{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "inputHidden": false, "outputHidden": false }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "pygame 1.9.6\n", "Hello from the pygame community. https://www.pygame.org/contribute.html\n" ] } ], "source": [ "from muselsl import stream, record\n", "from linux_muse import list_muses\n", "from multiprocessing import Process\n", "from mne import Epochs, find_events\n", "from time import time, strftime, gmtime\n", "import os\n", "from stimulus_presentation import ssvep\n", "from utils import utils\n", "from collections import OrderedDict\n", "import warnings\n", "warnings.filterwarnings('ignore')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# SSVEP\n", "\n", "The steady-state visual evoked potential (SSVEP) is a repetitive evoked potential that is naturally produced when viewing stimuli flashing between a range of 6-75hz. Electrical activity at the same frequency as the visual stimulation can be detected in the occipital areas of the brain, likely due to the perceptual recreation of the stimulus in the primary visual cortex.\n", "\n", "The SSVEP is often used in BCI applications due to its ease of detection and the amount of information that a user can communicate due to the high potential frequency resolution of the SSVEP.\n", "\n", "In this notebook, we will use the Muse EEG headband with an extra occipital electrode to detect the SSVEP and evaluate it's use in SSVEP-based BCIs." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "## Extra Electrode\n", "\n", "Although the SSVEP is detectable at the default temporal electrodes, it can be seen much more clearly directly over the occipital cortex.\n", "\n", "The Muse 2016 supports the addition of an extra electrode which can be connected through the devices microUSB charging port.\n", "\n", "- [Instructions on how to build an extra electrode for Muse](http://forum.choosemuse.com/t/step-by-step-tutorial-for-making-muse-auxilliary-channel-electrode/3172?u=tttz)\n", "- [Working with the extra electrode](https://eeg-notebooks.readthedocs.io/en/latest/using_an_extra_electrode_muse.html)\n", "\n", "For this experiment, the extra electrode should be placed at POz, right at the back of the skull. It can be secured in place with a bandana or a hat\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 1: Connect to an EEG Device\n", "\n", "*Note: if using Windows 10 and BlueMuse, skip this section and connect using the BlueMuse GUI*\n", "\n", "Make sure your device is turned on and run the following code. It should detect and connect to the device and begin 'Streaming...'\n", "\n", "If the device is not found or the connection times out, try running this code again" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found Muse-8798\n" ] } ], "source": [ "# Search for available Muse devices\n", "muses = list_muses.list_muses()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Connecting to Muse: 00:55:da:b3:87:98...\n", "Connected.\n", "Streaming EEG...\n" ] } ], "source": [ "# Start a background process that will stream data from the first available Muse\n", "stream_process = Process(target=stream, args=(muses[0]['address'],))\n", "stream_process.start()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 2: Apply the EEG Device and Wait for Signal Quality to Stabilize\n", "Once your Muse is connected and streaming data, put it on and run the following code to **in your terminal** (make sure your virtualenv is activated) to see the raw EEG data stream.\n", "\n", "The numbers on the side of the graph indicate the variance of the signal. Wait until this decreases below 10 for all electrodes before proceeding.\n", "\n", "*Note: the extra electrode's data is included in the stream as the 'Right Aux' Channel*" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "`muselsl view --version 2`\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 3: Run the Experiment\n", "Modify the variables in the following code chunk to define how long you want to run the experiment and the name of the subject and session you are collecting data from." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "inputHidden": false, "outputHidden": false }, "outputs": [], "source": [ "# Define these parameters \n", "duration = 120 # in seconds. 120 is recommended\n", "subject = 1 # unique id for each participant\n", "session = 1 # represents a data collection session. Multiple trials can be performed for each session" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Seat the subject in front of the computer and run the following cell to run a single trial of the experiment.\n", "\n", "In order to maximise the possibility of success, participants should take the experiment in a quiet environment and do their best to minimize movement that might contaminate the signal. With their jaw and face relaxed, subjects should look directly at the flashing stimuli.\n", "\n", "Data will be recorded into CSV files in the `eeg-notebooks/data` directory" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Looking for a EEG stream...\n", "Started acquiring data.\n", "Looking for a Markers stream...\n", "Flickering frequencies (Hz): [30.0, 20.0]\n", "\n", "Start recording at time t=1590600387.941\n", "Time correction: -3.2616499993309844e-05\n", "Time correction: -3.848249934890191e-05\n", "Done - wrote file: /home/cayden/eeg-notebooks/data/visual/SSVEP/subject1/session4/recording_2020-05-27-17.26.26.csv.csv.\n", "58.5784 \tWARNING \tUser requested fullscreen with size [1600 900], but screen is actually [1920, 1080]. Using actual size\n" ] } ], "source": [ "recording_path = os.path.join(os.path.expanduser(\"~\"), \"eeg-notebooks\", \"data\", \"visual\", \"SSVEP\", \"subject\" + str(subject), \"session\" + str(session), (\"recording_%s.csv\" %\n", " strftime(\"%Y-%m-%d-%H.%M.%S\", gmtime())) + \".csv\")\n", "\n", "stimulus = Process(target=ssvep.present, args=(duration,))\n", "recording = Process(target=record, args=(duration, recording_path))\n", "\n", "stimulus.start()\n", "recording.start()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Repeat Data Collection 3-6 times\n", "\n", "The SSVEP is a very prominent signal, but visualizing it can sometimes take many rounds of stimulus presentation. Depending on experimental conditions, this may require as little as one two minute trial or as many as 6. We recommend repeating the above experiment 3-6 times before proceeding. \n", "\n", "Make sure to take breaks, though! Inattention, fatigue, and distraction will decrease the quality of potentials such as the SSVEP" ] }, { "cell_type": "markdown", "metadata": { "inputHidden": false, "outputHidden": false }, "source": [ "## Step 4: Prepare the Data for Analysis\n", "\n", "Once a suitable data set has been collected, it is now time to analyze the data and see if we can identify the N170\n", "\n", "\n", "### Load data into MNE objects\n", "\n", "[MNE](https://martinos.org/mne/stable/index.html) is a very powerful Python library for analyzing EEG data. It provides helpful functions for performing key tasks such as filtering EEG data, rejecting artifacts, and grouping EEG data into chunks (epochs).\n", "\n", "The first step to using MNE is to read the data we've collected into an MNE `Raw` object" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['../data/visual/SSVEP/subject1/session1/data_2017-09-14-21.32.15.csv', '../data/visual/SSVEP/subject1/session1/data_2017-09-14-21.25.17.csv', '../data/visual/SSVEP/subject1/session1/data_2017-09-14-21.22.51.csv', '../data/visual/SSVEP/subject1/session1/data_2017-09-14-21.29.57.csv', '../data/visual/SSVEP/subject1/session1/data_2017-09-14-21.20.04.csv', '../data/visual/SSVEP/subject1/session1/data_2017-09-14-21.27.36.csv']\n", "../data/visual/SSVEP/subject1/session1/data_2017-09-14-21.32.15.csv\n", "Creating RawArray with float64 data, n_channels=6, n_times=30732\n", " Range : 0 ... 30731 = 0.000 ... 120.043 secs\n", "Ready.\n", "../data/visual/SSVEP/subject1/session1/data_2017-09-14-21.25.17.csv\n", "Creating RawArray with float64 data, n_channels=6, n_times=30720\n", " Range : 0 ... 30719 = 0.000 ... 119.996 secs\n", "Ready.\n", "../data/visual/SSVEP/subject1/session1/data_2017-09-14-21.22.51.csv\n", "Creating RawArray with float64 data, n_channels=6, n_times=30732\n", " Range : 0 ... 30731 = 0.000 ... 120.043 secs\n", "Ready.\n", "../data/visual/SSVEP/subject1/session1/data_2017-09-14-21.29.57.csv\n", "Creating RawArray with float64 data, n_channels=6, n_times=30732\n", " Range : 0 ... 30731 = 0.000 ... 120.043 secs\n", "Ready.\n", "../data/visual/SSVEP/subject1/session1/data_2017-09-14-21.20.04.csv\n", "Creating RawArray with float64 data, n_channels=6, n_times=30732\n", " Range : 0 ... 30731 = 0.000 ... 120.043 secs\n", "Ready.\n", "../data/visual/SSVEP/subject1/session1/data_2017-09-14-21.27.36.csv\n", "Creating RawArray with float64 data, n_channels=6, n_times=30720\n", " Range : 0 ... 30719 = 0.000 ... 119.996 secs\n", "Ready.\n", "raw is\n", "[, , , , , ]\n" ] } ], "source": [ "raw = utils.load_data('visual/SSVEP', sfreq=256., \n", " subject_nb=subject, session_nb=session,\n", " ch_ind=[0, 1, 2, 3, 4], \n", " replace_ch_names={'Right AUX': 'POz'})" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Power Spectral Density\n", "\n", "One way to analyze the SSVEP is to plot the power spectral density, or PSD. SSVEPs should appear as peaks in power for certain frequencies. We expect clear peaks in the spectral domain at the stimulation frequencies of 30 and 20 Hz." