{ "cells": [ { "cell_type": "markdown", "id": "39735caa", "metadata": {}, "source": [ "# Time of flight measurement\n", "Here show how to measure time of flight for your system.\n", "This is useful to calibrate the acquisition delay for subsequent experiments." ] }, { "cell_type": "code", "execution_count": 1, "id": "a9d3008b", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:28.298905Z", "iopub.status.busy": "2024-11-13T02:35:28.298088Z", "iopub.status.idle": "2024-11-13T02:35:29.941629Z", "shell.execute_reply": "2024-11-13T02:35:29.940771Z" }, "tags": [ "imports" ] }, "outputs": [], "source": [ "import json\n", "\n", "import numpy as np\n", "import rich # noqa:F401\n", "from qcodes.parameters import ManualParameter\n", "\n", "import quantify_core.data.handling as dh\n", "from quantify_core.analysis.time_of_flight_analysis import TimeOfFlightAnalysis\n", "from quantify_scheduler import Schedule\n", "from quantify_scheduler.backends.qblox import constants\n", "from quantify_scheduler.device_under_test.quantum_device import QuantumDevice\n", "from quantify_scheduler.gettables import ScheduleGettable\n", "from quantify_scheduler.math import closest_number_ceil\n", "from quantify_scheduler.operations.gate_library import Measure\n", "\n", "from utils import initialize_hardware, run # noqa:F401" ] }, { "cell_type": "code", "execution_count": 2, "id": "a86c16c4", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:29.944643Z", "iopub.status.busy": "2024-11-13T02:35:29.943927Z", "iopub.status.idle": "2024-11-13T02:35:29.947739Z", "shell.execute_reply": "2024-11-13T02:35:29.947196Z" }, "tags": [ "config", "header_1" ] }, "outputs": [], "source": [ "hw_config_path = \"configs/tuning_transmon_coupled_pair_hardware_config.json\"\n", "device_path = \"devices/transmon_device_2q.json\"" ] }, { "cell_type": "code", "execution_count": 3, "id": "f2bccfbd", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:29.949580Z", "iopub.status.busy": "2024-11-13T02:35:29.949258Z", "iopub.status.idle": "2024-11-13T02:35:29.953221Z", "shell.execute_reply": "2024-11-13T02:35:29.952590Z" }, "tags": [ "header_2" ] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Data will be saved in:\n", "/root/quantify-data\n" ] } ], "source": [ "with open(hw_config_path) as hw_cfg_json_file:\n", " hardware_cfg = json.load(hw_cfg_json_file)\n", "\n", "# Enter your own dataset directory here!\n", "dh.set_datadir(dh.default_datadir())" ] }, { "cell_type": "code", "execution_count": 4, "id": "f07203d0", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:29.954871Z", "iopub.status.busy": "2024-11-13T02:35:29.954706Z", "iopub.status.idle": "2024-11-13T02:35:30.470994Z", "shell.execute_reply": "2024-11-13T02:35:30.470275Z" }, "tags": [ "header_3" ] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/builds/qblox/packages/software/qblox_instruments_docs/.venv/lib/python3.9/site-packages/quantify_scheduler/backends/types/qblox.py:1220: ValidationWarning: Setting `auto_lo_cal=on_lo_interm_freq_change` will overwrite settings `dc_offset_i=0.0` and `dc_offset_q=0.0`. To suppress this warning, do not set either `dc_offset_i` or `dc_offset_q` for this port-clock.\n", " warnings.warn(\n", "/builds/qblox/packages/software/qblox_instruments_docs/.venv/lib/python3.9/site-packages/quantify_scheduler/backends/types/qblox.py:1235: ValidationWarning: Setting `auto_sideband_cal=on_interm_freq_change` will overwrite settings `amp_ratio=1.0` and `phase_error=0.0`. To suppress this warning, do not set either `amp_ratio` or `phase_error` for this port-clock.\n", " warnings.warn(\n" ] } ], "source": [ "quantum_device = QuantumDevice.from_json_file(device_path)\n", "qubit = quantum_device.get_element(\"q0\")\n", "quantum_device.hardware_config(hardware_cfg)\n", "meas_ctrl, _, cluster = initialize_hardware(quantum_device, ip=None)" ] }, { "cell_type": "markdown", "id": "63f2e17a", "metadata": { "tags": [ "no_demo" ] }, "source": [ "## Setup\n", "In this section we configure the hardware configuration which specifies the connectivity of our system.\n", "\n", "The experiments of this tutorial are meant to be executed with a Qblox Cluster controlling a transmon system.\n", "The experiments can also be executed using a dummy Qblox device that is created via an instance of the `Cluster` class, and is initialized with a dummy configuration.\n", "When using a dummy device, the analysis will not work because the experiments will return `np.nan` values.\n", "\n", "### Configuration file\n", "\n", "This is a template hardware configuration file for a 2-qubit system with a flux-control line which can be used to tune the qubit frequency. We will only work with qubit 0.\n", "\n", "The hardware connectivity is as follows, by cluster slot:\n", "\n", "- **QCM** (Slot 2)\n", " - $\\text{O}^{1}$: Flux line for `q0`.\n", " - $\\text{O}^{2}$: Flux line for `q1`.\n", "\n", "- **QCM-RF** (Slot 6)\n", " - $\\text{O}^{1}$: Drive line for `q0` using fixed 80 MHz IF.\n", " - $\\text{O}^{2}$: Drive line for `q1` using fixed 80 MHz IF.\n", "\n", "- **QRM-RF** (Slot 8)\n", " - $\\text{O}^{1}$ and $\\text{I}^{1}$: Shared readout line for `q0`/`q1` using a fixed LO set at 7.5 GHz.\n", "\n", "Note that in the hardware configuration below the mixers are uncorrected, but for high fidelity experiments this should also be done for all the modules." ] }, { "cell_type": "markdown", "id": "1f05a132", "metadata": { "tags": [ "no_demo" ] }, "source": [ "### Quantum device settings\n", "Here we initialize our `QuantumDevice` and our qubit parameters, checkout this [tutorial](https://quantify-os.org/docs/quantify-scheduler/tutorials/Operations%20and%20Qubits.html) for further details.\n", "\n", "In short, a `QuantumDevice` contains device elements where we save our found parameters. Here we are loading a template for 2 qubits, but we will only use qubit 0." ] }, { "cell_type": "markdown", "id": "a572682b", "metadata": { "lines_to_next_cell": 0 }, "source": [ "## Schedule definition" ] }, { "cell_type": "code", "execution_count": 5, "id": "b277614c", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:30.473425Z", "iopub.status.busy": "2024-11-13T02:35:30.473220Z", "iopub.status.idle": "2024-11-13T02:35:30.477129Z", "shell.execute_reply": "2024-11-13T02:35:30.476448Z" } }, "outputs": [], "source": [ "def tof_trace_schedule(\n", " qubit_name: str,\n", " repetitions: int = 1,\n", ") -> Schedule:\n", " schedule = Schedule(\"Trace measurement schedule\", repetitions=repetitions)\n", " schedule.add(Measure(qubit_name, acq_protocol=\"Trace\"))\n", " return schedule" ] }, { "cell_type": "markdown", "id": "74b1b10d", "metadata": { "lines_to_next_cell": 0 }, "source": [ "## Measuring time of flight with trace acquisition" ] }, { "cell_type": "code", "execution_count": 6, "id": "a93ab46e", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:30.479029Z", "iopub.status.busy": "2024-11-13T02:35:30.478838Z", "iopub.status.idle": "2024-11-13T02:35:30.483127Z", "shell.execute_reply": "2024-11-13T02:35:30.482521Z" }, "lines_to_next_cell": 0 }, "outputs": [], "source": [ "def set_readout_attenuation_hardware_config(attenuation_dB: int):\n", " hwcfg = quantum_device.hardware_config()\n", " output_att = hwcfg[\"hardware_options\"][\"output_att\"]\n", " output_att[f\"{qubit.ports.readout()}-{qubit.name}.ro\"] = attenuation_dB\n", " quantum_device.hardware_config(hwcfg)\n", "\n", "\n", "set_readout_attenuation_hardware_config(0)\n", "qubit.measure.pulse_duration(300e-9)\n", "qubit.measure.integration_time(1e-6)\n", "qubit.measure.pulse_amp(0.1)\n", "qubit.measure.acq_delay(4e-9)" ] }, { "cell_type": "code", "execution_count": 7, "id": "10c0a437", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:30.484827Z", "iopub.status.busy": "2024-11-13T02:35:30.484664Z", "iopub.status.idle": "2024-11-13T02:35:30.488728Z", "shell.execute_reply": "2024-11-13T02:35:30.488121Z" }, "lines_to_next_cell": 0 }, "outputs": [], "source": [ "tof_t = ManualParameter(name=\"tof_t\", unit=\"ns\", label=\"Trace acquisition sample\")\n", "tof_t.batched = True\n", "tof_t.batch_size = round(qubit.measure.integration_time() * constants.SAMPLING_RATE)\n", "\n", "tof_sched_kwargs = dict(\n", " qubit_name=qubit.name,\n", ")\n", "\n", "# set gettable\n", "gettable = ScheduleGettable(\n", " quantum_device,\n", " schedule_function=tof_trace_schedule,\n", " schedule_kwargs=tof_sched_kwargs,\n", " real_imag=False,\n", " batched=True,\n", ")\n", "\n", "# set measurement control\n", "meas_ctrl.gettables(gettable)" ] }, { "cell_type": "code", "execution_count": 8, "id": "ed667dc0", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:30.490431Z", "iopub.status.busy": "2024-11-13T02:35:30.490264Z", "iopub.status.idle": "2024-11-13T02:35:30.648772Z", "shell.execute_reply": "2024-11-13T02:35:30.648089Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Starting batched measurement...\n", "Iterative settable(s) [outer loop(s)]:\n", "\t --- (None) --- \n", "Batched settable(s):\n", "\t tof_t \n", "Batch size limit: 1000\n", "\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "2d259e7e47ca471fb8220cc4642a8045", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Completed: 0%| [ elapsed time: 00:00 | time left: ? ] it" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
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       "Dimensions:  (x0: 1000)\n",
       "Coordinates:\n",
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       "Attributes:\n",
       "    tuid:                             20241113-023530-493-5de724\n",
       "    name:                             Time of flight measurement q0\n",
