﻿<?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 7  » Help with conditional formatting</title><generator>InstantForum 2017-1 Final</generator><description>Millisecond Forums</description><link>https://forums.millisecond.com/</link><webMaster>Millisecond Forums</webMaster><lastBuildDate>Wed, 01 Jul 2026 22:55:23 GMT</lastBuildDate><ttl>20</ttl><item><title>RE: Help with conditional formatting</title><link>https://forums.millisecond.com/Topic41886.aspx</link><description>&lt;blockquote data-id="41885" class="if-quote-wrapper" unselectable="on" data-guid="1781541422552" contenteditable="false" id="if_insertedNode_1781541421595"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="41885" 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="41885" 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="41885" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;sbashyam - 6/15/2026&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-41885"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="41884" class="if-quote-wrapper" unselectable="on" data-guid="1781541422552" contenteditable="false" id="if_insertedNode_1781538555169"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="41884" 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="41884" 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="41884" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 6/15/2026&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-41884"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="41883" class="if-quote-wrapper" unselectable="on" data-guid="1781541422552" contenteditable="false" id="if_insertedNode_1781524280009"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="41883" 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="41883" 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="41883" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;sbashyam - 6/14/2026&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-41883"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;Hi, I am posting my entire inquist code below for reference. I have coded this such that if the airplane stimuli is displayed on the screen, a white rectangle blocks out another stimuli that is displayed on scree. This works for all trials except in either trial test_2a, or test2, regardless of the stimuli presented, the right side of the screen is always blocked out. Can you help me debug this? Thank you.&lt;br/&gt;&lt;br/&gt;&amp;lt;data&amp;gt;&lt;br/&gt;/ columns = (date, time, subject, group, blockcode, trialcode, response, latency, stimulusitem)&lt;br/&gt;&amp;lt;/data&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;defaults&amp;gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ quitcommand = (Shift+'Q')&lt;br/&gt;/ fontstyle = ("Verdana", -13, false, false, false, false, 5, 0)&lt;br/&gt;&amp;lt;/defaults&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;values&amp;gt;&lt;br/&gt;/ x = 0%&lt;br/&gt;&amp;lt;/values&amp;gt;&lt;br/&gt;&lt;br/&gt;******ITEMS***********&lt;br/&gt;&lt;br/&gt;&amp;lt;item instructions&amp;gt;&lt;br/&gt;/1 = "Continue"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text continue&amp;gt;&lt;br/&gt;/items = instructions&lt;br/&gt;/select = 1&lt;br/&gt;/vposition = 95%&lt;br/&gt;/hposition = 95%&lt;br/&gt;/color = black&lt;br/&gt;/fontstyle = ("Heiti TC", 3.00%, false, false, false, false, 5, 0)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item stimuli&amp;gt;&lt;br/&gt;/1 = "lunch.png"&lt;br/&gt;/2 = "lemonades.png"&lt;br/&gt;/3 = "coloring.png"&lt;br/&gt;/4 = "puzzle.png"&lt;br/&gt;/5 = "airplanes.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture activity_group&amp;gt;&lt;br/&gt;/items = stimuli&lt;br/&gt;/ selectionrate = block&lt;br/&gt;/size = (35%, 35%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 80%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item gippy_pool&amp;gt;&lt;br/&gt;/ 1 = "gippy1.jpeg"&lt;br/&gt;/ 2 = "gippy2.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item tipa_pool&amp;gt;&lt;br/&gt;/ 1 = "tipa1.jpeg"&lt;br/&gt;/ 2 = "tipa2.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item rules_and_comp&amp;gt;&lt;br/&gt;/ 1 = "gippyrule.jpeg"&lt;br/&gt;/ 2 = "tiparule.jpeg"&lt;br/&gt;/ 3 = "comprehension.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture gippy_intro_pic&amp;gt;&lt;br/&gt;/ items = gippy_pool&lt;br/&gt;/ select = random&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture tipa_intro_pic&amp;gt;&lt;br/&gt;/ items = tipa_pool&lt;br/&gt;/ select = random&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture gippy_rule_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 1&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture tipa_rule_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 2&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture comprehension_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 3&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item likert&amp;gt;&lt;br/&gt;/1 = "smile_1.png"&lt;br/&gt;/2 = "smile_2.png"&lt;br/&gt;/3 = "smile_3.png"&lt;br/&gt;/4 = "sad_1.png"&lt;br/&gt;/5 = "sad_2.png"&lt;br/&gt;/6 = "sad_3.png"&lt;br/&gt;/7 = "OK.png"&lt;br/&gt;/8 = "notOK.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture OK&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 7&lt;br/&gt;/size = (40%, 40%)&lt;br/&gt;/ hposition = 40%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture not_OK&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 8&lt;br/&gt;/size = (40%, 40%)&lt;br/&gt;/ hposition = 60%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture a_little_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 1&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 25%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture sort_of_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 2&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture very_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 3&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 75%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture a_little_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 4&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 25%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture sort_of_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 5&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture very_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 6&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 75%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item boys&amp;gt;&lt;br/&gt;/1 = "person_a.jpg"&lt;br/&gt;/2 = "person_b.jpg"&lt;br/&gt;/3 = "person_c.jpg"&lt;br/&gt;/4 = "person_d.jpg"&lt;br/&gt;/5 = "person_e.jpg"&lt;br/&gt;/6 = "person_f.jpg"&lt;br/&gt;/7 = "person_g.jpg"&lt;br/&gt;/8 = "person_h.jpg"&lt;br/&gt;/9 = "person_i.jpg"&lt;br/&gt;/10 = "person_j.jpg"&lt;br/&gt;/11 = "person_k.jpg"&lt;br/&gt;/12 = "person_l.jpg"&lt;br/&gt;/13 = "person_m.jpg"&lt;br/&gt;/14 = "person_n.jpg"&lt;br/&gt;/15 = "person_o.jpg"&lt;br/&gt;/16 = "boy_v.png"&lt;br/&gt;/17 = "boy_x.png"&lt;br/&gt;/18 = "boy_w.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item girls&amp;gt;&lt;br/&gt;/1 = "girl_a.jpg"&lt;br/&gt;/2 = "girl_b.jpg"&lt;br/&gt;/3 = "girl_c.jpg"&lt;br/&gt;/4 = "girl_d.jpg"&lt;br/&gt;/5 = "girl_e.jpg"&lt;br/&gt;/6 = "girl_f.jpg"&lt;br/&gt;/7 = "girl_g.jpg"&lt;br/&gt;/8 = "girl_h.png"&lt;br/&gt;/9 = "girl_i.png"&lt;br/&gt;/10 = "girl_j.png"&lt;br/&gt;/11 = "girl_k.png"&lt;br/&gt;/12 = "girl_l.png"&lt;br/&gt;/13 = "girl_m.png"&lt;br/&gt;/14 = "girl_n.png"&lt;br/&gt;/15 = "girl_o.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape rectangle&amp;gt;&lt;br/&gt;/size = (100%, 100%)&lt;br/&gt;/shape = rectangle&lt;br/&gt;/color = white&lt;br/&gt;/ position = (50%, 50%)&lt;br/&gt;&amp;lt;/shape&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item black_speech&amp;gt;&lt;br/&gt;/1 = "black_speech_right.png"&lt;br/&gt;/2 = "black_Speech_left.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture black_speech_right&amp;gt;&lt;br/&gt;/ items = black_speech&lt;br/&gt;/ select = 1&lt;br/&gt;/ size = (15%, 15%)&lt;br/&gt;/ hposition = 60%&lt;br/&gt;/ vposition =35%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture black_speech_left&amp;gt;&lt;br/&gt;/items = black_speech&lt;br/&gt;/select = 2&lt;br/&gt;/size = (15%, 15%)&lt;br/&gt;/ hposition = 40%&lt;br/&gt;/ vposition = 35%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture flower_picture&amp;gt;&lt;br/&gt;/items = stimuli&lt;br/&gt;/select = 2&lt;br/&gt;/size = (10%, 10%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 80%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture person_a&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_a_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 20%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_a_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 20%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_b_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 2&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 80%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_b_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 2&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 80%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_c_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 3&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_c_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 3&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_a&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 4&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_b&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 5&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_c&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 6&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_d&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 7&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_e&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 8&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_f&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 9&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_g&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 10&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_h&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 11&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_i&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 12&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_j&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 13&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_k&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 14&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_l&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 15&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape whiterect&amp;gt;&lt;br/&gt;/ shape = rectangle&lt;br/&gt;/ color = white&lt;br/&gt;/ size = (30%, 80%)&lt;br/&gt;/ hposition = values.x&lt;br/&gt;/ vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/shape&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial gippy_intro_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1=gippy_intro_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial gippy_rule_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = gippy_rule_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial tipa_intro_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = tipa_intro_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial tipa_rule_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = tipa_rule_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial comprehension_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = comprehension_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block gippy_block&amp;gt;&lt;br/&gt;/ trials = [1 = gippy_intro_trial; 2 = gippy_rule_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block tipa_block&amp;gt;&lt;br/&gt;/ trials = [1 = tipa_intro_trial; 2 = tipa_rule_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block comprehension_block&amp;gt;&lt;br/&gt;/ trials = [1 = comprehension_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;// Group 1: Named "gippy_first"&lt;br/&gt;&amp;lt;expt gippy_first&amp;gt;&lt;br/&gt;/ subjects = (1 of 2)&lt;br/&gt;/ blocks = [1 = gippy_block; 2 = comprehension_block; 3=noreplace(test1_girls, test1a_girls); 4=noreplace(test2_girls, test2a_girls); 5=noreplace(test3_girls, test3a_girls);&lt;br/&gt;6=noreplace(test4_girls, test4a_girls)]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test1_girls&amp;gt;&lt;br/&gt;/trials = [1 = test1_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_a, &lt;br/&gt;girl_b, &lt;br/&gt;girl_c, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test1_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test1_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1_speech&amp;gt;&lt;br/&gt;/ stimulusframes = [1=continue, black_speech_right]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial judgment&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2=OK,not_OK]&lt;br/&gt;/ validresponse = (OK,not_OK)&lt;br/&gt;/ branch = [if(trial.judgment.response == "OK") trial.good]&lt;br/&gt;/ branch = [if(trial.judgment.response == "not_OK") trial.bad]&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial good&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2= a_little_good, sort_of_good, very_good]&lt;br/&gt;/ validresponse = (a_little_good, sort_of_good, very_good)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial bad&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2= a_little_bad, sort_of_bad, very_bad]&lt;br/&gt;/ validresponse = (a_little_bad, sort_of_bad, very_bad)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test1a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test1a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_a, &lt;br/&gt;girl_b, &lt;br/&gt;girl_c, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test1a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test1a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1a_speech&amp;gt;&lt;br/&gt;/ stimulusframes = [1=continue, black_speech_left]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test2_girls&amp;gt;&lt;br/&gt;/trials = [1 = test2_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_d, &lt;br/&gt;girl_j, &lt;br/&gt;girl_h, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test2_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test2_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test2_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test2a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test2a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_d, &lt;br/&gt;girl_j, &lt;br/&gt;girl_h, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test2a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test2a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes &lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test2a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test3_girls&amp;gt;&lt;br/&gt;/trials = [1 = test3_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_g, &lt;br/&gt;girl_e, &lt;br/&gt;girl_i, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test3_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test3_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test3_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test3a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test3a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_g, &lt;br/&gt;girl_e, &lt;br/&gt;girl_i, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test3a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test3a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test3a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test4_girls&amp;gt;&lt;br/&gt;/trials = [1 = test4_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_f, &lt;br/&gt;girl_k, &lt;br/&gt;girl_l, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test4_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test4_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test4_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test4a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test4a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_f, &lt;br/&gt;girl_k, &lt;br/&gt;girl_l, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test4a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test4a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test4a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="41883"&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;Please don't paste entire scripts into a post's body. This is error prone and difficult to work with. Further, if your code requires external files to run (images, etc.), you need to provide those files along with it. Helping you debug your problem is obviously not possible otherwise.&lt;br/&gt;&lt;br/&gt;Please put everything in a ZIP archive and then attach the archive to your post via +Insert -&amp;gt; Add File...&lt;br/&gt;If the archive is too large to attach here, upload it somewhere else (e.g. your DropBox or similar) and provide the download link.&lt;a class="if-quote-goto quote-link" href="#" data-id="41884"&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;Hi Dave,&lt;br/&gt;My apologies, I have attached the file &lt;a href="https://drive.google.com/file/d/10gKBTGuMVjIXgxONbNbW7iYXyyRbSYxe/view?usp=sharing" id="if_insertedNode_1781539353488"&gt;here&lt;/a&gt;&amp;nbsp;&lt;br/&gt;Thank you&lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="41885"&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;I'm not sure I understand the issue. Here's what I'm seeing when running the&amp;nbsp;cpc_girls.iqx script from your archive, which seems to match what you pasted in your original post. I gave the masking rectangle a blue color, so it's very obvious whether it's displayed or not.&lt;br/&gt;&lt;br/&gt;Here is a run that had airplanes in test2a&lt;br/&gt;&lt;br/&gt;&lt;img 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Y+3zOdSvmZsn3e/PU75xW9i0802i4suOD8mTFyiT28HECBAgAABAgQIECDQvIAApHkrRxIgQIAAAQIECBBoSmDe10L94uQTiw3Kt5svGChvfn/kwwc0XjNVft71zr2LDccPK14f9dLo6hoV5auRjv/ed+InJ/8illxyybj4rxc1ApDZYcPur981jvj0obHhJpvHuHHjowwZTj7pxPjwQQc3znfW6b+LnXbba06tfdXz6MMPxrY7vCauu/a6xs343//2V/GCF67VVK8/P+mEeOd79m88MfLxj34w3n/gRxo1PfLQA/GjH34/jj/hp3M2bR+qfS6G6wmQsuG+rJoNQMoZH/CBfePHJ548x2bf/Q9shBx33XFzfOwTh8TvfvfHhrHXXzV1qTmIAAECBAgQIECAQL8FBCD9JvMFAgQIECBAgAABAosXmHdj8HmPLEOCiy+6IFZ7wRoxZcqz8cED9oufnHTKYk9WBhLnn3dOLLnUMnHgAfvOCU0W9aXyBv5Xj/nmfIFLX/VMfvrJ2GnXN8wJKvqab/m0x1l/ObtxWPnarD323DPOOefcXr9WvgLqiSceb7yaqxUCkL6sVlhplaY3dS+f4Hnr3nvHmWeetUjSzxx+aHz2c19e6MmZvmbgzwkQIECAAAECBAgQ6FtAANK3kSMIECBAgAABAgQI9Fvg1puuj/0+8KG49bZbG8FCGX6ssMKKceYZp8WKKz2vcb7u7u64+u+XxpeOPiau/Ps/5wQQ5bEvfvG6ceC+74lddt+r8URF+Zk1a1b844qL46vHfr3X47941JHx8s1f2evN9MXV89gjDw04ACnrKsOczxxxWJz62z/O6WGjjTeOzx35ydhxl92LV2u9ISadN6klApCyn8VZlU/i7Lrbbk33Uz4xcuopJ8Wxxx0f/7r66sYcy/lutOHL4vPFBvMbbrJFv68tXyBAgAABAgQIECBAoDkBAUhzTo4iQIAAAQIECBAgQIAAAQIECBAgQIAAAQIEWkhAANJCw1IqAQIECBAgQIAAAQIECBAgQIAAAQIECBAg0JyAAKQ5J0cRIECAAAECBAgQIDAEAk89+Xi8fLNXxM033Tygsw3VPiIDWtyXCBAgQIAAAQIECBBoKQEBSEuNS7EECBAgQIAAAQIECBAgQIAAAQIECBAgQIBAMwICkGaUHEOAAAECBAgQIECAAAECBAgQIECAAAECBAi0lIAApKXGpVgCBAgQIECAAAECBAgQIECAAAECBAgQIECgGQEBSDNKjiFAgAABAgQIECBAgAABAgQIECBAgAABAgRaSkAA0lLjUiwBAgQIECBAgAABAgQIECBAgAABAgQIECDQjIAApBklxxAgQIAAAQIECBAgQIAAAQIECBAgQIAAAQItJSAAaalxKZYAAQIECBAgQIAAAQIECBAgQIAAAQIECBBoRkAA0oySYwgQIECAAAECBAgQIECAAAECBAgQIECAAIGWEhCAtNS4FEuAAAECBAgQIECAAAECBAgQIECAAAECBAg0IyAAaUbJMQQIECBAgAABAgQIECBAgAABAgQIECBAgEBLCQhAWmpciiVAgAABAgQIECBAgAABAgQIECBAgAABAgSaERCANKPkGAIECBAgQIAAAQIECBAgQIAAAQIECBAgQKClBAQgLTUuxRIgQIAAAQIECBAgQIAAAQIECBAgQIAAAQLNCAhAmlFyDAECBAgQIECAAAECBAgQIECAAAECBAgQINBSAgKQlhqXYgkQIECAAAECBAgQIECAAAECBAgQIECAAIFmBAQgzSg5hgABAgQIECBAgAABAgQIECBAgAABAgQIEGgpAQFIS41LsQQIECBAgAABAgQIECBAgAABAgQIECBAgEAzAgKQZpQcQ4AAAQIECBAgQIAAAQIECBAgQIAAAQIECLSUgACkpcalWAIECBAgQIAAAQIECBAgQIAAAQIECBAgQKAZAQFIM0qOIUCAAAECBAgQIECAAAECBAgQIECAAAECBFpKQADSUuNSLAECBAgQIECAAAECBAgQIECAAAECBAgQINCMgACkGSXHECBAgAABAgQIECBAgAABAgQIECBAgAABAi0lIABpqXEplgABAgQIECBAgAABAgQIECBAgAABAgQIEGhGQADSjJJjCBAgQIAAAQIECBAgQIAAAQIECBAgQIAAgZYSEIC01LgUS4AAAQIECBAgQIAAAQIECBAgQIAAAQIECDQjIABpRskxBAgQIECAAAECBAgQIECAAAECBAgQIECAQEsJCEBaalyKJUCAAAECBAgQIECAAAECBAgQIECAAAECBJoREIA0o+QYAgQIECBAgAABAgQIECBAgAABAgQIECBAoKUEBCAtNS7FEiBAgAABAgQIECBAgAABAgQIECBAgAABAs0ICECaUXIMAQIECBAgQIAAAQIECBAgQIAAAQIECBAg0FICApCWGpdiCRAgQIAAAQIECBAgQIAAAQIECBAgQIAAgWYEBCDNKDmGAAECBAgQIECAAAECBAgQIECAAAECBAgQaCkBAUhLjUuxBAgQIECAAAECBAgQIECAAAECBAgQIECAQDMCApBmlBxDgAABAgQIECBAgAABAi0v8PrvPtzyPWiAAAECBAi0msDpH1qh1UpWbxsJCEDaaJhaIUCAAAECBAgQIECAAIFFCwhAXB0ECBAgQGDkBQQgI29uxbkCAhBXAwECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIJqsdx8AACAASURBVECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAgQIJBCQACSYsyaJECAAIGaCQhAajaQZOUIQJINXLsECBAgQIAAAQIECBDIKiAAyTp5fRMgQIBAlQICkCr1rS0AcQ0QIECAAAECBAgQIECAQAoBAUiKMWuSAAECBGomIACp2UCSlSMASTZw7RIgQIAAAQIECBAgQCCrgAAk6+T1TYAAAQJVCghAqtS3tgDENUCAAAECBAgQIECAAAECKQQEICnGrEkCBAgQqJmAAKRmA0lWjgAk2cC1S4AAAQIECBAgQIAAgawCApCsk9c3AQIECFQpIACpUt/aAhDXAAECBAgQIECAAAECBAikEBCApBizJgkQIECgZgICkJoNJFk5ApBkA9cuAQIECBAgQIAAAQIEsgoIQLJOXt8ECBAgUKWAAKRKfWsLQFwDBAgQIECAAAECBAg0JbD0MkvHk088GV0dnbHWWmvEz04+MTbfatumvusgAnUQEIDUYQpqIECAAIFsAgKQbBOvV78CkHrNQzUECBAYdoHJTz8VV13+tzj+hBPjL2efF489+tiwrfmZww+NQz756VhiyaWHbQ0nJkCAAIHhE3j0kYdi+RVWGpYFOjo7o3vWrOjo7Cj+2d1Yo/zvHR0dMWvmrMb/fuMb94jf/vYPw7K+k+YUEIDknLuuCRAgQKBaAQFItf7ZVxeAZL8C9E+AQFsL3H/vXXH00V+Jb3zre5X3+aED94/DDz8iVln1BY2bWz4ECBAgUD+Bkf77ubOrsxF2lP8soo+YOXPmIlF+9fOfxlvfvk+/0Lq7u/3M6ZdY+x8sAGn/GeuQAAECBOonIACp30wyVSQAyTRtvRIgkELg/LNPjwMPOiRuvOGG2va7226viy/835Gx8aZb1bZGhREgQCCTwEgHHwO17erqKkKSWbHK81aO++69r6nTCEGaYkpzkAAkzag1SoAAAQI1EhCA1GgYCUsRgCQcupYJEGg/gaefeiJO+OH342MHf2pEm5s4pjNWXaYrll1iVIzrmrv0Q1Nmxp0PTI/J03peadLXZ/2XrB8ffP/74m1vf1csv+LKfR3uzwkQIEBgiAReusEG8Z9//3uIzjb8p+kqniCcWTxEWD5H2N3zlqw49ujPx8cPOXz4F7dCWwgIQNpijJogQIAAgRYTEIC02MDarFwBSJsNVDsECOQSuPbqK+MTh346zjnn3EE3PrqrI1ZfdlS8cPlRsfL4zlh6XOegzzmrePXIzY/NjGvvmRYPTV70a03mXaj87d4jPnVwfOSjHxOGDHoCTkCAAIHeBVrliY/equ/ZM6R4YVbxY6qroytmzJweZQY/o/iZ40OgLwEBSF9C/pwAAQIECAy9gABk6E2dsXkBAUjzVo4kQIBApQLle9FvvvG6OOWUU+Kyv/8zzj7rnEHVs1wRcGzwgrGxTvEERxl+zP/pK/x47tduF1dBeWeqcS+q59gyDPnXQzPi2rumxjPTm7tJNWbMmDjxh9+Nvd+xT4waNXpQ/foyAQIECESUf69Onz69bSlWWHGFeOjBh+br72tf/UIc/Mkj2rZnjfVPQADSPy9HEyBAgACBoRAQgAyFonMMVEAAMlA53yNAgMAICUyZ8mz87tRT4h377DfgFVec2BUvXXVMrL7UqBg/uq9wYyDL9AQoxS/lFnFHdxF2FP+919PMDU6mTJ8VVxavybrxvmnFb+/2veaJP/xOvP3d+8bYseP6PtgRBAgQILCQQCs/9dHfcW673XZxwfnn9/drjk8gIABJMGQtEiBAgEDtBAQgtRtJqoIEIKnGrVkCBFpF4Prr/hkHfuTjceEFF/Sr5KXHdsZ6xVMdL1lmTIwd1a+vjvDBCz9B8sDTM+Pqu6fFbY/PWGQt48aNi9/+6uTY9Q1vHuF6LUeAAIHWFsgUfpST6ixepziueHJwSpGwz5wxrbWHp/ohFRCADCmnkxEgQIAAgaYEBCBNMTlomAQEIMME67QECBAYiMDFF50br9p+p+Ld5n2/Iqp8bdW6zx8TW608NkaVj1603Kf312jNmNkdfy2CkPLJkEV9TvvdL2P3vfZuuY4VTIAAgZEWOOH4b8f+B350pJetfL3Ors5iX5DGVunFk4kdMWPGosP1yotVwIgKCEBGlNtiBAgQIECgISAAcSFUKSAAqVLf2gQIEHhO4LKLz4+tX/2aPoOPF60wOnZ40cTGxq+dbbLZ66yimTLu6eietdBrs258dHr8684p8eiUhcOStdZaK0768fdim+12dh0RIECAwAICP/nRd+N97/8wl/LnSxmEFL8oMKvYS8uHgADENUCAAAECBEZeQAAy8uZWnCsgAHE1ECBAoGKBKy69MLbYerteq5gwuiPWe/7Y2Hzl2RuAD8f+HRUDLHb5nuDjpsfK12NNjUcmz3/zavTo0XHGH06NHXfds85NqI0AAQIjJpDtVVf9gd1tt9fF6af/uT9fcWwbCghA2nCoWiJAgACB2gsIQGo/orYuUADS1uPVHAECdRe4+qpLY+fd9owHH3hwTqmjuiJetMqY2L7Yy2PhT84AZLbDJfdPj+vvmhrTi9dkzfs5+4zfC0HqfrGrjwCBYRfoGjUmurt7XvXUzKsUh72gx98rXgAAIABJREFUGi7w8IP3x/IrrlzDypQ0UgICkJGStg4BAgQIEJgrIABxNVQpIACpUt/aBAikF7jysoti8622neOw5rKjYucXj+/FJVvwMS/B/K+/KsOPC26bGrc8PH3OQeWTIGed/rvYfqfXp7+mABAgkE+gsd9F8TrBmcUrnvreQSqfz4Idd7fJKyRNcmACApCBufkWAQIECBAYjIAAZDB6vjtYAQHIYAV9nwABAgMUuPP2m+KDHz4ozjjjzMYZ1lhmVOz04gnFa8rnvX2VOfiYC9tVvLt9ZnnDqtgnZPbnvFunxE0Pzg1BPnXox+J/P35wrLTyqgOciK8RIECgtQS87mpg8xozZkxMnTp1YF/2rZYXEIC0/Ag1QIAAAQItKCAAacGhtVHJApA2GqZWCBBoLYGrLv9bbLblq+YUvWYRgOy83oJPfwhA5p/q/E+DLBiCTDrrT54Caa3/N1AtAQIDFBB+DBDuua9tscUWcdlllw3uJL7dkgICkJYcm6IJECBAoMUFBCAtPsAWL18A0uIDVD4BAq0p8Mzkp+M3v/pZ7LPvgY0GlhnXGa9YY3y8aJneAg8hyMJT7glC7nhiZvzjzqnxwHObo3/+qMPjgx/6aCy3wkqteWGomgABAk0ICD+aQFrMIaO7Ohp7ST3zzOQYP37C4E7m2y0nIABpuZEpmAABAgTaQEAA0gZDbOEWBCAtPDylEyDQugL/vPKSePnmr5zTQPn6q12ee/qjo/i387/DXQDS+6R7QpBzb54SN8+zH8j5Z58e2+24W+teHConQIDAYgS+/c1j4qMfO5TRIASWW3pCPPrEM9FRvF5x1sz5nywcxGl9tUUEBCAtMihlEiBAgEBbCQhA2mqcLdeMAKTlRqZgAgRaXeC+e+6MQw49OH5+yq8brSxVPv3xwnGxznJdz7VWBh6zb8gIPxY97x6jv907NW68Z3rjt3nLz0Ybbxz/78TjY8NNtmj1S0X9BAgQWEjA0x9Dc1GsuvJKcd9DDxVbS3WHTdGHxrRVziIAaZVJqZMAAQIE2klAANJO02y9XgQgrTczFRMg0OICV191aWyy2dZzupj36Y+FWxOA9BWAzOruiEk3PRs3Pzp3Q/QLz/1zvPo1r2vxK0X5BAgQmF9g/ZesHzdcfwOWIRTo6uiIGbM8BTKEpLU/lQCk9iNSIAECBAi0oYAApA2H2kItCUBaaFhKJUCg9QXuvP2meO++B8SkSZMazSw3vjO2XHNcvHCp2U9/zO5R8NHXtGd1FEbds6KzeFrmnOI1WLfM8xqsZZdbNs74429iq2126Os0/pwAAQItI+Dpj+EZVUdn8ZNk5szhObmz1k5AAFK7kSiIAAECBBIICEASDLnGLQpAajwcpREg0H4C1/zz8tjo5VvOaWz1pUbF614yvvjfAo/+TnveAOSpqd1x8W1T4vbHZ8w5zUWTzoxXbb9Lf0/reAIECNRSoLN4UmH+/aFqWWZLFjWqsP3MZz8VR372iy1Zv6L7JyAA6Z+XowkQIECAwFAICECGQtE5BiogABmonO8RIECgnwLlO8bLAGTjTbea8801i83Pd25sfi4A6SdndBSvvir3Sunu6LkluOBTIOW/++sFZ8U22+7U31M7ngABArUT6OzqbOxX4TP0Ah2FbbERiA3Rh562lmcUgNRyLIoiQIAAgTYXEIC0+YBr3p4ApOYDUh4BAu0jcO3VVxYbc28+p6HVluyK1647IcaPFn4MdMqNp0CK34nu7J4ZDz0zM664bWrc9VTPa0xWW6IrjvzSl+Nt794vllp62YEu4XsECBCoXMCrr4Z3BJ1dXXNegWVD9OG1rsPZBSB1mIIaCBAgQCCbgAAk28Tr1a8ApF7zUA0BAm0ssGAA4vVXQzXsuZvXnvPfYi+QeTZDf8NLJ8a3Tj491thku6FazHkIECAwogIzZkyP0aPHjOia2RabOGFCzJwxI6YX+4Dce8+dsdLKq2YjSNWvACTVuDVLgAABAjUREIDUZBBJyxCAJB28tgkQGFmB/15/TWz32l3ivnvvm7OwAGQoZ9ATgjwxpTsuuXVK3PFkz14gL1phVExcZe04+f/9tHj6ZouhXNC5CBAgMCICnv4YEeb5Fpn9FMiUKc/GuHHlayp92klAANJO09QLAQIECLSKgACkVSbVnnUKQNpzrroiQKBmAv++5qrYYKPN5lT1guL1V69bf3x0dnbVrNJWLWfRT4GUHV3y1/Niq212aNXm1E2AQGKB3gKQMWPGxLRp0xKrDG/ryy+/XDz88CPDu4izVyYgAKmM3sIECBAgkFhAAJJ4+DVoXQBSgyEogQCB9hdYMACZ+/THvL3bC2RwV0JPCPLg5JlxebEXyD1P9+wFUn5+88uTY7c93uQ3eQcH7NsECIywQG/hR0dnR4zqGhXTp08f4WqGf7myt9mfKjd8L+t4ZvJkPzOGf+SVrCAAqYTdogQIECCQXEAAkvwCqLh9AUjFA7A8AQLtL3DbzTfEG974lrju2usaza44sSu2W3tcLD9+wcBDADK4q2HuUyBn3/Rs3PpIz2uwZn8u/duk2PKV2w9uCd8mQIDACAr0FoB0dXTErCInWFxAUN7AH12EJOMmjo3JTz0bM4u9LfrzKb9fRQBR1boL2nQVm6J3dnZ6yqY/F00LHSsAaaFhKZUAAQIE2kZAANI2o2zJRgQgLTk2RRMg0EoC/7n2H/HSDTedU3L5+qvdXjqhlxYEIIOZaxl/dEZPCPJM8WaYC29+ds5eIOW/E4AMRtd3CRAYaYHewo/OruJvuZlzw97eaiqP6SgSkiXHjo7Hp0yJ8mZ++Z/pxWbqzYQa84YQwx1ILHj+4V6v2RmuuvLKce8DD8Spp5wUb3nbu5v9muNaREAA0iKDUiYBAgQItJWAAKStxtlyzQhAWm5kCiZAoJUE7r37jtjv/R+IM888q1H2akt0xS4vmRCjF8o6hB9DM9d5ngK5sXgK5LG5T4GsueYa8Yff/tJm6EMD7SwECAyzQO8BSFcRgCz+aY7OIuwYXdQ2rXtmdHV3xLabbxDnXfnvIhQpnhopQuIFQ5QyHOl5QqTn9VNdXR0xs7s7Ylbxn3k+ZTjx7LlfjMO+f25889eTBt39vGHHwsFOWUt3I7jp79Mrgy6sdChfxTVrVmy8ySbxz3/8Y/CndIZaCQhAajUOxRAgQIBAEgEBSJJB17RNAUhNB6MsAgTaQ+CGf18d62+wyZxmMjz90RHFDbqO8sbZrGj8Y8Q/PSHItCL7mFQ8BXL743NDkMsvuSA232rbEa/IggQIEOiPQG/hR7PfnziueO3VlHKD9O7o/scPIoonPx6694F43p6fj8VGJ12jY6uXrxOXHPee6HzloUUG0Bkz/va1ZpcdluO6tjm48cRLGZaU9YxcGNITwJSf6dOnxahRZaTk0y4CApB2maQ+CBAgQKCVBAQgrTSt9qtVANJ+M9URAQI1EZhV/PbotVdfERtvulWjouWKPT+2XXtCrDxx7iavc0vt6wmQ4p3vxW+lzn7FUzMtljFAd/Gu+DKIKH8LeKQ+3cValz84Lf5zz5TYas2x8eJlxxR1j+Rn7lMgZxVPgdw2z1MgApCRnIO1CBAYqMBAA5Dlll4qHn/66eLhjTHRfeUXIqYUf/t2zpNEF093FI93lBuI9JQ2+z5/40fE7L+pR+7nRV8+Tz4xOVbY7QsxfebU+Q5d1Kuyyn9f2vX1mrC+1m3QPLche/nasO7yiRifthEQgLTNKDVCgAABAi0kIABpoWG1YakCkDYcqpYIEKiHwM03Xldsur1tPPLIo42CViv2/ti9170/5r3xNLf2ngCjeJd7cfPq7idmxk0PTo3XrjX+ud9J7bvHWcV3b31sevzn3qmxwfNHx1pLdc1zg6vv7zd7RFljcXuovF3UeL/8s9NnxD8eKQKQO8rfQO7989LVx8bLlhkTS48r+hvye21zA5DL7p8eN9w1NaaUN/yKz5577h7HffPr8YLV1262PccRIEBgRAXK8Lx89dPsT0exGXd38e/6+pSvkeou/q7rLP5S/dXn94k37Vw8fVg8/dG/z5D/hdy/5ec7+rnQochl3v/t8+KEU86KCcWTGJOnTWmEE83sZzKIxRtfnb3O2/7nzXHKL3492NP5fk0EBCA1GYQyCBAgQCCVgAAk1bhr16wApHYjURABAu0icON//hXrvXTjOe0MJAApn/q464npcdb1kwfI0hEvWmlMbL7a2Fh6bPnbvYv+LdaZRXgxedqsuOGJGXHNnVNjxnOhwQAX7vfXtl57fLxk2dExqvwN5UF95r9RuOBTIFdcemG8YstXD2oFXyZAgMBwCQzk6Y8yJFlqwoR48ulnYtTojph20dHP7WMx2CcXBvv38RAoNZ5S6eljapHnjHv1Jxbax6T8s972FFlcUNLfEMVTIEMwy5qcQgBSk0EogwABAgRSCQhAUo27ds0KQGo3EgURINAOAg/cf0986MMfit/+9o+Ndp5XbH6+6/rjY/Qib+7P/5Ko8hb+rOJVUncW4cfZNzwTSy8xLtZ+4aoxccyoXnmmTJ8ZDz/1eNx932MxrfjvI/Ep70ktOWFsLL/cxFh2iWViuSXHxcZrPS/223WjePG6z++zhL9Muia+eOolcdX1t8Wz0+b+lvKay4yKjZ4/LlYpzAb+WfRrsAQgA1f1TQIEhl9gYAFIsftSd7FnRxEUdF/81TINmL2n+SALrjIAWTi8eWbKzJi4/aG97gmyYKCx8Mbqcym6iqdkuounSPp6VVbjNVjlK7CKr77n3W+Ln5x0yiA9fb0OAgKQOkxBDQQIECCQTUAAkm3i9epXAFKveaiGAIE2Ebjphmtj3fU3nNPNasXN/N03mPDc/y7DjnmfUuhlh4zinsv9T8+MP1z7dLxknTXi2PduH7ts/7IB6dx1xwNx/On/iD///Za44577ins5899UWmGFJePFq60Sr1zv+bHn1i+Ol7zkhQNaZ7Bf+sEv/xrHnnZJ3HTbA3NO9YrilV8bLDcmxvae+yxmybm+txWvD7vy9inx6LM9/+6Cc86Ibbbfeb5XzAy2dt8nQIDAUAkMJABZe6014pbb74ylildEPX7hl4aqlHnOM9JByCKeXOnojo4tjyzqena+HucPP8rwvOcXAcpXiS24cfoSSywRTxf7pBS7hTz3+sbFc83eJkUAMgyXVUWnFIBUBG9ZAgQIEEgtIABJPf7KmxeAVD4CBRAg0I4C8wYgSxavntpijbGx9rKz7+L3HYDc93R3nP7vp+Ol664exx2wY2y79XqN30Lt+Yz0jaiRndDTxaa3H/rmGXHqpKtiynNPhpSGG75gbKyz9KgYN7qZLdWfC0BGFTe4ild5nX19sRn64zPmNHLlpRfFZlu+amQbsxoBAgT6ENhy663j8ksv7ZdT+fqrUcUTDTOLTcxnXvqV2ff++3WOvg8e6Z87i3l116wxcdqFV8cbD/9xdBSbvc+MaY19T2aWT79ce3zE5KdixT2OjYcfuH9OW8svMSGemjYjphd7qXTP6PlZMGb06OKJyeb3SDnkEx+No7/2rb6pHFF7AQFI7UekQAIECBBoQwEBSBsOtYVaEoC00LCUSoBAawg8++wz8Yff/DLe/u59GwWXr7/aY87TH+W/mTcAWfDVV53x6DMz4tJbn40nZ4yKN263cfz0s28pvtOzyfjcz0jfjBqI/ewNbHteITJnt/N+vJL+56dd0XhN1vW33DmngHKPkJ3WnRAvLMKQRX9mPwHSY33+HVPjlgenFfua9Hzj75f9NTbdYpuBNOU7BAgQGDaBVVd7ftx37z3Nn78IP8YUQe/M4tWHa62xevz3lI82/93yZ1FH8XdlueF6+ZfjvD+aiictongN4/yfEfy5UwQaRXq9wM+9frRWHPrNX14eH//2qTG6uyuml/0Un67yR0PX6OIn6ozG0x8rTJgYDz/zdPEqrOf+vKN4YqS73H2r57VXjVdgFZ9yw/VnJj8d44vjfVpfQADS+jPUAQECBAi0noAApPVm1k4VC0DaaZp6IUCgFgJ33PbfeM2Ou8Ytt9zSqKf3AKT3UmcVN33ue3J6/Pk/z8ZrNl8vzjquCFHm39N7kD2O4A2shTZcfy4EWeimWnMt3X3Hg/GeY0+L8678T+MLr1t/iVh96cXtEzIX7tnp3XHBf6fEHU/1/OavAKQ5c0cRIDCyAuPGjYupU6c2vejqq64Ud97/cLH/R8T0S4qnP6IfeyfN3ly8ETYUX13w4cReqxihnyEdRfhR7GkyqE9nGeJE/OzP/47tN1kzVlt1yZ4wvrMrOrc6uDh1EYIU/7ur2C+lDD3KzxITxsXkKVN7fnoVf7bMMsvE448/3vgzm6APahq1+rIApFbjUAwBAgQIJBEQgCQZdE3bFIDUdDDKIkCgdQUW3P+jJwBZoryb8lxTi76pc1+x78efr58cG633ovjF4XvF2muuMgwQI3QDa6EAZGjWvfa62+OA486MS669KTYoNkvfaMWxseTY3pjmfwrkLzc8G7c/9xqsciP0zbZ4VfFQytDUNAxDckoCBBIK9OfvpNHFK5xmFn/NdXfPiMcu/G4sPXpyc6FBU0FHX/jD+XdnL48Jzg5pFvq50kud5T5Xffzdft/902LVvT4VpeEKy0yM+x56PEZ1dRZPfoyO6TOnlXHHQieeVbw+qz/z6UvQn1cnIACpzt7KBAgQIJBXQACSd/Z16FwAUocpqIEAgbYRePyxR+JLX/xcHHPscY2eil8sjTWWGhU7r1e+NmPxAcis4uAHGxufPxU7brF+nD3kT3/MZh7OG1fzjnLBG0hDt+6dt94f+3ztj/G3a/4baxchyCbLjY6lx/Z2/rnmf7lh8pwA5DOHHxoH/e8nYrkVVmqba08jBAi0vkB/brCvuNwy8dCjjzeeYJhxyTEVND90f6fPLb6X8GPBN0AORafFa7HGbndETJv2dM/P6uL/yn1EonN0bLruKnHq594eF199R7zrK6cUAVP5CqzywZHOmDplSowqNpr3aW0BAUhrz0/1BAgQINCaAgKQ1pxbu1QtAGmXSeqDAIFaCNx60/XxonVfMqeWiWM64xWrj4v1lu/7hsn9xcbnf7zuydhwvbXi/33i9bHhBqsPU0/DcdNqwVIXtdHH0K2952EnxR8v/Fdj4V1fumS8YKnit3cXWrYnAJlVvNf97OufnhOArLnmGnH6H38bL3nZy4fJ2GkJECDQf4H+BCCdxd4ds2bOjAkTxsbkC79cvNGpHxss9b+0Xr4xdH+f95x8ZOt/ZMq4WGH7DzVWLvf66CxeuTV+dHc8ddGxPYlH+SkCkWuvuTk2+sB3Gr/DMHrMqJhShCCN73iCcEiuoipOIgCpQt2aBAgQIJBdQACS/Qqotn8BSLX+VidAoM0EFgxAlhvfGa9Zd2IsX/yzr0/5+qs/Xvd07LDp+nHed/YfxptBQ33TqrfOmriR1Xg/e1FLWc6sAdRU/FruHkUIctpF18QuL10iXrhk8V73XpFnFcHHzLji9qnx6JTndkEvjvvHFRfHJq/Yuq+x+HMCBAiMmEAzN9Ubf1uWm3PPGlX8lxkx47JjorPYDL3YyKL3Osub+eXjiMP6GcDf4fPV08TPjGGov+OVxV4g5b4gxaera0zM+NvRhW2xB0vDtvzZNDO6i03my/8btfWnY2ZHsY/UjFmN/UDK/zQzr2Eo2ykHKSAAGSSgrxMgQIAAgQEICEAGgOYrQyYgABkySiciQIBAxIIByMoTi/0/Xjqh5+bUYj73PdNRhB9PFRu1rh3nfmvf4pdOi+MHEgo0PYTB3qxa3EJDeSNr8XXu8ckyAPlXrFKEH1uvOTFWmlA6d8cNj02Pf9wxI56aMqPnPmFHccNqgc3kBSBNXywOJEBghAQWvKFevnZpVrnRR/FZZuml4vEnnmw8rbDMhDHxxLPTih0rOmLKpV8rwo/ymEX8fVk8ARfdc8Pf4WtloD9XhvJnRj+6Kx4ZPObkK+LTx/8+ZsycHn//0UGx6QYvXPQJukbFyjseFg8+8WystPJK8cD9D/RjMYfWSUAAUqdpqIUAAQIEsggIQLJMup59CkDqORdVESDQogILBSDFBuh7NTZAX/Tn/saTH5Pj+SsuHfu/Yes48v2vmbtdyLA7DPSG1eIKm+dmVvEbsnfd81iMGzs6VlxxyUF0s2CdPZvcvuXwn8XvL/hXzCxu/r2ueApk9SU744mpHXHpbc/GHY9PK6KQRd9YE4AMYhy+SoDAsAjMDkBetuHL4rrrriuC27l/h5XBx7hi0+7p02Y0HvboLt7J1H35V4qfF32/YnFYil3opIv7eTLv38XlcRWFHrNrLp+IKVPxruLVV1seVvzX4ufFNT+ImNyzJ8giP8XPnY4tP974Y5uij8xVNRyrCECGQ9U5CRAgQIDA4gUEIK6QKgUEIFXqW5sAgbYTeOzRh+Oozx4Rx32nuJFSfFZeTABS/r5ud/HSpoefmRm///fTsf3GL45Jx3+geL3GSPym7oL0QxWEzH+T6xPfPCO+8atJ8Z2D9ogP/s+rBjnvXm6aFfewXn/wSXHGX68p9gAZE1usOT7+ec+UuPXRabHXdpvEJmutGpf/96645J83xaNPPdsQLz8/P+mE2OvN/xPjJ5Sb0/sQIECgHgLzPgEyKrpiZvEEyI2nfjK+/bNJ8e3fX/rcXhXlT4+u4tVMo2Lm377aeE1TPT69/RypOOjoE6Yjxr768EYAMq18/VVfnyIAedm7vh3/vun2eMUWm8fll13W1zf8eQ0FBCA1HIqSCBAgQKDtBQQgbT/iWjcoAKn1eBRHgECrCdx79x2x55veGldecUWj9MUFIOWf3z854g/XPlney4rtNl43zv/O+6tpudzMdbD3qcodyOc7R0ccUgQgxxYByHf/d484sAxABrvGgjpF2W878hfxuwv+GdOmFzcFy/ddFZ+37/iKOHq/HWK15y9f/LsiJRnVFV/43tlx/Gl/jXseKryLjydAqrnUrEqAQO8CZfhRPpgwtvirbMlxS8eDFxz13Kurev5eG/PqT8WM6dPnPNn2hX12i8MP2AHnYASKpxQ7tz+kCEBGRffFRQDy3OvGFnnKRg7fGeO2+VRMnTmlsQ+IT+sJCEBab2YqJkCAAIHWFxCAtP4MW7kDAUgrT0/tBAjUTmDBV2A9r3gC5M0bLVm8qKSzeE3Twr+le//k7vjTtU/F6i9cPj7xxm3jg3sP7abct932QHz2/10c40d3xQ+O2KOJV2sN8EmQ8iZQGaIskHB84pt/jq//6rz42oFviI+/Y5vo6CqSnqH8NDb4iNjt4J/Eny++tjhzR6yz5qpx6mF7xcYbrjn/SsWNxWuuvT3ecfSf4rr/3t74TeoyBNl4062GsiLnIkCAQL8FRhVPcxRpbfE32KyYfvE3iv86pbgZX/67eW6wFz9COrY5pPh3PXuCdF98TE/A6zMIgeIVWMVG6B0dxdM0lxQBSDNP0xT8o7c5NGZ1dsfMSp7YHES7vtoQEIC4EAgQIECAwMgLCEBG3tyKcwUEIK4GAgQIDKHAggHI7FMXv9dbPJzQGaOLGybrvmBMbPW88dFRvH/8gWe647RrJ8erNlknzv9+8fTHPO97H3RZRTbwqzOuiv/5/Cmx767bxAlHvnH+m2m9LjDAAGQRj3Yc+q0/x9dOnRRrFgHP0e/ZJd608yaDbqu3E7z+kOI1WH+7plDuiIu+vn9ss9WLF7FOcTNxzOh45Xu/G5dc89941zv3jqO/ekyssuoLhqUuJyVAgMDiBMonCA54//viRyeeVIQZo2PWhV8q/lmG5WX40cun2Pxj9LaHNjKQyX/7YozpHFMRcA328RiKzrtnFN5jC89ninSp+Gczn/IJnVd/Mp6eOSNuv/XGWH3NdZv5lmNqJCAAqdEwlEKAAAECaQQEIGlGXctGBSC1HIuiCBBoVYFFBSA9/ZSvN+mMMcWrol70vLGx9apj49anIqaPWzku+mG598fQvkrjkstvig8ef3b864ZbY9/dto4TPvOm4XsCZBEByAMPPBEf/95Z8Ytzr4jvfnSvOHDvVw7LaG+65d7Y56unxWX/vjku+triApBi+eLJj8ceeSpe84mT4+obb4mr/35pbLjJFsNSl5MSIEBgUQJl+NF47VXj6bnOYkPzIvzobUPzOU/YzT7TjBi91SdjRvEzpfvyrzXx9/oAZlC85mnJHT8dT11Y7DEybWrx42uBJ03KJ09m9TyJ0q9PZ/EUYLn5eH9fHVXU07H1wbHMkhPisbM/XSxZVfBTLF3U/rkTz4+jTvxzrLrqqnH3XXf3i8DB1QsIQKqfgQoIECBAIJ+AACTfzOvUsQCkTtNQCwECLS/QWwBSPpVQPgFxxNt2KN7fPisO/Ppv4gXLj4rtXjQxfvr3p+LVG64dF/6gCEAGcC9pcWC//vNVsXfx9MdL1lkzjnzbq2Pv121U3rlpwri/T4Es4pzF/bFpU6bF/37jrDj+DxfEdw8qApD/2aaJ9ft/yG233Bfv/OofY+mlJsR3P7hTrLnWKos5SVlvZ2y9//fj0utuit/88uTYbY83xbhx4/u/sG8QIEBggAJlANJV7E9Ufh740//FistNbPJMs+KV+3+v+Pvrzpg86fMxfnyTTy40efbysLPOvzF2O/KkmDC6O578axHMzOjnz4Uy4Jgddsy7bmO/qUX8zGgEQeWPqV7+fNzoGPfyg2Nq54zo/mvx6q9my1koPOoHwuIOHTs6OjY7qPHUpn1Ahsh0BE8jABlBbEsRIECAAIHnBAQgLoUqBQQgVepbmwCBthO47eYbYp31Npiz38cG66wRV/7g/TGucYOqM26+6e7Y7mM/jnseeSK6it+oLX+JdrtNXxxnf3v/gf027WIEz7vw3/GB4/8Ut97+ULxvt+IVWEc08wqs8oRN31la/PzKe1hdnXHw/2fvPOCjqpYw/m1LD72XUEPm2R7NAAAgAElEQVSvD6R3EQEBBRtYELtiAwsiIAioCIoIFrCDgiAWioCIBZCqgvTeCdICoaRn25tzNwkBAtndbJIt3/Fpwu4pc/5zuff3zndnZtJivDvnD3w0+DY8oSJAnNFgXL0y5BCqu6TBGnpHC7RrWVudoOU4w5MTFklkynrJOhOCNSt/R+16eZOeK0dD2IEESCAgCdgkgsJoMsIYHIq0P1536r6lgQqSB4dFxjZ/AZYN70oYYc73O9cB26BrORS2VW9AZxJxWKWKcqUp4cEodkrKLqdbUCSQclGL0ruq6YLk2TkLK9eth339RGdu8Y4p8koAUU90qR2imi2nwulOA2DH/CJAASS/SHMdEiABEiABErhEgAIIr4aCJEABpCDpc20SIAG/IqBygdes3QBpaWmoX6MKtn79TLqokeUwR86Dtu04jEaPfqgdmrRtXBN/fvkUkGz2OIt1WgqsX7F59wERQFrj85EigDgVZXLl4ZM6wMr6mQsHWjLy+UlLMEnqgEwd3DvvBBB36Mk2mksUyD+7DmDLxr9Qv9EN7szCMSRAAiTgFoGRw4dIDaLJuLh2PILcSSclSbBU3RCP1o7K2IkSPAxqbnXvv/TgsCQlwRgW5tZ+MwddU5SQtQxS+8SazfNQJ5EyaclAsKS+cuo5ljsTnRmtb/miSO2MAHGGlbf1oQDibR6hPSRAAiRAAoFAgAJIIHjZe/dIAcR7fUPLSIAEfIjAubgzGDN6JCZ/MA31qlXG1pnPXjeiY/uOo2jwyGQ5vNKjbaOaWPmhFED38KnO2n9EAJn6K7bIAb9rAkh24N0veOsQQH7HtEG98Xjftq7nfs/D60ATQHZSAMlDxJyaBEjgGgQc6a90sK4eJz8dqbACsuVhlEZe8tS3HCLyh1VKoUi0TEb6rrxckHN7jAAFEI+h5EQkQAIkQAIk4DQBCiBOo2LHPCBAASQPoHJKEiCBwCKg8n8f2LsD0XXqo3aVCvj384EICc45J/umrYfR5PH30UZFgUwTAcTDb7X+vfEAnpYIkA1S5+IhrQj6HXnzpnAO7s4QQJ7v2xnD7m2D4iUkzYmXNCWA/L19P5584mGMHj0WJUuV9RLLaAYJkIA/E1DPDZX+yi4FwW1rJKWTLzRVCF1nlQgNMdYTB/7XqwfiAzx0LV/QrExMiEdYeIQPWEwTMwhQAOG1QAIkQAIkQAL5T4ACSP4z54qXCFAA4dVAAiRAArkkEHNkP6IqRyM8KAidW9TB/PH9Zcac00TZbVYsX70HXUdMR+dmtbHknQdzacnlw08cj8MbM9fiw3nLPRAB4r5pL0x2RIC0qheNtx/qhJbNa7g/mYdHtn3yE6zZuhdBpiBs2rCOdUA8zJfTkQAJZE9ACSB6iQDUGY1SZ2OCU8+MAmcpYg30kqJK/XS5XZlKUSZQab9UISwtxWLOz0yXl8zjARkCyMUL5xARWZhRIHnM25PTUwDxJE3ORQIkQAIkQALOEaAA4hwn9sobAhRA8oYrZyUBEgggAkcP70OlKjVQp1ol7FCpr1xoW7cewV3j5+HZXk0x8O42Lox0oqucKX27eCP6jv0GD3ZviS9G3i5nTM4WOHdifie7XLyQhEFTfkHTGqUwsJ+kwJKC5d5y2HXm1HncOGQmth84gm2b/kGd+v9zclfsRgIkQALuE8gUQEQAsK1+RzQA3xMAnN69SnFlUCm+5Kd2/7+iycsAUDU+8v/x5PQWsusYJjVAkmVPPXp0w/z5P8kWAziNWa5I5v9gCiD5z5wrkgAJkAAJkAAFEF4DBUmAAkhB0ufaJEACPk8gOTkJc7+ZgScGPocurepiwTjnoj/ya+PfLtkgAshs3N25KT5/6VaEF8pl8dr8Mjyf1jl9+gJueulrbN17CNu3bEDdBk3yaWUuQwIkEOgEMupG2NdKCiwfO/x3yXdS60TfYrA2xC4i/ON3dYPFYkWtqNJ4olttRERIsfXcNIMdiRdSEB4RmptZXB7b46WvsHj1FlSqXAmHDx12eTwHFBwBCiAFx54rkwAJkAAJBC4BCiCB63tv2DkFEG/wAm0gARLwWQLHjh5CtehaqFqxDHbNeR6QQx1vanOWbMQ9b8xGycgIDLytFUY90cWbzCtwWy6cT0SHQdOxec9BCiAF7g0aQAKBRSBTAFknESD+rIBotUN0aPn4p/hnyz4JAkmDJP+SoA+jlBMxo0LZSjg65znAKM9Pu0qJlaXpJapCixARhUhFkljldy+JtLhlyAwsWbUVFaMq4uiRo4F18fr4bimA+LgDaT4JkAAJkIBPEqAA4pNu8xujKYD4jSu5ERIggYIgoASQytVronpUOeyeJQc46oDGi9qK1bvwxLRlctSkxyt3tED/227wIuu8wRQ9mj78ITbu3E8BxBvcQRtIIIAIOAQQHex/TXIc8gdgC+o8AubkFE3f0IrBm80ihEidER9otwydjiUrt6F8hfI4FnPMByymiRkEKIDwWiABEiABEiCB/CdAAST/mXPFSwQogPBqIAESIIFcEIg5ehBRlaqhZtUohwDihS0uLgEXLyahcuVSnrHOkF60Vr2J6+tN3kxu9tCH+IcCiK97kvaTgM8RuJQC6z3RQfzgfuqmB8p2fRWnLqhqGvIOwb8fAalJbs6Uv8O6DP4Mv67fhbLlyuK/Y/+xCHr+4s/VahRAcoWPg0mABEiABEjALQIUQNzCxkEeIkABxEMgOQ0JkEBgEsgQQGpVi8Kumd4pgHjEM3IyNfHrFRj55TKkppphyyzYq0ONyhVQqVQRPNW9MXp1aeAt9c2d23YWAWTm9E/R585+CA0Ld24se5EACZCAmwQyiqCr4fb1EvngXcGDbu7KzWGS9krfZjjstiQUCgnCheXj3Jwof4fdMvQbiQDZqAkgx/87nr+Lc7VcEaAAkit8HEwCJEACJEACbhGgAOIWNg7yEAEKIB4CyWlIgAQCk4AvRIB4wjM/LN2E4SKA7Dksb7lmTqh+s8uh1aWTu/u7tsAbA9qjYiUPRZt4wvjrzSEFeZs+8pGWAmvQs09ixIhRKF6ydF6vyvlJgAQCnMAlAURSYK17V2jYApeIeoZIqQ9j65elxIdVBKEp8mhJEx7eXRle1/pFcZsd3brdjCVLlgau/3xw5xRAfNBpNJkESIAESMDnCVAA8XkX+vQGKID4tPtoPAmQQEETuCSAVJAUWIML2pz8W18OqeKT0jBm+kpMnPObJoJISVslh6B3p0Z4o38H1K5ZMf/scXslSYElNUBUCqxnnnoMI0eNRomSZdyejQNJgARIwBkCNpsNpiATjDYjUv8aL8W9A1gAUcBE67hz1I/4/pc1qFW9MnZ9/YwzGAu0j7HVUImGtCAxPp6RgwXqCdcXpwDiOjOOIAESIAESIIHcEqAAkluCHJ8bAhRAckOPY0mABAKeQMAKIBmezyj6rtdj6rdr8PZ3K3H4RBwmPtEDg+9r7wPXxyUB5OmBj2HUaxRAfMBpNJEEfJ5ARgSITm+Abd07EkkQ4AKI7H/R3/+h5+D3UKJwKGKXjnWoIt7YVMV2axr07V6TSJVUWMwWrf5HRk0XbzSZNl1OgAIIrwgSIAESIAESyH8CFEDynzlXvESAAgivBhIgARLIBYGAF0CuYDdy6jK8MetXqMO9d5/siUHeLoJIPfemD6oUWAcw8MlHMHr0WEaA5OLvA4eSAAk4TyA0NBTmlDRYNk0CUiw5Dhz93kKMGtQrx34+2UEEhEfGLsDni1eiaGQo4pa9Idvw0sIoItboWr+kYQ4PD0NCQqJPIg9koymABLL3uXcSIAESIIGCIkABpKDIc11FgAIIrwMSIAESyAUBCiBXw3vlg6V4a9ZvmPRULxFA2uWCbj4MlUO3Zg99pKXAogCSD7y5BAmQQCaBud/MwL39H0SNqBLY8e2wa6fBkhSDF1PTUKTzq7CtmeB/BA0S/WKRCIr2wwFzKupVK45tM4XHdZsRny/6F0+8OQPnFo1BRLFw17moqBuJXnSpyTPDbLYiuOMQ2C12nDgegzJlK7g0BTsXPAEKIAXvA1pAAiRAAiQQeAQogASez71pxxRAvMkbtIUESMDnCGQIILWqRmHXrOd8zv68MHj4R79gwje/YcAtbTD6gTYoV654XizjmTnlMKupCCCqCPq2zf+gXsOmnpmXs5AACZCAEwQy0ibZ/5koIsA1Bhh0WLl2F24c/Dksa6Rgus7qxMy+0EUiPHRS7Nymh07qaTia1JLaKBExaSol2HUiQGxpiL5nIvbHnJXxMubvyVpaKqebzQC9RHHY1rwp1ddDZQ411pmIk1ToWjrEGZ1eB6vFytRXTkP3no4UQLzHF7SEBEiABEggcAhQAAkcX3vjTimAeKNXaBMJkIDPEMiMAKkWhd2zpQh6oBeyFc/9u+Ughn65HAajEeMeaI9G9St7rT/3HjiO3qO/x859R7B9ywbUbdDEa22lYSRAAv5HIEMAebp3W7z/yp3yDDFfvklVBkNnQMWuY/DfhThMfqoPnrmntW+AkFSIx/+LRbkKZQCDQfQF2ZvSNXQSdSFRLf8lGGVfz4nsINEf8rn2U2+FbbUSeXISI2QOuxXV+4zGkVOpsIoopIkZOqNTOsbNz36OZRt3OtbVh6B57fJY/5kqvK7EJQU9fX31q4oUUTbbU6BrO0K6OL5TqR7ZfJMABRDf9ButJgESIAES8G0CFEB823++bj0FEF/3IO0nARIoUAJKAKlcNRo1KpfDrrlD5A1eOTwJ8GK2GQKIXor7jhvQHo0bVClQH11v8RaPTMVfO/bDZDJh88b1qFP/f15rKw0jARLwPwJ6gx52OV8PFn1gWP8uGPlYl8s3KcJBhZ6v4dSZi/J4sSFhxUSEB/sGhwdfm42vf9suASs2WPRmGEX0kHLhknZKpA71Q/6xZr40oEPRcCPifpfaH3aB4UxTk+hMiGj7PJKsVhEkDLCvF/HEqUgQi0SADBX2DhHDZJIoFATBbDOJ9BGvBdnodUGoX7sSNu/eLz3sMIkQZZZ1VGP0hzMO8t4+FEC81ze0jARIgARIwH8JUADxX9/6ws4ogPiCl2gjCZCA1xI4eeIYbu56C/bt2Y0ebRtg7th+17V1154YPPj2InnT9HHp52Luca+lcLlh3/78L0bPXoPo8kXw5gMdUbdWRe3w6JpNHWKp7/P9ZVo9mj86Vep/7MOgZ57EsOGvsgC6j1xjNJME/IWAwajUDJEFRASR43uY7Tq8eGc7THixOzZvPoL/DZwqgQ4qbMLRHKmy1M1S3Tc91Iw6VL9tDA6dTIR11TiZ2jNzf7N4I+59/ZscjVSrnRbho0REhLxAkHMx+KsmNEtR8o7DRbSwYNGYvujeRVIZOhGdYZf6H9X7vYfjB48iVQlR6eJGjgZn+MKJNZydi/3ylwAFkPzlzdVIgARIgARIQBGgAMLroCAJUAApSPpcmwRIwOcJ2CTaY/eOzVrqpNrVK2Hn14NkT5cOqy7boJzy7N57DP0n/IS/vxiYmUbD5yFkbEDe6rWkWfHS+8vw3tw/8O7Anhh8f/sct/fYm/Px6U+rMWtYX9zT8wbp74oSIn1lXe2NYW2YE2PlgFGdHbYU8WP99n3am7xbNv6F+o3U2mwkQAIkkH8EVAqsTp06Yc3KVUi9Mv1VphkGFClZHPFnTuPLp2/G/fdcESXirrkqWlHSSE2cuR4vTVuICiUjcHThSJnNMwKIehaePZOKMre/JjU9rLCqe7WaXdJJKVHHKJF3hxe8jnJFJW1VbppRojdueCHz2Wtf97b87toLBmHthyBZbNTJOHv6c0Qn9pqMBjHdhjBTKAymICz76Ru07NCd6a9y4y8vGEsBxAucQBNIgARIgAQCjgAFkIBzuVdtmAKIV7mDxpAACfgigZgj+xFVORq1o0UA0eqAyBusUpT1qiZvm+7bfxz9x83Hus9EAFF5T3ylie3amVhGei8tP7t8kLEF0R/GffY73pj5O5JSVFFbO959qhcG3ZezAPL4mwtEAFkl6UagiSB393C2ELkddwyfhXkrN+OjQX0woEcTBIcGCdeM/O1X+CBd+FDIH319Hr5b8Q8uJqeiWrVqWLzgB9So3cBXvEE7SYAE/IyAEkLeHDoQw9/+FHqbHMSrMhm2ICmFkYrHH+qDqdN/1B4Zj/dsg2nDbvPM7mWRz79fjUfenafVuLCvHu+ZefN7FpOY3/QFGCQdls0k8kWaRYqiiwhidV4EmfDZUrz8+a8IDQ5CcuqlYupzpr+PvgNUbRCFKAjR0ZWxb98+2FjvK7+97NH1KIB4FCcnIwESIAESIAGnCFAAcQoTO+URAQogeQSW05IACQQOgSOH9kodkJrahuvI4ciOr5/NNv3Grj3HUP/hKaIN2NC8TnWs+/QJn4D0zlfLMeSTxZqwUKlUMRQvXgxGSReil7duQ01GnIyLx77DR2E2p+dGF2Fk0sBeeO7+ds7tT8SURyUK5LNFazSNZY6IIHfd4oQIImdbvYZ8hZ9WblGlc7W1gsWe3yY9hNbNxB/phWozjTDIW8aSaP/pMT9i9rL1iItP0qI/Nm9YhwaNmztnK3uRAAmQQB4QUAKIuq9a5T7bplkjDB74EHbu3ohR47+Ww3aL1BA3yndmuf8WQuzCUZ6xQObVtx8p0Qxm2NdOknu8G+mnPGNJrmYp1HEI4lOsCA8KUYEmklDMLIXUR8ucoc7PG2qArtEg7VlyKQJEhkvdj4zUWNWqVcLBAzHyDHc869h8lwAFEN/1HS0nARIgARLwXQIUQHzXd/5gOQUQf/Ai90ACJFBgBE4ej0HHzl2we9fuTBvqRVfBtm8lFVaqOiRxpPzYszcGtR98LzPoo0W96LwRQCRdhxZKYTanR0LkHs3bM0QAmbbouhM55AcderRvhDcHdES9WhUy9+6UBTLBI2N/wBeL10kqsShMffImtGtV+/pDZZ8//7ENQ75cge17D13R1xEFot6itqdH4zgOtq6Outny73oKIE45iZ1IgATyioASQHJqjruaRGpoKZ5y2expaPHoNGzYcRSWfz+Q51VKLicsgOECZPHy7bh12Cypha6DedVohIugo6IQa1YMx+65Y5w3KtQkAsizUodFtPOrniYi+KuARxHrVdF0O2t/OM/VS3tSAPFSx9AsEiABEiABvyZAAcSv3ev1m6MA4vUuooEkQALeTCDm6EFEVaqWrYk1q5bHR090w8SF/2DJ6i2ZfSpXKIFBt3fAc31benRre/Ydx8tf/KFFYnzxQk+ULlvMY/NPmfUnXvl0qaQGEWFFez9WiQsiKMhhkBIWenVoLMJHe9SpqYQP99p/x87i8SmLsXjVFswZ2Q93d1eFbHOYSx1EyaFUryFfC+Nt8oZ0TgOuno8CiHv+4igSIAHPEXBGAIkIC0WCRQSQlS4c7F/LRFUKqdUQOdW3ok610tgxU373pSZpGQ8ePow690yFRQqnn5z/EkqULIUzZxNRsudI7flkW/OO0zuaPON3DJq2BOFhEUhMSpJxDrFcJ1E55UuXxPFTZ7RnX5qkxzIYlEzC5ssEKID4svdoOwmQAAmQgK8SoADiq57zD7spgPiHH7kLEiCBAiKQrQAiBy9atEFGvQx1iKJKq8qZSZikaFKpOlrUqyoRIE96xmpZ7+K5RLz/3Xq8+vkS3HPzDZg5um+2abg8s2BezKLDmdMX8eikBZi/YpNG7PtR9+D2rv9zYTEduj7/BX5Ztz1TnNEOsLT0WDqESfqr0mWLSpqUCBw89p8ccqU6DrhYBN0FxuxKAiSQFwT+Wf8nmrW8fs2kkUMew5gJ0yVd1ThN+M1VsXK9EcEtnkOaHPAH6YKwfMrDaNWoSu7mzAsw2c1pDMKBfUdR89535Vsr/vpyKJrULOnoGWJCaLNBEoBpFAHkTaf3o2v5ghYxGBYSjKSktMw0WHrhUygiAvEXE7W0j2lpjvogKgrEGdEqv5BwHdcIUABxjRd7kwAJkAAJkIAnCFAA8QRFzuEuAQog7pLjOBIgARIQAlcKICUkj/gt9Yphw1k9dhw8lc5Ih6jiEejZNAonT8Vg3rZ4NKtdzWMCSKq8kTpDokyeeG8e+t3YDLNeF/Eji/jiK4567M15+ELqgKgoDiVaDOjeBq/1by0RNukHWzluJEMA2YEWkoKrdmEzTLpUOaSyyFu8IelFa63Qy7nhzzsTcOTipXz3Wzf9jfqNbshxBXYgARIggbwikNOBepXKJXDoaByWv/4AOnSuK2f/OafNupatGzbvRouB02HZMkFSP72AYF0IUtZIZInUIPH2tvvwWdS/701YrEEYcHNDfPlqb8AQnGm2Q8zQiwDifKowvYyR7GLy7JR0V/L8saYnwtKiPbTnqXwp/7NYfLNOirf7NL/towCS38S5HgmQAAmQAAkAFEB4FRQkAQogBUmfa5MACfg8gewEkDsaRsgZkh4GeUu1UHhhpFnMSEw8Ly/s2hCbrMPi7UloXLsS1nqoCPqiP7ai1/CvcFfnppgzpl/6m8G+hdYqNUsGiAAyc+nfuP3GG3Dg+Fls2XMQ3796H/p0beT0ZrpJBMjSdTvRuHpJNChiQ6hRpezK2hxpTX7emUwBxGmq7EgCJJAfBPSq4HY2dYoy1nbUAAFee6QrRj1wIyARCe62Ip1H4EJyKuxr3sKC5RvQe8T32uy2vyc7akh5aYuXAuRF2r6sRWDMeK437r+jhQgTxsutVbWwbBLhZ7vi8+vsKbjVSzDLnBkF0LN21dI9ygcmg04iQFgA3UsvDZfMogDiEi52JgESIAESIAGPEKAA4hGMnMRNAhRA3ATHYSRAAiSgCGQvgISlw7n6cOpCqh4rDptRsXxZ/PX5wFxHaqQkp+DzBf9g+BfL8FC3Fnh3UHcRQLz/Dd7Lrh554/gRFf2xZDUa1qwqdVO64OOlmzHjl/WYPbwf+naTNFhO7UmHbi98iaVrt6NZrYqoWygFwXpHmivVbDDKC7zq7d2rRRBGgPDvMwmQQEETyIgAMUnUgdl69UF7Rt2lKkWCcXDxW3Lw77iXudNC278iERR2mFWaKLkHt33iY/y98zBubFwTS6bcJ5+Z3Jk2D8fYsO9YAmr1HatFaKyY8hxaNy7n5LMhZ7N0rV+CQThYRWC5VgsODkZKig8Wi895+wHXgwJIwLmcGyYBEiABEvACAhRAvMAJAWwCBZAAdj63TgIkkHsCrgogVmMoTiWH4mSqAX99+rgY4P4bvMr6JRL9ccvwGdpG+t7UFLPHSgSI63XAcw/CnRnkrVpl7GNvLMCnC1fBICLHrGF34+4eTfHA6Ln4aulfGPFQVzx/ZysULRKh9c2paTVA/tqJ2xqWQ5lQydVuc+Rrd7TLDwuzRoGsWvELWra5kcVtcwLM70mABPKMgBJAlMjR/eZOWPzz71eto2pU6OQ/Urdc6oBIgW+tDoh7Td/6RRkvdTJWSdorqQEiNz+Et3weqvqF+d+PgaR49ybOi1F6Ewa/9QOmyHNCJ+mo7ujcUKId+3tmJYnMRGgIjI1fgFUvkS+2azMtXrwEzpyJ9cy6nKVACVAAKVD8XJwESIAESCBACVAACVDHe8m2KYB4iSNoBgmQgG8SuL4AovZ0ucCh0qvHJlixMdaEZ/q0xQv3X7/obU5UlizfhluGTdfKfKtjm3tuugGzxqoC6DmN9ILvxegn3lyAj9WhlvwzU8SPe3o21Qx7avwifPnzWkRXKoePn+qKFs2q52ywHB5qAsj6HehZOwLlI68Ul64tgDxwf1+8Nf5tlClbIed12IMESIAE8oCAEkBMBhMiwoJxLj4hmxWUQCJahfzHvGZ8rup1FOn8KhKTktCwbhVs+PRpmUvujzoTdK2lfoak4rKtmygFLyTaQaWXUt8VVLOloPmjn0h0ylGxxY61HzyOlk1rqNrnnmkyZ58XZ2Heqi2oVKYEjpw8fdW8SpRSwojOEASr5VJUoWcM4CwFQYACSEFQ55okQAIkQAKBToACSKBfAQW7fwogBcufq5MACfg4ASWAVK4anV5gG1BF0O9omJECS23uSgFEj9gkG+ZtuYCW9aOx5pMnckVg8R/bcPfY2ahQrgQsEu1wXgp7P3RLS0wY2Enm9eJUWHKg9NS4hfh4/kotLuProXfh3lubXWIhqVnuHTMXDaqWwlN9miMiMivTayCTA6qbJQXWMhFAetWNQLlIyQN/Wbu2AFKpciUsW7IQNWo3yJU/OJgESIAE3CWgBJDo6lVx4Mh/sJmzP2hv174R/ly1DZs+G4RGtSUFlLtN7rH6Ni+J0DHh0nNK1le6grHVi1qkxdFF41ChTIjUBCk4AaTFgA+wef8Rza4ts55HncqyZ6nV4bEmU+laDZHprGjftjVWrlpz1dSqoHqVyhVx6GCM6CCeUl48tgNO5AYBCiBuQOMQEiABEiABEsglAQoguQTI4bkiQAEkV/g4mARIINAJxJ2NxdNPD8TsOaqAbHYCiPr0chFECSA/bk9Aq3rRWP2xSoPlXtPqfyz8BzN+244pUjfjZFwi+oz8GjWjK+OVvu3Qv7s6zPfgQZF7Zl49SsJgBo5fiGkL/tTsmz7kDvTvLYVsr2wqXMaFFC8J8cm49ZVZ+GPjLvSsG3lFBMjVB3hXFkLfvmUD6jZo4qldch4SIAEScIlARgoso0RiWKVekc169X3LGBQCuzlNDuJ1Il5IHZDcpFFU4STZRXeYU6DvMEKriXHs53EoXVwEaEvWdIIubcv1zhJ0khKXhvDur0DpDXaYYP97AkSTkSAQz4oxp06fQYU+4wSDHnapqaLSi13edChZPAJxZ5PEJ1at+Dqb7xOgAOL7PuQOSIAESIAEfI8ABRDf85k/WUwBxJ+8yb2QAAnkO4GUlGQsXvAD7uh7v7b21REg6tOrBZD52xLRvH41rPnY/QiQ+PgkTJv3F75buRvvPtIJbVrWxLxlm3H76Jm4t0tzfD1aUmGpEyNvEkFMBjz31kJM+bFO0+8AACAASURBVH6FpHKx48uX7sADt2UjfrjhyYW/bsXQr1Zg/6EYdK0djvIRWblTAHEDKYeQAAnkI4Ho6Gjs379f7o166FU0RjaF0PVSq6NMycI4cfocbBskTVVqHh3I20JgavcUrFInxGSxIHW91BxR4oMmTOeudtV1kRr1aNBvInYe+E8KktthkEhGyyapSZKSBzVJZP61m46gzTPva6nH0sxSAyRLMxj04gOblqLRnv4cpQCSj38h8nApCiB5CJdTkwAJkAAJkMA1CFAA4aVRkAQogBQkfa5NAiTg8wQsFjP+XvcnWrfrrO3FGQHkTLINi3YmonHt6lj7mUSAKJHC7vqBUlxcAibNXYdvftuAJ3u1xIsD2sOaZsWMhRvw8Nvfo3/XZpgx8i5VNbfgRZD0gudPS22PD+cvl+MkPb544XYM6OMZ8UOlROn+4gwsXbsNLWqVRa3CVgTrsqaQuVoAWXMyDXtj0pAqqWBUYwSIz/915AZIwKcJ6OXAXWkMISFBSEm5dq2Jzp3bYcXyNbi3eytMH3Zb3u1ZhI7jB4+j/ANTYJBn3YgBXfHaY5JeUd0ytboYIhhItEqumtqwXtIV6izYsD0GrZ6YBrPVIs+IICwccyd63Ng4V9Nfd7DNAEO7wRL1YUeTxvWwcdP2y7rXqlUDe/buE584nhHKP1YLU2DlnUPyb2YKIPnHmiuRAAmQAAmQQAYBCiC8FgqSAAWQgqTPtUmABHyegHpDd8fWDWj4P8dBvjMCiNluwL54KXJrCcGPr96B6tGl3StmK8LJD79swZ2vz8JdnZpgzuv9tIOpdX/vx5Mf/YItew7iga4tMH30nXJQVbAiyIn/4vDctF/w/R8b5dxMj89e6IMBvVsKMQ+9vSzb6/7idCxdtwPda0n0RxGjlsPekUEr+5QpVjnUWrorGTHxjgMtCiA+/9eRGyABnyagUmAZJMJDRR1c796oN4TK95KmSmQC8+q3827PBrmBSmooSGqo1yb/jLFz/hSt2YrXHuqBkY+1xtHjZkSVVrbkosmeG9z3rkR8HIdeCq6brSrVlkRc/CO1ScyqQMeVtZxysdZVQ+UZ0fIl7VMJTpS1L+9gEl8EhQQjMTFJ+0IVQ88uLZknLeJc+UOAAkj+cOYqJEACJEACJJCVAAUQXg8FSYACSEHS59okQAI+T0Clwziwdweia9XX9pK9AKK+uTzC43SSXeqAxKNdg2isnOp+HZBNWw7ho0Vb8cCNddCmVQ05rFIn/jqs/Ws3Hv/wF2zfd1SKorfC56/2dk9kyZWHlOiiw6FDJ/D8J79i/p+bUSw8FO8/3RP39MpS8DxXazgGfzhnDSYtWIODR0+jR+0wqf8hSeQzW/YCiMqh/7NE4lAA8YADOAUJkECuCSgBxGQywSIREBlRB9lNqtJgVapYBoePHodt7Xtyb7fkeu0cJ1CRhKogh4j+Qz/5AxNmLoNJ7qFpImhHlSmEooVLwiIKghIJjBIpMe+th5GWmoYLJ07ghqZVZHpRGKSOyODJy5CaLkpP/fEvGHQpWqorTaLXB+Gnt+5Fj5aNpBK7EkJcj4zMcR9ZO0gaRl3zFx2fSNoxR8rIy5vyh10Kg6hsZHaxmymwXCLstZ0pgHita2gYCZAACZCAHxOgAOLHzvWBrVEA8QEn0UQSIAHvJhBzZD+iKkdrRjorgMQmWTF/WwJaN6yBlZ88KYdKni3sqmxZs34vnpz6K7btPYgB3dvgy1f7pIP0UNTFdd2i0qPY8Px7SzDpuz+kpw431KuGiY90RNvmtTzu0Fsk/dWSNVtRo1IRNClmQOHgrAeCFEA8DpwTkgAJeJyAowi6IV38uPYzQYkMqulF8L6v542SBqt77mxRhb21VImuNFEERPwo0vcjJBw5ItF2NhiDJHVX2rVTd2U3u1HWDQoOQeKad0Ugkfu2Lf+Krde46y3sjzmDvrf3wuwfFlxz86omi8JjE072PHhWu0KdfT1DgAKIZzhyFhIgARIgARJwhQAFEFdosa+nCVAA8TRRzkcCJBBwBNwRQBSkE0k6/Lo3Cbe1a4RZY1XBcs8LExYp6qoKpT87eT5qVquCV+5qi/49Gjh8pF6u9bju4tjDR3PW4p0f/sThY2flTzp0a1Mfb/Zvh4b1K+fJ9dFDE0C2oU+TiigVZobd7EhZotYWdSnbNRkBkieu4KQkQAJuEqgu9+gDBw87PVoSZklghQ221VKg3Buauv1LCit7SCGEtRoseoZZojskcsKgokfsMNpDobcnwwyjFiUy6PZWmDC4R8FYLqm19C0Ga4EpghAWJQI50RgB4gQkH+hCAcQHnEQTSYAESIAE/I4ABRC/c6lPbYgCiE+5i8aSAAl4I4ErBZDbG4Rl8zLt1ak8TiZbsWBbIlo3qIFVU5+QrXlcjcjEtW1XDF7+/A/8LFESzRvVwbiHO6Njs0qeXVJekf1zzW4Mm7ESa7bu1VKhhIcGY9KTt+CRO6XeR15tTyJNur+kCqDvQLe6EagQqc9MnGKT3/TIPj0MBRBv/NtEm0ggcAmo1Fb2bNIwXYuIUdXHiAyCeelYNyI48oCzFkUi/xokBWFqiiYuOP6THmEi+9MiPOzyvXoeSG0RTfh3OfrETduzRLq8+M53mPiDSsFlFBOsWnqrnJpehJzd27dKyst6OXXl915OgAKIlzuI5pEACZAACfglAQogfulWn9kUBRCfcRUNJQES8FYCWQWQIiF6dKsVisLy8/J2tQBySoIUluxIQIsG1bFimgggLhx8ucti/q+b8Oz7C3Es9iKio6ujQ/P6aF2rHDo1KIcKJUMch1euFCaXA6UUyfM+bNrveE+lupIzJEkSookfw/p3wSv3t0V4WC6L5F5vs3Jwds+rs/HDii0wmy24pW6oCCCX6n/YJUWL7hr58SmAuHsVcRwJkEBeEFApsFxpjerWwubdBzH/rQdxq6oBlcclM1yxzdv7mloNkagPK7q0a40/1qyXuivZRwpevQ8p0C7pvth8mwAFEN/2H60nARIgARLwTQIUQHzTb/5iNQUQf/Ek90ECJFBgBLIKIBFBOrSqGoKqRTIO4a93IqXDqSQ9ftmbgJ5tGmDO2H75tAc5wLFZsGlHDN6Q4uE/rvg3PTpD5Z93mKAK8AYFB6NihQpSnsSK0hFBGHRbM7SoXQ4fL96Ej+avRnyyvOGr5I4rzoJaSUTLWwOk1kdLOZDLh9br5a/w059bpP5HYan/oZf6H1kNuty4vXFWVIjQI0z8RAEkH5zDJUiABJwisGj+XPTsfbdTfTM6KbnEZAqG2WqG7W9Jg6WC3ZxM5eTSQv7UWaBt2HwUNzwxWXYlabAMjtRXNhdqe2RNg3XyeAzKlKvoT4QCYi8UQALCzdwkCZAACZCAlxGgAOJlDgkwcyiABJjDuV0SIAHPE8gqgIRIiox6lULQtJQzAghwMhGSBise7RpHY8VHj4pxrr0BnPvd6JCQkIK/th7G5IX/4KeVmzQbVASHiuS4lBXkGvnRpZ9ONAaVz/2V+27C0AHtEBoSnHuzXJihpwggi0QA6S7pr6IitZwrWdoV6oxSeNIVGwogLkBmVxIggTwlsGj+dyKA3OXyGg0a1MbWrbu0cZb1E5F+nu/yPAEzwChF11u9IhGDqWjT6n9YvVZeAHCxZRVAEuIvICKysIszsHtBE6AAUtAe4PokQAIkQAKBSIACSCB63Xv2TAHEe3xBS0iABHyUQFYBRJ2vR0UY0K1OWPpurp+T5FSiHfO2XUSHxrWw/KPHZIxzhVg9ikrLeqXWlV+UuepXETZiT17EkrW7sHF/LP7ddwxrt+xziCLS6kRXRfWokqhQOAIPda6JJo2rOsbnZ5PlPpy9GpMWrMWhmFh0rRUuAsiVvC8XQGyq8K2kPVGNAkh+OotrkQAJXI+AuwKI3hAk0QtSVwMmLH37Idzcppa6uxF2dgR0ZixZuRs9RDTXS7oxqyaGO//M1eR1XRAstlTy9XECFEB83IE0nwRIgARIwCcJUADxSbf5jdEUQPzGldwICZBAQRHIKoAoG0qGG3B7fWcEEB2SzEZsjEuFzlQcnw++Bc0aKSHBS1tWbUEVrs1vweNKLDo7bhv6NRZK9EdHqWNStZAZRqiDwKztyoNAtQnHZ78fTsOB2DQ5PHQcgG3fsgF1GzTxUvg0iwRIwJ8JuJMCS/HQ6aXOkaY9mxAkt7fk1W/ILS6fxWhfcYwhBLpmT0nhcwNat22OP/9c65LlOnlDwGQyIjWNAohL4LywMwUQL3QKTSIBEiABEvB7AhRA/N7FXr1BCiBe7R4aRwIk4AsEri2A5FyR1iohI2cSbVi49SLaN6mJ3z9QabDYnCFw36hv8d3yjUgzWyX9VWR6+qsr3+a9tgCiokF+liL0MRdV4nwKIM4wZx8SIIG8IeCuAKKs0RlM6NOrExYuXIGg8FAk/DZKFbWQ4AYKIZnekiLnQe1HSOFzEcolZaNF4VGMXGgGgwFWmefUyf9QqnQ5F0ayq7cRoADibR6hPSRAAiRAAoFAgAJIIHjZe/dIAcR7fUPLSIAEfIRAbgQQtcVzKXb8fdwiBzNBeKRHS4x8vLMrWTl8hJKHzRRt6TZJY7Lgz+0oFR6EVpVNKBOe3WHftVPBMAWWh33C6UiABNwmkBsBJGPR6tUq4uDh/1CsREXELnxO5flz2x6fHqhSOjrCYhzNZoOxzcsSGGOXFIhSn0vSIFrdSBMWESbiUlIyqlStgoMHDvo0okA3ngJIoF8B3D8JkAAJkEBBEKAAUhDUuWYGAQogvBZIgARIIJcErhRAIoP1aFstDFGFrizInf1CdokCOSm1QBZuv4COjWvj96lSC0TeMmW7NoEX3luC6UvXIS4+GTfXjkSlSJWcJKd2RT0QeTv6552JiIl3sGYKrJz48XsSIIG8IuAJAcRhm0HSYtnwWK+OmPZyD/lzgIogGgsRQewW6Nq8okXEqHoptapFYefe/W65UUWO6PUmmKXmis3KOituQfSSQRRAvMQRNIMESIAESCCgCFAACSh3e91mKYB4nUtoEAmQgK8RSE5Owg/fzsT9Dz6umW406FC9lAkdKoU6vRWrIQwxSSH4ddNhdGhSC799+Ehgn1vlQO72YTMxb/km1KpSDI2LGlAo6MraH9lNQAHE6QuSHUmABPKVwAeT38Ezg17K9Zo6vU6CH3QS5GDDnZ3q49s3BuR6Tp+dwK5H9btH49DxJBj0drRv3Qi/rdgg23FPFFL1VqIqlMCRo6dhV1EmbD5LgAKIz7qOhpMACZAACfgwAQogPuw8PzCdAogfOJFbIAESKFgC6iBkz84tqF2vcaYhjkLoES4ZFpsMrNifghQJSOjdvhG+fu1utw9qXFrYlzrLAdQdr8zEj39s0iI+bq4TjgqF5K3cHPfgED/OpOhR2GSHyWBHbJIVfx5IQazUYFGNESA5QmQHEiCBPCJQt24d7Ny5yyOzq0gFFUSojuitayZJ1IKjzlFANUlzNeunjbhvwjyBkIYO7dpg1Zq/hIs5VxiUCGKXlFoUQHKFscAHUwApcBfQABIgARIggQAkQAEkAJ3uRVumAOJFzqApJEACvkvgyKG9qFy1ZuYG3BFA1ODj8ZIKa0c8alatgLH3tsed3S+JKr5Lx0OWy5vND0jh89m/bpB6KXZ0ldRXUSJ+6OzOpCJJ7yOFz1X+d9V+3pmMI+kF0NWfKYB4yE+chgRIwGUCKmpDNRXBERkZjvj4JO2g3Z2mEgJ2atcCy9esl0oXRqSuGIcgKX0ROE0vIvkW3D58urblWjWqY/+BQ1L4PPepJQsVjsDFCwkUQHz8YqIA4uMOpPkkQAIkQAI+SYACiE+6zW+MpgDiN67kRkiABAqSgKcEEFW49WSCHQt2XETbBjUwb2w/FCsZ6W7GjoJE4vG1P5m7Fu/MX4t9h07g5qY1UTksFbq0c06u4zhItOuMIpg43oamAOIkOnYjARLIcwIZAkjGQiapV6FqTbjbDLogzPhgJPo/+6pEgkhEyMpx0JlEBfHnwuhK3DYG48YHJ+OPHQelAogOdWrXxJ6DIn6kprqLUtJaGiRyROJpJI2WXfjpVYSNJfdiitsGcWCuCVAAyTVCTkACJEACJEACLhOgAOIyMg7wIAEKIB6EyalIgAQCl4DHBBBBaDOEICYxDD9vPowbpR7IorfvQ0hoSODClUOst2f8gamL1uLQsXMIlVeZO0aHICoy58RXl6BlvEmtxjh+zyqA1G9QHwt+mIsq1WsFMGdunQRIoKAIKAGkTp1a2L9vH6Kjo7Frz25Vt9vtpiJJYDPhxSfvwjsff4O6VaOw7ZtnJB2USozliDbxuybpqcp0GopTqZLmymJDmzYtsHrtP/JegaSs0vbtelOkoiqUx/nzZ5AqetSK5UvRvFUH1yfiCK8iQAHEq9xBY0iABEiABAKEAAWQAHG0l26TAoiXOoZmkQAJ+BaBC+fjMGb0SLz73oea4Y4UWGHymyuH9Jf2nGA2YnMcsOPQOdzcqg5+fvchCV9w7wDHt0heaa0O58/F475xP2Lxqi3y5q0ON9eIQKXCksrK6UK2V4sfapWsAsgfv/yENh27wGQK8m1ctJ4ESMAnCTz5xMP46utvkJziiFRQkQaealoEgwi/kRFFcGHZSBFG3Eut5Sl78mYeOyp1G4UT8WYtcmbYS8/grXc/EhHJdRWpUOFIJCWkCDGhJsXkVd0Pd+bJm31yVk8QoADiCYqcgwRIgARIgARcI0ABxDVe7O1ZAhRAPMuTs5EACQQogZSUZCya/z3u7NdfI5BbAcSu0yM+zYh/z9qw52gcurWqh8XvPBh4IojU9+g78lt8+9sGoSriR+1wVCoSLL/JoZRTtT+UN64WQI5dtGLtwRTEpTi+27rpb9RvdEOAXr3cNgmQgLcRWL5sETrd3NMjZoUEGbToBSWEqMxNtjVjAEmx5aiH5J5I7xHDcjuJPCdVmIxZZ0ZQ6xHa76o983BfvD99jkS7uL6AEjvCQkLQum0b/LL0F9cn4AifIEABxCfcRCNJgARIgAT8jAAFED9zqI9thwKIjzmM5pIACXgnAYvFjI1/r0GL1h01A4uESBHa6DCUkEiQ3Bwv/SdF0ZfsTIBN8nB0b1kfi955QGb33JvB3knTYVXcmXgMeHsefvpzi/xJhy5S9LxKEYMLwkfG7q5+2/nK+h8UQLz5SqBtJEACGQS2b9mAmbNmYfzb77kERYcQiXCzSjSDiCGpKQgJCkHyH6OBYBFCJF2UzzURc6SoCXQ3DBbT07Ti8XZ5TtzevRPm/fyHFrmhWp26dbFj+3bt9yvrrKjPfl74A7r27ONz26fBuSNAASR3/DiaBEiABEiABNwhQAHEHWoc4ykCFEA8RZLzkAAJBDyBQ/t3o2p0bY2DSVI11agQhLZlc1e7wybyyYl4K37enai9vdunQyPMGn23QwPx0zTual9/bzqAwdN+w9pt+6GTVDCda4ehSmGjS2KSiqLRDr3Si55nvUCzCiClSpfCit+Wona9xgF/DRMACZCAfxI4G3sKJUqVRfWKxXH4+Fkp6q0EAzvq1aiCbbNflOiJZBFCrrF3lX5RapR4TbMr8SMZ+tbDtFRhwWFhsJmTUaFCJRyUgudsJJATAQogORHi9yRAAiRAAiTgeQIUQDzPlDM6T4ACiPOs2JMESIAErksgqwCiOpaW6I/euagDouZQ77Da5dj/WLwFS3cloFWDGpj+Ui9Ur17mUmYnv/KLDtu2H8agacvwx8bdMBj0uLFGGCpLzQ+XI2nUgZ2W4uXyFptkx58HkhGb6PhuzZ+/aUVtDeqNYjYSIAES8GMC4aHhSE5LQp2aNbBj136ou56UCEf1MsHYO/9Nn0izWKvvaBw8liDpvJTlwEfvjMXAF0dKmSwfjGTx42vNm7dGAcSbvUPbSIAESIAE/JUABRB/9axv7IsCiG/4iVaSAAn4AIFrCyDKeJeP7y/bsdkejH3xOqzaeRot6lXH1Ge6omGjKnJy5UfpsOQt4+cmLcHnP61BohQCLlU4GM0qBqNcpIgfTh9sXf8AbPdZCzYeTUV86qV+W/5djwaNm/vAFUYTSYAESMCzBOrVq4cdO3ZoKaRUSim71Y63nuyFl/ure6KXiMJKyLbroWv7sgSiyLNUovq0yA+DCVbJD2m2OQrHs5GAswQogDhLiv1IgARIgARIwHMEKIB4jiVncp0ABRDXmXEECZAACWRL4EoBJMykQ4OoEDQqaUzvnxsRRAerIRSHL5rw246jkmLLgDs6NsGMV2+HMUjmt6toB18VQ3RISk7BI2/Nx5xl/2hpWYqGB6NV5WBUjHQu7YpNDsUcIsm1BZB9cVb8czQFF9MLnyunDHzyEYwaNRqlSpfjVU0CJEACAUvgyvoYOiXa64NhWTsOeqkbAovkx9LlZ4SF3PtVUXMpSh7SZghSrZei+UxSwP3JR+/ClGnfymNPqruzkYCLBCiAuAiM3UmABEiABEjAAwQogHgAIqdwmwAFELfRcSAJkAAJXE4gLS0VK3/7GV1u6Z35RekISYNVLyxLx9yIIHIeZAjDkfggLNsRowkeBknzdFenppg1pq8jyMSnIkLUG8d2DJ2yFFPnr0J8krzFK28h14gqhIbFjCgWZHbyEnPuUO73/Sk4eNYMecFZa3pJr/WvFK5v+L8WTq7DbiRAAiTg3wTUfVE1JYjY5RmjF3HZmi4+NKldFbEnTmHn/BEIN4jwbszd8yyTpKrTpFIQ2mVOk9zPLUbs33sUtQdMkjRXGcKHTqut9fTAW/HjT//i8KHD/u0I7i5PCVAAyVO8nJwESIAESIAEsiVAAYQXRkESoABSkPS5NgmQgN8ROLhvF6rVqJO5ryIhenSoHooyESoKJOtBvfsHR6q497GLFvwmhdFTJQe6Eg2qRZXAoF6t8fQ97XwqEuSxcQvw6cLVwsau1XRvUycKNYrJGZjlvJPXhnPiR0KaHSv3pSBGaqlkNCV+NL6hlZPrsBsJkAAJBAYBJXzs270N9Ro2FQHCkW5KNZ1EY0ionTzKTDj321soHOqpqEMbtm2LQcMnpkowoxk6a7CsI5EdSoRRzzj1hPDZCMfAuGZ8bZcUQHzNY7SXBEiABEjAHwhQAPEHL/ruHiiA+K7vaDkJkIAXEog7G4vhw4di2sdfZGtdealn0blGKEIlPZajuS+E2ORwKOaCFb/tSXIUg5WDqZKFInBDvap45OZG6N2lgRxUOZdCKl9RykHWa5/8ivfnrcG5C0nqaAsViwejYfkQlA1X52vOH6qpozH9ddJeZezrl93JOHT+kvjxz7o/0bRF23zdNhcjARIgAV8hoASHjH9HjXgZH077HOfPn9dqhShBRKc3yfPFLHfvYInM0MMcZIMu1YwQmw0N61SFUYT6VTOHAqln1S1eS23Y9rFPsPPQaRE2JMgDJiTHn4NFlRlRQR5aBOMlOgaJCPlfkybYuHEDEuLjERqaNZLSVyjSTm8lQAHEWz1Du0iABEiABPyZAAUQf/au9++NAoj3+4gWkgAJ+BiB/Xu2I7pW/RytVjVCalQIRvMyoZIJKvtIBlXa4+rvLhdNbJKK5Mg5K5btvKi9nZvxtm6xyDA8dmtrjHu2myM1liYsFKQgosOIqUvx/g9/4mJiiqPorrQO0aGoWSwoM3LFpk7CJDXW1UKIc9EeV4L/ZY+IH+cuiR/du3fF1A+nIKpydI4+YgcSIAESIAFHBEZGWiybiBzBwcGZqbEyRBF3OWWMr1S5ErZu3oSIyMLaWlfWJXF3fo4jgSsJUADhNUECJEACJEAC+U+AAkj+M+eKlwhQAOHVQAIkQAIeJnD08D50uqkbDuw/4NTMSgaoUtyIztGRV0QzOHPgf0kMSZMokF1xFqw7kHzVui3qVceEhzqibZvaDjFEBAYtOsShsDhlp2ud1Bpqbj127TqKIZ//jiVrt0lNW/XmsA4Gux7NapRD7RKS1916QZtaRbTo7ZcK3bq23tW915xMw96YNEkTdvn+/l63Eje0kFRhbCRAAiRAArkioMQQvaTGsljMMJmCECQie/XoSggRgWTKmMF4/s1P8e+mf2EoXBIl5FljKlwIqRcu4HTcWe0R9MtPP6Jjl1vkcaGXMiAqHISNBPKeAAWQvGfMFUiABEiABEjgSgIUQHhNFCQBCiAFSZ9rkwAJ+C2Bs7Gn8OrI4ZgqaUNcaVLjFVVKmtA2KgTBqmyIm80iJ0u7z5mxet/lYoi8U6ulIlFt4G0d8eHQXiKCiNCiVBglhmQ2Z0WRjKiSLP1FyDiw/wRe/uIPzF+5Wd4SVkKOtoA2e4c6lVCrhAge1gToVAkTET2UTbkRQM7LNv89mYJjIgAli+BxjYAarF+zHM1bdXCTKoeRAAmQAAlkR0BFiISGhsIspTti5r2KcmVUyioR6LVHhNzoRSiBXv41qNRZIoQ3fx4qGm/RoiWM9OAlle8EKIDkO3IuSAIkQAIkQAKgAMKLoCAJUAApSPpcmwRIwO8JnDxxDM899yy+/3GBHPg7E9GRn0h0qFe9Ev5XvQwupKShe9NqeKxvG5iTU3D46BmEyNu4FSuVvL5BJnljN0gpNXqMmbIY42b8CrPF4si4pZ185SykZEgjnWqESQF0594AXnUiDXuOpUntk5znz9jAutV/oEXrjvkJmGuRAAmQQMAQ6NatK5YuXYY9345Bjajr1OwwFIKp2eNIs1kofgTM1eFdG6UA4l3+oDUkQAIkQAKBQYACSGD42Vt3SQHEWz1Du0iABPyOQEZB2dTUlMyCrv/+vQbtb+yKhISEfNlv8eLFEFmoEI4ePXpNQUZFiWQWpJUXeKMrl0O1ssUlPYlEdhy/gN37j1yq3S5KR3YSREZ9jyJFisBitiBeitgWVFNpVVav/JXiR0E5gOuSAAkEBIH+9/fF97O+Q68eHTBn2C3X3PPzn6zCe18uFKHccykPAwIwN+kxAhRAbFUV0gAAIABJREFUPIaSE5EACZAACZCA0wQogDiNih3zgAAFkDyAyilJgARIwFUCShT5ZfF89LnrvszCsq7OkVP/3r17YdrUqShVupzWNe5sLKZ/8Sm++Go2UlNScFZysp8/f177LqOQeoaQoYkcKqzjGi2jiG3NmjUxZuQruOueBzJ7Dnr2SUx+f1pO5nnse1Wct07dupj2wbto0qwN88p7jCwnIgESIIFrE3j5pUGYOPF9WNa9fd3gvwlzN2Ho5G9EhKcAwuupYAhQACkY7lyVBEiABEggsAlQAAls/xf07imAFLQHuD4JkAAJXINAcnISdm79F4t/XoK//tmE2DNxEikSj6SkJJyJjb0mN4vFitTU1Ku+f+jB+/D5F19fl/fhg3swZuxYfDl9Fp7q3RETnu6CsBATZi3ZiGWb/0O7BpXQoFoZlCgSgePJQZg490/M++lnvD56BIaPHJvt3PEXz2PE8KGY+4OkAVN54KWlpaYhMTERZrM5V/4f9vLzeG7wC5miTq4m42ASIAESIAGnCWRENeqk7pMS8es3aIBD+w/CsnECkCqRhJpmrpIcWuSHpDc0ygeieXw6bzueeucrpMmzSs2hngtqDq23/FSfqcLqbCSQVwQogOQVWc5LAiRAAiRAAtcmQAGEV0dBEqAAUpD0uTYJkAAJeBmBI4f2YvSYMZoA8mK/m/D2s93EwvTaJapIevohlTrZekuKnI+asQwjhw8R8eN1L9sJzSEBEiABEshLAkqoiDtzGiXLlM0ULmDTw/aXRICoiMGgYCmKnohf/orF2E/nI+aCGaePxcCqF4FDniXqH6tEgWREGipbGzf+HzZu2JCXZnNuEgAFEF4EJEACJEACJJD/BCiA5D9zrniJAAUQXg0kQAIkQAKXEZj0zjg8/9IwDOnXGeOf7S7fZVvlQw60fsWo6UsxdtTwa0Z/EC0JkAAJkIB/EVARG51uvBGrVv0Ju07EDHsw2kROxroLzyBNZ4ZORBC71IwySJFzqzw+dDABEgBit5rVD+ilLpPFYIO9/H/yYbJ8koROcadwMuE5HLLvR4ouTRNUVGpGo1HGspGAhwlQAPEwUE5HAiRAAiRAAk4QoADiBCR2yTMCFEDyDC0nJgESIAHfJDDpnbew5PtZePPBjrihYZVrCCAQAeQ3jP92JUaPHIYXhgz3zc3SahIgARIggRwJqGgPq9WC++7ti7nfz5N0VkrQAJoUXYqNEaquVJDjWSEBg42s22FOsmFH0ebyZ0lzqJMUWFoEoXxvkT8bwxyDsxXXrWh4cSu2X7hHxBMdIsJCER8fn6N97EACrhCgAOIKLfYlARIgARIgAc8QoADiGY6cxT0CFEDc48ZRJEACJOCXBNQh13sTx2PxdzMxboAIII2qOg6tsmljPvkV42avwJhRw/DS0Ff9kgc3RQIkQAIkIFKFPBtMehW/EQyryQRduY1a9EeeNRFbOsYMxUrDIimWfnmdkDxbkxMHDAEKIAHjam6UBEiABEjAiwhQAPEiZwSgKRRAAtDp3DIJkAAJZEdg+bJFGDJiDDb884+Wm/2FfjdKDZBrpcAClAAy+qtlGND/HkSEh2Pv/sNoWL827r7zTjS+oRUhkwAJkAAJ+DgBi0RsmIKDtGeCQReMsqX2IiZUojgkvVWeNhU1Iqmz6lmPYsexm7Sldm79F7XqNsrTZTl5YBCgABIYfuYuSYAESIAEvIsABRDv8kegWUMBJNA8zv2SAAmQwBUEFv44B0OGj8ae3bu1YrR2VbxW2j1dmqF9g8qYvWI79hw6jvMJyUhOldzs0kcVuLXrpZNWH/3SW8AZ40NCQvDMU4/hpSFDUbJUWTInARIgARLwIQIq4sNglIgPdY+Xe32H8r9huaGS/EEJE/IMyLembIhAyNEKWl2RLt27YOHCRfm2OhfyTwIUQPzTr9wVCZAACZCAdxOgAOLd/vF36yiA+LuHuT8SIAESuAaBTz6ajCeeGax9a5eitVWM9VAooi/+sx3BufhPRONIFznUu7+a0KGkDvlFDsPU28BKKClqKA5joUcRW3hA5qFYkbhJSIv/CqlI1uZ4bdQreFGKqoeFR9AXJEACJEACXk7AbE5DUFAwQgwhKCf/HCz9i5T4SH8IFJTtSnA/WhMGiwETJozBc8+/rBVK1+vVF2wk4BoBCiCu8WJvEiABEiABEvAEAQognqDIOdwlQAHEXXIcRwIkQAI+SEC91fvFJx/i0YHPam/26uUAqVxId5iKDcNBU7FMEcOxNZXvXb3pqw6+XD/8qp28CWnnP8ZB8wropZjte5PG4+nnXvRBajSZBEiABPybgHo2qHYu7gxKli4jd38DGgSPwcYS/eRBkZqPm1cRJmKLEjaUTXaptp6lGQ/XhM5ggt6oR1JSEgWQfPSMPy1FAcSfvMm9kAAJkAAJ+AoBCiC+4in/tJMCiH/6lbsiARIggasIqFRXg18agUMHD2mCRvGwntCVGIlYfSHHgZPWPJnaRM2ph+HsWNiSZmpFdKdMnICnnn2Bh1a8PkmABEjAiwioWh/16zXEnn37YbAZYKmySx4LVrFQiR+XixB5a7asdTwa9e3/w7byM2QpU5bnk/xqtcJ0vDHMUhjdaLAgRdIyGgxKrGcjAecJUABxnhV7kgAJkAAJkICnCFAA8RRJzuMOAQog7lDjGBIgARLwIQL7dm/DmNdfx8xZczWrq4a0Q1iRZ7A9pEE+7cKOQmcnwpI0B8n2BDzyYH+MGDEcUZWj82l9LkMCJEACJHAtAhn1Pgw6IyLD6uJciZkifigxPD+Fj6zWpcF4uKGsbke0oRW2VfziCtPlmXKkBeINSTDq7BIJkgijUQklbCTgHAEKIM5xYi8SIAESIAES8CQBCiCepMm5XCVAAcRVYuxPAiRAAj5E4JuvPkf/hx6Xt2btKG+ogZDI/thb5PYC2UHt5B1IOfcBDluWo3Pnznhz9Kto2qJtgdjCRUmABEiABKSkuUR+FC5cGLpkE9qUmoxfwlpdCgjUAEkkn9UswXwSZaHLz0iLFFTDeRyM7YQmum7YUGLi5e4SW3THomE32xF7+gRKlCxDd5KA0wQogDiNih1JgARIgARIwGMEKIB4DCUncoMABRA3oHEICZAACXg7AZvNhlkzPsUDjwxEsC4UwaG34kKJUU6Y7alUWOrt4Yy5Li1b1hYPy5nXcSZpAZo2uwHvvPka2t3YzQm72IUESIAESMBTBNQzIiU5CRGFCiHEZkLR8rtw3KTqb2RtjhpQoTG10ST8Oawu9qSnlnd6nttPrcTi5McQFdQIe8svlMdKcubYWvYYHD7WA6n2VNisrtepctoIdvQ7AhRA/M6l3BAJkAAJkIAPEKAA4gNO8mMTKYD4sXO5NRIggcAkcOTQXrzxxpv47PMZKG+sjojwfthd9L5rwigXvwSm8x/hqHUfgkQsMUbci8TiL+USngU1LvwMs6koDoWpKI9LYkgV839IOjsBp1J+QUREOKa+PxH3DXgsl+txOAmQAAmQgDMElPihlyLjOkOw1PuwwFpZ6n1c2TQNOw3hMa1Q1lAB+8vNd2bqPOlT0/of9h+7CS3QG2uqDBVNJjJznX4nl2FeygtIk3ogVouqWcJGAjkToACSMyP2IAESIAESIAFPE6AA4mminM8VAhRAXKHFviRAAiTg5QQW/DAb9/R/WHKiJ6NQSGcYSozGOWMJsTr7iAy1Hd15ya9+fkK6RCGFZSPvhaX4yFztNCrtEFLjJuN02jJUDrkLScUexylj2fQ5HbYYTw+TuiA/ICQkBJ9Nex/3PvBIrtbkYBIgARIggZwJmM1pCJb7rk5uxbao/XI7vjLyQ81hR4O4wdif+BeSKq7LedK87GE3o3PiAiw/OxIlK27ASX1Y+mqSkstiR9iJekiypuKTjybj4cef1sQdNhK4HgEKILw+SIAESIAESCD/CVAAyX/mXPESAQogvBpIgARIwA8IqDd6v5v9Ffr1f0hlLIEhrDsspd7VDrEc4sd12vkvRQB5K7ODXiJAbCVyJ4CodWsk74L5woc4mrocxfUVYS7yOM5F9klfxxERYjw9XESQH1GlamVMfmcceva+2w+8wS2QAAmQgPcSKFq0KFLjLyCq1ArsCS0tz4yrnxEd4rdh5fl+sEdtzy6bYf5vLs0I3anqsBulMHvZTbJ+lqLnuhDgUCXo9DotCkSnlB02ErgOAQogvDxIgARIgARIIP8JUADJf+Zc8RIBCiC8GkiABEjAxwmot3m/nTUd/R9+AiWMNVAk4kHsK9T7ql1VSj2EUNtZ7A5tetl34RfmwnDxPcTb42C3uRsBYkfhuA9gTPgJuoieOFP0QdFdVJoSO4rFTUJK4myEogisRZ7E+cgM20QEsVsRHDscqUnztSiQAY88CYMhPwvt+rjzaT4JkAAJuEDg4oVzKFa0OKqE1Mf+Et+LWn51rSZIKsSIQ9VRpuxa7A9W0RZecE82iw2mICCmKtoH34OVpYZn+X8zFgQda4I0cwoqV6mM/fv28zniwjURiF0pgASi17lnEiABEiCBgiZAAaSgPRDY61MACWz/c/ckQAI+TuBM7El8MGUSxrz5NioYGqNQ4eewI6LFFbuSA67z3yLowjgEh/VBfMlsiqHbL6LCxTkwWxNxqtggGe/aG7RVk9bAeuETHEldr62tKzwI9qIZBXMdIkhq4hyEoLCIIAOziCBAiTNvIil5vqQwicdXX3yE+x983Me9QvNJgARIwLsI2O12LTJCb9Aj1K5DUqVs6n5ApY5KRLtjw7HKsgT2yru9axNiTQWpBXLSEAtL+c2O1F12iQjRmhERR2ojUW+GOdVMAcTrPOddBlEA8S5/0BoSIAESIIHAIEABJDD87K27pADirZ6hXSRAAiSQAwF1oLXw+znofde9KBxyI0JKvZ0lN3qWwRfnSp2PkQgKuRWppcZfY9aMVFlK+JAcWi4KIIa48bBelFoiWtOJAPJcFgFEfWZHkbiJSEv8FhH2orAUfQpxkbem97fDdHqopMJaoB3Off3lJ+h3v6TyYiMBEiABEvAIAfW8SJC0V4WLFkM3/XAsqXB/NvMaUdP+H/Yeawd7xb3afdv7mogex/8HWNOASvvkcZVe+FwXhJqJx7H/dEdYkQa1XzYSuBYBCiC8NkiABEiABEgg/wlQAMl/5lzxEgEKILwaSIAESMBHCfw071vcekc/lAzqgKLFx2CPSXK5X3ZgpUNw4iKY4sYhObg1rKUm5NmBlv7seNjiHQJImC4c9sLPILmIpMHKbA6BxShFbK3J8+T7V4DI++QzJbaor+S7Uy+KCLIQM6d/yoLoPnpN0mwSIAHvJaAiQAySRcpaXhU+TxcOLjPXAKNEUbQO/VBSTLWRb7wg9VU2OMtaEnDybDNEp9TA3kpzpYdsSrWUEJhia0okY4pWD8RmTX++eK9LaFkBEaAAUkDguSwJkAAJkEBAE6AAEtDuL/DNUwApcBfQABIgARJwncCShd+jZ5+7EYYyKBreA2ci7kClhLVICYrC4YhW2oRlbHEodG4GYqwxSC45VkSGCNcXcnJEuZTdiIz/ATZ9KE5E3oEEsSO7VtQWD5x5HeeTfoK92DCgkBJBHC3k7CikSRSI3Z6CWdM/YxSIk+zZjQRIgARyImCz2bS0UG1M/bC6/GtXd9fZ0SNmNpbax0FX6l+Yg7MUGc9p8nz/Xg99TD2Rz1PlQbdTaoNkEWr0VhFx6sNqt2Hfru2oGl2bRdHz3T/evyAFEO/3ES0kARIgARLwPwIUQPzPp760IwogvuQt2koCJEACQkCl9lg0fy569bkHxtAusER0Ac4+rwVTBEup8fCwHogrJYLHxR9gPDcWxrBbkVJyjNewq3ruc1xMmCuRKzfAXORRKbKrxBKVe17OsU6rKJCf0LlLZ0x4czQaNWnpNXbTEBIgARLwRQJWqxU3d70Zv//xO1BFUltZsyt8ngZdTEMEl92DFIP3R07oZQ+6Y3UQYSiDCxVWilsybNYhSJeCNCmKrrNaYDFboNc7ni9sJJBBgAIIrwUSIAESIAESyH8CFEDynzlXvESAAgivBhIgARLwMQIZ0R+FTO1RTGp6HExcBd3ZFyX5lR3BuhARQHpCJ1Ehhc5NwjFTRZhLveNlO5Q0LLEjYEv8ASg6HKbUbRL5MU9SluhRJexRXDTvw5nU5Zjx+UeSCutRFrP1Mu/RHBIgAd8ioKI/go0meUIYYa28Xanol2/AbED1c7fiWOohpETtkO+lvoa3N4MIIAdqi5VGKda+SX5miVgxW1HxZGeJfjyOWrVrYdfO7Aq+e/sGaV9eEqAAkpd0OTcJkAAJkAAJZE+AAgivjIIkQAGkIOlzbRIgARJwg4ASQHrcehdMwTchrewUIH6RRIC8qM2kBJCyITdJSvSasCf9hohCT2BHZEc3VsnLIXbUSj2IlLh3EZP2O2ySl95uk8MstWSx0SicthfJifOQak/EnJlf4u57B+SlMZybBEiABPyegFHusy1D7sTq4iNFK0ivmZG+a4NEiOhP1oO5/AFJlShppeza3di7my0UTc27sPlEDzQLfwNrS956ub0WSYt1rLr2mRKAVP0TNhLIIEABhNcCCZAACZAACeQ/AQog+c+cK14iQAGEVwMJkAAJ+BCBXxb9iO633QmDsSPMZT8Uy3UonrQeRc5OwFn7GRST6I9DQVWgPzcChpBbkFZaRX9458FPkbPjkJrwHZJF6FA2RuhLwVb0JSRF9kSwpMJKS1qEkqVL4ouPP8Att97pQ16iqSRAAiTgPQRuuqmzpL9aAX35vbAaLFcZFnG4Dpob+uP3ikO9x2hnLJFHW+jhBkjR2WCPksiWrM1mRefTE/C7ba7EhliQkiKF0SmCOEM1IPpQAAkIN3OTJEACJEACXkaAAoiXOSTAzKEAEmAO53ZJgAR8m8Avi+bhlp53Su2PjkgtrQSQy1vhtN0oFvcxTsnBUFKpd0VX8E7xw2G1DsbYV2BJ/BEoPgqI7Je5mUK2i0DscFxMXobJ747HQ488jojIwr7tPFpPAiRAAvlMQNWMUjUwgg0mpFaUguGZtTKUIUZ0PvM6ViZ/D3OlVfJVaD5bl8vlJHIl/FRzJFniYa8k0Sv2K8QdXTIMR5vBak2D2ZwGo6QBYyMBRYACCK8DEiABEiABEsh/AhRA8p85V7xEgAIIrwYSIAES8BECZ2JPYsp77+Kj8d+jePgd2Fvskastj1+AyHOvIzK0J46XfFW+92YBxI5CZ8YiNXkeSuoqI6HoszgffildV6Wz43E2cT4SbHH4bvZXuKPv/T7iKZpJAiRAAt5DQEU+6AySarDiNjEqqwhgh0EKn9uiVkpZkKLeY7DTlqjnWwSMh6uhgakN/i3/wRUj7eh08i2sTJkFK8yyx2yKvzu9Fjv6EwEKIP7kTe6FBEiABEjAVwhQAPEVT/mnnRRA/NOv3BUJkIAfEvht6QJ07XE79MYOkv7qfdmh5DjP0iKTVqBo3AQcl/ofllLvyTdZD3vU794mhjhsCpIoEHPyfNiLSBRIob6X7clwajCsyUvQtevNePut11GvYVM/9Cy3RAIkQAJ5Q+CtN17DKyNGo1GJH7A5opYsYsxcqGFSLLaeaS/po1RkiC829Qy0IOi/Wkiz6YGKu6947qk9yef/1YGEgFAA8UUX55HNFEDyCCynJQESIAESIIHrEKAAwsujIAlQAClI+lybBEiABFwg8OuS+bj5lt4whd6ItDJTRd/IInDY01D84g/Qx89D4UKP45QxDEXiJiHGtgUldFVRRCJG9hd72IXV8q+r4fRQ2FIWoXTkCzhZRNJgSSH3jBYdvxwX4qciNm0rvv/2a/S56978M4wrkQAJkICPE9Ab9AiyG5BaeYPsRKI/7OkCiDVFoj+a4QZ9E6yP+lS+uySM+NqWdUdryrZE4C+3V0y3XWG+DobDtSAI8OjDD2Dax1/42vZobx4QoACSB1A5JQmQAAmQAAnkQIACCC+RgiRAAaQg6XNtEiABEnCSgErdsWzxPPTs9RDCw3vifImRMjKLABK/ELpzQ2EI7gZL6YlA/I/y52Gw2xx9jFIc3VLqbfnN26JAgBoXfkTCxem4gFhYiwxDSmSvLHuTFC2nJQokaSmaNG2CDye/jeatOjhJjd1IgARIILAJaIW/lbZRYc/lIFIlcuJMU6RV2CePkkSfhnTL8QX4NW0EovX1saPCbAn6uDzVVXXzWRw62UlqgaTAZrOxGLpPe9szxlMA8QxHzkICJEACJEACrhCgAOIKLfb1NAEKIJ4myvlIgARIIA8I/Pn7z+h5e1+JlGiIyOLjcSKoWKaYUTHpL4RJ6qu9QVGwl5oin1tFAPkBODss0xKTCCDmUuPlz5enzcoDU92YUtJgnX5ZRA5Jg1VsDGyF7soyhx0149fiXPwUnE7bjLnfzNCiQAwGb9yHG1vnEBIgARLIQwJKAAnS6ZFWadflq+hEFTkUDVTZLgKIj99PZS/GQ9Wlzolkuqq4VfYZdBVR4+H6sBksiD15AkWLl6QIkofXnC9MTQHEF7xEG0mABEiABPyNAAUQf/Oob+2HAohv+YvWkgAJBCgBVf+jSzeV/qoT0kp/JBSy1PRIXITwuDdQKPQ2nCjxsoOQRIBAIkAgESAGORUyhfZCSqm3vJSeHSYRa2wJC1AjbACSij6II8aS6baqiBX5/tQgWJKXIiw8VBNBuve6w0v3QrNIgARIoOAJqKjBM7EnUap0OdQMvQl7Sl9eILx+2kFsO3Vbet2MtII3ODcW6ET0P1oXwfKsSK30rzz3wq+a7aaYF/Gr9SdUjKqII4ePUADJDW8/GEsBxA+cyC2QAAmQAAn4HAEKID7nMr8ymAKIX7mTmyEBEvBHArGnT2DKe+/i9fETYQzpJKmslACS3uxmFL64AJbUVUiSwuf29BRX4ZZjqHBhMf7P3n3AR1Wlbxx/pqXRwYYgYENR0bWLBbCi2HsH7N21IChgd+1i711EQEWRIiKyCGL/23Xt0lEUEAiElJnM/z13MiEhQRJIZiYzv+tHDcmde875nruZ9T7znhMp/l4lef/SzGZ9kkzjgoxYmFF5c/ZYt7ZZMlr5+c/q98jPirS4QdGmlQOOLZe8ooX5z+vv0l806pWXdMQxlTdLT/LgaB4BBBBIOYGdd9lFn3/2mTpt+r6+j65XqX/d5lylqdG3Fd3kI/t+bsr1vbYdaj+3h+aXLlXbtpP0iy+vysvb2xKLM2fs7X2fZbBqq5t+5xOApN+cMiIEEEAAgdQXIABJ/TlK5x4SgKTz7DI2BBBIC4HPP3lfvc46X7/9lK3Qejdradbm5eNqsnyKbXZ+u/7I6qiSDd3yV5XXPq8LgPZLxyq69AnNj8yyCoyT9XeLC20lrSa1uLRfwYU3KLL8pdieJC2tMqVpnyp9Df55lS2DNdqWwbrFfn78KtcPKDj/YqsCmaAbru2viy+5TK3W37AWfeBUBBBAILME3PJXvkCOom1tA3SfbYAeP2zJqMCMjto62E3ftXk0PVAsX/fN2kZbRLfQz+1sCUi34Xulw6pEZm/jvUUuXrhQzZq7ZSQ5MlWAACRTZ55xI4AAAggkU4AAJJn6tE0Awj2AAAIIpLjA5LfHar8ehyuUva9KWrtlTNyOtmVH/ptq+ve9amkbo89odWmdjyS0+DFFlzygcNQeHpUdvibnKNqqb43b2mTpeBUsfVoLw994r2mdd6L+bn6eCrPaVLpG6M9+CheMUTtbyuuvFueqIGvTSj9vv+AOLVjxhpZHFmr0a8N1+NEn1rgPnIgAAghkmoA/4PeWQYx2WGUDdEsBcmfsoO3bDdPH/m3Tg8UtgzXdAg53ePuarBqASLvP66dPit/Wxm1bas7sOekxbkaxVgIEIGvFxosQQAABBBBYJwECkHXi48XrKEAAso6AvBwBBBCob4HyACTXApANH6vc3PJxarT4UbVofLLmNDu1zrviW/SwVX+4ypKVR20DEF9kgRotvF3LCsfKZw/jmjQ5T0ubn2VVJM0qXXebv0dp2fLnND86S5Hm1yvc5MhVxmOVJGVVIAQgdT7VXBABBNJMwFWAyDIQtVslAPFZGYRVS3jfj5amx6hLc2xM7WNj2czC9tKqG6HLgvzgzG0VtgCIZbDSY9rXdhQEIGsrx+sQQAABBBBYewECkLW345XrLkAAsu6GXAEBBBCoV4FYAHKEbWTefZUAJKyAbYDuWzZZYW+D25VVGnXVoVUDkCzlyNf0LBW1rF21SW7xTG1QPMeexRVpjluuK6ttlS4Go/nK/us6FRSNV7S5LYPVZNWNzqMK/n6p7Xfyth5/+D6d3uds5eZV3ey2rsbOdRBAAIGGKrB0yd/eMk9bBLbTL5u4JaEqHH6fcn7bSoUdfq6X943kmBWp6aw9tLS0wCpAvrNgp0KlZHmHLBCypb/c4TaJ58hcAQKQzJ17Ro4AAgggkDwBApDk2dOyLZdr/wHAfwFwJyCAAAIpKvDn/HneBui33v6AArn7W9Bxf3lPOxT9qOYLH9H/AqUq9vb/cJuM1/ERXarNF49VyfIR3h4gwSZnaHktw4+a98in4J99bRms0cpucaOKmrl9QAIVXm4P7dzPbR+QcLRYY0eN0KFHrrpXSM1b40wEEEAgXQXiG6C32fhrzc3KrjTMdkX5mj2/i6LtfrDvh9OEIKqD/n5ck2zJxr1bvKApzXapZlz2HjPDVYCU6Mbrr9F1N9yaJmNnGLUVIACprRjnI4AAAgggsO4CBCDrbsgV1l6AAGTt7XglAgggUO8Cn3w4Raecfpb+mNVUzVrdoHk5W69sc/lE5S64RpGsLipuXU8BSJURusy8HoKWsnbcRuguAOnQ+Gz93vwMFQXX836y6YLBKloxSXnBzbUo/Jv+jvyiMQQg9X7/0QACCDQ8AffZJr/frX1lR5X9P+x7JTMUmHuIIpv+ZKUQdV85mCyxHQtffpq2AAAgAElEQVT+py8XHasd1U2ft11luUjXqWhYBy75UpPyeylgPsXFxcnqKu0mWYAAJMkTQPMIIIAAAhkpQACSkdOeMoMmAEmZqaAjCCCAQFWBae9O0KFHnaCSwm0U2vBuLfWvv/Kk5ePlX3SVsrIOVOGGg+379RdMJGpuOv09TPnLhmpR6SIVthyk0iY9bVgBBf64RJEV471u+Gz5lqjtJXL+eWdq4IBBatuu8mbpieor7SCAAAKpKOACkECosS3ztKJs/49Vir0jc6V5B0mb2FJRaXX45Zuxpe3wYUd1wY83Vr/8s7dWaSTCMlhpNfe1GwwBSO28OBsBBBBAAIG6ECAAqQtFrrG2AgQgayvH6xBAAIEECLw7cZz2PegwBbO7K9zafaK1QsiRP17Bhf2UlXuACtIkANm4+C8VLLxJ+cUTFWlpy5M0OaZKAOJt6lu2b++4N15RzyNW3SskARNDEwgggECKChQsX6bGjddTW39bzW73hvUyVKmnm8+7WL+XfKKC9u9X+VmKDqmG3bI3BwtAvGN1AYgF6D7bCD0aKSEAqaFqOp5GAJKOs8qYEEAAAQRSXYAAJNVnKL37RwCS3vPL6BBAoIELlAcgWRaAbPx45dEsf1ONFt2qlnmHa3arfvazhl8B4jZyz/6rv4oL3yzbCN0CEDua/3WNCgreVEm0SNs0u1GLCifr96LJIgBp4Dc43UcAgToXOOaYIzX+9QnaLet0Td34qirXD8zorCyfXyvaf1XnbSfzgn6rFsyeu72ixWHb4P0L60o1G6GXNlb27G1UFF1CAJLMyUpy2wQgSZ4AmkcAAQQQyEgBApCMnPaUGTQBSMpMBR1BAAEEKgvMmvGzBg4apKFDX1GT0LZq1fJKTc/tsjLosAqQDZY8p5YtrtQPjXZLG77YRuhjpVa3xSpAYgua2JFlGY+Vftia9VnzL1ZJ0Tsa9cpQHWZLhJWvd582CgwEAQQQWDsBf8CvaMB+b7b52S5QVi5X4VK+GZ2U48tKuwDEfQjAZ5ucR22Tc3X4xUZc3f4mYQVndlY4Wmp7gBQpFLL3FY6MEyAAybgpZ8AIIIAAAikgQACSApOQwV0gAMngyWfoCCCQ2gJTJ41XtwNsD4yyI9uXo8Z5B2nh+nfFvpP/pgUgQ9SqxRX6vtEu9o10qACJKrYR+hht3OgU/dnibIWDbapMVNACkPCKd7Tn3nvqkfvv1g477ZHak0nvEEAAgQQIeOGH7ZGUa3+taP91LDRe5fDN2ko5UfdzVwGyyv4gCehj/TXht+qO7VQUKbIAxPY50bKqTZXmqMPvB2hGyc/qf9VluvX2e+TzWXBif3NkjgABSObMNSNFAAEEEEgdAQKQ1JmLTOwJAUgmzjpjRgCBBiGwagDiAo5Q9r4qaf2I9d8nvwUg/oK3FN7I/hy1T7ymRQBii5b8eaVXAbJZzsFa0vJ8LczqVGW+mvzVVysKJtjeKH6NeX24Djj4yAYxp3QSAQQQqE+BwXfeqiv7D1TAF1Kk/bdl7wuVQw6fLYHVodGmmr7+mPQKQHxhHTT7Ob1deo/2bPK0PmixV9n4Ko6/VD0WfacJS4/3puHrLz7RttvvTBVhfd6UKXhtApAUnBS6hAACCCCQ9gIEIGk/xSk9QAKQlJ4eOocAApksUG0AkrufSjZ8WFsUzdD6ix7Tp/4ChTd8MK2Y2i+4W4uWv6aWFnwsanGR8nN2qjK+Dn8/rgX5I7WsdKbeGjNSPQ6L7RXCgQACCGSyQGlpqQKBgIIBWwAqmm1BSJF2azZKHzRdGST7Zm2tVnnHakFLW2bQX7VCpOH6FauJilUwYw8bv19F7b7WVsX5aqS5ChT7VGxbgvxS/D9tXjBZX6+YUD5MZ0YFSMOd9bXpOQHI2qjxGgQQQAABBNZNgABk3fx49boJEICsmx+vRgABBOpF4Mf/faWL/n2lJr3zX+WFOql1o9MUyWqjGXluD5CoNiz4Qs0X3q1fs1qmXwBS9JOWLrpLi0umKdriVtsH5OiqxrYcWOCPsxVZMZEApF7uQC6KAAINUeA/N12rQdffosN9F+jHjU7STwsPki8SqxD0R0rVMaebfi75QI1zjtCS9a+3d5P02wPDN6+TbYReNdgJZvkUCYfkj0YtHCqRz+9TqZlEIhEvNOLIHAECkMyZa0aKAAIIIJA6AgQgqTMXmdgTApBMnHXGjAACKS3wx7zZuv32W/XIY08rz7+N1mtxvX7N2c4LPuJH28Kv1XThvfop2HgtA5D4tZKx7rlP7f9+UnmFX2p5sxM1K2+fSvOxYfh3rfjrFuWXTLIAxG2EXk0AooB8f5yvaOE7BCApfTfTOQQQSKSA2wPEHw1p07ZT9EugqTVtZQ8lfh216D69UfKwolYVItsjw5cbUnSj7+1tpbqNwhPZ43poa8bWbsFIbdDhE82X3xqwv302btv43G2MvnkkX7/O3t1rOGphCEfmCRCAZN6cM2IEEEAAgeQLEIAkfw4yuQcEIJk8+4wdAQRSUmDalLe1T/ce1jefsrP3VtFGD9iXjdyjmpX9Xf6WtPAyBXMOVHiDmi+BFVgyTFp8s336NaJgo+Pstf9J+B64ob+uU3j5K954mvjWU6T5lRaEVAw5fN4+IJGCcYq2cgHIUdXMk22WPv9SbyP08aNf1r4HHapgMMSneFPyjqZTCCCQCAFXOdip8472m7Wx1P7zsgf+rmUXdLv3j7LAe0ZH7b3ea5rWZBv7djJC8PrV8M2w5b6soCO6ya/WUPEqjZlDQVj6e3sLhkpVULBcubl59dshrp5yAgQgKTcldAgBBBBAIAMECEAyYJJTeIgEICk8OXQNAQQyV+C9yW+p6349vSU6NvBvqY2aXqCvmh5SKQDx/fVvhXIPUnFN9wDJH67AoptUap+CjdpfwUbHKry+BSCJ3DzdlyXfgmsUtb7EDnv41nKQ1PS0SpPtBSCFb6pNs0Ga2+z4apdpCfxxkZ0zyYxiL5345hvav8fhmXvTMHIEEMhYAVfJ4KoHN27bXr6Azx7+/2gW1VU3WCXEjA7q2nKspjbdzM5Jv6WfvABE9j636QwjKFrlnnAmYQVmbm8fBIgtk+WWwPL7y95IMvYOyqyBE4Bk1nwzWgQQQACB1BAgAEmNecjUXhCAZOrMM24EEEhpgVgAsjLw8FlQYNvaqnVoBzVt1lff+f6ULAAJ5h5gS2A9VLOxLB0m3+IbbRWQ2EMxrwLEC0ASePiCCv05wCpARpR9HtkFINcp2vSUSp0I/XmVSleMtVHb8i0urrGKlVhsE/sUswuG/PbJ5XiY03Grjhry7BParUu3BA6GphBAAIHUEgjY7uduX/NwNEeHNDlH45tdZr/sK1RB2IN+34zOirb/KuHVf4mScgGIz8L2qM+W93IJecS9bzgDn3ItHCq295FwxL23lGjx3wvVrHnLRHWNdlJEgAAkRSaCbiCAAAIIZJQAAUhGTXfKDZYAJOWmhA4hgECmC6xYUaBRrw7XKb3OVjC7q1qtf6M2WvikvlphAYbfIoDS+JIlUeVl76vSDe5QobfW+xoOF4AsutE7yR6ByW8VICVeAJLgNdDtwVS7hfcoumycllrwsaTZSfZcqvJGvBsXfKj8xQ9oWfGXsqzDgo54+LFyjD6/fXK5tFQ77bKznnzkfu24655rEuDnCCCAQFoL+HwWEAetAsT2+vBZ9YPPn6ut8rbS961et1/1S+xvqwCZs5022/Az/Zblqj9CaefhApCoReZtWzTT3CVLva0/TEQhC0Oi9h4atkAkGrQAJBzWaaeeoCEvjkg7Awb0zwIEINwhCCCAAAIIJF6AACTx5rRY4fmRlcwn+MkX/AgggAAC/yTw9Rcfe+HHD9/+qFwLOJa1XrnHR6PwHLX7+3H9XPiGfai1RG1tk/SWTS+25bH2XSNqbvEstbYQpHjFNBXk7adFra6y19ha6Cl4+FSk3Pn9VLBigtTq9mr3AQn8caG3BNZOO++spx59gAAkBeeRLiGAQGIFvAoQe9hfMu1uffDlXO110YPKKY3Yb1T7v/tWDLGldtRPpZ+7WghbJuszWwErDZfAmmUBiIXjhVPuUbbLd6rZ5mSLkwfr1xlztVHrjfT7vN8TO0m0lnQBApCkTwEdQAABBBDIQAECkAyc9BQaMhUgKTQZdAUBBBCY/ssPuuzKqzR69Fg19bfURnmH6af1bI+MVas0bBN031+X2R4gB5btAVJhg9t/ZIxvhuseCtlrUnYD3BLlzb/KApDxFoDcYQGI2yS9cl7v9gApLZ5UvqTXxPGjdMDBR3ITIYAAAhkp8Nefv2uDDTdWtlU6FH5svzfDlnj4XPmDTxc9MFWPDB9vX4YVtQqIvECuVmzwf1YQ4paCSq8jb2ZnFUSLVfL+PQrakldWDlNlgFuecr9+mT7LvDbQ/D/mpxcAo1mjAAHIGok4AQEEEEAAgToXIACpc1IuWAsBApBaYHEqAgggUN8Crijv/Slva599D3YJhZpm7WxLYN2h6aG2lZt2AcjCyxXKPqDmm6DXd+fr8Po+q27JtX1AVqx4Sx0CmykU2kY5OTsqOxBbqz1cukxz8l/RgvA33lInTZo00ZjXhqvbAT3rsBdcCgEEEGg4Aj99/7W22mYHr+Ch9MO7vfeQ8sMF3lbs4d/9KmWFshQJ21JQbf5n37B9MtLs6DDnGM3z/6qid2+y8VkJSNlm5xWHedLAoRrx38+9b1EMn2Y3QA2GQwBSAyROQQABBBBAoI4FCEDqGJTL1UqAAKRWXJyMAAII1L/ANBeAdO9R3lDAF1DzrC4KtbpGf2RtHnuoZQFIcMFl8ufEK0BsL/HCb9Ri0WOaE8xT0QaD7bz6frBVoZqkzlkqVIDU4Npvj3tdB/Y8qgZncgoCCCCQngLfff2ZttthF9v3w6fS910AUvVotGdfq46I2j4hWerY6mX9mLeFJQDptQ9Ix3nH6bfIdyr5eLBmzQurwxEDLBC6rRLGksUFan7Itd73Sm25LLd3CkfmCBCAZM5cM1IEEEAAgdQRIABJnbnIxJ4QgGTirDNmBBBIaYF4ALJdx0118C4dde+wibYJuD2jss1b2/m31OY5J2m27Rn+6+KbFcg+SOENH1Lz5ZPUdNEdmhWZrixfjnJs6ayl3gbn9XOEFt2n0qVPWBZjS6w0OVeRlpfWaUPxChC3BNao//RW15230I/T/9KCJQW2gW2pWmUHtFPnTXTqrSP1xpSvRABSp/xcDAEEGqDArz/9Tx236axgJKiiD+yBf/yZfsB+T9tKWLb2lb74bZl26XWzSiMR+ez70U2+b4AjXU2Xo7acl41R87ZSKOpX8bTb5evi9rqyb69SEbOkoFDN9x9oP/EpYnuk+AlA0uc+qMFICEBqgMQpCCCAAAII1LEAAUgdg3K5WgkQgNSKi5MRQACB+hdwAUjX/Q5W9x231pt39VYo6Ner73ylPre9rJKSsErtWZa3ormlIo2zuyqn1U1aUPSptDD2oMcdgdyeimx4b710dtOl4y38eEozw996198kuJ38zc/RzMZu2a66OmIVIG4JrJE3nq6jD9qh6oXtU85H9nteowlA6gqd6yCAQAMWcJUMwVDQtnYKKTrtVhtJWQLiK9Zdz3+sq87cXypZoQWLi7R+z+tsScGQNm16sX5ofm4K7wf1TxMST3iK3Lue/R1Vlz8G6sPwaE36zxnab59O8lnFizvCHz+gQGlJ+cWWFhSp2f4DTMgCEBcG2fsJR+YIEIBkzlwzUgQQQACB1BEgAEmducjEnhCAZOKsM2YEEEhpgXgFyEF7bKMJD55tT27KNnC15zOlFoC8PP4rnXL7CG/vC3/OQSrd4CEpf1R5ALKyAuSWlQ/A6nTEhcpZeJ8K85/1rpptFSdqcoGKWp5fZ61sVvSjliy6SwuL3tNrXgDyr6rXtoqYI/oN0RgLQG69+Tqdd8HFatlq/TrrAxdCAAEEGpKA28siEAzYe4NVdrx/Z3nXu5zzpD7+308qtYoIK/uw70f16Guf69LBIxTxRRRt+6t9L9yQhhrrq7d/Sba2nXm0/qcf1djGX2CbvEesSjD66X1S8Qr59xrovVdGP3BjX7nUV35hsZrue01svxRvjxACkIZ3A6x9jwlA1t6OVyKAAAIIILC2AgQgayvH6+pCgACkLhS5BgIIIFCHAuUByO4WgDxgAYhb/6rCMWnKdzpwwDPekiZ5gVZqmnukfm91pdZb/q5aLR2qiG0W/kuL8+x5TnYd9qripXzyL7xX0fzH7AFUVMHGZ6vEWwKrLtvzKTT/cl13ml+XHrebmjaxkMUtt+U9pCrzsIddR179gkZP/Vrrrb+eXn/5Re1dYe+Ueho8l0UAAQRSViC2l4VP0Y9sD5D4W0cgW8G9LlPT7JAWTbjBfm/bUlEKyb+3VQ1Gi+UPBGwfDL+9Kqw8Cw9ah3bWlnnXqzTL/c6NFYe4PdT9xRaShOcqWGp1Ez6rNLHfwRGrUIwEm9qyW0vkL4k1GPX+soDevi4NBu36TTS65R7yRcJ2rcrvZ3bV2O/0cKF1qYn9cZl6zv/Crrc89vveAg17N/Dacn99q3s1e8WP9irrbcBaidp6kKXFCtj7Q8SCjA4d2mvGjJmKfmwVkNaeb8/4Elh32fVi4/EOC4JCXfvZKSW2HJgLQDgySYAAJJNmm7EigAACCKSKAAFIqsxEZvaDACQz551RI4BACgusrADZVhPuP6tKAJKfv0KPvv6Jrn50jPd8K5jbQ+GNHrBnSKs+WErEIONt1vWnZ8PKsSWwbjwjpIuO3V1n3/6aRkz8P425pbcO3X/7+BMsHdnflsCa+pVatWqp118Zqn32rctluBLhRxsIIIBA3Qn43b4e9jw/+pE98HfJhTv8tsn37lcpaCFByaf32DJYZQ/8LfQI7XWlxR6lCoVCar1hE82e87f8oSxFSoq8ZaFcoBIPCNyfo6sE8vGer3pu3Y2o8pVifZAaNWumgvylFnwEbF+oEmVnZ+vFIU+rd6+ztMItFTnNKmBc+LJHX9sWpMQqQGzcFd+mLPTx7XaZN8ZI2JbAYg+Q+pqylLwuAUhKTgudQgABBBBIcwECkDSf4BQfHgFIik8Q3UMAgcwTiAcgO3baXM9ecbh22K6dIVjQEP/krD3UclUghwx8znsYleNrrVaNDtPMVlfYeXUdRCTS34Upsf5vZnuaLF50v566ZmsdfciOOmXQMA2b+KkXgBxGAJLISaEtBBBoQALeg3wXEnxQoQLE9d+qP4I7Xa68Jo209J0bLVi3FKE0rMMGDte4ad8oYNUSrw57UX4rksht1EgHHXq0N+phQ57xqi/cMXHSJD37/EteaDDkmSfs3JUVFaf2Odt7P3rphafLtVxfTj79TO/8du3aeu3Nmf2nVWq4pasqHn61aJKnrKygmrdcTz/+/Iv3TjDkmce9DCdgiUdWXmMdd9Lp3rVeG/6i9+JS69dxJ5/utfvQ/Xer9QYb66TTTrdVI0Mqff8/nkNO16tVFDaPaTfbK9zyX2WHP8tCoUti1zELApAGdJPXQVcJQOoAkUsggAACCCBQSwECkFqCcXqdChCA1CknF0MAAQTWXSAegHTuuJkevegQ7bXbpnZRv6a+/4PuGf2x3rijl9fIu+9/r5NuG6E/F+arWdauatn8Kv2WV81m4evepYRcIS+ar7YLHtaCgrH6O7rAa/PV60/VMT130qmDXtJLZRUgBCAJmQ4aQQCBBijgHuS7x/zhD20JKLdOYoUjtPc19q2ISt6zDdIDtgyWt65VUL49rrAAIKp266+v+x+4V7l5uepx2DHeK19/eWj5FcZNmKCnnn5BjRrleUFHxaWjjjnpNC+IqHi+CyuOOu6U2HVGvKSIgtZsxHKQiPJyc3To0Sd44cqrw15wu5Z4IUTUltc62q7ljlGvvlRecZJr5x98+LGVAhB3zrEWgLh+uHb9FqAcfewp9mfb1+TDe/Tz3GXa7vgbVWwhSvR9C4TK1wSz4hBbGsstmXX4YT31+qjRClhFCEfmCBCAZM5cM1IEEEAAgdQRIABJnbnIxJ4QgGTirDNmBBBIaYF4ALJdx0318HkHqeueHb3CiKku8Lj1ZfU5tItuPf9A+55Pb07+RocOeM5bBqRt1m7KDW6mpYUfqGXecfq2VR8bp3uok2pVIbF9PNqH52u9/IlauPxVzSz9wVZpsaVWylaPdxPkHp69eu1p2m7zDXT+/W9q8mc/WAVIr0oVIEcPGKI3pnypxo0aa+zrI9R1/0NSem7pHAIIIFCfAm4JLH/Urw+fuky7btdaG/e8QTPfuEUhf1hvfzxdPS9/2Nudo/QDq4jw295KXnGHVUB0sb0yrKJj9EvPKrtxkzUGIC8++2T5MIKhoI487uTyICL+A1ehceyJsTCjYjDi/nz0Cad6369Y0RH/czw0WVMA0qxZU+1/yBHedVxViHtnOfrkM23JqyJbAuwO2/9jkC37VaqJ9/1b3XdpU9atoI6/YZRGvT1FtgKYt/wVR+YJEIBk3pwzYgQQQACB5AsQgCR/DjK5BwQgmTz7jB0BBFJSoGIA8tC5B6nbXhaA2OEqPvbr97QO3buzxtxmD5X8Fm7Y0h0jJ36l426ILQmy6mEruJd95vWf9wepGJGsemYsrrAruWVVyq62iX9bNQ5tZX+yrWjtU7QBlSg//JNmhX+QPXtzZ3sfPo5viVuxX9WuI2/XDgV82mXXHXX80UdrzJuT9OnHH2rYNSeqZbNsXfbEf/Xpt7+ssgSWu2pUh/Ybove+/E1jXhuubgf0TMk5pVMIIIBAIgQGXdNXt9/zgMLv3W7NBdTywAHadYetNOGuWBCR1/0arSgq9vbHiL53h33HflFbgO7b06pDVKyLzjhORxx9cnkAMnKELYtVtj9GxQqQeAASsfegxlYRUl11RqUKkAqVJK4f8QBktP3erhhCVHzNmgKQsW+9paefGeJVpLj+5Ib8OuToU/Xq7Wer3+Nva/qsWTa6bFv+yo2zxMZZqt3PeUqff/uTfDb+goLlxhBKxLTQRooJEICk2ITQHQQQQACBjBAgAMmIaU7ZQRKApOzU0DEEEMhUgZUBSAc9dG6P8gDEebz7noUgVz+jI7ruoFG32wMtSxi+/G6WLn1koqZ9/r327tpVl17QW5/93/saNnKcZs34006JL4MSjznWbrN079VlG9DGQpGV14mFI7FnaZaJxGpObDmUCmd4r3CHF47Y0WbjZtpxxx20f9ddtEm7Tpbn5MZ+bte67+EnNW/mL3riwoP1nW3Ke+8b7+uX6b9XCUD+/GuxTrnxVX0+/Q+9YculsAl6pv6vhnEjgEBcIBAMqF3r5pr+2vVqut81yl9mm4B/eFvsl7OLra3aI/6+EP3uWWnJIt3+0qe65qHh3u/ft0aPrFUFyGX9BmjmjJlVqjlcf+JBx+oqQFb9fm0DkOdsT5KILXn18kvP69VXX9HrY8brxB7d9OLY/3oVLdGPbemrsL332B4noX2utoA+aG9NYf29cIGaNW/JTZOhAgQgGTrxDBsBBBBAIKkCBCBJ5c/4xglAMv4WAAABBFJNIB6AdNqive44cz8dvn9nL0xwucGkaf/Tgf2etQBke4264/TyJd7HTvpaRwx6wX2QV927dtMl559TLytf+eyBklsqfd686Zozd07sYZr90xZQUds2bdSmTQdb0z3kPZCKuk121+IoKirQw088q6aBQt19xr66Zeg0vfTOJ+rVYw/d3LurNmm/QflVj7z6BY2e8pUuuehcXXPNQLVu4zaM50AAAQQyU8Bt6O32s3BBc+nHt2jqN4t14Nn3quir+6SiIgsCzCVcJN8+A2x5KJ8i9vvcH7Z9QHxhRWwfkFAwS6NHDvMqOtyxuj1A4hUgLrA4xpa5cvtwDOh/hXbdeedK8PUZgLi23fXd3iNvWJ/D9pZzwkm9bOQlcitbbdWmmX4YeYO9Tbklvq70Ahq350lpiVXAcGS0AAFIRk8/g0cAAQQQSJIAAUiS4GnWEyAA4UZAAAEEUkwgHoC4bvXYY1u9de9ZWrGiSAsXLVVe4zw98OpHuumZN3V0t39p5K2xZU2KC4v19Buf6qL7XtNee++hS8/vo1BWk8SNzBV31NFWI/Pn/6onn39FF+2/jc44fFedeuPLtgH6p3pxwAk65ZCdvKVL3DHgkbf1zJsfav7CpXp73Os6sOdRiRsvLSGAAAIpKnD/4Dt02ZUDtWjKnWoRDMu319W2GFZI4Y9usjDAlnxym59bSLJBj+u0YHG+ywdi/1EQ9OnKC8/RgQcerB6H//Mm6BX3AIlvRL5qABJfosrtS+KClIqbpq8uGMnJydYhRxzn9WdNS2C5c+LXGWN7QBUXlmjpn3N15uVW6WGhSLPGufru5Ru1Vc/+Wl5WgegConC4RKFQVorOHt1KhAABSCKUaQMBBBBAAIHKAgQg3BHJFCAASaY+bSOAAALVCPz4v690/sWX6b2p79l+H9vrjVtP0djJ3+qxt77Q2Lt6a+KU79Tjalu2xEovjum+o179T2wz2VETv9TR1w1R0PbS6Nqtmy467+zytdsbEvTzQ1/QO5Pe1fN9j9ekL+foufEfaEVJiV6/sZeOPGB7byjv2FJgfZ/5r77+abpuv+UGnXPehWrRcr2GNEz6igACCNSLgHvIH8zKtc3A3dJXd+uE61/TyEkfqUvnjpr2eB8r2YuFyN7uTl362b+tQsICkdEvPCWfvS6Um1WrJbBWF4DE9wxxLb0y7AV7b7JyEzuefuFFjXvzLas68emVl16o9D71xLMvaPz4CWq9cWs99uDg8tAkNzen2n1GKgYg4ZKwd/23R72mR18aWcnWVX+4vUZcmxwIEIBwDyCAAAIIIJB4AQKQxJvT4koBAhDuBgQQQCAFBd6b/Ja67neIenTZVs/3P1Y32jJQM39foHH39I494Jn8nQ62EMRnYcdx++2kEbecrOIVVgUy6lv9t1AAACAASURBVFNdaFUgLgC5/MJz66wqI5FE9z/6pKZMmaK+Jx+oT3+crXf/73s9d/XxOv3QXWz1kqAuvHOshr79oZYuL1TPngfrnjtv09bb/iuRXaQtBBBAIGUF4stguQ5GP7Glr+zBv7/71fLZPhifPnOtdtqqhbcslNsjQ8Fs+Xa+xM4s1dBH71Jui4008d3JevSxp73xVazCqG4TdHfO6gKQrOwsHXrk8d51XIVGPKCIn3/tgKu0078q/+6OByBt2rbRQ4PvLDeuTQASjUStT73K9znZZttt9fVXX3lLg3Eg4AQIQLgPEEAAAQQQSLwAAUjizWlxpQABCHcDAgggkIICH3/wro4+/hRt376VLYF1pt794HvdOuJ9jbJqkLw82yzclvcYNekbHXPDC95SH+s1a6zD9tlJ7TZqqpueGmsBSHddbvtixDceT8EhrrZLD1gAMnnyu+U/37bjpnrykoPVZZct1evGVzR80icqKYnoqKMO1x233qKOnWJVIRwIIIAAAjGBH777Uttsv5P8Vu0RnnaHZEtLhXa/zKpCLA/5fLD9o9DeHiwAKY1o7wue1gdf/2zvJT69POx5nXRaL6/yIicnR0Off6q8QqO2AYjrR3UVGvEAZNA1fbXzjjtWmrK6CEDc/iclJUU6/tQzvGtHo26NRg4EVgoQgHA3IIAAAgggkHgBApDEm9PiSgECEO4GBBBAIAUFFvz1h+6/d7DGvDZSj1zUQ8VFJdr3qqcs5NheY+6MVYG4cGPMpG9t8/Pn7Gu3uav9y22WbodXAeIFIA3tiHpDeODRpzTl3Xe9zg8ddIpOOXQnnXztcI145zNvJffhLz6jY088VcGgrWfPgQACCCBQScA99G/WrJny8/O9DdEVyLG3jGILOSIK2DJQLS1I/3PidfbWEdLMRaXqcOhV3vvISAtAjju1txesXz+ov3b81w7e1+5oKAGI62vEQvLjTu0Ve6ckAOF/HasIEIBwSyCAAAIIIJB4AQKQxJvT4koBAhDuBgQQQCBFBaZOGq9uB/RUjz230x19uuu0u99UoS1lcvXxe+mso3Yp7/Xk97/T6XeN1Nz5i8u/13ADkNgQCovn66HHhuqDaZ+XBTsu7ok9hBvy7OM64ZTeysrKTtGZo1sIIIBAcgXiD/2zs7PllsSKRKz0ww63F4Y73G9Tn8/2AgnYV7Y0lqI+bdq+ne647Rb7/RoLDl4dNsQLDwJuqSw7XADy9LNDlJebq5psgu5ek4wKENdu2EKb4086LTZWApDk3owp2DoBSApOCl1CAAEEEEh7AQKQtJ/ilB4gAUhKTw+dQwCBTBZwAUj3gw7V/jt30ug7TtNHn83Qfv2fVvedO+rF/keqTZsNYjz2/Or1d77UMde9oDZtW6vHAd11xCGH2fMs7xFXwyS0h3H3PfpEeRVIfBCvvzxUR9nSYBwIIIAAAjUTcAFA/tLFXhDStFkL2/rDr0AwUL7BuLtKyPaTemXEUIUtZD/BKkDcElju923FIx5muGUYhz73VPmPVrcHiDvBvcaFLqNHDq+yB0h9LYHldSzg95aRdO+A8+bM0kat29YMi7MyQoAAJCOmmUEigAACCKSYAAFIik1IhnWHACTDJpzhIoBAwxH468/fdd/gu3XrHYPVc+/OGndHL41652sdff0QHdltB42KL4Vln3SdPO179b57pGbP/7sBL3+16txENWzky5r0zrtauHCpRo54UcfYwzQOBBBAAIF1F/jR9gnp13+gRo97U9t22lq3/ecG