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Effective window size : 8.000 (s)\n" ] }, { "data": { "image/png": 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SdXXkMmAE8IrveWvJ2NJO2pYCIU1lnbt0CrN/fxnDjh6JLeNOnI5peJ3RXa8rFDQ1Nfm/nBRSj0jkKTVNE4szCW8UVxRoampScXDtaGpq8hvuQ6mpqWHZsmVcdtllEe5V6ElOTubqq6/miSee6LJNU1NT2PZntcHmBKHr+iTgK2AzcKIQwtB1/QrkcuQcIcT6Q9r/BzhLCNH7okny/XVxcXFpmzdvxuPxsvqGuzjlmfsC2nx8xxPoS+eQN2deUJ9poNB6N6xinSSR0sPldiHOO5qsJ18lZ8SEsF4rWNTYCORwejz++OOsXr2al156KdLdCgsFBQUcd9xxHDx4sNOqA92NjZkzZ9LS0lIvhEjv7bUHfJhAe3RdzwHeBWqBC4UQrYFBrbeOnZWMjW/3elCkZ8owgfLi/cSkdgywTNUnULFh+6A3cAN1MzxcREoP0zQwTVtU78GpsRHI4fR46aWXBvTe26FMmDCB/Px8Vq1axamnntrh9XCOjUGzRKnrehrwPpAGnCGEKGv3cuvSZG6HN8pjfXJ1HHeUDD7a/FgpcSM7bpYOnzMVe8GeDscHGwkJCSQkJHTf8AghYnoYXgxsGEb0Gjg1NgLpSo/a2lo2bNjA6aef3g+9Ch9Llizh3Xff7fS1cI6NQWHgdF2PB94GJgJni/Y7x5KtgAcCE7Tpuh4LzEQ6mgRNsm/i3LJlI0NnHN3h9dxJ2biqHbij2I07FNjtdr/DgSJyepimCaYNM4rj4NTYCKQrPT799FOOPfZY4uPj+6FX4eOMM87go48+6vS1cI6NAW/gdF23IoO1FyCXJb88tI0Qoh4ZCH6Fruvt1xCvAJKBV/vSh6Q0jYYqB8njtzHulI7ryNYYDcPt5N/39SkaIeo5ePBggFfXkU6k9DANAwMbZhQvUaqxEUhXenzxxRccd9xx/dCj8DJz5kyKi4v9XpLtCefYGAx7cA8Bi5EzuAxd1y9v95pdCPGm7/GvkSm8Vum6/gwwErgNeF8I8XFfOhAbZ2Pvl3tJndh1LMforFGkbHHR1NRAUlJqXy4XtYwaNaq/uxBVREoP0zAwDRv0wZ063KixEciherhcLg4ePMi6dev4xS9+0cW7Bi42m40ZM2awZs0aZs2axfDhbY7r3Y2NzlIh9pQBP4NDLjECnAM8d8jPo62NfN6TpwJO4BHgOuBp4MI+98AEe9FuEsZ0/YuqGXkLjTGnsXfz6j5fLlqJj48fdEsrfSFSepgYGFG+RKnGRiDt9WhoaGDSpElMmjSJ9evXM3ny5G7ePTDRdZ0f/OAHjB8/nkceecR/vLux0Zc0ZQN+BieEOKkXbdcAC0PdB8Nr4iw/SM7Crgfmgltg03MTqdvwNiw4J9RdiApaA4BTUlL6uSfRQaT0kHtwVkwzeg2cGhuBtNfjr3/9KyeccAJXX301ixYtGrSVF9xuN/Hx8axZs4Y5c+Zw/fXXk5iYGNaxMRhmcP2Ox2vgaaghvRt319y543HuqTxsm4FMSUlJQCaFI51I6WEacgZHFNclVGMjkPZ61NXVMXXqVMaMGUNubm6fkgtHMyeeeCLHHnss48aNw+v1+jOUdDc2+lJvc8DP4KICE3A2kJZ5+IQoGeNiMeoGr+SjR4/u7y5EFRHTo3UGF8UGTo2NQNrrERcXh8PhoL6+nszMzP7rVJgZOnRoQJq3uDgZltzd2FAGrp8xTbkPYulmM9QWC6Y5MMpeHPwWRvSy6n3rgFVIIqWHiQGGRQ7EKEWNjUDa6xEfH4/D4Qj40h+MNDQ08Pbbb/tnbzExMn44nJ95cM6FI4yj2QR6dpdhdlHqPdr46Pbev6ehocGfmFcROT1M08TEilxKiE7U2AikvR6maWKaJpqmDer6kUlJSQwbNqzDZw3n2FAGLgQ0NRhYLD0zcBYNvvndEjxRHPQd7N9YaWlpQPbyI51I6SHDBCxR/eWoxkYg7fWorq4mMzPTP5MbrGiaxoIFC7DZbKSkpPirWIRzbKglyhDQ3IDfwNnZSLI/cqEjI8efgX1LDbs2r2XK7JMi1MPe4XWBNVYaut546I4ZMyZ8nRqARE4PXyYTM3r34NTYCKS9HtXV1cyePZvMzEx/uZnBSKshB7kfV1VVRUZGRljHhprBhYCmBgPNYmBi0sAXh2078poT0Y76IQe/2hCh3vUerwvi08HdywoWsbGxxMbGhqdTA5BI6WEacg/O8EavgVNjI5D2elRVVTF06FCysrKorq7217sbbJSUlJCTkwNIA9dqzMM5NpSBCwH2erDYvOzjd7gpxaDrulxJWTDq7ElQHL3LNV4XJGSCq5fp4err6ztNxXOkEik9TExM04ppRO8SpRobgbTXo3VmExMTw8iRIwMK8g4mCgsLGT9+PACZmZn+YqndjY2+BHorAxcCnPWxxCY7SUQnkWl4ObxlSB2XiKUuep1NvC5IGAKupt69r6ysLKBC8JFOxPQwTEDD9EavgVNjI5BD9Witgj558mS2bt3aX90KK9u2bfNnaWn9vND92OhLqi61BxcCYlpsmPFJDOFM3FTgpoIYMrpuHw+mN3rvLTxOiEsFTy/3u8eOHRueDg1QIqWHYRiYmkYUb8GpsXEI7fW48MIL+e9//8uiRYuIjYvlnkfv4fF1j3PdGddx4fF9zyTYrzia4dU/0VK2n21bt5Cdnc2+ffvYsmULp512GhDesaEMXAhIMa14rOOwkYaVVGpZQSKT+rtbQeN1SQPndfbufa1xLQpJpPQwPAZoYEbxHpwaG4G01+OKK65g8uTJlJaWsvbLtTSajWxN3sonGz9hxtgZTBwxsR972kf+8TN493G+qIYcm8YpixaRmpbGZZdd5s8/Gc6xoQxcCEjwmsSkyAoBGhqgYfpikrQu4t4smhWHy0l8bPQFdnp9Mzh3L+uct7r9pqf3urL8oCRSepim6ZvBRe8SpRobgbTXIycnh82bN7NixQpS5qXw6h9fxXSbmDEmB6sODmwDVyyXW1dUwtUjTObd/WtihuWxaNEif5PuxobHE3wZqOhdJxtAJGMhZkjgL6eGt6njI0w6T4Abn5bItw8W4nFE35eS1wVxab1foiwvL6e8vDw8nRqAREoP0zDBAkYUGzg1NgI5VI+8vDyuu+46fnnlL7ENs0E5HD/1eBZOCXlueECGAG1+HlbeDVWHlocOJWdehwm8XgbnHHc0Z19+LWeccUbArC2cY0PN4ELAwsQq4tKH+J+buLGQSANrsZJGKsd0eE/s6DxYdh9Vp/+GnLkTItndbmldonT30slk3Lhx4enQACVSepheAxMLpid6lyjV2AikKz1mj5/Nk/c9yT/+8Q9W/WlV2BIvf/03eP8m3+O/wk2FkBiONJinXMFXjTFYtv2MOU991mlgbTjHhprBhYBhNhfxQ9tGRxz5JDCeLC4BDLx0DCjLXjiLNI+gYPWKCPa0Z3iCXKK02WzYbOqeqZVI6WEaBqZFgyj2olRjI5DD6XHpxZeya8cudu/eHbbr71sDrbsnjjqo3BG2S/Hk8g+47sc3ocV0HusWzrGhDFwIyLA6SWpn4JKZQTyjSWA8jXxFFa90eE/erGmYDz2Nq3B/JLvaI4J1MqmtraW2tjY8nRqAREoPwzBBAyOKU3WpsRHI4fSIj4/n2muv5bHHHgvb9Sedhz91aVo+5HSdfKlPlJaWsnz5cr7//e932SacY0MZuBCQqHlIGZrW4biGFSf7sXURMjBx7ixMV/AxHuHC64K4FDmT6w0VFRVUVFSEp1MDkIjpYSJncNG7QqnGxiF0p8ctt9zC888/H7YaekddAtd+Duf+C364DuKSw3IZHnzwQa688kqysrK6bBPOsaHWDEKAhoWElM6n38O5mWa2H+7NUYfXBbZ4ep2cvjVLgUISKT0MT/QHequxEUh3euTk5HDttddy991388wzz4SlD3kL5E+42LNnD88++2y3gevhHBtqBhcCtjWNwtLFrUI8+ViI6TJ9l2Y1qSmCim1h7GAv8TplsuXeYrVa+5R1YLARKT1MDLBoeKM4Dk6NjUB6osevf/1r3nnnHb755psI9Sp0mKbJT3/6U2655RZyc3MP27Y7LfriaKMMXAh4vfLYw2bdt5CMl85dEmMyvHz5NycHvgpT54KgtZpAb6mpqaGmpib0HRqgREqP1jCBKC4Hp8bGIfREj/T0dB566CGuvfZaXK6u89tGI6+99ho7d+7k5z//ebdtu9NCGbh+prswRCvJGF3kp4zPS8HhSzoaLfS2TE4rlZWVVFZWhr5DA5RI6WF6DUzNEtVLlGpsBNJTPS699FLGjh3LL3/5ywj0KjTs27ePG2+8kWeffbZH1brDOTbUHlwIiPEMOezrVlLw0EgNT5DN1ViI97+WmDeUmfN3UL95BB4n2KIvsUmPmTAhuuL5+ptI6WEaMlVXNIcJqLERSE/10DSNf/7zn8yePZv58+dz0UUXhblnfaOlpYULL7yQ2267jWOO6Rj/2xndaWEYwS+9qxlcCKhI3HTY12MYSh2fYCEBB3sCXovPHM7qL5dhSbHjGODVRCwWS1DLCZufh5rwhfz0G8Hq0VsMwwSLFtWZTCKlxUChN3pkZGTw5ptv8uMf/5gvvjh8vcn+xOv1cvXVVzNu3Dhuv/32Hr+vOy36YuCCmsHpuj4RmAoMQ678VwJbhRAFQfdkAOO0HX6J0UoiseSSzGw8BLZNGTGR5Cd+QmNeFq5Zv5GKDlBaCxi2Vu3tKQe/hqEDNzd1lwSrR68xkbeq0etjEjktBgi91WPmzJn8+9//ZsmSJaxYsYJZs2aFs3u9xjAMbrjhBiorK3nvvfd6VcMtnGOjxwZO1/XJwA3AUiDHd7j1U5i+NuXAK8CTQogwxsZHF4bWfTLQLJZi4KKK10hmDhrSayh71BSm/OYdKp9+BmdDuHvaQ4KcCLQWMOztQE3MgpZBGAMcrB69xfTIGVw0J1uOlBYDhWD0OOuss3j88cc588wzeeONN1i4MDx5KnuL2+3mmmuuobi4mPfff99fJaCnhHNsdGvgdF0fB9wPnAe0AJ8BTwJFQDXSyGUA44H5wA+An+i6/gbwCyHEIFx8OgRLz26dLcTioRo3lcT67xFg6tgZrIo1cDWCeBvGnd75XlzFNhg2NVSdDj0TJwaX9TwhA1qqQ9yZKCBYPXqLiQGahhHFYQKR0mKgEKwe559/PklJSSxZsoRHH32Uyy67LMQ96x3V1dVcfPHFxMfH88EHH5CYmNjrc4RzbPRkBrcd2AJcDbwhhDhsCl5d15OQs7ybfe/tnTkfgJiWzisGdEYCk6jgOYZzCxba1UFKNNj9gZvavTFkTICsQ5bsTBPeuxGu/jR4L8ceE+S5gy0tH5MA7o7pOgc8werRW0yvCRZLVIcJREqLgUJf9DjjjDNYuXIlS5Ys4fPPP+eBBx4IyrD0lbVr13L55ZezdOlS/vSnPwUd5xjOsdGTXc4LhRBzhRDPdWfcAIQQTUKIfwshZgMX972L0Y/L7HlOqxy+z1AuopnA6P7E4VkMm1NMWj7U7+v4PmeDXMpzNsLrl/a1x93QhyXKqigLeehPIqWHKROZRHVFbzU2AumrHkcddRTr1q2jpqaGWbNm8emnn4awd4ensbGR2267jQsuuIDHHnuMBx54oE9B/OEcG90aOCHEW8GeXAixPNj3DiQ8WudBmGYXyW9tpGMQmKo/JXsUbkshw44CeymsfUAaMwCvR+5RZR8FZRvbvsgawpOmrg3N9+XZQ6qrq/0bxooI6mEYYI3uODg1NgIJhR7p6em88MIL3H///Vx99dUsXbqUnTt3hqiHHXG73Tz11FNMmjSJ6upqtmzZwuLFi/t83nCODeW3GwIsnWT9KDYP8JjZeQ45CwkdDFxG9jiajJ1MOlcWGnU1wf4vwPDCJ3fAhn9C3kLY8gIkDYPGMlh+TTg+TRu2OJnVpKfouo6u6726hifIrCkDgWD0CAbDK+PgotnARUqLgUKo9NA0jSVLlrBjxw6OPvpojj/+eM477zxWrlzZJ/f69lRUVPDAAw8wbtw4Xn31Vd58802effbZwyZQ7g3dadGXUjrKwIWEjgNpLwdI01I7ba0Rg3lI/pNhI3UayvcQs+dzMidK41K/D3YsA80KpesgYzyMPY9NcqoAACAASURBVBWGToYPfwZDxsgZVnOYboxt8b2vCddb3E0Qm0xUJp0eKJgmWOPcaFFcLkcRXhITE/n5z39OcXExp556Krfeeitjxozh1ltv5eOPP6apqefVi03TpKioiCeffJKzzjqLiRMnsnXrVpYtW8ZHH33EvHnzwvhJQktvwgTygPMBF/C6EKLCd+x+YBGQAnwL3CmE+CwcnY1mTNNE0zSKzf1UUs0uisgiE8M0KKWCEVqb16TWybe5NiSbZEcz3zx8FVMe+pxRJ2Tx5WMQnwb6YulpmJ4vf8Q7YLghcSh8/pCcZZ3wq9B8DsMrDSpIA9ebmnCt6XZ6c2fnsksDNxjDBILRIxhMw8QW58IdxWECkdJioBAuPZKSkvjxj3/Mj370I7Zs2cLy5cu555572LRpE+PGjWPKlCnk5+eTk5NDUlISNpuNlpYWamtrKSkpoaCggM2bNxMTE8NJJ53EVVddxcsvv0xKSkpI+9mecI6NHhk4XdcnAV8ijZgG3KPr+gnA+8AYoB45jTke+EjX9YVCiHUh722UYnoNnLiIJ44DlLLSXMMsbRoZpPOA+TgAP+IqUrS2okuHzuCwWBhur2Gr1UZW0UZGzz6NlOGQMwsyxweWtZj4Xflvwfuw7dXDB0mbpvzpaRKJkm/lXh9IA+dx9Ox9gL9oYa8MXOsMbhASjB5BYXjBSlQHekdMiwFCuPXQNI3p06czffp07rrrLhwOB9u3b2f79u3s37+f4uJiWlpacLvdJCQkkJaWxuTJk1m8eDFTp05l5MiREfN87U4Lr7fnXuqH0tMZ3M+BWOAWoBT4PfA6kAjMF0J8DaDr+mnAG8AvgQuD7tUAQ0PDhZt44qinkdFaPmdwEs20cEArpdqsYy8HmEabJYpnDHY2kkxbKV3PVfex973HGXtwF8w+jSkX4C/D036stT5OyoIT7oSKLV33rUpAbVGbUeyO+n0w/ju+PqbLmVX6qJ69N5h4FpcdYpJ6/bYBQaRivwyvKWfdUTyDU3FwgURaj/j4eGbPns3s2bMjet2e0J0WXTnr9YSe7sGdCDwthPirEOI14FZkqq6HWo0bgBDiI+Bp5EzuCELDiVzL8+DhSm0psVos6VoaF2vncq32PfZxMOAdCUzGRaAb5IQREzl/8U00FW/GNE2sMaC1NMLny2hsbmTt9rUB7UfMgxFzISZRzoTcDnAdEk/WXAnVvUig5rJDrM/gJGZBU5iLMLe/niJIfKm6ojmTiULRH/TUwA0HNrd73jpn6KxU9VbgyMrHY5o4ceI0XXjpOJ2O02Jx4Q441roPZ7Zrb7FYGJEzlo+2fsYH93yXOnsdRes/wLN9LX956y/c+Z87O718ygio3gVf/QV2vBH4Wm8cUEwT7GWBM8TmXlSxCKb0vKsR4jr3xRnwBKNHUJgGmtWM6ji4iGkxQFB6tBFOLXpq4OIgwK+99XFnOzTOXpx30PAJa/mF+QeKzL2dvt6ZY4mNDLyH1InTNI3kyQs42uWgYueXbF31Imsr91H81VvMb2nsdLo+Yh5883eYcYV0OHG0y2npqJOOKj2huRpq2xU76G2YQH19PfX1vSuJ4GwYvAYuGD2CwTAAqxnVS5SR0mKgoPRoI5xaqHpwIcCiWVlnbsbAS3oXoQGN2HnQeILbtOv9m7dWkvBix0agBTp78U04y/dg++wV0tOGYnrc/J/HA1kjsbfY8Rpe0pPT/e1tcXDSbyAlFxIzZdxc/vFw1CX0KitJcyXMvra3n76NYGp+ed1gjem+3UAkYjXQDAPNZkb1EqWqBxeI0qONcGrRGwN3lq7rrb7uicivzgt1XZ95SLs5IenZAEIDvHg5UzuJIaR32uZUjmevdoANbGU20k3RSnLADM7AiUYsE8bOwJk3ife3fkZz3iTSijYyYsREPJnDKSwp4NMtq/jpeT/1hyYApI6Q5xh9Mqz/BxS86zNwQMk68Dilt+WYk7r+HBXbILcf96DDnmNzkGIa+JYoo9fAKRT9QW8M3KW+n/Zc30XbI+ovTUMjkQTO5rQuXWtztGFkm1ksY0U7A5eKmyIAWiigghfJ5XpiySYuJo49Q0cyM3c8FXGJ2Idkk1RSxAsv/YHE0dOgoZq/fPpfbj735oDrxKfCot/Bga/A7lvWXvR7+ORXcqbnmCU9JVtDAQC+/jvMvR4aS2Dy+cHrUF5eDkB2dnav32uNAcMzuGZzfdGjN5imAVYT04jeu4NIaTFQUHq00Z0WfSmU21MDd3LQVzgC0CwaI8jpNm5E0zQsZlsbGxm4kU6oDnaTyGSc7CcW+YueNnoak/ImkZyQzIhho3Da4jhnxVMY6cNwv/ko6yr3smrzKk486sSAa+fMgC8egWoB2TMgIV2mw2qqhModMtbN44SsKdLoFa+SBm/kMR3j5ayxMp2WrQfptBobZfLMYP5oW2PuBpOB64sevcIwsVhN8ETvfWXEtBggKD3a6E6LsBs4IcTqoK9wBGC1WJmm9TyvXOvSooaGiRfT918mi2ngc3+702adBkBuRi4AdZoFV1Y+Y7Ly2PraA5w9dgYrN63E4/Vw6qxTA66RtwBGLmhzEsmZIV3+P7kDxpwC+9bIGLsPfgozroR1T8Hi9qkza0ohI5dEnydl6xLo4Rg/fnyPNTgUa5w0unHhS5gQcfqiR28wDRNsBrij18BFSouBgtKjjXBqccR5O4YD0zQ5VTuhR22HMZTP+db/3EYaXhrw0oBGLCZduy2mpmSQetEdxC44D9Nq4xzDy28v/CV7Kzp6bs69HnKmyzg5gJlXS4N21GWQnCOXA7e/Jj0sc2fDsbcfUmR1xdMAZE6Us75w09usKYo25B4cmCFKrqtQRBN9CfTuSUXvlUGc1xRCnBLE+wYkHo+n+0Y+5jGDt/iQBtNOqpaMlRSa2QGYnYYStMdisXC0fjQtzha+XXAus3PGwb7txMfGs7FoIzPHzcTpdhIX07EcuKZJz8qcmXDgSyjfJJcDJ3wXhoyFuEPTZRVvAcMgfZQFsRxGnwQW6+GdQMrKygDIycnpulE7vJ6286WOhNrdkDayR28dEPRWj2AxDQPNakR1HFyktBgoKD3a6E6LcKfqGktHp5EkYKjvcZ3v31b3wSo4JLhrkNObO4wYLYZF5nEsZwVXsBQrSdhZz1CW9vgcCXEJLLji9zAkG95/ioU5Y/nDX37A0hMuZr3Xw2UnXYbT7WTCiED325FHy39zZ8tZ3J5PYOwpnRg3j5tNxVuZYa9FS81k1ImyDt2BL+CYn3Tdr95kLAf49G4Y5Zv4DtXl+Uf3bCI8IOitHsFimibYiOpqApHSYqCg9GgjnFp0a+CEEKPbP9d1fSzwKfAYcL8Qosx3PAeZg3IJcMTM3qD3m6BDtDRSTGlVbKRjIw0bvYt2zsnw3e3ExjP6lfs4I3MEntLdCFcLK9atIDUxtYOBayUuGeImysKqiZ3kN/U01SOcTcxorIHUTDInws434eDXh49bGzduXK8+g6MWhk2TjwdjeEBv9QgW0zB9YQLRO4WLlBYDBaVHG+HUIphA70eAz4UQt7Y/6DN0t/gM3SNIQ6fohhiyyKSjb76BCzeVxNGNd8fQkaDP51RXM980VJMzdCTb9m1jxpgZ3V579ImdH3c0VOFITMNtryMGiE2UGUcMj8xr6WoEWwLEJEjPzPxj5XKjtQejqTXW7bM/SieYwbQk2W+Ypgz0juIZnELRHwTjZHIScDivylW+NkcMwXyxDCGdteY3NJnNAXtvpm81uJmt1PJhx2vhpZFv2g4cdSKc/SPSF11JdkomV1ljaHG24PK4WL1lNY3N0gW3prGmx31z2mvRhuTQUNOWDNpik4VWP7lDBo6Xroe6vVD0gXx95Z2wbWWVfz29laKP2hJA1x+QFclNUxpL/ZBq96YhXxsslJWVddAjHJgG8i85isWLlBYDBaVHG+HUIhgDZwKTD/P61CD7MmAJxsDNYDLfmBv5gs7L5rmoIJZcqlkecNxDLc2ItgNWG2TlwYQ5TE9MRW+q55TGamaMmcH6wvUs+f0SNhRt4LHlj/W4b057DbbMEbQ0tGVaTsiA/ONg1IkyUNxik84qybmyikHGeDj4rUFzs7RmHl+h1Pp9bQmbK7dBTZGc9eXMkvF57UkZAQ2BRRdCzqbnYM2fw3uNVpqbm/16hBMZ6I0vKWV0EiktBgpKjzbCqUUwBu5D4P90Xb9S13X/1EPXdU3X9auQ2U06Tj0GMcEEIqZradxiuQ47HTdYZWycBxM3dtb7Z3UAbqoxOnkPAAnJWMZM5+SkdBZMms+kvEnMGTqS11c8Tdm2NXi8PfP2dDfWEpeVh7OhrRRBUpasID73BunOP+50qNoBKcPhw5/JGLs45zBsZWMBeO0SqNguy/jsWyONoL1MJobe/bE0iIcyfC6svrdHXQwawyM/SyQYO3YsY8eODft1NNNEs2ohmcA18nX3jYIgUloMFJQebYRTi2D24H4KzAP+BfxJ1/XWamMTgGxgv6/NEYPVag3ZuTSsuKkgjlya2YmNIRg0YUU6pbgoIYYush8svgniEhg29Tj4+N+cHBuPHpPA87s3cEpWPpt2b2LOhO5Thbqb60nMHo2rpNB/LG+h3DvTNPjOo7KIdGoeTFoMY0+FrS+B4Yady6RHZMoIeO/H0hDuXAP1++Wsb8wpsPq3HZcnAZKGyjAGlZOydxiGzKajhWAGV8nLpHB0CHqlUISGvny/9nrqIYQ4AMwE7gdqgaN9P7W+YzN9baISXdfjdF2/X9f1El3XW3Rd/1LX9T55ffZ1c9802xwEbKThoBgr6YBGLLm0UECjLzjcwImNFIzOAsLjEuS/eZOgtIj4VS8wpq6CYx1NzM4Zz13/vYtVm1d12x9PUz3pWXk4XW0VkiyWQKNjsbZVHohNhNnXwPBzSsmcX03B+zKTStIwaQhNA6zZuzANOeOzl0FMkrfTz5A0DN47TChCX/B6ZEB0pCgtLaW0tDT8FzIMsGiYWvTuwUVMiwGC0qON7rToLgXi4Qgqk4kQol4I8SshxFQhRILvZ6rvWF33Z+hXnkVWJP8vcDNgAO/rur6gPzqTSAJF7GUFqwBIQKeRr7GRTgyZxDAMO9/ipsJfHNVGJh46Oo3U8knbk4t+CT95Em3h+ezNGkVeVh55Q/P4f+/8v24DJ71N9WQOzcPhdh62XeYhUQhOp4OUiY0UfQB5xxlkLNxIc42D3LluRnz/RRb+3IvFInNgVmrPs5/7OpwzOUcaz9bJSOlGcPhKRZX4tisbSrr3p9j8QsdjzVWRW54EcDgcOBzhT89iGoYULYojvSOlxUBB6dFGOLU4ourB6bp+NHAJcKsQ4lHfsf8gq5DfD0Q8zDiNFARF7Ed6LFpJxUU5NtJI4ii8NNHEJuLIx+VrI5M01xBLW+S/Fzt1fEI6i6RXZnyS/Fl0Odcsuhw+/BeP//hxVqxbwd6KvSTEJZCVloWtE99+h6OJkZnDKfO4O7x2OMaMGQNA4oOriM8ezqQLHWz/Vzlzbo6hiYk0swMPtUxZejwe6khgIiYetHbDMP84cNmhqVyGIhz8GvZ/LkMatr4knVO++X8y+8r4M2XbuDRIzm6bYZomFL4P0w+pfdFUIeP+7OWBy6DhWhJt1SP8GKDJzKbRSuS0GBgoPdroTgujD0vv3c7g+rJ8p+v6qd23iihLATfgTysshHAA/wCO03U9N5iT9uUXkEoKBeZuMnxFTzU0YhiKho1YhmMjHQtJxJKLnfXYSCGGDDxUUsoT/vO4qCCZGbipwEsz3k4cUSwWC1NHTeX2f97OC6te4L6X7+t0edXhcpCa2LPA8xZ2Y2cTjXyNnQ042APZ66hnDZm5w5n7q51oCY0kMR07G3FRwvC5BolMIpXjqOXjgPNpGgw7SoYh7FwGR31P1rFb/w+ZymvVb2D2DyAmST7+6i/w+vdg17ttlcybq+Vsbdur0rnF65Hem5v+DWn5soK4s9H3WetlEPuGf/Xo40YlpmHKDU6idwanUARLWA0csELX9ZW6rp+t63q3Oxi6rsfoun6eruurgfeC7ll4mAXsFEIcmkrsa2Td0kOLt/YIwzCoqqoC5H6aEILq6mr/a0IIamrkkqLX60UIQW1tLQDJ3kQKGnbjaZYejm63m4aKOH8Jd4/LSm25QXODDSf7iHXOokAcoN65Ey+NtDiaEEJgbykliek0OHchKp+h2vEVIF1whRA4PR54/Cdk1VRycVo+FiycMO0ENhVu4usNX7Nl9xZAlq6ora/F5XIBJg0NDQghfM9leXkhBG63nN1VOD5kb/UKWrx7Odi8jOLq96mva8BhFhNDBna7nb37t2MzhuGmFHtLBTv3rMJiJhNPPpWu99hZ9AXNbMfBPiorKylv3sWelVBXDPUtFXjzCkjMhIRMiB1RR7W3kLR8aaRicxsYfUkpW1+ED2+DPVsr2LbmAKfcB6Ub4K2b7XzxfBk7l0sHlgZPCQ3uUpp8s7gVdzWy7nm7v+rCgQMH2Ldvn/93u3//fvbv3w9II1m0fT/b17btF+zdu5eDB9tiG4qLiykpkTPtkpIStm3bFrC/sHv37oCYn6KiooDnhYWF/vpYAAUFBVRUVPif79q1i8rKtvANIQTNzXY0zYKG0aux5/F4EEJQV1fnH3vNzc3+sedyuRBC0NAg7xycTidCCH95E4fDIceeXf45tbS0IITwp15qHXvNzc2UlJRQXFyMEIKWFrm3a7fbEUL4l6caGxvlWHXKpfHuxl5dXR1CCH8u2NraWoQQ/iX4mpoahBD+L8jq6mqEEP6buqqqKoRoC7mprKxk165d/ucVFRUUFBT4n5eXl1NY2OZ4VVZWRlFRUcDz3bt3+5+XlpayZ88e//NWDVof79y5k7172xKlH27sAezbt48DB9rcGw439gD27NkT9rEX7Pde+7FXUlLC/v37EUJ0OfaCpSdLlLOAh4G3gEpd1z9GGoQioAZpGDKQXpTzkWm60pGhAkEZjDCSC3QWadU6CoZHsC8AZJOFBV/pHN8fnqXuRFodJS0kYrHPQEvQyOVHuPCgoeHVakliGk2WbzGSKqmLWUsmf6RRKwCz432Id8H5sG8r2jcvMslpx22xMm/iPH73wu/YfXA35Y3lPHTdQ+g5OqZp0GT5Foum4fa6MBJ3AnIZocW2ASmj77xaDZonA7dWhelOxHAlYzEyiUmtwaIlgebFtNmxkUY84/GY5XizX8WG9CRJcJ5Ek60OJ4203mOYmMz7EaxvV75n6kWyqoE7Tn55DZsGU5ZCyU7ImOIiM00GkVduslH4bjwznpQenM6YZjb/KwFPBZx8rwzizJzqonQ9xA8BZ71G9jwn1rhkvB4o+yqWobMdGEbgllbDQTlLtOXF0FIZAwu7/926XK4+3X32HBM0mz+cpKVawxkrZ7m9P5WGGYaZoMvl6lVS8sGOy+XqUxLhwUQ4/060nnoA+pwwfgScCyTTMQGzBjQAbwCPCyG+IcrQdb0I2CaEWHzI8bFIg/0TIcTfennOuoSEhLSNGzcG3S/TNPmYzziWuSRpiT16TwUvksIcqnkbCwk4KGIMD1LLCmRlghiGcFrgm179M5XHekh5ZwsuWx6p1/6Zf330L8pqy1i9ZTWXnnQpR40+irjVzzLsmhMo++fXJJ99AbZhaxjBzZh4OcADDOMKYsnByT5qeI9U5lPHSiwkkcI8Upnvv6SLcur5jCxfMukGvsTBHtI5kViG46WFtfvuZ1x+BglMJIVjaGQtaZ6z+eoxOPa2rjVoqZNB5JkT5GyspkjG2E2/rK2unGnCy+fD+O9Ir0+Lz/Z//Xe5z3fUpTKsYe8aWfjV8MjCr1VC7usd9T3Y+oqM+WuqhJHzwets8yBt3b+zV8ig9hFzZb7OfWvlvqGmQcU2GShfu0emNQuGw+0T/u/R58jIW0fp/4Zx2mO/Yudb0llnZBfe/oZXfk5bx6IT7OEORnEPFuKD66hCEWJmzpxJS0tLvRAivfvWgfTYyUQI8QXwhW+Zcg4wBchCGrpKpKPGBiFENG8EtACd/Fn7/5pbOnkt7GiaRqqZTCN2kuiZgcviIsDCUC6glCcYxb2+eWCsLxDcgpdmGvmKVI4DwJXSSHNaPVxzDkP3jIMNH/P9077Pzsr3yMlM44udX7C7bDd3jBhFHY2k5YyhovwrUizTaBi6hkSmYtCEnXV4acBDA8nMJJHJVPM2oBHPqIB+xpLNqs9MFs+XZXxSmU8S07AgQxqsJPDGqm+45aw/kDC0lFpWYCURqw3mXB/4mQ/yKMP5CRrSSiWkt2VD0TTIHC9/ArWVe3pzfxh4PC1f7u1lTpTP00fL6gpzroeC92He/8lMLavuhcYScNRJJ5WkLLk06vVATYHcAzz7cTl7tMVJA2cvlwHrCY/JCgkpw+W+4MGv2gycaYK7GWJ9syzDK48d6vPjcckMMA0HYcJ32gx0+yrrrooYLKNsgInbAfV729p1xsFv5LXHLur4WktpGmZuNP8JKxQ9J5g4OK8Q4mshxLNCiAeEEA8KIf4thFgX5cYN5FJkZ44krcdKOnmtW0KR5DaVFBp6UWVIw4qGRjyjsZHuDwSPZ5TPK9GkhrewswEXJbjYT+lJDWQl/R9aTAINE1w4S1bBni1kpTRz0SnH89sbziI5Yx+GpQYvTcSPrEbTPuC1T77BwIGTAwzjCmLIwk0l8eSTxEyspGDQjHbwErZsKwnQo85ex3Mrn6PO3hY9YiXZb6QAZg35Dh999SVN3gKSmemfPcQl46t17qWBLwATN1W91razEj/62fILvnVWlJwjPTgnni2LxQ6dJD007WUQmyITQ49ZJGdxdXug+FN4/yaZfcXjlIVjrXHSSFVuhxPuhF2f11D4WRPVu+R7HHXg9t1CHfwGXvsetNTK96y8C/Z2kuF17//gi0dkP968WrZvLJUG1euRM8eqVZmYmhUw+fA2ef3mammI3Z3cstUUyL608smd8l/ThI33nCpTf4WYgwcPBuwXHekoPdoIpxZHWkXvjcAkXdcPrYB2jO/fTRHuj58UkmmgMaj3juQX/scJjCeDs5ArxlaGch5O9mJnEwnxM4jT8hjKeXg1O+7Nr2N88waJzzxJZd3fcVi3cfGxk2iI2YCJgStlDzvWxVJeV4HT2E81y4gjn1QWks4i4hjlL/OTz914PfDON+/gcLXFtJz3+/O4+ISLsTvsNDuaWblpJXX2Ov+au8PlYOHaN8hoquODNXuJM+SUqjXRtJ1vqGYZDXxOCvM5wJ8DUpeBzM956LH29CT2zWqDhT+XRnXYVN/S4laYfgXMv0UuSU6/AjQLXPACFH4gQxXyFspE0+lj5AyufDOs+SNkzwBng0naBCe73pEeoAe/kYYMoKYQjr4RDnwlj48+KdDogDQ4VTth0hL8QfKV26HhgDRSW1+Cd64HLCZewwIYZE2V+UHtpfDBbdJAHorHKZd2K3dKR5yDX8lj9jIZCN9UJX83bods88Wj0rD3BY/Ho/bg2qH0aKM7LSIe6D2AeQ2IAX7QekDX9Tjg+8BaIURQM7iYmC4KpPWCIaRRSz0fmKuoNet79d7OKoHHkIGVFOIZQwuFeKkni+/5Z3qgUXfbVbgvuhZz+GjynqlgZNlShj3/BckZZxLHSBISZtNY7kXPHU/V498ykl9gJQkNjSRmksRR/uv9/Ol7WVWwinV719HQ3IBpmjQ2N3LDWTcwJX8K9hY7Dc0NvP/t+/zo7z+ixFep4G9v/42kIdnEuBxs2u5iT9keYsimlg8o45/Y2YCFJJKYRioLSOc0DAITs9bzP7z0zdsK2vbtWplzvczIkjZSvpY+Cs58VBqyumI48W7ImiQN0MhjZCHZba+ALR4SMyEzM5P8KRnoi6WBw5QzQ5CzwzGLYO39cplzxDy5DLljGWx+Hr76mywyO2waTDkfvC4ZA1i2SV57yDhoqYHTH4JJd2+mOncvthQHI+fD+DPkfuDJv5XGsBXThI3/kcayeBW8dyNsfVleY/tr0piOPLOIumITR73cd9z+mjSqrQbO7ZBB+EYn/hHb3+ha21GjRjFq1KiuGxxhKD3a6E6LvqTqOqICvYUQX+m6/irwZ1/MWxFwFTAKuLo/+5ZIAq+abzOSXEZquVSa1eSQRaqW0v2bOyGOfGwMASCHazq87qWeuNhxNLEJzltM4uZkWP434vbVETf0O7jYS1xCDt+ZYpJ9zGK+/WIZTgck+nYr3/36PTKSMzh2yrGYpklpTSlpSWl4DS/7q/Zz13N3UWOv4f7v349hGKzZvob8rHxqGmuIj42nsbmRjzd8jMPtYOiw0SSZBjlDcti0ZxPjhp9PJvUYuDFxomHFRN7hxZKNm0pMPBi0UM9neGnEQx02XywhgJ2NJPs8Mk3cWIgN+PwmJo18Tapv8i49B7WAm4XhswM1a83FCXDcLyDJ5+ma7/OozJggjdIY39Ln5PMhJhGssfDvRXDFR3JvbuN/ZOJqqw0ueh1euQAShsgk1l63dJYZOR/WPQUn+GZ8jjrIng6eFhm7N+cHbf3aVyBTc6dMqCRnpkyrVvKtL/jdIh1eXE3w5SOy5NHk8+W5trwgDe3Mq+Hrv0kDPeIHe9nxmxjWlcLY0+TSqydLFqcF+PYJmSi75Ftp4C0W37LsDnmOid+Vy6KxSV0XxlUoIsWRNoMDuBJZjfxK4C/IGd1ZQoi1wZ4wFC6umqbxXe1UbtV+SCkVrGMzn/vyTwZDLDkk0HlFbwAraaRwDA18jqYlyLpyuePg9x9C7jhspGBNyGJUSibxLXayLDYefONBDMPgDy/9gcKSQipLCqC+ivqmeqaPmY6z2cnlx13OZ1s/IzE+ke/M+Q5jc8aSnJDM8i+Xs2rLKqbkT8FqsVLfXE9xRTF3XnA7MRm5JBperBYr5bXlOF1OrKRSXe0lg++yqVCwr6rQ1+9kavmAZrbh5AAmMmbKTXnA52tExgF6mg/m0wAAIABJREFUaeAAD3T4/AZ2anjb/9zOemp4q0u9mtkR4D4/Yl5HhxCrTc7QjrlZPq9uOkBZ5QE0DXLnyNcND+z7DEb4PBwTM+Ccp+Tj434OY0+Rs8Xxp8t9vBTf7nDCEGmwUkd2tpTpxWPR0GI8tBa2mPcjaWTHnymL1G76D5z+oDTGo46DvPlyNnrcL6UXaVo+xCSaxCSaJI/wMGmJdKrRrDJ+0F4Ge1bJhNrVQnqS7nhD1vqrErDqHunNWrtHzgyXXyPTrH36G9mfAwcO+GO4XKpKTIAeRzrh1OKIM3BCCIcQ4nYhRK4QIl4IcbQQ4uPu39k1oYpnOVc7gxQtmQbsJBCPg8PnguwLGZxJPPnEMpI0jpO34ot/ArYY0DSSmEFszBhoscO7f8eSmsm3Bd9yzr3nMDxzOLcsuQXn9rV89PIf2Fuxl7NyxnPDqT9k8ojJlNWWcdbcszjnmHPQ9m0nOzmDsTljqW+qZ3zuePKz8vn1v34ps6U4mmFIDtOzR/Pjs3/M0frR7Dq4i3jG8sbqLwHYVlyEw1NLYUkhn28qIolpVPMWbqpIYCIxZOKiLGAfTho/Lx5qsJLUIbOLm2piyPYbLRMvXrr+5rWzrsPSaGdMvbjNu9EwDP/Nz+kPyL6d+kc5e0ptV6i9fU7PxExYcKt8nDqibcY4dJLcg8ucKBNSB2LgAbR2ziGt70vJhVlXy2tmTYEpF7S9y2JpW34ds0juGWrYmLi4Bf1cufeYMlzOJqt2SkeZkm/l3uRxd0gv09e/J41nynDIPx4++ZXcm5x0nnSaSR3ZpsWeFXHYK+CdG2DLS91KOahpPzaOdLrToi97lUecgQsHfdkE7YwqqhnRLs9kOBnK+Z3GPFmIQ9OsUFcOBwSWMTOYmD6My0++HHuL9PZMLi1iombh47WvMXzr/8h3lDNz8gzuv+Z+Tp99OsNMEz57BUtNCQ9f9zAtrhb0tCzOmnsWlzdWs3ThUnA2QfIQkqwxpCSmkJGcQa29Fhtp7Nq/H4/XQ2pSAs0tUFpTygfrVrKrII5EpuKhihiysJFBMrOp5k0ADNxYScJFKRW8iL0xllLP89hZjxc7tXyCg2IS0fH6PFe92LHS9XKwm2qcHAgsNtsJ7WPP8vPzyc/PB+DpFU/7jx99Y2BMm4Piw54T2mZ2afkw7eJDXjS9eCwc1vtx4e2Hz7c5+kQ4+iYvGjGkjXFjtckZ56RzIS0PTvg1zLgKTvkjjDgG4lPhjAfh7Cek0bPGylCL85+T10rKkvt2Fqv0+ky35pMan0XRhzDm5LYiuJ3RcFDu9Q1m2o+NI51watFrA6fr+j91Xb9P1/XYLl6fr+v6P/vetSOXUzieaUzCipWPzP9RapZTbwY6Uaw3t3DADMonJoDYrmrLtdLSCBfc/v/ZO+/wtsrz/X9ebVmSZVve27Ed2c5ezh4QEhISICGssDeFFij9tXR96aAto5SWUaBAy2zYK4UQIIOQvXdiK957D3loWOP8/ngdOw4O2RAgd65cl3V0ll7pnOc873M/903KyJlcnJxDXEQclvZmeP/vTJx8OckBH7qdK9FZwmHXSnjmx+DpzpZWvQ7tzbBvDQT8eLo8xG1czMj0EVyXYEclBHhcePW9xZpwczh1rXUU1xTj9Xkpry/H25ZGZUkKze3NJNgSuO/F+7AGz8FHI+VVXsyMQE8iWmz4aWVn6Wr0JOFiHxFcQF6egRann3a20MJnuHEQxIOOBPzI+T4FHwINjsaPKaiS8kx+nNTyIgoKKgy4cdDa7dggTWkP/uvN4A9mkYcu62Q/+8r34fLIDPDwQNPOpj7rH4pXlr/S57UQkuRSXt8r6SSrjPB1WpRHewYTAlSaIAJtn3PpY5GkgogBso3iICxxkmSTc6nM4nQmGYhNMdDVLqc4tz0Pq//cS34xx4Gum+tUtEw27Af84KyU9bxtL0jZtbM4i5PFiWRwNwC/BFba7fbIft5PRxI3fjA4FX1whyJdpGAUBsYwjDeVxWxnL/9QXqBJkZX+fYqDHewhj0KaldPsTnT9gzDiPDRpQ5nscTE1fSTX2+IhIg7r8OmIW/+Oz9uJLiwW185VtIREwSf/goPTttOvhy8WwVO3EwwEUKr38nn7hwS0Gpa1fwTeTpYaZL2M/euxmqw8u+RZlu1cxvzx83nonYfo8vkJBBRaO1uZM2YOkwdNxu0yoMLIqyv+y0ufvYk/4CeEQdTwPC+v/jMuZxQdwb2YGExDcwBnZzshZOMin3dXrgZFYeu+UlzsP+TDKrRq36Hev4QAHdTwLF1UdxvQJuGhHC02AOp5jUoepp31NLMUPy34cdLKSnw008KnVFRUUF5RThMf4OlyU9lUiYfSHleINlcbrR2tBOgkQCdeKnGyrifAFFTnsW7/OnYV7/rKFM7THz/d8/dHmz7Ep+Kk3QQUgqg4umjz4cEy907JIo04xJTZmiT7B7PnQ+5dkHFjNc2eCnydMhCqtLI1oXITrH1YBrQ1D8pgGJogp2G93W2he9+WfX3fJxyuM/lDxukcixOdonwLqTO50W63Z53C8zmLQxArookhihrqyBXDWc8WNijb+ERZiQ8/K5Q1LGfN6T2Jg06nag2cew1i8ROIqgKYthDiM0CtIdzdjiEsCuHz0HHeLTAwF9a+S1BvoCtzKJjCwGDilrFxlKkqqNvzDltGRmF+8zH8H/+TKl0bbsUDy19G5Wrjjjl38OaXb5IWm0Z1U3UPMaWisYKM+AzGZY3j6kevw9dmJ68ij8UbF/P4h4/jcenwtAxk+mQDa3YU4ekM77HiaW33oMFGuH8+xVX1dHY1sXbPzh5fvcqGSkBQXxtKUFdCMx9jZRrhzKSTXWh92ZQ17UCNhQCdeCjrnrasRqAm3/UXXOSzoegdqnmyp54XVDegJYoBCVFUNlZQ513Oa6v/Tid7ePHzF1myZQlBXARop5XlOFmFn2b8OMnrfIiOrib+8tZfqG3pFcWtb62nqLaI7SVf0NLegkoodIkgEGRn0YlLxkEA8+ufHDGbPB5ojZB5gczmQiLAFCf3aYqWTfXRg2T2FjcCZjwMQ66WLhFCJY0RRt0OX9wvMzp3EziOzP85i7M4Ik40wH0MTANCkPJdZ5otzjeKU12DOxTpIoXruZxcRrBN2UMNdSgonMskOnD12wN3EF1KP67fJ4OoZIhJhev+1GfxwoX3I3xejA9+RlJSEmSMJNBazZqhZhbzOVz4E5w5wzFVlVCfnsiUj7agG38pVq+GFSktNFs1dFRth6xxsG8tOUk5PH/X8wxKHsSkQZOYNnQaV027iow4qcNlMpiICYvh7WVbCTOFYdQZWbJlCc8tfY7NOzvxNudSXtuMIy+KZTuWoVFr6PJq0CgR5BV1oA4k09IQQ01LDRrFRpdSz+urXkdHDJ62RJrqI1mxrpUtu1tQYcRLGQdKmymvaaeo+TOqgk8TQhY64nD5pE73ur3b6QwcwFFZQBRXUlhZTUyiAWt8C9t2+hicnkBdewFFzatw+veyo3oRVpMVd5cbFFhf/Ue8vi7U3hy6qKdd2cK2bWHceOEE7rrwLm598taeqdO1+9Zy4djzaTf/ix8/+2NyM8egDjUiUFi8aXHP99JfsKtvrae0rrTfr1chiG63g1Nlu5M8odetPikpiaSkJDIvkC0S0YOlHVJktlw3MVe2Zai6mamWWNm+UPqlbLUIBmR7BUj1FtdX/X6/Uzg4HmdxesfihEkmDodjK1IBpBxYYrfbbzvKJmdxAriUOWiFhnCszBez0aMnVSQxUAzAjQcdWlxK/xKa/+V9fMopVEtQqWD6taDtK+dpmH49TL0SdJKs4tarWXRREo0JEbhw8VROAa9MCDDCl86o6X8jde5DjDFNJfuGd0m6+GGcZjU7rr2C4IwbwNnAoJg0MhUFnVbHry//NQAatYYrp14JgElvIsISwdzcuVw17Sqiw6K5bNJl2EJtdPm7cDWnIYTgrdVv9wSFtqZ4SqvaePS9R0m0DsNR0kqUNYot+bup8y/mQIFBTmG22WipT6S+qYv/fPoana4AOuIorS/FGBzCP1+pZ2/FZnbu7ULtj2dH+Qo2HViDq8NMbVs+NZVRlFe52V10gGWld9FFLTsc1QzJiCfevpLVX8aQlhjG/vI8wqKqSc0spKrOS7O7iHdXfc7DLy3DE6xg6baPibVkk52SRoQlArPRzJ5SaWnU5mpjRKadmoYOjDojNS1VeAkSVII0dBRQVl9Gu6udpds+oaKxgtrmWt78UtIWC6oL2Ji/8Stfbaenkz0lu3B53H0yuF3Fu3B5XF/LFG53HVmBJ68ijy/39GqQ2TLlz0ithdF3yOb5Q6Ezy6lLgNhhULNNGtp2tcu/O+qgYp1UjFEU2Pdu77Zt1dBSesRTOYsfIE6KRelwOCqQxiErgGftdvtjJ7vP7yJOZwZnFVIKSy3UDBM5jGAww8gB4B/iDwD8W3kdt+KhXKlit7KfD5Sl+BQ/JUoFzlOg8HFUdE9hlpeXU15ezscsZxwjWSDm4FLcDBQDSFEno73hUSIic2DyZXIzSzgDSWeWmIZL7eMR5WmqvaU0PDABPj6yqYPJYKLN1UZWUhZJUUkkRyX3MWgNKkEy4zOJsERQ1VSFXqsHBNsKt/Gry35Frj0XR5WD22bdRq2znBZnEL3aCkEdgYCKupY66lrqMOgMfLFtD8XFZpramsixLUSvtuBzxfP68s95afF2yvKHUFrdRF2tgWZXFXEhY7njqZ9hZgiuxgGU5IWSFT8cvclJ/v5ISqobibPaUXVOIiyiFYshkpqGTuzWq7l66i1cmDuPDze9jdPVTExYDCaDDObjct10+CvoCrbS1F5PSlwMcdYBPHDNAyRGJuBTKWi1HpLTGvn7B4+xtuAthKGMPdX/o6D6ACt3rcTr89LgbKCutbdncMXOFQSDQbYXbueFz57H7fWgECS/Ih+AjzZ/xG1P3cYfX//jEb+Ppz9++oh16JaOFqqbq3t+G4ciYfRXRaEz58DgK3tf+9xgCOuuybXD+r9J5Zf2KhnsSr+QyxvyoeAT2PmydG84ESgKrPzdiW17vOhvPH6oONpYqFQnHlJOWsnE4XB02O32ucBTwL30eqv9YHA6A9zhiBcxHDSLCxUWVIpAQeEZ5RUGiYFUUM1WZRcpIpEIwmjBSbPSykAx4Ot3fArg1LSzTb+HMMJ6jpcj7Ixg8BE9xjRCzXlM4b/KewwXg1k+YQ8T8kOJjkySDExLxFe2yYzPZMGEBT1/zx8/n7yKPCobK/ly75cs+sUi1Co104dPp93dTlJkEi8ue5Gm5iaumnYVtc21/OuTf2Gz2Ni224WzoRVbqI0v93zJuv3rMOqNCAQP3/AwVzx8BSMzRjI+azwDYgcQbg6nqjiRsJBiYi3Z3DTzJopqCvl32dMUVZRy44wbUVCIMKWgeJPZsNfBtJHTMKOjsHQ1jc5GtK5raW3dSWfdJOKyHazb2cjwpHMJ0emZOXIMjV4rnmAV+q7J+FmFLmwf1Q0dJNnrWVv9GxqD+fi0GdgTRhJDLBE549krVpIQY2JsxgD2qlvQR25CVd1BVftO9NrdgMIfFv0Be4KdtHQpWF1cU8xHmz8iJzmHvWV7mTRoLJq9q4Egr65cxMVjL+ZA1QEyEzKJCo1iy4EtjBk4hkZnI5HWXn5ZTUsNr654leykbHLtuVQ0VNDgbGBkxkicnU7qW+tRqVTsKNlBYmLi196wdCFwqKGGOVaqqZiipNLL7kWShVm7UzaVm2JkwKvdKZvnhUrqfEYPOr7fLkiHhepvyOTrZG7a3zccbSy+1QAH0O0i8GO73V4A/O1U7PO7hG/zx3qhmEk+hQQJkiMGoigKJhHCp8oqZolpVFPHWmUTvxX3nLJjHqzt6YTsFGlQmming9K4aiKJxHWI69BUMa7ffRyOa8QC2pUOfhW+jBHpOTBlIeRvhDEXwLKX4dxreqRD1Go1s0bPAuTDRVpsGtFh0RTXFlNYU4ime70ISwQR3QFyQvYEPtwg++RsoTYqGyvRaXWEGuIoqq4mOymbutY6fn/V7/nP5//h3nn3EmYO47rp16HX6rl0kvSzu3327QyIG0BTWxOVjVJ9IT0ugwev+zs1zTWEmcNIjU4lOSoZq8nK4u2LuSXuFkxYMKjisZrcRJoycXdtwKg1E27IYvOezdw4bQAGZLtEuH4QAVLQGaOox49TtZTdexXG57jILy/kinPPw0UeJgbjp40WZSl+lQFFtBOlH0OE7X3amwYSErIbi8GMmyKmDL2QV5a9jT1pAF2iGkelg10lu7hyypVUNFRg0Bm4ZPK5tL/1GAoB9pXtIykyibsuvIt9ZftYuXslgWCAvIo89pTu4ZEbH+Hz7Z+TlZSFVq1l0apFWEOszBkzh3BzOPsr9uPp8uDsdGLQGcAA7215j6wBWWQmyM72jzZ9xORBkwkz99p8rd+/Hn/Qz5TBUwCo0+0nIyoHa6Jscm8tlUa24QNgx4tSNszbBsNvBBQITYLaHXJfiiKlz7raZQP90eBqlAxPv7d/r7xTicTExNN7gO8QTudYnIhdjsrhcLx+hPceB4YB/ThNfX/xbSsSZIkMcoRU4RdCsJB5XCsWMILBVFBFK224FDcHlGL8yskz5PZTwH4Kel5XUsMK1lKklBJL1DF72h0OMyamiQkUz5sPkYn4qx3w+UtQmQ+bemW1qCvrs51GrcFqsjIifQR/v/Xv/e47NTqVoWlDAdBqtNx36X0AzM2dy6M3PcrwAcOpaKzAYrQQb4vHapK6lpNyJpEandqznwFxMjO1hdoYNmBYz3IhBPE2aQh/7rBzsSfaibJG0e5uxxIiG8j/dO2fqGutI8GWgKfLg06jI0ZzEXUtTYTqY9AibQ/UmNF1N/qrCSGOO3nrlx9gDRWoPcOIYA5BOjExlFaWQVBBERrMTCNMl4NWbWRI4hTSk6zMHHU+Hl8nF02cwp1z7sTlq6W5vZa8ijw8/hbSYtJoapccfAUvPr+fD9e/R2hIKA3OBkZnjmbhtIUMTBjIrbNuZWfxTmpb5PaPvPsIDc4GYsJjSI9LZ+HUhWwv2o6jykFMWAy/ffW3eHwe5o+fz1ur36Ld3U5hTWHPmJXVl/V5DVDeUM7e0r09r7do3sHaff9z+zsYdJ2XlMmylWDq/VLCTG+BgRdIHczYoVJMetsLsu2gdqdkaxZ+Lqcy5ecM9Gu71NkANru0JDqLMwcnc3895amHw+HY53A4+nG2+v7iTLOeF0KQJOIRQtCiOBkthlJKBevYQhMnf/U6aaeF3v67VpyUKBVMrB6Ju7oTC6YTPu/LxFwUAR1KJx+F7YaaQsgaDx2t4HVLaa/FT/TdsKMVyvO+dt8hhhDm5s7teT179GwAxmWNQ6fVEWWNori2GEuIhdtm3dYz7ZyZkMmEnOOz4Q4zh6FRa6itruWhKx7q8979V96PRq1h8qDJ6Lo1vRZMXHBExXQNYeiIJ8wcRk7iCC4dfytJ4UPREI6BNDTYCGEIXhGCRonCZkqlozmZtIgpnDfgr4CCypeMX1vMiIFJOAO7GJI6nFe/fIKwxA2YjSG0uZtQCRVBvITozBh0Ou65+B7KG8oRQqDX6vnJ3J9g0BmYMWIGC6cu5J217/Dry3/NfS/ex/ABwxmdMZqLxl3EXRfeRUldCTaLDYvRQqenkzBzGMu3LWdQ/CCa25txdjpRFIVAMEBZfRmPf/h4z+d1d7kx6o28veZtdhTtoKS2pOe9DfkbKA30ZYYaI8CS0GcRLcVSDUUfKq2AvE4oWQk122HTU1K1praskPWP9d2us17qcnq+gQBXVlZGWVnZ0Vf8AeBoY3FGBbizOLOgFVpGMpTVbKReaaSO4zf2CiiBPiSCNtpxHuJd10YH08R4YkQUScQzlOyTOucQjHzOalqmnE/Q0wGxaZJ6t+wleO1+yRnfsBiqCqClDsr3Q+G2kzpmXHgclY2VaNSaU1ZT1Wg0aDR9qwDThk4DYNboWYzNkk4GP7nwJ0fcRyhTUHe7n4erJxJuTEUIgRYpSGlmKIqiRS90BAmi1+qZO+xHCARaIhBoWThZSo+YIou4/PwcMmNHc/cVM0gLm0ZAn0dU+jLCw90EcWOxRjNj6ASGpg7lnKFTe85DZ67Dj5PZo2cze/RsKhoqGJs1hsvPH8x5w8/jppk3oVFriI+MIsIcQWZCJmMGjsHldaHX6rGarNw+83ZqW2q58R83UlZfhkFnIL8iny0FW3js/cd6JOBAMkW3FmylpqWm5wbX4GygvKEvGSFuFCQd9vxhv0gKVbcYStGF+RFqqbRSvlbKigX8Pko+DadsDbx3tSSrQHeAy4LWbyDu9Pfb+KHidI7FMe3Vbrcfb5ul4nA4Lj6B8/lO4pskmRwvQjGTQCzppDJQDOBLNpKqJGJA31NDOxq2swczJrLJZK2ymQABfPj5W/Bf3CSuJEiQmWIqJBx9X8cCK6EUU8Yg7LRcNxmbMQGcDbBvLVz+a7BGyqnLHcsgbz0MmnzSxzQbzQwfMPzIK3R5wOvql/RyJCQknPyAHNrnaKCXKGRETklricLAEDSqtSjd08+HEkB0xKFCR5BOFEKI1VyGlwqGpY1GSzQdbKfoQBzDhm/HQzgmtZGgv51gSDWzz4nCTwsqTHgoBoIo+FALC4/c+AgGo5cJQ1N7fv9BvDToH+OcoeeQk5xDY1sjeRUys154zkISEhLo9HTS0tHCPz/6J1dOvZKXl7/MiAEj2FWyi/zKfJramrCF2hAIOjwd2Cw2Oj2dWEIseH1evD6vfBBRaYiNiO1xdPD6vOi1erp8XSSM0VFUU8QjRbfwm8t/y4yRsk132/Mw7DrY/rwGf5f0y9vxH6mVaY6RTg9GmxSDzpx10l/d1+JU/Da+LzidY3GsGdzcfv7POcLyg//P4gzAXGYQIozMEFNIEYmYMfE6H/In5XFaFOdXanKHZ2sA7XRSSz0AK5Q1ePBSqpQzU0xlTbctzalEDFEElCARhLHZcIDtyh7IGEW1t5Sm0O6pPCUoZfuHnweOTfLvivyv1OeOFUII/pQxGrYv63+FLZ/AildP8BOdeoQyvufvgBJAi4ZgP1JdIeRgIAMNNvw0YWIIXVSjI7bbjT3AgSI/as8g3BxAqA0Q8OGmiACtNPMJFfwFDyX4qKeD7XRRS6Q1Er9oINbWy97wUoGeJM4dMQkAs8FMgk3evC4eL5937194P6MzR1PdXM3ozNG4vW4m5kxkQvYElu1YRqe3E6HyI4Rs94iPiGdv2V4OVB2gs1vjdEfRDlbuXtnnc178wMW0u9p5fPHjlNWX8cryV4gOi6ampVev1e+B+DHg9wVJPLeB2KEw4efSHaHwM1ACsiUBZL3uFCvwncW3gGPK4BwOR59A2K1BWQ+c53A4Vva/1Q8Hp1qL8lQiVJj7vL5EzObXwQc5R0xkD3l8pCzjVq5GjZp0kcJqNpJBGknEE1SC7GQfnXTiI0CX0oUKNfVKI6EilEzSKKMCa7fRaGlpKQCpqakndc4JxJIiEgnFwofKpwQJ8ozpQVbfOA8TW7mQGTBgOBhMUi6soNs3b98aUGlQZtyAcHeA0dwrnOjugO2fw8RLjnzgjhbYuhRGnPdVwcW2RrBGHdfnOFXjcTQEfW5UehPBfghEBzNAI+k9y0IYTAg5gJoYbiLc/AhJhoUofIJQ74aAFwUfGiIwMZhwZtLC5wRw46MRNSb8NOGjBQ2RKCj4acJPMwbS8eNEh4G0mDRibCEoKJSVlvWMxYKJC3qkx5656x8EVDUMTrm6h4xT5/2cUM1gXl++FK1ay6fbPqW6uRqbxYY90U59q3zYeuHTF5ibO5cISwRajZbfvPIbPD4Pq/eupsPTQZQ1ikAwQHN7MwVVBcx/ZSxCgP1SJyLaKcciSsqApU6F3B/L8Tn3L3JZ3gdwxbvSwfxQovSpYFl+U7+N7wJO51icaA3uzL2jn8VRcZe4mTEMZz8HGCWG8pbyP/6lvMp+5QAlVHCAYj5VvqCIUlYrGwkQRIWgkhqmiHEUUcoFnItRGDiPKYxBTu3pdDp0umOb9vw6aIWGueI8LJhIJh49Oh5X/k02mTTSLF0UMkdRnxjJatVWmHSpJKOseoP2YDuPK/+GV34jA9+qN2RW9+StcFCiqr0ZfN7+H9Fz50DbIcq+B9dRa8HvO67P0Wc88jfBR/+EN/7cu0L7YWyG5hoo2nFcxwBQXE4UY+gRew0B1Fgwd39PoYxDoOn2L1dz3fTriLJGEa1cA2otmmA4fpoJYwY64tEQiQ35YKBCRwvLaOBNgnSgxoSHQmp5kSY+xEgGXd2tsBYLiPAVuMnvGQsfjQzJCmHe+HkACHUHHlHSE9wA1PpOhLoLq8lKelw6jioHba42oqxRdPm78Af9eHwegkqQO5+5k0ZnI2PtYxmRPqLHd3DWqFlMzJZW63UtdWwr3IYQsLVgK+3GUlRaP/6An+2lm5j5KHimru45fmgiFC+XtkT5/5PN5e9f1zuWK34LdXuO+2vqg1N1rXwfcDrH4myV8xTgTK7B9QfZLA5FwTJ+Ie5gtBhGC628q3xMO52UU0UHnbzLEjJJo0SpIE0k8bbyET8S15IqEkkSkhJvFL1ecvHx8af0PM2YiSCMq8UCPlCWMkzksFnZwdPKy9zNzdTRyFplC6OG3Ixp0CQoz8NTuZ64tavBNgg2fAgxafDeozB1Iax5B8r2weYlMvNb+y78/FVorJQamwDhcdBcLet8+ZtkwJl1y9f7zShKv+/3GY+6Uti/DmIH9G7zl0vgoZW929YUw8bFkD7iuMYp6HOj1UUQVE6M/pcY2c3DDwA6A2Z/DkYierI/GQaNKHjRYsPCaNwUE0A6NHSwHTVypkBPMm2sJ4QsKngYC7m4OUBofAoeiuhiIJ3sw8TQ7kN2EjiEkSuNZ50EcZMYmUhseCwCwRu/fIPyhnLyyvNIiEwgJizFRzDYAAAgAElEQVQGo06Sb/aV7+OC0RcwIn0E5Q3lPPD6Az3EnQdef4DGtkZaO1pZvGExBdUFpCT7OSfCzu6S3bz2xWs8dstw3vn3Oz29dwdNXiMypJlr9GBpA9ReAx6nrNe1lkLMEHnOzgr53qFegEfDqb5Wvss4nWNxNsCdAnxX2VD3ituIwka0kKSEHAYSgpF7lN9xu7iGJOIxoKeKWqyEohEawoSVsO4pydMNjVAzlpGkikQuYw4AcziPLuFjJ/tRo2KEGMQ/lOf5P/VP+Ti1jsEuK6mb6uDyp+Czf8upTCUI4y6CbZ9JxuW510ivupYa2PMlrHsfftxtP2OLh7K9kDYUNn8s2ZkT5sv3DmZzgYAknBjNshl942JJdMmd03vyXrfU7OxslVOpS/8FtgT5d1sTvPJbCLGCqw26e+5wtYE5vHcfdaVQshtGz5ZTpCq19OeLS+89HyEIEMAoDPhP1gUgGACtHhFQ0PTzHQvU6EgghCwUAnipQIMVDyVoCCeSeQgEVibhpgAtMWiJARRaWYaJYXRRh5oQ2lhHKBO7A5wLH41osFHJY6gwEsTNuCwpErDoF4sIik5SolNIie4rXjlnzBz+sOgP/PWmvyKEINGW2NPcD3D55Mu578X7WDh1IUu2LOGOOXeQ1/ABu0q2U1LUxIIJCyipLaG4thif34dWo0WtkZ53waCUDdMYIWYYLPulVFbRGMDxkdTITJ0CVVvA7z6+AHcWx46Tub+ebRM4Bfi2G71PFPEipk/2aRIhCCFIJZFBwk6osKATOtJEMhEijLni600jSkpKKCkp+dp1jhcjhXxMTuzOGONFDKkiETduOugkgThaaWOXsp/tyh6KrG48UdEoJit+awSE2mB2tw74j5+WOpi2eBkwLrwLHJtlBrV3DRTvhLBoaKmVmd6gSdKJs6GitwijKLLW98HfYfGTMgBNXCCzxUC3sPX2z+G/v6Niy5c0L3pIBtWrfi8DntECS5+HyESZNbY1ysytIh/am2TQfKu7d67SAXkb5DE+fQEeWUhgwwfSF3D9h7DyNdi3jiBBjMKIX/FBd33qhBDwS8HsQP8C3WbGYEAGGIEaA6moCcNHA7HcigGpUKIlli7qCMGOhVysTMZdm01jrQs/zQj0tLGeAB14KUOgxslq/LSiJQqBmkC3Go6LPLpUpVTwMF3U4e/u42zkffm7iExkYs5EwrsfDNRqNeOzegk4WUlZzBs/jwUTF5Brz2VE+gi6Am4clQ7UKjWx4bHsKd1DWmwajW2N3V+xwmPvP4ZKJX3uYodK3czpD0rT1vQZEJUDLUXQXAwdtRA4TuOO03GtfFdxOsfibIA7i69gyjHKax0Og8GAwWA4+oqnAEakXmQ0NmaJc1itbKSeBt6O2knDqDFUUcvyIWr2RBxBbNocIacpd62A1CEyCM26VcqBeVwyuNjHwvTrJPEkdSiU7pE1tI+fltOYTZWw7j0YOEa6KTRWyX1XHUDxdCKCTgyN5bB/HU05g+nSaWUwvOB2mVXGpIGzkU+23kdr8Rq8XW24C9ahuJywcyUc2AIzb4JPn5dM0Tl30KTtZJ2yWRJiAgHY+glBFEIwEgx0wX9/LwPsiaA7gyPQf61RRwyq7p68g5AZ2zkIVD1Tmiq03W0JQVTI2opZGYVeE0aADlRo8dFAI++iJYZQJgAqfNRjIBUttu7tFVzk4WQ1WmLoZC9OVhPERxvretzTb5xxY58HtUsOIxLdNPMmdFodt5x/CwCRYWFEmKNweV1EWiN5ZskzDEsbRnl9OQoK9a6drNqzipLaEh5971G2Fmxlb+leWnVlDJgOKZNh/E+lO/nOl2HkzXLIAj7Y+IR0Jj8avslr5UzH6RyLY+2D+9lhi0KQRJPL7HZ7f81DisPh+MfJntx3BWcyi/JEMFoMO/pK/SAuLu4Un8mRMYFRdOImVkQTSzRDyKaMSqp1tWjiNORTyIaoBsLZTLSSQIw4zHz+0l+wke2MveUxREO5rMOldCv0RsRBdYFkXJ5zNfxpHsz7Kdz8V3jyNrBGy2xQUaB