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" ], "text/plain": [ " Size: 24kB\n", "Dimensions: (x0: 1000)\n", "Coordinates:\n", " * x0 (x0) int64 8kB 0 1 2 3 4 5 6 7 ... 992 993 994 995 996 997 998 999\n", "Data variables:\n", " y0 (x0) float64 8kB -0.0003358 -0.001058 ... 0.0007684 0.0002685\n", " y1 (x0) float64 8kB 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0\n", "Attributes:\n", " tuid: 20241113-023530-493-5de724\n", " name: Time of flight measurement q0\n", " grid_2d: False\n", " grid_2d_uniformly_spaced: False\n", " 1d_2_settables_uniformly_spaced: False" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "tof_t_setpoints = np.arange(tof_t.batch_size)\n", "\n", "meas_ctrl.settables(tof_t)\n", "meas_ctrl.setpoints(tof_t_setpoints)\n", "\n", "# replace the get method for the gettable in case the cluster is a dummy\n", "if \"dummy\" in str(cluster._transport):\n", "\n", " def get_fake_tof_data():\n", " \"\"\"Generate mock data for a time of flight measurement.\"\"\"\n", " y = (\n", " np.heaviside(tof_t_setpoints - 200, 0.5)\n", " - np.heaviside(tof_t_setpoints - tof_t_setpoints.size * 0.7, 0.5)\n", " ) * 30e-3\n", " y += np.random.normal(loc=0.0, scale=1e-3, size=y.size)\n", " return [y, np.zeros_like(y)]\n", "\n", " gettable.get = get_fake_tof_data\n", "\n", "tof_ds = dh.to_gridded_dataset(meas_ctrl.run(\"Time of flight measurement \" + qubit.name))\n", "tof_ds" ] }, { "cell_type": "markdown", "id": "580cfe08", "metadata": { "lines_to_next_cell": 0 }, "source": [ "## Analysis" ] }, { "cell_type": "code", "execution_count": 9, "id": "54a3594f", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:30.650941Z", "iopub.status.busy": "2024-11-13T02:35:30.650629Z", "iopub.status.idle": "2024-11-13T02:35:31.428186Z", "shell.execute_reply": "2024-11-13T02:35:31.427480Z" } }, "outputs": [ { "data": { "image/png": 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fAGAVgDNKrXc05G+iDvJ3sAmA9gDWALgfmzEyViZxAMTY/eUS5B9wR0Th7pg+ajHKPGtplY3KfFtZraJgIZWykjq4CYD/AegMYDBknxxAPtTHQr6RnS2EOGq7+Pm2/QcRNQPwLoC+kB3QtcrsWMi3/QNhfVDKKBS8g3Ec5INPoo3y/UNEvSGP/X+Qg2i+p1rkEixcDyFEnJKtbDrkg1A4ZK1ACmQAuRrAJ5C1ETUs7Doajo29dB3yITzfdRdCpBFRIwBvA+gAGZy6mJXfmkTIc2NeA6IWBXks1lyD9ayAz0PeM89BDqxpampmqnU5CaCXEGKj+YpCiCgiegzyOEbhbk1PMuT9Mlf5TIFZMykhRBYRdYE890OQP+27EfI78p2yvvm+M4moKeS90AnA05DfhUTI2sx3IAcn/QqWM7hdgwzOEi3MM1fgc6TMvwngjo3tX4HtsXD+g4XmW8qLi06QNTx9IQPOcspsPYAbAA4DeEUIsdN8fdi4Z83EK5982dWUMaDaQiaJ6AmZkS4cwAg72zStv4yILgOYCnkfVIUT/fGEEGuJ6Djk9W6t7Nsb8tpchbzvBwL4ifv/MHb/IP4+MsZYySOi5QBqCCFal3RZGGN5EZEAMFII8VVJl4UxVnjcB4gxxooREUUQkSPJEzTgFLmMMcZYseMAiDHGitd2yA7q9lSD7WZIjDHGGCsC3AeIMcaK1xYA/6dkYDuP/H2rXCAzkT0OG5m+GGOMMVY0OABijLHiNQ6yQ3hvAEHI38FaD9kRfByAdfe2aIwxB0XBctIZxtgDiJMgMMYYY4wxxsoM7gPEGGOMMcYYKzM4AGKMMcYYY4yVGRwAMcYYY4wxxsoMDoAYewARUSciukxE/B1mjDEV/n1kjNnDPw6M3WNEFEhEccofaJcCbqYygOoogu8wEXkR0VQiOkFEKUQkVJ9rRPQnEXWwsb47EU0hor+JKEa1bhwR7SGimUTka2VdDRE9TUT7iOim2b5vE9E/RDSWiLROHpOGiNYT0So7y9UhomNENMbGMjoiWkxEu+xsqzcRXSWih63M76ycy+tmx2k6T88QkXmGuAIjaQARbSGiS0SUo+wvmYj+JaJviOghG+s/SkS/EFE0ERlV5U0nouNENNvGdfUioreU5dT3VA4RXSSin4iotpV1nzc7P7Y+aUQUYmEbdYjoe+U7lqNaPpmIjhDRu0TkYePY/YjoY+W+jFetH0NEO5Vjc2Rw20IjooFElEBE5a3Mr6pcy9NElKUqq56IzirnwdZ1vmf3ZVFcWwcV2e+jquzbHCz3ZbP1CvX7aqM8gUR0nohGFdUxMlaWcBpsxlRIvjEcA2ClECKlmHZTB0Cg8v/BKMHBL5UHm58AtAfwPYBvAaSZZkOWswOAbUT0jBDie7P1ywH4B/JhYw2AnQBuAhAAApTp4wEMI6LHhRAXzYowCcBHAH4D8DmARGVdAPAHEAngCwANIK+Lo14H0AvAHmsLEFENAH9CPixVsbKMFsAKAE8DiLGxrR4AfoT8TQ0CcMJsfm/IFNd7ACwBcAuAEfIclwfQHMAqALUAvGv36OxQruuPkOMK/ans+zqAbAA+kIOudgMwULmu68zWbwlgF4CTAL6BvKYGZbYHgIcAjAbQmYgihRA5qnVJOZYuAFYD+A5AqjJbB3m++wI4TkQNhRBnzYofCiAJwP8cONQ0AHFmZQ+DvCdvQd7bsbg79pI3gNoA3gLQlojaCbNUqMp9sQvyPK0B8IeyLYK8tjUBzAAwnIgeFULccaCcBaKU5Sul3OUB3Dab/xCAowBSIK93NIAsZbYrgKoA+gM4RUTNhBAlel+ikNe2hH0AYIOdZR6HvO8BFP731Rplu8sh78VQh4+AMXaXEII//OGP8oF8MBQAOhTjPnwhA4XfAGgKuI3hSjl1hSxLO2U7nW0sQwB+APAflNT5qnmfArgDoLaN9asCuARgjdl0DwCZAD60U8axkA/fNR08pmaQD/o3AOy2skyYcjynASQAeM/CMhoAy5Rt7QVwzcq2ukA+dO5UzmVHC8ucg3xAJRvlngYgHUCFIrjHeihl6W9jGS8A6yEfmj3N5u0EsBuA1sb6D0M+LD9nNr2Fsu+uNtZ1gxwU9gcL8961dq4dPPZFAC4D8HHgvn/Swrx1AC4ACLGxfgRksD6rsNfKxj5cARxU7mMBoIaFZb5TjtXXxna8lXP9y31wXxbq2jqxn+Eogt/HAux3CoArFu6zAv2+2ljnFeWapFj67eIPf/hj/8NN4BjLi8z+W+SEEMlCiDZCiCeFEMbi2o+DWgGIB7DF2gJCCAHga8g3jaaaK9NbyDEAPhVCnLOxfjSA6QD6ElEl1awmkA/CK+yU8WvIYKSxneVARD6Qb1rXQr65t7RMeQDbId/EtsPd2glzswEMATAQVs4PET0KGURsAPCClWUqQL5B/045l9YshwwKI2ws46gXAWwXQvxkbQEhRBqA1wCEQAZMpvK6QHnzL4QwWFkdQtYm/KMsq9YCMjj4zca6WZDXqam9AymAFgA2CRs1uEKIvyBrXvPsn4iCIAesnS6EsFrjJ4Q4DeAzAGOp+PqZzICsaXvNxjKdASwUQiRbW0AIkQpgIYA26qZsJXRflnbVIQMZkwL/vlpDRJGQteavQtbYMcYKgAMgxsq2wwCm2XkAAmQzIiBvc4sgyAej/Q7sZ6/y3+qqadchm72ZN4HKQwiRCVnL5EhTjy8g35y/iLtN6cz5ADgEoJ0QwlYTGw2AvsKseZiZcpBNhwbjbjMrc2kAPgSwzcZ2gLvnuJqd5RxRHQ5cFyHEZWW/6utigHzo3ejAfmKR/7rsAfCag/dUaFH1L1H5CvKa2BOL/OfadB4cvac9IL8HRYqIOkI24xwJK00vicjULO6KA5u8AlkTVEE1rSTuy1JLCYS7Ie+Ll8L8vlrahxfki4M/IGs6GWMFxH2AGANARO0h39KZOttvVT2XGSCbNe1Qlo0A8BeAukKI27CCiPwhm5h0EEKcNJu3HLIpSL628ETkCmAigD4AakA+5BQLIYTVt/RmwpT/XlNNMz0QxcI+00NcdQD7lH1fBjDB3opE5AcZaETbWW4wZI1NeyHEHWvP1UKI/wAMsLdfIYTdsinn7zdl/9aWyYRsGmOPj/JfazVSzqgGx64LIK9NbgCk1Eq+6OC6YQAOqCcIIf6BrBmyxwdAmr2HQ6VGqgLk3ysDgHg7NVOfO7Bv0/7Nz3VB72lHz7VdRFQRslZ0mRBiLRG1tbJogPLfRAc2a1rGH7LJZ0ndl3k4e22VdQr1+6gEKs8BeB6yhs0UwGZBNtU9COB/Qohrlrdg1TjIa5Jb61rI31dL5kD+Fo4QQoiif3fAWNnBARBj0hEAL0P+MXwXsibBVDORA9nR2CRQ+eTrlGzGX1muEmRncrUwWPj+KW/Df4fsTPsDgF+QNzGAyaOQtQ7m62sh+z4k2iiXU5RtvgLgshBC/aBnyqKVaW8bQoh05Y+1ZwGKMBGyr4nVt/JEFA7gSwAfmQLVB9BjsHOcTnCHA9dFkY4CXBclc1UkZFOwgngMsp+RJV5ENB/yITfYbJ6eiM5B9k1Z58Db9XyUppg1AbxjNsvhexryvAEFu6etlYsgm0Olw4GXAwpHjt/pc6RSlPclUIhrW9jfR8VSyD5CP0PWfiUo67vhbtKIvkTUSORP2mKRkgRlJmR/RofWUa1r7ffVfLl+AEZA9q2Ld2YfjLH8OABiDICQmZwWKhmk3gWwQQhhr2lIcegF2S+loxDiT2sLEVEqLP+BXwVgABE1MK91KgilT8RipUxPFHZ7Tu7bFcDbkG+pZwghoqws5wLZGfwC8j/Q3peU7Hleyj/dATSCDCRmCSFulFjBHKA8hA4CsADA35Dn3t7ylXG3X10AZHa6DpAP1+ayIV8eDIUMBi5AJgLQQ9bQBgPoBJmh7WXIlxW29u+Ju7UEWgDhkP1rDsKxZn730ssAngTQSum7Y4tpviMBmENB2j24Lwt7bXuhEL+PRNQYMvh5WQhh8b4hov+DfCH2PmT/P5uUNNRfQmZ4e8/e8mbrOvT7SkShkM065zlRq8QYs4EDIMbuL20BHLX1x92ORMi311l2lrOLiPpD/mH3AjDU0YCQiH6HzMQWZqsjup1tREKmX24A2exjho3FpynLNRZC6Auyv3tJacd/E3ebW5ochTyW4trvW5DBfeeC1pIpzbO+hExj/ReAgfaaLAEYBdkJ39xbQoh/LUxfApkqeZWwnmJ6IRHNAzCNiJYJIdKtLAfINOCPmk1LBdBECJFtp+wAACI6C5mxsZYjyxcEETUA8AmAd5VmhPbcApCB/LUolthd5h7dl4W9tm1RuN/HNgCSIYMOi4QQKUS0EMBUWxtSAvu3IAOlTwC86UxtpKO/r0Skg3yxFQPgTUe3zxizjQMgxu4vYcibRcgpQogxcG68nHyIKBgyOUE/yE68LwghjjmxiXKQ/Qac/n0hInfIh4opkE1T+gsh1thYvh2AyQBeFPnHk7kvCSHSlH4d/sokH8i+DC8D2EFEjylZ0nIRURVYP5+ZDr6d94dMEOFlZ7l8VLU+cyHTuL8L4H2hGv/HhtWQfRsIMrFEIGR2rA+IKEsIkacJndK8Z74D210Cec5qIW8TVXOmvh6ArNWoAuBZAPuVsXEuObCvcnAwM6TS98/fxiLXzM+bUkv1PWRyjpmO7EfpA3IUsj+bvQ7xfRzYXrHfl0VwbcNQiN9HZf1oBwLfywD8icjfRnPifpDBzyQhxGxHC1CA39epkJkWmwshMhzdD2PMNg6AGLu/+MF+R9hioTzkvgBgFuSD6jgAXzrwht9cGwBuQogkJ/ffGjKDVy3I5lVTbW2DiAIgm538AhtvdO9HQoh8fV+I6GsAFyEzf81XTe8EKym9VcvUsZWKXPEWgNnO9h9Qmt8sghzv6E/IYPOCo+sr13Cz2eSviOgEgI+I6BtbyURsMCXFqA4bAZAQ4gyAM+ppSg3DIch0wv0c2Fc4HE+Nfxq2a1w+RP7kA59C9j95ysGg0uQdAFuI6FvIoCEasjkZIIPdKpBNvlo4srESui8tsXZtC/v76AcgQwncbDE9GwXAQpIJ5UXNx5BjmzkU/BTk95WIWkE2A37dyZdQjDE7OABijJn60XwB+ZCzEbKNfIEeNJTsUo52wDft/wXIh+yzAFoKIWx2uFYeJr6CbK7zQkE6wt9vhBAxRPQrgO7I+5b8b8h+IVbftEM+oNrbvhFyTBKHEVFzyM7iOshak5VFeK6XQI611Bmy9sNZpuaVfs6uKIQwKA/2HxORRtgZj0vIMZMc1R22A6CD6n8QUW8AoyGbQTmS0lpdrq1E9AxkzZy1Tv+HIMeMWebMtlX7KNb70ooCX1sHNIWdjJIq1n7HekDWJrV3ZCMF+X1VahK/gxyzbI5DpWWMOYwDIMbKOCWYWAM5hsUrAD538CHX1Dbfw+ZSyG3io15HPe9VyAfhlQBGO9jMYzSAnpAPFG5W3uh6qeYlKIHZPaek3RUOntNoyE7guZRy/+7kbjPgwHVReMLydXkM8g3/GQC9hRBXHdkYEWkdqTVU+lokQdZ8qNcnB8+VxRoZR/cPea7dId/ymwJD9T1tr/+axXtaCHHYgX0DAIgoBDIr2VYAO63cxxWV/wYT0W3z2jIhxPdE9BNkCu9wyGxmpnIdE0LcIguptEvivizstS0iZwC84cByyTaClJYAzjoSsBbi93Uh5L05AEBlspzyWgfAV7lvrtsL5Bljd3EAxFhepje9trImmUZd97azrYJ8v5Ic2C5QtA8Iz0C+0XxGCOHMm3jTA3ElACfsLBui/DfPAwMRPQTgA8gmbGOcqF0Yr/zXkQEvoyEf5Ls4uO2i9g1kf6aJDiyrhQxeCusq5HVxRAiA9eoJyhvrRZBZulo72veAiHwAxBBRWysJDsxZOt6DRPS5EGKFnXVNtQO3VPt/AbLvSCMH9w3kfcuvvqftBUAW72knDYbsX/SEat/W/A1AEFEVIcR15cG6H4DNSqKAS8rHEtNvkfpYS+K+LPC1VRT29zEFQLoQ4hcHtmHLI3BsrCugAL+vRBSIuxno7KUfH6d83oKD/ccYYxwAMWYuAfLNaVUby0Qp/w2F7c7XrQuw/yjIPjT2NCjAtvNR3gJ/DOBHJ4MfQL41z4B8G7rVzrKmPgjmD4szIAeRnOhk06pBsDNqOuSDXTDk297zTmy7qKVAjlviiOq4e38VxhXI62ITEVWHPEfm1+U5AHUAPOxkx+t0yP4NrQDYDICUPlzeyH+8aZC1DfYekk2Dt6rXTwEQSUR+DvRBqw7gthAiWTXNdB5aQgZ/trSADCji7Cxny1LIPkO2PAz5kmC0UibTWDG+AH6EzMi3zs42giFTUKvHmSmJ+7Iw19b078L8Pl6BHCbAZk0UETWCbKpW28r9Xxn2f/MK8/t6EzI1tr1g72vIbIwroQwwzRhzkBCCP/zhj+oDYAtkYONmZT5B1nhsBaCzskwEZM2DgByzwnz+DgDfWpjeR1mnvY3yPQH58CLM9w/5UqOCE8daRdlOrwKeq9kA7gCoa2cfFwGstTDvIoA5xXQdlwPY7cByUQDes7PMu5DZu2wtE2bpegN4GnIgycftrF8fctDdl4vg2LsrZRlkYxlPyAfnawA8zeZ9BZluuCD7/kP5frjbWIYg31anAQgym/ce5Jv+UBvrayCzy0Wrv6eQLy4MkAk0bJXRW7n31liYt1aZV8XG+nWV+352cdy7Zvtqq1zLGhbmnVGuIdk5178C2Hcf3JcFvrbKvML+PjZTpve3c76WKb8LFs8r5IuyNx043kL9vjqwfbu/XfzhD38sf7gGiLH83oRs3nCGiNZB/pHJHbdCCCGUfiu/AzhGRL9ADuZHkCl+G0N2jp0F58dtWA8ZHP1BRKshkwIkQz6sBkEOHNkEsmN6DwvrfwtgIBE9LBwbCLW28t8GDmRGygHwg8g7fsf7kA/bx4loDeQb6pvKvPKQb3L7K8cwWb0xInJT5lcgopcdKOtWUbCMUiXtR8jU5FuJ6AfIh1Z18ypvyHTDgwGcQ9FktPsFst/B90Q0ArI25jrkNfSGDBS6Q96vg0X+cXRqA8h08LqcFkJsV/37NciO9+eI6EfIWgdTZjINZJ+WVpBvuP8nhDCvQfkEcqDMY0S0CjLtsektvBayedoTkN+DwUKVmlkIEU1EHwB4j4geB7AXwG3Ih1BA9o+pAtmvwh9AVwvHMxmyudlZ5Z6+omwDStlrQjY9uwx5/5ek/wPwE4BdRLQNspymfiCmc90ZsuO/eYf9krgvC3xtFYX6fRRCHCSiFQBWK+PwnIDM8iYgXx6Vg7wvHwMwSghhrZbIG3ebS9tS2N9XxlhxKekIjD/8uR8/kH+4foRsOpUGoJ2FZSIBbIB8W5ytfK4r67WCfMCKA1DfwrrLYeXNHWT62smQ2aJMD2+ZkG9EV0OOCdEJ8gFMY7buQshmSDUdPM6OkH94hQOfHFh48wrZkfx/AHYrx29a/iZk+/WPAfhZWM8X8m2wI/sWAP7PyWs4HTJwtbfcXwBG2lnmeQA77Sxj63p7KefomIVjToYcef5DAF5FeA+bxu7ZqtwrpuucopRjJSzUKqjOiaPX5U8L69dV7tVLkMGPevkYyIfYnjbKHgg5Vspp5X42rWuEfCHxO4BWVtbVQNZu7FWuh3rfWZAP+isBVLOxfz/Ih/X9yn1sWv+6cp9PhZUa4qL+QNYmx8NKzS5kELcdMtBUH6sR8jfjd8gxZCytWxL3ZYGvrbJ+gX8flfW1kIPz7lPOq/r3LQayBtPqvals4wLkgML2jrXQv692tr8TMnFMsd+H/OFPafuQENZecDDGGGOMMcZY6aIp6QIwxhhjjDHG2L3CARBjjDHGGGOszOAAiDHGGGOMMVZmcADEGGOMMcYYKzM4AGKMMcYYY4yVGRwAMcYYY4wxxsoMDoAYY4wxxhhjZQYHQIwxxhhjjLEygwMgxhhjjDHGWJnBARBjjDHGGGOszOAAiDHGGGOMMVZmcADEGGOMMcYYKzM4AGKMMcYYY4yVGRwAMcYYY4wxxsoMDoAYY4wxxhhjZQYHQIwxxhhjjLEygwMgxhhjjDHGWJnBARBjjDHGGGOszOAAiDHGGGOMMVZmcADEGGOMMcYYKzM4AGKMMcYYY4yVGRwAMcYYY4wxxsoMDoAYY4wxxhhjZQYHQIwxxhhjjLEygwMgxhhjjDHGWJnBARBjjDHGGGOszOAAiDHGGGOMMVZmcADEGGOMMcYYKzM4AGKMMcYYY4yVGRwAMcYYY4wxxsoMDoAYY4wxxhhjZQYHQIwxxhhjjLEygwMgxhhjjDHGWJnBARBjjDHGGGOszOAAiDHGGGOMMVZmcADEGGOMMcYYKzM4AGKMMcYYY4yVGRwAMcYYY4wxxsoMDoAYY4wxxhhjZQYHQIwxxhhjjLEygwMgxhhjjDHGWJnBARArU4hoMBGJAnymlHTZWckioi5ElEFEK4twm4FEFEdEl4nIpQDrNyCiJCLaVVRlYowxxko7XUkXgLF7bDuAlwGQ2fSKAN4G8DmACxbW21LM5WL3v+YA3AG0KsJt1gEQqPx/MICr6plENBzAH0KIWCvrRwLwLeIyMcYYY6UaCSFKugyMlTgiqgEZ+LQTQuwo4eKw+xARNQewCMDPQoi3i2ibvgB+BpAOoJsQwmg2XwAYIYRYamX96gBWAzgphHihKMrEGGOMlXZcA8QYYw4QQhwA0KiIt5kMoI2dxcxrK9XrXwHwSFGWiTHGGCvtuA8QY4wxxhhjrMzgAIgxJxFRRyK6SkQuRORFRK8R0UEiuk1EP5ot601EbxLRISKKJyKjklThtrLOVCJys7EvHyKaSUT/Kp3dTUkZ0onoIhF9RkQBVtatSERfEtFxZXnTuglEtI+IJhKR07XAJA0mom1EdI2IslVlOklEi4koyMb6GiIaQUR7ieiGqlzZRBRNRD8QUQMr67oR0VvKubulrJdBRFeI6BsiepiInlCSCmjM1n2eiP524Pgsrq/Mu0BEXSxMDyaiVUQUYyGBRpZyXoZa2d9yInpP9e9aRJSpNH8DgCVm2xtqtv52IhppZdu+RPQxER0homTVNpKVaR8rzfAsrfs8Ef2tXO8hyvU23cPpRHSCiBYSUaCl9RljjLH7FTeBY8x5VQBUBVANwFoAlSGTJPwG4HfTQkSkhezf0RLABgAbASQBEAD8AEQAmAagCxE9Lsw65CmB0SFlf98B+AlAijK7HIC6AIYDaElEj6rXV4Ki0wBclHW/hexnQgD8lXVnAXiCiLqZ79uOdyETRuwA8DWAOwCyAXgACAPwDIB+RFRXCBFnYf2vATwLYD3kebulnBMPALUBtAWwg4gaCiGiVcdEyvItAfwAYBOARACekAkEHgfwL4A1AKpDvuBR96kJBRDuwPGFWFkfAGpAXo9cSrlWQV7PJQDileMx8QXQDsAKIooRQmw322YY8v4WX4VM1OEOYB6A7wHsVeYJyEQeauGQ92IeROQOef9UhbwHfsTd+8dHOZaXAfQhooeFEBlmmwhVllkJoA/kvbwYwE0Arso+n4a81hFCiHjzMjDGGGP3Iw6AGCu4hQB2AZii9OUw9wjkw3xvIcQGSxsgomWQD/V9IR/c1V6CfBCvL4Q4b2X9xwHsBNAYwGHVrP+DfEitK4S4bmXdFZBBWxflv3YpQdmrAOYKIV6xssx0AGeVMrxsNq8JZPAzXAjxjZX1fSGDgAEAZqtm9YUMcqwmqiCiTgDWOXIsRagyZIDTRwix3tICRPQhgGMABiF/AJOHECITwFfKevMAbBdCfFWAcpnun4ZCiNNWyvUJgOOQ1+kTC4sEQwZ8lYUQiRbWfxfAGciA+GXz+Ywxxtj9iJvAMVZwGgDjrQQ/gKx9+Q2ypsIiIcRWACcBPGZhdhsAv1gLfhS7ALwJwDzIaQtglbXgR/EHgFMAOtlYxpwnZM3SbGsLKLU+38LyMT0OWeNjdSwd5XyOwt1aD/W6R2xl6RNCbIGshbmXqir/tXqdlBq2t6CqIbwH2gD41VrwAwBCiLMAfoHtRAzPWQp+lPUTAHwDeb8xxhhjDwSuAWKs4JaYpy1WE0LshKydARG5Qo41ZCmjVzxkMyhz1WG/tkAA+NjCrDDYCDJM6xLRZSv7trbOHShZx5Q+MoGw/DuSZGW71QFcs3XelP38aGFyGMzGybHiuAPLFKXbyn/9bS0khNhc/EXJoxpkM0V7rkDWAlpyQ8k0Z8t/AKoTETnZlJIxxhgrERwAMVZwp+wtQERPAvgIQD3YrnHdaWGaL4DUghUNvgA0RFTFznJZkM2cHEZEdQDMgXzrbzWBg41yFeaYrjmw3L1+CI8CEAPgbSKaDCDBrAzZAOJLIDjww90+P7akKMtaYnBwfU8AWgA5jhWNMcYYKzkcADFWcNaavgEAiCgCsuP4dsiAIQH5O9UDwKQiL5n0kfKx509