2024-07-23T09:58:14.042108Z",
     "iopub.status.idle": "2024-07-23T09:58:14.122220Z",
     "shell.execute_reply": "2024-07-23T09:58:14.121192Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sequencer 0\n",
      "Integration results:\n",
      "I = 0.278732779677577\n",
      "Q = 0.02196922325354177\n",
      "R = sqrt(I^2 + Q^2) = 0.27959722680518956\n",
      "---------------------------------------------------------------------------------\n",
      "Sequencer 1\n",
      "Integration results:\n",
      "I = -0.13905471421592575\n",
      "Q = -0.015300439667806547\n",
      "R = sqrt(I^2 + Q^2) = 0.13989394911754036\n",
      "---------------------------------------------------------------------------------\n",
      "Sequencer 2\n",
      "Integration results:\n",
      "I = 0.06665852467024914\n",
      "Q = 0.011223253541768442\n",
      "R = sqrt(I^2 + Q^2) = 0.06759674793417973\n",
      "---------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "for seq in range(0, num_seq):\n",
    "    readout_module.store_scope_acquisition(seq, \"scope\")\n",
    "    acq = readout_module.get_acquisitions(seq)\n",
    "    bins = acq[\"scope\"][\"acquisition\"][\"bins\"]\n",
    "    I_data = bins[\"integration\"][\"path0\"][0] / waveform_len\n",
    "    Q_data = bins[\"integration\"][\"path1\"][0] / waveform_len\n",
    "    print(f\"Sequencer {seq}\")\n",
    "    print(\"Integration results:\")\n",
    "    print(f\"I = {I_data}\")\n",
    "    print(f\"Q = {Q_data}\")\n",
    "    print(f\"R = sqrt(I^2 + Q^2) = {math.sqrt(I_data**2 + Q_data**2)}\")\n",
    "    print(\"---------------------------------------------------------------------------------\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a0f17dc0",
   "metadata": {},
   "source": [
    "Again, the acquired signals on the input are automatically demodulated at 20MHz, 30MHz and 40MHz and we see that the amplitude of the IQ vectors match the gain values we set divided by two, which matches our expectations.\n",
    "\n",
    "Now, let's try it one final time with six sequencers, each with 0.15 AWG gain. We will modulate the outputs of sequencer 0 to 5 with carrier frequencies at 20MHz, 30Mhz, 40MHz, 50MHz, 60MHz and 70MHz respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "967619c1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:14.125487Z",
     "iopub.status.busy": "2024-07-23T09:58:14.125213Z",
     "iopub.status.idle": "2024-07-23T09:58:15.477961Z",
     "shell.execute_reply": "2024-07-23T09:58:15.474593Z"
    }
   },
   "outputs": [],
   "source": [
    "num_seq = 6\n",
    "for seq in range(0, num_seq):\n",
    "    # Program sequencers\n",
    "    readout_module.sequencers[seq].sequence(\"sequence.json\")\n",
    "\n",
    "    # Configure the channel map\n",
    "    readout_module.sequencers[seq].connect_out0(\"I\")\n",
    "    readout_module.sequencers[seq].connect_out1(\"Q\")\n",
    "\n",
    "    # Connect input paths of the same sequencer.\n",
    "    readout_module.sequencers[seq].connect_acq_I(\"in0\")\n",
    "    readout_module.sequencers[seq].connect_acq_Q(\"in1\")\n",
    "\n",
    "    # Configure the sequencers\n",
    "    readout_module.sequencers[seq].sync_en(True)\n",
    "    readout_module.sequencers[seq].gain_awg_path0(0.15)\n",
    "    readout_module.sequencers[seq].gain_awg_path1(0.0)\n",
    "    readout_module.sequencers[seq].mod_en_awg(True)\n",
    "    readout_module.sequencers[seq].demod_en_acq(True)\n",
    "    readout_module.sequencers[seq].integration_length_acq(waveform_len)\n",
    "\n",
    "# Set the frequencies\n",
    "readout_module.sequencer0.nco_freq(20e6)\n",
    "readout_module.sequencer1.nco_freq(30e6)\n",
    "readout_module.sequencer2.nco_freq(40e6)\n",
    "readout_module.sequencer3.nco_freq(50e6)\n",
    "readout_module.sequencer4.nco_freq(60e6)\n",
    "readout_module.sequencer5.nco_freq(70e6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "440b1166",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:15.489255Z",
     "iopub.status.busy": "2024-07-23T09:58:15.488386Z",
     "iopub.status.idle": "2024-07-23T09:58:15.585836Z",
     "shell.execute_reply": "2024-07-23T09:58:15.582414Z"
    }
   },
   "outputs": [],
   "source": [
    "# Start the sequencers\n",
    "for seq in range(0, 6):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop\n",
    "for seq in range(0, 6):\n",
    "    readout_module.get_acquisition_status(seq)\n",
    "\n",
    "# Get acquisition data\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7211ea1c",
   "metadata": {},
   "source": [
    "Now lets have a look at the FFT of the scope acquisition to verify the presence of six tones at 20MHz, 30Mhz, 40MHz, 50MHz, 60MHz and 70MHz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "aa2c5f60",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:15.596865Z",
     "iopub.status.busy": "2024-07-23T09:58:15.596014Z",
     "iopub.status.idle": "2024-07-23T09:58:15.733300Z",
     "shell.execute_reply": "2024-07-23T09:58:15.732620Z"
    },
    "tags": [
     "nbsphinx-thumbnail"
    ]
   },
   "outputs": [
    {
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      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the FFT\n",
    "fig, bx = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "yf = abs(rfft(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:waveform_len]))\n",
    "xf = rfftfreq(1000, 1 / 1e3)\n",
    "bx.plot(xf[0:100], yf[0:100] * norm_fact)\n",
    "bx.set_xlabel(\"Frequency (MHz)\")\n",
    "bx.set_ylabel(\"Amplitude\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "16034435",
   "metadata": {},
   "source": [
    "Note that we lose a little bit of power over the frequency range, but that is to be expected due to frequency dependant components in the output and input path. Now let's check if the hardware demodulated and integrated results match our expectations."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "8ab2f02f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:15.735760Z",
     "iopub.status.busy": "2024-07-23T09:58:15.735559Z",
     "iopub.status.idle": "2024-07-23T09:58:15.909875Z",
     "shell.execute_reply": "2024-07-23T09:58:15.906582Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sequencer 0\n",
      "Integration results:\n",
      "I = 0.08383732291157792\n",
      "Q = 0.006258915486077187\n",
      "R = sqrt(I^2 + Q^2) = 0.08407062944954108\n",
      "---------------------------------------------------------------------------------\n",
      "Sequencer 1\n",
      "Integration results:\n",
      "I = -0.0832266731802638\n",
      "Q = -0.009926233512457255\n",
      "R = sqrt(I^2 + Q^2) = 0.08381652128547375\n",
      "---------------------------------------------------------------------------------\n",
      "Sequencer 2\n",
      "Integration results:\n",
      "I = 0.08155593551538837\n",
      "Q = 0.01285686370297997\n",
      "R = sqrt(I^2 + Q^2) = 0.0825631247111396\n",
      "---------------------------------------------------------------------------------\n",
      "Sequencer 3\n",
      "Integration results:\n",
      "I = -0.0802237420615535\n",
      "Q = -0.0169438202247191\n",
      "R = sqrt(I^2 + Q^2) = 0.08199354751543726\n",
      "---------------------------------------------------------------------------------\n",
      "Sequencer 4\n",
      "Integration results:\n",
      "I = 0.0784103566194431\n",
      "Q = 0.020122129946262824\n",
      "R = sqrt(I^2 + Q^2) = 0.08095112191169762\n",
      "---------------------------------------------------------------------------------\n",
      "Sequencer 5\n",
      "Integration results:\n",
      "I = -0.07625012212994627\n",
      "Q = -0.022866145578895946\n",
      "R = sqrt(I^2 + Q^2) = 0.07960491026605697\n",
      "---------------------------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "for seq in range(0, num_seq):\n",