4FwCfhR9gUpOCydkAPi++S38Gz1+H0ZhBbcteCtXFhJrqyYyIQIUKvT6EBoMHp3ML6Izsq1mKPnEQNbOzObcmFlOVAyZegi8+FV9EOCHDpsPYi6j9YjMxKz+FCg0k5aDUlaHYMjAKI9rSPDAmyAA3bDocQR3liAj4QWuQge44YOunKyiMmfgO0V2Pi4vDTSfN7CGEIWiJQkcCGsIQqHFTRBdVGBhAkE5a+AwdCWiJwkU+RjJRkE4HbgoIYRAeCjF2Z42HI0gXQTzdrRB9MT57DO4uJ8GEsdgsNqYOmcrI9JHsr9jPO+veYMZkC9HWaJ5b+hyOKgdNbU0EggG0Gi0PXv8gABUNFWCMZsKP9Gj03RldCQg1FCyB5ElfL/j8TV4rZzqONhYnoxR1rBnc3w77/wAggNv7ee/g/x8Mvm8B7rsAqwjtIcsAxIhIcsVw5olZxBPDXiWfOBHN+WIaVd032jalo8cfz4efpcoXVKVFsSbkAErCwN6dDzsXup/2EQLuewNCLDK7qyuBhf/X+166fL7bZ+uAV/4P1r0LBdvwmI14OmoovfwaCs1OWnBSHRrgM1bxJh/in30rf5hUiXPtS+SYRuPPncXusZl8lNXBsuhy9tR9xn+T8iihgk+umoQy+TIUjRYfflR+P8pNfwWgVteGq95BCEbeu/EcyJ4I1YWwalHv51EUcDZKlubX4WAGd5xs0f6gxtinMR1kU3o4M9ERjYmhaLEhkEHYRx1tbERLDGrCieEGWlmJhdEo+NARi48m9CRQx3/Qk4wfZ8++u6inkQ8OeV2Ji/39nptKpRBisJAcnYxKpWLBxAWkx6VT31qPL+hic+E6kqOTqWysJMGWQFFNEWkxaQxJGYKny4PX5+XZT57lweaL0ZmDLPpiESKpjuUvlaE1QnMRrP4LrPpj32eFlhLocp300P7gcDL312Ot3p1zwkf4AeC7WoM71SguLgZgwIDTb83zdUgglnY6+am4FZ/i4w0WIxRBGZVkkcEAJZk7lF8zXUyinU62pmtQawyMU4KohIoSYwtpIhkAn+JDazhEPPq2x2WGdxgiTMmUzZpNTtY1EJeOO1jPi9eORmfZhW7eeIqUT/n9qLt5VdmDXWRQZ3RzPTcT5ttGimUoqQPOIUEp5Tqu5ouEDxCqAYxlJC8qb9BMK53CxV7FwZwwEwPqgjzHa8z1l1GVEUOXKkAYIWzT5kPEUHy+TnyrXiJk6kLZ/7fyNYhOkdOw4y+WbM4Jl8j65KHweUEfcsQa3BGxb62cztVoj7hK72/D3u/7RjKwMQ81RqxMJIiHdragwogKIyHk4KEYC7moCEFNCC0sw8xIOtkNBAgcIh/nx4mfVrqow0sZFvoyQA5ViBmS2l3njUwkJy0Rj16FyjkcnUaHzWLjy44vae1sJT0uneb2Zj7d9inN7c1YQy3Utdbx9pq3SY9Lx5lWizE2jpQh7azevZYhsReze5FsN8h7HxBSJLqzAQzDz4xr5UzA6bxvHGuj9w9KPPl48V1rEzhdCAk5MReBU40YEcVvuAuQWpxGxcAOpEJ9JdWEEcpIhjCWkRRTRoYxm1qc/E35F/+P2/mz8gTP8hA6oeM/vMFMZSpb2cXl4iJa0lJpUcoYIPqy+cKwUjB5NDmadNYom9jIdhKT5uASbqJEJBPJJS5pNEalEAsmnlVe4Zfix1h+tb5nHxkiFYAZEZdCNxFwPhcwkiEUUEyosNA8Osjk4HlchouPQ+9EnTiIwmQj1yBrGAH7aJbcMZ9xTzyD8YWfIXxeOd06+gLJ1nQ2SNZoZJIk0Ri7hQAq8iVjNCa1b4D7+BmYe+eRB1tRZPuFPgQyRh5xtaP9NkKZ2Oe1CgOx3ASABitabERzDQAmBgMQxE0rX+DmAB4KCet+DpeN5620sgwVetpYRxAfGsJRODIbZNaoWah1rdT6q9G2DyfXnsurK17FbDBjC7VhNpq5/7X7Ka0vZfqw6aiEipeWvcTAhIEUVhfyv6o3aA7LIzsim9bwAlKnSkufbc9Loef4MVL8OSoHIkJCziqldON03jeOtQZXAXzY/X+Vw+E4s+Tzv2WcDXASsbGx3/Yp9EAteutPkxjDS8pbXCcuYw2baKSZmWIKZkxsUXbyE3EjatR8xh9YyTrOEROop5FIxUa5Us1OsY8ufKxVNlNHA166SFOS+YClgGA+UriwQ93FR8rnLFfWkEg800InkCMG8qWykUjC0QoN/0/cTp5SQIpIxHKYykx/yBVyCjSbTAYoKdSKetQaPTb0WCZeiw8fPiWPaGQ29oTyb0ZFD8MzdT4tWhvt/hbak9UMriyW065LnsEzeBy+mt1YNnwIP3kWqg7A0uckiea2x2UQBNnOsO3TIwe4YFCyPFMGQUUeRCVJtZeiHVBfLrPFwu1gCiPWaJYM1WNFMAitdRARh6Y72h+czjyIOH5MJQ+hI5EwpqPGTIBOWlmOQE801+JiL9FcSzOfAEE0hKPF1kNQORRWkxUPLYRotcQb5QNMXWsdN5x3A7kDc1GpVOwq3sVts24jIz6D1XtX8+T/nuTWWbdSWF3Itedei9PlpLGtkcjQSPQWGHePFHROmw5lq6XeZYwGTEosDfuhvlnyjSzxx+ZZd6bDH/D3+DEeK07nfeNYa3CLgXnAMqDebre/Zrfb59vt9jPjkf0szuJrECdi+I3qbhJFHBMYzV4cJJOIET1NtGDBjEmEcJe4iTeVxYxjFKvZxAvKImaJaRQpZVzNJdTTiBo1ExnDQ8pTtNNJJOG8wCJacaJGxS5lPzeLhUSJCAxIPafh5DCA3owvW2SSLfonR3wd9EJHiug1h5zPbOYyg6liPBbMXCrmYBcZ5KizYNat1GYPpGZoDjvPn0BHiIZXM0oIhkVTctlC3PtXSEmyFa/KFofr/gJ3PgPmMHjjAXj+Z7BliZyOXf+BzPpa6vrW8TZ8CG/9BQZPkaa0K16VGZ2rHQ5slpng1qXw7iOy3/AgAgFpcdTR2+CNzyv7/jpaJUmmcDu8JQkdFkb3Ox4qtBjIJIJZ3TW9KKp4jE72AWBmONFcg4EU4rkDH3WoCSWIB4EgQMdX9hnEi6B3qvWKyVcwIn0EarUaIQR3zr2TsVljsYXamDd+Ho/c+AhZiVk0dzRz5dQr0Wl0qFUyEB80xJ1yPwy9BkbdBr5O6Wiw9mFor4aaHbKZvLbbBSgYkLH9u4rXVr72bZ9CHxxTgHM4HD9xOBxJwDjgeWA08B7QYLfbF9vt9hvsdvv34PnjxHC2BidRVFREUVHRt30aX4sUkciV4mL0QocBPVHYejLwwSKLP4qfk0w8a5RN3C6uIYM02mhHCIEKFWZMpIhEporxZJFOPLFo0TKH87iUufxW3MNQkUMyidSX1VNUVIRVhPZRfDlVEEJgEiHMFFMRQjBbnMscMZ0oYSNMWFkUv5vd8T5CDDZ2nDMcDWp+erWCS3goPHeSrMOp1HDpfXj0ahoSbL3N7BfcLoPSxT+Vjg2eDlj+Mnz4uGxuX/ykJLP88g1IyoKf/gcyRsl+wsp8MIXJloqBYyAxi4bCfZSvXSoD2YHN0tNvy5LeD+PYLJVlti6VtcL6Mjld+slzGEjrfwBa64lunY6OePQkoicJDVE9KimHQ0dSt5RYLQoKtbxAEE+fdYJ0oqL3uxqbNVY6kh9h/HPtuYSbw2ntDtbt7nbMBpmZL/piEV6fl2azA40OksbDvFegYfrbqBPqWf+0G78Hsi+Btu7WgsJPYeuz4O/6bs5fur3u497mdN43jqsPzuFwbHY4HL92OBzZQA7wZyAW+A9Qa7fbv7Db7Xfb7fbk03CuZyxUqrPthAAmkwmT6cTMTr8NaNGSKpL6LEsUceiEjvPFNHRCRzhWtN1P9BdzPtORSvkTxRjGipEkEsdUxhElbGiEuidYTmM8KYbEb208LJippYFYognDSmGqGQN6TOpQ6mmiYLSdLuGHc6/BT5B8CtlDvmxA//PnkGiX05XJ2bKFYuxFEBYjySSr35KZnRC9KizRyTAwV6rHbP4YQkLlshEz4KK7MbpasFbugXcfhU/+BfkbZDa44lXJPt23Fiw26HLLbd3tkJQN/i6ZEYJsiD+IujKZWTo29yxSYyaGa1FhROGrRJnwbm1Nr68ETXk1Gmw9DeMH0UV1j9feofB9jY9imCmMoCIfcjvcHaREp6BWqTlQdYC7/3U3D739EK0drQgBhlB4c8eL6CL8TPidi5E3S1kwTyvsfl26j3fUwVO37qB8/XcvyHl93uPe5mj3jZO5v57wlg6HI9/hcDzkcDjGAsnAvUg1u78BJXa7fbvdbj/NrkpnBr6rUl2nGrGxsWdUHe5oEEJwBRf1+948IX+6RmEgWth61j+83moQ+q8QTgBUQkVcbNy3Nh5qoeZJ8ScuEjMZQhYjGMxgshghBlNGJdFE8bjyb8qUSt7lY7awk0462U0+ysEaykEB5NgBYA5DyR4PQ8+BS/6flD7rFkzugSFEyoglZklFFIQMgmo15vFzsV56rySy+LwQES8ZnvvWyqZ1kMuNFtmq4G6HMRfI4y1+Qqq5fPgPuU3ZPlj/PuxcLut0h7A11JjRENZH37Ln9EhFQyiJ7TdjKvQRzVVAkDr+S4BOvFQjaQkCBaWHlVnDczSzlCD937xDQ0IxGeQNOjosmpToFMwGM1VNVRyoOkBZfRkPv/Nwz/ppsWlETGll0MwwdhbvQAipe5kyRWZyCWOg3dfC+sf97Pov7H+/38OekTiRAHe0+8a3EuAOhcPhqHI4HP90OBznATHAjUApdNOdzuIszlAcC0FoGhOOus6ZCJOQJfIoYWO4GMRAMYAJjKZKqWUW07hH3MKXbCRIkGqllgBBPle+ZCkrpRzYQcy8mXXKFt5I2I/fHMqHtr0yCCX0rSPuUfJh4f1w6X1yejHyECPLkTNkG8Gv3pSB8d4XpVP7oElSQcaeKxmd8RkwZo50fABIGCinPvevl44OtcWS2LJ1Kdz2DxncXn9Artt9c1VjRKkrlev1A41XhdodRKAhkkuJYDYtLKWFpWgIRYUWBS91/Bc/TjwU46OBap7+CjlFIYhaLSW/QNbsosOiiQ6LZmTGSK6ceiUGnYFNjk04Kh0AxIbH0uiu5dH3/8rKXdJtbOAc+MeXf+CytxTsF4Ln/BWMebwCXydUboCSL2DtI+Bq4oyG13/8Ae504pgDnN1u/4okgN1ujzl8mcPhaHE4HK86HI5LHA7HD6Lh+2Q67b9PKCwspLCw8Ns+jVOOLJFxQtudieNhIwKFIEII9EJHKGZCMPI78TPqaKSeRqqpo4RyAFoVJwdioY4GDOhZzmp2KLLl4j1lCW2KJGr4lQCPKy/QJjqlE0PORBgyree4PWOh1UtZM5AyaNOvk83yw6dD9niZ/ZnD4Orfy3W0OhgzG6ZfKzVFqwtl3fDeF+V0atUBaCiXzenvyduNgQwiqwZBU1X/g+DplJkgsh1Biw03hQRxocaCCgNOVqPgx0Nht2VQGH5a8NPaY0ukEKCRdwCwJ8j+PkuIBSEE0WHRaFQaMuIy+NO1f+LicRfz+fbP2VO6h/iIeLbt28bm/ZtpbGtk1e5V+AN+8ivzqWiS4+7z+9hSsJmivHo8rVC5CSKzoGpzP5/nDMKJZHBHu05Oa6O33W4fBfwPiLXb7UuAHzkcjoM2uR8BP3gN7bMkEwmLxXL0lX5AOBPHwygMZNEbsEOxoEWDEIIpylhiRCQ+/ORTiEbRsJ8DqFFhwECAIOuULaSKRFYp6ylSysgSVcQpMXTQSTqpPKu8yk1cSVAVJEYdxSZlO420oEQE2Kt1EKaE8SNxrTz44dnzQZeE/mAwQXis9NRb8AsZ3ABm3ChreXkbZL/fhsWo9CGw+mPImdT/vjydkjRzCMKZgZP1qDASoJMWlpHEfbSxHiuTCWEwXirx04CTlUSyAA/F+LunQq/sDtptrEODjYEJWfzxmj/2zBCMGDCCl5a/xC/+8wvuvuhu2tracPlcbMzfyMb8jYToQ7hw7IW8t+497p13L0adkfzKfDITM9HXRhM7DDJmSe3Lrc+D/UKwnIFqX17XcYoEcPTr5HRLdT0B/Be4EkgEttrt9oOGVWcbwDjbB3cQMTExxMR8Jan/weJMHY+r6RUjPldMZLIYC8j2BTvpmJH1pAaamMJYKpQapjCOLNL5kbgODVreV5aSIVJpppV/KM+zmo0MFnaqqOW3ysN8yQbeV5ZSTjW7lH3UhDdwnflyjBjYqezDpbgpVspYqazr9xz9SuCrT+4hoZJhGXUIMSg5GwZNlKLXSdmw+HEpUzbrNqng0t4i2xUOGs36fTLAqfo+25sZhY0L0RGLjjjiuAM1FryUoyUaFTq0ROKhAg9ldFGHhxL0JPbZj48WvMjM8dD7glqtZvqw6cwYMYPosGiMIUYGpQ7iyR89iclgkhm1Vs+YzDF8uu1T6p31VDRUIEY7mPxrGdyEkG0Evk6Z0Z2RjeLrjl/H9nReJ8fCjrA6HI5fAtjt9g+AfwIr7Hb7TM46e5/FWXzn8HUPZFlkkMkANIc0yv9c/AiA8G6PuIXKxUQLG0nE84KyiJFiKFuV3fxYXI9B6LFgZhf7GcFgchnOX3iCS7gAmwhnoXIxb/I/tGh4T/mEdtoJEmQ6k1jLZhQUpohxfMhSbIRzDhNpVzrQo0On0sFv3kERgj1KHkNFtjxBrR5ueAgKtsggV7AVssbC+TdLxqarTXr/Fe2UlkjudkmgOWhUqyjQ3owhNBUAtWICIYkmPprQ0G3FgwUvZagx0ci7GEhBoO2uywXw46SN1Vg5t9+xTYtNY3DK4J563fRh0xmSOoTrp1/P4o2LARicMph7nr+HBFsC+8v30+Zq44W1T3DPxfcAoLdIax5PC+x8RRJSvk7U+ZtG4MwqwR1TBteTczocDr/D4fgRkin5GXDWlpazU5QHUVBQQEFBwbd9GmcMvovjIYToE9z6g07omEguAxnA/eJeQjHzqPg/MsUAZoqpjBejuJYFjBUjEEKQKdJoKKyjoKAAndAxkDT2cQA9OtSoqaCanysPcIBi6mjk38rraNDg7GYxbmEX+RRJKn6ojVba2MT2vidlCIG0YbLvbn63+ck5V8MVv5Y6nMPPg9Ld0tuvYCtodPDPH0kyi7sd/tY9baoo8Ner5Fgg0JOAipCe1wIVUSzEwlj8tCLQ4WIPNTxLF9VY6PWi89H4lbE7b9QUEiMT6XB20NokpzetJitR1igAwi3h/Gzez3jgmgcIDQllX9m+nobxqsYqCtp30lGr4PeAuxm++J3cb+MBKF5xjF/yacTx+uLB6b1OjiXA1dnt9smHLnA4HA8CvwPOwFngbx5npyglrFYrVus34/b9XcD3eTxChRmd0BEpIpgvZqMVfYWWDzI4AS7nIiKsET1jEYaVz5RVpIpEfiJuYhpSiaVOaaBCqcKluOmiiyqlFpfipoFGXlbeopBSWhUn/6N/v7ugKRRfeJQkqRyKg03jzgbJ7LzobrBEyBrdcz+F2hLZg+fzwifPAUJ6Apbvx8aCPsLMUVyNhtDuaUsTaizUswg9KbjII5wZBGjv9rt7r2e7g+zLKv6OjyYiwyOJsclpOXuineykbEJDJI9vePpwtBotseGxxNviyYzPxOf38daat9hRvYHOVh8Zs2CT9wOy5sH6x6B4mXQrKKsvO6Hv81Qh4D1+Yv7pvE6O5WwWAF/h7jgcjqfhsAnoHyjOBjiJ6OhooqOPQ2/we46z4yEhhOgzFlHYuElcwXxmk0AsicRxjVhAgojFLEzcIq5iAXMoopTnlNeoUxpZIC6ghnqeVV5lCmOJ4qvCSTvZx8u89dUTCIuGlMEweCpMvhwyR8Ho2TDtKpgwH3atlA3rm5fAmrcko3PT/2DZy2gPql5v+hjaW1B1N/0bSCaS+agxo+DHyEA8FKHChJXJNLMEP80Eu8WdnazCRyNqTAToIC46juQEqYeREp1CUlQS1pC+N/nkqGTuuvAuRmaMZH/5fupb68kTq3CMf5Zi/zY+ansKXbiPwk8Vsi/3o1LD++veJ+CXwe4IvrWnFcGu42c9ns7r5KgBzuFwdAI1drv96W5G5aHvHcVg6izO4izOoi9sIpyJIhed0CGEQCu0ZIhUrheXc5u4hhBhRC3U/EH8nL04sAgzuYxgr5LP+WJaj5WRoii4FQ8uxU2b0oEbKRMVUA5j3c2/V2Z1A0f3uieYrNIQdvw82U5gi4ePnpLO7ZMvh2UvQepgmclV5MMHj0mFlsOgJRIdcRhIQY0ZgUBHLH5aUWGihaX4aOxmXLagwkgQN7kDc0mJlgIBCgH+f3vnHWZVde7/zz5leu8DQxuBRVW6ChjBjmJvib3HluQmuSYa/SXGm+Reo6ZoYtTYYu8idrELNkAQUFiU6b33dsr+/bHOnDJzhunMcGZ9nofnzN577b3X+bLOfvcq7/vGp+Z6e3BOGnDSwNUnXU1MZAxzJ89le952ahprsIYZ1HZUsHHPRlLjU6mlmKjlefxuza/49vudVHyUSLWE716A//3BHjpaVA66fuawHTBmh3VU5cfsawiOeuA64FohxHZUaK6npZQ1w1azgwjdg1Ps3r0bgOnTp/dScmyg9fAxEC3ijBj+wR8ppwq7YSedFKZ64lKmkEQVNTxnvkY1tXTgYJFxKInEc6/5CPOZw9Ec6f1ttpsd2LFhMdQ7/bbORSqGAT+8TRm+4y9XrgiGAT95CJrr4PZTYOJsFZOz3i9cl2eBip0UMrgagwgSON57eBw/A0zKeYxqXsdClMfAReGmleqyaqqpZvr06TipIynRJN6pVoe2sRewEOM8BMIiCLeH43A5iI6IZnzKeLKSszAxSY5N5tktjzDLfRwdzg7K2vLp+HwqO+JNwmINKpx55OxIxFKVQtJUSDkQzZMz02EAACAASURBVNBpw+V29Sv6SG9tw9rfzPR+9DXY8hTgOOAZYBrKdaBYCPGcZzXlmEbHolQkJiaSmJg40tUYNWg9fAxUi0gjgsmeDArnGKuJ86QYmo3gM77GjZtVxkqOM46ihjpSSMaChefM1yijwnudNbzNhyiXhGazhfvNx303iUlQ2do742sCpE+CyXNV7M2C79ScnT0c3vyXCvd/549U7w6Vr87AIIoZ3kt2LkjJ4ErctBHDYTSxhQgm46SOiIxdXj1a2UViXAyJSWpM0UEtTmrgI19W9qbWJmZNnMXZS8/mxIUncsXxV3DFCVdQxA7CFudT1VCF+8hvyV19Hxtb3iJzPtgW5lBaWEdbLbQ3BOraQTkOhr5/YriUgesPvbWNwXQg+hxEUUr5IfChEOJ64EeocFznAecKIYqAx4HHpJR5A67NQYruwSlSU1NHugqjCq2Hj6HWItGIZ4KZqfL6GdE0mk0cykwSiGeeMYvbzD+TSyGlZgULjLmEE04Tzewxcyilggy/gMpuTyb3blgssOxsZegypqhA0O+sVas1566AYgnpU1RvLjZRLViZuwKWBsboTOQEwpmIgZ1wJlHBU4TH2UhFaeKkATvplPMo4/gJJg5ctCj3Bk9PsbqxmlMWn8Kcyb7oh5mJmURFRNFOE40tjSQnJjBnqmBDzoP8+vhTiNtbT01pC1EmtNcHfjUHFViI9M0xDgGmaWJ1hfXbwA3n76TfXQ8pZaOU8iEp5ZHATOAewA78P2CvEOIDIcQFQ1zPUY12E9BoDjyLjXnEGMopPdaIIcVIwmZYSTDimW/M5j3zE94w13nnhDroYDu7WG9uJJlETNPkDfN91vBOzzeZvli5G6RkwXihQot98iwcdS68/ZByMH/rAWWIouOhsXuwyEgOwYKdSKZhIQwwMbDRxFZa2YuKl2ESRoY3a4GdVNoce8DZgZs2bvvhbSyevjjguuNTxnPVCVdR1VBFQkwCVouVaeOncdbSs3C6nGTPdFBX0YzbBW0eA9fRAo42yHs/ImjGhcHgcruwuiP6