﻿<?xml version="1.0" encoding="UTF-8"?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/"><channel><title>Millisecond Forums » Millisecond Forums » Inquisit 5  » How do I have three items on the trial but 1 of the items is a different color and size?</title><generator>InstantForum 2017-1 Final</generator><description>Millisecond Forums</description><link>https://forums.millisecond.com/</link><webMaster>Millisecond Forums</webMaster><lastBuildDate>Mon, 29 Jun 2026 11:28:04 GMT</lastBuildDate><ttl>20</ttl><item><title>How do I have three items on the trial but 1 of the items is a different color and size?</title><link>https://forums.millisecond.com/Topic30088.aspx</link><description>Hi everyone,&amp;nbsp;&lt;br/&gt;I am trying to create a trial with a stimuli image, a question underneath it, and two response options. The question should be in white color font while the two response options should be in black font inside a white textbox. However, when I run the code all the test items are black font inside a white textbox.&amp;nbsp;&lt;br/&gt;&lt;br/&gt;Could someone please help? &lt;br/&gt;I also cannot get participants to actively click on the textboxes to move fowards as the "validresponse" line does not work.&lt;br/&gt;&lt;br/&gt;Here is my code:&lt;br/&gt;&lt;br/&gt;*****ITEMS &amp;amp; STIMULI *****&lt;br/&gt;&amp;lt;text DetectionQuestion&amp;gt;&lt;br/&gt;/ items = DetectionQuestion&lt;br/&gt;/ position = (50, 70)&lt;br/&gt;/ select = sequence&lt;br/&gt;/ txcolor = (white)&lt;br/&gt;/fontstyle = ("Arial", 3.0%, true, false, false, false, 5, 1)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item DetectionQuestion&amp;gt;&lt;br/&gt;/1 = "Did this statement correct earlier misinformation?"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text NoDetection&amp;gt;&lt;br/&gt;/ items = ("0 - No")&lt;br/&gt;/ position = (25%, 80%)&lt;br/&gt;/ fontstyle = ("Arial", 2%, false, false, false, false, 5, 1)&lt;br/&gt;/ txcolor = (black)&lt;br/&gt;/ txbgcolor = (white)&lt;br/&gt;/ size = (10%, 5%)&lt;br/&gt;/ vjustify = center&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text YesDetection&amp;gt;&lt;br/&gt;/ items = ("1 - Yes")&lt;br/&gt;/ position = (75%, 80%)&lt;br/&gt;/ fontstyle = ("Arial", 2%, false, false, false, false, 5, 1)&lt;br/&gt;/ txcolor = (black)&lt;br/&gt;/ txbgcolor = (white)&lt;br/&gt;/ size = (10%, 5%)&lt;br/&gt;/ vjustify = center&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture statements_block3&amp;gt;&lt;br/&gt;/ items = ("Gas_2018_C.png","Gas_2018_C.png", "Cali_Fires_C.png", "Amazon_Rainforest_C.png", "Clinton_Nkorea_C.png", "Cinderella_Castle_C.png", &lt;br/&gt;"Library_AmericanFlag_C.png", "Military_Pay_C.png", "Mexican_Border_Crossings_C.png", "US_Trading_Partner_C.png", "Test_American_Cars_C.png",&lt;br/&gt;"Tax_Pres_Law_C.png", "Pres_Vacation_C.png", "Immigration_Boy_Cage_C.png", "Global_Warming_Antarctica_C.png", "Murder_Year_C.png", "Bernie_Tax_Income_C.png",&lt;br/&gt;"Biden_StudentDebt_C.png", "Chess_Players_C.png", "Liberian_Women_C.png", "SKorea_Population_C.png", "Missing_People_C.png", "Bloomberg_Campaign_Money_C.png",&lt;br/&gt;"Alabama_Senate_C.png", "Black_Homeownership_C.png", "Rural_Hospitals_C.png", "Race_Starbucks_C.png", "Brooms_Standing_C.png", "SwimmingPool_Deaths_C.png",&lt;br/&gt;"Voter_Turnout_C.png", "CoronaBeer_COVID_C.png", "Tax_Allocation_C.png", "Rep_Control_C.png", "Cali_Statelaw_C.png", "Soccer_Revenue_Gap_C.png", "Pope_GunControl_C.png",&lt;br/&gt;"Coffee_C.png", "Federal_State_Dollars_C.png", "UT_Athletes_Ipad_C.png", "Obama_Website_C.png", "Trump_Signed_Legislation_C.png", "GunControl_Warrant_C.png",&lt;br/&gt;"Abortion_Bieber_C.png", "Veteran_Suicide_C.png", "Vaccines_Autism_C.png", "Marriage_License_Benefits_C.png")&lt;br/&gt; / size = (60%, 60%)&lt;br/&gt; / position = (50, 32)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;*****Instructions*****&lt;br/&gt;&amp;lt;item Instructions&amp;gt;&lt;br/&gt;/  1 = "1 Welcomeb.jpg"&lt;br/&gt;/  2 = "2 BackgroundInfob.jpg"&lt;br/&gt;/  3 = "3 FamInstr1b.jpg"&lt;br/&gt;/  4 = "4 FamInstr2b.jpg"&lt;br/&gt;/  5 = "5 BeliefInstr1b.jpg"&lt;br/&gt;/  6 = "6 BeliefInstr2b.jpg"&lt;br/&gt;/  7 = "7 CorrectionInstr1b.jpg"&lt;br/&gt;/  8 = "8 CorrectionInstr2b.jpg"&lt;br/&gt;/  9 = "9 CorrectionInstr3b.jpg"&lt;br/&gt;/  10 = "10 CorrectionInstr4b.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture InstructionsDisplay&amp;gt;&lt;br/&gt;/ items = Instructions&lt;br/&gt;/ select = sequence&lt;br/&gt;/ size = (100%, 100%)&lt;br/&gt;/ position = (50%, 50%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Instructions&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = InstructionsDisplay]&lt;br/&gt;/ validresponse = (205)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;*****TRIAL*****&lt;br/&gt;&amp;lt;trial makeDetections&amp;gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ stimulusframes = [1 = DetectionQuestion, NoDetection, YesDetection, statements_block2]&lt;br/&gt;/ trialduration = 8000&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;*****BLOCK*****&lt;br/&gt;&amp;lt;block Correction&amp;gt;&lt;br/&gt;/ onblockbegin = [values.trialCount = 0; values.makeDetections = 1; values.instructnum = 7]&lt;br/&gt;/ trials = [1-4 = Instructions; 5-50 = makeDetections]&lt;br/&gt;/ onblockend = [values.missingRespCount = 0]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;</description><pubDate>Tue, 10 Nov 2020 19:05:54 GMT</pubDate><dc:creator>KempInquisit</dc:creator></item><item><title>RE: How do I have three items on the trial but 1 of the items is a different color and size?</title><link>https://forums.millisecond.com/Topic30093.aspx</link><description>&lt;blockquote data-id="30090" class="if-quote-wrapper" unselectable="on" data-guid="1605035130536" id="if_insertedNode_1605035129828" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="30090" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="30090" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="30090" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;KempInquisit - 11/10/2020&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-30090"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="30089" class="if-quote-wrapper" unselectable="on" data-guid="1605035130536" id="if_insertedNode_1605030785381" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="30089" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="30089" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="30089" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 11/10/2020&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-30089"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="30088" class="if-quote-wrapper" unselectable="on" data-guid="1605035130536" id="if_insertedNode_1605029672281" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="30088" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="30088" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="30088" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;KempInquisit - 11/10/2020&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-30088"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;Hi everyone,&amp;nbsp;&lt;br/&gt;I am trying to create a trial with a stimuli image, a question underneath it, and two response options. The question should be in white color font while the two response options should be in black font inside a white textbox. However, when I run the code all the test items are black font inside a white textbox.&amp;nbsp;&lt;br/&gt;&lt;br/&gt;Could someone please help? &lt;br/&gt;I also cannot get participants to actively click on the textboxes to move fowards as the "validresponse" line does not work.&lt;br/&gt;&lt;br/&gt;Here is my code:&lt;br/&gt;&lt;br/&gt;*****ITEMS &amp;amp; STIMULI *****&lt;br/&gt;&amp;lt;text DetectionQuestion&amp;gt;&lt;br/&gt;/ items = DetectionQuestion&lt;br/&gt;/ position = (50, 70)&lt;br/&gt;/ select = sequence&lt;br/&gt;/ txcolor = (white)&lt;br/&gt;/fontstyle = ("Arial", 3.0%, true, false, false, false, 5, 1)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item DetectionQuestion&amp;gt;&lt;br/&gt;/1 = "Did this statement correct earlier misinformation?"