    "    readout_module.store_scope_acquisition(seq, \"scope\")\n",
    "    acq = readout_module.get_acquisitions(seq)\n",
    "    bins = acq[\"scope\"][\"acquisition\"][\"bins\"]\n",
    "    I_data = bins[\"integration\"][\"path0\"][0] / waveform_len\n",
    "    Q_data = bins[\"integration\"][\"path1\"][0] / waveform_len\n",
    "    print(f\"Sequencer {seq}\")\n",
    "    print(\"Integration results:\")\n",
    "    print(f\"I = {I_data}\")\n",
    "    print(f\"Q = {Q_data}\")\n",
    "    print(f\"R = sqrt(I^2 + Q^2) = {math.sqrt(I_data**2 + Q_data**2)}\")\n",
    "    print(\"---------------------------------------------------------------------------------\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d9cbc40d",
   "metadata": {},
   "source": [
    "Taking the power loss over frequency into account, the amplitudes of the IQ vectors match our expectations again."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21cf0db3",
   "metadata": {},
   "source": [
    "\n",
    "Real mode\n",
    "---------------\n",
    "\n",
    "Many applications require multiple outputs to be controlled independently and only output real signals instead of a modulated IQ pair. To achieve this we will connect one sequencer to each output and only use path 0 to control an even numbered output and path 1 to control an odd numbered output. To demonstrate this, we will simply output an independently timed sine on output $\\text{O}^{1}$ and a sawtooth on output $\\text{O}^{2}$, which we will then acquire on the inputs.\n",
    "\n",
    "*Note that before we make these new connections between the sequencers and the physical inputs and outputs* ($\\text{O}^{[1-2]}$ and $\\text{I}^{[1-2]}$), *we must first erase the exisiting connections using the API, namely* `disconnect_outputs()` and `disconnect_inputs()`.\n",
    "\n",
    "Lets create a Q1ASM program to sequence the waveforms for sequencer 0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "71258bd6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:15.920720Z",
     "iopub.status.busy": "2024-07-23T09:58:15.919920Z",
     "iopub.status.idle": "2024-07-23T09:58:19.198409Z",
     "shell.execute_reply": "2024-07-23T09:58:19.197644Z"
    }
   },
   "outputs": [],
   "source": [
    "# Reset\n",
    "cluster.reset()\n",
    "\n",
    "# Program\n",
    "program = \"\"\"\n",
    "wait_sync 4\n",
    "play      1,1,4\n",
    "wait      140\n",
    "acquire   0,0,16380\n",
    "stop\n",
    "\"\"\"\n",
    "\n",
    "# Write sequence to file\n",
    "with open(\"sequence0.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(\n",
    "        {\n",
    "            \"waveforms\": waveforms,\n",
    "            \"weights\": waveforms,\n",
    "            \"acquisitions\": acquisitions,\n",
    "            \"program\": program,\n",
    "        },\n",
    "        file,\n",
    "        indent=4,\n",
    "    )\n",
    "    file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2397f7e9",
   "metadata": {},
   "source": [
    "Lets create a Q1ASM program to sequence the waveforms for sequencer 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "66e1cf9d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:19.201010Z",
     "iopub.status.busy": "2024-07-23T09:58:19.200839Z",
     "iopub.status.idle": "2024-07-23T09:58:19.212920Z",
     "shell.execute_reply": "2024-07-23T09:58:19.212398Z"
    }
   },
   "outputs": [],
   "source": [
    "# Program\n",
    "program = \"\"\"\n",
    "wait_sync 4\n",
    "wait      500\n",
    "play      2,2,1000\n",
    "stop\n",
    "\"\"\"\n",
    "\n",
    "# Write sequence to file\n",
    "with open(\"sequence1.json\", \"w\", encoding=\"utf-8\") as file:\n",
    "    json.dump(\n",
    "        {\n",
    "            \"waveforms\": waveforms,\n",
    "            \"weights\": waveforms,\n",
    "            \"acquisitions\": acquisitions,\n",
    "            \"program\": program,\n",
    "        },\n",
    "        file,\n",
    "        indent=4,\n",
    "    )\n",
    "    file.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b770c91",
   "metadata": {},
   "source": [
    "Let's configure both sequencers and connect them to their respective outputs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "4633258d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:19.215102Z",
     "iopub.status.busy": "2024-07-23T09:58:19.214940Z",
     "iopub.status.idle": "2024-07-23T09:58:19.578368Z",
     "shell.execute_reply": "2024-07-23T09:58:19.575030Z"
    }
   },
   "outputs": [],
   "source": [
    "# Configure scope mode\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\")\n",
    "\n",
    "# Program sequencer\n",
    "num_seq = 2\n",
    "for seq in range(0, num_seq):\n",
    "    readout_module.sequencers[seq].sequence(f\"sequence{seq}.json\")\n",
    "\n",
    "# Configure the channel map\n",
    "readout_module.sequencer0.connect_out0(\"I\")\n",
    "readout_module.sequencer1.connect_out1(\"I\")\n",
    "\n",
    "readout_module.sequencer0.connect_acq_I(\"in0\")\n",
    "readout_module.sequencer0.connect_acq_Q(\"in1\")\n",
    "\n",
    "# Configure sequencer\n",
    "for seq in range(0, num_seq):\n",
    "    readout_module.sequencers[seq].sync_en(True)\n",
    "    readout_module.sequencers[seq].mod_en_awg(False)\n",
    "    readout_module.sequencers[seq].demod_en_acq(False)\n",
    "\n",
    "readout_module.sequencer0.gain_awg_path1(\n",
    "    0.0\n",
    ")  # Disable sequencer 0 path 1, because we will not use it.\n",
    "readout_module.sequencer1.gain_awg_path1(\n",
    "    0.0\n",
    ")  # Disable sequencer 1 path 1, because we will not use it."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fdccf4ef",
   "metadata": {},
   "source": [
    "Now, let start the sequencers and visualize the resulting sequence."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "cd1ec013",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:19.586021Z",
     "iopub.status.busy": "2024-07-23T09:58:19.585851Z",
     "iopub.status.idle": "2024-07-23T09:58:19.754927Z",
     "shell.execute_reply": "2024-07-23T09:58:19.754191Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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xhAT42BtMRERE5Bgy8oo46/nFpOYUcpFjOc96v4u/T8GxT+g2ES56Hfxb1l7IGmAaml4qIlJCRTeRGhaVlMXUD9aWfv/N7aNtTFN/PT6pNxf2b81lb6wiNaeQOz5dz1e3jbI7loiIiAgAuYXF/LoziY0xh1m1dQ+xmUV85XqSnr4xxz5p+G0w6m7wawneDWPd2tI13TzqdBMRUdFNpAbN23KIO2dtKP3+7euH4PJy2Jiofhvcvjnf3jGKS99Yydr9h7nu3dV8dNMwjPqyxomIiIg0KAXFbt5euo+vN8SRkJGPqyiD17xf4zHnVqiohublCzctgNb9688abVVW8nOp001EREU3kRqyNTaDaV9uAqzdOB+f1Iuze4XZG6oBGNiuGdcOb8cnv8ewbE8K1727hk/+MtzuWCIiItJIFBZ72JeSzcKdSTy3YBdg0t/YyxBHLP/n+zWtSC1/0k0/Q/hgcDb8t18lnW7aSEFEREU3kRqRlJnPLR+to6DYw5ndQ3jnhqE4HQ3108za9++L++Ln8uKtpftYHpXCJ78fYMqI9nbHEhERkQZs9vpYHvhqMwB+5POA15fs951f8eDel0DL7tBmIHSb0IC72ipQuqabim4iIiq6iVQzt8fk7s82kpCZT5fQprxy9UAV3GrAP8/rSXpuIV+ui+WR77YxolMLuoQ2tTuWiIiINCCmabI5NoPftsfyw5KV/Nf7awY7dtPaSKv4hJF3wdC/QPOOtRu0Djna6abppSIiKrqJVKO8QjfXvbuadQcO4+9y8tZ1gwn09bY7VoP1n0v6snJvKrGH87jm7d9Z9MAZNPXRrzURERE5eQkZ+azZn8a8LfEkHM6ibcIiXne9yv3H2zR9wgwYcXvj6mg7BhNH6VciIo2d3p2KVKNXFu5h3YHDADxzeT86hajzqiZ5Ox28c8MQLnl9JUlZBdz0wVpevWogrYIaxu5fIiIiUjsOpObg9pi8unAPyzbt5EGvz3jTa6l10PWnwR1Og3P+Da36Hb3MoY2ySpUUHj3qdBMRUdFNpBq4PSbTvtzE95viAXjj2kGc27e1zakahx6tAnn7+iFM/WANa6LTeOCrzXx8s3Y0FRERkRNLyMhn9vqDPP/zbtoayUx0rGGZz2z8jILSMabhxAhsA93PgzP/CU2C7Qtcn2hNNxERFd1EqsOPWw+VFtwm9A5Twa2Wjenakg9vGsY1b69meVQKry2K4p5xXe2OJSIiInVMfpGbxbuS2RybzvI160jIhSGO3XzkvYixzq2l40zDgdHpTAjpgTH6XgjQDvSVVbKmm4iIqOgmcsrcHpNZq2NKv//XxX1sTNN4jerckkfO78m/5+3kxV9243QY3HlmF7tjiYiIiM08HpMPVu4n9nAe762IBuAW5w/M9Z4Ff1iRwoMDs/UAnIGtMcY/DiHd7Alc3xnWVFvTdNscRETEfiq6iZwC0zR59PttrNqXisvLwY/3nEZogNYTs8vNYzqyOzGLL9fF8uIvuxncvhkjOrWwO5aIiIjY4LfIJOZtPcTs9QcJJJcLnL+z3/fdigf3vxrH2L9Bi861G7IBKu100/RSEREV3UROVkZuEbd+so7f96VhGPDK5AF0CdXGCXYyDINnLutHTFouv+9L465ZG1j4f2cQ1EQ7yIqIiDQGpmmSnF3Ai/M2E7V5Oec517