beB6YzDP10GNrUnFr1CrKU8F3gNWAk8M5roHG07n0DaUgxUpJVLKka7GqEHr4eNAa3EaJ/IT4wqOM37ALlScwyzG0UY7JxkrmGxk0UwLTpy4cHOb+05vypseSZ+kVl/GpUBcMpx8rXImn71cLURJmwyGBaqKYePbKiN6V0yTDK6kVi4kv+4V6vkUC+FEkE0Us3DT4h3udDqKcTsaqeKVHrNkZyZlMi55HOkJ6TS3NRMVHkVyXDI7C3cybXYFjTuiSZqqshQ8cG4hH/27jA9ugc33puByDq0hcrld2Nxh/Q6t1VvbGDED58cS4DTwhl0fgLvfwYseolQkJyeTnDxm8952Q+vh40BrkWokk2wkMotpPGo+h4nJQg5lJUtZYMwljRQaPBm9a6kjnVRKKKPD7ODv7od7vrDVBhd4vKuzPWGpZhyhksPaw9R2wXfw/Xr4y2UqQ3mdZy6wrRke/Bm0tZCcnEwip2AhAivRRCGIYYEnRY8FO6nYnfG0duzESeD4Yj3raWQzbhxMyZjCqoWrSE9Ip7qhmuyMbA6dcihvfP0GMRHRpF77OWI1tNa6qJ+3gY2vVTFhKWQeWc/Wh+IxzaEL+eV2u7G6wnH208ANZ9sYcCIzTyaBS1BzcQLVz96KZ4XlkNTuIEEbOEVKSspIV2FUofXwMVJaJBjxHM585jGbcCOMTJRzdRyx3Gc+yuXG+ewy93KYMYtKaviGHYRhp9ysopEmEokn2UjkRfMNzjVWq4t2/b3b7GC6VczLsAjI264Wosw8El6+S0VSWXWNyntXWw53nE7Kn9YBKdTnb8Ya2wZJYCGSataSyo/UbRzQ4HiPMOZhYuKmCSuxuGjCRT11VJBkX8X4lPEsnbmUI2ceidWiVhzmlOUQGzEdV0QjpmlSuPxplmdM5dMXkph5tkmmO4+679L4/NF66r6JY+l/GyT2kDi9r7hNNxbT1u8e3HC2jX4ZOCGEDdVTuxw40XN+HfAv4BEp5ZYhr6HmoKFzrkMbfIXWw8dIanEGq7qFH4slmulGNtONbGYjmMFU3jI/ZBvf8xvjp/zL/A8dODjTOImPzc/53NxEOikkkcAcY0b3mxxxukq+mpGt3Am2f6yyoL/zb6gogI42lQnBZofYJKWHaRJe1I41rgqSwMBKNHO9AZwNhwNLhxUL0dSwlga+IJLphDOBBE6klndpp5BwJnDUnIBgU9x1xV202J/m3S0vMT5uAS63i2Wzl1J0x1s0tcVARBtrSv9K0YdHc/TsFeS8n8XCqwens9vtxmLacTr6Z+CGs230ycAJIQ5FGbULwRtC4CNUb+0VKeUoC7F5YNGLTBSd/ixCiBGuyehA6+FjJLUIFlszjljSUT2HU43jcZouJhrjmMg4JhlZXMZ5vGi+wW5yKTcrWGQcxmZzG1ONKUw3s2mgiRTDbwViynhfgteYBLUoJSwCDpmvQoXlfAvyKxVNpbmO3VKS/M59pEzMBqdvRiedy3z1tqaT5jiTZpw0s4NYDqeDYq9bAkA1rzGOG7t9v4SYBFqxER8dw87Cnd6M4xOmJfDWxrdYtKCD2uYqYuIiaHW0YLHB2tc+Y/Wpywbs9uRyu7AYbhz9NHDD2Tb62oPb6vksBP7AGHUH6An9hq7QQ3KBaD18jDYt4oxYVpm+qP82w8qp+Fx6sxjHHGMGX5ibuMa4iDSSqTMaWMdnvMsnFFPKtVziLf+5uYnFzMNueB6p4ZHqc8kpKovBprfgmEtg4izI205qGIRNmAYVuRATfKm+YY+ADgfRLCCSmdTyLtEcSgwqoJSbZpzUUMdHJLCy+/nYSI1PIiUuhahwFRs0OyOb2568jbSJR5MSl4R7ohViGgmLhQ1/spESsxcxcTrJ07pdrlecThfz417D5byoX+eNhiHKl1C9tfeklKMnDssoQTt6K/SCikC0Hj5Goxb7ezG1GVZWsZKd5m7SScVu2EgjhbPMVTzJS7hMN+/yMScaKwDYwS5iiKbCrOJYlgdeO2OK8mk77xY1f9dYQ9KWN2D5uWpl5nuPBa9EWAQ42jGwYCUKJ1VEMh0D1SO1EEkMC2jmW6+BMzG9vTsDG+kpkZx39Fke9wRIT0zn0mMvZWf+u8RFJxO9GCxGEWL5QmJ27USuXY4xGRZcBc42iO6Hi5rT4Sbc3oqzn6sze2sbg+lA9DWSyXlSynf7YtyEED8XQozyxOpDy2BCyYQSbrdbD9f6ofXwcbBqsco4xtcrQ0VWuca4CKthJZcCAOrMemrMOjayhRfMtdTTQIVZxQvmWnVSdDxc/n++xSkp4zFbGnF3Jm612tRqy/J8qClTEVJME+wRymnNQwelhPklcEnkBCIRnpWXyrjVsNZ73MDKxAkOHH4RXQzD4KylZxFmi6TD2UZaWiJtRiMuSzuRUxuo3hiDLRI++xPkfdw/rRztLuzWdpyO/v0/99Y2BvN87fcqSiHEh/s5bACHAvb9lBlShBDHAhcBy1D+eKXAB8BvpZRlQcqfBtwOzAIqUD3TP0opB+zMdjD+cIeDzpxOes5JofXwcbBqMdMIPlY33rMaM88sYq35LplGOvvMPA5jNlXU8h0SKz08mDOnUhKZTtOePUqPJafAJ8+pOJixSbD1fTWUmZCmUvh4SOF8b/JVUD00G4m46aCV3bSym0Y2kcRpnlBhdsalxuGiOeD2sVGxrDz0GGoaa4lzZ5BXnsdTHz7Fhr2fcMKps1hw1TheudAkMdukqcJC8dcgVveulctpYre19dvADWfbGIibQDbdM3kbQDoQDtQCNwyyXv3hTiAJeBHY46nfjcBqIcQ8KaX39UUIsQpYA3wI/ASYi8prl+LZHhB6Dk6hQ1MFovXwEWpanGqcQKPZxLOsYZmxmAXM5QtjM9lMJIcC3LixYuVB8yku5ExKKGe6ka1OjojCdsw5pHQawM44l7Vl0NoAWUK5GkxfAtUlUFUEyeOJMjwGwNEOzfWQkIadFOykUslLOKkmihm4aMBKHAY2EuPDcHcxcADJcSkkx6WQyAxe/eJV5mfP56en/pRvc7/lq90xOI4I44NttYTHH0vFdgsTloI7vIX/e/lP/OGSPwTVxNlhYrM6+r2KcjjbRr8NnJRyck/HhBBnAk8O5LqD4BfAeiml97VBCPEO8AlwPaq31sndwBbgRCmly1O2AbhFCHGvlHJAaWX76/cRqiQlDV1cu1BA6+EjFLWIIZocM58rjB9hGAZLWYRpmrzJ+8QRx7nGav6f+y42GBt50XyDh427AWgz23k64VVONo7FYtpINOLVopT2Ftj+KZxzk+rBxSbDS39W83eYcNYv1Y1L90HB97D8HAAyuJwa3sJJMvGspI0copiBBRWOq2sPrhMT9ci8+dybvS/pDpeDJz58gsPnHM7ijJV89nQFh5+WwaZ/gTurnpLakh71cDrUEKXL2b8eXG9tYzCRooZ0dYSU8lXgAeC2obxuL/f81N+4de4DalCxMgEQQsxCDUs+2GncPNyP0uHsA1DdkMblcmlj74fWw0coamEYBlcaPwpwQzAMg5M4hplMBeAG41I2m9uYwgSeNdfwvPkaN5i/wW7a+cq9hdc642DawlSkkyWrYfx05V6QOkH13qLilIN4Jw3VUONLxWklliROIYOrCCOdKl6kijXYSSWKmbhooopXA+quMox39z87eu7RzMueh8PpYPriROLP3Mm4RRCe1k5taTsJ0V2ypfvhbHdjs3b0e4hyONvGcCz/k8C4YbhunxFCxAAxQJXf7vmez03+ZaWUJUCR3/F+o+fgFHv37mXv3r0jXY1Rg9bDR6hqMa1z2NGP8UaG1xk8w0jjJGMlqUYypWY50txHNFHU1NbwedPXGFgwTRNzzg9UtJOlZ/gWoxgGtNSreJfZh6mhyd0b4b1HA3znyN3mSbZqxUos4/lvOijFTioZXIWLepr5tls9rcTg8oQr6yTcHs6yWcvYtGcT6VOicU0sIv1Qk+fNW2hubiXOntRjQlOn08Q+AAM3nG1jOAzcHGDHMFy3P/wXEAa84Levc/lRsCzkpQzSKFdVKVtqmiZSSqqrVaBVt9uNlJKaGpV7yeVyIaWktrYWUN1vKSV1dXUAOBwOpJTU16v4cx0dHUgpaWhQCZ3a29uRUtLYqFZOtbW1IaWkqUk11NbWVqSUNDerYYmWlhaklLS0qNxVzc3NSClpbVXZj5uampBS0tamVms1NjYipaS9XU1uNzQ0IKWko0P9oOrr65FS4nCo3FV1dXVIKXE6naSlpREdHY2U0vtGVlNTg5TS+xJQXV2NlNL7I6mqqgoItFpZWel1/ASoqKjwTkIDlJeXB/wYysrK2LdvX8B2Tk6Od7u0tJTc3FzvdklJCXl5ed7t4uJi8vPzvdtFRUUUFBR4twsLCyksLPRuFxQUUFRU5N3Oz8+nuLjYu52Xl0dJiRrGSUtL89ahk5ycHMrKfGuf9u3bF7C9d+9eyst9b+t79uyhosK3Cm737t1UVvoSb0opD4q2l5aWRlxc3LC1PYDa2tpR2fYWGHO5mgtZVrmQsDo705hCSmQyGa5UnNUdvME61sZt5p2WzRQUFFBqqv//wsJC2tralaFLmUDV64/Q8tT/wPzjIDrB1/Ye/Bm4nN62ZyeJDK6kJNdFaWkpDmoJZyL78rYHtLWKQiip2ubd7mx7cybN4fQjTic3J5ea2hrKasuIj4nn/fYHiPjiCNbd5qRKdm97eTn5WI1WnO39a3tpaWkkJSXtt+0NlIGsopzYw6E4VPiui4BrupaTUhYEPSvw2hbwOGz0gpSyLdh+IcQPgN8Bz0opP/E75PG8JFjUlTYgqi/31fRMZ9LCzgfcWCcxMdFrPMY6iYmJNDc3D/qBdbBiGAaZrjSWOhcwN3EO66I+YWnDQvZZ8qikhlhi+CzySya3Z/Epn3KCuQIr0HDyjUQApGQR/ua/caZMVOl7/nMrsSWP0r5oNaRMgJK92MpLYILqOapoJ8q4OKkkmTOoTnuI8JaLgAxVJ1cMpqUyaF1PWXIKe/bsYUvuFgpqC/jR0T/i7py7SQqLojj9M5r+eAwTL7QTG27gCQiDy4kaomztn6t0YmIiDofDawyHEqOn7mZPCCHcdF9FGXDNYMellL06MwghVqBCgPWFVCml/xAkQogZwAYgFzhaStnsd+y/gbuAcVLK0i7nfQ20SykDA7r1ASFEXWRkZPzWrVt7LxzidL5J22wHco3R6EXr4UNr4cNtupGuvUwjmxJrOev4lNUcx/fs5jtzN27cFFBMFpn82LiYSCNC+cn9/Sr45RMQEaVWUW5+V0VIGS/USkyAk3+sPj2JUgFK+CeZXEsJ92ElmhgW0UE5iRxHHZ+QyLE91vWnD/yUto42bj73ZsLt4RRVFfHoe4/y90sfZOO/oHwbnPOMKvv5ur2kP3oNO0/9C6svmNdnPXprG/PmzaO1tbVeStnzBGAPDKS13cH+Ddxg2IWKedkXGv03hBATUPno6oBT/I2bh06jlkn3YcpM4PP+VdWHnoNTdA7XHGy+TsOF1sOH1sKHxbBg2Weyj31Mnz6d5Swh3UglnVRqacAAruICXuc9Hjaf4TouxRYdr/LQRXgGmqLjYemZkL8DFp6oAjlnZEPBThUH86u1qqcHjPN4bUUxiwbW46SROA7HwIaTGqp5HQMbUcwmgsABuruuvItL7rmExJhEEmMTaWxtpLm9mYh4aCiEmAxfWafDjd3qwNnWP/MwnG1jIG4Ctw95LXzXLgMe7+95QohklHELB46RUpYHKdbZxVoEfON37jiUg/iAu2A6kokiPT19pKswqtB6+NBaBNKph2EYCA7x7p/GFHIpIMqI5ExzFT/ndh40n+R04wSyxk0NvIjNDhffof6uLISZS+H1+yB7nlpp+co9cNxlKjkrKrSXSrdTT5gnY0Eyp9PMNlrYQQeJ3QxcmC2MuuY64qPjAUiITqDNE13FOrGK0tIavn1yOmExUJ8bjs1w9HuIsre2MZhQiAf9eIEQIhp4CxgPrJRSBl2OI6X8TgixCzU/+Iifq8B1gBt4eaB10AZOkZDQ7xGEkEbr4UNrEUhPesw1ZjAXNY8WZoTxK66niWZeM9/j+hOupMeQEre9ApEx4LwYXvg/lXvO2QGVBV4DZyWKGBYRyTTCK02wV2BJSCOWRcSwgDreD7hkB2U4jRrSE9K9RiYjKYNVC1fR7mjnMfMGFoVdwncvTsd0Q5MzlsPTnf3uwfXWNsa0gUMlV10CPArMFELM9DtWLqVc57d9E7AWeFcI8TxqxeeNKN+43WgGRefqNrv9gEVqG9VoPXxoLQLpqx6TDNXTqqCK+hgLW8wNHMos7NiIM2J9BaM8f9vDIXk8dLQq/7l//wJuehqSxxHJDAzsKvBy8QcQEaPCgYFyVyBwqqWdAty0Mj55fMD+ouoiTv7dyZy99GycrfmkWQED3GUtYLHhau2fT9twto1QCIPfOZt5BSqKiv+/W/0LSinfAM5C5bS7z/P3H4CfDqYCg/G0DyVycnIClkmPdbQePrQWgfRXjyQSqaGOAorZwg7+Yj5Eudl9BSQAk2ZDVLwK+ZWYAWU54GjHSrQ3qwBNdZ4IKT6cVNHAFzSzjQa+xEktbtrISskKKHfGEWcwbdw0rl99PZkZqUy6rJijfwuRE5sgPIymPHuPvnID0WIwaxwO+h7c/kKH9VB+DSoe5ZDR35WooUpGRkbvhcYQWg8fWotA+qtHFpk8Yb7EcmMx3/I9y40lrOdrzuaU7oVnHqmSrGYJ1Utb9xjs2wInXAltTWC1Q3Odz6Hcg4GNOj4C3IQxnjAyAIOrTrwqoNxh2Ydxw2q1cGXRtEV8sn0d08RlxM+uw/KljQ15azlyZxRzZ4qutxiQFmPawI0GdLBlRXx8/EhXYVSh9fChtQikv3okG4n83LgagM/dm5hhHMImttFithJlRNJoNhFrxPhOmLYIkjIhMRPWvwQWK2x8E/ZuhiKpYl22NikjOGk2AImcRBjfogb2LHRQjIUowuzdzcTcyXMBmJg6kZyyHNZ8sYbGqFKskXY6EkpY/1/JpN8D6XOHXov+EApDlJpRQkdHhzfqhEbr4Y/WIpDB6LHKOIZM0jmW5bzJB6w3v+YB80lyTF9EHsZNhYhoNQ/XUKVcB0r2QuFOOPdmuPSPYLqhcJf3FBsJxHM08RyFnSSc1GMnqVs4L3+sVivZGdlU1FXw1fefgy2cpoydxJ68m8ZgMaOGWIve0AZuCNB+cIrc3NyAsFhjHa2HD61FIIPRY7qRjdWwEmvEEE8sa833mGZM4TnzNXabOWwwv6bEE+6L8EiVGTzzEDU8OeUwmHG4Onbdfd3m4TqxkYSTaqzE4qSWNvJowxeMyk2gQbLb7Dic7VjsYYTZDNyz9tFQ6qKjD0GNhrNtaAM3BOghSkVmZiaZmZm9FxwjaD18aC0CGSo9jmAhM41pzEYQTRTb+J5XzXfYwEZVwDDg1peVE3jWDF/KHX++eC2gJwdgJxUXzViJpYR/UMu7VPAUJmqFZD6/9ZaNCIug3dHOkdOXYAuPwjBNWp3NvPXxBzx/vpN2R7DoiD6Gs21oAzcEaAOniIuLIy4ubqSrMWrQevjQWgQyVHrEGTFcbpzPNGMKVxkXMJ5MjjWOwoqFV8y3+bv7YVqNDtWTO/ZiFQHFnz0b4bvPVFoePwwsTOJ32EkjhXOwkUA0h9LMNly0BpSNj46nvK6cy465mKiYBMIsVgorC6nbE0ZddA4fPFjG9ueGX4tgaAOnGTLa29u9keA1Wg9/tBaBDIce0UYURxoLWWWsxIKFYrOUucZMygOyhnWhqRZ+eBs0egId5/kSwRjYsBJFHEdgI4V4ltFBOe3kYseXhfu4ecdxzUnXgNuFYQ/nsf96hILKAlKOraBi3Eba2tvo8EzjtbS1dKvCcLYNbeCGgMF42ocSeXl5AaloxjpaDx9ai0CGW48OHMwwpjKR8TTRxHemZJv5PQ1mlwUjNz2tenVvPQDFe1QGcfm1CtbsRwLHYENlC6lmLXaSvY7hdpud2KRSTLcTbGFEWO08/LOHmXq8hdbYUqzZVRRW57Np12buf/P+bnXtTYvBBOjWbgJDgB6iVIwbN6J5bkcdWg8fWotAhluPWGKYwDhiiaaKavIoYq+Zy3xjLsvMRdixE21EQefL+XX3wZq/qcDNz/8RDlkAp97oDfNleIOEmViJJ5xJtFNAM9uI5XDq+QS7eyl2G1hcTsLt4cyaOIvsS7IpqCygsrKGrTdk0np+95Q4w6mFNnBDgDZwitjY2N4LjSG0Hj60FoEMtx5LmEcs0ThwUkk10UTyS+Na3uVjvmEHpVRwtHkEWYZnccek2XD9P5RvXEQMfPEqfLceksepBSoeQ+eimVgWEsNCqnkNJ3U08y2RzMDpLqPZ9ilJrssAmDVxFg6ng52FO7FObqfmMElkYTrlOyBlBlhtw6+FHlsbAnSoLkVbW5s3O7NG6+GP1iKQ4dYj2UgkzAgjikhcuFnO4UQaEbhxU0gJG8yvqaQ68CTDUDEtF58M1/8T6ivgvUfhidvge5VNzEoEdlIxsBLGOBI4hjZyiWAKja4NmGFWXO5GrxuB3Wanqa0JwzBoG5dLdPVktj4On/weSjZDXX7vWnRmaB8I2sANAdoPTpGfn09+fn7vBccIWg8fWotADpQehmFwhnESiYZaPbmIw6gxa/mhcTqNNPGZ+RV7zC5xIG125SSeOVXNxV17LxR8D4CdNO8CkziOIILJOKnHRhwp7nOx2ONpdG6gno+9l4uJiGHBIQuIiQ8nrDKThkKIm6CSpa65DPJy96/FYEIh6iHKIUAPUSrGjx/fe6ExhNbDh9YikJHSYzwZLDHmsZh5vMEH5JuFRBtRvOh+gxuNKwgnDAcOYoxoOGwlhEcpg9dcB1s/IPawY7rFsLSThI1ULO4awmzZuNwWnPhGtS70JF6N/TyWzCt2szh+Ac5GG++v20xKxkKSo8cTmTQ831cbuCFAGzhFTExM74XGEFoPH1qLQEZKD6thZRlLACh2l3K0cSRpJNNhOJDsxYWLNtpZwVJ1QmfUk8NPA/mlykLgcnjT7ABk4AnG7HZh2KNwu1ox6J4jMysli4T4WOLnNBIdEU3ev8qZMR+2PxzDMXcMz/fVQ5SaIaO1tZXW1tbeC44RtB4+tBaBjAY9GmlmAuPIMsaRRSYVVFNGJTXUdy+cNR3SJkNTDTx2M9R6QoFVFfvKmG6wR+F2BY/PdeUJVxITGcO9r9/L+u/X4yxKIHMh5H3i4vvXtR/cqEXPwSkKCgooKCjoveAYQevhQ2sRyGjQ41hjOSmoscEwI4wWWjEwMHGz09yD03TxgPkEDlMlJCU2Cda/DKt+DPf9GMpyld9cJy4XNnsadlfwDN0Wi4UwWxiV9ZW8ufFNWL2eaSebLHtoL7s+bKBk89B/R23ghgA9RKnIysoiKyur94JjBK2HD61FIKNBj8ON+QHPrjRSqKKGLMbxlPkyO9jFXjOPOjwBmeOSIWerGrZceaFKv9Pa6HMKd7sIs08g1nWo95pNbMHExOm5xuxJs7n1/Fupa6pjyqJonvv0WbKysoiJiqdgw9B/R23ghgCrtft481gkOjqa6Ojoka7GqEHr4UNrEcho1GMZi5nJNOYzmxuMy/mKLUw1JlPbOWSZmAEZU9TfS8+CrR/ArGXKdw7A7VKZC1xOTExqeY96PqGNXGp5m0peIDE2nsykTOZlz0OMF6z5Yg3R0dEcsiKMLfkbaWlrobaxFrfbt3Iywj3wFSjawA0BugenaGlpoaWle6y5sYrWw4fWIpDRqIfNsLLUWESYEcY4I50FzOFEVngNXB7FOM+7WRW2WtVCk+x58OGTap/bBbYwcDmxYKeFncSzgno+xkENHRTTjpqzu/HUG0lLSCMuKo6auho22p7DaKcmZQAAHMhJREFUnFTCX67+kkfvWs/H99bT0QzOdliUd+eAv5M2cEPAYPw0QonCwkIKCwtHuhqjBq2HD61FIAeDHouNeaSTSh31dJgdvGGu49mId3255hauUhFQGqpVkOa6ctWDc7QRxnhSOJsY5hFOFiZOojmUatZgYmIYBnMnz+WcZeewXW5nX8E+rrzuJDa711LypZXKxgruOPkrdq2B1rA+Zk4NgjZwQ4DuwSkmTJjAhAkTRroaowathw+tRSAHix6RRNBMC2/xIclGItvMnXzNFnVw6RnKoJ37K/jsBXjjnxAWCWvvJWrD94Sj5hgTOYFkTiWOZXRQhBMVj9IwDNIT02mztJE9MZtwezhJs51YG+MprS0lN+xLPvhnJY1heQOuvzZwQ8BgQsmEElFRUURFRY10NUYNWg8fWotADhY9DMPgTfMDmmnlfE4jlmjcuANHrezhcO6v4ebnIW2iMnKNNeD3XIxgMhYiyOBqmtjq3Z+RmMGW3C2ICQKAv/3X/3LOFYtpaG4kPNaC49T3abDnDbj+2sANAXqIUtHc3Exzcx9y1I8RtB4+tBaBHEx6/N74JZMYj8Ww8APjSKYwkQd5MrBQRLSak7PawOmA2cth20fdrhXJNEzavZnB0xPSWf/delJiUgCIjYplydVhHLVkEbMTF2GfXoHD0tTtOn1FG7ghQBs4RVFREUVFRb0XHCNoPXxoLQI5mPTIMsax3FDRT1YYRzKHGYBBs9lCkVlCh9nhK2yxqcUmE2ZAWQ50JjhtqIaPnga3m2gOpZEvqeAZ2iyS689eREtd4IKbpedl0DTzG7IzsnHRwUDRobqGAJ3wVDFx4sSRrsKoQuvhQ2sRyMGsh92wkWwmcqt5J04cHGscxTHmMuKNOJVf7rZXVMEZR8Lur2HcVBX9JGsGfL+B8DlH0cpeOiimjUQWzlhInGtSwD3CY2HesiyOmn0UdxnPD7iu+smsGTIiIyOJjIwc6WqMGrQePrQWgRzsekwmCycOJjCedeanVFCF03SpQMwxnkgmKVnw/J9g0zsq+smPboPSfQAksAIrcTSxCXuYHVfkbjoo8WYJBzjhyFkkxCTgNgaejkz34IYAPUSpaGpSY+U6sK5C6+FDaxHIwa7HYmMepVTgxk2MGc2L5ptMNSYxw5zGocZMVSgmAY67VC1CmXNUt2tYiCSGxbS3tdNgXYfF3k4aFxOB6t3W8zGRTAPLwA2c7sENAdrAKYqLiykuLu694BhB6+FDaxFIKOhxKsdzAkdzmXEerbTSSDOPms/RarbRZrbjxlQhvZafE3ji7k0AWIkmgZXUNpTQWjEeEycOyjBx4abD6xSue3AjjN1uH+kqjAomTZrUe6ExhNbDh9YikFDQwzAMolDDrHdwE7eb9zCVSbzPp7xhvs8NxmUcyiwcpgO74XlGuhzw3iMwfRFxLMdCOJnxi7Gb43EzBTftFHAH6VyJmxYa+ALD4oYB9iF0D24I0I7eioiICCIiIka6GqMGrYcPrUUgoaaHYRj8yrieKcYkWmhlpbGMJlpoMpt5yHyaD01PJOWaMuUjB4SRDkBi+CJiIjKJZRFuWrCRTDWvkM6VOKklLmXgI2TawA0BeohS0djYSGNj40hXY9Sg9fChtQgkFPWINqIIx04bHZzNKaw13+VP5n1UUc0X5iYeMJ+AYy4CsQQc7SoLgWnSWFlKY2MjBjY6KCeWhViIJIIpgMEh8wdeJz1EOQQ4nQMfIw4lSkpKABBCjHBNRgdaDx9ai0BCVY8pTGI2Arth42iWstn8ll8a19JEM+v4VGUjyJoBa++D7z6DaYtxFOVSeepNiBkzcFBJAscQxzIALIQRlzrwSFHawA0BeohSMXny5JGuwqhC6+FDaxFIqOpxiOGbWzyc+fzAOJxII4JIIogww8k3ixgXGYl928cwcRbEJROPJG776zBlEo7wCuykeK9hJR5bhF5kohkFhIeHj3QVRhVaDx9ai0DGgh5JRmBm7+P4Ac+xhvy4D/jDsrMxpi6A7MOwLjhB+ctVFhCddRgWItTwpduF1RpNePLAQ5rpObghQM/BKRoaGmhoaBjpaowatB4+tBaBjEU9Yomm0CwlasI8vjh+LvumKAPYEJ1K41k3w0M/J21XtjJuZTnwwRNYiMLZ5BjwPXUPbgjQBk5RWqryNsXFxY1wTUYHWg8fWotAxqIehmHwP8ZNfGFu5mHzGezY+Ad/UlqYJmL5uSqvXN4OiIqDr17HOmUiqzfu4xm/Ycv+oA3cEKBjUSqmTJky0lUYVWg9fGgtAhnLeqSSzA3GZQDkkO/TYsYMeO8xyNkK4VHwkwexffQExVUDX+OgDZxmyAgLCxvpKowqtB4+tBaBjGU9phqTAXCaLl7lbfLshaz0rJpk8lyIT4HPXoTYZIzyQnKbBh5IQ3c9NENGfX099fX1I12NUYPWw4fWIhCtB9gMK6kk8W7Hx+Q25rHT3MO6aS2w6GSoKgSrFRprqHMP3MDpHtwQoIcoFWVlZQDEx8ePcE1GB1oPH1qLQLQeimUs5vP6r/mP9UXmMRcrVjZatlN1yw2sAmiopIaBrzjVBm4I0AZOkZ2dPdJVGFVoPXxoLQLReijshp2bEm+gmlp2sIsVLON+83HqYus5yTTZc8YZ1K37GwMNRqkNnGbI0EGnA9F6+NBaBKL18GG328kgjQzSAGg2WyiklH3k89WCFFpxAwNbaKK7HkOAwzFwP41Qoq6ujrq6upGuxqhB6+FDaxGI1sNHVy3iieM841S2s5PlLKF1EJEQtYEbArQfnKK8vJzy8vKRrsaoQevhQ2sRiNbDR1ctUoxEpjKZ783dpJOK0xy4m4ChH86DQwhRFxkZGb9169aRrsqI0xl02mbTI9+g9fBHaxGI1sNHVy0qzWpSSPLG+D1uwUwKm931UsqEHi/SA1pdzZChf6yBaD18aC0C0Xr46KpFqpEcsN0xwPk30EOUQ4LuBStqa2upra0d6WqMGrQePrQWgWg9fPSmRaPbOuBr69eIIUAbOEVFRQUAiYmJI1yT0YHWw4fWIhCth4/etHAPoh+mDdwQoP3gFFOnTh3pKowqtB4+tBaBaD18DKcW2sANAdrAKazWgQ8lhCJaDx9ai0C0Hj5608JqGbhW+sk8BOiM3oqamhpqampGuhqjBq2HD61FIFoPH71pMZgOhO7BDQF6Dk5RWVkJQFJS0gjXZHSg9fChtQhE6+FjOLUIOQMnhLgfuA54TUp5RpDjpwG3A7OACuAR4I9SykH4y2sApk2bNtJVGFVoPXxoLQLRevjoTQu32z3ga4eUgRNCHApcBbT1cHwVsAb4EPgJMBf4LZDi2R4Qg/kPCCX0XGQgWg8fWotAtB4+etNCGzgffweeAo7p4fjdwBbgRCmlC0AI0QDcIoS4V0q5ZyA31UOUiurqagCSk5N7KTk20Hr40FoEovXwMZxahMxrhBDiXGAxcGsPx2ehhiUf7DRuHu5H6XD2QO+tDZyiqqqKqqqqka7GqEHr4UNrEYjWw8dwahESPTghRCSqd3anlLJUCBGs2HzP5yb/nVLKEiFEkd/xfqOHGxTTp08f6SqMKrQePrQWgWg9fAynFqHyZP4VKmHQ3fspk+n5LA1yrBQYN9Cbu91u7xuIaZpIKb3dbrfbjZTSuwzW5XIhpfSGpnE6nUgpvekiHA4HUkpvOvuOjg6klDQ0NADQ3t6OlJLGxkYA2trakFLS1NQEQGtrK1JKmpubAWhpaUFKSUtLCwDNzc1IKWltbQWgqakJKSVtbWrasrGxESkl7e3tADQ0NCClpKOjA4D6+nqklN4UQXV1dUgpcTqdGIbh3Xa5VCe5pqYGKaV3HL26uhoppbfXW1VVhZTSq2VlZSW7d+/2bldUVLBnj2/kuLy8nL1793q3y8rK2LdvX8B2Tk6Od7u0tJTc3FzvdklJCXl5ed7t4uJi8vPzvdtFRUUUFBR4twsLCyksLPRuFxQUUFRU5N3Oz8+nuLjYu52Xl0dJSQmg3Efy8vIoLfU1uZycHG82Z4B9+/YFbO/duzcgsvqePXu8kR4Adu/e7V11BiClPCjanmEY3u3haHugQj4dLG3PMAxKSkqGre0B5ObmHhRtzzAM73ZPbW+gjKoenBDCAoT1payUss1zzkTg18DVUsrW/ZwS6flsD3KsDYjqR1U1QaiqqvIaUo3So729nYiIiJGuyojTqYVG0flbCQvr0+MupKmqqvK+lAw1o8rAAT8APupLQSFEqpSyCrgL2A4808spncYvPMixCL/j/SWuvb2dk046aYCnhw6db8p6yFah9fChtQhE6+GjNy08Pf64gVx7tBm4XcDlfSzbKIRYCJwHXAhM8pt7swFRQojJQLWUshHf0GQm3YcpM4HPB1hnN2BpbGwcXF9ao9FoNMGIQz1n+82oMnBSyjLg8b6WF0JM8Pz5dJDD44FclNP3A0BnRtJFwDd+1xgHZPkd7xdSylGloUaj0WgUB3v/+CvgzCD/KoGvPX+/AyCl/A7VQ7xGCOEfvfM61NvByweu2hqNRqMZboxQ9OESQuQBW7uG6hJCrAbWoiKZPA/MAW5E+cZdf4CrqdFoNJph5GDvwfULKeUbwFlAMnCf5+8/AD8dyXppNBqNZugJyR6cRqPRaDRjqgen0Wg0mrGDNnAajUajCUm0gdNoNBpNSKINnEaj0WhCEm3gNBqNRhOSaAOn0Wg0mpBEGziNRqPRhCTawGk0Go0mJNGBggeAECIcuAO4GEgEvgVulVJ+MKIVG2aEEIuBy4CVwCSgGpWF4TYp5V6/ch8DRwe5xPNSyh8Of02HHyHECnpO7TRTSrnLr+xS4M/AAqABFSbuFillyCTPE0I8Dly6nyJZUsriUGwbQohM4GfA4ahg7jHASinlx0HKngbcDswCKoBHgD9KKZ1dyiWg2syZqFyVXwG/kFIOKCj8gaIvWgghkoErgNOAGYAd2An8RUr5YpfrXQY81sPtIjvzgvaENnAD43HgbOBvwF7UQ/9tIcTRUsovRrBew82vgWXAi8A2IAMVy3OLEGKJlHKnX9kC4NYu5+cdiEoeYP4GbO6yz5tWWQgxD/gA+A74BSpzxX8D2cCpB6iOB4IHgfe77DNQmTzypJTFfvtDrW0I1G9jL+p3sTRoISFWAWtQsXB/AswFfgukeLY7y1mANz3H70a9SF4PfCyEWCil3MfopS9aHAn8EXgLFSrRiXqeviCE+K2U8n+CnHMrqt3409FbZbSB6ydCiCXAD4GfSyn/5tn3BLADuBOVtDVU+QtwgZTS27CEEM+jEs7+GmXoO6mVUj51YKs3InwipVyzn+N/Qj2gVkgpm8AbDPzfQohjpJQfDn8Vhx/Pi13Ay50QYjmq99E1nVWotY3NQIqUsloIcQbwag/l7ga2ACdKKV0AQogG4BYhxL1Syj2ecuegDMOZnW1LCPECsBv4HXDJ8H2VQdMXLb4Dpkkp8zt3CCHuR70g3SKEuFtK2TUB9VsD6b3qObj+cw7gAB7u3OHpJj8CLPd00UMSKeXn/sbNs28PqsHO7FpeCGETQsQcqPqNFEKIWCFEt5dFIUQccDzwRKdx8/AE0IRK1hvKXACYwDNdD4RS25BSNkopq/dXRggxCzUs+WCncfNwP+o5fLbfvnNQowCv+d2jEngBOEMIYR+qug81fdFCSpnrb9w8+0xU7zYSmBzsPCFEnKd322e0ges/84FdXR5YoPLPGcC8A1+lkUMIYQDpQFWXQzOBZlTm9RIhxG/62zgPEp5Ezau1CiHeE0LM9Ts2FzVKssn/BM9LwlZUWwpJPA/h84DPpZR5XQ6PlbbhT+f/dde2UAIUEdgW5gObPQ99f74GYoGpw1XJESbD89n1WQLwGVAPNAshXhJCTOzLBUO9UQ0HmUBpkP2d+8YdwLqMBi5EZU9/wW/fPtQY+w9Rw5bbPNv3H+jKDSMdwEuoCfXTgd8DS4D1QojpnjKdvfme2ksot5UTUWmpug5PjoW2EYz+tIUx94wRQiQBVwEfe3qrnTSjFpncgEpv9ndgNbBBCJHS23X1HFz/iQTag+xv8zs+JhBCzAD+CaxH9WQAkFJe2aXofzxzCNcIIf4qpZQHsJrDgpTyc9QK0k7WCiFeR72h/w5l+DvbQk/tJZTbygWooXz/F58x0TZ6oLe2ENWl7Jh5xnh6708D8XTJzelZVem/svJVIcSnqEU4P6f7YqUAdA+u/7QC4UH2R/gdD3mEEBmoRlYLnCuldPdyyj2oIdyVw123kUJK+S1qovxYz67OttBTewnJtuKZWzsdeLe3+RgPId826F9bGGvPmPtQPf7LpZTbeysspXwL2IXvd9Yj2sD1n1J8ww3+dO4rCXIspBBCxANvo964TpRSlvXhtELPZ9KwVWx0UIjvO3YOKfXUXkK1rZxB8NWTPTEW2kZ/2sKYecYIIX6HcoH4lZTy2X6c6v876xFt4PrPVmBGkBVgh3s+vz3A9TmgCCEigNeB6cDqfgwpZXs+K/db6uAnG9933IHy8VnkX0AIEYZajDSqnXYHwYWoVaJr+1h+LLSNzv/rrm1hHMo3cmuXsgs9C7j8ORyl615CACHEDSin979KKe/u5+n+v7Me0Qau/7yE8ry/qnOHJ7LJ5cAGz6qokEQIYUVF4TgSNSz5ZZAycR49up73G8BNd2fggxIhRGqQfctRw2zvAkgp61Hf9+IuL0QXoyI8vNj1Ggc7Hl2OA17tGqllrLSNYEgpv0MNq13j+c6dXIf67i/77XsJtZDk9M4dngUV5wKvSSkdw1/j4UUIcT5wL6qX/8v9lAv2O7sAOATP72x/6EUm/URK+ZUQ4kXgzx6ft32oEEWTCHR0DkXuQYXXeR1IEkJc5HesyeOUugB4RgjxLOpNMwa1XHwRcKeUMvcA13m4eF4I0YJaaFIFzAGu8fx9u1+5Wz1lPhZCPIx6W/8l8LaUMhQf6OejnivBhidDtm0IIW7z/NnpD3qx54WnTkr5D8++m1C92nc9ARLmoCIBPSil3O13uZeAL4EnhBB3o9rU9agOye3D+kWGgN608ATLeAIVAOED4EIhhP8l1kkpyz1/fy6E2Ax8g3LHWYJ63u5GrajcL9rADYxLgP/xfCailjqfLKXcMKK1Gn46ffxOpXuYqXyUo2Y+sAHluJqOejvdAVwmpfzPAarngWANaijul0AcKq7gM8DtUkpvSCEp5TdCiONQUW7+ivqR/hu45YDX+MBwIUqLYMY7lNtG1/BSV3g+84F/AEgp3xBCnIVaZXsfaojtD13PlVK6hBAnA3ehVhVGonzgLvGP+TqK6U2LWUAYkAo8GuT8lUCngXse5RZwEmpet9hzjd97Rkj2i2GaXX0JNRqNRqM5+NFzcBqNRqMJSbSB02g0Gk1Iog2cRqPRaEISbeA0Go1GE5JoA6fRaDSakEQbOI1Go9GEJNrAaTQajSYk0QZOo9GMGEKI64QQDUKI5AN0v1eFEB8diHtpRh7t6K0ZMwghVgD7e7gdGSy+pmZ48GSl2AP8S0r5O7/9t6OifSyWUm4Kct4K1P/jTf0N0iuEOAzYApwhpexrMGjNQYoO1aUZizwLvBVk/8EQBimUuB5IwBPK6kAgpfxWCPEx8P/oe7YDzUGKNnCascg3Usqn+lrYE/09vGt0fM3A8WRx/jEq6PSBTpPzJPCoEGKBlPKbA3xvzQFEGziNxg8hxGXAY8DxqLRAlwETgauBxz05uq5FpUuaiQoYvBG4Q0r5UZdrRaACz16ICsq9HbgNuAC4VEpp+JXNA/KklCu6XGMFajjucinl4377w1GBni9EpQ5pAz4Dfiul3BLsfFTW7P8GpgJlwD+llH8OosF8VAqbH6B6WBXAek/dC1EBb3dLKZcFOfcm4M/A0VLKT7se92MJKgPH/+6nTJ/x9MqO7uFwvpRyst/2257P81BR6jUhijZwmrFIlCe/lj/tUspGv+27UXn//o3KANCZ2PVJ4EeolCaPAeEoI7NOCHFWl3mdZ1HZrV9H5a46BHgFGFRaGCGEHXgHWOqpzz9Q2dWvBjYIIX4QZO7qWlQE/0eAOuAi4E4hRJGU8hm/a69G5SZrBh5GDdtmACcCc6SU+4QQ/wF+KYQQQRLeXoEyfvszbuAzRl/vp0x8kP8nPN+1K3/01NefQ1DpZcr9d0opyzwvFCt6qaPmIEcbOM1Y5Peef/48D/zQbzsSmO8/LCmEOBNlzH4spXzIb//fUfm7/i6EeF1KaQohTkAZt/9IKS/zK/sp8Oog638j6uF8kpTSm/RRCHE/Kv3M3XR/eE8EZnamGBFCPIpKX/ITVJofhBBRKKNd7/nuxX7n3+EZVgR4CNV7vBL4ld/9lwEzgF/34TvM8nzu20+ZPufLk1Ku898WQiQCX6Byjl0Q5JR9qAzZmhBGGzjNWOQhumfTLuuy/a8gc24XAY3AmiA9i9dRvYVpqGSMZ3j23+VfSEq5RgghgYAMj/3kIlR26M1B6rEOuFQIESmlbPXb/5h//iwpZYsQ4kvUMGwnJwIpwM1djFvnOW7P524hxCfAJUKI30gpnZ4iVwJOoC+53VIBp5SyYT9lbkBp2ZXDUEY8KJ4e7svAFOA4KWUwI1oNxATRSRNCaAOnGYvs6UM27WAP1plALF2GvLqQ7jk3GzU/F+w6OxmcgZuJ6mHub3FGCmq+rJOcIGWqAX//s2mezy1BynblIVTW7tUogx+LmtN6wy8b8/7oi3/S1z24CTiDFe5St5WoBKGf9VCmc/5T+0mFMNrAaTTBCbZi0kAZlWBDXp3sGOD9enrQBvuNGqgFK7/Yz/W6Gj/XQCq1H14G7kX12tYA5wPRdJ8H64lKwCaEiO9LZua+IoT4DWph0B+klE/up2gS0CSlbBuqe2tGH9rAaTR9Zw8wHfhSStnUS9kcVKSg6cB3XY7NDFK+BvXQ7Up2D/VIBT7sHDYcIjp7m/OA9/ZXUErZLoR4AvipEGIcytAVoxa/9IXOF4FpQLde2kAQQpwH/AE1n/rbXopPZeAvI5qDBB2qS6PpO0+gfjNBl7YLIdL9Nl/zfN7UpcwZBB+e3A3MEEKM9ysbjpqHClaPDHrowXWpR394D6hCrZDMDHJdo8uufwNW4E7gCOBxKWVfe4ofez6PGFhVu9XtCNTc31fAZVLKHocehRAZKBeFT4bi3prRi+7BaTR9REr5khDiMeBGIcQC4A2UQchCLdaYiqfHJaV8VwjxOmrBRxKqZ3MIyrl5BzCny+X/gVrF+b4Q4gEgDLiY4EOlf0f56d0lhDgG+BDlyjAROBblE7dyAN+vRQhxJcoFYocQotNNIBW1AOUv+Aw3UsqdQoj1qEUvJvBoP263GdXLPZmhiWTyGsqt40XgHCEC3iGapJRr/LZP9nx2XWikCTF0D06j6QdSyiuAS1ALSG4B7gMuBZo82/6cjzIKS4B7gKOAs1AP967X3YCaO7KgVl5eDzyFcrjuWtYBnAL8DGV8fg/81XO/HAbhPO3x41uOchq/EmV8rgWKUPN+Xel0l/hIShlsIUtP9zGBB4ETBtHj9CcN1Zu8B+Ub6P/vb13KXgxsklJ2+3/QhBY62LJGc4ARQjxOl0gmByueea/ngQuklM/289w41Hziv6WUtw1H/YLccx4qeokOtjwG0D04jUYzGG5ADdO+0t8TPT5wv0MtVDkg6XJQvoqfaOM2NtBzcBqNpl8IIdJQc31HoeJV3iKlbB/ItaSUDwAPDGH1ervfGb2X0oQK2sBpNJr+MgsV3qsOZZzuGdnqaDTB0XNwGo1GowlJ9BycRqPRaEISbeA0Go1GE5JoA6fRaDSakEQbOI1Go9GEJNrAaTQajSYk0QZOo9FoNCHJ/wdCCZYf7aWR7QAAAABJRU5ErkJggg==\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "%matplotlib inline\n", "raw.plot_psd();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can clearly see some peaks in the EEG at 20 and 30hz. The peaks are certainly strongest in the POz channel" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Epoching\n", "\n", "Next, we will chunk (epoch) the data into segments representing the data 100ms before to 800ms after each stimulus.