7+unnn5BfgsQRloFSMXjGKuo8NnyWW5prO233a78RzUJQN54dZgVmsSqUGqyB0jrjVvr0QfuKV9+qzaboMc7dt4l/9aCBYvU3fbEmjRp0rqDcYW0ESAASZupZCAIIIAAAg1IgACkAU1WGnaVACQNJ5UhIYBA+ghMeedN7X/wEd7yJbtsu4WO2mMr3T7sHS0rKNIBu22rF645Vq03auYVeoyZ+JWOuPYF7b7H7rro3D5q0rhpA4eI2sO4cZo48V3N/eMPvTb8Rao/GviM0n0EEEgNAfee4sIM+4e3xNVxh/fQyaedrl5nnqvlywt0zlm91bPHQVUCELcfSKNGeTVaAqvUKk+OPTG2DNUrw15QMBBYYwASrzJZ1wAkYtUux510uld94vrsql+88XIgYAIEINwGCCCAAAIIJF6AACTx5rS4UoAAhLsBAQQQSHGByW+P1X49Dvd6GX+YE+9y0D6le8x+O+v607qq39OTNG7ql+revbuuuOQ8C01KU3xka+6eC0DemjhZfxCArBmLMxBAAIFaCLilsVwo4JbDevbpB9U0r7lOO+McLwA584zTdPghh1S6mgsnXGWIe4+55LyzvJ+5kOO4k0/3QoYB/a/QrjvvXP4a93511HGxJQsrLqf1TxUg8SWzxrw2QkVFxfKXhRarqwCJX2uj1hvp0fvvqdLf+DcIQGpxY2TAqQQgGTDJDBEBBBBAIOUECEBSbkoyqkMEIBk13QwWAQQaqsBP33+ty/v215tvvqWcnBxt3amTNtxgfU2Y8HalIbkHTt26dtO/LzynoQ61Ur/nzJurp54bqq++/IolsNJiRhkEAgikkoCrBAkGgxpl+31ELMzofdb5WrZsWZUAZObs2brsyqu9ro969aXypancn+NVGxPGvqaCghXlw8vKztKhRx7vBfcuAHEhiTvWFIC4c8a8PqJ8zxD359UFIE88+4LGj59g+1+10UOD7yxvO14BEv/GksWLvP1POBBwAgQg3AcIIIAAAggkXoAAJPHmtLhSgACEuwEBBBBooAIlJcW2rMgQndr77PIR7GPhx5UXn2f7orvqj4a/3EcwFNRd9z2qqVOm6JEH7lZvW54lr1HjBjpjdBsBBBBILYERQ5/TyWeer1HDnvM2Pj/9zPOqDUAut71CZs6c6VWMuDDDnesOVxHiAhD354rLXLmfjX97op546jkvtB/+4jM1CkCOO7mXt+TjqgFITk62eh51vHeNeDWJa/vxp5/3PhgQCoX0so2l4hEPZtz32ndorxnTZ9gm7yUW+IRSaxLoTcIFCEASTk6DCCCAAAIIiACEmyCZAgQgydSnbQQQQKCOBF6zB1LHnni69unaVVdcfG4dXbX+LuOimdhngdd0+DT4ocf03tSp3rrz7mGd+0QxBwIIIIDAugtsutmmmjFztka/ahUgtkn56gKQ+Abob48bpfyl+eUNuyqPI445yQstVq0Mca9xgYWrzrj/7tu9vUbcUZMKkFWvFX+dW7bL7QflDheAuOPIY0/2qkwee/BebbD++uV9qxiAuJ+vKChQdnbOuqNxhQYvQADS4KeQASCAAAIINEABApAGOGlp1GUCkDSaTIaCAAKZKxALQE7TXvvsrb6XXNAAIGoegdz94KN6/71p3pjcJ3+POj62pjwHAggggMC6CTRr3kz5y5brNduk3B2rC0DWtMyVCyNGWkVixSP+mnFvvKJi288jfqwpAHFhRTzkqO56FfcTcT8vCYd1wim9vUBk+JBnFbIlvdwRb99931Wo9D79JD37/Etshr5ut0xavJoAJC2mkUEggAACCDQwAQKQBjZhadZdApA0m1CGgwACmSngApATTuml7t266uLzG8L+H67+o2ZLdA1/daTemfSuFi5cRACSmbc3o0YAgXoScPt/ROyv14cN9VpY2wCkutAiHkCMH/2qCguLykewugDEBRWumsMdq4YcbrN1F/K748ILztaB++5bScRVm/h9ft10/QBts/XW3s/i7Q9/6mGdfO7F3s9LSkq8ACS+AXw9sXLZFBcgAEnxCaJ7CCCAAAJpKUAAkpbT2mAGRQDSYKaKjiKAAALVC7gHOW+8Okxnnn+R9tu3m0478YSkUrVu08hbSuXP+YXr3g/LSXy+iO5+8DFNe+8DPf/0ozrx1D4sY7LuslwBAQQQKKuG8GnMK0NsE3S/TrV9lpbbJuhnnXm6Djv44HKhNVWA1EUAEg8tAoGA3hg5TCXFJeXtu3DkUtuEfdasWZX2AYmf0H/Qjfr5l5/VZc89daVVQdp/4OiYk06XLyC1tM3PFy1aal9HvfcmdxCAZPbNTwCS2fPP6BFAAAEEkiNAAJIcd1qNCRCAcCcggAACDVxgxm8/6qabb9aHH3+qU046Up07/auBjahUtky89+nc1R3xZbDcQzYX9hx+9IkNbIx0FwEEEEgtARcC+G1fDhcu2Je2L5P9w34Zu9+zo0cOVYktW+UPZinkD+iw407ygocJY19TQcGK8oG4PUDcvkx1EYC4a7igxbWz6ibo3n+0VPh5xQoRt7xVYXGR+px9gSKlEXuPGK4sC86PPuVMFdoYorY/iVdzaK+Pb96eWjNBbxItQACSaHHaQwABBBBAQGyCzk2QVAECkKTy0zgCCCCw7gIrA5DPdMqJR6nzNp3X/aJlV/AHfPYJYdmnZmu2ZfnaNeyevFkj/7Ai1suvjdTbEyfbMlh/6+WXntcx9pDMfUqYAwEEEEBg7QXmzJquTdpvVuUC8X0zttisnTZo0UIffPaVd059BiDu+vFKk+oCEPfz+MbqFQMQn0p04+336YvPvywbh0+hQEglkZX7jrgfuADEVYC4JbA4MluAACSz55/RI4AAAggkR4AKkOS402pMgACEOwEBBBBo4AJffPqB+l59reb9Pq/OAxCPpubbddSr5J33PawPP/hA1w3sp0v+fbnWW3+jem2PiyOAAALpLuCqQEpLS71Aee7M33TBRRdrzLjx1Q/bAoSdO3fWoGv6uZI975y6rABx11s1AAlbdUeO7WleVBzWY08+qf++91HsbcmVrLh/l1pXLKivrrLDBR5PPHy/zjrvYi/02H///TVp0qR0n1LGVwMBApAaIHEKAggggAACdSxAAFLHoFyuVgIEILXi4mQEEEAg9QRGvfKS99Bo605b2RJYVgHSafvU62Qd9OiZIUM1efJULbP16Ue/NpxlsOrAlEsggAAC1QlEbNmoM/qcqtdHjVPBioLygCFeGdI0L0e9TjtG3brup+N7naOsYEivDHtepbbJeOyw5azcHhwWQowbOcI2QbdqjJDf/hzUscfbcloWYJx03NHqvHUHbbppR+Xm5Slgy3EdceLp8tteJLm5Ia1YUaRSy1ncklgVD5+d5y3YFVs7USFbPtFt7WE7fHinFdtyWEHrD5Ue3NurEyAA4d5AAAEEEEAg8QIEIIk3p8WVAgQg3A0IIIBAAxeIByDugZN72NShfXsdcvC+2q97N+9hk78+V6+qV7tY6cnCRQv1yJPP6fPPPi9vzW2Q6/YB4QFXvU4AF0cAAQS837MB+108f+LdWu/AqxTwBW3D9MrLS8WZXDVGli0/ZYUZZWFEsfe+FLSQwu3EUaM9OGxPEp8tixiwgCNsr3GvdxeM2ibmw28+Ryfuu1XVWYlaD/e83L4fVcHyZRaoNGLmEFitAAEINwcCCCCAAAKJFyAASbw5LRKAcA8ggAACaSPglsC6ov9AvTv53VXG5FPTZrk66KB9ddqJJ9pGsEF7hmSb3pYvf+6+SEI64uUa1a2rFdXM2bO1ePFifff9D/rok//T7Flzq50nVwFy2FEnEICkzV3MQBBAIFUFXADik1+lHw22igx7Dwllq/e1r+qFcf+tly67wOOcI/bTvZcfprxcq/bwhd2aV94G7bL3Mfnj8UqF5n0WgOxxmfeNXXbdVZ9+8km99I2LpocAAUh6zCOjQAABBBBoWAIEIA1rvtKtt1SApNuMMh4EEMhIga+/+Fh9+w/SxInvVDt+9/jKVVO42KHHQd114Xm97JO4oaRYBW0ZlPffn6xJ776nvxf/7S3iPv/PfOXnF5b1xz7x6/V19eEMS2AlZepoFAEEMkjALVP1+9xZ6rDZliqxpa2iH95TefRWpWFlGhZMWCjhAoq8XA0e+qH+WLDY25uj1JbRGvziWO81Bx54gPy2dFWvU07Qyaef6S2B5QUrFTYknzdnptps0sE7P/rhYPfPmmtbX+4e8Yn6PTjce6+rUaVJza/OmWkmQACSZhPKcBBAAAEEGoQAAUiDmKa07SQBSNpOLQNDAIFMFliWv0SPP/qQF4pUf/i047+21aknHKnNt9g29qBpnTY7jz+oKi8v8ZYtiZYu0RdffK7x73yk77//RcuXuZAjHm7U7OHW/YPv0FnnXKBGjZt4S5sEQyFlZWVn8vQydgQQQKDeBdzm6P+++Hw99OiT6rbb9nr3/t61a9MfkW/3ft57QcHy5crJyf3H18+e+YvaddjSQhV7j5jmwpZV3iNcyFIhMKl6sYBCXS5XxIpGSktsP5CV5Y616zdnp70AAUjaTzEDRAABBBBIQQECkBSclAzqEgFIBk02Q0UAgcwUWGEb2I4c8aKuu/l2Tf9tuldd4T0YsuVEKlZZ5GZnq/2mm2jvPTtpry57qmXLTT0wv69YwUCh/vhzvn2qNltz/1ioN8a8rR9++FHLlxdUQvXWanePrVbZtLbSSWXruW+84fracIOWapSTpRZNG+vUvTvq89/+1MuTv9CMOX9o2JCnddJpZ2TmpDFqBBBAIAUEzjm7t556+gV13bWzpjzQp3Y98tuyVLvHlqX6aMok7W4bpv/TMWvGz/Ye1LEsALm7dm3F3q0Usn1Awi7Pd2EJBwKrESAA4dZAAAEEEEAg8QIEIIk3p8WVAgQg3A0IIIBABggMefZx9TnnQu2/e2fde0EPffPTHF368FgtWLTUHhnZciFmEHW7pVeztPra8qwMQ+xDu/aJ3D49uuiqk3fXVptuJH/Qlkyp5li2dIX63PGaRv73cwtAniEAWVt8XocAAgjUgcDJJx2n4SNGap+dt9XUh86s3RXtF79vj8u9CpApE8ZpnwMO+cfXlwcg9n4RfX+V5bZq0rJVh2Tt09eW6ypVIBBQOGx7h3AgUI0AAQi3BQIIIIAAAokXIABJvDktrhQgAOFuQAABBDJA4IVnHlPvsy7QOYfvoycGHBUbsUslXOJh67TPmrNId7z8iZ4b974KCotqLOIPuPhk5bJX7oWltvi7qwA5eK/tdXufbtphO6sk8ZYtsYDFa7Jsua1qW4mqz42v6Pm3PtaZZ5ymawcNsvXnt6pxfzgRAQQQQKDuBHr2PFjjx0/QbjtsrY8fO6d2Fy4LQNyL3ntnvPbe/+B/fP0al8BaU+vRsEZMnq6TBj7mhS7sA7ImsMz9OQFI5s49I0cAAQQQSJ4AAUjy7GnZHklZiTg14twJCCCAQJoLuAqQ3mdfoLMO21tPDrQAZHWVHvE108uXsPLpwaFTdfVT47WiuFgD+l2hm2+9y9OquHltRb5+ff+tu+55QAfssZ1u69Ndu+wQW0qrRoflJH1ucAHIR2rTto0ef+heHXrk8TV6KSchgAACCNSdgPtPhJ4H9dBb70zUzp231v89sXYBiAsjpk6yAKR7j3/s3OxZv6ld+829JRqj02wJrMrZeg0GZhUfwSwFd71CEbfAI/+JUwOzzDyFACQz551RI4AAAggkV4AAJLn+md46AUim3wGMHwEEMkKg2gqQGo582kc/65rn39W0L3/QoGv6lgcgq3v5ygCkc1kA0qGGLcVOe+L1T3XPyA/1068zNfzFZ3XiqX1q9XpORgABBBCoG4GDDjpQEye+o39ZAPJFbQMQt8CibUrujvfenaC9ux30j52aO3uG2rbbNFa94TZB963FZ7Tstb4ufS3kt0pEApC6uQnS8CoEIGk4qQwJAQQQQCDlBQhAUn6K0rqDBCBpPb0MDgEEEIgJrEsAMn3WAg18bqqGjX+/VgHIgV2213+sAmTX7dvXahpmzV6k8+4bqwkffa3hQ57VCaf0rtXrORkBBBBAoG4EunbrpvemTtUO226lL586t5YXjSqwdz9biiqqqf99U/vsu4YlsOIVILa0olcB4pZNrO1hAUhw975WAVJqGUip7QNSolAoq7ZX4fw0FyAASfMJZngIIIAAAikpQACSktOSMZ0iAMmYqWagCCCQyQLrEoDMmLlAA55fmwCkswUg+9Y6AHGf+o0tg/Wx+vQ6Wddde5023WLrTJ4+xo4AAggkXMBVUBxxxKEaO3a8GjfKVf47t9SyD1GvGiNge0DtbUHKu5Mn/+PrKy2B5W2CvhYBiL3Kt/eVVnviV3FRsbcZOgcCqwoQgHBPIIAAAgggkHgBApDEm9PiSgECEO4GBBBAIAME1iUA+W3mX14FyPC3PqhVBYjbA+RWF4Ds0KHWwr1vfFkvWADSpEkTvfjcEzrimJNqfQ1egAACCCCwbgJ/L1qglq3Wt+04Air98M5aX6z7v5/X1P/7RqFgSEVFRf8cgMz8Re06bGn7eFj08Z4LQNbu8He50otOfvnxO222ZafV7le1dlfnVekgQACSDrPIGBBAAAEEGpoAAUhDm7H06i8BSHrNJ6NBAAEEqhVIVgBS603Qy3rf94EJemrsNC3JL9DLLz2v40/uxcwigAACCCRYoGD5MjVq3MTbj7z0w9qHEsfeMEqvTXjP67Vbkspn1SCrO8orQKxoI+r2AFnLw9/takWLS2zZrfFrXHZrLZvgZQ1cgACkgU8g3UcAAQQQaJACBCANctrSptMEIGkzlQwEAQQQWL3AugQg02f8pQGuAmTCBxp49ZXeJuj/9BCrfBP03a0C5Iy1qwC5ygKQJ8d+YAHIMgIQbmwEEEAgSQLL8peoSdPm8lsoEVmbUCIrR76dL7beR9e4KfmsGT+r/aYdZcUmFoAM9l6zNkdo76sUjpSqRcsWWrhgIRUga4OY5q8hAEnzCWZ4CCCAAAIpKUAAkpLTkjGdIgDJmKlmoAggkMkCLgDpc86FOvuwffTEwCPto7g115g9d7GufXaKnh83NWFLYD044kPd/8aH+nX6XAKQmk8VZyKAAAJ1KuD2AfH7/cq2vTQKp91V+1DCZ7tx7HGFiz9sQ/LwP+7JMbvSElhrH4Bk2cbrJZGI8vJytXx5QZ16cLH0ECAASY95ZBQIIIAAAg1LgACkYc1XuvWWACTdZpTxIIAAAtUIxCtAzj5iHz05wAKQ6OqXIanycvsQ7u3PTdaAJ8Zq4DV9vQqQfzriFSD7d9lOt/VeuwqQP+Yt1JmDx2j8+98QgHBHI4AAAkkUcBV/Pr9PpR/dHXvvKK1FZUapvXavK7ze5y9drMZNmlU7Ehe0zJ09Q5u032ydK0CyrAKkxCpACECSeNOkeNMEICk+QXQPAQQQQCAtBQhA0nJaG8ygCEAazFTRUQQQQGDtBeIByJmH7qUnrznSljOxNUZqcdz1/GT1e2xsrStAbrNN0HdZi03Q85csV687XtOoyV8SgNRinjgVAQQQWFeBiIUHgYBfnbbppB++/6H8cleeeojuvmi/2J+tsqMmR9R2D/HvdaUXmmRlZWnFihVeRcmqhwtAjjrqCI0ePdb7UXQt9huJX7NiBciyZctZAqsmE5Vh5xCAZNiEM1wEEEAAgZQQIABJiWnI2E4QgGTs1DNwBBDIJIHyAKTn3rEAJFizh1dxozutAqT/42N14gnH6NZbbtFmW3ZaLV+8AuTALtvr1j7dtMv2HWpPbQ/LTr1xhF56+1MCkNrr8QoEEECgVgLFxUUKhbK04K8/tNHGbVUasaWvAkELLkJW9FGiaGmJdz1XO3j24d31xLVH2VcRKZgthe3L8Ar7ofupqw6xgN1+hy8rKVGz/QfYtVauueiCjtUd2dnZKi4uVuNGOcp/59aya9ViGO7a1gcqQGphlqGnEoBk6MQzbAQQQACBpAoQgCSVP+MbJwDJ+FsAAAQQyASBeABy7H476rFLD9V6G7ao1bDvtAqQ/lYB0rx5c28j9L79B6329ZUDkO5WAdJ+Lfay9em0G4Zr6IRPdM+d/9E5513obcTLgQACCCCw7gLVBREbbLiBFi1apKiFHxu2bqL585dbQ1YNEs1SOFqkVq1ytWRRWBF/yCKOQvtewH5mS2P5ir19pVy1h/tnwP5d6io/7KtSvws/Si1ACVnRSIki4chqKzLiAUjTRtbOO/9ZcwDiAg9XzGjLbMmW6HKhi8U2Cu3ZX5FocWzZrgrhy7qrcYV0ESAASZeZZBwIIIAAAg1JgACkIc1W+vWVACT95pQRIYAAAlUEhjz7uHqffYHybAmSC4/aR3f++5BaKT3/xie64YVJmjFvga4b2E833nJHDQKQzlYBYgHI2lSA2LOs068foRcJQGo1T5yMAAII1EQgYpuEB2wpxC233FK//PKLFxa4ICFqYUUokKuSaGHZXh8+rzIkUlqsaDQkfzSs5i1DatosS9N/iwUkqzt8ylHLVkHl54etsqPE2ijVe5Pf1l5dD6jykvhm6+4H227eXt8O+bdVc6xhrxHX50CJlizL0em3jNK4yVPls+5EolaZYofflvH6/JP31flfu1W77FZNnDgnPQUIQNJzXhkVAggggEBqCxCApPb8pHvvCEDSfYYZHwIIZLzAooV/6aEH79UNN9+u7GBQ5x25j+674tBauYx/91td/fxUff3Dbzr5pGN1y003rXYZrHgFyGFdd/ACkM6d2tWqLe9kApDam/EKBBBAoIYCLVu11JIlS7wKCX/AlrmyYGPjto00b+4KqwCJBQhrOrwaD3ttOGIVIF71h62IZRUZrjJEpS4YKbuOBRXNm+Rq8ZKCaqsyXBjz7Vefaufd9pYXzNgyVtt13FyP9T1auaGQHnztYz07brJ3fReUuEoTF3T4Q7ZEV9gqUqKxEMZngU40YlUpgahVOfo0f57rl9uuJNY3N1b3erepO0dmCxCAZPb8M3oEEEAAgeQIEIAkx51WYwIEINwJCCCAQBoKFBau0NNPPKKL/9237JO99tDIbfthz4nco5+DunTW4HMP1DZbb2JPkexTtrZ0SPWHfSLYHkjd/eIUXf/sRK0ocg+Uorp+UH8vUFn1cA+X+l91me6650Hddf6h6nt6N7t+7fYbib07xj+KRgAAIABJREFUUQGShrclQ0IAgSQLuN/RAUspfFZd4Zap2m7b9vrx+3kqKYmFBXV+2K9/n3K9941oaaFVk4S8fT4qHvE+Re19yFVtRC1Aie85Ej8vECtQse9b0YcvYMtw2VJakUYWehRoiy3aavHiBfrrr0L7+cr3slAgx8IYtzyXXU+uAsXez+znP/7vK22x1XZUhdT5ZDecCxKANJy5oqcIIIAAAukjQACSPnPZEEdCANIQZ40+I4AAAqsRcA+SXn7peZ102pnuM7JSoyz58uyB0hLbwDZoD38K7N/eA6nY4R4mua+zc7J04B7b6ZguHb1Px77//R8a98GXmjd/kXde/MGRW2f93DN76+Zb/qMNNty4Si9c+64C5O7BD+rei47QZadZAFLrI7aRbXwJrD26dNEDg2/Xrnt0rfWVeAECCCCAQOyXfdRS8GCWhQH2K9bl3opmW42GbV5etn9GXTn57D0m6tIKO7bq1MECljn2PmM7pdv3i4uKFAyGKjVVatUiQavmcOFEMNuqRZo2Urs2G+mb72ZZNYdf226/gX775Q+v6qPEOp/v3s/K+hxra809z872qyRs+5DYZu6lFqC4gKWoqFBZWbaJO0fGCRCAZNyUM2AEEEAAgRQQIABJgUnI4C4QgGTw5DN0BBBIH4FPP5qqSy7vr48/+sgLK3w5tjRItm1A+3eRe8pl37NMwT1gClkIsqxEwWY5ijYNqdQ2uY0Wu6dHFZcEcU/G3KayrjLEvsoNetf059lDK/tWZMEKXTeoX7UVIOFwiQUgl+m++x/VfRaAXOoFIKtWl5Rd3y1D4p7EeT+PtT9//lKde99ojZn6Zfknec879wwNHDBAm7TfIn0mjJEggAACCRRwv+WffvAenXupVQXa17mNglqxIlyj8KC23XRVHLk5AasqKbXQwb064rUzd/YMW2arfbWXa9QoTwUFK2zpqmwtmB/bwNwdUW8prSz7e90qVPxWQhLwN1KrNoX6Y4Zbmsu9L9r7mr05lpRYdQjLYtV2mhv0+QQgDXr66DwCCCCAQAMVIABpoBOXJt0mAEmTiWQYCCCQmQJvjRmpE049wzaZzY89MLKHPL6Qfbq1yJ46ubXSV/lkbHklR6w+JBY9eA+a7CurEPHZQysXRkTtwZW7Ruyssp+7pUXKHkoNurqvrr/pNm8T3YrH4w/fp7vufUi//fqbBvbuoQF9uik31z5h633k2FIYW4O9xJ6IffTZr3r9k+ma9dcSff3bXP0yfV5ZDFLWhuu3jcVVlMSX59pss830+MODtX+PI3hYlZm3O6NGAIG1FHBVFjdce7VuvvUub5kpl26X2qbmskqItTnc+0bQ5yo5wmrUOEvLl1lAYZcNu2zB3ivcX+7wzgsEVVhY6P3eri5oiO/L4X4WsGtGrFIlFArbtax6cS37t/oxBeyzAa7ypdCub4uAlb2nFVn/3GbvHJkhQACSGfPMKBFAAAEEUkuAACS15iPTekMAkmkzzngRQCAtBP7683fdN/hu3XrHvd7DLF+uVXPYX666wz2EWv2eHus2fFdJ4gKR5s2b69prrtLlfa+pdMGr+12uO+66L/Y9b4kS94W3ZW35A7HqelAextiSXV7fi12AU3amu44LcyKxb+Tk5GjkiCHqecRx6zYYXo0AAghkiIALGVwIEsqyDc/td2zswb/7HW1fW0CxxRZNbD/xQm/5QdvavGx9xJX7N7kdQ7JymtpyVr+XLaHlgop/rsoY9epLOvzoE2u014YXdtvh9ifx3mWiWeqwaZ5mzFxm/Yl4YUVdHj5/QFts2US//mIfHrBLl9o/IpbeUAlSl8qpey0CkNSdG3qGAAIIIJC+AgQg6Tu3DWFkBCANYZboIwIIIFBBwG3gelX/ARr75nh7WmSb2boP8RZaYFC3z4cqmZcvq2XfjRaEde3Aq3TjLXdUOmdZ/hJdc3U/PfzYU/I1tmWz7IFVadkSKyvrTWK5RrCpbYprz94itvSIXLWJ/f1Ph9d+s2xFbZzRIvuIcVmwMu6NV7wgJP4JYm4UBBBAAIHVC7gQxFXurawGrLDHUw3g4hWD3v5RZZuKuxC+1H7ft2jZQnNmzVJObl6NQo/VNXfaqSdo6EuveP2MRCJq17a5Zs1ZbG8ZWWVBuldmUoPe/vMpAV+WNuu4iX75eZZXaeL2zzr+5F7rfF0ukPoCBCCpP0f0EAEEEEAg/QQIQNJvThvSiAhAGtJs0VcEEEDABN4c/aoOPfL48uWo6qPaI/Zgy3FH5bc9QNyngkvdBup2XHXlpbrpltutEsNCjFUOVwFy510PeFUosbXb6/YIeOu0u4oQ64+reLG/srOzNd5Muh94KJ/erVturoYAAmkmEK8EceHC9YP666+FC/XEk895QUN1RzyEiP/M7dVxZp/TtHHr1rp64A1eVYmrmnDXdX/7banDda2icNeZ9u4Edd3vEK9Zf8CCj2isf377WafOG+u7b+es0/4lIVtisUmTRlqypMCqP2LvV/GxpNmUM5xqBAhAuC0QQAABBBBIvAABSOLNaXGlAAEIdwMCCCDQwATiAcjKTWJX3WR83QcUaJ2naLatvz67wCvZcEumuC8GXn2lt4a8O6p7yOUtgTX4/vIHYrZGyrp3psIVvCW4Sv2xVb4CsQdu8Q8C33rzdTrvgovVstX6ddomF0MAAQTSWSC+/FTFMcbDjPj3XEDiwo3V/e6vax8XRrjj5x++scBjx7L3oAr/AeMFLS5rjyoUzNLW27XV99/MVlHY7X1l+1e5EL7s9Bzb32rTrVpp4Z/L9Od8W+bKbz+30snSSFF5FYtrb9Ux1/WYuF7qCBCApM5c0BMEEEAAgcwRIADJnLlOxZESgKTirNAnBBBA4B8E3MbnPY+yChDviAcA/7zHRrWXc8tKZdtSKBs3sjXQI4pMXxZ7aOQ+Dhu/tv07FAqpf99/lwcfa5qcfnbuXfdYFYhVavhb5NjyVhHbm+Sf14pf0zWr+7lbVsvnNkp3f1nQ4gKh3XffQ08++oC222GXtbkkr0EAAQQQSDGBeECTv3SxNt+yoxZa1Yr37ucF81WPWAWjex+rvgqx4vJfn308TTvsvIe33BZH5ggQgGTOXDNSBBBAAIHUESAASZ25yMSeEIBk4qwzZgQQaNAChYUrvLXKe591QaVxrGmj8fjJXuWIW7JkNZvKup83a9pMRx/ZU/379VPHTtvXekmTB++7S/c+8IimT58hX9A+o2vBis9CitgqJnVbFeKuWHHsk98e6y2HxYEAAgggkL4CRUWFGnB1Xz3y2NMqLLQN3O1wQYYLxd3h9iVZda+TPr1O0WOPP62srOz0hWFkaxQgAFkjEScggAACCCBQ5wIEIHVOygVrIUAAUgssTkUAAQRSSWDalLd19nmX6scff/S6VfFBT8V+ru778XPWW389nXrScRo46Dqtv0HrOhvi/775XP0HDNLYsbZZe4X++UKWhsQWXffWcF+L2pVYH10Fi9sPxJbqktuexC1hYn8TgNTZFHIhBBBAoMEJjBzxooqLi21D89MtEAlWCfDdclfx5bwa3ODocJ0IEIDUCSMXQQABBBBAoFYCBCC14uLkOhYgAKljUC6HAAIIJFLALQ0S34uj4te16UP8dWv7+jW1dcO1V+veBx/V0iVLvZCm4uGWMPE1zpK9Gal0RdhCjDVXh/hsPXef25fE2/8jdr34J37fGDlMPY84VsFgaE3d4ucIIIAAAgggkIECBCAZOOkMGQEEEEAg6QIEIEmfgozuAAFIRk8/g0cAAQTqXyC+fvu3X/2fHn70Ub319n81c8bMSg2v3NDdVbJYcUeubVBrn9J14Y63h0hJbBN27zyrGokHHvGLbLHlFhry7BPaY699639AtIAAAggggAACDVaAAKTBTh0dRwABBBBowAIEIA148tKg6wQgaTCJDAEBBBBoiAJff/GxxowZq2GvjNJ3335b6yH8a8cddWavk3Xyqaer1Xob1nqfklo3yAsQQAABBBBAoMELEIA0+ClkAAgggAACDVCAAKQBTloadZkAJI0mk6EggAACDV3gt5+/18svj9BzL47Qjz/84A1nt9131/bbbaUTjztG222/k1q0Wl/Z2TkNfaj0HwEEEEAAAQSSIEAAkgR0mkQAAQQQyHgBApCMvwWSCkAAklR+GkcAAQQQQAABBBBAAAEEEEiUAAFIoqRpBwEEEEAAgZUCBCDcDckUIABJpj5tI4AAAggggAACCCCAAAIIJEyAACRh1DSEAAIIIIBAuQABCDdDMgUIQJKpT9sIIIAAAggggAACCCCAAAIJEyAASRg1DSGAAAIIIEAAwj2QEgIEICkxDXQCAQQQQAABBBBAAAEEEECgvgUIQOpbmOsjgAACCCBQVYAKEO6KZAoQgCRTn7YRQAABBBBAAAEEEEAAAQQSJkAAkjBqGkIAAQQQQKBcgACEmyGZAgQgydSnbQQQQAABBBBAAAEEEEAAgYQJEIAkjJqGEEAAAQQQIADhHkgJAQKQlJgGOoEAAggggAACCCCAAAIIIFDfAgQg9S3M9RFAAAEEEKgqQAUId0UyBQhAkqlP2wgggAACCCCAAAIIIIAAAgkTIABJGDUNIYAAAgggUC5AAMLNkEwBApBk6tM2AggggAACCCCAAAIIIIBAwgQIQBJGTUMIIIAAAggQgHAPpIQAAUhKTAOdQAABBBBAAAEEEEAAAQQQqG8BApD6Fub6CCCAAAIIVBWgAoS7IpkCBCDJ1KdtBBBAAAEEEEAAAQQQQACBhAkQgCSMmoYQQAABBBAoFyAA4WZIpgABSDL1aRsBBBBAAAEEEEAAAQQQQCBhAgQgCaOmIQQQQAABBAhAuAdSQoAAJCWmgU4ggAACCCCAAAIIIIAAAgjUtwABSH0Lc30EEEAAAQSqClABwl2RTAECkGTq0zYCCCCAAAIIIIAAAggggEDCBAhAEkZNQwgggAACCJQLEIBwMyRTgAAkmfq0jQACCCCAAAIIIIAAAgggkDABApCEUdMQAggggAACBCDcAykhQACSEtNAJxBAAAEEEEAAAQQQQAABBOpbgACkvoW5PgIIIIAAAlUFqADhrkimAAFIMvVpGwEEEEAAAQQQQAABBBBAIGECBCAJo6YhBBBAAAEEygUIQLgZkilAAJJMfdpGAAEEEEAAAQQQQAABBBBImAABSMKoaQgBBBBAAAECEO6BlBAgAEmJaaATCCCAAAIIIIAAAggggAAC9S1AAFLfwlwfAQQQQACBqgJUgHBXJFOAACSZ+rSNAAIIIIAAAggggAACCCCQMAECkIRR0xACCCCAAALlAgQg3AzJFCAASaY+bSOAAAIIIIAAAggggAACCCRMgAAkYdQ0hAACCCCAAAEI90BKCBCApMQ00AkEEEAAAQQQQAABBBBAAIH6FiAAqW9hro8AAggggEBVASpAuCuSKUAAkkx92kYAAQQQQAABBBBAAAEEEEiYAAFIwqhpCAEEEEAAgXIBAhBuhmQKEIAkU5+2EUAAAQQQQAABBBBAAAEEEiZAAJIwahpCAAEEEECAAIR7ICUECEBSYhroBAIIIIAAAggggAACCCCAQH0LEIDUtzDXRwABBBBAoKoAFSDcFckUIABJpj5tI4AAAggggAACCCCAAAIIJEyAACRh1DSEAAIIIIBAuQABCDdDMgUIQJKpT9sIIIAAAggggAACCCCAAAIJEyAASRg1DSGAAAIIIEAAwj2QEgIEICkxDXQCAQQQQAABBBBAAAEEEECgvgUIQOpbmOsjgAACCCBQVYAKEO6KZAoQgCRTn7YRQAABBBBAAAEEEEAAAQQSJkAAkjBqGkIAAQQQQKBcgACEmyGZAgQgydSnbQQQQAABBBBAAAEEEEAAgYQJEIAkjJqGEEAAAQQQIADhHkgJAQKQlJgGOoEAAggggAACCCCAAAIIIFDfAgQg9S3M9RFAAAEEEKgqQAUId0UyBQhAkqlP2wgggAACCCCAAAIIIIAAAgkTIABJGDUNIYAAAgggUC5AAMLNkEwBApBk6tM2AggggAACCCCAAAIIIIBAwgQIQBJGTUMIIIAAAggQgHAPpIQAAUhKTAOdQAABBBBAAAEEEEAAAQQQqG8BApD6Fub6CCCAAAIIVBWgAoS7IpkCBCDJ1KdtBBBAAAEEEEAAAQQQQACBhAkQgCSMmoYQQAABBBAoFyAA4WZIpgABSDL1aRsBBBBAAAEEEEAAAQQQQCBhAgQgCaOmIQQQQAABBAhAuAdSQoAAJCWmgU4ggAACCCCAAAIIIIAAAgjUtwABSH0Lc30EEEAAAQSqClABwl2RTAECkGTq0zYCCCCAAAIIIIAAAggggEDCBAhAEkZNQwgggAACCJQLEIBwMyRTgAAkmfq0jQACCCCAAAIIIIAAAgggkDABApCEUdMQAggggAACBCDcAykhQACSEtNAJxBAAAEEEEAAAQQQQAABBOpbgACkvoW5PgIIIIAAAlUFqADhrkimAAFIMvVpGwEEEEAAAQQQQAABBBBAIGECBCAJo6YhBBBAAAEEygUIQLgZkilAAJJMfdpGAAEEEEAAAQQQQAABBBBImAABSMKoaQgBBBBAAAECEO6BlBAgAEmJaaATCCCAAAIIIIAAAggggAAC9S1AAFLfwlwfAQQQQACBqgJUgHBXJFOAACSZ+rSNAAIIIIAAAggggAACCCCQMAECkIRR0xACCCCAAALlAgQg3AzJFCAASaY+bSOAAAIIIIAAAggggAACCCRMgAAkYdQ0hAACCCCAAAEI90BKCBCApMQ00AkEEEAAAQQQQAABBBBAAIH6FiAAqW9hro8AAggggEBVASpAuCuSKUAAkkx92kYAAQQQQAABBBBAAAEEEEiYAAFIwqhpCAEEEEAAgXIBAhBuhmQKEIAkU5+2EUAAAQQQQAABBBBAAAEEEiZAAJIwahpCAAEEEECAAIR7ICUECEBSYhroBAIIIIAAAggggAACCCCAQH0LEIDUtzDXRwABBBBAoKoAFSDcFckUIABJpj5tI4AAAggggAACCCCAAAIIJEyAACRh1DSEAAIIIIBAuQABCDdDMgUIQJKpT9sIIIAAAggggAACCCCAAAIJEyAASRg1DSGAAAIIIEAAwj2QEgIEICkxDXQCAQQQQAABBBBAAAEEEECgvgUIQOpbmOsjgAACCCBQVYAKEO6KZAoQgCRTn7YRQAABBBBAAAEEEEAAAQQSJkAAkjBqGkIAAQQQQKBcgACEmyGZAgQgydSnbQQQQAABBBBAAAEEEEAAgYQJEIAkjJqGEEAAAQQQIADhHkgJAQKQlJgGOoEAAggggAACCCCAAAIIIFDfAgQg9S3M9RFAAAEEEKgqQAUId0UyBQhAkqlP2wgggAACCCCAAAIIIIAAAgkTIABJGDUNIYAAAgggUC5AAMLNkEwBApBk6tM2AggggAACCCCAAAIIIIBAwgQIQBJGTUMIIIAAAggQgHAPpIQAAUhKTAOdQAABBBBAAAEEEEAAAQQQqG8BApD6Fub6CCCAAAIIVBWgAoS7IpkCBCDJ1KdtBBBAAAEEEEAAAQQQQACBhAkQgCSMmoYQQAABBBAoFyAA4WZIpgABSDL1aRsBBBBAAAEEEEAAAQQQQCBhAgQgCaOmIQQQQAABBAhAuAdSQoAAJCWmgU4ggAACCCCAAAIIIIAAAgjUtwABSH0Lc30EEEAAAQSqClABwl2RTAECkGTq0zYCCCCAAAIIIIAAAggggEDCBAhAEkZNQwgggAACCJQLEIBwMyRTgAAkmfq0jQACCCCAAAIIIIAAAgggkDABApCEUdMQAggggAACBCDcAykhQACSEtNAJxBAAAEEEEAAAQQQQAABBOpbgACkvoW5PgIIIIAAAlUFqADhrkimAAFIMvVpGwEEEEAAAQQQQAABBBBAIGECBCAJo6YhBBBAAAEEygUIQLgZkilAAJJMfdpGAAEEEEAAAQQQQAABBBBImAABSMKoaQgBBBBAAAECEO6BlBAgAEmJaaATCCCAAAIIIIAAAggggAAC9S1AAFLfwlwfAQQQQACBqgJUgHBXJFOAACSZ+rSNAAIIIIAAAggggAACCCCQMAECkIRR0xACCCCAAALlAgQg3AzJFCAASaY+bSOAAAIIIIAAAggggAACCCRMgAAkYdQ0hAACCCCAAAEI90BKCBCApMQ00AkEEEAAAQQQQAABBBBAAIH6FiAAqW9hro8AAggggEBVASpAuCuSKUAAkkx92kbg/9k7C+gsj63771vaAm1xd3eXkBASICS4uxWKF3d3dyhe3N2CEw+BEEhwCe7uDi3Q9v7PzP2e/CkaeS1hv9/qorc878w8vzPzfmudPedsEiABEiABEiABEiABEiABErAYAQogFkPNiUiABEiABEggjAAFEG4GaxKgAGJN+pybBEiABEiABEiABEiABEiABEjAYgQogFgMNSciARIgARIgAQog3AM2QYACiE2EgYsgARIgARIgARIgARIgARIgARIwNwEKIOYmzPFJgARIgARI4EMCrADhrrAmAQog1qTPuUmABEiABEiABEiABEiABEiABCxGgAKIxVBzIhIgARIgARIII0ABhJvBmgQogFiTPucmARIgARIgARIgARIgARIgARKwGAEKIBZDzYlIgARIgARIgAII94BNEKAAYhNh4CJIgARIgARIgARIgARIgARIgATMTYACiLkJc3wSIAESIAES+JAAK0C4K6xJgAKINelzbhIgARIgARIgARIgARIgARIgAYsRoABiMdSciARIgARIgATCCFAA4WawJgEKINakz7lJgARIgARIgARIgARIgARIgAQsRoACiMVQcyISIAESIAESoADCPWATBCiA2EQYuAgSIAESIAESIAESIAESIAESIAFzE6AAYm7CHJ8ESIAESIAEPiTAChDuCmsSoABiTfqcmwRIgARIgARIgARIgARIgARIwGIEKIBYDDUnIgESIAESIIEwAhRAuBmsSYACiDXpc24SIAESIAESIAESIAESIAESIAGLEaAAYjHUnIgESIAESIAEKIBwD9gEAQogNhEGLoIESIAESIAESIAESIAESIAESMDcBCiAmJswxycBEiABEiCBDwmwAoS7wpoEKIBYkz7nJgESIAESIAESIAESIAESIAESsBgBCiAWQ82JSIAESIAESCCMAAUQbgZrEqAAYk36nJsESIAESIAESIAESIAESIAESMBiBCiAWAw1JyIBEiABEiABCiDcAzZBgAKITYSBiyABEiABEiABEiABEiABEiABEjA3AQog5ibM8UmABEiABEjgQwKsAOGusCYBCiDWpM+5SYAESIAESIAESIAESIAESIAELEaAAojFUHMiEiABEiABEggjQAGEm8GaBCiAWJM+5yYBEiABEiABEiABEiABEiABErAYAQogFkPNiUiABEiABEiAAgj3gE0QoABiE2HgIkiABEiABEiABEiABEiABEiABMxNgAKIuQlzfBIgARIgARL4kAArQLgrrEmAAog16XNuEiABEiABEiABEiABEiABEiABixGgAGIx1JyIBEiABEiABMIIUADhZrAmAQog1qTPuUmABEiABEiABEiABEiABEiABCxGgAKIxVBzIhIgARIgARKgAMI9YBMEKIDYRBi4CBIgARIgARIgARIgARIgARIgAXMToABibsIcnwRIgARIgAQ+JMAKEO4KaxKgAGJN+pybBEiABEiABEiABEiABEiABEjAYgQogFgMNSciARIgARIggTACFEC4GaxJgAKINelzbhIgARIgARIgARIgARIgARIgAYsRoABiMdSciARIgARIgAQogHAP2AQBCiA2EQYuggRIgARIgARIgARIgARIgARIwNwEKICYmzDHJwESIAESIIEPCbAChLvCmgQogFiTPucmARIgARIgARIgARIgARIgARKwGAEKIBZDzYlIgARIgARIIIwABRBuBmsSoABiTfqcmwRIgARIgARIgARIgARIgARIwGIEKIBYDDUnIgESIAESIAEKINwDNkGAAohNhIGLIAESIAESIAESIAESIAESIAESMDcBCiDmJszxSYAESIAESOBDAqwA4a6wJgEKINakz7lJgARIgARIgARIgARIgARIgAQsRoACiMVQcyISIAESIAESCCNAAYSbwZoEKIBYkz7nJgESIAESIAESIAESIAESIAESsBgBCiAWQ82JSIAESIAESIACCPeATRCgAGITYeAiSIAESIAESIAESIAESIAESIAEzE2AAoi5CXN8EiABEiABEviQACtAuCusSYACiDXpc24SIAESIAESIAESIAESIAESIAGLEaAAYjHUnIgESIAESIAEwghQAOFmsCYBCiDWpM+5SYAESIAESIAESIAESIAESIAELEaAAojFUHMiEiABEiABEqAAwj1gEwQogNhEGLgIEiABEiABEiABEiABEiABEiABcxOgAGJuwhyfBEiABEiABD4kwAoQ7gprEqAAYk36nJsESIAESIAESIAESIAESIAESMBiBCiAWAw1JyIBEiABEiCBMAIUQLgZrEmAAog16XNuEiABEiABEiABEiABEiABEiABixGgAGIx1JyIBEiABEiABCiAcA/YBAEKIDYRBi6CBEiABEiABEiABEiABEiABEjA3AQogJibMMcnARIgARIggQ8JsAKEu8KaBCiAWJM+5yYBEiABEiABEiABEiABEiABErAYAQogFkPNiUiABEiABEggjAAFEG4GaxKgAGJN+pybBEiABEiABEiABEiABEiABEjAYgQogFgMNSciARIgARIgAQog3AM2QYACiE2EgYsgARIgARIgARIgARIgARIgARIwNwEKIOYmzPFJgARIgARI4EMCrADhrrAmAQog1qTPuUmABEiABEiABEiABEiABEiABCxGgAKIxVBzIhIgARIgARIII0ABhJtSfneWAAAgAElEQVTBmgQogFiTPucmARIgARIgARIgARIgARIgARKwGAEKIBZDzYlIgARIgARIgAII94BNEKAAYhNh4CJIgARIgARIgARIgARIgARIgATMTYACiLkJc3wSIAESIAES+JAAK0C4K6xJgAKINelzbhIgARIgARIgARIgARIgARIgAYsRoABiMdSciARIgARIgATCCFAA4WawJgEKINakz7lJgARIgARIgARIgARIgARiDIH//ve/+l2eP3uCwyFBeP7iBZauXI3BA/ojT/4i+Oabb2LMu0bXF6EAEl0jx3WTAAmQAAlEZwIUQKJz9KL/2imARP8Y8g1IgARIgARIgARIgARIgASsRECJHv/5z3/w8sVzXDx/Cq9evULoyVCMHDcJVy5fQezYsTF10li0atsJsWLFstIqOa1BgAII9wIJkAAJkAAJWJ4ABRDLM+eM/58ABRDuBhIgARIgARIgARIwIwEjOWrGKTg0CZCAFQgY1R5379zE+TMn8ejRY6zb6A5v3wA8fPAQ//z3H/z3n//iu+++w8ljB5EtZz4tlPBjXQIUQKzLn7OTAAmQAAl8nQQogHydcbeVt6YAYiuR4DpIgARIgARIgARiFAGVHFX/3L93W5Kfh5E1ew6kz5iNCdAYFeX//zJGMvzt2ze4c+sa7t+9iyL2TjH0bb/e1zIETfXnqROHcfrUKdy+cwfLVq2Xqo8T+Ouvv/H2r7da+Pgm1jf45+9/8NNPP+HO7Vv44cefeP5tYOtQALGBIHAJJEACJEACXx0BCiBfXcht6oUpgNhUOLgYEiABEiABEiCB6EzASI6+eP4Up0OP4c2bN9i3bz8mTZ2Jwf164dcOXekBEJ0D/N7aDdHj77//wrXLF/DixTNcvnQJ02bNx6PHjxESvF9u/38fg974630V42w/ffIIx4+EyNl+i81bt2HegqVIljwZcuXKiYBdu/H69WsN6T/f/Ae5c+fB+XPnkClzZpwKDeXZt5HtQwHERgLBZZAACZAACXxVBCiAfFXhtrmXpQBicyHhgkiABEiABEiABKIbASM5eufWdRw9FILHT55i/aYtCNy7Dw8ePECsb2Jh0IBeGDBoBJOg0S24H1mvEe8/Xr3EpQtn8PD+PXh4eWPj5h24cOGCjnHadGmlIuAk4sb9IQa88df9Cv/88w9uXLuIG9ev4djRY1jnvg179+5FgYIFkTd3NqROmRJ/ivAxZ95ivJQ9odpcuZYpgwzpU2P9hi1o1LAOZsycy+oPG9lGFEBsJBBcBgmQAAmQwFdFgALIVxVum3tZCiA2FxIuiARIgARIgARIIDoQMJLgb9681q1w1M1vL29vLF2xFtevXYdKmv4llQFGK5zLkihPmz4LBZDoENxPrNFoa/b82RMc2L8HL1++wuz5SxC0bx9e//latz5SLY9U6yM3N1fs3OHBeEfDeBtnW53hQH9PxPnhByxfsRLbdnrjyZMnKOHogFQpkqNS+XLInDULDoQcQNee/fDHH3/oty1qZ4ffp03CyLHj4enpjcAAHxQo7EABxAb2gopt1VkPbWAlXAIJkAAJkAAJfF0EKIB8XfG2tbelAGJrEeF6SIAESIAESIAEbJqA0fbo0YN7UObHly9dxJZtO7Bg0TL8IInSV69e4e+//9YtcL75j3gAiBHyd99+J+2RnuNb+ZMmyDYd3g8W925bs7OnTuDx44c4c/Y8pkyfLW2uHuHZ02dhZtexYsXS/x77+9gYNrgfevUdxHhHk3Ab51r9qSq5Hsr5Vmd77sKl8Pb2ReYsmZE/by7kzJ4N5UX4cCjhgnOnj2Pd+nUYOmKs9vtR5z1PnjwYN3IwylephezZs+PWrZt4cP8+4v7wYzQhEfOWacT2zz9e4fzZk+gflCXmvSTfiARIgARIgARsnAAFEBsPUAxfHgWQGB5gvh4JkAAJkAAJkIDpCKgb4bduXMWVy+fF2yMYG6Tl0bGjR2FXrBiyZk4Hv12BuHbtmq76UMnwGjWqYNOmbciUKRPOnz9vuoVwJLMTMIQPJXIdP3wADx4+wnYPD3h4+iJx4iRwcrTD4aOhOCltrpTg9d133yF7jhy4Lm2S/nr7Fvv3BiBvgaIUQMweKdNM8JdU74QePyRVPS/h5+ePVWvdJZbX4eBgL22usks7q/SoVaeutDbLpCcM2uOLcROnwMvLR1d/qaqfzOL1MfO38ShbqQZUe7SUqVIjefLkui0aP5YnYJzhh/fv4sih/VKh8yc2b9uOO4UnW34xnJEESIAESIAEvnICFEC+8g1g5denAGLlAHB6EiABEiABEiAB2yVg3BxWwsdu352I++OPmDN3HnZIElxVexQpXABVK5bHs+cv9Ev0GzhUt0X6/vvvUVPEj+pVKqN56/aoWrUi1q7dyGS47YZar+zdtmYXz53C4UOHcOv2bSyRtmZXr1xB3nz5UMGtFBImTChVHt9j5tyFOH3qtG5zlUVaIXXr2BZjJSl+TVqgPX70APHiJ7TxN/56l2e0M1Om5ufOnNRnc+SYCeLbE4QECRLAuYQ9UqdKhZJOJeDiVhGx48TVz6iWd7t9PdCz3xCcPn1at7lT/z1DhgwYOqA3mjT/VUNVYkpxJxeUK+eKDRs2fb2grfTmb9++wZWLZ3Hi+HF9hucvWo6LFy8im1TlpG7haaVVcVoSIAESIAES+HoJUAD5emNvC29OAcQWosA1kAAJkAAJkAAJ2AwBQ/T4WxKb169cxBNpc3T58mVMnjEbB6XXv0qCFyqQG9mzZpXkZlmky5AFkyaM1YlvI4FesUJ5jB4xBNNnzsLqNRvx+/RJaNikpa4K4cf2CBgxf/zwPo4dDhFB6zk8fXyxWkSrhJIMz5s3D+qIoKUS3ZWr1ZLb//5o06GrtDZ6oL1e1M3/Dm1bolbt2ihUxB7x48eXZOslCl42Fmojzio5fun8aTyQNlehJ09hzsJlImSd0qbm6mzHjxcPLZo3R47cBcLOtPruyxfP4OOxHS3adpQqoMRSCXYF/5X/U1Ue/Xt3R8cuPXXM1bN9e3fDzN/nYcrEsWj5a0fuBTPvBSO2yp/n+JEQ8Wp5Cv+A3eLJtAaxY8dGgfz5UNrZEdmyZMH8e+XMvBoOTwIkQAIkQAIk8D4BCiDcE9YkQAHEmvQ5NwmQAAmQAAmQgM0QMMSLP//8AweD9+DFs+fw3RUg/h6eeC7+HUULF0LOHFmRI1s2VKleE8lTpIbXdndJni7B9u0ecjP8jW6D41qmDAZI8rOka0XtAXD37l2dVM+UNafNvCsX8j8CRtJU3RQ/f/Y0zp6/gHXu2xASHIx8+fOjhEMR5M6ZE/bSBil/IXucPnkEPj4+GDJ8jIgkz/QY6dKlQ48uHdC2Qxd4bt+ERk1boU7talggSXX6vdjGTjPO9rOnj3HkwD48ffZMqri84OHlpxdoV7QQcom3Ry6JdfmKVZAwcVIdOyN+6vtnTx2Tc74dw0ePR4ECBcX75SnOnj2LNyKmTBw7Eh06d5fKr9hh+ypv3ry6HV7Ivt1aSFFVQvyYnoAR2/NnTkiV1iURq69i/eZt2Be0HxkyZkB5t9LIlDEjijs4IF8hOx2PMScKmn4hHJEESIAESIAESOCzBCiAcINYkwAFEGvS59wkQAIkQAIkQAJWJ6ASaKra49mTx3IL/Li0LnqE32bMkSR4CFJJCxzXMs7SCiclyri4wM7BWRuZvxaR5FBIINp36YWzZ87irfgHKAPkgoUKYfXyRcicLbf4AvwprZISIUXKFDh/7pzcQo5j9XflAv6/6PHq5Qvx6dglQlZKzJo9G17eu7SoYVe0CPLkyi7ihwPcKlTGjz/F11Uel86fwoyZMzF77iIdb5Uc/yHuD1i+eC4qV68jCe5YaNWiCdascxchxB2OJcsy6W3lDafOtvL2uHv7Ji6LyHX16jX8vmApjh4+LMJVelSq4IpUKf93tvMXLiYVWt9+NGb+XtuwZsNGLFu+GqVKlUTa1CmxbacXnotI2qFdK4wYNU7/LhjVH0pE/UFMz5OnSI6L58/pPUQxzHSb4V1T88MH9+nfbFXtsXW7F+6L4bydXVHUqlYJceLERvVa9ZAgYWI8kZZ0ewJ80a33AOTuHmK6xXAkEiABEiABEiCBcBGgABIuTHzITAQogJgJLIclARIgARIgARKwXQIqoa1uZCuj4pPSq//PP15hf/AB/D5vkbROeYLChQvDoWhB7fXQ+OemSJUmfVi1wIP7d7DL11vEjx54Km1W3orhtWptlTNXLkyZMFKS5tX1s6dOHEax4s4oUtQOAbt2MQFqxe1gJEzVnzevX5KE6UMtcG3YvB27pMoni7QzK1oor4gfRaXKJztcy1fVqzXEsUMhezFs5FhteK0Mz9UnfoL46NSuNUaMnqD/t0pwZ86SGfek4ueGGKHHT5CIAogVYm6cbSVwHT4YhJfiz7NfWtctWrYKL6S1WeEiRfTZVj4fzVu2QeIkycLaXL27XBV7JWJevXQO3Xr2wd6gfahTq5oYoufG3IVLcevWLbRq3gSjx07UlR/vVovcuHYRGbPkQJEiRaUSIYit70y0D4xzfOfWddy+eR2hoSexadtOeHh4iTl9OqnSyy8tzAqgeHEHlCjppmdV++H2zWvYsmkjOnbrBanrQYWpd0y0Ig5DAiRAAiRAAiQQXgIUQMJLis+ZgwAFEHNQ5ZgkQAIkQAIkQAI2ScBol3Ln9g0cOxSC+w8eyE1uT/j670aC+AlQprQTckgrnAL588LesVTYzW0juanarLi7u2u/j8yZs+DokSPaA0B5QEweNxJVatTTiVCVdJsxdSJGiKly86aNMG7CFAogVtwRKu7HjwTj6ePH0vbIGxu37MTdO3dgV8xOJ8PTS/K0YuWqSJ02Q5iYYYgfO7ZswODhY3HmzBltdH3+wnld7dO9awcMHDQ0zOhciWgJEyVGqtSpcEn8P9jyyLIBN8729WuXsHd3AP6QeGzcsl2Ei/1IkjgJyop5fZZMmVDMrgiK2juHmZp/rDLDED+U2XlXqRhQomgLOcfKEH367Hnw9vZDx/at0bNXH6nwSvOvs63O/vzZ09G5ex+0F1+YCZOmUQAx0VY4emifPlfu7puwftM2aXl1FUVFtHR2tBPhMgdKODsjbfos/zp7u3136uqdxUtW4Cfxdrl39x4qz7hvohVxGBIgARIgARIggfASoAASXlJ8zhwEKICYgyrHJAESIAESIAESsCkCRkLzxtWLOHP6FM6J18PCpatw7epVXblR1sUJGSW57epWFhkyZw/r///ure4Anx1YtXY9lshNcje3MjqpuVPEk9RpUmPogN5o2qJtWOJNzVenTk14enpj0/qVUlFQjQKIBXeE4q/+efTwniTD/aXCIxv6DRyMgIBASYL+hAplXfDjjz+hcoVycClXOcy74d1437x+RUyuz0t7q7pIkTwFMmbKiHv37sv+OS2trppi2LARSJw0eZjgdfFcKHLlLYTSLqXhJf4SFEDMH/CwVkjSckp5dJw7ew7Xrl+Xs71SqnBuIH/BAnByKCpVG7lQyqWMCFyZ9KJUbD7VkkqN+fDBXXhs34Je/Ycg3k/xMGHMMPmdyI1x48frFmd1a1fHqFFjdGXY+3FWFULq7O/Y4Qn3dStQoUot7oVIbAUjtk8eP8S+wF2IGycOZs1bgF1yhr/77juUEkPzfHlyI7t4MlWtWVe3GDREMDWdan22ZeNazJy7EAekAsjRsTjOSivC69euswIkEvHgV0iABEiABEggqgQogESVIL8fFQIUQKJCj98lARIgARIgARKwWQJGAu35syfYt8cfj6Vd1d59+7F85VrE/SEuHOzl9r/cBs+dKyfKlK2EHyQh/m4CTb2Y+t+qn//1KxfQpXtvBAbuRYP6teRGeWKslkSouu3du3tntOvY7V+3vFXyLZe0yrl48SIePbive9DTA8C8W8WI95s3r3Em9Ciei59HsLQ1W7RsNS5fuohC0vqoUL7cUukTD02bNkX2XPk/2fpIiRnr16/H0BFjdcukAvlyapP7lavWo1bNKpg2dUaY+KHeSu2D8WOG6+cH9e+FPv0Ha08IfsxDwDinjx7eFx+XAIn1C+0BsWLVOiRLllRMyvNJVYCDFj6cy5RHXPFqef9sf2xlRqXQzp0e0vJsnFQIFUM58QDq3rMvhgzujxmz5qF8eTeJ9ShkzZH3o8KG2n+FChXWBuk3RER7v0LEPERixqjGGVaeTBfPncKrly8RsHs3Vq51R+jJE8iTNx+KSKu6pPL726RJE32G3/+oMZTZvfrN7zNwuPzuP0Y5MUKPJR49i6QKxM6+GBI12BQzgPEtSIAESIAESCAaEaAAEo2CFQOXSgEkBgaVr0QCJEACJEACJACdBN+/LwgvXr7C6g2bceTQIfFoyILqlcsjXdq0unVKvkJ2cpv4e43rfYHCqBoJ8NmJzj374dmzZ+jwa0skT5YMUyUReuXyJYwdNQxt2nX6l8G5rjx4cA+ZsmSTyoLvdNUAqwHMtyONxPbLF88REhSAl68k3uvWY3fgfj2pq7Q1yyItynLlzAkX13JImDhpWIXPx1a1fvUy7PDw0Df969