HN6h0rP8V8qH+dQDRsPzQ2xllpE+IEEJPRM9DNvv718piGUT0A4BXhBBJ9650jDHGGDPHARBjxWckZI1FNyFEtrWFiGgQzDKLFZH5kP187LFbk6XSGbIZWy0hxAVrCxFRJSe2+cATQmwhouqQ2fXMj90FQC0AUwCkoYwEhowxxtj9igMgxopPOICjtoIfhbXvYTIA7wLuOxXAOSHELwVc35pwAEm2gh9FcRxTUiHWdWbfBfpdFEKkQaadtoiIfCAz4DkTAKVDNi8riBQ4drw+kOeWMcYYKxM4CxxjxccAO98xkgORWsvAdQUWxncxW5+I6FULNS5XcDc7ma31PyCiBfaWU7F7TIoOVqZfARBqaZBRs3L1I6LmZpOjIMemKagoAH7WBv5Uae3MRpWBS19wYNFoAJWUcYMcFQUHrqONdcMcWK465HVhjDHGygQOgBgrPhcBNCMii2/wleDnc+RvMmWyA0A3IqptYx+PQaakDjGb/jeAoURkrXM7iKgiZDM9ZwawvAjAh4gaWdkmEdEwAL2trP835CCuz9ooly/kODjmabR3AmhERG2dKK/aP5BJHyba2Hc/yME9nfEIgEXK4LO21ITMgOdMMoQ9AIYQkb+TZQJkivSuStIKi5R76ynI68IYY4yVCdwEjrHiswDAOAD7iWg9ZBIEQKZLrgqgB4CbADbDclOlBQBGA/iXiFYBuIy7GdTKAagD4EnIZlfmne+nQw66eZ6Ivofsi5SpzPOA7HPUFzKBwddOHNMWyHGL/iCibyCzn+UA8IIM5J6ArKVZDOBF85WFEIeVwV+/JqLuAI4CuAOZNc0Dsq9MW+XfP5mtvh4yKNyqHNM5yGZt5gHFo5YKLoSIIaKPALxLRK0A7Ie8Jh5K2dsBeAhyHKGXHDkZii2Q12UHEf0KWdOjLpMOMvh5AcCnTmwXAN6FHBD2nHLMVwH8IISIcWDdeZDjKZnun0u4e/94Qx7rYKW885wsF2OMMfbA4gCIMekW5GCisQ4sew0ycEm0tZAQIoqIHgPwHuSDqKmmJxmyJmWu8pkCC82chBBZRNQUwP8gkw8MguyvAchgJhZyrJ8Z5rUKQoh4IqoHYBqAjpB9dzyU2WnKupsAzBZCODK2jmm7OUTUCcAHAPop5dYCyIA8L39AZp6rr5TZkhGQg5w+DxloBCrTDQDiIGs93jcvlzJuUWcAr0IGb09BBoLOeBdynKDxkAFJZchzGaOUvQdkYNkVljP2XYJZKm4hRJyS7vwDyOtsXuuWAxm4zIa8F8xFmW9Tte3rynWcATlgbTXIoG2FarErkGPxmK+bQURNAPwf5D0wEHfvnxTIgHoB5P2TYWH30coy9lxXymBzbCfGGGPsfkE8bh1jrDQhouEAlgFwEULwuDSMMcYYy4P7ADHGGGOMMcbKDA6AGGOMMcYYY2UGB0CMMcYYY4yxMoMDIMZYaRMLmViAO+UzxhhjLB9OgsAYY4wxxhgrM7gGiDHGGGOMMVZm8DhA9xgREeTYIyklXRbGGGOlhg+A6+ZjgjHGGMuPA6B7rzKsDHrIipYn5IifAOAFIL0Ey8IYY/dAFchBfRljjNnAAdC9lwIA0dHR8PX1LdAGhBBITU2Ft7c3ZIUSs0SkpgIhIQCA2OvXAS+vEi7R/YnvJ8fweXIMnyfHFOV5Sk5ORtWqVQFuWcAYYw7hAKiE+Pr6FioA0mg0/IBhh9Dc7eLm6+vLAZAVfD85hs+TY/g8OYbPE2OMlRxOgsAYY4wxxhgrM7gGiJVeLi7Qjx8PFxcXkItLSZeGMcYYY4zdBzgAYqWXqyuy3nsPLt7eADcxYYwxxhhj4CZwjDHGGGOMsTKEAyBWehmNoP/+A6KiAKOxpEvDGGOMMcbuA9wEjpVeGRnwfvhh+f+pqZwFjjHGGGOMcQ0QY4wxxhhjrOzgGiDGGGOsDCM5EFFlABF+fn61PDw8/HQ6nRePT8QYexDl5ORkZGRkJCcmJl4EcArAVSGEUC/DARBjjDFWRhFR04oVK3aqUqVKjfDwcL9GjRpl+/n56T08PHI0Gm4kwhh7sBiNRmRkZOhSUlJcjh071ubixYspMTExV4hoO4DdpkCIAyDGGGOsDCKilpGRkSP69u3r1a5du9hHHnkkWqfTCftrMsbY/c9oNOLff//13bFjR601a9bU/OeffzyIaKsQQnAAxBhjjJUxRNQiMjJyxKhRo7SjR48+w7U9jLHSRqPRoGnTpslNmzZNDgkJCZk7d+6wf/75BwC2cADEGGOMlSFE5B4WFjbg2WefdR09evRFDn4YY6Xd008/HZOZmRmalJTUh4gO8q8eK710OuhHjIB48UVAx7E+Y4wpaletWrVy//79ozn4YYyVFf3794+pVq1aBQAR/FTISi83N2R9+ilcvL0BzmZUpqUZDPDSaku6GIzdF9zc3B5u1KiRNiQkJKuky8IYY/eKt7e3oXnz5sZ9+/Y14lc/jLFSbVXcdfQ7dRQ7E2+XdFEYK3FEpA0ODm7StGnTxJIuC2OM3WvNmjW7Vbly5focALHSSwhQQgJw8yYgOLFRWfVtXCwAYH7M1RIuCWP3BXcPDw/PSpUqZZZ0QRhj7F6rXLlypoeHhxs3gWOlV3o6vMPD5f+npgJeXiVbHsYYK3nurq6uOm9v74ySLghjjN1rvr6+OS4uLjquAWKMMcbKDg0RkVar5WpxxliZ4+LiYiQi4hogxlipsifpDn66GYfJodVRydWtpIvD2APv9u3buhEjRjz+999/18vKysrzpdJoNMaKFSvemTRp0l9jxoyJKqEiMsaYUzgAYozdt6IzM/Hr7ZvoX7ESyru42Fz2pl6Pn2/F46ebcQCAOdf+w8zwWveimIyVasOHD29769Yt73///XdJaGhonr5DRqMR3333XZXx48f3q1+//jetW7e+U1LlZIwxR3EAxBi7b024eAYZRiOiMjPwoY1gZkbUJexNTswzLSUnJ8+/ORE6YwWze/fuev/+++8i8+AHkCOtDxky5Nr69euPrVixolbr1q3/KYkyMsaYM7gPEGPsvpVhNAIAzqSlWl3GIES+4AcAjOAuDowVhYyMDPewsDCbWeNatGhxjYj4S8cYeyBwAMQYu+8ZbM2zkuLcWMofxf7LzMDKG9eRZrB1dhgrPE9Pz8xz58552lpm0qRJFxYtWnTA9O/IyMiB27dvr2Bt+fnz54d36tTpSfW0GTNm1O3Xr1+7Z599tlXlypVf9PX1fc3Pz+/VunXrDl28eHFYVFSUe9u2bbsHBwe/6OPjM8nHx2dSeHj48z/88ENl8+2HhoaO/PXXXytGREQMKVeu3Cs+Pj6TKlWqNPbJJ5/snJiYqJsxY0bdOnXqDPP395/o7e09qXz58q/07NmzQ3p6ep7nIqPRiHHjxjWpWrXqKF9f39e8vb0n+fj4TCpfvvyERx99tM/+/fv9zPcdGRk5cP/+/X4bNmwIat68eV9/f/+JderUGWaaX6lSpbG2zmWtWrWePXnypLetZRhjhcNN4FjppdMh+5lnoHNxAemK71ZPMxhwQ5+FhzxsPh+wQjDaGMfJWk1PKY9/MOb8aQBAYk42xlWpVsKlYaVZ27Ztjz/zzDPdFi9e/EejRo2SNRr7707T0tI8kpKSrHbcS05Odk1LS8uTUCEpKcnt999/bzJkyJC/z549u9jX19dgNBqxYsWKquPHjx9QpUqVuEGDBv37+++/b3Z3dzfm5OTQRx99VHvs2LH9u3fvPs/T09No2lZqaqrXm2+++cTnn3/+W/v27W9pNBrEx8e7PPXUUz0ef/zx/gCwatWqDU2aNEkGgMuXL3t06dJlwNSpUxt+9tlnR0zbefvtt+uvWbOm+eLFi9d269Yt3nTsiYmJutdff71Jz549h1y5cuVL9b7T0tI8Vq9e/dCvv/768CuvvPJ3v379NgUGBmarjtPX3rlLSUnh5zPGihHXALHSy80NmQsXAsuWAW7Flw1s1LlTePnCGRxLTSm2fZR1RhvzDFYiHfOgydk+QMk5OfjjdsJ9X8NyLj2tpIvASrlly5b9HREREdujR49n/P39XzPVvvj4+EwKCAgY36hRo4GbN28OLIp9BQcHJyxcuPCAr6+vAZB9jIYPHx5dp06dqHLlyqW+/fbbp93d3Y0AoNPpxNSpU8/6+PikbtmypaL5tsaNG7e3Y8eOt0xBS2BgYPYHH3yw48SJE7UWLVr0myn4AYDw8PCMl156afdff/2Vp7PhwYMHq4wdO3ZH9+7d49WBn7+/f86SJUv+8fPzS12+fHm+NxAbN25stHv37u/Gjh17RR38FMTixYvDAgICxsfExHBaS8aKCL9hYKyQbufIv237khPR0NunhEtTMnbcuY0KLi54uASO31oTuMLWAE2LuojT6Wk4nJKMKdXCC7m14qMhTu/Aipevr69h5cqVuwHsNp+XkJDg8tVXX4UPHTr0mb///vur+vXrW++w54CqVasmWJoeHByc6Ovrm2VpXmBgYOLly5d9AMSpp7ds2TLftpo3b56o0+lyHnnkkUTzefXq1Uu8c+dOnh+xtWvXbvX09LT6FiQ8PDzu3Llz5QBcUU/v0KHDqcIGPiajRo2KGjVq1OdFsS3GmMQBECu9hADS0gAiwMtL/reM+y8zA2tvxuHpwGAEF1Gt2H+ZGfgoWv7t/61BkyLZpjOs9gEqZAh0WqlZ2ZV0b7P6GoXAtju3UNvTC9XcPe7pvhlzVkBAQPbkyZPPHT16NOiDDz5o9N133+0qzPZcXV1zLE13c3MzuLm5WZzn4uJiyMzMzPc84+vrm295X19fg06nM1hqxufl5WXIycnJs5309HTNgAEDOh46dKhmRkaGu/k6er3etUqVKtvNp9evX99iIMcYuz9wAMRKr/R0+AQHy/9PTZVBUDF6EMKr1y6eQ5rRgPPpaVhYu16RbDNOry+S7RSUwVofoHyT7/0VyjIacTotFfW9vOHiQL8JANiReBufXfsPgGMBJbdjZsXp6tWr7n/88UfQyJEj/7O1XMOGDeM2b95c516V6155/vnn22ZmZuqOHDmyJCQkJF8N1NNPP/24pfU8PT0tBmuMsfsD/+1krIgU5+O13mhEttFWTxjHpBllS47/smxmtC1xcfospDvY96a4msBZcz49Decd7HfzaXQUply5gOU3Yhze/hln+/RwzSYrRocOHfKfNWtWG3vLERGEELk3o5ubW3ZqaqrVl6x6vf6BeP44duxY9ffff3+PpeAHAIxGY0G+gMJo4/c8MzPTtQDbZIw54YH4AWLsQRCdlYlTdsarScxxvkm4QQgMPnMcg88ct/qwXxBvXDqHnYm3C70d9V//29nZ+DH+Rp7jPJic5FRH/disLAw/exJDzhx3aHlrSRCs1QwVRo4QeOXSOUy4eNahAO1vpfncuoR4h/dhK+OdJfwjzopT48aNE+Pi4ipkZmbavNVOnTpVsWrVqrk/KJUqVbpz7NixAGvLb9u2rWZRlrO4GI1GjVartfilNBqNOHr0qNMpGH18fNKOHz9uscPkvn37/G/fvl3O2W0yxpzDfzsZKyKHUpIx6dI5xOmzcFOvx3WzWpbXLp7F06eP47/MDKe2m5yTg1SDASkGQ5FmJDuRloqZV6/YX9AOdQXER1cvY9mNGMyIugQAuKHPwttRF/HKxbMW103OycHR1OQ8D/3H02Q2vQwLb0iFELiSkY7b2XcDLGsBg/lk80DteAGy9mWrNnozWzb925+ciJHnThZZNjZnwzau/2HFKSwsLLNOnTr/9enT54nY2Nh8NRM5OTm0ePHisM2bNzd5/fXXj5qmjxkz5sjy5csf+/7770NMtR1GoxH79+/3e+qpp564evVqkWSNK24RERFXp02b9oh6fCCj0Yht27ZVaNeuXffU1FSnO+p17tz56PPPP//kqVOncttlJyYm6mbPnl2zf//+A93d3S3WNjHGig73AWLMzMm0FPwQfwNjKldFiFu+Pq92Xc/KwpQrFwAAa+pFwkurBQCcy0gHIPt4PFsppOgKfB85rtSAmRIIxNvpH/TyhdO4mZ2N16uGoX05OWaitbcyky6ew9WsDKQoQaCpf4zVPkA2QomhZ47DCMBXq8NrVcPQ3DffWIYWqYOtpBzZxH+aEuzNiLqEvhWDoBdGDAwMzrOeM0GK8wEQh0CseK1fv/6XkSNHtmnQoMHozMzMPNlTtFqtoVKlSglffPHFGnVa6X79+sXGxMT8OnXq1M5jxozxNxqNGg8Pj8xKlSrd6tix49nOnTtf+vnnn2urt+Xr66v38vKy+PDv5eWV5ePjY3Wer6+v3mxauru7u8U3Rr6+vhbffvj4+OR4eXnleUO1dOnS7YMHD+5cuXLlCQaDQUtEwtvbOz04ODhh8ODBR86cORPv7e1tvu9MPz8/qz9+ixYt2jt27NhH27dvP9yUWMHT0zOjatWq8bNnz/751Vdf7aFefvHixWFTpkzpcezYsUXWmuIxxpzDARBjZl6/dB4AMPPqFcyrWTd3epbRiGtZmQh39wDZ6Hehzj52M1sPL23eF4Sl7YFVfTSeGg3SVTU36hTNBiGgVf59NDUZt7OzcVOpydmblJgbAFk7t6fSLTcvtFYDZLQRSZhKmGzIwTtRF/MkGxBC5KnpAeS1P5CciH/u3G0yeCA5CX/cvpvoKdWQg8Wx1wAAT5QLQHkXq2NA2iScbALHXYBYcQsODtb/8ssvWwFsdWa9CRMmXJowYcIla/PHjRt3Wf3vt99++zSA05aWXbZs2T5r29myZctv5tOio6MXW1s+Li7uC0vT69evn3r+/Plv1NNCQ0Mzd+3atdHatgBcNJ9w9OjR1TaWh6enp3H58uV7Aey1NP/VV1/N829Og81Y0eMAiJVZmUYDDqcko7G3LzyUWhq1OH3eF21TLp/H6fQ0vBlaHW39y1vdrvrh+XBKMjYlxGN05aq507ROPrCqH4fNUztnGg24odcjzEK65Jt6Pdw0GvjqnP+a641GXMxIR21Pr9ygxZHyldO5IF05b0IIqM9qtioAeuvyhTzbUO/D2Xa5P9+6aaVcec9VkiEHRiHsjpszL+ZqnsAGAPqdOoocs8BkbUKeIUfyDNZqvqwz1Nv5Kf4GXDUatPD1R6Cr5X7RHP8w9mAJCwsbERUV9ZW1+QaDQePl5cVZ5BgrRtwHiJVeWi2ye/WC6NcPsBDgzL32H9777zJmX4uyuLr5g6WpWdcftxNwQ59l9U29+uH3q9hr+O12AtbcvKHarnOPrOqgx7xW4/VL5/Hi+dM4kpKcZ3pKTg6GnT2BgaePObUvk9nRUXjt0jmsirtud1l1YgZv1XlONxrzBBumLHaZxvytUjR0d1u/3XZ8+IzrWZlWl7eUY2lfcqLdbf52OyHfus4GNJpCRCXqPX19IwYLr0fj2bMn8OTxw9iVmH9MIg6AGHuw6PV6lzlz5tSwlFhi27ZtFTIzM90iIiKKplMhY8wirgFipZe7OzJXrIC3t3duO6E0gyG3T84O5WFyT1KiU5s9mpqC586exAvBIehXsVK++TkW2l7FZN2tTTI9sGYZjdAR2a1hUW/OvAbootKvaHvibTTy8b27P1XtlSO1HqbyZAkBP50uN3vZ2ptxGGbWX2lP0h0kZGejZ4Dsw6wODlJVSRoSsvM2gTfVjCXm5H+xqVXOyh+3E3DSRiY9NSFEnv2ZMwqBpUqTNJN4vR6/WqkxKiz1lTE/2wLA1cwMhCo1dUIIq039bDWB++DqZfzmn3dsIFvNMRlj95+PP/7458mTJ3ebMmVKX61Wm/sjRkTC09MzY9q0aZt0Ol1xZfJnjIEDIFaG/Bh/A8tuxOCNqtXRrpz1Jmx32X6wXBYbYzEAMu8/IqfdrVPQEiHDYED/U0dR2c0dr1YNQ5w+C22sNKuzVQNkopNjcGDqlQvw0GjxTNDdTvhZRqPFJn7mnjt3Eok5Ofg+ooHN5d77Tzbbr+/ljYc8PPPUAKkDr8ScHLioa4CUc2ApAPoz8TZerRqGC0pA5wgDABeyXomdbjRizc28zdS23bmFy05m4SsIS9dp9PnTeCfsIVzKSMdvtxPw2UN1EODighn/XYa/TofxVWQ2XXujPX11/RqeVl1fDn8Ye7AMGTLk2pAhQxaVdDkYK8s4AGJlxjJlMMq516IcDIBsq2IlQ1yOyP8Im616IiYAZ9PTYIAcO2iikiK6mruHxb486k7+eYOhu/+vJcKtnGwcUVI7dw+omDsvLluPI7eT7R6zKTCxNZaRejDWOL0eD3l4Wm0eliNEnofz4WdP4o2q1eGptRy0XMvKdKpNrjzPzr0kLc7gR1i5Tmq/3UrAgZQkAMA3N2KQmJODw6my+eLLIaHQENnMXgfIvkfq2jUOgBhjjDHncB8gVnqlpcHH1xek0QBpd5tTW2py9sutm9CbjTtj78HSQ6u1mIHMUkCgVwVF1losJVuoGQHMmsCptq0eE0gLIFNV/muZd8cgevH8aSyOvZabrtkeden1QmDUuVPYovSzSVP130lSBju1NjirQYh88z6OvoIsKyOgC1i+NtbEZGVh+Q37fZTuFWHl/9VSDXevcUJOdm7wA9ytObSVvc7kvKqmrLRlFWSMMcaKGwdArMzRWWg29UXMVax0oMO/mjtpLD78WxrAUx2caK08sLppNBBCYOvtWzivGlTTYKEJ3InUFIw8dyp3+rmMdKSrAqJzFpqSnXVwoE7zQ4rOysRn1/4DgDz7+DzmKqZHXcTC69EWt/Pl9as4ZmGw0RtWxga6lZ2d5zzZ8+rFs7m1KfeDPNn6rASFp1XXIFE1mCsgmwhuvX0rt/+V7X3d3f6/qcm4mO5400HGWMHNmjWrZvXq1V/w9fV9bdy4cU0KunxQUNBLxVnOyMjIQdu3b69QnPtg7EHGTeBYmaOzUsvw662beCG4isV5KRZqZ9w0Gljqgm9qaqemDoqILNcQGITA0dQUfKpkpTONTaN+mDYFQ29cPp9n3XPpaXn61ux3INuZiVEIh8eeMU86sC/ZegByQ6/HD6rsdyaWzg8ATL1yweJ0a/SFSDVdHPIGQPaX/y8rM8+/9UaRe+3t0Zvt4N2oi/jWTt8txpzRu3fv9tu2bWusnpadna0zGo1aNze3PGMEPPTQQ9eOHj26Oioqyr127doTn3rqqf1r1679696WuPitXr268kcffdRlwYIFa/r27Rur0dh+h2xr+eTkZB/z5X/99deKPXv2HP3SSy/9OmfOnH8LU9a0tDT3pKSkgg1GVghHjhzxGTt2bMczZ86EGQyG3M6nWq3WEBoaeuPjjz/e1qVLlzyZaK5ever+0ksvPXbo0KEaaWlpnkIIAuTgsPXq1YuaN2/ejnr16tl9g2c0GvHkk092CQ4OTlbGWWLMqgcmACIifwBTADwJIAB3WyjdBrATwLtCiDjLa+duowmAdwDUB+CpTDYAiAGwGMAyIYQ6IwsBeAnAiwDKq/ZpBHANwEwhxLrCHhu7t6yNw5NuNGJjQnzuv1MMOTiRmoL6Xt5Wx5qx1vzLXIYqcNCArAZAURb6qKhDDqPI27xNbUns3ZoYW9nRzK1LiEdHd8/cf9vqg5LmxHbLMiOE1Voga7It9B2zJsMslXiSgYcMYUVr/fr12wFsV0+bNGlS5MmTJyv9/vvvv1tax9PT0xAUFJRQqVKl/FW/pcDixYsbDR8+/O/+/fvHFsfy5cqVyw4MDEwICgoqkRTYM2bMqHvs2LFKa9asKXDwOnDgwD4tW7a8sHXr1k3e3t65P1R6vZ7mzJlTc8iQIU+fPn36y8DAwGzT9FatWg1r0aLFuV27di0PDw/PMAWK0dHRbtOnT49s06bNC2fPnv0yICAg28puAQATJ05s/Oeffzbt06fP7oKWn5UdD0QTOCLSAvgTQBqAtgAqCyEqCSEqAWgB4CyAPUTkaWMbTQD8BGAhgLqq9asCGArgKQAfma3WH8AzAJ4UQgSr1gkB8ByA94ioRREeKrsHbmZn420rtQ3q5lxGyJqWfclJ+VI6A7Kvj6MPueoH1r8Sb+N/FvZvqe9QqiEHMaqaghRDDkaeP5VvOQC4lpVlcbo9X9+IybPvczaaUyVZ6adUWvxXREkSjJBN+pxhKXugNebNLF04FTa7DwQGBmZfvXp1yRdffHGopMtSHOLi4vwbNGhwq7iWb9GiRWJMTMzCt95661zBSlg4SUlJbqmpqW4FXT8+Pt7lxo0bAV9//fVedfADAK6uruKNN944Hx4eHvPtt99WM02fOXNm3YoVKyb++OOPO2vUqJGhriWrWrVq1pIlS/5p3LjxhTfffNNmc8PVq1dXXrVqVevu3btzzQ9zyAMRAAHoDSBKCDFNCHFLqNrrCCGShBBzAfwKYLSNbUwDMEEI8asQIvdJUQhhFEKcAzAYQH8iClKt0xnAp0KIq+oNCekUgNkA+hX66FixO2OW2eyg2cChtuyy0ifDIITDY9akqx5YrfXFMVioe3n14jnMvHol99/XCxjk2LM/7e4L23UJ1itSY/XFs//7xZjzp4tkO29eOo/dDvTlUTMfzNYZbnaa4jDGCk+v17t4e3s7/BbI2eUfdBqNBsOGDdtpq2lgUFBQclRUlJ/p3ydOnAhs3rx5lK3ttm/f/vL58+eDrM2/cOGC58svv9z3s88+W1ehQgXuEMkc8qA0gXsYgL0q2W0AehV0G0KINCI6DKA2ANMT4LcAjtnYZgyAdnbKxe4Db12+AHjmTzHtCIMQuGmhBuhSZjqm/+dYZjVrqaLN92Mu2ryfiBPNpJyxwEbQYyKEwAonE0U8KL6Pi8WAwPxjOhVUsiEHi80GYbVngZVkEo5wtTEeEmP3UqtWrXqNGzfuwKBBg3J/LCIjIwe+9tprez777LOW//33X7Ber3dxd3fPqlu37n8rVqzYsnXr1qC5c+e2vn79ekB2draLVqs1REZGXvz+++//CA4OzvPju3379gqvv/56+ytXrlTOzs52AeQAou7u7lktW7Y88+WXX+4yX8eSq1evuo8ZM6bNwYMHa2VmZubWeri