\n", "\n", "*Note: we will not reject epochs here because the amplitude of the SSVEP at POz is so large it is difficult to separate from eye blinks*" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "197 events found\n", "Event IDs: [1 2]\n", "sample drop %: 2.538071065989844\n" ] } ], "source": [ "events = find_events(raw)\n", "event_id = {'30 Hz': 1, '20 Hz': 2}\n", "\n", "epochs = Epochs(raw, events=events, event_id=event_id, \n", " tmin=-0.5, tmax=4, baseline=None, preload=True,\n", " verbose=False, picks=[0, 1, 2, 3, 4])\n", "print('sample drop %: ', (1 - len(epochs.events)/len(events)) * 100)\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Stimuli-Specific PSD\n", "\n", "Next, we can compare the PSD of epochs specifically during 20hz and 30hz stimulus presentation" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Effective window size : 4.016 (s)\n", "Effective window size : 4.016 (s)\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from mne.time_frequency import psd_welch\n", "import matplotlib.pyplot as plt\n", "import numpy as np\n", "\n", "f, axs = plt.subplots(2, 1, figsize=(10, 10))\n", "psd1, freq1 = psd_welch(epochs['30 Hz'], n_fft=1028, n_per_seg=256 * 3)\n", "psd2, freq2 = psd_welch(epochs['20 Hz'], n_fft=1028, n_per_seg=256 * 3)\n", "psd1 = 10 * np.log10(psd1)\n", "psd2 = 10 * np.log10(psd2)\n", "\n", "psd1_mean = psd1.mean(0)\n", "psd1_std = psd1.mean(0)\n", "\n", "psd2_mean = psd2.mean(0)\n", "psd2_std = psd2.mean(0)\n", "\n", "axs[0].plot(freq1, psd1_mean[[0, 3], :].mean(0), color='b', label='30 Hz')\n", "axs[0].plot(freq2, psd2_mean[[0, 3], :].mean(0), color='r', label='20 Hz')\n", "\n", "axs[1].plot(freq1, psd1_mean[4, :], color='b', label='30 Hz')\n", "axs[1].plot(freq2, psd2_mean[4, :], color='r', label='20 Hz')\n", "\n", "axs[0].set_title('TP9 and TP10')\n", "axs[1].set_title('POz')\n", "axs[0].set_ylabel('Power Spectral Density (dB)')\n", "axs[1].set_ylabel('Power Spectral Density (dB)')\n", "axs[0].set_xlim((2, 50))\n", "axs[1].set_xlim((2, 50))\n", "axs[1].set_xlabel('Frequency (Hz)')\n", "axs[0].legend()\n", "axs[1].legend()\n", "\n", "plt.show();" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "With this visualization we can clearly see distinct peaks at 30hz and 20hz in the PSD, corresponding to the frequency of the visual stimulation. The peaks are much larger at the POz electrode, but still visible at TP9 and TP10" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Spectrogram\n", "We can also look for SSVEPs in the spectrogram, which uses color to represent the power of frequencies in the EEG signal over time" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Applying baseline correction (mode: logratio)\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Applying baseline correction (mode: logratio)\n" ] }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from mne.time_frequency import tfr_morlet\n", "\n", "frequencies = np.logspace(1, 1.75, 60)\n", "tfr, itc = tfr_morlet(epochs['30 Hz'], freqs=frequencies, \n", " n_cycles=15, return_itc=True)\n", "tfr.plot(picks=[4], baseline=(-0.5, -0.1), mode='logratio', \n", " title='POz - 30 Hz stim');\n", "\n", "tfr, itc = tfr_morlet(epochs['20 Hz'], freqs=frequencies, \n", " n_cycles=15, return_itc=True)\n", "tfr.plot(picks=[4], baseline=(-0.5, -0.1), mode='logratio', \n", " title='POz - 20 Hz stim');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Once again we can see clear SSVEPs at 30hz and 20hz" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Decoding\n", "\n", "We can use a filter bank approach on the original 4 Muse electrodes (to see how the headband alone without external electrodes could be used to classify SSVEP):\n", "\n", "1. Apply bandpass filters around both stimulation frequencies\n", "2. Concatenate bandpass-filtered channels\n", "2. Extract epochs (from 1 to 3 s after stimulus onset, to avoid classifying the ERP)\n", "3. Apply common classification pipelines" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Filtering raw data in 6 contiguous segments\n", "Setting up band-pass filter from 25 - 35 Hz\n", "Using filter length: 30732\n", "\n", "IIR filter parameters\n", "---------------------\n", "Butterworth bandpass zero-phase (two-pass forward and reverse) non-causal filter:\n", "- Filter order 16 (effective, after forward-backward)\n", "- Cutoffs at 25.00, 35.00 Hz: -6.02, -6.02 dB\n", "\n", "Filtering raw data in 6 contiguous segments\n", "Setting up band-pass filter from 15 - 25 Hz\n", "Using filter length: 30732\n", "\n", "IIR filter parameters\n", "---------------------\n", "Butterworth bandpass zero-phase (two-pass forward and reverse) non-causal filter:\n", "- Filter order 16 (effective, after forward-backward)\n", "- Cutoffs at 15.00, 25.00 Hz: -6.02, -6.02 dB\n", "\n", "197 events found\n", "Event IDs: [1 2]\n", "197 events found\n", "Event IDs: [1 2]\n" ] } ], "source": [ "# Bandpass filter the raw data\n", "muse_raw = raw.drop_channels(['POz'])\n", "raw_filt_30Hz = muse_raw.copy().filter(25, 35, method='iir')\n", "raw_filt_20Hz = muse_raw.copy().filter(15, 25, method='iir')\n", "raw_filt_30Hz.rename_channels(lambda x: x + '_30Hz')\n", "raw_filt_20Hz.rename_channels(lambda x: x + '_20Hz')\n", "\n", "# Concatenate with the bandpass filtered channels\n", "raw_all = raw_filt_30Hz.add_channels([raw_filt_20Hz], \n", " force_update_info=True)\n", "\n", "# Extract epochs\n", "events = find_events(raw_all)\n", "event_id = {'30 Hz': 1, '20 Hz': 2}\n", "\n", "epochs_all = Epochs(raw_all, events=events, event_id=event_id, tmin=1, \n", " tmax=3, baseline=None, reject={'eeg': 100e-6}, \n", " preload=True, verbose=False,)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "epochs_all.pick_types(eeg=True)\n", "X = epochs_all.get_data() * 1e6\n", "times = epochs.times\n", "y = epochs_all.events[:, -1]" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Decoding the N170\n", "\n", "Next, we will use 4 different machine learning pipelines to classify the SSVEP based on the data we collected. The \n", "\n", "- **CSP + RegLDA** : Common Spatial Patterns + Regularized Linear Discriminat Analysis. This is a very common EEG analysis pipeline.\n", "- **Cov + TS** : Covariance + Tangent space mapping. One of the most reliable Riemannian geometry-based pipelines.\n", "- **Cov + MDM**: Covariance + MDM. A very simple, yet effective (for low channel count), Riemannian geometry classifier.\n", "- **CSP + Cov + TS**: Common Spatial Patterns + Covariance + Tangent spacem mapping. Riemannian pipeline with the standard CSP procedure beforehand\n", "\n", "Evaluation is done through cross-validation, with area-under-the-curve (AUC) as metric (AUC is probably the best metric for binary and unbalanced classification problem)\n", "\n", "*Note: because we're doing machine learning here, the following cell may take a while to complete*" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CSP + RegLDA\n", "Cov + TS\n", "Cov + MDM\n", "CSP + Cov + TS\n" ] } ], "source": [ "import pandas as pd\n", "from sklearn.pipeline import make_pipeline\n", "\n", "from mne.decoding import Vectorizer\n", "\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.preprocessing import StandardScaler\n", "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis as LDA\n", "\n", "from sklearn.model_selection import cross_val_score, StratifiedShuffleSplit\n", "\n", "from pyriemann.estimation import Covariances, ERPCovariances, XdawnCovariances\n", "from pyriemann.spatialfilters import CSP\n", "from pyriemann.tangentspace import TangentSpace\n", "from pyriemann.classification import MDM\n", "\n", "from collections import OrderedDict\n", "\n", "clfs = OrderedDict()\n", "\n", "clfs['CSP + RegLDA'] = make_pipeline(Covariances(), CSP(4), LDA(shrinkage='auto', solver='eigen'))\n", "clfs['Cov + TS'] = make_pipeline(Covariances(), TangentSpace(), LogisticRegression())\n", "clfs['Cov + MDM'] = make_pipeline(Covariances(), MDM())\n", "clfs['CSP + Cov + TS'] = make_pipeline(Covariances(), CSP(4, log=False), TangentSpace(), LogisticRegression())\n", "\n", "# define cross validation \n", "cv = StratifiedShuffleSplit(n_splits=20, test_size=0.25, \n", " random_state=42)\n", "\n", "# run cross validation for each pipeline\n", "auc = []\n", "methods = []\n", "for m in clfs:\n", " print(m)\n", " try:\n", " res = cross_val_score(clfs[m], X, y==2, scoring='roc_auc', \n", " cv=cv, n_jobs=-1)\n", " auc.extend(res)\n", " methods.extend([m]*len(res))\n", " except:\n", " pass\n", " \n", "results = pd.DataFrame(data=auc, columns=['AUC'])\n", "results['Method'] = methods" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import seaborn as sns\n", "fig = plt.figure(figsize=[8,4])\n", "sns.barplot(data=results, x='AUC', y='Method')\n", "plt.xlim(0.4, 1)\n", "sns.despine()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The different classifiers get some impressive accuracy on this dataset, all around .95 AUC. This is impressive considering this pipeline only included data from the temporal electrodes" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Step 6: Share your Data!\n", "\n", "How did your experiment go? If you're excited by your results we'd love to see your data!\n", "\n", "Follow the instructions on our [Contributions](https://github.com/NeuroTechX/eeg-notebooks/blob/master/CONTRIBUTING.md) page to make a pull request with your data and we'll review it to be added to the EEG notebooks project." ] } ], "metadata": { "kernel_info": { "name": "mne" }, "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.9" }, "nteract": { "version": "0.8.4" } }, "nbformat": 4, "nbformat_minor": 4 }