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text NoDetection&amp;gt;&lt;br/&gt;/ items = ("0 - No")&lt;br/&gt;/ position = (25%, 80%)&lt;br/&gt;/ fontstyle = ("Arial", 2%, false, false, false, false, 5, 1)&lt;br/&gt;/ txcolor = (black)&lt;br/&gt;/ txbgcolor = (white)&lt;br/&gt;/ size = (10%, 5%)&lt;br/&gt;/ vjustify = center&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text YesDetection&amp;gt;&lt;br/&gt;/ items = ("1 - Yes")&lt;br/&gt;/ position = (75%, 80%)&lt;br/&gt;/ fontstyle = ("Arial", 2%, false, false, false, false, 5, 1)&lt;br/&gt;/ txcolor = (black)&lt;br/&gt;/ txbgcolor = (white)&lt;br/&gt;/ size = (10%, 5%)&lt;br/&gt;/ vjustify = center&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture statements_block3&amp;gt;&lt;br/&gt;/ items = ("Gas_2018_C.png","Gas_2018_C.png", "Cali_Fires_C.png", "Amazon_Rainforest_C.png", "Clinton_Nkorea_C.png", "Cinderella_Castle_C.png", &lt;br/&gt;"Library_AmericanFlag_C.png", "Military_Pay_C.png", "Mexican_Border_Crossings_C.png", "US_Trading_Partner_C.png", "Test_American_Cars_C.png",&lt;br/&gt;"Tax_Pres_Law_C.png", "Pres_Vacation_C.png", "Immigration_Boy_Cage_C.png", "Global_Warming_Antarctica_C.png", "Murder_Year_C.png", "Bernie_Tax_Income_C.png",&lt;br/&gt;"Biden_StudentDebt_C.png", "Chess_Players_C.png", "Liberian_Women_C.png", "SKorea_Population_C.png", "Missing_People_C.png", "Bloomberg_Campaign_Money_C.png",&lt;br/&gt;"Alabama_Senate_C.png", "Black_Homeownership_C.png", "Rural_Hospitals_C.png", "Race_Starbucks_C.png", "Brooms_Standing_C.png", "SwimmingPool_Deaths_C.png",&lt;br/&gt;"Voter_Turnout_C.png", "CoronaBeer_COVID_C.png", "Tax_Allocation_C.png", "Rep_Control_C.png", "Cali_Statelaw_C.png", "Soccer_Revenue_Gap_C.png", "Pope_GunControl_C.png",&lt;br/&gt;"Coffee_C.png", "Federal_State_Dollars_C.png", "UT_Athletes_Ipad_C.png", "Obama_Website_C.png", "Trump_Signed_Legislation_C.png", "GunControl_Warrant_C.png",&lt;br/&gt;"Abortion_Bieber_C.png", "Veteran_Suicide_C.png", "Vaccines_Autism_C.png", "Marriage_License_Benefits_C.png")&lt;br/&gt; / size = (60%, 60%)&lt;br/&gt; / position = (50, 32)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;*****Instructions*****&lt;br/&gt;&amp;lt;item Instructions&amp;gt;&lt;br/&gt;/  1 = "1 Welcomeb.jpg"&lt;br/&gt;/  2 = "2 BackgroundInfob.jpg"&lt;br/&gt;/  3 = "3 FamInstr1b.jpg"&lt;br/&gt;/  4 = "4 FamInstr2b.jpg"&lt;br/&gt;/  5 = "5 BeliefInstr1b.jpg"&lt;br/&gt;/  6 = "6 BeliefInstr2b.jpg"&lt;br/&gt;/  7 = "7 CorrectionInstr1b.jpg"&lt;br/&gt;/  8 = "8 CorrectionInstr2b.jpg"&lt;br/&gt;/  9 = "9 CorrectionInstr3b.jpg"&lt;br/&gt;/  10 = "10 CorrectionInstr4b.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture InstructionsDisplay&amp;gt;&lt;br/&gt;/ items = Instructions&lt;br/&gt;/ select = sequence&lt;br/&gt;/ size = (100%, 100%)&lt;br/&gt;/ position = (50%, 50%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Instructions&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = InstructionsDisplay]&lt;br/&gt;/ validresponse = (205)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;*****TRIAL*****&lt;br/&gt;&amp;lt;trial makeDetections&amp;gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ stimulusframes = [1 = DetectionQuestion, NoDetection, YesDetection, statements_block2]&lt;br/&gt;/ trialduration = 8000&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;*****BLOCK*****&lt;br/&gt;&amp;lt;block Correction&amp;gt;&lt;br/&gt;/ onblockbegin = [values.trialCount = 0; values.makeDetections = 1; values.instructnum = 7]&lt;br/&gt;/ trials = [1-4 = Instructions; 5-50 = makeDetections]&lt;br/&gt;/ onblockend = [values.missingRespCount = 0]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="30088"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;&amp;gt; The question should be in white color font while the two response options should be in black font inside a white textbox. However, when I run the code all the test items are black font inside a white textbox. &lt;br/&gt;&lt;br/&gt;The default screen color is white as is the default txbgcolor, so:&lt;br/&gt;(1) You won't see the white font &amp;lt;text DetectionQuestion&amp;gt; at all against the white background.&lt;br/&gt;(2) You won't see any "white box" around the two response options against the white background.&lt;br/&gt;&lt;br/&gt;Set your /screencolor to black per &amp;lt;defaults&amp;gt;. Set /txbgcolor = black for the detection question &amp;lt;text&amp;gt; element.&lt;br/&gt;&lt;br/&gt;&lt;img 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4fFSvu/9fbbzl3jJo2RdgUAwIV6/03kkRcgRD0HAQBeOnxwr9O8z5cvb8C7DRvc36nb2FFDA97N39atWmo5c+b0eH0OhoeTK5ctcu777B+etZ+uXVFXBgDgkdT7byKPvAAh6jkIAPDSnTu3nWf+pQvnAtpt7sxpTr26dm4f0F7+Nn3qBI/X5aiCUbZt03r1JdxTrZrbrxdny5bNhsT2VdcFAOCR1PtvIo+8ACHqOQgA8IH/ef11p5m/ffMPAe21fu0Kp151PqkZ0F7+1LtnV4/X5EqVKtjpk8fUl3CfzSlrs3QNwdYfAIBfU++/iTzyAoSo5yAAwAcaN6rvNPPnzpwW0F4H9+106vXXN/8W0F7+cPnieatf72OP1+PWLZva3bt31JfxUK6vr2zZslm3rzqo6wIAkCn1/pvIIy9AiHoOAgB8YOSwWKeZH+i/O3b54nmnXjlz5rRffvkloN18aUvKOnupaFGP1+LhQwaoL+GR9u/5MUvXk56epq4MAMBDqfffRB55AULUcxAA4AMrliY6zfx6n9YOeLey5co6dTt8cG/Au/lC/JRxXq3DC+fPVF+Ck66d2ztfU8vmjdV1AQB4KPX+m8gjL0CIeg4CAHxg3+4dTjP/9VKlAt6tQoVop27LFs8PeDdvpKXdsnZtmnu8/kZFRdnWjcnqy3B2+uSxLF3fvt071JUBAHiAev9N5JEXIEQ9BwEAPuD6K6C5cj0R8G49u3d26jagb8+Ad/PUvt077K233/Z47a1QIdpOHj+ivowsGzywj/M1Nm/WSF0XAIAHqPffRB55AULUcxAA4CN5ns7jNPcvnD8T0F6J8xKcelWrViWgvTy1cP5Mr9bdls0b2+3b6erL8Mi1q5ftmd8/43ytu1O3qisDAHAf9f6byCMvQIh6DgIAfMT1J7QC/XDE9Q/9P/P7ZwLayxO9e3b1as0dNri/+hK8NmXCN87X27RJA3VdAADuo95/E3nkBQhRz0EAgI983uBTp7m/YmliQHvduXPbeU06cexQQLu5OnH8sH3wQWWv1tvEeQnqy/CJ9PQ0K1CggPN17/pxi7oyAAD3qPffRB55AULUcxAA4CN9Y752mvuTx48KeDfXT05dtXxxwLs9zpoVSVn6dczf5qWiRW1Lyjr1ZfhU3KQxztffuGF9dV0AAO5R77+JPPIChKjnIADARxKmTXKa+92+6hDwbl06tXPqNnhgn4B3e5SRw2K9WmM/b/CpXb54Xn0ZPnfnzm2LKhjlfB9St29UVwYAwMx4EEf0BQhRz0EAgI8kr1nuNPdr1/ow4N3mJMQFbbeHuXThnDX4rI5X6+uo4YPUl+FX8VPGOd+Lhg3qqusCAGBmPIgj+gKEqOcgAMBHDu3f5TT3X/3znwPebXfqVqduz/3xuYB3+60tKeusyEtFPF5Xn/3Ds7ZmRZL6Mvzu7t07VqhwIef7smPrBnVlAADk+28ij7wAIeo5CADwkZ+uXXGe/RkZGQHtlnbrplOv3LlzB7TXb2Xlp7welqpV37cTxw9LryGQZsRNdL439et9rK4LAIB8/03kkRcgRD0HAQA+9ELeF5xm/9kzJwPerXTp0k7dDu3fFfBuaWm3rG3rL7xaT/v06hbw3moZGRlZ+unBbZvWqysDACKcev9N5JEXIEQ9BwEAPlTO8dNJFX88/7ukBY/tVaxYsYD32rd7h7319tteraWLvp0V8N7BYtb0Kc73qd6ntdV1AQARTr3/JvLICxCinoMAAB9q2qSB0+xfumhewLvdunnjsb0GDegd0E6J8xK8WkNLly5t+/f8GNDOweaXX36xoi+/7HzPtqSsU1cGAEQw9f6byCMvQIh6DgIAfCi2f4zT7B/3zTBJv/Gjh2faqWy5svavA3sC1qV3z65erZ/t27aw9PS0gPUNZq6fipstWzar80lNdV0AQART77+JPPIChKjnIADAh1wfiHRs30rWcdum9Q/8BFUg/77aiWOHrEqVSl6tndOnTghY31BRvHhx5/u3OWWtui4AIEKp999EHnkBQtRzEADgQxuSv3ea/dWqVZH2TEu7ZZcvXbiXQFmzIsnyPJ3H4zWz6Msv84EDmZg7c5rzfaxd60N1XQBAhFLvv4k88gKEqOcgAMCHjh054DT7i778srpqwI0YOtCr9bJhg7p2+eJ59WUEtVf//Gfn+7nxh9XqugCACKTefxN55AUIUc9BAIAPuXwgwn9y9+4ddd2AuHThnNWv97FXa+XoEYPVlxESFsyZ4XxPa9aopq4LAIhA6v03kUdegBD1HAQA+FhUVJTT/D914qi6qt9tTllrRV4q4vEa+dwfn7N1q5aqLyOkvFaihPP93ZD8vbouACDCqPffRB55AULUcxAA4GMVK1Zwmv/h/rfO4iaN8Wp9rFatip08fkR9GSEncV5Clu4xAACBpN5/E3nkBQhRz0EAgI+1atHEaf4v+naWuqpfnD1z0hp8VsertbFf7+7qywhpr5cq5Xyv169doa4LAIgg6v03kUdegBD1HAQA+Niwwf2d5v/IYbHqqj63YmmiPffH57xaFxcvmK2+jJC36NtZzve7cuWK6roAgAii3n8TeeQFCFHPQQCAj7n+amCbVs3UVX3mzp3b1qNbJ6/WwzJlytiBvanqSwkbf33zb873fvV3S9R1AQARQr3/JvLICxCinoMAAB/bkrLOaf5XrvR3dVWf+HFbSpYe+jwsHdu3stu309WXElaSFs51vv/lypVV1wUARAj1/pvIIy9AiHoOAgB87MTxw07zPyoqSl3VaxPGjPB6HZwRN1F9GWHrndLvOH8fkhbOVdcFAEQA9f6byCMvQIh6DgIAfCw9Pc3+8tprTmvA5Yvn1XU9cvL4EavzSU2v1r9ixYqF/SfHqi1bPN/5+/F6qVLqugCACKDefxN55AUIUc9BAIAfvFaihNMasGPrBnXVLEtaONeefPJJr9a+Rp/XsyuXL6ovJSK8F/2u8/dl/uzp6roAgDCn3n8TeeQFCFHPQQCAHzRuWN9pDZg7c5q6qrNbN29Yl07tvF73UrdvVF9KRFmzIsn5e/NKsVfUdQEAYU69/ybyyAsQop6DAAA/GDF0oNMaENOji7qqky0p65x/yi+zlChZ0rZuTFZfSkT64IPKzt8n/mYfAMCf1PtvIo+8ACHqOQgA8IMVSxOd1oAqVSqpqz7W6BGDvV7runZub2m3bqovJWJtSP7e+XsVVTCKT7AFAPiNev9N5JEXIEQ9BwEAfnBo/66QXweOHTlgNf5R1as1Lnfu3HwaZ5D45OMazt+3iWNHqusCAMKUev9N5JEXIEQ9BwEAfnD37h37XfbfOa0Dly6cU9d9QOK8BOf+maVunVp26sRR9aXg/9q2ab3z9+7ZPzxr13+6qq4MAAhD6v03kUdegBD1HAQA+InL3+V6991y6pr3uf7TVWvXprnXaxs/URWcGjao6/w9HDksVl0XABCG1PtvIo+8ACHqOQgA8JM9O7c9dg2YPH6UuuY9KetX2SvFXvFqTXvzrbf4VNQgtjt1q/P3Mnv27Oq6AIAwpN5/E3nkBQhRz0EAgB/VrvVhpvP/xSIv2onjh9UVzcxs2OD+Xq9nPbt3trt376gvBY/Rsnlj5+8pPxUHAPA19f6byCMvQIh6DgIA/GzsqKEPzP6WzRvbrZs31NXsXwf2WJUqlbxax57/0/O2Ymmi+lLg6OC+nc7f2zxP5wmK1ykAIHyo999EHnkBQtRzEAAQAFs3JtvmlLX3EgzmJMR5vYZ93uBTO3vmpPpSkEVfdmjt/D2eMuEbdV0AQBhR77+JPPIChKjnIAAgwly+dCFLv56YWaZNHqu+FHjo+NGDzt/nqIJR9u9/31VXBgCECfX+m8gjL0CIeg4CACJI8prlVrhwYa/WrXLlytru1K3qS4GXun3Vwfl7PnvGVHVdAECYUO+/iTzyAoSo5yAAIELE9o/xes3q17u7ZWRkqC8FPnDk0D7n7/t/v/qqui4AIEyo999EHnkBQtRzEAAQ5vbt3mHly0d7tVYVKFDA1qxIUl8KfKxNq2bOr4FF385S1wUAhAH1/pvIIy9AiHoOAgDCWPyUcV6vU02bNLCLF86qLwV+sHfXdufXwTul31HXBQCEAfX+m8gjL0CIeg4CAMLQyeNHrN6ntb1eo2bGT1ZfCvys0ef1nF8PK5ctUtcFAIQ49f6byCMvQIh6DgIAwkzivATLmTOnV2tThQrRdmBvqvpSEADbN//g/LqoWLGCui4AIMSp999EHnkBQtRzEAAQJi5dOGctmzf2el2K7R+jvhQEWO1aHzq/Pn5Yt1JdFwAQwtT7byKPvAAh6jkIAAgDK5ctsvz583u1Hr1Y5EVbv3aF+lIgsCH5e+fXSa2a1dV1AQAhTL3/JvLICxCinoMAgBB26+YN6/ZVB6/XolYtmtjVK5fUlwOhypX+7vx62bZpvbouACBEqfffRB55AULUcxAAEKJS1q+y/371Va/Xobkzp6kvBUFg9XdLnF8zbVo1U9cFAIQo9f6byCMvQIh6DgIAQlBs/xiv158PPqhshw/uVV8Kgkjp0qWdXjt5ns5jGRkZ6roAgBCk3n8TeeQFCFHPQQBACEndvtHKlivr9dozclis+lIQhJYkznF+DW1I/l5dFwAQgtT7byKPvAAh6jkIAAgR474Z5vWa89c3/8bf98Ij/eW115xeS927fqmuCgAIQer9N5FHXoAQ9RwEAAS5fx3YY9WqVfF6vekb87XdvXtHfTkIckMH9XN6PRUsWFBdFQAQgtT7byKPvAAh6jkIAAhiCdMmeb3OvFS0qCWvWa6+FISI3albnV9bqds3qusCAEKMev9N5JEXIEQ9BwEAQej0yWPW4LM6Xq8xHdu3sus/XVVfDkJMkZeKOL2+YvvHqKsCAEKMev9N5JEXIEQ9BwEAQWbRt7Msd+7cXq0tz/3xOVu6aJ76UhCiYnp0cXqddenUTl0VABBi1PtvIo+8ACHqOQgACBKXL12wNq2aeb2uNG5U386dPaW+HISwzSlrnV5rL+R9QV0VABBi1PtvIo+8ACHqOQgACAJrViRZwYIFvV5T5iTEqS8FYeDOndtOr7cnn3xSXRUAEGLU+28ij7wAIeo5CAAQSk9Ps57dO3u9ltSu9aEdO3JAfTkII7/L/jun115GRoa6KgAghKj330QeeQFC1HMQACCyOWWtvVaihNfryOTxo9SXgjCU5+k8Tq+/9PQ0dVUAQAhR77+JPPIChKjnIABAYPDAPl6vH+XLR9uendvUl4IwlT9/fqfXIZ/KCwDICvX+m8gjL0CIeg4CAAJod+pWey/6Xa/XjqGD+qkvBWGuyEtFnF6Lly+eV1cFAIQQ9f6byCMvQIh6DgIAAmTCmBFerxn/8/rrtiVlnfpSEAFcf2367JmT6qoAgBCi3n8TeeQFCFHPQQCAn504dshq1azu9XoR06OL3b6drr4cRIi33n7b6XV58vgRdVUAQAhR77+JPPIChKjnIADAjxZ9O8ty5Mjh1TpRqHAhW7vyn+pLQYR5991yTq/Po4f3q6sCAEKIev9N5JEXIEQ9BwEAfnDzxnX7skNrr9eIdm2a29Url9SXgwhUqVIFp9fowX071VUBACFEvf8m8sgLEKKegwAAH9ucstZe/fOfvVob8jydx5YkzlFfCiJY9epVnF6rfHIvACAr1PtvIo+8ACHqOQgA8KFRwwd5vS40bFDXzp4+ob4URLhPPq7h9HpN3b5RXRUAEELU+28ij7wAIeo5CADwgWNHDliNf1T1ek2YNX2K+lIAMzP7vMGnTq9ZPsUXAJAV6v03kUdegBD1HAQAeClxXoL9LvvvvFoLqlevYocP7lVfCnBP0yYNnF67G5K/V1cFAIQQ9f6byCMvQIh6DgIAPHT9p6vWvm0Lr9eB8aOHqy8FeECbVs2cXr/rVi1VVwUAhBD1/pvIIy9AiHoOAgA8sGnDGitevLhX879MmTK268ct6ksBHsr1U39XLlukrgoACCHq/TeRR16AEPUcBIoliocAACAASURBVABkUcK0SfZKsVe8mv29e3a1jIwM9aUAmZo2eazTa3nksFh1VQBACFHvv4k88gKEqOcgACALYvvHeDXz8+bLa6uWL1ZfBvBYcxLinF7TDRvUVVcFAIQQ9f6byCMvQIh6DgIAHNy+nW7NmzXyat43+ryenT93Wn0pgJMdWzc4va6LFSumrgoACCHq/TeRR16AEPUcBAA8xumTx6xixQpezfr4KePUlwFkyZXLF51f3z9du6KuCwAIEer9N5FHXoAQ9RwEADxC6vaNVrhwYY9nfLlyZW3Pzm3qywA8UuSlIk6v8507NqurAgBChHr/TeSRFyBEPQcBAJn4LmmBV/O9b8zX9ssvv6gvA/BY/bofOb3W582KV1cFAIQI9f6byCMvQIh6DgIAHmLqxNEez/X8+fPbmhVJ6ksAvDZ0UD+n13yvHl+pqwIAQoR6/03kkRcgRD0HAQC/EdOji8czvXGj+nbh/Bn1JQA+sWJpotPrvnz5aHVVAECIUO+/iTzyAoSo5yAA4P+6cf2afd7gU4/n+aABvdWXAPjU4YN7nV//KetXqesCAEKAev9N5JEXIEQ9BwEA/1eZMmU8nuWzpk9R1wd87u7dO87/BipVqqCuCwAIAer9N5FHXoAQ9RwEAJhZhQrRHs3wnDlzWvLqZer6gN+M+2aY87+H+Cnj1HUBAEFOvf8m8sgLEKKegwAQ8Y4dOeDR/P7La6/Z/j0/qusDfrVmRZLzv4nSpUvb1SuX1JUBAEFMvf8m8sgLEKKegwAQ8caPHp7l2V2zRjW7dOGcujoQEH9982/O/zamTR6rrgsACGLq/TeRR16AEPUcBICI17BB3SzN7Y7tW6krAwF1YG+q87+PEiVLqusCAIKYev9N5JEXIEQ9BwEg4i1bPN95Zo8cFquuC0hUrfq+87+T5DXL1XUBAEFKvf8m8sgLEKKegwAQ8W7dvOE0rxPnJairAjK7U7c6v7epX+9jdV0AQJBS77+JPPIChKjnIABEhIP7dtrBfTstfso4mzZ5rMVNGmNTJ462qRNH25QJ31j9eh9nOqdz585t7do0tzEjh9joEYNt9IjBNmr4IBs5LNZGDB1ow4cMsOFDBtiwwf1t6KB+NiS2rw0e2McGD+xjgwb0ttj+MfcysF8vG9C3p/Xv08P69e5u/Xp3t74xX1ufXt2sd8+uFtOji8X06GK9enxlPbt3th7dOlmPbp2se9cv7esuHa3bVx2sa+f21rVze+vSqZ117tjGunRqZ92+6mDdu35pPbt3tt49u1rfmK+tf58eNrBfLxs0oLcNie1rwwb3txFDB9roEYNt7KihNn70cJswZoRNmfCNxU0aY/FTxtn0qRNsZvxkmz1jqs1JiLN5s+ItcV6CLZw/0xYvmG1JC+fassXz7bukBbZiaaKtWr7Y1qxIsnWrllrymuW2fu0K25D8vW38YbVtTllrW1LW2bZN623H1g2Wun2j7dyx2XanbrW9u7bbvt077MDeVDu0f5cdPrjXjhzaZ8eOHLATxw7ZqRNH7cL5M3bt6mVLS7tlGRkZ6pcQzKzFF42c398cPbxfXRcAEITU+28ij7wAIeo5CABh7drVy9a4YX35rCfeJ3fu3JYvX157qWhRK1GypJUtV9YqV/q71a71oX3e4FNr2byxfdmhtcX06GKx/WNs9IjBNmXCNzYzfrIlzkuwC+fP2Ibk723Xj1vs2JEDduH8Gbt184b6JRpStm5Mdv5+xfaPUdcFAAQh9fsJIo+8ACHqOQgAYWtzylrLly+vfM6T4E727NktKirKSpQsaRUqRFudT2paqxZNrGf3zjZscH+LmzTGEucl2JoVSbYlZZ3t273DTh4/YpcvXbDbt9PVL/OAK1eurNN9LViwoLoqACAIqdd9Io+8ACHqOQgAYevrLh3lM56Ef579w7NWomRJq1r1fWverJH1jfnaJo4daYu+nWUbkr+3/Xt+tHNnT1l6epr6n4RPzJsV73xv+JViAMBvqddtIo+8ACHqOQgAYeuFvC/IZzwhv84LeV+wUm+8YTX+UdVat2xqA/r2tKkTR1vSwrm2acMaO7R/l104f8bu3r2j/ueTqfT0NMvzdB6n67104Zy6LgAgyKjXYiKPvAAh6jkIAGHpx20p8vlOiDcp8lIRq1KlkrVt/YWNGDrQFs6faVtS1tmJ44flP13Xq8dXj+1fuXJFaUcAQHBSr69EHnkBQtRzEADC1jO/f0Y+4wnxVwoVLmSVKlWwVi2a2LDB/W3BnBm2acMaO3bkgN8/hOLnn39+bL8ZcRP92gEAEJrU6yeRR16AEPUcBICw1bljG/mMJ0SVqKgoK18+2lp80cgGD+xjc2dOs80pa+3c2VM++fe1avli+1//K9dDz92lUzv+PhwA4KHU6yORR16AEPUcBICwlbJ+leXK9YR8zhMSbHn+T89b5coV7esuHW1m/GTbkrLOzp877fxva++u7VbqjTfuO2aOHDnshbwvWNLCuX78Vw0ACHXqNZDIIy9AiHoOAkBYO3/utH1U+0P5rCckFPJC3hesatX3LaZHF5s/e7rt3LHZrl29fN+/qelTJzzyGHGTxoj+tQMAQoF6rSPyyAsQop6DABARdmzdYDu2brBmTT+37NmzP3QeRxWMsm5fdbCJY0fa5PGjbMqEb2zqxNE2deJoi5s0xqZNHmvxU8bdy/SpE2xG3ERLmDbJEqZNspnxk23W9Ck2e8ZUm5MQdy9zZ06zebPibd6seJs/e7otmDPDEucl3MvC+TNt0bezbPGC2bYkcY4tSZxjSQvnWtLCubZ00TxbumieLVs835Yv+da+S1pgK5Ym3svKZYtsxdJE+y5pgS1bPN+SFs61xQtm28L5My1xXoLNmxVvcxLibPaMqTYzfrJNnzrB4qeMs7hJY2zKhG9swpgRNn70cBs7aqiNHjHYRgwdaMMG97chsX1t0IDeNrBfL+vfp4f1jfnaevfsaj27d7buXb+0bl91sC6d2lnH9q2sfdsW1rb1F9a6ZVNr8UUj+6JpQ2vS+DNr3LC+fd7gU6tf72Or92ltq/NJTatd60OrWaOaVa9exapWfd8qV65olSpVsAoVoi06+j0rV66slSlTxv765t+sWLFiFlUwyp75/TP2u+y/k6/XkZyXiha1+nU/sv59ethfXnvtkf/tayVKqP+5AwCCmHpNI/LICxCinoMAEFGKFy/+yJnctEkDdUVk4vbtdLv+01W7dOGcnTl13I4dOWAH9qZa6vaNtjllrSWvWW4rlibaom9n2ZyEOIubNMbGjhpqgwf2sT69ulnH9q2s0ef1rGrV9+2d0u/YS0WLWp6n88jfB4Rjjh7er365AACClHqNIvLICxCinoMAEDEO7d/lNJd//vlndVUE0N27d+zqlUt26sRRO7A31bZtWm9rV/7TFs6fafFTxtmIoQOtV4+vrHXLplbv09pWsWIF+5/XX7eoglGWI0cO+fuIYMzoEYPV31YAQJBSr1FEHnkBQtRzEAAixshhsU5zedG3s9RVEUKuXrlkx48etB1bN9iq5Ytt1vQpNmxwf+vcsY3V+7S2lStX1goVLiR/vxHIxPToov62AACClHqNIvLICxCinoMAEDGGDxngNJfHjx6uroowlJGRYZcvnrcjh/bZtk3r7bukBTZ96gQbNKC3tW/bwj6q/aG9U/odK1CggPy9ibdp2byx+nYDAIKUeo0i8sgLEKKegwAQMeYkxDnN5Z7dO6urIsKl3bppJ44dss0pay1xXoINHzLA2rRqZpUrV7QXi7wof+/yuNSu9aH6FgIAgpR6jSLyyAsQop6DABAx1q1a6jSXG3xWR10VeKT09DQ7efyIbdu03hYvmG2jhg+y9m1bWNWq71vRl1+Wv7cpW66s+hYBAIKUeo0i8sgLEKKegwAQMfbu2u40l0u98Ya6KuCVu3fv2OmTx2zH1g2WtHCujftmmLX4opG9+dZbAXlv81LRoupbAAAIUur9N5FHXoAQ9RwEgIhx+eJ5p7mcM2dOdVXAb+7evWNHD++3NSuSbOyooda8WSP765t/8+l7m9y5c6svEwAQpNT7byKPvAAh6jkIABHlmd8/4zSbMzIy1FWBgLpz57b968Ae+y5pgQ0d1M/q1/vYq19zTbt1U31JAIAgpN5/E3nkBQhRz0EAiCglSpZ0ms1nT59QVwWCwk/Xrlha2i1bsTTR9uzcZi/kfcHp39D5c6fV1QEAQUi9/ybyyAsQop6DABBR3in9jtNsPnH8sLoqEJTKlCnj9G/o8MG96qoAgCCk3n8TeeQFCFHPQQCIKO9Fv+s0m48c2qeuCgSlWjWrO/0b2pKyTl0VABCE1PtvIo+8ACHqOQgAEaVy5YpOs/nA3lR1VUSAX375xe7evWO3bt6wa1cv26UL5+zyxfOWnp6mrpapNq2aOf0bSlo4V10VABCE1PtvIo+8ACHqOQgAEaXGP6o6zebdqVvVVRECMjIy7KdrV+zMqeN2cN9O27Zpva3+bonNnjHVRgwdaF06tbP69T62d98tZ3957TV7qWhRiyoYZc//6Xl78sknH/kazJXrCStYsKCVeuMNq1zp71a/7kfWplUzi+nRxUYMHWi7U7fahuTv7cTxwwH9cJHBA/s4/RuaOHZkwDoBAEKHev9N5JEXIEQ9BwEgotStU8tpNu/YukFdFUEq7dZNa9WiidX5pKb8PcSvU6tm9YC8bmfGT3bqE9Oji9+7AABCj3q9JPLICxCinoMAEFEaNqjrNJs3p6xVV0UQ2rox2flTQ1UZNXyQjRwWey9zEuJ8eg/WrEhy6tHo83o+PS8AIDyo10kij7wAIeo5CAARpXmzRk6z+Yd1K9VVEWQ2p6yVv2fwNC2bN7ZbN2/45D7sTt3qdM7o6Pd8cj4AQHhRr4lEHnkBQtRzEAAiStvWXzjN5rUr/6muiiBy7MgB+fsFb/NikRd9ci/Onj7hdL5ChQv55HwAgPCiXg+JPPIChKjnIABElC6d2jnN5hVLE6U9b1y/ZqdOHDUzs9TtG2375h9sc8pa25D8vSWvWW5rViTZymWLbNni+bYkcY4tXjDbkhbOtXNnT9m5s6ek3cPR+NHD5e8XfJGdOzZ7fS9u3053Pt/du3d8cPcBAOFEvRYSeeQFCFHPQQCIKD27d3aazUkL5/qtw+WL5+3MqeM2f/Z0GztqqPXs3tkaN6xvlSpVsOLFi1vu3Lm9XlumTPjGb/0j0Tul35G/X/BF+vfp4ZP7ERUV5XQ+HgoDAH5LvRYSeeQFCFHPQQCIKP379HCazQvmzPDZOU+fPGazZ0y1tq2/sL+89lrA1pf69T6227fTfXYdkSxXrifk7xd88pqo+5FP7ke5cmWdzrd313afnA8AED7UayGRR16AEPUcBICIMiS2r9Nsnj1jqlfnOX/utMVNGiP/SapVyxf76M5FtnZtmsvfL/giSxLn+OR+NPisjtP5+PRhAMBvqddCIo+8ACHqOQgAEWXU8EFOszl+yjiPjn/44F5r2KCufG35T75o2tDHdzAyJa9Z7rfv0ZNPPmnP/+l5i4qKspeKFrVChQvZk08+6Zdz/XTtik/uR6sWTZzOl7x6mU/OBwAIH+r3RkQeeQFC1HMQACLKhDEjnGbzxLEjs3zsebPi5WvKw5KRkeGHOxl5+vTq5nzPy5ePtvGjh9vC+TPth3Urbd/uHXb2zEm7fPG8Xbt62W7dvPHYDzJIT0+zyxfP24njh23f7h22OWWtrf5uiS2YM8Mmjx9lHdq1tPLlo53/puDnDT712b1w/dCT75IW