WpASdHRxwQ0+zFS1aiYsVyYcnvd/eLEkBKli6Fg3LTPMDPA3YOJRlz84VcV3sE7tkjye0n2LTdU5/trFLlU7F8GUmQF0I2aWOXJ3+RMGPy8C4lcJcnZkuVwbr1m0Xoqor6tWuJp09l/DZ5vG5j5yh7YfKEMXrsT7XOUhULmeXs/+eb/2g/GAphX6ZvnGHVtuzY4WA8ECPzLdt2wEdaEz58+BDlypZBwXx5pVVdWlSoXA1Jkqb46PlS5/Dpk0fYtnkD+g0egR9E+GrTsileybjTZsxBihQpxadpFKZedvryovgECZAACZAACZCASQlQADEpTg4WQQIUQCIIjI+TAAmQAAmQAAnYHgEjgfb27RsEBfjggngwHD1+Qvw9vPBchItCkhR1c5G+/7Fjo1mL1roiQyXLVBurj30MEWPHtk3o1qu/JNySYuSQAbrdVYcuvaT3/BW0afULRonHR6xY337gAbAv0A+u5arA1dUF2ySRx+oP0+8ZFSMV77u3r+NAcDBeiAAyY84ifVM8k/izVChbWlpXJZcb++UkYV1Ux+BTQpQx1s6tGzFy3G84K34fTX9ugNatWmD79h3a6NxBjJWnTByDfAWLfTCOMstOlTo13r55K7f+r+r9xY9pCBhnWyW2L5w9JW3NHoi3x1ZsFA8I9SlSuBAc7ZV5fQ6Uq1hFe7J87my/vyoj9quWLZQWS0vE6+U02rVpgRbNm2tPmKDdfqhZrzHy5suPSWOHoUSpcp88z2reY4f2w7GkKwrKb87ewEAKYZ/ZBoq9qpZ7KILx6RNHcVfE4tkLliJ4/37tt1PWtZRU78RB3Tq1UaSY02eFSzXNyWMHsXXrVl29U6hwYfzcoLb+DWjeur32afrl5/piaN8PVWc9NM3m5CgkQAIkQAIkQALhJkABJNyo+KAZCFAAMQNUDkkCJEACJEACJGAZAkbLFOXXcP5MKM6IB4CX3y7x5vCSW9iZ4VCsMAoXLIiCBfPDoYSLvo39pVY4RhucrVu36cS3k5MTWjf/GaXLuKFxk2bSVmm/9oAYPmK0Tra+L24oD4DB4gkyYfJ0LF04B/Ua/cIkqIm2g0owKxHj8aMHOLg/EC+luidIxI+VazaIGPJWJ8OL2xdB6pSpULN2Pd2mKjzxVrf2d/t7o1e/IfhTxIxWEu+mTX9BgL8f2rTvqpOpvbt1RM26jT5aKXTn1nWp+MkuPiGZRIA5SdNrE8b77u0b2L3LD4/FwH67eOp4evoga7ascBRvjxIO9lL5kUUEh7KRYq72xv17t7HL1xsDho7Ue0Ulydu176TP9napJGjYpIX+LZkoLc4qVavzWTFT7c/JE0brBPywwf10sp3i5783g/Gb/eL5UxwOCdKt5QL2BErV1iYxm38s7csKonixQrpKr3pNETBSpdUDfI6j4u7rsQVrN7pjqbS8U9U7zX5uhDfym9CoaSukTJUSg/r2QJPmv+pxqsx8YKIdymFIgARIgARIgATCS4ACSHhJ8TlzEKAAYg6qHJMESIAESIAESMBsBIyEtkp6HQzeg1s3bmKv3Bje6eWP82Jy61zSGaWc7JEzew7YFy+OdBmyfjGB9u5ifTw2Y86Cxdi8ebv2+6gnbXAKFrZDn769sWHjVnTv0h7tO3RCmnQZP5mUK67aJoWE4Ma1y0ieMg0FkCjuBiPm169ekHZHB3Hz5i24b92JYGGcXG54165RBalTpULhQgVQqKijeLz8+MXb4mpJalwlnm1Yv1bErvG6RU6vbh1Qs04DbN20Hu069UB6uYk+QpLZNeo0/Ggc1Rgb167Qt8wrVSyLVavXM+ltgngfDtkr4sRd+O/eg81bPXDr1i3Yi3+DowhcqtrDuZQL0qbP9EWB61NLUXG7ce0iNrm7Y7jEPnmy5OjZtT3qi2Cp9s+WjavR5f8EjOGD+qLxL63DdY5dXV0RFBQkLfIuIHmK1NwL/xcA4wwr8XKvVNWo1lbrN21FyIFDujKvbq1qSJsmjZiaZ4VzaTf8FC/BF8+wUUFyVKpu+g4chpDgEF2Z16t3X11R0lbO782bN3SrwrYduoS1I6MAEsUDyq+TAAmQAAmQQCQIUACJBDR+xWQEKICYDCUHIgESIAESIAESMCcBlexS/zyRBJq/r5dujTJ/8TJpUeSBNGnTwN6uMDJlSC9J8EKoVque+G/E1q1wwuO/YbTBWbZoHqb/Ph9Xr17Fr62boWGD+kiYKDGmTp2KOfMWaQ+IGdOmf1LUUOMoA9906dPruW9Jov5TbbbMySomjG3cFH/18gVOHj+EE9LS7P6DB5i3aJlOnhaWqowypRyRJVNmVKhUFYmSJItQ6yPFaO9uH93iatKUmVCiVbPGdfUtcY9tG9FMBI0ff/wRU8aPRnURPz51A13FuVPHX7F85VrMnv6brhjgJ2IEjLP9x6uX8NyxBfHj/6TPoa+vn4gIKaSSqwhySGLcrmgRlKtUPVyVXJ9bgYrZudPHsWDhQm1sXsKpBNq3bq5FLvVZvnguRkkrtNdiaN5e2mH17DMw3L8jCRMl1GM8ffI0YhBi4NPGGf5TPDiuXj6Po0eO4IGc3Wkz54qgdRNFitqhtIjVCRMmRJ26dUXQyhLuM6zGfvnima7c6tC1l6anYtWiZRsoLxHlFXLn9i1MHj8KPzdr86/4UQCJgZuNr0QCJEACJGDzBCiA2HyIYvQCKYDE6PDy5UiABEiABEggehMwbg2rPvFXLp6Vao/r2C9G06ukXcq5s2d0X35nRzskkgRa5cqVULBIcS2SqE94W8+o5x8+uCuJ120YNGyUJMpiocUvjdBW2uCoeefOnoVRYyehVKmSmCTJ8Fx5C30yGaoSq48e3hOvkPQoamenjZrDI8BE7yiZdvVGzFVrogA/H9wXQ+SQgwexwX2bVGhIMty+sFQB2CNP7lywc1QeAT9EeAEqroekwmDq9JnYvGU76terJVUk1XWLo6A9vmgqIojIbRg7YohuYfa5j2p5psQTldy9cum89o3gJ3wEDMHwqnC7Kd4pBw4dxoo1G/XZzv9/rZCyZckCOzlLReydIny231+F8dvgs3OzeE0sFr+IHWgiLa+aNmqIUm6V9Pgh+wJ0NY8S2Qb164WOXXqG62XUd5UXTIIECZE7Tx4cOXw4XN+LiQ+p30H1+6vO8JED+3FHzOAD9+3H9p3eiCPVHsVErLa3K4pcObJL+7IyiJ8gUYQreS6cPSni5XYMHTFW+4W0btEELVq3k8qPI1oQOXUqFN06tcPAISM+8GmiABITdx3fiQRIgARIwNYJUACx9QjF7PVRAInZ8eXbkQAJkAAJkEC0JGAkwZXJdci+3bgpba68fH3hv2sv7t69o3u855Mko2p7VKlqDanSSBIh0cOAouZRHgOrV63ASDE0T5MmLZo3bYg2bTsijiTWfxPTa9UeJ1/+/Jg8biSKFS/1WZ4q8bd+9TK0bt9ZGymPFuGEAkjEtuDpk0fg5+cnfgBPsGHzDpw8cULzr1+7mrQ+yo4sWbMhR+78WqiKKFsjAe4pFR79h47WLdP69uqKRo0aI2OWHDh76hiq166vRZcp4uXw/s3xj72JqlrIJi2ZXr54iQdSocKKn/DFW8XiUHCgPs/rxbshYM8+qQq4LYbX1fXZ1h4QUsml2lGpT3gFzU/NbggUZ0KPouWvnXD58iV069wOtWvV1qKmGv/UicNoI62SDkgrpdkzJqNB42Zh84fnrVT7vFr1mqB1y6aYKB5AUV1zeOa0pWeM3+1L50/D28sTL1+9wpoNW3D82DHt29KkYV1kFLEiu5zj3PkK60qeiJ5h9b4Xz53C1GlTsXDxcjhIm8OGdWqgWat28t9D0bFrT+wO2I1+vbuhQ6cuSJI0xQdxoABiS7uGayEBEiABEvhaCFAA+VoibZvvSQHENuPCVZEACZAACZDAV0fASE6r2/kP7t2RZPQJPH/xAiOlFY26TZ1dkszlXEsikbSYKevmpk3NjZvGkU00HjkQhCXLlmH23EUoXboU+ksy3LlMBfz55x9QSTx7x5LImSu3VAIMhGv5al9MaKp3qCfVBLv3BGHlkvkoU67KF7/z1QX6nRc2EqYP7t9B6LHD+Pb777F46TKsWesuHgA/SbWHHcq7uuhvNG3RRld7qIqLyIgMai7lP+Dv44lO3Xvrm+ijhg1CeWmfpQS0E0dD0KlbH5w+fQqD+/fGryJiqTZqn/uoMVVlUoHCxfSt//379n3N4fzkuxtnW7WHuy2G8T6eO3UifKDc3j8oFV05coqnRwl75MudW1d7FC5WImysyJ7tdxej5n/65BF2Sexbi8CRIH4CdGzXCr+264TvY8fRSXglfgwYPFRE1t3o06MLuvXoo0XQiMzfWnTY2BQAACAASURBVPwn1q7fhLXLF8GtYvVI7dPotoHe9fY4digYiZMmxfwFC7FRPJRev36tz3D92jXw048/SfuyavhB/ozMGTbaFG5cu1IqADfCx8dXV261adUSdg4lcfnCaYyfMFF+z1eJAPULhg4b/lHxQ/GlABLddhnXSwIkQAIkEBMIUACJCVGMvu9AAST6xo4rJwESIAESIIEYQSCsT7yIDscOB+tqj/1ibr1lu6e0pnqAYsXsxAOgMJIkToJq1atrU3Mj6RYZAOq7SjjZ4+eBSdNmwsvLVyfMalavKiJHVZ2cW7NiMXoPGKITpeNHD9WtkcKTCFXijRJqHj96LG18TiFZ8lSRWeJX8R0Vg2tXzkvi8jyOnTgp8fbC3r17dTK8tHNxlC5ZEpkyZULBosXDxf5LQoVKcG/btg2Dh41GgYIF0UranLVq20l/bW+AF0aMmYTDIrR1bNcaffoNClfyW73DskVz0L5zDwyUdkl9BwyN8lpjUvDf9YA4GLxHV8koU/NNW3bi0eNH0gqpKIqLv0fyZMlQsUpV8c7JHKWz/Sl2B/fvgY9UkI2bOFX2V06MHT4QxVT7NKkuUWs8f+YERo4ejfVSrdCqRVOMGDlat2WKSHWCGidL1iy4e+cOzp05pVuhhec3I7rG24jt9asXcOTQQVy5eg0e3v5yhoOQLl06lBZ/Hiepzsghv4fqDEeE5ftMDPFj59aNGDF2Ms6eOYMu4rvTpEkTZM+VH2oNM2fOlJZ2s1FHKsUmjJ+IlKnTfZI/BZDouuu4bhIgARIggehMgAJIdI5e9F87BZDoH0O+AQmQAAmQAAlESwJGAk3dyt8lpuZv3rzByjXrsStgD5ImS4oaVSvih7hxUda1DOyKl0TsOHF1Ei0qSUU1pzLVDgkKQJde/bXZec9uHeUmcX1kzZFXj61aWPUbNByvxEi3b8+u2gMgvMm7J48fIm269EgprblOhYZ+sYIgWgYuiotWAtOxQ/vFH+Au3Lduk8T0bjE3vw9nMaLOnVPaW2XLhmo1a8seSKlnikq81fdVzAN8dsjeWocVq9bCzc0VtapV0mbnauzjR4IxaOhIeHp6o7MkVQcNHqaT3+H5qLErV64oLbt24YAk2fPkLxLuvRKe8aPrM8bZVufBz9sDr6RN2IbN2xAQECi38pOEne2SziVQ3KmMFpuierY/xUp5uixYtBjLV6xFhQrlUK9WdTRq2lI/rtZ57+4tDB8+FEuWrkTjhvUwTCoHPpc8/9g8ahxVNRYvXnykT58OoSdPRqh1VnSKsxFbxfXFs2fY7uEJb7/duHL5ChzFC6eNeHGoM17GrRySpUgd5biq+ZSXSHDQHnTt2V+f2XoicnTv2VtXeKjf8/FjR2Ly1FlSxecsbQvHI3O23J89hxRAotOO41pJgARIgARiCgEKIDElktHzPSiARM+4cdUkQAIkQAIkEC0JGMkz5ZtwUVpM3bx+DaGnz2DO/CW4fv06iom5dbkyzsggScTSZcoibfpMulojvALE56CouR89uIdNG9ehj1R3JEqcGF07tkWLVm21uKL+3s9zq7TI6arn7Nm1IzqJmW5EEvD+XttQq34TMUx3grv7lgh9N1oG9AuLNuKt/rx54wqOHAyRtjhvsGTFanh4eCFr1qwifEjrI2kfpUzNVQWO8Z2IcP9UUlrFcfvmdVLpMxuHDx3Cz43roW+fPkifMZuOzY1rlzFMkt8rV61DwwZ1MG7sBGnhkzzccVNrTSZi3Zs3b+Xm/+1wVY3ExDgbYoL6808RDm/fvIYTx4/iulRzzfh9vpztayhUpIi0MyuJdGnSoHzFKkiVJr3Jzvb7TFVc3rx5LaLUbvHwmYh9Qfu02Xmj+nVRolQ5HV/1jBJoFsybLQLYKBFHymLyhPHaCyaie0/ts8Mhe8XQ21W30vMQUcAUv1m2sFeM86jWckfal50JPY5r8lu908sHG923iuCTHk6OdignbQnjSdu6ytXr6nc31e/2lUtnsW7tWmlPNgIFCxVCu1ZNxaS+gx5fxXjpwrno3L0PnJyd0KtLe5StVOOL7CmA2MLO4hpIgARIgAS+NgIUQL62iNvW+1IAsa14cDUkQAIkQAIkECMJGMmwh/fvYpefN54/f4bd0irFy2cXvv/uO5RxcZbb/zmRJXMmlClbEfHiJzQ5h/17/eWmvj/GTpiiE2mtfmmIBj8311UaKsmnDJlb/toR165dw9BBfdGhc3fp4f9tuJOhaoxB/Xth5uwFmDBmuB4roolUk7+0FQc0Wo0pU3MldO0Xr4eNYmp+6dIlFC/uAAe7QsgmLYOKFLXThsimEj6MZPzzZ0/gsX0LRo2bjJs3b6B7lw6oW7cusuXMp+d6+OAupkyeiN+mzULd2tXRu1evMDPs8GBTYyghL16CBMgt3hVHjxz9Kjwf3mdj+PAY/irq9r+XtJvavtNbKrh+gEvpEsglbZCyiwl2SZeyurrGnOdCrUeJMDu3bcKg4aO1oX3nDm3wyy/NdPs8Q/xQlQOzZ02TlmijdPJ81NBBKGLvFKm1qXceO2ooRo6ZiMEDeqN3v8ExYi8YZzL0+CE8vH8PgSIkuW/1kPZ+Z7XnTVkXJ+3lUrZ8ec1WfUwVWzW3+7qV2OHpqat3alSvLBVa7bX3kxJYVMXNiiUL0L3PAGTJkhXDBvZGlRr1wjU/BZDw/MLxGRIgARIgARIwLQEKIKblydEiRoACSMR48WkSIAESIAESIIEIEDCS4BfOnkTQ3kDcuXsP2zx9cezIEfHKyInG9Wvp0SpWrIgs2XPju+++/+Lt3QhMrx9Vawjc5SnCxDzskKRs5UrlULNaVdRr9EvYUOdOH0frdp1x8EAIZs/4DbXqNtJmvRFJ5qkkqFtZN+wN3IuLF85IK6xMEfp+RN/LVp83bt97bHPXsVyxei0CxBQ+tpiOl3UthZTJk6O4gz2cSrmK0XkCzSginL/03ioBrtoaKfGjn9wajy9tiQb164GadRrqtkRqLiVcTJk8HqPGToSzs7M2Qy9k5xihvWf4yLhWqIZfmjbE3HmLY0TS+0t8jb9XcdYtpO7chL+vN27dvi3tkHxxRM522nRp0aBODSRMmBAlSjgiZ56CWmg0dazfX6taz4P7d7DFfYN4RUzEt99+i97dOqFug8ba6N7YZ+qszp01Ff1lf6RJmxbjRw1Bxaq1I70P1V4oX74c/P13SZXTPuQtUDTSY4WXvzmfUxzfvn0DdYZVO78Zs37Hnr3BIho+FCGiEn75ubE2ODfOsKmrXVR8Nq1fhekiJgfv349OImDVqF5Nt0tTMVR/r1oVdhaj+kSJEmP+7KlwdHYL9/mlAGLO3cOxSYAESIAESODjBCiAcGdYkwAFEGvS59wkQAIkQAIkEAMJvNv///zZUG1Ye/xkKBYtWYHvJQluX6yotLkqjdy5cqJwMUdd7WGqdinv4jT68u/x88TI8VNw7NhRtG3dHK1athSxJY9OlqlnLp4LlRvbA+Dj4y8G2K20H0QcaYkV0aT869d/aoPlRw8f4Z74W8SOHSfCY0TH7WDEWxnAX79yUVqbncW5CxexYMlKuSl+Brly59Gtj1KmTAkXFxftk2HKao/3mZ09dQzLly/H+EnTULSYHUZKNU/pspXDHlNtcxbN+x09+w5E/gIFMXxQb2m9VS3CsdJt0rp3wixJ0i6YM0NXE8WKFSs6hjDca1ZxU+fixfOnYhweivPnz+P4iRNYvno9Xr58qYUtN5eSSJM6tZia19AiojnO9scWrNam/Fx27NiJIcPHwEEMuBvVrYG2Hbv9y1hdrWfdqqVo06EL0qZJi17dOqBpi7bhTp5/bG61p3Llyq2rm54+eRRuD5lwgzfzg8Z5VGyUgHRW2lyFnjqNZas36NZx2XNkRzkRLxNKtVNZEXmLFS8VVkkT0d/Jz72KWof6Hd2+eYMWp/6QKo+2rZqhRcvW2k/EOF8+HpvRpn1XVW6CkUMGhHm6hBcTBZDwkuJzJEACJEACJGA6AhRATMeSI0WcAAWQiDPjN0iABEiABEiABD5CwEiOXjx3Cn6+Pnjy9Cn2BAXLregApBNPj6pSeVEwf37kzZdPboQX0NUexndMDVQl8lSS1n39aowW8ePR40fo16sbGjVughSp0oYl765ePofhI0ZglST6WrVoiiFDhyFxkuQRToaq+W5ev4SsIqzkk3c8EBIS4YS6qRmYezwjdoap/PMXL6SlmR92SoXPS6mwcJW2ZkWk1VgqET5Ku5aVm+RpzboktR51K3zT1q1Yv2ELGjeqi1pya1x5Ehhtj/7++y95Zjk6du2JDBkzYfTQ/ihXuWakYqViXkje79y5czgdehQZMmWP1DhmhWKiwY02V8oDIjgoEFfFA2KPtEMK2L0XSZMmRXm30rC3sxOxK5duI6bEP0t/trqvwaq167UvRYN6NdGmdauwigFjLWqPBPjsQLM2HXR1yJjhg1GnQZMox015nuTOW0CqERLi4sVLUR7PUuyMM6xEB+WX8vjRY3j7+sHDyx+PHj0ULyNnaVVXRAtapcu4ad8W9TGl6GG8q/Eb6r5xIyZOmYF4P8VD356dUblaLfFrSho2p/JaUSb2L6SF2SQxP6/fuFmEcVEAiTAyfoEESIAESIAEokyAAkiUEXKAKBCgABIFePwqCZAACZAACZDA/wioG9AnjhyA/65duHvvHjZLn/jb0hJHJdAql3eTxGAilHJxRfKUaXQiy9QtU96Ng0rqnT9zQm6C78CYCb8haZKkYnb+Kxo3bRHWAkkl25RHxDDp+79g8XI0rFcbQ0X8MMSRiMZVVT9sc1+HepKM69mto/YCMOc7RnR9pnzeaH2kPDR8PHfiyZMnWL95u9wUP4zUYnBdq1pF/PjjjyhTxgX5CxXTrY/MzULtP++dWzB8zCTtT9ChbUvUqVMbBQo7hCVOVcyVD0z12g2QOHFiLF88D3YOJSON5g/xmVDtk9St9Cty8/9HSdjGtI+Ktdrb58+cxPbt2/WN/I2bd+LSxYso7uiA2tUqI378+HAu5YKUqdOZ/Wx/jK9a3/zZM7Bk5ToxXj+GAX17onLlSshXsNgHiXrlZVGrXiNJ7j/CqqXz4VK2SpSrdtS+UqJKjXqNUb9OTcyZt8gsAoEp95ZR8fHs6WP4e3vg2o0bYmruh2ARbpMkToLqVSsgZYoUulrPTqo9LHGGAwO8RLzajHkLliJ/wQLoINV6Stwwqj7Umk8eO6hbFZ4KDcWMKePDPJwiyoYCSESJ8XkSIAESIAESiDoBCiBRZ8gRIk+AAkjk2fGbJEACJEACJPDVEjBuDqubz5cvncfJEyfhv3sPtm7bqXvGl3RyQGkxFi5m7xDm7WGJVjhqDnWTed36DZg2Yw5cypRG04b10PiXVmHVJmrtTx4/xLIlC9Gr7yBUq1YJ40aPRuZsuSIdTzVv0yYNsHbdJgQGeKNIMacoJ1YjvRgzfNFImCpz6SOH9uPmjZu69dGKNRu0AFJMbv9XKu+K1BJ7F9dySJIshUVaH6l1qZZD27e4Y5CYWatPj64dUa9BI13J825LKl/Prbptzj///Qe/jRuF6uIJEtmb7GpeZe7uUKK0tAfKEeMqftT7PX54HyH79uCemIjvEwP7ldLmKlmyZChZwh6lSzojfbp0cCzlppPjljjb729rw+9j57bNGDpqvD7fql1S6zbtkChJsn/FVv1dcNAudOrWB9euXcW4kUPQpPmvJjmjamzVCm3+omXYsWWDeFG4RnpfmeHohg1p/GYr8/DjR0Jw+9YtnD13XlrVrZB/vw07aRdXqVwZfYbLlC2PFCJWm6tCz1iUIbAFizA5a858bNm6A7VqVkWjenVRQTxZ3n1uj58HRomgHRJ8AKOHD0LT5q0j7NNkjEcBxJw7jWOTAAmQAAmQwMcJUADhzrAmAQog1qTPuUmABEiABEggmhEwEuEq+evj44OHDx/C2z9Q94kv7lgcZUo5IlHCRHIDuwoyZM5u9pv/7ybIVDJb9fZftmotvLx8dEurZk2biM9IiX+tQxlgz541DQOHjBCD5hIYP2b4vyoFIhuSbNmy4YbcpL5755b2NYlscj2y85vje0Zi2zAVf/nyFQL37YOP325tcF1REqaFCuRH5syZtOhjmIybYy0fG1Ptw43SMmfKjNlImzYd+vbojEpVa4SZq6vvqD3r57UNvQcMk/36QDw/+qJhkxbSAum7SMdIcZn3+zQMkD3UsV1r7TkRE+JtMF40b6YIHw/guysQB+Vs58uXX3x7nJE3T27kyZsPWXPktVSIPzqP0S5p1cqVmDR1JlJItUJvqbyqUbu+VOLE/0D8UMnzkeMm48jRo+L50QmdpAVaZHx+PvXS+fLnw5XLV3Dr5nV99m3pY5zhx48eYLe/N+5LXIOCg/UZ/k7OQPlyLsiXOzfy5s2tK7biJ0hkkb2szqVqSbdl41qMmzxdV3V079IezVu0+Fc7ObX+QyGBUlU3AZ6e3ujTswv69BsUpd8aCiC2tEO5FhIgARIgga+FAAWQryXStvmeFEBsMy5cFQmQAAmQAAnYDAHjFrBqNeMjbYaev3gp7VK84B+wVwxrX+v+/xXKlcMPP8QVr4fyOgFo7pvD78NRt5oPSuVHx259cfnyJQyUNjjVq1dHtpz5PkiGzp01FcNGj0e6dOkxsE83VKpWJ0o3wY0qhBQpU2uvk7NnzkZpPFsJ/Nu3b3DrxhXslNZHz54/xxrx1TgvfhcFxfdCmUureLu4uknro/Tyvt9aTOwyRI2gPb5YsWo1Fi1eASenEvilcT3xBmil422IEX///Tf2BfqK4fkQXL16BUP690arth31eqMiWKiY16xZTURAPxwM3oscuQtEaTxbibnBtoxrGezft19XdqhPzRpVMGniJO0B8S5fa607ZF8AlixbjvnSLsnFpbSc9+6wL+GifYXe/aj4hx4/iEFDR2pRtJdUavTuO+ADkSQq76HOiWrxlyJFSm0Kb+52b+FdqyEw3L19E9u3bsaf8lu9cq07Tp8+hZw5c6GhnGHFp1KlSrpKTwmCllq7Wptqv7V6xVJM+G0G/v7nb8yeNgkFi9ojuZidG2dTPXfl4lkMHjpEV9e1bdMcQ4YM/6DCJ7xMjOcogESUGJ8nARIgARIggagToAASdYYcIfIEKIBEnh2/SQIkQAIkQAIxmoBR7aGMjy+eP41Dh49i605vBO8PRo6cOeHm4qTNcR0c7FHU3jnMaDoqieWIAjUSaWtWLsNoaY+ibjS3/7UFWv/a/oMkp0pUbhJT9B59B4oHRBL079UVdRs2jXLiWq1BGfOWkHZAKlG8ctW6KI8ZUQ6meN4QrVRi8tTJoyLknMHho8ewbuMWuS0fByWK28HZ0RGFCxdGngJFEDfuDxZvfWS0zDmwfw9GjZ2IPXv2iuF1LbRq2RzFxKvg3Y969mDwHgweNhr+/rswZGAfdO3eG3Fk3VHdoypxnFtuzV+9ehUPH9yPcf4fa1YsxomTJ+Hpu1t8NY4jk1T4/NygDgqqap8sWUVYzKtFJPWJKsuI7F3F3U9amc2at1ALGg3q1w4zun9/HBX/G9cvY9TIkVgkbZ7aSHusgYMG69ZOpvoYlSg5c+cXz5vS2LJlu0V5fOyd1X97+eKZtPzarX2Yjh4/AffNO7R/SwlHe6nkcRGz+pwoWNheV0pZun2ZiovyaNq6dSv6DxqOvPnyoVPbFmjaou2/xDXdhk2qVkaOGIpZsxegUcM6GDZsuPjuZIySUKPGrTrroam2AMchARIgARIgARIIJwEKIOEExcfMQoACiFmwclASIAESIAESiP4EVFL/kpg7BwYFwdtvjyTTbqFSBTcUkQqADOnTw9GpZKRNw01BRyXuVAukldIGZ74YmWeRxOyQfj3g7FLug/YoKum1bdNadOnRF7G+/RaTxo5AtVoNTLEMXe0yoG8PzJ6/GL+NH6W9BSx1k9okL/B/g9y6cRXenjvw8NFjeHj7Y59UACh/i7o1q0jMCyJ9xkxhN8VNOW94xzKqERbNm4XpkhA9feoURokXQI0aNWRdeT5IPF88dwoDBg3CJjFoHz6kP1opb4jESU2SoFYiUYaMmSWZnhJnTp8O7ytEq+ce3r8LPx9P3Ll7V8TPw9i1Z59mV9q5OMq5uUm1xXeoWKWGFn/MnURXZ0xVefl6bsPAYWNw8+YN9OjSAfXq1UemrDk/GlO1/nHjRmPm7/PQUMSbIUOGIm26TCaJvxFIta4x4icydsIUvRfbd+puleovQ7y8c1vMzMUT5YW0qvP2C8A+EatTyh5tWLcmcspZzpwlM3LnK6wrZSwpXL3LSxnGr1izFstXrJVWieXRoU0rOJcprytQ3n3uxfOnmPrbRKkQmQ7XMqUxoE8v3c4wquumABKtfoa4WBIgARIggRhEgAJIDApmNHwVCiDRMGhcMgmQAAmQAAmYm8DyxXOxadsO7Nq1R0yun6Jr53ZImiQJSpcuJV4PJSze8uhj77t5wyqpTnAXw/PNqFG9sqyxI+wdS39UfDhyIAg/N2uN23duw3P7Ju1XYSqRQiXUHIoXl/Y353BgX6AWCaLTRyWvHz64ixnTpmC1tJm5ePEi7Is74NfmP+s4V6xSXQzFk5k9yf05ZsZt/jMnj6P5rx3x048/YVC/ntrvI2GiJB+0Obt75yaGDh2MFSvXaXP6IUOGIWmylCaJuVFZUtq1An5p2gizfp8fncIdobWqvaF8Go4fDoGfv79uebdy7UZcvXJFKggKo65UPCWIHw+uZcvpVmjmSKwr3q9evsDihXN1MlytafyoYWFeL++fY/W88vmZMnk8Ro+bhLJlXTF0UH/kK1jMJPF/F6Caq3CRItIa7iwCA3xM4iUUoQDJw2oNd0X42LrZHbek4mODCH63bt6Es3MJ1KxaSf+9Oidq/6t/N9XvXkTWqeZV/8yfPR0r5Tfm4IEQ/Nq6ORrWr/+BR5Mhds39fbpUiAxDkaJ2GDNiEIo7lTHJ2imARCRyfJYESIAESIAETEeAAojpWHKkiBOgABJxZvwGCZAACZAACcR4AiOHDcQySR5fvnxZv2uHdq1QIF9elC7jioyZc1jc48MArpJXr1//ieBAf4wQU+N9Up3S7teW0gapHoo6OH8QF/W8Ej/adOiqPSBm/DYBdRo0Mekt7TdvXov3R3r8/ddf2gRdmStHp49i9OD+HdSp1xDHjx3Dy5cvUUiS2906/oqMmTKiYBEH/U7GLXNLv5tKeF+9dA4LFy7A+EnTYO/ggK4d2qBWvcYfrEmt8dGDexg7dpS0zZmP+tIeq0+vXsieK3+Ub44b763W00fap02fORcb1ixDxaq1TZKYtTTXiMxnxF7tE1Vh8OjxEwQEBkmFQYiuBKkqN/kL5M2L1KlToVSZcrq1kvqY4ra+qkTz8vbG2IlTdLukFj83kCqr1h8VW9Q61XmcPmWiVGX8hgIFCkr1Tz84OrtGeS0f4/XHH6+kJVNafCOVMZcvXbSKAbp654VzZ4rJ+yQRPm5JJUUs5MtfAEP794RbxWqyN2NZ1bdFre/5syfYLGbn48Xv486dO+jZtSPq1q2HzNly/QurelYJbksWzEGfAUPkdzUDZs+YrNvbRXUvvfv/Q9gCKyKnn8+SAAmQAAmQgGkIUAAxDUeOEjkCFEAix43fIgESIAESIIEYTeD2zWtigH0NewID4b7VQwyR9yFXrlxwK+OMxGL46yomyYbngqkSU18CqhLPr6UNzrrVyzBq3G94+PABBg/ogzp164eZM787hkqmKaPsgUNHIWhvECZI26t2HbvqViumXPPVy2IMLv30M2TIgCNHjph07C8xMdXfK7Zb3ddItc8TBB88JJ4B2xE7dmw4ORaDk1S3pE2bRhvcW8MzYMmC36Ully/cN23TPgDNfm4MR/FbebdljuJgJL8njB2JSVNm6hvwM6b9hnQZspo0JmqenLly6mTz6dDjSJ02Q4wXQN4/V39K4j/0+GEtkIZKK7J1G7dqgdHZ2RkuJR21wFilShVtDq98O9T/jsznoHi9/DZtGjbI+KrKq2njhqhUrc4nh1KxWbl0AXr1HyxiTBppSTcCTqXLmzT+7ybS1e9kpizZxVQ8Jw4dOvjBnozMO0fmO4EBXggJOYgly9cgNDRUBJD8qF65HOLFi4fq1avrFnHWqP5Qvyv37t7C6pXLMXXmHHz//fcYKr/ZlavV1GLR+7/Dao0+OzejZbvO+OGHH7Fi8TwUsXeKDJJPfkeJVnUXvjLpmByMBEiABEiABEjgywQogHyZEZ8wHwEKIOZjy5FJgARIgARIINoSMG58q5u7Ifv24N69+/D29YVfwF68eP4cTk6OkmCrIEnyOGFtiMz5smo9KpG2eOF8TJ42S9ruJMDyJfOQO29B/PBjvA8S0Op5ZbTbtUdvbZTdV27s9+wzQBJwsU2aDFUJvlXLFqKd9P7/pUlDTJsx26Tjm5Pp+2Ord/nnn7/FV+UoPDw8dLujjVt24tzZM5Lwz629QFQCs2atWpL0z6hv4KuPKcWkd5PLf/31FmtXLsUUqbRQhuwdpQqpXr26n2wzpCqDlHl3+849pC1RUcyZOQW58hYyKUKjPc9PklhOly6d9v+IbhU/pgKi9ovRfulgyD48f/4CS1auxcGDB5E4cWK4uZREjuzZkD1bVjiXdkP8BInCXUWkRJPZEr+NW3YgJDgEnaXip379eshbwO6TYpNaT3DQLtRv3EyLd+tWLZXqpeKmet0PxlHzbdmwGg2atECTn+tjztxFVhPC1FoeP7wPf18vvH37FstXr9P+HyoOlcq7Ip1UqeQW0S6icYgKPLU3ThwNwbLlK3Q1lmqZpjySito7f7QiRT0fuMsTjZu1ESHpW0yfPE6LXab+fbl+9QLabUsYlVfjd0mABEiABEiABCJBgAJIJKDxKyYjQAHEZCg5EAmQAAmQAAnEPAKGEGIICv5+frguGSdgvAAAIABJREFUbZ68/QNx7OhR5JG2NxXcSsGldElJtiVF3oJFTZ4YV3Pv3+svZtZbMGXa73Au6Yzm0ganUdOWH03Aq+dvXr+CESOGY8myVejSqS169+6HJMlSmDxAKvGoPCaUD4mv11aUKFnW5Ak7ky/6CwMaMVeC02FJbF+5ek3aHe2Fn/jBqMRyhbJlULhgASRNmlSqQsoiSdIUJr1druZ/+uQRNqxdhbGTpuqWXP16dUO9Bo2QPEXqj/JVCfNli+agZ99BYkyeCkvm//7RlmhRZaniffnCGalsyI9SpUrBy8sr0tUNUV2LrXzfMEBXApQynj954gT2SsWYp/cuMSu/CccSxaWKyA45s+eAg6Mj0qTLrIWCj7VUU/9N+X2oKi/VLunZs2fo1a2TFt0+V8mjvrd5/Sr0HTxCvvMUi6UllFvF6mYVJNSe6yRt4uYvWIrVyxehRp2GZp3vS/E24vD27RvdMu7k8eNiXL8HHl7+uH79mq7OKV6ssAghueBQwklad2X8ZBy+NNeX/l7FQwnD23Z6SPXOFjRqUBs1q1dD1Zr1P3p+1fO7vLejY/e+ct5fYMLo4cKzQdj/L/nSfOH9ezXPtk1rMeeWa3i/wudIgARIgARIgARMRIACiIlAcphIEaAAEils/BIJkAAJkAAJfL0EVGJ8t7+vTlQF7AnEBmlNlEjaYhW3L4oqFSsgbty4KFexiknaJRkJq/mLl0tVghdatWyKnxs1lASeyycTaeom9JAhgzBn3iItTvTr01f3mjf1TWK1A1SVQi6pjrh0+RKeP32KuNK2xRzzWGu3Kf7KUPrYkRDcvnUbJ0+FYtVad9y4fgN2dnYoL+KXam9UqVIl5M5XONw3/D/1PiqpfOvGZSxdsgQz5yxAooSJtAFyWfEyUJUWH2Or1rhgzgyMHj8Z/8i/z5PKAdcKyvvgG5NjU+v7beIYDJK2av37dseAQSPMMo/JF27BARWje2JCH3riiLTIuqpNuf39dyFrtmwo4VAU1apUEiErhW6h964IYgiXq6Rdkor991JhNHxwP11h9rF2ScYrqe+tkGqwSdNmazPyubOm6SqQyLbdCi8qdfbtitnj+PFjuH/3DhKJAGxLZ18JIrduXMWpE0dx+cpVbNnhCW9pJZdVVeQ42otvS0Wkl7Z9yhxefUyxdsPDw89zG/rI2VDx6N2zCypWqBBW+fE+X7VO93UrMe33+bh48QJGDumvxW1VrWfqj1pf964dcD77cFMPzfFIgARIgARIgAS+QIACCLeINQlQALEmfc5NAiRAAiRAAtGUgEokqcTV8cPB0vv+EB4+eoSVazbiwoXzyJYtO2rXrIwUyZLD1a0s0mbIHJbMCm+SzUikKT+HNVJdcU1uMKsqgFq1aiNT1pwfTTobyfrRI4f+zwNCKkWmTByrfQjMkQxV87188QyJkyRD6jSpxQT5skmSiLa4JQwfByV+7QsMkPZYb7B4+SocEL8QVRVSvqwLUqdMiZJOJVDS9X+t0SLzUS1w1q7fiHlyq75kKWcMHdhXJ8o/FT+1rvmzp2OMGGSrzziJfb1Gv5gtDmrPVxCRL2BXgIiAniY1Z44ML1v9jiFs/CmePYcPBOGZeMtsFwFzh4ePmGDfhqNUgvTu1hEXLl5CzTr1dGXP2VPHsGTpUkydPlsb3ffu1kEbzKvPp343VDyCdnujY9c++jdi2KB+6CAt0Mwhfr3P+uWL50ibLr20nHqj23+F97fNkjF7tzrnyMF9eCK/01t27ISnVIWoOJQuXQr58uTULbJqi5dSsuSp9Fn7WHXOl9ZtVO+sldZjo8b/hlevXsl5HILKVWsiQaIkHz3D6jvHjwSja89+OHz4MIaIP0iHzt1N3qrQWLv6vShmb49UzT2+9Dr8exIgARIgARIgARMToABiYqAcLkIEKIBECBcfJgESIAESIAESeJeAkShTN42PHAqRSogr0v5mPwKDgnUf97KupVC0UCHEjx8fbuUrImmylF9sl6TGDDPOFU+Nb76JJeJHV1SpXlPaG6X5aADUd1QLnulTJmLYyLE6wTqwT3c4l6lgtsSkSi6ePHZA32yuVbMqVq5aZ5HEqzV3oBFvdfv92KFgPJd2Qzs8vSS57YsrUgVTooQIICXs8dNPP6FW7dpImz5LGP9PJYgNscvXYyt+n78Inp4+aC2VPhXKlf2i4fVu351o37U3Hj9+pNvm1G/8i1mNqJWBcoECBaWl0HXcv3dHVznx82kC7ybSlSfPLn9/PHj4EF5+u3Hy5EkkSZJUVxEVl6T02o2bsH27Bxo3qotuXbqI30fRz55dNbYSTbr36gtfX3+MGj4Iv7brqKtFzP1Rc587fVzOvhOKFSsGHx8fs/3OmOJd3o3D1cvn4O3pqePg6RuAE9IqK2nSZHLeXOAs5zdlqpQoVMRBV7Op74VXTLpw9iSWLVuGBUtWIFWq1OgnlR+VqtXSYuinzr5qJ9e7Xz9s3boTQwb20fEzZyWNEuTU2kqMPG8KrByDBEiABEiABEggAgQogEQAFh81OQEKICZHygFJgARIgARI4OskYNwAPnf6BG7cuI5z5y/oZJjyAciTJy9cnB20iXYt6eefr6CdriB5P7mm/tvNG1fw+8wZmLdomSSrUmH0sIG6BdLnDMxVQn7l0gXo0qMfMmXOjLnSBqmog7NZA6HWOnbUUAwdMRZLFszWlQfmqDQx60tEYXAVb/W5K+2ODuzfiwcPHsBdTKv9pN1RmjRpUcLRDnZifJw5U0aUKV/lo/38jTEWz5+FqTPn4YyYnSumdeQ2epp0GT+bVN4X6If+4vmwV/xJ3NetgKvMYW5D8ju3byBb9lxInTo1TosBeniTw1HAHKO+quL94vlT8ZYJwhNpGRckRt1r1m+S//YcT548xcRxI+Hs5IQiIix86XP92iX0798Pa6Ql2+ABvdG2fUftR2OJSgz1HnNnTUWPPgMwefxotG7X2SLzfolJeP/eiMPB/YF49PgJQsS4ftXajfjjjz+Ev6OImMX17/PPTZvp6pyP/VYbc6mxDuzfLVVbC7UI7OJSGm1bNQszMP9U27pHD+6hV+8eWLV6A3pKNVCHTl20wG2u+Knqj4vnQrWwVu63W+FFxedIgARIgARIgARMRIACiIlAcphIEaAAEils/BIJkAAJkAAJkMCnCLzbLmnzxvW6GmDFmvUIDjkgSfDvUKmCG1ImT67bJTm7lAu7aazG2755HTZt3YZly9egQoVy6Cn92p1dKny2JYtKwAX47ECjZq0RP1588QOYj8LFSpgtkfZu4s9J2mwdlPc6E3oM6TNl+6oEkHc5qH9XSdITR0Pg5+eP23fuiAGyNy5JiyOH4sVRo0p5JEuaBKXLlEXK1GmF07c6Pg/u38GaVSswccoMfPOfbzBr6gS5VV8CiaSt2KfEBRXvKxfPonO37tglxuwD+/WUKoB+uvLDXMlT9X7GPqtZ72dUrlRW71FzzheTf2EM4evS+dNQt/LzFy6GWFLpdf3aZd2G6XPCkvqu8vkZOnQQFohIWr9uTQwfPhKp02awqCBVoUJ5BATsRujxw7otX3TcC+rMqnUrYWDnzp16j7tLNcaBkBCkEpGvXq1qSJYsGZykMiRnnvz48af4Ye+pnlXtvzZvWKOF7j1iuN665S+oJWbnn6u8U3Oqcz9p4njd7qxuneoYMXw40mfMZtb4Gf49/QcNpwASk39c+G4kQAIkQAI2S4ACiM2G5qtYGAWQryLMfEkSIAESIAESsDyBd30AThw9gEdSIaBM01WCTfllqD7/9kULIIWIIVWqVMG+oL1YuW6T9lfo1qU9qlapjBIl3T67cDWHEk169R+C13/+iUVzZ6KUWyWLvKyqOkmSNCm+k1Zf169d00LO1/x5v93R0SNHxJfhOvwCAhEUtF/anyWFW5mSKFKwIBIlSoQcOXNisZidL1m+Gtlz5ECvzhLzWvV1EvRTyWSVxLx66RyGjxiO1XLzv2vnduglLZA+J5iYKibq/Qb174Xpv8/Dknm/o0bdRqYa+qsdxxBCvv3uW216rlqZfa6KRyXP/5Q2ZMOHDcL0mXO0SDpm5HBky5nP4gJEqtSp8Ndff+Ha1auIG/eHGBHDp08eYd+e/7UpCwoO0V4hj588FgHEEUUL5xfhOgWqVKuBVGn+532ixGZVuXX+vJzJIQNQu04dZMyc45MsjFaFIyV+02bORWnx+Zk8cRyyZM9j9vipvePm5ia/RUFwm3QjRsSLL0ECJEACJEAC0YkABZDoFK2Yt1YKIDEvpnwjEiABEiABErA5AirxZdz89fHcqY2zV6xZJ73fd0jLqkxSDeKAA4eOiZBwHeOkBVLZcuWRMUuOzybF1Hgb167Qhrt3797B79MmoVqtBmZPpCm46n3ULeY0cuu8oHicBO0NNKv3hM0FNBwLUoyePH4oJtj7cOr0GTwSA+bFInY8kZY79vbFkChhPGx034qaNaqgbq2aqFWv8Rc9H54/e4KePbphqYzT7tcW6N6jpxhRZ7JYzAsXKYJToaG4cum8VLKks8i84UAdrR9R+yTWt7FESPxO2mA9/qyYoASwKZPGYsjw0Sgg527mlAkoWKS4Rd9frVdVrcSTarPceXLjyOEjMaryyxAprl+5gJDgYG1mvnDZahw+dAi5cueW9ljFUCBfPrx58wbjJk/Dt1LN1al9azRt1hIJxez8c5Uwauw50p5w4NCRyJI1m24dmDNPQbPHT82r/lEirGpTaD/ktNnn5AQkQAIkQAIkQAL/JkABhDvCmgQogFiTPucmARIgARIgga+MgFEloKongoMCcPDgIVy/cQNz5y8RE/PXmP7beDRp1gqx48T9Yhscr+3uGD5uMo4fPYbfJoxG0xZttE+IJT7qPZYvnouO3XqjZbOfMXHydLO2b7HEO5lrDqMlmjI8PhV6AleuXsPcBUtx9uxZlCxVEiOHDoCdQ8kvJk4fP3qARQvmYuCQkahUqTxmTp+OFKnSWkyEUO8RP348vcceP35sLlxf3bjqLMWJEwdx4sbBnVu3PllJpfj77NyMyjXqIWu2bFi7crF4CRWzWPyNwKj17vHzQKXqddC4YT38PmdBjDz7hu/Hq5cv5DdWKvikKmTz1u3w9JGqENn/L1+8RJGiRTFiUB+UrVRD4/mc+KF+85ctmot2nXogp1R/LZgzI1xeL6Y4EOpdlPdMoiRJkS9vPqRt7WOKYTkGCZAACZAACZBABAhQAIkALD5qcgIUQEyOlAOSAAmQAAmQAAl8icC77ZLUrf6ChYrg8pXLuHfnFhInSf5F8eNg8B4MkET4bunBP1VuhCvRRLWgslQffrX+Rg3rwsPTF+tXLxUD7qpfeuWv/u+NmP/x6iUmTRiDEaMn6FZnI0aN+6hB+rsJZ3XjfszIoZg8daZunTZjykTkylvIYkzV2m/fvIZMWbLDSUy6fX19LTZ3TJ9Isc0mgoaq/rhy+RJ+ipfgg1dWCezQ44dQrlI1SWS/QMpUKUWAnBcmnFnq3KuFqbX80rQh3DdtwyJphVa7/s8xUgB59/wpvkqAeiIiZOBuP/TqNwRXrlzBWKnW69K9z2fb1qlxDMF4mJx59Vk0dwYcS5a1WOWMitnOrRtQv3EzNGpQF7cKTYzpx4rvRwIkQAIkQAI2R4ACiM2F5KtaEAWQryrcfFkSIAESIAESsD0CKjmWK1cuXRFw/97tzwoghgF29169xbTXCz3EJL1Xn/5IkDCxxcQPRVDdZs6TNy9uSvXKtatXZM3JbA+sja5IxXDNisX4pWVbLYAMGzFGWqLF+ehqjdY1KtE6Y/Z8xJXKIGWUXr5KLYu+nUqgLpo3Cx279sKo4YPQtUffGJ30tiRcFeM0adPg8aPHuHXz+kfbKKlnGtSvrUWHonZ2uh2TQ/Hi+KVRHd2Wyd6xtF6yJYQQtRZVwXBNfH8unDutzdctMa8lY/K5uZT3RwknZx2Dvbt9UKx4qS9Wb00cNxILFq/A6zevMbBPD7Ro08GizFTM2v3aEqvWbsCC2TOw+GFFW8HJdZAACZAACZDAV0OAAshXE+r/1959QElVrGsffy4qoiJilpwkqCg5MwwM0YFhyCJJkJwRCYqgmEVEkJxzBglKDgOCKAhKkBwkCwhKkGD2q9r3Tn+DQ5jQvXsD/z7rrLN0uquqf1XdZ616uur15BslAPHktDAoBBBAAAEEbh0Bu7n8pNnE3G0K6R4zG6APP5LqqpvLP588oa6vdNZ4cyd9vTo19eabbypNusyub0b/cuonZcvxhO5NkUK7TXBzhyngzCNuAna+P502UXVfaKK2rZvpvQ8+umoAYjdb7S/9X+nxllKmTKkB5rSPvW7H7Q1nu4FatlxZrflyjb7+MkrP5Cnk+pqLm+6N9yy7HmwA8vOpn02geNDUaXjssvm19ls2rlPJ0s+a56VVz9e6ODU4BgwdrW83bHAKoZcpVUKRkVWUIXO2gM+LPbGWJm16pbgvhfbs3n3TFECP68qxn8nSZcpq7ddfa+XyhSpSPOyqn0c7d0sXzFG7Tt2cAvf9zMmv2vUauf75tWssV+5c+mHfPu3bs0tNZt8V17fL8xBAAAEEEEDATwIEIH6CpJkECRCAJIiNFyGAAAIIIICAvwTs1Sr2WqNNGzdq/76dSps+y1U3yDq0a6mRo8ebzcf7tOaLKKXLmMX14uN2U2/tmhUKj6iuokULa968Ba5v6PnLPhjt2M1IW0OhXMWqatakoT7uN+CKAZJdF6vMBmuj5m104vgJ9f7gbbVu97IzZLcDEDtmW0DZjunAD/uuW+w5GK43ap/WNnuO7Dp44KAOHdinRx5Lc1mIYU9bRUZWVlTUSo0Y8okJzpqa+hPnzOd/uXbv3ae+A4aYk2MnVTG8nMqXCVOY2ZxPnzFrQNaJHasNY+yJk+IhxbV0ydKABy5em1c7HxUrVdTKFV9oxbIF1wxANq7/Sm1f7qpv1q5z6js1aNTU1Hq52/XPrw2tMmXOottuv11HDh9W1eHnvMbKeBBAAAEEELjpBQhAbvop9vQbJADx9PQwOAQQQAABBG5+AbuhVrlyhJYti9K336xRzlz5r7hBNm/OdD1fv7FTLP2+lPepW5eOyp4tq6kLEGnukr/dtU01uwn+4ftv6V1zcqGv+UVzkxZtXev7ZlgN1u/IoX3K/sQzqhJZUZMmT79iLQC7aVm6bHlt2LBeSc0JmxfqP6/8efOoTv1GTr2XJEmSuMJhAy+74Z4i5f3Knj27Nm/a5BRC5+EfAesbHYDu27vTnK7I6Jtb+zdb76d8xSpKnTqNVq1YbgpZP+x83uzfzp09rfffe1sffTzABKG3m6voHlB4hTLKmD69WrVpr/sfeMivn027docM7KtOXburR7fOerX7m66tQ/9oJ74Va9CqRRONnzhVCz+bqdAy4Vc0tmFRlcgIUydpqf76+y9NHDNCNZ+v73xXu/XZjX63NogJK1fRnALJrRVRUYoY/HPiIWgBAQQQQAABBOIlQAASLy6e7GcBAhA/g9IcAggggAACCMRPwF6pUr16NS02G2XLl3yuYqY4bsxf+NuNzv/91XElcwXRl+rycnstWbFa367foBKhJRRWoqhKlw5T3gLFXCmqazf2ypYtq9WrV5sTK7uVKk161zf04ifsrWfbDdRffv5JadNlVEiJEOdX9P890WHnfPaMyU6dkJxPP618uXNqxqy5Sn5PctV5rpoyZsigWs/X8xXMDuSJEDvf9iSKrTtStUqlqwY23lK+cUZj57pUWJi+WrPGnK74RllzPO37HP/++2+qVq2qVq360lyFNlyVq9X2rRX7ui/MCYRPBg/TggWLnZoguXJm17SZc3TPPfeoYoWyejxLZtWp18C5Vss+ErtO7FqoUaOqOfW1UJu+XascT+W+5T771uDll9qYk3gTNHzwJ05h8SsFGkvmz1ZkjTrmSsOHdfToURUqVFjh5UoptERxFQkp7drJPTveAf16q/sb7+idN7ur3UtdCEBunK8HRooAAgggcBMJEIDcRJN5A74VApAbcNIYMgIIIIAAAjeTgA1AatWq4RQ1nztzsnM1UsyNSrthvtJsdFYxm2m58uTW9MkTtem79Tp27LiGjhqvnTt2KDQ0ROVKlzT1ACoomzlZYDe9AvUrY9t2qtSpdOniJXOv/WlXQpebab7tfF688Kvz6/y8+fLpm3XrLnt7dmPbbnyHlAjV3j17tHDeLCVPfq/2m6unFi1dpgkTpylDxgyqVjncnADKFvBfldvxtm/bUmPHT9KQAR87VzAFam3dTPMc1/di57tmzar67LMFWvvlCj2dp4BzJZp1X7NyiSKq11aWLI9r2ZJF5oTHw06z9jWjhw/S5OmztcYEJ00bv6Ca1aooU9bs2r5lkxYsXqJRYyYoQ4aMKl+2pDJnyqRmLds6m+4JnTvb59/mJEP27Dl04OABnTtzRnebQC6xoUpcnbzyPOvQ/dVOGjh0pN56vZvatO902Xeg/fulixcUWipM27dt1QRz8uOi+eehJjDZ9N13KlqsmCqUKalSJUsqT4GiAf2ujl4rEREVtXTpcu3ZtdW5YrHykF+8wsk4EEAAAQQQuGUECEBuman25BslAPHktDAoBBBAAAEEbh0Be7qjyYsNNG3GHLNZNlzVn6t32aai3UwLN6c/vlrzlRabzfASphiyfdh//+XKpU4dgJe7vKZkyZKpckQFPWGuKWravKUeeTS13xFt+HHq5HHn9EL+AgWcX63ziJ+ANfzjj991T/Lkeuqpp7Rl85bLGrAbqJPGjVCrdp3MSZswTZky7f82xP/S9xvXm3ogx9S+czenZsQzuXKp0rOlVSh/foWVr+RscPt7Q9qO18719m3bnBM/j6VO5/c+4id4cz3bznfjF+trytRPnSuVipUs68y3/V549tln9aUpPL98yTwVLlbKCS9sMDJhzDCnCPrevXvU/ZVO5pRIdWXO+oQDY+dr25YNzjVlr73e0zlZls2EFjWrVtKTT+RQeOXqCVontt2zZ35RRlNL4oEHHjCB3P6bayLi+G7sfL31RjcNHj5aL5lgsMurr18WKtn5mTFlvJq2bKeCBQtq9qyZTlC0Ysl8nT5zVt3eeFvHjx1TGVOvJWuWTGrerJmyZHsqYJ8pO14bmJ4/f14/mpMoyZLdpUqDTsXx3fI0BBBAAAEEEPCXAAGIvyRpJyECBCAJUeM1CCCAAAIIIOA3Abux2LFDa40YNU6f9OmlF5u1vmxDbemCOXqu/ot6+ulntGjhAmcDK7oGgH2trcfRo+e7+tf8J725+9/WCKlqaks8/eSTqlW7rh546BHnF+P+2Bi3m3tzZk4xtUhe1CudO+iNt97nBEg8V4KdC/vfO5LeocyZM2vP7j2XtXD6l1OmwHSoTpw4boosL7qsJoz137ltkyKq1NCRI0eVNm0a539DzVVoJYoXUoXy5ZW/UIjTnj/m27Zz4fyvyvz446bexDlz4ucXZ/3x8J+AnVO7of5B734aNWyAatdr5NSJWB21SJWqPqfcefJoyeJFuvPOZLJ1YcaOHqH+g4brgglA+3zwjiqERyilOU0U82SH/V6w83/i+FGtX7tGQ0eO1cJFi82GvFkjZUJVsWK4cucrHK8gxK7ZNauWqoI5oVb7ueoaMXKc39aY/zQD35J1GGxOQr1jaiDVrV1DH370yWX2ti6Lrd2zZfNmU6h+mfIVKu77vra1dL5aFaXqtRuYgOsvpbgvhbmqrIwKmgCzYkSEczrDtp/QUzr/ffe2rfO/ntWD5v8Dcpjwa/Omzc5YCEACv07oAQEEEEAAgf8KEICwJoIpQAASTH36RgABBBBAAAFnw8tugH7Y5xP17PGqOppf9992222OjN3ILFmqlL77doMWL5hr6oOUcf69fY29Omvy+FF698O+5hfFx/XaKy+rbJky5iTJDI0zBXpT3JvC/HOoMpl6ES1atTUnDlIkemPNjqdq1UgtWrREUUvnq0jxsES3eastgZgBSLp06XRg/wEfgfW1dQVeMmvA1tsYO26ir+C4/ZsNw4aPGe/8qj9vvvx6u0dXHf3xmD7sO9Bcl7Xb+VV5ZMUKypM3r9ngLpLo63XsWHds3WhqFpQyYU0WbTRX+PDwr4A96TGo/8fOKS77PdDl1R7ms/2nypQr51yZNGvaRJWuEGE2ss9pgHneqLGTdFuS2zSgby/z+SuplPc/eM0gwp42Wr92tQ4dPKSB5tSCrR1k10nRQvnN/5ZWwSKhcV4nzZo01NTps5yr+kqWrXjLBiD2e7dD51dVq0YVDRg47LKi9bZWS/tOr5orrkpo0qQpvsDQfpZ+OfWTmcO++qjvACW98051bNfKCaeSJk2q4kULOt/V7Tu87BS6t4/Ehpg2XPt69TKVLFNRLZs3Vr/+g53/byEA8e9nmNYQQAABBBCIiwABSFyUeE6gBAhAAiVLuwgggAACCCAQZ4FPPu7l/KL45fat1anra74Cueu+WqmwsuEqXLiI5s+f52ym2Y203367pP59e2vIiDHmWpqzzqZ56bIVnF+CHz1yQCuXL9XK1V9q9tz5Sp8uvfmVcWmncHb9Rk2dDfWE/sLY9v3Io4+YK5z+0L49u8wvix9N9CZdnJFusifedvttSpUqlY4cPuK8M2trf+FfuGgx/bDvB61ds0K58hZ2fO1G5pgRgzX107n60sxrg3q1zX+fN8FEGec6rdVRi/WDCVL6mA3OM6Y2Q1jJEKVNk1qdOnXRI4+lceY7IZupdkyjhg10AplXu7ykV7u/maB2brKp8+vbsUHmrOmTzWezmd7o3tUxtgW0a9VtpCfNFWmLFszTmdOn9GHv3vp09ufKlCmz+vZ+V3lN/Qh7KiQuDzuPdp18t/4rZ7190Ke/Dh06qIIF8it71sxq0by5U3z9emskm6k5c/z4ce3etV2PpUobl65vuudYy5Um/K3+fAOFm9Mb4ydM9X0auJ/SAAAgAElEQVSfXrp0UQXMKZsD+3/QV6uj9HTugo6pDS9/OvGjPnj/XQ0bMdZcIZhWA813/lPP5NGK5Uu0Zes2p6j6gw8+qEhzjaGt2dKocXMlu+vuBH9XW3jbb8MX6mjqtFn6fNZUlXk2kgDkpluRvCEEEEAAgRtFgADkRpmpm3OcBCA357zyrhBAAAEEELhhBOyGmr3Tv4PZZH7BbGz3NidBbC0He/VQiZKltGvnDi0ytT+KhZZzNsl/PnVCH/Z6X2MnTNGDDzyocaOH6smcuZX83vt8V63YTbfvN63XYbPJOXXGTM2eM1+PZ82qkiGFVSaslMqFR8br+pvoDXp7nUpK0+fj5kqk77ds8Z1OuGGwPTDQ6OvI7kt5n5L8TxKnkHy079CBfdXRnAR4rmYVjRk32fn3di5t8fExpvj55k2b9LK5Lq1p02bK9HgO