6uuojIiL+mzdv3vbIyMgUADh58qR369atR6ampnoPHjx4mFarNQLAs88+u2P+/Pn5arucXV6tVq1az65bt25t/fr1c9+uJSYm6l588cWW27dvfzgjI8Pd1EfGw8Mjs06dOlcjIiJuZGVlaZctW7ZPva2srCzNCy+88Oj+/fsfiouLK5+VleWm1WoNlStXvvl///d/fz399NMxALBnzx7/rl27Pp+VleVqNBq1Pj4+9QEgLCzs+okTJ76zdy5NAgICsu0d35UrVwK7du160fTvuLg43wYNGtj8A1S9evWUmzdv+lmap9frqXv37n379u37z9ChQ6/t3LnTckdeM6tXr648b9685lOnTt3z4YcftoyKigpKTk72FkKQh4dHZrt27U4sWLBgb/ny5XMD2ISEBJennnqq+4kTJx4iImEahFoIQTqdLmfAgAF7Fy9e/I8j+2cl70EJgKoAOG5nmesAQm3M9xNC2Htdn2cbQgh7QVcVAIXqqMiKkVaLnE6dcDVbD6OVsWccYa0GyJl+No7IEXlrgP5QUk+rpZRgX4+iPt77yYq468UWXN4LrhpuAsfuD2lpae7JycmuZtM83n777c4zZ878rX///tc1Gg3S09M1/fv379ilS5cBRqORFixY8Ev79u1vaTQaxMfHuzz11FM9Xn755VbqZArx8fEugwYNevr111/fMmHChDWurq65P5lRUVHuI0aMaD9gwIAnd+3atdFeOXv37t2jcuXKd44fP75IHTAlJibqXnvttaY9e/YcdOnSpa90Op2oX79+amJi4mc1a9Yc/vHHH//eu3fv/NldVJxd3vxcpaSk5Hk2Gzx4cPvbt297/f3338tq166dW8ORmZmpmTVrVu3333+/R/fu3fM9eE+ePPnJNm3anP3hhx82RkREpGo0Guj1elq4cGH4iy++OKBOnTpfNWrUKKVVq1aJSUlJn9rr41UYRqMR48aNa5qYmOg9dOjQ3FY1BoNBo9Vqbb4hdHV1NRoMBot/xAcOHNjO19c3/csvvzzgTHmSk5NdL168GPLqq692ee211/4ePHhwtKenpxEAzp075zl8+PDOQ4cObb958+YtpnXeeOONpm5ubtmnTp2aFxYWluft5NGjR30ef/zxUYMHD77Qpk2b286UhZWMB+W1oRawmHBLLQeFD+gc2gYRaYioAYCRADYUcp+suLi7I2PNGny5ZCGy3QrcrPmeMYq8CQjmKKmn1ayNFVTcdMpAq6XZ6niHn1FyTQ+rgUd8LL6YvKe4Bojd7/r27Xt44MCB103Nozw9PY3Lli3768KFC2GTJk3a2bFjx1umeYGBgdkffPDBjv3799dSb2PhwoU1GzRocPn1118/rw5+ACAsLCxz06ZNvx85cqRWTk6OzTcCFy5c8Lxy5UrltWvXbjOvLfL3989ZunTpfq1Wa1i/fn3RVQsXkNFoxM6dOxtu3LjxF3XwAwDu7u7G//3vf2datGhx0tK6LVq0uPDNN9/sqV+/fqrp3Lq6uorx48df6tChw9G5c+c+7Gg5hg4d2rpBgwZPF+QYDh8+7NugQYNnNm3a1HjdunWrzfsHFdSHH35Ye9++fXV+/vnnn+1l5LMkKSnJ56+//vph5MiR/5mCHwCoXbt2+oYNGzbv2LGjoVHVfD0qKqr8448/fsU8+AGAyMjIlNmzZ6+pUKGC3dpHdn/gv5oOIqI+RHSDiG4ASIVsGrdACHHZznpuRORr+gDwAWRzIv7cm0/qA9Jx/4Orl/GPjbTSQMklIfDT6vCiqn/M61XCSqQc1oS5u5fIfpv6+KKBt3eJ7FvNR6sr8e8Zf0r2c7+LjIzMV6UdGBiY7eXlldayZct885o3b56YlJSUJ1X0pUuXylWpUiXR2j48PT2N3t7eaSdOnLD5pTx06FC5oKCgW+ZBlFpoaOjNU6dOlbO1nXvh3LlzXh4eHpmmrGmWVKtWzWKNQ8+ePS9amg4AderUSYiOjnb4+FauXLn7+PHj3zu6PCCbp40ZM6Z5u3btRj788MPXTpw48XXz5s1t/pHbtm1bhQoVKkywN4bRX3/9VX7mzJndvvnmmx+DgoIKFHTUqFHjqrXmkkFBQXpPT8/MCxcu5CbXCg8Pv/Xnn3/WPHr0aL4U5gAwcuTI/9RNF9n97UFpApcHEdUG8BuALkKI8/aWt7KNyQBaCiF6OLK8kOmu1ynr6gDUBDCPiFKFEGttrPoWZOrtPFJTU1GQNxZKWZCaKr9jxNmfrDKdp2wnBtcsafaSKux0oGN9qIsrrlros1QY5g9YvvdBc7gArQ4JSpNArSMD7xSD1NRUZGeV/As/T9z9TShp/PvkmKI8T/fLtbfFy8vL4tsbnU5n8PX1zTfP19fXYDAY8jyjZGRkuGzcuLHF2rVrW1rbj8Fg0Lq6utr80U9JSXFxc3OzWaXt7u6enZqa6mprmXshMTHRxdXV1WZZrTUhc3Nzs3oevLy8sjMzM4ttnKDNmzcHjh49undQUNCdbdu2fWUv8DHp2LHjrVu3bs21tUx8fLzL4MGDB06YMOGPzp07528r7iCdTmfzPnF1dc2+ffu2K4B0AJg1a9ah3r17d2nbtu2InJwcrfp76+npmdG1a9d/zfthsfvXAxkACZm1LbyQ25hZiHVzAJwhohcAbAZgKwD6EMCnqn/7ALjm7e0N7wK+OTY9jHp7e/MDhg0iNRU+NWviCyEwcPsWZBUwCcKDpJG3D1r6+uOLQnSot+S2Wd8jfy+vAm2noourxYQSzmri7YtnK1XG+ItnAQAeLi5AMWeocyXKN/iqt7c3PDILlnSoipub06nLK7u64bqF4yStrsC/J0WNf58cU5TnyfgAveQprCFDhvy1dOnS/SVdDmbdrFmzar733ntPvfnmm7/aS+mt1WqNOTk5Nt8G6/V6jSmRhNFoRI8ePbo3aNDgyvTp0y2PCVFM/P39c/76669fLM07c+aM15NPPjlowYIFN8aOHXvF0jLs/vKgBECO9M3RKcsVhlPbEEL8R0SVichFCGHxDY2QKbdzn1hMf+iIqFB/9Ezr8wOGDUSg9HTc/71/ik7XChWRdQ8ehrQFvO+K8m6t4HL35azuHnwPdBYCICKCpoD7fiG4CqZFOZZF0GRk5bzrNPL2wZHUFBiEuK9+C/j3yTFFdZ7Kynl2d3fPTklJsfmTvmzZstBnn332qq0WFl5eXtl6vd7mM0VmZqaLt7d3iVfv+vr6ZmdnZ9ssq8FgKJIbwMPDI0ev12sLs409e/b4T5s2refGjRuXtW/f3u4YSJUqVUq+fv26zbc3V65c8alYsWISAOzdu7fc0aNHa+t0uhxTtjo1vV7vCgCVK1euc+3atYUFbWnjrLp166Z16tTp5M6dO0M5AHowPCh9gK4BsNcZsTKAqzbmJxKRvVekudsgovJEtMXO8gBQunuGsweKjgju9+AHvyAB0MJaEUW2fwHAX3f3mSDtHjTJMx981HQ8BQ2AGnv7Or2O+to+VykE7fzLA5BjSDFW2lWvXj3x0qVLVseDyczM1EyYMKF/enq6zYf4pk2b3omLi6tgK1lCdHR0QL169ZwbzMsJGo3G6EjNXd26ddPS09M9EhISrDZXO378uEOpn+2pXbt2YmxsbPnCbGPSpEnthg4dutOR4AcAHn744bj9+/dXt7XMX3/9Vb1WrVpxANC6des7mZmZH6ampn6SkpIyy/zTs2fPvUOHDt1+/fr1Ig9+GjVqNHD//v1Ws94QkRBKinJ2/3tQAqATADrYWaaDslyBtkFEXgCaADBV1yYDiFT6+1hbJxhAqrXaH8buNRfSwF1TqBd4Dqnq5o5Ib4v9QC0qr3NBNfeia4IoIKAhgq9WHmtl1+Kt55scWh1PlMvbJ9d0PAX9a6dVld9RtTzuNj3U0N1A1NIYUoyVNmPGjLlw6dKlkFdffbVRampqni9PTEyM24ABA9pHRERcsZdlrHbt2ulVq1a90bdv3w6xsbF5+vkkJibqRo4c+Uh2drbOmfTVzgoJCYmbNm1aPXvLaTQaPPbYY8d79uzZTd0hPycnh7Zv316hc+fOXa5duxZYFGXq16/f9aSkJK+JEyc2Sk9PL9Dz4eXLlysPGzbM4b7Zb7755tnbt2/79u/fv+3Fixc91EFhTEyM2+jRo5sfPny41ocffni4IOUpSlWqVLk9ffr0R6Kjo/P9wYmNjXX9888/67Vs2dK5AeBYiXlQmsBtADCZiKYB+BzAbaE0oFYyqz0LoBuAhja28TaAdUSUA2Cb0jQNRKSB7E/0CYA1Qog4QPbzIaI/AMwiov8TQqSoN0ZEIQAWAphXdIfJitPTgZXwvQOpjgNcXJCQ/WDGtC73qAaIiDA+pBqeP2cx+2o+Hz1Uy/5CBTC+SjWcTEvFwMBKDiWIKKimPn5o7uOLLXfyv9QsaA2Q+VWq7emFc+lpVpf/MLwmPFUBkxbEARC7p8qVK5fp6+ubLwWwmpeXV6avr6/efJqfn5/FH1UvL690d3d3iwGLr69vnr+7wcHB+p9++mnl66+/3uHrr79uazAYtIB88+7q6pr9yCOPnN24caPFPhrmNmzYsHHMmDFtH3744TFZWVm5QZCLi0t2RERE1MaNG1frdLo8Xyxbx2Hl2Kwuv3Dhwl9efPHFbnPmzOk8Y8aMjePHj7+krJPh4+OTpyn+qlWr/hwzZkyrVq1aPW8atNXDwyOzUqVKt5588snTVapUSUxJScmTCtNeWX19ffVeXl55OhS6u7sb161b9/0rr7zSoUqVKm0CAgLunD9//htApsE+duxYVXuZ4NLT0z06duw40lazzPbt2x/duHHjNkCm5d6zZ8+KsWPHPt66devn0tPTPYRqoNd69epF7dix42tbWfDUvL29s3x8fOx2rlSO3969nOdaLFy48O9evXp1r1279gSNRmNUH6NOp8vp1KnTkfHjx1vNvMfuL/QgpM8EACLyAzAVQFcAFXD3xWsigJ0A3hFC3FCWbQvgKwCNhRDJqm00AjANQH0ApjcpRgAxAJYAWCqEMKiW94MMnHoBUPf6FgBuAVgEmQrb4fY3SsCWlJSUBF9f55vAAHezB3EnY9tEairIR9ZS9Nq3C73CquMHBwKgqm7uiM6y+bt43/oovBbqe3mj2wnHxudt7uOHAykOJefJ47cGTRCv1+PZs7LStYaHJy5mWE4G4K3V4qd6kQCAZ8+cQHwRJEGI9PbBh+F3gyq90YieJ48UervWbKjfCK5E6Hbi39zGZr81aAJADlhracwmwPZ5+a1BEww8dRTJSvO9EcFV8FWs5ZeHdTy98FmNOgCAJ4/LF6FjKldFgIsL3vvvMiI8vTBbmV/S+PfJMUV5npKTk+Hn5wfIAb+TbS1LRBUjIyM/WrRoUZKjmbnY/W3EiBGPJicnu//44487SrosjN3voqKi3AcNGlTlQWkCByFEkhDiDSFEfSFEsBCikvKpI4QYbQp+lGV3CCFqmP8hEEIcEUL0EEKEq9avLIRoJoRYbB7IKPt8TQjxkGr5Ssr+6wsh5jkT/LCSVU7nWMbPe1GDYs/TgY6Pv/dO2EO5/59pNEJDBB8nm1YVhDrxQC0PT6vLqd+xFNXjsPlrG2f6JP36cGN8UL2m1fl1PL3QyKx5n+lYXS3sx2jjJVJND0/U9nQsY56lbduiJVUNkFNrMsYeFJmZmZopU6bYHLA0JydH4+Liwj8DjDmh5J/0GCsuGg1yWrfGiaZNIDSER32t9l3Mw81KANSjQkWL09+u9pDF6Wr/58AyagEutoefeEjVn6aZz93jKu8ig7yPwmshwtMLA+0EUkIVSjzs5VwaZY3qed1WvyNxDzroO/NDRkRo5GO99vXTh2rj1aphFrfvRvn3ZOvoNESY/VBtrKxr7fnl7kl0dTLw1kA2gwO4CRxjpZVGoxFz587t8u2331axlDQhMTFRd+jQoeoNGzaMK4HiMfbAelD6ADHmPA8PZPz6KyZfOQ8jZIIAR7hYeRMf4eWNTbdu5pn2VIWKaOHnj9Z+/tidlGh1my39/DH7odp47ZLNIREAyJoAUyBjjbrfiZYIH4fXwg29HjWUmpjqHp6YXaMObur1DjX7A2RTNWeoa4DcNNZrL4rl0dxso0XZ1IqI4G9WW0hEEEJYrKWxGQBBXp8KZtvrWcHUZ/nu2ub33bp6kehz6qjVbWuJcq8BB0CMlU6urq5i2rRpG1577bWeo0aN8jKNh2Oi1WoNLVu2PDVp0qQCDQrPWFnFARAr1YQQMP21sPGMnoe1MWV8tPm/LqbHzoEVg/MFQL5abW7/DkAGUKsjGmLQ6WM29++t1cHbwr7UzEv4sLcPLNUxWGoapiNCjuqB2Y0IWULgER9/7EvO3yWgZ0AgNibE59+2qhSOBpfq4kR4euH/wh7C06ePO7SuWnHXKlm7B1w1lK+9ma1+lKFusl8yESHC0wunlSQHY0KqWth23nPoYSUgNQ3I2sDLJ3dQ2RwOgBgrtSZNmnRh0qRJF0q6HIyVJtwEjpVq6mdVrYM9UHRWHuZdNZRn7Bng7sNvDU9PrKkXmecLtSqiIep4euHJ8gG50zwtNHNq5eef28EdkDUx6j489TzzN01z9HHX0oO8+WP1wloReKViMJ4ol3f4h+cqheDD8JoYGlTZ4rbVwZWt5lu2ympe0+IoW9vsWj4AH4XnzTrnQoTlderjh4j8iSIbeHnD10LAOTI4/9AaXXz9c9exV5anAyvhSVWzyYe98qcNV2d1c7URRKqv4qqIBlhauz6C3dxyr4GtfkiMMcYYy4sDIFZ6paXBLzwcq9t2hFt6htW3+uasPUwKAXxT52GsVj1Eq5f00mrzNE3TEeGzGnUwvkq13GkuFgIFQt6+JeV0Lnmao421UFuQlJOTb5ollmqA1GUUAIJc3dDS2wdElKccAwIrIdLb12qTQPW23Wyc26J6Nu9X8e74h0Yb26zn5Y0GZkkMPDVaBLm6wVdnuRbvIY/8YxRZSobRyccfs8JrYVr1GnfLYqEM7hoNhlUKsZucYWq1h1DFzQ3/qxaOcFUZXjPrg6TmrdWhspschsK0fa4BYowxxhzHARAr1TS3bsHvTiIA+bDoSAh0LSsTTbx989WUZAsBV40mz+CV+bKRObD9rqoaIQAgUJ4g41E/vzzN7dw0GrT3z1s782SFAHhrtfkG5zRnKejT2DgLzZTU7H6q/VsLHNUP94E2BiKdUi3c4nRLj+zfRzSwup1AVWKINKP9hEfTwu4GKZ52+jdZCqgslU9DhAgvb7uDzTr6w1rDwxNLatdHK79yCHBxxYKadbG8Tn10tHNdzfdjvAeJJhhzRFBQ0Eslte8ZM2bU7du3b7uS2r81J0+e9K5Vq9azxbX97du3V4iMjBxU2O3cr+ePseLAfYBYmaElQg0PT1ywMi6LiadWixnVa0AvBA4kJ+GDq5cBANlCvuu3OcBbuQr47XaCzdTHwRaCBXUwEermAVeNBm38yiHZkINgV7c8NUJ+Wh16BwShX8VKdmu1LAZANlYZH1INVd080EHVHM7WQJ9zatRBltGYp3yVXF1xQ69HO//ymFilmsVaL0v8dTr461ywqFYE3rx8HolmtVzqICbFRg2YKRRorsr6Z6npoZq3Ln9A42knyDGxVGNo8Zw5EH1XN0sn7qvVIdmQk+dYLG2Swx9WXNzd3Se7uLjk+8K5uLhk169f/8qXX375Z7169XJH8E1OTs7f1vMeSUpKcktLS7P+NqaEpKSk6NLS0vJXMxeRpKQkl7S0NHf7S9rdzn15/iw5deqUV9euXZ+eNGnS9nHjxl22t/zChQvDPv744/aXL1/+Wj191apVIe+//36769evVzQNrAvI+7tWrVrRn3/++Z88XlbpxAEQKzM0AKZWC8e3cbHYdudWnnk1PTzxZmh1fBV7DQMqVlKagxEe8y8HXJXLhLvnH+vGvAP8qMpVUd/LG019LD+wAkCkty/k2LsSIW+g4qc005qsqjlR1wi9W72G1VTd5iwtpQHBQ6NBhtGIJmbpoH10OgyrZLnPj0mYKgW3KdC7mpmRO61HhUA08fFFiJt7viZgoW4euKHPOxCqu0aDTKMREUpfp1B3D0yqWh3/uyL7/L5QKQQXMtLRxr88ZkVHAQCSDdYDIEt9vWzVAAkAo4Or4k52NnoGBOZOf9y/HA6kJNlND26xpshCGeo4OB6Q2oJadXEiNRWt/ctZnO9YnSZjBUdESElJmWU+PTExUffKK68079at26CLFy9+rdPpOA5n98TRo0d9unTpMjQzM9MtJSXF9pgRAA4fPuw7efLk3hqNRphPf+mllwZMnz5905gxYy67urrmzk9PT9dMmzbt4V69ej1z8eLFRZ6enpZaO7MHGDeBY2WCFvIPeZCrm8X+FXNq1EGImzveCauBumYPvN/VbYBFtSJQ0TX/76z5X3x3jQbty1Ww2NfEpIZn/kBKHShY6pCvrqHQOfHQa6m2SkPA4tr1MDm0OrpXCLSwlm0zzRIMAHkTR2iIEOruYbH/ywRVfyiTeTXrYmBgpTzz1E0CuwcE4q1q4XmCxGwLtS79KgahrqcXWvr5504zNREcYiWRg0lFV1fMrlEHj6uaGmqJ8GZodXS1Mv6TiaXmZ5Zq2R7x8cOU0HAsqV3P5vbUKri4om258nZr+vjJk91r/v7+OcuXL9+r0WjE+vXrHR+5mbFCOHPmjFenTp2eHTJkyN569epdsbd8amqqtm/fvv0HDx68y3ze559//nCnTp2OjB8//pI6+AEAT09P40cffXQsMDDw9jfffJP/Dxd74HEAxMoEe53RbTXzKufiglB3y60XCvrg+clD+bOUmVgKntQ1QDpH83lboQEhwMUVbfzL2z0vlvhZKJ+6/LYajqnHNzKduypu7hheKSTPcasf+NU/UpOqhkEDYEpo/n5FLwRXwac16uTJSDexSjWsjmiYLykCAHgpTdzMa8GcZuEmsFQDREqNYhW3QrdUUW3UehkYuxfCwsLijx8/7linNZZPfHy8i16v56pcBxmNRrz55pt/zJo166gjy/fq1atzrVq1rr/55psnzedFR0f716pVK8HW+qGhobfOnTtnuQqePdC4CRwrEwryoO+Igj531jdLieyj0+HVKmFw1ZDF5m0hqodmNwfH3LGmIPHThJBqmBvzn9X56vPrb2cQ19x1bNRkqbenDk47lKuAx/zK2Uy7rUZEFgM2APiyVgSOp6Xgcb/C/W2znCyhUJt0GD81sZImhAAR2f0p3L17d7k33nij7ZkzZ6rl5OToAICIhK+vb+qgQYP++fjjj49qVN/r5557roW/v3/mZ599dsTS9ubPnx++adOm2lu2bPnNfN6nn35aY9WqVY1iY2MDUlNTPQHAzc1N36xZs3MLFy78OzQ0NFO9/Lp16ypNnz69TVRUVGVTPxCNRmMsX7580ujRo3dPnjw53wjW33//fciMGTPy9B0xGAxaHx+f1L59+x5YsGDBQXvnZMOGDUEjRowYuHjx4h/79Oljc8Tq//u//6v/zTfftEhKSvIxGo15fgANBoMmJCQk32Bt8+bNC587d26bhIQEf/Vx+fj4pPXr1+/gp59++q/Gwd/S6dOnRyxfvvzRW7du+RsMBg0RQafT5YSGht547733tnfv3j3P/kNDQ0ceOnRoeWBgYLal7bVq1arXuHHjDgwaNOi6QwVQ1KtXL61evXoOjYn05ptvNrx48WLlkydPLrt9+3a+P0xZWVkunp6eNlOquru756SmptpsZnfy5EnvPn369P322283TJkypdXFixeDExMTfQ0Gg9bd3T2rWbNm5xcuXLhTfd/l5OTQU0891XnPnj31le8QgNzvEzp06HBk3bp1fzp6fZjzOABipZdGg4zISERn66HRWv8RaWShdsBRRTEgp+kh9ony1l+i1vH0wtjKVZGQnY1KFpriObc/5x+bO5evgKisDFS3UhOmrgGqYGdsn5dCQrE6LhbjqoRaXUadgMD8yjka/NhT0dUVHVwL/+La0h1gKYV2ceIKIFYSjEYjrly5Uumll146bG+5Pn36DO7ateu/GzZs+MX0UGw0GrFly5aKI0eO7O3q6mr44IMPTpjWSUtLc9NqtVZv7eTkZFdLHfaPHDnyUGJiouf//ve/Xd26dYszNW2KjY11HTVqVJvevXv3OHz48I+m5ePj412GDRs25KWXXto6derUNb6+vgZAPqD+8MMPlcePH983KCgo47nnnrtqWufw4cO+Y8eO7T99+vRNo0ePvmLaR2ZmpmbXrl3lX3jhhd516tS5PX78+EvWyv/hhx/W/uSTT56cOXPmBnvBzyeffFJr+fLlLZcsWbK+U6dON80fitevX1/pjTfe6GI+7cMPP+y8YMGCdT169IgzrWM0GqGUsaebm5vho48+sj0yN4Dly5dX/fTTTzvPmTNnzbBhw6JN20pPT9d8+OGHEUOGDBly7NixBWFhYbkP+KmpqV6ZmZlaABYDoLS0NPfk5OTC/TGzYcOGDUGLFy9ut3Xr1q+9vb0NlgIgd3f37LS0NJt/sDIzM3W+vrZbCaSkpOji4uIqDBkypNeoUaP2jho16g/TfRQbG+s6cuTIfPfdzJkz61y7dq38/v37v1QnEQGAy5cvezz22GPDFi5ceHns2LF2m/mxguHQkpVeHh64sm0rJny3AgYrD+7+Oh3er16z4PsogidPRyunugcE4rngEJtZ6BxRkNoJIsKYylXR2SyFt0meGiA7AdBTFSpiZd2HUc3KNQGAKm5u6Fo+AIMCKxX6eItbhKrP2JtVq6OSqysmW2iiVxzutoDjEIjdW1FRUe6DBg1qo9PpDH369Im1s6yHVqs1LF++fK+6RkCj0aBLly4333nnnT9++OGHpkVRLg8Pj6y9e/eu69279w11v47g4GD92rVrt125cqXyxYsXc398du/eXSE8PDzmo48+OmZ6aAUAnU4nBg8eHDNixIidixcvbqLex7x58+o/8cQTR8eNG5en47y7u7vxiSeeSJg8efK2tLQ0iy+YjUYjhg