DPZwEOo4ICULOO0PsSaN0fel2knUerje5HEZESKrqJnATTNHno2y38vi8NX28HT17UR+u41RGGYfD29UOY9N8VRKfk8O8fdvDMZf1wOPQCUEREpCEyTZPP1hxk7qY4NselM754Ga+6XgefY5ww6AY4+0ltiFBTSoqXml4qIqKim8jJ+GZDHD9uTQDghSsGcH4/FdzqkgBfb/51UR+mvLuar9bHUuwxefbyfng7HXZHExERkVO0JzGL9i38+XDlfuZsjictp5B+mYv5xPtVnA4TXEfHFoX1x7vDSHC6oNtEaNUHfIPsC98IHJ1eam8OEZG6QEU3kSoyTZNPVx8AwOV0ML5XqM2JpCJjurbkxSv78/fZW/h2Yxytg3z5+8QedscSERGRk2SaJv9bvJfnFuzCwMPFjhVMduxmnHMjrV1pR8c5fTDajYBx0/FuO8TGxI3UkU430/TYHERExH4quolUQXZBMde/u5oNMekAfHfnaHy8nPaGkmO6dFBbvJ0O7v5sIzOX7GV8rzAGtWtmdywRERGphEMZeayJTqNTy6ZsiDnMD8vWMC7re35ybaGnI6bikwZOwTjjIQhqW6tZ5SjzyO6l2khBRERFN5Eqmf79NjbEpOPj5eDiAeH0bB1gdyQ5gQv7t2FRZBLfbozjgS83M++e02jiUqFURESkrioodvPu8mienb8LgB5GDI96fcxXzu3l3734BsHo+yB8EHQ8XZsh1AnavVREpISKbiKVtD0+g282xOEw4OObhzOsY3O7I0klPX5hb1btTWVfSg7PLojksQt72x1JRERE/iQlu4DVe1N5e+keCuO38Z3rHQY49lU8OLgdDL8dht8KDn2YVjdpeqmIiIpuIpVwKCOPB7/eCsDEPq1UcKtngvy8eebyftzw3hreX7Gfs3uFMapzS7tjiYiINHpFbg+3f7KBX3cm4k0xH3k/zXfOHeV2HvV0Hoej85lW91RQOPS5zJ7AckKaXioicpSKbiKVcN/nm9gal4FhwA0jO9gdR07C6d1CuGZ4O2atjuGBLzfzxa0jiWjuZ3csERGRRmfZnmS+3RDHjkOZRCZkcY5jLTO8NnG1128Vn3DTAhztRtRuSDkFJdNL1ekmIqKim8gJfLhyP6ujrR2xnrmsH8M7tbA5kZysh8/ryaq9qUSn5HDj+2v44W6t7yYiIlLTcgqK+WxNDB1a+PP52hiW7zzIQ16zeMi5mkyXP50dh8qf1G8yjLjDmkbqpxkG9Urp7qU25xARqQNUdBM5joy8Ip5fYC3iO3V0B64cEmFzIjkV/j5ezLplOBe/voK9yTm8/lsUD0zobncsERGRBiuv0M1NH6xlfXQSXYx4mhlZvOY9n7Od6wEIMTIBMEN6YrQdDN3Ph46ngaupNkWot0oeN1XdRERUdBM5jr99tZmsgmLat/Dj0fN72R1HqkHroCY8MakPt32ynreW7uP8fq3p2TrQ7lgiIiL1nsdjkpZbyHvLo1m4M4nUzBz6FG3mclbwhe/Sik8acQeMuB0juF3thpUaY2p6qYhIKRXdRI5h4c5Eft6RiMOAF67oj8OhT1sbigm9wxjXI5SFkUnc8ekG5tw1mgBfb7tjiYiI1Es5BcWs3JvKs/MjKUrewxDHbrw9EXzl/RodvRL/NNqAjmPhzH+C1mlrmEo6FDW/VERERTeRisSl53Hv55sAuHJIBEM6aC2RhsQwDJ67oj/nv7qM6JQcHv52G69ePdDuWCIiIvVGUlY+ry7cw7I9KRxIzeUCxyo+8/6Qlj6Z5caa3v4YvS+G3pdA17NrP6zUrtJpwep0ExFR0U3kT4rdHu77fCPZBcUMahfMkxf1sTuS1IDm/i7+e80grnxzFXM2x3Ne39ZM7NPK7lgiIiJ12uaD6Tw2ZzubDqYDJnc5v+MK1xLaO5LKD27RFS57ByO0F3i5ajuq2MTEceQLdbqJiKjoJvInj36/jbX7D9PUx4uXJg/A5eWwO5LUkMHtm3Hr2E78b/Fenpy7nbN6hOrxFhER+ZP03EJ+35fG8z/vYm9SJv2MfTzhtYwbvH4pPzgoAvpdCV0nQNsh4NAu4Y2PppeKiJRQ0U3kD2JSc/lszUEAnr+iH+1b+NucSGraPeO68tX6WOIz8nli7nb+c0lfuyOJiIjYyuMxWR9zmMhDmXy8aj/tU5bQ1YjjOed6BvpGlT/BFQDnPAl9LgPfoNoPLHXLkemlpnYvFRFR0U3kj95fGQ3AqM4tmNintc1ppDb4ejuZfkEv7v18I5+ujmFQu2ZcNrit3bFERERqnWma7DiUyfmvLqe7EcMAx17+5VzGcFdk2YEOb/AUWV9f+zV0HV/7YaXuOlJ0M7R7qYiIim4iJb7ZEMv7K/YDcOOoDrZmkdp1Yf82RKfk8OIvu3n0+20MbBdMp5CmdscSERGpMcVuDw7DwASeXRDJm0v24cTNACOKx7x+53rnzziNo51KZsvuGCm7rZ1HJ70GzdrbF17qNFPTS0VESqnoJgJsiDnMg19vBeDOMztzTm8tqN/Y3HlmF1btTWXVvlTu+Xwjc+4cg8NhnPhEERGReiSnoJj49DxufH8t6bmFdDIOcan7Jz7zPshI547yJzh94KyHMUbd84ddKUWOo/R5oqKbiEi9WzH89ddfp0OHDvj6+jJ8+HDWrFlTqfM+//xzDMPg4osvrtmAUu+k5xZy68frKXR7OLtXGP93dne7I4kNnA6Dl68agL/Lyba4TL7bFGd3JBERkWpjmibPzI+k92MLuPilBbTLXMd0zxvM5m9M9VpQpuDmadENzn0OHk6Av+2B0feq4CZVoN1LRURK1KtOty+++IJp06Yxc+ZMhg8fzssvv8yECRPYtWsXoaGhxzxv//79PPDAA5x22mm1mFbqi7eX7SM5q4DOIf68PHmAupsasbBAX87v15ov18Xy0DdbGdW5Ja2CfO2OJSIiclIy84t4cu4Oftp6iEK3h/6enTzktZ5bveaVH9ztXDjzn+ApxtFm4NEim3eT2g0t9V/Jc0druomI1K+i24svvsgtt9zC1KlTAZg5cybz5s3jvffe48EHH6zwHLfbzbXXXssTTzzBsmXLSE9PP+5tFBQUUFBQUPp9ZmZmteWXuic5q4APjqzj9veJPfD3qVd/JaQGPHx+LxbuTCI1p5BnF0TywhX9MfTpvoiI1BOZ+UX8uOUQB9Ny2Lnsa8JJ5hlHJOO8NtDEKCw7uPv50PsS6HaOdh2VaqTppSIiJepNhaGwsJD169fz0EMPlV7mcDgYP348q1atOuZ5Tz75JKGhodx8880sW7bshLczY8YMnnjiiWrJLHXf9O+3kVPopm94EOf0CrM7jtQBQU28ef7K/kx9fy3fbIjj2uHtGdy+md2xREREjimv0M3CyESiD6Xw5doYJuT9yCPen4J3BYP9WkDboXD2vyCkW61nlYbPNDS9VESkRL0puqWkpOB2uwkLK1sYCQsLIzIyssJzli9fzrvvvsumTZsqfTsPPfQQ06ZNK/0+MzOTiIiIk8osddu8LYf4aVsCXg6DGZf2VTeTlDqzeygXDWjD95vi+WDlfga1C9bzQ0RE6hTTNFm8K5mFkYnM2RjLve4Pud25gLsNT/liW98roeeF0Lq/dh2VWqSim4hIvSm6VVVWVhbXXXcdb7/9Ni1btqz0eT4+Pvj4+NRgMqkLUrMLmP79NgDuOKMzfcI1pULKmjq6I3M2xzN3czxdQppy7/iudkcSEZFGbk9iFjsOZbIiKoU10WkMPjyf67x+YSq5dPY6VHZwi64w6DoYfKOmjkrtKl3TTUU3EZF6U3Rr2bIlTqeTxMTEMpcnJibSqlWrcuP37t3L/v37ufDCC0sv83isxTy9vLzYtWsXnTt3rtnQUmc9PncHqTmFdA8L4K6zVEyR8gZEBHPXmV14bVEUL/26m6ljOhDoW9E8HRERkZqTX+Tm09UxbIlNZ86mWHoZMRw2m/Kc95uMdm0vf8KwW6FVX6vgJmIDA22kICJSot4U3VwuF4MHD2bhwoVcfPHFgFVEW7hwIXfddVe58T169GDr1q1lLnvkkUfIysrilVde0ZTRRmz+tgTmbo7H6TB47op+uLwcdkeSOurecV2ZtTqG1JxCrnt3Dd/ePkq724qISI1LzirgibnbOZSRT1RcIu7iYnoYMXzr+pQBjr3lTxh1DwycAiHdaz+syJ9oTTcRkaPqTdENYNq0adxwww0MGTKEYcOG8fLLL5OTk1O6m+n1119PeHg4M2bMwNfXlz59+pQ5Pzg4GKDc5dJ4uD0mT861PhX+69hO9GsbbG8gqdO8nA7+c0kfbvtkA5sPpvP95jguGdjW7lgiItJA5Re5+WxNDO+tiCYvLYGrnQv52nt2xa/YDSdc+LK1A6l/i9qOKnJshnYvFREpUa+KbpMnTyY5OZnp06eTkJDAgAEDmD9/funmCjExMTgc6lqSY1u2J5n4jHyC/by5d5ymlcqJTezTmr9N6M5zC3bxzE+7mNC7FX6uevWrU0RE6jC3xyQ6JZsffvmV6O1r8ODgCedyTvfZjNP4U9Gi7xXWGm1r37U627qMsyWzyPFZRTdD00tFROpX0Q3grrvuqnA6KcDixYuPe+4HH3xQ/YGk3ih2e3h2/i4ALh4Qjq+30+ZEUl/cPKYjn6+N4WBaHv9dFMXfJ/awO5KIiNRjC3cmcvOH6wDoaRzgFq953OdcDq4/DfQNtgptbQZCr0ngE2Bd3mFMreYVqZKS6aXqdBMRqX9FN5GT9cW6g+w4lElQE2/uPquL3XGkHvH1dvLPc3ty+6cb+N/ivQzp0IyzeoTZHUtEROqRLbHpbIvLZFdCJh+tiuYa52/c4fU9bY2Uik8YfS+c9Sg4tYmP1DfavVREpISKbtIoJGXm8+rCPQDcN74rLZr62JxI6puJfVpx5ZC2fLkultd/26uim4iInFBqdgGfrz3Iyr0p7I3aTQdHIk94fcATvrHlB/e5HCbOgCbNwamX6FKPaU03EZFS+hddGoV/fruVxMwCwoObcPWwdnbHkXrIMAwemNCd7zbGs/7AYdYfOMzg9s3sjiUiInXMzkOZfL8pnq1x6URF7eFy51I+9f4SfMuOMw0HRv9rYMDV0G4UaF1iaSC0e6mIyFEqukmD99W6g/y6Mwmnw+D9qUO1lpuctNAAXyYNaMPs9bFMeWc17904lJGdtWOciEhjVuT2sHBnEqk5Bfzvt710yFzDFc4ldMPBRT4rym+GAND3Soxz/gUBrWo/sEhtUdFNRERFN2nY8grdvPjLbgDuG9eVbmEBNieS+u6hc3uwam8qcel5PPzdVn65/3ScDuPEJ4qISINgmiYp2YXsTc7mn99sZV9KDgARRiLTvL7mMtfysuMdXhiGA4bfZm2A0G4k+AbaEV2kVhjaSEFEpJSKbtJgFbs93PbJeg5l5NMq0Je/nt7J7kjSALRo6sOP957GmGcWsS85hzmb47hkYFu7Y4mISA2LSsrm6w2xLN+Twta4DMBkomMtX/q8R0sjs8xYs0lzjNBe0KwDxlkPQ2Abe0KL2OHImm4GHpuDiIjYT0U3abDmbT3Ekt3J+Hg5eO2agfh4aVqpVI+gJt7cOrYTz/+8m49XHVDRTUSkAdufksNri6L4ekMsIRzGxyhminMT93t9TYs/FdsI6wPn/Buj85n2hBWpE7R7qYhICRXdpMH65PcDANx2emeGdmhucxppaK4cEsGLv+xmQ0w6W2Mz6Ns2yO5IIiJSDdbuT8PXy8nCyERe/tXa+TyYLP7h9QO3e80tf4JvEAS0gYihcN7z4KUd0qWRK9m9VDU3EREV3aRh+nT1AdbuP4yXw+Ca4dqtVKpfaKAvk/q34btN8Tzw1Wa+vmMUTX30K1VEpL7KK3Rzw3trWLM/DTA5zbGVr11fY2Iw0NhTdkOEFl0hpDt0PB0G36BCm8gfaXqpiEgpvUOUBie/yM0zP0UCcNWwCMICfW1OJA3VQ+f1ZMXeVHYlZvHod9t4afIAuyOJiEgVRCVl88rCPUQeymRPUjZO3PzN6yumOhfgZxSUHeztBxHDYcJTENrzaDePiJR1ZCMFU9NLRURUdJOG59n5u8jMLyY0wIcnJvWxO440YGGBvsycMpjLZ67k241xXDO8naYyi4jUYaZpEpeeR2JmPv/8Zhu7ErPwophzHOu40CuGsY6tDHDsLXtOWB+MC1+FtoNtSi1S35R0uqnoJiKiops0KImZ+Xy0aj8AD57bA6dDn0JLzRrcvhlXDY3gszUHeez77cy9e4yedyIidcyO+Ezmboln56FMFu9Kpim5+JPPg17zuc3rh/IndDsXLngR/EMwnN61H1ikPivtAtX0UhERFd2kQbn7s40Ue0x6tg7k0kHaUVJqxwPndOeHLYfYcSiTX3cmMqF3K7sjiYg0eqZpMm/rId5auo8tsRkAjHJs43efN2hlHC5/QreJENwOel8K7UfWclqRBuTI9FJD00tFRFR0k4YjKimLNdFpAPzrot42p5HGpEVTHyYPieCd5dH8sOWQim4iIjb6dmMsT8zdQV5uDv7k08+xl+leWznHuY62RkrZwW0GWpshDPsrBIXbE1ikwSnZvVRFNxERFd2kQTBNkxd/2Q3Amd1DGKJ1taSWTRrQhneWR/Pj1kNMHd2BQe2a2R1JRKRR2JuczS87EunXNogv1h7k+03x+FLAV64n6eeILn9CYDhMnAHhg62vtSGCSPUq/TulopuIiIpu0iDM3XKIH7cm4OUwuG98N7vjSCPUr20w5/QK4+cdidw9ayNL/36m1nYTEakh+UVutsVlsD0+k9d/iyIjK4srnEvobxziTtdW2jpS8SP/6AlNW0HHsXDWw9Csg225RRqFkumlKrqJiKjoJg3DtxtiAbjt9M70jwi2N4w0Ws9f2Z/RTy8iLj2PpbuTObNHqN2RREQajIzcIvKK3Hy17iAv/LIbBx46GfH8w2sul/kuK3+CVxNo0QXOegS6T6z9wCKNlvWho6nppSIiKrpJ/ff7vlR+25UMwIX929icRhqzQF9vrhgcwXsronli7nZGdGpBE5fT7lgiIvVafHoe//h6C8v2WOuxOfDwgNdX3OX1fZlxJgb0vADDNxh6XABdxoNTL3VFalvJ7FJDu5eKiKjoJvXf8wt2ATChdxjdwpranEYau/vO7spP2w6xPzWXF37exSMX9LI7kohIvfT5mhie/3k3KdkFdDbimO96lU5GPC7DXXagTyD0moQx7K/Qur89YUXkKMP6wNFQo5uIiIpuUr99te4g6w4cxsth8ORFfTC0GLLYLNDXm6cu7cvU99fy/sr93Di6A22b+dkdS0SkzssvcrNqXypfrj3I9oNp9MlayghMenod4E6vOeVPaDMIRt0F3c4Fl37PitQZpS/HVXUTEVHRTeqtzPwinv4pEoB7x3UlLNDX5kQiljO7hzKqcwtW7k3lw5X7efh8dbuJiBzL3uRs/vbVZjbEpAMmQ4xdPO/9BcNcuyo+YezfYehfICCsNmOKSGWVbKRganqpiIiKblJvvfTLblJzCukU4s9tZ3S2O45IGTeP6cjKval88nsMFw0Ip094kN2RRERsZ5omRW6TFVEp7ErM4psNsRxOPEigkctIRzqfuf5Tdry3P0aTZtC8Iwy8DtoOgRb6N1+kbitpdVOnm4iIim5SL0UlZfPRqgMAPDGpN95Oh82JRMo6s3soQzs0Y+3+w/zfl5v54Z4xep6KSKPj8ZiYgMc0WbgziZd/3U1kQhYAbY1kpjh/5a8+P+D48+JPAa3hnH9j9L289kOLyKkxVHQTESmhopvUS68t2oPbYzK+ZxindQ2xO45IOQ6HwVvXDeGsFxazKzGLj1cd4KYxHe2OJSJSazLyirj49RWkZhdQ5DZxF+VTiBc3O3/kQa/P8f7zhggAQRFwzZcQpmn5IvWVcWR6qWpuIiIqukk9tDc5m7mb4wG4b3xXm9OIHFszfxcPTOjOw99u4+1l+7h+ZHu81O0mIg1YdkExr/y6m/dX7KfYYwImU5y/cr5jNYN9dpXfebRFVxh2C/S9AjLjILQXOJy2ZBeR6mIc+a/WdBMRUdFN6pVit4fH52zHY8L4nmFaJ0vqvMsGteXFn3dzKCOfn3ckcl7f1nZHEhGpFqZpEp+RT1Gxh2V7kvn49wNEJWXjMcGBh6HGbu72+paxzq3lTw5oDec+A70uOnqZX/PaCy8iNcdxZHqpqVY3EREV3aRe+WHLIZbtScHbaXD/2epyk7rP19vJNcPb8dqiKN5fEa2im4g0GB+s3M8Tc3eUfj/I2M2nXl8y0rmDQtNZtqvNFWBthtDpDPAPgRF3gFMvQ0UaIoMju5dqfqmIiIpuUr/MOTKt9JbTOtG7jbrcpH6YMqI9byzey9r9h/l1RyLje4XZHUlE5JRsPpjOE3N34MDDKMd2Hvb6lJ6OmNLjLsMNDm/oNgHOflI7joo0JkbJ/1R0ExFR0U3qjTXRaSyKTMIw4NJB4XbHEam0sEBfpoxozwcr9/PkDzs4q0cojpKpFyIi9Yxpmjz77UpucC7geufPdHYcKjugZXcYNx06nQ4+AfaEFBH7GEfWZdT0UhERFd2kfihye7j/i00AXD6oLV1C9SJe6pe/T+zO1xtiiUnL5ZWFe7j/7G52RxIRqTyPG9a9BzvnkONx8V7qEny8i8qOGXITnPssOL3tySgidYJhlHywqKKbiIiKblIvzN+WQFx6Hi2bunh8Um+744hUmZ/LiwfO6c5jc7Yzc8lebhjVgeb+LrtjiYgcn7sY9i+Djy8uvagpgAEpzlBaDr0CTvs/8G4CLj+7UopIXVI6vVS7l4qIqOgmdV5aTiHPzI8E4Nrh7fH30dNW6qfrR7bny3UH2R6fyedrY7jjjC52RxIRKS/qV1j7LqTsgdQ95Q6vMAbyecFohp57Pdef1t2GgCJSt2l6qYhICVUvpM575dfdxB7OI8DXiykj2tsdR+SkGYbB1NEdeeCrzXy86gB/Pa0TXk6H3bFEpLErzIUtX8DBNbB7PuSllR/TZhAMu4UtmU259kcHIQG+PDdCHxyISAWOTC/V6rUiIiq6SR2XX+Qu3bH0mcv6ERLgY3MikVNzQb/WzPhxJ4cy8pm/PYEL+rWxO5KINFZZiXB4P3w0CYrzyx/vewWkRUPvi2HEHeBwsujX3cAeRnduga+3s5YDi0h9ULKmm2FqeqmIiIpuUqd9ue4gh3OLaNusCef0CrM7jsgp8/V2MmVEe15ZuIcXft7NmC4tCfbT2m4iUosObbY2RVj/QfljI++CtkOg9yXlDuUXufl2YxwAg9o3q+GQIlJvaSMFEZFSKrpJnVXk9vDmkn0A3DpW0/Ck4bhxVAc+XX2A6JQcXlsUxaMX9LI7kog0ZKYJu36C6CWQsBUOrCh7vN0o6HIW9JsMwe2OeTVzN8dzIDWX0AAfLhoQXsOhRaS+Mgy9ZhcRKXHSRbfCwkKio6Pp3LkzXl6q3Un1m7s5vnTH0iuGRNgdR6TaNPN3MePSftzy0Tq+XHeQW8d2IjTQ1+5YItLQFObA8pdg6XPlj7XuD93OhU5nQLsRf+hMObZPV8cAMHV0R4KaeFdzWBFpMErXdNP0UhGRKlfLcnNzufvuu/nwww8B2L17N506deLuu+8mPDycBx98sNpDSuNT7Pbw30VRgPXiXuvGSENzVo9Q+oQHsi0uk7eX7ePh89XtJiLVYPcC+PEBSI+p+PigG6DXJOg8rlKFthLb4jLYdDAdb6fBFUPaVlNYEWmYStZ00/RSEZEq9/4+9NBDbN68mcWLF+Pre7QzY/z48XzxxRfVGk4ar+83xbMvJYdmft7cMKqD3XFEqp3TYXDXmV0BmLflEG6PXpiKyCk4tBkeD4JZV5YvuIX2gr8ugcczYNKr0GV8lQpuALPWWNc5sU9rWjbVpkYichyOkreYem0jIlLlTrfvvvuOL774ghEjRpTuTAPQu3dv9u7dW63hpHHKKShmxk+RAPx1bGea+mj6sjRMZ3QPIaiJN/EZ+Xy7MY7LB6t7REQqIT8DshIgaiEkbYfNX4CnqOwYvxZw3XfQqm+VC2x/ll1QzPdHNlC4dvix13wTEYE/7F6qopuISNWLbsnJyYSGhpa7PCcnp0wRTuRk/W32ZlKyC/D1dnDNML24l4bL19vJ7Wd05umfInln2T4uGxSu36MicmwJ2+C3p2DXvGOPGTMNRt8LvkGnXGwr8d3GOHIK3XQO8Wd4x+bVcp0i0pAd+d2j6aUiIlUvug0ZMoR58+Zx9913A0c/yXjnnXcYOXJk9aaTRie7oJhfdyYBMP2C3gT5aaFmadiuHtqOV37dQ2RCFt9siOMydbuJyB/Froe0vbDrR9j+bfnjA68DLx9rymjH08HlV603b5pm6QYK1w5vrw8GROTEjuxeqk43EZGTKLo99dRTnHvuuezYsYPi4mJeeeUVduzYwcqVK1myZElNZJRG5KNV+yks9tApxJ+rh2nHUmn4gvy8ueusLjy3YBf/WxzFpep2E2ncTBO2fgVr3obkSCjILHu8w2kw/DYozre+Dgir0TgbD6az81AmPl4OLhukDwVE5MQ0vVRE5Kgqb6QwZswYNm3aRHFxMX379uXnn38mNDSUVatWMXjw4JrIKI2Ex2Py8aoDANx5RhcVHqTRuH5ke/xdTvYm5/DJ6mPsOCgiDZfHY63P9stj8EQwfHMLxK45WnALDIewPnDhq3DDXOh5AfS9vMYLbgCf/m79TrqgXxt1n4tIpRx9Da+im4jISa1Q37lzZ95+++3qziKN3C87EzmUkU9THy/O79fa7jgitSbA15tp53TnXz/s4D/zdjCyUwu6hDa1O5aI1LTcNFj1Omz/BtL2lT/uGwRnPwmDb6z1aGBtbDRvazwA12gDBRGpLE0vFREpVamiW2Zm5okHHREYGHjSYaTxKih289j32wG4ckgEvt5OmxOJ1K6pozqweFcSy/ak8J95O3h/6jC7I4lITSjKt6aPHlgJ+36DrEPlxwy/Hc75Nzjt3b37lx2J5Bd56NjSn0Htgm3NIiL1R2mnmzZSEBGpXNEtODi40lP93G73KQWSxumJuTtIyMwnLNCHv0/sbncckVrncBg8ekEvznlpKUv3pJBTUIy/j71vuEWkGqXuhTl3w4EV5Y81aQ5XzYL2dWtDqjmbrS63C/u30ZIPIlJ56nQTESlVqXd0v/32W+nX+/fv58EHH+TGG28s3a101apVfPjhh8yYMaNmUkqDFp+ex+drrDVjnpjUW11u0mh1DW1KmyBf4jPy+dvszfzvWq2TKVKvZSVA5DyIXQubPyt/vPM4OOsRaD0AHFVeZrdGRSVls2R3MgCT+mvJBxGpCm2kICJSolJFt9NPP7306yeffJIXX3yRq6++uvSySZMm0bdvX9566y1uuOGG6k8pDdrs9bF4TBjRqTkT++iFvTRehmEw/cJe3PbJBn7cmsC+5Gw6hWhtN5F6w+OBnd9bU6r2/AKbZ1U87sZ50GFM7WaroplL9uL2mIzvGUaX0AC744hIPWI41OkmIlKiynOXVq1axcyZM8tdPmTIEP7yl79USyhpPPKL3Hyx9iAAk4dG2JxGxH4T+7RmXI9QFkYm8f6K/fzr4j52RxKRE8lOhl8erbibLbgdtBkEfs1h6C0Q1qv281XR4ZxC5h6ZWnrHmZ1tTiMi9U3JdHRDa7qJiFDluQwREREV7lz6zjvvEBGhoolUzZtL9hGXnkerQF/OVZebCAA3j+kIWF2gGblFNqcRkWPaOhteHwEvdCtfcGs9AK74AO7bCld+CBe8VC8KbmD97iko9tC7TSADI4LtjiMi9U7JGpAquomIVLnT7aWXXuKyyy7jp59+Yvjw4QCsWbOGPXv28PXXX1d7QGm40nMLeWNJFACPXNBTa7mJHDGycwt6tAogMiGLz9bGcNvp6jQRsV3iDghsA7HrYPlL1s6i+xYfPW44IKwPnPusNa5Ze9uingqPx+ST1QcAmDKivTZQEJEq0/RSEZGjqlx0O++889i9ezdvvPEGkZGRAFx44YXcdttt6nSTKnl2wS7yizz0bB3I+X3V5SZSwjAMbh7Tkb/N3sL7K6K5YWQHmrhUlBaxzYpXremjFfFrYe082m5E7WaqIcujUjiQmkuAjxcXDWhjdxwRqY8MbaQgIlKiykU3sKaYPvXUU9WdRRqR/Sk5zFpt7Vh677iu+iRd5E8mDWjDy7/uIS49j/dWRHPnmV3sjiTSOJim9WfbbNj6FcSshoKMsmP8Q2H4X6FVf+h6dukbzIbg49+tLrfLBrfFz3VSLxNFpJEzDHW6iYiUqPKrqaVLlx73+NixY086TGW8/vrrPPfccyQkJNC/f39ee+01hg0bVuHYt99+m48++oht27YBMHjwYJ566qljjpfa88uORKBkx9JWNqcRqXt8vJz8bUJ37vtiEzMX7+XGUR3w99EbYJEatXU2fH1zBQcMOP0fEDEUYtfDsFusjREamLj0PBbutP59njKifk6PFRH7OY5ML0UbKYiIVL3odsYZZ5S77I9dSm63+5QCHc8XX3zBtGnTmDlzJsOHD+fll19mwoQJ7Nq1i9DQ0HLjFy9ezNVXX82oUaPw9fXlmWee4ZxzzmH79u2Eh4fXWE45voJiN+8ujwbQtFKR45jUvw2vLNxDdEoOs9fHcsOoDnZHEmlY4jdB7FrYvwyiFkJh9tFjDm8Yfit4+UKP8yB8sHV5l/G2RK0Nn6+JwWPCyE4t6BLa1O44IlJPGZpeKiJSqspFt8OHD5f5vqioiI0bN/Loo4/yn//8p9qCVeTFF1/klltuYerUqQDMnDmTefPm8d577/Hggw+WG//pp5+W+f6dd97h66+/ZuHChVx//fU1mlWObc6meBIy8wkL9OGKIVoHUORYHA6DqaM7MP377by2KIrJQyO04YjIqcpNg+glsP072PFdxWPOeAj6XAYtu9ZmMtvN23oIgKuG6d9mETl5hsN6rWLgsTmJiIj9qlx0CwoKKnfZ2WefjcvlYtq0aaxfv75agv1ZYWEh69ev56GHHiq9zOFwMH78eFatWlWp68jNzaWoqIjmzY89JaSgoICCgoLS7zMzM08+tJSTlJXPE3N3AHDpoLYqIIicwFVD2zFz8V7iM/L5YcshLh/c1u5IIvWPxw2RP8Cif0PKHvhj90XTMKuLrfclENwOIoY3qDXaKmvl3hT2Jefg5TA4q0f52QMiIpVVsnupQ9NLRURObiOFioSFhbFr167qurpyUlJScLvdhIWFlbvdkl1UT+Qf//gHbdq0Yfz4Y08NmTFjBk888cQpZZVjm78tgeyCYkIDfLj9jM52xxGp81xeDqaMbM+z83fx0i+7Oa9vKy1uLlIZHg+sfAU2fAyZ8VCcd/RYQBtoPxLaj4bBU6Fk/aFG7OVf9gDWtPYAX2+b04hIfWYYJZ1uKrqJiFT5nduWLVvKfG+aJocOHeLpp59mwIAB1ZWr2j399NN8/vnnLF68GF9f32OOe+ihh5g2bVrp95mZmUREaJpFdUjLKeTVhdaL+htHdyBQL+pFKmXqqI58+nsMcel5zFyyj2lnd7M7kkjd5C4G0w27foL5D0FWfNnjhhPuWgst9KHPH+UUFLMhxlo+5L7x+v0iIqempNNN00tFRE6i6DZgwAAMw8D8U7vwiBEjeO+996ot2J+1bNkSp9NJYmJimcsTExNp1er4u18+//zzPP300/z666/069fvuGN9fHzw8fE55bxS3hdrD5KSXUhE8yZcM6yd3XFE6o0mLicPn9+TOz7dwPsrorl1bCftZCpSImGrtdnBli9hzZuQn1F+zPDboevZENIDgrSR0p+t3JtKscckPLgJ7Vr42R1HROq5kt1LHep0ExGpetEtOjq6zPcOh4OQkJDjdo9VB5fLxeDBg1m4cCEXX3wxAB6Ph4ULF3LXXXcd87xnn32W//znPyxYsIAhQ4bUaEY5No/H5Iu1MQDcfVZXgv1cNicSqV8m9m5F+xZ+HEjN5dediVw0QIUDEWLXwTvjKj7Wshtc+ja06gsOrR96PF+tOwjAuX2O/yGmiEhlGA7rLaZDnW4iIlUvui1ZsoTJkyeX6wYrLCzk888/r9FdQadNm8YNN9zAkCFDGDZsGC+//DI5OTmlu5lef/31hIeHM2PGDACeeeYZpk+fzqxZs+jQoQMJCQkANG3alKZNm9ZYTinv932p7E/NJcDHiwv6tbY7jki943AYXNCvNa//tpdn5+/irB6hWndJGq9d8+HL68BdePQypwsGXmd1vbUfZXW2ealz/US2xWXw845EDAOuHKrlNETk1Gl6qYjIUVUuuk2dOpWJEycSGlp2Z6usrCymTp1ao0W3yZMnk5yczPTp00lISGDAgAHMnz+/dHOFmJiY0nZmgDfeeIPCwkIuv/zyMtfz2GOP8fjjj9dYTikrNbuAuz7bCMBFA9toEXiRk3TDqA58uS6WuPQ85myO59rh7e2OJFLzivKtddp+fRwifwSfAEiOpMwOpINvhHP+bR2TKvlg5X4ALuzXhm5huv9E5NQZml4qIlKqytUP0zQxDKPc5bGxsQQFBVVLqOO56667jjmddPHixWW+379/f43nkRObszmetByrG+GGkR3sDSNSj4UG+HLLaR156sdIPl51gKuHtsPhKP/7WKTey02Dfb/Bgoch61DFYwJaQ6+L4YwHoUlwbaZrMNwekwXbrVkA141UEV9Eqkfp7qWmOt1ERCpddBs4cCCGYWAYBuPGjcPL6+ipbreb6OhoJk6cWCMhpX5bE50GwF/GdKSrPkUXOSVXDong1YVRRCZksWB7Auf21XRtaSA8Hsg4CFu/hEX/Pva4ITdD/6shYmjtZWug1u1PIyu/mAAfLwZGBNsdR0QaiJJON6eml4qIVL7oVrJ5waZNm5gwYUKZNdFcLhcdOnTgsssuq/aAUr/tiM/k153WjrMTtUCzyCkL9nNx05iOvLpwD68s3MPEPq0q7D4WqTcObYH4jbD8RTi8v+Ix4x6DzmdCaG/w0kY81cE0TR6bsx2AMV1b4uV0nOAMEZHKcRzZvMbQ9FIRkcoX3R577DEAOnTowOTJk2t8t1JpGP7z4w6K3CZn9QhlcPtmdscRaRBuHt2Rd5ftIzIhi6V7Uji9W4jdkUQqz10MK16GhK2w47uKx7iaQmG2tU7byLtAheVqt+NQJpEJWbicDh4+v6fdcUSkATGcVtFNa7qJiJzEmm433HBDTeSQBmhfcjYrolJxOgz+dXEfdeOIVJMgP28uH9yWD1cdYPb6WBXdpH4oyofVM+HXxyo+3nYY9LkUBl0PLv/azdYIfb7mIABn9QilbTM/m9OISEPiMLR7qYhIiUoV3Zo3b87u3btp2bIlzZo1O27xJC0trdrCSf02a3UMAKd1bUl4cBOb04g0LFcMieDDVQf4cesh7h/flU4hTU98kkhty0mB2LWw5Flrvbac5D8NMKDXJGv6aIvOtkRsjPIK3Xy13iq63TCqg71hRKTB0ZpuIiJHVaro9tJLLxEQEFD6tTqW5ERiUnP5ZPUBQC/oRWpCn/AgzuoRyqLIJF78ZTf/vWaQ3ZFEIDMets6G/cthz4KKx/gGweAbYezfwEeb69hhye4k8os8hAc3YUSn5nbHEZEGxtCabiIipSpVdPvjlNIbb7yxprJIA/L8z7vIL/IwolNzztDUN5Ea8bcJ3fltVxI/bDnEbadn0Cc8yO5I0liZJkQthFlXgFlBZ0NAG5g4A7qeramjNit2e3jqx0gAJvTWRiwiUv1KNlJwYGKapn7PiEijVqmiW2ZmZqWvMDAw8KTDSMOw+WA6P2yJB+CR83vpH1qRGtKzdSCT+rfh+03xPLdgFx/eNMzuSNJYFOVD3HrY/RPs+glSoyoeN/w2GHEHBLfTZgh1xIaYdGLScgnw9eLecV3tjiMiDVDJ9FIHHkxTv/5FpHGrVNEtODj4hIWTkk8x3G53tQST+uutZfvwmDCpfxt13ojUsGlnd2Pu5niW7E7mQGoO7Vuoi0hqkMdj7Ty67EUozCp7zHBA70ug/WjoNxl8tM5gXTTryNIP43qEEuTnbXMaEWmInEc63ZyGSZFp4kBVNxFpvCpVdPvtt99qOoc0EAXFbpbushbKvnF0B3vDiDQC7Vv4M7pLS5btSeHDlQeYfmEvuyNJQ1NcaE0Z3f0TrHsfopdUPG7SazBwSu1mkyqJT8/ju01WJ/r1Wm9VRGqI4XSWfu3xuMHpsDGNiIi9KlV0O/3002s6hzQQ326II6ugmFaBvgxoG2x3HJFG4eYxHVm2J4X3V0YzpmsLzuoRZnckqe8Kc2Djp9YU0i2flz3mdMH4J6DDaIheBv2vBv8W9uSUKlm5NxWAARHBDGrXzOY0ItJQlWykAGB6tIOpiDRulSq6/dnhw4d599132blzJwC9evVi6tSpNG+uHbAas8z8Ip5dsAuAv5zWEYdDreQiteH0biFc2L8NczfH8+nvMSq6ycnLiIXv74R9iys+Hj4YLn0bWnS2vm/dv9aiyanxeEw+XxMDwMjOKpKKSM1xOI52tnk8WnpIRBq3Khfdli5dyoUXXkhQUBBDhgwB4NVXX+XJJ59k7ty5jB07ttpDSv3w/aZ40nIK6dTSn+tHdrA7jkijYRgGt47txNzN8azcm0pmfhGBvlqrSSoh/SD88ihs//bYY4bfDuGDwNsPepyvFbHrqYWRSaw7cBg/l5NrhrWzO46INGBli27qdBORxq3KRbc777yTyZMn88Ybb+A8Ml/f7XZzxx13cOedd7J169ZqDyn1Q8kn6NeOaI/LS2s3iNSmXq0D6dTSn30pObz66x4euUBru8kxJO4AdyEsngG75x97XM9JVlebt2/tZZMa89mRf6OvH9mBiOZ+NqcRkYbsj9NLPe5iG5OIiNivykW3qKgoZs+eXVpwA3A6nUybNo2PPvqoWsNJ/fHW0r1sj8/E5XRwycBwu+OINDoOh8GjF/Ri6gdr+WxNDPeM76puNykrdS9s+xp++8+xx4y+F8Y9Bn94wyT1X0Gxm1VH1nO7aEAbm9OISEPn/OOabm51uolI41blotugQYPYuXMn3bt3L3P5zp076d9fa7s0Vh+uPADAlBHtae7vsjmNSON0RvcQuoY2ZU9SNp+vieGvYzvbHUns5PFAzCrwawGHNsO3f6143Ig7YOzfwE/rsjZU87YcIq/ITWiADz1aBdgdR0QaOMcfO91MFd1EpHGrctHtnnvu4d577yUqKooRI0YA8Pvvv/P666/z9NNPs2XLltKx/fr1q76kUmdFJWUTl56Hw4Bp53SzO45Io2UYBn85rSP/+Horry6M4pKBbQkJ8LE7ltQm04S0feDytzZEiPq1/JhmHWHCf6AgG7qdA020i2VDVuz28MrCPQBMHd0RQ2vyiUgNM7SRgohIqSoX3a6++moA/v73v1d4zDAMTNPEMAzcbv2SbQyemLsdgIHtmtHU56Q2xBWRanL54Ag+XR3DltgM3lsRzT8m9rA7ktQ004RdP8K8ByAr/tjjht8OZz4EvkG1l01st2xPCgdSc2nu7+L6ke3tjiMijYDhOPp+QGu6iUhjV+UKSXR0dE3kkHoqJjWXZXtSMAz410V97I4j0ug5HQa3n96Z2z/dwJxN8fx9Qnd1tjRUHjfsXwafXAaeCt7UtB0KE2ZYRTYvFzTrUOsRxX5LdicDMLFPK/z1wZiI1IY/vO4wNb1URBq5Kr/6at9en5LKUe+tsIqwY7q0pFebQJvTiAjAGd1D8fFyEJeex9I9KZzeLcTuSFJdCrJg9wLY8iXsWXDscTfOgw5jai+X1En5RW7mbT0EwNiu+j0gIrXEMPCYBg7DxPSo6CYijdtJfeQZHx/P8uXLSUpKwvOnX6T33HNPtQSTum/d/jQ+WrUfgFtO62RvGBEp1cTl5NJBbflsTQxPzNnOwv87Xd1uDUF6DHw4CQ4fo+P87Ceh+/kQ1Ba8fWs3m9RJs9fHkpxVQJsgX87qEWp3HBFpRDwYODDLvVcUEWlsqlx0++CDD7j11ltxuVy0aNGizBs5wzBUdGtEXlm4B48JlwwM57SuLe2OIyJ/8M/zejBnUxz7UnJYvCuZM/WGu/7xeGDlq7DxY8hLh9wU63LfYKuwlrYPJr0GPc4Hpw/8YeFqkWK3hzeX7gXglrGdcHnp+SEitceDA/Bgao1vEWnkqlx0e/TRR5k+fToPPfQQDr3Ab7RSsgtYHmW9AZx2djd10YjUMQG+3lwzvB1vL4vmpV93q+hWnyRsgwX/hOgl5Y+1GQiXvw/NO9Z+LqlXft2ZxMG0PJr7u7hqaDu744hII+PBem+g3UtFpLGrctEtNzeXq666SgW3Ru6XHYmYJvQJDySiuZ/dcUSkAred3pkPVu5nS2wGW2Mz6NtWu1bWWaYJq9+EJU9D3uGyx1oPgDMftham7nCapo5KpfwWmQTAxQPCaeJy2pxGRBobq9NNGymIiFS5cnbzzTfz1Vdf1UQWqSdM0+SjVQcAOL9vG5vTiMixtGjqwzm9WgHwyPfbbE4jZZgmxK6HFa/Av0LgiWCY/48jBbcjncOhveG25XDrEuh2DnQ9WwU3qZT03EJ+3pEAwNhuWv5BRGqfaajTTUQETqLTbcaMGVxwwQXMnz+fvn374u3tXeb4iy++WG3hpG5aEZXKzkOZNPF2cvWwCLvjiMhxPHx+T37cdojNB9NJysonNEBFG9sU5UN2Aiz6N2yt4MMrhzec9QgMvRl8Amo/nzQY763Yz+HcIjqH+DOqs4puIlL7SjrdUNFNRBq5kyq6LViwgO7duwOU20hBGrZit4d/fL0FgCuGtCXYz2VzIhE5njbBTejZKpAdhzL5eNUB/u+c7nZHanwKc6xC25q3wVNU9lhYX/BywbBbrU42v+b2ZJQGw+0x+WrdQQDuHd9NGyiIiC1Kim7avVREGrsqF91eeOEF3nvvPW688cYaiCN13aaD6cSl5xHg68UDE/TmXaQ+mDw0gsfmbGfmkr1MHd2R5v4qltco07Q62dL2QfIuiJwH7oKyY5p3gkvfhrZD7MkoDdayPckcysgnqIk35/QKszuOiDRS5pGlEkx1uolII1flopuPjw+jR4+uiSxSD3y+1vr0/PRuIQT6ep9gtIjUBTeM6sDnaw+y81AmX6+P5ZaxneyO1DBlxEHMKtjyBez5uewxb38YehP0ugTaDACHFraXmvHp6hgALhkYjq+3nmciYo+ju5eq001EGrcqF93uvfdeXnvtNV599dWayCN12N7kbGavjwXgqqHtbE4jIlVxw8j2PPjNVv63OIrrR7XHx0tvxk+Zu8j6s/0bmP9PKMgoe7xVX+hxIRTnw8Ap0KKzPTml0YhPz2PhzkQApozQv9MiYp/S3UtVdBORRq7KRbc1a9awaNEifvjhB3r37l1uI4Vvvvmm2sJJ3fL+imgAxnYLYUxXLcwsUp9cPrgtL/6ym6SsApbtTmG8pp2dvOhl8OEFxz4+7FZrM4QQTcGX2vXJ7wfwmDCyUwu6hGozDhGxj1ladCu2OYmIiL2qXHQLDg7m0ksvrYksUodFJWXxye/WlJWrhmrHUpH6xsvp4Ly+rflg5X6e+nEnY7uFaIH1qvB4YN8i2Px5xTuPAjTrCNd9Y63XJlLLcguL+fj3AwDcOLqDvWFEpNErmV5qmqbNSURE7FXlotv7779fEzmkjlsUmQTAiE7NOa9va5vTiMjJuPusLszdHM++lBwWbE/gwv5t7I5Ud5kmmB74+VH4/XVwNYXC7PLjznrUKrKF9YGQbrWfU+SIX3cmkZVfTLvmfpzdU52sImIv03CAqY0URESqXHSTxicjr4h3lllTS8/u1crmNCJyslo09eHaEe15deEe/rsoivP7tsbhMOyOVbcU5UFqFHx0EeSmHr38jwW3jqfDBS9ZnW0OdQtK3TBnUzwAk/q30d9rEbFd6ZpupopuItK4nVTRbfbs2Xz55ZfExMRQWFhY5tiGDRuqJZjUHV+vjyUpq4D2LfyYrKmlIvXazaM78t7yaHYlZrElLoMBEcF2R6obshJgzj2wZ0HFx10B0P1c6Hkh9JpUu9lETmBfcjaLd1kd6ZMGqINVROxnlkwvdWsjBRFp3Kr8Ef2rr77K1KlTCQsLY+PGjQwbNowWLVqwb98+zj333JrIKDYyTZPP11pruf1lTEea+qg5UqQ+C/LzZmTnFgCsiEqxOY2NTBOiFsKCh+HlvvBC9/IFN58guH0l3PQzTNsBl72tgpvUSS/+sptij8nwjs3pFqYNFETEfkc3UlCnm4g0blWuoPzvf//jrbfe4uqrr+aDDz7g73//O506dWL69OmkpaXVREax0YaYw+xOzMbX28FFA8PtjiMi1WBs15b8siORt5bu4/LBbQkL9LU7Uu3JTYP5D8KWL4495p6N0LQVuPxqL5fISfJ4zNIC+v+dox1zRaRu8BiGtaabqU43EWncqtzpFhMTw6hRowBo0qQJWVlZAFx33XV89tln1ZtObPfpkR1LL+jXhkBfb5vTiEh1uGJIBH3Dg8jIK+KpH3faHadmeTyQnQTLX4LZN8OzHcsX3Fp0heu+gynfwGPp1sYIKrhJPfHNxjgO5xbh53IysF2w3XFERIA/drqp6CYijVuVO91atWpFWloa7du3p127dvz+++/079+f6OhobQndwOxNzub7zdbCzFNGtLc5jYhUF19vJzMu7cuF/13O95vi+cuYTvRtG2R3rOrlLoLkXfDDfRC7tuIx578Ag6eCw1mr0USqi2mavLZoD2AtAeHt1MYeIlI3HN1IQUU3EWncqlx0O+uss5gzZw4DBw5k6tSp3H///cyePZt169Zx6aWX1kRGsclbS/bh9piM6xGqxdZFGpg+4UFc0K8NczfH8+W6g/W/6GaaVkfb3oWw9l1I2QMFGUePB7aFfldC0zDoerbVzWZoh0ep337fl8aB1Fz8XE5uPb2z3XFEREqZJf/Gak03EWnkqlx0e+utt/AcaRO+8847adGiBStXrmTSpEnceuut1R5Q7LF0dzJfrDsIwM1jOtqcRkRqwlVDI5i7OZ7P1sQwdXQHOoU0tTvSydn7G/z4N0jdU/ZyhzeE9Yb+V8PwW1VkkwbnvRXRAFwyMBx/bXQkInWIqU43ERHgJIpuDocDh+Po9IWrrrqKq666qlpDif1mrbbWcrtkYDijurS0OY2I1IRRnVswqnMLVu5NZf72BO44o4vdkSrn0BbIT4eErRC7DrZ/U/Z457PgtAcgfBB4N7ElokhNK3J7SjdQuGZ4O5vTiIiUZWJ90KXdS0WksdPHolLOrzsSmb89AYAbRnWwN4yI1BjDMJjYpxUr96Yy58jabi6vOrwm1PZv4asbKz7W6Qy44CVIj4F2o8DLVZvJRGrdO8uiyS1008zPm56tAu2OIyJShsew1kvVRgoi0tip6CblvLl0LwBXD4vQWm4iDdyE3q14dv4uIhOy+HHrIS4eGG53pLIKc2HNW/DrY+WPtegCbYdCy64w8i7w8rHWahNp4EzT5J1l+wC4fHBbHA5NnRaRuuZIp5upTjcRadxUdJMylu1JZu3+w3g7De4b383uOCJSw8ICfbl2eDveXLqPp37cyYX92+C08w28aVrTRbd/CzvnVjzm8vehjzbukcZr4c4kUnMK8XYaPDChu91xRETKMY0jnfPqdBORRk5FNynj41UHALh2eHvCAn1tTiMitWF0l5a8uXQfSVkFfLsxjssHt639EHnpsOp12PUTJG6teMxp/wdnPaoNEaRRM02TR7/fBsDg9s3w8XLanEhEpLzSNd20kYKINHInVXQrLi5m8eLF7N27l2uuuYaAgADi4+MJDAykadN6uvudcCgjj0WRSQBcPUyLMos0FqO7tMTf5SSn0M23G2Nrr+iWvAsW/avijrb+V4PpAd9gGHGbpo2KHBGVlM2hjHwAHjm/l81pREQqVrKmGyq6iUgjV+Wi24EDB5g4cSIxMTEUFBRw9tlnExAQwDPPPENBQQEzZ86siZxSCz75/QDFHpPhHZvTvVWA3XFEpJY4HQZvXjeEKe+uZkVUKj9tPcS5fVvXzI2ZJnjc8M0t5XcdLXHjPOgwpmZuX6Se++hIR/ppXVvSJzzI5jQiIhUr6XTzuLWmm4g0blUuut17770MGTKEzZs306JFi9LLL7nkEm655ZZqDSe1a8H2RACuGa4uN5HGZkiHZqVff78pvnqLbh43LHwSVrx87DHhQ6DDaBhwLYRojSqRiqRmF/DZmhgAbh3b2eY0IiLHUbKmmzrdRKSRq3LRbdmyZaxcuRKXy1Xm8g4dOhAXF1dtwaR2fbsxlqikbLydBmd0C7U7jojUMl9vJ9/eMYpL/reSxbuTOJiWS0Rzv1O70qwEa+fRg2tg/7KKx0yYYXW1teqrtdpETuCT32Mo9pj0axvEmK4t7Y4jInJMJZ1uKrqJSGNX5aKbx+PBXUGbcGxsLAEBmpJYX725ZB8At5/emSA/b5vTiIgd+rcNpm94EFvjMnh3eTSPT+p9cle0/Tv4/Q04+HvFxyNGwKi7ocf5KrSJVFJOQTFvLIkC4OYxHW1OIyJyAg7rbWZeQZHNQURE7FXlots555zDyy+/zFtvvQWAYRhkZ2fz2GOPcd5551V7QKl5C3cmEpmQhcvp4OYxWqxcpLFyOAxuP6Mzd3y6gQ9W7ufOM7sQEuBz4hMTt8PS5wADCjIh6teyx9sMglF3QZ/LaiS3SGOwZHcy+UUe2jX3Y1L/NnbHERE5Lh//QMiDlMRYu6OIiNiqykW3F154gQkTJtCrVy/y8/O55ppr2LNnDy1btuSzzz6riYxSw95canW53TCqvbrcRBq5EZ2OrtX52qI9PHlRn4oH5qRCciSsfA12/1T++NC/QNcJ1vpszdrXUFqRxqHY7eGZ+ZEAnNMrDEMdoiJSx/lEDIKUhTRN3YJpmvq9JSKNVpWLbm3btmXz5s18/vnnbNmyhezsbG6++WauvfZamjRpUhMZpQZFJWWxdn8aANeP7GBvGBGxXXN/F5P6t2HO5ng2xBwu/0LZXQTzH4S175Q/uWkrGH0vhA+CdiNqL7RIA7clLoMDqbk09fHirrO62B1HROSEWvUaDRufo5dnN9EpOXQKaWp3JBERW1S56Jafn4+vry9TpkypiTxSw9wek/8uimLO5jia+7tYu/8wAEPaNzv1RdPrioIscDUtu1aUuwhi10LEcHA4ay9LcQG4C8HnGOsd5qZBk2antq5Vfib4Bp78+Q1RdjIcWG7tmtnnsppfN8zjhsJs8A2q+FhxAbiO/P0yTWsKZkVj/6ggC7z9avf5esS0s7sxZ3M82+IyeWdZNLf0LIKts2HXj1CUC2n7jg72D4XuE2HwjRA+uNazijQGK6NSABjdpQXBfq4TjBYRsZ8rYjAeDNoaKby5Ziu3nj/S7kiN0uGcQoL9vG3tNCxye9gSm86gds0A2HQwnR6tAmniOrnXuKnZBbRoWonlT05SXqEbL6dBkduDj5cTp+PofVfk9pBb6CaoyfFnh2XkFRHg44XjyLm5hcW4nA68nI5yY+PT81gRlcKkAW3w8Sp7n+QUFFPk9hDg643TYRCVlI2fy0mb4CbEp+eRU1CMr7eTrPxierWx3g9mFxSTlV/Eb5HJXNi/NQG+R7NmFxTj9pg08Xbi8nKQU1AMgL+PFynZBaRkF9CjlXU9xW4PkQlZ9GodiMNhcCgjj0e/2871I9szvFNzMvOKyy1DU+z2UFDswd/HC4/HJCOviGb+1usWj8csvT8amyoX3UJDQ7nkkkuYMmUK48aNw