3+vsc375+aS5Mmuxvt+6VROnztSvv/6qKhHhypHdFEqvVVtpTN2W6Pbiw1C1amWngPLm79Y7dSaut0ken7Z5rpyTXEsXfqbK1WqrbetmeufdXub0h71CaZPzuf/3H/P9MGWqxo2fovDw8mrdrLHKhleJN130urNXNO3Ytllff71WQ4aP0TFTj8LWDspnrtqqVr260mfMesVrmC5eOG8Cz4eVOnVq7dix/Zb97NtQ4Zuvv1A5EyaUNKc85s793Pe9O958F7fp0EUVw8tpwsQpTi0X6/79pm80cNAQjTcn8+zprGGD+uqJnHmcq85sOHn8x8PmpNVmTZo2XdNNLSgbkISXL+3MSWS1Wk4NkYQ8bN9ZHs9ian/8eFn9Hk6AJEST1yCAAAIIIJA4AQKQxPnx6sQJEIAkzo9XI4AAAggggEAiBewmlb3aqGqtuoqsXNFsnE11NtRmTp2gxs3bqFDhQvp87lzdaU5/7N6xRR/37aeZsz9T1qzZ1KfXW+YanNJXrcNhr9fZv3enOa2x2xRNHulcnRRSIkShxQoppHgxlS4f4ZwuiL5y63pv5avVy1Wxcg2z8ReiWbPmshl+PbBr/P3Rxx411xr9qgsXLjqbpKdNgFG0eAmdOnXS/Hp8hR7PntPMzV+aOnGM3u3VV0dNAWN70qdwkaK+8ONKzdu6D3t2bdMXX6w21yX97xVaxYsVVDYTWrVq094JyuLzyJgpo07+9JMZ1ylf/Zn4vJ7nXlvAfv5s0XJbu6V8+TKmWHlltW7fWflMXYgWjRto/ORpiopaqeZNG6pRwxd8p4IS62oLmm/7fqPWrl2nXiZ0vfvuuxVivhfSpUmjlzt1vewapuir0AoWCVFISIg5jbYgUScTEjv2YL7eWtjv4Vx5C5nv5sL6YuVK5/N78qdjJrAurZ9+OmGunVqhbE884wzTfo9PmjZDy5ZF6bla1VSv9nMKLRMey88GK/t2bzNBxV6NmTBJn89baE4A5XRqthQuVNAUr68R56vKbL92TGdO/6xHH0vt1AratWuXE8jYBwFIMFcQfSOAAAII3KoCBCC36sx7430TgHhjHhgFAggggAACt6yA3fhav3aVQsMqKCyspD7/fL5+M1ep2NMfW7//Xls3b1CWbE8pasnnGm1qQsyeM8/ZKG3ZpJHKmYLE1/tFvm3/n3/+dq5U+u3SJfV87yNtMcVw8+XPp3y5c6pe3TrOVS3XC0HshlqXTu01yZwueKNbFzVr1f66fd+ykxqHN/7wIw+bAOS8Lpk5sbZ9PnxXb77TSzVrRGqYqdXw69kzGjliqHqbegHJkyfXAHNlTtlnKzuBRlzm/NCBPWZT9oS5omeSxpnTQjZwqRLxrArky2dOG9Ryrk+6Vjt2TPZX/w89/IgyZc6k7du2x+Fd8ZT4CtjP5+GDe5XdbJjnfPppZz3s27tXRYoWMaeDzpjr0Pap17s9VblKNaVOm+G6cx/X/u382sepk8e1bPFCbTD1RiZOmaF7k9+rCuXClM5smjdr0dqpMRK9Pt/r9bG6vNxOXbu9cUsHIEcO7zefiWwmoHjSnNTZ4oTI/ft+qG493vLV7rFhgw0sJ02frW/WrVPH9q3MZ7uG8piry672sM42tN707Vrn/wN6vtvb1H/6zpzwe0pPZMushvXrqlCxUr4g41pzbdvaaK48KxISplKlSmrBgoW+OSMAieunhOchgAACCCDgPwECEP9Z0lL8BQhA4m/GKxBAAAEEEEDAjwJ2A3TThq9VtERpFS1aVMuXL9fo4YPUwRTSDQkpps8++1xRi+epz4AhWmV+1W9/CV6/bl3lLVgsXpuh0YXT7ebaNnNN0ieDRji/Ci5Xroy5GquoKlSooBxP5b7i9Tf27drX2188b9v6vbkO6RvnhAKPhAvYQOL0L6dNPZffdOLYEZUsXdapr/DtujXm7v971KdPbxN4TVIGU7tl/OhhzpU5cQk/okdk15UNOH7Ys8P8Kv24Bg8dphkz5/7fVWhFFBpSXFVq1L7qVWgxg7n69Z4zocyYW3bTO+GzfP1XRp8eSJ0mvVKaa9F+/vkX/U+S/1H69OmdX/y/Ywqj2/o+/gw/Yo4q+mqsnds2mcDsuMabwt22ZoS96qpUyWLKkC6dGjZqrDr1X3A28lcsW+icVkloHaHri3j7GdG1euxVgDlz5jTX0m12Tm+FhJbSXhNc7TWnOB5+NI3mzZmpt97vrZMnTzqBsQ2wUpk5vl54Gf1da2u2bNn4jVMP6JPBIxz70qZ4fYmihVSnTl1lzJL9qt/Vtg27dt5/5w31+WSQunXpqI7misXoOSMA8fYaY3QIIIAAAjenAAHIzTmvN8q7IgC5UWaKcSKAAAIIIHCTCkRffWI3uPOaX+cvNb/GLlS4qH46+ZMWz5/jbLANGTnOqbkxuH8fhVeqHOeNtKuR2XoRRw79oPXfrDcnDAbq7Lmz5pqVAipepJBq1KypDJmyOZtrMTfr7GmAx00R5FMnT+nixQu+Qu036bQE/G09ZTZPd5r6LhcvXFCP17pq0JARqlk9Uu3atFG/AQOcui2lTI2B7mbz1Ba8tnVhEvqwa2zvrq36Ye8e5yq05ctX6JlcuVSxfJjy5c2jipE1neu2YvZhX9PEXME0ZeqnmjRupCKr177uKaGEju9Wf529quhBc9Lmn7//cSjuvPNOpTFXUY0a2l8Fi4bqrrvvidPGeWIdo7+LDh74QSPHjNecufOV0RTkLlIwj+Z8ttCpV2I39JOZ6/jispGf2PF49fWXzPefrcuR1dRV2rlzp958/VV9/Mlg5/TWYPM57t3rHXPqaprzvTpq6ABzuq+cUtx3f7zNoovX23Dq4IEDesWcMLEhabGihRXxbHmFlizpXLVln/ffQMr+uzJly2jd2rX6+suVypkrv69/AhCvrizGhQACCCBwMwsQgNzMs+v990YA4v05YoQIIIAAAgjc1ALRvwB/LHVa5ciRQ80bv6BXXuupAgULqnjhfJpmfrX/p7kWZcSgfuaX18X0wEOPxHsj7WqAduN19cpl2mquNxoyYoxz/U5ExfLKYjY9W7Rsc1lfdgM9n+k/VSpTBHn7dr+N4aae3Gu8ufwFCmjTxo1OsfqKlavpxx+PqUe3zlqzdr0TUNSrW0tNXmxkaryE+YUo+kTIlo3rdPTIEb3bu5++2/Ct8hXIr4rmyqOiptZM0dAyvsLNttPs2bObcR11akWky/D4Lfurf79MwDUaOf/rWeeqqeh6PEWLFdMH77yuwua6Ixs0uBk2RF+Zt8Wc8jr/6zm9+f5H5vTBN853Q67cuU1o+s0tvw7sNVVJTUhlT+msWbVSBUxgbU9yzZk+SXM+n+dcE2ivElu2ZL4eS53+utfNXW99RQch603x9U2bv9fH/Qfr3NmzerZCGaUxJ3VatWqltOmzXDYvNrB+ylypdvTIUVNn6Pxl12YRgFxPnL8jgAACCCDgfwECEP+b0mLcBQhA4m7FMxFAAAEEEEAgQAKXzH3vd5tfeT/08EO69957deTwEWUyIcTPP59yajAM6PO+ipcq5/dfXkef8jhyaL+O/XhYkyZPcTbvbM2J0OKFlducEniudh09miqtxo0aojYdOuvlDm2cWhVubsoGiD2ozZY1v86OWrFCNapFaqYpKG8fBQoU1I4d29WlYztVr15d2Z/MFRDn33//Teu+XKEf9u831+uMdAKtEqElFFaiqCIjI52r0M6dPa3HUqUxgddjZkw7nE1cHoERsJ//Rx551AkZGtSvrdde7eYUunc7/Ij57qKvzNu3e7t279ppTg6NUteX2qh0hcq3fABig6o7kt7hfFc3rP+8hgwb7YQhJYoX0mRzYirUnNx6w5zqig4v/fFdGf1dfezoIe0z19otWrxUYydOdaasRPEieiJHNjVq1MQEIZmc66/s83Llyaf77kvpXM0VcwwEIIH5HNMqAggggAAC1xIgAGF9BFOAACSY+vSNAAIIIIAAAo6AvVrG1ndIclsS5zqTf//5V/fcc7e5Eiu/3n+7h/NLcHvFiT820q5Gbvs9cmifDu7fp6nTP9WIUeOUOUtmFStSQOnMdTxRq77W2q+/9hVlv1VrAPhjydoNysqVK2nBwkW6/bbbzfz/6Vx7ZB8zp45X8dDSui/lAwGf71/PnTH1XNbpyJEf9fpb7+u8+aV4gXx5VbZ0SecX7d3feEehJhhZsGBBoq7g8ofZzdyGPVHwYqP6JnQsroKFCunp3AU89XZtQGNrB+XOW8jUp7k7oOvSU2/8KoOJvnLqtttuc+q2/HL6tPnflOY6u4uqXauq2rZuHe8aTfF537b/4yaw3mvCqcVLlqmvORFiT+aVCCms+804ur7STeu+Wq06DZroOTOekaPGX9Y8AUh8tHkuAggggAAC/hEgAPGPI60kTIAAJGFuvAoBBBBAAAEE/CwQHW7YAshJ70iqOs/XUOsWLQK6kfbftxB9TdKOrRuV3Py6uXuPHqYOwAI98OADpvbHSecalSOHD+kec70Lj4QL2MCrWZOGpuD0NKfug91IzZw5sz41V+ikz5glQfUCEjqa6KLOyxYv0IGDBzV0xFgdPnxYadOm1UHzzx+ZegZt2ne65X/1n1DfuL7OXoWWJl1G3f/AQ54MGOw6sY9AhrBxtQr286zFvfcm10VzYif6cfddd+lVU2y8UqWKJsAqGPDPS/R82KsJbVjZt18/fTpnnh588EGVDCmivfuPOPU/vvxiqVO0nhMgwV419I8AAgggcKsLEIDc6isguO+fACS4/vSOAAIIIIAAAkYg5i+KzfkPvdOzuyIiIpzCtcF4RG+u7d+7Uzt3bDMb9VNMUe55CikRoiWLlwR8cy8Y79nNPv/443cTLLyrHm++65wAKVykiFPzoVDRkkG59ij6ep3jx46YQum7tGz5co2dMNUJQA6bgtip0qRn49uFBRI9Dy50RReJELDzlCFjBh09etT5/NpwYaQpWB8SWtIEmFld/azYsdjg+uyZX7T9++80ZPhIc4JvlhOiJ70zqQ4fPOAEqjEfnABJxOTzUgQQQAABBBIoQACSQDhe5hcBAhC/MNIIAggggAACCCRGwG5ipbw/pbkGK6nGDB9kfrFbVI8+lsbVjbSrjd/Wi7DX39h77x829Ugez57TE+NKjHewX2uvPJo9Y4qeq9dQzRo3VP16dZx6AV65Vsxer/PjkUOmDsgZFStZ9rICysG2o38Egi1gv6+zZstq6ib9qIcfeUQTxwxzri2zQUMwT8jY75U9O7ea03on1G/gUHMdVgoNNye6/vu9QgAS7BVE/wgggAACt6IAAcitOOveec8EIN6ZC0aCAAIIIIDALS1grzI5ceK48hUs5hScDuZG2n8nwv7COPrX6V7ZpL+RF4u1/O23S1o8b46ezpVbmbM+4an5jj4BZE+qUPz8Rl5pjD0QAvbz8fabr+nLr9abGk1vONcU2ocXvrPtd7X9jt783VolS3aXsj3xTKxxEYAEYlXQJgIIIIAAAtcWIABhhQRTgAAkmPr0jQACCCCAAAIIIIAAAggg4JoAAYhr1HSEAAIIIICAT4AAhMUQTAECkGDq0zcCCCCAAAIIIIAAAggggIBrAgQgrlHTEQIIIIAAAgQgrAFPCBCAeGIaGAQCCCCAAAIIIIAAAggggECgBQhAAi1M+wgggAACCMQW4AQIqyKYAgQgwdSnbwQQQAABBBBAAAEEEEAAAdcECEBco6YjBBBAAAEEfAIEICyGYAoQgARTn74RQAABBBBAAAEEEEAAAQRcEyAAcY2ajhBAAAEEECAAYQ14QoAAxBPTwCAQQAABBBBAAAEEEEAAAQQCLUAAEmhh2kcAAQQQQCC2ACdAWBXBFCAACaY+fSOAAAIIIIAAAggggAACCLgmQADiGjUdIYAAAggg4BMgAGExBFOAACSY+vSNAAIIIIAAAggggAACCCDgmgABiGvUdIQAAggggAABCGvAEwIEIJ6YBgaBAAIIIIAAAggggAACCCAQaAECkEAL0z4CCCCAAAKxBTgBwqoIpgABSDD16RsBBBBAAAEEEEAAAQQQQMA1AQIQ16jpCAEEEEAAAZ8AAQiLIZgCBCDB1KdvBBBAAAEEEEAAAQQQQAAB1wQIQFyjpiMEEEAAAQQIQFgDnhAgAPHENDAIBBBAAAEEEEAAAQQQQACBQAsQgARamPYRQAABBBCILcAJEFZFMAUIQIKpT98IIIAAAggggAACCCCAAAKuCRCAuEZNRwgggAACCPgECEBYDMEUIAAJpj59I4AAAggggAACCCCAAAIIuCZAAOIaNR0hgAACCCBAAMIa8IQAAYgnpoFBIIAAAggggAACCCCAAAIIBFqAACTQwrSPAAIIIIBAbAFOgLAqgilAABJMffpGAAEEEEAAAQQQQAABBBBwTYAAxDVqOkIAAQQQQMAnQADCYgimAAFIMPXpGwEEEEAAAQQQQAABBBBAwDUBAhDXqOkIAQQQQAABAhDWgCcECEA8MQ0MAgEEEEAAAQQQQAABBBBAINACBCCBFqZ9BBBAAAEEYgtwAoRVEUwBApBg6tM3AggggAACCCCAAAIIIICAawIEIK5R0xECCCCAAAI+AQIQFkMwBQhAgqlP3wgggAACCCCAAAIIIIAAAq4JEIC4Rk1HCCCAAAIIEICwBjwhQADiiWlgEAgggAACCCCAAAIIIIAAAoEWIAAJtDDtI4AAAgggEFuAEyCsimAKEIAEU5++EUAAAQQQQAABBBBAAAEEXBMgAHGNmo4QQAABBBDwCRCAsBiCKUAAEkx9+kYAAQQQQAABBBBAAAEEEHBNgADENWo6QgABBBBAgACENeAJAQIQT0wDg0AAAQQQQAABBBBAAAEEEAi0AAFIoIVpHwEEEEAAgdgCnABhVQRTgAAkmPr0jQACCCCAAAIIIIAAAggg4JoAAYhr1HSEAAIIIICAT4AAhMUQTAECkGDq0zcCCCCAAAIIIIAAAggggIBrAgQgrlHTEQIIIIAAAgQgrAFPCBCAeGIaGAQCCCCAAAIIIIAAAggggECgBQhAAi1M+wgggAACCMQW4AQIqyKYAgQgwdSnbwQQQAABBBBAAAEEEEAAAdcECEBco6YjBBBAAAEEfAIEICyGYAoQgARTn74RQAABBBBAAAEEEEAAAQRcEyAAcY2ajhBAAAEEECAAYQ14QoAAxBPTwCAQQAABBBBAAAEEEEAAAQQCLUAAEmhh2kcAAQQQQCC2ACdAWBXBFCAACaY+fSOAAAIIIIAAAggggAACCLgmQADiGjUdIYAAAggg4BMgAGExBFOAACSY+vSNAAIIIIAAAggggAACCCDgmgABiGvUdIQAAggggAABCGvAEwIEIJ6YBgaBAAIIIIAAAggggAACCCAQaAECkEAL0z4CCCCAAAKxBTgBwqoIpgABSDD16RsBBBBAAAEEEEAAAQQQQMA1AQIQ16jpCAEEEEAAAZ8AAQiLIZgCBCDB1KdvBBBAAAEEEEAAAQQQQAAB1wQIQFyjpiMEEEAAAQQIQFgDnhAgAPHENDAIBBBAAAEEEEAAAQQQQACBQAsQgARamPYRQAABBBCILcAJEFZFMAUIQIKpT98IIIAAAggggAACCCCAAAKuCRCAuEZNRwgggAACCPgECEBYDMEUIAAJpj59I4AAAggggAACCCCAAAIIuCZAAOIaNR0hgAACCCBAAMIa8IQAAYgnpoFBIIAAAggggAACCCCAAAIIBFqAACTQwrSPAAIIIIBAbAFOgLAqgilAABJMffpGAAEEEEAAAQQQQAABBBBwTYAAxDVqOkIAAQQQQMAnQADCYgimAAFIMPXpGwEEEEAAAQQQQAABBBBAwDUBAhDXqOkIAQQQQAABAhDWgCcECEA8MQ0MAgEEEEAAAQQQQAABBBBAINACBCCBFqZ9BBBAAAEEYgtwAoRVEUwBApBg6tM3AggggAACCCCAAAIIIICAawIEIK5R0xECCCCAAAI+AQIQFkMwBQhAgqlP3wgggAACCCCAAAIIIIAAAq4JEIC4Rk1HCCCAAAIIEICwBjwhQADiiWlgEAgggAACCCCAAAIIIIAAAoEWIAAJtDDtI4AAAgggEFuAEyCsimAKEIAEU5++EUAAAQQQQAABBBBAAAEEXBMgAHGNmo4QQAABBBDwCRCAsBiCKUAAEkx9+kYAAQQQQAABBBBAAAEEEHBNgADENWo6QgABBBBAgACENeAJAQIQT0wDg0AAAQQQQ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" alt=""&gt;&lt;br/&gt;&lt;br/&gt;and here's one that had airplanes in test2:&lt;br/&gt;&lt;br/&gt;&lt;img src="data:image/png;base64,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" alt=""&gt;&lt;br/&gt;&lt;br/&gt;The problem isn't the rectangle, that's working fine. The problem is with the girl pics.&lt;br/&gt;&lt;br/&gt;Both blocks test2 and test2a display girl d, j, and h.&lt;br/&gt;&lt;br/&gt;&amp;lt;block test2_girls&amp;gt;&lt;br/&gt;/trials = [1 = test2_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;&lt;strong&gt;girl_d, &lt;br/&gt;girl_j, &lt;br/&gt;girl_h,&lt;/strong&gt; &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;Girl D is on the left at 25%&lt;br/&gt;&amp;lt;picture girl_d&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 7&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;&lt;strong&gt;/hposition = 25%&lt;/strong&gt;&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;Girl J is ALSO at 25%, so you never see Girl D&lt;br/&gt;&amp;lt;picture girl_j&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 13&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;&lt;strong&gt;/hposition = 25%&lt;/strong&gt;&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;Girl H is in the center&lt;br/&gt;&amp;lt;picture girl_h&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 11&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;&lt;strong&gt;/hposition = 50%&lt;/strong&gt;&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;NO girl stimulus is on the right at 75% ever. It's not blocked out, there just isn't one.&lt;br/&gt;&lt;br/&gt;If I had to guess, I'd say that Girl D is all wrong for these blocks, but you'll know that better than I.</description><pubDate>Mon, 15 Jun 2026 17:33:42 GMT</pubDate><dc:creator>Dave</dc:creator></item><item><title>RE: Help with conditional formatting</title><link>https://forums.millisecond.com/Topic41887.aspx</link><description>&lt;blockquote data-id="41886" class="if-quote-wrapper" unselectable="on" data-guid="1781544654434" contenteditable="false" id="if_insertedNode_1781544653354"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="41886" title=""&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="41886" title=""&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"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="41886" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 6/15/2026&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-41886"&gt;&lt;div class="if-quote-message-margin"&gt;&lt;blockquote data-id="41885" class="if-quote-wrapper" unselectable="on" data-guid="1781544654434" contenteditable="false" id="if_insertedNode_1781541421595"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="41885" 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="41885" 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="41885" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;sbashyam - 6/15/2026&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-41885"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="41884" class="if-quote-wrapper" unselectable="on" data-guid="1781544654434" contenteditable="false" id="if_insertedNode_1781538555169"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="41884" 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="41884" 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="41884" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 6/15/2026&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-41884"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;&lt;blockquote data-id="41883" class="if-quote-wrapper" unselectable="on" data-guid="1781544654434" contenteditable="false" id="if_insertedNode_1781524280009"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="41883" 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="41883" 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="41883" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;sbashyam - 6/14/2026&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-41883"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;Hi, I am posting my entire inquist code below for reference. I have coded this such that if the airplane stimuli is displayed on the screen, a white rectangle blocks out another stimuli that is displayed on scree. This works for all trials except in either trial test_2a, or test2, regardless of the stimuli presented, the right side of the screen is always blocked out. Can you help me debug this? Thank you.&lt;br/&gt;&lt;br/&gt;&amp;lt;data&amp;gt;&lt;br/&gt;/ columns = (date, time, subject, group, blockcode, trialcode, response, latency, stimulusitem)&lt;br/&gt;&amp;lt;/data&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;defaults&amp;gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ quitcommand = (Shift+'Q')&lt;br/&gt;/ fontstyle = ("Verdana", -13, false, false, false, false, 5, 0)&lt;br/&gt;&amp;lt;/defaults&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;values&amp;gt;&lt;br/&gt;/ x = 0%&lt;br/&gt;&amp;lt;/values&amp;gt;&lt;br/&gt;&lt;br/&gt;******ITEMS***********&lt;br/&gt;&lt;br/&gt;&amp;lt;item instructions&amp;gt;&lt;br/&gt;/1 = "Continue"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text continue&amp;gt;&lt;br/&gt;/items = instructions&lt;br/&gt;/select = 1&lt;br/&gt;/vposition = 95%&lt;br/&gt;/hposition = 95%&lt;br/&gt;/color = black&lt;br/&gt;/fontstyle = ("Heiti TC", 3.00%, false, false, false, false, 5, 0)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item stimuli&amp;gt;&lt;br/&gt;/1 = "lunch.png"&lt;br/&gt;/2 = "lemonades.png"&lt;br/&gt;/3 = "coloring.png"&lt;br/&gt;/4 = "puzzle.png"&lt;br/&gt;/5 = "airplanes.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture activity_group&amp;gt;&lt;br/&gt;/items = stimuli&lt;br/&gt;/ selectionrate = block&lt;br/&gt;/size = (35%, 35%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 80%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item gippy_pool&amp;gt;&lt;br/&gt;/ 1 = "gippy1.jpeg"&lt;br/&gt;/ 2 = "gippy2.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item tipa_pool&amp;gt;&lt;br/&gt;/ 1 = "tipa1.jpeg"&lt;br/&gt;/ 2 = "tipa2.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item rules_and_comp&amp;gt;&lt;br/&gt;/ 1 = "gippyrule.jpeg"&lt;br/&gt;/ 2 = "tiparule.jpeg"&lt;br/&gt;/ 3 = "comprehension.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture gippy_intro_pic&amp;gt;&lt;br/&gt;/ items = gippy_pool&lt;br/&gt;/ select = random&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture tipa_intro_pic&amp;gt;&lt;br/&gt;/ items = tipa_pool&lt;br/&gt;/ select = random&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture gippy_rule_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 1&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture tipa_rule_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 2&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture comprehension_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 3&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item likert&amp;gt;&lt;br/&gt;/1 = "smile_1.png"&lt;br/&gt;/2 = "smile_2.png"&lt;br/&gt;/3 = "smile_3.png"&lt;br/&gt;/4 = "sad_1.png"&lt;br/&gt;/5 = "sad_2.png"&lt;br/&gt;/6 = "sad_3.png"&lt;br/&gt;/7 = "OK.png"&lt;br/&gt;/8 = "notOK.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture OK&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 7&lt;br/&gt;/size = (40%, 40%)&lt;br/&gt;/ hposition = 40%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture not_OK&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 8&lt;br/&gt;/size = (40%, 40%)&lt;br/&gt;/ hposition = 60%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture a_little_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 1&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 25%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture sort_of_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 2&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture very_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 3&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 75%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture a_little_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 4&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 25%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture sort_of_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 5&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture very_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 6&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 75%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item boys&amp;gt;&lt;br/&gt;/1 = "person_a.jpg"&lt;br/&gt;/2 = "person_b.jpg"&lt;br/&gt;/3 = "person_c.jpg"&lt;br/&gt;/4 = "person_d.jpg"&lt;br/&gt;/5 = "person_e.jpg"&lt;br/&gt;/6 = "person_f.jpg"&lt;br/&gt;/7 = "person_g.jpg"&lt;br/&gt;/8 = "person_h.jpg"&lt;br/&gt;/9 = "person_i.jpg"&lt;br/&gt;/10 = "person_j.jpg"&lt;br/&gt;/11 = "person_k.jpg"&lt;br/&gt;/12 = "person_l.jpg"&lt;br/&gt;/13 = "person_m.jpg"&lt;br/&gt;/14 = "person_n.jpg"&lt;br/&gt;/15 = "person_o.jpg"&lt;br/&gt;/16 = "boy_v.png"&lt;br/&gt;/17 = "boy_x.png"&lt;br/&gt;/18 = "boy_w.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item girls&amp;gt;&lt;br/&gt;/1 = "girl_a.jpg"&lt;br/&gt;/2 = "girl_b.jpg"&lt;br/&gt;/3 = "girl_c.jpg"&lt;br/&gt;/4 = "girl_d.jpg"&lt;br/&gt;/5 = "girl_e.jpg"&lt;br/&gt;/6 = "girl_f.jpg"&lt;br/&gt;/7 = "girl_g.jpg"&lt;br/&gt;/8 = "girl_h.png"&lt;br/&gt;/9 = "girl_i.png"&lt;br/&gt;/10 = "girl_j.png"&lt;br/&gt;/11 = "girl_k.png"&lt;br/&gt;/12 = "girl_l.png"&lt;br/&gt;/13 = "girl_m.png"&lt;br/&gt;/14 = "girl_n.png"&lt;br/&gt;/15 = "girl_o.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape rectangle&amp;gt;&lt;br/&gt;/size = (100%, 100%)&lt;br/&gt;/shape = rectangle&lt;br/&gt;/color = white&lt;br/&gt;/ position = (50%, 50%)&lt;br/&gt;&amp;lt;/shape&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item black_speech&amp;gt;&lt;br/&gt;/1 = "black_speech_right.png"&lt;br/&gt;/2 = "black_Speech_left.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture black_speech_right&amp;gt;&lt;br/&gt;/ items = black_speech&lt;br/&gt;/ select = 1&lt;br/&gt;/ size = (15%, 15%)&lt;br/&gt;/ hposition = 60%&lt;br/&gt;/ vposition =35%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture black_speech_left&amp;gt;&lt;br/&gt;/items = black_speech&lt;br/&gt;/select = 2&lt;br/&gt;/size = (15%, 15%)&lt;br/&gt;/ hposition = 40%&lt;br/&gt;/ vposition = 35%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture flower_picture&amp;gt;&lt;br/&gt;/items = stimuli&lt;br/&gt;/select = 2&lt;br/&gt;/size = (10%, 10%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 80%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture person_a&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_a_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 20%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_a_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 20%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_b_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 2&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 80%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_b_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 2&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 80%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_c_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 3&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_c_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 3&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_a&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 4&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_b&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 5&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_c&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 6&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_d&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 7&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_e&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 8&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_f&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 9&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_g&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 10&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_h&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 11&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_i&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 12&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_j&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 13&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_k&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 14&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_l&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 15&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape whiterect&amp;gt;&lt;br/&gt;/ shape = rectangle&lt;br/&gt;/ color = white&lt;br/&gt;/ size = (30%, 80%)&lt;br/&gt;/ hposition = values.x&lt;br/&gt;/ vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/shape&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial gippy_intro_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1=gippy_intro_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial gippy_rule_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = gippy_rule_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial tipa_intro_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = tipa_intro_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial tipa_rule_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = tipa_rule_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial comprehension_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = comprehension_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block gippy_block&amp;gt;&lt;br/&gt;/ trials = [1 = gippy_intro_trial; 2 = gippy_rule_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block tipa_block&amp;gt;&lt;br/&gt;/ trials = [1 = tipa_intro_trial; 2 = tipa_rule_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block comprehension_block&amp;gt;&lt;br/&gt;/ trials = [1 = comprehension_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;// Group 1: Named "gippy_first"&lt;br/&gt;&amp;lt;expt gippy_first&amp;gt;&lt;br/&gt;/ subjects = (1 of 2)&lt;br/&gt;/ blocks = [1 = gippy_block; 2 = comprehension_block; 3=noreplace(test1_girls, test1a_girls); 4=noreplace(test2_girls, test2a_girls); 5=noreplace(test3_girls, test3a_girls);&lt;br/&gt;6=noreplace(test4_girls, test4a_girls)]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test1_girls&amp;gt;&lt;br/&gt;/trials = [1 = test1_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_a, &lt;br/&gt;girl_b, &lt;br/&gt;girl_c, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test1_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test1_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1_speech&amp;gt;&lt;br/&gt;/ stimulusframes = [1=continue, black_speech_right]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial judgment&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2=OK,not_OK]&lt;br/&gt;/ validresponse = (OK,not_OK)&lt;br/&gt;/ branch = [if(trial.judgment.response == "OK") trial.good]&lt;br/&gt;/ branch = [if(trial.judgment.response == "not_OK") trial.bad]&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial good&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2= a_little_good, sort_of_good, very_good]&lt;br/&gt;/ validresponse = (a_little_good, sort_of_good, very_good)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial bad&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2= a_little_bad, sort_of_bad, very_bad]&lt;br/&gt;/ validresponse = (a_little_bad, sort_of_bad, very_bad)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test1a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test1a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_a, &lt;br/&gt;girl_b, &lt;br/&gt;girl_c, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test1a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test1a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1a_speech&amp;gt;&lt;br/&gt;/ stimulusframes = [1=continue, black_speech_left]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test2_girls&amp;gt;&lt;br/&gt;/trials = [1 = test2_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_d, &lt;br/&gt;girl_j, &lt;br/&gt;girl_h, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test2_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test2_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test2_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test2a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test2a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_d, &lt;br/&gt;girl_j, &lt;br/&gt;girl_h, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test2a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test2a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes &lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test2a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test3_girls&amp;gt;&lt;br/&gt;/trials = [1 = test3_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_g, &lt;br/&gt;girl_e, &lt;br/&gt;girl_i, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test3_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test3_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test3_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test3a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test3a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_g, &lt;br/&gt;girl_e, &lt;br/&gt;girl_i, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test3a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test3a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test3a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test4_girls&amp;gt;&lt;br/&gt;/trials = [1 = test4_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_f, &lt;br/&gt;girl_k, &lt;br/&gt;girl_l, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test4_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test4_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test4_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test4a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test4a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_f, &lt;br/&gt;girl_k, &lt;br/&gt;girl_l, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test4a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test4a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test4a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="41883"&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;Please don't paste entire scripts into a post's body. This is error prone and difficult to work with. Further, if your code requires external files to run (images, etc.), you need to provide those files along with it. Helping you debug your problem is obviously not possible otherwise.