+OycAIDwoH5fROSRFyBEPQcBIKJMmzzWaTaPHjE4S8cd980w+XrysNSsUc3M/s9P6v068Exs/xin+16+fHTAOvWN+dqpkycPlzPj+lAycV6Cz84JAAgP6vdGRB55AULUcxAAIsqs6VOcZvPQQf2ydNy33n5bvp48LPNmxdvwIQMe+N8njx/lpzsc3nanbnW+9zeuXwtIp/r1Pnbqs3LZIp+d0/VvLc6Mn+yzcwIAwoP6vRGRR16AEPUcBICIMn/2dKfZPKBvT+djnjh+WL6WPCyFX3zRKlWqkOn/X+/T2n680+EpIyPD+RNUN/6wOiCdSpQs6dRn3+4dPjun60+A8sAXAPBb6vdHRB55AULUcxAAIsqSxDlOszmmRxfnY25OWStfS36bls0b26JvZz32v9u0YY0f73Z4+uTjGk7fg2GD+/u9y7//fdf5NXH50gWfnTd+yjinc44cFuuzcwIAwoP6PRKRR16AEPUcBICI8l3SAqfZ3LVz+8ce69KFc9ak8WfWpPFnliNHDp+uDU8++aQVK1bMKlasYB/V/tDq1/3IGn1ez5o2aWCtWjSx9m1bWOeObax71y+td8+u1rtnV+vV4ytb/d0SW/3dEjMza9yovk+uE/dz/cCPypUr+r2L609j5s2X16fndf1gkqz8ZCkAIDKo999EHnkBQtRzEAAiypoVSU6zuX3bFo88zrpVS+2Z3z/j8ewvVLiQNW5Y30aPGGxzZ06zdauW2q4ft9jJ40fs+k9Xvb7Ou3fvOPV47o/PeX2uSJO6faPz9znt1k2/dtmQ/L1Tj0qVKvj0vEkL5zqdt3vXL316XgBA6FPvv4k88gKEqOcgAESU9WtXOM3mFl80yvQYe3dt92jef9G0oa3+bomdPnnM79d5+3a6U6c8T+fxe5dw4/qQM1u2bLYlZZ1fu8yIm+jUo0O7lj49r+sD7XZtmvv0vACA0KfefxN55AUIUc9BAIgorn/PrXHD+pkeY9CA3o/9+hw5cliuXE/Ye9HvWsK0SXb54vkAXiUP4vytxj+qOt3fUcMH+bVHj26dnHpMHDvSp+d1/Um8Jo0/8+l5AQChT73/JvLICxCinoMAEFG2b/7BaTY/6hNFixcv/tiv/6j2hwG8qgfxIM6/xowc4nR/q1Wr4tcerg8E16xI8ul5Xf8d1a1Ty6fnBQCEPvX+m8gjL0CIeg4CQETZnbrVaTbXqlk902O4fH2uXE8E8KoexIM4/9q2ab3T/c2Xz7cfkvBbhQsXdurxrwN7fHpe11/Prlr1fZ+eFwAQ+tT7byKPvAAh6jkIABFl3+4dTrP5UT/J9NRTTzkd4+aN6wG8svvxIM6/0tPTnNf5u3fv+KXDjevXnDvcunnDp+c+fHCv03nfi37Xp+cFAIQ+9f6byCMvQIh6DgJARNmzc5vTbK7xj6qZHuOVYq84HePMqeMBvLL78SDO/6Kiopzusb/+PuC//33X6fxFX37Z5+c+deKo07lLvfGGz88NAAht6v03kUdegBD1HASAiOL6q6k1a1TL9BjR0e85HWP/nh8DeGX340Gc/7351ltO9/jo4f1+Of+WlHVO5/fH3yu8cP6M07lfKfaKz88NAAht6v03kUdegBD1HASAiOKLvxFX79PaTsfY+MPqwF3Yb/Agzv+qV6/idI93bN3gl/OvW7XU6fytWjTx+bl/unbF6dwFChTw+bkBAKFNvf8m8sgLEKKegwAQUXb9uMVpNteulflPEXVo19LpGEsXzQvgld2PB3H+17xZI6d77OtPLP2PpIVznc7/dZeOPj+369/I4/UFAPgt9f6byCMvQIh6DgJAREndvtFpNn/ycY1MjzFoQG+nY0wePyqAV3Y/HsT5X0yPLk73eN6seL+cf/aMqU7nj+0f4/Nz3717x+ncuXPn9vm5AQChTb3/JvLICxCinoMAEFFcH8TV+aRmpsdImDbJ6Ri9e3YN4JXdjwdx/jd21FCnezzum2F+Of/EsSOdzj921FCfn/vnn392OnfOnDl9fm4AQGhT77+JPPIChKjnIABElB+3pTjN5rp1amV6jNXfLXE6RuNG9QN4ZffjQZz/zZ05zeke++uB7NBB/ZzOP33qBJ+fOyMjw+nc2bNn9/m5AQChTb3/JvLICxCinoMAEFF2bN3gNJvrfVo702Ps3LHZ6RgVKkQH8Mrux4M4/1uzIsnpHrf4opFfzu/6q7GJ8xL8cn7e5wAAPKHefxN55AUIUc9BAIgo2zatd5rN9et9nOkxTp885nSMIi8VCeCVPahw4cKP7fjW229LO4Yy14e6Nf5R1S/nb9+2hdP5Vy5b5JfzZ8+e3en8GRkZfjk/ACA0qfffRB55AULUcxAAIorrg7gGn9XJ9BhpabecjqH+abN+vbs/tqO//n5ZJDh6eL/T6+B/Xn/dzp456fPzN25Y3+n8KetX+fzcZma5cj3hdP5///uuX84PAAhN6v03kUdegBD1HASAiLJ1Y7LTbP68waeZHiM9Pc3pGM/+4dkAXtmDXD6Y4sihfdKOoezs6RNZWu/r1qllrVs2teVLvrUZcRMtec1y+9eBPXb9p6senb9WzepO503dvtHHV/5/5M6d2+n8d+/e8cv5AQChSb3/JvLICxCinoMAEFG2pKxzms0NG9TN9Bhpt246HeO5Pz4XuAvLRNykMZn2m5MQp64X0i6cP+Oz9wL58uW16Oj3rGGDutbtqw42cliszZ4x1VYtX2zbN/9gh/bveuD8NWtUczr27tStfrn+PE/ncTp/enqaX84PAAhN6v03kUdegBD1HASAiLI5Za3TbG7cMPNPPL1184bTMV7I+0LgLuwRdqdutddKlLCiL79sRV9+2cqWK2v/OrBHXSssFCpcKGDvF5566ikrVLiQbU5Za2ZmnTu2cfq6c2dP+eXan/vjc07nT0u75ZfzAwBCk3r/TeSRFyBEPQcBIKJs2rDGaTY3bpT5g7ibN647HSNfvrwBvDIo9OnVTfLeYfSIwZayftVj/7vy5f33yb0v5H3Bqeutmzf81gEAEHrU+28ij7wAIeo5CAARZeMPq51mc5PGn2V6jBvXrzkd43//f//bWjZvbIULFw6KtGze2Hr37BrAux3+ftyWInv/kLp9o+XIkeOR/03cpDF+u/Z8+fI69bx547rfOgAAQo96/03kkRcgRD0HASCiuPwUUbZs2axpkwaZHuP6T1fla4c3KV26tB3ctzOAdz28Ja9eZs/+4dmAfx/79e5u69euyPQn07p0amcZGRl+u+4CBQo49fT0wygAAOFJ/T6IyCMvQIh6DgJARNmQ/L3TbG7erFGmx7h44ax87fBF+CP6vnP54nlr3bJpQL9/hQsXNjOzK5cvWsMGda1Q4UL3siRxjt+vuWDBgk49r1297PcuAIDQoX7/Q+SRFyBEPQcBIKL8sG6l02xu8UXmD+J2p26Vrx2+yMpliwJ45yPDqOGDAvb9q1zp79JrLVy4sFPPq1cuSXsCAIKL+v0PkUdegBD1HASAiLJ+7Qqn2dyyeeNMj+H6gQ/Bnkf9+i08tzllbUA+TXVG3ETpdRZ5qYhTz8sXz0t7AgCCi/r9D5FHXoAQ9RwEgIiSvGa502xu1aLJI4+TK9cT8vXD29Su9aHf7/fNG9f9+nfKgtXli+dtTkKcValS6bEfqOBpzp45Kb3GV4q94tTz0oVz0p4AgOCifv9D5JEXIEQ9BwEgoiSvXuY0m9u0avbI47Rr01y+fnibBXNm+OUeHzm0z96LftdeL1Xq3rme/cOz9mKRF+31UqWsQoVoq13rQ2vcqL51aNfS+vTqZsOHDLDdqVtt+ZJvbcfWDXby+BG7dfOGX/opHNibals3Jtuq5YttyoRv7OsuHa12rQ/tv199NcvftzJlytih/bvUl2TFixd36nvh/Bl1VQBAEFG//yHyyAsQop6DABBR1q1a6jSb27b+4pHH2ZD8veXPn1++hniTy5cu+Pz+zp893acd8+XLa2XKlLEGn9Wxnt0724QxIyxp4Vzbtmm9nTh2yG7euO7cbfGC2da+bYt72bZpvc+v3xM///yznTl13HanbrXkNcstcV6CjR893Pr06mbNmzWygf16WcWKFWxgv142sF8vdd17eBAHAPCE+v0PkUdegBD1HASAiLJ25T+dZnO7Ns0fe6xrVy9b44b17/u6ggUL2tddOsrXlkclV64n/PJBDQf37ZRcT9Wq71v/Pj0y7fXzzz9b545tHvq1n3xcw+f3IVLwq6kAAE+o3wcReeQFCFHPQQCIKGtWJDnN5vZtWzgf8/jRg/dy4/o1MzPbu2u7lXrjDStRsqR8nflPSpQsabVrfWjnzp7yy70dMXSg9Prei37XDh/c+0Cv2rU+fOTXNW5U3y/3I9y9VLSo0/eFD2sAAPya+v0QkUdegBD1HASAiLL6uyVOs7lj+1Y+O+fVK5eCIv72P6+/Ll9TCxUudF+n6z9ddfq6A3tT/X5/wo3zp6b64VegAQChS/1egcgjL0CIeg4CQERZtXyx02z+skNrddWQEx39nnxNzZYtm+3Zue1epyWJc5y+5oMPKgvvXGgqXLiw070NxENgAEDoUL9PIPLICxCinoMAEFFWLE10ms1dOrVTVw05cZPGyNfUbNmyWWz/mHud4qeMc/qav7z2mvDOhaZChQs53VsexAEAfk39PoHIIy9AiHoOAkBEcX0Q17Vze3XVkHPqxFH5mpot2/0P4s6cOu78dQ/7+3LIXFTBKKf7+tO1K+qqAIAgon6fQOSRFyBEPQcBIKIsX/Kt02z+uktHddWQtCVlnb1Y5EXpuvrrX001MytXrqzT121OWSu6a6GpQIECTvf1+k9X1VUBAEFEvf8m8sgLEKKegwAQUZYumuc0m7t3/VJdNWTdunnDWjZvbM2bNbLn/vhcQNfUwoULP9CnbesvnL527cp/Cu5W6MqfP7/Tff3PJwkDAGDGgziiL0CIeg4CQERJWjjXaTb37N5ZXTVs/PLLL3br5g27fPG8nTx+xA7u22mp2zfahuTvbcXSREucl2DxU8ZZbP8Y+/DDDzxeT8uXj7ajh/c/cP5uX3Vw+vrlS74V3J3QlTdfXqf7euvmDXVVAEAQUe+/iTzyAoSo5yAARBTXT9GM6dFFXTUiNfisjtP3p9Qbb9grxV6x6tWrWPXqaVStkQAAIABJREFUVWxgv16ZHrNvzNdOx0yclxDAKw19z//peaf7yoM4AMCvqfffRB55AULUcxAAIsriBbOdZnPvnl3VVSPOhuTvndfONSuSnI87JLav0zFnTZ/iv4sLQ66/dpyWdktdFQAQRNT7byKPvAAh6jkIABFl4fyZTrO5b8zX6qoh64d1K+/7tcUX8r5g69eueOTXXP/pqvPfHMuWLZvdvXvHuc/YUUOdjjl14mhvLz2iPPP7Z5zua3p6mroqACCIqPffRB55AULUcxAAIkrivASn2dyvd3d11ZA0eGCfTO/poAG9M/26gf16Oa+br5cqlaVOcZPGOB139IjB3l5+RHnqqaec7uvt2+nqqgCAIKLefxN55AUIUc9BAIgoC+bMcJrNA/r2VFcNOanbNz72vv64LeWBrzu0f1eW1s34KeOy1Gv2jKlOx33Ug0I8KHfu3E73NSs/vQgACH/q/TeRR16AEPUcBICIMn/2dKfZ/Kg//o+H69e7+2Pva59e3R74uoYN6jqvmaXeeCPLvRZ9O8vp2PxdwKzJlesJp/v673/fVVcFAAQR9f6byCMvQIh6DgJARJk7c5rTbI7tH6OuGnIKFy7sdG9//WBm7cp/ZmnN3JyyNsu9VixNdDp2l07tfHk7wl7OnDmd7uvPP/+srgoACCLq/TeRR16AEPUcBICIMichzmk282uKWZcvX16ne3vy+JF7X/PXN//mvF527tjGo17Jq5c5Hb91y6a+uhURIXv27E73NSMjQ10VABBE1PtvIo+8ACHqOQgAEcX174UNie2rrhpyKlas4HRv//MJqq4fovCfnD1z0qNemzascTp+44b1fXk7wh7vcwAAnlDvv4k88gKEqOcgAESUmfGTnWbzsMH91VVDTtvWXzjd2zEjh9iF82ecf7UxW7ZsNnHsSI97/bgtxekcdT6p6cO7Ed5++eUXp3v6u+y/U1cFAAQZ9f6byCMvQIh6DgJAREmYNslpNg8fMkBdNeTETxnndG8HDehtX3fp6LxOlihZ0qte+3bvcDpP1arv++hOhL+MjAyne5ojRw51VQBAkFHvv4k88gKEqOcgAESU6VMnOM3mkcNi1VVDzrZN653ubfny0VlaJ1ctX+xVr8MH9zqd573od310J8Lfv/991+me5sr1hLoqACDIqPffRB55AULUcxAAIorrT22NGj5IXTXkHNy30+ne5sufz3mNrF/3I697nTh+2Olc75R+xwd3ITLcvXvH6Z4++eST6qoAgCCj3n8TeeQFCFHPQQCIKNMmj3WazWNGDlFXDTnHjx70+Rp5YG+q172OHTngdK5y5cr64C5Ehjt3bjvd06eeekpdFQAQZNT7byKPvAAh6jkIABHF9ZM6x44aqq4acs6eOenT9bFf7+4+6eX6q6nly0f75HyRID09zeme5nk6j7oqACDIqPffRB55AULUcxAAIsrUiaOdZvO4b4apq4acq1cu+WxtfP5Pz9u1q5d90sv1V2YrV/q7T84XCVwfxD37h2fVVQEAQUa9/ybyyAsQop6DABBR+Ik4/0m7ddNna+PsGVN91otPTfU91+/18396Xl0VABBk1PtvIo+8ACHqOQgAEYW/Eec/GRkZPlkXff3ppbtTtzqdt2aNaj49bzi7dfOG0z19Ie8L6qoAgCCj3n8TeeQFCFHPQQCIKK6fmjp6xGB11ZCU5+k8Xq+LKetX+bRT6vaNTuf95OMaPj1vOLt547rTPc2XL6+6KgAgyKj330QeeQFC1HMQACKK64O4kcNi1VVDUlRUlFdrYsvmjZ3Ok56eZltS1tnM+Mn3krx62UP/222b1judu369j315K8La9Z+uOt3TAgUKqKsCAIKMev9N5JEXIEQ9BwEgosyIm+g0m0cMHaiuGpKKFy/u1Zp44tihRx4/dftGq13rw0y/PrZ/zANfszllrdO5G31ez1+3Jey4PoiLiopSVwUABBn1/pvIIy9AiHoOAkBESZg2yWk2Dx8yQF01JL319tser4eP+inEUyeO2icf13A6ToUK0fd9bcr6VU5f17RJA3/fnrBx7eplp3tasGBBdVUAQJBR77+JPPIChKjnIABElJnxk51m87DB/dVVQ1KFCtEerYUvFS1qd+7cfugxkxbOtdy5c2fpeCePH7n39evXrnD6Gtdfi4XZ1SuXnO5p4cKF1VUBAEFGvf8m8sgLEKKegwAQUWZNn+I0m4cO6qeuGpJq1qjm0VqYtHDuQ4+3YmmiR8ebOnH0vWOsW7XU6Wvatv4iULcp5F25fNHpnr5Y5EV1VQBAkFHvv4k88gKEqOcgAESU2TOmOs3mIbF91VVD0ucNPs3yOljjH1Ufeqx+vbt7vLa2+KLRveOs/m6J09d0bN8qULcp5Lk+iHupaFF1VQBAkFHvv4k88gKEqOcgAESUOQlxTrN50IDe6qohqWXzxlleB1O3b3zgOAP69vRqbV2zIunesVx/qq5r5/aBvFUh7fLF8073lAdxAIDfUu+/iTzyAoSo5yAARJS5M6c5zeaHffomHq9Lp3ZZWgO7fdXhgWMMie3r9dr66783t3TRPKev6dGtUyBvVUhzfRBX9OWX1VUBAEFGvf8m8sgLEKKegwAQUebNineazTyI80zfmK+d17+cOXPahfNn7vv6aZPHer2uzoyffN8xFy+Y7fR1vXt2DeStCmk8iAMAeEq9/ybyyAsQop6DABBR5s+e7jSbB/brpa4akpo2aeC8/sVNGnPf17o+MMssb739tu3f8+MDnRLnJTh9ff8+PQJ1m0IeD+IAAJ5S77+JPPIChKjnIABElAVzZjjN5gF9e6qrhqTePbs63d/f/u2wzSlrPVpD33zrLRs1fJBt3/xDpp34dWTfu3ThnNM9faXYK+qqAIAgo95/E3nkBQhRz0EAiCj8dJR/9erxldP97dXjq3tfc+LYIcuXL2+W188e3Trd97fgMjMzfrLT8YYO6ufPWxNWeBAHAPCUev9N5JEXIEQ9BwEgoiycP9NpNveN+VpdNSR