+Eo/8SpSa+//jrPPfccCQkJ9O/fn9dee41hw4Ydc/xXX33Fo48+yv79++natSvPPPNMo1577j9ztxC69jlmOHaTmh7IxV6BnOncSEuzLXzU3Hqj32U85KZaXSvFedbOg4ZhrcsUv/HolUUvgaZhcObDEPkDJGyFojyrUFCUa41pMxC6ng2HD4B/SwiKsMbmZ0B6DLTsCt3Ptc45sAIC21pv6Pcvh7BekBYNTUOhRWfweCA1Cg5HQ+v+4CmGfYuP5ul/DSRssdaXCusNoT3h8H6rqLXn57J3RPPO0Ol0yEmBnXOh7xXWz5h1COI3WfdDj/Ot3Rfj1kGzjlb3TmoUtB0Kh7ZAfjoEtIbsRGux2I5jIXadlTU9xiqoZcZbRbc+l1qFv8x4cHpZ92XidtizAFp2t66zKNf62QwnBLezHoM+l0KrfrDvN1j1P2sHqOB2kLIb+k2GpB3W49OsA7TqY92PiTusDLt+tAo7eelW4SawDfi1tP6fGW/dZq+LrGLQ6pnWONNj3W/NO0HCNlj9BrQdZn2/cy60HQIBrayf17uJVUAKOvKYJe+y8vuHQnG+dT93Pdt63LudC0k7YcnTENweIoZZxUJM6/FN3Qv+IZB32Lrugkzrftv+rTW+eUfr/us20brcXQQBYRD5o3W+dxPr/vbygZQ91mNWYtMsMN2QEgWeIutxSosuOwas+9PLB3b9BB1Pt567BVnWfeIbZN1nuSlWTi8fcBz5B2zJ09b/nT4w6DrreZmwFXKSwauJ9ZwqyLR+ri5nW1MxDSe07gcY1nO0INM6LzDcut3gdrDuPatYG9rTKtp5iq3HduC11nNj+7fW7fa53MqXk2w9H11+1n3gdFmPdeQ86zEK6wPevtbjmBoFrgAIH2g9twtzrMdp/3IIDKe9lw/fu7aRY/rS8bcUWJRU8S8U32C4ab71fBORGlHk9vDZmoMAnNldu4uLSD3hG0h2QCcCs/ayY8UcZrUMJ7ugiCK3SYcW/pzRPQR/H+ut6B+76vOL3BR7TIqKPRxIy6VlUxfeTgfN/FxsiDlMeHATDMN6CRoa6EN2fjGFbg+/7kxicLtmuD0mAb5edGjpD1jFj8JiDxl5hayOTuPsnmE4HAaBvt54Ow32p+byW2QS/j5OfL2dDGrXjCYuJ4dzCpmzOR7ThIl9WlFQ7GFgRDDLolJ45LutHEzLo30LP/q1Deam0R3ILiimoMjDrsQs3B4Tp8PgQGoOvVoHcm7f1vj7eBF5KJNfdiQSFuhLz9aB+Hg7MIDfIpP4fV8awzs1Z2C7YKKSssnKL6ZTiD9PzN1BXqGbMV1aclbPUFKzC3nxl90Mbt+MuMN5pOcVcuvYzmw6mE6xx8OZ3UNxOgyW7k7mt13JAIztFkJ+oZtij4fLB0fQxOWgyG1yMC2X1dFprIlOo11zP9q38KO5v4uU7AJi0nLJzi/mkoFtcXusHWhHd2nJ1rgM5m9LYE9SdulDfX6/1szbcogAHy8uHRTO+pjD7EnMxu0x6RMexKaD6dZTwtuBj5eTjLwiwGRi79a0DvZl/YHDZOUXM6R9M0ICfBjZuQUeExbtTGRPUjatAn3pHOLHgh1JbInNKL3dlk19aNe8Cb5eDpr5+9A6yJfklCQW7c0iq8iBn8vJdSPa08zfxZbYdFZt3U0XIx5nx1EYGESn5ODtZRDW1Id1MVbGAF8vsvKLj9yCeeT/BuE+VoErHauR4ozuIQT5ejF/eyIFxW7AYHjH5myPzyS7oBgDDyYOuoU15bSmcew+mMimwrZk4YfTYdCxpT8OA/xcXmw6mI6Bh7fmLiWsbWcCcqLpEuzkv7v8CTYzOUwAYNCMTPJxkYcvDgN8zXx8KOQwf2y+MOHIzsGtSOWf3zYHDFqQQSqBpcdKeDsNHO4CwgO82JflwJ88XBSVuc5AchjpvZuDxc3IxI+XIpfjb+QT5WlD+7DmJOc72ZdhPUcudSylnSOJd7gYR3E+WfjRv3kxTX2c7M9y8sFfT6dLaOPrejVM0zRPPOyob7/9llmzZjFv3jyCgoKYPHkyU6ZMYciQITWVsdQXX3zB9ddfz8yZMxk+fDgvv/wyX331Fbt27SI0tPwL0ZUrVzJ27FhmzJjBBRdcwKxZs3jmmWfYsGEDffocY52iP8nMzCQoKIiMjAwCA+t/N1H67HsI3vah3TFEpL7qdTGc9n9WIdan8f2jKVLbvl4fy/99tZmWTV0s/8dZ+HrXfveriMjJMH96EGP1G+Sb3jxU9Bd+9AzHxKAQ7yNFCYM/FwGOxWF48JgOehgxOPBQgDfRZms8WA0gBh4MOPLfo9cZQjo+RhF5pot+jn0s8/TFjYNuRizxZkuy8COEdAxMTKCvI5pdnggOE0AeLkwcdDFiCTXS2eMJ5zABRBjJGJh0MeJoQgE/e4bQxkgl2QwiD1+K8MKbYpqRxenOzezxtMWJm+GOSArxYpOnM4dMaw3djo4Efvf0JMJIxpdCYs0QOhvxdHHE0YZUYs2WrDF74Dad+BiFBJLLMEckBXgTSC5+Rj7vFJ/HKMcO2hrJOHGThR8xZhjNyWSoI5LujlgKTG8WegYSZ4Zw0Ayhl+MA7Y1EWhtpHDabkmIGEWqks8bTA2+Kec31XwAyTT/eKj6fSc6VdHPEARDlaUMXRzyz3WOJ8YTS3pFInunikNmCIpy4cXCVczHNjUx+cQ+moyMBgHSzKf7kUYQXQx278KOAHz3D6WHEEGYc5if3MPyMAhLMZmzwdKWX4wB3eX1PmtmUIHIoxotFngHsM1tztmM9XYx4EmhGGyONItPJOk93Rjp3ALDQPZB8vPGliHHOPzSNHPGLezAm0N04iNPw8It7MD4UMdixmwK86eeIpth04GV4yp0b7QmjoyORAtObbWYHBjv2AJBt+rLE049mZNPfsRd/o4ADnlDaO6wPr1PNALZ6OjHIsZsMsymHaUpXI45oszW9HAcq9fegxF5Pa5oZWTQ3stnhaU8xDvo5ogEoMp14G24A9nvC6OBILD1vm6cDDszS23ObBk7DKgclm4EEkYPLcBNntiCYbPyNghNmyTZ9iTNbctAMYXwF93WJDNOPea3v4prbHq7Sz1pXVaVOVOWiW4msrCxmz57NZ599xqJFi+jUqRNTpkxh+vTpJxW6MoYPH87QoUP573+tXwIej4eIiAjuvvtuHnzwwXLjJ0+eTE5ODj/88EPpZSNGjGDAgAHMnDmzwtsoKCigoODokyszM5OIiIgGU3QjdS+8NgiAoqCOOH0DcCTvgJAe1h/TbXWrGU7IjIP0A1ZnT/NOVsdRcDtw+Vu7E0YevV/xCbT+ZMZa3T3Fedbl3v4Q0s3qmnM4retL3GHdDljdQs06WNfZcax1m4cPWJ1cpseastdupNXBE9Da6ujZvwwSt1ldUX8W0sPqPPMJgLC+VkePp8jqWCrpUIrfCC26WB1F0csgOwFCelqdSH0vt2534RPlr7vLeMiIte6L9Biry6zzOKtjKri9tVh81EIrc9thMPJOqyMrba/VRZa0w+oOLOncOrjW6ozyb2ldr+GE9qOsrqb0A1CQDTGrrE6p7CSrKzAnGUJ7WR/v5R22ppX6tQDDYXXltehi3Uf7frMWuW/Vz3rM4jdZ3Wd+LaypgOvet7qr/Fpa3VslXAFWF1riNut+LBEYbj02JY9pr4ugSbD1/eED1v3dZqDVnZW6x5pmGLu24udgq75W11lxHnQ6w+rISo06OmWxZXfrPmvSzPp5AQZeZ/0MSX947oT2su6bgDbW+mGBra37ND8DOoyxfv6S52hwO2jS3Brfqi+0H13xY+zVxLqfgyKOdKr5WPdTWrTVGZiXZnXyNe9oPaZ7F0FOkvWz9zjf2lzAdB/tcnM4rOmlh/dbl6XuBUwYeRcc2gxevlbHW36m1WVWnActulqPYVC49bi7/K3naWac9Xim7jl6vwB0P9/KGLPKyh3a0+oADWht3Y9g/R1qM9D6OUo2PWjeCcKHWNcXv9H6+XpOsv7uFeVB4nbyU/aT5G7K6yHTeebu68FdbHVqikitueR/K9gYk87fJnTnzjO1npuI1COFuRR9cQPee60ZJwWmFz5GcZkhcWYL0swAQowMWhmH2e8JIxM/Es1mdDQSyMC/tKhRYHrjYxSVOX+vpzVNjTzCjPRKRfpzEQLKFh7+KN/0xo2jUoWHP56TQhBtjZQTDxZpZArOehKfsffaHaNa1ErR7Y927NjBtddey5YtW3C73ad6dRUqLCzEz8+P2bNnc/HFF5defsMNN5Cens73339f7px27doxbdo07rvvvtLLHnvsMb777js2b95c4e08/vjjPPFE+TfjDaboBlZRx+sP869N89hrXnk8VuHgeCoz5s+K8q3iWaczT+5NfMltlmQ/3s9wIhWd+8fLSv6KVPb6jzf+j/dVVe63krFVOacy94lpWgVE/xBrWmJF1//n+/p4GUzTmvro3/Lo/WCaVuHTcB59rCu6jyq63h1zrEJhh9HW98UFVjGySbPK3Q8ez5Fpl2HHHlNcaBUem7ay8pzocTsVOSlW8a+q11WZ52BFj3dxofXzB4Uff9wxnitx6XmMefpXTBw8f0V/Lh/ctmq5ReSU7EvO5qwXluAw4Pd/jiM0wNfuSCIiVeMuhsUzKN7wKV45h+xO02B5mrSAkO4YBRkYidsrd5JPoLV8SVEuptMHw12AiYHBH8oDvkEUtBmKK24NRkGm9Xq+5ANwwwk+TfGE9MSdGImzWQTF3gF4N22O0XYIZkAb2P4NpO3DSNldepVFzbvhzDiAw7sJZkArjIJsq3HjCNNw4vYLwRnYGiMzzlrip2mYtaRO8s7ScXlBXYhvMYJOsd9hAGbH08DhjWF6rA+9HU5rne+Yldb7HYC2QzE7noERs8pqEAhuZzU/tBte2qhgYlCMA+/WfawPvb39rAaATZ/CwdXWB+TthltL2/iHwLavSz/oTu17Cy069reaHXb9aC3j0vMCqyFj82dWY0NYHzi0ybrdtH0weKrVvNG8ExRkYTq8MApzMWPXYiRtt24nPQYyDpZ97AbfAL0use67tGjrQ/5OZ1gNLZE/WE0ZQW2txgXTA3sXWq/5+11pfbDf4wLrg/vkXeAusD6kD+1p3V7sWms5ppiV1nuk4bda939WvDXrxfTA5s+tZofmnaymk32/Wcv09L3CWuomqK211E1BFnQ/z2oq6XsFOI+/Hl59UStFt/z8fObMmcOsWbOYP38+YWFhXH311Tz99NMnFfpE4uPjCQ8PZ+XKlYwceXQhzr///e8sWbKE1atXlzvH5XLx4YcfcvXVV5de9r///Y8nnniCxMTEcuOhEXS6iYhUwXXvrmbZnhT8XE4W/+0MvekXqUVP/biTt5bu44zuIXww9djr14qI1Hmmaa39G7UQfnzg6OU9J0FId2jSjLyEPTTxD7AKFoe2WLNRWvWFPb8eWQf6PGt92gMrYe9vMOE/1myMnCRrtkXCVus6A1pb6yd7uWDk3dZ6wEnbrWJH0k6r8NF2qPV1dhIM/Yt1XuI2a7ZE+gGroOQfYs2cyDpkzYhpGgoZcdDxNEg/aBUbshOt4kn4YGvd4wMrIPOQVURxNbXWQ45bbxVAnN7QeqBVtNo621qDOv2AVbjoONb6cBmsmSv5GdYHp807w9avrCU9Sm6jhMdjFbVMjzUjx6/50ft6/QfWusa9LrKKM97+1trXCVutwkd+etnrKuEutmbTNA059mPpLj4yY6Z55RsfivKO3AeuiseXrLPdb/LRzccqUtVmiNp0Kk0gtaWmM9aH+6CaVKXoVuUWowULFjBr1iy+++47vLy8uPzyy/n5558ZO3bsSQeuS3x8fPDxqbndUERE6pN3bxjKpP8uJzIhi1d+3cN/LulrdySRRmFfcjbvLLOm3V81NMLmNCIip8gwrCLVsE4w7JYKhzQ51rmFuVaxpmTGxJj7y48ZctPxb7/9kaaNdiOOPabtkV3Y/7hBVFivise27l/x8Z4XVnDbo/50gQMGHGkKad2v4utvEnx0KZf+kyse43BYS+P8mWHAkKnWnz9qM8D6A+BdQcENrPv4eAW3kjElBb7KFli8j/noWvxbls9bkbpc0KnL2UrUdMb6cB/YoMrzpS655BLy8vL46KOPSEhI4M0336yVglvLli1xOp3lOtQSExNp1ariXxqtWrWq0ngRESnL5eXgiUm9AZi9PpakrHybE4k0Dj9tS8BjwshOLZjQW69bRKQRc/lpTVkRqbeqXHRLTEzkyy+/5KKLLsLbu/bm47pcLgYPHszChQtLL/N4PCxcuLDMdNM/GjlyZJnxAL/88ssxx4uISHnDOjand5tACoo9TPui4vUwRaT6ZOQW8cHK/QBc0L81hj45FhEREamXKlV0y8zMLP3aNE0yMzOP+acmTZs2jbfffpsPP/yQnTt3cvvtt5OTk8PUqVYr6vXXX89DDz1UOv7ee+9l/vz5vPDCC0RGRvL444+zbt067rrrrhrNKSLSkBiGwTOX9cNhwPKoFKKSsu2OJNKgLdiRQHJWAeHBTbh4QPiJTxARERGROqlSfbrNmjXj0KFDhIaGEhwcXOEnrqZpYhhGje1eCjB58mSSk5OZPn06CQkJDBgwoHQTB4CYmBgcf9gVcNSoUcyaNYtHHnmEf/7zn3Tt2pXvvvuOPn361FhGEZGGqE94EGd2D2VhZBLPzo/kreuH2B1JpEHKLijm77O3ADBpQBv8fTSlSkRERKS+qtTupUuWLGH06NF4eXmxZMmS4449/fTTqy1cXVCVXSlERBqy3YlZTHh5KaYJv04bS5fQALsjiTQ47yzbx7/n7QTgo5uGMbbbCRa0FhEREZFaVe27l/6xkNaxY0ciIiLKdbuZpsnBgwdPIq6IiNQH3cICGNW5BSuiUrlr1kZ+uvc0rTUlUo0Kit18uc56LdUnPJDTura0OZGIiIiInIoqb6TQsWNHkpOTy12elpZGx44dqyWUiIjUTdMvsHYyjUzIYltcza7jKdLYfLMhjt2J2fh4OXj7+iEqaouIiIjUc1UuupWs3fZn2dnZ+Pr6VksoERGpm7q3CuCsHqEAXPfeatyeE65QICKVtCY6DYCpozvSOqiJzWlERERE5FRVenXeadOmAdYudo8++ih+fn6lx9xuN6tXr2bAgAHVHlBEROqWqaM7sCgyifTcIrbEpjOwXTO7I4nUe7GHc/l2YxwAIzo1tzmNiIiIiFSHShfdNm7cCFidblu3bsXlcpUec7lc9O/fnwceeKD6E4qISJ1yWtcQzuvbih+3JvDmkn28MWWQpsGJnKK3l+4DoHWQL8M7trA5jYiIiIhUh0oX3X777TcApk6dyiuvvKKdPEVEGrGrhrZj/rYE5m9P4O1l+/jr2M52RxKpt+LT8/hsrbWBwmMX9qaJy2lzIhERERGpDlVe0+39999XwU1EpJEb2y2EJy/qA8Arv+4hPbfQ5kQi9df/FkdRWOwhNMCH07uF2B1HRERERKpJpTvd/mjdunV8+eWXxMTEUFhY9o3WN998Uy3BRESkbrtmWDs+XnWAXYlZfLTqAPeM62p3JJF6p8jt4aetCQBMv7CXutxEREREGpAqd7p9/vnnjBo1ip07d/Ltt99SVFTE9u3bWbRoEUFBQTWRUURE6iCHw+DKoREAvLpwD1FJ2TYnEql//vfbXlJzCnF5OTiti7rcRERERBqSKhfdnnrqKV566SXmzp2Ly+XilVdeITIykiuvvJJ27drVREYREamjrh/Znh6tAij2mHyxNsbuOCL1zvebrR1L7xvflSA/b5vTiIiIiEh1qnLRbe/evZx//vmAtWtpTk4OhmFw//3389Zbb1V7QBERqbu8nQ6mju4AwDvLo9ken2FvIJF6ZNPBdPYl5+DtNLhuRHu744iIiIhINaty0a1Zs2ZkZWUBEB4ezrZt2wBIT08