&lt;br/&gt;&lt;br/&gt;Please put everything in a ZIP archive and then attach the archive to your post via +Insert -&amp;gt; Add File...&lt;br/&gt;If the archive is too large to attach here, upload it somewhere else (e.g. your DropBox or similar) and provide the download link.&lt;a class="if-quote-goto quote-link" href="#" data-id="41884"&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;Hi Dave,&lt;br/&gt;My apologies, I have attached the file &lt;a href="https://drive.google.com/file/d/10gKBTGuMVjIXgxONbNbW7iYXyyRbSYxe/view?usp=sharing" id="if_insertedNode_1781539353488"&gt;here&lt;/a&gt;&amp;nbsp;&lt;br/&gt;Thank you&lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="41885"&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;I'm not sure I understand the issue. Here's what I'm seeing when running the&amp;nbsp;cpc_girls.iqx script from your archive, which seems to match what you pasted in your original post. I gave the masking rectangle a blue color, so it's very obvious whether it's displayed or not.&lt;br/&gt;&lt;br/&gt;Here is a run that had airplanes in test2a&lt;br/&gt;&lt;br/&gt;&lt;img 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" alt=""&gt;&lt;br/&gt;&lt;br/&gt;and here's one that had airplanes in test2:&lt;br/&gt;&lt;br/&gt;&lt;img src="data:image/png;base64,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" alt=""&gt;&lt;br/&gt;&lt;br/&gt;The problem isn't the rectangle, that's working fine. The problem is that with the girl pics.&lt;br/&gt;&lt;br/&gt;Both blocks test2 and test2a display girl d, j, and h.&lt;br/&gt;&lt;br/&gt;&amp;lt;block test2_girls&amp;gt;&lt;br/&gt;/trials = [1 = test2_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;&lt;strong&gt;girl_d, &lt;br/&gt;girl_j, &lt;br/&gt;girl_h,&lt;/strong&gt; &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;Girl D is on the left at 25%&lt;br/&gt;&amp;lt;picture girl_d&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 7&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;&lt;strong&gt;/hposition = 25%&lt;/strong&gt;&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;Girl J is ALSO at 25%, so you never see Girl D&lt;br/&gt;&amp;lt;picture girl_j&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 13&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;&lt;strong&gt;/hposition = 25%&lt;/strong&gt;&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;Girl H is in the center&lt;br/&gt;&amp;lt;picture girl_h&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 11&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;&lt;strong&gt;/hposition = 50%&lt;/strong&gt;&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;NO girl stimulus is on the right at 75% ever. It's not blocked out, there just isn't one.&lt;br/&gt;&lt;br/&gt;If I had to guess, I'd say that Girl D is all wrong for these blocks, but you'll know that better than I.&lt;a class="if-quote-goto quote-link" href="#" data-id="41886"&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!</description><pubDate>Mon, 15 Jun 2026 17:31:18 GMT</pubDate><dc:creator>sbashyam</dc:creator></item><item><title>Help with conditional formatting</title><link>https://forums.millisecond.com/Topic41883.aspx</link><description>Hi, I am posting my entire inquist code below for reference. I have coded this such that if the airplane stimuli is displayed on the screen, a white rectangle blocks out another stimuli that is displayed on scree. This works for all trials except in either trial test_2a, or test2, regardless of the stimuli presented, the right side of the screen is always blocked out. Can you help me debug this? Thank you.&lt;br/&gt;&lt;br/&gt;&amp;lt;data&amp;gt;&lt;br/&gt;/ columns = (date, time, subject, group, blockcode, trialcode, response, latency, stimulusitem)&lt;br/&gt;&amp;lt;/data&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;defaults&amp;gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ quitcommand = (Shift+'Q')&lt;br/&gt;/ fontstyle = ("Verdana", -13, false, false, false, false, 5, 0)&lt;br/&gt;&amp;lt;/defaults&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;values&amp;gt;&lt;br/&gt;/ x = 0%&lt;br/&gt;&amp;lt;/values&amp;gt;&lt;br/&gt;&lt;br/&gt;******ITEMS***********&lt;br/&gt;&lt;br/&gt;&amp;lt;item instructions&amp;gt;&lt;br/&gt;/1 = "Continue"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text continue&amp;gt;&lt;br/&gt;/items = instructions&lt;br/&gt;/select = 1&lt;br/&gt;/vposition = 95%&lt;br/&gt;/hposition = 95%&lt;br/&gt;/color = black&lt;br/&gt;/fontstyle = ("Heiti TC", 3.00%, false, false, false, false, 5, 0)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item stimuli&amp;gt;&lt;br/&gt;/1 = "lunch.png"&lt;br/&gt;/2 = "lemonades.png"&lt;br/&gt;/3 = "coloring.png"&lt;br/&gt;/4 = "puzzle.png"&lt;br/&gt;/5 = "airplanes.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture activity_group&amp;gt;&lt;br/&gt;/items = stimuli&lt;br/&gt;/ selectionrate = block&lt;br/&gt;/size = (35%, 35%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 80%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item gippy_pool&amp;gt;&lt;br/&gt;/ 1 = "gippy1.jpeg"&lt;br/&gt;/ 2 = "gippy2.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item tipa_pool&amp;gt;&lt;br/&gt;/ 1 = "tipa1.jpeg"&lt;br/&gt;/ 2 = "tipa2.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item rules_and_comp&amp;gt;&lt;br/&gt;/ 1 = "gippyrule.jpeg"&lt;br/&gt;/ 2 = "tiparule.jpeg"&lt;br/&gt;/ 3 = "comprehension.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture gippy_intro_pic&amp;gt;&lt;br/&gt;/ items = gippy_pool&lt;br/&gt;/ select = random&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture tipa_intro_pic&amp;gt;&lt;br/&gt;/ items = tipa_pool&lt;br/&gt;/ select = random&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture gippy_rule_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 1&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture tipa_rule_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 2&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture comprehension_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 3&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item likert&amp;gt;&lt;br/&gt;/1 = "smile_1.png"&lt;br/&gt;/2 = "smile_2.png"&lt;br/&gt;/3 = "smile_3.png"&lt;br/&gt;/4 = "sad_1.png"&lt;br/&gt;/5 = "sad_2.png"&lt;br/&gt;/6 = "sad_3.png"&lt;br/&gt;/7 = "OK.png"&lt;br/&gt;/8 = "notOK.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture OK&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 7&lt;br/&gt;/size = (40%, 40%)&lt;br/&gt;/ hposition = 40%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture not_OK&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 8&lt;br/&gt;/size = (40%, 40%)&lt;br/&gt;/ hposition = 60%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture a_little_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 1&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 25%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture sort_of_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 2&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture very_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 3&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 75%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture a_little_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 4&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 25%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture sort_of_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 5&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture very_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 6&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 75%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item boys&amp;gt;&lt;br/&gt;/1 = "person_a.jpg"&lt;br/&gt;/2 = "person_b.jpg"&lt;br/&gt;/3 = "person_c.jpg"&lt;br/&gt;/4 = "person_d.jpg"&lt;br/&gt;/5 = "person_e.jpg"&lt;br/&gt;/6 = "person_f.jpg"&lt;br/&gt;/7 = "person_g.jpg"&lt;br/&gt;/8 = "person_h.jpg"&lt;br/&gt;/9 = "person_i.jpg"&lt;br/&gt;/10 = "person_j.jpg"&lt;br/&gt;/11 = "person_k.jpg"&lt;br/&gt;/12 = "person_l.jpg"&lt;br/&gt;/13 = "person_m.jpg"&lt;br/&gt;/14 = "person_n.jpg"&lt;br/&gt;/15 = "person_o.jpg"&lt;br/&gt;/16 = "boy_v.png"&lt;br/&gt;/17 = "boy_x.png"&lt;br/&gt;/18 = "boy_w.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item girls&amp;gt;&lt;br/&gt;/1 = "girl_a.jpg"&lt;br/&gt;/2 = "girl_b.jpg"&lt;br/&gt;/3 = "girl_c.jpg"&lt;br/&gt;/4 = "girl_d.jpg"&lt;br/&gt;/5 = "girl_e.jpg"&lt;br/&gt;/6 = "girl_f.jpg"&lt;br/&gt;/7 = "girl_g.jpg"&lt;br/&gt;/8 = "girl_h.png"&lt;br/&gt;/9 = "girl_i.png"&lt;br/&gt;/10 = "girl_j.png"&lt;br/&gt;/11 = "girl_k.png"&lt;br/&gt;/12 = "girl_l.png"&lt;br/&gt;/13 = "girl_m.png"&lt;br/&gt;/14 = "girl_n.png"&lt;br/&gt;/15 = "girl_o.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape rectangle&amp;gt;&lt;br/&gt;/size = (100%, 100%)&lt;br/&gt;/shape = rectangle&lt;br/&gt;/color = white&lt;br/&gt;/ position = (50%, 50%)&lt;br/&gt;&amp;lt;/shape&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item black_speech&amp;gt;&lt;br/&gt;/1 = "black_speech_right.png"&lt;br/&gt;/2 = "black_Speech_left.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture black_speech_right&amp;gt;&lt;br/&gt;/ items = black_speech&lt;br/&gt;/ select = 1&lt;br/&gt;/ size = (15%, 15%)&lt;br/&gt;/ hposition = 60%&lt;br/&gt;/ vposition =35%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture black_speech_left&amp;gt;&lt;br/&gt;/items = black_speech&lt;br/&gt;/select = 2&lt;br/&gt;/size = (15%, 15%)&lt;br/&gt;/ hposition = 40%&lt;br/&gt;/ vposition = 35%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture flower_picture&amp;gt;&lt;br/&gt;/items = stimuli&lt;br/&gt;/select = 2&lt;br/&gt;/size = (10%, 10%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 80%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture person_a&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_a_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 20%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_a_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 20%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_b_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 2&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 80%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_b_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 2&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 80%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_c_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 3&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_c_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 3&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_a&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 4&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_b&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 5&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_c&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 6&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_d&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 7&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_e&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 8&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_f&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 9&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_g&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 10&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_h&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 11&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_i&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 12&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_j&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 13&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_k&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 14&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_l&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 15&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape whiterect&amp;gt;&lt;br/&gt;/ shape = rectangle&lt;br/&gt;/ color = white&lt;br/&gt;/ size = (30%, 80%)&lt;br/&gt;/ hposition = values.x&lt;br/&gt;/ vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/shape&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial gippy_intro_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1=gippy_intro_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial gippy_rule_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = gippy_rule_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial tipa_intro_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = tipa_intro_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial tipa_rule_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = tipa_rule_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial comprehension_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = comprehension_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block gippy_block&amp;gt;&lt;br/&gt;/ trials = [1 = gippy_intro_trial; 2 = gippy_rule_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block tipa_block&amp;gt;&lt;br/&gt;/ trials = [1 = tipa_intro_trial; 2 = tipa_rule_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block comprehension_block&amp;gt;&lt;br/&gt;/ trials = [1 = comprehension_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;// Group 1: Named "gippy_first"&lt;br/&gt;&amp;lt;expt gippy_first&amp;gt;&lt;br/&gt;/ subjects = (1 of 2)&lt;br/&gt;/ blocks = [1 = gippy_block; 2 = comprehension_block; 3=noreplace(test1_girls, test1a_girls); 4=noreplace(test2_girls, test2a_girls); 5=noreplace(test3_girls, test3a_girls);&lt;br/&gt;6=noreplace(test4_girls, test4a_girls)]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test1_girls&amp;gt;&lt;br/&gt;/trials = [1 = test1_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_a, &lt;br/&gt;girl_b, &lt;br/&gt;girl_c, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test1_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test1_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1_speech&amp;gt;&lt;br/&gt;/ stimulusframes = [1=continue, black_speech_right]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial judgment&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2=OK,not_OK]&lt;br/&gt;/ validresponse = (OK,not_OK)&lt;br/&gt;/ branch = [if(trial.judgment.response == "OK") trial.good]&lt;br/&gt;/ branch = [if(trial.judgment.response == "not_OK") trial.bad]&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial good&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2= a_little_good, sort_of_good, very_good]&lt;br/&gt;/ validresponse = (a_little_good, sort_of_good, very_good)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial bad&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2= a_little_bad, sort_of_bad, very_bad]&lt;br/&gt;/ validresponse = (a_little_bad, sort_of_bad, very_bad)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test1a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test1a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_a, &lt;br/&gt;girl_b, &lt;br/&gt;girl_c, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test1a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test1a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1a_speech&amp;gt;&lt;br/&gt;/ stimulusframes = [1=continue, black_speech_left]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test2_girls&amp;gt;&lt;br/&gt;/trials = [1 = test2_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_d, &lt;br/&gt;girl_j, &lt;br/&gt;girl_h, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test2_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test2_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test2_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test2a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test2a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_d, &lt;br/&gt;girl_j, &lt;br/&gt;girl_h, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test2a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test2a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes &lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test2a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test3_girls&amp;gt;&lt;br/&gt;/trials = [1 = test3_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_g, &lt;br/&gt;girl_e, &lt;br/&gt;girl_i, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test3_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test3_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test3_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test3a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test3a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_g, &lt;br/&gt;girl_e, &lt;br/&gt;girl_i, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test3a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test3a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test3a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test4_girls&amp;gt;&lt;br/&gt;/trials = [1 = test4_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_f, &lt;br/&gt;girl_k, &lt;br/&gt;girl_l, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test4_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test4_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test4_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test4a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test4a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_f, &lt;br/&gt;girl_k, &lt;br/&gt;girl_l, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test4a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test4a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test4a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;</description><pubDate>Mon, 15 Jun 2026 17:31:18 GMT</pubDate><dc:creator>sbashyam</dc:creator></item><item><title>RE: Help with conditional formatting</title><link>https://forums.millisecond.com/Topic41885.aspx</link><description>&lt;blockquote data-id="41884" class="if-quote-wrapper" unselectable="on" data-guid="1781538555844" contenteditable="false" id="if_insertedNode_1781538555169"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="41884" title=""&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="41884" title=""&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"&gt;&lt;div unselectable="on" class="if-quote-toggle-wrapper"&gt;&lt;a class="if-quote-toggle quote-link" href="#" data-id="41884" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;Dave - 6/15/2026&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-41884"&gt;&lt;div class="if-quote-message-margin"&gt;&lt;blockquote data-id="41883" class="if-quote-wrapper" unselectable="on" data-guid="1781538555844" contenteditable="false" id="if_insertedNode_1781524280009"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="41883" 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="41883" 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="41883" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;sbashyam - 6/14/2026&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-41883"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;Hi, I am posting my entire inquist code below for reference. I have coded this such that if the airplane stimuli is displayed on the screen, a white rectangle blocks out another stimuli that is displayed on scree. This works for all trials except in either trial test_2a, or test2, regardless of the stimuli presented, the right side of the screen is always blocked out. Can you help me debug this? Thank you.&lt;br/&gt;&lt;br/&gt;&amp;lt;data&amp;gt;&lt;br/&gt;/ columns = (date, time, subject, group, blockcode, trialcode, response, latency, stimulusitem)&lt;br/&gt;&amp;lt;/data&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;defaults&amp;gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ quitcommand = (Shift+'Q')&lt;br/&gt;/ fontstyle = ("Verdana", -13, false, false, false, false, 5, 0)&lt;br/&gt;&amp;lt;/defaults&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;values&amp;gt;&lt;br/&gt;/ x = 0%&lt;br/&gt;&amp;lt;/values&amp;gt;&lt;br/&gt;&lt;br/&gt;******ITEMS***********&lt;br/&gt;&lt;br/&gt;&amp;lt;item instructions&amp;gt;&lt;br/&gt;/1 = "Continue"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text continue&amp;gt;&lt;br/&gt;/items = instructions&lt;br/&gt;/select = 1&lt;br/&gt;/vposition = 95%&lt;br/&gt;/hposition = 95%&lt;br/&gt;/color = black&lt;br/&gt;/fontstyle = ("Heiti TC", 3.00%, false, false, false, false, 5, 0)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item stimuli&amp;gt;&lt;br/&gt;/1 = "lunch.png"&lt;br/&gt;/2 = "lemonades.png"&lt;br/&gt;/3 = "coloring.png"&lt;br/&gt;/4 = "puzzle.png"&lt;br/&gt;/5 = "airplanes.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture activity_group&amp;gt;&lt;br/&gt;/items = stimuli&lt;br/&gt;/ selectionrate = block&lt;br/&gt;/size = (35%, 35%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 80%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item gippy_pool&amp;gt;&lt;br/&gt;/ 1 = "gippy1.jpeg"&lt;br/&gt;/ 2 = "gippy2.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item tipa_pool&amp;gt;&lt;br/&gt;/ 1 = "tipa1.jpeg"&lt;br/&gt;/ 2 = "tipa2.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item rules_and_comp&amp;gt;&lt;br/&gt;/ 1 = "gippyrule.jpeg"&lt;br/&gt;/ 2 = "tiparule.jpeg"&lt;br/&gt;/ 3 = "comprehension.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture gippy_intro_pic&amp;gt;&lt;br/&gt;/ items = gippy_pool&lt;br/&gt;/ select = random&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture tipa_intro_pic&amp;gt;&lt;br/&gt;/ items = tipa_pool&lt;br/&gt;/ select = random&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture gippy_rule_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 1&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture tipa_rule_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 2&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture comprehension_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 3&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item likert&amp;gt;&lt;br/&gt;/1 = "smile_1.png"&lt;br/&gt;/2 = "smile_2.png"&lt;br/&gt;/3 = "smile_3.png"&lt;br/&gt;/4 = "sad_1.png"&lt;br/&gt;/5 = "sad_2.png"&lt;br/&gt;/6 = "sad_3.png"&lt;br/&gt;/7 = "OK.png"&lt;br/&gt;/8 = "notOK.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture OK&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 7&lt;br/&gt;/size = (40%, 40%)&lt;br/&gt;/ hposition = 40%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture not_OK&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 8&lt;br/&gt;/size = (40%, 40%)&lt;br/&gt;/ hposition = 60%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture a_little_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 1&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 25%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture sort_of_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 2&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture very_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 3&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 75%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture a_little_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 4&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 25%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture sort_of_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 5&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture very_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 6&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 75%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item boys&amp;gt;&lt;br/&gt;/1 = "person_a.jpg"&lt;br/&gt;/2 = "person_b.jpg"&lt;br/&gt;/3 = "person_c.jpg"&lt;br/&gt;/4 = "person_d.jpg"&lt;br/&gt;/5 = "person_e.jpg"&lt;br/&gt;/6 = "person_f.jpg"&lt;br/&gt;/7 = "person_g.jpg"&lt;br/&gt;/8 = "person_h.jpg"&lt;br/&gt;/9 = "person_i.jpg"&lt;br/&gt;/10 = "person_j.jpg"&lt;br/&gt;/11 = "person_k.jpg"&lt;br/&gt;/12 = "person_l.jpg"&lt;br/&gt;/13 = "person_m.jpg"&lt;br/&gt;/14 = "person_n.jpg"&lt;br/&gt;/15 = "person_o.jpg"&lt;br/&gt;/16 = "boy_v.png"&lt;br/&gt;/17 = "boy_x.png"&lt;br/&gt;/18 = "boy_w.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item girls&amp;gt;&lt;br/&gt;/1 = "girl_a.jpg"&lt;br/&gt;/2 = "girl_b.jpg"&lt;br/&gt;/3 = "girl_c.jpg"&lt;br/&gt;/4 = "girl_d.jpg"&lt;br/&gt;/5 = "girl_e.jpg"&lt;br/&gt;/6 = "girl_f.jpg"&lt;br/&gt;/7 = "girl_g.jpg"&lt;br/&gt;/8 = "girl_h.png"&lt;br/&gt;/9 = "girl_i.png"&lt;br/&gt;/10 = "girl_j.png"&lt;br/&gt;/11 = "girl_k.png"&lt;br/&gt;/12 = "girl_l.png"&lt;br/&gt;/13 = "girl_m.png"&lt;br/&gt;/14 = "girl_n.png"&lt;br/&gt;/15 = "girl_o.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape rectangle&amp;gt;&lt;br/&gt;/size = (100%, 100%)&lt;br/&gt;/shape = rectangle&lt;br/&gt;/color = white&lt;br/&gt;/ position = (50%, 50%)&lt;br/&gt;&amp;lt;/shape&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item black_speech&amp;gt;&lt;br/&gt;/1 = "black_speech_right.png"&lt;br/&gt;/2 = "black_Speech_left.