4d2nrevHntN23a9M2oUaOi7B3TihUrmk6dOnVLly5d8gU/1ixYsKDxqFGjdvbq1StOvY5Go0GbNm1uT5s2bcumTZusjzugsmvXrpDevXvvHz58eLR6W56ensYZM2acbNCgwaW5c+fWdahgVmzbtq1ChQoVJmzfvr3Qb6WioqLcR44cOWD69OmbmjZtmmxtuapVq945e/as5T9qd7dluxOoIiUlxeebb77ZOGnSpAvq+yg4OFi/bt26bZcvX6584cKF3A7A58+fL9+oUaOr5sEPAISHh2fMmzdvY506dayWnRUe1wCxUs2g/Gmy9tBfXudSqAfswqSF8dFqkWIw4BEf/0Jsxb6FtSIQp9fjnaiLAGw3PSsoD40Gj/r6QQg4VENl75wTEcZZSJhwP6rv5Y0Pw2uisqs7Al1l0oJ75f4ODVlpkJmZ6ebj4zPJfLqnp2dGw4YNL2/ZsmW1vYfy8PDwjAsXLiy2Nr9Tp05xr732WpH0s6hZs2aMtfK4urqKoKCgWwcPHixfo0aNGADo1avXjU6dOv1ocQUAjz76aNxPP/2UJwCKjo4u16JFC6ttgq29tU9MTNR16dKlR3p6utvBgwe/DgkJyXLkmOLj48u1bNnSZl8Vc7GxseXq1q171Nr8pk2b3rl586a/I9v64osvDphnUFOrXbt2XFRUVKGuX8eOHW/dunVrbmG2Aciau+7du/cxBai2ln311VePP/744yM//PDD66NHj75Uvnz53OZwMTExbh988MHDUVFRlZs3b263FiYwMPBmixYtEi3Nc3V1FZUqVbp1+PBh/5o1a6YDQJ06dW6tWLGi2Z49e062aNEi0fyetVcryAqPAyBWysnfbPNmX9PCauD7+Fi8WiWsCLZeMItr18PljIxCNcFzRDV3jzy1LbYSPhQUEeEd1cCjZY1MbV4SOARixcvd3T3LUhpsZ3377bdVZ82a1fbmzZvlzfuwCCFgMBiK5HnEVrM5AHBzc8tOSUnJrabWaDT49NNPay9durTlnTt3/IQQeb5URqOR/P39U9TTMjMz7fYdMZeRkeEWGRn57J07d/x69+6939HgBwCys7Nd/P39ndpfVlaWy3PPPTdkxIgRFt/TCSFQoUKFREe2pdFoxNChQx/fsWNH/fT09HxV99nZ2bq2bdsedaZ8xWXIkCGPCSGwYsWK3faWbdCgQeqKFSu+e/vtt9vOmjWrs16vdwVk37Ty5csnPvLIIxc7duxosQ+aOa1Wa/N9qJubW7a6yd/kyZPPHjhwIKRHjx7PZmVluahfCrq5uWW1atXqzA8//LDd3d2d028XEw6AWOmVno7ajZtguSEHb21an2dWc18/q4NLOqfgIZC/zgWNfRxLGFCUuN1r6cMN4Nj97OTJk95vvfVWry+//PLHfv36xVoaM8jLy+uNkijbpk2bgubPn99+5cqVq5944okE8zfxhw8f9u3Ro8czhd1PcnKy73PPPbdzzJgx51u3bv3c5MmTU2fOnHm8sNu15dtvv11RFDUJEyZMaHru3Lngv//+e1nNmjXTzc/RW2+91eDIkSO2xxq4B+bOnfvQ1q1bIw8ePLjE0XGpevToEdejR48frM0fMGBA2yIroIpGo8GGDRv+BPCn+byYmBi3bt269XrrrbcaWksCwgqPn4VY6SUEXKOjEXQ9FlRMj4gWhqO57xVHDRArGaZL+SDeh6zs+PXXXytHREREDRo06LqlB1Oj0ZhvUGlXV9ccvV5vNau+tQ70BoPB5g9cVlaWi4+PT24/pM2bN1dr27btyc6dO+cLfqxtz93dPTs9Pd2pF8hBQUE3Z8+efbRmzZrpmzdvXrlkyZJ2s2fPdqgDqouLS3ZiYqLV/eXk5OQro6ura/atW7fyJYlQr7N8+fKqjuz/n3/+qT527Nj9tWvXzhf8ALKWzHyaTqfLSUlJsXr9MjIyijwBwqJFi1qkp6d7NGzY8CUfH59J6k/dunXHJSYm+vr4+ExavHhxGABMmjQpcunSpdaz8QDIysrSubq6GmwtU9RCQkKyBg0adPTQoUM2y8YKhwMgViYU1yP/g/jcWVRZ1FjJ41CW3W80Go3RaMzbaicnJ0djqw/J119/XU0IkeeHKSwsLPHq1atWO9Tt3r27uqXpFy5cqGy+fxO9Xk9xcXEVmjZtesc0TUnpbLVsa9euDTOfVrVq1Tvnz5+32nn+yy+/rP7xxx/nHzFa0bRp0+Tvvvtu1Xvvvddt5cqVVawtZ1KxYsU7e/futbq/7du359tGpUqVEg8fPhxkbZ21a9cGz5w5s616mq+vrz4rKytfoGU0Gm1ev71794aZTwsICEg8dOiQxet39epV96tXrwZb215BnT59+tuMjIyPUlJSZpl/tm3btiQ4ODg+JSVllinxREJCgue2bdvylV3t2rVr5WvUqHHH1jIF0alTpyeXLVtmNcDRaDTCUmDJig4/CTFWCPVUGcDud69UqYZAF1dMfECSCzDHPYiBOCudQkJC4qZNm1ZPPa1z587XT548WX3r1q15HuITEhJcpk+fHvHZZ5+1Ng9CRo0adfH48ePhs2bNqmkaKNRoNOLAgQN+PXr06Hjs2DGLtScZGRnurVq16r1p06Ygdc1IbGysa9++fTuGhYVdN3VEB4COHTte3blzZ73Dhw/n6cgXHR3tNnHixEbr1q1rZL6PcePGndyyZUuj+fPnh6v3odfrafv27RVmzpzZ0d3d3WatQefOnRPmz5//0/jx4/v9/vvvNjONDRs27ND777/f6Y8//ggwBXdGoxHnzp3zHDNmTPPNmzdHmq8zZsyYf1evXt1q6dKloeY1RAcOHPB79913O3Tp0uWUenrbtm1jT548Wf3kyZN5/rBFRkZeXbJkSdP4+PjcNtuma9GrV68OUVFR+QKtvn37Hp0+fXrHPXv2+Jumpaena5YuXRrarl27p+31mbkXBg0adGHLli2NNmzYEGQeNOv1epoxY0bdK1euBA8ZMsT6IHgFVKNGjYQvv/yy2blz5zzN5yUnJ2t/+umnBo0aNbpW1Ptld3EfIMYKYGntejiRloqO5R6cAdA7lw+wmsaaPeg4BGLFw8/Pz6lUvAsXLvzlxRdf7DZnzpzOM2bM2Dh+/PhLTZo0SX7zzTd/Gz58eN+UlBRvIQS5uLhkly9fPqlevXrXfv7553WtW7cert5OaGho5vLly1dPnTq1w3vvvfeUwWDQuri45JQvXz7p0UcfvTBx4sTf/vzzzzxBkJ+fX1br1q1Pt2jR4tq0adPajB49ukJaWpqnEIJMA6GuW7duk3qdQYMGXT9w4MC+rl27Ds3IyHBXls0KCAhIaty48ZVVq1atHzJkSC/1Ok2aNEn+4osvfpwxY0b7qVOn9jIldTANhNqnT58D6jGAfHx8cry8vDLMz9XgwYNjbt++vendd999rEuXLuusndM33njjfHJysuuIESP6JCUl+ZiOJyAgIDEyMjLq888/3/Tuu++2U6/Tv3//2JiYmJ/ff//9jhMnTixnSu6g0WiMXl5e6b169Tr86aef/qte5/HHH78zfPjwv9u3bz9co9EYr1279qVOpxPz58//Z8CAAR3q1KnzUnZ2tg6QWQCDg4NvPfnkk6ebN28ec/jw4Tw1OtOmTTuZmprq0r9//0GpqalegEyoERwcnDBx4sSdX331VXP18tu2baswcODAIT/99NO37du3v2XtXKh5e3tn+vr66h1Z1tI16NKly80pU6b8OmHChO7Dhg3LkwBDq9UaqlatGvftt99+Z20wV1vbNufl5ZWnrLNmzTr81FNPBTZu3PglIhLqJAhardbQrFmzczNnzuT+P8WIzNvdsuJFRL4AkpKSkmBvcC1rhBBITU2Ft7f3fT9GSkkSqakgH5lhbeSh/VjS5JESLtH9ie8nx9yP5+lqZgZGnz8NX60WP9SLLOniALg/z9P9qCjPU3JyMvz8/ADATwhhM2AhooqRkZEfLVq0KKl58+ZJhdpxCfrggw/qbN68uc6ePXs2lHRZmPMiIyMHjR07dr8j4yAxVpSUMcyqcBM4xhh7wPFrLFbajBs3rslrr70WaW2+Xq/XuLq6OpUamt07devWHRoTE2MrCYPGw8ODrx8rMRwAsdKLCBm1a+O/8HB+E81KJdP4VhwAsdImMDAw/Y8//og4c+aMl/k8vV5Pf/3110O1a9eOL4myMftcXFxyPvnkk3rJycn5MsGdOnXK6/r164EtWrRwqKkbY8WB+wCx0svTE6d3/Y3/xUajkmuRZ9xkrMRxWM9Kq7feeuvsrl27wpo1azYWQJ4+EhqNxlivXr0rM2fO/Nf6FlhJ+vTTT7eMHj26x+LFi5/QarV5EkK4ublljR49enuNGjVs9pthrDhxAMQYY4yx+4pOpxNbtmz5DcBvJV0W5ryOHTveunTp0rKSLgdj1nATOFaqmZoGEb8rZ6URD4TKGGOMOY0DIFZ6paej3mOPY2HvAXDL4Jp2VvpwWM8YY4w5jwMgVnoJAY9z51Dt8mV+Rc5KNcFpEBhjrNDmz58f3qlTpycLu53nnnuuxcSJE/MNosvuH9wHiJUJ/KaclUam+5rDH1ZcKlSoMGHZsmWre/ToEWdruVatWvUaP378gYEDB15XT1+zZk3wjBkz2ly7di1Ir9e7mKYTkXBzc9O3bNnyzLx583aHhoZmqtdLTEzUvfzyy4/+9ddf9UyDp5rmabVaQ2Bg4O0xY8bsefXVVy8W1bGyojVhwoTGCxYs6Lpx48ZFXbt2vVnS5XFEcnKya1pamtX03Y5KS0tz02q19/VPc//+/dv+/PPPj7q4uFhNRx4UFHTr4sWLuX25ypUr90pOTo7N2GHIkCE7v/zyy4NFWdbiwAEQY4w9sDi0Z8Xrzp07fi+88MKAw4cPLzEPUtTS0tLck5KS8qTbXLNmTfDo0aMHvPXWW7+OGDHiir+/f54HratXr7qPHj26Td++fZ86ePDgGvW8du3a9S1XrlzaL7/88l3Dhg1TNJq7DVbS09M169atq/zWW291jY+P95w5c+bxIjpc5qQZM2bUPXbsWKU1a9b8ZT4vKCgoPTAwMKFcuXLZJVE2ZltKSor7yy+//PusWbOOOrpOZmame0ZGxsxiLNY9w03gWJnAwwAxxpjz3Nzc9O3btz/+1FNP9c7JyXHql3TatGntXn/99d8nTZp0wTz4AYDQ0NDMjRs3bjl37ly1hISE3Nqhn376KTghIcFvy5Ytmxs1apQn+AEAT09P45AhQ66tWLFizZIlS9oV+OBYoSUlJbmlpqZarDGZMmXK2ZiYmIUtWrRIvMfFYswuDoBYmcBZ4FhpxE3g2L2watWqv4UQNGzYsNbOrHft2rXA55577oqtZVxdXUWVKlXizp49622a9s8//wQ1bNjwik6ns3lrt2vX7jYAREdHF7rJEmOsbOEmcIwx9oDimk12L+h0OvHzzz+va9as2cjPP//8+vjx4y85sl5mZqZ7UFCQ3t5yJ0+e/FZdyxMTE+MbEBCQ5sg+/Pz8Uo4fP+5XtWrVeFvLhYaGjty4cePqd95555EzZ85UuXXrll92draLVqs1BAQEJE6YMGHnuHHjLqvXee6551oEBwenPvvss5cmTpzY+sCBA3VycnK0//zzz6LatWunA8C8efPC586d2+bmzZvljEajBpADtfr5+aU8++yz+2bMmHFSvU1Tk7GWLVtGr1q1qlFsbGxAamqqJyBr25o1a3Zu4cKFf5s3N1y3bl2l6dOnt4mKiqpsMBi0pv2UL18+afTo0bsnT558zvyYf/jhh8rTp09vFxMTE2haR6vVGvz9/ZMnTpy448MPP+x848aNBep1pk+fHrF8+fJHb9265W8wGDREBJ1OlxMaGnrjvffe2969e/d4ANizZ49/165dn8/KynI1Go1aHx+f+gAQFhZ2/cSJE98BQHx8vEvTpk2HX716dYl6H0ePHvUZP358u1OnToXp9frcZpPu7u5ZzZo1O79w4cKd5sdfqVKlsbt37142ceLE1mfOnAm5ffu2f3Z2ts7V1TU7IiIiat68edsjIyNTbN0DAKDX6+mVV15pumHDhqapqame6r5lAJCTk6Nr3LjxWfP1/u///q/+N9980yIpKclHfZ3Lly+fNGLEiD1Tp07Nt44lRqMREyZMaLJhw4YmyraIiODi4pJdq1at6Dlz5vz56KOPJpkfu/l1UqtVq9az69atW1u/fv1UR8pwPwgNDR25devWVe+8807To0ePVrt582Z5vV7v4uLiklO9evXrn3zyyZ/t27e/pV7ntddei1y+fHmbzMxMN41GYwQAIQSEEJqaNWv+9/PPP2+oWrVqlqNl4ACIlV5EyKxaBUkGAz8pslKNkxyy4hYWFpa5ePHin5577rmnmzdv/rX5Q1phmDdxMxgMGp1OZ3RkXa1Wa9Tr9XZbs6Smpnr16tVrYI8ePY7MmTNnT3h4eAYA5OTk0A8//FB5woQJfatWrfpDr169cpM9pKWluUVFRem6des2sFevXkc+//zzXeHh4Rmm8q5fv77StGnTnpo7d+7agQMHXjfVWBmNRvz+++8VR40a1cfPzy9r0qRJF0zbTEpKctu1a1fE+fPnK02ZMmVnnz59Yl1dXQUAxMbGuo4cObJN7969ux8+fPgn0zrx8fEuw4YNG/LSSy9tnTp16hpfX1+Duuzjx4/vGxQUlPHcc89dNa1z9OhRnzFjxgyYNm3az2PGjLls2gcAHD582HfUqFGd4+PjA9TnaPny5VU//fTTznPmzFkzbNiwaNNxpqenaz788MOIIUOGDDl27NiCsLCwzFatWiUmJSV9OmnSpMiTJ09W+v333383P+eZmZna1NRUL/W0nJwc6tmz56AnnnjixKZNm35VN42MiYlxGz169OPmxw8At2/fLtetW7f+AwYM+Hfp0qU7AgMDswGZLGPSpElNe/ToMejy5ctf2as1HD9+fLO///671rp1675r3rx5kvm998EHH9TZvHlzHfW0Tz75pNb333/f7Ntvv13TunXrO6Z1jEYjNm3aFDRmzJi+gYGBGSNHjvzP1r4B4O23366/Zs2a5osXL17brVu3eNO2EhMTda+//nqTnj17Drly5cqXnp6eufd/UlKSr61tpqWleaSkpBToeX7fvn1hDRs2rBMTE1MxMzPTjYig0WiM/v7+KV27dj362WefHXZ3d8/zXRw6dGjrXbt21UlMTPTJycnREhFcXV31ISEhN996662/n3766Rh7+01NTfXq3r17/y5dupz8/ffffwoLC8sE5L32wQcfRPTv33/wuXPnvgwICMgGgFOnTnl9/fXXbdeuXbuybdu2t9TX7fbt27p+/fp1eeWVV1quXbs2X180a7gJHCu9PD1x5NAhDP/tZ+R4eJR0aRgrcnfDeo6AWPHr3bv3jdGjR2/v37//wMTExAfuBerTTz99YN68eYdNwQ8ga7cGDx4cM2TIkN1ffPFFY/N1Nm/e3Ozzzz//ZdasWUdr1KiRoX7wWrBgQeNhw4btGjx4cIz6wVuj0aBr1643J0+evHXFihVNzbdpNBo1+/fv/2HQoEHX1YFJcHCwft26ddsuX74ccvHixdw/Wrt3764QHh4e89FHHx0zBT/qso8YMWLn4sWLm6j3MWfOnIc7dOhwbPz48ZfU+wCAJk2aJK9YseJX89qPXbt2hfTu3Xv/8OHDo9XH6enpaZwxY8bJBg0aXJo7d25dW+fYnrVr1wa7uLjkfPXVV/vN+4WFhIRkWTp+AMjOzta98cYbO2bMmHHSFPwAgL+/f85XX321X6fTGdavX1/J3v43bNjQdMmSJb88+uij+YIfa1asWNH0vffe++Pxxx+/o15Ho9GgV69ecaNGjdq5atWqBo5s6+DBg1XGjh27o3v37vHqbfn7++csWbLkHz8/v9Tly5dXc6hgVixevDgsICBgfExMjM2moQ899FDCzZs3/V544YWDhw4dWpKcnDwrJSVl1s2bNz9buXLlmj179tQYMWJES/U61apVi7lx44bvV199tT4qKmpeamrqrJSUlFkXLlxY8MILLxx46aWX+u/evbucI+Xs06fPkc8///ywKfgB5L323nvvnaxZs+a1L7/8soZp+tGjR/2Dg4MT2rdvf8v8upUvXz7nyy+/3N6xY8coR/ZrwgEQY4w94Dj8YffKRx99dKx27drXevTo0bWky+Ks5557zmrK7EaNGt2MjY3N9+BWvXr169ZSOMfGxpZr2LBhgrVttm7d+mZ8fHy+bTZs2PCS+g2/mqurq6hUqdKtQ4cO5a7Xq1evG3v37v3R2n4effTRuLi4uDz7iY6OLle7dm2rZatXr16aq6trnuaJX3zxxYFFixbtt7ZO7dq146Kiohx6uLXm9OnT5apUqWK1XJaOX5mera7hMhcaGnrz1KlTdsuWnJzs42xShvj4+HJNmjSxuk5ERMSdGzdu+DuyrbVr126dOnXqGWvzw8PD486dO1eoczxq1KiohISEz0NCQmw2B/viiy8OnT9//pvx48dfCgsLyzQFFq6uruLxxx+/s3bt2o2//PJLM/U6Z8+eXbl169ZfO3bseEsdwJYvXz5nwoQJl3r27PnPZ599FulIOW19Hx966KGbly5dyj0PjRs3Trx+/XrFNWvWBOv1+nxNemrXrp3+4osv2uxvaO6Be4PDmDNMD4bcAo4xxorGhg0b/qhfv/7wV155pfGcOXP+LenyOMrDw8NqszpfX9/srKwsV/Pp1apVs/qwnpWV5eLr62s1xXP58uWz1X1cTOw173Nzc8tOTk7OXU+j0eDTTz+tvXTp0pZ37tzxM6+5MRqN5O/vn6f/S2ZmpouXl5fN9NMajUaY/3vo0KGP79ixo356enq+ZhPZ2dm6tm3bHrW1TXvS0tJc3N3dbZbL/PiVshlt1di4u7tnp6am5jvX5oQQ5GjNj0l2drZLo0aNXiIii++ajEYj1alTJ8qRbaWnp2sGDBjQ8dChQzUzMjLczefr9XrXKlWqbHeqgMWkZs2a6QaDQZuYmKizlMXRkvr16yf8+OOPDtWG2fo+enh4ZCcnJ+een7p166aNGzdu67hx43oNHz7cW30ttFqtoWbNmtHLli373Zl+UBwAsdIrIwMPd+6MudnZmP/dypIuDWNFzpTdkGuA2L3k7e1tWLt27U8dOnR4oUWLFjfMBz91ltFohFnTImNOTo5DT6kGg0Hj6urqUH+hgnBzc3Powa84bdq0KWj+/PntV65cufqJJ55IMH+AP3z4sG+PHj2eKex+JkyY0PTcuXPBf//997KaNWumm+/nrbfeanDkyJHKhd3Pg+jkyZPz1E21Cur5559vm5mZqTty5MgSSzU0Tz/99OOF3UdRcnFxyUlOTnY4APLx8cnOyspysb+k82bMmHHSPKkIIIPK0aNHtxw5cuQT+/btW+/o9rgJHCu9jEb4HD2GWqdOQ2Mstr+PjJUYToPNSkqTJk2SZ86cuX7s2LH9Lly44GlpGXd398y4uDi7b+Xr168/RN1vICQkJPnmzZvettYxSUpK8mnQoEGhEzIkJye7uLm52c1Yp+bq6pqdmppq9UXy7du3XcybmTlCqVnKXW/z5s3V2rZte7Jz5875gh8AMBgM+do4uLm5Zaenp1stm9FohNFozLPeP//8U33s2LH7a9eunS/4UdbJtx8PD48cvV6vtX9UkqenZ3ZWVpbNl+/mx1+UiEgYbTwPWDqXLi4u2Tdu3LDanyYhIcHlp59+CnZk/8eOHav+/vvv77HWPM3SOQZgs8yZmZl2v2OW9OjRo2NycrLNa5eTk6P19fXNAWTmv5EjRz5ia/nU1FSdq6vrPR341tPT0zhz5syD58+fD3VmPQ6AWJnALeAYY6xojRkzJqp79+6HevTo0dfSg1uVKlXiv/766+q2tqHX6+natWtBderUyW260rx58/jjx4+H2Rt49a+//ioPAM6kvrXm6NGjAcHBwXecWSc4OPjOsWPHAqzN37t3b0BgYKBT29Tr9RQXF1ehadOmuesp6aitvudYu3ZtmPm00NDQO+fPn7datt9//72iefM8o9GoMW8Wp7Z37958+6ldu3ZibGxseWvrmIuIiLhz7do1q+WydPxFydfXN2Xfvn3+1ub/888/VcynVaxYMXHXrl1B1tZZsGBBzfnz5+dJduHp6anPzMzMF+gZjUaNVqu11pQOR48ezZcAwcfHJ+348eM+ltbZt2+f/+3btwvUZ+jUqVNVd+7cWcHa/KioKHclI1wOIIPD33//vaGtbZ45c6ZCSEhIkV+7d999N2LIkCFWxyHTaDTCvGmoPRwAMcYYY6xAvv76672enp5Zp06dqmE+75133vnrk08+6fLJJ5/UsvSmOTo62q1nz56datWqddWU7hYABg4ceL1ChQpJnTp16nbkyBEf87ffmZmZmu+//z5k2LBh/UaMGLGjMOU3Go34/vvvQ1auXNl67NixR5xZd8yYMUeWL1/+2OrVqyury2g0GvHHH38EfPjhh08MHTr0sKPbi42Nde3Xr1+H6tWrX69Ro0ZuprqOHTte3blzZ73Dhw/nSYccHR3tNnHixEbr1q1rZL6tcePGndy6dWvk/Pnzw9WdxhMSElzef//9OhMnTnxSp9PladYUGRl5dcmSJU3j4+NzmzAZjUYcOHDAr1evXh2ioqLyBQH9+vW7npSU5DVx4sRG6enpdp8p+/TpE5uZmek6atSoR8zvidjYWNe+fft2ND/+otSzZ89DI0eOfOrQoUO559JoNOLQoUO+AwcObPPvv//mu4+feeaZw7Nnz+64YcOGIPN7cevWrQGLFy9+rG/fvqfV01u1ahWze/fu2levXs3TzyciIuLqtGnTHlGfK6PRiG3btlVo165d99TU1Hx9rzp37nz0+eeff/LUqVO5KcUTExN1s2fPrtm/f/+B7u7uBXoB0KZNm7NvvfVWx6NHj+YLrk6dOuXVr1+/7p06dcrt4/foo48mGo1GGjt2bDPza52Tk0PffPNN1XXr1j06bty4YwUpjy