17/ql0/1dtni+mZml3bpp775bLstr57hvhjl3ip8yzumYI4fF+uu2hB0exAEAPKXefxN55AUIUc9BAIgoi76d5TSb+/Tqpq4akrp2bu90f1csTTQzsyaNP8vyujl6xOAsdZo6cbTTcceOGuqPWxKWLl4463RPixUrpq4KAAgy6v03kUdegBD1HASAiMInaPrXlx1aO93fVcsX28B+vbK8Zg4a0DvLnSaMGeF07AljRvjhjoQnHsQBADyl3n8TeeQFCFHPQQCIKEsS5zjN5pgeXdRVQ1L7ti2c7u9XX7bN8nrZuWMbjzqNHTXU6fhTJ4728d0IXzyIAwB4Sr3/JvLICxCinoMAEFGSFs51ms2//jABuGvTqplf1soGn9XxuNPIYbFO54ifMs6HdyK8XTh/xumeFi9eXF0VABBk1PtvIo+8ACHqOQgAEcX1QVyPbp3UVUNSy+aNfb5OvvnWW/bTtSsedxo6qJ/TeWbGT/bhnQhvPIgDAHhKvf8m8sgLEKKegwAQUVLWr3KazV07t1dXDUlfNG3o0zUyz9N57PDBvV51iu0f43SuOQlxProL4Y8HcQAAT6n330QeeQFC1HMQACJK8uplTrO5ZfPG6qohqXGj+j5dI39Yt9LrTv379HA6V+K8BB/cgcjg+iDuv199VV0VABBk1PtvIo+8ACHqOQgAEWXrxmSn2Vy/3sfqqiHp8waf+mx99NVPqLn+RNzcmdN8cr5IwIM4AICn1PtvIo+8ACHqOQgAEWXPzm1Os7lq1ffVVUNS/bof+WRtjO0f47NOI4YOdDrn9KkTfHbOcMeDOACAp9T7byKPvAAh6jkIABHlyKF9TrO5XLmy6qohqc4nNb1eF79o2jDL592zc9t9+bXxo4c7nXfi2JG+ug1hjwdxAABPqfffRB55AULUcxAAIsqZU8edZvNrJUqoq4ak2rU+9GpNfPfdcpaenpalc44eMfiB4wzs1+ve/x8/ZZzTuUcNH+Tr2xG2zp877XRPX/3zn9VVAQBBRr3/JvLICxCinoMAEFEuX7rgNJsLFS6krhqSavyjqldr4vbNP2TpfDVrVMv0WOXLR9vNG9dtTkKc07kHD+zjp7sSfngQBwDwlHr/TeSRFyBEPQcBIKKk3brpNJuf+f0z6qohqWrV9z1eDwf07Zmlc6WsX/XYYy5dNM8Wzp/pdP6+MV/76a6EHx7EAQA8pd5/E3nkBQhRz0EAiCi//PKL83zOyMhQ1w05H3xQ2aO18L9ffdVu307P0rk6d2zz2ON+3uBTW77kW6cOX3fp6Ke7En54EAf8/+3deZDsZX3v8S6oInVTh6pgIZYxVdECw3IjxkQU694IRMOJES4xGvcVDKAGUS+SuF7cEEURRNEAKqgQISqoEFQUQQiLAuYgQkBRFtk3WZSA4HP/GjL26en+9fZ8ZuZ5vate/zBDz7d//Zun+/mdmR5Jk5befxMXHwDS66AkNdejf//RndbnX957T3rUFdekF+LO/s7Xx/5amzxik063/c1TT+r0efu9aZ85HJHVmQtxkqRJS++/iYsPAOl1UJKaa6utt+q0Pt9+683pUVdcu+22y9jPg//45jeM/XUefPDBTre9wYYblHPP/nanz/2H1+45hyOyOrvpxp93OqZ/9uQnp0eVJC2z0vtv4uIDQHodlKTmeur223dan6+/7ur0qCuucS/EPfZxj53ogue999zd6fYf8wePKReef3anz331Hi+fwxFZnbkQJ0matPT+m7j4AJBeByWpudau3bnT+nzVlZelR11x7brrs8d6DvzaSSdM9HVuu+WmTre/9TZbl3UXn9/pc1/8oufN+Gis3lyIkyRNWnr/TVx8AEivg5LUXM//u+d0Wp8vXXdhetQV1zgX4l71ihdP/HW6Xlzb/mlPK5df+oNOn/s3f7PrDI/E6s6FOEnSpKX338TFB4D0OihJzfXqPV7eaX3+3nlnpUddce26y193fv676IJzJv46n/30Jzt9jYMPek+5/dabO33udk95ygyPxOrOhThJ0qSl99/ExQeA9DooSc31hte/ptP6fNa3/i096oprl12e1enY7rH7y6b6Onvt+apOX+fQDx9U7rzjtk6fu2bNmhkdhdXfjTdc1+mYPnm77dKjSpKWWen9N3HxASC9DkpSc73zbft3Wp9P/cq/pkddcXW9EPfj//zhxF/jwQcfLI/+/Ud3+jrnnHV6KaWUTR6xycjP3WDDDWZ1GFZ9LsRJkiYtvf8mLj4ApNdBSWquD77/3Z3W5xOPPzY96orr2c/udiHuJ1f8aOKvcdcv7uj8HLvwF1k/cOC7Rn7uvvvsPavDsOpzIU6SNGnp/Tdx8QEgvQ5KUnMd8dEPd1qfjzn6iPSoK64aF+K+dtIJnb7GU7ff/uH/54f/8f2Rn+9XkbvnQpwkadLS+2/i4gNAeh2UpObq+kb/hx96cHrUFdeznrW207G96srLJv4aV//0ik5f4+CD3vNb/9873vrmJT93n9ftWX796wemvfvN5EKcJGnS0vtv4uIDQHodlKTm+tIJn++0Ph/0vgPSo664alyIK6WUp26//dDb/8PH/mG58vJL1vv/TvvqF9f73BOOO2aqWVrMhThJ0qSl99/ExQeA9DooSc31jVO+3Gl9fts//d/0qCuuv/qrOhfiPvqRDw69/Xe+bf8l/9+7fnHHb9H4db0Qt91TnpIeVZK0zErvv4mLDwDpdVCSmuvSdRd2Wp9f8bIXpkddcdW6EFdKKd/55illzZo16932V7/8hRncEw3LhThJ0qSl99/ExQeA9DooSc11xWXrOq3Pi9/sX93q8hdpN33kpjP7ejffdH05+YvHP+yan105s9vW0rkQJ0matPT+m7j4AJBeByWpue64/dZO6/Pv/M7vpEddcXX5acO37P/G9JiaMhfiJEmTlt5/ExcfANLroCQ12aaP3LTTGn3rLTemR11xbb3N1kOP6blnfzs9oqbMhThJ0qSl99/ExQeA9DooSU329B126LRG/+iSi9Kjrrh+ee89Zd999l7vWP7Rln9UvnfeWenxNINciJMkTVp6/01cfABIr4OS1GSv3uPlndbob339q+lRV2wnHn9s+ehHPviwe++5Oz2SZpQLcZKkSUvvv4mLDwDpdVCSmuzA97yz0xr9maM+nh5VWnbdeP21nb5//METSVJ/6f03cfEBIL0OSlKTHXfs0Z3W6APe8U/pUaVllwtxkqRJS++/iYsPAOl1UJKa7LtnnNZpjX7ZS1+QHlVz6KGHHioPPHB/ue++X5V777m73PWLO8odt99abrvlpvXcesuNQ91y8w2d3XbLTeWuX9xR7rvvV+Whhx5KH4aJcyFOkjRp6f03cfEBIL0OSlKTXXn5JZ3WaO9xNV4PPfRQ+eW995Tbb725XH/d1eUnV/yoXPbDi8u6i88vF11wTjnvnDPK2Wd+o3znm6eUb5zy5fLVL3+hfPELnyv/8rlPl89++pPlyCMOKx877EPlkIMPLAe974Dy7gPeWt7+lv3Kfm/ap+zzuj3Lnq9+ZXnVK19SXvbSF5QXPP9vy3Oe83/Krrv8dVm7dufyjGc+ozx9hx3KU7ffvjzpT/+0PGHbJ5Qtt9yybLHFFuWxj3ts2fSRm5Y1a9aUDTfcMP7cv2DjjTcuj3vcY8vW22xdnrzddmXHnXYsz3rW2vLc5+5WXvnyF5W999q9vHHf15a3v2W/8r53v6N8+IPvK584/JDymaM+Xv7lc58uJ3/x+PL1r32pnHn6qeXcs79d1l18frn2mqvKL+68fa6PswtxkqRJSz/3EhcfANLroCQ12Z133NZpjd5oo43So1bpwQcfLLfdclP5yRU/Kj+48Nxy7tnfLqefdnI5+YvHl88fc1T5548fWg4+6D3lgHf8U3njvq8tf7/HK8rz/+45Ze3anctTt9++bLX1VmWzR20Wf07lt8/drbfZuuy89i/Lq17x4vKW/d9YPvKh95fjP/upcvppJ5eLLjinXHXlZeX2W28uv/71A2OdLy7ESZImLf38SFx8AEivg5LUbF0vHN1y8w3pUSfu7rvuLNdec1VZd/H55TvfPKV84fOfKYcd8oHylv3fWF758heVZzzzGeXxj398/LmQvC222KI8fYcdyote+Lzyxn1fWz74/neXY44+opz6lX8t551zRrnisnXltltuKqW4ECdJmrz08x1x8QEgvQ5KUrPtuNOOndbpS9ddmB51YDfecF353nlnla986V/KkUccVt5zwNvK3nvtXnbd5a/LE5/4xLJmzZr4cxyrz+/93u+Vp26/fafPdSFOktRf+nmMuPgAkF4HJanZ/n6PV3Rap08/7eTonNdfd3U575wzyuc+88/lLfu/sTz72c8qmz5y0/jzF4ziQpwkqb/0cxNx8QEgvQ5KUrO9/73/r9M6/ekjPzb3WX7zm9+Ua6+5qpxz1unlmKOPKPu9aZ+y89q/9FNtrGguxEmS+ks/NxEXHwDS66AkNdvxn/1Up3X6nW/bf6Zf9+qfXlG+e8Zp5ahPfLS84fWvKX/xF39RNtpoo/jzEcyaC3GSpP7Sz03ExQeA9DooSc129ne+3mmdfulLnj/x13jggfvLJT/4Xjnm6CPKHru/rDzmDx4Tf96BWlyIkyT1l35uIi4+AKTXQUlqtisvv6TTOv3k7bbrfJt333VnueDcM8vhhx5cnvvc3coGG24Qf56BlO2f9rQ5fgdLklZi6ecm4uIDQHodlKRmu/OO2zqt0xtuuOGSt/HAA/eXM08/tRz0vgPKzmv/Mv6cQjcbbbRR2Xjjjctmj9qsPO5xjy1bPH6LsvU2W5cnbPuE9Wy77bZDPfGJTxzqT570pIf9zz/+47L55puXTR+5aRMXaV2IkyT1l35uIi4+AKTXQUlqukf//qM7rdU333T9w//P7bfdUk468bjyohc+L/4cshxt9qjNylZbb1Weuv32Ze3ancvf/u1u5cUvel7ZY/eXlb332r3su8/eZf/99i3vfNv+5b3venv54PvfXQ798EHlE4cfUo7+5OHlc5/553LCcceUk048rpxy8onl9NNOLmeefmo556zTywXnnlkuuuCcsu7i88ul6y4sl1/6g3Ll5ZeUq668rFz90yvKddf8tNzw82vKzTddX2675aZyx+23lrvvurP88t57yn33/ao88MD95aGHHgqecb/d/ff/V7nn7l+U22+9udx4w3Xl2qt/XH78nz8sP7rkonLx9/69nHfOGeWsb/1b+cYpXy4nf/H48oXPf6Yc+6lPlE9+7CPlkIMPLAe+553lHW99c3nTG15X9t5r97LbbruUP3vyk8tmj9osfh70ei7ESZLWL/3cRFx8AEivg5LUdDvttFOntfqCc88sp37lX8urXvmS+PPGvGy++eZlx512LC99yfPL3nvtXvbfb9/y3ne9vRz64YPK0Z88vJxw3DHllJNPLGeefmq54Nwzyw//4/vlJ1f8qFx/3dXl9ltvLr+8955ldZGr9X71y3vLjTdcVy6/9Afl3LO/Xb520gnlM0d9vBz0vgPKG17/mvLCFzy3/PnTn14233zzuZ1TLsRJkvpLv94hLj4ApNdBSWq6PV/9yk5r9SaP2CT+fDGJjTfeuPzJk55Udt312eU1e+9R3vuut5ejPvHR8tUvf6Gce/a3yxWXrSs333R9uf/+/0o/FAr2wAP3l9tuualcdeVl5cLzzy7fPPWkctyxR5dDDj6w/OOb31Be+fIXlf/15/+7rFmzZqzzz4U4SVJ/6ddGxMUHgPQ6KElN97WTTog/D0xqgw03KDvutGN5/T/sVQ475APlhOOOKWeefmpZd/H55dprrip333Vn+vBqFXbrLTeWS9ddWLbddtuR5+hhh3wgPa4kaZmVfv1EXHwASK+DktR0p5x8Yvx5YJTf/d3/UZ75zGeUN73hdeXoTx5ezv7O18u1V//Yr4Eq2pFHHDby3L3y8kvSY0qSllnp11XExQeA9DooSU135eWXxJ8HFmzyiE3KX/3V2rL/fvuWYz/1iXLu2d8uP7/2Z+lDJA3s6p9eUbbaeqslz+dXveLF6RElScuw9Ost4uIDQHodlKSmu3TdhWWbbbapvvbvtNNO5e1v2a98/pijygXnnlluvP7a9KGQxu6X995TXv8Pe613fn/6yI+lR5MkLdPS+2/i4gNAeh2UpGZ79wFvrbbW77rrs8shBx9Y/v273yp33nFb+q5LM+2iC8552LqLz0+PI0laxqX338TFB4D0OihJzXXFZevKjjvtOLd1feONNy4vfcnzy5FHHFYuuuCcct99v0rfZUmSpGVRev9NXHwASK+DktRc+7xuz5mv5c997m7luGOPLpdf+oP03ZMkSVq2pfffxMUHgPQ6KElN9Zvf/GZm6/cuuzyrfP6Yo8oNP78mfbckSZJWROn9N3HxASC9DkpSU5195jemWrPXrFlTPvKh95drr/5x+q5IkiStuNL7b+LiA0B6HZSkpvr5tT+baK3e4vFblE8f+bFy9113pu+CJEnSii29/yYuPgCk10FJaq6ddtqp8xr9hG2fUE48/tjy4IMPpseWJEla8aX338TFB4D0OihJzXXkEYd1Wp8/9IH3+ounkiRJMyy9/yYuPgCk10FJarKvf+1LA9fkx/zBY8p7Dnhbeeihh9IjSpIkrbrS+2/i4gNAeh2UpGa7/rqryzFHH/Gw00872a+gSpIkzbH0/pu4+ACQXgclSZIkSapSev9NXHwASK+DkiRJkiRVKb3/Ji4+AKTXQUmSJEmSqpTefxMXHwDS66AkSZIkSVVK77+Jiw8A6XVQkiRJkqQqpfffxMUHgPQ6KEmSJElSldL7b+LiA0B6HZQkSZIkqUrp/Tdx8QEgvQ5KkiRJklSl9P6buPgAkF4HJUmSJEmqUnr/TVx8AEivg5IkSZIkVSm9/yYuPgCk10FJkiRJkqqU3n8TFx8A0uugJEmSJElVSu+/iYsPAOl1UJIkSZKkKqX338TFB4D0OihJkiRJUpXS+2/i4gNAeh2UJEmSJKlK6f03cfEBIL0OSpIkSZJUpfT+m7j4AJBeByVJkiRJqlJ6/01cfABIr4OSJEmSJFUpvf8mLj4ApNdBSZIkSZKqlN5/ExcfANLroCRJkiRJVUrvv4mLDwDpdVCSJEmSpCql99/ExQeA9DooSZIkSVKV0vtv4uIDQHodlCRJkiSpSun9N3HxASC9DkqSJEmSVKX0/pu4+ACQXgclSZIkSapSev9NXHwASK+DkiRJkiRVKb3/Ji4+AKTXQUmSJEmSqpTefxMXHwDS66AkSZIkSVVK77+Jiw8A6XVQkiRJkqQqpfffxMUHgPQ6KEmSJElSldL7b+LiA0B6HZQkSZIkqUrp/Tdx8QEgvQ5KkiRJklSl9P6buPgAkF4HJUmSJEmqUnr/TVx8AEivg5IkSZIkVSm9/yYuPgCk10FJkiRJkqqU3n8TFx8A0uugJEmSJElVSu+/iYsPAOl1UJIkSZKkKqX338TFB4D0OihJkiRJUpXS+2/i4gNAeh2UJEmSJKlK6f03cfEBIL0OSpIkSZJUpfT+m7j4AJBeByVJkiRJqlJ6/01cfABIr4OSJEmSJFUpvf8mLj4ApNdBSZIkSZKqlN5/ExcfANLroCRJkiRJVUrvv4mLDwDpdVCSJEmSpCql99/ExQeA9DooSZIkSVKV0vtv4uIDQHodlCRJkiSpSun9N3HxASC9DkqSJEmSVKX0/pu4+ACQXgclSZIkSapSev9NXHwASK+DkiRJkiRVKb3/Ji4+AKTXQUmSJEmSqpTefxMXHwDS66AkSZIkSVVK77+Jiw8A6XVQkiRJkqQqpfffxMUHgPQ6KEmSJElSldL7b+LiA0B6HZQkSZIkqUrp/Tdx8QEgvQ5KkiRJklSl9P6buPgAkF4HJUmSJEmqUnr/TVx8AEivg5IkSZKEHJx5AAAcO0lEQVQkVSm9/yYuPgCk10FJkiRJkqqU3n8TFx8A0uugJEmSJElVSu+/iYsPAOl1UJIkSZKkKqX338TFB4D0OihJkiRJUpXS+2/i4gNAeh2UJEmSJKlK6f03cfEBIL0OSpIkSZJUpfT+m7j4AJBeByVJkiRJqlJ6/01cfABIr4OSJEmSJFUpvf8mLj4ApNdBSZIkSZKqlN5/ExcfANLroCRJkiRJVUrvv4mLDwDpdVCSJEmSpCql99/ExQeA9DooSZIkSVKV0vtv4uIDQHodlCRJkiSpSun9N3HxASC9DkqSJEmSVKX0/pu4+ACQXgclSZIkSapSev9NXHwASK+DkiRJkiRVKb3/Ji4+AKTXQUmSJEmSqpTefxMXHwDS66AkSZIkSVVK77+Jiw8A6XVQkiRJkqQqpfffxMUHgPQ6KEmSJElSldL7b+LiA0B6HZQkSZIkqUrp/Tdx8QEgvQ5KkiRJklSl9P6buPgAkF4HJUmSJEmqUnr/TVx8AEivg5IkSZIkVSm9/yYuPgCk10FJkiRJkqqU3n8TFx8A0uugJEmSJElVSu+/iYsPAOl1UJIkSZKkKqX338TFB4D0OihJkiRJUpXS+2/i4gNAeh2UJEmSJKlK6f03cfEBIL0OSpIkSZJUpfT+m7j4AJBeByVJkiRJqlJ6/01cfABIr4OSJEmSJFUpvf8mLj4ApNdBSZIkSZKqlN5/ExcfANLroCRJkiRJVUrvv4mLDwDpdVCSJEmSpCql99/ExQeA9DooSZIkSVKV0vtv4uIDQHodlCRJkiSpSun9N3HxASC9DkqSJEmSVKX0/pu4+ACQXgclSZIkSapSev9NXHwASK+DkiRJkiRVKb3/Ji4+AKTXQUmSJEmSqpTefxMXHwDS66AkSZIkSVVK77+Jiw8A6XVQkiRJkqQqpfffxMUHgPQ6KEmSJElSldL7b+LiA0B6HZQkSZIkqUrp/Tdx8QEgvQ5KkiRJklSl9P6buPgAkF4HJUmSJEmqUnr/TVx8AEivg5IkSZIkVSm9/yYuPgCk10FJkiRJkqqU3n8TFx8A0uugJEmSJElVSu+/iYsPAOl1UJIkSZKkKqX338TFB4D0OihJkiRJUpXS+2/i4gNAeh2UJEmSJKlK6f03cfEBIL0OSpIkSZJUpfT+m7j4AJBeByVJkiRJqlJ6/01cfABIr4OSJEmSJFUpvf8mLj4ApNdBSZIkSZKqlN5/ExcfANLroCRJkiRJVUrvv4mLDwDpdVCSJEmSpCql99/ExQeA9DooSZIkSVKV0vtv4uIDQHodlCRJkiSpSun9N3HxASC9DkqSJEmSVKX0/pu4+ACQXgclSZIkSapSev9NXHwASK+DkiRJkiRVKb3/Ji4+AKTXQUmSJEmSqpTefxMXHwDS66AkSZIkSVVK77+Jiw8A6XVQkiRJkqQqpfffxMUHgPQ6KEmSJElSldL7b+LiA0B6HZQkSZIkqUrp/Tdx8QEgvQ5KkiRJklSl9P6buPgAkF4HJUmSJEmqUnr/TVx8AEivg5IkSZIkVSm9/yYuPgCk10FJkiRJkqqU3n8TFx8A0uugJEmSJElVSu+/iYsPAOl1UJIkSZKkKqX338TFB4D0OihJkiRJUpXS+2/i4gNAeh2UJEmSJKlK6f03cfEBIL0OSpIkSZJUpfT+m7j4AJBeByVJkiRJqlJ6/01cfABIr4OSJEmSJFUpvf8mLj4ApNdBSZIkSZKqlN5/ExcfANLroCRJkiRJVUrvv4mLDwDpdVCSJEmSpCql99/ExQeA9DooSZIkSVKV0vtv4uIDQHodlCRJkiSpSun9N3HxASC9DkqSJEmSVKX0/pu4+ACQXgclSZIkSapSev9NXHwASK+DkiRJkiRVKb3/Ji4+AKTXQUmSJEmSqpTefxMXHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAKCacdrndXuOdXs//fHlU8806W0svq2VMGfy8V/Jt7/aOX7Lz2p+TEataathzatxnJbrbfe7/bZb1nuev/22W+LHdzmb52uK2r5/3nfXe/xLKeXwQw+OzwY0KT4AQDWT1PX2khe4Fm8wlvOcKaOOz3K//dXO8Vt+WnhMRq1pK3nNq3mcluttL9hhxx3LUn3/vO/Gj+9yVOM1RS2HH3rwko//4nbYccf4rEBT4gMAVDNpXW4vdYHrpz++fOSsy2HOlC7HZznf/mrn+C0/rTwmo9a0lbrm1T5Oy/W2F5xy8ollqU45+cT48V1uar2mqGGf1+255GM/KBfjgIriAwBUM2nzfKE57ddZTS+a58GFuOXN8Vt+WnlMWl4XW9L/K4ld3naiZavp+7+//l9D7T83rANARfEBAKrp8oJrqV9jmdeL92lfBLoQN/3xWc63v9o5fstPK49Jy+tiS/ovtvipp+FWy/d//6+kLvVecP331/kBVBIfAKCacTZe/W/sPOi9ZLre3qBfjVl4sTfpZnCpNx4edFuD/vug900Z9gK0y5zDfg1k2vfiGfe2xzk+o/6fWd3+Uveh63nT6w2+UNz/61X9s3V5Q/JxZ+s/JxZmGHSuD7qIPcnxG/d7fJz7P2ymcb7mKSefuN731uLzZ5zPneaxmeSYzOMxmWb2cb4fp30spvnV1Fl873Q5DwapsUZ0OQ6Trv2jbnvQfZjVGrPUfZ73OlBzXZ/Xc9pS/32ex3Ocx37Q1+36PeQnJoFK4gMAVDPOi8dBG4tJbm/QX2pb/OJynJkWm+ZFc/+/AC9uqX81HjXnsNtc3CQvcie57XEvKnRp8YXKcW9/1H0YtDHqPz+Gfc2FrzesSY/vUhvpxQ17H6aFj096/s7i+2HQDAu6vJn3sHn6P2/Y1x3nc6d5bCY5JrN+TKaZvUuD/uGgf95h93fUfety32fxvdPlPFhKjTVi1HGYZu0fdduLm/Ua038hq9Y6UGtd79Kkz2lL/fd5Hc9xH/tp1ik/EQdUEh8AoJquLwAHff6gF2ijbq/rBmWcmRZM+qK5S+Meu1Evkrvc/lImve1xjk/Xx2nx/zOP2+/fTIx730c16KLApLNNcl5NcyFzmu+FxfVfaO76F/VKWfonUEY16edO89hMckxm+ZhMM/sk34/TPhaTXIib5/fOvNbHUY37k9/Trv3Dbnvea8zi7+ea68ByWtcnfU5b6r/XPJ79TXIBrf84+RV1oKL4AADVjPuCq/+n2fr/RX/Y7Q16Ibr4/x/08RrvETfo8/ob9FNxw+ZcfJyGbVgn+VfraW971PHp/8nHxbfT5acix739/k1H/zm2eDMxaMM26ieYhm0u+7/2NLPN6rya9v2IBj1Gw45h/33sr/88GvXxQZ/T9df8hn3uNI/NtMdk1o/JNLOP+/3Y9fj2f+64F+Jm/b3T9den+817jRh1HKZdn8d5DBYa9vFBa0yX94gbdgxnvQ7UXtdn/Zw2yeM2i+PZP0t/S/00f5fv/2H3FWBO4gMAVDPqxWO//hek41yI638xPehF4jS/mrrUjKPu96D70f/CftSL4mG/1jnNr4iMmn2S2x51fBY/BoM2Tv0b6nFvf9TH+98baPF9HHV+jLrgMmr+aWbrcl71z9/lp5/GfXy7/EXEhWMwyXyD7ue431+TfO40j800x2QWj8mszvlJvh8nfSzGvRA37++drua9Row6DsPuYxfjPAaDjlOX7+FRF+JqrwPzfszm/Zw26nGrdTy7fp1R35tLHSeAOYsPAFDNsBePg0xzIW7Ui91eb/0XhDUuxA16wTnsX9Anua8LzeK9Vqa97XlfVBj18S6P7+LbWPw5ozYa/efPoMd22HzTzDar82rax2fx+THuZqrr1x71Zt79DfuaXT93msdmmmMyi8dkmtmnnW3Sx2LcC3HT3sdx5hxm3mvEqPs67fo8zmMw6Roz6kJc7XWgxmM2zffQtBfi5nE8J33sB+nyh7gAKogPAFDNsBePg0xzIa7r1xp3plEzTvI1pr0Q1+X9YCb9F+dpb3vSDctS7+Mzzu0P+pf3ce5L/wz9P1XZ5ULuUm9EPe1sszqvalz0mfb/HXU/hh2jYV9zqc+d9rGZ5phM+5jM4rya5vtxnNsddZyW+visv3em+Wmcea4RXY7TtOvzqNlGfXwWF+JGfY1ZrwM1HrNpvoemfU0xj+M56WPfr8tP/wNUEh8AoJquLxAHff6gF7uzeDE67kz9lsOFuF6v+xtQT/Kvz9PcdteLCl3f3H6c259kw774NpbbhbjFs83qvFptF+JGzdDlc6d9bKY5JtM+JrM4r6b5fhznvo/63KU+XuN7p6v0hbhBMyzVuH8IosvHl+uFuGG3U+tC3Dye07rc11rHc5ILcf3HftLvO4AZiA8AUE3XF4i93vhvDN76hbgFXTap476p8jS3Pe57OS208NOP0/wajwtxLsRN8jVbvhA37ffjOPd91Ocu9XEX4ma3Po+67VEfdyFu/fs0z+e0Lve11vGc9kKc94UDwuIDAFTT9QVir9ftz9oP+/hyfY+4eV+IG3UfS5nde7J0ue1Rx2fU+2lNu2mZ5n7Pe8M27WMy6mvXfo+4cf//ebyX0SwuxE372ExzTGbxmMxq9lm/n9m4nzvs49Pcx3HnHGY5XYjr12V9nuYx6PWW73vEJS/Ezfs5bdR9rXU8J32POIBlIj4AQDVdXygPegPqQX8Bbdjtdfmrqf2fsxovxPV6628sZvnmyKNue5yfWBv1q1ODju8sNjVLmfeGbd4/jVbjQtw432f9X38ef91vVhfipjku0xyTWTwmk/7/s/h+nOVjMezjyZ/kHHYOL6cLcV0e02keg15vNhfiaq8DNX/SeR7PaaPua63j6UIcsMLFBwCoZtKWelE97HMG/Wrr4ot5g95XZxYX4ga9V8yorzGLC3ELm51hHxt2+8NMc9vj/grPUj9ZsNC4x7//zaH7f0Jh4eODfnJh3pvsaWab1XnV5fwdZtD32bD7uPjjgx7/Yb8etdR9GHUcJvncaR6baY7JLB6TSWefxffjLB+LYR+f9/dOV8vhQtw06/M0j8Ggc32SC3G114Habzkw6+e0Ufe11vH0q6nAChcfAKCaSVtqIzrqhWLXN0sedhujLPU1Ft/WqK8xzYW4QZv+UXW9b7O47VHHZ9DGZFj950KX49+/sRnW4mNfY5M96WyzOq+6HL9JvwcG1f8TIl3+6uOomcaZe5zPneaxmeaYzOIxmXT2ab8fx5l31OeO+vg8v3e6Sl6Im8X6PGq2UR+fxYW42utAzV9N7dIkz2mj5qtxPF2IA1a4+AAA1UxS19tb6sXksM3a7bfd8lsfn2RDttRmaPGLzFFzTvsTceO86J72p2vGve1Rx2fUZrL/6/dvmroc/16v2+ao/4JIrb+uN8lsszqvuh6/UbpceFrq+6vLOTbse7Pr5437udM8NtMck1k9JpPMPu3346j7Ns7ndrmteX3vdJX+ibhp1+dRs436+KwuxNVcB+b9mNV4TutyX+d9PF2IA1a4+AAA1YxTlwtGXV9QDnpBuvDid9oLcb3e4BfONS/ELRj067bDbnMc09z2qOMz6NxYfB8Xb7a7Xrjo+iuDS33uoPs8rwtxk8w2q/NqnOM3zff4NOfYOF9z1hfiJn1spj0ms3pMJp29v67fj7N8LLre1jy+d7pKX4gb9b1TyvD1edrHYJYX4kbdl3G+z5IX4qb9HlrqnB73Qty8j6cLccAKFx8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAAAAAABaEB8AAAAAAFoQHwAAAAAAWhAfAIqULH3+AwBQl5Qsff4TFx8A0uugGi99/gMAUJeULH3+ExcfANLroBovff4DAFCXlCx9/hMXHwDS66AaL33+AwBQl5Qsff4TFx8A0uugGi99/gMAUJeULH3+ExcfANLroBovff4DAFCXlCx9/hMXHwDS66AaL33+AwBQl5Qsff4TFx8A0uugGi99/gMAUJeULH3+ExcfANLroBovff4DAFCXlCx9/hMXHwDS66AaL33+AwBQl5Qsff4TFx8A0uugGi99/gMAUJeULH3+ExcfANLroBovff4DAFCXlCx9/hMXHwDS66AaL33+AwBQl5Qsff4TFx8A0uugGi99/gMAUJeULH3+ExcfANLroBovff4DAFCXlCx9/hMXHwDS66AaL33+AwBQl5Qsff4TFx8A0utg1eZ93/fea/fS6/XKBw5818CPX/OzK0uv1yt777X7zL/2Si19/gMAUFcr7b3X7mXt2p1nfpu9Xq+ccNwxIz/nvHPOmOnXXi2lz3/i4gNAeh2sVo37v/Ck1+v1yjU/u3K9j7sQt37p8x8AgLpa6AMHvqv0er2ZX4gr5b9fPw/ab5x3zhml17PfGFb6/CcuPgCk18EqDfpJtYX/NssnqcUX4rbccsv1Pu5C3Pqlz38AAOpa7a1du/PD93UeF+JOOO6YJW97yy23bOIYT1P6/CcuPgCk18EqbbnllgMvjC313ydt8cW9Xm/9X1EddiGu/3EZ9C9cq7H0+Q8AQF2rtYXX+r1e7+GfTJvHhbhSBv+K6sJP4S3+ldTFMw07/gsX8BYM+9XXlV76/CcuPgCk18G5N+zi18IT2Kwuei2+vYV/CVt824NmWXiSHqSF93VIn/8AANS1WrvmZ1f+1uv8Xm9+F+IWbn/heI67z1i8R+m/CLdgtV6MS5//xMUHgPQ6OPcWnpQG/QGFhX81mseFuIWvu/jJd9AT5MIT3+InuoUfN5/lT+st19LnPwAAdbVSrzffC3ELe4aFPwrRf2wX9hmL/3G//yf1Bu2VBu1jVlPp85+4+ACQXgfn3sKTzbALcbP6ybP+n7BbuP2Fr91/Ia7mT+st19LnPwAAdbVSrzf/i1mL36N60K+kDtsDLf68Xq+d97FOn//ExQeA9Do496b5ibiFjy826HYWGnTxbOFfohb/lNzCk9zCRcJBP/a98C9cq/3XU9PnPwAAdbVSr9ftQty4e45BX6f/ItqwX0tdsLDPWHwxb8Fq/s2c9PlPXHwASK+Dc2+anzqbxYW4xT/a7ULc+qXPfwAA6mqlXm9lXIgrZfAfdVitj1X6/CcuPgCk18Eq1f6rqf0X9haeXBf/VdVS/GpqKZ4IAQBa00q9Xp33Wev11t9PLOwzJv2DCwvvObcafyggff4TFx8A0utglfovgC3132b1dQZdPFv814j8sYb/Ln3+AwBQVyv1erkLcaUM/mMNi/97Kf+97+j/CbxZv5f2cip9/hMXHwDS62C1atz/YRfilnoj1GE/Nr4an/j6S5//AADU1Uq9XvZC3LB9xuILb4t/YGAxfzWVVSo+AKTXwarN+753fc+5pX50vMXHJX3+AwBQVyv1etkLcaUM3mcM+nXV/otxq/kvqKbPf+LiA0B6HVTjpc9/AADqkpKlz3/i4gNAeh1U46XPfwAA6pKSpc9/4uIDQHodVOOlz38AAOqSkqXPf+LiA0B6HVTjpc9/AADqkpKlz3/i4gNAeh1U46XPfwAA6pKSpc9/4uIDQHodVOOlz38AAOqSkqXPf+LiA0B6HVTjpc9/AADqkpKlz3/i4gNAeh1U46XPfwAA6pKSpc9/4uIDQHodVOOlz38AAOqSkqXPf+LiA0B6HVTjpc9/AADqkpKlz3/i4gNAeh1U46XPfwAA6pKSpc9/4uIDQHodVOOlz38AAOqSkqXPf+LiA0B6HVTjpc9/AADqkpKlz3/i4gNAeh1U46XPfwAA6pKSpc9/4uIDQHodVOOlz38AAOqSkqXPf+LiA0B6HVTjpc9/AADqkpKlz3/i4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAABAC+IDAAAAAEAL4gMAAAAAQAviAwAAAADAqvf/ATFZN7lRiT9wAAAAAElFTkSuQmCC" alt=""&gt;&lt;br/&gt;&lt;br/&gt;&amp;gt; I also cannot get participants to actively click on the textboxes to move fowards as the "validresponse" line does not work.&lt;br/&gt;&lt;br/&gt;*****TRIAL*****&lt;br/&gt;&amp;lt;trial makeDetections&amp;gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ stimulusframes = [1 = DetectionQuestion, NoDetection, YesDetection, statements_block2]&lt;br/&gt;&lt;strong&gt;/ validresponse = (NoDetection, YesDetection)&lt;/strong&gt;&lt;br/&gt;/ trialduration = 8000&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;It works perfectly fine. Note that you have fixed the trial's duration to 8 seconds, so you'll wait a couple of seconds before the next trial starts.&lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="30089"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Thank you very much it worked, great help!!&lt;br/&gt;Is there anyway to keep the stimuli and text elements on the screen even after participants have made their response?&lt;br/&gt;&lt;br/&gt;Best, &lt;br/&gt;Paige&lt;a class="if-quote-goto quote-link" href="#" data-id="30090"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Set their /erase attributes to false if you want them to remain on-screen.</description><pubDate>Tue, 10 Nov 2020 19:05:54 GMT</pubDate><dc:creator>Dave</dc:creator></item><item><title>RE: How do I have three items on the trial but 1 of the items is a different color and size?</title><link>https://forums.millisecond.com/Topic30090.aspx</link><description>&lt;blockquote data-id="30089" class="if-quote-wrapper" unselectable="on" data-guid="1605030786317" contenteditable="false" id="if_insertedNode_1605030785381"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="30089" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="30089" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="30089" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 11/10/2020&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-30089"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="30088" class="if-quote-wrapper" unselectable="on" data-guid="1605030786317" id="if_insertedNode_1605029672281" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="30088" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="30088" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="30088" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;KempInquisit - 11/10/2020&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-30088"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;Hi everyone,&amp;nbsp;&lt;br/&gt;I am trying to create a trial with a stimuli image, a question underneath it, and two response options. The question should be in white color font while the two response options should be in black font inside a white textbox. However, when I run the code all the test items are black font inside a white textbox.&amp;nbsp;&lt;br/&gt;&lt;br/&gt;Could someone please help? &lt;br/&gt;I also cannot get participants to actively click on the textboxes to move fowards as the "validresponse" line does not work.&lt;br/&gt;&lt;br/&gt;Here is my code:&lt;br/&gt;&lt;br/&gt;*****ITEMS &amp;amp; STIMULI *****&lt;br/&gt;&amp;lt;text DetectionQuestion&amp;gt;&lt;br/&gt;/ items = DetectionQuestion&lt;br/&gt;/ position = (50, 70)&lt;br/&gt;/ select = sequence&lt;br/&gt;/ txcolor = (white)&lt;br/&gt;/fontstyle = ("Arial", 3.0%, true, false, false, false, 5, 1)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item DetectionQuestion&amp;gt;&lt;br/&gt;/1 = "Did this statement correct earlier misinformation?"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text NoDetection&amp;gt;&lt;br/&gt;/ items = ("0 - No")&lt;br/&gt;/ position = (25%, 80%)&lt;br/&gt;/ fontstyle = ("Arial", 2%, false, false, false, false, 5, 1)&lt;br/&gt;/ txcolor = (black)&lt;br/&gt;/ txbgcolor = (white)&lt;br/&gt;/ size = (10%, 5%)&lt;br/&gt;/ vjustify = center&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text YesDetection&amp;gt;&lt;br/&gt;/ items = ("1 - Yes")&lt;br/&gt;/ position = (75%, 80%)&lt;br/&gt;/ fontstyle = ("Arial", 2%, false, false, false, false, 5, 1)&lt;br/&gt;/ txcolor = (black)&lt;br/&gt;/ txbgcolor = (white)&lt;br/&gt;/ size = (10%, 5%)&lt;br/&gt;/ vjustify = center&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture statements_block3&amp;gt;&lt;br/&gt;/ items = ("Gas_2018_C.png","Gas_2018_C.png", "Cali_Fires_C.png", "Amazon_Rainforest_C.png", "Clinton_Nkorea_C.png", "Cinderella_Castle_C.png", &lt;br/&gt;"Library_AmericanFlag_C.png", "Military_Pay_C.png", "Mexican_Border_Crossings_C.png", "US_Trading_Partner_C.png", "Test_American_Cars_C.png",&lt;br/&gt;"Tax_Pres_Law_C.png", "Pres_Vacation_C.png", "Immigration_Boy_Cage_C.png", "Global_Warming_Antarctica_C.png", "Murder_Year_C.png", "Bernie_Tax_Income_C.png",&lt;br/&gt;"Biden_StudentDebt_C.png", "Chess_Players_C.png", "Liberian_Women_C.png", "SKorea_Population_C.png", "Missing_People_C.png", "Bloomberg_Campaign_Money_C.png",&lt;br/&gt;"Alabama_Senate_C.png", "Black_Homeownership_C.png", "Rural_Hospitals_C.png", "Race_Starbucks_C.png", "Brooms_Standing_C.png", "SwimmingPool_Deaths_C.png",&lt;br/&gt;"Voter_Turnout_C.png", "CoronaBeer_COVID_C.png", "Tax_Allocation_C.png", "Rep_Control_C.png", "Cali_Statelaw_C.png", "Soccer_Revenue_Gap_C.png", "Pope_GunControl_C.png",&lt;br/&gt;"Coffee_C.png", "Federal_State_Dollars_C.png", "UT_Athletes_Ipad_C.png", "Obama_Website_C.png", "Trump_Signed_Legislation_C.png", "GunControl_Warrant_C.png",&lt;br/&gt;"Abortion_Bieber_C.png", "Veteran_Suicide_C.png", "Vaccines_Autism_C.png", "Marriage_License_Benefits_C.png")&lt;br/&gt; / size = (60%, 60%)&lt;br/&gt; / position = (50, 32)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;*****Instructions*****&lt;br/&gt;&amp;lt;item Instructions&amp;gt;&lt;br/&gt;/  1 = "1 Welcomeb.jpg"&lt;br/&gt;/  2 = "2 BackgroundInfob.jpg"&lt;br/&gt;/  3 = "3 FamInstr1b.jpg"&lt;br/&gt;/  4 = "4 FamInstr2b.jpg"&lt;br/&gt;/  5 = "5 BeliefInstr1b.jpg"&lt;br/&gt;/  6 = "6 BeliefInstr2b.jpg"&lt;br/&gt;/  7 = "7 CorrectionInstr1b.jpg"&lt;br/&gt;/  8 = "8 CorrectionInstr2b.jpg"&lt;br/&gt;/  9 = "9 CorrectionInstr3b.jpg"&lt;br/&gt;/  10 = "10 CorrectionInstr4b.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture InstructionsDisplay&amp;gt;&lt;br/&gt;/ items = Instructions&lt;br/&gt;/ select = sequence&lt;br/&gt;/ size = (100%, 100%)&lt;br/&gt;/ position = (50%, 50%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Instructions&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = InstructionsDisplay]&lt;br/&gt;/ validresponse = (205)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;*****TRIAL*****&lt;br/&gt;&amp;lt;trial makeDetections&amp;gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ stimulusframes = [1 = DetectionQuestion, NoDetection, YesDetection, statements_block2]&lt;br/&gt;/ trialduration = 8000&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;*****BLOCK*****&lt;br/&gt;&amp;lt;block Correction&amp;gt;&lt;br/&gt;/ onblockbegin = [values.trialCount = 0; values.makeDetections = 1; values.instructnum = 7]&lt;br/&gt;/ trials = [1-4 = Instructions; 5-50 = makeDetections]&lt;br/&gt;/ onblockend = [values.missingRespCount = 0]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="30088"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;&amp;gt; The question should be in white color font while the two response options should be in black font inside a white textbox. However, when I run the code all the test items are black font inside a white textbox. &lt;br/&gt;&lt;br/&gt;The default screen color is white as is the default txbgcolor, so:&lt;br/&gt;(1) You won't see the white font &amp;lt;text DetectionQuestion&amp;gt; at all against the white background.&lt;br/&gt;(2) You won't see any "white box" around the two response options against the white background.&lt;br/&gt;&lt;br/&gt;Set your /screencolor to black per &amp;lt;defaults&amp;gt;. Set /txbgcolor = black for the detection question &amp;lt;text&amp;gt; element.&lt;br/&gt;&lt;br/&gt;&lt;img 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" alt=""&gt;&lt;br/&gt;&lt;br/&gt;&amp;gt; I also cannot get participants to actively click on the textboxes to move fowards as the "validresponse" line does not work.&lt;br/&gt;&lt;br/&gt;*****TRIAL*****&lt;br/&gt;&amp;lt;trial makeDetections&amp;gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ stimulusframes = [1 = DetectionQuestion, NoDetection, YesDetection, statements_block2]&lt;br/&gt;&lt;strong&gt;/ validresponse = (NoDetection, YesDetection)&lt;/strong&gt;&lt;br/&gt;/ trialduration = 8000&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;It works perfectly fine. Note that you have fixed the trial's duration to 8 seconds, so you'll wait a couple of seconds before the next trial starts.&lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="30089"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;Thank you very much it worked, great help!!&lt;br/&gt;Is there anyway to keep the stimuli and text elements on the screen even after participants have made their response?&lt;br/&gt;&lt;br/&gt;Best, &lt;br/&gt;Paige</description><pubDate>Tue, 10 Nov 2020 17:54:01 GMT</pubDate><dc:creator>KempInquisit</dc:creator></item><item><title>RE: How do I have three items on the trial but 1 of the items is a different color and size?</title><link>https://forums.millisecond.com/Topic30089.aspx</link><description>&lt;blockquote data-id="30088" class="if-quote-wrapper" unselectable="on" data-guid="1605029673205" id="if_insertedNode_1605029672281" contenteditable="false"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="30088" title="Move Cursor Below" contenteditable="false"&gt;&lt;span unselectable="on"&gt;+&lt;/span&gt;&lt;/a&gt;&lt;a class="quote-delete" unselectable="on" style="display: none;" href="#" data-id="30088" title="Delete Quote" contenteditable="false"&gt;&lt;span unselectable="on"&gt;x&lt;/span&gt;&lt;/a&gt;&lt;span unselectable="on" class="quote-markup"&gt;[quote]&lt;/span&gt;&lt;div unselectable="on" class="if-quote-header" contenteditable="false"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="30088" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;KempInquisit - 11/10/2020&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-30088"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;Hi everyone,&amp;nbsp;&lt;br/&gt;I am trying to create a trial with a stimuli image, a question underneath it, and two response options. The question should be in white color font while the two response options should be in black font inside a white textbox. However, when I run the code all the test items are black font inside a white textbox.&amp;nbsp;&lt;br/&gt;&lt;br/&gt;Could someone please help? &lt;br/&gt;I also cannot get participants to actively click on the textboxes to move fowards as the "validresponse" line does not work.&lt;br/&gt;&lt;br/&gt;Here is my code:&lt;br/&gt;&lt;br/&gt;*****ITEMS &amp;amp; STIMULI *****&lt;br/&gt;&amp;lt;text DetectionQuestion&amp;gt;&lt;br/&gt;/ items = DetectionQuestion&lt;br/&gt;/ position = (50, 70)&lt;br/&gt;/ select = sequence&lt;br/&gt;/ txcolor = (white)&lt;br/&gt;/fontstyle = ("Arial", 3.0%, true, false, false, false, 5, 1)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item DetectionQuestion&amp;gt;&lt;br/&gt;/1 = "Did this statement correct earlier misinformation?"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text NoDetection&amp;gt;&lt;br/&gt;/ items = ("0 - No")&lt;br/&gt;/ position = (25%, 80%)&lt;br/&gt;/ fontstyle = ("Arial", 2%, false, false, false, false, 5, 1)&lt;br/&gt;/ txcolor = (black)&lt;br/&gt;/ txbgcolor = (white)&lt;br/&gt;/ size = (10%, 5%)&lt;br/&gt;/ vjustify = center&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text YesDetection&amp;gt;&lt;br/&gt;/ items = ("1 - Yes")&lt;br/&gt;/ position = (75%, 80%)&lt;br/&gt;/ fontstyle = ("Arial", 2%, false, false, false, false, 5, 1)&lt;br/&gt;/ txcolor = (black)&lt;br/&gt;/ txbgcolor = (white)&lt;br/&gt;/ size = (10%, 5%)&lt;br/&gt;/ vjustify = center&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture statements_block3&amp;gt;&lt;br/&gt;/ items = ("Gas_2018_C.png","Gas_2018_C.png", "Cali_Fires_C.png", "Amazon_Rainforest_C.png", "Clinton_Nkorea_C.png", "Cinderella_Castle_C.png", &lt;br/&gt;"Library_AmericanFlag_C.png", "Military_Pay_C.png", "Mexican_Border_Crossings_C.png", "US_Trading_Partner_C.png", "Test_American_Cars_C.png",&lt;br/&gt;"Tax_Pres_Law_C.png", "Pres_Vacation_C.png", "Immigration_Boy_Cage_C.png", "Global_Warming_Antarctica_C.png", "Murder_Year_C.png", "Bernie_Tax_Income_C.png",&lt;br/&gt;"Biden_StudentDebt_C.png", "Chess_Players_C.png", "Liberian_Women_C.png", "SKorea_Population_C.png", "Missing_People_C.png", "Bloomberg_Campaign_Money_C.png",&lt;br/&gt;"Alabama_Senate_C.png", "Black_Homeownership_C.png", "Rural_Hospitals_C.png", "Race_Starbucks_C.png", "Brooms_Standing_C.png", "SwimmingPool_Deaths_C.png",&lt;br/&gt;"Voter_Turnout_C.png", "CoronaBeer_COVID_C.png", "Tax_Allocation_C.png", "Rep_Control_C.png", "Cali_Statelaw_C.png", "Soccer_Revenue_Gap_C.png", "Pope_GunControl_C.png",&lt;br/&gt;"Coffee_C.png", "Federal_State_Dollars_C.png", "UT_Athletes_Ipad_C.png", "Obama_Website_C.png", "Trump_Signed_Legislation_C.png", "GunControl_Warrant_C.png",&lt;br/&gt;"Abortion_Bieber_C.png", "Veteran_Suicide_C.png", "Vaccines_Autism_C.png", "Marriage_License_Benefits_C.png")&lt;br/&gt; / size = (60%, 60%)&lt;br/&gt; / position = (50, 32)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;*****Instructions*****&lt;br/&gt;&amp;lt;item Instructions&amp;gt;&lt;br/&gt;/  1 = "1 Welcomeb.jpg"&lt;br/&gt;/  2 = "2 BackgroundInfob.jpg"&lt;br/&gt;/  3 = "3 FamInstr1b.jpg"&lt;br/&gt;/  4 = "4 FamInstr2b.jpg"&lt;br/&gt;/  5 = "5 BeliefInstr1b.jpg"&lt;br/&gt;/  6 = "6 BeliefInstr2b.jpg"&lt;br/&gt;/  7 = "7 CorrectionInstr1b.jpg"&lt;br/&gt;/  8 = "8 CorrectionInstr2b.jpg"&lt;br/&gt;/  9 = "9 CorrectionInstr3b.jpg"&lt;br/&gt;/  10 = "10 CorrectionInstr4b.jpg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture InstructionsDisplay&amp;gt;&lt;br/&gt;/ items = Instructions&lt;br/&gt;/ select = sequence&lt;br/&gt;/ size = (100%, 100%)&lt;br/&gt;/ position = (50%, 50%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial Instructions&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = InstructionsDisplay]&lt;br/&gt;/ validresponse = (205)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;*****TRIAL*****&lt;br/&gt;&amp;lt;trial makeDetections&amp;gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ stimulusframes = [1 = DetectionQuestion, NoDetection, YesDetection, statements_block2]&lt;br/&gt;/ trialduration = 8000&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;*****BLOCK*****&lt;br/&gt;&amp;lt;block Correction&amp;gt;&lt;br/&gt;/ onblockbegin = [values.trialCount = 0; values.makeDetections = 1; values.instructnum = 7]&lt;br/&gt;/ trials = [1-4 = Instructions; 5-50 = makeDetections]&lt;br/&gt;/ onblockend = [values.missingRespCount = 0]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="30088"&gt;&lt;span class="goto"&gt;&lt;/span&gt;&lt;/a&gt;&lt;/div&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[/quote]&lt;/span&gt;&lt;/blockquote&gt;&lt;br/&gt;&amp;gt; The question should be in white color font while the two response options should be in black font inside a white textbox. However, when I run the code all the test items are black font inside a white textbox. &lt;br/&gt;&lt;br/&gt;The default screen color is white as is the default txbgcolor, so:&lt;br/&gt;(1) You won't see the white font &amp;lt;text DetectionQuestion&amp;gt; at all against the white background.&lt;br/&gt;(2) You won't see any "white box" around the two response options against the white background.&lt;br/&gt;&lt;br/&gt;Set your /screencolor to black per &amp;lt;defaults&amp;gt;. Set /txbgcolor = black for the detection question &amp;lt;text&amp;gt; element.&lt;br/&gt;&lt;br/&gt;&lt;img 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" alt=""&gt;&lt;br/&gt;&lt;br/&gt;&amp;gt; I also cannot get participants to actively click on the textboxes to move fowards as the "validresponse" line does not work.&lt;br/&gt;&lt;br/&gt;*****TRIAL*****&lt;br/&gt;&amp;lt;trial makeDetections&amp;gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ stimulusframes = [1 = DetectionQuestion, NoDetection, YesDetection, statements_block2]&lt;br/&gt;&lt;strong&gt;/ validresponse = (NoDetection, YesDetection)&lt;/strong&gt;&lt;br/&gt;/ trialduration = 8000&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;It works perfectly fine. Note that you have fixed the trial's duration to 8 seconds, so you'll wait a couple of seconds before the next trial starts.&lt;br/&gt;</description><pubDate>Tue, 10 Nov 2020 17:45:56 GMT</pubDate><dc:creator>Dave</dc:creator></item></channel></rss>