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture black_speech_right&amp;gt;&lt;br/&gt;/ items = black_speech&lt;br/&gt;/ select = 1&lt;br/&gt;/ size = (15%, 15%)&lt;br/&gt;/ hposition = 60%&lt;br/&gt;/ vposition =35%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture black_speech_left&amp;gt;&lt;br/&gt;/items = black_speech&lt;br/&gt;/select = 2&lt;br/&gt;/size = (15%, 15%)&lt;br/&gt;/ hposition = 40%&lt;br/&gt;/ vposition = 35%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture flower_picture&amp;gt;&lt;br/&gt;/items = stimuli&lt;br/&gt;/select = 2&lt;br/&gt;/size = (10%, 10%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 80%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture person_a&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_a_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 20%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_a_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 20%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_b_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 2&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 80%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_b_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 2&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 80%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_c_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 3&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_c_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 3&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_a&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 4&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_b&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 5&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_c&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 6&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_d&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 7&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_e&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 8&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_f&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 9&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_g&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 10&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_h&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 11&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_i&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 12&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_j&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 13&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_k&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 14&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_l&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 15&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape whiterect&amp;gt;&lt;br/&gt;/ shape = rectangle&lt;br/&gt;/ color = white&lt;br/&gt;/ size = (30%, 80%)&lt;br/&gt;/ hposition = values.x&lt;br/&gt;/ vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/shape&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial gippy_intro_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1=gippy_intro_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial gippy_rule_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = gippy_rule_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial tipa_intro_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = tipa_intro_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial tipa_rule_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = tipa_rule_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial comprehension_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = comprehension_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block gippy_block&amp;gt;&lt;br/&gt;/ trials = [1 = gippy_intro_trial; 2 = gippy_rule_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block tipa_block&amp;gt;&lt;br/&gt;/ trials = [1 = tipa_intro_trial; 2 = tipa_rule_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block comprehension_block&amp;gt;&lt;br/&gt;/ trials = [1 = comprehension_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;// Group 1: Named "gippy_first"&lt;br/&gt;&amp;lt;expt gippy_first&amp;gt;&lt;br/&gt;/ subjects = (1 of 2)&lt;br/&gt;/ blocks = [1 = gippy_block; 2 = comprehension_block; 3=noreplace(test1_girls, test1a_girls); 4=noreplace(test2_girls, test2a_girls); 5=noreplace(test3_girls, test3a_girls);&lt;br/&gt;6=noreplace(test4_girls, test4a_girls)]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test1_girls&amp;gt;&lt;br/&gt;/trials = [1 = test1_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_a, &lt;br/&gt;girl_b, &lt;br/&gt;girl_c, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test1_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test1_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1_speech&amp;gt;&lt;br/&gt;/ stimulusframes = [1=continue, black_speech_right]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial judgment&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2=OK,not_OK]&lt;br/&gt;/ validresponse = (OK,not_OK)&lt;br/&gt;/ branch = [if(trial.judgment.response == "OK") trial.good]&lt;br/&gt;/ branch = [if(trial.judgment.response == "not_OK") trial.bad]&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial good&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2= a_little_good, sort_of_good, very_good]&lt;br/&gt;/ validresponse = (a_little_good, sort_of_good, very_good)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial bad&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2= a_little_bad, sort_of_bad, very_bad]&lt;br/&gt;/ validresponse = (a_little_bad, sort_of_bad, very_bad)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test1a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test1a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_a, &lt;br/&gt;girl_b, &lt;br/&gt;girl_c, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test1a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test1a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1a_speech&amp;gt;&lt;br/&gt;/ stimulusframes = [1=continue, black_speech_left]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test2_girls&amp;gt;&lt;br/&gt;/trials = [1 = test2_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_d, &lt;br/&gt;girl_j, &lt;br/&gt;girl_h, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test2_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test2_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test2_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test2a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test2a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_d, &lt;br/&gt;girl_j, &lt;br/&gt;girl_h, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test2a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test2a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes &lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test2a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test3_girls&amp;gt;&lt;br/&gt;/trials = [1 = test3_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_g, &lt;br/&gt;girl_e, &lt;br/&gt;girl_i, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test3_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test3_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test3_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test3a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test3a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_g, &lt;br/&gt;girl_e, &lt;br/&gt;girl_i, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test3a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test3a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test3a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test4_girls&amp;gt;&lt;br/&gt;/trials = [1 = test4_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_f, &lt;br/&gt;girl_k, &lt;br/&gt;girl_l, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test4_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test4_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test4_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test4a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test4a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_f, &lt;br/&gt;girl_k, &lt;br/&gt;girl_l, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test4a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test4a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test4a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="41883"&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;Please don't paste entire scripts into a post's body. This is error prone and difficult to work with. Further, if your code requires external files to run (images, etc.), you need to provide those files along with it. Helping you debug your problem is obviously not possible otherwise.&lt;br/&gt;&lt;br/&gt;Please put everything in a ZIP archive and then attach the archive to your post via +Insert -&amp;gt; Add File...&lt;br/&gt;If the archive is too large to attach here, upload it somewhere else (e.g. your DropBox or similar) and provide the download link.&lt;a class="if-quote-goto quote-link" href="#" data-id="41884"&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;Hi Dave,&lt;br/&gt;My apologies, I have attached the file &lt;a href="https://drive.google.com/file/d/10gKBTGuMVjIXgxONbNbW7iYXyyRbSYxe/view?usp=sharing" id="if_insertedNode_1781539353488"&gt;here&lt;/a&gt;&amp;nbsp;&lt;br/&gt;Thank you&lt;br/&gt;</description><pubDate>Mon, 15 Jun 2026 16:02:36 GMT</pubDate><dc:creator>sbashyam</dc:creator></item><item><title>RE: Help with conditional formatting</title><link>https://forums.millisecond.com/Topic41884.aspx</link><description>&lt;blockquote data-id="41883" class="if-quote-wrapper" unselectable="on" data-guid="1781524280813" contenteditable="false" id="if_insertedNode_1781524280009"&gt;&lt;a class="quote-para" unselectable="on" style="display: none;" href="#" data-id="41883" 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="41883" 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="41883" title=" "&gt;&amp;nbsp;&lt;/a&gt;&lt;/div&gt;&lt;span unselectable="on" class="quote-markup"&gt;[b]&lt;/span&gt;sbashyam - 6/14/2026&lt;span unselectable="on" class="quote-markup"&gt;[/b]&lt;/span&gt;&lt;/div&gt;&lt;div class="if-quote-message if-quote-message-41883"&gt;&lt;div class="if-quote-message-margin" contenteditable="true"&gt;Hi, I am posting my entire inquist code below for reference. I have coded this such that if the airplane stimuli is displayed on the screen, a white rectangle blocks out another stimuli that is displayed on scree. This works for all trials except in either trial test_2a, or test2, regardless of the stimuli presented, the right side of the screen is always blocked out. Can you help me debug this? Thank you.&lt;br/&gt;&lt;br/&gt;&amp;lt;data&amp;gt;&lt;br/&gt;/ columns = (date, time, subject, group, blockcode, trialcode, response, latency, stimulusitem)&lt;br/&gt;&amp;lt;/data&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;defaults&amp;gt;&lt;br/&gt;/ inputdevice = mouse&lt;br/&gt;/ quitcommand = (Shift+'Q')&lt;br/&gt;/ fontstyle = ("Verdana", -13, false, false, false, false, 5, 0)&lt;br/&gt;&amp;lt;/defaults&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;values&amp;gt;&lt;br/&gt;/ x = 0%&lt;br/&gt;&amp;lt;/values&amp;gt;&lt;br/&gt;&lt;br/&gt;******ITEMS***********&lt;br/&gt;&lt;br/&gt;&amp;lt;item instructions&amp;gt;&lt;br/&gt;/1 = "Continue"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;text continue&amp;gt;&lt;br/&gt;/items = instructions&lt;br/&gt;/select = 1&lt;br/&gt;/vposition = 95%&lt;br/&gt;/hposition = 95%&lt;br/&gt;/color = black&lt;br/&gt;/fontstyle = ("Heiti TC", 3.00%, false, false, false, false, 5, 0)&lt;br/&gt;&amp;lt;/text&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item stimuli&amp;gt;&lt;br/&gt;/1 = "lunch.png"&lt;br/&gt;/2 = "lemonades.png"&lt;br/&gt;/3 = "coloring.png"&lt;br/&gt;/4 = "puzzle.png"&lt;br/&gt;/5 = "airplanes.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture activity_group&amp;gt;&lt;br/&gt;/items = stimuli&lt;br/&gt;/ selectionrate = block&lt;br/&gt;/size = (35%, 35%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 80%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item gippy_pool&amp;gt;&lt;br/&gt;/ 1 = "gippy1.jpeg"&lt;br/&gt;/ 2 = "gippy2.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item tipa_pool&amp;gt;&lt;br/&gt;/ 1 = "tipa1.jpeg"&lt;br/&gt;/ 2 = "tipa2.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item rules_and_comp&amp;gt;&lt;br/&gt;/ 1 = "gippyrule.jpeg"&lt;br/&gt;/ 2 = "tiparule.jpeg"&lt;br/&gt;/ 3 = "comprehension.jpeg"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture gippy_intro_pic&amp;gt;&lt;br/&gt;/ items = gippy_pool&lt;br/&gt;/ select = random&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture tipa_intro_pic&amp;gt;&lt;br/&gt;/ items = tipa_pool&lt;br/&gt;/ select = random&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture gippy_rule_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 1&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture tipa_rule_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 2&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture comprehension_pic&amp;gt;&lt;br/&gt;/ items = rules_and_comp&lt;br/&gt;/ select = 3&lt;br/&gt;/ size = (80%, 80%)&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item likert&amp;gt;&lt;br/&gt;/1 = "smile_1.png"&lt;br/&gt;/2 = "smile_2.png"&lt;br/&gt;/3 = "smile_3.png"&lt;br/&gt;/4 = "sad_1.png"&lt;br/&gt;/5 = "sad_2.png"&lt;br/&gt;/6 = "sad_3.png"&lt;br/&gt;/7 = "OK.png"&lt;br/&gt;/8 = "notOK.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture OK&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 7&lt;br/&gt;/size = (40%, 40%)&lt;br/&gt;/ hposition = 40%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture not_OK&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 8&lt;br/&gt;/size = (40%, 40%)&lt;br/&gt;/ hposition = 60%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture a_little_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 1&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 25%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture sort_of_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 2&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture very_good&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 3&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 75%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture a_little_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 4&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 25%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture sort_of_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 5&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 50%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture very_bad&amp;gt;&lt;br/&gt;/items = likert&lt;br/&gt;/select = 6&lt;br/&gt;/size = (25%, 25%)&lt;br/&gt;/ hposition = 75%&lt;br/&gt;/ vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item boys&amp;gt;&lt;br/&gt;/1 = "person_a.jpg"&lt;br/&gt;/2 = "person_b.jpg"&lt;br/&gt;/3 = "person_c.jpg"&lt;br/&gt;/4 = "person_d.jpg"&lt;br/&gt;/5 = "person_e.jpg"&lt;br/&gt;/6 = "person_f.jpg"&lt;br/&gt;/7 = "person_g.jpg"&lt;br/&gt;/8 = "person_h.jpg"&lt;br/&gt;/9 = "person_i.jpg"&lt;br/&gt;/10 = "person_j.jpg"&lt;br/&gt;/11 = "person_k.jpg"&lt;br/&gt;/12 = "person_l.jpg"&lt;br/&gt;/13 = "person_m.jpg"&lt;br/&gt;/14 = "person_n.jpg"&lt;br/&gt;/15 = "person_o.jpg"&lt;br/&gt;/16 = "boy_v.png"&lt;br/&gt;/17 = "boy_x.png"&lt;br/&gt;/18 = "boy_w.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item girls&amp;gt;&lt;br/&gt;/1 = "girl_a.jpg"&lt;br/&gt;/2 = "girl_b.jpg"&lt;br/&gt;/3 = "girl_c.jpg"&lt;br/&gt;/4 = "girl_d.jpg"&lt;br/&gt;/5 = "girl_e.jpg"&lt;br/&gt;/6 = "girl_f.jpg"&lt;br/&gt;/7 = "girl_g.jpg"&lt;br/&gt;/8 = "girl_h.png"&lt;br/&gt;/9 = "girl_i.png"&lt;br/&gt;/10 = "girl_j.png"&lt;br/&gt;/11 = "girl_k.png"&lt;br/&gt;/12 = "girl_l.png"&lt;br/&gt;/13 = "girl_m.png"&lt;br/&gt;/14 = "girl_n.png"&lt;br/&gt;/15 = "girl_o.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape rectangle&amp;gt;&lt;br/&gt;/size = (100%, 100%)&lt;br/&gt;/shape = rectangle&lt;br/&gt;/color = white&lt;br/&gt;/ position = (50%, 50%)&lt;br/&gt;&amp;lt;/shape&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;item black_speech&amp;gt;&lt;br/&gt;/1 = "black_speech_right.png"&lt;br/&gt;/2 = "black_Speech_left.png"&lt;br/&gt;&amp;lt;/item&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture black_speech_right&amp;gt;&lt;br/&gt;/ items = black_speech&lt;br/&gt;/ select = 1&lt;br/&gt;/ size = (15%, 15%)&lt;br/&gt;/ hposition = 60%&lt;br/&gt;/ vposition =35%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture black_speech_left&amp;gt;&lt;br/&gt;/items = black_speech&lt;br/&gt;/select = 2&lt;br/&gt;/size = (15%, 15%)&lt;br/&gt;/ hposition = 40%&lt;br/&gt;/ vposition = 35%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture flower_picture&amp;gt;&lt;br/&gt;/items = stimuli&lt;br/&gt;/select = 2&lt;br/&gt;/size = (10%, 10%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 80%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture person_a&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_a_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 20%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_a_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 1&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 20%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_b_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 2&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 80%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_b_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 2&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 80%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_c_boy&amp;gt;&lt;br/&gt;/items = boys&lt;br/&gt;/select = 3&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture intro_c_girl&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 3&lt;br/&gt;/size = (50%,50%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_a&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 4&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_b&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 5&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_c&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 6&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_d&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 7&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_e&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 8&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_f&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 9&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_g&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 10&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_h&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 11&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_i&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 12&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_j&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 13&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 25%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_k&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 14&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 50%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;picture girl_l&amp;gt;&lt;br/&gt;/items = girls&lt;br/&gt;/select = 15&lt;br/&gt;/size = (30%,30%)&lt;br/&gt;/hposition = 75%&lt;br/&gt;/vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/picture&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;shape whiterect&amp;gt;&lt;br/&gt;/ shape = rectangle&lt;br/&gt;/ color = white&lt;br/&gt;/ size = (30%, 80%)&lt;br/&gt;/ hposition = values.x&lt;br/&gt;/ vposition = 50%&lt;br/&gt;/ erase = false&lt;br/&gt;&amp;lt;/shape&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial gippy_intro_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1=gippy_intro_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial gippy_rule_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = gippy_rule_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial tipa_intro_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = tipa_intro_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial tipa_rule_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = tipa_rule_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial comprehension_trial&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = comprehension_pic, continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block gippy_block&amp;gt;&lt;br/&gt;/ trials = [1 = gippy_intro_trial; 2 = gippy_rule_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block tipa_block&amp;gt;&lt;br/&gt;/ trials = [1 = tipa_intro_trial; 2 = tipa_rule_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block comprehension_block&amp;gt;&lt;br/&gt;/ trials = [1 = comprehension_trial]&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;// Group 1: Named "gippy_first"&lt;br/&gt;&amp;lt;expt gippy_first&amp;gt;&lt;br/&gt;/ subjects = (1 of 2)&lt;br/&gt;/ blocks = [1 = gippy_block; 2 = comprehension_block; 3=noreplace(test1_girls, test1a_girls); 4=noreplace(test2_girls, test2a_girls); 5=noreplace(test3_girls, test3a_girls);&lt;br/&gt;6=noreplace(test4_girls, test4a_girls)]&lt;br/&gt;&amp;lt;/expt&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test1_girls&amp;gt;&lt;br/&gt;/trials = [1 = test1_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_a, &lt;br/&gt;girl_b, &lt;br/&gt;girl_c, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test1_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test1_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1_speech&amp;gt;&lt;br/&gt;/ stimulusframes = [1=continue, black_speech_right]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial judgment&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2=OK,not_OK]&lt;br/&gt;/ validresponse = (OK,not_OK)&lt;br/&gt;/ branch = [if(trial.judgment.response == "OK") trial.good]&lt;br/&gt;/ branch = [if(trial.judgment.response == "not_OK") trial.bad]&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial good&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2= a_little_good, sort_of_good, very_good]&lt;br/&gt;/ validresponse = (a_little_good, sort_of_good, very_good)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial bad&amp;gt;&lt;br/&gt;/ stimulusframes = [1 = rectangle; 2= a_little_bad, sort_of_bad, very_bad]&lt;br/&gt;/ validresponse = (a_little_bad, sort_of_bad, very_bad)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test1a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test1a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_a, &lt;br/&gt;girl_b, &lt;br/&gt;girl_c, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test1a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test1a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test1a_speech&amp;gt;&lt;br/&gt;/ stimulusframes = [1=continue, black_speech_left]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test2_girls&amp;gt;&lt;br/&gt;/trials = [1 = test2_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_d, &lt;br/&gt;girl_j, &lt;br/&gt;girl_h, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test2_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test2_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test2_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test2a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test2a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_d, &lt;br/&gt;girl_j, &lt;br/&gt;girl_h, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test2a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test2a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes &lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test2a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test3_girls&amp;gt;&lt;br/&gt;/trials = [1 = test3_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_g, &lt;br/&gt;girl_e, &lt;br/&gt;girl_i, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test3_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test3_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test3_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test3a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test3a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_g, &lt;br/&gt;girl_e, &lt;br/&gt;girl_i, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test3a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test3a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test3a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test4_girls&amp;gt;&lt;br/&gt;/trials = [1 = test4_intro; 2 = test1_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_f, &lt;br/&gt;girl_k, &lt;br/&gt;girl_l, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test4_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test4_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(25%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test4_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt; &lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;&lt;br/&gt;/stimulusframes = [1= continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;block test4a_girls&amp;gt;&lt;br/&gt;/trials = [1 = test4a_intro; 2 = test1a_speech; 3 = judgment]&lt;br/&gt;/ bgstim = (&lt;br/&gt;girl_f, &lt;br/&gt;girl_k, &lt;br/&gt;girl_l, &lt;br/&gt;activity_group)&lt;br/&gt;&amp;lt;/block&amp;gt;&lt;br/&gt;&lt;br/&gt;&amp;lt;trial test4a_intro&amp;gt;&lt;br/&gt;/ ontrialbegin = [&lt;br/&gt;  trial.test4a_intro.resetstimulusframes(); // resets the trial's stimulus presentation sequence to its initial state&lt;br/&gt;  if (picture.activity_group.currentitem == "airplanes.png") {&amp;nbsp;// if current activity is either airplanes or airplanes&lt;br/&gt;&amp;nbsp; values.x = replace(75%); // pick left or right girl position at random&lt;br/&gt;&amp;nbsp; trial.test4a_intro.insertstimulusframe(shape.whiterect, 1); // cover up the randomly picked girl with white rectangle&lt;br/&gt;&amp;nbsp; };&lt;br/&gt;]&lt;br/&gt;/stimulusframes = [1=continue]&lt;br/&gt;/ validresponse = (continue)&lt;br/&gt;&amp;lt;/trial&amp;gt;&lt;br/&gt;&lt;br/&gt;&lt;a class="if-quote-goto quote-link" href="#" data-id="41883"&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;Please don't paste entire scripts into a post's body. This is error prone and difficult to work with. Further, if your code requires external files to run (images, etc.), you need to provide those files along with it. Helping you debug your problem is obviously not possible otherwise.&lt;br/&gt;&lt;br/&gt;Please put everything in a ZIP archive and then attach the archive to your post via +Insert -&amp;gt; Add File...&lt;br/&gt;If the archive is too large to attach here, upload it somewhere else (e.g. your DropBox or similar) and provide the download link.</description><pubDate>Mon, 15 Jun 2026 11:54:23 GMT</pubDate><dc:creator>Dave</dc:creator></item></channel></rss>