3NmjVL2Lp1a8O//vqrvPk1MBqNeOeddxo99NBD15zZJvcBYmUC1wCx0siU3EPwQECsmPj5+SXbmq/RaPDLL79saN68+XDzZkv9+vWL1Wg0P7z77rvtZs6c+aRer899sCYi4erqqm/RosXZdevW/Wy+3R07dqx9+eWXH33qqacGp6SkeKnf7mq1WkPFihXvTJgw4a9XX331gvm61kRERIwzr0nRaDTGgICAO2+//favvXv3vqGe5+3tbfPBsl+/frExMTG/Tpkypcvo0aP9TQNkEpHw8/NLGTZs2L7XX3/9vPl627dvb2IaONREOR/ZzZs3P7d+/fpN6nmDBg26fuDAgX1du3YdmpGR4S6EIDc3t6yAgICkxo0bX1m1atX6IUOG9FKv06RJk+QFCxb8NH369Pb/+9//ehoMBq1Op8vx8/NLqVGjRux33323oXXr1mPV68yfP/+fAQMGdKhTp85L2dnZOgDw9PTMCA4OvvXkk0+ebt68eczhw4fzNPVyd3c3rlu37vtXXnmlQ5UqVdoEBATcOX/+/DfKPIO3t3eeAW1dXV3Fpk2bvn/55Zc7hIWFvZydnZ17T5gGgl27dm2e4wfs34deXl5Zfn5+dgOBefPmHRw/fjy6d+8+OC0tzVMIQe7u7lmBgYG3W7VqdfHNN9/csnnz5lrqdSZPnnw2NTXV5eWXX+41dOjQ3GBBqR1JfuGFF3abDw48cuTI/3bv3n22UaNGo4OCgm6dPn36WwBYunTp9sGDB3euXLnyBIPBoCUi4e3tnR4cHJwwePDgI2fOnIn39vbO8z1atGjR3rFjxz7avn374abECZ6enhlVq1aNnz179s+vvvpqD/XyixcvDpsyZUqPY8eOLbKVCW7hwoX7R44cqenUqdOzmZmZbqbvGBEJDw+PzC5duhz94osvcrMCurq6ijVr1vwwceLE9pUrV25tGlzXdC4CAwNvz5w5c4P5AKaWeHt7p7m7uxuszffx8clSN0fs1q1bfP/+/f/p06fPML1e76KuqSQiUa1atdjly5f/Ym+/asR/OO8tIvIFkJSUlARfX5tjW1klhEBqaiq8vb1BnN7MKpGaCvKRv1WvHT2E2Q2b2FmjbOL7yTH343m6la3HkDMnoAXwS4P74/6+H8/T/agoz1NycjL8/PwAwE8IYfNBkYgqRkZGfrRo0aKk5s2bF9lgpve78uXLv3L06NGFoaGhhe7IXhi2Bg691zw8PCZnZGTMLOlysMIJCQkZs2bNmtXOpvcuq6KiotwHDRpUhZvAsTKBH8NYacavsRhjakuXLg3ds2ePv61lbPUrYvePsLCwEbbmGwwGjZeXV4lnK3zQcADESjV9+fJIKudf0sVgrFgQh/aMMQv2798fPH78+E4JCQkWUxIvXbo0tEKFCsWSaIAVLb1e7zJnzpwamZmZ+Z7Zt23bViEzM9MtIiIizdK6zDruA8RKLy8v7Dt9EjPjrqOmh8UsrYwxVuYIIWym1S2NvLy80m31ObhXfH199Z6ensWS4lnto48+Oty1a9eQ0NDQiRqNxqhuZklEoly5csmzZs1yqs8EKxkff/zxz5MnT+42ZcqUvlqtNvceJiLh6emZMW3atE06nY5r8xykZKwUHACxUs30i8DvyVlpxn/5mBOycnJyDBkZGQ6P3VIaREdHLy7pMgDA22+/fRrAabsLFlL58uVz9u/fv66498OK35AhQ64NGTJkUUmXo7RITU3V5uTkGLgJHCvVOABipRkPhMoKICMrKys7MTGxQIMnMsbYg+zOnTuuer0+mwMgVnplZCCyd1989MIouGQVepw8xu47nGSNOUsIkZ2QkHD+2LFj/iVdFsYYu9eOHDlS/ubNm9e4CRwrvYxGlNu3D+UAaMpYe3fGGLMmMTHx3wMHDrROT0/XeHp68o8jY6xMMBqN2L9/v8eNGzcOcA0QKxP4RTkr7XhMN+aE01evXr2zbdu2iiVdEMYYu1f27dvnf/HixRQApzgAYmUCB0CsNOI02KwghBC3Ll26tHvRokUV9+/f71fS5WGMseJ26tQpr08//TT03LlzBwFEcxM4xhgrBQQ40GeOy8zM/H779u06AF3Hjx/v0qFDh1ucSpcxVtoYjUbs3bu33GeffVZ169at21NTU78WQnAabMYYe1CpAx5+cmXOEEJkE9HK7du3i5iYmNbh4eH1Hn30UX3jxo1vVahQQe/t7W0gIr6tGGMPFCEEpaWlae/cueNy5MiR8vv37/e4fPlyyrlz5/5Ugp8MgAdCZWUENxVipRHf1awwlCBo+bFjx/44duxYxK5du5oGBQWFu7m5eet0Oh1xmkHG2ANGCIGcnJwcvV6fc/PmzfNxcXEHAZwCEC1UnWU5AGKlmsHDA9lC8JMiY4xZoDwQXAdwnYj+TEhI8AXgAcAN/MvJGHswZQHIBJAorGQIcigAIiJfANEAvIuubACAbACPCSEOFvF2GQO8vPDn5Yv4LD4W9T09S7o0jBUrbqvECkt5UEhSPowxVmo5WgPko3ymANhXRPsOBvAdAE7DyYqNKe7n15isNOIWSowxxpjzHA2ATC8XjwkhdhbFjoko1GzbjBUbfk5kpZ0QgiMixhhjzAEOjQMkhLgO4AUAfxfVjoUQVwGMKMptMpZHZiYaDx2KaS9PgEuWvqRLw1iRUyf34DdJjDHGmGOcGQg1EcA3RNSpqHYuhPhaCJFWVNtjLA+DARX/3I7mu/aADIaSLg1jjDHGGLsPOBMA/QfZb+d3IjpLRGOJqKiTIjBWPLhlECuF+LZmjDHGnOdwACSE+FcI0QpAMwD/APgUwDUimk1EDxVXARkrCvygyEo7bgLHGGOMOcaZGiAAgBDisBDiWQChAGYDGATgPBFtJKIORV1AxooCB0CsNFLf1xwAMcYYY45xOgAyEULECyFmAKgGYDCAAABbiegUEY0mIh54hTHGihEnfWOMMcacV+AAyEQIkSOEWK00j3sEwP+3d99xclX1/8dfn+2bbBpJIAQCCYQAEVAEC6KCFQVsiP5UUFHwC34VGypYviiIClhAUCmKggVFUIqAiqJUEVDpJSGN9JCebLK72fL5/XHvbO5Optw7ZWd25v18POYBe+uZkzsz93PPOZ/zH+ASYJmZfcfMZhR7DpFimdqApOapDUhERCSOogOgKHd/2N0/BEwDLiJoGXrOzG40syNLeS6RJBT+SG2KpMFW/CMiIhJLSQOglLB73LkE3eM+SDBe6E4zu7cc5xPJaPRobl22lLc+9m/6RqtHptQeBfYiIiLJlSUAiphGkDVuJtAPPFXm84kM4eoWJHVCV7qIiEg8TeU4aJgN7lPAMcBa4AfA5e6+vBznExGpR8oCJyIiklzJAiAzayfo7vYpYH/gUeBk4Lfu3lOq84jE1t3NIf9zGl/e1s0/Lrm40qURERERkSpQdABkZnsAnwBOAcYCNwKnuft9xR5bpCj9/Uy97TamAnf3D1S6NCIiIiJSBQoOgMzstQStPe8ANgJXAj929yUlKpuIiOQwtAucOsGJiIjEkSgAMrNW4AMEgc9BBEkNTgOudfeu0hdPpDSULUtqkWkmVBERkcRiB0BmdjRwDbATcDPwWXe/q0zlEikp3SdKrdM8QCIiIvEkaQFaB/wY+Lm7LypPcUTKQ/GP1CJd1yIiIsnFmgfIzFoIurr9tFTBj5m1mtk1ZjatFMcTERERERHJJ+5EqJMJUlwfUMJzTwFOBA4s4TFFstCzcqlt6gEnIiIST5IucAacYGYvK9G5x5foOCKZjRrFTXOf5eq1qzmkvb3SpREpOU2EKiIiklzcAGgNcBuwW/gqlTuBZ0t4PJHtzOgfNYqernZly5KapKtaREQkuVgBkLv3AG8rc1lESm7wqbjuFKXGaR4gERGReAqeCFWk6vX0cOhnP8e4nm7+850LKl0akZJTy6aIiEhycZMgVAUzG29mF5rZE2a2wsxWhq+nzewyM9slxjEOMbNbzGxBZP9lZvaQmZ1iZo1p27ea2TfMbF5k+5VmttzM/mVmx5bvHUtR+vqYfv0NvOmWW2nsH6h0aUTKSvMAiYiIxDNiWoDCwORO4BbgSGCde/CTb2bjgJOA+83sIHffmuUYhwDXA58E7gy79mFmDcA+wAXAfsDnI7udFa57ubuvixzLCLLiXW9mS9390ZK9WSk5PSeXWmUoAYKIiEgSI6kF6F3AInc/x93XpoIfAHff6O4/AG4HTs1xjHOAT7v77angJ9x/wN3nACcA70lrSToa+Fo0+An3cXd/ArgIeH/R705EpAgKgkREROIZSQHQgcA/8mzzN3LPK5TzGO6+BfgPsG9k8a+B+TmOuQTQZK4iUhFq3RQREUlmJAVAuwMr8myzHNgjx/px7t6Z5Bjufom79+XY/gBgXp5jSoXpJlFEREREYASNAQIagf482/RR/HuKfQwzeyVwOnBEjm1agdbIojEA7o4XOGo5tW+h+9cLdx86UaTqKyNdT/FUez0N+EBVlK3a66lalLKeVNciIsmMpACoaphZO3AucCLwfndfkGPzLwFfS1/Y2dlJQ0NhDXDuTmdnZ6osBR2jHnhnJ2PD/+/v6xusMxlK11M81VpPqZJs2bKF1qZtFS0LVG89VZtS1pO+20REkilpAGRmY4FJQLe7Lw+XtUYTDpTwXPsCfwLe4u5zCzzGWcCr3P3tCfZ5M3Ap8CBwsLuvzLPLt4HvR/4eAyzt6Oigo6MjaZGB7U/7Ojo6dIORg48axe8f+Q/Xb1jHS8eOKbi+a52up3iqtZ7MDNwZNXo0Hc0tlS5O1dZTtSllPQ0MKM2/iEgSRQdAZrYX8E3gzcD4yPIj3P0+YK6Z9QPnufvPij1fSpi1ba8ij3F+3G3NbAJwOTAL+Ki73x/zHD3AYACY+qEzs6J+9FL76wYjh4YGeiZNZGODY9aguspB11M81V1P1VOu6q6n6lGqelI9i4gkU1QSBDPbDXgUOBT4FnA8QUpog8HeR+8E7gZ+UuSkoXHG5jSF2xVjh2OY2T7A/cCTwKFxgx+pvFTPeN0eiIiIiAgU3wJ0HrAReEmYQjoVFA1y90eAj4QtRZ8Abi3wXEuBKXm2mQoszrF+g5l15MkEN+QYZtYM3Aic4+7XxS2sVIGeHl72lf9jbE838847t9KlESkLBfciIiLJFJsG+2XA9angJ49/EKSMLtQTwBvybPOGcLuCjmFmo4FDgDmRxR8CnlbwMwL19THrF7/kbdddT0N/vgSCIiOb8oCJiIjEU2wAtDfBRKBxrAd2KeJcNwG7m9k5ZjbRIp2ezWysmZ0OHANcmeMYZwMXm9kxYXrq1P4NZjYT+BVwg7uviuxzCHBbEeWWqqDn5FKbUle2KwQSERGJpdgAqJXIAP88+gjm8imIu/cDbwTaCcYULTezlWa2EniIoHXp1ZGueEea2bwwM13qGI8AxwGnAs9E9l8K/IYgq9wX0069E3BRatssr3sKfV8yPBT+SK3StS0iIpJMKdJgx/39Lfp32t03EgQo6UFKpm3vAmZmWP4IEDvttbu/L0ERRURERESkihXbArSKYN6fOMYDq4s8n0hB9JRcaldwdasDnIiISDzFBkDzgYNjbntguL3IsFMAJLVKU8CIiIgkU2wA9HPg7WZ2mpmlj+8ZfCBpZu8G3h1uLzLsNFGg1DpXE5CIiEgsxY4B+hnwauDHwLfNbAnQFa77jpmdA0wDdgZ+CVxV5PlE4mtv54b77+WPG9fz0ra2SpdGpCy2Z4ETERGROIoKgNzdCSY5vQQ4ApgOjAOeDjfZTJBd7V53/3cx5xJJrKGBzt1354WOdmgotrFTRERERGpBKbLApTKrPVKKY4mUUuqpuDrASe1TG5CIiEgcJQmARKrStm0c+s1vMaanm1Vn/1+lSyNSFuoCJyIikoz6BUnt6u3lwCt/wvHX/JKGvr5Kl0akLExpsEVERBKJ3QJkZkUHS+4+UOwxRAqhLHAiIiIiAjEDIDObT5DgoChmttDdZxZ7HJGkFP5IrTL1gRMREUkkbgvQacDUtGVGkAb718DfsuxnwIuBk4E7CdJliww7BUBS6xT/iIiIxBMrAHL3v2ZabmY/Ax5w92ty7W9mtwN/As5LXEIREclKwb2IiEgyw5IEIQyg/gt8bjjOJyJSb1xtQCIiIrEMZxa4e4FXD+P5RAbpKbnUKg0BEhERSWY45wFaBUwexvNJvWtv5/o7/szfNm/k4Lb2SpdGpEwU3ouIiCRRihaguL++W4HWEpxPJJ6GBtbNmsXimXtDo6a8EhEREZHiA6B1wPiY244F1hd5PpGEgo5BekYutUpd4ERERJIptgvcPGC/mNvuB8wv8nwi8W3bxiEX/YDRPV10n3lmpUsjUhaa41dERCSZYluAbgT+n5kdmWujcP37gN8XeT6R+Hp7OfQHl3Di5T+hsa+v0qURKStXE5CIiEgsxbYAfR84CrjTzB4Fngc6I+s7gOnAS4C7wu1FKkCPyaU2bb+yFQGJiIjEUVQLkLv3uvvrgeMJ0lw3ANMirwbgHuDd7v56d9djeBERERERqZiSpMF29xsJusOJVCW1/0itU/uPiIhIPMoNLHVBA8WlVlkY3isAEhERiUcBkIjICKbYXkREJBkFQFIXdJMotU4tQCIiIvEUNQbIzM4lyPIW1yJ3P7uYc4rE1tbG7276A/dv2cxLWlsrXRqR8tBMqCIiIokUmwRhD4Jsb7mO/1KgDXgQ6C/yfCLxNTay6sUHMXfTBl7SWJJ8HyJVR62bIiIiyRR1V+juJ+XbxsxGA1cCuwKnFHM+kULpJlFqnasJSEREJJayjwFy9y3AycCLgVPLfT6RQdu2cfAVP+HdV/+Chm3bKl0akbJQDzgREZFkhiUJgrt3AzcDHxiO84kA0NvLq8+/gFMuuoSGfs3BK7XJ1L4pIiKSyHBmgVsE7D+M5xMRqRtqARIREYlnOAOg9cD4YTyfyCA9IxcRERERGN4AaBSweRjPJzJIAZDUKo0BEhERSWY4A6AZwPxhPJ+ISM0zRfciIiKJDEsAZGYzgROBO4bjfCI70l2i1DZ3tQGJiIjEUdQ8QGZ2MrBnjk06CCZLPZYgCcJ5xZxPRERERESkGEUFQMAJBF3bstlEEPh8GfiRu/cUeT6R+NrauP7aX/Hw1k4Oam2tdGlEykJpsEVERJIpKgBy99eXqiAiJdfYyNJXvoInNm/koMbGSpdGpKzUAU5ERCSe4UyCICIiJaYscCIiIskU2wVOpHr19vLiX/yKlp4uGv73fytdGpGyUAc4ERGRZIpqATKzK8zspTG3PcTMrizmfCKJbNvG679+Dp/49oU0bOutdGlEykotQCIiIvEU2wXuY8ArY277ZuDdRZ5PREQyUggkIiISx3COAdoHWDiM5xMZpExZUqs0EaqIiEgywzUR6suBDwA3D8f5RETqjeZBFRERiSdREgQzOxQ4naHjbj9sZtm6wY0CpgGHAg8DFxZSSJFi6SG51KpU66biHxERkXiSZoEbRxDQRO8nJ4TLMtlCEPhcDPzWXc8oRURERESkchIFQO5+J3Bn6m8zGwAudvcfl7pgIiIiIiIipVbsPEALgKWlKIhIybW28vufXsFjXV3Mbm2pdGlEykIToYqIiCRTVADk7jNLVRCRkmtqYsHrXsfDnZuY3aw5f6U2aXybiIhIMsOZBlukYnSTKLXO1QYkIiISS+zH4mZ2EHAQcL+7az4fqX69vbzohj/Q0NOFffSjlS6NSFmk5gFSihkREZF4kvQLug8YDfwHeDmAmd0NzEhwjAXufmSC7UUKt20bR595FkcDvz/xQ5UujUiZqH1TREQkiSQB0H+A14b/Tfk5sGeCYyxOsK2IiIiIiEhJxQ6A3P11GZZdXdLSiIhIIsoCJyIikoySIEhdUCchqVUKgERERJJRACQiIiIiInVDAZDUBbUASe1TG5CIiEgcJZkd0syOA44kyAg3Lsemi9xd6bhEREpEXeBERESSKSoAMrNm4A7gCILscM8D83PsoixwMnxaW7nx0ot5urub/dpaKl0akbIwU/umiIhIEsW2AJ0BvAo40t3vKUF5REqnqYlnj34r93VuZr+m5kqXRqSsNBGqiIhIPMWOAXoXcJ2CH6lWuimUWqcucCIiIskUGwDtDTxbioKIlFxfH/vd/idefcffaOjrq3RpRERERKQKFNsFbidgYykKIlJyPT0c96nPAHDz8e+pbFlEREREpCoU2wK0EZhQioKIlJOGiUut2t4FTp3gRERE4ig2AJoPTCtFQUREJDkF9yIiIskUGwD9ATjWzDShqohIBan9R0REJJ5iA5eLgHXA+SUoi0jZaKoUqVmpi1sRkIiISCzFJkH4EsHkp2eY2fHAA0B/ju0XufvZRZ5TRERCiu1FRESSKTYA2gMYDaTmAZqaZ/tcwZFI2ZhuE6XGqQFIREQknqICIHc/qUTlECm9lhZuvuDbzOvpZp+WlkqXRqQsNBGqiIhIMsW2AIlUr+ZmHnv3u3hgSyczm5srXRqRslDbpoiISDLK3iZ1QTeJUus0D5CIiEg8CoCkdvX1MfMfd/Gye+7D+voqXRoRERERqQJFdYEzs1MIEiEk1Q8sBu5w92XFlEEkq54ePvCx0wC4/W1vr3BhRMpDCT5ERESSKXYM0AeAQ4EOoA9YAQxE1huwe/jf5eE2ELQ87Qz0m9mx7n5XkeUQyUm3iFLr1AFOREQknmK7wJ1FcG95GjDK3fd09xmR13SCQOcPwFPAzHD5nsBE4N/At4osg4hI3RqcB1URkIiISCzFBkBfAu529yvdPeMgC3dfB3wIeAXwP5HlW4HbgNlFlkEkP1MbkIiIiIgUHwAdCDycbyN37wL+CLw/bdVWYEyRZRAREREREYml2ABoL2BtzG0XAPsXeT6Rgqj9R2rV9olQ1QdOREQkjlKkwR7IvwkA64AJJTifiIiEtgdAIiIiEkexWeD6gOaY2zYQP1gSKV5LC7d+7as8v20be7W0VLo0ImWhNNgiIiLJFNsCtAjYNea2U4Dn05YV9cttZuPN7EIze8LMVpjZyvD1tJldZma7xDjGIWZ2i5ktiOy/zMweMrNTzKwxy36zzOxZM9u3mPcgZdTczEMnnsCt73sv3hw3ThcZmdQCJCIiEk+xAdBTwDFmlvM4YRBxDPBk2qppwIZCThwe805gC3AkMNXdp7j7FOAw4FngfjMbleMYhwDXA5cD+0f2nwZ8EDgWuCDDfrOBvwDjgfZCyi/DQzeFUvPUB05ERCSRYrvAfQ34D/AnM7sUWAJsjqwfDewBnA7sB5yYWhEGH+8CHizw3O8CFrn7Oekr3H0j8AMz2xs4FbgoyzHOAT7t7ren7T8AzDGzE4Cnzew77r4qLPe+wJ8IUnp/qcCyy3Do72f6gw/R092FTdmt0qURKQt1gBMREUmmqADI3R83s7cA3wNuIfMzSAOeBo5298cAzCyVPnsRcEaBpz8Q+Eeebf4GvLPQY7j7FjP7D7AvsCpcPAB8wN3vNzMFQNWsu5uTT/wwAHc8f1SFCyNSXmoAEhERiafYFiDc/U7gJWY2HpgOjIus3gwsdPf1abs9RZAS+7mwtaUQuwOP59lmOUELVDbj3L0zyTHc/TnguVgllKqhgeJSq5QGW0REJJmiA6AUd98APBpz2wFgTpGnbAT682zTR2ky3ZWsnqQyTPGPiIiIiKAb+7Izs1agNbJoDIC7417YE9vUvoXuXy/cffvTcdVXVrqe4qn2eqqWslV7PVWLUtaT6lpEJJmaCYAiyQne4u5zCzzGWcCr3P3tJSzalwiSRQzR2dlJQ0NhSfjcnc7OoOeeqWkjK+/sZGz4/z3btg3WmQyl6ymeaq2ngf6gIby7u6cqrvFqradqU8p6qoZ/dxGRkaQkAZCZtREkCpjO0DFA6ZaFY4ZKzt3nAHsVeYzzS1ScqG8D34/8PQZY2tHRQUdHR0EHTD3t6+jo0A1GDtFnom0tLQXXd63T9RRPtdZTU2PwNd7a1loV13i11lO1KWU9DQxojnERkSSKDoDM7GTgm8BkgvG4zo6ZWVPLFgJ7F3vOUJyxOU3hdsUo6hju3gP0pP5O/dCZWVE/eqn9dYORQ6RuVFe56XqKp6rrqYrKVdX1VEVKVU+qZxGRZIqaCNXMXgf8BPgr8DLgYIJA5x1AM8EkoW8D5hG0hMws5nxplgJT8mwzFVicY/0GM8v3yDTfMaRaNTfzpy9+np9+9lN4c3OlSyNSFql7Xw0DERERiaeoAIhgfMvD7v5Bd/8vsCZc3u/u/e7e4+63AUcBnwfeVOT5op4A3pBnmzeE2xV0DDMbDRxC8RnrpBJaWrj3lI/y+5M+hLe0VLo0IiIiIlIFig2AZhFMNpqTuy8C/gz8b5Hni7oJ2N3MzjGziRbpA2BmY83sdOAY4MocxzgbuNjMjgmztaX2bzCzmcCvgBvcfVXWI8gIoS4iUuvUBCQiIhJHsQHQNGBlzG2fBF5e5PkGuXs/8EaCbnZ3A8vNbKWZrQQeAg4AXu3uWwDM7Egzm2dmYyPHeAQ4DjgVeCay/1LgNwRZ5b6Yoxjrga2lek9SYv397Pb4E8x68inozzdllMjItH0iVBEREYmj2CQIBsRNP7OaIFFCybj7RoIAJVeQktr2LjKMQQqDoILSXrv7uwrZT4ZJdzefOP7/AfD3Jc9XuDAi5WFq3RQREUmk2BagTmBUzG17S3A+kYLoFlFqnVqARERE4ik2IFkF7Bb5e3P430yZ1UYDW4o8n4iIiIiISMGKDYDuAt6RSiXt7psIMsEdnGHbg4EFRZ5PpCBqAZJapWtbREQkmWLHAP0AeC/wpJl9091/AlwBnGFmvcC/CYKsI8LtPlnk+UREJAPNAyQiIhJPUQGQuz9pZq8lSG+9X7j4PIKg55PA+HDZauAs4PJiziciIkMNToSqUUAiIiKxFNsChLs/RpBGOvV3D/AV4CtmNh4YCLvGiVSMMmVJrVIabBERkWSKDoBycfcN5Ty+SE7Nzfz1k//Lqr5edm9urnRpRMpEwb