nNze3etOJiEidd9mgtgxsF4xpwgs/78Y0TbsjidQLn/x+AIAL+7chwFddbiIiIiINTZWLbmPHjuWXX34B4IorruDee+/llltu4eqrr2bcuHHVHlBEROo2L6eDByf2AGBRZBI/bDlkcyKRui+7oJjZ62MBuGRguM1pRERERKQmVHn30v/+97/k5+cD8PDDD+Pt7c3KlSu57LLLeOSRR6o9oIiI1H3DO7Xg6mERfLbmIP9bvJcJvVvh8qry5zoijcY/Zm8BwNtpMKR9c5vTiIiIiEhNqHLRrXnzoy8MHQ4HDz74YLUGEhGR+unmMZ34al0sOw9l8unqA0wd3dHuSCJ1Um5hMb/tSgLgmmHtaOJy2pxIRERERGpCpYpumZmZlb7CwMDAkw4jIiL1V5fQptx1Vhde/nUPby7Zx6WD2hLUROtUifzZjB8jyS10Exbow2MX9rY7joiIiIjUkEoV3YKDgzEM47hjTNPEMAzcbne1BBMRkfrnmuHteGdZNAmZ+by2cA+PXNDL7kgidYrbYzJnczwA/zyvJw7H8V9fiYiIiEj9Vami22+//VbTOUREpAEIDfDlyYt6M+3LzbyzPJoxXVtyRvdQu2OJ1Bmfr40hI6+IAF8vzu/b2u44IiIiIlKDKlV0O/3002s6h4iINBAX9GvDs/N3kZCZz9cb4lR0Ezkiv8jN8wt2AXDt8PZ4ObXZiIiIiEhDdlKv9pYtW8aUKVMYNWoUcXFxAHz88ccsX768WsOJiEj94/JyMOPSvgDM3RzPl+sO2pxIpG74aNV+DucW0SbIlwfO6WZ3HBERERGpYVUuun399ddMmDCBJk2asGHDBgoKCgDIyMjgqaeeqvaAIiJS/wxsF1z69XvLo+0LIlJHeDwmby3dB8A947qqy01ERESkEajyK75///vfzJw5k7fffhtv76O70o0ePZoNGzZUazgREamfgv1c/PeagQBEJmSx6WC6vYFEbPbJ6gOkZBfi73Jy6aC2dscRERERkVpQ5aLbrl27GDt2bLnLg4KCSE9Pr45MIiLSAFzQrw2XD7aKC68t3GNzGhH7FLk9pWu5jerSEpeXutxEREREGoMqv+pr1aoVUVFR5S5fvnw5nTp1qpZQIiLSMNx+RmcAFu1KYk10ms1pROyx6WA6mfnFADx1SV+b04iIiIhIbaly0e2WW27h3nvvZfXq1RiGQXx8PJ9++ikPPPAAt99+e01kFBGReqpzSFMuGRiOacKDX28hr9BtdySRWvfmEmsttwv7tyEkwMfmNCIiIiJSW7yqesKDDz6Ix+Nh3Lhx5ObmMnbsWHx8fHjggQe4++67ayKjiIjUY09e1Julu5PZl5LDE3O38/Rl/eyOJFJr4tPz+HVnIoYBd5/Vxe44IiIiIlKLDNM0zZM5sbCwkKioKLKzs+nVqxdNmzYlLy+PJk2aVHdGW2VmZhIUFERGRgaBgYF2xxERqZfmbzvEbZ9swNtpsOPJiXhr50ZpBNwek17T51NQ7GFQu2C+uWO03ZFERERE5BRVpU500u96XC4XvXr1YtiwYXh7e/Piiy/SsWPHk706ERFpwMb3DCPQ14sit8k9n220O45IrdgSm05BsQeA60a2tzmNiIiIiNS2ShfdCgoKeOihhxgyZAijRo3iu+++A+D999+nY8eOvPTSS9x///01lVNEROoxL6eDm8ZYH8z8tC2BqKRsmxOJ1CyPx2TGj5GAVXS+ZGBbmxOJiIiISG2rdNFt+vTpvPHGG3To0IH9+/dzxRVX8Ne//pWXXnqJF198kf379/OPf/yjJrOKiEg9du+4rnQO8QfgrlkbbE4jUrM2xaazZr+1Y+/NYzQTQERERKQxqnTR7auvvuKjjz5i9uzZ/Pzzz7jdboqLi9m8eTNXXXUVTqezJnOKiEg9ZxgGj1zQC4DIhCyueft3mxOJ1Jz3lkcDcH7f1ozs3MLmNCIiIiJih0oX3WJjYxk8eDAAffr0wcfHh/vvvx/DMGosnIiINCxndg8t/Xrl3lRyC4ttTCNSM3YlZPHDlkMAXDUswuY0IiIiImKXShfd3G43Lper9HsvLy+aNm1aI6FERKThmjllcOnX76/Yb18QkRry6PfbABjesTmndQ2xOY2IiIiI2MWrsgNN0+TGG2/Ex8cHgPz8fG677Tb8/f3LjPvmm2+qN6GIiDQoE/u04pxeYfy8I5HnFuzi5jEd8fXWEgXSMGyJTWdNtLWW27COzW1OIyIiIiJ2qnTR7YYbbijz/ZQpU6o9jIiINA4PntuDn3ckAnDeq8tYOO10LVcgDUJJwQ3gogFtbEwiIiIiInardNHt/fffr8kcIiLSiHQKacotp3Xk7WXR7EvOIfZwHhHN/eyOJXJKkrMK+Pe8nQD8bUJ3uoQG2JxIREREROxU6TXdREREqtP/ndO99OuLXl+Bx2PamEbk1M3fnlD69YTeYTYmEREREZG6QEU3ERGxha+3k3vO6gJAWk4h2+IzbE4kcvKSMvN59DtrA4VpZ3dTl5uIiIiIqOgmIiL2uePMLqVfP/XjTtzqdpN66puNcaVfX9CvtY1JRERERKSuUNFNRERs4+vtZNZfhgPw+740ftx6yOZEIlWXlV/Ep6sPAPDweT3pFNLU5kQiIiIiUheo6CYiIrYa1aUldx+ZZvr4nO2k5xbanEikaj5dHcPBtDyC/by5ZFC43XFEREREpI5Q0U1ERGx3xxld6NTSn9ScQj75/YDdcUQqraDYzez1sYC1llvLpj42JxIRERGRukJFNxERsV0Tl5MpI9oD8MrCPexLzrY5kUjlfPp7DFFJ2QT4enF+X63lJiIiIiJHqegmIiJ1wpQR7Wnfwo8it8lZLywhKTPf7kgix5WaXcD/FkcB8MA53WmhLjcRERER+QMV3UREpE5weTm4aMDR9bC+XHfQxjQiJ/bG4r2kZBcS6OvFxQO0lpuIiIiIlKWim4iI1BkXD2hT+vWHqw6QnFVgYxqRY1u4M5F3lkcD8MgFvQjy87Y5kYiIiIjUNSq6iYhIndEppCnL/3Emgb5eJGcVcOesDZimaXcskXLeWLy39OtzeoXZmERERERE6ioV3UREpE5p28yPb+4YTRNvJ2ui01i4M8nuSCJlRCZksj7mMACf3DycYD+XzYlEREREpC5S0U1EROqcLqFNuXZ4OwBu+2Q92QXFNicSOertpdGYJpzbpxVjura0O46IiIiI1FEquomISJ006cj6bsUek3eW7bM5jYglt7CYX3YkAHDDqA72hhERERGROk1FNxERqZP6tQ3mtCNdRK8s3ENCRr7NiUTg6Z8iycwvpmVTF0PaN7M7joiIiIjUYSq6iYhInfXKVQMBME2YuWTvCUaL1KzCYg/fb4oH4MmL+uDl1MsoERERETk2vVoUEZE6q7m/i/vHdwPgg5X7OZCaY3Miacz+M28HGXlFhAT4MKF3K7vjiIiIiEgdp6KbiIjUaVcPiyj9+m+zt2Capo1ppLFavS+VD1cdAODfF/fB6TBsTiQiIiIidV29KbqlpaVx7bXXEhgYSHBwMDfffDPZ2dnHHX/33XfTvXt3mjRpQrt27bjnnnvIyMioxdQiInKqQgN9mTzEKrytiU7jbW2qIDb4bE0MAJOHRKjLTUREREQqpd4U3a699lq2b9/OL7/8wg8//MDSpUv561//eszx8fHxxMfH8/zzz7Nt2zY++OAD5s+fz80331yLqUVEpDo8c3k/bj+jMwCv/7aXjNwimxNJY3IgNYd5Ww8BcM3wdjanEREREZH6wjDrwTydnTt30qtXL9auXcuQIUMAmD9/Pueddx6xsbG0adOmUtfz1VdfMWXKFHJycvDy8qrUOZmZmQQFBZGRkUFgYOBJ/wwiInJqCos9jJyxkNScQi4ZGM5LkwfYHUkaiUv+t4KNMen0ah3IvHvGYBiaWioiIiLSWFWlTlQvOt1WrVpFcHBwacENYPz48TgcDlavXl3p6ym5Q45XcCsoKCAzM7PMHxERsZ/Ly8G/Lu4DwLcb41gUmWhzImkMvtkQy8aYdABeuLK/Cm4iIiIiUmn1ouiWkJBAaGhomcu8vLxo3rw5CQkJlbqOlJQU/vWvfx13SirAjBkzCAoKKv0TERFx3PEiIlJ7zu3TiibeTgCemLvD5jTS0BW7PfzrB+t5NrZbCD1bq+NdRERERCrP1qLbgw8+iGEYx/0TGRl5yreTmZnJ+eefT69evXj88cePO/ahhx4iIyOj9M/BgwdP+fZFRKR6GIbB29dbXc8HUnP5bmOczYmkIXvgq80cPrJ+4POX97M5jYiIiIjUN5Vb2KyG/N///R833njjccd06tSJVq1akZSUVOby4uJi0tLSaNXq+DuIZWVlMXHiRAICAvj222/x9vY+7ngfHx98fHwqlV9ERGrfmK4t6dU6kB2HMrnvi02c3SsMfx9b/zmTBigrv4g5m+MBuHJIW0IDfW1OJCIiIiL1ja3vUkJCQggJCTnhuJEjR5Kens769esZPHgwAIsWLcLj8TB8+PBjnpeZmcmECRPw8fFhzpw5+PrqBbOISEPw6tUDGf/iEsBa5P7n+0+3OZE0JKZpcvHrK/Ac2WrqyYv62BtIREREROqlerGmW8+ePZk4cSK33HILa9asYcWKFdx1111cddVVpTuXxsXF0aNHD9asWQNYBbdzzjmHnJwc3n33XTIzM0lISCAhIQG3223njyMiIqeoS2hTHruwFwC7E7OZv+2QzYmkIdmdmM3e5BwALh/cFt8j6wiKiIiIiFRFvSi6AXz66af06NGDcePGcd555zFmzBjeeuut0uNFRUXs2rWL/2/vzqOjqNI+jv86CdkISYBAFiCENQgEDARiXFAhE0AEHFEQeUFQdEBAUUYRZwR13gFGjuigvLiMio6IigouIyBLEJDIFmIAMSyGPYAQskCAbPf9A6lJyy6dFOl8P+f0OV23blU9lb7ndteTW3ULCgokSampqVq9erU2btyopk2bKjw83HrxnDYAqPyG3NBINzc/PVr6qc82qrC41OaI4C5mLNtuvf9zUrSNkQAAAKAycxhjjN1BXM3y8vIUFBSk3NxcBQYyaxkAXE12HylQpynJkqSbmoXo3w+c/5EDwKVYse0XDXxrjTwc0gcPXqfrGte2OyQAAABcRS4nT1RpRroBAPBbkbX99VCnxpKkFdsOa092gc0RoTI7erxQo2ZvkHT6tlISbgAAALgSJN0AAJXaE12jVdP/9MzU972zRqWlDODG7/P1pizlFBQpJMBH47pfY3c4AAAAqORIugEAKrVqnh7W7JI//3JcYz9NtzkiVEa5BUX65+JtkqT7b4xSzereNkcEAACAyo6kGwCg0uvZNkK3twmXJM1Zv1eb9uXaHBEqm1eTt+lQ/ik1DqmuQQlRdocDAAAAN0DSDQDgFp7s2sJ6/7evflRxCbOZ4tJs2H1Ub67IlCSNSYpWgI+XzREBAADAHZB0AwC4hcja/pr94HVyOKTVmdmatmSb3SGhEigsLtVTn26UJCW1DNVtMWE2RwQAAAB3QdINAOA2EprU1vjbW0qSpi3drvW7sm2OCFe7L3/Yr4yD+ZKke+Mj5XA4bI4IAAAA7oKkGwDArQy+Pko3N68jSeozI0XZxwttjghXK2OMPtuwV5J0e5twq90AAAAArkDSDQDgVhwOh/50c2NrmdtMcT5z1u/Vd9uPyMvDoTFJ0YxyAwAAgEuRdAMAuJ3rm4RoXPfTEyvMXLVTy7f+YnNEuNrsPlKgZ7/YLEl6PKm5GoVUtzkiAAAAuBuSbgAAt/RQp8a6u319SdLURVt1sqjE5ohwtSgqKdWjH21QQWGJOkbV0p86NbE7JAAAALghkm4AALfkcDg0qnMz+VbzUNqeHD31abqKS0rtDgtXgSkLM7Rhd44kadxtLeTpwW2lAAAAcD2SbgAAtxVZ218v3NVWkjQvbb9mr91jc0Sw24JNWXpj+c+SpDF/aK7YyJo2RwQAAAB3RdINAODWerYJV6dfZ6V8Zt4mbjOtwopLSvXM56ef49a0boCG38JtpQAAACg/JN0AAG7N4XBozB+aW8sd/r5YeSeLbIwIdpm2dLt+yT8lSfrnPdfKy5OfQQAAACg//NoEALi9mHpB6hhVS5KUf7JYYz9JV0mpsTkqVKTDx05p2pJtkqSQAG9dExZoc0QAAABwdyTdAABuz8PDoY/+dJ1ahp9OtMzfdMBKwMD9GWM0YlaqJKmGj5dWju0sDyZPAAAAQDkj6QYAqBIcDoc+HpZgLf9zyTZtP3TMxohQUV78ZqtWZ2ZLkl6+51r5VvO0OSIAAABUBSTdAABVRoCPl/41KM5afvaLzTZGg4qwL+eEXk3eLknqF9dAXa4JtTkiAAAAVBUk3QAAVUpiy1A92qWZJGnl9sN6hdtM3dqwf6+33j/bq5WNkQAAAKCqIekGAKhyHvk16SZJLy7aqvS9OfYFg3LzVfp+bdyXK+n0KDc/b24rBQAAQMUh6QYAqHI8PRyaclcba7nXq98pt6DIxojgatsPHdPIDzZIkoL8qukfZT5vAAAAoCKQdAMAVEl3xzXQPR0aWMs9XllhYzRwpZJSo8Sp31rL0/rH2hgNAAAAqiqSbgCAKmtynzZqXKe6JGnv0ROaNH+LzRHBFf721Y/W+6SWobq5eR0bowEAAEBVRdINAFCl/fuBeOv969/+rD3ZBTZGgyu1L+eE3k3ZKUm6M7aeXr7nWlvjAQAAQNVF0g0AUKXVC/bTkBuirOVRszfIGGNfQLgi4z7bKGOkNvWDNLXftfL39rI7JAAAAFRRJN0AAFXeX267Rm/dFydJStuTo4/W7rE5IvweH6/bo+Vbf5EkPdurlc3RAAAAoKoj6QYAqPK8PD3U5ZpQxdQLkiQ99dlGbT+Ub3NUuBwHck/qyU/SJUk3NK2tdpE1bY4IAAAAVR1JNwAAfjUgPtJ6nzh1Oc93qyQKCot13aQl1vLIW5vZGA0AAABwGkk3AAB+dU/HSE2/t5213GfGKmUfL7QxIlxMaanRU59utJZf+5/2SmhS28aIAAAAgNNIugEAUEaPNuFaMPomeXt66FD+KT35SbqKS0rtDgvn8dbKTH3xw35J0vjbW6pb6zCbIwIAAABOI+kGAMBvtAgL1OuD2svhkBZvOai/zN2kgsJiu8PCb2QcyNffv94iSRp2cxOnWWgBAAAAu5F0AwDgHG6Nrqt/3NlGkvTRuj26983VOllUYnNUOONEYYnun7lW0umJE8Z2i5bD4bA5KgAAAOC/SLoBAHAefTs00L8GxSnQ10tpe3L013mbZIyxO6wqb/P+XF0zfoH25ZyQJN1xbT0SbgAAALjqkHQDAOACEluG6vnerSVJn6zfq/dSdtkcUdVWWmr00qKt1vKt0XX0x9h6NkYEAAAAnBtJNwAALqL3tRG6q319SdKELzYrfW+OvQFVYa8s3a7FWw5Jkh7p3FRvD+4gL09+zgAAAODqw69UAAAuwuFw6NlerRQW6CtJ6vXqd9p9pMDmqKqez1L36qXFp0e5PderlR5P4jluAAAAuHqRdAMA4BIE+HjprcFx1nKnKcnatC/Xxoiqlj3ZBZqyMEOS1L9jpAYlNLQ5IgAAAODCSLoBAHCJWkUEafztLa3l577crNJSJlYob7kFRer7eoqyck8qspa/nrn9Gka4AQAA4KpH0g0AgMtw/42N9M6QDpKktTuPauyn6STeylFuQZEeeHetsnJPKqq2v+YMS5C/t5fdYQEAAAAXRdINAIDLdGt0XT3fu5Ukac76vWr89Nfaefi4zVG5n+KSUg19b63W7TqqQF8vvdK/nUJ/fa4eAAAAcLUj6QYAwO8wKCFKf05qbi0//nGafcG4IWOMRnyQqrU7j0qSZvxPe8XUD7I5KgAAAODSkXQDAOB3Gtm5me779YH+qbtz9NyXm22OyD0Ul5TqzRU/