2IiEgSZQ2ARCqqpYW/nv5JnujeypktLZUujYiIiIhUAc3LIzVN4yKk1qkLnIiISDKxW4DM7CiGzvlTiKXufkeRxxCJZ2CAnZ+bxx493bD7npUujUhZqAOciIhIMkm6wF0J7B75u5Df3XnArAL2E0muq4svHPsOAO5durjChREpL7UAiYiIxJOkC9zhwC0Egc8fgT3cvSHhS8GPiEgpDfaBUwgkIiISR+wAyN2Xuvu7gHcCBwNPm9npZqZxRFL11E1IapWubRERkWQSBy/ufgswm6BL3PeBf5nZS0pcLhERSUDtPyIiIvEU1Hrj7lvc/fPAocAA8LCZfcfMRpW0dCIloolQpValrm0FQCIiIvEU1X3N3R8DDgM+BZxC0C3u6FIUTERE8lNoLyIikkzR43c8cBlBt7h/AX80s+vMbHLRpRMRkVjUAiQiIhJPkjTYObn7CuB9ZjYX+CqwBvhEqY4vklhzM//46EdY29/Hri3NlS6NiIiIiFSBkgVAZjYBuBA4GbgP+G6pji1SkJYWbvni53m2p4uvtLRUujQiZaEucCIiIsmUJAAysxMIMsI1AR8DfuauSSmkeugmUWqdqxOciIhILEWNATKzmWb2V+CXwF+A/dz9KgU/UhUGBpiwdCk7L1sOAwOVLo1IWVgY3etbV0REJJ6CWoDMrBk4E/gKsAR4k7vfWcqCiRStq4uz33gUAA8sWwITKlwekbJQ+6aIiEgSiQMgM3sNwSSoewEXAN9y9+5SF0yklDQPkIiIiIhAgi5wZraTmf0UuAt4AXixu5+t4EdEpHJSob16wImIiMSTpAXoQWDv8P/3Bu4wS/xUfb67vy7pTiLFUvuP1Cpd2yIiIskkCYC+CexZ5PkWF7m/iIhkoBYgERGReGIHQO5+dRnLIVJWekoutWp7FziFQCIiInEUlQZbZMRQBCS1SoOAREREEinJRKgiVampiXs+8D429vezc5MudalNynAoIiKSjO4KpXa1tnL92V9lXk83X29trXRpRMpKDUAiIiLxqAuc1DR33RZKbVMPOBERkWQUAEntcqdj3TrGrVuP6e5QRERERFAXOKllW7dy/uFHAPDv5ctg3PjKlkdEREREKk4tQCIiI5jSYIuIiCSjAEjqgvJkSa3StS0iIpKMAiARkRqg9h8REZF4FABJXTA9JpcaZeHFrYSHIiIi8SgAkrqg+EdEREREQAGQiIiIiIjUEaXBltrV1MQD73w7nQMDTGxqrnRpRMpCE6GKiIgkowBIaldrK9d8+5s8v62H81pbK10akbJQ904REZFk1AVOalzwXFw3iVLrNA+QiIhIPGoBktrlTsvWrbRu68WUIktEREREUAAktWzrVi455JUAPLZiOYwdV+ECiZSeKce7iIhIIuoCJyJSA9TIKSIiEo8CIBGREUxZ4ERERJJRACR1Qb2EpFbp0hYREUlGAZCISA1QC5CIiEg8CoCkLpiek0vNUwgkIiIShwIgEZERTGOAREREklEabKldjY38+81vossHGN/YWOnSiIiIiEgVUAAktautjcsv/h7LerdxQVtbpUsjUhap7p1qARIREYlHXeBEREYy9YETERFJRAGQ1DQP7wqVAkFqla5tERGRZNQFTmrXli1cNfvFADy1agV0jKlwgUTKRw1AIiIi8agFSERkBNveA04hkIiISBwKgKROqKOQ1CZd2SPH2t5tnDrnKW5e80KliyIiUtcUAImI1AC1/1S/a1YuZ3FPN5cvX1LpooiI1DUFQFK01du28fG5T3P72tWVLkpWekoutUtX90ixbWCg0kUQEREUAEkJ/GzlMhZ1d3HpssWVLkpWukWUWqVre+RQK52ISHVQAFTHNvf1MXfrlqKP06OnmiIV57q7TmTVth6e3NI5bOd7cNMGFnZ3Ddv5REQkO6XBrmMnPfsEWwcGuGCvWRxUiymiGxt57LWvoccHGNvYWOnSiJSFhU1Ain+SOenZJwG4dJ/9mdk+qqznWtC1la8vml/Wc4iISHwKgOrY1rDl5uHNG4sMgKr01qutjYsu+yGr+nr5fltbpUsjIlVo7tYtZQ+AFnd3l/X4IiKSjLrASU2r0tBMpAx0tVcr/cuIiFQXBUA16pktnTwbc3xPPQyiNquHdyn1aPtEqJn1DAxw9Yplsb8P6o2+GURE6o8CoBrg7nx/ySJ+uXI5AF39/Xxu/hw+O+/ZWGlXrVZvAbZs4cpDX8GNr3g1tkU3f1Kb8n1+b1i9kutWr+Sz854dphKNLA0FPhzpd+eK5Ut4aNPGEpdIRETKTQFQDZjf3cVf16/l2hdWALCpv29wXV+M1FA1Gv4A0NrVTVt3d02/RxHI3gL0vMaflMVf1q3hpjUv8LVF8ypdFBERSUgBUA1IT0PdGwl6YvU9V3QgMmLl6wKnj3d5rNq2rdJFEBGRAikAqgGeduvTO7D974EYLUDFXgSVGOC7pb+fm9e8UJJ5jERGtDwRjgKg3JLWz9b+fvrdGVBqAxGREUsBUA2IxjgD7vT69hah/lg/0iPvFumG1Su5fPkSzlwwN9b2I+8diiSU5aNe7fk/NvT1ctmyxSzo2ppzu4VdW/nk3KdLPuYmOobqsc7NPJNjctS1vdt491OP8vn5czTxrIjICKYAqAZEf4eX9HSzLRIADQzDj3Ql7q9S82p0x0jyIFLLtneBc7b097O8pzttfXVHQJcsXcwta1fzieeeybnd2YvmMb+7q+AxN70DA3xt4Tx+v3rVkOWpAHFTXx9nLZjL5+bPydpyfv/GDQA8u3VL1hagzv4+ntyyecgx0lvpRUSkshQA1YDoT+tpc5/mxtUvDP7dX+dJEFLq4T1KfYpe2yc+8zgnz3mKpZHEB9mu/b+vX8u5i+axtb+/rOXLZ36elp+UNb29Ode7O5v7+rKuv3/TBh7avJGfrliaMcCJJo/ZluV7M5oxLtvDpc/Pm8MX5s/lvo3rc5ZXREQqRwFQDUj/Mf/npg3b18V48njvMPxQuzvLerpjjUmCILHDdxYvLO4moqGBZw49hMcPfSk06FKX2uZsbxF9pHPT4PJsXeC+s2QRD2zayB/XvjBkubtz8ZJF3LB6ZbmKOvR8ke+oLUUEYz9ctpj3Pv0Yj3duzrg++t0TbTdOVU9DJFRMTyzD4DbbRVvao54PW+AeCLvqqZVaRKT66K6wxsXpArekp5veBD/SW/r7+eXK5Tzf3RV7n5vXvsApc57iR8sWx9r+g888zt83rOObzy/Iu22/OzeuXsUjmzcNXdHeznlXX8WZV10J7aNil1VkZNkxwvEha3O3f3alffaf3NLJX9av5aoVy7IGE6UULevxTz06pEWqz501vUOzrXU0NmY8zu3r1gDw61XLM66PZseMzo+Wqp3ow6JUALSwq4vLly9hQ1/Q+hQNkv4Uni8q2uI+paWFJ7d08q4nH+GnK5ZmLJOIiFSGAqAakCvGydYClN4Ss3VggGe3buHqlcsGf/wf2rSR/2zeccDxNSuXce0LKzht7tN5z59y9YrgpuT2DDcN6bYNDLA5z5Pg6C3dw5s3cuWKpXx54XPxdhCpIZnSYHuG9RB87h/t3ERnpLtXe1rr6JaB7Z+9MxfMpXugvF3k0r8/FnR30dnfxz83buDshc/xwWee4NlItscGjJ6BAf65cUPG7ntNtuPP2tytW7h46fODf2+OvP9UgBidMy31Hfi/zz3NzWte4NKlwYObhjzfI9GWtwlNzYOBz/ocXfNERGT4NVW6AFK8XANss7UApY8N2tLfNzhTfKs18I5JOw8ONr7pgINpjdwkzYmRenpe11Y6+/t4ScfYnGX8xcplLOzu4qt77k1j2Fcnzril6F3dsp6erJtp8LHUukz35Nmu+9vXreFHyxazZ2vb4LK2hqEtKunfGT0DTls5H5Wlna/JjK8tnMfTke+ZGyOJCxoMrly+hNvXreEVY8bx9Rkzh+zfHOnz95d1a3iuaytdaYHS5r7tf6e27hvYMQBKmdO1Jdw2ewS0uLuL/1u4PUGDA5nbqgJxuwOLiEjpKQCqAf/KkRY2awtQ2t+dkRuEhd1dQ/q3b+3vHxIANUVuMNb19vJkWtrY57u7OD3M6PSL/Q5kckvLDudL+c0LwTiDxzs3c/CYsRnLls9jnZsyLr/1+YVc9prXAbB27lx1g5OaNqQFKPJHNHa5I2yBfT6SKa41rcUk6UODTX19fHvxAt40YSKvnzAx1j5rercxd+tWDhs7boezNcKQ4AcY7IIGQQtQqiX5wQwt1E1hM80/N24YbPVJ7zYXTXiQ0hcpSXfa+J5UsJKrBeiZtDL3uQ9JmpBOI4NERCpHXeBGuJvWrOLWtauzru935/HOzTu02uzYAjT0iWj0KXD6IN7myA3TZ+Y9MyR4gqEzpGe60bg9Q3mj8xXFeTLa1b+9TA9Hxv789oUVg2W+auVyxq3fwLj1G/IeT2SkSt1j+5C0y9H122/CezMM3E9/SJLeApSvRfbaF1bwaOdmvrNkUc45dKK+MH8O33h+Pn9dv3aHgOuuDet22D7ahcws9w9XqgXoG8/PH1yW/h015HsprJ6+SN2ktwCl6qAhSwvQfRvXD+lil9onV4+5FTlarkVEpLwUAI1wVyzPPbh2XV8vZy6Yy2fmPcvDmzbi7nx94Ty+lDaBaPQGocFsyI1SV9oYgMbIDdXqtNS0f1q7mu8vWTT4d6pffTSouTRMhBC9sWqM3Crkm7z1uhdW8N8srT7XrFy+w7FBQ4Ckvgzg/GvjBn6/etWQa783Q5/Y3rTPyoptQ2/M8wVA0YcnZ8eco2dl+JDkzxnGBN605oUdlkWTFjQwtBU6XaYxQOmiY4dWbuthRU/PkLrZMQCCL86fw4VLFmY8XqZkLf15WoBOfe5plm5TECQiUgkKgEawOJnb1mzbHqCcvWgeWwb6eXDzRuamzb2xbkgXk6EDgremBUC5bj4uWbaYjZGnq6nAJ/0W6sbVq4bcZDSa8cjmTdy7YX3GcUtPbunkC/PnsLBrK1evzJzlKeWCxQtZqRsLqWcO5zw/n5+uWDqka1ZPhhagaIBz/8b1/HzlsiHrBwhS2N+85oWMKZ2jncs6+/sTpa5/Ydu2HT7vmb7Vol85DdiQhzBd/f1DWr+ac3w/pUQDoGtWLuejc54c8j3XMzDAxkir05aBfp6I2bqV0u++w9ijdDdsWDek7CIiMjw0BmgESw9MMknvXtKX5cf2wcjcQX3uQwOg/vQucPHbU1KtOelnvXLFUiY0NQ/+3WjGmWGr1Hf33nfItn9au5pLwlajr+TK9Ba6a8M6ntoyNH2vWoCkVqUG5kc/pVdFgpi1kTTSmQKY6Gf9vCwtGafMeQqAy5cv4c0TJnLMxMncunY1J03ZbUgwAvCtxQv53YxZQ5Yt7NrKhUsW8oox4zmwo2P7sfG8Lb4wdEzTur7eIa1Wxz31KF/bc+/Bv5/a0pmxG13UlgzfnUsj46K2+QA/WbEkb7ly2dTft8ODpnT/3LKZBzZt5PDxE4o6l4iIJKMAaARL79eeSfqM5tkCoEci831sHegfcoORqwtcPtnOB7A4esMRuTFbl9at7pLI3EFx08mu7u2ldcgShUBSm1JXdpzsiZkCoEzjgqJ60ppo7li/ljvWrwWC5ARTWlp32Gfpth42b+7npWPG0WTG+YsXsrinm0XdK7kuMgRwQ8zPczRBQXqXPYAfLNs+/mZxTzcXLM7cVS0l04Sr0Zbl+V1bY2W7zOXZmPv/ad0aBUAiIsNsxARAZjYe+DLwVmAS23/31wF3A19391WZ9x48xiHA14ADgFRKsH5gGXAl8HN370/bZx/gHOBlwJhw8QCwErgOuNjdK9LfKs6s6fPTu7qlBReZ9LoPCUjSz5OoBSjHTdlvwoQFMLQ1K1vmOhHJLttnbXPaxKJx90uJZmBLt6C7i90iKbVTPhcJSH627wEZA68k8pUx6eONfN+df8yRWCauhTEnii62bkREJLkRMQbIzBqBO4EtwJHAVHef4u5TgMOAZ4H7zSxrnuMw+LkeuBzYP7L/NOCDwLHABWn77B6e91bgxZF9dgPeAewN/LqU7zWJTN040v01fFKbsj7HzUzKY52bOWP+nMG/16YFTc0N8S+bry6cN6QLTjbRG5JMT3gL4Q3G3BfNZu6LZmONI+JSFylYrtbWXHrd6R0Y4PksN+x/S/sOiXIfmsAkk9vXrc45bjCOfC1FSScajbY+l0vcf49M47JERKS8RkoL0LuARe5+TvoKd98I/MDM9gZOBS7KcoxzgE+7++1p+w8Ac8zsBOBpM/tOpCXpLOA77n5t2j4OLDGz04D/mtnB7v5IMW+wEBsLmF28kH2ufWEFa3u38Zlp04HkE/hdvzpnwxwwNADKN3A4rm1tbXz62l8AcFl7e0mOKVJtUrHF5gwp5+P487o13JDjM/r3HONpHB+S9CSTMY1NOefPqYR5ecbmDKf0jHMiIlJ+I+Wx+IHAP/Js87dwu4KO4e5bgP8A0RH4+fYZAP6e57xls7SAp5gXpc1VEddf1q8dnI09zliDqDsypLpNF+0C11WGG4Iqu/8SKZlUF6roOL4k4owlzGZ9X1/OFiKAn69cxlLNeZOVAiARkeE3UgKg3YEVebZZDuyRY/04d8+XxzT9GKU4b9kM903FlSuW4u6Ju6jFCWiiaWnjZLdLSqOKpFYt7S5/dy4pn1ePG1/pIoiI1J2R0gWukSBZQS59FP9+0o9R9HnNrBWGJCQbA8Gs7YXO/5Dat7PALi/F6BkYKHisQS6dZegC19rVzRXHvQeApqeexjMM1pbt15PmI8mtWuspzlhAqV7HTdq56Guq2q5JEZFqN1ICoJHsSwSZ54bo7OykIUEygSh3p7Ozk67e4Q+AHlm7hp4YiRSS2hRpzdqcoGXrTWPG8dfNGzOvdGeX5UED3ububjobGzNvV+dS1xOAFTlYvZZVaz2tVfeyEa1vaxedjfkTxeSSui5FRCSeERkAmdm+wJ+At7j73AKPcRbwKnd/e4J9TgTOcPeDE5zq28D3I3+PAZZ2dHTQEZkQMInU077+LVlu/Mvo3JVLOaRjbMmP+6+t23/AexNkbPvo7nvw12eeyLtdR0cHjB5dUNlqXep66ujoqKob+2pTrfU0rX0US2JkWpTqtNOYMTQV+DAsZUDjiEREEhmRAZC7zwH2KvIY5xewz6+AXyXcpwcYfESbunEys6Juoh7p2pJ3lvFyWVeGFqCoZ7bEn4BwXFNzrO3MbHu6LNlB6nqsphv7alSN9fSJ3fbgwU0b8vbVjevq/Q7gpGefLNHRJJ+mhoair6dquh5FREaCkZIEIc74nqZwu2KkH2O4zpvYyhgTmkZdPmt2yc5dSCrtJNYmCLD0wy/1bqfmZm496JCSHOv/9tybXVpa828oIiIygo2UAGgpMCXPNlOBxTnWbzCzfH3O0o9RivOWRVuCLhPfmrEPe7aVbh6c9BagnWK2wpTaT/d9EQCHjR1XkfOL1Jo92qo3UcjBHWNibTctT7KT8U0jsuODiIiU0EgJgJ4A3pBnmzeE2xV0DDMbDRwCzEmwTwPwujznLYtRCQKgqa3BE93Dxo5PtF8xkgRohdotvNH5wrQZnL3n3rx8jAIhkWK0WvX+JLQ1xEti8oOZ++VcX44slnHtmRacvTZmUCciIqVVvb92Q90E7G5m55jZRIv0ezKzsWZ2OnAMcGWOY5wNXGxmx4SpqVP7N5jZTIKxPTe4e3RK9POBM8zsBDMbFdnHzGw34HJggbs/Uoo3mURb5Eblqn0PyBnYtIc3Dv+35178ZvaLS16WTBOjpt9kvHHCxIz7ZlueRHtjI4eNG8/Xpu/NS6I3FGasnLk3Pnu2xv+IxJB6cPHVPfMPsSw2p+JHpuyWcI/8gcuFe82ivbGR0ZFg6f07T+ETU6cN/n3cpF0Snrd0Prrr7kP+Pm1Svg4GIiJSDiMiAHL3fuCNQDtwN7DczFaa2UrgIeAA4NXuvgXAzI40s3lmNjZyjEeA44BTgWci+y8FfkOQVe6LaeddBrweOBZ4LLLPcuA2YAFwQhnfelbRgKelwciVA6g93NbMaClDy8xAhhuTaAD0hWnTs950FFqaTMdrMOPbe83i5PDGqqe9je/f9kd48kkYNWqH7UVkqNbw++HwcRPybjuxuWXI3zun/Z3Pe3dOdvPfnSfT2e0HvpQDwwcgbZFMkh+ashvHTtqZ2w98KVftewBv2WlSovOWUrMZh4cTn75z4s406cGMiEhFjJjO0O6+kSBA+WKMbe8CZmZY/ggQO+11uM884P1J9hkOLZEWoBZrYCBHt47mMndHG8jzYPb1EyaysKsr874FnvO4yTtnXTc20sd/qyaJFImtOc8N+exRo3l6a5ClcVxTEy9E0m+/aHQHL2xYV/C5L5m5H5+a92zW9a15vseiCVEydeUzM6a2ttJdhu+ED0+ZyjUrlw/+/eYJE7lj/dodtmtuMD4/bQZv3WkzB47qoGdrZTJ5iojUuxHRAiQ7aorcp+RrAcqmAfh/k+M9hc11ofSntQCdvefeO2yzZ1sbM9t3bIXJ1H0uk5N33Y19I/s35RirEA2A5m/TJJEiceXKqjittY3v7L3vYEvPrFFD59Xq9eLmohndmP153P6jRvM/u07Luj5drpbulpjjnMY2Ng62nufTwNB6239U5nw7TdZAW0MDh4wZV/YHUyIikp2+gUeonSI3+c15WoCymdDczIemTI217RHjd8q6LhrE7NrSymHjxu/QtaPBjPP3mrXDvi0xu4AcP3kKH99tj8G/cz2p7ghvpFq7uvnF8e+DAw4APWkVSeSA0UNv4gfcaTDj8lmzuWjmfhyYtn5dJDX/kVkmS94tTLF9Wjgm53WR75VROSZA/v7M/di1NX567tYc3w8NZpwxbXreY7Q3NHJZgdMHvGmnzGMb87WwiYjI8FAANEKNamjkkpn78eN9ZtNohbcANeT5QX7tuAl8dvc9+WQk+EgXDYBSgdi395rFjLZ2LowEPY0ZTjWmwJS0ufrODwaH7kx+bh729NNQwcxPIiPRudOH9iJOfce0Nzay36jRO7R6rIkEQKdM3Jlzp+/YEnziLlO5at8X8faJkwF4VTgeBoIHOSmvyTIG6TO77znk7wlZvj8+FI4DzDbe540TJg758dt31Gg+tMtU9ohkaet13+E9ZpP+Q9qY5fupPWYmOxERKS8FQCPYzPZRzGgvfH6fOD/uHY2NvHmnSYxqHPrDfUjkCW80+EqFGQeM7uDHs2YPDkrOdr6xObq9pIu2cuUKgKa2tnHWHjP4xowdb8BE6tnYxqbBLmyHjR3P/0SykqUHF+1pn3nPk4XtVePGM6t9FIePHU9LQwOHZkhL39RgTG1tG+xqF/1MR1tH9mkfNdg69MrIPF9H7TSJP7zoJcweNZqPTtmNV2cJlF46Ziy/mX0Qn8rx4Cb6vWXA+3fZlSvCucUg6NIXDWQ+l1Y/UXEnZJ7cXJk500REZKgRkwRBcmsE0of27tXWnrPlppjeGN+YMZOjn/jvDsvTxwNFZXoqmt7NJpfoDVm+lqsjxu+Ed3bGPrZIrWi1BnrC8Tit1sDe7e30urNtYIDPTpvOpOZm/rVpI2+YsBOt1sCVK5YCwfdFLrkmPH7bxMmcsMuug+mnO7N89tIbYqMPVtK/Hz61+x4cNnY8h4wZ2p2uvbGR74Vz/fwikngg3fgEEzRnehLYgNEQKVK2Vp1s+2eicT8iItVB38Y1Ir2FBoJ+9vvnCDAsbJFJTc532Ngdn9hmerI5qqEh6xPPXGORMl1s+4/uGExbnc/0tnaOn7wLp07dPf/GInXmE+HDji9H5vAZ19TE92buxyX77M/l+76IfUeNZmJzC8dMnExbQyNmxmlTp/H2iZMzJin58T6zmdDURLPZ4PEzOXXqNDoam/K2hHSlZWB7acdY3rLTJD4xddoOAUZbQyOvGT8h43dbyrsn78KhY8bmbJ2JI/pA5ct77MWEpia+On1vGmN2gTPb/v2WLVDMVL8iIlIZagGqEaMaGtncH9xcHDpmLDs3tzA7T+vK9LYg8Dlvr324a8M6jpowiQeefizvuSzHTUGulNhmxpSWFlZu2zZk+cvGjuOqlct22P6bM/bhkqXP8+nIzc3Juyr4Ecnk2ImTefOEiUMyoMW5fX/HpOwp5We0t/PL/Q+ie2CA0TkCkVytI1HpaekbzIZ8vlPijtgb3djIN2bsE3ProRrY3g0uWvrXjJ/Aq8eNx8zY0p89ZfY502fytUXzwv2Ni2fuxy9XLecjU3b8jrp81mx2bYmfxEFERMpLLUA1Inpz8o0Z+3D67ntmvSm5eOZ+HDVhIp8KbzwmNbdw/OQpsRMSpA77srBrymsj/fDzjhMYO36HZaMiA4OPCQdHv3zMOF46ZixX738gB4/JnFFKRIZKT/9ciqRjjWYZg598n/VMtuWbNGwYfTuSoCV9fGKqJSvbD2SLGS+PtJgbsM+o0Zw7Y5+M4zL3bGsvyyTUIiJSGLUA1Yi920exoDvzZKPp9h01mn3T5vAoxJl77MVDmzbyirHjuGfjeiDOxKY73pFNbmnh41OnMaqxkdeMm8DBHWM4OEsa3UTMGNhjD8ws9iBlkVqSq7W2WHFCmSYz+sJusbs0t2TNylYJB0UTtGSpprgtW/nGJIqISHVRAFQjPhZ2DXvjhMzzT5RCW0MD3QMD7B8GT6MbG3ndhKHzA8Wd2BTg6MjN0Nsj3XAOz5LZKbFRo9jy5JN0dHSU5lG4yAiR6t71ogRJRpKK80m/bNZs7t2wnndM2pn2HGMHKy1boJgtsEl/72rbEREZWRQA1YgxTU18LsbkfklNiqRtvWTm/vx53Rres/MuWbfP18MlejvxvzkGVYtI4S6f9SLu2rCO4yZn/6wWK5XBsdWy3/7v3trG+3fZtWxlKJVsLUDFBDaTmpuHzI0kIiLVQwGQZPWmCRN516TtN1DT2tr4WJYMbKknzvnmJYo+UI3bvUREkpnW1sYHp0wt6zkmNbfwy/0PHDKGr1Sm50nJXWrZvonitgA1ZwgCz52+D5ctXzw4KauIiFQPBUAyxPS2NhZ1d3P0TpM4PUFq2R/usz83rXmBE3Yp701XIl1djDriCGhshHvugSImjRWRHU0KJ1UtlUv32Z+FXVsHE6wMl0LHSr138hQe27KZI8bv2G13Rns7F+69b7FFExGRMlAAJEOcN2MfHty0kdcnHEs0o30Un43RBW9Y23wGBmh85JHB/xeR6jazfVRF5svJ1gUuGw/HOn5kV7XuiIiMRAqAZIiJzS0cHaaiLodyZqUSESmEvpdEROqLktfIsNKwHxGpNolbgMpTDBERGSYKgGRYvXPSzkxsauZdOWafFxEZTukToYqISG1TFzgZVuObmvnl/gdW7XwgIlJ/9G0kIlJf1AIkw07Bj4hUk2zprqP2CyeABnWBExEZ6dQCJDVtYOJEzDTEWUSyy/Uk8DezD2JjXx9TW9sGlykAEhEZ2RQASe0aPZotCxfS0dGh7AsiklWur4fxTc2Mb2oevsKIiEjZqQuciIjUpdQP4Es7hnfiVRERqSy1AImISF26er8Dea5rK4eNHVfpooiIyDBSACS1q6uL9qOPhsZG+NOfoL290iUSkSoyuaWFyS0tifdT1wkRkZFN3+NSuwYGaLrvPuzuu2FgoNKlEZER7qt77sWEpia+tdesShdFRESKoBYgERGRGA4fN4FXjR2vVP4iIiOcWoBERERiUvAjIjLyKQASEREREZG6oQBIRERERETqhgIgERERERGpG0qCIDXNR40CQL32RURERAQUAEktGz2azpUr6ejoAA1cFhERERHUBU5EREREROqIAiAREREREakbCoCkdnV303788XDssdDdXenSiIiIiEgV0BggqV39/TTdccfg/4uIiIiIqAVIRERERETqhgIgERERERGpGwqARERERESkbigAEhERERGRuqEASERERERE6oaywFXIpk2bCt7X3ens7GRgYAAzK2Gpaot3djIu/P9NmzYpE1wWup7iUT3Fo3qKp5T1VMzviYhIPTJ3r3QZ6oqZ7QYsrXQ5RESk5uzu7ssqXQgRkWqnAGiYWfCobyqwuYjDjCEIonYv8ji1TvUUj+opHtVTPKqneEpdT2OA5a4fdRGRvNQFbpiFP05FPaGLdJfY7O7q+5CF6ike1VM8qqd4VE/xlKGeVNciIjEpCYKIiIiIiNQNBUAiIiIiIlI3FACNTD3AOeF/JTvVUzyqp3hUT/GonuJRPYmIVIiSIIiIiIiISN1QC5CIiIiIiNQNBUAiIiIiIlI3FACJiIiIiEjdUAA0QpjZeDO70MyeMLMVZrYyfD1tZpeZ2S6VLmOpmdmJZvZo2vtdEb7nz5lZU9r2bzCzv5nZosj2S8zsXjM7ziITb0T2OcTMbjGzBZF9lpnZQ2Z2ipk1Dt87Li0zazSzP5jZe9KW12U9he/7vrDcK9Pe+y1mNjtt+33M7Fozey6y7XIz+6+ZnWlmrRnOsauZXWFmz0Su2xVm9riZnW9mY4fvHSdnZruY2U/MbGFaHS00s1+b2bS07RN/L5lZu5l9ycweCesztc/c8Bx7D987TsbMOszsNjP7WNryxJ+Pery+RESqhrvrVeUvoBH4D/A1YCJh8opw3Tjg08A8YFSly1rC93wk8CQwK8O6XYBbgNMjy94JPA68GmiOLG8CXgrcC3wy7TiHAAuAo4HWyPIGYF/gJuC7la6LIurwmwQZpk6q93oC9gEWAa+Ifn7CdY3Ae4G5qfcH7A4sBj4Q/VwBBkwDrgRuSDtOBzAf+CQwJm2fycA3gIeAhkrXR456+gvwVaAtbXkT8NFo+Qv9Xgqvl8uA3dL2GQ18KKz3qZWuiwx1Mzb8fCwCPhNZnvjzUa/Xl1566aVXtbyUBW4EMLPjgfe7+7tzbHMJsNDdLxq+kpWPmV0ALHD3K7Ks3xf4hbu/Ivz7SeAD7v54lu13I7g52MPd+8NltwJXuPsfs+wzGngaeLm7ryr2PQ0nM3sH8HWC9/yAu18dLq/LejKzLwO4+7dybHMn8AV3/6+Z/RCY4+6XZtm2Afgv8BF3fyRc9nlgV3c/I8c5bgF+7u43Fv5uysPMxhEEx9M9yw+Dmd0HfMzdnynke8nMDgUuJ7hWBrLs8zlgT3f/dHHvqHTMrB34B3A7QWCzwd0vDtcl/nzU4/UlIlJN1AVuZDiQ4Mc3l7+F29WKB4C/5li/hOBJKWbWDEzKdlMP4O7LgFUET51Tctaru28heMK9b/xiV56Z7QP8ADge6Iosr+d6mk7w9DyXm4DUTXm+9zwA/J2hn7mR/jndGViRLfgJLSX83FHY+z0QuCtb8JNln2pgwPfd/dwM6wr5fNTj9SUiUjUUAI0MuwMr8myzHNhjGMoyLNz9JndfkGOTAwi61wBMAVbHOGx6HY1z986E+1S18Gnz74FPuXv6DX8911MLeSacdPdL3f3R8M9CPnMj/XO6ENgpbH3IZhpBdy+oozpy963u/rssqwv5fNRN3YmIVCMFQCNDI9CfZ5s+gn76NS/spnUFcEm4KE79QGF1NGLq1cyMYOzAbe5+S4ZN6r2expvZpeHg++gA/6fM7EozmxrZtpDP3Ij+nLp7H0H3x2+a2YTwegLAzFrN7IMELWmpAKju6qgIpaiHeq07EZGSUwAkI4YFTgIeBa529xsqW6Kq80lgV+D/Kl2QKnUWcAdwuLtPcfcpBPV1OPAU8GdLyyxYh84DPg6sA9aEAeIqYCvwE+A9ebqviYiIVD0FQCOQme0bpludVemyDJfwvd4BnAoc5e4/yLP9j8zsRwnPcVY4iHjEMbPDgTMIBqX3JdivnurpOnf/o7tvTS3wwIbweloKvDbTjhakZH8kycnM7EgzmzdSUhOb2WSC7IofAzrcfWIYKO5CkAHtg8BZZtaSZf/E30tmNi6soyOLfwfVoZDPRz1cXyIi1aTen3aOSO4+B9ir0uUYDuH8GV8BTgHOJsj8lvcJtLt/Ium53P385CWsPDObAlxLkN0tURa2eqon4Nk8658E9iYYfD6Eu/8K+FWSk7n7XcDMJPtU2PuAm939+vQV4UD+683sFcB7gF9n2Cbx95K7b2Rk1VFehXw+6uT6EhGpGgqARoY4/bqbwu1qhpl1ENzY9wEHufuGLJvG7fdeSB1Vdb2GXbauAy5y9/vzbF639RTqyrN+K8FcNFDYZ26kf073A/6VZ5sngJcRBED1WEeFKkU91GvdiYiUnAKgkWEpQQavXKYSTKxXS75L8N4/kSc170pgUozjpdfRBjPryJPBqdrr9XCCiRj3M7OzMqwfB2wL52x5J/VbT1uAtjzbtBNk0YLtn7k1ObafSjAeLWWkf07j3Dg72383Cnm/SwkyOCbZp9oV8vmox+tLRKRqaAzQyPAE8IY827wh3K4mhHPZvAU4I0/wk8petdrMXpLjeFOBXYBlkcU56zVMKX0IMCd+yYeXu9/t7h3uvktqYH/0RdA69GF3P7ae64kgc9k+ebbZn+0ZzvK95wbgdQz9zI30z+kCYHaebWYTpMuGwt7vE8Dr8qTaruY6yqSQz0c9Xl8iItXD3fWq8hdB+tOHgXOAiYBF1o0FTieYE2d0pctawvf8XoIZzeNu/3aCH/5XA81pdfcS4F7g9LR9Dia4mTsGaI0sbyDoW38j8L1K10WR9Xg18M56ryeCbG8LgCOBhrR1zcBHgGdS749gItjFwAnAqMi2Fq67Evh92nFGE0y2ejowJm2ficC54ee4oRzvsQR1NAlYBBwFNKatayR4ILEU2DWyLPH3EvAHgjT2u6XtMwo4Maz3qZWujxz19HXgM5G/E38+6vH60ksvvfSqppe553y4LlXCzMYRJAM4mvBmI1y1Abgb+Jq7r6xM6UrPzD4OfAfI1a2kF3iFuy8P93k98GWCJ/2tkW2eBy4C/uBpF7yZHUxwA3cAwQ0YwABBC8hPgKvcPc7cOVXJzH4A/NHd/xZZVpf1ZGaHAN8iaMVojqzqAR4AvuyRyXfNbCbwDeBQYEy42IFVwG+Bi929O+0cUwjq6QiC7ocW7rMWuA34prtvKvmbKxEzezFwPsG/c7SO+ghShX/V3R+ObJ/4e8nM2oDPAv+PoLUxtc9mghv4//MdJ/GtGmb2OWCju18VWZb481GP15eISLVQACQiIiIiInVDY4BERERERKRuKAASEREREZG6oQBIRERERETqhgIgERERERGpGwqARERERESkbigAEhERERGRuqEASERERERE6oYCIBERERERqRsKgEREREREpG40VboAIiJSu8zsGmCJu391GM/ZAEwN/9zk7puG69xZyjOF4Pd2q7uvq2RZRERELUA1wcxOMDMv4PXlSpddKsvM3mJmXWb2yxIec2czW2VmC8ysuYD9DzKzjWZ2b6nKJBW1JzB9mM/5WWBJ+HpymM89hJm9HlgRlmWNmU2uZHlEREQtQLXi78AnAUtbPhk4G7gEeC7DfneUuVxS/V4OtAGHl/CY+wE7h/+/K7A4utLMTgL+4u4rsuz/EmBsicsk9WUMQeDzJWB5hctyP/BWYDfgp8BoYHVFSyQiUucUANWA8EbyR+nLzWwmQQB0o7vfNdzlkhHhz8C7gD+W8JiPAvcAW4GlGdb/HDgFuCrL/vcCD1HhJ/cy4q1191srXQh37wH+bGbTK10WEREJKAASqWPu/hBwcImPuQk4Is9m6a2V0f0XAq8oZZlEREREUjQGSERERERE6oYCIAHAzN5oZovNrNnMRpvZGWb2sJmtM7PfpW3bYWZnmtm/zewFMxsIkyqsC/f5ipm15jjXGDM738z+Gw52TyVl2Gpm88zsIjOblGXfyWZ2mZk9Hm6f2neNmT1gZp81s8QtmxY4wcz+ZmZLzaw3UqYnzexKM9slx/4NZnaKmf3TzFZGytVrZkvM7DozOyjLvq1m9qWw7taG+3WZ2UIzu8bMDjSzN4VJBRrS9v2omd0T4/1l3D9c95yZvSXD8l3N7NdmtixDAo2esF4+mOV8V5vZeZG/Z5lZt5l5uOgnacf7YNr+fzezj2U59lgzu9DMHjGzTZFjbAqXXWhmY7Ps+1Ezuyf89z4x/PdOXcNbzewJM7vczHbOtH8uxdRXuP/hZvab8N8pdW33hZ+Jm83spTn2nWdmR5nZh8zssVRdh9fTTRZ0h00lvfinmW0O128Mr7v3ZTnueAsSWhxgZoeZ2W/D67kn3H9VeLxTzawxaZ1FzvNaM/uzmS0ys/7w2P1hXdxmZq8s9Nhp55kdlnknM3tV+H5Sn/fe8LNwk5m9JMcx3mxmD5pZZ4Z/57VmdquZ7VeK8oqISHmoC5yk7A5MI8jY9HuCFLJ3AH8iGCcCQHiT80fgVcBNwM3ARsCBccBs4BzgLWb2Wnd3IiwIjP4dnu9a4Hpgc7h6ArA/cBLwKjN7ZXR/C4Kip4HmcN9fEYwzMWB8uO93gTeZ2THp587j6wTjpe4CfgasB3qBdoIMVh8Ajjez/d19VYb9fwZ8GLiRoN7WhnXSDuwLHAncZWYvdvclkfdk4favAq4DbgE2AKMIEgi8FvgvcAMwg+ChxUDkvHsAe8V4f7tl2R9gJsG/x6CwXL8m+Pf8CfBC+H5SxgKvA35hZsvc/e9px5zO0O+XxQSJOtqAS4HfAP8M1zlBIo+ovQiuxSHMrI3g+plGcA38ju3Xz5jwvXwSOM7MDnT3rrRD7BFu80vgOIJr+UqCQekt4TnfT/BvPdvdX0gvQybF1peZHQXcCswD/gCsBLoJrvWpwNuAh83saHf/S4Yi7A18GTgwrJdfAtvC93sScLeZnUZwfd5C8JleT/C5ORr4jZk1ufuv0o47niChxReBE4EHCeo8Vb6JwIuBywmu1RNiVNcQFiTF+DnBdX4dQdKCfqCR4DPwRuCfZvYBd/9t0uOn2Tl8nQV8juDzfi2wiuBzMRU4BviPmb3V3YckigkDydsIxqmdS/D9M7ia4Lo/Drg1/K7oLbK8IiJSDu6uV42+CG70HDgyxrYnhdv+DfghMDbLdq8Kt3tnjmO9Kdzm+AzrPkdwYzYrx/6vDfc/JG35DwiCrak59n1LuO9bE9RTK8FN9MU5ttmF4IbxhxnWHRKe88M59h9LENickbb8+Hz/RsCbgc5wu6a0dV8Hlib4923KsM6BU9KW7RYuf1eOYxrwOHBlhnV3Ab/Kst8O58uwzSLgvAzLzyAITGfn2He/8Br7QoZ1Xw/PfxcwPsv+kwgCoh3+rXOcs9j6uoMg8UNrln2bwzI/CViWOl0H7JKlPgYIgoqTMqxvBO4DHs2wbnp47E3AETne24fD7V6e8FpoJwimrgMas2zTQBAwL85WP1n+ne/KsPzIsJzLgAOy7NsE/DVTXQNfCa+NlhznTn0fvCpLXU6Pe13ppZdeeulVnpe6wEm6BuBTnn3iwGaCVqFbsh3A3VM3D6/JsPoI4FZ3n5ujDPcCZ7Jj+tojgV+7e660tn8BniIIGuIaRdCy9L1sG3jQ6vMrMr+n1xK0+GSdSyesz/9he6tHdN9HPEeWPg+eQv8k2/oymRb+N+u/k7s7QZrhP2fbpgyOAG5396ezbeDuzxK0puRKxPARd9+QZf81wDUE11tcxdbXeuAbHmQMy7RvL0HL2YsIWmUyucYztE6G9fEwwTX6iwzr+wlar15kGbpIhi5y97uzrIPg2l9DcD0nsR/Bw4XvheXYgbsPEHw2p4Xbl8JX3D1jlkF37yN42PIighauqGnAInffluPY/yVoHVqcYxsREakgdYGTdD8JbzgyCm+C7gYwsxaCuYYyZfR6gcyTH85gx+5O6edw4MIMq6aTI8hI7WtmC7KcO9s+6wmzjoU3gDuT+bOxMctxZxC0wmStt/A8v8uweDrxbpQej7FNKaVmqx+fayN3v638RRliT4IWhXwWErQGZrLSg0xzuTwPzDAzC6/HfIqqL3f/fzDYlW4CQVCerjv873SCgCldrve0lKA1I9s1upTgmp9M0B0sXXrgPoS7D5jZYoLPQhLTw/8uyLNdav104LGE58jkgTzrnw//O4MgsEtZR/5/Ywe+VnDJRESk7BQASbqn8m1gZm8FLiB4QpqrFTHTE+OxBN25CjEWaDCz3fNs10MwdiC2cNDyxQRP/bMmcMhRrmLeU6a5ctIlGc9UCosIugmdbWZnEdwERsvQC7wQMzgopXFsH/OTy+Zw20wytjRk2H8UQfewvhjbL6KI+jKzCcC3CMYfZSt3Srb1W7MsB+iKsR6CLmmZxK2zfGVPl9q+IxzflU3qIcvkhMfPJt/7SV1j6e/nXuBLZvYZgrFA6WPMNuVoPRcRkSqhAEjS5fzxNrPZBAPH/04QMKxhx0H1AJ8veckCF4SvfO6Me8Dwxut2gpvULwBLyHzTexTBAPua5+7bzOyjBN3+/ptlsy4zuw74jLtvHL7SVZ8S1NcPCQbfX0TQHTP9xhqCAfpXlKjI1SZfi1xKd/5NyurPBF0RLwpfOzCzpcDZ7v7z4SyYiIjEpwBIkvoYQYvFMZ4jw1GYVjdfS00hfkgwziefvC1ZEUcRdHWZ5e7PZdvIzKYkOOaI5+53mNkMgux66e+9GZhFkHlsC3USGOZSaH2Z2XiCLIP/4+5Zx3qlUlnXqHeSv1Wmj8ytysMmbMH7lJldQPDvOTptkw6CQPZnZvaUBxMNi4hIlVEAJEntRZAtKl9612zX1iaCm4RCdAJz3P3WAvfPZi9gY67gJ1SO97SxiH2TnLugz7q7byFIO52RmY0hyACWJADaSuYxLnFsJt77HUNQt8OqwPpKjZt5OM/hq/37upA6T3U1u9PdC+1GOuzcfRlBl8cdWDBv2hEEqcsVAImIVCFlgZOk+slz3VgwEWm2DFwLyTC/S9r+Zmafy9DispDt2bZy7f8tM/txvu0i8r6n0BuyLF8I7JEjg1aqXMeb2cvTFi8imKulUIuAcZZl4s+IVyc5qAUTl54cY9MlwJRw8H5ci4jx75hj3+kxtptB/G5VRSuyvlItH/muwWzXX8WF1/4eZK7zbrKPq0ttn/N6MLM2M3vGzDJlYRw2Zvb+XJOkwmDWumXs2AooIiJVQgGQJDUPeJmZZXyCHwY/l5D9x/8u4Bgz2zfHOV5DkPZ2t7Tl9wAfNLOsA63NbDJBN71YE1iG5gFjzOzgLMc0M/sQ8K4s+99DkLnrwznKNRb4KTum0b4bONjMjkxQ3qgHCZI+fDbHuY8nGFyfxCuAK8LJZ3PZhyADXpJkCPcDJ4Zdv5K6Fzg6TFqRUXhtHUvw7zJciqmvhQTj6LKm7Q6vzbOLLmX5nEgwf9K9GdYtJHuK7WcJ5tX5ZJ4g+n0EKbDjJAwpp1MI5hjKysyaCYL0SpdVRESyqPYuFVJ9fgycDvzLzG5ke4rY8QRPcd9OcENzG5m7Kv0YOBX4r5n9miC9barrywSCm5y3EnQjSh9Mfi7BjdBcM/sNwQ1GalB0O8GYo3cTjBX4WYL3dAfBvEV/MbNrCJ7e9hH0759CMLHrHsCVwMfTd3b3/5jZzwn6/b8NeJQgTbGH5ZrF9gkYr0/b/UaCoPCv4XuaQ9CtLT2geGWmgrv7snA8wtfN7HDgXwT/Ju1h2V8H7E0wj9An4lRG6A6Cf5e7zOx2gpaLaJmaCG7mTwa+n+C4ENxAvheYE77nxcB1YbeifC4lmE8pdf3MZ/v100HwXk8Iy3tpwnIVo+D6cvfNZnYFcIGZHQA8w/ZWk52BQwmCo+8BXyzz+8jmnRmCTgN2Ag4CjgOudfcHM+x7NXAacKuZ3QXc7O5zANx9a5g17yrgxeH61WxvlR0DvJjg4cO1MdKXl9vvgMvD776H2DEj4WiCOcgmAzcMc9lERCSuSs/Eqlf5XgQBxTJg3xjbvpGg1WR8jG0PJciGtILgJs8J+v7/h2Cix1HAeQQTM2bavwM4H3iE7Tf7TpD5agHBJISTsuy7C3A5QcCyNbJvJ/AcQYC1dwF1tSvwc4Kn1X3hMbcSTGx5KUFw9RZgfpb9GwieDv+TYB6VVLn6wn+D3wEvzrJvC3AWwRiQdZF9M72aMuxvBIHf3eG5UnU5D/gRQfD25rBuGzLsPw94S4blhwH/ADZkKEcvQfDxTaA9w75XA+flqO/dCILUpwmSAnwobf0/gI9l2Xcc8F2CQDN6/WwKl30XGJdl35OBe2JcD1nrK8c+xdRXO0ELTyoDXGqfpcBvCQLgiQSf0f2z/Bu+NUfZvglcnWP9AeF1Oz5t+fQ81+MLBEH3x4HGHMd/J8FDjU3AVzOsP5IgiHyeoDUsdfzVBIHGp4CWBP8WXwfuyrB8dvg+d8qz//hwuwMyfNY+T/C9sC1DfWwKy3t0hmOm6nJ63Pehl1566aVXeV7mPtzTeIhIUmZ2EkGA1uzBTPUiZWdm0wkeCrzJ3f9W4eLEZmZfB4509yMrXJRBkbqc4e6LKlsaEZH6pjFAIiIiIiJSNxQAiYhILWozs+kFJtsoKTPbnfLMiyYiIgVQEgQREak1vQSZ+RYSjKMqNO160czsDUC0+2C+OdRERKTMFACJjAwrCObAGahwOaS+bCBIRJAkrXw1uAx4LPz/5ZUsCHAfQWbLJoJkLZUuj4hI3VMSBBERERERqRsaAyQiIiIiInVDAZCIiIiIiNQNBUAiIiIiIlI3FACJiIiIiEjdUAAkIiIiIiJ1QwGQiIiIiIjUDQVAIiIiIiJSNxQAiYiIiIhI3VAAJCIiIiIideP/AzdR66ziOn+8AAAAAElFTkSuQmCC", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "tof_analysis = TimeOfFlightAnalysis(tuid=dh.get_latest_tuid())\n", "tof_analysis.run(playback_delay=149e-9).display_figs_mpl()" ] }, { "cell_type": "code", "execution_count": 10, "id": "1c36d9b7", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:31.430611Z", "iopub.status.busy": "2024-11-13T02:35:31.430012Z", "iopub.status.idle": "2024-11-13T02:35:31.433640Z", "shell.execute_reply": "2024-11-13T02:35:31.433073Z" } }, "outputs": [], "source": [ "fit_results = tof_analysis.quantities_of_interest\n", "nco_prop_delay = fit_results[\"nco_prop_delay\"]\n", "measured_tof = fit_results[\"tof\"]\n", "\n", "qubit.measure.acq_delay(\n", " closest_number_ceil(\n", " measured_tof * constants.SAMPLING_RATE, constants.MIN_TIME_BETWEEN_OPERATIONS\n", " )\n", " / constants.SAMPLING_RATE\n", ")" ] }, { "cell_type": "code", "execution_count": 11, "id": "4f6a7b02", "metadata": { "execution": { "iopub.execute_input": "2024-11-13T02:35:31.435396Z", "iopub.status.busy": "2024-11-13T02:35:31.435229Z", "iopub.status.idle": "2024-11-13T02:35:31.469055Z", "shell.execute_reply": "2024-11-13T02:35:31.468431Z" }, "tags": [ "no_demo" ] }, "outputs": [ { "data": { "text/html": [ "
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