a+Hmg5Kka8IDdX2T2jZHBQAAAFweHooCAMAVeK53a+3LOaHFWw7pne926lDeKb3Yt618q3naHVqlNWbOD/o8bb8kaVTnphrZuSkTJwAAAKDSYaQbAABX6M1Bcboluo4k6T8bs9T15eVMrvA7fbx2j5Vwe/iWJhqd2Fw+XiQwAQAAUPmQdAMA4Ao5HA7NHNJR7RvWlCTtOlKgf638WUUlpTZHVrlM/SZDT36aLknq2TZCT3ZrIU8PRrgBAACgciLpBgCAi7x1X5xubn56xNvEr39St5eXq5jE20XtPlKgzi8u07Sl2yVJjetU19S+bW2OCgAAALgyJN0AAHCRYH9vzRzSQYN+nVxhxy/H9fZ3mTp6vNDmyK5eB/NOqtOUZP38y3FJUniQr2YNjVc1T36iAAAAoHLjFy0AAC7kcDj0fO/W6t+xgaTTI95ufXGZfsk/ZXNkV59jp4oVP3GJtXx9k9pa9VRnhQf52RgVAAAA4Bok3QAAKAfjb2+l+34d8ZZTUKQOf1+sD1bvtjmqq4cxRg++u86p7KV+1zJLKQAAANwGSTcAAMqBn7ennuvdWi/0aWOVPT13o1btOGxjVFeH4pJS3fPG90r5+YhVtnLsrQoN9LUxKgAAAMC1SLoBAFCO+nZooFGdm1rL989cq7U7s22MyD6lpUZTFv6kpn+Zr9WZ//0bbHjmD6pf09/GyAAAAADXI+kGAEA5G5MUrVfvjZW/t6dOFpXq7tdSNOzf63X4WNV6ztuX6fs1PXmHtdy2QbA2PddVNat72xgVAAAAUD4cxhhjdxBXs7y8PAUFBSk3N1eBgYF2hwMAqMSOHi/Uw7NSnW6rXPuXRNWp4WNjVOXv+KliPflpuv6TnmWVTejZUkNuaGRjVAAAAMDlu5w8ESPdAACoIDWre2vm/R3UrVWYVdbh74u1YFPWBbaq3HJPFOn2V1Y6Jdym3NWGhBsAAADcXqVJumVnZ2vAgAEKDAxUcHCwHnjgAR07duyStjXGqHv37nI4HJo3b175BgoAwAX4eHnq1Xtj1atthFU27P1UDfjX90rfm2NfYC5mjNH8jVnq8uK3yjx83CpfMuZm3R3XwMbIAAAAgIpRaZJuAwYM0ObNm7Vo0SJ99dVXWr58uR566KFL2vbll1+Ww+Eo5wgBALg0Xp4emtY/Vj/9rZvaRQZLkr7bfkS9Xv1OEz7fpBOFJfYGeIUW/3hQjcZ9reGzUnX42Cn5eHnomdtbKnPSbWpSJ8Du8AAAAIAKUSme6bZlyxa1bNlSa9euVVxcnCRpwYIFuu2227R3715FREScd9u0tDTdfvvtWrduncLDwzV37lzdcccd561/6tQpnTr13wdb5+XlqUGDBjzTDQBQLg4fO6VuL684a1KFdwZ3UKfmdeTpUTn+aZRbUKT5m7L08bo9St2dY5V7eji0cuytCg/ysy84AAAAwEXc7pluKSkpCg4OthJukpSYmCgPDw+tXr36vNsVFBTo3nvv1fTp0xUWFnbeemVNmjRJQUFB1qtBA26BAQCUn5AAH337xC36YXySerQJt8qHzFyrJk9/rfW7slUJ/j+mITPX6KnPNjol3J7t2VLL/nwLCTcAAABUSV52B3ApDhw4oLp16zqVeXl5qVatWjpw4MB5t3vsscd0/fXXq3fv3pd8rHHjxunxxx+3ls+MdAMAoLxU9zn9dTz93nbqF/eLBr29xlrXZ0aKJKl5aIDeHxqvujV8bYnxfEbMStV/Np49EcTrA9ura6tL+4cXAAAA4I5sHen21FNPyeFwXPD1008//a59f/HFF1q6dKlefvnly9rOx8dHgYGBTi8AACpKp+Z1lPrMH3RfQkOn8q0Hj6nj35foyLFTKiwutSm60zbsPqrlW3/R3a+tOivh9lCnxpozLIGEGwAAAKo8W0e6jRkzRoMHD75gncaNGyssLEyHDh1yKi8uLlZ2dvZ5bxtdunSpduzYoeDgYKfyPn366KabbtKyZcuuIHIAAMpPrereeq53a/Xt0EBTFmZoWcYv1rr2/7tYkuRbzUOzH7xOsZE1KySmk0UlembeJn2VnqUTRWdP9NCxUS3NGNBOtQN8KiQeAAAA4GpXqSZSWLdundq3by9J+uabb9StW7fzTqRw4MABHT582KksJiZG//znP9WzZ081atToko59OQ/IAwCgPOSdLNKwf6/Xqh1HzlrXsLa/BiVEaUB8pHIKihQa6OPSGbtLSo0yDx9Tj2krdeocI+xCAnz0ybAERYVUd9kxAQAAgKvV5eSJKkXSTZK6d++ugwcP6rXXXlNRUZGGDBmiuLg4ffDBB5Kkffv2qUuXLnrvvffUsWPHc+7D4XBcdPbS3yLpBgC4Whw9XqhVO45o1upd50zAnVEv2E//e0dreXk61DoiSEWlparu7WU9O+63so8Xak3mEfl4eSoi2E8ZB/O1YfdRJf90SHuOnlBJ6bl/KnzzWCc1D63hknMDAAAAKoPLyRNViokUJGnWrFkaOXKkunTpIg8PD/Xp00fTpk2z1hcVFSkjI0MFBQU2RgkAQPmpWd1bPdqEq0ebcB05dkp/eGm5so8XnlVvX84JDZm59rz7+VvvVgoL8tPnafu0dme2DuadurTj+1dT3w4NdFvrcLWpH+TSEXUAAACAu6k0I93swkg3AMDVLPt4oXYdOa7N+/P013mbXL7/x//QXA91aqxqnh7y9CDJBgAAgKrNLUe6AQCAs9Wq7q1a1b0VG1lTd7arp1IjBfh46VRxiRZuPqhHZm+4rP35eHmomqeHnuwWrYHXNWQ0GwAAAPA7kXQDAMBN+Hv/92vdx8tTvdpGqFfb05MNGWOUd7JYQX7VtD/nhNZkZiv/ZJEa1PJXy/BA1Q7wYSQbAAAA4EIk3QAAqAIcDoeC/KpJkiKC/XRHbD2bIwIAAADcm4fdAQAAAAAAAADuhqQbAAAAAAAA4GIk3QAAAAAAAAAXI+kGAAAAAAAAuBhJNwAAAAAAAMDFSLoBAAAAAAAALkbSDQAAAAAAAHAxkm4AAAAAAACAi5F0AwAAAAAAAFyMpBsAAAAAAADgYiTdAAAAAAAAABcj6QYAAAAAAAC4GEk3AAAAAAAAwMW87A7gameMkSTl5eXZHAkAAAAAAADsdCY/dCZfdCEk3S4iPz9fktSgQQObIwEAAAAAAMDVID8/X0FBQRes4zCXkpqrwkpLS7V//37VqFFDDofD7nBcIi8vTw0aNNCePXsUGBhodziwGe0BZdEeUBbtAWXRHlAW7QG/RZtAWbQHlOVu7cEYo/z8fEVERMjD48JPbWOk20V4eHiofv36dodRLgIDA92iwcM1aA8oi/aAsmgPKIv2gLJoD/gt2gTKoj2gLHdqDxcb4XYGEykAAAAAAAAALkbSDQAAAAAAAHAxkm5VkI+PjyZMmCAfHx+7Q8FVgPaAsmgPKIv2gLJoDyiL9oDfok2gLNoDyqrK7YGJFAAAAAAAAAAXY6QbAAAAAAAA4GIk3QAAAAAAAAAXI+kGAAAAAAAAuBhJNwAAAAAAAMDFSLpVMdOnT1dUVJR8fX0VHx+vNWvW2B0SysGkSZPUoUMH1ahRQ3Xr1tUdd9yhjIwMpzq33HKLHA6H02vYsGFOdXbv3q0ePXrI399fdevW1RNPPKHi4uKKPBW4wLPPPnvWZ92iRQtr/cmTJzVixAjVrl1bAQEB6tOnjw4ePOi0D9qC+4iKijqrPTgcDo0YMUI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      "text/plain": [
       "<Figure size 1500x465.839 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Start sequencers\n",
    "for seq in range(0, num_seq):\n",
    "    readout_module.arm_sequencer(seq)\n",
    "readout_module.start_sequencer()\n",
    "\n",
    "# Wait for sequencers to stop (only sequencer 0 will acquire)\n",
    "for seq in range(0, num_seq):\n",
    "    readout_module.get_sequencer_status(seq)\n",
    "readout_module.get_acquisition_status(0)\n",
    "\n",
    "# Get acquisition\n",
    "readout_module.store_scope_acquisition(0, \"scope\")\n",
    "acq = readout_module.get_acquisitions(0)\n",
    "\n",
    "# Plot result\n",
    "fig, ax = plt.subplots(1, 1, figsize=(15, 15 / 2 / 1.61))\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path0\"][\"data\"][0:2000])\n",
    "ax.plot(acq[\"scope\"][\"acquisition\"][\"scope\"][\"path1\"][\"data\"][0:2000])\n",
    "ax.set_xlabel(\"Time (ns)\")\n",
    "ax.set_ylabel(\"Relative amplitude\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "431a0b4b",
   "metadata": {},
   "source": [
    "As expected, we see a sine and sawtooth that are independently sequenced on the outputs."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e953df87",
   "metadata": {},
   "source": [
    "Stop\n",
    "----\n",
    "\n",
    "Finally, let's 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": 36,
   "id": "c598e4f9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-23T09:58:19.757323Z",
     "iopub.status.busy": "2024-07-23T09:58:19.757147Z",
     "iopub.status.idle": "2024-07-23T09:58:27.699711Z",
     "shell.execute_reply": "2024-07-23T09:58:27.698942Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Snapshot:\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cluster0_module4:\n",
      "\tparameter                    value\n",
      "--------------------------------------------------------------------------------\n",
      "in0_gain                      :\t-6 (dB)\n",
      "in0_offset                    :\t0 (V)\n",
      "in1_gain                      :\t-6 (dB)\n",
      "in1_offset                    :\t0 (V)\n",
      "marker0_inv_en                :\tFalse \n",
      "marker1_inv_en                :\tFalse \n",
      "marker2_inv_en                :\tFalse \n",
      "marker3_inv_en                :\tFalse \n",
      "out0_offset                   :\t0 (V)\n",
      "out1_offset                   :\t0 (V)\n",
      "present                       :\tTrue \n",
      "scope_acq_avg_mode_en_path0   :\tFalse \n",
      "scope_acq_avg_mode_en_path1   :\tFalse \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                   :\t0 \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_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                          :\tTrue \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                    :\tin0 \n",
      "connect_acq_Q                    :\tin1 \n",
      "connect_out0                     :\tI \n",
      "connect_out1                     :\tI \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                   :\t0 \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_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                          :\tTrue \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                    :\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_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                    :\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_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                    :\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_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                    :\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_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": [
    "# Print an overview of the instrument parameters.\n",
    "print(\"Snapshot:\")\n",
    "readout_module.print_readable_snapshot(update=True)\n",
    "\n",
    "# Reset the cluster\n",
    "cluster.reset()\n",
    "print(cluster.get_system_status())"
   ]
  }
 ],
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